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Nouveautés de Python

What’s New In Python 3.6

Summary – Release highlights

Nouvelles fonctionnalités

PEP 498: Formatted string literals

PEP 526: Syntax for variable annotations

PEP 515: Underscores in Numeric Literals

PEP 525: Asynchronous Generators

PEP 530: Asynchronous Comprehensions

PEP 487: Simpler customization of class creation

PEP 487: Descriptor Protocol Enhancements

PEP 519: Adding a file system path protocol

PEP 495: Local Time Disambiguation

PEP 529: Change Windows filesystem encoding to UTF-8

PEP 528: Change Windows console encoding to UTF-8

PEP 520: Preserving Class Attribute Definition Order

PEP 468: Preserving Keyword Argument Order

New dict implementation

PEP 523: Adding a frame evaluation API to CPython

PYTHONMALLOC environment variable

DTrace and SystemTap probing support

Other Language Changes

New Modules

secrets

Improved Modules

array

ast

asyncio

binascii

cmath

collections

concurrent.futures

contextlib

datetime

decimal

distutils

email

encodings

enum

faulthandler

fileinput

hashlib

http.client

idlelib and IDLE

importlib

inspect

json

logging

math

multiprocessing

os

pathlib

pdb

pickle

pickletools

pydoc

random

re

readline

rlcompleter

shlex

site

sqlite3

socket

socketserver

ssl

statistics

struct

subprocess

sys

telnetlib

time

timeit

tkinter

traceback

tracemalloc

typing

unicodedata

unittest.mock

urllib.request

urllib.robotparser

venv

warnings

winreg

winsound

xmlrpc.client

zipfile

zlib

Optimizations

Build and C API Changes

Autres Améliorations

Deprecated

Nouveaux mot-clefs

Deprecated Python behavior

Deprecated Python modules, functions and methods

asynchat

asyncore

dbm

distutils

grp

importlib

os

re

ssl

tkinter

venv

xml

Deprecated functions and types of the C API

Deprecated Build Options

Removed

API and Feature Removals

Porting to Python 3.6

Changes in “python” Command Behavior

Changes in the Python API

Changes in the C API

CPython bytecode changes

Notable changes in Python 3.6.2

New make regen-all build target

Removal of make touch build target

Notable changes in Python 3.6.4

Notable changes in Python 3.6.5

Notable changes in Python 3.6.7

Notable changes in Python 3.6.10

Nouveautés de Python 3.5

Summary – Release highlights

Nouvelles fonctionnalités

PEP 492 - Coroutines with async and await syntax

PEP 465 - A dedicated infix operator for matrix multiplication

PEP 448 - Additional Unpacking Generalizations

PEP 461 - percent formatting support for bytes and bytearray

PEP 484 - Type Hints

PEP 471 - os.scandir() function – a better and faster directory iterator

PEP 475: Retry system calls failing with EINTR

PEP 479: Change StopIteration handling inside generators

PEP 485: A function for testing approximate equality

PEP 486: Make the Python Launcher aware of virtual environments

PEP 488 : Élimination des fichiers PYO

PEP 489: Multi-phase extension module initialization

Other Language Changes

New Modules

typing

zipapp

Improved Modules

argparse

asyncio

bz2

cgi

cmath

code

collections

collections.abc

compileall

concurrent.futures

configparser

contextlib

csv

curses

dbm

difflib

distutils

doctest

email

enum

faulthandler

functools

glob

gzip

heapq

http

http.client

idlelib and IDLE

imaplib

imghdr

importlib

inspect

io

ipaddress

json

linecache

locale

logging

lzma

math

multiprocessing

operator

os

pathlib

pickle

poplib

re

readline

selectors

shutil

signal

smtpd

smtplib

sndhdr

socket

ssl

Memory BIO Support

Application-Layer Protocol Negotiation Support

Other Changes

sqlite3

subprocess

sys

sysconfig

tarfile

threading

time

timeit

tkinter

traceback

types

unicodedata

unittest

unittest.mock

urllib

wsgiref

xmlrpc

xml.sax

zipfile

Other module-level changes

Optimizations

Build and C API Changes

Deprecated

Nouveaux mot-clefs

Deprecated Python Behavior

Unsupported Operating Systems

Deprecated Python modules, functions and methods

Removed

API and Feature Removals

Portage vers Python 3.5

Changes in Python behavior

Changes in the Python API

Changes in the C API

Notable changes in Python 3.5.4

New make regen-all build target

Removal of make touch build target

Nouveautés de Python 3.4

Summary – Release Highlights

Nouvelles fonctionnalités

PEP 453: Explicit Bootstrapping of PIP in Python Installations

Bootstrapping pip By Default

Documentation Changes

PEP 446: Newly Created File Descriptors Are Non-Inheritable

Improvements to Codec Handling

PEP 451: A ModuleSpec Type for the Import System

Other Language Changes

New Modules

asyncio

ensurepip

enum

pathlib

selectors

statistics

tracemalloc

Improved Modules

abc

aifc

argparse

audioop

base64

collections

colorsys

contextlib

dbm

dis

doctest

email

filecmp

functools

gc

glob

hashlib

hmac

html

http

idlelib and IDLE

importlib

inspect

ipaddress

logging

marshal

mmap

multiprocessing

operator

os

pdb

pickle

plistlib

poplib

pprint

pty

pydoc

re

resource

select

shelve

shutil

smtpd

smtplib

socket

sqlite3

ssl

stat

struct

subprocess

sunau

sys

tarfile

textwrap

threading

traceback

types

urllib

unittest

venv

wave

weakref

xml.etree

zipfile

CPython Implementation Changes

PEP 445: Customization of CPython Memory Allocators

PEP 442: Safe Object Finalization

PEP 456: Secure and Interchangeable Hash Algorithm

PEP 436: Argument Clinic

Other Build and C API Changes

Autres Améliorations

Significant Optimizations

Deprecated

Deprecations in the Python API

Fonctionnalités obsolètes

Removed

Operating Systems No Longer Supported

API and Feature Removals

Code Cleanups

Portage vers Python 3.4

Changes in “python” Command Behavior

Changes in the Python API

Changes in the C API

Changed in 3.4.3

PEP 476: Enabling certificate verification by default for stdlib http clients

Nouveautés de Python 3.3

Summary – Release highlights

PEP 405: Virtual Environments

PEP 420: Implicit Namespace Packages

PEP 3118: New memoryview implementation and buffer protocol documentation

Features

API changes

PEP 393: Flexible String Representation

Functionality

Performance and resource usage

PEP 397: Python Launcher for Windows

PEP 3151: Reworking the OS and IO exception hierarchy

PEP 380: Syntax for Delegating to a Subgenerator

PEP 409: Suppressing exception context

PEP 414: Explicit Unicode literals

PEP 3155: Qualified name for classes and functions

PEP 412: Key-Sharing Dictionary

PEP 362: Function Signature Object

PEP 421: Adding sys.implementation

SimpleNamespace

Using importlib as the Implementation of Import

New APIs

Visible Changes

Other Language Changes

A Finer-Grained Import Lock

Builtin functions and types

New Modules

faulthandler

ipaddress

lzma

Improved Modules

abc

array

base64

binascii

bz2

codecs

collections

contextlib

crypt

curses

datetime

decimal

Features

API changes

email

Policy Framework

Provisional Policy with New Header API

Other API Changes

ftplib

functools

gc

hmac

http

html

imaplib

inspect

io

itertools

logging

math

mmap

multiprocessing

nntplib

os

pdb

pickle

pydoc

re

sched

select

shlex

shutil

signal

smtpd

smtplib

socket

socketserver

sqlite3

ssl

stat

struct

subprocess

sys

tarfile

tempfile

textwrap

threading

time

types

unittest

urllib

webbrowser

xml.etree.ElementTree

zlib

Optimizations

Build and C API Changes

Deprecated

Unsupported Operating Systems

Deprecated Python modules, functions and methods

Deprecated functions and types of the C API

Fonctionnalités obsolètes

Portage vers Python 3.3

Portage de code Python

Porting C code

Building C extensions

Command Line Switch Changes

Nouveautés de Python 3.2

PEP 384: Defining a Stable ABI

PEP 389: Argparse Command Line Parsing Module

PEP 391: Dictionary Based Configuration for Logging

PEP 3148: The concurrent.futures module

PEP 3147: PYC Repository Directories

PEP 3149: ABI Version Tagged .so Files

PEP 3333: Python Web Server Gateway Interface v1.0.1

Other Language Changes

New, Improved, and Deprecated Modules

email

elementtree

functools

itertools

collections

threading

datetime and time

math

abc

io

reprlib

logging

csv

contextlib

decimal and fractions

ftp

popen

select

gzip and zipfile

tarfile

hashlib

ast

os

shutil

sqlite3

html

socket

ssl

nntp

certificates

imaplib

http.client

unittest

random

poplib

asyncore

tempfile

inspect

pydoc

dis

dbm

ctypes

site

sysconfig

pdb

configparser

urllib.parse

mailbox

turtledemo

Fils d’exécution

Optimizations

Unicode

Codecs

Documentation

IDLE

Code Repository

Build and C API Changes

Portage vers Python 3.2

Nouveautés de Python 3.1

PEP 372: Ordered Dictionaries

PEP 378: Format Specifier for Thousands Separator

Other Language Changes

New, Improved, and Deprecated Modules

Optimizations

IDLE

Build and C API Changes

Portage vers Python 3.1

Nouveautés de Python 3.0

Common Stumbling Blocks

Print Is A Function

Views And Iterators Instead Of Lists

Ordering Comparisons

Integers

Text Vs. Data Instead Of Unicode Vs. 8-bit

Overview Of Syntax Changes

New Syntax

Changed Syntax

Removed Syntax

Changes Already Present In Python 2.6

Library Changes

PEP 3101: A New Approach To String Formatting

Changes To Exceptions

Miscellaneous Other Changes

Operators And Special Methods

Builtins

Build and C API Changes

Performances

Portage vers Python 3.0

Nouveautés de Python 2.7

The Future for Python 2.x

Changes to the Handling of Deprecation Warnings

Python 3.1 Features

PEP 372: Adding an Ordered Dictionary to collections

PEP 378: Format Specifier for Thousands Separator

PEP 389: The argparse Module for Parsing Command Lines

PEP 391: Dictionary-Based Configuration For Logging

PEP 3106: Dictionary Views

PEP 3137: The memoryview Object

Other Language Changes

Interpreter Changes

Optimizations

New and Improved Modules

New module: importlib

New module: sysconfig

ttk: Themed Widgets for Tk

Updated module: unittest

Module mis-à-jour : ElementTree 1.3

Build and C API Changes

Capsules

Port-Specific Changes: Windows

Port-Specific Changes: Mac OS X

Port-Specific Changes: FreeBSD

Autres changements et corrections

Portage vers Python 2.7

New Features Added to Python 2.7 Maintenance Releases

Two new environment variables for debug mode

PEP 434: IDLE Enhancement Exception for All Branches

PEP 466: Network Security Enhancements for Python 2.7

PEP 477: Backport ensurepip (PEP 453) to Python 2.7

Bootstrapping pip By Default

Documentation Changes

PEP 476: Enabling certificate verification by default for stdlib http clients

PEP 493: HTTPS verification migration tools for Python 2.7

New make regen-all build target

Removal of make touch build target

Remerciements

Nouveautés de Python 2.6

Python 3.0

Changes to the Development Process

New Issue Tracker: Roundup

New Documentation Format: reStructuredText Using Sphinx

PEP 343: The “with” statement

Écrire des gestionnaires de contexte

Le module contextlib

PEP 366: Explicit Relative Imports From a Main Module

PEP 370: Per-user site-packages Directory

PEP 371: The multiprocessing Package

PEP 3101: Advanced String Formatting

PEP 3105: print As a Function

PEP 3110: Exception-Handling Changes

PEP 3112: Byte Literals

PEP 3116: New I/O Library

PEP 3118: Revised Buffer Protocol

PEP 3119: Abstract Base Classes

PEP 3127: Integer Literal Support and Syntax

PEP 3129: Class Decorators

PEP 3141: A Type Hierarchy for Numbers

The fractions Module

Other Language Changes

Optimizations

Interpreter Changes

New and Improved Modules

The ast module

The future_builtins module

The json module: JavaScript Object Notation

The plistlib module: A Property-List Parser

ctypes Enhancements

Improved SSL Support

Deprecations and Removals

Build and C API Changes

Port-Specific Changes: Windows

Port-Specific Changes: Mac OS X

Port-Specific Changes: IRIX

Portage vers Python 2.6

Remerciements

Nouveautés de Python 2.5

PEP 308 : Expressions conditionnelles

PEP 309 : Application partielle de fonction

PEP 314: Metadata for Python Software Packages v1.1

PEP 328: Absolute and Relative Imports

PEP 338: Executing Modules as Scripts

PEP 341: Unified try/except/finally

PEP 342: New Generator Features

PEP 343: The “with” statement

Écrire des gestionnaires de contexte

Le module contextlib

PEP 352: Exceptions as New-Style Classes

PEP 353: Using ssize_t as the index type

PEP 357: The “__index__” method

Other Language Changes

Changements de l’interpréteur interactif

Optimizations

Modules ajoutés, modifiés, et supprimés

The ctypes package

The ElementTree package

The hashlib package

The sqlite3 package

The wsgiref package

Build and C API Changes

Port-Specific Changes

Portage vers Python 2.5

Remerciements

Nouveautés de Python 2.4

PEP 218: Built-In Set Objects

PEP 237: Unifying Long Integers and Integers

PEP 289: Generator Expressions

PEP 292: Simpler String Substitutions

PEP 318: Decorators for Functions and Methods

PEP 322: Reverse Iteration

PEP 324: New subprocess Module

PEP 327: Decimal Data Type

Why is Decimal needed?

The Decimal type

The Context type

PEP 328: Multi-line Imports

PEP 331: Locale-Independent Float/String Conversions

Other Language Changes

Optimizations

New, Improved, and Deprecated Modules

cookielib

doctest

Build and C API Changes

Port-Specific Changes

Portage vers Python 2.4

Remerciements

Nouveautés de Python 2.3

PEP 218: A Standard Set Datatype

PEP 255 : Générateurs simples

PEP 263: Source Code Encodings

PEP 273: Importing Modules from ZIP Archives

PEP 277: Unicode file name support for Windows NT

PEP 278: Universal Newline Support

PEP 279: enumerate()

PEP 282: The logging Package

PEP 285 : Un type booléen

PEP 293: Codec Error Handling Callbacks

PEP 301: Package Index and Metadata for Distutils

PEP 302: New Import Hooks

PEP 305: Comma-separated Files

PEP 307: Pickle Enhancements

Extended Slices

Other Language Changes

String Changes

Optimizations

New, Improved, and Deprecated Modules

Date/Time Type

The optparse Module

Pymalloc: A Specialized Object Allocator

Build and C API Changes

Port-Specific Changes

Autres changements et corrections

Portage vers Python 2.3

Remerciements

Nouveautés de Python 2.2

Introduction

PEP 252 et 253 : Changements concernant les types et classes

Anciennes et nouvelles classes

Descripteurs

Héritage multiple : la règle du diamant

Attribute Access

Related Links

PEP 234 : Itérateurs

PEP 255 : Générateurs simples

PEP 237: Unifying Long Integers and Integers

PEP 238: Changing the Division Operator

Unicode Changes

PEP 227: Nested Scopes

New and Improved Modules

Interpreter Changes and Fixes

Autres changements et corrections

Remerciements

Nouveautés de Python 2.1

Introduction

PEP 227: Nested Scopes

PEP 236 : Directives __future__

PEP 207: Rich Comparisons

PEP 230: Warning Framework

PEP 229: New Build System

PEP 205: Weak References

PEP 232 : Attributs de fonctions

PEP 235: Importing Modules on Case-Insensitive Platforms

PEP 217: Interactive Display Hook

PEP 208: New Coercion Model

PEP 241: Metadata in Python Packages

New and Improved Modules

Autres changements et corrections

Remerciements

Nouveautés de Python 2.0

Introduction

À propos de Python 1.6

Nouveau processus de développement

Unicode

Compréhensions de listes

Augmented Assignment

Méthodes de chaînes de caractères

Garbage Collection of Cycles

Other Core Changes

Changements mineurs du langage

Changements concernant les fonctions primitives

Porting to 2.0

Extending/Embedding Changes

Distutils: Making Modules Easy to Install

Modules XML

Support de SAX2

Support du DOM

Relationship to PyXML

Module changes

Nouveaux modules

IDLE Improvements

Deleted and Deprecated Modules

Remerciements

Changements

Python 3.6.11 final

Python 3.6.11 release candidate 1

Security

Core and Builtins

Library

Python 3.6.10 final

macOS

Python 3.6.10 release candidate 1

Security

Library

Python 3.6.9 final

Library

macOS

Python 3.6.9 release candidate 1

Security

Library

Documentation

Tests

macOS

Python 3.6.8 final

Library

Build

C API

Python 3.6.8 release candidate 1

Security

Core and Builtins

Library

Documentation

Tests

Build

Windows

macOS

IDLE

Tools/Demos

Python 3.6.7 final

Python 3.6.7 release candidate 2

Core and Builtins

Library

Documentation

Tests

macOS

C API

Python 3.6.7 release candidate 1

Security

Core and Builtins

Library

Documentation

Tests

Build

Windows

macOS

IDLE

Tools/Demos

C API

Python 3.6.6 final

Python 3.6.6 release candidate 1

Core and Builtins

Library

Documentation

Tests

Build

Windows

macOS

IDLE

Tools/Demos

C API

Python 3.6.5 final

Tests

Build

Python 3.6.5 release candidate 1

Security

Core and Builtins

Library

Documentation

Tests

Build

Windows

macOS

IDLE

Tools/Demos

C API

Python 3.6.4 final

Python 3.6.4 release candidate 1

Core and Builtins

Library

Documentation

Tests

Build

Windows

macOS

IDLE

Tools/Demos

C API

Python 3.6.3 final

Library

Build

Python 3.6.3 release candidate 1

Security

Core and Builtins

Library

Documentation

Tests

Build

Windows

IDLE

Tools/Demos

Python 3.6.2 final

Python 3.6.2 release candidate 2

Security

Python 3.6.2 release candidate 1

Core and Builtins

Library

Security

Library

IDLE

C API

Build

Documentation

Tools/Demos

Tests

Windows

Python 3.6.1 final

Core and Builtins

Build

Python 3.6.1 release candidate 1

Core and Builtins

Library

IDLE

Windows

C API

Documentation

Tests

Build

Python 3.6.0 final

Python 3.6.0 release candidate 2

Core and Builtins

Tools/Demos

Windows

Build

Python 3.6.0 release candidate 1

Core and Builtins

Library

C API

Documentation

Tools/Demos

Python 3.6.0 beta 4

Core and Builtins

Library

Documentation

Tests

Build

Python 3.6.0 beta 3

Core and Builtins

Library

Windows

Build

Tests

Python 3.6.0 beta 2

Core and Builtins

Library

Windows

C API

Build

Tests

Python 3.6.0 beta 1

Core and Builtins

Library

IDLE

C API

Tests

Build

Tools/Demos

Windows

Python 3.6.0 alpha 4

Core and Builtins

Library

IDLE

Tests

Windows

Build

Python 3.6.0 alpha 3

Core and Builtins

Library

Security

Library

Security

Library

IDLE

C API

Build

Tools/Demos

Documentation

Tests

Python 3.6.0 alpha 2

Core and Builtins

Library

Security

Library

Security

Library

IDLE

Documentation

Tests

Windows

Build

Windows

C API

Tools/Demos

Python 3.6.0 alpha 1

Core and Builtins

Library

Security

Library

Security

Library

Security

Library

IDLE

Documentation

Tests

Build

Windows

Tools/Demos

C API

Python 3.5.3 final

Python 3.5.3 release candidate 1

Core and Builtins

Library

Security

Library

Security

Library

IDLE

C API

Documentation

Tests

Tools/Demos

Windows

Build

Python 3.5.2 final

Core and Builtins

Tests

IDLE

Python 3.5.2 release candidate 1

Core and Builtins

Security

Library

Security

Library

Security

Library

Security

Library

Security

Library

IDLE

Documentation

Tests

Build

Windows

Tools/Demos

Windows

Python 3.5.1 final

Core and Builtins

Windows

Python 3.5.1 release candidate 1

Core and Builtins

Library

IDLE

Documentation

Tests

Build

Windows

Tools/Demos

Python 3.5.0 final

Build

Python 3.5.0 release candidate 4

Library

Build

Python 3.5.0 release candidate 3

Core and Builtins

Library

Python 3.5.0 release candidate 2

Core and Builtins

Library

Python 3.5.0 release candidate 1

Core and Builtins

Library

IDLE

Documentation

Tests

Python 3.5.0 beta 4

Core and Builtins

Library

Build

Python 3.5.0 beta 3

Core and Builtins

Library

Tests

Documentation

Build

Python 3.5.0 beta 2

Core and Builtins

Library

Python 3.5.0 beta 1

Core and Builtins

Library

IDLE

Tests

Documentation

Tools/Demos

Python 3.5.0 alpha 4

Core and Builtins

Library

Build

Tests

Tools/Demos

C API

Python 3.5.0 alpha 3

Core and Builtins

Library

Build

Tests

Tools/Demos

Python 3.5.0 alpha 2

Core and Builtins

Library

Build

C API

Windows

Python 3.5.0 alpha 1

Core and Builtins

Library

IDLE

Build

C API

Documentation

Tests

Tools/Demos

Windows

Le tutoriel Python

1. Mise en bouche

2. Mode d’emploi de l’interpréteur Python

2.1. Lancement de l’interpréteur

2.1.1. Passage d’arguments

2.1.2. Mode interactif

2.2. L’interpréteur et son environnement

2.2.1. Encodage du code source

3. Introduction informelle à Python

3.1. Utilisation de Python comme une calculatrice

3.1.1. Les nombres

3.1.2. Chaînes de caractères

3.1.3. Listes

3.2. Premiers pas vers la programmation

4. D’autres outils de contrôle de flux

4.1. L’instruction if

4.2. L’instruction for

4.3. La fonction range()

4.4. Les instructions break, continue et les clauses else au sein des boucles

4.5. L’instruction pass

4.6. Définir des fonctions

4.7. D’avantage sur la définition des fonctions

4.7.1. Valeur par défaut des arguments

4.7.2. Les arguments nommés

4.7.3. Listes d’arguments arbitraires

4.7.4. Séparation des listes d’arguments

4.7.5. Fonctions anonymes

4.7.6. Chaînes de documentation

4.7.7. Annotations de fonctions

4.8. Aparté : le style de codage

5. Structures de données

5.1. Compléments sur les listes

5.1.1. Utilisation des listes comme des piles

5.1.2. Utilisation des listes comme des files

5.1.3. Compréhensions de listes

5.1.4. Compréhensions de listes imbriquées

5.2. L’instruction del

5.3. Tuples et séquences

5.4. Ensembles

5.5. Dictionnaires

5.6. Techniques de boucles

5.7. Plus d’informations sur les conditions

5.8. Comparer des séquences avec d’autres types

6. Modules

6.1. Les modules en détail

6.1.1. Exécuter des modules comme des scripts

6.1.2. Les dossiers de recherche de modules

6.1.3. Fichiers Python « compilés »

6.2. Modules standards

6.3. La fonction dir()

6.4. Les paquets

6.4.1. Importer * depuis un paquet

6.4.2. Références internes dans un paquet

6.4.3. Paquets dans plusieurs dossiers

7. Les entrées/sorties

7.1. Formatage de données

7.1.1. Anciennes méthodes de formatage de chaînes

7.2. Lecture et écriture de fichiers

7.2.1. Méthodes des objets fichiers

7.2.2. Sauvegarde de données structurées avec le module json

8. Erreurs et exceptions

8.1. Les erreurs de syntaxe

8.2. Exceptions

8.3. Gestion des exceptions

8.4. Déclencher des exceptions

8.5. Exceptions définies par l’utilisateur

8.6. Définition d’actions de nettoyage

8.7. Actions de nettoyage prédéfinies

9. Classes

9.1. Objets et noms : préambule

9.2. Portées et espaces de nommage en Python

9.2.1. Exemple de portées et d’espaces de nommage

9.3. Une première approche des classes

9.3.1. Syntaxe de définition des classes

9.3.2. Objets classes

9.3.3. Objets instances

9.3.4. Objets méthode

9.3.5. Classes et variables d’instance

9.4. Remarques diverses

9.5. Héritage

9.5.1. Héritage multiple

9.6. Variables privées

9.7. Trucs et astuces

9.8. Itérateurs

9.9. Générateurs

9.10. Expressions et générateurs

10. Survol de la bibliothèque standard

10.1. Interface avec le système d’exploitation

10.2. Jokers sur les noms de fichiers

10.3. Paramètres passés en ligne de commande

10.4. Redirection de la sortie d’erreur et fin d’exécution

10.5. Recherche de motifs dans les chaînes

10.6. Mathématiques

10.7. Accès à internet

10.8. Dates et heures

10.9. Compression de données

10.10. Mesure des performances

10.11. Contrôle qualité

10.12. Piles fournies

11. Survol de la bibliothèque standard – Deuxième partie

11.1. Formatage de l’affichage

11.2. Gabarits (templates en anglais)

11.3. Traitement des données binaires

11.4. Fils d’exécution

11.5. Journalisation

11.6. Références faibles

11.7. Outils pour les listes

11.8. Arithmétique décimale à virgule flottante

12. Environnements virtuels et paquets

12.1. Introduction

12.2. Création d’environnements virtuels

12.3. Gestion des paquets avec pip

13. Pour aller plus loin

14. Édition interactive des entrées et substitution d’historique

14.1. Complétion automatique et édition de l’historique

14.2. Alternatives à l’interpréteur interactif

15. Arithmétique en nombres à virgule flottante : problèmes et limites

15.1. Erreurs de représentation

16. Annexe

16.1. Mode interactif

16.1.1. Gestion des erreurs

16.1.2. Scripts Python exécutables

16.1.3. Configuration du mode interactif

16.1.4. Modules de personnalisation

Installation et utilisation de Python

1. Ligne de commande et environnement

1.1. Ligne de commande

1.1.1. Options de l’interface

1.1.2. Options génériques

1.1.3. Options diverses

1.1.4. Options à ne pas utiliser

1.2. Variables d’environnement

1.2.1. Variables en mode débogage

2. Utilisation de Python sur les plateformes Unix

2.1. Récupérer et installer la dernière version de Python

2.1.1. Sur Linux

2.1.2. Sur FreeBSD et OpenBSD

2.1.3. Sur OpenSolaris

2.2. Compiler Python

2.3. Fichiers et chemins liés à Python

2.4. Divers

2.5. Éditeurs et IDEs

3. Utilisation de Python sur Windows

3.1. Installer Python

3.1.1. Versions supportées

3.1.2. Étapes d’installation

3.1.3. Suppression de la limitation MAX_PATH

3.1.4. Installation sans l’interface utilisateur

3.1.5. Installation sans téléchargement

3.1.6. Modification d’une installation

3.1.7. Autres plateformes

3.2. Paquets alternatifs

3.3. Configurer Python

3.3.1. Digression : Définition des variables d’environnement

3.3.2. Trouver l’exécutable Python

3.4. Lanceur Python pour Windows

3.4.1. Pour commencer

3.4.1.1. Depuis la ligne de commande

3.4.1.2. Environnements virtuels

3.4.1.3. À partir d’un script

3.4.1.4. À partir d’associations de fichiers

3.4.2. Lignes Shebang

3.4.3. Arguments dans les lignes shebang

3.4.4. Personnalisation

3.4.4.1. Personnalisation via des fichiers INI

3.4.4.2. Personnalisation des versions Python par défaut

3.4.5. Diagnostics

3.5. Recherche de modules

3.6. Modules supplémentaires

3.6.1. PyWin32

3.6.2. cx_Freeze

3.6.3. WConio

3.7. Compiler Python sous Windows

3.8. Embedded Distribution

3.8.1. Application Python

3.8.2. Embarquer Python

3.9. Autres ressources

4. Utilisation de Python sur un Macintosh

4.1. Obtenir et installer MacPython

4.1.1. Comment exécuter un script Python

4.1.2. Lancer des scripts avec une interface graphique

4.1.3. Configuration

4.2. L”IDE

4.3. Installation de paquets Python additionnels

4.4. Programmation d’interface graphique sur le Mac

4.5. Distribuer des Applications Python sur le Mac

4.6. Autres ressources

La référence du langage Python

1. Introduction

1.1. Autres implémentations

1.2. Notations

2. Analyse lexicale

2.1. Structure des lignes

2.1.1. Lignes logiques

2.1.2. Lignes physiques

2.1.3. Commentaires

2.1.4. Déclaration d’encodage

2.1.5. Continuation de ligne explicite

2.1.6. Continuation de ligne implicite

2.1.7. Lignes vierges

2.1.8. Indentation

2.1.9. Espaces entre lexèmes

2.2. Autres lexèmes

2.3. Identifiants et mots-clés

2.3.1. Mots-clés

2.3.2. Classes réservées pour les identifiants

2.4. Littéraux

2.4.1. Littéraux de chaînes de caractères et de suites d’octets

2.4.2. Concaténation de chaînes de caractères

2.4.3. Chaînes de caractères formatées littérales

2.4.4. Littéraux numériques

2.4.5. Entiers littéraux

2.4.6. Nombres à virgule flottante littéraux

2.4.7. Imaginaires littéraux

2.5. Opérateurs

2.6. Délimiteurs

3. Modèle de données

3.1. Objets, valeurs et types

3.2. Hiérarchie des types standards

3.3. Méthodes spéciales

3.3.1. Personnalisation de base

3.3.2. Personnalisation de l’accès aux attributs

3.3.2.1. Personnalisation de l’accès aux attributs d’un module

3.3.2.2. Implémentation de descripteurs

3.3.2.3. Invocation des descripteurs

3.3.2.4. __slots__

3.3.2.4.1. Note sur l’utilisation de __slots__

3.3.3. Personnalisation de la création de classes

3.3.3.1. Méta-classes

3.3.3.2. Détermination de la méta-classe appropriée

3.3.3.3. Préparation de l’espace de nommage de la classe

3.3.3.4. Exécution du corps de la classe

3.3.3.5. Création de l’objet classe

3.3.3.6. Uses for metaclasses

3.3.4. Personnalisation des instances et vérification des sous-classes

3.3.5. Émulation d’objets appelables

3.3.6. Émulation de types conteneurs

3.3.7. Émulation de types numériques

3.3.8. Gestionnaire de contexte With

3.3.9. Recherche des méthodes spéciales

3.4. Coroutines

3.4.1. Objets attendables (awaitables)

3.4.2. Objets coroutines

3.4.3. Itérateurs asynchrones

3.4.4. Gestionnaires de contexte asynchrones

4. Modèle d’exécution

4.1. Structure d’un programme

4.2. Noms et liaisons

4.2.1. Liaisons des noms

4.2.2. Résolution des noms

4.2.3. Noms natifs et restrictions d’exécution

4.2.4. Interaction avec les fonctionnalités dynamiques

4.3. Exceptions

5. Le système d’importation

5.1. importlib

5.2. Les paquets

5.2.1. Paquets classiques

5.2.2. Paquets espaces de nommage

5.3. Recherche

5.3.1. Cache des modules

5.3.2. Chercheurs et chargeurs

5.3.3. Points d’entrées automatiques pour l’importation

5.3.4. Méta-chemins

5.4. Chargement

5.4.1. Chargeurs

5.4.2. Sous-modules

5.4.3. Spécificateurs de modules

5.4.4. Attributs des modules importés

5.4.5. module.__path__

5.4.6. Représentation textuelle d’un module

5.5. Le chercheur dans path

5.5.1. Chercheurs d’entrée dans path

5.5.2. Protocole des chercheurs d’entrée dans path

5.6. Remplacement du système d’importation standard

5.7. Cas particulier de __main__

5.7.1. __main__.__spec__

5.8. Idées d’amélioration

5.9. Références

6. Expressions

6.1. Conversions arithmétiques

6.2. Atomes

6.2.1. Identifiants (noms)

6.2.2. Littéraux

6.2.3. Formes parenthésées

6.2.4. Agencements des listes, ensembles et dictionnaires

6.2.5. Agencements de listes

6.2.6. Agencements d’ensembles

6.2.7. Agencements de dictionnaires

6.2.8. Expressions génératrices

6.2.9. Expressions yield

6.2.9.1. Méthodes des générateurs-itérateurs

6.2.9.2. Exemples

6.2.9.3. Fonctions génératrices asynchrones

6.2.9.4. Méthodes des générateurs-itérateurs asynchrones

6.3. Primaires

6.3.1. Références à des attributs

6.3.2. Sélections

6.3.3. Tranches

6.3.4. Appels

6.4. Expression await

6.5. L’opérateur puissance

6.6. Arithmétique unaire et opérations sur les bits

6.7. Opérations arithmétiques binaires

6.8. Opérations de décalage

6.9. Opérations binaires bit à bit

6.10. Comparaisons

6.10.1. Comparaisons de valeurs

6.10.2. Opérations de tests d’appartenance à un ensemble

6.10.3. Comparaisons d’identifiants

6.11. Opérations booléennes

6.12. Expressions conditionnelles

6.13. Expressions lambda

6.14. Listes d’expressions

6.15. Ordre d’évaluation

6.16. Priorités des opérateurs

7. Les instructions simples

7.1. Les expressions

7.2. Les assignations

7.2.1. Les assignations augmentées

7.2.2. Les assignations annotées

7.3. L’instruction assert

7.4. L’instruction pass

7.5. L’instruction del

7.6. L’instruction return

7.7. L’instruction yield

7.8. L’instruction raise

7.9. L’instruction break

7.10. L’instruction continue

7.11. L’instruction import

7.11.1. L’instruction future

7.12. L’instruction global

7.13. L’instruction nonlocal

8. Instructions composées

8.1. L’instruction if

8.2. L’instruction while

8.3. L’instruction for

8.4. L’instruction try

8.5. L’instruction with

8.6. Définition de fonctions

8.7. Définition de classes

8.8. Coroutines

8.8.1. Définition de fonctions coroutines

8.8.2. L’instruction async for

8.8.3. L’instruction async with

9. Composants de plus haut niveau

9.1. Programmes Python complets

9.2. Fichier d’entrée

9.3. Entrée interactive

9.4. Entrée d’expression

10. Spécification complète de la grammaire

La bibliothèque standard

1. Introduction

2. Fonctions natives

3. Constantes natives

3.1. Constantes ajoutées par le module site

4. Types natifs

4.1. Valeurs booléennes

4.2. Opérations booléennes — and, or, not

4.3. Comparaisons

4.4. Types numériques — int, float, complex

4.4.1. Opérations sur les bits des nombres entiers

4.4.2. Méthodes supplémentaires sur les entiers

4.4.3. Méthodes supplémentaires sur les nombres à virgule flottante

4.4.4. Hachage des types numériques

4.5. Les types itérateurs

4.5.1. Types générateurs

4.6. Types séquentiels — list, tuple, range

4.6.1. Opérations communes sur les séquences

4.6.2. Types de séquences immuables

4.6.3. Types de séquences muables

4.6.4. Listes

4.6.5. Tuples

4.6.6. Ranges

4.7. Type Séquence de Texte — str

4.7.1. Méthodes de chaînes de caractères

4.7.2. Formatage de chaines à la printf

4.8. Séquences Binaires — bytes, bytearray, memoryview

4.8.1. Objets bytes

4.8.2. Objets bytearray

4.8.3. Opérations sur les bytes et bytearray

4.8.4. Formatage de bytes a la printf

4.8.5. Vues de mémoires

4.9. Types d’ensembles — set, frozenset

4.10. Les types de correspondances — dict

4.10.1. Les vues de dictionnaires

4.11. Le type gestionnaire de contexte

4.12. Autres types natifs

4.12.1. Modules

4.12.2. Les classes et instances de classes

4.12.3. Fonctions

4.12.4. Méthodes

4.12.5. Objets code

4.12.6. Objets type

4.12.7. L’objet Null

4.12.8. L’objet points de suspension

4.12.9. L’objet NotImplemented

4.12.10. Valeurs booléennes

4.12.11. Objets internes

4.13. Attributs spéciaux

5. Exceptions natives

5.1. Classes de base

5.2. Exceptions concrètes

5.2.1. Exceptions système

5.3. Avertissements

5.4. Hiérarchie des exceptions

6. Services de Manipulation de Texte

6.1. string — Opérations usuelles sur des chaînes

6.1.1. Chaînes constantes

6.1.2. Formatage personnalisé de chaîne

6.1.3. Syntaxe de formatage de chaîne

6.1.3.1. Mini-langage de spécification de format

6.1.3.2. Exemples de formats

6.1.4. Chaînes modèles

6.1.5. Fonctions d’assistance

6.2. re — Opérations à base d’expressions rationnelles

6.2.1. Syntaxe des expressions rationnelles

6.2.2. Contenu du module

6.2.3. Objets d’expressions rationnelles

6.2.4. Objets de correspondance

6.2.5. Exemples d’expressions rationnelles

6.2.5.1. Rechercher une paire

6.2.5.2. Simuler scanf()

6.2.5.3. search() vs. match()

6.2.5.4. Construire un répertoire téléphonique

6.2.5.5. Mélanger les lettres des mots

6.2.5.6. Trouver tous les adverbes

6.2.5.7. Trouver tous les adverbes et leurs positions

6.2.5.8. Notation brutes de chaînes

6.2.5.9. Écrire un analyseur lexical

6.3. difflib — Helpers for computing deltas

6.3.1. SequenceMatcher Objects

6.3.2. SequenceMatcher Examples

6.3.3. Differ Objects

6.3.4. Differ Example

6.3.5. A command-line interface to difflib

6.4. textwrap — Encapsulation et remplissage de texte

6.5. unicodedata — Base de données Unicode

6.6. stringprep — Préparation des chaines de caractères internet

6.7. readline — interface pour GNU readline

6.7.1. Fichier d’initialisation

6.7.2. Tampon de ligne

6.7.3. Fichier d’historique

6.7.4. Liste d’historique

6.7.5. Fonctions de rappel au démarrage

6.7.6. Complétion

6.7.7. Exemple

6.8. rlcompleter — Fonction de complétion pour GNU readline

6.8.1. Objets pour la complétion (Completer Objects)

7. Services autour des Données Binaires

7.1. struct — manipulation de données agrégées sous forme binaire comme une séquence d’octets

7.1.1. Fonctions et exceptions

7.1.2. Chaînes de spécification du format

7.1.2.1. Boutisme, taille et alignement

7.1.2.2. Caractères de format

7.1.2.3. Exemples

7.1.3. Classes

7.2. codecs — Registre des codecs et classes de base associées

7.2.1. Classes de base de codecs

7.2.1.1. Gestionnaires d’erreurs

7.2.1.2. Stateless Encoding and Decoding

7.2.1.3. Incremental Encoding and Decoding

7.2.1.3.1. IncrementalEncoder Objects

7.2.1.3.2. IncrementalDecoder Objects

7.2.1.4. Stream Encoding and Decoding

7.2.1.4.1. StreamWriter Objects

7.2.1.4.2. StreamReader Objects

7.2.1.4.3. StreamReaderWriter Objects

7.2.1.4.4. StreamRecoder Objects

7.2.2. Encodings and Unicode

7.2.3. Standard Encodings

7.2.4. Python Specific Encodings

7.2.4.1. Text Encodings

7.2.4.2. Binary Transforms

7.2.4.3. Text Transforms

7.2.5. encodings.idna — Internationalized Domain Names in Applications

7.2.6. encodings.mbcs — Windows ANSI codepage

7.2.7. encodings.utf_8_sig — UTF-8 codec with BOM signature

8. Types de données

8.1. datetime — Types de base pour la date et l’heure

8.1.1. Types disponibles

8.1.2. Objets timedelta

8.1.3. Objets date

8.1.4. Objets datetime

8.1.5. Objets time

8.1.6. Objets tzinfo

8.1.7. Objets timezone

8.1.8. Comportement de strftime() et strptime()

8.2. calendar — General calendar-related functions

8.3. collections — Types de données de conteneurs

8.3.1. Objets ChainMap

8.3.1.1. Exemples et cas pratiques utilisant ChainMap

8.3.2. Objets Counter

8.3.3. Objets deque

8.3.3.1. Cas pratiques utilisant deque

8.3.4. Objets defaultdict

8.3.4.1. Exemples utilisant defaultdict

8.3.5. namedtuple(): fonction de construction pour n-uplets (tuples) avec des champs nommés

8.3.6. Objets OrderedDict

8.3.6.1. Exemples et cas pratiques utilisant OrderDict

8.3.7. Objets UserDict

8.3.8. Objets UserList

8.3.9. Objets UserString

8.4. collections.abc — Classes de base abstraites pour les conteneurs

8.4.1. Classes de base abstraites de collections

8.5. heapq — File de priorité basée sur un tas

8.5.1. Exemples simples

8.5.2. Notes d’implémentation de la file de priorité

8.5.3. Théorie

8.6. bisect — Algorithme de bissection de listes

8.6.1. Chercher dans des listes triées

8.6.2. Autres Exemples

8.7. array — Tableaux efficaces de valeurs numériques

8.8. weakref — Weak references

8.8.1. Objets à références faibles

8.8.2. Exemple

8.8.3. Finalizer Objects

8.8.4. Comparing finalizers with __del__() methods

8.9. types — Dynamic type creation and names for built-in types

8.9.1. Dynamic Type Creation

8.9.2. Standard Interpreter Types

8.9.3. Additional Utility Classes and Functions

8.9.4. Coroutine Utility Functions

8.10. copy — Opérations de copie superficielle et récursive

8.11. pprint — L’affichage élégant de données

8.11.1. Les Objets PrettyPrinter

8.11.2. Exemple

8.12. reprlib — Alternate repr() implementation

8.12.1. Repr Objects

8.12.2. Subclassing Repr Objects

8.13. enum — Énumerations

8.13.1. Contenu du module

8.13.2. Création d’une Enum

8.13.3. Accès dynamique aux membres et à leurs attributs

8.13.4. Duplication de membres et de valeurs

8.13.5. Coercition d’unicité des valeurs d’une énumération

8.13.6. Valeurs automatiques

8.13.7. Itération

8.13.8. Comparaisons

8.13.9. Membres et attributs autorisés dans une énumération

8.13.10. Restricted subclassing of enumerations

8.13.11. Sérialisation

8.13.12. API par fonction

8.13.13. Énumérations dérivées

8.13.13.1. IntEnum

8.13.13.2. IntFlag

8.13.13.3. Option

8.13.13.4. Autres

8.13.14. Exemples intéressants

8.13.14.1. Omettre les valeurs

8.13.14.1.1. Avec auto

8.13.14.1.2. Avec object

8.13.14.1.3. Avec une chaîne de caractères de description

8.13.14.1.4. Avec une méthode ad-hoc __new__()

8.13.14.2. OrderedEnum

8.13.14.3. DuplicateFreeEnum

8.13.14.4. Planet

8.13.15. En quoi les Enums sont différentes ?

8.13.15.1. Classes Enum

8.13.15.2. Membres d’Enum (c.-à-d. instances)

8.13.15.3. Aspects approfondis

8.13.15.3.1. Noms de la forme __dunder__ disponibles

8.13.15.3.2. Noms de la forme _sunder_ disponibles

8.13.15.3.3. Type des membres de Enum

8.13.15.3.4. Valeur booléenne des classes Enum et de leurs membres

8.13.15.3.5. Classes Enum avec des méthodes

8.13.15.3.6. Combinaison de membres de Flag

9. Modules numériques et mathématiques

9.1. numbers — Classes de base abstraites numériques

9.1.1. La tour numérique

9.1.2. Notes pour implémenter des types

9.1.2.1. Ajouter plus d’ABC numériques

9.1.2.2. Implémentation des opérations arithmétiques

9.2. Fonctions mathématiques — math

9.2.1. Fonctions arithmétiques et de représentation

9.2.2. Fonctions logarithme et exponentielle

9.2.3. Fonctions trigonométriques

9.2.4. Conversion angulaire

9.2.5. Fonctions hyperboliques

9.2.6. Fonctions spéciales

9.2.7. Constantes

9.3. Fonctions mathématiques pour nombres complexes — cmath

9.3.1. Conversion vers et à partir de coordonnées polaires

9.3.2. Fonctions logarithme et exponentielle

9.3.3. Fonctions trigonométriques

9.3.4. Fonctions hyperboliques

9.3.5. Fonctions de classifications

9.3.6. Constantes

9.4. decimal — Arithmétique décimale en virgule fixe et flottante

9.4.1. Introduction pratique

9.4.2. Les objets Decimal

9.4.2.1. Logical operands

9.4.3. Context objects

9.4.4. Constantes

9.4.5. Rounding modes

9.4.6. Signals

9.4.7. Floating Point Notes

9.4.7.1. Mitigating round-off error with increased precision

9.4.7.2. Special values

9.4.8. Working with threads

9.4.9. Cas pratiques

9.4.10. FAQ decimal

9.5. fractions — Nombres rationnels

9.6. random — Génère des nombres pseudo-aléatoires

9.6.1. Fonctions de gestion d’état

9.6.2. Fonctions pour les entiers

9.6.3. Fonctions pour les séquences

9.6.4. Distributions pour les nombre réels

9.6.5. Générateur alternatif

9.6.6. Remarques sur la reproductibilité

9.6.7. Exemples et recettes

9.7. statistics — Mathematical statistics functions

9.7.1. Averages and measures of central location

9.7.2. Measures of spread

9.7.3. Function details

9.7.4. Exceptions

10. Modules de programmation fonctionnelle

10.1. itertools — Fonctions créant des itérateurs pour boucler efficacement

10.1.1. Fonctions d”itertool

10.1.2. Recettes itertools

10.2. functools — Fonctions de haut niveau et opérations sur des objets appelables

10.2.1. Objets partial

10.3. operator — Opérateurs standards en tant que fonctions

10.3.1. Correspondances entre opérateurs et fonctions

10.3.2. Inplace Operators

11. Accès aux Fichiers et aux Dossiers

11.1. pathlib — Chemins de système de fichiers orientés objet

11.1.1. Utilisation basique

11.1.2. Chemins purs

11.1.2.1. Propriétés générales

11.1.2.2. Opérateurs

11.1.2.3. Accéder aux parties individuelles

11.1.2.4. Méthodes et propriétés

11.1.3. Chemins concrets

11.1.3.1. Méthodes

11.2. os.path — manipulation courante des chemins

11.3. fileinput — Iterate over lines from multiple input streams

11.4. stat — Interpreting stat() results

11.5. filecmp – Comparaisons de fichiers et de répertoires

11.5.1. La classe dircmp

11.6. tempfile — Génération de fichiers et répertoires temporaires

11.6.1. Exemples

11.6.2. Fonctions et variables obsolètes

11.7. glob — Recherche de chemins de style Unix selon certains motifs

11.8. fnmatch — Filtrage par motif des noms de fichiers Unix

11.9. linecache — Accès direct aux lignes d’un texte

11.10. shutil — Opérations de haut niveau sur les fichiers

11.10.1. Opérations sur les répertoires et les fichiers

11.10.1.1. copytree example

11.10.1.2. rmtree example

11.10.2. Archiving operations

11.10.2.1. Archiving example

11.10.3. Querying the size of the output terminal

11.11. macpath — Fonctions de manipulation de chemins pour Mac OS 9

12. Persistance des données

12.1. pickle — Module de sérialisation d’objets Python

12.1.1. Relations aux autres modules python

12.1.1.1. Comparaison avec marshal

12.1.1.2. Comparison with json

12.1.2. Data stream format

12.1.3. Module Interface

12.1.4. What can be pickled and unpickled?

12.1.5. Pickling Class Instances

12.1.5.1. Persistence of External Objects

12.1.5.2. Dispatch Tables

12.1.5.3. Handling Stateful Objects

12.1.6. Restricting Globals

12.1.7. Performances

12.1.8. Exemples

12.2. copyreg — Enregistre les fonctions support de pickle

12.2.1. Exemple

12.3. shelve — Objet Python persistant

12.3.1. Limites

12.3.2. Exemple

12.4. marshal — Internal Python object serialization

12.5. dbm — Interfaces to Unix « databases »

12.5.1. dbm.gnu — GNU’s reinterpretation of dbm

12.5.2. dbm.ndbm — Interface based on ndbm

12.5.3. dbm.dumb — Portable DBM implementation

12.6. sqlite3 — Interface DB-API 2.0 pour bases de données SQLite

12.6.1. Fonctions et constantes du module

12.6.2. Objets de connexions

12.6.3. Cursor Objects

12.6.4. Row Objects

12.6.5. Exceptions

12.6.6. SQLite and Python types

12.6.6.1. Introduction

12.6.6.2. Using adapters to store additional Python types in SQLite databases

12.6.6.2.1. Letting your object adapt itself

12.6.6.2.2. Registering an adapter callable

12.6.6.3. Converting SQLite values to custom Python types

12.6.6.4. Default adapters and converters

12.6.7. Controlling Transactions

12.6.8. Using sqlite3 efficiently

12.6.8.1. Using shortcut methods

12.6.8.2. Accessing columns by name instead of by index

12.6.8.3. Using the connection as a context manager

12.6.9. Common issues

12.6.9.1. Fils d’exécution

13. Compression de donnée et archivage

13.1. zlib — Compression compatible avec gzip

13.2. gzip — Support pour les fichiers gzip

13.2.1. Exemples d’utilisation

13.3. bz2 — Prise en charge de la compression bzip2

13.3.1. (Dé)compression de fichiers

13.3.2. (Dé)compression incrémentielle

13.3.3. (Dé)compression en une fois

13.4. lzma — Compression via l’algorithme LZMA

13.4.1. Lire et écrire des fichiers compressés

13.4.2. Compresser et décompresser une donnée en mémoire

13.4.3. Divers

13.4.4. Préciser des chaînes de filtre personnalisées

13.4.5. Exemples

13.5. zipfile — Travailler avec des archives ZIP

13.5.1. Objets ZipFile

13.5.2. Objets PyZipFile

13.5.3. Objets ZipInfo

13.5.4. Interface en ligne de commande

13.5.4.1. Options de la ligne de commande

13.6. tarfile — Read and write tar archive files

13.6.1. TarFile Objects

13.6.2. TarInfo Objects

13.6.3. Interface en ligne de commande

13.6.3.1. Options de la ligne de commande

13.6.4. Exemples

13.6.5. Supported tar formats

13.6.6. Unicode issues

14. Formats de fichiers

14.1. csv — Lecture et écriture de fichiers CSV

14.1.1. Contenu du module

14.1.2. Dialectes et paramètres de formatage

14.1.3. Objets lecteurs

14.1.4. Objets transcripteurs

14.1.5. Exemples

14.2. configparser — Configuration file parser

14.2.1. Quick Start

14.2.2. Supported Datatypes

14.2.3. Fallback Values

14.2.4. Supported INI File Structure

14.2.5. Interpolation of values

14.2.6. Mapping Protocol Access

14.2.7. Customizing Parser Behaviour

14.2.8. Legacy API Examples

14.2.9. ConfigParser Objects

14.2.10. RawConfigParser Objects

14.2.11. Exceptions

14.3. netrc — traitement de fichier netrc

14.3.1. Objets netrc

14.4. xdrlib — Encode and decode XDR data

14.4.1. Packer Objects

14.4.2. Unpacker Objects

14.4.3. Exceptions

14.5. plistlib — Generate and parse Mac OS X .plist files

14.5.1. Exemples

15. Service de cryptographie

15.1. hashlib — Algorithmes de hachage sécurisés et synthèse de messages

15.1.1. Algorithmes de hachage

15.1.2. Synthèse de messages de taille variable SHAKE

15.1.3. Dérivation de clé

15.1.4. BLAKE2

15.1.4.1. Création d’objets hachés

15.1.4.2. Constantes

15.1.4.3. Exemples

15.1.4.3.1. Hachage simple

15.1.4.3.2. Usage de tailles d’empreintes différentes

15.1.4.3.3. Code d’authentification de message

15.1.4.3.4. Hachage randomisé

15.1.4.3.5. Personnalisation

15.1.4.3.6. Mode Arbre

15.1.4.4. Crédits

15.2. hmac — Authentification de messages par hachage en combinaison avec une clé secrète

15.3. secrets — Générer des nombres aléatoires de façon sécurisée pour la gestion des secrets

15.3.1. Nombres aléatoires

15.3.2. Génération de jetons

15.3.2.1. Combien d’octets mon jeton doit-il comporter ?

15.3.3. Autres fonctions

15.3.4. Recettes et bonnes pratiques

16. Services génériques du système d’exploitation

16.1. os — Diverses interfaces pour le système d’exploitation

16.1.1. Noms de fichiers, arguments en ligne de commande, et variables d’environnement

16.1.2. Paramètres de processus

16.1.3. Création de fichiers objets

16.1.4. Opérations sur les descripteurs de fichiers

16.1.4.1. Demander la taille d’un terminal

16.1.4.2. Héritage de descripteurs de fichiers

16.1.5. Fichiers et répertoires

16.1.5.1. Attributs étendus pour Linux

16.1.6. Gestion des processus

16.1.7. Interface pour l’ordonnanceur

16.1.8. Diverses informations sur le système

16.1.9. Nombres aléatoires

16.2. io — Core tools for working with streams

16.2.1. Aperçu

16.2.1.1. Text I/O

16.2.1.2. Binary I/O

16.2.1.3. Raw I/O

16.2.2. High-level Module Interface

16.2.2.1. In-memory streams

16.2.3. Class hierarchy

16.2.3.1. I/O Base Classes

16.2.3.2. Raw File I/O

16.2.3.3. Buffered Streams

16.2.3.4. Text I/O

16.2.4. Performances

16.2.4.1. Binary I/O

16.2.4.2. Text I/O

16.2.4.3. Fils d’exécution

16.2.4.4. Reentrancy

16.3. time — Accès au temps et conversions

16.3.1. Fonctions

16.3.2. Constantes d’identification d’horloge

16.3.3. Constantes de fuseau horaire

16.4. argparse – Parseur d’arguments, d’options, et de sous-commandes de ligne de commande

16.4.1. Exemple

16.4.1.1. Créer un analyseur (parser en anglais)

16.4.1.2. Ajouter des arguments

16.4.1.3. Analyse des arguments

16.4.2. Objets ArgumentParser

16.4.2.1. Le paramètre prog

16.4.2.2. Le paramètre usage

16.4.2.3. Le paramètre description

16.4.2.4. Le paramètre epilog

16.4.2.5. Le paramètre parents

16.4.2.6. Le paramètre formatter_class

16.4.2.7. Le paramètre prefix_chars

16.4.2.8. Le paramètre fromfile_prefix_chars

16.4.2.9. Le paramètre argument_default

16.4.2.10. Le paramètre allow_abbrev

16.4.2.11. Le paramètre conflict_handler

16.4.2.12. Le paramètre add_help

16.4.3. La méthode add_argument()

16.4.3.1. Les paramètres name et flags

16.4.3.2. Le paramètre action

16.4.3.3. Le paramètre nargs

16.4.3.4. Le paramètre const

16.4.3.5. Le paramètre default

16.4.3.6. Le paramètre type

16.4.3.7. Le paramètre choices

16.4.3.8. Le paramètre required

16.4.3.9. Le paramètre help

16.4.3.10. Le paramètre metavar

16.4.3.11. Le paramètre dest

16.4.3.12. Classes Action

16.4.4. La méthode parse_args()

16.4.4.1. Option value syntax

16.4.4.2. Arguments invalides

16.4.4.3. Arguments contenant -

16.4.4.4. Arguments abrégés (Par comparaison de leurs préfixes)

16.4.4.5. Au-delà de sys.argv

16.4.4.6. L’objet namespace

16.4.5. Autres outils

16.4.5.1. Sous commandes

16.4.5.2. Objets FileType

16.4.5.3. Groupes d’arguments

16.4.5.4. Exclusion mutuelle

16.4.5.5. Valeurs par défaut de l’analyseur

16.4.5.6. Afficher l’aide

16.4.5.7. Parsing partiel

16.4.5.8. Personnaliser le parsing de fichiers

16.4.5.9. Exiting methods

16.4.6. Mettre à jour du code optparse

16.5. getopt – Analyseur de style C pour les options de ligne de commande

16.6. logging — Fonctionnalités de journalisation pour Python

16.6.1. Objets Enregistreurs

16.6.2. Niveaux de journalisation

16.6.3. Handler Objects

16.6.4. Formatter Objects

16.6.5. Filter Objects

16.6.6. LogRecord Objects

16.6.7. LogRecord attributes

16.6.8. LoggerAdapter Objects

16.6.9. Thread Safety

16.6.10. Fonctions de niveau module

16.6.11. Module-Level Attributes

16.6.12. Integration with the warnings module

16.7. logging.config — Logging configuration

16.7.1. Configuration functions

16.7.2. Configuration dictionary schema

16.7.2.1. Dictionary Schema Details

16.7.2.2. Incremental Configuration

16.7.2.3. Object connections

16.7.2.4. User-defined objects

16.7.2.5. Access to external objects

16.7.2.6. Access to internal objects

16.7.2.7. Import resolution and custom importers

16.7.3. Configuration file format

16.8. logging.handlers — Logging handlers

16.8.1. StreamHandler

16.8.2. FileHandler

16.8.3. NullHandler

16.8.4. WatchedFileHandler

16.8.5. BaseRotatingHandler

16.8.6. RotatingFileHandler

16.8.7. TimedRotatingFileHandler

16.8.8. SocketHandler

16.8.9. DatagramHandler

16.8.10. SysLogHandler

16.8.11. NTEventLogHandler

16.8.12. SMTPHandler

16.8.13. MemoryHandler

16.8.14. HTTPHandler

16.8.15. QueueHandler

16.8.16. QueueListener

16.9. Saisie de mot de passe portable

16.10. curses — Terminal handling for character-cell displays

16.10.1. Fonctions

16.10.2. Window Objects

16.10.3. Constantes

16.11. curses.textpad — Text input widget for curses programs

16.11.1. Textbox objects

16.12. curses.ascii — Utilities for ASCII characters

16.13. curses.panel — A panel stack extension for curses

16.13.1. Fonctions

16.13.2. Panel Objects

16.14. platform — Access to underlying platform’s identifying data

16.14.1. Cross Platform

16.14.2. Java Platform

16.14.3. Windows Platform

16.14.3.1. Win95/98 specific

16.14.4. Mac OS Platform

16.14.5. Unix Platforms

16.15. errno — Symboles du système errno standard

16.16. ctypes — Bibliothèque Python d’appels à des fonctions externes

16.16.1. Didacticiel de ctypes

16.16.1.1. Chargement des DLL

16.16.1.2. Accès aux fonctions des DLL chargées

16.16.1.3. Appel de fonctions

16.16.1.4. Types de données fondamentaux

16.16.1.5. Appel de fonctions, suite

16.16.1.6. Appel de fonctions avec des types de données personnalisés

16.16.1.7. Définition du type des arguments nécessaires (prototypes de fonction)

16.16.1.8. Types de sortie

16.16.1.9. Passage de pointeurs (passage de paramètres par référence)

16.16.1.10. Structures et unions

16.16.1.11. Alignement et boutisme des structures et des unions

16.16.1.12. Champs de bits dans les structures et les unions

16.16.1.13. Tableaux

16.16.1.14. Pointeurs

16.16.1.15. Conversions de type

16.16.1.16. Types incomplets

16.16.1.17. Fonctions de rappel

16.16.1.18. Accès aux variables exportées depuis une DLL

16.16.1.19. Pièges

16.16.1.20. Types de données à taille flottante

16.16.2. Référence du module

16.16.2.1. Recherche de bibliothèques partagées

16.16.2.2. Chargement des bibliothèques partagées

16.16.2.3. Fonctions externes

16.16.2.4. Prototypes de fonction

16.16.2.5. Fonctions utilitaires

16.16.2.6. Types de données

16.16.2.7. Types de données fondamentaux

16.16.2.8. Types de donnée dérivés de Structure

16.16.2.9. Tableaux et pointeurs

17. Exécution concourante

17.1. threading — Parallélisme basé sur les fils d’exécution (threads)

17.1.1. Données locales au fil d’exécution

17.1.2. Objets Threads

17.1.3. Verrous

17.1.4. RLock Objects

17.1.5. Condition Objects

17.1.6. Semaphore Objects

17.1.6.1. Semaphore Example

17.1.7. Event Objects

17.1.8. Timer Objects

17.1.9. Barrier Objects

17.1.10. Using locks, conditions, and semaphores in the with statement

17.2. multiprocessing — Parallélisme par processus

17.2.1. Introduction

17.2.1.1. La classe Process

17.2.1.2. Contextes et méthodes de démarrage

17.2.1.3. Échange d’objets entre les processus

17.2.1.4. Synchronisation entre processus

17.2.1.5. Partager un état entre les processus

17.2.1.6. Utiliser un réservoir de workers

17.2.2. Référence

17.2.2.1. Process et exceptions

17.2.2.2. Tubes (pipes) et Queues

17.2.2.3. Divers

17.2.2.4. Objets de connexions

17.2.2.5. Primitives de synchronisation

17.2.2.6. Objets ctypes partagés

17.2.2.6.1. Le module multiprocessing.sharedctypes

17.2.2.7. Gestionnaires

17.2.2.7.1. Gestionnaires personnalisés

17.2.2.7.2. Utiliser un gestionnaire distant

17.2.2.8. Objets mandataires

17.2.2.8.1. Nettoyage

17.2.2.9. Bassins de processus

17.2.2.10. Auditeurs et Clients

17.2.2.10.1. Formats d’adresses

17.2.2.11. Clés d’authentification

17.2.2.12. Journalisation

17.2.2.13. Le module multiprocessing.dummy

17.2.3. Lignes directrices de programmation

17.2.3.1. Toutes les méthodes de démarrage

17.2.3.2. Les méthodes de démarrage spawn et forkserver

17.2.4. Exemples

17.3. Le paquet concurrent

17.4. concurrent.futures — Launching parallel tasks

17.4.1. Executor Objects

17.4.2. ThreadPoolExecutor

17.4.2.1. ThreadPoolExecutor Example

17.4.3. ProcessPoolExecutor

17.4.3.1. ProcessPoolExecutor Example

17.4.4. Future Objects

17.4.5. Module Functions

17.4.6. Exception classes

17.5. subprocess — Gestion de sous-processus

17.5.1. Utiliser le module subprocess

17.5.1.1. Arguments fréquemment utilisés

17.5.1.2. Constructeur de Popen

17.5.1.3. Exceptions

17.5.2. Considérations de sécurité

17.5.3. Objets Popen

17.5.4. Utilitaires Popen pour Windows

17.5.4.1. Constantes

17.5.5. Ancienne interface (API) haut-niveau

17.5.6. Remplacer les fonctions plus anciennes par le module subprocess

17.5.6.1. Remplacement des backquotes des shells /bin/sh

17.5.6.2. Remplacer les pipes du shell

17.5.6.3. Remplacer os.system()

17.5.6.4. Remplacer les fonctions de la famille os.spawn

17.5.6.5. Remplacer os.popen(), os.popen2(), os.popen3()

17.5.6.6. Remplacer les fonctions du module popen2

17.5.7. Remplacement des fonctions originales d’invocation du shell

17.5.8. Notes

17.5.8.1. Convertir une séquence d’arguments vers une chaîne de caractères sous Windows

17.6. sched — Event scheduler

17.6.1. Scheduler Objects

17.7. queue — File synchronisée

17.7.1. Objets Queue

17.8. dummy_threading — Module de substitution au module threading

17.9. _thread — API bas niveau de gestion de fils d’exécution

17.10. _dummy_thread — Module de substitution pour le module _thread

18. Communication et réseau entre processus

18.1. socket — Low-level networking interface

18.1.1. Socket families

18.1.2. Module contents

18.1.2.1. Exceptions

18.1.2.2. Constantes

18.1.2.3. Fonctions

18.1.2.3.1. Creating sockets

18.1.2.3.2. Autres fonctions

18.1.3. Socket Objects

18.1.4. Notes on socket timeouts

18.1.4.1. Timeouts and the connect method

18.1.4.2. Timeouts and the accept method

18.1.5. Exemple

18.2. ssl — Emballage TLS/SSL pour les objets connecteurs

18.2.1. Fonctions, constantes et exceptions

18.2.1.1. Création de connecteurs

18.2.1.2. Création de contexte

18.2.1.3. Random generation

18.2.1.4. Certificate handling

18.2.1.5. Constantes

18.2.2. SSL Sockets

18.2.3. SSL Contexts

18.2.4. Certificates

18.2.4.1. Certificate chains

18.2.4.2. CA certificates

18.2.4.3. Combined key and certificate

18.2.4.4. Self-signed certificates

18.2.5. Exemples

18.2.5.1. Testing for SSL support

18.2.5.2. Client-side operation

18.2.5.3. Server-side operation

18.2.6. Notes on non-blocking sockets

18.2.7. Memory BIO Support

18.2.8. SSL session

18.2.9. Security considerations

18.2.9.1. Best defaults

18.2.9.2. Manual settings

18.2.9.2.1. Verifying certificates

18.2.9.2.2. Protocol versions

18.2.9.2.3. Cipher selection

18.2.9.3. Multi-processing

18.2.10. LibreSSL support

18.3. select — Waiting for I/O completion

18.3.1. /dev/poll Polling Objects

18.3.2. Edge and Level Trigger Polling (epoll) Objects

18.3.3. Polling Objects

18.3.4. Kqueue Objects

18.3.5. Kevent Objects

18.4. selectors — High-level I/O multiplexing

18.4.1. Introduction

18.4.2. Classes

18.4.3. Exemples

18.5. asyncio — Entrées/Sorties asynchrone, boucle d’évènements, coroutines et tâches

18.5.1. Base Event Loop

18.5.1.1. Exécuter une boucle d’évènements

18.5.1.2. Appels

18.5.1.3. Appels différés

18.5.1.4. Futurs

18.5.1.5. Tâches

18.5.1.6. Créer des connections

18.5.1.7. Attendre des connections

18.5.1.8. Surveiller des descripteurs de fichiers

18.5.1.9. Opérations bas niveau sur les socket

18.5.1.10. Résout le nom d’hôte

18.5.1.11. Connect pipes

18.5.1.12. Signaux UNIX

18.5.1.13. Exécuteur

18.5.1.14. API de gestion d’erreur

18.5.1.15. Mode débogage

18.5.1.16. Serveur

18.5.1.17. Handle

18.5.1.18. Exemples de boucles d’évènements

18.5.1.18.1. « Hello World » avec call_soon()

18.5.1.18.2. Afficher la date actuelle avec call_later()

18.5.1.18.3. Watch a file descriptor for read events

18.5.1.18.4. Définit les gestionnaires de signaux pour SIGINT et SIGTERM

18.5.2. Boucles d’évènements

18.5.2.1. Fonctions des boucles d’évènements

18.5.2.2. Boucles d’évènements disponibles

18.5.2.3. Support des plateformes

18.5.2.3.1. Windows

18.5.2.3.2. Mac OS X

18.5.2.4. Event loop policies and the default policy

18.5.2.5. Event loop policy interface

18.5.2.6. Access to the global loop policy

18.5.2.7. Customizing the event loop policy

18.5.3. Tâches et coroutines

18.5.3.1. Coroutines

18.5.3.1.1. Exemple : Coroutine « Hello World »

18.5.3.1.2. Exemple : Coroutine affichant la date actuelle

18.5.3.1.3. Exemple : Chaîner des coroutines

18.5.3.2. InvalidStateError

18.5.3.3. TimeoutError

18.5.3.4. Future

18.5.3.4.1. Exemple : Futur avec run_until_complete()

18.5.3.4.2. Exemple : Futur avec run_forever()

18.5.3.5. Task

18.5.3.5.1. Exemple : Exécution parallèle de tâches

18.5.3.6. Task functions

18.5.4. Transports et protocoles (APi basée sur des fonctions de rappel)

18.5.4.1. Transports

18.5.4.1.1. BaseTransport

18.5.4.1.2. ReadTransport

18.5.4.1.3. WriteTransport

18.5.4.1.4. DatagramTransport

18.5.4.1.5. BaseSubprocessTransport

18.5.4.2. Protocols

18.5.4.2.1. Protocol classes

18.5.4.2.2. Connection callbacks

18.5.4.2.3. Streaming protocols

18.5.4.2.4. Protocoles de datagrammes

18.5.4.2.5. Flow control callbacks

18.5.4.2.6. Coroutines et protocoles

18.5.4.3. Exemples de protocole

18.5.4.3.1. Protocole « echo client » en TCP

18.5.4.3.2. Protocole « echo serveur » en TCP

18.5.4.3.3. Protocole « echo client » en UDP

18.5.4.3.4. Protocole « echo serveur » en UDP

18.5.4.3.5. Register an open socket to wait for data using a protocol

18.5.5. Streams (coroutine based API)

18.5.5.1. Stream functions

18.5.5.2. StreamReader

18.5.5.3. StreamWriter

18.5.5.4. StreamReaderProtocol

18.5.5.5. IncompleteReadError

18.5.5.6. LimitOverrunError

18.5.5.7. Stream examples

18.5.5.7.1. TCP echo client using streams

18.5.5.7.2. TCP echo server using streams

18.5.5.7.3. Récupère les en-têtes HTTP

18.5.5.7.4. Register an open socket to wait for data using streams

18.5.6. Subprocess

18.5.6.1. Boucle d’évènements Windows

18.5.6.2. Créer un processus fils : API de haut niveau utilisant Process

18.5.6.3. Create a subprocess: low-level API using subprocess.Popen

18.5.6.4. Constantes

18.5.6.5. Process

18.5.6.6. Processus fils et fils d’exécution

18.5.6.7. Subprocess examples

18.5.6.7.1. Subprocess using transport and protocol

18.5.6.7.2. Subprocess using streams

18.5.7. Primitives de synchronisation

18.5.7.1. Locks

18.5.7.1.1. Lock

18.5.7.1.2. Event

18.5.7.1.3. Condition

18.5.7.2. Sémaphores

18.5.7.2.1. Sémaphore

18.5.7.2.2. BoundedSemaphore

18.5.8. Queues

18.5.8.1. Queue

18.5.8.2. PriorityQueue

18.5.8.3. LifoQueue

18.5.8.3.1. Exceptions

18.5.9. Programmer avec asyncio

18.5.9.1. Mode de débogage d”asyncio

18.5.9.2. Annulation

18.5.9.3. Concourance et multithreading

18.5.9.4. Gérer les fonctions bloquantes correctement

18.5.9.5. Journalisation

18.5.9.6. Détecte les coroutines qui ne sont jamais exécutées

18.5.9.7. Detect exceptions never consumed

18.5.9.8. Chaîner les coroutines correctement

18.5.9.9. Pending task destroyed

18.5.9.10. Close transports and event loops

18.6. asyncore — Gestionnaire de socket asynchrone

18.6.1. Exemple de client HTTP basique avec asyncore

18.6.2. Serveur echo basique avec asyncore

18.7. asynchat — Gestionnaire d’interfaces de connexion (socket) commande/réponse asynchrones

18.7.1. Exemple asynchat

18.8. signal — Set handlers for asynchronous events

18.8.1. General rules

18.8.1.1. Execution of Python signal handlers

18.8.1.2. Signals and threads

18.8.2. Module contents

18.8.3. Exemple

18.9. mmap — Memory-mapped file support

19. Traitement des données provenant d’Internet

19.1. email — Un paquet de gestion des e-mails et MIME

19.1.1. email.message: Representing an email message

19.1.2. email.parser : Analyser des e-mails

19.1.2.1. API FeedParser

19.1.2.2. API de Parser

19.1.2.3. Notes complémentaires

19.1.3. email.generator: Generating MIME documents

19.1.4. email.policy: Policy Objects

19.1.5. email.errors: Exception and Defect classes

19.1.6. email.headerregistry: Custom Header Objects

19.1.7. email.contentmanager: Managing MIME Content

19.1.7.1. Content Manager Instances

19.1.8. email: Exemples

19.1.9. email.message.Message: Representing an email message using the compat32 API

19.1.10. email.mime: Creating email and MIME objects from scratch

19.1.11. email.header: Internationalized headers

19.1.12. email.charset: Representing character sets

19.1.13. email.encoders : Encodeurs

19.1.14. email.utils: Miscellaneous utilities

19.1.15. email.iterators: Itérateurs

19.2. json — Encodage et décodage JSON

19.2.1. Utilisation basique

19.2.2. Encodeurs et décodeurs

19.2.3. Exceptions

19.2.4. Conformité au standard et Interopérabilité

19.2.4.1. Encodage des caractères

19.2.4.2. Valeurs numériques infinies et NaN

19.2.4.3. Noms répétés au sein d’un objet

19.2.4.4. Valeurs de plus haut niveau autres qu’objets ou tableaux

19.2.4.5. Limitations de l’implémentation

19.2.5. Interface en ligne de commande

19.2.5.1. Options de la ligne de commande

19.3. mailcap — Manipulation de fichiers Mailcap

19.4. mailbox — Manipuler les boîtes de courriels dans différents formats

19.4.1. Objets Mailbox

19.4.1.1. Maildir

19.4.1.2. mbox

19.4.1.3. MH

19.4.1.4. Babyl

19.4.1.5. MMDF

19.4.2. Message objects

19.4.2.1. MaildirMessage

19.4.2.2. mboxMessage

19.4.2.3. MHMessage

19.4.2.4. BabylMessage

19.4.2.5. MMDFMessage

19.4.3. Exceptions

19.4.4. Exemples

19.5. mimetypes — Map filenames to MIME types

19.5.1. MimeTypes Objects

19.6. base64 — Encodages base16, base32, base64 et base85

19.7. binhex — Encode et décode les fichiers binhex4

19.7.1. Notes

19.8. binascii — Conversion entre binaire et ASCII

19.9. quopri — Encode et décode des données MIME quoted-printable

19.10. uu — Encode et décode les fichiers uuencode

20. Outils de traitement de balises structurées

20.1. html — Support du HyperText Markup Language

20.2. html.parser — Simple HTML and XHTML parser

20.2.1. Example HTML Parser Application

20.2.2. HTMLParser Methods

20.2.3. Exemples

20.3. html.entities — Définitions des entités HTML générales

20.4. Modules de traitement XML

20.4.1. Vulnérabilités XML

20.4.2. Les paquets defusedxml et defusedexpat

20.5. xml.etree.ElementTree — The ElementTree XML API

20.5.1. Tutoriel

20.5.1.1. XML tree and elements

20.5.1.2. Parsing XML

20.5.1.3. Pull API for non-blocking parsing

20.5.1.4. Finding interesting elements

20.5.1.5. Modifying an XML File

20.5.1.6. Building XML documents

20.5.1.7. Parsing XML with Namespaces

20.5.1.8. Additional resources

20.5.2. XPath support

20.5.2.1. Exemple

20.5.2.2. Supported XPath syntax

20.5.3. Référence

20.5.3.1. Fonctions

20.5.3.2. Objets Elements

20.5.3.3. ElementTree Objects

20.5.3.4. QName Objects

20.5.3.5. TreeBuilder Objects

20.5.3.6. XMLParser Objects

20.5.3.7. XMLPullParser Objects

20.5.3.8. Exceptions

20.6. xml.dom — L’API Document Object Model

20.6.1. Contenu du module

20.6.2. Objets dans le DOM

20.6.2.1. Objets DOMImplementation

20.6.2.2. Objets nœuds

20.6.2.3. Objet NodeList

20.6.2.4. Objets DocumnentType

20.6.2.5. Objets Document

20.6.2.6. Objets Elements

20.6.2.7. Objets Attr

20.6.2.8. Objets NameNodeMap

20.6.2.9. Objets Comment

20.6.2.10. Objets Text et CDATASection

20.6.2.11. Objets ProcessingInstruction

20.6.2.12. Exceptions

20.6.3. Conformité

20.6.3.1. Correspondance des types

20.6.3.2. Méthodes d’accès

20.7. xml.dom.minidom — Minimal DOM implementation

20.7.1. DOM Objects

20.7.2. DOM Example

20.7.3. minidom and the DOM standard

20.8. xml.dom.pulldom — Support for building partial DOM trees

20.8.1. DOMEventStream Objects

20.9. xml.sax — Prise en charge des analyseurs SAX2

20.9.1. Les objets SAXException

20.10. xml.sax.handler — Base classes for SAX handlers

20.10.1. ContentHandler Objects

20.10.2. DTDHandler Objects

20.10.3. EntityResolver Objects

20.10.4. ErrorHandler Objects

20.11. xml.sax.saxutils — Utilitaires SAX

20.12. xml.sax.xmlreader — Interface for XML parsers

20.12.1. XMLReader Objects

20.12.2. IncrementalParser Objects

20.12.3. Locator Objects

20.12.4. InputSource Objects

20.12.5. The Attributes Interface

20.12.6. The AttributesNS Interface

20.13. xml.parsers.expat — Fast XML parsing using Expat

20.13.1. XMLParser Objects

20.13.2. ExpatError Exceptions

20.13.3. Exemple

20.13.4. Content Model Descriptions

20.13.5. Expat error constants

21. Gestion des protocoles internet

21.1. webbrowser — Convenient Web-browser controller

21.1.1. Browser Controller Objects

21.2. cgi — Common Gateway Interface support

21.2.1. Introduction

21.2.2. Using the cgi module

21.2.3. Higher Level Interface

21.2.4. Fonctions

21.2.5. Caring about security

21.2.6. Installing your CGI script on a Unix system

21.2.7. Testing your CGI script

21.2.8. Debugging CGI scripts

21.2.9. Common problems and solutions

21.3. cgitb — Gestionnaire d’exceptions pour les scripts CGI

21.4. wsgiref — Outils et implémentation de référence de WSGI

21.4.1. wsgiref.util — outils pour les environnements WSGI

21.4.2. wsgiref.headers – WSGI response header tools

21.4.3. wsgiref.simple_server – a simple WSGI HTTP server

21.4.4. wsgiref.validate — WSGI conformance checker

21.4.5. wsgiref.handlers – server/gateway base classes

21.4.6. Exemples

21.5. urllib — Modules de gestion des URLs

21.6. urllib.request — Extensible library for opening URLs

21.6.1. Request Objects

21.6.2. OpenerDirector Objects

21.6.3. BaseHandler Objects

21.6.4. HTTPRedirectHandler Objects

21.6.5. HTTPCookieProcessor Objects

21.6.6. ProxyHandler Objects

21.6.7. HTTPPasswordMgr Objects

21.6.8. HTTPPasswordMgrWithPriorAuth Objects

21.6.9. AbstractBasicAuthHandler Objects

21.6.10. HTTPBasicAuthHandler Objects

21.6.11. ProxyBasicAuthHandler Objects

21.6.12. AbstractDigestAuthHandler Objects

21.6.13. HTTPDigestAuthHandler Objects

21.6.14. ProxyDigestAuthHandler Objects

21.6.15. HTTPHandler Objects

21.6.16. HTTPSHandler Objects

21.6.17. FileHandler Objects

21.6.18. DataHandler Objects

21.6.19. FTPHandler Objects

21.6.20. CacheFTPHandler Objects

21.6.21. UnknownHandler Objects

21.6.22. HTTPErrorProcessor Objects

21.6.23. Exemples

21.6.24. Legacy interface

21.6.25. urllib.request Restrictions

21.7. urllib.response — Response classes used by urllib

21.8. urllib.parse — Parse URLs into components

21.8.1. URL Parsing

21.8.2. Parsing ASCII Encoded Bytes

21.8.3. Structured Parse Results

21.8.4. URL Quoting

21.9. urllib.error — Classes d’exceptions levées par urllib.request

21.10. urllib.robotparser — Analyseur de fichiers robots.txt

21.11. http — modules HTTP

21.11.1. Codes d’état HTTP

21.12. http.client — HTTP protocol client

21.12.1. HTTPConnection Objects

21.12.2. HTTPResponse Objects

21.12.3. Exemples

21.12.4. HTTPMessage Objects

21.13. ftplib — FTP protocol client

21.13.1. FTP Objects

21.13.2. FTP_TLS Objects

21.14. poplib — POP3 protocol client

21.14.1. POP3 Objects

21.14.2. POP3 Example

21.15. imaplib — IMAP4 protocol client

21.15.1. IMAP4 Objects

21.15.2. IMAP4 Example

21.16. nntplib — NNTP protocol client

21.16.1. NNTP Objects

21.16.1.1. Attributes

21.16.1.2. Méthodes

21.16.2. Fonctions utilitaires

21.17. smtplib — SMTP protocol client

21.17.1. SMTP Objects

21.17.2. SMTP Example

21.18. smtpd — SMTP Server

21.18.1. SMTPServer Objects

21.18.2. DebuggingServer Objects

21.18.3. PureProxy Objects

21.18.4. MailmanProxy Objects

21.18.5. SMTPChannel Objects

21.19. telnetlib — Telnet client

21.19.1. Telnet Objects

21.19.2. Telnet Example

21.20. uuid — UUID objects according to RFC 4122

21.20.1. Exemple

21.21. socketserver — A framework for network servers

21.21.1. Server Creation Notes

21.21.2. Objets Serveur

21.21.3. Request Handler Objects

21.21.4. Exemples

21.21.4.1. socketserver.TCPServer Example

21.21.4.2. socketserver.UDPServer Example

21.21.4.3. Asynchronous Mixins

21.22. http.server — HTTP servers

21.23. http.cookies — gestion d’état pour HTTP

21.23.1. Objets Cookie

21.23.2. Objets Morsel

21.23.3. Exemple

21.24. http.cookiejar — Cookie handling for HTTP clients

21.24.1. CookieJar and FileCookieJar Objects

21.24.2. FileCookieJar subclasses and co-operation with web browsers

21.24.3. CookiePolicy Objects

21.24.4. DefaultCookiePolicy Objects

21.24.5. Objets Cookie

21.24.6. Exemples

21.25. xmlrpc — Modules Serveur et Client XMLRPC

21.26. xmlrpc.client — XML-RPC client access

21.26.1. ServerProxy Objects

21.26.2. Objets DateTime

21.26.3. Binary Objects

21.26.4. Fault Objects

21.26.5. ProtocolError Objects

21.26.6. MultiCall Objects

21.26.7. Convenience Functions

21.26.8. Example of Client Usage

21.26.9. Example of Client and Server Usage

21.27. xmlrpc.server — Basic XML-RPC servers

21.27.1. SimpleXMLRPCServer Objects

21.27.1.1. SimpleXMLRPCServer Example

21.27.2. CGIXMLRPCRequestHandler

21.27.3. Documenting XMLRPC server

21.27.4. DocXMLRPCServer Objects

21.27.5. DocCGIXMLRPCRequestHandler

21.28. ipaddress — IPv4/IPv6 manipulation library

21.28.1. Convenience factory functions

21.28.2. IP Addresses

21.28.2.1. Address objects

21.28.2.2. Conversion to Strings and Integers

21.28.2.3. Opérateurs

21.28.2.3.1. Comparison operators

21.28.2.3.2. Arithmetic operators

21.28.3. IP Network definitions

21.28.3.1. Prefix, net mask and host mask

21.28.3.2. Network objects

21.28.3.3. Opérateurs

21.28.3.3.1. Logical operators

21.28.3.3.2. Itération

21.28.3.3.3. Networks as containers of addresses

21.28.4. Interface objects

21.28.4.1. Opérateurs

21.28.4.1.1. Logical operators

21.28.5. Other Module Level Functions

21.28.6. Custom Exceptions

22. Services multimédia

22.1. audioloop — Manipulation de données audio brutes

22.2. aifc — Lis et écrit dans les fichiers AIFF et AIFC

22.3. sunau — Read and write Sun AU files

22.3.1. AU_read Objects

22.3.2. AU_write Objects

22.4. wave — Lecture et écriture des fichiers WAV

22.4.1. Objets Wave_read

22.4.2. Objets Wave_write

22.5. chunk — Read IFF chunked data

22.6. colorsys — Conversions entre les systèmes de couleurs

22.7. imghdr — Determine the type of an image

22.8. sndhdr — Détermine le type d’un fichier audio

22.9. ossaudiodev — Access to OSS-compatible audio devices

22.9.1. Audio Device Objects

22.9.2. Mixer Device Objects

23. Internationalisation

23.1. gettext — Services d’internationalisation multilingue

23.1.1. API GNU gettext

23.1.2. API basée sur les classes

23.1.2.1. La classe NullTranslations

23.1.2.2. La classe GNUTranslations

23.1.2.3. Support du catalogue de message de Solaris

23.1.2.4. Le constructeur Catalog

23.1.3. Internationaliser vos programmes et modules

23.1.3.1. Localiser votre module

23.1.3.2. Localiser votre application

23.1.3.3. Changer de langue à la volée

23.1.3.4. Traductions différées

23.1.4. Remerciements

23.2. locale — Services d’internationalisation

23.2.1. Contexte, détails, conseils, astuces et mises en garde

23.2.2. Pour les auteurs d’extensions et les programmes qui intègrent Python

23.2.3. Accéder aux catalogues de messages

24. Frameworks d’applications

24.1. turtle — Tortue graphique

24.1.1. Introduction

24.1.2. Résumé des méthodes de Turtle et Screen

24.1.2.1. Les méthodes du module Turtle

24.1.2.2. Methods of TurtleScreen/Screen

24.1.3. Methods of RawTurtle/Turtle and corresponding functions

24.1.3.1. Les mouvements dans le module Turtle

24.1.3.2. Tell Turtle’s state

24.1.3.3. Settings for measurement

24.1.3.4. Pen control

24.1.3.4.1. Drawing state

24.1.3.4.2. Color control

24.1.3.4.3. Filling

24.1.3.4.4. More drawing control

24.1.3.5. Turtle state

24.1.3.5.1. Visibility

24.1.3.5.2. Appearance

24.1.3.6. Using events

24.1.3.7. Special Turtle methods

24.1.3.8. Compound shapes

24.1.4. Methods of TurtleScreen/Screen and corresponding functions

24.1.4.1. Window control

24.1.4.2. Animation control

24.1.4.3. Using screen events

24.1.4.4. Input methods

24.1.4.5. Settings and special methods

24.1.4.6. Methods specific to Screen, not inherited from TurtleScreen

24.1.5. Public classes

24.1.6. Help and configuration

24.1.6.1. How to use help

24.1.6.2. Translation of docstrings into different languages

24.1.6.3. How to configure Screen and Turtles

24.1.7. turtledemo — Demo scripts

24.1.8. Changes since Python 2.6

24.1.9. Changes since Python 3.0

24.2. cmd — Interpréteurs en ligne de commande.

24.2.1. Objets Cmd

24.2.2. Exemple

24.3. shlex — Simple lexical analysis

24.3.1. shlex Objects

24.3.2. Parsing Rules

24.3.3. Improved Compatibility with Shells

25. Interfaces Utilisateur Graphiques avec Tk

25.1. tkinter — Interface Python pour Tcl/Tk

25.1.1. Modules Tkinter

25.1.2. Guide de survie Tkinter

25.1.2.1. Mode d’emploi

25.1.2.2. Un simple programme Hello World

25.1.3. Un (très) rapide aperçu de Tcl/Tk

25.1.4. Correspondance entre Basic Tk et Tkinter

25.1.5. Relations entre Tk et Tkinter

25.1.6. Guide pratique

25.1.6.1. Définition des options

25.1.6.2. L’empaqueteur

25.1.6.3. Options de l’empaqueteur

25.1.6.4. Association des variables de l’objet graphique

25.1.6.5. Le gestionnaire de fenêtres

25.1.6.6. Types de données des options Tk

25.1.6.7. Liaisons et événements

25.1.6.8. Le paramètre index

25.1.6.9. Images

25.1.7. Gestionnaires de fichiers

25.2. tkinter.ttk — Tk themed widgets

25.2.1. Using Ttk

25.2.2. Ttk Widgets

25.2.3. Widget

25.2.3.1. Standard Options

25.2.3.2. Scrollable Widget Options

25.2.3.3. Label Options

25.2.3.4. Compatibility Options

25.2.3.5. Widget States

25.2.3.6. ttk.Widget

25.2.4. Combobox

25.2.4.1. Options

25.2.4.2. Virtual events

25.2.4.3. ttk.Combobox

25.2.5. Notebook

25.2.5.1. Options

25.2.5.2. Tab Options

25.2.5.3. Tab Identifiers

25.2.5.4. Virtual Events

25.2.5.5. ttk.Notebook

25.2.6. Progressbar

25.2.6.1. Options

25.2.6.2. ttk.Progressbar

25.2.7. Separator

25.2.7.1. Options

25.2.8. Sizegrip

25.2.8.1. Platform-specific notes

25.2.8.2. Bugs

25.2.9. Treeview

25.2.9.1. Options

25.2.9.2. Item Options

25.2.9.3. Tag Options

25.2.9.4. Column Identifiers

25.2.9.5. Virtual Events

25.2.9.6. ttk.Treeview

25.2.10. Ttk Styling

25.2.10.1. Layouts

25.3. tkinter.tix — Extension widgets for Tk

25.3.1. Using Tix

25.3.2. Tix Widgets

25.3.2.1. Basic Widgets

25.3.2.2. File Selectors

25.3.2.3. Hierarchical ListBox

25.3.2.4. Tabular ListBox

25.3.2.5. Manager Widgets

25.3.2.6. Image Types

25.3.2.7. Miscellaneous Widgets

25.3.2.8. Form Geometry Manager

25.3.3. Tix Commands

25.4. tkinter.scrolledtext — Gadget texte avec barre de défilement

25.5. IDLE

25.5.1. Menus

25.5.1.1. Menu File (Console et Éditeur)

25.5.1.2. Menu Edit (console et éditeur)

25.5.1.3. Menu Format (fenêtre d’édition uniquement)

25.5.1.4. Menu Run (fenêtre d’édition uniquement)

25.5.1.5. Menu Shell (fenêtre de console uniquement)

25.5.1.6. Menu Debug (fenêtre de console uniquement)

25.5.1.7. Menu Options (console et éditeur)

25.5.1.8. Menu Windows (console et éditeur)

25.5.1.9. Menu Help (console et éditeur)

25.5.1.10. Menus Contextuels

25.5.2. Édition et navigation

25.5.2.1. Editor windows

25.5.2.2. Key bindings

25.5.2.3. Indentation automatique

25.5.2.4. Complétions

25.5.2.5. Info-bulles

25.5.2.6. Fenêtre de console Python

25.5.2.7. Coloration du texte

25.5.3. Démarrage et exécution du code

25.5.3.1. Utilisation de la ligne de commande

25.5.3.2. Échec au démarrage

25.5.3.3. Running user code

25.5.3.4. User output in Shell

25.5.3.5. Développer des applications tkinter

25.5.3.6. Exécution sans sous-processus

25.5.4. Aide et préférences

25.5.4.1. Help sources

25.5.4.2. Modifier les préférences

25.5.4.3. IDLE on macOS

25.5.4.4. Extensions

25.6. Autres paquets d’interface graphique utilisateur

26. Outils de développement

26.1. typing — Support for type hints

26.1.1. Type aliases

26.1.2. NewType

26.1.3. Callable

26.1.4. Generics

26.1.5. User-defined generic types

26.1.6. The Any type

26.1.7. Classes, functions, and decorators

26.2. pydoc — Générateur de documentation et système d’aide en ligne

26.3. doctest — Test interactive Python examples

26.3.1. Simple Usage: Checking Examples in Docstrings

26.3.2. Simple Usage: Checking Examples in a Text File

26.3.3. How It Works

26.3.3.1. Which Docstrings Are Examined?

26.3.3.2. How are Docstring Examples Recognized?

26.3.3.3. What’s the Execution Context?

26.3.3.4. What About Exceptions?

26.3.3.5. Option Flags

26.3.3.6. Directives

26.3.3.7. Avertissements

26.3.4. Basic API

26.3.5. Unittest API

26.3.6. Advanced API

26.3.6.1. DocTest Objects

26.3.6.2. Example Objects

26.3.6.3. DocTestFinder objects

26.3.6.4. DocTestParser objects

26.3.6.5. DocTestRunner objects

26.3.6.6. OutputChecker objects

26.3.7. Debugging

26.3.8. Soapbox

26.4. unittest — Framework de tests unitaires

26.4.1. Exemple basique

26.4.2. Interface en ligne de commande

26.4.2.1. Options de la ligne de commande

26.4.3. Découverte des tests

26.4.4. Organiser le code de test

26.4.5. Réutilisation d’ancien code de test

26.4.6. Ignorer des tests et des erreurs prévisibles

26.4.7. Distinguer les itérations de test à l’aide de sous-tests

26.4.8. Classes et fonctions

26.4.8.1. Scénarios de tests

26.4.8.1.1. Alias obsolètes

26.4.8.2. Regroupement des tests

26.4.8.3. Chargement et exécution des tests

26.4.8.3.1. Protocole de chargement des tests (load_tests Protocol)

26.4.9. Classes et modules d’aménagements des tests

26.4.9.1. Classes de mise en place (setUpClass) et de démantèlement des tests (tearDownClass)

26.4.9.2. Module de mise en place (setUpModule) et de démantèlement des tests (tearDownModule)

26.4.10. Traitement des signaux

26.5. unittest.mock — Bibliothèque d’objets simulacres

26.5.1. Guide rapide

26.5.2. La classe Mock

26.5.2.1. Calling

26.5.2.2. Deleting Attributes

26.5.2.3. Mock names and the name attribute

26.5.2.4. Attaching Mocks as Attributes

26.5.3. The patchers

26.5.3.1. patch

26.5.3.2. patch.object

26.5.3.3. patch.dict

26.5.3.4. patch.multiple

26.5.3.5. patch methods: start and stop

26.5.3.6. patch builtins

26.5.3.7. TEST_PREFIX

26.5.3.8. Nesting Patch Decorators

26.5.3.9. Where to patch

26.5.3.10. Patching Descriptors and Proxy Objects

26.5.4. MagicMock and magic method support

26.5.4.1. Mocking Magic Methods

26.5.4.2. Magic Mock

26.5.5. Helpers

26.5.5.1. sentinel

26.5.5.2. DEFAULT

26.5.5.3. call

26.5.5.4. create_autospec

26.5.5.5. ANY

26.5.5.6. FILTER_DIR

26.5.5.7. mock_open

26.5.5.8. Autospeccing

26.6. unittest.mock — getting started

26.6.1. Utilisation de Mock ou l’art de singer

26.6.1.1. Simulation des méthodes

26.6.1.2. S’assurer de la bonne utilisation d’un objet

26.6.1.3. Simulation des classes

26.6.1.4. Naming your mocks

26.6.1.5. Tracking all Calls

26.6.1.6. Setting Return Values and Attributes

26.6.1.7. Raising exceptions with mocks

26.6.1.8. Side effect functions and iterables

26.6.1.9. Creating a Mock from an Existing Object

26.6.2. Patch Decorators

26.6.3. Further Examples

26.6.3.1. Mocking chained calls

26.6.3.2. Partial mocking

26.6.3.3. Mocking a Generator Method

26.6.3.4. Applying the same patch to every test method

26.6.3.5. Mocking Unbound Methods

26.6.3.6. Checking multiple calls with mock

26.6.3.7. Coping with mutable arguments

26.6.3.8. Nesting Patches

26.6.3.9. Mocking a dictionary with MagicMock

26.6.3.10. Mock subclasses and their attributes

26.6.3.11. Mocking imports with patch.dict

26.6.3.12. Tracking order of calls and less verbose call assertions

26.6.3.13. More complex argument matching

26.7. 2to3 — Traduction automatique de code en Python 2 vers Python 3

26.7.1. Utilisation de 2to3

26.7.2. Correcteurs

26.7.3. lib2to3 — la bibliothèque de 2to3

26.8. test — Regression tests package for Python

26.8.1. Writing Unit Tests for the test package

26.8.2. Running tests using the command-line interface

26.9. test.support — Utilities for the Python test suite

27. Débogueur et instrumentation

27.1. bdb — Framework de débogage

27.2. faulthandler — Dump the Python traceback

27.2.1. Dumping the traceback

27.2.2. Fault handler state

27.2.3. Dumping the tracebacks after a timeout

27.2.4. Dumping the traceback on a user signal

27.2.5. Issue with file descriptors

27.2.6. Exemple

27.3. pdb — Le débogueur Python

27.3.1. Commande du débogueur

27.4. The Python Profilers

27.4.1. Introduction to the profilers

27.4.2. Instant User’s Manual

27.4.3. profile and cProfile Module Reference

27.4.4. The Stats Class

27.4.5. What Is Deterministic Profiling?

27.4.6. Limitations

27.4.7. Calibration

27.4.8. Using a custom timer

27.5. timeit — Mesurer le temps d’exécution de fragments de code

27.5.1. Exemples simples

27.5.2. Interface Python

27.5.3. Interface en ligne de commande

27.5.4. Exemples

27.6. trace — Trace or track Python statement execution

27.6.1. Utilisation en ligne de commande.

27.6.1.1. Main options

27.6.1.2. Modifiers

27.6.1.3. Filters

27.6.2. Programmatic Interface

27.7. tracemalloc — Trace memory allocations

27.7.1. Exemples

27.7.1.1. Display the top 10

27.7.1.2. Compute differences

27.7.1.3. Get the traceback of a memory block

27.7.1.4. Pretty top

27.7.2. API

27.7.2.1. Fonctions

27.7.2.2. DomainFilter

27.7.2.3. Filter

27.7.2.4. Frame

27.7.2.5. Snapshot

27.7.2.6. Statistic

27.7.2.7. StatisticDiff

27.7.2.8. Trace

27.7.2.9. Traceback

28. Paquets et distribution de paquets logiciels

28.1. distutils — Création et installation des modules Python

28.2. ensurepip — Bootstrapping the pip installer

28.2.1. Command line interface

28.2.2. Module API

28.3. venv — Création d’environnements virtuels

28.3.1. Création d’environnements virtuels

28.3.2. API

28.3.3. Un exemple d’extension de EnvBuilder

28.4. zipapp — Manage executable python zip archives

28.4.1. Exemple de base

28.4.2. Interface en ligne de commande

28.4.3. API Python

28.4.4. Exemples

28.4.5. Spécification de l’interprète

28.4.6. Création d’applications autonomes avec zipapp

28.4.6.1. Création d’un exécutable Windows

28.4.6.2. Mises en garde

28.4.7. Le format d’archive d’application Zip Python

29. Environnement d’exécution Python

29.1. sys — Paramètres et fonctions propres à des systèmes

29.2. sysconfig — Provide access to Python’s configuration information

29.2.1. Configuration variables

29.2.2. Installation paths

29.2.3. Autres fonctions

29.2.4. Using sysconfig as a script

29.3. builtins — Objets natifs

29.4. __main__ — Point d’entrée des scripts

29.5. warnings — Contrôle des alertes

29.5.1. Catégories d’avertissement

29.5.2. Le filtre des avertissements

29.5.2.1. Default Warning Filters

29.5.3. Suppression temporaire des avertissements

29.5.4. Tester les avertissements

29.5.5. Updating Code For New Versions of Python

29.5.6. Fonctions disponibles

29.5.7. Gestionnaires de contexte disponibles

29.6. contextlib — Utilities for with-statement contexts

29.6.1. Utilitaires

29.6.2. Exemples et Recettes

29.6.2.1. Gérer un nombre variable de gestionnaires de contexte

29.6.2.2. Simplifying support for single optional context managers

29.6.2.3. Attraper des exceptions depuis les méthodes __enter__

29.6.2.4. Nettoyer dans une méthode __enter__

29.6.2.5. Remplacer un try-finally avec une option variable

29.6.2.6. Utiliser un gestionnaire de contexte en tant que décorateur de fonction

29.6.3. Gestionnaires de contexte à usage unique, réutilisables et réentrants

29.6.3.1. Gestionnaires de contexte réentrants

29.6.3.2. Gestionnaires de contexte réutilisables

29.7. abc — Classes de Base Abstraites

29.8. atexit — Gestionnaire de fin de programme

29.8.1. Exemple avec atexit

29.9. traceback — Print or retrieve a stack traceback

29.9.1. TracebackException Objects

29.9.2. StackSummary Objects

29.9.3. FrameSummary Objects

29.9.4. Traceback Examples

29.10. __future__ — Définitions des futurs

29.11. gc — Garbage Collector interface

29.12. inspect — Inspect live objects

29.12.1. Types and members

29.12.2. Retrieving source code

29.12.3. Introspecting callables with the Signature object

29.12.4. Classes et fonctions

29.12.5. The interpreter stack

29.12.6. Fetching attributes statically

29.12.7. Current State of Generators and Coroutines

29.12.8. Code Objects Bit Flags

29.12.9. Interface en ligne de commande

29.13. site — Site-specific configuration hook

29.13.1. Readline configuration

29.13.2. Module contents

29.14. fpectl — Floating point exception control

29.14.1. Exemple

29.14.2. Limitations and other considerations

30. Interpréteurs Python personnalisés

30.1. code — Interpreter base classes

30.1.1. Interactive Interpreter Objects

30.1.2. Interactive Console Objects

30.2. codeop — Compilation de code Python

31. Importer des modules

31.1. zipimport — Importer des modules à partir d’archives Zip

31.1.1. Objets zimporter

31.1.2. Exemples

31.2. pkgutil — Package extension utility

31.3. modulefinder — Identifie les modules utilisés par un script

31.3.1. Exemples d’utilisation de la classe ModuleFinder

31.4. runpy — Locating and executing Python modules

31.5. importlib — The implementation of import

31.5.1. Introduction

31.5.2. Fonctions

31.5.3. importlib.abc – Abstract base classes related to import

31.5.4. importlib.machinery – Importers and path hooks

31.5.5. importlib.util – Utility code for importers

31.5.6. Exemples

31.5.6.1. Importing programmatically

31.5.6.2. Checking if a module can be imported

31.5.6.3. Importing a source file directly

31.5.6.4. Setting up an importer

31.5.6.5. Approximating importlib.import_module()

32. Services du Langage Python

32.1. parser — Accès aux arbres syntaxiques

32.1.1. Creating ST Objects

32.1.2. Converting ST Objects

32.1.3. Queries on ST Objects

32.1.4. Exceptions and Error Handling

32.1.5. ST Objects

32.1.6. Example: Emulation of compile()

32.2. ast — Arbres Syntaxiques Abstraits

32.2.1. Les classes nœud

32.2.2. Grammaire abstraite

32.2.3. Outils du module ast

32.3. symtable — Access to the compiler’s symbol tables

32.3.1. Generating Symbol Tables

32.3.2. Examining Symbol Tables

32.4. symbol — Constantes utilisées dans les Arbres Syntaxiques

32.5. token — Constantes utilisées avec les arbres d’analyse Python (parse trees)

32.6. keyword — Tester si des chaînes sont des mot-clés Python

32.7. tokenize — Analyseur lexical de Python

32.7.1. Analyse Lexicale

32.7.2. Utilisation en ligne de commande.

32.7.3. Exemples

32.8. tabnanny — Détection d’indentation ambiguë

32.9. pyclbr — Python class browser support

32.9.1. Objets classes

32.9.2. Objets fonctions

32.10. py_compile — Compile Python source files

32.11. compileall — Byte-compile Python libraries

32.11.1. Command-line use

32.11.2. Public functions

32.12. dis – Désassembleur pour le code intermédiaire de Python

32.12.1. Analyse du code intermédiaire

32.12.2. Analyse de fonctions

32.12.3. Les instructions du code intermédiaire en Python

32.12.4. Opcode collections

32.13. pickletools — Tools for pickle developers

32.13.1. Utilisation de la ligne de commande

32.13.1.1. Options de la ligne de commande

32.13.2. Programmatic Interface

33. Services divers

33.1. formatter — Generic output formatting

33.1.1. The Formatter Interface

33.1.2. Formatter Implementations

33.1.3. The Writer Interface

33.1.4. Writer Implementations

34. Services spécifiques à MS Windows

34.1. msilib — Read and write Microsoft Installer files

34.1.1. Database Objects

34.1.2. View Objects

34.1.3. Summary Information Objects

34.1.4. Record Objects

34.1.5. Errors

34.1.6. CAB Objects

34.1.7. Directory Objects

34.1.8. Features

34.1.9. GUI classes

34.1.10. Precomputed tables

34.2. msvcrt — Useful routines from the MS VC++ runtime

34.2.1. File Operations

34.2.2. Console I/O

34.2.3. Other Functions

34.3. winreg — Windows registry access

34.3.1. Fonctions

34.3.2. Constantes

34.3.2.1. HKEY_* Constants

34.3.2.2. Access Rights

34.3.2.2.1. 64-bit Specific

34.3.2.3. Value Types

34.3.3. Registry Handle Objects

34.4. winsound — Sound-playing interface for Windows

35. Services spécifiques à Unix

35.1. posix — Les appels système POSIX les plus courants

35.1.1. Prise en charge de gros fichiers

35.1.2. Contenu du Module

35.2. pwd — The password database

35.3. spwd — La base de données de mots de passe shadow

35.4. grp — The group database

35.5. crypt — Function to check Unix passwords

35.5.1. Hashing Methods

35.5.2. Module Attributes

35.5.3. Module Functions

35.5.4. Exemples

35.6. termios — Le style POSIX le contrôle TTY

35.6.1. Exemple

35.7. tty — Fonctions de gestion du terminal

35.8. pty — Outils de manipulation de pseudo-terminaux

35.8.1. Exemple

35.9. fcntl — The fcntl and ioctl system calls

35.10. pipes — Interface au pipelines shell

35.10.1. L’Objet Template

35.11. resource — Resource usage information

35.11.1. Resource Limits

35.11.2. Resource Usage

35.12. nis — Interface à Sun’s NIS (pages jaunes)

35.13. syslog — Unix syslog library routines

35.13.1. Exemples

35.13.1.1. Simple example

36. Modules remplacés

36.1. optparse — Parser for command line options

36.1.1. Background

36.1.1.1. Terminology

36.1.1.2. What are options for?

36.1.1.3. What are positional arguments for?

36.1.2. Tutoriel

36.1.2.1. Understanding option actions

36.1.2.2. The store action

36.1.2.3. Handling boolean (flag) options

36.1.2.4. Other actions

36.1.2.5. Valeurs par défaut

36.1.2.6. Generating help

36.1.2.6.1. Grouping Options

36.1.2.7. Printing a version string

36.1.2.8. How optparse handles errors

36.1.2.9. Putting it all together

36.1.3. Reference Guide

36.1.3.1. Creating the parser

36.1.3.2. Populating the parser

36.1.3.3. Defining options

36.1.3.4. Option attributes

36.1.3.5. Standard option actions

36.1.3.6. Standard option types

36.1.3.7. Analyse des arguments

36.1.3.8. Querying and manipulating your option parser

36.1.3.9. Conflicts between options

36.1.3.10. Nettoyage

36.1.3.11. Other methods

36.1.4. Option Callbacks

36.1.4.1. Defining a callback option

36.1.4.2. How callbacks are called

36.1.4.3. Raising errors in a callback

36.1.4.4. Callback example 1: trivial callback

36.1.4.5. Callback example 2: check option order

36.1.4.6. Callback example 3: check option order (generalized)

36.1.4.7. Callback example 4: check arbitrary condition

36.1.4.8. Callback example 5: fixed arguments

36.1.4.9. Callback example 6: variable arguments

36.1.5. Extending optparse

36.1.5.1. Adding new types

36.1.5.2. Adding new actions

36.2. imp — Access the import internals

36.2.1. Exemples

37. Modules non Documentés

37.1. Modules spécifiques à une plateforme

Extension et intégration de l’interpréteur Python

Les outils tiers recommandés

Création d’extensions sans outils tiers

1. Étendre Python en C ou C++

1.1. Un exemple simple

1.2. Intermezzo: Les erreurs et exceptions

1.3. Retour vers l’exemple

1.4. La fonction d’initialisation et le tableau des méthodes du module

1.5. Compilation and Linkage

1.6. Calling Python Functions from C

1.7. Extracting Parameters in Extension Functions

1.8. Keyword Parameters for Extension Functions

1.9. Building Arbitrary Values

1.10. Reference Counts

1.10.1. Reference Counting in Python

1.10.2. Ownership Rules

1.10.3. Thin Ice

1.10.4. NULL Pointers

1.11. Writing Extensions in C++

1.12. Providing a C API for an Extension Module

2. Defining Extension Types: Tutorial

2.1. The Basics

2.2. Adding data and methods to the Basic example

2.3. Providing finer control over data attributes

2.4. Supporting cyclic garbage collection

2.5. Subclassing other types

3. Defining Extension Types: Assorted Topics

3.1. Finalization and De-allocation

3.2. Object Presentation

3.3. Attribute Management

3.3.1. Generic Attribute Management

3.3.2. Type-specific Attribute Management

3.4. Object Comparison

3.5. Abstract Protocol Support

3.6. Weak Reference Support

3.7. More Suggestions

4. Construire des extensions C et C++

4.1. Construire les extensions C et C++ avec distutils

4.2. Distribuer vos modules d’extension

5. Construire des extensions C et C++ sur Windows

5.1. Une approche « recette de cuisine »

5.2. Différences entre Unix et Windows

5.3. Utiliser les DLL en pratique

Intégrer l’interpréteur CPython dans une plus grande application

1. Intégrer Python dans une autre application

1.1. Intégration de très haut niveau

1.2. Au-delà de l’intégration de haut niveau : survol

1.3. Intégration pure

1.4. Étendre un Python intégré

1.5. Intégrer Python dans du C++

1.6. Compiler et Lier en environnement Unix ou similaire

Manuel de référence de l’API Python/C

Introduction

Include Files

Objects, Types and Reference Counts

Reference Counts

Reference Count Details

Types

Exceptions

Embarquer Python

Debugging Builds

ABI Stable

The Very High Level Layer

Reference Counting

Gestion des exceptions

Printing and clearing

Lever des exceptions

Issuing warnings

Querying the error indicator

Traitement des signaux

Exception Classes

Objets exception

Objets exception Unicode

Contrôle de la récursion

Exceptions standards

Standard Warning Categories

Utilitaires

Operating System Utilities

System Functions

Process Control

Importer des modules

Data marshalling support

Analyse des arguments et construction des valeurs

Analyse des arguments

Chaînes et tampons

Les nombres

Autres objets

Fonction de l’API

Construction des valeurs

Conversion et formatage de chaînes

Réflexion

Codec registry and support functions

Codec lookup API

Registry API for Unicode encoding error handlers

Couche d’abstraction des objets

Protocole Objet

Number Protocol

Sequence Protocol

Mapping Protocol

Protocole d’itération

Protocole tampon

La structure buffer

Buffer request types

request-independent fields

readonly, format

shape, strides, suboffsets

contiguity requests

compound requests

Complex arrays

NumPy-style: shape and strides

PIL-style: shape, strides and suboffsets

Fonctions relatives aux tampons

Ancien Buffer Protocol

Couche des objets concrets

Objets fondamentaux

Objets type

L’objet None

Objets numériques

Objets Integer

Les objets booléens

Objets représentant les nombres à virgule flottante

Objets nombres complexes

Nombres complexes en tant que structures C

Nombres complexes en tant qu’objets Python

Objets séquences

Objets bytes

Objets tableau d’octets

Macros de vérification de type

Fonctions directes sur l’API

Macros

Unicode Objects and Codecs

Unicode Objects

Unicode Type

Unicode Character Properties

Creating and accessing Unicode strings

Deprecated Py_UNICODE APIs

Locale Encoding

File System Encoding

wchar_t Support

Built-in Codecs

Generic Codecs

UTF-8 Codecs

UTF-32 Codecs

UTF-16 Codecs

UTF-7 Codecs

Unicode-Escape Codecs

Raw-Unicode-Escape Codecs

Latin-1 Codecs

ASCII Codecs

Character Map Codecs

MBCS codecs for Windows

Methods & Slots

Methods and Slot Functions

Tuple Objects

Struct Sequence Objects

List Objects

Objets conteneurs

Objets dictionnaires

Set Objects

Objets fonctions

Objets fonctions

Instance Method Objects

Objets méthode

Objets Cellules

Objets code

Autres objets

Objets fichiers

Module Objects

Initializing C modules

Single-phase initialization

Multi-phase initialization

Low-level module creation functions

Support functions

Module lookup

Itérateurs

Les descripteurs

Slice Objects

Ellipsis Object

Objets de type MemoryView

Objets à références faibles

Capsules

Objets générateur

Objets coroutines

Objets DateTime

Initialization, Finalization, and Threads

Initializing and finalizing the interpreter

Process-wide parameters

Thread State and the Global Interpreter Lock

Releasing the GIL from extension code

Non-Python created threads

High-level API

Low-level API

Sub-interpreter support

Bugs and caveats

Asynchronous Notifications

Profiling and Tracing

Support avancé du débogueur

Memory Management

Aperçu

Raw Memory Interface

Memory Interface

Object allocators

Customize Memory Allocators

The pymalloc allocator

Customize pymalloc Arena Allocator

Exemples

Implémentation d’objets

Allouer des objets dans le tas

Common Object Structures

Objets type

Number Object Structures

Mapping Object Structures

Sequence Object Structures

Buffer Object Structures

Async Object Structures

Supporting Cyclic Garbage Collection

Version des API et ABI

Distribuer des modules Python

Vocabulaire

Licence libre et collaboration

Installer les outils

Lire le manuel

Comment puis-je …?

… choisir un nom pour mon projet ?

… créer et distribuer des extensions binaires ?

Installation de modules Python

Vocabulaire

Utilisation de base

Comment puis-je … ?

… Installer pip avec une version de Python antérieures à la 3.4 ?

… Installer des paquets juste pour l’utilisateur actuel ?

… Installer des paquets Python scientifiques ?

… Travailler avec plusieurs versions de Python installés en parallèle ?

Les problèmes d’installation typiques

Installer dans le Python du système sur Linux

Pip n’est pas installé

Installation d’extensions binaires

Les HOWTOs de Python

Portage de code Python 2 vers Python 3

La version courte

Détails

Abandon de la compatibilité Python 2.6 et antérieures

Assurez vous de spécifier la bonne version supportée dans le fichier setup.py

Obtenir une bonne couverture de code

Apprendre les différences entre Python 2 et 3

Mettre à jour votre code

Division

Texte et données binaires

Utilisez la détection de fonctionnalités plutôt que la détection de version

Prévenir les régressions de compatibilité

Vérifier quelles dépendances empêchent la migration

Mettre à jour votre fichier setup.py pour spécifier la compatibilité avec Python 3

Utiliser l’intégration continue pour maintenir la compatibilité

Envisager l’utilisation d’un vérificateur de type statique optionnel

Portage des modules d’extension vers Python 3

Compilation conditionnelle

Modifications apportées aux API des objets

Unification de str et unicode

Unification de long et int

Initialisation et état du module

CObject remplacé par Capsule

Autres options

Curses Programming with Python

What is curses?

The Python curses module

Starting and ending a curses application

Windows and Pads

Displaying Text

Attributes and Color

User Input

For More Information

Guide pour l’utilisation des descripteurs

Résumé

Définition et introduction

Protocole descripteur

Invocation des descripteurs

Exemple de descripteur

Propriétés

Fonctions et méthodes

Méthodes statiques et méthodes de classe

Guide pratique : programmation fonctionnelle

Introduction

Preuves formelles

Modularité

Facilité de débogage et de test

Composabilité

Itérateurs

Types de données itérables

Expressions génératrices et compréhension de listes

Générateurs

Transmettre des valeurs au générateur

Fonctions natives

Le module itertools

Créer de nouveaux itérateurs

Appliquer des fonctions au contenu des itérateurs

Sélectionner des éléments

Fonctions combinatoires

Grouper les éléments

Le module functools

Le module operator

Expressions lambda et fonctions courtes

Historique des modifications et remerciements

Références

Général

Spécifique à Python

Documentation Python

Tutoriel sur la journalisation

Les bases de l’utilisation du module logging

Quand utiliser logging

Un exemple simple

Enregistrer les évènements dans un fichier

Employer logging à partir de différents modules

Journalisation de données variables

Modifier le format du message affiché

Afficher l’horodatage dans les messages

Étapes suivantes

Usage avancé de Logging

Flux du processus de journalisation

Loggers

Handlers

Formatters

Configuration de Logging

Comportement par défaut (si aucune configuration n’est fournie)

Configuration de la journalisation pour une bibliothèque

Niveaux de journalisation

Niveaux personnalisés

Gestionnaires utiles

Exceptions levées par la journalisation

Utilisation d’objets arbitraires comme messages

Optimisation

Logging Cookbook

Using logging in multiple modules

Logging from multiple threads

Multiple handlers and formatters

Logging to multiple destinations

Configuration server example

Dealing with handlers that block

Sending and receiving logging events across a network

Adding contextual information to your logging output

Using LoggerAdapters to impart contextual information

Using objects other than dicts to pass contextual information

Using Filters to impart contextual information

Logging to a single file from multiple processes

Using file rotation

Use of alternative formatting styles

Customizing LogRecord

Subclassing QueueHandler - a ZeroMQ example

Subclassing QueueListener - a ZeroMQ example

An example dictionary-based configuration

Using a rotator and namer to customize log rotation processing

A more elaborate multiprocessing example

Inserting a BOM into messages sent to a SysLogHandler

Implementing structured logging

Customizing handlers with dictConfig()

Using particular formatting styles throughout your application

Using LogRecord factories

Using custom message objects

Configuring filters with dictConfig()

Customized exception formatting

Speaking logging messages

Buffering logging messages and outputting them conditionally

Formatting times using UTC (GMT) via configuration

Using a context manager for selective logging

Guide des expressions régulières

Introduction

Motifs simples

Correspondance de caractères

Répétitions

Utilisation des expressions régulières

Compilation des expressions régulières

La maudite barre oblique inverse

Recherche de correspondances

Fonctions de niveau module

Options de compilation

Des motifs plus puissants

Plus de métacaractères

Regroupement

Groupes non de capture et groupes nommés

Assertions prédictives

Modification de chaînes

Découpage de chaînes

Recherche et substitution

Problèmes classiques

Utilisez les méthodes du type string

match() contre search()

Glouton contre non-glouton

Utilisez re.VERBOSE

Vos commentaires

Socket Programming HOWTO

Interfaces de connexion (sockets)

Historique

Créer un connecteur

Communication Entre Processus

Using a Socket

Données binaires

Déconnexion

When Sockets Die

Non-blocking Sockets

Guide pour le tri

Les bases du tri

Fonctions clef

Fonctions du module operator

Ascendant et descendant

Stabilité des tris et tris complexes

La méthode traditionnelle utilisant Decorate-Sort-Undecorate

La méthode traditionnelle d’utiliser le paramètre cmp

Curiosités et conclusion

Guide Unicode

Introduction à Unicode

Histoire des codes de caractères

Définitions

Encodages

Références

Prise en charge Unicode de Python

Le type String

Conversion en octets

Littéraux Unicode dans le code source Python

Propriétés Unicode

Expressions régulières Unicode

Références

Lecture et écriture de données Unicode

Noms de fichiers Unicode

Conseils pour écrire des programmes compatibles Unicode

Conversion entre les encodages de fichiers

Fichiers dans un encodage inconnu

Références

Remerciements

HOWTO Fetch Internet Resources Using The urllib Package

Introduction

Fetching URLs

Data

Headers

Gestion des exceptions

URLError

HTTPError

Error Codes

Wrapping it Up

Number 1

Number 2

info and geturl

Openers and Handlers

Basic Authentication

Proxies

Sockets and Layers

Notes

Tutoriel argparse

Concepts

Les bases

Introduction aux arguments positionnels

Introduction aux arguments optionnels

Les paramètres raccourcis

Combinaison d’arguments positionnels et optionnels

Aller un peu plus loin

Paramètres en conflit

Conclusion

Introduction au module ipaddress

Créer un objet Adresse/Réseau/Interface

Note sur les versions d’IP

Adresses IP des hôtes

Définir des réseaux

Interfaces des hôtes

Inspecter les objets Address/Network/Interface

Réseaux en tant que listes d’adresses

Comparaisons

Utiliser des adresse IP avec d’autre modules

Obtenir plus de détails lors de l’échec de la création de l’instance

Argument Clinic How-To

Les objectifs d’Argument Clinic

Concepts de base et utilisation

Convertissez votre première fonction

Sujets avancés

Valeurs par défaut

Renaming the C functions and variables generated by Argument Clinic

Conversion des fonctions en utilisant PyArg_UnpackTuple

Groupes optionnels

Using real Argument Clinic converters, instead of « legacy converters »

Py_buffer

Advanced converters

Parameter default values

The NULL default value

Expressions specified as default values

Using a return converter

Cloning existing functions

Calling Python code

Using a « self converter »

Writing a custom converter

Writing a custom return converter

METH_O and METH_NOARGS

tp_new and tp_init functions

Changing and redirecting Clinic’s output

The #ifdef trick

Using Argument Clinic in Python files

Instrumenter CPython avec DTrace et SystemTap

Activer les marqueurs statiques

Sondes DTrace statiques

Marqueurs statiques SystemTap

Marqueurs statiques disponibles

Tapsets de SystemTap

Exemples

Questions fréquemment posées sur Python

FAQ générale sur Python

Informations générales

Python c’est le monde réel

FAQ de programmation

Questions générales

Fondamentaux

Nombres et chaînes de caractères

Performances

Séquences (n-uplets / listes)

Dictionnaires

Objets

Modules

FAQ histoire et design

Pourquoi Python utilise-t-il l’indentation pour grouper les instructions ?

Pourquoi ai-je d’étranges résultats suite à de simples opérations arithmétiques ?

Pourquoi les calculs à virgules flottantes sont si imprécis ?

Pourquoi les chaînes de caractères Python sont-elles immuables ?

Pourquoi « self » doit-il être explicitement utilisé dans les définitions et les appels de méthode ?

Pourquoi ne puis-je pas utiliser d’assignation dans une expression ?

Pourquoi Python utilise des méthodes pour certaines fonctionnalités (ex : list.index()) mais des fonctions pour d’autres (ex : len(list)) ?

Pourquoi join() est une méthode de chaîne plutôt qu’une de liste ou de tuple ?

À quel point les exceptions sont-elles rapides ?

Pourquoi n’y a-t-il pas une instruction switch ou une structure similaire à switch / case en Python ?

Est-il possible d’émuler des fils d’exécution dans l’interpréteur plutôt que se baser sur les implémentations spécifique aux OS ?

Pourquoi les expressions lambda ne peuvent pas contenir d’instructions ?

Python peut-il être compilé en code machine, en C ou dans un autre langage ?

Comment Python gère la mémoire ?

Pourquoi CPython n’utilise-il pas un ramasse-miette plus traditionnel ?

Pourquoi toute la mémoire n’est pas libérée lorsque CPython s’arrête ?

Pourquoi les tuples et les list sont deux types de données séparés ?

How are lists implemented in CPython?

How are dictionaries implemented in CPython?

Pourquoi les clés du dictionnaire sont immuables ?

Pourquoi list.sort() ne renvoie pas la liste triée ?

Comment spécifiez-vous et appliquez-vous une spécification d’interface en Python ?

Pourquoi n’y a-t-il pas de goto en Python ?

Pourquoi les chaînes de caractères brutes (r-strings) ne peuvent-elles pas se terminer par un backslash ?

Pourquoi la déclaration with pour les assignations d’attributs n’existe pas en Python ?

Pourquoi les deux-points sont-ils nécessaires pour les déclarations if/while/def/class ?

Pourquoi Python permet-il les virgules à la fin des listes et des tuples ?

FAQ sur la bibliothèque et les extensions

Questions générales sur la bibliothèque

Tâches fréquentes

Fils d’exécution

Les entrées/sorties

Programmation réseau et Internet

Bases de données

Mathématiques et calcul numérique

FAQ extension/intégration

Puis-je créer mes propres fonctions en C ?

Puis-je créer mes propres fonctions en C++ ?

Écrire directement en C est difficile ; existe-t-il des alternatives ?

Comment puis-je exécuter des instructions quelconques Python à partir de C ?

Comment puis-je évaluer une expression quelconque de Python à partir de C ?

Comment puis-je extraire des donnés en C d’un objet Python ?

Comment utiliser Py_BuildValue() pour créer un tuple de longueur définie ?

Comment puis-je appeler la méthode d’un objet à partir de C ?

Comment puis-je récupérer la sortie de PyErr_Print() (ou tout ce qui s’affiche sur stdout/stderr) ?

Comment accéder à un module écrit en Python à partir de C ?

Comment s’interfacer avec les objets C++ depuis Python ?

J’ai ajouté un module en utilisant le fichier Setup et la compilation échoue ; pourquoi ?

Comment déboguer une extension ?

Je veux compiler un module Python sur mon système Linux, mais il manque certains fichiers. Pourquoi ?

Comment distinguer une « entrée incomplète » (incomplete input) d’une « entrée invalide » (invalid input) ?

Comment puis-je trouver les symboles g++ indéfinis __builtin_new ou __pure_virtual ?

Puis-je créer une classe d’objets avec certaines méthodes implémentées en C et d’autres en Python (p. ex. en utilisant l’héritage) ?

FAQ : Python et Windows

Comment exécuter un programme Python sous Windows ?

Comment rendre des scripts Python exécutables ?

Pourquoi Python met-il du temps à démarrer ?

Comment construire un exécutable depuis un script Python ?

Est-ce qu’un fichier *.pyd est la même chose qu’une DLL ?

Comment puis-je intégrer Python dans une application Windows ?

Comment empêcher mon éditeur d’utiliser des tabulations dans mes fichiers Python ?

Comment puis-je vérifier de manière non bloquante qu’une touche a été pressée ?

FAQ interface graphique

Questions générales sur l’interface graphique

Quelles bibliothèques d’interfaces graphiques multi-plateformes existent en Python ?

Quelles boîtes à outils IUG spécifiques à la plate-forme existent pour Python ?

Questions à propos de Tkinter

FAQ « Pourquoi Python est installé sur mon ordinateur ? »

Qu’est-ce que Python ?

Pourquoi Python est installé sur ma machine ?

Puis-je supprimer Python ?

Glossaire

À propos de ces documents

Contributeurs de la documentation Python

S’attaquer aux bogues

Bogues de documentation

Utilisation du gestionnaire de tickets Python

Commencer à contribuer à Python vous-même

Copyright

Histoire et licence

Histoire du logiciel

Conditions générales pour accéder à, ou utiliser, Python

PSF LICENSE AGREEMENT FOR PYTHON 3.6.11

LICENCE D’UTILISATION BEOPEN.COM POUR PYTHON 2.0

LICENCE D’UTILISATION CNRI POUR PYTHON 1.6.1

LICENCE D’UTILISATION CWI POUR PYTHON 0.9.0 à 1.2

Licences et remerciements pour les logiciels tiers

Mersenne twister

Interfaces de connexion (sockets)

Virgule flottante et contrôle d’exception

Interfaces de connexion asynchrones

Gestion de témoin (cookie)

Traçage d’exécution

Les fonctions UUencode et UUdecode

Appel de procédures distantes en XML (RPC, pour Remote Procedure Call)

test_epoll

Select kqueue

SipHash24

strtod et dtoa

OpenSSL

expat

libffi

zlib

cfuhash

libmpdec

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Nouveautés de Python

La série d’essais « Quoi de neuf dans Python » reprend les plus importants changements entres les versions majeures de Python. Elles sont à lire pour quiconque souhaitant être à jour suite à une nouvelle sortie.

What’s New In Python 3.6

Summary – Release highlights

Nouvelles fonctionnalités

Other Language Changes

New Modules

Improved Modules

Optimizations

Build and C API Changes

Autres Améliorations

Deprecated

Removed

Porting to Python 3.6

Notable changes in Python 3.6.2

Notable changes in Python 3.6.4

Notable changes in Python 3.6.5

Notable changes in Python 3.6.7

Notable changes in Python 3.6.10

Nouveautés de Python 3.5

Summary – Release highlights

Nouvelles fonctionnalités

Other Language Changes

New Modules

Improved Modules

Other module-level changes

Optimizations

Build and C API Changes

Deprecated

Removed

Portage vers Python 3.5

Notable changes in Python 3.5.4

Nouveautés de Python 3.4

Summary – Release Highlights

Nouvelles fonctionnalités

New Modules

Improved Modules

CPython Implementation Changes

Deprecated

Removed

Portage vers Python 3.4

Changed in 3.4.3

Nouveautés de Python 3.3

Summary – Release highlights

PEP 405: Virtual Environments

PEP 420: Implicit Namespace Packages

PEP 3118: New memoryview implementation and buffer protocol documentation

PEP 393: Flexible String Representation

PEP 397: Python Launcher for Windows

PEP 3151: Reworking the OS and IO exception hierarchy

PEP 380: Syntax for Delegating to a Subgenerator

PEP 409: Suppressing exception context

PEP 414: Explicit Unicode literals

PEP 3155: Qualified name for classes and functions

PEP 412: Key-Sharing Dictionary

PEP 362: Function Signature Object

PEP 421: Adding sys.implementation

Using importlib as the Implementation of Import

Other Language Changes

A Finer-Grained Import Lock

Builtin functions and types

New Modules

Improved Modules

Optimizations

Build and C API Changes

Deprecated

Portage vers Python 3.3

Nouveautés de Python 3.2

PEP 384: Defining a Stable ABI

PEP 389: Argparse Command Line Parsing Module

PEP 391: Dictionary Based Configuration for Logging

PEP 3148: The concurrent.futures module

PEP 3147: PYC Repository Directories

PEP 3149: ABI Version Tagged .so Files

PEP 3333: Python Web Server Gateway Interface v1.0.1

Other Language Changes

New, Improved, and Deprecated Modules

Fils d’exécution

Optimizations

Unicode

Codecs

Documentation

IDLE

Code Repository

Build and C API Changes

Portage vers Python 3.2

Nouveautés de Python 3.1

PEP 372: Ordered Dictionaries

PEP 378: Format Specifier for Thousands Separator

Other Language Changes

New, Improved, and Deprecated Modules

Optimizations

IDLE

Build and C API Changes

Portage vers Python 3.1

Nouveautés de Python 3.0

Common Stumbling Blocks

Overview Of Syntax Changes

Changes Already Present In Python 2.6

Library Changes

PEP 3101: A New Approach To String Formatting

Changes To Exceptions

Miscellaneous Other Changes

Build and C API Changes

Performances

Portage vers Python 3.0

Nouveautés de Python 2.7

The Future for Python 2.x

Changes to the Handling of Deprecation Warnings

Python 3.1 Features

PEP 372: Adding an Ordered Dictionary to collections

PEP 378: Format Specifier for Thousands Separator

PEP 389: The argparse Module for Parsing Command Lines

PEP 391: Dictionary-Based Configuration For Logging

PEP 3106: Dictionary Views

PEP 3137: The memoryview Object

Other Language Changes

New and Improved Modules

Build and C API Changes

Autres changements et corrections

Portage vers Python 2.7

New Features Added to Python 2.7 Maintenance Releases

Remerciements

Nouveautés de Python 2.6

Python 3.0

Changes to the Development Process

PEP 343: The “with” statement

PEP 366: Explicit Relative Imports From a Main Module

PEP 370: Per-user site-packages Directory

PEP 371: The multiprocessing Package

PEP 3101: Advanced String Formatting

PEP 3105: print As a Function

PEP 3110: Exception-Handling Changes

PEP 3112: Byte Literals

PEP 3116: New I/O Library

PEP 3118: Revised Buffer Protocol

PEP 3119: Abstract Base Classes

PEP 3127: Integer Literal Support and Syntax

PEP 3129: Class Decorators

PEP 3141: A Type Hierarchy for Numbers

Other Language Changes

New and Improved Modules

Deprecations and Removals

Build and C API Changes

Portage vers Python 2.6

Remerciements

Nouveautés de Python 2.5

PEP 308 : Expressions conditionnelles

PEP 309 : Application partielle de fonction

PEP 314: Metadata for Python Software Packages v1.1

PEP 328: Absolute and Relative Imports

PEP 338: Executing Modules as Scripts

PEP 341: Unified try/except/finally

PEP 342: New Generator Features

PEP 343: The “with” statement

PEP 352: Exceptions as New-Style Classes

PEP 353: Using ssize_t as the index type

PEP 357: The “__index__” method

Other Language Changes

Modules ajoutés, modifiés, et supprimés

Build and C API Changes

Portage vers Python 2.5

Remerciements

Nouveautés de Python 2.4

PEP 218: Built-In Set Objects

PEP 237: Unifying Long Integers and Integers

PEP 289: Generator Expressions

PEP 292: Simpler String Substitutions

PEP 318: Decorators for Functions and Methods

PEP 322: Reverse Iteration

PEP 324: New subprocess Module

PEP 327: Decimal Data Type

PEP 328: Multi-line Imports

PEP 331: Locale-Independent Float/String Conversions

Other Language Changes

New, Improved, and Deprecated Modules

Build and C API Changes

Portage vers Python 2.4

Remerciements

Nouveautés de Python 2.3

PEP 218: A Standard Set Datatype

PEP 255 : Générateurs simples

PEP 263: Source Code Encodings

PEP 273: Importing Modules from ZIP Archives

PEP 277: Unicode file name support for Windows NT

PEP 278: Universal Newline Support

PEP 279: enumerate()

PEP 282: The logging Package

PEP 285 : Un type booléen

PEP 293: Codec Error Handling Callbacks

PEP 301: Package Index and Metadata for Distutils

PEP 302: New Import Hooks

PEP 305: Comma-separated Files

PEP 307: Pickle Enhancements

Extended Slices

Other Language Changes

New, Improved, and Deprecated Modules

Pymalloc: A Specialized Object Allocator

Build and C API Changes

Autres changements et corrections

Portage vers Python 2.3

Remerciements

Nouveautés de Python 2.2

Introduction

PEP 252 et 253 : Changements concernant les types et classes

PEP 234 : Itérateurs

PEP 255 : Générateurs simples

PEP 237: Unifying Long Integers and Integers

PEP 238: Changing the Division Operator

Unicode Changes

PEP 227: Nested Scopes

New and Improved Modules

Interpreter Changes and Fixes

Autres changements et corrections

Remerciements

Nouveautés de Python 2.1

Introduction

PEP 227: Nested Scopes

PEP 236 : Directives __future__

PEP 207: Rich Comparisons

PEP 230: Warning Framework

PEP 229: New Build System

PEP 205: Weak References

PEP 232 : Attributs de fonctions

PEP 235: Importing Modules on Case-Insensitive Platforms

PEP 217: Interactive Display Hook

PEP 208: New Coercion Model

PEP 241: Metadata in Python Packages

New and Improved Modules

Autres changements et corrections

Remerciements

Nouveautés de Python 2.0

Introduction

À propos de Python 1.6

Nouveau processus de développement

Unicode

Compréhensions de listes

Augmented Assignment

Méthodes de chaînes de caractères

Garbage Collection of Cycles

Other Core Changes

Porting to 2.0

Extending/Embedding Changes

Distutils: Making Modules Easy to Install

Modules XML

Module changes

Nouveaux modules

IDLE Improvements

Deleted and Deprecated Modules

Remerciements

Le « Changelog » est une version HTML du fichier crée depuis [https://pypi.org/project/blurb] le contenu du dossier Misc/NEWS.d [https://github.com/python/cpython/tree/3.6/Misc/NEWS.d], qui contient toutes les modifications conséquentes de la version actuelle de Python.

Changements

Python 3.6.11 final

Python 3.6.11 release candidate 1

Python 3.6.10 final

Python 3.6.10 release candidate 1

Python 3.6.9 final

Python 3.6.9 release candidate 1

Python 3.6.8 final

Python 3.6.8 release candidate 1

Python 3.6.7 final

Python 3.6.7 release candidate 2

Python 3.6.7 release candidate 1

Python 3.6.6 final

Python 3.6.6 release candidate 1

Python 3.6.5 final

Python 3.6.5 release candidate 1

Python 3.6.4 final

Python 3.6.4 release candidate 1

Python 3.6.3 final

Python 3.6.3 release candidate 1

Python 3.6.2 final

Python 3.6.2 release candidate 2

Python 3.6.2 release candidate 1

Python 3.6.1 final

Python 3.6.1 release candidate 1

Python 3.6.0 final

Python 3.6.0 release candidate 2

Python 3.6.0 release candidate 1

Python 3.6.0 beta 4

Python 3.6.0 beta 3

Python 3.6.0 beta 2

Python 3.6.0 beta 1

Python 3.6.0 alpha 4

Python 3.6.0 alpha 3

Python 3.6.0 alpha 2

Python 3.6.0 alpha 1

Python 3.5.3 final

Python 3.5.3 release candidate 1

Python 3.5.2 final

Python 3.5.2 release candidate 1

Python 3.5.1 final

Python 3.5.1 release candidate 1

Python 3.5.0 final

Python 3.5.0 release candidate 4

Python 3.5.0 release candidate 3

Python 3.5.0 release candidate 2

Python 3.5.0 release candidate 1

Python 3.5.0 beta 4

Python 3.5.0 beta 3

Python 3.5.0 beta 2

Python 3.5.0 beta 1

Python 3.5.0 alpha 4

Python 3.5.0 alpha 3

Python 3.5.0 alpha 2

Python 3.5.0 alpha 1

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What’s New In Python 3.6

Editors

Elvis Pranskevichus <elvis@magic.io>, Yury Selivanov <yury@magic.io>

This article explains the new features in Python 3.6, compared to 3.5. Python 3.6 was released on December 23, 2016. For full details, see the changelog.

Voir aussi

PEP 494 [https://www.python.org/dev/peps/pep-0494] - Python 3.6 Release Schedule

Summary – Release highlights

New syntax features:

PEP 498, formatted string literals.

PEP 515, underscores in numeric literals.

PEP 526, syntax for variable annotations.

PEP 525, asynchronous generators.

PEP 530: asynchronous comprehensions.

New library modules:

secrets: PEP 506 – Adding A Secrets Module To The Standard Library.

CPython implementation improvements:

The dict type has been reimplemented to use a more compact representation based on a proposal by Raymond Hettinger [https://mail.python.org/pipermail/python-dev/2012-December/123028.html] and similar to the PyPy dict implementation [https://morepypy.blogspot.com/2015/01/faster-more-memory-efficient-and-more.html]. This resulted in dictionaries using 20% to 25% less memory when compared to Python 3.5.

Customization of class creation has been simplified with the new protocol.

The class attribute definition order is now preserved.

The order of elements in **kwargs now corresponds to the order in which keyword arguments were passed to the function.

DTrace and SystemTap probing support has been added.

The new PYTHONMALLOC environment variable can now be used to debug the interpreter memory allocation and access errors.

Significant improvements in the standard library:

The asyncio module has received new features, significant usability and performance improvements, and a fair amount of bug fixes. Starting with Python 3.6 the asyncio module is no longer provisional and its API is considered stable.

A new file system path protocol has been implemented to support path-like objects. All standard library functions operating on paths have been updated to work with the new protocol.

The datetime module has gained support for Local Time Disambiguation.

The typing module received a number of improvements.

The tracemalloc module has been significantly reworked and is now used to provide better output for ResourceWarning as well as provide better diagnostics for memory allocation errors. See the PYTHONMALLOC section for more information.

Security improvements:

The new secrets module has been added to simplify the generation of cryptographically strong pseudo-random numbers suitable for managing secrets such as account authentication, tokens, and similar.

On Linux, os.urandom() now blocks until the system urandom entropy pool is initialized to increase the security. See the PEP 524 [https://www.python.org/dev/peps/pep-0524] for the rationale.

The hashlib and ssl modules now support OpenSSL 1.1.0.

The default settings and feature set of the ssl module have been improved.

The hashlib module received support for the BLAKE2, SHA-3 and SHAKE hash algorithms and the scrypt() key derivation function.

Windows improvements:

PEP 528 and PEP 529, Windows filesystem and console encoding changed to UTF-8.

The py.exe launcher, when used interactively, no longer prefers Python 2 over Python 3 when the user doesn’t specify a version (via command line arguments or a config file). Handling of shebang lines remains unchanged - « python » refers to Python 2 in that case.

python.exe and pythonw.exe have been marked as long-path aware, which means that the 260 character path limit may no longer apply. See removing the MAX_PATH limitation for details.

A ._pth file can be added to force isolated mode and fully specify all search paths to avoid registry and environment lookup. See the documentation for more information.

A python36.zip file now works as a landmark to infer PYTHONHOME. See the documentation for more information.

Nouvelles fonctionnalités

PEP 498: Formatted string literals

PEP 498 [https://www.python.org/dev/peps/pep-0498] introduces a new kind of string literals: f-strings, or formatted string literals.

Formatted string literals are prefixed with 'f' and are similar to the format strings accepted by str.format(). They contain replacement fields surrounded by curly braces. The replacement fields are expressions, which are evaluated at run time, and then formatted using the format() protocol:

>>> name = "Fred"
>>> f"He said his name is {name}."
'He said his name is Fred.'
>>> width = 10
>>> precision = 4
>>> value = decimal.Decimal("12.34567")
>>> f"result: {value:{width}.{precision}}"  # nested fields
'result:      12.35'

Voir aussi

PEP 498 [https://www.python.org/dev/peps/pep-0498] – Literal String Interpolation.

PEP written and implemented by Eric V. Smith.

Feature documentation.

PEP 526: Syntax for variable annotations

PEP 484 [https://www.python.org/dev/peps/pep-0484] introduced the standard for type annotations of function parameters, a.k.a. type hints. This PEP adds syntax to Python for annotating the types of variables including class variables and instance variables:

primes: List[int] = []

captain: str  # Note: no initial value!

class Starship:
    stats: Dict[str, int] = {}

Just as for function annotations, the Python interpreter does not attach any particular meaning to variable annotations and only stores them in the __annotations__ attribute of a class or module.

In contrast to variable declarations in statically typed languages, the goal of annotation syntax is to provide an easy way to specify structured type metadata for third party tools and libraries via the abstract syntax tree and the __annotations__ attribute.

Voir aussi

PEP 526 [https://www.python.org/dev/peps/pep-0526] – Syntax for variable annotations.

PEP written by Ryan Gonzalez, Philip House, Ivan Levkivskyi, Lisa Roach, and Guido van Rossum. Implemented by Ivan Levkivskyi.

Tools that use or will use the new syntax: mypy [http://www.mypy-lang.org/], pytype [https://github.com/google/pytype], PyCharm, etc.

PEP 515: Underscores in Numeric Literals

PEP 515 [https://www.python.org/dev/peps/pep-0515] adds the ability to use underscores in numeric literals for improved readability. For example:

>>> 1_000_000_000_000_000
1000000000000000
>>> 0x_FF_FF_FF_FF
4294967295

Single underscores are allowed between digits and after any base specifier. Leading, trailing, or multiple underscores in a row are not allowed.

The string formatting language also now has support for the '_' option to signal the use of an underscore for a thousands separator for floating point presentation types and for integer presentation type 'd'. For integer presentation types 'b', 'o', 'x', and 'X', underscores will be inserted every 4 digits:

>>> '{:_}'.format(1000000)
'1_000_000'
>>> '{:_x}'.format(0xFFFFFFFF)
'ffff_ffff'

Voir aussi

PEP 515 [https://www.python.org/dev/peps/pep-0515] – Underscores in Numeric Literals

PEP written by Georg Brandl and Serhiy Storchaka.

PEP 525: Asynchronous Generators

PEP 492 [https://www.python.org/dev/peps/pep-0492] introduced support for native coroutines and async / await syntax to Python 3.5. A notable limitation of the Python 3.5 implementation is that it was not possible to use await and yield in the same function body. In Python 3.6 this restriction has been lifted, making it possible to define asynchronous generators:

async def ticker(delay, to):
    """Yield numbers from 0 to *to* every *delay* seconds."""
    for i in range(to):
        yield i
        await asyncio.sleep(delay)

The new syntax allows for faster and more concise code.

Voir aussi

PEP 525 [https://www.python.org/dev/peps/pep-0525] – Asynchronous Generators

PEP written and implemented by Yury Selivanov.

PEP 530: Asynchronous Comprehensions

PEP 530 [https://www.python.org/dev/peps/pep-0530] adds support for using async for in list, set, dict comprehensions and generator expressions:

result = [i async for i in aiter() if i % 2]

Additionally, await expressions are supported in all kinds of comprehensions:

result = [await fun() for fun in funcs if await condition()]

Voir aussi

PEP 530 [https://www.python.org/dev/peps/pep-0530] – Asynchronous Comprehensions

PEP written and implemented by Yury Selivanov.

PEP 487: Simpler customization of class creation

It is now possible to customize subclass creation without using a metaclass. The new __init_subclass__ classmethod will be called on the base class whenever a new subclass is created:

class PluginBase:
    subclasses = []

    def __init_subclass__(cls, **kwargs):
        super().__init_subclass__(**kwargs)
        cls.subclasses.append(cls)

class Plugin1(PluginBase):
    pass

class Plugin2(PluginBase):
    pass

In order to allow zero-argument super() calls to work correctly from __init_subclass__() implementations, custom metaclasses must ensure that the new __classcell__ namespace entry is propagated to type.__new__ (as described in Création de l’objet classe).

Voir aussi

PEP 487 [https://www.python.org/dev/peps/pep-0487] – Simpler customization of class creation

PEP written and implemented by Martin Teichmann.

Feature documentation

PEP 487: Descriptor Protocol Enhancements

PEP 487 [https://www.python.org/dev/peps/pep-0487] extends the descriptor protocol to include the new optional __set_name__() method. Whenever a new class is defined, the new method will be called on all descriptors included in the definition, providing them with a reference to the class being defined and the name given to the descriptor within the class namespace. In other words, instances of descriptors can now know the attribute name of the descriptor in the owner class:

class IntField:
    def __get__(self, instance, owner):
        return instance.__dict__[self.name]

    def __set__(self, instance, value):
        if not isinstance(value, int):
            raise ValueError(f'expecting integer in {self.name}')
        instance.__dict__[self.name] = value

    # this is the new initializer:
    def __set_name__(self, owner, name):
        self.name = name

class Model:
    int_field = IntField()

Voir aussi

PEP 487 [https://www.python.org/dev/peps/pep-0487] – Simpler customization of class creation

PEP written and implemented by Martin Teichmann.

Feature documentation

PEP 519: Adding a file system path protocol

File system paths have historically been represented as str or bytes objects. This has led to people who write code which operate on file system paths to assume that such objects are only one of those two types (an int representing a file descriptor does not count as that is not a file path). Unfortunately that assumption prevents alternative object representations of file system paths like pathlib from working with pre-existing code, including Python’s standard library.

To fix this situation, a new interface represented by os.PathLike has been defined. By implementing the __fspath__() method, an object signals that it represents a path. An object can then provide a low-level representation of a file system path as a str or bytes object. This means an object is considered path-like if it implements os.PathLike or is a str or bytes object which represents a file system path. Code can use os.fspath(), os.fsdecode(), or os.fsencode() to explicitly get a str and/or bytes representation of a path-like object.

The built-in open() function has been updated to accept os.PathLike objects, as have all relevant functions in the os and os.path modules, and most other functions and classes in the standard library. The os.DirEntry class and relevant classes in pathlib have also been updated to implement os.PathLike.

The hope is that updating the fundamental functions for operating on file system paths will lead to third-party code to implicitly support all path-like objects without any code changes, or at least very minimal ones (e.g. calling os.fspath() at the beginning of code before operating on a path-like object).

Here are some examples of how the new interface allows for pathlib.Path to be used more easily and transparently with pre-existing code:

>>> import pathlib
>>> with open(pathlib.Path("README")) as f:
...     contents = f.read()
...
>>> import os.path
>>> os.path.splitext(pathlib.Path("some_file.txt"))
('some_file', '.txt')
>>> os.path.join("/a/b", pathlib.Path("c"))
'/a/b/c'
>>> import os
>>> os.fspath(pathlib.Path("some_file.txt"))
'some_file.txt'

(Implemented by Brett Cannon, Ethan Furman, Dusty Phillips, and Jelle Zijlstra.)

Voir aussi

PEP 519 [https://www.python.org/dev/peps/pep-0519] – Adding a file system path protocol

PEP written by Brett Cannon and Koos Zevenhoven.

PEP 495: Local Time Disambiguation

In most world locations, there have been and will be times when local clocks are moved back. In those times, intervals are introduced in which local clocks show the same time twice in the same day. In these situations, the information displayed on a local clock (or stored in a Python datetime instance) is insufficient to identify a particular moment in time.

PEP 495 [https://www.python.org/dev/peps/pep-0495] adds the new fold attribute to instances of datetime.datetime and datetime.time classes to differentiate between two moments in time for which local times are the same:

>>> u0 = datetime(2016, 11, 6, 4, tzinfo=timezone.utc)
>>> for i in range(4):
...     u = u0 + i*HOUR
...     t = u.astimezone(Eastern)
...     print(u.time(), 'UTC =', t.time(), t.tzname(), t.fold)
...
04:00:00 UTC = 00:00:00 EDT 0
05:00:00 UTC = 01:00:00 EDT 0
06:00:00 UTC = 01:00:00 EST 1
07:00:00 UTC = 02:00:00 EST 0

The values of the fold attribute have the value 0 for all instances except those that represent the second (chronologically) moment in time in an ambiguous case.

Voir aussi

PEP 495 [https://www.python.org/dev/peps/pep-0495] – Local Time Disambiguation

PEP written by Alexander Belopolsky and Tim Peters, implementation by Alexander Belopolsky.

PEP 529: Change Windows filesystem encoding to UTF-8

Representing filesystem paths is best performed with str (Unicode) rather than bytes. However, there are some situations where using bytes is sufficient and correct.

Prior to Python 3.6, data loss could result when using bytes paths on Windows. With this change, using bytes to represent paths is now supported on Windows, provided those bytes are encoded with the encoding returned by sys.getfilesystemencoding(), which now defaults to 'utf-8'.

Applications that do not use str to represent paths should use os.fsencode() and os.fsdecode() to ensure their bytes are correctly encoded. To revert to the previous behaviour, set PYTHONLEGACYWINDOWSFSENCODING or call sys._enablelegacywindowsfsencoding().

See PEP 529 [https://www.python.org/dev/peps/pep-0529] for more information and discussion of code modifications that may be required.

PEP 528: Change Windows console encoding to UTF-8

The default console on Windows will now accept all Unicode characters and provide correctly read str objects to Python code. sys.stdin, sys.stdout and sys.stderr now default to utf-8 encoding.

This change only applies when using an interactive console, and not when redirecting files or pipes. To revert to the previous behaviour for interactive console use, set PYTHONLEGACYWINDOWSSTDIO.

Voir aussi

PEP 528 [https://www.python.org/dev/peps/pep-0528] – Change Windows console encoding to UTF-8

PEP written and implemented by Steve Dower.

PEP 520: Preserving Class Attribute Definition Order

Attributes in a class definition body have a natural ordering: the same order in which the names appear in the source. This order is now preserved in the new class’s __dict__ attribute.

Also, the effective default class execution namespace (returned from type.__prepare__()) is now an insertion-order-preserving mapping.

Voir aussi

PEP 520 [https://www.python.org/dev/peps/pep-0520] – Preserving Class Attribute Definition Order

PEP written and implemented by Eric Snow.

PEP 468: Preserving Keyword Argument Order

**kwargs in a function signature is now guaranteed to be an insertion-order-preserving mapping.

Voir aussi

PEP 468 [https://www.python.org/dev/peps/pep-0468] – Preserving Keyword Argument Order

PEP written and implemented by Eric Snow.

New dict implementation

The dict type now uses a « compact » representation based on a proposal by Raymond Hettinger [https://mail.python.org/pipermail/python-dev/2012-December/123028.html] which was first implemented by PyPy [https://morepypy.blogspot.com/2015/01/faster-more-memory-efficient-and-more.html]. The memory usage of the new dict() is between 20% and 25% smaller compared to Python 3.5.

The order-preserving aspect of this new implementation is considered an implementation detail and should not be relied upon (this may change in the future, but it is desired to have this new dict implementation in the language for a few releases before changing the language spec to mandate order-preserving semantics for all current and future Python implementations; this also helps preserve backwards-compatibility with older versions of the language where random iteration order is still in effect, e.g. Python 3.5).

(Contributed by INADA Naoki in bpo-27350 [https://bugs.python.org/issue27350]. Idea originally suggested by Raymond Hettinger [https://mail.python.org/pipermail/python-dev/2012-December/123028.html].)

PEP 523: Adding a frame evaluation API to CPython

While Python provides extensive support to customize how code executes, one place it has not done so is in the evaluation of frame objects. If you wanted some way to intercept frame evaluation in Python there really wasn’t any way without directly manipulating function pointers for defined functions.

PEP 523 [https://www.python.org/dev/peps/pep-0523] changes this by providing an API to make frame evaluation pluggable at the C level. This will allow for tools such as debuggers and JITs to intercept frame evaluation before the execution of Python code begins. This enables the use of alternative evaluation implementations for Python code, tracking frame evaluation, etc.

This API is not part of the limited C API and is marked as private to signal that usage of this API is expected to be limited and only applicable to very select, low-level use-cases. Semantics of the API will change with Python as necessary.

Voir aussi

PEP 523 [https://www.python.org/dev/peps/pep-0523] – Adding a frame evaluation API to CPython

PEP written by Brett Cannon and Dino Viehland.

PYTHONMALLOC environment variable

The new PYTHONMALLOC environment variable allows setting the Python memory allocators and installing debug hooks.

It is now possible to install debug hooks on Python memory allocators on Python compiled in release mode using PYTHONMALLOC=debug. Effects of debug hooks:

Newly allocated memory is filled with the byte 0xCB

Freed memory is filled with the byte 0xDB

Detect violations of the Python memory allocator API. For example, PyObject_Free() called on a memory block allocated by PyMem_Malloc().

Detect writes before the start of a buffer (buffer underflows)

Detect writes after the end of a buffer (buffer overflows)

Check that the GIL is held when allocator functions of PYMEM_DOMAIN_OBJ (ex: PyObject_Malloc()) and PYMEM_DOMAIN_MEM (ex: PyMem_Malloc()) domains are called.

Checking if the GIL is held is also a new feature of Python 3.6.

Reportez-vous à la fonction PyMem_SetupDebugHooks() pour ce qui concerne les fonctions de débogage de l’allocateur mémoire de Python.

It is now also possible to force the usage of the malloc() allocator of the C library for all Python memory allocations using PYTHONMALLOC=malloc. This is helpful when using external memory debuggers like Valgrind on a Python compiled in release mode.

On error, the debug hooks on Python memory allocators now use the tracemalloc module to get the traceback where a memory block was allocated.

Example of fatal error on buffer overflow using python3.6 -X tracemalloc=5 (store 5 frames in traces):

Debug memory block at address p=0x7fbcd41666f8: API 'o'
    4 bytes originally requested
    The 7 pad bytes at p-7 are FORBIDDENBYTE, as expected.
    The 8 pad bytes at tail=0x7fbcd41666fc are not all FORBIDDENBYTE (0xfb):
        at tail+0: 0x02 *** OUCH
        at tail+1: 0xfb
        at tail+2: 0xfb
        at tail+3: 0xfb
        at tail+4: 0xfb
        at tail+5: 0xfb
        at tail+6: 0xfb
        at tail+7: 0xfb
    The block was made by call #1233329 to debug malloc/realloc.
    Data at p: 1a 2b 30 00

Memory block allocated at (most recent call first):
  File "test/test_bytes.py", line 323
  File "unittest/case.py", line 600
  File "unittest/case.py", line 648
  File "unittest/suite.py", line 122
  File "unittest/suite.py", line 84

Fatal Python error: bad trailing pad byte

Current thread 0x00007fbcdbd32700 (most recent call first):
  File "test/test_bytes.py", line 323 in test_hex
  File "unittest/case.py", line 600 in run
  File "unittest/case.py", line 648 in __call__
  File "unittest/suite.py", line 122 in run
  File "unittest/suite.py", line 84 in __call__
  File "unittest/suite.py", line 122 in run
  File "unittest/suite.py", line 84 in __call__
  ...

(Contributed by Victor Stinner in bpo-26516 [https://bugs.python.org/issue26516] and bpo-26564 [https://bugs.python.org/issue26564].)

DTrace and SystemTap probing support

Python can now be built --with-dtrace which enables static markers for the following events in the interpreter:

function call/return

garbage collection started/finished

line of code executed.

This can be used to instrument running interpreters in production, without the need to recompile specific debug builds or providing application-specific profiling/debugging code.

More details in Instrumenter CPython avec DTrace et SystemTap.

The current implementation is tested on Linux and macOS. Additional markers may be added in the future.

(Contributed by Łukasz Langa in bpo-21590 [https://bugs.python.org/issue21590], based on patches by Jesús Cea Avión, David Malcolm, and Nikhil Benesch.)

Other Language Changes

Some smaller changes made to the core Python language are:

A global or nonlocal statement must now textually appear before the first use of the affected name in the same scope. Previously this was a SyntaxWarning.

It is now possible to set a special method to None to indicate that the corresponding operation is not available. For example, if a class sets __iter__() to None, the class is not iterable. (Contributed by Andrew Barnert and Ivan Levkivskyi in bpo-25958 [https://bugs.python.org/issue25958].)

Long sequences of repeated traceback lines are now abbreviated as "[Previous line repeated {count} more times]" (see traceback for an example). (Contributed by Emanuel Barry in bpo-26823 [https://bugs.python.org/issue26823].)

Import now raises the new exception ModuleNotFoundError (subclass of ImportError) when it cannot find a module. Code that currently checks for ImportError (in try-except) will still work. (Contributed by Eric Snow in bpo-15767 [https://bugs.python.org/issue15767].)

Class methods relying on zero-argument super() will now work correctly when called from metaclass methods during class creation. (Contributed by Martin Teichmann in bpo-23722 [https://bugs.python.org/issue23722].)

New Modules

secrets

The main purpose of the new secrets module is to provide an obvious way to reliably generate cryptographically strong pseudo-random values suitable for managing secrets, such as account authentication, tokens, and similar.

Avertissement

Note that the pseudo-random generators in the random module should NOT be used for security purposes. Use secrets on Python 3.6+ and os.urandom() on Python 3.5 and earlier.

Voir aussi

PEP 506 [https://www.python.org/dev/peps/pep-0506] – Adding A Secrets Module To The Standard Library

PEP written and implemented by Steven D’Aprano.

Improved Modules

array

Exhausted iterators of array.array will now stay exhausted even if the iterated array is extended. This is consistent with the behavior of other mutable sequences.

Contributed by Serhiy Storchaka in bpo-26492 [https://bugs.python.org/issue26492].

ast

The new ast.Constant AST node has been added. It can be used by external AST optimizers for the purposes of constant folding.

Contributed by Victor Stinner in bpo-26146 [https://bugs.python.org/issue26146].

asyncio

Starting with Python 3.6 the asyncio module is no longer provisional and its API is considered stable.

Notable changes in the asyncio module since Python 3.5.0 (all backported to 3.5.x due to the provisional status):

The get_event_loop() function has been changed to always return the currently running loop when called from coroutines and callbacks. (Contributed by Yury Selivanov in bpo-28613 [https://bugs.python.org/issue28613].)

The ensure_future() function and all functions that use it, such as loop.run_until_complete(), now accept all kinds of awaitable objects. (Contributed by Yury Selivanov.)

New run_coroutine_threadsafe() function to submit coroutines to event loops from other threads. (Contributed by Vincent Michel.)

New Transport.is_closing() method to check if the transport is closing or closed. (Contributed by Yury Selivanov.)

The loop.create_server() method can now accept a list of hosts. (Contributed by Yann Sionneau.)

New loop.create_future() method to create Future objects. This allows alternative event loop implementations, such as uvloop [https://github.com/MagicStack/uvloop], to provide a faster asyncio.Future implementation. (Contributed by Yury Selivanov in bpo-27041 [https://bugs.python.org/issue27041].)

New loop.get_exception_handler() method to get the current exception handler. (Contributed by Yury Selivanov in bpo-27040 [https://bugs.python.org/issue27040].)

New StreamReader.readuntil() method to read data from the stream until a separator bytes sequence appears. (Contributed by Mark Korenberg.)

The performance of StreamReader.readexactly() has been improved. (Contributed by Mark Korenberg in bpo-28370 [https://bugs.python.org/issue28370].)

The loop.getaddrinfo() method is optimized to avoid calling the system getaddrinfo function if the address is already resolved. (Contributed by A. Jesse Jiryu Davis.)

The loop.stop() method has been changed to stop the loop immediately after the current iteration. Any new callbacks scheduled as a result of the last iteration will be discarded. (Contributed by Guido van Rossum in bpo-25593 [https://bugs.python.org/issue25593].)

Future.set_exception will now raise TypeError when passed an instance of the StopIteration exception. (Contributed by Chris Angelico in bpo-26221 [https://bugs.python.org/issue26221].)

New loop.connect_accepted_socket() method to be used by servers that accept connections outside of asyncio, but that use asyncio to handle them. (Contributed by Jim Fulton in bpo-27392 [https://bugs.python.org/issue27392].)

TCP_NODELAY flag is now set for all TCP transports by default. (Contributed by Yury Selivanov in bpo-27456 [https://bugs.python.org/issue27456].)

New loop.shutdown_asyncgens() to properly close pending asynchronous generators before closing the loop. (Contributed by Yury Selivanov in bpo-28003 [https://bugs.python.org/issue28003].)

Future and Task classes now have an optimized C implementation which makes asyncio code up to 30% faster. (Contributed by Yury Selivanov and INADA Naoki in bpo-26081 [https://bugs.python.org/issue26081] and bpo-28544 [https://bugs.python.org/issue28544].)

binascii

The b2a_base64() function now accepts an optional newline keyword argument to control whether the newline character is appended to the return value. (Contributed by Victor Stinner in bpo-25357 [https://bugs.python.org/issue25357].)

cmath

The new cmath.tau (τ) constant has been added. (Contributed by Lisa Roach in bpo-12345 [https://bugs.python.org/issue12345], see PEP 628 [https://www.python.org/dev/peps/pep-0628] for details.)

New constants: cmath.inf and cmath.nan to match math.inf and math.nan, and also cmath.infj and cmath.nanj to match the format used by complex repr. (Contributed by Mark Dickinson in bpo-23229 [https://bugs.python.org/issue23229].)

collections

The new Collection abstract base class has been added to represent sized iterable container classes. (Contributed by Ivan Levkivskyi, docs by Neil Girdhar in bpo-27598 [https://bugs.python.org/issue27598].)

The new Reversible abstract base class represents iterable classes that also provide the __reversed__() method. (Contributed by Ivan Levkivskyi in bpo-25987 [https://bugs.python.org/issue25987].)

The new AsyncGenerator abstract base class represents asynchronous generators. (Contributed by Yury Selivanov in bpo-28720 [https://bugs.python.org/issue28720].)

The namedtuple() function now accepts an optional keyword argument module, which, when specified, is used for the __module__ attribute of the returned named tuple class. (Contributed by Raymond Hettinger in bpo-17941 [https://bugs.python.org/issue17941].)

The verbose and rename arguments for namedtuple() are now keyword-only. (Contributed by Raymond Hettinger in bpo-25628 [https://bugs.python.org/issue25628].)

Recursive collections.deque instances can now be pickled. (Contributed by Serhiy Storchaka in bpo-26482 [https://bugs.python.org/issue26482].)

concurrent.futures

The ThreadPoolExecutor class constructor now accepts an optional thread_name_prefix argument to make it possible to customize the names of the threads created by the pool. (Contributed by Gregory P. Smith in bpo-27664 [https://bugs.python.org/issue27664].)

contextlib

The contextlib.AbstractContextManager class has been added to provide an abstract base class for context managers. It provides a sensible default implementation for __enter__() which returns self and leaves __exit__() an abstract method. A matching class has been added to the typing module as typing.ContextManager. (Contributed by Brett Cannon in bpo-25609 [https://bugs.python.org/issue25609].)

datetime

The datetime and time classes have the new fold attribute used to disambiguate local time when necessary. Many functions in the datetime have been updated to support local time disambiguation. See Local Time Disambiguation section for more information. (Contributed by Alexander Belopolsky in bpo-24773 [https://bugs.python.org/issue24773].)

The datetime.strftime() and date.strftime() methods now support ISO 8601 date directives %G, %u and %V. (Contributed by Ashley Anderson in bpo-12006 [https://bugs.python.org/issue12006].)

The datetime.isoformat() function now accepts an optional timespec argument that specifies the number of additional components of the time value to include. (Contributed by Alessandro Cucci and Alexander Belopolsky in bpo-19475 [https://bugs.python.org/issue19475].)

The datetime.combine() now accepts an optional tzinfo argument. (Contributed by Alexander Belopolsky in bpo-27661 [https://bugs.python.org/issue27661].)

decimal

New Decimal.as_integer_ratio() method that returns a pair (n, d) of integers that represent the given Decimal instance as a fraction, in lowest terms and with a positive denominator:

>>> Decimal('-3.14').as_integer_ratio()
(-157, 50)

(Contributed by Stefan Krah amd Mark Dickinson in bpo-25928 [https://bugs.python.org/issue25928].)

distutils

The default_format attribute has been removed from distutils.command.sdist.sdist and the formats attribute defaults to ['gztar']. Although not anticipated, any code relying on the presence of default_format may need to be adapted. See bpo-27819 [https://bugs.python.org/issue27819] for more details.

email

The new email API, enabled via the policy keyword to various constructors, is no longer provisional. The email documentation has been reorganized and rewritten to focus on the new API, while retaining the old documentation for the legacy API. (Contributed by R. David Murray in bpo-24277 [https://bugs.python.org/issue24277].)

The email.mime classes now all accept an optional policy keyword. (Contributed by Berker Peksag in bpo-27331 [https://bugs.python.org/issue27331].)

The DecodedGenerator now supports the policy keyword.

There is a new policy attribute, message_factory, that controls what class is used by default when the parser creates new message objects. For the email.policy.compat32 policy this is Message, for the new policies it is EmailMessage. (Contributed by R. David Murray in bpo-20476 [https://bugs.python.org/issue20476].)

encodings

On Windows, added the 'oem' encoding to use CP_OEMCP, and the 'ansi' alias for the existing 'mbcs' encoding, which uses the CP_ACP code page. (Contributed by Steve Dower in bpo-27959 [https://bugs.python.org/issue27959].)

enum

Two new enumeration base classes have been added to the enum module: Flag and IntFlags. Both are used to define constants that can be combined using the bitwise operators. (Contributed by Ethan Furman in bpo-23591 [https://bugs.python.org/issue23591].)

Many standard library modules have been updated to use the IntFlags class for their constants.

The new enum.auto value can be used to assign values to enum members automatically:

>>> from enum import Enum, auto
>>> class Color(Enum):
...     red = auto()
...     blue = auto()
...     green = auto()
...
>>> list(Color)
[<Color.red: 1>, <Color.blue: 2>, <Color.green: 3>]

faulthandler

On Windows, the faulthandler module now installs a handler for Windows exceptions: see faulthandler.enable(). (Contributed by Victor Stinner in bpo-23848 [https://bugs.python.org/issue23848].)

fileinput

hook_encoded() now supports the errors argument. (Contributed by Joseph Hackman in bpo-25788 [https://bugs.python.org/issue25788].)

hashlib

hashlib supports OpenSSL 1.1.0. The minimum recommend version is 1.0.2. (Contributed by Christian Heimes in bpo-26470 [https://bugs.python.org/issue26470].)

BLAKE2 hash functions were added to the module. blake2b() and blake2s() are always available and support the full feature set of BLAKE2. (Contributed by Christian Heimes in bpo-26798 [https://bugs.python.org/issue26798] based on code by Dmitry Chestnykh and Samuel Neves. Documentation written by Dmitry Chestnykh.)

The SHA-3 hash functions sha3_224(), sha3_256(), sha3_384(), sha3_512(), and SHAKE hash functions shake_128() and shake_256() were added. (Contributed by Christian Heimes in bpo-16113 [https://bugs.python.org/issue16113]. Keccak Code Package by Guido Bertoni, Joan Daemen, Michaël Peeters, Gilles Van Assche, and Ronny Van Keer.)

The password-based key derivation function scrypt() is now available with OpenSSL 1.1.0 and newer. (Contributed by Christian Heimes in bpo-27928 [https://bugs.python.org/issue27928].)

http.client

HTTPConnection.request() and endheaders() both now support chunked encoding request bodies. (Contributed by Demian Brecht and Rolf Krahl in bpo-12319 [https://bugs.python.org/issue12319].)

idlelib and IDLE

The idlelib package is being modernized and refactored to make IDLE look and work better and to make the code easier to understand, test, and improve. Part of making IDLE look better, especially on Linux and Mac, is using ttk widgets, mostly in the dialogs. As a result, IDLE no longer runs with tcl/tk 8.4. It now requires tcl/tk 8.5 or 8.6. We recommend running the latest release of either.

“Modernizing” includes renaming and consolidation of idlelib modules. The renaming of files with partial uppercase names is similar to the renaming of, for instance, Tkinter and TkFont to tkinter and tkinter.font in 3.0. As a result, imports of idlelib files that worked in 3.5 will usually not work in 3.6. At least a module name change will be needed (see idlelib/README.txt), sometimes more. (Name changes contributed by Al Swiegart and Terry Reedy in bpo-24225 [https://bugs.python.org/issue24225]. Most idlelib patches since have been and will be part of the process.)

In compensation, the eventual result with be that some idlelib classes will be easier to use, with better APIs and docstrings explaining them. Additional useful information will be added to idlelib when available.

New in 3.6.2:

Multiple fixes for autocompletion. (Contributed by Louie Lu in bpo-15786 [https://bugs.python.org/issue15786].)

New in 3.6.3:

Module Browser (on the File menu, formerly called Class Browser), now displays nested functions and classes in addition to top-level functions and classes. (Contributed by Guilherme Polo, Cheryl Sabella, and Terry Jan Reedy in bpo-1612262 [https://bugs.python.org/issue1612262].)

The IDLE features formerly implemented as extensions have been reimplemented as normal features. Their settings have been moved from the Extensions tab to other dialog tabs. (Contributed by Charles Wohlganger and Terry Jan Reedy in bpo-27099 [https://bugs.python.org/issue27099].)

The Settings dialog (Options, Configure IDLE) has been partly rewritten to improve both appearance and function. (Contributed by Cheryl Sabella and Terry Jan Reedy in multiple issues.)

New in 3.6.4:

The font sample now includes a selection of non-Latin characters so that users can better see the effect of selecting a particular font. (Contributed by Terry Jan Reedy in bpo-13802 [https://bugs.python.org/issue13802].) The sample can be edited to include other characters. (Contributed by Serhiy Storchaka in bpo-31860 [https://bugs.python.org/issue31860].)

New in 3.6.6:

Editor code context option revised. Box displays all context lines up to maxlines. Clicking on a context line jumps the editor to that line. Context colors for custom themes is added to Highlights tab of Settings dialog. (Contributed by Cheryl Sabella and Terry Jan Reedy in bpo-33642 [https://bugs.python.org/issue33642], bpo-33768 [https://bugs.python.org/issue33768], and bpo-33679 [https://bugs.python.org/issue33679].)

On Windows, a new API call tells Windows that tk scales for DPI. On Windows 8.1+ or 10, with DPI compatibility properties of the Python binary unchanged, and a monitor resolution greater than 96 DPI, this should make text and lines sharper. It should otherwise have no effect. (Contributed by Terry Jan Reedy in bpo-33656 [https://bugs.python.org/issue33656].)

New in 3.6.7:

Output over N lines (50 by default) is squeezed down to a button. N can be changed in the PyShell section of the General page of the Settings dialog. Fewer, but possibly extra long, lines can be squeezed by right clicking on the output. Squeezed output can be expanded in place by double-clicking the button or into the clipboard or a separate window by right-clicking the button. (Contributed by Tal Einat in bpo-1529353 [https://bugs.python.org/issue1529353].)

importlib

Import now raises the new exception ModuleNotFoundError (subclass of ImportError) when it cannot find a module. Code that current checks for ImportError (in try-except) will still work. (Contributed by Eric Snow in bpo-15767 [https://bugs.python.org/issue15767].)

importlib.util.LazyLoader now calls create_module() on the wrapped loader, removing the restriction that importlib.machinery.BuiltinImporter and importlib.machinery.ExtensionFileLoader couldn’t be used with importlib.util.LazyLoader.

importlib.util.cache_from_source(), importlib.util.source_from_cache(), and importlib.util.spec_from_file_location() now accept a path-like object.

inspect

The inspect.signature() function now reports the implicit .0 parameters generated by the compiler for comprehension and generator expression scopes as if they were positional-only parameters called implicit0. (Contributed by Jelle Zijlstra in bpo-19611 [https://bugs.python.org/issue19611].)

To reduce code churn when upgrading from Python 2.7 and the legacy inspect.getargspec() API, the previously documented deprecation of inspect.getfullargspec() has been reversed. While this function is convenient for single/source Python 2/3 code bases, the richer inspect.signature() interface remains the recommended approach for new code. (Contributed by Nick Coghlan in bpo-27172 [https://bugs.python.org/issue27172])

json

json.load() and json.loads() now support binary input. Encoded JSON should be represented using either UTF-8, UTF-16, or UTF-32. (Contributed by Serhiy Storchaka in bpo-17909 [https://bugs.python.org/issue17909].)

logging

The new WatchedFileHandler.reopenIfNeeded() method has been added to add the ability to check if the log file needs to be reopened. (Contributed by Marian Horban in bpo-24884 [https://bugs.python.org/issue24884].)

math

The tau (τ) constant has been added to the math and cmath modules. (Contributed by Lisa Roach in bpo-12345 [https://bugs.python.org/issue12345], see PEP 628 [https://www.python.org/dev/peps/pep-0628] for details.)

multiprocessing

Proxy Objects returned by multiprocessing.Manager() can now be nested. (Contributed by Davin Potts in bpo-6766 [https://bugs.python.org/issue6766].)

os

See the summary of PEP 519 for details on how the os and os.path modules now support path-like objects.

scandir() now supports bytes paths on Windows.

A new close() method allows explicitly closing a scandir() iterator. The scandir() iterator now supports the context manager protocol. If a scandir() iterator is neither exhausted nor explicitly closed a ResourceWarning will be emitted in its destructor. (Contributed by Serhiy Storchaka in bpo-25994 [https://bugs.python.org/issue25994].)

On Linux, os.urandom() now blocks until the system urandom entropy pool is initialized to increase the security. See the PEP 524 [https://www.python.org/dev/peps/pep-0524] for the rationale.

The Linux getrandom() syscall (get random bytes) is now exposed as the new os.getrandom() function. (Contributed by Victor Stinner, part of the PEP 524 [https://www.python.org/dev/peps/pep-0524])

pathlib

pathlib now supports path-like objects. (Contributed by Brett Cannon in bpo-27186 [https://bugs.python.org/issue27186].)

See the summary of PEP 519 for details.

pdb

The Pdb class constructor has a new optional readrc argument to control whether .pdbrc files should be read.

pickle

Objects that need __new__ called with keyword arguments can now be pickled using pickle protocols older than protocol version 4. Protocol version 4 already supports this case. (Contributed by Serhiy Storchaka in bpo-24164 [https://bugs.python.org/issue24164].)

pickletools

pickletools.dis() now outputs the implicit memo index for the MEMOIZE opcode. (Contributed by Serhiy Storchaka in bpo-25382 [https://bugs.python.org/issue25382].)

pydoc

The pydoc module has learned to respect the MANPAGER environment variable. (Contributed by Matthias Klose in bpo-8637 [https://bugs.python.org/issue8637].)

help() and pydoc can now list named tuple fields in the order they were defined rather than alphabetically. (Contributed by Raymond Hettinger in bpo-24879 [https://bugs.python.org/issue24879].)

random

The new choices() function returns a list of elements of specified size from the given population with optional weights. (Contributed by Raymond Hettinger in bpo-18844 [https://bugs.python.org/issue18844].)

re

Added support of modifier spans in regular expressions. Examples: '(?i:p)ython' matches 'python' and 'Python', but not 'PYTHON'; '(?i)g(?-i:v)r' matches 'GvR' and 'gvr', but not 'GVR'. (Contributed by Serhiy Storchaka in bpo-433028 [https://bugs.python.org/issue433028].)

Match object groups can be accessed by __getitem__, which is equivalent to group(). So mo['name'] is now equivalent to mo.group('name'). (Contributed by Eric Smith in bpo-24454 [https://bugs.python.org/issue24454].)

Match objects now support index-like objects as group indices. (Contributed by Jeroen Demeyer and Xiang Zhang in bpo-27177 [https://bugs.python.org/issue27177].)

readline

Added set_auto_history() to enable or disable automatic addition of input to the history list. (Contributed by Tyler Crompton in bpo-26870 [https://bugs.python.org/issue26870].)

rlcompleter

Private and special attribute names now are omitted unless the prefix starts with underscores. A space or a colon is added after some completed keywords. (Contributed by Serhiy Storchaka in bpo-25011 [https://bugs.python.org/issue25011] and bpo-25209 [https://bugs.python.org/issue25209].)

shlex

The shlex has much improved shell compatibility through the new punctuation_chars argument to control which characters are treated as punctuation. (Contributed by Vinay Sajip in bpo-1521950 [https://bugs.python.org/issue1521950].)

site

When specifying paths to add to sys.path in a .pth file, you may now specify file paths on top of directories (e.g. zip files). (Contributed by Wolfgang Langner in bpo-26587 [https://bugs.python.org/issue26587]).

sqlite3

sqlite3.Cursor.lastrowid now supports the REPLACE statement. (Contributed by Alex LordThorsen in bpo-16864 [https://bugs.python.org/issue16864].)

socket

The ioctl() function now supports the SIO_LOOPBACK_FAST_PATH control code. (Contributed by Daniel Stokes in bpo-26536 [https://bugs.python.org/issue26536].)

The getsockopt() constants SO_DOMAIN, SO_PROTOCOL, SO_PEERSEC, and SO_PASSSEC are now supported. (Contributed by Christian Heimes in bpo-26907 [https://bugs.python.org/issue26907].)

The setsockopt() now supports the setsockopt(level, optname, None, optlen: int) form. (Contributed by Christian Heimes in bpo-27744 [https://bugs.python.org/issue27744].)

The socket module now supports the address family AF_ALG to interface with Linux Kernel crypto API. ALG_*, SOL_ALG and sendmsg_afalg() were added. (Contributed by Christian Heimes in bpo-27744 [https://bugs.python.org/issue27744] with support from Victor Stinner.)

New Linux constants TCP_USER_TIMEOUT and TCP_CONGESTION were added. (Contributed by Omar Sandoval, issue:26273).

socketserver

Servers based on the socketserver module, including those defined in http.server, xmlrpc.server and wsgiref.simple_server, now support the context manager protocol. (Contributed by Aviv Palivoda in bpo-26404 [https://bugs.python.org/issue26404].)

The wfile attribute of StreamRequestHandler classes now implements the io.BufferedIOBase writable interface. In particular, calling write() is now guaranteed to send the data in full. (Contributed by Martin Panter in bpo-26721 [https://bugs.python.org/issue26721].)

ssl

ssl supports OpenSSL 1.1.0. The minimum recommend version is 1.0.2. (Contributed by Christian Heimes in bpo-26470 [https://bugs.python.org/issue26470].)

3DES has been removed from the default cipher suites and ChaCha20 Poly1305 cipher suites have been added. (Contributed by Christian Heimes in bpo-27850 [https://bugs.python.org/issue27850] and bpo-27766 [https://bugs.python.org/issue27766].)

SSLContext has better default configuration for options and ciphers. (Contributed by Christian Heimes in bpo-28043 [https://bugs.python.org/issue28043].)

SSL session can be copied from one client-side connection to another with the new SSLSession class. TLS session resumption can speed up the initial handshake, reduce latency and improve performance (Contributed by Christian Heimes in bpo-19500 [https://bugs.python.org/issue19500] based on a draft by Alex Warhawk.)

The new get_ciphers() method can be used to get a list of enabled ciphers in order of cipher priority.

All constants and flags have been converted to IntEnum and IntFlags. (Contributed by Christian Heimes in bpo-28025 [https://bugs.python.org/issue28025].)

Server and client-side specific TLS protocols for SSLContext were added. (Contributed by Christian Heimes in bpo-28085 [https://bugs.python.org/issue28085].)

Added SSLContext.post_handshake_auth to enable and ssl.SSLSocket.verify_client_post_handshake() to initiate TLS 1.3 post-handshake authentication. (Contributed by Christian Heimes in bpo-34670 [https://bugs.python.org/issue34670].)

statistics

A new harmonic_mean() function has been added. (Contributed by Steven D’Aprano in bpo-27181 [https://bugs.python.org/issue27181].)

struct

struct now supports IEEE 754 half-precision floats via the 'e' format specifier. (Contributed by Eli Stevens, Mark Dickinson in bpo-11734 [https://bugs.python.org/issue11734].)

subprocess

subprocess.Popen destructor now emits a ResourceWarning warning if the child process is still running. Use the context manager protocol (with proc: ...) or explicitly call the wait() method to read the exit status of the child process. (Contributed by Victor Stinner in bpo-26741 [https://bugs.python.org/issue26741].)

The subprocess.Popen constructor and all functions that pass arguments through to it now accept encoding and errors arguments. Specifying either of these will enable text mode for the stdin, stdout and stderr streams. (Contributed by Steve Dower in bpo-6135 [https://bugs.python.org/issue6135].)

sys

The new getfilesystemencodeerrors() function returns the name of the error mode used to convert between Unicode filenames and bytes filenames. (Contributed by Steve Dower in bpo-27781 [https://bugs.python.org/issue27781].)

On Windows the return value of the getwindowsversion() function now includes the platform_version field which contains the accurate major version, minor version and build number of the current operating system, rather than the version that is being emulated for the process (Contributed by Steve Dower in bpo-27932 [https://bugs.python.org/issue27932].)

telnetlib

Telnet is now a context manager (contributed by Stéphane Wirtel in bpo-25485 [https://bugs.python.org/issue25485]).

time

The struct_time attributes tm_gmtoff and tm_zone are now available on all platforms.

timeit

The new Timer.autorange() convenience method has been added to call Timer.timeit() repeatedly so that the total run time is greater or equal to 200 milliseconds. (Contributed by Steven D’Aprano in bpo-6422 [https://bugs.python.org/issue6422].)

timeit now warns when there is substantial (4x) variance between best and worst times. (Contributed by Serhiy Storchaka in bpo-23552 [https://bugs.python.org/issue23552].)

tkinter

Added methods trace_add(), trace_remove() and trace_info() in the tkinter.Variable class. They replace old methods trace_variable(), trace(), trace_vdelete() and trace_vinfo() that use obsolete Tcl commands and might not work in future versions of Tcl. (Contributed by Serhiy Storchaka in bpo-22115 [https://bugs.python.org/issue22115]).

traceback

Both the traceback module and the interpreter’s builtin exception display now abbreviate long sequences of repeated lines in tracebacks as shown in the following example:

>>> def f(): f()
...
>>> f()
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "<stdin>", line 1, in f
  File "<stdin>", line 1, in f
  File "<stdin>", line 1, in f
  [Previous line repeated 995 more times]
RecursionError: maximum recursion depth exceeded

(Contributed by Emanuel Barry in bpo-26823 [https://bugs.python.org/issue26823].)

tracemalloc

The tracemalloc module now supports tracing memory allocations in multiple different address spaces.

The new DomainFilter filter class has been added to filter block traces by their address space (domain).

(Contributed by Victor Stinner in bpo-26588 [https://bugs.python.org/issue26588].)

typing

Since the typing module is provisional, all changes introduced in Python 3.6 have also been backported to Python 3.5.x.

The typing module has a much improved support for generic type aliases. For example Dict[str, Tuple[S, T]] is now a valid type annotation. (Contributed by Guido van Rossum in Github #195 [https://github.com/python/typing/pull/195].)

The typing.ContextManager class has been added for representing contextlib.AbstractContextManager. (Contributed by Brett Cannon in bpo-25609 [https://bugs.python.org/issue25609].)

The typing.Collection class has been added for representing collections.abc.Collection. (Contributed by Ivan Levkivskyi in bpo-27598 [https://bugs.python.org/issue27598].)

The typing.ClassVar type construct has been added to mark class variables. As introduced in PEP 526 [https://www.python.org/dev/peps/pep-0526], a variable annotation wrapped in ClassVar indicates that a given attribute is intended to be used as a class variable and should not be set on instances of that class. (Contributed by Ivan Levkivskyi in Github #280 [https://github.com/python/typing/pull/280].)

A new TYPE_CHECKING constant that is assumed to be True by the static type chekers, but is False at runtime. (Contributed by Guido van Rossum in Github #230 [https://github.com/python/typing/issues/230].)

A new NewType() helper function has been added to create lightweight distinct types for annotations:

from typing import NewType

UserId = NewType('UserId', int)
some_id = UserId(524313)

The static type checker will treat the new type as if it were a subclass of the original type. (Contributed by Ivan Levkivskyi in Github #189 [https://github.com/python/typing/issues/189].)

unicodedata

The unicodedata module now uses data from Unicode 9.0.0 [http://unicode.org/versions/Unicode9.0.0/]. (Contributed by Benjamin Peterson.)

unittest.mock

The Mock class has the following improvements:

Two new methods, Mock.assert_called() and Mock.assert_called_once() to check if the mock object was called. (Contributed by Amit Saha in bpo-26323 [https://bugs.python.org/issue26323].)

The Mock.reset_mock() method now has two optional keyword only arguments: return_value and side_effect. (Contributed by Kushal Das in bpo-21271 [https://bugs.python.org/issue21271].)

urllib.request

If a HTTP request has a file or iterable body (other than a bytes object) but no Content-Length header, rather than throwing an error, AbstractHTTPHandler now falls back to use chunked transfer encoding. (Contributed by Demian Brecht and Rolf Krahl in bpo-12319 [https://bugs.python.org/issue12319].)

urllib.robotparser

RobotFileParser now supports the Crawl-delay and Request-rate extensions. (Contributed by Nikolay Bogoychev in bpo-16099 [https://bugs.python.org/issue16099].)

venv

venv accepts a new parameter --prompt. This parameter provides an alternative prefix for the virtual environment. (Proposed by Łukasz Balcerzak and ported to 3.6 by Stéphane Wirtel in bpo-22829 [https://bugs.python.org/issue22829].)

warnings

A new optional source parameter has been added to the warnings.warn_explicit() function: the destroyed object which emitted a ResourceWarning. A source attribute has also been added to warnings.WarningMessage (contributed by Victor Stinner in bpo-26568 [https://bugs.python.org/issue26568] and bpo-26567 [https://bugs.python.org/issue26567]).

When a ResourceWarning warning is logged, the tracemalloc module is now used to try to retrieve the traceback where the destroyed object was allocated.

Example with the script example.py:

import warnings

def func():
    return open(__file__)

f = func()
f = None

Output of the command python3.6 -Wd -X tracemalloc=5 example.py:

example.py:7: ResourceWarning: unclosed file <_io.TextIOWrapper name='example.py' mode='r' encoding='UTF-8'>
  f = None
Object allocated at (most recent call first):
  File "example.py", lineno 4
    return open(__file__)
  File "example.py", lineno 6
    f = func()

The « Object allocated at » traceback is new and is only displayed if tracemalloc is tracing Python memory allocations and if the warnings module was already imported.

winreg

Added the 64-bit integer type REG_QWORD. (Contributed by Clement Rouault in bpo-23026 [https://bugs.python.org/issue23026].)

winsound

Allowed keyword arguments to be passed to Beep, MessageBeep, and PlaySound (bpo-27982 [https://bugs.python.org/issue27982]).

xmlrpc.client

The xmlrpc.client module now supports unmarshalling additional data types used by the Apache XML-RPC implementation for numerics and None. (Contributed by Serhiy Storchaka in bpo-26885 [https://bugs.python.org/issue26885].)

zipfile

A new ZipInfo.from_file() class method allows making a ZipInfo instance from a filesystem file. A new ZipInfo.is_dir() method can be used to check if the ZipInfo instance represents a directory. (Contributed by Thomas Kluyver in bpo-26039 [https://bugs.python.org/issue26039].)

The ZipFile.open() method can now be used to write data into a ZIP file, as well as for extracting data. (Contributed by Thomas Kluyver in bpo-26039 [https://bugs.python.org/issue26039].)

zlib

The compress() and decompress() functions now accept keyword arguments. (Contributed by Aviv Palivoda in bpo-26243 [https://bugs.python.org/issue26243] and Xiang Zhang in bpo-16764 [https://bugs.python.org/issue16764] respectively.)

Optimizations

The Python interpreter now uses a 16-bit wordcode instead of bytecode which made a number of opcode optimizations possible. (Contributed by Demur Rumed with input and reviews from Serhiy Storchaka and Victor Stinner in bpo-26647 [https://bugs.python.org/issue26647] and bpo-28050 [https://bugs.python.org/issue28050].)

The asyncio.Future class now has an optimized C implementation. (Contributed by Yury Selivanov and INADA Naoki in bpo-26081 [https://bugs.python.org/issue26081].)

The asyncio.Task class now has an optimized C implementation. (Contributed by Yury Selivanov in bpo-28544 [https://bugs.python.org/issue28544].)

Various implementation improvements in the typing module (such as caching of generic types) allow up to 30 times performance improvements and reduced memory footprint.

The ASCII decoder is now up to 60 times as fast for error handlers surrogateescape, ignore and replace (Contributed by Victor Stinner in bpo-24870 [https://bugs.python.org/issue24870]).

The ASCII and the Latin1 encoders are now up to 3 times as fast for the error handler surrogateescape (Contributed by Victor Stinner in bpo-25227 [https://bugs.python.org/issue25227]).

The UTF-8 encoder is now up to 75 times as fast for error handlers ignore, replace, surrogateescape, surrogatepass (Contributed by Victor Stinner in bpo-25267 [https://bugs.python.org/issue25267]).

The UTF-8 decoder is now up to 15 times as fast for error handlers ignore, replace and surrogateescape (Contributed by Victor Stinner in bpo-25301 [https://bugs.python.org/issue25301]).

bytes % args is now up to 2 times faster. (Contributed by Victor Stinner in bpo-25349 [https://bugs.python.org/issue25349]).

bytearray % args is now between 2.5 and 5 times faster. (Contributed by Victor Stinner in bpo-25399 [https://bugs.python.org/issue25399]).

Optimize bytes.fromhex() and bytearray.fromhex(): they are now between 2x and 3.5x faster. (Contributed by Victor Stinner in bpo-25401 [https://bugs.python.org/issue25401]).

Optimize bytes.replace(b'', b'.') and bytearray.replace(b'', b'.'): up to 80% faster. (Contributed by Josh Snider in bpo-26574 [https://bugs.python.org/issue26574]).

Allocator functions of the PyMem_Malloc() domain (PYMEM_DOMAIN_MEM) now use the pymalloc memory allocator instead of malloc() function of the C library. The pymalloc allocator is optimized for objects smaller or equal to 512 bytes with a short lifetime, and use malloc() for larger memory blocks. (Contributed by Victor Stinner in bpo-26249 [https://bugs.python.org/issue26249]).

pickle.load() and pickle.loads() are now up to 10% faster when deserializing many small objects (Contributed by Victor Stinner in bpo-27056 [https://bugs.python.org/issue27056]).

Passing keyword arguments to a function has an overhead in comparison with passing positional arguments. Now in extension functions implemented with using Argument Clinic this overhead is significantly decreased. (Contributed by Serhiy Storchaka in bpo-27574 [https://bugs.python.org/issue27574]).

Optimized glob() and iglob() functions in the glob module; they are now about 3–6 times faster. (Contributed by Serhiy Storchaka in bpo-25596 [https://bugs.python.org/issue25596]).

Optimized globbing in pathlib by using os.scandir(); it is now about 1.5–4 times faster. (Contributed by Serhiy Storchaka in bpo-26032 [https://bugs.python.org/issue26032]).

xml.etree.ElementTree parsing, iteration and deepcopy performance has been significantly improved. (Contributed by Serhiy Storchaka in bpo-25638 [https://bugs.python.org/issue25638], bpo-25873 [https://bugs.python.org/issue25873], and bpo-25869 [https://bugs.python.org/issue25869].)

Creation of fractions.Fraction instances from floats and decimals is now 2 to 3 times faster. (Contributed by Serhiy Storchaka in bpo-25971 [https://bugs.python.org/issue25971].)

Build and C API Changes

Python now requires some C99 support in the toolchain to build. Most notably, Python now uses standard integer types and macros in place of custom macros like PY_LONG_LONG. For more information, see PEP 7 [https://www.python.org/dev/peps/pep-0007] and bpo-17884 [https://bugs.python.org/issue17884].

Cross-compiling CPython with the Android NDK and the Android API level set to 21 (Android 5.0 Lollipop) or greater runs successfully. While Android is not yet a supported platform, the Python test suite runs on the Android emulator with only about 16 tests failures. See the Android meta-issue bpo-26865 [https://bugs.python.org/issue26865].

The --enable-optimizations configure flag has been added. Turning it on will activate expensive optimizations like PGO. (Original patch by Alecsandru Patrascu of Intel in bpo-26359 [https://bugs.python.org/issue26359].)

The GIL must now be held when allocator functions of PYMEM_DOMAIN_OBJ (ex: PyObject_Malloc()) and PYMEM_DOMAIN_MEM (ex: PyMem_Malloc()) domains are called.

New Py_FinalizeEx() API which indicates if flushing buffered data failed. (Contributed by Martin Panter in bpo-5319 [https://bugs.python.org/issue5319].)

PyArg_ParseTupleAndKeywords() now supports positional-only parameters. Positional-only parameters are defined by empty names. (Contributed by Serhiy Storchaka in bpo-26282 [https://bugs.python.org/issue26282]).

PyTraceback_Print method now abbreviates long sequences of repeated lines as "[Previous line repeated {count} more times]". (Contributed by Emanuel Barry in bpo-26823 [https://bugs.python.org/issue26823].)

The new PyErr_SetImportErrorSubclass() function allows for specifying a subclass of ImportError to raise. (Contributed by Eric Snow in bpo-15767 [https://bugs.python.org/issue15767].)

The new PyErr_ResourceWarning() function can be used to generate a ResourceWarning providing the source of the resource allocation. (Contributed by Victor Stinner in bpo-26567 [https://bugs.python.org/issue26567].)

The new PyOS_FSPath() function returns the file system representation of a path-like object. (Contributed by Brett Cannon in bpo-27186 [https://bugs.python.org/issue27186].)

The PyUnicode_FSConverter() and PyUnicode_FSDecoder() functions will now accept path-like objects.

Autres Améliorations

When --version (short form: -V) is supplied twice, Python prints sys.version for detailed information.

$ ./python -VV
Python 3.6.0b4+ (3.6:223967b49e49+, Nov 21 2016, 20:55:04)
[GCC 4.2.1 Compatible Apple LLVM 8.0.0 (clang-800.0.42.1)]

Deprecated

Nouveaux mot-clefs

async and await are not recommended to be used as variable, class, function or module names. Introduced by PEP 492 [https://www.python.org/dev/peps/pep-0492] in Python 3.5, they will become proper keywords in Python 3.7. Starting in Python 3.6, the use of async or await as names will generate a DeprecationWarning.

Deprecated Python behavior

Raising the StopIteration exception inside a generator will now generate a DeprecationWarning, and will trigger a RuntimeError in Python 3.7. See PEP 479: Change StopIteration handling inside generators for details.

The __aiter__() method is now expected to return an asynchronous iterator directly instead of returning an awaitable as previously. Doing the former will trigger a DeprecationWarning. Backward compatibility will be removed in Python 3.7. (Contributed by Yury Selivanov in bpo-27243 [https://bugs.python.org/issue27243].)

A backslash-character pair that is not a valid escape sequence now generates a DeprecationWarning. Although this will eventually become a SyntaxError, that will not be for several Python releases. (Contributed by Emanuel Barry in bpo-27364 [https://bugs.python.org/issue27364].)

When performing a relative import, falling back on __name__ and __path__ from the calling module when __spec__ or __package__ are not defined now raises an ImportWarning. (Contributed by Rose Ames in bpo-25791 [https://bugs.python.org/issue25791].)

Deprecated Python modules, functions and methods

asynchat

The asynchat has been deprecated in favor of asyncio. (Contributed by Mariatta in bpo-25002 [https://bugs.python.org/issue25002].)

asyncore

The asyncore has been deprecated in favor of asyncio. (Contributed by Mariatta in bpo-25002 [https://bugs.python.org/issue25002].)

dbm

Unlike other dbm implementations, the dbm.dumb module creates databases with the 'rw' mode and allows modifying the database opened with the 'r' mode. This behavior is now deprecated and will be removed in 3.8. (Contributed by Serhiy Storchaka in bpo-21708 [https://bugs.python.org/issue21708].)

distutils

The undocumented extra_path argument to the Distribution constructor is now considered deprecated and will raise a warning if set. Support for this parameter will be removed in a future Python release. See bpo-27919 [https://bugs.python.org/issue27919] for details.

grp

The support of non-integer arguments in getgrgid() has been deprecated. (Contributed by Serhiy Storchaka in bpo-26129 [https://bugs.python.org/issue26129].)

importlib

The importlib.machinery.SourceFileLoader.load_module() and importlib.machinery.SourcelessFileLoader.load_module() methods are now deprecated. They were the only remaining implementations of importlib.abc.Loader.load_module() in importlib that had not been deprecated in previous versions of Python in favour of importlib.abc.Loader.exec_module().

The importlib.machinery.WindowsRegistryFinder class is now deprecated. As of 3.6.0, it is still added to sys.meta_path by default (on Windows), but this may change in future releases.

os

Undocumented support of general bytes-like objects as paths in os functions, compile() and similar functions is now deprecated. (Contributed by Serhiy Storchaka in bpo-25791 [https://bugs.python.org/issue25791] and bpo-26754 [https://bugs.python.org/issue26754].)

re

Support for inline flags (?letters) in the middle of the regular expression has been deprecated and will be removed in a future Python version. Flags at the start of a regular expression are still allowed. (Contributed by Serhiy Storchaka in bpo-22493 [https://bugs.python.org/issue22493].)

ssl

OpenSSL 0.9.8, 1.0.0 and 1.0.1 are deprecated and no longer supported. In the future the ssl module will require at least OpenSSL 1.0.2 or 1.1.0.

SSL-related arguments like certfile, keyfile and check_hostname in ftplib, http.client, imaplib, poplib, and smtplib have been deprecated in favor of context. (Contributed by Christian Heimes in bpo-28022 [https://bugs.python.org/issue28022].)

A couple of protocols and functions of the ssl module are now deprecated. Some features will no longer be available in future versions of OpenSSL. Other features are deprecated in favor of a different API. (Contributed by Christian Heimes in bpo-28022 [https://bugs.python.org/issue28022] and bpo-26470 [https://bugs.python.org/issue26470].)

tkinter

The tkinter.tix module is now deprecated. tkinter users should use tkinter.ttk instead.

venv

The pyvenv script has been deprecated in favour of python3 -m venv. This prevents confusion as to what Python interpreter pyvenv is connected to and thus what Python interpreter will be used by the virtual environment. (Contributed by Brett Cannon in bpo-25154 [https://bugs.python.org/issue25154].)

xml

As mitigation against DTD and external entity retrieval, the xml.dom.minidom and mod:xml.sax modules no longer process external entities by default. (Contributed by Christian Heimes in bpo-17239 [https://bugs.python.org/issue17239].)

Deprecated functions and types of the C API

Undocumented functions PyUnicode_AsEncodedObject(), PyUnicode_AsDecodedObject(), PyUnicode_AsEncodedUnicode() and PyUnicode_AsDecodedUnicode() are deprecated now. Use the generic codec based API instead.

Deprecated Build Options

The --with-system-ffi configure flag is now on by default on non-macOS UNIX platforms. It may be disabled by using --without-system-ffi, but using the flag is deprecated and will not be accepted in Python 3.7. macOS is unaffected by this change. Note that many OS distributors already use the --with-system-ffi flag when building their system Python.

Removed

API and Feature Removals

Unknown escapes consisting of '\' and an ASCII letter in regular expressions will now cause an error. In replacement templates for re.sub() they are still allowed, but deprecated. The re.LOCALE flag can now only be used with binary patterns.

inspect.getmoduleinfo() was removed (was deprecated since CPython 3.3). inspect.getmodulename() should be used for obtaining the module name for a given path. (Contributed by Yury Selivanov in bpo-13248 [https://bugs.python.org/issue13248].)

traceback.Ignore class and traceback.usage, traceback.modname, traceback.fullmodname, traceback.find_lines_from_code, traceback.find_lines, traceback.find_strings, traceback.find_executable_lines methods were removed from the traceback module. They were undocumented methods deprecated since Python 3.2 and equivalent functionality is available from private methods.

The tk_menuBar() and tk_bindForTraversal() dummy methods in tkinter widget classes were removed (corresponding Tk commands were obsolete since Tk 4.0).

The open() method of the zipfile.ZipFile class no longer supports the 'U' mode (was deprecated since Python 3.4). Use io.TextIOWrapper for reading compressed text files in universal newlines mode.

The undocumented IN, CDROM, DLFCN, TYPES, CDIO, and STROPTS modules have been removed. They had been available in the platform specific Lib/plat-*/ directories, but were chronically out of date, inconsistently available across platforms, and unmaintained. The script that created these modules is still available in the source distribution at Tools/scripts/h2py.py [https://github.com/python/cpython/tree/3.6/Tools/scripts/h2py.py].

The deprecated asynchat.fifo class has been removed.

Porting to Python 3.6

This section lists previously described changes and other bugfixes that may require changes to your code.

Changes in “python” Command Behavior

The output of a special Python build with defined COUNT_ALLOCS, SHOW_ALLOC_COUNT or SHOW_TRACK_COUNT macros is now off by default. It can be re-enabled using the -X showalloccount option. It now outputs to stderr instead of stdout. (Contributed by Serhiy Storchaka in bpo-23034 [https://bugs.python.org/issue23034].)

Changes in the Python API

open() will no longer allow combining the 'U' mode flag with '+'. (Contributed by Jeff Balogh and John O’Connor in bpo-2091 [https://bugs.python.org/issue2091].)

sqlite3 no longer implicitly commits an open transaction before DDL statements.

On Linux, os.urandom() now blocks until the system urandom entropy pool is initialized to increase the security.

When importlib.abc.Loader.exec_module() is defined, importlib.abc.Loader.create_module() must also be defined.

PyErr_SetImportError() now sets TypeError when its msg argument is not set. Previously only NULL was returned.

The format of the co_lnotab attribute of code objects changed to support a negative line number delta. By default, Python does not emit bytecode with a negative line number delta. Functions using frame.f_lineno, PyFrame_GetLineNumber() or PyCode_Addr2Line() are not affected. Functions directly decoding co_lnotab should be updated to use a signed 8-bit integer type for the line number delta, but this is only required to support applications using a negative line number delta. See Objects/lnotab_notes.txt for the co_lnotab format and how to decode it, and see the PEP 511 [https://www.python.org/dev/peps/pep-0511] for the rationale.

The functions in the compileall module now return booleans instead of 1 or 0 to represent success or failure, respectively. Thanks to booleans being a subclass of integers, this should only be an issue if you7 were doing identity checks for 1 or 0. See bpo-25768 [https://bugs.python.org/issue25768].

Reading the port attribute of urllib.parse.urlsplit() and urlparse() results now raises ValueError for out-of-range values, rather than returning None. See bpo-20059 [https://bugs.python.org/issue20059].

The imp module now raises a DeprecationWarning instead of PendingDeprecationWarning.

The following modules have had missing APIs added to their __all__ attributes to match the documented APIs: calendar, cgi, csv, ElementTree, enum, fileinput, ftplib, logging, mailbox, mimetypes, optparse, plistlib, smtpd, subprocess, tarfile, threading and wave. This means they will export new symbols when import * is used. (Contributed by Joel Taddei and Jacek Kołodziej in bpo-23883 [https://bugs.python.org/issue23883].)

When performing a relative import, if __package__ does not compare equal to __spec__.parent then ImportWarning is raised. (Contributed by Brett Cannon in bpo-25791 [https://bugs.python.org/issue25791].)

When a relative import is performed and no parent package is known, then ImportError will be raised. Previously, SystemError could be raised. (Contributed by Brett Cannon in bpo-18018 [https://bugs.python.org/issue18018].)

Servers based on the socketserver module, including those defined in http.server, xmlrpc.server and wsgiref.simple_server, now only catch exceptions derived from Exception. Therefore if a request handler raises an exception like SystemExit or KeyboardInterrupt, handle_error() is no longer called, and the exception will stop a single-threaded server. (Contributed by Martin Panter in bpo-23430 [https://bugs.python.org/issue23430].)

spwd.getspnam() now raises a PermissionError instead of KeyError if the user doesn’t have privileges.

The socket.socket.close() method now raises an exception if an error (e.g. EBADF) was reported by the underlying system call. (Contributed by Martin Panter in bpo-26685 [https://bugs.python.org/issue26685].)

The decode_data argument for the smtpd.SMTPChannel and smtpd.SMTPServer constructors is now False by default. This means that the argument passed to process_message() is now a bytes object by default, and process_message() will be passed keyword arguments. Code that has already been updated in accordance with the deprecation warning generated by 3.5 will not be affected.

All optional arguments of the dump(), dumps(), load() and loads() functions and JSONEncoder and JSONDecoder class constructors in the json module are now keyword-only. (Contributed by Serhiy Storchaka in bpo-18726 [https://bugs.python.org/issue18726].)

Les sous-classes de type qui ne redéfinissent pas type.__new__ ne devraient plus utiliser la forme à un argument pour récupérer le type d’un objet.

As part of PEP 487 [https://www.python.org/dev/peps/pep-0487], the handling of keyword arguments passed to type (other than the metaclass hint, metaclass) is now consistently delegated to object.__init_subclass__(). This means that type.__new__() and type.__init__() both now accept arbitrary keyword arguments, but object.__init_subclass__() (which is called from type.__new__()) will reject them by default. Custom metaclasses accepting additional keyword arguments will need to adjust their calls to type.__new__() (whether direct or via super) accordingly.

In distutils.command.sdist.sdist, the default_format attribute has been removed and is no longer honored. Instead, the gzipped tarfile format is the default on all platforms and no platform-specific selection is made. In environments where distributions are built on Windows and zip distributions are required, configure the project with a setup.cfg file containing the following:

[sdist]
formats=zip

This behavior has also been backported to earlier Python versions by Setuptools 26.0.0.

In the urllib.request module and the http.client.HTTPConnection.request() method, if no Content-Length header field has been specified and the request body is a file object, it is now sent with HTTP 1.1 chunked encoding. If a file object has to be sent to a HTTP 1.0 server, the Content-Length value now has to be specified by the caller. (Contributed by Demian Brecht and Rolf Krahl with tweaks from Martin Panter in bpo-12319 [https://bugs.python.org/issue12319].)

The DictReader now returns rows of type OrderedDict. (Contributed by Steve Holden in bpo-27842 [https://bugs.python.org/issue27842].)

The crypt.METHOD_CRYPT will no longer be added to crypt.methods if unsupported by the platform. (Contributed by Victor Stinner in bpo-25287 [https://bugs.python.org/issue25287].)

The verbose and rename arguments for namedtuple() are now keyword-only. (Contributed by Raymond Hettinger in bpo-25628 [https://bugs.python.org/issue25628].)

On Linux, ctypes.util.find_library() now looks in LD_LIBRARY_PATH for shared libraries. (Contributed by Vinay Sajip in bpo-9998 [https://bugs.python.org/issue9998].)

The imaplib.IMAP4 class now handles flags containing the ']' character in messages sent from the server to improve real-world compatibility. (Contributed by Lita Cho in bpo-21815 [https://bugs.python.org/issue21815].)

The mmap.write() function now returns the number of bytes written like other write methods. (Contributed by Jakub Stasiak in bpo-26335 [https://bugs.python.org/issue26335].)

The pkgutil.iter_modules() and pkgutil.walk_packages() functions now return ModuleInfo named tuples. (Contributed by Ramchandra Apte in bpo-17211 [https://bugs.python.org/issue17211].)

re.sub() now raises an error for invalid numerical group references in replacement templates even if the pattern is not found in the string. The error message for invalid group references now includes the group index and the position of the reference. (Contributed by SilentGhost, Serhiy Storchaka in bpo-25953 [https://bugs.python.org/issue25953].)

zipfile.ZipFile will now raise NotImplementedError for unrecognized compression values. Previously a plain RuntimeError was raised. Additionally, calling ZipFile methods on a closed ZipFile or calling the write() method on a ZipFile created with mode 'r' will raise a ValueError. Previously, a RuntimeError was raised in those scenarios.

when custom metaclasses are combined with zero-argument super() or direct references from methods to the implicit __class__ closure variable, the implicit __classcell__ namespace entry must now be passed up to type.__new__ for initialisation. Failing to do so will result in a DeprecationWarning in Python 3.6 and a RuntimeError in Python 3.8.

With the introduction of ModuleNotFoundError, import system consumers may start expecting import system replacements to raise that more specific exception when appropriate, rather than the less-specific ImportError. To provide future compatibility with such consumers, implementors of alternative import systems that completely replace __import__() will need to update their implementations to raise the new subclass when a module can’t be found at all. Implementors of compliant plugins to the default import system shouldn’t need to make any changes, as the default import system will raise the new subclass when appropriate.

Changes in the C API

The PyMem_Malloc() allocator family now uses the pymalloc allocator rather than the system malloc(). Applications calling PyMem_Malloc() without holding the GIL can now crash. Set the PYTHONMALLOC environment variable to debug to validate the usage of memory allocators in your application. See bpo-26249 [https://bugs.python.org/issue26249].

Py_Exit() (and the main interpreter) now override the exit status with 120 if flushing buffered data failed. See bpo-5319 [https://bugs.python.org/issue5319].

CPython bytecode changes

There have been several major changes to the bytecode in Python 3.6.

The Python interpreter now uses a 16-bit wordcode instead of bytecode. (Contributed by Demur Rumed with input and reviews from Serhiy Storchaka and Victor Stinner in bpo-26647 [https://bugs.python.org/issue26647] and bpo-28050 [https://bugs.python.org/issue28050].)

The new FORMAT_VALUE and BUILD_STRING opcodes as part of the formatted string literal implementation. (Contributed by Eric Smith in bpo-25483 [https://bugs.python.org/issue25483] and Serhiy Storchaka in bpo-27078 [https://bugs.python.org/issue27078].)

The new BUILD_CONST_KEY_MAP opcode to optimize the creation of dictionaries with constant keys. (Contributed by Serhiy Storchaka in bpo-27140 [https://bugs.python.org/issue27140].)

The function call opcodes have been heavily reworked for better performance and simpler implementation. The MAKE_FUNCTION, CALL_FUNCTION, CALL_FUNCTION_KW and BUILD_MAP_UNPACK_WITH_CALL opcodes have been modified, the new CALL_FUNCTION_EX and BUILD_TUPLE_UNPACK_WITH_CALL have been added, and CALL_FUNCTION_VAR, CALL_FUNCTION_VAR_KW and MAKE_CLOSURE opcodes have been removed. (Contributed by Demur Rumed in bpo-27095 [https://bugs.python.org/issue27095], and Serhiy Storchaka in bpo-27213 [https://bugs.python.org/issue27213], bpo-28257 [https://bugs.python.org/issue28257].)

The new SETUP_ANNOTATIONS and STORE_ANNOTATION opcodes have been added to support the new variable annotation syntax. (Contributed by Ivan Levkivskyi in bpo-27985 [https://bugs.python.org/issue27985].)

Notable changes in Python 3.6.2

New make regen-all build target

To simplify cross-compilation, and to ensure that CPython can reliably be compiled without requiring an existing version of Python to already be available, the autotools-based build system no longer attempts to implicitly recompile generated files based on file modification times.

Instead, a new make regen-all command has been added to force regeneration of these files when desired (e.g. after an initial version of Python has already been built based on the pregenerated versions).

More selective regeneration targets are also defined - see Makefile.pre.in [https://github.com/python/cpython/tree/3.6/Makefile.pre.in] for details.

(Contributed by Victor Stinner in bpo-23404 [https://bugs.python.org/issue23404].)

Nouveau dans la version 3.6.2.

Removal of make touch build target

The make touch build target previously used to request implicit regeneration of generated files by updating their modification times has been removed.

It has been replaced by the new make regen-all target.

(Contributed by Victor Stinner in bpo-23404 [https://bugs.python.org/issue23404].)

Modifié dans la version 3.6.2.

Notable changes in Python 3.6.4

The PyExc_RecursionErrorInst singleton that was part of the public API has been removed as its members being never cleared may cause a segfault during finalization of the interpreter. (Contributed by Xavier de Gaye in bpo-22898 [https://bugs.python.org/issue22898] and bpo-30697 [https://bugs.python.org/issue30697].)

Notable changes in Python 3.6.5

The locale.localeconv() function now sets temporarily the LC_CTYPE locale to the LC_NUMERIC locale in some cases. (Contributed by Victor Stinner in bpo-31900 [https://bugs.python.org/issue31900].)

Notable changes in Python 3.6.7

xml.dom.minidom and mod:xml.sax modules no longer process external entities by default. See also bpo-17239 [https://bugs.python.org/issue17239].

In 3.6.7 the tokenize module now implicitly emits a NEWLINE token when provided with input that does not have a trailing new line. This behavior now matches what the C tokenizer does internally. (Contributed by Ammar Askar in bpo-33899 [https://bugs.python.org/issue33899].)

Notable changes in Python 3.6.10

Due to significant security concerns, the reuse_address parameter of asyncio.loop.create_datagram_endpoint() is no longer supported. This is because of the behavior of the socket option SO_REUSEADDR in UDP. For more details, see the documentation for loop.create_datagram_endpoint(). (Contributed by Kyle Stanley, Antoine Pitrou, and Yury Selivanov in bpo-37228 [https://bugs.python.org/issue37228].)

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Nouveautés de Python 3.5

Editors

Elvis Pranskevichus <elvis@magic.io>, Yury Selivanov <yury@magic.io>

This article explains the new features in Python 3.5, compared to 3.4. Python 3.5 was released on September 13, 2015.  See the changelog [https://docs.python.org/3.5/whatsnew/changelog.html] for a full list of changes.

Voir aussi

PEP 478 [https://www.python.org/dev/peps/pep-0478] - Python 3.5 Release Schedule

Summary – Release highlights

New syntax features:

PEP 492, coroutines with async and await syntax.

PEP 465, a new matrix multiplication operator: a @ b.

PEP 448, additional unpacking generalizations.

New library modules:

typing: PEP 484 – Type Hints.

zipapp: PEP 441 Improving Python ZIP Application Support.

New built-in features:

bytes % args, bytearray % args: PEP 461 – Adding % formatting to bytes and bytearray.

New bytes.hex(), bytearray.hex() and memoryview.hex() methods. (Contributed by Arnon Yaari in bpo-9951 [https://bugs.python.org/issue9951].)

memoryview now supports tuple indexing (including multi-dimensional). (Contributed by Antoine Pitrou in bpo-23632 [https://bugs.python.org/issue23632].)

Generators have a new gi_yieldfrom attribute, which returns the object being iterated by yield from expressions. (Contributed by Benno Leslie and Yury Selivanov in bpo-24450 [https://bugs.python.org/issue24450].)

A new RecursionError exception is now raised when maximum recursion depth is reached. (Contributed by Georg Brandl in bpo-19235 [https://bugs.python.org/issue19235].)

CPython implementation improvements:

When the LC_TYPE locale is the POSIX locale (C locale), sys.stdin and sys.stdout now use the surrogateescape error handler, instead of the strict error handler. (Contributed by Victor Stinner in bpo-19977 [https://bugs.python.org/issue19977].)

.pyo files are no longer used and have been replaced by a more flexible scheme that includes the optimization level explicitly in .pyc name. (See PEP 488 overview.)

Builtin and extension modules are now initialized in a multi-phase process, which is similar to how Python modules are loaded. (See PEP 489 overview.)

Significant improvements in the standard library:

collections.OrderedDict is now implemented in C, which makes it 4 to 100 times faster.

The ssl module gained support for Memory BIO, which decouples SSL protocol handling from network IO.

The new os.scandir() function provides a better and significantly faster way of directory traversal.

functools.lru_cache() has been mostly reimplemented in C, yielding much better performance.

The new subprocess.run() function provides a streamlined way to run subprocesses.

The traceback module has been significantly enhanced for improved performance and developer convenience.

Security improvements:

SSLv3 is now disabled throughout the standard library. It can still be enabled by instantiating a ssl.SSLContext manually. (See bpo-22638 [https://bugs.python.org/issue22638] for more details; this change was backported to CPython 3.4 and 2.7.)

HTTP cookie parsing is now stricter, in order to protect against potential injection attacks. (Contributed by Antoine Pitrou in bpo-22796 [https://bugs.python.org/issue22796].)

Windows improvements:

A new installer for Windows has replaced the old MSI. See Utilisation de Python sur Windows for more information.

Windows builds now use Microsoft Visual C++ 14.0, and extension modules should use the same.

Please read on for a comprehensive list of user-facing changes, including many other smaller improvements, CPython optimizations, deprecations, and potential porting issues.

Nouvelles fonctionnalités

PEP 492 - Coroutines with async and await syntax

PEP 492 [https://www.python.org/dev/peps/pep-0492] greatly improves support for asynchronous programming in Python by adding awaitable objects, coroutine functions, asynchronous iteration, and asynchronous context managers.

Coroutine functions are declared using the new async def syntax:

>>> async def coro():
...     return 'spam'

Inside a coroutine function, the new await expression can be used to suspend coroutine execution until the result is available. Any object can be awaited, as long as it implements the awaitable protocol by defining the __await__() method.

PEP 492 also adds async for statement for convenient iteration over asynchronous iterables.

An example of a rudimentary HTTP client written using the new syntax:

import asyncio

async def http_get(domain):
    reader, writer = await asyncio.open_connection(domain, 80)

    writer.write(b'\r\n'.join([
        b'GET / HTTP/1.1',
        b'Host: %b' % domain.encode('latin-1'),
        b'Connection: close',
        b'', b''
    ]))

    async for line in reader:
        print('>>>', line)

    writer.close()

loop = asyncio.get_event_loop()
try:
    loop.run_until_complete(http_get('example.com'))
finally:
    loop.close()

Similarly to asynchronous iteration, there is a new syntax for asynchronous context managers. The following script:

import asyncio

async def coro(name, lock):
    print('coro {}: waiting for lock'.format(name))
    async with lock:
        print('coro {}: holding the lock'.format(name))
        await asyncio.sleep(1)
        print('coro {}: releasing the lock'.format(name))

loop = asyncio.get_event_loop()
lock = asyncio.Lock()
coros = asyncio.gather(coro(1, lock), coro(2, lock))
try:
    loop.run_until_complete(coros)
finally:
    loop.close()

affichera :

coro 2: waiting for lock
coro 2: holding the lock
coro 1: waiting for lock
coro 2: releasing the lock
coro 1: holding the lock
coro 1: releasing the lock

Note that both async for and async with can only be used inside a coroutine function declared with async def.

Coroutine functions are intended to be run inside a compatible event loop, such as the asyncio loop.

Note

Modifié dans la version 3.5.2: À partir de CPython 3.5.2, __aiter__ peut directement renvoyer des itérateurs asynchrones. Renvoyer un objet awaitable entraine un avertissement PendingDeprecationWarning.

See more details in the Itérateurs asynchrones documentation section.

Voir aussi

PEP 492 [https://www.python.org/dev/peps/pep-0492] – Coroutines with async and await syntax

PEP written and implemented by Yury Selivanov.

PEP 465 - A dedicated infix operator for matrix multiplication

PEP 465 [https://www.python.org/dev/peps/pep-0465] adds the @ infix operator for matrix multiplication. Currently, no builtin Python types implement the new operator, however, it can be implemented by defining __matmul__(), __rmatmul__(), and __imatmul__() for regular, reflected, and in-place matrix multiplication. The semantics of these methods is similar to that of methods defining other infix arithmetic operators.

Matrix multiplication is a notably common operation in many fields of mathematics, science, engineering, and the addition of @ allows writing cleaner code:

S = (H @ beta - r).T @ inv(H @ V @ H.T) @ (H @ beta - r)

instead of:

S = dot((dot(H, beta) - r).T,
        dot(inv(dot(dot(H, V), H.T)), dot(H, beta) - r))

NumPy 1.10 has support for the new operator:

>>> import numpy

>>> x = numpy.ones(3)
>>> x
array([ 1., 1., 1.])

>>> m = numpy.eye(3)
>>> m
array([[ 1., 0., 0.],
       [ 0., 1., 0.],
       [ 0., 0., 1.]])

>>> x @ m
array([ 1., 1., 1.])

Voir aussi

PEP 465 [https://www.python.org/dev/peps/pep-0465] – A dedicated infix operator for matrix multiplication

PEP written by Nathaniel J. Smith; implemented by Benjamin Peterson.

PEP 448 - Additional Unpacking Generalizations

PEP 448 [https://www.python.org/dev/peps/pep-0448] extends the allowed uses of the * iterable unpacking operator and ** dictionary unpacking operator. It is now possible to use an arbitrary number of unpackings in function calls:

>>> print(*[1], *[2], 3, *[4, 5])
1 2 3 4 5

>>> def fn(a, b, c, d):
...     print(a, b, c, d)
...

>>> fn(**{'a': 1, 'c': 3}, **{'b': 2, 'd': 4})
1 2 3 4

Similarly, tuple, list, set, and dictionary displays allow multiple unpackings (see Listes d’expressions and Agencements de dictionnaires):

>>> *range(4), 4
(0, 1, 2, 3, 4)

>>> [*range(4), 4]
[0, 1, 2, 3, 4]

>>> {*range(4), 4, *(5, 6, 7)}
{0, 1, 2, 3, 4, 5, 6, 7}

>>> {'x': 1, **{'y': 2}}
{'x': 1, 'y': 2}

Voir aussi

PEP 448 [https://www.python.org/dev/peps/pep-0448] – Additional Unpacking Generalizations

PEP written by Joshua Landau; implemented by Neil Girdhar, Thomas Wouters, and Joshua Landau.

PEP 461 - percent formatting support for bytes and bytearray

PEP 461 [https://www.python.org/dev/peps/pep-0461] adds support for the % interpolation operator to bytes and bytearray.

While interpolation is usually thought of as a string operation, there are cases where interpolation on bytes or bytearrays makes sense, and the work needed to make up for this missing functionality detracts from the overall readability of the code. This issue is particularly important when dealing with wire format protocols, which are often a mixture of binary and ASCII compatible text.

Exemples :

>>> b'Hello %b!' % b'World'
b'Hello World!'

>>> b'x=%i y=%f' % (1, 2.5)
b'x=1 y=2.500000'

Unicode is not allowed for %b, but it is accepted by %a (equivalent of repr(obj).encode('ascii', 'backslashreplace')):

>>> b'Hello %b!' % 'World'
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: %b requires bytes, or an object that implements __bytes__, not 'str'

>>> b'price: %a' % '10€'
b"price: '10\\u20ac'"

Note that %s and %r conversion types, although supported, should only be used in codebases that need compatibility with Python 2.

Voir aussi

PEP 461 [https://www.python.org/dev/peps/pep-0461] – Adding % formatting to bytes and bytearray

PEP written by Ethan Furman; implemented by Neil Schemenauer and Ethan Furman.

PEP 484 - Type Hints

Function annotation syntax has been a Python feature since version 3.0 (PEP 3107 [https://www.python.org/dev/peps/pep-3107]), however the semantics of annotations has been left undefined.

Experience has shown that the majority of function annotation uses were to provide type hints to function parameters and return values. It became evident that it would be beneficial for Python users, if the standard library included the base definitions and tools for type annotations.

PEP 484 [https://www.python.org/dev/peps/pep-0484] introduces a provisional module to provide these standard definitions and tools, along with some conventions for situations where annotations are not available.

For example, here is a simple function whose argument and return type are declared in the annotations:

def greeting(name: str) -> str:
    return 'Hello ' + name

While these annotations are available at runtime through the usual __annotations__ attribute, no automatic type checking happens at runtime. Instead, it is assumed that a separate off-line type checker (e.g. mypy [http://mypy-lang.org]) will be used for on-demand source code analysis.

The type system supports unions, generic types, and a special type named Any which is consistent with (i.e. assignable to and from) all types.

Voir aussi

Documentation du module typing

PEP 484 [https://www.python.org/dev/peps/pep-0484] – Type Hints

PEP written by Guido van Rossum, Jukka Lehtosalo, and Łukasz Langa; implemented by Guido van Rossum.

PEP 483 [https://www.python.org/dev/peps/pep-0483] – The Theory of Type Hints

PEP écrite par Guido van Rossum

PEP 471 - os.scandir() function – a better and faster directory iterator

PEP 471 [https://www.python.org/dev/peps/pep-0471] adds a new directory iteration function, os.scandir(), to the standard library. Additionally, os.walk() is now implemented using scandir, which makes it 3 to 5 times faster on POSIX systems and 7 to 20 times faster on Windows systems. This is largely achieved by greatly reducing the number of calls to os.stat() required to walk a directory tree.

Additionally, scandir returns an iterator, as opposed to returning a list of file names, which improves memory efficiency when iterating over very large directories.

The following example shows a simple use of os.scandir() to display all the files (excluding directories) in the given path that don’t start with '.'. The entry.is_file() call will generally not make an additional system call:

for entry in os.scandir(path):
    if not entry.name.startswith('.') and entry.is_file():
        print(entry.name)

Voir aussi

PEP 471 [https://www.python.org/dev/peps/pep-0471] – os.scandir() function – a better and faster directory iterator

PEP written and implemented by Ben Hoyt with the help of Victor Stinner.

PEP 475: Retry system calls failing with EINTR

An errno.EINTR error code is returned whenever a system call, that is waiting for I/O, is interrupted by a signal. Previously, Python would raise InterruptedError in such cases. This meant that, when writing a Python application, the developer had two choices:

Ignore the InterruptedError.

Handle the InterruptedError and attempt to restart the interrupted system call at every call site.

The first option makes an application fail intermittently. The second option adds a large amount of boilerplate that makes the code nearly unreadable. Compare:

print("Hello World")

et  :

while True:
    try:
        print("Hello World")
        break
    except InterruptedError:
        continue

PEP 475 [https://www.python.org/dev/peps/pep-0475] implements automatic retry of system calls on EINTR. This removes the burden of dealing with EINTR or InterruptedError in user code in most situations and makes Python programs, including the standard library, more robust. Note that the system call is only retried if the signal handler does not raise an exception.

Below is a list of functions which are now retried when interrupted by a signal:

open() et io.open();

functions of the faulthandler module;

os functions: fchdir(), fchmod(), fchown(), fdatasync(), fstat(), fstatvfs(), fsync(), ftruncate(), mkfifo(), mknod(), open(), posix_fadvise(), posix_fallocate(), pread(), pwrite(), read(), readv(), sendfile(), wait3(), wait4(), wait(), waitid(), waitpid(), write(), writev();

special cases: os.close() and os.dup2() now ignore EINTR errors; the syscall is not retried (see the PEP for the rationale);

select functions: devpoll.poll(), epoll.poll(), kqueue.control(), poll.poll(), select();

methods of the socket class: accept(), connect() (except for non-blocking sockets), recv(), recvfrom(), recvmsg(), send(), sendall(), sendmsg(), sendto();

signal.sigtimedwait() and signal.sigwaitinfo();

time.sleep().

Voir aussi

PEP 475 [https://www.python.org/dev/peps/pep-0475] – Retry system calls failing with EINTR

PEP and implementation written by Charles-François Natali and Victor Stinner, with the help of Antoine Pitrou (the French connection).

PEP 479: Change StopIteration handling inside generators

The interaction of generators and StopIteration in Python 3.4 and earlier was sometimes surprising, and could conceal obscure bugs. Previously, StopIteration raised accidentally inside a generator function was interpreted as the end of the iteration by the loop construct driving the generator.

PEP 479 [https://www.python.org/dev/peps/pep-0479] changes the behavior of generators: when a StopIteration exception is raised inside a generator, it is replaced with a RuntimeError before it exits the generator frame. The main goal of this change is to ease debugging in the situation where an unguarded next() call raises StopIteration and causes the iteration controlled by the generator to terminate silently. This is particularly pernicious in combination with the yield from construct.

This is a backwards incompatible change, so to enable the new behavior, a __future__ import is necessary:

>>> from __future__ import generator_stop

>>> def gen():
...     next(iter([]))
...     yield
...
>>> next(gen())
Traceback (most recent call last):
  File "<stdin>", line 2, in gen
StopIteration

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
RuntimeError: generator raised StopIteration

Without a __future__ import, a PendingDeprecationWarning will be raised whenever a StopIteration exception is raised inside a generator.

Voir aussi

PEP 479 [https://www.python.org/dev/peps/pep-0479] – Change StopIteration handling inside generators

PEP written by Chris Angelico and Guido van Rossum. Implemented by Chris Angelico, Yury Selivanov and Nick Coghlan.

PEP 485: A function for testing approximate equality

PEP 485 [https://www.python.org/dev/peps/pep-0485] adds the math.isclose() and cmath.isclose() functions which tell whether two values are approximately equal or « close » to each other. Whether or not two values are considered close is determined according to given absolute and relative tolerances. Relative tolerance is the maximum allowed difference between isclose arguments, relative to the larger absolute value:

>>> import math
>>> a = 5.0
>>> b = 4.99998
>>> math.isclose(a, b, rel_tol=1e-5)
True
>>> math.isclose(a, b, rel_tol=1e-6)
False

It is also possible to compare two values using absolute tolerance, which must be a non-negative value:

>>> import math
>>> a = 5.0
>>> b = 4.99998
>>> math.isclose(a, b, abs_tol=0.00003)
True
>>> math.isclose(a, b, abs_tol=0.00001)
False

Voir aussi

PEP 485 [https://www.python.org/dev/peps/pep-0485] – Une fonction pour tester des égalités approximées

PEP written by Christopher Barker; implemented by Chris Barker and Tal Einat.

PEP 486: Make the Python Launcher aware of virtual environments

PEP 486 [https://www.python.org/dev/peps/pep-0486] makes the Windows launcher (see PEP 397 [https://www.python.org/dev/peps/pep-0397]) aware of an active virtual environment. When the default interpreter would be used and the VIRTUAL_ENV environment variable is set, the interpreter in the virtual environment will be used.

Voir aussi

PEP 486 [https://www.python.org/dev/peps/pep-0486] – Make the Python Launcher aware of virtual environments

PEP written and implemented by Paul Moore.

PEP 488 : Élimination des fichiers PYO

PEP 488 [https://www.python.org/dev/peps/pep-0488] does away with the concept of .pyo files. This means that .pyc files represent both unoptimized and optimized bytecode. To prevent the need to constantly regenerate bytecode files, .pyc files now have an optional opt- tag in their name when the bytecode is optimized. This has the side-effect of no more bytecode file name clashes when running under either -O or -OO. Consequently, bytecode files generated from -O, and -OO may now exist simultaneously. importlib.util.cache_from_source() has an updated API to help with this change.

Voir aussi

PEP 488 [https://www.python.org/dev/peps/pep-0488] : Élimination des fichiers PYO

PEP written and implemented by Brett Cannon.

PEP 489: Multi-phase extension module initialization

PEP 489 [https://www.python.org/dev/peps/pep-0489] updates extension module initialization to take advantage of the two step module loading mechanism introduced by PEP 451 [https://www.python.org/dev/peps/pep-0451] in Python 3.4.

This change brings the import semantics of extension modules that opt-in to using the new mechanism much closer to those of Python source and bytecode modules, including the ability to use any valid identifier as a module name, rather than being restricted to ASCII.

Voir aussi

PEP 489 [https://www.python.org/dev/peps/pep-0489] – Multi-phase extension module initialization

PEP written by Petr Viktorin, Stefan Behnel, and Nick Coghlan; implemented by Petr Viktorin.

Other Language Changes

Some smaller changes made to the core Python language are:

Added the "namereplace" error handlers. The "backslashreplace" error handlers now work with decoding and translating. (Contributed by Serhiy Storchaka in bpo-19676 [https://bugs.python.org/issue19676] and bpo-22286 [https://bugs.python.org/issue22286].)

The -b option now affects comparisons of bytes with int. (Contributed by Serhiy Storchaka in bpo-23681 [https://bugs.python.org/issue23681].)

New Kazakh kz1048 and Tajik koi8_t codecs. (Contributed by Serhiy Storchaka in bpo-22682 [https://bugs.python.org/issue22682] and bpo-22681 [https://bugs.python.org/issue22681].)

Property docstrings are now writable. This is especially useful for collections.namedtuple() docstrings. (Contributed by Berker Peksag in bpo-24064 [https://bugs.python.org/issue24064].)

Circular imports involving relative imports are now supported. (Contributed by Brett Cannon and Antoine Pitrou in bpo-17636 [https://bugs.python.org/issue17636].)

New Modules

typing

The new typing provisional module provides standard definitions and tools for function type annotations. See Type Hints for more information.

zipapp

The new zipapp module (specified in PEP 441 [https://www.python.org/dev/peps/pep-0441]) provides an API and command line tool for creating executable Python Zip Applications, which were introduced in Python 2.6 in bpo-1739468 [https://bugs.python.org/issue1739468], but which were not well publicized, either at the time or since.

With the new module, bundling your application is as simple as putting all the files, including a __main__.py file, into a directory myapp and running:

$ python -m zipapp myapp
$ python myapp.pyz

The module implementation has been contributed by Paul Moore in bpo-23491 [https://bugs.python.org/issue23491].

Voir aussi

PEP 441 [https://www.python.org/dev/peps/pep-0441] – Improving Python ZIP Application Support

Improved Modules

argparse

The ArgumentParser class now allows disabling abbreviated usage of long options by setting Le paramètre allow_abbrev to False. (Contributed by Jonathan Paugh, Steven Bethard, paul j3 and Daniel Eriksson in bpo-14910 [https://bugs.python.org/issue14910].)

asyncio

Since the asyncio module is provisional, all changes introduced in Python 3.5 have also been backported to Python 3.4.x.

Notable changes in the asyncio module since Python 3.4.0:

New debugging APIs: loop.set_debug() and loop.get_debug() methods. (Contributed by Victor Stinner.)

The proactor event loop now supports SSL. (Contributed by Antoine Pitrou and Victor Stinner in bpo-22560 [https://bugs.python.org/issue22560].)

A new loop.is_closed() method to check if the event loop is closed. (Contributed by Victor Stinner in bpo-21326 [https://bugs.python.org/issue21326].)

A new loop.create_task() to conveniently create and schedule a new Task for a coroutine. The create_task method is also used by all asyncio functions that wrap coroutines into tasks, such as asyncio.wait(), asyncio.gather(), etc. (Contributed by Victor Stinner.)

A new transport.get_write_buffer_limits() method to inquire for high- and low- water limits of the flow control. (Contributed by Victor Stinner.)

The async() function is deprecated in favor of ensure_future(). (Contributed by Yury Selivanov.)

New loop.set_task_factory() and loop.get_task_factory() methods to customize the task factory that loop.create_task() method uses. (Contributed by Yury Selivanov.)

New Queue.join() and Queue.task_done() queue methods. (Contributed by Victor Stinner.)

The JoinableQueue class was removed, in favor of the asyncio.Queue class. (Contributed by Victor Stinner.)

Nouveautés dans la 3.5.1 :

The ensure_future() function and all functions that use it, such as loop.run_until_complete(), now accept all kinds of awaitable objects. (Contributed by Yury Selivanov.)

New run_coroutine_threadsafe() function to submit coroutines to event loops from other threads. (Contributed by Vincent Michel.)

New Transport.is_closing() method to check if the transport is closing or closed. (Contributed by Yury Selivanov.)

The loop.create_server() method can now accept a list of hosts. (Contributed by Yann Sionneau.)

Updates in 3.5.2:

New loop.create_future() method to create Future objects. This allows alternative event loop implementations, such as uvloop [https://github.com/MagicStack/uvloop], to provide a faster asyncio.Future implementation. (Contributed by Yury Selivanov.)

New loop.get_exception_handler() method to get the current exception handler. (Contributed by Yury Selivanov.)

New StreamReader.readuntil() method to read data from the stream until a separator bytes sequence appears. (Contributed by Mark Korenberg.)

The loop.create_connection() and loop.create_server() methods are optimized to avoid calling the system getaddrinfo function if the address is already resolved. (Contributed by A. Jesse Jiryu Davis.)

The loop.sock_connect(sock, address) no longer requires the address to be resolved prior to the call. (Contributed by A. Jesse Jiryu Davis.)

bz2

The BZ2Decompressor.decompress method now accepts an optional max_length argument to limit the maximum size of decompressed data. (Contributed by Nikolaus Rath in bpo-15955 [https://bugs.python.org/issue15955].)

cgi

The FieldStorage class now supports the context manager protocol. (Contributed by Berker Peksag in bpo-20289 [https://bugs.python.org/issue20289].)

cmath

A new function isclose() provides a way to test for approximate equality. (Contributed by Chris Barker and Tal Einat in bpo-24270 [https://bugs.python.org/issue24270].)

code

The InteractiveInterpreter.showtraceback() method now prints the full chained traceback, just like the interactive interpreter. (Contributed by Claudiu Popa in bpo-17442 [https://bugs.python.org/issue17442].)

collections

The OrderedDict class is now implemented in C, which makes it 4 to 100 times faster. (Contributed by Eric Snow in bpo-16991 [https://bugs.python.org/issue16991].)

OrderedDict.items(), OrderedDict.keys(), OrderedDict.values() views now support reversed() iteration. (Contributed by Serhiy Storchaka in bpo-19505 [https://bugs.python.org/issue19505].)

The deque class now defines index(), insert(), and copy(), and supports the + and * operators. This allows deques to be recognized as a MutableSequence and improves their substitutability for lists. (Contributed by Raymond Hettinger in bpo-23704 [https://bugs.python.org/issue23704].)

Docstrings produced by namedtuple() can now be updated:

Point = namedtuple('Point', ['x', 'y'])
Point.__doc__ += ': Cartesian coodinate'
Point.x.__doc__ = 'abscissa'
Point.y.__doc__ = 'ordinate'

(Contributed by Berker Peksag in bpo-24064 [https://bugs.python.org/issue24064].)

The UserString class now implements the __getnewargs__(), __rmod__(), casefold(), format_map(), isprintable(), and maketrans() methods to match the corresponding methods of str. (Contributed by Joe Jevnik in bpo-22189 [https://bugs.python.org/issue22189].)

collections.abc

The Sequence.index() method now accepts start and stop arguments to match the corresponding methods of tuple, list, etc. (Contributed by Devin Jeanpierre in bpo-23086 [https://bugs.python.org/issue23086].)

A new Generator abstract base class. (Contributed by Stefan Behnel in bpo-24018 [https://bugs.python.org/issue24018].)

New Awaitable, Coroutine, AsyncIterator, and AsyncIterable abstract base classes. (Contributed by Yury Selivanov in bpo-24184 [https://bugs.python.org/issue24184].)

For earlier Python versions, a backport of the new ABCs is available in an external PyPI package [https://pypi.org/project/backports_abc].

compileall

A new compileall option, -j N, allows running N workers simultaneously to perform parallel bytecode compilation. The compile_dir() function has a corresponding workers parameter. (Contributed by Claudiu Popa in bpo-16104 [https://bugs.python.org/issue16104].)

Another new option, -r, allows controlling the maximum recursion level for subdirectories. (Contributed by Claudiu Popa in bpo-19628 [https://bugs.python.org/issue19628].)

The -q command line option can now be specified more than once, in which case all output, including errors, will be suppressed. The corresponding quiet parameter in compile_dir(), compile_file(), and compile_path() can now accept an integer value indicating the level of output suppression. (Contributed by Thomas Kluyver in bpo-21338 [https://bugs.python.org/issue21338].)

concurrent.futures

The Executor.map() method now accepts a chunksize argument to allow batching of tasks to improve performance when ProcessPoolExecutor() is used. (Contributed by Dan O’Reilly in bpo-11271 [https://bugs.python.org/issue11271].)

The number of workers in the ThreadPoolExecutor constructor is optional now. The default value is 5 times the number of CPUs. (Contributed by Claudiu Popa in bpo-21527 [https://bugs.python.org/issue21527].)

configparser

configparser now provides a way to customize the conversion of values by specifying a dictionary of converters in the ConfigParser constructor, or by defining them as methods in ConfigParser subclasses. Converters defined in a parser instance are inherited by its section proxies.

Exemple :

>>> import configparser
>>> conv = {}
>>> conv['list'] = lambda v: [e.strip() for e in v.split() if e.strip()]
>>> cfg = configparser.ConfigParser(converters=conv)
>>> cfg.read_string("""
... [s]
... list = a b c d e f g
... """)
>>> cfg.get('s', 'list')
'a b c d e f g'
>>> cfg.getlist('s', 'list')
['a', 'b', 'c', 'd', 'e', 'f', 'g']
>>> section = cfg['s']
>>> section.getlist('list')
['a', 'b', 'c', 'd', 'e', 'f', 'g']

(Contributed by Łukasz Langa in bpo-18159 [https://bugs.python.org/issue18159].)

contextlib

The new redirect_stderr() context manager (similar to redirect_stdout()) makes it easier for utility scripts to handle inflexible APIs that write their output to sys.stderr and don’t provide any options to redirect it:

>>> import contextlib, io, logging
>>> f = io.StringIO()
>>> with contextlib.redirect_stderr(f):
...     logging.warning('warning')
...
>>> f.getvalue()
'WARNING:root:warning\n'

(Contributed by Berker Peksag in bpo-22389 [https://bugs.python.org/issue22389].)

csv

The writerow() method now supports arbitrary iterables, not just sequences. (Contributed by Serhiy Storchaka in bpo-23171 [https://bugs.python.org/issue23171].)

curses

The new update_lines_cols() function updates the LINES and COLS environment variables. This is useful for detecting manual screen resizing. (Contributed by Arnon Yaari in bpo-4254 [https://bugs.python.org/issue4254].)

dbm

dumb.open always creates a new database when the flag has the value "n". (Contributed by Claudiu Popa in bpo-18039 [https://bugs.python.org/issue18039].)

difflib

The charset of HTML documents generated by HtmlDiff.make_file() can now be customized by using a new charset keyword-only argument. The default charset of HTML document changed from "ISO-8859-1" to "utf-8". (Contributed by Berker Peksag in bpo-2052 [https://bugs.python.org/issue2052].)

The diff_bytes() function can now compare lists of byte strings. This fixes a regression from Python 2. (Contributed by Terry J. Reedy and Greg Ward in bpo-17445 [https://bugs.python.org/issue17445].)

distutils

Both the build and build_ext commands now accept a -j option to enable parallel building of extension modules. (Contributed by Antoine Pitrou in bpo-5309 [https://bugs.python.org/issue5309].)

The distutils module now supports xz compression, and can be enabled by passing xztar as an argument to bdist --format. (Contributed by Serhiy Storchaka in bpo-16314 [https://bugs.python.org/issue16314].)

doctest

The DocTestSuite() function returns an empty unittest.TestSuite if module contains no docstrings, instead of raising ValueError. (Contributed by Glenn Jones in bpo-15916 [https://bugs.python.org/issue15916].)

email

A new policy option Policy.mangle_from_ controls whether or not lines that start with "From " in email bodies are prefixed with a ">" character by generators. The default is True for compat32 and False for all other policies. (Contributed by Milan Oberkirch in bpo-20098 [https://bugs.python.org/issue20098].)

A new Message.get_content_disposition() method provides easy access to a canonical value for the Content-Disposition header. (Contributed by Abhilash Raj in bpo-21083 [https://bugs.python.org/issue21083].)

A new policy option EmailPolicy.utf8 can be set to True to encode email headers using the UTF-8 charset instead of using encoded words. This allows Messages to be formatted according to RFC 6532 [https://tools.ietf.org/html/rfc6532.html] and used with an SMTP server that supports the RFC 6531 [https://tools.ietf.org/html/rfc6531.html] SMTPUTF8 extension. (Contributed by R. David Murray in bpo-24211 [https://bugs.python.org/issue24211].)

The mime.text.MIMEText constructor now accepts a charset.Charset instance. (Contributed by Claude Paroz and Berker Peksag in bpo-16324 [https://bugs.python.org/issue16324].)

enum

The Enum callable has a new parameter start to specify the initial number of enum values if only names are provided:

>>> Animal = enum.Enum('Animal', 'cat dog', start=10)
>>> Animal.cat
<Animal.cat: 10>
>>> Animal.dog
<Animal.dog: 11>

(Contributed by Ethan Furman in bpo-21706 [https://bugs.python.org/issue21706].)

faulthandler

The enable(), register(), dump_traceback() and dump_traceback_later() functions now accept file descriptors in addition to file-like objects. (Contributed by Wei Wu in bpo-23566 [https://bugs.python.org/issue23566].)

functools

Most of the lru_cache() machinery is now implemented in C, making it significantly faster. (Contributed by Matt Joiner, Alexey Kachayev, and Serhiy Storchaka in bpo-14373 [https://bugs.python.org/issue14373].)

glob

The iglob() and glob() functions now support recursive search in subdirectories, using the "**" pattern. (Contributed by Serhiy Storchaka in bpo-13968 [https://bugs.python.org/issue13968].)

gzip

The mode argument of the GzipFile constructor now accepts "x" to request exclusive creation. (Contributed by Tim Heaney in bpo-19222 [https://bugs.python.org/issue19222].)

heapq

Element comparison in merge() can now be customized by passing a key function in a new optional key keyword argument, and a new optional reverse keyword argument can be used to reverse element comparison:

>>> import heapq
>>> a = ['9', '777', '55555']
>>> b = ['88', '6666']
>>> list(heapq.merge(a, b, key=len))
['9', '88', '777', '6666', '55555']
>>> list(heapq.merge(reversed(a), reversed(b), key=len, reverse=True))
['55555', '6666', '777', '88', '9']

(Contributed by Raymond Hettinger in bpo-13742 [https://bugs.python.org/issue13742].)

http

A new HTTPStatus enum that defines a set of HTTP status codes, reason phrases and long descriptions written in English. (Contributed by Demian Brecht in bpo-21793 [https://bugs.python.org/issue21793].)

http.client

HTTPConnection.getresponse() now raises a RemoteDisconnected exception when a remote server connection is closed unexpectedly. Additionally, if a ConnectionError (of which RemoteDisconnected is a subclass) is raised, the client socket is now closed automatically, and will reconnect on the next request:

import http.client
conn = http.client.HTTPConnection('www.python.org')
for retries in range(3):
    try:
        conn.request('GET', '/')
        resp = conn.getresponse()
    except http.client.RemoteDisconnected:
        pass

(Contributed by Martin Panter in bpo-3566 [https://bugs.python.org/issue3566].)

idlelib and IDLE

Since idlelib implements the IDLE shell and editor and is not intended for import by other programs, it gets improvements with every release. See Lib/idlelib/NEWS.txt for a cumulative list of changes since 3.4.0, as well as changes made in future 3.5.x releases. This file is also available from the IDLE Help ‣ About IDLE dialog.

imaplib

The IMAP4 class now supports the context manager protocol. When used in a with statement, the IMAP4 LOGOUT command will be called automatically at the end of the block. (Contributed by Tarek Ziadé and Serhiy Storchaka in bpo-4972 [https://bugs.python.org/issue4972].)

The imaplib module now supports RFC 5161 [https://tools.ietf.org/html/rfc5161.html] (ENABLE Extension) and RFC 6855 [https://tools.ietf.org/html/rfc6855.html] (UTF-8 Support) via the IMAP4.enable() method. A new IMAP4.utf8_enabled attribute tracks whether or not RFC 6855 [https://tools.ietf.org/html/rfc6855.html] support is enabled. (Contributed by Milan Oberkirch, R. David Murray, and Maciej Szulik in bpo-21800 [https://bugs.python.org/issue21800].)

The imaplib module now automatically encodes non-ASCII string usernames and passwords using UTF-8, as recommended by the RFCs. (Contributed by Milan Oberkirch in bpo-21800 [https://bugs.python.org/issue21800].)

imghdr

The what() function now recognizes the OpenEXR [http://www.openexr.com] format (contributed by Martin Vignali and Claudiu Popa in bpo-20295 [https://bugs.python.org/issue20295]), and the WebP [https://en.wikipedia.org/wiki/WebP] format (contributed by Fabrice Aneche and Claudiu Popa in bpo-20197 [https://bugs.python.org/issue20197].)

importlib

The util.LazyLoader class allows for lazy loading of modules in applications where startup time is important. (Contributed by Brett Cannon in bpo-17621 [https://bugs.python.org/issue17621].)

The abc.InspectLoader.source_to_code() method is now a static method. This makes it easier to initialize a module object with code compiled from a string by running exec(code, module.__dict__). (Contributed by Brett Cannon in bpo-21156 [https://bugs.python.org/issue21156].)

The new util.module_from_spec() function is now the preferred way to create a new module. As opposed to creating a types.ModuleType instance directly, this new function will set the various import-controlled attributes based on the passed-in spec object. (Contributed by Brett Cannon in bpo-20383 [https://bugs.python.org/issue20383].)

inspect

Both the Signature and Parameter classes are now picklable and hashable. (Contributed by Yury Selivanov in bpo-20726 [https://bugs.python.org/issue20726] and bpo-20334 [https://bugs.python.org/issue20334].)

A new BoundArguments.apply_defaults() method provides a way to set default values for missing arguments:

>>> def foo(a, b='ham', *args): pass
>>> ba = inspect.signature(foo).bind('spam')
>>> ba.apply_defaults()
>>> ba.arguments
OrderedDict([('a', 'spam'), ('b', 'ham'), ('args', ())])

(Contributed by Yury Selivanov in bpo-24190 [https://bugs.python.org/issue24190].)

A new class method Signature.from_callable() makes subclassing of Signature easier. (Contributed by Yury Selivanov and Eric Snow in bpo-17373 [https://bugs.python.org/issue17373].)

The signature() function now accepts a follow_wrapped optional keyword argument, which, when set to False, disables automatic following of __wrapped__ links. (Contributed by Yury Selivanov in bpo-20691 [https://bugs.python.org/issue20691].)

A set of new functions to inspect coroutine functions and coroutine objects has been added: iscoroutine(), iscoroutinefunction(), isawaitable(), getcoroutinelocals(), and getcoroutinestate(). (Contributed by Yury Selivanov in bpo-24017 [https://bugs.python.org/issue24017] and bpo-24400 [https://bugs.python.org/issue24400].)

The stack(), trace(), getouterframes(), and getinnerframes() functions now return a list of named tuples. (Contributed by Daniel Shahaf in bpo-16808 [https://bugs.python.org/issue16808].)

io

A new BufferedIOBase.readinto1() method, that uses at most one call to the underlying raw stream’s RawIOBase.read() or RawIOBase.readinto() methods. (Contributed by Nikolaus Rath in bpo-20578 [https://bugs.python.org/issue20578].)

ipaddress

Both the IPv4Network and IPv6Network classes now accept an (address, netmask) tuple argument, so as to easily construct network objects from existing addresses:

>>> import ipaddress
>>> ipaddress.IPv4Network(('127.0.0.0', 8))
IPv4Network('127.0.0.0/8')
>>> ipaddress.IPv4Network(('127.0.0.0', '255.0.0.0'))
IPv4Network('127.0.0.0/8')

(Contributed by Peter Moody and Antoine Pitrou in bpo-16531 [https://bugs.python.org/issue16531].)

A new reverse_pointer attribute for the IPv4Network and IPv6Network classes returns the name of the reverse DNS PTR record:

>>> import ipaddress
>>> addr = ipaddress.IPv4Address('127.0.0.1')
>>> addr.reverse_pointer
'1.0.0.127.in-addr.arpa'
>>> addr6 = ipaddress.IPv6Address('::1')
>>> addr6.reverse_pointer
'1.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.ip6.arpa'

(Contributed by Leon Weber in bpo-20480 [https://bugs.python.org/issue20480].)

json

The json.tool command line interface now preserves the order of keys in JSON objects passed in input. The new --sort-keys option can be used to sort the keys alphabetically. (Contributed by Berker Peksag in bpo-21650 [https://bugs.python.org/issue21650].)

JSON decoder now raises JSONDecodeError instead of ValueError to provide better context information about the error. (Contributed by Serhiy Storchaka in bpo-19361 [https://bugs.python.org/issue19361].)

linecache

A new lazycache() function can be used to capture information about a non-file-based module to permit getting its lines later via getline(). This avoids doing I/O until a line is actually needed, without having to carry the module globals around indefinitely. (Contributed by Robert Collins in bpo-17911 [https://bugs.python.org/issue17911].)

locale

A new delocalize() function can be used to convert a string into a normalized number string, taking the LC_NUMERIC settings into account:

>>> import locale
>>> locale.setlocale(locale.LC_NUMERIC, 'de_DE.UTF-8')
'de_DE.UTF-8'
>>> locale.delocalize('1.234,56')
'1234.56'
>>> locale.setlocale(locale.LC_NUMERIC, 'en_US.UTF-8')
'en_US.UTF-8'
>>> locale.delocalize('1,234.56')
'1234.56'

(Contributed by Cédric Krier in bpo-13918 [https://bugs.python.org/issue13918].)

logging

All logging methods (Logger log(), exception(), critical(), debug(), etc.), now accept exception instances as an exc_info argument, in addition to boolean values and exception tuples:

>>> import logging
>>> try:
...     1/0
... except ZeroDivisionError as ex:
...     logging.error('exception', exc_info=ex)
ERROR:root:exception

(Contributed by Yury Selivanov in bpo-20537 [https://bugs.python.org/issue20537].)

The handlers.HTTPHandler class now accepts an optional ssl.SSLContext instance to configure SSL settings used in an HTTP connection. (Contributed by Alex Gaynor in bpo-22788 [https://bugs.python.org/issue22788].)

The handlers.QueueListener class now takes a respect_handler_level keyword argument which, if set to True, will pass messages to handlers taking handler levels into account. (Contributed by Vinay Sajip.)

lzma

The LZMADecompressor.decompress() method now accepts an optional max_length argument to limit the maximum size of decompressed data. (Contributed by Martin Panter in bpo-15955 [https://bugs.python.org/issue15955].)

math

Two new constants have been added to the math module: inf and nan. (Contributed by Mark Dickinson in bpo-23185 [https://bugs.python.org/issue23185].)

A new function isclose() provides a way to test for approximate equality. (Contributed by Chris Barker and Tal Einat in bpo-24270 [https://bugs.python.org/issue24270].)

A new gcd() function has been added. The fractions.gcd() function is now deprecated. (Contributed by Mark Dickinson and Serhiy Storchaka in bpo-22486 [https://bugs.python.org/issue22486].)

multiprocessing

sharedctypes.synchronized() objects now support the context manager protocol. (Contributed by Charles-François Natali in bpo-21565 [https://bugs.python.org/issue21565].)

operator

attrgetter(), itemgetter(), and methodcaller() objects now support pickling. (Contributed by Josh Rosenberg and Serhiy Storchaka in bpo-22955 [https://bugs.python.org/issue22955].)

New matmul() and imatmul() functions to perform matrix multiplication. (Contributed by Benjamin Peterson in bpo-21176 [https://bugs.python.org/issue21176].)

os

The new scandir() function returning an iterator of DirEntry objects has been added. If possible, scandir() extracts file attributes while scanning a directory, removing the need to perform subsequent system calls to determine file type or attributes, which may significantly improve performance. (Contributed by Ben Hoyt with the help of Victor Stinner in bpo-22524 [https://bugs.python.org/issue22524].)

On Windows, a new stat_result.st_file_attributes attribute is now available. It corresponds to the dwFileAttributes member of the BY_HANDLE_FILE_INFORMATION structure returned by GetFileInformationByHandle(). (Contributed by Ben Hoyt in bpo-21719 [https://bugs.python.org/issue21719].)

The urandom() function now uses the getrandom() syscall on Linux 3.17 or newer, and getentropy() on OpenBSD 5.6 and newer, removing the need to use /dev/urandom and avoiding failures due to potential file descriptor exhaustion. (Contributed by Victor Stinner in bpo-22181 [https://bugs.python.org/issue22181].)

New get_blocking() and set_blocking() functions allow getting and setting a file descriptor’s blocking mode (O_NONBLOCK.) (Contributed by Victor Stinner in bpo-22054 [https://bugs.python.org/issue22054].)

The truncate() and ftruncate() functions are now supported on Windows. (Contributed by Steve Dower in bpo-23668 [https://bugs.python.org/issue23668].)

There is a new os.path.commonpath() function returning the longest common sub-path of each passed pathname. Unlike the os.path.commonprefix() function, it always returns a valid path:

>>> os.path.commonprefix(['/usr/lib', '/usr/local/lib'])
'/usr/l'

>>> os.path.commonpath(['/usr/lib', '/usr/local/lib'])
'/usr'

(Contributed by Rafik Draoui and Serhiy Storchaka in bpo-10395 [https://bugs.python.org/issue10395].)

pathlib

The new Path.samefile() method can be used to check whether the path points to the same file as another path, which can be either another Path object, or a string:

>>> import pathlib
>>> p1 = pathlib.Path('/etc/hosts')
>>> p2 = pathlib.Path('/etc/../etc/hosts')
>>> p1.samefile(p2)
True

(Contributed by Vajrasky Kok and Antoine Pitrou in bpo-19775 [https://bugs.python.org/issue19775].)

The Path.mkdir() method now accepts a new optional exist_ok argument to match mkdir -p and os.makedirs() functionality. (Contributed by Berker Peksag in bpo-21539 [https://bugs.python.org/issue21539].)

There is a new Path.expanduser() method to expand ~ and ~user prefixes. (Contributed by Serhiy Storchaka and Claudiu Popa in bpo-19776 [https://bugs.python.org/issue19776].)

A new Path.home() class method can be used to get a Path instance representing the user’s home directory. (Contributed by Victor Salgado and Mayank Tripathi in bpo-19777 [https://bugs.python.org/issue19777].)

New Path.write_text(), Path.read_text(), Path.write_bytes(), Path.read_bytes() methods to simplify read/write operations on files.

The following code snippet will create or rewrite existing file ~/spam42:

>>> import pathlib
>>> p = pathlib.Path('~/spam42')
>>> p.expanduser().write_text('ham')
3

(Contributed by Christopher Welborn in bpo-20218 [https://bugs.python.org/issue20218].)

pickle

Nested objects, such as unbound methods or nested classes, can now be pickled using pickle protocols older than protocol version 4. Protocol version 4 already supports these cases. (Contributed by Serhiy Storchaka in bpo-23611 [https://bugs.python.org/issue23611].)

poplib

A new POP3.utf8() command enables RFC 6856 [https://tools.ietf.org/html/rfc6856.html] (Internationalized Email) support, if a POP server supports it. (Contributed by Milan OberKirch in bpo-21804 [https://bugs.python.org/issue21804].)

re

References and conditional references to groups with fixed length are now allowed in lookbehind assertions:

>>> import re
>>> pat = re.compile(r'(a|b).(?<=\1)c')
>>> pat.match('aac')
<_sre.SRE_Match object; span=(0, 3), match='aac'>
>>> pat.match('bbc')
<_sre.SRE_Match object; span=(0, 3), match='bbc'>

(Contribution par Serhiy Storchaka; bpo-9179 [https://bugs.python.org/issue9179].)

The number of capturing groups in regular expressions is no longer limited to 100. (Contributed by Serhiy Storchaka in bpo-22437 [https://bugs.python.org/issue22437].)

The sub() and subn() functions now replace unmatched groups with empty strings instead of raising an exception. (Contributed by Serhiy Storchaka in bpo-1519638 [https://bugs.python.org/issue1519638].)

The re.error exceptions have new attributes, msg, pattern, pos, lineno, and colno, that provide better context information about the error:

>>> re.compile("""
...     (?x)
...     .++
... """)
Traceback (most recent call last):
   ...
sre_constants.error: multiple repeat at position 16 (line 3, column 7)

(Contribution par Serhiy Storchaka; bpo-22578 [https://bugs.python.org/issue22578].)

readline

A new append_history_file() function can be used to append the specified number of trailing elements in history to the given file. (Contributed by Bruno Cauet in bpo-22940 [https://bugs.python.org/issue22940].)

selectors

The new DevpollSelector supports efficient /dev/poll polling on Solaris. (Contributed by Giampaolo Rodola” in bpo-18931 [https://bugs.python.org/issue18931].)

shutil

The move() function now accepts a copy_function argument, allowing, for example, the copy() function to be used instead of the default copy2() if there is a need to ignore file metadata when moving. (Contributed by Claudiu Popa in bpo-19840 [https://bugs.python.org/issue19840].)

The make_archive() function now supports the xztar format. (Contributed by Serhiy Storchaka in bpo-5411 [https://bugs.python.org/issue5411].)

signal

On Windows, the set_wakeup_fd() function now also supports socket handles. (Contributed by Victor Stinner in bpo-22018 [https://bugs.python.org/issue22018].)

Various SIG* constants in the signal module have been converted into Enums. This allows meaningful names to be printed during debugging, instead of integer « magic numbers ». (Contributed by Giampaolo Rodola” in bpo-21076 [https://bugs.python.org/issue21076].)

smtpd

Both the SMTPServer and SMTPChannel classes now accept a decode_data keyword argument to determine if the DATA portion of the SMTP transaction is decoded using the "utf-8" codec or is instead provided to the SMTPServer.process_message() method as a byte string. The default is True for backward compatibility reasons, but will change to False in Python 3.6. If decode_data is set to False, the process_message method must be prepared to accept keyword arguments. (Contributed by Maciej Szulik in bpo-19662 [https://bugs.python.org/issue19662].)

The SMTPServer class now advertises the 8BITMIME extension (RFC 6152 [https://tools.ietf.org/html/rfc6152.html]) if decode_data has been set True. If the client specifies BODY=8BITMIME on the MAIL command, it is passed to SMTPServer.process_message() via the mail_options keyword. (Contributed by Milan Oberkirch and R. David Murray in bpo-21795 [https://bugs.python.org/issue21795].)

The SMTPServer class now also supports the SMTPUTF8 extension (RFC 6531 [https://tools.ietf.org/html/rfc6531.html]: Internationalized Email). If the client specified SMTPUTF8 BODY=8BITMIME on the MAIL command, they are passed to SMTPServer.process_message() via the mail_options keyword. It is the responsibility of the process_message method to correctly handle the SMTPUTF8 data. (Contributed by Milan Oberkirch in bpo-21725 [https://bugs.python.org/issue21725].)

It is now possible to provide, directly or via name resolution, IPv6 addresses in the SMTPServer constructor, and have it successfully connect. (Contributed by Milan Oberkirch in bpo-14758 [https://bugs.python.org/issue14758].)

smtplib

A new SMTP.auth() method provides a convenient way to implement custom authentication mechanisms. (Contributed by Milan Oberkirch in bpo-15014 [https://bugs.python.org/issue15014].)

The SMTP.set_debuglevel() method now accepts an additional debuglevel (2), which enables timestamps in debug messages. (Contributed by Gavin Chappell and Maciej Szulik in bpo-16914 [https://bugs.python.org/issue16914].)

Both the SMTP.sendmail() and SMTP.send_message() methods now support RFC 6531 [https://tools.ietf.org/html/rfc6531.html] (SMTPUTF8). (Contributed by Milan Oberkirch and R. David Murray in bpo-22027 [https://bugs.python.org/issue22027].)

sndhdr

The what() and whathdr() functions now return a namedtuple(). (Contributed by Claudiu Popa in bpo-18615 [https://bugs.python.org/issue18615].)

socket

Functions with timeouts now use a monotonic clock, instead of a system clock. (Contributed by Victor Stinner in bpo-22043 [https://bugs.python.org/issue22043].)

A new socket.sendfile() method allows sending a file over a socket by using the high-performance os.sendfile() function on UNIX, resulting in uploads being from 2 to 3 times faster than when using plain socket.send(). (Contributed by Giampaolo Rodola” in bpo-17552 [https://bugs.python.org/issue17552].)

The socket.sendall() method no longer resets the socket timeout every time bytes are received or sent. The socket timeout is now the maximum total duration to send all data. (Contributed by Victor Stinner in bpo-23853 [https://bugs.python.org/issue23853].)

The backlog argument of the socket.listen() method is now optional. By default it is set to SOMAXCONN or to 128, whichever is less. (Contributed by Charles-François Natali in bpo-21455 [https://bugs.python.org/issue21455].)

ssl

Memory BIO Support

(Contributed by Geert Jansen in bpo-21965 [https://bugs.python.org/issue21965].)

The new SSLObject class has been added to provide SSL protocol support for cases when the network I/O capabilities of SSLSocket are not necessary or are suboptimal. SSLObject represents an SSL protocol instance, but does not implement any network I/O methods, and instead provides a memory buffer interface. The new MemoryBIO class can be used to pass data between Python and an SSL protocol instance.

The memory BIO SSL support is primarily intended to be used in frameworks implementing asynchronous I/O for which SSLSocket’s readiness model (« select/poll ») is inefficient.

A new SSLContext.wrap_bio() method can be used to create a new SSLObject instance.

Application-Layer Protocol Negotiation Support

(Contributed by Benjamin Peterson in bpo-20188 [https://bugs.python.org/issue20188].)

Where OpenSSL support is present, the ssl module now implements the Application-Layer Protocol Negotiation TLS extension as described in RFC 7301 [https://tools.ietf.org/html/rfc7301.html].

The new SSLContext.set_alpn_protocols() can be used to specify which protocols a socket should advertise during the TLS handshake.

The new SSLSocket.selected_alpn_protocol() returns the protocol that was selected during the TLS handshake. The HAS_ALPN flag indicates whether ALPN support is present.

Other Changes

There is a new SSLSocket.version() method to query the actual protocol version in use. (Contributed by Antoine Pitrou in bpo-20421 [https://bugs.python.org/issue20421].)

The SSLSocket class now implements a SSLSocket.sendfile() method. (Contributed by Giampaolo Rodola” in bpo-17552 [https://bugs.python.org/issue17552].)

The SSLSocket.send() method now raises either the ssl.SSLWantReadError or ssl.SSLWantWriteError exception on a non-blocking socket if the operation would block. Previously, it would return 0. (Contributed by Nikolaus Rath in bpo-20951 [https://bugs.python.org/issue20951].)

The cert_time_to_seconds() function now interprets the input time as UTC and not as local time, per RFC 5280 [https://tools.ietf.org/html/rfc5280.html]. Additionally, the return value is always an int. (Contributed by Akira Li in bpo-19940 [https://bugs.python.org/issue19940].)

New SSLObject.shared_ciphers() and SSLSocket.shared_ciphers() methods return the list of ciphers sent by the client during the handshake. (Contributed by Benjamin Peterson in bpo-23186 [https://bugs.python.org/issue23186].)

The SSLSocket.do_handshake(), SSLSocket.read(), SSLSocket.shutdown(), and SSLSocket.write() methods of the SSLSocket class no longer reset the socket timeout every time bytes are received or sent. The socket timeout is now the maximum total duration of the method. (Contributed by Victor Stinner in bpo-23853 [https://bugs.python.org/issue23853].)

The match_hostname() function now supports matching of IP addresses. (Contributed by Antoine Pitrou in bpo-23239 [https://bugs.python.org/issue23239].)

sqlite3

The Row class now fully supports the sequence protocol, in particular reversed() iteration and slice indexing. (Contributed by Claudiu Popa in bpo-10203 [https://bugs.python.org/issue10203]; by Lucas Sinclair, Jessica McKellar, and Serhiy Storchaka in bpo-13583 [https://bugs.python.org/issue13583].)

subprocess

The new run() function has been added. It runs the specified command and returns a CompletedProcess object, which describes a finished process. The new API is more consistent and is the recommended approach to invoking subprocesses in Python code that does not need to maintain compatibility with earlier Python versions. (Contributed by Thomas Kluyver in bpo-23342 [https://bugs.python.org/issue23342].)

Exemples :

>>> subprocess.run(["ls", "-l"])  # doesn't capture output
CompletedProcess(args=['ls', '-l'], returncode=0)

>>> subprocess.run("exit 1", shell=True, check=True)
Traceback (most recent call last):
  ...
subprocess.CalledProcessError: Command 'exit 1' returned non-zero exit status 1

>>> subprocess.run(["ls", "-l", "/dev/null"], stdout=subprocess.PIPE)
CompletedProcess(args=['ls', '-l', '/dev/null'], returncode=0,
stdout=b'crw-rw-rw- 1 root root 1, 3 Jan 23 16:23 /dev/null\n')

sys

A new set_coroutine_wrapper() function allows setting a global hook that will be called whenever a coroutine object is created by an async def function. A corresponding get_coroutine_wrapper() can be used to obtain a currently set wrapper. Both functions are provisional, and are intended for debugging purposes only. (Contributed by Yury Selivanov in bpo-24017 [https://bugs.python.org/issue24017].)

A new is_finalizing() function can be used to check if the Python interpreter is shutting down. (Contributed by Antoine Pitrou in bpo-22696 [https://bugs.python.org/issue22696].)

sysconfig

The name of the user scripts directory on Windows now includes the first two components of the Python version. (Contributed by Paul Moore in bpo-23437 [https://bugs.python.org/issue23437].)

tarfile

The mode argument of the open() function now accepts "x" to request exclusive creation. (Contributed by Berker Peksag in bpo-21717 [https://bugs.python.org/issue21717].)

The TarFile.extractall() and TarFile.extract() methods now take a keyword argument numeric_owner. If set to True, the extracted files and directories will be owned by the numeric uid and gid from the tarfile. If set to False (the default, and the behavior in versions prior to 3.5), they will be owned by the named user and group in the tarfile. (Contributed by Michael Vogt and Eric Smith in bpo-23193 [https://bugs.python.org/issue23193].)

The TarFile.list() now accepts an optional members keyword argument that can be set to a subset of the list returned by TarFile.getmembers(). (Contributed by Serhiy Storchaka in bpo-21549 [https://bugs.python.org/issue21549].)

threading

Both the Lock.acquire() and RLock.acquire() methods now use a monotonic clock for timeout management. (Contributed by Victor Stinner in bpo-22043 [https://bugs.python.org/issue22043].)

time

The monotonic() function is now always available. (Contributed by Victor Stinner in bpo-22043 [https://bugs.python.org/issue22043].)

timeit

A new command line option -u or --unit=U can be used to specify the time unit for the timer output. Supported options are usec, msec, or sec. (Contributed by Julian Gindi in bpo-18983 [https://bugs.python.org/issue18983].)

The timeit() function has a new globals parameter for specifying the namespace in which the code will be running. (Contributed by Ben Roberts in bpo-2527 [https://bugs.python.org/issue2527].)

tkinter

The tkinter._fix module used for setting up the Tcl/Tk environment on Windows has been replaced by a private function in the _tkinter module which makes no permanent changes to environment variables. (Contributed by Zachary Ware in bpo-20035 [https://bugs.python.org/issue20035].)

traceback

New walk_stack() and walk_tb() functions to conveniently traverse frame and traceback objects. (Contributed by Robert Collins in bpo-17911 [https://bugs.python.org/issue17911].)

New lightweight classes: TracebackException, StackSummary, and FrameSummary. (Contributed by Robert Collins in bpo-17911 [https://bugs.python.org/issue17911].)

Both the print_tb() and print_stack() functions now support negative values for the limit argument. (Contributed by Dmitry Kazakov in bpo-22619 [https://bugs.python.org/issue22619].)

types

A new coroutine() function to transform generator and generator-like objects into awaitables. (Contributed by Yury Selivanov in bpo-24017 [https://bugs.python.org/issue24017].)

A new type called CoroutineType, which is used for coroutine objects created by async def functions. (Contributed by Yury Selivanov in bpo-24400 [https://bugs.python.org/issue24400].)

unicodedata

The unicodedata module now uses data from Unicode 8.0.0 [http://unicode.org/versions/Unicode8.0.0/].

unittest

The TestLoader.loadTestsFromModule() method now accepts a keyword-only argument pattern which is passed to load_tests as the third argument. Found packages are now checked for load_tests regardless of whether their path matches pattern, because it is impossible for a package name to match the default pattern. (Contributed by Robert Collins and Barry A. Warsaw in bpo-16662 [https://bugs.python.org/issue16662].)

Unittest discovery errors now are exposed in the TestLoader.errors attribute of the TestLoader instance. (Contributed by Robert Collins in bpo-19746 [https://bugs.python.org/issue19746].)

A new command line option --locals to show local variables in tracebacks. (Contributed by Robert Collins in bpo-22936 [https://bugs.python.org/issue22936].)

unittest.mock

The Mock class has the following improvements:

The class constructor has a new unsafe parameter, which causes mock objects to raise AttributeError on attribute names starting with "assert". (Contributed by Kushal Das in bpo-21238 [https://bugs.python.org/issue21238].)

A new Mock.assert_not_called() method to check if the mock object was called. (Contributed by Kushal Das in bpo-21262 [https://bugs.python.org/issue21262].)

The MagicMock class now supports __truediv__(), __divmod__() and __matmul__() operators. (Contributed by Johannes Baiter in bpo-20968 [https://bugs.python.org/issue20968], and Håkan Lövdahl in bpo-23581 [https://bugs.python.org/issue23581] and bpo-23568 [https://bugs.python.org/issue23568].)

It is no longer necessary to explicitly pass create=True to the patch() function when patching builtin names. (Contributed by Kushal Das in bpo-17660 [https://bugs.python.org/issue17660].)

urllib

A new request.HTTPPasswordMgrWithPriorAuth class allows HTTP Basic Authentication credentials to be managed so as to eliminate unnecessary 401 response handling, or to unconditionally send credentials on the first request in order to communicate with servers that return a 404 response instead of a 401 if the Authorization header is not sent. (Contributed by Matej Cepl in bpo-19494 [https://bugs.python.org/issue19494] and Akshit Khurana in bpo-7159 [https://bugs.python.org/issue7159].)

A new quote_via argument for the parse.urlencode() function provides a way to control the encoding of query parts if needed. (Contributed by Samwyse and Arnon Yaari in bpo-13866 [https://bugs.python.org/issue13866].)

The request.urlopen() function accepts an ssl.SSLContext object as a context argument, which will be used for the HTTPS connection. (Contributed by Alex Gaynor in bpo-22366 [https://bugs.python.org/issue22366].)

The parse.urljoin() was updated to use the RFC 3986 [https://tools.ietf.org/html/rfc3986.html] semantics for the resolution of relative URLs, rather than RFC 1808 [https://tools.ietf.org/html/rfc1808.html] and RFC 2396 [https://tools.ietf.org/html/rfc2396.html]. (Contributed by Demian Brecht and Senthil Kumaran in bpo-22118 [https://bugs.python.org/issue22118].)

wsgiref

The headers argument of the headers.Headers class constructor is now optional. (Contributed by Pablo Torres Navarrete and SilentGhost in bpo-5800 [https://bugs.python.org/issue5800].)

xmlrpc

The client.ServerProxy class now supports the context manager protocol. (Contributed by Claudiu Popa in bpo-20627 [https://bugs.python.org/issue20627].)

The client.ServerProxy constructor now accepts an optional ssl.SSLContext instance. (Contributed by Alex Gaynor in bpo-22960 [https://bugs.python.org/issue22960].)

xml.sax

SAX parsers now support a character stream of the xmlreader.InputSource object. (Contributed by Serhiy Storchaka in bpo-2175 [https://bugs.python.org/issue2175].)

parseString() now accepts a str instance. (Contributed by Serhiy Storchaka in bpo-10590 [https://bugs.python.org/issue10590].)

zipfile

ZIP output can now be written to unseekable streams. (Contributed by Serhiy Storchaka in bpo-23252 [https://bugs.python.org/issue23252].)

The mode argument of ZipFile.open() method now accepts "x" to request exclusive creation. (Contributed by Serhiy Storchaka in bpo-21717 [https://bugs.python.org/issue21717].)

Other module-level changes

Many functions in the mmap, ossaudiodev, socket, ssl, and codecs modules now accept writable bytes-like objects. (Contributed by Serhiy Storchaka in bpo-23001 [https://bugs.python.org/issue23001].)

Optimizations

The os.walk() function has been sped up by 3 to 5 times on POSIX systems, and by 7 to 20 times on Windows. This was done using the new os.scandir() function, which exposes file information from the underlying readdir or FindFirstFile/FindNextFile system calls. (Contributed by Ben Hoyt with help from Victor Stinner in bpo-23605 [https://bugs.python.org/issue23605].)

Construction of bytes(int) (filled by zero bytes) is faster and uses less memory for large objects. calloc() is used instead of malloc() to allocate memory for these objects. (Contributed by Victor Stinner in bpo-21233 [https://bugs.python.org/issue21233].)

Some operations on ipaddress IPv4Network and IPv6Network have been massively sped up, such as subnets(), supernet(), summarize_address_range(), collapse_addresses(). The speed up can range from 3 to 15 times. (Contributed by Antoine Pitrou, Michel Albert, and Markus in bpo-21486 [https://bugs.python.org/issue21486], bpo-21487 [https://bugs.python.org/issue21487], bpo-20826 [https://bugs.python.org/issue20826], bpo-23266 [https://bugs.python.org/issue23266].)

Pickling of ipaddress objects was optimized to produce significantly smaller output. (Contributed by Serhiy Storchaka in bpo-23133 [https://bugs.python.org/issue23133].)

Many operations on io.BytesIO are now 50% to 100% faster. (Contributed by Serhiy Storchaka in bpo-15381 [https://bugs.python.org/issue15381] and David Wilson in bpo-22003 [https://bugs.python.org/issue22003].)

The marshal.dumps() function is now faster: 65–85% with versions 3 and 4, 20–25% with versions 0 to 2 on typical data, and up to 5 times in best cases. (Contributed by Serhiy Storchaka in bpo-20416 [https://bugs.python.org/issue20416] and bpo-23344 [https://bugs.python.org/issue23344].)

The UTF-32 encoder is now 3 to 7 times faster. (Contributed by Serhiy Storchaka in bpo-15027 [https://bugs.python.org/issue15027].)

Regular expressions are now parsed up to 10% faster. (Contributed by Serhiy Storchaka in bpo-19380 [https://bugs.python.org/issue19380].)

The json.dumps() function was optimized to run with ensure_ascii=False as fast as with ensure_ascii=True. (Contributed by Naoki Inada in bpo-23206 [https://bugs.python.org/issue23206].)

The PyObject_IsInstance() and PyObject_IsSubclass() functions have been sped up in the common case that the second argument has type as its metaclass. (Contributed Georg Brandl by in bpo-22540 [https://bugs.python.org/issue22540].)

Method caching was slightly improved, yielding up to 5% performance improvement in some benchmarks. (Contributed by Antoine Pitrou in bpo-22847 [https://bugs.python.org/issue22847].)

Objects from the random module now use 50% less memory on 64-bit builds. (Contributed by Serhiy Storchaka in bpo-23488 [https://bugs.python.org/issue23488].)

The property() getter calls are up to 25% faster. (Contributed by Joe Jevnik in bpo-23910 [https://bugs.python.org/issue23910].)

Instantiation of fractions.Fraction is now up to 30% faster. (Contributed by Stefan Behnel in bpo-22464 [https://bugs.python.org/issue22464].)

String methods find(), rfind(), split(), partition() and the in string operator are now significantly faster for searching 1-character substrings. (Contributed by Serhiy Storchaka in bpo-23573 [https://bugs.python.org/issue23573].)

Build and C API Changes

New calloc functions were added:

PyMem_RawCalloc(),

PyMem_Calloc(),

PyObject_Calloc().

(Contribution par Victor Stinner; bpo-21233 [https://bugs.python.org/issue21233].)

New encoding/decoding helper functions:

Py_DecodeLocale() (replaced _Py_char2wchar()),

Py_EncodeLocale() (replaced _Py_wchar2char()).

(Contribution par Victor Stinner; bpo-18395 [https://bugs.python.org/issue18395].)

A new PyCodec_NameReplaceErrors() function to replace the unicode encode error with \N{...} escapes. (Contributed by Serhiy Storchaka in bpo-19676 [https://bugs.python.org/issue19676].)

A new PyErr_FormatV() function similar to PyErr_Format(), but accepts a va_list argument. (Contributed by Antoine Pitrou in bpo-18711 [https://bugs.python.org/issue18711].)

A new PyExc_RecursionError exception. (Contributed by Georg Brandl in bpo-19235 [https://bugs.python.org/issue19235].)

New PyModule_FromDefAndSpec(), PyModule_FromDefAndSpec2(), and PyModule_ExecDef() functions introduced by PEP 489 [https://www.python.org/dev/peps/pep-0489] – multi-phase extension module initialization. (Contributed by Petr Viktorin in bpo-24268 [https://bugs.python.org/issue24268].)

New PyNumber_MatrixMultiply() and PyNumber_InPlaceMatrixMultiply() functions to perform matrix multiplication. (Contributed by Benjamin Peterson in bpo-21176 [https://bugs.python.org/issue21176]. See also PEP 465 [https://www.python.org/dev/peps/pep-0465] for details.)

The PyTypeObject.tp_finalize slot is now part of the stable ABI.

Windows builds now require Microsoft Visual C++ 14.0, which is available as part of Visual Studio 2015 [https://www.visualstudio.com/].

Extension modules now include a platform information tag in their filename on some platforms (the tag is optional, and CPython will import extensions without it, although if the tag is present and mismatched, the extension won’t be loaded):

On Linux, extension module filenames end with .cpython-<major><minor>m-<architecture>-<os>.pyd:

<major> is the major number of the Python version; for Python 3.5 this is 3.

<minor> is the minor number of the Python version; for Python 3.5 this is 5.

<architecture> is the hardware architecture the extension module was built to run on. It’s most commonly either i386 for 32-bit Intel platforms or x86_64 for 64-bit Intel (and AMD) platforms.

<os> is always linux-gnu, except for extensions built to talk to the 32-bit ABI on 64-bit platforms, in which case it is linux-gnu32 (and <architecture> will be x86_64).

On Windows, extension module filenames end with <debug>.cp<major><minor>-<platform>.pyd:

<major> is the major number of the Python version; for Python 3.5 this is 3.

<minor> is the minor number of the Python version; for Python 3.5 this is 5.

<platform> is the platform the extension module was built for, either win32 for Win32, win_amd64 for Win64, win_ia64 for Windows Itanium 64, and win_arm for Windows on ARM.

If built in debug mode, <debug> will be _d, otherwise it will be blank.

On OS X platforms, extension module filenames now end with -darwin.so.

On all other platforms, extension module filenames are the same as they were with Python 3.4.

Deprecated

Nouveaux mot-clefs

async and await are not recommended to be used as variable, class, function or module names. Introduced by PEP 492 [https://www.python.org/dev/peps/pep-0492] in Python 3.5, they will become proper keywords in Python 3.7.

Deprecated Python Behavior

Raising the StopIteration exception inside a generator will now generate a silent PendingDeprecationWarning, which will become a non-silent deprecation warning in Python 3.6 and will trigger a RuntimeError in Python 3.7. See PEP 479: Change StopIteration handling inside generators for details.

Unsupported Operating Systems

Windows XP is no longer supported by Microsoft, thus, per PEP 11 [https://www.python.org/dev/peps/pep-0011], CPython 3.5 is no longer officially supported on this OS.

Deprecated Python modules, functions and methods

The formatter module has now graduated to full deprecation and is still slated for removal in Python 3.6.

The asyncio.async() function is deprecated in favor of ensure_future().

The smtpd module has in the past always decoded the DATA portion of email messages using the utf-8 codec. This can now be controlled by the new decode_data keyword to SMTPServer. The default value is True, but this default is deprecated. Specify the decode_data keyword with an appropriate value to avoid the deprecation warning.

Directly assigning values to the key, value and coded_value of http.cookies.Morsel objects is deprecated. Use the set() method instead. In addition, the undocumented LegalChars parameter of set() is deprecated, and is now ignored.

Passing a format string as keyword argument format_string to the format() method of the string.Formatter class has been deprecated. (Contributed by Serhiy Storchaka in bpo-23671 [https://bugs.python.org/issue23671].)

The platform.dist() and platform.linux_distribution() functions are now deprecated. Linux distributions use too many different ways of describing themselves, so the functionality is left to a package. (Contributed by Vajrasky Kok and Berker Peksag in bpo-1322 [https://bugs.python.org/issue1322].)

The previously undocumented from_function and from_builtin methods of inspect.Signature are deprecated. Use the new Signature.from_callable() method instead. (Contributed by Yury Selivanov in bpo-24248 [https://bugs.python.org/issue24248].)

The inspect.getargspec() function is deprecated and scheduled to be removed in Python 3.6. (See bpo-20438 [https://bugs.python.org/issue20438] for details.)

The inspect getfullargspec(), getcallargs(), and formatargspec() functions are deprecated in favor of the inspect.signature() API. (Contributed by Yury Selivanov in bpo-20438 [https://bugs.python.org/issue20438].)

getargvalues() and formatargvalues() functions were inadvertently marked as deprecated with the release of Python 3.5.0.

Use of re.LOCALE flag with str patterns or re.ASCII is now deprecated. (Contributed by Serhiy Storchaka in bpo-22407 [https://bugs.python.org/issue22407].)

Use of unrecognized special sequences consisting of '\' and an ASCII letter in regular expression patterns and replacement patterns now raises a deprecation warning and will be forbidden in Python 3.6. (Contributed by Serhiy Storchaka in bpo-23622 [https://bugs.python.org/issue23622].)

The undocumented and unofficial use_load_tests default argument of the unittest.TestLoader.loadTestsFromModule() method now is deprecated and ignored. (Contributed by Robert Collins and Barry A. Warsaw in bpo-16662 [https://bugs.python.org/issue16662].)

Removed

API and Feature Removals

The following obsolete and previously deprecated APIs and features have been removed:

The __version__ attribute has been dropped from the email package. The email code hasn’t been shipped separately from the stdlib for a long time, and the __version__ string was not updated in the last few releases.

The internal Netrc class in the ftplib module was deprecated in 3.4, and has now been removed. (Contributed by Matt Chaput in bpo-6623 [https://bugs.python.org/issue6623].)

The concept of .pyo files has been removed.

The JoinableQueue class in the provisional asyncio module was deprecated in 3.4.4 and is now removed. (Contributed by A. Jesse Jiryu Davis in bpo-23464 [https://bugs.python.org/issue23464].)

Portage vers Python 3.5

This section lists previously described changes and other bugfixes that may require changes to your code.

Changes in Python behavior

Due to an oversight, earlier Python versions erroneously accepted the following syntax:

f(1 for x in [1], *args)
f(1 for x in [1], **kwargs)

Python 3.5 now correctly raises a SyntaxError, as generator expressions must be put in parentheses if not a sole argument to a function.

Changes in the Python API

PEP 475 [https://www.python.org/dev/peps/pep-0475]: System calls are now retried when interrupted by a signal instead of raising InterruptedError if the Python signal handler does not raise an exception.

Before Python 3.5, a datetime.time object was considered to be false if it represented midnight in UTC. This behavior was considered obscure and error-prone and has been removed in Python 3.5. See bpo-13936 [https://bugs.python.org/issue13936] for full details.

The ssl.SSLSocket.send() method now raises either ssl.SSLWantReadError or ssl.SSLWantWriteError on a non-blocking socket if the operation would block. Previously, it would return 0. (Contributed by Nikolaus Rath in bpo-20951 [https://bugs.python.org/issue20951].)

The __name__ attribute of generators is now set from the function name, instead of being set from the code name. Use gen.gi_code.co_name to retrieve the code name. Generators also have a new __qualname__ attribute, the qualified name, which is now used for the representation of a generator (repr(gen)). (Contributed by Victor Stinner in bpo-21205 [https://bugs.python.org/issue21205].)

The deprecated « strict » mode and argument of HTMLParser, HTMLParser.error(), and the HTMLParserError exception have been removed. (Contributed by Ezio Melotti in bpo-15114 [https://bugs.python.org/issue15114].) The convert_charrefs argument of HTMLParser is now True by default. (Contributed by Berker Peksag in bpo-21047 [https://bugs.python.org/issue21047].)

Although it is not formally part of the API, it is worth noting for porting purposes (ie: fixing tests) that error messages that were previously of the form « “sometype” does not support the buffer protocol » are now of the form « a bytes-like object is required, not “sometype” ». (Contributed by Ezio Melotti in bpo-16518 [https://bugs.python.org/issue16518].)

If the current directory is set to a directory that no longer exists then FileNotFoundError will no longer be raised and instead find_spec() will return None without caching None in sys.path_importer_cache, which is different than the typical case (bpo-22834 [https://bugs.python.org/issue22834]).

HTTP status code and messages from http.client and http.server were refactored into a common HTTPStatus enum. The values in http.client and http.server remain available for backwards compatibility. (Contributed by Demian Brecht in bpo-21793 [https://bugs.python.org/issue21793].)

When an import loader defines importlib.machinery.Loader.exec_module() it is now expected to also define create_module() (raises a DeprecationWarning now, will be an error in Python 3.6). If the loader inherits from importlib.abc.Loader then there is nothing to do, else simply define create_module() to return None. (Contributed by Brett Cannon in bpo-23014 [https://bugs.python.org/issue23014].)

The re.split() function always ignored empty pattern matches, so the "x*" pattern worked the same as "x+", and the "\b" pattern never worked. Now re.split() raises a warning if the pattern could match an empty string. For compatibility, use patterns that never match an empty string (e.g. "x+" instead of "x*"). Patterns that could only match an empty string (such as "\b") now raise an error. (Contributed by Serhiy Storchaka in bpo-22818 [https://bugs.python.org/issue22818].)

The http.cookies.Morsel dict-like interface has been made self consistent: morsel comparison now takes the key and value into account, copy() now results in a Morsel instance rather than a dict, and update() will now raise an exception if any of the keys in the update dictionary are invalid. In addition, the undocumented LegalChars parameter of set() is deprecated and is now ignored. (Contributed by Demian Brecht in bpo-2211 [https://bugs.python.org/issue2211].)

PEP 488 [https://www.python.org/dev/peps/pep-0488] has removed .pyo files from Python and introduced the optional opt- tag in .pyc file names. The importlib.util.cache_from_source() has gained an optimization parameter to help control the opt- tag. Because of this, the debug_override parameter of the function is now deprecated. .pyo files are also no longer supported as a file argument to the Python interpreter and thus serve no purpose when distributed on their own (i.e. sourceless code distribution). Due to the fact that the magic number for bytecode has changed in Python 3.5, all old .pyo files from previous versions of Python are invalid regardless of this PEP.

The socket module now exports the CAN_RAW_FD_FRAMES constant on linux 3.6 and greater.

The ssl.cert_time_to_seconds() function now interprets the input time as UTC and not as local time, per RFC 5280 [https://tools.ietf.org/html/rfc5280.html]. Additionally, the return value is always an int. (Contributed by Akira Li in bpo-19940 [https://bugs.python.org/issue19940].)

The pygettext.py Tool now uses the standard +NNNN format for timezones in the POT-Creation-Date header.

The smtplib module now uses sys.stderr instead of the previous module-level stderr variable for debug output. If your (test) program depends on patching the module-level variable to capture the debug output, you will need to update it to capture sys.stderr instead.

The str.startswith() and str.endswith() methods no longer return True when finding the empty string and the indexes are completely out of range. (Contributed by Serhiy Storchaka in bpo-24284 [https://bugs.python.org/issue24284].)

The inspect.getdoc() function now returns documentation strings inherited from base classes. Documentation strings no longer need to be duplicated if the inherited documentation is appropriate. To suppress an inherited string, an empty string must be specified (or the documentation may be filled in). This change affects the output of the pydoc module and the help() function. (Contributed by Serhiy Storchaka in bpo-15582 [https://bugs.python.org/issue15582].)

Nested functools.partial() calls are now flattened. If you were relying on the previous behavior, you can now either add an attribute to a functools.partial() object or you can create a subclass of functools.partial(). (Contributed by Alexander Belopolsky in bpo-7830 [https://bugs.python.org/issue7830].)

Changes in the C API

The undocumented format member of the (non-public) PyMemoryViewObject structure has been removed. All extensions relying on the relevant parts in memoryobject.h must be rebuilt.

The PyMemAllocator structure was renamed to PyMemAllocatorEx and a new calloc field was added.

Removed non-documented macro PyObject_REPR which leaked references. Use format character %R in PyUnicode_FromFormat()-like functions to format the repr() of the object. (Contributed by Serhiy Storchaka in bpo-22453 [https://bugs.python.org/issue22453].)

Because the lack of the __module__ attribute breaks pickling and introspection, a deprecation warning is now raised for builtin types without the __module__ attribute. This would be an AttributeError in the future. (Contributed by Serhiy Storchaka in bpo-20204 [https://bugs.python.org/issue20204].)

As part of the PEP 492 [https://www.python.org/dev/peps/pep-0492] implementation, the tp_reserved slot of PyTypeObject was replaced with a tp_as_async slot. Refer to Objets coroutines for new types, structures and functions.

Notable changes in Python 3.5.4

New make regen-all build target

To simplify cross-compilation, and to ensure that CPython can reliably be compiled without requiring an existing version of Python to already be available, the autotools-based build system no longer attempts to implicitly recompile generated files based on file modification times.

Instead, a new make regen-all command has been added to force regeneration of these files when desired (e.g. after an initial version of Python has already been built based on the pregenerated versions).

More selective regeneration targets are also defined - see Makefile.pre.in [https://github.com/python/cpython/tree/3.6/Makefile.pre.in] for details.

(Contributed by Victor Stinner in bpo-23404 [https://bugs.python.org/issue23404].)

Nouveau dans la version 3.5.4.

Removal of make touch build target

The make touch build target previously used to request implicit regeneration of generated files by updating their modification times has been removed.

It has been replaced by the new make regen-all target.

(Contributed by Victor Stinner in bpo-23404 [https://bugs.python.org/issue23404].)

Modifié dans la version 3.5.4.

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Nouveautés de Python 3.4

Auteur

R. David Murray <rdmurray@bitdance.com> (Editor)

This article explains the new features in Python 3.4, compared to 3.3. Python 3.4 was released on March 16, 2014. For full details, see the changelog [https://docs.python.org/3.4/whatsnew/changelog.html].

Voir aussi

PEP 429 [https://www.python.org/dev/peps/pep-0429] – Python 3.4 Release Schedule

Summary – Release Highlights

New syntax features:

No new syntax features were added in Python 3.4.

Other new features:

pip should always be available (PEP 453 [https://www.python.org/dev/peps/pep-0453]).

Newly created file descriptors are non-inheritable (PEP 446 [https://www.python.org/dev/peps/pep-0446]).

command line option for isolated mode (bpo-16499 [https://bugs.python.org/issue16499]).

improvements in the handling of codecs that are not text encodings (multiple issues).

A ModuleSpec Type for the Import System (PEP 451 [https://www.python.org/dev/peps/pep-0451]). (Affects importer authors.)

The marshal format has been made more compact and efficient (bpo-16475 [https://bugs.python.org/issue16475]).

New library modules:

asyncio: New provisional API for asynchronous IO (PEP 3156 [https://www.python.org/dev/peps/pep-3156]).

ensurepip: Bootstrapping the pip installer (PEP 453 [https://www.python.org/dev/peps/pep-0453]).

enum: Support for enumeration types (PEP 435 [https://www.python.org/dev/peps/pep-0435]).

pathlib: Object-oriented filesystem paths (PEP 428 [https://www.python.org/dev/peps/pep-0428]).

selectors: High-level and efficient I/O multiplexing, built upon the select module primitives (part of PEP 3156 [https://www.python.org/dev/peps/pep-3156]).

statistics: A basic numerically stable statistics library (PEP 450 [https://www.python.org/dev/peps/pep-0450]).

tracemalloc: Trace Python memory allocations (PEP 454 [https://www.python.org/dev/peps/pep-0454]).

Significantly improved library modules:

Single-dispatch generic functions in functools (PEP 443 [https://www.python.org/dev/peps/pep-0443]).

New pickle protocol 4 (PEP 3154 [https://www.python.org/dev/peps/pep-3154]).

multiprocessing now has an option to avoid using os.fork on Unix (bpo-8713 [https://bugs.python.org/issue8713]).

email has a new submodule, contentmanager, and a new Message subclass (EmailMessage) that simplify MIME handling (bpo-18891 [https://bugs.python.org/issue18891]).

The inspect and pydoc modules are now capable of correct introspection of a much wider variety of callable objects, which improves the output of the Python help() system.

The ipaddress module API has been declared stable

Security improvements:

Secure and interchangeable hash algorithm (PEP 456 [https://www.python.org/dev/peps/pep-0456]).

Make newly created file descriptors non-inheritable (PEP 446 [https://www.python.org/dev/peps/pep-0446]) to avoid leaking file descriptors to child processes.

New command line option for isolated mode, (bpo-16499 [https://bugs.python.org/issue16499]).

multiprocessing now has an option to avoid using os.fork on Unix. spawn and forkserver are more secure because they avoid sharing data with child processes.

multiprocessing child processes on Windows no longer inherit all of the parent’s inheritable handles, only the necessary ones.

A new hashlib.pbkdf2_hmac() function provides the PKCS#5 password-based key derivation function 2 [https://en.wikipedia.org/wiki/PBKDF2].

TLSv1.1 and TLSv1.2 support for ssl.

Retrieving certificates from the Windows system cert store support for ssl.

Server-side SNI (Server Name Indication) support for ssl.

The ssl.SSLContext class has a lot of improvements.

All modules in the standard library that support SSL now support server certificate verification, including hostname matching (ssl.match_hostname()) and CRLs (Certificate Revocation lists, see ssl.SSLContext.load_verify_locations()).

CPython implementation improvements:

Safe object finalization (PEP 442 [https://www.python.org/dev/peps/pep-0442]).

Leveraging PEP 442 [https://www.python.org/dev/peps/pep-0442], in most cases module globals are no longer set to None during finalization (bpo-18214 [https://bugs.python.org/issue18214]).

Configurable memory allocators (PEP 445 [https://www.python.org/dev/peps/pep-0445]).

Argument Clinic (PEP 436 [https://www.python.org/dev/peps/pep-0436]).

Please read on for a comprehensive list of user-facing changes, including many other smaller improvements, CPython optimizations, deprecations, and potential porting issues.

Nouvelles fonctionnalités

PEP 453: Explicit Bootstrapping of PIP in Python Installations

Bootstrapping pip By Default

The new ensurepip module (defined in PEP 453 [https://www.python.org/dev/peps/pep-0453]) provides a standard cross-platform mechanism to bootstrap the pip installer into Python installations and virtual environments. The version of pip included with Python 3.4.0 is pip 1.5.4, and future 3.4.x maintenance releases will update the bundled version to the latest version of pip that is available at the time of creating the release candidate.

By default, the commands pipX and pipX.Y will be installed on all platforms (where X.Y stands for the version of the Python installation), along with the pip Python package and its dependencies. On Windows and in virtual environments on all platforms, the unversioned pip command will also be installed. On other platforms, the system wide unversioned pip command typically refers to the separately installed Python 2 version.

The pyvenv command line utility and the venv module make use of the ensurepip module to make pip readily available in virtual environments. When using the command line utility, pip is installed by default, while when using the venv module API installation of pip must be requested explicitly.

For CPython source builds on POSIX systems, the make install and make altinstall commands bootstrap pip by default. This behaviour can be controlled through configure options, and overridden through Makefile options.

On Windows and Mac OS X, the CPython installers now default to installing pip along with CPython itself (users may opt out of installing it during the installation process). Window users will need to opt in to the automatic PATH modifications to have pip available from the command line by default, otherwise it can still be accessed through the Python launcher for Windows as py -m pip.

As discussed in the PEP [https://www.python.org/dev/peps/pep-0453/#recommendations-for-downstream-distributors], platform packagers may choose not to install these commands by default, as long as, when invoked, they provide clear and simple directions on how to install them on that platform (usually using the system package manager).

Note

To avoid conflicts between parallel Python 2 and Python 3 installations, only the versioned pip3 and pip3.4 commands are bootstrapped by default when ensurepip is invoked directly - the --default-pip option is needed to also request the unversioned pip command. pyvenv and the Windows installer ensure that the unqualified pip command is made available in those environments, and pip can always be invoked via the -m switch rather than directly to avoid ambiguity on systems with multiple Python installations.

Documentation Changes

As part of this change, the Installation de modules Python and Distribuer des modules Python sections of the documentation have been completely redesigned as short getting started and FAQ documents. Most packaging documentation has now been moved out to the Python Packaging Authority maintained Python Packaging User Guide [https://packaging.python.org] and the documentation of the individual projects.

However, as this migration is currently still incomplete, the legacy versions of those guides remaining available as Installation des modules python (Version historique) and Distribuer des modules Python (Version historique).

Voir aussi

PEP 453 [https://www.python.org/dev/peps/pep-0453] – Explicit bootstrapping of pip in Python installations

PEP written by Donald Stufft and Nick Coghlan, implemented by Donald Stufft, Nick Coghlan, Martin von Löwis and Ned Deily.

PEP 446: Newly Created File Descriptors Are Non-Inheritable

PEP 446 [https://www.python.org/dev/peps/pep-0446] makes newly created file descriptors non-inheritable. In general, this is the behavior an application will want: when launching a new process, having currently open files also open in the new process can lead to all sorts of hard to find bugs, and potentially to security issues.

However, there are occasions when inheritance is desired. To support these cases, the following new functions and methods are available:

os.get_inheritable(), os.set_inheritable()

os.get_handle_inheritable(), os.set_handle_inheritable()

socket.socket.get_inheritable(), socket.socket.set_inheritable()

Voir aussi

PEP 446 [https://www.python.org/dev/peps/pep-0446] – Make newly created file descriptors non-inheritable

PEP written and implemented by Victor Stinner.

Improvements to Codec Handling

Since it was first introduced, the codecs module has always been intended to operate as a type-neutral dynamic encoding and decoding system. However, its close coupling with the Python text model, especially the type restricted convenience methods on the builtin str, bytes and bytearray types, has historically obscured that fact.

As a key step in clarifying the situation, the codecs.encode() and codecs.decode() convenience functions are now properly documented in Python 2.7, 3.3 and 3.4. These functions have existed in the codecs module (and have been covered by the regression test suite) since Python 2.4, but were previously only discoverable through runtime introspection.

Unlike the convenience methods on str, bytes and bytearray, the codecs convenience functions support arbitrary codecs in both Python 2 and Python 3, rather than being limited to Unicode text encodings (in Python 3) or basestring <-> basestring conversions (in Python 2).

In Python 3.4, the interpreter is able to identify the known non-text encodings provided in the standard library and direct users towards these general purpose convenience functions when appropriate:

>>> b"abcdef".decode("hex")
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
LookupError: 'hex' is not a text encoding; use codecs.decode() to handle arbitrary codecs

>>> "hello".encode("rot13")
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
LookupError: 'rot13' is not a text encoding; use codecs.encode() to handle arbitrary codecs

>>> open("foo.txt", encoding="hex")
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
LookupError: 'hex' is not a text encoding; use codecs.open() to handle arbitrary codecs

In a related change, whenever it is feasible without breaking backwards compatibility, exceptions raised during encoding and decoding operations are wrapped in a chained exception of the same type that mentions the name of the codec responsible for producing the error:

>>> import codecs

>>> codecs.decode(b"abcdefgh", "hex")
Traceback (most recent call last):
  File "/usr/lib/python3.4/encodings/hex_codec.py", line 20, in hex_decode
    return (binascii.a2b_hex(input), len(input))
binascii.Error: Non-hexadecimal digit found

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
binascii.Error: decoding with 'hex' codec failed (Error: Non-hexadecimal digit found)

>>> codecs.encode("hello", "bz2")
Traceback (most recent call last):
  File "/usr/lib/python3.4/encodings/bz2_codec.py", line 17, in bz2_encode
    return (bz2.compress(input), len(input))
  File "/usr/lib/python3.4/bz2.py", line 498, in compress
    return comp.compress(data) + comp.flush()
TypeError: 'str' does not support the buffer interface

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: encoding with 'bz2' codec failed (TypeError: 'str' does not support the buffer interface)

Finally, as the examples above show, these improvements have permitted the restoration of the convenience aliases for the non-Unicode codecs that were themselves restored in Python 3.2. This means that encoding binary data to and from its hexadecimal representation (for example) can now be written as:

>>> from codecs import encode, decode
>>> encode(b"hello", "hex")
b'68656c6c6f'
>>> decode(b"68656c6c6f", "hex")
b'hello'

The binary and text transforms provided in the standard library are detailed in Binary Transforms and Text Transforms.

(Contributed by Nick Coghlan in bpo-7475 [https://bugs.python.org/issue7475], bpo-17827 [https://bugs.python.org/issue17827], bpo-17828 [https://bugs.python.org/issue17828] and bpo-19619 [https://bugs.python.org/issue19619].)

PEP 451: A ModuleSpec Type for the Import System

PEP 451 [https://www.python.org/dev/peps/pep-0451] provides an encapsulation of the information about a module that the import machinery will use to load it (that is, a module specification). This helps simplify both the import implementation and several import-related APIs. The change is also a stepping stone for several future import-related improvements [https://mail.python.org/pipermail/python-dev/2013-November/130111.html].

The public-facing changes from the PEP are entirely backward-compatible. Furthermore, they should be transparent to everyone but importer authors. Key finder and loader methods have been deprecated, but they will continue working. New importers should use the new methods described in the PEP. Existing importers should be updated to implement the new methods. See the Deprecated section for a list of methods that should be replaced and their replacements.

Other Language Changes

Some smaller changes made to the core Python language are:

Unicode database updated to UCD version 6.3.

min() and max() now accept a default keyword-only argument that can be used to specify the value they return if the iterable they are evaluating has no elements. (Contributed by Julian Berman in bpo-18111 [https://bugs.python.org/issue18111].)

Module objects are now weakref’able.

Module __file__ attributes (and related values) should now always contain absolute paths by default, with the sole exception of __main__.__file__ when a script has been executed directly using a relative path. (Contributed by Brett Cannon in bpo-18416 [https://bugs.python.org/issue18416].)

All the UTF-* codecs (except UTF-7) now reject surrogates during both encoding and decoding unless the surrogatepass error handler is used, with the exception of the UTF-16 decoder (which accepts valid surrogate pairs) and the UTF-16 encoder (which produces them while encoding non-BMP characters). (Contributed by Victor Stinner, Kang-Hao (Kenny) Lu and Serhiy Storchaka in bpo-12892 [https://bugs.python.org/issue12892].)

New German EBCDIC codec cp273. (Contributed by Michael Bierenfeld and Andrew Kuchling in bpo-1097797 [https://bugs.python.org/issue1097797].)

New Ukrainian codec cp1125. (Contributed by Serhiy Storchaka in bpo-19668 [https://bugs.python.org/issue19668].)

bytes.join() and bytearray.join() now accept arbitrary buffer objects as arguments. (Contributed by Antoine Pitrou in bpo-15958 [https://bugs.python.org/issue15958].)

The int constructor now accepts any object that has an __index__ method for its base argument. (Contributed by Mark Dickinson in bpo-16772 [https://bugs.python.org/issue16772].)

Frame objects now have a clear() method that clears all references to local variables from the frame. (Contributed by Antoine Pitrou in bpo-17934 [https://bugs.python.org/issue17934].)

memoryview is now registered as a Sequence, and supports the reversed() builtin. (Contributed by Nick Coghlan and Claudiu Popa in bpo-18690 [https://bugs.python.org/issue18690] and bpo-19078 [https://bugs.python.org/issue19078].)

Signatures reported by help() have been modified and improved in several cases as a result of the introduction of Argument Clinic and other changes to the inspect and pydoc modules.

__length_hint__() is now part of the formal language specification (see PEP 424 [https://www.python.org/dev/peps/pep-0424]). (Contributed by Armin Ronacher in bpo-16148 [https://bugs.python.org/issue16148].)

New Modules

asyncio

The new asyncio module (defined in PEP 3156 [https://www.python.org/dev/peps/pep-3156]) provides a standard pluggable event loop model for Python, providing solid asynchronous IO support in the standard library, and making it easier for other event loop implementations to interoperate with the standard library and each other.

For Python 3.4, this module is considered a provisional API.

Voir aussi

PEP 3156 [https://www.python.org/dev/peps/pep-3156] – Asynchronous IO Support Rebooted: the « asyncio » Module

PEP written and implementation led by Guido van Rossum.

ensurepip

The new ensurepip module is the primary infrastructure for the PEP 453 [https://www.python.org/dev/peps/pep-0453] implementation. In the normal course of events end users will not need to interact with this module, but it can be used to manually bootstrap pip if the automated bootstrapping into an installation or virtual environment was declined.

ensurepip includes a bundled copy of pip, up-to-date as of the first release candidate of the release of CPython with which it ships (this applies to both maintenance releases and feature releases). ensurepip does not access the internet. If the installation has Internet access, after ensurepip is run the bundled pip can be used to upgrade pip to a more recent release than the bundled one. (Note that such an upgraded version of pip is considered to be a separately installed package and will not be removed if Python is uninstalled.)

The module is named ensurepip because if called when pip is already installed, it does nothing. It also has an --upgrade option that will cause it to install the bundled copy of pip if the existing installed version of pip is older than the bundled copy.

enum

The new enum module (defined in PEP 435 [https://www.python.org/dev/peps/pep-0435]) provides a standard implementation of enumeration types, allowing other modules (such as socket) to provide more informative error messages and better debugging support by replacing opaque integer constants with backwards compatible enumeration values.

Voir aussi

PEP 435 [https://www.python.org/dev/peps/pep-0435] – Adding an Enum type to the Python standard library

PEP written by Barry Warsaw, Eli Bendersky and Ethan Furman, implemented by Ethan Furman.

pathlib

The new pathlib module offers classes representing filesystem paths with semantics appropriate for different operating systems. Path classes are divided between pure paths, which provide purely computational operations without I/O, and concrete paths, which inherit from pure paths but also provide I/O operations.

For Python 3.4, this module is considered a provisional API.

Voir aussi

PEP 428 [https://www.python.org/dev/peps/pep-0428] – The pathlib module – object-oriented filesystem paths

PEP written and implemented by Antoine Pitrou.

selectors

The new selectors module (created as part of implementing PEP 3156 [https://www.python.org/dev/peps/pep-3156]) allows high-level and efficient I/O multiplexing, built upon the select module primitives.

statistics

The new statistics module (defined in PEP 450 [https://www.python.org/dev/peps/pep-0450]) offers some core statistics functionality directly in the standard library. This module supports calculation of the mean, median, mode, variance and standard deviation of a data series.

Voir aussi

PEP 450 [https://www.python.org/dev/peps/pep-0450] – Adding A Statistics Module To The Standard Library

PEP written and implemented by Steven D’Aprano

tracemalloc

The new tracemalloc module (defined in PEP 454 [https://www.python.org/dev/peps/pep-0454]) is a debug tool to trace memory blocks allocated by Python. It provides the following information:

Trace where an object was allocated

Statistics on allocated memory blocks per filename and per line number: total size, number and average size of allocated memory blocks

Compute the differences between two snapshots to detect memory leaks

Voir aussi

PEP 454 [https://www.python.org/dev/peps/pep-0454] – Add a new tracemalloc module to trace Python memory allocations

PEP written and implemented by Victor Stinner

Improved Modules

abc

New function abc.get_cache_token() can be used to know when to invalidate caches that are affected by changes in the object graph. (Contributed by Łukasz Langa in bpo-16832 [https://bugs.python.org/issue16832].)

New class ABC has ABCMeta as its meta class. Using ABC as a base class has essentially the same effect as specifying metaclass=abc.ABCMeta, but is simpler to type and easier to read. (Contributed by Bruno Dupuis in bpo-16049 [https://bugs.python.org/issue16049].)

aifc

The getparams() method now returns a namedtuple rather than a plain tuple. (Contributed by Claudiu Popa in bpo-17818 [https://bugs.python.org/issue17818].)

aifc.open() now supports the context management protocol: when used in a with block, the close() method of the returned object will be called automatically at the end of the block. (Contributed by Serhiy Storchacha in bpo-16486 [https://bugs.python.org/issue16486].)

The writeframesraw() and writeframes() methods now accept any bytes-like object. (Contributed by Serhiy Storchaka in bpo-8311 [https://bugs.python.org/issue8311].)

argparse

The FileType class now accepts encoding and errors arguments, which are passed through to open(). (Contributed by Lucas Maystre in bpo-11175 [https://bugs.python.org/issue11175].)

audioop

audioop now supports 24-bit samples. (Contributed by Serhiy Storchaka in bpo-12866 [https://bugs.python.org/issue12866].)

New byteswap() function converts big-endian samples to little-endian and vice versa. (Contributed by Serhiy Storchaka in bpo-19641 [https://bugs.python.org/issue19641].)

All audioop functions now accept any bytes-like object. Strings are not accepted: they didn’t work before, now they raise an error right away. (Contributed by Serhiy Storchaka in bpo-16685 [https://bugs.python.org/issue16685].)

base64

The encoding and decoding functions in base64 now accept any bytes-like object in cases where it previously required a bytes or bytearray instance. (Contributed by Nick Coghlan in bpo-17839 [https://bugs.python.org/issue17839].)

New functions a85encode(), a85decode(), b85encode(), and b85decode() provide the ability to encode and decode binary data from and to Ascii85 and the git/mercurial Base85 formats, respectively. The a85 functions have options that can be used to make them compatible with the variants of the Ascii85 encoding, including the Adobe variant. (Contributed by Martin Morrison, the Mercurial project, Serhiy Storchaka, and Antoine Pitrou in bpo-17618 [https://bugs.python.org/issue17618].)

collections

The ChainMap.new_child() method now accepts an m argument specifying the child map to add to the chain. This allows an existing mapping and/or a custom mapping type to be used for the child. (Contributed by Vinay Sajip in bpo-16613 [https://bugs.python.org/issue16613].)

colorsys

The number of digits in the coefficients for the RGB — YIQ conversions have been expanded so that they match the FCC NTSC versions. The change in results should be less than 1% and may better match results found elsewhere. (Contributed by Brian Landers and Serhiy Storchaka in bpo-14323 [https://bugs.python.org/issue14323].)

contextlib

The new contextlib.suppress context manager helps to clarify the intent of code that deliberately suppresses exceptions from a single statement. (Contributed by Raymond Hettinger in bpo-15806 [https://bugs.python.org/issue15806] and Zero Piraeus in bpo-19266 [https://bugs.python.org/issue19266].)

The new contextlib.redirect_stdout() context manager makes it easier for utility scripts to handle inflexible APIs that write their output to sys.stdout and don’t provide any options to redirect it. Using the context manager, the sys.stdout output can be redirected to any other stream or, in conjunction with io.StringIO, to a string. The latter can be especially useful, for example, to capture output from a function that was written to implement a command line interface. It is recommended only for utility scripts because it affects the global state of sys.stdout. (Contributed by Raymond Hettinger in bpo-15805 [https://bugs.python.org/issue15805].)

The contextlib documentation has also been updated to include a discussion of the differences between single use, reusable and reentrant context managers.

dbm

dbm.open() objects now support the context management protocol. When used in a with statement, the close method of the database object will be called automatically at the end of the block. (Contributed by Claudiu Popa and Nick Coghlan in bpo-19282 [https://bugs.python.org/issue19282].)

dis

Functions show_code(), dis(), distb(), and disassemble() now accept a keyword-only file argument that controls where they write their output.

The dis module is now built around an Instruction class that provides object oriented access to the details of each individual bytecode operation.

A new method, get_instructions(), provides an iterator that emits the Instruction stream for a given piece of Python code. Thus it is now possible to write a program that inspects and manipulates a bytecode object in ways different from those provided by the dis module itself. For example:

>>> import dis
>>> for instr in dis.get_instructions(lambda x: x + 1):
...     print(instr.opname)
LOAD_FAST
LOAD_CONST
BINARY_ADD
RETURN_VALUE

The various display tools in the dis module have been rewritten to use these new components.

In addition, a new application-friendly class Bytecode provides an object-oriented API for inspecting bytecode in both in human-readable form and for iterating over instructions. The Bytecode constructor takes the same arguments that get_instruction() does (plus an optional current_offset), and the resulting object can be iterated to produce Instruction objects. But it also has a dis method, equivalent to calling dis on the constructor argument, but returned as a multi-line string:

>>> bytecode = dis.Bytecode(lambda x: x + 1, current_offset=3)
>>> for instr in bytecode:
...     print('{} ({})'.format(instr.opname, instr.opcode))
LOAD_FAST (124)
LOAD_CONST (100)
BINARY_ADD (23)
RETURN_VALUE (83)
>>> bytecode.dis().splitlines()
['  1           0 LOAD_FAST                0 (x)',
 '      -->     3 LOAD_CONST               1 (1)',
 '              6 BINARY_ADD',
 '              7 RETURN_VALUE']

Bytecode also has a class method, from_traceback(), that provides the ability to manipulate a traceback (that is, print(Bytecode.from_traceback(tb).dis()) is equivalent to distb(tb)).

(Contributed by Nick Coghlan, Ryan Kelly and Thomas Kluyver in bpo-11816 [https://bugs.python.org/issue11816] and Claudiu Popa in bpo-17916 [https://bugs.python.org/issue17916].)

New function stack_effect() computes the effect on the Python stack of a given opcode and argument, information that is not otherwise available. (Contributed by Larry Hastings in bpo-19722 [https://bugs.python.org/issue19722].)

doctest

A new option flag, FAIL_FAST, halts test running as soon as the first failure is detected. (Contributed by R. David Murray and Daniel Urban in bpo-16522 [https://bugs.python.org/issue16522].)

The doctest command line interface now uses argparse, and has two new options, -o and -f. -o allows doctest options to be specified on the command line, and -f is a shorthand for -o FAIL_FAST (to parallel the similar option supported by the unittest CLI). (Contributed by R. David Murray in bpo-11390 [https://bugs.python.org/issue11390].)

doctest will now find doctests in extension module __doc__ strings. (Contributed by Zachary Ware in bpo-3158 [https://bugs.python.org/issue3158].)

email

as_string() now accepts a policy argument to override the default policy of the message when generating a string representation of it. This means that as_string can now be used in more circumstances, instead of having to create and use a generator in order to pass formatting parameters to its flatten method. (Contributed by R. David Murray in bpo-18600 [https://bugs.python.org/issue18600].)

New method as_bytes() added to produce a bytes representation of the message in a fashion similar to how as_string produces a string representation. It does not accept the maxheaderlen argument, but does accept the unixfrom and policy arguments. The Message __bytes__() method calls it, meaning that bytes(mymsg) will now produce the intuitive result: a bytes object containing the fully formatted message. (Contributed by R. David Murray in bpo-18600 [https://bugs.python.org/issue18600].)

The Message.set_param() message now accepts a replace keyword argument. When specified, the associated header will be updated without changing its location in the list of headers. For backward compatibility, the default is False. (Contributed by R. David Murray in bpo-18891 [https://bugs.python.org/issue18891].)

A pair of new subclasses of Message have been added (EmailMessage and MIMEPart), along with a new sub-module, contentmanager and a new policy attribute content_manager. All documentation is currently in the new module, which is being added as part of email’s new provisional API. These classes provide a number of new methods that make extracting content from and inserting content into email messages much easier. For details, see the contentmanager documentation and the email: Exemples. These API additions complete the bulk of the work that was planned as part of the email6 project. The currently provisional API is scheduled to become final in Python 3.5 (possibly with a few minor additions in the area of error handling). (Contributed by R. David Murray in bpo-18891 [https://bugs.python.org/issue18891].)

filecmp

A new clear_cache() function provides the ability to clear the filecmp comparison cache, which uses os.stat() information to determine if the file has changed since the last compare. This can be used, for example, if the file might have been changed and re-checked in less time than the resolution of a particular filesystem’s file modification time field. (Contributed by Mark Levitt in bpo-18149 [https://bugs.python.org/issue18149].)

New module attribute DEFAULT_IGNORES provides the list of directories that are used as the default value for the ignore parameter of the dircmp() function. (Contributed by Eli Bendersky in bpo-15442 [https://bugs.python.org/issue15442].)

functools

The new partialmethod() descriptor brings partial argument application to descriptors, just as partial() provides for normal callables. The new descriptor also makes it easier to get arbitrary callables (including partial() instances) to behave like normal instance methods when included in a class definition. (Contributed by Alon Horev and Nick Coghlan in bpo-4331 [https://bugs.python.org/issue4331].)

The new singledispatch() decorator brings support for single-dispatch generic functions to the Python standard library. Where object oriented programming focuses on grouping multiple operations on a common set of data into a class, a generic function focuses on grouping multiple implementations of an operation that allows it to work with different kinds of data.

Voir aussi

PEP 443 [https://www.python.org/dev/peps/pep-0443] – Single-dispatch generic functions

PEP written and implemented by Łukasz Langa.

total_ordering() now supports a return value of NotImplemented from the underlying comparison function. (Contributed by Katie Miller in bpo-10042 [https://bugs.python.org/issue10042].)

A pure-python version of the partial() function is now in the stdlib; in CPython it is overridden by the C accelerated version, but it is available for other implementations to use. (Contributed by Brian Thorne in bpo-12428 [https://bugs.python.org/issue12428].)

gc

New function get_stats() returns a list of three per-generation dictionaries containing the collections statistics since interpreter startup. (Contributed by Antoine Pitrou in bpo-16351 [https://bugs.python.org/issue16351].)

glob

A new function escape() provides a way to escape special characters in a filename so that they do not become part of the globbing expansion but are instead matched literally. (Contributed by Serhiy Storchaka in bpo-8402 [https://bugs.python.org/issue8402].)

hashlib

A new hashlib.pbkdf2_hmac() function provides the PKCS#5 password-based key derivation function 2 [https://en.wikipedia.org/wiki/PBKDF2]. (Contributed by Christian Heimes in bpo-18582 [https://bugs.python.org/issue18582].)

The name attribute of hashlib hash objects is now a formally supported interface. It has always existed in CPython’s hashlib (although it did not return lower case names for all supported hashes), but it was not a public interface and so some other Python implementations have not previously supported it. (Contributed by Jason R. Coombs in bpo-18532 [https://bugs.python.org/issue18532].)

hmac

hmac now accepts bytearray as well as bytes for the key argument to the new() function, and the msg parameter to both the new() function and the update() method now accepts any type supported by the hashlib module. (Contributed by Jonas Borgström in bpo-18240 [https://bugs.python.org/issue18240].)

The digestmod argument to the hmac.new() function may now be any hash digest name recognized by hashlib. In addition, the current behavior in which the value of digestmod defaults to MD5 is deprecated: in a future version of Python there will be no default value. (Contributed by Christian Heimes in bpo-17276 [https://bugs.python.org/issue17276].)

With the addition of block_size and name attributes (and the formal documentation of the digest_size attribute), the hmac module now conforms fully to the PEP 247 [https://www.python.org/dev/peps/pep-0247] API. (Contributed by Christian Heimes in bpo-18775 [https://bugs.python.org/issue18775].)

html

New function unescape() function converts HTML5 character references to the corresponding Unicode characters. (Contributed by Ezio Melotti in bpo-2927 [https://bugs.python.org/issue2927].)

HTMLParser accepts a new keyword argument convert_charrefs that, when True, automatically converts all character references. For backward-compatibility, its value defaults to False, but it will change to True in a future version of Python, so you are invited to set it explicitly and update your code to use this new feature. (Contributed by Ezio Melotti in bpo-13633 [https://bugs.python.org/issue13633].)

The strict argument of HTMLParser is now deprecated. (Contributed by Ezio Melotti in bpo-15114 [https://bugs.python.org/issue15114].)

http

send_error() now accepts an optional additional explain parameter which can be used to provide an extended error description, overriding the hardcoded default if there is one. This extended error description will be formatted using the error_message_format attribute and sent as the body of the error response. (Contributed by Karl Cow in bpo-12921 [https://bugs.python.org/issue12921].)

The http.server command line interface now has a -b/--bind option that causes the server to listen on a specific address. (Contributed by Malte Swart in bpo-17764 [https://bugs.python.org/issue17764].)

idlelib and IDLE

Since idlelib implements the IDLE shell and editor and is not intended for import by other programs, it gets improvements with every release. See Lib/idlelib/NEWS.txt for a cumulative list of changes since 3.3.0, as well as changes made in future 3.4.x releases. This file is also available from the IDLE Help ‣ About IDLE dialog.

importlib

The InspectLoader ABC defines a new method, source_to_code() that accepts source data and a path and returns a code object. The default implementation is equivalent to compile(data, path, 'exec', dont_inherit=True). (Contributed by Eric Snow and Brett Cannon in bpo-15627 [https://bugs.python.org/issue15627].)

InspectLoader also now has a default implementation for the get_code() method. However, it will normally be desirable to override the default implementation for performance reasons. (Contributed by Brett Cannon in bpo-18072 [https://bugs.python.org/issue18072].)

The reload() function has been moved from imp to importlib as part of the imp module deprecation. (Contributed by Berker Peksag in bpo-18193 [https://bugs.python.org/issue18193].)

importlib.util now has a MAGIC_NUMBER attribute providing access to the bytecode version number. This replaces the get_magic() function in the deprecated imp module. (Contributed by Brett Cannon in bpo-18192 [https://bugs.python.org/issue18192].)

New importlib.util functions cache_from_source() and source_from_cache() replace the same-named functions in the deprecated imp module. (Contributed by Brett Cannon in bpo-18194 [https://bugs.python.org/issue18194].)

The importlib bootstrap NamespaceLoader now conforms to the InspectLoader ABC, which means that runpy and python -m can now be used with namespace packages. (Contributed by Brett Cannon in bpo-18058 [https://bugs.python.org/issue18058].)

importlib.util has a new function decode_source() that decodes source from bytes using universal newline processing. This is useful for implementing InspectLoader.get_source() methods.

importlib.machinery.ExtensionFileLoader now has a get_filename() method. This was inadvertently omitted in the original implementation. (Contributed by Eric Snow in bpo-19152 [https://bugs.python.org/issue19152].)

inspect

The inspect module now offers a basic command line interface to quickly display source code and other information for modules, classes and functions. (Contributed by Claudiu Popa and Nick Coghlan in bpo-18626 [https://bugs.python.org/issue18626].)

unwrap() makes it easy to unravel wrapper function chains created by functools.wraps() (and any other API that sets the __wrapped__ attribute on a wrapper function). (Contributed by Daniel Urban, Aaron Iles and Nick Coghlan in bpo-13266 [https://bugs.python.org/issue13266].)

As part of the implementation of the new enum module, the inspect module now has substantially better support for custom __dir__ methods and dynamic class attributes provided through metaclasses. (Contributed by Ethan Furman in bpo-18929 [https://bugs.python.org/issue18929] and bpo-19030 [https://bugs.python.org/issue19030].)

getfullargspec() and getargspec() now use the signature() API. This allows them to support a much broader range of callables, including those with __signature__ attributes, those with metadata provided by argument clinic, functools.partial() objects and more. Note that, unlike signature(), these functions still ignore __wrapped__ attributes, and report the already bound first argument for bound methods, so it is still necessary to update your code to use signature() directly if those features are desired. (Contributed by Yury Selivanov in bpo-17481 [https://bugs.python.org/issue17481].)

signature() now supports duck types of CPython functions, which adds support for functions compiled with Cython. (Contributed by Stefan Behnel and Yury Selivanov in bpo-17159 [https://bugs.python.org/issue17159].)

ipaddress

ipaddress was added to the standard library in Python 3.3 as a provisional API. With the release of Python 3.4, this qualification has been removed: ipaddress is now considered a stable API, covered by the normal standard library requirements to maintain backwards compatibility.

A new is_global property is True if an address is globally routeable. (Contributed by Peter Moody in bpo-17400 [https://bugs.python.org/issue17400].)

logging

The TimedRotatingFileHandler has a new atTime parameter that can be used to specify the time of day when rollover should happen. (Contributed by Ronald Oussoren in bpo-9556 [https://bugs.python.org/issue9556].)

SocketHandler and DatagramHandler now support Unix domain sockets (by setting port to None). (Contributed by Vinay Sajip in commit ce46195b56a9.)

fileConfig() now accepts a configparser.RawConfigParser subclass instance for the fname parameter. This facilitates using a configuration file when logging configuration is just a part of the overall application configuration, or where the application modifies the configuration before passing it to fileConfig(). (Contributed by Vinay Sajip in bpo-16110 [https://bugs.python.org/issue16110].)

Logging configuration data received from a socket via the logging.config.listen() function can now be validated before being processed by supplying a verification function as the argument to the new verify keyword argument. (Contributed by Vinay Sajip in bpo-15452 [https://bugs.python.org/issue15452].)

marshal

The default marshal version has been bumped to 3. The code implementing the new version restores the Python2 behavior of recording only one copy of interned strings and preserving the interning on deserialization, and extends this « one copy » ability to any object type (including handling recursive references). This reduces both the size of .pyc files and the amount of memory a module occupies in memory when it is loaded from a .pyc (or .pyo) file. (Contributed by Kristján Valur Jónsson in bpo-16475 [https://bugs.python.org/issue16475], with additional speedups by Antoine Pitrou in bpo-19219 [https://bugs.python.org/issue19219].)

mmap

mmap objects can now be weakrefed. (Contributed by Valerie Lambert in bpo-4885 [https://bugs.python.org/issue4885].)

multiprocessing

On Unix two new start methods, spawn and forkserver, have been added for starting processes using multiprocessing. These make the mixing of processes with threads more robust, and the spawn method matches the semantics that multiprocessing has always used on Windows. New function get_all_start_methods() reports all start methods available on the platform, get_start_method() reports the current start method, and set_start_method() sets the start method. (Contributed by Richard Oudkerk in bpo-8713 [https://bugs.python.org/issue8713].)

multiprocessing also now has the concept of a context, which determines how child processes are created. New function get_context() returns a context that uses a specified start method. It has the same API as the multiprocessing module itself, so you can use it to create Pools and other objects that will operate within that context. This allows a framework and an application or different parts of the same application to use multiprocessing without interfering with each other. (Contributed by Richard Oudkerk in bpo-18999 [https://bugs.python.org/issue18999].)

Except when using the old fork start method, child processes no longer inherit unneeded handles/file descriptors from their parents (part of bpo-8713 [https://bugs.python.org/issue8713]).

multiprocessing now relies on runpy (which implements the -m switch) to initialise __main__ appropriately in child processes when using the spawn or forkserver start methods. This resolves some edge cases where combining multiprocessing, the -m command line switch, and explicit relative imports could cause obscure failures in child processes. (Contributed by Nick Coghlan in bpo-19946 [https://bugs.python.org/issue19946].)

operator

New function length_hint() provides an implementation of the specification for how the __length_hint__() special method should be used, as part of the PEP 424 [https://www.python.org/dev/peps/pep-0424] formal specification of this language feature. (Contributed by Armin Ronacher in bpo-16148 [https://bugs.python.org/issue16148].)

There is now a pure-python version of the operator module available for reference and for use by alternate implementations of Python. (Contributed by Zachary Ware in bpo-16694 [https://bugs.python.org/issue16694].)

os

There are new functions to get and set the inheritable flag of a file descriptor (os.get_inheritable(), os.set_inheritable()) or a Windows handle (os.get_handle_inheritable(), os.set_handle_inheritable()).

New function cpu_count() reports the number of CPUs available on the platform on which Python is running (or None if the count can’t be determined). The multiprocessing.cpu_count() function is now implemented in terms of this function). (Contributed by Trent Nelson, Yogesh Chaudhari, Victor Stinner, and Charles-François Natali in bpo-17914 [https://bugs.python.org/issue17914].)

os.path.samestat() is now available on the Windows platform (and the os.path.samefile() implementation is now shared between Unix and Windows). (Contributed by Brian Curtin in bpo-11939 [https://bugs.python.org/issue11939].)

os.path.ismount() now recognizes volumes mounted below a drive root on Windows. (Contributed by Tim Golden in bpo-9035 [https://bugs.python.org/issue9035].)

os.open() supports two new flags on platforms that provide them, O_PATH (un-opened file descriptor), and O_TMPFILE (unnamed temporary file; as of 3.4.0 release available only on Linux systems with a kernel version of 3.11 or newer that have uapi headers). (Contributed by Christian Heimes in bpo-18673 [https://bugs.python.org/issue18673] and Benjamin Peterson, respectively.)

pdb

pdb has been enhanced to handle generators, yield, and yield from in a more useful fashion. This is especially helpful when debugging asyncio based programs. (Contributed by Andrew Svetlov and Xavier de Gaye in bpo-16596 [https://bugs.python.org/issue16596].)

The print command has been removed from pdb, restoring access to the Python print() function from the pdb command line. Python2’s pdb did not have a print command; instead, entering print executed the print statement. In Python3 print was mistakenly made an alias for the pdb p command. p, however, prints the repr of its argument, not the str like the Python2 print command did. Worse, the Python3 pdb print command shadowed the Python3 print function, making it inaccessible at the pdb prompt. (Contributed by Connor Osborn in bpo-18764 [https://bugs.python.org/issue18764].)

pickle

pickle now supports (but does not use by default) a new pickle protocol, protocol 4. This new protocol addresses a number of issues that were present in previous protocols, such as the serialization of nested classes, very large strings and containers, and classes whose __new__() method takes keyword-only arguments. It also provides some efficiency improvements.

Voir aussi

PEP 3154 [https://www.python.org/dev/peps/pep-3154] – Pickle protocol 4

PEP written by Antoine Pitrou and implemented by Alexandre Vassalotti.

plistlib

plistlib now has an API that is similar to the standard pattern for stdlib serialization protocols, with new load(), dump(), loads(), and dumps() functions. (The older API is now deprecated.) In addition to the already supported XML plist format (FMT_XML), it also now supports the binary plist format (FMT_BINARY). (Contributed by Ronald Oussoren and others in bpo-14455 [https://bugs.python.org/issue14455].)

poplib

Two new methods have been added to poplib: capa(), which returns the list of capabilities advertised by the POP server, and stls(), which switches a clear-text POP3 session into an encrypted POP3 session if the POP server supports it. (Contributed by Lorenzo Catucci in bpo-4473 [https://bugs.python.org/issue4473].)

pprint

The pprint module’s PrettyPrinter class and its pformat(), and pprint() functions have a new option, compact, that controls how the output is formatted. Currently setting compact to True means that sequences will be printed with as many sequence elements as will fit within width on each (indented) line. (Contributed by Serhiy Storchaka in bpo-19132 [https://bugs.python.org/issue19132].)

Long strings are now wrapped using Python’s normal line continuation syntax. (Contributed by Antoine Pitrou in bpo-17150 [https://bugs.python.org/issue17150].)

pty

pty.spawn() now returns the status value from os.waitpid() on the child process, instead of None. (Contributed by Gregory P. Smith.)

pydoc

The pydoc module is now based directly on the inspect.signature() introspection API, allowing it to provide signature information for a wider variety of callable objects. This change also means that __wrapped__ attributes are now taken into account when displaying help information. (Contributed by Larry Hastings in bpo-19674 [https://bugs.python.org/issue19674].)

The pydoc module no longer displays the self parameter for already bound methods. Instead, it aims to always display the exact current signature of the supplied callable. (Contributed by Larry Hastings in bpo-20710 [https://bugs.python.org/issue20710].)

In addition to the changes that have been made to pydoc directly, its handling of custom __dir__ methods and various descriptor behaviours has also been improved substantially by the underlying changes in the inspect module.

As the help() builtin is based on pydoc, the above changes also affect the behaviour of help().

re

New fullmatch() function and regex.fullmatch() method anchor the pattern at both ends of the string to match. This provides a way to be explicit about the goal of the match, which avoids a class of subtle bugs where $ characters get lost during code changes or the addition of alternatives to an existing regular expression. (Contributed by Matthew Barnett in bpo-16203 [https://bugs.python.org/issue16203].)

The repr of regex objects now includes the pattern and the flags; the repr of match objects now includes the start, end, and the part of the string that matched. (Contributed by Hugo Lopes Tavares and Serhiy Storchaka in bpo-13592 [https://bugs.python.org/issue13592] and bpo-17087 [https://bugs.python.org/issue17087].)

resource

New prlimit() function, available on Linux platforms with a kernel version of 2.6.36 or later and glibc of 2.13 or later, provides the ability to query or set the resource limits for processes other than the one making the call. (Contributed by Christian Heimes in bpo-16595 [https://bugs.python.org/issue16595].)

On Linux kernel version 2.6.36 or later, there are also some new Linux specific constants: RLIMIT_MSGQUEUE, RLIMIT_NICE, RLIMIT_RTPRIO, RLIMIT_RTTIME, and RLIMIT_SIGPENDING. (Contributed by Christian Heimes in bpo-19324 [https://bugs.python.org/issue19324].)

On FreeBSD version 9 and later, there some new FreeBSD specific constants: RLIMIT_SBSIZE, RLIMIT_SWAP, and RLIMIT_NPTS. (Contributed by Claudiu Popa in bpo-19343 [https://bugs.python.org/issue19343].)

select

epoll objects now support the context management protocol. When used in a with statement, the close() method will be called automatically at the end of the block. (Contributed by Serhiy Storchaka in bpo-16488 [https://bugs.python.org/issue16488].)

devpoll objects now have fileno() and close() methods, as well as a new attribute closed. (Contributed by Victor Stinner in bpo-18794 [https://bugs.python.org/issue18794].)

shelve

Shelf instances may now be used in with statements, and will be automatically closed at the end of the with block. (Contributed by Filip Gruszczyński in bpo-13896 [https://bugs.python.org/issue13896].)

shutil

copyfile() now raises a specific Error subclass, SameFileError, when the source and destination are the same file, which allows an application to take appropriate action on this specific error. (Contributed by Atsuo Ishimoto and Hynek Schlawack in bpo-1492704 [https://bugs.python.org/issue1492704].)

smtpd

The SMTPServer and SMTPChannel classes now accept a map keyword argument which, if specified, is passed in to asynchat.async_chat as its map argument. This allows an application to avoid affecting the global socket map. (Contributed by Vinay Sajip in bpo-11959 [https://bugs.python.org/issue11959].)

smtplib

SMTPException is now a subclass of OSError, which allows both socket level errors and SMTP protocol level errors to be caught in one try/except statement by code that only cares whether or not an error occurred. (Contributed by Ned Jackson Lovely in bpo-2118 [https://bugs.python.org/issue2118].)

socket

The socket module now supports the CAN_BCM protocol on platforms that support it. (Contributed by Brian Thorne in bpo-15359 [https://bugs.python.org/issue15359].)

Socket objects have new methods to get or set their inheritable flag, get_inheritable() and set_inheritable().

The socket.AF_* and socket.SOCK_* constants are now enumeration values using the new enum module. This allows meaningful names to be printed during debugging, instead of integer « magic numbers ».

The AF_LINK constant is now available on BSD and OSX.

inet_pton() and inet_ntop() are now supported on Windows. (Contributed by Atsuo Ishimoto in bpo-7171 [https://bugs.python.org/issue7171].)

sqlite3

A new boolean parameter to the connect() function, uri, can be used to indicate that the database parameter is a uri (see the SQLite URI documentation [https://www.sqlite.org/uri.html]). (Contributed by poq in bpo-13773 [https://bugs.python.org/issue13773].)

ssl

PROTOCOL_TLSv1_1 and PROTOCOL_TLSv1_2 (TLSv1.1 and TLSv1.2 support) have been added; support for these protocols is only available if Python is linked with OpenSSL 1.0.1 or later. (Contributed by Michele Orrù and Antoine Pitrou in bpo-16692 [https://bugs.python.org/issue16692].)

New function create_default_context() provides a standard way to obtain an SSLContext whose settings are intended to be a reasonable balance between compatibility and security. These settings are more stringent than the defaults provided by the SSLContext constructor, and may be adjusted in the future, without prior deprecation, if best-practice security requirements change. The new recommended best practice for using stdlib libraries that support SSL is to use create_default_context() to obtain an SSLContext object, modify it if needed, and then pass it as the context argument of the appropriate stdlib API. (Contributed by Christian Heimes in bpo-19689 [https://bugs.python.org/issue19689].)

SSLContext method load_verify_locations() accepts a new optional argument cadata, which can be used to provide PEM or DER encoded certificates directly via strings or bytes, respectively. (Contributed by Christian Heimes in bpo-18138 [https://bugs.python.org/issue18138].)

New function get_default_verify_paths() returns a named tuple of the paths and environment variables that the set_default_verify_paths() method uses to set OpenSSL’s default cafile and capath. This can be an aid in debugging default verification issues. (Contributed by Christian Heimes in bpo-18143 [https://bugs.python.org/issue18143].)

SSLContext has a new method, cert_store_stats(), that reports the number of loaded X.509 certs, X.509 CA certs, and certificate revocation lists (crls), as well as a get_ca_certs() method that returns a list of the loaded CA certificates. (Contributed by Christian Heimes in bpo-18147 [https://bugs.python.org/issue18147].)

If OpenSSL 0.9.8 or later is available, SSLContext has a new attribute verify_flags that can be used to control the certificate verification process by setting it to some combination of the new constants VERIFY_DEFAULT, VERIFY_CRL_CHECK_LEAF, VERIFY_CRL_CHECK_CHAIN, or VERIFY_X509_STRICT. OpenSSL does not do any CRL verification by default. (Contributed by Christien Heimes in bpo-8813 [https://bugs.python.org/issue8813].)

New SSLContext method load_default_certs() loads a set of default « certificate authority » (CA) certificates from default locations, which vary according to the platform. It can be used to load both TLS web server authentication certificates (purpose=SERVER_AUTH) for a client to use to verify a server, and certificates for a server to use in verifying client certificates (purpose=CLIENT_AUTH). (Contributed by Christian Heimes in bpo-19292 [https://bugs.python.org/issue19292].)

Two new windows-only functions, enum_certificates() and enum_crls() provide the ability to retrieve certificates, certificate information, and CRLs from the Windows cert store. (Contributed by Christian Heimes in bpo-17134 [https://bugs.python.org/issue17134].)

Support for server-side SNI (Server Name Indication) using the new ssl.SSLContext.set_servername_callback() method. (Contributed by Daniel Black in bpo-8109 [https://bugs.python.org/issue8109].)

The dictionary returned by SSLSocket.getpeercert() contains additional X509v3 extension items: crlDistributionPoints, calIssuers, and OCSP URIs. (Contributed by Christian Heimes in bpo-18379 [https://bugs.python.org/issue18379].)

stat

The stat module is now backed by a C implementation in _stat. A C implementation is required as most of the values aren’t standardized and are platform-dependent. (Contributed by Christian Heimes in bpo-11016 [https://bugs.python.org/issue11016].)

The module supports new ST_MODE flags, S_IFDOOR, S_IFPORT, and S_IFWHT. (Contributed by Christian Hiemes in bpo-11016 [https://bugs.python.org/issue11016].)

struct

New function iter_unpack and a new struct.Struct.iter_unpack() method on compiled formats provide streamed unpacking of a buffer containing repeated instances of a given format of data. (Contributed by Antoine Pitrou in bpo-17804 [https://bugs.python.org/issue17804].)

subprocess

check_output() now accepts an input argument that can be used to provide the contents of stdin for the command that is run. (Contributed by Zack Weinberg in bpo-16624 [https://bugs.python.org/issue16624].)

getstatus() and getstatusoutput() now work on Windows. This change was actually inadvertently made in 3.3.4. (Contributed by Tim Golden in bpo-10197 [https://bugs.python.org/issue10197].)

sunau

The getparams() method now returns a namedtuple rather than a plain tuple. (Contributed by Claudiu Popa in bpo-18901 [https://bugs.python.org/issue18901].)

sunau.open() now supports the context management protocol: when used in a with block, the close method of the returned object will be called automatically at the end of the block. (Contributed by Serhiy Storchaka in bpo-18878 [https://bugs.python.org/issue18878].)

AU_write.setsampwidth() now supports 24 bit samples, thus adding support for writing 24 sample using the module. (Contributed by Serhiy Storchaka in bpo-19261 [https://bugs.python.org/issue19261].)

The writeframesraw() and writeframes() methods now accept any bytes-like object. (Contributed by Serhiy Storchaka in bpo-8311 [https://bugs.python.org/issue8311].)

sys

New function sys.getallocatedblocks() returns the current number of blocks allocated by the interpreter. (In CPython with the default --with-pymalloc setting, this is allocations made through the PyObject_Malloc() API.) This can be useful for tracking memory leaks, especially if automated via a test suite. (Contributed by Antoine Pitrou in bpo-13390 [https://bugs.python.org/issue13390].)

When the Python interpreter starts in interactive mode, it checks for an __interactivehook__ attribute on the sys module. If the attribute exists, its value is called with no arguments just before interactive mode is started. The check is made after the PYTHONSTARTUP file is read, so it can be set there. The site module sets it to a function that enables tab completion and history saving (in ~/.python-history) if the platform supports readline. If you do not want this (new) behavior, you can override it in PYTHONSTARTUP, sitecustomize, or usercustomize by deleting this attribute from sys (or setting it to some other callable). (Contributed by Éric Araujo and Antoine Pitrou in bpo-5845 [https://bugs.python.org/issue5845].)

tarfile

The tarfile module now supports a simple Interface en ligne de commande when called as a script directly or via -m. This can be used to create and extract tarfile archives. (Contributed by Berker Peksag in bpo-13477 [https://bugs.python.org/issue13477].)

textwrap

The TextWrapper class has two new attributes/constructor arguments: max_lines, which limits the number of lines in the output, and placeholder, which is a string that will appear at the end of the output if it has been truncated because of max_lines. Building on these capabilities, a new convenience function shorten() collapses all of the whitespace in the input to single spaces and produces a single line of a given width that ends with the placeholder (by default, [...]). (Contributed by Antoine Pitrou and Serhiy Storchaka in bpo-18585 [https://bugs.python.org/issue18585] and bpo-18725 [https://bugs.python.org/issue18725].)

threading

The Thread object representing the main thread can be obtained from the new main_thread() function. In normal conditions this will be the thread from which the Python interpreter was started. (Contributed by Andrew Svetlov in bpo-18882 [https://bugs.python.org/issue18882].)

traceback

A new traceback.clear_frames() function takes a traceback object and clears the local variables in all of the frames it references, reducing the amount of memory consumed. (Contributed by Andrew Kuchling in bpo-1565525 [https://bugs.python.org/issue1565525].)

types

A new DynamicClassAttribute() descriptor provides a way to define an attribute that acts normally when looked up through an instance object, but which is routed to the class __getattr__ when looked up through the class. This allows one to have properties active on a class, and have virtual attributes on the class with the same name (see Enum for an example). (Contributed by Ethan Furman in bpo-19030 [https://bugs.python.org/issue19030].)

urllib

urllib.request now supports data: URLs via the DataHandler class. (Contributed by Mathias Panzenböck in bpo-16423 [https://bugs.python.org/issue16423].)

The http method that will be used by a Request class can now be specified by setting a method class attribute on the subclass. (Contributed by Jason R Coombs in bpo-18978 [https://bugs.python.org/issue18978].)

Request objects are now reusable: if the full_url or data attributes are modified, all relevant internal properties are updated. This means, for example, that it is now possible to use the same Request object in more than one OpenerDirector.open() call with different data arguments, or to modify a Request’s url rather than recomputing it from scratch. There is also a new remove_header() method that can be used to remove headers from a Request. (Contributed by Alexey Kachayev in bpo-16464 [https://bugs.python.org/issue16464], Daniel Wozniak in bpo-17485 [https://bugs.python.org/issue17485], and Damien Brecht and Senthil Kumaran in bpo-17272 [https://bugs.python.org/issue17272].)

HTTPError objects now have a headers attribute that provides access to the HTTP response headers associated with the error. (Contributed by Berker Peksag in bpo-15701 [https://bugs.python.org/issue15701].)

unittest

The TestCase class has a new method, subTest(), that produces a context manager whose with block becomes a « sub-test ». This context manager allows a test method to dynamically generate subtests by, say, calling the subTest context manager inside a loop. A single test method can thereby produce an indefinite number of separately-identified and separately-counted tests, all of which will run even if one or more of them fail. For example:

class NumbersTest(unittest.TestCase):
    def test_even(self):
        for i in range(6):
            with self.subTest(i=i):
                self.assertEqual(i % 2, 0)

will result in six subtests, each identified in the unittest verbose output with a label consisting of the variable name i and a particular value for that variable (i=0, i=1, etc). See Distinguer les itérations de test à l’aide de sous-tests for the full version of this example. (Contributed by Antoine Pitrou in bpo-16997 [https://bugs.python.org/issue16997].)

unittest.main() now accepts an iterable of test names for defaultTest, where previously it only accepted a single test name as a string. (Contributed by Jyrki Pulliainen in bpo-15132 [https://bugs.python.org/issue15132].)

If SkipTest is raised during test discovery (that is, at the module level in the test file), it is now reported as a skip instead of an error. (Contributed by Zach Ware in bpo-16935 [https://bugs.python.org/issue16935].)

discover() now sorts the discovered files to provide consistent test ordering. (Contributed by Martin Melin and Jeff Ramnani in bpo-16709 [https://bugs.python.org/issue16709].)

TestSuite now drops references to tests as soon as the test has been run, if the test is successful. On Python interpreters that do garbage collection, this allows the tests to be garbage collected if nothing else is holding a reference to the test. It is possible to override this behavior by creating a TestSuite subclass that defines a custom _removeTestAtIndex method. (Contributed by Tom Wardill, Matt McClure, and Andrew Svetlov in bpo-11798 [https://bugs.python.org/issue11798].)

A new test assertion context-manager, assertLogs(), will ensure that a given block of code emits a log message using the logging module. By default the message can come from any logger and have a priority of INFO or higher, but both the logger name and an alternative minimum logging level may be specified. The object returned by the context manager can be queried for the LogRecords and/or formatted messages that were logged. (Contributed by Antoine Pitrou in bpo-18937 [https://bugs.python.org/issue18937].)

Test discovery now works with namespace packages (Contributed by Claudiu Popa in bpo-17457 [https://bugs.python.org/issue17457].)

unittest.mock objects now inspect their specification signatures when matching calls, which means an argument can now be matched by either position or name, instead of only by position. (Contributed by Antoine Pitrou in bpo-17015 [https://bugs.python.org/issue17015].)

mock_open() objects now have readline and readlines methods. (Contributed by Toshio Kuratomi in bpo-17467 [https://bugs.python.org/issue17467].)

venv

venv now includes activation scripts for the csh and fish shells. (Contributed by Andrew Svetlov in bpo-15417 [https://bugs.python.org/issue15417].)

EnvBuilder and the create() convenience function take a new keyword argument with_pip, which defaults to False, that controls whether or not EnvBuilder ensures that pip is installed in the virtual environment. (Contributed by Nick Coghlan in bpo-19552 [https://bugs.python.org/issue19552] as part of the PEP 453 [https://www.python.org/dev/peps/pep-0453] implementation.)

wave

The getparams() method now returns a namedtuple rather than a plain tuple. (Contributed by Claudiu Popa in bpo-17487 [https://bugs.python.org/issue17487].)

wave.open() now supports the context management protocol. (Contributed by Claudiu Popa in bpo-17616 [https://bugs.python.org/issue17616].)

wave can now write output to unseekable files. (Contributed by David Jones, Guilherme Polo, and Serhiy Storchaka in bpo-5202 [https://bugs.python.org/issue5202].)

The writeframesraw() and writeframes() methods now accept any bytes-like object. (Contributed by Serhiy Storchaka in bpo-8311 [https://bugs.python.org/issue8311].)

weakref

New WeakMethod class simulates weak references to bound methods. (Contributed by Antoine Pitrou in bpo-14631 [https://bugs.python.org/issue14631].)

New finalize class makes it possible to register a callback to be invoked when an object is garbage collected, without needing to carefully manage the lifecycle of the weak reference itself. (Contributed by Richard Oudkerk in bpo-15528 [https://bugs.python.org/issue15528].)

The callback, if any, associated with a ref is now exposed via the __callback__ attribute. (Contributed by Mark Dickinson in bpo-17643 [https://bugs.python.org/issue17643].)

xml.etree

A new parser, XMLPullParser, allows a non-blocking applications to parse XML documents. An example can be seen at Pull API for non-blocking parsing. (Contributed by Antoine Pitrou in bpo-17741 [https://bugs.python.org/issue17741].)

The xml.etree.ElementTree tostring() and tostringlist() functions, and the ElementTree write() method, now have a short_empty_elements keyword-only parameter providing control over whether elements with no content are written in abbreviated (<tag />) or expanded (<tag></tag>) form. (Contributed by Ariel Poliak and Serhiy Storchaka in bpo-14377 [https://bugs.python.org/issue14377].)

zipfile

The writepy() method of the PyZipFile class has a new filterfunc option that can be used to control which directories and files are added to the archive. For example, this could be used to exclude test files from the archive. (Contributed by Christian Tismer in bpo-19274 [https://bugs.python.org/issue19274].)

The allowZip64 parameter to ZipFile and PyZipfile is now True by default. (Contributed by William Mallard in bpo-17201 [https://bugs.python.org/issue17201].)

CPython Implementation Changes

PEP 445: Customization of CPython Memory Allocators

PEP 445 [https://www.python.org/dev/peps/pep-0445] adds new C level interfaces to customize memory allocation in the CPython interpreter.

Voir aussi

PEP 445 [https://www.python.org/dev/peps/pep-0445] – Add new APIs to customize Python memory allocators

PEP written and implemented by Victor Stinner.

PEP 442: Safe Object Finalization

PEP 442 [https://www.python.org/dev/peps/pep-0442] removes the current limitations and quirks of object finalization in CPython. With it, objects with __del__() methods, as well as generators with finally clauses, can be finalized when they are part of a reference cycle.

As part of this change, module globals are no longer forcibly set to None during interpreter shutdown in most cases, instead relying on the normal operation of the cyclic garbage collector. This avoids a whole class of interpreter-shutdown-time errors, usually involving __del__ methods, that have plagued Python since the cyclic GC was first introduced.

Voir aussi

PEP 442 [https://www.python.org/dev/peps/pep-0442] – Safe object finalization

PEP written and implemented by Antoine Pitrou.

PEP 456: Secure and Interchangeable Hash Algorithm

PEP 456 [https://www.python.org/dev/peps/pep-0456] follows up on earlier security fix work done on Python’s hash algorithm to address certain DOS attacks to which public facing APIs backed by dictionary lookups may be subject. (See bpo-14621 [https://bugs.python.org/issue14621] for the start of the current round of improvements.) The PEP unifies CPython’s hash code to make it easier for a packager to substitute a different hash algorithm, and switches Python’s default implementation to a SipHash implementation on platforms that have a 64 bit data type. Any performance differences in comparison with the older FNV algorithm are trivial.

The PEP adds additional fields to the sys.hash_info struct sequence to describe the hash algorithm in use by the currently executing binary. Otherwise, the PEP does not alter any existing CPython APIs.

PEP 436: Argument Clinic

« Argument Clinic » (PEP 436 [https://www.python.org/dev/peps/pep-0436]) is now part of the CPython build process and can be used to simplify the process of defining and maintaining accurate signatures for builtins and standard library extension modules implemented in C.

Some standard library extension modules have been converted to use Argument Clinic in Python 3.4, and pydoc and inspect have been updated accordingly.

It is expected that signature metadata for programmatic introspection will be added to additional callables implemented in C as part of Python 3.4 maintenance releases.

Note

The Argument Clinic PEP is not fully up to date with the state of the implementation. This has been deemed acceptable by the release manager and core development team in this case, as Argument Clinic will not be made available as a public API for third party use in Python 3.4.

Voir aussi

PEP 436 [https://www.python.org/dev/peps/pep-0436] – The Argument Clinic DSL

PEP written and implemented by Larry Hastings.

Other Build and C API Changes

The new PyType_GetSlot() function has been added to the stable ABI, allowing retrieval of function pointers from named type slots when using the limited API. (Contributed by Martin von Löwis in bpo-17162 [https://bugs.python.org/issue17162].)

The new Py_SetStandardStreamEncoding() pre-initialization API allows applications embedding the CPython interpreter to reliably force a particular encoding and error handler for the standard streams. (Contributed by Bastien Montagne and Nick Coghlan in bpo-16129 [https://bugs.python.org/issue16129].)

Most Python C APIs that don’t mutate string arguments are now correctly marked as accepting const char * rather than char *. (Contributed by Serhiy Storchaka in bpo-1772673 [https://bugs.python.org/issue1772673].)

A new shell version of python-config can be used even when a python interpreter is not available (for example, in cross compilation scenarios).

PyUnicode_FromFormat() now supports width and precision specifications for %s, %A, %U, %V, %S, and %R. (Contributed by Ysj Ray and Victor Stinner in bpo-7330 [https://bugs.python.org/issue7330].)

New function PyStructSequence_InitType2() supplements the existing PyStructSequence_InitType() function. The difference is that it returns 0 on success and -1 on failure.

The CPython source can now be compiled using the address sanity checking features of recent versions of GCC and clang: the false alarms in the small object allocator have been silenced. (Contributed by Dhiru Kholia in bpo-18596 [https://bugs.python.org/issue18596].)

The Windows build now uses Address Space Layout Randomization [https://en.wikipedia.org/wiki/Address_space_layout_randomization] and Data Execution Prevention [https://en.wikipedia.org/wiki/Data_Execution_Prevention]. (Contributed by Christian Heimes in bpo-16632 [https://bugs.python.org/issue16632].)

New function PyObject_LengthHint() is the C API equivalent of operator.length_hint(). (Contributed by Armin Ronacher in bpo-16148 [https://bugs.python.org/issue16148].)

Autres Améliorations

The python command has a new option, -I, which causes it to run in « isolated mode », which means that sys.path contains neither the script’s directory nor the user’s site-packages directory, and all PYTHON* environment variables are ignored (it implies both -s and -E). Other restrictions may also be applied in the future, with the goal being to isolate the execution of a script from the user’s environment. This is appropriate, for example, when Python is used to run a system script. On most POSIX systems it can and should be used in the #! line of system scripts. (Contributed by Christian Heimes in bpo-16499 [https://bugs.python.org/issue16499].)

Tab-completion is now enabled by default in the interactive interpreter on systems that support readline. History is also enabled by default, and is written to (and read from) the file ~/.python-history. (Contributed by Antoine Pitrou and Éric Araujo in bpo-5845 [https://bugs.python.org/issue5845].)

Invoking the Python interpreter with --version now outputs the version to standard output instead of standard error (bpo-18338 [https://bugs.python.org/issue18338]). Similar changes were made to argparse (bpo-18920 [https://bugs.python.org/issue18920]) and other modules that have script-like invocation capabilities (bpo-18922 [https://bugs.python.org/issue18922]).

The CPython Windows installer now adds .py to the PATHEXT variable when extensions are registered, allowing users to run a python script at the windows command prompt by just typing its name without the .py extension. (Contributed by Paul Moore in bpo-18569 [https://bugs.python.org/issue18569].)

A new make target coverage-report [https://devguide.python.org/coverage/#measuring-coverage-of-c-code-with-gcov-and-lcov] will build python, run the test suite, and generate an HTML coverage report for the C codebase using gcov and lcov [http://ltp.sourceforge.net/coverage/lcov.php].

The -R option to the python regression test suite now also checks for memory allocation leaks, using sys.getallocatedblocks(). (Contributed by Antoine Pitrou in bpo-13390 [https://bugs.python.org/issue13390].)

python -m now works with namespace packages.

The stat module is now implemented in C, which means it gets the values for its constants from the C header files, instead of having the values hard-coded in the python module as was previously the case.

Loading multiple python modules from a single OS module (.so, .dll) now works correctly (previously it silently returned the first python module in the file). (Contributed by Václav Šmilauer in bpo-16421 [https://bugs.python.org/issue16421].)

A new opcode, LOAD_CLASSDEREF, has been added to fix a bug in the loading of free variables in class bodies that could be triggered by certain uses of __prepare__. (Contributed by Benjamin Peterson in bpo-17853 [https://bugs.python.org/issue17853].)

A number of MemoryError-related crashes were identified and fixed by Victor Stinner using his PEP 445 [https://www.python.org/dev/peps/pep-0445]-based pyfailmalloc tool (bpo-18408 [https://bugs.python.org/issue18408], bpo-18520 [https://bugs.python.org/issue18520]).

The pyvenv command now accepts a --copies option to use copies rather than symlinks even on systems where symlinks are the default. (Contributed by Vinay Sajip in bpo-18807 [https://bugs.python.org/issue18807].)

The pyvenv command also accepts a --without-pip option to suppress the otherwise-automatic bootstrapping of pip into the virtual environment. (Contributed by Nick Coghlan in bpo-19552 [https://bugs.python.org/issue19552] as part of the PEP 453 [https://www.python.org/dev/peps/pep-0453] implementation.)

The encoding name is now optional in the value set for the PYTHONIOENCODING environment variable. This makes it possible to set just the error handler, without changing the default encoding. (Contributed by Serhiy Storchaka in bpo-18818 [https://bugs.python.org/issue18818].)

The bz2, lzma, and gzip module open functions now support x (exclusive creation) mode. (Contributed by Tim Heaney and Vajrasky Kok in bpo-19201 [https://bugs.python.org/issue19201], bpo-19222 [https://bugs.python.org/issue19222], and bpo-19223 [https://bugs.python.org/issue19223].)

Significant Optimizations

The UTF-32 decoder is now 3x to 4x faster. (Contributed by Serhiy Storchaka in bpo-14625 [https://bugs.python.org/issue14625].)

The cost of hash collisions for sets is now reduced. Each hash table probe now checks a series of consecutive, adjacent key/hash pairs before continuing to make random probes through the hash table. This exploits cache locality to make collision resolution less expensive. The collision resolution scheme can be described as a hybrid of linear probing and open addressing. The number of additional linear probes defaults to nine. This can be changed at compile-time by defining LINEAR_PROBES to be any value. Set LINEAR_PROBES=0 to turn-off linear probing entirely. (Contributed by Raymond Hettinger in bpo-18771 [https://bugs.python.org/issue18771].)

The interpreter starts about 30% faster. A couple of measures lead to the speedup. The interpreter loads fewer modules on startup, e.g. the re, collections and locale modules and their dependencies are no longer imported by default. The marshal module has been improved to load compiled Python code faster. (Contributed by Antoine Pitrou, Christian Heimes and Victor Stinner in bpo-19219 [https://bugs.python.org/issue19219], bpo-19218 [https://bugs.python.org/issue19218], bpo-19209 [https://bugs.python.org/issue19209], bpo-19205 [https://bugs.python.org/issue19205] and bpo-9548 [https://bugs.python.org/issue9548].)

bz2.BZ2File is now as fast or faster than the Python2 version for most cases. lzma.LZMAFile has also been optimized. (Contributed by Serhiy Storchaka and Nadeem Vawda in bpo-16034 [https://bugs.python.org/issue16034].)

random.getrandbits() is 20%-40% faster for small integers (the most common use case). (Contributed by Serhiy Storchaka in bpo-16674 [https://bugs.python.org/issue16674].)

By taking advantage of the new storage format for strings, pickling of strings is now significantly faster. (Contributed by Victor Stinner and Antoine Pitrou in bpo-15596 [https://bugs.python.org/issue15596].)

A performance issue in io.FileIO.readall() has been solved. This particularly affects Windows, and significantly speeds up the case of piping significant amounts of data through subprocess. (Contributed by Richard Oudkerk in bpo-15758 [https://bugs.python.org/issue15758].)

html.escape() is now 10x faster. (Contributed by Matt Bryant in bpo-18020 [https://bugs.python.org/issue18020].)

On Windows, the native VirtualAlloc is now used instead of the CRT malloc in obmalloc. Artificial benchmarks show about a 3% memory savings.

os.urandom() now uses a lazily-opened persistent file descriptor so as to avoid using many file descriptors when run in parallel from multiple threads. (Contributed by Antoine Pitrou in bpo-18756 [https://bugs.python.org/issue18756].)

Deprecated

This section covers various APIs and other features that have been deprecated in Python 3.4, and will be removed in Python 3.5 or later. In most (but not all) cases, using the deprecated APIs will produce a DeprecationWarning when the interpreter is run with deprecation warnings enabled (for example, by using -Wd).

Deprecations in the Python API

As mentioned in PEP 451: A ModuleSpec Type for the Import System, a number of importlib methods and functions are deprecated: importlib.find_loader() is replaced by importlib.util.find_spec(); importlib.machinery.PathFinder.find_module() is replaced by importlib.machinery.PathFinder.find_spec(); importlib.abc.MetaPathFinder.find_module() is replaced by importlib.abc.MetaPathFinder.find_spec(); importlib.abc.PathEntryFinder.find_loader() and find_module() are replaced by importlib.abc.PathEntryFinder.find_spec(); all of the xxxLoader ABC load_module methods (importlib.abc.Loader.load_module(), importlib.abc.InspectLoader.load_module(), importlib.abc.FileLoader.load_module(), importlib.abc.SourceLoader.load_module()) should no longer be implemented, instead loaders should implement an exec_module method (importlib.abc.Loader.exec_module(), importlib.abc.InspectLoader.exec_module() importlib.abc.SourceLoader.exec_module()) and let the import system take care of the rest; and importlib.abc.Loader.module_repr(), importlib.util.module_for_loader(), importlib.util.set_loader(), and importlib.util.set_package() are no longer needed because their functions are now handled automatically by the import system.

The imp module is pending deprecation. To keep compatibility with Python 2/3 code bases, the module’s removal is currently not scheduled.

The formatter module is pending deprecation and is slated for removal in Python 3.6.

MD5 as the default digestmod for the hmac.new() function is deprecated. Python 3.6 will require an explicit digest name or constructor as digestmod argument.

The internal Netrc class in the ftplib module has been documented as deprecated in its docstring for quite some time. It now emits a DeprecationWarning and will be removed completely in Python 3.5.

The undocumented endtime argument to subprocess.Popen.wait() should not have been exposed and is hopefully not in use; it is deprecated and will mostly likely be removed in Python 3.5.

The strict argument of HTMLParser is deprecated.

The plistlib readPlist(), writePlist(), readPlistFromBytes(), and writePlistToBytes() functions are deprecated in favor of the corresponding new functions load(), dump(), loads(), and dumps(). Data() is deprecated in favor of just using the bytes constructor.

The sysconfig key SO is deprecated, it has been replaced by EXT_SUFFIX.

The U mode accepted by various open functions is deprecated. In Python3 it does not do anything useful, and should be replaced by appropriate uses of io.TextIOWrapper (if needed) and its newline argument.

The parser argument of xml.etree.ElementTree.iterparse() has been deprecated, as has the html argument of XMLParser(). To prepare for the removal of the latter, all arguments to XMLParser should be passed by keyword.

Fonctionnalités obsolètes

Running IDLE with the -n flag (no subprocess) is deprecated. However, the feature will not be removed until bpo-18823 [https://bugs.python.org/issue18823] is resolved.

The site module adding a « site-python » directory to sys.path, if it exists, is deprecated (bpo-19375 [https://bugs.python.org/issue19375]).

Removed

Operating Systems No Longer Supported

Support for the following operating systems has been removed from the source and build tools:

OS/2 (bpo-16135 [https://bugs.python.org/issue16135]).

Windows 2000 (changeset e52df05b496a).

Windows systems where COMSPEC points to command.com (bpo-14470 [https://bugs.python.org/issue14470]).

VMS (bpo-16136 [https://bugs.python.org/issue16136]).

API and Feature Removals

The following obsolete and previously deprecated APIs and features have been removed:

The unmaintained Misc/TextMate and Misc/vim directories have been removed (see the devguide [https://devguide.python.org] for suggestions on what to use instead).

The SO makefile macro is removed (it was replaced by the SHLIB_SUFFIX and EXT_SUFFIX macros) (bpo-16754 [https://bugs.python.org/issue16754]).

The PyThreadState.tick_counter field has been removed; its value has been meaningless since Python 3.2, when the « new GIL » was introduced (bpo-19199 [https://bugs.python.org/issue19199]).

PyLoader and PyPycLoader have been removed from importlib. (Contributed by Taras Lyapun in bpo-15641 [https://bugs.python.org/issue15641].)

The strict argument to HTTPConnection and HTTPSConnection has been removed. HTTP 0.9-style « Simple Responses » are no longer supported.

The deprecated urllib.request.Request getter and setter methods add_data, has_data, get_data, get_type, get_host, get_selector, set_proxy, get_origin_req_host, and is_unverifiable have been removed (use direct attribute access instead).

Support for loading the deprecated TYPE_INT64 has been removed from marshal. (Contributed by Dan Riti in bpo-15480 [https://bugs.python.org/issue15480].)

inspect.Signature: positional-only parameters are now required to have a valid name.

object.__format__() no longer accepts non-empty format strings, it now raises a TypeError instead. Using a non-empty string has been deprecated since Python 3.2. This change has been made to prevent a situation where previously working (but incorrect) code would start failing if an object gained a __format__ method, which means that your code may now raise a TypeError if you are using an 's' format code with objects that do not have a __format__ method that handles it. See bpo-7994 [https://bugs.python.org/issue7994] for background.

difflib.SequenceMatcher.isbjunk() and difflib.SequenceMatcher.isbpopular() were deprecated in 3.2, and have now been removed: use x in sm.bjunk and x in sm.bpopular, where sm is a SequenceMatcher object (bpo-13248 [https://bugs.python.org/issue13248]).

Code Cleanups

The unused and undocumented internal Scanner class has been removed from the pydoc module.

The private and effectively unused _gestalt module has been removed, along with the private platform functions _mac_ver_lookup, _mac_ver_gstalt, and _bcd2str, which would only have ever been called on badly broken OSX systems (see bpo-18393 [https://bugs.python.org/issue18393]).

The hardcoded copies of certain stat constants that were included in the tarfile module namespace have been removed.

Portage vers Python 3.4

This section lists previously described changes and other bugfixes that may require changes to your code.

Changes in “python” Command Behavior

In a posix shell, setting the PATH environment variable to an empty value is equivalent to not setting it at all. However, setting PYTHONPATH to an empty value was not equivalent to not setting it at all: setting PYTHONPATH to an empty value was equivalent to setting it to ., which leads to confusion when reasoning by analogy to how PATH works. The behavior now conforms to the posix convention for PATH.

The [X refs, Y blocks] output of a debug (--with-pydebug) build of the CPython interpreter is now off by default. It can be re-enabled using the -X showrefcount option. (Contributed by Ezio Melotti in bpo-17323 [https://bugs.python.org/issue17323].)

The python command and most stdlib scripts (as well as argparse) now output --version information to stdout instead of stderr (for issue list see Autres Améliorations above).

Changes in the Python API

The ABCs defined in importlib.abc now either raise the appropriate exception or return a default value instead of raising NotImplementedError blindly. This will only affect code calling super() and falling through all the way to the ABCs. For compatibility, catch both NotImplementedError or the appropriate exception as needed.

The module type now initializes the __package__ and __loader__ attributes to None by default. To determine if these attributes were set in a backwards-compatible fashion, use e.g. getattr(module, '__loader__', None) is not None. (bpo-17115 [https://bugs.python.org/issue17115].)

importlib.util.module_for_loader() now sets __loader__ and __package__ unconditionally to properly support reloading. If this is not desired then you will need to set these attributes manually. You can use importlib.util.module_to_load() for module management.

Import now resets relevant attributes (e.g. __name__, __loader__, __package__, __file__, __cached__) unconditionally when reloading. Note that this restores a pre-3.3 behavior in that it means a module is re-found when re-loaded (bpo-19413 [https://bugs.python.org/issue19413]).

Frozen packages no longer set __path__ to a list containing the package name, they now set it to an empty list. The previous behavior could cause the import system to do the wrong thing on submodule imports if there was also a directory with the same name as the frozen package. The correct way to determine if a module is a package or not is to use hasattr(module, '__path__') (bpo-18065 [https://bugs.python.org/issue18065]).

Frozen modules no longer define a __file__ attribute. It’s semantically incorrect for frozen modules to set the attribute as they are not loaded from any explicit location. If you must know that a module comes from frozen code then you can see if the module’s __spec__.location is set to 'frozen', check if the loader is a subclass of importlib.machinery.FrozenImporter, or if Python 2 compatibility is necessary you can use imp.is_frozen().

py_compile.compile() now raises FileExistsError if the file path it would write to is a symlink or a non-regular file. This is to act as a warning that import will overwrite those files with a regular file regardless of what type of file path they were originally.

importlib.abc.SourceLoader.get_source() no longer raises ImportError when the source code being loaded triggers a SyntaxError or UnicodeDecodeError. As ImportError is meant to be raised only when source code cannot be found but it should, it was felt to be over-reaching/overloading of that meaning when the source code is found but improperly structured. If you were catching ImportError before and wish to continue to ignore syntax or decoding issues, catch all three exceptions now.

functools.update_wrapper() and functools.wraps() now correctly set the __wrapped__ attribute to the function being wrapped, even if that function also had its __wrapped__ attribute set. This means __wrapped__ attributes now correctly link a stack of decorated functions rather than every __wrapped__ attribute in the chain referring to the innermost function. Introspection libraries that assumed the previous behaviour was intentional can use inspect.unwrap() to access the first function in the chain that has no __wrapped__ attribute.

inspect.getfullargspec() has been reimplemented on top of inspect.signature() and hence handles a much wider variety of callable objects than it did in the past. It is expected that additional builtin and extension module callables will gain signature metadata over the course of the Python 3.4 series. Code that assumes that inspect.getfullargspec() will fail on non-Python callables may need to be adjusted accordingly.

importlib.machinery.PathFinder now passes on the current working directory to objects in sys.path_hooks for the empty string. This results in sys.path_importer_cache never containing '', thus iterating through sys.path_importer_cache based on sys.path will not find all keys. A module’s __file__ when imported in the current working directory will also now have an absolute path, including when using -m with the interpreter (except for __main__.__file__ when a script has been executed directly using a relative path) (Contributed by Brett Cannon in bpo-18416 [https://bugs.python.org/issue18416]). is specified on the command-line) (bpo-18416 [https://bugs.python.org/issue18416]).

The removal of the strict argument to HTTPConnection and HTTPSConnection changes the meaning of the remaining arguments if you are specifying them positionally rather than by keyword. If you’ve been paying attention to deprecation warnings your code should already be specifying any additional arguments via keywords.

Strings between from __future__ import ... statements now always raise a SyntaxError. Previously if there was no leading docstring, an interstitial string would sometimes be ignored. This brings CPython into compliance with the language spec; Jython and PyPy already were. (bpo-17434 [https://bugs.python.org/issue17434]).

ssl.SSLSocket.getpeercert() and ssl.SSLSocket.do_handshake() now raise an OSError with ENOTCONN when the SSLSocket is not connected, instead of the previous behavior of raising an AttributeError. In addition, getpeercert() will raise a ValueError if the handshake has not yet been done.

base64.b32decode() now raises a binascii.Error when the input string contains non-b32-alphabet characters, instead of a TypeError. This particular TypeError was missed when the other TypeErrors were converted. (Contributed by Serhiy Storchaka in bpo-18011 [https://bugs.python.org/issue18011].) Note: this change was also inadvertently applied in Python 3.3.3.

The file attribute is now automatically closed when the creating cgi.FieldStorage instance is garbage collected. If you were pulling the file object out separately from the cgi.FieldStorage instance and not keeping the instance alive, then you should either store the entire cgi.FieldStorage instance or read the contents of the file before the cgi.FieldStorage instance is garbage collected.

Calling read or write on a closed SSL socket now raises an informative ValueError rather than the previous more mysterious AttributeError (bpo-9177 [https://bugs.python.org/issue9177]).

slice.indices() no longer produces an OverflowError for huge values. As a consequence of this fix, slice.indices() now raises a ValueError if given a negative length; previously it returned nonsense values (bpo-14794 [https://bugs.python.org/issue14794]).

The complex constructor, unlike the cmath functions, was incorrectly accepting float values if an object’s __complex__ special method returned one. This now raises a TypeError. (bpo-16290 [https://bugs.python.org/issue16290].)

The int constructor in 3.2 and 3.3 erroneously accepts float values for the base parameter. It is unlikely anyone was doing this, but if so, it will now raise a TypeError (bpo-16772 [https://bugs.python.org/issue16772]).

Defaults for keyword-only arguments are now evaluated after defaults for regular keyword arguments, instead of before. Hopefully no one wrote any code that depends on the previous buggy behavior (bpo-16967 [https://bugs.python.org/issue16967]).

Stale thread states are now cleared after fork(). This may cause some system resources to be released that previously were incorrectly kept perpetually alive (for example, database connections kept in thread-local storage). (bpo-17094 [https://bugs.python.org/issue17094].)

Parameter names in __annotations__ dicts are now mangled properly, similarly to __kwdefaults__. (Contributed by Yury Selivanov in bpo-20625 [https://bugs.python.org/issue20625].)

hashlib.hash.name now always returns the identifier in lower case. Previously some builtin hashes had uppercase names, but now that it is a formal public interface the naming has been made consistent (bpo-18532 [https://bugs.python.org/issue18532]).

Because unittest.TestSuite now drops references to tests after they are run, test harnesses that re-use a TestSuite to re-run a set of tests may fail. Test suites should not be re-used in this fashion since it means state is retained between test runs, breaking the test isolation that unittest is designed to provide. However, if the lack of isolation is considered acceptable, the old behavior can be restored by creating a TestSuite subclass that defines a _removeTestAtIndex method that does nothing (see TestSuite.__iter__()) (bpo-11798 [https://bugs.python.org/issue11798]).

unittest now uses argparse for command line parsing. There are certain invalid command forms that used to work that are no longer allowed; in theory this should not cause backward compatibility issues since the disallowed command forms didn’t make any sense and are unlikely to be in use.

The re.split(), re.findall(), and re.sub() functions, and the group() and groups() methods of match objects now always return a bytes object when the string to be matched is a bytes-like object. Previously the return type matched the input type, so if your code was depending on the return value being, say, a bytearray, you will need to change your code.

audioop functions now raise an error immediately if passed string input, instead of failing randomly later on (bpo-16685 [https://bugs.python.org/issue16685]).

The new convert_charrefs argument to HTMLParser currently defaults to False for backward compatibility, but will eventually be changed to default to True. It is recommended that you add this keyword, with the appropriate value, to any HTMLParser calls in your code (bpo-13633 [https://bugs.python.org/issue13633]).

Since the digestmod argument to the hmac.new() function will in the future have no default, all calls to hmac.new() should be changed to explicitly specify a digestmod (bpo-17276 [https://bugs.python.org/issue17276]).

Calling sysconfig.get_config_var() with the SO key, or looking SO up in the results of a call to sysconfig.get_config_vars() is deprecated. This key should be replaced by EXT_SUFFIX or SHLIB_SUFFIX, depending on the context (bpo-19555 [https://bugs.python.org/issue19555]).

Any calls to open functions that specify U should be modified. U is ineffective in Python3 and will eventually raise an error if used. Depending on the function, the equivalent of its old Python2 behavior can be achieved using either a newline argument, or if necessary by wrapping the stream in TextIOWrapper to use its newline argument (bpo-15204 [https://bugs.python.org/issue15204]).

If you use pyvenv in a script and desire that pip not be installed, you must add --without-pip to your command invocation.

The default behavior of json.dump() and json.dumps() when an indent is specified has changed: it no longer produces trailing spaces after the item separating commas at the ends of lines. This will matter only if you have tests that are doing white-space-sensitive comparisons of such output (bpo-16333 [https://bugs.python.org/issue16333]).

doctest now looks for doctests in extension module __doc__ strings, so if your doctest test discovery includes extension modules that have things that look like doctests in them you may see test failures you’ve never seen before when running your tests (bpo-3158 [https://bugs.python.org/issue3158]).

The collections.abc module has been slightly refactored as part of the Python startup improvements. As a consequence of this, it is no longer the case that importing collections automatically imports collections.abc. If your program depended on the (undocumented) implicit import, you will need to add an explicit import collections.abc (bpo-20784 [https://bugs.python.org/issue20784]).

Changes in the C API

PyEval_EvalFrameEx(), PyObject_Repr(), and PyObject_Str(), along with some other internal C APIs, now include a debugging assertion that ensures they are not used in situations where they may silently discard a currently active exception. In cases where discarding the active exception is expected and desired (for example, because it has already been saved locally with PyErr_Fetch() or is being deliberately replaced with a different exception), an explicit PyErr_Clear() call will be needed to avoid triggering the assertion when invoking these operations (directly or indirectly) and running against a version of Python that is compiled with assertions enabled.

PyErr_SetImportError() now sets TypeError when its msg argument is not set. Previously only NULL was returned with no exception set.

The result of the PyOS_ReadlineFunctionPointer callback must now be a string allocated by PyMem_RawMalloc() or PyMem_RawRealloc(), or NULL if an error occurred, instead of a string allocated by PyMem_Malloc() or PyMem_Realloc() (bpo-16742 [https://bugs.python.org/issue16742])

PyThread_set_key_value() now always set the value. In Python 3.3, the function did nothing if the key already exists (if the current value is a non-NULL pointer).

The f_tstate (thread state) field of the PyFrameObject structure has been removed to fix a bug: see bpo-14432 [https://bugs.python.org/issue14432] for the rationale.

Changed in 3.4.3

PEP 476: Enabling certificate verification by default for stdlib http clients

http.client and modules which use it, such as urllib.request and xmlrpc.client, will now verify that the server presents a certificate which is signed by a CA in the platform trust store and whose hostname matches the hostname being requested by default, significantly improving security for many applications.

For applications which require the old previous behavior, they can pass an alternate context:

import urllib.request
import ssl

# This disables all verification
context = ssl._create_unverified_context()

# This allows using a specific certificate for the host, which doesn't need
# to be in the trust store
context = ssl.create_default_context(cafile="/path/to/file.crt")

urllib.request.urlopen("https://invalid-cert", context=context)

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Nouveautés de Python 3.3

This article explains the new features in Python 3.3, compared to 3.2. Python 3.3 was released on September 29, 2012. For full details, see the changelog [https://docs.python.org/3.3/whatsnew/changelog.html].

Voir aussi

PEP 398 [https://www.python.org/dev/peps/pep-0398] - Python 3.3 Release Schedule

Summary – Release highlights

New syntax features:

New yield from expression for generator delegation.

The u'unicode' syntax is accepted again for str objects.

New library modules:

faulthandler (helps debugging low-level crashes)

ipaddress (high-level objects representing IP addresses and masks)

lzma (compress data using the XZ / LZMA algorithm)

unittest.mock (replace parts of your system under test with mock objects)

venv (Python virtual environments, as in the popular virtualenv package)

New built-in features:

Reworked I/O exception hierarchy.

Implementation improvements:

Rewritten import machinery based on importlib.

More compact unicode strings.

More compact attribute dictionaries.

Significantly Improved Library Modules:

C Accelerator for the decimal module.

Better unicode handling in the email module (provisional).

Security improvements:

Hash randomization is switched on by default.

Please read on for a comprehensive list of user-facing changes.

PEP 405: Virtual Environments

Virtual environments help create separate Python setups while sharing a system-wide base install, for ease of maintenance. Virtual environments have their own set of private site packages (i.e. locally-installed libraries), and are optionally segregated from the system-wide site packages. Their concept and implementation are inspired by the popular virtualenv third-party package, but benefit from tighter integration with the interpreter core.

This PEP adds the venv module for programmatic access, and the pyvenv script for command-line access and administration. The Python interpreter checks for a pyvenv.cfg, file whose existence signals the base of a virtual environment’s directory tree.

Voir aussi

PEP 405 [https://www.python.org/dev/peps/pep-0405] - Python Virtual Environments

PEP written by Carl Meyer; implementation by Carl Meyer and Vinay Sajip

PEP 420: Implicit Namespace Packages

Native support for package directories that don’t require __init__.py marker files and can automatically span multiple path segments (inspired by various third party approaches to namespace packages, as described in PEP 420 [https://www.python.org/dev/peps/pep-0420])

Voir aussi

PEP 420 [https://www.python.org/dev/peps/pep-0420] - Implicit Namespace Packages

PEP written by Eric V. Smith; implementation by Eric V. Smith and Barry Warsaw

PEP 3118: New memoryview implementation and buffer protocol documentation

The implementation of PEP 3118 [https://www.python.org/dev/peps/pep-3118] has been significantly improved.

The new memoryview implementation comprehensively fixes all ownership and lifetime issues of dynamically allocated fields in the Py_buffer struct that led to multiple crash reports. Additionally, several functions that crashed or returned incorrect results for non-contiguous or multi-dimensional input have been fixed.

The memoryview object now has a PEP-3118 compliant getbufferproc() that checks the consumer’s request type. Many new features have been added, most of them work in full generality for non-contiguous arrays and arrays with suboffsets.

The documentation has been updated, clearly spelling out responsibilities for both exporters and consumers. Buffer request flags are grouped into basic and compound flags. The memory layout of non-contiguous and multi-dimensional NumPy-style arrays is explained.

Features

All native single character format specifiers in struct module syntax (optionally prefixed with “@”) are now supported.

With some restrictions, the cast() method allows changing of format and shape of C-contiguous arrays.

Multi-dimensional list representations are supported for any array type.

Multi-dimensional comparisons are supported for any array type.

One-dimensional memoryviews of hashable (read-only) types with formats B, b or c are now hashable. (Contributed by Antoine Pitrou in bpo-13411 [https://bugs.python.org/issue13411].)

Arbitrary slicing of any 1-D arrays type is supported. For example, it is now possible to reverse a memoryview in O(1) by using a negative step.

API changes

The maximum number of dimensions is officially limited to 64.

The representation of empty shape, strides and suboffsets is now an empty tuple instead of None.

Accessing a memoryview element with format “B” (unsigned bytes) now returns an integer (in accordance with the struct module syntax). For returning a bytes object the view must be cast to “c” first.

memoryview comparisons now use the logical structure of the operands and compare all array elements by value. All format strings in struct module syntax are supported. Views with unrecognised format strings are still permitted, but will always compare as unequal, regardless of view contents.

For further changes see Build and C API Changes and Porting C code.

(Contribution par Stefan Krah; bpo-10181 [https://bugs.python.org/issue10181].)

Voir aussi

PEP 3118 [https://www.python.org/dev/peps/pep-3118] - Revising the Buffer Protocol

PEP 393: Flexible String Representation

The Unicode string type is changed to support multiple internal representations, depending on the character with the largest Unicode ordinal (1, 2, or 4 bytes) in the represented string. This allows a space-efficient representation in common cases, but gives access to full UCS-4 on all systems. For compatibility with existing APIs, several representations may exist in parallel; over time, this compatibility should be phased out.

On the Python side, there should be no downside to this change.

On the C API side, PEP 393 is fully backward compatible. The legacy API should remain available at least five years. Applications using the legacy API will not fully benefit of the memory reduction, or - worse - may use a bit more memory, because Python may have to maintain two versions of each string (in the legacy format and in the new efficient storage).

Functionality

Changes introduced by PEP 393 [https://www.python.org/dev/peps/pep-0393] are the following:

Python now always supports the full range of Unicode code points, including non-BMP ones (i.e. from U+0000 to U+10FFFF). The distinction between narrow and wide builds no longer exists and Python now behaves like a wide build, even under Windows.

With the death of narrow builds, the problems specific to narrow builds have also been fixed, for example:

len() now always returns 1 for non-BMP characters, so len('\U0010FFFF') == 1;

surrogate pairs are not recombined in string literals, so '\uDBFF\uDFFF' != '\U0010FFFF';

indexing or slicing non-BMP characters returns the expected value, so '\U0010FFFF'[0] now returns '\U0010FFFF' and not '\uDBFF';

all other functions in the standard library now correctly handle non-BMP code points.

The value of sys.maxunicode is now always 1114111 (0x10FFFF in hexadecimal). The PyUnicode_GetMax() function still returns either 0xFFFF or 0x10FFFF for backward compatibility, and it should not be used with the new Unicode API (see bpo-13054 [https://bugs.python.org/issue13054]).

The ./configure flag --with-wide-unicode has been removed.

Performance and resource usage

The storage of Unicode strings now depends on the highest code point in the string:

pure ASCII and Latin1 strings (U+0000-U+00FF) use 1 byte per code point;

BMP strings (U+0000-U+FFFF) use 2 bytes per code point;

non-BMP strings (U+10000-U+10FFFF) use 4 bytes per code point.

The net effect is that for most applications, memory usage of string storage should decrease significantly - especially compared to former wide unicode builds - as, in many cases, strings will be pure ASCII even in international contexts (because many strings store non-human language data, such as XML fragments, HTTP headers, JSON-encoded data, etc.). We also hope that it will, for the same reasons, increase CPU cache efficiency on non-trivial applications. The memory usage of Python 3.3 is two to three times smaller than Python 3.2, and a little bit better than Python 2.7, on a Django benchmark (see the PEP for details).

Voir aussi

PEP 393 [https://www.python.org/dev/peps/pep-0393] - Flexible String Representation

PEP written by Martin von Löwis; implementation by Torsten Becker and Martin von Löwis.

PEP 397: Python Launcher for Windows

The Python 3.3 Windows installer now includes a py launcher application that can be used to launch Python applications in a version independent fashion.

This launcher is invoked implicitly when double-clicking *.py files. If only a single Python version is installed on the system, that version will be used to run the file. If multiple versions are installed, the most recent version is used by default, but this can be overridden by including a Unix-style « shebang line » in the Python script.

The launcher can also be used explicitly from the command line as the py application. Running py follows the same version selection rules as implicitly launching scripts, but a more specific version can be selected by passing appropriate arguments (such as -3 to request Python 3 when Python 2 is also installed, or -2.6 to specifically request an earlier Python version when a more recent version is installed).

In addition to the launcher, the Windows installer now includes an option to add the newly installed Python to the system PATH. (Contributed by Brian Curtin in bpo-3561 [https://bugs.python.org/issue3561].)

Voir aussi

PEP 397 [https://www.python.org/dev/peps/pep-0397] - Python Launcher for Windows

PEP written by Mark Hammond and Martin v. Löwis; implementation by Vinay Sajip.

Launcher documentation: Lanceur Python pour Windows

Installer PATH modification: Trouver l’exécutable Python

PEP 3151: Reworking the OS and IO exception hierarchy

The hierarchy of exceptions raised by operating system errors is now both simplified and finer-grained.

You don’t have to worry anymore about choosing the appropriate exception type between OSError, IOError, EnvironmentError, WindowsError, mmap.error, socket.error or select.error. All these exception types are now only one: OSError. The other names are kept as aliases for compatibility reasons.

Also, it is now easier to catch a specific error condition. Instead of inspecting the errno attribute (or args[0]) for a particular constant from the errno module, you can catch the adequate OSError subclass. The available subclasses are the following:

BlockingIOError

ChildProcessError

ConnectionError

FileExistsError

FileNotFoundError

InterruptedError

IsADirectoryError

NotADirectoryError

PermissionError

ProcessLookupError

TimeoutError

And the ConnectionError itself has finer-grained subclasses:

BrokenPipeError

ConnectionAbortedError

ConnectionRefusedError

ConnectionResetError

Thanks to the new exceptions, common usages of the errno can now be avoided. For example, the following code written for Python 3.2:

from errno import ENOENT, EACCES, EPERM

try:
    with open("document.txt") as f:
        content = f.read()
except IOError as err:
    if err.errno == ENOENT:
        print("document.txt file is missing")
    elif err.errno in (EACCES, EPERM):
        print("You are not allowed to read document.txt")
    else:
        raise

can now be written without the errno import and without manual inspection of exception attributes:

try:
    with open("document.txt") as f:
        content = f.read()
except FileNotFoundError:
    print("document.txt file is missing")
except PermissionError:
    print("You are not allowed to read document.txt")

Voir aussi

PEP 3151 [https://www.python.org/dev/peps/pep-3151] - Reworking the OS and IO Exception Hierarchy

PEP written and implemented by Antoine Pitrou

PEP 380: Syntax for Delegating to a Subgenerator

PEP 380 adds the yield from expression, allowing a generator to delegate part of its operations to another generator. This allows a section of code containing yield to be factored out and placed in another generator. Additionally, the subgenerator is allowed to return with a value, and the value is made available to the delegating generator.

While designed primarily for use in delegating to a subgenerator, the yield from expression actually allows delegation to arbitrary subiterators.

For simple iterators, yield from iterable is essentially just a shortened form of for item in iterable: yield item:

>>> def g(x):
...     yield from range(x, 0, -1)
...     yield from range(x)
...
>>> list(g(5))
[5, 4, 3, 2, 1, 0, 1, 2, 3, 4]

However, unlike an ordinary loop, yield from allows subgenerators to receive sent and thrown values directly from the calling scope, and return a final value to the outer generator:

>>> def accumulate():
...     tally = 0
...     while 1:
...         next = yield
...         if next is None:
...             return tally
...         tally += next
...
>>> def gather_tallies(tallies):
...     while 1:
...         tally = yield from accumulate()
...         tallies.append(tally)
...
>>> tallies = []
>>> acc = gather_tallies(tallies)
>>> next(acc)  # Ensure the accumulator is ready to accept values
>>> for i in range(4):
...     acc.send(i)
...
>>> acc.send(None)  # Finish the first tally
>>> for i in range(5):
...     acc.send(i)
...
>>> acc.send(None)  # Finish the second tally
>>> tallies
[6, 10]

The main principle driving this change is to allow even generators that are designed to be used with the send and throw methods to be split into multiple subgenerators as easily as a single large function can be split into multiple subfunctions.

Voir aussi

PEP 380 [https://www.python.org/dev/peps/pep-0380] – Syntaxe pour déléguer à un sous-générateur

PEP written by Greg Ewing; implementation by Greg Ewing, integrated into 3.3 by Renaud Blanch, Ryan Kelly and Nick Coghlan; documentation by Zbigniew Jędrzejewski-Szmek and Nick Coghlan

PEP 409: Suppressing exception context

PEP 409 introduces new syntax that allows the display of the chained exception context to be disabled. This allows cleaner error messages in applications that convert between exception types:

>>> class D:
...     def __init__(self, extra):
...         self._extra_attributes = extra
...     def __getattr__(self, attr):
...         try:
...             return self._extra_attributes[attr]
...         except KeyError:
...             raise AttributeError(attr) from None
...
>>> D({}).x
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "<stdin>", line 8, in __getattr__
AttributeError: x

Without the from None suffix to suppress the cause, the original exception would be displayed by default:

>>> class C:
...     def __init__(self, extra):
...         self._extra_attributes = extra
...     def __getattr__(self, attr):
...         try:
...             return self._extra_attributes[attr]
...         except KeyError:
...             raise AttributeError(attr)
...
>>> C({}).x
Traceback (most recent call last):
  File "<stdin>", line 6, in __getattr__
KeyError: 'x'

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "<stdin>", line 8, in __getattr__
AttributeError: x

No debugging capability is lost, as the original exception context remains available if needed (for example, if an intervening library has incorrectly suppressed valuable underlying details):

>>> try:
...     D({}).x
... except AttributeError as exc:
...     print(repr(exc.__context__))
...
KeyError('x',)

Voir aussi

PEP 409 [https://www.python.org/dev/peps/pep-0409] - Suppressing exception context

PEP written by Ethan Furman; implemented by Ethan Furman and Nick Coghlan.

PEP 414: Explicit Unicode literals

To ease the transition from Python 2 for Unicode aware Python applications that make heavy use of Unicode literals, Python 3.3 once again supports the « u » prefix for string literals. This prefix has no semantic significance in Python 3, it is provided solely to reduce the number of purely mechanical changes in migrating to Python 3, making it easier for developers to focus on the more significant semantic changes (such as the stricter default separation of binary and text data).

Voir aussi

PEP 414 [https://www.python.org/dev/peps/pep-0414] - Explicit Unicode literals

PEP written by Armin Ronacher.

PEP 3155: Qualified name for classes and functions

Functions and class objects have a new __qualname__ attribute representing the « path » from the module top-level to their definition. For global functions and classes, this is the same as __name__. For other functions and classes, it provides better information about where they were actually defined, and how they might be accessible from the global scope.

Example with (non-bound) methods:

>>> class C:
...     def meth(self):
...         pass
>>> C.meth.__name__
'meth'
>>> C.meth.__qualname__
'C.meth'

Example with nested classes:

>>> class C:
...     class D:
...         def meth(self):
...             pass
...
>>> C.D.__name__
'D'
>>> C.D.__qualname__
'C.D'
>>> C.D.meth.__name__
'meth'
>>> C.D.meth.__qualname__
'C.D.meth'

Example with nested functions:

>>> def outer():
...     def inner():
...         pass
...     return inner
...
>>> outer().__name__
'inner'
>>> outer().__qualname__
'outer.<locals>.inner'

The string representation of those objects is also changed to include the new, more precise information:

>>> str(C.D)
"<class '__main__.C.D'>"
>>> str(C.D.meth)
'<function C.D.meth at 0x7f46b9fe31e0>'

Voir aussi

PEP 3155 [https://www.python.org/dev/peps/pep-3155] - Qualified name for classes and functions

PEP written and implemented by Antoine Pitrou.

PEP 412: Key-Sharing Dictionary

Dictionaries used for the storage of objects” attributes are now able to share part of their internal storage between each other (namely, the part which stores the keys and their respective hashes). This reduces the memory consumption of programs creating many instances of non-builtin types.

Voir aussi

PEP 412 [https://www.python.org/dev/peps/pep-0412] - Key-Sharing Dictionary

PEP written and implemented by Mark Shannon.

PEP 362: Function Signature Object

A new function inspect.signature() makes introspection of python callables easy and straightforward. A broad range of callables is supported: python functions, decorated or not, classes, and functools.partial() objects. New classes inspect.Signature, inspect.Parameter and inspect.BoundArguments hold information about the call signatures, such as, annotations, default values, parameters kinds, and bound arguments, which considerably simplifies writing decorators and any code that validates or amends calling signatures or arguments.

Voir aussi

PEP 362 [https://www.python.org/dev/peps/pep-0362]: - Function Signature Object

PEP written by Brett Cannon, Yury Selivanov, Larry Hastings, Jiwon Seo; implemented by Yury Selivanov.

PEP 421: Adding sys.implementation

A new attribute on the sys module exposes details specific to the implementation of the currently running interpreter. The initial set of attributes on sys.implementation are name, version, hexversion, and cache_tag.

The intention of sys.implementation is to consolidate into one namespace the implementation-specific data used by the standard library. This allows different Python implementations to share a single standard library code base much more easily. In its initial state, sys.implementation holds only a small portion of the implementation-specific data. Over time that ratio will shift in order to make the standard library more portable.

One example of improved standard library portability is cache_tag. As of Python 3.3, sys.implementation.cache_tag is used by importlib to support PEP 3147 [https://www.python.org/dev/peps/pep-3147] compliance. Any Python implementation that uses importlib for its built-in import system may use cache_tag to control the caching behavior for modules.

SimpleNamespace

The implementation of sys.implementation also introduces a new type to Python: types.SimpleNamespace. In contrast to a mapping-based namespace, like dict, SimpleNamespace is attribute-based, like object. However, unlike object, SimpleNamespace instances are writable. This means that you can add, remove, and modify the namespace through normal attribute access.

Voir aussi

PEP 421 [https://www.python.org/dev/peps/pep-0421] - Adding sys.implementation

PEP written and implemented by Eric Snow.

Using importlib as the Implementation of Import

bpo-2377 [https://bugs.python.org/issue2377] - Replace __import__ w/ importlib.__import__ bpo-13959 [https://bugs.python.org/issue13959] - Re-implement parts of imp in pure Python bpo-14605 [https://bugs.python.org/issue14605] - Make import machinery explicit bpo-14646 [https://bugs.python.org/issue14646] - Require loaders set __loader__ and __package__

The __import__() function is now powered by importlib.__import__(). This work leads to the completion of « phase 2 » of PEP 302 [https://www.python.org/dev/peps/pep-0302]. There are multiple benefits to this change. First, it has allowed for more of the machinery powering import to be exposed instead of being implicit and hidden within the C code. It also provides a single implementation for all Python VMs supporting Python 3.3 to use, helping to end any VM-specific deviations in import semantics. And finally it eases the maintenance of import, allowing for future growth to occur.

For the common user, there should be no visible change in semantics. For those whose code currently manipulates import or calls import programmatically, the code changes that might possibly be required are covered in the Porting Python code section of this document.

New APIs

One of the large benefits of this work is the exposure of what goes into making the import statement work. That means the various importers that were once implicit are now fully exposed as part of the importlib package.

The abstract base classes defined in importlib.abc have been expanded to properly delineate between meta path finders and path entry finders by introducing importlib.abc.MetaPathFinder and importlib.abc.PathEntryFinder, respectively. The old ABC of importlib.abc.Finder is now only provided for backwards-compatibility and does not enforce any method requirements.

In terms of finders, importlib.machinery.FileFinder exposes the mechanism used to search for source and bytecode files of a module. Previously this class was an implicit member of sys.path_hooks.

For loaders, the new abstract base class importlib.abc.FileLoader helps write a loader that uses the file system as the storage mechanism for a module’s code. The loader for source files (importlib.machinery.SourceFileLoader), sourceless bytecode files (importlib.machinery.SourcelessFileLoader), and extension modules (importlib.machinery.ExtensionFileLoader) are now available for direct use.

ImportError now has name and path attributes which are set when there is relevant data to provide. The message for failed imports will also provide the full name of the module now instead of just the tail end of the module’s name.

The importlib.invalidate_caches() function will now call the method with the same name on all finders cached in sys.path_importer_cache to help clean up any stored state as necessary.

Visible Changes

For potential required changes to code, see the Porting Python code section.

Beyond the expanse of what importlib now exposes, there are other visible changes to import. The biggest is that sys.meta_path and sys.path_hooks now store all of the meta path finders and path entry hooks used by import. Previously the finders were implicit and hidden within the C code of import instead of being directly exposed. This means that one can now easily remove or change the order of the various finders to fit one’s needs.

Another change is that all modules have a __loader__ attribute, storing the loader used to create the module. PEP 302 [https://www.python.org/dev/peps/pep-0302] has been updated to make this attribute mandatory for loaders to implement, so in the future once 3rd-party loaders have been updated people will be able to rely on the existence of the attribute. Until such time, though, import is setting the module post-load.

Loaders are also now expected to set the __package__ attribute from PEP 366 [https://www.python.org/dev/peps/pep-0366]. Once again, import itself is already setting this on all loaders from importlib and import itself is setting the attribute post-load.

None is now inserted into sys.path_importer_cache when no finder can be found on sys.path_hooks. Since imp.NullImporter is not directly exposed on sys.path_hooks it could no longer be relied upon to always be available to use as a value representing no finder found.

All other changes relate to semantic changes which should be taken into consideration when updating code for Python 3.3, and thus should be read about in the Porting Python code section of this document.

(Implementation by Brett Cannon)

Other Language Changes

Some smaller changes made to the core Python language are:

Added support for Unicode name aliases and named sequences. Both unicodedata.lookup() and '\N{...}' now resolve name aliases, and unicodedata.lookup() resolves named sequences too.

(Contribution par Ezio Melotti; bpo-12753 [https://bugs.python.org/issue12753].)

Unicode database updated to UCD version 6.1.0

Equality comparisons on range() objects now return a result reflecting the equality of the underlying sequences generated by those range objects. (bpo-13201 [https://bugs.python.org/issue13201])

The count(), find(), rfind(), index() and rindex() methods of bytes and bytearray objects now accept an integer between 0 and 255 as their first argument.

(Contribution par Petri Lehtinen; bpo-12170 [https://bugs.python.org/issue12170].)

The rjust(), ljust(), and center() methods of bytes and bytearray now accept a bytearray for the fill argument. (Contributed by Petri Lehtinen in bpo-12380 [https://bugs.python.org/issue12380].)

New methods have been added to list and bytearray: copy() and clear() (bpo-10516 [https://bugs.python.org/issue10516]). Consequently, MutableSequence now also defines a clear() method (bpo-11388 [https://bugs.python.org/issue11388]).

Raw bytes literals can now be written rb"..." as well as br"...".

(Contribution par Antoine Pitrou; bpo-13748 [https://bugs.python.org/issue13748].)

dict.setdefault() now does only one lookup for the given key, making it atomic when used with built-in types.

(Contribution par Filip Gruszczyński; bpo-13521 [https://bugs.python.org/issue13521].)

The error messages produced when a function call does not match the function signature have been significantly improved.

(Contribution par Benjamin Peterson)

A Finer-Grained Import Lock

Previous versions of CPython have always relied on a global import lock. This led to unexpected annoyances, such as deadlocks when importing a module would trigger code execution in a different thread as a side-effect. Clumsy workarounds were sometimes employed, such as the PyImport_ImportModuleNoBlock() C API function.

In Python 3.3, importing a module takes a per-module lock. This correctly serializes importation of a given module from multiple threads (preventing the exposure of incompletely initialized modules), while eliminating the aforementioned annoyances.

(Contribution par Antoine Pitrou; bpo-9260 [https://bugs.python.org/issue9260].)

Builtin functions and types

open() gets a new opener parameter: the underlying file descriptor for the file object is then obtained by calling opener with (file, flags). It can be used to use custom flags like os.O_CLOEXEC for example. The 'x' mode was added: open for exclusive creation, failing if the file already exists.

print(): added the flush keyword argument. If the flush keyword argument is true, the stream is forcibly flushed.

hash(): hash randomization is enabled by default, see object.__hash__() and PYTHONHASHSEED.

The str type gets a new casefold() method: return a casefolded copy of the string, casefolded strings may be used for caseless matching. For example, 'ß'.casefold() returns 'ss'.

The sequence documentation has been substantially rewritten to better explain the binary/text sequence distinction and to provide specific documentation sections for the individual builtin sequence types (bpo-4966 [https://bugs.python.org/issue4966]).

New Modules

faulthandler

This new debug module faulthandler contains functions to dump Python tracebacks explicitly, on a fault (a crash like a segmentation fault), after a timeout, or on a user signal. Call faulthandler.enable() to install fault handlers for the SIGSEGV, SIGFPE, SIGABRT, SIGBUS, and SIGILL signals. You can also enable them at startup by setting the PYTHONFAULTHANDLER environment variable or by using -X faulthandler command line option.

Example of a segmentation fault on Linux:

$ python -q -X faulthandler
>>> import ctypes
>>> ctypes.string_at(0)
Fatal Python error: Segmentation fault

Current thread 0x00007fb899f39700:
  File "/home/python/cpython/Lib/ctypes/__init__.py", line 486 in string_at
  File "<stdin>", line 1 in <module>
Segmentation fault

ipaddress

The new ipaddress module provides tools for creating and manipulating objects representing IPv4 and IPv6 addresses, networks and interfaces (i.e. an IP address associated with a specific IP subnet).

(Contribution par Google et Peter Moody; PEP 3144 [https://www.python.org/dev/peps/pep-3144])

lzma

The newly-added lzma module provides data compression and decompression using the LZMA algorithm, including support for the .xz and .lzma file formats.

(Contributed by Nadeem Vawda and Per Øyvind Karlsen in bpo-6715 [https://bugs.python.org/issue6715].)

Improved Modules

abc

Improved support for abstract base classes containing descriptors composed with abstract methods. The recommended approach to declaring abstract descriptors is now to provide __isabstractmethod__ as a dynamically updated property. The built-in descriptors have been updated accordingly.

abc.abstractproperty has been deprecated, use property with abc.abstractmethod() instead.

abc.abstractclassmethod has been deprecated, use classmethod with abc.abstractmethod() instead.

abc.abstractstaticmethod has been deprecated, use staticmethod with abc.abstractmethod() instead.

(Contribution par Darren Dale; bpo-11610 [https://bugs.python.org/issue11610].)

abc.ABCMeta.register() now returns the registered subclass, which means it can now be used as a class decorator (bpo-10868 [https://bugs.python.org/issue10868]).

array

The array module supports the long long type using q and Q type codes.

(Contribution par Oren Tirosh et Hirokazu Yamamoto; bpo-1172711 [https://bugs.python.org/issue1172711].)

base64

ASCII-only Unicode strings are now accepted by the decoding functions of the base64 modern interface. For example, base64.b64decode('YWJj') returns b'abc'. (Contributed by Catalin Iacob in bpo-13641 [https://bugs.python.org/issue13641].)

binascii

In addition to the binary objects they normally accept, the a2b_ functions now all also accept ASCII-only strings as input. (Contributed by Antoine Pitrou in bpo-13637 [https://bugs.python.org/issue13637].)

bz2

The bz2 module has been rewritten from scratch. In the process, several new features have been added:

New bz2.open() function: open a bzip2-compressed file in binary or text mode.

bz2.BZ2File can now read from and write to arbitrary file-like objects, by means of its constructor’s fileobj argument.

(Contribution par Nadeem Vawda; bpo-5863 [https://bugs.python.org/issue5863].)

bz2.BZ2File and bz2.decompress() can now decompress multi-stream inputs (such as those produced by the pbzip2 tool). bz2.BZ2File can now also be used to create this type of file, using the 'a' (append) mode.

(Contribution par Nir Aides; bpo-1625 [https://bugs.python.org/issue1625].)

bz2.BZ2File now implements all of the io.BufferedIOBase API, except for the detach() and truncate() methods.

codecs

The mbcs codec has been rewritten to handle correctly replace and ignore error handlers on all Windows versions. The mbcs codec now supports all error handlers, instead of only replace to encode and ignore to decode.

A new Windows-only codec has been added: cp65001 (bpo-13216 [https://bugs.python.org/issue13216]). It is the Windows code page 65001 (Windows UTF-8, CP_UTF8). For example, it is used by sys.stdout if the console output code page is set to cp65001 (e.g., using chcp 65001 command).

Multibyte CJK decoders now resynchronize faster. They only ignore the first byte of an invalid byte sequence. For example, b'\xff\n'.decode('gb2312', 'replace') now returns a \n after the replacement character.

(bpo-12016 [https://bugs.python.org/issue12016])

Incremental CJK codec encoders are no longer reset at each call to their encode() methods. For example:

>>> import codecs
>>> encoder = codecs.getincrementalencoder('hz')('strict')
>>> b''.join(encoder.encode(x) for x in '\u52ff\u65bd\u65bc\u4eba\u3002 Bye.')
b'~{NpJ)l6HK!#~} Bye.'

This example gives b'~{Np~}~{J)~}~{l6~}~{HK~}~{!#~} Bye.' with older Python versions.

(bpo-12100 [https://bugs.python.org/issue12100])

The unicode_internal codec has been deprecated.

collections

Addition of a new ChainMap class to allow treating a number of mappings as a single unit. (Written by Raymond Hettinger for bpo-11089 [https://bugs.python.org/issue11089], made public in bpo-11297 [https://bugs.python.org/issue11297].)

The abstract base classes have been moved in a new collections.abc module, to better differentiate between the abstract and the concrete collections classes. Aliases for ABCs are still present in the collections module to preserve existing imports. (bpo-11085 [https://bugs.python.org/issue11085])

The Counter class now supports the unary + and - operators, as well as the in-place operators +=, -=, |=, and &=. (Contributed by Raymond Hettinger in bpo-13121 [https://bugs.python.org/issue13121].)

contextlib

ExitStack now provides a solid foundation for programmatic manipulation of context managers and similar cleanup functionality. Unlike the previous contextlib.nested API (which was deprecated and removed), the new API is designed to work correctly regardless of whether context managers acquire their resources in their __init__ method (for example, file objects) or in their __enter__ method (for example, synchronisation objects from the threading module).

(bpo-13585 [https://bugs.python.org/issue13585])

crypt

Addition of salt and modular crypt format (hashing method) and the mksalt() function to the crypt module.

(bpo-10924 [https://bugs.python.org/issue10924])

curses

If the curses module is linked to the ncursesw library, use Unicode functions when Unicode strings or characters are passed (e.g. waddwstr()), and bytes functions otherwise (e.g. waddstr()).

Use the locale encoding instead of utf-8 to encode Unicode strings.

curses.window has a new curses.window.encoding attribute.

The curses.window class has a new get_wch() method to get a wide character

The curses module has a new unget_wch() function to push a wide character so the next get_wch() will return it

(Contribution par Iñigo Serna; bpo-6755 [https://bugs.python.org/issue6755].)

datetime

Equality comparisons between naive and aware datetime instances now return False instead of raising TypeError (bpo-15006 [https://bugs.python.org/issue15006]).

New datetime.datetime.timestamp() method: Return POSIX timestamp corresponding to the datetime instance.

The datetime.datetime.strftime() method supports formatting years older than 1000.

The datetime.datetime.astimezone() method can now be called without arguments to convert datetime instance to the system timezone.

decimal

bpo-7652 [https://bugs.python.org/issue7652] - integrate fast native decimal arithmetic.

C-module and libmpdec written by Stefan Krah.

The new C version of the decimal module integrates the high speed libmpdec library for arbitrary precision correctly-rounded decimal floating point arithmetic. libmpdec conforms to IBM’s General Decimal Arithmetic Specification.

Performance gains range from 10x for database applications to 100x for numerically intensive applications. These numbers are expected gains for standard precisions used in decimal floating point arithmetic. Since the precision is user configurable, the exact figures may vary. For example, in integer bignum arithmetic the differences can be significantly higher.

The following table is meant as an illustration. Benchmarks are available at http://www.bytereef.org/mpdecimal/quickstart.html.

decimal.py

_decimal

speedup

pi

42.02s

0.345s

120x

telco

172.19s

5.68s

30x

psycopg

3.57s

0.29s

12x

Features

The FloatOperation signal optionally enables stricter semantics for mixing floats and Decimals.

If Python is compiled without threads, the C version automatically disables the expensive thread local context machinery. In this case, the variable HAVE_THREADS is set to False.

API changes

The C module has the following context limits, depending on the machine architecture:

32-bit

64-bit

MAX_PREC

425000000

999999999999999999

MAX_EMAX

425000000

999999999999999999

MIN_EMIN

-425000000

-999999999999999999

In the context templates (DefaultContext, BasicContext and ExtendedContext) the magnitude of Emax and Emin has changed to 999999.

The Decimal constructor in decimal.py does not observe the context limits and converts values with arbitrary exponents or precision exactly. Since the C version has internal limits, the following scheme is used: If possible, values are converted exactly, otherwise InvalidOperation is raised and the result is NaN. In the latter case it is always possible to use create_decimal() in order to obtain a rounded or inexact value.

The power function in decimal.py is always correctly-rounded. In the C version, it is defined in terms of the correctly-rounded exp() and ln() functions, but the final result is only « almost always correctly rounded ».

In the C version, the context dictionary containing the signals is a MutableMapping. For speed reasons, flags and traps always refer to the same MutableMapping that the context was initialized with. If a new signal dictionary is assigned, flags and traps are updated with the new values, but they do not reference the RHS dictionary.

Pickling a Context produces a different output in order to have a common interchange format for the Python and C versions.

The order of arguments in the Context constructor has been changed to match the order displayed by repr().

The watchexp parameter in the quantize() method is deprecated.

email

Policy Framework

The email package now has a policy framework. A Policy is an object with several methods and properties that control how the email package behaves. The primary policy for Python 3.3 is the Compat32 policy, which provides backward compatibility with the email package in Python 3.2. A policy can be specified when an email message is parsed by a parser, or when a Message object is created, or when an email is serialized using a generator. Unless overridden, a policy passed to a parser is inherited by all the Message object and sub-objects created by the parser. By default a generator will use the policy of the Message object it is serializing. The default policy is compat32.

The minimum set of controls implemented by all policy objects are:

max_line_length

The maximum length, excluding the linesep character(s), individual lines may have when a Message is serialized. Defaults to 78.

linesep

The character used to separate individual lines when a Message is serialized. Defaults to \n.

cte_type

7bit or 8bit. 8bit applies only to a Bytes generator, and means that non-ASCII may be used where allowed by the protocol (or where it exists in the original input).

raise_on_defect

Causes a parser to raise error when defects are encountered instead of adding them to the Message object’s defects list.

A new policy instance, with new settings, is created using the clone() method of policy objects. clone takes any of the above controls as keyword arguments. Any control not specified in the call retains its default value. Thus you can create a policy that uses \r\n linesep characters like this:

mypolicy = compat32.clone(linesep='\r\n')

Policies can be used to make the generation of messages in the format needed by your application simpler. Instead of having to remember to specify linesep='\r\n' in all the places you call a generator, you can specify it once, when you set the policy used by the parser or the Message, whichever your program uses to create Message objects. On the other hand, if you need to generate messages in multiple forms, you can still specify the parameters in the appropriate generator call. Or you can have custom policy instances for your different cases, and pass those in when you create the generator.

Provisional Policy with New Header API

While the policy framework is worthwhile all by itself, the main motivation for introducing it is to allow the creation of new policies that implement new features for the email package in a way that maintains backward compatibility for those who do not use the new policies. Because the new policies introduce a new API, we are releasing them in Python 3.3 as a provisional policy. Backwards incompatible changes (up to and including removal of the code) may occur if deemed necessary by the core developers.

The new policies are instances of EmailPolicy, and add the following additional controls:

refold_source

Controls whether or not headers parsed by a parser are refolded by the generator. It can be none, long, or all. The default is long, which means that source headers with a line longer than max_line_length get refolded. none means no line get refolded, and all means that all lines get refolded.

header_factory

A callable that take a name and value and produces a custom header object.

The header_factory is the key to the new features provided by the new policies. When one of the new policies is used, any header retrieved from a Message object is an object produced by the header_factory, and any time you set a header on a Message it becomes an object produced by header_factory. All such header objects have a name attribute equal to the header name. Address and Date headers have additional attributes that give you access to the parsed data of the header. This means you can now do things like this:

>>> m = Message(policy=SMTP)
>>> m['To'] = 'Éric <foo@example.com>'
>>> m['to']
'Éric <foo@example.com>'
>>> m['to'].addresses
(Address(display_name='Éric', username='foo', domain='example.com'),)
>>> m['to'].addresses[0].username
'foo'
>>> m['to'].addresses[0].display_name
'Éric'
>>> m['Date'] = email.utils.localtime()
>>> m['Date'].datetime
datetime.datetime(2012, 5, 25, 21, 39, 24, 465484, tzinfo=datetime.timezone(datetime.timedelta(-1, 72000), 'EDT'))
>>> m['Date']
'Fri, 25 May 2012 21:44:27 -0400'
>>> print(m)
To: =?utf-8?q?=C3=89ric?= <foo@example.com>
Date: Fri, 25 May 2012 21:44:27 -0400

You will note that the unicode display name is automatically encoded as utf-8 when the message is serialized, but that when the header is accessed directly, you get the unicode version. This eliminates any need to deal with the email.header decode_header() or make_header() functions.

You can also create addresses from parts:

>>> m['cc'] = [Group('pals', [Address('Bob', 'bob', 'example.com'),
...                           Address('Sally', 'sally', 'example.com')]),
...            Address('Bonzo', addr_spec='bonz@laugh.com')]
>>> print(m)
To: =?utf-8?q?=C3=89ric?= <foo@example.com>
Date: Fri, 25 May 2012 21:44:27 -0400
cc: pals: Bob <bob@example.com>, Sally <sally@example.com>;, Bonzo <bonz@laugh.com>

Decoding to unicode is done automatically:

>>> m2 = message_from_string(str(m))
>>> m2['to']
'Éric <foo@example.com>'

When you parse a message, you can use the addresses and groups attributes of the header objects to access the groups and individual addresses:

>>> m2['cc'].addresses
(Address(display_name='Bob', username='bob', domain='example.com'), Address(display_name='Sally', username='sally', domain='example.com'), Address(display_name='Bonzo', username='bonz', domain='laugh.com'))
>>> m2['cc'].groups
(Group(display_name='pals', addresses=(Address(display_name='Bob', username='bob', domain='example.com'), Address(display_name='Sally', username='sally', domain='example.com')), Group(display_name=None, addresses=(Address(display_name='Bonzo', username='bonz', domain='laugh.com'),))

In summary, if you use one of the new policies, header manipulation works the way it ought to: your application works with unicode strings, and the email package transparently encodes and decodes the unicode to and from the RFC standard Content Transfer Encodings.

Other API Changes

New BytesHeaderParser, added to the parser module to complement HeaderParser and complete the Bytes API.

New utility functions:

format_datetime(): given a datetime, produce a string formatted for use in an email header.

parsedate_to_datetime(): given a date string from an email header, convert it into an aware datetime, or a naive datetime if the offset is -0000.

localtime(): With no argument, returns the current local time as an aware datetime using the local timezone. Given an aware datetime, converts it into an aware datetime using the local timezone.

ftplib

ftplib.FTP now accepts a source_address keyword argument to specify the (host, port) to use as the source address in the bind call when creating the outgoing socket. (Contributed by Giampaolo Rodolà in bpo-8594 [https://bugs.python.org/issue8594].)

The FTP_TLS class now provides a new ccc() function to revert control channel back to plaintext. This can be useful to take advantage of firewalls that know how to handle NAT with non-secure FTP without opening fixed ports. (Contributed by Giampaolo Rodolà in bpo-12139 [https://bugs.python.org/issue12139].)

Added ftplib.FTP.mlsd() method which provides a parsable directory listing format and deprecates ftplib.FTP.nlst() and ftplib.FTP.dir(). (Contributed by Giampaolo Rodolà in bpo-11072 [https://bugs.python.org/issue11072].)

functools

The functools.lru_cache() decorator now accepts a typed keyword argument (that defaults to False to ensure that it caches values of different types that compare equal in separate cache slots. (Contributed by Raymond Hettinger in bpo-13227 [https://bugs.python.org/issue13227].)

gc

It is now possible to register callbacks invoked by the garbage collector before and after collection using the new callbacks list.

hmac

A new compare_digest() function has been added to prevent side channel attacks on digests through timing analysis. (Contributed by Nick Coghlan and Christian Heimes in bpo-15061 [https://bugs.python.org/issue15061].)

http

http.server.BaseHTTPRequestHandler now buffers the headers and writes them all at once when end_headers() is called. A new method flush_headers() can be used to directly manage when the accumulated headers are sent. (Contributed by Andrew Schaaf in bpo-3709 [https://bugs.python.org/issue3709].)

http.server now produces valid HTML 4.01 strict output. (Contributed by Ezio Melotti in bpo-13295 [https://bugs.python.org/issue13295].)

http.client.HTTPResponse now has a readinto() method, which means it can be used as an io.RawIOBase class. (Contributed by John Kuhn in bpo-13464 [https://bugs.python.org/issue13464].)

html

html.parser.HTMLParser is now able to parse broken markup without raising errors, therefore the strict argument of the constructor and the HTMLParseError exception are now deprecated. The ability to parse broken markup is the result of a number of bug fixes that are also available on the latest bug fix releases of Python 2.7/3.2. (Contributed by Ezio Melotti in bpo-15114 [https://bugs.python.org/issue15114], and bpo-14538 [https://bugs.python.org/issue14538], bpo-13993 [https://bugs.python.org/issue13993], bpo-13960 [https://bugs.python.org/issue13960], bpo-13358 [https://bugs.python.org/issue13358], bpo-1745761 [https://bugs.python.org/issue1745761], bpo-755670 [https://bugs.python.org/issue755670], bpo-13357 [https://bugs.python.org/issue13357], bpo-12629 [https://bugs.python.org/issue12629], bpo-1200313 [https://bugs.python.org/issue1200313], bpo-670664 [https://bugs.python.org/issue670664], bpo-13273 [https://bugs.python.org/issue13273], bpo-12888 [https://bugs.python.org/issue12888], bpo-7311 [https://bugs.python.org/issue7311].)

A new html5 dictionary that maps HTML5 named character references to the equivalent Unicode character(s) (e.g. html5['gt;'] == '>') has been added to the html.entities module. The dictionary is now also used by HTMLParser. (Contributed by Ezio Melotti in bpo-11113 [https://bugs.python.org/issue11113] and bpo-15156 [https://bugs.python.org/issue15156].)

imaplib

The IMAP4_SSL constructor now accepts an SSLContext parameter to control parameters of the secure channel.

(Contribution par Sijin Joseph; bpo-8808 [https://bugs.python.org/issue8808].)

inspect

A new getclosurevars() function has been added. This function reports the current binding of all names referenced from the function body and where those names were resolved, making it easier to verify correct internal state when testing code that relies on stateful closures.

(Contribution par Meador Inge et Nick Coghlan; bpo-13062 [https://bugs.python.org/issue13062].)

A new getgeneratorlocals() function has been added. This function reports the current binding of local variables in the generator’s stack frame, making it easier to verify correct internal state when testing generators.

(Contribution par Meador Inge; bpo-15153 [https://bugs.python.org/issue15153].)

io

The open() function has a new 'x' mode that can be used to exclusively create a new file, and raise a FileExistsError if the file already exists. It is based on the C11 “x” mode to fopen().

(Contribution par David Townshend; bpo-12760 [https://bugs.python.org/issue12760].)

The constructor of the TextIOWrapper class has a new write_through optional argument. If write_through is True, calls to write() are guaranteed not to be buffered: any data written on the TextIOWrapper object is immediately handled to its underlying binary buffer.

itertools

accumulate() now takes an optional func argument for providing a user-supplied binary function.

logging

The basicConfig() function now supports an optional handlers argument taking an iterable of handlers to be added to the root logger.

A class level attribute append_nul has been added to SysLogHandler to allow control of the appending of the NUL (\000) byte to syslog records, since for some deamons it is required while for others it is passed through to the log.

math

The math module has a new function, log2(), which returns the base-2 logarithm of x.

(Written by Mark Dickinson in bpo-11888 [https://bugs.python.org/issue11888].)

mmap

The read() method is now more compatible with other file-like objects: if the argument is omitted or specified as None, it returns the bytes from the current file position to the end of the mapping. (Contributed by Petri Lehtinen in bpo-12021 [https://bugs.python.org/issue12021].)

multiprocessing

The new multiprocessing.connection.wait() function allows polling multiple objects (such as connections, sockets and pipes) with a timeout. (Contributed by Richard Oudkerk in bpo-12328 [https://bugs.python.org/issue12328].)

multiprocessing.Connection objects can now be transferred over multiprocessing connections. (Contributed by Richard Oudkerk in bpo-4892 [https://bugs.python.org/issue4892].)

multiprocessing.Process now accepts a daemon keyword argument to override the default behavior of inheriting the daemon flag from the parent process (bpo-6064 [https://bugs.python.org/issue6064]).

New attribute multiprocessing.Process.sentinel allows a program to wait on multiple Process objects at one time using the appropriate OS primitives (for example, select on posix systems).

New methods multiprocessing.pool.Pool.starmap() and starmap_async() provide itertools.starmap() equivalents to the existing multiprocessing.pool.Pool.map() and map_async() functions. (Contributed by Hynek Schlawack in bpo-12708 [https://bugs.python.org/issue12708].)

nntplib

The nntplib.NNTP class now supports the context management protocol to unconditionally consume socket.error exceptions and to close the NNTP connection when done:

>>> from nntplib import NNTP
>>> with NNTP('news.gmane.org') as n:
...     n.group('gmane.comp.python.committers')
...
('211 1755 1 1755 gmane.comp.python.committers', 1755, 1, 1755, 'gmane.comp.python.committers')
>>>

(Contribution par Giampaolo Rodolà; bpo-9795 [https://bugs.python.org/issue9795].)

os

The os module has a new pipe2() function that makes it possible to create a pipe with O_CLOEXEC or O_NONBLOCK flags set atomically. This is especially useful to avoid race conditions in multi-threaded programs.

The os module has a new sendfile() function which provides an efficient « zero-copy » way for copying data from one file (or socket) descriptor to another. The phrase « zero-copy » refers to the fact that all of the copying of data between the two descriptors is done entirely by the kernel, with no copying of data into userspace buffers. sendfile() can be used to efficiently copy data from a file on disk to a network socket, e.g. for downloading a file.

(Patch submitted by Ross Lagerwall and Giampaolo Rodolà in bpo-10882 [https://bugs.python.org/issue10882].)

To avoid race conditions like symlink attacks and issues with temporary files and directories, it is more reliable (and also faster) to manipulate file descriptors instead of file names. Python 3.3 enhances existing functions and introduces new functions to work on file descriptors (bpo-4761 [https://bugs.python.org/issue4761], bpo-10755 [https://bugs.python.org/issue10755] and bpo-14626 [https://bugs.python.org/issue14626]).

The os module has a new fwalk() function similar to walk() except that it also yields file descriptors referring to the directories visited. This is especially useful to avoid symlink races.

The following functions get new optional dir_fd (paths relative to directory descriptors) and/or follow_symlinks (not following symlinks): access(), chflags(), chmod(), chown(), link(), lstat(), mkdir(), mkfifo(), mknod(), open(), readlink(), remove(), rename(), replace(), rmdir(), stat(), symlink(), unlink(), utime(). Platform support for using these parameters can be checked via the sets os.supports_dir_fd and os.supports_follows_symlinks.

The following functions now support a file descriptor for their path argument: chdir(), chmod(), chown(), execve(), listdir(), pathconf(), exists(), stat(), statvfs(), utime(). Platform support for this can be checked via the os.supports_fd set.

access() accepts an effective_ids keyword argument to turn on using the effective uid/gid rather than the real uid/gid in the access check. Platform support for this can be checked via the supports_effective_ids set.

The os module has two new functions: getpriority() and setpriority(). They can be used to get or set process niceness/priority in a fashion similar to os.nice() but extended to all processes instead of just the current one.

(Patch submitted by Giampaolo Rodolà in bpo-10784 [https://bugs.python.org/issue10784].)

The new os.replace() function allows cross-platform renaming of a file with overwriting the destination. With os.rename(), an existing destination file is overwritten under POSIX, but raises an error under Windows. (Contributed by Antoine Pitrou in bpo-8828 [https://bugs.python.org/issue8828].)

The stat family of functions (stat(), fstat(), and lstat()) now support reading a file’s timestamps with nanosecond precision. Symmetrically, utime() can now write file timestamps with nanosecond precision. (Contributed by Larry Hastings in bpo-14127 [https://bugs.python.org/issue14127].)

The new os.get_terminal_size() function queries the size of the terminal attached to a file descriptor. See also shutil.get_terminal_size(). (Contributed by Zbigniew Jędrzejewski-Szmek in bpo-13609 [https://bugs.python.org/issue13609].)

New functions to support Linux extended attributes (bpo-12720 [https://bugs.python.org/issue12720]): getxattr(), listxattr(), removexattr(), setxattr().

New interface to the scheduler. These functions control how a process is allocated CPU time by the operating system. New functions: sched_get_priority_max(), sched_get_priority_min(), sched_getaffinity(), sched_getparam(), sched_getscheduler(), sched_rr_get_interval(), sched_setaffinity(), sched_setparam(), sched_setscheduler(), sched_yield(),

New functions to control the file system:

posix_fadvise(): Announces an intention to access data in a specific pattern thus allowing the kernel to make optimizations.

posix_fallocate(): Ensures that enough disk space is allocated for a file.

sync(): Force write of everything to disk.

Additional new posix functions:

lockf(): Apply, test or remove a POSIX lock on an open file descriptor.

pread(): Read from a file descriptor at an offset, the file offset remains unchanged.

pwrite(): Write to a file descriptor from an offset, leaving the file offset unchanged.

readv(): Read from a file descriptor into a number of writable buffers.

truncate(): Truncate the file corresponding to path, so that it is at most length bytes in size.

waitid(): Wait for the completion of one or more child processes.

writev(): Write the contents of buffers to a file descriptor, where buffers is an arbitrary sequence of buffers.

getgrouplist() (bpo-9344 [https://bugs.python.org/issue9344]): Return list of group ids that specified user belongs to.

times() and uname(): Return type changed from a tuple to a tuple-like object with named attributes.

Some platforms now support additional constants for the lseek() function, such as os.SEEK_HOLE and os.SEEK_DATA.

New constants RTLD_LAZY, RTLD_NOW, RTLD_GLOBAL, RTLD_LOCAL, RTLD_NODELETE, RTLD_NOLOAD, and RTLD_DEEPBIND are available on platforms that support them. These are for use with the sys.setdlopenflags() function, and supersede the similar constants defined in ctypes and DLFCN. (Contributed by Victor Stinner in bpo-13226 [https://bugs.python.org/issue13226].)

os.symlink() now accepts (and ignores) the target_is_directory keyword argument on non-Windows platforms, to ease cross-platform support.

pdb

Tab-completion is now available not only for command names, but also their arguments. For example, for the break command, function and file names are completed.

(Contribution par Georg Brandl; bpo-14210 [https://bugs.python.org/issue14210].)

pickle

pickle.Pickler objects now have an optional dispatch_table attribute allowing per-pickler reduction functions to be set.

(Contribution par Richard Oudkerk; bpo-14166 [https://bugs.python.org/issue14166].)

pydoc

The Tk GUI and the serve() function have been removed from the pydoc module: pydoc -g and serve() have been deprecated in Python 3.2.

re

str regular expressions now support \u and \U escapes.

(Contribution par Serhiy Storchaka; bpo-3665 [https://bugs.python.org/issue3665].)

sched

run() now accepts a blocking parameter which when set to false makes the method execute the scheduled events due to expire soonest (if any) and then return immediately. This is useful in case you want to use the scheduler in non-blocking applications. (Contributed by Giampaolo Rodolà in bpo-13449 [https://bugs.python.org/issue13449].)

scheduler class can now be safely used in multi-threaded environments. (Contributed by Josiah Carlson and Giampaolo Rodolà in bpo-8684 [https://bugs.python.org/issue8684].)

timefunc and delayfunct parameters of scheduler class constructor are now optional and defaults to time.time() and time.sleep() respectively. (Contributed by Chris Clark in bpo-13245 [https://bugs.python.org/issue13245].)

enter() and enterabs() argument parameter is now optional. (Contributed by Chris Clark in bpo-13245 [https://bugs.python.org/issue13245].)

enter() and enterabs() now accept a kwargs parameter. (Contributed by Chris Clark in bpo-13245 [https://bugs.python.org/issue13245].)

select

Solaris and derivative platforms have a new class select.devpoll for high performance asynchronous sockets via /dev/poll. (Contributed by Jesús Cea Avión in bpo-6397 [https://bugs.python.org/issue6397].)

shlex

The previously undocumented helper function quote from the pipes modules has been moved to the shlex module and documented. quote() properly escapes all characters in a string that might be otherwise given special meaning by the shell.

shutil

Nouvelles fonctions :

disk_usage(): provides total, used and free disk space statistics. (Contributed by Giampaolo Rodolà in bpo-12442 [https://bugs.python.org/issue12442].)

chown(): allows one to change user and/or group of the given path also specifying the user/group names and not only their numeric ids. (Contributed by Sandro Tosi in bpo-12191 [https://bugs.python.org/issue12191].)

shutil.get_terminal_size(): returns the size of the terminal window to which the interpreter is attached. (Contributed by Zbigniew Jędrzejewski-Szmek in bpo-13609 [https://bugs.python.org/issue13609].)

copy2() and copystat() now preserve file timestamps with nanosecond precision on platforms that support it. They also preserve file « extended attributes » on Linux. (Contributed by Larry Hastings in bpo-14127 [https://bugs.python.org/issue14127] and bpo-15238 [https://bugs.python.org/issue15238].)

Several functions now take an optional symlinks argument: when that parameter is true, symlinks aren’t dereferenced and the operation instead acts on the symlink itself (or creates one, if relevant). (Contributed by Hynek Schlawack in bpo-12715 [https://bugs.python.org/issue12715].)

When copying files to a different file system, move() now handles symlinks the way the posix mv command does, recreating the symlink rather than copying the target file contents. (Contributed by Jonathan Niehof in bpo-9993 [https://bugs.python.org/issue9993].) move() now also returns the dst argument as its result.

rmtree() is now resistant to symlink attacks on platforms which support the new dir_fd parameter in os.open() and os.unlink(). (Contributed by Martin von Löwis and Hynek Schlawack in bpo-4489 [https://bugs.python.org/issue4489].)

signal

Le module signal a de nouvelles fonctions :

pthread_sigmask(): fetch and/or change the signal mask of the calling thread (Contributed by Jean-Paul Calderone in bpo-8407 [https://bugs.python.org/issue8407]);

pthread_kill(): send a signal to a thread;

sigpending(): examine pending functions;

sigwait(): wait a signal;

sigwaitinfo(): wait for a signal, returning detailed information about it;

sigtimedwait(): like sigwaitinfo() but with a timeout.

The signal handler writes the signal number as a single byte instead of a nul byte into the wakeup file descriptor. So it is possible to wait more than one signal and know which signals were raised.

signal.signal() and signal.siginterrupt() raise an OSError, instead of a RuntimeError: OSError has an errno attribute.

smtpd

The smtpd module now supports RFC 5321 [https://tools.ietf.org/html/rfc5321.html] (extended SMTP) and RFC 1870 [https://tools.ietf.org/html/rfc1870.html] (size extension). Per the standard, these extensions are enabled if and only if the client initiates the session with an EHLO command.

(Initial ELHO support by Alberto Trevino. Size extension by Juhana Jauhiainen. Substantial additional work on the patch contributed by Michele Orrù and Dan Boswell. bpo-8739 [https://bugs.python.org/issue8739])

smtplib

The SMTP, SMTP_SSL, and LMTP classes now accept a source_address keyword argument to specify the (host, port) to use as the source address in the bind call when creating the outgoing socket. (Contributed by Paulo Scardine in bpo-11281 [https://bugs.python.org/issue11281].)

SMTP now supports the context management protocol, allowing an SMTP instance to be used in a with statement. (Contributed by Giampaolo Rodolà in bpo-11289 [https://bugs.python.org/issue11289].)

The SMTP_SSL constructor and the starttls() method now accept an SSLContext parameter to control parameters of the secure channel. (Contributed by Kasun Herath in bpo-8809 [https://bugs.python.org/issue8809].)

socket

The socket class now exposes additional methods to process ancillary data when supported by the underlying platform:

sendmsg()

recvmsg()

recvmsg_into()

(Contributed by David Watson in bpo-6560 [https://bugs.python.org/issue6560], based on an earlier patch by Heiko Wundram)

The socket class now supports the PF_CAN protocol family (https://en.wikipedia.org/wiki/Socketcan), on Linux (https://lwn.net/Articles/253425).

(Contributed by Matthias Fuchs, updated by Tiago Gonçalves in bpo-10141 [https://bugs.python.org/issue10141].)

The socket class now supports the PF_RDS protocol family (https://en.wikipedia.org/wiki/Reliable_Datagram_Sockets and https://oss.oracle.com/projects/rds/).

The socket class now supports the PF_SYSTEM protocol family on OS X. (Contributed by Michael Goderbauer in bpo-13777 [https://bugs.python.org/issue13777].)

New function sethostname() allows the hostname to be set on unix systems if the calling process has sufficient privileges. (Contributed by Ross Lagerwall in bpo-10866 [https://bugs.python.org/issue10866].)

socketserver

BaseServer now has an overridable method service_actions() that is called by the serve_forever() method in the service loop. ForkingMixIn now uses this to clean up zombie child processes. (Contributed by Justin Warkentin in bpo-11109 [https://bugs.python.org/issue11109].)

sqlite3

New sqlite3.Connection method set_trace_callback() can be used to capture a trace of all sql commands processed by sqlite. (Contributed by Torsten Landschoff in bpo-11688 [https://bugs.python.org/issue11688].)

ssl

The ssl module has two new random generation functions:

RAND_bytes(): generate cryptographically strong pseudo-random bytes.

RAND_pseudo_bytes(): generate pseudo-random bytes.

(Contribution par Victor Stinner; bpo-12049 [https://bugs.python.org/issue12049].)

The ssl module now exposes a finer-grained exception hierarchy in order to make it easier to inspect the various kinds of errors. (Contributed by Antoine Pitrou in bpo-11183 [https://bugs.python.org/issue11183].)

load_cert_chain() now accepts a password argument to be used if the private key is encrypted. (Contributed by Adam Simpkins in bpo-12803 [https://bugs.python.org/issue12803].)

Diffie-Hellman key exchange, both regular and Elliptic Curve-based, is now supported through the load_dh_params() and set_ecdh_curve() methods. (Contributed by Antoine Pitrou in bpo-13626 [https://bugs.python.org/issue13626] and bpo-13627 [https://bugs.python.org/issue13627].)

SSL sockets have a new get_channel_binding() method allowing the implementation of certain authentication mechanisms such as SCRAM-SHA-1-PLUS. (Contributed by Jacek Konieczny in bpo-12551 [https://bugs.python.org/issue12551].)

You can query the SSL compression algorithm used by an SSL socket, thanks to its new compression() method. The new attribute OP_NO_COMPRESSION can be used to disable compression. (Contributed by Antoine Pitrou in bpo-13634 [https://bugs.python.org/issue13634].)

Support has been added for the Next Protocol Negotiation extension using the ssl.SSLContext.set_npn_protocols() method. (Contributed by Colin Marc in bpo-14204 [https://bugs.python.org/issue14204].)

SSL errors can now be introspected more easily thanks to library and reason attributes. (Contributed by Antoine Pitrou in bpo-14837 [https://bugs.python.org/issue14837].)

The get_server_certificate() function now supports IPv6. (Contributed by Charles-François Natali in bpo-11811 [https://bugs.python.org/issue11811].)

New attribute OP_CIPHER_SERVER_PREFERENCE allows setting SSLv3 server sockets to use the server’s cipher ordering preference rather than the client’s (bpo-13635 [https://bugs.python.org/issue13635]).

stat

The undocumented tarfile.filemode function has been moved to stat.filemode(). It can be used to convert a file’s mode to a string of the form “-rwxrwxrwx”.

(Contribution par Giampaolo Rodolà; bpo-14807 [https://bugs.python.org/issue14807].)

struct

The struct module now supports ssize_t and size_t via the new codes n and N, respectively. (Contributed by Antoine Pitrou in bpo-3163 [https://bugs.python.org/issue3163].)

subprocess

Command strings can now be bytes objects on posix platforms. (Contributed by Victor Stinner in bpo-8513 [https://bugs.python.org/issue8513].)

A new constant DEVNULL allows suppressing output in a platform-independent fashion. (Contributed by Ross Lagerwall in bpo-5870 [https://bugs.python.org/issue5870].)

sys

The sys module has a new thread_info struct sequence holding informations about the thread implementation (bpo-11223 [https://bugs.python.org/issue11223]).

tarfile

tarfile now supports lzma encoding via the lzma module. (Contributed by Lars Gustäbel in bpo-5689 [https://bugs.python.org/issue5689].)

tempfile

tempfile.SpooledTemporaryFile’s truncate() method now accepts a size parameter. (Contributed by Ryan Kelly in bpo-9957 [https://bugs.python.org/issue9957].)

textwrap

The textwrap module has a new indent() that makes it straightforward to add a common prefix to selected lines in a block of text (bpo-13857 [https://bugs.python.org/issue13857]).

threading

threading.Condition, threading.Semaphore, threading.BoundedSemaphore, threading.Event, and threading.Timer, all of which used to be factory functions returning a class instance, are now classes and may be subclassed. (Contributed by Éric Araujo in bpo-10968 [https://bugs.python.org/issue10968].)

The threading.Thread constructor now accepts a daemon keyword argument to override the default behavior of inheriting the deamon flag value from the parent thread (bpo-6064 [https://bugs.python.org/issue6064]).

The formerly private function _thread.get_ident is now available as the public function threading.get_ident(). This eliminates several cases of direct access to the _thread module in the stdlib. Third party code that used _thread.get_ident should likewise be changed to use the new public interface.

time

The PEP 418 [https://www.python.org/dev/peps/pep-0418] added new functions to the time module:

get_clock_info(): Get information on a clock.

monotonic(): Monotonic clock (cannot go backward), not affected by system clock updates.

perf_counter(): Performance counter with the highest available resolution to measure a short duration.

process_time(): Sum of the system and user CPU time of the current process.

Other new functions:

clock_getres(), clock_gettime() and clock_settime() functions with CLOCK_xxx constants. (Contributed by Victor Stinner in bpo-10278 [https://bugs.python.org/issue10278].)

To improve cross platform consistency, sleep() now raises a ValueError when passed a negative sleep value. Previously this was an error on posix, but produced an infinite sleep on Windows.

types

Add a new types.MappingProxyType class: Read-only proxy of a mapping. (bpo-14386 [https://bugs.python.org/issue14386])

The new functions types.new_class() and types.prepare_class() provide support for PEP 3115 compliant dynamic type creation. (bpo-14588 [https://bugs.python.org/issue14588])

unittest

assertRaises(), assertRaisesRegex(), assertWarns(), and assertWarnsRegex() now accept a keyword argument msg when used as context managers. (Contributed by Ezio Melotti and Winston Ewert in bpo-10775 [https://bugs.python.org/issue10775].)

unittest.TestCase.run() now returns the TestResult object.

urllib

The Request class, now accepts a method argument used by get_method() to determine what HTTP method should be used. For example, this will send a 'HEAD' request:

>>> urlopen(Request('https://www.python.org', method='HEAD'))

(bpo-1673007 [https://bugs.python.org/issue1673007])

webbrowser

The webbrowser module supports more « browsers »: Google Chrome (named chrome, chromium, chrome-browser or chromium-browser depending on the version and operating system), and the generic launchers xdg-open, from the FreeDesktop.org project, and gvfs-open, which is the default URI handler for GNOME 3. (The former contributed by Arnaud Calmettes in bpo-13620 [https://bugs.python.org/issue13620], the latter by Matthias Klose in bpo-14493 [https://bugs.python.org/issue14493].)

xml.etree.ElementTree

The xml.etree.ElementTree module now imports its C accelerator by default; there is no longer a need to explicitly import xml.etree.cElementTree (this module stays for backwards compatibility, but is now deprecated). In addition, the iter family of methods of Element has been optimized (rewritten in C). The module’s documentation has also been greatly improved with added examples and a more detailed reference.

zlib

New attribute zlib.Decompress.eof makes it possible to distinguish between a properly-formed compressed stream and an incomplete or truncated one. (Contributed by Nadeem Vawda in bpo-12646 [https://bugs.python.org/issue12646].)

New attribute zlib.ZLIB_RUNTIME_VERSION reports the version string of the underlying zlib library that is loaded at runtime. (Contributed by Torsten Landschoff in bpo-12306 [https://bugs.python.org/issue12306].)

Optimizations

Major performance enhancements have been added:

Thanks to PEP 393 [https://www.python.org/dev/peps/pep-0393], some operations on Unicode strings have been optimized:

the memory footprint is divided by 2 to 4 depending on the text

encode an ASCII string to UTF-8 doesn’t need to encode characters anymore, the UTF-8 representation is shared with the ASCII representation

l’encodeur UTF-8 a été optimisé

repeating a single ASCII letter and getting a substring of an ASCII string is 4 times faster

UTF-8 is now 2x to 4x faster. UTF-16 encoding is now up to 10x faster.

(Contributed by Serhiy Storchaka, bpo-14624 [https://bugs.python.org/issue14624], bpo-14738 [https://bugs.python.org/issue14738] and bpo-15026 [https://bugs.python.org/issue15026].)

Build and C API Changes

Changes to Python’s build process and to the C API include:

New PEP 3118 [https://www.python.org/dev/peps/pep-3118] related function:

PyMemoryView_FromMemory()

PEP 393 [https://www.python.org/dev/peps/pep-0393] added new Unicode types, macros and functions:

High-level API:

PyUnicode_CopyCharacters()

PyUnicode_FindChar()

PyUnicode_GetLength(), PyUnicode_GET_LENGTH

PyUnicode_New()

PyUnicode_Substring()

PyUnicode_ReadChar(), PyUnicode_WriteChar()

Low-level API:

Py_UCS1, Py_UCS2, Py_UCS4 types

PyASCIIObject and PyCompactUnicodeObject structures

PyUnicode_READY

PyUnicode_FromKindAndData()

PyUnicode_AsUCS4(), PyUnicode_AsUCS4Copy()

PyUnicode_DATA, PyUnicode_1BYTE_DATA, PyUnicode_2BYTE_DATA, PyUnicode_4BYTE_DATA

PyUnicode_KIND with PyUnicode_Kind enum: PyUnicode_WCHAR_KIND, PyUnicode_1BYTE_KIND, PyUnicode_2BYTE_KIND, PyUnicode_4BYTE_KIND

PyUnicode_READ, PyUnicode_READ_CHAR, PyUnicode_WRITE

PyUnicode_MAX_CHAR_VALUE

PyArg_ParseTuple now accepts a bytearray for the c format (bpo-12380 [https://bugs.python.org/issue12380]).

Deprecated

Unsupported Operating Systems

OS/2 and VMS are no longer supported due to the lack of a maintainer.

Windows 2000 and Windows platforms which set COMSPEC to command.com are no longer supported due to maintenance burden.

OSF support, which was deprecated in 3.2, has been completely removed.

Deprecated Python modules, functions and methods

Passing a non-empty string to object.__format__() is deprecated, and will produce a TypeError in Python 3.4 (bpo-9856 [https://bugs.python.org/issue9856]).

The unicode_internal codec has been deprecated because of the PEP 393 [https://www.python.org/dev/peps/pep-0393], use UTF-8, UTF-16 (utf-16-le or utf-16-be), or UTF-32 (utf-32-le or utf-32-be)

ftplib.FTP.nlst() and ftplib.FTP.dir(): use ftplib.FTP.mlsd()

platform.popen(): use the subprocess module. Check especially the Remplacer les fonctions plus anciennes par le module subprocess section (bpo-11377 [https://bugs.python.org/issue11377]).

bpo-13374 [https://bugs.python.org/issue13374]: The Windows bytes API has been deprecated in the os module. Use Unicode filenames, instead of bytes filenames, to not depend on the ANSI code page anymore and to support any filename.

bpo-13988 [https://bugs.python.org/issue13988]: The xml.etree.cElementTree module is deprecated. The accelerator is used automatically whenever available.

The behaviour of time.clock() depends on the platform: use the new time.perf_counter() or time.process_time() function instead, depending on your requirements, to have a well defined behaviour.

The os.stat_float_times() function is deprecated.

abc module:

abc.abstractproperty has been deprecated, use property with abc.abstractmethod() instead.

abc.abstractclassmethod has been deprecated, use classmethod with abc.abstractmethod() instead.

abc.abstractstaticmethod has been deprecated, use staticmethod with abc.abstractmethod() instead.

importlib package:

importlib.abc.SourceLoader.path_mtime() is now deprecated in favour of importlib.abc.SourceLoader.path_stats() as bytecode files now store both the modification time and size of the source file the bytecode file was compiled from.

Deprecated functions and types of the C API

The Py_UNICODE has been deprecated by PEP 393 [https://www.python.org/dev/peps/pep-0393] and will be removed in Python 4. All functions using this type are deprecated:

Unicode functions and methods using Py_UNICODE and Py_UNICODE* types:

PyUnicode_FromUnicode: use PyUnicode_FromWideChar() or PyUnicode_FromKindAndData()

PyUnicode_AS_UNICODE, PyUnicode_AsUnicode(), PyUnicode_AsUnicodeAndSize(): use PyUnicode_AsWideCharString()

PyUnicode_AS_DATA: use PyUnicode_DATA with PyUnicode_READ and PyUnicode_WRITE

PyUnicode_GET_SIZE, PyUnicode_GetSize(): use PyUnicode_GET_LENGTH or PyUnicode_GetLength()

PyUnicode_GET_DATA_SIZE: use PyUnicode_GET_LENGTH(str) * PyUnicode_KIND(str) (only work on ready strings)

PyUnicode_AsUnicodeCopy(): use PyUnicode_AsUCS4Copy() or PyUnicode_AsWideCharString()

PyUnicode_GetMax()

Functions and macros manipulating Py_UNICODE* strings:

Py_UNICODE_strlen: use PyUnicode_GetLength() or PyUnicode_GET_LENGTH

Py_UNICODE_strcat : utilisez PyUnicode_CopyCharacters() ou PyUnicode_FromFormat()

Py_UNICODE_strcpy, Py_UNICODE_strncpy, Py_UNICODE_COPY: use PyUnicode_CopyCharacters() or PyUnicode_Substring()

Py_UNICODE_strcmp : utilisez PyUnicode_Compare()

Py_UNICODE_strncmp : utilisez PyUnicode_Tailmatch()

Py_UNICODE_strchr, Py_UNICODE_strrchr : utilisez PyUnicode_FindChar()

Py_UNICODE_FILL : utilisez PyUnicode_Fill()

Py_UNICODE_MATCH

Encodeurs :

PyUnicode_Encode() : utilisez PyUnicode_AsEncodedObject()

PyUnicode_EncodeUTF7()

PyUnicode_EncodeUTF8() : utilisez PyUnicode_AsUTF8() ou PyUnicode_AsUTF8String()

PyUnicode_EncodeUTF32()

PyUnicode_EncodeUTF16()

PyUnicode_EncodeUnicodeEscape:() utilisez PyUnicode_AsUnicodeEscapeString()

PyUnicode_EncodeRawUnicodeEscape:() utilisez PyUnicode_AsRawUnicodeEscapeString()

PyUnicode_EncodeLatin1() : utilisez PyUnicode_AsLatin1String()

PyUnicode_EncodeASCII() : utilisez PyUnicode_AsASCIIString()

PyUnicode_EncodeCharmap()

PyUnicode_TranslateCharmap()

PyUnicode_EncodeMBCS(): use PyUnicode_AsMBCSString() or PyUnicode_EncodeCodePage() (with CP_ACP code_page)

PyUnicode_EncodeDecimal(), PyUnicode_TransformDecimalToASCII()

Fonctionnalités obsolètes

The array module’s 'u' format code is now deprecated and will be removed in Python 4 together with the rest of the (Py_UNICODE) API.

Portage vers Python 3.3

This section lists previously described changes and other bugfixes that may require changes to your code.

Portage de code Python

Hash randomization is enabled by default. Set the PYTHONHASHSEED environment variable to 0 to disable hash randomization. See also the object.__hash__() method.

bpo-12326 [https://bugs.python.org/issue12326]: On Linux, sys.platform doesn’t contain the major version anymore. It is now always “linux”, instead of “linux2” or “linux3” depending on the Linux version used to build Python. Replace sys.platform == “linux2” with sys.platform.startswith(“linux”), or directly sys.platform == “linux” if you don’t need to support older Python versions.

bpo-13847 [https://bugs.python.org/issue13847], bpo-14180 [https://bugs.python.org/issue14180]: time and datetime: OverflowError is now raised instead of ValueError if a timestamp is out of range. OSError is now raised if C functions gmtime() or localtime() failed.

The default finders used by import now utilize a cache of what is contained within a specific directory. If you create a Python source file or sourceless bytecode file, make sure to call importlib.invalidate_caches() to clear out the cache for the finders to notice the new file.

ImportError now uses the full name of the module that was attempted to be imported. Doctests that check ImportErrors” message will need to be updated to use the full name of the module instead of just the tail of the name.

The index argument to __import__() now defaults to 0 instead of -1 and no longer support negative values. It was an oversight when PEP 328 [https://www.python.org/dev/peps/pep-0328] was implemented that the default value remained -1. If you need to continue to perform a relative import followed by an absolute import, then perform the relative import using an index of 1, followed by another import using an index of 0. It is preferred, though, that you use importlib.import_module() rather than call __import__() directly.

__import__() no longer allows one to use an index value other than 0 for top-level modules. E.g. __import__('sys', level=1) is now an error.

Because sys.meta_path and sys.path_hooks now have finders on them by default, you will most likely want to use list.insert() instead of list.append() to add to those lists.

Because None is now inserted into sys.path_importer_cache, if you are clearing out entries in the dictionary of paths that do not have a finder, you will need to remove keys paired with values of None and imp.NullImporter to be backwards-compatible. This will lead to extra overhead on older versions of Python that re-insert None into sys.path_importer_cache where it represents the use of implicit finders, but semantically it should not change anything.

importlib.abc.Finder no longer specifies a find_module() abstract method that must be implemented. If you were relying on subclasses to implement that method, make sure to check for the method’s existence first. You will probably want to check for find_loader() first, though, in the case of working with path entry finders.

pkgutil has been converted to use importlib internally. This eliminates many edge cases where the old behaviour of the PEP 302 import emulation failed to match the behaviour of the real import system. The import emulation itself is still present, but is now deprecated. The pkgutil.iter_importers() and pkgutil.walk_packages() functions special case the standard import hooks so they are still supported even though they do not provide the non-standard iter_modules() method.

A longstanding RFC-compliance bug (bpo-1079 [https://bugs.python.org/issue1079]) in the parsing done by email.header.decode_header() has been fixed. Code that uses the standard idiom to convert encoded headers into unicode (str(make_header(decode_header(h))) will see no change, but code that looks at the individual tuples returned by decode_header will see that whitespace that precedes or follows ASCII sections is now included in the ASCII section. Code that builds headers using make_header should also continue to work without change, since make_header continues to add whitespace between ASCII and non-ASCII sections if it is not already present in the input strings.

email.utils.formataddr() now does the correct content transfer encoding when passed non-ASCII display names. Any code that depended on the previous buggy behavior that preserved the non-ASCII unicode in the formatted output string will need to be changed (bpo-1690608 [https://bugs.python.org/issue1690608]).

poplib.POP3.quit() may now raise protocol errors like all other poplib methods. Code that assumes quit does not raise poplib.error_proto errors may need to be changed if errors on quit are encountered by a particular application (bpo-11291 [https://bugs.python.org/issue11291]).

The strict argument to email.parser.Parser, deprecated since Python 2.4, has finally been removed.

The deprecated method unittest.TestCase.assertSameElements has been removed.

The deprecated variable time.accept2dyear has been removed.

The deprecated Context._clamp attribute has been removed from the decimal module. It was previously replaced by the public attribute clamp. (See bpo-8540 [https://bugs.python.org/issue8540].)

The undocumented internal helper class SSLFakeFile has been removed from smtplib, since its functionality has long been provided directly by socket.socket.makefile().

Passing a negative value to time.sleep() on Windows now raises an error instead of sleeping forever. It has always raised an error on posix.

The ast.__version__ constant has been removed. If you need to make decisions affected by the AST version, use sys.version_info to make the decision.

Code that used to work around the fact that the threading module used factory functions by subclassing the private classes will need to change to subclass the now-public classes.

The undocumented debugging machinery in the threading module has been removed, simplifying the code. This should have no effect on production code, but is mentioned here in case any application debug frameworks were interacting with it (bpo-13550 [https://bugs.python.org/issue13550]).

Porting C code

In the course of changes to the buffer API the undocumented smalltable member of the Py_buffer structure has been removed and the layout of the PyMemoryViewObject has changed.

All extensions relying on the relevant parts in memoryobject.h or object.h must be rebuilt.

Due to PEP 393, the Py_UNICODE type and all functions using this type are deprecated (but will stay available for at least five years). If you were using low-level Unicode APIs to construct and access unicode objects and you want to benefit of the memory footprint reduction provided by PEP 393, you have to convert your code to the new Unicode API.

However, if you only have been using high-level functions such as PyUnicode_Concat(), PyUnicode_Join() or PyUnicode_FromFormat(), your code will automatically take advantage of the new unicode representations.

PyImport_GetMagicNumber() now returns -1 upon failure.

As a negative value for the level argument to __import__() is no longer valid, the same now holds for PyImport_ImportModuleLevel(). This also means that the value of level used by PyImport_ImportModuleEx() is now 0 instead of -1.

Building C extensions

The range of possible file names for C extensions has been narrowed. Very rarely used spellings have been suppressed: under POSIX, files named xxxmodule.so, xxxmodule.abi3.so and xxxmodule.cpython-*.so are no longer recognized as implementing the xxx module. If you had been generating such files, you have to switch to the other spellings (i.e., remove the module string from the file names).

(implemented in bpo-14040 [https://bugs.python.org/issue14040].)

Command Line Switch Changes

The -Q command-line flag and related artifacts have been removed. Code checking sys.flags.division_warning will need updating.

(bpo-10998 [https://bugs.python.org/issue10998], contributed by Éric Araujo.)

When python is started with -S, import site will no longer add site-specific paths to the module search paths. In previous versions, it did.

(bpo-11591 [https://bugs.python.org/issue11591], contributed by Carl Meyer with editions by Éric Araujo.)

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Nouveautés de Python 3.2

Auteur

Raymond Hettinger

This article explains the new features in Python 3.2 as compared to 3.1. It focuses on a few highlights and gives a few examples. For full details, see the Misc/NEWS [https://hg.python.org/cpython/file/3.2/Misc/NEWS] file.

Voir aussi

PEP 392 [https://www.python.org/dev/peps/pep-0392] - Python 3.2 Release Schedule

PEP 384: Defining a Stable ABI

In the past, extension modules built for one Python version were often not usable with other Python versions. Particularly on Windows, every feature release of Python required rebuilding all extension modules that one wanted to use. This requirement was the result of the free access to Python interpreter internals that extension modules could use.

With Python 3.2, an alternative approach becomes available: extension modules which restrict themselves to a limited API (by defining Py_LIMITED_API) cannot use many of the internals, but are constrained to a set of API functions that are promised to be stable for several releases. As a consequence, extension modules built for 3.2 in that mode will also work with 3.3, 3.4, and so on. Extension modules that make use of details of memory structures can still be built, but will need to be recompiled for every feature release.

Voir aussi

PEP 384 [https://www.python.org/dev/peps/pep-0384] - Defining a Stable ABI

PEP written by Martin von Löwis.

PEP 389: Argparse Command Line Parsing Module

A new module for command line parsing, argparse, was introduced to overcome the limitations of optparse which did not provide support for positional arguments (not just options), subcommands, required options and other common patterns of specifying and validating options.

This module has already had widespread success in the community as a third-party module. Being more fully featured than its predecessor, the argparse module is now the preferred module for command-line processing. The older module is still being kept available because of the substantial amount of legacy code that depends on it.

Here’s an annotated example parser showing features like limiting results to a set of choices, specifying a metavar in the help screen, validating that one or more positional arguments is present, and making a required option:

import argparse
parser = argparse.ArgumentParser(
            description = 'Manage servers',         # main description for help
            epilog = 'Tested on Solaris and Linux') # displayed after help
parser.add_argument('action',                       # argument name
            choices = ['deploy', 'start', 'stop'],  # three allowed values
            help = 'action on each target')         # help msg
parser.add_argument('targets',
            metavar = 'HOSTNAME',                   # var name used in help msg
            nargs = '+',                            # require one or more targets
            help = 'url for target machines')       # help msg explanation
parser.add_argument('-u', '--user',                 # -u or --user option
            required = True,                        # make it a required argument
            help = 'login as user')

Example of calling the parser on a command string:

>>> cmd = 'deploy sneezy.example.com sleepy.example.com -u skycaptain'
>>> result = parser.parse_args(cmd.split())
>>> result.action
'deploy'
>>> result.targets
['sneezy.example.com', 'sleepy.example.com']
>>> result.user
'skycaptain'

Example of the parser’s automatically generated help:

>>> parser.parse_args('-h'.split())

usage: manage_cloud.py [-h] -u USER
                       {deploy,start,stop} HOSTNAME [HOSTNAME ...]

Manage servers

positional arguments:
  {deploy,start,stop}   action on each target
  HOSTNAME              url for target machines

optional arguments:
  -h, --help            show this help message and exit
  -u USER, --user USER  login as user

Tested on Solaris and Linux

An especially nice argparse feature is the ability to define subparsers, each with their own argument patterns and help displays:

import argparse
parser = argparse.ArgumentParser(prog='HELM')
subparsers = parser.add_subparsers()

parser_l = subparsers.add_parser('launch', help='Launch Control')   # first subgroup
parser_l.add_argument('-m', '--missiles', action='store_true')
parser_l.add_argument('-t', '--torpedos', action='store_true')

parser_m = subparsers.add_parser('move', help='Move Vessel',        # second subgroup
                                 aliases=('steer', 'turn'))         # equivalent names
parser_m.add_argument('-c', '--course', type=int, required=True)
parser_m.add_argument('-s', '--speed', type=int, default=0)

$ ./helm.py --help                         # top level help (launch and move)
$ ./helm.py launch --help                  # help for launch options
$ ./helm.py launch --missiles              # set missiles=True and torpedos=False
$ ./helm.py steer --course 180 --speed 5   # set movement parameters

Voir aussi

PEP 389 [https://www.python.org/dev/peps/pep-0389] - New Command Line Parsing Module

PEP written by Steven Bethard.

Mettre à jour du code optparse for details on the differences from optparse.

PEP 391: Dictionary Based Configuration for Logging

The logging module provided two kinds of configuration, one style with function calls for each option or another style driven by an external file saved in a ConfigParser format. Those options did not provide the flexibility to create configurations from JSON or YAML files, nor did they support incremental configuration, which is needed for specifying logger options from a command line.

To support a more flexible style, the module now offers logging.config.dictConfig() for specifying logging configuration with plain Python dictionaries. The configuration options include formatters, handlers, filters, and loggers. Here’s a working example of a configuration dictionary:

{"version": 1,
 "formatters": {"brief": {"format": "%(levelname)-8s: %(name)-15s: %(message)s"},
                "full": {"format": "%(asctime)s %(name)-15s %(levelname)-8s %(message)s"}
                },
 "handlers": {"console": {
                   "class": "logging.StreamHandler",
                   "formatter": "brief",
                   "level": "INFO",
                   "stream": "ext://sys.stdout"},
              "console_priority": {
                   "class": "logging.StreamHandler",
                   "formatter": "full",
                   "level": "ERROR",
                   "stream": "ext://sys.stderr"}
              },
 "root": {"level": "DEBUG", "handlers": ["console", "console_priority"]}}

If that dictionary is stored in a file called conf.json, it can be loaded and called with code like this:

>>> import json, logging.config
>>> with open('conf.json') as f:
...     conf = json.load(f)
...
>>> logging.config.dictConfig(conf)
>>> logging.info("Transaction completed normally")
INFO    : root           : Transaction completed normally
>>> logging.critical("Abnormal termination")
2011-02-17 11:14:36,694 root            CRITICAL Abnormal termination

Voir aussi

PEP 391 [https://www.python.org/dev/peps/pep-0391] - Dictionary Based Configuration for Logging

PEP written by Vinay Sajip.

PEP 3148: The concurrent.futures module

Code for creating and managing concurrency is being collected in a new top-level namespace, concurrent. Its first member is a futures package which provides a uniform high-level interface for managing threads and processes.

The design for concurrent.futures was inspired by the java.util.concurrent package. In that model, a running call and its result are represented by a Future object that abstracts features common to threads, processes, and remote procedure calls. That object supports status checks (running or done), timeouts, cancellations, adding callbacks, and access to results or exceptions.

The primary offering of the new module is a pair of executor classes for launching and managing calls. The goal of the executors is to make it easier to use existing tools for making parallel calls. They save the effort needed to setup a pool of resources, launch the calls, create a results queue, add time-out handling, and limit the total number of threads, processes, or remote procedure calls.

Ideally, each application should share a single executor across multiple components so that process and thread limits can be centrally managed. This solves the design challenge that arises when each component has its own competing strategy for resource management.

Both classes share a common interface with three methods: submit() for scheduling a callable and returning a Future object; map() for scheduling many asynchronous calls at a time, and shutdown() for freeing resources. The class is a context manager and can be used in a with statement to assure that resources are automatically released when currently pending futures are done executing.

A simple of example of ThreadPoolExecutor is a launch of four parallel threads for copying files:

import concurrent.futures, shutil
with concurrent.futures.ThreadPoolExecutor(max_workers=4) as e:
    e.submit(shutil.copy, 'src1.txt', 'dest1.txt')
    e.submit(shutil.copy, 'src2.txt', 'dest2.txt')
    e.submit(shutil.copy, 'src3.txt', 'dest3.txt')
    e.submit(shutil.copy, 'src3.txt', 'dest4.txt')

Voir aussi

PEP 3148 [https://www.python.org/dev/peps/pep-3148] - Futures – Execute Computations Asynchronously

PEP written by Brian Quinlan.

Code for Threaded Parallel URL reads, an example using threads to fetch multiple web pages in parallel.

Code for computing prime numbers in parallel, an example demonstrating ProcessPoolExecutor.

PEP 3147: PYC Repository Directories

Python’s scheme for caching bytecode in .pyc files did not work well in environments with multiple Python interpreters. If one interpreter encountered a cached file created by another interpreter, it would recompile the source and overwrite the cached file, thus losing the benefits of caching.

The issue of « pyc fights » has become more pronounced as it has become commonplace for Linux distributions to ship with multiple versions of Python. These conflicts also arise with CPython alternatives such as Unladen Swallow.

To solve this problem, Python’s import machinery has been extended to use distinct filenames for each interpreter. Instead of Python 3.2 and Python 3.3 and Unladen Swallow each competing for a file called « mymodule.pyc », they will now look for « mymodule.cpython-32.pyc », « mymodule.cpython-33.pyc », and « mymodule.unladen10.pyc ». And to prevent all of these new files from cluttering source directories, the pyc files are now collected in a « __pycache__ » directory stored under the package directory.

Aside from the filenames and target directories, the new scheme has a few aspects that are visible to the programmer:

Imported modules now have a __cached__ attribute which stores the name of the actual file that was imported:

>>> import collections
>>> collections.__cached__
'c:/py32/lib/__pycache__/collections.cpython-32.pyc'

The tag that is unique to each interpreter is accessible from the imp module:

>>> import imp
>>> imp.get_tag()
'cpython-32'

Scripts that try to deduce source filename from the imported file now need to be smarter. It is no longer sufficient to simply strip the « c » from a « .pyc » filename. Instead, use the new functions in the imp module:

>>> imp.source_from_cache('c:/py32/lib/__pycache__/collections.cpython-32.pyc')
'c:/py32/lib/collections.py'
>>> imp.cache_from_source('c:/py32/lib/collections.py')
'c:/py32/lib/__pycache__/collections.cpython-32.pyc'

The py_compile and compileall modules have been updated to reflect the new naming convention and target directory. The command-line invocation of compileall has new options: -i for specifying a list of files and directories to compile and -b which causes bytecode files to be written to their legacy location rather than __pycache__.

The importlib.abc module has been updated with new abstract base classes for loading bytecode files. The obsolete ABCs, PyLoader and PyPycLoader, have been deprecated (instructions on how to stay Python 3.1 compatible are included with the documentation).

Voir aussi

PEP 3147 [https://www.python.org/dev/peps/pep-3147] - PYC Repository Directories

PEP written by Barry Warsaw.

PEP 3149: ABI Version Tagged .so Files

The PYC repository directory allows multiple bytecode cache files to be co-located. This PEP implements a similar mechanism for shared object files by giving them a common directory and distinct names for each version.

The common directory is « pyshared » and the file names are made distinct by identifying the Python implementation (such as CPython, PyPy, Jython, etc.), the major and minor version numbers, and optional build flags (such as « d » for debug, « m » for pymalloc, « u » for wide-unicode). For an arbitrary package « foo », you may see these files when the distribution package is installed:

/usr/share/pyshared/foo.cpython-32m.so
/usr/share/pyshared/foo.cpython-33md.so

In Python itself, the tags are accessible from functions in the sysconfig module:

>>> import sysconfig
>>> sysconfig.get_config_var('SOABI')       # find the version tag
'cpython-32mu'
>>> sysconfig.get_config_var('EXT_SUFFIX')  # find the full filename extension
'.cpython-32mu.so'

Voir aussi

PEP 3149 [https://www.python.org/dev/peps/pep-3149] - ABI Version Tagged .so Files

PEP written by Barry Warsaw.

PEP 3333: Python Web Server Gateway Interface v1.0.1

This informational PEP clarifies how bytes/text issues are to be handled by the WSGI protocol. The challenge is that string handling in Python 3 is most conveniently handled with the str type even though the HTTP protocol is itself bytes oriented.

The PEP differentiates so-called native strings that are used for request/response headers and metadata versus byte strings which are used for the bodies of requests and responses.

The native strings are always of type str but are restricted to code points between U+0000 through U+00FF which are translatable to bytes using Latin-1 encoding. These strings are used for the keys and values in the environment dictionary and for response headers and statuses in the start_response() function. They must follow RFC 2616 [https://tools.ietf.org/html/rfc2616.html] with respect to encoding. That is, they must either be ISO-8859-1 characters or use RFC 2047 [https://tools.ietf.org/html/rfc2047.html] MIME encoding.

For developers porting WSGI applications from Python 2, here are the salient points:

If the app already used strings for headers in Python 2, no change is needed.

If instead, the app encoded output headers or decoded input headers, then the headers will need to be re-encoded to Latin-1. For example, an output header encoded in utf-8 was using h.encode('utf-8') now needs to convert from bytes to native strings using h.encode('utf-8').decode('latin-1').

Values yielded by an application or sent using the write() method must be byte strings. The start_response() function and environ must use native strings. The two cannot be mixed.

For server implementers writing CGI-to-WSGI pathways or other CGI-style protocols, the users must to be able access the environment using native strings even though the underlying platform may have a different convention. To bridge this gap, the wsgiref module has a new function, wsgiref.handlers.read_environ() for transcoding CGI variables from os.environ into native strings and returning a new dictionary.

Voir aussi

PEP 3333 [https://www.python.org/dev/peps/pep-3333] - Python Web Server Gateway Interface v1.0.1

PEP written by Phillip Eby.

Other Language Changes

Some smaller changes made to the core Python language are:

String formatting for format() and str.format() gained new capabilities for the format character #. Previously, for integers in binary, octal, or hexadecimal, it caused the output to be prefixed with “0b”, “0o”, or “0x” respectively. Now it can also handle floats, complex, and Decimal, causing the output to always have a decimal point even when no digits follow it.

>>> format(20, '#o')
'0o24'
>>> format(12.34, '#5.0f')
'  12.'

(Suggested by Mark Dickinson and implemented by Eric Smith in bpo-7094 [https://bugs.python.org/issue7094].)

There is also a new str.format_map() method that extends the capabilities of the existing str.format() method by accepting arbitrary mapping objects. This new method makes it possible to use string formatting with any of Python’s many dictionary-like objects such as defaultdict, Shelf, ConfigParser, or dbm. It is also useful with custom dict subclasses that normalize keys before look-up or that supply a __missing__() method for unknown keys:

>>> import shelve
>>> d = shelve.open('tmp.shl')
>>> 'The {project_name} status is {status} as of {date}'.format_map(d)
'The testing project status is green as of February 15, 2011'

>>> class LowerCasedDict(dict):
...     def __getitem__(self, key):
...         return dict.__getitem__(self, key.lower())
>>> lcd = LowerCasedDict(part='widgets', quantity=10)
>>> 'There are {QUANTITY} {Part} in stock'.format_map(lcd)
'There are 10 widgets in stock'

>>> class PlaceholderDict(dict):
...     def __missing__(self, key):
...         return '<{}>'.format(key)
>>> 'Hello {name}, welcome to {location}'.format_map(PlaceholderDict())
'Hello <name>, welcome to <location>'

(Suggested by Raymond Hettinger and implemented by Eric Smith in bpo-6081 [https://bugs.python.org/issue6081].)

The interpreter can now be started with a quiet option, -q, to prevent the copyright and version information from being displayed in the interactive mode. The option can be introspected using the sys.flags attribute:

$ python -q
>>> sys.flags
sys.flags(debug=0, division_warning=0, inspect=0, interactive=0,
optimize=0, dont_write_bytecode=0, no_user_site=0, no_site=0,
ignore_environment=0, verbose=0, bytes_warning=0, quiet=1)

(Contribution par Marcin Wojdyr; bpo-1772833 [https://bugs.python.org/issue1772833]).

The hasattr() function works by calling getattr() and detecting whether an exception is raised. This technique allows it to detect methods created dynamically by __getattr__() or __getattribute__() which would otherwise be absent from the class dictionary. Formerly, hasattr would catch any exception, possibly masking genuine errors. Now, hasattr has been tightened to only catch AttributeError and let other exceptions pass through:

>>> class A:
...     @property
...     def f(self):
...         return 1 // 0
...
>>> a = A()
>>> hasattr(a, 'f')
Traceback (most recent call last):
  ...
ZeroDivisionError: integer division or modulo by zero

(Discovered by Yury Selivanov and fixed by Benjamin Peterson; bpo-9666 [https://bugs.python.org/issue9666].)

The str() of a float or complex number is now the same as its repr(). Previously, the str() form was shorter but that just caused confusion and is no longer needed now that the shortest possible repr() is displayed by default:

>>> import math
>>> repr(math.pi)
'3.141592653589793'
>>> str(math.pi)
'3.141592653589793'

(Proposed and implemented by Mark Dickinson; bpo-9337 [https://bugs.python.org/issue9337].)

memoryview objects now have a release() method and they also now support the context management protocol. This allows timely release of any resources that were acquired when requesting a buffer from the original object.

>>> with memoryview(b'abcdefgh') as v:
...     print(v.tolist())
[97, 98, 99, 100, 101, 102, 103, 104]

(Contribution par Antoine Pitrou; bpo-9757 [https://bugs.python.org/issue9757].)

Previously it was illegal to delete a name from the local namespace if it occurs as a free variable in a nested block:

def outer(x):
    def inner():
        return x
    inner()
    del x

This is now allowed. Remember that the target of an except clause is cleared, so this code which used to work with Python 2.6, raised a SyntaxError with Python 3.1 and now works again:

def f():
    def print_error():
        print(e)
    try:
        something
    except Exception as e:
        print_error()
        # implicit "del e" here

(See bpo-4617 [https://bugs.python.org/issue4617].)

The internal structsequence tool now creates subclasses of tuple. This means that C structures like those returned by os.stat(), time.gmtime(), and sys.version_info now work like a named tuple and now work with functions and methods that expect a tuple as an argument. This is a big step forward in making the C structures as flexible as their pure Python counterparts:

>>> import sys
>>> isinstance(sys.version_info, tuple)
True
>>> 'Version %d.%d.%d %s(%d)' % sys.version_info
'Version 3.2.0 final(0)'

(Suggested by Arfrever Frehtes Taifersar Arahesis and implemented by Benjamin Peterson in bpo-8413 [https://bugs.python.org/issue8413].)

Warnings are now easier to control using the PYTHONWARNINGS environment variable as an alternative to using -W at the command line:

$ export PYTHONWARNINGS='ignore::RuntimeWarning::,once::UnicodeWarning::'

(Suggested by Barry Warsaw and implemented by Philip Jenvey in bpo-7301 [https://bugs.python.org/issue7301].)

A new warning category, ResourceWarning, has been added. It is emitted when potential issues with resource consumption or cleanup are detected. It is silenced by default in normal release builds but can be enabled through the means provided by the warnings module, or on the command line.

A ResourceWarning is issued at interpreter shutdown if the gc.garbage list isn’t empty, and if gc.DEBUG_UNCOLLECTABLE is set, all uncollectable objects are printed. This is meant to make the programmer aware that their code contains object finalization issues.

A ResourceWarning is also issued when a file object is destroyed without having been explicitly closed. While the deallocator for such object ensures it closes the underlying operating system resource (usually, a file descriptor), the delay in deallocating the object could produce various issues, especially under Windows. Here is an example of enabling the warning from the command line:

$ python -q -Wdefault
>>> f = open("foo", "wb")
>>> del f
__main__:1: ResourceWarning: unclosed file <_io.BufferedWriter name='foo'>

(Added by Antoine Pitrou and Georg Brandl in bpo-10093 [https://bugs.python.org/issue10093] and bpo-477863 [https://bugs.python.org/issue477863].)

range objects now support index and count methods. This is part of an effort to make more objects fully implement the collections.Sequence abstract base class. As a result, the language will have a more uniform API. In addition, range objects now support slicing and negative indices, even with values larger than sys.maxsize. This makes range more interoperable with lists:

>>> range(0, 100, 2).count(10)
1
>>> range(0, 100, 2).index(10)
5
>>> range(0, 100, 2)[5]
10
>>> range(0, 100, 2)[0:5]
range(0, 10, 2)

(Contributed by Daniel Stutzbach in bpo-9213 [https://bugs.python.org/issue9213], by Alexander Belopolsky in bpo-2690 [https://bugs.python.org/issue2690], and by Nick Coghlan in bpo-10889 [https://bugs.python.org/issue10889].)

The callable() builtin function from Py2.x was resurrected. It provides a concise, readable alternative to using an abstract base class in an expression like isinstance(x, collections.Callable):

>>> callable(max)
True
>>> callable(20)
False

(See bpo-10518 [https://bugs.python.org/issue10518].)

Python’s import mechanism can now load modules installed in directories with non-ASCII characters in the path name. This solved an aggravating problem with home directories for users with non-ASCII characters in their usernames.

(Required extensive work by Victor Stinner in bpo-9425 [https://bugs.python.org/issue9425].)

New, Improved, and Deprecated Modules

Python’s standard library has undergone significant maintenance efforts and quality improvements.

The biggest news for Python 3.2 is that the email package, mailbox module, and nntplib modules now work correctly with the bytes/text model in Python 3. For the first time, there is correct handling of messages with mixed encodings.

Throughout the standard library, there has been more careful attention to encodings and text versus bytes issues. In particular, interactions with the operating system are now better able to exchange non-ASCII data using the Windows MBCS encoding, locale-aware encodings, or UTF-8.

Another significant win is the addition of substantially better support for SSL connections and security certificates.

In addition, more classes now implement a context manager to support convenient and reliable resource clean-up using a with statement.

email

The usability of the email package in Python 3 has been mostly fixed by the extensive efforts of R. David Murray. The problem was that emails are typically read and stored in the form of bytes rather than str text, and they may contain multiple encodings within a single email. So, the email package had to be extended to parse and generate email messages in bytes format.

New functions message_from_bytes() and message_from_binary_file(), and new classes BytesFeedParser and BytesParser allow binary message data to be parsed into model objects.

Given bytes input to the model, get_payload() will by default decode a message body that has a Content-Transfer-Encoding of 8bit using the charset specified in the MIME headers and return the resulting string.

Given bytes input to the model, Generator will convert message bodies that have a Content-Transfer-Encoding of 8bit to instead have a 7bit Content-Transfer-Encoding.

Headers with unencoded non-ASCII bytes are deemed to be RFC 2047 [https://tools.ietf.org/html/rfc2047.html]-encoded using the unknown-8bit character set.

A new class BytesGenerator produces bytes as output, preserving any unchanged non-ASCII data that was present in the input used to build the model, including message bodies with a Content-Transfer-Encoding of 8bit.

The smtplib SMTP class now accepts a byte string for the msg argument to the sendmail() method, and a new method, send_message() accepts a Message object and can optionally obtain the from_addr and to_addrs addresses directly from the object.

(Proposed and implemented by R. David Murray, bpo-4661 [https://bugs.python.org/issue4661] and bpo-10321 [https://bugs.python.org/issue10321].)

elementtree

The xml.etree.ElementTree package and its xml.etree.cElementTree counterpart have been updated to version 1.3.

Several new and useful functions and methods have been added:

xml.etree.ElementTree.fromstringlist() which builds an XML document from a sequence of fragments

xml.etree.ElementTree.register_namespace() for registering a global namespace prefix

xml.etree.ElementTree.tostringlist() for string representation including all sublists

xml.etree.ElementTree.Element.extend() for appending a sequence of zero or more elements

xml.etree.ElementTree.Element.iterfind() searches an element and subelements

xml.etree.ElementTree.Element.itertext() creates a text iterator over an element and its subelements

xml.etree.ElementTree.TreeBuilder.end() closes the current element

xml.etree.ElementTree.TreeBuilder.doctype() handles a doctype declaration

Deux méthodes ont été dépréciées :

xml.etree.ElementTree.getchildren() use list(elem) instead.

xml.etree.ElementTree.getiterator() use Element.iter instead.

For details of the update, see Introducing ElementTree [http://effbot.org/zone/elementtree-13-intro.htm] on Fredrik Lundh’s website.

(Contribution par Florent Xicluna et Fredrik Lundh; bpo-6472 [https://bugs.python.org/issue6472])

functools

The functools module includes a new decorator for caching function calls. functools.lru_cache() can save repeated queries to an external resource whenever the results are expected to be the same.

For example, adding a caching decorator to a database query function can save database accesses for popular searches:

>>> import functools
>>> @functools.lru_cache(maxsize=300)
... def get_phone_number(name):
...     c = conn.cursor()
...     c.execute('SELECT phonenumber FROM phonelist WHERE name=?', (name,))
...     return c.fetchone()[0]

>>> for name in user_requests:
...     get_phone_number(name)        # cached lookup

To help with choosing an effective cache size, the wrapped function is instrumented for tracking cache statistics:

>>> get_phone_number.cache_info()
CacheInfo(hits=4805, misses=980, maxsize=300, currsize=300)

If the phonelist table gets updated, the outdated contents of the cache can be cleared with:

>>> get_phone_number.cache_clear()

(Contributed by Raymond Hettinger and incorporating design ideas from Jim Baker, Miki Tebeka, and Nick Coghlan; see recipe 498245 [https://code.activestate.com/recipes/498245], recipe 577479 [https://code.activestate.com/recipes/577479], bpo-10586 [https://bugs.python.org/issue10586], and bpo-10593 [https://bugs.python.org/issue10593].)

The functools.wraps() decorator now adds a __wrapped__ attribute pointing to the original callable function. This allows wrapped functions to be introspected. It also copies __annotations__ if defined. And now it also gracefully skips over missing attributes such as __doc__ which might not be defined for the wrapped callable.

In the above example, the cache can be removed by recovering the original function:

>>> get_phone_number = get_phone_number.__wrapped__    # uncached function

(By Nick Coghlan and Terrence Cole; bpo-9567 [https://bugs.python.org/issue9567], bpo-3445 [https://bugs.python.org/issue3445], and bpo-8814 [https://bugs.python.org/issue8814].)

To help write classes with rich comparison methods, a new decorator functools.total_ordering() will use existing equality and inequality methods to fill in the remaining methods.

For example, supplying __eq__ and __lt__ will enable total_ordering() to fill-in __le__, __gt__ and __ge__:

@total_ordering
class Student:
    def __eq__(self, other):
        return ((self.lastname.lower(), self.firstname.lower()) ==
                (other.lastname.lower(), other.firstname.lower()))

    def __lt__(self, other):
        return ((self.lastname.lower(), self.firstname.lower()) <
                (other.lastname.lower(), other.firstname.lower()))

With the total_ordering decorator, the remaining comparison methods are filled in automatically.

(Contributed by Raymond Hettinger.)

To aid in porting programs from Python 2, the functools.cmp_to_key() function converts an old-style comparison function to modern key function:

>>> # locale-aware sort order
>>> sorted(iterable, key=cmp_to_key(locale.strcoll))

For sorting examples and a brief sorting tutorial, see the Sorting HowTo [https://wiki.python.org/moin/HowTo/Sorting/] tutorial.

(Contributed by Raymond Hettinger.)

itertools

The itertools module has a new accumulate() function modeled on APL’s scan operator and Numpy’s accumulate function:

>>> from itertools import accumulate
>>> list(accumulate([8, 2, 50]))
[8, 10, 60]

>>> prob_dist = [0.1, 0.4, 0.2, 0.3]
>>> list(accumulate(prob_dist))      # cumulative probability distribution
[0.1, 0.5, 0.7, 1.0]

For an example using accumulate(), see the examples for the random module.

(Contributed by Raymond Hettinger and incorporating design suggestions from Mark Dickinson.)

collections

The collections.Counter class now has two forms of in-place subtraction, the existing -= operator for saturating subtraction [https://en.wikipedia.org/wiki/Saturation_arithmetic] and the new subtract() method for regular subtraction. The former is suitable for multisets [https://en.wikipedia.org/wiki/Multiset] which only have positive counts, and the latter is more suitable for use cases that allow negative counts:

>>> from collections import Counter
>>> tally = Counter(dogs=5, cats=3)
>>> tally -= Counter(dogs=2, cats=8)    # saturating subtraction
>>> tally
Counter({'dogs': 3})

>>> tally = Counter(dogs=5, cats=3)
>>> tally.subtract(dogs=2, cats=8)      # regular subtraction
>>> tally
Counter({'dogs': 3, 'cats': -5})

(Contributed by Raymond Hettinger.)

The collections.OrderedDict class has a new method move_to_end() which takes an existing key and moves it to either the first or last position in the ordered sequence.

The default is to move an item to the last position. This is equivalent of renewing an entry with od[k] = od.pop(k).

A fast move-to-end operation is useful for resequencing entries. For example, an ordered dictionary can be used to track order of access by aging entries from the oldest to the most recently accessed.

>>> from collections import OrderedDict
>>> d = OrderedDict.fromkeys(['a', 'b', 'X', 'd', 'e'])
>>> list(d)
['a', 'b', 'X', 'd', 'e']
>>> d.move_to_end('X')
>>> list(d)
['a', 'b', 'd', 'e', 'X']

(Contributed by Raymond Hettinger.)

The collections.deque class grew two new methods count() and reverse() that make them more substitutable for list objects:

>>> from collections import deque
>>> d = deque('simsalabim')
>>> d.count('s')
2
>>> d.reverse()
>>> d
deque(['m', 'i', 'b', 'a', 'l', 'a', 's', 'm', 'i', 's'])

(Contributed by Raymond Hettinger.)

threading

The threading module has a new Barrier synchronization class for making multiple threads wait until all of them have reached a common barrier point. Barriers are useful for making sure that a task with multiple preconditions does not run until all of the predecessor tasks are complete.

Barriers can work with an arbitrary number of threads. This is a generalization of a Rendezvous [https://en.wikipedia.org/wiki/Synchronous_rendezvous] which is defined for only two threads.

Implemented as a two-phase cyclic barrier, Barrier objects are suitable for use in loops. The separate filling and draining phases assure that all threads get released (drained) before any one of them can loop back and re-enter the barrier. The barrier fully resets after each cycle.

Example of using barriers:

from threading import Barrier, Thread

def get_votes(site):
    ballots = conduct_election(site)
    all_polls_closed.wait()        # do not count until all polls are closed
    totals = summarize(ballots)
    publish(site, totals)

all_polls_closed = Barrier(len(sites))
for site in sites:
    Thread(target=get_votes, args=(site,)).start()

In this example, the barrier enforces a rule that votes cannot be counted at any polling site until all polls are closed. Notice how a solution with a barrier is similar to one with threading.Thread.join(), but the threads stay alive and continue to do work (summarizing ballots) after the barrier point is crossed.

If any of the predecessor tasks can hang or be delayed, a barrier can be created with an optional timeout parameter. Then if the timeout period elapses before all the predecessor tasks reach the barrier point, all waiting threads are released and a BrokenBarrierError exception is raised:

def get_votes(site):
    ballots = conduct_election(site)
    try:
        all_polls_closed.wait(timeout=midnight - time.now())
    except BrokenBarrierError:
        lockbox = seal_ballots(ballots)
        queue.put(lockbox)
    else:
        totals = summarize(ballots)
        publish(site, totals)

In this example, the barrier enforces a more robust rule. If some election sites do not finish before midnight, the barrier times-out and the ballots are sealed and deposited in a queue for later handling.

See Barrier Synchronization Patterns [https://parlab.eecs.berkeley.edu/wiki/_media/patterns/paraplop_g1_3.pdf] for more examples of how barriers can be used in parallel computing. Also, there is a simple but thorough explanation of barriers in The Little Book of Semaphores [http://greenteapress.com/semaphores/downey08semaphores.pdf], section 3.6.

(Contributed by Kristján Valur Jónsson with an API review by Jeffrey Yasskin in bpo-8777 [https://bugs.python.org/issue8777].)

datetime and time

The datetime module has a new type timezone that implements the tzinfo interface by returning a fixed UTC offset and timezone name. This makes it easier to create timezone-aware datetime objects:

>>> from datetime import datetime, timezone

>>> datetime.now(timezone.utc)
datetime.datetime(2010, 12, 8, 21, 4, 2, 923754, tzinfo=datetime.timezone.utc)

>>> datetime.strptime("01/01/2000 12:00 +0000", "%m/%d/%Y %H:%M %z")
datetime.datetime(2000, 1, 1, 12, 0, tzinfo=datetime.timezone.utc)

Also, timedelta objects can now be multiplied by float and divided by float and int objects. And timedelta objects can now divide one another.

The datetime.date.strftime() method is no longer restricted to years after 1900. The new supported year range is from 1000 to 9999 inclusive.

Whenever a two-digit year is used in a time tuple, the interpretation has been governed by time.accept2dyear. The default is True which means that for a two-digit year, the century is guessed according to the POSIX rules governing the %y strptime format.

Starting with Py3.2, use of the century guessing heuristic will emit a DeprecationWarning. Instead, it is recommended that time.accept2dyear be set to False so that large date ranges can be used without guesswork:

>>> import time, warnings
>>> warnings.resetwarnings()      # remove the default warning filters

>>> time.accept2dyear = True      # guess whether 11 means 11 or 2011
>>> time.asctime((11, 1, 1, 12, 34, 56, 4, 1, 0))
Warning (from warnings module):
  ...
DeprecationWarning: Century info guessed for a 2-digit year.
'Fri Jan  1 12:34:56 2011'

>>> time.accept2dyear = False     # use the full range of allowable dates
>>> time.asctime((11, 1, 1, 12, 34, 56, 4, 1, 0))
'Fri Jan  1 12:34:56 11'

Several functions now have significantly expanded date ranges. When time.accept2dyear is false, the time.asctime() function will accept any year that fits in a C int, while the time.mktime() and time.strftime() functions will accept the full range supported by the corresponding operating system functions.

(Contributed by Alexander Belopolsky and Victor Stinner in bpo-1289118 [https://bugs.python.org/issue1289118], bpo-5094 [https://bugs.python.org/issue5094], bpo-6641 [https://bugs.python.org/issue6641], bpo-2706 [https://bugs.python.org/issue2706], bpo-1777412 [https://bugs.python.org/issue1777412], bpo-8013 [https://bugs.python.org/issue8013], and bpo-10827 [https://bugs.python.org/issue10827].)

math

The math module has been updated with six new functions inspired by the C99 standard.

The isfinite() function provides a reliable and fast way to detect special values. It returns True for regular numbers and False for Nan or Infinity:

>>> from math import isfinite
>>> [isfinite(x) for x in (123, 4.56, float('Nan'), float('Inf'))]
[True, True, False, False]

The expm1() function computes e**x-1 for small values of x without incurring the loss of precision that usually accompanies the subtraction of nearly equal quantities:

>>> from math import expm1
>>> expm1(0.013671875)   # more accurate way to compute e**x-1 for a small x
0.013765762467652909

The erf() function computes a probability integral or Gaussian error function [https://en.wikipedia.org/wiki/Error_function]. The complementary error function, erfc(), is 1 - erf(x):

>>> from math import erf, erfc, sqrt
>>> erf(1.0/sqrt(2.0))   # portion of normal distribution within 1 standard deviation
0.682689492137086
>>> erfc(1.0/sqrt(2.0))  # portion of normal distribution outside 1 standard deviation
0.31731050786291404
>>> erf(1.0/sqrt(2.0)) + erfc(1.0/sqrt(2.0))
1.0

The gamma() function is a continuous extension of the factorial function. See https://en.wikipedia.org/wiki/Gamma_function for details. Because the function is related to factorials, it grows large even for small values of x, so there is also a lgamma() function for computing the natural logarithm of the gamma function:

>>> from math import gamma, lgamma
>>> gamma(7.0)           # six factorial
720.0
>>> lgamma(801.0)        # log(800 factorial)
4551.950730698041

(Contributed by Mark Dickinson.)

abc

The abc module now supports abstractclassmethod() and abstractstaticmethod().

These tools make it possible to define an abstract base class that requires a particular classmethod() or staticmethod() to be implemented:

class Temperature(metaclass=abc.ABCMeta):
    @abc.abstractclassmethod
    def from_fahrenheit(cls, t):
        ...
    @abc.abstractclassmethod
    def from_celsius(cls, t):
        ...

(Patch submitted by Daniel Urban; bpo-5867 [https://bugs.python.org/issue5867].)

io

The io.BytesIO has a new method, getbuffer(), which provides functionality similar to memoryview(). It creates an editable view of the data without making a copy. The buffer’s random access and support for slice notation are well-suited to in-place editing:

>>> REC_LEN, LOC_START, LOC_LEN = 34, 7, 11

>>> def change_location(buffer, record_number, location):
...     start = record_number * REC_LEN + LOC_START
...     buffer[start: start+LOC_LEN] = location

>>> import io

>>> byte_stream = io.BytesIO(
...     b'G3805  storeroom  Main chassis    '
...     b'X7899  shipping   Reserve cog     '
...     b'L6988  receiving  Primary sprocket'
... )
>>> buffer = byte_stream.getbuffer()
>>> change_location(buffer, 1, b'warehouse  ')
>>> change_location(buffer, 0, b'showroom   ')
>>> print(byte_stream.getvalue())
b'G3805  showroom   Main chassis    '
b'X7899  warehouse  Reserve cog     '
b'L6988  receiving  Primary sprocket'

(Contribution par Antoine Pitrou; bpo-5506 [https://bugs.python.org/issue5506].)

reprlib

When writing a __repr__() method for a custom container, it is easy to forget to handle the case where a member refers back to the container itself. Python’s builtin objects such as list and set handle self-reference by displaying « … » in the recursive part of the representation string.

To help write such __repr__() methods, the reprlib module has a new decorator, recursive_repr(), for detecting recursive calls to __repr__() and substituting a placeholder string instead:

>>> class MyList(list):
...     @recursive_repr()
...     def __repr__(self):
...         return '<' + '|'.join(map(repr, self)) + '>'
...
>>> m = MyList('abc')
>>> m.append(m)
>>> m.append('x')
>>> print(m)
<'a'|'b'|'c'|...|'x'>

(Contribution par Raymond Hettinger; bpo-9826 [https://bugs.python.org/issue9826] et issue:9840)

logging

In addition to dictionary-based configuration described above, the logging package has many other improvements.

The logging documentation has been augmented by a basic tutorial, an advanced tutorial, and a cookbook of logging recipes. These documents are the fastest way to learn about logging.

The logging.basicConfig() set-up function gained a style argument to support three different types of string formatting. It defaults to « % » for traditional %-formatting, can be set to « { » for the new str.format() style, or can be set to « $ » for the shell-style formatting provided by string.Template. The following three configurations are equivalent:

>>> from logging import basicConfig
>>> basicConfig(style='%', format="%(name)s -> %(levelname)s: %(message)s")
>>> basicConfig(style='{', format="{name} -> {levelname} {message}")
>>> basicConfig(style='$', format="$name -> $levelname: $message")

If no configuration is set-up before a logging event occurs, there is now a default configuration using a StreamHandler directed to sys.stderr for events of WARNING level or higher. Formerly, an event occurring before a configuration was set-up would either raise an exception or silently drop the event depending on the value of logging.raiseExceptions. The new default handler is stored in logging.lastResort.

The use of filters has been simplified. Instead of creating a Filter object, the predicate can be any Python callable that returns True or False.

There were a number of other improvements that add flexibility and simplify configuration. See the module documentation for a full listing of changes in Python 3.2.

csv

The csv module now supports a new dialect, unix_dialect, which applies quoting for all fields and a traditional Unix style with '\n' as the line terminator. The registered dialect name is unix.

The csv.DictWriter has a new method, writeheader() for writing-out an initial row to document the field names:

>>> import csv, sys
>>> w = csv.DictWriter(sys.stdout, ['name', 'dept'], dialect='unix')
>>> w.writeheader()
"name","dept"
>>> w.writerows([
...     {'name': 'tom', 'dept': 'accounting'},
...     {'name': 'susan', 'dept': 'Salesl'}])
"tom","accounting"
"susan","sales"

(New dialect suggested by Jay Talbot in bpo-5975 [https://bugs.python.org/issue5975], and the new method suggested by Ed Abraham in bpo-1537721 [https://bugs.python.org/issue1537721].)

contextlib

There is a new and slightly mind-blowing tool ContextDecorator that is helpful for creating a context manager that does double duty as a function decorator.

As a convenience, this new functionality is used by contextmanager() so that no extra effort is needed to support both roles.

The basic idea is that both context managers and function decorators can be used for pre-action and post-action wrappers. Context managers wrap a group of statements using a with statement, and function decorators wrap a group of statements enclosed in a function. So, occasionally there is a need to write a pre-action or post-action wrapper that can be used in either role.

For example, it is sometimes useful to wrap functions or groups of statements with a logger that can track the time of entry and time of exit. Rather than writing both a function decorator and a context manager for the task, the contextmanager() provides both capabilities in a single definition:

from contextlib import contextmanager
import logging

logging.basicConfig(level=logging.INFO)

@contextmanager
def track_entry_and_exit(name):
    logging.info('Entering: %s', name)
    yield
    logging.info('Exiting: %s', name)

Formerly, this would have only been usable as a context manager:

with track_entry_and_exit('widget loader'):
    print('Some time consuming activity goes here')
    load_widget()

Now, it can be used as a decorator as well:

@track_entry_and_exit('widget loader')
def activity():
    print('Some time consuming activity goes here')
    load_widget()

Trying to fulfill two roles at once places some limitations on the technique. Context managers normally have the flexibility to return an argument usable by a with statement, but there is no parallel for function decorators.

In the above example, there is not a clean way for the track_entry_and_exit context manager to return a logging instance for use in the body of enclosed statements.

(Contribution par Michael Foord; bpo-9110 [https://bugs.python.org/issue9110])

decimal and fractions

Mark Dickinson crafted an elegant and efficient scheme for assuring that different numeric datatypes will have the same hash value whenever their actual values are equal (bpo-8188 [https://bugs.python.org/issue8188]):

assert hash(Fraction(3, 2)) == hash(1.5) == \
       hash(Decimal("1.5")) == hash(complex(1.5, 0))

Some of the hashing details are exposed through a new attribute, sys.hash_info, which describes the bit width of the hash value, the prime modulus, the hash values for infinity and nan, and the multiplier used for the imaginary part of a number:

>>> sys.hash_info
sys.hash_info(width=64, modulus=2305843009213693951, inf=314159, nan=0, imag=1000003)

An early decision to limit the inter-operability of various numeric types has been relaxed. It is still unsupported (and ill-advised) to have implicit mixing in arithmetic expressions such as Decimal('1.1') + float('1.1') because the latter loses information in the process of constructing the binary float. However, since existing floating point value can be converted losslessly to either a decimal or rational representation, it makes sense to add them to the constructor and to support mixed-type comparisons.

The decimal.Decimal constructor now accepts float objects directly so there in no longer a need to use the from_float() method (bpo-8257 [https://bugs.python.org/issue8257]).

Mixed type comparisons are now fully supported so that Decimal objects can be directly compared with float and fractions.Fraction (bpo-2531 [https://bugs.python.org/issue2531] and bpo-8188 [https://bugs.python.org/issue8188]).

Similar changes were made to fractions.Fraction so that the from_float() and from_decimal() methods are no longer needed (bpo-8294 [https://bugs.python.org/issue8294]):

>>> from decimal import Decimal
>>> from fractions import Fraction
>>> Decimal(1.1)
Decimal('1.100000000000000088817841970012523233890533447265625')
>>> Fraction(1.1)
Fraction(2476979795053773, 2251799813685248)

Another useful change for the decimal module is that the Context.clamp attribute is now public. This is useful in creating contexts that correspond to the decimal interchange formats specified in IEEE 754 (see bpo-8540 [https://bugs.python.org/issue8540]).

(Contributed by Mark Dickinson and Raymond Hettinger.)

ftp

The ftplib.FTP class now supports the context management protocol to unconditionally consume socket.error exceptions and to close the FTP connection when done:

>>> from ftplib import FTP
>>> with FTP("ftp1.at.proftpd.org") as ftp:
        ftp.login()
        ftp.dir()

'230 Anonymous login ok, restrictions apply.'
dr-xr-xr-x   9 ftp      ftp           154 May  6 10:43 .
dr-xr-xr-x   9 ftp      ftp           154 May  6 10:43 ..
dr-xr-xr-x   5 ftp      ftp          4096 May  6 10:43 CentOS
dr-xr-xr-x   3 ftp      ftp            18 Jul 10  2008 Fedora

Other file-like objects such as mmap.mmap and fileinput.input() also grew auto-closing context managers:

with fileinput.input(files=('log1.txt', 'log2.txt')) as f:
    for line in f:
        process(line)

(Contributed by Tarek Ziadé and Giampaolo Rodolà in bpo-4972 [https://bugs.python.org/issue4972], and by Georg Brandl in bpo-8046 [https://bugs.python.org/issue8046] and bpo-1286 [https://bugs.python.org/issue1286].)

The FTP_TLS class now accepts a context parameter, which is a ssl.SSLContext object allowing bundling SSL configuration options, certificates and private keys into a single (potentially long-lived) structure.

(Contribution par Giampaolo Rodolà; bpo-8806 [https://bugs.python.org/issue8806])

popen

The os.popen() and subprocess.Popen() functions now support with statements for auto-closing of the file descriptors.

(Contribution par Antoine Pitrou et Brian Curtin; bpo-7461 [https://bugs.python.org/issue7461] et bpo-10554 [https://bugs.python.org/issue10554])

select

The select module now exposes a new, constant attribute, PIPE_BUF, which gives the minimum number of bytes which are guaranteed not to block when select.select() says a pipe is ready for writing.

>>> import select
>>> select.PIPE_BUF
512

(Available on Unix systems. Patch by Sébastien Sablé in bpo-9862 [https://bugs.python.org/issue9862])

gzip and zipfile

gzip.GzipFile now implements the io.BufferedIOBase abstract base class (except for truncate()). It also has a peek() method and supports unseekable as well as zero-padded file objects.

The gzip module also gains the compress() and decompress() functions for easier in-memory compression and decompression. Keep in mind that text needs to be encoded as bytes before compressing and decompressing:

>>> import gzip
>>> s = 'Three shall be the number thou shalt count, '
>>> s += 'and the number of the counting shall be three'
>>> b = s.encode()                        # convert to utf-8
>>> len(b)
89
>>> c = gzip.compress(b)
>>> len(c)
77
>>> gzip.decompress(c).decode()[:42]      # decompress and convert to text
'Three shall be the number thou shalt count'

(Contributed by Anand B. Pillai in bpo-3488 [https://bugs.python.org/issue3488]; and by Antoine Pitrou, Nir Aides and Brian Curtin in bpo-9962 [https://bugs.python.org/issue9962], bpo-1675951 [https://bugs.python.org/issue1675951], bpo-7471 [https://bugs.python.org/issue7471] and bpo-2846 [https://bugs.python.org/issue2846].)

Also, the zipfile.ZipExtFile class was reworked internally to represent files stored inside an archive. The new implementation is significantly faster and can be wrapped in an io.BufferedReader object for more speedups. It also solves an issue where interleaved calls to read and readline gave the wrong results.

(Patch submitted by Nir Aides in bpo-7610 [https://bugs.python.org/issue7610].)

tarfile

The TarFile class can now be used as a context manager. In addition, its add() method has a new option, filter, that controls which files are added to the archive and allows the file metadata to be edited.

The new filter option replaces the older, less flexible exclude parameter which is now deprecated. If specified, the optional filter parameter needs to be a keyword argument. The user-supplied filter function accepts a TarInfo object and returns an updated TarInfo object, or if it wants the file to be excluded, the function can return None:

>>> import tarfile, glob

>>> def myfilter(tarinfo):
...     if tarinfo.isfile():             # only save real files
...         tarinfo.uname = 'monty'      # redact the user name
...         return tarinfo

>>> with tarfile.open(name='myarchive.tar.gz', mode='w:gz') as tf:
...     for filename in glob.glob('*.txt'):
...         tf.add(filename, filter=myfilter)
...     tf.list()
-rw-r--r-- monty/501        902 2011-01-26 17:59:11 annotations.txt
-rw-r--r-- monty/501        123 2011-01-26 17:59:11 general_questions.txt
-rw-r--r-- monty/501       3514 2011-01-26 17:59:11 prion.txt
-rw-r--r-- monty/501        124 2011-01-26 17:59:11 py_todo.txt
-rw-r--r-- monty/501       1399 2011-01-26 17:59:11 semaphore_notes.txt

(Proposed by Tarek Ziadé and implemented by Lars Gustäbel in bpo-6856 [https://bugs.python.org/issue6856].)

hashlib

The hashlib module has two new constant attributes listing the hashing algorithms guaranteed to be present in all implementations and those available on the current implementation:

>>> import hashlib

>>> hashlib.algorithms_guaranteed
{'sha1', 'sha224', 'sha384', 'sha256', 'sha512', 'md5'}

>>> hashlib.algorithms_available
{'md2', 'SHA256', 'SHA512', 'dsaWithSHA', 'mdc2', 'SHA224', 'MD4', 'sha256',
'sha512', 'ripemd160', 'SHA1', 'MDC2', 'SHA', 'SHA384', 'MD2',
'ecdsa-with-SHA1','md4', 'md5', 'sha1', 'DSA-SHA', 'sha224',
'dsaEncryption', 'DSA', 'RIPEMD160', 'sha', 'MD5', 'sha384'}

(Suggested by Carl Chenet in bpo-7418 [https://bugs.python.org/issue7418].)

ast

The ast module has a wonderful a general-purpose tool for safely evaluating expression strings using the Python literal syntax. The ast.literal_eval() function serves as a secure alternative to the builtin eval() function which is easily abused. Python 3.2 adds bytes and set literals to the list of supported types: strings, bytes, numbers, tuples, lists, dicts, sets, booleans, and None.

>>> from ast import literal_eval

>>> request = "{'req': 3, 'func': 'pow', 'args': (2, 0.5)}"
>>> literal_eval(request)
{'args': (2, 0.5), 'req': 3, 'func': 'pow'}

>>> request = "os.system('do something harmful')"
>>> literal_eval(request)
Traceback (most recent call last):
  ...
ValueError: malformed node or string: <_ast.Call object at 0x101739a10>

(Implemented by Benjamin Peterson and Georg Brandl.)

os

Different operating systems use various encodings for filenames and environment variables. The os module provides two new functions, fsencode() and fsdecode(), for encoding and decoding filenames:

>>> import os
>>> filename = 'Sehenswürdigkeiten'
>>> os.fsencode(filename)
b'Sehensw\xc3\xbcrdigkeiten'

Some operating systems allow direct access to encoded bytes in the environment. If so, the os.supports_bytes_environ constant will be true.

For direct access to encoded environment variables (if available), use the new os.getenvb() function or use os.environb which is a bytes version of os.environ.

(Contribution par Victor Stinner)

shutil

The shutil.copytree() function has two new options:

ignore_dangling_symlinks: when symlinks=False so that the function copies a file pointed to by a symlink, not the symlink itself. This option will silence the error raised if the file doesn’t exist.

copy_function: is a callable that will be used to copy files. shutil.copy2() is used by default.

(Contributed by Tarek Ziadé.)

In addition, the shutil module now supports archiving operations for zipfiles, uncompressed tarfiles, gzipped tarfiles, and bzipped tarfiles. And there are functions for registering additional archiving file formats (such as xz compressed tarfiles or custom formats).

The principal functions are make_archive() and unpack_archive(). By default, both operate on the current directory (which can be set by os.chdir()) and on any sub-directories. The archive filename needs to be specified with a full pathname. The archiving step is non-destructive (the original files are left unchanged).

>>> import shutil, pprint

>>> os.chdir('mydata')  # change to the source directory
>>> f = shutil.make_archive('/var/backup/mydata',
...                         'zip')      # archive the current directory
>>> f                                   # show the name of archive
'/var/backup/mydata.zip'
>>> os.chdir('tmp')                     # change to an unpacking
>>> shutil.unpack_archive('/var/backup/mydata.zip')  # recover the data

>>> pprint.pprint(shutil.get_archive_formats())  # display known formats
[('bztar', "bzip2'ed tar-file"),
 ('gztar', "gzip'ed tar-file"),
 ('tar', 'uncompressed tar file'),
 ('zip', 'ZIP file')]

>>> shutil.register_archive_format(     # register a new archive format
...     name='xz',
...     function=xz.compress,           # callable archiving function
...     extra_args=[('level', 8)],      # arguments to the function
...     description='xz compression'
... )

(Contributed by Tarek Ziadé.)

sqlite3

The sqlite3 module was updated to pysqlite version 2.6.0. It has two new capabilities.

The sqlite3.Connection.in_transit attribute is true if there is an active transaction for uncommitted changes.

The sqlite3.Connection.enable_load_extension() and sqlite3.Connection.load_extension() methods allows you to load SQLite extensions from « .so » files. One well-known extension is the fulltext-search extension distributed with SQLite.

(Contributed by R. David Murray and Shashwat Anand; bpo-8845 [https://bugs.python.org/issue8845].)

html

A new html module was introduced with only a single function, escape(), which is used for escaping reserved characters from HTML markup:

>>> import html
>>> html.escape('x > 2 && x < 7')
'x &gt; 2 &amp;&amp; x &lt; 7'

socket

The socket module has two new improvements.

Socket objects now have a detach() method which puts the socket into closed state without actually closing the underlying file descriptor. The latter can then be reused for other purposes. (Added by Antoine Pitrou; bpo-8524 [https://bugs.python.org/issue8524].)

socket.create_connection() now supports the context management protocol to unconditionally consume socket.error exceptions and to close the socket when done. (Contributed by Giampaolo Rodolà; bpo-9794 [https://bugs.python.org/issue9794].)

ssl

The ssl module added a number of features to satisfy common requirements for secure (encrypted, authenticated) internet connections:

A new class, SSLContext, serves as a container for persistent SSL data, such as protocol settings, certificates, private keys, and various other options. It includes a wrap_socket() for creating an SSL socket from an SSL context.

A new function, ssl.match_hostname(), supports server identity verification for higher-level protocols by implementing the rules of HTTPS (from RFC 2818 [https://tools.ietf.org/html/rfc2818.html]) which are also suitable for other protocols.

The ssl.wrap_socket() constructor function now takes a ciphers argument. The ciphers string lists the allowed encryption algorithms using the format described in the OpenSSL documentation [https://www.openssl.org/docs/apps/ciphers.html#CIPHER-LIST-FORMAT].

When linked against recent versions of OpenSSL, the ssl module now supports the Server Name Indication extension to the TLS protocol, allowing multiple « virtual hosts » using different certificates on a single IP port. This extension is only supported in client mode, and is activated by passing the server_hostname argument to ssl.SSLContext.wrap_socket().

Various options have been added to the ssl module, such as OP_NO_SSLv2 which disables the insecure and obsolete SSLv2 protocol.

The extension now loads all the OpenSSL ciphers and digest algorithms. If some SSL certificates cannot be verified, they are reported as an « unknown algorithm » error.

The version of OpenSSL being used is now accessible using the module attributes ssl.OPENSSL_VERSION (a string), ssl.OPENSSL_VERSION_INFO (a 5-tuple), and ssl.OPENSSL_VERSION_NUMBER (an integer).

(Contributed by Antoine Pitrou in bpo-8850 [https://bugs.python.org/issue8850], bpo-1589 [https://bugs.python.org/issue1589], bpo-8322 [https://bugs.python.org/issue8322], bpo-5639 [https://bugs.python.org/issue5639], bpo-4870 [https://bugs.python.org/issue4870], bpo-8484 [https://bugs.python.org/issue8484], and bpo-8321 [https://bugs.python.org/issue8321].)

nntp

The nntplib module has a revamped implementation with better bytes and text semantics as well as more practical APIs. These improvements break compatibility with the nntplib version in Python 3.1, which was partly dysfunctional in itself.

Support for secure connections through both implicit (using nntplib.NNTP_SSL) and explicit (using nntplib.NNTP.starttls()) TLS has also been added.

(Contribution par Antoine Pitrou, bpo-9360 [https://bugs.python.org/issue9360], et Andrew Vant, bpo-1926 [https://bugs.python.org/issue1926])

certificates

http.client.HTTPSConnection, urllib.request.HTTPSHandler and urllib.request.urlopen() now take optional arguments to allow for server certificate checking against a set of Certificate Authorities, as recommended in public uses of HTTPS.

(Ajouté par Antoine Pitrou; bpo-9003 [https://bugs.python.org/issue9003].)

imaplib

Support for explicit TLS on standard IMAP4 connections has been added through the new imaplib.IMAP4.starttls method.

(Contribution par Lorenzo M. Catucci et Antoine Pitrou; bpo-4471 [https://bugs.python.org/issue4471].)

http.client

There were a number of small API improvements in the http.client module. The old-style HTTP 0.9 simple responses are no longer supported and the strict parameter is deprecated in all classes.

The HTTPConnection and HTTPSConnection classes now have a source_address parameter for a (host, port) tuple indicating where the HTTP connection is made from.

Support for certificate checking and HTTPS virtual hosts were added to HTTPSConnection.

The request() method on connection objects allowed an optional body argument so that a file object could be used to supply the content of the request. Conveniently, the body argument now also accepts an iterable object so long as it includes an explicit Content-Length header. This extended interface is much more flexible than before.

To establish an HTTPS connection through a proxy server, there is a new set_tunnel() method that sets the host and port for HTTP Connect tunneling.

To match the behavior of http.server, the HTTP client library now also encodes headers with ISO-8859-1 (Latin-1) encoding. It was already doing that for incoming headers, so now the behavior is consistent for both incoming and outgoing traffic. (See work by Armin Ronacher in bpo-10980 [https://bugs.python.org/issue10980].)

unittest

The unittest module has a number of improvements supporting test discovery for packages, easier experimentation at the interactive prompt, new testcase methods, improved diagnostic messages for test failures, and better method names.

The command-line call python -m unittest can now accept file paths instead of module names for running specific tests (bpo-10620 [https://bugs.python.org/issue10620]). The new test discovery can find tests within packages, locating any test importable from the top-level directory. The top-level directory can be specified with the -t option, a pattern for matching files with -p, and a directory to start discovery with -s:

$ python -m unittest discover -s my_proj_dir -p _test.py

(Contributed by Michael Foord.)

Experimentation at the interactive prompt is now easier because the unittest.case.TestCase class can now be instantiated without arguments:

>>> from unittest import TestCase
>>> TestCase().assertEqual(pow(2, 3), 8)

(Contributed by Michael Foord.)

The unittest module has two new methods, assertWarns() and assertWarnsRegex() to verify that a given warning type is triggered by the code under test:

with self.assertWarns(DeprecationWarning):
    legacy_function('XYZ')

(Contribution par Antoine Pitrou; bpo-9754 [https://bugs.python.org/issue9754].)

Another new method, assertCountEqual() is used to compare two iterables to determine if their element counts are equal (whether the same elements are present with the same number of occurrences regardless of order):

def test_anagram(self):
    self.assertCountEqual('algorithm', 'logarithm')

(Contributed by Raymond Hettinger.)

A principal feature of the unittest module is an effort to produce meaningful diagnostics when a test fails. When possible, the failure is recorded along with a diff of the output. This is especially helpful for analyzing log files of failed test runs. However, since diffs can sometime be voluminous, there is a new maxDiff attribute that sets maximum length of diffs displayed.

In addition, the method names in the module have undergone a number of clean-ups.

For example, assertRegex() is the new name for assertRegexpMatches() which was misnamed because the test uses re.search(), not re.match(). Other methods using regular expressions are now named using short form « Regex » in preference to « Regexp » – this matches the names used in other unittest implementations, matches Python’s old name for the re module, and it has unambiguous camel-casing.

(Contributed by Raymond Hettinger and implemented by Ezio Melotti.)

To improve consistency, some long-standing method aliases are being deprecated in favor of the preferred names:

Old Name

Preferred Name

assert_()

assertTrue()

assertEquals()

assertEqual()

assertNotEquals()

assertNotEqual()

assertAlmostEquals()

assertAlmostEqual()

assertNotAlmostEquals()

assertNotAlmostEqual()

Likewise, the TestCase.fail* methods deprecated in Python 3.1 are expected to be removed in Python 3.3. Also see the Alias obsolètes section in the unittest documentation.

(Contribution par Ezio Melotti; bpo-9424 [https://bugs.python.org/issue9424])

The assertDictContainsSubset() method was deprecated because it was misimplemented with the arguments in the wrong order. This created hard-to-debug optical illusions where tests like TestCase().assertDictContainsSubset({'a':1, 'b':2}, {'a':1}) would fail.

(Contributed by Raymond Hettinger.)

random

The integer methods in the random module now do a better job of producing uniform distributions. Previously, they computed selections with int(n*random()) which had a slight bias whenever n was not a power of two. Now, multiple selections are made from a range up to the next power of two and a selection is kept only when it falls within the range 0 <= x < n. The functions and methods affected are randrange(), randint(), choice(), shuffle() and sample().

(Contribution par Raymond Hettinger; bpo-9025 [https://bugs.python.org/issue9025])

poplib

POP3_SSL class now accepts a context parameter, which is a ssl.SSLContext object allowing bundling SSL configuration options, certificates and private keys into a single (potentially long-lived) structure.

(Contribution par Giampaolo Rodolà; bpo-8807 [https://bugs.python.org/issue8807])

asyncore

asyncore.dispatcher now provides a handle_accepted() method returning a (sock, addr) pair which is called when a connection has actually been established with a new remote endpoint. This is supposed to be used as a replacement for old handle_accept() and avoids the user to call accept() directly.

(Contribution par Giampaolo Rodolà; bpo-6706 [https://bugs.python.org/issue6706])

tempfile

The tempfile module has a new context manager, TemporaryDirectory which provides easy deterministic cleanup of temporary directories:

with tempfile.TemporaryDirectory() as tmpdirname:
    print('created temporary dir:', tmpdirname)

(Contribution par Neil Schemenauer et Nick Coghlan; bpo-5178 [https://bugs.python.org/issue5178].)

inspect

The inspect module has a new function getgeneratorstate() to easily identify the current state of a generator-iterator:

>>> from inspect import getgeneratorstate
>>> def gen():
...     yield 'demo'
>>> g = gen()
>>> getgeneratorstate(g)
'GEN_CREATED'
>>> next(g)
'demo'
>>> getgeneratorstate(g)
'GEN_SUSPENDED'
>>> next(g, None)
>>> getgeneratorstate(g)
'GEN_CLOSED'

(Contribution par Rodolpho Eckhardt et Nick Coghlan; bpo-10220 [https://bugs.python.org/issue10220].)

To support lookups without the possibility of activating a dynamic attribute, the inspect module has a new function, getattr_static(). Unlike hasattr(), this is a true read-only search, guaranteed not to change state while it is searching:

>>> class A:
...     @property
...     def f(self):
...         print('Running')
...         return 10
...
>>> a = A()
>>> getattr(a, 'f')
Running
10
>>> inspect.getattr_static(a, 'f')
<property object at 0x1022bd788>

(Contributed by Michael Foord.)

pydoc

The pydoc module now provides a much-improved Web server interface, as well as a new command-line option -b to automatically open a browser window to display that server:

$ pydoc3.2 -b

(Contribution par Ron Adam; bpo-2001 [https://bugs.python.org/issue2001].)

dis

The dis module gained two new functions for inspecting code, code_info() and show_code(). Both provide detailed code object information for the supplied function, method, source code string or code object. The former returns a string and the latter prints it:

>>> import dis, random
>>> dis.show_code(random.choice)
Name:              choice
Filename:          /Library/Frameworks/Python.framework/Versions/3.2/lib/python3.2/random.py
Argument count:    2
Kw-only arguments: 0
Number of locals:  3
Stack size:        11
Flags:             OPTIMIZED, NEWLOCALS, NOFREE
Constants:
   0: 'Choose a random element from a non-empty sequence.'
   1: 'Cannot choose from an empty sequence'
Names:
   0: _randbelow
   1: len
   2: ValueError
   3: IndexError
Variable names:
   0: self
   1: seq
   2: i

In addition, the dis() function now accepts string arguments so that the common idiom dis(compile(s, '', 'eval')) can be shortened to dis(s):

>>> dis('3*x+1 if x%2==1 else x//2')
  1           0 LOAD_NAME                0 (x)
              3 LOAD_CONST               0 (2)
              6 BINARY_MODULO
              7 LOAD_CONST               1 (1)
             10 COMPARE_OP               2 (==)
             13 POP_JUMP_IF_FALSE       28
             16 LOAD_CONST               2 (3)
             19 LOAD_NAME                0 (x)
             22 BINARY_MULTIPLY
             23 LOAD_CONST               1 (1)
             26 BINARY_ADD
             27 RETURN_VALUE
        >>   28 LOAD_NAME                0 (x)
             31 LOAD_CONST               0 (2)
             34 BINARY_FLOOR_DIVIDE
             35 RETURN_VALUE

Taken together, these improvements make it easier to explore how CPython is implemented and to see for yourself what the language syntax does under-the-hood.

(Contribution par Nick Coghlan; bpo-9147 [https://bugs.python.org/issue9147].)

dbm

All database modules now support the get() and setdefault() methods.

(Suggested by Ray Allen in bpo-9523 [https://bugs.python.org/issue9523].)

ctypes

A new type, ctypes.c_ssize_t represents the C ssize_t datatype.

site

The site module has three new functions useful for reporting on the details of a given Python installation.

getsitepackages() lists all global site-packages directories.

getuserbase() reports on the user’s base directory where data can be stored.

getusersitepackages() reveals the user-specific site-packages directory path.

>>> import site
>>> site.getsitepackages()
['/Library/Frameworks/Python.framework/Versions/3.2/lib/python3.2/site-packages',
 '/Library/Frameworks/Python.framework/Versions/3.2/lib/site-python',
 '/Library/Python/3.2/site-packages']
>>> site.getuserbase()
'/Users/raymondhettinger/Library/Python/3.2'
>>> site.getusersitepackages()
'/Users/raymondhettinger/Library/Python/3.2/lib/python/site-packages'

Conveniently, some of site’s functionality is accessible directly from the command-line:

$ python -m site --user-base
/Users/raymondhettinger/.local
$ python -m site --user-site
/Users/raymondhettinger/.local/lib/python3.2/site-packages

(Contribution par Tarek Ziadé; bpo-6693 [https://bugs.python.org/issue6693].)

sysconfig

The new sysconfig module makes it straightforward to discover installation paths and configuration variables that vary across platforms and installations.

The module offers access simple access functions for platform and version information:

get_platform() returning values like linux-i586 or macosx-10.6-ppc.

get_python_version() returns a Python version string such as « 3.2 ».

It also provides access to the paths and variables corresponding to one of seven named schemes used by distutils. Those include posix_prefix, posix_home, posix_user, nt, nt_user, os2, os2_home:

get_paths() makes a dictionary containing installation paths for the current installation scheme.

get_config_vars() returns a dictionary of platform specific variables.

There is also a convenient command-line interface:

C:\Python32>python -m sysconfig
Platform: "win32"
Python version: "3.2"
Current installation scheme: "nt"

Paths:
        data = "C:\Python32"
        include = "C:\Python32\Include"
        platinclude = "C:\Python32\Include"
        platlib = "C:\Python32\Lib\site-packages"
        platstdlib = "C:\Python32\Lib"
        purelib = "C:\Python32\Lib\site-packages"
        scripts = "C:\Python32\Scripts"
        stdlib = "C:\Python32\Lib"

Variables:
        BINDIR = "C:\Python32"
        BINLIBDEST = "C:\Python32\Lib"
        EXE = ".exe"
        INCLUDEPY = "C:\Python32\Include"
        LIBDEST = "C:\Python32\Lib"
        SO = ".pyd"
        VERSION = "32"
        abiflags = ""
        base = "C:\Python32"
        exec_prefix = "C:\Python32"
        platbase = "C:\Python32"
        prefix = "C:\Python32"
        projectbase = "C:\Python32"
        py_version = "3.2"
        py_version_nodot = "32"
        py_version_short = "3.2"
        srcdir = "C:\Python32"
        userbase = "C:\Documents and Settings\Raymond\Application Data\Python"

(Moved out of Distutils by Tarek Ziadé.)

pdb

The pdb debugger module gained a number of usability improvements:

pdb.py now has a -c option that executes commands as given in a .pdbrc script file.

A .pdbrc script file can contain continue and next commands that continue debugging.

The Pdb class constructor now accepts a nosigint argument.

New commands: l(list), ll(long list) and source for listing source code.

New commands: display and undisplay for showing or hiding the value of an expression if it has changed.

New command: interact for starting an interactive interpreter containing the global and local names found in the current scope.

Breakpoints can be cleared by breakpoint number.

(Contributed by Georg Brandl, Antonio Cuni and Ilya Sandler.)

configparser

The configparser module was modified to improve usability and predictability of the default parser and its supported INI syntax. The old ConfigParser class was removed in favor of SafeConfigParser which has in turn been renamed to ConfigParser. Support for inline comments is now turned off by default and section or option duplicates are not allowed in a single configuration source.

Config parsers gained a new API based on the mapping protocol:

>>> parser = ConfigParser()
>>> parser.read_string("""
... [DEFAULT]
... location = upper left
... visible = yes
... editable = no
... color = blue
...
... [main]
... title = Main Menu
... color = green
...
... [options]
... title = Options
... """)
>>> parser['main']['color']
'green'
>>> parser['main']['editable']
'no'
>>> section = parser['options']
>>> section['title']
'Options'
>>> section['title'] = 'Options (editable: %(editable)s)'
>>> section['title']
'Options (editable: no)'

The new API is implemented on top of the classical API, so custom parser subclasses should be able to use it without modifications.

The INI file structure accepted by config parsers can now be customized. Users can specify alternative option/value delimiters and comment prefixes, change the name of the DEFAULT section or switch the interpolation syntax.

There is support for pluggable interpolation including an additional interpolation handler ExtendedInterpolation:

>>> parser = ConfigParser(interpolation=ExtendedInterpolation())
>>> parser.read_dict({'buildout': {'directory': '/home/ambv/zope9'},
...                   'custom': {'prefix': '/usr/local'}})
>>> parser.read_string("""
... [buildout]
... parts =
...   zope9
...   instance
... find-links =
...   ${buildout:directory}/downloads/dist
...
... [zope9]
... recipe = plone.recipe.zope9install
... location = /opt/zope
...
... [instance]
... recipe = plone.recipe.zope9instance
... zope9-location = ${zope9:location}
... zope-conf = ${custom:prefix}/etc/zope.conf
... """)
>>> parser['buildout']['find-links']
'\n/home/ambv/zope9/downloads/dist'
>>> parser['instance']['zope-conf']
'/usr/local/etc/zope.conf'
>>> instance = parser['instance']
>>> instance['zope-conf']
'/usr/local/etc/zope.conf'
>>> instance['zope9-location']
'/opt/zope'

A number of smaller features were also introduced, like support for specifying encoding in read operations, specifying fallback values for get-functions, or reading directly from dictionaries and strings.

(All changes contributed by Łukasz Langa.)

urllib.parse

A number of usability improvements were made for the urllib.parse module.

The urlparse() function now supports IPv6 [https://en.wikipedia.org/wiki/IPv6] addresses as described in RFC 2732 [https://tools.ietf.org/html/rfc2732.html]:

>>> import urllib.parse
>>> urllib.parse.urlparse('http://[dead:beef:cafe:5417:affe:8FA3:deaf:feed]/foo/')
ParseResult(scheme='http',
            netloc='[dead:beef:cafe:5417:affe:8FA3:deaf:feed]',
            path='/foo/',
            params='',
            query='',
            fragment='')

The urldefrag() function now returns a named tuple:

>>> r = urllib.parse.urldefrag('http://python.org/about/#target')
>>> r
DefragResult(url='http://python.org/about/', fragment='target')
>>> r[0]
'http://python.org/about/'
>>> r.fragment
'target'

And, the urlencode() function is now much more flexible, accepting either a string or bytes type for the query argument. If it is a string, then the safe, encoding, and error parameters are sent to quote_plus() for encoding:

>>> urllib.parse.urlencode([
...      ('type', 'telenovela'),
...      ('name', '¿Dónde Está Elisa?')],
...      encoding='latin-1')
'type=telenovela&name=%BFD%F3nde+Est%E1+Elisa%3F'

As detailed in Parsing ASCII Encoded Bytes, all the urllib.parse functions now accept ASCII-encoded byte strings as input, so long as they are not mixed with regular strings. If ASCII-encoded byte strings are given as parameters, the return types will also be an ASCII-encoded byte strings:

>>> urllib.parse.urlparse(b'http://www.python.org:80/about/')
ParseResultBytes(scheme=b'http', netloc=b'www.python.org:80',
                 path=b'/about/', params=b'', query=b'', fragment=b'')

(Work by Nick Coghlan, Dan Mahn, and Senthil Kumaran in bpo-2987 [https://bugs.python.org/issue2987], bpo-5468 [https://bugs.python.org/issue5468], and bpo-9873 [https://bugs.python.org/issue9873].)

mailbox

Thanks to a concerted effort by R. David Murray, the mailbox module has been fixed for Python 3.2. The challenge was that mailbox had been originally designed with a text interface, but email messages are best represented with bytes because various parts of a message may have different encodings.

The solution harnessed the email package’s binary support for parsing arbitrary email messages. In addition, the solution required a number of API changes.

As expected, the add() method for mailbox.Mailbox objects now accepts binary input.

StringIO and text file input are deprecated. Also, string input will fail early if non-ASCII characters are used. Previously it would fail when the email was processed in a later step.

There is also support for binary output. The get_file() method now returns a file in the binary mode (where it used to incorrectly set the file to text-mode). There is also a new get_bytes() method that returns a bytes representation of a message corresponding to a given key.

It is still possible to get non-binary output using the old API’s get_string() method, but that approach is not very useful. Instead, it is best to extract messages from a Message object or to load them from binary input.

(Contributed by R. David Murray, with efforts from Steffen Daode Nurpmeso and an initial patch by Victor Stinner in bpo-9124 [https://bugs.python.org/issue9124].)

turtledemo

The demonstration code for the turtle module was moved from the Demo directory to main library. It includes over a dozen sample scripts with lively displays. Being on sys.path, it can now be run directly from the command-line:

$ python -m turtledemo

(Moved from the Demo directory by Alexander Belopolsky in bpo-10199 [https://bugs.python.org/issue10199].)

Fils d’exécution

The mechanism for serializing execution of concurrently running Python threads (generally known as the GIL or Global Interpreter Lock) has been rewritten. Among the objectives were more predictable switching intervals and reduced overhead due to lock contention and the number of ensuing system calls. The notion of a « check interval » to allow thread switches has been abandoned and replaced by an absolute duration expressed in seconds. This parameter is tunable through sys.setswitchinterval(). It currently defaults to 5 milliseconds.

Additional details about the implementation can be read from a python-dev mailing-list message [https://mail.python.org/pipermail/python-dev/2009-October/093321.html] (however, « priority requests » as exposed in this message have not been kept for inclusion).

(Contribution par Antoine Pitrou)

Les verrous standards et récursifs acceptent désormais un argument optionnel timeout à leur méthode acquire(). (Contribution par Antoine Pitrou; bpo-7316 [https://bugs.python.org/issue7316]).

Pareillement, threading.Semaphore.acquire() acquière un argument timeout (Contribution par Torsten Landschoff; bpo-850728 [https://bugs.python.org/issue850728]).

Regular and recursive lock acquisitions can now be interrupted by signals on platforms using Pthreads. This means that Python programs that deadlock while acquiring locks can be successfully killed by repeatedly sending SIGINT to the process (by pressing Ctrl+C in most shells). (Contributed by Reid Kleckner; bpo-8844 [https://bugs.python.org/issue8844].)

Optimizations

A number of small performance enhancements have been added:

Python’s peephole optimizer now recognizes patterns such x in {1, 2, 3} as being a test for membership in a set of constants. The optimizer recasts the set as a frozenset and stores the pre-built constant.

Now that the speed penalty is gone, it is practical to start writing membership tests using set-notation. This style is both semantically clear and operationally fast:

extension = name.rpartition('.')[2]
if extension in {'xml', 'html', 'xhtml', 'css'}:
    handle(name)

(Patch and additional tests contributed by Dave Malcolm; bpo-6690 [https://bugs.python.org/issue6690]).

Serializing and unserializing data using the pickle module is now several times faster.

(Contributed by Alexandre Vassalotti, Antoine Pitrou and the Unladen Swallow team in bpo-9410 [https://bugs.python.org/issue9410] and bpo-3873 [https://bugs.python.org/issue3873].)

The Timsort algorithm [https://en.wikipedia.org/wiki/Timsort] used in list.sort() and sorted() now runs faster and uses less memory when called with a key function. Previously, every element of a list was wrapped with a temporary object that remembered the key value associated with each element. Now, two arrays of keys and values are sorted in parallel. This saves the memory consumed by the sort wrappers, and it saves time lost to delegating comparisons.

(Patch by Daniel Stutzbach in bpo-9915 [https://bugs.python.org/issue9915].)

JSON decoding performance is improved and memory consumption is reduced whenever the same string is repeated for multiple keys. Also, JSON encoding now uses the C speedups when the sort_keys argument is true.

(Contributed by Antoine Pitrou in bpo-7451 [https://bugs.python.org/issue7451] and by Raymond Hettinger and Antoine Pitrou in bpo-10314 [https://bugs.python.org/issue10314].)

Recursive locks (created with the threading.RLock() API) now benefit from a C implementation which makes them as fast as regular locks, and between 10x and 15x faster than their previous pure Python implementation.

(Contribution par Antoine Pitrou; bpo-3001 [https://bugs.python.org/issue3001].)

The fast-search algorithm in stringlib is now used by the split(), rsplit(), splitlines() and replace() methods on bytes, bytearray and str objects. Likewise, the algorithm is also used by rfind(), rindex(), rsplit() and rpartition().

(Patch by Florent Xicluna in bpo-7622 [https://bugs.python.org/issue7622] and bpo-7462 [https://bugs.python.org/issue7462].)

Integer to string conversions now work two « digits » at a time, reducing the number of division and modulo operations.

(bpo-6713 [https://bugs.python.org/issue6713] by Gawain Bolton, Mark Dickinson, and Victor Stinner.)

There were several other minor optimizations. Set differencing now runs faster when one operand is much larger than the other (patch by Andress Bennetts in bpo-8685 [https://bugs.python.org/issue8685]). The array.repeat() method has a faster implementation (bpo-1569291 [https://bugs.python.org/issue1569291] by Alexander Belopolsky). The BaseHTTPRequestHandler has more efficient buffering (bpo-3709 [https://bugs.python.org/issue3709] by Andrew Schaaf). The operator.attrgetter() function has been sped-up (bpo-10160 [https://bugs.python.org/issue10160] by Christos Georgiou). And ConfigParser loads multi-line arguments a bit faster (bpo-7113 [https://bugs.python.org/issue7113] by Łukasz Langa).

Unicode

Python has been updated to Unicode 6.0.0 [http://unicode.org/versions/Unicode6.0.0/]. The update to the standard adds over 2,000 new characters including emoji [https://en.wikipedia.org/wiki/Emoji] symbols which are important for mobile phones.

In addition, the updated standard has altered the character properties for two Kannada characters (U+0CF1, U+0CF2) and one New Tai Lue numeric character (U+19DA), making the former eligible for use in identifiers while disqualifying the latter. For more information, see Unicode Character Database Changes [http://www.unicode.org/versions/Unicode6.0.0/#Database_Changes].

Codecs

Support was added for cp720 Arabic DOS encoding (bpo-1616979 [https://bugs.python.org/issue1616979]).

MBCS encoding no longer ignores the error handler argument. In the default strict mode, it raises an UnicodeDecodeError when it encounters an undecodable byte sequence and an UnicodeEncodeError for an unencodable character.

The MBCS codec supports 'strict' and 'ignore' error handlers for decoding, and 'strict' and 'replace' for encoding.

To emulate Python3.1 MBCS encoding, select the 'ignore' handler for decoding and the 'replace' handler for encoding.

On Mac OS X, Python decodes command line arguments with 'utf-8' rather than the locale encoding.

By default, tarfile uses 'utf-8' encoding on Windows (instead of 'mbcs') and the 'surrogateescape' error handler on all operating systems.

Documentation

The documentation continues to be improved.

A table of quick links has been added to the top of lengthy sections such as Fonctions natives. In the case of itertools, the links are accompanied by tables of cheatsheet-style summaries to provide an overview and memory jog without having to read all of the docs.

In some cases, the pure Python source code can be a helpful adjunct to the documentation, so now many modules now feature quick links to the latest version of the source code. For example, the functools module documentation has a quick link at the top labeled:

Source code Lib/functools.py [https://github.com/python/cpython/tree/3.6/Lib/functools.py].

(Contributed by Raymond Hettinger; see rationale [https://rhettinger.wordpress.com/2011/01/28/open-your-source-more/].)

The docs now contain more examples and recipes. In particular, re module has an extensive section, Exemples d’expressions rationnelles. Likewise, the itertools module continues to be updated with new Recettes itertools.

The datetime module now has an auxiliary implementation in pure Python. No functionality was changed. This just provides an easier-to-read alternate implementation.

(Contribution par Alexander Belopolsky; bpo-9528 [https://bugs.python.org/issue9528].)

The unmaintained Demo directory has been removed. Some demos were integrated into the documentation, some were moved to the Tools/demo directory, and others were removed altogether.

(Contribution par Georg Brandl; bpo-7962 [https://bugs.python.org/issue7962].)

IDLE

The format menu now has an option to clean source files by stripping trailing whitespace.

(Contribution par Raymond Hettinger; bpo-5150 [https://bugs.python.org/issue5150].)

IDLE on Mac OS X now works with both Carbon AquaTk and Cocoa AquaTk.

(Contributed by Kevin Walzer, Ned Deily, and Ronald Oussoren; bpo-6075 [https://bugs.python.org/issue6075].)

Code Repository

In addition to the existing Subversion code repository at http://svn.python.org there is now a Mercurial [https://www.mercurial-scm.org/] repository at https://hg.python.org/.

After the 3.2 release, there are plans to switch to Mercurial as the primary repository. This distributed version control system should make it easier for members of the community to create and share external changesets. See PEP 385 [https://www.python.org/dev/peps/pep-0385] for details.

To learn to use the new version control system, see the tutorial by Joel Spolsky [http://hginit.com] or the Guide to Mercurial Workflows [https://www.mercurial-scm.org/guide].

Build and C API Changes

Changes to Python’s build process and to the C API include:

The idle, pydoc and 2to3 scripts are now installed with a version-specific suffix on make altinstall (bpo-10679 [https://bugs.python.org/issue10679]).

The C functions that access the Unicode Database now accept and return characters from the full Unicode range, even on narrow unicode builds (Py_UNICODE_TOLOWER, Py_UNICODE_ISDECIMAL, and others). A visible difference in Python is that unicodedata.numeric() now returns the correct value for large code points, and repr() may consider more characters as printable.

(Reported by Bupjoe Lee and fixed by Amaury Forgeot D’Arc; bpo-5127 [https://bugs.python.org/issue5127].)

Computed gotos are now enabled by default on supported compilers (which are detected by the configure script). They can still be disabled selectively by specifying --without-computed-gotos.

(Contribution par Antoine Pitrou; bpo-9203 [https://bugs.python.org/issue9203].)

The option --with-wctype-functions was removed. The built-in unicode database is now used for all functions.

(Contribution par Amaury Forgeot D’Arc; bpo-9210 [https://bugs.python.org/issue9210].)

Hash values are now values of a new type, Py_hash_t, which is defined to be the same size as a pointer. Previously they were of type long, which on some 64-bit operating systems is still only 32 bits long. As a result of this fix, set and dict can now hold more than 2**32 entries on builds with 64-bit pointers (previously, they could grow to that size but their performance degraded catastrophically).

(Suggested by Raymond Hettinger and implemented by Benjamin Peterson; bpo-9778 [https://bugs.python.org/issue9778].)

A new macro Py_VA_COPY copies the state of the variable argument list. It is equivalent to C99 va_copy but available on all Python platforms (bpo-2443 [https://bugs.python.org/issue2443]).

A new C API function PySys_SetArgvEx() allows an embedded interpreter to set sys.argv without also modifying sys.path (bpo-5753 [https://bugs.python.org/issue5753]).

PyEval_CallObject is now only available in macro form. The function declaration, which was kept for backwards compatibility reasons, is now removed – the macro was introduced in 1997 (bpo-8276 [https://bugs.python.org/issue8276]).

There is a new function PyLong_AsLongLongAndOverflow() which is analogous to PyLong_AsLongAndOverflow(). They both serve to convert Python int into a native fixed-width type while providing detection of cases where the conversion won’t fit (bpo-7767 [https://bugs.python.org/issue7767]).

The PyUnicode_CompareWithASCIIString() function now returns not equal if the Python string is NUL terminated.

There is a new function PyErr_NewExceptionWithDoc() that is like PyErr_NewException() but allows a docstring to be specified. This lets C exceptions have the same self-documenting capabilities as their pure Python counterparts (bpo-7033 [https://bugs.python.org/issue7033]).

When compiled with the --with-valgrind option, the pymalloc allocator will be automatically disabled when running under Valgrind. This gives improved memory leak detection when running under Valgrind, while taking advantage of pymalloc at other times (bpo-2422 [https://bugs.python.org/issue2422]).

Removed the O? format from the PyArg_Parse functions. The format is no longer used and it had never been documented (bpo-8837 [https://bugs.python.org/issue8837]).

There were a number of other small changes to the C-API. See the Misc/NEWS [https://github.com/python/cpython/tree/3.6/Misc/NEWS] file for a complete list.

Also, there were a number of updates to the Mac OS X build, see Mac/BuildScript/README.txt [https://github.com/python/cpython/tree/3.6/Mac/BuildScript/README.txt] for details. For users running a 32/64-bit build, there is a known problem with the default Tcl/Tk on Mac OS X 10.6. Accordingly, we recommend installing an updated alternative such as ActiveState Tcl/Tk 8.5.9 [https://www.activestate.com/activetcl/downloads]. See https://www.python.org/download/mac/tcltk/ for additional details.

Portage vers Python 3.2

This section lists previously described changes and other bugfixes that may require changes to your code:

The configparser module has a number of clean-ups. The major change is to replace the old ConfigParser class with long-standing preferred alternative SafeConfigParser. In addition there are a number of smaller incompatibilities:

The interpolation syntax is now validated on get() and set() operations. In the default interpolation scheme, only two tokens with percent signs are valid: %(name)s and %%, the latter being an escaped percent sign.

The set() and add_section() methods now verify that values are actual strings. Formerly, unsupported types could be introduced unintentionally.

Duplicate sections or options from a single source now raise either DuplicateSectionError or DuplicateOptionError. Formerly, duplicates would silently overwrite a previous entry.

Inline comments are now disabled by default so now the ; character can be safely used in values.

Comments now can be indented. Consequently, for ; or # to appear at the start of a line in multiline values, it has to be interpolated. This keeps comment prefix characters in values from being mistaken as comments.

"" is now a valid value and is no longer automatically converted to an empty string. For empty strings, use "option =" in a line.

The nntplib module was reworked extensively, meaning that its APIs are often incompatible with the 3.1 APIs.

Les objets bytearray ne peuvent plus être utilisés en tant que nom de fichiers : ils doivent être convertis en bytes à la place.

The array.tostring() and array.fromstring() have been renamed to array.tobytes() and array.frombytes() for clarity. The old names have been deprecated. (See bpo-8990 [https://bugs.python.org/issue8990].)

Les fonctions PyArg_Parse*() :

Le format « t# » a été supprimé : utiliser « s# » ou « s* » à la place

Les formats « w » et « w# » ont été supprimés : utiliser « w* » à la place

The PyCObject type, deprecated in 3.1, has been removed. To wrap opaque C pointers in Python objects, the PyCapsule API should be used instead; the new type has a well-defined interface for passing typing safety information and a less complicated signature for calling a destructor.

The sys.setfilesystemencoding() function was removed because it had a flawed design.

The random.seed() function and method now salt string seeds with an sha512 hash function. To access the previous version of seed in order to reproduce Python 3.1 sequences, set the version argument to 1, random.seed(s, version=1).

The previously deprecated string.maketrans() function has been removed in favor of the static methods bytes.maketrans() and bytearray.maketrans(). This change solves the confusion around which types were supported by the string module. Now, str, bytes, and bytearray each have their own maketrans and translate methods with intermediate translation tables of the appropriate type.

(Contribution par Georg Brandl; bpo-5675 [https://bugs.python.org/issue5675].)

The previously deprecated contextlib.nested() function has been removed in favor of a plain with statement which can accept multiple context managers. The latter technique is faster (because it is built-in), and it does a better job finalizing multiple context managers when one of them raises an exception:

with open('mylog.txt') as infile, open('a.out', 'w') as outfile:
    for line in infile:
        if '<critical>' in line:
            outfile.write(line)

(Contributed by Georg Brandl and Mattias Brändström; appspot issue 53094 [https://codereview.appspot.com/53094].)

struct.pack() now only allows bytes for the s string pack code. Formerly, it would accept text arguments and implicitly encode them to bytes using UTF-8. This was problematic because it made assumptions about the correct encoding and because a variable-length encoding can fail when writing to fixed length segment of a structure.

Code such as struct.pack('<6sHHBBB', 'GIF87a', x, y) should be rewritten with to use bytes instead of text, struct.pack('<6sHHBBB', b'GIF87a', x, y).

(Discovered by David Beazley and fixed by Victor Stinner; bpo-10783 [https://bugs.python.org/issue10783].)

The xml.etree.ElementTree class now raises an xml.etree.ElementTree.ParseError when a parse fails. Previously it raised an xml.parsers.expat.ExpatError.

The new, longer str() value on floats may break doctests which rely on the old output format.

In subprocess.Popen, the default value for close_fds is now True under Unix; under Windows, it is True if the three standard streams are set to None, False otherwise. Previously, close_fds was always False by default, which produced difficult to solve bugs or race conditions when open file descriptors would leak into the child process.

Support for legacy HTTP 0.9 has been removed from urllib.request and http.client. Such support is still present on the server side (in http.server).

(Contribution par Antoine Pitrou; bpo-10711 [https://bugs.python.org/issue10711].)

SSL sockets in timeout mode now raise socket.timeout when a timeout occurs, rather than a generic SSLError.

(Contribution par Antoine Pitrou; bpo-10272 [https://bugs.python.org/issue10272].)

The misleading functions PyEval_AcquireLock() and PyEval_ReleaseLock() have been officially deprecated. The thread-state aware APIs (such as PyEval_SaveThread() and PyEval_RestoreThread()) should be used instead.

Due to security risks, asyncore.handle_accept() has been deprecated, and a new function, asyncore.handle_accepted(), was added to replace it.

(Contribution par Giampaolo Rodola; bpo-6706 [https://bugs.python.org/issue6706].)

Due to the new GIL implementation, PyEval_InitThreads() cannot be called before Py_Initialize() anymore.

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Nouveautés de Python 3.1

Auteur

Raymond Hettinger

This article explains the new features in Python 3.1, compared to 3.0.

PEP 372: Ordered Dictionaries

Regular Python dictionaries iterate over key/value pairs in arbitrary order. Over the years, a number of authors have written alternative implementations that remember the order that the keys were originally inserted. Based on the experiences from those implementations, a new collections.OrderedDict class has been introduced.

The OrderedDict API is substantially the same as regular dictionaries but will iterate over keys and values in a guaranteed order depending on when a key was first inserted. If a new entry overwrites an existing entry, the original insertion position is left unchanged. Deleting an entry and reinserting it will move it to the end.

The standard library now supports use of ordered dictionaries in several modules. The configparser module uses them by default. This lets configuration files be read, modified, and then written back in their original order. The _asdict() method for collections.namedtuple() now returns an ordered dictionary with the values appearing in the same order as the underlying tuple indicies. The json module is being built-out with an object_pairs_hook to allow OrderedDicts to be built by the decoder. Support was also added for third-party tools like PyYAML [http://pyyaml.org/].

Voir aussi

PEP 372 [https://www.python.org/dev/peps/pep-0372] - Ordered Dictionaries

PEP written by Armin Ronacher and Raymond Hettinger. Implementation written by Raymond Hettinger.

PEP 378: Format Specifier for Thousands Separator

The built-in format() function and the str.format() method use a mini-language that now includes a simple, non-locale aware way to format a number with a thousands separator. That provides a way to humanize a program’s output, improving its professional appearance and readability:

>>> format(1234567, ',d')
'1,234,567'
>>> format(1234567.89, ',.2f')
'1,234,567.89'
>>> format(12345.6 + 8901234.12j, ',f')
'12,345.600000+8,901,234.120000j'
>>> format(Decimal('1234567.89'), ',f')
'1,234,567.89'

The supported types are int, float, complex and decimal.Decimal.

Discussions are underway about how to specify alternative separators like dots, spaces, apostrophes, or underscores. Locale-aware applications should use the existing n format specifier which already has some support for thousands separators.

Voir aussi

PEP 378 [https://www.python.org/dev/peps/pep-0378] - Format Specifier for Thousands Separator

PEP written by Raymond Hettinger and implemented by Eric Smith and Mark Dickinson.

Other Language Changes

Some smaller changes made to the core Python language are:

Directories and zip archives containing a __main__.py file can now be executed directly by passing their name to the interpreter. The directory/zipfile is automatically inserted as the first entry in sys.path. (Suggestion and initial patch by Andy Chu; revised patch by Phillip J. Eby and Nick Coghlan; bpo-1739468 [https://bugs.python.org/issue1739468].)

The int() type gained a bit_length method that returns the number of bits necessary to represent its argument in binary:

>>> n = 37
>>> bin(37)
'0b100101'
>>> n.bit_length()
6
>>> n = 2**123-1
>>> n.bit_length()
123
>>> (n+1).bit_length()
124

(Contributed by Fredrik Johansson, Victor Stinner, Raymond Hettinger, and Mark Dickinson; bpo-3439 [https://bugs.python.org/issue3439].)

The fields in format() strings can now be automatically numbered:

>>> 'Sir {} of {}'.format('Gallahad', 'Camelot')
'Sir Gallahad of Camelot'

Formerly, the string would have required numbered fields such as: 'Sir {0} of {1}'.

(Contribution par Eric Smith; bpo-5237 [https://bugs.python.org/issue5237].)

The string.maketrans() function is deprecated and is replaced by new static methods, bytes.maketrans() and bytearray.maketrans(). This change solves the confusion around which types were supported by the string module. Now, str, bytes, and bytearray each have their own maketrans and translate methods with intermediate translation tables of the appropriate type.

(Contribution par Georg Brandl; bpo-5675 [https://bugs.python.org/issue5675].)

The syntax of the with statement now allows multiple context managers in a single statement:

>>> with open('mylog.txt') as infile, open('a.out', 'w') as outfile:
...     for line in infile:
...         if '<critical>' in line:
...             outfile.write(line)

With the new syntax, the contextlib.nested() function is no longer needed and is now deprecated.

(Contributed by Georg Brandl and Mattias Brändström; appspot issue 53094 [https://codereview.appspot.com/53094].)

round(x, n) now returns an integer if x is an integer. Previously it returned a float:

>>> round(1123, -2)
1100

(Contribution par Mark Dickinson; bpo-4707 [https://bugs.python.org/issue4707].)

Python now uses David Gay’s algorithm for finding the shortest floating point representation that doesn’t change its value. This should help mitigate some of the confusion surrounding binary floating point numbers.

The significance is easily seen with a number like 1.1 which does not have an exact equivalent in binary floating point. Since there is no exact equivalent, an expression like float('1.1') evaluates to the nearest representable value which is 0x1.199999999999ap+0 in hex or 1.100000000000000088817841970012523233890533447265625 in decimal. That nearest value was and still is used in subsequent floating point calculations.

What is new is how the number gets displayed. Formerly, Python used a simple approach. The value of repr(1.1) was computed as format(1.1, '.17g') which evaluated to '1.1000000000000001'. The advantage of using 17 digits was that it relied on IEEE-754 guarantees to assure that eval(repr(1.1)) would round-trip exactly to its original value. The disadvantage is that many people found the output to be confusing (mistaking intrinsic limitations of binary floating point representation as being a problem with Python itself).

The new algorithm for repr(1.1) is smarter and returns '1.1'. Effectively, it searches all equivalent string representations (ones that get stored with the same underlying float value) and returns the shortest representation.

The new algorithm tends to emit cleaner representations when possible, but it does not change the underlying values. So, it is still the case that 1.1 + 2.2 != 3.3 even though the representations may suggest otherwise.

The new algorithm depends on certain features in the underlying floating point implementation. If the required features are not found, the old algorithm will continue to be used. Also, the text pickle protocols assure cross-platform portability by using the old algorithm.

(Contribution par Eric Smith et Mark Dickinson; bpo-1580 [https://bugs.python.org/issue1580].)

New, Improved, and Deprecated Modules

Added a collections.Counter class to support convenient counting of unique items in a sequence or iterable:

>>> Counter(['red', 'blue', 'red', 'green', 'blue', 'blue'])
Counter({'blue': 3, 'red': 2, 'green': 1})

(Contribution par Raymond Hettinger; bpo-1696199 [https://bugs.python.org/issue1696199].)

Added a new module, tkinter.ttk for access to the Tk themed widget set. The basic idea of ttk is to separate, to the extent possible, the code implementing a widget’s behavior from the code implementing its appearance.

(Contribution par Guilherme Polo; bpo-2983 [https://bugs.python.org/issue2983].)

The gzip.GzipFile and bz2.BZ2File classes now support the context management protocol:

>>> # Automatically close file after writing
>>> with gzip.GzipFile(filename, "wb") as f:
...     f.write(b"xxx")

(Contribution par Antoine Pitrou)

The decimal module now supports methods for creating a decimal object from a binary float. The conversion is exact but can sometimes be surprising:

>>> Decimal.from_float(1.1)
Decimal('1.100000000000000088817841970012523233890533447265625')

The long decimal result shows the actual binary fraction being stored for 1.1. The fraction has many digits because 1.1 cannot be exactly represented in binary.

(Contributed by Raymond Hettinger and Mark Dickinson.)

The itertools module grew two new functions. The itertools.combinations_with_replacement() function is one of four for generating combinatorics including permutations and Cartesian products. The itertools.compress() function mimics its namesake from APL. Also, the existing itertools.count() function now has an optional step argument and can accept any type of counting sequence including fractions.Fraction and decimal.Decimal:

>>> [p+q for p,q in combinations_with_replacement('LOVE', 2)]
['LL', 'LO', 'LV', 'LE', 'OO', 'OV', 'OE', 'VV', 'VE', 'EE']

>>> list(compress(data=range(10), selectors=[0,0,1,1,0,1,0,1,0,0]))
[2, 3, 5, 7]

>>> c = count(start=Fraction(1,2), step=Fraction(1,6))
>>> [next(c), next(c), next(c), next(c)]
[Fraction(1, 2), Fraction(2, 3), Fraction(5, 6), Fraction(1, 1)]

(Contributed by Raymond Hettinger.)

collections.namedtuple() now supports a keyword argument rename which lets invalid fieldnames be automatically converted to positional names in the form _0, _1, etc. This is useful when the field names are being created by an external source such as a CSV header, SQL field list, or user input:

>>> query = input()
SELECT region, dept, count(*) FROM main GROUPBY region, dept

>>> cursor.execute(query)
>>> query_fields = [desc[0] for desc in cursor.description]
>>> UserQuery = namedtuple('UserQuery', query_fields, rename=True)
>>> pprint.pprint([UserQuery(*row) for row in cursor])
[UserQuery(region='South', dept='Shipping', _2=185),
 UserQuery(region='North', dept='Accounting', _2=37),
 UserQuery(region='West', dept='Sales', _2=419)]

(Contribution par Raymond Hettinger; bpo-1818 [https://bugs.python.org/issue1818].)

The re.sub(), re.subn() and re.split() functions now accept a flags parameter.

(Contributed by Gregory Smith.)

The logging module now implements a simple logging.NullHandler class for applications that are not using logging but are calling library code that does. Setting-up a null handler will suppress spurious warnings such as « No handlers could be found for logger foo »:

>>> h = logging.NullHandler()
>>> logging.getLogger("foo").addHandler(h)

(Contribution par Vinay Sajip ; bpo-4384 [https://bugs.python.org/issue4384]).

The runpy module which supports the -m command line switch now supports the execution of packages by looking for and executing a __main__ submodule when a package name is supplied.

(Contribution par Andi Vajda; bpo-4195 [https://bugs.python.org/issue4195].)

The pdb module can now access and display source code loaded via zipimport (or any other conformant PEP 302 [https://www.python.org/dev/peps/pep-0302] loader).

(Contribution par Alexander Belopolsky; bpo-4201 [https://bugs.python.org/issue4201].)

functools.partial objects can now be pickled.

(Suggested by Antoine Pitrou and Jesse Noller. Implemented by Jack Diederich; bpo-5228 [https://bugs.python.org/issue5228].)

Add pydoc help topics for symbols so that help('@') works as expected in the interactive environment.

(Contribution par David Laban; bpo-4739 [https://bugs.python.org/issue4739].)

The unittest module now supports skipping individual tests or classes of tests. And it supports marking a test as an expected failure, a test that is known to be broken, but shouldn’t be counted as a failure on a TestResult:

class TestGizmo(unittest.TestCase):

    @unittest.skipUnless(sys.platform.startswith("win"), "requires Windows")
    def test_gizmo_on_windows(self):
        ...

    @unittest.expectedFailure
    def test_gimzo_without_required_library(self):
        ...

Also, tests for exceptions have been builtout to work with context managers using the with statement:

def test_division_by_zero(self):
    with self.assertRaises(ZeroDivisionError):
        x / 0

In addition, several new assertion methods were added including assertSetEqual(), assertDictEqual(), assertDictContainsSubset(), assertListEqual(), assertTupleEqual(), assertSequenceEqual(), assertRaisesRegexp(), assertIsNone(), and assertIsNotNone().

(Contribution par Benjamin Peterson et Antoine Pitrou)

The io module has three new constants for the seek() method SEEK_SET, SEEK_CUR, and SEEK_END.

The sys.version_info tuple is now a named tuple:

>>> sys.version_info
sys.version_info(major=3, minor=1, micro=0, releaselevel='alpha', serial=2)

(Contribution par Ross Ligh; bpo-4285 [https://bugs.python.org/issue4285].)

The nntplib and imaplib modules now support IPv6.

(Contribution par Derek Morr; bpo-1655 [https://bugs.python.org/issue1655] et bpo-1664 [https://bugs.python.org/issue1664])

The pickle module has been adapted for better interoperability with Python 2.x when used with protocol 2 or lower. The reorganization of the standard library changed the formal reference for many objects. For example, __builtin__.set in Python 2 is called builtins.set in Python 3. This change confounded efforts to share data between different versions of Python. But now when protocol 2 or lower is selected, the pickler will automatically use the old Python 2 names for both loading and dumping. This remapping is turned-on by default but can be disabled with the fix_imports option:

>>> s = {1, 2, 3}
>>> pickle.dumps(s, protocol=0)
b'c__builtin__\nset\np0\n((lp1\nL1L\naL2L\naL3L\natp2\nRp3\n.'
>>> pickle.dumps(s, protocol=0, fix_imports=False)
b'cbuiltins\nset\np0\n((lp1\nL1L\naL2L\naL3L\natp2\nRp3\n.'

An unfortunate but unavoidable side-effect of this change is that protocol 2 pickles produced by Python 3.1 won’t be readable with Python 3.0. The latest pickle protocol, protocol 3, should be used when migrating data between Python 3.x implementations, as it doesn’t attempt to remain compatible with Python 2.x.

(Contribution par Alexandre Vassalotti et Antoine Pitrou; bpo-6137 [https://bugs.python.org/issue6137].)

A new module, importlib was added. It provides a complete, portable, pure Python reference implementation of the import statement and its counterpart, the __import__() function. It represents a substantial step forward in documenting and defining the actions that take place during imports.

(Contributed by Brett Cannon.)

Optimizations

Major performance enhancements have been added:

The new I/O library (as defined in PEP 3116 [https://www.python.org/dev/peps/pep-3116]) was mostly written in Python and quickly proved to be a problematic bottleneck in Python 3.0. In Python 3.1, the I/O library has been entirely rewritten in C and is 2 to 20 times faster depending on the task at hand. The pure Python version is still available for experimentation purposes through the _pyio module.

(Contribution par Amaury Forgeot d’Arc et Antoine Pitrou)

Added a heuristic so that tuples and dicts containing only untrackable objects are not tracked by the garbage collector. This can reduce the size of collections and therefore the garbage collection overhead on long-running programs, depending on their particular use of datatypes.

(Contribution par Antoine Pitrou; bpo-4688 [https://bugs.python.org/issue4688].)

Enabling a configure option named --with-computed-gotos on compilers that support it (notably: gcc, SunPro, icc), the bytecode evaluation loop is compiled with a new dispatch mechanism which gives speedups of up to 20%, depending on the system, the compiler, and the benchmark.

(Contribution par Antoine Pitrou ainsi qu’un certain nombre d’autres participants ; bpo-4753 [https://bugs.python.org/issue4753]).

The decoding of UTF-8, UTF-16 and LATIN-1 is now two to four times faster.

(Contribution par Antoine Pitrou et Amaury Forgeot d’Arc; bpo-4868 [https://bugs.python.org/issue4868].)

The json module now has a C extension to substantially improve its performance. In addition, the API was modified so that json works only with str, not with bytes. That change makes the module closely match the JSON specification [http://json.org/] which is defined in terms of Unicode.

(Contributed by Bob Ippolito and converted to Py3.1 by Antoine Pitrou and Benjamin Peterson; bpo-4136 [https://bugs.python.org/issue4136].)

Unpickling now interns the attribute names of pickled objects. This saves memory and allows pickles to be smaller.

(Contribution par Jake McGuire et Antoine Pitrou; bpo-5084 [https://bugs.python.org/issue5084].)

IDLE

IDLE’s format menu now provides an option to strip trailing whitespace from a source file.

(Contribution par Roger D. Serwy; bpo-5150 [https://bugs.python.org/issue5150].)

Build and C API Changes

Changes to Python’s build process and to the C API include:

Integers are now stored internally either in base 2**15 or in base 2**30, the base being determined at build time. Previously, they were always stored in base 2**15. Using base 2**30 gives significant performance improvements on 64-bit machines, but benchmark results on 32-bit machines have been mixed. Therefore, the default is to use base 2**30 on 64-bit machines and base 2**15 on 32-bit machines; on Unix, there’s a new configure option --enable-big-digits that can be used to override this default.

Apart from the performance improvements this change should be invisible to end users, with one exception: for testing and debugging purposes there’s a new sys.int_info that provides information about the internal format, giving the number of bits per digit and the size in bytes of the C type used to store each digit:

>>> import sys
>>> sys.int_info
sys.int_info(bits_per_digit=30, sizeof_digit=4)

(Contribution par Mark Dickinson; bpo-4258 [https://bugs.python.org/issue4258].)

The PyLong_AsUnsignedLongLong() function now handles a negative pylong by raising OverflowError instead of TypeError.

(Contribution par Mark Dickinson et Lisandro Dalcrin; bpo-5175 [https://bugs.python.org/issue5175])

Deprecated PyNumber_Int(). Use PyNumber_Long() instead.

(Contribution par Mark Dickinson; bpo-4910 [https://bugs.python.org/issue4910])

Added a new PyOS_string_to_double() function to replace the deprecated functions PyOS_ascii_strtod() and PyOS_ascii_atof().

(Contribution par Mark Dickinson; bpo-5914 [https://bugs.python.org/issue5914])

Added PyCapsule as a replacement for the PyCObject API. The principal difference is that the new type has a well defined interface for passing typing safety information and a less complicated signature for calling a destructor. The old type had a problematic API and is now deprecated.

(Contribution par Larry Hastings; bpo-5630 [https://bugs.python.org/issue5630])

Portage vers Python 3.1

This section lists previously described changes and other bugfixes that may require changes to your code:

The new floating point string representations can break existing doctests. For example:

def e():
    '''Compute the base of natural logarithms.

    >>> e()
    2.7182818284590451

    '''
    return sum(1/math.factorial(x) for x in reversed(range(30)))

doctest.testmod()

**********************************************************************
Failed example:
    e()
Expected:
    2.7182818284590451
Got:
    2.718281828459045
**********************************************************************

The automatic name remapping in the pickle module for protocol 2 or lower can make Python 3.1 pickles unreadable in Python 3.0. One solution is to use protocol 3. Another solution is to set the fix_imports option to False. See the discussion above for more details.

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Nouveautés de Python 3.0

Auteur

Guido van Rossum

This article explains the new features in Python 3.0, compared to 2.6. Python 3.0, also known as « Python 3000 » or « Py3K », is the first ever intentionally backwards incompatible Python release. There are more changes than in a typical release, and more that are important for all Python users. Nevertheless, after digesting the changes, you’ll find that Python really hasn’t changed all that much – by and large, we’re mostly fixing well-known annoyances and warts, and removing a lot of old cruft.

This article doesn’t attempt to provide a complete specification of all new features, but instead tries to give a convenient overview. For full details, you should refer to the documentation for Python 3.0, and/or the many PEPs referenced in the text. If you want to understand the complete implementation and design rationale for a particular feature, PEPs usually have more details than the regular documentation; but note that PEPs usually are not kept up-to-date once a feature has been fully implemented.

Due to time constraints this document is not as complete as it should have been. As always for a new release, the Misc/NEWS file in the source distribution contains a wealth of detailed information about every small thing that was changed.

Common Stumbling Blocks

This section lists those few changes that are most likely to trip you up if you’re used to Python 2.5.

Print Is A Function

The print statement has been replaced with a print() function, with keyword arguments to replace most of the special syntax of the old print statement (PEP 3105 [https://www.python.org/dev/peps/pep-3105]). Examples:

Old: print "The answer is", 2*2
New: print("The answer is", 2*2)

Old: print x,           # Trailing comma suppresses newline
New: print(x, end=" ")  # Appends a space instead of a newline

Old: print              # Prints a newline
New: print()            # You must call the function!

Old: print >>sys.stderr, "fatal error"
New: print("fatal error", file=sys.stderr)

Old: print (x, y)       # prints repr((x, y))
New: print((x, y))      # Not the same as print(x, y)!

You can also customize the separator between items, e.g.:

print("There are <", 2**32, "> possibilities!", sep="")

which produces:

There are <4294967296> possibilities!

Note:

The print() function doesn’t support the « softspace » feature of the old print statement. For example, in Python 2.x, print "A\n", "B" would write "A\nB\n"; but in Python 3.0, print("A\n", "B") writes "A\n B\n".

Initially, you’ll be finding yourself typing the old print x a lot in interactive mode. Time to retrain your fingers to type print(x) instead!

When using the 2to3 source-to-source conversion tool, all print statements are automatically converted to print() function calls, so this is mostly a non-issue for larger projects.

Views And Iterators Instead Of Lists

Some well-known APIs no longer return lists:

dict methods dict.keys(), dict.items() and dict.values() return « views » instead of lists. For example, this no longer works: k = d.keys(); k.sort(). Use k = sorted(d) instead (this works in Python 2.5 too and is just as efficient).

Also, the dict.iterkeys(), dict.iteritems() and dict.itervalues() methods are no longer supported.

map() and filter() return iterators. If you really need a list and the input sequences are all of equal length, a quick fix is to wrap map() in list(), e.g. list(map(...)), but a better fix is often to use a list comprehension (especially when the original code uses lambda), or rewriting the code so it doesn’t need a list at all. Particularly tricky is map() invoked for the side effects of the function; the correct transformation is to use a regular for loop (since creating a list would just be wasteful).

If the input sequences are not of equal length, map() will stop at the termination of the shortest of the sequences. For full compatibility with map() from Python 2.x, also wrap the sequences in itertools.zip_longest(), e.g. map(func, *sequences) becomes list(map(func, itertools.zip_longest(*sequences))).

range() now behaves like xrange() used to behave, except it works with values of arbitrary size. The latter no longer exists.

zip() renvoie maintenant un itérateur.

Ordering Comparisons

Python 3.0 has simplified the rules for ordering comparisons:

The ordering comparison operators (<, <=, >=, >) raise a TypeError exception when the operands don’t have a meaningful natural ordering. Thus, expressions like 1 < '', 0 > None or len <= len are no longer valid, and e.g. None < None raises TypeError instead of returning False. A corollary is that sorting a heterogeneous list no longer makes sense – all the elements must be comparable to each other. Note that this does not apply to the == and != operators: objects of different incomparable types always compare unequal to each other.

builtin.sorted() and list.sort() no longer accept the cmp argument providing a comparison function. Use the key argument instead. N.B. the key and reverse arguments are now « keyword-only ».

The cmp() function should be treated as gone, and the __cmp__() special method is no longer supported. Use __lt__() for sorting, __eq__() with __hash__(), and other rich comparisons as needed. (If you really need the cmp() functionality, you could use the expression (a > b) - (a < b) as the equivalent for cmp(a, b).)

Integers

PEP 237 [https://www.python.org/dev/peps/pep-0237]: Essentially, long renamed to int. That is, there is only one built-in integral type, named int; but it behaves mostly like the old long type.

PEP 238 [https://www.python.org/dev/peps/pep-0238]: An expression like 1/2 returns a float. Use 1//2 to get the truncating behavior. (The latter syntax has existed for years, at least since Python 2.2.)

The sys.maxint constant was removed, since there is no longer a limit to the value of integers. However, sys.maxsize can be used as an integer larger than any practical list or string index. It conforms to the implementation’s « natural » integer size and is typically the same as sys.maxint in previous releases on the same platform (assuming the same build options).

The repr() of a long integer doesn’t include the trailing L anymore, so code that unconditionally strips that character will chop off the last digit instead. (Use str() instead.)

Octal literals are no longer of the form 0720; use 0o720 instead.

Text Vs. Data Instead Of Unicode Vs. 8-bit

Everything you thought you knew about binary data and Unicode has changed.

Python 3.0 uses the concepts of text and (binary) data instead of Unicode strings and 8-bit strings. All text is Unicode; however encoded Unicode is represented as binary data. The type used to hold text is str, the type used to hold data is bytes. The biggest difference with the 2.x situation is that any attempt to mix text and data in Python 3.0 raises TypeError, whereas if you were to mix Unicode and 8-bit strings in Python 2.x, it would work if the 8-bit string happened to contain only 7-bit (ASCII) bytes, but you would get UnicodeDecodeError if it contained non-ASCII values. This value-specific behavior has caused numerous sad faces over the years.

As a consequence of this change in philosophy, pretty much all code that uses Unicode, encodings or binary data most likely has to change. The change is for the better, as in the 2.x world there were numerous bugs having to do with mixing encoded and unencoded text. To be prepared in Python 2.x, start using unicode for all unencoded text, and str for binary or encoded data only. Then the 2to3 tool will do most of the work for you.

You can no longer use u"..." literals for Unicode text. However, you must use b"..." literals for binary data.

As the str and bytes types cannot be mixed, you must always explicitly convert between them. Use str.encode() to go from str to bytes, and bytes.decode() to go from bytes to str. You can also use bytes(s, encoding=...) and str(b, encoding=...), respectively.

Like str, the bytes type is immutable. There is a separate mutable type to hold buffered binary data, bytearray. Nearly all APIs that accept bytes also accept bytearray. The mutable API is based on collections.MutableSequence.

All backslashes in raw string literals are interpreted literally. This means that '\U' and '\u' escapes in raw strings are not treated specially. For example, r'\u20ac' is a string of 6 characters in Python 3.0, whereas in 2.6, ur'\u20ac' was the single « euro » character. (Of course, this change only affects raw string literals; the euro character is '\u20ac' in Python 3.0.)

The built-in basestring abstract type was removed. Use str instead. The str and bytes types don’t have functionality enough in common to warrant a shared base class. The 2to3 tool (see below) replaces every occurrence of basestring with str.

Files opened as text files (still the default mode for open()) always use an encoding to map between strings (in memory) and bytes (on disk). Binary files (opened with a b in the mode argument) always use bytes in memory. This means that if a file is opened using an incorrect mode or encoding, I/O will likely fail loudly, instead of silently producing incorrect data. It also means that even Unix users will have to specify the correct mode (text or binary) when opening a file. There is a platform-dependent default encoding, which on Unixy platforms can be set with the LANG environment variable (and sometimes also with some other platform-specific locale-related environment variables). In many cases, but not all, the system default is UTF-8; you should never count on this default. Any application reading or writing more than pure ASCII text should probably have a way to override the encoding. There is no longer any need for using the encoding-aware streams in the codecs module.

The initial values of sys.stdin, sys.stdout and sys.stderr are now unicode-only text files (i.e., they are instances of io.TextIOBase). To read and write bytes data with these streams, you need to use their io.TextIOBase.buffer attribute.

Filenames are passed to and returned from APIs as (Unicode) strings. This can present platform-specific problems because on some platforms filenames are arbitrary byte strings. (On the other hand, on Windows filenames are natively stored as Unicode.) As a work-around, most APIs (e.g. open() and many functions in the os module) that take filenames accept bytes objects as well as strings, and a few APIs have a way to ask for a bytes return value. Thus, os.listdir() returns a list of bytes instances if the argument is a bytes instance, and os.getcwdb() returns the current working directory as a bytes instance. Note that when os.listdir() returns a list of strings, filenames that cannot be decoded properly are omitted rather than raising UnicodeError.

Some system APIs like os.environ and sys.argv can also present problems when the bytes made available by the system is not interpretable using the default encoding. Setting the LANG variable and rerunning the program is probably the best approach.

PEP 3138 [https://www.python.org/dev/peps/pep-3138]: The repr() of a string no longer escapes non-ASCII characters. It still escapes control characters and code points with non-printable status in the Unicode standard, however.

PEP 3120 [https://www.python.org/dev/peps/pep-3120]: The default source encoding is now UTF-8.

PEP 3131 [https://www.python.org/dev/peps/pep-3131]: Non-ASCII letters are now allowed in identifiers. (However, the standard library remains ASCII-only with the exception of contributor names in comments.)

The StringIO and cStringIO modules are gone. Instead, import the io module and use io.StringIO or io.BytesIO for text and data respectively.

See also the Guide Unicode, which was updated for Python 3.0.

Overview Of Syntax Changes

This section gives a brief overview of every syntactic change in Python 3.0.

New Syntax

PEP 3107 [https://www.python.org/dev/peps/pep-3107]: Function argument and return value annotations. This provides a standardized way of annotating a function’s parameters and return value. There are no semantics attached to such annotations except that they can be introspected at runtime using the __annotations__ attribute. The intent is to encourage experimentation through metaclasses, decorators or frameworks.

PEP 3102 [https://www.python.org/dev/peps/pep-3102]: Keyword-only arguments. Named parameters occurring after *args in the parameter list must be specified using keyword syntax in the call. You can also use a bare * in the parameter list to indicate that you don’t accept a variable-length argument list, but you do have keyword-only arguments.

Keyword arguments are allowed after the list of base classes in a class definition. This is used by the new convention for specifying a metaclass (see next section), but can be used for other purposes as well, as long as the metaclass supports it.

PEP 3104 [https://www.python.org/dev/peps/pep-3104]: nonlocal statement. Using nonlocal x you can now assign directly to a variable in an outer (but non-global) scope. nonlocal is a new reserved word.

PEP 3132 [https://www.python.org/dev/peps/pep-3132]: Extended Iterable Unpacking. You can now write things like a, b, *rest = some_sequence. And even *rest, a = stuff. The rest object is always a (possibly empty) list; the right-hand side may be any iterable. Example:

(a, *rest, b) = range(5)

This sets a to 0, b to 4, and rest to [1, 2, 3].

Dictionary comprehensions: {k: v for k, v in stuff} means the same thing as dict(stuff) but is more flexible. (This is PEP 274 [https://www.python.org/dev/peps/pep-0274] vindicated. :-)

Set literals, e.g. {1, 2}. Note that {} is an empty dictionary; use set() for an empty set. Set comprehensions are also supported; e.g., {x for x in stuff} means the same thing as set(stuff) but is more flexible.

New octal literals, e.g. 0o720 (already in 2.6). The old octal literals (0720) are gone.

New binary literals, e.g. 0b1010 (already in 2.6), and there is a new corresponding built-in function, bin().

Bytes literals are introduced with a leading b or B, and there is a new corresponding built-in function, bytes().

Changed Syntax

PEP 3109 [https://www.python.org/dev/peps/pep-3109] and PEP 3134 [https://www.python.org/dev/peps/pep-3134]: new raise statement syntax: raise [expr [from expr]]. See below.

as and with are now reserved words. (Since 2.6, actually.)

True, False, and None are reserved words. (2.6 partially enforced the restrictions on None already.)

Change from except exc, var to except exc as var. See PEP 3110 [https://www.python.org/dev/peps/pep-3110].

PEP 3115 [https://www.python.org/dev/peps/pep-3115]: New Metaclass Syntax. Instead of:

class C:
    __metaclass__ = M
    ...

you must now use:

class C(metaclass=M):
    ...

The module-global __metaclass__ variable is no longer supported. (It was a crutch to make it easier to default to new-style classes without deriving every class from object.)

List comprehensions no longer support the syntactic form [... for var in item1, item2, ...]. Use [... for var in (item1, item2, ...)] instead. Also note that list comprehensions have different semantics: they are closer to syntactic sugar for a generator expression inside a list() constructor, and in particular the loop control variables are no longer leaked into the surrounding scope.

The ellipsis (...) can be used as an atomic expression anywhere. (Previously it was only allowed in slices.) Also, it must now be spelled as .... (Previously it could also be spelled as . . ., by a mere accident of the grammar.)

Removed Syntax

PEP 3113 [https://www.python.org/dev/peps/pep-3113]: Tuple parameter unpacking removed. You can no longer write def foo(a, (b, c)): .... Use def foo(a, b_c): b, c = b_c instead.

Removed backticks (use repr() instead).

Removed <> (use != instead).

Removed keyword: exec() is no longer a keyword; it remains as a function. (Fortunately the function syntax was also accepted in 2.x.) Also note that exec() no longer takes a stream argument; instead of exec(f) you can use exec(f.read()).

Integer literals no longer support a trailing l or L.

String literals no longer support a leading u or U.

The from module import * syntax is only allowed at the module level, no longer inside functions.

The only acceptable syntax for relative imports is from .[module] import name. All import forms not starting with . are interpreted as absolute imports. (PEP 328 [https://www.python.org/dev/peps/pep-0328])

Classic classes are gone.

Changes Already Present In Python 2.6

Since many users presumably make the jump straight from Python 2.5 to Python 3.0, this section reminds the reader of new features that were originally designed for Python 3.0 but that were back-ported to Python 2.6. The corresponding sections in Nouveautés de Python 2.6 should be consulted for longer descriptions.

PEP 343: The “with” statement. The with statement is now a standard feature and no longer needs to be imported from the __future__. Also check out Écrire des gestionnaires de contexte and Le module contextlib.

PEP 366: Explicit Relative Imports From a Main Module. This enhances the usefulness of the -m option when the referenced module lives in a package.

PEP 370: Per-user site-packages Directory.

PEP 371: The multiprocessing Package.

PEP 3101: Advanced String Formatting. Note: the 2.6 description mentions the format() method for both 8-bit and Unicode strings. In 3.0, only the str type (text strings with Unicode support) supports this method; the bytes type does not. The plan is to eventually make this the only API for string formatting, and to start deprecating the % operator in Python 3.1.

PEP 3105: print As a Function. This is now a standard feature and no longer needs to be imported from __future__. More details were given above.

PEP 3110: Exception-Handling Changes. The except exc as var syntax is now standard and except exc, var is no longer supported. (Of course, the as var part is still optional.)

PEP 3112: Byte Literals. The b"..." string literal notation (and its variants like b'...', b"""...""", and br"...") now produces a literal of type bytes.

PEP 3116: New I/O Library. The io module is now the standard way of doing file I/O. The built-in open() function is now an alias for io.open() and has additional keyword arguments encoding, errors, newline and closefd. Also note that an invalid mode argument now raises ValueError, not IOError. The binary file object underlying a text file object can be accessed as f.buffer (but beware that the text object maintains a buffer of itself in order to speed up the encoding and decoding operations).

PEP 3118: Revised Buffer Protocol. The old builtin buffer() is now really gone; the new builtin memoryview() provides (mostly) similar functionality.

PEP 3119: Abstract Base Classes. The abc module and the ABCs defined in the collections module plays a somewhat more prominent role in the language now, and built-in collection types like dict and list conform to the collections.MutableMapping and collections.MutableSequence ABCs, respectively.

PEP 3127: Integer Literal Support and Syntax. As mentioned above, the new octal literal notation is the only one supported, and binary literals have been added.

PEP 3129: Class Decorators.

PEP 3141: A Type Hierarchy for Numbers. The numbers module is another new use of ABCs, defining Python’s « numeric tower ». Also note the new fractions module which implements numbers.Rational.

Library Changes

Due to time constraints, this document does not exhaustively cover the very extensive changes to the standard library. PEP 3108 [https://www.python.org/dev/peps/pep-3108] is the reference for the major changes to the library. Here’s a capsule review:

Many old modules were removed. Some, like gopherlib (no longer used) and md5 (replaced by hashlib), were already deprecated by PEP 4 [https://www.python.org/dev/peps/pep-0004]. Others were removed as a result of the removal of support for various platforms such as Irix, BeOS and Mac OS 9 (see PEP 11 [https://www.python.org/dev/peps/pep-0011]). Some modules were also selected for removal in Python 3.0 due to lack of use or because a better replacement exists. See PEP 3108 [https://www.python.org/dev/peps/pep-3108] for an exhaustive list.

The bsddb3 package was removed because its presence in the core standard library has proved over time to be a particular burden for the core developers due to testing instability and Berkeley DB’s release schedule. However, the package is alive and well, externally maintained at https://www.jcea.es/programacion/pybsddb.htm.

Some modules were renamed because their old name disobeyed PEP 8 [https://www.python.org/dev/peps/pep-0008], or for various other reasons. Here’s the list:

Old Name

New Name

_winreg

winreg

ConfigParser

configparser

copy_reg

copyreg

Queue

queue

SocketServer

socketserver

markupbase

_markupbase

repr

reprlib

test.test_support

test.support

A common pattern in Python 2.x is to have one version of a module implemented in pure Python, with an optional accelerated version implemented as a C extension; for example, pickle and cPickle. This places the burden of importing the accelerated version and falling back on the pure Python version on each user of these modules. In Python 3.0, the accelerated versions are considered implementation details of the pure Python versions. Users should always import the standard version, which attempts to import the accelerated version and falls back to the pure Python version. The pickle / cPickle pair received this treatment. The profile module is on the list for 3.1. The StringIO module has been turned into a class in the io module.

Some related modules have been grouped into packages, and usually the submodule names have been simplified. The resulting new packages are:

dbm (anydbm, dbhash, dbm, dumbdbm, gdbm, whichdb).

html (HTMLParser, htmlentitydefs).

http (httplib, BaseHTTPServer, CGIHTTPServer, SimpleHTTPServer, Cookie, cookielib).

tkinter (all Tkinter-related modules except turtle). The target audience of turtle doesn’t really care about tkinter. Also note that as of Python 2.6, the functionality of turtle has been greatly enhanced.

urllib (urllib, urllib2, urlparse, robotparse).

xmlrpc (xmlrpclib, DocXMLRPCServer, SimpleXMLRPCServer).

Some other changes to standard library modules, not covered by PEP 3108 [https://www.python.org/dev/peps/pep-3108]:

Killed sets. Use the built-in set() class.

Cleanup of the sys module: removed sys.exitfunc(), sys.exc_clear(), sys.exc_type, sys.exc_value, sys.exc_traceback. (Note that sys.last_type etc. remain.)

Cleanup of the array.array type: the read() and write() methods are gone; use fromfile() and tofile() instead. Also, the 'c' typecode for array is gone – use either 'b' for bytes or 'u' for Unicode characters.

Cleanup of the operator module: removed sequenceIncludes() and isCallable().

Cleanup of the thread module: acquire_lock() and release_lock() are gone; use acquire() and release() instead.

Cleanup of the random module: removed the jumpahead() API.

The new module is gone.

The functions os.tmpnam(), os.tempnam() and os.tmpfile() have been removed in favor of the tempfile module.

The tokenize module has been changed to work with bytes. The main entry point is now tokenize.tokenize(), instead of generate_tokens.

string.letters and its friends (string.lowercase and string.uppercase) are gone. Use string.ascii_letters etc. instead. (The reason for the removal is that string.letters and friends had locale-specific behavior, which is a bad idea for such attractively-named global « constants ».)

Renamed module __builtin__ to builtins (removing the underscores, adding an “s”). The __builtins__ variable found in most global namespaces is unchanged. To modify a builtin, you should use builtins, not __builtins__!

PEP 3101 [https://www.python.org/dev/peps/pep-3101]: A New Approach To String Formatting

A new system for built-in string formatting operations replaces the % string formatting operator. (However, the % operator is still supported; it will be deprecated in Python 3.1 and removed from the language at some later time.) Read PEP 3101 [https://www.python.org/dev/peps/pep-3101] for the full scoop.

Changes To Exceptions

The APIs for raising and catching exception have been cleaned up and new powerful features added:

PEP 352 [https://www.python.org/dev/peps/pep-0352]: All exceptions must be derived (directly or indirectly) from BaseException. This is the root of the exception hierarchy. This is not new as a recommendation, but the requirement to inherit from BaseException is new. (Python 2.6 still allowed classic classes to be raised, and placed no restriction on what you can catch.) As a consequence, string exceptions are finally truly and utterly dead.

Almost all exceptions should actually derive from Exception; BaseException should only be used as a base class for exceptions that should only be handled at the top level, such as SystemExit or KeyboardInterrupt. The recommended idiom for handling all exceptions except for this latter category is to use except Exception.

StandardError was removed.

Exceptions no longer behave as sequences. Use the args attribute instead.

PEP 3109 [https://www.python.org/dev/peps/pep-3109]: Raising exceptions. You must now use raise Exception(args) instead of raise Exception, args. Additionally, you can no longer explicitly specify a traceback; instead, if you have to do this, you can assign directly to the __traceback__ attribute (see below).

PEP 3110 [https://www.python.org/dev/peps/pep-3110]: Catching exceptions. You must now use except SomeException as variable instead of except SomeException, variable. Moreover, the variable is explicitly deleted when the except block is left.

PEP 3134 [https://www.python.org/dev/peps/pep-3134]: Exception chaining. There are two cases: implicit chaining and explicit chaining. Implicit chaining happens when an exception is raised in an except or finally handler block. This usually happens due to a bug in the handler block; we call this a secondary exception. In this case, the original exception (that was being handled) is saved as the __context__ attribute of the secondary exception. Explicit chaining is invoked with this syntax:

raise SecondaryException() from primary_exception

(where primary_exception is any expression that produces an exception object, probably an exception that was previously caught). In this case, the primary exception is stored on the __cause__ attribute of the secondary exception. The traceback printed when an unhandled exception occurs walks the chain of __cause__ and __context__ attributes and prints a separate traceback for each component of the chain, with the primary exception at the top. (Java users may recognize this behavior.)

PEP 3134 [https://www.python.org/dev/peps/pep-3134]: Exception objects now store their traceback as the __traceback__ attribute. This means that an exception object now contains all the information pertaining to an exception, and there are fewer reasons to use sys.exc_info() (though the latter is not removed).

A few exception messages are improved when Windows fails to load an extension module. For example, error code 193 is now %1 is not a valid Win32 application. Strings now deal with non-English locales.

Miscellaneous Other Changes

Operators And Special Methods

!= now returns the opposite of ==, unless == returns NotImplemented.

The concept of « unbound methods » has been removed from the language. When referencing a method as a class attribute, you now get a plain function object.

__getslice__(), __setslice__() and __delslice__() were killed. The syntax a[i:j] now translates to a.__getitem__(slice(i, j)) (or __setitem__() or __delitem__(), when used as an assignment or deletion target, respectively).

PEP 3114 [https://www.python.org/dev/peps/pep-3114]: the standard next() method has been renamed to __next__().

The __oct__() and __hex__() special methods are removed – oct() and hex() use __index__() now to convert the argument to an integer.

Removed support for __members__ and __methods__.

The function attributes named func_X have been renamed to use the __X__ form, freeing up these names in the function attribute namespace for user-defined attributes. To wit, func_closure, func_code, func_defaults, func_dict, func_doc, func_globals, func_name were renamed to __closure__, __code__, __defaults__, __dict__, __doc__, __globals__, __name__, respectively.

__nonzero__() is now __bool__().

Builtins

PEP 3135 [https://www.python.org/dev/peps/pep-3135]: New super(). You can now invoke super() without arguments and (assuming this is in a regular instance method defined inside a class statement) the right class and instance will automatically be chosen. With arguments, the behavior of super() is unchanged.

PEP 3111 [https://www.python.org/dev/peps/pep-3111]: raw_input() was renamed to input(). That is, the new input() function reads a line from sys.stdin and returns it with the trailing newline stripped. It raises EOFError if the input is terminated prematurely. To get the old behavior of input(), use eval(input()).

A new built-in function next() was added to call the __next__() method on an object.

The round() function rounding strategy and return type have changed. Exact halfway cases are now rounded to the nearest even result instead of away from zero. (For example, round(2.5) now returns 2 rather than 3.) round(x[, n]) now delegates to x.__round__([n]) instead of always returning a float. It generally returns an integer when called with a single argument and a value of the same type as x when called with two arguments.

Moved intern() to sys.intern().

Removed: apply(). Instead of apply(f, args) use f(*args).

Removed callable(). Instead of callable(f) you can use isinstance(f, collections.Callable). The operator.isCallable() function is also gone.

Removed coerce(). This function no longer serves a purpose now that classic classes are gone.

Removed execfile(). Instead of execfile(fn) use exec(open(fn).read()).

Removed the file type. Use open(). There are now several different kinds of streams that open can return in the io module.

Removed reduce(). Use functools.reduce() if you really need it; however, 99 percent of the time an explicit for loop is more readable.

Removed reload(). Use imp.reload().

Removed. dict.has_key() – use the in operator instead.

Build and C API Changes

Due to time constraints, here is a very incomplete list of changes to the C API.

Support for several platforms was dropped, including but not limited to Mac OS 9, BeOS, RISCOS, Irix, and Tru64.

PEP 3118 [https://www.python.org/dev/peps/pep-3118]: New Buffer API.

PEP 3121 [https://www.python.org/dev/peps/pep-3121]: Extension Module Initialization & Finalization.

PEP 3123 [https://www.python.org/dev/peps/pep-3123]: Making PyObject_HEAD conform to standard C.

No more C API support for restricted execution.

PyNumber_Coerce(), PyNumber_CoerceEx(), PyMember_Get(), and PyMember_Set() C APIs are removed.

New C API PyImport_ImportModuleNoBlock(), works like PyImport_ImportModule() but won’t block on the import lock (returning an error instead).

Renamed the boolean conversion C-level slot and method: nb_nonzero is now nb_bool.

Removed METH_OLDARGS and WITH_CYCLE_GC from the C API.

Performances

The net result of the 3.0 generalizations is that Python 3.0 runs the pystone benchmark around 10% slower than Python 2.5. Most likely the biggest cause is the removal of special-casing for small integers. There’s room for improvement, but it will happen after 3.0 is released!

Portage vers Python 3.0

For porting existing Python 2.5 or 2.6 source code to Python 3.0, the best strategy is the following:

(Prerequisite:) Start with excellent test coverage.

Port to Python 2.6. This should be no more work than the average port from Python 2.x to Python 2.(x+1). Make sure all your tests pass.

(Still using 2.6:) Turn on the -3 command line switch. This enables warnings about features that will be removed (or change) in 3.0. Run your test suite again, and fix code that you get warnings about until there are no warnings left, and all your tests still pass.

Run the 2to3 source-to-source translator over your source code tree. (See 2to3 — Traduction automatique de code en Python 2 vers Python 3 for more on this tool.) Run the result of the translation under Python 3.0. Manually fix up any remaining issues, fixing problems until all tests pass again.

It is not recommended to try to write source code that runs unchanged under both Python 2.6 and 3.0; you’d have to use a very contorted coding style, e.g. avoiding print statements, metaclasses, and much more. If you are maintaining a library that needs to support both Python 2.6 and Python 3.0, the best approach is to modify step 3 above by editing the 2.6 version of the source code and running the 2to3 translator again, rather than editing the 3.0 version of the source code.

For porting C extensions to Python 3.0, please see Portage des modules d’extension vers Python 3.

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Nouveautés de Python 2.7

Auteur

A.M. Kuchling (amk at amk.ca)

This article explains the new features in Python 2.7. Python 2.7 was released on July 3, 2010.

Numeric handling has been improved in many ways, for both floating-point numbers and for the Decimal class. There are some useful additions to the standard library, such as a greatly enhanced unittest module, the argparse module for parsing command-line options, convenient OrderedDict and Counter classes in the collections module, and many other improvements.

Python 2.7 is planned to be the last of the 2.x releases, so we worked on making it a good release for the long term. To help with porting to Python 3, several new features from the Python 3.x series have been included in 2.7.

This article doesn’t attempt to provide a complete specification of the new features, but instead provides a convenient overview. For full details, you should refer to the documentation for Python 2.7 at https://docs.python.org. If you want to understand the rationale for the design and implementation, refer to the PEP for a particular new feature or the issue on https://bugs.python.org in which a change was discussed. Whenever possible, « What’s New in Python » links to the bug/patch item for each change.

The Future for Python 2.x

Python 2.7 is the last major release in the 2.x series, as the Python maintainers have shifted the focus of their new feature development efforts to the Python 3.x series. This means that while Python 2 continues to receive bug fixes, and to be updated to build correctly on new hardware and versions of supported operated systems, there will be no new full feature releases for the language or standard library.

However, while there is a large common subset between Python 2.7 and Python 3, and many of the changes involved in migrating to that common subset, or directly to Python 3, can be safely automated, some other changes (notably those associated with Unicode handling) may require careful consideration, and preferably robust automated regression test suites, to migrate effectively.

This means that Python 2.7 will remain in place for a long time, providing a stable and supported base platform for production systems that have not yet been ported to Python 3. The full expected lifecycle of the Python 2.7 series is detailed in PEP 373 [https://www.python.org/dev/peps/pep-0373].

Some key consequences of the long-term significance of 2.7 are:

As noted above, the 2.7 release has a much longer period of maintenance when compared to earlier 2.x versions. Python 2.7 is currently expected to remain supported by the core development team (receiving security updates and other bug fixes) until at least 2020 (10 years after its initial release, compared to the more typical support period of 18–24 months).

As the Python 2.7 standard library ages, making effective use of the Python Package Index (either directly or via a redistributor) becomes more important for Python 2 users. In addition to a wide variety of third party packages for various tasks, the available packages include backports of new modules and features from the Python 3 standard library that are compatible with Python 2, as well as various tools and libraries that can make it easier to migrate to Python 3. The Python Packaging User Guide [https://packaging.python.org] provides guidance on downloading and installing software from the Python Package Index.

While the preferred approach to enhancing Python 2 is now the publication of new packages on the Python Package Index, this approach doesn’t necessarily work in all cases, especially those related to network security. In exceptional cases that cannot be handled adequately by publishing new or updated packages on PyPI, the Python Enhancement Proposal process may be used to make the case for adding new features directly to the Python 2 standard library. Any such additions, and the maintenance releases where they were added, will be noted in the New Features Added to Python 2.7 Maintenance Releases section below.

For projects wishing to migrate from Python 2 to Python 3, or for library and framework developers wishing to support users on both Python 2 and Python 3, there are a variety of tools and guides available to help decide on a suitable approach and manage some of the technical details involved. The recommended starting point is the Portage de code Python 2 vers Python 3 HOWTO guide.

Changes to the Handling of Deprecation Warnings

For Python 2.7, a policy decision was made to silence warnings only of interest to developers by default. DeprecationWarning and its descendants are now ignored unless otherwise requested, preventing users from seeing warnings triggered by an application. This change was also made in the branch that became Python 3.2. (Discussed on stdlib-sig and carried out in bpo-7319 [https://bugs.python.org/issue7319].)

In previous releases, DeprecationWarning messages were enabled by default, providing Python developers with a clear indication of where their code may break in a future major version of Python.

However, there are increasingly many users of Python-based applications who are not directly involved in the development of those applications. DeprecationWarning messages are irrelevant to such users, making them worry about an application that’s actually working correctly and burdening application developers with responding to these concerns.

You can re-enable display of DeprecationWarning messages by running Python with the -Wdefault (short form: -Wd) switch, or by setting the PYTHONWARNINGS environment variable to "default" (or "d") before running Python. Python code can also re-enable them by calling warnings.simplefilter('default').

The unittest module also automatically reenables deprecation warnings when running tests.

Python 3.1 Features

Much as Python 2.6 incorporated features from Python 3.0, version 2.7 incorporates some of the new features in Python 3.1. The 2.x series continues to provide tools for migrating to the 3.x series.

A partial list of 3.1 features that were backported to 2.7:

The syntax for set literals ({1,2,3} is a mutable set).

Dictionary and set comprehensions ({i: i*2 for i in range(3)}).

Multiple context managers in a single with statement.

A new version of the io library, rewritten in C for performance.

The ordered-dictionary type described in PEP 372: Adding an Ordered Dictionary to collections.

The new "," format specifier described in PEP 378: Format Specifier for Thousands Separator.

The memoryview object.

A small subset of the importlib module, described below.

The repr() of a float x is shorter in many cases: it’s now based on the shortest decimal string that’s guaranteed to round back to x. As in previous versions of Python, it’s guaranteed that float(repr(x)) recovers x.

Float-to-string and string-to-float conversions are correctly rounded. The round() function is also now correctly rounded.

The PyCapsule type, used to provide a C API for extension modules.

The PyLong_AsLongAndOverflow() C API function.

Other new Python3-mode warnings include:

operator.isCallable() and operator.sequenceIncludes(), which are not supported in 3.x, now trigger warnings.

The -3 switch now automatically enables the -Qwarn switch that causes warnings about using classic division with integers and long integers.

PEP 372: Adding an Ordered Dictionary to collections

Regular Python dictionaries iterate over key/value pairs in arbitrary order. Over the years, a number of authors have written alternative implementations that remember the order that the keys were originally inserted. Based on the experiences from those implementations, 2.7 introduces a new OrderedDict class in the collections module.

The OrderedDict API provides the same interface as regular dictionaries but iterates over keys and values in a guaranteed order depending on when a key was first inserted:

>>> from collections import OrderedDict
>>> d = OrderedDict([('first', 1),
...                  ('second', 2),
...                  ('third', 3)])
>>> d.items()
[('first', 1), ('second', 2), ('third', 3)]

If a new entry overwrites an existing entry, the original insertion position is left unchanged:

>>> d['second'] = 4
>>> d.items()
[('first', 1), ('second', 4), ('third', 3)]

Deleting an entry and reinserting it will move it to the end:

>>> del d['second']
>>> d['second'] = 5
>>> d.items()
[('first', 1), ('third', 3), ('second', 5)]

The popitem() method has an optional last argument that defaults to True. If last is true, the most recently added key is returned and removed; if it’s false, the oldest key is selected:

>>> od = OrderedDict([(x,0) for x in range(20)])
>>> od.popitem()
(19, 0)
>>> od.popitem()
(18, 0)
>>> od.popitem(last=False)
(0, 0)
>>> od.popitem(last=False)
(1, 0)

Comparing two ordered dictionaries checks both the keys and values, and requires that the insertion order was the same:

>>> od1 = OrderedDict([('first', 1),
...                    ('second', 2),
...                    ('third', 3)])
>>> od2 = OrderedDict([('third', 3),
...                    ('first', 1),
...                    ('second', 2)])
>>> od1 == od2
False
>>> # Move 'third' key to the end
>>> del od2['third']; od2['third'] = 3
>>> od1 == od2
True

Comparing an OrderedDict with a regular dictionary ignores the insertion order and just compares the keys and values.

How does the OrderedDict work? It maintains a doubly-linked list of keys, appending new keys to the list as they’re inserted. A secondary dictionary maps keys to their corresponding list node, so deletion doesn’t have to traverse the entire linked list and therefore remains O(1).

The standard library now supports use of ordered dictionaries in several modules.

The ConfigParser module uses them by default, meaning that configuration files can now be read, modified, and then written back in their original order.

The _asdict() method for collections.namedtuple() now returns an ordered dictionary with the values appearing in the same order as the underlying tuple indices.

The json module’s JSONDecoder class constructor was extended with an object_pairs_hook parameter to allow OrderedDict instances to be built by the decoder. Support was also added for third-party tools like PyYAML [http://pyyaml.org/].

Voir aussi

PEP 372 [https://www.python.org/dev/peps/pep-0372] - Adding an ordered dictionary to collections

PEP written by Armin Ronacher and Raymond Hettinger; implemented by Raymond Hettinger.

PEP 378: Format Specifier for Thousands Separator

To make program output more readable, it can be useful to add separators to large numbers, rendering them as 18,446,744,073,709,551,616 instead of 18446744073709551616.

The fully general solution for doing this is the locale module, which can use different separators (« , » in North America, « . » in Europe) and different grouping sizes, but locale is complicated to use and unsuitable for multi-threaded applications where different threads are producing output for different locales.

Therefore, a simple comma-grouping mechanism has been added to the mini-language used by the str.format() method. When formatting a floating-point number, simply include a comma between the width and the precision:

>>> '{:20,.2f}'.format(18446744073709551616.0)
'18,446,744,073,709,551,616.00'

When formatting an integer, include the comma after the width:

>>> '{:20,d}'.format(18446744073709551616)
'18,446,744,073,709,551,616'

This mechanism is not adaptable at all; commas are always used as the separator and the grouping is always into three-digit groups. The comma-formatting mechanism isn’t as general as the locale module, but it’s easier to use.

Voir aussi

PEP 378 [https://www.python.org/dev/peps/pep-0378] - Format Specifier for Thousands Separator

PEP written by Raymond Hettinger; implemented by Eric Smith.

PEP 389: The argparse Module for Parsing Command Lines

The argparse module for parsing command-line arguments was added as a more powerful replacement for the optparse module.

This means Python now supports three different modules for parsing command-line arguments: getopt, optparse, and argparse. The getopt module closely resembles the C library’s getopt() function, so it remains useful if you’re writing a Python prototype that will eventually be rewritten in C. optparse becomes redundant, but there are no plans to remove it because there are many scripts still using it, and there’s no automated way to update these scripts. (Making the argparse API consistent with optparse’s interface was discussed but rejected as too messy and difficult.)

In short, if you’re writing a new script and don’t need to worry about compatibility with earlier versions of Python, use argparse instead of optparse.

Here’s an example:

import argparse

parser = argparse.ArgumentParser(description='Command-line example.')

# Add optional switches
parser.add_argument('-v', action='store_true', dest='is_verbose',
                    help='produce verbose output')
parser.add_argument('-o', action='store', dest='output',
                    metavar='FILE',
                    help='direct output to FILE instead of stdout')
parser.add_argument('-C', action='store', type=int, dest='context',
                    metavar='NUM', default=0,
                    help='display NUM lines of added context')

# Allow any number of additional arguments.
parser.add_argument(nargs='*', action='store', dest='inputs',
                    help='input filenames (default is stdin)')

args = parser.parse_args()
print args.__dict__

Unless you override it, -h and --help switches are automatically added, and produce neatly formatted output:

-> ./python.exe argparse-example.py --help
usage: argparse-example.py [-h] [-v] [-o FILE] [-C NUM] [inputs [inputs ...]]

Command-line example.

positional arguments:
  inputs      input filenames (default is stdin)

optional arguments:
  -h, --help  show this help message and exit
  -v          produce verbose output
  -o FILE     direct output to FILE instead of stdout
  -C NUM      display NUM lines of added context

As with optparse, the command-line switches and arguments are returned as an object with attributes named by the dest parameters:

-> ./python.exe argparse-example.py -v
{'output': None,
 'is_verbose': True,
 'context': 0,
 'inputs': []}

-> ./python.exe argparse-example.py -v -o /tmp/output -C 4 file1 file2
{'output': '/tmp/output',
 'is_verbose': True,
 'context': 4,
 'inputs': ['file1', 'file2']}

argparse has much fancier validation than optparse; you can specify an exact number of arguments as an integer, 0 or more arguments by passing '*', 1 or more by passing '+', or an optional argument with '?'. A top-level parser can contain sub-parsers to define subcommands that have different sets of switches, as in svn commit, svn checkout, etc. You can specify an argument’s type as FileType, which will automatically open files for you and understands that '-' means standard input or output.

Voir aussi

Documentation du module argparse

The documentation page of the argparse module.

Mettre à jour du code optparse

Part of the Python documentation, describing how to convert code that uses optparse.

PEP 389 [https://www.python.org/dev/peps/pep-0389] - argparse - New Command Line Parsing Module

PEP written and implemented by Steven Bethard.

PEP 391: Dictionary-Based Configuration For Logging

The logging module is very flexible; applications can define a tree of logging subsystems, and each logger in this tree can filter out certain messages, format them differently, and direct messages to a varying number of handlers.

All this flexibility can require a lot of configuration. You can write Python statements to create objects and set their properties, but a complex set-up requires verbose but boring code. logging also supports a fileConfig() function that parses a file, but the file format doesn’t support configuring filters, and it’s messier to generate programmatically.

Python 2.7 adds a dictConfig() function that uses a dictionary to configure logging. There are many ways to produce a dictionary from different sources: construct one with code; parse a file containing JSON; or use a YAML parsing library if one is installed. For more information see Configuration functions.

The following example configures two loggers, the root logger and a logger named « network ». Messages sent to the root logger will be sent to the system log using the syslog protocol, and messages to the « network » logger will be written to a network.log file that will be rotated once the log reaches 1MB.

import logging
import logging.config

configdict = {
 'version': 1,    # Configuration schema in use; must be 1 for now
 'formatters': {
     'standard': {
         'format': ('%(asctime)s %(name)-15s '
                    '%(levelname)-8s %(message)s')}},

 'handlers': {'netlog': {'backupCount': 10,
                     'class': 'logging.handlers.RotatingFileHandler',
                     'filename': '/logs/network.log',
                     'formatter': 'standard',
                     'level': 'INFO',
                     'maxBytes': 1000000},
              'syslog': {'class': 'logging.handlers.SysLogHandler',
                         'formatter': 'standard',
                         'level': 'ERROR'}},

 # Specify all the subordinate loggers
 'loggers': {
             'network': {
                         'handlers': ['netlog']
             }
 },
 # Specify properties of the root logger
 'root': {
          'handlers': ['syslog']
 },
}

# Set up configuration
logging.config.dictConfig(configdict)

# As an example, log two error messages
logger = logging.getLogger('/')
logger.error('Database not found')

netlogger = logging.getLogger('network')
netlogger.error('Connection failed')

Three smaller enhancements to the logging module, all implemented by Vinay Sajip, are:

The SysLogHandler class now supports syslogging over TCP. The constructor has a socktype parameter giving the type of socket to use, either socket.SOCK_DGRAM for UDP or socket.SOCK_STREAM for TCP. The default protocol remains UDP.

Logger instances gained a getChild() method that retrieves a descendant logger using a relative path. For example, once you retrieve a logger by doing log = getLogger('app'), calling log.getChild('network.listen') is equivalent to getLogger('app.network.listen').

The LoggerAdapter class gained an isEnabledFor() method that takes a level and returns whether the underlying logger would process a message of that level of importance.

Voir aussi

PEP 391 [https://www.python.org/dev/peps/pep-0391] - Dictionary-Based Configuration For Logging

PEP written and implemented by Vinay Sajip.

PEP 3106: Dictionary Views

The dictionary methods keys(), values(), and items() are different in Python 3.x. They return an object called a view instead of a fully materialized list.

It’s not possible to change the return values of keys(), values(), and items() in Python 2.7 because too much code would break. Instead the 3.x versions were added under the new names viewkeys(), viewvalues(), and viewitems().

>>> d = dict((i*10, chr(65+i)) for i in range(26))
>>> d
{0: 'A', 130: 'N', 10: 'B', 140: 'O', 20: ..., 250: 'Z'}
>>> d.viewkeys()
dict_keys([0, 130, 10, 140, 20, 150, 30, ..., 250])

Views can be iterated over, but the key and item views also behave like sets. The & operator performs intersection, and | performs a union:

>>> d1 = dict((i*10, chr(65+i)) for i in range(26))
>>> d2 = dict((i**.5, i) for i in range(1000))
>>> d1.viewkeys() & d2.viewkeys()
set([0.0, 10.0, 20.0, 30.0])
>>> d1.viewkeys() | range(0, 30)
set([0, 1, 130, 3, 4, 5, 6, ..., 120, 250])

The view keeps track of the dictionary and its contents change as the dictionary is modified:

>>> vk = d.viewkeys()
>>> vk
dict_keys([0, 130, 10, ..., 250])
>>> d[260] = '&'
>>> vk
dict_keys([0, 130, 260, 10, ..., 250])

However, note that you can’t add or remove keys while you’re iterating over the view:

>>> for k in vk:
...     d[k*2] = k
...
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
RuntimeError: dictionary changed size during iteration

You can use the view methods in Python 2.x code, and the 2to3 converter will change them to the standard keys(), values(), and items() methods.

Voir aussi

PEP 3106 [https://www.python.org/dev/peps/pep-3106] - Revamping dict.keys(), .values() and .items()

PEP written by Guido van Rossum. Backported to 2.7 by Alexandre Vassalotti; bpo-1967 [https://bugs.python.org/issue1967].

PEP 3137: The memoryview Object

The memoryview object provides a view of another object’s memory content that matches the bytes type’s interface.

>>> import string
>>> m = memoryview(string.letters)
>>> m
<memory at 0x37f850>
>>> len(m)           # Returns length of underlying object
52
>>> m[0], m[25], m[26]   # Indexing returns one byte
('a', 'z', 'A')
>>> m2 = m[0:26]         # Slicing returns another memoryview
>>> m2
<memory at 0x37f080>

The content of the view can be converted to a string of bytes or a list of integers:

>>> m2.tobytes()
'abcdefghijklmnopqrstuvwxyz'
>>> m2.tolist()
[97, 98, 99, 100, 101, 102, 103, ... 121, 122]
>>>

memoryview objects allow modifying the underlying object if it’s a mutable object.

>>> m2[0] = 75
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: cannot modify read-only memory
>>> b = bytearray(string.letters)  # Creating a mutable object
>>> b
bytearray(b'abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ')
>>> mb = memoryview(b)
>>> mb[0] = '*'         # Assign to view, changing the bytearray.
>>> b[0:5]              # The bytearray has been changed.
bytearray(b'*bcde')
>>>

Voir aussi

PEP 3137 [https://www.python.org/dev/peps/pep-3137] - Immutable Bytes and Mutable Buffer

PEP written by Guido van Rossum. Implemented by Travis Oliphant, Antoine Pitrou and others. Backported to 2.7 by Antoine Pitrou; bpo-2396 [https://bugs.python.org/issue2396].

Other Language Changes

Some smaller changes made to the core Python language are:

The syntax for set literals has been backported from Python 3.x. Curly brackets are used to surround the contents of the resulting mutable set; set literals are distinguished from dictionaries by not containing colons and values. {} continues to represent an empty dictionary; use set() for an empty set.

>>> {1, 2, 3, 4, 5}
set([1, 2, 3, 4, 5])
>>> set() # empty set
set([])
>>> {}    # empty dict
{}

Backported by Alexandre Vassalotti; bpo-2335 [https://bugs.python.org/issue2335].

Dictionary and set comprehensions are another feature backported from 3.x, generalizing list/generator comprehensions to use the literal syntax for sets and dictionaries.

>>> {x: x*x for x in range(6)}
{0: 0, 1: 1, 2: 4, 3: 9, 4: 16, 5: 25}
>>> {('a'*x) for x in range(6)}
set(['', 'a', 'aa', 'aaa', 'aaaa', 'aaaaa'])

Backported by Alexandre Vassalotti; bpo-2333 [https://bugs.python.org/issue2333].

The with statement can now use multiple context managers in one statement. Context managers are processed from left to right and each one is treated as beginning a new with statement. This means that:

with A() as a, B() as b:
    ... suite of statements ...

est équivalente à :

with A() as a:
    with B() as b:
        ... suite of statements ...

The contextlib.nested() function provides a very similar function, so it’s no longer necessary and has been deprecated.

(Proposed in https://codereview.appspot.com/53094; implemented by Georg Brandl.)

Conversions between floating-point numbers and strings are now correctly rounded on most platforms. These conversions occur in many different places: str() on floats and complex numbers; the float and complex constructors; numeric formatting; serializing and deserializing floats and complex numbers using the marshal, pickle and json modules; parsing of float and imaginary literals in Python code; and Decimal-to-float conversion.

Related to this, the repr() of a floating-point number x now returns a result based on the shortest decimal string that’s guaranteed to round back to x under correct rounding (with round-half-to-even rounding mode). Previously it gave a string based on rounding x to 17 decimal digits.

The rounding library responsible for this improvement works on Windows and on Unix platforms using the gcc, icc, or suncc compilers. There may be a small number of platforms where correct operation of this code cannot be guaranteed, so the code is not used on such systems. You can find out which code is being used by checking sys.float_repr_style, which will be short if the new code is in use and legacy if it isn’t.

Implemented by Eric Smith and Mark Dickinson, using David Gay’s dtoa.c library; bpo-7117 [https://bugs.python.org/issue7117].

Conversions from long integers and regular integers to floating point now round differently, returning the floating-point number closest to the number. This doesn’t matter for small integers that can be converted exactly, but for large numbers that will unavoidably lose precision, Python 2.7 now approximates more closely. For example, Python 2.6 computed the following:

>>> n = 295147905179352891391
>>> float(n)
2.9514790517935283e+20
>>> n - long(float(n))
65535L

Python 2.7’s floating-point result is larger, but much closer to the true value:

>>> n = 295147905179352891391
>>> float(n)
2.9514790517935289e+20
>>> n - long(float(n))
-1L

(Implemented by Mark Dickinson; bpo-3166 [https://bugs.python.org/issue3166].)

Integer division is also more accurate in its rounding behaviours. (Also implemented by Mark Dickinson; bpo-1811 [https://bugs.python.org/issue1811].)

Implicit coercion for complex numbers has been removed; the interpreter will no longer ever attempt to call a __coerce__() method on complex objects. (Removed by Meador Inge and Mark Dickinson; bpo-5211 [https://bugs.python.org/issue5211].)

The str.format() method now supports automatic numbering of the replacement fields. This makes using str.format() more closely resemble using %s formatting:

>>> '{}:{}:{}'.format(2009, 04, 'Sunday')
'2009:4:Sunday'
>>> '{}:{}:{day}'.format(2009, 4, day='Sunday')
'2009:4:Sunday'

The auto-numbering takes the fields from left to right, so the first {...} specifier will use the first argument to str.format(), the next specifier will use the next argument, and so on. You can’t mix auto-numbering and explicit numbering – either number all of your specifier fields or none of them – but you can mix auto-numbering and named fields, as in the second example above. (Contributed by Eric Smith; bpo-5237 [https://bugs.python.org/issue5237].)

Complex numbers now correctly support usage with format(), and default to being right-aligned. Specifying a precision or comma-separation applies to both the real and imaginary parts of the number, but a specified field width and alignment is applied to the whole of the resulting 1.5+3j output. (Contributed by Eric Smith; bpo-1588 [https://bugs.python.org/issue1588] and bpo-7988 [https://bugs.python.org/issue7988].)

The “F” format code now always formats its output using uppercase characters, so it will now produce “INF” and “NAN”. (Contributed by Eric Smith; bpo-3382 [https://bugs.python.org/issue3382].)

A low-level change: the object.__format__() method now triggers a PendingDeprecationWarning if it’s passed a format string, because the __format__() method for object converts the object to a string representation and formats that. Previously the method silently applied the format string to the string representation, but that could hide mistakes in Python code. If you’re supplying formatting information such as an alignment or precision, presumably you’re expecting the formatting to be applied in some object-specific way. (Fixed by Eric Smith; bpo-7994 [https://bugs.python.org/issue7994].)

The int() and long() types gained a bit_length method that returns the number of bits necessary to represent its argument in binary:

>>> n = 37
>>> bin(n)
'0b100101'
>>> n.bit_length()
6
>>> n = 2**123-1
>>> n.bit_length()
123
>>> (n+1).bit_length()
124

(Contributed by Fredrik Johansson and Victor Stinner; bpo-3439 [https://bugs.python.org/issue3439].)

The import statement will no longer try an absolute import if a relative import (e.g. from .os import sep) fails. This fixes a bug, but could possibly break certain import statements that were only working by accident. (Fixed by Meador Inge; bpo-7902 [https://bugs.python.org/issue7902].)

It’s now possible for a subclass of the built-in unicode type to override the __unicode__() method. (Implemented by Victor Stinner; bpo-1583863 [https://bugs.python.org/issue1583863].)

The bytearray type’s translate() method now accepts None as its first argument. (Fixed by Georg Brandl; bpo-4759 [https://bugs.python.org/issue4759].)

When using @classmethod and @staticmethod to wrap methods as class or static methods, the wrapper object now exposes the wrapped function as their __func__ attribute. (Contributed by Amaury Forgeot d’Arc, after a suggestion by George Sakkis; bpo-5982 [https://bugs.python.org/issue5982].)

When a restricted set of attributes were set using __slots__, deleting an unset attribute would not raise AttributeError as you would expect. Fixed by Benjamin Peterson; bpo-7604 [https://bugs.python.org/issue7604].)

Two new encodings are now supported: « cp720 », used primarily for Arabic text; and « cp858 », a variant of CP 850 that adds the euro symbol. (CP720 contributed by Alexander Belchenko and Amaury Forgeot d’Arc in bpo-1616979 [https://bugs.python.org/issue1616979]; CP858 contributed by Tim Hatch in bpo-8016 [https://bugs.python.org/issue8016].)

The file object will now set the filename attribute on the IOError exception when trying to open a directory on POSIX platforms (noted by Jan Kaliszewski; bpo-4764 [https://bugs.python.org/issue4764]), and now explicitly checks for and forbids writing to read-only file objects instead of trusting the C library to catch and report the error (fixed by Stefan Krah; bpo-5677 [https://bugs.python.org/issue5677]).

The Python tokenizer now translates line endings itself, so the compile() built-in function now accepts code using any line-ending convention. Additionally, it no longer requires that the code end in a newline.

Extra parentheses in function definitions are illegal in Python 3.x, meaning that you get a syntax error from def f((x)): pass. In Python3-warning mode, Python 2.7 will now warn about this odd usage. (Noted by James Lingard; bpo-7362 [https://bugs.python.org/issue7362].)

It’s now possible to create weak references to old-style class objects. New-style classes were always weak-referenceable. (Fixed by Antoine Pitrou; bpo-8268 [https://bugs.python.org/issue8268].)

When a module object is garbage-collected, the module’s dictionary is now only cleared if no one else is holding a reference to the dictionary (bpo-7140 [https://bugs.python.org/issue7140]).

Interpreter Changes

A new environment variable, PYTHONWARNINGS, allows controlling warnings. It should be set to a string containing warning settings, equivalent to those used with the -W switch, separated by commas. (Contributed by Brian Curtin; bpo-7301 [https://bugs.python.org/issue7301].)

For example, the following setting will print warnings every time they occur, but turn warnings from the Cookie module into an error. (The exact syntax for setting an environment variable varies across operating systems and shells.)

export PYTHONWARNINGS=all,error:::Cookie:0

Optimizations

Several performance enhancements have been added:

A new opcode was added to perform the initial setup for with statements, looking up the __enter__() and __exit__() methods. (Contributed by Benjamin Peterson.)

The garbage collector now performs better for one common usage pattern: when many objects are being allocated without deallocating any of them. This would previously take quadratic time for garbage collection, but now the number of full garbage collections is reduced as the number of objects on the heap grows. The new logic only performs a full garbage collection pass when the middle generation has been collected 10 times and when the number of survivor objects from the middle generation exceeds 10% of the number of objects in the oldest generation. (Suggested by Martin von Löwis and implemented by Antoine Pitrou; bpo-4074 [https://bugs.python.org/issue4074].)

The garbage collector tries to avoid tracking simple containers which can’t be part of a cycle. In Python 2.7, this is now true for tuples and dicts containing atomic types (such as ints, strings, etc.). Transitively, a dict containing tuples of atomic types won’t be tracked either. This helps reduce the cost of each garbage collection by decreasing the number of objects to be considered and traversed by the collector. (Contributed by Antoine Pitrou; bpo-4688 [https://bugs.python.org/issue4688].)

Long integers are now stored internally either in base 2**15 or in base 2**30, the base being determined at build time. Previously, they were always stored in base 2**15. Using base 2**30 gives significant performance improvements on 64-bit machines, but benchmark results on 32-bit machines have been mixed. Therefore, the default is to use base 2**30 on 64-bit machines and base 2**15 on 32-bit machines; on Unix, there’s a new configure option --enable-big-digits that can be used to override this default.

Apart from the performance improvements this change should be invisible to end users, with one exception: for testing and debugging purposes there’s a new structseq sys.long_info that provides information about the internal format, giving the number of bits per digit and the size in bytes of the C type used to store each digit:

>>> import sys
>>> sys.long_info
sys.long_info(bits_per_digit=30, sizeof_digit=4)

(Contribution par Mark Dickinson; bpo-4258 [https://bugs.python.org/issue4258].)

Another set of changes made long objects a few bytes smaller: 2 bytes smaller on 32-bit systems and 6 bytes on 64-bit. (Contributed by Mark Dickinson; bpo-5260 [https://bugs.python.org/issue5260].)

The division algorithm for long integers has been made faster by tightening the inner loop, doing shifts instead of multiplications, and fixing an unnecessary extra iteration. Various benchmarks show speedups of between 50% and 150% for long integer divisions and modulo operations. (Contributed by Mark Dickinson; bpo-5512 [https://bugs.python.org/issue5512].) Bitwise operations are also significantly faster (initial patch by Gregory Smith; bpo-1087418 [https://bugs.python.org/issue1087418]).

The implementation of % checks for the left-side operand being a Python string and special-cases it; this results in a 1–3% performance increase for applications that frequently use % with strings, such as templating libraries. (Implemented by Collin Winter; bpo-5176 [https://bugs.python.org/issue5176].)

List comprehensions with an if condition are compiled into faster bytecode. (Patch by Antoine Pitrou, back-ported to 2.7 by Jeffrey Yasskin; bpo-4715 [https://bugs.python.org/issue4715].)

Converting an integer or long integer to a decimal string was made faster by special-casing base 10 instead of using a generalized conversion function that supports arbitrary bases. (Patch by Gawain Bolton; bpo-6713 [https://bugs.python.org/issue6713].)

The split(), replace(), rindex(), rpartition(), and rsplit() methods of string-like types (strings, Unicode strings, and bytearray objects) now use a fast reverse-search algorithm instead of a character-by-character scan. This is sometimes faster by a factor of 10. (Added by Florent Xicluna; bpo-7462 [https://bugs.python.org/issue7462] and bpo-7622 [https://bugs.python.org/issue7622].)

The pickle and cPickle modules now automatically intern the strings used for attribute names, reducing memory usage of the objects resulting from unpickling. (Contributed by Jake McGuire; bpo-5084 [https://bugs.python.org/issue5084].)

The cPickle module now special-cases dictionaries, nearly halving the time required to pickle them. (Contributed by Collin Winter; bpo-5670 [https://bugs.python.org/issue5670].)

New and Improved Modules

As in every release, Python’s standard library received a number of enhancements and bug fixes. Here’s a partial list of the most notable changes, sorted alphabetically by module name. Consult the Misc/NEWS file in the source tree for a more complete list of changes, or look through the Subversion logs for all the details.

The bdb module’s base debugging class Bdb gained a feature for skipping modules. The constructor now takes an iterable containing glob-style patterns such as django.*; the debugger will not step into stack frames from a module that matches one of these patterns. (Contributed by Maru Newby after a suggestion by Senthil Kumaran; bpo-5142 [https://bugs.python.org/issue5142].)

The binascii module now supports the buffer API, so it can be used with memoryview instances and other similar buffer objects. (Backported from 3.x by Florent Xicluna; bpo-7703 [https://bugs.python.org/issue7703].)

Updated module: the bsddb module has been updated from 4.7.2devel9 to version 4.8.4 of the pybsddb package [https://www.jcea.es/programacion/pybsddb.htm]. The new version features better Python 3.x compatibility, various bug fixes, and adds several new BerkeleyDB flags and methods. (Updated by Jesús Cea Avión; bpo-8156 [https://bugs.python.org/issue8156]. The pybsddb changelog can be read at http://hg.jcea.es/pybsddb/file/tip/ChangeLog.)

The bz2 module’s BZ2File now supports the context management protocol, so you can write with bz2.BZ2File(...) as f:. (Contributed by Hagen Fürstenau; bpo-3860 [https://bugs.python.org/issue3860].)

New class: the Counter class in the collections module is useful for tallying data. Counter instances behave mostly like dictionaries but return zero for missing keys instead of raising a KeyError:

>>> from collections import Counter
>>> c = Counter()
>>> for letter in 'here is a sample of english text':
...   c[letter] += 1
...
>>> c
Counter({' ': 6, 'e': 5, 's': 3, 'a': 2, 'i': 2, 'h': 2,
'l': 2, 't': 2, 'g': 1, 'f': 1, 'm': 1, 'o': 1, 'n': 1,
'p': 1, 'r': 1, 'x': 1})
>>> c['e']
5
>>> c['z']
0

There are three additional Counter methods. most_common() returns the N most common elements and their counts. elements() returns an iterator over the contained elements, repeating each element as many times as its count. subtract() takes an iterable and subtracts one for each element instead of adding; if the argument is a dictionary or another Counter, the counts are subtracted.

>>> c.most_common(5)
[(' ', 6), ('e', 5), ('s', 3), ('a', 2), ('i', 2)]
>>> c.elements() ->
   'a', 'a', ' ', ' ', ' ', ' ', ' ', ' ',
   'e', 'e', 'e', 'e', 'e', 'g', 'f', 'i', 'i',
   'h', 'h', 'm', 'l', 'l', 'o', 'n', 'p', 's',
   's', 's', 'r', 't', 't', 'x'
>>> c['e']
5
>>> c.subtract('very heavy on the letter e')
>>> c['e']    # Count is now lower
-1

Contributed by Raymond Hettinger; bpo-1696199 [https://bugs.python.org/issue1696199].

New class: OrderedDict is described in the earlier section PEP 372: Adding an Ordered Dictionary to collections.

New method: The deque data type now has a count() method that returns the number of contained elements equal to the supplied argument x, and a reverse() method that reverses the elements of the deque in-place. deque also exposes its maximum length as the read-only maxlen attribute. (Both features added by Raymond Hettinger.)

The namedtuple class now has an optional rename parameter. If rename is true, field names that are invalid because they’ve been repeated or aren’t legal Python identifiers will be renamed to legal names that are derived from the field’s position within the list of fields:

>>> from collections import namedtuple
>>> T = namedtuple('T', ['field1', '$illegal', 'for', 'field2'], rename=True)
>>> T._fields
('field1', '_1', '_2', 'field2')

(Added by Raymond Hettinger; bpo-1818 [https://bugs.python.org/issue1818].)

Finally, the Mapping abstract base class now returns NotImplemented if a mapping is compared to another type that isn’t a Mapping. (Fixed by Daniel Stutzbach; bpo-8729 [https://bugs.python.org/issue8729].)

Constructors for the parsing classes in the ConfigParser module now take an allow_no_value parameter, defaulting to false; if true, options without values will be allowed. For example:

>>> import ConfigParser, StringIO
>>> sample_config = """
... [mysqld]
... user = mysql
... pid-file = /var/run/mysqld/mysqld.pid
... skip-bdb
... """
>>> config = ConfigParser.RawConfigParser(allow_no_value=True)
>>> config.readfp(StringIO.StringIO(sample_config))
>>> config.get('mysqld', 'user')
'mysql'
>>> print config.get('mysqld', 'skip-bdb')
None
>>> print config.get('mysqld', 'unknown')
Traceback (most recent call last):
  ...
NoOptionError: No option 'unknown' in section: 'mysqld'

(Contributed by Mats Kindahl; bpo-7005 [https://bugs.python.org/issue7005].)

Deprecated function: contextlib.nested(), which allows handling more than one context manager with a single with statement, has been deprecated, because the with statement now supports multiple context managers.

The cookielib module now ignores cookies that have an invalid version field, one that doesn’t contain an integer value. (Fixed by John J. Lee; bpo-3924 [https://bugs.python.org/issue3924].)

The copy module’s deepcopy() function will now correctly copy bound instance methods. (Implemented by Robert Collins; bpo-1515 [https://bugs.python.org/issue1515].)

The ctypes module now always converts None to a C NULL pointer for arguments declared as pointers. (Changed by Thomas Heller; bpo-4606 [https://bugs.python.org/issue4606].) The underlying libffi library [https://sourceware.org/libffi/] has been updated to version 3.0.9, containing various fixes for different platforms. (Updated by Matthias Klose; bpo-8142 [https://bugs.python.org/issue8142].)

New method: the datetime module’s timedelta class gained a total_seconds() method that returns the number of seconds in the duration. (Contributed by Brian Quinlan; bpo-5788 [https://bugs.python.org/issue5788].)

New method: the Decimal class gained a from_float() class method that performs an exact conversion of a floating-point number to a Decimal. This exact conversion strives for the closest decimal approximation to the floating-point representation’s value; the resulting decimal value will therefore still include the inaccuracy, if any. For example, Decimal.from_float(0.1) returns Decimal('0.1000000000000000055511151231257827021181583404541015625'). (Implemented by Raymond Hettinger; bpo-4796 [https://bugs.python.org/issue4796].)

Comparing instances of Decimal with floating-point numbers now produces sensible results based on the numeric values of the operands. Previously such comparisons would fall back to Python’s default rules for comparing objects, which produced arbitrary results based on their type. Note that you still cannot combine Decimal and floating-point in other operations such as addition, since you should be explicitly choosing how to convert between float and Decimal. (Fixed by Mark Dickinson; bpo-2531 [https://bugs.python.org/issue2531].)

The constructor for Decimal now accepts floating-point numbers (added by Raymond Hettinger; bpo-8257 [https://bugs.python.org/issue8257]) and non-European Unicode characters such as Arabic-Indic digits (contributed by Mark Dickinson; bpo-6595 [https://bugs.python.org/issue6595]).

Most of the methods of the Context class now accept integers as well as Decimal instances; the only exceptions are the canonical() and is_canonical() methods. (Patch by Juan José Conti; bpo-7633 [https://bugs.python.org/issue7633].)

When using Decimal instances with a string’s format() method, the default alignment was previously left-alignment. This has been changed to right-alignment, which is more sensible for numeric types. (Changed by Mark Dickinson; bpo-6857 [https://bugs.python.org/issue6857].)

Comparisons involving a signaling NaN value (or sNAN) now signal InvalidOperation instead of silently returning a true or false value depending on the comparison operator. Quiet NaN values (or NaN) are now hashable. (Fixed by Mark Dickinson; bpo-7279 [https://bugs.python.org/issue7279].)

The difflib module now produces output that is more compatible with modern diff/patch tools through one small change, using a tab character instead of spaces as a separator in the header giving the filename. (Fixed by Anatoly Techtonik; bpo-7585 [https://bugs.python.org/issue7585].)

The Distutils sdist command now always regenerates the MANIFEST file, since even if the MANIFEST.in or setup.py files haven’t been modified, the user might have created some new files that should be included. (Fixed by Tarek Ziadé; bpo-8688 [https://bugs.python.org/issue8688].)

The doctest module’s IGNORE_EXCEPTION_DETAIL flag will now ignore the name of the module containing the exception being tested. (Patch by Lennart Regebro; bpo-7490 [https://bugs.python.org/issue7490].)

The email module’s Message class will now accept a Unicode-valued payload, automatically converting the payload to the encoding specified by output_charset. (Added by R. David Murray; bpo-1368247 [https://bugs.python.org/issue1368247].)

The Fraction class now accepts a single float or Decimal instance, or two rational numbers, as arguments to its constructor. (Implemented by Mark Dickinson; rationals added in bpo-5812 [https://bugs.python.org/issue5812], and float/decimal in bpo-8294 [https://bugs.python.org/issue8294].)

Ordering comparisons (<, <=, >, >=) between fractions and complex numbers now raise a TypeError. This fixes an oversight, making the Fraction match the other numeric types.

New class: FTP_TLS in the ftplib module provides secure FTP connections using TLS encapsulation of authentication as well as subsequent control and data transfers. (Contributed by Giampaolo Rodola; bpo-2054 [https://bugs.python.org/issue2054].)

The storbinary() method for binary uploads can now restart uploads thanks to an added rest parameter (patch by Pablo Mouzo; bpo-6845 [https://bugs.python.org/issue6845].)

New class decorator: total_ordering() in the functools module takes a class that defines an __eq__() method and one of __lt__(), __le__(), __gt__(), or __ge__(), and generates the missing comparison methods. Since the __cmp__() method is being deprecated in Python 3.x, this decorator makes it easier to define ordered classes. (Added by Raymond Hettinger; bpo-5479 [https://bugs.python.org/issue5479].)

New function: cmp_to_key() will take an old-style comparison function that expects two arguments and return a new callable that can be used as the key parameter to functions such as sorted(), min() and max(), etc. The primary intended use is to help with making code compatible with Python 3.x. (Added by Raymond Hettinger.)

New function: the gc module’s is_tracked() returns true if a given instance is tracked by the garbage collector, false otherwise. (Contributed by Antoine Pitrou; bpo-4688 [https://bugs.python.org/issue4688].)

The gzip module’s GzipFile now supports the context management protocol, so you can write with gzip.GzipFile(...) as f: (contributed by Hagen Fürstenau; bpo-3860 [https://bugs.python.org/issue3860]), and it now implements the io.BufferedIOBase ABC, so you can wrap it with io.BufferedReader for faster processing (contributed by Nir Aides; bpo-7471 [https://bugs.python.org/issue7471]). It’s also now possible to override the modification time recorded in a gzipped file by providing an optional timestamp to the constructor. (Contributed by Jacques Frechet; bpo-4272 [https://bugs.python.org/issue4272].)

Files in gzip format can be padded with trailing zero bytes; the gzip module will now consume these trailing bytes. (Fixed by Tadek Pietraszek and Brian Curtin; bpo-2846 [https://bugs.python.org/issue2846].)

New attribute: the hashlib module now has an algorithms attribute containing a tuple naming the supported algorithms. In Python 2.7, hashlib.algorithms contains ('md5', 'sha1', 'sha224', 'sha256', 'sha384', 'sha512'). (Contributed by Carl Chenet; bpo-7418 [https://bugs.python.org/issue7418].)

The default HTTPResponse class used by the httplib module now supports buffering, resulting in much faster reading of HTTP responses. (Contributed by Kristján Valur Jónsson; bpo-4879 [https://bugs.python.org/issue4879].)

The HTTPConnection and HTTPSConnection classes now support a source_address parameter, a (host, port) 2-tuple giving the source address that will be used for the connection. (Contributed by Eldon Ziegler; bpo-3972 [https://bugs.python.org/issue3972].)

The ihooks module now supports relative imports. Note that ihooks is an older module for customizing imports, superseded by the imputil module added in Python 2.0. (Relative import support added by Neil Schemenauer.)

The imaplib module now supports IPv6 addresses. (Contributed by Derek Morr; bpo-1655 [https://bugs.python.org/issue1655].)

New function: the inspect module’s getcallargs() takes a callable and its positional and keyword arguments, and figures out which of the callable’s parameters will receive each argument, returning a dictionary mapping argument names to their values. For example:

>>> from inspect import getcallargs
>>> def f(a, b=1, *pos, **named):
...     pass
>>> getcallargs(f, 1, 2, 3)
{'a': 1, 'b': 2, 'pos': (3,), 'named': {}}
>>> getcallargs(f, a=2, x=4)
{'a': 2, 'b': 1, 'pos': (), 'named': {'x': 4}}
>>> getcallargs(f)
Traceback (most recent call last):
...
TypeError: f() takes at least 1 argument (0 given)

Contributed by George Sakkis; bpo-3135 [https://bugs.python.org/issue3135].

Updated module: The io library has been upgraded to the version shipped with Python 3.1. For 3.1, the I/O library was entirely rewritten in C and is 2 to 20 times faster depending on the task being performed. The original Python version was renamed to the _pyio module.

One minor resulting change: the io.TextIOBase class now has an errors attribute giving the error setting used for encoding and decoding errors (one of 'strict', 'replace', 'ignore').

The io.FileIO class now raises an OSError when passed an invalid file descriptor. (Implemented by Benjamin Peterson; bpo-4991 [https://bugs.python.org/issue4991].) The truncate() method now preserves the file position; previously it would change the file position to the end of the new file. (Fixed by Pascal Chambon; bpo-6939 [https://bugs.python.org/issue6939].)

New function: itertools.compress(data, selectors) takes two iterators. Elements of data are returned if the corresponding value in selectors is true:

itertools.compress('ABCDEF', [1,0,1,0,1,1]) =>
  A, C, E, F

New function: itertools.combinations_with_replacement(iter, r) returns all the possible r-length combinations of elements from the iterable iter. Unlike combinations(), individual elements can be repeated in the generated combinations:

itertools.combinations_with_replacement('abc', 2) =>
  ('a', 'a'), ('a', 'b'), ('a', 'c'),
  ('b', 'b'), ('b', 'c'), ('c', 'c')

Note that elements are treated as unique depending on their position in the input, not their actual values.

The itertools.count() function now has a step argument that allows incrementing by values other than 1. count() also now allows keyword arguments, and using non-integer values such as floats or Decimal instances. (Implemented by Raymond Hettinger; bpo-5032 [https://bugs.python.org/issue5032].)

itertools.combinations() and itertools.product() previously raised ValueError for values of r larger than the input iterable. This was deemed a specification error, so they now return an empty iterator. (Fixed by Raymond Hettinger; bpo-4816 [https://bugs.python.org/issue4816].)

Updated module: The json module was upgraded to version 2.0.9 of the simplejson package, which includes a C extension that makes encoding and decoding faster. (Contributed by Bob Ippolito; bpo-4136 [https://bugs.python.org/issue4136].)

To support the new collections.OrderedDict type, json.load() now has an optional object_pairs_hook parameter that will be called with any object literal that decodes to a list of pairs. (Contributed by Raymond Hettinger; bpo-5381 [https://bugs.python.org/issue5381].)

The mailbox module’s Maildir class now records the timestamp on the directories it reads, and only re-reads them if the modification time has subsequently changed. This improves performance by avoiding unneeded directory scans. (Fixed by A.M. Kuchling and Antoine Pitrou; bpo-1607951 [https://bugs.python.org/issue1607951], bpo-6896 [https://bugs.python.org/issue6896].)

New functions: the math module gained erf() and erfc() for the error function and the complementary error function, expm1() which computes e**x - 1 with more precision than using exp() and subtracting 1, gamma() for the Gamma function, and lgamma() for the natural log of the Gamma function. (Contributed by Mark Dickinson and nirinA raseliarison; bpo-3366 [https://bugs.python.org/issue3366].)

The multiprocessing module’s Manager* classes can now be passed a callable that will be called whenever a subprocess is started, along with a set of arguments that will be passed to the callable. (Contributed by lekma; bpo-5585 [https://bugs.python.org/issue5585].)

The Pool class, which controls a pool of worker processes, now has an optional maxtasksperchild parameter. Worker processes will perform the specified number of tasks and then exit, causing the Pool to start a new worker. This is useful if tasks may leak memory or other resources, or if some tasks will cause the worker to become very large. (Contributed by Charles Cazabon; bpo-6963 [https://bugs.python.org/issue6963].)

The nntplib module now supports IPv6 addresses. (Contributed by Derek Morr; bpo-1664 [https://bugs.python.org/issue1664].)

New functions: the os module wraps the following POSIX system calls: getresgid() and getresuid(), which return the real, effective, and saved GIDs and UIDs; setresgid() and setresuid(), which set real, effective, and saved GIDs and UIDs to new values; initgroups(), which initialize the group access list for the current process. (GID/UID functions contributed by Travis H.; bpo-6508 [https://bugs.python.org/issue6508]. Support for initgroups added by Jean-Paul Calderone; bpo-7333 [https://bugs.python.org/issue7333].)

The os.fork() function now re-initializes the import lock in the child process; this fixes problems on Solaris when fork() is called from a thread. (Fixed by Zsolt Cserna; bpo-7242 [https://bugs.python.org/issue7242].)

In the os.path module, the normpath() and abspath() functions now preserve Unicode; if their input path is a Unicode string, the return value is also a Unicode string. (normpath() fixed by Matt Giuca in bpo-5827 [https://bugs.python.org/issue5827]; abspath() fixed by Ezio Melotti in bpo-3426 [https://bugs.python.org/issue3426].)

The pydoc module now has help for the various symbols that Python uses. You can now do help('<<') or help('@'), for example. (Contributed by David Laban; bpo-4739 [https://bugs.python.org/issue4739].)

The re module’s split(), sub(), and subn() now accept an optional flags argument, for consistency with the other functions in the module. (Added by Gregory P. Smith.)

New function: run_path() in the runpy module will execute the code at a provided path argument. path can be the path of a Python source file (example.py), a compiled bytecode file (example.pyc), a directory (./package/), or a zip archive (example.zip). If a directory or zip path is provided, it will be added to the front of sys.path and the module __main__ will be imported. It’s expected that the directory or zip contains a __main__.py; if it doesn’t, some other __main__.py might be imported from a location later in sys.path. This makes more of the machinery of runpy available to scripts that want to mimic the way Python’s command line processes an explicit path name. (Added by Nick Coghlan; bpo-6816 [https://bugs.python.org/issue6816].)

New function: in the shutil module, make_archive() takes a filename, archive type (zip or tar-format), and a directory path, and creates an archive containing the directory’s contents. (Added by Tarek Ziadé.)

shutil’s copyfile() and copytree() functions now raise a SpecialFileError exception when asked to copy a named pipe. Previously the code would treat named pipes like a regular file by opening them for reading, and this would block indefinitely. (Fixed by Antoine Pitrou; bpo-3002 [https://bugs.python.org/issue3002].)

The signal module no longer re-installs the signal handler unless this is truly necessary, which fixes a bug that could make it impossible to catch the EINTR signal robustly. (Fixed by Charles-Francois Natali; bpo-8354 [https://bugs.python.org/issue8354].)

New functions: in the site module, three new functions return various site- and user-specific paths. getsitepackages() returns a list containing all global site-packages directories, getusersitepackages() returns the path of the user’s site-packages directory, and getuserbase() returns the value of the USER_BASE environment variable, giving the path to a directory that can be used to store data. (Contributed by Tarek Ziadé; bpo-6693 [https://bugs.python.org/issue6693].)

The site module now reports exceptions occurring when the sitecustomize module is imported, and will no longer catch and swallow the KeyboardInterrupt exception. (Fixed by Victor Stinner; bpo-3137 [https://bugs.python.org/issue3137].)

The create_connection() function gained a source_address parameter, a (host, port) 2-tuple giving the source address that will be used for the connection. (Contributed by Eldon Ziegler; bpo-3972 [https://bugs.python.org/issue3972].)

The recv_into() and recvfrom_into() methods will now write into objects that support the buffer API, most usefully the bytearray and memoryview objects. (Implemented by Antoine Pitrou; bpo-8104 [https://bugs.python.org/issue8104].)

The SocketServer module’s TCPServer class now supports socket timeouts and disabling the Nagle algorithm. The disable_nagle_algorithm class attribute defaults to False; if overridden to be true, new request connections will have the TCP_NODELAY option set to prevent buffering many small sends into a single TCP packet. The timeout class attribute can hold a timeout in seconds that will be applied to the request socket; if no request is received within that time, handle_timeout() will be called and handle_request() will return. (Contributed by Kristján Valur Jónsson; bpo-6192 [https://bugs.python.org/issue6192] and bpo-6267 [https://bugs.python.org/issue6267].)

Updated module: the sqlite3 module has been updated to version 2.6.0 of the pysqlite package [https://github.com/ghaering/pysqlite]. Version 2.6.0 includes a number of bugfixes, and adds the ability to load SQLite extensions from shared libraries. Call the enable_load_extension(True) method to enable extensions, and then call load_extension() to load a particular shared library. (Updated by Gerhard Häring.)

The ssl module’s SSLSocket objects now support the buffer API, which fixed a test suite failure (fix by Antoine Pitrou; bpo-7133 [https://bugs.python.org/issue7133]) and automatically set OpenSSL’s SSL_MODE_AUTO_RETRY, which will prevent an error code being returned from recv() operations that trigger an SSL renegotiation (fix by Antoine Pitrou; bpo-8222 [https://bugs.python.org/issue8222]).

The ssl.wrap_socket() constructor function now takes a ciphers argument that’s a string listing the encryption algorithms to be allowed; the format of the string is described in the OpenSSL documentation [https://www.openssl.org/docs/manmaster/man1/ciphers.html#CIPHER-LIST-FORMAT]. (Added by Antoine Pitrou; bpo-8322 [https://bugs.python.org/issue8322].)

Another change makes the extension load all of OpenSSL’s ciphers and digest algorithms so that they’re all available. Some SSL certificates couldn’t be verified, reporting an « unknown algorithm » error. (Reported by Beda Kosata, and fixed by Antoine Pitrou; bpo-8484 [https://bugs.python.org/issue8484].)

The version of OpenSSL being used is now available as the module attributes ssl.OPENSSL_VERSION (a string), ssl.OPENSSL_VERSION_INFO (a 5-tuple), and ssl.OPENSSL_VERSION_NUMBER (an integer). (Added by Antoine Pitrou; bpo-8321 [https://bugs.python.org/issue8321].)

The struct module will no longer silently ignore overflow errors when a value is too large for a particular integer format code (one of bBhHiIlLqQ); it now always raises a struct.error exception. (Changed by Mark Dickinson; bpo-1523 [https://bugs.python.org/issue1523].) The pack() function will also attempt to use __index__() to convert and pack non-integers before trying the __int__() method or reporting an error. (Changed by Mark Dickinson; bpo-8300 [https://bugs.python.org/issue8300].)

New function: the subprocess module’s check_output() runs a command with a specified set of arguments and returns the command’s output as a string when the command runs without error, or raises a CalledProcessError exception otherwise.

>>> subprocess.check_output(['df', '-h', '.'])
'Filesystem     Size   Used  Avail Capacity  Mounted on\n
/dev/disk0s2    52G    49G   3.0G    94%    /\n'

>>> subprocess.check_output(['df', '-h', '/bogus'])
  ...
subprocess.CalledProcessError: Command '['df', '-h', '/bogus']' returned non-zero exit status 1

(Contributed by Gregory P. Smith.)

The subprocess module will now retry its internal system calls on receiving an EINTR signal. (Reported by several people; final patch by Gregory P. Smith in bpo-1068268 [https://bugs.python.org/issue1068268].)

New function: is_declared_global() in the symtable module returns true for variables that are explicitly declared to be global, false for ones that are implicitly global. (Contributed by Jeremy Hylton.)

The syslog module will now use the value of sys.argv[0] as the identifier instead of the previous default value of 'python'. (Changed by Sean Reifschneider; bpo-8451 [https://bugs.python.org/issue8451].)

The sys.version_info value is now a named tuple, with attributes named major, minor, micro, releaselevel, and serial. (Contributed by Ross Light; bpo-4285 [https://bugs.python.org/issue4285].)

sys.getwindowsversion() also returns a named tuple, with attributes named major, minor, build, platform, service_pack, service_pack_major, service_pack_minor, suite_mask, and product_type. (Contributed by Brian Curtin; bpo-7766 [https://bugs.python.org/issue7766].)

The tarfile module’s default error handling has changed, to no longer suppress fatal errors. The default error level was previously 0, which meant that errors would only result in a message being written to the debug log, but because the debug log is not activated by default, these errors go unnoticed. The default error level is now 1, which raises an exception if there’s an error. (Changed by Lars Gustäbel; bpo-7357 [https://bugs.python.org/issue7357].)

tarfile now supports filtering the TarInfo objects being added to a tar file. When you call add(), you may supply an optional filter argument that’s a callable. The filter callable will be passed the TarInfo for every file being added, and can modify and return it. If the callable returns None, the file will be excluded from the resulting archive. This is more powerful than the existing exclude argument, which has therefore been deprecated. (Added by Lars Gustäbel; bpo-6856 [https://bugs.python.org/issue6856].) The TarFile class also now supports the context management protocol. (Added by Lars Gustäbel; bpo-7232 [https://bugs.python.org/issue7232].)

The wait() method of the threading.Event class now returns the internal flag on exit. This means the method will usually return true because wait() is supposed to block until the internal flag becomes true. The return value will only be false if a timeout was provided and the operation timed out. (Contributed by Tim Lesher; bpo-1674032 [https://bugs.python.org/issue1674032].)

The Unicode database provided by the unicodedata module is now used internally to determine which characters are numeric, whitespace, or represent line breaks. The database also includes information from the Unihan.txt data file (patch by Anders Chrigström and Amaury Forgeot d’Arc; bpo-1571184 [https://bugs.python.org/issue1571184]) and has been updated to version 5.2.0 (updated by Florent Xicluna; bpo-8024 [https://bugs.python.org/issue8024]).

The urlparse module’s urlsplit() now handles unknown URL schemes in a fashion compliant with RFC 3986 [https://tools.ietf.org/html/rfc3986.html]: if the URL is of the form "<something>://...", the text before the :// is treated as the scheme, even if it’s a made-up scheme that the module doesn’t know about. This change may break code that worked around the old behaviour. For example, Python 2.6.4 or 2.5 will return the following:

>>> import urlparse
>>> urlparse.urlsplit('invented://host/filename?query')
('invented', '', '//host/filename?query', '', '')

Python 2.7 (and Python 2.6.5) will return:

>>> import urlparse
>>> urlparse.urlsplit('invented://host/filename?query')
('invented', 'host', '/filename?query', '', '')

(Python 2.7 actually produces slightly different output, since it returns a named tuple instead of a standard tuple.)

The urlparse module also supports IPv6 literal addresses as defined by RFC 2732 [https://tools.ietf.org/html/rfc2732.html] (contributed by Senthil Kumaran; bpo-2987 [https://bugs.python.org/issue2987]).

>>> urlparse.urlparse('http://[1080::8:800:200C:417A]/foo')
ParseResult(scheme='http', netloc='[1080::8:800:200C:417A]',
            path='/foo', params='', query='', fragment='')

New class: the WeakSet class in the weakref module is a set that only holds weak references to its elements; elements will be removed once there are no references pointing to them. (Originally implemented in Python 3.x by Raymond Hettinger, and backported to 2.7 by Michael Foord.)

The ElementTree library, xml.etree, no longer escapes ampersands and angle brackets when outputting an XML processing instruction (which looks like <?xml-stylesheet href="#style1"?>) or comment (which looks like <!-- comment -->). (Patch by Neil Muller; bpo-2746 [https://bugs.python.org/issue2746].)

The XML-RPC client and server, provided by the xmlrpclib and SimpleXMLRPCServer modules, have improved performance by supporting HTTP/1.1 keep-alive and by optionally using gzip encoding to compress the XML being exchanged. The gzip compression is controlled by the encode_threshold attribute of SimpleXMLRPCRequestHandler, which contains a size in bytes; responses larger than this will be compressed. (Contributed by Kristján Valur Jónsson; bpo-6267 [https://bugs.python.org/issue6267].)

The zipfile module’s ZipFile now supports the context management protocol, so you can write with zipfile.ZipFile(...) as f:. (Contributed by Brian Curtin; bpo-5511 [https://bugs.python.org/issue5511].)

zipfile now also supports archiving empty directories and extracts them correctly. (Fixed by Kuba Wieczorek; bpo-4710 [https://bugs.python.org/issue4710].) Reading files out of an archive is faster, and interleaving read() and readline() now works correctly. (Contributed by Nir Aides; bpo-7610 [https://bugs.python.org/issue7610].)

The is_zipfile() function now accepts a file object, in addition to the path names accepted in earlier versions. (Contributed by Gabriel Genellina; bpo-4756 [https://bugs.python.org/issue4756].)

The writestr() method now has an optional compress_type parameter that lets you override the default compression method specified in the ZipFile constructor. (Contributed by Ronald Oussoren; bpo-6003 [https://bugs.python.org/issue6003].)

New module: importlib

Python 3.1 includes the importlib package, a re-implementation of the logic underlying Python’s import statement. importlib is useful for implementors of Python interpreters and to users who wish to write new importers that can participate in the import process. Python 2.7 doesn’t contain the complete importlib package, but instead has a tiny subset that contains a single function, import_module().

import_module(name, package=None) imports a module. name is a string containing the module or package’s name. It’s possible to do relative imports by providing a string that begins with a . character, such as ..utils.errors. For relative imports, the package argument must be provided and is the name of the package that will be used as the anchor for the relative import. import_module() both inserts the imported module into sys.modules and returns the module object.

Here are some examples:

>>> from importlib import import_module
>>> anydbm = import_module('anydbm')  # Standard absolute import
>>> anydbm
<module 'anydbm' from '/p/python/Lib/anydbm.py'>
>>> # Relative import
>>> file_util = import_module('..file_util', 'distutils.command')
>>> file_util
<module 'distutils.file_util' from '/python/Lib/distutils/file_util.pyc'>

importlib was implemented by Brett Cannon and introduced in Python 3.1.

New module: sysconfig

The sysconfig module has been pulled out of the Distutils package, becoming a new top-level module in its own right. sysconfig provides functions for getting information about Python’s build process: compiler switches, installation paths, the platform name, and whether Python is running from its source directory.

Some of the functions in the module are:

get_config_var() returns variables from Python’s Makefile and the pyconfig.h file.

get_config_vars() returns a dictionary containing all of the configuration variables.

get_path() returns the configured path for a particular type of module: the standard library, site-specific modules, platform-specific modules, etc.

is_python_build() returns true if you’re running a binary from a Python source tree, and false otherwise.

Consult the sysconfig documentation for more details and for a complete list of functions.

The Distutils package and sysconfig are now maintained by Tarek Ziadé, who has also started a Distutils2 package (source repository at https://hg.python.org/distutils2/) for developing a next-generation version of Distutils.

ttk: Themed Widgets for Tk

Tcl/Tk 8.5 includes a set of themed widgets that re-implement basic Tk widgets but have a more customizable appearance and can therefore more closely resemble the native platform’s widgets. This widget set was originally called Tile, but was renamed to Ttk (for « themed Tk ») on being added to Tcl/Tck release 8.5.

To learn more, read the ttk module documentation. You may also wish to read the Tcl/Tk manual page describing the Ttk theme engine, available at https://www.tcl.tk/man/tcl8.5/TkCmd/ttk_intro.htm. Some screenshots of the Python/Ttk code in use are at https://code.google.com/archive/p/python-ttk/wikis/Screenshots.wiki.

The ttk module was written by Guilherme Polo and added in bpo-2983 [https://bugs.python.org/issue2983]. An alternate version called Tile.py, written by Martin Franklin and maintained by Kevin Walzer, was proposed for inclusion in bpo-2618 [https://bugs.python.org/issue2618], but the authors argued that Guilherme Polo’s work was more comprehensive.

Updated module: unittest

The unittest module was greatly enhanced; many new features were added. Most of these features were implemented by Michael Foord, unless otherwise noted. The enhanced version of the module is downloadable separately for use with Python versions 2.4 to 2.6, packaged as the unittest2 package, from https://pypi.org/project/unittest2.

When used from the command line, the module can automatically discover tests. It’s not as fancy as py.test [http://pytest.org] or nose [https://nose.readthedocs.io/], but provides a simple way to run tests kept within a set of package directories. For example, the following command will search the test/ subdirectory for any importable test files named test*.py:

python -m unittest discover -s test

Consult the unittest module documentation for more details. (Developed in bpo-6001 [https://bugs.python.org/issue6001].)

The main() function supports some other new options:

-b or --buffer will buffer the standard output and standard error streams during each test. If the test passes, any resulting output will be discarded; on failure, the buffered output will be displayed.

-c or --catch will cause the control-C interrupt to be handled more gracefully. Instead of interrupting the test process immediately, the currently running test will be completed and then the partial results up to the interruption will be reported. If you’re impatient, a second press of control-C will cause an immediate interruption.

This control-C handler tries to avoid causing problems when the code being tested or the tests being run have defined a signal handler of their own, by noticing that a signal handler was already set and calling it. If this doesn’t work for you, there’s a removeHandler() decorator that can be used to mark tests that should have the control-C handling disabled.

-f or --failfast makes test execution stop immediately when a test fails instead of continuing to execute further tests. (Suggested by Cliff Dyer and implemented by Michael Foord; bpo-8074 [https://bugs.python.org/issue8074].)

The progress messages now show “x” for expected failures and “u” for unexpected successes when run in verbose mode. (Contributed by Benjamin Peterson.)

Test cases can raise the SkipTest exception to skip a test (bpo-1034053 [https://bugs.python.org/issue1034053]).

The error messages for assertEqual(), assertTrue(), and assertFalse() failures now provide more information. If you set the longMessage attribute of your TestCase classes to true, both the standard error message and any additional message you provide will be printed for failures. (Added by Michael Foord; bpo-5663 [https://bugs.python.org/issue5663].)

The assertRaises() method now returns a context handler when called without providing a callable object to run. For example, you can write this:

with self.assertRaises(KeyError):
    {}['foo']

(Implemented by Antoine Pitrou; bpo-4444 [https://bugs.python.org/issue4444].)

Module- and class-level setup and teardown fixtures are now supported. Modules can contain setUpModule() and tearDownModule() functions. Classes can have setUpClass() and tearDownClass() methods that must be defined as class methods (using @classmethod or equivalent). These functions and methods are invoked when the test runner switches to a test case in a different module or class.

The methods addCleanup() and doCleanups() were added. addCleanup() lets you add cleanup functions that will be called unconditionally (after setUp() if setUp() fails, otherwise after tearDown()). This allows for much simpler resource allocation and deallocation during tests (bpo-5679 [https://bugs.python.org/issue5679]).

A number of new methods were added that provide more specialized tests. Many of these methods were written by Google engineers for use in their test suites; Gregory P. Smith, Michael Foord, and GvR worked on merging them into Python’s version of unittest.

assertIsNone() and assertIsNotNone() take one expression and verify that the result is or is not None.

assertIs() and assertIsNot() take two values and check whether the two values evaluate to the same object or not. (Added by Michael Foord; bpo-2578 [https://bugs.python.org/issue2578].)

assertIsInstance() and assertNotIsInstance() check whether the resulting object is an instance of a particular class, or of one of a tuple of classes. (Added by Georg Brandl; bpo-7031 [https://bugs.python.org/issue7031].)

assertGreater(), assertGreaterEqual(), assertLess(), and assertLessEqual() compare two quantities.

assertMultiLineEqual() compares two strings, and if they’re not equal, displays a helpful comparison that highlights the differences in the two strings. This comparison is now used by default when Unicode strings are compared with assertEqual().

assertRegexpMatches() and assertNotRegexpMatches() checks whether the first argument is a string matching or not matching the regular expression provided as the second argument (bpo-8038 [https://bugs.python.org/issue8038]).

assertRaisesRegexp() checks whether a particular exception is raised, and then also checks that the string representation of the exception matches the provided regular expression.

assertIn() and assertNotIn() tests whether first is or is not in second.

assertItemsEqual() tests whether two provided sequences contain the same elements.

assertSetEqual() compares whether two sets are equal, and only reports the differences between the sets in case of error.

Similarly, assertListEqual() and assertTupleEqual() compare the specified types and explain any differences without necessarily printing their full values; these methods are now used by default when comparing lists and tuples using assertEqual(). More generally, assertSequenceEqual() compares two sequences and can optionally check whether both sequences are of a particular type.

assertDictEqual() compares two dictionaries and reports the differences; it’s now used by default when you compare two dictionaries using assertEqual(). assertDictContainsSubset() checks whether all of the key/value pairs in first are found in second.

assertAlmostEqual() and assertNotAlmostEqual() test whether first and second are approximately equal. This method can either round their difference to an optionally-specified number of places (the default is 7) and compare it to zero, or require the difference to be smaller than a supplied delta value.

loadTestsFromName() properly honors the suiteClass attribute of the TestLoader. (Fixed by Mark Roddy; bpo-6866 [https://bugs.python.org/issue6866].)

A new hook lets you extend the assertEqual() method to handle new data types. The addTypeEqualityFunc() method takes a type object and a function. The function will be used when both of the objects being compared are of the specified type. This function should compare the two objects and raise an exception if they don’t match; it’s a good idea for the function to provide additional information about why the two objects aren’t matching, much as the new sequence comparison methods do.

unittest.main() now takes an optional exit argument. If false, main() doesn’t call sys.exit(), allowing main() to be used from the interactive interpreter. (Contributed by J. Pablo Fernández; bpo-3379 [https://bugs.python.org/issue3379].)

TestResult has new startTestRun() and stopTestRun() methods that are called immediately before and after a test run. (Contributed by Robert Collins; bpo-5728 [https://bugs.python.org/issue5728].)

With all these changes, the unittest.py was becoming awkwardly large, so the module was turned into a package and the code split into several files (by Benjamin Peterson). This doesn’t affect how the module is imported or used.

Voir aussi

http://www.voidspace.org.uk/python/articles/unittest2.shtml

Describes the new features, how to use them, and the rationale for various design decisions. (By Michael Foord.)

Module mis-à-jour : ElementTree 1.3

The version of the ElementTree library included with Python was updated to version 1.3. Some of the new features are:

The various parsing functions now take a parser keyword argument giving an XMLParser instance that will be used. This makes it possible to override the file’s internal encoding:

p = ET.XMLParser(encoding='utf-8')
t = ET.XML("""<root/>""", parser=p)

Errors in parsing XML now raise a ParseError exception, whose instances have a position attribute containing a (line, column) tuple giving the location of the problem.

ElementTree’s code for converting trees to a string has been significantly reworked, making it roughly twice as fast in many cases. The ElementTree.write() and Element.write() methods now have a method parameter that can be « xml » (the default), « html », or « text ». HTML mode will output empty elements as <empty></empty> instead of <empty/>, and text mode will skip over elements and only output the text chunks. If you set the tag attribute of an element to None but leave its children in place, the element will be omitted when the tree is written out, so you don’t need to do more extensive rearrangement to remove a single element.

Namespace handling has also been improved. All xmlns:<whatever> declarations are now output on the root element, not scattered throughout the resulting XML. You can set the default namespace for a tree by setting the default_namespace attribute and can register new prefixes with register_namespace(). In XML mode, you can use the true/false xml_declaration parameter to suppress the XML declaration.

New Element method: extend() appends the items from a sequence to the element’s children. Elements themselves behave like sequences, so it’s easy to move children from one element to another:

from xml.etree import ElementTree as ET

t = ET.XML("""<list>
  <item>1</item> <item>2</item>  <item>3</item>
</list>""")
new = ET.XML('<root/>')
new.extend(t)

# Outputs <root><item>1</item>...</root>
print ET.tostring(new)

New Element method: iter() yields the children of the element as a generator. It’s also possible to write for child in elem: to loop over an element’s children. The existing method getiterator() is now deprecated, as is getchildren() which constructs and returns a list of children.

New Element method: itertext() yields all chunks of text that are descendants of the element. For example:

t = ET.XML("""<list>
  <item>1</item> <item>2</item>  <item>3</item>
</list>""")

# Outputs ['\n  ', '1', ' ', '2', '  ', '3', '\n']
print list(t.itertext())

Deprecated: using an element as a Boolean (i.e., if elem:) would return true if the element had any children, or false if there were no children. This behaviour is confusing – None is false, but so is a childless element? – so it will now trigger a FutureWarning. In your code, you should be explicit: write len(elem) != 0 if you’re interested in the number of children, or elem is not None.

Fredrik Lundh develops ElementTree and produced the 1.3 version; you can read his article describing 1.3 at http://effbot.org/zone/elementtree-13-intro.htm. Florent Xicluna updated the version included with Python, after discussions on python-dev and in bpo-6472 [https://bugs.python.org/issue6472].)

Build and C API Changes

Changes to Python’s build process and to the C API include:

The latest release of the GNU Debugger, GDB 7, can be scripted using Python [https://sourceware.org/gdb/current/onlinedocs/gdb/Python.html]. When you begin debugging an executable program P, GDB will look for a file named P-gdb.py and automatically read it. Dave Malcolm contributed a python-gdb.py that adds a number of commands useful when debugging Python itself. For example, py-up and py-down go up or down one Python stack frame, which usually corresponds to several C stack frames. py-print prints the value of a Python variable, and py-bt prints the Python stack trace. (Added as a result of bpo-8032 [https://bugs.python.org/issue8032].)

If you use the .gdbinit file provided with Python, the « pyo » macro in the 2.7 version now works correctly when the thread being debugged doesn’t hold the GIL; the macro now acquires it before printing. (Contributed by Victor Stinner; bpo-3632 [https://bugs.python.org/issue3632].)

Py_AddPendingCall() is now thread-safe, letting any worker thread submit notifications to the main Python thread. This is particularly useful for asynchronous IO operations. (Contributed by Kristján Valur Jónsson; bpo-4293 [https://bugs.python.org/issue4293].)

New function: PyCode_NewEmpty() creates an empty code object; only the filename, function name, and first line number are required. This is useful for extension modules that are attempting to construct a more useful traceback stack. Previously such extensions needed to call PyCode_New(), which had many more arguments. (Added by Jeffrey Yasskin.)

New function: PyErr_NewExceptionWithDoc() creates a new exception class, just as the existing PyErr_NewException() does, but takes an extra char * argument containing the docstring for the new exception class. (Added by “lekma” on the Python bug tracker; bpo-7033 [https://bugs.python.org/issue7033].)

New function: PyFrame_GetLineNumber() takes a frame object and returns the line number that the frame is currently executing. Previously code would need to get the index of the bytecode instruction currently executing, and then look up the line number corresponding to that address. (Added by Jeffrey Yasskin.)

New functions: PyLong_AsLongAndOverflow() and PyLong_AsLongLongAndOverflow() approximates a Python long integer as a C long or long long. If the number is too large to fit into the output type, an overflow flag is set and returned to the caller. (Contributed by Case Van Horsen; bpo-7528 [https://bugs.python.org/issue7528] and bpo-7767 [https://bugs.python.org/issue7767].)

New function: stemming from the rewrite of string-to-float conversion, a new PyOS_string_to_double() function was added. The old PyOS_ascii_strtod() and PyOS_ascii_atof() functions are now deprecated.

New function: PySys_SetArgvEx() sets the value of sys.argv and can optionally update sys.path to include the directory containing the script named by sys.argv[0] depending on the value of an updatepath parameter.

This function was added to close a security hole for applications that embed Python. The old function, PySys_SetArgv(), would always update sys.path, and sometimes it would add the current directory. This meant that, if you ran an application embedding Python in a directory controlled by someone else, attackers could put a Trojan-horse module in the directory (say, a file named os.py) that your application would then import and run.

If you maintain a C/C++ application that embeds Python, check whether you’re calling PySys_SetArgv() and carefully consider whether the application should be using PySys_SetArgvEx() with updatepath set to false.

Security issue reported as CVE-2008-5983 [https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2008-5983]; discussed in bpo-5753 [https://bugs.python.org/issue5753], and fixed by Antoine Pitrou.

New macros: the Python header files now define the following macros: Py_ISALNUM, Py_ISALPHA, Py_ISDIGIT, Py_ISLOWER, Py_ISSPACE, Py_ISUPPER, Py_ISXDIGIT, Py_TOLOWER, and Py_TOUPPER. All of these functions are analogous to the C standard macros for classifying characters, but ignore the current locale setting, because in several places Python needs to analyze characters in a locale-independent way. (Added by Eric Smith; bpo-5793 [https://bugs.python.org/issue5793].)

Removed function: PyEval_CallObject is now only available as a macro. A function version was being kept around to preserve ABI linking compatibility, but that was in 1997; it can certainly be deleted by now. (Removed by Antoine Pitrou; bpo-8276 [https://bugs.python.org/issue8276].)

New format codes: the PyFormat_FromString(), PyFormat_FromStringV(), and PyErr_Format() functions now accept %lld and %llu format codes for displaying C’s long long types. (Contributed by Mark Dickinson; bpo-7228 [https://bugs.python.org/issue7228].)

The complicated interaction between threads and process forking has been changed. Previously, the child process created by os.fork() might fail because the child is created with only a single thread running, the thread performing the os.fork(). If other threads were holding a lock, such as Python’s import lock, when the fork was performed, the lock would still be marked as « held » in the new process. But in the child process nothing would ever release the lock, since the other threads weren’t replicated, and the child process would no longer be able to perform imports.

Python 2.7 acquires the import lock before performing an os.fork(), and will also clean up any locks created using the threading module. C extension modules that have internal locks, or that call fork() themselves, will not benefit from this clean-up.

(Fixed by Thomas Wouters; bpo-1590864 [https://bugs.python.org/issue1590864].)

The Py_Finalize() function now calls the internal threading._shutdown() function; this prevents some exceptions from being raised when an interpreter shuts down. (Patch by Adam Olsen; bpo-1722344 [https://bugs.python.org/issue1722344].)

When using the PyMemberDef structure to define attributes of a type, Python will no longer let you try to delete or set a T_STRING_INPLACE attribute.

Global symbols defined by the ctypes module are now prefixed with Py, or with _ctypes. (Implemented by Thomas Heller; bpo-3102 [https://bugs.python.org/issue3102].)

New configure option: the --with-system-expat switch allows building the pyexpat module to use the system Expat library. (Contributed by Arfrever Frehtes Taifersar Arahesis; bpo-7609 [https://bugs.python.org/issue7609].)

New configure option: the --with-valgrind option will now disable the pymalloc allocator, which is difficult for the Valgrind memory-error detector to analyze correctly. Valgrind will therefore be better at detecting memory leaks and overruns. (Contributed by James Henstridge; bpo-2422 [https://bugs.python.org/issue2422].)

New configure option: you can now supply an empty string to --with-dbmliborder= in order to disable all of the various DBM modules. (Added by Arfrever Frehtes Taifersar Arahesis; bpo-6491 [https://bugs.python.org/issue6491].)

The configure script now checks for floating-point rounding bugs on certain 32-bit Intel chips and defines a X87_DOUBLE_ROUNDING preprocessor definition. No code currently uses this definition, but it’s available if anyone wishes to use it. (Added by Mark Dickinson; bpo-2937 [https://bugs.python.org/issue2937].)

configure also now sets a LDCXXSHARED Makefile variable for supporting C++ linking. (Contributed by Arfrever Frehtes Taifersar Arahesis; bpo-1222585 [https://bugs.python.org/issue1222585].)

The build process now creates the necessary files for pkg-config support. (Contributed by Clinton Roy; bpo-3585 [https://bugs.python.org/issue3585].)

The build process now supports Subversion 1.7. (Contributed by Arfrever Frehtes Taifersar Arahesis; bpo-6094 [https://bugs.python.org/issue6094].)

Capsules

Python 3.1 adds a new C datatype, PyCapsule, for providing a C API to an extension module. A capsule is essentially the holder of a C void * pointer, and is made available as a module attribute; for example, the socket module’s API is exposed as socket.CAPI, and unicodedata exposes ucnhash_CAPI. Other extensions can import the module, access its dictionary to get the capsule object, and then get the void * pointer, which will usually point to an array of pointers to the module’s various API functions.

There is an existing data type already used for this, PyCObject, but it doesn’t provide type safety. Evil code written in pure Python could cause a segmentation fault by taking a PyCObject from module A and somehow substituting it for the PyCObject in module B. Capsules know their own name, and getting the pointer requires providing the name:

void *vtable;

if (!PyCapsule_IsValid(capsule, "mymodule.CAPI") {
        PyErr_SetString(PyExc_ValueError, "argument type invalid");
        return NULL;
}

vtable = PyCapsule_GetPointer(capsule, "mymodule.CAPI");

You are assured that vtable points to whatever you’re expecting. If a different capsule was passed in, PyCapsule_IsValid() would detect the mismatched name and return false. Refer to Providing a C API for an Extension Module for more information on using these objects.

Python 2.7 now uses capsules internally to provide various extension-module APIs, but the PyCObject_AsVoidPtr() was modified to handle capsules, preserving compile-time compatibility with the CObject interface. Use of PyCObject_AsVoidPtr() will signal a PendingDeprecationWarning, which is silent by default.

Implemented in Python 3.1 and backported to 2.7 by Larry Hastings; discussed in bpo-5630 [https://bugs.python.org/issue5630].

Port-Specific Changes: Windows

The msvcrt module now contains some constants from the crtassem.h header file: CRT_ASSEMBLY_VERSION, VC_ASSEMBLY_PUBLICKEYTOKEN, and LIBRARIES_ASSEMBLY_NAME_PREFIX. (Contributed by David Cournapeau; bpo-4365 [https://bugs.python.org/issue4365].)

The _winreg module for accessing the registry now implements the CreateKeyEx() and DeleteKeyEx() functions, extended versions of previously-supported functions that take several extra arguments. The DisableReflectionKey(), EnableReflectionKey(), and QueryReflectionKey() were also tested and documented. (Implemented by Brian Curtin: bpo-7347 [https://bugs.python.org/issue7347].)

The new _beginthreadex() API is used to start threads, and the native thread-local storage functions are now used. (Contributed by Kristján Valur Jónsson; bpo-3582 [https://bugs.python.org/issue3582].)

The os.kill() function now works on Windows. The signal value can be the constants CTRL_C_EVENT, CTRL_BREAK_EVENT, or any integer. The first two constants will send Control-C and Control-Break keystroke events to subprocesses; any other value will use the TerminateProcess() API. (Contributed by Miki Tebeka; bpo-1220212 [https://bugs.python.org/issue1220212].)

The os.listdir() function now correctly fails for an empty path. (Fixed by Hirokazu Yamamoto; bpo-5913 [https://bugs.python.org/issue5913].)

The mimelib module will now read the MIME database from the Windows registry when initializing. (Patch by Gabriel Genellina; bpo-4969 [https://bugs.python.org/issue4969].)

Port-Specific Changes: Mac OS X

The path /Library/Python/2.7/site-packages is now appended to sys.path, in order to share added packages between the system installation and a user-installed copy of the same version. (Changed by Ronald Oussoren; bpo-4865 [https://bugs.python.org/issue4865].)

Modifié dans la version 2.7.13: As of 2.7.13, this change was removed. /Library/Python/2.7/site-packages, the site-packages directory used by the Apple-supplied system Python 2.7 is no longer appended to sys.path for user-installed Pythons such as from the python.org installers. As of macOS 10.12, Apple changed how the system site-packages directory is configured, which could cause installation of pip components, like setuptools, to fail. Packages installed for the system Python will no longer be shared with user-installed Pythons. (bpo-28440 [https://bugs.python.org/issue28440])

Port-Specific Changes: FreeBSD

FreeBSD 7.1’s SO_SETFIB constant, used with getsockopt()/setsockopt() to select an alternate routing table, is now available in the socket module. (Added by Kyle VanderBeek; bpo-8235 [https://bugs.python.org/issue8235].)

Autres changements et corrections

Two benchmark scripts, iobench and ccbench, were added to the Tools directory. iobench measures the speed of the built-in file I/O objects returned by open() while performing various operations, and ccbench is a concurrency benchmark that tries to measure computing throughput, thread switching latency, and IO processing bandwidth when performing several tasks using a varying number of threads.

The Tools/i18n/msgfmt.py script now understands plural forms in .po files. (Fixed by Martin von Löwis; bpo-5464 [https://bugs.python.org/issue5464].)

When importing a module from a .pyc or .pyo file with an existing .py counterpart, the co_filename attributes of the resulting code objects are overwritten when the original filename is obsolete. This can happen if the file has been renamed, moved, or is accessed through different paths. (Patch by Ziga Seilnacht and Jean-Paul Calderone; bpo-1180193 [https://bugs.python.org/issue1180193].)

The regrtest.py script now takes a --randseed= switch that takes an integer that will be used as the random seed for the -r option that executes tests in random order. The -r option also reports the seed that was used (Added by Collin Winter.)

Another regrtest.py switch is -j, which takes an integer specifying how many tests run in parallel. This allows reducing the total runtime on multi-core machines. This option is compatible with several other options, including the -R switch which is known to produce long runtimes. (Added by Antoine Pitrou, bpo-6152 [https://bugs.python.org/issue6152].) This can also be used with a new -F switch that runs selected tests in a loop until they fail. (Added by Antoine Pitrou; bpo-7312 [https://bugs.python.org/issue7312].)

When executed as a script, the py_compile.py module now accepts '-' as an argument, which will read standard input for the list of filenames to be compiled. (Contributed by Piotr Ożarowski; bpo-8233 [https://bugs.python.org/issue8233].)

Portage vers Python 2.7

This section lists previously described changes and other bugfixes that may require changes to your code:

The range() function processes its arguments more consistently; it will now call __int__() on non-float, non-integer arguments that are supplied to it. (Fixed by Alexander Belopolsky; bpo-1533 [https://bugs.python.org/issue1533].)

The string format() method changed the default precision used for floating-point and complex numbers from 6 decimal places to 12, which matches the precision used by str(). (Changed by Eric Smith; bpo-5920 [https://bugs.python.org/issue5920].)

Because of an optimization for the with statement, the special methods __enter__() and __exit__() must belong to the object’s type, and cannot be directly attached to the object’s instance. This affects new-style classes (derived from object) and C extension types. (bpo-6101 [https://bugs.python.org/issue6101].)

Due to a bug in Python 2.6, the exc_value parameter to __exit__() methods was often the string representation of the exception, not an instance. This was fixed in 2.7, so exc_value will be an instance as expected. (Fixed by Florent Xicluna; bpo-7853 [https://bugs.python.org/issue7853].)

When a restricted set of attributes were set using __slots__, deleting an unset attribute would not raise AttributeError as you would expect. Fixed by Benjamin Peterson; bpo-7604 [https://bugs.python.org/issue7604].)

In the standard library:

Operations with datetime instances that resulted in a year falling outside the supported range didn’t always raise OverflowError. Such errors are now checked more carefully and will now raise the exception. (Reported by Mark Leander, patch by Anand B. Pillai and Alexander Belopolsky; bpo-7150 [https://bugs.python.org/issue7150].)

When using Decimal instances with a string’s format() method, the default alignment was previously left-alignment. This has been changed to right-alignment, which might change the output of your programs. (Changed by Mark Dickinson; bpo-6857 [https://bugs.python.org/issue6857].)

Comparisons involving a signaling NaN value (or sNAN) now signal InvalidOperation instead of silently returning a true or false value depending on the comparison operator. Quiet NaN values (or NaN) are now hashable. (Fixed by Mark Dickinson; bpo-7279 [https://bugs.python.org/issue7279].)

The ElementTree library, xml.etree, no longer escapes ampersands and angle brackets when outputting an XML processing instruction (which looks like <?xml-stylesheet href= »#style1 »?>) or comment (which looks like <!– comment –>). (Patch by Neil Muller; bpo-2746 [https://bugs.python.org/issue2746].)

The readline() method of StringIO objects now does nothing when a negative length is requested, as other file-like objects do. (bpo-7348 [https://bugs.python.org/issue7348]).

The syslog module will now use the value of sys.argv[0] as the identifier instead of the previous default value of 'python'. (Changed by Sean Reifschneider; bpo-8451 [https://bugs.python.org/issue8451].)

The tarfile module’s default error handling has changed, to no longer suppress fatal errors. The default error level was previously 0, which meant that errors would only result in a message being written to the debug log, but because the debug log is not activated by default, these errors go unnoticed. The default error level is now 1, which raises an exception if there’s an error. (Changed by Lars Gustäbel; bpo-7357 [https://bugs.python.org/issue7357].)

The urlparse module’s urlsplit() now handles unknown URL schemes in a fashion compliant with RFC 3986 [https://tools.ietf.org/html/rfc3986.html]: if the URL is of the form "<something>://...", the text before the :// is treated as the scheme, even if it’s a made-up scheme that the module doesn’t know about. This change may break code that worked around the old behaviour. For example, Python 2.6.4 or 2.5 will return the following:

>>> import urlparse
>>> urlparse.urlsplit('invented://host/filename?query')
('invented', '', '//host/filename?query', '', '')

Python 2.7 (and Python 2.6.5) will return:

>>> import urlparse
>>> urlparse.urlsplit('invented://host/filename?query')
('invented', 'host', '/filename?query', '', '')

(Python 2.7 actually produces slightly different output, since it returns a named tuple instead of a standard tuple.)

For C extensions:

C extensions that use integer format codes with the PyArg_Parse* family of functions will now raise a TypeError exception instead of triggering a DeprecationWarning (bpo-5080 [https://bugs.python.org/issue5080]).

Use the new PyOS_string_to_double() function instead of the old PyOS_ascii_strtod() and PyOS_ascii_atof() functions, which are now deprecated.

For applications that embed Python:

The PySys_SetArgvEx() function was added, letting applications close a security hole when the existing PySys_SetArgv() function was used. Check whether you’re calling PySys_SetArgv() and carefully consider whether the application should be using PySys_SetArgvEx() with updatepath set to false.

New Features Added to Python 2.7 Maintenance Releases

New features may be added to Python 2.7 maintenance releases when the situation genuinely calls for it. Any such additions must go through the Python Enhancement Proposal process, and make a compelling case for why they can’t be adequately addressed by either adding the new feature solely to Python 3, or else by publishing it on the Python Package Index.

In addition to the specific proposals listed below, there is a general exemption allowing new -3 warnings to be added in any Python 2.7 maintenance release.

Two new environment variables for debug mode

In debug mode, the [xxx refs] statistic is not written by default, the PYTHONSHOWREFCOUNT environment variable now must also be set. (Contributed by Victor Stinner; bpo-31733 [https://bugs.python.org/issue31733].)

When Python is compiled with COUNT_ALLOC defined, allocation counts are no longer dumped by default anymore: the PYTHONSHOWALLOCCOUNT environment variable must now also be set. Moreover, allocation counts are now dumped into stderr, rather than stdout. (Contributed by Victor Stinner; bpo-31692 [https://bugs.python.org/issue31692].)

Nouveau dans la version 2.7.15.

PEP 434: IDLE Enhancement Exception for All Branches

PEP 434 [https://www.python.org/dev/peps/pep-0434] describes a general exemption for changes made to the IDLE development environment shipped along with Python. This exemption makes it possible for the IDLE developers to provide a more consistent user experience across all supported versions of Python 2 and 3.

For details of any IDLE changes, refer to the NEWS file for the specific release.

PEP 466: Network Security Enhancements for Python 2.7

PEP 466 [https://www.python.org/dev/peps/pep-0466] describes a number of network security enhancement proposals that have been approved for inclusion in Python 2.7 maintenance releases, with the first of those changes appearing in the Python 2.7.7 release.

PEP 466 [https://www.python.org/dev/peps/pep-0466] related features added in Python 2.7.7:

hmac.compare_digest() was backported from Python 3 to make a timing attack resistant comparison operation available to Python 2 applications. (Contributed by Alex Gaynor; bpo-21306 [https://bugs.python.org/issue21306].)

OpenSSL 1.0.1g was upgraded in the official Windows installers published on python.org. (Contributed by Zachary Ware; bpo-21462 [https://bugs.python.org/issue21462].)

PEP 466 [https://www.python.org/dev/peps/pep-0466] related features added in Python 2.7.8:

hashlib.pbkdf2_hmac() was backported from Python 3 to make a hashing algorithm suitable for secure password storage broadly available to Python 2 applications. (Contributed by Alex Gaynor; bpo-21304 [https://bugs.python.org/issue21304].)

OpenSSL 1.0.1h was upgraded for the official Windows installers published on python.org. (contributed by Zachary Ware in bpo-21671 [https://bugs.python.org/issue21671] for CVE-2014-0224)

PEP 466 [https://www.python.org/dev/peps/pep-0466] related features added in Python 2.7.9:

Most of Python 3.4’s ssl module was backported. This means ssl now supports Server Name Indication, TLS1.x settings, access to the platform certificate store, the SSLContext class, and other features. (Contributed by Alex Gaynor and David Reid; bpo-21308 [https://bugs.python.org/issue21308].)

Refer to the « Version added: 2.7.9 » notes in the module documentation for specific details.

os.urandom() was changed to cache a file descriptor to /dev/urandom instead of reopening /dev/urandom on every call. (Contributed by Alex Gaynor; bpo-21305 [https://bugs.python.org/issue21305].)

hashlib.algorithms_guaranteed and hashlib.algorithms_available were backported from Python 3 to make it easier for Python 2 applications to select the strongest available hash algorithm. (Contributed by Alex Gaynor in bpo-21307 [https://bugs.python.org/issue21307])

PEP 477: Backport ensurepip (PEP 453) to Python 2.7

PEP 477 [https://www.python.org/dev/peps/pep-0477] approves the inclusion of the PEP 453 [https://www.python.org/dev/peps/pep-0453] ensurepip module and the improved documentation that was enabled by it in the Python 2.7 maintenance releases, appearing first in the Python 2.7.9 release.

Bootstrapping pip By Default

The new ensurepip module (defined in PEP 453 [https://www.python.org/dev/peps/pep-0453]) provides a standard cross-platform mechanism to bootstrap the pip installer into Python installations. The version of pip included with Python 2.7.9 is pip 1.5.6, and future 2.7.x maintenance releases will update the bundled version to the latest version of pip that is available at the time of creating the release candidate.

By default, the commands pip, pipX and pipX.Y will be installed on all platforms (where X.Y stands for the version of the Python installation), along with the pip Python package and its dependencies.

For CPython source builds on POSIX systems, the make install and make altinstall commands do not bootstrap pip by default. This behaviour can be controlled through configure options, and overridden through Makefile options.

On Windows and Mac OS X, the CPython installers now default to installing pip along with CPython itself (users may opt out of installing it during the installation process). Window users will need to opt in to the automatic PATH modifications to have pip available from the command line by default, otherwise it can still be accessed through the Python launcher for Windows as py -m pip.

As discussed in the PEP [https://www.python.org/dev/peps/pep-0477/#disabling-ensurepip-by-downstream-distributors], platform packagers may choose not to install these commands by default, as long as, when invoked, they provide clear and simple directions on how to install them on that platform (usually using the system package manager).

Documentation Changes

As part of this change, the Installation de modules Python and Distribuer des modules Python sections of the documentation have been completely redesigned as short getting started and FAQ documents. Most packaging documentation has now been moved out to the Python Packaging Authority maintained Python Packaging User Guide [http://packaging.python.org] and the documentation of the individual projects.

However, as this migration is currently still incomplete, the legacy versions of those guides remaining available as Installation des modules python (Version historique) and Distribuer des modules Python (Version historique).

Voir aussi

PEP 453 [https://www.python.org/dev/peps/pep-0453] – Explicit bootstrapping of pip in Python installations

PEP written by Donald Stufft and Nick Coghlan, implemented by Donald Stufft, Nick Coghlan, Martin von Löwis and Ned Deily.

PEP 476: Enabling certificate verification by default for stdlib http clients

PEP 476 [https://www.python.org/dev/peps/pep-0476] updated httplib and modules which use it, such as urllib2 and xmlrpclib, to now verify that the server presents a certificate which is signed by a Certificate Authority in the platform trust store and whose hostname matches the hostname being requested by default, significantly improving security for many applications. This change was made in the Python 2.7.9 release.

For applications which require the old previous behavior, they can pass an alternate context:

import urllib2
import ssl

# This disables all verification
context = ssl._create_unverified_context()

# This allows using a specific certificate for the host, which doesn't need
# to be in the trust store
context = ssl.create_default_context(cafile="/path/to/file.crt")

urllib2.urlopen("https://invalid-cert", context=context)

PEP 493: HTTPS verification migration tools for Python 2.7

PEP 493 [https://www.python.org/dev/peps/pep-0493] provides additional migration tools to support a more incremental infrastructure upgrade process for environments containing applications and services relying on the historically permissive processing of server certificates when establishing client HTTPS connections. These additions were made in the Python 2.7.12 release.

These tools are intended for use in cases where affected applications and services can’t be modified to explicitly pass a more permissive SSL context when establishing the connection.

For applications and services which can’t be modified at all, the new PYTHONHTTPSVERIFY environment variable may be set to 0 to revert an entire Python process back to the default permissive behaviour of Python 2.7.8 and earlier.

For cases where the connection establishment code can’t be modified, but the overall application can be, the new ssl._https_verify_certificates() function can be used to adjust the default behaviour at runtime.

New make regen-all build target

To simplify cross-compilation, and to ensure that CPython can reliably be compiled without requiring an existing version of Python to already be available, the autotools-based build system no longer attempts to implicitly recompile generated files based on file modification times.

Instead, a new make regen-all command has been added to force regeneration of these files when desired (e.g. after an initial version of Python has already been built based on the pregenerated versions).

More selective regeneration targets are also defined - see Makefile.pre.in [https://github.com/python/cpython/tree/3.6/Makefile.pre.in] for details.

(Contributed by Victor Stinner in bpo-23404 [https://bugs.python.org/issue23404].)

Nouveau dans la version 2.7.14.

Removal of make touch build target

The make touch build target previously used to request implicit regeneration of generated files by updating their modification times has been removed.

It has been replaced by the new make regen-all target.

(Contributed by Victor Stinner in bpo-23404 [https://bugs.python.org/issue23404].)

Modifié dans la version 2.7.14.

Remerciements

The author would like to thank the following people for offering suggestions, corrections and assistance with various drafts of this article: Nick Coghlan, Philip Jenvey, Ryan Lovett, R. David Murray, Hugh Secker-Walker.

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Nouveautés de Python 2.6

Auteur

A.M. Kuchling (amk at amk.ca)

This article explains the new features in Python 2.6, released on October 1 2008. The release schedule is described in PEP 361 [https://www.python.org/dev/peps/pep-0361].

The major theme of Python 2.6 is preparing the migration path to Python 3.0, a major redesign of the language. Whenever possible, Python 2.6 incorporates new features and syntax from 3.0 while remaining compatible with existing code by not removing older features or syntax. When it’s not possible to do that, Python 2.6 tries to do what it can, adding compatibility functions in a future_builtins module and a -3 switch to warn about usages that will become unsupported in 3.0.

Some significant new packages have been added to the standard library, such as the multiprocessing and json modules, but there aren’t many new features that aren’t related to Python 3.0 in some way.

Python 2.6 also sees a number of improvements and bugfixes throughout the source. A search through the change logs finds there were 259 patches applied and 612 bugs fixed between Python 2.5 and 2.6. Both figures are likely to be underestimates.

This article doesn’t attempt to provide a complete specification of the new features, but instead provides a convenient overview. For full details, you should refer to the documentation for Python 2.6. If you want to understand the rationale for the design and implementation, refer to the PEP for a particular new feature. Whenever possible, « What’s New in Python » links to the bug/patch item for each change.

Python 3.0

The development cycle for Python versions 2.6 and 3.0 was synchronized, with the alpha and beta releases for both versions being made on the same days. The development of 3.0 has influenced many features in 2.6.

Python 3.0 is a far-ranging redesign of Python that breaks compatibility with the 2.x series. This means that existing Python code will need some conversion in order to run on Python 3.0. However, not all the changes in 3.0 necessarily break compatibility. In cases where new features won’t cause existing code to break, they’ve been backported to 2.6 and are described in this document in the appropriate place. Some of the 3.0-derived features are:

A __complex__() method for converting objects to a complex number.

Alternate syntax for catching exceptions: except TypeError as exc.

The addition of functools.reduce() as a synonym for the built-in reduce() function.

Python 3.0 adds several new built-in functions and changes the semantics of some existing builtins. Functions that are new in 3.0 such as bin() have simply been added to Python 2.6, but existing builtins haven’t been changed; instead, the future_builtins module has versions with the new 3.0 semantics. Code written to be compatible with 3.0 can do from future_builtins import hex, map as necessary.

A new command-line switch, -3, enables warnings about features that will be removed in Python 3.0. You can run code with this switch to see how much work will be necessary to port code to 3.0. The value of this switch is available to Python code as the boolean variable sys.py3kwarning, and to C extension code as Py_Py3kWarningFlag.

Voir aussi

The 3xxx series of PEPs, which contains proposals for Python 3.0. PEP 3000 [https://www.python.org/dev/peps/pep-3000] describes the development process for Python 3.0. Start with PEP 3100 [https://www.python.org/dev/peps/pep-3100] that describes the general goals for Python 3.0, and then explore the higher-numbered PEPS that propose specific features.

Changes to the Development Process

While 2.6 was being developed, the Python development process underwent two significant changes: we switched from SourceForge’s issue tracker to a customized Roundup installation, and the documentation was converted from LaTeX to reStructuredText.

New Issue Tracker: Roundup

For a long time, the Python developers had been growing increasingly annoyed by SourceForge’s bug tracker. SourceForge’s hosted solution doesn’t permit much customization; for example, it wasn’t possible to customize the life cycle of issues.

The infrastructure committee of the Python Software Foundation therefore posted a call for issue trackers, asking volunteers to set up different products and import some of the bugs and patches from SourceForge. Four different trackers were examined: Jira [https://www.atlassian.com/software/jira/], Launchpad [https://launchpad.net/], Roundup [http://roundup.sourceforge.net/], and Trac [https://trac.edgewall.org/]. The committee eventually settled on Jira and Roundup as the two candidates. Jira is a commercial product that offers no-cost hosted instances to free-software projects; Roundup is an open-source project that requires volunteers to administer it and a server to host it.

After posting a call for volunteers, a new Roundup installation was set up at https://bugs.python.org. One installation of Roundup can host multiple trackers, and this server now also hosts issue trackers for Jython and for the Python web site. It will surely find other uses in the future. Where possible, this edition of « What’s New in Python » links to the bug/patch item for each change.

Hosting of the Python bug tracker is kindly provided by Upfront Systems [http://www.upfrontsystems.co.za/] of Stellenbosch, South Africa. Martin von Löwis put a lot of effort into importing existing bugs and patches from SourceForge; his scripts for this import operation are at http://svn.python.org/view/tracker/importer/ and may be useful to other projects wishing to move from SourceForge to Roundup.

Voir aussi

https://bugs.python.org

The Python bug tracker.

http://bugs.jython.org:

The Jython bug tracker.

http://roundup.sourceforge.net/

Roundup downloads and documentation.

http://svn.python.org/view/tracker/importer/

Martin von Löwis’s conversion scripts.

New Documentation Format: reStructuredText Using Sphinx

The Python documentation was written using LaTeX since the project started around 1989. In the 1980s and early 1990s, most documentation was printed out for later study, not viewed online. LaTeX was widely used because it provided attractive printed output while remaining straightforward to write once the basic rules of the markup were learned.

Today LaTeX is still used for writing publications destined for printing, but the landscape for programming tools has shifted. We no longer print out reams of documentation; instead, we browse through it online and HTML has become the most important format to support. Unfortunately, converting LaTeX to HTML is fairly complicated and Fred L. Drake Jr., the long-time Python documentation editor, spent a lot of time maintaining the conversion process. Occasionally people would suggest converting the documentation into SGML and later XML, but performing a good conversion is a major task and no one ever committed the time required to finish the job.

During the 2.6 development cycle, Georg Brandl put a lot of effort into building a new toolchain for processing the documentation. The resulting package is called Sphinx, and is available from http://sphinx-doc.org/.

Sphinx concentrates on HTML output, producing attractively styled and modern HTML; printed output is still supported through conversion to LaTeX. The input format is reStructuredText, a markup syntax supporting custom extensions and directives that is commonly used in the Python community.

Sphinx is a standalone package that can be used for writing, and almost two dozen other projects (listed on the Sphinx web site [http://sphinx-doc.org/examples.html]) have adopted Sphinx as their documentation tool.

Voir aussi

Documenting Python [https://devguide.python.org/documenting/]

Describes how to write for Python’s documentation.

Sphinx [http://sphinx-doc.org/]

Documentation and code for the Sphinx toolchain.

Docutils [http://docutils.sourceforge.net]

The underlying reStructuredText parser and toolset.

PEP 343: The “with” statement

The previous version, Python 2.5, added the “with” statement as an optional feature, to be enabled by a from __future__ import with_statement directive. In 2.6 the statement no longer needs to be specially enabled; this means that with is now always a keyword. The rest of this section is a copy of the corresponding section from the « What’s New in Python 2.5 » document; if you’re familiar with the “with” statement from Python 2.5, you can skip this section.

The “with” statement clarifies code that previously would use try...finally blocks to ensure that clean-up code is executed. In this section, I’ll discuss the statement as it will commonly be used. In the next section, I’ll examine the implementation details and show how to write objects for use with this statement.

The “with” statement is a control-flow structure whose basic structure is:

with expression [as variable]:
    with-block

The expression is evaluated, and it should result in an object that supports the context management protocol (that is, has __enter__() and __exit__() methods).

The object’s __enter__() is called before with-block is executed and therefore can run set-up code. It also may return a value that is bound to the name variable, if given. (Note carefully that variable is not assigned the result of expression.)

After execution of the with-block is finished, the object’s __exit__() method is called, even if the block raised an exception, and can therefore run clean-up code.

Some standard Python objects now support the context management protocol and can be used with the “with” statement. File objects are one example:

with open('/etc/passwd', 'r') as f:
    for line in f:
        print line
        ... more processing code ...

After this statement has executed, the file object in f will have been automatically closed, even if the for loop raised an exception part-way through the block.

Note

In this case, f is the same object created by open(), because file.__enter__() returns self.

The threading module’s locks and condition variables also support the “with” statement:

lock = threading.Lock()
with lock:
    # Critical section of code
    ...

The lock is acquired before the block is executed and always released once the block is complete.

The localcontext() function in the decimal module makes it easy to save and restore the current decimal context, which encapsulates the desired precision and rounding characteristics for computations:

from decimal import Decimal, Context, localcontext

# Displays with default precision of 28 digits
v = Decimal('578')
print v.sqrt()

with localcontext(Context(prec=16)):
    # All code in this block uses a precision of 16 digits.
    # The original context is restored on exiting the block.
    print v.sqrt()

Écrire des gestionnaires de contexte

Under the hood, the “with” statement is fairly complicated. Most people will only use “with” in company with existing objects and don’t need to know these details, so you can skip the rest of this section if you like. Authors of new objects will need to understand the details of the underlying implementation and should keep reading.

A high-level explanation of the context management protocol is:

The expression is evaluated and should result in an object called a « context manager ». The context manager must have __enter__() and __exit__() methods.

The context manager’s __enter__() method is called. The value returned is assigned to VAR. If no as VAR clause is present, the value is simply discarded.

Le code dans BLOCK est exécuté.

If BLOCK raises an exception, the context manager’s __exit__() method is called with three arguments, the exception details (type, value, traceback, the same values returned by sys.exc_info(), which can also be None if no exception occurred). The method’s return value controls whether an exception is re-raised: any false value re-raises the exception, and True will result in suppressing it. You’ll only rarely want to suppress the exception, because if you do the author of the code containing the “with” statement will never realize anything went wrong.

If BLOCK didn’t raise an exception, the __exit__() method is still called, but type, value, and traceback are all None.

Let’s think through an example. I won’t present detailed code but will only sketch the methods necessary for a database that supports transactions.

(For people unfamiliar with database terminology: a set of changes to the database are grouped into a transaction. Transactions can be either committed, meaning that all the changes are written into the database, or rolled back, meaning that the changes are all discarded and the database is unchanged. See any database textbook for more information.)

Let’s assume there’s an object representing a database connection. Our goal will be to let the user write code like this:

db_connection = DatabaseConnection()
with db_connection as cursor:
    cursor.execute('insert into ...')
    cursor.execute('delete from ...')
    # ... more operations ...

The transaction should be committed if the code in the block runs flawlessly or rolled back if there’s an exception. Here’s the basic interface for DatabaseConnection that I’ll assume:

class DatabaseConnection:
    # Database interface
    def cursor(self):
        "Returns a cursor object and starts a new transaction"
    def commit(self):
        "Commits current transaction"
    def rollback(self):
        "Rolls back current transaction"

The __enter__() method is pretty easy, having only to start a new transaction. For this application the resulting cursor object would be a useful result, so the method will return it. The user can then add as cursor to their “with” statement to bind the cursor to a variable name.

class DatabaseConnection:
    ...
    def __enter__(self):
        # Code to start a new transaction
        cursor = self.cursor()
        return cursor

The __exit__() method is the most complicated because it’s where most of the work has to be done. The method has to check if an exception occurred. If there was no exception, the transaction is committed. The transaction is rolled back if there was an exception.

In the code below, execution will just fall off the end of the function, returning the default value of None. None is false, so the exception will be re-raised automatically. If you wished, you could be more explicit and add a return statement at the marked location.

class DatabaseConnection:
    ...
    def __exit__(self, type, value, tb):
        if tb is None:
            # No exception, so commit
            self.commit()
        else:
            # Exception occurred, so rollback.
            self.rollback()
            # return False

Le module contextlib

The contextlib module provides some functions and a decorator that are useful when writing objects for use with the “with” statement.

The decorator is called contextmanager(), and lets you write a single generator function instead of defining a new class. The generator should yield exactly one value. The code up to the yield will be executed as the __enter__() method, and the value yielded will be the method’s return value that will get bound to the variable in the “with” statement’s as clause, if any. The code after the yield will be executed in the __exit__() method. Any exception raised in the block will be raised by the yield statement.

Using this decorator, our database example from the previous section could be written as:

from contextlib import contextmanager

@contextmanager
def db_transaction(connection):
    cursor = connection.cursor()
    try:
        yield cursor
    except:
        connection.rollback()
        raise
    else:
        connection.commit()

db = DatabaseConnection()
with db_transaction(db) as cursor:
    ...

The contextlib module also has a nested(mgr1, mgr2, ...) function that combines a number of context managers so you don’t need to write nested “with” statements. In this example, the single “with” statement both starts a database transaction and acquires a thread lock:

lock = threading.Lock()
with nested (db_transaction(db), lock) as (cursor, locked):
    ...

Finally, the closing() function returns its argument so that it can be bound to a variable, and calls the argument’s .close() method at the end of the block.

import urllib, sys
from contextlib import closing

with closing(urllib.urlopen('http://www.yahoo.com')) as f:
    for line in f:
        sys.stdout.write(line)

Voir aussi

PEP 343 [https://www.python.org/dev/peps/pep-0343] - The « with » statement

PEP written by Guido van Rossum and Nick Coghlan; implemented by Mike Bland, Guido van Rossum, and Neal Norwitz. The PEP shows the code generated for a “with” statement, which can be helpful in learning how the statement works.

The documentation for the contextlib module.

PEP 366: Explicit Relative Imports From a Main Module

Python’s -m switch allows running a module as a script. When you ran a module that was located inside a package, relative imports didn’t work correctly.

The fix for Python 2.6 adds a __package__ attribute to modules. When this attribute is present, relative imports will be relative to the value of this attribute instead of the __name__ attribute.

PEP 302-style importers can then set __package__ as necessary. The runpy module that implements the -m switch now does this, so relative imports will now work correctly in scripts running from inside a package.

PEP 370: Per-user site-packages Directory

When you run Python, the module search path sys.path usually includes a directory whose path ends in "site-packages". This directory is intended to hold locally-installed packages available to all users using a machine or a particular site installation.

Python 2.6 introduces a convention for user-specific site directories. The directory varies depending on the platform:

UNIX et Mac OS X : ~/.local/

Windows : %APPDATA%/Python

Within this directory, there will be version-specific subdirectories, such as lib/python2.6/site-packages on Unix/Mac OS and Python26/site-packages on Windows.

If you don’t like the default directory, it can be overridden by an environment variable. PYTHONUSERBASE sets the root directory used for all Python versions supporting this feature. On Windows, the directory for application-specific data can be changed by setting the APPDATA environment variable. You can also modify the site.py file for your Python installation.

The feature can be disabled entirely by running Python with the -s option or setting the PYTHONNOUSERSITE environment variable.

Voir aussi

PEP 370 [https://www.python.org/dev/peps/pep-0370] - Per-user site-packages Directory

PEP written and implemented by Christian Heimes.

PEP 371: The multiprocessing Package

The new multiprocessing package lets Python programs create new processes that will perform a computation and return a result to the parent. The parent and child processes can communicate using queues and pipes, synchronize their operations using locks and semaphores, and can share simple arrays of data.

The multiprocessing module started out as an exact emulation of the threading module using processes instead of threads. That goal was discarded along the path to Python 2.6, but the general approach of the module is still similar. The fundamental class is the Process, which is passed a callable object and a collection of arguments. The start() method sets the callable running in a subprocess, after which you can call the is_alive() method to check whether the subprocess is still running and the join() method to wait for the process to exit.

Here’s a simple example where the subprocess will calculate a factorial. The function doing the calculation is written strangely so that it takes significantly longer when the input argument is a multiple of 4.

import time
from multiprocessing import Process, Queue

def factorial(queue, N):
    "Compute a factorial."
    # If N is a multiple of 4, this function will take much longer.
    if (N % 4) == 0:
        time.sleep(.05 * N/4)

    # Calculate the result
    fact = 1L
    for i in range(1, N+1):
        fact = fact * i

    # Put the result on the queue
    queue.put(fact)

if __name__ == '__main__':
    queue = Queue()

    N = 5

    p = Process(target=factorial, args=(queue, N))
    p.start()
    p.join()

    result = queue.get()
    print 'Factorial', N, '=', result

A Queue is used to communicate the result of the factorial. The Queue object is stored in a global variable. The child process will use the value of the variable when the child was created; because it’s a Queue, parent and child can use the object to communicate. (If the parent were to change the value of the global variable, the child’s value would be unaffected, and vice versa.)

Two other classes, Pool and Manager, provide higher-level interfaces. Pool will create a fixed number of worker processes, and requests can then be distributed to the workers by calling apply() or apply_async() to add a single request, and map() or map_async() to add a number of requests. The following code uses a Pool to spread requests across 5 worker processes and retrieve a list of results:

from multiprocessing import Pool

def factorial(N, dictionary):
    "Compute a factorial."
    ...
p = Pool(5)
result = p.map(factorial, range(1, 1000, 10))
for v in result:
    print v

Ceci produit l’affichage suivant :

1
39916800
51090942171709440000
8222838654177922817725562880000000
33452526613163807108170062053440751665152000000000
...

The other high-level interface, the Manager class, creates a separate server process that can hold master copies of Python data structures. Other processes can then access and modify these data structures using proxy objects. The following example creates a shared dictionary by calling the dict() method; the worker processes then insert values into the dictionary. (Locking is not done for you automatically, which doesn’t matter in this example. Manager’s methods also include Lock(), RLock(), and Semaphore() to create shared locks.)

import time
from multiprocessing import Pool, Manager

def factorial(N, dictionary):
    "Compute a factorial."
    # Calculate the result
    fact = 1L
    for i in range(1, N+1):
        fact = fact * i

    # Store result in dictionary
    dictionary[N] = fact

if __name__ == '__main__':
    p = Pool(5)
    mgr = Manager()
    d = mgr.dict()         # Create shared dictionary

    # Run tasks using the pool
    for N in range(1, 1000, 10):
        p.apply_async(factorial, (N, d))

    # Mark pool as closed -- no more tasks can be added.
    p.close()

    # Wait for tasks to exit
    p.join()

    # Output results
    for k, v in sorted(d.items()):
        print k, v

This will produce the output:

1 1
11 39916800
21 51090942171709440000
31 8222838654177922817725562880000000
41 33452526613163807108170062053440751665152000000000
51 15511187532873822802242430164693032110632597200169861120000...

Voir aussi

The documentation for the multiprocessing module.

PEP 371 [https://www.python.org/dev/peps/pep-0371] - Addition of the multiprocessing package

PEP written by Jesse Noller and Richard Oudkerk; implemented by Richard Oudkerk and Jesse Noller.

PEP 3101: Advanced String Formatting

In Python 3.0, the % operator is supplemented by a more powerful string formatting method, format(). Support for the str.format() method has been backported to Python 2.6.

In 2.6, both 8-bit and Unicode strings have a .format() method that treats the string as a template and takes the arguments to be formatted. The formatting template uses curly brackets ({, }) as special characters:

>>> # Substitute positional argument 0 into the string.
>>> "User ID: {0}".format("root")
'User ID: root'
>>> # Use the named keyword arguments
>>> "User ID: {uid}   Last seen: {last_login}".format(
...    uid="root",
...    last_login = "5 Mar 2008 07:20")
'User ID: root   Last seen: 5 Mar 2008 07:20'

Curly brackets can be escaped by doubling them:

>>> "Empty dict: {{}}".format()
"Empty dict: {}"

Field names can be integers indicating positional arguments, such as {0}, {1}, etc. or names of keyword arguments. You can also supply compound field names that read attributes or access dictionary keys:

>>> import sys
>>> print 'Platform: {0.platform}\nPython version: {0.version}'.format(sys)
Platform: darwin
Python version: 2.6a1+ (trunk:61261M, Mar  5 2008, 20:29:41)
[GCC 4.0.1 (Apple Computer, Inc. build 5367)]'

>>> import mimetypes
>>> 'Content-type: {0[.mp4]}'.format(mimetypes.types_map)
'Content-type: video/mp4'

Note that when using dictionary-style notation such as [.mp4], you don’t need to put any quotation marks around the string; it will look up the value using .mp4 as the key. Strings beginning with a number will be converted to an integer. You can’t write more complicated expressions inside a format string.

So far we’ve shown how to specify which field to substitute into the resulting string. The precise formatting used is also controllable by adding a colon followed by a format specifier. For example:

>>> # Field 0: left justify, pad to 15 characters
>>> # Field 1: right justify, pad to 6 characters
>>> fmt = '{0:15} ${1:>6}'
>>> fmt.format('Registration', 35)
'Registration    $    35'
>>> fmt.format('Tutorial', 50)
'Tutorial        $    50'
>>> fmt.format('Banquet', 125)
'Banquet         $   125'

Format specifiers can reference other fields through nesting:

>>> fmt = '{0:{1}}'
>>> width = 15
>>> fmt.format('Invoice #1234', width)
'Invoice #1234  '
>>> width = 35
>>> fmt.format('Invoice #1234', width)
'Invoice #1234                      '

The alignment of a field within the desired width can be specified:

Caractère

Effect

< (par défaut)

Left-align

>

Right-align

^

Center

=

(For numeric types only) Pad after the sign.

Format specifiers can also include a presentation type, which controls how the value is formatted. For example, floating-point numbers can be formatted as a general number or in exponential notation:

>>> '{0:g}'.format(3.75)
'3.75'
>>> '{0:e}'.format(3.75)
'3.750000e+00'

A variety of presentation types are available. Consult the 2.6 documentation for a complete list; here’s a sample:

b

Format binaire. Affiche le nombre en base 2.

c

Caractère. Convertit l’entier en le caractère Unicode associé avant de l’afficher.

d

Entier décimal. Affiche le nombre en base 10.

o

Format octal. Affiche le nombre en base 8.

x

Format hexadécimal. Affiche le nombre en base 16 en utilisant les lettres minuscules pour les chiffres au-dessus de 9.

e

Exponent notation. Prints the number in scientific notation using the letter “e” to indicate the exponent.

g

General format. This prints the number as a fixed-point number, unless the number is too large, in which case it switches to “e” exponent notation.

n

Number. This is the same as “g” (for floats) or “d” (for integers), except that it uses the current locale setting to insert the appropriate number separator characters.

%

Pourcentage. Multiplie le nombre par 100 et l’affiche en virgule fixe (“f”), suivi d’un symbole pourcent '%'.

Classes and types can define a __format__() method to control how they’re formatted. It receives a single argument, the format specifier:

def __format__(self, format_spec):
    if isinstance(format_spec, unicode):
        return unicode(str(self))
    else:
        return str(self)

There’s also a format() builtin that will format a single value. It calls the type’s __format__() method with the provided specifier:

>>> format(75.6564, '.2f')
'75.66'

Voir aussi

Syntaxe de formatage de chaîne

The reference documentation for format fields.

PEP 3101 [https://www.python.org/dev/peps/pep-3101] - Advanced String Formatting

PEP written by Talin. Implemented by Eric Smith.

PEP 3105: print As a Function

The print statement becomes the print() function in Python 3.0. Making print() a function makes it possible to replace the function by doing def print(...) or importing a new function from somewhere else.

Python 2.6 has a __future__ import that removes print as language syntax, letting you use the functional form instead. For example:

>>> from __future__ import print_function
>>> print('# of entries', len(dictionary), file=sys.stderr)

The signature of the new function is:

def print(*args, sep=' ', end='\n', file=None)

The parameters are:

args: positional arguments whose values will be printed out.

sep: the separator, which will be printed between arguments.

end: the ending text, which will be printed after all of the arguments have been output.

file: the file object to which the output will be sent.

Voir aussi

PEP 3105 [https://www.python.org/dev/peps/pep-3105] - Make print a function

PEP written by Georg Brandl.

PEP 3110: Exception-Handling Changes

One error that Python programmers occasionally make is writing the following code:

try:
    ...
except TypeError, ValueError:  # Wrong!
    ...

The author is probably trying to catch both TypeError and ValueError exceptions, but this code actually does something different: it will catch TypeError and bind the resulting exception object to the local name "ValueError". The ValueError exception will not be caught at all. The correct code specifies a tuple of exceptions:

try:
    ...
except (TypeError, ValueError):
    ...

This error happens because the use of the comma here is ambiguous: does it indicate two different nodes in the parse tree, or a single node that’s a tuple?

Python 3.0 makes this unambiguous by replacing the comma with the word « as ». To catch an exception and store the exception object in the variable exc, you must write:

try:
    ...
except TypeError as exc:
    ...

Python 3.0 will only support the use of « as », and therefore interprets the first example as catching two different exceptions. Python 2.6 supports both the comma and « as », so existing code will continue to work. We therefore suggest using « as » when writing new Python code that will only be executed with 2.6.

Voir aussi

PEP 3110 [https://www.python.org/dev/peps/pep-3110] - Catching Exceptions in Python 3000

PEP written and implemented by Collin Winter.

PEP 3112: Byte Literals

Python 3.0 adopts Unicode as the language’s fundamental string type and denotes 8-bit literals differently, either as b'string' or using a bytes constructor. For future compatibility, Python 2.6 adds bytes as a synonym for the str type, and it also supports the b'' notation.

The 2.6 str differs from 3.0’s bytes type in various ways; most notably, the constructor is completely different. In 3.0, bytes([65, 66, 67]) is 3 elements long, containing the bytes representing ABC; in 2.6, bytes([65, 66, 67]) returns the 12-byte string representing the str() of the list.

The primary use of bytes in 2.6 will be to write tests of object type such as isinstance(x, bytes). This will help the 2to3 converter, which can’t tell whether 2.x code intends strings to contain either characters or 8-bit bytes; you can now use either bytes or str to represent your intention exactly, and the resulting code will also be correct in Python 3.0.

There’s also a __future__ import that causes all string literals to become Unicode strings. This means that \u escape sequences can be used to include Unicode characters:

from __future__ import unicode_literals

s = ('\u751f\u3080\u304e\u3000\u751f\u3054'
     '\u3081\u3000\u751f\u305f\u307e\u3054')

print len(s)               # 12 Unicode characters

At the C level, Python 3.0 will rename the existing 8-bit string type, called PyStringObject in Python 2.x, to PyBytesObject. Python 2.6 uses #define to support using the names PyBytesObject(), PyBytes_Check(), PyBytes_FromStringAndSize(), and all the other functions and macros used with strings.

Instances of the bytes type are immutable just as strings are. A new bytearray type stores a mutable sequence of bytes:

>>> bytearray([65, 66, 67])
bytearray(b'ABC')
>>> b = bytearray(u'\u21ef\u3244', 'utf-8')
>>> b
bytearray(b'\xe2\x87\xaf\xe3\x89\x84')
>>> b[0] = '\xe3'
>>> b
bytearray(b'\xe3\x87\xaf\xe3\x89\x84')
>>> unicode(str(b), 'utf-8')
u'\u31ef \u3244'

Byte arrays support most of the methods of string types, such as startswith()/endswith(), find()/rfind(), and some of the methods of lists, such as append(), pop(), and reverse().

>>> b = bytearray('ABC')
>>> b.append('d')
>>> b.append(ord('e'))
>>> b
bytearray(b'ABCde')

There’s also a corresponding C API, with PyByteArray_FromObject(), PyByteArray_FromStringAndSize(), and various other functions.

Voir aussi

PEP 3112 [https://www.python.org/dev/peps/pep-3112] - Bytes literals in Python 3000

PEP written by Jason Orendorff; backported to 2.6 by Christian Heimes.

PEP 3116: New I/O Library

Python’s built-in file objects support a number of methods, but file-like objects don’t necessarily support all of them. Objects that imitate files usually support read() and write(), but they may not support readline(), for example. Python 3.0 introduces a layered I/O library in the io module that separates buffering and text-handling features from the fundamental read and write operations.

There are three levels of abstract base classes provided by the io module:

RawIOBase defines raw I/O operations: read(), readinto(), write(), seek(), tell(), truncate(), and close(). Most of the methods of this class will often map to a single system call. There are also readable(), writable(), and seekable() methods for determining what operations a given object will allow.

Python 3.0 has concrete implementations of this class for files and sockets, but Python 2.6 hasn’t restructured its file and socket objects in this way.

BufferedIOBase is an abstract base class that buffers data in memory to reduce the number of system calls used, making I/O processing more efficient. It supports all of the methods of RawIOBase, and adds a raw attribute holding the underlying raw object.

There are five concrete classes implementing this ABC. BufferedWriter and BufferedReader are for objects that support write-only or read-only usage that have a seek() method for random access. BufferedRandom objects support read and write access upon the same underlying stream, and BufferedRWPair is for objects such as TTYs that have both read and write operations acting upon unconnected streams of data. The BytesIO class supports reading, writing, and seeking over an in-memory buffer.

TextIOBase: Provides functions for reading and writing strings (remember, strings will be Unicode in Python 3.0), and supporting universal newlines. TextIOBase defines the readline() method and supports iteration upon objects.

There are two concrete implementations. TextIOWrapper wraps a buffered I/O object, supporting all of the methods for text I/O and adding a buffer attribute for access to the underlying object. StringIO simply buffers everything in memory without ever writing anything to disk.

(In Python 2.6, io.StringIO is implemented in pure Python, so it’s pretty slow. You should therefore stick with the existing StringIO module or cStringIO for now. At some point Python 3.0’s io module will be rewritten into C for speed, and perhaps the C implementation will be backported to the 2.x releases.)

In Python 2.6, the underlying implementations haven’t been restructured to build on top of the io module’s classes. The module is being provided to make it easier to write code that’s forward-compatible with 3.0, and to save developers the effort of writing their own implementations of buffering and text I/O.

Voir aussi

PEP 3116 [https://www.python.org/dev/peps/pep-3116] - New I/O

PEP written by Daniel Stutzbach, Mike Verdone, and Guido van Rossum. Code by Guido van Rossum, Georg Brandl, Walter Doerwald, Jeremy Hylton, Martin von Löwis, Tony Lownds, and others.

PEP 3118: Revised Buffer Protocol

The buffer protocol is a C-level API that lets Python types exchange pointers into their internal representations. A memory-mapped file can be viewed as a buffer of characters, for example, and this lets another module such as re treat memory-mapped files as a string of characters to be searched.

The primary users of the buffer protocol are numeric-processing packages such as NumPy, which expose the internal representation of arrays so that callers can write data directly into an array instead of going through a slower API. This PEP updates the buffer protocol in light of experience from NumPy development, adding a number of new features such as indicating the shape of an array or locking a memory region.

The most important new C API function is PyObject_GetBuffer(PyObject *obj, Py_buffer *view, int flags), which takes an object and a set of flags, and fills in the Py_buffer structure with information about the object’s memory representation. Objects can use this operation to lock memory in place while an external caller could be modifying the contents, so there’s a corresponding PyBuffer_Release(Py_buffer *view) to indicate that the external caller is done.

The flags argument to PyObject_GetBuffer() specifies constraints upon the memory returned. Some examples are:

PyBUF_WRITABLE indicates that the memory must be writable.

PyBUF_LOCK requests a read-only or exclusive lock on the memory.

PyBUF_C_CONTIGUOUS and PyBUF_F_CONTIGUOUS requests a C-contiguous (last dimension varies the fastest) or Fortran-contiguous (first dimension varies the fastest) array layout.

Two new argument codes for PyArg_ParseTuple(), s* and z*, return locked buffer objects for a parameter.

Voir aussi

PEP 3118 [https://www.python.org/dev/peps/pep-3118] - Revising the buffer protocol

PEP written by Travis Oliphant and Carl Banks; implemented by Travis Oliphant.

PEP 3119: Abstract Base Classes

Some object-oriented languages such as Java support interfaces, declaring that a class has a given set of methods or supports a given access protocol. Abstract Base Classes (or ABCs) are an equivalent feature for Python. The ABC support consists of an abc module containing a metaclass called ABCMeta, special handling of this metaclass by the isinstance() and issubclass() builtins, and a collection of basic ABCs that the Python developers think will be widely useful. Future versions of Python will probably add more ABCs.

Let’s say you have a particular class and wish to know whether it supports dictionary-style access. The phrase « dictionary-style » is vague, however. It probably means that accessing items with obj[1] works. Does it imply that setting items with obj[2] = value works? Or that the object will have keys(), values(), and items() methods? What about the iterative variants such as iterkeys()? copy() and update()? Iterating over the object with iter()?

The Python 2.6 collections module includes a number of different ABCs that represent these distinctions. Iterable indicates that a class defines __iter__(), and Container means the class defines a __contains__() method and therefore supports x in y expressions. The basic dictionary interface of getting items, setting items, and keys(), values(), and items(), is defined by the MutableMapping ABC.

You can derive your own classes from a particular ABC to indicate they support that ABC’s interface:

import collections

class Storage(collections.MutableMapping):
    ...

Alternatively, you could write the class without deriving from the desired ABC and instead register the class by calling the ABC’s register() method:

import collections

class Storage:
    ...

collections.MutableMapping.register(Storage)

For classes that you write, deriving from the ABC is probably clearer. The register() method is useful when you’ve written a new ABC that can describe an existing type or class, or if you want to declare that some third-party class implements an ABC. For example, if you defined a PrintableType ABC, it’s legal to do:

# Register Python's types
PrintableType.register(int)
PrintableType.register(float)
PrintableType.register(str)

Classes should obey the semantics specified by an ABC, but Python can’t check this; it’s up to the class author to understand the ABC’s requirements and to implement the code accordingly.

To check whether an object supports a particular interface, you can now write:

def func(d):
    if not isinstance(d, collections.MutableMapping):
        raise ValueError("Mapping object expected, not %r" % d)

Don’t feel that you must now begin writing lots of checks as in the above example. Python has a strong tradition of duck-typing, where explicit type-checking is never done and code simply calls methods on an object, trusting that those methods will be there and raising an exception if they aren’t. Be judicious in checking for ABCs and only do it where it’s absolutely necessary.

You can write your own ABCs by using abc.ABCMeta as the metaclass in a class definition:

from abc import ABCMeta, abstractmethod

class Drawable():
    __metaclass__ = ABCMeta

    @abstractmethod
    def draw(self, x, y, scale=1.0):
        pass

    def draw_doubled(self, x, y):
        self.draw(x, y, scale=2.0)

class Square(Drawable):
    def draw(self, x, y, scale):
        ...

In the Drawable ABC above, the draw_doubled() method renders the object at twice its size and can be implemented in terms of other methods described in Drawable. Classes implementing this ABC therefore don’t need to provide their own implementation of draw_doubled(), though they can do so. An implementation of draw() is necessary, though; the ABC can’t provide a useful generic implementation.

You can apply the @abstractmethod decorator to methods such as draw() that must be implemented; Python will then raise an exception for classes that don’t define the method. Note that the exception is only raised when you actually try to create an instance of a subclass lacking the method:

>>> class Circle(Drawable):
...     pass
...
>>> c = Circle()
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: Can't instantiate abstract class Circle with abstract methods draw
>>>

Abstract data attributes can be declared using the @abstractproperty decorator:

from abc import abstractproperty
...

@abstractproperty
def readonly(self):
   return self._x

Subclasses must then define a readonly() property.

Voir aussi

PEP 3119 [https://www.python.org/dev/peps/pep-3119] – Introduction aux classes de bases abstraites

PEP written by Guido van Rossum and Talin. Implemented by Guido van Rossum. Backported to 2.6 by Benjamin Aranguren, with Alex Martelli.

PEP 3127: Integer Literal Support and Syntax

Python 3.0 changes the syntax for octal (base-8) integer literals, prefixing them with « 0o » or « 0O » instead of a leading zero, and adds support for binary (base-2) integer literals, signalled by a « 0b » or « 0B » prefix.

Python 2.6 doesn’t drop support for a leading 0 signalling an octal number, but it does add support for « 0o » and « 0b »:

>>> 0o21, 2*8 + 1
(17, 17)
>>> 0b101111
47

The oct() builtin still returns numbers prefixed with a leading zero, and a new bin() builtin returns the binary representation for a number:

>>> oct(42)
'052'
>>> future_builtins.oct(42)
'0o52'
>>> bin(173)
'0b10101101'

The int() and long() builtins will now accept the « 0o » and « 0b » prefixes when base-8 or base-2 are requested, or when the base argument is zero (signalling that the base used should be determined from the string):

>>> int ('0o52', 0)
42
>>> int('1101', 2)
13
>>> int('0b1101', 2)
13
>>> int('0b1101', 0)
13

Voir aussi

PEP 3127 [https://www.python.org/dev/peps/pep-3127] - Integer Literal Support and Syntax

PEP written by Patrick Maupin; backported to 2.6 by Eric Smith.

PEP 3129: Class Decorators

Decorators have been extended from functions to classes. It’s now legal to write:

@foo
@bar
class A:
  pass

C’est équivalent à :

class A:
  pass

A = foo(bar(A))

Voir aussi

PEP 3129 [https://www.python.org/dev/peps/pep-3129] – Décorateurs de classes

PEP written by Collin Winter.

PEP 3141: A Type Hierarchy for Numbers

Python 3.0 adds several abstract base classes for numeric types inspired by Scheme’s numeric tower. These classes were backported to 2.6 as the numbers module.

The most general ABC is Number. It defines no operations at all, and only exists to allow checking if an object is a number by doing isinstance(obj, Number).

Complex is a subclass of Number. Complex numbers can undergo the basic operations of addition, subtraction, multiplication, division, and exponentiation, and you can retrieve the real and imaginary parts and obtain a number’s conjugate. Python’s built-in complex type is an implementation of Complex.

Real further derives from Complex, and adds operations that only work on real numbers: floor(), trunc(), rounding, taking the remainder mod N, floor division, and comparisons.

Rational numbers derive from Real, have numerator and denominator properties, and can be converted to floats. Python 2.6 adds a simple rational-number class, Fraction, in the fractions module. (It’s called Fraction instead of Rational to avoid a name clash with numbers.Rational.)

Integral numbers derive from Rational, and can be shifted left and right with << and >>, combined using bitwise operations such as & and |, and can be used as array indexes and slice boundaries.

In Python 3.0, the PEP slightly redefines the existing builtins round(), math.floor(), math.ceil(), and adds a new one, math.trunc(), that’s been backported to Python 2.6. math.trunc() rounds toward zero, returning the closest Integral that’s between the function’s argument and zero.

Voir aussi

PEP 3141 [https://www.python.org/dev/peps/pep-3141] - A Type Hierarchy for Numbers

PEP written by Jeffrey Yasskin.

Scheme’s numerical tower [https://www.gnu.org/software/guile/manual/html_node/Numerical-Tower.html#Numerical-Tower], from the Guile manual.

Scheme’s number datatypes [http://schemers.org/Documents/Standards/R5RS/HTML/r5rs-Z-H-9.html#%_sec_6.2] from the R5RS Scheme specification.

The fractions Module

To fill out the hierarchy of numeric types, the fractions module provides a rational-number class. Rational numbers store their values as a numerator and denominator forming a fraction, and can exactly represent numbers such as 2/3 that floating-point numbers can only approximate.

The Fraction constructor takes two Integral values that will be the numerator and denominator of the resulting fraction.

>>> from fractions import Fraction
>>> a = Fraction(2, 3)
>>> b = Fraction(2, 5)
>>> float(a), float(b)
(0.66666666666666663, 0.40000000000000002)
>>> a+b
Fraction(16, 15)
>>> a/b
Fraction(5, 3)

For converting floating-point numbers to rationals, the float type now has an as_integer_ratio() method that returns the numerator and denominator for a fraction that evaluates to the same floating-point value:

>>> (2.5) .as_integer_ratio()
(5, 2)
>>> (3.1415) .as_integer_ratio()
(7074029114692207L, 2251799813685248L)
>>> (1./3) .as_integer_ratio()
(6004799503160661L, 18014398509481984L)

Note that values that can only be approximated by floating-point numbers, such as 1./3, are not simplified to the number being approximated; the fraction attempts to match the floating-point value exactly.

The fractions module is based upon an implementation by Sjoerd Mullender that was in Python’s Demo/classes/ directory for a long time. This implementation was significantly updated by Jeffrey Yasskin.

Other Language Changes

Some smaller changes made to the core Python language are:

Directories and zip archives containing a __main__.py file can now be executed directly by passing their name to the interpreter. The directory or zip archive is automatically inserted as the first entry in sys.path. (Suggestion and initial patch by Andy Chu, subsequently revised by Phillip J. Eby and Nick Coghlan; bpo-1739468 [https://bugs.python.org/issue1739468].)

The hasattr() function was catching and ignoring all errors, under the assumption that they meant a __getattr__() method was failing somehow and the return value of hasattr() would therefore be False. This logic shouldn’t be applied to KeyboardInterrupt and SystemExit, however; Python 2.6 will no longer discard such exceptions when hasattr() encounters them. (Fixed by Benjamin Peterson; bpo-2196 [https://bugs.python.org/issue2196].)

When calling a function using the ** syntax to provide keyword arguments, you are no longer required to use a Python dictionary; any mapping will now work:

>>> def f(**kw):
...    print sorted(kw)
...
>>> ud=UserDict.UserDict()
>>> ud['a'] = 1
>>> ud['b'] = 'string'
>>> f(**ud)
['a', 'b']

(Contribution par Alexander Belopolsky; bpo-1686487 [https://bugs.python.org/issue1686487].)

It’s also become legal to provide keyword arguments after a *args argument to a function call.

>>> def f(*args, **kw):
...     print args, kw
...
>>> f(1,2,3, *(4,5,6), keyword=13)
(1, 2, 3, 4, 5, 6) {'keyword': 13}

Previously this would have been a syntax error. (Contributed by Amaury Forgeot d’Arc; bpo-3473 [https://bugs.python.org/issue3473].)

A new builtin, next(iterator, [default]) returns the next item from the specified iterator. If the default argument is supplied, it will be returned if iterator has been exhausted; otherwise, the StopIteration exception will be raised. (Backported in bpo-2719 [https://bugs.python.org/issue2719].)

Tuples now have index() and count() methods matching the list type’s index() and count() methods:

>>> t = (0,1,2,3,4,0,1,2)
>>> t.index(3)
3
>>> t.count(0)
2

(Contributed by Raymond Hettinger)

The built-in types now have improved support for extended slicing syntax, accepting various combinations of (start, stop, step). Previously, the support was partial and certain corner cases wouldn’t work. (Implemented by Thomas Wouters.)

Properties now have three attributes, getter, setter and deleter, that are decorators providing useful shortcuts for adding a getter, setter or deleter function to an existing property. You would use them like this:

class C(object):
    @property
    def x(self):
        return self._x

    @x.setter
    def x(self, value):
        self._x = value

    @x.deleter
    def x(self):
        del self._x

class D(C):
    @C.x.getter
    def x(self):
        return self._x * 2

    @x.setter
    def x(self, value):
        self._x = value / 2

Several methods of the built-in set types now accept multiple iterables: intersection(), intersection_update(), union(), update(), difference() and difference_update().

>>> s=set('1234567890')
>>> s.intersection('abc123', 'cdf246')  # Intersection between all inputs
set(['2'])
>>> s.difference('246', '789')
set(['1', '0', '3', '5'])

(Contributed by Raymond Hettinger.)

Many floating-point features were added. The float() function will now turn the string nan into an IEEE 754 Not A Number value, and +inf and -inf into positive or negative infinity. This works on any platform with IEEE 754 semantics. (Contributed by Christian Heimes; bpo-1635 [https://bugs.python.org/issue1635].)

Other functions in the math module, isinf() and isnan(), return true if their floating-point argument is infinite or Not A Number. (bpo-1640 [https://bugs.python.org/issue1640])

Conversion functions were added to convert floating-point numbers into hexadecimal strings (bpo-3008 [https://bugs.python.org/issue3008]). These functions convert floats to and from a string representation without introducing rounding errors from the conversion between decimal and binary. Floats have a hex() method that returns a string representation, and the float.fromhex() method converts a string back into a number:

>>> a = 3.75
>>> a.hex()
'0x1.e000000000000p+1'
>>> float.fromhex('0x1.e000000000000p+1')
3.75
>>> b=1./3
>>> b.hex()
'0x1.5555555555555p-2'

A numerical nicety: when creating a complex number from two floats on systems that support signed zeros (-0 and +0), the complex() constructor will now preserve the sign of the zero. (Fixed by Mark T. Dickinson; bpo-1507 [https://bugs.python.org/issue1507].)

Classes that inherit a __hash__() method from a parent class can set __hash__ = None to indicate that the class isn’t hashable. This will make hash(obj) raise a TypeError and the class will not be indicated as implementing the Hashable ABC.

You should do this when you’ve defined a __cmp__() or __eq__() method that compares objects by their value rather than by identity. All objects have a default hash method that uses id(obj) as the hash value. There’s no tidy way to remove the __hash__() method inherited from a parent class, so assigning None was implemented as an override. At the C level, extensions can set tp_hash to PyObject_HashNotImplemented(). (Fixed by Nick Coghlan and Amaury Forgeot d’Arc; bpo-2235 [https://bugs.python.org/issue2235].)

The GeneratorExit exception now subclasses BaseException instead of Exception. This means that an exception handler that does except Exception: will not inadvertently catch GeneratorExit. (Contributed by Chad Austin; bpo-1537 [https://bugs.python.org/issue1537].)

Generator objects now have a gi_code attribute that refers to the original code object backing the generator. (Contributed by Collin Winter; bpo-1473257 [https://bugs.python.org/issue1473257].)

The compile() built-in function now accepts keyword arguments as well as positional parameters. (Contributed by Thomas Wouters; bpo-1444529 [https://bugs.python.org/issue1444529].)

The complex() constructor now accepts strings containing parenthesized complex numbers, meaning that complex(repr(cplx)) will now round-trip values. For example, complex('(3+4j)') now returns the value (3+4j). (bpo-1491866 [https://bugs.python.org/issue1491866])

The string translate() method now accepts None as the translation table parameter, which is treated as the identity transformation. This makes it easier to carry out operations that only delete characters. (Contributed by Bengt Richter and implemented by Raymond Hettinger; bpo-1193128 [https://bugs.python.org/issue1193128].)

The built-in dir() function now checks for a __dir__() method on the objects it receives. This method must return a list of strings containing the names of valid attributes for the object, and lets the object control the value that dir() produces. Objects that have __getattr__() or __getattribute__() methods can use this to advertise pseudo-attributes they will honor. (bpo-1591665 [https://bugs.python.org/issue1591665])

Instance method objects have new attributes for the object and function comprising the method; the new synonym for im_self is __self__, and im_func is also available as __func__. The old names are still supported in Python 2.6, but are gone in 3.0.

An obscure change: when you use the locals() function inside a class statement, the resulting dictionary no longer returns free variables. (Free variables, in this case, are variables referenced in the class statement that aren’t attributes of the class.)

Optimizations

The warnings module has been rewritten in C. This makes it possible to invoke warnings from the parser, and may also make the interpreter’s startup faster. (Contributed by Neal Norwitz and Brett Cannon; bpo-1631171 [https://bugs.python.org/issue1631171].)

Type objects now have a cache of methods that can reduce the work required to find the correct method implementation for a particular class; once cached, the interpreter doesn’t need to traverse base classes to figure out the right method to call. The cache is cleared if a base class or the class itself is modified, so the cache should remain correct even in the face of Python’s dynamic nature. (Original optimization implemented by Armin Rigo, updated for Python 2.6 by Kevin Jacobs; bpo-1700288 [https://bugs.python.org/issue1700288].)

By default, this change is only applied to types that are included with the Python core. Extension modules may not necessarily be compatible with this cache, so they must explicitly add Py_TPFLAGS_HAVE_VERSION_TAG to the module’s tp_flags field to enable the method cache. (To be compatible with the method cache, the extension module’s code must not directly access and modify the tp_dict member of any of the types it implements. Most modules don’t do this, but it’s impossible for the Python interpreter to determine that. See bpo-1878 [https://bugs.python.org/issue1878] for some discussion.)

Function calls that use keyword arguments are significantly faster by doing a quick pointer comparison, usually saving the time of a full string comparison. (Contributed by Raymond Hettinger, after an initial implementation by Antoine Pitrou; bpo-1819 [https://bugs.python.org/issue1819].)

All of the functions in the struct module have been rewritten in C, thanks to work at the Need For Speed sprint. (Contributed by Raymond Hettinger.)

Some of the standard built-in types now set a bit in their type objects. This speeds up checking whether an object is a subclass of one of these types. (Contributed by Neal Norwitz.)

Unicode strings now use faster code for detecting whitespace and line breaks; this speeds up the split() method by about 25% and splitlines() by 35%. (Contributed by Antoine Pitrou.) Memory usage is reduced by using pymalloc for the Unicode string’s data.

The with statement now stores the __exit__() method on the stack, producing a small speedup. (Implemented by Jeffrey Yasskin.)

To reduce memory usage, the garbage collector will now clear internal free lists when garbage-collecting the highest generation of objects. This may return memory to the operating system sooner.

Interpreter Changes

Two command-line options have been reserved for use by other Python implementations. The -J switch has been reserved for use by Jython for Jython-specific options, such as switches that are passed to the underlying JVM. -X has been reserved for options specific to a particular implementation of Python such as CPython, Jython, or IronPython. If either option is used with Python 2.6, the interpreter will report that the option isn’t currently used.

Python can now be prevented from writing .pyc or .pyo files by supplying the -B switch to the Python interpreter, or by setting the PYTHONDONTWRITEBYTECODE environment variable before running the interpreter. This setting is available to Python programs as the sys.dont_write_bytecode variable, and Python code can change the value to modify the interpreter’s behaviour. (Contributed by Neal Norwitz and Georg Brandl.)

The encoding used for standard input, output, and standard error can be specified by setting the PYTHONIOENCODING environment variable before running the interpreter. The value should be a string in the form <encoding> or <encoding>:<errorhandler>. The encoding part specifies the encoding’s name, e.g. utf-8 or latin-1; the optional errorhandler part specifies what to do with characters that can’t be handled by the encoding, and should be one of « error », « ignore », or « replace ». (Contributed by Martin von Löwis.)

New and Improved Modules

As in every release, Python’s standard library received a number of enhancements and bug fixes. Here’s a partial list of the most notable changes, sorted alphabetically by module name. Consult the Misc/NEWS file in the source tree for a more complete list of changes, or look through the Subversion logs for all the details.

The asyncore and asynchat modules are being actively maintained again, and a number of patches and bugfixes were applied. (Maintained by Josiah Carlson; see bpo-1736190 [https://bugs.python.org/issue1736190] for one patch.)

The bsddb module also has a new maintainer, Jesús Cea Avión, and the package is now available as a standalone package. The web page for the package is www.jcea.es/programacion/pybsddb.htm [https://www.jcea.es/programacion/pybsddb.htm]. The plan is to remove the package from the standard library in Python 3.0, because its pace of releases is much more frequent than Python’s.

The bsddb.dbshelve module now uses the highest pickling protocol available, instead of restricting itself to protocol 1. (Contributed by W. Barnes.)

The cgi module will now read variables from the query string of an HTTP POST request. This makes it possible to use form actions with URLs that include query strings such as « /cgi-bin/add.py?category=1 ». (Contributed by Alexandre Fiori and Nubis; bpo-1817 [https://bugs.python.org/issue1817].)

The parse_qs() and parse_qsl() functions have been relocated from the cgi module to the urlparse module. The versions still available in the cgi module will trigger PendingDeprecationWarning messages in 2.6 (bpo-600362 [https://bugs.python.org/issue600362]).

The cmath module underwent extensive revision, contributed by Mark Dickinson and Christian Heimes. Five new functions were added:

polar() converts a complex number to polar form, returning the modulus and argument of the complex number.

rect() does the opposite, turning a modulus, argument pair back into the corresponding complex number.

phase() returns the argument (also called the angle) of a complex number.

isnan() returns True if either the real or imaginary part of its argument is a NaN.

isinf() returns True if either the real or imaginary part of its argument is infinite.

The revisions also improved the numerical soundness of the cmath module. For all functions, the real and imaginary parts of the results are accurate to within a few units of least precision (ulps) whenever possible. See bpo-1381 [https://bugs.python.org/issue1381] for the details. The branch cuts for asinh(), atanh(): and atan() have also been corrected.

The tests for the module have been greatly expanded; nearly 2000 new test cases exercise the algebraic functions.

On IEEE 754 platforms, the cmath module now handles IEEE 754 special values and floating-point exceptions in a manner consistent with Annex “G” of the C99 standard.

A new data type in the collections module: namedtuple(typename, fieldnames) is a factory function that creates subclasses of the standard tuple whose fields are accessible by name as well as index. For example:

>>> var_type = collections.namedtuple('variable',
...             'id name type size')
>>> # Names are separated by spaces or commas.
>>> # 'id, name, type, size' would also work.
>>> var_type._fields
('id', 'name', 'type', 'size')

>>> var = var_type(1, 'frequency', 'int', 4)
>>> print var[0], var.id    # Equivalent
1 1
>>> print var[2], var.type  # Equivalent
int int
>>> var._asdict()
{'size': 4, 'type': 'int', 'id': 1, 'name': 'frequency'}
>>> v2 = var._replace(name='amplitude')
>>> v2
variable(id=1, name='amplitude', type='int', size=4)

Several places in the standard library that returned tuples have been modified to return namedtuple instances. For example, the Decimal.as_tuple() method now returns a named tuple with sign, digits, and exponent fields.

(Contributed by Raymond Hettinger.)

Another change to the collections module is that the deque type now supports an optional maxlen parameter; if supplied, the deque’s size will be restricted to no more than maxlen items. Adding more items to a full deque causes old items to be discarded.

>>> from collections import deque
>>> dq=deque(maxlen=3)
>>> dq
deque([], maxlen=3)
>>> dq.append(1); dq.append(2); dq.append(3)
>>> dq
deque([1, 2, 3], maxlen=3)
>>> dq.append(4)
>>> dq
deque([2, 3, 4], maxlen=3)

(Contributed by Raymond Hettinger.)

The Cookie module’s Morsel objects now support an httponly attribute. In some browsers. cookies with this attribute set cannot be accessed or manipulated by JavaScript code. (Contributed by Arvin Schnell; bpo-1638033 [https://bugs.python.org/issue1638033].)

A new window method in the curses module, chgat(), changes the display attributes for a certain number of characters on a single line. (Contributed by Fabian Kreutz.)

# Boldface text starting at y=0,x=21
# and affecting the rest of the line.
stdscr.chgat(0, 21, curses.A_BOLD)

The Textbox class in the curses.textpad module now supports editing in insert mode as well as overwrite mode. Insert mode is enabled by supplying a true value for the insert_mode parameter when creating the Textbox instance.

The datetime module’s strftime() methods now support a %f format code that expands to the number of microseconds in the object, zero-padded on the left to six places. (Contributed by Skip Montanaro; bpo-1158 [https://bugs.python.org/issue1158].)

The decimal module was updated to version 1.66 of the General Decimal Specification [http://speleotrove.com/decimal/decarith.html]. New features include some methods for some basic mathematical functions such as exp() and log10():

>>> Decimal(1).exp()
Decimal("2.718281828459045235360287471")
>>> Decimal("2.7182818").ln()
Decimal("0.9999999895305022877376682436")
>>> Decimal(1000).log10()
Decimal("3")

The as_tuple() method of Decimal objects now returns a named tuple with sign, digits, and exponent fields.

(Implemented by Facundo Batista and Mark Dickinson. Named tuple support added by Raymond Hettinger.)

The difflib module’s SequenceMatcher class now returns named tuples representing matches, with a, b, and size attributes. (Contributed by Raymond Hettinger.)

An optional timeout parameter, specifying a timeout measured in seconds, was added to the ftplib.FTP class constructor as well as the connect() method. (Added by Facundo Batista.) Also, the FTP class’s storbinary() and storlines() now take an optional callback parameter that will be called with each block of data after the data has been sent. (Contributed by Phil Schwartz; bpo-1221598 [https://bugs.python.org/issue1221598].)

The reduce() built-in function is also available in the functools module. In Python 3.0, the builtin has been dropped and reduce() is only available from functools; currently there are no plans to drop the builtin in the 2.x series. (Patched by Christian Heimes; bpo-1739906 [https://bugs.python.org/issue1739906].)

When possible, the getpass module will now use /dev/tty to print a prompt message and read the password, falling back to standard error and standard input. If the password may be echoed to the terminal, a warning is printed before the prompt is displayed. (Contributed by Gregory P. Smith.)

The glob.glob() function can now return Unicode filenames if a Unicode path was used and Unicode filenames are matched within the directory. (bpo-1001604 [https://bugs.python.org/issue1001604])

A new function in the heapq module, merge(iter1, iter2, ...), takes any number of iterables returning data in sorted order, and returns a new generator that returns the contents of all the iterators, also in sorted order. For example:

>>> list(heapq.merge([1, 3, 5, 9], [2, 8, 16]))
[1, 2, 3, 5, 8, 9, 16]

Another new function, heappushpop(heap, item), pushes item onto heap, then pops off and returns the smallest item. This is more efficient than making a call to heappush() and then heappop().

heapq is now implemented to only use less-than comparison, instead of the less-than-or-equal comparison it previously used. This makes heapq’s usage of a type match the list.sort() method. (Contributed by Raymond Hettinger.)

An optional timeout parameter, specifying a timeout measured in seconds, was added to the httplib.HTTPConnection and HTTPSConnection class constructors. (Added by Facundo Batista.)

Most of the inspect module’s functions, such as getmoduleinfo() and getargs(), now return named tuples. In addition to behaving like tuples, the elements of the return value can also be accessed as attributes. (Contributed by Raymond Hettinger.)

Some new functions in the module include isgenerator(), isgeneratorfunction(), and isabstract().

The itertools module gained several new functions.

izip_longest(iter1, iter2, ...[, fillvalue]) makes tuples from each of the elements; if some of the iterables are shorter than others, the missing values are set to fillvalue. For example:

>>> tuple(itertools.izip_longest([1,2,3], [1,2,3,4,5]))
((1, 1), (2, 2), (3, 3), (None, 4), (None, 5))

product(iter1, iter2, ..., [repeat=N]) returns the Cartesian product of the supplied iterables, a set of tuples containing every possible combination of the elements returned from each iterable.

>>> list(itertools.product([1,2,3], [4,5,6]))
[(1, 4), (1, 5), (1, 6),
 (2, 4), (2, 5), (2, 6),
 (3, 4), (3, 5), (3, 6)]

The optional repeat keyword argument is used for taking the product of an iterable or a set of iterables with themselves, repeated N times. With a single iterable argument, N-tuples are returned:

>>> list(itertools.product([1,2], repeat=3))
[(1, 1, 1), (1, 1, 2), (1, 2, 1), (1, 2, 2),
 (2, 1, 1), (2, 1, 2), (2, 2, 1), (2, 2, 2)]

With two iterables, 2N-tuples are returned.

>>> list(itertools.product([1,2], [3,4], repeat=2))
[(1, 3, 1, 3), (1, 3, 1, 4), (1, 3, 2, 3), (1, 3, 2, 4),
 (1, 4, 1, 3), (1, 4, 1, 4), (1, 4, 2, 3), (1, 4, 2, 4),
 (2, 3, 1, 3), (2, 3, 1, 4), (2, 3, 2, 3), (2, 3, 2, 4),
 (2, 4, 1, 3), (2, 4, 1, 4), (2, 4, 2, 3), (2, 4, 2, 4)]

combinations(iterable, r) returns sub-sequences of length r from the elements of iterable.

>>> list(itertools.combinations('123', 2))
[('1', '2'), ('1', '3'), ('2', '3')]
>>> list(itertools.combinations('123', 3))
[('1', '2', '3')]
>>> list(itertools.combinations('1234', 3))
[('1', '2', '3'), ('1', '2', '4'),
 ('1', '3', '4'), ('2', '3', '4')]

permutations(iter[, r]) returns all the permutations of length r of the iterable’s elements. If r is not specified, it will default to the number of elements produced by the iterable.

>>> list(itertools.permutations([1,2,3,4], 2))
[(1, 2), (1, 3), (1, 4),
 (2, 1), (2, 3), (2, 4),
 (3, 1), (3, 2), (3, 4),
 (4, 1), (4, 2), (4, 3)]

itertools.chain(*iterables) is an existing function in itertools that gained a new constructor in Python 2.6. itertools.chain.from_iterable(iterable) takes a single iterable that should return other iterables. chain() will then return all the elements of the first iterable, then all the elements of the second, and so on.

>>> list(itertools.chain.from_iterable([[1,2,3], [4,5,6]]))
[1, 2, 3, 4, 5, 6]

(All contributed by Raymond Hettinger.)

The logging module’s FileHandler class and its subclasses WatchedFileHandler, RotatingFileHandler, and TimedRotatingFileHandler now have an optional delay parameter to their constructors. If delay is true, opening of the log file is deferred until the first emit() call is made. (Contributed by Vinay Sajip.)

TimedRotatingFileHandler also has a utc constructor parameter. If the argument is true, UTC time will be used in determining when midnight occurs and in generating filenames; otherwise local time will be used.

Several new functions were added to the math module:

isinf() and isnan() determine whether a given float is a (positive or negative) infinity or a NaN (Not a Number), respectively.

copysign() copies the sign bit of an IEEE 754 number, returning the absolute value of x combined with the sign bit of y. For example, math.copysign(1, -0.0) returns -1.0. (Contributed by Christian Heimes.)

factorial() computes the factorial of a number. (Contributed by Raymond Hettinger; bpo-2138 [https://bugs.python.org/issue2138].)

fsum() adds up the stream of numbers from an iterable, and is careful to avoid loss of precision through using partial sums. (Contributed by Jean Brouwers, Raymond Hettinger, and Mark Dickinson; bpo-2819 [https://bugs.python.org/issue2819].)

acosh(), asinh() and atanh() compute the inverse hyperbolic functions.

log1p() returns the natural logarithm of 1+x (base e).

trunc() rounds a number toward zero, returning the closest Integral that’s between the function’s argument and zero. Added as part of the backport of PEP 3141’s type hierarchy for numbers.

The math module has been improved to give more consistent behaviour across platforms, especially with respect to handling of floating-point exceptions and IEEE 754 special values.

Whenever possible, the module follows the recommendations of the C99 standard about 754’s special values. For example, sqrt(-1.) should now give a ValueError across almost all platforms, while sqrt(float('NaN')) should return a NaN on all IEEE 754 platforms. Where Annex “F” of the C99 standard recommends signaling “divide-by-zero” or “invalid”, Python will raise ValueError. Where Annex “F” of the C99 standard recommends signaling “overflow”, Python will raise OverflowError. (See bpo-711019 [https://bugs.python.org/issue711019] and bpo-1640 [https://bugs.python.org/issue1640].)

(Contributed by Christian Heimes and Mark Dickinson.)

mmap objects now have a rfind() method that searches for a substring beginning at the end of the string and searching backwards. The find() method also gained an end parameter giving an index at which to stop searching. (Contributed by John Lenton.)

The operator module gained a methodcaller() function that takes a name and an optional set of arguments, returning a callable that will call the named function on any arguments passed to it. For example:

>>> # Equivalent to lambda s: s.replace('old', 'new')
>>> replacer = operator.methodcaller('replace', 'old', 'new')
>>> replacer('old wine in old bottles')
'new wine in new bottles'

(Contributed by Georg Brandl, after a suggestion by Gregory Petrosyan.)

The attrgetter() function now accepts dotted names and performs the corresponding attribute lookups:

>>> inst_name = operator.attrgetter(
...        '__class__.__name__')
>>> inst_name('')
'str'
>>> inst_name(help)
'_Helper'

(Contributed by Georg Brandl, after a suggestion by Barry Warsaw.)

The os module now wraps several new system calls. fchmod(fd, mode) and fchown(fd, uid, gid) change the mode and ownership of an opened file, and lchmod(path, mode) changes the mode of a symlink. (Contributed by Georg Brandl and Christian Heimes.)

chflags() and lchflags() are wrappers for the corresponding system calls (where they’re available), changing the flags set on a file. Constants for the flag values are defined in the stat module; some possible values include UF_IMMUTABLE to signal the file may not be changed and UF_APPEND to indicate that data can only be appended to the file. (Contributed by M. Levinson.)

os.closerange(low, high) efficiently closes all file descriptors from low to high, ignoring any errors and not including high itself. This function is now used by the subprocess module to make starting processes faster. (Contributed by Georg Brandl; bpo-1663329 [https://bugs.python.org/issue1663329].)

The os.environ object’s clear() method will now unset the environment variables using os.unsetenv() in addition to clearing the object’s keys. (Contributed by Martin Horcicka; bpo-1181 [https://bugs.python.org/issue1181].)

The os.walk() function now has a followlinks parameter. If set to True, it will follow symlinks pointing to directories and visit the directory’s contents. For backward compatibility, the parameter’s default value is false. Note that the function can fall into an infinite recursion if there’s a symlink that points to a parent directory. (bpo-1273829 [https://bugs.python.org/issue1273829])

In the os.path module, the splitext() function has been changed to not split on leading period characters. This produces better results when operating on Unix’s dot-files. For example, os.path.splitext('.ipython') now returns ('.ipython', '') instead of ('', '.ipython'). (bpo-1115886 [https://bugs.python.org/issue1115886])

A new function, os.path.relpath(path, start='.'), returns a relative path from the start path, if it’s supplied, or from the current working directory to the destination path. (Contributed by Richard Barran; bpo-1339796 [https://bugs.python.org/issue1339796].)

On Windows, os.path.expandvars() will now expand environment variables given in the form « %var% », and « ~user » will be expanded into the user’s home directory path. (Contributed by Josiah Carlson; bpo-957650 [https://bugs.python.org/issue957650].)

The Python debugger provided by the pdb module gained a new command: « run » restarts the Python program being debugged and can optionally take new command-line arguments for the program. (Contributed by Rocky Bernstein; bpo-1393667 [https://bugs.python.org/issue1393667].)

The pdb.post_mortem() function, used to begin debugging a traceback, will now use the traceback returned by sys.exc_info() if no traceback is supplied. (Contributed by Facundo Batista; bpo-1106316 [https://bugs.python.org/issue1106316].)

The pickletools module now has an optimize() function that takes a string containing a pickle and removes some unused opcodes, returning a shorter pickle that contains the same data structure. (Contributed by Raymond Hettinger.)

A get_data() function was added to the pkgutil module that returns the contents of resource files included with an installed Python package. For example:

>>> import pkgutil
>>> print pkgutil.get_data('test', 'exception_hierarchy.txt')
BaseException
 +-- SystemExit
 +-- KeyboardInterrupt
 +-- GeneratorExit
 +-- Exception
      +-- StopIteration
      +-- StandardError
 ...

(Contributed by Paul Moore; bpo-2439 [https://bugs.python.org/issue2439].)

The pyexpat module’s Parser objects now allow setting their buffer_size attribute to change the size of the buffer used to hold character data. (Contributed by Achim Gaedke; bpo-1137 [https://bugs.python.org/issue1137].)

The Queue module now provides queue variants that retrieve entries in different orders. The PriorityQueue class stores queued items in a heap and retrieves them in priority order, and LifoQueue retrieves the most recently added entries first, meaning that it behaves like a stack. (Contributed by Raymond Hettinger.)

The random module’s Random objects can now be pickled on a 32-bit system and unpickled on a 64-bit system, and vice versa. Unfortunately, this change also means that Python 2.6’s Random objects can’t be unpickled correctly on earlier versions of Python. (Contributed by Shawn Ligocki; bpo-1727780 [https://bugs.python.org/issue1727780].)

The new triangular(low, high, mode) function returns random numbers following a triangular distribution. The returned values are between low and high, not including high itself, and with mode as the most frequently occurring value in the distribution. (Contributed by Wladmir van der Laan and Raymond Hettinger; bpo-1681432 [https://bugs.python.org/issue1681432].)

Long regular expression searches carried out by the re module will check for signals being delivered, so time-consuming searches can now be interrupted. (Contributed by Josh Hoyt and Ralf Schmitt; bpo-846388 [https://bugs.python.org/issue846388].)

The regular expression module is implemented by compiling bytecodes for a tiny regex-specific virtual machine. Untrusted code could create malicious strings of bytecode directly and cause crashes, so Python 2.6 includes a verifier for the regex bytecode. (Contributed by Guido van Rossum from work for Google App Engine; bpo-3487 [https://bugs.python.org/issue3487].)

The rlcompleter module’s Completer.complete() method will now ignore exceptions triggered while evaluating a name. (Fixed by Lorenz Quack; bpo-2250 [https://bugs.python.org/issue2250].)

The sched module’s scheduler instances now have a read-only queue attribute that returns the contents of the scheduler’s queue, represented as a list of named tuples with the fields (time, priority, action, argument). (Contributed by Raymond Hettinger; bpo-1861 [https://bugs.python.org/issue1861].)

The select module now has wrapper functions for the Linux epoll() and BSD kqueue() system calls. modify() method was added to the existing poll objects; pollobj.modify(fd, eventmask) takes a file descriptor or file object and an event mask, modifying the recorded event mask for that file. (Contributed by Christian Heimes; bpo-1657 [https://bugs.python.org/issue1657].)

The shutil.copytree() function now has an optional ignore argument that takes a callable object. This callable will receive each directory path and a list of the directory’s contents, and returns a list of names that will be ignored, not copied.

The shutil module also provides an ignore_patterns() function for use with this new parameter. ignore_patterns() takes an arbitrary number of glob-style patterns and returns a callable that will ignore any files and directories that match any of these patterns. The following example copies a directory tree, but skips both .svn directories and Emacs backup files, which have names ending with “~”:

shutil.copytree('Doc/library', '/tmp/library',
                ignore=shutil.ignore_patterns('*~', '.svn'))

(Contribution par Tarek Ziadé; bpo-2663 [https://bugs.python.org/issue2663].)

Integrating signal handling with GUI handling event loops like those used by Tkinter or GTk+ has long been a problem; most software ends up polling, waking up every fraction of a second to check if any GUI events have occurred. The signal module can now make this more efficient. Calling signal.set_wakeup_fd(fd) sets a file descriptor to be used; when a signal is received, a byte is written to that file descriptor. There’s also a C-level function, PySignal_SetWakeupFd(), for setting the descriptor.

Event loops will use this by opening a pipe to create two descriptors, one for reading and one for writing. The writable descriptor will be passed to set_wakeup_fd(), and the readable descriptor will be added to the list of descriptors monitored by the event loop via select() or poll(). On receiving a signal, a byte will be written and the main event loop will be woken up, avoiding the need to poll.

(Contributed by Adam Olsen; bpo-1583 [https://bugs.python.org/issue1583].)

The siginterrupt() function is now available from Python code, and allows changing whether signals can interrupt system calls or not. (Contributed by Ralf Schmitt.)

The setitimer() and getitimer() functions have also been added (where they’re available). setitimer() allows setting interval timers that will cause a signal to be delivered to the process after a specified time, measured in wall-clock time, consumed process time, or combined process+system time. (Contributed by Guilherme Polo; bpo-2240 [https://bugs.python.org/issue2240].)

The smtplib module now supports SMTP over SSL thanks to the addition of the SMTP_SSL class. This class supports an interface identical to the existing SMTP class. (Contributed by Monty Taylor.) Both class constructors also have an optional timeout parameter that specifies a timeout for the initial connection attempt, measured in seconds. (Contributed by Facundo Batista.)

An implementation of the LMTP protocol (RFC 2033 [https://tools.ietf.org/html/rfc2033.html]) was also added to the module. LMTP is used in place of SMTP when transferring e-mail between agents that don’t manage a mail queue. (LMTP implemented by Leif Hedstrom; bpo-957003 [https://bugs.python.org/issue957003].)

SMTP.starttls() now complies with RFC 3207 [https://tools.ietf.org/html/rfc3207.html] and forgets any knowledge obtained from the server not obtained from the TLS negotiation itself. (Patch contributed by Bill Fenner; bpo-829951 [https://bugs.python.org/issue829951].)

The socket module now supports TIPC (http://tipc.sourceforge.net/), a high-performance non-IP-based protocol designed for use in clustered environments. TIPC addresses are 4- or 5-tuples. (Contributed by Alberto Bertogli; bpo-1646 [https://bugs.python.org/issue1646].)

A new function, create_connection(), takes an address and connects to it using an optional timeout value, returning the connected socket object. This function also looks up the address’s type and connects to it using IPv4 or IPv6 as appropriate. Changing your code to use create_connection() instead of socket(socket.AF_INET, ...) may be all that’s required to make your code work with IPv6.

The base classes in the SocketServer module now support calling a handle_timeout() method after a span of inactivity specified by the server’s timeout attribute. (Contributed by Michael Pomraning.) The serve_forever() method now takes an optional poll interval measured in seconds, controlling how often the server will check for a shutdown request. (Contributed by Pedro Werneck and Jeffrey Yasskin; bpo-742598 [https://bugs.python.org/issue742598], bpo-1193577 [https://bugs.python.org/issue1193577].)

The sqlite3 module, maintained by Gerhard Häring, has been updated from version 2.3.2 in Python 2.5 to version 2.4.1.

The struct module now supports the C99 _Bool type, using the format character '?'. (Contributed by David Remahl.)

The Popen objects provided by the subprocess module now have terminate(), kill(), and send_signal() methods. On Windows, send_signal() only supports the SIGTERM signal, and all these methods are aliases for the Win32 API function TerminateProcess(). (Contributed by Christian Heimes.)

A new variable in the sys module, float_info, is an object containing information derived from the float.h file about the platform’s floating-point support. Attributes of this object include mant_dig (number of digits in the mantissa), epsilon (smallest difference between 1.0 and the next largest value representable), and several others. (Contributed by Christian Heimes; bpo-1534 [https://bugs.python.org/issue1534].)

Another new variable, dont_write_bytecode, controls whether Python writes any .pyc or .pyo files on importing a module. If this variable is true, the compiled files are not written. The variable is initially set on start-up by supplying the -B switch to the Python interpreter, or by setting the PYTHONDONTWRITEBYTECODE environment variable before running the interpreter. Python code can subsequently change the value of this variable to control whether bytecode files are written or not. (Contributed by Neal Norwitz and Georg Brandl.)

Information about the command-line arguments supplied to the Python interpreter is available by reading attributes of a named tuple available as sys.flags. For example, the verbose attribute is true if Python was executed in verbose mode, debug is true in debugging mode, etc. These attributes are all read-only. (Contributed by Christian Heimes.)

A new function, getsizeof(), takes a Python object and returns the amount of memory used by the object, measured in bytes. Built-in objects return correct results; third-party extensions may not, but can define a __sizeof__() method to return the object’s size. (Contributed by Robert Schuppenies; bpo-2898 [https://bugs.python.org/issue2898].)

It’s now possible to determine the current profiler and tracer functions by calling sys.getprofile() and sys.gettrace(). (Contributed by Georg Brandl; bpo-1648 [https://bugs.python.org/issue1648].)

The tarfile module now supports POSIX.1-2001 (pax) tarfiles in addition to the POSIX.1-1988 (ustar) and GNU tar formats that were already supported. The default format is GNU tar; specify the format parameter to open a file using a different format:

tar = tarfile.open("output.tar", "w",
                   format=tarfile.PAX_FORMAT)

The new encoding and errors parameters specify an encoding and an error handling scheme for character conversions. 'strict', 'ignore', and 'replace' are the three standard ways Python can handle errors,; 'utf-8' is a special value that replaces bad characters with their UTF-8 representation. (Character conversions occur because the PAX format supports Unicode filenames, defaulting to UTF-8 encoding.)

The TarFile.add() method now accepts an exclude argument that’s a function that can be used to exclude certain filenames from an archive. The function must take a filename and return true if the file should be excluded or false if it should be archived. The function is applied to both the name initially passed to add() and to the names of files in recursively-added directories.

(All changes contributed by Lars Gustäbel).

An optional timeout parameter was added to the telnetlib.Telnet class constructor, specifying a timeout measured in seconds. (Added by Facundo Batista.)

The tempfile.NamedTemporaryFile class usually deletes the temporary file it created when the file is closed. This behaviour can now be changed by passing delete=False to the constructor. (Contributed by Damien Miller; bpo-1537850 [https://bugs.python.org/issue1537850].)

A new class, SpooledTemporaryFile, behaves like a temporary file but stores its data in memory until a maximum size is exceeded. On reaching that limit, the contents will be written to an on-disk temporary file. (Contributed by Dustin J. Mitchell.)

The NamedTemporaryFile and SpooledTemporaryFile classes both work as context managers, so you can write with tempfile.NamedTemporaryFile() as tmp: .... (Contributed by Alexander Belopolsky; bpo-2021 [https://bugs.python.org/issue2021].)

The test.test_support module gained a number of context managers useful for writing tests. EnvironmentVarGuard() is a context manager that temporarily changes environment variables and automatically restores them to their old values.

Another context manager, TransientResource, can surround calls to resources that may or may not be available; it will catch and ignore a specified list of exceptions. For example, a network test may ignore certain failures when connecting to an external web site:

with test_support.TransientResource(IOError,
                                errno=errno.ETIMEDOUT):
    f = urllib.urlopen('https://sf.net')
    ...

Finally, check_warnings() resets the warning module’s warning filters and returns an object that will record all warning messages triggered (bpo-3781 [https://bugs.python.org/issue3781]):

with test_support.check_warnings() as wrec:
    warnings.simplefilter("always")
    # ... code that triggers a warning ...
    assert str(wrec.message) == "function is outdated"
    assert len(wrec.warnings) == 1, "Multiple warnings raised"

(Contributed by Brett Cannon.)

The textwrap module can now preserve existing whitespace at the beginnings and ends of the newly-created lines by specifying drop_whitespace=False as an argument:

>>> S = """This  sentence  has a bunch   of
...   extra   whitespace."""
>>> print textwrap.fill(S, width=15)
This  sentence
has a bunch
of    extra
whitespace.
>>> print textwrap.fill(S, drop_whitespace=False, width=15)
This  sentence
  has a bunch
   of    extra
   whitespace.
>>>

(Contributed by Dwayne Bailey; bpo-1581073 [https://bugs.python.org/issue1581073].)

The threading module API is being changed to use properties such as daemon instead of setDaemon() and isDaemon() methods, and some methods have been renamed to use underscores instead of camel-case; for example, the activeCount() method is renamed to active_count(). Both the 2.6 and 3.0 versions of the module support the same properties and renamed methods, but don’t remove the old methods. No date has been set for the deprecation of the old APIs in Python 3.x; the old APIs won’t be removed in any 2.x version. (Carried out by several people, most notably Benjamin Peterson.)

The threading module’s Thread objects gained an ident property that returns the thread’s identifier, a nonzero integer. (Contributed by Gregory P. Smith; bpo-2871 [https://bugs.python.org/issue2871].)

The timeit module now accepts callables as well as strings for the statement being timed and for the setup code. Two convenience functions were added for creating Timer instances: repeat(stmt, setup, time, repeat, number) and timeit(stmt, setup, time, number) create an instance and call the corresponding method. (Contributed by Erik Demaine; bpo-1533909 [https://bugs.python.org/issue1533909].)

The Tkinter module now accepts lists and tuples for options, separating the elements by spaces before passing the resulting value to Tcl/Tk. (Contributed by Guilherme Polo; bpo-2906 [https://bugs.python.org/issue2906].)

The turtle module for turtle graphics was greatly enhanced by Gregor Lingl. New features in the module include:

Better animation of turtle movement and rotation.

Control over turtle movement using the new delay(), tracer(), and speed() methods.

The ability to set new shapes for the turtle, and to define a new coordinate system.

Turtles now have an undo() method that can roll back actions.

Simple support for reacting to input events such as mouse and keyboard activity, making it possible to write simple games.

A turtle.cfg file can be used to customize the starting appearance of the turtle’s screen.

The module’s docstrings can be replaced by new docstrings that have been translated into another language.

(bpo-1513695 [https://bugs.python.org/issue1513695])

An optional timeout parameter was added to the urllib.urlopen() function and the urllib.ftpwrapper class constructor, as well as the urllib2.urlopen() function. The parameter specifies a timeout measured in seconds. For example:

>>> u = urllib2.urlopen("http://slow.example.com",
                        timeout=3)
Traceback (most recent call last):
  ...
urllib2.URLError: <urlopen error timed out>
>>>

(Added by Facundo Batista.)

The Unicode database provided by the unicodedata module has been updated to version 5.1.0. (Updated by Martin von Löwis; bpo-3811 [https://bugs.python.org/issue3811].)

The warnings module’s formatwarning() and showwarning() gained an optional line argument that can be used to supply the line of source code. (Added as part of bpo-1631171 [https://bugs.python.org/issue1631171], which re-implemented part of the warnings module in C code.)

A new function, catch_warnings(), is a context manager intended for testing purposes that lets you temporarily modify the warning filters and then restore their original values (bpo-3781 [https://bugs.python.org/issue3781]).

The XML-RPC SimpleXMLRPCServer and DocXMLRPCServer classes can now be prevented from immediately opening and binding to their socket by passing False as the bind_and_activate constructor parameter. This can be used to modify the instance’s allow_reuse_address attribute before calling the server_bind() and server_activate() methods to open the socket and begin listening for connections. (Contributed by Peter Parente; bpo-1599845 [https://bugs.python.org/issue1599845].)

SimpleXMLRPCServer also has a _send_traceback_header attribute; if true, the exception and formatted traceback are returned as HTTP headers « X-Exception » and « X-Traceback ». This feature is for debugging purposes only and should not be used on production servers because the tracebacks might reveal passwords or other sensitive information. (Contributed by Alan McIntyre as part of his project for Google’s Summer of Code 2007.)

The xmlrpclib module no longer automatically converts datetime.date and datetime.time to the xmlrpclib.DateTime type; the conversion semantics were not necessarily correct for all applications. Code using xmlrpclib should convert date and time instances. (bpo-1330538 [https://bugs.python.org/issue1330538]) The code can also handle dates before 1900 (contributed by Ralf Schmitt; bpo-2014 [https://bugs.python.org/issue2014]) and 64-bit integers represented by using <i8> in XML-RPC responses (contributed by Riku Lindblad; bpo-2985 [https://bugs.python.org/issue2985]).

The zipfile module’s ZipFile class now has extract() and extractall() methods that will unpack a single file or all the files in the archive to the current directory, or to a specified directory:

z = zipfile.ZipFile('python-251.zip')

# Unpack a single file, writing it relative
# to the /tmp directory.
z.extract('Python/sysmodule.c', '/tmp')

# Unpack all the files in the archive.
z.extractall()

(Contributed by Alan McIntyre; bpo-467924 [https://bugs.python.org/issue467924].)

The open(), read() and extract() methods can now take either a filename or a ZipInfo object. This is useful when an archive accidentally contains a duplicated filename. (Contributed by Graham Horler; bpo-1775025 [https://bugs.python.org/issue1775025].)

Finally, zipfile now supports using Unicode filenames for archived files. (Contributed by Alexey Borzenkov; bpo-1734346 [https://bugs.python.org/issue1734346].)

The ast module

The ast module provides an Abstract Syntax Tree representation of Python code, and Armin Ronacher contributed a set of helper functions that perform a variety of common tasks. These will be useful for HTML templating packages, code analyzers, and similar tools that process Python code.

The parse() function takes an expression and returns an AST. The dump() function outputs a representation of a tree, suitable for debugging:

import ast

t = ast.parse("""
d = {}
for i in 'abcdefghijklm':
    d[i + i] = ord(i) - ord('a') + 1
print d
""")
print ast.dump(t)

This outputs a deeply nested tree:

Module(body=[
  Assign(targets=[
    Name(id='d', ctx=Store())
   ], value=Dict(keys=[], values=[]))
  For(target=Name(id='i', ctx=Store()),
      iter=Str(s='abcdefghijklm'), body=[
    Assign(targets=[
      Subscript(value=
        Name(id='d', ctx=Load()),
          slice=
          Index(value=
            BinOp(left=Name(id='i', ctx=Load()), op=Add(),
             right=Name(id='i', ctx=Load()))), ctx=Store())
     ], value=
     BinOp(left=
      BinOp(left=
       Call(func=
        Name(id='ord', ctx=Load()), args=[
          Name(id='i', ctx=Load())
         ], keywords=[], starargs=None, kwargs=None),
       op=Sub(), right=Call(func=
        Name(id='ord', ctx=Load()), args=[
          Str(s='a')
         ], keywords=[], starargs=None, kwargs=None)),
       op=Add(), right=Num(n=1)))
    ], orelse=[])
   Print(dest=None, values=[
     Name(id='d', ctx=Load())
   ], nl=True)
 ])

The literal_eval() method takes a string or an AST representing a literal expression, parses and evaluates it, and returns the resulting value. A literal expression is a Python expression containing only strings, numbers, dictionaries, etc. but no statements or function calls. If you need to evaluate an expression but cannot accept the security risk of using an eval() call, literal_eval() will handle it safely:

>>> literal = '("a", "b", {2:4, 3:8, 1:2})'
>>> print ast.literal_eval(literal)
('a', 'b', {1: 2, 2: 4, 3: 8})
>>> print ast.literal_eval('"a" + "b"')
Traceback (most recent call last):
  ...
ValueError: malformed string

The module also includes NodeVisitor and NodeTransformer classes for traversing and modifying an AST, and functions for common transformations such as changing line numbers.

The future_builtins module

Python 3.0 makes many changes to the repertoire of built-in functions, and most of the changes can’t be introduced in the Python 2.x series because they would break compatibility. The future_builtins module provides versions of these built-in functions that can be imported when writing 3.0-compatible code.

The functions in this module currently include:

ascii(obj): equivalent to repr(). In Python 3.0, repr() will return a Unicode string, while ascii() will return a pure ASCII bytestring.

filter(predicate, iterable), map(func, iterable1, ...): the 3.0 versions return iterators, unlike the 2.x builtins which return lists.

hex(value), oct(value): instead of calling the __hex__() or __oct__() methods, these versions will call the __index__() method and convert the result to hexadecimal or octal. oct() will use the new 0o notation for its result.

The json module: JavaScript Object Notation

The new json module supports the encoding and decoding of Python types in JSON (Javascript Object Notation). JSON is a lightweight interchange format often used in web applications. For more information about JSON, see http://www.json.org.

json comes with support for decoding and encoding most built-in Python types. The following example encodes and decodes a dictionary:

>>> import json
>>> data = {"spam": "foo", "parrot": 42}
>>> in_json = json.dumps(data) # Encode the data
>>> in_json
'{"parrot": 42, "spam": "foo"}'
>>> json.loads(in_json) # Decode into a Python object
{"spam": "foo", "parrot": 42}

It’s also possible to write your own decoders and encoders to support more types. Pretty-printing of the JSON strings is also supported.

json (originally called simplejson) was written by Bob Ippolito.

The plistlib module: A Property-List Parser

The .plist format is commonly used on Mac OS X to store basic data types (numbers, strings, lists, and dictionaries) by serializing them into an XML-based format. It resembles the XML-RPC serialization of data types.

Despite being primarily used on Mac OS X, the format has nothing Mac-specific about it and the Python implementation works on any platform that Python supports, so the plistlib module has been promoted to the standard library.

Using the module is simple:

import sys
import plistlib
import datetime

# Create data structure
data_struct = dict(lastAccessed=datetime.datetime.now(),
                   version=1,
                   categories=('Personal','Shared','Private'))

# Create string containing XML.
plist_str = plistlib.writePlistToString(data_struct)
new_struct = plistlib.readPlistFromString(plist_str)
print data_struct
print new_struct

# Write data structure to a file and read it back.
plistlib.writePlist(data_struct, '/tmp/customizations.plist')
new_struct = plistlib.readPlist('/tmp/customizations.plist')

# read/writePlist accepts file-like objects as well as paths.
plistlib.writePlist(data_struct, sys.stdout)

ctypes Enhancements

Thomas Heller continued to maintain and enhance the ctypes module.

ctypes now supports a c_bool datatype that represents the C99 bool type. (Contributed by David Remahl; bpo-1649190 [https://bugs.python.org/issue1649190].)

The ctypes string, buffer and array types have improved support for extended slicing syntax, where various combinations of (start, stop, step) are supplied. (Implemented by Thomas Wouters.)

All ctypes data types now support from_buffer() and from_buffer_copy() methods that create a ctypes instance based on a provided buffer object. from_buffer_copy() copies the contents of the object, while from_buffer() will share the same memory area.

A new calling convention tells ctypes to clear the errno or Win32 LastError variables at the outset of each wrapped call. (Implemented by Thomas Heller; bpo-1798 [https://bugs.python.org/issue1798].)

You can now retrieve the Unix errno variable after a function call. When creating a wrapped function, you can supply use_errno=True as a keyword parameter to the DLL() function and then call the module-level methods set_errno() and get_errno() to set and retrieve the error value.

The Win32 LastError variable is similarly supported by the DLL(), OleDLL(), and WinDLL() functions. You supply use_last_error=True as a keyword parameter and then call the module-level methods set_last_error() and get_last_error().

The byref() function, used to retrieve a pointer to a ctypes instance, now has an optional offset parameter that is a byte count that will be added to the returned pointer.

Improved SSL Support

Bill Janssen made extensive improvements to Python 2.6’s support for the Secure Sockets Layer by adding a new module, ssl, that’s built atop the OpenSSL [https://www.openssl.org/] library. This new module provides more control over the protocol negotiated, the X.509 certificates used, and has better support for writing SSL servers (as opposed to clients) in Python. The existing SSL support in the socket module hasn’t been removed and continues to work, though it will be removed in Python 3.0.

To use the new module, you must first create a TCP connection in the usual way and then pass it to the ssl.wrap_socket() function. It’s possible to specify whether a certificate is required, and to obtain certificate info by calling the getpeercert() method.

Voir aussi

The documentation for the ssl module.

Deprecations and Removals

String exceptions have been removed. Attempting to use them raises a TypeError.

Changes to the Exception interface as dictated by PEP 352 [https://www.python.org/dev/peps/pep-0352] continue to be made. For 2.6, the message attribute is being deprecated in favor of the args attribute.

(3.0-warning mode) Python 3.0 will feature a reorganized standard library that will drop many outdated modules and rename others. Python 2.6 running in 3.0-warning mode will warn about these modules when they are imported.

The list of deprecated modules is: audiodev, bgenlocations, buildtools, bundlebuilder, Canvas, compiler, dircache, dl, fpformat, gensuitemodule, ihooks, imageop, imgfile, linuxaudiodev, mhlib, mimetools, multifile, new, pure, statvfs, sunaudiodev, test.testall, and toaiff.

The gopherlib module has been removed.

The MimeWriter module and mimify module have been deprecated; use the email package instead.

The md5 module has been deprecated; use the hashlib module instead.

The posixfile module has been deprecated; fcntl.lockf() provides better locking.

The popen2 module has been deprecated; use the subprocess module.

The rgbimg module has been removed.

The sets module has been deprecated; it’s better to use the built-in set and frozenset types.

The sha module has been deprecated; use the hashlib module instead.

Build and C API Changes

Changes to Python’s build process and to the C API include:

Python now must be compiled with C89 compilers (after 19 years!). This means that the Python source tree has dropped its own implementations of memmove() and strerror(), which are in the C89 standard library.

Python 2.6 can be built with Microsoft Visual Studio 2008 (version 9.0), and this is the new default compiler. See the PCbuild directory for the build files. (Implemented by Christian Heimes.)

On Mac OS X, Python 2.6 can be compiled as a 4-way universal build. The configure script can take a --with-universal-archs=[32-bit|64-bit|all] switch, controlling whether the binaries are built for 32-bit architectures (x86, PowerPC), 64-bit (x86-64 and PPC-64), or both. (Contributed by Ronald Oussoren.)

The BerkeleyDB module now has a C API object, available as bsddb.db.api. This object can be used by other C extensions that wish to use the bsddb module for their own purposes. (Contributed by Duncan Grisby.)

The new buffer interface, previously described in the PEP 3118 section, adds PyObject_GetBuffer() and PyBuffer_Release(), as well as a few other functions.

Python’s use of the C stdio library is now thread-safe, or at least as thread-safe as the underlying library is. A long-standing potential bug occurred if one thread closed a file object while another thread was reading from or writing to the object. In 2.6 file objects have a reference count, manipulated by the PyFile_IncUseCount() and PyFile_DecUseCount() functions. File objects can’t be closed unless the reference count is zero. PyFile_IncUseCount() should be called while the GIL is still held, before carrying out an I/O operation using the FILE * pointer, and PyFile_DecUseCount() should be called immediately after the GIL is re-acquired. (Contributed by Antoine Pitrou and Gregory P. Smith.)

Importing modules simultaneously in two different threads no longer deadlocks; it will now raise an ImportError. A new API function, PyImport_ImportModuleNoBlock(), will look for a module in sys.modules first, then try to import it after acquiring an import lock. If the import lock is held by another thread, an ImportError is raised. (Contributed by Christian Heimes.)

Several functions return information about the platform’s floating-point support. PyFloat_GetMax() returns the maximum representable floating point value, and PyFloat_GetMin() returns the minimum positive value. PyFloat_GetInfo() returns an object containing more information from the float.h file, such as "mant_dig" (number of digits in the mantissa), "epsilon" (smallest difference between 1.0 and the next largest value representable), and several others. (Contributed by Christian Heimes; bpo-1534 [https://bugs.python.org/issue1534].)

C functions and methods that use PyComplex_AsCComplex() will now accept arguments that have a __complex__() method. In particular, the functions in the cmath module will now accept objects with this method. This is a backport of a Python 3.0 change. (Contributed by Mark Dickinson; bpo-1675423 [https://bugs.python.org/issue1675423].)

Python’s C API now includes two functions for case-insensitive string comparisons, PyOS_stricmp(char*, char*) and PyOS_strnicmp(char*, char*, Py_ssize_t). (Contributed by Christian Heimes; bpo-1635 [https://bugs.python.org/issue1635].)

Many C extensions define their own little macro for adding integers and strings to the module’s dictionary in the init* function. Python 2.6 finally defines standard macros for adding values to a module, PyModule_AddStringMacro and PyModule_AddIntMacro(). (Contributed by Christian Heimes.)

Some macros were renamed in both 3.0 and 2.6 to make it clearer that they are macros, not functions. Py_Size() became Py_SIZE(), Py_Type() became Py_TYPE(), and Py_Refcnt() became Py_REFCNT(). The mixed-case macros are still available in Python 2.6 for backward compatibility. (bpo-1629 [https://bugs.python.org/issue1629])

Distutils now places C extensions it builds in a different directory when running on a debug version of Python. (Contributed by Collin Winter; bpo-1530959 [https://bugs.python.org/issue1530959].)

Several basic data types, such as integers and strings, maintain internal free lists of objects that can be re-used. The data structures for these free lists now follow a naming convention: the variable is always named free_list, the counter is always named numfree, and a macro Py<typename>_MAXFREELIST is always defined.

A new Makefile target, « make patchcheck », prepares the Python source tree for making a patch: it fixes trailing whitespace in all modified .py files, checks whether the documentation has been changed, and reports whether the Misc/ACKS and Misc/NEWS files have been updated. (Contributed by Brett Cannon.)

Another new target, « make profile-opt », compiles a Python binary using GCC’s profile-guided optimization. It compiles Python with profiling enabled, runs the test suite to obtain a set of profiling results, and then compiles using these results for optimization. (Contributed by Gregory P. Smith.)

Port-Specific Changes: Windows

The support for Windows 95, 98, ME and NT4 has been dropped. Python 2.6 requires at least Windows 2000 SP4.

The new default compiler on Windows is Visual Studio 2008 (version 9.0). The build directories for Visual Studio 2003 (version 7.1) and 2005 (version 8.0) were moved into the PC/ directory. The new PCbuild directory supports cross compilation for X64, debug builds and Profile Guided Optimization (PGO). PGO builds are roughly 10% faster than normal builds. (Contributed by Christian Heimes with help from Amaury Forgeot d’Arc and Martin von Löwis.)

The msvcrt module now supports both the normal and wide char variants of the console I/O API. The getwch() function reads a keypress and returns a Unicode value, as does the getwche() function. The putwch() function takes a Unicode character and writes it to the console. (Contributed by Christian Heimes.)

os.path.expandvars() will now expand environment variables in the form « %var% », and « ~user » will be expanded into the user’s home directory path. (Contributed by Josiah Carlson; bpo-957650 [https://bugs.python.org/issue957650].)

The socket module’s socket objects now have an ioctl() method that provides a limited interface to the WSAIoctl() system interface.

The _winreg module now has a function, ExpandEnvironmentStrings(), that expands environment variable references such as %NAME% in an input string. The handle objects provided by this module now support the context protocol, so they can be used in with statements. (Contributed by Christian Heimes.)

_winreg also has better support for x64 systems, exposing the DisableReflectionKey(), EnableReflectionKey(), and QueryReflectionKey() functions, which enable and disable registry reflection for 32-bit processes running on 64-bit systems. (bpo-1753245 [https://bugs.python.org/issue1753245])

The msilib module’s Record object gained GetInteger() and GetString() methods that return field values as an integer or a string. (Contributed by Floris Bruynooghe; bpo-2125 [https://bugs.python.org/issue2125].)

Port-Specific Changes: Mac OS X

When compiling a framework build of Python, you can now specify the framework name to be used by providing the --with-framework-name= option to the configure script.

The macfs module has been removed. This in turn required the macostools.touched() function to be removed because it depended on the macfs module. (bpo-1490190 [https://bugs.python.org/issue1490190])

Many other Mac OS modules have been deprecated and will be removed in Python 3.0: _builtinSuites, aepack, aetools, aetypes, applesingle, appletrawmain, appletrunner, argvemulator, Audio_mac, autoGIL, Carbon, cfmfile, CodeWarrior, ColorPicker, EasyDialogs, Explorer, Finder, FrameWork, findertools, ic, icglue, icopen, macerrors, MacOS, macfs, macostools, macresource, MiniAEFrame, Nav, Netscape, OSATerminology, pimp, PixMapWrapper, StdSuites, SystemEvents, Terminal, and terminalcommand.

Port-Specific Changes: IRIX

A number of old IRIX-specific modules were deprecated and will be removed in Python 3.0: al and AL, cd, cddb, cdplayer, CL and cl, DEVICE, ERRNO, FILE, FL and fl, flp, fm, GET, GLWS, GL and gl, IN, IOCTL, jpeg, panelparser, readcd, SV and sv, torgb, videoreader, and WAIT.

Portage vers Python 2.6

This section lists previously described changes and other bugfixes that may require changes to your code:

Classes that aren’t supposed to be hashable should set __hash__ = None in their definitions to indicate the fact.

String exceptions have been removed. Attempting to use them raises a TypeError.

The __init__() method of collections.deque now clears any existing contents of the deque before adding elements from the iterable. This change makes the behavior match list.__init__().

object.__init__() previously accepted arbitrary arguments and keyword arguments, ignoring them. In Python 2.6, this is no longer allowed and will result in a TypeError. This will affect __init__() methods that end up calling the corresponding method on object (perhaps through using super()). See bpo-1683368 [https://bugs.python.org/issue1683368] for discussion.

The Decimal constructor now accepts leading and trailing whitespace when passed a string. Previously it would raise an InvalidOperation exception. On the other hand, the create_decimal() method of Context objects now explicitly disallows extra whitespace, raising a ConversionSyntax exception.

Due to an implementation accident, if you passed a file path to the built-in __import__() function, it would actually import the specified file. This was never intended to work, however, and the implementation now explicitly checks for this case and raises an ImportError.

C API: the PyImport_Import() and PyImport_ImportModule() functions now default to absolute imports, not relative imports. This will affect C extensions that import other modules.

C API: extension data types that shouldn’t be hashable should define their tp_hash slot to PyObject_HashNotImplemented().

The socket module exception socket.error now inherits from IOError. Previously it wasn’t a subclass of StandardError but now it is, through IOError. (Implemented by Gregory P. Smith; bpo-1706815 [https://bugs.python.org/issue1706815].)

The xmlrpclib module no longer automatically converts datetime.date and datetime.time to the xmlrpclib.DateTime type; the conversion semantics were not necessarily correct for all applications. Code using xmlrpclib should convert date and time instances. (bpo-1330538 [https://bugs.python.org/issue1330538])

(3.0-warning mode) The Exception class now warns when accessed using slicing or index access; having Exception behave like a tuple is being phased out.

(3.0-warning mode) inequality comparisons between two dictionaries or two objects that don’t implement comparison methods are reported as warnings. dict1 == dict2 still works, but dict1 < dict2 is being phased out.

Comparisons between cells, which are an implementation detail of Python’s scoping rules, also cause warnings because such comparisons are forbidden entirely in 3.0.

Remerciements

The author would like to thank the following people for offering suggestions, corrections and assistance with various drafts of this article: Georg Brandl, Steve Brown, Nick Coghlan, Ralph Corderoy, Jim Jewett, Kent Johnson, Chris Lambacher, Martin Michlmayr, Antoine Pitrou, Brian Warner.

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Nouveautés de Python 2.5

Auteur

A.M. Kuchling

This article explains the new features in Python 2.5. The final release of Python 2.5 is scheduled for August 2006; PEP 356 [https://www.python.org/dev/peps/pep-0356] describes the planned release schedule.

The changes in Python 2.5 are an interesting mix of language and library improvements. The library enhancements will be more important to Python’s user community, I think, because several widely-useful packages were added. New modules include ElementTree for XML processing (xml.etree), the SQLite database module (sqlite), and the ctypes module for calling C functions.

The language changes are of middling significance. Some pleasant new features were added, but most of them aren’t features that you’ll use every day. Conditional expressions were finally added to the language using a novel syntax; see section PEP 308 : Expressions conditionnelles. The new “with” statement will make writing cleanup code easier (section PEP 343: The “with” statement). Values can now be passed into generators (section PEP 342: New Generator Features). Imports are now visible as either absolute or relative (section PEP 328: Absolute and Relative Imports). Some corner cases of exception handling are handled better (section PEP 341: Unified try/except/finally). All these improvements are worthwhile, but they’re improvements to one specific language feature or another; none of them are broad modifications to Python’s semantics.

As well as the language and library additions, other improvements and bugfixes were made throughout the source tree. A search through the SVN change logs finds there were 353 patches applied and 458 bugs fixed between Python 2.4 and 2.5. (Both figures are likely to be underestimates.)

This article doesn’t try to be a complete specification of the new features; instead changes are briefly introduced using helpful examples. For full details, you should always refer to the documentation for Python 2.5 at https://docs.python.org. If you want to understand the complete implementation and design rationale, refer to the PEP for a particular new feature.

Comments, suggestions, and error reports for this document are welcome; please e-mail them to the author or open a bug in the Python bug tracker.

PEP 308 : Expressions conditionnelles

For a long time, people have been requesting a way to write conditional expressions, which are expressions that return value A or value B depending on whether a Boolean value is true or false. A conditional expression lets you write a single assignment statement that has the same effect as the following:

if condition:
    x = true_value
else:
    x = false_value

There have been endless tedious discussions of syntax on both python-dev and comp.lang.python. A vote was even held that found the majority of voters wanted conditional expressions in some form, but there was no syntax that was preferred by a clear majority. Candidates included C’s cond ? true_v : false_v, if cond then true_v else false_v, and 16 other variations.

Guido van Rossum a finalement choisi une syntaxe surprenante :

x = true_value if condition else false_value

Evaluation is still lazy as in existing Boolean expressions, so the order of evaluation jumps around a bit. The condition expression in the middle is evaluated first, and the true_value expression is evaluated only if the condition was true. Similarly, the false_value expression is only evaluated when the condition is false.

This syntax may seem strange and backwards; why does the condition go in the middle of the expression, and not in the front as in C’s c ? x : y? The decision was checked by applying the new syntax to the modules in the standard library and seeing how the resulting code read. In many cases where a conditional expression is used, one value seems to be the “common case” and one value is an “exceptional case”, used only on rarer occasions when the condition isn’t met. The conditional syntax makes this pattern a bit more obvious:

contents = ((doc + '\n') if doc else '')

I read the above statement as meaning « here contents is usually assigned a value of doc+'\n'; sometimes doc is empty, in which special case an empty string is returned. » I doubt I will use conditional expressions very often where there isn’t a clear common and uncommon case.

There was some discussion of whether the language should require surrounding conditional expressions with parentheses. The decision was made to not require parentheses in the Python language’s grammar, but as a matter of style I think you should always use them. Consider these two statements:

# First version -- no parens
level = 1 if logging else 0

# Second version -- with parens
level = (1 if logging else 0)

In the first version, I think a reader’s eye might group the statement into “level = 1”, “if logging”, “else 0”, and think that the condition decides whether the assignment to level is performed. The second version reads better, in my opinion, because it makes it clear that the assignment is always performed and the choice is being made between two values.

Another reason for including the brackets: a few odd combinations of list comprehensions and lambdas could look like incorrect conditional expressions. See PEP 308 [https://www.python.org/dev/peps/pep-0308] for some examples. If you put parentheses around your conditional expressions, you won’t run into this case.

Voir aussi

PEP 308 [https://www.python.org/dev/peps/pep-0308] – Expressions conditionnelles

PEP écrite par Guido van Rossum et Raymond D. Hettinger; implémentée par Thomas Wouters.

PEP 309 : Application partielle de fonction

The functools module is intended to contain tools for functional-style programming.

One useful tool in this module is the partial() function. For programs written in a functional style, you’ll sometimes want to construct variants of existing functions that have some of the parameters filled in. Consider a Python function f(a, b, c); you could create a new function g(b, c) that was equivalent to f(1, b, c). This is called « partial function application ».

partial() takes the arguments (function, arg1, arg2, ... kwarg1=value1, kwarg2=value2). The resulting object is callable, so you can just call it to invoke function with the filled-in arguments.

Voici un exemple court mais réaliste :

import functools

def log (message, subsystem):
    "Write the contents of 'message' to the specified subsystem."
    print '%s: %s' % (subsystem, message)
    ...

server_log = functools.partial(log, subsystem='server')
server_log('Unable to open socket')

Here’s another example, from a program that uses PyGTK. Here a context-sensitive pop-up menu is being constructed dynamically. The callback provided for the menu option is a partially applied version of the open_item() method, where the first argument has been provided.

...
class Application:
    def open_item(self, path):
       ...
    def init (self):
        open_func = functools.partial(self.open_item, item_path)
        popup_menu.append( ("Open", open_func, 1) )

Another function in the functools module is the update_wrapper(wrapper, wrapped) function that helps you write well-behaved decorators. update_wrapper() copies the name, module, and docstring attribute to a wrapper function so that tracebacks inside the wrapped function are easier to understand. For example, you might write:

def my_decorator(f):
    def wrapper(*args, **kwds):
        print 'Calling decorated function'
        return f(*args, **kwds)
    functools.update_wrapper(wrapper, f)
    return wrapper

wraps() is a decorator that can be used inside your own decorators to copy the wrapped function’s information. An alternate version of the previous example would be:

def my_decorator(f):
    @functools.wraps(f)
    def wrapper(*args, **kwds):
        print 'Calling decorated function'
        return f(*args, **kwds)
    return wrapper

Voir aussi

PEP 309 [https://www.python.org/dev/peps/pep-0309] – Application partielle de fonction

PEP proposed and written by Peter Harris; implemented by Hye-Shik Chang and Nick Coghlan, with adaptations by Raymond Hettinger.

PEP 314: Metadata for Python Software Packages v1.1

Some simple dependency support was added to Distutils. The setup() function now has requires, provides, and obsoletes keyword parameters. When you build a source distribution using the sdist command, the dependency information will be recorded in the PKG-INFO file.

Another new keyword parameter is download_url, which should be set to a URL for the package’s source code. This means it’s now possible to look up an entry in the package index, determine the dependencies for a package, and download the required packages.

VERSION = '1.0'
setup(name='PyPackage',
      version=VERSION,
      requires=['numarray', 'zlib (>=1.1.4)'],
      obsoletes=['OldPackage']
      download_url=('http://www.example.com/pypackage/dist/pkg-%s.tar.gz'
                    % VERSION),
     )

Another new enhancement to the Python package index at https://pypi.org is storing source and binary archives for a package. The new upload Distutils command will upload a package to the repository.

Before a package can be uploaded, you must be able to build a distribution using the sdist Distutils command. Once that works, you can run python setup.py upload to add your package to the PyPI archive. Optionally you can GPG-sign the package by supplying the --sign and --identity options.

Package uploading was implemented by Martin von Löwis and Richard Jones.

Voir aussi

PEP 314 [https://www.python.org/dev/peps/pep-0314] - Metadata for Python Software Packages v1.1

PEP proposed and written by A.M. Kuchling, Richard Jones, and Fred Drake; implemented by Richard Jones and Fred Drake.

PEP 328: Absolute and Relative Imports

The simpler part of PEP 328 was implemented in Python 2.4: parentheses could now be used to enclose the names imported from a module using the from ... import ... statement, making it easier to import many different names.

The more complicated part has been implemented in Python 2.5: importing a module can be specified to use absolute or package-relative imports. The plan is to move toward making absolute imports the default in future versions of Python.

Let’s say you have a package directory like this:

pkg/
pkg/__init__.py
pkg/main.py
pkg/string.py

This defines a package named pkg containing the pkg.main and pkg.string submodules.

Consider the code in the main.py module. What happens if it executes the statement import string? In Python 2.4 and earlier, it will first look in the package’s directory to perform a relative import, finds pkg/string.py, imports the contents of that file as the pkg.string module, and that module is bound to the name string in the pkg.main module’s namespace.

That’s fine if pkg.string was what you wanted. But what if you wanted Python’s standard string module? There’s no clean way to ignore pkg.string and look for the standard module; generally you had to look at the contents of sys.modules, which is slightly unclean. Holger Krekel’s py.std package provides a tidier way to perform imports from the standard library, import py; py.std.string.join(), but that package isn’t available on all Python installations.

Reading code which relies on relative imports is also less clear, because a reader may be confused about which module, string or pkg.string, is intended to be used. Python users soon learned not to duplicate the names of standard library modules in the names of their packages” submodules, but you can’t protect against having your submodule’s name being used for a new module added in a future version of Python.

In Python 2.5, you can switch import’s behaviour to absolute imports using a from __future__ import absolute_import directive. This absolute-import behaviour will become the default in a future version (probably Python 2.7). Once absolute imports are the default, import string will always find the standard library’s version. It’s suggested that users should begin using absolute imports as much as possible, so it’s preferable to begin writing from pkg import string in your code.

Relative imports are still possible by adding a leading period to the module name when using the from ... import form:

# Import names from pkg.string
from .string import name1, name2
# Import pkg.string
from . import string

This imports the string module relative to the current package, so in pkg.main this will import name1 and name2 from pkg.string. Additional leading periods perform the relative import starting from the parent of the current package. For example, code in the A.B.C module can do:

from . import D                 # Imports A.B.D
from .. import E                # Imports A.E
from ..F import G               # Imports A.F.G

Leading periods cannot be used with the import modname form of the import statement, only the from ... import form.

Voir aussi

PEP 328 [https://www.python.org/dev/peps/pep-0328] - Imports: Multi-Line and Absolute/Relative

PEP écrite par Aahz; implémentée par Thomas Wouters.

https://pylib.readthedocs.org/

The py library by Holger Krekel, which contains the py.std package.

PEP 338: Executing Modules as Scripts

The -m switch added in Python 2.4 to execute a module as a script gained a few more abilities. Instead of being implemented in C code inside the Python interpreter, the switch now uses an implementation in a new module, runpy.

The runpy module implements a more sophisticated import mechanism so that it’s now possible to run modules in a package such as pychecker.checker. The module also supports alternative import mechanisms such as the zipimport module. This means you can add a .zip archive’s path to sys.path and then use the -m switch to execute code from the archive.

Voir aussi

PEP 338 [https://www.python.org/dev/peps/pep-0338] - Executing modules as scripts

PEP written and implemented by Nick Coghlan.

PEP 341: Unified try/except/finally

Until Python 2.5, the try statement came in two flavours. You could use a finally block to ensure that code is always executed, or one or more except blocks to catch specific exceptions. You couldn’t combine both except blocks and a finally block, because generating the right bytecode for the combined version was complicated and it wasn’t clear what the semantics of the combined statement should be.

Guido van Rossum spent some time working with Java, which does support the equivalent of combining except blocks and a finally block, and this clarified what the statement should mean. In Python 2.5, you can now write:

try:
    block-1 ...
except Exception1:
    handler-1 ...
except Exception2:
    handler-2 ...
else:
    else-block
finally:
    final-block

The code in block-1 is executed. If the code raises an exception, the various except blocks are tested: if the exception is of class Exception1, handler-1 is executed; otherwise if it’s of class Exception2, handler-2 is executed, and so forth. If no exception is raised, the else-block is executed.

No matter what happened previously, the final-block is executed once the code block is complete and any raised exceptions handled. Even if there’s an error in an exception handler or the else-block and a new exception is raised, the code in the final-block is still run.

Voir aussi

PEP 341 [https://www.python.org/dev/peps/pep-0341] - Unifying try-except and try-finally

PEP written by Georg Brandl; implementation by Thomas Lee.

PEP 342: New Generator Features

Python 2.5 adds a simple way to pass values into a generator. As introduced in Python 2.3, generators only produce output; once a generator’s code was invoked to create an iterator, there was no way to pass any new information into the function when its execution is resumed. Sometimes the ability to pass in some information would be useful. Hackish solutions to this include making the generator’s code look at a global variable and then changing the global variable’s value, or passing in some mutable object that callers then modify.

To refresh your memory of basic generators, here’s a simple example:

def counter (maximum):
    i = 0
    while i < maximum:
        yield i
        i += 1

When you call counter(10), the result is an iterator that returns the values from 0 up to 9. On encountering the yield statement, the iterator returns the provided value and suspends the function’s execution, preserving the local variables. Execution resumes on the following call to the iterator’s next() method, picking up after the yield statement.

In Python 2.3, yield was a statement; it didn’t return any value. In 2.5, yield is now an expression, returning a value that can be assigned to a variable or otherwise operated on:

val = (yield i)

I recommend that you always put parentheses around a yield expression when you’re doing something with the returned value, as in the above example. The parentheses aren’t always necessary, but it’s easier to always add them instead of having to remember when they’re needed.

(PEP 342 [https://www.python.org/dev/peps/pep-0342] explains the exact rules, which are that a yield-expression must always be parenthesized except when it occurs at the top-level expression on the right-hand side of an assignment. This means you can write val = yield i but have to use parentheses when there’s an operation, as in val = (yield i) + 12.)

Values are sent into a generator by calling its send(value) method. The generator’s code is then resumed and the yield expression returns the specified value. If the regular next() method is called, the yield returns None.

Here’s the previous example, modified to allow changing the value of the internal counter.

def counter (maximum):
    i = 0
    while i < maximum:
        val = (yield i)
        # If value provided, change counter
        if val is not None:
            i = val
        else:
            i += 1

And here’s an example of changing the counter:

>>> it = counter(10)
>>> print it.next()
0
>>> print it.next()
1
>>> print it.send(8)
8
>>> print it.next()
9
>>> print it.next()
Traceback (most recent call last):
  File "t.py", line 15, in ?
    print it.next()
StopIteration

yield will usually return None, so you should always check for this case. Don’t just use its value in expressions unless you’re sure that the send() method will be the only method used to resume your generator function.

In addition to send(), there are two other new methods on generators:

throw(type, value=None, traceback=None) is used to raise an exception inside the generator; the exception is raised by the yield expression where the generator’s execution is paused.

close() raises a new GeneratorExit exception inside the generator to terminate the iteration. On receiving this exception, the generator’s code must either raise GeneratorExit or StopIteration. Catching the GeneratorExit exception and returning a value is illegal and will trigger a RuntimeError; if the function raises some other exception, that exception is propagated to the caller. close() will also be called by Python’s garbage collector when the generator is garbage-collected.

If you need to run cleanup code when a GeneratorExit occurs, I suggest using a try: ... finally: suite instead of catching GeneratorExit.

Ces changements cumulés transforment les générateurs de producteurs unidirectionnels d’information vers un statut hybride à la fois producteur et consommateur.

Generators also become coroutines, a more generalized form of subroutines. Subroutines are entered at one point and exited at another point (the top of the function, and a return statement), but coroutines can be entered, exited, and resumed at many different points (the yield statements). We’ll have to figure out patterns for using coroutines effectively in Python.

The addition of the close() method has one side effect that isn’t obvious. close() is called when a generator is garbage-collected, so this means the generator’s code gets one last chance to run before the generator is destroyed. This last chance means that try...finally statements in generators can now be guaranteed to work; the finally clause will now always get a chance to run. The syntactic restriction that you couldn’t mix yield statements with a try...finally suite has therefore been removed. This seems like a minor bit of language trivia, but using generators and try...finally is actually necessary in order to implement the with statement described by PEP 343. I’ll look at this new statement in the following section.

Another even more esoteric effect of this change: previously, the gi_frame attribute of a generator was always a frame object. It’s now possible for gi_frame to be None once the generator has been exhausted.

Voir aussi

PEP 342 [https://www.python.org/dev/peps/pep-0342] – Coroutines via des générateurs améliorés

PEP written by Guido van Rossum and Phillip J. Eby; implemented by Phillip J. Eby. Includes examples of some fancier uses of generators as coroutines.

Earlier versions of these features were proposed in PEP 288 [https://www.python.org/dev/peps/pep-0288] by Raymond Hettinger and PEP 325 [https://www.python.org/dev/peps/pep-0325] by Samuele Pedroni.

https://en.wikipedia.org/wiki/Coroutine

L’article de Wikipédia sur les coroutines.

http://www.sidhe.org/~dan/blog/archives/000178.html

An explanation of coroutines from a Perl point of view, written by Dan Sugalski.

PEP 343: The “with” statement

The “with” statement clarifies code that previously would use try...finally blocks to ensure that clean-up code is executed. In this section, I’ll discuss the statement as it will commonly be used. In the next section, I’ll examine the implementation details and show how to write objects for use with this statement.

The “with” statement is a new control-flow structure whose basic structure is:

with expression [as variable]:
    with-block

The expression is evaluated, and it should result in an object that supports the context management protocol (that is, has __enter__() and __exit__() methods.

The object’s __enter__() is called before with-block is executed and therefore can run set-up code. It also may return a value that is bound to the name variable, if given. (Note carefully that variable is not assigned the result of expression.)

After execution of the with-block is finished, the object’s __exit__() method is called, even if the block raised an exception, and can therefore run clean-up code.

To enable the statement in Python 2.5, you need to add the following directive to your module:

from __future__ import with_statement

The statement will always be enabled in Python 2.6.

Some standard Python objects now support the context management protocol and can be used with the “with” statement. File objects are one example:

with open('/etc/passwd', 'r') as f:
    for line in f:
        print line
        ... more processing code ...

After this statement has executed, the file object in f will have been automatically closed, even if the for loop raised an exception part-way through the block.

Note

In this case, f is the same object created by open(), because file.__enter__() returns self.

The threading module’s locks and condition variables also support the “with” statement:

lock = threading.Lock()
with lock:
    # Critical section of code
    ...

The lock is acquired before the block is executed and always released once the block is complete.

The new localcontext() function in the decimal module makes it easy to save and restore the current decimal context, which encapsulates the desired precision and rounding characteristics for computations:

from decimal import Decimal, Context, localcontext

# Displays with default precision of 28 digits
v = Decimal('578')
print v.sqrt()

with localcontext(Context(prec=16)):
    # All code in this block uses a precision of 16 digits.
    # The original context is restored on exiting the block.
    print v.sqrt()

Écrire des gestionnaires de contexte

Under the hood, the “with” statement is fairly complicated. Most people will only use “with” in company with existing objects and don’t need to know these details, so you can skip the rest of this section if you like. Authors of new objects will need to understand the details of the underlying implementation and should keep reading.

A high-level explanation of the context management protocol is:

The expression is evaluated and should result in an object called a « context manager ». The context manager must have __enter__() and __exit__() methods.

The context manager’s __enter__() method is called. The value returned is assigned to VAR. If no 'as VAR' clause is present, the value is simply discarded.

Le code dans BLOCK est exécuté.

If BLOCK raises an exception, the __exit__(type, value, traceback) is called with the exception details, the same values returned by sys.exc_info(). The method’s return value controls whether the exception is re-raised: any false value re-raises the exception, and True will result in suppressing it. You’ll only rarely want to suppress the exception, because if you do the author of the code containing the “with” statement will never realize anything went wrong.

If BLOCK didn’t raise an exception, the __exit__() method is still called, but type, value, and traceback are all None.

Let’s think through an example. I won’t present detailed code but will only sketch the methods necessary for a database that supports transactions.

(For people unfamiliar with database terminology: a set of changes to the database are grouped into a transaction. Transactions can be either committed, meaning that all the changes are written into the database, or rolled back, meaning that the changes are all discarded and the database is unchanged. See any database textbook for more information.)

Let’s assume there’s an object representing a database connection. Our goal will be to let the user write code like this:

db_connection = DatabaseConnection()
with db_connection as cursor:
    cursor.execute('insert into ...')
    cursor.execute('delete from ...')
    # ... more operations ...

The transaction should be committed if the code in the block runs flawlessly or rolled back if there’s an exception. Here’s the basic interface for DatabaseConnection that I’ll assume:

class DatabaseConnection:
    # Database interface
    def cursor (self):
        "Returns a cursor object and starts a new transaction"
    def commit (self):
        "Commits current transaction"
    def rollback (self):
        "Rolls back current transaction"

The __enter__() method is pretty easy, having only to start a new transaction. For this application the resulting cursor object would be a useful result, so the method will return it. The user can then add as cursor to their “with” statement to bind the cursor to a variable name.

class DatabaseConnection:
    ...
    def __enter__ (self):
        # Code to start a new transaction
        cursor = self.cursor()
        return cursor

The __exit__() method is the most complicated because it’s where most of the work has to be done. The method has to check if an exception occurred. If there was no exception, the transaction is committed. The transaction is rolled back if there was an exception.

In the code below, execution will just fall off the end of the function, returning the default value of None. None is false, so the exception will be re-raised automatically. If you wished, you could be more explicit and add a return statement at the marked location.

class DatabaseConnection:
    ...
    def __exit__ (self, type, value, tb):
        if tb is None:
            # No exception, so commit
            self.commit()
        else:
            # Exception occurred, so rollback.
            self.rollback()
            # return False

Le module contextlib

The new contextlib module provides some functions and a decorator that are useful for writing objects for use with the “with” statement.

The decorator is called contextmanager(), and lets you write a single generator function instead of defining a new class. The generator should yield exactly one value. The code up to the yield will be executed as the __enter__() method, and the value yielded will be the method’s return value that will get bound to the variable in the “with” statement’s as clause, if any. The code after the yield will be executed in the __exit__() method. Any exception raised in the block will be raised by the yield statement.

Our database example from the previous section could be written using this decorator as:

from contextlib import contextmanager

@contextmanager
def db_transaction (connection):
    cursor = connection.cursor()
    try:
        yield cursor
    except:
        connection.rollback()
        raise
    else:
        connection.commit()

db = DatabaseConnection()
with db_transaction(db) as cursor:
    ...

The contextlib module also has a nested(mgr1, mgr2, ...) function that combines a number of context managers so you don’t need to write nested “with” statements. In this example, the single “with” statement both starts a database transaction and acquires a thread lock:

lock = threading.Lock()
with nested (db_transaction(db), lock) as (cursor, locked):
    ...

Finally, the closing(object) function returns object so that it can be bound to a variable, and calls object.close at the end of the block.

import urllib, sys
from contextlib import closing

with closing(urllib.urlopen('http://www.yahoo.com')) as f:
    for line in f:
        sys.stdout.write(line)

Voir aussi

PEP 343 [https://www.python.org/dev/peps/pep-0343] - The « with » statement

PEP written by Guido van Rossum and Nick Coghlan; implemented by Mike Bland, Guido van Rossum, and Neal Norwitz. The PEP shows the code generated for a “with” statement, which can be helpful in learning how the statement works.

The documentation for the contextlib module.

PEP 352: Exceptions as New-Style Classes

Exception classes can now be new-style classes, not just classic classes, and the built-in Exception class and all the standard built-in exceptions (NameError, ValueError, etc.) are now new-style classes.

The inheritance hierarchy for exceptions has been rearranged a bit. In 2.5, the inheritance relationships are:

BaseException       # New in Python 2.5
|- KeyboardInterrupt
|- SystemExit
|- Exception
   |- (all other current built-in exceptions)

This rearrangement was done because people often want to catch all exceptions that indicate program errors. KeyboardInterrupt and SystemExit aren’t errors, though, and usually represent an explicit action such as the user hitting Control-C or code calling sys.exit(). A bare except: will catch all exceptions, so you commonly need to list KeyboardInterrupt and SystemExit in order to re-raise them. The usual pattern is:

try:
    ...
except (KeyboardInterrupt, SystemExit):
    raise
except:
    # Log error...
    # Continue running program...

In Python 2.5, you can now write except Exception to achieve the same result, catching all the exceptions that usually indicate errors but leaving KeyboardInterrupt and SystemExit alone. As in previous versions, a bare except: still catches all exceptions.

The goal for Python 3.0 is to require any class raised as an exception to derive from BaseException or some descendant of BaseException, and future releases in the Python 2.x series may begin to enforce this constraint. Therefore, I suggest you begin making all your exception classes derive from Exception now. It’s been suggested that the bare except: form should be removed in Python 3.0, but Guido van Rossum hasn’t decided whether to do this or not.

Raising of strings as exceptions, as in the statement raise "Error occurred", is deprecated in Python 2.5 and will trigger a warning. The aim is to be able to remove the string-exception feature in a few releases.

Voir aussi

PEP 352 [https://www.python.org/dev/peps/pep-0352] - Required Superclass for Exceptions

PEP written by Brett Cannon and Guido van Rossum; implemented by Brett Cannon.

PEP 353: Using ssize_t as the index type

A wide-ranging change to Python’s C API, using a new Py_ssize_t type definition instead of int, will permit the interpreter to handle more data on 64-bit platforms. This change doesn’t affect Python’s capacity on 32-bit platforms.

Various pieces of the Python interpreter used C’s int type to store sizes or counts; for example, the number of items in a list or tuple were stored in an int. The C compilers for most 64-bit platforms still define int as a 32-bit type, so that meant that lists could only hold up to 2**31 - 1 = 2147483647 items. (There are actually a few different programming models that 64-bit C compilers can use – see http://www.unix.org/version2/whatsnew/lp64_wp.html for a discussion – but the most commonly available model leaves int as 32 bits.)

A limit of 2147483647 items doesn’t really matter on a 32-bit platform because you’ll run out of memory before hitting the length limit. Each list item requires space for a pointer, which is 4 bytes, plus space for a PyObject representing the item. 2147483647*4 is already more bytes than a 32-bit address space can contain.

It’s possible to address that much memory on a 64-bit platform, however. The pointers for a list that size would only require 16 GiB of space, so it’s not unreasonable that Python programmers might construct lists that large. Therefore, the Python interpreter had to be changed to use some type other than int, and this will be a 64-bit type on 64-bit platforms. The change will cause incompatibilities on 64-bit machines, so it was deemed worth making the transition now, while the number of 64-bit users is still relatively small. (In 5 or 10 years, we may all be on 64-bit machines, and the transition would be more painful then.)

This change most strongly affects authors of C extension modules. Python strings and container types such as lists and tuples now use Py_ssize_t to store their size. Functions such as PyList_Size() now return Py_ssize_t. Code in extension modules may therefore need to have some variables changed to Py_ssize_t.

The PyArg_ParseTuple() and Py_BuildValue() functions have a new conversion code, n, for Py_ssize_t. PyArg_ParseTuple()”s s# and t# still output int by default, but you can define the macro PY_SSIZE_T_CLEAN before including Python.h to make them return Py_ssize_t.

PEP 353 [https://www.python.org/dev/peps/pep-0353] has a section on conversion guidelines that extension authors should read to learn about supporting 64-bit platforms.

Voir aussi

PEP 353 [https://www.python.org/dev/peps/pep-0353] - Using ssize_t as the index type

PEP written and implemented by Martin von Löwis.

PEP 357: The “__index__” method

The NumPy developers had a problem that could only be solved by adding a new special method, __index__(). When using slice notation, as in [start:stop:step], the values of the start, stop, and step indexes must all be either integers or long integers. NumPy defines a variety of specialized integer types corresponding to unsigned and signed integers of 8, 16, 32, and 64 bits, but there was no way to signal that these types could be used as slice indexes.

Slicing can’t just use the existing __int__() method because that method is also used to implement coercion to integers. If slicing used __int__(), floating-point numbers would also become legal slice indexes and that’s clearly an undesirable behaviour.

Instead, a new special method called __index__() was added. It takes no arguments and returns an integer giving the slice index to use. For example:

class C:
    def __index__ (self):
        return self.value

The return value must be either a Python integer or long integer. The interpreter will check that the type returned is correct, and raises a TypeError if this requirement isn’t met.

A corresponding nb_index slot was added to the C-level PyNumberMethods structure to let C extensions implement this protocol. PyNumber_Index(obj) can be used in extension code to call the __index__() function and retrieve its result.

Voir aussi

PEP 357 [https://www.python.org/dev/peps/pep-0357] - Allowing Any Object to be Used for Slicing

PEP written and implemented by Travis Oliphant.

Other Language Changes

Here are all of the changes that Python 2.5 makes to the core Python language.

The dict type has a new hook for letting subclasses provide a default value when a key isn’t contained in the dictionary. When a key isn’t found, the dictionary’s __missing__(key) method will be called. This hook is used to implement the new defaultdict class in the collections module. The following example defines a dictionary that returns zero for any missing key:

class zerodict (dict):
    def __missing__ (self, key):
        return 0

d = zerodict({1:1, 2:2})
print d[1], d[2]   # Prints 1, 2
print d[3], d[4]   # Prints 0, 0

Both 8-bit and Unicode strings have new partition(sep) and rpartition(sep) methods that simplify a common use case.

The find(S) method is often used to get an index which is then used to slice the string and obtain the pieces that are before and after the separator. partition(sep) condenses this pattern into a single method call that returns a 3-tuple containing the substring before the separator, the separator itself, and the substring after the separator. If the separator isn’t found, the first element of the tuple is the entire string and the other two elements are empty. rpartition(sep) also returns a 3-tuple but starts searching from the end of the string; the r stands for “reverse”.

Quelques exemples :

>>> ('http://www.python.org').partition('://')
('http', '://', 'www.python.org')
>>> ('file:/usr/share/doc/index.html').partition('://')
('file:/usr/share/doc/index.html', '', '')
>>> (u'Subject: a quick question').partition(':')
(u'Subject', u':', u' a quick question')
>>> 'www.python.org'.rpartition('.')
('www.python', '.', 'org')
>>> 'www.python.org'.rpartition(':')
('', '', 'www.python.org')

(Implemented by Fredrik Lundh following a suggestion by Raymond Hettinger.)

The startswith() and endswith() methods of string types now accept tuples of strings to check for.

def is_image_file (filename):
    return filename.endswith(('.gif', '.jpg', '.tiff'))

(Implemented by Georg Brandl following a suggestion by Tom Lynn.)

The min() and max() built-in functions gained a key keyword parameter analogous to the key argument for sort(). This parameter supplies a function that takes a single argument and is called for every value in the list; min()/max() will return the element with the smallest/largest return value from this function. For example, to find the longest string in a list, you can do:

L = ['medium', 'longest', 'short']
# Prints 'longest'
print max(L, key=len)
# Prints 'short', because lexicographically 'short' has the largest value
print max(L)

(Contributed by Steven Bethard and Raymond Hettinger.)

Two new built-in functions, any() and all(), evaluate whether an iterator contains any true or false values. any() returns True if any value returned by the iterator is true; otherwise it will return False. all() returns True only if all of the values returned by the iterator evaluate as true. (Suggested by Guido van Rossum, and implemented by Raymond Hettinger.)

The result of a class’s __hash__() method can now be either a long integer or a regular integer. If a long integer is returned, the hash of that value is taken. In earlier versions the hash value was required to be a regular integer, but in 2.5 the id() built-in was changed to always return non-negative numbers, and users often seem to use id(self) in __hash__() methods (though this is discouraged).

ASCII is now the default encoding for modules. It’s now a syntax error if a module contains string literals with 8-bit characters but doesn’t have an encoding declaration. In Python 2.4 this triggered a warning, not a syntax error. See PEP 263 [https://www.python.org/dev/peps/pep-0263] for how to declare a module’s encoding; for example, you might add a line like this near the top of the source file:

# -*- coding: latin1 -*-

A new warning, UnicodeWarning, is triggered when you attempt to compare a Unicode string and an 8-bit string that can’t be converted to Unicode using the default ASCII encoding. The result of the comparison is false:

>>> chr(128) == unichr(128)   # Can't convert chr(128) to Unicode
__main__:1: UnicodeWarning: Unicode equal comparison failed
  to convert both arguments to Unicode - interpreting them
  as being unequal
False
>>> chr(127) == unichr(127)   # chr(127) can be converted
True

Previously this would raise a UnicodeDecodeError exception, but in 2.5 this could result in puzzling problems when accessing a dictionary. If you looked up unichr(128) and chr(128) was being used as a key, you’d get a UnicodeDecodeError exception. Other changes in 2.5 resulted in this exception being raised instead of suppressed by the code in dictobject.c that implements dictionaries.

Raising an exception for such a comparison is strictly correct, but the change might have broken code, so instead UnicodeWarning was introduced.

(Implemented by Marc-André Lemburg.)

One error that Python programmers sometimes make is forgetting to include an __init__.py module in a package directory. Debugging this mistake can be confusing, and usually requires running Python with the -v switch to log all the paths searched. In Python 2.5, a new ImportWarning warning is triggered when an import would have picked up a directory as a package but no __init__.py was found. This warning is silently ignored by default; provide the -Wd option when running the Python executable to display the warning message. (Implemented by Thomas Wouters.)

The list of base classes in a class definition can now be empty. As an example, this is now legal:

class C():
    pass

(Implemented by Brett Cannon.)

Changements de l’interpréteur interactif

In the interactive interpreter, quit and exit have long been strings so that new users get a somewhat helpful message when they try to quit:

>>> quit
'Use Ctrl-D (i.e. EOF) to exit.'

In Python 2.5, quit and exit are now objects that still produce string representations of themselves, but are also callable. Newbies who try quit() or exit() will now exit the interpreter as they expect. (Implemented by Georg Brandl.)

The Python executable now accepts the standard long options --help and --version; on Windows, it also accepts the /? option for displaying a help message. (Implemented by Georg Brandl.)

Optimizations

Several of the optimizations were developed at the NeedForSpeed sprint, an event held in Reykjavik, Iceland, from May 21–28 2006. The sprint focused on speed enhancements to the CPython implementation and was funded by EWT LLC with local support from CCP Games. Those optimizations added at this sprint are specially marked in the following list.

When they were introduced in Python 2.4, the built-in set and frozenset types were built on top of Python’s dictionary type. In 2.5 the internal data structure has been customized for implementing sets, and as a result sets will use a third less memory and are somewhat faster. (Implemented by Raymond Hettinger.)

The speed of some Unicode operations, such as finding substrings, string splitting, and character map encoding and decoding, has been improved. (Substring search and splitting improvements were added by Fredrik Lundh and Andrew Dalke at the NeedForSpeed sprint. Character maps were improved by Walter Dörwald and Martin von Löwis.)

The long(str, base) function is now faster on long digit strings because fewer intermediate results are calculated. The peak is for strings of around 800–1000 digits where the function is 6 times faster. (Contributed by Alan McIntyre and committed at the NeedForSpeed sprint.)

It’s now illegal to mix iterating over a file with for line in file and calling the file object’s read()/readline()/readlines() methods. Iteration uses an internal buffer and the read*() methods don’t use that buffer. Instead they would return the data following the buffer, causing the data to appear out of order. Mixing iteration and these methods will now trigger a ValueError from the read*() method. (Implemented by Thomas Wouters.)

The struct module now compiles structure format strings into an internal representation and caches this representation, yielding a 20% speedup. (Contributed by Bob Ippolito at the NeedForSpeed sprint.)

The re module got a 1 or 2% speedup by switching to Python’s allocator functions instead of the system’s malloc() and free(). (Contributed by Jack Diederich at the NeedForSpeed sprint.)

The code generator’s peephole optimizer now performs simple constant folding in expressions. If you write something like a = 2+3, the code generator will do the arithmetic and produce code corresponding to a = 5. (Proposed and implemented by Raymond Hettinger.)

Function calls are now faster because code objects now keep the most recently finished frame (a « zombie frame ») in an internal field of the code object, reusing it the next time the code object is invoked. (Original patch by Michael Hudson, modified by Armin Rigo and Richard Jones; committed at the NeedForSpeed sprint.) Frame objects are also slightly smaller, which may improve cache locality and reduce memory usage a bit. (Contributed by Neal Norwitz.)

Python’s built-in exceptions are now new-style classes, a change that speeds up instantiation considerably. Exception handling in Python 2.5 is therefore about 30% faster than in 2.4. (Contributed by Richard Jones, Georg Brandl and Sean Reifschneider at the NeedForSpeed sprint.)

Importing now caches the paths tried, recording whether they exist or not so that the interpreter makes fewer open() and stat() calls on startup. (Contributed by Martin von Löwis and Georg Brandl.)

Modules ajoutés, modifiés, et supprimés

The standard library received many enhancements and bug fixes in Python 2.5. Here’s a partial list of the most notable changes, sorted alphabetically by module name. Consult the Misc/NEWS file in the source tree for a more complete list of changes, or look through the SVN logs for all the details.

The audioop module now supports the a-LAW encoding, and the code for u-LAW encoding has been improved. (Contributed by Lars Immisch.)

The codecs module gained support for incremental codecs. The codec.lookup() function now returns a CodecInfo instance instead of a tuple. CodecInfo instances behave like a 4-tuple to preserve backward compatibility but also have the attributes encode, decode, incrementalencoder, incrementaldecoder, streamwriter, and streamreader. Incremental codecs can receive input and produce output in multiple chunks; the output is the same as if the entire input was fed to the non-incremental codec. See the codecs module documentation for details. (Designed and implemented by Walter Dörwald.)

The collections module gained a new type, defaultdict, that subclasses the standard dict type. The new type mostly behaves like a dictionary but constructs a default value when a key isn’t present, automatically adding it to the dictionary for the requested key value.

The first argument to defaultdict’s constructor is a factory function that gets called whenever a key is requested but not found. This factory function receives no arguments, so you can use built-in type constructors such as list() or int(). For example, you can make an index of words based on their initial letter like this:

words = """Nel mezzo del cammin di nostra vita
mi ritrovai per una selva oscura
che la diritta via era smarrita""".lower().split()

index = defaultdict(list)

for w in words:
    init_letter = w[0]
    index[init_letter].append(w)

Printing index results in the following output:

defaultdict(<type 'list'>, {'c': ['cammin', 'che'], 'e': ['era'],
        'd': ['del', 'di', 'diritta'], 'm': ['mezzo', 'mi'],
        'l': ['la'], 'o': ['oscura'], 'n': ['nel', 'nostra'],
        'p': ['per'], 's': ['selva', 'smarrita'],
        'r': ['ritrovai'], 'u': ['una'], 'v': ['vita', 'via']}

(Contribution par Guido van Rossum.)

The deque double-ended queue type supplied by the collections module now has a remove(value) method that removes the first occurrence of value in the queue, raising ValueError if the value isn’t found. (Contributed by Raymond Hettinger.)

New module: The contextlib module contains helper functions for use with the new “with” statement. See section Le module contextlib for more about this module.

New module: The cProfile module is a C implementation of the existing profile module that has much lower overhead. The module’s interface is the same as profile: you run cProfile.run('main()') to profile a function, can save profile data to a file, etc. It’s not yet known if the Hotshot profiler, which is also written in C but doesn’t match the profile module’s interface, will continue to be maintained in future versions of Python. (Contributed by Armin Rigo.)

Also, the pstats module for analyzing the data measured by the profiler now supports directing the output to any file object by supplying a stream argument to the Stats constructor. (Contributed by Skip Montanaro.)

The csv module, which parses files in comma-separated value format, received several enhancements and a number of bugfixes. You can now set the maximum size in bytes of a field by calling the csv.field_size_limit(new_limit) function; omitting the new_limit argument will return the currently-set limit. The reader class now has a line_num attribute that counts the number of physical lines read from the source; records can span multiple physical lines, so line_num is not the same as the number of records read.

The CSV parser is now stricter about multi-line quoted fields. Previously, if a line ended within a quoted field without a terminating newline character, a newline would be inserted into the returned field. This behavior caused problems when reading files that contained carriage return characters within fields, so the code was changed to return the field without inserting newlines. As a consequence, if newlines embedded within fields are important, the input should be split into lines in a manner that preserves the newline characters.

(Contributed by Skip Montanaro and Andrew McNamara.)

The datetime class in the datetime module now has a strptime(string, format) method for parsing date strings, contributed by Josh Spoerri. It uses the same format characters as time.strptime() and time.strftime():

from datetime import datetime

ts = datetime.strptime('10:13:15 2006-03-07',
                       '%H:%M:%S %Y-%m-%d')

The SequenceMatcher.get_matching_blocks() method in the difflib module now guarantees to return a minimal list of blocks describing matching subsequences. Previously, the algorithm would occasionally break a block of matching elements into two list entries. (Enhancement by Tim Peters.)

The doctest module gained a SKIP option that keeps an example from being executed at all. This is intended for code snippets that are usage examples intended for the reader and aren’t actually test cases.

An encoding parameter was added to the testfile() function and the DocFileSuite class to specify the file’s encoding. This makes it easier to use non-ASCII characters in tests contained within a docstring. (Contributed by Bjorn Tillenius.)

The email package has been updated to version 4.0. (Contributed by Barry Warsaw.)

The fileinput module was made more flexible. Unicode filenames are now supported, and a mode parameter that defaults to "r" was added to the input() function to allow opening files in binary or universal newlines mode. Another new parameter, openhook, lets you use a function other than open() to open the input files. Once you’re iterating over the set of files, the FileInput object’s new fileno() returns the file descriptor for the currently opened file. (Contributed by Georg Brandl.)

In the gc module, the new get_count() function returns a 3-tuple containing the current collection counts for the three GC generations. This is accounting information for the garbage collector; when these counts reach a specified threshold, a garbage collection sweep will be made. The existing gc.collect() function now takes an optional generation argument of 0, 1, or 2 to specify which generation to collect. (Contributed by Barry Warsaw.)

The nsmallest() and nlargest() functions in the heapq module now support a key keyword parameter similar to the one provided by the min()/max() functions and the sort() methods. For example:

>>> import heapq
>>> L = ["short", 'medium', 'longest', 'longer still']
>>> heapq.nsmallest(2, L)  # Return two lowest elements, lexicographically
['longer still', 'longest']
>>> heapq.nsmallest(2, L, key=len)   # Return two shortest elements
['short', 'medium']

(Contributed by Raymond Hettinger.)

The itertools.islice() function now accepts None for the start and step arguments. This makes it more compatible with the attributes of slice objects, so that you can now write the following:

s = slice(5)     # Create slice object
itertools.islice(iterable, s.start, s.stop, s.step)

(Contributed by Raymond Hettinger.)

The format() function in the locale module has been modified and two new functions were added, format_string() and currency().

The format() function’s val parameter could previously be a string as long as no more than one %char specifier appeared; now the parameter must be exactly one %char specifier with no surrounding text. An optional monetary parameter was also added which, if True, will use the locale’s rules for formatting currency in placing a separator between groups of three digits.

To format strings with multiple %char specifiers, use the new format_string() function that works like format() but also supports mixing %char specifiers with arbitrary text.

A new currency() function was also added that formats a number according to the current locale’s settings.

(Contributed by Georg Brandl.)

The mailbox module underwent a massive rewrite to add the capability to modify mailboxes in addition to reading them. A new set of classes that include mbox, MH, and Maildir are used to read mailboxes, and have an add(message) method to add messages, remove(key) to remove messages, and lock()/unlock() to lock/unlock the mailbox. The following example converts a maildir-format mailbox into an mbox-format one:

import mailbox

# 'factory=None' uses email.Message.Message as the class representing
# individual messages.
src = mailbox.Maildir('maildir', factory=None)
dest = mailbox.mbox('/tmp/mbox')

for msg in src:
    dest.add(msg)

(Contributed by Gregory K. Johnson. Funding was provided by Google’s 2005 Summer of Code.)

New module: the msilib module allows creating Microsoft Installer .msi files and CAB files. Some support for reading the .msi database is also included. (Contributed by Martin von Löwis.)

The nis module now supports accessing domains other than the system default domain by supplying a domain argument to the nis.match() and nis.maps() functions. (Contributed by Ben Bell.)

The operator module’s itemgetter() and attrgetter() functions now support multiple fields. A call such as operator.attrgetter('a', 'b') will return a function that retrieves the a and b attributes. Combining this new feature with the sort() method’s key parameter lets you easily sort lists using multiple fields. (Contributed by Raymond Hettinger.)

The optparse module was updated to version 1.5.1 of the Optik library. The OptionParser class gained an epilog attribute, a string that will be printed after the help message, and a destroy() method to break reference cycles created by the object. (Contributed by Greg Ward.)

The os module underwent several changes. The stat_float_times variable now defaults to true, meaning that os.stat() will now return time values as floats. (This doesn’t necessarily mean that os.stat() will return times that are precise to fractions of a second; not all systems support such precision.)

Constants named os.SEEK_SET, os.SEEK_CUR, and os.SEEK_END have been added; these are the parameters to the os.lseek() function. Two new constants for locking are os.O_SHLOCK and os.O_EXLOCK.

Two new functions, wait3() and wait4(), were added. They’re similar the waitpid() function which waits for a child process to exit and returns a tuple of the process ID and its exit status, but wait3() and wait4() return additional information. wait3() doesn’t take a process ID as input, so it waits for any child process to exit and returns a 3-tuple of process-id, exit-status, resource-usage as returned from the resource.getrusage() function. wait4(pid) does take a process ID. (Contributed by Chad J. Schroeder.)

On FreeBSD, the os.stat() function now returns times with nanosecond resolution, and the returned object now has st_gen and st_birthtime. The st_flags attribute is also available, if the platform supports it. (Contributed by Antti Louko and Diego Pettenò.)

The Python debugger provided by the pdb module can now store lists of commands to execute when a breakpoint is reached and execution stops. Once breakpoint #1 has been created, enter commands 1 and enter a series of commands to be executed, finishing the list with end. The command list can include commands that resume execution, such as continue or next. (Contributed by Grégoire Dooms.)

The pickle and cPickle modules no longer accept a return value of None from the __reduce__() method; the method must return a tuple of arguments instead. The ability to return None was deprecated in Python 2.4, so this completes the removal of the feature.

The pkgutil module, containing various utility functions for finding packages, was enhanced to support PEP 302’s import hooks and now also works for packages stored in ZIP-format archives. (Contributed by Phillip J. Eby.)

The pybench benchmark suite by Marc-André Lemburg is now included in the Tools/pybench directory. The pybench suite is an improvement on the commonly used pystone.py program because pybench provides a more detailed measurement of the interpreter’s speed. It times particular operations such as function calls, tuple slicing, method lookups, and numeric operations, instead of performing many different operations and reducing the result to a single number as pystone.py does.

The pyexpat module now uses version 2.0 of the Expat parser. (Contributed by Trent Mick.)

The Queue class provided by the Queue module gained two new methods. join() blocks until all items in the queue have been retrieved and all processing work on the items have been completed. Worker threads call the other new method, task_done(), to signal that processing for an item has been completed. (Contributed by Raymond Hettinger.)

The old regex and regsub modules, which have been deprecated ever since Python 2.0, have finally been deleted. Other deleted modules: statcache, tzparse, whrandom.

Also deleted: the lib-old directory, which includes ancient modules such as dircmp and ni, was removed. lib-old wasn’t on the default sys.path, so unless your programs explicitly added the directory to sys.path, this removal shouldn’t affect your code.

The rlcompleter module is no longer dependent on importing the readline module and therefore now works on non-Unix platforms. (Patch from Robert Kiendl.)

The SimpleXMLRPCServer and DocXMLRPCServer classes now have a rpc_paths attribute that constrains XML-RPC operations to a limited set of URL paths; the default is to allow only '/' and '/RPC2'. Setting rpc_paths to None or an empty tuple disables this path checking.

The socket module now supports AF_NETLINK sockets on Linux, thanks to a patch from Philippe Biondi. Netlink sockets are a Linux-specific mechanism for communications between a user-space process and kernel code; an introductory article about them is at https://www.linuxjournal.com/article/7356. In Python code, netlink addresses are represented as a tuple of 2 integers, (pid, group_mask).

Two new methods on socket objects, recv_into(buffer) and recvfrom_into(buffer), store the received data in an object that supports the buffer protocol instead of returning the data as a string. This means you can put the data directly into an array or a memory-mapped file.

Socket objects also gained getfamily(), gettype(), and getproto() accessor methods to retrieve the family, type, and protocol values for the socket.

New module: the spwd module provides functions for accessing the shadow password database on systems that support shadow passwords.

The struct is now faster because it compiles format strings into Struct objects with pack() and unpack() methods. This is similar to how the re module lets you create compiled regular expression objects. You can still use the module-level pack() and unpack() functions; they’ll create Struct objects and cache them. Or you can use Struct instances directly:

s = struct.Struct('ih3s')

data = s.pack(1972, 187, 'abc')
year, number, name = s.unpack(data)

You can also pack and unpack data to and from buffer objects directly using the pack_into(buffer, offset, v1, v2, ...) and unpack_from(buffer, offset) methods. This lets you store data directly into an array or a memory-mapped file.

(Struct objects were implemented by Bob Ippolito at the NeedForSpeed sprint. Support for buffer objects was added by Martin Blais, also at the NeedForSpeed sprint.)

The Python developers switched from CVS to Subversion during the 2.5 development process. Information about the exact build version is available as the sys.subversion variable, a 3-tuple of (interpreter-name, branch-name, revision-range). For example, at the time of writing my copy of 2.5 was reporting ('CPython', 'trunk', '45313:45315').

This information is also available to C extensions via the Py_GetBuildInfo() function that returns a string of build information like this: "trunk:45355:45356M, Apr 13 2006, 07:42:19". (Contributed by Barry Warsaw.)

Another new function, sys._current_frames(), returns the current stack frames for all running threads as a dictionary mapping thread identifiers to the topmost stack frame currently active in that thread at the time the function is called. (Contributed by Tim Peters.)

The TarFile class in the tarfile module now has an extractall() method that extracts all members from the archive into the current working directory. It’s also possible to set a different directory as the extraction target, and to unpack only a subset of the archive’s members.

The compression used for a tarfile opened in stream mode can now be autodetected using the mode 'r|*'. (Contributed by Lars Gustäbel.)

The threading module now lets you set the stack size used when new threads are created. The stack_size([*size*]) function returns the currently configured stack size, and supplying the optional size parameter sets a new value. Not all platforms support changing the stack size, but Windows, POSIX threading, and OS/2 all do. (Contributed by Andrew MacIntyre.)

The unicodedata module has been updated to use version 4.1.0 of the Unicode character database. Version 3.2.0 is required by some specifications, so it’s still available as unicodedata.ucd_3_2_0.

New module: the uuid module generates universally unique identifiers (UUIDs) according to RFC 4122 [https://tools.ietf.org/html/rfc4122.html]. The RFC defines several different UUID versions that are generated from a starting string, from system properties, or purely randomly. This module contains a UUID class and functions named uuid1(), uuid3(), uuid4(), and uuid5() to generate different versions of UUID. (Version 2 UUIDs are not specified in RFC 4122 [https://tools.ietf.org/html/rfc4122.html] and are not supported by this module.)

>>> import uuid
>>> # make a UUID based on the host ID and current time
>>> uuid.uuid1()
UUID('a8098c1a-f86e-11da-bd1a-00112444be1e')

>>> # make a UUID using an MD5 hash of a namespace UUID and a name
>>> uuid.uuid3(uuid.NAMESPACE_DNS, 'python.org')
UUID('6fa459ea-ee8a-3ca4-894e-db77e160355e')

>>> # make a random UUID
>>> uuid.uuid4()
UUID('16fd2706-8baf-433b-82eb-8c7fada847da')

>>> # make a UUID using a SHA-1 hash of a namespace UUID and a name
>>> uuid.uuid5(uuid.NAMESPACE_DNS, 'python.org')
UUID('886313e1-3b8a-5372-9b90-0c9aee199e5d')

(Contributed by Ka-Ping Yee.)

The weakref module’s WeakKeyDictionary and WeakValueDictionary types gained new methods for iterating over the weak references contained in the dictionary. iterkeyrefs() and keyrefs() methods were added to WeakKeyDictionary, and itervaluerefs() and valuerefs() were added to WeakValueDictionary. (Contributed by Fred L. Drake, Jr.)

The webbrowser module received a number of enhancements. It’s now usable as a script with python -m webbrowser, taking a URL as the argument; there are a number of switches to control the behaviour (-n for a new browser window, -t for a new tab). New module-level functions, open_new() and open_new_tab(), were added to support this. The module’s open() function supports an additional feature, an autoraise parameter that signals whether to raise the open window when possible. A number of additional browsers were added to the supported list such as Firefox, Opera, Konqueror, and elinks. (Contributed by Oleg Broytmann and Georg Brandl.)

The xmlrpclib module now supports returning datetime objects for the XML-RPC date type. Supply use_datetime=True to the loads() function or the Unmarshaller class to enable this feature. (Contributed by Skip Montanaro.)

The zipfile module now supports the ZIP64 version of the format, meaning that a .zip archive can now be larger than 4 GiB and can contain individual files larger than 4 GiB. (Contributed by Ronald Oussoren.)

The zlib module’s Compress and Decompress objects now support a copy() method that makes a copy of the object’s internal state and returns a new Compress or Decompress object. (Contributed by Chris AtLee.)

The ctypes package

The ctypes package, written by Thomas Heller, has been added to the standard library. ctypes lets you call arbitrary functions in shared libraries or DLLs. Long-time users may remember the dl module, which provides functions for loading shared libraries and calling functions in them. The ctypes package is much fancier.

To load a shared library or DLL, you must create an instance of the CDLL class and provide the name or path of the shared library or DLL. Once that’s done, you can call arbitrary functions by accessing them as attributes of the CDLL object.

import ctypes

libc = ctypes.CDLL('libc.so.6')
result = libc.printf("Line of output\n")

Type constructors for the various C types are provided: c_int(), c_float(), c_double(), c_char_p() (equivalent to char *), and so forth. Unlike Python’s types, the C versions are all mutable; you can assign to their value attribute to change the wrapped value. Python integers and strings will be automatically converted to the corresponding C types, but for other types you must call the correct type constructor. (And I mean must; getting it wrong will often result in the interpreter crashing with a segmentation fault.)

You shouldn’t use c_char_p() with a Python string when the C function will be modifying the memory area, because Python strings are supposed to be immutable; breaking this rule will cause puzzling bugs. When you need a modifiable memory area, use create_string_buffer():

s = "this is a string"
buf = ctypes.create_string_buffer(s)
libc.strfry(buf)

C functions are assumed to return integers, but you can set the restype attribute of the function object to change this:

>>> libc.atof('2.71828')
-1783957616
>>> libc.atof.restype = ctypes.c_double
>>> libc.atof('2.71828')
2.71828

ctypes also provides a wrapper for Python’s C API as the ctypes.pythonapi object. This object does not release the global interpreter lock before calling a function, because the lock must be held when calling into the interpreter’s code. There’s a py_object() type constructor that will create a PyObject * pointer. A simple usage:

import ctypes

d = {}
ctypes.pythonapi.PyObject_SetItem(ctypes.py_object(d),
          ctypes.py_object("abc"),  ctypes.py_object(1))
# d is now {'abc', 1}.

Don’t forget to use py_object(); if it’s omitted you end up with a segmentation fault.

ctypes has been around for a while, but people still write and distribution hand-coded extension modules because you can’t rely on ctypes being present. Perhaps developers will begin to write Python wrappers atop a library accessed through ctypes instead of extension modules, now that ctypes is included with core Python.

Voir aussi

http://starship.python.net/crew/theller/ctypes/

The ctypes web page, with a tutorial, reference, and FAQ.

The documentation for the ctypes module.

The ElementTree package

A subset of Fredrik Lundh’s ElementTree library for processing XML has been added to the standard library as xml.etree. The available modules are ElementTree, ElementPath, and ElementInclude from ElementTree 1.2.6. The cElementTree accelerator module is also included.

The rest of this section will provide a brief overview of using ElementTree. Full documentation for ElementTree is available at http://effbot.org/zone/element-index.htm.

ElementTree represents an XML document as a tree of element nodes. The text content of the document is stored as the text and tail attributes of (This is one of the major differences between ElementTree and the Document Object Model; in the DOM there are many different types of node, including TextNode.)

The most commonly used parsing function is parse(), that takes either a string (assumed to contain a filename) or a file-like object and returns an ElementTree instance:

from xml.etree import ElementTree as ET

tree = ET.parse('ex-1.xml')

feed = urllib.urlopen(
          'http://planet.python.org/rss10.xml')
tree = ET.parse(feed)

Once you have an ElementTree instance, you can call its getroot() method to get the root Element node.

There’s also an XML() function that takes a string literal and returns an Element node (not an ElementTree). This function provides a tidy way to incorporate XML fragments, approaching the convenience of an XML literal:

svg = ET.XML("""<svg width="10px" version="1.0">
             </svg>""")
svg.set('height', '320px')
svg.append(elem1)

Each XML element supports some dictionary-like and some list-like access methods. Dictionary-like operations are used to access attribute values, and list-like operations are used to access child nodes.

Opération

Résultat

elem[n]

Returns n’th child element.

elem[m:n]

Returns list of m’th through n’th child elements.

len(elem)

Returns number of child elements.

list(elem)

Returns list of child elements.

elem.append(elem2)

Adds elem2 as a child.

elem.insert(index, elem2)

Inserts elem2 at the specified location.

del elem[n]

Deletes n’th child element.

elem.keys()

Returns list of attribute names.

elem.get(name)

Returns value of attribute name.

elem.set(name, value)

Sets new value for attribute name.

elem.attrib

Retrieves the dictionary containing attributes.

del elem.attrib[name]

Supprime l’attribut name.

Comments and processing instructions are also represented as Element nodes. To check if a node is a comment or processing instructions:

if elem.tag is ET.Comment:
    ...
elif elem.tag is ET.ProcessingInstruction:
    ...

To generate XML output, you should call the ElementTree.write() method. Like parse(), it can take either a string or a file-like object:

# Encoding is US-ASCII
tree.write('output.xml')

# Encoding is UTF-8
f = open('output.xml', 'w')
tree.write(f, encoding='utf-8')

(Caution: the default encoding used for output is ASCII. For general XML work, where an element’s name may contain arbitrary Unicode characters, ASCII isn’t a very useful encoding because it will raise an exception if an element’s name contains any characters with values greater than 127. Therefore, it’s best to specify a different encoding such as UTF-8 that can handle any Unicode character.)

This section is only a partial description of the ElementTree interfaces. Please read the package’s official documentation for more details.

Voir aussi

http://effbot.org/zone/element-index.htm

Official documentation for ElementTree.

The hashlib package

A new hashlib module, written by Gregory P. Smith, has been added to replace the md5 and sha modules. hashlib adds support for additional secure hashes (SHA-224, SHA-256, SHA-384, and SHA-512). When available, the module uses OpenSSL for fast platform optimized implementations of algorithms.

The old md5 and sha modules still exist as wrappers around hashlib to preserve backwards compatibility. The new module’s interface is very close to that of the old modules, but not identical. The most significant difference is that the constructor functions for creating new hashing objects are named differently.

# Old versions
h = md5.md5()
h = md5.new()

# New version
h = hashlib.md5()

# Old versions
h = sha.sha()
h = sha.new()

# New version
h = hashlib.sha1()

# Hash that weren't previously available
h = hashlib.sha224()
h = hashlib.sha256()
h = hashlib.sha384()
h = hashlib.sha512()

# Alternative form
h = hashlib.new('md5')          # Provide algorithm as a string

Once a hash object has been created, its methods are the same as before: update(string) hashes the specified string into the current digest state, digest() and hexdigest() return the digest value as a binary string or a string of hex digits, and copy() returns a new hashing object with the same digest state.

Voir aussi

The documentation for the hashlib module.

The sqlite3 package

The pysqlite module (http://www.pysqlite.org), a wrapper for the SQLite embedded database, has been added to the standard library under the package name sqlite3.

SQLite est une bibliothèque C qui fournit une base de données légère sur disque ne nécessitant pas de processus serveur et qui utilise une variante (non standard) du langage de requête SQL pour accéder aux données. Certaines applications peuvent utiliser SQLite pour le stockage de données internes. Il est également possible de créer une application prototype utilisant SQLite, puis de modifier le code pour utiliser une base de données plus robuste telle que PostgreSQL ou Oracle.

pysqlite was written by Gerhard Häring and provides a SQL interface compliant with the DB-API 2.0 specification described by PEP 249 [https://www.python.org/dev/peps/pep-0249].

If you’re compiling the Python source yourself, note that the source tree doesn’t include the SQLite code, only the wrapper module. You’ll need to have the SQLite libraries and headers installed before compiling Python, and the build process will compile the module when the necessary headers are available.

To use the module, you must first create a Connection object that represents the database. Here the data will be stored in the /tmp/example file:

conn = sqlite3.connect('/tmp/example')

Vous pouvez également fournir le nom spécial :memory: pour créer une base de données dans la mémoire vive.

Once you have a Connection, you can create a Cursor object and call its execute() method to perform SQL commands:

c = conn.cursor()

# Create table
c.execute('''create table stocks
(date text, trans text, symbol text,
 qty real, price real)''')

# Insert a row of data
c.execute("""insert into stocks
          values ('2006-01-05','BUY','RHAT',100,35.14)""")

Usually your SQL operations will need to use values from Python variables. You shouldn’t assemble your query using Python’s string operations because doing so is insecure; it makes your program vulnerable to an SQL injection attack.

Instead, use the DB-API’s parameter substitution. Put ? as a placeholder wherever you want to use a value, and then provide a tuple of values as the second argument to the cursor’s execute() method. (Other database modules may use a different placeholder, such as %s or :1.) For example:

# Never do this -- insecure!
symbol = 'IBM'
c.execute("... where symbol = '%s'" % symbol)

# Do this instead
t = (symbol,)
c.execute('select * from stocks where symbol=?', t)

# Larger example
for t in (('2006-03-28', 'BUY', 'IBM', 1000, 45.00),
          ('2006-04-05', 'BUY', 'MSOFT', 1000, 72.00),
          ('2006-04-06', 'SELL', 'IBM', 500, 53.00),
         ):
    c.execute('insert into stocks values (?,?,?,?,?)', t)

To retrieve data after executing a SELECT statement, you can either treat the cursor as an iterator, call the cursor’s fetchone() method to retrieve a single matching row, or call fetchall() to get a list of the matching rows.

Cet exemple utilise la forme itérateur :

>>> c = conn.cursor()
>>> c.execute('select * from stocks order by price')
>>> for row in c:
...    print row
...
(u'2006-01-05', u'BUY', u'RHAT', 100, 35.140000000000001)
(u'2006-03-28', u'BUY', u'IBM', 1000, 45.0)
(u'2006-04-06', u'SELL', u'IBM', 500, 53.0)
(u'2006-04-05', u'BUY', u'MSOFT', 1000, 72.0)
>>>

For more information about the SQL dialect supported by SQLite, see https://www.sqlite.org.

Voir aussi

http://www.pysqlite.org

The pysqlite web page.

https://www.sqlite.org

Dans la page Web de SQLite, la documentation décrit la syntaxe et les types de données disponibles qui sont pris en charge par cette variante SQL.

The documentation for the sqlite3 module.

PEP 249 [https://www.python.org/dev/peps/pep-0249] — Spécifications de l’API 2.0 pour la base de données

PEP écrite par Marc-André Lemburg.

The wsgiref package

The Web Server Gateway Interface (WSGI) v1.0 defines a standard interface between web servers and Python web applications and is described in PEP 333 [https://www.python.org/dev/peps/pep-0333]. The wsgiref package is a reference implementation of the WSGI specification.

The package includes a basic HTTP server that will run a WSGI application; this server is useful for debugging but isn’t intended for production use. Setting up a server takes only a few lines of code:

from wsgiref import simple_server

wsgi_app = ...

host = ''
port = 8000
httpd = simple_server.make_server(host, port, wsgi_app)
httpd.serve_forever()

Voir aussi

http://www.wsgi.org

A central web site for WSGI-related resources.

PEP 333 [https://www.python.org/dev/peps/pep-0333] - Python Web Server Gateway Interface v1.0

PEP written by Phillip J. Eby.

Build and C API Changes

Changes to Python’s build process and to the C API include:

The Python source tree was converted from CVS to Subversion, in a complex migration procedure that was supervised and flawlessly carried out by Martin von Löwis. The procedure was developed as PEP 347 [https://www.python.org/dev/peps/pep-0347].

Coverity, a company that markets a source code analysis tool called Prevent, provided the results of their examination of the Python source code. The analysis found about 60 bugs that were quickly fixed. Many of the bugs were refcounting problems, often occurring in error-handling code. See https://scan.coverity.com for the statistics.

The largest change to the C API came from PEP 353 [https://www.python.org/dev/peps/pep-0353], which modifies the interpreter to use a Py_ssize_t type definition instead of int. See the earlier section PEP 353: Using ssize_t as the index type for a discussion of this change.

The design of the bytecode compiler has changed a great deal, no longer generating bytecode by traversing the parse tree. Instead the parse tree is converted to an abstract syntax tree (or AST), and it is the abstract syntax tree that’s traversed to produce the bytecode.

It’s possible for Python code to obtain AST objects by using the compile() built-in and specifying _ast.PyCF_ONLY_AST as the value of the flags parameter:

from _ast import PyCF_ONLY_AST
ast = compile("""a=0
for i in range(10):
    a += i
""", "<string>", 'exec', PyCF_ONLY_AST)

assignment = ast.body[0]
for_loop = ast.body[1]

No official documentation has been written for the AST code yet, but PEP 339 [https://www.python.org/dev/peps/pep-0339] discusses the design. To start learning about the code, read the definition of the various AST nodes in Parser/Python.asdl. A Python script reads this file and generates a set of C structure definitions in Include/Python-ast.h. The PyParser_ASTFromString() and PyParser_ASTFromFile(), defined in Include/pythonrun.h, take Python source as input and return the root of an AST representing the contents. This AST can then be turned into a code object by PyAST_Compile(). For more information, read the source code, and then ask questions on python-dev.

The AST code was developed under Jeremy Hylton’s management, and implemented by (in alphabetical order) Brett Cannon, Nick Coghlan, Grant Edwards, John Ehresman, Kurt Kaiser, Neal Norwitz, Tim Peters, Armin Rigo, and Neil Schemenauer, plus the participants in a number of AST sprints at conferences such as PyCon.

Evan Jones’s patch to obmalloc, first described in a talk at PyCon DC 2005, was applied. Python 2.4 allocated small objects in 256K-sized arenas, but never freed arenas. With this patch, Python will free arenas when they’re empty. The net effect is that on some platforms, when you allocate many objects, Python’s memory usage may actually drop when you delete them and the memory may be returned to the operating system. (Implemented by Evan Jones, and reworked by Tim Peters.)

Note that this change means extension modules must be more careful when allocating memory. Python’s API has many different functions for allocating memory that are grouped into families. For example, PyMem_Malloc(), PyMem_Realloc(), and PyMem_Free() are one family that allocates raw memory, while PyObject_Malloc(), PyObject_Realloc(), and PyObject_Free() are another family that’s supposed to be used for creating Python objects.

Previously these different families all reduced to the platform’s malloc() and free() functions. This meant it didn’t matter if you got things wrong and allocated memory with the PyMem() function but freed it with the PyObject() function. With 2.5’s changes to obmalloc, these families now do different things and mismatches will probably result in a segfault. You should carefully test your C extension modules with Python 2.5.

The built-in set types now have an official C API. Call PySet_New() and PyFrozenSet_New() to create a new set, PySet_Add() and PySet_Discard() to add and remove elements, and PySet_Contains() and PySet_Size() to examine the set’s state. (Contributed by Raymond Hettinger.)

C code can now obtain information about the exact revision of the Python interpreter by calling the Py_GetBuildInfo() function that returns a string of build information like this: "trunk:45355:45356M, Apr 13 2006, 07:42:19". (Contributed by Barry Warsaw.)

Two new macros can be used to indicate C functions that are local to the current file so that a faster calling convention can be used. Py_LOCAL(type) declares the function as returning a value of the specified type and uses a fast-calling qualifier. Py_LOCAL_INLINE(type) does the same thing and also requests the function be inlined. If PY_LOCAL_AGGRESSIVE() is defined before python.h is included, a set of more aggressive optimizations are enabled for the module; you should benchmark the results to find out if these optimizations actually make the code faster. (Contributed by Fredrik Lundh at the NeedForSpeed sprint.)

PyErr_NewException(name, base, dict) can now accept a tuple of base classes as its base argument. (Contributed by Georg Brandl.)

The PyErr_Warn() function for issuing warnings is now deprecated in favour of PyErr_WarnEx(category, message, stacklevel) which lets you specify the number of stack frames separating this function and the caller. A stacklevel of 1 is the function calling PyErr_WarnEx(), 2 is the function above that, and so forth. (Added by Neal Norwitz.)

The CPython interpreter is still written in C, but the code can now be compiled with a C++ compiler without errors. (Implemented by Anthony Baxter, Martin von Löwis, Skip Montanaro.)

The PyRange_New() function was removed. It was never documented, never used in the core code, and had dangerously lax error checking. In the unlikely case that your extensions were using it, you can replace it by something like the following:

range = PyObject_CallFunction((PyObject*) &PyRange_Type, "lll",
                              start, stop, step);

Port-Specific Changes

MacOS X (10.3 and higher): dynamic loading of modules now uses the dlopen() function instead of MacOS-specific functions.

MacOS X: an --enable-universalsdk switch was added to the configure script that compiles the interpreter as a universal binary able to run on both PowerPC and Intel processors. (Contributed by Ronald Oussoren; bpo-2573 [https://bugs.python.org/issue2573].)

Windows: .dll is no longer supported as a filename extension for extension modules. .pyd is now the only filename extension that will be searched for.

Portage vers Python 2.5

This section lists previously described changes that may require changes to your code:

ASCII is now the default encoding for modules. It’s now a syntax error if a module contains string literals with 8-bit characters but doesn’t have an encoding declaration. In Python 2.4 this triggered a warning, not a syntax error.

Previously, the gi_frame attribute of a generator was always a frame object. Because of the PEP 342 [https://www.python.org/dev/peps/pep-0342] changes described in section PEP 342: New Generator Features, it’s now possible for gi_frame to be None.

A new warning, UnicodeWarning, is triggered when you attempt to compare a Unicode string and an 8-bit string that can’t be converted to Unicode using the default ASCII encoding. Previously such comparisons would raise a UnicodeDecodeError exception.

Library: the csv module is now stricter about multi-line quoted fields. If your files contain newlines embedded within fields, the input should be split into lines in a manner which preserves the newline characters.

Library: the locale module’s format() function’s would previously accept any string as long as no more than one %char specifier appeared. In Python 2.5, the argument must be exactly one %char specifier with no surrounding text.

Library: The pickle and cPickle modules no longer accept a return value of None from the __reduce__() method; the method must return a tuple of arguments instead. The modules also no longer accept the deprecated bin keyword parameter.

Library: The SimpleXMLRPCServer and DocXMLRPCServer classes now have a rpc_paths attribute that constrains XML-RPC operations to a limited set of URL paths; the default is to allow only '/' and '/RPC2'. Setting rpc_paths to None or an empty tuple disables this path checking.

C API: Many functions now use Py_ssize_t instead of int to allow processing more data on 64-bit machines. Extension code may need to make the same change to avoid warnings and to support 64-bit machines. See the earlier section PEP 353: Using ssize_t as the index type for a discussion of this change.

C API: The obmalloc changes mean that you must be careful to not mix usage of the PyMem_*() and PyObject_*() families of functions. Memory allocated with one family’s *_Malloc() must be freed with the corresponding family’s *_Free() function.

Remerciements

The author would like to thank the following people for offering suggestions, corrections and assistance with various drafts of this article: Georg Brandl, Nick Coghlan, Phillip J. Eby, Lars Gustäbel, Raymond Hettinger, Ralf W. Grosse-Kunstleve, Kent Johnson, Iain Lowe, Martin von Löwis, Fredrik Lundh, Andrew McNamara, Skip Montanaro, Gustavo Niemeyer, Paul Prescod, James Pryor, Mike Rovner, Scott Weikart, Barry Warsaw, Thomas Wouters.

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Nouveautés de Python 2.4

Auteur

A.M. Kuchling

This article explains the new features in Python 2.4.1, released on March 30, 2005.

Python 2.4 is a medium-sized release. It doesn’t introduce as many changes as the radical Python 2.2, but introduces more features than the conservative 2.3 release. The most significant new language features are function decorators and generator expressions; most other changes are to the standard library.

According to the CVS change logs, there were 481 patches applied and 502 bugs fixed between Python 2.3 and 2.4. Both figures are likely to be underestimates.

This article doesn’t attempt to provide a complete specification of every single new feature, but instead provides a brief introduction to each feature. For full details, you should refer to the documentation for Python 2.4, such as the Python Library Reference and the Python Reference Manual. Often you will be referred to the PEP for a particular new feature for explanations of the implementation and design rationale.

PEP 218: Built-In Set Objects

Python 2.3 introduced the sets module. C implementations of set data types have now been added to the Python core as two new built-in types, set(iterable) and frozenset(iterable). They provide high speed operations for membership testing, for eliminating duplicates from sequences, and for mathematical operations like unions, intersections, differences, and symmetric differences.

>>> a = set('abracadabra')              # form a set from a string
>>> 'z' in a                            # fast membership testing
False
>>> a                                   # unique letters in a
set(['a', 'r', 'b', 'c', 'd'])
>>> ''.join(a)                          # convert back into a string
'arbcd'

>>> b = set('alacazam')                 # form a second set
>>> a - b                               # letters in a but not in b
set(['r', 'd', 'b'])
>>> a | b                               # letters in either a or b
set(['a', 'c', 'r', 'd', 'b', 'm', 'z', 'l'])
>>> a & b                               # letters in both a and b
set(['a', 'c'])
>>> a ^ b                               # letters in a or b but not both
set(['r', 'd', 'b', 'm', 'z', 'l'])

>>> a.add('z')                          # add a new element
>>> a.update('wxy')                     # add multiple new elements
>>> a
set(['a', 'c', 'b', 'd', 'r', 'w', 'y', 'x', 'z'])
>>> a.remove('x')                       # take one element out
>>> a
set(['a', 'c', 'b', 'd', 'r', 'w', 'y', 'z'])

The frozenset() type is an immutable version of set(). Since it is immutable and hashable, it may be used as a dictionary key or as a member of another set.

The sets module remains in the standard library, and may be useful if you wish to subclass the Set or ImmutableSet classes. There are currently no plans to deprecate the module.

Voir aussi

PEP 218 [https://www.python.org/dev/peps/pep-0218] - Adding a Built-In Set Object Type

Originally proposed by Greg Wilson and ultimately implemented by Raymond Hettinger.

PEP 237: Unifying Long Integers and Integers

The lengthy transition process for this PEP, begun in Python 2.2, takes another step forward in Python 2.4. In 2.3, certain integer operations that would behave differently after int/long unification triggered FutureWarning warnings and returned values limited to 32 or 64 bits (depending on your platform). In 2.4, these expressions no longer produce a warning and instead produce a different result that’s usually a long integer.

The problematic expressions are primarily left shifts and lengthy hexadecimal and octal constants. For example, 2 << 32 results in a warning in 2.3, evaluating to 0 on 32-bit platforms. In Python 2.4, this expression now returns the correct answer, 8589934592.

Voir aussi

PEP 237 [https://www.python.org/dev/peps/pep-0237] - Unifying Long Integers and Integers

Original PEP written by Moshe Zadka and GvR. The changes for 2.4 were implemented by Kalle Svensson.

PEP 289: Generator Expressions

The iterator feature introduced in Python 2.2 and the itertools module make it easier to write programs that loop through large data sets without having the entire data set in memory at one time. List comprehensions don’t fit into this picture very well because they produce a Python list object containing all of the items. This unavoidably pulls all of the objects into memory, which can be a problem if your data set is very large. When trying to write a functionally-styled program, it would be natural to write something like:

links = [link for link in get_all_links() if not link.followed]
for link in links:
    ...

instead of

for link in get_all_links():
    if link.followed:
        continue
    ...

The first form is more concise and perhaps more readable, but if you’re dealing with a large number of link objects you’d have to write the second form to avoid having all link objects in memory at the same time.

Generator expressions work similarly to list comprehensions but don’t materialize the entire list; instead they create a generator that will return elements one by one. The above example could be written as:

links = (link for link in get_all_links() if not link.followed)
for link in links:
    ...

Generator expressions always have to be written inside parentheses, as in the above example. The parentheses signalling a function call also count, so if you want to create an iterator that will be immediately passed to a function you could write:

print sum(obj.count for obj in list_all_objects())

Generator expressions differ from list comprehensions in various small ways. Most notably, the loop variable (obj in the above example) is not accessible outside of the generator expression. List comprehensions leave the variable assigned to its last value; future versions of Python will change this, making list comprehensions match generator expressions in this respect.

Voir aussi

PEP 289 [https://www.python.org/dev/peps/pep-0289] - Generator Expressions

Proposed by Raymond Hettinger and implemented by Jiwon Seo with early efforts steered by Hye-Shik Chang.

PEP 292: Simpler String Substitutions

Some new classes in the standard library provide an alternative mechanism for substituting variables into strings; this style of substitution may be better for applications where untrained users need to edit templates.

The usual way of substituting variables by name is the % operator:

>>> '%(page)i: %(title)s' % {'page':2, 'title': 'The Best of Times'}
'2: The Best of Times'

When writing the template string, it can be easy to forget the i or s after the closing parenthesis. This isn’t a big problem if the template is in a Python module, because you run the code, get an « Unsupported format character » ValueError, and fix the problem. However, consider an application such as Mailman where template strings or translations are being edited by users who aren’t aware of the Python language. The format string’s syntax is complicated to explain to such users, and if they make a mistake, it’s difficult to provide helpful feedback to them.

PEP 292 adds a Template class to the string module that uses $ to indicate a substitution:

>>> import string
>>> t = string.Template('$page: $title')
>>> t.substitute({'page':2, 'title': 'The Best of Times'})
'2: The Best of Times'

If a key is missing from the dictionary, the substitute() method will raise a KeyError. There’s also a safe_substitute() method that ignores missing keys:

>>> t = string.Template('$page: $title')
>>> t.safe_substitute({'page':3})
'3: $title'

Voir aussi

PEP 292 [https://www.python.org/dev/peps/pep-0292] - Simpler String Substitutions

Écrit et implémenté par Barry Warsaw.

PEP 318: Decorators for Functions and Methods

Python 2.2 extended Python’s object model by adding static methods and class methods, but it didn’t extend Python’s syntax to provide any new way of defining static or class methods. Instead, you had to write a def statement in the usual way, and pass the resulting method to a staticmethod() or classmethod() function that would wrap up the function as a method of the new type. Your code would look like this:

class C:
   def meth (cls):
       ...

   meth = classmethod(meth)   # Rebind name to wrapped-up class method

If the method was very long, it would be easy to miss or forget the classmethod() invocation after the function body.

The intention was always to add some syntax to make such definitions more readable, but at the time of 2.2’s release a good syntax was not obvious. Today a good syntax still isn’t obvious but users are asking for easier access to the feature; a new syntactic feature has been added to meet this need.

The new feature is called « function decorators ». The name comes from the idea that classmethod(), staticmethod(), and friends are storing additional information on a function object; they’re decorating functions with more details.

The notation borrows from Java and uses the '@' character as an indicator. Using the new syntax, the example above would be written:

class C:

   @classmethod
   def meth (cls):
       ...

The @classmethod is shorthand for the meth=classmethod(meth) assignment. More generally, if you have the following:

@A
@B
@C
def f ():
    ...

It’s equivalent to the following pre-decorator code:

def f(): ...
f = A(B(C(f)))

Decorators must come on the line before a function definition, one decorator per line, and can’t be on the same line as the def statement, meaning that @A def f(): ... is illegal. You can only decorate function definitions, either at the module level or inside a class; you can’t decorate class definitions.

A decorator is just a function that takes the function to be decorated as an argument and returns either the same function or some new object. The return value of the decorator need not be callable (though it typically is), unless further decorators will be applied to the result. It’s easy to write your own decorators. The following simple example just sets an attribute on the function object:

>>> def deco(func):
...    func.attr = 'decorated'
...    return func
...
>>> @deco
... def f(): pass
...
>>> f
<function f at 0x402ef0d4>
>>> f.attr
'decorated'
>>>

As a slightly more realistic example, the following decorator checks that the supplied argument is an integer:

def require_int (func):
    def wrapper (arg):
        assert isinstance(arg, int)
        return func(arg)

    return wrapper

@require_int
def p1 (arg):
    print arg

@require_int
def p2(arg):
    print arg*2

An example in PEP 318 [https://www.python.org/dev/peps/pep-0318] contains a fancier version of this idea that lets you both specify the required type and check the returned type.

Decorator functions can take arguments. If arguments are supplied, your decorator function is called with only those arguments and must return a new decorator function; this function must take a single function and return a function, as previously described. In other words, @A @B @C(args) becomes:

def f(): ...
_deco = C(args)
f = A(B(_deco(f)))

Getting this right can be slightly brain-bending, but it’s not too difficult.

A small related change makes the func_name attribute of functions writable. This attribute is used to display function names in tracebacks, so decorators should change the name of any new function that’s constructed and returned.

Voir aussi

PEP 318 [https://www.python.org/dev/peps/pep-0318] - Decorators for Functions, Methods and Classes

Written by Kevin D. Smith, Jim Jewett, and Skip Montanaro. Several people wrote patches implementing function decorators, but the one that was actually checked in was patch #979728, written by Mark Russell.

https://wiki.python.org/moin/PythonDecoratorLibrary

This Wiki page contains several examples of decorators.

PEP 322: Reverse Iteration

A new built-in function, reversed(seq), takes a sequence and returns an iterator that loops over the elements of the sequence in reverse order.

>>> for i in reversed(xrange(1,4)):
...    print i
...
3
2
1

Compared to extended slicing, such as range(1,4)[::-1], reversed() is easier to read, runs faster, and uses substantially less memory.

Note that reversed() only accepts sequences, not arbitrary iterators. If you want to reverse an iterator, first convert it to a list with list().

>>> input = open('/etc/passwd', 'r')
>>> for line in reversed(list(input)):
...   print line
...
root:*:0:0:System Administrator:/var/root:/bin/tcsh
  ...

Voir aussi

PEP 322 [https://www.python.org/dev/peps/pep-0322] - Reverse Iteration

Written and implemented by Raymond Hettinger.

PEP 324: New subprocess Module

The standard library provides a number of ways to execute a subprocess, offering different features and different levels of complexity. os.system(command) is easy to use, but slow (it runs a shell process which executes the command) and dangerous (you have to be careful about escaping the shell’s metacharacters). The popen2 module offers classes that can capture standard output and standard error from the subprocess, but the naming is confusing. The subprocess module cleans this up, providing a unified interface that offers all the features you might need.

Instead of popen2’s collection of classes, subprocess contains a single class called Popen whose constructor supports a number of different keyword arguments.

class Popen(args, bufsize=0, executable=None,
            stdin=None, stdout=None, stderr=None,
            preexec_fn=None, close_fds=False, shell=False,
            cwd=None, env=None, universal_newlines=False,
            startupinfo=None, creationflags=0):

args is commonly a sequence of strings that will be the arguments to the program executed as the subprocess. (If the shell argument is true, args can be a string which will then be passed on to the shell for interpretation, just as os.system() does.)

stdin, stdout, and stderr specify what the subprocess’s input, output, and error streams will be. You can provide a file object or a file descriptor, or you can use the constant subprocess.PIPE to create a pipe between the subprocess and the parent.

The constructor has a number of handy options:

close_fds requests that all file descriptors be closed before running the subprocess.

cwd specifies the working directory in which the subprocess will be executed (defaulting to whatever the parent’s working directory is).

env is a dictionary specifying environment variables.

preexec_fn is a function that gets called before the child is started.

universal_newlines opens the child’s input and output using Python’s universal newlines feature.

Once you’ve created the Popen instance, you can call its wait() method to pause until the subprocess has exited, poll() to check if it’s exited without pausing, or communicate(data) to send the string data to the subprocess’s standard input. communicate(data) then reads any data that the subprocess has sent to its standard output or standard error, returning a tuple (stdout_data, stderr_data).

call() is a shortcut that passes its arguments along to the Popen constructor, waits for the command to complete, and returns the status code of the subprocess. It can serve as a safer analog to os.system():

sts = subprocess.call(['dpkg', '-i', '/tmp/new-package.deb'])
if sts == 0:
    # Success
    ...
else:
    # dpkg returned an error
    ...

The command is invoked without use of the shell. If you really do want to use the shell, you can add shell=True as a keyword argument and provide a string instead of a sequence:

sts = subprocess.call('dpkg -i /tmp/new-package.deb', shell=True)

The PEP takes various examples of shell and Python code and shows how they’d be translated into Python code that uses subprocess. Reading this section of the PEP is highly recommended.

Voir aussi

PEP 324 [https://www.python.org/dev/peps/pep-0324] - subprocess - New process module

Written and implemented by Peter Åstrand, with assistance from Fredrik Lundh and others.

PEP 327: Decimal Data Type

Python has always supported floating-point (FP) numbers, based on the underlying C double type, as a data type. However, while most programming languages provide a floating-point type, many people (even programmers) are unaware that floating-point numbers don’t represent certain decimal fractions accurately. The new Decimal type can represent these fractions accurately, up to a user-specified precision limit.

Why is Decimal needed?

The limitations arise from the representation used for floating-point numbers. FP numbers are made up of three components:

The sign, which is positive or negative.

The mantissa, which is a single-digit binary number followed by a fractional part. For example, 1.01 in base-2 notation is 1 + 0/2 + 1/4, or 1.25 in decimal notation.

The exponent, which tells where the decimal point is located in the number represented.

For example, the number 1.25 has positive sign, a mantissa value of 1.01 (in binary), and an exponent of 0 (the decimal point doesn’t need to be shifted). The number 5 has the same sign and mantissa, but the exponent is 2 because the mantissa is multiplied by 4 (2 to the power of the exponent 2); 1.25 * 4 equals 5.

Modern systems usually provide floating-point support that conforms to a standard called IEEE 754. C’s double type is usually implemented as a 64-bit IEEE 754 number, which uses 52 bits of space for the mantissa. This means that numbers can only be specified to 52 bits of precision. If you’re trying to represent numbers whose expansion repeats endlessly, the expansion is cut off after 52 bits. Unfortunately, most software needs to produce output in base 10, and common fractions in base 10 are often repeating decimals in binary. For example, 1.1 decimal is binary 1.0001100110011 ...; .1 = 1/16 + 1/32 + 1/256 plus an infinite number of additional terms. IEEE 754 has to chop off that infinitely repeated decimal after 52 digits, so the representation is slightly inaccurate.

Sometimes you can see this inaccuracy when the number is printed:

>>> 1.1
1.1000000000000001

The inaccuracy isn’t always visible when you print the number because the FP-to-decimal-string conversion is provided by the C library, and most C libraries try to produce sensible output. Even if it’s not displayed, however, the inaccuracy is still there and subsequent operations can magnify the error.

For many applications this doesn’t matter. If I’m plotting points and displaying them on my monitor, the difference between 1.1 and 1.1000000000000001 is too small to be visible. Reports often limit output to a certain number of decimal places, and if you round the number to two or three or even eight decimal places, the error is never apparent. However, for applications where it does matter, it’s a lot of work to implement your own custom arithmetic routines.

Hence, the Decimal type was created.

The Decimal type

A new module, decimal, was added to Python’s standard library. It contains two classes, Decimal and Context. Decimal instances represent numbers, and Context instances are used to wrap up various settings such as the precision and default rounding mode.

Decimal instances are immutable, like regular Python integers and FP numbers; once it’s been created, you can’t change the value an instance represents. Decimal instances can be created from integers or strings:

>>> import decimal
>>> decimal.Decimal(1972)
Decimal("1972")
>>> decimal.Decimal("1.1")
Decimal("1.1")

You can also provide tuples containing the sign, the mantissa represented as a tuple of decimal digits, and the exponent:

>>> decimal.Decimal((1, (1, 4, 7, 5), -2))
Decimal("-14.75")

Cautionary note: the sign bit is a Boolean value, so 0 is positive and 1 is negative.

Converting from floating-point numbers poses a bit of a problem: should the FP number representing 1.1 turn into the decimal number for exactly 1.1, or for 1.1 plus whatever inaccuracies are introduced? The decision was to dodge the issue and leave such a conversion out of the API. Instead, you should convert the floating-point number into a string using the desired precision and pass the string to the Decimal constructor:

>>> f = 1.1
>>> decimal.Decimal(str(f))
Decimal("1.1")
>>> decimal.Decimal('%.12f' % f)
Decimal("1.100000000000")

Once you have Decimal instances, you can perform the usual mathematical operations on them. One limitation: exponentiation requires an integer exponent:

>>> a = decimal.Decimal('35.72')
>>> b = decimal.Decimal('1.73')
>>> a+b
Decimal("37.45")
>>> a-b
Decimal("33.99")
>>> a*b
Decimal("61.7956")
>>> a/b
Decimal("20.64739884393063583815028902")
>>> a ** 2
Decimal("1275.9184")
>>> a**b
Traceback (most recent call last):
  ...
decimal.InvalidOperation: x ** (non-integer)

You can combine Decimal instances with integers, but not with floating-point numbers:

>>> a + 4
Decimal("39.72")
>>> a + 4.5
Traceback (most recent call last):
  ...
TypeError: You can interact Decimal only with int, long or Decimal data types.
>>>

Decimal numbers can be used with the math and cmath modules, but note that they’ll be immediately converted to floating-point numbers before the operation is performed, resulting in a possible loss of precision and accuracy. You’ll also get back a regular floating-point number and not a Decimal.

>>> import math, cmath
>>> d = decimal.Decimal('123456789012.345')
>>> math.sqrt(d)
351364.18288201344
>>> cmath.sqrt(-d)
351364.18288201344j

Decimal instances have a sqrt() method that returns a Decimal, but if you need other things such as trigonometric functions you’ll have to implement them.

>>> d.sqrt()
Decimal("351364.1828820134592177245001")

The Context type

Instances of the Context class encapsulate several settings for decimal operations:

prec is the precision, the number of decimal places.

rounding specifies the rounding mode. The decimal module has constants for the various possibilities: ROUND_DOWN, ROUND_CEILING, ROUND_HALF_EVEN, and various others.

traps is a dictionary specifying what happens on encountering certain error conditions: either an exception is raised or a value is returned. Some examples of error conditions are division by zero, loss of precision, and overflow.

There’s a thread-local default context available by calling getcontext(); you can change the properties of this context to alter the default precision, rounding, or trap handling. The following example shows the effect of changing the precision of the default context:

>>> decimal.getcontext().prec
28
>>> decimal.Decimal(1) / decimal.Decimal(7)
Decimal("0.1428571428571428571428571429")
>>> decimal.getcontext().prec = 9
>>> decimal.Decimal(1) / decimal.Decimal(7)
Decimal("0.142857143")

The default action for error conditions is selectable; the module can either return a special value such as infinity or not-a-number, or exceptions can be raised:

>>> decimal.Decimal(1) / decimal.Decimal(0)
Traceback (most recent call last):
  ...
decimal.DivisionByZero: x / 0
>>> decimal.getcontext().traps[decimal.DivisionByZero] = False
>>> decimal.Decimal(1) / decimal.Decimal(0)
Decimal("Infinity")
>>>

The Context instance also has various methods for formatting numbers such as to_eng_string() and to_sci_string().

For more information, see the documentation for the decimal module, which includes a quick-start tutorial and a reference.

Voir aussi

PEP 327 [https://www.python.org/dev/peps/pep-0327] - Decimal Data Type

Written by Facundo Batista and implemented by Facundo Batista, Eric Price, Raymond Hettinger, Aahz, and Tim Peters.

http://www.lahey.com/float.htm

The article uses Fortran code to illustrate many of the problems that floating-point inaccuracy can cause.

http://speleotrove.com/decimal/

A description of a decimal-based representation. This representation is being proposed as a standard, and underlies the new Python decimal type. Much of this material was written by Mike Cowlishaw, designer of the Rexx language.

PEP 328: Multi-line Imports

One language change is a small syntactic tweak aimed at making it easier to import many names from a module. In a from module import names statement, names is a sequence of names separated by commas. If the sequence is very long, you can either write multiple imports from the same module, or you can use backslashes to escape the line endings like this:

from SimpleXMLRPCServer import SimpleXMLRPCServer,\
            SimpleXMLRPCRequestHandler,\
            CGIXMLRPCRequestHandler,\
            resolve_dotted_attribute

The syntactic change in Python 2.4 simply allows putting the names within parentheses. Python ignores newlines within a parenthesized expression, so the backslashes are no longer needed:

from SimpleXMLRPCServer import (SimpleXMLRPCServer,
                                SimpleXMLRPCRequestHandler,
                                CGIXMLRPCRequestHandler,
                                resolve_dotted_attribute)

The PEP also proposes that all import statements be absolute imports, with a leading . character to indicate a relative import. This part of the PEP was not implemented for Python 2.4, but was completed for Python 2.5.

Voir aussi

PEP 328 [https://www.python.org/dev/peps/pep-0328] - Imports: Multi-Line and Absolute/Relative

Written by Aahz. Multi-line imports were implemented by Dima Dorfman.

PEP 331: Locale-Independent Float/String Conversions

The locale modules lets Python software select various conversions and display conventions that are localized to a particular country or language. However, the module was careful to not change the numeric locale because various functions in Python’s implementation required that the numeric locale remain set to the 'C' locale. Often this was because the code was using the C library’s atof() function.

Not setting the numeric locale caused trouble for extensions that used third-party C libraries, however, because they wouldn’t have the correct locale set. The motivating example was GTK+, whose user interface widgets weren’t displaying numbers in the current locale.

The solution described in the PEP is to add three new functions to the Python API that perform ASCII-only conversions, ignoring the locale setting:

PyOS_ascii_strtod(str, ptr) and PyOS_ascii_atof(str, ptr) both convert a string to a C double.

PyOS_ascii_formatd(buffer, buf_len, format, d) converts a double to an ASCII string.

The code for these functions came from the GLib library (https://developer.gnome.org/glib/stable/), whose developers kindly relicensed the relevant functions and donated them to the Python Software Foundation. The locale module can now change the numeric locale, letting extensions such as GTK+ produce the correct results.

Voir aussi

PEP 331 [https://www.python.org/dev/peps/pep-0331] - Locale-Independent Float/String Conversions

Written by Christian R. Reis, and implemented by Gustavo Carneiro.

Other Language Changes

Here are all of the changes that Python 2.4 makes to the core Python language.

Decorators for functions and methods were added (PEP 318 [https://www.python.org/dev/peps/pep-0318]).

Built-in set() and frozenset() types were added (PEP 218 [https://www.python.org/dev/peps/pep-0218]). Other new built-ins include the reversed(seq) function (PEP 322 [https://www.python.org/dev/peps/pep-0322]).

Generator expressions were added (PEP 289 [https://www.python.org/dev/peps/pep-0289]).

Certain numeric expressions no longer return values restricted to 32 or 64 bits (PEP 237 [https://www.python.org/dev/peps/pep-0237]).

You can now put parentheses around the list of names in a from module import names statement (PEP 328 [https://www.python.org/dev/peps/pep-0328]).

The dict.update() method now accepts the same argument forms as the dict constructor. This includes any mapping, any iterable of key/value pairs, and keyword arguments. (Contributed by Raymond Hettinger.)

The string methods ljust(), rjust(), and center() now take an optional argument for specifying a fill character other than a space. (Contributed by Raymond Hettinger.)

Strings also gained an rsplit() method that works like the split() method but splits from the end of the string. (Contributed by Sean Reifschneider.)

>>> 'www.python.org'.split('.', 1)
['www', 'python.org']
'www.python.org'.rsplit('.', 1)
['www.python', 'org']

Three keyword parameters, cmp, key, and reverse, were added to the sort() method of lists. These parameters make some common usages of sort() simpler. All of these parameters are optional.

For the cmp parameter, the value should be a comparison function that takes two parameters and returns -1, 0, or +1 depending on how the parameters compare. This function will then be used to sort the list. Previously this was the only parameter that could be provided to sort().

key should be a single-parameter function that takes a list element and returns a comparison key for the element. The list is then sorted using the comparison keys. The following example sorts a list case-insensitively:

>>> L = ['A', 'b', 'c', 'D']
>>> L.sort()                 # Case-sensitive sort
>>> L
['A', 'D', 'b', 'c']
>>> # Using 'key' parameter to sort list
>>> L.sort(key=lambda x: x.lower())
>>> L
['A', 'b', 'c', 'D']
>>> # Old-fashioned way
>>> L.sort(cmp=lambda x,y: cmp(x.lower(), y.lower()))
>>> L
['A', 'b', 'c', 'D']

The last example, which uses the cmp parameter, is the old way to perform a case-insensitive sort. It works but is slower than using a key parameter. Using key calls lower() method once for each element in the list while using cmp will call it twice for each comparison, so using key saves on invocations of the lower() method.

For simple key functions and comparison functions, it is often possible to avoid a lambda expression by using an unbound method instead. For example, the above case-insensitive sort is best written as:

>>> L.sort(key=str.lower)
>>> L
['A', 'b', 'c', 'D']

Finally, the reverse parameter takes a Boolean value. If the value is true, the list will be sorted into reverse order. Instead of L.sort(); L.reverse(), you can now write L.sort(reverse=True).

The results of sorting are now guaranteed to be stable. This means that two entries with equal keys will be returned in the same order as they were input. For example, you can sort a list of people by name, and then sort the list by age, resulting in a list sorted by age where people with the same age are in name-sorted order.

(All changes to sort() contributed by Raymond Hettinger.)

There is a new built-in function sorted(iterable) that works like the in-place list.sort() method but can be used in expressions. The differences are:

the input may be any iterable;

a newly formed copy is sorted, leaving the original intact; and

the expression returns the new sorted copy

>>> L = [9,7,8,3,2,4,1,6,5]
>>> [10+i for i in sorted(L)]       # usable in a list comprehension
[11, 12, 13, 14, 15, 16, 17, 18, 19]
>>> L                               # original is left unchanged
[9,7,8,3,2,4,1,6,5]
>>> sorted('Monty Python')          # any iterable may be an input
[' ', 'M', 'P', 'h', 'n', 'n', 'o', 'o', 't', 't', 'y', 'y']

>>> # List the contents of a dict sorted by key values
>>> colormap = dict(red=1, blue=2, green=3, black=4, yellow=5)
>>> for k, v in sorted(colormap.iteritems()):
...     print k, v
...
black 4
blue 2
green 3
red 1
yellow 5

(Contributed by Raymond Hettinger.)

Integer operations will no longer trigger an OverflowWarning. The OverflowWarning warning will disappear in Python 2.5.

The interpreter gained a new switch, -m, that takes a name, searches for the corresponding module on sys.path, and runs the module as a script. For example, you can now run the Python profiler with python -m profile. (Contributed by Nick Coghlan.)

The eval(expr, globals, locals) and execfile(filename, globals, locals) functions and the exec statement now accept any mapping type for the locals parameter. Previously this had to be a regular Python dictionary. (Contributed by Raymond Hettinger.)

The zip() built-in function and itertools.izip() now return an empty list if called with no arguments. Previously they raised a TypeError exception. This makes them more suitable for use with variable length argument lists:

>>> def transpose(array):
...    return zip(*array)
...
>>> transpose([(1,2,3), (4,5,6)])
[(1, 4), (2, 5), (3, 6)]
>>> transpose([])
[]

(Contributed by Raymond Hettinger.)

Encountering a failure while importing a module no longer leaves a partially-initialized module object in sys.modules. The incomplete module object left behind would fool further imports of the same module into succeeding, leading to confusing errors. (Fixed by Tim Peters.)

None is now a constant; code that binds a new value to the name None is now a syntax error. (Contributed by Raymond Hettinger.)

Optimizations

The inner loops for list and tuple slicing were optimized and now run about one-third faster. The inner loops for dictionaries were also optimized, resulting in performance boosts for keys(), values(), items(), iterkeys(), itervalues(), and iteritems(). (Contributed by Raymond Hettinger.)

The machinery for growing and shrinking lists was optimized for speed and for space efficiency. Appending and popping from lists now runs faster due to more efficient code paths and less frequent use of the underlying system realloc(). List comprehensions also benefit. list.extend() was also optimized and no longer converts its argument into a temporary list before extending the base list. (Contributed by Raymond Hettinger.)

list(), tuple(), map(), filter(), and zip() now run several times faster with non-sequence arguments that supply a __len__() method. (Contributed by Raymond Hettinger.)

The methods list.__getitem__(), dict.__getitem__(), and dict.__contains__() are now implemented as method_descriptor objects rather than wrapper_descriptor objects. This form of access doubles their performance and makes them more suitable for use as arguments to functionals: map(mydict.__getitem__, keylist). (Contributed by Raymond Hettinger.)

Added a new opcode, LIST_APPEND, that simplifies the generated bytecode for list comprehensions and speeds them up by about a third. (Contributed by Raymond Hettinger.)

The peephole bytecode optimizer has been improved to produce shorter, faster bytecode; remarkably, the resulting bytecode is more readable. (Enhanced by Raymond Hettinger.)

String concatenations in statements of the form s = s + "abc" and s += "abc" are now performed more efficiently in certain circumstances. This optimization won’t be present in other Python implementations such as Jython, so you shouldn’t rely on it; using the join() method of strings is still recommended when you want to efficiently glue a large number of strings together. (Contributed by Armin Rigo.)

The net result of the 2.4 optimizations is that Python 2.4 runs the pystone benchmark around 5% faster than Python 2.3 and 35% faster than Python 2.2. (pystone is not a particularly good benchmark, but it’s the most commonly used measurement of Python’s performance. Your own applications may show greater or smaller benefits from Python 2.4.)

New, Improved, and Deprecated Modules

As usual, Python’s standard library received a number of enhancements and bug fixes. Here’s a partial list of the most notable changes, sorted alphabetically by module name. Consult the Misc/NEWS file in the source tree for a more complete list of changes, or look through the CVS logs for all the details.

The asyncore module’s loop() function now has a count parameter that lets you perform a limited number of passes through the polling loop. The default is still to loop forever.

The base64 module now has more complete RFC 3548 [https://tools.ietf.org/html/rfc3548.html] support for Base64, Base32, and Base16 encoding and decoding, including optional case folding and optional alternative alphabets. (Contributed by Barry Warsaw.)

The bisect module now has an underlying C implementation for improved performance. (Contributed by Dmitry Vasiliev.)

The CJKCodecs collections of East Asian codecs, maintained by Hye-Shik Chang, was integrated into 2.4. The new encodings are:

Chinois (PRC) : gb2312, gbk, gb18030, big5hkscs, hz

Chinois (ROC) : big5, cp950

Japonais : cp932, euc-jis-2004, euc-jp, euc-jisx0213, iso-2022-jp,

iso-2022-jp-1, iso-2022-jp-2, iso-2022-jp-3, iso-2022-jp-ext, iso-2022-jp-2004, shift-jis, shift-jisx0213, shift-jis-2004

Coréen : cp949, euc-kr, johab, iso-2022-kr

D’autres encodages ont été ajoutés : HP Roman8, ISO_8859-11, ISO_8859-16, PCTP-154, et TIS-620.

The UTF-8 and UTF-16 codecs now cope better with receiving partial input. Previously the StreamReader class would try to read more data, making it impossible to resume decoding from the stream. The read() method will now return as much data as it can and future calls will resume decoding where previous ones left off. (Implemented by Walter Dörwald.)

There is a new collections module for various specialized collection datatypes. Currently it contains just one type, deque, a double-ended queue that supports efficiently adding and removing elements from either end:

>>> from collections import deque
>>> d = deque('ghi')        # make a new deque with three items
>>> d.append('j')           # add a new entry to the right side
>>> d.appendleft('f')       # add a new entry to the left side
>>> d                       # show the representation of the deque
deque(['f', 'g', 'h', 'i', 'j'])
>>> d.pop()                 # return and remove the rightmost item
'j'
>>> d.popleft()             # return and remove the leftmost item
'f'
>>> list(d)                 # list the contents of the deque
['g', 'h', 'i']
>>> 'h' in d                # search the deque
True

Several modules, such as the Queue and threading modules, now take advantage of collections.deque for improved performance. (Contributed by Raymond Hettinger.)

The ConfigParser classes have been enhanced slightly. The read() method now returns a list of the files that were successfully parsed, and the set() method raises TypeError if passed a value argument that isn’t a string. (Contributed by John Belmonte and David Goodger.)

The curses module now supports the ncurses extension use_default_colors(). On platforms where the terminal supports transparency, this makes it possible to use a transparent background. (Contributed by Jörg Lehmann.)

The difflib module now includes an HtmlDiff class that creates an HTML table showing a side by side comparison of two versions of a text. (Contributed by Dan Gass.)

The email package was updated to version 3.0, which dropped various deprecated APIs and removes support for Python versions earlier than 2.3. The 3.0 version of the package uses a new incremental parser for MIME messages, available in the email.FeedParser module. The new parser doesn’t require reading the entire message into memory, and doesn’t raise exceptions if a message is malformed; instead it records any problems in the defect attribute of the message. (Developed by Anthony Baxter, Barry Warsaw, Thomas Wouters, and others.)

The heapq module has been converted to C. The resulting tenfold improvement in speed makes the module suitable for handling high volumes of data. In addition, the module has two new functions nlargest() and nsmallest() that use heaps to find the N largest or smallest values in a dataset without the expense of a full sort. (Contributed by Raymond Hettinger.)

The httplib module now contains constants for HTTP status codes defined in various HTTP-related RFC documents. Constants have names such as OK, CREATED, CONTINUE, and MOVED_PERMANENTLY; use pydoc to get a full list. (Contributed by Andrew Eland.)

The imaplib module now supports IMAP’s THREAD command (contributed by Yves Dionne) and new deleteacl() and myrights() methods (contributed by Arnaud Mazin).

The itertools module gained a groupby(iterable[, *func*]) function. iterable is something that can be iterated over to return a stream of elements, and the optional func parameter is a function that takes an element and returns a key value; if omitted, the key is simply the element itself. groupby() then groups the elements into subsequences which have matching values of the key, and returns a series of 2-tuples containing the key value and an iterator over the subsequence.

Here’s an example to make this clearer. The key function simply returns whether a number is even or odd, so the result of groupby() is to return consecutive runs of odd or even numbers.

>>> import itertools
>>> L = [2, 4, 6, 7, 8, 9, 11, 12, 14]
>>> for key_val, it in itertools.groupby(L, lambda x: x % 2):
...    print key_val, list(it)
...
0 [2, 4, 6]
1 [7]
0 [8]
1 [9, 11]
0 [12, 14]
>>>

groupby() is typically used with sorted input. The logic for groupby() is similar to the Unix uniq filter which makes it handy for eliminating, counting, or identifying duplicate elements:

>>> word = 'abracadabra'
>>> letters = sorted(word)   # Turn string into a sorted list of letters
>>> letters
['a', 'a', 'a', 'a', 'a', 'b', 'b', 'c', 'd', 'r', 'r']
>>> for k, g in itertools.groupby(letters):
...    print k, list(g)
...
a ['a', 'a', 'a', 'a', 'a']
b ['b', 'b']
c ['c']
d ['d']
r ['r', 'r']
>>> # List unique letters
>>> [k for k, g in groupby(letters)]
['a', 'b', 'c', 'd', 'r']
>>> # Count letter occurrences
>>> [(k, len(list(g))) for k, g in groupby(letters)]
[('a', 5), ('b', 2), ('c', 1), ('d', 1), ('r', 2)]

(Contribution par Hye-Shik Chang.)

itertools also gained a function named tee(iterator, N) that returns N independent iterators that replicate iterator. If N is omitted, the default is 2.

>>> L = [1,2,3]
>>> i1, i2 = itertools.tee(L)
>>> i1,i2
(<itertools.tee object at 0x402c2080>, <itertools.tee object at 0x402c2090>)
>>> list(i1)               # Run the first iterator to exhaustion
[1, 2, 3]
>>> list(i2)               # Run the second iterator to exhaustion
[1, 2, 3]

Note that tee() has to keep copies of the values returned by the iterator; in the worst case, it may need to keep all of them. This should therefore be used carefully if the leading iterator can run far ahead of the trailing iterator in a long stream of inputs. If the separation is large, then you might as well use list() instead. When the iterators track closely with one another, tee() is ideal. Possible applications include bookmarking, windowing, or lookahead iterators. (Contributed by Raymond Hettinger.)

A number of functions were added to the locale module, such as bind_textdomain_codeset() to specify a particular encoding and a family of l*gettext() functions that return messages in the chosen encoding. (Contributed by Gustavo Niemeyer.)

Some keyword arguments were added to the logging package’s basicConfig() function to simplify log configuration. The default behavior is to log messages to standard error, but various keyword arguments can be specified to log to a particular file, change the logging format, or set the logging level. For example:

import logging
logging.basicConfig(filename='/var/log/application.log',
    level=0,  # Log all messages
    format='%(levelname):%(process):%(thread):%(message)')

Other additions to the logging package include a log(level, msg) convenience method, as well as a TimedRotatingFileHandler class that rotates its log files at a timed interval. The module already had RotatingFileHandler, which rotated logs once the file exceeded a certain size. Both classes derive from a new BaseRotatingHandler class that can be used to implement other rotating handlers.

(Changements implémentés par Vinay Sajip.)

The marshal module now shares interned strings on unpacking a data structure. This may shrink the size of certain pickle strings, but the primary effect is to make .pyc files significantly smaller. (Contributed by Martin von Löwis.)

The nntplib module’s NNTP class gained description() and descriptions() methods to retrieve newsgroup descriptions for a single group or for a range of groups. (Contributed by Jürgen A. Erhard.)

Two new functions were added to the operator module, attrgetter(attr) and itemgetter(index). Both functions return callables that take a single argument and return the corresponding attribute or item; these callables make excellent data extractors when used with map() or sorted(). For example:

>>> L = [('c', 2), ('d', 1), ('a', 4), ('b', 3)]
>>> map(operator.itemgetter(0), L)
['c', 'd', 'a', 'b']
>>> map(operator.itemgetter(1), L)
[2, 1, 4, 3]
>>> sorted(L, key=operator.itemgetter(1)) # Sort list by second tuple item
[('d', 1), ('c', 2), ('b', 3), ('a', 4)]

(Contributed by Raymond Hettinger.)

The optparse module was updated in various ways. The module now passes its messages through gettext.gettext(), making it possible to internationalize Optik’s help and error messages. Help messages for options can now include the string '%default', which will be replaced by the option’s default value. (Contributed by Greg Ward.)

The long-term plan is to deprecate the rfc822 module in some future Python release in favor of the email package. To this end, the email.Utils.formatdate() function has been changed to make it usable as a replacement for rfc822.formatdate(). You may want to write new e-mail processing code with this in mind. (Change implemented by Anthony Baxter.)

A new urandom(n) function was added to the os module, returning a string containing n bytes of random data. This function provides access to platform-specific sources of randomness such as /dev/urandom on Linux or the Windows CryptoAPI. (Contributed by Trevor Perrin.)

Another new function: os.path.lexists(path) returns true if the file specified by path exists, whether or not it’s a symbolic link. This differs from the existing os.path.exists(path) function, which returns false if path is a symlink that points to a destination that doesn’t exist. (Contributed by Beni Cherniavsky.)

A new getsid() function was added to the posix module that underlies the os module. (Contributed by J. Raynor.)

Le module poplib supporte maintenant POP sur SSL. (Contribution par Hector Urtubia.)

The profile module can now profile C extension functions. (Contributed by Nick Bastin.)

The random module has a new method called getrandbits(N) that returns a long integer N bits in length. The existing randrange() method now uses getrandbits() where appropriate, making generation of arbitrarily large random numbers more efficient. (Contributed by Raymond Hettinger.)

The regular expression language accepted by the re module was extended with simple conditional expressions, written as (?(group)A|B). group is either a numeric group ID or a group name defined with (?P<group>...) earlier in the expression. If the specified group matched, the regular expression pattern A will be tested against the string; if the group didn’t match, the pattern B will be used instead. (Contributed by Gustavo Niemeyer.)

The re module is also no longer recursive, thanks to a massive amount of work by Gustavo Niemeyer. In a recursive regular expression engine, certain patterns result in a large amount of C stack space being consumed, and it was possible to overflow the stack. For example, if you matched a 30000-byte string of a characters against the expression (a|b)+, one stack frame was consumed per character. Python 2.3 tried to check for stack overflow and raise a RuntimeError exception, but certain patterns could sidestep the checking and if you were unlucky Python could segfault. Python 2.4’s regular expression engine can match this pattern without problems.

The signal module now performs tighter error-checking on the parameters to the signal.signal() function. For example, you can’t set a handler on the SIGKILL signal; previous versions of Python would quietly accept this, but 2.4 will raise a RuntimeError exception.

Two new functions were added to the socket module. socketpair() returns a pair of connected sockets and getservbyport(port) looks up the service name for a given port number. (Contributed by Dave Cole and Barry Warsaw.)

The sys.exitfunc() function has been deprecated. Code should be using the existing atexit module, which correctly handles calling multiple exit functions. Eventually sys.exitfunc() will become a purely internal interface, accessed only by atexit.

The tarfile module now generates GNU-format tar files by default. (Contributed by Lars Gustäbel.)

The threading module now has an elegantly simple way to support thread-local data. The module contains a local class whose attribute values are local to different threads.

import threading

data = threading.local()
data.number = 42
data.url = ('www.python.org', 80)

Other threads can assign and retrieve their own values for the number and url attributes. You can subclass local to initialize attributes or to add methods. (Contributed by Jim Fulton.)

The timeit module now automatically disables periodic garbage collection during the timing loop. This change makes consecutive timings more comparable. (Contributed by Raymond Hettinger.)

The weakref module now supports a wider variety of objects including Python functions, class instances, sets, frozensets, deques, arrays, files, sockets, and regular expression pattern objects. (Contributed by Raymond Hettinger.)

The xmlrpclib module now supports a multi-call extension for transmitting multiple XML-RPC calls in a single HTTP operation. (Contributed by Brian Quinlan.)

The mpz, rotor, and xreadlines modules have been removed.

cookielib

The cookielib library supports client-side handling for HTTP cookies, mirroring the Cookie module’s server-side cookie support. Cookies are stored in cookie jars; the library transparently stores cookies offered by the web server in the cookie jar, and fetches the cookie from the jar when connecting to the server. As in web browsers, policy objects control whether cookies are accepted or not.

In order to store cookies across sessions, two implementations of cookie jars are provided: one that stores cookies in the Netscape format so applications can use the Mozilla or Lynx cookie files, and one that stores cookies in the same format as the Perl libwww library.

urllib2 has been changed to interact with cookielib: HTTPCookieProcessor manages a cookie jar that is used when accessing URLs.

This module was contributed by John J. Lee.

doctest

The doctest module underwent considerable refactoring thanks to Edward Loper and Tim Peters. Testing can still be as simple as running doctest.testmod(), but the refactorings allow customizing the module’s operation in various ways

The new DocTestFinder class extracts the tests from a given object’s docstrings:

def f (x, y):
    """>>> f(2,2)
4
>>> f(3,2)
6
    """
    return x*y

finder = doctest.DocTestFinder()

# Get list of DocTest instances
tests = finder.find(f)

The new DocTestRunner class then runs individual tests and can produce a summary of the results:

runner = doctest.DocTestRunner()
for t in tests:
    tried, failed = runner.run(t)

runner.summarize(verbose=1)

The above example produces the following output:

1 items passed all tests:
   2 tests in f
2 tests in 1 items.
2 passed and 0 failed.
Test passed.

DocTestRunner uses an instance of the OutputChecker class to compare the expected output with the actual output. This class takes a number of different flags that customize its behaviour; ambitious users can also write a completely new subclass of OutputChecker.

The default output checker provides a number of handy features. For example, with the doctest.ELLIPSIS option flag, an ellipsis (...) in the expected output matches any substring, making it easier to accommodate outputs that vary in minor ways:

def o (n):
    """>>> o(1)
<__main__.C instance at 0x...>
>>>
"""

Another special string, <BLANKLINE>, matches a blank line:

def p (n):
    """>>> p(1)
<BLANKLINE>
>>>
"""

Another new capability is producing a diff-style display of the output by specifying the doctest.REPORT_UDIFF (unified diffs), doctest.REPORT_CDIFF (context diffs), or doctest.REPORT_NDIFF (delta-style) option flags. For example:

def g (n):
    """>>> g(4)
here
is
a
lengthy
>>>"""
    L = 'here is a rather lengthy list of words'.split()
    for word in L[:n]:
        print word

Running the above function’s tests with doctest.REPORT_UDIFF specified, you get the following output:

**********************************************************************
File "t.py", line 15, in g
Failed example:
    g(4)
Differences (unified diff with -expected +actual):
    @@ -2,3 +2,3 @@
     is
     a
    -lengthy
    +rather
**********************************************************************

Build and C API Changes

Some of the changes to Python’s build process and to the C API are:

Three new convenience macros were added for common return values from extension functions: Py_RETURN_NONE, Py_RETURN_TRUE, and Py_RETURN_FALSE. (Contributed by Brett Cannon.)

Another new macro, Py_CLEAR(obj), decreases the reference count of obj and sets obj to the null pointer. (Contributed by Jim Fulton.)

A new function, PyTuple_Pack(N, obj1, obj2, ..., objN), constructs tuples from a variable length argument list of Python objects. (Contributed by Raymond Hettinger.)

A new function, PyDict_Contains(d, k), implements fast dictionary lookups without masking exceptions raised during the look-up process. (Contributed by Raymond Hettinger.)

The Py_IS_NAN(X) macro returns 1 if its float or double argument X is a NaN. (Contributed by Tim Peters.)

C code can avoid unnecessary locking by using the new PyEval_ThreadsInitialized() function to tell if any thread operations have been performed. If this function returns false, no lock operations are needed. (Contributed by Nick Coghlan.)

A new function, PyArg_VaParseTupleAndKeywords(), is the same as PyArg_ParseTupleAndKeywords() but takes a va_list instead of a number of arguments. (Contributed by Greg Chapman.)

A new method flag, METH_COEXISTS, allows a function defined in slots to co-exist with a PyCFunction having the same name. This can halve the access time for a method such as set.__contains__(). (Contributed by Raymond Hettinger.)

Python can now be built with additional profiling for the interpreter itself, intended as an aid to people developing the Python core. Providing --enable-profiling to the configure script will let you profile the interpreter with gprof, and providing the --with-tsc switch enables profiling using the Pentium’s Time-Stamp-Counter register. Note that the --with-tsc switch is slightly misnamed, because the profiling feature also works on the PowerPC platform, though that processor architecture doesn’t call that register « the TSC register ». (Contributed by Jeremy Hylton.)

The tracebackobject type has been renamed to PyTracebackObject.

Port-Specific Changes

The Windows port now builds under MSVC++ 7.1 as well as version 6. (Contributed by Martin von Löwis.)

Portage vers Python 2.4

This section lists previously described changes that may require changes to your code:

Left shifts and hexadecimal/octal constants that are too large no longer trigger a FutureWarning and return a value limited to 32 or 64 bits; instead they return a long integer.

Integer operations will no longer trigger an OverflowWarning. The OverflowWarning warning will disappear in Python 2.5.

The zip() built-in function and itertools.izip() now return an empty list instead of raising a TypeError exception if called with no arguments.

You can no longer compare the date and datetime instances provided by the datetime module. Two instances of different classes will now always be unequal, and relative comparisons (<, >) will raise a TypeError.

dircache.listdir() now passes exceptions to the caller instead of returning empty lists.

LexicalHandler.startDTD() used to receive the public and system IDs in the wrong order. This has been corrected; applications relying on the wrong order need to be fixed.

fcntl.ioctl() now warns if the mutate argument is omitted and relevant.

The tarfile module now generates GNU-format tar files by default.

Encountering a failure while importing a module no longer leaves a partially-initialized module object in sys.modules.

None is now a constant; code that binds a new value to the name None is now a syntax error.

The signals.signal() function now raises a RuntimeError exception for certain illegal values; previously these errors would pass silently. For example, you can no longer set a handler on the SIGKILL signal.

Remerciements

The author would like to thank the following people for offering suggestions, corrections and assistance with various drafts of this article: Koray Can, Hye-Shik Chang, Michael Dyck, Raymond Hettinger, Brian Hurt, Hamish Lawson, Fredrik Lundh, Sean Reifschneider, Sadruddin Rejeb.

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Nouveautés de Python 2.3

Auteur

A.M. Kuchling

This article explains the new features in Python 2.3. Python 2.3 was released on July 29, 2003.

The main themes for Python 2.3 are polishing some of the features added in 2.2, adding various small but useful enhancements to the core language, and expanding the standard library. The new object model introduced in the previous version has benefited from 18 months of bugfixes and from optimization efforts that have improved the performance of new-style classes. A few new built-in functions have been added such as sum() and enumerate(). The in operator can now be used for substring searches (e.g. "ab" in "abc" returns True).

Some of the many new library features include Boolean, set, heap, and date/time data types, the ability to import modules from ZIP-format archives, metadata support for the long-awaited Python catalog, an updated version of IDLE, and modules for logging messages, wrapping text, parsing CSV files, processing command-line options, using BerkeleyDB databases… the list of new and enhanced modules is lengthy.

This article doesn’t attempt to provide a complete specification of the new features, but instead provides a convenient overview. For full details, you should refer to the documentation for Python 2.3, such as the Python Library Reference and the Python Reference Manual. If you want to understand the complete implementation and design rationale, refer to the PEP for a particular new feature.

PEP 218: A Standard Set Datatype

The new sets module contains an implementation of a set datatype. The Set class is for mutable sets, sets that can have members added and removed. The ImmutableSet class is for sets that can’t be modified, and instances of ImmutableSet can therefore be used as dictionary keys. Sets are built on top of dictionaries, so the elements within a set must be hashable.

Here’s a simple example:

>>> import sets
>>> S = sets.Set([1,2,3])
>>> S
Set([1, 2, 3])
>>> 1 in S
True
>>> 0 in S
False
>>> S.add(5)
>>> S.remove(3)
>>> S
Set([1, 2, 5])
>>>

The union and intersection of sets can be computed with the union() and intersection() methods; an alternative notation uses the bitwise operators & and |. Mutable sets also have in-place versions of these methods, union_update() and intersection_update().

>>> S1 = sets.Set([1,2,3])
>>> S2 = sets.Set([4,5,6])
>>> S1.union(S2)
Set([1, 2, 3, 4, 5, 6])
>>> S1 | S2                  # Alternative notation
Set([1, 2, 3, 4, 5, 6])
>>> S1.intersection(S2)
Set([])
>>> S1 & S2                  # Alternative notation
Set([])
>>> S1.union_update(S2)
>>> S1
Set([1, 2, 3, 4, 5, 6])
>>>

It’s also possible to take the symmetric difference of two sets. This is the set of all elements in the union that aren’t in the intersection. Another way of putting it is that the symmetric difference contains all elements that are in exactly one set. Again, there’s an alternative notation (^), and an in-place version with the ungainly name symmetric_difference_update().

>>> S1 = sets.Set([1,2,3,4])
>>> S2 = sets.Set([3,4,5,6])
>>> S1.symmetric_difference(S2)
Set([1, 2, 5, 6])
>>> S1 ^ S2
Set([1, 2, 5, 6])
>>>

There are also issubset() and issuperset() methods for checking whether one set is a subset or superset of another:

>>> S1 = sets.Set([1,2,3])
>>> S2 = sets.Set([2,3])
>>> S2.issubset(S1)
True
>>> S1.issubset(S2)
False
>>> S1.issuperset(S2)
True
>>>

Voir aussi

PEP 218 [https://www.python.org/dev/peps/pep-0218] - Adding a Built-In Set Object Type

PEP written by Greg V. Wilson. Implemented by Greg V. Wilson, Alex Martelli, and GvR.

PEP 255 : Générateurs simples

In Python 2.2, generators were added as an optional feature, to be enabled by a from __future__ import generators directive. In 2.3 generators no longer need to be specially enabled, and are now always present; this means that yield is now always a keyword. The rest of this section is a copy of the description of generators from the « What’s New in Python 2.2 » document; if you read it back when Python 2.2 came out, you can skip the rest of this section.

You’re doubtless familiar with how function calls work in Python or C. When you call a function, it gets a private namespace where its local variables are created. When the function reaches a return statement, the local variables are destroyed and the resulting value is returned to the caller. A later call to the same function will get a fresh new set of local variables. But, what if the local variables weren’t thrown away on exiting a function? What if you could later resume the function where it left off? This is what generators provide; they can be thought of as resumable functions.

Here’s the simplest example of a generator function:

def generate_ints(N):
    for i in range(N):
        yield i

A new keyword, yield, was introduced for generators. Any function containing a yield statement is a generator function; this is detected by Python’s bytecode compiler which compiles the function specially as a result.

When you call a generator function, it doesn’t return a single value; instead it returns a generator object that supports the iterator protocol. On executing the yield statement, the generator outputs the value of i, similar to a return statement. The big difference between yield and a return statement is that on reaching a yield the generator’s state of execution is suspended and local variables are preserved. On the next call to the generator’s .next() method, the function will resume executing immediately after the yield statement. (For complicated reasons, the yield statement isn’t allowed inside the try block of a try…finally statement; read PEP 255 [https://www.python.org/dev/peps/pep-0255] for a full explanation of the interaction between yield and exceptions.)

Here’s a sample usage of the generate_ints() generator:

>>> gen = generate_ints(3)
>>> gen
<generator object at 0x8117f90>
>>> gen.next()
0
>>> gen.next()
1
>>> gen.next()
2
>>> gen.next()
Traceback (most recent call last):
  File "stdin", line 1, in ?
  File "stdin", line 2, in generate_ints
StopIteration

You could equally write for i in generate_ints(5), or a,b,c = generate_ints(3).

Inside a generator function, the return statement can only be used without a value, and signals the end of the procession of values; afterwards the generator cannot return any further values. return with a value, such as return 5, is a syntax error inside a generator function. The end of the generator’s results can also be indicated by raising StopIteration manually, or by just letting the flow of execution fall off the bottom of the function.

You could achieve the effect of generators manually by writing your own class and storing all the local variables of the generator as instance variables. For example, returning a list of integers could be done by setting self.count to 0, and having the next() method increment self.count and return it. However, for a moderately complicated generator, writing a corresponding class would be much messier. Lib/test/test_generators.py contains a number of more interesting examples. The simplest one implements an in-order traversal of a tree using generators recursively.

# A recursive generator that generates Tree leaves in in-order.
def inorder(t):
    if t:
        for x in inorder(t.left):
            yield x
        yield t.label
        for x in inorder(t.right):
            yield x

Two other examples in Lib/test/test_generators.py produce solutions for the N-Queens problem (placing $N$ queens on an $NxN$ chess board so that no queen threatens another) and the Knight’s Tour (a route that takes a knight to every square of an $NxN$ chessboard without visiting any square twice).

The idea of generators comes from other programming languages, especially Icon (https://www.cs.arizona.edu/icon/), where the idea of generators is central. In Icon, every expression and function call behaves like a generator. One example from « An Overview of the Icon Programming Language » at https://www.cs.arizona.edu/icon/docs/ipd266.htm gives an idea of what this looks like:

sentence := "Store it in the neighboring harbor"
if (i := find("or", sentence)) > 5 then write(i)

In Icon the find() function returns the indexes at which the substring « or » is found: 3, 23, 33. In the if statement, i is first assigned a value of 3, but 3 is less than 5, so the comparison fails, and Icon retries it with the second value of 23. 23 is greater than 5, so the comparison now succeeds, and the code prints the value 23 to the screen.

Python doesn’t go nearly as far as Icon in adopting generators as a central concept. Generators are considered part of the core Python language, but learning or using them isn’t compulsory; if they don’t solve any problems that you have, feel free to ignore them. One novel feature of Python’s interface as compared to Icon’s is that a generator’s state is represented as a concrete object (the iterator) that can be passed around to other functions or stored in a data structure.

Voir aussi

PEP 255 [https://www.python.org/dev/peps/pep-0255]: Générateurs simples

Written by Neil Schemenauer, Tim Peters, Magnus Lie Hetland. Implemented mostly by Neil Schemenauer and Tim Peters, with other fixes from the Python Labs crew.

PEP 263: Source Code Encodings

Python source files can now be declared as being in different character set encodings. Encodings are declared by including a specially formatted comment in the first or second line of the source file. For example, a UTF-8 file can be declared with:

#!/usr/bin/env python
# -*- coding: UTF-8 -*-

Without such an encoding declaration, the default encoding used is 7-bit ASCII. Executing or importing modules that contain string literals with 8-bit characters and have no encoding declaration will result in a DeprecationWarning being signalled by Python 2.3; in 2.4 this will be a syntax error.

The encoding declaration only affects Unicode string literals, which will be converted to Unicode using the specified encoding. Note that Python identifiers are still restricted to ASCII characters, so you can’t have variable names that use characters outside of the usual alphanumerics.

Voir aussi

PEP 263 [https://www.python.org/dev/peps/pep-0263] - Defining Python Source Code Encodings

Written by Marc-André Lemburg and Martin von Löwis; implemented by Suzuki Hisao and Martin von Löwis.

PEP 273: Importing Modules from ZIP Archives

The new zipimport module adds support for importing modules from a ZIP-format archive. You don’t need to import the module explicitly; it will be automatically imported if a ZIP archive’s filename is added to sys.path. For example:

amk@nyman:~/src/python$ unzip -l /tmp/example.zip
Archive:  /tmp/example.zip
  Length     Date   Time    Name
 --------    ----   ----    ----
     8467  11-26-02 22:30   jwzthreading.py
 --------                   -------
     8467                   1 file
amk@nyman:~/src/python$ ./python
Python 2.3 (#1, Aug 1 2003, 19:54:32)
>>> import sys
>>> sys.path.insert(0, '/tmp/example.zip')  # Add .zip file to front of path
>>> import jwzthreading
>>> jwzthreading.__file__
'/tmp/example.zip/jwzthreading.py'
>>>

An entry in sys.path can now be the filename of a ZIP archive. The ZIP archive can contain any kind of files, but only files named *.py, *.pyc, or *.pyo can be imported. If an archive only contains *.py files, Python will not attempt to modify the archive by adding the corresponding *.pyc file, meaning that if a ZIP archive doesn’t contain *.pyc files, importing may be rather slow.

A path within the archive can also be specified to only import from a subdirectory; for example, the path /tmp/example.zip/lib/ would only import from the lib/ subdirectory within the archive.

Voir aussi

PEP 273 [https://www.python.org/dev/peps/pep-0273] - Import Modules from Zip Archives

Written by James C. Ahlstrom, who also provided an implementation. Python 2.3 follows the specification in PEP 273 [https://www.python.org/dev/peps/pep-0273], but uses an implementation written by Just van Rossum that uses the import hooks described in PEP 302 [https://www.python.org/dev/peps/pep-0302]. See section PEP 302: New Import Hooks for a description of the new import hooks.

PEP 277: Unicode file name support for Windows NT

On Windows NT, 2000, and XP, the system stores file names as Unicode strings. Traditionally, Python has represented file names as byte strings, which is inadequate because it renders some file names inaccessible.

Python now allows using arbitrary Unicode strings (within the limitations of the file system) for all functions that expect file names, most notably the open() built-in function. If a Unicode string is passed to os.listdir(), Python now returns a list of Unicode strings. A new function, os.getcwdu(), returns the current directory as a Unicode string.

Byte strings still work as file names, and on Windows Python will transparently convert them to Unicode using the mbcs encoding.

Other systems also allow Unicode strings as file names but convert them to byte strings before passing them to the system, which can cause a UnicodeError to be raised. Applications can test whether arbitrary Unicode strings are supported as file names by checking os.path.supports_unicode_filenames, a Boolean value.

Under MacOS, os.listdir() may now return Unicode filenames.

Voir aussi

PEP 277 [https://www.python.org/dev/peps/pep-0277] - Unicode file name support for Windows NT

Written by Neil Hodgson; implemented by Neil Hodgson, Martin von Löwis, and Mark Hammond.

PEP 278: Universal Newline Support

The three major operating systems used today are Microsoft Windows, Apple’s Macintosh OS, and the various Unix derivatives. A minor irritation of cross-platform work is that these three platforms all use different characters to mark the ends of lines in text files. Unix uses the linefeed (ASCII character 10), MacOS uses the carriage return (ASCII character 13), and Windows uses a two-character sequence of a carriage return plus a newline.

Python’s file objects can now support end of line conventions other than the one followed by the platform on which Python is running. Opening a file with the mode 'U' or 'rU' will open a file for reading in universal newlines mode. All three line ending conventions will be translated to a '\n' in the strings returned by the various file methods such as read() and readline().

Universal newline support is also used when importing modules and when executing a file with the execfile() function. This means that Python modules can be shared between all three operating systems without needing to convert the line-endings.

This feature can be disabled when compiling Python by specifying the --without-universal-newlines switch when running Python’s configure script.

Voir aussi

PEP 278 [https://www.python.org/dev/peps/pep-0278] - Universal Newline Support

Written and implemented by Jack Jansen.

PEP 279: enumerate()

A new built-in function, enumerate(), will make certain loops a bit clearer. enumerate(thing), where thing is either an iterator or a sequence, returns an iterator that will return (0, thing[0]), (1, thing[1]), (2, thing[2]), and so forth.

A common idiom to change every element of a list looks like this:

for i in range(len(L)):
    item = L[i]
    # ... compute some result based on item ...
    L[i] = result

This can be rewritten using enumerate() as:

for i, item in enumerate(L):
    # ... compute some result based on item ...
    L[i] = result

Voir aussi

PEP 279 [https://www.python.org/dev/peps/pep-0279] - The enumerate() built-in function

Written and implemented by Raymond D. Hettinger.

PEP 282: The logging Package

A standard package for writing logs, logging, has been added to Python 2.3. It provides a powerful and flexible mechanism for generating logging output which can then be filtered and processed in various ways. A configuration file written in a standard format can be used to control the logging behavior of a program. Python includes handlers that will write log records to standard error or to a file or socket, send them to the system log, or even e-mail them to a particular address; of course, it’s also possible to write your own handler classes.

The Logger class is the primary class. Most application code will deal with one or more Logger objects, each one used by a particular subsystem of the application. Each Logger is identified by a name, and names are organized into a hierarchy using . as the component separator. For example, you might have Logger instances named server, server.auth and server.network. The latter two instances are below server in the hierarchy. This means that if you turn up the verbosity for server or direct server messages to a different handler, the changes will also apply to records logged to server.auth and server.network. There’s also a root Logger that’s the parent of all other loggers.

For simple uses, the logging package contains some convenience functions that always use the root log:

import logging

logging.debug('Debugging information')
logging.info('Informational message')
logging.warning('Warning:config file %s not found', 'server.conf')
logging.error('Error occurred')
logging.critical('Critical error -- shutting down')

Ceci produit l’affichage suivant :

WARNING:root:Warning:config file server.conf not found
ERROR:root:Error occurred
CRITICAL:root:Critical error -- shutting down

In the default configuration, informational and debugging messages are suppressed and the output is sent to standard error. You can enable the display of informational and debugging messages by calling the setLevel() method on the root logger.

Notice the warning() call’s use of string formatting operators; all of the functions for logging messages take the arguments (msg, arg1, arg2, ...) and log the string resulting from msg % (arg1, arg2, ...).

There’s also an exception() function that records the most recent traceback. Any of the other functions will also record the traceback if you specify a true value for the keyword argument exc_info.

def f():
    try:    1/0
    except: logging.exception('Problem recorded')

f()

Ceci produit l’affichage suivant :

ERROR:root:Problem recorded
Traceback (most recent call last):
  File "t.py", line 6, in f
    1/0
ZeroDivisionError: integer division or modulo by zero

Slightly more advanced programs will use a logger other than the root logger. The getLogger(name) function is used to get a particular log, creating it if it doesn’t exist yet. getLogger(None) returns the root logger.

log = logging.getLogger('server')
 ...
log.info('Listening on port %i', port)
 ...
log.critical('Disk full')
 ...

Log records are usually propagated up the hierarchy, so a message logged to server.auth is also seen by server and root, but a Logger can prevent this by setting its propagate attribute to False.

There are more classes provided by the logging package that can be customized. When a Logger instance is told to log a message, it creates a LogRecord instance that is sent to any number of different Handler instances. Loggers and handlers can also have an attached list of filters, and each filter can cause the LogRecord to be ignored or can modify the record before passing it along. When they’re finally output, LogRecord instances are converted to text by a Formatter class. All of these classes can be replaced by your own specially-written classes.

With all of these features the logging package should provide enough flexibility for even the most complicated applications. This is only an incomplete overview of its features, so please see the package’s reference documentation for all of the details. Reading PEP 282 [https://www.python.org/dev/peps/pep-0282] will also be helpful.

Voir aussi

PEP 282 [https://www.python.org/dev/peps/pep-0282] - A Logging System

Written by Vinay Sajip and Trent Mick; implemented by Vinay Sajip.

PEP 285 : Un type booléen

A Boolean type was added to Python 2.3. Two new constants were added to the __builtin__ module, True and False. (True and False constants were added to the built-ins in Python 2.2.1, but the 2.2.1 versions are simply set to integer values of 1 and 0 and aren’t a different type.)

The type object for this new type is named bool; the constructor for it takes any Python value and converts it to True or False.

>>> bool(1)
True
>>> bool(0)
False
>>> bool([])
False
>>> bool( (1,) )
True

Most of the standard library modules and built-in functions have been changed to return Booleans.

>>> obj = []
>>> hasattr(obj, 'append')
True
>>> isinstance(obj, list)
True
>>> isinstance(obj, tuple)
False

Python’s Booleans were added with the primary goal of making code clearer. For example, if you’re reading a function and encounter the statement return 1, you might wonder whether the 1 represents a Boolean truth value, an index, or a coefficient that multiplies some other quantity. If the statement is return True, however, the meaning of the return value is quite clear.

Python’s Booleans were not added for the sake of strict type-checking. A very strict language such as Pascal would also prevent you performing arithmetic with Booleans, and would require that the expression in an if statement always evaluate to a Boolean result. Python is not this strict and never will be, as PEP 285 [https://www.python.org/dev/peps/pep-0285] explicitly says. This means you can still use any expression in an if statement, even ones that evaluate to a list or tuple or some random object. The Boolean type is a subclass of the int class so that arithmetic using a Boolean still works.

>>> True + 1
2
>>> False + 1
1
>>> False * 75
0
>>> True * 75
75

To sum up True and False in a sentence: they’re alternative ways to spell the integer values 1 and 0, with the single difference that str() and repr() return the strings 'True' and 'False' instead of '1' and '0'.

Voir aussi

PEP 285 [https://www.python.org/dev/peps/pep-0285] – Ajout d’un type bool

Written and implemented by GvR.

PEP 293: Codec Error Handling Callbacks

When encoding a Unicode string into a byte string, unencodable characters may be encountered. So far, Python has allowed specifying the error processing as either « strict » (raising UnicodeError), « ignore » (skipping the character), or « replace » (using a question mark in the output string), with « strict » being the default behavior. It may be desirable to specify alternative processing of such errors, such as inserting an XML character reference or HTML entity reference into the converted string.

Python now has a flexible framework to add different processing strategies. New error handlers can be added with codecs.register_error(), and codecs then can access the error handler with codecs.lookup_error(). An equivalent C API has been added for codecs written in C. The error handler gets the necessary state information such as the string being converted, the position in the string where the error was detected, and the target encoding. The handler can then either raise an exception or return a replacement string.

Two additional error handlers have been implemented using this framework: « backslashreplace » uses Python backslash quoting to represent unencodable characters and « xmlcharrefreplace » emits XML character references.

Voir aussi

PEP 293 [https://www.python.org/dev/peps/pep-0293] - Codec Error Handling Callbacks

Written and implemented by Walter Dörwald.

PEP 301: Package Index and Metadata for Distutils

Support for the long-requested Python catalog makes its first appearance in 2.3.

The heart of the catalog is the new Distutils register command. Running python setup.py register will collect the metadata describing a package, such as its name, version, maintainer, description, &c., and send it to a central catalog server. The resulting catalog is available from https://pypi.org.

To make the catalog a bit more useful, a new optional classifiers keyword argument has been added to the Distutils setup() function. A list of Trove [http://catb.org/~esr/trove/]-style strings can be supplied to help classify the software.

Here’s an example setup.py with classifiers, written to be compatible with older versions of the Distutils:

from distutils import core
kw = {'name': "Quixote",
      'version': "0.5.1",
      'description': "A highly Pythonic Web application framework",
      # ...
      }

if (hasattr(core, 'setup_keywords') and
    'classifiers' in core.setup_keywords):
    kw['classifiers'] = \
        ['Topic :: Internet :: WWW/HTTP :: Dynamic Content',
         'Environment :: No Input/Output (Daemon)',
         'Intended Audience :: Developers'],

core.setup(**kw)

The full list of classifiers can be obtained by running python setup.py register --list-classifiers.

Voir aussi

PEP 301 [https://www.python.org/dev/peps/pep-0301] - Package Index and Metadata for Distutils

Written and implemented by Richard Jones.

PEP 302: New Import Hooks

While it’s been possible to write custom import hooks ever since the ihooks module was introduced in Python 1.3, no one has ever been really happy with it because writing new import hooks is difficult and messy. There have been various proposed alternatives such as the imputil and iu modules, but none of them has ever gained much acceptance, and none of them were easily usable from C code.

PEP 302 [https://www.python.org/dev/peps/pep-0302] borrows ideas from its predecessors, especially from Gordon McMillan’s iu module. Three new items are added to the sys module:

sys.path_hooks is a list of callable objects; most often they’ll be classes. Each callable takes a string containing a path and either returns an importer object that will handle imports from this path or raises an ImportError exception if it can’t handle this path.

sys.path_importer_cache caches importer objects for each path, so sys.path_hooks will only need to be traversed once for each path.

sys.meta_path is a list of importer objects that will be traversed before sys.path is checked. This list is initially empty, but user code can add objects to it. Additional built-in and frozen modules can be imported by an object added to this list.

Importer objects must have a single method, find_module(fullname, path=None). fullname will be a module or package name, e.g. string or distutils.core. find_module() must return a loader object that has a single method, load_module(fullname), that creates and returns the corresponding module object.

Pseudo-code for Python’s new import logic, therefore, looks something like this (simplified a bit; see PEP 302 [https://www.python.org/dev/peps/pep-0302] for the full details):

for mp in sys.meta_path:
    loader = mp(fullname)
    if loader is not None:
        <module> = loader.load_module(fullname)

for path in sys.path:
    for hook in sys.path_hooks:
        try:
            importer = hook(path)
        except ImportError:
            # ImportError, so try the other path hooks
            pass
        else:
            loader = importer.find_module(fullname)
            <module> = loader.load_module(fullname)

# Not found!
raise ImportError

Voir aussi

PEP 302 [https://www.python.org/dev/peps/pep-0302] — Nouveaux crochets d’importation

Written by Just van Rossum and Paul Moore. Implemented by Just van Rossum.

PEP 305: Comma-separated Files

Comma-separated files are a format frequently used for exporting data from databases and spreadsheets. Python 2.3 adds a parser for comma-separated files.

Comma-separated format is deceptively simple at first glance:

Costs,150,200,3.95

Read a line and call line.split(','): what could be simpler? But toss in string data that can contain commas, and things get more complicated:

"Costs",150,200,3.95,"Includes taxes, shipping, and sundry items"

A big ugly regular expression can parse this, but using the new csv package is much simpler:

import csv

input = open('datafile', 'rb')
reader = csv.reader(input)
for line in reader:
    print line

The reader() function takes a number of different options. The field separator isn’t limited to the comma and can be changed to any character, and so can the quoting and line-ending characters.

Different dialects of comma-separated files can be defined and registered; currently there are two dialects, both used by Microsoft Excel. A separate csv.writer class will generate comma-separated files from a succession of tuples or lists, quoting strings that contain the delimiter.

Voir aussi

PEP 305 [https://www.python.org/dev/peps/pep-0305] – Interface des fichiers CSV

Written and implemented by Kevin Altis, Dave Cole, Andrew McNamara, Skip Montanaro, Cliff Wells.

PEP 307: Pickle Enhancements

The pickle and cPickle modules received some attention during the 2.3 development cycle. In 2.2, new-style classes could be pickled without difficulty, but they weren’t pickled very compactly; PEP 307 [https://www.python.org/dev/peps/pep-0307] quotes a trivial example where a new-style class results in a pickled string three times longer than that for a classic class.

The solution was to invent a new pickle protocol. The pickle.dumps() function has supported a text-or-binary flag for a long time. In 2.3, this flag is redefined from a Boolean to an integer: 0 is the old text-mode pickle format, 1 is the old binary format, and now 2 is a new 2.3-specific format. A new constant, pickle.HIGHEST_PROTOCOL, can be used to select the fanciest protocol available.

Unpickling is no longer considered a safe operation. 2.2’s pickle provided hooks for trying to prevent unsafe classes from being unpickled (specifically, a __safe_for_unpickling__ attribute), but none of this code was ever audited and therefore it’s all been ripped out in 2.3. You should not unpickle untrusted data in any version of Python.

To reduce the pickling overhead for new-style classes, a new interface for customizing pickling was added using three special methods: __getstate__(), __setstate__(), and __getnewargs__(). Consult PEP 307 [https://www.python.org/dev/peps/pep-0307] for the full semantics of these methods.

As a way to compress pickles yet further, it’s now possible to use integer codes instead of long strings to identify pickled classes. The Python Software Foundation will maintain a list of standardized codes; there’s also a range of codes for private use. Currently no codes have been specified.

Voir aussi

PEP 307 [https://www.python.org/dev/peps/pep-0307] - Extensions to the pickle protocol

Written and implemented by Guido van Rossum and Tim Peters.

Extended Slices

Ever since Python 1.4, the slicing syntax has supported an optional third « step » or « stride » argument. For example, these are all legal Python syntax: L[1:10:2], L[:-1:1], L[::-1]. This was added to Python at the request of the developers of Numerical Python, which uses the third argument extensively. However, Python’s built-in list, tuple, and string sequence types have never supported this feature, raising a TypeError if you tried it. Michael Hudson contributed a patch to fix this shortcoming.

For example, you can now easily extract the elements of a list that have even indexes:

>>> L = range(10)
>>> L[::2]
[0, 2, 4, 6, 8]

Negative values also work to make a copy of the same list in reverse order:

>>> L[::-1]
[9, 8, 7, 6, 5, 4, 3, 2, 1, 0]

This also works for tuples, arrays, and strings:

>>> s='abcd'
>>> s[::2]
'ac'
>>> s[::-1]
'dcba'

If you have a mutable sequence such as a list or an array you can assign to or delete an extended slice, but there are some differences between assignment to extended and regular slices. Assignment to a regular slice can be used to change the length of the sequence:

>>> a = range(3)
>>> a
[0, 1, 2]
>>> a[1:3] = [4, 5, 6]
>>> a
[0, 4, 5, 6]

Extended slices aren’t this flexible. When assigning to an extended slice, the list on the right hand side of the statement must contain the same number of items as the slice it is replacing:

>>> a = range(4)
>>> a
[0, 1, 2, 3]
>>> a[::2]
[0, 2]
>>> a[::2] = [0, -1]
>>> a
[0, 1, -1, 3]
>>> a[::2] = [0,1,2]
Traceback (most recent call last):
  File "<stdin>", line 1, in ?
ValueError: attempt to assign sequence of size 3 to extended slice of size 2

Deletion is more straightforward:

>>> a = range(4)
>>> a
[0, 1, 2, 3]
>>> a[::2]
[0, 2]
>>> del a[::2]
>>> a
[1, 3]

One can also now pass slice objects to the __getitem__() methods of the built-in sequences:

>>> range(10).__getitem__(slice(0, 5, 2))
[0, 2, 4]

Or use slice objects directly in subscripts:

>>> range(10)[slice(0, 5, 2)]
[0, 2, 4]

To simplify implementing sequences that support extended slicing, slice objects now have a method indices(length) which, given the length of a sequence, returns a (start, stop, step) tuple that can be passed directly to range(). indices() handles omitted and out-of-bounds indices in a manner consistent with regular slices (and this innocuous phrase hides a welter of confusing details!). The method is intended to be used like this:

class FakeSeq:
    ...
    def calc_item(self, i):
        ...
    def __getitem__(self, item):
        if isinstance(item, slice):
            indices = item.indices(len(self))
            return FakeSeq([self.calc_item(i) for i in range(*indices)])
        else:
            return self.calc_item(i)

From this example you can also see that the built-in slice object is now the type object for the slice type, and is no longer a function. This is consistent with Python 2.2, where int, str, etc., underwent the same change.

Other Language Changes

Here are all of the changes that Python 2.3 makes to the core Python language.

The yield statement is now always a keyword, as described in section PEP 255 : Générateurs simples of this document.

A new built-in function enumerate() was added, as described in section PEP 279: enumerate() of this document.

Two new constants, True and False were added along with the built-in bool type, as described in section PEP 285 : Un type booléen of this document.

The int() type constructor will now return a long integer instead of raising an OverflowError when a string or floating-point number is too large to fit into an integer. This can lead to the paradoxical result that isinstance(int(expression), int) is false, but that seems unlikely to cause problems in practice.

Built-in types now support the extended slicing syntax, as described in section Extended Slices of this document.

A new built-in function, sum(iterable, start=0), adds up the numeric items in the iterable object and returns their sum. sum() only accepts numbers, meaning that you can’t use it to concatenate a bunch of strings. (Contributed by Alex Martelli.)

list.insert(pos, value) used to insert value at the front of the list when pos was negative. The behaviour has now been changed to be consistent with slice indexing, so when pos is -1 the value will be inserted before the last element, and so forth.

list.index(value), which searches for value within the list and returns its index, now takes optional start and stop arguments to limit the search to only part of the list.

Dictionaries have a new method, pop(key[, *default*]), that returns the value corresponding to key and removes that key/value pair from the dictionary. If the requested key isn’t present in the dictionary, default is returned if it’s specified and KeyError raised if it isn’t.

>>> d = {1:2}
>>> d
{1: 2}
>>> d.pop(4)
Traceback (most recent call last):
  File "stdin", line 1, in ?
KeyError: 4
>>> d.pop(1)
2
>>> d.pop(1)
Traceback (most recent call last):
  File "stdin", line 1, in ?
KeyError: 'pop(): dictionary is empty'
>>> d
{}
>>>

There’s also a new class method, dict.fromkeys(iterable, value), that creates a dictionary with keys taken from the supplied iterator iterable and all values set to value, defaulting to None.

(Patches contributed by Raymond Hettinger.)

Also, the dict() constructor now accepts keyword arguments to simplify creating small dictionaries:

>>> dict(red=1, blue=2, green=3, black=4)
{'blue': 2, 'black': 4, 'green': 3, 'red': 1}

(Contributed by Just van Rossum.)

The assert statement no longer checks the __debug__ flag, so you can no longer disable assertions by assigning to __debug__. Running Python with the -O switch will still generate code that doesn’t execute any assertions.

Most type objects are now callable, so you can use them to create new objects such as functions, classes, and modules. (This means that the new module can be deprecated in a future Python version, because you can now use the type objects available in the types module.) For example, you can create a new module object with the following code:

>>> import types
>>> m = types.ModuleType('abc','docstring')
>>> m
<module 'abc' (built-in)>
>>> m.__doc__
'docstring'

A new warning, PendingDeprecationWarning was added to indicate features which are in the process of being deprecated. The warning will not be printed by default. To check for use of features that will be deprecated in the future, supply -Walways::PendingDeprecationWarning:: on the command line or use warnings.filterwarnings().

The process of deprecating string-based exceptions, as in raise "Error occurred", has begun. Raising a string will now trigger PendingDeprecationWarning.

Using None as a variable name will now result in a SyntaxWarning warning. In a future version of Python, None may finally become a keyword.

The xreadlines() method of file objects, introduced in Python 2.1, is no longer necessary because files now behave as their own iterator. xreadlines() was originally introduced as a faster way to loop over all the lines in a file, but now you can simply write for line in file_obj. File objects also have a new read-only encoding attribute that gives the encoding used by the file; Unicode strings written to the file will be automatically converted to bytes using the given encoding.

The method resolution order used by new-style classes has changed, though you’ll only notice the difference if you have a really complicated inheritance hierarchy. Classic classes are unaffected by this change. Python 2.2 originally used a topological sort of a class’s ancestors, but 2.3 now uses the C3 algorithm as described in the paper « A Monotonic Superclass Linearization for Dylan » [http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.19.3910]. To understand the motivation for this change, read Michele Simionato’s article « Python 2.3 Method Resolution Order » [http://www.phyast.pitt.edu/~micheles/mro.html], or read the thread on python-dev starting with the message at https://mail.python.org/pipermail/python-dev/2002-October/029035.html. Samuele Pedroni first pointed out the problem and also implemented the fix by coding the C3 algorithm.

Python runs multithreaded programs by switching between threads after executing N bytecodes. The default value for N has been increased from 10 to 100 bytecodes, speeding up single-threaded applications by reducing the switching overhead. Some multithreaded applications may suffer slower response time, but that’s easily fixed by setting the limit back to a lower number using sys.setcheckinterval(N). The limit can be retrieved with the new sys.getcheckinterval() function.

One minor but far-reaching change is that the names of extension types defined by the modules included with Python now contain the module and a '.' in front of the type name. For example, in Python 2.2, if you created a socket and printed its __class__, you’d get this output:

>>> s = socket.socket()
>>> s.__class__
<type 'socket'>

In 2.3, you get this:

>>> s.__class__
<type '_socket.socket'>

One of the noted incompatibilities between old- and new-style classes has been removed: you can now assign to the __name__ and __bases__ attributes of new-style classes. There are some restrictions on what can be assigned to __bases__ along the lines of those relating to assigning to an instance’s __class__ attribute.

String Changes

The in operator now works differently for strings. Previously, when evaluating X in Y where X and Y are strings, X could only be a single character. That’s now changed; X can be a string of any length, and X in Y will return True if X is a substring of Y. If X is the empty string, the result is always True.

>>> 'ab' in 'abcd'
True
>>> 'ad' in 'abcd'
False
>>> '' in 'abcd'
True

Note that this doesn’t tell you where the substring starts; if you need that information, use the find() string method.

The strip(), lstrip(), and rstrip() string methods now have an optional argument for specifying the characters to strip. The default is still to remove all whitespace characters:

>>> '   abc '.strip()
'abc'
>>> '><><abc<><><>'.strip('<>')
'abc'
>>> '><><abc<><><>\n'.strip('<>')
'abc<><><>\n'
>>> u'\u4000\u4001abc\u4000'.strip(u'\u4000')
u'\u4001abc'
>>>

(Suggested by Simon Brunning and implemented by Walter Dörwald.)

The startswith() and endswith() string methods now accept negative numbers for the start and end parameters.

Another new string method is zfill(), originally a function in the string module. zfill() pads a numeric string with zeros on the left until it’s the specified width. Note that the % operator is still more flexible and powerful than zfill().

>>> '45'.zfill(4)
'0045'
>>> '12345'.zfill(4)
'12345'
>>> 'goofy'.zfill(6)
'0goofy'

(Contributed by Walter Dörwald.)

A new type object, basestring, has been added. Both 8-bit strings and Unicode strings inherit from this type, so isinstance(obj, basestring) will return True for either kind of string. It’s a completely abstract type, so you can’t create basestring instances.

Interned strings are no longer immortal and will now be garbage-collected in the usual way when the only reference to them is from the internal dictionary of interned strings. (Implemented by Oren Tirosh.)

Optimizations

The creation of new-style class instances has been made much faster; they’re now faster than classic classes!

The sort() method of list objects has been extensively rewritten by Tim Peters, and the implementation is significantly faster.

Multiplication of large long integers is now much faster thanks to an implementation of Karatsuba multiplication, an algorithm that scales better than the O(n*n) required for the grade-school multiplication algorithm. (Original patch by Christopher A. Craig, and significantly reworked by Tim Peters.)

The SET_LINENO opcode is now gone. This may provide a small speed increase, depending on your compiler’s idiosyncrasies. See section Autres changements et corrections for a longer explanation. (Removed by Michael Hudson.)

xrange() objects now have their own iterator, making for i in xrange(n) slightly faster than for i in range(n). (Patch by Raymond Hettinger.)

A number of small rearrangements have been made in various hotspots to improve performance, such as inlining a function or removing some code. (Implemented mostly by GvR, but lots of people have contributed single changes.)

The net result of the 2.3 optimizations is that Python 2.3 runs the pystone benchmark around 25% faster than Python 2.2.

New, Improved, and Deprecated Modules

As usual, Python’s standard library received a number of enhancements and bug fixes. Here’s a partial list of the most notable changes, sorted alphabetically by module name. Consult the Misc/NEWS file in the source tree for a more complete list of changes, or look through the CVS logs for all the details.

The array module now supports arrays of Unicode characters using the 'u' format character. Arrays also now support using the += assignment operator to add another array’s contents, and the *= assignment operator to repeat an array. (Contributed by Jason Orendorff.)

The bsddb module has been replaced by version 4.1.6 of the PyBSDDB [http://pybsddb.sourceforge.net] package, providing a more complete interface to the transactional features of the BerkeleyDB library.

The old version of the module has been renamed to bsddb185 and is no longer built automatically; you’ll have to edit Modules/Setup to enable it. Note that the new bsddb package is intended to be compatible with the old module, so be sure to file bugs if you discover any incompatibilities. When upgrading to Python 2.3, if the new interpreter is compiled with a new version of the underlying BerkeleyDB library, you will almost certainly have to convert your database files to the new version. You can do this fairly easily with the new scripts db2pickle.py and pickle2db.py which you will find in the distribution’s Tools/scripts directory. If you’ve already been using the PyBSDDB package and importing it as bsddb3, you will have to change your import statements to import it as bsddb.

The new bz2 module is an interface to the bz2 data compression library. bz2-compressed data is usually smaller than corresponding zlib-compressed data. (Contributed by Gustavo Niemeyer.)

A set of standard date/time types has been added in the new datetime module. See the following section for more details.

The Distutils Extension class now supports an extra constructor argument named depends for listing additional source files that an extension depends on. This lets Distutils recompile the module if any of the dependency files are modified. For example, if sampmodule.c includes the header file sample.h, you would create the Extension object like this:

ext = Extension("samp",
                sources=["sampmodule.c"],
                depends=["sample.h"])

Modifying sample.h would then cause the module to be recompiled. (Contributed by Jeremy Hylton.)

Other minor changes to Distutils: it now checks for the CC, CFLAGS, CPP, LDFLAGS, and CPPFLAGS environment variables, using them to override the settings in Python’s configuration (contributed by Robert Weber).

Previously the doctest module would only search the docstrings of public methods and functions for test cases, but it now also examines private ones as well. The DocTestSuite() function creates a unittest.TestSuite object from a set of doctest tests.

The new gc.get_referents(object) function returns a list of all the objects referenced by object.

The getopt module gained a new function, gnu_getopt(), that supports the same arguments as the existing getopt() function but uses GNU-style scanning mode. The existing getopt() stops processing options as soon as a non-option argument is encountered, but in GNU-style mode processing continues, meaning that options and arguments can be mixed. For example:

>>> getopt.getopt(['-f', 'filename', 'output', '-v'], 'f:v')
([('-f', 'filename')], ['output', '-v'])
>>> getopt.gnu_getopt(['-f', 'filename', 'output', '-v'], 'f:v')
([('-f', 'filename'), ('-v', '')], ['output'])

(Contributed by Peter Åstrand.)

The grp, pwd, and resource modules now return enhanced tuples:

>>> import grp
>>> g = grp.getgrnam('amk')
>>> g.gr_name, g.gr_gid
('amk', 500)

The gzip module can now handle files exceeding 2 GiB.

The new heapq module contains an implementation of a heap queue algorithm. A heap is an array-like data structure that keeps items in a partially sorted order such that, for every index k, heap[k] <= heap[2*k+1] and heap[k] <= heap[2*k+2]. This makes it quick to remove the smallest item, and inserting a new item while maintaining the heap property is O(lg n). (See https://xlinux.nist.gov/dads//HTML/priorityque.html for more information about the priority queue data structure.)

The heapq module provides heappush() and heappop() functions for adding and removing items while maintaining the heap property on top of some other mutable Python sequence type. Here’s an example that uses a Python list:

>>> import heapq
>>> heap = []
>>> for item in [3, 7, 5, 11, 1]:
...    heapq.heappush(heap, item)
...
>>> heap
[1, 3, 5, 11, 7]
>>> heapq.heappop(heap)
1
>>> heapq.heappop(heap)
3
>>> heap
[5, 7, 11]

(Contributed by Kevin O’Connor.)

The IDLE integrated development environment has been updated using the code from the IDLEfork project (http://idlefork.sourceforge.net). The most notable feature is that the code being developed is now executed in a subprocess, meaning that there’s no longer any need for manual reload() operations. IDLE’s core code has been incorporated into the standard library as the idlelib package.

The imaplib module now supports IMAP over SSL. (Contributed by Piers Lauder and Tino Lange.)

The itertools contains a number of useful functions for use with iterators, inspired by various functions provided by the ML and Haskell languages. For example, itertools.ifilter(predicate, iterator) returns all elements in the iterator for which the function predicate() returns True, and itertools.repeat(obj, N) returns obj N times. There are a number of other functions in the module; see the package’s reference documentation for details. (Contributed by Raymond Hettinger.)

Two new functions in the math module, degrees(rads) and radians(degs), convert between radians and degrees. Other functions in the math module such as math.sin() and math.cos() have always required input values measured in radians. Also, an optional base argument was added to math.log() to make it easier to compute logarithms for bases other than e and 10. (Contributed by Raymond Hettinger.)

Several new POSIX functions (getpgid(), killpg(), lchown(), loadavg(), major(), makedev(), minor(), and mknod()) were added to the posix module that underlies the os module. (Contributed by Gustavo Niemeyer, Geert Jansen, and Denis S. Otkidach.)

In the os module, the *stat() family of functions can now report fractions of a second in a timestamp. Such time stamps are represented as floats, similar to the value returned by time.time().

During testing, it was found that some applications will break if time stamps are floats. For compatibility, when using the tuple interface of the stat_result time stamps will be represented as integers. When using named fields (a feature first introduced in Python 2.2), time stamps are still represented as integers, unless os.stat_float_times() is invoked to enable float return values:

>>> os.stat("/tmp").st_mtime
1034791200
>>> os.stat_float_times(True)
>>> os.stat("/tmp").st_mtime
1034791200.6335014

In Python 2.4, the default will change to always returning floats.

Application developers should enable this feature only if all their libraries work properly when confronted with floating point time stamps, or if they use the tuple API. If used, the feature should be activated on an application level instead of trying to enable it on a per-use basis.

The optparse module contains a new parser for command-line arguments that can convert option values to a particular Python type and will automatically generate a usage message. See the following section for more details.

The old and never-documented linuxaudiodev module has been deprecated, and a new version named ossaudiodev has been added. The module was renamed because the OSS sound drivers can be used on platforms other than Linux, and the interface has also been tidied and brought up to date in various ways. (Contributed by Greg Ward and Nicholas FitzRoy-Dale.)

The new platform module contains a number of functions that try to determine various properties of the platform you’re running on. There are functions for getting the architecture, CPU type, the Windows OS version, and even the Linux distribution version. (Contributed by Marc-André Lemburg.)

The parser objects provided by the pyexpat module can now optionally buffer character data, resulting in fewer calls to your character data handler and therefore faster performance. Setting the parser object’s buffer_text attribute to True will enable buffering.

The sample(population, k) function was added to the random module. population is a sequence or xrange object containing the elements of a population, and sample() chooses k elements from the population without replacing chosen elements. k can be any value up to len(population). For example:

>>> days = ['Mo', 'Tu', 'We', 'Th', 'Fr', 'St', 'Sn']
>>> random.sample(days, 3)      # Choose 3 elements
['St', 'Sn', 'Th']
>>> random.sample(days, 7)      # Choose 7 elements
['Tu', 'Th', 'Mo', 'We', 'St', 'Fr', 'Sn']
>>> random.sample(days, 7)      # Choose 7 again
['We', 'Mo', 'Sn', 'Fr', 'Tu', 'St', 'Th']
>>> random.sample(days, 8)      # Can't choose eight
Traceback (most recent call last):
  File "<stdin>", line 1, in ?
  File "random.py", line 414, in sample
      raise ValueError, "sample larger than population"
ValueError: sample larger than population
>>> random.sample(xrange(1,10000,2), 10)   # Choose ten odd nos. under 10000
[3407, 3805, 1505, 7023, 2401, 2267, 9733, 3151, 8083, 9195]

The random module now uses a new algorithm, the Mersenne Twister, implemented in C. It’s faster and more extensively studied than the previous algorithm.

(All changes contributed by Raymond Hettinger.)

The readline module also gained a number of new functions: get_history_item(), get_current_history_length(), and redisplay().

The rexec and Bastion modules have been declared dead, and attempts to import them will fail with a RuntimeError. New-style classes provide new ways to break out of the restricted execution environment provided by rexec, and no one has interest in fixing them or time to do so. If you have applications using rexec, rewrite them to use something else.

(Sticking with Python 2.2 or 2.1 will not make your applications any safer because there are known bugs in the rexec module in those versions. To repeat: if you’re using rexec, stop using it immediately.)

The rotor module has been deprecated because the algorithm it uses for encryption is not believed to be secure. If you need encryption, use one of the several AES Python modules that are available separately.

The shutil module gained a move(src, dest) function that recursively moves a file or directory to a new location.

Support for more advanced POSIX signal handling was added to the signal but then removed again as it proved impossible to make it work reliably across platforms.

The socket module now supports timeouts. You can call the settimeout(t) method on a socket object to set a timeout of t seconds. Subsequent socket operations that take longer than t seconds to complete will abort and raise a socket.timeout exception.

The original timeout implementation was by Tim O’Malley. Michael Gilfix integrated it into the Python socket module and shepherded it through a lengthy review. After the code was checked in, Guido van Rossum rewrote parts of it. (This is a good example of a collaborative development process in action.)

On Windows, the socket module now ships with Secure Sockets Layer (SSL) support.

The value of the C PYTHON_API_VERSION macro is now exposed at the Python level as sys.api_version. The current exception can be cleared by calling the new sys.exc_clear() function.

The new tarfile module allows reading from and writing to tar-format archive files. (Contributed by Lars Gustäbel.)

The new textwrap module contains functions for wrapping strings containing paragraphs of text. The wrap(text, width) function takes a string and returns a list containing the text split into lines of no more than the chosen width. The fill(text, width) function returns a single string, reformatted to fit into lines no longer than the chosen width. (As you can guess, fill() is built on top of wrap(). For example:

>>> import textwrap
>>> paragraph = "Not a whit, we defy augury: ... more text ..."
>>> textwrap.wrap(paragraph, 60)
["Not a whit, we defy augury: there's a special providence in",
 "the fall of a sparrow. If it be now, 'tis not to come; if it",
 ...]
>>> print textwrap.fill(paragraph, 35)
Not a whit, we defy augury: there's
a special providence in the fall of
a sparrow. If it be now, 'tis not
to come; if it be not to come, it
will be now; if it be not now, yet
it will come: the readiness is all.
>>>

The module also contains a TextWrapper class that actually implements the text wrapping strategy. Both the TextWrapper class and the wrap() and fill() functions support a number of additional keyword arguments for fine-tuning the formatting; consult the module’s documentation for details. (Contributed by Greg Ward.)

The thread and threading modules now have companion modules, dummy_thread and dummy_threading, that provide a do-nothing implementation of the thread module’s interface for platforms where threads are not supported. The intention is to simplify thread-aware modules (ones that don’t rely on threads to run) by putting the following code at the top:

try:
    import threading as _threading
except ImportError:
    import dummy_threading as _threading

In this example, _threading is used as the module name to make it clear that the module being used is not necessarily the actual threading module. Code can call functions and use classes in _threading whether or not threads are supported, avoiding an if statement and making the code slightly clearer. This module will not magically make multithreaded code run without threads; code that waits for another thread to return or to do something will simply hang forever.

The time module’s strptime() function has long been an annoyance because it uses the platform C library’s strptime() implementation, and different platforms sometimes have odd bugs. Brett Cannon contributed a portable implementation that’s written in pure Python and should behave identically on all platforms.

The new timeit module helps measure how long snippets of Python code take to execute. The timeit.py file can be run directly from the command line, or the module’s Timer class can be imported and used directly. Here’s a short example that figures out whether it’s faster to convert an 8-bit string to Unicode by appending an empty Unicode string to it or by using the unicode() function:

import timeit

timer1 = timeit.Timer('unicode("abc")')
timer2 = timeit.Timer('"abc" + u""')

# Run three trials
print timer1.repeat(repeat=3, number=100000)
print timer2.repeat(repeat=3, number=100000)

# On my laptop this outputs:
# [0.36831796169281006, 0.37441694736480713, 0.35304892063140869]
# [0.17574405670166016, 0.18193507194519043, 0.17565798759460449]

The Tix module has received various bug fixes and updates for the current version of the Tix package.

The Tkinter module now works with a thread-enabled version of Tcl. Tcl’s threading model requires that widgets only be accessed from the thread in which they’re created; accesses from another thread can cause Tcl to panic. For certain Tcl interfaces, Tkinter will now automatically avoid this when a widget is accessed from a different thread by marshalling a command, passing it to the correct thread, and waiting for the results. Other interfaces can’t be handled automatically but Tkinter will now raise an exception on such an access so that you can at least find out about the problem. See https://mail.python.org/pipermail/python-dev/2002-December/031107.html for a more detailed explanation of this change. (Implemented by Martin von Löwis.)

Calling Tcl methods through _tkinter no longer returns only strings. Instead, if Tcl returns other objects those objects are converted to their Python equivalent, if one exists, or wrapped with a _tkinter.Tcl_Obj object if no Python equivalent exists. This behavior can be controlled through the wantobjects() method of tkapp objects.

When using _tkinter through the Tkinter module (as most Tkinter applications will), this feature is always activated. It should not cause compatibility problems, since Tkinter would always convert string results to Python types where possible.

If any incompatibilities are found, the old behavior can be restored by setting the wantobjects variable in the Tkinter module to false before creating the first tkapp object.

import Tkinter
Tkinter.wantobjects = 0

Any breakage caused by this change should be reported as a bug.

The UserDict module has a new DictMixin class which defines all dictionary methods for classes that already have a minimum mapping interface. This greatly simplifies writing classes that need to be substitutable for dictionaries, such as the classes in the shelve module.

Adding the mix-in as a superclass provides the full dictionary interface whenever the class defines __getitem__(), __setitem__(), __delitem__(), and keys(). For example:

>>> import UserDict
>>> class SeqDict(UserDict.DictMixin):
...     """Dictionary lookalike implemented with lists."""
...     def __init__(self):
...         self.keylist = []
...         self.valuelist = []
...     def __getitem__(self, key):
...         try:
...             i = self.keylist.index(key)
...         except ValueError:
...             raise KeyError
...         return self.valuelist[i]
...     def __setitem__(self, key, value):
...         try:
...             i = self.keylist.index(key)
...             self.valuelist[i] = value
...         except ValueError:
...             self.keylist.append(key)
...             self.valuelist.append(value)
...     def __delitem__(self, key):
...         try:
...             i = self.keylist.index(key)
...         except ValueError:
...             raise KeyError
...         self.keylist.pop(i)
...         self.valuelist.pop(i)
...     def keys(self):
...         return list(self.keylist)
...
>>> s = SeqDict()
>>> dir(s)      # See that other dictionary methods are implemented
['__cmp__', '__contains__', '__delitem__', '__doc__', '__getitem__',
 '__init__', '__iter__', '__len__', '__module__', '__repr__',
 '__setitem__', 'clear', 'get', 'has_key', 'items', 'iteritems',
 'iterkeys', 'itervalues', 'keylist', 'keys', 'pop', 'popitem',
 'setdefault', 'update', 'valuelist', 'values']

(Contributed by Raymond Hettinger.)

The DOM implementation in xml.dom.minidom can now generate XML output in a particular encoding by providing an optional encoding argument to the toxml() and toprettyxml() methods of DOM nodes.

The xmlrpclib module now supports an XML-RPC extension for handling nil data values such as Python’s None. Nil values are always supported on unmarshalling an XML-RPC response. To generate requests containing None, you must supply a true value for the allow_none parameter when creating a Marshaller instance.

The new DocXMLRPCServer module allows writing self-documenting XML-RPC servers. Run it in demo mode (as a program) to see it in action. Pointing the Web browser to the RPC server produces pydoc-style documentation; pointing xmlrpclib to the server allows invoking the actual methods. (Contributed by Brian Quinlan.)

Support for internationalized domain names (RFCs 3454, 3490, 3491, and 3492) has been added. The « idna » encoding can be used to convert between a Unicode domain name and the ASCII-compatible encoding (ACE) of that name.

>{}>{}> u"www.Alliancefrançaise.nu".encode("idna")
'www.xn--alliancefranaise-npb.nu'

The socket module has also been extended to transparently convert Unicode hostnames to the ACE version before passing them to the C library. Modules that deal with hostnames such as httplib and ftplib) also support Unicode host names; httplib also sends HTTP Host headers using the ACE version of the domain name. urllib supports Unicode URLs with non-ASCII host names as long as the path part of the URL is ASCII only.

To implement this change, the stringprep module, the mkstringprep tool and the punycode encoding have been added.

Date/Time Type

Date and time types suitable for expressing timestamps were added as the datetime module. The types don’t support different calendars or many fancy features, and just stick to the basics of representing time.

The three primary types are: date, representing a day, month, and year; time, consisting of hour, minute, and second; and datetime, which contains all the attributes of both date and time. There’s also a timedelta class representing differences between two points in time, and time zone logic is implemented by classes inheriting from the abstract tzinfo class.

You can create instances of date and time by either supplying keyword arguments to the appropriate constructor, e.g. datetime.date(year=1972, month=10, day=15), or by using one of a number of class methods. For example, the date.today() class method returns the current local date.

Once created, instances of the date/time classes are all immutable. There are a number of methods for producing formatted strings from objects:

>>> import datetime
>>> now = datetime.datetime.now()
>>> now.isoformat()
'2002-12-30T21:27:03.994956'
>>> now.ctime()  # Only available on date, datetime
'Mon Dec 30 21:27:03 2002'
>>> now.strftime('%Y %d %b')
'2002 30 Dec'

The replace() method allows modifying one or more fields of a date or datetime instance, returning a new instance:

>>> d = datetime.datetime.now()
>>> d
datetime.datetime(2002, 12, 30, 22, 15, 38, 827738)
>>> d.replace(year=2001, hour = 12)
datetime.datetime(2001, 12, 30, 12, 15, 38, 827738)
>>>

Instances can be compared, hashed, and converted to strings (the result is the same as that of isoformat()). date and datetime instances can be subtracted from each other, and added to timedelta instances. The largest missing feature is that there’s no standard library support for parsing strings and getting back a date or datetime.

For more information, refer to the module’s reference documentation. (Contributed by Tim Peters.)

The optparse Module

The getopt module provides simple parsing of command-line arguments. The new optparse module (originally named Optik) provides more elaborate command-line parsing that follows the Unix conventions, automatically creates the output for --help, and can perform different actions for different options.

You start by creating an instance of OptionParser and telling it what your program’s options are.

import sys
from optparse import OptionParser

op = OptionParser()
op.add_option('-i', '--input',
              action='store', type='string', dest='input',
              help='set input filename')
op.add_option('-l', '--length',
              action='store', type='int', dest='length',
              help='set maximum length of output')

Parsing a command line is then done by calling the parse_args() method.

options, args = op.parse_args(sys.argv[1:])
print options
print args

This returns an object containing all of the option values, and a list of strings containing the remaining arguments.

Invoking the script with the various arguments now works as you’d expect it to. Note that the length argument is automatically converted to an integer.

$ ./python opt.py -i data arg1
<Values at 0x400cad4c: {'input': 'data', 'length': None}>
['arg1']
$ ./python opt.py --input=data --length=4
<Values at 0x400cad2c: {'input': 'data', 'length': 4}>
[]
$

The help message is automatically generated for you:

$ ./python opt.py --help
usage: opt.py [options]

options:
  -h, --help            show this help message and exit
  -iINPUT, --input=INPUT
                        set input filename
  -lLENGTH, --length=LENGTH
                        set maximum length of output
$

See the module’s documentation for more details.

Optik was written by Greg Ward, with suggestions from the readers of the Getopt SIG.

Pymalloc: A Specialized Object Allocator

Pymalloc, a specialized object allocator written by Vladimir Marangozov, was a feature added to Python 2.1. Pymalloc is intended to be faster than the system malloc() and to have less memory overhead for allocation patterns typical of Python programs. The allocator uses C’s malloc() function to get large pools of memory and then fulfills smaller memory requests from these pools.

In 2.1 and 2.2, pymalloc was an experimental feature and wasn’t enabled by default; you had to explicitly enable it when compiling Python by providing the --with-pymalloc option to the configure script. In 2.3, pymalloc has had further enhancements and is now enabled by default; you’ll have to supply --without-pymalloc to disable it.

This change is transparent to code written in Python; however, pymalloc may expose bugs in C extensions. Authors of C extension modules should test their code with pymalloc enabled, because some incorrect code may cause core dumps at runtime.

There’s one particularly common error that causes problems. There are a number of memory allocation functions in Python’s C API that have previously just been aliases for the C library’s malloc() and free(), meaning that if you accidentally called mismatched functions the error wouldn’t be noticeable. When the object allocator is enabled, these functions aren’t aliases of malloc() and free() any more, and calling the wrong function to free memory may get you a core dump. For example, if memory was allocated using PyObject_Malloc(), it has to be freed using PyObject_Free(), not free(). A few modules included with Python fell afoul of this and had to be fixed; doubtless there are more third-party modules that will have the same problem.

As part of this change, the confusing multiple interfaces for allocating memory have been consolidated down into two API families. Memory allocated with one family must not be manipulated with functions from the other family. There is one family for allocating chunks of memory and another family of functions specifically for allocating Python objects.

To allocate and free an undistinguished chunk of memory use the « raw memory » family: PyMem_Malloc(), PyMem_Realloc(), and PyMem_Free().

The « object memory » family is the interface to the pymalloc facility described above and is biased towards a large number of « small » allocations: PyObject_Malloc(), PyObject_Realloc(), and PyObject_Free().

To allocate and free Python objects, use the « object » family PyObject_New(), PyObject_NewVar(), and PyObject_Del().

Thanks to lots of work by Tim Peters, pymalloc in 2.3 also provides debugging features to catch memory overwrites and doubled frees in both extension modules and in the interpreter itself. To enable this support, compile a debugging version of the Python interpreter by running configure with --with-pydebug.

To aid extension writers, a header file Misc/pymemcompat.h is distributed with the source to Python 2.3 that allows Python extensions to use the 2.3 interfaces to memory allocation while compiling against any version of Python since 1.5.2. You would copy the file from Python’s source distribution and bundle it with the source of your extension.

Voir aussi

https://hg.python.org/cpython/file/default/Objects/obmalloc.c

For the full details of the pymalloc implementation, see the comments at the top of the file Objects/obmalloc.c in the Python source code. The above link points to the file within the python.org SVN browser.

Build and C API Changes

Changes to Python’s build process and to the C API include:

The cycle detection implementation used by the garbage collection has proven to be stable, so it’s now been made mandatory. You can no longer compile Python without it, and the --with-cycle-gc switch to configure has been removed.

Python can now optionally be built as a shared library (libpython2.3.so) by supplying --enable-shared when running Python’s configure script. (Contributed by Ondrej Palkovsky.)

The DL_EXPORT and DL_IMPORT macros are now deprecated. Initialization functions for Python extension modules should now be declared using the new macro PyMODINIT_FUNC, while the Python core will generally use the PyAPI_FUNC and PyAPI_DATA macros.

The interpreter can be compiled without any docstrings for the built-in functions and modules by supplying --without-doc-strings to the configure script. This makes the Python executable about 10% smaller, but will also mean that you can’t get help for Python’s built-ins. (Contributed by Gustavo Niemeyer.)

The PyArg_NoArgs() macro is now deprecated, and code that uses it should be changed. For Python 2.2 and later, the method definition table can specify the METH_NOARGS flag, signalling that there are no arguments, and the argument checking can then be removed. If compatibility with pre-2.2 versions of Python is important, the code could use PyArg_ParseTuple(args, "") instead, but this will be slower than using METH_NOARGS.

PyArg_ParseTuple() accepts new format characters for various sizes of unsigned integers: B for unsigned char, H for unsigned short int, I for unsigned int, and K for unsigned long long.

A new function, PyObject_DelItemString(mapping, char *key) was added as shorthand for PyObject_DelItem(mapping, PyString_New(key)).

File objects now manage their internal string buffer differently, increasing it exponentially when needed. This results in the benchmark tests in Lib/test/test_bufio.py speeding up considerably (from 57 seconds to 1.7 seconds, according to one measurement).

It’s now possible to define class and static methods for a C extension type by setting either the METH_CLASS or METH_STATIC flags in a method’s PyMethodDef structure.

Python now includes a copy of the Expat XML parser’s source code, removing any dependence on a system version or local installation of Expat.

If you dynamically allocate type objects in your extension, you should be aware of a change in the rules relating to the __module__ and __name__ attributes. In summary, you will want to ensure the type’s dictionary contains a '__module__' key; making the module name the part of the type name leading up to the final period will no longer have the desired effect. For more detail, read the API reference documentation or the source.

Port-Specific Changes

Support for a port to IBM’s OS/2 using the EMX runtime environment was merged into the main Python source tree. EMX is a POSIX emulation layer over the OS/2 system APIs. The Python port for EMX tries to support all the POSIX-like capability exposed by the EMX runtime, and mostly succeeds; fork() and fcntl() are restricted by the limitations of the underlying emulation layer. The standard OS/2 port, which uses IBM’s Visual Age compiler, also gained support for case-sensitive import semantics as part of the integration of the EMX port into CVS. (Contributed by Andrew MacIntyre.)

On MacOS, most toolbox modules have been weaklinked to improve backward compatibility. This means that modules will no longer fail to load if a single routine is missing on the current OS version. Instead calling the missing routine will raise an exception. (Contributed by Jack Jansen.)

The RPM spec files, found in the Misc/RPM/ directory in the Python source distribution, were updated for 2.3. (Contributed by Sean Reifschneider.)

Other new platforms now supported by Python include AtheOS (http://atheos.cx/), GNU/Hurd, and OpenVMS.

Autres changements et corrections

As usual, there were a bunch of other improvements and bugfixes scattered throughout the source tree. A search through the CVS change logs finds there were 523 patches applied and 514 bugs fixed between Python 2.2 and 2.3. Both figures are likely to be underestimates.

Some of the more notable changes are:

If the PYTHONINSPECT environment variable is set, the Python interpreter will enter the interactive prompt after running a Python program, as if Python had been invoked with the -i option. The environment variable can be set before running the Python interpreter, or it can be set by the Python program as part of its execution.

The regrtest.py script now provides a way to allow « all resources except foo. » A resource name passed to the -u option can now be prefixed with a hyphen ('-') to mean « remove this resource. » For example, the option “-uall,-bsddb” could be used to enable the use of all resources except bsddb.

The tools used to build the documentation now work under Cygwin as well as Unix.

The SET_LINENO opcode has been removed. Back in the mists of time, this opcode was needed to produce line numbers in tracebacks and support trace functions (for, e.g., pdb). Since Python 1.5, the line numbers in tracebacks have been computed using a different mechanism that works with « python -O ». For Python 2.3 Michael Hudson implemented a similar scheme to determine when to call the trace function, removing the need for SET_LINENO entirely.

It would be difficult to detect any resulting difference from Python code, apart from a slight speed up when Python is run without -O.

C extensions that access the f_lineno field of frame objects should instead call PyCode_Addr2Line(f->f_code, f->f_lasti). This will have the added effect of making the code work as desired under « python -O » in earlier versions of Python.

A nifty new feature is that trace functions can now assign to the f_lineno attribute of frame objects, changing the line that will be executed next. A jump command has been added to the pdb debugger taking advantage of this new feature. (Implemented by Richie Hindle.)

Portage vers Python 2.3

This section lists previously described changes that may require changes to your code:

yield is now always a keyword; if it’s used as a variable name in your code, a different name must be chosen.

For strings X and Y, X in Y now works if X is more than one character long.

The int() type constructor will now return a long integer instead of raising an OverflowError when a string or floating-point number is too large to fit into an integer.

If you have Unicode strings that contain 8-bit characters, you must declare the file’s encoding (UTF-8, Latin-1, or whatever) by adding a comment to the top of the file. See section PEP 263: Source Code Encodings for more information.

Calling Tcl methods through _tkinter no longer returns only strings. Instead, if Tcl returns other objects those objects are converted to their Python equivalent, if one exists, or wrapped with a _tkinter.Tcl_Obj object if no Python equivalent exists.

Large octal and hex literals such as 0xffffffff now trigger a FutureWarning. Currently they’re stored as 32-bit numbers and result in a negative value, but in Python 2.4 they’ll become positive long integers.

There are a few ways to fix this warning. If you really need a positive number, just add an L to the end of the literal. If you’re trying to get a 32-bit integer with low bits set and have previously used an expression such as ~(1 << 31), it’s probably clearest to start with all bits set and clear the desired upper bits. For example, to clear just the top bit (bit 31), you could write 0xffffffffL &~(1L<<31).

You can no longer disable assertions by assigning to __debug__.

The Distutils setup() function has gained various new keyword arguments such as depends. Old versions of the Distutils will abort if passed unknown keywords. A solution is to check for the presence of the new get_distutil_options() function in your setup.py and only uses the new keywords with a version of the Distutils that supports them:

from distutils import core

kw = {'sources': 'foo.c', ...}
if hasattr(core, 'get_distutil_options'):
    kw['depends'] = ['foo.h']
ext = Extension(**kw)

Using None as a variable name will now result in a SyntaxWarning warning.

Names of extension types defined by the modules included with Python now contain the module and a '.' in front of the type name.

Remerciements

The author would like to thank the following people for offering suggestions, corrections and assistance with various drafts of this article: Jeff Bauer, Simon Brunning, Brett Cannon, Michael Chermside, Andrew Dalke, Scott David Daniels, Fred L. Drake, Jr., David Fraser, Kelly Gerber, Raymond Hettinger, Michael Hudson, Chris Lambert, Detlef Lannert, Martin von Löwis, Andrew MacIntyre, Lalo Martins, Chad Netzer, Gustavo Niemeyer, Neal Norwitz, Hans Nowak, Chris Reedy, Francesco Ricciardi, Vinay Sajip, Neil Schemenauer, Roman Suzi, Jason Tishler, Just van Rossum.

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Nouveautés de Python 2.2

Auteur

A.M. Kuchling

Introduction

This article explains the new features in Python 2.2.2, released on October 14, 2002. Python 2.2.2 is a bugfix release of Python 2.2, originally released on December 21, 2001.

Python 2.2 can be thought of as the « cleanup release ». There are some features such as generators and iterators that are completely new, but most of the changes, significant and far-reaching though they may be, are aimed at cleaning up irregularities and dark corners of the language design.

This article doesn’t attempt to provide a complete specification of the new features, but instead provides a convenient overview. For full details, you should refer to the documentation for Python 2.2, such as the Python Library Reference [https://docs.python.org/2.2/lib/lib.html] and the Python Reference Manual [https://docs.python.org/2.2/ref/ref.html]. If you want to understand the complete implementation and design rationale for a change, refer to the PEP for a particular new feature.

PEP 252 et 253 : Changements concernant les types et classes

The largest and most far-reaching changes in Python 2.2 are to Python’s model of objects and classes. The changes should be backward compatible, so it’s likely that your code will continue to run unchanged, but the changes provide some amazing new capabilities. Before beginning this, the longest and most complicated section of this article, I’ll provide an overview of the changes and offer some comments.

A long time ago I wrote a Web page listing flaws in Python’s design. One of the most significant flaws was that it’s impossible to subclass Python types implemented in C. In particular, it’s not possible to subclass built-in types, so you can’t just subclass, say, lists in order to add a single useful method to them. The UserList module provides a class that supports all of the methods of lists and that can be subclassed further, but there’s lots of C code that expects a regular Python list and won’t accept a UserList instance.

Python 2.2 fixes this, and in the process adds some exciting new capabilities. A brief summary:

You can subclass built-in types such as lists and even integers, and your subclasses should work in every place that requires the original type.

It’s now possible to define static and class methods, in addition to the instance methods available in previous versions of Python.

It’s also possible to automatically call methods on accessing or setting an instance attribute by using a new mechanism called properties. Many uses of __getattr__() can be rewritten to use properties instead, making the resulting code simpler and faster. As a small side benefit, attributes can now have docstrings, too.

The list of legal attributes for an instance can be limited to a particular set using slots, making it possible to safeguard against typos and perhaps make more optimizations possible in future versions of Python.

Some users have voiced concern about all these changes. Sure, they say, the new features are neat and lend themselves to all sorts of tricks that weren’t possible in previous versions of Python, but they also make the language more complicated. Some people have said that they’ve always recommended Python for its simplicity, and feel that its simplicity is being lost.

Personally, I think there’s no need to worry. Many of the new features are quite esoteric, and you can write a lot of Python code without ever needed to be aware of them. Writing a simple class is no more difficult than it ever was, so you don’t need to bother learning or teaching them unless they’re actually needed. Some very complicated tasks that were previously only possible from C will now be possible in pure Python, and to my mind that’s all for the better.

I’m not going to attempt to cover every single corner case and small change that were required to make the new features work. Instead this section will paint only the broad strokes. See section Related Links, « Related Links », for further sources of information about Python 2.2’s new object model.

Anciennes et nouvelles classes

First, you should know that Python 2.2 really has two kinds of classes: classic or old-style classes, and new-style classes. The old-style class model is exactly the same as the class model in earlier versions of Python. All the new features described in this section apply only to new-style classes. This divergence isn’t intended to last forever; eventually old-style classes will be dropped, possibly in Python 3.0.

So how do you define a new-style class? You do it by subclassing an existing new-style class. Most of Python’s built-in types, such as integers, lists, dictionaries, and even files, are new-style classes now. A new-style class named object, the base class for all built-in types, has also been added so if no built-in type is suitable, you can just subclass object:

class C(object):
    def __init__ (self):
        ...
    ...

This means that class statements that don’t have any base classes are always classic classes in Python 2.2. (Actually you can also change this by setting a module-level variable named __metaclass__ — see PEP 253 [https://www.python.org/dev/peps/pep-0253] for the details — but it’s easier to just subclass object.)

The type objects for the built-in types are available as built-ins, named using a clever trick. Python has always had built-in functions named int(), float(), and str(). In 2.2, they aren’t functions any more, but type objects that behave as factories when called.

>>> int
<type 'int'>
>>> int('123')
123

To make the set of types complete, new type objects such as dict() and file() have been added. Here’s a more interesting example, adding a lock() method to file objects:

class LockableFile(file):
    def lock (self, operation, length=0, start=0, whence=0):
        import fcntl
        return fcntl.lockf(self.fileno(), operation,
                           length, start, whence)

The now-obsolete posixfile module contained a class that emulated all of a file object’s methods and also added a lock() method, but this class couldn’t be passed to internal functions that expected a built-in file, something which is possible with our new LockableFile.

Descripteurs

In previous versions of Python, there was no consistent way to discover what attributes and methods were supported by an object. There were some informal conventions, such as defining __members__ and __methods__ attributes that were lists of names, but often the author of an extension type or a class wouldn’t bother to define them. You could fall back on inspecting the __dict__ of an object, but when class inheritance or an arbitrary __getattr__() hook were in use this could still be inaccurate.

The one big idea underlying the new class model is that an API for describing the attributes of an object using descriptors has been formalized. Descriptors specify the value of an attribute, stating whether it’s a method or a field. With the descriptor API, static methods and class methods become possible, as well as more exotic constructs.

Attribute descriptors are objects that live inside class objects, and have a few attributes of their own:

__name__ is the attribute’s name.

__doc__ is the attribute’s docstring.

__get__(object) is a method that retrieves the attribute value from object.

__set__(object, value) sets the attribute on object to value.

__delete__(object, value) deletes the value attribute of object.

For example, when you write obj.x, the steps that Python actually performs are:

descriptor = obj.__class__.x
descriptor.__get__(obj)

For methods, descriptor.__get__() returns a temporary object that’s callable, and wraps up the instance and the method to be called on it. This is also why static methods and class methods are now possible; they have descriptors that wrap up just the method, or the method and the class. As a brief explanation of these new kinds of methods, static methods aren’t passed the instance, and therefore resemble regular functions. Class methods are passed the class of the object, but not the object itself. Static and class methods are defined like this:

class C(object):
    def f(arg1, arg2):
        ...
    f = staticmethod(f)

    def g(cls, arg1, arg2):
        ...
    g = classmethod(g)

The staticmethod() function takes the function f(), and returns it wrapped up in a descriptor so it can be stored in the class object. You might expect there to be special syntax for creating such methods (def static f, defstatic f(), or something like that) but no such syntax has been defined yet; that’s been left for future versions of Python.

More new features, such as slots and properties, are also implemented as new kinds of descriptors, and it’s not difficult to write a descriptor class that does something novel. For example, it would be possible to write a descriptor class that made it possible to write Eiffel-style preconditions and postconditions for a method. A class that used this feature might be defined like this:

from eiffel import eiffelmethod

class C(object):
    def f(self, arg1, arg2):
        # The actual function
        ...
    def pre_f(self):
        # Check preconditions
        ...
    def post_f(self):
        # Check postconditions
        ...

    f = eiffelmethod(f, pre_f, post_f)

Note that a person using the new eiffelmethod() doesn’t have to understand anything about descriptors. This is why I think the new features don’t increase the basic complexity of the language. There will be a few wizards who need to know about it in order to write eiffelmethod() or the ZODB or whatever, but most users will just write code on top of the resulting libraries and ignore the implementation details.

Héritage multiple : la règle du diamant

Multiple inheritance has also been made more useful through changing the rules under which names are resolved. Consider this set of classes (diagram taken from PEP 253 [https://www.python.org/dev/peps/pep-0253] by Guido van Rossum):

      class A:
        ^ ^  def save(self): ...
       /   \
      /     \
     /       \
    /         \
class B     class C:
    ^         ^  def save(self): ...
     \       /
      \     /
       \   /
        \ /
      class D

The lookup rule for classic classes is simple but not very smart; the base classes are searched depth-first, going from left to right. A reference to D.save() will search the classes D, B, and then A, where save() would be found and returned. C.save() would never be found at all. This is bad, because if C’s save() method is saving some internal state specific to C, not calling it will result in that state never getting saved.

New-style classes follow a different algorithm that’s a bit more complicated to explain, but does the right thing in this situation. (Note that Python 2.3 changes this algorithm to one that produces the same results in most cases, but produces more useful results for really complicated inheritance graphs.)

List all the base classes, following the classic lookup rule and include a class multiple times if it’s visited repeatedly. In the above example, the list of visited classes is [D, B, A, C, A].

Scan the list for duplicated classes. If any are found, remove all but one occurrence, leaving the last one in the list. In the above example, the list becomes [D, B, C, A] after dropping duplicates.

Following this rule, referring to D.save() will return C.save(), which is the behaviour we’re after. This lookup rule is the same as the one followed by Common Lisp. A new built-in function, super(), provides a way to get at a class’s superclasses without having to reimplement Python’s algorithm. The most commonly used form will be super(class, obj), which returns a bound superclass object (not the actual class object). This form will be used in methods to call a method in the superclass; for example, D’s save() method would look like this:

class D (B,C):
    def save (self):
        # Call superclass .save()
        super(D, self).save()
        # Save D's private information here
        ...

super() can also return unbound superclass objects when called as super(class) or super(class1, class2), but this probably won’t often be useful.

Attribute Access

A fair number of sophisticated Python classes define hooks for attribute access using __getattr__(); most commonly this is done for convenience, to make code more readable by automatically mapping an attribute access such as obj.parent into a method call such as obj.get_parent. Python 2.2 adds some new ways of controlling attribute access.

First, __getattr__(attr_name) is still supported by new-style classes, and nothing about it has changed. As before, it will be called when an attempt is made to access obj.foo and no attribute named foo is found in the instance’s dictionary.

New-style classes also support a new method, __getattribute__(attr_name). The difference between the two methods is that __getattribute__() is always called whenever any attribute is accessed, while the old __getattr__() is only called if foo isn’t found in the instance’s dictionary.

However, Python 2.2’s support for properties will often be a simpler way to trap attribute references. Writing a __getattr__() method is complicated because to avoid recursion you can’t use regular attribute accesses inside them, and instead have to mess around with the contents of __dict__. __getattr__() methods also end up being called by Python when it checks for other methods such as __repr__() or __coerce__(), and so have to be written with this in mind. Finally, calling a function on every attribute access results in a sizable performance loss.

property is a new built-in type that packages up three functions that get, set, or delete an attribute, and a docstring. For example, if you want to define a size attribute that’s computed, but also settable, you could write:

class C(object):
    def get_size (self):
        result = ... computation ...
        return result
    def set_size (self, size):
        ... compute something based on the size
        and set internal state appropriately ...

    # Define a property.  The 'delete this attribute'
    # method is defined as None, so the attribute
    # can't be deleted.
    size = property(get_size, set_size,
                    None,
                    "Storage size of this instance")

That is certainly clearer and easier to write than a pair of __getattr__()/__setattr__() methods that check for the size attribute and handle it specially while retrieving all other attributes from the instance’s __dict__. Accesses to size are also the only ones which have to perform the work of calling a function, so references to other attributes run at their usual speed.

Finally, it’s possible to constrain the list of attributes that can be referenced on an object using the new __slots__ class attribute. Python objects are usually very dynamic; at any time it’s possible to define a new attribute on an instance by just doing obj.new_attr=1. A new-style class can define a class attribute named __slots__ to limit the legal attributes to a particular set of names. An example will make this clear:

>>> class C(object):
...     __slots__ = ('template', 'name')
...
>>> obj = C()
>>> print obj.template
None
>>> obj.template = 'Test'
>>> print obj.template
Test
>>> obj.newattr = None
Traceback (most recent call last):
  File "<stdin>", line 1, in ?
AttributeError: 'C' object has no attribute 'newattr'

Note how you get an AttributeError on the attempt to assign to an attribute not listed in __slots__.

Related Links

This section has just been a quick overview of the new features, giving enough of an explanation to start you programming, but many details have been simplified or ignored. Where should you go to get a more complete picture?

https://docs.python.org/dev/howto/descriptor.html is a lengthy tutorial introduction to the descriptor features, written by Guido van Rossum. If my description has whetted your appetite, go read this tutorial next, because it goes into much more detail about the new features while still remaining quite easy to read.

Next, there are two relevant PEPs, PEP 252 [https://www.python.org/dev/peps/pep-0252] and PEP 253 [https://www.python.org/dev/peps/pep-0253]. PEP 252 [https://www.python.org/dev/peps/pep-0252] is titled « Making Types Look More Like Classes », and covers the descriptor API. PEP 253 [https://www.python.org/dev/peps/pep-0253] is titled « Subtyping Built-in Types », and describes the changes to type objects that make it possible to subtype built-in objects. PEP 253 [https://www.python.org/dev/peps/pep-0253] is the more complicated PEP of the two, and at a few points the necessary explanations of types and meta-types may cause your head to explode. Both PEPs were written and implemented by Guido van Rossum, with substantial assistance from the rest of the Zope Corp. team.

Finally, there’s the ultimate authority: the source code. Most of the machinery for the type handling is in Objects/typeobject.c, but you should only resort to it after all other avenues have been exhausted, including posting a question to python-list or python-dev.

PEP 234 : Itérateurs

Another significant addition to 2.2 is an iteration interface at both the C and Python levels. Objects can define how they can be looped over by callers.

In Python versions up to 2.1, the usual way to make for item in obj work is to define a __getitem__() method that looks something like this:

def __getitem__(self, index):
    return <next item>

__getitem__() is more properly used to define an indexing operation on an object so that you can write obj[5] to retrieve the sixth element. It’s a bit misleading when you’re using this only to support for loops. Consider some file-like object that wants to be looped over; the index parameter is essentially meaningless, as the class probably assumes that a series of __getitem__() calls will be made with index incrementing by one each time. In other words, the presence of the __getitem__() method doesn’t mean that using file[5] to randomly access the sixth element will work, though it really should.

In Python 2.2, iteration can be implemented separately, and __getitem__() methods can be limited to classes that really do support random access. The basic idea of iterators is simple. A new built-in function, iter(obj) or iter(C, sentinel), is used to get an iterator. iter(obj) returns an iterator for the object obj, while iter(C, sentinel) returns an iterator that will invoke the callable object C until it returns sentinel to signal that the iterator is done.

Python classes can define an __iter__() method, which should create and return a new iterator for the object; if the object is its own iterator, this method can just return self. In particular, iterators will usually be their own iterators. Extension types implemented in C can implement a tp_iter function in order to return an iterator, and extension types that want to behave as iterators can define a tp_iternext function.

So, after all this, what do iterators actually do? They have one required method, next(), which takes no arguments and returns the next value. When there are no more values to be returned, calling next() should raise the StopIteration exception.

>>> L = [1,2,3]
>>> i = iter(L)
>>> print i
<iterator object at 0x8116870>
>>> i.next()
1
>>> i.next()
2
>>> i.next()
3
>>> i.next()
Traceback (most recent call last):
  File "<stdin>", line 1, in ?
StopIteration
>>>

In 2.2, Python’s for statement no longer expects a sequence; it expects something for which iter() will return an iterator. For backward compatibility and convenience, an iterator is automatically constructed for sequences that don’t implement __iter__() or a tp_iter slot, so for i in [1,2,3] will still work. Wherever the Python interpreter loops over a sequence, it’s been changed to use the iterator protocol. This means you can do things like this:

>>> L = [1,2,3]
>>> i = iter(L)
>>> a,b,c = i
>>> a,b,c
(1, 2, 3)

Iterator support has been added to some of Python’s basic types. Calling iter() on a dictionary will return an iterator which loops over its keys:

>>> m = {'Jan': 1, 'Feb': 2, 'Mar': 3, 'Apr': 4, 'May': 5, 'Jun': 6,
...      'Jul': 7, 'Aug': 8, 'Sep': 9, 'Oct': 10, 'Nov': 11, 'Dec': 12}
>>> for key in m: print key, m[key]
...
Mar 3
Feb 2
Aug 8
Sep 9
May 5
Jun 6
Jul 7
Jan 1
Apr 4
Nov 11
Dec 12
Oct 10

That’s just the default behaviour. If you want to iterate over keys, values, or key/value pairs, you can explicitly call the iterkeys(), itervalues(), or iteritems() methods to get an appropriate iterator. In a minor related change, the in operator now works on dictionaries, so key in dict is now equivalent to dict.has_key(key).

Files also provide an iterator, which calls the readline() method until there are no more lines in the file. This means you can now read each line of a file using code like this:

for line in file:
    # do something for each line
    ...

Note that you can only go forward in an iterator; there’s no way to get the previous element, reset the iterator, or make a copy of it. An iterator object could provide such additional capabilities, but the iterator protocol only requires a next() method.

Voir aussi

PEP 234 [https://www.python.org/dev/peps/pep-0234] – Itérateurs

Written by Ka-Ping Yee and GvR; implemented by the Python Labs crew, mostly by GvR and Tim Peters.

PEP 255 : Générateurs simples

Generators are another new feature, one that interacts with the introduction of iterators.

You’re doubtless familiar with how function calls work in Python or C. When you call a function, it gets a private namespace where its local variables are created. When the function reaches a return statement, the local variables are destroyed and the resulting value is returned to the caller. A later call to the same function will get a fresh new set of local variables. But, what if the local variables weren’t thrown away on exiting a function? What if you could later resume the function where it left off? This is what generators provide; they can be thought of as resumable functions.

Here’s the simplest example of a generator function:

def generate_ints(N):
    for i in range(N):
        yield i

A new keyword, yield, was introduced for generators. Any function containing a yield statement is a generator function; this is detected by Python’s bytecode compiler which compiles the function specially as a result. Because a new keyword was introduced, generators must be explicitly enabled in a module by including a from __future__ import generators statement near the top of the module’s source code. In Python 2.3 this statement will become unnecessary.

When you call a generator function, it doesn’t return a single value; instead it returns a generator object that supports the iterator protocol. On executing the yield statement, the generator outputs the value of i, similar to a return statement. The big difference between yield and a return statement is that on reaching a yield the generator’s state of execution is suspended and local variables are preserved. On the next call to the generator’s next() method, the function will resume executing immediately after the yield statement. (For complicated reasons, the yield statement isn’t allowed inside the try block of a try…finally statement; read PEP 255 [https://www.python.org/dev/peps/pep-0255] for a full explanation of the interaction between yield and exceptions.)

Here’s a sample usage of the generate_ints() generator:

>>> gen = generate_ints(3)
>>> gen
<generator object at 0x8117f90>
>>> gen.next()
0
>>> gen.next()
1
>>> gen.next()
2
>>> gen.next()
Traceback (most recent call last):
  File "<stdin>", line 1, in ?
  File "<stdin>", line 2, in generate_ints
StopIteration

You could equally write for i in generate_ints(5), or a,b,c = generate_ints(3).

Inside a generator function, the return statement can only be used without a value, and signals the end of the procession of values; afterwards the generator cannot return any further values. return with a value, such as return 5, is a syntax error inside a generator function. The end of the generator’s results can also be indicated by raising StopIteration manually, or by just letting the flow of execution fall off the bottom of the function.

You could achieve the effect of generators manually by writing your own class and storing all the local variables of the generator as instance variables. For example, returning a list of integers could be done by setting self.count to 0, and having the next() method increment self.count and return it. However, for a moderately complicated generator, writing a corresponding class would be much messier. Lib/test/test_generators.py contains a number of more interesting examples. The simplest one implements an in-order traversal of a tree using generators recursively.

# A recursive generator that generates Tree leaves in in-order.
def inorder(t):
    if t:
        for x in inorder(t.left):
            yield x
        yield t.label
        for x in inorder(t.right):
            yield x

Two other examples in Lib/test/test_generators.py produce solutions for the N-Queens problem (placing $N$ queens on an $NxN$ chess board so that no queen threatens another) and the Knight’s Tour (a route that takes a knight to every square of an $NxN$ chessboard without visiting any square twice).

The idea of generators comes from other programming languages, especially Icon (https://www.cs.arizona.edu/icon/), where the idea of generators is central. In Icon, every expression and function call behaves like a generator. One example from « An Overview of the Icon Programming Language » at https://www.cs.arizona.edu/icon/docs/ipd266.htm gives an idea of what this looks like:

sentence := "Store it in the neighboring harbor"
if (i := find("or", sentence)) > 5 then write(i)

In Icon the find() function returns the indexes at which the substring « or » is found: 3, 23, 33. In the if statement, i is first assigned a value of 3, but 3 is less than 5, so the comparison fails, and Icon retries it with the second value of 23. 23 is greater than 5, so the comparison now succeeds, and the code prints the value 23 to the screen.

Python doesn’t go nearly as far as Icon in adopting generators as a central concept. Generators are considered a new part of the core Python language, but learning or using them isn’t compulsory; if they don’t solve any problems that you have, feel free to ignore them. One novel feature of Python’s interface as compared to Icon’s is that a generator’s state is represented as a concrete object (the iterator) that can be passed around to other functions or stored in a data structure.

Voir aussi

PEP 255 [https://www.python.org/dev/peps/pep-0255]: Générateurs simples

Written by Neil Schemenauer, Tim Peters, Magnus Lie Hetland. Implemented mostly by Neil Schemenauer and Tim Peters, with other fixes from the Python Labs crew.

PEP 237: Unifying Long Integers and Integers

In recent versions, the distinction between regular integers, which are 32-bit values on most machines, and long integers, which can be of arbitrary size, was becoming an annoyance. For example, on platforms that support files larger than 2**32 bytes, the tell() method of file objects has to return a long integer. However, there were various bits of Python that expected plain integers and would raise an error if a long integer was provided instead. For example, in Python 1.5, only regular integers could be used as a slice index, and 'abc'[1L:] would raise a TypeError exception with the message “slice index must be int”.

Python 2.2 will shift values from short to long integers as required. The “L” suffix is no longer needed to indicate a long integer literal, as now the compiler will choose the appropriate type. (Using the “L” suffix will be discouraged in future 2.x versions of Python, triggering a warning in Python 2.4, and probably dropped in Python 3.0.) Many operations that used to raise an OverflowError will now return a long integer as their result. For example:

>>> 1234567890123
1234567890123L
>>> 2 ** 64
18446744073709551616L

In most cases, integers and long integers will now be treated identically. You can still distinguish them with the type() built-in function, but that’s rarely needed.

Voir aussi

PEP 237 [https://www.python.org/dev/peps/pep-0237] - Unifying Long Integers and Integers

Written by Moshe Zadka and Guido van Rossum. Implemented mostly by Guido van Rossum.

PEP 238: Changing the Division Operator

The most controversial change in Python 2.2 heralds the start of an effort to fix an old design flaw that’s been in Python from the beginning. Currently Python’s division operator, /, behaves like C’s division operator when presented with two integer arguments: it returns an integer result that’s truncated down when there would be a fractional part. For example, 3/2 is 1, not 1.5, and (-1)/2 is -1, not -0.5. This means that the results of division can vary unexpectedly depending on the type of the two operands and because Python is dynamically typed, it can be difficult to determine the possible types of the operands.

(The controversy is over whether this is really a design flaw, and whether it’s worth breaking existing code to fix this. It’s caused endless discussions on python-dev, and in July 2001 erupted into a storm of acidly sarcastic postings on comp.lang.python. I won’t argue for either side here and will stick to describing what’s implemented in 2.2. Read PEP 238 [https://www.python.org/dev/peps/pep-0238] for a summary of arguments and counter-arguments.)

Because this change might break code, it’s being introduced very gradually. Python 2.2 begins the transition, but the switch won’t be complete until Python 3.0.

First, I’ll borrow some terminology from PEP 238 [https://www.python.org/dev/peps/pep-0238]. « True division » is the division that most non-programmers are familiar with: 3/2 is 1.5, 1/4 is 0.25, and so forth. « Floor division » is what Python’s / operator currently does when given integer operands; the result is the floor of the value returned by true division. « Classic division » is the current mixed behaviour of /; it returns the result of floor division when the operands are integers, and returns the result of true division when one of the operands is a floating-point number.

Here are the changes 2.2 introduces:

A new operator, //, is the floor division operator. (Yes, we know it looks like C++”s comment symbol.) // always performs floor division no matter what the types of its operands are, so 1 // 2 is 0 and 1.0 // 2.0 is also 0.0.

// is always available in Python 2.2; you don’t need to enable it using a __future__ statement.

By including a from __future__ import division in a module, the / operator will be changed to return the result of true division, so 1/2 is 0.5. Without the __future__ statement, / still means classic division. The default meaning of / will not change until Python 3.0.

Classes can define methods called __truediv__() and __floordiv__() to overload the two division operators. At the C level, there are also slots in the PyNumberMethods structure so extension types can define the two operators.

Python 2.2 supports some command-line arguments for testing whether code will work with the changed division semantics. Running python with -Q warn will cause a warning to be issued whenever division is applied to two integers. You can use this to find code that’s affected by the change and fix it. By default, Python 2.2 will simply perform classic division without a warning; the warning will be turned on by default in Python 2.3.

Voir aussi

PEP 238 [https://www.python.org/dev/peps/pep-0238] - Changing the Division Operator

Written by Moshe Zadka and Guido van Rossum. Implemented by Guido van Rossum..

Unicode Changes

Python’s Unicode support has been enhanced a bit in 2.2. Unicode strings are usually stored as UCS-2, as 16-bit unsigned integers. Python 2.2 can also be compiled to use UCS-4, 32-bit unsigned integers, as its internal encoding by supplying --enable-unicode=ucs4 to the configure script. (It’s also possible to specify --disable-unicode to completely disable Unicode support.)

When built to use UCS-4 (a « wide Python »), the interpreter can natively handle Unicode characters from U+000000 to U+110000, so the range of legal values for the unichr() function is expanded accordingly. Using an interpreter compiled to use UCS-2 (a « narrow Python »), values greater than 65535 will still cause unichr() to raise a ValueError exception. This is all described in PEP 261 [https://www.python.org/dev/peps/pep-0261], « Support for “wide” Unicode characters »; consult it for further details.

Another change is simpler to explain. Since their introduction, Unicode strings have supported an encode() method to convert the string to a selected encoding such as UTF-8 or Latin-1. A symmetric decode([*encoding*]) method has been added to 8-bit strings (though not to Unicode strings) in 2.2. decode() assumes that the string is in the specified encoding and decodes it, returning whatever is returned by the codec.

Using this new feature, codecs have been added for tasks not directly related to Unicode. For example, codecs have been added for uu-encoding, MIME’s base64 encoding, and compression with the zlib module:

>>> s = """Here is a lengthy piece of redundant, overly verbose,
... and repetitive text.
... """
>>> data = s.encode('zlib')
>>> data
'x\x9c\r\xc9\xc1\r\x80 \x10\x04\xc0?Ul...'
>>> data.decode('zlib')
'Here is a lengthy piece of redundant, overly verbose,\nand repetitive text.\n'
>>> print s.encode('uu')
begin 666 <data>
M2&5R92!I<R!A(&QE;F=T:'D@<&EE8V4@;V8@<F5D=6YD86YT+"!O=F5R;'D@
>=F5R8F]S92P*86YD(')E<&5T:71I=F4@=&5X="X*

end
>>> "sheesh".encode('rot-13')
'furrfu'

To convert a class instance to Unicode, a __unicode__() method can be defined by a class, analogous to __str__().

encode(), decode(), and __unicode__() were implemented by Marc-André Lemburg. The changes to support using UCS-4 internally were implemented by Fredrik Lundh and Martin von Löwis.

Voir aussi

PEP 261 [https://www.python.org/dev/peps/pep-0261] - Support for “wide” Unicode characters

Written by Paul Prescod.

PEP 227: Nested Scopes

In Python 2.1, statically nested scopes were added as an optional feature, to be enabled by a from __future__ import nested_scopes directive. In 2.2 nested scopes no longer need to be specially enabled, and are now always present. The rest of this section is a copy of the description of nested scopes from my « What’s New in Python 2.1 » document; if you read it when 2.1 came out, you can skip the rest of this section.

The largest change introduced in Python 2.1, and made complete in 2.2, is to Python’s scoping rules. In Python 2.0, at any given time there are at most three namespaces used to look up variable names: local, module-level, and the built-in namespace. This often surprised people because it didn’t match their intuitive expectations. For example, a nested recursive function definition doesn’t work:

def f():
    ...
    def g(value):
        ...
        return g(value-1) + 1
    ...

The function g() will always raise a NameError exception, because the binding of the name g isn’t in either its local namespace or in the module-level namespace. This isn’t much of a problem in practice (how often do you recursively define interior functions like this?), but this also made using the lambda statement clumsier, and this was a problem in practice. In code which uses lambda you can often find local variables being copied by passing them as the default values of arguments.

def find(self, name):
    "Return list of any entries equal to 'name'"
    L = filter(lambda x, name=name: x == name,
               self.list_attribute)
    return L

The readability of Python code written in a strongly functional style suffers greatly as a result.

The most significant change to Python 2.2 is that static scoping has been added to the language to fix this problem. As a first effect, the name=name default argument is now unnecessary in the above example. Put simply, when a given variable name is not assigned a value within a function (by an assignment, or the def, class, or import statements), references to the variable will be looked up in the local namespace of the enclosing scope. A more detailed explanation of the rules, and a dissection of the implementation, can be found in the PEP.

This change may cause some compatibility problems for code where the same variable name is used both at the module level and as a local variable within a function that contains further function definitions. This seems rather unlikely though, since such code would have been pretty confusing to read in the first place.

One side effect of the change is that the from module import * and exec statements have been made illegal inside a function scope under certain conditions. The Python reference manual has said all along that from module import * is only legal at the top level of a module, but the CPython interpreter has never enforced this before. As part of the implementation of nested scopes, the compiler which turns Python source into bytecodes has to generate different code to access variables in a containing scope. from module import * and exec make it impossible for the compiler to figure this out, because they add names to the local namespace that are unknowable at compile time. Therefore, if a function contains function definitions or lambda expressions with free variables, the compiler will flag this by raising a SyntaxError exception.

To make the preceding explanation a bit clearer, here’s an example:

x = 1
def f():
    # The next line is a syntax error
    exec 'x=2'
    def g():
        return x

Line 4 containing the exec statement is a syntax error, since exec would define a new local variable named x whose value should be accessed by g().

This shouldn’t be much of a limitation, since exec is rarely used in most Python code (and when it is used, it’s often a sign of a poor design anyway).

Voir aussi

PEP 227 [https://www.python.org/dev/peps/pep-0227] - Statically Nested Scopes

Écrit et implémenté par Jeremy Hylton.

New and Improved Modules

The xmlrpclib module was contributed to the standard library by Fredrik Lundh, providing support for writing XML-RPC clients. XML-RPC is a simple remote procedure call protocol built on top of HTTP and XML. For example, the following snippet retrieves a list of RSS channels from the O’Reilly Network, and then lists the recent headlines for one channel:

import xmlrpclib
s = xmlrpclib.Server(
      'http://www.oreillynet.com/meerkat/xml-rpc/server.php')
channels = s.meerkat.getChannels()
# channels is a list of dictionaries, like this:
# [{'id': 4, 'title': 'Freshmeat Daily News'}
#  {'id': 190, 'title': '32Bits Online'},
#  {'id': 4549, 'title': '3DGamers'}, ... ]

# Get the items for one channel
items = s.meerkat.getItems( {'channel': 4} )

# 'items' is another list of dictionaries, like this:
# [{'link': 'http://freshmeat.net/releases/52719/',
#   'description': 'A utility which converts HTML to XSL FO.',
#   'title': 'html2fo 0.3 (Default)'}, ... ]

The SimpleXMLRPCServer module makes it easy to create straightforward XML-RPC servers. See http://www.xmlrpc.com/ for more information about XML-RPC.

The new hmac module implements the HMAC algorithm described by RFC 2104 [https://tools.ietf.org/html/rfc2104.html]. (Contributed by Gerhard Häring.)

Several functions that originally returned lengthy tuples now return pseudo-sequences that still behave like tuples but also have mnemonic attributes such as memberst_mtime or tm_year. The enhanced functions include stat(), fstat(), statvfs(), and fstatvfs() in the os module, and localtime(), gmtime(), and strptime() in the time module.

For example, to obtain a file’s size using the old tuples, you’d end up writing something like file_size = os.stat(filename)[stat.ST_SIZE], but now this can be written more clearly as file_size = os.stat(filename).st_size.

The original patch for this feature was contributed by Nick Mathewson.

The Python profiler has been extensively reworked and various errors in its output have been corrected. (Contributed by Fred L. Drake, Jr. and Tim Peters.)

The socket module can be compiled to support IPv6; specify the --enable-ipv6 option to Python’s configure script. (Contributed by Jun-ichiro « itojun » Hagino.)

Two new format characters were added to the struct module for 64-bit integers on platforms that support the C long long type. q is for a signed 64-bit integer, and Q is for an unsigned one. The value is returned in Python’s long integer type. (Contributed by Tim Peters.)

In the interpreter’s interactive mode, there’s a new built-in function help() that uses the pydoc module introduced in Python 2.1 to provide interactive help. help(object) displays any available help text about object. help() with no argument puts you in an online help utility, where you can enter the names of functions, classes, or modules to read their help text. (Contributed by Guido van Rossum, using Ka-Ping Yee’s pydoc module.)

Various bugfixes and performance improvements have been made to the SRE engine underlying the re module. For example, the re.sub() and re.split() functions have been rewritten in C. Another contributed patch speeds up certain Unicode character ranges by a factor of two, and a new finditer() method that returns an iterator over all the non-overlapping matches in a given string. (SRE is maintained by Fredrik Lundh. The BIGCHARSET patch was contributed by Martin von Löwis.)

The smtplib module now supports RFC 2487 [https://tools.ietf.org/html/rfc2487.html], « Secure SMTP over TLS », so it’s now possible to encrypt the SMTP traffic between a Python program and the mail transport agent being handed a message. smtplib also supports SMTP authentication. (Contributed by Gerhard Häring.)

The imaplib module, maintained by Piers Lauder, has support for several new extensions: the NAMESPACE extension defined in RFC 2342 [https://tools.ietf.org/html/rfc2342.html], SORT, GETACL and SETACL. (Contributed by Anthony Baxter and Michel Pelletier.)

The rfc822 module’s parsing of email addresses is now compliant with RFC 2822 [https://tools.ietf.org/html/rfc2822.html], an update to RFC 822 [https://tools.ietf.org/html/rfc822.html]. (The module’s name is not going to be changed to rfc2822.) A new package, email, has also been added for parsing and generating e-mail messages. (Contributed by Barry Warsaw, and arising out of his work on Mailman.)

The difflib module now contains a new Differ class for producing human-readable lists of changes (a « delta ») between two sequences of lines of text. There are also two generator functions, ndiff() and restore(), which respectively return a delta from two sequences, or one of the original sequences from a delta. (Grunt work contributed by David Goodger, from ndiff.py code by Tim Peters who then did the generatorization.)

New constants ascii_letters, ascii_lowercase, and ascii_uppercase were added to the string module. There were several modules in the standard library that used string.letters to mean the ranges A-Za-z, but that assumption is incorrect when locales are in use, because string.letters varies depending on the set of legal characters defined by the current locale. The buggy modules have all been fixed to use ascii_letters instead. (Reported by an unknown person; fixed by Fred L. Drake, Jr.)

The mimetypes module now makes it easier to use alternative MIME-type databases by the addition of a MimeTypes class, which takes a list of filenames to be parsed. (Contributed by Fred L. Drake, Jr.)

A Timer class was added to the threading module that allows scheduling an activity to happen at some future time. (Contributed by Itamar Shtull-Trauring.)

Interpreter Changes and Fixes

Some of the changes only affect people who deal with the Python interpreter at the C level because they’re writing Python extension modules, embedding the interpreter, or just hacking on the interpreter itself. If you only write Python code, none of the changes described here will affect you very much.

Profiling and tracing functions can now be implemented in C, which can operate at much higher speeds than Python-based functions and should reduce the overhead of profiling and tracing. This will be of interest to authors of development environments for Python. Two new C functions were added to Python’s API, PyEval_SetProfile() and PyEval_SetTrace(). The existing sys.setprofile() and sys.settrace() functions still exist, and have simply been changed to use the new C-level interface. (Contributed by Fred L. Drake, Jr.)

Another low-level API, primarily of interest to implementors of Python debuggers and development tools, was added. PyInterpreterState_Head() and PyInterpreterState_Next() let a caller walk through all the existing interpreter objects; PyInterpreterState_ThreadHead() and PyThreadState_Next() allow looping over all the thread states for a given interpreter. (Contributed by David Beazley.)

The C-level interface to the garbage collector has been changed to make it easier to write extension types that support garbage collection and to debug misuses of the functions. Various functions have slightly different semantics, so a bunch of functions had to be renamed. Extensions that use the old API will still compile but will not participate in garbage collection, so updating them for 2.2 should be considered fairly high priority.

To upgrade an extension module to the new API, perform the following steps:

Rename Py_TPFLAGS_GC() to PyTPFLAGS_HAVE_GC().

Use PyObject_GC_New() or PyObject_GC_NewVar() to allocate

objects, and PyObject_GC_Del() to deallocate them.

Rename PyObject_GC_Init() to PyObject_GC_Track() and

PyObject_GC_Fini() to PyObject_GC_UnTrack().

Remove PyGC_HEAD_SIZE() from object size calculations.

Remove calls to PyObject_AS_GC() and PyObject_FROM_GC().

A new et format sequence was added to PyArg_ParseTuple(); et takes both a parameter and an encoding name, and converts the parameter to the given encoding if the parameter turns out to be a Unicode string, or leaves it alone if it’s an 8-bit string, assuming it to already be in the desired encoding. This differs from the es format character, which assumes that 8-bit strings are in Python’s default ASCII encoding and converts them to the specified new encoding. (Contributed by M.-A. Lemburg, and used for the MBCS support on Windows described in the following section.)

A different argument parsing function, PyArg_UnpackTuple(), has been added that’s simpler and presumably faster. Instead of specifying a format string, the caller simply gives the minimum and maximum number of arguments expected, and a set of pointers to PyObject* variables that will be filled in with argument values.

Two new flags METH_NOARGS and METH_O are available in method definition tables to simplify implementation of methods with no arguments or a single untyped argument. Calling such methods is more efficient than calling a corresponding method that uses METH_VARARGS. Also, the old METH_OLDARGS style of writing C methods is now officially deprecated.

Two new wrapper functions, PyOS_snprintf() and PyOS_vsnprintf() were added to provide cross-platform implementations for the relatively new snprintf() and vsnprintf() C lib APIs. In contrast to the standard sprintf() and vsprintf() functions, the Python versions check the bounds of the buffer used to protect against buffer overruns. (Contributed by M.-A. Lemburg.)

The _PyTuple_Resize() function has lost an unused parameter, so now it takes 2 parameters instead of 3. The third argument was never used, and can simply be discarded when porting code from earlier versions to Python 2.2.

Autres changements et corrections

As usual there were a bunch of other improvements and bugfixes scattered throughout the source tree. A search through the CVS change logs finds there were 527 patches applied and 683 bugs fixed between Python 2.1 and 2.2; 2.2.1 applied 139 patches and fixed 143 bugs; 2.2.2 applied 106 patches and fixed 82 bugs. These figures are likely to be underestimates.

Some of the more notable changes are:

The code for the MacOS port for Python, maintained by Jack Jansen, is now kept in the main Python CVS tree, and many changes have been made to support MacOS X.

The most significant change is the ability to build Python as a framework, enabled by supplying the --enable-framework option to the configure script when compiling Python. According to Jack Jansen, « This installs a self-contained Python installation plus the OS X framework « glue » into /Library/Frameworks/Python.framework (or another location of choice). For now there is little immediate added benefit to this (actually, there is the disadvantage that you have to change your PATH to be able to find Python), but it is the basis for creating a full-blown Python application, porting the MacPython IDE, possibly using Python as a standard OSA scripting language and much more. »

Most of the MacPython toolbox modules, which interface to MacOS APIs such as windowing, QuickTime, scripting, etc. have been ported to OS X, but they’ve been left commented out in setup.py. People who want to experiment with these modules can uncomment them manually.

Keyword arguments passed to built-in functions that don’t take them now cause a TypeError exception to be raised, with the message « function takes no keyword arguments ».

Weak references, added in Python 2.1 as an extension module, are now part of the core because they’re used in the implementation of new-style classes. The ReferenceError exception has therefore moved from the weakref module to become a built-in exception.

A new script, Tools/scripts/cleanfuture.py by Tim Peters, automatically removes obsolete __future__ statements from Python source code.

An additional flags argument has been added to the built-in function compile(), so the behaviour of __future__ statements can now be correctly observed in simulated shells, such as those presented by IDLE and other development environments. This is described in PEP 264 [https://www.python.org/dev/peps/pep-0264]. (Contributed by Michael Hudson.)

The new license introduced with Python 1.6 wasn’t GPL-compatible. This is fixed by some minor textual changes to the 2.2 license, so it’s now legal to embed Python inside a GPLed program again. Note that Python itself is not GPLed, but instead is under a license that’s essentially equivalent to the BSD license, same as it always was. The license changes were also applied to the Python 2.0.1 and 2.1.1 releases.

When presented with a Unicode filename on Windows, Python will now convert it to an MBCS encoded string, as used by the Microsoft file APIs. As MBCS is explicitly used by the file APIs, Python’s choice of ASCII as the default encoding turns out to be an annoyance. On Unix, the locale’s character set is used if locale.nl_langinfo(CODESET) is available. (Windows support was contributed by Mark Hammond with assistance from Marc-André Lemburg. Unix support was added by Martin von Löwis.)

Large file support is now enabled on Windows. (Contributed by Tim Peters.)

The Tools/scripts/ftpmirror.py script now parses a .netrc file, if you have one. (Contributed by Mike Romberg.)

Some features of the object returned by the xrange() function are now deprecated, and trigger warnings when they’re accessed; they’ll disappear in Python 2.3. xrange objects tried to pretend they were full sequence types by supporting slicing, sequence multiplication, and the in operator, but these features were rarely used and therefore buggy. The tolist() method and the start, stop, and step attributes are also being deprecated. At the C level, the fourth argument to the PyRange_New() function, repeat, has also been deprecated.

There were a bunch of patches to the dictionary implementation, mostly to fix potential core dumps if a dictionary contains objects that sneakily changed their hash value, or mutated the dictionary they were contained in. For a while python-dev fell into a gentle rhythm of Michael Hudson finding a case that dumped core, Tim Peters fixing the bug, Michael finding another case, and round and round it went.

On Windows, Python can now be compiled with Borland C thanks to a number of patches contributed by Stephen Hansen, though the result isn’t fully functional yet. (But this is progress…)

Another Windows enhancement: Wise Solutions generously offered PythonLabs use of their InstallerMaster 8.1 system. Earlier PythonLabs Windows installers used Wise 5.0a, which was beginning to show its age. (Packaged up by Tim Peters.)

Files ending in .pyw can now be imported on Windows. .pyw is a Windows-only thing, used to indicate that a script needs to be run using PYTHONW.EXE instead of PYTHON.EXE in order to prevent a DOS console from popping up to display the output. This patch makes it possible to import such scripts, in case they’re also usable as modules. (Implemented by David Bolen.)

On platforms where Python uses the C dlopen() function to load extension modules, it’s now possible to set the flags used by dlopen() using the sys.getdlopenflags() and sys.setdlopenflags() functions. (Contributed by Bram Stolk.)

The pow() built-in function no longer supports 3 arguments when floating-point numbers are supplied. pow(x, y, z) returns (x**y) % z, but this is never useful for floating point numbers, and the final result varies unpredictably depending on the platform. A call such as pow(2.0, 8.0, 7.0) will now raise a TypeError exception.

Remerciements

The author would like to thank the following people for offering suggestions, corrections and assistance with various drafts of this article: Fred Bremmer, Keith Briggs, Andrew Dalke, Fred L. Drake, Jr., Carel Fellinger, David Goodger, Mark Hammond, Stephen Hansen, Michael Hudson, Jack Jansen, Marc-André Lemburg, Martin von Löwis, Fredrik Lundh, Michael McLay, Nick Mathewson, Paul Moore, Gustavo Niemeyer, Don O’Donnell, Joonas Paalasma, Tim Peters, Jens Quade, Tom Reinhardt, Neil Schemenauer, Guido van Rossum, Greg Ward, Edward Welbourne.

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Nouveautés de Python 2.1

Auteur

A.M. Kuchling

Introduction

This article explains the new features in Python 2.1. While there aren’t as many changes in 2.1 as there were in Python 2.0, there are still some pleasant surprises in store. 2.1 is the first release to be steered through the use of Python Enhancement Proposals, or PEPs, so most of the sizable changes have accompanying PEPs that provide more complete documentation and a design rationale for the change. This article doesn’t attempt to document the new features completely, but simply provides an overview of the new features for Python programmers. Refer to the Python 2.1 documentation, or to the specific PEP, for more details about any new feature that particularly interests you.

One recent goal of the Python development team has been to accelerate the pace of new releases, with a new release coming every 6 to 9 months. 2.1 is the first release to come out at this faster pace, with the first alpha appearing in January, 3 months after the final version of 2.0 was released.

The final release of Python 2.1 was made on April 17, 2001.

PEP 227: Nested Scopes

The largest change in Python 2.1 is to Python’s scoping rules. In Python 2.0, at any given time there are at most three namespaces used to look up variable names: local, module-level, and the built-in namespace. This often surprised people because it didn’t match their intuitive expectations. For example, a nested recursive function definition doesn’t work:

def f():
    ...
    def g(value):
        ...
        return g(value-1) + 1
    ...

The function g() will always raise a NameError exception, because the binding of the name g isn’t in either its local namespace or in the module-level namespace. This isn’t much of a problem in practice (how often do you recursively define interior functions like this?), but this also made using the lambda statement clumsier, and this was a problem in practice. In code which uses lambda you can often find local variables being copied by passing them as the default values of arguments.

def find(self, name):
    "Return list of any entries equal to 'name'"
    L = filter(lambda x, name=name: x == name,
               self.list_attribute)
    return L

The readability of Python code written in a strongly functional style suffers greatly as a result.

The most significant change to Python 2.1 is that static scoping has been added to the language to fix this problem. As a first effect, the name=name default argument is now unnecessary in the above example. Put simply, when a given variable name is not assigned a value within a function (by an assignment, or the def, class, or import statements), references to the variable will be looked up in the local namespace of the enclosing scope. A more detailed explanation of the rules, and a dissection of the implementation, can be found in the PEP.

This change may cause some compatibility problems for code where the same variable name is used both at the module level and as a local variable within a function that contains further function definitions. This seems rather unlikely though, since such code would have been pretty confusing to read in the first place.

One side effect of the change is that the from module import * and exec statements have been made illegal inside a function scope under certain conditions. The Python reference manual has said all along that from module import * is only legal at the top level of a module, but the CPython interpreter has never enforced this before. As part of the implementation of nested scopes, the compiler which turns Python source into bytecodes has to generate different code to access variables in a containing scope. from module import * and exec make it impossible for the compiler to figure this out, because they add names to the local namespace that are unknowable at compile time. Therefore, if a function contains function definitions or lambda expressions with free variables, the compiler will flag this by raising a SyntaxError exception.

To make the preceding explanation a bit clearer, here’s an example:

x = 1
def f():
    # The next line is a syntax error
    exec 'x=2'
    def g():
        return x

Line 4 containing the exec statement is a syntax error, since exec would define a new local variable named x whose value should be accessed by g().

This shouldn’t be much of a limitation, since exec is rarely used in most Python code (and when it is used, it’s often a sign of a poor design anyway).

Compatibility concerns have led to nested scopes being introduced gradually; in Python 2.1, they aren’t enabled by default, but can be turned on within a module by using a future statement as described in PEP 236. (See the following section for further discussion of PEP 236.) In Python 2.2, nested scopes will become the default and there will be no way to turn them off, but users will have had all of 2.1’s lifetime to fix any breakage resulting from their introduction.

Voir aussi

PEP 227 [https://www.python.org/dev/peps/pep-0227] - Statically Nested Scopes

Écrit et implémenté par Jeremy Hylton.

PEP 236 : Directives __future__

The reaction to nested scopes was widespread concern about the dangers of breaking code with the 2.1 release, and it was strong enough to make the Pythoneers take a more conservative approach. This approach consists of introducing a convention for enabling optional functionality in release N that will become compulsory in release N+1.

The syntax uses a from...import statement using the reserved module name __future__. Nested scopes can be enabled by the following statement:

from __future__ import nested_scopes

While it looks like a normal import statement, it’s not; there are strict rules on where such a future statement can be put. They can only be at the top of a module, and must precede any Python code or regular import statements. This is because such statements can affect how the Python bytecode compiler parses code and generates bytecode, so they must precede any statement that will result in bytecodes being produced.

Voir aussi

PEP 236 [https://www.python.org/dev/peps/pep-0236] – Retour vers le __future__

Écrit par Tim Peters, et implémenté principalement par Jeremy Hylton.

PEP 207: Rich Comparisons

In earlier versions, Python’s support for implementing comparisons on user-defined classes and extension types was quite simple. Classes could implement a __cmp__() method that was given two instances of a class, and could only return 0 if they were equal or +1 or -1 if they weren’t; the method couldn’t raise an exception or return anything other than a Boolean value. Users of Numeric Python often found this model too weak and restrictive, because in the number-crunching programs that numeric Python is used for, it would be more useful to be able to perform elementwise comparisons of two matrices, returning a matrix containing the results of a given comparison for each element. If the two matrices are of different sizes, then the compare has to be able to raise an exception to signal the error.

In Python 2.1, rich comparisons were added in order to support this need. Python classes can now individually overload each of the <, <=, >, >=, ==, and != operations. The new magic method names are:

Opération

Nom de méthode

<

__lt__()

<=

__le__()

>

__gt__()

>=

__ge__()

==

__eq__()

!=

__ne__()

(The magic methods are named after the corresponding Fortran operators .LT.. .LE., &c. Numeric programmers are almost certainly quite familiar with these names and will find them easy to remember.)

Each of these magic methods is of the form method(self, other), where self will be the object on the left-hand side of the operator, while other will be the object on the right-hand side. For example, the expression A < B will cause A.__lt__(B) to be called.

Each of these magic methods can return anything at all: a Boolean, a matrix, a list, or any other Python object. Alternatively they can raise an exception if the comparison is impossible, inconsistent, or otherwise meaningless.

The built-in cmp(A,B) function can use the rich comparison machinery, and now accepts an optional argument specifying which comparison operation to use; this is given as one of the strings "<", "<=", ">", ">=", "==", or "!=". If called without the optional third argument, cmp() will only return -1, 0, or +1 as in previous versions of Python; otherwise it will call the appropriate method and can return any Python object.

There are also corresponding changes of interest to C programmers; there’s a new slot tp_richcmp in type objects and an API for performing a given rich comparison. I won’t cover the C API here, but will refer you to PEP 207, or to 2.1’s C API documentation, for the full list of related functions.

Voir aussi

PEP 207 [https://www.python.org/dev/peps/pep-0207] - Rich Comparisons

Written by Guido van Rossum, heavily based on earlier work by David Ascher, and implemented by Guido van Rossum.

PEP 230: Warning Framework

Over its 10 years of existence, Python has accumulated a certain number of obsolete modules and features along the way. It’s difficult to know when a feature is safe to remove, since there’s no way of knowing how much code uses it — perhaps no programs depend on the feature, or perhaps many do. To enable removing old features in a more structured way, a warning framework was added. When the Python developers want to get rid of a feature, it will first trigger a warning in the next version of Python. The following Python version can then drop the feature, and users will have had a full release cycle to remove uses of the old feature.

Python 2.1 adds the warning framework to be used in this scheme. It adds a warnings module that provide functions to issue warnings, and to filter out warnings that you don’t want to be displayed. Third-party modules can also use this framework to deprecate old features that they no longer wish to support.

For example, in Python 2.1 the regex module is deprecated, so importing it causes a warning to be printed:

>>> import regex
__main__:1: DeprecationWarning: the regex module
         is deprecated; please use the re module
>>>

Warnings can be issued by calling the warnings.warn() function:

warnings.warn("feature X no longer supported")

The first parameter is the warning message; an additional optional parameters can be used to specify a particular warning category.

Filters can be added to disable certain warnings; a regular expression pattern can be applied to the message or to the module name in order to suppress a warning. For example, you may have a program that uses the regex module and not want to spare the time to convert it to use the re module right now. The warning can be suppressed by calling

import warnings
warnings.filterwarnings(action = 'ignore',
                        message='.*regex module is deprecated',
                        category=DeprecationWarning,
                        module = '__main__')

This adds a filter that will apply only to warnings of the class DeprecationWarning triggered in the __main__ module, and applies a regular expression to only match the message about the regex module being deprecated, and will cause such warnings to be ignored. Warnings can also be printed only once, printed every time the offending code is executed, or turned into exceptions that will cause the program to stop (unless the exceptions are caught in the usual way, of course).

Functions were also added to Python’s C API for issuing warnings; refer to PEP 230 or to Python’s API documentation for the details.

Voir aussi

PEP 5 [https://www.python.org/dev/peps/pep-0005] - Guidelines for Language Evolution

Written by Paul Prescod, to specify procedures to be followed when removing old features from Python. The policy described in this PEP hasn’t been officially adopted, but the eventual policy probably won’t be too different from Prescod’s proposal.

PEP 230 [https://www.python.org/dev/peps/pep-0230] - Warning Framework

Written and implemented by Guido van Rossum.

PEP 229: New Build System

When compiling Python, the user had to go in and edit the Modules/Setup file in order to enable various additional modules; the default set is relatively small and limited to modules that compile on most Unix platforms. This means that on Unix platforms with many more features, most notably Linux, Python installations often don’t contain all useful modules they could.

Python 2.0 added the Distutils, a set of modules for distributing and installing extensions. In Python 2.1, the Distutils are used to compile much of the standard library of extension modules, autodetecting which ones are supported on the current machine. It’s hoped that this will make Python installations easier and more featureful.

Instead of having to edit the Modules/Setup file in order to enable modules, a setup.py script in the top directory of the Python source distribution is run at build time, and attempts to discover which modules can be enabled by examining the modules and header files on the system. If a module is configured in Modules/Setup, the setup.py script won’t attempt to compile that module and will defer to the Modules/Setup file’s contents. This provides a way to specific any strange command-line flags or libraries that are required for a specific platform.

In another far-reaching change to the build mechanism, Neil Schemenauer restructured things so Python now uses a single makefile that isn’t recursive, instead of makefiles in the top directory and in each of the Python/, Parser/, Objects/, and Modules/ subdirectories. This makes building Python faster and also makes hacking the Makefiles clearer and simpler.

Voir aussi

PEP 229 [https://www.python.org/dev/peps/pep-0229] - Using Distutils to Build Python

Written and implemented by A.M. Kuchling.

PEP 205: Weak References

Weak references, available through the weakref module, are a minor but useful new data type in the Python programmer’s toolbox.

Storing a reference to an object (say, in a dictionary or a list) has the side effect of keeping that object alive forever. There are a few specific cases where this behaviour is undesirable, object caches being the most common one, and another being circular references in data structures such as trees.

For example, consider a memoizing function that caches the results of another function f(x) by storing the function’s argument and its result in a dictionary:

_cache = {}
def memoize(x):
    if _cache.has_key(x):
        return _cache[x]

    retval = f(x)

    # Cache the returned object
    _cache[x] = retval

    return retval

This version works for simple things such as integers, but it has a side effect; the _cache dictionary holds a reference to the return values, so they’ll never be deallocated until the Python process exits and cleans up. This isn’t very noticeable for integers, but if f() returns an object, or a data structure that takes up a lot of memory, this can be a problem.

Weak references provide a way to implement a cache that won’t keep objects alive beyond their time. If an object is only accessible through weak references, the object will be deallocated and the weak references will now indicate that the object it referred to no longer exists. A weak reference to an object obj is created by calling wr = weakref.ref(obj). The object being referred to is returned by calling the weak reference as if it were a function: wr(). It will return the referenced object, or None if the object no longer exists.

This makes it possible to write a memoize() function whose cache doesn’t keep objects alive, by storing weak references in the cache.

_cache = {}
def memoize(x):
    if _cache.has_key(x):
        obj = _cache[x]()
        # If weak reference object still exists,
        # return it
        if obj is not None: return obj

    retval = f(x)

    # Cache a weak reference
    _cache[x] = weakref.ref(retval)

    return retval

The weakref module also allows creating proxy objects which behave like weak references — an object referenced only by proxy objects is deallocated – but instead of requiring an explicit call to retrieve the object, the proxy transparently forwards all operations to the object as long as the object still exists. If the object is deallocated, attempting to use a proxy will cause a weakref.ReferenceError exception to be raised.

proxy = weakref.proxy(obj)
proxy.attr   # Equivalent to obj.attr
proxy.meth() # Equivalent to obj.meth()
del obj
proxy.attr   # raises weakref.ReferenceError

Voir aussi

PEP 205 [https://www.python.org/dev/peps/pep-0205] - Weak References

Écrit et implémenté par Fred L. Drake, Jr.

PEP 232 : Attributs de fonctions

In Python 2.1, functions can now have arbitrary information attached to them. People were often using docstrings to hold information about functions and methods, because the __doc__ attribute was the only way of attaching any information to a function. For example, in the Zope Web application server, functions are marked as safe for public access by having a docstring, and in John Aycock’s SPARK parsing framework, docstrings hold parts of the BNF grammar to be parsed. This overloading is unfortunate, since docstrings are really intended to hold a function’s documentation; for example, it means you can’t properly document functions intended for private use in Zope.

Arbitrary attributes can now be set and retrieved on functions using the regular Python syntax:

def f(): pass

f.publish = 1
f.secure = 1
f.grammar = "A ::= B (C D)*"

The dictionary containing attributes can be accessed as the function’s __dict__. Unlike the __dict__ attribute of class instances, in functions you can actually assign a new dictionary to __dict__, though the new value is restricted to a regular Python dictionary; you can’t be tricky and set it to a UserDict instance, or any other random object that behaves like a mapping.

Voir aussi

PEP 232 [https://www.python.org/dev/peps/pep-0232] – Attributs de fonctions

Écrit et implémenté par Barry Warsaw.

PEP 235: Importing Modules on Case-Insensitive Platforms

Some operating systems have filesystems that are case-insensitive, MacOS and Windows being the primary examples; on these systems, it’s impossible to distinguish the filenames FILE.PY and file.py, even though they do store the file’s name in its original case (they’re case-preserving, too).

In Python 2.1, the import statement will work to simulate case-sensitivity on case-insensitive platforms. Python will now search for the first case-sensitive match by default, raising an ImportError if no such file is found, so import file will not import a module named FILE.PY. Case-insensitive matching can be requested by setting the PYTHONCASEOK environment variable before starting the Python interpreter.

PEP 217: Interactive Display Hook

When using the Python interpreter interactively, the output of commands is displayed using the built-in repr() function. In Python 2.1, the variable sys.displayhook() can be set to a callable object which will be called instead of repr(). For example, you can set it to a special pretty-printing function:

>>> # Create a recursive data structure
... L = [1,2,3]
>>> L.append(L)
>>> L # Show Python's default output
[1, 2, 3, [...]]
>>> # Use pprint.pprint() as the display function
... import sys, pprint
>>> sys.displayhook = pprint.pprint
>>> L
[1, 2, 3,  <Recursion on list with id=135143996>]
>>>

Voir aussi

PEP 217 [https://www.python.org/dev/peps/pep-0217] - Display Hook for Interactive Use

Written and implemented by Moshe Zadka.

PEP 208: New Coercion Model

How numeric coercion is done at the C level was significantly modified. This will only affect the authors of C extensions to Python, allowing them more flexibility in writing extension types that support numeric operations.

Extension types can now set the type flag Py_TPFLAGS_CHECKTYPES in their PyTypeObject structure to indicate that they support the new coercion model. In such extension types, the numeric slot functions can no longer assume that they’ll be passed two arguments of the same type; instead they may be passed two arguments of differing types, and can then perform their own internal coercion. If the slot function is passed a type it can’t handle, it can indicate the failure by returning a reference to the Py_NotImplemented singleton value. The numeric functions of the other type will then be tried, and perhaps they can handle the operation; if the other type also returns Py_NotImplemented, then a TypeError will be raised. Numeric methods written in Python can also return Py_NotImplemented, causing the interpreter to act as if the method did not exist (perhaps raising a TypeError, perhaps trying another object’s numeric methods).

Voir aussi

PEP 208 [https://www.python.org/dev/peps/pep-0208] - Reworking the Coercion Model

Written and implemented by Neil Schemenauer, heavily based upon earlier work by Marc-André Lemburg. Read this to understand the fine points of how numeric operations will now be processed at the C level.

PEP 241: Metadata in Python Packages

A common complaint from Python users is that there’s no single catalog of all the Python modules in existence. T. Middleton’s Vaults of Parnassus at http://www.vex.net/parnassus/ are the largest catalog of Python modules, but registering software at the Vaults is optional, and many people don’t bother.

As a first small step toward fixing the problem, Python software packaged using the Distutils sdist command will include a file named PKG-INFO containing information about the package such as its name, version, and author (metadata, in cataloguing terminology). PEP 241 contains the full list of fields that can be present in the PKG-INFO file. As people began to package their software using Python 2.1, more and more packages will include metadata, making it possible to build automated cataloguing systems and experiment with them. With the result experience, perhaps it’ll be possible to design a really good catalog and then build support for it into Python 2.2. For example, the Distutils sdist and bdist_* commands could support an upload option that would automatically upload your package to a catalog server.

You can start creating packages containing PKG-INFO even if you’re not using Python 2.1, since a new release of the Distutils will be made for users of earlier Python versions. Version 1.0.2 of the Distutils includes the changes described in PEP 241, as well as various bugfixes and enhancements. It will be available from the Distutils SIG at https://www.python.org/community/sigs/current/distutils-sig/.

Voir aussi

PEP 241 [https://www.python.org/dev/peps/pep-0241] - Metadata for Python Software Packages

Written and implemented by A.M. Kuchling.

PEP 243 [https://www.python.org/dev/peps/pep-0243] - Module Repository Upload Mechanism

Written by Sean Reifschneider, this draft PEP describes a proposed mechanism for uploading Python packages to a central server.

New and Improved Modules

Ka-Ping Yee contributed two new modules: inspect.py, a module for getting information about live Python code, and pydoc.py, a module for interactively converting docstrings to HTML or text. As a bonus, Tools/scripts/pydoc, which is now automatically installed, uses pydoc.py to display documentation given a Python module, package, or class name. For example, pydoc xml.dom displays the following:

Python Library Documentation: package xml.dom in xml

NAME
    xml.dom - W3C Document Object Model implementation for Python.

FILE
    /usr/local/lib/python2.1/xml/dom/__init__.pyc

DESCRIPTION
    The Python mapping of the Document Object Model is documented in the
    Python Library Reference in the section on the xml.dom package.

    This package contains the following modules:
      ...

pydoc also includes a Tk-based interactive help browser. pydoc quickly becomes addictive; try it out!

Two different modules for unit testing were added to the standard library. The doctest module, contributed by Tim Peters, provides a testing framework based on running embedded examples in docstrings and comparing the results against the expected output. PyUnit, contributed by Steve Purcell, is a unit testing framework inspired by JUnit, which was in turn an adaptation of Kent Beck’s Smalltalk testing framework. See http://pyunit.sourceforge.net/ for more information about PyUnit.

The difflib module contains a class, SequenceMatcher, which compares two sequences and computes the changes required to transform one sequence into the other. For example, this module can be used to write a tool similar to the Unix diff program, and in fact the sample program Tools/scripts/ndiff.py demonstrates how to write such a script.

curses.panel, a wrapper for the panel library, part of ncurses and of SYSV curses, was contributed by Thomas Gellekum. The panel library provides windows with the additional feature of depth. Windows can be moved higher or lower in the depth ordering, and the panel library figures out where panels overlap and which sections are visible.

The PyXML package has gone through a few releases since Python 2.0, and Python 2.1 includes an updated version of the xml package. Some of the noteworthy changes include support for Expat 1.2 and later versions, the ability for Expat parsers to handle files in any encoding supported by Python, and various bugfixes for SAX, DOM, and the minidom module.

Ping also contributed another hook for handling uncaught exceptions. sys.excepthook() can be set to a callable object. When an exception isn’t caught by any try…except blocks, the exception will be passed to sys.excepthook(), which can then do whatever it likes. At the Ninth Python Conference, Ping demonstrated an application for this hook: printing an extended traceback that not only lists the stack frames, but also lists the function arguments and the local variables for each frame.

Various functions in the time module, such as asctime() and localtime(), require a floating point argument containing the time in seconds since the epoch. The most common use of these functions is to work with the current time, so the floating point argument has been made optional; when a value isn’t provided, the current time will be used. For example, log file entries usually need a string containing the current time; in Python 2.1, time.asctime() can be used, instead of the lengthier time.asctime(time.localtime(time.time())) that was previously required.

This change was proposed and implemented by Thomas Wouters.

The ftplib module now defaults to retrieving files in passive mode, because passive mode is more likely to work from behind a firewall. This request came from the Debian bug tracking system, since other Debian packages use ftplib to retrieve files and then don’t work from behind a firewall. It’s deemed unlikely that this will cause problems for anyone, because Netscape defaults to passive mode and few people complain, but if passive mode is unsuitable for your application or network setup, call set_pasv(0) on FTP objects to disable passive mode.

Support for raw socket access has been added to the socket module, contributed by Grant Edwards.

The pstats module now contains a simple interactive statistics browser for displaying timing profiles for Python programs, invoked when the module is run as a script. Contributed by Eric S. Raymond.

A new implementation-dependent function, sys._getframe([depth]), has been added to return a given frame object from the current call stack. sys._getframe() returns the frame at the top of the call stack; if the optional integer argument depth is supplied, the function returns the frame that is depth calls below the top of the stack. For example, sys._getframe(1) returns the caller’s frame object.

This function is only present in CPython, not in Jython or the .NET implementation. Use it for debugging, and resist the temptation to put it into production code.

Autres changements et corrections

There were relatively few smaller changes made in Python 2.1 due to the shorter release cycle. A search through the CVS change logs turns up 117 patches applied, and 136 bugs fixed; both figures are likely to be underestimates. Some of the more notable changes are:

A specialized object allocator is now optionally available, that should be faster than the system malloc() and have less memory overhead. The allocator uses C’s malloc() function to get large pools of memory, and then fulfills smaller memory requests from these pools. It can be enabled by providing the --with-pymalloc option to the configure script; see Objects/obmalloc.c for the implementation details.

Authors of C extension modules should test their code with the object allocator enabled, because some incorrect code may break, causing core dumps at runtime. There are a bunch of memory allocation functions in Python’s C API that have previously been just aliases for the C library’s malloc() and free(), meaning that if you accidentally called mismatched functions, the error wouldn’t be noticeable. When the object allocator is enabled, these functions aren’t aliases of malloc() and free() any more, and calling the wrong function to free memory will get you a core dump. For example, if memory was allocated using PyMem_New(), it has to be freed using PyMem_Del(), not free(). A few modules included with Python fell afoul of this and had to be fixed; doubtless there are more third-party modules that will have the same problem.

The object allocator was contributed by Vladimir Marangozov.

The speed of line-oriented file I/O has been improved because people often complain about its lack of speed, and because it’s often been used as a naïve benchmark. The readline() method of file objects has therefore been rewritten to be much faster. The exact amount of the speedup will vary from platform to platform depending on how slow the C library’s getc() was, but is around 66%, and potentially much faster on some particular operating systems. Tim Peters did much of the benchmarking and coding for this change, motivated by a discussion in comp.lang.python.

A new module and method for file objects was also added, contributed by Jeff Epler. The new method, xreadlines(), is similar to the existing xrange() built-in. xreadlines() returns an opaque sequence object that only supports being iterated over, reading a line on every iteration but not reading the entire file into memory as the existing readlines() method does. You’d use it like this:

for line in sys.stdin.xreadlines():
    # ... do something for each line ...
    ...

For a fuller discussion of the line I/O changes, see the python-dev summary for January 1–15, 2001 at https://mail.python.org/pipermail/python-dev/2001-January/.

A new method, popitem(), was added to dictionaries to enable destructively iterating through the contents of a dictionary; this can be faster for large dictionaries because there’s no need to construct a list containing all the keys or values. D.popitem() removes a random (key, value) pair from the dictionary D and returns it as a 2-tuple. This was implemented mostly by Tim Peters and Guido van Rossum, after a suggestion and preliminary patch by Moshe Zadka.

Modules can now control which names are imported when from module import * is used, by defining an __all__ attribute containing a list of names that will be imported. One common complaint is that if the module imports other modules such as sys or string, from module import * will add them to the importing module’s namespace. To fix this, simply list the public names in __all__:

# List public names
__all__ = ['Database', 'open']

A stricter version of this patch was first suggested and implemented by Ben Wolfson, but after some python-dev discussion, a weaker final version was checked in.

Applying repr() to strings previously used octal escapes for non-printable characters; for example, a newline was '\012'. This was a vestigial trace of Python’s C ancestry, but today octal is of very little practical use. Ka-Ping Yee suggested using hex escapes instead of octal ones, and using the \n, \t, \r escapes for the appropriate characters, and implemented this new formatting.

Syntax errors detected at compile-time can now raise exceptions containing the filename and line number of the error, a pleasant side effect of the compiler reorganization done by Jeremy Hylton.

C extensions which import other modules have been changed to use PyImport_ImportModule(), which means that they will use any import hooks that have been installed. This is also encouraged for third-party extensions that need to import some other module from C code.

The size of the Unicode character database was shrunk by another 340K thanks to Fredrik Lundh.

Some new ports were contributed: MacOS X (by Steven Majewski), Cygwin (by Jason Tishler); RISCOS (by Dietmar Schwertberger); Unixware 7 (by Billy G. Allie).

And there’s the usual list of minor bugfixes, minor memory leaks, docstring edits, and other tweaks, too lengthy to be worth itemizing; see the CVS logs for the full details if you want them.

Remerciements

The author would like to thank the following people for offering suggestions on various drafts of this article: Graeme Cross, David Goodger, Jay Graves, Michael Hudson, Marc-André Lemburg, Fredrik Lundh, Neil Schemenauer, Thomas Wouters.

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Nouveautés de Python 2.0

Auteur

A.M. Kuchling et Moshe Zadka

Introduction

Une nouvelle version de Python, la version 2.0, est sortie le 16 octobre 2000. Cet article traite des nouvelles fonctionnalités intéressantes de cette version, met en évidence d’autres changements utiles, et souligne quelques incompatibilités qui peuvent nécessiter la réécriture du code.

Le développement de Python n’a jamais complètement été arrêté entre chaque versions, et un flux constant de corrections de bogues et d’améliorations ont toujours été soumis. Une foule de corrections mineures, quelques optimisations, des docstrings supplémentaires, et de meilleurs messages d’erreur sont apparus avec l’arrivée de la version 2.0; tous les énumérer serait impossible, mais ils sont certainement significatif. Consultez les journaux CVS publics disponibles pour obtenir la liste complète. Ce progrès est dû aux cinq développeurs travaillant pour PythonLabs qui sont désormais payés pour passer leurs journées à corriger les bugs, mais aussi en raison de l’amélioration de la communication résultant du passage à SourceForge.

À propos de Python 1.6

Python 1.6 peut être vu comme la version des obligations contractuelles. Après que l’équipe de développement eût quitté le CNRI en mai 2000, celui-ci a demandé la création d’une version 1.6, contenant tout le travail sur Python réalisé au CNRI. Python 1.6 représente de ce fait l’état de l’arbre CVS tel qu’il était en mai 2000, la nouvelle fonctionnalité la plus remarquable étant le support d’Unicode. Le développement a continué après mai bien sûr, donc la branche 1.6 a reçu quelques corrections pour être sûr qu’elle soit compatible avec Python 2.0. La version 1.6 fait donc partie de l’évolution de Python, ce n’est pas une branche séparée.

Alors, devriez-vous vous intéresser à Python 1.6 ? Probablement pas. Les versions 1.6final et 2.0beta1 sont sorties le même jour (5 septembre 2000), le plan étant de finaliser Python 2.0 environ un mois plus tard. Si vous avez des applications à maintenir, il n’y a pas vraiment d’intérêt à casser des choses en migrant sur la version 1.6, les réparer, puis avoir de nouveau des choses cassées à peine un mois plus tard en passant à la 2.0; il vaut mieux partir directement de la 2.0. La plupart des fonctionnalités vraiment intéressantes décrites dans ce document sont seulement dans la 2.0, parce que beaucoup de travail a été réalisé entre mai et septembre.

Nouveau processus de développement

The most important change in Python 2.0 may not be to the code at all, but to how Python is developed: in May 2000 the Python developers began using the tools made available by SourceForge for storing source code, tracking bug reports, and managing the queue of patch submissions. To report bugs or submit patches for Python 2.0, use the bug tracking and patch manager tools available from Python’s project page, located at https://sourceforge.net/projects/python/.

The most important of the services now hosted at SourceForge is the Python CVS tree, the version-controlled repository containing the source code for Python. Previously, there were roughly 7 or so people who had write access to the CVS tree, and all patches had to be inspected and checked in by one of the people on this short list. Obviously, this wasn’t very scalable. By moving the CVS tree to SourceForge, it became possible to grant write access to more people; as of September 2000 there were 27 people able to check in changes, a fourfold increase. This makes possible large-scale changes that wouldn’t be attempted if they’d have to be filtered through the small group of core developers. For example, one day Peter Schneider-Kamp took it into his head to drop K&R C compatibility and convert the C source for Python to ANSI C. After getting approval on the python-dev mailing list, he launched into a flurry of checkins that lasted about a week, other developers joined in to help, and the job was done. If there were only 5 people with write access, probably that task would have been viewed as « nice, but not worth the time and effort needed » and it would never have gotten done.

The shift to using SourceForge’s services has resulted in a remarkable increase in the speed of development. Patches now get submitted, commented on, revised by people other than the original submitter, and bounced back and forth between people until the patch is deemed worth checking in. Bugs are tracked in one central location and can be assigned to a specific person for fixing, and we can count the number of open bugs to measure progress. This didn’t come without a cost: developers now have more e-mail to deal with, more mailing lists to follow, and special tools had to be written for the new environment. For example, SourceForge sends default patch and bug notification e-mail messages that are completely unhelpful, so Ka-Ping Yee wrote an HTML screen-scraper that sends more useful messages.

The ease of adding code caused a few initial growing pains, such as code was checked in before it was ready or without getting clear agreement from the developer group. The approval process that has emerged is somewhat similar to that used by the Apache group. Developers can vote +1, +0, -0, or -1 on a patch; +1 and -1 denote acceptance or rejection, while +0 and -0 mean the developer is mostly indifferent to the change, though with a slight positive or negative slant. The most significant change from the Apache model is that the voting is essentially advisory, letting Guido van Rossum, who has Benevolent Dictator For Life status, know what the general opinion is. He can still ignore the result of a vote, and approve or reject a change even if the community disagrees with him.

Producing an actual patch is the last step in adding a new feature, and is usually easy compared to the earlier task of coming up with a good design. Discussions of new features can often explode into lengthy mailing list threads, making the discussion hard to follow, and no one can read every posting to python-dev. Therefore, a relatively formal process has been set up to write Python Enhancement Proposals (PEPs), modelled on the Internet RFC process. PEPs are draft documents that describe a proposed new feature, and are continually revised until the community reaches a consensus, either accepting or rejecting the proposal. Quoting from the introduction to PEP 1, « PEP Purpose and Guidelines »:

PEP stands for Python Enhancement Proposal. A PEP is a design document providing information to the Python community, or describing a new feature for Python. The PEP should provide a concise technical specification of the feature and a rationale for the feature.

We intend PEPs to be the primary mechanisms for proposing new features, for collecting community input on an issue, and for documenting the design decisions that have gone into Python. The PEP author is responsible for building consensus within the community and documenting dissenting opinions.

Read the rest of PEP 1 for the details of the PEP editorial process, style, and format. PEPs are kept in the Python CVS tree on SourceForge, though they’re not part of the Python 2.0 distribution, and are also available in HTML form from https://www.python.org/dev/peps/. As of September 2000, there are 25 PEPS, ranging from PEP 201, « Lockstep Iteration », to PEP 225, « Elementwise/Objectwise Operators ».

Unicode

The largest new feature in Python 2.0 is a new fundamental data type: Unicode strings. Unicode uses 16-bit numbers to represent characters instead of the 8-bit number used by ASCII, meaning that 65,536 distinct characters can be supported.

The final interface for Unicode support was arrived at through countless often-stormy discussions on the python-dev mailing list, and mostly implemented by Marc-André Lemburg, based on a Unicode string type implementation by Fredrik Lundh. A detailed explanation of the interface was written up as PEP 100 [https://www.python.org/dev/peps/pep-0100], « Python Unicode Integration ». This article will simply cover the most significant points about the Unicode interfaces.

In Python source code, Unicode strings are written as u"string". Arbitrary Unicode characters can be written using a new escape sequence, \uHHHH, where HHHH is a 4-digit hexadecimal number from 0000 to FFFF. The existing \xHHHH escape sequence can also be used, and octal escapes can be used for characters up to U+01FF, which is represented by \777.

Unicode strings, just like regular strings, are an immutable sequence type. They can be indexed and sliced, but not modified in place. Unicode strings have an encode( [encoding] ) method that returns an 8-bit string in the desired encoding. Encodings are named by strings, such as 'ascii', 'utf-8', 'iso-8859-1', or whatever. A codec API is defined for implementing and registering new encodings that are then available throughout a Python program. If an encoding isn’t specified, the default encoding is usually 7-bit ASCII, though it can be changed for your Python installation by calling the sys.setdefaultencoding(encoding) function in a customized version of site.py.

Combining 8-bit and Unicode strings always coerces to Unicode, using the default ASCII encoding; the result of 'a' + u'bc' is u'abc'.

De nouvelles fonctions primitives ont été ajoutées, et des fonctions existantes ont été modifiées pour supporter Unicode :

unichr(ch) renvoie une chaîne Unicode de longueur 1, contenant le caractère ch.

ord(u), quand u est une chaîne normale ou Unicode de longueur 1, renvoie un entier représentant le nombre de caractères.

unicode(string [, encoding]  [, errors] ) creates a Unicode string from an 8-bit string. encoding is a string naming the encoding to use. The errors parameter specifies the treatment of characters that are invalid for the current encoding; passing 'strict' as the value causes an exception to be raised on any encoding error, while 'ignore' causes errors to be silently ignored and 'replace' uses U+FFFD, the official replacement character, in case of any problems.

The exec statement, and various built-ins such as eval(), getattr(), and setattr() will also accept Unicode strings as well as regular strings. (It’s possible that the process of fixing this missed some built-ins; if you find a built-in function that accepts strings but doesn’t accept Unicode strings at all, please report it as a bug.)

A new module, unicodedata, provides an interface to Unicode character properties. For example, unicodedata.category(u'A') returns the 2-character string “Lu”, the “L” denoting it’s a letter, and “u” meaning that it’s uppercase. unicodedata.bidirectional(u'\u0660') returns “AN”, meaning that U+0660 is an Arabic number.

The codecs module contains functions to look up existing encodings and register new ones. Unless you want to implement a new encoding, you’ll most often use the codecs.lookup(encoding) function, which returns a 4-element tuple: (encode_func, decode_func, stream_reader, stream_writer).

encode_func is a function that takes a Unicode string, and returns a 2-tuple (string, length). string is an 8-bit string containing a portion (perhaps all) of the Unicode string converted into the given encoding, and length tells you how much of the Unicode string was converted.

decode_func is the opposite of encode_func, taking an 8-bit string and returning a 2-tuple (ustring, length), consisting of the resulting Unicode string ustring and the integer length telling how much of the 8-bit string was consumed.

stream_reader is a class that supports decoding input from a stream. stream_reader(file_obj) returns an object that supports the read(), readline(), and readlines() methods. These methods will all translate from the given encoding and return Unicode strings.

stream_writer, similarly, is a class that supports encoding output to a stream. stream_writer(file_obj) returns an object that supports the write() and writelines() methods. These methods expect Unicode strings, translating them to the given encoding on output.

Par exemple, le code suivant écrit une chaîne Unicode dans un fichier, en l’encodant en UTF-8 :

import codecs

unistr = u'\u0660\u2000ab ...'

(UTF8_encode, UTF8_decode,
 UTF8_streamreader, UTF8_streamwriter) = codecs.lookup('UTF-8')

output = UTF8_streamwriter( open( '/tmp/output', 'wb') )
output.write( unistr )
output.close()

Le code suivant lirait ensuite le texte UTF-8 du fichier :

input = UTF8_streamreader( open( '/tmp/output', 'rb') )
print repr(input.read())
input.close()

Des expressions rationnelles supportant l’Unicode sont disponibles dans le module re, qui a une implémentation sous-jacente appelée SRE écrite par Fredrik Lundh de Secret Labs AB.

A -U command line option was added which causes the Python compiler to interpret all string literals as Unicode string literals. This is intended to be used in testing and future-proofing your Python code, since some future version of Python may drop support for 8-bit strings and provide only Unicode strings.

Compréhensions de listes

Lists are a workhorse data type in Python, and many programs manipulate a list at some point. Two common operations on lists are to loop over them, and either pick out the elements that meet a certain criterion, or apply some function to each element. For example, given a list of strings, you might want to pull out all the strings containing a given substring, or strip off trailing whitespace from each line.

The existing map() and filter() functions can be used for this purpose, but they require a function as one of their arguments. This is fine if there’s an existing built-in function that can be passed directly, but if there isn’t, you have to create a little function to do the required work, and Python’s scoping rules make the result ugly if the little function needs additional information. Take the first example in the previous paragraph, finding all the strings in the list containing a given substring. You could write the following to do it:

# Given the list L, make a list of all strings
# containing the substring S.
sublist = filter( lambda s, substring=S:
                     string.find(s, substring) != -1,
                  L)

Because of Python’s scoping rules, a default argument is used so that the anonymous function created by the lambda statement knows what substring is being searched for. List comprehensions make this cleaner:

sublist = [ s for s in L if string.find(s, S) != -1 ]

Les compréhensions de liste sont de la forme suivante :

[ expression for expr in sequence1
             for expr2 in sequence2 ...
             for exprN in sequenceN
             if condition ]

The for…in clauses contain the sequences to be iterated over. The sequences do not have to be the same length, because they are not iterated over in parallel, but from left to right; this is explained more clearly in the following paragraphs. The elements of the generated list will be the successive values of expression. The final if clause is optional; if present, expression is only evaluated and added to the result if condition is true.

Pour que la sémantique soit très claire, une compréhension de liste est équivalente au code Python suivant :

for expr1 in sequence1:
    for expr2 in sequence2:
    ...
        for exprN in sequenceN:
             if (condition):
                  # Append the value of
                  # the expression to the
                  # resulting list.

This means that when there are multiple for…in clauses, the resulting list will be equal to the product of the lengths of all the sequences. If you have two lists of length 3, the output list is 9 elements long:

seq1 = 'abc'
seq2 = (1,2,3)
>>> [ (x,y) for x in seq1 for y in seq2]
[('a', 1), ('a', 2), ('a', 3), ('b', 1), ('b', 2), ('b', 3), ('c', 1),
('c', 2), ('c', 3)]

To avoid introducing an ambiguity into Python’s grammar, if expression is creating a tuple, it must be surrounded with parentheses. The first list comprehension below is a syntax error, while the second one is correct:

# Syntax error
[ x,y for x in seq1 for y in seq2]
# Correct
[ (x,y) for x in seq1 for y in seq2]

The idea of list comprehensions originally comes from the functional programming language Haskell (https://www.haskell.org). Greg Ewing argued most effectively for adding them to Python and wrote the initial list comprehension patch, which was then discussed for a seemingly endless time on the python-dev mailing list and kept up-to-date by Skip Montanaro.

Augmented Assignment

Augmented assignment operators, another long-requested feature, have been added to Python 2.0. Augmented assignment operators include +=, -=, *=, and so forth. For example, the statement a += 2 increments the value of the variable a by 2, equivalent to the slightly lengthier a = a + 2.

The full list of supported assignment operators is +=, -=, *=, /=, %=, **=, &=, |=, ^=, >>=, and <<=. Python classes can override the augmented assignment operators by defining methods named __iadd__(), __isub__(), etc. For example, the following Number class stores a number and supports using += to create a new instance with an incremented value.

class Number:
    def __init__(self, value):
        self.value = value
    def __iadd__(self, increment):
        return Number( self.value + increment)

n = Number(5)
n += 3
print n.value

The __iadd__() special method is called with the value of the increment, and should return a new instance with an appropriately modified value; this return value is bound as the new value of the variable on the left-hand side.

Augmented assignment operators were first introduced in the C programming language, and most C-derived languages, such as awk, C++, Java, Perl, and PHP also support them. The augmented assignment patch was implemented by Thomas Wouters.

Méthodes de chaînes de caractères

Until now string-manipulation functionality was in the string module, which was usually a front-end for the strop module written in C. The addition of Unicode posed a difficulty for the strop module, because the functions would all need to be rewritten in order to accept either 8-bit or Unicode strings. For functions such as string.replace(), which takes 3 string arguments, that means eight possible permutations, and correspondingly complicated code.

Instead, Python 2.0 pushes the problem onto the string type, making string manipulation functionality available through methods on both 8-bit strings and Unicode strings.

>>> 'andrew'.capitalize()
'Andrew'
>>> 'hostname'.replace('os', 'linux')
'hlinuxtname'
>>> 'moshe'.find('sh')
2

One thing that hasn’t changed, a noteworthy April Fools” joke notwithstanding, is that Python strings are immutable. Thus, the string methods return new strings, and do not modify the string on which they operate.

The old string module is still around for backwards compatibility, but it mostly acts as a front-end to the new string methods.

Two methods which have no parallel in pre-2.0 versions, although they did exist in JPython for quite some time, are startswith() and endswith(). s.startswith(t) is equivalent to s[:len(t)] == t, while s.endswith(t) is equivalent to s[-len(t):] == t.

One other method which deserves special mention is join(). The join() method of a string receives one parameter, a sequence of strings, and is equivalent to the string.join() function from the old string module, with the arguments reversed. In other words, s.join(seq) is equivalent to the old string.join(seq, s).

Garbage Collection of Cycles

The C implementation of Python uses reference counting to implement garbage collection. Every Python object maintains a count of the number of references pointing to itself, and adjusts the count as references are created or destroyed. Once the reference count reaches zero, the object is no longer accessible, since you need to have a reference to an object to access it, and if the count is zero, no references exist any longer.

Reference counting has some pleasant properties: it’s easy to understand and implement, and the resulting implementation is portable, fairly fast, and reacts well with other libraries that implement their own memory handling schemes. The major problem with reference counting is that it sometimes doesn’t realise that objects are no longer accessible, resulting in a memory leak. This happens when there are cycles of references.

Consider the simplest possible cycle, a class instance which has a reference to itself:

instance = SomeClass()
instance.myself = instance

After the above two lines of code have been executed, the reference count of instance is 2; one reference is from the variable named 'instance', and the other is from the myself attribute of the instance.

If the next line of code is del instance, what happens? The reference count of instance is decreased by 1, so it has a reference count of 1; the reference in the myself attribute still exists. Yet the instance is no longer accessible through Python code, and it could be deleted. Several objects can participate in a cycle if they have references to each other, causing all of the objects to be leaked.

Python 2.0 fixes this problem by periodically executing a cycle detection algorithm which looks for inaccessible cycles and deletes the objects involved. A new gc module provides functions to perform a garbage collection, obtain debugging statistics, and tuning the collector’s parameters.

Running the cycle detection algorithm takes some time, and therefore will result in some additional overhead. It is hoped that after we’ve gotten experience with the cycle collection from using 2.0, Python 2.1 will be able to minimize the overhead with careful tuning. It’s not yet obvious how much performance is lost, because benchmarking this is tricky and depends crucially on how often the program creates and destroys objects. The detection of cycles can be disabled when Python is compiled, if you can’t afford even a tiny speed penalty or suspect that the cycle collection is buggy, by specifying the --without-cycle-gc switch when running the configure script.

Several people tackled this problem and contributed to a solution. An early implementation of the cycle detection approach was written by Toby Kelsey. The current algorithm was suggested by Eric Tiedemann during a visit to CNRI, and Guido van Rossum and Neil Schemenauer wrote two different implementations, which were later integrated by Neil. Lots of other people offered suggestions along the way; the March 2000 archives of the python-dev mailing list contain most of the relevant discussion, especially in the threads titled « Reference cycle collection for Python » and « Finalization again ».

Other Core Changes

Various minor changes have been made to Python’s syntax and built-in functions. None of the changes are very far-reaching, but they’re handy conveniences.

Changements mineurs du langage

A new syntax makes it more convenient to call a given function with a tuple of arguments and/or a dictionary of keyword arguments. In Python 1.5 and earlier, you’d use the apply() built-in function: apply(f, args, kw) calls the function f() with the argument tuple args and the keyword arguments in the dictionary kw. apply() is the same in 2.0, but thanks to a patch from Greg Ewing, f(*args, **kw) is a shorter and clearer way to achieve the same effect. This syntax is symmetrical with the syntax for defining functions:

def f(*args, **kw):
    # args is a tuple of positional args,
    # kw is a dictionary of keyword args
    ...

The print statement can now have its output directed to a file-like object by following the print with >> file, similar to the redirection operator in Unix shells. Previously you’d either have to use the write() method of the file-like object, which lacks the convenience and simplicity of print, or you could assign a new value to sys.stdout and then restore the old value. For sending output to standard error, it’s much easier to write this:

print >> sys.stderr, "Warning: action field not supplied"

Modules can now be renamed on importing them, using the syntax import module as name or from module import name as othername. The patch was submitted by Thomas Wouters.

A new format style is available when using the % operator; “%r” will insert the repr() of its argument. This was also added from symmetry considerations, this time for symmetry with the existing “%s” format style, which inserts the str() of its argument. For example, '%r %s' % ('abc', 'abc') returns a string containing 'abc' abc.

Previously there was no way to implement a class that overrode Python’s built-in in operator and implemented a custom version. obj in seq returns true if obj is present in the sequence seq; Python computes this by simply trying every index of the sequence until either obj is found or an IndexError is encountered. Moshe Zadka contributed a patch which adds a __contains__() magic method for providing a custom implementation for in. Additionally, new built-in objects written in C can define what in means for them via a new slot in the sequence protocol.

Earlier versions of Python used a recursive algorithm for deleting objects. Deeply nested data structures could cause the interpreter to fill up the C stack and crash; Christian Tismer rewrote the deletion logic to fix this problem. On a related note, comparing recursive objects recursed infinitely and crashed; Jeremy Hylton rewrote the code to no longer crash, producing a useful result instead. For example, after this code:

a = []
b = []
a.append(a)
b.append(b)

The comparison a==b returns true, because the two recursive data structures are isomorphic. See the thread « trashcan and PR#7 » in the April 2000 archives of the python-dev mailing list for the discussion leading up to this implementation, and some useful relevant links. Note that comparisons can now also raise exceptions. In earlier versions of Python, a comparison operation such as cmp(a,b) would always produce an answer, even if a user-defined __cmp__() method encountered an error, since the resulting exception would simply be silently swallowed.

Work has been done on porting Python to 64-bit Windows on the Itanium processor, mostly by Trent Mick of ActiveState. (Confusingly, sys.platform is still 'win32' on Win64 because it seems that for ease of porting, MS Visual C++ treats code as 32 bit on Itanium.) PythonWin also supports Windows CE; see the Python CE page at http://pythonce.sourceforge.net/ for more information.

Another new platform is Darwin/MacOS X; initial support for it is in Python 2.0. Dynamic loading works, if you specify « configure –with-dyld –with-suffix=.x ». Consult the README in the Python source distribution for more instructions.

An attempt has been made to alleviate one of Python’s warts, the often-confusing NameError exception when code refers to a local variable before the variable has been assigned a value. For example, the following code raises an exception on the print statement in both 1.5.2 and 2.0; in 1.5.2 a NameError exception is raised, while 2.0 raises a new UnboundLocalError exception. UnboundLocalError is a subclass of NameError, so any existing code that expects NameError to be raised should still work.

def f():
    print "i=",i
    i = i + 1
f()

Two new exceptions, TabError and IndentationError, have been introduced. They’re both subclasses of SyntaxError, and are raised when Python code is found to be improperly indented.

Changements concernant les fonctions primitives

A new built-in, zip(seq1, seq2, ...), has been added. zip() returns a list of tuples where each tuple contains the i-th element from each of the argument sequences. The difference between zip() and map(None, seq1, seq2) is that map() pads the sequences with None if the sequences aren’t all of the same length, while zip() truncates the returned list to the length of the shortest argument sequence.

The int() and long() functions now accept an optional « base » parameter when the first argument is a string. int('123', 10) returns 123, while int('123', 16) returns 291. int(123, 16) raises a TypeError exception with the message « can’t convert non-string with explicit base ».

A new variable holding more detailed version information has been added to the sys module. sys.version_info is a tuple (major, minor, micro, level, serial) For example, in a hypothetical 2.0.1beta1, sys.version_info would be (2, 0, 1, 'beta', 1). level is a string such as "alpha", "beta", or "final" for a final release.

Dictionaries have an odd new method, setdefault(key, default), which behaves similarly to the existing get() method. However, if the key is missing, setdefault() both returns the value of default as get() would do, and also inserts it into the dictionary as the value for key. Thus, the following lines of code:

if dict.has_key( key ): return dict[key]
else:
    dict[key] = []
    return dict[key]

can be reduced to a single return dict.setdefault(key, []) statement.

The interpreter sets a maximum recursion depth in order to catch runaway recursion before filling the C stack and causing a core dump or GPF.. Previously this limit was fixed when you compiled Python, but in 2.0 the maximum recursion depth can be read and modified using sys.getrecursionlimit() and sys.setrecursionlimit(). The default value is 1000, and a rough maximum value for a given platform can be found by running a new script, Misc/find_recursionlimit.py.

Porting to 2.0

New Python releases try hard to be compatible with previous releases, and the record has been pretty good. However, some changes are considered useful enough, usually because they fix initial design decisions that turned out to be actively mistaken, that breaking backward compatibility can’t always be avoided. This section lists the changes in Python 2.0 that may cause old Python code to break.

The change which will probably break the most code is tightening up the arguments accepted by some methods. Some methods would take multiple arguments and treat them as a tuple, particularly various list methods such as append() and insert(). In earlier versions of Python, if L is a list, L.append( 1,2 ) appends the tuple (1,2) to the list. In Python 2.0 this causes a TypeError exception to be raised, with the message: “append requires exactly 1 argument; 2 given”. The fix is to simply add an extra set of parentheses to pass both values as a tuple: L.append( (1,2) ).

The earlier versions of these methods were more forgiving because they used an old function in Python’s C interface to parse their arguments; 2.0 modernizes them to use PyArg_ParseTuple(), the current argument parsing function, which provides more helpful error messages and treats multi-argument calls as errors. If you absolutely must use 2.0 but can’t fix your code, you can edit Objects/listobject.c and define the preprocessor symbol NO_STRICT_LIST_APPEND to preserve the old behaviour; this isn’t recommended.

Some of the functions in the socket module are still forgiving in this way. For example, socket.connect( ('hostname', 25) )() is the correct form, passing a tuple representing an IP address, but socket.connect( 'hostname', 25 )() also works. socket.connect_ex() and socket.bind() are similarly easy-going. 2.0alpha1 tightened these functions up, but because the documentation actually used the erroneous multiple argument form, many people wrote code which would break with the stricter checking. GvR backed out the changes in the face of public reaction, so for the socket module, the documentation was fixed and the multiple argument form is simply marked as deprecated; it will be tightened up again in a future Python version.

The \x escape in string literals now takes exactly 2 hex digits. Previously it would consume all the hex digits following the “x” and take the lowest 8 bits of the result, so \x123456 was equivalent to \x56.

The AttributeError and NameError exceptions have a more friendly error message, whose text will be something like 'Spam' instance has no attribute 'eggs' or name 'eggs' is not defined. Previously the error message was just the missing attribute name eggs, and code written to take advantage of this fact will break in 2.0.

Some work has been done to make integers and long integers a bit more interchangeable. In 1.5.2, large-file support was added for Solaris, to allow reading files larger than 2 GiB; this made the tell() method of file objects return a long integer instead of a regular integer. Some code would subtract two file offsets and attempt to use the result to multiply a sequence or slice a string, but this raised a TypeError. In 2.0, long integers can be used to multiply or slice a sequence, and it’ll behave as you’d intuitively expect it to; 3L * 'abc' produces “abcabcabc”, and (0,1,2,3)[2L:4L] produces (2,3). Long integers can also be used in various contexts where previously only integers were accepted, such as in the seek() method of file objects, and in the formats supported by the % operator (%d, %i, %x, etc.). For example, "%d" % 2L**64 will produce the string 18446744073709551616.

The subtlest long integer change of all is that the str() of a long integer no longer has a trailing “L” character, though repr() still includes it. The “L” annoyed many people who wanted to print long integers that looked just like regular integers, since they had to go out of their way to chop off the character. This is no longer a problem in 2.0, but code which does str(longval)[:-1] and assumes the “L” is there, will now lose the final digit.

Taking the repr() of a float now uses a different formatting precision than str(). repr() uses %.17g format string for C’s sprintf(), while str() uses %.12g as before. The effect is that repr() may occasionally show more decimal places than str(), for certain numbers. For example, the number 8.1 can’t be represented exactly in binary, so repr(8.1) is '8.0999999999999996', while str(8.1) is '8.1'.

The -X command-line option, which turned all standard exceptions into strings instead of classes, has been removed; the standard exceptions will now always be classes. The exceptions module containing the standard exceptions was translated from Python to a built-in C module, written by Barry Warsaw and Fredrik Lundh.

Extending/Embedding Changes

Some of the changes are under the covers, and will only be apparent to people writing C extension modules or embedding a Python interpreter in a larger application. If you aren’t dealing with Python’s C API, you can safely skip this section.

The version number of the Python C API was incremented, so C extensions compiled for 1.5.2 must be recompiled in order to work with 2.0. On Windows, it’s not possible for Python 2.0 to import a third party extension built for Python 1.5.x due to how Windows DLLs work, so Python will raise an exception and the import will fail.

Users of Jim Fulton’s ExtensionClass module will be pleased to find out that hooks have been added so that ExtensionClasses are now supported by isinstance() and issubclass(). This means you no longer have to remember to write code such as if type(obj) == myExtensionClass, but can use the more natural if isinstance(obj, myExtensionClass).

The Python/importdl.c file, which was a mass of #ifdefs to support dynamic loading on many different platforms, was cleaned up and reorganised by Greg Stein. importdl.c is now quite small, and platform-specific code has been moved into a bunch of Python/dynload_*.c files. Another cleanup: there were also a number of my*.h files in the Include/ directory that held various portability hacks; they’ve been merged into a single file, Include/pyport.h.

Vladimir Marangozov’s long-awaited malloc restructuring was completed, to make it easy to have the Python interpreter use a custom allocator instead of C’s standard malloc(). For documentation, read the comments in Include/pymem.h and Include/objimpl.h. For the lengthy discussions during which the interface was hammered out, see the Web archives of the “patches” and “python-dev” lists at python.org.

Recent versions of the GUSI development environment for MacOS support POSIX threads. Therefore, Python’s POSIX threading support now works on the Macintosh. Threading support using the user-space GNU pth library was also contributed.

Threading support on Windows was enhanced, too. Windows supports thread locks that use kernel objects only in case of contention; in the common case when there’s no contention, they use simpler functions which are an order of magnitude faster. A threaded version of Python 1.5.2 on NT is twice as slow as an unthreaded version; with the 2.0 changes, the difference is only 10%. These improvements were contributed by Yakov Markovitch.

Python 2.0’s source now uses only ANSI C prototypes, so compiling Python now requires an ANSI C compiler, and can no longer be done using a compiler that only supports K&R C.

Previously the Python virtual machine used 16-bit numbers in its bytecode, limiting the size of source files. In particular, this affected the maximum size of literal lists and dictionaries in Python source; occasionally people who are generating Python code would run into this limit. A patch by Charles G. Waldman raises the limit from 2^16 to 2^{32}.

Three new convenience functions intended for adding constants to a module’s dictionary at module initialization time were added: PyModule_AddObject(), PyModule_AddIntConstant(), and PyModule_AddStringConstant(). Each of these functions takes a module object, a null-terminated C string containing the name to be added, and a third argument for the value to be assigned to the name. This third argument is, respectively, a Python object, a C long, or a C string.

A wrapper API was added for Unix-style signal handlers. PyOS_getsig() gets a signal handler and PyOS_setsig() will set a new handler.

Distutils: Making Modules Easy to Install

Before Python 2.0, installing modules was a tedious affair – there was no way to figure out automatically where Python is installed, or what compiler options to use for extension modules. Software authors had to go through an arduous ritual of editing Makefiles and configuration files, which only really work on Unix and leave Windows and MacOS unsupported. Python users faced wildly differing installation instructions which varied between different extension packages, which made administering a Python installation something of a chore.

The SIG for distribution utilities, shepherded by Greg Ward, has created the Distutils, a system to make package installation much easier. They form the distutils package, a new part of Python’s standard library. In the best case, installing a Python module from source will require the same steps: first you simply mean unpack the tarball or zip archive, and the run « python setup.py install ». The platform will be automatically detected, the compiler will be recognized, C extension modules will be compiled, and the distribution installed into the proper directory. Optional command-line arguments provide more control over the installation process, the distutils package offers many places to override defaults – separating the build from the install, building or installing in non-default directories, and more.

In order to use the Distutils, you need to write a setup.py script. For the simple case, when the software contains only .py files, a minimal setup.py can be just a few lines long:

from distutils.core import setup
setup (name = "foo", version = "1.0",
       py_modules = ["module1", "module2"])

The setup.py file isn’t much more complicated if the software consists of a few packages:

from distutils.core import setup
setup (name = "foo", version = "1.0",
       packages = ["package", "package.subpackage"])

A C extension can be the most complicated case; here’s an example taken from the PyXML package:

from distutils.core import setup, Extension

expat_extension = Extension('xml.parsers.pyexpat',
     define_macros = [('XML_NS', None)],
     include_dirs = [ 'extensions/expat/xmltok',
                      'extensions/expat/xmlparse' ],
     sources = [ 'extensions/pyexpat.c',
                 'extensions/expat/xmltok/xmltok.c',
                 'extensions/expat/xmltok/xmlrole.c', ]
       )
setup (name = "PyXML", version = "0.5.4",
       ext_modules =[ expat_extension ] )

The Distutils can also take care of creating source and binary distributions. The « sdist » command, run by « python setup.py sdist”, builds a source distribution such as foo-1.0.tar.gz. Adding new commands isn’t difficult, « bdist_rpm » and « bdist_wininst » commands have already been contributed to create an RPM distribution and a Windows installer for the software, respectively. Commands to create other distribution formats such as Debian packages and Solaris .pkg files are in various stages of development.

All this is documented in a new manual, Distributing Python Modules, that joins the basic set of Python documentation.

Modules XML

Python 1.5.2 included a simple XML parser in the form of the xmllib module, contributed by Sjoerd Mullender. Since 1.5.2’s release, two different interfaces for processing XML have become common: SAX2 (version 2 of the Simple API for XML) provides an event-driven interface with some similarities to xmllib, and the DOM (Document Object Model) provides a tree-based interface, transforming an XML document into a tree of nodes that can be traversed and modified. Python 2.0 includes a SAX2 interface and a stripped-down DOM interface as part of the xml package. Here we will give a brief overview of these new interfaces; consult the Python documentation or the source code for complete details. The Python XML SIG is also working on improved documentation.

Support de SAX2

SAX defines an event-driven interface for parsing XML. To use SAX, you must write a SAX handler class. Handler classes inherit from various classes provided by SAX, and override various methods that will then be called by the XML parser. For example, the startElement() and endElement() methods are called for every starting and end tag encountered by the parser, the characters() method is called for every chunk of character data, and so forth.

The advantage of the event-driven approach is that the whole document doesn’t have to be resident in memory at any one time, which matters if you are processing really huge documents. However, writing the SAX handler class can get very complicated if you’re trying to modify the document structure in some elaborate way.

For example, this little example program defines a handler that prints a message for every starting and ending tag, and then parses the file hamlet.xml using it:

from xml import sax

class SimpleHandler(sax.ContentHandler):
    def startElement(self, name, attrs):
        print 'Start of element:', name, attrs.keys()

    def endElement(self, name):
        print 'End of element:', name

# Create a parser object
parser = sax.make_parser()

# Tell it what handler to use
handler = SimpleHandler()
parser.setContentHandler( handler )

# Parse a file!
parser.parse( 'hamlet.xml' )

For more information, consult the Python documentation, or the XML HOWTO at http://pyxml.sourceforge.net/topics/howto/xml-howto.html.

Support du DOM

The Document Object Model is a tree-based representation for an XML document. A top-level Document instance is the root of the tree, and has a single child which is the top-level Element instance. This Element has children nodes representing character data and any sub-elements, which may have further children of their own, and so forth. Using the DOM you can traverse the resulting tree any way you like, access element and attribute values, insert and delete nodes, and convert the tree back into XML.

The DOM is useful for modifying XML documents, because you can create a DOM tree, modify it by adding new nodes or rearranging subtrees, and then produce a new XML document as output. You can also construct a DOM tree manually and convert it to XML, which can be a more flexible way of producing XML output than simply writing <tag1>…</tag1> to a file.

The DOM implementation included with Python lives in the xml.dom.minidom module. It’s a lightweight implementation of the Level 1 DOM with support for XML namespaces. The parse() and parseString() convenience functions are provided for generating a DOM tree:

from xml.dom import minidom
doc = minidom.parse('hamlet.xml')

doc is a Document instance. Document, like all the other DOM classes such as Element and Text, is a subclass of the Node base class. All the nodes in a DOM tree therefore support certain common methods, such as toxml() which returns a string containing the XML representation of the node and its children. Each class also has special methods of its own; for example, Element and Document instances have a method to find all child elements with a given tag name. Continuing from the previous 2-line example:

perslist = doc.getElementsByTagName( 'PERSONA' )
print perslist[0].toxml()
print perslist[1].toxml()

For the Hamlet XML file, the above few lines output:

<PERSONA>CLAUDIUS, king of Denmark. </PERSONA>
<PERSONA>HAMLET, son to the late, and nephew to the present king.</PERSONA>

The root element of the document is available as doc.documentElement, and its children can be easily modified by deleting, adding, or removing nodes:

root = doc.documentElement

# Remove the first child
root.removeChild( root.childNodes[0] )

# Move the new first child to the end
root.appendChild( root.childNodes[0] )

# Insert the new first child (originally,
# the third child) before the 20th child.
root.insertBefore( root.childNodes[0], root.childNodes[20] )

Again, I will refer you to the Python documentation for a complete listing of the different Node classes and their various methods.

Relationship to PyXML

The XML Special Interest Group has been working on XML-related Python code for a while. Its code distribution, called PyXML, is available from the SIG’s Web pages at https://www.python.org/community/sigs/current/xml-sig. The PyXML distribution also used the package name xml. If you’ve written programs that used PyXML, you’re probably wondering about its compatibility with the 2.0 xml package.

The answer is that Python 2.0’s xml package isn’t compatible with PyXML, but can be made compatible by installing a recent version PyXML. Many applications can get by with the XML support that is included with Python 2.0, but more complicated applications will require that the full PyXML package will be installed. When installed, PyXML versions 0.6.0 or greater will replace the xml package shipped with Python, and will be a strict superset of the standard package, adding a bunch of additional features. Some of the additional features in PyXML include:

4DOM, a full DOM implementation from FourThought, Inc.

The xmlproc validating parser, written by Lars Marius Garshol.

The sgmlop parser accelerator module, written by Fredrik Lundh.

Module changes

Lots of improvements and bugfixes were made to Python’s extensive standard library; some of the affected modules include readline, ConfigParser, cgi, calendar, posix, readline, xmllib, aifc, chunk, wave, random, shelve, and nntplib. Consult the CVS logs for the exact patch-by-patch details.

Brian Gallew contributed OpenSSL support for the socket module. OpenSSL is an implementation of the Secure Socket Layer, which encrypts the data being sent over a socket. When compiling Python, you can edit Modules/Setup to include SSL support, which adds an additional function to the socket module: socket.ssl(socket, keyfile, certfile), which takes a socket object and returns an SSL socket. The httplib and urllib modules were also changed to support https:// URLs, though no one has implemented FTP or SMTP over SSL.

The httplib module has been rewritten by Greg Stein to support HTTP/1.1. Backward compatibility with the 1.5 version of httplib is provided, though using HTTP/1.1 features such as pipelining will require rewriting code to use a different set of interfaces.

The Tkinter module now supports Tcl/Tk version 8.1, 8.2, or 8.3, and support for the older 7.x versions has been dropped. The Tkinter module now supports displaying Unicode strings in Tk widgets. Also, Fredrik Lundh contributed an optimization which makes operations like create_line and create_polygon much faster, especially when using lots of coordinates.

The curses module has been greatly extended, starting from Oliver Andrich’s enhanced version, to provide many additional functions from ncurses and SYSV curses, such as colour, alternative character set support, pads, and mouse support. This means the module is no longer compatible with operating systems that only have BSD curses, but there don’t seem to be any currently maintained OSes that fall into this category.

As mentioned in the earlier discussion of 2.0’s Unicode support, the underlying implementation of the regular expressions provided by the re module has been changed. SRE, a new regular expression engine written by Fredrik Lundh and partially funded by Hewlett Packard, supports matching against both 8-bit strings and Unicode strings.

Nouveaux modules

A number of new modules were added. We’ll simply list them with brief descriptions; consult the 2.0 documentation for the details of a particular module.

atexit: For registering functions to be called before the Python interpreter exits. Code that currently sets sys.exitfunc directly should be changed to use the atexit module instead, importing atexit and calling atexit.register() with the function to be called on exit. (Contributed by Skip Montanaro.)

codecs, encodings, unicodedata: Added as part of the new Unicode support.

filecmp: Supersedes the old cmp, cmpcache and dircmp modules, which have now become deprecated. (Contributed by Gordon MacMillan and Moshe Zadka.)

gettext: This module provides internationalization (I18N) and localization (L10N) support for Python programs by providing an interface to the GNU gettext message catalog library. (Integrated by Barry Warsaw, from separate contributions by Martin von Löwis, Peter Funk, and James Henstridge.)

linuxaudiodev: Support for the /dev/audio device on Linux, a twin to the existing sunaudiodev module. (Contributed by Peter Bosch, with fixes by Jeremy Hylton.)

mmap: An interface to memory-mapped files on both Windows and Unix. A file’s contents can be mapped directly into memory, at which point it behaves like a mutable string, so its contents can be read and modified. They can even be passed to functions that expect ordinary strings, such as the re module. (Contributed by Sam Rushing, with some extensions by A.M. Kuchling.)

pyexpat: An interface to the Expat XML parser. (Contributed by Paul Prescod.)

robotparser: Parse a robots.txt file, which is used for writing Web spiders that politely avoid certain areas of a Web site. The parser accepts the contents of a robots.txt file, builds a set of rules from it, and can then answer questions about the fetchability of a given URL. (Contributed by Skip Montanaro.)

tabnanny: A module/script to check Python source code for ambiguous indentation. (Contributed by Tim Peters.)

UserString: A base class useful for deriving objects that behave like strings.

webbrowser: A module that provides a platform independent way to launch a web browser on a specific URL. For each platform, various browsers are tried in a specific order. The user can alter which browser is launched by setting the BROWSER environment variable. (Originally inspired by Eric S. Raymond’s patch to urllib which added similar functionality, but the final module comes from code originally implemented by Fred Drake as Tools/idle/BrowserControl.py, and adapted for the standard library by Fred.)

_winreg: An interface to the Windows registry. _winreg is an adaptation of functions that have been part of PythonWin since 1995, but has now been added to the core distribution, and enhanced to support Unicode. _winreg was written by Bill Tutt and Mark Hammond.

zipfile: A module for reading and writing ZIP-format archives. These are archives produced by PKZIP on DOS/Windows or zip on Unix, not to be confused with gzip-format files (which are supported by the gzip module) (Contributed by James C. Ahlstrom.)

imputil: A module that provides a simpler way for writing customized import hooks, in comparison to the existing ihooks module. (Implemented by Greg Stein, with much discussion on python-dev along the way.)

IDLE Improvements

IDLE is the official Python cross-platform IDE, written using Tkinter. Python 2.0 includes IDLE 0.6, which adds a number of new features and improvements. A partial list:

UI improvements and optimizations, especially in the area of syntax highlighting and auto-indentation.

The class browser now shows more information, such as the top level functions in a module.

Tab width is now a user settable option. When opening an existing Python file, IDLE automatically detects the indentation conventions, and adapts.

There is now support for calling browsers on various platforms, used to open the Python documentation in a browser.

IDLE now has a command line, which is largely similar to the vanilla Python interpreter.

Call tips were added in many places.

IDLE can now be installed as a package.

In the editor window, there is now a line/column bar at the bottom.

Three new keystroke commands: Check module (Alt-F5), Import module (F5) and Run script (Ctrl-F5).

Deleted and Deprecated Modules

A few modules have been dropped because they’re obsolete, or because there are now better ways to do the same thing. The stdwin module is gone; it was for a platform-independent windowing toolkit that’s no longer developed.

A number of modules have been moved to the lib-old subdirectory: cmp, cmpcache, dircmp, dump, find, grep, packmail, poly, util, whatsound, zmod. If you have code which relies on a module that’s been moved to lib-old, you can simply add that directory to sys.path to get them back, but you’re encouraged to update any code that uses these modules.

Remerciements

The authors would like to thank the following people for offering suggestions on various drafts of this article: David Bolen, Mark Hammond, Gregg Hauser, Jeremy Hylton, Fredrik Lundh, Detlef Lannert, Aahz Maruch, Skip Montanaro, Vladimir Marangozov, Tobias Polzin, Guido van Rossum, Neil Schemenauer, and Russ Schmidt.

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Changements

Python 3.6.11 final

Release date: 2020-06-27

There were no new changes in version 3.6.11.

Python 3.6.11 release candidate 1

Release date: 2020-06-17

Security

bpo-39073 [https://bugs.python.org/issue39073]: Disallow CR or LF in email.headerregistry.Address arguments to guard against header injection attacks.

bpo-38576 [https://bugs.python.org/issue38576]: Disallow control characters in hostnames in http.client, addressing CVE-2019-18348. Such potentially malicious header injection URLs now cause a InvalidURL to be raised.

bpo-39503 [https://bugs.python.org/issue39503]: CVE-2020-8492: The AbstractBasicAuthHandler class of the urllib.request module uses an inefficient regular expression which can be exploited by an attacker to cause a denial of service. Fix the regex to prevent the catastrophic backtracking. Vulnerability reported by Ben Caller and Matt Schwager.

bpo-39401 [https://bugs.python.org/issue39401]: Avoid unsafe load of api-ms-win-core-path-l1-1-0.dll at startup on Windows 7.

Core and Builtins

bpo-39510 [https://bugs.python.org/issue39510]: Fix segfault in readinto() method on closed BufferedReader.

bpo-39421 [https://bugs.python.org/issue39421]: Fix possible crashes when operating with the functions in the heapq module and custom comparison operators.

Library

bpo-39503 [https://bugs.python.org/issue39503]: AbstractBasicAuthHandler of urllib.request now parses all WWW-Authenticate HTTP headers and accepts multiple challenges per header: use the realm of the first Basic challenge.

Python 3.6.10 final

Release date: 2019-12-18

macOS

bpo-38295 [https://bugs.python.org/issue38295]: Prevent failure of test_relative_path in test_py_compile on macOS Catalina.

Python 3.6.10 release candidate 1

Release date: 2019-12-11

Security

bpo-38945 [https://bugs.python.org/issue38945]: Newline characters have been escaped when performing uu encoding to prevent them from overflowing into to content section of the encoded file. This prevents malicious or accidental modification of data during the decoding process.

bpo-37228 [https://bugs.python.org/issue37228]: Due to significant security concerns, the reuse_address parameter of asyncio.loop.create_datagram_endpoint() is no longer supported. This is because of the behavior of SO_REUSEADDR in UDP. For more details, see the documentation for loop.create_datagram_endpoint(). (Contributed by Kyle Stanley, Antoine Pitrou, and Yury Selivanov in bpo-37228 [https://bugs.python.org/issue37228].)

bpo-38804 [https://bugs.python.org/issue38804]: Fixes a ReDoS vulnerability in http.cookiejar. Patch by Ben Caller.

bpo-38243 [https://bugs.python.org/issue38243]: Escape the server title of xmlrpc.server.DocXMLRPCServer when rendering the document page as HTML. (Contributed by Dong-hee Na in bpo-38243 [https://bugs.python.org/issue38243].)

bpo-38174 [https://bugs.python.org/issue38174]: Update vendorized expat library version to 2.2.8, which resolves CVE-2019-15903.

bpo-37461 [https://bugs.python.org/issue37461]: Fix an infinite loop when parsing specially crafted email headers. Patch by Abhilash Raj.

bpo-34155 [https://bugs.python.org/issue34155]: Fix parsing of invalid email addresses with more than one @ (e.g. a@b@c.com.) to not return the part before 2nd @ as valid email address. Patch by maxking & jpic.

Library

bpo-38216 [https://bugs.python.org/issue38216]: Allow the rare code that wants to send invalid http requests from the http.client library a way to do so. The fixes for bpo-30458 [https://bugs.python.org/issue30458] led to breakage for some projects that were relying on this ability to test their own behavior in the face of bad requests.

bpo-36564 [https://bugs.python.org/issue36564]: Fix infinite loop in email header folding logic that would be triggered when an email policy’s max_line_length is not long enough to include the required markup and any values in the message. Patch by Paul Ganssle

Python 3.6.9 final

Release date: 2019-07-02

Library

bpo-37437 [https://bugs.python.org/issue37437]: Update vendorized expat version to 2.2.7.

macOS

bpo-34602 [https://bugs.python.org/issue34602]: Avoid test suite failures on macOS by no longer calling resource.setrlimit to increase the process stack size limit at runtime. The runtime change is no longer needed since the interpreter is being built with a larger default stack size.

Python 3.6.9 release candidate 1

Release date: 2019-06-18

Security

bpo-35907 [https://bugs.python.org/issue35907]: CVE-2019-9948: Avoid file reading by disallowing local-file:// and local_file:// URL schemes in URLopener().open() and URLopener().retrieve() of urllib.request.

bpo-36742 [https://bugs.python.org/issue36742]: Fixes mishandling of pre-normalization characters in urlsplit().

bpo-30458 [https://bugs.python.org/issue30458]: Address CVE-2019-9740 by disallowing URL paths with embedded whitespace or control characters through into the underlying http client request. Such potentially malicious header injection URLs now cause an http.client.InvalidURL exception to be raised.

bpo-36216 [https://bugs.python.org/issue36216]: Changes urlsplit() to raise ValueError when the URL contains characters that decompose under IDNA encoding (NFKC-normalization) into characters that affect how the URL is parsed.

bpo-33529 [https://bugs.python.org/issue33529]: Prevent fold function used in email header encoding from entering infinite loop when there are too many non-ASCII characters in a header.

bpo-35746 [https://bugs.python.org/issue35746]: [CVE-2019-5010] Fix a NULL pointer deref in ssl module. The cert parser did not handle CRL distribution points with empty DP or URI correctly. A malicious or buggy certificate can result into segfault. Vulnerability (TALOS-2018-0758) reported by Colin Read and Nicolas Edet of Cisco.

bpo-35121 [https://bugs.python.org/issue35121]: Don’t send cookies of domain A without Domain attribute to domain B when domain A is a suffix match of domain B while using a cookiejar with http.cookiejar.DefaultCookiePolicy policy. Patch by Karthikeyan Singaravelan.

Library

bpo-35643 [https://bugs.python.org/issue35643]: Fixed a SyntaxWarning: invalid escape sequence in Modules/_sha3/cleanup.py. Patch by Mickaël Schoentgen.

bpo-35121 [https://bugs.python.org/issue35121]: Don’t set cookie for a request when the request path is a prefix match of the cookie’s path attribute but doesn’t end with « / ». Patch by Karthikeyan Singaravelan.

Documentation

bpo-35605 [https://bugs.python.org/issue35605]: Fix documentation build for sphinx<1.6. Patch by Anthony Sottile.

bpo-35564 [https://bugs.python.org/issue35564]: Explicitly set master_doc variable in conf.py for compliance with Sphinx 2.0

Tests

bpo-36816 [https://bugs.python.org/issue36816]: Update Lib/test/selfsigned_pythontestdotnet.pem to match self-signed.pythontest.net’s new TLS certificate.

bpo-35925 [https://bugs.python.org/issue35925]: Skip specific nntplib and ssl networking tests when they would otherwise fail due to a modern OS or distro with a default OpenSSL policy of rejecting connections to servers with weak certificates or disabling TLS below TLSv1.2.

bpo-27313 [https://bugs.python.org/issue27313]: Avoid test_ttk_guionly ComboboxTest failure with macOS Cocoa Tk.

bpo-32947 [https://bugs.python.org/issue32947]: test_ssl fixes for TLS 1.3 and OpenSSL 1.1.1.

macOS

bpo-34602 [https://bugs.python.org/issue34602]: Avoid failures setting macOS stack resource limit with resource.setrlimit. This reverts an earlier fix for bpo-18075 [https://bugs.python.org/issue18075] which forced a non-default stack size when building the interpreter executable on macOS.

Python 3.6.8 final

Release date: 2018-12-23

Library

bpo-31715 [https://bugs.python.org/issue31715]: Associate .mjs file extension with application/javascript MIME Type.

Build

bpo-35499 [https://bugs.python.org/issue35499]: make profile-opt no longer replaces CFLAGS_NODIST with CFLAGS. It now adds profile-guided optimization (PGO) flags to CFLAGS_NODIST: existing CFLAGS_NODIST flags are kept.

bpo-35257 [https://bugs.python.org/issue35257]: Avoid leaking the linker flags from Link Time Optimizations (LTO) into distutils when compiling C extensions.

C API

bpo-35259 [https://bugs.python.org/issue35259]: Conditionally declare Py_FinalizeEx() (new in 3.6) based on Py_LIMITED_API. Patch by Arthur Neufeld.

Python 3.6.8 release candidate 1

Release date: 2018-12-11

Security

bpo-34812 [https://bugs.python.org/issue34812]: The -I command line option (run Python in isolated mode) is now also copied by the multiprocessing and distutils modules when spawning child processes. Previously, only -E and -s options (enabled by -I) were copied.

bpo-34791 [https://bugs.python.org/issue34791]: The xml.sax and xml.dom.domreg no longer use environment variables to override parser implementations when sys.flags.ignore_environment is set by -E or -I arguments.

Core and Builtins

bpo-35444 [https://bugs.python.org/issue35444]: Fixed error handling in pickling methods when fail to look up builtin « getattr ».

bpo-35436 [https://bugs.python.org/issue35436]: Fix various issues with memory allocation error handling. Patch by Zackery Spytz.

bpo-35357 [https://bugs.python.org/issue35357]: Internal attributes” names of unittest.mock._Call and unittest.mock.MagicProxy (name, parent & from_kall) are now prefixed with _mock_ in order to prevent clashes with widely used object attributes. Fixed minor typo in test function name.

bpo-35372 [https://bugs.python.org/issue35372]: Fixed the code page decoder for input longer than 2 GiB containing undecodable bytes.

bpo-33954 [https://bugs.python.org/issue33954]: For str.format(), float.__format__() and complex.__format__() methods for non-ASCII decimal point when using the « n » formatter.

bpo-35214 [https://bugs.python.org/issue35214]: Fixed an out of bounds memory access when parsing a truncated unicode escape sequence at the end of a string such as '\N'. It would read one byte beyond the end of the memory allocation.

bpo-35214 [https://bugs.python.org/issue35214]: The interpreter and extension modules have had annotations added so that they work properly under clang’s Memory Sanitizer. A new configure flag –with-memory-sanitizer has been added to make test builds of this nature easier to perform.

bpo-35193 [https://bugs.python.org/issue35193]: Fix an off by one error in the bytecode peephole optimizer where it could read bytes beyond the end of bounds of an array when removing unreachable code. This bug was present in every release of Python 3.6 until now.

bpo-29341 [https://bugs.python.org/issue29341]: Clarify in the docstrings of os methods that path-like objects are also accepted as input parameters.

bpo-35050 [https://bugs.python.org/issue35050]: socket: Fix off-by-one bug in length check for AF_ALG name and type.

bpo-34974 [https://bugs.python.org/issue34974]: bytes and bytearray constructors no longer convert unexpected exceptions (e.g. MemoryError and KeyboardInterrupt) to TypeError.

bpo-34973 [https://bugs.python.org/issue34973]: Fixed crash in bytes() when the list argument is mutated while it is iterated.

bpo-34824 [https://bugs.python.org/issue34824]: Fix a possible null pointer dereference in Modules/_ssl.c. Patch by Zackery Spytz.

bpo-1621 [https://bugs.python.org/issue1621]: Do not assume signed integer overflow behavior (C undefined behavior) when performing set hash table resizing.

Library

bpo-35052 [https://bugs.python.org/issue35052]: Fix xml.dom.minidom cloneNode() on a document with an entity: pass the correct arguments to the user data handler of an entity.

bpo-35330 [https://bugs.python.org/issue35330]: When a Mock instance was used to wrap an object, if side_effect is used in one of the mocks of it methods, don’t call the original implementation and return the result of using the side effect the same way that it is done with return_value.

bpo-34172 [https://bugs.python.org/issue34172]: Revert the fix for this issue previously released in 3.6.7 pending further investigation: Fix a reference issue inside multiprocessing.Pool that caused the pool to remain alive if it was deleted without being closed or terminated explicitly.

bpo-10496 [https://bugs.python.org/issue10496]: posixpath.expanduser() now returns the input path unchanged if the HOME environment variable is not set and the current user has no home directory (if the current user identifier doesn’t exist in the password database). This change fix the site module if the current user doesn’t exist in the password database (if the user has no home directory).

bpo-35310 [https://bugs.python.org/issue35310]: Fix a bug in select.select() where, in some cases, the file descriptor sequences were returned unmodified after a signal interruption, even though the file descriptors might not be ready yet. select.select() will now always return empty lists if a timeout has occurred. Patch by Oran Avraham.

bpo-35380 [https://bugs.python.org/issue35380]: Enable TCP_NODELAY on Windows for proactor asyncio event loop.

bpo-35371 [https://bugs.python.org/issue35371]: Fixed possible crash in os.utime() on Windows when pass incorrect arguments.

bpo-27903 [https://bugs.python.org/issue27903]: Fix ResourceWarning in platform.dist() on SuSE and Caldera OpenLinux. Patch by Ville Skyttä.

bpo-28604 [https://bugs.python.org/issue28604]: locale.localeconv() now sets temporarily the LC_CTYPE locale to the LC_MONETARY locale if the two locales are different and monetary strings are non-ASCII. This temporary change affects other threads.

bpo-35277 [https://bugs.python.org/issue35277]: Update ensurepip to install pip 18.1 and setuptools 40.6.2.

bpo-35226 [https://bugs.python.org/issue35226]: Recursively check arguments when testing for equality of unittest.mock.call objects and add note that tracking of parameters used to create ancestors of mocks in mock_calls is not possible.

bpo-35189 [https://bugs.python.org/issue35189]: Modify the following fnctl function to retry if interrupted by a signal (EINTR): flock, lockf, fnctl

bpo-35062 [https://bugs.python.org/issue35062]: Fix incorrect parsing of _io.IncrementalNewlineDecoder’s translate argument.

bpo-35079 [https://bugs.python.org/issue35079]: Improve difflib.SequenceManager.get_matching_blocks doc by adding “non-overlapping” and changing “!=” to “<”.

bpo-35017 [https://bugs.python.org/issue35017]: socketserver.BaseServer.serve_forever() now exits immediately if it’s shutdown() method is called while it is polling for new events.

bpo-31047 [https://bugs.python.org/issue31047]: Fix ntpath.abspath regression where it didn’t remove a trailing separator on Windows. Patch by Tim Graham.

bpo-34794 [https://bugs.python.org/issue34794]: Fixed a leak in Tkinter when pass the Python wrapper around Tcl_Obj back to Tcl/Tk.

bpo-35008 [https://bugs.python.org/issue35008]: Fixed references leaks when call the __setstate__() method of xml.etree.ElementTree.Element in the C implementation for already initialized element.

bpo-23420 [https://bugs.python.org/issue23420]: Verify the value for the parameter “-s” of the cProfile CLI. Patch by Robert Kuska

bpo-16965 [https://bugs.python.org/issue16965]: The 2to3 execfile fixer now opens the file with mode 'rb'. Patch by Zackery Spytz.

bpo-34966 [https://bugs.python.org/issue34966]: pydoc now supports aliases not only to methods defined in the end class, but also to inherited methods. The docstring is not duplicated for aliases.

bpo-34941 [https://bugs.python.org/issue34941]: Methods find(), findtext() and findall() of the Element class in the xml.etree.ElementTree module are now able to find children which are instances of Element subclasses.

bpo-34936 [https://bugs.python.org/issue34936]: Fix TclError in tkinter.Spinbox.selection_element(). Patch by Juliette Monsel.

bpo-34900 [https://bugs.python.org/issue34900]: Fixed unittest.TestCase.debug() when used to call test methods with subtests. Patch by Bruno Oliveira.

bpo-34866 [https://bugs.python.org/issue34866]: Adding max_num_fields to cgi.FieldStorage to make DOS attacks harder by limiting the number of MiniFieldStorage objects created by FieldStorage.

bpo-34738 [https://bugs.python.org/issue34738]: ZIP files created by distutils will now include entries for directories.

bpo-31177 [https://bugs.python.org/issue31177]: Fix bug that prevented using reset_mock on mock instances with deleted attributes

bpo-34604 [https://bugs.python.org/issue34604]: Fix possible mojibake in the error message of pwd.getpwnam and grp.getgrnam using string representation because of invisible characters or trailing whitespaces. Patch by William Grzybowski.

bpo-34574 [https://bugs.python.org/issue34574]: OrderedDict iterators are not exhausted during pickling anymore. Patch by Sergey Fedoseev.

bpo-34052 [https://bugs.python.org/issue34052]: sqlite3.Connection.create_aggregate(), sqlite3.Connection.create_function(), sqlite3.Connection.set_authorizer(), sqlite3.Connection.set_progress_handler() methods raises TypeError when unhashable objects are passed as callable. These methods now don’t pass such objects to SQLite API. Previous behavior could lead to segfaults. Patch by Sergey Fedoseev.

bpo-29877 [https://bugs.python.org/issue29877]: compileall: import ProcessPoolExecutor only when needed, preventing hangs on low resource platforms

bpo-22005 [https://bugs.python.org/issue22005]: Implemented unpickling instances of datetime, date and time pickled by Python 2. encoding='latin1' should be used for successful decoding.

Documentation

bpo-35089 [https://bugs.python.org/issue35089]: Remove mention of typing.io and typing.re. Their types should be imported from typing directly.

bpo-35038 [https://bugs.python.org/issue35038]: Fix the documentation about an unexisting f_restricted attribute in the frame object. Patch by Stéphane Wirtel

bpo-35035 [https://bugs.python.org/issue35035]: Rename documentation for email.utils to email.utils.rst.

bpo-34967 [https://bugs.python.org/issue34967]: Use app.add_object_type() instead of the deprecated Sphinx function app.description_unit()

bpo-33594 [https://bugs.python.org/issue33594]: Document getargspec, from_function and from_builtin as deprecated in their respective docstring, and include version since deprecation in DeprecationWarning message.

bpo-32613 [https://bugs.python.org/issue32613]: Update the faq/windows.html to use the py command from PEP 397 instead of python.

Tests

bpo-33725 [https://bugs.python.org/issue33725]: test_multiprocessing_fork may crash on recent versions of macOS. Until the issue is resolved, skip the test on macOS.

bpo-35352 [https://bugs.python.org/issue35352]: Modify test_asyncio to use the certificate set from the test directory.

bpo-35317 [https://bugs.python.org/issue35317]: Fix mktime() overflow error in test_email: run test_localtime_daylight_true_dst_true() and test_localtime_daylight_false_dst_true() with a specific timezone.

bpo-21263 [https://bugs.python.org/issue21263]: After several reports that test_gdb does not work properly on macOS and since gdb is not shipped by default anymore, test_gdb is now skipped on macOS when LLVM Clang has been used to compile Python. Patch by Lysandros Nikolaou

bpo-34279 [https://bugs.python.org/issue34279]: regrtest issue a warning when no tests have been executed in a particular test file. Also, a new final result state is issued if no test have been executed across all test files. Patch by Pablo Galindo.

Build

bpo-35351 [https://bugs.python.org/issue35351]: When building Python with clang and LTO, LTO flags are no longer passed into CFLAGS to build third-party C extensions through distutils.

bpo-35139 [https://bugs.python.org/issue35139]: Fix a compiler error when statically linking pyexpat in Modules/Setup.

bpo-35011 [https://bugs.python.org/issue35011]: Restores the use of pyexpatns.h to isolate our embedded copy of the expat C library so that its symbols do not conflict at link or dynamic loading time with an embedding application or other extension modules with their own version of libexpat.

bpo-28015 [https://bugs.python.org/issue28015]: Have –with-lto works correctly with clang.

bpo-33015 [https://bugs.python.org/issue33015]: Fix an undefined behaviour in the pthread implementation of PyThread_start_new_thread(): add a function wrapper to always return NULL.

bpo-31625 [https://bugs.python.org/issue31625]: Stop using ranlib on static libraries. Instead, we assume ar supports the “s” flag.

bpo-31354 [https://bugs.python.org/issue31354]: Allow –with-lto to be used on all builds, not just make profile-opt.

Windows

bpo-35401 [https://bugs.python.org/issue35401]: Updates Windows build to OpenSSL 1.0.2q

bpo-32890 [https://bugs.python.org/issue32890]: Fix usage of GetLastError() instead of errno in os.execve() and os.truncate().

macOS

bpo-15663 [https://bugs.python.org/issue15663]: The macOS 10.6+ installer now provides a private copy of Tcl/Tk 8.6, like the 10.9+ installer does.

bpo-35402 [https://bugs.python.org/issue35402]: Update macOS installer to use Tcl/Tk 8.6.9.1. [NOTE: This change was reverted for the released python.org 3.6.8 macOS installers due to regressions found in Tk 8.6.9.1. For now, the installers provide Tcl/Tk 8.6.8.]

bpo-35401 [https://bugs.python.org/issue35401]: Update macOS installer to use OpenSSL 1.0.2q.

bpo-35025 [https://bugs.python.org/issue35025]: Properly guard the use of the CLOCK_GETTIME et al. macros in timemodule on macOS.

bpo-24658 [https://bugs.python.org/issue24658]: On macOS, fix reading from and writing into a file with a size larger than 2 GiB.

IDLE

bpo-35213 [https://bugs.python.org/issue35213]: Where appropriate, use “macOS” in idlelib.

bpo-34864 [https://bugs.python.org/issue34864]: On macOS, warn if the system preference « Prefer tabs when opening documents » is set to « Always ».

bpo-34864 [https://bugs.python.org/issue34864]: Document two IDLE on MacOS issues. The System Preferences Dock « prefer tabs always » setting disables some IDLE features. Menus are a bit different than as described for Windows and Linux.

bpo-35202 [https://bugs.python.org/issue35202]: Remove unused imports from lib/idlelib

bpo-33000 [https://bugs.python.org/issue33000]: Document that IDLE’s shell has no line limit. A program that runs indefinitely can overfill memory.

bpo-23220 [https://bugs.python.org/issue23220]: Explain how IDLE’s Shell displays output.

bpo-35099 [https://bugs.python.org/issue35099]: Improve the doc about IDLE running user code. The section is renamed from « IDLE – console differences » is renamed « Running user code ». It mostly covers the implications of using custom sys.stdxxx objects.

bpo-35097 [https://bugs.python.org/issue35097]: Add IDLE doc subsection explaining editor windows. Topics include opening, title and status bar, .py* extension, and running.

bpo-35093 [https://bugs.python.org/issue35093]: Document the IDLE document viewer in the IDLE doc. Add a paragraph in « Help and preferences », « Help sources » subsection.

bpo-35088 [https://bugs.python.org/issue35088]: Update idlelib.help.copy_string docstring. We now use git and backporting instead of hg and forward merging.

bpo-35087 [https://bugs.python.org/issue35087]: Update idlelib help files for the current doc build. The main change is the elimination of chapter-section numbers.

Tools/Demos

bpo-34989 [https://bugs.python.org/issue34989]: python-gdb.py now handles errors on computing the line number of a Python frame.

Python 3.6.7 final

Release date: 2018-10-20

There were no new changes in version 3.6.7.

Python 3.6.7 release candidate 2

Release date: 2018-10-13

Core and Builtins

bpo-34879 [https://bugs.python.org/issue34879]: Fix a possible null pointer dereference in bytesobject.c. Patch by Zackery Spytz.

bpo-34320 [https://bugs.python.org/issue34320]: Fix dict(od) didn’t copy iteration order of OrderedDict.

Library

bpo-34769 [https://bugs.python.org/issue34769]: Fix for async generators not finalizing when event loop is in debug mode and garbage collector runs in another thread.

bpo-34922 [https://bugs.python.org/issue34922]: Fixed integer overflow in the digest() and hexdigest() methods for the SHAKE algorithm in the hashlib module.

bpo-34871 [https://bugs.python.org/issue34871]: Fix inspect module polluted sys.modules when parsing __text_signature__ of callable.

bpo-34872 [https://bugs.python.org/issue34872]: Fix self-cancellation in C implementation of asyncio.Task

bpo-34819 [https://bugs.python.org/issue34819]: Use a monotonic clock to compute timeouts in Executor.map() and as_completed(), in order to prevent timeouts from deviating when the system clock is adjusted.

bpo-34521 [https://bugs.python.org/issue34521]: Use socket.CMSG_SPACE() to calculate ancillary data size instead of socket.CMSG_LEN() in multiprocessing.reduction.recvfds() as RFC 3542 [https://tools.ietf.org/html/rfc3542.html] requires the use of the former for portable applications.

bpo-34282 [https://bugs.python.org/issue34282]: Fix enum members getting shadowed by parent attributes.

bpo-34172 [https://bugs.python.org/issue34172]: Fix a reference issue inside multiprocessing.Pool that caused the pool to remain alive if it was deleted without being closed or terminated explicitly.

bpo-33729 [https://bugs.python.org/issue33729]: Fixed issues with arguments parsing in hashlib.

Documentation

bpo-32174 [https://bugs.python.org/issue32174]: chm document displays non-ASCII charaters properly on some MBCS Windows systems.

Tests

bpo-32962 [https://bugs.python.org/issue32962]: Fixed test_gdb when Python is compiled with flags -mcet -fcf-protection -O0.

macOS

bpo-34370 [https://bugs.python.org/issue34370]: Revert to using the released Tk 8.6.8 with macOS installers instead of the Tk 8.6.x development snapshot used with 3.7.1rc1 and 3.6.7rc1. The snapshot introduced at least one significant regression (bpo-34927 [https://bugs.python.org/issue34927]).

C API

bpo-34910 [https://bugs.python.org/issue34910]: Ensure that PyObject_Print() always returns -1 on error. Patch by Zackery Spytz.

Python 3.6.7 release candidate 1

Release date: 2018-09-26

Security

bpo-17239 [https://bugs.python.org/issue17239]: The xml.sax and xml.dom.minidom parsers no longer processes external entities by default. External DTD and ENTITY declarations no longer load files or create network connections.

bpo-34623 [https://bugs.python.org/issue34623]: CVE-2018-14647: The C accelerated _elementtree module now initializes hash randomization salt from _Py_HashSecret instead of libexpat’s default CSPRNG.

bpo-34405 [https://bugs.python.org/issue34405]: Updated to OpenSSL 1.0.2p for Windows builds.

bpo-33871 [https://bugs.python.org/issue33871]: Fixed sending the part of the file in os.sendfile() on macOS. Using the trailers argument could cause sending more bytes from the input file than was specified.

bpo-32533 [https://bugs.python.org/issue32533]: Fixed thread-safety of error handling in _ssl.

Core and Builtins

bpo-34735 [https://bugs.python.org/issue34735]: Fix a memory leak in Modules/timemodule.c. Patch by Zackery Spytz.

bpo-34588 [https://bugs.python.org/issue34588]: Fix an off-by-one in the recursive call pruning feature of traceback formatting.

bpo-34527 [https://bugs.python.org/issue34527]: On FreeBSD, Py_DecodeLocale() and Py_EncodeLocale() now also forces the ASCII encoding if the LC_CTYPE locale is « POSIX », not only if the LC_CTYPE locale is « C ».

bpo-34400 [https://bugs.python.org/issue34400]: Fix undefined behavior in parsetok.c. Patch by Zackery Spytz.

bpo-34377 [https://bugs.python.org/issue34377]: Update valgrind suppression list to use _PyObject_Free/_PyObject_Realloc instead of PyObject_Free/PyObject_Realloc.

bpo-24618 [https://bugs.python.org/issue24618]: Fixed reading invalid memory when create the code object with too small varnames tuple or too large argument counts.

bpo-34068 [https://bugs.python.org/issue34068]: In io.IOBase.close(), ensure that the closed attribute is not set with a live exception. Patch by Zackery Spytz and Serhiy Storchaka.

bpo-34080 [https://bugs.python.org/issue34080]: Fixed a memory leak in the compiler when it raised some uncommon errors during tokenizing.

bpo-34066 [https://bugs.python.org/issue34066]: Disabled interruption by Ctrl-C between calling open() and entering a with block in with open().

bpo-33956 [https://bugs.python.org/issue33956]: Update vendored Expat library copy to version 2.2.5.

bpo-24596 [https://bugs.python.org/issue24596]: Decref the module object in PyRun_SimpleFileExFlags() before calling PyErr_Print(). Patch by Zackery Spytz.

bpo-33451 [https://bugs.python.org/issue33451]: Close directly executed pyc files before calling PyEval_EvalCode().

bpo-33312 [https://bugs.python.org/issue33312]: Fixed clang ubsan (undefined behavior sanitizer) warnings in dictobject.c by adjusting how the internal struct _dictkeysobject shared keys structure is declared.

bpo-25750 [https://bugs.python.org/issue25750]: Fix rare Python crash due to bad refcounting in type_getattro() if a descriptor deletes itself from the class. Patch by Jeroen Demeyer.

bpo-25862 [https://bugs.python.org/issue25862]: Fix assertion failures in the tell() method of io.TextIOWrapper. Patch by Zackery Spytz.

Library

bpo-34670 [https://bugs.python.org/issue34670]: Add SSLContext.post_handshake_auth and SSLSocket.verify_client_post_handshake for TLS 1.3’s post handshake authentication feature.

bpo-34652 [https://bugs.python.org/issue34652]: Ensure os.lchmod() is never defined on Linux.

bpo-34625 [https://bugs.python.org/issue34625]: Update vendorized expat library version to 2.2.6.

bpo-32270 [https://bugs.python.org/issue32270]: The subprocess module no longer mistakenly closes redirected fds even when they were in pass_fds when outside of the default {0, 1, 2} set.

bpo-34610 [https://bugs.python.org/issue34610]: Fixed iterator of multiprocessing.managers.DictProxy.

bpo-34421 [https://bugs.python.org/issue34421]: Fix distutils logging for non-ASCII strings. This caused installation issues on Windows.

bpo-34604 [https://bugs.python.org/issue34604]: Fix possible mojibake in the error message of pwd.getpwnam and grp.getgrnam. Patch by William Grzybowski.

bpo-34530 [https://bugs.python.org/issue34530]: distutils.spawn.find_executable() now falls back on os.defpath if the PATH environment variable is not set.

bpo-34563 [https://bugs.python.org/issue34563]: On Windows, fix multiprocessing.Connection for very large read: fix _winapi.PeekNamedPipe() and _winapi.ReadFile() for read larger than INT_MAX (usually 2^31-1).

bpo-13312 [https://bugs.python.org/issue13312]: Avoids a possible integer underflow (undefined behavior) in the time module’s year handling code when passed a very low negative year value.

bpo-34472 [https://bugs.python.org/issue34472]: Improved compatibility for streamed files in zipfile. Previously an optional signature was not being written and certain ZIP applications were not supported. Patch by Silas Sewell.

bpo-6700 [https://bugs.python.org/issue6700]: Fix inspect.getsourcelines for module level frames/tracebacks. Patch by Vladimir Matveev.

bpo-32947 [https://bugs.python.org/issue32947]: Add OP_ENABLE_MIDDLEBOX_COMPAT and test workaround for TLSv1.3 for future compatibility with OpenSSL 1.1.1.

bpo-34341 [https://bugs.python.org/issue34341]: Appending to the ZIP archive with the ZIP64 extension no longer grows the size of extra fields of existing entries.

bpo-18540 [https://bugs.python.org/issue18540]: The imaplib.IMAP4 and imaplib.IMAP4_SSL classes now resolve to the local host IP correctly when the default value of host parameter ('') is used.

bpo-34246 [https://bugs.python.org/issue34246]: smtplib.SMTP.send_message() no longer modifies the content of the mail_options argument. Patch by Pablo S. Blum de Aguiar.

bpo-31047 [https://bugs.python.org/issue31047]: Fix ntpath.abspath for invalid paths on windows. Patch by Franz Woellert.

bpo-34263 [https://bugs.python.org/issue34263]: asyncio’s event loop will not pass timeouts longer than one day to epoll/select etc.

bpo-32215 [https://bugs.python.org/issue32215]: Fix performance regression in sqlite3 when a DML statement appeared in a different line than the rest of the SQL query.

bpo-19891 [https://bugs.python.org/issue19891]: Ignore errors caused by missing / non-writable homedir while writing history during exit of an interactive session. Patch by Anthony Sottile.

bpo-940286 [https://bugs.python.org/issue940286]: pydoc’s Helper.showtopic() method now prints the cross references of a topic correctly.

bpo-34164 [https://bugs.python.org/issue34164]: base64.b32decode() could raise UnboundLocalError or OverflowError for incorrect padding. Now it always raises base64.Error in these cases.

bpo-33967 [https://bugs.python.org/issue33967]: functools.singledispatch now raises TypeError instead of IndexError when no positional arguments are passed.

bpo-34054 [https://bugs.python.org/issue34054]: The multiprocessing module now uses the monotonic clock time.monotonic() instead of the system clock time.time() to implement timeout.

bpo-34010 [https://bugs.python.org/issue34010]: Fixed a performance regression for reading streams with tarfile. The buffered read should use a list, instead of appending to a bytes object.

bpo-34019 [https://bugs.python.org/issue34019]: webbrowser: Correct the arguments passed to Opera Browser when opening a new URL using the webbrowser module. Patch by Bumsik Kim.

bpo-33978 [https://bugs.python.org/issue33978]: Closed existing logging handlers before reconfiguration via fileConfig and dictConfig. Patch by Karthikeyan Singaravelan.

bpo-14117 [https://bugs.python.org/issue14117]: Make minor tweaks to turtledemo. The “wikipedia” example is now “rosette”, decribing what it draws. The “penrose” print output is reduced. The’1024” output of “tree” is eliminated.

bpo-33974 [https://bugs.python.org/issue33974]: Fixed passing lists and tuples of strings containing special characters ", \, {, } and \n as options to ttk widgets.

bpo-27500 [https://bugs.python.org/issue27500]: Fix getaddrinfo to resolve IPv6 addresses correctly.

bpo-24567 [https://bugs.python.org/issue24567]: Improve random.choices() to handle subnormal input weights that could occasionally trigger an IndexError.

bpo-33871 [https://bugs.python.org/issue33871]: Fixed integer overflow in os.readv() and os.writev() and in os.sendfile() with headers or trailers arguments (on BSD-based OSes and macOS).

bpo-33899 [https://bugs.python.org/issue33899]: Tokenize module now implicitly emits a NEWLINE when provided with input that does not have a trailing new line. This behavior now matches what the C tokenizer does internally. Contributed by Ammar Askar.

bpo-33916 [https://bugs.python.org/issue33916]: bz2 and lzma: When Decompressor.__init__() is called twice, free the old lock to not leak memory.

bpo-32568 [https://bugs.python.org/issue32568]: Make select.epoll() and its documentation consistent regarding sizehint and flags.

bpo-33663 [https://bugs.python.org/issue33663]: Convert content length to string before putting to header.

bpo-26544 [https://bugs.python.org/issue26544]: Fixed implementation of platform.libc_ver(). It almost always returned version “2.9” for glibc.

bpo-27397 [https://bugs.python.org/issue27397]: Make email module properly handle invalid-length base64 strings.

bpo-33476 [https://bugs.python.org/issue33476]: Fix _header_value_parser.py when address group is missing final “;”. Contributed by Enrique Perez-Terron

bpo-33570 [https://bugs.python.org/issue33570]: Change TLS 1.3 cipher suite settings for compatibility with OpenSSL 1.1.1-pre6 and newer. OpenSSL 1.1.1 will have TLS 1.3 cipers enabled by default.

bpo-33365 [https://bugs.python.org/issue33365]: Print the header values besides the header keys instead just the header keys if debuglevel is set to >0 in http.client. Patch by Marco Strigl.

bpo-33336 [https://bugs.python.org/issue33336]: imaplib now allows MOVE command in IMAP4.uid() (RFC 6851: IMAP MOVE Extension) and potentially as a name of supported method of IMAP4 object.

bpo-32356 [https://bugs.python.org/issue32356]: asyncio.transport.resume_reading() and pause_reading() are now idempotent.

bpo-31608 [https://bugs.python.org/issue31608]: Raise a TypeError instead of crashing if a collections.deque subclass returns a non-deque from __new__. Patch by Oren Milman.

bpo-29456 [https://bugs.python.org/issue29456]: Fix bugs in hangul normalization: u1176, u11a7 and u11c3

Documentation

bpo-28617 [https://bugs.python.org/issue28617]: Fixed info in the stdtypes docs concerning the types that support membership tests.

bpo-34065 [https://bugs.python.org/issue34065]: Fix wrongly written basicConfig documentation markup syntax

bpo-33847 [https://bugs.python.org/issue33847]: Add “@” operator entry to index.

bpo-25041 [https://bugs.python.org/issue25041]: Document AF_PACKET in the socket module.

Tests

bpo-34587 [https://bugs.python.org/issue34587]: test_socket: Remove RDSTest.testCongestion(). The test tries to fill the receiver’s socket buffer and expects an error. But the RDS protocol doesn’t require that. Moreover, the Linux implementation of RDS expects that the producer of the messages reduces its rate, it’s not the role of the receiver to trigger an error. The test fails on Fedora 28 by design, so just remove it.

bpo-34661 [https://bugs.python.org/issue34661]: Fix test_shutil if unzip doesn’t support -t.

bpo-34200 [https://bugs.python.org/issue34200]: Fixed non-deterministic flakiness of test_pkg by not using the scary test.support.module_cleanup() logic to save and restore sys.modules contents between test cases.

bpo-34594 [https://bugs.python.org/issue34594]: Fix usage of hardcoded errno values in the tests.

bpo-34542 [https://bugs.python.org/issue34542]: Use 3072 RSA keys and SHA-256 signature for test certs and keys.

bpo-34391 [https://bugs.python.org/issue34391]: Fix ftplib test for TLS 1.3 by reading from data socket.

bpo-34399 [https://bugs.python.org/issue34399]: Update all RSA keys and DH params to use at least 2048 bits.

bpo-33746 [https://bugs.python.org/issue33746]: Fix test_unittest when run in verbose mode.

bpo-33901 [https://bugs.python.org/issue33901]: Fix test_dbm_gnu on macOS with gdbm 1.15: add a larger value to make sure that the file size changes.

bpo-33873 [https://bugs.python.org/issue33873]: Fix a bug in regrtest that caused an extra test to run if –huntrleaks/-R was used. Exit with error in case that invalid parameters are specified to –huntrleaks/-R (at least one warmup run and one repetition must be used).

bpo-32663 [https://bugs.python.org/issue32663]: Making sure the SMTPUTF8SimTests class of tests gets run in test_smtplib.py.

Build

bpo-34710 [https://bugs.python.org/issue34710]: Fixed SSL module build with OpenSSL & pedantic CFLAGS.

bpo-34582 [https://bugs.python.org/issue34582]: Add JUnit XML output for regression tests and update Azure DevOps builds.

bpo-34121 [https://bugs.python.org/issue34121]: Fix detection of C11 atomic support on clang.

bpo-30345 [https://bugs.python.org/issue30345]: Add -g to LDFLAGS when compiling with LTO to get debug symbols.

Windows

bpo-34770 [https://bugs.python.org/issue34770]: Fix a possible null pointer dereference in pyshellext.cpp.

bpo-34603 [https://bugs.python.org/issue34603]: Fix returning structs from functions produced by MSVC

bpo-34225 [https://bugs.python.org/issue34225]: Ensure INCLUDE and LIB directories do not end with a backslash.

bpo-34006 [https://bugs.python.org/issue34006]: Revert line length limit for Windows help docs. The line-length limit is not needed because the pages appear in a separate app rather than on a browser tab. It can also interact badly with the DPI setting.

bpo-31546 [https://bugs.python.org/issue31546]: Restore running PyOS_InputHook while waiting for user input at the prompt. The restores integration of interactive GUI windows (such as Matplotlib figures) with the prompt on Windows.

bpo-30237 [https://bugs.python.org/issue30237]: Output error when ReadConsole is canceled by CancelSynchronousIo instead of crashing.

bpo-29097 [https://bugs.python.org/issue29097]: Fix bug where datetime.fromtimestamp() erronously throws an OSError on Windows for values between 0 and 86400. Patch by Ammar Askar.

macOS

bpo-34370 [https://bugs.python.org/issue34370]: Have macOS 10.9+ installer builds for 3.7.1rc and 3.6.7rc use a development snapshot of Tk 8.6 (post-8.6.8) to mitigate certain scroller issues seen with IDLE and tkinter apps.

bpo-34405 [https://bugs.python.org/issue34405]: Update to OpenSSL 1.0.2p for macOS installer builds.

bpo-31903 [https://bugs.python.org/issue31903]: In _scproxy, drop the GIL when calling into SystemConfiguration to avoid deadlocks.

IDLE

bpo-34548 [https://bugs.python.org/issue34548]: Use configured color theme for read-only text views.

bpo-1529353 [https://bugs.python.org/issue1529353]: Enable « squeezing » of long outputs in the shell, to avoid performance degradation and to clean up the history without losing it. Squeezed outputs may be copied, viewed in a separate window, and « unsqueezed ».

bpo-34047 [https://bugs.python.org/issue34047]: Fixed mousewheel scrolling direction on macOS.

bpo-34275 [https://bugs.python.org/issue34275]: Make IDLE calltips always visible on Mac. Some MacOS-tk combinations need .update_idletasks(). Patch by Kevin Walzer.

bpo-34120 [https://bugs.python.org/issue34120]: Fix unresponsiveness after closing certain windows and dialogs.

bpo-33975 [https://bugs.python.org/issue33975]: Avoid small type when running htests. Since part of the purpose of human-viewed tests is to determine that widgets look right, it is important that they look the same for testing as when running IDLE.

bpo-33905 [https://bugs.python.org/issue33905]: Add test for idlelib.stackview.StackBrowser.

bpo-33924 [https://bugs.python.org/issue33924]: Change mainmenu.menudefs key “windows” to “window”. Every other menudef key is lowercase version of main menu entry.

bpo-33906 [https://bugs.python.org/issue33906]: Rename idlelib.windows as window Match Window on the main menu and remove last plural module name.

bpo-33917 [https://bugs.python.org/issue33917]: Fix and document idlelib/idle_test/template.py. The revised file compiles, runs, and tests OK. idle_test/README.txt explains how to use it to create new IDLE test files.

bpo-33904 [https://bugs.python.org/issue33904]: IDLE: In rstrip, rename class RstripExtension as Rstrip

bpo-33907 [https://bugs.python.org/issue33907]: For consistency and clarity, rename an IDLE module and classes. Module calltips and its class CallTips are now calltip and Calltip. In module calltip_w, class CallTip is now CalltipWindow.

bpo-33856 [https://bugs.python.org/issue33856]: Add « help » in the welcome message of IDLE

bpo-33839 [https://bugs.python.org/issue33839]: IDLE: refactor ToolTip and CallTip and add documentation and tests

bpo-33855 [https://bugs.python.org/issue33855]: Minimally test all IDLE modules. Add missing files, import module, instantiate classes, and check coverage. Check existing files.

Tools/Demos

bpo-32962 [https://bugs.python.org/issue32962]: python-gdb now catches UnicodeDecodeError exceptions when calling string().

bpo-32962 [https://bugs.python.org/issue32962]: python-gdb now catches ValueError on read_var(): when Python has no debug symbols for example.

C API

bpo-23927 [https://bugs.python.org/issue23927]: Fixed SystemError in PyArg_ParseTupleAndKeywords() when the w* format unit is used for optional parameter.

Python 3.6.6 final

Release date: 2018-06-27

There were no new changes in version 3.6.6.

Python 3.6.6 release candidate 1

Release date: 2018-06-11

Core and Builtins

bpo-33786 [https://bugs.python.org/issue33786]: Fix asynchronous generators to handle GeneratorExit in athrow() correctly

bpo-30654 [https://bugs.python.org/issue30654]: Fixed reset of the SIGINT handler to SIG_DFL on interpreter shutdown even when there was a custom handler set previously. Patch by Philipp Kerling.

bpo-33622 [https://bugs.python.org/issue33622]: Fixed a leak when the garbage collector fails to add an object with the __del__ method or referenced by it into the gc.garbage list. PyGC_Collect() can now be called when an exception is set and preserves it.

bpo-31849 [https://bugs.python.org/issue31849]: Fix signed/unsigned comparison warning in pyhash.c.

bpo-33391 [https://bugs.python.org/issue33391]: Fix a leak in set_symmetric_difference().

bpo-28055 [https://bugs.python.org/issue28055]: Fix unaligned accesses in siphash24(). Patch by Rolf Eike Beer.

bpo-33231 [https://bugs.python.org/issue33231]: Fix potential memory leak in normalizestring().

bpo-29922 [https://bugs.python.org/issue29922]: Improved error messages in “async with” when __aenter__() or __aexit__() return non-awaitable object.

bpo-33199 [https://bugs.python.org/issue33199]: Fix ma_version_tag in dict implementation is uninitialized when copying from key-sharing dict.

bpo-33041 [https://bugs.python.org/issue33041]: Fixed jumping when the function contains an async for loop.

bpo-32282 [https://bugs.python.org/issue32282]: Fix an unnecessary ifdef in the include of VersionHelpers.h in socketmodule on Windows.

bpo-21983 [https://bugs.python.org/issue21983]: Fix a crash in ctypes.cast() in case the type argument is a ctypes structured data type. Patch by Eryk Sun and Oren Milman.

Library

bpo-30167 [https://bugs.python.org/issue30167]: Prevent site.main() exception if PYTHONSTARTUP is set. Patch by Steve Weber.

bpo-33812 [https://bugs.python.org/issue33812]: Datetime instance d with non-None tzinfo, but with d.tzinfo.utcoffset(d) returning None is now treated as naive by the astimezone() method.

bpo-30805 [https://bugs.python.org/issue30805]: Avoid race condition with debug logging

bpo-33767 [https://bugs.python.org/issue33767]: The concatenation (+) and repetition (*) sequence operations now raise TypeError instead of SystemError when performed on mmap.mmap objects. Patch by Zackery Spytz.

bpo-32684 [https://bugs.python.org/issue32684]: Fix gather to propagate cancellation of itself even with return_exceptions.

bpo-33674 [https://bugs.python.org/issue33674]: Fix a race condition in SSLProtocol.connection_made() of asyncio.sslproto: start immediately the handshake instead of using call_soon(). Previously, data_received() could be called before the handshake started, causing the handshake to hang or fail.

bpo-31647 [https://bugs.python.org/issue31647]: Fixed bug where calling write_eof() on a _SelectorSocketTransport after it’s already closed raises AttributeError.

bpo-33672 [https://bugs.python.org/issue33672]: Fix Task.__repr__ crash with Cython’s bogus coroutines

bpo-33469 [https://bugs.python.org/issue33469]: Fix RuntimeError after closing loop that used run_in_executor

bpo-11874 [https://bugs.python.org/issue11874]: Use a better regex when breaking usage into wrappable parts. Avoids bogus assertion errors from custom metavar strings.

bpo-30877 [https://bugs.python.org/issue30877]: Fixed a bug in the Python implementation of the JSON decoder that prevented the cache of parsed strings from clearing after finishing the decoding. Based on patch by c-fos.

bpo-33548 [https://bugs.python.org/issue33548]: tempfile._candidate_tempdir_list should consider common TEMP locations

bpo-33542 [https://bugs.python.org/issue33542]: Prevent uuid.get_node from using a DUID instead of a MAC on Windows. Patch by Zvi Effron

bpo-26819 [https://bugs.python.org/issue26819]: Fix race condition with ReadTransport.resume_reading in Windows proactor event loop.

bpo-28556 [https://bugs.python.org/issue28556]: Minor fixes in typing module: add annotations to NamedTuple.__new__, pass *args and **kwds in Generic.__new__. Original PRs by Paulius Šarka and Chad Dombrova.

bpo-20087 [https://bugs.python.org/issue20087]: Updated alias mapping with glibc 2.27 supported locales.

bpo-33422 [https://bugs.python.org/issue33422]: Fix trailing quotation marks getting deleted when looking up byte/string literals on pydoc. Patch by Andrés Delfino.

bpo-33197 [https://bugs.python.org/issue33197]: Update error message when constructing invalid inspect.Parameters Patch by Dong-hee Na.

bpo-33383 [https://bugs.python.org/issue33383]: Fixed crash in the get() method of the dbm.ndbm database object when it is called with a single argument.

bpo-33329 [https://bugs.python.org/issue33329]: Fix multiprocessing regression on newer glibcs

bpo-991266 [https://bugs.python.org/issue991266]: Fix quoting of the Comment attribute of http.cookies.SimpleCookie.

bpo-33131 [https://bugs.python.org/issue33131]: Upgrade bundled version of pip to 10.0.1.

bpo-33308 [https://bugs.python.org/issue33308]: Fixed a crash in the parser module when converting an ST object to a tree of tuples or lists with line_info=False and col_info=True.

bpo-33263 [https://bugs.python.org/issue33263]: Fix FD leak in _SelectorSocketTransport Patch by Vlad Starostin.

bpo-33256 [https://bugs.python.org/issue33256]: Fix display of <module> call in the html produced by cgitb.html(). Patch by Stéphane Blondon.

bpo-33203 [https://bugs.python.org/issue33203]: random.Random.choice() now raises IndexError for empty sequences consistently even when called from subclasses without a getrandbits() implementation.

bpo-33224 [https://bugs.python.org/issue33224]: Update difflib.mdiff() for PEP 479. Convert an uncaught StopIteration in a generator into a return-statement.

bpo-33209 [https://bugs.python.org/issue33209]: End framing at the end of C implementation of pickle.Pickler.dump().

bpo-32861 [https://bugs.python.org/issue32861]: The urllib.robotparser’s __str__ representation now includes wildcard entries and the « Crawl-delay » and « Request-rate » fields. Patch by Michael Lazar.

bpo-33096 [https://bugs.python.org/issue33096]: Allow ttk.Treeview.insert to insert iid that has a false boolean value. Note iid=0 and iid=False would be same. Patch by Garvit Khatri.

bpo-33127 [https://bugs.python.org/issue33127]: The ssl module now compiles with LibreSSL 2.7.1.

bpo-33021 [https://bugs.python.org/issue33021]: Release the GIL during fstat() calls, avoiding hang of all threads when calling mmap.mmap(), os.urandom(), and random.seed(). Patch by Nir Soffer.

bpo-27683 [https://bugs.python.org/issue27683]: Fix a regression in ipaddress that result of hosts() is empty when the network is constructed by a tuple containing an integer mask and only 1 bit left for addresses.

bpo-32844 [https://bugs.python.org/issue32844]: Fix wrong redirection of a low descriptor (0 or 1) to stderr in subprocess if another low descriptor is closed.

bpo-31908 [https://bugs.python.org/issue31908]: Fix output of cover files for trace module command-line tool. Previously emitted cover files only when --missing option was used. Patch by Michael Selik.

bpo-31457 [https://bugs.python.org/issue31457]: If nested log adapters are used, the inner process() methods are no longer omitted.

bpo-16865 [https://bugs.python.org/issue16865]: Support arrays >=2GiB in ctypes. Patch by Segev Finer.

bpo-31238 [https://bugs.python.org/issue31238]: pydoc: the stop() method of the private ServerThread class now waits until DocServer.serve_until_quit() completes and then explicitly sets its docserver attribute to None to break a reference cycle.

Documentation

bpo-33503 [https://bugs.python.org/issue33503]: Fix broken pypi link

bpo-33421 [https://bugs.python.org/issue33421]: Add missing documentation for typing.AsyncContextManager.

bpo-33378 [https://bugs.python.org/issue33378]: Add Korean language switcher for https://docs.python.org/3/

bpo-33276 [https://bugs.python.org/issue33276]: Clarify that the __path__ attribute on modules cannot be just any value.

bpo-33201 [https://bugs.python.org/issue33201]: Modernize documentation for writing C extension types.

bpo-33195 [https://bugs.python.org/issue33195]: Deprecate Py_UNICODE usage in c-api/arg document. Py_UNICODE related APIs are deprecated since Python 3.3, but it is missed in the document.

bpo-33126 [https://bugs.python.org/issue33126]: Document PyBuffer_ToContiguous().

bpo-27212 [https://bugs.python.org/issue27212]: Modify documentation for the islice() recipe to consume initial values up to the start index.

bpo-28247 [https://bugs.python.org/issue28247]: Update zipapp documentation to describe how to make standalone applications.

bpo-18802 [https://bugs.python.org/issue18802]: Documentation changes for ipaddress. Patch by Jon Foster and Berker Peksag.

bpo-27428 [https://bugs.python.org/issue27428]: Update documentation to clarify that WindowsRegistryFinder implements MetaPathFinder. (Patch by Himanshu Lakhara)

bpo-8243 [https://bugs.python.org/issue8243]: Add a note about curses.addch and curses.addstr exception behavior when writing outside a window, or pad.

bpo-31432 [https://bugs.python.org/issue31432]: Clarify meaning of CERT_NONE, CERT_OPTIONAL, and CERT_REQUIRED flags for ssl.SSLContext.verify_mode.

Tests

bpo-33655 [https://bugs.python.org/issue33655]: Ignore test_posix_fallocate failures on BSD platforms that might be due to running on ZFS.

bpo-19417 [https://bugs.python.org/issue19417]: Add test_bdb.py.

Build

bpo-5755 [https://bugs.python.org/issue5755]: Move -Wstrict-prototypes option to CFLAGS_NODIST from OPT. This option emitted annoying warnings when building extension modules written in C++.

bpo-33614 [https://bugs.python.org/issue33614]: Ensures module definition files for the stable ABI on Windows are correctly regenerated.

bpo-33522 [https://bugs.python.org/issue33522]: Enable CI builds on Visual Studio Team Services at https://python.visualstudio.com/cpython

bpo-33012 [https://bugs.python.org/issue33012]: Add -Wno-cast-function-type for gcc 8 for silencing warnings about function casts like casting to PyCFunction in method definition lists.

bpo-33394 [https://bugs.python.org/issue33394]: Enable the verbose build for extension modules, when GNU make is passed macros on the command line.

Windows

bpo-33184 [https://bugs.python.org/issue33184]: Update Windows installer to OpenSSL 1.0.2o.

macOS

bpo-33184 [https://bugs.python.org/issue33184]: Update macOS installer build to use OpenSSL 1.0.2o.

IDLE

bpo-33656 [https://bugs.python.org/issue33656]: On Windows, add API call saying that tk scales for DPI. On Windows 8.1+ or 10, with DPI compatibility properties of the Python binary unchanged, and a monitor resolution greater than 96 DPI, this should make text and lines sharper. It should otherwise have no effect.

bpo-33768 [https://bugs.python.org/issue33768]: Clicking on a context line moves that line to the top of the editor window.

bpo-33763 [https://bugs.python.org/issue33763]: IDLE: Use read-only text widget for code context instead of label widget.

bpo-33664 [https://bugs.python.org/issue33664]: Scroll IDLE editor text by lines. Previously, the mouse wheel and scrollbar slider moved text by a fixed number of pixels, resulting in partial lines at the top of the editor box. The change also applies to the shell and grep output windows, but not to read-only text views.

bpo-33679 [https://bugs.python.org/issue33679]: Enable theme-specific color configuration for Code Context. Use the Highlights tab to see the setting for built-in themes or add settings to custom themes.

bpo-33642 [https://bugs.python.org/issue33642]: Display up to maxlines non-blank lines for Code Context. If there is no current context, show a single blank line.

bpo-33628 [https://bugs.python.org/issue33628]: IDLE: Cleanup codecontext.py and its test.

bpo-33564 [https://bugs.python.org/issue33564]: IDLE’s code context now recognizes async as a block opener.

bpo-29706 [https://bugs.python.org/issue29706]: IDLE now colors async and await as keywords in 3.6. They become full keywords in 3.7.

bpo-21474 [https://bugs.python.org/issue21474]: Update word/identifier definition from ascii to unicode. In text and entry boxes, this affects selection by double-click, movement left/right by control-left/right, and deletion left/right by control-BACKSPACE/DEL.

bpo-33204 [https://bugs.python.org/issue33204]: IDLE: consistently color invalid string prefixes. A “u” string prefix cannot be paired with either “r” or “f”. Consistently color as much of the prefix, starting at the right, as is valid. Revise and extend colorizer test.

bpo-32831 [https://bugs.python.org/issue32831]: Add docstrings and tests for codecontext.

Tools/Demos

bpo-33189 [https://bugs.python.org/issue33189]: pygettext.py now recognizes only literal strings as docstrings and translatable strings, and rejects bytes literals and f-string expressions.

bpo-31920 [https://bugs.python.org/issue31920]: Fixed handling directories as arguments in the pygettext script. Based on patch by Oleg Krasnikov.

bpo-29673 [https://bugs.python.org/issue29673]: Fix pystackv and pystack gdbinit macros.

bpo-32885 [https://bugs.python.org/issue32885]: Add an -n flag for Tools/scripts/pathfix.py to disable automatic backup creation (files with ~ suffix).

bpo-31583 [https://bugs.python.org/issue31583]: Fix 2to3 for using with –add-suffix option but without –output-dir option for relative path to files in current directory.

C API

bpo-32374 [https://bugs.python.org/issue32374]: Document that m_traverse for multi-phase initialized modules can be called with m_state=NULL, and add a sanity check

Python 3.6.5 final

Release date: 2018-03-28

Tests

bpo-32872 [https://bugs.python.org/issue32872]: Avoid regrtest compatibility issue with namespace packages.

Build

bpo-33163 [https://bugs.python.org/issue33163]: Upgrade pip to 9.0.3 and setuptools to v39.0.1.

Python 3.6.5 release candidate 1

Release date: 2018-03-13

Security

bpo-33001 [https://bugs.python.org/issue33001]: Minimal fix to prevent buffer overrun in os.symlink on Windows

bpo-32981 [https://bugs.python.org/issue32981]: Regexes in difflib and poplib were vulnerable to catastrophic backtracking. These regexes formed potential DOS vectors (REDOS). They have been refactored. This resolves CVE-2018-1060 and CVE-2018-1061. Patch by Jamie Davis.

Core and Builtins

bpo-33026 [https://bugs.python.org/issue33026]: Fixed jumping out of « with » block by setting f_lineno.

bpo-17288 [https://bugs.python.org/issue17288]: Prevent jumps from “return” and “exception” trace events.

bpo-32889 [https://bugs.python.org/issue32889]: Update Valgrind suppression list to account for the rename of Py_ADDRESS_IN_RANG to address_in_range.

bpo-32650 [https://bugs.python.org/issue32650]: Pdb and other debuggers dependent on bdb.py will correctly step over (next command) native coroutines. Patch by Pablo Galindo.

bpo-32685 [https://bugs.python.org/issue32685]: Improve suggestion when the Python 2 form of print statement is either present on the same line as the header of a compound statement or else terminated by a semi-colon instead of a newline. Patch by Nitish Chandra.

bpo-32583 [https://bugs.python.org/issue32583]: Fix possible crashing in builtin Unicode decoders caused by write out-of-bound errors when using customized decode error handlers.

bpo-26163 [https://bugs.python.org/issue26163]: Improved frozenset() hash to create more distinct hash values when faced with datasets containing many similar values.

bpo-27169 [https://bugs.python.org/issue27169]: The __debug__ constant is now optimized out at compile time. This fixes also bpo-22091 [https://bugs.python.org/issue22091].

bpo-32329 [https://bugs.python.org/issue32329]: sys.flags.hash_randomization is now properly set to 0 when hash randomization is turned off by PYTHONHASHSEED=0.

bpo-30416 [https://bugs.python.org/issue30416]: The optimizer is now protected from spending much time doing complex calculations and consuming much memory for creating large constants in constant folding.

bpo-18533 [https://bugs.python.org/issue18533]: repr() on a dict containing its own values() or items() no longer raises RecursionError; OrderedDict similarly. Instead, use ..., as for other recursive structures. Patch by Ben North.

bpo-32028 [https://bugs.python.org/issue32028]: Leading whitespace is now correctly ignored when generating suggestions for converting Py2 print statements to Py3 builtin print function calls. Patch by Sanyam Khurana.

bpo-32137 [https://bugs.python.org/issue32137]: The repr of deeply nested dict now raises a RecursionError instead of crashing due to a stack overflow.

Library

bpo-33064 [https://bugs.python.org/issue33064]: lib2to3 now properly supports trailing commas after *args and **kwargs in function signatures.

bpo-31804 [https://bugs.python.org/issue31804]: Avoid failing in multiprocessing.Process if the standard streams are closed or None at exit.

bpo-33037 [https://bugs.python.org/issue33037]: Skip sending/receiving data after SSL transport closing.

bpo-30353 [https://bugs.python.org/issue30353]: Fix ctypes pass-by-value for structs on 64-bit Cygwin/MinGW.

bpo-33009 [https://bugs.python.org/issue33009]: Fix inspect.signature() for single-parameter partialmethods.

bpo-32969 [https://bugs.python.org/issue32969]: Expose several missing constants in zlib and fix corresponding documentation.

bpo-32713 [https://bugs.python.org/issue32713]: Fixed tarfile.itn handling of out-of-bounds float values. Patch by Joffrey Fuhrer.

bpo-30622 [https://bugs.python.org/issue30622]: The ssl module now detects missing NPN support in LibreSSL.

bpo-32922 [https://bugs.python.org/issue32922]: dbm.open() now encodes filename with the filesystem encoding rather than default encoding.

bpo-32859 [https://bugs.python.org/issue32859]: In os.dup2, don’t check every call whether the dup3 syscall exists or not.

bpo-21060 [https://bugs.python.org/issue21060]: Rewrite confusing message from setup.py upload from « No dist file created in earlier command » to the more helpful « Must create and upload files in one command ».

bpo-32857 [https://bugs.python.org/issue32857]: In tkinter, after_cancel(None) now raises a ValueError instead of canceling the first scheduled function. Patch by Cheryl Sabella.

bpo-32852 [https://bugs.python.org/issue32852]: Make sure sys.argv remains as a list when running trace.

bpo-32841 [https://bugs.python.org/issue32841]: Fixed asyncio.Condition issue which silently ignored cancellation after notifying and cancelling a conditional lock. Patch by Bar Harel.

bpo-31787 [https://bugs.python.org/issue31787]: Fixed refleaks of __init__() methods in various modules. (Contributed by Oren Milman)

bpo-30157 [https://bugs.python.org/issue30157]: Fixed guessing quote and delimiter in csv.Sniffer.sniff() when only the last field is quoted. Patch by Jake Davis.

bpo-32394 [https://bugs.python.org/issue32394]: socket: Remove TCP_FASTOPEN, TCP_KEEPCNT flags on older version Windows during run-time.

bpo-32777 [https://bugs.python.org/issue32777]: Fix a rare but potential pre-exec child process deadlock in subprocess on POSIX systems when marking file descriptors inheritable on exec in the child process. This bug appears to have been introduced in 3.4.

bpo-32647 [https://bugs.python.org/issue32647]: The ctypes module used to depend on indirect linking for dlopen. The shared extension is now explicitly linked against libdl on platforms with dl.

bpo-32734 [https://bugs.python.org/issue32734]: Fixed asyncio.Lock() safety issue which allowed acquiring and locking the same lock multiple times, without it being free. Patch by Bar Harel.

bpo-32727 [https://bugs.python.org/issue32727]: Do not include name field in SMTP envelope from address. Patch by Stéphane Wirtel

bpo-27931 [https://bugs.python.org/issue27931]: Fix email address header parsing error when the username is an empty quoted string. Patch by Xiang Zhang.

bpo-32304 [https://bugs.python.org/issue32304]: distutils” upload command no longer corrupts tar files ending with a CR byte, and no longer tries to convert CR to CRLF in any of the upload text fields.

bpo-32502 [https://bugs.python.org/issue32502]: uuid.uuid1 no longer raises an exception if a 64-bit hardware address is encountered.

bpo-31848 [https://bugs.python.org/issue31848]: Fix the error handling in Aifc_read.initfp() when the SSND chunk is not found. Patch by Zackery Spytz.

bpo-32555 [https://bugs.python.org/issue32555]: On FreeBSD and Solaris, os.strerror() now always decode the byte string from the current locale encoding, rather than using ASCII/surrogateescape in some cases.

bpo-32521 [https://bugs.python.org/issue32521]: The nis module is now compatible with new libnsl and headers location.

bpo-32473 [https://bugs.python.org/issue32473]: Improve ABCMeta._dump_registry() output readability

bpo-32521 [https://bugs.python.org/issue32521]: glibc has removed Sun RPC. Use replacement libtirpc headers and library in nis module.

bpo-32228 [https://bugs.python.org/issue32228]: Ensure that truncate() preserves the file position (as reported by tell()) after writes longer than the buffer size.

bpo-26133 [https://bugs.python.org/issue26133]: Don’t unsubscribe signals in asyncio UNIX event loop on interpreter shutdown.

bpo-32185 [https://bugs.python.org/issue32185]: The SSL module no longer sends IP addresses in SNI TLS extension on platforms with OpenSSL 1.0.2+ or inet_pton.

bpo-32323 [https://bugs.python.org/issue32323]: urllib.parse.urlsplit() does not convert zone-id (scope) to lower case for scoped IPv6 addresses in hostnames now.

bpo-32302 [https://bugs.python.org/issue32302]: Fix bdist_wininst of distutils for CRT v142: it binary compatible with CRT v140.

bpo-32255 [https://bugs.python.org/issue32255]: A single empty field is now always quoted when written into a CSV file. This allows to distinguish an empty row from a row consisting of a single empty field. Patch by Licht Takeuchi.

bpo-32277 [https://bugs.python.org/issue32277]: Raise NotImplementedError instead of SystemError on platforms where chmod(..., follow_symlinks=False) is not supported. Patch by Anthony Sottile.

bpo-32199 [https://bugs.python.org/issue32199]: The getnode() ip getter now uses “ip link” instead of “ip link list”.

bpo-27456 [https://bugs.python.org/issue27456]: Ensure TCP_NODELAY is set on Linux. Tests by Victor Stinner.

bpo-31900 [https://bugs.python.org/issue31900]: The locale.localeconv() function now sets temporarily the LC_CTYPE locale to the LC_NUMERIC locale to decode decimal_point and thousands_sep byte strings if they are non-ASCII or longer than 1 byte, and the LC_NUMERIC locale is different than the LC_CTYPE locale. This temporary change affects other threads.

Same change for the str.format() method when formatting a number (int, float, float and subclasses) with the n type (ex: '{:n}'.format(1234)).

bpo-31802 [https://bugs.python.org/issue31802]: Importing native path module (posixpath, ntpath) now works even if the os module still is not imported.

Documentation

bpo-17232 [https://bugs.python.org/issue17232]: Clarify docs for -O and -OO. Patch by Terry Reedy.

bpo-32800 [https://bugs.python.org/issue32800]: Update link to w3c doc for xml default namespaces.

bpo-8722 [https://bugs.python.org/issue8722]: Document __getattr__() behavior when property get() method raises AttributeError.

bpo-32614 [https://bugs.python.org/issue32614]: Modify RE examples in documentation to use raw strings to prevent DeprecationWarning and add text to REGEX HOWTO to highlight the deprecation.

bpo-31972 [https://bugs.python.org/issue31972]: Improve docstrings for pathlib.PurePath subclasses.

bpo-17799 [https://bugs.python.org/issue17799]: Explain real behaviour of sys.settrace and sys.setprofile and their C-API counterparts regarding which type of events are received in each function. Patch by Pablo Galindo Salgado.

Tests

bpo-32517 [https://bugs.python.org/issue32517]: Fix failing test_asyncio on macOS 10.12.2+ due to transport of KqueueSelector loop was not being closed.

bpo-32721 [https://bugs.python.org/issue32721]: Fix test_hashlib to not fail if the _md5 module is not built.

bpo-32252 [https://bugs.python.org/issue32252]: Fix faulthandler_suppress_crash_report() used to prevent core dump files when testing crashes. getrlimit() returns zero on success.

bpo-31518 [https://bugs.python.org/issue31518]: Debian Unstable has disabled TLS 1.0 and 1.1 for SSLv23_METHOD(). Change TLS/SSL protocol of some tests to PROTOCOL_TLS or PROTOCOL_TLSv1_2 to make them pass on Debian.

Build

bpo-32635 [https://bugs.python.org/issue32635]: Fix segfault of the crypt module when libxcrypt is provided instead of libcrypt at the system.

Windows

bpo-33016 [https://bugs.python.org/issue33016]: Fix potential use of uninitialized memory in nt._getfinalpathname

bpo-32903 [https://bugs.python.org/issue32903]: Fix a memory leak in os.chdir() on Windows if the current directory is set to a UNC path.

bpo-31966 [https://bugs.python.org/issue31966]: Fixed WindowsConsoleIO.write() for writing empty data.

bpo-32409 [https://bugs.python.org/issue32409]: Ensures activate.bat can handle Unicode contents.

bpo-32457 [https://bugs.python.org/issue32457]: Improves handling of denormalized executable path when launching Python.

bpo-32370 [https://bugs.python.org/issue32370]: Use the correct encoding for ipconfig output in the uuid module. Patch by Segev Finer.

bpo-29248 [https://bugs.python.org/issue29248]: Fix os.readlink() on Windows, which was mistakenly treating the PrintNameOffset field of the reparse data buffer as a number of characters instead of bytes. Patch by Craig Holmquist and SSE4.

bpo-32588 [https://bugs.python.org/issue32588]: Create standalone _distutils_findvs module.

macOS

bpo-32726 [https://bugs.python.org/issue32726]: Provide an additional, more modern macOS installer variant that supports macOS 10.9+ systems in 64-bit mode only. Upgrade the supplied third-party libraries to OpenSSL 1.0.2n, XZ 5.2.3, and SQLite 3.22.0. The 10.9+ installer now links with and supplies its own copy of Tcl/Tk 8.6.8.

IDLE

bpo-32984 [https://bugs.python.org/issue32984]: Set __file__ while running a startup file. Like Python, IDLE optionally runs one startup file in the Shell window before presenting the first interactive input prompt. For IDLE, -s runs a file named in environmental variable IDLESTARTUP or PYTHONSTARTUP; -r file runs file. Python sets __file__ to the startup file name before running the file and unsets it before the first prompt. IDLE now does the same when run normally, without the -n option.

bpo-32940 [https://bugs.python.org/issue32940]: Simplify and rename StringTranslatePseudoMapping in pyparse.

bpo-32916 [https://bugs.python.org/issue32916]: Change str to code in pyparse.

bpo-32905 [https://bugs.python.org/issue32905]: Remove unused code in pyparse module.

bpo-32874 [https://bugs.python.org/issue32874]: Add tests for pyparse.

bpo-32837 [https://bugs.python.org/issue32837]: Using the system and place-dependent default encoding for open() is a bad idea for IDLE’s system and location-independent files.

bpo-32826 [https://bugs.python.org/issue32826]: Add « encoding=utf-8 » to open() in IDLE’s test_help_about. GUI test test_file_buttons() only looks at initial ascii-only lines, but failed on systems where open() defaults to “ascii” because readline() internally reads and decodes far enough ahead to encounter a non-ascii character in CREDITS.txt.

bpo-32765 [https://bugs.python.org/issue32765]: Update configdialog General tab docstring to add new widgets to the widget list.

Tools/Demos

bpo-24960 [https://bugs.python.org/issue24960]: 2to3 and lib2to3 can now read pickled grammar files using pkgutil.get_data() rather than probing the filesystem. This lets 2to3 and lib2to3 work when run from a zipfile.

bpo-32222 [https://bugs.python.org/issue32222]: Fix pygettext not extracting docstrings for functions with type annotated arguments. Patch by Toby Harradine.

C API

bpo-29084 [https://bugs.python.org/issue29084]: Undocumented C API for OrderedDict has been excluded from the limited C API. It was added by mistake and actually never worked in the limited C API.

Python 3.6.4 final

Release date: 2017-12-18

There were no new code changes in version 3.6.4 since v3.6.4rc1.

Python 3.6.4 release candidate 1

Release date: 2017-12-05

Core and Builtins

bpo-32176 [https://bugs.python.org/issue32176]: co_flags.CO_NOFREE is now always set correctly by the code object constructor based on freevars and cellvars, rather than needing to be set correctly by the caller. This ensures it will be cleared automatically when additional cell references are injected into a modified code object and function.

bpo-31949 [https://bugs.python.org/issue31949]: Fixed several issues in printing tracebacks (PyTraceBack_Print()).

Setting sys.tracebacklimit to 0 or less now suppresses printing tracebacks.

Setting sys.tracebacklimit to None now causes using the default limit.

Setting sys.tracebacklimit to an integer larger than LONG_MAX now means using the limit LONG_MAX rather than the default limit.

Fixed integer overflows in the case of more than 2**31 traceback items on Windows.

Fixed output errors handling.

bpo-30696 [https://bugs.python.org/issue30696]: Fix the interactive interpreter looping endlessly when no memory.

bpo-20047 [https://bugs.python.org/issue20047]: Bytearray methods partition() and rpartition() now accept only bytes-like objects as separator, as documented. In particular they now raise TypeError rather of returning a bogus result when an integer is passed as a separator.

bpo-31852 [https://bugs.python.org/issue31852]: Fix a segmentation fault caused by a combination of the async soft keyword and continuation lines.

bpo-21720 [https://bugs.python.org/issue21720]: BytesWarning no longer emitted when the fromlist argument of __import__() or the __all__ attribute of the module contain bytes instances.

bpo-31825 [https://bugs.python.org/issue31825]: Fixed OverflowError in the “unicode-escape” codec and in codecs.escape_decode() when decode an escaped non-ascii byte.

bpo-28603 [https://bugs.python.org/issue28603]: Print the full context/cause chain of exceptions on interpreter exit, even if an exception in the chain is unhashable or compares equal to later ones. Patch by Zane Bitter.

bpo-31786 [https://bugs.python.org/issue31786]: Fix timeout rounding in the select module to round correctly negative timeouts between -1.0 and 0.0. The functions now block waiting for events as expected. Previously, the call was incorrectly non-blocking. Patch by Pablo Galindo.

bpo-31642 [https://bugs.python.org/issue31642]: Restored blocking « from package import module » by setting sys.modules[« package.module »] to None.

bpo-31626 [https://bugs.python.org/issue31626]: Fixed a bug in debug memory allocator. There was a write to freed memory after shrinking a memory block.

bpo-31619 [https://bugs.python.org/issue31619]: Fixed a ValueError when convert a string with large number of underscores to integer with binary base.

bpo-31592 [https://bugs.python.org/issue31592]: Fixed an assertion failure in Python parser in case of a bad unicodedata.normalize(). Patch by Oren Milman.

bpo-31588 [https://bugs.python.org/issue31588]: Raise a TypeError with a helpful error message when class creation fails due to a metaclass with a bad __prepare__() method. Patch by Oren Milman.

bpo-31566 [https://bugs.python.org/issue31566]: Fix an assertion failure in _warnings.warn() in case of a bad __name__ global. Patch by Oren Milman.

bpo-31505 [https://bugs.python.org/issue31505]: Fix an assertion failure in json, in case _json.make_encoder() received a bad encoder() argument. Patch by Oren Milman.

bpo-31492 [https://bugs.python.org/issue31492]: Fix assertion failures in case of failing to import from a module with a bad __name__ attribute, and in case of failing to access an attribute of such a module. Patch by Oren Milman.

bpo-31490 [https://bugs.python.org/issue31490]: Fix an assertion failure in ctypes class definition, in case the class has an attribute whose name is specified in _anonymous_ but not in _fields_. Patch by Oren Milman.

bpo-31478 [https://bugs.python.org/issue31478]: Fix an assertion failure in _random.Random.seed() in case the argument has a bad __abs__() method. Patch by Oren Milman.

bpo-31315 [https://bugs.python.org/issue31315]: Fix an assertion failure in imp.create_dynamic(), when spec.name is not a string. Patch by Oren Milman.

bpo-31311 [https://bugs.python.org/issue31311]: Fix a crash in the __setstate__() method of ctypes._CData, in case of a bad __dict__. Patch by Oren Milman.

bpo-31293 [https://bugs.python.org/issue31293]: Fix crashes in true division and multiplication of a timedelta object by a float with a bad as_integer_ratio() method. Patch by Oren Milman.

bpo-31285 [https://bugs.python.org/issue31285]: Fix an assertion failure in warnings.warn_explicit, when the return value of the received loader’s get_source() has a bad splitlines() method. Patch by Oren Milman.

bpo-30817 [https://bugs.python.org/issue30817]: PyErr_PrintEx() clears now the ignored exception that may be raised by _PySys_SetObjectId(), for example when no memory.

Library

bpo-28556 [https://bugs.python.org/issue28556]: Two minor fixes for typing module: allow shallow copying instances of generic classes, improve interaction of __init_subclass__ with generics. Original PRs by Ivan Levkivskyi.

bpo-27240 [https://bugs.python.org/issue27240]: The header folding algorithm for the new email policies has been rewritten, which also fixes bpo-30788 [https://bugs.python.org/issue30788], bpo-31831 [https://bugs.python.org/issue31831], and bpo-32182 [https://bugs.python.org/issue32182]. In particular, RFC2231 folding is now done correctly.

bpo-32186 [https://bugs.python.org/issue32186]: io.FileIO.readall() and io.FileIO.read() now release the GIL when getting the file size. Fixed hang of all threads with inaccessible NFS server. Patch by Nir Soffer.

bpo-12239 [https://bugs.python.org/issue12239]: Make msilib.SummaryInformation.GetProperty() return None when the value of property is VT_EMPTY. Initial patch by Mark Mc Mahon.

bpo-31325 [https://bugs.python.org/issue31325]: Fix wrong usage of collections.namedtuple() in the RobotFileParser.parse() method.

Initial patch by Robin Wellner.

bpo-12382 [https://bugs.python.org/issue12382]: msilib.OpenDatabase() now raises a better exception message when it couldn’t open or create an MSI file. Initial patch by William Tisäter.

bpo-32110 [https://bugs.python.org/issue32110]: codecs.StreamReader.read(n) now returns not more than n characters/bytes for non-negative n. This makes it compatible with read() methods of other file-like objects.

bpo-32072 [https://bugs.python.org/issue32072]: Fixed issues with binary plists:

Fixed saving bytearrays.

Identical objects will be saved only once.

Equal references will be load as identical objects.

Added support for saving and loading recursive data structures.

bpo-32034 [https://bugs.python.org/issue32034]: Make asyncio.IncompleteReadError and LimitOverrunError pickleable.

bpo-32015 [https://bugs.python.org/issue32015]: Fixed the looping of asyncio in the case of reconnection the socket during waiting async read/write from/to the socket.

bpo-32011 [https://bugs.python.org/issue32011]: Restored support of loading marshal files with the TYPE_INT64 code. These files can be produced in Python 2.7.

bpo-31970 [https://bugs.python.org/issue31970]: Reduce performance overhead of asyncio debug mode.

bpo-9678 [https://bugs.python.org/issue9678]: Fixed determining the MAC address in the uuid module:

Using ifconfig on NetBSD and OpenBSD.

Using arp on Linux, FreeBSD, NetBSD and OpenBSD.

Based on patch by Takayuki Shimizukawa.

bpo-30057 [https://bugs.python.org/issue30057]: Fix potential missed signal in signal.signal().

bpo-31933 [https://bugs.python.org/issue31933]: Fix Blake2 params leaf_size and node_offset on big endian platforms. Patch by Jack O’Connor.

bpo-31927 [https://bugs.python.org/issue31927]: Fixed compilation of the socket module on NetBSD 8. Fixed assertion failure or reading arbitrary data when parse a AF_BLUETOOTH address on NetBSD and DragonFly BSD.

bpo-27666 [https://bugs.python.org/issue27666]: Fixed stack corruption in curses.box() and curses.ungetmouse() when the size of types chtype or mmask_t is less than the size of C long. curses.box() now accepts characters as arguments. Based on patch by Steve Fink.

bpo-31897 [https://bugs.python.org/issue31897]: plistlib now catches more errors when read binary plists and raises InvalidFileException instead of unexpected exceptions.

bpo-25720 [https://bugs.python.org/issue25720]: Fix the method for checking pad state of curses WINDOW. Patch by Masayuki Yamamoto.

bpo-31893 [https://bugs.python.org/issue31893]: Fixed the layout of the kqueue_event structure on OpenBSD and NetBSD. Fixed the comparison of the kqueue_event objects.

bpo-31891 [https://bugs.python.org/issue31891]: Fixed building the curses module on NetBSD.

bpo-28416 [https://bugs.python.org/issue28416]: Instances of pickle.Pickler subclass with the persistent_id() method and pickle.Unpickler subclass with the persistent_load() method no longer create reference cycles.

bpo-28326 [https://bugs.python.org/issue28326]: Fix multiprocessing.Process when stdout and/or stderr is closed or None.

bpo-31457 [https://bugs.python.org/issue31457]: If nested log adapters are used, the inner process() methods are no longer omitted.

bpo-31457 [https://bugs.python.org/issue31457]: The manager property on LoggerAdapter objects is now properly settable.

bpo-31806 [https://bugs.python.org/issue31806]: Fix timeout rounding in time.sleep(), threading.Lock.acquire() and socket.socket.settimeout() to round correctly negative timeouts between -1.0 and 0.0. The functions now block waiting for events as expected. Previously, the call was incorrectly non-blocking. Patch by Pablo Galindo.

bpo-28603 [https://bugs.python.org/issue28603]: traceback: Fix a TypeError that occurred during printing of exception tracebacks when either the current exception or an exception in its context/cause chain is unhashable. Patch by Zane Bitter.

bpo-30058 [https://bugs.python.org/issue30058]: Fixed buffer overflow in select.kqueue.control().

bpo-31770 [https://bugs.python.org/issue31770]: Prevent a crash when calling the __init__() method of a sqlite3.Cursor object more than once. Patch by Oren Milman.

bpo-31672 [https://bugs.python.org/issue31672]: idpattern in string.Template matched some non-ASCII characters. Now it uses -i regular expression local flag to avoid non-ASCII characters.

bpo-31764 [https://bugs.python.org/issue31764]: Prevent a crash in sqlite3.Cursor.close() in case the Cursor object is uninitialized. Patch by Oren Milman.

bpo-31752 [https://bugs.python.org/issue31752]: Fix possible crash in timedelta constructor called with custom integers.

bpo-31701 [https://bugs.python.org/issue31701]: On Windows, faulthandler.enable() now ignores MSC and COM exceptions.

bpo-31728 [https://bugs.python.org/issue31728]: Prevent crashes in _elementtree due to unsafe cleanup of Element.text and Element.tail. Patch by Oren Milman.

bpo-31620 [https://bugs.python.org/issue31620]: an empty asyncio.Queue now doesn’t leak memory when queue.get pollers timeout

bpo-31632 [https://bugs.python.org/issue31632]: Fix method set_protocol() of class _SSLProtocolTransport in asyncio module. This method was previously modifying a wrong reference to the protocol.

bpo-31675 [https://bugs.python.org/issue31675]: Fixed memory leaks in Tkinter’s methods splitlist() and split() when pass a string larger than 2 GiB.

bpo-31673 [https://bugs.python.org/issue31673]: Fixed typo in the name of Tkinter’s method adderrorinfo().

bpo-30806 [https://bugs.python.org/issue30806]: Fix the string representation of a netrc object.

bpo-15037 [https://bugs.python.org/issue15037]: Added a workaround for getkey() in curses for ncurses 5.7 and earlier.

bpo-25351 [https://bugs.python.org/issue25351]: Avoid venv activate failures with undefined variables

bpo-25532 [https://bugs.python.org/issue25532]: inspect.unwrap() will now only try to unwrap an object sys.getrecursionlimit() times, to protect against objects which create a new object on every attribute access.

bpo-30347 [https://bugs.python.org/issue30347]: Stop crashes when concurrently iterate over itertools.groupby() iterators.

bpo-31516 [https://bugs.python.org/issue31516]: threading.current_thread() should not return a dummy thread at shutdown.

bpo-31351 [https://bugs.python.org/issue31351]: python -m ensurepip now exits with non-zero exit code if pip bootstrapping has failed.

bpo-31482 [https://bugs.python.org/issue31482]: random.seed() now works with bytes in version=1

bpo-31334 [https://bugs.python.org/issue31334]: Fix poll.poll([timeout]) in the select module for arbitrary negative timeouts on all OSes where it can only be a non-negative integer or -1. Patch by Riccardo Coccioli.

bpo-31310 [https://bugs.python.org/issue31310]: multiprocessing’s semaphore tracker should be launched again if crashed.

bpo-31308 [https://bugs.python.org/issue31308]: Make multiprocessing’s forkserver process immune to Ctrl-C and other user interruptions. If it crashes, restart it when necessary.

Documentation

bpo-32105 [https://bugs.python.org/issue32105]: Added asyncio.BaseEventLoop.connect_accepted_socket versionadded marker.

bpo-31537 [https://bugs.python.org/issue31537]: Fix incorrect usage of get_history_length in readline documentation example code. Patch by Brad Smith.

bpo-30085 [https://bugs.python.org/issue30085]: The operator functions without double underscores are preferred for clarity. The one with underscores are only kept for back-compatibility.

Tests

bpo-31380 [https://bugs.python.org/issue31380]: Skip test_httpservers test_undecodable_file on macOS: fails on APFS.

bpo-31705 [https://bugs.python.org/issue31705]: Skip test_socket.test_sha256() on Linux kernel older than 4.5. The test fails with ENOKEY on kernel 3.10 (on ppc64le). A fix was merged into the kernel 4.5.

bpo-31174 [https://bugs.python.org/issue31174]: Fix test_tools.test_unparse: DirectoryTestCase now stores the names sample to always test the same files. It prevents false alarms when hunting reference leaks.

bpo-30695 [https://bugs.python.org/issue30695]: Add the set_nomemory(start, stop) and remove_mem_hooks() functions to the _testcapi module.

Build

bpo-32059 [https://bugs.python.org/issue32059]: detect_modules() in setup.py now also searches the sysroot paths when cross-compiling.

bpo-31957 [https://bugs.python.org/issue31957]: Fixes Windows SDK version detection when building for Windows.

bpo-31609 [https://bugs.python.org/issue31609]: Fixes quotes in PCbuild/clean.bat

bpo-31934 [https://bugs.python.org/issue31934]: Abort the build when building out of a not clean source tree.

bpo-31926 [https://bugs.python.org/issue31926]: Fixed Argument Clinic sometimes causing compilation errors when there was more than one function and/or method in a .c file with the same name.

bpo-28791 [https://bugs.python.org/issue28791]: Update Windows builds to use SQLite 3.21.0.

bpo-28791 [https://bugs.python.org/issue28791]: Update OS X installer to use SQLite 3.21.0.

bpo-22140 [https://bugs.python.org/issue22140]: Prevent double substitution of prefix in python-config.sh.

bpo-31536 [https://bugs.python.org/issue31536]: Avoid wholesale rebuild after make regen-all if nothing changed.

Windows

bpo-1102 [https://bugs.python.org/issue1102]: Return None when View.Fetch() returns ERROR_NO_MORE_ITEMS instead of raising MSIError.

Initial patch by Anthony Tuininga.

bpo-31944 [https://bugs.python.org/issue31944]: Fixes Modify button in Apps and Features dialog.

macOS

bpo-31392 [https://bugs.python.org/issue31392]: Update macOS installer to use OpenSSL 1.0.2m

IDLE

bpo-32207 [https://bugs.python.org/issue32207]: Improve tk event exception tracebacks in IDLE. When tk event handling is driven by IDLE’s run loop, a confusing and distracting queue.EMPTY traceback context is no longer added to tk event exception tracebacks. The traceback is now the same as when event handling is driven by user code. Patch based on a suggestion by Serhiy Storchaka.

bpo-32164 [https://bugs.python.org/issue32164]: Delete unused file idlelib/tabbedpages.py. Use of TabbedPageSet in configdialog was replaced by ttk.Notebook.

bpo-32100 [https://bugs.python.org/issue32100]: IDLE: Fix old and new bugs in pathbrowser; improve tests. Patch mostly by Cheryl Sabella.

bpo-31858 [https://bugs.python.org/issue31858]: IDLE – Restrict shell prompt manipulation to the shell. Editor and output windows only see an empty last prompt line. This simplifies the code and fixes a minor bug when newline is inserted. Sys.ps1, if present, is read on Shell start-up, but is not set or changed.

bpo-31860 [https://bugs.python.org/issue31860]: The font sample in the IDLE configuration dialog is now editable. Changes persist while IDLE remains open

bpo-31836 [https://bugs.python.org/issue31836]: Test_code_module now passes if run after test_idle, which sets ps1.

The code module uses sys.ps1 if present or sets it to “>>> “ if not. Test_code_module now properly tests both behaviors. Ditto for ps2.

bpo-28603 [https://bugs.python.org/issue28603]: Fix a TypeError that caused a shell restart when printing a traceback that includes an exception that is unhashable. Patch by Zane Bitter.

bpo-13802 [https://bugs.python.org/issue13802]: Use non-Latin characters in the IDLE’s Font settings sample. Even if one selects a font that defines a limited subset of the unicode Basic Multilingual Plane, tcl/tk will use other fonts that define a character. The expanded example give users of non-Latin characters a better idea of what they might see in IDLE’s shell and editors. To make room for the expanded sample, frames on the Font tab are re-arranged. The Font/Tabs help explains a bit about the additions.

bpo-31460 [https://bugs.python.org/issue31460]: Simplify the API of IDLE’s Module Browser.

Passing a widget instead of an flist with a root widget opens the option of creating a browser frame that is only part of a window. Passing a full file name instead of pieces assumed to come from a .py file opens the possibility of browsing python files that do not end in .py.

bpo-31649 [https://bugs.python.org/issue31649]: IDLE - Make _htest, _utest parameters keyword only.

bpo-31559 [https://bugs.python.org/issue31559]: Remove test order dependence in idle_test.test_browser.

bpo-31459 [https://bugs.python.org/issue31459]: Rename IDLE’s module browser from Class Browser to Module Browser. The original module-level class and method browser became a module browser, with the addition of module-level functions, years ago. Nested classes and functions were added yesterday. For back-compatibility, the virtual event <<open-class-browser>>, which appears on the Keys tab of the Settings dialog, is not changed. Patch by Cheryl Sabella.

bpo-31500 [https://bugs.python.org/issue31500]: Default fonts now are scaled on HiDPI displays.

bpo-1612262 [https://bugs.python.org/issue1612262]: IDLE module browser now shows nested classes and functions. Original patches for code and tests by Guilherme Polo and Cheryl Sabella, respectively.

Tools/Demos

bpo-30722 [https://bugs.python.org/issue30722]: Make redemo work with Python 3.6 and newer versions.

Also, remove the LOCALE option since it doesn’t work with string patterns in Python 3.

Patch by Christoph Sarnowski.

C API

bpo-20891 [https://bugs.python.org/issue20891]: Fix PyGILState_Ensure(). When PyGILState_Ensure() is called in a non-Python thread before PyEval_InitThreads(), only call PyEval_InitThreads() after calling PyThreadState_New() to fix a crash.

bpo-31532 [https://bugs.python.org/issue31532]: Fix memory corruption due to allocator mix in getpath.c between Py_GetPath() and Py_SetPath()

bpo-30697 [https://bugs.python.org/issue30697]: The PyExc_RecursionErrorInst singleton is removed and PyErr_NormalizeException() does not use it anymore. This singleton is persistent and its members being never cleared may cause a segfault during finalization of the interpreter. See also bpo-22898 [https://bugs.python.org/issue22898].

Python 3.6.3 final

Release date: 2017-10-03

Library

bpo-31641 [https://bugs.python.org/issue31641]: Re-allow arbitrary iterables in concurrent.futures.as_completed(). Fixes regression in 3.6.3rc1.

Build

bpo-31662 [https://bugs.python.org/issue31662]: Fix typos in Windows uploadrelease.bat script. Fix Windows Doc build issues in Doc/make.bat.

bpo-31423 [https://bugs.python.org/issue31423]: Fix building the PDF documentation with newer versions of Sphinx.

Python 3.6.3 release candidate 1

Release date: 2017-09-18

Security

bpo-29781 [https://bugs.python.org/issue29781]: SSLObject.version() now correctly returns None when handshake over BIO has not been performed yet.

bpo-30947 [https://bugs.python.org/issue30947]: Upgrade libexpat embedded copy from version 2.2.1 to 2.2.3 to get security fixes.

Core and Builtins

bpo-31471 [https://bugs.python.org/issue31471]: Fix an assertion failure in subprocess.Popen() on Windows, in case the env argument has a bad keys() method. Patch by Oren Milman.

bpo-31418 [https://bugs.python.org/issue31418]: Fix an assertion failure in PyErr_WriteUnraisable() in case of an exception with a bad __module__ attribute. Patch by Oren Milman.

bpo-31416 [https://bugs.python.org/issue31416]: Fix assertion failures in case of a bad warnings.filters or warnings.defaultaction. Patch by Oren Milman.

bpo-31411 [https://bugs.python.org/issue31411]: Raise a TypeError instead of SystemError in case warnings.onceregistry is not a dictionary. Patch by Oren Milman.

bpo-31373 [https://bugs.python.org/issue31373]: Fix several possible instances of undefined behavior due to floating-point demotions.

bpo-30465 [https://bugs.python.org/issue30465]: Location information (lineno and col_offset) in f-strings is now (mostly) correct. This fixes tools like flake8 from showing warnings on the wrong line (typically the first line of the file).

bpo-31343 [https://bugs.python.org/issue31343]: Include sys/sysmacros.h for major(), minor(), and makedev(). GNU C libray plans to remove the functions from sys/types.h.

bpo-31291 [https://bugs.python.org/issue31291]: Fix an assertion failure in zipimport.zipimporter.get_data on Windows, when the return value of pathname.replace('/','\\') isn’t a string. Patch by Oren Milman.

bpo-31271 [https://bugs.python.org/issue31271]: Fix an assertion failure in the write() method of io.TextIOWrapper, when the encoder doesn’t return a bytes object. Patch by Oren Milman.

bpo-31243 [https://bugs.python.org/issue31243]: Fix a crash in some methods of io.TextIOWrapper, when the decoder’s state is invalid. Patch by Oren Milman.

bpo-30721 [https://bugs.python.org/issue30721]: print now shows correct usage hint for using Python 2 redirection syntax. Patch by Sanyam Khurana.

bpo-31070 [https://bugs.python.org/issue31070]: Fix a race condition in importlib _get_module_lock().

bpo-31095 [https://bugs.python.org/issue31095]: Fix potential crash during GC caused by tp_dealloc which doesn’t call PyObject_GC_UnTrack().

bpo-31071 [https://bugs.python.org/issue31071]: Avoid masking original TypeError in call with * unpacking when other arguments are passed.

bpo-30978 [https://bugs.python.org/issue30978]: str.format_map() now passes key lookup exceptions through. Previously any exception was replaced with a KeyError exception.

bpo-30808 [https://bugs.python.org/issue30808]: Use _Py_atomic API for concurrency-sensitive signal state.

bpo-30876 [https://bugs.python.org/issue30876]: Relative import from unloaded package now reimports the package instead of failing with SystemError. Relative import from non-package now fails with ImportError rather than SystemError.

bpo-30703 [https://bugs.python.org/issue30703]: Improve signal delivery.

Avoid using Py_AddPendingCall from signal handler, to avoid calling signal-unsafe functions. The tests I’m adding here fail without the rest of the patch, on Linux and OS X. This means our signal delivery logic had defects (some signals could be lost).

bpo-30765 [https://bugs.python.org/issue30765]: Avoid blocking in pthread_mutex_lock() when PyThread_acquire_lock() is asked not to block.

bpo-31161 [https://bugs.python.org/issue31161]: Make sure the “Missing parentheses” syntax error message is only applied to SyntaxError, not to subclasses. Patch by Martijn Pieters.

bpo-30814 [https://bugs.python.org/issue30814]: Fixed a race condition when import a submodule from a package.

bpo-30597 [https://bugs.python.org/issue30597]: print now shows expected input in custom error message when used as a Python 2 statement. Patch by Sanyam Khurana.

Library

bpo-31499 [https://bugs.python.org/issue31499]: xml.etree: Fix a crash when a parser is part of a reference cycle.

bpo-28556 [https://bugs.python.org/issue28556]: typing.get_type_hints now finds the right globalns for classes and modules by default (when no globalns was specified by the caller).

bpo-28556 [https://bugs.python.org/issue28556]: Speed improvements to the typing module. Original PRs by Ivan Levkivskyi and Mitar.

bpo-31544 [https://bugs.python.org/issue31544]: The C accelerator module of ElementTree ignored exceptions raised when looking up TreeBuilder target methods in XMLParser().

bpo-31234 [https://bugs.python.org/issue31234]: socket.create_connection() now fixes manually a reference cycle: clear the variable storing the last exception on success.

bpo-31457 [https://bugs.python.org/issue31457]: LoggerAdapter objects can now be nested.

bpo-31400 [https://bugs.python.org/issue31400]: Improves SSL error handling to avoid losing error numbers.

bpo-28958 [https://bugs.python.org/issue28958]: ssl.SSLContext() now uses OpenSSL error information when a context cannot be instantiated.

bpo-27340 [https://bugs.python.org/issue27340]: SSLSocket.sendall() now uses memoryview to create slices of data. This fixes support for all bytes-like object. It is also more efficient and avoids costly copies.

bpo-31178 [https://bugs.python.org/issue31178]: Fix string concatenation bug in rare error path in the subprocess module

bpo-31350 [https://bugs.python.org/issue31350]: Micro-optimize asyncio._get_running_loop() to become up to 10% faster.

bpo-31170 [https://bugs.python.org/issue31170]: expat: Update libexpat from 2.2.3 to 2.2.4. Fix copying of partial characters for UTF-8 input (libexpat bug 115): https://github.com/libexpat/libexpat/issues/115

bpo-29136 [https://bugs.python.org/issue29136]: Add TLS 1.3 cipher suites and OP_NO_TLSv1_3.

bpo-29212 [https://bugs.python.org/issue29212]: Fix concurrent.futures.thread.ThreadPoolExecutor threads to have a non repr() based thread name by default when no thread_name_prefix is supplied. They will now identify themselves as « ThreadPoolExecutor-y_n ».

bpo-9146 [https://bugs.python.org/issue9146]: Fix a segmentation fault in _hashopenssl when standard hash functions such as md5 are not available in the linked OpenSSL library. As in some special FIPS-140 build environments.

bpo-27144 [https://bugs.python.org/issue27144]: The map() and as_completed() iterators in concurrent.futures now avoid keeping a reference to yielded objects.

bpo-10746 [https://bugs.python.org/issue10746]: Fix ctypes producing wrong PEP 3118 type codes for integer types.

bpo-22536 [https://bugs.python.org/issue22536]: The subprocess module now sets the filename when FileNotFoundError is raised on POSIX systems due to the executable or cwd not being found.

bpo-31249 [https://bugs.python.org/issue31249]: concurrent.futures: WorkItem.run() used by ThreadPoolExecutor now breaks a reference cycle between an exception object and the WorkItem object.

bpo-31247 [https://bugs.python.org/issue31247]: xmlrpc.server now explicitly breaks reference cycles when using sys.exc_info() in code handling exceptions.

bpo-30102 [https://bugs.python.org/issue30102]: The ssl and hashlib modules now call OPENSSL_add_all_algorithms_noconf() on OpenSSL < 1.1.0. The function detects CPU features and enables optimizations on some CPU architectures such as POWER8. Patch is based on research from Gustavo Serra Scalet.

bpo-31185 [https://bugs.python.org/issue31185]: Fixed miscellaneous errors in asyncio speedup module.

bpo-31135 [https://bugs.python.org/issue31135]: ttk: fix the destroy() method of LabeledScale and OptionMenu classes. Call the parent destroy() method even if the used attribute doesn’t exist. The LabeledScale.destroy() method now also explicitly clears label and scale attributes to help the garbage collector to destroy all widgets.

bpo-31107 [https://bugs.python.org/issue31107]: Fix copyreg._slotnames() mangled attribute calculation for classes whose name begins with an underscore. Patch by Shane Harvey.

bpo-31061 [https://bugs.python.org/issue31061]: Fixed a crash when using asyncio and threads.

bpo-30502 [https://bugs.python.org/issue30502]: Fix handling of long oids in ssl. Based on patch by Christian Heimes.

bpo-30119 [https://bugs.python.org/issue30119]: ftplib.FTP.putline() now throws ValueError on commands that contains CR or LF. Patch by Dong-hee Na.

bpo-30595 [https://bugs.python.org/issue30595]: multiprocessing.Queue.get() with a timeout now polls its reader in non-blocking mode if it succeeded to acquire the lock but the acquire took longer than the timeout.

bpo-29403 [https://bugs.python.org/issue29403]: Fix unittest.mock’s autospec to not fail on method-bound builtin functions. Patch by Aaron Gallagher.

bpo-30961 [https://bugs.python.org/issue30961]: Fix decrementing a borrowed reference in tracemalloc.

bpo-25684 [https://bugs.python.org/issue25684]: Change ttk.OptionMenu radiobuttons to be unique across instances of OptionMenu.

bpo-30886 [https://bugs.python.org/issue30886]: Fix multiprocessing.Queue.join_thread(): it now waits until the thread completes, even if the thread was started by the same process which created the queue.

bpo-29854 [https://bugs.python.org/issue29854]: Fix segfault in readline when using readline’s history-size option. Patch by Nir Soffer.

bpo-30319 [https://bugs.python.org/issue30319]: socket.close() now ignores ECONNRESET error.

bpo-30828 [https://bugs.python.org/issue30828]: Fix out of bounds write in asyncio.CFuture.remove_done_callback().

bpo-30807 [https://bugs.python.org/issue30807]: signal.setitimer() may disable the timer when passed a tiny value.

Tiny values (such as 1e-6) are valid non-zero values for setitimer(), which is specified as taking microsecond-resolution intervals. However, on some platform, our conversion routine could convert 1e-6 into a zero interval, therefore disabling the timer instead of (re-)scheduling it.

bpo-30441 [https://bugs.python.org/issue30441]: Fix bug when modifying os.environ while iterating over it

bpo-30532 [https://bugs.python.org/issue30532]: Fix email header value parser dropping folding white space in certain cases.

bpo-30879 [https://bugs.python.org/issue30879]: os.listdir() and os.scandir() now emit bytes names when called with bytes-like argument.

bpo-30746 [https://bugs.python.org/issue30746]: Prohibited the “=” character in environment variable names in os.putenv() and os.spawn*().

bpo-29755 [https://bugs.python.org/issue29755]: Fixed the lgettext() family of functions in the gettext module. They now always return bytes.

Documentation

bpo-31294 [https://bugs.python.org/issue31294]: Fix incomplete code snippet in the ZeroMQSocketListener and ZeroMQSocketHandler examples and adapt them to Python 3.

bpo-21649 [https://bugs.python.org/issue21649]: Add RFC 7525 and Mozilla server side TLS links to SSL documentation.

bpo-30803 [https://bugs.python.org/issue30803]: Clarify doc on truth value testing. Original patch by Peter Thomassen.

Tests

bpo-31320 [https://bugs.python.org/issue31320]: Silence traceback in test_ssl

bpo-25674 [https://bugs.python.org/issue25674]: Remove sha256.tbs-internet.com ssl test

bpo-30715 [https://bugs.python.org/issue30715]: Address ALPN callback changes for OpenSSL 1.1.0f. The latest version behaves like OpenSSL 1.0.2 and no longer aborts handshake.

bpo-30822 [https://bugs.python.org/issue30822]: regrtest: Exclude tzdata from regrtest –all. When running the test suite using –use=all / -u all, exclude tzdata since it makes test_datetime too slow (15-20 min on some buildbots) which then times out on some buildbots. Fix also regrtest command line parser to allow passing -u extralargefile to run test_zipfile64.

Build

bpo-30854 [https://bugs.python.org/issue30854]: Fix compile error when compiling –without-threads. Patch by Masayuki Yamamoto.

Windows

bpo-30389 [https://bugs.python.org/issue30389]: Adds detection of Visual Studio 2017 to distutils on Windows.

bpo-31340 [https://bugs.python.org/issue31340]: Change to building with MSVC v141 (included with Visual Studio 2017)

bpo-30581 [https://bugs.python.org/issue30581]: os.cpu_count() now returns the correct number of processors on Windows when the number of logical processors is greater than 64.

bpo-30731 [https://bugs.python.org/issue30731]: Add a missing xmlns to python.manifest so that it matches the schema.

IDLE

bpo-31493 [https://bugs.python.org/issue31493]: IDLE code context – fix code update and font update timers.

Canceling timers prevents a warning message when test_idle completes.

bpo-31488 [https://bugs.python.org/issue31488]: IDLE - Update non-key options in former extension classes. When applying configdialog changes, call .reload for each feature class. Change ParenMatch so updated options affect existing instances attached to existing editor windows.

bpo-31477 [https://bugs.python.org/issue31477]: IDLE - Improve rstrip entry in doc. Strip trailing whitespace strips more than blank spaces. Multiline string literals are not skipped.

bpo-31480 [https://bugs.python.org/issue31480]: IDLE - make tests pass with zzdummy extension disabled by default.

bpo-31421 [https://bugs.python.org/issue31421]: Document how IDLE runs tkinter programs. IDLE calls tcl/tk update in the background in order to make live

interaction and experimentation with tkinter applications much easier.

bpo-31414 [https://bugs.python.org/issue31414]: IDLE – fix tk entry box tests by deleting first. Adding to an int entry is not the same as deleting and inserting because int(“”) will fail.

bpo-31051 [https://bugs.python.org/issue31051]: Rearrange IDLE configdialog GenPage into Window, Editor, and Help sections.

bpo-30617 [https://bugs.python.org/issue30617]: IDLE - Add docstrings and tests for outwin subclass of editor.

Move some data and functions from the class to module level. Patch by Cheryl Sabella.

bpo-31287 [https://bugs.python.org/issue31287]: IDLE - Do not modify tkinter.message in test_configdialog.

bpo-27099 [https://bugs.python.org/issue27099]: Convert IDLE’s built-in “extensions” to regular features.

About 10 IDLE features were implemented as supposedly optional extensions. Their different behavior could be confusing or worse for users and not good for maintenance. Hence the conversion.

The main difference for users is that user configurable key bindings for builtin features are now handled uniformly. Now, editing a binding in a keyset only affects its value in the keyset. All bindings are defined together in the system-specific default keysets in config-extensions.def. All custom keysets are saved as a whole in config-extension.cfg. All take effect as soon as one clicks Apply or Ok.

The affected events are “<<force-open-completions>>”, “<<expand-word>>”, “<<force-open-calltip>>”, “<<flash-paren>>”, “<<format-paragraph>>”, “<<run-module>>”, “<<check-module>>”, and “<<zoom-height>>”. Any (global) customizations made before 3.6.3 will not affect their keyset-specific customization after 3.6.3. and vice versa.

Inital patch by Charles Wohlganger.

bpo-31206 [https://bugs.python.org/issue31206]: IDLE: Factor HighPage(Frame) class from ConfigDialog. Patch by Cheryl Sabella.

bpo-31001 [https://bugs.python.org/issue31001]: Add tests for configdialog highlight tab. Patch by Cheryl Sabella.

bpo-31205 [https://bugs.python.org/issue31205]: IDLE: Factor KeysPage(Frame) class from ConfigDialog. The slightly modified tests continue to pass. Patch by Cheryl Sabella.

bpo-31130 [https://bugs.python.org/issue31130]: IDLE – stop leaks in test_configdialog. Initial patch by Victor Stinner.

bpo-31002 [https://bugs.python.org/issue31002]: Add tests for configdialog keys tab. Patch by Cheryl Sabella.

bpo-19903 [https://bugs.python.org/issue19903]: IDLE: Calltips use inspect.signature instead of inspect.getfullargspec. This improves calltips for builtins converted to use Argument Clinic. Patch by Louie Lu.

bpo-31083 [https://bugs.python.org/issue31083]: IDLE - Add an outline of a TabPage class in configdialog. Update existing classes to match outline. Initial patch by Cheryl Sabella.

bpo-31050 [https://bugs.python.org/issue31050]: Factor GenPage(Frame) class from ConfigDialog. The slightly modified tests continue to pass. Patch by Cheryl Sabella.

bpo-31004 [https://bugs.python.org/issue31004]: IDLE - Factor FontPage(Frame) class from ConfigDialog.

Slightly modified tests continue to pass. Fix General tests. Patch mostly by Cheryl Sabella.

bpo-30781 [https://bugs.python.org/issue30781]: IDLE - Use ttk widgets in ConfigDialog. Patches by Terry Jan Reedy and Cheryl Sabella.

bpo-31060 [https://bugs.python.org/issue31060]: IDLE - Finish rearranging methods of ConfigDialog Grouping methods pertaining to each tab and the buttons will aid writing tests and improving the tabs and will enable splitting the groups into classes.

bpo-30853 [https://bugs.python.org/issue30853]: IDLE – Factor a VarTrace class out of ConfigDialog.

Instance tracers manages pairs consisting of a tk variable and a callback function. When tracing is turned on, setting the variable calls the function. Test coverage for the new class is 100%.

bpo-31003 [https://bugs.python.org/issue31003]: IDLE: Add more tests for General tab.

bpo-30993 [https://bugs.python.org/issue30993]: IDLE - Improve configdialog font page and tests.

In configdialog: Document causal pathways in create_font_tab docstring. Simplify some attribute names. Move set_samples calls to var_changed_font (idea from Cheryl Sabella). Move related functions to positions after the create widgets function.

In test_configdialog: Fix test_font_set so not order dependent. Fix renamed test_indent_scale so it tests the widget. Adjust tests for movement of set_samples call. Add tests for load functions. Put all font tests in one class and tab indent tests in another. Except for two lines, these tests completely cover the related functions.

bpo-30981 [https://bugs.python.org/issue30981]: IDLE – Add more configdialog font page tests.

bpo-28523 [https://bugs.python.org/issue28523]: IDLE: replace “colour” with “color” in configdialog.

bpo-30917 [https://bugs.python.org/issue30917]: Add tests for idlelib.config.IdleConf. Increase coverage from 46% to 96%. Patch by Louie Lu.

bpo-30934 [https://bugs.python.org/issue30934]: Document coverage details for idlelib tests.

Add section to idlelib/idle-test/README.txt.

Include check that branches are taken both ways.

Exclude IDLE-specific code that does not run during unit tests.

bpo-30913 [https://bugs.python.org/issue30913]: IDLE: Document ConfigDialog tk Vars, methods, and widgets in docstrings This will facilitate improving the dialog and splitting up the class. Original patch by Cheryl Sabella.

bpo-30899 [https://bugs.python.org/issue30899]: IDLE: Add tests for ConfigParser subclasses in config. Patch by Louie Lu.

bpo-30881 [https://bugs.python.org/issue30881]: IDLE: Add docstrings to browser.py. Patch by Cheryl Sabella.

bpo-30851 [https://bugs.python.org/issue30851]: IDLE: Remove unused variables in configdialog. One is a duplicate, one is set but cannot be altered by users. Patch by Cheryl Sabella.

bpo-30870 [https://bugs.python.org/issue30870]: IDLE: In Settings dialog, select font with Up, Down keys as well as mouse. Initial patch by Louie Lu.

bpo-8231 [https://bugs.python.org/issue8231]: IDLE: call config.IdleConf.GetUserCfgDir only once.

bpo-30779 [https://bugs.python.org/issue30779]: IDLE: Factor ConfigChanges class from configdialog, put in config; test. * In config, put dump test code in a function; run it and unittest in “if __name__ == “__main__”. * Add class config.ConfigChanges based on changes_class_v4.py on bpo issue. * Add class test_config.ChangesTest, partly using configdialog_tests_v1.py. * Revise configdialog to use ConfigChanges; see tracker msg297804. * Revise test_configdialog to match configdialog changes. * Remove configdialog functions unused or moved to ConfigChanges. Cheryl Sabella contributed parts of the patch.

bpo-30777 [https://bugs.python.org/issue30777]: IDLE: configdialog - Add docstrings and fix comments. Patch by Cheryl Sabella.

bpo-30495 [https://bugs.python.org/issue30495]: IDLE: Improve textview with docstrings, PEP8 names, and more tests. Patch by Cheryl Sabella.

bpo-30723 [https://bugs.python.org/issue30723]: IDLE: Make several improvements to parenmatch. Add “parens” style to highlight both opener and closer. Make “default” style, which is not default, a synonym for “opener”. Make time-delay work the same with all styles. Add help for config dialog extensions tab, including help for parenmatch. Add new tests. Original patch by Charles Wohlganger.

bpo-30674 [https://bugs.python.org/issue30674]: IDLE: add docstrings to grep module. Patch by Cheryl Sabella

bpo-21519 [https://bugs.python.org/issue21519]: IDLE’s basic custom key entry dialog now detects duplicates properly. Original patch by Saimadhav Heblikar.

bpo-29910 [https://bugs.python.org/issue29910]: IDLE no longer deletes a character after commenting out a region by a key shortcut. Add return 'break' for this and other potential conflicts between IDLE and default key bindings.

bpo-30728 [https://bugs.python.org/issue30728]: Review and change idlelib.configdialog names. Lowercase method and attribute names. Replace “colour” with “color”, expand overly cryptic names, delete unneeded underscores. Replace import * with specific imports. Patches by Cheryl Sabella.

bpo-6739 [https://bugs.python.org/issue6739]: IDLE: Verify user-entered key sequences by trying to bind them with tk. Add tests for all 3 validation functions. Original patch by G Polo. Tests added by Cheryl Sabella.

Tools/Demos

bpo-30983 [https://bugs.python.org/issue30983]: gdb integration commands (py-bt, etc.) work on optimized shared builds now, too. PEP 523 introduced _PyEval_EvalFrameDefault which inlines PyEval_EvalFrameEx on non-debug shared builds. This broke the ability to use py-bt, py-up, and a few other Python-specific gdb integrations. The problem is fixed by only looking for _PyEval_EvalFrameDefault frames in python-gdb.py. Original patch by Bruno « Polaco » Penteado.

Python 3.6.2 final

Release date: 2017-07-17

No changes since release candidate 2

Python 3.6.2 release candidate 2

Release date: 2017-07-07

Security

bpo-30730 [https://bugs.python.org/issue30730]: Prevent environment variables injection in subprocess on Windows. Prevent passing other environment variables and command arguments.

bpo-30694 [https://bugs.python.org/issue30694]: Upgrade expat copy from 2.2.0 to 2.2.1 to get fixes of multiple security vulnerabilities including: CVE-2017-9233 (External entity infinite loop DoS), CVE-2016-9063 (Integer overflow, re-fix), CVE-2016-0718 (Fix regression bugs from 2.2.0’s fix to CVE-2016-0718) and CVE-2012-0876 (Counter hash flooding with SipHash). Note: the CVE-2016-5300 (Use os-specific entropy sources like getrandom) doesn’t impact Python, since Python already gets entropy from the OS to set the expat secret using XML_SetHashSalt().

bpo-30500 [https://bugs.python.org/issue30500]: Fix urllib.parse.splithost() to correctly parse fragments. For example, splithost('//127.0.0.1#@evil.com/') now correctly returns the 127.0.0.1 host, instead of treating @evil.com as the host in an authentication (login@host).

Python 3.6.2 release candidate 1

Release date: 2017-06-17

Core and Builtins

bpo-30682 [https://bugs.python.org/issue30682]: Removed a too-strict assertion that failed for certain f-strings, such as eval(« f”\n” ») and eval(« f”\r” »).

bpo-30604 [https://bugs.python.org/issue30604]: Move co_extra_freefuncs to not be per-thread to avoid crashes

bpo-29104 [https://bugs.python.org/issue29104]: Fixed parsing backslashes in f-strings.

bpo-27945 [https://bugs.python.org/issue27945]: Fixed various segfaults with dict when input collections are mutated during searching, inserting or comparing. Based on patches by Duane Griffin and Tim Mitchell.

bpo-25794 [https://bugs.python.org/issue25794]: Fixed type.__setattr__() and type.__delattr__() for non-interned attribute names. Based on patch by Eryk Sun.

bpo-30039 [https://bugs.python.org/issue30039]: If a KeyboardInterrupt happens when the interpreter is in the middle of resuming a chain of nested “yield from” or “await” calls, it’s now correctly delivered to the innermost frame.

bpo-12414 [https://bugs.python.org/issue12414]: sys.getsizeof() on a code object now returns the sizes which includes the code struct and sizes of objects which it references. Patch by Dong-hee Na.

bpo-29949 [https://bugs.python.org/issue29949]: Fix memory usage regression of set and frozenset object.

bpo-29935 [https://bugs.python.org/issue29935]: Fixed error messages in the index() method of tuple, list and deque when pass indices of wrong type.

bpo-29859 [https://bugs.python.org/issue29859]: Show correct error messages when any of the pthread_* calls in thread_pthread.h fails.

bpo-28876 [https://bugs.python.org/issue28876]: bool(range) works even if len(range) raises OverflowError.

bpo-29600 [https://bugs.python.org/issue29600]: Fix wrapping coroutine return values in StopIteration.

bpo-28856 [https://bugs.python.org/issue28856]: Fix an oversight that %b format for bytes should support objects follow the buffer protocol.

bpo-29714 [https://bugs.python.org/issue29714]: Fix a regression that bytes format may fail when containing zero bytes inside.

bpo-29478 [https://bugs.python.org/issue29478]: If max_line_length=None is specified while using the Compat32 policy, it is no longer ignored. Patch by Mircea Cosbuc.

Library

bpo-30616 [https://bugs.python.org/issue30616]: Functional API of enum allows to create empty enums. Patched by Dong-hee Na

bpo-30038 [https://bugs.python.org/issue30038]: Fix race condition between signal delivery and wakeup file descriptor. Patch by Nathaniel Smith.

bpo-23894 [https://bugs.python.org/issue23894]: lib2to3 now recognizes rb'...' and f'...' strings.

bpo-23890 [https://bugs.python.org/issue23890]: unittest.TestCase.assertRaises() now manually breaks a reference cycle to not keep objects alive longer than expected.

bpo-30149 [https://bugs.python.org/issue30149]: inspect.signature() now supports callables with variable-argument parameters wrapped with partialmethod. Patch by Dong-hee Na.

bpo-30645 [https://bugs.python.org/issue30645]: Fix path calculation in imp.load_package(), fixing it for cases when a package is only shipped with bytecodes. Patch by Alexandru Ardelean.

bpo-29931 [https://bugs.python.org/issue29931]: Fixed comparison check for ipaddress.ip_interface objects. Patch by Sanjay Sundaresan.

bpo-30605 [https://bugs.python.org/issue30605]: re.compile() no longer raises a BytesWarning when compiling a bytes instance with misplaced inline modifier. Patch by Roy Williams.

Security

bpo-29591 [https://bugs.python.org/issue29591]: Update expat copy from 2.1.1 to 2.2.0 to get fixes of CVE-2016-0718 and CVE-2016-4472. See https://sourceforge.net/p/expat/bugs/537/ for more information.

Library

bpo-24484 [https://bugs.python.org/issue24484]: Avoid race condition in multiprocessing cleanup (#2159)

bpo-28994 [https://bugs.python.org/issue28994]: The traceback no longer displayed for SystemExit raised in a callback registered by atexit.

bpo-30508 [https://bugs.python.org/issue30508]: Don’t log exceptions if Task/Future « cancel() » method was called.

bpo-28556 [https://bugs.python.org/issue28556]: Updates to typing module: Add generic AsyncContextManager, add support for ContextManager on all versions. Original PRs by Jelle Zijlstra and Ivan Levkivskyi

bpo-29870 [https://bugs.python.org/issue29870]: Fix ssl sockets leaks when connection is aborted in asyncio/ssl implementation. Patch by Michaël Sghaïer.

bpo-29743 [https://bugs.python.org/issue29743]: Closing transport during handshake process leaks open socket. Patch by Nikolay Kim

bpo-27585 [https://bugs.python.org/issue27585]: Fix waiter cancellation in asyncio.Lock. Patch by Mathieu Sornay.

bpo-30418 [https://bugs.python.org/issue30418]: On Windows, subprocess.Popen.communicate() now also ignore EINVAL on stdin.write() if the child process is still running but closed the pipe.

bpo-29822 [https://bugs.python.org/issue29822]: inspect.isabstract() now works during __init_subclass__. Patch by Nate Soares.

bpo-29581 [https://bugs.python.org/issue29581]: ABCMeta.__new__ now accepts **kwargs, allowing abstract base classes to use keyword parameters in __init_subclass__. Patch by Nate Soares.

bpo-30557 [https://bugs.python.org/issue30557]: faulthandler now correctly filters and displays exception codes on Windows

bpo-30378 [https://bugs.python.org/issue30378]: Fix the problem that logging.handlers.SysLogHandler cannot handle IPv6 addresses.

bpo-29960 [https://bugs.python.org/issue29960]: Preserve generator state when _random.Random.setstate() raises an exception. Patch by Bryan Olson.

bpo-30414 [https://bugs.python.org/issue30414]: multiprocessing.Queue._feed background running thread do not break from main loop on exception.

bpo-30003 [https://bugs.python.org/issue30003]: Fix handling escape characters in HZ codec. Based on patch by Ma Lin.

bpo-30301 [https://bugs.python.org/issue30301]: Fix AttributeError when using SimpleQueue.empty() under spawn and forkserver start methods.

bpo-30329 [https://bugs.python.org/issue30329]: imaplib and poplib now catch the Windows socket WSAEINVAL error (code 10022) on shutdown(SHUT_RDWR): An invalid operation was attempted. This error occurs sometimes on SSL connections.

bpo-30375 [https://bugs.python.org/issue30375]: Warnings emitted when compile a regular expression now always point to the line in the user code. Previously they could point into inners of the re module if emitted from inside of groups or conditionals.

bpo-30048 [https://bugs.python.org/issue30048]: Fixed Task.cancel() can be ignored when the task is running coroutine and the coroutine returned without any more await.

bpo-30266 [https://bugs.python.org/issue30266]: contextlib.AbstractContextManager now supports anti-registration by setting __enter__ = None or __exit__ = None, following the pattern introduced in bpo-25958 [https://bugs.python.org/issue25958]. Patch by Jelle Zijlstra.

bpo-30298 [https://bugs.python.org/issue30298]: Weaken the condition of deprecation warnings for inline modifiers. Now allowed several subsequential inline modifiers at the start of the pattern (e.g. '(?i)(?s)...'). In verbose mode whitespaces and comments now are allowed before and between inline modifiers (e.g. '(?x) (?i) (?s)...').

bpo-29990 [https://bugs.python.org/issue29990]: Fix range checking in GB18030 decoder. Original patch by Ma Lin.

bpo-26293 [https://bugs.python.org/issue26293]: Change resulted because of zipfile breakage. (See also: bpo-29094 [https://bugs.python.org/issue29094])

bpo-30243 [https://bugs.python.org/issue30243]: Removed the __init__ methods of _json’s scanner and encoder. Misusing them could cause memory leaks or crashes. Now scanner and encoder objects are completely initialized in the __new__ methods.

bpo-30185 [https://bugs.python.org/issue30185]: Avoid KeyboardInterrupt tracebacks in forkserver helper process when Ctrl-C is received.

bpo-28556 [https://bugs.python.org/issue28556]: Various updates to typing module: add typing.NoReturn type, use WrapperDescriptorType, minor bug-fixes. Original PRs by Jim Fasarakis-Hilliard and Ivan Levkivskyi.

bpo-30205 [https://bugs.python.org/issue30205]: Fix getsockname() for unbound AF_UNIX sockets on Linux.

bpo-30070 [https://bugs.python.org/issue30070]: Fixed leaks and crashes in errors handling in the parser module.

bpo-30061 [https://bugs.python.org/issue30061]: Fixed crashes in IOBase methods __next__() and readlines() when readline() or __next__() respectively return non-sizeable object. Fixed possible other errors caused by not checking results of PyObject_Size(), PySequence_Size(), or PyMapping_Size().

bpo-30017 [https://bugs.python.org/issue30017]: Allowed calling the close() method of the zip entry writer object multiple times. Writing to a closed writer now always produces a ValueError.

bpo-30068 [https://bugs.python.org/issue30068]: _io._IOBase.readlines will check if it’s closed first when hint is present.

bpo-29694 [https://bugs.python.org/issue29694]: Fixed race condition in pathlib mkdir with flags parents=True. Patch by Armin Rigo.

bpo-29692 [https://bugs.python.org/issue29692]: Fixed arbitrary unchaining of RuntimeError exceptions in contextlib.contextmanager. Patch by Siddharth Velankar.

bpo-29998 [https://bugs.python.org/issue29998]: Pickling and copying ImportError now preserves name and path attributes.

bpo-29953 [https://bugs.python.org/issue29953]: Fixed memory leaks in the replace() method of datetime and time objects when pass out of bound fold argument.

bpo-29942 [https://bugs.python.org/issue29942]: Fix a crash in itertools.chain.from_iterable when encountering long runs of empty iterables.

bpo-27863 [https://bugs.python.org/issue27863]: Fixed multiple crashes in ElementTree caused by race conditions and wrong types.

bpo-28699 [https://bugs.python.org/issue28699]: Fixed a bug in pools in multiprocessing.pool that raising an exception at the very first of an iterable may swallow the exception or make the program hang. Patch by Davin Potts and Xiang Zhang.

bpo-25803 [https://bugs.python.org/issue25803]: Avoid incorrect errors raised by Path.mkdir(exist_ok=True) when the OS gives priority to errors such as EACCES over EEXIST.

bpo-29861 [https://bugs.python.org/issue29861]: Release references to tasks, their arguments and their results as soon as they are finished in multiprocessing.Pool.

bpo-29884 [https://bugs.python.org/issue29884]: faulthandler: Restore the old sigaltstack during teardown. Patch by Christophe Zeitouny.

bpo-25455 [https://bugs.python.org/issue25455]: Fixed crashes in repr of recursive buffered file-like objects.

bpo-29800 [https://bugs.python.org/issue29800]: Fix crashes in partial.__repr__ if the keys of partial.keywords are not strings. Patch by Michael Seifert.

bpo-29742 [https://bugs.python.org/issue29742]: get_extra_info() raises exception if get called on closed ssl transport. Patch by Nikolay Kim.

bpo-8256 [https://bugs.python.org/issue8256]: Fixed possible failing or crashing input() if attributes « encoding » or « errors » of sys.stdin or sys.stdout are not set or are not strings.

bpo-28298 [https://bugs.python.org/issue28298]: Fix a bug that prevented array “Q”, “L” and “I” from accepting big intables (objects that have __int__) as elements. Patch by Oren Milman.

bpo-28231 [https://bugs.python.org/issue28231]: The zipfile module now accepts path-like objects for external paths.

bpo-26915 [https://bugs.python.org/issue26915]: index() and count() methods of collections.abc.Sequence now check identity before checking equality when do comparisons.

bpo-29615 [https://bugs.python.org/issue29615]: SimpleXMLRPCDispatcher no longer chains KeyError (or any other exception) to exception(s) raised in the dispatched methods. Patch by Petr Motejlek.

bpo-30177 [https://bugs.python.org/issue30177]: path.resolve(strict=False) no longer cuts the path after the first element not present in the filesystem. Patch by Antoine Pietri.

IDLE

bpo-15786 [https://bugs.python.org/issue15786]: Fix several problems with IDLE’s autocompletion box. The following should now work: clicking on selection box items; using the scrollbar; selecting an item by hitting Return. Hangs on MacOSX should no longer happen. Patch by Louie Lu.

bpo-25514 [https://bugs.python.org/issue25514]: Add doc subsubsection about IDLE failure to start. Popup no-connection message directs users to this section.

bpo-30642 [https://bugs.python.org/issue30642]: Fix reference leaks in IDLE tests. Patches by Louie Lu and Terry Jan Reedy.

bpo-30495 [https://bugs.python.org/issue30495]: Add docstrings for textview.py and use PEP8 names. Patches by Cheryl Sabella and Terry Jan Reedy.

bpo-30290 [https://bugs.python.org/issue30290]: Help-about: use pep8 names and add tests. Increase coverage to 100%. Patches by Louie Lu, Cheryl Sabella, and Terry Jan Reedy.

bpo-30303 [https://bugs.python.org/issue30303]: Add _utest option to textview; add new tests. Increase coverage to 100%. Patches by Louie Lu and Terry Jan Reedy.

C API

bpo-27867 [https://bugs.python.org/issue27867]: Function PySlice_GetIndicesEx() no longer replaced with a macro if Py_LIMITED_API is not set.

Build

bpo-29941 [https://bugs.python.org/issue29941]: Add --with-assertions configure flag to explicitly enable C assert() checks. Defaults to off. --with-pydebug implies --with-assertions.

bpo-28787 [https://bugs.python.org/issue28787]: Fix out-of-tree builds of Python when configured with --with--dtrace.

bpo-29243 [https://bugs.python.org/issue29243]: Prevent unnecessary rebuilding of Python during make test, make install and some other make targets when configured with --enable-optimizations.

bpo-23404 [https://bugs.python.org/issue23404]: Don’t regenerate generated files based on file modification time anymore: the action is now explicit. Replace make touch with make regen-all.

bpo-29643 [https://bugs.python.org/issue29643]: Fix --enable-optimization didn’t work.

Documentation

bpo-30176 [https://bugs.python.org/issue30176]: Add missing attribute related constants in curses documentation.

bpo-30052 [https://bugs.python.org/issue30052]: the link targets for bytes() and bytearray() are now their respective type definitions, rather than the corresponding builtin function entries. Use bytes and bytearray to reference the latter.

In order to ensure this and future cross-reference updates are applied automatically, the daily documentation builds now disable the default output caching features in Sphinx.

bpo-26985 [https://bugs.python.org/issue26985]: Add missing info of code object in inspect documentation.

Tools/Demos

bpo-29367 [https://bugs.python.org/issue29367]: python-gdb.py now supports also method-wrapper (wrapperobject) objects.

Tests

bpo-30357 [https://bugs.python.org/issue30357]: test_thread: setUp() now uses support.threading_setup() and support.threading_cleanup() to wait until threads complete to avoid random side effects on following tests. Initial patch written by Grzegorz Grzywacz.

bpo-30197 [https://bugs.python.org/issue30197]: Enhanced functions swap_attr() and swap_item() in the test.support module. They now work when delete replaced attribute or item inside the with statement. The old value of the attribute or item (or None if it doesn’t exist) now will be assigned to the target of the « as » clause, if there is one.

Windows

bpo-30687 [https://bugs.python.org/issue30687]: Locate msbuild.exe on Windows when building rather than vcvarsall.bat

bpo-30450 [https://bugs.python.org/issue30450]: The build process on Windows no longer depends on Subversion, instead pulling external code from GitHub via a Python script. If Python 3.6 is not found on the system (via py -3.6), NuGet is used to download a copy of 32-bit Python.

Python 3.6.1 final

Release date: 2017-03-21

Core and Builtins

bpo-29723 [https://bugs.python.org/issue29723]: The sys.path[0] initialization change for bpo-29139 [https://bugs.python.org/issue29139] caused a regression by revealing an inconsistency in how sys.path is initialized when executing __main__ from a zipfile, directory, or other import location. The interpreter now consistently avoids ever adding the import location’s parent directory to sys.path, and ensures no other sys.path entries are inadvertently modified when inserting the import location named on the command line.

Build

bpo-27593 [https://bugs.python.org/issue27593]: fix format of git information used in sys.version

Fix incompatible comment in python.h

Python 3.6.1 release candidate 1

Release date: 2017-03-04

Core and Builtins

bpo-28893 [https://bugs.python.org/issue28893]: Set correct __cause__ for errors about invalid awaitables returned from __aiter__ and __anext__.

bpo-29683 [https://bugs.python.org/issue29683]: Fixes to memory allocation in _PyCode_SetExtra. Patch by Brian Coleman.

bpo-29684 [https://bugs.python.org/issue29684]: Fix minor regression of PyEval_CallObjectWithKeywords. It should raise TypeError when kwargs is not a dict. But it might cause segv when args=NULL and kwargs is not a dict.

bpo-28598 [https://bugs.python.org/issue28598]: Support __rmod__ for subclasses of str being called before str.__mod__. Patch by Martijn Pieters.

bpo-29607 [https://bugs.python.org/issue29607]: Fix stack_effect computation for CALL_FUNCTION_EX. Patch by Matthieu Dartiailh.

bpo-29602 [https://bugs.python.org/issue29602]: Fix incorrect handling of signed zeros in complex constructor for complex subclasses and for inputs having a __complex__ method. Patch by Serhiy Storchaka.

bpo-29347 [https://bugs.python.org/issue29347]: Fixed possibly dereferencing undefined pointers when creating weakref objects.

bpo-29438 [https://bugs.python.org/issue29438]: Fixed use-after-free problem in key sharing dict.

bpo-29319 [https://bugs.python.org/issue29319]: Prevent RunMainFromImporter overwriting sys.path[0].

bpo-29337 [https://bugs.python.org/issue29337]: Fixed possible BytesWarning when compare the code objects. Warnings could be emitted at compile time.

bpo-29327 [https://bugs.python.org/issue29327]: Fixed a crash when pass the iterable keyword argument to sorted().

bpo-29034 [https://bugs.python.org/issue29034]: Fix memory leak and use-after-free in os module (path_converter).

bpo-29159 [https://bugs.python.org/issue29159]: Fix regression in bytes(x) when x.__index__() raises Exception.

bpo-28932 [https://bugs.python.org/issue28932]: Do not include <sys/random.h> if it does not exist.

bpo-25677 [https://bugs.python.org/issue25677]: Correct the positioning of the syntax error caret for indented blocks. Based on patch by Michael Layzell.

bpo-29000 [https://bugs.python.org/issue29000]: Fixed bytes formatting of octals with zero padding in alternate form.

bpo-26919 [https://bugs.python.org/issue26919]: On Android, operating system data is now always encoded/decoded to/from UTF-8, instead of the locale encoding to avoid inconsistencies with os.fsencode() and os.fsdecode() which are already using UTF-8.

bpo-28991 [https://bugs.python.org/issue28991]: functools.lru_cache() was susceptible to an obscure reentrancy bug triggerable by a monkey-patched len() function.

bpo-28739 [https://bugs.python.org/issue28739]: f-string expressions are no longer accepted as docstrings and by ast.literal_eval() even if they do not include expressions.

bpo-28512 [https://bugs.python.org/issue28512]: Fixed setting the offset attribute of SyntaxError by PyErr_SyntaxLocationEx() and PyErr_SyntaxLocationObject().

bpo-28918 [https://bugs.python.org/issue28918]: Fix the cross compilation of xxlimited when Python has been built with Py_DEBUG defined.

bpo-28731 [https://bugs.python.org/issue28731]: Optimize _PyDict_NewPresized() to create correct size dict. Improve speed of dict literal with constant keys up to 30%.

Library

bpo-29169 [https://bugs.python.org/issue29169]: Update zlib to 1.2.11.

bpo-29623 [https://bugs.python.org/issue29623]: Allow use of path-like object as a single argument in ConfigParser.read(). Patch by David Ellis.

bpo-28963 [https://bugs.python.org/issue28963]: Fix out of bound iteration in asyncio.Future.remove_done_callback implemented in C.

bpo-29704 [https://bugs.python.org/issue29704]: asyncio.subprocess.SubprocessStreamProtocol no longer closes before all pipes are closed.

bpo-29271 [https://bugs.python.org/issue29271]: Fix Task.current_task and Task.all_tasks implemented in C to accept None argument as their pure Python implementation.

bpo-29703 [https://bugs.python.org/issue29703]: Fix asyncio to support instantiation of new event loops in child processes.

bpo-29376 [https://bugs.python.org/issue29376]: Fix assertion error in threading._DummyThread.is_alive().

bpo-28624 [https://bugs.python.org/issue28624]: Add a test that checks that cwd parameter of Popen() accepts PathLike objects. Patch by Sayan Chowdhury.

bpo-28518 [https://bugs.python.org/issue28518]: Start a transaction implicitly before a DML statement. Patch by Aviv Palivoda.

bpo-29532 [https://bugs.python.org/issue29532]: Altering a kwarg dictionary passed to functools.partial() no longer affects a partial object after creation.

bpo-29110 [https://bugs.python.org/issue29110]: Fix file object leak in aifc.open() when file is given as a filesystem path and is not in valid AIFF format. Patch by Anthony Zhang.

bpo-28556 [https://bugs.python.org/issue28556]: Various updates to typing module: typing.Counter, typing.ChainMap, improved ABC caching, etc. Original PRs by Jelle Zijlstra, Ivan Levkivskyi, Manuel Krebber, and Łukasz Langa.

bpo-29100 [https://bugs.python.org/issue29100]: Fix datetime.fromtimestamp() regression introduced in Python 3.6.0: check minimum and maximum years.

bpo-29519 [https://bugs.python.org/issue29519]: Fix weakref spewing exceptions during interpreter shutdown when used with a rare combination of multiprocessing and custom codecs.

bpo-29416 [https://bugs.python.org/issue29416]: Prevent infinite loop in pathlib.Path.mkdir

bpo-29444 [https://bugs.python.org/issue29444]: Fixed out-of-bounds buffer access in the group() method of the match object. Based on patch by WGH.

bpo-29335 [https://bugs.python.org/issue29335]: Fix subprocess.Popen.wait() when the child process has exited to a stopped instead of terminated state (ex: when under ptrace).

bpo-29290 [https://bugs.python.org/issue29290]: Fix a regression in argparse that help messages would wrap at non-breaking spaces.

bpo-28735 [https://bugs.python.org/issue28735]: Fixed the comparison of mock.MagickMock with mock.ANY.

bpo-29316 [https://bugs.python.org/issue29316]: Restore the provisional status of typing module, add corresponding note to documentation. Patch by Ivan L.

bpo-29219 [https://bugs.python.org/issue29219]: Fixed infinite recursion in the repr of uninitialized ctypes.CDLL instances.

bpo-29011 [https://bugs.python.org/issue29011]: Fix an important omission by adding Deque to the typing module.

bpo-28969 [https://bugs.python.org/issue28969]: Fixed race condition in C implementation of functools.lru_cache. KeyError could be raised when cached function with full cache was simultaneously called from differen threads with the same uncached arguments.

bpo-29142 [https://bugs.python.org/issue29142]: In urllib.request, suffixes in no_proxy environment variable with leading dots could match related hostnames again (e.g. .b.c matches a.b.c). Patch by Milan Oberkirch.

bpo-28961 [https://bugs.python.org/issue28961]: Fix unittest.mock._Call helper: don’t ignore the name parameter anymore. Patch written by Jiajun Huang.

bpo-29203 [https://bugs.python.org/issue29203]: functools.lru_cache() now respects PEP 468 and preserves the order of keyword arguments. f(a=1, b=2) is now cached separately from f(b=2, a=1) since both calls could potentially give different results.

bpo-15812 [https://bugs.python.org/issue15812]: inspect.getframeinfo() now correctly shows the first line of a context. Patch by Sam Breese.

bpo-29094 [https://bugs.python.org/issue29094]: Offsets in a ZIP file created with extern file object and modes « w » and « x » now are relative to the start of the file.

bpo-29085 [https://bugs.python.org/issue29085]: Allow random.Random.seed() to use high quality OS randomness rather than the pid and time.

bpo-29061 [https://bugs.python.org/issue29061]: Fixed bug in secrets.randbelow() which would hang when given a negative input. Patch by Brendan Donegan.

bpo-29079 [https://bugs.python.org/issue29079]: Prevent infinite loop in pathlib.resolve() on Windows

bpo-13051 [https://bugs.python.org/issue13051]: Fixed recursion errors in large or resized curses.textpad.Textbox. Based on patch by Tycho Andersen.

bpo-29119 [https://bugs.python.org/issue29119]: Fix weakrefs in the pure python version of collections.OrderedDict move_to_end() method. Contributed by Andra Bogildea.

bpo-9770 [https://bugs.python.org/issue9770]: curses.ascii predicates now work correctly with negative integers.

bpo-28427 [https://bugs.python.org/issue28427]: old keys should not remove new values from WeakValueDictionary when collecting from another thread.

bpo-28923 [https://bugs.python.org/issue28923]: Remove editor artifacts from Tix.py.

bpo-29055 [https://bugs.python.org/issue29055]: Neaten-up empty population error on random.choice() by suppressing the upstream exception.

bpo-28871 [https://bugs.python.org/issue28871]: Fixed a crash when deallocate deep ElementTree.

bpo-19542 [https://bugs.python.org/issue19542]: Fix bugs in WeakValueDictionary.setdefault() and WeakValueDictionary.pop() when a GC collection happens in another thread.

bpo-20191 [https://bugs.python.org/issue20191]: Fixed a crash in resource.prlimit() when passing a sequence that doesn’t own its elements as limits.

bpo-28779 [https://bugs.python.org/issue28779]: multiprocessing.set_forkserver_preload() would crash the forkserver process if a preloaded module instantiated some multiprocessing objects such as locks.

bpo-28847 [https://bugs.python.org/issue28847]: dbm.dumb now supports reading read-only files and no longer writes the index file when it is not changed.

bpo-26937 [https://bugs.python.org/issue26937]: The chown() method of the tarfile.TarFile class does not fail now when the grp module cannot be imported, as for example on Android platforms.

IDLE

bpo-29071 [https://bugs.python.org/issue29071]: IDLE colors f-string prefixes (but not invalid ur prefixes).

bpo-28572 [https://bugs.python.org/issue28572]: Add 10% to coverage of IDLE’s test_configdialog. Update and augment description of the configuration system.

Windows

bpo-29579 [https://bugs.python.org/issue29579]: Removes readme.txt from the installer

bpo-29326 [https://bugs.python.org/issue29326]: Ignores blank lines in ._pth files (Patch by Alexey Izbyshev)

bpo-28164 [https://bugs.python.org/issue28164]: Correctly handle special console filenames (patch by Eryk Sun)

bpo-29409 [https://bugs.python.org/issue29409]: Implement PEP 529 for io.FileIO (Patch by Eryk Sun)

bpo-29392 [https://bugs.python.org/issue29392]: Prevent crash when passing invalid arguments into msvcrt module.

bpo-25778 [https://bugs.python.org/issue25778]: winreg does not truncate string correctly (Patch by Eryk Sun)

bpo-28896 [https://bugs.python.org/issue28896]: Deprecate WindowsRegistryFinder and disable it by default.

C API

bpo-27867 [https://bugs.python.org/issue27867]: Function PySlice_GetIndicesEx() is replaced with a macro if Py_LIMITED_API is not set or set to the value between 0x03050400 and 0x03060000 (not including) or 0x03060100 or higher.

bpo-29083 [https://bugs.python.org/issue29083]: Fixed the declaration of some public API functions. PyArg_VaParse() and PyArg_VaParseTupleAndKeywords() were not available in limited API. PyArg_ValidateKeywordArguments(), PyArg_UnpackTuple() and Py_BuildValue() were not available in limited API of version < 3.3 when PY_SSIZE_T_CLEAN is defined.

bpo-29058 [https://bugs.python.org/issue29058]: All stable API extensions added after Python 3.2 are now available only when Py_LIMITED_API is set to the PY_VERSION_HEX value of the minimum Python version supporting this API.

Documentation

bpo-28929 [https://bugs.python.org/issue28929]: Link the documentation to its source file on GitHub.

bpo-25008 [https://bugs.python.org/issue25008]: Document smtpd.py as effectively deprecated and add a pointer to aiosmtpd, a third-party asyncio-based replacement.

bpo-26355 [https://bugs.python.org/issue26355]: Add canonical header link on each page to corresponding major version of the documentation. Patch by Matthias Bussonnier.

bpo-29349 [https://bugs.python.org/issue29349]: Fix Python 2 syntax in code for building the documentation.

Tests

bpo-28087 [https://bugs.python.org/issue28087]: Skip test_asyncore and test_eintr poll failures on macOS. Skip some tests of select.poll when running on macOS due to unresolved issues with the underlying system poll function on some macOS versions.

bpo-29571 [https://bugs.python.org/issue29571]: to match the behaviour of the re.LOCALE flag, test_re.test_locale_flag now uses locale.getpreferredencoding(False) to determine the candidate encoding for the test regex (allowing it to correctly skip the test when the default locale encoding is a multi-byte encoding)

bpo-28950 [https://bugs.python.org/issue28950]: Disallow -j0 to be combined with -T/-l in regrtest command line arguments.

bpo-28683 [https://bugs.python.org/issue28683]: Fix the tests that bind() a unix socket and raise PermissionError on Android for a non-root user.

bpo-26939 [https://bugs.python.org/issue26939]: Add the support.setswitchinterval() function to fix test_functools hanging on the Android armv7 qemu emulator.

Build

bpo-27593 [https://bugs.python.org/issue27593]: sys.version and the platform module python_build(), python_branch(), and python_revision() functions now use git information rather than hg when building from a repo.

bpo-29572 [https://bugs.python.org/issue29572]: Update Windows build and OS X installers to use OpenSSL 1.0.2k.

bpo-26851 [https://bugs.python.org/issue26851]: Set Android compilation and link flags.

bpo-28768 [https://bugs.python.org/issue28768]: Fix implicit declaration of function _setmode. Patch by Masayuki Yamamoto

bpo-29080 [https://bugs.python.org/issue29080]: Removes hard dependency on hg.exe from PCBuild/build.bat

bpo-23903 [https://bugs.python.org/issue23903]: Added missed names to PC/python3.def.

bpo-28762 [https://bugs.python.org/issue28762]: lockf() is available on Android API level 24, but the F_LOCK macro is not defined in android-ndk-r13.

bpo-28538 [https://bugs.python.org/issue28538]: Fix the compilation error that occurs because if_nameindex() is available on Android API level 24, but the if_nameindex structure is not defined.

bpo-20211 [https://bugs.python.org/issue20211]: Do not add the directory for installing C header files and the directory for installing object code libraries to the cross compilation search paths. Original patch by Thomas Petazzoni.

bpo-28849 [https://bugs.python.org/issue28849]: Do not define sys.implementation._multiarch on Android.

Python 3.6.0 final

Release date: 2016-12-23

No changes since release candidate 2

Python 3.6.0 release candidate 2

Release date: 2016-12-16

Core and Builtins

bpo-28147 [https://bugs.python.org/issue28147]: Fix a memory leak in split-table dictionaries: setattr() must not convert combined table into split table. Patch written by INADA Naoki.

bpo-28990 [https://bugs.python.org/issue28990]: Fix asyncio SSL hanging if connection is closed before handshake is completed. (Patch by HoHo-Ho)

Tools/Demos

bpo-28770 [https://bugs.python.org/issue28770]: Fix python-gdb.py for fastcalls.

Windows

bpo-28896 [https://bugs.python.org/issue28896]: Deprecate WindowsRegistryFinder.

Build

bpo-28898 [https://bugs.python.org/issue28898]: Prevent gdb build errors due to HAVE_LONG_LONG redefinition.

Python 3.6.0 release candidate 1

Release date: 2016-12-06

Core and Builtins

bpo-23722 [https://bugs.python.org/issue23722]: Rather than silently producing a class that doesn’t support zero-argument super() in methods, failing to pass the new __classcell__ namespace entry up to type.__new__ now results in a DeprecationWarning and a class that supports zero-argument super().

bpo-28797 [https://bugs.python.org/issue28797]: Modifying the class __dict__ inside the __set_name__ method of a descriptor that is used inside that class no longer prevents calling the __set_name__ method of other descriptors.

bpo-28782 [https://bugs.python.org/issue28782]: Fix a bug in the implementation yield from when checking if the next instruction is YIELD_FROM. Regression introduced by WORDCODE (bpo-26647 [https://bugs.python.org/issue26647]).

Library

bpo-27030 [https://bugs.python.org/issue27030]: Unknown escapes in re.sub() replacement template are allowed again. But they still are deprecated and will be disabled in 3.7.

bpo-28835 [https://bugs.python.org/issue28835]: Fix a regression introduced in warnings.catch_warnings(): call warnings.showwarning() if it was overriden inside the context manager.

bpo-27172 [https://bugs.python.org/issue27172]: To assist with upgrades from 2.7, the previously documented deprecation of inspect.getfullargspec() has been reversed. This decision may be revisited again after the Python 2.7 branch is no longer officially supported.

bpo-26273 [https://bugs.python.org/issue26273]: Add new socket.TCP_CONGESTION (Linux 2.6.13) and socket.TCP_USER_TIMEOUT (Linux 2.6.37) constants. Patch written by Omar Sandoval.

bpo-24142 [https://bugs.python.org/issue24142]: Reading a corrupt config file left configparser in an invalid state. Original patch by Florian Höch.

bpo-28843 [https://bugs.python.org/issue28843]: Fix asyncio C Task to handle exceptions __traceback__.

C API

bpo-28808 [https://bugs.python.org/issue28808]: PyUnicode_CompareWithASCIIString() now never raises exceptions.

Documentation

bpo-23722 [https://bugs.python.org/issue23722]: The data model reference and the porting section in the What’s New guide now cover the additional __classcell__ handling needed for custom metaclasses to fully support PEP 487 and zero-argument super().

Tools/Demos

bpo-28023 [https://bugs.python.org/issue28023]: Fix python-gdb.py didn’t support new dict implementation.

Python 3.6.0 beta 4

Release date: 2016-11-21

Core and Builtins

bpo-28532 [https://bugs.python.org/issue28532]: Show sys.version when -V option is supplied twice.

bpo-27100 [https://bugs.python.org/issue27100]: The with-statement now checks for __enter__ before it checks for __exit__. This gives less confusing error messages when both methods are missing. Patch by Jonathan Ellington.

bpo-28746 [https://bugs.python.org/issue28746]: Fix the set_inheritable() file descriptor method on platforms that do not have the ioctl FIOCLEX and FIONCLEX commands.

bpo-26920 [https://bugs.python.org/issue26920]: Fix not getting the locale’s charset upon initializing the interpreter, on platforms that do not have langinfo.

bpo-28648 [https://bugs.python.org/issue28648]: Fixed crash in Py_DecodeLocale() in debug build on Mac OS X when decode astral characters. Patch by Xiang Zhang.

bpo-19398 [https://bugs.python.org/issue19398]: Extra slash no longer added to sys.path components in case of empty compile-time PYTHONPATH components.

bpo-28665 [https://bugs.python.org/issue28665]: Improve speed of the STORE_DEREF opcode by 40%.

bpo-28583 [https://bugs.python.org/issue28583]: PyDict_SetDefault didn’t combine split table when needed. Patch by Xiang Zhang.

bpo-27243 [https://bugs.python.org/issue27243]: Change PendingDeprecationWarning -> DeprecationWarning. As it was agreed in the issue, __aiter__ returning an awaitable should result in PendingDeprecationWarning in 3.5 and in DeprecationWarning in 3.6.

bpo-26182 [https://bugs.python.org/issue26182]: Fix a refleak in code that raises DeprecationWarning.

bpo-28721 [https://bugs.python.org/issue28721]: Fix asynchronous generators aclose() and athrow() to handle StopAsyncIteration propagation properly.

Library

bpo-28752 [https://bugs.python.org/issue28752]: Restored the __reduce__() methods of datetime objects.

bpo-28727 [https://bugs.python.org/issue28727]: Regular expression patterns, _sre.SRE_Pattern objects created by re.compile(), become comparable (only x==y and x!=y operators). This change should fix the bpo-18383 [https://bugs.python.org/issue18383]: don’t duplicate warning filters when the warnings module is reloaded (thing usually only done in unit tests).

bpo-20572 [https://bugs.python.org/issue20572]: The subprocess.Popen.wait method’s undocumented endtime parameter now raises a DeprecationWarning.

bpo-25659 [https://bugs.python.org/issue25659]: In ctypes, prevent a crash calling the from_buffer() and from_buffer_copy() methods on abstract classes like Array.

bpo-19717 [https://bugs.python.org/issue19717]: Makes Path.resolve() succeed on paths that do not exist. Patch by Vajrasky Kok

bpo-28563 [https://bugs.python.org/issue28563]: Fixed possible DoS and arbitrary code execution when handle plural form selections in the gettext module. The expression parser now supports exact syntax supported by GNU gettext.

bpo-28387 [https://bugs.python.org/issue28387]: Fixed possible crash in _io.TextIOWrapper deallocator when the garbage collector is invoked in other thread. Based on patch by Sebastian Cufre.

bpo-28600 [https://bugs.python.org/issue28600]: Optimize loop.call_soon.

bpo-28613 [https://bugs.python.org/issue28613]: Fix get_event_loop() return the current loop if called from coroutines/callbacks.

bpo-28634 [https://bugs.python.org/issue28634]: Fix asyncio.isfuture() to support unittest.Mock.

bpo-26081 [https://bugs.python.org/issue26081]: Fix refleak in _asyncio.Future.__iter__().throw.

bpo-28639 [https://bugs.python.org/issue28639]: Fix inspect.isawaitable to always return bool Patch by Justin Mayfield.

bpo-28652 [https://bugs.python.org/issue28652]: Make loop methods reject socket kinds they do not support.

bpo-28653 [https://bugs.python.org/issue28653]: Fix a refleak in functools.lru_cache.

bpo-28703 [https://bugs.python.org/issue28703]: Fix asyncio.iscoroutinefunction to handle Mock objects.

bpo-28704 [https://bugs.python.org/issue28704]: Fix create_unix_server to support Path-like objects (PEP 519).

bpo-28720 [https://bugs.python.org/issue28720]: Add collections.abc.AsyncGenerator.

Documentation

bpo-28513 [https://bugs.python.org/issue28513]: Documented command-line interface of zipfile.

Tests

bpo-28666 [https://bugs.python.org/issue28666]: Now test.support.rmtree is able to remove unwritable or unreadable directories.

bpo-23839 [https://bugs.python.org/issue23839]: Various caches now are cleared before running every test file.

Build

bpo-10656 [https://bugs.python.org/issue10656]: Fix out-of-tree building on AIX. Patch by Tristan Carel and Michael Haubenwallner.

bpo-26359 [https://bugs.python.org/issue26359]: Rename –with-optimiations to –enable-optimizations.

bpo-28676 [https://bugs.python.org/issue28676]: Prevent missing “getentropy” declaration warning on macOS. Patch by Gareth Rees.

Python 3.6.0 beta 3

Release date: 2016-10-31

Core and Builtins

bpo-28128 [https://bugs.python.org/issue28128]: Deprecation warning for invalid str and byte escape sequences now prints better information about where the error occurs. Patch by Serhiy Storchaka and Eric Smith.

bpo-28509 [https://bugs.python.org/issue28509]: dict.update() no longer allocate unnecessary large memory.

bpo-28426 [https://bugs.python.org/issue28426]: Fixed potential crash in PyUnicode_AsDecodedObject() in debug build.

bpo-28517 [https://bugs.python.org/issue28517]: Fixed of-by-one error in the peephole optimizer that caused keeping unreachable code.

bpo-28214 [https://bugs.python.org/issue28214]: Improved exception reporting for problematic __set_name__ attributes.

bpo-23782 [https://bugs.python.org/issue23782]: Fixed possible memory leak in _PyTraceback_Add() and exception loss in PyTraceBack_Here().

bpo-28471 [https://bugs.python.org/issue28471]: Fix « Python memory allocator called without holding the GIL » crash in socket.setblocking.

Library

bpo-27517 [https://bugs.python.org/issue27517]: LZMA compressor and decompressor no longer raise exceptions if given empty data twice. Patch by Benjamin Fogle.

bpo-28549 [https://bugs.python.org/issue28549]: Fixed segfault in curses’s addch() with ncurses6.

bpo-28449 [https://bugs.python.org/issue28449]: tarfile.open() with mode « r » or « r: » now tries to open a tar file with compression before trying to open it without compression. Otherwise it had 50% chance failed with ignore_zeros=True.

bpo-23262 [https://bugs.python.org/issue23262]: The webbrowser module now supports Firefox 36+ and derived browsers. Based on patch by Oleg Broytman.

bpo-27939 [https://bugs.python.org/issue27939]: Fixed bugs in tkinter.ttk.LabeledScale and tkinter.Scale caused by representing the scale as float value internally in Tk. tkinter.IntVar now works if float value is set to underlying Tk variable.

bpo-18844 [https://bugs.python.org/issue18844]: The various ways of specifying weights for random.choices() now produce the same result sequences.

bpo-28255 [https://bugs.python.org/issue28255]: calendar.TextCalendar().prmonth() no longer prints a space at the start of new line after printing a month’s calendar. Patch by Xiang Zhang.

bpo-20491 [https://bugs.python.org/issue20491]: The textwrap.TextWrapper class now honors non-breaking spaces. Based on patch by Kaarle Ritvanen.

bpo-28353 [https://bugs.python.org/issue28353]: os.fwalk() no longer fails on broken links.

bpo-28430 [https://bugs.python.org/issue28430]: Fix iterator of C implemented asyncio.Future doesn’t accept non-None value is passed to it.send(val).

bpo-27025 [https://bugs.python.org/issue27025]: Generated names for Tkinter widgets now start by the « ! » prefix for readability.

bpo-25464 [https://bugs.python.org/issue25464]: Fixed HList.header_exists() in tkinter.tix module by addin a workaround to Tix library bug.

bpo-28488 [https://bugs.python.org/issue28488]: shutil.make_archive() no longer adds entry « ./ » to ZIP archive.

bpo-25953 [https://bugs.python.org/issue25953]: re.sub() now raises an error for invalid numerical group reference in replacement template even if the pattern is not found in the string. Error message for invalid group reference now includes the group index and the position of the reference. Based on patch by SilentGhost.

bpo-18219 [https://bugs.python.org/issue18219]: Optimize csv.DictWriter for large number of columns. Patch by Mariatta Wijaya.

bpo-28448 [https://bugs.python.org/issue28448]: Fix C implemented asyncio.Future didn’t work on Windows.

bpo-28480 [https://bugs.python.org/issue28480]: Fix error building socket module when multithreading is disabled.

bpo-24452 [https://bugs.python.org/issue24452]: Make webbrowser support Chrome on Mac OS X.

bpo-20766 [https://bugs.python.org/issue20766]: Fix references leaked by pdb in the handling of SIGINT handlers.

bpo-28492 [https://bugs.python.org/issue28492]: Fix how StopIteration exception is raised in _asyncio.Future.

bpo-28500 [https://bugs.python.org/issue28500]: Fix asyncio to handle async gens GC from another thread.

bpo-26923 [https://bugs.python.org/issue26923]: Fix asyncio.Gather to refuse being cancelled once all children are done. Patch by Johannes Ebke.

bpo-26796 [https://bugs.python.org/issue26796]: Don’t configure the number of workers for default threadpool executor. Initial patch by Hans Lawrenz.

bpo-28544 [https://bugs.python.org/issue28544]: Implement asyncio.Task in C.

Windows

bpo-28522 [https://bugs.python.org/issue28522]: Fixes mishandled buffer reallocation in getpathp.c

Build

bpo-28444 [https://bugs.python.org/issue28444]: Fix missing extensions modules when cross compiling.

bpo-28208 [https://bugs.python.org/issue28208]: Update Windows build and OS X installers to use SQLite 3.14.2.

bpo-28248 [https://bugs.python.org/issue28248]: Update Windows build and OS X installers to use OpenSSL 1.0.2j.

Tests

bpo-26944 [https://bugs.python.org/issue26944]: Fix test_posix for Android where “id -G” is entirely wrong or missing the effective gid.

bpo-28409 [https://bugs.python.org/issue28409]: regrtest: fix the parser of command line arguments.

Python 3.6.0 beta 2

Release date: 2016-10-10

Core and Builtins

bpo-28183 [https://bugs.python.org/issue28183]: Optimize and cleanup dict iteration.

bpo-26081 [https://bugs.python.org/issue26081]: Added C implementation of asyncio.Future. Original patch by Yury Selivanov.

bpo-28379 [https://bugs.python.org/issue28379]: Added sanity checks and tests for PyUnicode_CopyCharacters(). Patch by Xiang Zhang.

bpo-28376 [https://bugs.python.org/issue28376]: The type of long range iterator is now registered as Iterator. Patch by Oren Milman.

bpo-28376 [https://bugs.python.org/issue28376]: Creating instances of range_iterator by calling range_iterator type now is deprecated. Patch by Oren Milman.

bpo-28376 [https://bugs.python.org/issue28376]: The constructor of range_iterator now checks that step is not 0. Patch by Oren Milman.

bpo-26906 [https://bugs.python.org/issue26906]: Resolving special methods of uninitialized type now causes implicit initialization of the type instead of a fail.

bpo-18287 [https://bugs.python.org/issue18287]: PyType_Ready() now checks that tp_name is not NULL. Original patch by Niklas Koep.

bpo-24098 [https://bugs.python.org/issue24098]: Fixed possible crash when AST is changed in process of compiling it.

bpo-28201 [https://bugs.python.org/issue28201]: Dict reduces possibility of 2nd conflict in hash table when hashes have same lower bits.

bpo-28350 [https://bugs.python.org/issue28350]: String constants with null character no longer interned.

bpo-26617 [https://bugs.python.org/issue26617]: Fix crash when GC runs during weakref callbacks.

bpo-27942 [https://bugs.python.org/issue27942]: String constants now interned recursively in tuples and frozensets.

bpo-21578 [https://bugs.python.org/issue21578]: Fixed misleading error message when ImportError called with invalid keyword args.

bpo-28203 [https://bugs.python.org/issue28203]: Fix incorrect type in complex(1.0, {2:3}) error message. Patch by Soumya Sharma.

bpo-28086 [https://bugs.python.org/issue28086]: Single var-positional argument of tuple subtype was passed unscathed to the C-defined function. Now it is converted to exact tuple.

bpo-28214 [https://bugs.python.org/issue28214]: Now __set_name__ is looked up on the class instead of the instance.

bpo-27955 [https://bugs.python.org/issue27955]: Fallback on reading /dev/urandom device when the getrandom() syscall fails with EPERM, for example when blocked by SECCOMP.

bpo-28192 [https://bugs.python.org/issue28192]: Don’t import readline in isolated mode.

Upgrade internal unicode databases to Unicode version 9.0.0.

bpo-28131 [https://bugs.python.org/issue28131]: Fix a regression in zipimport’s compile_source(). zipimport should use the same optimization level as the interpreter.

bpo-28126 [https://bugs.python.org/issue28126]: Replace Py_MEMCPY with memcpy(). Visual Studio can properly optimize memcpy().

bpo-28120 [https://bugs.python.org/issue28120]: Fix dict.pop() for splitted dictionary when trying to remove a « pending key » (Not yet inserted in split-table). Patch by Xiang Zhang.

bpo-26182 [https://bugs.python.org/issue26182]: Raise DeprecationWarning when async and await keywords are used as variable/attribute/class/function name.

Library

bpo-27998 [https://bugs.python.org/issue27998]: Fixed bytes path support in os.scandir() on Windows. Patch by Eryk Sun.

bpo-28317 [https://bugs.python.org/issue28317]: The disassembler now decodes FORMAT_VALUE argument.

bpo-26293 [https://bugs.python.org/issue26293]: Fixed writing ZIP files that starts not from the start of the file. Offsets in ZIP file now are relative to the start of the archive in conforming to the specification.

bpo-28380 [https://bugs.python.org/issue28380]: unittest.mock Mock autospec functions now properly support assert_called, assert_not_called, and assert_called_once.

bpo-27181 [https://bugs.python.org/issue27181]: remove statistics.geometric_mean and defer until 3.7.

bpo-28229 [https://bugs.python.org/issue28229]: lzma module now supports pathlib.

bpo-28321 [https://bugs.python.org/issue28321]: Fixed writing non-BMP characters with binary format in plistlib.

bpo-28225 [https://bugs.python.org/issue28225]: bz2 module now supports pathlib. Initial patch by Ethan Furman.

bpo-28227 [https://bugs.python.org/issue28227]: gzip now supports pathlib. Patch by Ethan Furman.

bpo-27358 [https://bugs.python.org/issue27358]: Optimized merging var-keyword arguments and improved error message when passing a non-mapping as a var-keyword argument.

bpo-28257 [https://bugs.python.org/issue28257]: Improved error message when passing a non-iterable as a var-positional argument. Added opcode BUILD_TUPLE_UNPACK_WITH_CALL.

bpo-28322 [https://bugs.python.org/issue28322]: Fixed possible crashes when unpickle itertools objects from incorrect pickle data. Based on patch by John Leitch.

bpo-28228 [https://bugs.python.org/issue28228]: imghdr now supports pathlib.

bpo-28226 [https://bugs.python.org/issue28226]: compileall now supports pathlib.

bpo-28314 [https://bugs.python.org/issue28314]: Fix function declaration (C flags) for the getiterator() method of xml.etree.ElementTree.Element.

bpo-28148 [https://bugs.python.org/issue28148]: Stop using localtime() and gmtime() in the time module.

Introduced platform independent _PyTime_localtime API that is similar to POSIX localtime_r, but available on all platforms. Patch by Ed Schouten.

bpo-28253 [https://bugs.python.org/issue28253]: Fixed calendar functions for extreme months: 0001-01 and 9999-12.

Methods itermonthdays() and itermonthdays2() are reimplemented so that they don’t call itermonthdates() which can cause datetime.date under/overflow.

bpo-28275 [https://bugs.python.org/issue28275]: Fixed possible use after free in the decompress() methods of the LZMADecompressor and BZ2Decompressor classes. Original patch by John Leitch.

bpo-27897 [https://bugs.python.org/issue27897]: Fixed possible crash in sqlite3.Connection.create_collation() if pass invalid string-like object as a name. Patch by Xiang Zhang.

bpo-18844 [https://bugs.python.org/issue18844]: random.choices() now has k as a keyword-only argument to improve the readability of common cases and come into line with the signature used in other languages.

bpo-18893 [https://bugs.python.org/issue18893]: Fix invalid exception handling in Lib/ctypes/macholib/dyld.py. Patch by Madison May.

bpo-27611 [https://bugs.python.org/issue27611]: Fixed support of default root window in the tkinter.tix module. Added the master parameter in the DisplayStyle constructor.

bpo-27348 [https://bugs.python.org/issue27348]: In the traceback module, restore the formatting of exception messages like « Exception: None ». This fixes a regression introduced in 3.5a2.

bpo-25651 [https://bugs.python.org/issue25651]: Allow falsy values to be used for msg parameter of subTest().

bpo-27778 [https://bugs.python.org/issue27778]: Fix a memory leak in os.getrandom() when the getrandom() is interrupted by a signal and a signal handler raises a Python exception.

bpo-28200 [https://bugs.python.org/issue28200]: Fix memory leak on Windows in the os module (fix path_converter() function).

bpo-25400 [https://bugs.python.org/issue25400]: RobotFileParser now correctly returns default values for crawl_delay and request_rate. Initial patch by Peter Wirtz.

bpo-27932 [https://bugs.python.org/issue27932]: Prevent memory leak in win32_ver().

Fix UnboundLocalError in socket._sendfile_use_sendfile.

bpo-28075 [https://bugs.python.org/issue28075]: Check for ERROR_ACCESS_DENIED in Windows implementation of os.stat(). Patch by Eryk Sun.

bpo-22493 [https://bugs.python.org/issue22493]: Warning message emitted by using inline flags in the middle of regular expression now contains a (truncated) regex pattern. Patch by Tim Graham.

bpo-25270 [https://bugs.python.org/issue25270]: Prevent codecs.escape_encode() from raising SystemError when an empty bytestring is passed.

bpo-28181 [https://bugs.python.org/issue28181]: Get antigravity over HTTPS. Patch by Kaartic Sivaraam.

bpo-25895 [https://bugs.python.org/issue25895]: Enable WebSocket URL schemes in urllib.parse.urljoin. Patch by Gergely Imreh and Markus Holtermann.

bpo-28114 [https://bugs.python.org/issue28114]: Fix a crash in parse_envlist() when env contains byte strings. Patch by Eryk Sun.

bpo-27599 [https://bugs.python.org/issue27599]: Fixed buffer overrun in binascii.b2a_qp() and binascii.a2b_qp().

bpo-27906 [https://bugs.python.org/issue27906]: Fix socket accept exhaustion during high TCP traffic. Patch by Kevin Conway.

bpo-28174 [https://bugs.python.org/issue28174]: Handle when SO_REUSEPORT isn’t properly supported. Patch by Seth Michael Larson.

bpo-26654 [https://bugs.python.org/issue26654]: Inspect functools.partial in asyncio.Handle.__repr__. Patch by iceboy.

bpo-26909 [https://bugs.python.org/issue26909]: Fix slow pipes IO in asyncio. Patch by INADA Naoki.

bpo-28176 [https://bugs.python.org/issue28176]: Fix callbacks race in asyncio.SelectorLoop.sock_connect.

bpo-27759 [https://bugs.python.org/issue27759]: Fix selectors incorrectly retain invalid file descriptors. Patch by Mark Williams.

bpo-28368 [https://bugs.python.org/issue28368]: Refuse monitoring processes if the child watcher has no loop attached. Patch by Vincent Michel.

bpo-28369 [https://bugs.python.org/issue28369]: Raise RuntimeError when transport’s FD is used with add_reader, add_writer, etc.

bpo-28370 [https://bugs.python.org/issue28370]: Speedup asyncio.StreamReader.readexactly. Patch by Коренберг Марк.

bpo-28371 [https://bugs.python.org/issue28371]: Deprecate passing asyncio.Handles to run_in_executor.

bpo-28372 [https://bugs.python.org/issue28372]: Fix asyncio to support formatting of non-python coroutines.

bpo-28399 [https://bugs.python.org/issue28399]: Remove UNIX socket from FS before binding. Patch by Коренберг Марк.

bpo-27972 [https://bugs.python.org/issue27972]: Prohibit Tasks to await on themselves.

Windows

bpo-28402 [https://bugs.python.org/issue28402]: Adds signed catalog files for stdlib on Windows.

bpo-28333 [https://bugs.python.org/issue28333]: Enables Unicode for ps1/ps2 and input() prompts. (Patch by Eryk Sun)

bpo-28251 [https://bugs.python.org/issue28251]: Improvements to help manuals on Windows.

bpo-28110 [https://bugs.python.org/issue28110]: launcher.msi has different product codes between 32-bit and 64-bit

bpo-28161 [https://bugs.python.org/issue28161]: Opening CON for write access fails

bpo-28162 [https://bugs.python.org/issue28162]: WindowsConsoleIO readall() fails if first line starts with Ctrl+Z

bpo-28163 [https://bugs.python.org/issue28163]: WindowsConsoleIO fileno() passes wrong flags to _open_osfhandle

bpo-28164 [https://bugs.python.org/issue28164]: _PyIO_get_console_type fails for various paths

bpo-28137 [https://bugs.python.org/issue28137]: Renames Windows path file to ._pth

bpo-28138 [https://bugs.python.org/issue28138]: Windows ._pth file should allow import site

C API

bpo-28426 [https://bugs.python.org/issue28426]: Deprecated undocumented functions PyUnicode_AsEncodedObject(), PyUnicode_AsDecodedObject(), PyUnicode_AsDecodedUnicode() and PyUnicode_AsEncodedUnicode().

Build

bpo-28258 [https://bugs.python.org/issue28258]: Fixed build with Estonian locale (python-config and distclean targets in Makefile). Patch by Arfrever Frehtes Taifersar Arahesis.

bpo-26661 [https://bugs.python.org/issue26661]: setup.py now detects system libffi with multiarch wrapper.

bpo-15819 [https://bugs.python.org/issue15819]: Remove redundant include search directory option for building outside the source tree.

Tests

bpo-28217 [https://bugs.python.org/issue28217]: Adds _testconsole module to test console input.

Python 3.6.0 beta 1

Release date: 2016-09-12

Core and Builtins

bpo-23722 [https://bugs.python.org/issue23722]: The __class__ cell used by zero-argument super() is now initialized from type.__new__ rather than __build_class__, so class methods relying on that will now work correctly when called from metaclass methods during class creation. Patch by Martin Teichmann.

bpo-25221 [https://bugs.python.org/issue25221]: Fix corrupted result from PyLong_FromLong(0) when Python is compiled with NSMALLPOSINTS = 0.

bpo-27080 [https://bugs.python.org/issue27080]: Implement formatting support for PEP 515. Initial patch by Chris Angelico.

bpo-27199 [https://bugs.python.org/issue27199]: In tarfile, expose copyfileobj bufsize to improve throughput. Patch by Jason Fried.

bpo-27948 [https://bugs.python.org/issue27948]: In f-strings, only allow backslashes inside the braces (where the expressions are). This is a breaking change from the 3.6 alpha releases, where backslashes are allowed anywhere in an f-string. Also, require that expressions inside f-strings be enclosed within literal braces, and not escapes like f'\x7b"hi"\x7d'.

bpo-28046 [https://bugs.python.org/issue28046]: Remove platform-specific directories from sys.path.

bpo-28071 [https://bugs.python.org/issue28071]: Add early-out for differencing from an empty set.

bpo-25758 [https://bugs.python.org/issue25758]: Prevents zipimport from unnecessarily encoding a filename (patch by Eryk Sun)

bpo-25856 [https://bugs.python.org/issue25856]: The __module__ attribute of extension classes and functions now is interned. This leads to more compact pickle data with protocol 4.

bpo-27213 [https://bugs.python.org/issue27213]: Rework CALL_FUNCTION* opcodes to produce shorter and more efficient bytecode. Patch by Demur Rumed, design by Serhiy Storchaka, reviewed by Serhiy Storchaka and Victor Stinner.

bpo-26331 [https://bugs.python.org/issue26331]: Implement tokenizing support for PEP 515. Patch by Georg Brandl.

bpo-27999 [https://bugs.python.org/issue27999]: Make « global after use » a SyntaxError, and ditto for nonlocal. Patch by Ivan Levkivskyi.

bpo-28003 [https://bugs.python.org/issue28003]: Implement PEP 525 – Asynchronous Generators.

bpo-27985 [https://bugs.python.org/issue27985]: Implement PEP 526 – Syntax for Variable Annotations. Patch by Ivan Levkivskyi.

bpo-26058 [https://bugs.python.org/issue26058]: Add a new private version to the builtin dict type, incremented at each dictionary creation and at each dictionary change. Implementation of the PEP 509.

bpo-27364 [https://bugs.python.org/issue27364]: A backslash-character pair that is not a valid escape sequence now generates a DeprecationWarning. Patch by Emanuel Barry.

bpo-27350 [https://bugs.python.org/issue27350]: dict implementation is changed like PyPy. It is more compact and preserves insertion order. (Concept developed by Raymond Hettinger and patch by Inada Naoki.)

bpo-27911 [https://bugs.python.org/issue27911]: Remove unnecessary error checks in exec_builtin_or_dynamic().

bpo-27078 [https://bugs.python.org/issue27078]: Added BUILD_STRING opcode. Optimized f-strings evaluation.

bpo-17884 [https://bugs.python.org/issue17884]: Python now requires systems with inttypes.h and stdint.h

bpo-27961 [https://bugs.python.org/issue27961]: Require platforms to support long long. Python hasn’t compiled without long long for years, so this is basically a formality.

bpo-27355 [https://bugs.python.org/issue27355]: Removed support for Windows CE. It was never finished, and Windows CE is no longer a relevant platform for Python.

Implement PEP 523.

bpo-27870 [https://bugs.python.org/issue27870]: A left shift of zero by a large integer no longer attempts to allocate large amounts of memory.

bpo-25402 [https://bugs.python.org/issue25402]: In int-to-decimal-string conversion, improve the estimate of the intermediate memory required, and remove an unnecessarily strict overflow check. Patch by Serhiy Storchaka.

bpo-27214 [https://bugs.python.org/issue27214]: In long_invert, be more careful about modifying object returned by long_add, and remove an unnecessary check for small longs. Thanks Oren Milman for analysis and patch.

bpo-27506 [https://bugs.python.org/issue27506]: Support passing the bytes/bytearray.translate() « delete » argument by keyword.

bpo-27812 [https://bugs.python.org/issue27812]: Properly clear out a generator’s frame’s backreference to the generator to prevent crashes in frame.clear().

bpo-27811 [https://bugs.python.org/issue27811]: Fix a crash when a coroutine that has not been awaited is finalized with warnings-as-errors enabled.

bpo-27587 [https://bugs.python.org/issue27587]: Fix another issue found by PVS-Studio: Null pointer check after use of “def” in _PyState_AddModule(). Initial patch by Christian Heimes.

bpo-27792 [https://bugs.python.org/issue27792]: The modulo operation applied to bool and other int subclasses now always returns an int. Previously the return type depended on the input values. Patch by Xiang Zhang.

bpo-26984 [https://bugs.python.org/issue26984]: int() now always returns an instance of exact int.

bpo-25604 [https://bugs.python.org/issue25604]: Fix a minor bug in integer true division; this bug could potentially have caused off-by-one-ulp results on platforms with unreliable ldexp implementations.

bpo-24254 [https://bugs.python.org/issue24254]: Make class definition namespace ordered by default.

bpo-27662 [https://bugs.python.org/issue27662]: Fix an overflow check in List_New: the original code was checking against Py_SIZE_MAX instead of the correct upper bound of Py_SSIZE_T_MAX. Patch by Xiang Zhang.

bpo-27782 [https://bugs.python.org/issue27782]: Multi-phase extension module import now correctly allows the m_methods field to be used to add module level functions to instances of non-module types returned from Py_create_mod. Patch by Xiang Zhang.

bpo-27936 [https://bugs.python.org/issue27936]: The round() function accepted a second None argument for some types but not for others. Fixed the inconsistency by accepting None for all numeric types.

bpo-27487 [https://bugs.python.org/issue27487]: Warn if a submodule argument to « python -m » or runpy.run_module() is found in sys.modules after parent packages are imported, but before the submodule is executed.

bpo-27157 [https://bugs.python.org/issue27157]: Make only type() itself accept the one-argument form. Patch by Eryk Sun and Emanuel Barry.

bpo-27558 [https://bugs.python.org/issue27558]: Fix a SystemError in the implementation of « raise » statement. In a brand new thread, raise a RuntimeError since there is no active exception to reraise. Patch written by Xiang Zhang.

bpo-28008 [https://bugs.python.org/issue28008]: Implement PEP 530 – asynchronous comprehensions.

bpo-27942 [https://bugs.python.org/issue27942]: Fix memory leak in codeobject.c

Library

bpo-28732 [https://bugs.python.org/issue28732]: Fix crash in os.spawnv() with no elements in args

bpo-28485 [https://bugs.python.org/issue28485]: Always raise ValueError for negative compileall.compile_dir(workers=…) parameter, even when multithreading is unavailable.

bpo-28037 [https://bugs.python.org/issue28037]: Use sqlite3_get_autocommit() instead of setting Connection->inTransaction manually.

bpo-25283 [https://bugs.python.org/issue25283]: Attributes tm_gmtoff and tm_zone are now available on all platforms in the return values of time.localtime() and time.gmtime().

bpo-24454 [https://bugs.python.org/issue24454]: Regular expression match object groups are now accessible using __getitem__. « mo[x] » is equivalent to « mo.group(x) ».

bpo-10740 [https://bugs.python.org/issue10740]: sqlite3 no longer implicitly commit an open transaction before DDL statements.

bpo-17941 [https://bugs.python.org/issue17941]: Add a module parameter to collections.namedtuple().

bpo-22493 [https://bugs.python.org/issue22493]: Inline flags now should be used only at the start of the regular expression. Deprecation warning is emitted if uses them in the middle of the regular expression.

bpo-26885 [https://bugs.python.org/issue26885]: xmlrpc now supports unmarshalling additional data types used by Apache XML-RPC implementation for numerics and None.

bpo-28070 [https://bugs.python.org/issue28070]: Fixed parsing inline verbose flag in regular expressions.

bpo-19500 [https://bugs.python.org/issue19500]: Add client-side SSL session resumption to the ssl module.

bpo-28022 [https://bugs.python.org/issue28022]: Deprecate ssl-related arguments in favor of SSLContext. The deprecation include manual creation of SSLSocket and certfile/keyfile (or similar) in ftplib, httplib, imaplib, smtplib, poplib and urllib.

bpo-28043 [https://bugs.python.org/issue28043]: SSLContext has improved default settings: OP_NO_SSLv2, OP_NO_SSLv3, OP_NO_COMPRESSION, OP_CIPHER_SERVER_PREFERENCE, OP_SINGLE_DH_USE, OP_SINGLE_ECDH_USE and HIGH ciphers without MD5.

bpo-24693 [https://bugs.python.org/issue24693]: Changed some RuntimeError’s in the zipfile module to more appropriate types. Improved some error messages and debugging output.

bpo-17909 [https://bugs.python.org/issue17909]: json.load and json.loads now support binary input encoded as UTF-8, UTF-16 or UTF-32. Patch by Serhiy Storchaka.

bpo-27137 [https://bugs.python.org/issue27137]: the pure Python fallback implementation of functools.partial now matches the behaviour of its accelerated C counterpart for subclassing, pickling and text representation purposes. Patch by Emanuel Barry and Serhiy Storchaka.

Fix possible integer overflows and crashes in the mmap module with unusual usage patterns.

bpo-1703178 [https://bugs.python.org/issue1703178]: Fix the ability to pass the –link-objects option to the distutils build_ext command.

bpo-28019 [https://bugs.python.org/issue28019]: itertools.count() no longer rounds non-integer step in range between 1.0 and 2.0 to 1.

bpo-18401 [https://bugs.python.org/issue18401]: Pdb now supports the “readrc” keyword argument to control whether .pdbrc files should be read. Patch by Martin Matusiak and Sam Kimbrel.

bpo-25969 [https://bugs.python.org/issue25969]: Update the lib2to3 grammar to handle the unpacking generalizations added in 3.5.

bpo-14977 [https://bugs.python.org/issue14977]: mailcap now respects the order of the lines in the mailcap files (« first match »), as required by RFC 1542. Patch by Michael Lazar.

bpo-28082 [https://bugs.python.org/issue28082]: Convert re flag constants to IntFlag.

bpo-28025 [https://bugs.python.org/issue28025]: Convert all ssl module constants to IntEnum and IntFlags. SSLContext properties now return flags and enums.

bpo-23591 [https://bugs.python.org/issue23591]: Add Flag, IntFlag, and auto() to enum module.

bpo-433028 [https://bugs.python.org/issue433028]: Added support of modifier spans in regular expressions.

bpo-24594 [https://bugs.python.org/issue24594]: Validates persist parameter when opening MSI database

bpo-17582 [https://bugs.python.org/issue17582]: xml.etree.ElementTree nows preserves whitespaces in attributes (Patch by Duane Griffin. Reviewed and approved by Stefan Behnel.)

bpo-28047 [https://bugs.python.org/issue28047]: Fixed calculation of line length used for the base64 CTE in the new email policies.

bpo-27576 [https://bugs.python.org/issue27576]: Fix call order in OrderedDict.__init__().

email.generator.DecodedGenerator now supports the policy keyword.

bpo-28027 [https://bugs.python.org/issue28027]: Remove undocumented modules from Lib/plat-*: IN, CDROM, DLFCN, TYPES, CDIO, and STROPTS.

bpo-27445 [https://bugs.python.org/issue27445]: Don’t pass str(_charset) to MIMEText.set_payload(). Patch by Claude Paroz.

bpo-24277 [https://bugs.python.org/issue24277]: The new email API is no longer provisional, and the docs have been reorganized and rewritten to emphasize the new API.

bpo-22450 [https://bugs.python.org/issue22450]: urllib now includes an Accept: */* header among the default headers. This makes the results of REST API requests more consistent and predictable especially when proxy servers are involved.

lib2to3.pgen3.driver.load_grammar() now creates a stable cache file between runs given the same Grammar.txt input regardless of the hash randomization setting.

bpo-28005 [https://bugs.python.org/issue28005]: Allow ImportErrors in encoding implementation to propagate.

bpo-26667 [https://bugs.python.org/issue26667]: Support path-like objects in importlib.util.

bpo-27570 [https://bugs.python.org/issue27570]: Avoid zero-length memcpy() etc calls with null source pointers in the « ctypes » and « array » modules.

bpo-22233 [https://bugs.python.org/issue22233]: Break email header lines only on the RFC specified CR and LF characters, not on arbitrary unicode line breaks. This also fixes a bug in HTTP header parsing.

bpo-27331 [https://bugs.python.org/issue27331]: The email.mime classes now all accept an optional policy keyword.

bpo-27988 [https://bugs.python.org/issue27988]: Fix email iter_attachments incorrect mutation of payload list.

bpo-16113 [https://bugs.python.org/issue16113]: Add SHA-3 and SHAKE support to hashlib module.

Eliminate a tautological-pointer-compare warning in _scproxy.c.

bpo-27776 [https://bugs.python.org/issue27776]: The os.urandom() function does now block on Linux 3.17 and newer until the system urandom entropy pool is initialized to increase the security. This change is part of the PEP 524 [https://www.python.org/dev/peps/pep-0524].

bpo-27778 [https://bugs.python.org/issue27778]: Expose the Linux getrandom() syscall as a new os.getrandom() function. This change is part of the PEP 524 [https://www.python.org/dev/peps/pep-0524].

bpo-27691 [https://bugs.python.org/issue27691]: Fix ssl module’s parsing of GEN_RID subject alternative name fields in X.509 certs.

bpo-18844 [https://bugs.python.org/issue18844]: Add random.choices().

bpo-25761 [https://bugs.python.org/issue25761]: Improved error reporting about truncated pickle data in C implementation of unpickler. UnpicklingError is now raised instead of AttributeError and ValueError in some cases.

bpo-26798 [https://bugs.python.org/issue26798]: Add BLAKE2 (blake2b and blake2s) to hashlib.

bpo-26032 [https://bugs.python.org/issue26032]: Optimized globbing in pathlib by using os.scandir(); it is now about 1.5–4 times faster.

bpo-25596 [https://bugs.python.org/issue25596]: Optimized glob() and iglob() functions in the glob module; they are now about 3–6 times faster.

bpo-27928 [https://bugs.python.org/issue27928]: Add scrypt (password-based key derivation function) to hashlib module (requires OpenSSL 1.1.0).

bpo-27850 [https://bugs.python.org/issue27850]: Remove 3DES from ssl module’s default cipher list to counter measure sweet32 attack (CVE-2016-2183).

bpo-27766 [https://bugs.python.org/issue27766]: Add ChaCha20 Poly1305 to ssl module’s default cipher list. (Required OpenSSL 1.1.0 or LibreSSL).

bpo-25387 [https://bugs.python.org/issue25387]: Check return value of winsound.MessageBeep.

bpo-27866 [https://bugs.python.org/issue27866]: Add SSLContext.get_ciphers() method to get a list of all enabled ciphers.

bpo-27744 [https://bugs.python.org/issue27744]: Add AF_ALG (Linux Kernel crypto) to socket module.

bpo-26470 [https://bugs.python.org/issue26470]: Port ssl and hashlib module to OpenSSL 1.1.0.

bpo-11620 [https://bugs.python.org/issue11620]: Fix support for SND_MEMORY in winsound.PlaySound. Based on a patch by Tim Lesher.

bpo-11734 [https://bugs.python.org/issue11734]: Add support for IEEE 754 half-precision floats to the struct module. Based on a patch by Eli Stevens.

bpo-27919 [https://bugs.python.org/issue27919]: Deprecated extra_path distribution option in distutils packaging.

bpo-23229 [https://bugs.python.org/issue23229]: Add new cmath constants: cmath.inf and cmath.nan to match math.inf and math.nan, and also cmath.infj and cmath.nanj to match the format used by complex repr.

bpo-27842 [https://bugs.python.org/issue27842]: The csv.DictReader now returns rows of type OrderedDict. (Contributed by Steve Holden.)

Remove support for passing a file descriptor to os.access. It never worked but previously didn’t raise.

bpo-12885 [https://bugs.python.org/issue12885]: Fix error when distutils encounters symlink.

bpo-27881 [https://bugs.python.org/issue27881]: Fixed possible bugs when setting sqlite3.Connection.isolation_level. Based on patch by Xiang Zhang.

bpo-27861 [https://bugs.python.org/issue27861]: Fixed a crash in sqlite3.Connection.cursor() when a factory creates not a cursor. Patch by Xiang Zhang.

bpo-19884 [https://bugs.python.org/issue19884]: Avoid spurious output on OS X with Gnu Readline.

bpo-27706 [https://bugs.python.org/issue27706]: Restore deterministic behavior of random.Random().seed() for string seeds using seeding version 1. Allows sequences of calls to random() to exactly match those obtained in Python 2. Patch by Nofar Schnider.

bpo-10513 [https://bugs.python.org/issue10513]: Fix a regression in Connection.commit(). Statements should not be reset after a commit.

bpo-12319 [https://bugs.python.org/issue12319]: Chunked transfer encoding support added to http.client.HTTPConnection requests. The urllib.request.AbstractHTTPHandler class does not enforce a Content-Length header any more. If a HTTP request has a file or iterable body, but no Content-Length header, the library now falls back to use chunked transfer-encoding.

A new version of typing.py from https://github.com/python/typing: - Collection (only for 3.6) (bpo-27598 [https://bugs.python.org/issue27598]) - Add FrozenSet to __all__ (upstream #261) - fix crash in _get_type_vars() (upstream #259) - Remove the dict constraint in ForwardRef._eval_type (upstream #252)

bpo-27832 [https://bugs.python.org/issue27832]: Make _normalize parameter to Fraction constuctor keyword-only, so that Fraction(2, 3, 4) now raises TypeError.

bpo-27539 [https://bugs.python.org/issue27539]: Fix unnormalised Fraction.__pow__ result in the case of negative exponent and negative base.

bpo-21718 [https://bugs.python.org/issue21718]: cursor.description is now available for queries using CTEs.

bpo-27819 [https://bugs.python.org/issue27819]: In distutils sdists, simply produce the « gztar » (gzipped tar format) distributions on all platforms unless « formats » is supplied.

bpo-2466 [https://bugs.python.org/issue2466]: posixpath.ismount now correctly recognizes mount points which the user does not have permission to access.

bpo-9998 [https://bugs.python.org/issue9998]: On Linux, ctypes.util.find_library now looks in LD_LIBRARY_PATH for shared libraries.

bpo-27573 [https://bugs.python.org/issue27573]: exit message for code.interact is now configurable.

bpo-27930 [https://bugs.python.org/issue27930]: Improved behaviour of logging.handlers.QueueListener. Thanks to Paulo Andrade and Petr Viktorin for the analysis and patch.

bpo-6766 [https://bugs.python.org/issue6766]: Distributed reference counting added to multiprocessing to support nesting of shared values / proxy objects.

bpo-21201 [https://bugs.python.org/issue21201]: Improves readability of multiprocessing error message. Thanks to Wojciech Walczak for patch.

asyncio: Add set_protocol / get_protocol to Transports.

bpo-27456 [https://bugs.python.org/issue27456]: asyncio: Set TCP_NODELAY by default.

IDLE

bpo-15308 [https://bugs.python.org/issue15308]: Add “interrupt execution” (^C) to Shell menu. Patch by Roger Serwy, updated by Bayard Randel.

bpo-27922 [https://bugs.python.org/issue27922]: Stop IDLE tests from “flashing” gui widgets on the screen.

bpo-27891 [https://bugs.python.org/issue27891]: Consistently group and sort imports within idlelib modules.

bpo-17642 [https://bugs.python.org/issue17642]: add larger font sizes for classroom projection.

Add version to title of IDLE help window.

bpo-25564 [https://bugs.python.org/issue25564]: In section on IDLE – console differences, mention that using exec means that __builtins__ is defined for each statement.

bpo-27821 [https://bugs.python.org/issue27821]: Fix 3.6.0a3 regression that prevented custom key sets from being selected when no custom theme was defined.

C API

bpo-26900 [https://bugs.python.org/issue26900]: Excluded underscored names and other private API from limited API.

bpo-26027 [https://bugs.python.org/issue26027]: Add support for path-like objects in PyUnicode_FSConverter() & PyUnicode_FSDecoder().

Tests

bpo-27427 [https://bugs.python.org/issue27427]: Additional tests for the math module. Patch by Francisco Couzo.

bpo-27953 [https://bugs.python.org/issue27953]: Skip math and cmath tests that fail on OS X 10.4 due to a poor libm implementation of tan.

bpo-26040 [https://bugs.python.org/issue26040]: Improve test_math and test_cmath coverage and rigour. Patch by Jeff Allen.

bpo-27787 [https://bugs.python.org/issue27787]: Call gc.collect() before checking each test for « dangling threads », since the dangling threads are weak references.

Build

bpo-27566 [https://bugs.python.org/issue27566]: Fix clean target in freeze makefile (patch by Lisa Roach)

bpo-27705 [https://bugs.python.org/issue27705]: Update message in validate_ucrtbase.py

bpo-27976 [https://bugs.python.org/issue27976]: Deprecate building _ctypes with the bundled copy of libffi on non-OSX UNIX platforms.

bpo-27983 [https://bugs.python.org/issue27983]: Cause lack of llvm-profdata tool when using clang as required for PGO linking to be a configure time error rather than make time when --with-optimizations is enabled. Also improve our ability to find the llvm-profdata tool on MacOS and some Linuxes.

bpo-21590 [https://bugs.python.org/issue21590]: Support for DTrace and SystemTap probes.

bpo-26307 [https://bugs.python.org/issue26307]: The profile-opt build now applies PGO to the built-in modules.

bpo-26359 [https://bugs.python.org/issue26359]: Add the –with-optimizations flag to turn on LTO and PGO build support when available.

bpo-27917 [https://bugs.python.org/issue27917]: Set platform triplets for Android builds.

bpo-25825 [https://bugs.python.org/issue25825]: Update references to the $(LIBPL) installation path on AIX. This path was changed in 3.2a4.

Update OS X installer to use SQLite 3.14.1 and XZ 5.2.2.

bpo-21122 [https://bugs.python.org/issue21122]: Fix LTO builds on OS X.

bpo-17128 [https://bugs.python.org/issue17128]: Build OS X installer with a private copy of OpenSSL. Also provide a sample Install Certificates command script to install a set of root certificates from the third-party certifi module.

Tools/Demos

bpo-27952 [https://bugs.python.org/issue27952]: Get Tools/scripts/fixcid.py working with Python 3 and the current « re » module, avoid invalid Python backslash escapes, and fix a bug parsing escaped C quote signs.

Windows

bpo-28065 [https://bugs.python.org/issue28065]: Update xz dependency to 5.2.2 and build it from source.

bpo-25144 [https://bugs.python.org/issue25144]: Ensures TargetDir is set before continuing with custom install.

bpo-1602 [https://bugs.python.org/issue1602]: Windows console doesn’t input or print Unicode (PEP 528)

bpo-27781 [https://bugs.python.org/issue27781]: Change file system encoding on Windows to UTF-8 (PEP 529)

bpo-27731 [https://bugs.python.org/issue27731]: Opt-out of MAX_PATH on Windows 10

bpo-6135 [https://bugs.python.org/issue6135]: Adds encoding and errors parameters to subprocess.

bpo-27959 [https://bugs.python.org/issue27959]: Adds oem encoding, alias ansi to mbcs, move aliasmbcs to codec lookup.

bpo-27982 [https://bugs.python.org/issue27982]: The functions of the winsound module now accept keyword arguments.

bpo-20366 [https://bugs.python.org/issue20366]: Build full text search support into SQLite on Windows.

bpo-27756 [https://bugs.python.org/issue27756]: Adds new icons for Python files and processes on Windows. Designs by Cherry Wang.

bpo-27883 [https://bugs.python.org/issue27883]: Update sqlite to 3.14.1.0 on Windows.

Python 3.6.0 alpha 4

Release date: 2016-08-15

Core and Builtins

bpo-27704 [https://bugs.python.org/issue27704]: Optimized creating bytes and bytearray from byte-like objects and iterables. Speed up to 3 times for short objects. Original patch by Naoki Inada.

bpo-26823 [https://bugs.python.org/issue26823]: Large sections of repeated lines in tracebacks are now abbreviated as « [Previous line repeated {count} more times] » by the builtin traceback rendering. Patch by Emanuel Barry.

bpo-27574 [https://bugs.python.org/issue27574]: Decreased an overhead of parsing keyword arguments in functions implemented with using Argument Clinic.

bpo-22557 [https://bugs.python.org/issue22557]: Now importing already imported modules is up to 2.5 times faster.

bpo-17596 [https://bugs.python.org/issue17596]: Include <wincrypt.h> to help with Min GW building.

bpo-17599 [https://bugs.python.org/issue17599]: On Windows, rename the privately defined REPARSE_DATA_BUFFER structure to avoid conflicting with the definition from Min GW.

bpo-27507 [https://bugs.python.org/issue27507]: Add integer overflow check in bytearray.extend(). Patch by Xiang Zhang.

bpo-27581 [https://bugs.python.org/issue27581]: Don’t rely on wrapping for overflow check in PySequence_Tuple(). Patch by Xiang Zhang.

bpo-1621 [https://bugs.python.org/issue1621]: Avoid signed integer overflow in list and tuple operations. Patch by Xiang Zhang.

bpo-27419 [https://bugs.python.org/issue27419]: Standard __import__() no longer look up « __import__ » in globals or builtins for importing submodules or « from import ». Fixed a crash if raise a warning about unabling to resolve package from __spec__ or __package__.

bpo-27083 [https://bugs.python.org/issue27083]: Respect the PYTHONCASEOK environment variable under Windows.

bpo-27514 [https://bugs.python.org/issue27514]: Make having too many statically nested blocks a SyntaxError instead of SystemError.

bpo-27366 [https://bugs.python.org/issue27366]: Implemented PEP 487 (Simpler customization of class creation). Upon subclassing, the __init_subclass__ classmethod is called on the base class. Descriptors are initialized with __set_name__ after class creation.

Library

bpo-26027 [https://bugs.python.org/issue26027]: Add PEP 519/__fspath__() support to the os and os.path modules. Includes code from Jelle Zijlstra. (See also: bpo-27524 [https://bugs.python.org/issue27524])

bpo-27598 [https://bugs.python.org/issue27598]: Add Collections to collections.abc. Patch by Ivan Levkivskyi, docs by Neil Girdhar.

bpo-25958 [https://bugs.python.org/issue25958]: Support « anti-registration » of special methods from various ABCs, like __hash__, __iter__ or __len__. All these (and several more) can be set to None in an implementation class and the behavior will be as if the method is not defined at all. (Previously, this mechanism existed only for __hash__, to make mutable classes unhashable.) Code contributed by Andrew Barnert and Ivan Levkivskyi.

bpo-16764 [https://bugs.python.org/issue16764]: Support keyword arguments to zlib.decompress(). Patch by Xiang Zhang.

bpo-27736 [https://bugs.python.org/issue27736]: Prevent segfault after interpreter re-initialization due to ref count problem introduced in code for bpo-27038 [https://bugs.python.org/issue27038] in 3.6.0a3. Patch by Xiang Zhang.

bpo-25628 [https://bugs.python.org/issue25628]: The verbose and rename parameters for collections.namedtuple are now keyword-only.

bpo-12345 [https://bugs.python.org/issue12345]: Add mathematical constant tau to math and cmath. See also PEP 628.

bpo-26823 [https://bugs.python.org/issue26823]: traceback.StackSummary.format now abbreviates large sections of repeated lines as « [Previous line repeated {count} more times] » (this change then further affects other traceback display operations in the module). Patch by Emanuel Barry.

bpo-27664 [https://bugs.python.org/issue27664]: Add to concurrent.futures.thread.ThreadPoolExecutor() the ability to specify a thread name prefix.

bpo-27181 [https://bugs.python.org/issue27181]: Add geometric_mean and harmonic_mean to statistics module.

bpo-27573 [https://bugs.python.org/issue27573]: code.interact now prints an message when exiting.

bpo-6422 [https://bugs.python.org/issue6422]: Add autorange method to timeit.Timer objects.

bpo-27773 [https://bugs.python.org/issue27773]: Correct some memory management errors server_hostname in _ssl.wrap_socket().

bpo-26750 [https://bugs.python.org/issue26750]: unittest.mock.create_autospec() now works properly for subclasses of property() and other data descriptors. Removes the never publicly used, never documented unittest.mock.DescriptorTypes tuple.

bpo-26754 [https://bugs.python.org/issue26754]: Undocumented support of general bytes-like objects as path in compile() and similar functions is now deprecated.

bpo-26800 [https://bugs.python.org/issue26800]: Undocumented support of general bytes-like objects as paths in os functions is now deprecated.

bpo-26981 [https://bugs.python.org/issue26981]: Add _order_ compatibility shim to enum.Enum for Python 2/3 code bases.

bpo-27661 [https://bugs.python.org/issue27661]: Added tzinfo keyword argument to datetime.combine.

In the curses module, raise an error if window.getstr() or window.instr() is passed a negative value.

bpo-27783 [https://bugs.python.org/issue27783]: Fix possible usage of uninitialized memory in operator.methodcaller.

bpo-27774 [https://bugs.python.org/issue27774]: Fix possible Py_DECREF on unowned object in _sre.

bpo-27760 [https://bugs.python.org/issue27760]: Fix possible integer overflow in binascii.b2a_qp.

bpo-27758 [https://bugs.python.org/issue27758]: Fix possible integer overflow in the _csv module for large record lengths.

bpo-27568 [https://bugs.python.org/issue27568]: Prevent HTTPoxy attack (CVE-2016-1000110). Ignore the HTTP_PROXY variable when REQUEST_METHOD environment is set, which indicates that the script is in CGI mode.

bpo-7063 [https://bugs.python.org/issue7063]: Remove dead code from the « array » module’s slice handling. Patch by Chuck.

bpo-27656 [https://bugs.python.org/issue27656]: Do not assume sched.h defines any SCHED_* constants.

bpo-27130 [https://bugs.python.org/issue27130]: In the « zlib » module, fix handling of large buffers (typically 4 GiB) when compressing and decompressing. Previously, inputs were limited to 4 GiB, and compression and decompression operations did not properly handle results of 4 GiB.

bpo-24773 [https://bugs.python.org/issue24773]: Implemented PEP 495 (Local Time Disambiguation).

Expose the EPOLLEXCLUSIVE constant (when it is defined) in the select module.

bpo-27567 [https://bugs.python.org/issue27567]: Expose the EPOLLRDHUP and POLLRDHUP constants in the select module.

bpo-1621 [https://bugs.python.org/issue1621]: Avoid signed int negation overflow in the « audioop » module.

bpo-27533 [https://bugs.python.org/issue27533]: Release GIL in nt._isdir

bpo-17711 [https://bugs.python.org/issue17711]: Fixed unpickling by the persistent ID with protocol 0. Original patch by Alexandre Vassalotti.

bpo-27522 [https://bugs.python.org/issue27522]: Avoid an unintentional reference cycle in email.feedparser.

bpo-27512 [https://bugs.python.org/issue27512]: Fix a segfault when os.fspath() called an __fspath__() method that raised an exception. Patch by Xiang Zhang.

IDLE

bpo-27714 [https://bugs.python.org/issue27714]: text_textview and test_autocomplete now pass when re-run in the same process. This occurs when test_idle fails when run with the -w option but without -jn. Fix warning from test_config.

bpo-27621 [https://bugs.python.org/issue27621]: Put query response validation error messages in the query box itself instead of in a separate messagebox. Redo tests to match. Add Mac OSX refinements. Original patch by Mark Roseman.

bpo-27620 [https://bugs.python.org/issue27620]: Escape key now closes Query box as cancelled.

bpo-27609 [https://bugs.python.org/issue27609]: IDLE: tab after initial whitespace should tab, not autocomplete. This fixes problem with writing docstrings at least twice indented.

bpo-27609 [https://bugs.python.org/issue27609]: Explicitly return None when there are also non-None returns. In a few cases, reverse a condition and eliminate a return.

bpo-25507 [https://bugs.python.org/issue25507]: IDLE no longer runs buggy code because of its tkinter imports. Users must include the same imports required to run directly in Python.

bpo-27173 [https://bugs.python.org/issue27173]: Add “IDLE Modern Unix” to the built-in key sets. Make the default key set depend on the platform. Add tests for the changes to the config module.

bpo-27452 [https://bugs.python.org/issue27452]: add line counter and crc to IDLE configHandler test dump.

Tests

bpo-25805 [https://bugs.python.org/issue25805]: Skip a test in test_pkgutil as needed that doesn’t work when __name__ == __main__. Patch by SilentGhost.

bpo-27472 [https://bugs.python.org/issue27472]: Add test.support.unix_shell as the path to the default shell.

bpo-27369 [https://bugs.python.org/issue27369]: In test_pyexpat, avoid testing an error message detail that changed in Expat 2.2.0.

bpo-27594 [https://bugs.python.org/issue27594]: Prevent assertion error when running test_ast with coverage enabled: ensure code object has a valid first line number. Patch suggested by Ivan Levkivskyi.

Windows

bpo-27647 [https://bugs.python.org/issue27647]: Update bundled Tcl/Tk to 8.6.6.

bpo-27610 [https://bugs.python.org/issue27610]: Adds PEP 514 metadata to Windows installer

bpo-27469 [https://bugs.python.org/issue27469]: Adds a shell extension to the launcher so that drag and drop works correctly.

bpo-27309 [https://bugs.python.org/issue27309]: Enables proper Windows styles in python[w].exe manifest.

Build

bpo-27713 [https://bugs.python.org/issue27713]: Suppress spurious build warnings when updating importlib’s bootstrap files. Patch by Xiang Zhang

bpo-25825 [https://bugs.python.org/issue25825]: Correct the references to Modules/python.exp, which is required on AIX. The references were accidentally changed in 3.5.0a1.

bpo-27453 [https://bugs.python.org/issue27453]: CPP invocation in configure must use CPPFLAGS. Patch by Chi Hsuan Yen.

bpo-27641 [https://bugs.python.org/issue27641]: The configure script now inserts comments into the makefile to prevent the pgen and _freeze_importlib executables from being cross-compiled.

bpo-26662 [https://bugs.python.org/issue26662]: Set PYTHON_FOR_GEN in configure as the Python program to be used for file generation during the build.

bpo-10910 [https://bugs.python.org/issue10910]: Avoid C++ compilation errors on FreeBSD and OS X. Also update FreedBSD version checks for the original ctype UTF-8 workaround.

Python 3.6.0 alpha 3

Release date: 2016-07-11

Core and Builtins

bpo-27473 [https://bugs.python.org/issue27473]: Fixed possible integer overflow in bytes and bytearray concatenations. Patch by Xiang Zhang.

bpo-23034 [https://bugs.python.org/issue23034]: The output of a special Python build with defined COUNT_ALLOCS, SHOW_ALLOC_COUNT or SHOW_TRACK_COUNT macros is now off by default. It can be re-enabled using the « -X showalloccount » option. It now outputs to stderr instead of stdout.

bpo-27443 [https://bugs.python.org/issue27443]: __length_hint__() of bytearray iterators no longer return a negative integer for a resized bytearray.

bpo-27007 [https://bugs.python.org/issue27007]: The fromhex() class methods of bytes and bytearray subclasses now return an instance of corresponding subclass.

Library

bpo-26844 [https://bugs.python.org/issue26844]: Fix error message for imp.find_module() to refer to “path” instead of “name”. Patch by Lev Maximov.

bpo-23804 [https://bugs.python.org/issue23804]: Fix SSL zero-length recv() calls to not block and not raise an error about unclean EOF.

bpo-27466 [https://bugs.python.org/issue27466]: Change time format returned by http.cookie.time2netscape, confirming the netscape cookie format and making it consistent with documentation.

bpo-21708 [https://bugs.python.org/issue21708]: Deprecated dbm.dumb behavior that differs from common dbm behavior: creating a database in “r” and “w” modes and modifying a database in “r” mode.

bpo-26721 [https://bugs.python.org/issue26721]: Change the socketserver.StreamRequestHandler.wfile attribute to implement BufferedIOBase. In particular, the write() method no longer does partial writes.

bpo-22115 [https://bugs.python.org/issue22115]: Added methods trace_add, trace_remove and trace_info in the tkinter.Variable class. They replace old methods trace_variable, trace, trace_vdelete and trace_vinfo that use obsolete Tcl commands and might not work in future versions of Tcl. Fixed old tracing methods: trace_vdelete() with wrong mode no longer break tracing, trace_vinfo() now always returns a list of pairs of strings, tracing in the « u » mode now works.

bpo-26243 [https://bugs.python.org/issue26243]: Only the level argument to zlib.compress() is keyword argument now. The first argument is positional-only.

bpo-27038 [https://bugs.python.org/issue27038]: Expose the DirEntry type as os.DirEntry. Code patch by Jelle Zijlstra.

bpo-27186 [https://bugs.python.org/issue27186]: Update os.fspath()/PyOS_FSPath() to check the return value of __fspath__() to be either str or bytes.

bpo-18726 [https://bugs.python.org/issue18726]: All optional parameters of the dump(), dumps(), load() and loads() functions and JSONEncoder and JSONDecoder class constructors in the json module are now keyword-only.

bpo-27319 [https://bugs.python.org/issue27319]: Methods selection_set(), selection_add(), selection_remove() and selection_toggle() of ttk.TreeView now allow passing multiple items as multiple arguments instead of passing them as a tuple. Deprecated undocumented ability of calling the selection() method with arguments.

bpo-27079 [https://bugs.python.org/issue27079]: Fixed curses.ascii functions isblank(), iscntrl() and ispunct().

bpo-27294 [https://bugs.python.org/issue27294]: Numerical state in the repr for Tkinter event objects is now represented as a combination of known flags.

bpo-27177 [https://bugs.python.org/issue27177]: Match objects in the re module now support index-like objects as group indices. Based on patches by Jeroen Demeyer and Xiang Zhang.

bpo-26754 [https://bugs.python.org/issue26754]: Some functions (compile() etc) accepted a filename argument encoded as an iterable of integers. Now only strings and byte-like objects are accepted.

bpo-26536 [https://bugs.python.org/issue26536]: socket.ioctl now supports SIO_LOOPBACK_FAST_PATH. Patch by Daniel Stokes.

bpo-27048 [https://bugs.python.org/issue27048]: Prevents distutils failing on Windows when environment variables contain non-ASCII characters

bpo-27330 [https://bugs.python.org/issue27330]: Fixed possible leaks in the ctypes module.

bpo-27238 [https://bugs.python.org/issue27238]: Got rid of bare excepts in the turtle module. Original patch by Jelle Zijlstra.

bpo-27122 [https://bugs.python.org/issue27122]: When an exception is raised within the context being managed by a contextlib.ExitStack() and one of the exit stack generators catches and raises it in a chain, do not re-raise the original exception when exiting, let the new chained one through. This avoids the PEP 479 bug described in issue25782.

Security

bpo-27278 [https://bugs.python.org/issue27278]: Fix os.urandom() implementation using getrandom() on Linux. Truncate size to INT_MAX and loop until we collected enough random bytes, instead of casting a directly Py_ssize_t to int.

Library

bpo-16864 [https://bugs.python.org/issue16864]: sqlite3.Cursor.lastrowid now supports REPLACE statement. Initial patch by Alex LordThorsen.

bpo-26386 [https://bugs.python.org/issue26386]: Fixed ttk.TreeView selection operations with item id’s containing spaces.

bpo-8637 [https://bugs.python.org/issue8637]: Honor a pager set by the env var MANPAGER (in preference to one set by the env var PAGER).

Security

bpo-22636 [https://bugs.python.org/issue22636]: Avoid shell injection problems with ctypes.util.find_library().

Library

bpo-16182 [https://bugs.python.org/issue16182]: Fix various functions in the « readline » module to use the locale encoding, and fix get_begidx() and get_endidx() to return code point indexes.

bpo-27392 [https://bugs.python.org/issue27392]: Add loop.connect_accepted_socket(). Patch by Jim Fulton.

IDLE

bpo-27477 [https://bugs.python.org/issue27477]: IDLE search dialogs now use ttk widgets.

bpo-27173 [https://bugs.python.org/issue27173]: Add “IDLE Modern Unix” to the built-in key sets. Make the default key set depend on the platform. Add tests for the changes to the config module.

bpo-27452 [https://bugs.python.org/issue27452]: make command line « idle-test> python test_help.py » work. __file__ is relative when python is started in the file’s directory.

bpo-27452 [https://bugs.python.org/issue27452]: add line counter and crc to IDLE configHandler test dump.

bpo-27380 [https://bugs.python.org/issue27380]: IDLE: add query.py with base Query dialog and ttk widgets. Module had subclasses SectionName, ModuleName, and HelpSource, which are used to get information from users by configdialog and file =>Load Module. Each subclass has itw own validity checks. Using ModuleName allows users to edit bad module names instead of starting over. Add tests and delete the two files combined into the new one.

bpo-27372 [https://bugs.python.org/issue27372]: Test_idle no longer changes the locale.

bpo-27365 [https://bugs.python.org/issue27365]: Allow non-ascii chars in IDLE NEWS.txt, for contributor names.

bpo-27245 [https://bugs.python.org/issue27245]: IDLE: Cleanly delete custom themes and key bindings. Previously, when IDLE was started from a console or by import, a cascade of warnings was emitted. Patch by Serhiy Storchaka.

bpo-24137 [https://bugs.python.org/issue24137]: Run IDLE, test_idle, and htest with tkinter default root disabled. Fix code and tests that fail with this restriction. Fix htests to not create a second and redundant root and mainloop.

bpo-27310 [https://bugs.python.org/issue27310]: Fix IDLE.app failure to launch on OS X due to vestigial import.

C API

bpo-26754 [https://bugs.python.org/issue26754]: PyUnicode_FSDecoder() accepted a filename argument encoded as an iterable of integers. Now only strings and byte-like objects are accepted.

Build

bpo-28066 [https://bugs.python.org/issue28066]: Fix the logic that searches build directories for generated include files when building outside the source tree.

bpo-27442 [https://bugs.python.org/issue27442]: Expose the Android API level that python was built against, in sysconfig.get_config_vars() as “ANDROID_API_LEVEL”.

bpo-27434 [https://bugs.python.org/issue27434]: The interpreter that runs the cross-build, found in PATH, must now be of the same feature version (e.g. 3.6) as the source being built.

bpo-26930 [https://bugs.python.org/issue26930]: Update Windows builds to use OpenSSL 1.0.2h.

bpo-23968 [https://bugs.python.org/issue23968]: Rename the platform directory from plat-$(MACHDEP) to plat-$(PLATFORM_TRIPLET). Rename the config directory (LIBPL) from config-$(LDVERSION) to config-$(LDVERSION)-$(PLATFORM_TRIPLET). Install the platform specific _sysconfigdata module into the platform directory and rename it to include the ABIFLAGS.

Don’t use largefile support for GNU/Hurd.

Tools/Demos

bpo-27332 [https://bugs.python.org/issue27332]: Fixed the type of the first argument of module-level functions generated by Argument Clinic. Patch by Petr Viktorin.

bpo-27418 [https://bugs.python.org/issue27418]: Fixed Tools/importbench/importbench.py.

Documentation

bpo-19489 [https://bugs.python.org/issue19489]: Moved the search box from the sidebar to the header and footer of each page. Patch by Ammar Askar.

bpo-27285 [https://bugs.python.org/issue27285]: Update documentation to reflect the deprecation of pyvenv and normalize on the term « virtual environment ». Patch by Steve Piercy.

Tests

bpo-27027 [https://bugs.python.org/issue27027]: Added test.support.is_android that is True when this is an Android build.

Python 3.6.0 alpha 2

Release date: 2016-06-13

Core and Builtins

bpo-27095 [https://bugs.python.org/issue27095]: Simplified MAKE_FUNCTION and removed MAKE_CLOSURE opcodes. Patch by Demur Rumed.

bpo-27190 [https://bugs.python.org/issue27190]: Raise NotSupportedError if sqlite3 is older than 3.3.1. Patch by Dave Sawyer.

bpo-27286 [https://bugs.python.org/issue27286]: Fixed compiling BUILD_MAP_UNPACK_WITH_CALL opcode. Calling function with generalized unpacking (PEP 448) and conflicting keyword names could cause undefined behavior.

bpo-27140 [https://bugs.python.org/issue27140]: Added BUILD_CONST_KEY_MAP opcode.

bpo-27186 [https://bugs.python.org/issue27186]: Add support for os.PathLike objects to open() (part of PEP 519).

bpo-27066 [https://bugs.python.org/issue27066]: Fixed SystemError if a custom opener (for open()) returns a negative number without setting an exception.

bpo-26983 [https://bugs.python.org/issue26983]: float() now always return an instance of exact float. The deprecation warning is emitted if __float__ returns an instance of a strict subclass of float. In a future versions of Python this can be an error.

bpo-27097 [https://bugs.python.org/issue27097]: Python interpreter is now about 7% faster due to optimized instruction decoding. Based on patch by Demur Rumed.

bpo-26647 [https://bugs.python.org/issue26647]: Python interpreter now uses 16-bit wordcode instead of bytecode. Patch by Demur Rumed.

bpo-23275 [https://bugs.python.org/issue23275]: Allow assigning to an empty target list in round brackets: () = iterable.

bpo-27243 [https://bugs.python.org/issue27243]: Update the __aiter__ protocol: instead of returning an awaitable that resolves to an asynchronous iterator, the asynchronous iterator should be returned directly. Doing the former will trigger a PendingDeprecationWarning.

Library

Comment out socket (SO_REUSEPORT) and posix (O_SHLOCK, O_EXLOCK) constants exposed on the API which are not implemented on GNU/Hurd. They would not work at runtime anyway.

bpo-27025 [https://bugs.python.org/issue27025]: Generated names for Tkinter widgets are now more meaningful and recognizable.

bpo-25455 [https://bugs.python.org/issue25455]: Fixed crashes in repr of recursive ElementTree.Element and functools.partial objects.

bpo-27294 [https://bugs.python.org/issue27294]: Improved repr for Tkinter event objects.

bpo-20508 [https://bugs.python.org/issue20508]: Improve exception message of IPv{4,6}Network.__getitem__. Patch by Gareth Rees.

Security

bpo-26556 [https://bugs.python.org/issue26556]: Update expat to 2.1.1, fixes CVE-2015-1283.

Fix TLS stripping vulnerability in smtplib, CVE-2016-0772. Reported by Team Oststrom.

Library

bpo-21386 [https://bugs.python.org/issue21386]: Implement missing IPv4Address.is_global property. It was documented since 07a5610bae9d. Initial patch by Roger Luethi.

bpo-27029 [https://bugs.python.org/issue27029]: Removed deprecated support of universal newlines mode from ZipFile.open().

bpo-27030 [https://bugs.python.org/issue27030]: Unknown escapes consisting of '\' and an ASCII letter in regular expressions now are errors. The re.LOCALE flag now can be used only with bytes patterns.

bpo-27186 [https://bugs.python.org/issue27186]: Add os.PathLike support to DirEntry (part of PEP 519). Initial patch by Jelle Zijlstra.

bpo-20900 [https://bugs.python.org/issue20900]: distutils register command now decodes HTTP responses correctly. Initial patch by ingrid.

bpo-27186 [https://bugs.python.org/issue27186]: Add os.PathLike support to pathlib, removing its provisional status (part of PEP 519). Initial patch by Dusty Phillips.

bpo-27186 [https://bugs.python.org/issue27186]: Add support for os.PathLike objects to os.fsencode() and os.fsdecode() (part of PEP 519).

bpo-27186 [https://bugs.python.org/issue27186]: Introduce os.PathLike and os.fspath() (part of PEP 519).

A new version of typing.py provides several new classes and features: @overload outside stubs, Reversible, DefaultDict, Text, ContextManager, Type[], NewType(), TYPE_CHECKING, and numerous bug fixes (note that some of the new features are not yet implemented in mypy or other static analyzers). Also classes for PEP 492 (Awaitable, AsyncIterable, AsyncIterator) have been added (in fact they made it into 3.5.1 but were never mentioned).

bpo-25738 [https://bugs.python.org/issue25738]: Stop http.server.BaseHTTPRequestHandler.send_error() from sending a message body for 205 Reset Content. Also, don’t send Content header fields in responses that don’t have a body. Patch by Susumu Koshiba.

bpo-21313 [https://bugs.python.org/issue21313]: Fix the « platform » module to tolerate when sys.version contains truncated build information.

Security

bpo-26839 [https://bugs.python.org/issue26839]: On Linux, os.urandom() now calls getrandom() with GRND_NONBLOCK to fall back on reading /dev/urandom if the urandom entropy pool is not initialized yet. Patch written by Colm Buckley.

Library

bpo-23883 [https://bugs.python.org/issue23883]: Added missing APIs to __all__ to match the documented APIs for the following modules: cgi, mailbox, mimetypes, plistlib and smtpd. Patches by Jacek Kołodziej.

bpo-27164 [https://bugs.python.org/issue27164]: In the zlib module, allow decompressing raw Deflate streams with a predefined zdict. Based on patch by Xiang Zhang.

bpo-24291 [https://bugs.python.org/issue24291]: Fix wsgiref.simple_server.WSGIRequestHandler to completely write data to the client. Previously it could do partial writes and truncate data. Also, wsgiref.handler.ServerHandler can now handle stdout doing partial writes, but this is deprecated.

bpo-21272 [https://bugs.python.org/issue21272]: Use _sysconfigdata.py to initialize distutils.sysconfig.

bpo-19611 [https://bugs.python.org/issue19611]: inspect now reports the implicit .0 parameters generated by the compiler for comprehension and generator expression scopes as if they were positional-only parameters called implicit0. Patch by Jelle Zijlstra.

bpo-26809 [https://bugs.python.org/issue26809]: Add __all__ to string. Patch by Emanuel Barry.

bpo-26373 [https://bugs.python.org/issue26373]: subprocess.Popen.communicate now correctly ignores BrokenPipeError when the child process dies before .communicate() is called in more/all circumstances.

signal, socket, and ssl module IntEnum constant name lookups now return a consistent name for values having multiple names. Ex: signal.Signals(6) now refers to itself as signal.SIGALRM rather than flipping between that and signal.SIGIOT based on the interpreter’s hash randomization seed.

bpo-27167 [https://bugs.python.org/issue27167]: Clarify the subprocess.CalledProcessError error message text when the child process died due to a signal.

bpo-25931 [https://bugs.python.org/issue25931]: Don’t define socketserver.Forking* names on platforms such as Windows that do not support os.fork().

bpo-21776 [https://bugs.python.org/issue21776]: distutils.upload now correctly handles HTTPError. Initial patch by Claudiu Popa.

bpo-26526 [https://bugs.python.org/issue26526]: Replace custom parse tree validation in the parser module with a simple DFA validator.

bpo-27114 [https://bugs.python.org/issue27114]: Fix SSLContext._load_windows_store_certs fails with PermissionError

bpo-18383 [https://bugs.python.org/issue18383]: Avoid creating duplicate filters when using filterwarnings and simplefilter. Based on patch by Alex Shkop.

bpo-23026 [https://bugs.python.org/issue23026]: winreg.QueryValueEx() now return an integer for REG_QWORD type.

bpo-26741 [https://bugs.python.org/issue26741]: subprocess.Popen destructor now emits a ResourceWarning warning if the child process is still running.

bpo-27056 [https://bugs.python.org/issue27056]: Optimize pickle.load() and pickle.loads(), up to 10% faster to deserialize a lot of small objects.

bpo-21271 [https://bugs.python.org/issue21271]: New keyword only parameters in reset_mock call.

IDLE

bpo-5124 [https://bugs.python.org/issue5124]: Paste with text selected now replaces the selection on X11. This matches how paste works on Windows, Mac, most modern Linux apps, and ttk widgets. Original patch by Serhiy Storchaka.

bpo-24750 [https://bugs.python.org/issue24750]: Switch all scrollbars in IDLE to ttk versions. Where needed, minimal tests are added to cover changes.

bpo-24759 [https://bugs.python.org/issue24759]: IDLE requires tk 8.5 and availability ttk widgets. Delete now unneeded tk version tests and code for older versions. Add test for IDLE syntax colorizer.

bpo-27239 [https://bugs.python.org/issue27239]: idlelib.macosx.isXyzTk functions initialize as needed.

bpo-27262 [https://bugs.python.org/issue27262]: move Aqua unbinding code, which enable context menus, to macosx.

bpo-24759 [https://bugs.python.org/issue24759]: Make clear in idlelib.idle_test.__init__ that the directory is a private implementation of test.test_idle and tool for maintainers.

bpo-27196 [https://bugs.python.org/issue27196]: Stop “ThemeChanged” warnings when running IDLE tests. These persisted after other warnings were suppressed in #20567. Apply Serhiy Storchaka’s update_idletasks solution to four test files. Record this additional advice in idle_test/README.txt

bpo-20567 [https://bugs.python.org/issue20567]: Revise idle_test/README.txt with advice about avoiding tk warning messages from tests. Apply advice to several IDLE tests.

bpo-24225 [https://bugs.python.org/issue24225]: Update idlelib/README.txt with new file names and event handlers.

bpo-27156 [https://bugs.python.org/issue27156]: Remove obsolete code not used by IDLE.

bpo-27117 [https://bugs.python.org/issue27117]: Make colorizer htest and turtledemo work with dark themes. Move code for configuring text widget colors to a new function.

bpo-24225 [https://bugs.python.org/issue24225]: Rename many idlelib/*.py and idle_test/test_*.py files. Edit files to replace old names with new names when the old name referred to the module rather than the class it contained. See the issue and IDLE section in What’s New in 3.6 for more.

bpo-26673 [https://bugs.python.org/issue26673]: When tk reports font size as 0, change to size 10. Such fonts on Linux prevented the configuration dialog from opening.

bpo-21939 [https://bugs.python.org/issue21939]: Add test for IDLE’s percolator. Original patch by Saimadhav Heblikar.

bpo-21676 [https://bugs.python.org/issue21676]: Add test for IDLE’s replace dialog. Original patch by Saimadhav Heblikar.

bpo-18410 [https://bugs.python.org/issue18410]: Add test for IDLE’s search dialog. Original patch by Westley Martínez.

bpo-21703 [https://bugs.python.org/issue21703]: Add test for undo delegator. Patch mostly by Saimadhav Heblikar .

bpo-27044 [https://bugs.python.org/issue27044]: Add ConfigDialog.remove_var_callbacks to stop memory leaks.

bpo-23977 [https://bugs.python.org/issue23977]: Add more asserts to test_delegator.

Documentation

bpo-16484 [https://bugs.python.org/issue16484]: Change the default PYTHONDOCS URL to « https: », and fix the resulting links to use lowercase. Patch by Sean Rodman, test by Kaushik Nadikuditi.

bpo-24136 [https://bugs.python.org/issue24136]: Document the new PEP 448 unpacking syntax of 3.5.

bpo-22558 [https://bugs.python.org/issue22558]: Add remaining doc links to source code for Python-coded modules. Patch by Yoni Lavi.

Tests

bpo-25285 [https://bugs.python.org/issue25285]: regrtest now uses subprocesses when the -j1 command line option is used: each test file runs in a fresh child process. Before, the -j1 option was ignored.

bpo-25285 [https://bugs.python.org/issue25285]: Tools/buildbot/test.bat script now uses -j1 by default to run each test file in fresh child process.

Windows

bpo-27064 [https://bugs.python.org/issue27064]: The py.exe launcher now defaults to Python 3. The Windows launcher py.exe no longer prefers an installed Python 2 version over Python 3 by default when used interactively.

Build

bpo-27229 [https://bugs.python.org/issue27229]: Fix the cross-compiling pgen rule for in-tree builds. Patch by Xavier de Gaye.

bpo-26930 [https://bugs.python.org/issue26930]: Update OS X 10.5+ 32-bit-only installer to build and link with OpenSSL 1.0.2h.

Windows

bpo-17500 [https://bugs.python.org/issue17500]: Remove unused and outdated icons. (See also: https://github.com/python/pythondotorg/issues/945)

C API

bpo-27186 [https://bugs.python.org/issue27186]: Add the PyOS_FSPath() function (part of PEP 519).

bpo-26282 [https://bugs.python.org/issue26282]: PyArg_ParseTupleAndKeywords() now supports positional-only parameters.

Tools/Demos

bpo-26282 [https://bugs.python.org/issue26282]: Argument Clinic now supports positional-only and keyword parameters in the same function.

Python 3.6.0 alpha 1

Release date: 2016-05-16

Core and Builtins

bpo-20041 [https://bugs.python.org/issue20041]: Fixed TypeError when frame.f_trace is set to None. Patch by Xavier de Gaye.

bpo-26168 [https://bugs.python.org/issue26168]: Fixed possible refleaks in failing Py_BuildValue() with the « N » format unit.

bpo-26991 [https://bugs.python.org/issue26991]: Fix possible refleak when creating a function with annotations.

bpo-27039 [https://bugs.python.org/issue27039]: Fixed bytearray.remove() for values greater than 127. Based on patch by Joe Jevnik.

bpo-23640 [https://bugs.python.org/issue23640]: int.from_bytes() no longer bypasses constructors for subclasses.

bpo-27005 [https://bugs.python.org/issue27005]: Optimized the float.fromhex() class method for exact float. It is now 2 times faster.

bpo-18531 [https://bugs.python.org/issue18531]: Single var-keyword argument of dict subtype was passed unscathed to the C-defined function. Now it is converted to exact dict.

bpo-26811 [https://bugs.python.org/issue26811]: gc.get_objects() no longer contains a broken tuple with NULL pointer.

bpo-20120 [https://bugs.python.org/issue20120]: Use RawConfigParser for .pypirc parsing, removing support for interpolation unintentionally added with move to Python 3. Behavior no longer does any interpolation in .pypirc files, matching behavior in Python 2.7 and Setuptools 19.0.

bpo-26249 [https://bugs.python.org/issue26249]: Memory functions of the PyMem_Malloc() domain (PYMEM_DOMAIN_MEM) now use the pymalloc allocator rather than system malloc(). Applications calling PyMem_Malloc() without holding the GIL can now crash: use PYTHONMALLOC=debug environment variable to validate the usage of memory allocators in your application.

bpo-26802 [https://bugs.python.org/issue26802]: Optimize function calls only using unpacking like func(*tuple) (no other positional argument, no keyword): avoid copying the tuple. Patch written by Joe Jevnik.

bpo-26659 [https://bugs.python.org/issue26659]: Make the builtin slice type support cycle collection.

bpo-26718 [https://bugs.python.org/issue26718]: super.__init__ no longer leaks memory if called multiple times. NOTE: A direct call of super.__init__ is not endorsed!

bpo-27138 [https://bugs.python.org/issue27138]: Fix the doc comment for FileFinder.find_spec().

bpo-27147 [https://bugs.python.org/issue27147]: Mention PEP 420 in the importlib docs.

bpo-25339 [https://bugs.python.org/issue25339]: PYTHONIOENCODING now has priority over locale in setting the error handler for stdin and stdout.

bpo-26494 [https://bugs.python.org/issue26494]: Fixed crash on iterating exhausting iterators. Affected classes are generic sequence iterators, iterators of str, bytes, bytearray, list, tuple, set, frozenset, dict, OrderedDict, corresponding views and os.scandir() iterator.

bpo-26574 [https://bugs.python.org/issue26574]: Optimize bytes.replace(b'', b'.') and bytearray.replace(b'', b'.'). Patch written by Josh Snider.

bpo-26581 [https://bugs.python.org/issue26581]: If coding cookie is specified multiple times on a line in Python source code file, only the first one is taken to account.

bpo-19711 [https://bugs.python.org/issue19711]: Add tests for reloading namespace packages.

bpo-21099 [https://bugs.python.org/issue21099]: Switch applicable importlib tests to use PEP 451 API.

bpo-26563 [https://bugs.python.org/issue26563]: Debug hooks on Python memory allocators now raise a fatal error if functions of the PyMem_Malloc() family are called without holding the GIL.

bpo-26564 [https://bugs.python.org/issue26564]: On error, the debug hooks on Python memory allocators now use the tracemalloc module to get the traceback where a memory block was allocated.

bpo-26558 [https://bugs.python.org/issue26558]: The debug hooks on Python memory allocator PyObject_Malloc() now detect when functions are called without holding the GIL.

bpo-26516 [https://bugs.python.org/issue26516]: Add PYTHONMALLOC environment variable to set the Python memory allocators and/or install debug hooks.

bpo-26516 [https://bugs.python.org/issue26516]: The PyMem_SetupDebugHooks() function can now also be used on Python compiled in release mode.

bpo-26516 [https://bugs.python.org/issue26516]: The PYTHONMALLOCSTATS environment variable can now also be used on Python compiled in release mode. It now has no effect if set to an empty string.

bpo-26516 [https://bugs.python.org/issue26516]: In debug mode, debug hooks are now also installed on Python memory allocators when Python is configured without pymalloc.

bpo-26464 [https://bugs.python.org/issue26464]: Fix str.translate() when string is ASCII and first replacements removes character, but next replacement uses a non-ASCII character or a string longer than 1 character. Regression introduced in Python 3.5.0.

bpo-22836 [https://bugs.python.org/issue22836]: Ensure exception reports from PyErr_Display() and PyErr_WriteUnraisable() are sensible even when formatting them produces secondary errors. This affects the reports produced by sys.__excepthook__() and when __del__() raises an exception.

bpo-26302 [https://bugs.python.org/issue26302]: Correct behavior to reject comma as a legal character for cookie names.

bpo-26136 [https://bugs.python.org/issue26136]: Upgrade the warning when a generator raises StopIteration from PendingDeprecationWarning to DeprecationWarning. Patch by Anish Shah.

bpo-26204 [https://bugs.python.org/issue26204]: The compiler now ignores all constant statements: bytes, str, int, float, complex, name constants (None, False, True), Ellipsis and ast.Constant; not only str and int. For example, 1.0 is now ignored in def f(): 1.0.

bpo-4806 [https://bugs.python.org/issue4806]: Avoid masking the original TypeError exception when using star (*) unpacking in function calls. Based on patch by Hagen Fürstenau and Daniel Urban.

bpo-26146 [https://bugs.python.org/issue26146]: Add a new kind of AST node: ast.Constant. It can be used by external AST optimizers, but the compiler does not emit directly such node.

bpo-23601 [https://bugs.python.org/issue23601]: Sped-up allocation of dict key objects by using Python’s small object allocator. (Contributed by Julian Taylor.)

bpo-18018 [https://bugs.python.org/issue18018]: Import raises ImportError instead of SystemError if a relative import is attempted without a known parent package.

bpo-25843 [https://bugs.python.org/issue25843]: When compiling code, don’t merge constants if they are equal but have a different types. For example, f1, f2 = lambda: 1, lambda: 1.0 is now correctly compiled to two different functions: f1() returns 1 (int) and f2() returns 1.0 (float), even if 1 and 1.0 are equal.

bpo-26107 [https://bugs.python.org/issue26107]: The format of the co_lnotab attribute of code objects changes to support negative line number delta.

bpo-26154 [https://bugs.python.org/issue26154]: Add a new private _PyThreadState_UncheckedGet() function to get the current Python thread state, but don’t issue a fatal error if it is NULL. This new function must be used instead of accessing directly the _PyThreadState_Current variable. The variable is no more exposed since Python 3.5.1 to hide the exact implementation of atomic C types, to avoid compiler issues.

bpo-25791 [https://bugs.python.org/issue25791]: If __package__ != __spec__.parent or if neither __package__ or __spec__ are defined then ImportWarning is raised.

bpo-22995 [https://bugs.python.org/issue22995]: [UPDATE] Comment out the one of the pickleability tests in _PyObject_GetState() due to regressions observed in Cython-based projects.

bpo-25961 [https://bugs.python.org/issue25961]: Disallowed null characters in the type name.

bpo-25973 [https://bugs.python.org/issue25973]: Fix segfault when an invalid nonlocal statement binds a name starting with two underscores.

bpo-22995 [https://bugs.python.org/issue22995]: Instances of extension types with a state that aren’t subclasses of list or dict and haven’t implemented any pickle-related methods (__reduce__, __reduce_ex__, __getnewargs__, __getnewargs_ex__, or __getstate__), can no longer be pickled. Including memoryview.

bpo-20440 [https://bugs.python.org/issue20440]: Massive replacing unsafe attribute setting code with special macro Py_SETREF.

bpo-25766 [https://bugs.python.org/issue25766]: Special method __bytes__() now works in str subclasses.

bpo-25421 [https://bugs.python.org/issue25421]: __sizeof__ methods of builtin types now use dynamic basic size. This allows sys.getsize() to work correctly with their subclasses with __slots__ defined.

bpo-25709 [https://bugs.python.org/issue25709]: Fixed problem with in-place string concatenation and utf-8 cache.

bpo-5319 [https://bugs.python.org/issue5319]: New Py_FinalizeEx() API allowing Python to set an exit status of 120 on failure to flush buffered streams.

bpo-25485 [https://bugs.python.org/issue25485]: telnetlib.Telnet is now a context manager.

bpo-24097 [https://bugs.python.org/issue24097]: Fixed crash in object.__reduce__() if slot name is freed inside __getattr__.

bpo-24731 [https://bugs.python.org/issue24731]: Fixed crash on converting objects with special methods __bytes__, __trunc__, and __float__ returning instances of subclasses of bytes, int, and float to subclasses of bytes, int, and float correspondingly.

bpo-25630 [https://bugs.python.org/issue25630]: Fix a possible segfault during argument parsing in functions that accept filesystem paths.

bpo-23564 [https://bugs.python.org/issue23564]: Fixed a partially broken sanity check in the _posixsubprocess internals regarding how fds_to_pass were passed to the child. The bug had no actual impact as subprocess.py already avoided it.

bpo-25388 [https://bugs.python.org/issue25388]: Fixed tokenizer crash when processing undecodable source code with a null byte.

bpo-25462 [https://bugs.python.org/issue25462]: The hash of the key now is calculated only once in most operations in C implementation of OrderedDict.

bpo-22995 [https://bugs.python.org/issue22995]: Default implementation of __reduce__ and __reduce_ex__ now rejects builtin types with not defined __new__.

bpo-24802 [https://bugs.python.org/issue24802]: Avoid buffer overreads when int(), float(), compile(), exec() and eval() are passed bytes-like objects. These objects are not necessarily terminated by a null byte, but the functions assumed they were.

bpo-25555 [https://bugs.python.org/issue25555]: Fix parser and AST: fill lineno and col_offset of « arg » node when compiling AST from Python objects.

bpo-24726 [https://bugs.python.org/issue24726]: Fixed a crash and leaking NULL in repr() of OrderedDict that was mutated by direct calls of dict methods.

bpo-25449 [https://bugs.python.org/issue25449]: Iterating OrderedDict with keys with unstable hash now raises KeyError in C implementations as well as in Python implementation.

bpo-25395 [https://bugs.python.org/issue25395]: Fixed crash when highly nested OrderedDict structures were garbage collected.

bpo-25401 [https://bugs.python.org/issue25401]: Optimize bytes.fromhex() and bytearray.fromhex(): they are now between 2x and 3.5x faster.

bpo-25399 [https://bugs.python.org/issue25399]: Optimize bytearray % args using the new private _PyBytesWriter API. Formatting is now between 2.5 and 5 times faster.

bpo-25274 [https://bugs.python.org/issue25274]: sys.setrecursionlimit() now raises a RecursionError if the new recursion limit is too low depending at the current recursion depth. Modify also the « lower-water mark » formula to make it monotonic. This mark is used to decide when the overflowed flag of the thread state is reset.

bpo-24402 [https://bugs.python.org/issue24402]: Fix input() to prompt to the redirected stdout when sys.stdout.fileno() fails.

bpo-25349 [https://bugs.python.org/issue25349]: Optimize bytes % args using the new private _PyBytesWriter API. Formatting is now up to 2 times faster.

bpo-24806 [https://bugs.python.org/issue24806]: Prevent builtin types that are not allowed to be subclassed from being subclassed through multiple inheritance.

bpo-25301 [https://bugs.python.org/issue25301]: The UTF-8 decoder is now up to 15 times as fast for error handlers: ignore, replace and surrogateescape.

bpo-24848 [https://bugs.python.org/issue24848]: Fixed a number of bugs in UTF-7 decoding of misformed data.

bpo-25267 [https://bugs.python.org/issue25267]: The UTF-8 encoder is now up to 75 times as fast for error handlers: ignore, replace, surrogateescape, surrogatepass. Patch co-written with Serhiy Storchaka.

bpo-25280 [https://bugs.python.org/issue25280]: Import trace messages emitted in verbose (-v) mode are no longer formatted twice.

bpo-25227 [https://bugs.python.org/issue25227]: Optimize ASCII and latin1 encoders with the surrogateescape error handler: the encoders are now up to 3 times as fast. Initial patch written by Serhiy Storchaka.

bpo-25003 [https://bugs.python.org/issue25003]: On Solaris 11.3 or newer, os.urandom() now uses the getrandom() function instead of the getentropy() function. The getentropy() function is blocking to generate very good quality entropy, os.urandom() doesn’t need such high-quality entropy.

bpo-9232 [https://bugs.python.org/issue9232]: Modify Python’s grammar to allow trailing commas in the argument list of a function declaration. For example, « def f(*, a = 3,): pass » is now legal. Patch from Mark Dickinson.

bpo-24965 [https://bugs.python.org/issue24965]: Implement PEP 498 « Literal String Interpolation ». This allows you to embed expressions inside f-strings, which are converted to normal strings at run time. Given x=3, then f’value={x}” == “value=3”. Patch by Eric V. Smith.

bpo-26478 [https://bugs.python.org/issue26478]: Fix semantic bugs when using binary operators with dictionary views and tuples.

bpo-26171 [https://bugs.python.org/issue26171]: Fix possible integer overflow and heap corruption in zipimporter.get_data().

bpo-25660 [https://bugs.python.org/issue25660]: Fix TAB key behaviour in REPL with readline.

bpo-26288 [https://bugs.python.org/issue26288]: Optimize PyLong_AsDouble.

bpo-26289 [https://bugs.python.org/issue26289]: Optimize floor and modulo division for single-digit longs. Microbenchmarks show 2-2.5x improvement. Built-in “divmod” function is now also ~10% faster. (See also: bpo-26315 [https://bugs.python.org/issue26315])

bpo-25887 [https://bugs.python.org/issue25887]: Raise a RuntimeError when a coroutine object is awaited more than once.

Library

bpo-27057 [https://bugs.python.org/issue27057]: Fix os.set_inheritable() on Android, ioctl() is blocked by SELinux and fails with EACCESS. The function now falls back to fcntl(). Patch written by Michał Bednarski.

bpo-27014 [https://bugs.python.org/issue27014]: Fix infinite recursion using typing.py. Thanks to Kalle Tuure!

bpo-27031 [https://bugs.python.org/issue27031]: Removed dummy methods in Tkinter widget classes: tk_menuBar() and tk_bindForTraversal().

bpo-14132 [https://bugs.python.org/issue14132]: Fix urllib.request redirect handling when the target only has a query string. Original fix by Ján Janech.

bpo-17214 [https://bugs.python.org/issue17214]: The « urllib.request » module now percent-encodes non-ASCII bytes found in redirect target URLs. Some servers send Location header fields with non-ASCII bytes, but « http.client » requires the request target to be ASCII-encodable, otherwise a UnicodeEncodeError is raised. Based on patch by Christian Heimes.

bpo-27033 [https://bugs.python.org/issue27033]: The default value of the decode_data parameter for smtpd.SMTPChannel and smtpd.SMTPServer constructors is changed to False.

bpo-27034 [https://bugs.python.org/issue27034]: Removed deprecated class asynchat.fifo.

bpo-26870 [https://bugs.python.org/issue26870]: Added readline.set_auto_history(), which can stop entries being automatically added to the history list. Based on patch by Tyler Crompton.

bpo-26039 [https://bugs.python.org/issue26039]: zipfile.ZipFile.open() can now be used to write data into a ZIP file, as well as for extracting data. Patch by Thomas Kluyver.

bpo-26892 [https://bugs.python.org/issue26892]: Honor debuglevel flag in urllib.request.HTTPHandler. Patch contributed by Chi Hsuan Yen.

bpo-22274 [https://bugs.python.org/issue22274]: In the subprocess module, allow stderr to be redirected to stdout even when stdout is not redirected. Patch by Akira Li.

bpo-26807 [https://bugs.python.org/issue26807]: mock_open “files” no longer error on readline at end of file. Patch from Yolanda Robla.

bpo-25745 [https://bugs.python.org/issue25745]: Fixed leaking a userptr in curses panel destructor.

bpo-26977 [https://bugs.python.org/issue26977]: Removed unnecessary, and ignored, call to sum of squares helper in statistics.pvariance.

bpo-26002 [https://bugs.python.org/issue26002]: Use bisect in statistics.median instead of a linear search. Patch by Upendra Kuma.

bpo-25974 [https://bugs.python.org/issue25974]: Make use of new Decimal.as_integer_ratio() method in statistics module. Patch by Stefan Krah.

bpo-26996 [https://bugs.python.org/issue26996]: Add secrets module as described in PEP 506.

bpo-26881 [https://bugs.python.org/issue26881]: The modulefinder module now supports extended opcode arguments.

bpo-23815 [https://bugs.python.org/issue23815]: Fixed crashes related to directly created instances of types in _tkinter and curses.panel modules.

bpo-17765 [https://bugs.python.org/issue17765]: weakref.ref() no longer silently ignores keyword arguments. Patch by Georg Brandl.

bpo-26873 [https://bugs.python.org/issue26873]: xmlrpc now raises ResponseError on unsupported type tags instead of silently return incorrect result.

bpo-26915 [https://bugs.python.org/issue26915]: The __contains__ methods in the collections ABCs now check for identity before checking equality. This better matches the behavior of the concrete classes, allows sensible handling of NaNs, and makes it easier to reason about container invariants.

bpo-26711 [https://bugs.python.org/issue26711]: Fixed the comparison of plistlib.Data with other types.

bpo-24114 [https://bugs.python.org/issue24114]: Fix an uninitialized variable in ctypes.util.

The bug only occurs on SunOS when the ctypes implementation searches for the crle program. Patch by Xiang Zhang. Tested on SunOS by Kees Bos.

bpo-26864 [https://bugs.python.org/issue26864]: In urllib.request, change the proxy bypass host checking against no_proxy to be case-insensitive, and to not match unrelated host names that happen to have a bypassed hostname as a suffix. Patch by Xiang Zhang.

bpo-24902 [https://bugs.python.org/issue24902]: Print server URL on http.server startup. Initial patch by Felix Kaiser.

bpo-25788 [https://bugs.python.org/issue25788]: fileinput.hook_encoded() now supports an « errors » argument for passing to open. Original patch by Joseph Hackman.

bpo-26634 [https://bugs.python.org/issue26634]: recursive_repr() now sets __qualname__ of wrapper. Patch by Xiang Zhang.

bpo-26804 [https://bugs.python.org/issue26804]: urllib.request will prefer lower_case proxy environment variables over UPPER_CASE or Mixed_Case ones. Patch contributed by Hans-Peter Jansen.

bpo-26837 [https://bugs.python.org/issue26837]: assertSequenceEqual() now correctly outputs non-stringified differing items (like bytes in the -b mode). This affects assertListEqual() and assertTupleEqual().

bpo-26041 [https://bugs.python.org/issue26041]: Remove « will be removed in Python 3.7 » from deprecation messages of platform.dist() and platform.linux_distribution(). Patch by Kumaripaba Miyurusara Athukorala.

bpo-26822 [https://bugs.python.org/issue26822]: itemgetter, attrgetter and methodcaller objects no longer silently ignore keyword arguments.

bpo-26733 [https://bugs.python.org/issue26733]: Disassembling a class now disassembles class and static methods. Patch by Xiang Zhang.

bpo-26801 [https://bugs.python.org/issue26801]: Fix error handling in shutil.get_terminal_size(), catch AttributeError instead of NameError. Patch written by Emanuel Barry.

bpo-24838 [https://bugs.python.org/issue24838]: tarfile’s ustar and gnu formats now correctly calculate name and link field limits for multibyte character encodings like utf-8.

Security

bpo-26657 [https://bugs.python.org/issue26657]: Fix directory traversal vulnerability with http.server on Windows. This fixes a regression that was introduced in 3.3.4rc1 and 3.4.0rc1. Based on patch by Philipp Hagemeister.

Library

bpo-26717 [https://bugs.python.org/issue26717]: Stop encoding Latin-1-ized WSGI paths with UTF-8. Patch by Anthony Sottile.

bpo-26782 [https://bugs.python.org/issue26782]: Add STARTUPINFO to subprocess.__all__ on Windows.

bpo-26404 [https://bugs.python.org/issue26404]: Add context manager to socketserver. Patch by Aviv Palivoda.

bpo-26735 [https://bugs.python.org/issue26735]: Fix os.urandom() on Solaris 11.3 and newer when reading more than 1,024 bytes: call getrandom() multiple times with a limit of 1024 bytes per call.

bpo-26585 [https://bugs.python.org/issue26585]: Eliminate http.server._quote_html() and use html.escape(quote=False). Patch by Xiang Zhang.

bpo-26685 [https://bugs.python.org/issue26685]: Raise OSError if closing a socket fails.

bpo-16329 [https://bugs.python.org/issue16329]: Add .webm to mimetypes.types_map. Patch by Giampaolo Rodola”.

bpo-13952 [https://bugs.python.org/issue13952]: Add .csv to mimetypes.types_map. Patch by Geoff Wilson.

bpo-26587 [https://bugs.python.org/issue26587]: the site module now allows .pth files to specify files to be added to sys.path (e.g. zip files).

bpo-25609 [https://bugs.python.org/issue25609]: Introduce contextlib.AbstractContextManager and typing.ContextManager.

bpo-26709 [https://bugs.python.org/issue26709]: Fixed Y2038 problem in loading binary PLists.

bpo-23735 [https://bugs.python.org/issue23735]: Handle terminal resizing with Readline 6.3+ by installing our own SIGWINCH handler. Patch by Eric Price.

bpo-25951 [https://bugs.python.org/issue25951]: Change SSLSocket.sendall() to return None, as explicitly documented for plain socket objects. Patch by Aviv Palivoda.

bpo-26586 [https://bugs.python.org/issue26586]: In http.server, respond with « 413 Request header fields too large » if there are too many header fields to parse, rather than killing the connection and raising an unhandled exception. Patch by Xiang Zhang.

bpo-26676 [https://bugs.python.org/issue26676]: Added missing XMLPullParser to ElementTree.__all__.

bpo-22854 [https://bugs.python.org/issue22854]: Change BufferedReader.writable() and BufferedWriter.readable() to always return False.

bpo-26492 [https://bugs.python.org/issue26492]: Exhausted iterator of array.array now conforms with the behavior of iterators of other mutable sequences: it lefts exhausted even if iterated array is extended.

bpo-26641 [https://bugs.python.org/issue26641]: doctest.DocFileTest and doctest.testfile() now support packages (module splitted into multiple directories) for the package parameter.

bpo-25195 [https://bugs.python.org/issue25195]: Fix a regression in mock.MagicMock. _Call is a subclass of tuple (changeset 3603bae63c13 only works for classes) so we need to implement __ne__ ourselves. Patch by Andrew Plummer.

bpo-26644 [https://bugs.python.org/issue26644]: Raise ValueError rather than SystemError when a negative length is passed to SSLSocket.recv() or read().

bpo-23804 [https://bugs.python.org/issue23804]: Fix SSL recv(0) and read(0) methods to return zero bytes instead of up to 1024.

bpo-26616 [https://bugs.python.org/issue26616]: Fixed a bug in datetime.astimezone() method.

bpo-26637 [https://bugs.python.org/issue26637]: The importlib module now emits an ImportError rather than a TypeError if __import__() is tried during the Python shutdown process but sys.path is already cleared (set to None).

bpo-21925 [https://bugs.python.org/issue21925]: warnings.formatwarning() now catches exceptions when calling linecache.getline() and tracemalloc.get_object_traceback() to be able to log ResourceWarning emitted late during the Python shutdown process.

bpo-23848 [https://bugs.python.org/issue23848]: On Windows, faulthandler.enable() now also installs an exception handler to dump the traceback of all Python threads on any Windows exception, not only on UNIX signals (SIGSEGV, SIGFPE, SIGABRT).

bpo-26530 [https://bugs.python.org/issue26530]: Add C functions _PyTraceMalloc_Track() and _PyTraceMalloc_Untrack() to track memory blocks using the tracemalloc module. Add _PyTraceMalloc_GetTraceback() to get the traceback of an object.

bpo-26588 [https://bugs.python.org/issue26588]: The _tracemalloc now supports tracing memory allocations of multiple address spaces (domains).

bpo-24266 [https://bugs.python.org/issue24266]: Ctrl+C during Readline history search now cancels the search mode when compiled with Readline 7.

bpo-26590 [https://bugs.python.org/issue26590]: Implement a safe finalizer for the _socket.socket type. It now releases the GIL to close the socket.

bpo-18787 [https://bugs.python.org/issue18787]: spwd.getspnam() now raises a PermissionError if the user doesn’t have privileges.

bpo-26560 [https://bugs.python.org/issue26560]: Avoid potential ValueError in BaseHandler.start_response. Initial patch by Peter Inglesby.

bpo-26567 [https://bugs.python.org/issue26567]: Add a new function PyErr_ResourceWarning() function to pass the destroyed object. Add a source attribute to warnings.WarningMessage. Add warnings._showwarnmsg() which uses tracemalloc to get the traceback where source object was allocated.

Security

bpo-26313 [https://bugs.python.org/issue26313]: ssl.py _load_windows_store_certs fails if windows cert store is empty. Patch by Baji.

Library

bpo-26569 [https://bugs.python.org/issue26569]: Fix pyclbr.readmodule() and pyclbr.readmodule_ex() to support importing packages.

bpo-26499 [https://bugs.python.org/issue26499]: Account for remaining Content-Length in HTTPResponse.readline() and read1(). Based on patch by Silent Ghost. Also document that HTTPResponse now supports these methods.

bpo-25320 [https://bugs.python.org/issue25320]: Handle sockets in directories unittest discovery is scanning. Patch from Victor van den Elzen.

bpo-16181 [https://bugs.python.org/issue16181]: cookiejar.http2time() now returns None if year is higher than datetime.MAXYEAR.

bpo-26513 [https://bugs.python.org/issue26513]: Fixes platform module detection of Windows Server

bpo-23718 [https://bugs.python.org/issue23718]: Fixed parsing time in week 0 before Jan 1. Original patch by Tamás Bence Gedai.

bpo-26323 [https://bugs.python.org/issue26323]: Add Mock.assert_called() and Mock.assert_called_once() methods to unittest.mock. Patch written by Amit Saha.

bpo-20589 [https://bugs.python.org/issue20589]: Invoking Path.owner() and Path.group() on Windows now raise NotImplementedError instead of ImportError.

bpo-26177 [https://bugs.python.org/issue26177]: Fixed the keys() method for Canvas and Scrollbar widgets.

bpo-15068 [https://bugs.python.org/issue15068]: Got rid of excessive buffering in fileinput. The bufsize parameter is now deprecated and ignored.

bpo-19475 [https://bugs.python.org/issue19475]: Added an optional argument timespec to the datetime isoformat() method to choose the precision of the time component.

bpo-2202 [https://bugs.python.org/issue2202]: Fix UnboundLocalError in AbstractDigestAuthHandler.get_algorithm_impls. Initial patch by Mathieu Dupuy.

bpo-26167 [https://bugs.python.org/issue26167]: Minimized overhead in copy.copy() and copy.deepcopy(). Optimized copying and deepcopying bytearrays, NotImplemented, slices, short lists, tuples, dicts, sets.

bpo-25718 [https://bugs.python.org/issue25718]: Fixed pickling and copying the accumulate() iterator with total is None.

bpo-26475 [https://bugs.python.org/issue26475]: Fixed debugging output for regular expressions with the (?x) flag.

bpo-26482 [https://bugs.python.org/issue26482]: Allowed pickling recursive dequeues.

bpo-26335 [https://bugs.python.org/issue26335]: Make mmap.write() return the number of bytes written like other write methods. Patch by Jakub Stasiak.

bpo-26457 [https://bugs.python.org/issue26457]: Fixed the subnets() methods in IP network classes for the case when resulting prefix length is equal to maximal prefix length. Based on patch by Xiang Zhang.

bpo-26385 [https://bugs.python.org/issue26385]: Remove the file if the internal open() call in NamedTemporaryFile() fails. Patch by Silent Ghost.

bpo-26402 [https://bugs.python.org/issue26402]: Fix XML-RPC client to retry when the server shuts down a persistent connection. This was a regression related to the new http.client.RemoteDisconnected exception in 3.5.0a4.

bpo-25913 [https://bugs.python.org/issue25913]: Leading <~ is optional now in base64.a85decode() with adobe=True. Patch by Swati Jaiswal.

bpo-26186 [https://bugs.python.org/issue26186]: Remove an invalid type check in importlib.util.LazyLoader.

bpo-26367 [https://bugs.python.org/issue26367]: importlib.__import__() raises ImportError like builtins.__import__() when level is specified but without an accompanying package specified.

bpo-26309 [https://bugs.python.org/issue26309]: In the « socketserver » module, shut down the request (closing the connected socket) when verify_request() returns false. Patch by Aviv Palivoda.

bpo-23430 [https://bugs.python.org/issue23430]: Change the socketserver module to only catch exceptions raised from a request handler that are derived from Exception (instead of BaseException). Therefore SystemExit and KeyboardInterrupt no longer trigger the handle_error() method, and will now to stop a single-threaded server.

Security

bpo-25939 [https://bugs.python.org/issue25939]: On Windows open the cert store readonly in ssl.enum_certificates.

Library

bpo-25995 [https://bugs.python.org/issue25995]: os.walk() no longer uses FDs proportional to the tree depth.

bpo-25994 [https://bugs.python.org/issue25994]: Added the close() method and the support of the context manager protocol for the os.scandir() iterator.

bpo-23992 [https://bugs.python.org/issue23992]: multiprocessing: make MapResult not fail-fast upon exception.

bpo-26243 [https://bugs.python.org/issue26243]: Support keyword arguments to zlib.compress(). Patch by Aviv Palivoda.

bpo-26117 [https://bugs.python.org/issue26117]: The os.scandir() iterator now closes file descriptor not only when the iteration is finished, but when it was failed with error.

bpo-25949 [https://bugs.python.org/issue25949]: __dict__ for an OrderedDict instance is now created only when needed.

bpo-25911 [https://bugs.python.org/issue25911]: Restored support of bytes paths in os.walk() on Windows.

bpo-26045 [https://bugs.python.org/issue26045]: Add UTF-8 suggestion to error message when posting a non-Latin-1 string with http.client.

bpo-26039 [https://bugs.python.org/issue26039]: Added zipfile.ZipInfo.from_file() and zipinfo.ZipInfo.is_dir(). Patch by Thomas Kluyver.

bpo-12923 [https://bugs.python.org/issue12923]: Reset FancyURLopener’s redirect counter even if there is an exception. Based on patches by Brian Brazil and Daniel Rocco.

bpo-25945 [https://bugs.python.org/issue25945]: Fixed a crash when unpickle the functools.partial object with wrong state. Fixed a leak in failed functools.partial constructor. « args » and « keywords » attributes of functools.partial have now always types tuple and dict correspondingly.

bpo-26202 [https://bugs.python.org/issue26202]: copy.deepcopy() now correctly copies range() objects with non-atomic attributes.

bpo-23076 [https://bugs.python.org/issue23076]: Path.glob() now raises a ValueError if it’s called with an invalid pattern. Patch by Thomas Nyberg.

bpo-19883 [https://bugs.python.org/issue19883]: Fixed possible integer overflows in zipimport.

bpo-26227 [https://bugs.python.org/issue26227]: On Windows, getnameinfo(), gethostbyaddr() and gethostbyname_ex() functions of the socket module now decode the hostname from the ANSI code page rather than UTF-8.

bpo-26099 [https://bugs.python.org/issue26099]: The site module now writes an error into stderr if sitecustomize module can be imported but executing the module raise an ImportError. Same change for usercustomize.

bpo-26147 [https://bugs.python.org/issue26147]: xmlrpc now works with strings not encodable with used non-UTF-8 encoding.

bpo-25935 [https://bugs.python.org/issue25935]: Garbage collector now breaks reference loops with OrderedDict.

bpo-16620 [https://bugs.python.org/issue16620]: Fixed AttributeError in msilib.Directory.glob().

bpo-26013 [https://bugs.python.org/issue26013]: Added compatibility with broken protocol 2 pickles created in old Python 3 versions (3.4.3 and lower).

bpo-26129 [https://bugs.python.org/issue26129]: Deprecated accepting non-integers in grp.getgrgid().

bpo-25850 [https://bugs.python.org/issue25850]: Use cross-compilation by default for 64-bit Windows.

bpo-25822 [https://bugs.python.org/issue25822]: Add docstrings to the fields of urllib.parse results. Patch contributed by Swati Jaiswal.

bpo-22642 [https://bugs.python.org/issue22642]: Convert trace module option parsing mechanism to argparse. Patch contributed by SilentGhost.

bpo-24705 [https://bugs.python.org/issue24705]: Fix sysconfig._parse_makefile not expanding ${} vars appearing before $() vars.

bpo-26069 [https://bugs.python.org/issue26069]: Remove the deprecated apis in the trace module.

bpo-22138 [https://bugs.python.org/issue22138]: Fix mock.patch behavior when patching descriptors. Restore original values after patching. Patch contributed by Sean McCully.

bpo-25672 [https://bugs.python.org/issue25672]: In the ssl module, enable the SSL_MODE_RELEASE_BUFFERS mode option if it is safe to do so.

bpo-26012 [https://bugs.python.org/issue26012]: Don’t traverse into symlinks for ** pattern in pathlib.Path.[r]glob().

bpo-24120 [https://bugs.python.org/issue24120]: Ignore PermissionError when traversing a tree with pathlib.Path.[r]glob(). Patch by Ulrich Petri.

bpo-21815 [https://bugs.python.org/issue21815]: Accept ] characters in the data portion of imap responses, in order to handle the flags with square brackets accepted and produced by servers such as gmail.

bpo-25447 [https://bugs.python.org/issue25447]: fileinput now uses sys.stdin as-is if it does not have a buffer attribute (restores backward compatibility).

bpo-25971 [https://bugs.python.org/issue25971]: Optimized creating Fractions from floats by 2 times and from Decimals by 3 times.

bpo-25802 [https://bugs.python.org/issue25802]: Document as deprecated the remaining implementations of importlib.abc.Loader.load_module().

bpo-25928 [https://bugs.python.org/issue25928]: Add Decimal.as_integer_ratio().

bpo-25447 [https://bugs.python.org/issue25447]: Copying the lru_cache() wrapper object now always works, independently from the type of the wrapped object (by returning the original object unchanged).

bpo-25768 [https://bugs.python.org/issue25768]: Have the functions in compileall return booleans instead of ints and add proper documentation and tests for the return values.

bpo-24103 [https://bugs.python.org/issue24103]: Fixed possible use after free in ElementTree.XMLPullParser.

bpo-25860 [https://bugs.python.org/issue25860]: os.fwalk() no longer skips remaining directories when error occurs. Original patch by Samson Lee.

bpo-25914 [https://bugs.python.org/issue25914]: Fixed and simplified OrderedDict.__sizeof__.

bpo-25869 [https://bugs.python.org/issue25869]: Optimized deepcopying ElementTree; it is now 20 times faster.

bpo-25873 [https://bugs.python.org/issue25873]: Optimized iterating ElementTree. Iterating elements Element.iter() is now 40% faster, iterating text Element.itertext() is now up to 2.5 times faster.

bpo-25902 [https://bugs.python.org/issue25902]: Fixed various refcount issues in ElementTree iteration.

bpo-22227 [https://bugs.python.org/issue22227]: The TarFile iterator is reimplemented using generator. This implementation is simpler that using class.

bpo-25638 [https://bugs.python.org/issue25638]: Optimized ElementTree.iterparse(); it is now 2x faster. Optimized ElementTree parsing; it is now 10% faster.

bpo-25761 [https://bugs.python.org/issue25761]: Improved detecting errors in broken pickle data.

bpo-25717 [https://bugs.python.org/issue25717]: Restore the previous behaviour of tolerating most fstat() errors when opening files. This was a regression in 3.5a1, and stopped anonymous temporary files from working in special cases.

bpo-24903 [https://bugs.python.org/issue24903]: Fix regression in number of arguments compileall accepts when “-d” is specified. The check on the number of arguments has been dropped completely as it never worked correctly anyway.

bpo-25764 [https://bugs.python.org/issue25764]: In the subprocess module, preserve any exception caused by fork() failure when preexec_fn is used.

bpo-25771 [https://bugs.python.org/issue25771]: Tweak the exception message for importlib.util.resolve_name() when “package” isn’t specified but necessary.

bpo-6478 [https://bugs.python.org/issue6478]: _strptime’s regexp cache now is reset after changing timezone with time.tzset().

bpo-14285 [https://bugs.python.org/issue14285]: When executing a package with the « python -m package » option, and package initialization fails, a proper traceback is now reported. The « runpy » module now lets exceptions from package initialization pass back to the caller, rather than raising ImportError.

bpo-19771 [https://bugs.python.org/issue19771]: Also in runpy and the « -m » option, omit the irrelevant message « … is a package and cannot be directly executed » if the package could not even be initialized (e.g. due to a bad *.pyc file).

bpo-25177 [https://bugs.python.org/issue25177]: Fixed problem with the mean of very small and very large numbers. As a side effect, statistics.mean and statistics.variance should be significantly faster.

bpo-25718 [https://bugs.python.org/issue25718]: Fixed copying object with state with boolean value is false.

bpo-10131 [https://bugs.python.org/issue10131]: Fixed deep copying of minidom documents. Based on patch by Marian Ganisin.

bpo-7990 [https://bugs.python.org/issue7990]: dir() on ElementTree.Element now lists properties: « tag », « text », « tail » and « attrib ». Original patch by Santoso Wijaya.

bpo-25725 [https://bugs.python.org/issue25725]: Fixed a reference leak in pickle.loads() when unpickling invalid data including tuple instructions.

bpo-25663 [https://bugs.python.org/issue25663]: In the Readline completer, avoid listing duplicate global names, and search the global namespace before searching builtins.

bpo-25688 [https://bugs.python.org/issue25688]: Fixed file leak in ElementTree.iterparse() raising an error.

bpo-23914 [https://bugs.python.org/issue23914]: Fixed SystemError raised by unpickler on broken pickle data.

bpo-25691 [https://bugs.python.org/issue25691]: Fixed crash on deleting ElementTree.Element attributes.

bpo-25624 [https://bugs.python.org/issue25624]: ZipFile now always writes a ZIP_STORED header for directory entries. Patch by Dingyuan Wang.

bpo-25626 [https://bugs.python.org/issue25626]: Change three zlib functions to accept sizes that fit in Py_ssize_t, but internally cap those sizes to UINT_MAX. This resolves a regression in 3.5 where GzipFile.read() failed to read chunks larger than 2 or 4 GiB. The change affects the zlib.Decompress.decompress() max_length parameter, the zlib.decompress() bufsize parameter, and the zlib.Decompress.flush() length parameter.

bpo-25583 [https://bugs.python.org/issue25583]: Avoid incorrect errors raised by os.makedirs(exist_ok=True) when the OS gives priority to errors such as EACCES over EEXIST.

bpo-25593 [https://bugs.python.org/issue25593]: Change semantics of EventLoop.stop() in asyncio.

bpo-6973 [https://bugs.python.org/issue6973]: When we know a subprocess.Popen process has died, do not allow the send_signal(), terminate(), or kill() methods to do anything as they could potentially signal a different process.

bpo-23883 [https://bugs.python.org/issue23883]: Added missing APIs to __all__ to match the documented APIs for the following modules: calendar, csv, enum, fileinput, ftplib, logging, optparse, tarfile, threading and wave. Also added a test.support.check__all__() helper. Patches by Jacek Kołodziej, Mauro S. M. Rodrigues and Joel Taddei.

bpo-25590 [https://bugs.python.org/issue25590]: In the Readline completer, only call getattr() once per attribute. Also complete names of attributes such as properties and slots which are listed by dir() but not yet created on an instance.

bpo-25498 [https://bugs.python.org/issue25498]: Fix a crash when garbage-collecting ctypes objects created by wrapping a memoryview. This was a regression made in 3.5a1. Based on patch by Eryksun.

bpo-25584 [https://bugs.python.org/issue25584]: Added « escape » to the __all__ list in the glob module.

bpo-25584 [https://bugs.python.org/issue25584]: Fixed recursive glob() with patterns starting with **.

bpo-25446 [https://bugs.python.org/issue25446]: Fix regression in smtplib’s AUTH LOGIN support.

bpo-18010 [https://bugs.python.org/issue18010]: Fix the pydoc web server’s module search function to handle exceptions from importing packages.

bpo-25554 [https://bugs.python.org/issue25554]: Got rid of circular references in regular expression parsing.

bpo-18973 [https://bugs.python.org/issue18973]: Command-line interface of the calendar module now uses argparse instead of optparse.

bpo-25510 [https://bugs.python.org/issue25510]: fileinput.FileInput.readline() now returns b”” instead of “” at the end if the FileInput was opened with binary mode. Patch by Ryosuke Ito.

bpo-25503 [https://bugs.python.org/issue25503]: Fixed inspect.getdoc() for inherited docstrings of properties. Original patch by John Mark Vandenberg.

bpo-25515 [https://bugs.python.org/issue25515]: Always use os.urandom as a source of randomness in uuid.uuid4.

bpo-21827 [https://bugs.python.org/issue21827]: Fixed textwrap.dedent() for the case when largest common whitespace is a substring of smallest leading whitespace. Based on patch by Robert Li.

bpo-25447 [https://bugs.python.org/issue25447]: The lru_cache() wrapper objects now can be copied and pickled (by returning the original object unchanged).

bpo-25390 [https://bugs.python.org/issue25390]: typing: Don’t crash on Union[str, Pattern].

bpo-25441 [https://bugs.python.org/issue25441]: asyncio: Raise error from drain() when socket is closed.

bpo-25410 [https://bugs.python.org/issue25410]: Cleaned up and fixed minor bugs in C implementation of OrderedDict.

bpo-25411 [https://bugs.python.org/issue25411]: Improved Unicode support in SMTPHandler through better use of the email package. Thanks to user simon04 for the patch.

Move the imp module from a PendingDeprecationWarning to DeprecationWarning.

bpo-25407 [https://bugs.python.org/issue25407]: Remove mentions of the formatter module being removed in Python 3.6.

bpo-25406 [https://bugs.python.org/issue25406]: Fixed a bug in C implementation of OrderedDict.move_to_end() that caused segmentation fault or hang in iterating after moving several items to the start of ordered dict.

bpo-25382 [https://bugs.python.org/issue25382]: pickletools.dis() now outputs implicit memo index for the MEMOIZE opcode.

bpo-25357 [https://bugs.python.org/issue25357]: Add an optional newline parameter to binascii.b2a_base64(). base64.b64encode() uses it to avoid a memory copy.

bpo-24164 [https://bugs.python.org/issue24164]: Objects that need calling __new__ with keyword arguments, can now be pickled using pickle protocols older than protocol version 4.

bpo-25364 [https://bugs.python.org/issue25364]: zipfile now works in threads disabled builds.

bpo-25328 [https://bugs.python.org/issue25328]: smtpd’s SMTPChannel now correctly raises a ValueError if both decode_data and enable_SMTPUTF8 are set to true.

bpo-16099 [https://bugs.python.org/issue16099]: RobotFileParser now supports Crawl-delay and Request-rate extensions. Patch by Nikolay Bogoychev.

bpo-25316 [https://bugs.python.org/issue25316]: distutils raises OSError instead of DistutilsPlatformError when MSVC is not installed.

bpo-25380 [https://bugs.python.org/issue25380]: Fixed protocol for the STACK_GLOBAL opcode in pickletools.opcodes.

bpo-23972 [https://bugs.python.org/issue23972]: Updates asyncio datagram create method allowing reuseport and reuseaddr socket options to be set prior to binding the socket. Mirroring the existing asyncio create_server method the reuseaddr option for datagram sockets defaults to True if the O/S is “posix” (except if the platform is Cygwin). Patch by Chris Laws.

bpo-25304 [https://bugs.python.org/issue25304]: Add asyncio.run_coroutine_threadsafe(). This lets you submit a coroutine to a loop from another thread, returning a concurrent.futures.Future. By Vincent Michel.

bpo-25232 [https://bugs.python.org/issue25232]: Fix CGIRequestHandler to split the query from the URL at the first question mark (?) rather than the last. Patch from Xiang Zhang.

bpo-24657 [https://bugs.python.org/issue24657]: Prevent CGIRequestHandler from collapsing slashes in the query part of the URL as if it were a path. Patch from Xiang Zhang.

bpo-25287 [https://bugs.python.org/issue25287]: Don’t add crypt.METHOD_CRYPT to crypt.methods if it’s not supported. Check if it is supported, it may not be supported on OpenBSD for example.

bpo-23600 [https://bugs.python.org/issue23600]: Default implementation of tzinfo.fromutc() was returning wrong results in some cases.

bpo-25203 [https://bugs.python.org/issue25203]: Failed readline.set_completer_delims() no longer left the module in inconsistent state.

bpo-25011 [https://bugs.python.org/issue25011]: rlcompleter now omits private and special attribute names unless the prefix starts with underscores.

bpo-25209 [https://bugs.python.org/issue25209]: rlcompleter now can add a space or a colon after completed keyword.

bpo-22241 [https://bugs.python.org/issue22241]: timezone.utc name is now plain “UTC”, not “UTC-00:00”.

bpo-23517 [https://bugs.python.org/issue23517]: fromtimestamp() and utcfromtimestamp() methods of datetime.datetime now round microseconds to nearest with ties going to nearest even integer (ROUND_HALF_EVEN), as round(float), instead of rounding towards -Infinity (ROUND_FLOOR).

bpo-23552 [https://bugs.python.org/issue23552]: Timeit now warns when there is substantial (4x) variance between best and worst times. Patch from Serhiy Storchaka.

bpo-24633 [https://bugs.python.org/issue24633]: site-packages/README -> README.txt.

bpo-24879 [https://bugs.python.org/issue24879]: help() and pydoc can now list named tuple fields in the order they were defined rather than alphabetically. The ordering is determined by the _fields attribute if present.

bpo-24874 [https://bugs.python.org/issue24874]: Improve speed of itertools.cycle() and make its pickle more compact.

Fix crash in itertools.cycle.__setstate__() when the first argument wasn’t a list.

bpo-20059 [https://bugs.python.org/issue20059]: urllib.parse raises ValueError on all invalid ports. Patch by Martin Panter.

bpo-24360 [https://bugs.python.org/issue24360]: Improve __repr__ of argparse.Namespace() for invalid identifiers. Patch by Matthias Bussonnier.

bpo-23426 [https://bugs.python.org/issue23426]: run_setup was broken in distutils. Patch from Alexander Belopolsky.

bpo-13938 [https://bugs.python.org/issue13938]: 2to3 converts StringTypes to a tuple. Patch from Mark Hammond.

bpo-2091 [https://bugs.python.org/issue2091]: open() accepted a “U” mode string containing “+”, but “U” can only be used with “r”. Patch from Jeff Balogh and John O’Connor.

bpo-8585 [https://bugs.python.org/issue8585]: improved tests for zipimporter2. Patch from Mark Lawrence.

bpo-18622 [https://bugs.python.org/issue18622]: unittest.mock.mock_open().reset_mock would recurse infinitely. Patch from Nicola Palumbo and Laurent De Buyst.

bpo-24426 [https://bugs.python.org/issue24426]: Fast searching optimization in regular expressions now works for patterns that starts with capturing groups. Fast searching optimization now can’t be disabled at compile time.

bpo-23661 [https://bugs.python.org/issue23661]: unittest.mock side_effects can now be exceptions again. This was a regression vs Python 3.4. Patch from Ignacio Rossi

bpo-13248 [https://bugs.python.org/issue13248]: Remove deprecated inspect.getmoduleinfo function.

bpo-25578 [https://bugs.python.org/issue25578]: Fix (another) memory leak in SSLSocket.getpeercer().

bpo-25530 [https://bugs.python.org/issue25530]: Disable the vulnerable SSLv3 protocol by default when creating ssl.SSLContext.

bpo-25569 [https://bugs.python.org/issue25569]: Fix memory leak in SSLSocket.getpeercert().

bpo-25471 [https://bugs.python.org/issue25471]: Sockets returned from accept() shouldn’t appear to be nonblocking.

bpo-25319 [https://bugs.python.org/issue25319]: When threading.Event is reinitialized, the underlying condition should use a regular lock rather than a recursive lock.

Skip getaddrinfo if host is already resolved. Patch by A. Jesse Jiryu Davis.

bpo-26050 [https://bugs.python.org/issue26050]: Add asyncio.StreamReader.readuntil() method. Patch by Марк Коренберг.

bpo-25924 [https://bugs.python.org/issue25924]: Avoid unnecessary serialization of getaddrinfo(3) calls on OS X versions 10.5 or higher. Original patch by A. Jesse Jiryu Davis.

bpo-26406 [https://bugs.python.org/issue26406]: Avoid unnecessary serialization of getaddrinfo(3) calls on current versions of OpenBSD and NetBSD. Patch by A. Jesse Jiryu Davis.

bpo-26848 [https://bugs.python.org/issue26848]: Fix asyncio/subprocess.communicate() to handle empty input. Patch by Jack O’Connor.

bpo-27040 [https://bugs.python.org/issue27040]: Add loop.get_exception_handler method

bpo-27041 [https://bugs.python.org/issue27041]: asyncio: Add loop.create_future method

IDLE

bpo-20640 [https://bugs.python.org/issue20640]: Add tests for idlelib.configHelpSourceEdit. Patch by Saimadhav Heblikar.

In the “IDLE-console differences” section of the IDLE doc, clarify how running with IDLE affects sys.modules and the standard streams.

bpo-25507 [https://bugs.python.org/issue25507]: fix incorrect change in IOBinding that prevented printing. Augment IOBinding htest to include all major IOBinding functions.

bpo-25905 [https://bugs.python.org/issue25905]: Revert unwanted conversion of “ to ’ RIGHT SINGLE QUOTATION MARK in README.txt and open this and NEWS.txt with “ascii”. Re-encode CREDITS.txt to utf-8 and open it with “utf-8”.

bpo-15348 [https://bugs.python.org/issue15348]: Stop the debugger engine (normally in a user process) before closing the debugger window (running in the IDLE process). This prevents the RuntimeErrors that were being caught and ignored.

bpo-24455 [https://bugs.python.org/issue24455]: Prevent IDLE from hanging when a) closing the shell while the debugger is active (15347); b) closing the debugger with the [X] button (15348); and c) activating the debugger when already active (24455). The patch by Mark Roseman does this by making two changes. 1. Suspend and resume the gui.interaction method with the tcl vwait mechanism intended for this purpose (instead of root.mainloop & .quit). 2. In gui.run, allow any existing interaction to terminate first.

Change “The program” to “Your program” in an IDLE “kill program?” message to make it clearer that the program referred to is the currently running user program, not IDLE itself.

bpo-24750 [https://bugs.python.org/issue24750]: Improve the appearance of the IDLE editor window status bar. Patch by Mark Roseman.

bpo-25313 [https://bugs.python.org/issue25313]: Change the handling of new built-in text color themes to better address the compatibility problem introduced by the addition of IDLE Dark. Consistently use the revised idleConf.CurrentTheme everywhere in idlelib.

bpo-24782 [https://bugs.python.org/issue24782]: Extension configuration is now a tab in the IDLE Preferences dialog rather than a separate dialog. The former tabs are now a sorted list. Patch by Mark Roseman.

bpo-22726 [https://bugs.python.org/issue22726]: Re-activate the config dialog help button with some content about the other buttons and the new IDLE Dark theme.

bpo-24820 [https://bugs.python.org/issue24820]: IDLE now has an “IDLE Dark” built-in text color theme. It is more or less IDLE Classic inverted, with a cobalt blue background. Strings, comments, keywords, … are still green, red, orange, … . To use it with IDLEs released before November 2015, hit the “Save as New Custom Theme” button and enter a new name, such as “Custom Dark”. The custom theme will work with any IDLE release, and can be modified.

bpo-25224 [https://bugs.python.org/issue25224]: README.txt is now an idlelib index for IDLE developers and curious users. The previous user content is now in the IDLE doc chapter. “IDLE” now means “Integrated Development and Learning Environment”.

bpo-24820 [https://bugs.python.org/issue24820]: Users can now set breakpoint colors in Settings -> Custom Highlighting. Original patch by Mark Roseman.

bpo-24972 [https://bugs.python.org/issue24972]: Inactive selection background now matches active selection background, as configured by users, on all systems. Found items are now always highlighted on Windows. Initial patch by Mark Roseman.

bpo-24570 [https://bugs.python.org/issue24570]: Idle: make calltip and completion boxes appear on Macs affected by a tk regression. Initial patch by Mark Roseman.

bpo-24988 [https://bugs.python.org/issue24988]: Idle ScrolledList context menus (used in debugger) now work on Mac Aqua. Patch by Mark Roseman.

bpo-24801 [https://bugs.python.org/issue24801]: Make right-click for context menu work on Mac Aqua. Patch by Mark Roseman.

bpo-25173 [https://bugs.python.org/issue25173]: Associate tkinter messageboxes with a specific widget. For Mac OSX, make them a “sheet”. Patch by Mark Roseman.

bpo-25198 [https://bugs.python.org/issue25198]: Enhance the initial html viewer now used for Idle Help. Properly indent fixed-pitch text (patch by Mark Roseman). Give code snippet a very Sphinx-like light blueish-gray background. Re-use initial width and height set by users for shell and editor. When the Table of Contents (TOC) menu is used, put the section header at the top of the screen.

bpo-25225 [https://bugs.python.org/issue25225]: Condense and rewrite Idle doc section on text colors.

bpo-21995 [https://bugs.python.org/issue21995]: Explain some differences between IDLE and console Python.

bpo-22820 [https://bugs.python.org/issue22820]: Explain need for print when running file from Idle editor.

bpo-25224 [https://bugs.python.org/issue25224]: Doc: augment Idle feature list and no-subprocess section.

bpo-25219 [https://bugs.python.org/issue25219]: Update doc for Idle command line options. Some were missing and notes were not correct.

bpo-24861 [https://bugs.python.org/issue24861]: Most of idlelib is private and subject to change. Use idleib.idle.* to start Idle. See idlelib.__init__.__doc__.

bpo-25199 [https://bugs.python.org/issue25199]: Idle: add synchronization comments for future maintainers.

bpo-16893 [https://bugs.python.org/issue16893]: Replace help.txt with help.html for Idle doc display. The new idlelib/help.html is rstripped Doc/build/html/library/idle.html. It looks better than help.txt and will better document Idle as released. The tkinter html viewer that works for this file was written by Rose Roseman. The now unused EditorWindow.HelpDialog class and helt.txt file are deprecated.

bpo-24199 [https://bugs.python.org/issue24199]: Deprecate unused idlelib.idlever with possible removal in 3.6.

bpo-24790 [https://bugs.python.org/issue24790]: Remove extraneous code (which also create 2 & 3 conflicts).

Documentation

bpo-26736 [https://bugs.python.org/issue26736]: Used HTTPS for external links in the documentation if possible.

bpo-6953 [https://bugs.python.org/issue6953]: Rework the Readline module documentation to group related functions together, and add more details such as what underlying Readline functions and variables are accessed.

bpo-23606 [https://bugs.python.org/issue23606]: Adds note to ctypes documentation regarding cdll.msvcrt.

bpo-24952 [https://bugs.python.org/issue24952]: Clarify the default size argument of stack_size() in the « threading » and « _thread » modules. Patch from Mattip.

bpo-26014 [https://bugs.python.org/issue26014]: Update 3.x packaging documentation: * « See also » links to the new docs are now provided in the legacy pages * links to setuptools documentation have been updated

Tests

bpo-21916 [https://bugs.python.org/issue21916]: Added tests for the turtle module. Patch by ingrid, Gregory Loyse and Jelle Zijlstra.

bpo-26295 [https://bugs.python.org/issue26295]: When using « python3 -m test –testdir=TESTDIR », regrtest doesn’t add « test. » prefix to test module names.

bpo-26523 [https://bugs.python.org/issue26523]: The multiprocessing thread pool (multiprocessing.dummy.Pool) was untested.

bpo-26015 [https://bugs.python.org/issue26015]: Added new tests for pickling iterators of mutable sequences.

bpo-26325 [https://bugs.python.org/issue26325]: Added test.support.check_no_resource_warning() to check that no ResourceWarning is emitted.

bpo-25940 [https://bugs.python.org/issue25940]: Changed test_ssl to use its internal local server more. This avoids relying on svn.python.org, which recently changed root certificate.

bpo-25616 [https://bugs.python.org/issue25616]: Tests for OrderedDict are extracted from test_collections into separate file test_ordered_dict.

bpo-25449 [https://bugs.python.org/issue25449]: Added tests for OrderedDict subclasses.

bpo-25188 [https://bugs.python.org/issue25188]: Add -P/–pgo to test.regrtest to suppress error output when running the test suite for the purposes of a PGO build. Initial patch by Alecsandru Patrascu.

bpo-22806 [https://bugs.python.org/issue22806]: Add python -m test --list-tests command to list tests.

bpo-18174 [https://bugs.python.org/issue18174]: python -m test --huntrleaks ... now also checks for leak of file descriptors. Patch written by Richard Oudkerk.

bpo-25260 [https://bugs.python.org/issue25260]: Fix python -m test --coverage on Windows. Remove the list of ignored directories.

PCbuild\rt.bat now accepts an unlimited number of arguments to pass along to regrtest.py. Previously there was a limit of 9.

bpo-26583 [https://bugs.python.org/issue26583]: Skip test_timestamp_overflow in test_import if bytecode files cannot be written.

Build

bpo-21277 [https://bugs.python.org/issue21277]: Don’t try to link _ctypes with a ffi_convenience library.

bpo-26884 [https://bugs.python.org/issue26884]: Fix linking extension modules for cross builds. Patch by Xavier de Gaye.

bpo-26932 [https://bugs.python.org/issue26932]: Fixed support of RTLD_* constants defined as enum values, not via macros (in particular on Android). Patch by Chi Hsuan Yen.

bpo-22359 [https://bugs.python.org/issue22359]: Disable the rules for running _freeze_importlib and pgen when cross-compiling. The output of these programs is normally saved with the source code anyway, and is still regenerated when doing a native build. Patch by Xavier de Gaye.

bpo-21668 [https://bugs.python.org/issue21668]: Link audioop, _datetime, _ctypes_test modules to libm, except on Mac OS X. Patch written by Chi Hsuan Yen.

bpo-25702 [https://bugs.python.org/issue25702]: A –with-lto configure option has been added that will enable link time optimizations at build time during a make profile-opt. Some compilers and toolchains are known to not produce stable code when using LTO, be sure to test things thoroughly before relying on it. It can provide a few % speed up over profile-opt alone.

bpo-26624 [https://bugs.python.org/issue26624]: Adds validation of ucrtbase[d].dll version with warning for old versions.

bpo-17603 [https://bugs.python.org/issue17603]: Avoid error about nonexistant fileblocks.o file by using a lower-level check for st_blocks in struct stat.

bpo-26079 [https://bugs.python.org/issue26079]: Fixing the build output folder for tix-8.4.3.6. Patch by Bjoern Thiel.

bpo-26465 [https://bugs.python.org/issue26465]: Update Windows builds to use OpenSSL 1.0.2g.

bpo-25348 [https://bugs.python.org/issue25348]: Added --pgo and --pgo-job arguments to PCbuild\build.bat for building with Profile-Guided Optimization. The old PCbuild\build_pgo.bat script is removed.

bpo-25827 [https://bugs.python.org/issue25827]: Add support for building with ICC to configure, including a new --with-icc flag.

bpo-25696 [https://bugs.python.org/issue25696]: Fix installation of Python on UNIX with make -j9.

bpo-24986 [https://bugs.python.org/issue24986]: It is now possible to build Python on Windows without errors when external libraries are not available.

bpo-24421 [https://bugs.python.org/issue24421]: Compile Modules/_math.c once, before building extensions. Previously it could fail to compile properly if the math and cmath builds were concurrent.

bpo-26465 [https://bugs.python.org/issue26465]: Update OS X 10.5+ 32-bit-only installer to build and link with OpenSSL 1.0.2g.

bpo-26268 [https://bugs.python.org/issue26268]: Update Windows builds to use OpenSSL 1.0.2f.

bpo-25136 [https://bugs.python.org/issue25136]: Support Apple Xcode 7’s new textual SDK stub libraries.

bpo-24324 [https://bugs.python.org/issue24324]: Do not enable unreachable code warnings when using gcc as the option does not work correctly in older versions of gcc and has been silently removed as of gcc-4.5.

Windows

bpo-27053 [https://bugs.python.org/issue27053]: Updates make_zip.py to correctly generate library ZIP file.

bpo-26268 [https://bugs.python.org/issue26268]: Update the prepare_ssl.py script to handle OpenSSL releases that don’t include the contents of the include directory (that is, 1.0.2e and later).

bpo-26071 [https://bugs.python.org/issue26071]: bdist_wininst created binaries fail to start and find 32bit Python

bpo-26073 [https://bugs.python.org/issue26073]: Update the list of magic numbers in launcher

bpo-26065 [https://bugs.python.org/issue26065]: Excludes venv from library when generating embeddable distro.

bpo-25022 [https://bugs.python.org/issue25022]: Removed very outdated PC/example_nt/ directory.

Tools/Demos

bpo-26799 [https://bugs.python.org/issue26799]: Fix python-gdb.py: don’t get C types once when the Python code is loaded, but get C types on demand. The C types can change if python-gdb.py is loaded before the Python executable. Patch written by Thomas Ilsche.

bpo-26271 [https://bugs.python.org/issue26271]: Fix the Freeze tool to properly use flags passed through configure. Patch by Daniel Shaulov.

bpo-26489 [https://bugs.python.org/issue26489]: Add dictionary unpacking support to Tools/parser/unparse.py. Patch by Guo Ci Teo.

bpo-26316 [https://bugs.python.org/issue26316]: Fix variable name typo in Argument Clinic.

bpo-25440 [https://bugs.python.org/issue25440]: Fix output of python-config –extension-suffix.

bpo-25154 [https://bugs.python.org/issue25154]: The pyvenv script has been deprecated in favour of python3 -m venv.

C API

bpo-26312 [https://bugs.python.org/issue26312]: SystemError is now raised in all programming bugs with using PyArg_ParseTupleAndKeywords(). RuntimeError did raised before in some programming bugs.

bpo-26198 [https://bugs.python.org/issue26198]: ValueError is now raised instead of TypeError on buffer overflow in parsing « es# » and « et# » format units. SystemError is now raised instead of TypeError on programmatical error in parsing format string.

Python 3.5.3 final

Release date: 2017-01-17

There were no code changes between 3.5.3rc1 and 3.5.3 final.

Python 3.5.3 release candidate 1

Release date: 2017-01-02

Core and Builtins

bpo-29073 [https://bugs.python.org/issue29073]: bytearray formatting no longer truncates on first null byte.

bpo-28932 [https://bugs.python.org/issue28932]: Do not include <sys/random.h> if it does not exist.

bpo-28147 [https://bugs.python.org/issue28147]: Fix a memory leak in split-table dictionaries: setattr() must not convert combined table into split table.

bpo-25677 [https://bugs.python.org/issue25677]: Correct the positioning of the syntax error caret for indented blocks. Based on patch by Michael Layzell.

bpo-29000 [https://bugs.python.org/issue29000]: Fixed bytes formatting of octals with zero padding in alternate form.

bpo-28512 [https://bugs.python.org/issue28512]: Fixed setting the offset attribute of SyntaxError by PyErr_SyntaxLocationEx() and PyErr_SyntaxLocationObject().

bpo-28991 [https://bugs.python.org/issue28991]: functools.lru_cache() was susceptible to an obscure reentrancy bug caused by a monkey-patched len() function.

bpo-28648 [https://bugs.python.org/issue28648]: Fixed crash in Py_DecodeLocale() in debug build on Mac OS X when decode astral characters. Patch by Xiang Zhang.

bpo-19398 [https://bugs.python.org/issue19398]: Extra slash no longer added to sys.path components in case of empty compile-time PYTHONPATH components.

bpo-28426 [https://bugs.python.org/issue28426]: Fixed potential crash in PyUnicode_AsDecodedObject() in debug build.

bpo-23782 [https://bugs.python.org/issue23782]: Fixed possible memory leak in _PyTraceback_Add() and exception loss in PyTraceBack_Here().

bpo-28379 [https://bugs.python.org/issue28379]: Added sanity checks and tests for PyUnicode_CopyCharacters(). Patch by Xiang Zhang.

bpo-28376 [https://bugs.python.org/issue28376]: The type of long range iterator is now registered as Iterator. Patch by Oren Milman.

bpo-28376 [https://bugs.python.org/issue28376]: The constructor of range_iterator now checks that step is not 0. Patch by Oren Milman.

bpo-26906 [https://bugs.python.org/issue26906]: Resolving special methods of uninitialized type now causes implicit initialization of the type instead of a fail.

bpo-18287 [https://bugs.python.org/issue18287]: PyType_Ready() now checks that tp_name is not NULL. Original patch by Niklas Koep.

bpo-24098 [https://bugs.python.org/issue24098]: Fixed possible crash when AST is changed in process of compiling it.

bpo-28350 [https://bugs.python.org/issue28350]: String constants with null character no longer interned.

bpo-26617 [https://bugs.python.org/issue26617]: Fix crash when GC runs during weakref callbacks.

bpo-27942 [https://bugs.python.org/issue27942]: String constants now interned recursively in tuples and frozensets.

bpo-21578 [https://bugs.python.org/issue21578]: Fixed misleading error message when ImportError called with invalid keyword args.

bpo-28203 [https://bugs.python.org/issue28203]: Fix incorrect type in error message from complex(1.0, {2:3}). Patch by Soumya Sharma.

bpo-27955 [https://bugs.python.org/issue27955]: Fallback on reading /dev/urandom device when the getrandom() syscall fails with EPERM, for example when blocked by SECCOMP.

bpo-28131 [https://bugs.python.org/issue28131]: Fix a regression in zipimport’s compile_source(). zipimport should use the same optimization level as the interpreter.

bpo-25221 [https://bugs.python.org/issue25221]: Fix corrupted result from PyLong_FromLong(0) when Python is compiled with NSMALLPOSINTS = 0.

bpo-25758 [https://bugs.python.org/issue25758]: Prevents zipimport from unnecessarily encoding a filename (patch by Eryk Sun)

bpo-28189 [https://bugs.python.org/issue28189]: dictitems_contains no longer swallows compare errors. (Patch by Xiang Zhang)

bpo-27812 [https://bugs.python.org/issue27812]: Properly clear out a generator’s frame’s backreference to the generator to prevent crashes in frame.clear().

bpo-27811 [https://bugs.python.org/issue27811]: Fix a crash when a coroutine that has not been awaited is finalized with warnings-as-errors enabled.

bpo-27587 [https://bugs.python.org/issue27587]: Fix another issue found by PVS-Studio: Null pointer check after use of “def” in _PyState_AddModule(). Initial patch by Christian Heimes.

bpo-26020 [https://bugs.python.org/issue26020]: set literal evaluation order did not match documented behaviour.

bpo-27782 [https://bugs.python.org/issue27782]: Multi-phase extension module import now correctly allows the m_methods field to be used to add module level functions to instances of non-module types returned from Py_create_mod. Patch by Xiang Zhang.

bpo-27936 [https://bugs.python.org/issue27936]: The round() function accepted a second None argument for some types but not for others. Fixed the inconsistency by accepting None for all numeric types.

bpo-27487 [https://bugs.python.org/issue27487]: Warn if a submodule argument to « python -m » or runpy.run_module() is found in sys.modules after parent packages are imported, but before the submodule is executed.

bpo-27558 [https://bugs.python.org/issue27558]: Fix a SystemError in the implementation of « raise » statement. In a brand new thread, raise a RuntimeError since there is no active exception to reraise. Patch written by Xiang Zhang.

bpo-27419 [https://bugs.python.org/issue27419]: Standard __import__() no longer look up « __import__ » in globals or builtins for importing submodules or « from import ». Fixed handling an error of non-string package name.

bpo-27083 [https://bugs.python.org/issue27083]: Respect the PYTHONCASEOK environment variable under Windows.

bpo-27514 [https://bugs.python.org/issue27514]: Make having too many statically nested blocks a SyntaxError instead of SystemError.

bpo-27473 [https://bugs.python.org/issue27473]: Fixed possible integer overflow in bytes and bytearray concatenations. Patch by Xiang Zhang.

bpo-27507 [https://bugs.python.org/issue27507]: Add integer overflow check in bytearray.extend(). Patch by Xiang Zhang.

bpo-27581 [https://bugs.python.org/issue27581]: Don’t rely on wrapping for overflow check in PySequence_Tuple(). Patch by Xiang Zhang.

bpo-27443 [https://bugs.python.org/issue27443]: __length_hint__() of bytearray iterators no longer return a negative integer for a resized bytearray.

bpo-27942 [https://bugs.python.org/issue27942]: Fix memory leak in codeobject.c

Library

bpo-15812 [https://bugs.python.org/issue15812]: inspect.getframeinfo() now correctly shows the first line of a context. Patch by Sam Breese.

bpo-29094 [https://bugs.python.org/issue29094]: Offsets in a ZIP file created with extern file object and modes « w » and « x » now are relative to the start of the file.

bpo-13051 [https://bugs.python.org/issue13051]: Fixed recursion errors in large or resized curses.textpad.Textbox. Based on patch by Tycho Andersen.

bpo-29119 [https://bugs.python.org/issue29119]: Fix weakrefs in the pure python version of collections.OrderedDict move_to_end() method. Contributed by Andra Bogildea.

bpo-9770 [https://bugs.python.org/issue9770]: curses.ascii predicates now work correctly with negative integers.

bpo-28427 [https://bugs.python.org/issue28427]: old keys should not remove new values from WeakValueDictionary when collecting from another thread.

bpo-28923 [https://bugs.python.org/issue28923]: Remove editor artifacts from Tix.py.

bpo-28871 [https://bugs.python.org/issue28871]: Fixed a crash when deallocate deep ElementTree.

bpo-19542 [https://bugs.python.org/issue19542]: Fix bugs in WeakValueDictionary.setdefault() and WeakValueDictionary.pop() when a GC collection happens in another thread.

bpo-20191 [https://bugs.python.org/issue20191]: Fixed a crash in resource.prlimit() when pass a sequence that doesn’t own its elements as limits.

bpo-28779 [https://bugs.python.org/issue28779]: multiprocessing.set_forkserver_preload() would crash the forkserver process if a preloaded module instantiated some multiprocessing objects such as locks.

bpo-28847 [https://bugs.python.org/issue28847]: dbm.dumb now supports reading read-only files and no longer writes the index file when it is not changed.

bpo-25659 [https://bugs.python.org/issue25659]: In ctypes, prevent a crash calling the from_buffer() and from_buffer_copy() methods on abstract classes like Array.

bpo-28732 [https://bugs.python.org/issue28732]: Fix crash in os.spawnv() with no elements in args

bpo-28485 [https://bugs.python.org/issue28485]: Always raise ValueError for negative compileall.compile_dir(workers=…) parameter, even when multithreading is unavailable.

bpo-28387 [https://bugs.python.org/issue28387]: Fixed possible crash in _io.TextIOWrapper deallocator when the garbage collector is invoked in other thread. Based on patch by Sebastian Cufre.

bpo-27517 [https://bugs.python.org/issue27517]: LZMA compressor and decompressor no longer raise exceptions if given empty data twice. Patch by Benjamin Fogle.

bpo-28549 [https://bugs.python.org/issue28549]: Fixed segfault in curses’s addch() with ncurses6.

bpo-28449 [https://bugs.python.org/issue28449]: tarfile.open() with mode « r » or « r: » now tries to open a tar file with compression before trying to open it without compression. Otherwise it had 50% chance failed with ignore_zeros=True.

bpo-23262 [https://bugs.python.org/issue23262]: The webbrowser module now supports Firefox 36+ and derived browsers. Based on patch by Oleg Broytman.

bpo-27939 [https://bugs.python.org/issue27939]: Fixed bugs in tkinter.ttk.LabeledScale and tkinter.Scale caused by representing the scale as float value internally in Tk. tkinter.IntVar now works if float value is set to underlying Tk variable.

bpo-28255 [https://bugs.python.org/issue28255]: calendar.TextCalendar().prmonth() no longer prints a space at the start of new line after printing a month’s calendar. Patch by Xiang Zhang.

bpo-20491 [https://bugs.python.org/issue20491]: The textwrap.TextWrapper class now honors non-breaking spaces. Based on patch by Kaarle Ritvanen.

bpo-28353 [https://bugs.python.org/issue28353]: os.fwalk() no longer fails on broken links.

bpo-25464 [https://bugs.python.org/issue25464]: Fixed HList.header_exists() in tkinter.tix module by addin a workaround to Tix library bug.

bpo-28488 [https://bugs.python.org/issue28488]: shutil.make_archive() no longer add entry « ./ » to ZIP archive.

bpo-24452 [https://bugs.python.org/issue24452]: Make webbrowser support Chrome on Mac OS X.

bpo-20766 [https://bugs.python.org/issue20766]: Fix references leaked by pdb in the handling of SIGINT handlers.

bpo-26293 [https://bugs.python.org/issue26293]: Fixed writing ZIP files that starts not from the start of the file. Offsets in ZIP file now are relative to the start of the archive in conforming to the specification.

bpo-28321 [https://bugs.python.org/issue28321]: Fixed writing non-BMP characters with binary format in plistlib.

bpo-28322 [https://bugs.python.org/issue28322]: Fixed possible crashes when unpickle itertools objects from incorrect pickle data. Based on patch by John Leitch.

Fix possible integer overflows and crashes in the mmap module with unusual usage patterns.

bpo-1703178 [https://bugs.python.org/issue1703178]: Fix the ability to pass the –link-objects option to the distutils build_ext command.

bpo-28253 [https://bugs.python.org/issue28253]: Fixed calendar functions for extreme months: 0001-01 and 9999-12.

Methods itermonthdays() and itermonthdays2() are reimplemented so that they don’t call itermonthdates() which can cause datetime.date under/overflow.

bpo-28275 [https://bugs.python.org/issue28275]: Fixed possible use after free in the decompress() methods of the LZMADecompressor and BZ2Decompressor classes. Original patch by John Leitch.

bpo-27897 [https://bugs.python.org/issue27897]: Fixed possible crash in sqlite3.Connection.create_collation() if pass invalid string-like object as a name. Patch by Xiang Zhang.

bpo-18893 [https://bugs.python.org/issue18893]: Fix invalid exception handling in Lib/ctypes/macholib/dyld.py. Patch by Madison May.

bpo-27611 [https://bugs.python.org/issue27611]: Fixed support of default root window in the tkinter.tix module.

bpo-27348 [https://bugs.python.org/issue27348]: In the traceback module, restore the formatting of exception messages like « Exception: None ». This fixes a regression introduced in 3.5a2.

bpo-25651 [https://bugs.python.org/issue25651]: Allow falsy values to be used for msg parameter of subTest().

bpo-27932 [https://bugs.python.org/issue27932]: Prevent memory leak in win32_ver().

Fix UnboundLocalError in socket._sendfile_use_sendfile.

bpo-28075 [https://bugs.python.org/issue28075]: Check for ERROR_ACCESS_DENIED in Windows implementation of os.stat(). Patch by Eryk Sun.

bpo-25270 [https://bugs.python.org/issue25270]: Prevent codecs.escape_encode() from raising SystemError when an empty bytestring is passed.

bpo-28181 [https://bugs.python.org/issue28181]: Get antigravity over HTTPS. Patch by Kaartic Sivaraam.

bpo-25895 [https://bugs.python.org/issue25895]: Enable WebSocket URL schemes in urllib.parse.urljoin. Patch by Gergely Imreh and Markus Holtermann.

bpo-27599 [https://bugs.python.org/issue27599]: Fixed buffer overrun in binascii.b2a_qp() and binascii.a2b_qp().

bpo-19003 [https://bugs.python.org/issue19003]: m email.generator now replaces only \r and/or \n line endings, per the RFC, instead of all unicode line endings.

bpo-28019 [https://bugs.python.org/issue28019]: itertools.count() no longer rounds non-integer step in range between 1.0 and 2.0 to 1.

bpo-25969 [https://bugs.python.org/issue25969]: Update the lib2to3 grammar to handle the unpacking generalizations added in 3.5.

bpo-14977 [https://bugs.python.org/issue14977]: mailcap now respects the order of the lines in the mailcap files (« first match »), as required by RFC 1542. Patch by Michael Lazar.

bpo-24594 [https://bugs.python.org/issue24594]: Validates persist parameter when opening MSI database

bpo-17582 [https://bugs.python.org/issue17582]: xml.etree.ElementTree nows preserves whitespaces in attributes (Patch by Duane Griffin. Reviewed and approved by Stefan Behnel.)

bpo-28047 [https://bugs.python.org/issue28047]: Fixed calculation of line length used for the base64 CTE in the new email policies.

bpo-27445 [https://bugs.python.org/issue27445]: Don’t pass str(_charset) to MIMEText.set_payload(). Patch by Claude Paroz.

bpo-22450 [https://bugs.python.org/issue22450]: urllib now includes an Accept: */* header among the default headers. This makes the results of REST API requests more consistent and predictable especially when proxy servers are involved.

lib2to3.pgen3.driver.load_grammar() now creates a stable cache file between runs given the same Grammar.txt input regardless of the hash randomization setting.

bpo-27570 [https://bugs.python.org/issue27570]: Avoid zero-length memcpy() etc calls with null source pointers in the « ctypes » and « array » modules.

bpo-22233 [https://bugs.python.org/issue22233]: Break email header lines only on the RFC specified CR and LF characters, not on arbitrary unicode line breaks. This also fixes a bug in HTTP header parsing.

bpo-27988 [https://bugs.python.org/issue27988]: Fix email iter_attachments incorrect mutation of payload list.

bpo-27691 [https://bugs.python.org/issue27691]: Fix ssl module’s parsing of GEN_RID subject alternative name fields in X.509 certs.

bpo-27850 [https://bugs.python.org/issue27850]: Remove 3DES from ssl module’s default cipher list to counter measure sweet32 attack (CVE-2016-2183).

bpo-27766 [https://bugs.python.org/issue27766]: Add ChaCha20 Poly1305 to ssl module’s default cipher list. (Required OpenSSL 1.1.0 or LibreSSL).

bpo-26470 [https://bugs.python.org/issue26470]: Port ssl and hashlib module to OpenSSL 1.1.0.

Remove support for passing a file descriptor to os.access. It never worked but previously didn’t raise.

bpo-12885 [https://bugs.python.org/issue12885]: Fix error when distutils encounters symlink.

bpo-27881 [https://bugs.python.org/issue27881]: Fixed possible bugs when setting sqlite3.Connection.isolation_level. Based on patch by Xiang Zhang.

bpo-27861 [https://bugs.python.org/issue27861]: Fixed a crash in sqlite3.Connection.cursor() when a factory creates not a cursor. Patch by Xiang Zhang.

bpo-19884 [https://bugs.python.org/issue19884]: Avoid spurious output on OS X with Gnu Readline.

bpo-27706 [https://bugs.python.org/issue27706]: Restore deterministic behavior of random.Random().seed() for string seeds using seeding version 1. Allows sequences of calls to random() to exactly match those obtained in Python 2. Patch by Nofar Schnider.

bpo-10513 [https://bugs.python.org/issue10513]: Fix a regression in Connection.commit(). Statements should not be reset after a commit.

A new version of typing.py from https://github.com/python/typing: Collection (only for 3.6) (bpo-27598 [https://bugs.python.org/issue27598]). Add FrozenSet to __all__ (upstream #261). Fix crash in _get_type_vars() (upstream #259). Remove the dict constraint in ForwardRef._eval_type (upstream #252).

bpo-27539 [https://bugs.python.org/issue27539]: Fix unnormalised Fraction.__pow__ result in the case of negative exponent and negative base.

bpo-21718 [https://bugs.python.org/issue21718]: cursor.description is now available for queries using CTEs.

bpo-2466 [https://bugs.python.org/issue2466]: posixpath.ismount now correctly recognizes mount points which the user does not have permission to access.

bpo-27773 [https://bugs.python.org/issue27773]: Correct some memory management errors server_hostname in _ssl.wrap_socket().

bpo-26750 [https://bugs.python.org/issue26750]: unittest.mock.create_autospec() now works properly for subclasses of property() and other data descriptors.

In the curses module, raise an error if window.getstr() or window.instr() is passed a negative value.

bpo-27783 [https://bugs.python.org/issue27783]: Fix possible usage of uninitialized memory in operator.methodcaller.

bpo-27774 [https://bugs.python.org/issue27774]: Fix possible Py_DECREF on unowned object in _sre.

bpo-27760 [https://bugs.python.org/issue27760]: Fix possible integer overflow in binascii.b2a_qp.

bpo-27758 [https://bugs.python.org/issue27758]: Fix possible integer overflow in the _csv module for large record lengths.

bpo-27568 [https://bugs.python.org/issue27568]: Prevent HTTPoxy attack (CVE-2016-1000110). Ignore the HTTP_PROXY variable when REQUEST_METHOD environment is set, which indicates that the script is in CGI mode.

bpo-27656 [https://bugs.python.org/issue27656]: Do not assume sched.h defines any SCHED_* constants.

bpo-27130 [https://bugs.python.org/issue27130]: In the « zlib » module, fix handling of large buffers (typically 4 GiB) when compressing and decompressing. Previously, inputs were limited to 4 GiB, and compression and decompression operations did not properly handle results of 4 GiB.

bpo-27533 [https://bugs.python.org/issue27533]: Release GIL in nt._isdir

bpo-17711 [https://bugs.python.org/issue17711]: Fixed unpickling by the persistent ID with protocol 0. Original patch by Alexandre Vassalotti.

bpo-27522 [https://bugs.python.org/issue27522]: Avoid an unintentional reference cycle in email.feedparser.

bpo-26844 [https://bugs.python.org/issue26844]: Fix error message for imp.find_module() to refer to “path” instead of “name”. Patch by Lev Maximov.

bpo-23804 [https://bugs.python.org/issue23804]: Fix SSL zero-length recv() calls to not block and not raise an error about unclean EOF.

bpo-27466 [https://bugs.python.org/issue27466]: Change time format returned by http.cookie.time2netscape, confirming the netscape cookie format and making it consistent with documentation.

bpo-26664 [https://bugs.python.org/issue26664]: Fix activate.fish by removing mis-use of $.

bpo-22115 [https://bugs.python.org/issue22115]: Fixed tracing Tkinter variables: trace_vdelete() with wrong mode no longer break tracing, trace_vinfo() now always returns a list of pairs of strings, tracing in the « u » mode now works.

Fix a scoping issue in importlib.util.LazyLoader which triggered an UnboundLocalError when lazy-loading a module that was already put into sys.modules.

bpo-27079 [https://bugs.python.org/issue27079]: Fixed curses.ascii functions isblank(), iscntrl() and ispunct().

bpo-26754 [https://bugs.python.org/issue26754]: Some functions (compile() etc) accepted a filename argument encoded as an iterable of integers. Now only strings and byte-like objects are accepted.

bpo-27048 [https://bugs.python.org/issue27048]: Prevents distutils failing on Windows when environment variables contain non-ASCII characters

bpo-27330 [https://bugs.python.org/issue27330]: Fixed possible leaks in the ctypes module.

bpo-27238 [https://bugs.python.org/issue27238]: Got rid of bare excepts in the turtle module. Original patch by Jelle Zijlstra.

bpo-27122 [https://bugs.python.org/issue27122]: When an exception is raised within the context being managed by a contextlib.ExitStack() and one of the exit stack generators catches and raises it in a chain, do not re-raise the original exception when exiting, let the new chained one through. This avoids the PEP 479 bug described in issue25782.

Security

bpo-27278 [https://bugs.python.org/issue27278]: Fix os.urandom() implementation using getrandom() on Linux. Truncate size to INT_MAX and loop until we collected enough random bytes, instead of casting a directly Py_ssize_t to int.

Library

bpo-26386 [https://bugs.python.org/issue26386]: Fixed ttk.TreeView selection operations with item id’s containing spaces.

Security

bpo-22636 [https://bugs.python.org/issue22636]: Avoid shell injection problems with ctypes.util.find_library().

Library

bpo-16182 [https://bugs.python.org/issue16182]: Fix various functions in the « readline » module to use the locale encoding, and fix get_begidx() and get_endidx() to return code point indexes.

bpo-27392 [https://bugs.python.org/issue27392]: Add loop.connect_accepted_socket(). Patch by Jim Fulton.

bpo-27930 [https://bugs.python.org/issue27930]: Improved behaviour of logging.handlers.QueueListener. Thanks to Paulo Andrade and Petr Viktorin for the analysis and patch.

bpo-21201 [https://bugs.python.org/issue21201]: Improves readability of multiprocessing error message. Thanks to Wojciech Walczak for patch.

bpo-27456 [https://bugs.python.org/issue27456]: asyncio: Set TCP_NODELAY by default.

bpo-27906 [https://bugs.python.org/issue27906]: Fix socket accept exhaustion during high TCP traffic. Patch by Kevin Conway.

bpo-28174 [https://bugs.python.org/issue28174]: Handle when SO_REUSEPORT isn’t properly supported. Patch by Seth Michael Larson.

bpo-26654 [https://bugs.python.org/issue26654]: Inspect functools.partial in asyncio.Handle.__repr__. Patch by iceboy.

bpo-26909 [https://bugs.python.org/issue26909]: Fix slow pipes IO in asyncio. Patch by INADA Naoki.

bpo-28176 [https://bugs.python.org/issue28176]: Fix callbacks race in asyncio.SelectorLoop.sock_connect.

bpo-27759 [https://bugs.python.org/issue27759]: Fix selectors incorrectly retain invalid file descriptors. Patch by Mark Williams.

bpo-28368 [https://bugs.python.org/issue28368]: Refuse monitoring processes if the child watcher has no loop attached. Patch by Vincent Michel.

bpo-28369 [https://bugs.python.org/issue28369]: Raise RuntimeError when transport’s FD is used with add_reader, add_writer, etc.

bpo-28370 [https://bugs.python.org/issue28370]: Speedup asyncio.StreamReader.readexactly. Patch by Коренберг Марк.

bpo-28371 [https://bugs.python.org/issue28371]: Deprecate passing asyncio.Handles to run_in_executor.

bpo-28372 [https://bugs.python.org/issue28372]: Fix asyncio to support formatting of non-python coroutines.

bpo-28399 [https://bugs.python.org/issue28399]: Remove UNIX socket from FS before binding. Patch by Коренберг Марк.

bpo-27972 [https://bugs.python.org/issue27972]: Prohibit Tasks to await on themselves.

bpo-26923 [https://bugs.python.org/issue26923]: Fix asyncio.Gather to refuse being cancelled once all children are done. Patch by Johannes Ebke.

bpo-26796 [https://bugs.python.org/issue26796]: Don’t configure the number of workers for default threadpool executor. Initial patch by Hans Lawrenz.

bpo-28600 [https://bugs.python.org/issue28600]: Optimize loop.call_soon().

bpo-28613 [https://bugs.python.org/issue28613]: Fix get_event_loop() return the current loop if called from coroutines/callbacks.

bpo-28639 [https://bugs.python.org/issue28639]: Fix inspect.isawaitable to always return bool Patch by Justin Mayfield.

bpo-28652 [https://bugs.python.org/issue28652]: Make loop methods reject socket kinds they do not support.

bpo-28653 [https://bugs.python.org/issue28653]: Fix a refleak in functools.lru_cache.

bpo-28703 [https://bugs.python.org/issue28703]: Fix asyncio.iscoroutinefunction to handle Mock objects.

bpo-24142 [https://bugs.python.org/issue24142]: Reading a corrupt config file left the parser in an invalid state. Original patch by Florian Höch.

bpo-28990 [https://bugs.python.org/issue28990]: Fix SSL hanging if connection is closed before handshake completed. (Patch by HoHo-Ho)

IDLE

bpo-15308 [https://bugs.python.org/issue15308]: Add “interrupt execution” (^C) to Shell menu. Patch by Roger Serwy, updated by Bayard Randel.

bpo-27922 [https://bugs.python.org/issue27922]: Stop IDLE tests from “flashing” gui widgets on the screen.

Add version to title of IDLE help window.

bpo-25564 [https://bugs.python.org/issue25564]: In section on IDLE – console differences, mention that using exec means that __builtins__ is defined for each statement.

bpo-27714 [https://bugs.python.org/issue27714]: text_textview and test_autocomplete now pass when re-run in the same process. This occurs when test_idle fails when run with the -w option but without -jn. Fix warning from test_config.

bpo-25507 [https://bugs.python.org/issue25507]: IDLE no longer runs buggy code because of its tkinter imports. Users must include the same imports required to run directly in Python.

bpo-27452 [https://bugs.python.org/issue27452]: add line counter and crc to IDLE configHandler test dump.

bpo-27365 [https://bugs.python.org/issue27365]: Allow non-ascii chars in IDLE NEWS.txt, for contributor names.

bpo-27245 [https://bugs.python.org/issue27245]: IDLE: Cleanly delete custom themes and key bindings. Previously, when IDLE was started from a console or by import, a cascade of warnings was emitted. Patch by Serhiy Storchaka.

C API

bpo-28808 [https://bugs.python.org/issue28808]: PyUnicode_CompareWithASCIIString() now never raises exceptions.

bpo-26754 [https://bugs.python.org/issue26754]: PyUnicode_FSDecoder() accepted a filename argument encoded as an iterable of integers. Now only strings and bytes-like objects are accepted.

Documentation

bpo-28513 [https://bugs.python.org/issue28513]: Documented command-line interface of zipfile.

Tests

bpo-28950 [https://bugs.python.org/issue28950]: Disallow -j0 to be combined with -T/-l/-M in regrtest command line arguments.

bpo-28666 [https://bugs.python.org/issue28666]: Now test.support.rmtree is able to remove unwritable or unreadable directories.

bpo-23839 [https://bugs.python.org/issue23839]: Various caches now are cleared before running every test file.

bpo-28409 [https://bugs.python.org/issue28409]: regrtest: fix the parser of command line arguments.

bpo-27787 [https://bugs.python.org/issue27787]: Call gc.collect() before checking each test for « dangling threads », since the dangling threads are weak references.

bpo-27369 [https://bugs.python.org/issue27369]: In test_pyexpat, avoid testing an error message detail that changed in Expat 2.2.0.

Tools/Demos

bpo-27952 [https://bugs.python.org/issue27952]: Get Tools/scripts/fixcid.py working with Python 3 and the current « re » module, avoid invalid Python backslash escapes, and fix a bug parsing escaped C quote signs.

bpo-27332 [https://bugs.python.org/issue27332]: Fixed the type of the first argument of module-level functions generated by Argument Clinic. Patch by Petr Viktorin.

bpo-27418 [https://bugs.python.org/issue27418]: Fixed Tools/importbench/importbench.py.

Windows

bpo-28251 [https://bugs.python.org/issue28251]: Improvements to help manuals on Windows.

bpo-28110 [https://bugs.python.org/issue28110]: launcher.msi has different product codes between 32-bit and 64-bit

bpo-25144 [https://bugs.python.org/issue25144]: Ensures TargetDir is set before continuing with custom install.

bpo-27469 [https://bugs.python.org/issue27469]: Adds a shell extension to the launcher so that drag and drop works correctly.

bpo-27309 [https://bugs.python.org/issue27309]: Enabled proper Windows styles in python[w].exe manifest.

Build

bpo-29080 [https://bugs.python.org/issue29080]: Removes hard dependency on hg.exe from PCBuild/build.bat

bpo-23903 [https://bugs.python.org/issue23903]: Added missed names to PC/python3.def.

bpo-10656 [https://bugs.python.org/issue10656]: Fix out-of-tree building on AIX. Patch by Tristan Carel and Michael Haubenwallner.

bpo-26359 [https://bugs.python.org/issue26359]: Rename –with-optimiations to –enable-optimizations.

bpo-28444 [https://bugs.python.org/issue28444]: Fix missing extensions modules when cross compiling.

bpo-28248 [https://bugs.python.org/issue28248]: Update Windows build and OS X installers to use OpenSSL 1.0.2j.

bpo-28258 [https://bugs.python.org/issue28258]: Fixed build with Estonian locale (python-config and distclean targets in Makefile). Patch by Arfrever Frehtes Taifersar Arahesis.

bpo-26661 [https://bugs.python.org/issue26661]: setup.py now detects system libffi with multiarch wrapper.

bpo-28066 [https://bugs.python.org/issue28066]: Fix the logic that searches build directories for generated include files when building outside the source tree.

bpo-15819 [https://bugs.python.org/issue15819]: Remove redundant include search directory option for building outside the source tree.

bpo-27566 [https://bugs.python.org/issue27566]: Fix clean target in freeze makefile (patch by Lisa Roach)

bpo-27705 [https://bugs.python.org/issue27705]: Update message in validate_ucrtbase.py

bpo-27983 [https://bugs.python.org/issue27983]: Cause lack of llvm-profdata tool when using clang as required for PGO linking to be a configure time error rather than make time when --with-optimizations is enabled. Also improve our ability to find the llvm-profdata tool on MacOS and some Linuxes.

bpo-26307 [https://bugs.python.org/issue26307]: The profile-opt build now applies PGO to the built-in modules.

bpo-26359 [https://bugs.python.org/issue26359]: Add the –with-optimizations configure flag.

bpo-27713 [https://bugs.python.org/issue27713]: Suppress spurious build warnings when updating importlib’s bootstrap files. Patch by Xiang Zhang

bpo-25825 [https://bugs.python.org/issue25825]: Correct the references to Modules/python.exp and ld_so_aix, which are required on AIX. This updates references to an installation path that was changed in 3.2a4, and undoes changed references to the build tree that were made in 3.5.0a1.

bpo-27453 [https://bugs.python.org/issue27453]: CPP invocation in configure must use CPPFLAGS. Patch by Chi Hsuan Yen.

bpo-27641 [https://bugs.python.org/issue27641]: The configure script now inserts comments into the makefile to prevent the pgen and _freeze_importlib executables from being cross-compiled.

bpo-26662 [https://bugs.python.org/issue26662]: Set PYTHON_FOR_GEN in configure as the Python program to be used for file generation during the build.

bpo-10910 [https://bugs.python.org/issue10910]: Avoid C++ compilation errors on FreeBSD and OS X. Also update FreedBSD version checks for the original ctype UTF-8 workaround.

bpo-28676 [https://bugs.python.org/issue28676]: Prevent missing “getentropy” declaration warning on macOS. Patch by Gareth Rees.

Python 3.5.2 final

Release date: 2016-06-26

Core and Builtins

bpo-26930 [https://bugs.python.org/issue26930]: Update Windows builds to use OpenSSL 1.0.2h.

Tests

bpo-26867 [https://bugs.python.org/issue26867]: Ubuntu’s openssl OP_NO_SSLv3 is forced on by default; fix test.

IDLE

bpo-27365 [https://bugs.python.org/issue27365]: Allow non-ascii in idlelib/NEWS.txt - minimal part for 3.5.2.

Python 3.5.2 release candidate 1

Release date: 2016-06-12

Core and Builtins

bpo-27066 [https://bugs.python.org/issue27066]: Fixed SystemError if a custom opener (for open()) returns a negative number without setting an exception.

bpo-20041 [https://bugs.python.org/issue20041]: Fixed TypeError when frame.f_trace is set to None. Patch by Xavier de Gaye.

bpo-26168 [https://bugs.python.org/issue26168]: Fixed possible refleaks in failing Py_BuildValue() with the « N » format unit.

bpo-26991 [https://bugs.python.org/issue26991]: Fix possible refleak when creating a function with annotations.

bpo-27039 [https://bugs.python.org/issue27039]: Fixed bytearray.remove() for values greater than 127. Patch by Joe Jevnik.

bpo-23640 [https://bugs.python.org/issue23640]: int.from_bytes() no longer bypasses constructors for subclasses.

bpo-26811 [https://bugs.python.org/issue26811]: gc.get_objects() no longer contains a broken tuple with NULL pointer.

bpo-20120 [https://bugs.python.org/issue20120]: Use RawConfigParser for .pypirc parsing, removing support for interpolation unintentionally added with move to Python 3. Behavior no longer does any interpolation in .pypirc files, matching behavior in Python 2.7 and Setuptools 19.0.

bpo-26659 [https://bugs.python.org/issue26659]: Make the builtin slice type support cycle collection.

bpo-26718 [https://bugs.python.org/issue26718]: super.__init__ no longer leaks memory if called multiple times. NOTE: A direct call of super.__init__ is not endorsed!

bpo-25339 [https://bugs.python.org/issue25339]: PYTHONIOENCODING now has priority over locale in setting the error handler for stdin and stdout.

bpo-26494 [https://bugs.python.org/issue26494]: Fixed crash on iterating exhausting iterators. Affected classes are generic sequence iterators, iterators of str, bytes, bytearray, list, tuple, set, frozenset, dict, OrderedDict, corresponding views and os.scandir() iterator.

bpo-26581 [https://bugs.python.org/issue26581]: If coding cookie is specified multiple times on a line in Python source code file, only the first one is taken to account.

bpo-26464 [https://bugs.python.org/issue26464]: Fix str.translate() when string is ASCII and first replacements removes character, but next replacement uses a non-ASCII character or a string longer than 1 character. Regression introduced in Python 3.5.0.

bpo-22836 [https://bugs.python.org/issue22836]: Ensure exception reports from PyErr_Display() and PyErr_WriteUnraisable() are sensible even when formatting them produces secondary errors. This affects the reports produced by sys.__excepthook__() and when __del__() raises an exception.

bpo-26302 [https://bugs.python.org/issue26302]: Correct behavior to reject comma as a legal character for cookie names.

bpo-4806 [https://bugs.python.org/issue4806]: Avoid masking the original TypeError exception when using star (*) unpacking in function calls. Based on patch by Hagen Fürstenau and Daniel Urban.

bpo-27138 [https://bugs.python.org/issue27138]: Fix the doc comment for FileFinder.find_spec().

bpo-26154 [https://bugs.python.org/issue26154]: Add a new private _PyThreadState_UncheckedGet() function to get the current Python thread state, but don’t issue a fatal error if it is NULL. This new function must be used instead of accessing directly the _PyThreadState_Current variable. The variable is no more exposed since Python 3.5.1 to hide the exact implementation of atomic C types, to avoid compiler issues.

bpo-26194 [https://bugs.python.org/issue26194]: Deque.insert() gave odd results for bounded deques that had reached their maximum size. Now an IndexError will be raised when attempting to insert into a full deque.

bpo-25843 [https://bugs.python.org/issue25843]: When compiling code, don’t merge constants if they are equal but have a different types. For example, f1, f2 = lambda: 1, lambda: 1.0 is now correctly compiled to two different functions: f1() returns 1 (int) and f2() returns 1.0 (int), even if 1 and 1.0 are equal.

bpo-22995 [https://bugs.python.org/issue22995]: [UPDATE] Comment out the one of the pickleability tests in _PyObject_GetState() due to regressions observed in Cython-based projects.

bpo-25961 [https://bugs.python.org/issue25961]: Disallowed null characters in the type name.

bpo-25973 [https://bugs.python.org/issue25973]: Fix segfault when an invalid nonlocal statement binds a name starting with two underscores.

bpo-22995 [https://bugs.python.org/issue22995]: Instances of extension types with a state that aren’t subclasses of list or dict and haven’t implemented any pickle-related methods (__reduce__, __reduce_ex__, __getnewargs__, __getnewargs_ex__, or __getstate__), can no longer be pickled. Including memoryview.

bpo-20440 [https://bugs.python.org/issue20440]: Massive replacing unsafe attribute setting code with special macro Py_SETREF.

bpo-25766 [https://bugs.python.org/issue25766]: Special method __bytes__() now works in str subclasses.

bpo-25421 [https://bugs.python.org/issue25421]: __sizeof__ methods of builtin types now use dynamic basic size. This allows sys.getsize() to work correctly with their subclasses with __slots__ defined.

bpo-25709 [https://bugs.python.org/issue25709]: Fixed problem with in-place string concatenation and utf-8 cache.

bpo-27147 [https://bugs.python.org/issue27147]: Mention PEP 420 in the importlib docs.

bpo-24097 [https://bugs.python.org/issue24097]: Fixed crash in object.__reduce__() if slot name is freed inside __getattr__.

bpo-24731 [https://bugs.python.org/issue24731]: Fixed crash on converting objects with special methods __bytes__, __trunc__, and __float__ returning instances of subclasses of bytes, int, and float to subclasses of bytes, int, and float correspondingly.

bpo-26478 [https://bugs.python.org/issue26478]: Fix semantic bugs when using binary operators with dictionary views and tuples.

bpo-26171 [https://bugs.python.org/issue26171]: Fix possible integer overflow and heap corruption in zipimporter.get_data().

bpo-25660 [https://bugs.python.org/issue25660]: Fix TAB key behaviour in REPL with readline.

bpo-25887 [https://bugs.python.org/issue25887]: Raise a RuntimeError when a coroutine object is awaited more than once.

bpo-27243 [https://bugs.python.org/issue27243]: Update the __aiter__ protocol: instead of returning an awaitable that resolves to an asynchronous iterator, the asynchronous iterator should be returned directly. Doing the former will trigger a PendingDeprecationWarning.

Security

bpo-26556 [https://bugs.python.org/issue26556]: Update expat to 2.1.1, fixes CVE-2015-1283.

Fix TLS stripping vulnerability in smtplib, CVE-2016-0772. Reported by Team Oststrom

Library

bpo-21386 [https://bugs.python.org/issue21386]: Implement missing IPv4Address.is_global property. It was documented since 07a5610bae9d. Initial patch by Roger Luethi.

bpo-20900 [https://bugs.python.org/issue20900]: distutils register command now decodes HTTP responses correctly. Initial patch by ingrid.

A new version of typing.py provides several new classes and features: @overload outside stubs, DefaultDict, Text, ContextManager, Type[], NewType(), TYPE_CHECKING, and numerous bug fixes (note that some of the new features are not yet implemented in mypy or other static analyzers). Also classes for PEP 492 (Awaitable, AsyncIterable, AsyncIterator) have been added (in fact they made it into 3.5.1 but were never mentioned).

bpo-25738 [https://bugs.python.org/issue25738]: Stop http.server.BaseHTTPRequestHandler.send_error() from sending a message body for 205 Reset Content. Also, don’t send Content header fields in responses that don’t have a body. Patch by Susumu Koshiba.

bpo-21313 [https://bugs.python.org/issue21313]: Fix the « platform » module to tolerate when sys.version contains truncated build information.

Security

bpo-26839 [https://bugs.python.org/issue26839]: On Linux, os.urandom() now calls getrandom() with GRND_NONBLOCK to fall back on reading /dev/urandom if the urandom entropy pool is not initialized yet. Patch written by Colm Buckley.

Library

bpo-27164 [https://bugs.python.org/issue27164]: In the zlib module, allow decompressing raw Deflate streams with a predefined zdict. Based on patch by Xiang Zhang.

bpo-24291 [https://bugs.python.org/issue24291]: Fix wsgiref.simple_server.WSGIRequestHandler to completely write data to the client. Previously it could do partial writes and truncate data. Also, wsgiref.handler.ServerHandler can now handle stdout doing partial writes, but this is deprecated.

bpo-26809 [https://bugs.python.org/issue26809]: Add __all__ to string. Patch by Emanuel Barry.

bpo-26373 [https://bugs.python.org/issue26373]: subprocess.Popen.communicate now correctly ignores BrokenPipeError when the child process dies before .communicate() is called in more/all circumstances.

bpo-21776 [https://bugs.python.org/issue21776]: distutils.upload now correctly handles HTTPError. Initial patch by Claudiu Popa.

bpo-27114 [https://bugs.python.org/issue27114]: Fix SSLContext._load_windows_store_certs fails with PermissionError

bpo-18383 [https://bugs.python.org/issue18383]: Avoid creating duplicate filters when using filterwarnings and simplefilter. Based on patch by Alex Shkop.

bpo-27057 [https://bugs.python.org/issue27057]: Fix os.set_inheritable() on Android, ioctl() is blocked by SELinux and fails with EACCESS. The function now falls back to fcntl(). Patch written by Michał Bednarski.

bpo-27014 [https://bugs.python.org/issue27014]: Fix infinite recursion using typing.py. Thanks to Kalle Tuure!

bpo-14132 [https://bugs.python.org/issue14132]: Fix urllib.request redirect handling when the target only has a query string. Original fix by Ján Janech.

bpo-17214 [https://bugs.python.org/issue17214]: The « urllib.request » module now percent-encodes non-ASCII bytes found in redirect target URLs. Some servers send Location header fields with non-ASCII bytes, but « http.client » requires the request target to be ASCII-encodable, otherwise a UnicodeEncodeError is raised. Based on patch by Christian Heimes.

bpo-26892 [https://bugs.python.org/issue26892]: Honor debuglevel flag in urllib.request.HTTPHandler. Patch contributed by Chi Hsuan Yen.

bpo-22274 [https://bugs.python.org/issue22274]: In the subprocess module, allow stderr to be redirected to stdout even when stdout is not redirected. Patch by Akira Li.

bpo-26807 [https://bugs.python.org/issue26807]: mock_open “files” no longer error on readline at end of file. Patch from Yolanda Robla.

bpo-25745 [https://bugs.python.org/issue25745]: Fixed leaking a userptr in curses panel destructor.

bpo-26977 [https://bugs.python.org/issue26977]: Removed unnecessary, and ignored, call to sum of squares helper in statistics.pvariance.

bpo-26881 [https://bugs.python.org/issue26881]: The modulefinder module now supports extended opcode arguments.

bpo-23815 [https://bugs.python.org/issue23815]: Fixed crashes related to directly created instances of types in _tkinter and curses.panel modules.

bpo-17765 [https://bugs.python.org/issue17765]: weakref.ref() no longer silently ignores keyword arguments. Patch by Georg Brandl.

bpo-26873 [https://bugs.python.org/issue26873]: xmlrpc now raises ResponseError on unsupported type tags instead of silently return incorrect result.

bpo-26711 [https://bugs.python.org/issue26711]: Fixed the comparison of plistlib.Data with other types.

bpo-24114 [https://bugs.python.org/issue24114]: Fix an uninitialized variable in ctypes.util.

The bug only occurs on SunOS when the ctypes implementation searches for the crle program. Patch by Xiang Zhang. Tested on SunOS by Kees Bos.

bpo-26864 [https://bugs.python.org/issue26864]: In urllib.request, change the proxy bypass host checking against no_proxy to be case-insensitive, and to not match unrelated host names that happen to have a bypassed hostname as a suffix. Patch by Xiang Zhang.

bpo-26634 [https://bugs.python.org/issue26634]: recursive_repr() now sets __qualname__ of wrapper. Patch by Xiang Zhang.

bpo-26804 [https://bugs.python.org/issue26804]: urllib.request will prefer lower_case proxy environment variables over UPPER_CASE or Mixed_Case ones. Patch contributed by Hans-Peter Jansen.

bpo-26837 [https://bugs.python.org/issue26837]: assertSequenceEqual() now correctly outputs non-stringified differing items (like bytes in the -b mode). This affects assertListEqual() and assertTupleEqual().

bpo-26041 [https://bugs.python.org/issue26041]: Remove « will be removed in Python 3.7 » from deprecation messages of platform.dist() and platform.linux_distribution(). Patch by Kumaripaba Miyurusara Athukorala.

bpo-26822 [https://bugs.python.org/issue26822]: itemgetter, attrgetter and methodcaller objects no longer silently ignore keyword arguments.

bpo-26733 [https://bugs.python.org/issue26733]: Disassembling a class now disassembles class and static methods. Patch by Xiang Zhang.

bpo-26801 [https://bugs.python.org/issue26801]: Fix error handling in shutil.get_terminal_size(), catch AttributeError instead of NameError. Patch written by Emanuel Barry.

bpo-24838 [https://bugs.python.org/issue24838]: tarfile’s ustar and gnu formats now correctly calculate name and link field limits for multibyte character encodings like utf-8.

Security

bpo-26657 [https://bugs.python.org/issue26657]: Fix directory traversal vulnerability with http.server on Windows. This fixes a regression that was introduced in 3.3.4rc1 and 3.4.0rc1. Based on patch by Philipp Hagemeister.

Library

bpo-26717 [https://bugs.python.org/issue26717]: Stop encoding Latin-1-ized WSGI paths with UTF-8. Patch by Anthony Sottile.

bpo-26735 [https://bugs.python.org/issue26735]: Fix os.urandom() on Solaris 11.3 and newer when reading more than 1,024 bytes: call getrandom() multiple times with a limit of 1024 bytes per call.

bpo-16329 [https://bugs.python.org/issue16329]: Add .webm to mimetypes.types_map. Patch by Giampaolo Rodola”.

bpo-13952 [https://bugs.python.org/issue13952]: Add .csv to mimetypes.types_map. Patch by Geoff Wilson.

bpo-26709 [https://bugs.python.org/issue26709]: Fixed Y2038 problem in loading binary PLists.

bpo-23735 [https://bugs.python.org/issue23735]: Handle terminal resizing with Readline 6.3+ by installing our own SIGWINCH handler. Patch by Eric Price.

bpo-26586 [https://bugs.python.org/issue26586]: In http.server, respond with « 413 Request header fields too large » if there are too many header fields to parse, rather than killing the connection and raising an unhandled exception. Patch by Xiang Zhang.

bpo-22854 [https://bugs.python.org/issue22854]: Change BufferedReader.writable() and BufferedWriter.readable() to always return False.

bpo-25195 [https://bugs.python.org/issue25195]: Fix a regression in mock.MagicMock. _Call is a subclass of tuple (changeset 3603bae63c13 only works for classes) so we need to implement __ne__ ourselves. Patch by Andrew Plummer.

bpo-26644 [https://bugs.python.org/issue26644]: Raise ValueError rather than SystemError when a negative length is passed to SSLSocket.recv() or read().

bpo-23804 [https://bugs.python.org/issue23804]: Fix SSL recv(0) and read(0) methods to return zero bytes instead of up to 1024.

bpo-26616 [https://bugs.python.org/issue26616]: Fixed a bug in datetime.astimezone() method.

bpo-21925 [https://bugs.python.org/issue21925]: warnings.formatwarning() now catches exceptions on linecache.getline(...) to be able to log ResourceWarning emitted late during the Python shutdown process.

bpo-24266 [https://bugs.python.org/issue24266]: Ctrl+C during Readline history search now cancels the search mode when compiled with Readline 7.

bpo-26560 [https://bugs.python.org/issue26560]: Avoid potential ValueError in BaseHandler.start_response. Initial patch by Peter Inglesby.

Security

bpo-26313 [https://bugs.python.org/issue26313]: ssl.py _load_windows_store_certs fails if windows cert store is empty. Patch by Baji.

Library

bpo-26569 [https://bugs.python.org/issue26569]: Fix pyclbr.readmodule() and pyclbr.readmodule_ex() to support importing packages.

bpo-26499 [https://bugs.python.org/issue26499]: Account for remaining Content-Length in HTTPResponse.readline() and read1(). Based on patch by Silent Ghost. Also document that HTTPResponse now supports these methods.

bpo-25320 [https://bugs.python.org/issue25320]: Handle sockets in directories unittest discovery is scanning. Patch from Victor van den Elzen.

bpo-16181 [https://bugs.python.org/issue16181]: cookiejar.http2time() now returns None if year is higher than datetime.MAXYEAR.

bpo-26513 [https://bugs.python.org/issue26513]: Fixes platform module detection of Windows Server

bpo-23718 [https://bugs.python.org/issue23718]: Fixed parsing time in week 0 before Jan 1. Original patch by Tamás Bence Gedai.

bpo-20589 [https://bugs.python.org/issue20589]: Invoking Path.owner() and Path.group() on Windows now raise NotImplementedError instead of ImportError.

bpo-26177 [https://bugs.python.org/issue26177]: Fixed the keys() method for Canvas and Scrollbar widgets.

bpo-15068 [https://bugs.python.org/issue15068]: Got rid of excessive buffering in the fileinput module. The bufsize parameter is no longer used.

bpo-2202 [https://bugs.python.org/issue2202]: Fix UnboundLocalError in AbstractDigestAuthHandler.get_algorithm_impls. Initial patch by Mathieu Dupuy.

bpo-25718 [https://bugs.python.org/issue25718]: Fixed pickling and copying the accumulate() iterator with total is None.

bpo-26475 [https://bugs.python.org/issue26475]: Fixed debugging output for regular expressions with the (?x) flag.

bpo-26457 [https://bugs.python.org/issue26457]: Fixed the subnets() methods in IP network classes for the case when resulting prefix length is equal to maximal prefix length. Based on patch by Xiang Zhang.

bpo-26385 [https://bugs.python.org/issue26385]: Remove the file if the internal open() call in NamedTemporaryFile() fails. Patch by Silent Ghost.

bpo-26402 [https://bugs.python.org/issue26402]: Fix XML-RPC client to retry when the server shuts down a persistent connection. This was a regression related to the new http.client.RemoteDisconnected exception in 3.5.0a4.

bpo-25913 [https://bugs.python.org/issue25913]: Leading <~ is optional now in base64.a85decode() with adobe=True. Patch by Swati Jaiswal.

bpo-26186 [https://bugs.python.org/issue26186]: Remove an invalid type check in importlib.util.LazyLoader.

bpo-26367 [https://bugs.python.org/issue26367]: importlib.__import__() raises SystemError like builtins.__import__() when level is specified but without an accompanying package specified.

bpo-26309 [https://bugs.python.org/issue26309]: In the « socketserver » module, shut down the request (closing the connected socket) when verify_request() returns false. Patch by Aviv Palivoda.

Security

bpo-25939 [https://bugs.python.org/issue25939]: On Windows open the cert store readonly in ssl.enum_certificates.

Library

bpo-25995 [https://bugs.python.org/issue25995]: os.walk() no longer uses FDs proportional to the tree depth.

bpo-26117 [https://bugs.python.org/issue26117]: The os.scandir() iterator now closes file descriptor not only when the iteration is finished, but when it was failed with error.

bpo-25911 [https://bugs.python.org/issue25911]: Restored support of bytes paths in os.walk() on Windows.

bpo-26045 [https://bugs.python.org/issue26045]: Add UTF-8 suggestion to error message when posting a non-Latin-1 string with http.client.

bpo-12923 [https://bugs.python.org/issue12923]: Reset FancyURLopener’s redirect counter even if there is an exception. Based on patches by Brian Brazil and Daniel Rocco.

bpo-25945 [https://bugs.python.org/issue25945]: Fixed a crash when unpickle the functools.partial object with wrong state. Fixed a leak in failed functools.partial constructor. « args » and « keywords » attributes of functools.partial have now always types tuple and dict correspondingly.

bpo-26202 [https://bugs.python.org/issue26202]: copy.deepcopy() now correctly copies range() objects with non-atomic attributes.

bpo-23076 [https://bugs.python.org/issue23076]: Path.glob() now raises a ValueError if it’s called with an invalid pattern. Patch by Thomas Nyberg.

bpo-19883 [https://bugs.python.org/issue19883]: Fixed possible integer overflows in zipimport.

bpo-26227 [https://bugs.python.org/issue26227]: On Windows, getnameinfo(), gethostbyaddr() and gethostbyname_ex() functions of the socket module now decode the hostname from the ANSI code page rather than UTF-8.

bpo-26147 [https://bugs.python.org/issue26147]: xmlrpc now works with strings not encodable with used non-UTF-8 encoding.

bpo-25935 [https://bugs.python.org/issue25935]: Garbage collector now breaks reference loops with OrderedDict.

bpo-16620 [https://bugs.python.org/issue16620]: Fixed AttributeError in msilib.Directory.glob().

bpo-26013 [https://bugs.python.org/issue26013]: Added compatibility with broken protocol 2 pickles created in old Python 3 versions (3.4.3 and lower).

bpo-25850 [https://bugs.python.org/issue25850]: Use cross-compilation by default for 64-bit Windows.

bpo-17633 [https://bugs.python.org/issue17633]: Improve zipimport’s support for namespace packages.

bpo-24705 [https://bugs.python.org/issue24705]: Fix sysconfig._parse_makefile not expanding ${} vars appearing before $() vars.

bpo-22138 [https://bugs.python.org/issue22138]: Fix mock.patch behavior when patching descriptors. Restore original values after patching. Patch contributed by Sean McCully.

bpo-25672 [https://bugs.python.org/issue25672]: In the ssl module, enable the SSL_MODE_RELEASE_BUFFERS mode option if it is safe to do so.

bpo-26012 [https://bugs.python.org/issue26012]: Don’t traverse into symlinks for ** pattern in pathlib.Path.[r]glob().

bpo-24120 [https://bugs.python.org/issue24120]: Ignore PermissionError when traversing a tree with pathlib.Path.[r]glob(). Patch by Ulrich Petri.

bpo-25447 [https://bugs.python.org/issue25447]: fileinput now uses sys.stdin as-is if it does not have a buffer attribute (restores backward compatibility).

bpo-25447 [https://bugs.python.org/issue25447]: Copying the lru_cache() wrapper object now always works, independently from the type of the wrapped object (by returning the original object unchanged).

bpo-24103 [https://bugs.python.org/issue24103]: Fixed possible use after free in ElementTree.XMLPullParser.

bpo-25860 [https://bugs.python.org/issue25860]: os.fwalk() no longer skips remaining directories when error occurs. Original patch by Samson Lee.

bpo-25914 [https://bugs.python.org/issue25914]: Fixed and simplified OrderedDict.__sizeof__.

bpo-25902 [https://bugs.python.org/issue25902]: Fixed various refcount issues in ElementTree iteration.

bpo-25717 [https://bugs.python.org/issue25717]: Restore the previous behaviour of tolerating most fstat() errors when opening files. This was a regression in 3.5a1, and stopped anonymous temporary files from working in special cases.

bpo-24903 [https://bugs.python.org/issue24903]: Fix regression in number of arguments compileall accepts when “-d” is specified. The check on the number of arguments has been dropped completely as it never worked correctly anyway.

bpo-25764 [https://bugs.python.org/issue25764]: In the subprocess module, preserve any exception caused by fork() failure when preexec_fn is used.

bpo-6478 [https://bugs.python.org/issue6478]: _strptime’s regexp cache now is reset after changing timezone with time.tzset().

bpo-14285 [https://bugs.python.org/issue14285]: When executing a package with the « python -m package » option, and package initialization fails, a proper traceback is now reported. The « runpy » module now lets exceptions from package initialization pass back to the caller, rather than raising ImportError.

bpo-19771 [https://bugs.python.org/issue19771]: Also in runpy and the « -m » option, omit the irrelevant message « … is a package and cannot be directly executed » if the package could not even be initialized (e.g. due to a bad *.pyc file).

bpo-25177 [https://bugs.python.org/issue25177]: Fixed problem with the mean of very small and very large numbers. As a side effect, statistics.mean and statistics.variance should be significantly faster.

bpo-25718 [https://bugs.python.org/issue25718]: Fixed copying object with state with boolean value is false.

bpo-10131 [https://bugs.python.org/issue10131]: Fixed deep copying of minidom documents. Based on patch by Marian Ganisin.

bpo-25725 [https://bugs.python.org/issue25725]: Fixed a reference leak in pickle.loads() when unpickling invalid data including tuple instructions.

bpo-25663 [https://bugs.python.org/issue25663]: In the Readline completer, avoid listing duplicate global names, and search the global namespace before searching builtins.

bpo-25688 [https://bugs.python.org/issue25688]: Fixed file leak in ElementTree.iterparse() raising an error.

bpo-23914 [https://bugs.python.org/issue23914]: Fixed SystemError raised by unpickler on broken pickle data.

bpo-25691 [https://bugs.python.org/issue25691]: Fixed crash on deleting ElementTree.Element attributes.

bpo-25624 [https://bugs.python.org/issue25624]: ZipFile now always writes a ZIP_STORED header for directory entries. Patch by Dingyuan Wang.

Skip getaddrinfo if host is already resolved. Patch by A. Jesse Jiryu Davis.

bpo-26050 [https://bugs.python.org/issue26050]: Add asyncio.StreamReader.readuntil() method. Patch by Марк Коренберг.

bpo-25924 [https://bugs.python.org/issue25924]: Avoid unnecessary serialization of getaddrinfo(3) calls on OS X versions 10.5 or higher. Original patch by A. Jesse Jiryu Davis.

bpo-26406 [https://bugs.python.org/issue26406]: Avoid unnecessary serialization of getaddrinfo(3) calls on current versions of OpenBSD and NetBSD. Patch by A. Jesse Jiryu Davis.

bpo-26848 [https://bugs.python.org/issue26848]: Fix asyncio/subprocess.communicate() to handle empty input. Patch by Jack O’Connor.

bpo-27040 [https://bugs.python.org/issue27040]: Add loop.get_exception_handler method

bpo-27041 [https://bugs.python.org/issue27041]: asyncio: Add loop.create_future method

bpo-27223 [https://bugs.python.org/issue27223]: asyncio: Fix _read_ready and _write_ready to respect _conn_lost. Patch by Łukasz Langa.

bpo-22970 [https://bugs.python.org/issue22970]: asyncio: Fix inconsistency cancelling Condition.wait. Patch by David Coles.

IDLE

bpo-5124 [https://bugs.python.org/issue5124]: Paste with text selected now replaces the selection on X11. This matches how paste works on Windows, Mac, most modern Linux apps, and ttk widgets. Original patch by Serhiy Storchaka.

bpo-24759 [https://bugs.python.org/issue24759]: Make clear in idlelib.idle_test.__init__ that the directory is a private implementation of test.test_idle and tool for maintainers.

bpo-27196 [https://bugs.python.org/issue27196]: Stop “ThemeChanged” warnings when running IDLE tests. These persisted after other warnings were suppressed in #20567. Apply Serhiy Storchaka’s update_idletasks solution to four test files. Record this additional advice in idle_test/README.txt

bpo-20567 [https://bugs.python.org/issue20567]: Revise idle_test/README.txt with advice about avoiding tk warning messages from tests. Apply advice to several IDLE tests.

bpo-27117 [https://bugs.python.org/issue27117]: Make colorizer htest and turtledemo work with dark themes. Move code for configuring text widget colors to a new function.

bpo-26673 [https://bugs.python.org/issue26673]: When tk reports font size as 0, change to size 10. Such fonts on Linux prevented the configuration dialog from opening.

bpo-21939 [https://bugs.python.org/issue21939]: Add test for IDLE’s percolator. Original patch by Saimadhav Heblikar.

bpo-21676 [https://bugs.python.org/issue21676]: Add test for IDLE’s replace dialog. Original patch by Saimadhav Heblikar.

bpo-18410 [https://bugs.python.org/issue18410]: Add test for IDLE’s search dialog. Original patch by Westley Martínez.

bpo-21703 [https://bugs.python.org/issue21703]: Add test for IDLE’s undo delegator. Original patch by Saimadhav Heblikar .

bpo-27044 [https://bugs.python.org/issue27044]: Add ConfigDialog.remove_var_callbacks to stop memory leaks.

bpo-23977 [https://bugs.python.org/issue23977]: Add more asserts to test_delegator.

bpo-20640 [https://bugs.python.org/issue20640]: Add tests for idlelib.configHelpSourceEdit. Patch by Saimadhav Heblikar.

In the “IDLE-console differences” section of the IDLE doc, clarify how running with IDLE affects sys.modules and the standard streams.

bpo-25507 [https://bugs.python.org/issue25507]: fix incorrect change in IOBinding that prevented printing. Augment IOBinding htest to include all major IOBinding functions.

bpo-25905 [https://bugs.python.org/issue25905]: Revert unwanted conversion of “ to ’ RIGHT SINGLE QUOTATION MARK in README.txt and open this and NEWS.txt with “ascii”. Re-encode CREDITS.txt to utf-8 and open it with “utf-8”.

Documentation

bpo-19489 [https://bugs.python.org/issue19489]: Moved the search box from the sidebar to the header and footer of each page. Patch by Ammar Askar.

bpo-24136 [https://bugs.python.org/issue24136]: Document the new PEP 448 unpacking syntax of 3.5.

bpo-26736 [https://bugs.python.org/issue26736]: Used HTTPS for external links in the documentation if possible.

bpo-6953 [https://bugs.python.org/issue6953]: Rework the Readline module documentation to group related functions together, and add more details such as what underlying Readline functions and variables are accessed.

bpo-23606 [https://bugs.python.org/issue23606]: Adds note to ctypes documentation regarding cdll.msvcrt.

bpo-25500 [https://bugs.python.org/issue25500]: Fix documentation to not claim that __import__ is searched for in the global scope.

bpo-26014 [https://bugs.python.org/issue26014]: Update 3.x packaging documentation: * « See also » links to the new docs are now provided in the legacy pages * links to setuptools documentation have been updated

Tests

bpo-21916 [https://bugs.python.org/issue21916]: Added tests for the turtle module. Patch by ingrid, Gregory Loyse and Jelle Zijlstra.

bpo-26523 [https://bugs.python.org/issue26523]: The multiprocessing thread pool (multiprocessing.dummy.Pool) was untested.

bpo-26015 [https://bugs.python.org/issue26015]: Added new tests for pickling iterators of mutable sequences.

bpo-26325 [https://bugs.python.org/issue26325]: Added test.support.check_no_resource_warning() to check that no ResourceWarning is emitted.

bpo-25940 [https://bugs.python.org/issue25940]: Changed test_ssl to use self-signed.pythontest.net. This avoids relying on svn.python.org, which recently changed root certificate.

bpo-25616 [https://bugs.python.org/issue25616]: Tests for OrderedDict are extracted from test_collections into separate file test_ordered_dict.

bpo-26583 [https://bugs.python.org/issue26583]: Skip test_timestamp_overflow in test_import if bytecode files cannot be written.

Build

bpo-26884 [https://bugs.python.org/issue26884]: Fix linking extension modules for cross builds. Patch by Xavier de Gaye.

bpo-22359 [https://bugs.python.org/issue22359]: Disable the rules for running _freeze_importlib and pgen when cross-compiling. The output of these programs is normally saved with the source code anyway, and is still regenerated when doing a native build. Patch by Xavier de Gaye.

bpo-27229 [https://bugs.python.org/issue27229]: Fix the cross-compiling pgen rule for in-tree builds. Patch by Xavier de Gaye.

bpo-21668 [https://bugs.python.org/issue21668]: Link audioop, _datetime, _ctypes_test modules to libm, except on Mac OS X. Patch written by Xavier de Gaye.

bpo-25702 [https://bugs.python.org/issue25702]: A –with-lto configure option has been added that will enable link time optimizations at build time during a make profile-opt. Some compilers and toolchains are known to not produce stable code when using LTO, be sure to test things thoroughly before relying on it. It can provide a few % speed up over profile-opt alone.

bpo-26624 [https://bugs.python.org/issue26624]: Adds validation of ucrtbase[d].dll version with warning for old versions.

bpo-17603 [https://bugs.python.org/issue17603]: Avoid error about nonexistant fileblocks.o file by using a lower-level check for st_blocks in struct stat.

bpo-26079 [https://bugs.python.org/issue26079]: Fixing the build output folder for tix-8.4.3.6. Patch by Bjoern Thiel.

bpo-26465 [https://bugs.python.org/issue26465]: Update Windows builds to use OpenSSL 1.0.2g.

bpo-24421 [https://bugs.python.org/issue24421]: Compile Modules/_math.c once, before building extensions. Previously it could fail to compile properly if the math and cmath builds were concurrent.

bpo-25348 [https://bugs.python.org/issue25348]: Added --pgo and --pgo-job arguments to PCbuild\build.bat for building with Profile-Guided Optimization. The old PCbuild\build_pgo.bat script is now deprecated, and simply calls PCbuild\build.bat --pgo %*.

bpo-25827 [https://bugs.python.org/issue25827]: Add support for building with ICC to configure, including a new --with-icc flag.

bpo-25696 [https://bugs.python.org/issue25696]: Fix installation of Python on UNIX with make -j9.

bpo-26930 [https://bugs.python.org/issue26930]: Update OS X 10.5+ 32-bit-only installer to build and link with OpenSSL 1.0.2h.

bpo-26268 [https://bugs.python.org/issue26268]: Update Windows builds to use OpenSSL 1.0.2f.

bpo-25136 [https://bugs.python.org/issue25136]: Support Apple Xcode 7’s new textual SDK stub libraries.

bpo-24324 [https://bugs.python.org/issue24324]: Do not enable unreachable code warnings when using gcc as the option does not work correctly in older versions of gcc and has been silently removed as of gcc-4.5.

Windows

bpo-27053 [https://bugs.python.org/issue27053]: Updates make_zip.py to correctly generate library ZIP file.

bpo-26268 [https://bugs.python.org/issue26268]: Update the prepare_ssl.py script to handle OpenSSL releases that don’t include the contents of the include directory (that is, 1.0.2e and later).

bpo-26071 [https://bugs.python.org/issue26071]: bdist_wininst created binaries fail to start and find 32bit Python

bpo-26073 [https://bugs.python.org/issue26073]: Update the list of magic numbers in launcher

bpo-26065 [https://bugs.python.org/issue26065]: Excludes venv from library when generating embeddable distro.

Tools/Demos

bpo-26799 [https://bugs.python.org/issue26799]: Fix python-gdb.py: don’t get C types once when the Python code is loaded, but get C types on demand. The C types can change if python-gdb.py is loaded before the Python executable. Patch written by Thomas Ilsche.

bpo-26271 [https://bugs.python.org/issue26271]: Fix the Freeze tool to properly use flags passed through configure. Patch by Daniel Shaulov.

bpo-26489 [https://bugs.python.org/issue26489]: Add dictionary unpacking support to Tools/parser/unparse.py. Patch by Guo Ci Teo.

bpo-26316 [https://bugs.python.org/issue26316]: Fix variable name typo in Argument Clinic.

Windows

bpo-17500 [https://bugs.python.org/issue17500]: Remove unused and outdated icons. (See also: https://github.com/python/pythondotorg/issues/945)

Python 3.5.1 final

Release date: 2015-12-06

Core and Builtins

bpo-25709 [https://bugs.python.org/issue25709]: Fixed problem with in-place string concatenation and utf-8 cache.

Windows

bpo-25715 [https://bugs.python.org/issue25715]: Python 3.5.1 installer shows wrong upgrade path and incorrect logic for launcher detection.

Python 3.5.1 release candidate 1

Release date: 2015-11-22

Core and Builtins

bpo-25630 [https://bugs.python.org/issue25630]: Fix a possible segfault during argument parsing in functions that accept filesystem paths.

bpo-23564 [https://bugs.python.org/issue23564]: Fixed a partially broken sanity check in the _posixsubprocess internals regarding how fds_to_pass were passed to the child. The bug had no actual impact as subprocess.py already avoided it.

bpo-25388 [https://bugs.python.org/issue25388]: Fixed tokenizer crash when processing undecodable source code with a null byte.

bpo-25462 [https://bugs.python.org/issue25462]: The hash of the key now is calculated only once in most operations in C implementation of OrderedDict.

bpo-22995 [https://bugs.python.org/issue22995]: Default implementation of __reduce__ and __reduce_ex__ now rejects builtin types with not defined __new__.

bpo-25555 [https://bugs.python.org/issue25555]: Fix parser and AST: fill lineno and col_offset of « arg » node when compiling AST from Python objects.

bpo-24802 [https://bugs.python.org/issue24802]: Avoid buffer overreads when int(), float(), compile(), exec() and eval() are passed bytes-like objects. These objects are not necessarily terminated by a null byte, but the functions assumed they were.

bpo-24726 [https://bugs.python.org/issue24726]: Fixed a crash and leaking NULL in repr() of OrderedDict that was mutated by direct calls of dict methods.

bpo-25449 [https://bugs.python.org/issue25449]: Iterating OrderedDict with keys with unstable hash now raises KeyError in C implementations as well as in Python implementation.

bpo-25395 [https://bugs.python.org/issue25395]: Fixed crash when highly nested OrderedDict structures were garbage collected.

bpo-25274 [https://bugs.python.org/issue25274]: sys.setrecursionlimit() now raises a RecursionError if the new recursion limit is too low depending at the current recursion depth. Modify also the « lower-water mark » formula to make it monotonic. This mark is used to decide when the overflowed flag of the thread state is reset.

bpo-24402 [https://bugs.python.org/issue24402]: Fix input() to prompt to the redirected stdout when sys.stdout.fileno() fails.

bpo-24806 [https://bugs.python.org/issue24806]: Prevent builtin types that are not allowed to be subclassed from being subclassed through multiple inheritance.

bpo-24848 [https://bugs.python.org/issue24848]: Fixed a number of bugs in UTF-7 decoding of misformed data.

bpo-25280 [https://bugs.python.org/issue25280]: Import trace messages emitted in verbose (-v) mode are no longer formatted twice.

bpo-25003 [https://bugs.python.org/issue25003]: On Solaris 11.3 or newer, os.urandom() now uses the getrandom() function instead of the getentropy() function. The getentropy() function is blocking to generate very good quality entropy, os.urandom() doesn’t need such high-quality entropy.

bpo-25182 [https://bugs.python.org/issue25182]: The stdprinter (used as sys.stderr before the io module is imported at startup) now uses the backslashreplace error handler.

bpo-25131 [https://bugs.python.org/issue25131]: Make the line number and column offset of set/dict literals and comprehensions correspond to the opening brace.

bpo-25150 [https://bugs.python.org/issue25150]: Hide the private _Py_atomic_xxx symbols from the public Python.h header to fix a compilation error with OpenMP. PyThreadState_GET() becomes an alias to PyThreadState_Get() to avoid ABI incompatibilities.

Library

bpo-25626 [https://bugs.python.org/issue25626]: Change three zlib functions to accept sizes that fit in Py_ssize_t, but internally cap those sizes to UINT_MAX. This resolves a regression in 3.5 where GzipFile.read() failed to read chunks larger than 2 or 4 GiB. The change affects the zlib.Decompress.decompress() max_length parameter, the zlib.decompress() bufsize parameter, and the zlib.Decompress.flush() length parameter.

bpo-25583 [https://bugs.python.org/issue25583]: Avoid incorrect errors raised by os.makedirs(exist_ok=True) when the OS gives priority to errors such as EACCES over EEXIST.

bpo-25593 [https://bugs.python.org/issue25593]: Change semantics of EventLoop.stop() in asyncio.

bpo-6973 [https://bugs.python.org/issue6973]: When we know a subprocess.Popen process has died, do not allow the send_signal(), terminate(), or kill() methods to do anything as they could potentially signal a different process.

bpo-25590 [https://bugs.python.org/issue25590]: In the Readline completer, only call getattr() once per attribute.

bpo-25498 [https://bugs.python.org/issue25498]: Fix a crash when garbage-collecting ctypes objects created by wrapping a memoryview. This was a regression made in 3.5a1. Based on patch by Eryksun.

bpo-25584 [https://bugs.python.org/issue25584]: Added « escape » to the __all__ list in the glob module.

bpo-25584 [https://bugs.python.org/issue25584]: Fixed recursive glob() with patterns starting with **.

bpo-25446 [https://bugs.python.org/issue25446]: Fix regression in smtplib’s AUTH LOGIN support.

bpo-18010 [https://bugs.python.org/issue18010]: Fix the pydoc web server’s module search function to handle exceptions from importing packages.

bpo-25554 [https://bugs.python.org/issue25554]: Got rid of circular references in regular expression parsing.

bpo-25510 [https://bugs.python.org/issue25510]: fileinput.FileInput.readline() now returns b”” instead of “” at the end if the FileInput was opened with binary mode. Patch by Ryosuke Ito.

bpo-25503 [https://bugs.python.org/issue25503]: Fixed inspect.getdoc() for inherited docstrings of properties. Original patch by John Mark Vandenberg.

bpo-25515 [https://bugs.python.org/issue25515]: Always use os.urandom as a source of randomness in uuid.uuid4.

bpo-21827 [https://bugs.python.org/issue21827]: Fixed textwrap.dedent() for the case when largest common whitespace is a substring of smallest leading whitespace. Based on patch by Robert Li.

bpo-25447 [https://bugs.python.org/issue25447]: The lru_cache() wrapper objects now can be copied and pickled (by returning the original object unchanged).

bpo-25390 [https://bugs.python.org/issue25390]: typing: Don’t crash on Union[str, Pattern].

bpo-25441 [https://bugs.python.org/issue25441]: asyncio: Raise error from drain() when socket is closed.

bpo-25410 [https://bugs.python.org/issue25410]: Cleaned up and fixed minor bugs in C implementation of OrderedDict.

bpo-25411 [https://bugs.python.org/issue25411]: Improved Unicode support in SMTPHandler through better use of the email package. Thanks to user simon04 for the patch.

bpo-25407 [https://bugs.python.org/issue25407]: Remove mentions of the formatter module being removed in Python 3.6.

bpo-25406 [https://bugs.python.org/issue25406]: Fixed a bug in C implementation of OrderedDict.move_to_end() that caused segmentation fault or hang in iterating after moving several items to the start of ordered dict.

bpo-25364 [https://bugs.python.org/issue25364]: zipfile now works in threads disabled builds.

bpo-25328 [https://bugs.python.org/issue25328]: smtpd’s SMTPChannel now correctly raises a ValueError if both decode_data and enable_SMTPUTF8 are set to true.

bpo-25316 [https://bugs.python.org/issue25316]: distutils raises OSError instead of DistutilsPlatformError when MSVC is not installed.

bpo-25380 [https://bugs.python.org/issue25380]: Fixed protocol for the STACK_GLOBAL opcode in pickletools.opcodes.

bpo-23972 [https://bugs.python.org/issue23972]: Updates asyncio datagram create method allowing reuseport and reuseaddr socket options to be set prior to binding the socket. Mirroring the existing asyncio create_server method the reuseaddr option for datagram sockets defaults to True if the O/S is “posix” (except if the platform is Cygwin). Patch by Chris Laws.

bpo-25304 [https://bugs.python.org/issue25304]: Add asyncio.run_coroutine_threadsafe(). This lets you submit a coroutine to a loop from another thread, returning a concurrent.futures.Future. By Vincent Michel.

bpo-25232 [https://bugs.python.org/issue25232]: Fix CGIRequestHandler to split the query from the URL at the first question mark (?) rather than the last. Patch from Xiang Zhang.

bpo-24657 [https://bugs.python.org/issue24657]: Prevent CGIRequestHandler from collapsing slashes in the query part of the URL as if it were a path. Patch from Xiang Zhang.

bpo-24483 [https://bugs.python.org/issue24483]: C implementation of functools.lru_cache() now calculates key’s hash only once.

bpo-22958 [https://bugs.python.org/issue22958]: Constructor and update method of weakref.WeakValueDictionary now accept the self and the dict keyword arguments.

bpo-22609 [https://bugs.python.org/issue22609]: Constructor of collections.UserDict now accepts the self keyword argument.

bpo-25111 [https://bugs.python.org/issue25111]: Fixed comparison of traceback.FrameSummary.

bpo-25262 [https://bugs.python.org/issue25262]: Added support for BINBYTES8 opcode in Python implementation of unpickler. Highest 32 bits of 64-bit size for BINUNICODE8 and BINBYTES8 opcodes no longer silently ignored on 32-bit platforms in C implementation.

bpo-25034 [https://bugs.python.org/issue25034]: Fix string.Formatter problem with auto-numbering and nested format_specs. Patch by Anthon van der Neut.

bpo-25233 [https://bugs.python.org/issue25233]: Rewrite the guts of asyncio.Queue and asyncio.Semaphore to be more understandable and correct.

bpo-25203 [https://bugs.python.org/issue25203]: Failed readline.set_completer_delims() no longer left the module in inconsistent state.

bpo-23600 [https://bugs.python.org/issue23600]: Default implementation of tzinfo.fromutc() was returning wrong results in some cases.

bpo-23329 [https://bugs.python.org/issue23329]: Allow the ssl module to be built with older versions of LibreSSL.

Prevent overflow in _Unpickler_Read.

bpo-25047 [https://bugs.python.org/issue25047]: The XML encoding declaration written by Element Tree now respects the letter case given by the user. This restores the ability to write encoding names in uppercase like « UTF-8 », which worked in Python 2.

bpo-25135 [https://bugs.python.org/issue25135]: Make deque_clear() safer by emptying the deque before clearing. This helps avoid possible reentrancy issues.

bpo-19143 [https://bugs.python.org/issue19143]: platform module now reads Windows version from kernel32.dll to avoid compatibility shims.

bpo-25092 [https://bugs.python.org/issue25092]: Fix datetime.strftime() failure when errno was already set to EINVAL.

bpo-23517 [https://bugs.python.org/issue23517]: Fix rounding in fromtimestamp() and utcfromtimestamp() methods of datetime.datetime: microseconds are now rounded to nearest with ties going to nearest even integer (ROUND_HALF_EVEN), instead of being rounding towards minus infinity (ROUND_FLOOR). It’s important that these methods use the same rounding mode than datetime.timedelta to keep the property: (datetime(1970,1,1) + timedelta(seconds=t)) == datetime.utcfromtimestamp(t). It also the rounding mode used by round(float) for example.

bpo-25155 [https://bugs.python.org/issue25155]: Fix datetime.datetime.now() and datetime.datetime.utcnow() on Windows to support date after year 2038. It was a regression introduced in Python 3.5.0.

bpo-25108 [https://bugs.python.org/issue25108]: Omitted internal frames in traceback functions print_stack(), format_stack(), and extract_stack() called without arguments.

bpo-25118 [https://bugs.python.org/issue25118]: Fix a regression of Python 3.5.0 in os.waitpid() on Windows.

bpo-24684 [https://bugs.python.org/issue24684]: socket.socket.getaddrinfo() now calls PyUnicode_AsEncodedString() instead of calling the encode() method of the host, to handle correctly custom string with an encode() method which doesn’t return a byte string. The encoder of the IDNA codec is now called directly instead of calling the encode() method of the string.

bpo-25060 [https://bugs.python.org/issue25060]: Correctly compute stack usage of the BUILD_MAP opcode.

bpo-24857 [https://bugs.python.org/issue24857]: Comparing call_args to a long sequence now correctly returns a boolean result instead of raising an exception. Patch by A Kaptur.

bpo-23144 [https://bugs.python.org/issue23144]: Make sure that HTMLParser.feed() returns all the data, even when convert_charrefs is True.

bpo-24982 [https://bugs.python.org/issue24982]: shutil.make_archive() with the « zip » format now adds entries for directories (including empty directories) in ZIP file.

bpo-25019 [https://bugs.python.org/issue25019]: Fixed a crash caused by setting non-string key of expat parser. Based on patch by John Leitch.

bpo-16180 [https://bugs.python.org/issue16180]: Exit pdb if file has syntax error, instead of trapping user in an infinite loop. Patch by Xavier de Gaye.

bpo-24891 [https://bugs.python.org/issue24891]: Fix a race condition at Python startup if the file descriptor of stdin (0), stdout (1) or stderr (2) is closed while Python is creating sys.stdin, sys.stdout and sys.stderr objects. These attributes are now set to None if the creation of the object failed, instead of raising an OSError exception. Initial patch written by Marco Paolini.

bpo-24992 [https://bugs.python.org/issue24992]: Fix error handling and a race condition (related to garbage collection) in collections.OrderedDict constructor.

bpo-24881 [https://bugs.python.org/issue24881]: Fixed setting binary mode in Python implementation of FileIO on Windows and Cygwin. Patch from Akira Li.

bpo-25578 [https://bugs.python.org/issue25578]: Fix (another) memory leak in SSLSocket.getpeercer().

bpo-25530 [https://bugs.python.org/issue25530]: Disable the vulnerable SSLv3 protocol by default when creating ssl.SSLContext.

bpo-25569 [https://bugs.python.org/issue25569]: Fix memory leak in SSLSocket.getpeercert().

bpo-25471 [https://bugs.python.org/issue25471]: Sockets returned from accept() shouldn’t appear to be nonblocking.

bpo-25319 [https://bugs.python.org/issue25319]: When threading.Event is reinitialized, the underlying condition should use a regular lock rather than a recursive lock.

bpo-21112 [https://bugs.python.org/issue21112]: Fix regression in unittest.expectedFailure on subclasses. Patch from Berker Peksag.

bpo-24764 [https://bugs.python.org/issue24764]: cgi.FieldStorage.read_multi() now ignores the Content-Length header in part headers. Patch written by Peter Landry and reviewed by Pierre Quentel.

bpo-24913 [https://bugs.python.org/issue24913]: Fix overrun error in deque.index(). Found by John Leitch and Bryce Darling.

bpo-24774 [https://bugs.python.org/issue24774]: Fix docstring in http.server.test. Patch from Chiu-Hsiang Hsu.

bpo-21159 [https://bugs.python.org/issue21159]: Improve message in configparser.InterpolationMissingOptionError. Patch from Łukasz Langa.

bpo-20362 [https://bugs.python.org/issue20362]: Honour TestCase.longMessage correctly in assertRegex. Patch from Ilia Kurenkov.

bpo-23572 [https://bugs.python.org/issue23572]: Fixed functools.singledispatch on classes with falsy metaclasses. Patch by Ethan Furman.

asyncio: ensure_future() now accepts awaitable objects.

IDLE

bpo-15348 [https://bugs.python.org/issue15348]: Stop the debugger engine (normally in a user process) before closing the debugger window (running in the IDLE process). This prevents the RuntimeErrors that were being caught and ignored.

bpo-24455 [https://bugs.python.org/issue24455]: Prevent IDLE from hanging when a) closing the shell while the debugger is active (15347); b) closing the debugger with the [X] button (15348); and c) activating the debugger when already active (24455). The patch by Mark Roseman does this by making two changes. 1. Suspend and resume the gui.interaction method with the tcl vwait mechanism intended for this purpose (instead of root.mainloop & .quit). 2. In gui.run, allow any existing interaction to terminate first.

Change “The program” to “Your program” in an IDLE “kill program?” message to make it clearer that the program referred to is the currently running user program, not IDLE itself.

bpo-24750 [https://bugs.python.org/issue24750]: Improve the appearance of the IDLE editor window status bar. Patch by Mark Roseman.

bpo-25313 [https://bugs.python.org/issue25313]: Change the handling of new built-in text color themes to better address the compatibility problem introduced by the addition of IDLE Dark. Consistently use the revised idleConf.CurrentTheme everywhere in idlelib.

bpo-24782 [https://bugs.python.org/issue24782]: Extension configuration is now a tab in the IDLE Preferences dialog rather than a separate dialog. The former tabs are now a sorted list. Patch by Mark Roseman.

bpo-22726 [https://bugs.python.org/issue22726]: Re-activate the config dialog help button with some content about the other buttons and the new IDLE Dark theme.

bpo-24820 [https://bugs.python.org/issue24820]: IDLE now has an “IDLE Dark” built-in text color theme. It is more or less IDLE Classic inverted, with a cobalt blue background. Strings, comments, keywords, … are still green, red, orange, … . To use it with IDLEs released before November 2015, hit the “Save as New Custom Theme” button and enter a new name, such as “Custom Dark”. The custom theme will work with any IDLE release, and can be modified.

bpo-25224 [https://bugs.python.org/issue25224]: README.txt is now an idlelib index for IDLE developers and curious users. The previous user content is now in the IDLE doc chapter. “IDLE” now means “Integrated Development and Learning Environment”.

bpo-24820 [https://bugs.python.org/issue24820]: Users can now set breakpoint colors in Settings -> Custom Highlighting. Original patch by Mark Roseman.

bpo-24972 [https://bugs.python.org/issue24972]: Inactive selection background now matches active selection background, as configured by users, on all systems. Found items are now always highlighted on Windows. Initial patch by Mark Roseman.

bpo-24570 [https://bugs.python.org/issue24570]: Idle: make calltip and completion boxes appear on Macs affected by a tk regression. Initial patch by Mark Roseman.

bpo-24988 [https://bugs.python.org/issue24988]: Idle ScrolledList context menus (used in debugger) now work on Mac Aqua. Patch by Mark Roseman.

bpo-24801 [https://bugs.python.org/issue24801]: Make right-click for context menu work on Mac Aqua. Patch by Mark Roseman.

bpo-25173 [https://bugs.python.org/issue25173]: Associate tkinter messageboxes with a specific widget. For Mac OSX, make them a “sheet”. Patch by Mark Roseman.

bpo-25198 [https://bugs.python.org/issue25198]: Enhance the initial html viewer now used for Idle Help. Properly indent fixed-pitch text (patch by Mark Roseman). Give code snippet a very Sphinx-like light blueish-gray background. Re-use initial width and height set by users for shell and editor. When the Table of Contents (TOC) menu is used, put the section header at the top of the screen.

bpo-25225 [https://bugs.python.org/issue25225]: Condense and rewrite Idle doc section on text colors.

bpo-21995 [https://bugs.python.org/issue21995]: Explain some differences between IDLE and console Python.

bpo-22820 [https://bugs.python.org/issue22820]: Explain need for print when running file from Idle editor.

bpo-25224 [https://bugs.python.org/issue25224]: Doc: augment Idle feature list and no-subprocess section.

bpo-25219 [https://bugs.python.org/issue25219]: Update doc for Idle command line options. Some were missing and notes were not correct.

bpo-24861 [https://bugs.python.org/issue24861]: Most of idlelib is private and subject to change. Use idleib.idle.* to start Idle. See idlelib.__init__.__doc__.

bpo-25199 [https://bugs.python.org/issue25199]: Idle: add synchronization comments for future maintainers.

bpo-16893 [https://bugs.python.org/issue16893]: Replace help.txt with help.html for Idle doc display. The new idlelib/help.html is rstripped Doc/build/html/library/idle.html. It looks better than help.txt and will better document Idle as released. The tkinter html viewer that works for this file was written by Mark Roseman. The now unused EditorWindow.HelpDialog class and helt.txt file are deprecated.

bpo-24199 [https://bugs.python.org/issue24199]: Deprecate unused idlelib.idlever with possible removal in 3.6.

bpo-24790 [https://bugs.python.org/issue24790]: Remove extraneous code (which also create 2 & 3 conflicts).

Documentation

bpo-22558 [https://bugs.python.org/issue22558]: Add remaining doc links to source code for Python-coded modules. Patch by Yoni Lavi.

bpo-12067 [https://bugs.python.org/issue12067]: Rewrite Comparisons section in the Expressions chapter of the language reference. Some of the details of comparing mixed types were incorrect or ambiguous. NotImplemented is only relevant at a lower level than the Expressions chapter. Added details of comparing range() objects, and default behaviour and consistency suggestions for user-defined classes. Patch from Andy Maier.

bpo-24952 [https://bugs.python.org/issue24952]: Clarify the default size argument of stack_size() in the « threading » and « _thread » modules. Patch from Mattip.

bpo-23725 [https://bugs.python.org/issue23725]: Overhaul tempfile docs. Note deprecated status of mktemp. Patch from Zbigniew Jędrzejewski-Szmek.

bpo-24808 [https://bugs.python.org/issue24808]: Update the types of some PyTypeObject fields. Patch by Joseph Weston.

bpo-22812 [https://bugs.python.org/issue22812]: Fix unittest discovery examples. Patch from Pam McA’Nulty.

Tests

bpo-25449 [https://bugs.python.org/issue25449]: Added tests for OrderedDict subclasses.

bpo-25099 [https://bugs.python.org/issue25099]: Make test_compileall not fail when an entry on sys.path cannot be written to (commonly seen in administrative installs on Windows).

bpo-23919 [https://bugs.python.org/issue23919]: Prevents assert dialogs appearing in the test suite.

PCbuild\rt.bat now accepts an unlimited number of arguments to pass along to regrtest.py. Previously there was a limit of 9.

Build

bpo-24915 [https://bugs.python.org/issue24915]: Add LLVM support for PGO builds and use the test suite to generate the profile data. Initial patch by Alecsandru Patrascu of Intel.

bpo-24910 [https://bugs.python.org/issue24910]: Windows MSIs now have unique display names.

bpo-24986 [https://bugs.python.org/issue24986]: It is now possible to build Python on Windows without errors when external libraries are not available.

Windows

bpo-25450 [https://bugs.python.org/issue25450]: Updates shortcuts to start Python in installation directory.

bpo-25164 [https://bugs.python.org/issue25164]: Changes default all-users install directory to match per-user directory.

bpo-25143 [https://bugs.python.org/issue25143]: Improves installer error messages for unsupported platforms.

bpo-25163 [https://bugs.python.org/issue25163]: Display correct directory in installer when using non-default settings.

bpo-25361 [https://bugs.python.org/issue25361]: Disables use of SSE2 instructions in Windows 32-bit build

bpo-25089 [https://bugs.python.org/issue25089]: Adds logging to installer for case where launcher is not selected on upgrade.

bpo-25165 [https://bugs.python.org/issue25165]: Windows uninstallation should not remove launcher if other versions remain

bpo-25112 [https://bugs.python.org/issue25112]: py.exe launcher is missing icons

bpo-25102 [https://bugs.python.org/issue25102]: Windows installer does not precompile for -O or -OO.

bpo-25081 [https://bugs.python.org/issue25081]: Makes Back button in installer go back to upgrade page when upgrading.

bpo-25091 [https://bugs.python.org/issue25091]: Increases font size of the installer.

bpo-25126 [https://bugs.python.org/issue25126]: Clarifies that the non-web installer will download some components.

bpo-25213 [https://bugs.python.org/issue25213]: Restores requestedExecutionLevel to manifest to disable UAC virtualization.

bpo-25022 [https://bugs.python.org/issue25022]: Removed very outdated PC/example_nt/ directory.

Tools/Demos

bpo-25440 [https://bugs.python.org/issue25440]: Fix output of python-config –extension-suffix.

Python 3.5.0 final

Release date: 2015-09-13

Build

bpo-25071 [https://bugs.python.org/issue25071]: Windows installer should not require TargetDir parameter when installing quietly.

Python 3.5.0 release candidate 4

Release date: 2015-09-09

Library

bpo-25029 [https://bugs.python.org/issue25029]: Fixes MemoryError in test_strptime.

Build

bpo-25027 [https://bugs.python.org/issue25027]: Reverts partial-static build options and adds vcruntime140.dll to Windows installation.

Python 3.5.0 release candidate 3

Release date: 2015-09-07

Core and Builtins

bpo-24305 [https://bugs.python.org/issue24305]: Prevent import subsystem stack frames from being counted by the warnings.warn(stacklevel=) parameter.

bpo-24912 [https://bugs.python.org/issue24912]: Prevent __class__ assignment to immutable built-in objects.

bpo-24975 [https://bugs.python.org/issue24975]: Fix AST compilation for PEP 448 syntax.

Library

bpo-24917 [https://bugs.python.org/issue24917]: time_strftime() buffer over-read.

bpo-24748 [https://bugs.python.org/issue24748]: To resolve a compatibility problem found with py2exe and pywin32, imp.load_dynamic() once again ignores previously loaded modules to support Python modules replacing themselves with extension modules. Patch by Petr Viktorin.

bpo-24635 [https://bugs.python.org/issue24635]: Fixed a bug in typing.py where isinstance([], typing.Iterable) would return True once, then False on subsequent calls.

bpo-24989 [https://bugs.python.org/issue24989]: Fixed buffer overread in BytesIO.readline() if a position is set beyond size. Based on patch by John Leitch.

bpo-24913 [https://bugs.python.org/issue24913]: Fix overrun error in deque.index(). Found by John Leitch and Bryce Darling.

Python 3.5.0 release candidate 2

Release date: 2015-08-25

Core and Builtins

bpo-24769 [https://bugs.python.org/issue24769]: Interpreter now starts properly when dynamic loading is disabled. Patch by Petr Viktorin.

bpo-21167 [https://bugs.python.org/issue21167]: NAN operations are now handled correctly when python is compiled with ICC even if -fp-model strict is not specified.

bpo-24492 [https://bugs.python.org/issue24492]: A « package » lacking a __name__ attribute when trying to perform a from .. import ... statement will trigger an ImportError instead of an AttributeError.

Library

bpo-24847 [https://bugs.python.org/issue24847]: Removes vcruntime140.dll dependency from Tcl/Tk.

bpo-24839 [https://bugs.python.org/issue24839]: platform._syscmd_ver raises DeprecationWarning

bpo-24867 [https://bugs.python.org/issue24867]: Fix Task.get_stack() for “async def” coroutines

Python 3.5.0 release candidate 1

Release date: 2015-08-09

Core and Builtins

bpo-24667 [https://bugs.python.org/issue24667]: Resize odict in all cases that the underlying dict resizes.

Library

bpo-24824 [https://bugs.python.org/issue24824]: Signatures of codecs.encode() and codecs.decode() now are compatible with pydoc.

bpo-24634 [https://bugs.python.org/issue24634]: Importing uuid should not try to load libc on Windows

bpo-24798 [https://bugs.python.org/issue24798]: _msvccompiler.py doesn’t properly support manifests

bpo-4395 [https://bugs.python.org/issue4395]: Better testing and documentation of binary operators. Patch by Martin Panter.

bpo-23973 [https://bugs.python.org/issue23973]: Update typing.py from GitHub repo.

bpo-23004 [https://bugs.python.org/issue23004]: mock_open() now reads binary data correctly when the type of read_data is bytes. Initial patch by Aaron Hill.

bpo-23888 [https://bugs.python.org/issue23888]: Handle fractional time in cookie expiry. Patch by ssh.

bpo-23652 [https://bugs.python.org/issue23652]: Make it possible to compile the select module against the libc headers from the Linux Standard Base, which do not include some EPOLL macros. Patch by Matt Frank.

bpo-22932 [https://bugs.python.org/issue22932]: Fix timezones in email.utils.formatdate. Patch from Dmitry Shachnev.

bpo-23779 [https://bugs.python.org/issue23779]: imaplib raises TypeError if authenticator tries to abort. Patch from Craig Holmquist.

bpo-23319 [https://bugs.python.org/issue23319]: Fix ctypes.BigEndianStructure, swap correctly bytes. Patch written by Matthieu Gautier.

bpo-23254 [https://bugs.python.org/issue23254]: Document how to close the TCPServer listening socket. Patch from Martin Panter.

bpo-19450 [https://bugs.python.org/issue19450]: Update Windows and OS X installer builds to use SQLite 3.8.11.

bpo-17527 [https://bugs.python.org/issue17527]: Add PATCH to wsgiref.validator. Patch from Luca Sbardella.

bpo-24791 [https://bugs.python.org/issue24791]: Fix grammar regression for call syntax: “g(*a or b)”.

IDLE

bpo-23672 [https://bugs.python.org/issue23672]: Allow Idle to edit and run files with astral chars in name. Patch by Mohd Sanad Zaki Rizvi.

bpo-24745 [https://bugs.python.org/issue24745]: Idle editor default font. Switch from Courier to platform-sensitive TkFixedFont. This should not affect current customized font selections. If there is a problem, edit $HOME/.idlerc/config-main.cfg and remove “fontxxx” entries from [Editor Window]. Patch by Mark Roseman.

bpo-21192 [https://bugs.python.org/issue21192]: Idle editor. When a file is run, put its name in the restart bar. Do not print false prompts. Original patch by Adnan Umer.

bpo-13884 [https://bugs.python.org/issue13884]: Idle menus. Remove tearoff lines. Patch by Roger Serwy.

Documentation

bpo-24129 [https://bugs.python.org/issue24129]: Clarify the reference documentation for name resolution. This includes removing the assumption that readers will be familiar with the name resolution scheme Python used prior to the introduction of lexical scoping for function namespaces. Patch by Ivan Levkivskyi.

bpo-20769 [https://bugs.python.org/issue20769]: Improve reload() docs. Patch by Dorian Pula.

bpo-23589 [https://bugs.python.org/issue23589]: Remove duplicate sentence from the FAQ. Patch by Yongzhi Pan.

bpo-24729 [https://bugs.python.org/issue24729]: Correct IO tutorial to match implementation regarding encoding parameter to open function.

Tests

bpo-24751 [https://bugs.python.org/issue24751]: When running regrtest with the -w command line option, a test run is no longer marked as a failure if all tests succeed when re-run.

Python 3.5.0 beta 4

Release date: 2015-07-26

Core and Builtins

bpo-23573 [https://bugs.python.org/issue23573]: Restored optimization of bytes.rfind() and bytearray.rfind() for single-byte argument on Linux.

bpo-24569 [https://bugs.python.org/issue24569]: Make PEP 448 dictionary evaluation more consistent.

bpo-24583 [https://bugs.python.org/issue24583]: Fix crash when set is mutated while being updated.

bpo-24407 [https://bugs.python.org/issue24407]: Fix crash when dict is mutated while being updated.

bpo-24619 [https://bugs.python.org/issue24619]: New approach for tokenizing async/await. As a consequence, it is now possible to have one-line “async def foo(): await ..” functions.

bpo-24687 [https://bugs.python.org/issue24687]: Plug refleak on SyntaxError in function parameters annotations.

bpo-15944 [https://bugs.python.org/issue15944]: memoryview: Allow arbitrary formats when casting to bytes. Patch by Martin Panter.

Library

bpo-23441 [https://bugs.python.org/issue23441]: rcompleter now prints a tab character instead of displaying possible completions for an empty word. Initial patch by Martin Sekera.

bpo-24683 [https://bugs.python.org/issue24683]: Fixed crashes in _json functions called with arguments of inappropriate type.

bpo-21697 [https://bugs.python.org/issue21697]: shutil.copytree() now correctly handles symbolic links that point to directories. Patch by Eduardo Seabra and Thomas Kluyver.

bpo-14373 [https://bugs.python.org/issue14373]: Fixed segmentation fault when gc.collect() is called during constructing lru_cache (C implementation).

bpo-24695 [https://bugs.python.org/issue24695]: Fix a regression in traceback.print_exception(). If exc_traceback is None we shouldn’t print a traceback header like described in the documentation.

bpo-24620 [https://bugs.python.org/issue24620]: Random.setstate() now validates the value of state last element.

bpo-22485 [https://bugs.python.org/issue22485]: Fixed an issue that caused inspect.getsource to return incorrect results on nested functions.

bpo-22153 [https://bugs.python.org/issue22153]: Improve unittest docs. Patch from Martin Panter and evilzero.

bpo-24580 [https://bugs.python.org/issue24580]: Symbolic group references to open group in re patterns now are explicitly forbidden as well as numeric group references.

bpo-24206 [https://bugs.python.org/issue24206]: Fixed __eq__ and __ne__ methods of inspect classes.

bpo-24631 [https://bugs.python.org/issue24631]: Fixed regression in the timeit module with multiline setup.

bpo-18622 [https://bugs.python.org/issue18622]: unittest.mock.mock_open().reset_mock would recurse infinitely. Patch from Nicola Palumbo and Laurent De Buyst.

bpo-23661 [https://bugs.python.org/issue23661]: unittest.mock side_effects can now be exceptions again. This was a regression vs Python 3.4. Patch from Ignacio Rossi

bpo-24608 [https://bugs.python.org/issue24608]: chunk.Chunk.read() now always returns bytes, not str.

bpo-18684 [https://bugs.python.org/issue18684]: Fixed reading out of the buffer in the re module.

bpo-24259 [https://bugs.python.org/issue24259]: tarfile now raises a ReadError if an archive is truncated inside a data segment.

bpo-15014 [https://bugs.python.org/issue15014]: SMTP.auth() and SMTP.login() now support RFC 4954’s optional initial-response argument to the SMTP AUTH command.

bpo-24669 [https://bugs.python.org/issue24669]: Fix inspect.getsource() for “async def” functions. Patch by Kai Groner.

bpo-24688 [https://bugs.python.org/issue24688]: ast.get_docstring() for “async def” functions.

Build

bpo-24603 [https://bugs.python.org/issue24603]: Update Windows builds and OS X 10.5 installer to use OpenSSL 1.0.2d.

Python 3.5.0 beta 3

Release date: 2015-07-05

Core and Builtins

bpo-24467 [https://bugs.python.org/issue24467]: Fixed possible buffer over-read in bytearray. The bytearray object now always allocates place for trailing null byte and it’s buffer now is always null-terminated.

Upgrade to Unicode 8.0.0.

bpo-24345 [https://bugs.python.org/issue24345]: Add Py_tp_finalize slot for the stable ABI.

bpo-24400 [https://bugs.python.org/issue24400]: Introduce a distinct type for PEP 492 coroutines; add types.CoroutineType, inspect.getcoroutinestate, inspect.getcoroutinelocals; coroutines no longer use CO_GENERATOR flag; sys.set_coroutine_wrapper works only for “async def” coroutines; inspect.iscoroutine no longer uses collections.abc.Coroutine, it’s intended to test for pure “async def” coroutines only; add new opcode: GET_YIELD_FROM_ITER; fix generators wrapper used in types.coroutine to be instance of collections.abc.Generator; collections.abc.Awaitable and collections.abc.Coroutine can no longer be used to detect generator-based coroutines–use inspect.isawaitable instead.

bpo-24450 [https://bugs.python.org/issue24450]: Add gi_yieldfrom to generators and cr_await to coroutines. Contributed by Benno Leslie and Yury Selivanov.

bpo-19235 [https://bugs.python.org/issue19235]: Add new RecursionError exception. Patch by Georg Brandl.

Library

bpo-21750 [https://bugs.python.org/issue21750]: mock_open.read_data can now be read from each instance, as it could in Python 3.3.

bpo-24552 [https://bugs.python.org/issue24552]: Fix use after free in an error case of the _pickle module.

bpo-24514 [https://bugs.python.org/issue24514]: tarfile now tolerates number fields consisting of only whitespace.

bpo-19176 [https://bugs.python.org/issue19176]: Fixed doctype() related bugs in C implementation of ElementTree. A deprecation warning no longer issued by XMLParser subclass with default doctype() method. Direct call of doctype() now issues a warning. Parser’s doctype() now is not called if target’s doctype() is called. Based on patch by Martin Panter.

bpo-20387 [https://bugs.python.org/issue20387]: Restore semantic round-trip correctness in tokenize/untokenize for tab-indented blocks.

bpo-24456 [https://bugs.python.org/issue24456]: Fixed possible buffer over-read in adpcm2lin() and lin2adpcm() functions of the audioop module.

bpo-24336 [https://bugs.python.org/issue24336]: The contextmanager decorator now works with functions with keyword arguments called « func » and « self ». Patch by Martin Panter.

bpo-24522 [https://bugs.python.org/issue24522]: Fix possible integer overflow in json accelerator module.

bpo-24489 [https://bugs.python.org/issue24489]: ensure a previously set C errno doesn’t disturb cmath.polar().

bpo-24408 [https://bugs.python.org/issue24408]: Fixed AttributeError in measure() and metrics() methods of tkinter.Font.

bpo-14373 [https://bugs.python.org/issue14373]: C implementation of functools.lru_cache() now can be used with methods.

bpo-24347 [https://bugs.python.org/issue24347]: Set KeyError if PyDict_GetItemWithError returns NULL.

bpo-24348 [https://bugs.python.org/issue24348]: Drop superfluous incref/decref.

bpo-24359 [https://bugs.python.org/issue24359]: Check for changed OrderedDict size during iteration.

bpo-24368 [https://bugs.python.org/issue24368]: Support keyword arguments in OrderedDict methods.

bpo-24362 [https://bugs.python.org/issue24362]: Simplify the C OrderedDict fast nodes resize logic.

bpo-24377 [https://bugs.python.org/issue24377]: Fix a ref leak in OrderedDict.__repr__.

bpo-24369 [https://bugs.python.org/issue24369]: Defend against key-changes during iteration.

Tests

bpo-24373 [https://bugs.python.org/issue24373]: _testmultiphase and xxlimited now use tp_traverse and tp_finalize to avoid reference leaks encountered when combining tp_dealloc with PyType_FromSpec (see bpo-16690 [https://bugs.python.org/issue16690] for details)

Documentation

bpo-24458 [https://bugs.python.org/issue24458]: Update documentation to cover multi-phase initialization for extension modules (PEP 489). Patch by Petr Viktorin.

bpo-24351 [https://bugs.python.org/issue24351]: Clarify what is meant by « identifier » in the context of string.Template instances.

Build

bpo-24432 [https://bugs.python.org/issue24432]: Update Windows builds and OS X 10.5 installer to use OpenSSL 1.0.2c.

Python 3.5.0 beta 2

Release date: 2015-05-31

Core and Builtins

bpo-24284 [https://bugs.python.org/issue24284]: The startswith and endswith methods of the str class no longer return True when finding the empty string and the indexes are completely out of range.

bpo-24115 [https://bugs.python.org/issue24115]: Update uses of PyObject_IsTrue(), PyObject_Not(), PyObject_IsInstance(), PyObject_RichCompareBool() and _PyDict_Contains() to check for and handle errors correctly.

bpo-24328 [https://bugs.python.org/issue24328]: Fix importing one character extension modules.

bpo-11205 [https://bugs.python.org/issue11205]: In dictionary displays, evaluate the key before the value.

bpo-24285 [https://bugs.python.org/issue24285]: Fixed regression that prevented importing extension modules from inside packages. Patch by Petr Viktorin.

Library

bpo-23247 [https://bugs.python.org/issue23247]: Fix a crash in the StreamWriter.reset() of CJK codecs.

bpo-24270 [https://bugs.python.org/issue24270]: Add math.isclose() and cmath.isclose() functions as per PEP 485. Contributed by Chris Barker and Tal Einat.

bpo-5633 [https://bugs.python.org/issue5633]: Fixed timeit when the statement is a string and the setup is not.

bpo-24326 [https://bugs.python.org/issue24326]: Fixed audioop.ratecv() with non-default weightB argument. Original patch by David Moore.

bpo-16991 [https://bugs.python.org/issue16991]: Add a C implementation of OrderedDict.

bpo-23934 [https://bugs.python.org/issue23934]: Fix inspect.signature to fail correctly for builtin types lacking signature information. Initial patch by James Powell.

Python 3.5.0 beta 1

Release date: 2015-05-24

Core and Builtins

bpo-24276 [https://bugs.python.org/issue24276]: Fixed optimization of property descriptor getter.

bpo-24268 [https://bugs.python.org/issue24268]: PEP 489: Multi-phase extension module initialization. Patch by Petr Viktorin.

bpo-23955 [https://bugs.python.org/issue23955]: Add pyvenv.cfg option to suppress registry/environment lookup for generating sys.path on Windows.

bpo-24257 [https://bugs.python.org/issue24257]: Fixed system error in the comparison of faked types.SimpleNamespace.

bpo-22939 [https://bugs.python.org/issue22939]: Fixed integer overflow in iterator object. Patch by Clement Rouault.

bpo-23985 [https://bugs.python.org/issue23985]: Fix a possible buffer overrun when deleting a slice from the front of a bytearray and then appending some other bytes data.

bpo-24102 [https://bugs.python.org/issue24102]: Fixed exception type checking in standard error handlers.

bpo-15027 [https://bugs.python.org/issue15027]: The UTF-32 encoder is now 3x to 7x faster.

bpo-23290 [https://bugs.python.org/issue23290]: Optimize set_merge() for cases where the target is empty. (Contributed by Serhiy Storchaka.)

bpo-2292 [https://bugs.python.org/issue2292]: PEP 448: Additional Unpacking Generalizations.

bpo-24096 [https://bugs.python.org/issue24096]: Make warnings.warn_explicit more robust against mutation of the warnings.filters list.

bpo-23996 [https://bugs.python.org/issue23996]: Avoid a crash when a delegated generator raises an unnormalized StopIteration exception. Patch by Stefan Behnel.

bpo-23910 [https://bugs.python.org/issue23910]: Optimize property() getter calls. Patch by Joe Jevnik.

bpo-23911 [https://bugs.python.org/issue23911]: Move path-based importlib bootstrap code to a separate frozen module.

bpo-24192 [https://bugs.python.org/issue24192]: Fix namespace package imports.

bpo-24022 [https://bugs.python.org/issue24022]: Fix tokenizer crash when processing undecodable source code.

bpo-9951 [https://bugs.python.org/issue9951]: Added a hex() method to bytes, bytearray, and memoryview.

bpo-22906 [https://bugs.python.org/issue22906]: PEP 479: Change StopIteration handling inside generators.

bpo-24017 [https://bugs.python.org/issue24017]: PEP 492: Coroutines with async and await syntax.

Library

bpo-14373 [https://bugs.python.org/issue14373]: Added C implementation of functools.lru_cache(). Based on patches by Matt Joiner and Alexey Kachayev.

bpo-24230 [https://bugs.python.org/issue24230]: The tempfile module now accepts bytes for prefix, suffix and dir parameters and returns bytes in such situations (matching the os module APIs).

bpo-22189 [https://bugs.python.org/issue22189]: collections.UserString now supports __getnewargs__(), __rmod__(), casefold(), format_map(), isprintable(), and maketrans(). Patch by Joe Jevnik.

bpo-24244 [https://bugs.python.org/issue24244]: Prevents termination when an invalid format string is encountered on Windows in strftime.

bpo-23973 [https://bugs.python.org/issue23973]: PEP 484: Add the typing module.

bpo-23086 [https://bugs.python.org/issue23086]: The collections.abc.Sequence() abstract base class added start and stop parameters to the index() mixin. Patch by Devin Jeanpierre.

bpo-20035 [https://bugs.python.org/issue20035]: Replaced the tkinter._fix module used for setting up the Tcl/Tk environment on Windows with a private function in the _tkinter module that makes no permanent changes to the environment.

bpo-24257 [https://bugs.python.org/issue24257]: Fixed segmentation fault in sqlite3.Row constructor with faked cursor type.

bpo-15836 [https://bugs.python.org/issue15836]: assertRaises(), assertRaisesRegex(), assertWarns() and assertWarnsRegex() assertments now check the type of the first argument to prevent possible user error. Based on patch by Daniel Wagner-Hall.

bpo-9858 [https://bugs.python.org/issue9858]: Add missing method stubs to _io.RawIOBase. Patch by Laura Rupprecht.

bpo-22955 [https://bugs.python.org/issue22955]: attrgetter, itemgetter and methodcaller objects in the operator module now support pickling. Added readable and evaluable repr for these objects. Based on patch by Josh Rosenberg.

bpo-22107 [https://bugs.python.org/issue22107]: tempfile.gettempdir() and tempfile.mkdtemp() now try again when a directory with the chosen name already exists on Windows as well as on Unix. tempfile.mkstemp() now fails early if parent directory is not valid (not exists or is a file) on Windows.

bpo-23780 [https://bugs.python.org/issue23780]: Improved error message in os.path.join() with single argument.

bpo-6598 [https://bugs.python.org/issue6598]: Increased time precision and random number range in email.utils.make_msgid() to strengthen the uniqueness of the message ID.

bpo-24091 [https://bugs.python.org/issue24091]: Fixed various crashes in corner cases in C implementation of ElementTree.

bpo-21931 [https://bugs.python.org/issue21931]: msilib.FCICreate() now raises TypeError in the case of a bad argument instead of a ValueError with a bogus FCI error number. Patch by Jeffrey Armstrong.

bpo-13866 [https://bugs.python.org/issue13866]: quote_via argument added to urllib.parse.urlencode.

bpo-20098 [https://bugs.python.org/issue20098]: New mangle_from policy option for email, default True for compat32, but False for all other policies.

bpo-24211 [https://bugs.python.org/issue24211]: The email library now supports RFC 6532: it can generate headers using utf-8 instead of encoded words.

bpo-16314 [https://bugs.python.org/issue16314]: Added support for the LZMA compression in distutils.

bpo-21804 [https://bugs.python.org/issue21804]: poplib now supports RFC 6856 (UTF8).

bpo-18682 [https://bugs.python.org/issue18682]: Optimized pprint functions for builtin scalar types.

bpo-22027 [https://bugs.python.org/issue22027]: smtplib now supports RFC 6531 (SMTPUTF8).

bpo-23488 [https://bugs.python.org/issue23488]: Random generator objects now consume 2x less memory on 64-bit.

bpo-1322 [https://bugs.python.org/issue1322]: platform.dist() and platform.linux_distribution() functions are now deprecated. Initial patch by Vajrasky Kok.

bpo-22486 [https://bugs.python.org/issue22486]: Added the math.gcd() function. The fractions.gcd() function now is deprecated. Based on patch by Mark Dickinson.

bpo-24064 [https://bugs.python.org/issue24064]: Property() docstrings are now writeable. (Patch by Berker Peksag.)

bpo-22681 [https://bugs.python.org/issue22681]: Added support for the koi8_t encoding.

bpo-22682 [https://bugs.python.org/issue22682]: Added support for the kz1048 encoding.

bpo-23796 [https://bugs.python.org/issue23796]: peek and read1 methods of BufferedReader now raise ValueError if they called on a closed object. Patch by John Hergenroeder.

bpo-21795 [https://bugs.python.org/issue21795]: smtpd now supports the 8BITMIME extension whenever the new decode_data constructor argument is set to False.

bpo-24155 [https://bugs.python.org/issue24155]: optimize heapq.heapify() for better cache performance when heapifying large lists.

bpo-21800 [https://bugs.python.org/issue21800]: imaplib now supports RFC 5161 (enable), RFC 6855 (utf8/internationalized email) and automatically encodes non-ASCII usernames and passwords to UTF8.

bpo-20274 [https://bugs.python.org/issue20274]: When calling a _sqlite.Connection, it now complains if passed any keyword arguments. Previously it silently ignored them.

bpo-20274 [https://bugs.python.org/issue20274]: Remove ignored and erroneous « kwargs » parameters from three METH_VARARGS methods on _sqlite.Connection.

bpo-24134 [https://bugs.python.org/issue24134]: assertRaises(), assertRaisesRegex(), assertWarns() and assertWarnsRegex() checks now emits a deprecation warning when callable is None or keyword arguments except msg is passed in the context manager mode.

bpo-24018 [https://bugs.python.org/issue24018]: Add a collections.abc.Generator abstract base class. Contributed by Stefan Behnel.

bpo-23880 [https://bugs.python.org/issue23880]: Tkinter’s getint() and getdouble() now support Tcl_Obj. Tkinter’s getdouble() now supports any numbers (in particular int).

bpo-22619 [https://bugs.python.org/issue22619]: Added negative limit support in the traceback module. Based on patch by Dmitry Kazakov.

bpo-24094 [https://bugs.python.org/issue24094]: Fix possible crash in json.encode with poorly behaved dict subclasses.

bpo-9246 [https://bugs.python.org/issue9246]: On POSIX, os.getcwd() now supports paths longer than 1025 bytes. Patch written by William Orr.

bpo-17445 [https://bugs.python.org/issue17445]: add difflib.diff_bytes() to support comparison of byte strings (fixes a regression from Python 2).

bpo-23917 [https://bugs.python.org/issue23917]: Fall back to sequential compilation when ProcessPoolExecutor doesn’t exist. Patch by Claudiu Popa.

bpo-23008 [https://bugs.python.org/issue23008]: Fixed resolving attributes with boolean value is False in pydoc.

Fix asyncio issue 235: LifoQueue and PriorityQueue’s put didn’t increment unfinished tasks (this bug was introduced when JoinableQueue was merged with Queue).

bpo-23908 [https://bugs.python.org/issue23908]: os functions now reject paths with embedded null character on Windows instead of silently truncating them.

bpo-23728 [https://bugs.python.org/issue23728]: binascii.crc_hqx() could return an integer outside of the range 0-0xffff for empty data.

bpo-23887 [https://bugs.python.org/issue23887]: urllib.error.HTTPError now has a proper repr() representation. Patch by Berker Peksag.

asyncio: New event loop APIs: set_task_factory() and get_task_factory().

asyncio: async() function is deprecated in favour of ensure_future().

bpo-24178 [https://bugs.python.org/issue24178]: asyncio.Lock, Condition, Semaphore, and BoundedSemaphore support new “async with” syntax. Contributed by Yury Selivanov.

bpo-24179 [https://bugs.python.org/issue24179]: Support “async for” for asyncio.StreamReader. Contributed by Yury Selivanov.

bpo-24184 [https://bugs.python.org/issue24184]: Add AsyncIterator and AsyncIterable ABCs to collections.abc. Contributed by Yury Selivanov.

bpo-22547 [https://bugs.python.org/issue22547]: Implement informative __repr__ for inspect.BoundArguments. Contributed by Yury Selivanov.

bpo-24190 [https://bugs.python.org/issue24190]: Implement inspect.BoundArgument.apply_defaults() method. Contributed by Yury Selivanov.

bpo-20691 [https://bugs.python.org/issue20691]: Add “follow_wrapped” argument to inspect.Signature.from_callable() and inspect.signature(). Contributed by Yury Selivanov.

bpo-24248 [https://bugs.python.org/issue24248]: Deprecate inspect.Signature.from_function() and inspect.Signature.from_builtin().

bpo-23898 [https://bugs.python.org/issue23898]: Fix inspect.classify_class_attrs() to support attributes with overloaded __eq__ and __bool__. Patch by Mike Bayer.

bpo-24298 [https://bugs.python.org/issue24298]: Fix inspect.signature() to correctly unwrap wrappers around bound methods.

IDLE

bpo-23184 [https://bugs.python.org/issue23184]: remove unused names and imports in idlelib. Initial patch by Al Sweigart.

Tests

bpo-21520 [https://bugs.python.org/issue21520]: test_zipfile no longer fails if the word “bad” appears anywhere in the name of the current directory.

bpo-9517 [https://bugs.python.org/issue9517]: Move script_helper into the support package. Patch by Christie Wilson.

Documentation

bpo-22155 [https://bugs.python.org/issue22155]: Add File Handlers subsection with createfilehandler to tkinter doc. Remove obsolete example from FAQ. Patch by Martin Panter.

bpo-24029 [https://bugs.python.org/issue24029]: Document the name binding behavior for submodule imports.

bpo-24077 [https://bugs.python.org/issue24077]: Fix typo in man page for -I command option: -s, not -S

Tools/Demos

bpo-24000 [https://bugs.python.org/issue24000]: Improved Argument Clinic’s mapping of converters to legacy « format units ». Updated the documentation to match.

bpo-24001 [https://bugs.python.org/issue24001]: Argument Clinic converters now use accept={type} instead of types={“type”} to specify the types the converter accepts.

bpo-23330 [https://bugs.python.org/issue23330]: h2py now supports arbitrary filenames in #include.

bpo-24031 [https://bugs.python.org/issue24031]: make patchcheck now supports git checkouts, too.

Python 3.5.0 alpha 4

Release date: 2015-04-19

Core and Builtins

bpo-22980 [https://bugs.python.org/issue22980]: Under Linux, GNU/KFreeBSD and the Hurd, C extensions now include the architecture triplet in the extension name, to make it easy to test builds for different ABIs in the same working tree. Under OS X, the extension name now includes PEP 3149-style information.

bpo-22631 [https://bugs.python.org/issue22631]: Added Linux-specific socket constant CAN_RAW_FD_FRAMES. Patch courtesy of Joe Jevnik.

bpo-23731 [https://bugs.python.org/issue23731]: Implement PEP 488: removal of .pyo files.

bpo-23726 [https://bugs.python.org/issue23726]: Don’t enable GC for user subclasses of non-GC types that don’t add any new fields. Patch by Eugene Toder.

bpo-23309 [https://bugs.python.org/issue23309]: Avoid a deadlock at shutdown if a daemon thread is aborted while it is holding a lock to a buffered I/O object, and the main thread tries to use the same I/O object (typically stdout or stderr). A fatal error is emitted instead.

bpo-22977 [https://bugs.python.org/issue22977]: Fixed formatting Windows error messages on Wine. Patch by Martin Panter.

bpo-23466 [https://bugs.python.org/issue23466]: %c, %o, %x, and %X in bytes formatting now raise TypeError on non-integer input.

bpo-24044 [https://bugs.python.org/issue24044]: Fix possible null pointer dereference in list.sort in out of memory conditions.

bpo-21354 [https://bugs.python.org/issue21354]: PyCFunction_New function is exposed by python DLL again.

Library

bpo-23840 [https://bugs.python.org/issue23840]: tokenize.open() now closes the temporary binary file on error to fix a resource warning.

bpo-16914 [https://bugs.python.org/issue16914]: new debuglevel 2 in smtplib adds timestamps to debug output.

bpo-7159 [https://bugs.python.org/issue7159]: urllib.request now supports sending auth credentials automatically after the first 401. This enhancement is a superset of the enhancement from bpo-19494 [https://bugs.python.org/issue19494] and supersedes that change.

bpo-23703 [https://bugs.python.org/issue23703]: Fix a regression in urljoin() introduced in 901e4e52b20a. Patch by Demian Brecht.

bpo-4254 [https://bugs.python.org/issue4254]: Adds _curses.update_lines_cols(). Patch by Arnon Yaari

bpo-19933 [https://bugs.python.org/issue19933]: Provide default argument for ndigits in round. Patch by Vajrasky Kok.

bpo-23193 [https://bugs.python.org/issue23193]: Add a numeric_owner parameter to tarfile.TarFile.extract and tarfile.TarFile.extractall. Patch by Michael Vogt and Eric Smith.

bpo-23342 [https://bugs.python.org/issue23342]: Add a subprocess.run() function than returns a CalledProcess instance for a more consistent API than the existing call* functions.

bpo-21217 [https://bugs.python.org/issue21217]: inspect.getsourcelines() now tries to compute the start and end lines from the code object, fixing an issue when a lambda function is used as decorator argument. Patch by Thomas Ballinger and Allison Kaptur.

bpo-24521 [https://bugs.python.org/issue24521]: Fix possible integer overflows in the pickle module.

bpo-22931 [https://bugs.python.org/issue22931]: Allow “[“ and “]” in cookie values.

The keywords attribute of functools.partial is now always a dictionary.

bpo-23811 [https://bugs.python.org/issue23811]: Add missing newline to the PyCompileError error message. Patch by Alex Shkop.

bpo-21116 [https://bugs.python.org/issue21116]: Avoid blowing memory when allocating a multiprocessing shared array that’s larger than 50% of the available RAM. Patch by Médéric Boquien.

bpo-22982 [https://bugs.python.org/issue22982]: Improve BOM handling when seeking to multiple positions of a writable text file.

bpo-23464 [https://bugs.python.org/issue23464]: Removed deprecated asyncio JoinableQueue.

bpo-23529 [https://bugs.python.org/issue23529]: Limit the size of decompressed data when reading from GzipFile, BZ2File or LZMAFile. This defeats denial of service attacks using compressed bombs (i.e. compressed payloads which decompress to a huge size). Patch by Martin Panter and Nikolaus Rath.

bpo-21859 [https://bugs.python.org/issue21859]: Added Python implementation of io.FileIO.

bpo-23865 [https://bugs.python.org/issue23865]: close() methods in multiple modules now are idempotent and more robust at shutdown. If they need to release multiple resources, all are released even if errors occur.

bpo-23400 [https://bugs.python.org/issue23400]: Raise same exception on both Python 2 and 3 if sem_open is not available. Patch by Davin Potts.

bpo-10838 [https://bugs.python.org/issue10838]: The subprocess now module includes SubprocessError and TimeoutError in its list of exported names for the users wild enough to use from subprocess import *.

bpo-23411 [https://bugs.python.org/issue23411]: Added DefragResult, ParseResult, SplitResult, DefragResultBytes, ParseResultBytes, and SplitResultBytes to urllib.parse.__all__. Patch by Martin Panter.

bpo-23881 [https://bugs.python.org/issue23881]: urllib.request.ftpwrapper constructor now closes the socket if the FTP connection failed to fix a ResourceWarning.

bpo-23853 [https://bugs.python.org/issue23853]: socket.socket.sendall() does no more reset the socket timeout each time data is sent successfully. The socket timeout is now the maximum total duration to send all data.

bpo-22721 [https://bugs.python.org/issue22721]: An order of multiline pprint output of set or dict containing orderable and non-orderable elements no longer depends on iteration order of set or dict.

bpo-15133 [https://bugs.python.org/issue15133]: _tkinter.tkapp.getboolean() now supports Tcl_Obj and always returns bool. tkinter.BooleanVar now validates input values (accepted bool, int, str, and Tcl_Obj). tkinter.BooleanVar.get() now always returns bool.

bpo-10590 [https://bugs.python.org/issue10590]: xml.sax.parseString() now supports string argument.

bpo-23338 [https://bugs.python.org/issue23338]: Fixed formatting ctypes error messages on Cygwin. Patch by Makoto Kato.

bpo-15582 [https://bugs.python.org/issue15582]: inspect.getdoc() now follows inheritance chains.

bpo-2175 [https://bugs.python.org/issue2175]: SAX parsers now support a character stream of InputSource object.

bpo-16840 [https://bugs.python.org/issue16840]: Tkinter now supports 64-bit integers added in Tcl 8.4 and arbitrary precision integers added in Tcl 8.5.

bpo-23834 [https://bugs.python.org/issue23834]: Fix socket.sendto(), use the C Py_ssize_t type to store the result of sendto() instead of the C int type.

bpo-23618 [https://bugs.python.org/issue23618]: socket.socket.connect() now waits until the connection completes instead of raising InterruptedError if the connection is interrupted by signals, signal handlers don’t raise an exception and the socket is blocking or has a timeout. socket.socket.connect() still raise InterruptedError for non-blocking sockets.

bpo-21526 [https://bugs.python.org/issue21526]: Tkinter now supports new boolean type in Tcl 8.5.

bpo-23836 [https://bugs.python.org/issue23836]: Fix the faulthandler module to handle reentrant calls to its signal handlers.

bpo-23838 [https://bugs.python.org/issue23838]: linecache now clears the cache and returns an empty result on MemoryError.

bpo-10395 [https://bugs.python.org/issue10395]: Added os.path.commonpath(). Implemented in posixpath and ntpath. Based on patch by Rafik Draoui.

bpo-23611 [https://bugs.python.org/issue23611]: Serializing more « lookupable » objects (such as unbound methods or nested classes) now are supported with pickle protocols < 4.

bpo-13583 [https://bugs.python.org/issue13583]: sqlite3.Row now supports slice indexing.

bpo-18473 [https://bugs.python.org/issue18473]: Fixed 2to3 and 3to2 compatible pickle mappings. Fixed ambiguous reverse mappings. Added many new mappings. Import mapping is no longer applied to modules already mapped with full name mapping.

bpo-23485 [https://bugs.python.org/issue23485]: select.select() is now retried automatically with the recomputed timeout when interrupted by a signal, except if the signal handler raises an exception. This change is part of the PEP 475.

bpo-23752 [https://bugs.python.org/issue23752]: When built from an existing file descriptor, io.FileIO() now only calls fstat() once. Before fstat() was called twice, which was not necessary.

bpo-23704 [https://bugs.python.org/issue23704]: collections.deque() objects now support __add__, __mul__, and __imul__().

bpo-23171 [https://bugs.python.org/issue23171]: csv.Writer.writerow() now supports arbitrary iterables.

bpo-23745 [https://bugs.python.org/issue23745]: The new email header parser now handles duplicate MIME parameter names without error, similar to how get_param behaves.

bpo-22117 [https://bugs.python.org/issue22117]: Fix os.utime(), it now rounds the timestamp towards minus infinity (-inf) instead of rounding towards zero.

bpo-23310 [https://bugs.python.org/issue23310]: Fix MagicMock’s initializer to work with __methods__, just like configure_mock(). Patch by Kasia Jachim.

Build

bpo-23817 [https://bugs.python.org/issue23817]: FreeBSD now uses « 1.0 » in the SOVERSION as other operating systems, instead of just « 1 ».

bpo-23501 [https://bugs.python.org/issue23501]: Argument Clinic now generates code into separate files by default.

Tests

bpo-23799 [https://bugs.python.org/issue23799]: Added test.support.start_threads() for running and cleaning up multiple threads.

bpo-22390 [https://bugs.python.org/issue22390]: test.regrtest now emits a warning if temporary files or directories are left after running a test.

Tools/Demos

bpo-18128 [https://bugs.python.org/issue18128]: pygettext now uses standard +NNNN format in the POT-Creation-Date header.

bpo-23935 [https://bugs.python.org/issue23935]: Argument Clinic’s understanding of format units accepting bytes, bytearrays, and buffers is now consistent with both the documentation and the implementation.

bpo-23944 [https://bugs.python.org/issue23944]: Argument Clinic now wraps long impl prototypes at column 78.

bpo-20586 [https://bugs.python.org/issue20586]: Argument Clinic now ensures that functions without docstrings have signatures.

bpo-23492 [https://bugs.python.org/issue23492]: Argument Clinic now generates argument parsing code with PyArg_Parse instead of PyArg_ParseTuple if possible.

bpo-23500 [https://bugs.python.org/issue23500]: Argument Clinic is now smarter about generating the « #ifndef » (empty) definition of the methoddef macro: it’s only generated once, even if Argument Clinic processes the same symbol multiple times, and it’s emitted at the end of all processing rather than immediately after the first use.

C API

bpo-23998 [https://bugs.python.org/issue23998]: PyImport_ReInitLock() now checks for lock allocation error

Python 3.5.0 alpha 3

Release date: 2015-03-28

Core and Builtins

bpo-23573 [https://bugs.python.org/issue23573]: Increased performance of string search operations (str.find, str.index, str.count, the in operator, str.split, str.partition) with arguments of different kinds (UCS1, UCS2, UCS4).

bpo-23753 [https://bugs.python.org/issue23753]: Python doesn’t support anymore platforms without stat() or fstat(), these functions are always required.

bpo-23681 [https://bugs.python.org/issue23681]: The -b option now affects comparisons of bytes with int.

bpo-23632 [https://bugs.python.org/issue23632]: Memoryviews now allow tuple indexing (including for multi-dimensional memoryviews).

bpo-23192 [https://bugs.python.org/issue23192]: Fixed generator lambdas. Patch by Bruno Cauet.

bpo-23629 [https://bugs.python.org/issue23629]: Fix the default __sizeof__ implementation for variable-sized objects.

Library

bpo-14260 [https://bugs.python.org/issue14260]: The groupindex attribute of regular expression pattern object now is non-modifiable mapping.

bpo-23792 [https://bugs.python.org/issue23792]: Ignore KeyboardInterrupt when the pydoc pager is active. This mimics the behavior of the standard unix pagers, and prevents pipepager from shutting down while the pager itself is still running.

bpo-23775 [https://bugs.python.org/issue23775]: pprint() of OrderedDict now outputs the same representation as repr().

bpo-23765 [https://bugs.python.org/issue23765]: Removed IsBadStringPtr calls in ctypes

bpo-22364 [https://bugs.python.org/issue22364]: Improved some re error messages using regex for hints.

bpo-23742 [https://bugs.python.org/issue23742]: ntpath.expandvars() no longer loses unbalanced single quotes.

bpo-21717 [https://bugs.python.org/issue21717]: The zipfile.ZipFile.open function now supports “x” (exclusive creation) mode.

bpo-21802 [https://bugs.python.org/issue21802]: The reader in BufferedRWPair now is closed even when closing writer failed in BufferedRWPair.close().

bpo-23622 [https://bugs.python.org/issue23622]: Unknown escapes in regular expressions that consist of '\' and ASCII letter now raise a deprecation warning and will be forbidden in Python 3.6.

bpo-23671 [https://bugs.python.org/issue23671]: string.Template now allows specifying the « self » parameter as a keyword argument. string.Formatter now allows specifying the « self » and the « format_string » parameters as keyword arguments.

bpo-23502 [https://bugs.python.org/issue23502]: The pprint module now supports mapping proxies.

bpo-17530 [https://bugs.python.org/issue17530]: pprint now wraps long bytes objects and bytearrays.

bpo-22687 [https://bugs.python.org/issue22687]: Fixed some corner cases in breaking words in tetxtwrap. Got rid of quadratic complexity in breaking long words.

bpo-4727 [https://bugs.python.org/issue4727]: The copy module now uses pickle protocol 4 (PEP 3154) and supports copying of instances of classes whose __new__ method takes keyword-only arguments.

bpo-23491 [https://bugs.python.org/issue23491]: Added a zipapp module to support creating executable zip file archives of Python code. Registered « .pyz » and « .pyzw » extensions on Windows for these archives (PEP 441).

bpo-23657 [https://bugs.python.org/issue23657]: Avoid explicit checks for str in zipapp, adding support for pathlib.Path objects as arguments.

bpo-23688 [https://bugs.python.org/issue23688]: Added support of arbitrary bytes-like objects and avoided unnecessary copying of memoryview in gzip.GzipFile.write(). Original patch by Wolfgang Maier.

bpo-23252 [https://bugs.python.org/issue23252]: Added support for writing ZIP files to unseekable streams.

bpo-23647 [https://bugs.python.org/issue23647]: Increase imaplib’s MAXLINE to accommodate modern mailbox sizes.

bpo-23539 [https://bugs.python.org/issue23539]: If body is None, http.client.HTTPConnection.request now sets Content-Length to 0 for PUT, POST, and PATCH headers to avoid 411 errors from some web servers.

bpo-22351 [https://bugs.python.org/issue22351]: The nntplib.NNTP constructor no longer leaves the connection and socket open until the garbage collector cleans them up. Patch by Martin Panter.

bpo-23704 [https://bugs.python.org/issue23704]: collections.deque() objects now support methods for index(), insert(), and copy(). This allows deques to be registered as a MutableSequence and it improves their substitutability for lists.

bpo-23715 [https://bugs.python.org/issue23715]: signal.sigwaitinfo() and signal.sigtimedwait() are now retried when interrupted by a signal not in the sigset parameter, if the signal handler does not raise an exception. signal.sigtimedwait() recomputes the timeout with a monotonic clock when it is retried.

bpo-23001 [https://bugs.python.org/issue23001]: Few functions in modules mmap, ossaudiodev, socket, ssl, and codecs, that accepted only read-only bytes-like object now accept writable bytes-like object too.

bpo-23646 [https://bugs.python.org/issue23646]: If time.sleep() is interrupted by a signal, the sleep is now retried with the recomputed delay, except if the signal handler raises an exception (PEP 475).

bpo-23136 [https://bugs.python.org/issue23136]: _strptime now uniformly handles all days in week 0, including Dec 30 of previous year. Based on patch by Jim Carroll.

bpo-23700 [https://bugs.python.org/issue23700]: Iterator of NamedTemporaryFile now keeps a reference to NamedTemporaryFile instance. Patch by Bohuslav Kabrda.

bpo-22903 [https://bugs.python.org/issue22903]: The fake test case created by unittest.loader when it fails importing a test module is now picklable.

bpo-22181 [https://bugs.python.org/issue22181]: On Linux, os.urandom() now uses the new getrandom() syscall if available, syscall introduced in the Linux kernel 3.17. It is more reliable and more secure, because it avoids the need of a file descriptor and waits until the kernel has enough entropy.

bpo-2211 [https://bugs.python.org/issue2211]: Updated the implementation of the http.cookies.Morsel class. Setting attributes key, value and coded_value directly now is deprecated. update() and setdefault() now transform and check keys. Comparing for equality now takes into account attributes key, value and coded_value. copy() now returns a Morsel, not a dict. repr() now contains all attributes. Optimized checking keys and quoting values. Added new tests. Original patch by Demian Brecht.

bpo-18983 [https://bugs.python.org/issue18983]: Allow selection of output units in timeit. Patch by Julian Gindi.

bpo-23631 [https://bugs.python.org/issue23631]: Fix traceback.format_list when a traceback has been mutated.

bpo-23568 [https://bugs.python.org/issue23568]: Add rdivmod support to MagicMock() objects. Patch by Håkan Lövdahl.

bpo-2052 [https://bugs.python.org/issue2052]: Add charset parameter to HtmlDiff.make_file().

bpo-23668 [https://bugs.python.org/issue23668]: Support os.truncate and os.ftruncate on Windows.

bpo-23138 [https://bugs.python.org/issue23138]: Fixed parsing cookies with absent keys or values in cookiejar. Patch by Demian Brecht.

bpo-23051 [https://bugs.python.org/issue23051]: multiprocessing.Pool methods imap() and imap_unordered() now handle exceptions raised by an iterator. Patch by Alon Diamant and Davin Potts.

bpo-23581 [https://bugs.python.org/issue23581]: Add matmul support to MagicMock. Patch by Håkan Lövdahl.

bpo-23566 [https://bugs.python.org/issue23566]: enable(), register(), dump_traceback() and dump_traceback_later() functions of faulthandler now accept file descriptors. Patch by Wei Wu.

bpo-22928 [https://bugs.python.org/issue22928]: Disabled HTTP header injections in http.client. Original patch by Demian Brecht.

bpo-23615 [https://bugs.python.org/issue23615]: Modules bz2, tarfile and tokenize now can be reloaded with imp.reload(). Patch by Thomas Kluyver.

bpo-23605 [https://bugs.python.org/issue23605]: os.walk() now calls os.scandir() instead of os.listdir(). The usage of os.scandir() reduces the number of calls to os.stat(). Initial patch written by Ben Hoyt.

Build

bpo-23585 [https://bugs.python.org/issue23585]: make patchcheck will ensure the interpreter is built.

Tests

bpo-23583 [https://bugs.python.org/issue23583]: Added tests for standard IO streams in IDLE.

bpo-22289 [https://bugs.python.org/issue22289]: Prevent test_urllib2net failures due to ftp connection timeout.

Tools/Demos

bpo-22826 [https://bugs.python.org/issue22826]: The result of open() in Tools/freeze/bkfile.py is now better compatible with regular files (in particular it now supports the context management protocol).

Python 3.5.0 alpha 2

Release date: 2015-03-09

Core and Builtins

bpo-23571 [https://bugs.python.org/issue23571]: PyObject_Call() and PyCFunction_Call() now raise a SystemError if a function returns a result and raises an exception. The SystemError is chained to the previous exception.

Library

bpo-22524 [https://bugs.python.org/issue22524]: New os.scandir() function, part of the PEP 471: « os.scandir() function – a better and faster directory iterator ». Patch written by Ben Hoyt.

bpo-23103 [https://bugs.python.org/issue23103]: Reduced the memory consumption of IPv4Address and IPv6Address.

bpo-21793 [https://bugs.python.org/issue21793]: BaseHTTPRequestHandler again logs response code as numeric, not as stringified enum. Patch by Demian Brecht.

bpo-23476 [https://bugs.python.org/issue23476]: In the ssl module, enable OpenSSL’s X509_V_FLAG_TRUSTED_FIRST flag on certificate stores when it is available.

bpo-23576 [https://bugs.python.org/issue23576]: Avoid stalling in SSL reads when EOF has been reached in the SSL layer but the underlying connection hasn’t been closed.

bpo-23504 [https://bugs.python.org/issue23504]: Added an __all__ to the types module.

bpo-23563 [https://bugs.python.org/issue23563]: Optimized utility functions in urllib.parse.

bpo-7830 [https://bugs.python.org/issue7830]: Flatten nested functools.partial.

bpo-20204 [https://bugs.python.org/issue20204]: Added the __module__ attribute to _tkinter classes.

bpo-19980 [https://bugs.python.org/issue19980]: Improved help() for non-recognized strings. help(“”) now shows the help on str. help(“help”) now shows the help on help(). Original patch by Mark Lawrence.

bpo-23521 [https://bugs.python.org/issue23521]: Corrected pure python implementation of timedelta division.

Eliminated OverflowError from timedelta * float for some floats; Corrected rounding in timedelta true division.

bpo-21619 [https://bugs.python.org/issue21619]: Popen objects no longer leave a zombie after exit in the with statement if the pipe was broken. Patch by Martin Panter.

bpo-22936 [https://bugs.python.org/issue22936]: Make it possible to show local variables in tracebacks for both the traceback module and unittest.

bpo-15955 [https://bugs.python.org/issue15955]: Add an option to limit the output size in bz2.decompress(). Patch by Nikolaus Rath.

bpo-6639 [https://bugs.python.org/issue6639]: Module-level turtle functions no longer raise TclError after closing the window.

bpo-814253 [https://bugs.python.org/issue814253]: Group references and conditional group references now work in lookbehind assertions in regular expressions. (See also: bpo-9179 [https://bugs.python.org/issue9179])

bpo-23215 [https://bugs.python.org/issue23215]: Multibyte codecs with custom error handlers that ignores errors consumed too much memory and raised SystemError or MemoryError. Original patch by Aleksi Torhamo.

bpo-5700 [https://bugs.python.org/issue5700]: io.FileIO() called flush() after closing the file. flush() was not called in close() if closefd=False.

bpo-23374 [https://bugs.python.org/issue23374]: Fixed pydoc failure with non-ASCII files when stdout encoding differs from file system encoding (e.g. on Mac OS).

bpo-23481 [https://bugs.python.org/issue23481]: Remove RC4 from the SSL module’s default cipher list.

bpo-21548 [https://bugs.python.org/issue21548]: Fix pydoc.synopsis() and pydoc.apropos() on modules with empty docstrings.

bpo-22885 [https://bugs.python.org/issue22885]: Fixed arbitrary code execution vulnerability in the dbm.dumb module. Original patch by Claudiu Popa.

bpo-23239 [https://bugs.python.org/issue23239]: ssl.match_hostname() now supports matching of IP addresses.

bpo-23146 [https://bugs.python.org/issue23146]: Fix mishandling of absolute Windows paths with forward slashes in pathlib.

bpo-23096 [https://bugs.python.org/issue23096]: Pickle representation of floats with protocol 0 now is the same for both Python and C implementations.

bpo-19105 [https://bugs.python.org/issue19105]: pprint now more efficiently uses free space at the right.

bpo-14910 [https://bugs.python.org/issue14910]: Add allow_abbrev parameter to argparse.ArgumentParser. Patch by Jonathan Paugh, Steven Bethard, paul j3 and Daniel Eriksson.

bpo-21717 [https://bugs.python.org/issue21717]: tarfile.open() now supports “x” (exclusive creation) mode.

bpo-23344 [https://bugs.python.org/issue23344]: marshal.dumps() is now 20-25% faster on average.

bpo-20416 [https://bugs.python.org/issue20416]: marshal.dumps() with protocols 3 and 4 is now 40-50% faster on average.

bpo-23421 [https://bugs.python.org/issue23421]: Fixed compression in tarfile CLI. Patch by wdv4758h.

bpo-23367 [https://bugs.python.org/issue23367]: Fix possible overflows in the unicodedata module.

bpo-23361 [https://bugs.python.org/issue23361]: Fix possible overflow in Windows subprocess creation code.

logging.handlers.QueueListener now takes a respect_handler_level keyword argument which, if set to True, will pass messages to handlers taking handler levels into account.

bpo-19705 [https://bugs.python.org/issue19705]: turtledemo now has a visual sorting algorithm demo. Original patch from Jason Yeo.

bpo-23801 [https://bugs.python.org/issue23801]: Fix issue where cgi.FieldStorage did not always ignore the entire preamble to a multipart body.

Build

bpo-23445 [https://bugs.python.org/issue23445]: pydebug builds now use « gcc -Og » where possible, to make the resulting executable faster.

bpo-23686 [https://bugs.python.org/issue23686]: Update OS X 10.5 installer build to use OpenSSL 1.0.2a.

C API

bpo-20204 [https://bugs.python.org/issue20204]: Deprecation warning is now raised for builtin types without the __module__ attribute.

Windows

bpo-23465 [https://bugs.python.org/issue23465]: Implement PEP 486 - Make the Python Launcher aware of virtual environments. Patch by Paul Moore.

bpo-23437 [https://bugs.python.org/issue23437]: Make user scripts directory versioned on Windows. Patch by Paul Moore.

Python 3.5.0 alpha 1

Release date: 2015-02-08

Core and Builtins

bpo-23285 [https://bugs.python.org/issue23285]: PEP 475 - EINTR handling.

bpo-22735 [https://bugs.python.org/issue22735]: Fix many edge cases (including crashes) involving custom mro() implementations.

bpo-22896 [https://bugs.python.org/issue22896]: Avoid using PyObject_AsCharBuffer(), PyObject_AsReadBuffer() and PyObject_AsWriteBuffer().

bpo-21295 [https://bugs.python.org/issue21295]: Revert some changes (bpo-16795 [https://bugs.python.org/issue16795]) to AST line numbers and column offsets that constituted a regression.

bpo-22986 [https://bugs.python.org/issue22986]: Allow changing an object’s __class__ between a dynamic type and static type in some cases.

bpo-15859 [https://bugs.python.org/issue15859]: PyUnicode_EncodeFSDefault(), PyUnicode_EncodeMBCS() and PyUnicode_EncodeCodePage() now raise an exception if the object is not a Unicode object. For PyUnicode_EncodeFSDefault(), it was already the case on platforms other than Windows. Patch written by Campbell Barton.

bpo-21408 [https://bugs.python.org/issue21408]: The default __ne__() now returns NotImplemented if __eq__() returned NotImplemented. Original patch by Martin Panter.

bpo-23321 [https://bugs.python.org/issue23321]: Fixed a crash in str.decode() when error handler returned replacement string longer than malformed input data.

bpo-22286 [https://bugs.python.org/issue22286]: The « backslashreplace » error handlers now works with decoding and translating.

bpo-23253 [https://bugs.python.org/issue23253]: Delay-load ShellExecute[AW] in os.startfile for reduced startup overhead on Windows.

bpo-22038 [https://bugs.python.org/issue22038]: pyatomic.h now uses stdatomic.h or GCC built-in functions for atomic memory access if available. Patch written by Vitor de Lima and Gustavo Temple.

bpo-20284 [https://bugs.python.org/issue20284]: %-interpolation (aka printf) formatting added for bytes and bytearray.

bpo-23048 [https://bugs.python.org/issue23048]: Fix jumping out of an infinite while loop in the pdb.

bpo-20335 [https://bugs.python.org/issue20335]: bytes constructor now raises TypeError when encoding or errors is specified with non-string argument. Based on patch by Renaud Blanch.

bpo-22834 [https://bugs.python.org/issue22834]: If the current working directory ends up being set to a non-existent directory then import will no longer raise FileNotFoundError.

bpo-22869 [https://bugs.python.org/issue22869]: Move the interpreter startup & shutdown code to a new dedicated pylifecycle.c module

bpo-22847 [https://bugs.python.org/issue22847]: Improve method cache efficiency.

bpo-22335 [https://bugs.python.org/issue22335]: Fix crash when trying to enlarge a bytearray to 0x7fffffff bytes on a 32-bit platform.

bpo-22653 [https://bugs.python.org/issue22653]: Fix an assertion failure in debug mode when doing a reentrant dict insertion in debug mode.

bpo-22643 [https://bugs.python.org/issue22643]: Fix integer overflow in Unicode case operations (upper, lower, title, swapcase, casefold).

bpo-17636 [https://bugs.python.org/issue17636]: Circular imports involving relative imports are now supported.

bpo-22604 [https://bugs.python.org/issue22604]: Fix assertion error in debug mode when dividing a complex number by (nan+0j).

bpo-21052 [https://bugs.python.org/issue21052]: Do not raise ImportWarning when sys.path_hooks or sys.meta_path are set to None.

bpo-16518 [https://bugs.python.org/issue16518]: Use “bytes-like object required” in error messages that previously used the far more cryptic « “x” does not support the buffer protocol.

bpo-22470 [https://bugs.python.org/issue22470]: Fixed integer overflow issues in « backslashreplace », « xmlcharrefreplace », and « surrogatepass » error handlers.

bpo-22540 [https://bugs.python.org/issue22540]: speed up PyObject_IsInstance and PyObject_IsSubclass in the common case that the second argument has metaclass type.

bpo-18711 [https://bugs.python.org/issue18711]: Add a new PyErr_FormatV function, similar to PyErr_Format but accepting a va_list argument.

bpo-22520 [https://bugs.python.org/issue22520]: Fix overflow checking when generating the repr of a unicode object.

bpo-22519 [https://bugs.python.org/issue22519]: Fix overflow checking in PyBytes_Repr.

bpo-22518 [https://bugs.python.org/issue22518]: Fix integer overflow issues in latin-1 encoding.

bpo-16324 [https://bugs.python.org/issue16324]: _charset parameter of MIMEText now also accepts email.charset.Charset instances. Initial patch by Claude Paroz.

bpo-1764286 [https://bugs.python.org/issue1764286]: Fix inspect.getsource() to support decorated functions. Patch by Claudiu Popa.

bpo-18554 [https://bugs.python.org/issue18554]: os.__all__ includes posix functions.

bpo-21391 [https://bugs.python.org/issue21391]: Use os.path.abspath in the shutil module.

bpo-11471 [https://bugs.python.org/issue11471]: avoid generating a JUMP_FORWARD instruction at the end of an if-block if there is no else-clause. Original patch by Eugene Toder.

bpo-22215 [https://bugs.python.org/issue22215]: Now ValueError is raised instead of TypeError when str or bytes argument contains not permitted null character or byte.

bpo-22258 [https://bugs.python.org/issue22258]: Fix the internal function set_inheritable() on Illumos. This platform exposes the function ioctl(FIOCLEX), but calling it fails with errno is ENOTTY: « Inappropriate ioctl for device ». set_inheritable() now falls back to the slower fcntl() (F_GETFD and then F_SETFD).

bpo-21389 [https://bugs.python.org/issue21389]: Displaying the __qualname__ of the underlying function in the repr of a bound method.

bpo-22206 [https://bugs.python.org/issue22206]: Using pthread, PyThread_create_key() now sets errno to ENOMEM and returns -1 (error) on integer overflow.

bpo-20184 [https://bugs.python.org/issue20184]: Argument Clinic based signature introspection added for 30 of the builtin functions.

bpo-22116 [https://bugs.python.org/issue22116]: C functions and methods (of the “builtin_function_or_method” type) can now be weakref’ed. Patch by Wei Wu.

bpo-22077 [https://bugs.python.org/issue22077]: Improve index error messages for bytearrays, bytes, lists, and tuples by adding “or slices”. Added “, not <typename>” for bytearrays. Original patch by Claudiu Popa.

bpo-20179 [https://bugs.python.org/issue20179]: Apply Argument Clinic to bytes and bytearray. Patch by Tal Einat.

bpo-22082 [https://bugs.python.org/issue22082]: Clear interned strings in slotdefs.

Upgrade Unicode database to Unicode 7.0.0.

bpo-21897 [https://bugs.python.org/issue21897]: Fix a crash with the f_locals attribute with closure variables when frame.clear() has been called.

bpo-21205 [https://bugs.python.org/issue21205]: Add a new __qualname__ attribute to generator, the qualified name, and use it in the representation of a generator (repr(gen)). The default name of the generator (__name__ attribute) is now get from the function instead of the code. Use gen.gi_code.co_name to get the name of the code.

bpo-21669 [https://bugs.python.org/issue21669]: With the aid of heuristics in SyntaxError.__init__, the parser now attempts to generate more meaningful (or at least more search engine friendly) error messages when « exec » and « print » are used as statements.

bpo-21642 [https://bugs.python.org/issue21642]: In the conditional if-else expression, allow an integer written with no space between itself and the else keyword (e.g. True if 42else False) to be valid syntax.

bpo-21523 [https://bugs.python.org/issue21523]: Fix over-pessimistic computation of the stack effect of some opcodes in the compiler. This also fixes a quadratic compilation time issue noticeable when compiling code with a large number of « and » and « or » operators.

bpo-21418 [https://bugs.python.org/issue21418]: Fix a crash in the builtin function super() when called without argument and without current frame (ex: embedded Python).

bpo-21425 [https://bugs.python.org/issue21425]: Fix flushing of standard streams in the interactive interpreter.

bpo-21435 [https://bugs.python.org/issue21435]: In rare cases, when running finalizers on objects in cyclic trash a bad pointer dereference could occur due to a subtle flaw in internal iteration logic.

bpo-21377 [https://bugs.python.org/issue21377]: PyBytes_Concat() now tries to concatenate in-place when the first argument has a reference count of 1. Patch by Nikolaus Rath.

bpo-20355 [https://bugs.python.org/issue20355]: -W command line options now have higher priority than the PYTHONWARNINGS environment variable. Patch by Arfrever.

bpo-21274 [https://bugs.python.org/issue21274]: Define PATH_MAX for GNU/Hurd in Python/pythonrun.c.

bpo-20904 [https://bugs.python.org/issue20904]: Support setting FPU precision on m68k.

bpo-21209 [https://bugs.python.org/issue21209]: Fix sending tuples to custom generator objects with the yield from syntax.

bpo-21193 [https://bugs.python.org/issue21193]: pow(a, b, c) now raises ValueError rather than TypeError when b is negative. Patch by Josh Rosenberg.

bpo-21176 [https://bugs.python.org/issue21176]: PEP 465: Add the “@” operator for matrix multiplication.

bpo-21134 [https://bugs.python.org/issue21134]: Fix segfault when str is called on an uninitialized UnicodeEncodeError, UnicodeDecodeError, or UnicodeTranslateError object.

bpo-19537 [https://bugs.python.org/issue19537]: Fix PyUnicode_DATA() alignment under m68k. Patch by Andreas Schwab.

bpo-20929 [https://bugs.python.org/issue20929]: Add a type cast to avoid shifting a negative number.

bpo-20731 [https://bugs.python.org/issue20731]: Properly position in source code files even if they are opened in text mode. Patch by Serhiy Storchaka.

bpo-20637 [https://bugs.python.org/issue20637]: Key-sharing now also works for instance dictionaries of subclasses. Patch by Peter Ingebretson.

bpo-8297 [https://bugs.python.org/issue8297]: Attributes missing from modules now include the module name in the error text. Original patch by ysj.ray.

bpo-19995 [https://bugs.python.org/issue19995]: %c, %o, %x, and %X now raise TypeError on non-integer input.

bpo-19655 [https://bugs.python.org/issue19655]: The ASDL parser - used by the build process to generate code for managing the Python AST in C - was rewritten. The new parser is self contained and does not require to carry long the spark.py parser-generator library; spark.py was removed from the source base.

bpo-12546 [https://bugs.python.org/issue12546]: Allow \x00 to be used as a fill character when using str, int, float, and complex __format__ methods.

bpo-20480 [https://bugs.python.org/issue20480]: Add ipaddress.reverse_pointer. Patch by Leon Weber.

bpo-13598 [https://bugs.python.org/issue13598]: Modify string.Formatter to support auto-numbering of replacement fields. It now matches the behavior of str.format() in this regard. Patches by Phil Elson and Ramchandra Apte.

bpo-8931 [https://bugs.python.org/issue8931]: Make alternate formatting (“#”) for type “c” raise an exception. In versions prior to 3.5, “#” with “c” had no effect. Now specifying it is an error. Patch by Torsten Landschoff.

bpo-23165 [https://bugs.python.org/issue23165]: Perform overflow checks before allocating memory in the _Py_char2wchar function.

Library

bpo-23399 [https://bugs.python.org/issue23399]: pyvenv creates relative symlinks where possible.

bpo-20289 [https://bugs.python.org/issue20289]: cgi.FieldStorage() now supports the context management protocol.

bpo-13128 [https://bugs.python.org/issue13128]: Print response headers for CONNECT requests when debuglevel > 0. Patch by Demian Brecht.

bpo-15381 [https://bugs.python.org/issue15381]: Optimized io.BytesIO to make less allocations and copyings.

bpo-22818 [https://bugs.python.org/issue22818]: Splitting on a pattern that could match an empty string now raises a warning. Patterns that can only match empty strings are now rejected.

bpo-23099 [https://bugs.python.org/issue23099]: Closing io.BytesIO with exported buffer is rejected now to prevent corrupting exported buffer.

bpo-23326 [https://bugs.python.org/issue23326]: Removed __ne__ implementations. Since fixing default __ne__ implementation in bpo-21408 [https://bugs.python.org/issue21408] they are redundant.

bpo-23363 [https://bugs.python.org/issue23363]: Fix possible overflow in itertools.permutations.

bpo-23364 [https://bugs.python.org/issue23364]: Fix possible overflow in itertools.product.

bpo-23366 [https://bugs.python.org/issue23366]: Fixed possible integer overflow in itertools.combinations.

bpo-23369 [https://bugs.python.org/issue23369]: Fixed possible integer overflow in _json.encode_basestring_ascii.

bpo-23353 [https://bugs.python.org/issue23353]: Fix the exception handling of generators in PyEval_EvalFrameEx(). At entry, save or swap the exception state even if PyEval_EvalFrameEx() is called with throwflag=0. At exit, the exception state is now always restored or swapped, not only if why is WHY_YIELD or WHY_RETURN. Patch co-written with Antoine Pitrou.

bpo-14099 [https://bugs.python.org/issue14099]: Restored support of writing ZIP files to tellable but non-seekable streams.

bpo-14099 [https://bugs.python.org/issue14099]: Writing to ZipFile and reading multiple ZipExtFiles is threadsafe now.

bpo-19361 [https://bugs.python.org/issue19361]: JSON decoder now raises JSONDecodeError instead of ValueError.

bpo-18518 [https://bugs.python.org/issue18518]: timeit now rejects statements which can’t be compiled outside a function or a loop (e.g. « return » or « break »).

bpo-23094 [https://bugs.python.org/issue23094]: Fixed readline with frames in Python implementation of pickle.

bpo-23268 [https://bugs.python.org/issue23268]: Fixed bugs in the comparison of ipaddress classes.

bpo-21408 [https://bugs.python.org/issue21408]: Removed incorrect implementations of __ne__() which didn’t returned NotImplemented if __eq__() returned NotImplemented. The default __ne__() now works correctly.

bpo-19996 [https://bugs.python.org/issue19996]: email.feedparser.FeedParser now handles (malformed) headers with no key rather than assuming the body has started.

bpo-20188 [https://bugs.python.org/issue20188]: Support Application-Layer Protocol Negotiation (ALPN) in the ssl module.

bpo-23133 [https://bugs.python.org/issue23133]: Pickling of ipaddress objects now produces more compact and portable representation.

bpo-23248 [https://bugs.python.org/issue23248]: Update ssl error codes from latest OpenSSL git master.

bpo-23266 [https://bugs.python.org/issue23266]: Much faster implementation of ipaddress.collapse_addresses() when there are many non-consecutive addresses.

bpo-23098 [https://bugs.python.org/issue23098]: 64-bit dev_t is now supported in the os module.

bpo-21817 [https://bugs.python.org/issue21817]: When an exception is raised in a task submitted to a ProcessPoolExecutor, the remote traceback is now displayed in the parent process. Patch by Claudiu Popa.

bpo-15955 [https://bugs.python.org/issue15955]: Add an option to limit output size when decompressing LZMA data. Patch by Nikolaus Rath and Martin Panter.

bpo-23250 [https://bugs.python.org/issue23250]: In the http.cookies module, capitalize « HttpOnly » and « Secure » as they are written in the standard.

bpo-23063 [https://bugs.python.org/issue23063]: In the distutils” check command, fix parsing of reST with code or code-block directives.

bpo-23209 [https://bugs.python.org/issue23209]: selectors.BaseSelector.get_key() now raises a RuntimeError if the selector is closed. And selectors.BaseSelector.close() now clears its internal reference to the selector mapping to break a reference cycle. Initial patch written by Martin Richard. (See also: bpo-23225 [https://bugs.python.org/issue23225])

bpo-17911 [https://bugs.python.org/issue17911]: Provide a way to seed the linecache for a PEP-302 module without actually loading the code.

bpo-17911 [https://bugs.python.org/issue17911]: Provide a new object API for traceback, including the ability to not lookup lines at all until the traceback is actually rendered, without any trace of the original objects being kept alive.

bpo-19777 [https://bugs.python.org/issue19777]: Provide a home() classmethod on Path objects. Contributed by Victor Salgado and Mayank Tripathi.

bpo-23206 [https://bugs.python.org/issue23206]: Make json.dumps(..., ensure_ascii=False) as fast as the default case of ensure_ascii=True. Patch by Naoki Inada.

bpo-23185 [https://bugs.python.org/issue23185]: Add math.inf and math.nan constants.

bpo-23186 [https://bugs.python.org/issue23186]: Add ssl.SSLObject.shared_ciphers() and ssl.SSLSocket.shared_ciphers() to fetch the client’s list ciphers sent at handshake.

bpo-23143 [https://bugs.python.org/issue23143]: Remove compatibility with OpenSSLs older than 0.9.8.

bpo-23132 [https://bugs.python.org/issue23132]: Improve performance and introspection support of comparison methods created by functool.total_ordering.

bpo-19776 [https://bugs.python.org/issue19776]: Add an expanduser() method on Path objects.

bpo-23112 [https://bugs.python.org/issue23112]: Fix SimpleHTTPServer to correctly carry the query string and fragment when it redirects to add a trailing slash.

bpo-21793 [https://bugs.python.org/issue21793]: Added http.HTTPStatus enums (i.e. HTTPStatus.OK, HTTPStatus.NOT_FOUND). Patch by Demian Brecht.

bpo-23093 [https://bugs.python.org/issue23093]: In the io, module allow more operations to work on detached streams.

bpo-23111 [https://bugs.python.org/issue23111]: In the ftplib, make ssl.PROTOCOL_SSLv23 the default protocol version.

bpo-22585 [https://bugs.python.org/issue22585]: On OpenBSD 5.6 and newer, os.urandom() now calls getentropy(), instead of reading /dev/urandom, to get pseudo-random bytes.

bpo-19104 [https://bugs.python.org/issue19104]: pprint now produces evaluable output for wrapped strings.

bpo-23071 [https://bugs.python.org/issue23071]: Added missing names to codecs.__all__. Patch by Martin Panter.

bpo-22783 [https://bugs.python.org/issue22783]: Pickling now uses the NEWOBJ opcode instead of the NEWOBJ_EX opcode if possible.

bpo-15513 [https://bugs.python.org/issue15513]: Added a __sizeof__ implementation for pickle classes.

bpo-19858 [https://bugs.python.org/issue19858]: pickletools.optimize() now aware of the MEMOIZE opcode, can produce more compact result and no longer produces invalid output if input data contains MEMOIZE opcodes together with PUT or BINPUT opcodes.

bpo-22095 [https://bugs.python.org/issue22095]: Fixed HTTPConnection.set_tunnel with default port. The port value in the host header was set to « None ». Patch by Demian Brecht.

bpo-23016 [https://bugs.python.org/issue23016]: A warning no longer produces an AttributeError when the program is run with pythonw.exe.

bpo-21775 [https://bugs.python.org/issue21775]: shutil.copytree(): fix crash when copying to VFAT. An exception handler assumed that OSError objects always have a “winerror” attribute. That is not the case, so the exception handler itself raised AttributeError when run on Linux (and, presumably, any other non-Windows OS). Patch by Greg Ward.

bpo-1218234 [https://bugs.python.org/issue1218234]: Fix inspect.getsource() to load updated source of reloaded module. Initial patch by Berker Peksag.

bpo-21740 [https://bugs.python.org/issue21740]: Support wrapped callables in doctest. Patch by Claudiu Popa.

bpo-23009 [https://bugs.python.org/issue23009]: Make sure selectors.EpollSelecrtor.select() works when no FD is registered.

bpo-22959 [https://bugs.python.org/issue22959]: In the constructor of http.client.HTTPSConnection, prefer the context’s check_hostname attribute over the check_hostname parameter.

bpo-22696 [https://bugs.python.org/issue22696]: Add function sys.is_finalizing() to know about interpreter shutdown.

bpo-16043 [https://bugs.python.org/issue16043]: Add a default limit for the amount of data xmlrpclib.gzip_decode will return. This resolves CVE-2013-1753.

bpo-14099 [https://bugs.python.org/issue14099]: ZipFile.open() no longer reopen the underlying file. Objects returned by ZipFile.open() can now operate independently of the ZipFile even if the ZipFile was created by passing in a file-like object as the first argument to the constructor.

bpo-22966 [https://bugs.python.org/issue22966]: Fix __pycache__ pyc file name clobber when pyc_compile is asked to compile a source file containing multiple dots in the source file name.

bpo-21971 [https://bugs.python.org/issue21971]: Update turtledemo doc and add module to the index.

bpo-21032 [https://bugs.python.org/issue21032]: Fixed socket leak if HTTPConnection.getresponse() fails. Original patch by Martin Panter.

bpo-22407 [https://bugs.python.org/issue22407]: Deprecated the use of re.LOCALE flag with str patterns or re.ASCII. It was newer worked.

bpo-22902 [https://bugs.python.org/issue22902]: The « ip » command is now used on Linux to determine MAC address in uuid.getnode(). Pach by Bruno Cauet.

bpo-22960 [https://bugs.python.org/issue22960]: Add a context argument to xmlrpclib.ServerProxy constructor.

bpo-22389 [https://bugs.python.org/issue22389]: Add contextlib.redirect_stderr().

bpo-21356 [https://bugs.python.org/issue21356]: Make ssl.RAND_egd() optional to support LibreSSL. The availability of the function is checked during the compilation. Patch written by Bernard Spil.

bpo-22915 [https://bugs.python.org/issue22915]: SAX parser now supports files opened with file descriptor or bytes path.

bpo-22609 [https://bugs.python.org/issue22609]: Constructors and update methods of mapping classes in the collections module now accept the self keyword argument.

bpo-22940 [https://bugs.python.org/issue22940]: Add readline.append_history_file.

bpo-19676 [https://bugs.python.org/issue19676]: Added the « namereplace » error handler.

bpo-22788 [https://bugs.python.org/issue22788]: Add context parameter to logging.handlers.HTTPHandler.

bpo-22921 [https://bugs.python.org/issue22921]: Allow SSLContext to take the hostname parameter even if OpenSSL doesn’t support SNI.

bpo-22894 [https://bugs.python.org/issue22894]: TestCase.subTest() would cause the test suite to be stopped when in failfast mode, even in the absence of failures.

bpo-22796 [https://bugs.python.org/issue22796]: HTTP cookie parsing is now stricter, in order to protect against potential injection attacks.

bpo-22370 [https://bugs.python.org/issue22370]: Windows detection in pathlib is now more robust.

bpo-22841 [https://bugs.python.org/issue22841]: Reject coroutines in asyncio add_signal_handler(). Patch by Ludovic.Gasc.

bpo-19494 [https://bugs.python.org/issue19494]: Added urllib.request.HTTPBasicPriorAuthHandler. Patch by Matej Cepl.

bpo-22578 [https://bugs.python.org/issue22578]: Added attributes to the re.error class.

bpo-22849 [https://bugs.python.org/issue22849]: Fix possible double free in the io.TextIOWrapper constructor.

bpo-12728 [https://bugs.python.org/issue12728]: Different Unicode characters having the same uppercase but different lowercase are now matched in case-insensitive regular expressions.

bpo-22821 [https://bugs.python.org/issue22821]: Fixed fcntl() with integer argument on 64-bit big-endian platforms.

bpo-21650 [https://bugs.python.org/issue21650]: Add an --sort-keys option to json.tool CLI.

bpo-22824 [https://bugs.python.org/issue22824]: Updated reprlib output format for sets to use set literals. Patch contributed by Berker Peksag.

bpo-22824 [https://bugs.python.org/issue22824]: Updated reprlib output format for arrays to display empty arrays without an unnecessary empty list. Suggested by Serhiy Storchaka.

bpo-22406 [https://bugs.python.org/issue22406]: Fixed the uu_codec codec incorrectly ported to 3.x. Based on patch by Martin Panter.

bpo-17293 [https://bugs.python.org/issue17293]: uuid.getnode() now determines MAC address on AIX using netstat. Based on patch by Aivars Kalvāns.

bpo-22769 [https://bugs.python.org/issue22769]: Fixed ttk.Treeview.tag_has() when called without arguments.

bpo-22417 [https://bugs.python.org/issue22417]: Verify certificates by default in httplib (PEP 476).

bpo-22775 [https://bugs.python.org/issue22775]: Fixed unpickling of http.cookies.SimpleCookie with protocol 2 and above. Patch by Tim Graham.

bpo-22776 [https://bugs.python.org/issue22776]: Brought excluded code into the scope of a try block in SysLogHandler.emit().

bpo-22665 [https://bugs.python.org/issue22665]: Add missing get_terminal_size and SameFileError to shutil.__all__.

bpo-6623 [https://bugs.python.org/issue6623]: Remove deprecated Netrc class in the ftplib module. Patch by Matt Chaput.

bpo-17381 [https://bugs.python.org/issue17381]: Fixed handling of case-insensitive ranges in regular expressions.

bpo-22410 [https://bugs.python.org/issue22410]: Module level functions in the re module now cache compiled locale-dependent regular expressions taking into account the locale.

bpo-22759 [https://bugs.python.org/issue22759]: Query methods on pathlib.Path() (exists(), is_dir(), etc.) now return False when the underlying stat call raises NotADirectoryError.

bpo-8876 [https://bugs.python.org/issue8876]: distutils now falls back to copying files when hard linking doesn’t work. This allows use with special filesystems such as VirtualBox shared folders.

bpo-22217 [https://bugs.python.org/issue22217]: Implemented reprs of classes in the zipfile module.

bpo-22457 [https://bugs.python.org/issue22457]: Honour load_tests in the start_dir of discovery.

bpo-18216 [https://bugs.python.org/issue18216]: gettext now raises an error when a .mo file has an unsupported major version number. Patch by Aaron Hill.

bpo-13918 [https://bugs.python.org/issue13918]: Provide a locale.delocalize() function which can remove locale-specific number formatting from a string representing a number, without then converting it to a specific type. Patch by Cédric Krier.

bpo-22676 [https://bugs.python.org/issue22676]: Make the pickling of global objects which don’t have a __module__ attribute less slow.

bpo-18853 [https://bugs.python.org/issue18853]: Fixed ResourceWarning in shlex.__nain__.

bpo-9351 [https://bugs.python.org/issue9351]: Defaults set with set_defaults on an argparse subparser are no longer ignored when also set on the parent parser.

bpo-7559 [https://bugs.python.org/issue7559]: unittest test loading ImportErrors are reported as import errors with their import exception rather than as attribute errors after the import has already failed.

bpo-19746 [https://bugs.python.org/issue19746]: Make it possible to examine the errors from unittest discovery without executing the test suite. The new errors attribute on TestLoader exposes these non-fatal errors encountered during discovery.

bpo-21991 [https://bugs.python.org/issue21991]: Make email.headerregistry’s header “params” attributes be read-only (MappingProxyType). Previously the dictionary was modifiable but a new one was created on each access of the attribute.

bpo-22638 [https://bugs.python.org/issue22638]: SSLv3 is now disabled throughout the standard library. It can still be enabled by instantiating a SSLContext manually.

bpo-22641 [https://bugs.python.org/issue22641]: In asyncio, the default SSL context for client connections is now created using ssl.create_default_context(), for stronger security.

bpo-17401 [https://bugs.python.org/issue17401]: Include closefd in io.FileIO repr.

bpo-21338 [https://bugs.python.org/issue21338]: Add silent mode for compileall. quiet parameters of compile_{dir, file, path} functions now have a multilevel value. Also, -q option of the CLI now have a multilevel value. Patch by Thomas Kluyver.

bpo-20152 [https://bugs.python.org/issue20152]: Convert the array and cmath modules to Argument Clinic.

bpo-18643 [https://bugs.python.org/issue18643]: Add socket.socketpair() on Windows.

bpo-22435 [https://bugs.python.org/issue22435]: Fix a file descriptor leak when socketserver bind fails.

bpo-13096 [https://bugs.python.org/issue13096]: Fixed segfault in CTypes POINTER handling of large values.

bpo-11694 [https://bugs.python.org/issue11694]: Raise ConversionError in xdrlib as documented. Patch by Filip Gruszczyński and Claudiu Popa.

bpo-19380 [https://bugs.python.org/issue19380]: Optimized parsing of regular expressions.

bpo-1519638 [https://bugs.python.org/issue1519638]: Now unmatched groups are replaced with empty strings in re.sub() and re.subn().

bpo-18615 [https://bugs.python.org/issue18615]: sndhdr.what/whathdr now return a namedtuple.

bpo-22462 [https://bugs.python.org/issue22462]: Fix pyexpat’s creation of a dummy frame to make it appear in exception tracebacks.

bpo-21965 [https://bugs.python.org/issue21965]: Add support for in-memory SSL to the ssl module. Patch by Geert Jansen.

bpo-21173 [https://bugs.python.org/issue21173]: Fix len() on a WeakKeyDictionary when .clear() was called with an iterator alive.

bpo-11866 [https://bugs.python.org/issue11866]: Eliminated race condition in the computation of names for new threads.

bpo-21905 [https://bugs.python.org/issue21905]: Avoid RuntimeError in pickle.whichmodule() when sys.modules is mutated while iterating. Patch by Olivier Grisel.

bpo-11271 [https://bugs.python.org/issue11271]: concurrent.futures.Executor.map() now takes a chunksize argument to allow batching of tasks in child processes and improve performance of ProcessPoolExecutor. Patch by Dan O’Reilly.

bpo-21883 [https://bugs.python.org/issue21883]: os.path.join() and os.path.relpath() now raise a TypeError with more helpful error message for unsupported or mismatched types of arguments.

bpo-22219 [https://bugs.python.org/issue22219]: The zipfile module CLI now adds entries for directories (including empty directories) in ZIP file.

bpo-22449 [https://bugs.python.org/issue22449]: In the ssl.SSLContext.load_default_certs, consult the environmental variables SSL_CERT_DIR and SSL_CERT_FILE on Windows.

bpo-22508 [https://bugs.python.org/issue22508]: The email.__version__ variable has been removed; the email code is no longer shipped separately from the stdlib, and __version__ hasn’t been updated in several releases.

bpo-20076 [https://bugs.python.org/issue20076]: Added non derived UTF-8 aliases to locale aliases table.

bpo-20079 [https://bugs.python.org/issue20079]: Added locales supported in glibc 2.18 to locale alias table.

bpo-20218 [https://bugs.python.org/issue20218]: Added convenience methods read_text/write_text and read_bytes/ write_bytes to pathlib.Path objects.

bpo-22396 [https://bugs.python.org/issue22396]: On 32-bit AIX platform, don’t expose os.posix_fadvise() nor os.posix_fallocate() because their prototypes in system headers are wrong.

bpo-22517 [https://bugs.python.org/issue22517]: When an io.BufferedRWPair object is deallocated, clear its weakrefs.

bpo-22437 [https://bugs.python.org/issue22437]: Number of capturing groups in regular expression is no longer limited by 100.

bpo-17442 [https://bugs.python.org/issue17442]: InteractiveInterpreter now displays the full chained traceback in its showtraceback method, to match the built in interactive interpreter.

bpo-23392 [https://bugs.python.org/issue23392]: Added tests for marshal C API that works with FILE*.

bpo-10510 [https://bugs.python.org/issue10510]: distutils register and upload methods now use HTML standards compliant CRLF line endings.

bpo-9850 [https://bugs.python.org/issue9850]: Fixed macpath.join() for empty first component. Patch by Oleg Oshmyan.

bpo-5309 [https://bugs.python.org/issue5309]: distutils” build and build_ext commands now accept a -j option to enable parallel building of extension modules.

bpo-22448 [https://bugs.python.org/issue22448]: Improve canceled timer handles cleanup to prevent unbound memory usage. Patch by Joshua Moore-Oliva.

bpo-22427 [https://bugs.python.org/issue22427]: TemporaryDirectory no longer attempts to clean up twice when used in the with statement in generator.

bpo-22362 [https://bugs.python.org/issue22362]: Forbidden ambiguous octal escapes out of range 0-0o377 in regular expressions.

bpo-20912 [https://bugs.python.org/issue20912]: Now directories added to ZIP file have correct Unix and MS-DOS directory attributes.

bpo-21866 [https://bugs.python.org/issue21866]: ZipFile.close() no longer writes ZIP64 central directory records if allowZip64 is false.

bpo-22278 [https://bugs.python.org/issue22278]: Fix urljoin problem with relative urls, a regression observed after changes to issue22118 were submitted.

bpo-22415 [https://bugs.python.org/issue22415]: Fixed debugging output of the GROUPREF_EXISTS opcode in the re module. Removed trailing spaces in debugging output.

bpo-22423 [https://bugs.python.org/issue22423]: Unhandled exception in thread no longer causes unhandled AttributeError when sys.stderr is None.

bpo-21332 [https://bugs.python.org/issue21332]: Ensure that bufsize=1 in subprocess.Popen() selects line buffering, rather than block buffering. Patch by Akira Li.

bpo-21091 [https://bugs.python.org/issue21091]: Fix API bug: email.message.EmailMessage.is_attachment is now a method.

bpo-21079 [https://bugs.python.org/issue21079]: Fix email.message.EmailMessage.is_attachment to return the correct result when the header has parameters as well as a value.

bpo-22247 [https://bugs.python.org/issue22247]: Add NNTPError to nntplib.__all__.

bpo-22366 [https://bugs.python.org/issue22366]: urllib.request.urlopen will accept a context object (SSLContext) as an argument which will then be used for HTTPS connection. Patch by Alex Gaynor.

bpo-4180 [https://bugs.python.org/issue4180]: The warnings registries are now reset when the filters are modified.

bpo-22419 [https://bugs.python.org/issue22419]: Limit the length of incoming HTTP request in wsgiref server to 65536 bytes and send a 414 error code for higher lengths. Patch contributed by Devin Cook.

Lax cookie parsing in http.cookies could be a security issue when combined with non-standard cookie handling in some Web browsers. Reported by Sergey Bobrov.

bpo-20537 [https://bugs.python.org/issue20537]: logging methods now accept an exception instance as well as a Boolean value or exception tuple. Thanks to Yury Selivanov for the patch.

bpo-22384 [https://bugs.python.org/issue22384]: An exception in Tkinter callback no longer crashes the program when it is run with pythonw.exe.

bpo-22168 [https://bugs.python.org/issue22168]: Prevent turtle AttributeError with non-default Canvas on OS X.

bpo-21147 [https://bugs.python.org/issue21147]: sqlite3 now raises an exception if the request contains a null character instead of truncating it. Based on patch by Victor Stinner.

bpo-13968 [https://bugs.python.org/issue13968]: The glob module now supports recursive search in subdirectories using the ** pattern.

bpo-21951 [https://bugs.python.org/issue21951]: Fixed a crash in Tkinter on AIX when called Tcl command with empty string or tuple argument.

bpo-21951 [https://bugs.python.org/issue21951]: Tkinter now most likely raises MemoryError instead of crash if the memory allocation fails.

bpo-22338 [https://bugs.python.org/issue22338]: Fix a crash in the json module on memory allocation failure.

bpo-12410 [https://bugs.python.org/issue12410]: imaplib.IMAP4 now supports the context management protocol. Original patch by Tarek Ziadé.

bpo-21270 [https://bugs.python.org/issue21270]: We now override tuple methods in mock.call objects so that they can be used as normal call attributes.

bpo-16662 [https://bugs.python.org/issue16662]: load_tests() is now unconditionally run when it is present in a package’s __init__.py. TestLoader.loadTestsFromModule() still accepts use_load_tests, but it is deprecated and ignored. A new keyword-only attribute pattern is added and documented. Patch given by Robert Collins, tweaked by Barry Warsaw.

bpo-22226 [https://bugs.python.org/issue22226]: First letter no longer is stripped from the « status » key in the result of Treeview.heading().

bpo-19524 [https://bugs.python.org/issue19524]: Fixed resource leak in the HTTP connection when an invalid response is received. Patch by Martin Panter.

bpo-20421 [https://bugs.python.org/issue20421]: Add a .version() method to SSL sockets exposing the actual protocol version in use.

bpo-19546 [https://bugs.python.org/issue19546]: configparser exceptions no longer expose implementation details. Chained KeyErrors are removed, which leads to cleaner tracebacks. Patch by Claudiu Popa.

bpo-22051 [https://bugs.python.org/issue22051]: turtledemo no longer reloads examples to re-run them. Initialization of variables and gui setup should be done in main(), which is called each time a demo is run, but not on import.

bpo-21933 [https://bugs.python.org/issue21933]: Turtledemo users can change the code font size with a menu selection or control(command) “-“ or “+” or control-mousewheel. Original patch by Lita Cho.

bpo-21597 [https://bugs.python.org/issue21597]: The separator between the turtledemo text pane and the drawing canvas can now be grabbed and dragged with a mouse. The code text pane can be widened to easily view or copy the full width of the text. The canvas can be widened on small screens. Original patches by Jan Kanis and Lita Cho.

bpo-18132 [https://bugs.python.org/issue18132]: Turtledemo buttons no longer disappear when the window is shrunk. Original patches by Jan Kanis and Lita Cho.

bpo-22043 [https://bugs.python.org/issue22043]: time.monotonic() is now always available. threading.Lock.acquire(), threading.RLock.acquire() and socket operations now use a monotonic clock, instead of the system clock, when a timeout is used.

bpo-21527 [https://bugs.python.org/issue21527]: Add a default number of workers to ThreadPoolExecutor equal to 5 times the number of CPUs. Patch by Claudiu Popa.

bpo-22216 [https://bugs.python.org/issue22216]: smtplib now resets its state more completely after a quit. The most obvious consequence of the previous behavior was a STARTTLS failure during a connect/starttls/quit/connect/starttls sequence.

bpo-22098 [https://bugs.python.org/issue22098]: ctypes” BigEndianStructure and LittleEndianStructure now define an empty __slots__ so that subclasses don’t always get an instance dict. Patch by Claudiu Popa.

bpo-22185 [https://bugs.python.org/issue22185]: Fix an occasional RuntimeError in threading.Condition.wait() caused by mutation of the waiters queue without holding the lock. Patch by Doug Zongker.

bpo-22287 [https://bugs.python.org/issue22287]: On UNIX, _PyTime_gettimeofday() now uses clock_gettime(CLOCK_REALTIME) if available. As a side effect, Python now depends on the librt library on Solaris and on Linux (only with glibc older than 2.17).

bpo-22182 [https://bugs.python.org/issue22182]: Use e.args to unpack exceptions correctly in distutils.file_util.move_file. Patch by Claudiu Popa.

The webbrowser module now uses subprocess’s start_new_session=True rather than a potentially risky preexec_fn=os.setsid call.

bpo-22042 [https://bugs.python.org/issue22042]: signal.set_wakeup_fd(fd) now raises an exception if the file descriptor is in blocking mode.

bpo-16808 [https://bugs.python.org/issue16808]: inspect.stack() now returns a named tuple instead of a tuple. Patch by Daniel Shahaf.

bpo-22236 [https://bugs.python.org/issue22236]: Fixed Tkinter images copying operations in NoDefaultRoot mode.

bpo-2527 [https://bugs.python.org/issue2527]: Add a globals argument to timeit functions, in order to override the globals namespace in which the timed code is executed. Patch by Ben Roberts.

bpo-22118 [https://bugs.python.org/issue22118]: Switch urllib.parse to use RFC 3986 semantics for the resolution of relative URLs, rather than RFCs 1808 and 2396. Patch by Demian Brecht.

bpo-21549 [https://bugs.python.org/issue21549]: Added the « members » parameter to TarFile.list().

bpo-19628 [https://bugs.python.org/issue19628]: Allow compileall recursion depth to be specified with a -r option.

bpo-15696 [https://bugs.python.org/issue15696]: Add a __sizeof__ implementation for mmap objects on Windows.

bpo-22068 [https://bugs.python.org/issue22068]: Avoided reference loops with Variables and Fonts in Tkinter.

bpo-22165 [https://bugs.python.org/issue22165]: SimpleHTTPRequestHandler now supports undecodable file names.

bpo-15381 [https://bugs.python.org/issue15381]: Optimized line reading in io.BytesIO.

bpo-8797 [https://bugs.python.org/issue8797]: Raise HTTPError on failed Basic Authentication immediately. Initial patch by Sam Bull.

bpo-20729 [https://bugs.python.org/issue20729]: Restored the use of lazy iterkeys()/itervalues()/iteritems() in the mailbox module.

bpo-21448 [https://bugs.python.org/issue21448]: Changed FeedParser feed() to avoid O(N**2) behavior when parsing long line. Original patch by Raymond Hettinger.

bpo-22184 [https://bugs.python.org/issue22184]: The functools LRU Cache decorator factory now gives an earlier and clearer error message when the user forgets the required parameters.

bpo-17923 [https://bugs.python.org/issue17923]: glob() patterns ending with a slash no longer match non-dirs on AIX. Based on patch by Delhallt.

bpo-21725 [https://bugs.python.org/issue21725]: Added support for RFC 6531 (SMTPUTF8) in smtpd.

bpo-22176 [https://bugs.python.org/issue22176]: Update the ctypes module’s libffi to v3.1. This release adds support for the Linux AArch64 and POWERPC ELF ABIv2 little endian architectures.

bpo-5411 [https://bugs.python.org/issue5411]: Added support for the « xztar » format in the shutil module.

bpo-21121 [https://bugs.python.org/issue21121]: Don’t force 3rd party C extensions to be built with <<<<<<< HEAD -Werror=declaration-after-statement. ======= -Werror=declaration-after-statement. >>>>>>> 3f819ca138… bpo-35110 [https://bugs.python.org/issue35110]: Fix unintentional spaces around hyphens and dashes. (GH-10231)

bpo-21975 [https://bugs.python.org/issue21975]: Fixed crash when using uninitialized sqlite3.Row (in particular when unpickling pickled sqlite3.Row). sqlite3.Row is now initialized in the __new__() method.

bpo-20170 [https://bugs.python.org/issue20170]: Convert posixmodule to use Argument Clinic.

bpo-21539 [https://bugs.python.org/issue21539]: Add an exists_ok argument to Pathlib.mkdir() to mimic mkdir -p and os.makedirs() functionality. When true, ignore FileExistsErrors. Patch by Berker Peksag.

bpo-22127 [https://bugs.python.org/issue22127]: Bypass IDNA for pure-ASCII host names in the socket module (in particular for numeric IPs).

bpo-21047 [https://bugs.python.org/issue21047]: set the default value for the convert_charrefs argument of HTMLParser to True. Patch by Berker Peksag.

Add an __all__ to html.entities.

bpo-15114 [https://bugs.python.org/issue15114]: the strict mode and argument of HTMLParser, HTMLParser.error, and the HTMLParserError exception have been removed.

bpo-22085 [https://bugs.python.org/issue22085]: Dropped support of Tk 8.3 in Tkinter.

bpo-21580 [https://bugs.python.org/issue21580]: Now Tkinter correctly handles bytes arguments passed to Tk. In particular this allows initializing images from binary data.

bpo-22003 [https://bugs.python.org/issue22003]: When initialized from a bytes object, io.BytesIO() now defers making a copy until it is mutated, improving performance and memory use on some use cases. Patch by David Wilson.

bpo-22018 [https://bugs.python.org/issue22018]: On Windows, signal.set_wakeup_fd() now also supports sockets. A side effect is that Python depends to the WinSock library.

bpo-22054 [https://bugs.python.org/issue22054]: Add os.get_blocking() and os.set_blocking() functions to get and set the blocking mode of a file descriptor (False if the O_NONBLOCK flag is set, True otherwise). These functions are not available on Windows.

bpo-17172 [https://bugs.python.org/issue17172]: Make turtledemo start as active on OS X even when run with subprocess. Patch by Lita Cho.

bpo-21704 [https://bugs.python.org/issue21704]: Fix build error for _multiprocessing when semaphores are not available. Patch by Arfrever Frehtes Taifersar Arahesis.

bpo-20173 [https://bugs.python.org/issue20173]: Convert sha1, sha256, sha512 and md5 to ArgumentClinic. Patch by Vajrasky Kok.

Fix repr(_socket.socket) on Windows 64-bit: don’t fail with OverflowError on closed socket. repr(socket.socket) already works fine.

bpo-22033 [https://bugs.python.org/issue22033]: Reprs of most Python implemented classes now contain actual class name instead of hardcoded one.

bpo-21947 [https://bugs.python.org/issue21947]: The dis module can now disassemble generator-iterator objects based on their gi_code attribute. Patch by Clement Rouault.

bpo-16133 [https://bugs.python.org/issue16133]: The asynchat.async_chat.handle_read() method now ignores BlockingIOError exceptions.

bpo-22044 [https://bugs.python.org/issue22044]: Fixed premature DECREF in call_tzinfo_method. Patch by Tom Flanagan.

bpo-19884 [https://bugs.python.org/issue19884]: readline: Disable the meta modifier key if stdout is not a terminal to not write the ANSI sequence "\033[1034h" into stdout. This sequence is used on some terminal (ex: TERM=xterm-256color ») to enable support of 8 bit characters.

bpo-4350 [https://bugs.python.org/issue4350]: Removed a number of out-of-dated and non-working for a long time Tkinter methods.

bpo-6167 [https://bugs.python.org/issue6167]: Scrollbar.activate() now returns the name of active element if the argument is not specified. Scrollbar.set() now always accepts only 2 arguments.

bpo-15275 [https://bugs.python.org/issue15275]: Clean up and speed up the ntpath module.

bpo-21888 [https://bugs.python.org/issue21888]: plistlib’s load() and loads() now work if the fmt parameter is specified.

bpo-22032 [https://bugs.python.org/issue22032]: __qualname__ instead of __name__ is now always used to format fully qualified class names of Python implemented classes.

bpo-22031 [https://bugs.python.org/issue22031]: Reprs now always use hexadecimal format with the « 0x » prefix when contain an id in form  » at 0x… ».

bpo-22018 [https://bugs.python.org/issue22018]: signal.set_wakeup_fd() now raises an OSError instead of a ValueError on fstat() failure.

bpo-21044 [https://bugs.python.org/issue21044]: tarfile.open() now handles fileobj with an integer “name” attribute. Based on patch by Antoine Pietri.

bpo-21966 [https://bugs.python.org/issue21966]: Respect -q command-line option when code module is ran.

bpo-19076 [https://bugs.python.org/issue19076]: Don’t pass the redundant “file” argument to self.error().

bpo-16382 [https://bugs.python.org/issue16382]: Improve exception message of warnings.warn() for bad category. Initial patch by Phil Elson.

bpo-21932 [https://bugs.python.org/issue21932]: os.read() now uses a Py_ssize_t() type instead of int for the size to support reading more than 2 GB at once. On Windows, the size is truncated to INT_MAX. As any call to os.read(), the OS may read less bytes than the number of requested bytes.

bpo-21942 [https://bugs.python.org/issue21942]: Fixed source file viewing in pydoc’s server mode on Windows.

bpo-11259 [https://bugs.python.org/issue11259]: asynchat.async_chat().set_terminator() now raises a ValueError if the number of received bytes is negative.

bpo-12523 [https://bugs.python.org/issue12523]: asynchat.async_chat.push() now raises a TypeError if it doesn’t get a bytes string

bpo-21707 [https://bugs.python.org/issue21707]: Add missing kwonlyargcount argument to ModuleFinder.replace_paths_in_code().

bpo-20639 [https://bugs.python.org/issue20639]: calling Path.with_suffix(“”) allows removing the suffix again. Patch by July Tikhonov.

bpo-21714 [https://bugs.python.org/issue21714]: Disallow the construction of invalid paths using Path.with_name(). Original patch by Antony Lee.

bpo-15014 [https://bugs.python.org/issue15014]: Added “auth” method to smtplib to make implementing auth mechanisms simpler, and used it internally in the login method.

bpo-21151 [https://bugs.python.org/issue21151]: Fixed a segfault in the winreg module when None is passed as a REG_BINARY value to SetValueEx. Patch by John Ehresman.

bpo-21090 [https://bugs.python.org/issue21090]: io.FileIO.readall() does not ignore I/O errors anymore. Before, it ignored I/O errors if at least the first C call read() succeed.

bpo-5800 [https://bugs.python.org/issue5800]: headers parameter of wsgiref.headers.Headers is now optional. Initial patch by Pablo Torres Navarrete and SilentGhost.

bpo-21781 [https://bugs.python.org/issue21781]: ssl.RAND_add() now supports strings longer than 2 GB.

bpo-21679 [https://bugs.python.org/issue21679]: Prevent extraneous fstat() calls during open(). Patch by Bohuslav Kabrda.

bpo-21863 [https://bugs.python.org/issue21863]: cProfile now displays the module name of C extension functions, in addition to their own name.

bpo-11453 [https://bugs.python.org/issue11453]: asyncore: emit a ResourceWarning when an unclosed file_wrapper object is destroyed. The destructor now closes the file if needed. The close() method can now be called twice: the second call does nothing.

bpo-21858 [https://bugs.python.org/issue21858]: Better handling of Python exceptions in the sqlite3 module.

bpo-21476 [https://bugs.python.org/issue21476]: Make sure the email.parser.BytesParser TextIOWrapper is discarded after parsing, so the input file isn’t unexpectedly closed.

bpo-20295 [https://bugs.python.org/issue20295]: imghdr now recognizes OpenEXR format images.

bpo-21729 [https://bugs.python.org/issue21729]: Used the « with » statement in the dbm.dumb module to ensure files closing. Patch by Claudiu Popa.

bpo-21491 [https://bugs.python.org/issue21491]: socketserver: Fix a race condition in child processes reaping.

bpo-21719 [https://bugs.python.org/issue21719]: Added the st_file_attributes field to os.stat_result on Windows.

bpo-21832 [https://bugs.python.org/issue21832]: Require named tuple inputs to be exact strings.

bpo-21722 [https://bugs.python.org/issue21722]: The distutils « upload » command now exits with a non-zero return code when uploading fails. Patch by Martin Dengler.

bpo-21723 [https://bugs.python.org/issue21723]: asyncio.Queue: support any type of number (ex: float) for the maximum size. Patch written by Vajrasky Kok.

bpo-21711 [https://bugs.python.org/issue21711]: support for « site-python » directories has now been removed from the site module (it was deprecated in 3.4).

bpo-17552 [https://bugs.python.org/issue17552]: new socket.sendfile() method allowing a file to be sent over a socket by using high-performance os.sendfile() on UNIX. Patch by Giampaolo Rodola”.

bpo-18039 [https://bugs.python.org/issue18039]: dbm.dump.open() now always creates a new database when the flag has the value “n”. Patch by Claudiu Popa.

bpo-21326 [https://bugs.python.org/issue21326]: Add a new is_closed() method to asyncio.BaseEventLoop. run_forever() and run_until_complete() methods of asyncio.BaseEventLoop now raise an exception if the event loop was closed.

bpo-21766 [https://bugs.python.org/issue21766]: Prevent a security hole in CGIHTTPServer by URL unquoting paths before checking for a CGI script at that path.

bpo-21310 [https://bugs.python.org/issue21310]: Fixed possible resource leak in failed open().

bpo-21256 [https://bugs.python.org/issue21256]: Printout of keyword args should be in deterministic order in a mock function call. This will help to write better doctests.

bpo-21677 [https://bugs.python.org/issue21677]: Fixed chaining nonnormalized exceptions in io close() methods.

bpo-11709 [https://bugs.python.org/issue11709]: Fix the pydoc.help function to not fail when sys.stdin is not a valid file.

bpo-21515 [https://bugs.python.org/issue21515]: tempfile.TemporaryFile now uses os.O_TMPFILE flag is available.

bpo-13223 [https://bugs.python.org/issue13223]: Fix pydoc.writedoc so that the HTML documentation for methods that use “self” in the example code is generated correctly.

bpo-21463 [https://bugs.python.org/issue21463]: In urllib.request, fix pruning of the FTP cache.

bpo-21618 [https://bugs.python.org/issue21618]: The subprocess module could fail to close open fds that were inherited by the calling process and already higher than POSIX resource limits would otherwise allow. On systems with a functioning /proc/self/fd or /dev/fd interface the max is now ignored and all fds are closed.

bpo-20383 [https://bugs.python.org/issue20383]: Introduce importlib.util.module_from_spec() as the preferred way to create a new module.

bpo-21552 [https://bugs.python.org/issue21552]: Fixed possible integer overflow of too long string lengths in the tkinter module on 64-bit platforms.

bpo-14315 [https://bugs.python.org/issue14315]: The zipfile module now ignores extra fields in the central directory that are too short to be parsed instead of letting a struct.unpack error bubble up as this « bad data » appears in many real world zip files in the wild and is ignored by other zip tools.

bpo-13742 [https://bugs.python.org/issue13742]: Added « key » and « reverse » parameters to heapq.merge(). (First draft of patch contributed by Simon Sapin.)

bpo-21402 [https://bugs.python.org/issue21402]: tkinter.ttk now works when default root window is not set.

bpo-3015 [https://bugs.python.org/issue3015]: _tkinter.create() now creates tkapp object with wantobject=1 by default.

bpo-10203 [https://bugs.python.org/issue10203]: sqlite3.Row now truly supports sequence protocol. In particular it supports reverse() and negative indices. Original patch by Claudiu Popa.

bpo-18807 [https://bugs.python.org/issue18807]: If copying (no symlinks) specified for a venv, then the python interpreter aliases (python, python3) are now created by copying rather than symlinking.

bpo-20197 [https://bugs.python.org/issue20197]: Added support for the WebP image type in the imghdr module. Patch by Fabrice Aneche and Claudiu Popa.

bpo-21513 [https://bugs.python.org/issue21513]: Speedup some properties of IP addresses (IPv4Address, IPv6Address) such as .is_private or .is_multicast.

bpo-21137 [https://bugs.python.org/issue21137]: Improve the repr for threading.Lock() and its variants by showing the « locked » or « unlocked » status. Patch by Berker Peksag.

bpo-21538 [https://bugs.python.org/issue21538]: The plistlib module now supports loading of binary plist files when reference or offset size is not a power of two.

bpo-21455 [https://bugs.python.org/issue21455]: Add a default backlog to socket.listen().

bpo-21525 [https://bugs.python.org/issue21525]: Most Tkinter methods which accepted tuples now accept lists too.

bpo-22166 [https://bugs.python.org/issue22166]: With the assistance of a new internal _codecs._forget_codec helping function, test_codecs now clears the encoding caches to avoid the appearance of a reference leak

bpo-22236 [https://bugs.python.org/issue22236]: Tkinter tests now don’t reuse default root window. New root window is created for every test class.

bpo-10744 [https://bugs.python.org/issue10744]: Fix PEP 3118 format strings on ctypes objects with a nontrivial shape.

bpo-20826 [https://bugs.python.org/issue20826]: Optimize ipaddress.collapse_addresses().

bpo-21487 [https://bugs.python.org/issue21487]: Optimize ipaddress.summarize_address_range() and ipaddress.{IPv4Network,IPv6Network}.subnets().

bpo-21486 [https://bugs.python.org/issue21486]: Optimize parsing of netmasks in ipaddress.IPv4Network and ipaddress.IPv6Network.

bpo-13916 [https://bugs.python.org/issue13916]: Disallowed the surrogatepass error handler for non UTF-* encodings.

bpo-20998 [https://bugs.python.org/issue20998]: Fixed re.fullmatch() of repeated single character pattern with ignore case. Original patch by Matthew Barnett.

bpo-21075 [https://bugs.python.org/issue21075]: fileinput.FileInput now reads bytes from standard stream if binary mode is specified. Patch by Sam Kimbrel.

bpo-19775 [https://bugs.python.org/issue19775]: Add a samefile() method to pathlib Path objects. Initial patch by Vajrasky Kok.

bpo-21226 [https://bugs.python.org/issue21226]: Set up modules properly in PyImport_ExecCodeModuleObject (and friends).

bpo-21398 [https://bugs.python.org/issue21398]: Fix a unicode error in the pydoc pager when the documentation contains characters not encodable to the stdout encoding.

bpo-16531 [https://bugs.python.org/issue16531]: ipaddress.IPv4Network and ipaddress.IPv6Network now accept an (address, netmask) tuple argument, so as to easily construct network objects from existing addresses.

bpo-21156 [https://bugs.python.org/issue21156]: importlib.abc.InspectLoader.source_to_code() is now a staticmethod.

bpo-21424 [https://bugs.python.org/issue21424]: Simplified and optimized heaqp.nlargest() and nmsmallest() to make fewer tuple comparisons.

bpo-21396 [https://bugs.python.org/issue21396]: Fix TextIOWrapper(…, write_through=True) to not force a flush() on the underlying binary stream. Patch by akira.

bpo-18314 [https://bugs.python.org/issue18314]: Unlink now removes junctions on Windows. Patch by Kim Gräsman

bpo-21088 [https://bugs.python.org/issue21088]: Bugfix for curses.window.addch() regression in 3.4.0. In porting to Argument Clinic, the first two arguments were reversed.

bpo-21407 [https://bugs.python.org/issue21407]: _decimal: The module now supports function signatures.

bpo-10650 [https://bugs.python.org/issue10650]: Remove the non-standard “watchexp” parameter from the Decimal.quantize() method in the Python version. It had never been present in the C version.

bpo-21469 [https://bugs.python.org/issue21469]: Reduced the risk of false positives in robotparser by checking to make sure that robots.txt has been read or does not exist prior to returning True in can_fetch().

bpo-19414 [https://bugs.python.org/issue19414]: Have the OrderedDict mark deleted links as unusable. This gives an early failure if the link is deleted during iteration.

bpo-21421 [https://bugs.python.org/issue21421]: Add __slots__ to the MappingViews ABC. Patch by Josh Rosenberg.

bpo-21101 [https://bugs.python.org/issue21101]: Eliminate double hashing in the C speed-up code for collections.Counter().

bpo-21321 [https://bugs.python.org/issue21321]: itertools.islice() now releases the reference to the source iterator when the slice is exhausted. Patch by Anton Afanasyev.

bpo-21057 [https://bugs.python.org/issue21057]: TextIOWrapper now allows the underlying binary stream’s read() or read1() method to return an arbitrary bytes-like object (such as a memoryview). Patch by Nikolaus Rath.

bpo-20951 [https://bugs.python.org/issue20951]: SSLSocket.send() now raises either SSLWantReadError or SSLWantWriteError on a non-blocking socket if the operation would block. Previously, it would return 0. Patch by Nikolaus Rath.

bpo-13248 [https://bugs.python.org/issue13248]: removed previously deprecated asyncore.dispatcher __getattr__ cheap inheritance hack.

bpo-9815 [https://bugs.python.org/issue9815]: assertRaises now tries to clear references to local variables in the exception’s traceback.

bpo-19940 [https://bugs.python.org/issue19940]: ssl.cert_time_to_seconds() now interprets the given time string in the UTC timezone (as specified in RFC 5280), not the local timezone.

bpo-13204 [https://bugs.python.org/issue13204]: Calling sys.flags.__new__ would crash the interpreter, now it raises a TypeError.

bpo-19385 [https://bugs.python.org/issue19385]: Make operations on a closed dbm.dumb database always raise the same exception.

bpo-21207 [https://bugs.python.org/issue21207]: Detect when the os.urandom cached fd has been closed or replaced, and open it anew.

bpo-21291 [https://bugs.python.org/issue21291]: subprocess’s Popen.wait() is now thread safe so that multiple threads may be calling wait() or poll() on a Popen instance at the same time without losing the Popen.returncode value.

bpo-21127 [https://bugs.python.org/issue21127]: Path objects can now be instantiated from str subclass instances (such as numpy.str_).

bpo-15002 [https://bugs.python.org/issue15002]: urllib.response object to use _TemporaryFileWrapper (and _TemporaryFileCloser) facility. Provides a better way to handle file descriptor close. Patch contributed by Christian Theune.

bpo-12220 [https://bugs.python.org/issue12220]: mindom now raises a custom ValueError indicating it doesn’t support spaces in URIs instead of letting a “split” ValueError bubble up.

bpo-21068 [https://bugs.python.org/issue21068]: The ssl.PROTOCOL* constants are now enum members.

bpo-21276 [https://bugs.python.org/issue21276]: posixmodule: Don’t define USE_XATTRS on KFreeBSD and the Hurd.

bpo-21262 [https://bugs.python.org/issue21262]: New method assert_not_called for Mock. It raises AssertionError if the mock has been called.

bpo-21238 [https://bugs.python.org/issue21238]: New keyword argument unsafe to Mock. It raises AttributeError incase of an attribute startswith assert or assret.

bpo-20896 [https://bugs.python.org/issue20896]: ssl.get_server_certificate() now uses PROTOCOL_SSLv23, not PROTOCOL_SSLv3, for maximum compatibility.

bpo-21239 [https://bugs.python.org/issue21239]: patch.stopall() didn’t work deterministically when the same name was patched more than once.

bpo-21203 [https://bugs.python.org/issue21203]: Updated fileConfig and dictConfig to remove inconsistencies. Thanks to Jure Koren for the patch.

bpo-21222 [https://bugs.python.org/issue21222]: Passing name keyword argument to mock.create_autospec now works.

bpo-21197 [https://bugs.python.org/issue21197]: Add lib64 -> lib symlink in venvs on 64-bit non-OS X POSIX.

bpo-17498 [https://bugs.python.org/issue17498]: Some SMTP servers disconnect after certain errors, violating strict RFC conformance. Instead of losing the error code when we issue the subsequent RSET, smtplib now returns the error code and defers raising the SMTPServerDisconnected error until the next command is issued.

bpo-17826 [https://bugs.python.org/issue17826]: setting an iterable side_effect on a mock function created by create_autospec now works. Patch by Kushal Das.

bpo-7776 [https://bugs.python.org/issue7776]: Fix Host: header and reconnection when using http.client.HTTPConnection.set_tunnel(). Patch by Nikolaus Rath.

bpo-20968 [https://bugs.python.org/issue20968]: unittest.mock.MagicMock now supports division. Patch by Johannes Baiter.

bpo-21529 [https://bugs.python.org/issue21529]: Fix arbitrary memory access in JSONDecoder.raw_decode with a negative second parameter. Bug reported by Guido Vranken. (See also: CVE-2014-4616)

bpo-21169 [https://bugs.python.org/issue21169]: getpass now handles non-ascii characters that the input stream encoding cannot encode by re-encoding using the replace error handler.

bpo-21171 [https://bugs.python.org/issue21171]: Fixed undocumented filter API of the rot13 codec. Patch by Berker Peksag.

bpo-20539 [https://bugs.python.org/issue20539]: Improved math.factorial error message for large positive inputs and changed exception type (OverflowError -> ValueError) for large negative inputs.

bpo-21172 [https://bugs.python.org/issue21172]: isinstance check relaxed from dict to collections.Mapping.

bpo-21155 [https://bugs.python.org/issue21155]: asyncio.EventLoop.create_unix_server() now raises a ValueError if path and sock are specified at the same time.

bpo-21136 [https://bugs.python.org/issue21136]: Avoid unnecessary normalization of Fractions resulting from power and other operations. Patch by Raymond Hettinger.

bpo-17621 [https://bugs.python.org/issue17621]: Introduce importlib.util.LazyLoader.

bpo-21076 [https://bugs.python.org/issue21076]: signal module constants were turned into enums. Patch by Giampaolo Rodola”.

bpo-20636 [https://bugs.python.org/issue20636]: Improved the repr of Tkinter widgets.

bpo-19505 [https://bugs.python.org/issue19505]: The items, keys, and values views of OrderedDict now support reverse iteration using reversed().

bpo-21149 [https://bugs.python.org/issue21149]: Improved thread-safety in logging cleanup during interpreter shutdown. Thanks to Devin Jeanpierre for the patch.

bpo-21058 [https://bugs.python.org/issue21058]: Fix a leak of file descriptor in tempfile.NamedTemporaryFile(), close the file descriptor if io.open() fails

bpo-21200 [https://bugs.python.org/issue21200]: Return None from pkgutil.get_loader() when __spec__ is missing.

bpo-21013 [https://bugs.python.org/issue21013]: Enhance ssl.create_default_context() when used for server side sockets to provide better security by default.

bpo-20145 [https://bugs.python.org/issue20145]: assertRaisesRegex and assertWarnsRegex now raise a TypeError if the second argument is not a string or compiled regex.

bpo-20633 [https://bugs.python.org/issue20633]: Replace relative import by absolute import.

bpo-20980 [https://bugs.python.org/issue20980]: Stop wrapping exception when using ThreadPool.

bpo-21082 [https://bugs.python.org/issue21082]: In os.makedirs, do not set the process-wide umask. Note this changes behavior of makedirs when exist_ok=True.

bpo-20990 [https://bugs.python.org/issue20990]: Fix issues found by pyflakes for multiprocessing.

bpo-21015 [https://bugs.python.org/issue21015]: SSL contexts will now automatically select an elliptic curve for ECDH key exchange on OpenSSL 1.0.2 and later, and otherwise default to « prime256v1 ».

bpo-21000 [https://bugs.python.org/issue21000]: Improve the command-line interface of json.tool.

bpo-20995 [https://bugs.python.org/issue20995]: Enhance default ciphers used by the ssl module to enable better security and prioritize perfect forward secrecy.

bpo-20884 [https://bugs.python.org/issue20884]: Don’t assume that __file__ is defined on importlib.__init__.

bpo-21499 [https://bugs.python.org/issue21499]: Ignore __builtins__ in several test_importlib.test_api tests.

bpo-20627 [https://bugs.python.org/issue20627]: xmlrpc.client.ServerProxy is now a context manager.

bpo-19165 [https://bugs.python.org/issue19165]: The formatter module now raises DeprecationWarning instead of PendingDeprecationWarning.

bpo-13936 [https://bugs.python.org/issue13936]: Remove the ability of datetime.time instances to be considered false in boolean contexts.

bpo-18931 [https://bugs.python.org/issue18931]: selectors module now supports /dev/poll on Solaris. Patch by Giampaolo Rodola”.

bpo-19977 [https://bugs.python.org/issue19977]: When the LC_TYPE locale is the POSIX locale (C locale), sys.stdin and sys.stdout are now using the surrogateescape error handler, instead of the strict error handler.

bpo-20574 [https://bugs.python.org/issue20574]: Implement incremental decoder for cp65001 code (Windows code page 65001, Microsoft UTF-8).

bpo-20879 [https://bugs.python.org/issue20879]: Delay the initialization of encoding and decoding tables for base32, ascii85 and base85 codecs in the base64 module, and delay the initialization of the unquote_to_bytes() table of the urllib.parse module, to not waste memory if these modules are not used.

bpo-19157 [https://bugs.python.org/issue19157]: Include the broadcast address in the usuable hosts for IPv6 in ipaddress.

bpo-11599 [https://bugs.python.org/issue11599]: When an external command (e.g. compiler) fails, distutils now prints out the whole command line (instead of just the command name) if the environment variable DISTUTILS_DEBUG is set.

bpo-4931 [https://bugs.python.org/issue4931]: distutils should not produce unhelpful « error: None » messages anymore. distutils.util.grok_environment_error is kept but doc-deprecated.

bpo-20875 [https://bugs.python.org/issue20875]: Prevent possible gzip « “read” is not defined » NameError. Patch by Claudiu Popa.

bpo-11558 [https://bugs.python.org/issue11558]: email.message.Message.attach now returns a more useful error message if attach is called on a message for which is_multipart is False.

bpo-20283 [https://bugs.python.org/issue20283]: RE pattern methods now accept the string keyword parameters as documented. The pattern and source keyword parameters are left as deprecated aliases.

bpo-20778 [https://bugs.python.org/issue20778]: Fix modulefinder to work with bytecode-only modules.

bpo-20791 [https://bugs.python.org/issue20791]: copy.copy() now doesn’t make a copy when the input is a bytes object. Initial patch by Peter Otten.

bpo-19748 [https://bugs.python.org/issue19748]: On AIX, time.mktime() now raises an OverflowError for year outsize range [1902; 2037].

bpo-19573 [https://bugs.python.org/issue19573]: inspect.signature: Use enum for parameter kind constants.

bpo-20726 [https://bugs.python.org/issue20726]: inspect.signature: Make Signature and Parameter picklable.

bpo-17373 [https://bugs.python.org/issue17373]: Add inspect.Signature.from_callable method.

bpo-20378 [https://bugs.python.org/issue20378]: Improve repr of inspect.Signature and inspect.Parameter.

bpo-20816 [https://bugs.python.org/issue20816]: Fix inspect.getcallargs() to raise correct TypeError for missing keyword-only arguments. Patch by Jeremiah Lowin.

bpo-20817 [https://bugs.python.org/issue20817]: Fix inspect.getcallargs() to fail correctly if more than 3 arguments are missing. Patch by Jeremiah Lowin.

bpo-6676 [https://bugs.python.org/issue6676]: Ensure a meaningful exception is raised when attempting to parse more than one XML document per pyexpat xmlparser instance. (Original patches by Hirokazu Yamamoto and Amaury Forgeot d’Arc, with suggested wording by David Gutteridge)

bpo-21117 [https://bugs.python.org/issue21117]: Fix inspect.signature to better support functools.partial. Due to the specifics of functools.partial implementation, positional-or-keyword arguments passed as keyword arguments become keyword-only.

bpo-20334 [https://bugs.python.org/issue20334]: inspect.Signature and inspect.Parameter are now hashable. Thanks to Antony Lee for bug reports and suggestions.

bpo-15916 [https://bugs.python.org/issue15916]: doctest.DocTestSuite returns an empty unittest.TestSuite instead of raising ValueError if it finds no tests

bpo-21209 [https://bugs.python.org/issue21209]: Fix asyncio.tasks.CoroWrapper to workaround a bug in yield-from implementation in CPythons prior to 3.4.1.

asyncio: Add gi_{frame,running,code} properties to CoroWrapper (upstream bpo-163 [https://bugs.python.org/issue163]).

bpo-21311 [https://bugs.python.org/issue21311]: Avoid exception in _osx_support with non-standard compiler configurations. Patch by John Szakmeister.

bpo-11571 [https://bugs.python.org/issue11571]: Ensure that the turtle window becomes the topmost window when launched on OS X.

bpo-21801 [https://bugs.python.org/issue21801]: Validate that __signature__ is None or an instance of Signature.

bpo-21923 [https://bugs.python.org/issue21923]: Prevent AttributeError in distutils.sysconfig.customize_compiler due to possible uninitialized _config_vars.

bpo-21323 [https://bugs.python.org/issue21323]: Fix http.server to again handle scripts in CGI subdirectories, broken by the fix for security bpo-19435 [https://bugs.python.org/issue19435]. Patch by Zach Byrne.

bpo-22733 [https://bugs.python.org/issue22733]: Fix ffi_prep_args not zero-extending argument values correctly on 64-bit Windows.

bpo-23302 [https://bugs.python.org/issue23302]: Default to TCP_NODELAY=1 upon establishing an HTTPConnection. Removed use of hard-coded MSS as it’s an optimization that’s no longer needed with Nagle disabled.

IDLE

bpo-20577 [https://bugs.python.org/issue20577]: Configuration of the max line length for the FormatParagraph extension has been moved from the General tab of the Idle preferences dialog to the FormatParagraph tab of the Config Extensions dialog. Patch by Tal Einat.

bpo-16893 [https://bugs.python.org/issue16893]: Update Idle doc chapter to match current Idle and add new information.

bpo-3068 [https://bugs.python.org/issue3068]: Add Idle extension configuration dialog to Options menu. Changes are written to HOME/.idlerc/config-extensions.cfg. Original patch by Tal Einat.

bpo-16233 [https://bugs.python.org/issue16233]: A module browser (File : Class Browser, Alt+C) requires an editor window with a filename. When Class Browser is requested otherwise, from a shell, output window, or “Untitled” editor, Idle no longer displays an error box. It now pops up an Open Module box (Alt+M). If a valid name is entered and a module is opened, a corresponding browser is also opened.

bpo-4832 [https://bugs.python.org/issue4832]: Save As to type Python files automatically adds .py to the name you enter (even if your system does not display it). Some systems automatically add .txt when type is Text files.

bpo-21986 [https://bugs.python.org/issue21986]: Code objects are not normally pickled by the pickle module. To match this, they are no longer pickled when running under Idle.

bpo-17390 [https://bugs.python.org/issue17390]: Adjust Editor window title; remove “Python”, move version to end.

bpo-14105 [https://bugs.python.org/issue14105]: Idle debugger breakpoints no longer disappear when inserting or deleting lines.

bpo-17172 [https://bugs.python.org/issue17172]: Turtledemo can now be run from Idle. Currently, the entry is on the Help menu, but it may move to Run. Patch by Ramchandra Apt and Lita Cho.

bpo-21765 [https://bugs.python.org/issue21765]: Add support for non-ascii identifiers to HyperParser.

bpo-21940 [https://bugs.python.org/issue21940]: Add unittest for WidgetRedirector. Initial patch by Saimadhav Heblikar.

bpo-18592 [https://bugs.python.org/issue18592]: Add unittest for SearchDialogBase. Patch by Phil Webster.

bpo-21694 [https://bugs.python.org/issue21694]: Add unittest for ParenMatch. Patch by Saimadhav Heblikar.

bpo-21686 [https://bugs.python.org/issue21686]: add unittest for HyperParser. Original patch by Saimadhav Heblikar.

bpo-12387 [https://bugs.python.org/issue12387]: Add missing upper(lower)case versions of default Windows key bindings for Idle so Caps Lock does not disable them. Patch by Roger Serwy.

bpo-21695 [https://bugs.python.org/issue21695]: Closing a Find-in-files output window while the search is still in progress no longer closes Idle.

bpo-18910 [https://bugs.python.org/issue18910]: Add unittest for textView. Patch by Phil Webster.

bpo-18292 [https://bugs.python.org/issue18292]: Add unittest for AutoExpand. Patch by Saihadhav Heblikar.

bpo-18409 [https://bugs.python.org/issue18409]: Add unittest for AutoComplete. Patch by Phil Webster.

bpo-21477 [https://bugs.python.org/issue21477]: htest.py - Improve framework, complete set of tests. Patches by Saimadhav Heblikar

bpo-18104 [https://bugs.python.org/issue18104]: Add idlelib/idle_test/htest.py with a few sample tests to begin consolidating and improving human-validated tests of Idle. Change other files as needed to work with htest. Running the module as __main__ runs all tests.

bpo-21139 [https://bugs.python.org/issue21139]: Change default paragraph width to 72, the PEP 8 recommendation.

bpo-21284 [https://bugs.python.org/issue21284]: Paragraph reformat test passes after user changes reformat width.

bpo-17654 [https://bugs.python.org/issue17654]: Ensure IDLE menus are customized properly on OS X for non-framework builds and for all variants of Tk.

bpo-23180 [https://bugs.python.org/issue23180]: Rename IDLE « Windows » menu item to « Window ». Patch by Al Sweigart.

Build

bpo-15506 [https://bugs.python.org/issue15506]: Use standard PKG_PROG_PKG_CONFIG autoconf macro in the configure script.

bpo-22935 [https://bugs.python.org/issue22935]: Allow the ssl module to be compiled if openssl doesn’t support SSL 3.

bpo-22592 [https://bugs.python.org/issue22592]: Drop support of the Borland C compiler to build Python. The distutils module still supports it to build extensions.

bpo-22591 [https://bugs.python.org/issue22591]: Drop support of MS-DOS, especially of the DJGPP compiler (MS-DOS port of GCC).

bpo-16537 [https://bugs.python.org/issue16537]: Check whether self.extensions is empty in setup.py. Patch by Jonathan Hosmer.

bpo-22359 [https://bugs.python.org/issue22359]: Remove incorrect uses of recursive make. Patch by Jonas Wagner.

bpo-21958 [https://bugs.python.org/issue21958]: Define HAVE_ROUND when building with Visual Studio 2013 and above. Patch by Zachary Turner.

bpo-18093 [https://bugs.python.org/issue18093]: the programs that embed the CPython runtime are now in a separate « Programs » directory, rather than being kept in the Modules directory.

bpo-15759 [https://bugs.python.org/issue15759]: « make suspicious », « make linkcheck » and « make doctest » in Doc/ now display special message when and only when there are failures.

bpo-21141 [https://bugs.python.org/issue21141]: The Windows build process no longer attempts to find Perl, instead relying on OpenSSL source being configured and ready to build. The PCbuild\build_ssl.py script has been re-written and re-named to PCbuild\prepare_ssl.py, and takes care of configuring OpenSSL source for both 32 and 64 bit platforms. OpenSSL sources obtained from svn.python.org will always be pre-configured and ready to build.

bpo-21037 [https://bugs.python.org/issue21037]: Add a build option to enable AddressSanitizer support.

bpo-19962 [https://bugs.python.org/issue19962]: The Windows build process now creates « python.bat » in the root of the source tree, which passes all arguments through to the most recently built interpreter.

bpo-21285 [https://bugs.python.org/issue21285]: Refactor and fix curses configure check to always search in a ncursesw directory.

bpo-15234 [https://bugs.python.org/issue15234]: For BerkelyDB and Sqlite, only add the found library and include directories if they aren’t already being searched. This avoids an explicit runtime library dependency.

bpo-17861 [https://bugs.python.org/issue17861]: Tools/scripts/generate_opcode_h.py automatically regenerates Include/opcode.h from Lib/opcode.py if the latter gets any change.

bpo-20644 [https://bugs.python.org/issue20644]: OS X installer build support for documentation build changes in 3.4.1: assume externally supplied sphinx-build is available in /usr/bin.

bpo-20022 [https://bugs.python.org/issue20022]: Eliminate use of deprecated bundlebuilder in OS X builds.

bpo-15968 [https://bugs.python.org/issue15968]: Incorporated Tcl, Tk, and Tix builds into the Windows build solution.

bpo-17095 [https://bugs.python.org/issue17095]: Fix Modules/Setup shared support.

bpo-21811 [https://bugs.python.org/issue21811]: Anticipated fixes to support OS X versions > 10.9.

bpo-21166 [https://bugs.python.org/issue21166]: Prevent possible segfaults and other random failures of python <<<<<<< HEAD --generate-posix-vars in pybuilddir.txt build target. ======= –generate-posix-vars in pybuilddir.txt build target. >>>>>>> 3f819ca138… bpo-35110 [https://bugs.python.org/issue35110]: Fix unintentional spaces around hyphens and dashes. (GH-10231)

bpo-18096 [https://bugs.python.org/issue18096]: Fix library order returned by python-config.

bpo-17219 [https://bugs.python.org/issue17219]: Add library build dir for Python extension cross-builds.

bpo-22919 [https://bugs.python.org/issue22919]: Windows build updated to support VC 14.0 (Visual Studio 2015), which will be used for the official release.

bpo-21236 [https://bugs.python.org/issue21236]: Build _msi.pyd with cabinet.lib instead of fci.lib

bpo-17128 [https://bugs.python.org/issue17128]: Use private version of OpenSSL for OS X 10.5+ installer.

C API

bpo-14203 [https://bugs.python.org/issue14203]: Remove obsolete support for view==NULL in PyBuffer_FillInfo(), bytearray_getbuffer(), bytesiobuf_getbuffer() and array_buffer_getbuf(). All functions now raise BufferError in that case.

bpo-22445 [https://bugs.python.org/issue22445]: PyBuffer_IsContiguous() now implements precise contiguity tests, compatible with NumPy’s NPY_RELAXED_STRIDES_CHECKING compilation flag. Previously the function reported false negatives for corner cases.

bpo-22079 [https://bugs.python.org/issue22079]: PyType_Ready() now checks that statically allocated type has no dynamically allocated bases.

bpo-22453 [https://bugs.python.org/issue22453]: Removed non-documented macro PyObject_REPR().

bpo-18395 [https://bugs.python.org/issue18395]: Rename _Py_char2wchar() to Py_DecodeLocale(), rename _Py_wchar2char() to Py_EncodeLocale(), and document these functions.

bpo-21233 [https://bugs.python.org/issue21233]: Add new C functions: PyMem_RawCalloc(), PyMem_Calloc(), PyObject_Calloc(), _PyObject_GC_Calloc(). bytes(int) is now using calloc() instead of malloc() for large objects which is faster and use less memory.

bpo-20942 [https://bugs.python.org/issue20942]: PyImport_ImportFrozenModuleObject() no longer sets __file__ to match what importlib does; this affects _frozen_importlib as well as any module loaded using imp.init_frozen().

Documentation

bpo-19548 [https://bugs.python.org/issue19548]: Update the codecs module documentation to better cover the distinction between text encodings and other codecs, together with other clarifications. Patch by Martin Panter.

bpo-22394 [https://bugs.python.org/issue22394]: Doc/Makefile now supports make venv PYTHON=../python to create a venv for generating the documentation, e.g., make html PYTHON=venv/bin/python3.

bpo-21514 [https://bugs.python.org/issue21514]: The documentation of the json module now refers to new JSON RFC 7159 instead of obsoleted RFC 4627.

bpo-21777 [https://bugs.python.org/issue21777]: The binary sequence methods on bytes and bytearray are now documented explicitly, rather than assuming users will be able to derive the expected behaviour from the behaviour of the corresponding str methods.

bpo-6916 [https://bugs.python.org/issue6916]: undocument deprecated asynchat.fifo class.

bpo-17386 [https://bugs.python.org/issue17386]: Expanded functionality of the Doc/make.bat script to make it much more comparable to Doc/Makefile.

bpo-21312 [https://bugs.python.org/issue21312]: Update the thread_foobar.h template file to include newer threading APIs. Patch by Jack McCracken.

bpo-21043 [https://bugs.python.org/issue21043]: Remove the recommendation for specific CA organizations and to mention the ability to load the OS certificates.

bpo-20765 [https://bugs.python.org/issue20765]: Add missing documentation for PurePath.with_name() and PurePath.with_suffix().

bpo-19407 [https://bugs.python.org/issue19407]: New package installation and distribution guides based on the Python Packaging Authority tools. Existing guides have been retained as legacy links from the distutils docs, as they still contain some required reference material for tool developers that isn’t recorded anywhere else.

bpo-19697 [https://bugs.python.org/issue19697]: Document cases where __main__.__spec__ is None.

Tests

bpo-18982 [https://bugs.python.org/issue18982]: Add tests for CLI of the calendar module.

bpo-19548 [https://bugs.python.org/issue19548]: Added some additional checks to test_codecs to ensure that statements in the updated documentation remain accurate. Patch by Martin Panter.

bpo-22838 [https://bugs.python.org/issue22838]: All test_re tests now work with unittest test discovery.

bpo-22173 [https://bugs.python.org/issue22173]: Update lib2to3 tests to use unittest test discovery.

bpo-16000 [https://bugs.python.org/issue16000]: Convert test_curses to use unittest.

bpo-21456 [https://bugs.python.org/issue21456]: Skip two tests in test_urllib2net.py if _ssl module not present. Patch by Remi Pointel.

bpo-20746 [https://bugs.python.org/issue20746]: Fix test_pdb to run in refleak mode (-R). Patch by Xavier de Gaye.

bpo-22060 [https://bugs.python.org/issue22060]: test_ctypes has been somewhat cleaned up and simplified; it now uses unittest test discovery to find its tests.

bpo-22104 [https://bugs.python.org/issue22104]: regrtest.py no longer holds a reference to the suite of tests loaded from test modules that don’t define test_main().

bpo-22111 [https://bugs.python.org/issue22111]: Assorted cleanups in test_imaplib. Patch by Milan Oberkirch.

bpo-22002 [https://bugs.python.org/issue22002]: Added load_package_tests function to test.support and used it to implement/augment test discovery in test_asyncio, test_email, test_importlib, test_json, and test_tools.

bpo-21976 [https://bugs.python.org/issue21976]: Fix test_ssl to accept LibreSSL version strings. Thanks to William Orr.

bpo-21918 [https://bugs.python.org/issue21918]: Converted test_tools from a module to a package containing separate test files for each tested script.

bpo-9554 [https://bugs.python.org/issue9554]: Use modern unittest features in test_argparse. Initial patch by Denver Coneybeare and Radu Voicilas.

bpo-20155 [https://bugs.python.org/issue20155]: Changed HTTP method names in failing tests in test_httpservers so that packet filtering software (specifically Windows Base Filtering Engine) does not interfere with the transaction semantics expected by the tests.

bpo-19493 [https://bugs.python.org/issue19493]: Refactored the ctypes test package to skip tests explicitly rather than silently.

bpo-18492 [https://bugs.python.org/issue18492]: All resources are now allowed when tests are not run by regrtest.py.

bpo-21634 [https://bugs.python.org/issue21634]: Fix pystone micro-benchmark: use floor division instead of true division to benchmark integers instead of floating point numbers. Set pystone version to 1.2. Patch written by Lennart Regebro.

bpo-21605 [https://bugs.python.org/issue21605]: Added tests for Tkinter images.

bpo-21493 [https://bugs.python.org/issue21493]: Added test for ntpath.expanduser(). Original patch by Claudiu Popa.

bpo-19925 [https://bugs.python.org/issue19925]: Added tests for the spwd module. Original patch by Vajrasky Kok.

bpo-21522 [https://bugs.python.org/issue21522]: Added Tkinter tests for Listbox.itemconfigure(), PanedWindow.paneconfigure(), and Menu.entryconfigure().

bpo-17756 [https://bugs.python.org/issue17756]: Fix test_code test when run from the installed location.

bpo-17752 [https://bugs.python.org/issue17752]: Fix distutils tests when run from the installed location.

bpo-18604 [https://bugs.python.org/issue18604]: Consolidated checks for GUI availability. All platforms now at least check whether Tk can be instantiated when the GUI resource is requested.

bpo-21275 [https://bugs.python.org/issue21275]: Fix a socket test on KFreeBSD.

bpo-21223 [https://bugs.python.org/issue21223]: Pass test_site/test_startup_imports when some of the extensions are built as builtins.

bpo-20635 [https://bugs.python.org/issue20635]: Added tests for Tk geometry managers.

Add test case for freeze.

bpo-20743 [https://bugs.python.org/issue20743]: Fix a reference leak in test_tcl.

bpo-21097 [https://bugs.python.org/issue21097]: Move test_namespace_pkgs into test_importlib.

bpo-21503 [https://bugs.python.org/issue21503]: Use test_both() consistently in test_importlib.

bpo-20939 [https://bugs.python.org/issue20939]: Avoid various network test failures due to new redirect of http://www.python.org/ to https://www.python.org: use http://www.example.com instead.

bpo-20668 [https://bugs.python.org/issue20668]: asyncio tests no longer rely on tests.txt file. (Patch by Vajrasky Kok)

bpo-21093 [https://bugs.python.org/issue21093]: Prevent failures of ctypes test_macholib on OS X if a copy of libz exists in $HOME/lib or /usr/local/lib.

bpo-22770 [https://bugs.python.org/issue22770]: Prevent some Tk segfaults on OS X when running gui tests.

bpo-23211 [https://bugs.python.org/issue23211]: Workaround test_logging failure on some OS X 10.6 systems.

bpo-23345 [https://bugs.python.org/issue23345]: Prevent test_ssl failures with large OpenSSL patch level values (like 0.9.8zc).

Tools/Demos

bpo-22314 [https://bugs.python.org/issue22314]: pydoc now works when the LINES environment variable is set.

bpo-22615 [https://bugs.python.org/issue22615]: Argument Clinic now supports the « type » argument for the int converter. This permits using the int converter with enums and typedefs.

bpo-20076 [https://bugs.python.org/issue20076]: The makelocalealias.py script no longer ignores UTF-8 mapping.

bpo-20079 [https://bugs.python.org/issue20079]: The makelocalealias.py script now can parse the SUPPORTED file from glibc sources and supports command line options for source paths.

bpo-22201 [https://bugs.python.org/issue22201]: Command-line interface of the zipfile module now correctly extracts ZIP files with directory entries. Patch by Ryan Wilson.

bpo-22120 [https://bugs.python.org/issue22120]: For functions using an unsigned integer return converter, Argument Clinic now generates a cast to that type for the comparison to -1 in the generated code. (This suppresses a compilation warning.)

bpo-18974 [https://bugs.python.org/issue18974]: Tools/scripts/diff.py now uses argparse instead of optparse.

bpo-21906 [https://bugs.python.org/issue21906]: Make Tools/scripts/md5sum.py work in Python 3. Patch by Zachary Ware.

bpo-21629 [https://bugs.python.org/issue21629]: Fix Argument Clinic’s « –converters » feature.

Add support for yield from to 2to3.

Add support for the PEP 465 matrix multiplication operator to 2to3.

bpo-16047 [https://bugs.python.org/issue16047]: Fix module exception list and __file__ handling in freeze. Patch by Meador Inge.

bpo-11824 [https://bugs.python.org/issue11824]: Consider ABI tags in freeze. Patch by Meador Inge.

bpo-20535 [https://bugs.python.org/issue20535]: PYTHONWARNING no longer affects the run_tests.py script. Patch by Arfrever Frehtes Taifersar Arahesis.

Windows

bpo-23260 [https://bugs.python.org/issue23260]: Update Windows installer

The bundled version of Tcl/Tk has been updated to 8.6.3. The most visible result of this change is the addition of new native file dialogs when running on Windows Vista or newer. See Tcl/Tk’s TIP 432 for more information. Also, this version of Tcl/Tk includes support for Windows 10.

bpo-17896 [https://bugs.python.org/issue17896]: The Windows build scripts now expect external library sources to be in PCbuild\..\externals rather than PCbuild\..\...

bpo-17717 [https://bugs.python.org/issue17717]: The Windows build scripts now use a copy of NASM pulled from svn.python.org to build OpenSSL.

bpo-21907 [https://bugs.python.org/issue21907]: Improved the batch scripts provided for building Python.

bpo-22644 [https://bugs.python.org/issue22644]: The bundled version of OpenSSL has been updated to 1.0.1j.

bpo-10747 [https://bugs.python.org/issue10747]: Use versioned labels in the Windows start menu. Patch by Olive Kilburn.

bpo-22980 [https://bugs.python.org/issue22980]: .pyd files with a version and platform tag (for example, « .cp35-win32.pyd ») will now be loaded in preference to those without tags.

(For information about older versions, consult the HISTORY file.)

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Le tutoriel Python

Python est un langage de programmation puissant et facile à apprendre. Il dispose de structures de données de haut niveau et permet une approche simple mais efficace de la programmation orientée objet. Parce que sa syntaxe est élégante, que son typage est dynamique et qu’il est interprété, Python est un langage idéal pour l’écriture de scripts et le développement rapide d’applications dans de nombreux domaines et sur la plupart des plateformes.

L’interpréteur Python et sa vaste bibliothèque standard sont disponibles librement, sous forme de sources ou de binaires, pour toutes les plateformes majeures depuis le site Internet https://www.python.org/ et peuvent être librement redistribués. Ce même site distribue et pointe vers des modules, des programmes et des outils tiers. Enfin, il constitue une source de documentation.

L’interpréteur Python peut être facilement étendu par de nouvelles fonctions et types de données implémentés en C ou C++ (ou tout autre langage appelable depuis le C). Python est également adapté comme langage d’extension pour personnaliser des applications.

Dans ce tutoriel, nous introduisons, de façon informelle, les concepts de base ainsi que les fonctionnalités du langage Python et de son écosystème. Il est utile de disposer d’un interpréteur Python à portée de main pour mettre en pratique les notions abordées. Si ce n’est pas possible, pas de souci, les exemples sont inclus et le tutoriel est adapté à une lecture « hors ligne ».

Pour une description des objets et modules de la bibliothèque standard, reportez-vous à La bibliothèque standard. La référence du langage Python présente le langage de manière plus formelle. Pour écrire des extensions en C ou en C++, lisez Extension et intégration de l’interpréteur Python et Manuel de référence de l’API Python/C. Des livres sont également disponibles qui couvrent Python dans le détail.

L’ambition de ce tutoriel n’est pas d’être exhaustif et de couvrir chaque fonctionnalité, ni même toutes les fonctionnalités les plus utilisées. Il vise, en revanche, à introduire les fonctionnalités les plus notables et à vous donner une bonne idée de la saveur et du style du langage. Après l’avoir lu, vous serez capable de lire et d’écrire des modules et des programmes Python et vous serez prêt à en apprendre davantage sur les modules de la bibliothèque Python décrits dans La bibliothèque standard.

Pensez aussi à consulter le Glossaire.

1. Mise en bouche

2. Mode d’emploi de l’interpréteur Python

2.1. Lancement de l’interpréteur

2.1.1. Passage d’arguments

2.1.2. Mode interactif

2.2. L’interpréteur et son environnement

2.2.1. Encodage du code source

3. Introduction informelle à Python

3.1. Utilisation de Python comme une calculatrice

3.1.1. Les nombres

3.1.2. Chaînes de caractères

3.1.3. Listes

3.2. Premiers pas vers la programmation

4. D’autres outils de contrôle de flux

4.1. L’instruction if

4.2. L’instruction for

4.3. La fonction range()

4.4. Les instructions break, continue et les clauses else au sein des boucles

4.5. L’instruction pass

4.6. Définir des fonctions

4.7. D’avantage sur la définition des fonctions

4.7.1. Valeur par défaut des arguments

4.7.2. Les arguments nommés

4.7.3. Listes d’arguments arbitraires

4.7.4. Séparation des listes d’arguments

4.7.5. Fonctions anonymes

4.7.6. Chaînes de documentation

4.7.7. Annotations de fonctions

4.8. Aparté : le style de codage

5. Structures de données

5.1. Compléments sur les listes

5.1.1. Utilisation des listes comme des piles

5.1.2. Utilisation des listes comme des files

5.1.3. Compréhensions de listes

5.1.4. Compréhensions de listes imbriquées

5.2. L’instruction del

5.3. Tuples et séquences

5.4. Ensembles

5.5. Dictionnaires

5.6. Techniques de boucles

5.7. Plus d’informations sur les conditions

5.8. Comparer des séquences avec d’autres types

6. Modules

6.1. Les modules en détail

6.1.1. Exécuter des modules comme des scripts

6.1.2. Les dossiers de recherche de modules

6.1.3. Fichiers Python « compilés »

6.2. Modules standards

6.3. La fonction dir()

6.4. Les paquets

6.4.1. Importer * depuis un paquet

6.4.2. Références internes dans un paquet

6.4.3. Paquets dans plusieurs dossiers

7. Les entrées/sorties

7.1. Formatage de données

7.1.1. Anciennes méthodes de formatage de chaînes

7.2. Lecture et écriture de fichiers

7.2.1. Méthodes des objets fichiers

7.2.2. Sauvegarde de données structurées avec le module json

8. Erreurs et exceptions

8.1. Les erreurs de syntaxe

8.2. Exceptions

8.3. Gestion des exceptions

8.4. Déclencher des exceptions

8.5. Exceptions définies par l’utilisateur

8.6. Définition d’actions de nettoyage

8.7. Actions de nettoyage prédéfinies

9. Classes

9.1. Objets et noms : préambule

9.2. Portées et espaces de nommage en Python

9.2.1. Exemple de portées et d’espaces de nommage

9.3. Une première approche des classes

9.3.1. Syntaxe de définition des classes

9.3.2. Objets classes

9.3.3. Objets instances

9.3.4. Objets méthode

9.3.5. Classes et variables d’instance

9.4. Remarques diverses

9.5. Héritage

9.5.1. Héritage multiple

9.6. Variables privées

9.7. Trucs et astuces

9.8. Itérateurs

9.9. Générateurs

9.10. Expressions et générateurs

10. Survol de la bibliothèque standard

10.1. Interface avec le système d’exploitation

10.2. Jokers sur les noms de fichiers

10.3. Paramètres passés en ligne de commande

10.4. Redirection de la sortie d’erreur et fin d’exécution

10.5. Recherche de motifs dans les chaînes

10.6. Mathématiques

10.7. Accès à internet

10.8. Dates et heures

10.9. Compression de données

10.10. Mesure des performances

10.11. Contrôle qualité

10.12. Piles fournies

11. Survol de la bibliothèque standard – Deuxième partie

11.1. Formatage de l’affichage

11.2. Gabarits (templates en anglais)

11.3. Traitement des données binaires

11.4. Fils d’exécution

11.5. Journalisation

11.6. Références faibles

11.7. Outils pour les listes

11.8. Arithmétique décimale à virgule flottante

12. Environnements virtuels et paquets

12.1. Introduction

12.2. Création d’environnements virtuels

12.3. Gestion des paquets avec pip

13. Pour aller plus loin

14. Édition interactive des entrées et substitution d’historique

14.1. Complétion automatique et édition de l’historique

14.2. Alternatives à l’interpréteur interactif

15. Arithmétique en nombres à virgule flottante : problèmes et limites

15.1. Erreurs de représentation

16. Annexe

16.1. Mode interactif

16.1.1. Gestion des erreurs

16.1.2. Scripts Python exécutables

16.1.3. Configuration du mode interactif

16.1.4. Modules de personnalisation

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1. Mise en bouche

Lorsqu’on travaille beaucoup sur ordinateur, on finit souvent par vouloir automatiser certaines tâches : par exemple, effectuer une recherche et un remplacement sur un grand nombre de fichiers de texte ; ou renommer et réorganiser des photos d’une manière un peu compliquée. Pour vous, ce peut être créer une petite base de données, une application graphique ou un simple jeu.

Quand on est un développeur professionnel, le besoin peut se faire sentir de travailler avec des bibliothèques C/C++/Java, mais on trouve que le cycle habituel écriture/compilation/test/compilation est trop lourd. Vous écrivez peut-être une suite de tests pour une telle bibliothèque et vous trouvez que l’écriture du code de test est pénible. Ou bien vous avez écrit un logiciel qui a besoin d’être extensible grâce à un langage de script, mais vous ne voulez pas concevoir ni implémenter un nouveau langage pour votre application.

Python est le langage parfait pour vous.

Vous pouvez écrire un script shell Unix ou des fichiers batch Windows pour certaines de ces tâches. Les scripts shell sont appropriés pour déplacer des fichiers et modifier des données textuelles, mais pas pour une application ayant une interface graphique ni pour des jeux. Vous pouvez écrire un programme en C/C++/Java, mais cela peut prendre beaucoup de temps, ne serait-ce que pour avoir une première maquette. Python est plus facile à utiliser et il vous aidera à terminer plus rapidement votre travail, que ce soit sous Windows, Mac OS X ou Unix.

Python reste facile à utiliser, mais c’est un vrai langage de programmation : il offre une bien meilleure structure et prise en charge des grands programmes que les scripts shell ou les fichiers batch. Par ailleurs, Python permet de beaucoup mieux vérifier les erreurs que le langage C et, en tant que langage de très haut niveau, il possède nativement des types de données très évolués tels que les tableaux de taille variable ou les dictionnaires. Grâce à ses types de données plus universels, Python est utilisable pour des domaines beaucoup plus variés que ne peuvent l’être Awk ou même Perl. Pourtant, vous pouvez faire de nombreuses choses au moins aussi facilement en Python que dans ces langages.

Python vous permet de découper votre programme en modules qui peuvent être réutilisés dans d’autres programmes Python. Il est fourni avec une grande variété de modules standards que vous pouvez utiliser comme base de vos programmes, ou comme exemples pour apprendre à programmer. Certains de ces modules donnent accès aux entrées/sorties, aux appels système, aux connecteurs réseaux et même aux outils comme Tk pour créer des interfaces graphiques.

Python est un langage interprété, ce qui peut vous faire gagner un temps considérable pendant le développement de vos programmes car aucune compilation ni édition de liens n’est nécessaire. L’interpréteur peut être utilisé de manière interactive, pour vous permettre d’expérimenter les fonctionnalités du langage, d’écrire des programmes jetables ou de tester des fonctions lors d’un développement incrémental. C’est aussi une calculatrice de bureau bien pratique.

Python permet d’écrire des programmes compacts et lisibles. Les programmes écrits en Python sont généralement beaucoup plus courts que leurs équivalents en C, C++ ou Java. Et ceci pour plusieurs raisons :

les types de données de haut niveau vous permettent d’exprimer des opérations complexes en une seule instruction ;

les instructions sont regroupées entre elles grâce à l’indentation, plutôt que par l’utilisation d’accolades ;

aucune déclaration de variable ou d’argument n’est nécessaire.

Python est extensible : si vous savez écrire un programme en C, une nouvelle fonction ou module peut être facilement ajouté à l’interpréteur afin de l’étendre, que ce soit pour effectuer des opérations critiques à vitesse maximale ou pour lier des programmes en Python à des bibliothèques disponibles uniquement sous forme binaire (par exemple des bibliothèques graphiques dédiées à un matériel). Une fois que vous êtes à l’aise avec ces principes, vous pouvez relier l’interpréteur Python à une application écrite en C et l’utiliser comme un langage d’extensions ou de commandes pour cette application.

Au fait, le nom du langage provient de l’émission de la BBC « Monty Python’s Flying Circus » et n’a rien à voir avec les reptiles. Faire référence aux sketchs des Monty Python dans la documentation n’est pas seulement permis, c’est encouragé !

Maintenant que vos papilles ont été chatouillées, nous allons pouvoir rentrer dans le vif du sujet Python. Et comme la meilleure façon d’apprendre un langage est de l’utiliser, ce tutoriel vous invite à jouer avec l’interpréteur au fur et à mesure de votre lecture.

Dans le prochain chapitre, nous expliquons l’utilisation de l’interpréteur. Ce n’est pas la section la plus passionnante, mais c’est un passage obligé pour que vous puissiez mettre en pratique les exemples donnés plus loin.

Le reste du tutoriel présente diverses fonctionnalités du langage et du système Python au travers d’exemples, en commençant par les expressions simples, les instructions et les types de données, jusqu’à aborder des concepts avancés comme les exceptions et les classes, en passant par les fonctions et modules.

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2. Mode d’emploi de l’interpréteur Python

2.1. Lancement de l’interpréteur

L’interpréteur Python se trouve en général comme /usr/local/bin/python3.6 sur ces machines où il est disponible ; ajoutez /usr/local/bin au chemin de recherche de votre shell Unix afin de pouvoir le lancer en tapant la commande :

python3.6

dans le shell. 1 Le choix du répertoire où se trouve l’interpréteur étant une option d’installation, d’autres chemins sont possibles ; voyez avec votre gourou Python local ou votre administrateur système (par exemple, /usr/local/python est un endroit courant).

Sur les machines Windows, Python est habituellement installé dans C:\Python36, même si vous pouvez changer cela lorsque vous lancez l’installateur. Pour ajouter ce dossier à votre chemin de recherche, vous pouvez taper la commande suivante dans un prompt de commande DOS :

set path=%path%;C:\python36

Tapez un caractère de fin de fichier (Ctrl-D sous Unix, Ctrl-Z sous Windows) dans une invite de commande primaire provoque la fermeture de l’interpréteur avec un code de sortie nul. Si cela ne fonctionne pas, vous pouvez fermer l’interpréteur en tapant la commande quit().

Les fonctionnalités d’édition de l’interpréteur comprennent l’édition interactive, la substitution depuis l’historique et la complétion sur les systèmes qui gèrent readline. Un moyen rapide de tester comment est gérée l’édition de la ligne de commande, c’est de taper Control-P à la première invite de commande que vous rencontrez. Si cela bipe, vous disposez de l’édition de la ligne de commande ; lisez l’appendice Édition interactive des entrées et substitution d’historique pour une introduction aux touches. Si rien ne semble se produire ou si ^P s’affiche, l’édition de la ligne de commande n’est pas disponible ; vous serez seulement en mesure d’utiliser la touche retour arrière pour supprimer des caractères de la ligne courante.

L’interpréteur fonctionne de façon similaire au shell Unix : lorsqu’il est appelé avec l’entrée standard connectée à un périphérique tty, il lit et exécute les commandes de façon interactive ; lorsqu’il est appelé avec un nom de fichier en argument ou avec un fichier comme entrée standard, il lit et exécute un script depuis ce fichier.

Une autre façon de lancer l’interpréteur est python -c commande [arg] .... Cela exécute les instructions de commande de façon analogue à l’option -c du shell. Parce que les instructions Python contiennent souvent des espaces et d’autres caractères spéciaux pour le shell, il est généralement conseillé de mettre commande entre guillemets simples.

Certains modules Python sont aussi utiles en tant que scripts. Ils peuvent être appelés avec python -m module [arg] ... qui exécute le fichier source de module comme si vous aviez tapé son nom complet dans la ligne de commande.

Quand un fichier de script est utilisé, il est parfois utile de pouvoir lancer le script puis d’entrer dans le mode interactif après coup. Cela est possible en passant -i avant le script.

Tous les paramètres utilisables en ligne de commande sont documentés dans Ligne de commande et environnement.

2.1.1. Passage d’arguments

Lorsqu’ils sont connus de l’interpréteur, le nom du script et les arguments additionnels sont représentés sous forme d’une liste assignée à la variable argv du module sys. Vous pouvez y accéder en exécutant import sys. La liste contient au minimum un élément ; quand aucun script ni aucun argument n’est donné, sys.argv[0] est une chaine vide. Quand '-' (qui représente l’entrée standard) est passé comme nom de script, sys.argv[0] contient '-'. Quand -c commande est utilisé, sys.argv[0] contient '-c'. Enfin, quand -m module est utilisé, le nom complet du module est assigné à sys.argv[0]. Les options trouvées après -c commande ou -m module ne sont pas lues comme options de l’interpréteur Python mais laissées dans sys.argv pour être utilisées par le module ou la commande.

2.1.2. Mode interactif

Lorsque des commandes sont lues depuis un tty, l’interpréteur est dit être en mode interactif. Dans ce mode, il demande la commande suivante avec le prompt primaire, en général trois signes plus-grand-que (>>>) ; pour les lignes de continuation, il affiche le prompt secondaire, par défaut trois points (...). L’interpréteur affiche un message de bienvenue indiquant son numéro de version et une notice de copyright avant d’afficher le premier prompt :

$ python3.6
Python 3.6 (default, Sep 16 2015, 09:25:04)
[GCC 4.8.2] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>>

Les lignes de continuation sont nécessaires pour entrer une construction multi-lignes. Par exemple, regardez cette instruction if :

>>> the_world_is_flat = True
>>> if the_world_is_flat:
...     print("Be careful not to fall off!")
...
Be careful not to fall off!

Pour plus d’informations sur le mode interactif, voir Mode interactif.

2.2. L’interpréteur et son environnement

2.2.1. Encodage du code source

Par défaut, Python considère que ses fichiers sources sont encodés en UTF-8. Dans cet encodage, les caractères de la plupart des langues peuvent être utilisés ensemble dans les chaînes de caractères, identifiants et commentaires. Notez que la bibliothèque standard n’utilise que des caractères ASCII dans ses identifiants et que nous considérons que c’est une bonne habitude que tout code portable devrait suivre. Pour afficher correctement tous ces caractères, votre éditeur doit reconnaître que le fichier est en UTF-8 et utiliser une police qui comprend tous les caractères utilisés dans le fichier.

Pour annoncer un encodage différent de l’encodage par défaut, une ligne de commentaire particulière doit être ajoutée en tant que première ligne du fichier. Sa syntaxe est la suivante :

# -*- coding: encoding -*-

où encoding est un des codecs supporté par Python.

Par exemple, pour déclarer un encodage Windows-1252, la première ligne de votre code source doit être :

# -*- coding: cp1252 -*-

Une exception à la règle première ligne est lorsque la première ligne est un shebang UNIX. Dans ce cas, la déclaration de l’encodage doit être placée sur la deuxième ligne du fichier. Par exemple :

#!/usr/bin/env python3
# -*- coding: cp1252 -*-

Notes

1

Sous Unix, par défaut, l’interpréteur Python 3.x n’est pas installé sous le nom de python afin de ne pas entrer en conflit avec une éventuelle installation de Python 2.x.

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3. Introduction informelle à Python

Dans les exemples qui suivent, les entrées et sorties se distinguent par la présence ou l’absence d’invite (>>> et …) : pour reproduire les exemples, vous devez taper tout ce qui est après l’invite, au moment où celle-ci apparaît ; les lignes qui n’affichent pas d’invite sont les sorties de l’interpréteur. Notez qu’une invite secondaire affichée seule sur une ligne dans un exemple indique que vous devez entrer une ligne vide ; ceci est utilisé pour terminer une commande multi-lignes.

Beaucoup d’exemples de ce manuel, même ceux saisis à l’invite de l’interpréteur, incluent des commentaires. Les commentaires en Python commencent avec un caractère croisillon, #, et s’étendent jusqu’à la fin de la ligne. Un commentaire peut apparaître au début d’une ligne ou à la suite d’un espace ou de code, mais pas à l’intérieur d’une chaîne de caractères littérale. Un caractère croisillon à l’intérieur d’une chaîne de caractères est juste un caractère croisillon. Comme les commentaires ne servent qu’à expliquer le code et ne sont pas interprétés par Python, ils peuvent être ignorés lorsque vous tapez les exemples.

Quelques exemples :

# this is the first comment
spam = 1  # and this is the second comment
          # ... and now a third!
text = "# This is not a comment because it's inside quotes."

3.1. Utilisation de Python comme une calculatrice

Essayons quelques commandes Python simples. Démarrez l’interpréteur et attendez l’invite primaire, >>>. Ça ne devrait pas être long.

3.1.1. Les nombres

L’interpréteur agit comme une simple calculatrice : vous pouvez lui entrer une expression et il vous affiche la valeur. La syntaxe des expressions est simple : les opérateurs +, -, * et / fonctionnent comme dans la plupart des langages (par exemple, Pascal ou C) ; les parenthèses peuvent être utilisées pour faire des regroupements. Par exemple :

>>> 2 + 2
4
>>> 50 - 5*6
20
>>> (50 - 5*6) / 4
5.0
>>> 8 / 5  # division always returns a floating point number
1.6

Les nombres entiers (comme 2, 4, 20) sont de type int, alors que les décimaux (comme 5.0, 1.6) sont de type float. Vous trouvez plus de détails sur les types numériques plus loin dans ce tutoriel.

Les divisions (/) donnent toujours des float. Utilisez l’opérateur // pour effectuer des divisions entières et donc obtenir un résultat entier. Pour obtenir le reste d’une division entière, utilisez l’opérateur % :

>>> 17 / 3  # classic division returns a float
5.666666666666667
>>>
>>> 17 // 3  # floor division discards the fractional part
5
>>> 17 % 3  # the % operator returns the remainder of the division
2
>>> 5 * 3 + 2  # result * divisor + remainder
17

En Python, il est possible de calculer des puissances avec l’opérateur ** 1 :

>>> 5 ** 2  # 5 squared
25
>>> 2 ** 7  # 2 to the power of 7
128

Le signe égal (=) est utilisé pour affecter une valeur à une variable. Dans ce cas, aucun résultat n’est affiché avant l’invite suivante :

>>> width = 20
>>> height = 5 * 9
>>> width * height
900

Si une variable n’est pas « définie » (si aucune valeur ne lui a été affectée), son utilisation produit une erreur :

>>> n  # try to access an undefined variable
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
NameError: name 'n' is not defined

Les nombres à virgule flottante sont tout à fait admis (NdT : Python utilise le point . comme séparateur entre la partie entière et la partie décimale des nombres, c’est la convention anglo-saxonne) ; les opérateurs avec des opérandes de types différents convertissent l’opérande de type entier en type virgule flottante :

>>> 4 * 3.75 - 1
14.0

En mode interactif, la dernière expression affichée est affectée à la variable _. Ainsi, lorsque vous utilisez Python comme calculatrice, cela vous permet de continuer des calculs facilement, par exemple :

>>> tax = 12.5 / 100
>>> price = 100.50
>>> price * tax
12.5625
>>> price + _
113.0625
>>> round(_, 2)
113.06

Cette variable doit être considérée comme une variable en lecture seule par l’utilisateur. Ne lui affectez pas de valeur explicitement — vous créeriez ainsi une variable locale indépendante, avec le même nom, qui masquerait la variable native et son fonctionnement magique.

En plus des int et des float, il existe les Decimal et les Fraction. Python gère aussi les nombres complexes, en utilisant le suffixe j ou J pour indiquer la partie imaginaire (tel que 3+5j).

3.1.2. Chaînes de caractères

En plus des nombres, Python sait aussi manipuler des chaînes de caractères, qui peuvent être exprimées de différentes manières. Elles peuvent être écrites entre guillemets simples ('...') ou entre guillemets ("...") sans distinction 2. \ peut être utilisé pour protéger un guillemet :

>>> 'spam eggs'  # single quotes
'spam eggs'
>>> 'doesn\'t'  # use \' to escape the single quote...
"doesn't"
>>> "doesn't"  # ...or use double quotes instead
"doesn't"
>>> '"Yes," they said.'
'"Yes," they said.'
>>> "\"Yes,\" they said."
'"Yes," they said.'
>>> '"Isn\'t," they said.'
'"Isn\'t," they said.'

En mode interactif, l’interpréteur affiche les chaînes de caractères entre guillemets. Les guillemets et autres caractères spéciaux sont protégés avec des barres obliques inverses (backslash en anglais). Bien que cela puisse être affiché différemment de ce qui a été entré (les guillemets peuvent changer), les deux formats sont équivalents. La chaîne est affichée entre guillemets si elle contient un guillemet simple et aucun guillemet, sinon elle est affichée entre guillemets simples. La fonction print() affiche les chaînes de manière plus lisible, en retirant les guillemets et en affichant les caractères spéciaux qui étaient protégés par une barre oblique inverse :

>>> '"Isn\'t," they said.'
'"Isn\'t," they said.'
>>> print('"Isn\'t," they said.')
"Isn't," they said.
>>> s = 'First line.\nSecond line.'  # \n means newline
>>> s  # without print(), \n is included in the output
'First line.\nSecond line.'
>>> print(s)  # with print(), \n produces a new line
First line.
Second line.

Si vous ne voulez pas que les caractères précédés d’un \ soient interprétés comme étant spéciaux, utilisez les chaînes brutes (raw strings en anglais) en préfixant la chaîne d’un r :

>>> print('C:\some\name')  # here \n means newline!
C:\some
ame
>>> print(r'C:\some\name')  # note the r before the quote
C:\some\name

Les chaînes de caractères peuvent s’étendre sur plusieurs lignes. Utilisez alors des triples guillemets, simples ou doubles : '''...''' ou """...""". Les retours à la ligne sont automatiquement inclus, mais on peut l’empêcher en ajoutant \ à la fin de la ligne. L’exemple suivant :

print("""\
Usage: thingy [OPTIONS]
     -h                        Display this usage message
     -H hostname               Hostname to connect to
""")

produit l’affichage suivant (notez que le premier retour à la ligne n’est pas inclus) :

Usage: thingy [OPTIONS]
     -h                        Display this usage message
     -H hostname               Hostname to connect to

Les chaînes peuvent être concaténées (collées ensemble) avec l’opérateur + et répétées avec l’opérateur * :

>>> # 3 times 'un', followed by 'ium'
>>> 3 * 'un' + 'ium'
'unununium'

Plusieurs chaînes de caractères, écrites littéralement (c’est-à-dire entre guillemets), côte à côte, sont automatiquement concaténées.

>>> 'Py' 'thon'
'Python'

Cette fonctionnalité est surtout intéressante pour couper des chaînes trop longues :

>>> text = ('Put several strings within parentheses '
...         'to have them joined together.')
>>> text
'Put several strings within parentheses to have them joined together.'

Cela ne fonctionne cependant qu’avec les chaînes littérales, pas avec les variables ni les expressions :

>>> prefix = 'Py'
>>> prefix 'thon'  # can't concatenate a variable and a string literal
  ...
SyntaxError: invalid syntax
>>> ('un' * 3) 'ium'
  ...
SyntaxError: invalid syntax

Pour concaténer des variables, ou des variables avec des chaînes littérales, utilisez l’opérateur + :

>>> prefix + 'thon'
'Python'

Les chaînes de caractères peuvent être indexées (i.e. on peut accéder aux caractères par leur position), le premier caractère d’une chaîne étant à la position 0. Il n’existe pas de type distinct pour les caractères, un caractère est simplement une chaîne de longueur 1 :

>>> word = 'Python'
>>> word[0]  # character in position 0
'P'
>>> word[5]  # character in position 5
'n'

Les indices peuvent également être négatifs, on compte alors en partant de la droite. Par exemple :

>>> word[-1]  # last character
'n'
>>> word[-2]  # second-last character
'o'
>>> word[-6]
'P'

Notez que, comme -0 égale 0, les indices négatifs commencent par -1.

En plus d’accéder à un élément par son indice, il est aussi possible de « trancher » (slice en anglais) une chaîne. Accéder à une chaîne par un indice permet d’obtenir un caractère, trancher permet d’obtenir une sous-chaîne :

>>> word[0:2]  # characters from position 0 (included) to 2 (excluded)
'Py'
>>> word[2:5]  # characters from position 2 (included) to 5 (excluded)
'tho'

Notez que le début est toujours inclus et la fin toujours exclue. Cela assure que s[:i] + s[i:] est toujours égal à s :

>>> word[:2] + word[2:]
'Python'
>>> word[:4] + word[4:]
'Python'

Les valeurs par défaut des indices de tranches ont une utilité ; le premier indice vaut zéro par défaut (i.e. lorsqu’il est omis), le deuxième correspond par défaut à la taille de la chaîne de caractères

>>> word[:2]   # character from the beginning to position 2 (excluded)
'Py'
>>> word[4:]   # characters from position 4 (included) to the end
'on'
>>> word[-2:]  # characters from the second-last (included) to the end
'on'

Pour mémoriser la façon dont les tranches fonctionnent, vous pouvez imaginer que les indices pointent entre les caractères, le côté gauche du premier caractère ayant la position 0. Le côté droit du dernier caractère d’une chaîne de n caractères a alors pour indice n. Par exemple :

 +---+---+---+---+---+---+
 | P | y | t | h | o | n |
 +---+---+---+---+---+---+
 0   1   2   3   4   5   6
-6  -5  -4  -3  -2  -1

La première ligne de nombres donne la position des indices 0…6 dans la chaîne ; la deuxième ligne donne l’indice négatif correspondant. La tranche de i à j est constituée de tous les caractères situés entre les bords libellés i et j, respectivement.

Pour des indices non négatifs, la longueur d’une tranche est la différence entre ces indices, si les deux sont entre les bornes. Par exemple, la longueur de word[1:3] est 2.

Utiliser un indice trop grand produit une erreur :

>>> word[42]  # the word only has 6 characters
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
IndexError: string index out of range

Cependant, les indices hors bornes sont gérés silencieusement lorsqu’ils sont utilisés dans des tranches :

>>> word[4:42]
'on'
>>> word[42:]
''

Les chaînes de caractères, en Python, ne peuvent pas être modifiées. On dit qu’elles sont immuables. Affecter une nouvelle valeur à un indice dans une chaîne produit une erreur :

>>> word[0] = 'J'
  ...
TypeError: 'str' object does not support item assignment
>>> word[2:] = 'py'
  ...
TypeError: 'str' object does not support item assignment

Si vous avez besoin d’une chaîne différente, vous devez en créer une nouvelle :

>>> 'J' + word[1:]
'Jython'
>>> word[:2] + 'py'
'Pypy'

La fonction native len() renvoie la longueur d’une chaîne :

>>> s = 'supercalifragilisticexpialidocious'
>>> len(s)
34

Voir aussi

Type Séquence de Texte — str

Les chaînes de caractères sont des exemples de types séquences ; elles acceptent donc les opérations classiques prises en charge par ces types.

Méthodes de chaînes de caractères

Les chaînes de caractères gèrent un large éventail de méthodes de transformations basiques et de recherche.

Chaînes de caractères formatées littérales

Des chaînes littérales qui contiennent des expressions.

Syntaxe de formatage de chaîne

Informations sur le formatage des chaînes avec la méthode str.format().

Formatage de chaines à la printf

Description détaillée des anciennes méthodes de mise en forme, appelées lorsque les chaînes de caractères sont à gauche de l’opérateur %.

3.1.3. Listes

Python connaît différents types de données combinés, utilisés pour regrouper plusieurs valeurs. Le plus souple est la liste, qui peut être écrit comme une suite, placée entre crochets, de valeurs (éléments) séparées par des virgules. Les éléments d’une liste ne sont pas obligatoirement tous du même type, bien qu’à l’usage ce soit souvent le cas.

>>> squares = [1, 4, 9, 16, 25]
>>> squares
[1, 4, 9, 16, 25]

Comme les chaînes de caractères (et toute autre type de sequence), les listes peuvent être indicées et découpées :

>>> squares[0]  # indexing returns the item
1
>>> squares[-1]
25
>>> squares[-3:]  # slicing returns a new list
[9, 16, 25]

Toutes les opérations par tranches renvoient une nouvelle liste contenant les éléments demandés. Cela signifie que l’opération suivante renvoie une copie (superficielle) de la liste :

>>> squares[:]
[1, 4, 9, 16, 25]

Les listes gèrent aussi les opérations comme les concaténations :

>>> squares + [36, 49, 64, 81, 100]
[1, 4, 9, 16, 25, 36, 49, 64, 81, 100]

Mais à la différence des chaînes qui sont immuables, les listes sont muables : il est possible de modifier leur contenu :

>>> cubes = [1, 8, 27, 65, 125]  # something's wrong here
>>> 4 ** 3  # the cube of 4 is 64, not 65!
64
>>> cubes[3] = 64  # replace the wrong value
>>> cubes
[1, 8, 27, 64, 125]

Il est aussi possible d’ajouter de nouveaux éléments à la fin d’une liste avec la méthode append() (les méthodes sont abordées plus tard) :

>>> cubes.append(216)  # add the cube of 6
>>> cubes.append(7 ** 3)  # and the cube of 7
>>> cubes
[1, 8, 27, 64, 125, 216, 343]

Des affectations de tranches sont également possibles, ce qui peut même modifier la taille de la liste ou la vider complètement :

>>> letters = ['a', 'b', 'c', 'd', 'e', 'f', 'g']
>>> letters
['a', 'b', 'c', 'd', 'e', 'f', 'g']
>>> # replace some values
>>> letters[2:5] = ['C', 'D', 'E']
>>> letters
['a', 'b', 'C', 'D', 'E', 'f', 'g']
>>> # now remove them
>>> letters[2:5] = []
>>> letters
['a', 'b', 'f', 'g']
>>> # clear the list by replacing all the elements with an empty list
>>> letters[:] = []
>>> letters
[]

La primitive len() s’applique aussi aux listes :

>>> letters = ['a', 'b', 'c', 'd']
>>> len(letters)
4

Il est possible d’imbriquer des listes (i.e. créer des listes contenant d’autres listes). Par exemple :

>>> a = ['a', 'b', 'c']
>>> n = [1, 2, 3]
>>> x = [a, n]
>>> x
[['a', 'b', 'c'], [1, 2, 3]]
>>> x[0]
['a', 'b', 'c']
>>> x[0][1]
'b'

3.2. Premiers pas vers la programmation

Bien entendu, on peut utiliser Python pour des tâches plus compliquées que d’additionner deux et deux. Par exemple, on peut écrire le début de la suite de Fibonacci comme ceci :

>>> # Fibonacci series:
... # the sum of two elements defines the next
... a, b = 0, 1
>>> while b < 10:
...     print(b)
...     a, b = b, a+b
...
1
1
2
3
5
8

Cet exemple introduit plusieurs nouvelles fonctionnalités.

La première ligne contient une affectation multiple : les variables a et b se voient affecter simultanément leurs nouvelles valeurs 0 et 1. Cette méthode est encore utilisée à la dernière ligne, pour démontrer que les expressions sur la partie droite de l’affectation sont toutes évaluées avant que les affectations ne soient effectuées. Ces expressions en partie droite sont toujours évaluées de la gauche vers la droite.

La boucle while s’exécute tant que la condition (ici : b < 10) reste vraie. En Python, comme en C, tout entier différent de zéro est vrai et zéro est faux. La condition peut aussi être une chaîne de caractères, une liste, ou en fait toute séquence ; une séquence avec une valeur non nulle est vraie, une séquence vide est fausse. Le test utilisé dans l’exemple est une simple comparaison. Les opérateurs de comparaison standards sont écrits comme en C : < (inférieur), > (supérieur), == (égal), <= (inférieur ou égal), >= (supérieur ou égal) et != (non égal).

Le corps de la boucle est indenté : l’indentation est la méthode utilisée par Python pour regrouper des instructions. En mode interactif, vous devez saisir une tabulation ou des espaces pour chaque ligne indentée. En pratique, vous aurez intérêt à utiliser un éditeur de texte pour les saisies plus compliquées ; tous les éditeurs de texte dignes de ce nom disposent d’une fonction d’auto-indentation. Lorsqu’une expression composée est saisie en mode interactif, elle doit être suivie d’une ligne vide pour indiquer qu’elle est terminée (car l’analyseur ne peut pas deviner que vous venez de saisir la dernière ligne). Notez bien que toutes les lignes à l’intérieur d’un bloc doivent être indentées au même niveau.

La fonction print() écrit les valeurs des paramètres qui lui sont fournis. Ce n’est pas la même chose que d’écrire l’expression que vous voulez afficher (comme nous l’avons fait dans l’exemple de la calculatrice), en raison de la manière qu’a print de gérer les paramètres multiples, les nombres décimaux et les chaînes. Les chaînes sont affichées sans apostrophe et une espace est insérée entre les éléments de telle sorte que vous pouvez facilement formater les choses, comme ceci :

>>> i = 256*256
>>> print('The value of i is', i)
The value of i is 65536

Le paramètre nommé end peut servir pour enlever le retour à la ligne ou pour terminer la ligne par une autre chaîne :

>>> a, b = 0, 1
>>> while b < 1000:
...     print(b, end=',')
...     a, b = b, a+b
...
1,1,2,3,5,8,13,21,34,55,89,144,233,377,610,987,

Notes

1

Puisque ** est prioritaire sur -, -3 ** 2 est interprété -(3 ** 2) et vaut donc -9. Pour éviter cela et obtenir 9, utilisez des parenthèses : (-3) ** 2.

2

Contrairement à d’autres langages, les caractères spéciaux comme \n ont la même signification entre guillemets ("...") ou entre guillemets simples ('...'). La seule différence est que, dans une chaîne entre guillemets, il n’est pas nécessaire de protéger les guillemets simples et vice-versa.

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4. D’autres outils de contrôle de flux

En plus de l’instruction while qui vient d’être présentée, Python dispose des instructions de contrôle de flux classiques que l’on trouve dans d’autres langages, mais toujours avec ses propres tournures.

4.1. L’instruction if

L’instruction if est sans doute la plus connue. Par exemple :

>>> x = int(input("Please enter an integer: "))
Please enter an integer: 42
>>> if x < 0:
...     x = 0
...     print('Negative changed to zero')
... elif x == 0:
...     print('Zero')
... elif x == 1:
...     print('Single')
... else:
...     print('More')
...
More

Il peut y avoir un nombre quelconque de parties elif et la partie else est facultative. Le mot clé elif est un raccourci pour else if, mais permet de gagner un niveau d’indentation. Une séquence if … elif … elif … est par ailleurs équivalente aux instructions switch ou case disponibles dans d’autres langages.

4.2. L’instruction for

L’instruction for que propose Python est un peu différente de celle que l’on peut trouver en C ou en Pascal. Au lieu de toujours itérer sur une suite arithmétique de nombres (comme en Pascal), ou de donner à l’utilisateur la possibilité de définir le pas d’itération et la condition de fin (comme en C), l’instruction for en Python itère sur les éléments d’une séquence (qui peut être une liste, une chaîne de caractères…), dans l’ordre dans lequel ils apparaissent dans la séquence. Par exemple :

>>> # Measure some strings:
... words = ['cat', 'window', 'defenestrate']
>>> for w in words:
...     print(w, len(w))
...
cat 3
window 6
defenestrate 12

Si vous devez modifier la séquence sur laquelle s’effectue l’itération à l’intérieur de la boucle (par exemple pour dupliquer ou supprimer un élément), il est plus que recommandé de commencer par en faire une copie, celle-ci n’étant pas implicite. La notation « par tranches » rend cette opération particulièrement simple :

>>> for w in words[:]:  # Loop over a slice copy of the entire list.
...     if len(w) > 6:
...         words.insert(0, w)
...
>>> words
['defenestrate', 'cat', 'window', 'defenestrate']

Avec for w in words:, l’exemple tenterait de créer une liste infinie, en insérant defenestrate indéfiniment.

4.3. La fonction range()

Si vous devez itérer sur une suite de nombres, la fonction native range() est faite pour cela. Elle génère des suites arithmétiques :

>>> for i in range(5):
...     print(i)
...
0
1
2
3
4

Le dernier élément fourni en paramètre ne fait jamais partie de la liste générée ; range(10) génère une liste de 10 valeurs, dont les valeurs vont de 0 à 9. Il est possible de spécifier une valeur de début et une valeur d’incrément différentes (y compris négative pour cette dernière, que l’on appelle également parfois le “pas”) :

range(5, 10)
   5, 6, 7, 8, 9

range(0, 10, 3)
   0, 3, 6, 9

range(-10, -100, -30)
  -10, -40, -70

Pour itérer sur les indices d’une séquence, on peut combiner les fonctions range() et len() :

>>> a = ['Mary', 'had', 'a', 'little', 'lamb']
>>> for i in range(len(a)):
...     print(i, a[i])
...
0 Mary
1 had
2 a
3 little
4 lamb

Cependant, dans la plupart des cas, il est plus pratique d’utiliser la fonction enumerate(). Voyez pour cela Techniques de boucles.

Une chose étrange se produit lorsqu’on affiche un range :

>>> print(range(10))
range(0, 10)

L’objet renvoyé par range() se comporte presque comme une liste, mais ce n’en est pas une. Cet objet génère les éléments de la séquence au fur et à mesure de l’itération, sans réellement produire la liste en tant que telle, économisant ainsi de l’espace.

On appelle de tels objets des iterables, c’est à dire des objets qui conviennent à des iterateurs, des fonctions ou constructions qui s’attendent à quelque chose duquel ils peuvent tirer des éléments, successivement, jusqu’à épuisement. On a vu que l’instruction for est un itérateur. La fonction list() en est un autre, qui crée des listes à partir d’itérables :

>>> list(range(5))
[0, 1, 2, 3, 4]

Plus loin nous voyons d’autres fonctions qui donnent des itérables ou en prennent en paramètre.

4.4. Les instructions break, continue et les clauses else au sein des boucles

L’instruction break, comme en C, interrompt la boucle for ou while la plus profonde.

Les boucles peuvent également disposer d’une instruction else ; celle-ci est exécutée lorsqu’une boucle se termine alors que tous ses éléments ont été traités (dans le cas d’un for) ou que la condition devient fausse (dans le cas d’un while), mais pas lorsque la boucle est interrompue par une instruction break. L’exemple suivant, qui effectue une recherche de nombres premiers, en est une démonstration :

>>> for n in range(2, 10):
...     for x in range(2, n):
...         if n % x == 0:
...             print(n, 'equals', x, '*', n//x)
...             break
...     else:
...         # loop fell through without finding a factor
...         print(n, 'is a prime number')
...
2 is a prime number
3 is a prime number
4 equals 2 * 2
5 is a prime number
6 equals 2 * 3
7 is a prime number
8 equals 2 * 4
9 equals 3 * 3

(Oui, ce code est correct. Regardez attentivement : l’instruction else est rattachée à la boucle for, et non à l’instruction if.)

Lorsqu’elle utilisée dans une boucle, la clause else est donc plus proche de celle associée à une instruction try que de celle associée à une instruction if : la clause else d’une instruction try s’exécute lorsqu’aucune exception n’est déclenchée, et celle d’une boucle lorsque aucun break n’intervient. Plus plus d’informations sur l’instruction try et le traitement des exceptions, consultez Gestion des exceptions.

L’instruction continue, également empruntée au C, fait passer la boucle à son itération suivante :

>>> for num in range(2, 10):
...     if num % 2 == 0:
...         print("Found an even number", num)
...         continue
...     print("Found a number", num)
Found an even number 2
Found a number 3
Found an even number 4
Found a number 5
Found an even number 6
Found a number 7
Found an even number 8
Found a number 9

4.5. L’instruction pass

L’instruction pass ne fait rien. Elle peut être utilisée lorsqu’une instruction est nécessaire pour fournir une syntaxe correcte, mais qu’aucune action ne doit être effectuée. Par exemple :

>>> while True:
...     pass  # Busy-wait for keyboard interrupt (Ctrl+C)
...

On utilise couramment cette instruction pour créer des classes minimales :

>>> class MyEmptyClass:
...     pass
...

Un autre cas d’utilisation du pass est de réserver un espace en phase de développement pour une fonction ou un traitement conditionnel, vous permettant ainsi de construire votre code à un niveau plus abstrait. L’instruction pass est alors ignorée silencieusement :

>>> def initlog(*args):
...     pass   # Remember to implement this!
...

4.6. Définir des fonctions

On peut créer une fonction qui écrit la suite de Fibonacci jusqu’à une limite imposée :

>>> def fib(n):    # write Fibonacci series up to n
...     """Print a Fibonacci series up to n."""
...     a, b = 0, 1
...     while a < n:
...         print(a, end=' ')
...         a, b = b, a+b
...     print()
...
>>> # Now call the function we just defined:
... fib(2000)
0 1 1 2 3 5 8 13 21 34 55 89 144 233 377 610 987 1597

Le mot-clé def introduit une définition de fonction. Il doit être suivi du nom de la fonction et d’une liste, entre parenthèses, de ses paramètres. L’instruction qui constitue le corps de la fonction débute à la ligne suivante et doit être indentée.

La première instruction d’une fonction peut, de façon facultative, être une chaîne de caractères littérale ; cette chaîne de caractères sera alors la chaîne de documentation de la fonction, appelée docstring (consultez la section Chaînes de documentation pour en savoir plus). Il existe des outils qui utilisent ces chaînes de documentation pour générer automatiquement une documentation en ligne ou imprimée, ou pour permettre à l’utilisateur de naviguer de façon interactive dans le code ; prenez-en l’habitude, c’est une bonne pratique que de documenter le code que vous écrivez.

L’exécution d’une fonction introduit une nouvelle table de symboles utilisée par les variables locales de la fonction. Plus précisément, toutes les affectations de variables effectuées au sein d’une fonction stockent la valeur dans la table de symboles locale ; en revanche, les références de variables sont recherchées dans la table de symboles locale, puis dans la table de symboles locale des fonctions englobantes, puis dans la table de symboles globale et finalement dans la table de noms des primitives. Par conséquent, bien qu’elles puissent être référencées, il est impossible d’affecter une valeur à une variable globale (sauf en utilisant une instruction global).

Les paramètres effectifs (arguments) d’une fonction sont introduits dans la table de symboles locale de la fonction appelée au moment où elle est appelée ; par conséquent, les passages de paramètres se font par valeur, la valeur étant toujours une référence à un objet et non la valeur de l’objet lui-même. 1 Lorsqu’une fonction appelle une autre fonction, une nouvelle table de symboles locale est créée pour cet appel.

Une définition de fonction introduit le nom de la fonction dans la table de symboles courante. La valeur du nom de la fonction est un type qui est reconnu par l’interpréteur comme une fonction définie par l’utilisateur. Cette valeur peut être affectée à un autre nom qui pourra alors être utilisé également comme une fonction. Ceci fournit un mécanisme de renommage général :

>>> fib
<function fib at 10042ed0>
>>> f = fib
>>> f(100)
0 1 1 2 3 5 8 13 21 34 55 89

Si vous venez d’autres langages, vous pouvez penser que fib n’est pas une fonction mais une procédure, puisqu’elle ne renvoie pas de résultat. En fait, même les fonctions sans instruction return renvoient une valeur, quoique ennuyeuse. Cette valeur est appelée None (c’est le nom d’une primitive). Écrire la valeur None est normalement supprimé par l’interpréteur lorsqu’il s’agit de la seule valeur qui doit être écrite. Vous pouvez le constater, si vous y tenez vraiment, en utilisant print() :

>>> fib(0)
>>> print(fib(0))
None

Il est facile d’écrire une fonction qui renvoie une liste de la série de Fibonacci au lieu de l’afficher :

>>> def fib2(n):  # return Fibonacci series up to n
...     """Return a list containing the Fibonacci series up to n."""
...     result = []
...     a, b = 0, 1
...     while a < n:
...         result.append(a)    # see below
...         a, b = b, a+b
...     return result
...
>>> f100 = fib2(100)    # call it
>>> f100                # write the result
[0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89]

Cet exemple, comme d’habitude, illustre de nouvelles fonctionnalités de Python :

L’instruction return provoque la sortie de la fonction en renvoyant une valeur. return sans expression en paramètre renvoie None. Arriver à la fin d’une fonction renvoie également None.

L’instruction result.append(a) appelle une méthode de l’objet result qui est une liste. Une méthode est une fonction qui « appartient » à un objet et qui est nommée obj.methodname, où obj est un objet (il peut également s’agir d’une expression) et methodname est le nom d’une méthode que le type de l’objet définit. Différents types définissent différentes méthodes. Des méthodes de différents types peuvent porter le même nom sans qu’il n’y ait d’ambigüité (vous pouvez définir vos propres types d’objets et leurs méthodes en utilisant des classes, voir Classes). La méthode append() donnée dans cet exemple est définie pour les listes ; elle ajoute un nouvel élément à la fin de la liste. Dans cet exemple, elle est l’équivalent de result = result + [a], mais elle est plus efficace.

4.7. D’avantage sur la définition des fonctions

Il est également possible de définir des fonctions avec un nombre variable d’arguments. Trois syntaxes peuvent être utilisées, éventuellement combinées.

4.7.1. Valeur par défaut des arguments

La forme la plus utile consiste à indiquer une valeur par défaut pour certains arguments. Ceci crée une fonction qui pourra être appelée avec moins d’arguments que ceux présents dans sa définition. Par exemple :

def ask_ok(prompt, retries=4, reminder='Please try again!'):
    while True:
        ok = input(prompt)
        if ok in ('y', 'ye', 'yes'):
            return True
        if ok in ('n', 'no', 'nop', 'nope'):
            return False
        retries = retries - 1
        if retries < 0:
            raise ValueError('invalid user response')
        print(reminder)

Cette fonction peut être appelée de plusieurs façons :

en ne fournissant que les arguments obligatoires : ask_ok('Do you really want to quit?')

en fournissant une partie des arguments facultatifs : ask_ok('OK to overwrite the file?', 2)

en fournissant tous les arguments : ask_ok('OK to overwrite the file?', 2, 'Come on, only yes or no!')

Cet exemple présente également le mot-clé in. Celui-ci permet de tester si une séquence contient une certaine valeur.

Les valeurs par défaut sont évaluées lors de la définition de la fonction dans la portée de définition, de telle sorte que

i = 5

def f(arg=i):
    print(arg)

i = 6
f()

affiche 5.

Avertissement important : la valeur par défaut n’est évaluée qu’une seule fois. Ceci fait une différence lorsque cette valeur par défaut est un objet muable tel qu’une liste, un dictionnaire ou des instances de la plupart des classes. Par exemple, la fonction suivante accumule les arguments qui lui sont passés au fil des appels successifs :

def f(a, L=[]):
    L.append(a)
    return L

print(f(1))
print(f(2))
print(f(3))

Ceci affiche

[1]
[1, 2]
[1, 2, 3]

Si vous ne voulez pas que cette valeur par défaut soit partagée entre des appels successifs, vous pouvez écrire la fonction de cette façon :

def f(a, L=None):
    if L is None:
        L = []
    L.append(a)
    return L

4.7.2. Les arguments nommés

Les fonctions peuvent également être appelées en utilisant des arguments nommés sous la forme kwarg=value. Par exemple, la fonction suivante :

def parrot(voltage, state='a stiff', action='voom', type='Norwegian Blue'):
    print("-- This parrot wouldn't", action, end=' ')
    print("if you put", voltage, "volts through it.")
    print("-- Lovely plumage, the", type)
    print("-- It's", state, "!")

accepte un argument obligatoire (voltage) et trois arguments facultatifs (state, action et type). Cette fonction peut être appelée de n’importe laquelle des façons suivantes :

parrot(1000)                                          # 1 positional argument
parrot(voltage=1000)                                  # 1 keyword argument
parrot(voltage=1000000, action='VOOOOOM')             # 2 keyword arguments
parrot(action='VOOOOOM', voltage=1000000)             # 2 keyword arguments
parrot('a million', 'bereft of life', 'jump')         # 3 positional arguments
parrot('a thousand', state='pushing up the daisies')  # 1 positional, 1 keyword

mais tous les appels qui suivent sont incorrects :

parrot()                     # required argument missing
parrot(voltage=5.0, 'dead')  # non-keyword argument after a keyword argument
parrot(110, voltage=220)     # duplicate value for the same argument
parrot(actor='John Cleese')  # unknown keyword argument

Dans un appel de fonction, les arguments nommés doivent suivre les arguments positionnés. Tous les arguments nommés doivent correspondre à l’un des arguments acceptés par la fonction (par exemple, actor n’est pas un argument accepté par la fonction parrot), mais leur ordre n’est pas important. Ceci inclut également les arguments obligatoires (parrot(voltage=1000) est également correct). Aucun argument ne peut recevoir une valeur plus d’une fois, comme l’illustre cet exemple incorrect du fait de cette restriction :

>>> def function(a):
...     pass
...
>>> function(0, a=0)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: function() got multiple values for keyword argument 'a'

Quand un dernier paramètre formel est présent sous la forme **name, il reçoit un dictionnaire (voir Les types de correspondances — dict) contenant tous les arguments nommés à l’exception de ceux correspondant à un paramètre formel. Ceci peut être combiné à un paramètre formel sous la forme *name (décrit dans la section suivante) qui lui reçoit un tuple contenant les arguments positionnés au-delà de la liste des paramètres formels (*name doit être présent avant **name). Par exemple, si vous définissez une fonction comme ceci :

def cheeseshop(kind, *arguments, **keywords):
    print("-- Do you have any", kind, "?")
    print("-- I'm sorry, we're all out of", kind)
    for arg in arguments:
        print(arg)
    print("-" * 40)
    for kw in keywords:
        print(kw, ":", keywords[kw])

Elle pourrait être appelée comme ceci :

cheeseshop("Limburger", "It's very runny, sir.",
           "It's really very, VERY runny, sir.",
           shopkeeper="Michael Palin",
           client="John Cleese",
           sketch="Cheese Shop Sketch")

et, bien sûr, elle affiche :

-- Do you have any Limburger ?
-- I'm sorry, we're all out of Limburger
It's very runny, sir.
It's really very, VERY runny, sir.
----------------------------------------
shopkeeper : Michael Palin
client : John Cleese
sketch : Cheese Shop Sketch

Notez que Python garantit que l’ordre d’affichage des arguments est le même que l’ordre dans lesquels ils sont fournis lors de l’appel à la fonction.

4.7.3. Listes d’arguments arbitraires

Pour terminer, l’option la moins fréquente consiste à indiquer qu’une fonction peut être appelée avec un nombre arbitraire d’arguments. Ces arguments sont intégrés dans un tuple (voir Tuples et séquences). Avant le nombre variable d’arguments, zéro arguments normaux ou plus peuvent apparaître

def write_multiple_items(file, separator, *args):
    file.write(separator.join(args))

Normalement, ces arguments variadiques sont les derniers paramètres, parce qu’ils agrègent toutes les valeurs suivantes. Tout paramètre placé après le paramètre *arg ne pourra être utilisé que par son nom.

>>> def concat(*args, sep="/"):
...     return sep.join(args)
...
>>> concat("earth", "mars", "venus")
'earth/mars/venus'
>>> concat("earth", "mars", "venus", sep=".")
'earth.mars.venus'

4.7.4. Séparation des listes d’arguments

La situation inverse intervient lorsque les arguments sont déjà dans une liste ou un tuple mais doivent être séparés pour un appel de fonction nécessitant des arguments positionnés séparés. Par exemple, la primitive range() attend des arguments start et stop distincts. S’ils ne sont pas disponibles séparément, écrivez l’appel de fonction en utilisant l’opérateur * pour séparer les arguments présents dans une liste ou un tuple :

>>> list(range(3, 6))            # normal call with separate arguments
[3, 4, 5]
>>> args = [3, 6]
>>> list(range(*args))            # call with arguments unpacked from a list
[3, 4, 5]

De la même façon, les dictionnaires peuvent fournir des arguments nommés en utilisant l’opérateur ** :

>>> def parrot(voltage, state='a stiff', action='voom'):
...     print("-- This parrot wouldn't", action, end=' ')
...     print("if you put", voltage, "volts through it.", end=' ')
...     print("E's", state, "!")
...
>>> d = {"voltage": "four million", "state": "bleedin' demised", "action": "VOOM"}
>>> parrot(**d)
-- This parrot wouldn't VOOM if you put four million volts through it. E's bleedin' demised !

4.7.5. Fonctions anonymes

Avec le mot-clé lambda, vous pouvez créer de petites fonctions anonymes. En voici une qui renvoie la somme de ses deux arguments : lambda a, b: a+b. Les fonctions lambda peuvent être utilisées partout où un objet fonction est attendu. Elles sont syntaxiquement restreintes à une seule expression. Sémantiquement, elles ne sont que du sucre syntaxique pour une définition de fonction normale. Comme les fonctions imbriquées, les fonctions lambda peuvent référencer des variables de la portée englobante :

>>> def make_incrementor(n):
...     return lambda x: x + n
...
>>> f = make_incrementor(42)
>>> f(0)
42
>>> f(1)
43

L’exemple précédent utilise une fonction anonyme pour renvoyer une fonction. Une autre utilisation classique est de donner une fonction minimaliste directement en tant que paramètre :

>>> pairs = [(1, 'one'), (2, 'two'), (3, 'three'), (4, 'four')]
>>> pairs.sort(key=lambda pair: pair[1])
>>> pairs
[(4, 'four'), (1, 'one'), (3, 'three'), (2, 'two')]

4.7.6. Chaînes de documentation

Voici quelques conventions concernant le contenu et le format des chaînes de documentation.

La première ligne devrait toujours être courte et résumer de manière concise l’utilité de l’objet. Afin d’être bref, nul besoin de rappeler le nom de l’objet ou son type, qui sont accessibles par d’autres moyens (sauf si le nom est un verbe qui décrit une opération). Cette ligne devrait commencer avec une majuscule et se terminer par un point.

S’il y a d’autres lignes dans la chaîne de documentation, la deuxième ligne devrait être vide, pour la séparer visuellement du reste de la description. Les autres lignes peuvent alors constituer un ou plusieurs paragraphes décrivant le mode d’utilisation de l’objet, ses effets de bord, etc.

L’analyseur de code Python ne supprime pas l’indentation des chaînes de caractères littérales multi-lignes, donc les outils qui utilisent la documentation doivent si besoin faire cette opération eux-mêmes. La convention suivante s’applique : la première ligne non vide après la première détermine la profondeur d’indentation de l’ensemble de la chaîne de documentation (on ne peut pas utiliser la première ligne qui est généralement accolée aux guillemets d’ouverture de la chaîne de caractères et dont l’indentation n’est donc pas visible). Les espaces « correspondant » à cette profondeur d’indentation sont alors supprimés du début de chacune des lignes de la chaîne. Aucune ligne ne devrait présenter un niveau d’indentation inférieur mais si cela arrive, toutes les espaces situés en début de ligne doivent être supprimées. L’équivalent des espaces doit être testé après expansion des tabulations (normalement remplacés par 4 espaces).

Voici un exemple de chaîne de documentation multi-lignes :

>>> def my_function():
...     """Do nothing, but document it.
...
...     No, really, it doesn't do anything.
...     """
...     pass
...
>>> print(my_function.__doc__)
Do nothing, but document it.

    No, really, it doesn't do anything.

4.7.7. Annotations de fonctions

Les annotations de fonction sont des métadonnées optionnelles décrivant les types utilisés par une fonction définie par l’utilisateur (voir les PEP 3107 [https://www.python.org/dev/peps/pep-3107] et PEP 484 [https://www.python.org/dev/peps/pep-0484] pour plus d’informations).

Les annotations sont stockées dans l’attribut __annotations__ de la fonction, sous forme d’un dictionnaire, et n’ont aucun autre effet. Les annotations sur les paramètres sont définis par deux points (:) après le nom du paramètre suivi d’une expression donnant la valeur de l’annotation. Les annotations de retour sont définies par -> suivi d’une expression, entre la liste des paramètres et les deux points de fin de l’instruction def. L’exemple suivant a un paramètre positionnel, un paramètre nommé et une valeur de retour annotée :

>>> def f(ham: str, eggs: str = 'eggs') -> str:
...     print("Annotations:", f.__annotations__)
...     print("Arguments:", ham, eggs)
...     return ham + ' and ' + eggs
...
>>> f('spam')
Annotations: {'ham': <class 'str'>, 'return': <class 'str'>, 'eggs': <class 'str'>}
Arguments: spam eggs
'spam and eggs'

4.8. Aparté : le style de codage

Maintenant que vous êtes prêt à écrire des programmes plus longs et plus complexes, il est temps de parler du style de codage. La plupart des langages peuvent être écrits (ou plutôt formatés) selon différents styles ; certains sont plus lisibles que d’autres. Rendre la lecture de votre code plus facile aux autres est toujours une bonne idée et adopter un bon style de codage peut énormément vous y aider.

En Python, la plupart des projets adhèrent au style défini dans la PEP 8 [https://www.python.org/dev/peps/pep-0008] ; elle met en avant un style de codage très lisible et agréable à l’œil. Chaque développeur Python se doit donc de la lire et de s’en inspirer autant que possible ; voici ses principaux points notables :

Utilisez des indentations de 4 espaces et pas de tabulation.

4 espaces constituent un bon compromis entre une indentation courte (qui permet une profondeur d’imbrication plus importante) et une longue (qui rend le code plus facile à lire). Les tabulations introduisent de la confusion et doivent être proscrites autant que possible.

Faites en sorte que les lignes ne dépassent pas 79 caractères, au besoin en insérant des retours à la ligne.

Vous facilitez ainsi la lecture pour les utilisateurs qui n’ont qu’un petit écran et, pour les autres, cela leur permet de visualiser plusieurs fichiers côte à côte.

Utilisez des lignes vides pour séparer les fonctions et les classes, ou pour scinder de gros blocs de code à l’intérieur de fonctions.

Lorsque c’est possible, placez les commentaires sur leurs propres lignes.

Utilisez les chaînes de documentation.

Utilisez des espaces autour des opérateurs et après les virgules, mais pas juste à l’intérieur des parenthèses : a = f(1, 2) + g(3, 4).

Nommez toujours vos classes et fonctions de la même manière ; la convention est d’utiliser une notation CamelCase pour les classes, et minuscules_avec_trait_bas pour les fonctions et méthodes. Utilisez toujours self comme nom du premier argument des méthodes (voyez Une première approche des classes pour en savoir plus sur les classes et les méthodes).

N’utilisez pas d’encodage exotique dès lors que votre code est censé être utilisé dans des environnements internationaux. Par défaut, Python travaille en UTF-8. Pour couvrir tous les cas, préférez le simple ASCII.

De la même manière, n’utilisez que des caractères ASCII pour vos noms de variables s’il est envisageable qu’une personne parlant une autre langue lise ou doive modifier votre code.

Notes

1

En fait, appels par référence d’objets serait sans doute une description plus juste dans la mesure où, si un objet muable est passé en argument, l’appelant verra toutes les modifications qui lui auront été apportées par l’appelé (insertion d’éléments dans une liste…).

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5. Structures de données

Ce chapitre reprend plus en détail quelques points déjà décrits précédemment et introduit également de nouvelles notions.

5.1. Compléments sur les listes

Le type liste dispose de méthodes supplémentaires. Voici toutes les méthodes des objets de type liste :

list.append(x)

Ajoute un élément à la fin de la liste. Équivalent à a[len(a):] = [x].

list.extend(iterable)

Étend la liste en y ajoutant tous les éléments de l’itérable. Équivalent à a[len(a):] = iterable.

list.insert(i, x)

Insère un élément à la position indiquée. Le premier argument est la position de l’élément courant avant lequel l’insertion doit s’effectuer, donc a.insert(0, x) insère l’élément en tête de la liste et a.insert(len(a), x) est équivalent à a.append(x).

list.remove(x)

Supprime de la liste le premier élément dont la valeur est égale à x. Une exception est levée s’il n’existe aucun élément avec cette valeur.

list.pop([i])

Enlève de la liste l’élément situé à la position indiquée et le renvoie en valeur de retour. Si aucune position n’est spécifiée, a.pop() enlève et renvoie le dernier élément de la liste (les crochets autour du i dans la signature de la méthode indiquent que ce paramètre est facultatif et non que vous devez placer des crochets dans votre code ! Vous retrouverez cette notation fréquemment dans le Guide de Référence de la Bibliothèque Python).

list.clear()

Supprime tous les éléments de la liste. Équivalent à del a[:].

list.index(x[, start[, end]])

Renvoie la position du premier élément de la liste dont la valeur égale x (en commençant par zéro). Une exception ValueError est levée si aucun élément n’est trouvé.

Les arguments optionnels start et end sont interprétés de la même manière que dans la notation des tranches et sont utilisés pour limiter la recherche à une sous-séquence particulière. L’indice renvoyé est calculé relativement au début de la séquence complète et non relativement à start.

list.count(x)

Renvoie le nombre d’éléments ayant la valeur x dans la liste.

list.sort(key=None, reverse=False)

Ordonne les éléments dans la liste (les arguments peuvent personnaliser l’ordonnancement, voir sorted() pour leur explication).

list.reverse()

Inverse l’ordre des éléments dans la liste.

list.copy()

Renvoie une copie superficielle de la liste. Équivalent à a[:].

L’exemple suivant utilise la plupart des méthodes des listes :

>>> fruits = ['orange', 'apple', 'pear', 'banana', 'kiwi', 'apple', 'banana']
>>> fruits.count('apple')
2
>>> fruits.count('tangerine')
0
>>> fruits.index('banana')
3
>>> fruits.index('banana', 4)  # Find next banana starting a position 4
6
>>> fruits.reverse()
>>> fruits
['banana', 'apple', 'kiwi', 'banana', 'pear', 'apple', 'orange']
>>> fruits.append('grape')
>>> fruits
['banana', 'apple', 'kiwi', 'banana', 'pear', 'apple', 'orange', 'grape']
>>> fruits.sort()
>>> fruits
['apple', 'apple', 'banana', 'banana', 'grape', 'kiwi', 'orange', 'pear']
>>> fruits.pop()
'pear'

Vous avez probablement remarqué que les méthodes telles que insert, remove ou sort, qui ne font que modifier la liste, n’affichent pas de valeur de retour (elles renvoient None) 1. C’est un principe respecté par toutes les structures de données variables en Python.

5.1.1. Utilisation des listes comme des piles

Les méthodes des listes rendent très facile leur utilisation comme des piles, où le dernier élément ajouté est le premier récupéré (« dernier entré, premier sorti » ou LIFO pour last-in, first-out en anglais). Pour ajouter un élément sur la pile, utilisez la méthode append(). Pour récupérer l’objet au sommet de la pile, utilisez la méthode pop() sans indicateur de position. Par exemple :

>>> stack = [3, 4, 5]
>>> stack.append(6)
>>> stack.append(7)
>>> stack
[3, 4, 5, 6, 7]
>>> stack.pop()
7
>>> stack
[3, 4, 5, 6]
>>> stack.pop()
6
>>> stack.pop()
5
>>> stack
[3, 4]

5.1.2. Utilisation des listes comme des files

Il est également possible d’utiliser une liste comme une file, où le premier élément ajouté est le premier récupéré (« premier entré, premier sorti » ou FIFO pour first-in, first-out) ; toutefois, les listes ne sont pas très efficaces pour réaliser ce type de traitement. Alors que les ajouts et suppressions en fin de liste sont rapides, les opérations d’insertions ou de retraits en début de liste sont lentes (car tous les autres éléments doivent être décalés d’une position).

Pour implémenter une file, utilisez la classe collections.deque qui a été conçue pour réaliser rapidement les opérations d’ajouts et de retraits aux deux extrémités. Par exemple :

>>> from collections import deque
>>> queue = deque(["Eric", "John", "Michael"])
>>> queue.append("Terry")           # Terry arrives
>>> queue.append("Graham")          # Graham arrives
>>> queue.popleft()                 # The first to arrive now leaves
'Eric'
>>> queue.popleft()                 # The second to arrive now leaves
'John'
>>> queue                           # Remaining queue in order of arrival
deque(['Michael', 'Terry', 'Graham'])

5.1.3. Compréhensions de listes

Les compréhensions de listes fournissent un moyen de construire des listes de manière très concise. Une application classique est la construction de nouvelles listes où chaque élément est le résultat d’une opération appliquée à chaque élément d’une autre séquence ; ou de créer une sous-séquence des éléments satisfaisant une condition spécifique.

Par exemple, supposons que l’on veuille créer une liste de carrés, comme :

>>> squares = []
>>> for x in range(10):
...     squares.append(x**2)
...
>>> squares
[0, 1, 4, 9, 16, 25, 36, 49, 64, 81]

Notez que cela crée (ou remplace) une variable nommée x qui existe toujours après l’exécution de la boucle. On peut calculer une liste de carrés sans effet de bord avec :

squares = list(map(lambda x: x**2, range(10)))

ou, de manière équivalente :

squares = [x**2 for x in range(10)]

qui est plus court et lisible.

Une compréhension de liste consiste à placer entre crochets une expression suivie par une clause for puis par zéro ou plus clauses for ou if. Le résultat est une nouvelle liste résultat de l’évaluation de l’expression dans le contexte des clauses for et if qui la suivent. Par exemple, cette compréhension de liste combine les éléments de deux listes s’ils ne sont pas égaux :

>>> [(x, y) for x in [1,2,3] for y in [3,1,4] if x != y]
[(1, 3), (1, 4), (2, 3), (2, 1), (2, 4), (3, 1), (3, 4)]

et c’est équivalent à :

>>> combs = []
>>> for x in [1,2,3]:
...     for y in [3,1,4]:
...         if x != y:
...             combs.append((x, y))
...
>>> combs
[(1, 3), (1, 4), (2, 3), (2, 1), (2, 4), (3, 1), (3, 4)]

Notez que l’ordre des instructions for et if est le même dans ces différents extraits de code.

Si l’expression est un n-uplet (c’est-à-dire (x, y) dans cet exemple), elle doit être entourée par des parenthèses :

>>> vec = [-4, -2, 0, 2, 4]
>>> # create a new list with the values doubled
>>> [x*2 for x in vec]
[-8, -4, 0, 4, 8]
>>> # filter the list to exclude negative numbers
>>> [x for x in vec if x >= 0]
[0, 2, 4]
>>> # apply a function to all the elements
>>> [abs(x) for x in vec]
[4, 2, 0, 2, 4]
>>> # call a method on each element
>>> freshfruit = ['  banana', '  loganberry ', 'passion fruit  ']
>>> [weapon.strip() for weapon in freshfruit]
['banana', 'loganberry', 'passion fruit']
>>> # create a list of 2-tuples like (number, square)
>>> [(x, x**2) for x in range(6)]
[(0, 0), (1, 1), (2, 4), (3, 9), (4, 16), (5, 25)]
>>> # the tuple must be parenthesized, otherwise an error is raised
>>> [x, x**2 for x in range(6)]
  File "<stdin>", line 1, in <module>
    [x, x**2 for x in range(6)]
               ^
SyntaxError: invalid syntax
>>> # flatten a list using a listcomp with two 'for'
>>> vec = [[1,2,3], [4,5,6], [7,8,9]]
>>> [num for elem in vec for num in elem]
[1, 2, 3, 4, 5, 6, 7, 8, 9]

Les compréhensions de listes peuvent contenir des expressions complexes et des fonctions imbriquées :

>>> from math import pi
>>> [str(round(pi, i)) for i in range(1, 6)]
['3.1', '3.14', '3.142', '3.1416', '3.14159']

5.1.4. Compréhensions de listes imbriquées

La première expression dans une compréhension de liste peut être n’importe quelle expression, y compris une autre compréhension de liste.

Voyez l’exemple suivant d’une matrice de 3 par 4, implémentée sous la forme de 3 listes de 4 éléments :

>>> matrix = [
...     [1, 2, 3, 4],
...     [5, 6, 7, 8],
...     [9, 10, 11, 12],
... ]

Cette compréhension de liste transpose les lignes et les colonnes :

>>> [[row[i] for row in matrix] for i in range(4)]
[[1, 5, 9], [2, 6, 10], [3, 7, 11], [4, 8, 12]]

Comme nous l’avons vu dans la section précédente, la compréhension de liste imbriquée est évaluée dans le contexte de l’instruction for qui la suit, donc cet exemple est équivalent à :

>>> transposed = []
>>> for i in range(4):
...     transposed.append([row[i] for row in matrix])
...
>>> transposed
[[1, 5, 9], [2, 6, 10], [3, 7, 11], [4, 8, 12]]

lequel à son tour est équivalent à :

>>> transposed = []
>>> for i in range(4):
...     # the following 3 lines implement the nested listcomp
...     transposed_row = []
...     for row in matrix:
...         transposed_row.append(row[i])
...     transposed.append(transposed_row)
...
>>> transposed
[[1, 5, 9], [2, 6, 10], [3, 7, 11], [4, 8, 12]]

Dans des cas concrets, il est toujours préférable d’utiliser des fonctions natives plutôt que des instructions de contrôle de flux complexes. La fonction zip() ferait dans ce cas un excellent travail :

>>> list(zip(*matrix))
[(1, 5, 9), (2, 6, 10), (3, 7, 11), (4, 8, 12)]

Voyez Séparation des listes d’arguments pour plus de détails sur l’astérisque de cette ligne.

5.2. L’instruction del

Il existe un moyen de retirer un élément d’une liste à partir de sa position au lieu de sa valeur : l’instruction del. Elle diffère de la méthode pop() qui, elle, renvoie une valeur. L’instruction del peut également être utilisée pour supprimer des tranches d’une liste ou la vider complètement (ce que nous avions fait auparavant en affectant une liste vide à la tranche). Par exemple :

>>> a = [-1, 1, 66.25, 333, 333, 1234.5]
>>> del a[0]
>>> a
[1, 66.25, 333, 333, 1234.5]
>>> del a[2:4]
>>> a
[1, 66.25, 1234.5]
>>> del a[:]
>>> a
[]

del peut aussi être utilisée pour supprimer des variables :

>>> del a

À partir de là, référencer le nom a est une erreur (au moins jusqu’à ce qu’une autre valeur lui soit affectée). Vous trouverez d’autres utilisations de la fonction del plus tard.

5.3. Tuples et séquences

Nous avons vu que les listes et les chaînes de caractères ont beaucoup de propriétés en commun, comme l’indiçage et les opérations sur des tranches. Ce sont deux exemples de séquences (voir Types séquentiels — list, tuple, range). Comme Python est un langage en constante évolution, d’autres types de séquences y seront peut-être ajoutés. Il existe également un autre type standard de séquence : le tuple (ou n-uplet, dénomination que nous utiliserons dans la suite de cette documentation).

Un n-uplet consiste en différentes valeurs séparées par des virgules, par exemple :

>>> t = 12345, 54321, 'hello!'
>>> t[0]
12345
>>> t
(12345, 54321, 'hello!')
>>> # Tuples may be nested:
... u = t, (1, 2, 3, 4, 5)
>>> u
((12345, 54321, 'hello!'), (1, 2, 3, 4, 5))
>>> # Tuples are immutable:
... t[0] = 88888
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: 'tuple' object does not support item assignment
>>> # but they can contain mutable objects:
... v = ([1, 2, 3], [3, 2, 1])
>>> v
([1, 2, 3], [3, 2, 1])

Comme vous pouvez le voir, les n-uplets sont toujours affichés entre parenthèses, de façon à ce que des n-uplets imbriqués soient interprétés correctement ; ils peuvent être saisis avec ou sans parenthèses, même si celles-ci sont souvent nécessaires (notamment lorsqu’un n-uplet fait partie d’une expression plus longue). Il n’est pas possible d’affecter de valeur à un élément d’un n-uplet ; par contre, il est possible de créer des n-uplets contenant des objets muables, comme des listes.

Si les n-uplets peuvent sembler similaires aux listes, ils sont souvent utilisés dans des cas différents et pour des raisons différentes. Les n-uplets sont immuables et contiennent souvent des séquences hétérogènes d’éléments qui sont accédés par « dissociation » (unpacking en anglais, voir plus loin) ou par indice (ou même par attributs dans le cas des namedtuples). Les listes sont souvent muables et contiennent des éléments généralement homogènes qui sont accédés par itération sur la liste.

Un problème spécifique est la construction de n-uplets ne contenant aucun ou un seul élément : la syntaxe a quelques tournures spécifiques pour s’en accommoder. Les n-uplets vides sont construits par une paire de parenthèses vides ; un n-uplet avec un seul élément est construit en faisant suivre la valeur par une virgule (il n’est pas suffisant de placer cette valeur entre parenthèses). Pas très joli, mais efficace. Par exemple :

>>> empty = ()
>>> singleton = 'hello',    # <-- note trailing comma
>>> len(empty)
0
>>> len(singleton)
1
>>> singleton
('hello',)

L’instruction t = 12345, 54321, 'hello !' est un exemple d’un d’agrégation de n-uplet (tuple packing en anglais) : les valeurs 12345, 54321 et hello ! sont agrégées ensemble dans un n-uplet. L’opération inverse est aussi possible :

>>> x, y, z = t

Ceci est appelé, de façon plus ou moins appropriée, un dissociation de séquence (sequence unpacking en anglais) et fonctionne pour toute séquence placée à droite de l’expression. Cette dissociation requiert autant de variables dans la partie gauche qu’il y a d’éléments dans la séquence. Notez également que cette affectation multiple est juste une combinaison entre une agrégation de n-uplet et une dissociation de séquence.

5.4. Ensembles

Python fournit également un type de donnée pour les ensembles. Un ensemble est une collection non ordonnée sans élément dupliqué. Des utilisations basiques concernent par exemple des tests d’appartenance ou des suppressions de doublons. Les ensembles savent également effectuer les opérations mathématiques telles que les unions, intersections, différences et différences symétriques.

Des accolades ou la fonction set() peuvent être utilisés pour créer des ensembles. Notez que pour créer un ensemble vide, {} ne fonctionne pas, cela crée un dictionnaire vide. Utilisez plutôt set().

Voici une brève démonstration :

>>> basket = {'apple', 'orange', 'apple', 'pear', 'orange', 'banana'}
>>> print(basket)                      # show that duplicates have been removed
{'orange', 'banana', 'pear', 'apple'}
>>> 'orange' in basket                 # fast membership testing
True
>>> 'crabgrass' in basket
False

>>> # Demonstrate set operations on unique letters from two words
...
>>> a = set('abracadabra')
>>> b = set('alacazam')
>>> a                                  # unique letters in a
{'a', 'r', 'b', 'c', 'd'}
>>> a - b                              # letters in a but not in b
{'r', 'd', 'b'}
>>> a | b                              # letters in a or b or both
{'a', 'c', 'r', 'd', 'b', 'm', 'z', 'l'}
>>> a & b                              # letters in both a and b
{'a', 'c'}
>>> a ^ b                              # letters in a or b but not both
{'r', 'd', 'b', 'm', 'z', 'l'}

Tout comme pour les compréhensions de listes, il est possible d’écrire des compréhensions d’ensembles :

>>> a = {x for x in 'abracadabra' if x not in 'abc'}
>>> a
{'r', 'd'}

5.5. Dictionnaires

Un autre type de donnée très utile, natif dans Python, est le dictionnaire (voir Les types de correspondances — dict). Ces dictionnaires sont parfois présents dans d’autres langages sous le nom de « mémoires associatives » ou de « tableaux associatifs ». À la différence des séquences, qui sont indexées par des nombres, les dictionnaires sont indexés par des clés, qui peuvent être de n’importe quel type immuable ; les chaînes de caractères et les nombres peuvent toujours être des clés. Des n-uplets peuvent être utilisés comme clés s’ils ne contiennent que des chaînes, des nombres ou des n-uplets ; si un n-uplet contient un objet muable, de façon directe ou indirecte, il ne peut pas être utilisé comme une clé. Vous ne pouvez pas utiliser des listes comme clés, car les listes peuvent être modifiées en place en utilisant des affectations par position, par tranches ou via des méthodes comme append() ou extend().

Le plus simple est de considérer les dictionnaires comme des ensembles non ordonnés de paires clé: valeur, les clés devant être uniques (au sein d’un dictionnaire). Une paire d’accolades crée un dictionnaire vide : {}. Placer une liste de paires clé:valeur séparées par des virgules à l’intérieur des accolades ajoute les valeurs correspondantes au dictionnaire ; c’est également de cette façon que les dictionnaires sont affichés.

Les opérations classiques sur un dictionnaire consistent à stocker une valeur pour une clé et à extraire la valeur correspondant à une clé. Il est également possible de supprimer une paire clé:valeur avec del. Si vous stockez une valeur pour une clé qui est déjà utilisée, l’ancienne valeur associée à cette clé est perdue. Si vous tentez d’extraire une valeur associée à une clé qui n’existe pas, une exception est levée.

Exécuter list(d.keys()) sur un dictionnaire d renvoie une liste de toutes les clés utilisées dans le dictionnaire, dans un ordre arbitraire (si vous voulez qu’elles soient classées, utilisez sorted(d.keys())) 2. Pour tester si une clé est dans le dictionnaire, utilisez le mot-clé in.

Voici un petit exemple utilisant un dictionnaire :

>>> tel = {'jack': 4098, 'sape': 4139}
>>> tel['guido'] = 4127
>>> tel
{'sape': 4139, 'guido': 4127, 'jack': 4098}
>>> tel['jack']
4098
>>> del tel['sape']
>>> tel['irv'] = 4127
>>> tel
{'guido': 4127, 'irv': 4127, 'jack': 4098}
>>> list(tel.keys())
['irv', 'guido', 'jack']
>>> sorted(tel.keys())
['guido', 'irv', 'jack']
>>> 'guido' in tel
True
>>> 'jack' not in tel
False

Le constructeur dict() fabrique un dictionnaire directement à partir d’une liste de paires clé-valeur stockées sous la forme de n-uplets :

>>> dict([('sape', 4139), ('guido', 4127), ('jack', 4098)])
{'sape': 4139, 'jack': 4098, 'guido': 4127}

De plus, il est possible de créer des dictionnaires par compréhension depuis un jeu de clef et valeurs :

>>> {x: x**2 for x in (2, 4, 6)}
{2: 4, 4: 16, 6: 36}

Lorsque les clés sont de simples chaînes de caractères, il est parfois plus facile de spécifier les paires en utilisant des paramètres nommés :

>>> dict(sape=4139, guido=4127, jack=4098)
{'sape': 4139, 'jack': 4098, 'guido': 4127}

5.6. Techniques de boucles

Lorsque vous faites une boucle sur un dictionnaire, les clés et leurs valeurs peuvent être récupérées en même temps en utilisant la méthode items() :

>>> knights = {'gallahad': 'the pure', 'robin': 'the brave'}
>>> for k, v in knights.items():
...     print(k, v)
...
gallahad the pure
robin the brave

Lorsque vous itérez sur une séquence, la position et la valeur correspondante peuvent être récupérées en même temps en utilisant la fonction enumerate().

>>> for i, v in enumerate(['tic', 'tac', 'toe']):
...     print(i, v)
...
0 tic
1 tac
2 toe

Pour faire des boucles sur deux séquences ou plus en même temps, les éléments peuvent être associés par la fonction zip() :

>>> questions = ['name', 'quest', 'favorite color']
>>> answers = ['lancelot', 'the holy grail', 'blue']
>>> for q, a in zip(questions, answers):
...     print('What is your {0}?  It is {1}.'.format(q, a))
...
What is your name?  It is lancelot.
What is your quest?  It is the holy grail.
What is your favorite color?  It is blue.

Pour faire une boucle en sens inverse sur une séquence, commencez par spécifier la séquence dans son ordre normal, puis appliquez la fonction reversed() :

>>> for i in reversed(range(1, 10, 2)):
...     print(i)
...
9
7
5
3
1

Pour parcourir les éléments d’une séquence de manière ordonnée, utilisez la fonction sorted(), elle renvoie une nouvelle liste ordonnée sans altérer la source :

>>> basket = ['apple', 'orange', 'apple', 'pear', 'orange', 'banana']
>>> for f in sorted(set(basket)):
...     print(f)
...
apple
banana
orange
pear

Il est parfois tentant de modifier une liste pendant son itération. Cependant, c’est souvent plus simple et plus sûr de créer une nouvelle liste à la place.

>>> import math
>>> raw_data = [56.2, float('NaN'), 51.7, 55.3, 52.5, float('NaN'), 47.8]
>>> filtered_data = []
>>> for value in raw_data:
...     if not math.isnan(value):
...         filtered_data.append(value)
...
>>> filtered_data
[56.2, 51.7, 55.3, 52.5, 47.8]

5.7. Plus d’informations sur les conditions

Les conditions utilisées dans une instruction while ou if peuvent contenir n’importe quel opérateur, pas seulement des comparaisons.

Les opérateurs de comparaison in et not in testent si une valeur est présente ou non dans une séquence. Les opérateurs is et is not testent si deux objets sont vraiment le même objet ; ceci n’est important que pour des objets muables comme des listes. Tous les opérateurs de comparaison ont la même priorité, qui est plus faible que celle des opérateurs numériques.

Les comparaisons peuvent être enchaînées. Par exemple, a < b == c teste si a est inférieur à b et si, de plus, b égale c.

Les comparaisons peuvent être combinées en utilisant les opérateurs booléens and et or, le résultat d’une comparaison (ou de toute expression booléenne) pouvant être inversé avec not. Ces opérateurs ont une priorité inférieure à celle des opérateurs de comparaison ; entre eux, not a la priorité la plus élevée et or la plus faible, de telle sorte que A and not B or C est équivalent à (A and (not B)) or C. Comme toujours, des parenthèses peuvent être utilisées pour exprimer l’instruction désirée.

Les opérateurs booléens and et or sont appelés opérateurs en circuit court : leurs arguments sont évalués de la gauche vers la droite et l’évaluation s’arrête dès que le résultat est déterminé. Par exemple, si A et C sont vrais et B est faux, A and B and C n’évalue pas l’expression C. Lorsqu’elle est utilisée en tant que valeur et non en tant que booléen, la valeur de retour d’un opérateur en circuit court est celle du dernier argument évalué.

Il est possible d’affecter le résultat d’une comparaison ou d’une autre expression booléenne à une variable. Par exemple :

>>> string1, string2, string3 = '', 'Trondheim', 'Hammer Dance'
>>> non_null = string1 or string2 or string3
>>> non_null
'Trondheim'

Notez qu’en Python, à la différence du C, des affectations ne peuvent pas intervenir à l’intérieur d’expressions. Les programmeurs C râleront peut-être après cela, mais cela évite des erreurs fréquentes que l’on rencontre en C, lorsque l’on tape = alors que l’on voulait faire un test avec ==.

5.8. Comparer des séquences avec d’autres types

Des séquences peuvent être comparées avec d’autres séquences du même type. La comparaison utilise un ordre lexicographique : les deux premiers éléments de chaque séquence sont comparés et, s’ils diffèrent, cela détermine le résultat de la comparaison ; s’ils sont égaux, les deux éléments suivants sont comparés à leur tour et ainsi de suite jusqu’à ce que l’une des séquences soit épuisée. Si deux éléments à comparer sont eux-mêmes des séquences du même type, alors la comparaison lexicographique est effectuée récursivement. Si tous les éléments des deux séquences sont égaux, les deux séquences sont alors considérées comme égales. Si une séquence est une sous-séquence de l’autre, la séquence la plus courte est celle dont la valeur est inférieure. La comparaison lexicographique des chaînes de caractères utilise le code Unicode des caractères. Voici quelques exemples de comparaisons entre séquences de même type :

(1, 2, 3)              < (1, 2, 4)
[1, 2, 3]              < [1, 2, 4]
'ABC' < 'C' < 'Pascal' < 'Python'
(1, 2, 3, 4)           < (1, 2, 4)
(1, 2)                 < (1, 2, -1)
(1, 2, 3)             == (1.0, 2.0, 3.0)
(1, 2, ('aa', 'ab'))   < (1, 2, ('abc', 'a'), 4)

Comparer des objets de type différents avec < ou > est autorisé si les objets ont des méthodes de comparaison appropriées. Par exemple, les types numériques sont comparés via leur valeur numérique, donc 0 égale 0,0, etc. Dans les autres cas, au lieu de donner un ordre imprévisible, l’interpréteur lève une exception TypeError.

Notes

1

D’autres langages renvoient l’objet modifié, ce qui permet de chaîner les méthodes comme ceci : d->insert("a")->remove("b")->sort();.

2

Appeler d.keys() renvoie un objet dictionary view qui gère les opérations du type test d’appartenance (in) et l’itération. Mais son contenu n’est pas indépendant du dictionnaire d’origine, c’est une simple vue.

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6. Modules

Lorsque vous quittez et entrez à nouveau dans l’interpréteur Python, tout ce que vous avez déclaré dans la session précédente est perdu. Afin de rédiger des programmes plus longs, vous devez utiliser un éditeur de texte, préparer votre code dans un fichier et exécuter Python avec ce fichier en paramètre. Cela s’appelle créer un script. Lorsque votre programme grandit, vous pouvez séparer votre code dans plusieurs fichiers. Ainsi, il vous est facile de réutiliser des fonctions écrites pour un programme dans un autre sans avoir à les copier.

Pour gérer cela, Python vous permet de placer des définitions dans un fichier et de les utiliser dans un script ou une session interactive. Un tel fichier est appelé un module et les définitions d’un module peuvent être importées dans un autre module ou dans le module main (qui est le module qui contient vos variables et définitions lors de l’exécution d’un script au niveau le plus haut ou en mode interactif).

Un module est un fichier contenant des définitions et des instructions. Son nom de fichier est le nom du module suffixé de .py. À l’intérieur d’un module, son propre nom est accessible par la variable __name__. Par exemple, prenez votre éditeur favori et créez un fichier fibo.py dans le répertoire courant qui contient :

# Fibonacci numbers module

def fib(n):    # write Fibonacci series up to n
    a, b = 0, 1
    while b < n:
        print(b, end=' ')
        a, b = b, a+b
    print()

def fib2(n):   # return Fibonacci series up to n
    result = []
    a, b = 0, 1
    while b < n:
        result.append(b)
        a, b = b, a+b
    return result

Maintenant, ouvrez un interpréteur et importez le module en tapant :

>>> import fibo

Cela n’importe pas les noms des fonctions définies dans fibo directement dans la table des symboles courants mais y ajoute simplement fibo. Vous pouvez donc appeler les fonctions via le nom du module :

>>> fibo.fib(1000)
1 1 2 3 5 8 13 21 34 55 89 144 233 377 610 987
>>> fibo.fib2(100)
[1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89]
>>> fibo.__name__
'fibo'

Si vous avez l’intention d’utiliser souvent une fonction, il est possible de lui assigner un nom local :

>>> fib = fibo.fib
>>> fib(500)
1 1 2 3 5 8 13 21 34 55 89 144 233 377

6.1. Les modules en détail

Un module peut contenir aussi bien des instructions que des déclarations de fonctions. Ces instructions permettent d’initialiser le module. Elles ne sont exécutées que la première fois que le nom d’un module est trouvé dans un import 1 (elles sont aussi exécutées lorsque le fichier est exécuté en tant que script).

Chaque module possède sa propre table de symboles, utilisée comme table de symboles globaux par toutes les fonctions définies par le module. Ainsi l’auteur d’un module peut utiliser des variables globales dans un module sans se soucier de collisions de noms avec des variables globales définies par l’utilisateur du module. Cependant, si vous savez ce que vous faites, vous pouvez modifier une variable globale d’un module avec la même notation que pour accéder aux fonctions : nommodule.nomelement.

Des modules peuvent importer d’autres modules. Il est courant, mais pas obligatoire, de ranger tous les import au début du module (ou du script). Les noms des modules importés sont insérés dans la table des symboles globaux du module qui importe.

Il existe une variante de l’instruction import qui importe les noms d’un module directement dans la table de symboles du module qui l’importe, par exemple :

>>> from fibo import fib, fib2
>>> fib(500)
1 1 2 3 5 8 13 21 34 55 89 144 233 377

Cela n’insère pas le nom du module depuis lequel les définitions sont récupérées dans la table des symboles locaux (dans cet exemple, fibo n’est pas défini).

Il existe même une variante permettant d’importer tous les noms qu’un module définit :

>>> from fibo import *
>>> fib(500)
1 1 2 3 5 8 13 21 34 55 89 144 233 377

Tous les noms ne commençant pas par un tiret bas (_) sont importés. Dans la grande majorité des cas, les développeurs n’utilisent pas cette syntaxe puisqu’en important un ensemble indéfini de noms, des noms déjà définis peuvent se retrouver masqués.

Notez qu’en général, importer * d’un module ou d’un paquet est déconseillé. Souvent, le code devient difficilement lisible. Son utilisation en mode interactif est acceptée pour gagner quelques secondes.

Si le nom du module est suivi par as, alors le nom suivant as est directement lié au module importé.

>>> import fibo as fib
>>> fib.fib(500)
0 1 1 2 3 5 8 13 21 34 55 89 144 233 377

Dans les faits, le module est importé de la même manière qu’avec import fibo, la seule différence est qu’il sera disponible sous le nom de fib.

C’est aussi valide en utilisant from, et a le même effet :

>>> from fibo import fib as fibonacci
>>> fibonacci(500)
0 1 1 2 3 5 8 13 21 34 55 89 144 233 377

Note

pour des raisons de performance, chaque module n’est importé qu’une fois par session. Si vous changez le code d’un module vous devez donc redémarrer l’interpréteur afin d’en voir l’impact ; ou, s’il s’agit simplement d’un seul module que vous voulez tester en mode interactif, vous pouvez le ré-importer explicitement en utilisant importlib.reload(), par exemple : import importlib; importlib.reload(nommodule).

6.1.1. Exécuter des modules comme des scripts

Lorsque vous exécutez un module Python avec

python fibo.py <arguments>

le code du module est exécuté comme si vous l’aviez importé mais son __name__ vaut "__main__". Donc, en ajoutant ces lignes à la fin du module :

if __name__ == "__main__":
    import sys
    fib(int(sys.argv[1]))

vous pouvez rendre le fichier utilisable comme script aussi bien que comme module importable, car le code qui analyse la ligne de commande n’est lancé que si le module est exécuté comme fichier « main » :

$ python fibo.py 50
1 1 2 3 5 8 13 21 34

Si le fichier est importé, le code n’est pas exécuté :

>>> import fibo
>>>

C’est typiquement utilisé soit pour proposer une interface utilisateur pour un module, soit pour lancer les tests sur le module (exécuter le module en tant que script lance les tests).

6.1.2. Les dossiers de recherche de modules

Lorsqu’un module nommé par exemple spam est importé, il est d’abord recherché parmi les modules natifs puis, s’il n’est pas trouvé, l’interpréteur cherche un fichier nommé spam.py dans une liste de dossiers donnée par la variable sys.path. Par défaut, sys.path est initialisée à :

le dossier contenant le script courant (ou le dossier courant si aucun script n’est donné) ;

PYTHONPATH (une liste de dossiers, utilisant la même syntaxe que la variable shell PATH) ;

la valeur par défaut, dépendante de l’installation.

Note

sur les systèmes qui gèrent les liens symboliques, le dossier contenant le script courant est résolu après avoir suivi le lien symbolique du script. Autrement dit, le dossier contenant le lien symbolique n’est pas ajouté aux dossiers de recherche de modules.

Après leur initialisation, les programmes Python peuvent modifier leur sys.path. Le dossier contenant le script courant est placé au début de la liste des dossiers à rechercher, avant les dossiers de bibliothèques. Cela signifie qu’un module dans ce dossier, ayant le même nom qu’un module, sera chargé à sa place. C’est une erreur typique, à moins que ce ne soit voulu. Voir Modules standards pour plus d’informations.

6.1.3. Fichiers Python « compilés »

Pour accélérer le chargement des modules, Python cache une version compilée de chaque module dans un fichier nommé module(version).pyc (ou version représente le format du fichier compilé, typiquement une version de Python) dans le dossier __pycache__. Par exemple, avec CPython 3.3, la version compilée de spam.py serait __pycache__/spam.cpython-33.pyc. Cette règle de nommage permet à des versions compilées par des versions différentes de Python de coexister.

Python compare les dates de modification du fichier source et de sa version compilée pour voir si le module doit être recompilé. Ce processus est entièrement automatique. Par ailleurs, les versions compilées sont indépendantes de la plateforme et peuvent donc être partagées entre des systèmes d’architectures différentes.

Il existe deux situations où Python ne vérifie pas le cache : le premier cas est lorsque le module est donné par la ligne de commande (cas où le module est toujours recompilé, sans même cacher sa version compilée) ; le second cas est lorsque le module n’a pas de source. Pour gérer un module sans source (où seule la version compilée est fournie), le module compilé doit se trouver dans le dossier source et sa source ne doit pas être présente.

Astuces pour les experts :

vous pouvez utiliser les options -O ou -OO lors de l’appel à Python pour réduire la taille des modules compilés. L’option -O supprime les instructions assert et l’option -OO supprime aussi les documentations __doc__. Cependant, puisque certains programmes ont besoin de ces __doc__, vous ne devriez utiliser -OO que si vous savez ce que vous faites. Les modules « optimisés » sont marqués d’un opt- et sont généralement plus petits. Les versions futures de Python pourraient changer les effets de l’optimisation ;

un programme ne s’exécute pas plus vite lorsqu’il est lu depuis un .pyc, il est juste chargé plus vite ;

le module compileall peut créer des fichiers .pyc pour tous les modules d’un dossier ;

There is more detail on this process, including a flow chart of the decisions, in PEP 3147 [https://www.python.org/dev/peps/pep-3147].

6.2. Modules standards

Python est accompagné d’une bibliothèque de modules standards, décrits dans la documentation de la Bibliothèque Python, plus loin. Certains modules sont intégrés dans l’interpréteur, ils exposent des outils qui ne font pas partie du langage mais qui font tout de même partie de l’interpréteur, soit pour le côté pratique, soit pour exposer des outils essentiels tels que l’accès aux appels système. La composition de ces modules est configurable à la compilation et dépend aussi de la plateforme cible. Par exemple, le module winreg n’est proposé que sur les systèmes Windows. Un module mérite une attention particulière, le module sys, qui est présent dans tous les interpréteurs Python. Les variables sys.ps1 et sys.ps2 définissent les chaînes d’invites principales et secondaires :

>>> import sys
>>> sys.ps1
'>>> '
>>> sys.ps2
'... '
>>> sys.ps1 = 'C> '
C> print('Yuck!')
Yuck!
C>

Ces deux variables ne sont définies que si l’interpréteur est en mode interactif.

La variable sys.path est une liste de chaînes qui détermine les chemins de recherche de modules pour l’interpréteur. Elle est initialisée à un chemin par défaut pris de la variable d’environnement PYTHONPATH ou d’une valeur par défaut interne si PYTHONPATH n’est pas définie. sys.path est modifiable en utilisant les opérations habituelles des listes :

>>> import sys
>>> sys.path.append('/ufs/guido/lib/python')

6.3. La fonction dir()

La fonction interne dir() est utilisée pour trouver quels noms sont définis par un module. Elle donne une liste de chaînes classées par ordre lexicographique :

>>> import fibo, sys
>>> dir(fibo)
['__name__', 'fib', 'fib2']
>>> dir(sys)
['__displayhook__', '__doc__', '__excepthook__', '__loader__', '__name__',
 '__package__', '__stderr__', '__stdin__', '__stdout__',
 '_clear_type_cache', '_current_frames', '_debugmallocstats', '_getframe',
 '_home', '_mercurial', '_xoptions', 'abiflags', 'api_version', 'argv',
 'base_exec_prefix', 'base_prefix', 'builtin_module_names', 'byteorder',
 'call_tracing', 'callstats', 'copyright', 'displayhook',
 'dont_write_bytecode', 'exc_info', 'excepthook', 'exec_prefix',
 'executable', 'exit', 'flags', 'float_info', 'float_repr_style',
 'getcheckinterval', 'getdefaultencoding', 'getdlopenflags',
 'getfilesystemencoding', 'getobjects', 'getprofile', 'getrecursionlimit',
 'getrefcount', 'getsizeof', 'getswitchinterval', 'gettotalrefcount',
 'gettrace', 'hash_info', 'hexversion', 'implementation', 'int_info',
 'intern', 'maxsize', 'maxunicode', 'meta_path', 'modules', 'path',
 'path_hooks', 'path_importer_cache', 'platform', 'prefix', 'ps1',
 'setcheckinterval', 'setdlopenflags', 'setprofile', 'setrecursionlimit',
 'setswitchinterval', 'settrace', 'stderr', 'stdin', 'stdout',
 'thread_info', 'version', 'version_info', 'warnoptions']

Sans paramètre, dir() liste les noms actuellement définis :

>>> a = [1, 2, 3, 4, 5]
>>> import fibo
>>> fib = fibo.fib
>>> dir()
['__builtins__', '__name__', 'a', 'fib', 'fibo', 'sys']

Notez qu’elle liste tous les types de noms : les variables, fonctions, modules, etc.

dir() ne liste ni les fonctions primitives, ni les variables internes. Si vous voulez les lister, elles sont définies dans le module builtins :

>>> import builtins
>>> dir(builtins)
['ArithmeticError', 'AssertionError', 'AttributeError', 'BaseException',
 'BlockingIOError', 'BrokenPipeError', 'BufferError', 'BytesWarning',
 'ChildProcessError', 'ConnectionAbortedError', 'ConnectionError',
 'ConnectionRefusedError', 'ConnectionResetError', 'DeprecationWarning',
 'EOFError', 'Ellipsis', 'EnvironmentError', 'Exception', 'False',
 'FileExistsError', 'FileNotFoundError', 'FloatingPointError',
 'FutureWarning', 'GeneratorExit', 'IOError', 'ImportError',
 'ImportWarning', 'IndentationError', 'IndexError', 'InterruptedError',
 'IsADirectoryError', 'KeyError', 'KeyboardInterrupt', 'LookupError',
 'MemoryError', 'NameError', 'None', 'NotADirectoryError', 'NotImplemented',
 'NotImplementedError', 'OSError', 'OverflowError',
 'PendingDeprecationWarning', 'PermissionError', 'ProcessLookupError',
 'ReferenceError', 'ResourceWarning', 'RuntimeError', 'RuntimeWarning',
 'StopIteration', 'SyntaxError', 'SyntaxWarning', 'SystemError',
 'SystemExit', 'TabError', 'TimeoutError', 'True', 'TypeError',
 'UnboundLocalError', 'UnicodeDecodeError', 'UnicodeEncodeError',
 'UnicodeError', 'UnicodeTranslateError', 'UnicodeWarning', 'UserWarning',
 'ValueError', 'Warning', 'ZeroDivisionError', '_', '__build_class__',
 '__debug__', '__doc__', '__import__', '__name__', '__package__', 'abs',
 'all', 'any', 'ascii', 'bin', 'bool', 'bytearray', 'bytes', 'callable',
 'chr', 'classmethod', 'compile', 'complex', 'copyright', 'credits',
 'delattr', 'dict', 'dir', 'divmod', 'enumerate', 'eval', 'exec', 'exit',
 'filter', 'float', 'format', 'frozenset', 'getattr', 'globals', 'hasattr',
 'hash', 'help', 'hex', 'id', 'input', 'int', 'isinstance', 'issubclass',
 'iter', 'len', 'license', 'list', 'locals', 'map', 'max', 'memoryview',
 'min', 'next', 'object', 'oct', 'open', 'ord', 'pow', 'print', 'property',
 'quit', 'range', 'repr', 'reversed', 'round', 'set', 'setattr', 'slice',
 'sorted', 'staticmethod', 'str', 'sum', 'super', 'tuple', 'type', 'vars',
 'zip']

6.4. Les paquets

Les paquets sont un moyen de structurer les espaces de nommage des modules Python en utilisant une notation « pointée ». Par exemple, le nom de module A.B désigne le sous-module B du paquet A. De la même manière que l’utilisation des modules évite aux auteurs de différents modules d’avoir à se soucier des noms de variables globales des autres, l’utilisation des noms de modules avec des points évite aux auteurs de paquets contenant plusieurs modules tel que NumPy ou Pillow d’avoir à se soucier des noms des modules des autres.

Imaginez que vous voulez construire un ensemble de modules (un « paquet ») pour gérer uniformément les fichiers contenant du son et des données sonores. Il existe un grand nombre de formats de fichiers pour stocker du son (généralement identifiés par leur extension, par exemple .wav, .aiff, .au), vous avez donc besoin de créer et maintenir un nombre croissant de modules pour gérer la conversion entre tous ces formats. Vous voulez aussi pouvoir appliquer un certain nombre d’opérations sur ces sons : mixer, ajouter de l’écho, égaliser, ajouter un effet stéréo artificiel, etc. Donc, en plus des modules de conversion, vous allez écrire une myriade de modules permettant d’effectuer ces opérations. Voici une structure possible pour votre paquet (exprimée sous la forme d’une arborescence de fichiers :

sound/                          Top-level package
      __init__.py               Initialize the sound package
      formats/                  Subpackage for file format conversions
              __init__.py
              wavread.py
              wavwrite.py
              aiffread.py
              aiffwrite.py
              auread.py
              auwrite.py
              ...
      effects/                  Subpackage for sound effects
              __init__.py
              echo.py
              surround.py
              reverse.py
              ...
      filters/                  Subpackage for filters
              __init__.py
              equalizer.py
              vocoder.py
              karaoke.py
              ...

Lorsqu’il importe des paquets, Python cherche dans chaque dossier de sys.path un sous-dossier du nom du paquet.

Les fichiers __init__.py sont nécessaires pour que Python considère les dossiers comme contenant des paquets, cela évite que des dossiers ayant des noms courants comme string ne masquent des modules qui auraient été trouvés plus tard dans la recherche des dossiers. Dans le plus simple des cas, __init__.py peut être vide, mais il peut aussi exécuter du code d’initialisation pour son paquet ou configurer la variable __all__ (documentée plus loin).

Les utilisateurs d’un module peuvent importer ses modules individuellement, par exemple :

import sound.effects.echo

charge le sous-module sound.effects.echo. Il doit alors être référencé par son nom complet.

sound.effects.echo.echofilter(input, output, delay=0.7, atten=4)

Une autre manière d’importer des sous-modules est :

from sound.effects import echo

charge aussi le sous-module echo et le rend disponible sans avoir à indiquer le préfixe du paquet. Il peut donc être utilisé comme ceci :

echo.echofilter(input, output, delay=0.7, atten=4)

Une autre méthode consiste à importer la fonction ou la variable désirée directement :

from sound.effects.echo import echofilter

Le sous-module echo est toujours chargé mais ici la fonction echofilter() est disponible directement :

echofilter(input, output, delay=0.7, atten=4)

Notez que lorsque vous utilisez from package import element, element peut aussi bien être un sous-module, un sous-paquet ou simplement un nom déclaré dans le paquet (une variable, une fonction ou une classe). L’instruction import cherche en premier si element est défini dans le paquet ; s’il ne l’est pas, elle cherche à charger un module et, si elle n’en trouve pas, une exception ImportError est levée.

Au contraire, en utilisant la syntaxe import element.souselement.soussouselement, chaque element sauf le dernier doit être un paquet. Le dernier element peut être un module ou un paquet, mais ne peut être ni une fonction, ni une classe, ni une variable définie dans l’élément précédent.

6.4.1. Importer * depuis un paquet

Qu’arrive-t-il lorsqu’un utilisateur écrit from sound.effects import * ? Idéalement, on pourrait espérer que Python aille chercher tous les sous-modules du paquet sur le système de fichiers et qu’ils seraient tous importés. Cela pourrait être long et importer certains sous-modules pourrait avoir des effets secondaires indésirables ou, du moins, désirés seulement lorsque le sous-module est importé explicitement.

La seule solution, pour l’auteur du paquet, est de fournir un index explicite du contenu du paquet. L’instruction import utilise la convention suivante : si le fichier __init__.py du paquet définit une liste nommée __all__, cette liste est utilisée comme liste des noms de modules devant être importés lorsque from package import * est utilisé. Il est de la responsabilité de l’auteur du paquet de maintenir cette liste à jour lorsque de nouvelles versions du paquet sont publiées. Un auteur de paquet peut aussi décider de ne pas autoriser d’importer * pour son paquet. Par exemple, le fichier sound/effects/__init__.py peut contenir le code suivant :

__all__ = ["echo", "surround", "reverse"]

Cela signifie que from sound.effects import * importe les trois sous-modules explicitement désignés du paquet sound.

Si __all__ n’est pas définie, l’instruction from sound.effects import * n’importe pas tous les sous-modules du paquet sound.effects dans l’espace de nommage courant mais s’assure seulement que le paquet sound.effects a été importé (i.e. que tout le code du fichier __init__.py a été exécuté) et importe ensuite les noms définis dans le paquet. Cela inclut tous les noms définis (et sous-modules chargés explicitement) par __init__.py. Sont aussi inclus tous les sous-modules du paquet ayant été chargés explicitement par une instruction import. Typiquement :

import sound.effects.echo
import sound.effects.surround
from sound.effects import *

Dans cet exemple, les modules echo et surround sont importés dans l’espace de nommage courant lorsque from...import est exécuté parce qu’ils sont définis dans le paquet sound.effects (cela fonctionne aussi lorsque __all__ est définie).

Bien que certains modules ont été pensés pour n’exporter que les noms respectant une certaine structure lorsque import * est utilisé, import * reste considéré comme une mauvaise pratique dans du code à destination d’un environnement de production.

Rappelez-vous que rien ne vous empêche d’utiliser from paquet import sous_module_specifique ! C’est d’ailleurs la manière recommandée, à moins que le module qui fait les imports ait besoin de sous-modules ayant le même nom mais provenant de paquets différents.

6.4.2. Références internes dans un paquet

Lorsque les paquets sont organisés en sous-paquets (comme le paquet sound par exemple), vous pouvez utiliser des importations absolues pour cibler des paquets voisins. Par exemple, si le module sound.filters.vocoder a besoin du module echo du paquet sound.effects, il peut utiliser from sound.effects import echo.

Il est aussi possible d’écrire des importations relatives de la forme from module import name. Ces importations relatives sont préfixées par des points pour indiquer leur origine (paquet courant ou parent). Depuis le module surround, par exemple vous pouvez écrire :

from . import echo
from .. import formats
from ..filters import equalizer

Notez que les importations relatives se fient au nom du module actuel. Puisque le nom du module principal est toujours "__main__", les modules utilisés par le module principal d’une application ne peuvent être importés que par des importations absolues.

6.4.3. Paquets dans plusieurs dossiers

Les paquets possèdent un attribut supplémentaire, __path__, qui est une liste initialisée avant l’exécution du fichier __init__.py, contenant le nom de son dossier dans le système de fichiers. Cette liste peut être modifiée, altérant ainsi les futures recherches de modules et sous-paquets contenus dans le paquet.

Bien que cette fonctionnalité ne soit que rarement utile, elle peut servir à élargir la liste des modules trouvés dans un paquet.

Notes

1

En réalité, la déclaration d’une fonction est elle-même une instruction ; son exécution enregistre le nom de la fonction dans la table des symboles globaux du module.

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7. Les entrées/sorties

Il existe bien des moyens de présenter les sorties d’un programmes ; les données peuvent être affichées sous une forme lisible par un être humain ou sauvegardées dans un fichier pour une utilisation future. Ce chapitre présente quelques possibilités.

7.1. Formatage de données

Jusqu’ici, nous avons rencontré deux moyens d’écrire des données : les déclarations d’expressions et la fonction print(). Une troisième méthode consiste à utiliser la méthode write() des fichiers, avec le fichier de sortie standard référencé en tant que sys.stdout. Voyez le Guide de Référence de la Bibliothèque Standard pour en savoir plus.

Souvent, vous voudrez plus de contrôle sur le formatage de votre sortie que des valeurs simplement séparées par des espaces. Il existe deux façons de mettre en forme votre sortie. La première est de le faire vous-même : en découpant et concaténant les chaînes, vous pouvez tout mettre en page comme vous l’imaginez ; le type string possède des méthodes pour aligner des chaines à une certaine largeur de colonne, nous voyons ceci un peu plus loin. La deuxième consiste à utiliser des littéraux de chaine formatés ou la méthode str.format().

Le module string contient une classe Template qui permet aussi de remplacer des valeurs au sein de chaînes de caractères.

Mais une question demeure, bien sûr : comment convertir des valeurs en chaînes de caractères ? Heureusement, Python fournit plusieurs moyens de convertir n’importe quelle valeur en chaîne : les fonctions repr() et str().

La fonction str() est destinée à représenter les valeurs sous une forme lisible par un être humain, alors que la fonction repr() est destinée à générer des représentations qui puissent être lues par l’interpréteur (ou qui lèvera une SyntaxError s’il n’existe aucune syntaxe équivalente). Pour les objets qui n’ont pas de représentation humaine spécifique, str() renvoie la même valeur que repr(). Beaucoup de valeurs, comme les nombres ou les structures telles que les listes ou les dictionnaires, ont la même représentation en utilisant les deux fonctions. Les chaînes de caractères, en particulier, ont deux représentations distinctes.

Quelques exemples :

>>> s = 'Hello, world.'
>>> str(s)
'Hello, world.'
>>> repr(s)
"'Hello, world.'"
>>> str(1/7)
'0.14285714285714285'
>>> x = 10 * 3.25
>>> y = 200 * 200
>>> s = 'The value of x is ' + repr(x) + ', and y is ' + repr(y) + '...'
>>> print(s)
The value of x is 32.5, and y is 40000...
>>> # The repr() of a string adds string quotes and backslashes:
... hello = 'hello, world\n'
>>> hellos = repr(hello)
>>> print(hellos)
'hello, world\n'
>>> # The argument to repr() may be any Python object:
... repr((x, y, ('spam', 'eggs')))
"(32.5, 40000, ('spam', 'eggs'))"

Voici deux façons d’écrire une table de carrés et de cubes :

>>> for x in range(1, 11):
...     print(repr(x).rjust(2), repr(x*x).rjust(3), end=' ')
...     # Note use of 'end' on previous line
...     print(repr(x*x*x).rjust(4))
...
 1   1    1
 2   4    8
 3   9   27
 4  16   64
 5  25  125
 6  36  216
 7  49  343
 8  64  512
 9  81  729
10 100 1000

>>> for x in range(1, 11):
...     print('{0:2d} {1:3d} {2:4d}'.format(x, x*x, x*x*x))
...
 1   1    1
 2   4    8
 3   9   27
 4  16   64
 5  25  125
 6  36  216
 7  49  343
 8  64  512
 9  81  729
10 100 1000

(Notez que dans ce premier exemple, une espace a été ajoutée entre chaque colonne. C’est le comportement par défaut de print(), elle ajoute des espaces entre ses arguments.)

Cet exemple illustre l’utilisation de la méthode str.rjust() des chaînes de caractères ; elle justifie à droite une chaîne dans un champ d’une largeur donnée en ajoutant des espaces sur la gauche. Il existe des méthodes similaires str.ljust() et str.center(). Ces méthodes n’écrivent rien, elles renvoient simplement une nouvelle chaîne. Si la chaîne passée en paramètre est trop longue, elle n’est pas tronquée mais renvoyée sans modification ; cela peut chambouler votre mise en page mais c’est souvent préférable à l’alternative, qui pourrait mentir sur une valeur (et si vous voulez vraiment tronquer vos valeurs, vous pouvez toujours utiliser une tranche, comme dans x.ljust(n)[:n]).

Il existe une autre méthode, str.zfill(), qui comble une chaîne numérique à gauche avec des zéros. Elle comprend les signes plus et moins :

>>> '12'.zfill(5)
'00012'
>>> '-3.14'.zfill(7)
'-003.14'
>>> '3.14159265359'.zfill(5)
'3.14159265359'

L’utilisation de base de la méthode str.format() ressemble à ceci :

>>> print('We are the {} who say "{}!"'.format('knights', 'Ni'))
We are the knights who say "Ni!"

Les accolades et les caractères à l’intérieur (appelés les champs de formatage) sont remplacés par les objets passés en paramètres à la méthode str.format(). Un nombre entre accolades se réfère à la position de l’objet passé à la méthode str.format().

>>> print('{0} and {1}'.format('spam', 'eggs'))
spam and eggs
>>> print('{1} and {0}'.format('spam', 'eggs'))
eggs and spam

Si des arguments nommés sont utilisés dans la méthode str.format(), leurs valeurs sont utilisées en se basant sur le nom des arguments

>>> print('This {food} is {adjective}.'.format(
...       food='spam', adjective='absolutely horrible'))
This spam is absolutely horrible.

Les arguments positionnés et nommés peuvent être combinés arbitrairement :

>>> print('The story of {0}, {1}, and {other}.'.format('Bill', 'Manfred',
                                                       other='Georg'))
The story of Bill, Manfred, and Georg.

'!a' (appliquer ascii()), '!s' (appliquer str()) et '!r' (appliquer repr()) peuvent être utilisées pour convertir les valeurs avant leur formatage :

>>> contents = 'eels'
>>> print('My hovercraft is full of {}.'.format(contents))
My hovercraft is full of eels.
>>> print('My hovercraft is full of {!r}.'.format(contents))
My hovercraft is full of 'eels'.

Un caractère ':' suivi d’une spécification de formatage peuvent suivre le nom du champ. Ceci offre un niveau de contrôle plus fin sur la façon dont les valeurs sont formatées. L’exemple suivant arrondit Pi à trois chiffres après la virgule (NdT : qui, en notation anglo-saxonne, est un point).

>>> import math
>>> print('The value of PI is approximately {0:.3f}.'.format(math.pi))
The value of PI is approximately 3.142.

Indiquer un entier après le ':' indique la largeur minimale de ce champ en nombre de caractères. C’est utile pour faire de jolis tableaux :

>>> table = {'Sjoerd': 4127, 'Jack': 4098, 'Dcab': 7678}
>>> for name, phone in table.items():
...     print('{0:10} ==> {1:10d}'.format(name, phone))
...
Jack       ==>       4098
Dcab       ==>       7678
Sjoerd     ==>       4127

Si vous avez une chaîne de formatage vraiment longue que vous ne voulez pas découper, il est possible de référencer les variables à formater par leur nom plutôt que par leur position. Utilisez simplement un dictionnaire et la notation entre crochets '[]' pour accéder aux clés

>>> table = {'Sjoerd': 4127, 'Jack': 4098, 'Dcab': 8637678}
>>> print('Jack: {0[Jack]:d}; Sjoerd: {0[Sjoerd]:d}; '
...       'Dcab: {0[Dcab]:d}'.format(table))
Jack: 4098; Sjoerd: 4127; Dcab: 8637678

Vous pouvez obtenir le même résultat en passant le tableau comme des arguments nommés en utilisant la notation **

>>> table = {'Sjoerd': 4127, 'Jack': 4098, 'Dcab': 8637678}
>>> print('Jack: {Jack:d}; Sjoerd: {Sjoerd:d}; Dcab: {Dcab:d}'.format(**table))
Jack: 4098; Sjoerd: 4127; Dcab: 8637678

C’est particulièrement utile en combinaison avec la fonction native vars() qui renvoie un dictionnaire contenant toutes les variables locales.

Pour avoir une description complète du formatage des chaînes de caractères avec la méthode str.format(), lisez : Syntaxe de formatage de chaîne.

7.1.1. Anciennes méthodes de formatage de chaînes

L’opérateur % peut aussi être utilisé pour formater des chaînes. Il interprète l’argument de gauche pratiquement comme une chaîne de formatage de la fonction sprintf() à appliquer à l’argument de droite, et il renvoie la chaîne résultant de cette opération de formatage. Par exemple :

>>> import math
>>> print('The value of PI is approximately %5.3f.' % math.pi)
The value of PI is approximately 3.142.

Vous trouvez plus d’informations dans la section Formatage de chaines à la printf.

7.2. Lecture et écriture de fichiers

La fonction open() renvoie un objet fichier et est le plus souvent utilisée avec deux arguments : open(nomfichier, mode).

>>> f = open('workfile', 'w')

Le premier argument est une chaîne contenant le nom du fichier. Le deuxième argument est une autre chaîne contenant quelques caractères décrivant la façon dont le fichier est utilisé. mode peut être 'r' quand le fichier n’est accédé qu’en lecture, 'w' en écriture seulement (un fichier existant portant le même nom sera alors écrasé) et 'a' ouvre le fichier en mode ajout (toute donnée écrite dans le fichier est automatiquement ajoutée à la fin). 'r+' ouvre le fichier en mode lecture/écriture. L’argument mode est optionnel, sa valeur par défaut est 'r'.

Normalement, les fichiers sont ouverts en mode texte, c’est-à-dire que vous lisez et écrivez des chaînes de caractères depuis et dans ce fichier, suivant un encodage donné. Si aucun encodage n’est spécifié, l’encodage par défaut dépend de la plateforme (voir open()). 'b' collé à la fin du mode indique que le fichier doit être ouvert en mode binaire c’est-à-dire que les données sont lues et écrites sous formes d’octets (type bytes). Ce mode est à utiliser pour les fichiers contenant autre chose que du texte.

En mode texte, le comportement par défaut, à la lecture, est de convertir les fin de lignes spécifiques à la plateforme (\n sur Unix, \r\n sur Windows etc…) en simples \n. Lors de l’écriture, le comportement par défaut est d’appliquer l’opération inverse : les \n sont convertis dans leur équivalent sur la plateforme courante. Ces modifications effectuées automatiquement sont normales pour du texte mais détérioreraient des données binaires contenues dans un fichier de type JPEG ou EXE. Soyez particulièrement attentifs à ouvrir ces fichiers binaires en mode binaire.

C’est une bonne pratique d’utiliser le mot-clé with lorsque vous traitez des fichiers. Vous fermez ainsi toujours correctement le fichier, même si une exception est levée. Utiliser with est aussi beaucoup plus court que d’utiliser l’équivalent avec des blocs try-finally :

>>> with open('workfile') as f:
...     read_data = f.read()
>>> f.closed
True

Si vous n’utilisez pas le mot clef with, vous devez appeler f.close() pour fermer le fichier et immédiatement libérer les ressources système qu’il utilise. Si vous ne fermez pas explicitement le fichier, le ramasse-miette de Python finira par détruire l’objet et fermer le fichier pour vous, mais le fichier peut rester ouvert pendant un moment. Un autre risque est que différentes implémentations de Python risquent faire ce nettoyage à des moments différents.

Après la fermeture du fichier, que ce soit via une instruction with ou en appelant f.close(), toute tentative d’utilisation de l’objet fichier échoue systématiquement.

>>> f.close()
>>> f.read()
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
ValueError: I/O operation on closed file.

7.2.1. Méthodes des objets fichiers

Les derniers exemples de cette section supposent qu’un objet fichier appelé f a déjà été créé.

Pour lire le contenu d’un fichier, appelez f.read(taille) : elle lit une certaine quantité de données et les donne sous la forme d’une chaîne (en mode texte) ou dans un objet bytes (en mode binaire). taille est un argument numérique optionnel. Quand taille est omis ou négatif, le contenu entier du fichier est lu et donné, c’est votre problème si le fichier est deux fois plus gros que la mémoire de votre machine. Sinon, un maximum de taille octets sont lus et donnés. Lorsque la fin du fichier est atteinte, f.read() renvoie une chaîne vide ('').

>>> f.read()
'This is the entire file.\n'
>>> f.read()
''

f.readline() lit une seule ligne du fichier ; un caractère de fin de ligne (\n) est laissé à la fin de la chaîne. Il n’est omis que sur la dernière ligne du fichier si celui-ci ne se termine pas un caractère de fin de ligne. Ceci permet de rendre la valeur de retour non ambigüe : si f.readline() renvoie une chaîne vide, c’est que la fin du fichier a été atteinte, alors qu’une ligne vide est représentée par '\n' (une chaîne de caractères ne contenant qu’une fin de ligne).

>>> f.readline()
'This is the first line of the file.\n'
>>> f.readline()
'Second line of the file\n'
>>> f.readline()
''

Pour lire ligne à ligne, vous pouvez aussi boucler sur l’objet fichier. C’est plus efficace en terme de gestion mémoire, plus rapide et donne un code plus simple :

>>> for line in f:
...     print(line, end='')
...
This is the first line of the file.
Second line of the file

Pour construire une liste avec toutes les lignes d’un fichier, il est aussi possible d’utiliser list(f) ou f.readlines().

f.write(chaine) écrit le contenu de chaine dans le fichier et renvoie le nombre de caractères écrits.

>>> f.write('This is a test\n')
15

Les autres types doivent être convertis, soit en une chaîne (en mode texte), soit en objet bytes (en mode binaire) avant de les écrire :

>>> value = ('the answer', 42)
>>> s = str(value)  # convert the tuple to string
>>> f.write(s)
18

f.tell() renvoie un entier indiquant la position actuelle dans le fichier, mesurée en octets à partir du début du fichier lorsque le fichier est ouvert en mode binaire, ou un nombre obscur en mode texte.

Pour modifier la position dans le fichier, utilisez f.seek(decalage, a_partir_de). La position est calculée en ajoutant decalage à un point de référence ; ce point de référence est déterminé par l’argument a_partir_de : 0 pour le début du fichier, 1 pour la position actuelle et 2 pour la fin du fichier. a_partir_de peut être omis et sa valeur par défaut est 0 (Python utilise le début du fichier comme point de référence) :

>>> f = open('workfile', 'rb+')
>>> f.write(b'0123456789abcdef')
16
>>> f.seek(5)      # Go to the 6th byte in the file
5
>>> f.read(1)
b'5'
>>> f.seek(-3, 2)  # Go to the 3rd byte before the end
13
>>> f.read(1)
b'd'

Sur un fichier en mode texte (ceux ouverts sans b dans le mode), seuls les changements de position relatifs au début du fichier sont autorisés (sauf une exception : se rendre à la fin du fichier avec seek(0, 2)) et les seules valeurs possibles pour le paramètre decalage sont les valeurs renvoyées par f.tell(), ou zéro. Toute autre valeur pour le paramètre decalage produit un comportement indéfini.

Les fichiers disposent de méthodes supplémentaires, telles que isatty() et truncate() qui sont moins souvent utilisées ; consultez la Référence de la Bibliothèque Standard pour avoir un guide complet des objets fichiers.

7.2.2. Sauvegarde de données structurées avec le module json

Les chaînes de caractères peuvent facilement être écrites dans un fichier et relues. Les nombres nécessitent un peu plus d’effort, car la méthode read() ne renvoie que des chaînes. Elles doivent donc être passées à une fonction comme int(), qui prend une chaîne comme '123' en entrée et renvoie sa valeur numérique 123. Mais dès que vous voulez enregistrer des types de données plus complexes comme des listes, des dictionnaires ou des instances de classes, le traitement lecture/écriture à la main devient vite compliqué.

Plutôt que de passer son temps à écrire et déboguer du code permettant de sauvegarder des types de données compliqués, Python permet d’utiliser JSON (JavaScript Object Notation) [http://json.org], un format répandu de représentation et d’échange de données. Le module standard appelé json peut transformer des données hiérarchisées Python en une représentation sous forme de chaîne de caractères. Ce processus est nommé sérialiser. Reconstruire les données à partir de leur représentation sous forme de chaîne est appelé déserialiser. Entre sa sérialisation et sa dé-sérialisation, la chaîne représentant les données peut avoir été stockée ou transmise à une autre machine.

Note

Le format JSON est couramment utilisé dans les applications modernes pour échanger des données. Beaucoup de développeurs le maîtrise, ce qui en fait un format de prédilection pour l’interopérabilité.

Si vous avez un objet x, vous pouvez voir sa représentation JSON en tapant simplement :

>>> import json
>>> json.dumps([1, 'simple', 'list'])
'[1, "simple", "list"]'

Une variante de la fonction dumps(), nommée dump(), sérialise simplement l’objet donné vers un fichier texte. Donc si f est un fichier texte ouvert en écriture, il est possible de faire :

json.dump(x, f)

Pour reconstruire l’objet, si f est cette fois un fichier texte ouvert en lecture :

x = json.load(f)

Cette méthode de sérialisation peut sérialiser des listes et des dictionnaires. Mais sérialiser d’autres types de données requiert un peu plus de travail. La documentation du module json explique comment faire.

Voir aussi

Le module pickle

Au contraire de JSON, pickle est un protocole permettant la sérialisation d’objets Python arbitrairement complexes. Il est donc spécifique à Python et ne peut pas être utilisé pour communiquer avec d’autres langages. Il est aussi, par défaut, une source de vulnérabilité : dé-sérialiser des données au format pickle provenant d’une source malveillante et particulièrement habile peut mener à exécuter du code arbitraire.

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8. Erreurs et exceptions

Jusqu’ici, les messages d’erreurs ont seulement été mentionnés. Mais si vous avez essayé les exemples vous avez certainement vu plus que cela. En fait, il y a au moins deux types d’erreurs à distinguer : les erreurs de syntaxe et les exceptions.

8.1. Les erreurs de syntaxe

Les erreurs de syntaxe, qui sont des erreurs d’analyse du code, sont peut-être celles que vous rencontrez le plus souvent lorsque vous êtes encore en phase d’apprentissage de Python :

>>> while True print('Hello world')
  File "<stdin>", line 1
    while True print('Hello world')
                   ^
SyntaxError: invalid syntax

L’analyseur indique la ligne incriminée et affiche une petite « flèche » pointant vers le premier endroit de la ligne où l’erreur a été détectée. L’erreur est causée (ou, au moins, a été détectée comme telle) par le symbole placé avant la flèche. Dans cet exemple la flèche est sur la fonction print() car il manque deux points (':') juste avant. Le nom du fichier et le numéro de ligne sont affichés pour vous permettre de localiser facilement l’erreur lorsque le code provient d’un script.

8.2. Exceptions

Même si une instruction ou une expression est syntaxiquement correcte, elle peut générer une erreur lors de son exécution. Les erreurs détectées durant l’exécution sont appelées des exceptions et ne sont pas toujours fatales : nous apprendrons bientôt comment les traiter dans vos programmes. La plupart des exceptions toutefois ne sont pas prises en charge par les programmes, ce qui génère des messages d’erreurs comme celui-ci :

>>> 10 * (1/0)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
ZeroDivisionError: division by zero
>>> 4 + spam*3
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
NameError: name 'spam' is not defined
>>> '2' + 2
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: Can't convert 'int' object to str implicitly

La dernière ligne du message d’erreur indique ce qui s’est passé. Les exceptions peuvent être de différents types et ce type est indiqué dans le message : les types indiqués dans l’exemple sont ZeroDivisionError, NameError et TypeError. Le texte affiché comme type de l’exception est le nom de l’exception native qui a été déclenchée. Ceci est vrai pour toutes les exceptions natives mais n’est pas une obligation pour les exceptions définies par l’utilisateur (même si c’est une convention bien pratique). Les noms des exceptions standards sont des identifiants natifs (pas des mots-clef réservés).

Le reste de la ligne fournit plus de détails en fonction du type de l’exception et de ce qui l’a causée.

La partie précédente du message d’erreur indique le contexte dans lequel s’est produite l’exception, sous la forme d’une trace de pile d’exécution. En général, celle-ci contient les lignes du code source ; toutefois, les lignes lues à partir de l’entrée standard ne sont pas affichées.

Vous trouvez la liste des exceptions natives et leur signification dans Exceptions natives.

8.3. Gestion des exceptions

Il est possible d’écrire des programmes qui prennent en charge certaines exceptions. Regardez l’exemple suivant, qui demande une saisie à l’utilisateur jusqu’à ce qu’un entier valide ait été entré, mais permet à l’utilisateur d’interrompre le programme (en utilisant Control-C ou un autre raccourci que le système accepte) ; notez qu’une interruption générée par l’utilisateur est signalée en levant l’exception KeyboardInterrupt. :

>>> while True:
...     try:
...         x = int(input("Please enter a number: "))
...         break
...     except ValueError:
...         print("Oops!  That was no valid number.  Try again...")
...

L’instruction try fonctionne comme ceci :

premièrement, la clause try (instruction(s) placée(s) entre les mots-clés try et except) est exécutée.

si aucune exception n’intervient, la clause except est sautée et l’exécution de l’instruction try est terminée.

si une exception intervient pendant l’exécution de la clause try, le reste de cette clause est sauté. Si le type d’exception levée correspond à un nom indiqué après le mot-clé except, la clause except correspondante est exécutée, puis l’exécution continue après l’instruction try.

si une exception intervient et ne correspond à aucune exception mentionnée dans la clause except, elle est transmise à l’instruction try de niveau supérieur ; si aucun gestionnaire d’exception n’est trouvé, il s’agit d’une exception non gérée et l’exécution s’arrête avec un message comme indiqué ci-dessus.

Une instruction try peut comporter plusieurs clauses except pour permettre la prise en charge de différentes exceptions. Mais un seul gestionnaire, au plus, sera exécuté. Les gestionnaires ne prennent en charge que les exceptions qui interviennent dans la clause try correspondante, pas dans d’autres gestionnaires de la même instruction try. Mais une même clause except peut citer plusieurs exceptions sous la forme d’un tuple entre parenthèses, comme dans cet exemple :

... except (RuntimeError, TypeError, NameError):
...     pass

Une classe dans une clause except est compatible avec une exception si elle est de la même classe ou d’une de ses classes dérivées. Mais l’inverse n’est pas vrai, une clause except spécifiant une classe dérivée n’est pas compatible avec une classe de base. Par exemple, le code suivant affiche B, C et D dans cet ordre :

class B(Exception):
    pass

class C(B):
    pass

class D(C):
    pass

for cls in [B, C, D]:
    try:
        raise cls()
    except D:
        print("D")
    except C:
        print("C")
    except B:
        print("B")

Notez que si les clauses except avaient été inversées (avec except B en premier), il aurait affiché B, B, B — la première clause except qui correspond est déclenchée.

La dernière clause except peut omettre le(s) nom(s) d’exception(s) et joue alors le rôle de joker. C’est toutefois à utiliser avec beaucoup de précautions car il est facile de masquer une vraie erreur de programmation par ce biais. Elle peut aussi être utilisée pour afficher un message d’erreur avant de propager l’exception (en permettant à un appelant de gérer également l’exception) :

import sys

try:
    f = open('myfile.txt')
    s = f.readline()
    i = int(s.strip())
except OSError as err:
    print("OS error: {0}".format(err))
except ValueError:
    print("Could not convert data to an integer.")
except:
    print("Unexpected error:", sys.exc_info()[0])
    raise

L’instruction try … except accepte également une clause else optionnelle qui, lorsqu’elle est présente, doit se placer après toutes les clauses except. Elle est utile pour du code qui doit être exécuté lorsqu’aucune exception n’a été levée par la clause try. Par exemple :

for arg in sys.argv[1:]:
    try:
        f = open(arg, 'r')
    except OSError:
        print('cannot open', arg)
    else:
        print(arg, 'has', len(f.readlines()), 'lines')
        f.close()

Il vaut mieux utiliser la clause else plutôt que d’ajouter du code à la clause try car cela évite de capturer accidentellement une exception qui n’a pas été levée par le code initialement protégé par l’instruction try … except.

Quand une exception intervient, une valeur peut lui être associée, que l’on appelle l’argument de l’exception. La présence de cet argument et son type dépendent du type de l’exception.

La clause except peut spécifier un nom de variable après le nom de l’exception. Cette variable est liée à une instance d’exception avec les arguments stockés dans instance.args. Pour plus de commodité, l’instance de l’exception définit la méthode __str__() afin que les arguments puissent être affichés directement sans avoir à référencer .args. Il est possible de construire une exception, y ajouter ses attributs, puis la lever plus tard.

>>> try:
...     raise Exception('spam', 'eggs')
... except Exception as inst:
...     print(type(inst))    # the exception instance
...     print(inst.args)     # arguments stored in .args
...     print(inst)          # __str__ allows args to be printed directly,
...                          # but may be overridden in exception subclasses
...     x, y = inst.args     # unpack args
...     print('x =', x)
...     print('y =', y)
...
<class 'Exception'>
('spam', 'eggs')
('spam', 'eggs')
x = spam
y = eggs

Si une exception a un argument, il est affiché dans la dernière partie du message des exceptions non gérées.

Les gestionnaires d’exceptions n’interceptent pas que les exceptions qui sont levées immédiatement dans leur clause try, mais aussi celles qui sont levées au sein de fonctions appelées (parfois indirectement) dans la clause try. Par exemple :

>>> def this_fails():
...     x = 1/0
...
>>> try:
...     this_fails()
... except ZeroDivisionError as err:
...     print('Handling run-time error:', err)
...
Handling run-time error: division by zero

8.4. Déclencher des exceptions

L’instruction raise permet au programmeur de déclencher une exception spécifique. Par exemple :

>>> raise NameError('HiThere')
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
NameError: HiThere

Le seul argument à raise indique l’exception à déclencher. Cela peut être soit une instance d’exception, soit une classe d’exception (une classe dérivée de Exception). Si une classe est donnée, elle est implicitement instanciée via l’appel de son constructeur, sans argument :

raise ValueError  # shorthand for 'raise ValueError()'

Si vous avez besoin de savoir si une exception a été levée mais que vous n’avez pas intention de la gérer, une forme plus simple de l’instruction raise permet de propager l’exception :

>>> try:
...     raise NameError('HiThere')
... except NameError:
...     print('An exception flew by!')
...     raise
...
An exception flew by!
Traceback (most recent call last):
  File "<stdin>", line 2, in <module>
NameError: HiThere

8.5. Exceptions définies par l’utilisateur

Les programmes peuvent nommer leurs propres exceptions en créant une nouvelle classe d’exception (voir Classes pour en savoir plus sur les classes de Python). Les exceptions sont typiquement dérivées de la classe Exception, directement ou non.

Les classes d’exceptions peuvent être définies pour faire tout ce qu’une autre classe peut faire. Elles sont le plus souvent gardées assez simples, n’offrant que les attributs permettant aux gestionnaires de ces exceptions d’extraire les informations relatives à l’erreur qui s’est produite. Lorsque l’on crée un module qui peut déclencher plusieurs types d’erreurs distincts, une pratique courante est de créer une classe de base pour l’ensemble des exceptions définies dans ce module et de créer des sous-classes spécifiques d’exceptions pour les différentes conditions d’erreurs :

class Error(Exception):
    """Base class for exceptions in this module."""
    pass

class InputError(Error):
    """Exception raised for errors in the input.

    Attributes:
        expression -- input expression in which the error occurred
        message -- explanation of the error
    """

    def __init__(self, expression, message):
        self.expression = expression
        self.message = message

class TransitionError(Error):
    """Raised when an operation attempts a state transition that's not
    allowed.

    Attributes:
        previous -- state at beginning of transition
        next -- attempted new state
        message -- explanation of why the specific transition is not allowed
    """

    def __init__(self, previous, next, message):
        self.previous = previous
        self.next = next
        self.message = message

Most exceptions are defined with names that end in « Error », similar to the naming of the standard exceptions.

Beaucoup de modules standards définissent leurs propres exceptions pour signaler les erreurs possibles dans les fonctions qu’ils définissent. Plus d’informations sur les classes sont présentées dans le chapitre Classes.

8.6. Définition d’actions de nettoyage

L’instruction try a une autre clause optionnelle qui est destinée à définir des actions de nettoyage devant être exécutées dans certaines circonstances. Par exemple :

>>> try:
...     raise KeyboardInterrupt
... finally:
...     print('Goodbye, world!')
...
Goodbye, world!
KeyboardInterrupt
Traceback (most recent call last):
  File "<stdin>", line 2, in <module>

Une clause finally est toujours exécutée avant de quitter l’instruction try, qu’une exception ait été levée ou non. Quand une exception a été levée dans la clause try et n’a pas été prise en charge par une clause except (ou si elle a été levée dans une clause except ou else), elle est propagée après l’exécution de la clause finally. La clause finally est également exécutée « à la sortie » quand n’importe quelle autre clause de l’instruction try est abandonnée par une instruction break, continue ou return. Voici un exemple plus compliqué :

>>> def divide(x, y):
...     try:
...         result = x / y
...     except ZeroDivisionError:
...         print("division by zero!")
...     else:
...         print("result is", result)
...     finally:
...         print("executing finally clause")
...
>>> divide(2, 1)
result is 2.0
executing finally clause
>>> divide(2, 0)
division by zero!
executing finally clause
>>> divide("2", "1")
executing finally clause
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "<stdin>", line 3, in divide
TypeError: unsupported operand type(s) for /: 'str' and 'str'

Comme vous pouvez le voir, la clause finally est exécutée dans tous les cas. L’exception de type TypeError, déclenchée en divisant deux chaînes de caractères, n’est pas prise en charge par la clause except et est donc propagée après que la clause finally a été exécutée.

Dans les vraies applications, la clause finally est notamment utile pour libérer des ressources externes (telles que des fichiers ou des connexions réseau), quelle qu’ait été l’utilisation de ces ressources.

8.7. Actions de nettoyage prédéfinies

Certains objets définissent des actions de nettoyage standards qui doivent être exécutées lorsque l’objet n’est plus nécessaire, indépendamment du fait que l’opération ayant utilisé l’objet ait réussi ou non. Regardez l’exemple suivant, qui tente d’ouvrir un fichier et d’afficher son contenu à l’écran :

for line in open("myfile.txt"):
    print(line, end="")

Le problème avec ce code est qu’il laisse le fichier ouvert pendant une durée indéterminée après que le code a fini de s’exécuter. Ce n’est pas un problème avec des scripts simples, mais peut l’être au sein d’applications plus conséquentes. L’instruction with permet d’utiliser certains objets comme des fichiers d’une façon qui assure qu’ils seront toujours nettoyés rapidement et correctement.

with open("myfile.txt") as f:
    for line in f:
        print(line, end="")

Après l’exécution du bloc, le fichier f est toujours fermé, même si un problème est survenu pendant l’exécution de ces lignes. D’autres objets qui, comme pour les fichiers, fournissent des actions de nettoyage prédéfinies l’indiquent dans leur documentation.

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9. Classes

Les classes sont un moyen de réunir des données et des fonctionnalités. Créer une nouvelle classe crée un nouveau type d’objet et ainsi de nouvelles instances de ce type peuvent être construites. Chaque instance peut avoir ses propres attributs, ce qui définit son état. Une instance peut aussi avoir des méthodes (définies par la classe de l’instance) pour modifier son état.

La notion de classes en Python s’inscrit dans le langage avec un minimum de syntaxe et de sémantique nouvelles. C’est un mélange des mécanismes rencontrés dans C++ et Modula-3. Les classes fournissent toutes les fonctionnalités standards de la programmation orientée objet : l’héritage de classes autorise les héritages multiples, une classe dérivée peut surcharger les méthodes de sa ou ses classes de base et une méthode peut appeler la méthode d’une classe de base qui possède le même nom. Les objets peuvent contenir n’importe quel nombre ou type de données. De la même manière que les modules, les classes participent à la nature dynamique de Python : elles sont créées pendant l’exécution et peuvent être modifiées après leur création.

Dans la terminologie C++, les membres des classes (y compris les données) sont publics (sauf exception, voir Variables privées) et toutes les fonctions membres sont virtuelles. Comme avec Modula-3, il n’y a aucune façon d’accéder aux membres d’un objet à partir de ses méthodes : une méthode est déclarée avec un premier argument explicite représentant l’objet et cet argument est transmis de manière implicite lors de l’appel. Comme avec Smalltalk, les classes elles-mêmes sont des objets. Il existe ainsi une sémantique pour les importer et les renommer. Au contraire de C++ et Modula-3, les types natifs peuvent être utilisés comme classes de base pour être étendus par l’utilisateur. Enfin, comme en C++, la plupart des opérateurs natifs avec une syntaxe spéciale (opérateurs arithmétiques, indiçage, etc.) peuvent être redéfinis pour les instances de classes.

En l’absence d’une terminologie communément admise pour parler des classes, nous utilisons parfois des termes de Smalltalk et C++. Nous voulions utiliser les termes de Modula-3 puisque sa sémantique orientée objet est plus proche de celle de Python que C++, mais il est probable que seul un petit nombre de lecteurs les connaissent.

9.1. Objets et noms : préambule

Les objets possèdent une existence propre et plusieurs noms peuvent être utilisés (dans divers contextes) pour faire référence à un même objet. Ce concept est connu sous le nom d’alias dans d’autres langages. Il n’apparaît pas au premier coup d’œil en Python et il peut être ignoré tant qu’on travaille avec des types de base immuables (nombres, chaînes, tuples). Cependant, les alias peuvent produire des effets surprenants sur la sémantique d’un code Python mettant en jeu des objets muables comme les listes, les dictionnaires et la plupart des autres types. En général, leur utilisation est bénéfique au programme car les alias se comportent, d’un certain point de vue, comme des pointeurs. Par exemple, transmettre un objet n’a aucun coût car c’est simplement un pointeur qui est transmis par l’implémentation ; et si une fonction modifie un objet passé en argument, le code à l’origine de l’appel voit le changement. Ceci élimine le besoin d’avoir deux mécanismes de transmission d’arguments comme en Pascal.

9.2. Portées et espaces de nommage en Python

Avant de présenter les classes, nous devons aborder la notion de portée en Python. Les définitions de classes font d’habiles manipulations avec les espaces de nommage, vous devez donc savoir comment les portées et les espaces de nommage fonctionnent. Soit dit en passant, la connaissance de ce sujet est aussi utile aux développeurs Python expérimentés.

Commençons par quelques définitions.

Un espace de nommage est une table de correspondance entre des noms et des objets. La plupart des espaces de nommage sont actuellement implémentés sous forme de dictionnaires Python, mais ceci n’est normalement pas visible (sauf pour les performances) et peut changer dans le futur. Comme exemples d’espaces de nommage, nous pouvons citer les primitives (fonctions comme abs() et les noms des exceptions de base) ; les noms globaux dans un module ; et les noms locaux lors d’un appel de fonction. D’une certaine manière, l’ensemble des attributs d’un objet forme lui-même un espace de nommage. L’important à retenir concernant les espaces de nommage est qu’il n’y a absolument aucun lien entre les noms de différents espaces de nommage ; par exemple, deux modules différents peuvent définir une fonction maximize sans qu’il n’y ait de confusion. Les utilisateurs des modules doivent préfixer le nom de la fonction avec celui du module.

À ce propos, nous utilisons le mot attribut pour tout nom suivant un point. Par exemple, dans l’expression z.real, real est un attribut de l’objet z. Rigoureusement parlant, les références à des noms dans des modules sont des références d’attributs : dans l’expression nommodule.nomfonction, nommodule est un objet module et nomfonction est un attribut de cet objet. Dans ces conditions, il existe une correspondance directe entre les attributs du module et les noms globaux définis dans le module : ils partagent le même espace de nommage 1 !

Les attributs peuvent être en lecture seule ou modifiables. S’ils sont modifiables, l’affectation à un attribut est possible. Les attributs de modules sont modifiables : vous pouvez écrire nommodule.la_reponse = 42. Les attributs modifiables peuvent aussi être effacés avec l’instruction del. Par exemple, del nommodule.la_reponse supprime l’attribut la_reponse de l’objet nommé nommodule.

Les espaces de nommage sont créés à différents moments et ont différentes durées de vie. L’espace de nommage contenant les primitives est créé au démarrage de l’interpréteur Python et n’est jamais effacé. L’espace de nommage globaux pour un module est créé lorsque la définition du module est lue. Habituellement, les espaces de nommage des modules durent aussi jusqu’à l’arrêt de l’interpréteur. Les instructions exécutées par la première invocation de l’interpréteur, qu’elles soient lues depuis un fichier de script ou de manière interactive, sont considérées comme faisant partie d’un module appelé __main__, de façon qu’elles possèdent leur propre espace de nommage (les primitives vivent elles-mêmes dans un module, appelé builtins).

L’espace des noms locaux d’une fonction est créé lors de son appel, puis effacé lorsqu’elle renvoie un résultat ou lève une exception non prise en charge (en fait, « oublié » serait une meilleure façon de décrire ce qui se passe réellement). Bien sûr, des invocations récursives ont chacune leur propre espace de nommage.

La portée est la zone textuelle d’un programme Python où un espace de nommage est directement accessible. « Directement accessible » signifie ici qu’une référence non qualifiée à un nom est cherchée dans l’espace de nommage.

Bien que les portées soient déterminées de manière statique, elles sont utilisées de manière dynamique. À n’importe quel moment de l’exécution, il y a au minimum trois portées imbriquées dont les espaces de nommage sont directement accessibles :

la portée la plus au centre, celle qui est consultée en premier, contient les noms locaux ;

les portées des fonctions englobantes, qui sont consultées en commençant avec la portée englobante la plus proche, contiennent des noms non-locaux mais aussi non-globaux ;

l’avant-dernière portée contient les noms globaux du module courant ;

la portée englobante, consultée en dernier, est l’espace de nommage contenant les primitives.

Si un nom est déclaré comme global, alors toutes les références et affectations vont directement dans la portée intermédiaire contenant les noms globaux du module. Pour pointer une variable qui se trouve en dehors de la portée la plus locale, vous pouvez utiliser l’instruction nonlocal. Si une telle variable n’est pas déclarée nonlocal, elle est en lecture seule (toute tentative de la modifier crée simplement une nouvelle variable dans la portée la plus locale, en laissant inchangée la variable du même nom dans sa portée d’origine).

Habituellement, la portée locale référence les noms locaux de la fonction courante. En dehors des fonctions, la portée locale référence le même espace de nommage que la portée globale : l’espace de nommage du module. Les définitions de classes créent un nouvel espace de nommage dans la portée locale.

Il est important de réaliser que les portées sont déterminées de manière textuelle : la portée globale d’une fonction définie dans un module est l’espace de nommage de ce module, quelle que soit la provenance de l’appel à la fonction. En revanche, la recherche réelle des noms est faite dynamiquement au moment de l’exécution. Cependant la définition du langage est en train d’évoluer vers une résolution statique des noms au moment de la « compilation », donc ne vous basez pas sur une résolution dynamique (en réalité, les variables locales sont déjà déterminées de manière statique) !

Une particularité de Python est que, si aucune instruction global n’est active, les affectations de noms vont toujours dans la portée la plus proche. Les affectations ne copient aucune donnée : elles se contentent de lier des noms à des objets. Ceci est également vrai pour l’effacement : l’instruction del x supprime la liaison de x dans l’espace de nommage référencé par la portée locale. En réalité, toutes les opérations qui impliquent des nouveaux noms utilisent la portée locale : en particulier, les instructions import et les définitions de fonctions effectuent une liaison du module ou du nom de fonction dans la portée locale.

L’instruction global peut être utilisée pour indiquer que certaines variables existent dans la portée globale et doivent être reliées en local ; l’instruction nonlocal indique que certaines variables existent dans une portée supérieure et doivent être reliées en local.

9.2.1. Exemple de portées et d’espaces de nommage

Ceci est un exemple montrant comment utiliser les différentes portées et espaces de nommage, et comment global et nonlocal modifient l’affectation de variable :

def scope_test():
    def do_local():
        spam = "local spam"

    def do_nonlocal():
        nonlocal spam
        spam = "nonlocal spam"

    def do_global():
        global spam
        spam = "global spam"

    spam = "test spam"
    do_local()
    print("After local assignment:", spam)
    do_nonlocal()
    print("After nonlocal assignment:", spam)
    do_global()
    print("After global assignment:", spam)

scope_test()
print("In global scope:", spam)

Ce code donne le résultat suivant :

After local assignment: test spam
After nonlocal assignment: nonlocal spam
After global assignment: nonlocal spam
In global scope: global spam

Vous pouvez constater que l’affectation locale (qui est effectuée par défaut) n’a pas modifié la liaison de spam dans scope_test. L’affectation nonlocal a changé la liaison de spam dans scope_test et l’affectation global a changé la liaison au niveau du module.

Vous pouvez également voir qu’aucune liaison pour spam n’a été faite avant l’affectation global.

9.3. Une première approche des classes

Le concept de classe introduit un peu de syntaxe nouvelle, trois nouveaux types d’objets ainsi que quelques nouveaux éléments de sémantique.

9.3.1. Syntaxe de définition des classes

La forme la plus simple de définition d’une classe est la suivante :

class ClassName:
    <statement-1>
    .
    .
    .
    <statement-N>

Les définitions de classes, comme les définitions de fonctions (définitions def), doivent être exécutées avant d’avoir un effet. Vous pouvez tout à fait placer une définition de classe dans une branche d’une instruction conditionnelle if ou encore à l’intérieur d’une fonction.

Dans la pratique, les déclarations dans une définition de classe sont généralement des définitions de fonctions mais d’autres déclarations sont permises et parfois utiles (nous revenons sur ce point plus tard). Les définitions de fonction à l’intérieur d’une classe ont normalement une forme particulière de liste d’arguments, dictée par les conventions d’appel aux méthodes (à nouveau, tout ceci est expliqué plus loin).

Quand une classe est définie, un nouvel espace de nommage est créé et utilisé comme portée locale — Ainsi, toutes les affectations de variables locales entrent dans ce nouvel espace de nommage. En particulier, les définitions de fonctions y lient le nom de la nouvelle fonction.

À la fin de la définition d’une classe, un objet classe est créé. C’est, pour simplifier, une encapsulation du contenu de l’espace de nommage créé par la définition de classe. Nous revoyons les objets classes dans la prochaine section. La portée locale initiale (celle qui prévaut avant le début de la définition de la classe) est ré-instanciée et l’objet de classe est lié ici au nom de classe donné dans l’en-tête de définition de classe (ClassName dans l’exemple).

9.3.2. Objets classes

Les objets classes prennent en charge deux types d’opérations : des références à des attributs et l’instanciation.

Les références d’attributs utilisent la syntaxe standard utilisée pour toutes les références d’attributs en Python : obj.nom. Les noms d’attribut valides sont tous les noms qui se trouvaient dans l’espace de nommage de la classe quand l’objet classe a été créé. Donc, si la définition de classe est de cette forme :

class MyClass:
    """A simple example class"""
    i = 12345

    def f(self):
        return 'hello world'

alors MyClass.i et MyClass.f sont des références valides à des attributs, renvoyant respectivement un entier et un objet fonction. Les attributs de classes peuvent également être affectés, de sorte que vous pouvez modifier la valeur de MyClass.i par affectation. __doc__ est aussi un attribut valide, renvoyant la docstring appartenant à la classe : "A simple example class".

L”instanciation de classes utilise la notation des fonctions. Considérez simplement que l’objet classe est une fonction sans paramètre qui renvoie une nouvelle instance de la classe. Par exemple (en considérant la classe définie ci-dessus) :

x = MyClass()

crée une nouvelle instance de la classe et affecte cet objet à la variable locale x.

L’opération d’instanciation (en « appelant » un objet classe) crée un objet vide. De nombreuses classes aiment créer des instances personnalisées correspondant à un état initial spécifique. À cet effet, une classe peut définir une méthode spéciale nommée __init__(), comme ceci :

def __init__(self):
    self.data = []

Quand une classe définit une méthode __init__(), l’instanciation de la classe appelle automatiquement __init__() pour la nouvelle instance de la classe. Donc, dans cet exemple, l’initialisation d’une nouvelle instance peut être obtenue par :

x = MyClass()

Bien sûr, la méthode __init__() peut avoir des arguments pour une plus grande flexibilité. Dans ce cas, les arguments donnés à l’opérateur d’instanciation de classe sont transmis à __init__(). Par exemple

>>> class Complex:
...     def __init__(self, realpart, imagpart):
...         self.r = realpart
...         self.i = imagpart
...
>>> x = Complex(3.0, -4.5)
>>> x.r, x.i
(3.0, -4.5)

9.3.3. Objets instances

Now what can we do with instance objects? The only operations understood by instance objects are attribute references. There are two kinds of valid attribute names: data attributes and methods.

Les attributs “données” correspondent à des « variables d’instance » en Smalltalk et aux « membres de données » en C++. Les attributs “données” n’ont pas à être déclarés. Comme les variables locales, ils existent dès lors qu’ils sont assignés une première fois. Par exemple, si x est l’instance de MyClass créée ci-dessus, le code suivant affiche la valeur 16, sans laisser de trace :

x.counter = 1
while x.counter < 10:
    x.counter = x.counter * 2
print(x.counter)
del x.counter

L’autre type de référence à un attribut d’instance est une méthode. Une méthode est une fonction qui « appartient à » un objet (en Python, le terme de méthode n’est pas unique aux instances de classes : d’autres types d’objets peuvent aussi avoir des méthodes. Par exemple, les objets listes ont des méthodes appelées append, insert, remove, sort et ainsi de suite. Toutefois, dans la discussion qui suit, sauf indication contraire, nous utilisons le terme de méthode exclusivement en référence à des méthodes d’objets instances de classe).

Les noms de méthodes valides d’un objet instance dépendent de sa classe. Par définition, tous les attributs d’une classe qui sont des objets fonctions définissent les méthodes correspondantes de ses instances. Donc, dans notre exemple, x.f est une référence valide à une méthode car MyClass.f est une fonction, mais pas x.i car MyClass.i n’en est pas une. Attention cependant, x.f n’est pas la même chose que MyClass.f — Il s’agit d’un objet méthode, pas d’un objet fonction.

9.3.4. Objets méthode

Le plus souvent, une méthode est appelée juste après avoir été liée :

x.f()

Dans l’exemple de la classe MyClass, cela renvoie la chaîne de caractères hello world. Toutefois, il n’est pas nécessaire d’appeler la méthode directement : x.f est un objet méthode, il peut être gardé de côté et être appelé plus tard. Par exemple :

xf = x.f
while True:
    print(xf())

affiche hello world jusqu’à la fin des temps.

Que se passe-t-il exactement quand une méthode est appelée ? Vous avez dû remarquer que x.f() a été appelée dans le code ci-dessus sans argument, alors que la définition de la méthode f() spécifie bien qu’elle prend un argument. Qu’est-il arrivé à l’argument ? Python doit sûrement lever une exception lorsqu’une fonction qui requiert un argument est appelée sans – même si l’argument n’est pas utilisé…

En fait, vous avez peut-être deviné la réponse : la particularité des méthodes est que l’objet est passé comme premier argument de la fonction. Dans notre exemple, l’appel x.f() est exactement équivalent à MyClass.f(x). En général, appeler une méthode avec une liste de n arguments est équivalent à appeler la fonction correspondante avec une liste d’arguments créée en ajoutant l’instance de l’objet de la méthode avant le premier argument.

If you still don’t understand how methods work, a look at the implementation can perhaps clarify matters. When a non-data attribute of an instance is referenced, the instance’s class is searched. If the name denotes a valid class attribute that is a function object, a method object is created by packing (pointers to) the instance object and the function object just found together in an abstract object: this is the method object. When the method object is called with an argument list, a new argument list is constructed from the instance object and the argument list, and the function object is called with this new argument list.

9.3.5. Classes et variables d’instance

En général, les variables d’instance stockent des informations relatives à chaque instance alors que les variables de classe servent à stocker les attributs et méthodes communes à toutes les instances de la classe :

class Dog:

    kind = 'canine'         # class variable shared by all instances

    def __init__(self, name):
        self.name = name    # instance variable unique to each instance

>>> d = Dog('Fido')
>>> e = Dog('Buddy')
>>> d.kind                  # shared by all dogs
'canine'
>>> e.kind                  # shared by all dogs
'canine'
>>> d.name                  # unique to d
'Fido'
>>> e.name                  # unique to e
'Buddy'

Comme nous l’avons vu dans Objets et noms : préambule, les données partagées muable (telles que les listes, dictionnaires, etc.) peuvent avoir des effets surprenants. Par exemple, la liste tricks dans le code suivant ne devrait pas être utilisée en tant que variable de classe car, dans ce cas, une seule liste est partagée par toutes les instances de Dog :

class Dog:

    tricks = []             # mistaken use of a class variable

    def __init__(self, name):
        self.name = name

    def add_trick(self, trick):
        self.tricks.append(trick)

>>> d = Dog('Fido')
>>> e = Dog('Buddy')
>>> d.add_trick('roll over')
>>> e.add_trick('play dead')
>>> d.tricks                # unexpectedly shared by all dogs
['roll over', 'play dead']

Une conception correcte de la classe est d’utiliser une variable d’instance à la place :

class Dog:

    def __init__(self, name):
        self.name = name
        self.tricks = []    # creates a new empty list for each dog

    def add_trick(self, trick):
        self.tricks.append(trick)

>>> d = Dog('Fido')
>>> e = Dog('Buddy')
>>> d.add_trick('roll over')
>>> e.add_trick('play dead')
>>> d.tricks
['roll over']
>>> e.tricks
['play dead']

9.4. Remarques diverses

Les attributs “données” surchargent les méthodes avec le même nom ; pour éviter des conflits de nommage, qui peuvent causer des bugs difficiles à trouver dans de grands programmes, il est sage d’adopter certaines conventions qui minimisent les risques de conflits. Parmi les conventions possibles, on peut citer la mise en majuscule des noms de méthodes, le préfixe des noms d’attributs “données” par une chaîne courte et unique (parfois juste la caractère souligné) ou l’utilisation de verbes pour les méthodes et de noms pour les attributs “données”.

Les attributs “données” peuvent être référencés par des méthodes comme par des utilisateurs ordinaires (« clients ») d’un objet. En d’autres termes, les classes ne sont pas utilisables pour implémenter des types de données purement abstraits. En fait, il n’est pas possible en Python d’imposer de masquer des données — tout est basé sur des conventions (d’un autre côté, l’implémentation de Python, écrite en C, peut complètement masquer les détails d’implémentation et contrôler l’accès à un objet si nécessaire ; ceci peut être utilisé par des extensions de Python écrites en C).

Les clients doivent utiliser les attributs “données” avec précaution — ils pourraient mettre le désordre dans les invariants gérés par les méthodes avec leurs propres valeurs d’attributs. Remarquez que les clients peuvent ajouter leurs propres attributs “données” à une instance d’objet sans altérer la validité des méthodes, pour autant que les noms n’entrent pas en conflit — là aussi, adopter une convention de nommage peut éviter bien des problèmes.

Il n’y a pas de notation abrégée pour référencer des attributs “données” (ou les autres méthodes !) depuis les méthodes. Nous pensons que ceci améliore en fait la lisibilité des méthodes : il n’y a aucune chance de confondre variables locales et variables d’instances quand on regarde le code d’une méthode.

Souvent, le premier argument d’une méthode est nommé self. Ce n’est qu’une convention : le nom self n’a aucune signification particulière en Python. Notez cependant que si vous ne suivez pas cette convention, votre code risque d’être moins lisible pour d’autres programmeurs Python et il est aussi possible qu’un programme qui fasse l’introspection de classes repose sur une telle convention.

Tout objet fonction qui est un attribut de classe définit une méthode pour des instances de cette classe. Il n’est pas nécessaire que le texte de définition de la fonction soit dans la définition de la classe : il est possible d’affecter un objet fonction à une variable locale de la classe. Par exemple :

# Function defined outside the class
def f1(self, x, y):
    return min(x, x+y)

class C:
    f = f1

    def g(self):
        return 'hello world'

    h = g

Maintenant, f, g et h sont toutes des attributs de la classe C et font référence à des fonctions objets. Par conséquent, ce sont toutes des méthodes des instances de C — h est exactement identique à g. Remarquez qu’en pratique, ceci ne sert qu’à embrouiller le lecteur d’un programme.

Les méthodes peuvent appeler d’autres méthodes en utilisant des méthodes qui sont des attributs de l’argument self :

class Bag:
    def __init__(self):
        self.data = []

    def add(self, x):
        self.data.append(x)

    def addtwice(self, x):
        self.add(x)
        self.add(x)

Les méthodes peuvent faire référence à des noms globaux de la même manière que les fonctions. La portée globale associée à une méthode est le module contenant la définition de la classe (la classe elle-même n’est jamais utilisée en tant que portée globale). Alors qu’il est rare d’avoir une bonne raison d’utiliser des données globales dans une méthode, il y a de nombreuses utilisations légitimes de la portée globale : par exemple, les fonctions et modules importés dans une portée globale peuvent être utilisés par des méthodes, de même que les fonctions et classes définies dans cette même portée. Habituellement, la classe contenant la méthode est elle-même définie dans cette portée globale et, dans la section suivante, nous verrons de bonnes raisons pour qu’une méthode référence sa propre classe.

Toute valeur est un objet et a donc une classe (appelée aussi son type). Elle est stockée dans objet.__class__.

9.5. Héritage

Bien sûr, ce terme de « classe » ne serait pas utilisé s’il n’y avait pas d’héritage. La syntaxe pour définir une sous-classe est de cette forme :

class DerivedClassName(BaseClassName):
    <statement-1>
    .
    .
    .
    <statement-N>

Le nom BaseClassName doit être défini dans une portée contenant la définition de la classe dérivée. À la place du nom d’une classe de base, une expression est aussi autorisée. Ceci peut être utile, par exemple, lorsque la classe est définie dans un autre module :

class DerivedClassName(modname.BaseClassName):

L’exécution d’une définition de classe dérivée se déroule comme pour une classe de base. Quand l’objet de la classe est construit, la classe de base est mémorisée. Elle est utilisée pour la résolution des références d’attributs : si un attribut n’est pas trouvé dans la classe, la recherche se poursuit en regardant dans la classe de base. Cette règle est appliquée récursivement si la classe de base est elle-même dérivée d’une autre classe.

Il n’y a rien de particulier dans l’instanciation des classes dérivées : DerivedClassName() crée une nouvelle instance de la classe. Les références aux méthodes sont résolues comme suit : l’attribut correspondant de la classe est recherché, en remontant la hiérarchie des classes de base si nécessaire, et la référence de méthode est valide si cela conduit à une fonction.

Les classes dérivées peuvent surcharger des méthodes de leurs classes de base. Comme les méthodes n’ont aucun privilège particulier quand elles appellent d’autres méthodes d’un même objet, une méthode d’une classe de base qui appelle une autre méthode définie dans la même classe peut en fait appeler une méthode d’une classe dérivée qui la surcharge (pour les programmeurs C++ : toutes les méthodes de Python sont en effet « virtuelles »).

Une méthode dans une classe dérivée peut aussi, en fait, vouloir étendre plutôt que simplement remplacer la méthode du même nom de sa classe de base. L’appel direct à la méthode de la classe de base s’écrit simplement BaseClassName.nomMethode(self, arguments). C’est parfois utile également aux clients (notez bien que ceci ne fonctionne que si la classe de base est accessible en tant que BaseClassName dans la portée globale).

Python définit deux fonctions primitives pour gérer l’héritage :

utilisez isinstance() pour tester le type d’une instance : isinstance(obj, int) renvoie True seulement si obj.__class__ est égal à int ou à une autre classe dérivée de int ;

utilisez issubclass() pour tester l’héritage d’une classe : issubclass(bool, int) renvoie True car la classe bool est une sous-classe de int. Cependant, issubclass(float, int) renvoie False car float n’est pas une sous-classe de int.

9.5.1. Héritage multiple

Python gère également une forme d’héritage multiple. Une définition de classe ayant plusieurs classes de base est de cette forme :

class DerivedClassName(Base1, Base2, Base3):
    <statement-1>
    .
    .
    .
    <statement-N>

Dans la plupart des cas, vous pouvez vous représenter la recherche d’attributs dans les classes parentes comme étant : le plus profond d’abord, de gauche à droite, sans chercher deux fois dans la même classe si elle apparaît plusieurs fois dans la hiérarchie. Ainsi, si un attribut n’est pas trouvé dans DerivedClassName, il est recherché dans Base1, puis (récursivement) dans les classes de base de Base1 ; s’il n’y est pas trouvé, il est recherché dans Base2 et ses classes de base, et ainsi de suite.

Dans les faits, c’est un peu plus complexe que ça ; l’ordre de la recherche (method resolution order, ou MRO en anglais) change dynamiquement pour gérer des appels coopératifs à super(). Cette approche est connue sous le nom de la « appel de la méthode la plus proche » (call-next-method en anglais) dans d’autres langages avec héritage multiple. Elle est plus puissante que le simple appel à super que l’on trouve dans les langages à héritage simple.

L’ordre défini dynamiquement est nécessaire car tous les cas d’héritage multiple comportent une ou plusieurs relations en losange (où au moins une classe peut être accédée à partir de plusieurs chemins en partant de la classe la plus basse). Par exemple, puisque toutes les classes héritent de object, tout héritage multiple ouvre plusieurs chemins pour atteindre object. Pour qu’une classe de base ne soit pas appelée plusieurs fois, l’algorithme dynamique linéarise l’ordre de recherche d’une façon qui préserve l’ordre d’héritage, de la gauche vers la droite, spécifié dans chaque classe, qui appelle chaque classe parente une seule fois, qui est monotone (ce qui signifie qu’une classe peut être sous-classée sans affecter l’ordre d’héritage de ses parents). Prises ensemble, ces propriétés permettent de concevoir des classes de façon fiable et extensible dans un contexte d’héritage multiple. Pour plus de détails, consultez http://www.python.org/download/releases/2.3/mro/.

9.6. Variables privées

Les membres « privés », qui ne peuvent être accédés que depuis l’intérieur d’un objet, n’existent pas en Python. Toutefois, il existe une convention respectée par la majorité du code Python : un nom préfixé par un tiret bas (comme _spam) doit être considéré comme une partie non publique de l’API (qu’il s’agisse d’une fonction, d’une méthode ou d’un attribut “données”). Il doit être vu comme un détail d’implémentation pouvant faire l’objet de modifications futures sans préavis.

Dès lors qu’il y a un cas d’utilisation valable pour avoir des attributs privés aux classes (notamment pour éviter des conflits avec des noms définis dans des sous-classes), il existe un support (certes limité) pour un tel mécanisme, appelé name mangling. Tout identifiant de la forme __spam (avec au moins deux tirets bas en tête et au plus un à la fin) est remplacé textuellement par _classname__spam, où classname est le nom de la classe sans le ou les premiers tirets-bas. Ce « découpage » est effectué sans tenir compte de la position syntaxique de l’identifiant, tant qu’il est présent dans la définition d’une classe.

Ce changement de nom est utile pour permettre à des sous-classes de surcharger des méthodes sans casser les appels de méthodes à l’intérieur d’une classe. Par exemple :

class Mapping:
    def __init__(self, iterable):
        self.items_list = []
        self.__update(iterable)

    def update(self, iterable):
        for item in iterable:
            self.items_list.append(item)

    __update = update   # private copy of original update() method

class MappingSubclass(Mapping):

    def update(self, keys, values):
        # provides new signature for update()
        # but does not break __init__()
        for item in zip(keys, values):
            self.items_list.append(item)

The above example would work even if MappingSubclass were to introduce a __update identifier since it is replaced with _Mapping__update in the Mapping class and _MappingSubclass__update in the MappingSubclass class respectively.

Notez que ces règles sont conçues avant tout pour éviter les accidents ; il reste possible d’accéder ou de modifier une variable considérée comme privée. Ceci peut même être utile dans certaines circonstances, comme au sein du débogueur.

Remarquez que le code que vous passez à exec(), eval() ne considère pas le nom de la classe appelante comme étant la classe courante ; le même effet s’applique à la directive global dont l’effet est, de la même façon, restreint au code compilé dans le même ensemble de byte-code. Les mêmes restrictions s’appliquent à getattr(), setattr() et delattr(), ainsi qu’aux références directes à __dict__.

9.7. Trucs et astuces

Il est parfois utile d’avoir un type de donnée similaire au « record » du Pascal ou au struct du C, qui regroupent ensemble quelques attributs “données” nommés. La définition d’une classe vide remplit parfaitement ce besoin :

class Employee:
    pass

john = Employee()  # Create an empty employee record

# Fill the fields of the record
john.name = 'John Doe'
john.dept = 'computer lab'
john.salary = 1000

À du code Python qui s’attend à recevoir un type de donnée abstrait spécifique, on peut souvent fournir une classe qui simule les méthodes de ce type. Par exemple, à une fonction qui formate des données extraites d’un objet fichier, vous pouvez lui passer comme argument une instance d’une classe qui implémente les méthodes read() et readline() en puisant ses données à partir d’un tampon de chaînes de caractères.

Les objets méthodes d’instances ont aussi des attributs : m.__self__ est l’instance d’objet avec la méthode m() et m.__func__ est l’objet fonction correspondant à la méthode.

9.8. Itérateurs

Vous avez maintenant certainement remarqué que l’on peut itérer sur la plupart des objets conteneurs en utilisant une instruction for :

for element in [1, 2, 3]:
    print(element)
for element in (1, 2, 3):
    print(element)
for key in {'one':1, 'two':2}:
    print(key)
for char in "123":
    print(char)
for line in open("myfile.txt"):
    print(line, end='')

Ce style est simple, concis et pratique. L’utilisation d’itérateurs imprègne et unifie Python. En arrière plan, l’instruction for appelle la fonction iter() sur l’objet conteneur. Cette fonction renvoie un objet itérateur qui définit la méthode __next__(), laquelle accède aux éléments du conteneur un par un. Lorsqu’il n’y a plus d’élément, __next__() lève une exception StopIteration qui indique à la boucle de l’instruction for de se terminer. Vous pouvez appeler la méthode __next__() en utilisant la fonction native next(). Cet exemple montre comment tout cela fonctionne :

>>> s = 'abc'
>>> it = iter(s)
>>> it
<iterator object at 0x00A1DB50>
>>> next(it)
'a'
>>> next(it)
'b'
>>> next(it)
'c'
>>> next(it)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
    next(it)
StopIteration

Une fois compris les mécanismes de gestion des itérateurs, il est simple d’ajouter ce comportement à vos classes. Définissez une méthode __iter__() qui renvoie un objet disposant d’une méthode __next__(). Si la classe définit elle-même la méthode __next__(), alors __iter__() peut simplement renvoyer self :

class Reverse:
    """Iterator for looping over a sequence backwards."""
    def __init__(self, data):
        self.data = data
        self.index = len(data)

    def __iter__(self):
        return self

    def __next__(self):
        if self.index == 0:
            raise StopIteration
        self.index = self.index - 1
        return self.data[self.index]

>>> rev = Reverse('spam')
>>> iter(rev)
<__main__.Reverse object at 0x00A1DB50>
>>> for char in rev:
...     print(char)
...
m
a
p
s

9.9. Générateurs

Les générateurs sont des outils simples et puissants pour créer des itérateurs. Ils sont écrits comme des fonctions classiques mais utilisent l’instruction yield lorsqu’ils veulent renvoyer des données. À chaque fois qu’il est appelé par next(), le générateur reprend son exécution là où il s’était arrêté (en conservant tout son contexte d’exécution). Un exemple montre très bien combien les générateurs sont simples à créer :

def reverse(data):
    for index in range(len(data)-1, -1, -1):
        yield data[index]

>>> for char in reverse('golf'):
...     print(char)
...
f
l
o
g

Tout ce qui peut être fait avec des générateurs peut également être fait avec des itérateurs basés sur des classes, comme décrit dans le paragraphe précédent. Ce qui rend les générateurs si compacts, c’est que les méthodes __iter__() et __next__() sont créées automatiquement.

Une autre fonctionnalité clé est que les variables locales ainsi que le contexte d’exécution sont sauvegardés automatiquement entre les appels. Cela simplifie d’autant plus l’écriture de ces fonctions et rend leur code beaucoup plus lisible qu’avec une approche utilisant des variables d’instance telles que self.index et self.data.

En plus de la création automatique de méthodes et de la sauvegarde du contexte d’exécution, les générateurs lèvent automatiquement une exception StopIteration lorsqu’ils terminent leur exécution. La combinaison de ces fonctionnalités rend très simple la création d’itérateurs, sans plus d’effort que l’écriture d’une fonction classique.

9.10. Expressions et générateurs

Des générateurs simples peuvent être codés très rapidement avec des expressions utilisant la même syntaxe que les compréhensions de listes, mais en utilisant des parenthèses à la place des crochets. Ces expressions sont conçues pour des situations où le générateur est utilisé tout de suite dans une fonction. Ces expressions sont plus compactes mais moins souples que des définitions complètes de générateurs et ont tendance à être plus économes en mémoire que leur équivalent en compréhension de listes.

Exemples :

>>> sum(i*i for i in range(10))                 # sum of squares
285

>>> xvec = [10, 20, 30]
>>> yvec = [7, 5, 3]
>>> sum(x*y for x,y in zip(xvec, yvec))         # dot product
260

>>> from math import pi, sin
>>> sine_table = {x: sin(x*pi/180) for x in range(0, 91)}

>>> unique_words = set(word  for line in page  for word in line.split())

>>> valedictorian = max((student.gpa, student.name) for student in graduates)

>>> data = 'golf'
>>> list(data[i] for i in range(len(data)-1, -1, -1))
['f', 'l', 'o', 'g']

Notes de bas de page

1

Il existe une exception : les modules disposent d’un attribut secret en lecture seule appelé __dict__ qui renvoie le dictionnaire utilisé pour implémenter l’espace de nommage du module ; le nom __dict__ est un attribut mais pas un nom global. Évidemment, si vous l’utilisez, vous brisez l’abstraction de l’implémentation des espaces de nommage. Il est donc réservé à des choses comme les débogueurs post-mortem.

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10. Survol de la bibliothèque standard

10.1. Interface avec le système d’exploitation

Le module os propose des dizaines de fonctions pour interagir avec le système d’exploitation :

>>> import os
>>> os.getcwd()      # Return the current working directory
'C:\\Python36'
>>> os.chdir('/server/accesslogs')   # Change current working directory
>>> os.system('mkdir today')   # Run the command mkdir in the system shell
0

Veillez bien à utiliser import os plutôt que from os import *, sinon os.open() cache la primitive open() qui fonctionne différemment.

Les primitives dir() et help() sont des aides utiles lorsque vous travaillez en mode interactif avez des gros modules comme os :

>>> import os
>>> dir(os)
<returns a list of all module functions>
>>> help(os)
<returns an extensive manual page created from the module's docstrings>

Pour la gestion des fichiers et dossiers, le module shutil expose une interface plus abstraite et plus facile à utiliser :

>>> import shutil
>>> shutil.copyfile('data.db', 'archive.db')
'archive.db'
>>> shutil.move('/build/executables', 'installdir')
'installdir'

10.2. Jokers sur les noms de fichiers

Le module glob fournit une fonction pour construire des listes de fichiers à partir de motifs :

>>> import glob
>>> glob.glob('*.py')
['primes.py', 'random.py', 'quote.py']

10.3. Paramètres passés en ligne de commande

Typiquement, les outils en ligne de commande ont besoin de lire les paramètres qui leur sont donnés. Ces paramètres sont stockés dans la variable argv du module sys sous la forme d’une liste. Par exemple, l’affichage suivant vient de l’exécution de python demo.py one two three depuis la ligne de commande :

>>> import sys
>>> print(sys.argv)
['demo.py', 'one', 'two', 'three']

Le module getopt analyse sys.argv en utilisant les conventions habituelles de la fonction Unix getopt(). Des outils d’analyse des paramètres de la ligne de commande plus flexibles et avancés sont disponibles dans le module argparse.

10.4. Redirection de la sortie d’erreur et fin d’exécution

Le module sys a aussi des attributs pour stdin, stdout et stderr. Ce dernier est utile pour émettre des messages d’avertissement ou d’erreur qui restent visibles même si stdout est redirigé :

>>> sys.stderr.write('Warning, log file not found starting a new one\n')
Warning, log file not found starting a new one

Le moyen le plus direct de terminer un script est d’utiliser sys.exit().

10.5. Recherche de motifs dans les chaînes

Le module re fournit des outils basés sur les expressions rationnelles permettant des opérations complexes sur les chaînes. C’est une solution optimisée, utilisant une syntaxe concise, pour rechercher des motifs complexes ou effectuer des remplacements complexes dans les chaînes :

>>> import re
>>> re.findall(r'\bf[a-z]*', 'which foot or hand fell fastest')
['foot', 'fell', 'fastest']
>>> re.sub(r'(\b[a-z]+) \1', r'\1', 'cat in the the hat')
'cat in the hat'

Lorsque les opérations sont simples, il est préférable d’utiliser les méthodes des chaînes. Elles sont plus lisibles et plus faciles à déboguer :

>>> 'tea for too'.replace('too', 'two')
'tea for two'

10.6. Mathématiques

Le module math donne accès aux fonctions sur les nombres à virgule flottante (float en anglais) de la bibliothèque C :

>>> import math
>>> math.cos(math.pi / 4)
0.70710678118654757
>>> math.log(1024, 2)
10.0

Le module random offre des outils pour faire des tirages aléatoires :

>>> import random
>>> random.choice(['apple', 'pear', 'banana'])
'apple'
>>> random.sample(range(100), 10)   # sampling without replacement
[30, 83, 16, 4, 8, 81, 41, 50, 18, 33]
>>> random.random()    # random float
0.17970987693706186
>>> random.randrange(6)    # random integer chosen from range(6)
4

Le module statistics permet de calculer des valeurs statistiques basiques (moyenne, médiane, variance…) :

>>> import statistics
>>> data = [2.75, 1.75, 1.25, 0.25, 0.5, 1.25, 3.5]
>>> statistics.mean(data)
1.6071428571428572
>>> statistics.median(data)
1.25
>>> statistics.variance(data)
1.3720238095238095

Le projet SciPy <https://scipy.org> contient beaucoup d’autres modules dédiés aux calculs numériques.

10.7. Accès à internet

Il existe beaucoup de modules permettant d’accéder à internet et gérer les protocoles réseaux. Les deux plus simples sont urllib.request qui permet de récupérer des données à partir d’une URL et smtplib pour envoyer des courriers électroniques :

>>> from urllib.request import urlopen
>>> with urlopen('http://tycho.usno.navy.mil/cgi-bin/timer.pl') as response:
...     for line in response:
...         line = line.decode('utf-8')  # Decoding the binary data to text.
...         if 'EST' in line or 'EDT' in line:  # look for Eastern Time
...             print(line)

<BR>Nov. 25, 09:43:32 PM EST

>>> import smtplib
>>> server = smtplib.SMTP('localhost')
>>> server.sendmail('soothsayer@example.org', 'jcaesar@example.org',
... """To: jcaesar@example.org
... From: soothsayer@example.org
...
... Beware the Ides of March.
... """)
>>> server.quit()

(Notez que le deuxième exemple a besoin d’un serveur mail tournant localement.)

10.8. Dates et heures

Le module datetime propose des classes pour manipuler les dates et les heures de manière simple ou plus complexe. Bien que faire des calculs de dates et d’heures soit possible, la priorité de l’implémentation est mise sur l’extraction efficace des attributs pour le formatage et la manipulation. Le module gère aussi les objets dépendant des fuseaux horaires

>>> # dates are easily constructed and formatted
>>> from datetime import date
>>> now = date.today()
>>> now
datetime.date(2003, 12, 2)
>>> now.strftime("%m-%d-%y. %d %b %Y is a %A on the %d day of %B.")
'12-02-03. 02 Dec 2003 is a Tuesday on the 02 day of December.'

>>> # dates support calendar arithmetic
>>> birthday = date(1964, 7, 31)
>>> age = now - birthday
>>> age.days
14368

10.9. Compression de données

Les formats d’archivage et de compression les plus communs sont directement gérés par les modules zlib, gzip, bz2, lzma, zipfile et tarfile

>>> import zlib
>>> s = b'witch which has which witches wrist watch'
>>> len(s)
41
>>> t = zlib.compress(s)
>>> len(t)
37
>>> zlib.decompress(t)
b'witch which has which witches wrist watch'
>>> zlib.crc32(s)
226805979

10.10. Mesure des performances

Certains utilisateurs de Python sont très intéressés par les performances de différentes approches d’un même problème. Python propose un outil de mesure répondant simplement à ces questions.

Par exemple, pour échanger deux variables, il peut être tentant d’utiliser l’empaquetage et le dépaquetage de tuples plutôt que la méthode traditionnelle. Le module timeit montre rapidement le léger gain de performance obtenu :

>>> from timeit import Timer
>>> Timer('t=a; a=b; b=t', 'a=1; b=2').timeit()
0.57535828626024577
>>> Timer('a,b = b,a', 'a=1; b=2').timeit()
0.54962537085770791

En opposition à timeit et sa granularité fine, profile et pstats fournissent des outils permettant d’identifier les parties les plus gourmandes en temps d’exécution dans des volumes de code plus grands.

10.11. Contrôle qualité

Une approche possible pour développer des applications de très bonne qualité est d’écrire des tests pour chaque fonction au fur et à mesure de son développement, puis d’exécuter ces tests fréquemment lors du processus de développement.

Le module doctest cherche des tests dans les chaînes de documentation. Un test ressemble à un simple copier-coller d’un appel et son résultat depuis le mode interactif. Cela améliore la documentation en fournissant des exemples tout en prouvant qu’ils sont justes :

def average(values):
    """Computes the arithmetic mean of a list of numbers.

    >>> print(average([20, 30, 70]))
    40.0
    """
    return sum(values) / len(values)

import doctest
doctest.testmod()   # automatically validate the embedded tests

Le module unittest requiert plus d’efforts que le module doctest mais il permet de construire un jeu de tests plus complet que l’on fait évoluer dans un fichier séparé :

import unittest

class TestStatisticalFunctions(unittest.TestCase):

    def test_average(self):
        self.assertEqual(average([20, 30, 70]), 40.0)
        self.assertEqual(round(average([1, 5, 7]), 1), 4.3)
        with self.assertRaises(ZeroDivisionError):
            average([])
        with self.assertRaises(TypeError):
            average(20, 30, 70)

unittest.main()  # Calling from the command line invokes all tests

10.12. Piles fournies

Python adopte le principe des « piles fournies ». Vous pouvez le constater au travers des fonctionnalités évoluées et solides fournies par ses plus gros paquets. Par exemple :

Les modules xmlrpc.client et xmlrpc.server permettent d’appeler des fonctions à distance quasiment sans effort. En dépit du nom des modules, aucune connaissance du XML n’est nécessaire.

Le paquet email est une bibliothèque pour gérer les messages électroniques, incluant les MIME et autres encodages basés sur la RFC 2822 [https://tools.ietf.org/html/rfc2822.html]. Contrairement à smtplib et poplib qui envoient et reçoivent des messages, le paquet email est une boite à outils pour construire, lire des structures de messages complexes (comprenant des pièces jointes) ou implémenter des encodages et protocoles.

Le paquet json permet de lire et d’écrire du JSON, format d’encodage de données répandu. Le module csv gère la lecture et l’écriture de données stockées sous forme de valeurs séparées par des virgules dans des fichiers (Comma-Separated Values en anglais), format typiquement interopérable avec les bases de données et les feuilles de calculs. Pour la lecture du XML, utilisez les paquets xml.etree.ElementTree, xml.dom et xml.sax. Combinés, ces modules et paquets simplifient grandement l’échange de données entre les applications Python et les autres outils.

Le module sqlite3 est une abstraction de la bibliothèque SQLite, permettant de manipuler une base de données persistante, accédée et manipulée en utilisant une syntaxe SQL quasi standard.

L’internationalisation est possible grâce à de nombreux paquets tels que gettext, locale ou codecs.

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11. Survol de la bibliothèque standard – Deuxième partie

Cette deuxième partie aborde des modules plus à destination des programmeurs professionnels. Ces modules sont rarement nécessaires dans de petits scripts.

11.1. Formatage de l’affichage

Le module reprlib est une variante de la fonction repr(), spécialisé dans l’affichage concis de conteneurs volumineux ou fortement imbriqués :

>>> import reprlib
>>> reprlib.repr(set('supercalifragilisticexpialidocious'))
"{'a', 'c', 'd', 'e', 'f', 'g', ...}"

Le module pprint propose un contrôle plus fin de l’affichage des objets, aussi bien natifs que ceux définis par l’utilisateur, de manière à être lisible par l’interpréteur. Lorsque le résultat fait plus d’une ligne, il est séparé sur plusieurs lignes et est indenté pour rendre la structure plus visible :

>>> import pprint
>>> t = [[[['black', 'cyan'], 'white', ['green', 'red']], [['magenta',
...     'yellow'], 'blue']]]
...
>>> pprint.pprint(t, width=30)
[[[['black', 'cyan'],
   'white',
   ['green', 'red']],
  [['magenta', 'yellow'],
   'blue']]]

Le module textwrap formate des paragraphes de texte pour tenir sur un écran d’une largeur donnée :

>>> import textwrap
>>> doc = """The wrap() method is just like fill() except that it returns
... a list of strings instead of one big string with newlines to separate
... the wrapped lines."""
...
>>> print(textwrap.fill(doc, width=40))
The wrap() method is just like fill()
except that it returns a list of strings
instead of one big string with newlines
to separate the wrapped lines.

Le module locale utilise une base de données des formats spécifiques à chaque région pour les dates, nombres, etc. L’attribut grouping de la fonction de formatage permet de formater directement des nombres avec un séparateur :

>>> import locale
>>> locale.setlocale(locale.LC_ALL, 'English_United States.1252')
'English_United States.1252'
>>> conv = locale.localeconv()          # get a mapping of conventions
>>> x = 1234567.8
>>> locale.format("%d", x, grouping=True)
'1,234,567'
>>> locale.format_string("%s%.*f", (conv['currency_symbol'],
...                      conv['frac_digits'], x), grouping=True)
'$1,234,567.80'

11.2. Gabarits (templates en anglais)

Le module string contient une classe polyvalente : Template. Elle permet d’écrire des gabarits (templates en anglais) avec une syntaxe simple, dans le but d’être utilisable par des non-développeurs. Ainsi, vos utilisateurs peuvent personnaliser leur application sans la modifier.

Le format utilise des marqueurs formés d’un $ suivi d’un identifiant Python valide (caractères alphanumériques et tirets-bas). Entourer le marqueur d’accolades permet de lui coller d’autres caractères alphanumériques sans intercaler une espace. Écrire $$ produit un simple $ :

>>> from string import Template
>>> t = Template('${village}folk send $$10 to $cause.')
>>> t.substitute(village='Nottingham', cause='the ditch fund')
'Nottinghamfolk send $10 to the ditch fund.'

La méthode substitute() lève une exception KeyError lorsqu’un marqueur n’a pas été fourni, ni dans un dictionnaire, ni sous forme d’un paramètre nommé. Dans certains cas, lorsque la donnée à appliquer peut n’être fournie que partiellement par l’utilisateur, la méthode safe_substitute() est plus appropriée car elle laisse tels quels les marqueurs manquants :

>>> t = Template('Return the $item to $owner.')
>>> d = dict(item='unladen swallow')
>>> t.substitute(d)
Traceback (most recent call last):
  ...
KeyError: 'owner'
>>> t.safe_substitute(d)
'Return the unladen swallow to $owner.'

Les classes filles de Template peuvent définir leur propre délimiteur. Typiquement, un script de renommage de photos par lots peut choisir le symbole pourcent comme marqueur pour les champs tels que la date actuelle, le numéro de l’image ou son format :

>>> import time, os.path
>>> photofiles = ['img_1074.jpg', 'img_1076.jpg', 'img_1077.jpg']
>>> class BatchRename(Template):
...     delimiter = '%'
>>> fmt = input('Enter rename style (%d-date %n-seqnum %f-format):  ')
Enter rename style (%d-date %n-seqnum %f-format):  Ashley_%n%f

>>> t = BatchRename(fmt)
>>> date = time.strftime('%d%b%y')
>>> for i, filename in enumerate(photofiles):
...     base, ext = os.path.splitext(filename)
...     newname = t.substitute(d=date, n=i, f=ext)
...     print('{0} --> {1}'.format(filename, newname))

img_1074.jpg --> Ashley_0.jpg
img_1076.jpg --> Ashley_1.jpg
img_1077.jpg --> Ashley_2.jpg

Une autre utilisation des gabarits consiste à séparer la logique métier des détails spécifiques à chaque format de sortie. Il est ainsi possible de générer des gabarits spécifiques pour les fichiers XML, texte, HTML…

11.3. Traitement des données binaires

Le module struct expose les fonctions pack() et unpack() permettant de travailler avec des données binaires. L’exemple suivant montre comment parcourir un entête de fichier ZIP sans recourir au module zipfile. Les marqueurs "H" et "I" représentent des nombres entiers non signés, stockés respectivement sur deux et quatre octets. Le "<" indique qu’ils ont une taille standard et utilisent la convention petit-boutiste :

import struct

with open('myfile.zip', 'rb') as f:
    data = f.read()

start = 0
for i in range(3):                      # show the first 3 file headers
    start += 14
    fields = struct.unpack('<IIIHH', data[start:start+16])
    crc32, comp_size, uncomp_size, filenamesize, extra_size = fields

    start += 16
    filename = data[start:start+filenamesize]
    start += filenamesize
    extra = data[start:start+extra_size]
    print(filename, hex(crc32), comp_size, uncomp_size)

    start += extra_size + comp_size     # skip to the next header

11.4. Fils d’exécution

Des tâches indépendantes peuvent être exécutées de manière non séquentielle en utilisant des fils d’exécution (threading en anglais). Les fils d’exécution peuvent être utilisés pour améliorer la réactivité d’une application qui interagit avec l’utilisateur pendant que d’autres traitements sont exécutés en arrière-plan. Une autre utilisation typique est de séparer sur deux fils d’exécution distincts les entrées / sorties et le calcul.

Le code suivant donne un exemple d’utilisation du module threading exécutant des tâches en arrière-plan pendant que le programme principal continue de s’exécuter :

import threading, zipfile

class AsyncZip(threading.Thread):
    def __init__(self, infile, outfile):
        threading.Thread.__init__(self)
        self.infile = infile
        self.outfile = outfile

    def run(self):
        f = zipfile.ZipFile(self.outfile, 'w', zipfile.ZIP_DEFLATED)
        f.write(self.infile)
        f.close()
        print('Finished background zip of:', self.infile)

background = AsyncZip('mydata.txt', 'myarchive.zip')
background.start()
print('The main program continues to run in foreground.')

background.join()    # Wait for the background task to finish
print('Main program waited until background was done.')

Le principal défi des applications avec plusieurs fils d’exécution consiste à coordonner ces fils qui partagent des données ou des ressources. Pour ce faire, le module threading expose quelques outils dédiés à la synchronisation comme les verrous (locks en anglais), les événements (events en anglais), les variables conditionnelles (condition variables en anglais) et les sémaphores (semaphore en anglais).

Bien que ces outils soient puissants, de petites erreurs de conception peuvent engendrer des problèmes difficiles à reproduire. Donc, l’approche classique pour coordonner des tâches est de restreindre l’accès d’une ressource à un seul fil d’exécution et d’utiliser le module queue pour alimenter ce fil d’exécution en requêtes venant d’autres fils d’exécution. Les applications utilisant des Queue pour leurs communication et coordination entre fils d’exécution sont plus simples à concevoir, plus lisibles et plus fiables.

11.5. Journalisation

Le module logging est un système de journalisation complet. Dans son utilisation la plus élémentaire, les messages sont simplement envoyés dans un fichier ou sur sys.stderr :

import logging
logging.debug('Debugging information')
logging.info('Informational message')
logging.warning('Warning:config file %s not found', 'server.conf')
logging.error('Error occurred')
logging.critical('Critical error -- shutting down')

Cela produit l’affichage suivant :

WARNING:root:Warning:config file server.conf not found
ERROR:root:Error occurred
CRITICAL:root:Critical error -- shutting down

Par défaut, les messages d’information et de débogage sont ignorés, les autres sont envoyés vers la sortie standard. Il est aussi possible d’envoyer les messages par courriel, datagrammes, en utilisant des connecteurs réseau ou vers un serveur HTTP. Des nouveaux filtres permettent d’utiliser des sorties différentes en fonction de la priorité du message : DEBUG, INFO, WARNING, ERROR et CRITICAL.

La configuration de la journalisation peut être effectuée directement dans le code Python ou peut être chargée depuis un fichier de configuration, permettant de personnaliser la journalisation sans modifier l’application.

11.6. Références faibles

Python gère lui-même la mémoire (par comptage des références pour la plupart des objets et en utilisant un ramasse-miettes (garbage collector en anglais) pour éliminer les cycles). La mémoire est libérée rapidement lorsque sa dernière référence est supprimée.

Cette approche fonctionne bien pour la majorité des applications mais, parfois, il est nécessaire de surveiller un objet seulement durant son utilisation par quelque chose d’autre. Malheureusement, le simple fait de le suivre crée une référence qui rend l’objet permanent. Le module weakref expose des outils pour suivre les objets sans pour autant créer une référence. Lorsqu’un objet n’est pas utilisé, il est automatiquement supprimé du tableau des références faibles et une fonction de rappel (callback en anglais) est appelée. Un exemple typique est le cache d’objets coûteux à créer :

>>> import weakref, gc
>>> class A:
...     def __init__(self, value):
...         self.value = value
...     def __repr__(self):
...         return str(self.value)
...
>>> a = A(10)                   # create a reference
>>> d = weakref.WeakValueDictionary()
>>> d['primary'] = a            # does not create a reference
>>> d['primary']                # fetch the object if it is still alive
10
>>> del a                       # remove the one reference
>>> gc.collect()                # run garbage collection right away
0
>>> d['primary']                # entry was automatically removed
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
    d['primary']                # entry was automatically removed
  File "C:/python36/lib/weakref.py", line 46, in __getitem__
    o = self.data[key]()
KeyError: 'primary'

11.7. Outils pour les listes

Beaucoup de structures de données peuvent être représentées avec les listes natives. Cependant, d’autres besoins peuvent émerger pour des structures ayant des caractéristiques différentes, typiquement en termes de performance.

Le module array fournit un objet array() ne permettant de stocker que des listes homogènes mais d’une manière plus compacte. L’exemple suivant montre une liste de nombres stockés chacun sur deux octets non signés (marqueur "H") plutôt que d’utiliser 16 octets comme l’aurait fait une liste classique :

>>> from array import array
>>> a = array('H', [4000, 10, 700, 22222])
>>> sum(a)
26932
>>> a[1:3]
array('H', [10, 700])

Le module collections fournit la classe deque(). Elle ressemble à une liste mais est plus rapide pour l’insertion ou l’extraction des éléments par la gauche et plus lente pour accéder aux éléments du milieu. Ces objets sont particulièrement adaptés pour construire des queues ou des algorithmes de parcours d’arbres en largeur (ou BFS, pour Breadth First Search en anglais) :

>>> from collections import deque
>>> d = deque(["task1", "task2", "task3"])
>>> d.append("task4")
>>> print("Handling", d.popleft())
Handling task1

unsearched = deque([starting_node])
def breadth_first_search(unsearched):
    node = unsearched.popleft()
    for m in gen_moves(node):
        if is_goal(m):
            return m
        unsearched.append(m)

En plus de fournir des implémentations de listes alternatives, la bibliothèque fournit des outils tels que bisect, un module contenant des fonctions de manipulation de listes triées :

>>> import bisect
>>> scores = [(100, 'perl'), (200, 'tcl'), (400, 'lua'), (500, 'python')]
>>> bisect.insort(scores, (300, 'ruby'))
>>> scores
[(100, 'perl'), (200, 'tcl'), (300, 'ruby'), (400, 'lua'), (500, 'python')]

Le module heapq permet d’implémenter des tas (heap en anglais) à partir de simples listes. La valeur la plus faible est toujours à la première position (indice 0). C’est utile dans les cas où l’application accède souvent à l’élément le plus petit mais sans vouloir classer entièrement la liste :

>>> from heapq import heapify, heappop, heappush
>>> data = [1, 3, 5, 7, 9, 2, 4, 6, 8, 0]
>>> heapify(data)                      # rearrange the list into heap order
>>> heappush(data, -5)                 # add a new entry
>>> [heappop(data) for i in range(3)]  # fetch the three smallest entries
[-5, 0, 1]

11.8. Arithmétique décimale à virgule flottante

Le module decimal exporte la classe Decimal : elle est spécialisée dans le calcul de nombres décimaux représentés en virgule flottante. Par rapport à la classe native float, elle est particulièrement utile pour :

les applications traitant de finance et autres utilisations nécessitant une représentation décimale exacte,

le contrôle de la précision,

le contrôle sur les arrondis pour répondre à des obligations légales ou réglementaires,

suivre les décimales significatives, ou

les applications pour lesquelles l’utilisateur attend des résultats identiques aux calculs faits à la main.

Par exemple, calculer 5 % de taxe sur une facture de 70 centimes donne un résultat différent en nombre à virgule flottante binaire et décimale. La différence devient significative lorsqu’on arrondit le résultat au centime près :

>>> from decimal import *
>>> round(Decimal('0.70') * Decimal('1.05'), 2)
Decimal('0.74')
>>> round(.70 * 1.05, 2)
0.73

Le résultat d’un calcul donné par Decimal conserve les zéros non-significatifs. La classe conserve automatiquement quatre décimales significatives pour des opérandes à deux décimales significatives. La classe Decimal imite les mathématiques telles qu’elles pourraient être effectuées à la main, évitant les problèmes typiques de l’arithmétique binaire à virgule flottante qui n’est pas capable de représenter exactement certaines quantités décimales.

La représentation exacte de la classe Decimal lui permet de faire des calculs de modulo ou des tests d’égalité qui ne seraient pas possibles avec une représentation à virgule flottante binaire :

>>> Decimal('1.00') % Decimal('.10')
Decimal('0.00')
>>> 1.00 % 0.10
0.09999999999999995

>>> sum([Decimal('0.1')]*10) == Decimal('1.0')
True
>>> sum([0.1]*10) == 1.0
False

Le module decimal permet de faire des calculs avec autant de précision que nécessaire :

>>> getcontext().prec = 36
>>> Decimal(1) / Decimal(7)
Decimal('0.142857142857142857142857142857142857')

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12. Environnements virtuels et paquets

12.1. Introduction

Les programmes Python utilisent souvent des paquets et modules qui ne font pas partie de la bibliothèque standard. Ils nécessitent aussi, parfois, une version spécifique d’une bibliothèque, par exemple parce qu’un certain bug a été corrigé ou encore que le programme a été implémenté en utilisant une version obsolète de l’interface de cette bibliothèque.

Cela signifie qu’il n’est pas toujours possible, pour une installation unique de Python, de couvrir tous les besoins de toutes les applications. Basiquement, si une application A dépend de la version 1.0 d’un module et qu’une application B dépend de la version 2.0, ces dépendances entrent en conflit et installer la version 1.0 ou 2.0 laisse une des deux applications incapable de fonctionner.

La solution est de créer un environnement virtuel, un dossier auto-suffisant qui contient une installation de Python pour une version particulière de Python ainsi que des paquets additionnels.

Différentes applications peuvent alors utiliser des environnements virtuels différents. Pour résoudre l’exemple précédent où il existe un conflit de dépendances, l’application A a son environnement virtuel avec la version 1.0 installée pendant que l’application B a un autre environnement virtuel avec la version 2.0. Si l’application B requiert que la bibliothèque soit mise à jour à la version 3.0, cela n’affecte pas l’environnement de A.

12.2. Création d’environnements virtuels

Le module utilisé pour créer et gérer des environnements virtuels s’appelle venv. venv installe en général la version de Python la plus récente dont vous disposez. Si plusieurs versions de Python sont sur votre système, vous pouvez choisir une version particulière en exécutant python3.X où X indique la version de votre choix.

Pour créer un environnement virtuel, décidez d’un dossier où vous voulez le placer et exécutez le module venv comme un script avec le chemin du dossier :

python3 -m venv tutorial-env

Cela crée le dossier tutorial-env (s’il n’existe pas) et des sous-dossiers contenant une copie de l’interpréteur Python, de la bibliothèque standard et quelques autres fichiers utiles.

Une fois l’environnement virtuel créé, vous pouvez l’activer.

Sur Windows, lancez :

tutorial-env\Scripts\activate.bat

Sur Unix et MacOS, lancez :

source tutorial-env/bin/activate

(Ce script est écrit pour le shell bash. Si vous utilisez csh ou fish, utilisez les variantes activate.csh ou activate.fish.)

Activer l’environnement virtuel change le prompt de votre ligne de commande pour afficher le nom de l’environnement virtuel que vous utilisez. Cela modifie aussi l’environnement afin, lorsque vous tapez python, d’exécuter la version spécifique de Python installée dans l’environnement. Par exemple :

$ source ~/envs/tutorial-env/bin/activate
(tutorial-env) $ python
Python 3.5.1 (default, May  6 2016, 10:59:36)
  ...
>>> import sys
>>> sys.path
['', '/usr/local/lib/python35.zip', ...,
'~/envs/tutorial-env/lib/python3.5/site-packages']
>>>

12.3. Gestion des paquets avec pip

Vous pouvez installer, mettre à jour et supprimer des paquets en utilisant un programme appelé pip. Par défaut, pip installe les paquets du Python Package Index, <https://pypi.org>. Vous pouvez parcourir le Python Package Index avec un navigateur ou utiliser la fonction de recherche (assez) limitée de pip :

(tutorial-env) $ pip search astronomy
skyfield               - Elegant astronomy for Python
gary                   - Galactic astronomy and gravitational dynamics.
novas                  - The United States Naval Observatory NOVAS astronomy library
astroobs               - Provides astronomy ephemeris to plan telescope observations
PyAstronomy            - A collection of astronomy related tools for Python.
...

pip a plusieurs sous-commandes : search, install, uninstall, freeze, etc. Consultez le guide Installation de modules Python pour une documentation exhaustive sur pip.

Vous pouvez installer la dernière version d’un paquet en indiquant son nom :

(tutorial-env) $ pip install novas
Collecting novas
  Downloading novas-3.1.1.3.tar.gz (136kB)
Installing collected packages: novas
  Running setup.py install for novas
Successfully installed novas-3.1.1.3

Vous pouvez installer une version spécifique d’un paquet en donnant le nom du paquet suivi de == et du numéro de version souhaitée :

(tutorial-env) $ pip install requests==2.6.0
Collecting requests==2.6.0
  Using cached requests-2.6.0-py2.py3-none-any.whl
Installing collected packages: requests
Successfully installed requests-2.6.0

Si vous relancez cette commande, pip remarque que la version demandée est déjà installée et ne fait rien. Vous pouvez fournir un numéro de version différent pour récupérer cette version ou lancer pip install --upgrade pour mettre à jour le paquet à la dernière version :

(tutorial-env) $ pip install --upgrade requests
Collecting requests
Installing collected packages: requests
  Found existing installation: requests 2.6.0
    Uninstalling requests-2.6.0:
      Successfully uninstalled requests-2.6.0
Successfully installed requests-2.7.0

pip uninstall suivi d’un ou plusieurs noms de paquets les supprime de votre environnement virtuel.

pip show affiche des informations à propos d’un paquet précis :

(tutorial-env) $ pip show requests
---
Metadata-Version: 2.0
Name: requests
Version: 2.7.0
Summary: Python HTTP for Humans.
Home-page: http://python-requests.org
Author: Kenneth Reitz
Author-email: me@kennethreitz.com
License: Apache 2.0
Location: /Users/akuchling/envs/tutorial-env/lib/python3.4/site-packages
Requires:

pip list liste tous les paquets installés dans l’environnement virtuel :

(tutorial-env) $ pip list
novas (3.1.1.3)
numpy (1.9.2)
pip (7.0.3)
requests (2.7.0)
setuptools (16.0)

pip freeze produit une liste similaire des paquets installés mais l’affichage adopte un format que pip install peut lire. La convention habituelle est de mettre cette liste dans un fichier requirements.txt :

(tutorial-env) $ pip freeze > requirements.txt
(tutorial-env) $ cat requirements.txt
novas==3.1.1.3
numpy==1.9.2
requests==2.7.0

Le fichier requirements.txt peut alors être ajouté dans un système de gestion de versions comme faisant partie de votre application. Les utilisateurs peuvent alors installer tous les paquets nécessaires à l’application avec install -r :

(tutorial-env) $ pip install -r requirements.txt
Collecting novas==3.1.1.3 (from -r requirements.txt (line 1))
  ...
Collecting numpy==1.9.2 (from -r requirements.txt (line 2))
  ...
Collecting requests==2.7.0 (from -r requirements.txt (line 3))
  ...
Installing collected packages: novas, numpy, requests
  Running setup.py install for novas
Successfully installed novas-3.1.1.3 numpy-1.9.2 requests-2.7.0

pip reconnait beaucoup d’autres options, documentées dans le guide Installation de modules Python. Lorsque vous avez écrit un paquet, si vous voulez le rendre disponible sur PyPI, lisez le guide Distribuer des modules Python.

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13. Pour aller plus loin

La lecture de ce tutoriel a probablement renforcé votre intérêt pour Python et vous devez être impatient de l’utiliser pour résoudre des vrais problèmes. Où aller pour en apprendre plus ?

Ce tutoriel fait partie de la documentation de Python, et la documentation de Python est vaste :

La bibliothèque standard :

Nous vous conseillons de naviguer dans le manuel, c’est une référence complète (quoique laconique) sur les types, fonctions et modules de la bibliothèque standard. La distribution standard de Python inclut énormément de code supplémentaire. Il existe des modules pour lire les courriels, récupérer des documents via HTTP, générer des nombres aléatoires, analyser les paramètres de la ligne de commande, écrire des programmes CGI, compresser des données et beaucoup d’autres fonctions. Une balade dans la documentation de la bibliothèque vous donnera une idée de ce qui est disponible.

Installation de modules Python explique comment installer des paquets écrits par d’autres utilisateurs de Python.

La référence du langage Python contient une explication détaillée de la syntaxe et sémantique de Python. C’est une lecture fastidieuse, mais elle a sa place dans une documentation exhaustive.

D’autres ressources :

https://www.python.org est le site principal pour Python. Il contient du code, de la documentation, des liens vers d’autres sites traitant de Python partout sur Internet. Il est répliqué dans différents endroits autour du globe, comme en Europe, au Japon et en Australie. Ces répliques peuvent dans certains cas être plus rapides que le site principal, en fonction de l’endroit où vous vous trouvez.

https://docs.python.org/fr/ offre un accès rapide à la documentation de Python en français.

https://pypi.org (The Python Package Index en anglais, pour le « répertoire des paquets Python ») : auparavant surnommé « La Fromagerie » (The Cheese Shop en anglais), c’est un catalogue de modules Python disponibles au téléchargement, construit par les utilisateurs. Lorsque vous commencez à distribuer du code, vous pouvez l’inscrire ici afin que les autres puissent le trouver.

https://code.activestate.com/recipes/langs/python/ : « The Python Cookbook » est un recueil assez imposant d’exemples de code, de modules et de scripts. Les contributions les plus remarquables y sont regroupées dans le livre « Python Cookbook » (O’Reilly & Associates, ISBN 0-596-00797-3).

http://www.pyvideo.org regroupe des liens vers des vidéos relatives à Python, enregistrées lors de conférences ou de réunions de groupes d’utilisateurs.

https://scipy.org : le projet « The Scientific Python » contient des modules pour manipuler et calculer rapidement sur des tableaux. Le projet héberge aussi divers paquets sur l’algèbre linéaire, les transformées de Fourier, des résolveurs non-linéaires, différentes distributions de nombres aléatoires, l’analyse statistique et d’autres choses du domaine scientifique.

Pour poser des questions ou remonter des problèmes liés à Python, vous pouvez écrire sur le forum comp.lang.python ou les envoyer à la liste de diffusion <python-list@python.org>. Le forum et la liste de diffusion sont liées, un message publié sur l’un sera automatiquement transféré sur l’autre. Des centaines de messages y sont publiés chaque jour, posant (ou répondant à) des questions, suggérant de nouvelles fonctionnalités et annonçant des nouveaux modules. Les archives sont disponibles à https://mail.python.org/pipermail/.

Avant de publier un message, assurez-vous d’avoir lu la liste de la Foire Aux Questions (aussi appelée FAQ). La FAQ répond à beaucoup de questions fréquentes et contient probablement une solution à votre problème.

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14. Édition interactive des entrées et substitution d’historique

Certaines versions de l’interpréteur Python prennent en charge l’édition de la ligne d’entrée courante et la substitution d’historique, similaires aux facilités que l’on trouve dans le shell Korn et dans le shell GNU Bash. Ces implémentations utilisent la bibliothèque GNU Readline [https://tiswww.case.edu/php/chet/readline/rltop.html], qui gère plusieurs styles d’édition. La bibliothèque a sa propre documentation, nous ne la dupliquons pas ici.

14.1. Complétion automatique et édition de l’historique

La complétion de noms de variables et de modules est automatiquement activée au démarrage de l’interpréteur. Ainsi, la touche Tab invoque la fonction de complétion ; la recherche s’effectue dans les noms d’instructions Python, les noms des variables locales et les noms de modules disponibles. Pour les expressions pointées telles que string.a, l’expression est évaluée jusqu’au dernier '.' avant de suggérer les options disponibles à partir des attributs de l’objet résultant de cette évaluation. Notez bien que ceci peut exécuter une partie du code de l’application si un objet disposant d’une méthode __getattr__() fait partie de l’expression. La configuration par défaut sauvegarde l’historique dans un fichier nommé .python_history dans votre dossier d’utilisateur. L’historique est ainsi conservé entre les sessions interactives successives.

14.2. Alternatives à l’interpréteur interactif

Cette facilité constitue un énorme pas en avant comparé aux versions précédentes de l’interpréteur. Toutefois, il reste des fonctions à implémenter comme l’indentation correcte sur les lignes de continuation (l’analyseur sait si une indentation doit suivre) ; le mécanisme de complétion devrait utiliser la table de symboles de l’interpréteur. Une commande pour vérifier (ou même suggérer) les correspondances de parenthèses, de guillemets, etc., serait également utile.

Une alternative améliorée de l’interpréteur interactif est développée depuis maintenant quelques temps : IPython [https://ipython.org/]. Il fournit la complétion, l’exploration d’objets et une gestion avancée de l’historique. Il peut également être personnalisé en profondeur et embarqué dans d’autres applications. Un autre environnement interactif amélioré similaire est bpython [http://www.bpython-interpreter.org/].

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15. Arithmétique en nombres à virgule flottante : problèmes et limites

Les nombres à virgule flottante sont représentés, au niveau matériel, en fractions de nombres binaires (base 2). Par exemple, la fraction décimale

0.125

a la valeur 1/10 + 2/100 + 5/1000 et, de la même manière, la fraction binaire

0.001

a la valeur 0/2 + 0/4 + 1/8. Ces deux fractions ont une valeur identique, la seule différence est que la première est une fraction décimale, la seconde est une fraction binaire.

Malheureusement, la plupart des fractions décimales ne peuvent pas avoir de représentation exacte en fractions binaires. Par conséquent, en général, les nombres à virgule flottante que vous donnez sont seulement approximés en fractions binaires pour être stockés dans la machine.

Le problème est plus simple à aborder en base 10. Prenons par exemple, la fraction 1/3. Vous pouvez l’approximer en une fraction décimale :

0.3

ou, mieux,

0.33

ou, mieux,

0.333

etc. Peu importe le nombre de décimales que vous écrivez, le résultat ne vaut jamais exactement 1/3, mais c’est une estimation s’en approchant toujours mieux.

De la même manière, peu importe combien de décimales en base 2 vous utilisez, la valeur décimale 0.1 ne peut pas être représentée exactement en fraction binaire. En base 2, 1/10 est le nombre périodique suivant

0.0001100110011001100110011001100110011001100110011...

En se limitant à une quantité finie de bits, on ne peut obtenir qu’une approximation. Sur la majorité des machines aujourd’hui, les nombres à virgule flottante sont approximés par une fraction binaire avec les 53 premiers bits comme numérateur et une puissance de deux au dénominateur. Dans le cas de 1/10, la fraction binaire est 3602879701896397 / 2 ** 55 qui est proche mais ne vaut pas exactement 1/10.

Du fait de la manière dont les flottants sont affichés par l’interpréteur, il est facile d’oublier que la valeur stockée est une approximation de la fraction décimale d’origine. Python n’affiche qu’une approximation décimale de la valeur stockée en binaire. Si Python devait afficher la vraie valeur décimale de l’approximation binaire stockée pour 0,1, il afficherait

>>> 0.1
0.1000000000000000055511151231257827021181583404541015625

C’est bien plus de décimales que ce qu’attendent la plupart des utilisateurs, donc Python affiche une valeur arrondie afin d’améliorer la lisibilité

>>> 1 / 10
0.1

Rappelez-vous simplement que, bien que la valeur affichée ressemble à la valeur exacte de 1/10, la valeur stockée est la représentation la plus proche en fraction binaire.

Il existe beaucoup de nombres décimaux qui partagent une même approximation en fraction binaire. Par exemple, 0.1, 0.10000000000000001 et 0.1000000000000000055511151231257827021181583404541015625 ont tous pour approximation 3602879701896397 / 2 ** 55. Puisque toutes ces valeurs décimales partagent la même approximation, chacune peut être affichée tout en respectant eval(repr(x)) == x.

Historiquement, le mode interactif de Python et la primitive repr() choisissaient la version avec 17 décimales significatives, 0.10000000000000001. Python, depuis la version 3.1 (sur la majorité des systèmes) est maintenant capable de choisir la plus courte représentation et n’affiche que 0.1.

Ce comportement est inhérent à la nature même de la représentation des nombres à virgule flottante dans la machine : ce n’est pas un bogue dans Python et ce n’est pas non plus un bogue dans votre code. Vous pouvez observer le même type de comportement dans tous les autres langages utilisant le support matériel pour le calcul des nombres à virgule flottante (bien que certains langages ne rendent pas visible la différence par défaut, ou pas dans tous les modes d’affichage).

Pour obtenir un affichage plus plaisant, les fonctions de formatage de chaînes de caractères peuvent limiter le nombre de décimales significatives affichées :

>>> format(math.pi, '.12g')  # give 12 significant digits
'3.14159265359'

>>> format(math.pi, '.2f')   # give 2 digits after the point
'3.14'

>>> repr(math.pi)
'3.141592653589793'

Il est important de comprendre que tout cela n’est, au sens propre, qu’une illusion : vous demandez simplement à Python d’arrondir la valeur stockée réellement dans la machine à l’affichage.

Une autre conséquence du fait que 0,1 n’est pas exactement stocké 1/10 est que la somme de trois valeurs de 0,1 ne donne pas 0,3 non plus :

>>> .1 + .1 + .1 == .3
False

Aussi, puisque 0,1 ne peut pas être stocké avec une représentation plus proche de sa valeur exacte 1/10, comme 0,3 qui ne peut pas être plus proche de sa valeur exacte 3/10, arrondir au préalable avec la fonction round() n’aide en rien :

>>> round(.1, 1) + round(.1, 1) + round(.1, 1) == round(.3, 1)
False

Bien que les nombres ne peuvent se rapprocher plus de la valeur qu’on attend qu’ils aient, la fonction round() peut être utile à postériori pour arrondir deux valeurs inexactes et pouvoir les comparer :

>>> round(.1 + .1 + .1, 10) == round(.3, 10)
True

L’arithmétique des nombres binaires à virgule flottante réserve beaucoup de surprises de ce genre. Le problème avec « 0.1 » est expliqué en détails ci-dessous, dans la section « Erreurs de représentation ». Voir The Perils of Floating Point [http://www.lahey.com/float.htm] pour une liste plus complète de ce genre de surprises.

Même s’il est vrai qu’il n’existe pas de réponse simple, ce n’est pas la peine de vous méfier outre mesure des nombres à virgule flottante ! Les erreurs, en Python, dans les opérations de nombres à virgule flottante sont dues au matériel sous-jacent et, sur la plupart des machines, sont de l’ordre de 1 sur 2**53 par opération. C’est plus que suffisant pour la plupart des tâches, mais vous devez garder à l’esprit que ce ne sont pas des opérations décimales et que chaque opération sur des nombres à virgule flottante peut souffrir d’une nouvelle erreur.

Bien que des cas pathologiques existent, pour la plupart des cas d’utilisations courants vous obtiendrez le résultat attendu à la fin en arrondissant simplement au nombre de décimales désirées à l’affichage avec str(). Pour un contrôle fin sur la manière dont les décimales sont affichées, consultez dans Syntaxe de formatage de chaîne les spécifications de formatage de la méthode str.format().

Pour les cas requérant une représentation décimale exacte, le module decimal peut être utile : il implémente l’arithmétique décimale et peut donc être un choix adapté pour des applications nécessitant une grande précision.

Une autre forme d’arithmétique exacte est implémentée dans le module fractions qui se base sur les nombres rationnels (donc 1/3 peut y être représenté exactement).

Si vous êtes un utilisateur intensif des opérations sur les nombres à virgule flottante, nous vous conseillons de considérer le paquet Numerical Python ainsi que les paquets pour les opérations statistiques et mathématiques fournis par le projet SciPy. Consultez <https://scipy.org>.

Python fournit des outils qui peuvent être utiles dans les rares occasions où vous voulez réellement connaître la valeur exacte d’un nombre à virgule flottante. La méthode float.as_integer_ratio() donne la valeur du nombre sous forme de fraction :

>>> x = 3.14159
>>> x.as_integer_ratio()
(3537115888337719, 1125899906842624)

Puisque le ratio est exact, il peut être utilisé pour recréer la valeur originale sans perte :

>>> x == 3537115888337719 / 1125899906842624
True

La méthode float.hex() donne le nombre en hexadécimal (base 16), donnant ici aussi la valeur exacte stockée par la machine :

>>> x.hex()
'0x1.921f9f01b866ep+1'

Cette représentation hexadécimale petit être utilisée pour reconstruire, sans approximation, le float :

>>> x == float.fromhex('0x1.921f9f01b866ep+1')
True

Puisque cette représentation est exacte, elle est pratique pour échanger des valeurs entre différentes versions de Python (indépendamment de la machine) ou d’autres langages qui comprennent ce format (tels que Java et C99).

Une autre fonction utile est math.fsum(), elle aide à diminuer les pertes de précision lors des additions. Elle surveille les décimales perdues au fur et à mesure que les valeurs sont ajoutées au total. Cela peut faire une différence au niveau de la précision globale en empêchant les erreurs de s’accumuler jusqu’à affecter le résultat final :

>>> sum([0.1] * 10) == 1.0
False
>>> math.fsum([0.1] * 10) == 1.0
True

15.1. Erreurs de représentation

Cette section explique en détail l’exemple du « 0.1 » et montre comment vous pouvez effectuer une analyse exacte de ce type de cas par vous-même. Nous supposons que la représentation binaire des nombres flottants vous est familière.

Le terme Erreur de représentation (representation error en anglais) signifie que la plupart des fractions décimales ne peuvent être représentées exactement en binaire. C’est la principale raison pour laquelle Python (ou Perl, C, C++, Java, Fortran et beaucoup d’autres) n’affiche habituellement pas le résultat exact en décimal.

Pourquoi ? 1/10 n’est pas représentable de manière exacte en fraction binaire. Cependant, toutes les machines d’aujourd’hui (novembre 2000) suivent la norme IEEE-754 en ce qui concerne l’arithmétique des nombres à virgule flottante et la plupart des plateformes utilisent un « IEEE-754 double précision » pour représenter les floats de Python. Les « IEEE-754 double précision » utilisent 53 bits de précision donc, à la lecture, l’ordinateur essaie de convertir 0,1 dans la fraction la plus proche possible de la forme J/2**N avec J un nombre entier d’exactement 53 bits. Pour réécrire

1 / 10 ~= J / (2**N)

en

J ~= 2**N / 10

en se rappelant que J fait exactement 53 bits (donc >= 2**52 mais < 2**53), la meilleure valeur possible pour N est 56 :

>>> 2**52 <=  2**56 // 10  < 2**53
True

Donc 56 est la seule valeur possible pour N qui laisse exactement 53 bits pour J. La meilleure valeur possible pour J est donc ce quotient, arrondi :

>>> q, r = divmod(2**56, 10)
>>> r
6

Puisque la retenue est plus grande que la moitié de 10, la meilleure approximation est obtenue en arrondissant par le haut :

>>> q+1
7205759403792794

Par conséquent la meilleure approximation possible pour 1/10 en « IEEE-754 double précision » est celle au-dessus de 2**56, soit :

7205759403792794 / 2 ** 56

Diviser le numérateur et le dénominateur par deux réduit la fraction à :

3602879701896397 / 2 ** 55

Notez que puisque l’arrondi a été fait vers le haut, le résultat est en réalité légèrement plus grand que 1/10 ; si nous n’avions pas arrondi par le haut, le quotient aurait été légèrement plus petit que 1/10. Mais dans aucun cas il ne vaut exactement 1/10 !

Donc l’ordinateur ne « voit » jamais 1/10 : ce qu’il voit est la fraction exacte donnée ci-dessus, la meilleure approximation utilisant les nombres à virgule flottante double précision de l”« IEEE-754 » :

>>> 0.1 * 2 ** 55
3602879701896397.0

Si nous multiplions cette fraction par 10**30, nous pouvons observer les valeurs de ses 55 décimales de poids fort :

>>> 3602879701896397 * 10 ** 55 // 2 ** 55
1000000000000000055511151231257827021181583404541015625

La valeur stockée dans l’ordinateur est donc égale à 0,1000000000000000055511151231257827021181583404541015625. Au lieu d’afficher toutes les décimales, beaucoup de langages (dont les vieilles versions de Python) arrondissent le résultat à la 17e décimale significative :

>>> format(0.1, '.17f')
'0.10000000000000001'

Les modules fractions et decimal rendent simples ces calculs :

>>> from decimal import Decimal
>>> from fractions import Fraction

>>> Fraction.from_float(0.1)
Fraction(3602879701896397, 36028797018963968)

>>> (0.1).as_integer_ratio()
(3602879701896397, 36028797018963968)

>>> Decimal.from_float(0.1)
Decimal('0.1000000000000000055511151231257827021181583404541015625')

>>> format(Decimal.from_float(0.1), '.17')
'0.10000000000000001'

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16. Annexe

16.1. Mode interactif

16.1.1. Gestion des erreurs

Quand une erreur se produit, l’interpréteur affiche un message d’erreur et la trace d’appels. En mode interactif, il revient à l’invite de commande primaire ; si l’entrée provient d’un fichier, l’interpréteur se termine avec un code de sortie non nul après avoir affiché la trace d’appels (les exceptions gérées par une clause except dans une instruction try ne sont pas considérées comme des erreurs dans ce contexte). Certaines erreurs sont inconditionnellement fatales et provoquent la fin du programme avec un code de sortie non nul ; les incohérences internes et, dans certains cas, les pénuries de mémoire sont traitées de la sorte. Tous les messages d’erreur sont écrits sur le flux d’erreur standard ; l’affichage normal des commandes exécutées est écrit sur la sortie standard.

Taper le caractère d’interruption (généralement Ctrl+C ou Supprimer) au niveau de l’invite de commande primaire annule l’entrée et revient à l’invite 1. Saisir une interruption tandis qu’une commande s’exécute lève une exception KeyboardInterrupt qui peut être gérée par une instruction try.

16.1.2. Scripts Python exécutables

Sur les systèmes Unix, un script Python peut être rendu directement exécutable, comme un script shell, en ajoutant la ligne

#!/usr/bin/env python3.5

(en supposant que l’interpréteur est dans le PATH de l’utilisateur) au début du script et en rendant le fichier exécutable. '#!' doivent être les deux premiers caractères du fichier. Sur certaines plateformes, cette première ligne doit finir avec une fin de ligne de type Unix ('\n') et pas de type Windows ('\r\n'). Notez que le caractère croisillon, '#', est utilisé pour initier un commentaire en Python.

Un script peut être rendu exécutable en utilisant la commande chmod.

$ chmod +x myscript.py

Sur les systèmes Windows il n’y a pas de « mode exécutable ». L’installateur Python associe automatiquement les fichiers en .py avec python.exe de telle sorte qu’un double clic sur un fichier Python le lance comme un script. L’extension peut aussi être .pyw. Dans ce cas, la console n’apparait pas.

16.1.3. Configuration du mode interactif

En mode interactif, il peut être pratique de faire exécuter quelques commandes au lancement de l’interpréteur. Configurez la variable d’environnement PYTHONSTARTUP avec le nom d’un fichier contenant les instructions à exécuter, à la même manière du .profile pour un shell Unix.

Ce fichier n’est lu qu’en mode interactif, pas quand Python lit les instructions depuis un fichier, ni quand /dev/tty est donné explicitement comme fichier source (pour tout le reste, Python se comporte alors comme dans une session interactive). Les instructions de ce fichier sont exécutées dans le même espace de nommage que vos commandes, donc les objets définis et modules importés peuvent être utilisés directement dans la session interactive. Dans ce fichier, il est aussi possible de changer les invites de commande sys.ps1 et sys.ps2.

Si vous voulez exécuter d’autres fichiers du dossier courant au démarrage, vous pouvez le programmer dans le fichier de démarrage global, par exemple avec le code suivant : if os.path.isfile('.pythonrc.py'): exec(open('.pythonrc.py').read()). Et si vous voulez exécuter le fichier de démarrage depuis un script, vous devez le faire explicitement dans le script :

import os
filename = os.environ.get('PYTHONSTARTUP')
if filename and os.path.isfile(filename):
    with open(filename) as fobj:
        startup_file = fobj.read()
    exec(startup_file)

16.1.4. Modules de personnalisation

Python peut être personnalisé via les modules sitecustomize et usercustomize. Pour découvrir comment ils fonctionnent, vous devez d’abord trouver l’emplacement de votre dossier « site-packages » utilisateur. Démarrez Python et exécutez ce code :

>>> import site
>>> site.getusersitepackages()
'/home/user/.local/lib/python3.5/site-packages'

Vous pouvez maintenant y créer un fichier usercustomize.py et y écrire ce que vous voulez. Il est toujours pris en compte par Python, peu importe le mode, sauf lorsque vous démarrez avec l’option -s qui désactive l’importation automatique.

sitecustomize fonctionne de la même manière mais est généralement créé par un administrateur et stocké dans le dossier site-packages global. Il est importé avant usercustomize. Pour plus de détails, consultez la documentation de site.

Notes

1

Un problème avec GNU Readline peut l’en empêcher.

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Installation et utilisation de Python

Cette partie de la documentation est consacrée aux informations générales au sujet de l’installation de l’environnement Python sur différentes plateformes, l’invocation de l’interpréteur et des choses qui facilitent le travail avec Python.

1. Ligne de commande et environnement

1.1. Ligne de commande

1.1.1. Options de l’interface

1.1.2. Options génériques

1.1.3. Options diverses

1.1.4. Options à ne pas utiliser

1.2. Variables d’environnement

1.2.1. Variables en mode débogage

2. Utilisation de Python sur les plateformes Unix

2.1. Récupérer et installer la dernière version de Python

2.1.1. Sur Linux

2.1.2. Sur FreeBSD et OpenBSD

2.1.3. Sur OpenSolaris

2.2. Compiler Python

2.3. Fichiers et chemins liés à Python

2.4. Divers

2.5. Éditeurs et IDEs

3. Utilisation de Python sur Windows

3.1. Installer Python

3.1.1. Versions supportées

3.1.2. Étapes d’installation

3.1.3. Suppression de la limitation MAX_PATH

3.1.4. Installation sans l’interface utilisateur

3.1.5. Installation sans téléchargement

3.1.6. Modification d’une installation

3.1.7. Autres plateformes

3.2. Paquets alternatifs

3.3. Configurer Python

3.3.1. Digression : Définition des variables d’environnement

3.3.2. Trouver l’exécutable Python

3.4. Lanceur Python pour Windows

3.4.1. Pour commencer

3.4.1.1. Depuis la ligne de commande

3.4.1.2. Environnements virtuels

3.4.1.3. À partir d’un script

3.4.1.4. À partir d’associations de fichiers

3.4.2. Lignes Shebang

3.4.3. Arguments dans les lignes shebang

3.4.4. Personnalisation

3.4.4.1. Personnalisation via des fichiers INI

3.4.4.2. Personnalisation des versions Python par défaut

3.4.5. Diagnostics

3.5. Recherche de modules

3.6. Modules supplémentaires

3.6.1. PyWin32

3.6.2. cx_Freeze

3.6.3. WConio

3.7. Compiler Python sous Windows

3.8. Embedded Distribution

3.8.1. Application Python

3.8.2. Embarquer Python

3.9. Autres ressources

4. Utilisation de Python sur un Macintosh

4.1. Obtenir et installer MacPython

4.1.1. Comment exécuter un script Python

4.1.2. Lancer des scripts avec une interface graphique

4.1.3. Configuration

4.2. L”IDE

4.3. Installation de paquets Python additionnels

4.4. Programmation d’interface graphique sur le Mac

4.5. Distribuer des Applications Python sur le Mac

4.6. Autres ressources

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1. Ligne de commande et environnement

L’interpréteur CPython analyse la ligne de commande et l’environnement à la recherche de différents paramètres.

CPython implementation detail: Le format des lignes de commande utilisé par d’autres implémentations peut s’avérer différent. Voir Autres implémentations pour plus d’informations.

1.1. Ligne de commande

Quand vous invoquez Python, vous pouvez spécifier n’importe laquelle de ces options :

python [-bBdEhiIOqsSuvVWx?] [-c command | -m module-name | script | - ] [args]

Le cas d’utilisation le plus courant est, bien entendu, la simple invocation d’un script :

python myscript.py

1.1.1. Options de l’interface

L’interface de l’interpréteur ressemble à celle du shell UNIX mais fournit quelques méthodes d’invocation supplémentaires :

Quand l’interpréteur est appelé avec l’entrée standard connectée à un périphérique tty, il lit les lignes de commande et les exécute jusqu’à ce qu’un caractère EOF (caractère fin de fichier, que vous pouvez produire avec Ctrl-D sous UNIX ou Ctrl-Z, Enter sous Windows) soit lu.

Quand l’interpréteur est appelé avec un argument correspondant à un nom de fichier ou avec un fichier comme entrée standard, il lit et exécute le script contenu dans ce fichier.

Quand l’interpréteur est appelé avec un argument correspondant à un répertoire, il lit et exécute un script d’un certain nom dans ce répertoire.

Quand l’interpréteur est appelé avec l’option -c commande, il exécute la ou les instructions Python données comme commande. Ici commande peut contenir plusieurs instructions séparées par des fins de ligne. Les blancs en début de ligne ne sont pas ignorés dans les instructions Python !

Quand l’interpréteur est appelé avec l’option -m nom-de-module, le module donné est recherché dans le chemin des modules Python et est exécuté en tant que script.

En mode non-interactif, toute l’entrée est analysée avant d’être exécutée.

Une option d’interface termine la liste des options consommées par l’interpréteur ; tous les arguments atterrissent dans sys.argv — notez que le premier élément, à l’indice zéro (sys.argv|0]), est une chaîne de caractères indiquant la source du programme.

-c <command>

Exécute le code Python dans command. command peut être une ou plusieurs instructions, séparées par des fins de ligne, dont les espaces en début de ligne sont significatives, comme dans le code d’un module.

Si cette option est donnée, le premier élément de sys.argv est "-c" et le répertoire courant est ajouté au début de sys.path (permettant aux modules de ce répertoire d’être importés comme des modules de premier niveau).

-m <module-name>

Parcourt sys.path à la recherche du module donné et exécute son contenu en tant que module __main__.

L’argument étant un nom de module, vous ne devez pas fournir d’extension de fichier (.py). Le nom du module doit être un nom de module Python valide, absolu, mais l’implémentation peut ne pas l’imposer (par exemple, l’utilisation d’un trait d’union peut être autorisée).

Les noms de paquets sont aussi autorisés (ainsi que les paquets-espace de nommage, namespace packages en anglais). Quand un nom de paquet est donné à la place d’un simple module, l’interpréteur exécute <pkg>.__main__ comme module principal. Ce comportement est délibérément identique au traitement d’un dossier ou d’un fichier zip donné en argument à l’interpréteur comme script.

Note

Cette option ne peut pas être utilisée avec les modules natifs et les modules d’extension écrits en C, étant donné qu’ils ne possèdent pas de fichiers modules en Python. Cependant, elle peut toujours être utilisée pour les modules pré-compilés, même si le fichier source original n’est pas disponible.

Si cette option est donnée, le premier élément de sys.argv est le chemin complet d’accès au fichier du module (pendant que le fichier est recherché, le premier élément est mis à "-m"). Comme avec l’option -c, le dossier courant est ajouté au début de sys.path.

De nombreux modules de la bibliothèque standard contiennent du code qui est invoqué quand ils sont exécutés comme scripts. Un exemple est le module timeit :

python -mtimeit -s 'setup here' 'benchmarked code here'
python -mtimeit -h # for details

Voir aussi

runpy.run_module()

Fonctionnalité équivalente directement disponible en code Python

PEP 338 [https://www.python.org/dev/peps/pep-0338] – Exécuter des modules en tant que scripts

Modifié dans la version 3.1: Fournir le nom d’un paquet pour exécuter un sous-module __main__.

Modifié dans la version 3.4: les paquets-espaces de nommage sont aussi gérés

-

Lit les commandes depuis l’entrée standard (sys.stdin). Si l’entrée standard est un terminal, l’option -i est activée implicitement.

Si cette option est donnée, le premier élément de sys.argv est "-" et le dossier courant est ajouté au début de sys.path.

<script>

Exécute le code Python contenu dans script, qui doit être un chemin d’accès (absolu ou relatif) à un fichier, faisant référence à un fichier Python, à un répertoire contenant un fichier __main__.py ou à un fichier zip contenant un fichier __main__.py.

Si cette option est donnée, le premier élément de sys.argv est le nom du script tel que donné sur la ligne de commande.

Si le nom du script se réfère directement à un fichier Python, le répertoire contenant ce fichier est ajouté au début de sys.path et le fichier est exécuté en tant que module __main__.

Si le nom du script fait référence à un dossier ou à un fichier zip, le nom du script est ajouté au début de sys.path et le fichier __main__.py à cet endroit est exécuté en tant que module __main__.

Voir aussi

runpy.run_path()

Fonctionnalité équivalente directement disponible en code Python

Si aucune option d’interface n’est donnée, l’option -i est activée implicitement, sys.argv[0] est une chaine vide ("") et le dossier courant est ajouté au début de sys.path. Aussi, la complétion par tabulation et l’édition de l’historique sont automatiquement activés, s’ils sont disponibles sur votre système (voir Readline configuration).

Voir aussi

Lancement de l’interpréteur

Modifié dans la version 3.4: Activation automatique de la complétion par tabulation et édition de l’historique.

1.1.2. Options génériques

-?

-h

--help

Affiche une brève description de toutes les options de la ligne de commande.

-V

--version

Affiche la version de Python et termine. Par exemple :

Python 3.6.0b2+

Lorsque l’option est doublée, affiche davantage d’informations sur la manière dont Python a été compilé, comme :

Python 3.6.0b2+ (3.6:84a3c5003510+, Oct 26 2016, 02:33:55)
[GCC 6.2.0 20161005]

Nouveau dans la version 3.6: L’option -VV.

1.1.3. Options diverses

-b

Affiche un avertissement (warning en anglais) lors d’une comparaison d’un objet de type bytes ou bytearray avec un objet de type str ou un objet de type bytes avec un objet de type int. Lève une erreur si cette option est doublée (-bb).

Modifié dans la version 3.5: Concerne les comparaisons de bytes avec int.

-B

S’il est donné, Python ne tente pas d’écrire de fichier .pyc ou .pyo à l’importation des modules sources. Voir aussi PYTHONDONTWRITEBYTECODE.

-d

Active la sortie de l’analyseur en mode débogage (pour les experts uniquement, en fonction des options de compilation). Voir aussi PYTHONDEBUG.

-E

Ignore toutes les variables d’environnement PYTHON* qui pourraient être définies. Par exemple, PYTHONPATH et PYTHONHOME.

-i

Quand un script est passé comme premier argument ou que l’option -c est utilisée, entre en mode interactif après avoir exécuté le script ou la commande, même lorsque sys.stdin ne semble pas être un terminal. Le fichier PYTHONSTARTUP n’est pas lu.

Cela peut être utile pour examiner les variables globales ou une trace de la pile lorsque le script lève une exception. Voir aussi PYTHONINSPECT.

-I

Lance Python en mode isolé. Cela implique aussi -E et -s. En mode isolé, sys.path ne contient ni le répertoire du script ni le répertoire site-packages de l’utilisateur. Toutes les variables d’environnement PYTHON* sont aussi ignorées. Davantage de restrictions peuvent être imposées pour éviter que l’utilisateur n’injecte du code malicieux.

Nouveau dans la version 3.4.

-O

Enlève les instructions assert et tout le code qui dépend de la valeur de __debug__. Ajoute .opt-1 au nom de fichier du code intermédiaire (bytecode), avant l’extension .pyc (voir la PEP 488 [https://www.python.org/dev/peps/pep-0488]). Voir aussi PYTHONOPTIMIZE.

Modifié dans la version 3.5: Modifie les noms de fichiers .pyc suivant la PEP 488 [https://www.python.org/dev/peps/pep-0488].

-OO

Agit comme -O et ignore aussi les docstrings. Ajoute .opt-2 au nom de fichier du code intermédiaire (bytecode), avant l’extension .pyc (voir la PEP 488 [https://www.python.org/dev/peps/pep-0488]).

Modifié dans la version 3.5: Modifie les noms de fichiers .pyc suivant la PEP 488 [https://www.python.org/dev/peps/pep-0488].

-q

N’affiche pas le copyright et la version, même en mode interactif.

Nouveau dans la version 3.2.

-R

Conservé pour compatibilité ascendante. Sur Python 3.3 ou supérieur, la randomisation des empreintes (hash en anglais) est activée par défaut.

Sur les versions précédentes de Python, cette option activait la randomisation des empreintes de manière à ce que les __hash__() de chaînes, bytes et datetime soient « salés » avec une valeur aléatoire non prévisible. Bien que ce sel soit constant durant le déroulement d’un processus Python, il n’est pas prévisible pour des invocations répétées de code Python.

L’imprévisibilité des empreintes a pour objectif de se protéger contre les dénis de service qui utiliseraient des valeurs d’entrée judicieusement choisies afin de forcer la construction des dictionnaires dans le pire cas, c’est-à-dire avec une complexité en O(n²). Voir http://www.ocert.org/advisories/ocert-2011-003.html pour obtenir les détails.

PYTHONHASHSEED vous permet de définir vous-même la valeur du sel pour l’algorithme de calcul des empreintes.

Nouveau dans la version 3.2.3.

-s

N’ajoute pas le répertoire utilisateur site-packages à sys.path.

Voir aussi

PEP 370 [https://www.python.org/dev/peps/pep-0370] – Répertoire site-packages propre à l’utilisateur

-S

Désactive l’importation du module site et les modifications locales de sys.path qu’il implique. Désactive aussi ces manipulations si site est importé explicitement plus tard (appelez site.main() si vous voulez les déclencher).

-u

Désactive les mémoires tampons de la couche binaire des flux de la sortie standard (stdout) et de la sortie d’erreurs (stderr) (ils restent accessibles via leur attribut buffer). La couche d’entrée-sortie est mise en tampon ligne par ligne lors de l’écriture sur la console, ou par blocs si elle est redirigée sur un fichier non-interactif.

Voir aussi PYTHONUNBUFFERED.

-v

Affiche un message chaque fois qu’un module est initialisé, montrant l’emplacement (nom du fichier ou module natif) à partir duquel il est chargé. Lorsque l’option est doublée (-vv), affiche un message pour chaque fichier vérifié lors de la recherche du module. Fournit aussi des informations sur le nettoyage des modules à la fin. Voir aussi PYTHONVERBOSE.

-W arg

Contrôle des avertissements. Le mécanisme d’avertissement de Python, par défaut, affiche les messages d’avertissement sur sys.stderr. Un message d’avertissement type est de la forme suivante :

file:line: category: message

Par défaut, chaque avertissement est affiché une seule fois pour chaque ligne de source où il se trouve. Cette option définit à quelle fréquence afficher ces avertissements.

L’option -W peut être répétée ; lorsqu’un avertissement correspond à plus d’une option, l’action associée à la dernière correspondance est effectuée. Les options -W invalides sont ignorées (cependant, un message d’avertissement est affiché sur les options invalides au moment où le premier avertissement est généré).

Les avertissements peuvent aussi être contrôlés dans le programme Python en utilisant le module warnings.

La forme la plus simple de l’argument est l’une des chaînes d’actions suivantes (ou une abréviation unique) :

ignore

Ignore tous les avertissements.

default

Demande explicitement le comportement par défaut (affiche chaque avertissement une fois par ligne de code source).

all

Affiche un avertissement à chaque fois qu’il se produit (ce qui peut générer beaucoup de messages si l’avertissement est déclenché à plusieurs reprises, comme à l’intérieur d’une boucle).

module

Affiche chaque avertissement uniquement la première fois qu’il apparaît dans chaque module.

once

Affiche chaque avertissement uniquement la première fois qu’il apparaît dans le programme.

error

Déclenche une exception au lieu d’afficher un message d’avertissement.

La forme complète de l’argument est :

action:message:category:module:line

Ici, action est tel qu’expliqué ci-dessus, mais s’applique uniquement aux messages qui correspondent aux champs restants. Les champs vides correspondent à toutes les valeurs ; les champs vides de fin peuvent être omis. Le champ message correspond au début du message d’avertissement affiché, cette expression est insensible à la casse. Le champ category correspond à la catégorie d’avertissement. Ce nom doit être un nom complet de classe ; La règle s’applique à tous les messages d’alertes construits avec une classe qui hérite de celle spécifiée. Le nom de la classe complète doit être donnée. Le champ module correspond au nom (pleinement qualifié) du module, cette correspondance est sensible à la casse. Le champ line correspond au numéro de ligne, où zéro correspond à n’importe quel numéro de ligne et correspond donc à l’option par défaut.

Voir aussi

warnings – le module qui gère les avertissements.

PEP 230 [https://www.python.org/dev/peps/pep-0230] – Gestion des alertes

PYTHONWARNINGS

-x

Saute la première ligne du code source, autorisant ainsi les directives de type #!cmd non conformes au standard Unix. L’objectif est de proposer une astuce spécifique pour le DOS.

-X

Réservée pour les options spécifiques aux différentes implémentations. CPython reconnaît actuellement les valeurs suivantes :

-X faulthandler pour activer faulthandler ;

-X showrefcount pour afficher le compteur des références et le nombre de blocs mémoire utilisés lorsque le programme se termine ou après chaque entrée de l’interpréteur interactif. Ceci ne fonctionne que sur les versions compilées en mode débogage.

-X tracemalloc pour lancer le suivi des allocations mémoire par Python en utilisant le module tracemalloc. Par défaut, seul l’appel (la frame en anglais) le plus récent est stocké dans la trace de la pile d’appels. Utilisez -X tracemalloc=NFRAME pour lancer le suivi avec une limite des traces à NFRAME appels. Voir tracemalloc.start() pour plus d’informations.

-X showalloccount pour afficher à la fin de l’exécution du programme le total des objets alloués pour chaque type. Ceci ne fonctionne que si Python a été compilé avec l’option COUNT_ALLOCS.

Il est aussi possible de passer des valeurs arbitraires et de les récupérer par le dictionnaire sys._xoptions.

Modifié dans la version 3.2: L’option -X a été ajoutée.

Nouveau dans la version 3.3: L’option -X faulthandler.

Nouveau dans la version 3.4: Les options -X showrefcount et -X tracemalloc .

Nouveau dans la version 3.6: L’option -X showalloccount.

1.1.4. Options à ne pas utiliser

-J

Utilisation réservée à Jython [http://www.jython.org/].

1.2. Variables d’environnement

Les variables d’environnement suivantes modifient le comportement de Python. Elles sont analysées avant les options de la ligne de commande, autres que -E ou -I. Il est d’usage que les options de la ligne de commande prennent le pas sur les variables d’environnement en cas de conflit.

PYTHONHOME

Modifie l’emplacement des bibliothèques standards de Python. Par défaut, les bibliothèques sont recherchées dans préfixe/lib/pythonversion et préfixe_exec/lib/pythonversion où préfixe et préfixe_exec sont des répertoires qui dépendent de l’installation (leur valeur par défaut étant /usr/local).

Quand PYTHONHOME est défini à un simple répertoire, sa valeur remplace à la fois préfixe et préfixe_exec. Pour spécifier des valeurs différentes à ces variables, définissez PYTHONHOME à préfixe:préfixe_exec.

PYTHONPATH

Augmente le chemin de recherche par défaut des fichiers de modules. Le format est le même que pour PATH du shell : un ou plusieurs chemins de répertoires séparés par os.pathsep (par exemple, le caractère deux-points sous Unix et point-virgule sous Windows). Les répertoires qui n’existent pas sont ignorés silencieusement.

En plus des répertoires normaux, des entrées individuelles de PYTHONPATH peuvent faire référence à des fichiers zip contenant des modules en pur Python (soit sous forme de code source, soit sous forme compilée). Les modules d’extensions ne peuvent pas être importés à partir de fichiers zip.

Le chemin de recherche par défaut dépend de l’installation mais commence généralement par préfixe/lib/pythonversion (voir PYTHONHOME ci-dessus). Il est toujours ajouté à PYTHONPATH.

Comme indiqué ci-dessus dans Options de l’interface, un répertoire supplémentaire est inséré dans le chemin de recherche devant PYTHONPATH. Le chemin de recherche peut être manipulé depuis un programme Python avec la variable sys.path.

PYTHONSTARTUP

S’il s’agit d’un nom de fichier accessible en lecture, les commandes Python de ce fichier sont exécutées avant que la première invite ne soit affichée en mode interactif. Le fichier est exécuté dans le même espace de nommage que les commandes interactives, de manière à ce que les objets définis ou importés puissent être utilisés sans qualificatif dans la session interactive. Vous pouvez aussi changer les invites sys.ps1 et sys.ps2 ainsi que le point d’entrée (hook en anglais) sys.__interactivehook__ dans ce fichier.

PYTHONOPTIMIZE

Si elle est définie à une chaîne non vide, c’est équivalent à spécifier l’option -O. Si elle est définie à un entier, c’est équivalent à spécifier l’option -O plusieurs fois.

PYTHONDEBUG

Si elle est définie à une chaîne non vide, c’est équivalent à spécifier l’option -d. Si elle est définie à un entier, c’est équivalent à spécifier l’option -d plusieurs fois.

PYTHONINSPECT

Si elle est définie à une chaîne non vide, c’est équivalent à spécifier l’option -i.

Cette variable peut aussi être modifiée par du code Python en utilisant os.environ pour forcer le mode introspectif à la fin du programme.

PYTHONUNBUFFERED

Si elle est définie à une chaîne non vide, c’est équivalent à spécifier l’option -u.

PYTHONVERBOSE

Si elle est définie à une chaîne non vide, c’est équivalent à spécifier l’option -v. Si elle est définie à un entier, c’est équivalent à spécifier l’option -v plusieurs fois.

PYTHONCASEOK

Si elle est définie, Python ignore la casse dans les instructions import. Ceci ne fonctionne que sous Windows et OS X.

PYTHONDONTWRITEBYTECODE

Si elle est définie et n’est pas une chaîne vide, Python n’écrit pas de fichier .pyc à l’importation des modules sources. C’est équivalent à spécifier l’option -B.

PYTHONHASHSEED

Si cette variable n’est pas définie ou définie à random, une valeur aléatoire est utilisée pour saler les empreintes des objets chaines, bytes et datetime.

Si PYTHONHASHSEED est définie à une valeur entière, elle est utilisée comme valeur de salage pour générer les empreintes des types utilisant l’imprévisibilité du hachage.

L’objectif est d’avoir des empreintes reproductibles, pour des tests de l’interpréteur lui-même ou pour qu’un groupe de processus Python puisse partager des empreintes.

Le nombre entier doit être écrit en base 10 et être compris entre 0 et 4 294 967 295. Spécifier la valeur 0 désactive l’imprévisibilité des empreintes.

Nouveau dans la version 3.2.3.

PYTHONIOENCODING

Si la variable est définie sous la forme nom_encodage:gestionnaire_erreur avant le lancement de l’interpréteur, cela prend le pas sur l’encodage utilisé pour l’entrée standard, la sortie standard ou la sortie d’erreur. nom_encodage et :gestionnaire_erreur sont facultatifs tous les deux et possèdent la même signification que dans str.encode().

Pour la sortie d’erreur, la partie :gestionnaire_erreur est ignorée : le gestionnaire est toujours 'backslashreplace'.

Modifié dans la version 3.4: La partie nom_encodage est maintenant optionnelle.

Modifié dans la version 3.6: Sous Windows, l’encodage spécifié par cette variable est ignoré pour le tampon des consoles interactives à moins que PYTHONLEGACYWINDOWSSTDIO ne soit aussi spécifié. Les fichiers et tubes (pipes en anglais) redirigés vers les flux standards ne sont pas concernés.

PYTHONNOUSERSITE

Si elle est définie, Python n’ajoute pas le répertoire site-packages propre à l'utilisateur à sys.path.

Voir aussi

PEP 370 [https://www.python.org/dev/peps/pep-0370] – Répertoire site-packages propre à l’utilisateur

PYTHONUSERBASE

Définit le répertoire base utilisateur. Celui-ci est utilisé pour déterminer le chemin du répertoire site-packages propre à l'utilisateur et des schémas d’installation de Distutils pour python setup.py install --user.

Voir aussi

PEP 370 [https://www.python.org/dev/peps/pep-0370] – Répertoire site-packages propre à l’utilisateur

PYTHONEXECUTABLE

Si cette variable d’environnement est définie, sys.argv[0] est définie à cette valeur au lieu de la valeur fournie par l’exécutable. Ne fonctionne que sur Mac OS X.

PYTHONWARNINGS

C’est équivalent à spécifier l’option -W. Si la valeur est une chaîne séparée par des virgules, c’est équivalent à spécifier l’option -W plusieurs fois.

PYTHONFAULTHANDLER

Si elle est définie à une chaîne non vide, faulthandler.enable() est appelée au démarrage : ceci installe un gestionnaire pour les signaux SIGSEGV, SIGFPE, SIGABRT, SIGBUS et SIGILL afin de générer une trace de la pile d’appels. C’est équivalent à spécifier l’option -X faulthandler.

Nouveau dans la version 3.3.

PYTHONTRACEMALLOC

Si elle est définie à une chaîne non vide, lance le suivi des allocations mémoire par Python en utilisant le module tracemalloc. La valeur de la variable définit le nombre maximum d’appels (les frames en anglais) stockés dans la trace de pile d’appels. Par exemple, PYTHONTRACEMALLOC=1 ne stocke que l’appel le plus récent. Voir tracemalloc.start() pour davantage d’informations.

Nouveau dans la version 3.4.

PYTHONASYNCIODEBUG

Si elle est définie à une chaîne non vide, active le mode debogage du module asyncio.

Nouveau dans la version 3.4.

PYTHONMALLOC

Définit l’allocateur mémoire de Python ou installe des points d’entrée (hooks en anglais) de débogage.

Définit la famille d’allocateurs mémoire utilisés par Python :

malloc : utilise la fonction malloc() de la bibliothèque C standard pour tous les domaines (PYMEM_DOMAIN_RAW, PYMEM_DOMAIN_MEM, PYMEM_DOMAIN_OBJ).

pymalloc : utilise l’allocateur pymalloc pour les domaines PYMEM_DOMAIN_MEM ainsi que PYMEM_DOMAIN_OBJ et utilise la fonction malloc() pour le domaine PYMEM_DOMAIN_RAW.

Installe des points d’entrée de débogage :

debug : installe des fonctions automatiques de débogage au-dessus de l’allocateur mémoire par défaut.

malloc_debug: identique à malloc mais installe aussi des fonctions automatiques de débogage.

pymalloc_debug: identique à pymalloc mais installe aussi des fonctions automatiques de débogage.

Quand Python est compilé en mode release, la valeur par défaut est pymalloc. Quand il est compilé en mode débogage, la valeur par défaut est pymalloc_debug et les fonctions automatiques de débogage sont utilisées automatiquement.

Si Python est configuré sans le support de pymalloc, pymalloc et pymalloc_debug ne sont pas disponibles. Les valeurs par défaut sont malloc en mode release et malloc_debug en mode débogage.

Reportez-vous à la fonction PyMem_SetupDebugHooks() pour ce qui concerne les fonctions automatiques de débogage de l’allocateur mémoire de Python.

Nouveau dans la version 3.6.

PYTHONMALLOCSTATS

Si elle est définie à une chaîne non vide, Python affiche des statistiques relatives à l’allocateur mémoire pymalloc chaque fois qu’un objet est créé par ce gestionnaire, ainsi qu’à la fin de l’exécution du programme.

Cette variable est ignorée si la variable d’environnement PYTHONMALLOC est utilisée pour forcer l’allocateur malloc() de la bibliothèque C standard ou si Python est configuré sans le support de pymalloc.

Modifié dans la version 3.6: Cette variable peut maintenant être utilisée avec Python compilé en mode release. Elle n’a pas d’effet si elle est définie à une chaine vide.

PYTHONLEGACYWINDOWSFSENCODING

Si elle est définie et n’est pas une chaîne vide, l’encodage par défaut respectivement du système de fichiers et des erreurs reviennent à leur valeur pré-3.6, respectivement 'mbcs' et 'replace'. Sinon, les nouvelles valeurs par défaut "UTF-8" et "surrogatepass" sont utilisées.

Vous pouvez aussi activer ceci à l’exécution avec sys._enablelegacywindowsfsencoding().

Disponibilité : Windows

Nouveau dans la version 3.6: Voir la PEP 529 [https://www.python.org/dev/peps/pep-0529] pour plus d’informations.

PYTHONLEGACYWINDOWSSTDIO

Si elle est définie et n’est pas une chaîne vide, n’utilise pas les lecteur et écrivain de la nouvelle console. Cela signifie que les caractères Unicode sont encodés avec l’encodage de la console active plutôt qu’en UTF-8.

Cette variable est ignorée si les flux standards sont redirigés (vers des fichiers ou des tubes) plutôt que pointant vers des mémoires tampons de console.

Disponibilité : Windows

Nouveau dans la version 3.6.

1.2.1. Variables en mode débogage

Définir ces variables n’a d’effet que si Python a été compilé en mode débogage, c’est-à-dire que l’option de compilation --with-pydebug a été spécifiée.

PYTHONTHREADDEBUG

Si elle est définie, Python affiche des informations de débogage relatives aux différents fils d’exécution.

PYTHONDUMPREFS

Si elle est définie, Python affiche (de manière brute) les objets et les compteurs de références toujours existant après la fermeture de l’interpréteur.

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2. Utilisation de Python sur les plateformes Unix

2.1. Récupérer et installer la dernière version de Python

2.1.1. Sur Linux

Python est pré-installé sur la plupart des distributions Linux, et est disponible en paquet sur toutes les autres. Cependant, il y a certaines fonctionnalités que vous voudrez utiliser qui ne seront pas disponibles sur le paquet de votre distribution. Vous pouvez facilement compiler la dernière version de Python depuis les sources.

Dans le cas où Python n’est pas pré-installé et n’est pas dans les dépôts non plus, vous pouvez facilement faire les paquets pour votre propre distribution. Jetez un œil à ces liens :

Voir aussi

https://www.debian.org/doc/manuals/maint-guide/first.fr.html

pour les utilisateurs de Debian

https://en.opensuse.org/Portal:Packaging

pour les utilisateurs d’OpenSuse

https://docs.fedoraproject.org/en-US/Fedora_Draft_Documentation/0.1/html/RPM_Guide/ch-creating-rpms.html

pour les utilisateurs de Fedora

http://www.slackbook.org/html/package-management-making-packages.html

pour les utilisateurs de Slackware

2.1.2. Sur FreeBSD et OpenBSD

Utilisateurs de FreeBSD, pour installer le paquet, utilisez :

pkg install python3

Utilisateurs d’OpenBSD, pour installer le paquet, utilisez :

pkg_add -r python

pkg_add ftp://ftp.openbsd.org/pub/OpenBSD/4.2/packages/<insert your architecture here>/python-<version>.tgz

Par exemple les utilisateurs d”i386 récupèrent la version 2.5.1 de Python en faisant :

pkg_add ftp://ftp.openbsd.org/pub/OpenBSD/4.2/packages/i386/python-2.5.1p2.tgz

2.1.3. Sur OpenSolaris

Vous pouvez récupérer Python depuis OpenCSW [https://www.opencsw.org/]. Différentes versions de Python sont disponibles et peuvent être installées. Exemple : pkgutil -i python27.

2.2. Compiler Python

Si vous voulez compiler CPython vous-même, la première chose à faire est de récupérer le code source [https://www.python.org/downloads/source/]. Vous pouvez télécharger la dernière version ou faire un clone [https://devguide.python.org/setup/#getting-the-source-code]. (Si vous voulez contribuer à des correctifs, il vous faut un clone.)

Le processus de compilation est le suivant :

./configure
make
make install

Les options de configuration et mises en garde pour certaines plateformes Unix spécifiques sont largement documentées dans le fichier README.rst [https://github.com/python/cpython/tree/3.6/README.rst] à la racine du dossier des sources Python.

Avertissement

make install peut écraser ou cacher le binaire python3. make altinstall est donc recommandé à la place de make install puisqu’il installe seulement exec_prefix/bin/pythonversion.

2.3. Fichiers et chemins liés à Python

Ceux-ci sont sujets à des différences en fonction des conventions locales d’installation ; prefix (${prefix}) et exec_prefix (${exec_prefix}) sont dépendants de l’installation et doivent être interprétés comme pour des logiciels GNU ; ils peuvent être égaux.

Par exemple, sur la plupart des systèmes Linux, leur valeur par défaut est /usr.

Fichier/dossier

Signification

exec_prefix/bin/python3

Emplacement recommandé de l’interpréteur.

prefix/lib/pythonversion, exec_prefix/lib/pythonversion

Emplacements recommandés des dossiers contenant les modules standards.

prefix/include/pythonversion, exec_prefix/include/pythonversion

Emplacements recommandés des dossiers contenant les entêtes nécessaires au développement d’extensions Python et à l’intégration de l’interpréteur.

2.4. Divers

Pour utiliser facilement des scripts Python sur Unix, vous devez les rendre exécutables, par exemple avec

$ chmod +x script

et mettre un shebang approprié en haut du script. Un bon choix est généralement

#!/usr/bin/env python3

qui cherche l’interpréteur Python dans le PATH complet. Cependant, certains systèmes Unix peuvent ne pas avoir la commande env, donc vous devrez littéralement écrire /usr/bin/python3 en tant que chemin d’interpréteur.

Pour utiliser des commandes shell dans vos scripts Python, regardez le module subprocess.

2.5. Éditeurs et IDEs

There are a number of IDEs that support Python programming language. Many editors and IDEs provide syntax highlighting, debugging tools, and PEP 8 [https://www.python.org/dev/peps/pep-0008] checks.

Merci d’aller sur Python Editors [https://wiki.python.org/moin/PythonEditors] et Integrated Development Environments [https://wiki.python.org/moin/IntegratedDevelopmentEnvironments] pour une liste exhaustive.

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3. Utilisation de Python sur Windows

Ce document a pour but de donner une vue d’ensemble des comportements spécifiques à Windows dont vous devriez être au courant si vous utilisez Python sur Microsoft Windows.

3.1. Installer Python

Contrairement à la plupart des systèmes Unix, Windows n’inclut pas d’installation de Python par défaut. Pour rendre Python disponible, l’équipe CPython a compilé des installateurs (paquets MSI) pour chaque release [https://www.python.org/download/releases/] depuis plusieurs années. Ces installateurs sont principalement destinés à une installation par utilisateur de Python, avec l’interpréteur et la bibliothèque standard utilisés par un seul utilisateur. Cet installateur peut aussi installer Python pour tous les utilisateurs sur une seule machine et un fichier ZIP séparé est disponible pour intégrer Python dans d’autres applications.

3.1.1. Versions supportées

Comme spécifié dans la PEP 11 [https://www.python.org/dev/peps/pep-0011], une release Python ne gère qu’une plateforme Windows alors que Microsoft considère la plateforme sous support étendu. Ce qui veut dire que Python 3.6 supporte Windows Vista et plus. Si vous avez besoin de compatibilité Windows XP, vous devez utiliser Python 3.4.

3.1.2. Étapes d’installation

Quatre installateurs Python 3.6 sont disponibles au téléchargement — deux de chaque pour les versions 32-bit et 64-bit de l’interpréteur. L”installateur web est léger, et téléchargera automatiquement les composants nécessaires. L”installateur hors-ligne inclut les composants nécessaires pour une installation par défaut et n’a besoin d’une connexion internet que pour des fonctionnalités optionnelles. Voir Installation sans téléchargement pour d’autres moyens d’éviter des téléchargements durant l’installation.

Après avoir lancé l’installateur, deux options s’affichent :

Si vous sélectionnez « Installer Maintenant » (Install Now):

Vous n’aurez pas besoin d’avoir les droits d’administrateur (sauf si une mise à jour de la bibliothèque d’exécution C est nécessaire ou si vous installez le Lanceur Python pour Windows pour tous les utilisateurs)

Python sera installé dans votre répertoire utilisateur

Le Lanceur Python pour Windows sera installé suivant l’option en bas de la première page

La bibliothèque standard, la suite de tests, le lanceur et pip seront installés

Si l’option est cochée, le dossier d’installation sera ajouté à votre PATH

Les raccourcis ne seront visibles que pour l’utilisateur actuel

Sélectionner « Personnaliser l’installation » (Customize installation) vous permettra de sélectionner les fonctionnalités à installer, le chemin d’installation et d’autres options ou des options post-installation. Pour installer des binaires ou symboles de débogage, vous devrez utiliser cette option.

Pour effectuer une installation pour tous les utilisateurs, vous devez sélectionner « Personnaliser l’installation ». Dans ce cas :

Vous pouvez avoir à donner une approbation ou des identifiants administrateur

Python sera installé dans le dossier Program Files

Le Lanceur Python pour Windows sera installé dans le dossier Windows

Des fonctionnalités optionnelles peuvent être sélectionnées durant l’installation

La bibliothèque standard peut être pré-compilée en code intermédiaire (bytecode en anglais)

Si sélectionné, le chemin d’installation sera ajouté au PATH système

Les raccourcis sont disponibles pour tous les utilisateurs

3.1.3. Suppression de la limitation MAX_PATH

Historiquement les chemins sous Windows étaient limités 260 caractères. Cela impliquait que les chemins plus longs n’étaient pas résolus, et seraient une cause d’erreurs.

Dans les dernières versions de Windows, cette limitation peut être étendue à approximativement 32.000 caractères. Votre administrateur devra activer la stratégie de groupe « Enable Win32 long paths » ou mettre la valeur du registre HKEY_LOCAL_MACHINE\SYSTEM\CurrentControlSet\Control\FileSystem@LongPathsEnabled à 1.

Ceci permet à la fonction open(), le module os et la plupart des autres fonctionnalités utilisant des chemins d’accepter et de renvoyer des chemins plus longs que 260 caractères quand vous utilisez des chaînes. (L’utilisation de chemins sous forme de bytes obsolète sur Windows, et cette fonctionnalité n’est pas disponible quand vous utilisez des bytes.)

Après avoir changé l’option si-dessus, aucune configuration supplémentaire n’est requise.

Modifié dans la version 3.6: Gestion des chemins longs.

3.1.4. Installation sans l’interface utilisateur

Toutes les options disponibles dans l’installateur graphique peuvent aussi être spécifiées dans l’invite de commande, permettant à des installateurs scriptés de répliquer une installation sur plusieurs machines sans interaction humaine. Ces options peuvent aussi être ajoutées sans enlever l’interface graphique pour changer les valeurs par défauts.

Pour complétement cacher l’interface de l’installateur et installer Python silencieusement, passez l’option /quiet. Pour sauter les interactions utilisateur mais afficher la progression et les erreurs, passez l’option /passive. L’option /uninstall peut être passée pour immédiatement démarrer la suppression de Python – Aucune confirmation ne sera demandée.

Toutes les autres options sont passées sous la forme name=value, ou value est normalement soit 0 pour désactiver une fonctionnalité, soit 1 pour activer une fonctionnalité, soit un chemin. Ci-dessous la liste complète des options.

Nom

Description

Valeur par défaut

InstallAllUsers

Effectue une installation pour tous les utilisateurs.

0

TargetDir

Le dossier d’installation

Sélection basée sur InstallAllUsers

DefaultAllUsersTargetDir

Le dossier d’installation par défaut pour les installations pour tous les utilisateurs

%ProgramFiles%\Python X.Y ou %ProgramFiles(x86)%\Python X.Y

DefaultJustForMeTargetDir

Le dossier d’installation par défaut pour des installations juste pour soi

%LocalAppData%\Programs\PythonXY or %LocalAppData%\Programs\PythonXY-32

DefaultCustomTargetDir

Le dossier d’installation personnalisé par défaut affiché par l’interface utilisateur

(vide)

AssociateFiles

Crée les associations de fichiers si le lanceur est aussi installé.

1

CompileAll

Compile tous les fichiers .py en .pyc.

0

PrependPath

Add install and Scripts directories to PATH and .PY to PATHEXT

0

Shortcuts

Crée des raccourcis pour l’interpréteur, la documentation et IDLE si installé.

1

Include_doc

Installe le manuel Python

1

Include_debug

Installe les binaires de débogage

0

Include_dev

Installe les fichiers d’en-tête et les bibliothèques développeur

1

Include_exe

Installe python.exe et les fichiers connexes

1

Include_launcher

Installe le Lanceur Python pour Windows.

1

InstallLauncherAllUsers

Installe le Lanceur Python pour Windows pour tous les utilisateurs.

1

Include_lib

Installe la bibliothèque standard et les modules d’extension

1

Include_pip

Installe pip et setuptools

1

Include_symbols

Installe les symboles de débogage (*.pdb)

0

Include_tcltk

Installe Tcl/Tk et IDLE

1

Include_test

Installe la suite de tests de la bibliothèque standard

1

Include_tools

Installe les scripts utilitaires

1

LauncherOnly

Installe seulement le lanceur. Ceci écrasera la plupart des autres options.

0

SimpleInstall

Désactive la plupart de l’interface d’installation

0

SimpleInstallDescription

Un message personnalisé à afficher quand l’interface d’installation simplifiée est utilisée.

(vide)

Par exemple, pour installer silencieusement Python sur tout le système, vous pourriez utilisez la commande suivante (depuis une invite de commande administrateur) :

python-3.6.0.exe /quiet InstallAllUsers=1 PrependPath=1 Include_test=0

Pour permettre à l’utilisateur d’installer facilement une copie de Python sans la suite de tests, vous pouvez proposer un raccourci avec la commande suivante. Cela affichera une page initiale simplifiée et interdira la personnalisation :

python-3.6.0.exe InstallAllUsers=0 Include_launcher=0 Include_test=0
    SimpleInstall=1 SimpleInstallDescription="Just for me, no test suite."

(Notez qu’omettre le lanceur omet aussi les associations de fichiers, et n’est recommandé que pour les installations par utilisateur quand il y a aussi une installation complète sur le système qui a inclus de lanceur.)

The options listed above can also be provided in a file named unattend.xml alongside the executable. This file specifies a list of options and values. When a value is provided as an attribute, it will be converted to a number if possible. Values provided as element text are always left as strings. This example file sets the same options as the previous example:

<Options>
    <Option Name="InstallAllUsers" Value="no" />
    <Option Name="Include_launcher" Value="0" />
    <Option Name="Include_test" Value="no" />
    <Option Name="SimpleInstall" Value="yes" />
    <Option Name="SimpleInstallDescription">Just for me, no test suite</Option>
</Options>

3.1.5. Installation sans téléchargement

Comme certaines fonctionnalités de Python ne sont pas incluses dans l’installateur initial, la sélection de certaines de ces fonctionnalités peut demander une connexion Internet. Pour éviter ce besoin, tous les composants nécessaires peuvent être téléchargés à la demande pour créer un installateur complet qui ne demandera plus de connexion Internet indépendamment des options sélectionnées. Notez que ce téléchargement peut être plus gros que nécessaire, mais lorsqu’un un grand nombre d’installations doivent être faites, il est très utile d’avoir une copie locale.

Execute the following command from Command Prompt to download all possible required files. Remember to substitute python-3.6.0.exe for the actual name of your installer, and to create layouts in their own directories to avoid collisions between files with the same name.

python-3.6.0.exe /layout [optional target directory]

Vous pouvez aussi spécifier l’option /quiet pour masquer la progression.

3.1.6. Modification d’une installation

Une fois Python installé, vous pouvez ajouter ou supprimer des fonctionnalités depuis l’outil Windows Programs and Features (Programmes et Fonctionnalités). Sélectionnez la ligne Python et choisissez « Uninstall/Change » (Désinstaller/Modifier) pour ouvrir l’installateur en mode maintenance.

« Modify » vous permet d’ajouter ou d’enlever des fonctionnalités en modifiant les cases à cocher (les cases inchangées n’installeront ou ne supprimeront rien). Certaines options ne peuvent pas être modifiées dans ce mode, comme le dossier d’installation. Pour modifier ces options, vous devrez ré-installer Python entièrement.

« Repair » vérifiera tous les fichiers qui doivent être installés avec les paramètres actuels le sont, et remplacera ceux qui ont étés supprimés ou modifiés.

« Uninstall » désinstallera Python entièrement, à l’exception du Lanceur Python pour Windows qui à sa propre ligne dans Programs and Features.

3.1.7. Autres plateformes

Avec le développement continu de Python, certaines plateformes qui étaient auparavant prises en charge ne sont plus prises en charge (en raison du manque d’utilisateurs ou de développeurs). Voir PEP 11 [https://www.python.org/dev/peps/pep-0011] pour plus de détails sur toutes les plateformes non prises en charge.

Windows CE [http://pythonce.sourceforge.net/] est toujours pris en charge.

L’installateur Cygwin [https://cygwin.com/] offre d’installer l’interpréteur Python (cf. Cygwin package source [ftp://ftp.uni-erlangen.de/pub/pc/gnuwin32/cygwin/mirrors/cygnus/release/Python], Maintainer releases [http://www.tishler.net/jason/software/Python/])

Voir Python pour Windows [https://www.python.org/downloads/windows/] pour des instructions détaillées sur les plateformes avec installateurs pré-compilés.

Voir aussi

Python on XP [http://dooling.com/index.php/2006/03/14/python-on-xp-7-minutes-to-hello-world/]

« 7 Minutes to « Hello World! » » by Richard Dooling, 2006

Installing on Windows [http://www.diveintopython.net/installing_python/windows.html]

in « Dive into Python: Python from novice to pro [http://www.diveintopython.net/] » by Mark Pilgrim, 2004, ISBN 1-59059-356-1

For Windows users [http://python.swaroopch.com/installation.html#installation-on-windows]

in « Installing Python » in « A Byte of Python [http://python.swaroopch.com/] » by Swaroop C H, 2003

3.2. Paquets alternatifs

À part la distribution standard CPython, il y a des paquets modifiés incluant des fonctionnalités additionnelles. La liste qui suit est une liste de versions populaires et de leurs fonctionnalités principales :

ActivePython [https://www.activestate.com/activePython/]

Installeur avec une compatibilité multi-plateforme, de la documentation, et PyWin32

Anaconda [https://www.continuum.io/downloads/]

Des modules scientifiques populaires (comme numpy, scipy et pandas) et le gestionnaire de paquets conda.

Canopy [https://www.enthought.com/products/canopy/]

Un « environnement d’analyse complet Python » avec des éditeurs et autres outils de développement.

WinPython [https://winPython.github.io/]

Distribution spécifique à Windows avec des paquets scientifiques pré-compilés et des outils pour construire des paquets.

Notez que ces paquets peuvent ne pas inclure la dernière version de Python ou d’autres bibliothèques, et ne sont pas maintenus ni supportés par les core devs Python.

3.3. Configurer Python

Pour exécuter Python confortablement à partir d’une invite de commandes, vous pouvez envisager de modifier certaines variables d’environnement par défaut dans Windows. Bien que l’installateur offre une option pour configurer les variables PATH et PATHEXT pour vous, ce n’est fiable que pour une seule installation à l’échelle du système. Si vous utilisez régulièrement plusieurs versions de Python, pensez à utiliser le Lanceur Python pour Windows.

3.3.1. Digression : Définition des variables d’environnement

Windows permet de configurer les variables d’environnement de façon permanente au niveau de l’utilisateur et du système, ou temporairement dans une invite de commandes.

Pour définir temporairement les variables d’environnement, ouvrez l’invite de commandes et utilisez la commande set :

C:\>set PATH=C:\Program Files\Python 3.6;%PATH%
C:\>set PYTHONPATH=%PYTHONPATH%;C:\My_python_lib
C:\>python

Ces modifications s’appliqueront à toutes les autres commandes exécutées dans cette console et seront héritées par toutes les applications démarrées à partir de cette console.

Un nom de variable entre des signes pour cent sera remplacé par sa valeur, vous permettant d’ajouter votre nouvelle valeur au début ou à la fin. Ajouter python.exe au début de PATH est un moyen courant de s’assurer que la version correcte de Python est lancée.

Pour modifier définitivement les variables d’environnement par défaut, recherchez « modifier les variables d’environnement », via le menu démarrer, ou ouvrez « Propriétés Système », Paramètres Système Avancés et cliquez sur le bouton Variables d’Environnement. Dans cette boîte de dialogue, vous pouvez ajouter ou modifier des variables utilisateurs et systèmes. Pour modifier les variables systèmes, vous avez besoin d’un accès non restreint à votre ordinateur (c’est-à-dire aux droits d’administrateur).

Note

Windows va concaténer les variables utilisateurs après les variables systèmes, ce qui peut provoquer des résultats inattendus lors de la modification de PATH.

La variable PYTHONPATH est utilisée par toutes les versions de Python 2 et Python 3, vous ne devez donc pas configurer cette variable de façon permanente à moins qu’elle n’ajoute que du code compatible avec toutes les versions de Python installées.

Voir aussi

https://support.microsoft.com/kb/100843

Variables d’environnement dans Windows NT

https://technet.microsoft.com/en-us/library/cc754250.aspx

La commande SET, pour modifier temporairement les variables d’environnement

https://technet.microsoft.com/en-us/library/cc755104.aspx

La commande SETX, pour modifier de façon permanente les variables d’environnement

https://support.microsoft.com/kb/310519

Comment gérer les variables d’environnement sous Windows XP

https://www.chem.gla.ac.uk/~louis/software/faq/q1.html

Définir les variables d’environnement, Louis J. Farrugia

3.3.2. Trouver l’exécutable Python

Modifié dans la version 3.5.

En plus d’utiliser l’entrée du menu Démarrer automatiquement créée pour l’interpréteur Python, vous souhaiterez peut-être démarrer Python depuis l’invite de commandes. L’installateur a une option pour installer cela pour vous.

Sur la première page de l’installateur, une option intitulée « Ajouter Python au PATH » peut être sélectionnée pour que l’installateur ajoute l’emplacement d’installation dans le PATH. L’emplacement du dossier Scripts\ y est également ajouté. Cela vous permet de taper Python pour exécuter l’interpréteur, et pip pour l’installateur de paquets. Ainsi, vous pouvez également exécuter vos scripts avec les options de ligne de commande, voir la documentation Ligne de commande.

Si vous n’activez pas cette option au moment de l’installation, vous pouvez toujours ré-exécuter l’installateur, sélectionner Modifier et l’activer. Vous pouvez également modifier manuellement le PATH à l’aide des instructions de Digression : Définition des variables d’environnement. Vous devez définir votre variable d’environnement PATH pour inclure le répertoire de votre installation Python, délimité par un point-virgule des autres entrées. Une variable d’exemple pourrait ressembler à ceci (en supposant que les deux premières entrées existaient déjà) :

C:\WINDOWS\system32;C:\WINDOWS;C:\Program Files\Python 3.6

3.4. Lanceur Python pour Windows

Nouveau dans la version 3.3.

Le lanceur Python pour Windows est un utilitaire qui facilite la recherche et l’exécution de différentes versions de Python. Il permet aux scripts (ou à la ligne de commande) d’indiquer une préférence pour une version Python spécifique, cherchera et exécutera cette version.

Contrairement à la variable PATH, le lanceur sélectionne correctement la version la plus appropriée de Python. Il préfère les installations par utilisateur sur celles du système, et les trie par version plutôt que d’utiliser la version la plus récente installée.

3.4.1. Pour commencer

3.4.1.1. Depuis la ligne de commande

Modifié dans la version 3.6.

Les installations systèmes de Python 3.3 et ultérieur mettent le lanceur dans votre PATH. Le lanceur est compatible avec toutes les versions disponibles de Python, peu importe lesquelles sont installées. Pour vérifier que le lanceur est disponible, exécutez la commande suivante dans l’invite de commandes :

py

Vous devriez voir se lancer la dernière version de Python installée — il peut être quitté normalement, et tous les arguments de ligne de commande supplémentaires spécifiés seront envoyés directement à Python.

Si plusieurs versions de Python sont installées (par exemple, 2.7 et 3.6), vous aurez remarqué que Python 3.6 se lance – pour lancer Python 2.7, essayez la commande :

py -2.7

Si vous voulez que la dernière version de Python 2.x que vous avez installé, essayez la commande :

py -2

Remarquez que la dernière version de Python 2.x démarre.

Si vous voyez l’erreur suivante, le lanceur n’est pas installé :

'py' is not recognized as an internal or external command,
operable program or batch file.

Les installations par utilisateur de Python n’ajoutent pas le lanceur à PATH sauf si l’option a été sélectionnée lors de l’installation.

3.4.1.2. Environnements virtuels

Nouveau dans la version 3.5.

Si le lanceur est exécuté sans version de Python explicite et qu’un environnement virtuel (créé avec le module de la bibliothèque standard venv ou l’outil externe virtualenv) est actif, le lanceur exécute l’interpréteur de l’environnement virtuel plutôt que l’interpréteur global. Pour exécuter l’interpréteur global, désactivez l’environnement virtuel ou spécifiez explicitement la version Python globale.

3.4.1.3. À partir d’un script

Créons un script Python de test, créez un fichier appelé hello.py avec le contenu suivant

#! python
import sys
sys.stdout.write("hello from Python %s\n" % (sys.version,))

À partir du répertoire dans lequel se trouve hello.py, exécutez la commande :

py hello.py

Vous devriez voir le numéro de version du Python 2.x le plus récemment installé. Maintenant, essayez de changer la première ligne en :

#! python3

La commande doit maintenant afficher les dernières informations de Python 3.x. Comme pour les exemples de ligne de commande ci-dessus, vous pouvez spécifier un qualificateur de version plus explicite. En supposant que vous avez installé Python 2.6, essayez de changer la première ligne à #! python2.6 et vous devriez trouver les informations de version 2.6 imprimées.

Notez que, contrairement à l’utilisation interactive, un « python » nu utilisera la dernière version de Python 2.x que vous avez installé. C’est pour la compatibilité ascendante et pour la compatibilité avec UNIX, où la commande python fait généralement référence à Python 2.

3.4.1.4. À partir d’associations de fichiers

Le lanceur aurait dû être associé à des fichiers Python (des fichiers comme .py, .pyw, .pyc) lorsqu’il a été installé. Cela signifie que lorsque vous double-cliquez sur l’un de ces fichiers à partir de l’Explorateur Windows, le lanceur sera utilisé, et donc vous pouvez utiliser les mêmes installations décrites ci-dessus pour que le script spécifie la version qui doit être utilisée.

L’avantage principal de ceci est qu’un seul lanceur peut prendre en charge plusieurs versions de Python en même temps en fonction du contenu de la première ligne.

3.4.2. Lignes Shebang

Si la première ligne d’un fichier de script commence par #!, elle est connue sous le nom de ligne « shebang ». Linux et d’autres systèmes basés sur Unix ont une prise en charge native de ces lignes et les shebangs sont couramment utilisés sur ces systèmes pour indiquer comment un script doit être exécuté. Ce lanceur permet aux mêmes installations d’être utilisés avec des scripts Python sur Windows et les exemples ci-dessus démontrent leur utilisation.

Pour permettre aux shebang dans les scripts Python d’être portables entre UNIX et Windows, ce lanceur prend en charge un certain nombre de commandes « virtuelles » pour spécifier l’interpréteur à utiliser. Les commandes virtuelles prises en charge sont :

/usr/bin/env python

/usr/bin/python

/usr/local/bin/python

python

Par exemple, si la première ligne de votre script commence par

#! /usr/bin/python

Le Python par défaut sera trouvé et utilisé. Comme de nombreux scripts Python écrits pour fonctionner sur UNIX auront déjà cette ligne, ils devraient fonctionner avec le lanceur sans modification. Si vous écrivez un nouveau script sur Windows et que vous pensez qu’il sera utile sur UNIX, vous devez utiliser l’une des lignes shebang commençant par /usr.

Any of the above virtual commands can be suffixed with an explicit version (either just the major version, or the major and minor version) - for example /usr/bin/python2.7 - which will cause that specific version to be located and used.

La forme /usr/bin/env de ligne shebang possède une autre propriété spéciale. Avant de rechercher les interpréteurs Python installés, cette forme recherche d’abord l’exécutable dans le PATH. Cela correspond au comportement du programme Unix env, qui effectue une recherche dans PATH.

3.4.3. Arguments dans les lignes shebang

Les lignes shebang peuvent également spécifier des options supplémentaires à passer à l’interpréteur Python. Par exemple, si vous avez une ligne shebang :

#! /usr/bin/python -v

Alors, Python sera démarré avec l’option -v

3.4.4. Personnalisation

3.4.4.1. Personnalisation via des fichiers INI

Two .ini files will be searched by the launcher - py.ini in the current user’s « application data » directory (i.e. the directory returned by calling the Windows function SHGetFolderPath with CSIDL_LOCAL_APPDATA) and py.ini in the same directory as the launcher. The same .ini files are used for both the “console” version of the launcher (i.e. py.exe) and for the “windows” version (i.e. pyw.exe).

Customization specified in the « application directory » will have precedence over the one next to the executable, so a user, who may not have write access to the .ini file next to the launcher, can override commands in that global .ini file.

3.4.4.2. Personnalisation des versions Python par défaut

In some cases, a version qualifier can be included in a command to dictate which version of Python will be used by the command. A version qualifier starts with a major version number and can optionally be followed by a period (“.”) and a minor version specifier. If the minor qualifier is specified, it may optionally be followed by « -32 » to indicate the 32-bit implementation of that version be used.

Par exemple, une ligne shebang valant #!python n’a pas de qualificateur de version, tandis que #!python3 a un qualificateur de version qui ne spécifie qu’une version majeure.

If no version qualifiers are found in a command, the environment variable PY_PYTHON can be set to specify the default version qualifier - the default value is « 2 ». Note this value could specify just a major version (e.g. « 2 ») or a major.minor qualifier (e.g. « 2.6 »), or even major.minor-32.

Si aucun qualificateur de version mineure n’est trouvé, la variable d’environnement PY_PYTHON{major} (où {major} est le qualificateur de version principale actuelle tel que déterminé ci-dessus) peut être définie pour spécifier la version complète. Si aucune option de ce type n’est trouvée, le lanceur énumérera les versions de Python installées et utilisera la dernière version mineure trouvée pour la version principale, qui est probablement la plus récemment installée dans cette famille.

On 64-bit Windows with both 32-bit and 64-bit implementations of the same (major.minor) Python version installed, the 64-bit version will always be preferred. This will be true for both 32-bit and 64-bit implementations of the launcher - a 32-bit launcher will prefer to execute a 64-bit Python installation of the specified version if available. This is so the behavior of the launcher can be predicted knowing only what versions are installed on the PC and without regard to the order in which they were installed (i.e., without knowing whether a 32 or 64-bit version of Python and corresponding launcher was installed last). As noted above, an optional « -32 » suffix can be used on a version specifier to change this behaviour.

Exemples :

Si aucune option pertinente n’est définie, les commandes python et python2 utiliseront la dernière version de Python 2.x installée et la commande python3 utilisera le dernier Python 3.x installé.

Les commandes python3.1 et python2.7 ne consultent aucune option du tout car les versions sont entièrement spécifiées.

Si PY_PYTHON=3, les commandes python et python3 utiliseront la dernière version de Python 3 installée.

Si PY_PYTHON=3.1-32, la commande python utilisera l’implémentation 32-bits de 3.1 alors que la commande python3 utilisera le dernier Python installé (PY_PYTHON n’a pas été considéré du tout comme une version majeure a été spécifiée.)

Si PY_PYTHON=3 et PY_PYTHON3=3.1, les commandes python et python3 utiliseront spécifiquement 3.1

En plus des variables d’environnement, les mêmes paramètres peuvent être configurés dans le .INI utilisé par le lanceur. La section dans le fichier INI est appelée [defaults] et le nom de la clé sera le même que les variables d’environnement sans le préfixe PY_ principal (et notez que les noms de clés dans le fichier INI sont insensibles à la case.) Le contenu d’une variable d’environnement remplacera les éléments spécifiés dans le fichier INI.

Par exemple :

Le paramètre PY_PYTHON=3.1 équivaut au fichier INI contenant :

[defaults]
python=3.1

Le paramètre PY_PYTHON=3 et PY_PYTHON3=3.1 équivaut au fichier INI contenant :

[defaults]
python=3
python3=3.1

3.4.5. Diagnostics

Si une variable d’environnement PYLAUNCH_DEBUG est définie (à n’importe quelle valeur), le lanceur affichera des informations de diagnostic sur stderr (c’est-à-dire sur la console). Bien que ces informations parviennent à être en même temps nombreuses et concises, elles devraient vous permettre de voir quelles versions de Python ont été trouvées, pourquoi une version particulière a été choisie et la ligne de commande exacte utilisée pour exécuter le Python cible.

3.5. Recherche de modules

Python stocke généralement sa bibliothèque (et donc votre dossier site-packages) dans le répertoire d’installation. Donc, si vous aviez installé Python dans C:\Python\, la bibliothèque par défaut résiderait dans C:\Python\Lib\ et les modules tiers devraient être stockés dans C:\Python\Lib\site-packages\.

To completely override sys.path, create a ._pth file with the same name as the DLL (python36._pth) or the executable (python._pth) and specify one line for each path to add to sys.path. The file based on the DLL name overrides the one based on the executable, which allows paths to be restricted for any program loading the runtime if desired.

Lorsque le fichier existe, toutes les variables de registre et d’environnement sont ignorées, le mode isolé est activé et site n’est pas importé, sauf si une ligne du fichier spécifie import site. Les chemins et les lignes vides commençant par # sont ignorés. Chaque chemin d’accès peut être absolu ou relatif à l’emplacement du fichier. Les importations autres que vers site ne sont pas autorisées, ni n’importe quelle instruction Python.

Note that .pth files (without leading underscore) will be processed normally by the site module.

Lorsque aucun fichier ._pth n’est trouvé, voilà comment sys.path est construit sur Windows :

Une entrée vide est ajoutée au début, qui correspond au répertoire courant.

Si la variable d’environnement PYTHONPATH existe, comme décrit dans Variables d’environnement, ses entrées sont ajoutées ensuite. Notez que sur Windows, les chemins d’accès de cette variable doivent être séparés par des points-virgules, pour les distinguer des deux points utilisés dans les identificateurs de lecteur (C:\ etc.).

Des « chemins d’accès d’application » supplémentaires peuvent être ajoutés dans le registre en tant que sous-clés de \SOFTWARE\Python\PythonCore{version}\PythonPath sous les ruches HKEY_CURRENT_USER et HKEY_LOCAL_MACHINE. Les sous-clés qui ont des chaînes de chemin délimitées par des points-virgules comme valeur par défaut entraînent l’ajout de chaque chemin d’accès à sys.path. (Notez que tous les installateurs connus utilisent seulement HKLM, donc HKCU est généralement vide.)

Si la variable d’environnement PYTHONHOME est définie, elle est supposée comme « Python Home ». Sinon, le chemin de l’exécutable principal de Python est utilisé pour chercher un « fichier de repère » (soit Lib\os.py ou pythonXY.zip) pour déduire le « Python Home ». Si un « Python Home » est trouvé, les sous-répertoires correspondants ajoutés à sys.path (Lib, plat-win, etc) sont basés sur ce dossier. Sinon, le chemin d’accès Python principal est construit à partir du PythonPath stocké dans le registre.

Si le « Python Home » ne peut pas être trouvé, PYTHONPATH n’est pas spécifié dans l’environnement et aucune entrée de registre ne peut être trouvée, un chemin par défaut avec des entrées relatives est utilisé (par exemple .\Lib ; .\plat-win, etc.).

Si un fichier pyvenv.cfg se trouve à côté de l’exécutable principal ou dans le répertoire un niveau au-dessus de l’exécutable, les variantes suivantes s’appliquent :

Si home est un chemin absolu et PYTHONHOME n’est pas défini, ce chemin d’accès est utilisé au lieu du chemin d’accès à l’exécutable principal lors de la déduction de l’emplacement du home.

Le résultat final de tout ceci est :

Lors de l’exécution de python.exe, ou tout autre .exe dans le répertoire principal de Python (soit une version installée, soit directement à partir du répertoire PCbuild), le chemin principal est déduit et les chemins d’accès principaux dans le Registre sont ignorés. D’autres « chemins d’application » dans le registre sont toujours lus.

Lorsque Python est hébergé dans un autre fichier .exe (répertoire différent, intégré via COM, etc.), le « Python Home » ne sera pas déduit, de sorte que le chemin d’accès principal du registre est utilisé. D’autres « chemins d’application » dans le registre sont toujours lus.

Si Python ne peut pas trouver son « home » et il n’y a pas de valeur de registre (.exe gelé, une installation très étrange) vous obtenez un chemin d’accès avec certains chemins par défaut, mais relatif.

Pour ceux qui veulent intégrer Python dans leur application ou leur distribution, les conseils suivants empêcheront les conflits avec d’autres installations :

Incluez un fichier ._pth à côté de votre exécutable contenant les répertoires à inclure. Ceci ignorera les chemins répertoriés dans le registre et les variables d’environnement, et ignorera également site à moins que import site soit listé.

If you are loading python3.dll or python36.dll in your own executable, explicitly call Py_SetPath() or (at least) Py_SetProgramName() before Py_Initialize().

Effacer et/ou écraser PYTHONPATH et configurez PYTHONHOME avant de lancer le python.exe de votre application.

Si vous ne pouvez pas utiliser les suggestions précédentes (par exemple, vous êtes une distribution qui permet aux gens d’exécuter python.exe directement), assurez-vous que le point de repère Lib\os.py existe dans votre répertoire d’installation. (Notez qu’il ne sera pas détecté à l’intérieur d’un fichier ZIP, mais un fichier ZIP correctement nommé sera détecté à la place.)

These will ensure that the files in a system-wide installation will not take precedence over the copy of the standard library bundled with your application. Otherwise, your users may experience problems using your application. Note that the first suggestion is the best, as the others may still be susceptible to non-standard paths in the registry and user site-packages.

Modifié dans la version 3.6:

Ajout de la gestion des ._pth et suppression de l’option applocal de pyvenv.cfg.

Ajout de pythonXX.zip comme point de repère potentiel lorsqu’il est directement adjacent à l’exécutable.

Obsolète depuis la version 3.6:

Les modules spécifiés dans le registre sous Modules (pas PythonPath) peuvent être importés par importlib.machinery.WindowsRegistryFinder. Ce Finder est activé sur Windows dans 3.6.0 et plus récent, mais il pourrait être nécessaire de l’ajouter explicitement à sys.meta_path à l’avenir.

3.6. Modules supplémentaires

Même si Python a l’ambition d’être portable parmi toutes les plates-formes, il existe des fonctionnalités propres à Windows. Certains modules, à la fois dans la bibliothèque standard et externe, et des exemples existent pour utiliser ces fonctionnalités.

Les modules standard de Windows sont documentés dans Services spécifiques à MS Windows.

3.6.1. PyWin32

Le module PyWin32 [https://pypi.org/project/pywin32] de Mark Hammond est une collection de modules pour un support avancé spécifique à Windows. Cela inclut les services pour :

Component Object Model [http://www.microsoft.com/com/] (COM)

Appels à l’API Win32

Registre

Journal d’événement

Microsoft Foundation Classes [http://msdn.microsoft.com/en-us/library/fe1cf721%28VS.80%29.aspx] (MFC) interfaces utilisateur

PythonWin [http://web.archive.org/web/20060524042422/http://www.python.org/windows/pythonwin/] est un exemple d’application MFC livrée avec PyWin32. Il s’agit d’un IDE embarqué avec débogueur intégré.

Voir aussi

Win32 How Do I…? [http://timgolden.me.uk/python/win32_how_do_i.html]

par Tim Golden

Python and COM [http://www.boddie.org.uk/python/COM.html]

par David et Paul Boddie

3.6.2. cx_Freeze

cx_Freeze [http://cx-freeze.sourceforge.net/] is a distutils extension (see Extension de Distutils) which wraps Python scripts into executable Windows programs (*.exe files). When you have done this, you can distribute your application without requiring your users to install Python.

3.6.3. WConio

Depuis la couche avancée de gestion de terminal de Python, curses, est limité aux systèmes de type UNIX, il existe une bibliothèque exclusive à Windows : Windows Console I/O for Python.

WConio [http://newcenturycomputers.net/projects/wconio.html] est un wrapper pour les fichiers Turbo-C CONIO.H, utilisé pour créer des interfaces texte utilisateur.

3.7. Compiler Python sous Windows

Si vous voulez compiler CPython vous-même, la première chose à faire est obtenir la source [https://www.python.org/downloads/source/]. Vous pouvez télécharger soit la source de la dernière version ou tout simplement prendre un checkout [https://devguide.python.org/setup/#getting-the-source-code].

L’arborescence source contient une solution de compilation et des fichiers projet pour Microsoft Visual Studio 2015, qui est le compilateur utilisé pour générer les versions officielles de Python. Ces fichiers se trouvent dans le répertoire PCbuild.

Consultez PC/readme.txt pour des informations générales sur le processus de construction.

Pour les modules d’extension, consultez Construire des extensions C et C++ sur Windows.

Voir aussi

Python + Windows + distutils + SWIG + gcc MinGW [http://sebsauvage.net/python/mingw.html]

ou « Creating Python extensions in C/C++ with SWIG and compiling them with MinGW gcc under Windows » ou « Installing Python extension with distutils and without Microsoft Visual C++ » par Sébastien Sauvage, 2003

MingW – Python extensions [http://oldwiki.mingw.org/index.php/Python%20extensions]

par Trent Apted et al, 2007

3.8. Embedded Distribution

Nouveau dans la version 3.5.

La distribution embarquée est un fichier ZIP contenant un environnement Python minimal. Il est destiné à agir dans le cadre d’une autre application, plutôt que d’être directement accessible par les utilisateurs finaux.

When extracted, the embedded distribution is (almost) fully isolated from the user’s system, including environment variables, system registry settings, and installed packages. The standard library is included as pre-compiled and optimized .pyc files in a ZIP, and python3.dll, python36.dll, python.exe and pythonw.exe are all provided. Tcl/tk (including all dependants, such as Idle), pip and the Python documentation are not included.

Note

La distribution intégrée n’inclut pas le Microsoft C Runtime [https://www.microsoft.com/en-us/download/details.aspx?id=48145] et il est de la responsabilité de l’installateur d’application de le fournir. Le runtime peut avoir déjà été installé sur le système d’un utilisateur précédemment ou automatiquement via Windows Update, et peut être détecté en trouvant ucrtbase.dll dans le répertoire système.

Les paquets tiers doivent être installés par le programme d’installation de l’application parallèlement à la distribution embarquée. L’utilisation de pip pour gérer les dépendances comme pour une installation Python régulière n’est pas prise en charge avec cette distribution, mais il reste possible d’inclure et d’utiliser pip pour les mises à jour automatiques. En général, les paquets tiers doivent être traités dans le cadre de l’application (vendoring) afin que le développeur puisse assurer la compatibilité avec les versions plus récentes avant de fournir des mises à jour aux utilisateurs.

Les deux cas d’utilisation recommandés pour cette distribution sont décrits ci-dessous.

3.8.1. Application Python

Une application écrite en Python n’exige pas nécessairement que les utilisateurs soient au courant de ce fait. La distribution embarquée peut être utilisée dans ce cas pour inclure une version privée de Python dans un package d’installation. Selon la façon dont il devrait être transparent (ou inversement, à quel point il doit paraître professionnel), il y a deux options.

L’utilisation d’un exécutable spécialisé en tant que lanceur nécessite de la programmation, mais fournit l’expérience la plus transparente pour les utilisateurs. Avec un lanceur personnalisé, il n’y a pas d’indications évidentes que le programme s’exécute sur Python : les icônes peuvent être personnalisées, les informations de la société et de la version peuvent être spécifiées, et les associations de fichiers se comportent correctement. Dans la plupart des cas, un lanceur personnalisé devrait simplement pouvoir appeler Py_Main avec une ligne de commande codée en dur.

L’approche la plus simple consiste à fournir un fichier batch ou un raccourci généré qui appelle directement le python.exe ou pythonw.exe avec les arguments de ligne de commande requis. Dans ce cas, l’application semble être Python et non son nom réel, et les utilisateurs peuvent avoir du mal à le distinguer des autres processus Python en cours d’exécution ou des associations de fichiers.

Avec cette dernière approche, les packages doivent être installés en tant que répertoires à côté de l’exécutable Python pour s’assurer qu’ils soient visibles par Python. Avec le lanceur spécialisé, les paquets peuvent être installés dans d’autres emplacements car il y a une possibilité de spécifier le chemin de recherche avant de lancer l’application.

3.8.2. Embarquer Python

Les applications écrites en code natif nécessitent souvent une certaine forme de langage de scripting, et la distribution Python intégrée peut être utilisée à cette fin. En général, la majorité de l’application est dans le code natif, qui soit invoque python.exe soit utilise directement python3.dll. Dans les deux cas, l’extraction de la distribution intégrée dans un sous-répertoire de l’installation de l’application est suffisante pour fournir un interpréteur Python chargeable.

Comme pour l’utilisation de l’application, les paquets peuvent être installés sur n’importe quel emplacement, car il est possible de spécifier des chemins de recherche avant d’initialiser l’interpréteur. Sinon, il n’y a pas de différences fondamentales entre l’utilisation de la distribution embarquée et une installation classique.

3.9. Autres ressources

Voir aussi

Python Programming On Win32 [http://shop.oreilly.com/product/9781565926219.do]

« Help for Windows Programmers » de Mark Hammond et Andy Robinson, O’Reilly Media, 2000, ISBN 1-56592-621-8

A Python for Windows Tutorial [http://www.imladris.com/Scripts/PythonForWindows.html]

par Amanda Birmingham, 2004

PEP 397 [https://www.python.org/dev/peps/pep-0397] - Python launcher for Windows

The proposal for the launcher to be included in the Python distribution.

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4. Utilisation de Python sur un Macintosh

Auteur

Bob Savage <bobsavage@mac.com>

Python sur un Macintosh exécutant Mac OS X est en principe très similaire à Python sur n’importe quelle autre plateforme Unix, mais il y a un certain nombre de fonctionnalités additionnelle telle que l’IDE et le gestionnaire de paquets qui méritent d’être soulignées.

4.1. Obtenir et installer MacPython

Mac OS X 10.8 contient déjà Python 2.7 pré-installé par Apple. Si vous le souhaitez, vous êtes invités à installer la version la plus récente de Python 3 à partir du site de Python (https://www.python.org). Une version « binaire universelle » de Python, qui s’exécute nativement sur les nouveaux processeurs Intel de Mac et les processeurs PPC, CPUs hérités de Mac, y est disponible.

Vous obtiendrez un certain nombre de choses après installation:

Un dossier MacPython 3.6 dans votre dossier Applications. Dedans vous trouverez IDLE, l’environnement de développement qui fait partie des distributions Python officielles ; PythonLauncher, qui gère le lancement de scripts Python depuis le Finder ; et l’outil « Build Applet », qui permets d’empaqueter des scripts Python en tant qu’applications à part entière sur votre système.

Un framework /Library/Frameworks/Python.framework, qui inclut l’exécutable Python et ses bibliothèques. L’installateur ajoute ce chemin à votre PATH. Pour désinstaller MacPython, vous pouvez simplement supprimer ces trois choses. Un lien symbolique vers l’exécutable Python est placé dans /usr/local/bin/.

Le build Python fourni par Apple est installé dans /System/Library/Frameworks/Python.framework et /usr/bin/python. Vous ne devriez jamais les modifier ou supprimer, car ils sont contrôlés et utilisés par Apple (ou d’autres logiciels). Rappelez vous que si vous choisissez d’installer un Python plus récent depuis python.org, vous aurez deux installations de Python différentes et fonctionnelles sur votre ordinateur, il est donc important que vos chemins et utilisations soit cohérentes avec ce que vous voulez faire.

IDLE inclut un menu d’aide qui vous permet d’accéder à la documentation Python. Si vous êtes entièrement novice, vous devriez commencer par lire le tutoriel d’introduction dans ce document.

Si vous êtes familier avec Python sur d’autres plateformes Unix, vous devriez lire la section sur comment exécuter des scripts Python depuis un shell Unix.

4.1.1. Comment exécuter un script Python

Le meilleur moyen de démarrer avec Python sur Max OS X est d’utiliser l’environnement de développement intégré IDLE, voir la section L”IDE et utilisez le menu d’aide (Help) quand l”IDE est lancé.

If you want to run Python scripts from the Terminal window command line or from the Finder you first need an editor to create your script. Mac OS X comes with a number of standard Unix command line editors, vim and emacs among them. If you want a more Mac-like editor, BBEdit or TextWrangler from Bare Bones Software (see http://www.barebones.com/products/bbedit/index.html) are good choices, as is TextMate (see https://macromates.com/). Other editors include Gvim (http://macvim.org) and Aquamacs (http://aquamacs.org/).

Pour exécuter votre script depuis la fenêtre Terminal, vous devez vous assurer que /usr/local/bin est dans le chemin de recherche de votre shell (PATH).

Pour exécuter votre script depuis le Finder vous avez deux options :

Glissez-le vers PythonLauncher

Sélectionnez PythonLauncher en tant qu’application par défaut pour ouvrir votre script (ou n’importe quel script .py) depuis la fenêtre info de votre Finder puis double-cliquez votre script. PythonLauncher a des préférences variées pour contrôler comment votre script est exécuté. Glisser des options permets de les changer pour une invocation, ou utilisez le menu Préférences pour changer les choses globalement.

4.1.2. Lancer des scripts avec une interface graphique

Avec les anciennes versions de Python, il y a une bizarrerie Max OS X dont vous devez être au courant : les programmes qui communiquent avec le gestionnaires de fenêtre Aqua (en d’autres termes, tout ce qui a une interface graphique) doivent être exécutés de façon spécifique. Utilisez pythonw au lieu de python pour exécuter ce genre de scripts.

Avec Python 3.6, vous pouvez utilisez python ou pythonw.

4.1.3. Configuration

Python sur OS X respecte tous les standards Unix pour les variables d’environnement comme PYTHONPATH, mais définir ces variables pour des programmes exécutés depuis le Finder n’est pas standard car le Finder ne lit pas votre .profile ou .cshrc au démarrage. Vous devez créer un fichier ~/.MacOSX/environment.plist. Voir le document technique d’Apple QA1067 pour plus de détails.

Pour plus d’informations sur l’installation de paquets Python dans MacPython, voir la section Installation de paquets Python additionnels.

4.2. L”IDE

MacPython ships with the standard IDLE development environment. A good introduction to using IDLE can be found at https://hkn.eecs.berkeley.edu/~dyoo/python/idle_intro/index.html.

4.3. Installation de paquets Python additionnels

Il y a plusieurs méthodes pour installer des paquets Python supplémentaires :

Les paquets peuvent être installés en utilisant distutils (python setup.py install).

Beaucoup de paquets peuvent aussi être installés via l’extension setuptools ou pip, voir https://pip.pypa.io/.

4.4. Programmation d’interface graphique sur le Mac

Il y a plusieurs options pour construire des applications avec interface graphique sur le Mac avec Python.

PyObjC est un binding Python vers le framework Objective-C/Cocoa d’Apple, qui est la base de la plupart des développements modernes sur Mac. Des informations sur PyObjC sont disponible à https://pythonhosted.org/pyobjc/.

La boîte à outils standard de Python pour des interfaces graphique est tkinter, basé sur la boite a outils multi-plateformes Tk (https://www.tcl.tk). Une version native Aqua de Tk est empaquetée avec OS X par Apple, et la dernière version peut être téléchargée et installée depuis https://www.activestate.com ; elle peut aussi être construite depuis les sources.

wxPython is another popular cross-platform GUI toolkit that runs natively on Mac OS X. Packages and documentation are available from http://www.wxpython.org.

PyQt est une boîte à outils multi-plateformes pour interfaces graphique populaire qui tourne nativement sur Mac OS X. Plus d’informations disponible sur https://riverbankcomputing.com/software/pyqt/intro.

4.5. Distribuer des Applications Python sur le Mac

L’outil « Build Applet » qui est placé dans le dossier MacPython 3.6 est suffisant pour empaqueter des petits scripts Python sur votre propre machine et pour les exécuter en tant qu’application Mac standard. Cependant, cet outil n’est pas assez robuste pour distribuer des applications Python à d’autres utilisateurs.

L’outil standard pour déployer des applications Python sur le Mac est py2app. Plus d’information sur l’installation et l’utilisation de py2app sur http://undefined.org/python/#py2app.

4.6. Autres ressources

La liste de diffusion courriel MacPython est une excellente ressource support pour les utilisateurs et développeurs Python sur Mac :

https://www.python.org/community/sigs/current/pythonmac-sig/

Une autre ressource utile est le wiki MacPython :

https://wiki.python.org/moin/MacPython

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La référence du langage Python

Cette documentation décrit la syntaxe et la « sémantique interne » du langage. Elle peut être laconique, mais essaye d’être exhaustive et exacte. La sémantique des objets natifs secondaires, des fonctions, et des modules est documentée dans La bibliothèque standard. Pour une présentation informelle du langage, voyez plutôt Le tutoriel Python. Pour les développeurs C ou C++, deux manuels supplémentaires existent : Extension et intégration de l’interpréteur Python survole l’écriture d’extensions, et Manuel de référence de l’API Python/C décrit l’interface C/C++ en détail.

1. Introduction

1.1. Autres implémentations

1.2. Notations

2. Analyse lexicale

2.1. Structure des lignes

2.2. Autres lexèmes

2.3. Identifiants et mots-clés

2.4. Littéraux

2.5. Opérateurs

2.6. Délimiteurs

3. Modèle de données

3.1. Objets, valeurs et types

3.2. Hiérarchie des types standards

3.3. Méthodes spéciales

3.4. Coroutines

4. Modèle d’exécution

4.1. Structure d’un programme

4.2. Noms et liaisons

4.3. Exceptions

5. Le système d’importation

5.1. importlib

5.2. Les paquets

5.3. Recherche

5.4. Chargement

5.5. Le chercheur dans path

5.6. Remplacement du système d’importation standard

5.7. Cas particulier de __main__

5.8. Idées d’amélioration

5.9. Références

6. Expressions

6.1. Conversions arithmétiques

6.2. Atomes

6.3. Primaires

6.4. Expression await

6.5. L’opérateur puissance

6.6. Arithmétique unaire et opérations sur les bits

6.7. Opérations arithmétiques binaires

6.8. Opérations de décalage

6.9. Opérations binaires bit à bit

6.10. Comparaisons

6.11. Opérations booléennes

6.12. Expressions conditionnelles

6.13. Expressions lambda

6.14. Listes d’expressions

6.15. Ordre d’évaluation

6.16. Priorités des opérateurs

7. Les instructions simples

7.1. Les expressions

7.2. Les assignations

7.3. L’instruction assert

7.4. L’instruction pass

7.5. L’instruction del

7.6. L’instruction return

7.7. L’instruction yield

7.8. L’instruction raise

7.9. L’instruction break

7.10. L’instruction continue

7.11. L’instruction import

7.12. L’instruction global

7.13. L’instruction nonlocal

8. Instructions composées

8.1. L’instruction if

8.2. L’instruction while

8.3. L’instruction for

8.4. L’instruction try

8.5. L’instruction with

8.6. Définition de fonctions

8.7. Définition de classes

8.8. Coroutines

9. Composants de plus haut niveau

9.1. Programmes Python complets

9.2. Fichier d’entrée

9.3. Entrée interactive

9.4. Entrée d’expression

10. Spécification complète de la grammaire

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1. Introduction

Ce manuel de référence décrit le langage de programmation Python. Il n’a pas vocation à être un tutoriel.

Nous essayons d’être le plus précis possible et nous utilisons le français (NdT : ou l’anglais pour les parties qui ne sont pas encore traduites) plutôt que des spécifications formelles, sauf pour la syntaxe et l’analyse lexicale. Nous espérons ainsi rendre ce document plus compréhensible pour un grand nombre de lecteurs, même si cela laisse un peu de place à l’ambiguïté. En conséquence, si vous arrivez de Mars et que vous essayez de ré-implémenter Python à partir de cet unique document, vous devrez faire des hypothèses et, finalement, vous aurez certainement implémenté un langage sensiblement différent. D’un autre côté, si vous utilisez Python et que vous vous demandez quelles règles s’appliquent pour telle partie du langage, vous devriez trouver une réponse satisfaisante ici. Si vous souhaitez voir une définition plus formelle du langage, nous acceptons toutes les bonnes volontés (ou bien inventez une machine pour nous cloner ☺).

S’agissant du manuel de référence d’un langage, il est dangereux de rentrer profondément dans les détails d’implémentation ; l’implémentation peut changer et d’autres implémentations du même langage peuvent fonctionner différemment. En même temps, CPython est l’implémentation de Python la plus répandue (bien que d’autres implémentations gagnent en popularité) et certaines de ses bizarreries méritent parfois d’être mentionnées, en particulier lorsque l’implémentation impose des limitations supplémentaires. Par conséquent, vous trouvez de courtes « notes d’implémentation » saupoudrées dans le texte.

Chaque implémentation de Python est livrée avec un certain nombre de modules natifs. Ceux-ci sont documentés dans La bibliothèque standard. Quelques modules natifs sont mentionnés quand ils interagissent significativement avec la définition du langage.

1.1. Autres implémentations

Bien qu’il existe une implémentation Python qui soit de loin la plus populaire, il existe d’autres implémentations qui présentent un intérêt particulier pour différents publics.

Parmi les implémentations les plus connues, nous pouvons citer :

CPython

C’est l’implémentation originelle et la plus entretenue de Python, écrite en C. Elle implémente généralement en premier les nouvelles fonctionnalités du langage.

Jython

Python implémenté en Java. Cette implémentation peut être utilisée comme langage de script pour les applications Java ou pour créer des applications utilisant des bibliothèques Java. Elle est également souvent utilisée pour créer des tests de bibliothèques Java. Plus d’informations peuvent être trouvées sur the Jython website [http://www.jython.org/] (site en anglais).

Python pour .NET

Cette implémentation utilise en fait l’implémentation CPython, mais c’est une application .NET et permet un accès aux bibliothèques .NET. Elle a été créée par Brian Lloyd. Pour plus d’informations, consultez la page d’accueil Python pour .NET [https://pythonnet.github.io/] (site en anglais).

IronPython

Un autre Python pour .NET. Contrairement à Python.NET, il s’agit d’une implémentation Python complète qui génère du code intermédiaire (IL) .NET et compile le code Python directement en assemblages .NET. Il a été créé par Jim Hugunin, le programmeur à l’origine de Jython. Pour plus d’informations, voir the IronPython website [http://ironpython.net/] (site en anglais).

PyPy

Une implémentation de Python complètement écrite en Python. Elle apporte des fonctionnalités avancées introuvables dans d’autres implémentations, telles que le fonctionnement sans pile (stackless en anglais) et un compilateur à la volée (Just in Time compiler en anglais). L’un des objectifs du projet est d’encourager l’expérimentation du langage lui-même en facilitant la modification de l’interpréteur (puisqu’il est écrit en Python). Des informations complémentaires sont disponibles sur la page d’accueil du projet PyPy [http://pypy.org/] (site en anglais).

Chacune de ces implémentations diffère d’une manière ou d’une autre par rapport au langage décrit dans ce manuel, ou comporte des spécificités que la documentation standard de Python ne couvre pas. Reportez-vous à la documentation spécifique à l’implémentation pour déterminer ce que vous devez savoir sur l’implémentation que vous utilisez.

1.2. Notations

Les descriptions de l’analyse lexicale et de la syntaxe utilisent une notation de grammaire BNF modifiée. Le style utilisé est le suivant :

name      ::=  lc_letter (lc_letter | "_")*
lc_letter ::=  "a"..."z"

La première ligne indique qu’un name est un lc_letter suivi d’une suite de zéro ou plus lc_letters ou tiret bas. Un lc_letter est, à son tour, l’un des caractères 'a' à 'z' (cette règle est effectivement respectée pour les noms définis dans les règles lexicales et grammaticales de ce document).

Chaque règle commence par un nom (qui est le nom que la règle définit) et ::=. Une barre verticale (|) est utilisée pour séparer les alternatives ; c’est l’opérateur le moins prioritaire de cette notation. Une étoile (*) signifie zéro ou plusieurs répétitions de l’élément précédent ; de même, un plus (+) signifie une ou plusieurs répétitions, et une expression entre crochets ([ ]) signifie zéro ou une occurrence (en d’autres termes, l’expression encadrée est facultative). Les opérateurs * et + agissent aussi étroitement que possible ; les parenthèses sont utilisées pour le regroupement. Les chaînes littérales sont entourées de guillemets anglais ". L’espace n’est utilisée que pour séparer les lexèmes. Les règles sont normalement contenues sur une seule ligne ; les règles avec de nombreuses alternatives peuvent être formatées avec chaque ligne représentant une alternative (et donc débutant par une barre verticale, sauf la première).

Dans les définitions lexicales (comme dans l’exemple ci-dessus), deux autres conventions sont utilisées : deux caractères littéraux séparés par des points de suspension signifient le choix d’un seul caractère dans la plage donnée (en incluant les bornes) de caractères ASCII. Une phrase entre les signes inférieur et supérieur (<...>) donne une description informelle du symbole défini ; par exemple, pour décrire la notion de « caractère de contrôle » si nécessaire.

Même si la notation utilisée est presque la même, il existe une grande différence entre la signification des définitions lexicales et syntaxiques : une définition lexicale opère sur les caractères individuels de l’entrée, tandis qu’une définition syntaxique opère sur le flux de lexèmes générés par l’analyse lexicale. Toutes les notations sous la forme BNF dans le chapitre suivant (« Analyse lexicale ») sont des définitions lexicales ; les notations dans les chapitres suivants sont des définitions syntaxiques.

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2. Analyse lexicale

Un programme Python est lu par un analyseur syntaxique (parser en anglais). En entrée de cet analyseur syntaxique, nous trouvons des lexèmes (tokens en anglais), produits par un analyseur lexical. Ce chapitre décrit comment l’analyseur lexical découpe le fichier en lexèmes.

Python lit le texte du programme comme des suites de caractères Unicode ; l’encodage du fichier source peut être spécifié par une déclaration d’encodage et vaut par défaut UTF-8, voir la PEP 3120 [https://www.python.org/dev/peps/pep-3120] pour les détails. Si le fichier source ne peut pas être décodé, une exception SyntaxError (erreur de syntaxe) est levée.

2.1. Structure des lignes

Un programme en Python est divisé en lignes logiques.

2.1.1. Lignes logiques

La fin d’une ligne logique est représentée par le lexème NEWLINE. Les instructions ne peuvent pas traverser les limites des lignes logiques, sauf quand NEWLINE est autorisé par la syntaxe (par exemple, entre les instructions des instructions composées). Une ligne logique est constituée d’une ou plusieurs lignes physiques en fonction des règles, explicites ou implicites, de continuation de ligne.

2.1.2. Lignes physiques

Une ligne physique est une suite de caractères terminée par une séquence de fin de ligne. Dans les fichiers sources et les chaînes de caractères, n’importe quelle séquence de fin de ligne des plateformes standards peut être utilisée ; Unix utilise le caractère ASCII LF (pour linefeed, saut de ligne en français), Windows utilise la séquence CR LF (carriage return suivi de linefeed) et Macintosh utilisait le caractère ASCII CR. Toutes ces séquences peuvent être utilisées, quelle que soit la plateforme. La fin de l’entrée est aussi une fin de ligne physique implicite.

Lorsque vous encapsulez Python, les chaînes de code source doivent être passées à l’API Python en utilisant les conventions du C standard pour les caractères de fin de ligne : le caractère \n, dont le code ASCII est LF.

2.1.3. Commentaires

Un commentaire commence par le caractère croisillon (#, hash en anglais et qui ressemble au symbole musical dièse, c’est pourquoi il est souvent improprement appelé caractère dièse) situé en dehors d’une chaine de caractères littérale et se termine à la fin de la ligne physique. Un commentaire signifie la fin de la ligne logique à moins qu’une règle de continuation de ligne implicite ne s’applique. Les commentaires sont ignorés au niveau syntaxique, ce ne sont pas des lexèmes.

2.1.4. Déclaration d’encodage

Si un commentaire placé sur la première ou deuxième ligne du script Python correspond à l’expression rationnelle coding[=:]\s*([-\w.]+), ce commentaire est analysé comme une déclaration d’encodage ; le premier groupe de cette expression désigne l’encodage du fichier source. Cette déclaration d’encodage doit être seule sur sa ligne et, si elle est sur la deuxième ligne, la première ligne doit aussi être une ligne composée uniquement d’un commentaire. Les formes recommandées pour l’expression de l’encodage sont

# -*- coding: <encoding-name> -*-

qui est reconnue aussi par GNU Emacs et

# vim:fileencoding=<encoding-name>

qui est reconnue par VIM de Bram Moolenaar.

Si aucune déclaration d’encodage n’est trouvée, l’encodage par défaut est utilisé : UTF-8. En plus, si les premiers octets du fichier sont l’indicateur d’ordre des octets UTF-8 (b'\xef\xbb\xbf', BOM en anglais pour byte order mark), le fichier est considéré comme étant en UTF-8 (cette convention est reconnue, entre autres, par notepad de Microsoft).

Si un encodage est déclaré, le nom de l’encodage doit être reconnu par Python. L’encodage est utilisé pour toute l’analyse lexicale, y compris les chaînes de caractères, les commentaires et les identifiants.

2.1.5. Continuation de ligne explicite

Deux lignes physiques, ou plus, peuvent être jointes pour former une seule ligne logique en utilisant la barre oblique inversée (\) selon la règle suivante : quand la ligne physique se termine par une barre oblique inversée qui ne fait pas partie d’une chaine de caractères ou d’un commentaire, la ligne immédiatement suivante lui est adjointe pour former une seule ligne logique, en supprimant la barre oblique inversée et le caractère de fin de ligne. Par exemple :

if 1900 < year < 2100 and 1 <= month <= 12 \
   and 1 <= day <= 31 and 0 <= hour < 24 \
   and 0 <= minute < 60 and 0 <= second < 60:   # Looks like a valid date
        return 1

Une ligne que se termine par une barre oblique inversée ne peut pas avoir de commentaire. La barre oblique inversée ne permet pas de continuer un commentaire. La barre oblique inversée ne permet pas de continuer un lexème, sauf s’il s’agit d’une chaîne de caractères (par exemple, les lexèmes autres que les chaînes de caractères ne peuvent pas être répartis sur plusieurs lignes en utilisant une barre oblique inversée). La barre oblique inversée n’est pas autorisée ailleurs sur la ligne, en dehors d’une chaîne de caractères.

2.1.6. Continuation de ligne implicite

Les expressions entre parenthèses, crochets ou accolades peuvent être réparties sur plusieurs lignes sans utiliser de barre oblique inversée. Par exemple :

month_names = ['Januari', 'Februari', 'Maart',      # These are the
               'April',   'Mei',      'Juni',       # Dutch names
               'Juli',    'Augustus', 'September',  # for the months
               'Oktober', 'November', 'December']   # of the year

Les lignes continuées implicitement peuvent avoir des commentaires. L’indentation des lignes de continuation n’est pas importante. Une ligne blanche est autorisée comme ligne de continuation. Il ne doit pas y avoir de lexème NEWLINE entre des lignes implicitement continuées. Les lignes continuées implicitement peuvent être utilisées dans des chaînes entre triples guillemets (voir ci-dessous) ; dans ce cas, elles ne peuvent pas avoir de commentaires.

2.1.7. Lignes vierges

Une ligne logique qui ne contient que des espaces, tabulations, caractères de saut de page (formfeed en anglais) ou commentaires est ignorée (c’est-à-dire que le lexème NEWLINE n’est pas produit). Pendant l’édition interactive d’instructions, la gestion des lignes vierges peut différer en fonction de l’implémentation de la boucle REPL. Dans l’interpréteur standard, une ligne complètement vierge (c’est-à-dire ne contenant strictement rien, même pas une espace ou un commentaire) termine une instruction multi-lignes.

2.1.8. Indentation

Des espaces ou tabulations au début d’une ligne logique sont utilisées pour connaître le niveau d’indentation de la ligne, qui est ensuite utilisé pour déterminer comment les instructions sont groupées.

Les tabulations sont remplacées (de la gauche vers la droite) par une à huit espaces de manière à ce que le nombre de caractères remplacés soit un multiple de huit (nous avons ainsi la même règle que celle d’Unix). Le nombre total d’espaces précédant le premier caractère non blanc détermine alors le niveau d’indentation de la ligne. L’indentation ne peut pas être répartie sur plusieurs lignes physiques à l’aide de barres obliques inversées ; les espaces jusqu’à la première barre oblique inversée déterminent l’indentation.

L’indentation est déclarée inconsistante et rejetée si, dans un même fichier source, le mélange des tabulations et des espaces est tel que la signification dépend du nombre d’espaces que représente une tabulation. Une exception TabError est levée dans ce cas.

Note de compatibilité entre les plateformes : en raison de la nature des éditeurs de texte sur les plateformes non Unix, il n’est pas judicieux d’utiliser un mélange d’espaces et de tabulations pour l’indentation dans un seul fichier source. Il convient également de noter que des plateformes peuvent explicitement limiter le niveau d’indentation maximal.

Un caractère de saut de page peut être présent au début de la ligne ; il est ignoré pour les calculs d’indentation ci-dessus. Les caractères de saut de page se trouvant ailleurs avec les espaces en tête de ligne ont un effet indéfini (par exemple, ils peuvent remettre à zéro le nombre d’espaces).

Les niveaux d’indentation de lignes consécutives sont utilisés pour générer les lexèmes INDENT et DEDENT, en utilisant une pile, de cette façon :

Avant que la première ligne du fichier ne soit lue, un « zéro » est posé sur la pile ; il ne sera plus jamais enlevé. Les nombres empilés sont toujours strictement croissants de bas en haut. Au début de chaque ligne logique, le niveau d’indentation de la ligne est comparé au sommet de la pile. S’ils sont égaux, il ne se passe rien. S’il est plus grand, il est empilé et un lexème INDENT est produit. S’il est plus petit, il doit être l’un des nombres présents dans la pile ; tous les nombres de la pile qui sont plus grands sont retirés et, pour chaque nombre retiré, un lexème DEDENT est produit. À la fin du fichier, un lexème DEDENT est produit pour chaque nombre supérieur à zéro restant sur la pile.

Voici un exemple de code Python correctement indenté (bien que très confus) :

def perm(l):
        # Compute the list of all permutations of l
    if len(l) <= 1:
                  return [l]
    r = []
    for i in range(len(l)):
             s = l[:i] + l[i+1:]
             p = perm(s)
             for x in p:
              r.append(l[i:i+1] + x)
    return r

L’exemple suivant montre plusieurs erreurs d’indentation :

 def perm(l):                       # error: first line indented
for i in range(len(l)):             # error: not indented
    s = l[:i] + l[i+1:]
        p = perm(l[:i] + l[i+1:])   # error: unexpected indent
        for x in p:
                r.append(l[i:i+1] + x)
            return r                # error: inconsistent dedent

En fait, les trois premières erreurs sont détectées par l’analyseur syntaxique ; seule la dernière erreur est trouvée par l’analyseur lexical (l’indentation de return r ne correspond à aucun niveau dans la pile).

2.1.9. Espaces entre lexèmes

Sauf au début d’une ligne logique ou dans les chaînes de caractères, les caractères « blancs » espace, tabulation et saut de page peuvent être utilisés de manière interchangeable pour séparer les lexèmes. Un blanc n’est nécessaire entre deux lexèmes que si leur concaténation pourrait être interprétée comme un lexème différent (par exemple, ab est un lexème, mais a b comporte deux lexèmes).

2.2. Autres lexèmes

Outre NEWLINE, INDENT et DEDENT, il existe les catégories de lexèmes suivantes : identifiants, mots clés, littéraux, opérateurs et délimiteurs. Les blancs (autres que les fins de lignes, vus auparavant) ne sont pas des lexèmes mais servent à délimiter les lexèmes. Quand une ambiguïté existe, le lexème correspond à la plus grande chaîne possible qui forme un lexème licite, en lisant de la gauche vers la droite.

2.3. Identifiants et mots-clés

Les identifiants (aussi appelés noms) sont décrits par les définitions lexicales suivantes.

La syntaxe des identifiants en Python est basée sur l’annexe UAX-31 du standard Unicode avec les modifications définies ci-dessous ; consultez la PEP 3131 [https://www.python.org/dev/peps/pep-3131] pour plus de détails.

Dans l’intervalle ASCII (U+0001..U+007F), les caractères licites pour les identifiants sont les mêmes que pour Python 2.x : les lettres minuscules et majuscules de A à Z, le souligné (ou underscore) _ et, sauf pour le premier caractère, les chiffres de 0 à 9.

Python 3.0 introduit des caractères supplémentaires en dehors de l’intervalle ASCII (voir la PEP 3131 [https://www.python.org/dev/peps/pep-3131]). Pour ces caractères, la classification utilise la version de la « base de données des caractères Unicode » telle qu’incluse dans le module unicodedata.

Les identifiants n’ont pas de limite de longueur. La casse est prise en compte.

identifier   ::=  xid_start xid_continue*
id_start     ::=  <all characters in general categories Lu, Ll, Lt, Lm, Lo, Nl, the underscore, and characters with the Other_ID_Start property>
id_continue  ::=  <all characters in id_start, plus characters in the categories Mn, Mc, Nd, Pc and others with the Other_ID_Continue property>
xid_start    ::=  <all characters in id_start whose NFKC normalization is in "id_start xid_continue*">
xid_continue ::=  <all characters in id_continue whose NFKC normalization is in "id_continue*">

Les codes de catégories Unicode cités ci-dessus signifient :

Lu — lettres majuscules

Ll — lettres minuscules

Lt — lettres majuscules particulières (catégorie titlecase de l’Unicode)

Lm — lettres modificatives avec chasse

Lo — autres lettres

Nl — nombres lettres (par exemple, les nombres romains)

Mn — symboles que l’on combine avec d’autres (accents ou autres) sans générer d’espace (nonspacing marks en anglais)

Mc — symboles que l’on combine avec d’autres en générant une espace (spacing combining marks en anglais)

Nd — chiffres (arabes et autres)

Pc — connecteurs (tirets et autres lignes)

Other_ID_Start – liste explicite des caractères de PropList.txt [http://www.unicode.org/Public/9.0.0/ucd/PropList.txt] pour la compatibilité descendante

Other_ID_Continue — pareillement

Tous les identifiants sont convertis dans la forme normale NFKC pendant l’analyse syntaxique : la comparaison des identifiants se base sur leur forme NFKC.

Un fichier HTML, ne faisant pas référence, listant tous les caractères valides pour Unicode 4.1 se trouve à https://www.dcl.hpi.uni-potsdam.de/home/loewis/table-3131.html.

2.3.1. Mots-clés

Les identifiants suivants sont des mots réservés par le langage et ne peuvent pas être utilisés en tant qu’identifiants normaux. Ils doivent être écrits exactement comme ci-dessous :

False      class      finally    is         return
None       continue   for        lambda     try
True       def        from       nonlocal   while
and        del        global     not        with
as         elif       if         or         yield
assert     else       import     pass
break      except     in         raise

2.3.2. Classes réservées pour les identifiants

Certaines classes d’identifiants (outre les mots-clés) ont une signification particulière. Ces classes se reconnaissent par des caractères de soulignement en tête et en queue d’identifiant :

_*

L’identifiant spécial _ n’est pas importé par from module import *. Il est utilisé dans l’interpréteur interactif pour stocker le résultat de la dernière évaluation ; il est stocké dans le module builtins. Lorsque vous n’êtes pas en mode interactif, _ n’a pas de signification particulière et n’est pas défini. Voir la section L’instruction import.

Note

Le nom _ est souvent utilisé pour internationaliser l’affichage ; reportez-vous à la documentation du module gettext pour plus d’informations sur cette convention.

__*__

Noms définis par le système. Ces noms sont définis par l’interpréteur et son implémentation (y compris la bibliothèque standard). Les noms actuels définis par le système sont abordés dans la section Méthodes spéciales, mais aussi ailleurs. D’autres noms seront probablement définis dans les futures versions de Python. Toute utilisation de noms de la forme __*__, dans n’importe quel contexte, qui n’est pas conforme à ce qu’indique explicitement la documentation, est sujette à des mauvaises surprises sans avertissement.

__*

Noms privés pour une classe. Les noms de cette forme, lorsqu’ils sont utilisés dans le contexte d’une définition de classe, sont réécrits sous une forme modifiée pour éviter les conflits de noms entre les attributs « privés » des classes de base et les classes dérivées. Voir la section Identifiants (noms).

2.4. Littéraux

Les littéraux sont des notations pour indiquer des valeurs constantes de certains types natifs.

2.4.1. Littéraux de chaînes de caractères et de suites d’octets

Les chaînes de caractères littérales sont définies par les définitions lexicales suivantes :

stringliteral   ::=  [stringprefix](shortstring | longstring)
stringprefix    ::=  "r" | "u" | "R" | "U" | "f" | "F"
                     | "fr" | "Fr" | "fR" | "FR" | "rf" | "rF" | "Rf" | "RF"
shortstring     ::=  "'" shortstringitem* "'" | '"' shortstringitem* '"'
longstring      ::=  "'''" longstringitem* "'''" | '"""' longstringitem* '"""'
shortstringitem ::=  shortstringchar | stringescapeseq
longstringitem  ::=  longstringchar | stringescapeseq
shortstringchar ::=  <any source character except "\" or newline or the quote>
longstringchar  ::=  <any source character except "\">
stringescapeseq ::=  "\" <any source character>

bytesliteral   ::=  bytesprefix(shortbytes | longbytes)
bytesprefix    ::=  "b" | "B" | "br" | "Br" | "bR" | "BR" | "rb" | "rB" | "Rb" | "RB"
shortbytes     ::=  "'" shortbytesitem* "'" | '"' shortbytesitem* '"'
longbytes      ::=  "'''" longbytesitem* "'''" | '"""' longbytesitem* '"""'
shortbytesitem ::=  shortbyteschar | bytesescapeseq
longbytesitem  ::=  longbyteschar | bytesescapeseq
shortbyteschar ::=  <any ASCII character except "\" or newline or the quote>
longbyteschar  ::=  <any ASCII character except "\">
bytesescapeseq ::=  "\" <any ASCII character>

Une restriction syntaxique non indiquée par ces règles est qu’aucun blanc n’est autorisé entre le stringprefix ou bytesprefix et le reste du littéral. Le jeu de caractères source est défini par la déclaration d’encodage ; il vaut UTF-8 si aucune déclaration d’encodage n’est donnée dans le fichier source ; voir la section Déclaration d’encodage.

Description en français : les deux types de littéraux peuvent être encadrés par une paire de guillemets simples (') ou doubles ("). Ils peuvent aussi être encadrés par une paire de trois guillemets simples ou une paire de trois guillemets doubles (on appelle alors généralement ces chaînes entre triples guillemets). La barre oblique inversée peut être utilisée pour échapper des caractères qui auraient sinon une signification spéciale, tels que le retour à la ligne, la barre oblique inversée elle-même ou le guillemet utilisé pour délimiter la chaîne.

Les littéraux de suites d’octets sont toujours préfixés par 'b' ou 'B' ; cela crée une instance de type bytes au lieu du type str. Ils ne peuvent contenir que des caractères ASCII ; les octets dont la valeur est supérieure ou égale à 128 doivent être exprimés à l’aide d’échappements.

Les chaînes et suites d’octets littérales peuvent être préfixées par la lettre 'r' ou 'R' ; de telles chaînes sont appelées chaines brutes (raw strings en anglais) et traitent la barre oblique inversée comme un caractère normal. En conséquence, les chaînes littérales '\U' et '\u' ne sont pas considérées comme spéciales. Comme les littéraux Unicode de Python 2.x se comportent différemment, la syntaxe 'ur' n’est pas reconnue en Python 3.x.

Nouveau dans la version 3.3: le préfixe 'rb' a été ajouté comme synonyme de 'br' pour les littéraux de suites d’octets.

Nouveau dans la version 3.3: le support du préfixe historique pour les chaînes Unicode a été réintroduit afin de simplifier la maintenance de code compatible Python 2.x et 3.x. Voir la PEP 414 [https://www.python.org/dev/peps/pep-0414] pour davantage d’informations.

Une chaîne littérale qui contient 'f' ou 'F' dans le préfixe est une chaîne de caractères littérale formatée ; lisez Chaînes de caractères formatées littérales. Le 'f' peut être combiné avec 'r' mais pas avec 'b' ou 'u', donc les chaînes de caractères formatées sont possibles mais les littéraux de suites d’octets ne peuvent pas l’être.

Dans les chaînes entre triples guillemets, les sauts de ligne et guillemets peuvent ne pas être échappés (et sont donc pris en compte), mais trois guillemets non échappés à la suite terminent le littéral (on entend par guillemet le caractère utilisé pour commencer le littéral, c’est-à-dire ' ou ").

À moins que le préfixe 'r' ou 'R' ne soit présent, les séquences d’échappement dans les littéraux de chaînes et suites d’octets sont interprétées comme elles le seraient par le C Standard. Les séquences d’échappement reconnues sont :

Séquence d’échappement

Signification

Notes

\newline

barre oblique inversée et retour à la ligne ignorés

\\

barre oblique inversée (\)

\'

guillemet simple (')

\"

guillemet double (")

\a

cloche ASCII (BEL)

\b

retour arrière ASCII (BS)

\f

saut de page ASCII (FF)

\n

saut de ligne ASCII (LF)

\r

retour à la ligne ASCII (CR)

\t

tabulation horizontale ASCII (TAB)

\v

tabulation verticale ASCII (VT)

\ooo

caractère dont le code est ooo en octal

(1,3)

\xhh

caractère dont le code est ooo en hexadécimal

(2,3)

Les séquences d’échappement reconnues seulement dans les chaînes littérales sont :

Séquence d’échappement

Signification

Notes

\N{name}

caractère dont le nom est name dans la base de données Unicode

(4)

\uxxxx

caractère dont le code est xxxx en hexadécimal

(5)

\Uxxxxxxxx

caractère dont le code est xxxxxxxx en hexadécimal sur 32 bits

(6)

Notes :

Comme dans le C Standard, jusqu’à trois chiffres en base huit sont acceptés.

Contrairement au C Standard, il est obligatoire de fournir deux chiffres hexadécimaux.

Dans un littéral de suite d’octets, un échappement hexadécimal ou octal est un octet dont la valeur est donnée. Dans une chaîne littérale, un échappement est un caractère Unicode dont le code est donné.

Modifié dans la version 3.3: Ajout du support pour les alias de noms 1.

Exactement quatre chiffres hexadécimaux sont requis.

N’importe quel caractère Unicode peut être encodé de cette façon. Exactement huit chiffres hexadécimaux sont requis.

Contrairement au C standard, toutes les séquences d’échappement non reconnues sont laissées inchangées dans la chaîne, c’est-à-dire que la barre oblique inversée est laissée dans le résultat (ce comportement est utile en cas de débogage : si une séquence d’échappement est mal tapée, la sortie résultante est plus facilement reconnue comme source de l’erreur). Notez bien également que les séquences d’échappement reconnues uniquement dans les littéraux de chaînes de caractères ne sont pas reconnues pour les littéraux de suites d’octets.

Modifié dans la version 3.6: Les séquences d’échappement non reconnues produisent un avertissement DeprecationWarning. Dans les futures versions de Python, elles génèreront une erreur de syntaxe.

Même dans une chaîne littérale brute, les guillemets peuvent être échappés avec une barre oblique inversée mais la barre oblique inversée reste dans le résultat ; par exemple, r"\"" est une chaîne de caractères valide composée de deux caractères : une barre oblique inversée et un guillemet double ; r"\" n’est pas une chaîne de caractères valide (même une chaîne de caractères brute ne peut pas se terminer par un nombre impair de barres obliques inversées). Plus précisément, une chaîne littérale brute ne peut pas se terminer par une seule barre oblique inversée (puisque la barre oblique inversée échappe le guillemet suivant). Notez également qu’une simple barre oblique inversée suivie d’un saut de ligne est interprétée comme deux caractères faisant partie du littéral et non comme une continuation de ligne.

2.4.2. Concaténation de chaînes de caractères

Plusieurs chaînes de caractères ou suites d’octets adjacentes (séparées par des blancs), utilisant éventuellement des conventions de guillemets différentes, sont autorisées. La signification est la même que leur concaténation. Ainsi, "hello" 'world' est l’équivalent de "helloworld". Cette fonctionnalité peut être utilisée pour réduire le nombre de barres obliques inverses, pour diviser de longues chaînes de caractères sur plusieurs lignes ou même pour ajouter des commentaires à des portions de chaînes de caractères. Par exemple :

re.compile("[A-Za-z_]"       # letter or underscore
           "[A-Za-z0-9_]*"   # letter, digit or underscore
          )

Notez que cette fonctionnalité agit au niveau syntaxique mais est implémentée au moment de la compilation. Pour concaténer les expressions des chaînes de caractères au moment de l’exécution, vous devez utiliser l’opérateur +. Notez également que la concaténation littérale peut utiliser un style différent de guillemets pour chaque composant (et même mélanger des chaînes de caractères brutes et des chaînes de caractères entre triples guillemets). Enfin, les chaînes de caractères formatées peuvent être concaténées avec des chaînes de caractères ordinaires.

2.4.3. Chaînes de caractères formatées littérales

Nouveau dans la version 3.6.

Une chaine de caractères formatée littérale ou f-string est une chaine de caractères littérale préfixée par 'f' ou 'F'. Ces chaines peuvent contenir des champs à remplacer, c’est-à-dire des expressions délimitées par des accolades {}. Alors que les autres littéraux de chaines ont des valeurs constantes, les chaines formatées sont de vraies expressions évaluées à l’exécution.

Les séquences d’échappement sont décodées comme à l’intérieur des chaînes de caractères ordinaires (sauf lorsqu’une chaîne de caractères est également marquée comme une chaîne brute). Après décodage, la grammaire s’appliquant au contenu de la chaîne de caractères est :

f_string          ::=  (literal_char | "{{" | "}}" | replacement_field)*
replacement_field ::=  "{" f_expression ["!" conversion] [":" format_spec] "}"
f_expression      ::=  (conditional_expression | "*" or_expr)
                         ("," conditional_expression | "," "*" or_expr)* [","]
                       | yield_expression
conversion        ::=  "s" | "r" | "a"
format_spec       ::=  (literal_char | NULL | replacement_field)*
literal_char      ::=  <any code point except "{", "}" or NULL>

Les portions qui sont en dehors des accolades sont traitées comme les littéraux, sauf les doubles accolades '{{' ou '}}' qui sont remplacées par la simple accolade correspondante. Une simple accolade ouvrante '{' marque le début du champ à remplacer, qui commence par une expression Python. Après l’expression, il peut y avoir un champ de conversion, introduit par un point d’exclamation '!'. Une spécification de format peut aussi être ajoutée, introduite par le caractère deux-points ':'. Le champ à remplacer se termine par une accolade fermante '}'.

Les expressions dans les chaînes de caractères formatées littérales sont traitées comme des expressions Python normales entourées de parenthèses, à quelques exceptions près. Une expression vide n’est pas autorisée et une expression lambda doit être explicitement entourée de parenthèses. Les expressions de remplacement peuvent contenir des sauts de ligne (par exemple dans les chaînes de caractères entre triples guillemets) mais elles ne peuvent pas contenir de commentaire. Chaque expression est évaluée dans le contexte où la chaîne de caractères formatée apparaît, de gauche à droite.

An await expression and comprehensions containing an async for clause are illegal in the expression in formatted string literals. (The reason is a problem with the implementation — this restriction is lifted in Python 3.7).

Si une conversion est spécifiée, le résultat de l’évaluation de l’expression est converti avant d’être formaté. La conversion '!s' appelle str() sur le résultat, '!r' appelle repr() et '!a' appelle ascii().

Le résultat est ensuite formaté en utilisant le protocole de format(). La spécification du format est passée à la méthode __format__() de l’expression ou du résultat de la conversion. Une chaîne vide est passée lorsque la spécification de format est omise. Le résultat formaté est alors inclus dans la valeur finale de la chaîne complète.

Les spécifications de format peuvent inclure des champs de remplacement imbriqués. Ces champs imbriqués peuvent inclure leurs propres champs de conversion et spécifications de format mais l’imbrication ne doit pas aller plus profond. Le mini-langage de spécification de format est le même que celui utilisé par la méthode .format() du type str.

Les chaînes formatées littérales peuvent être concaténées mais les champs à remplacer ne peuvent pas être divisés entre les littéraux.

Quelques exemples de chaines formatées littérales :

>>> name = "Fred"
>>> f"He said his name is {name!r}."
"He said his name is 'Fred'."
>>> f"He said his name is {repr(name)}."  # repr() is equivalent to !r
"He said his name is 'Fred'."
>>> width = 10
>>> precision = 4
>>> value = decimal.Decimal("12.34567")
>>> f"result: {value:{width}.{precision}}"  # nested fields
'result:      12.35'
>>> today = datetime(year=2017, month=1, day=27)
>>> f"{today:%B %d, %Y}"  # using date format specifier
'January 27, 2017'
>>> number = 1024
>>> f"{number:#0x}"  # using integer format specifier
'0x400'

Une conséquence de partager la même syntaxe avec les chaînes littérales normales est que les caractères dans les champs à remplacer ne doivent pas entrer en conflit avec le guillemet utilisé pour encadrer la chaine formatée littérale :

f"abc {a["x"]} def"    # error: outer string literal ended prematurely
f"abc {a['x']} def"    # workaround: use different quoting

La barre oblique inversée (ou antislash) n’est pas autorisée dans les expressions des champs à remplacer et son utilisation génère une erreur :

f"newline: {ord('\n')}"  # raises SyntaxError

Pour inclure une valeur où l’échappement par barre oblique inversée est nécessaire, vous devez créer une variable temporaire.

>>> newline = ord('\n')
>>> f"newline: {newline}"
'newline: 10'

Une chaine formatée littérale ne peut pas être utilisée en tant que docstring, même si elle ne comporte pas d’expression.

>>> def foo():
...     f"Not a docstring"
...
>>> foo.__doc__ is None
True

Consultez aussi la PEP 498 [https://www.python.org/dev/peps/pep-0498] qui propose l’ajout des chaines formatées littérales et str.format() qui utilise un mécanisme similaire pour formater les chaînes de caractères.

2.4.4. Littéraux numériques

Il existe trois types de littéraux numériques : les entiers, les nombres à virgule flottante et les nombres imaginaires. Il n’y a pas de littéraux complexes (les nombres complexes peuvent être construits en ajoutant un nombre réel et un nombre imaginaire).

Notez que les littéraux numériques ne comportent pas de signe ; une phrase telle que -1 est en fait une expression composée de l’opérateur unitaire - et du littéral 1.

2.4.5. Entiers littéraux

Les entiers littéraux sont décrits par les définitions lexicales suivantes :

integer      ::=  decinteger | bininteger | octinteger | hexinteger
decinteger   ::=  nonzerodigit (["_"] digit)* | "0"+ (["_"] "0")*
bininteger   ::=  "0" ("b" | "B") (["_"] bindigit)+
octinteger   ::=  "0" ("o" | "O") (["_"] octdigit)+
hexinteger   ::=  "0" ("x" | "X") (["_"] hexdigit)+
nonzerodigit ::=  "1"..."9"
digit        ::=  "0"..."9"
bindigit     ::=  "0" | "1"
octdigit     ::=  "0"..."7"
hexdigit     ::=  digit | "a"..."f" | "A"..."F"

Il n’y a pas de limite pour la longueur des entiers littéraux, sauf celle relative à la capacité mémoire.

Les tirets bas sont ignorés pour déterminer la valeur numérique du littéral. Ils peuvent être utilisés pour grouper les chiffres afin de faciliter la lecture. Un souligné peut être placé entre des chiffres ou après la spécification de la base telle que 0x.

Notez que placer des zéros en tête de nombre pour un nombre décimal différent de zéro n’est pas autorisé. Cela permet d’éviter l’ambigüité avec les littéraux en base octale selon le style C que Python utilisait avant la version 3.0.

Quelques exemples d’entiers littéraux :

7     2147483647                        0o177    0b100110111
3     79228162514264337593543950336     0o377    0xdeadbeef
      100_000_000_000                   0b_1110_0101

Modifié dans la version 3.6: Les tirets bas ne sont pas autorisés pour grouper les littéraux.

2.4.6. Nombres à virgule flottante littéraux

Les nombres à virgule flottante littéraux sont décrits par les définitions lexicales suivantes :

floatnumber   ::=  pointfloat | exponentfloat
pointfloat    ::=  [digitpart] fraction | digitpart "."
exponentfloat ::=  (digitpart | pointfloat) exponent
digitpart     ::=  digit (["_"] digit)*
fraction      ::=  "." digitpart
exponent      ::=  ("e" | "E") ["+" | "-"] digitpart

Notez que la partie entière et l’exposant sont toujours interprétés comme étant en base 10. Par exemple, 077e010 est licite et désigne le même nombre que 77e10. La plage autorisée pour les littéraux de nombres à virgule flottante dépend de l’implémentation. Comme pour les entiers littéraux, les soulignés permettent de grouper des chiffres.

Quelques exemples de nombres à virgule flottante littéraux :

3.14    10.    .001    1e100    3.14e-10    0e0    3.14_15_93

Modifié dans la version 3.6: Les tirets bas ne sont pas autorisés pour grouper les littéraux.

2.4.7. Imaginaires littéraux

Les nombres imaginaires sont décrits par les définitions lexicales suivantes :

imagnumber ::=  (floatnumber | digitpart) ("j" | "J")

Un littéral imaginaire produit un nombre complexe dont la partie réelle est 0.0. Les nombres complexes sont représentés comme une paire de nombres à virgule flottante et possèdent les mêmes restrictions concernant les plages autorisées. Pour créer un nombre complexe dont la partie réelle est non nulle, ajoutez un nombre à virgule flottante à votre littéral imaginaire. Par exemple (3+4j). Voici d’autres exemples de littéraux imaginaires :

3.14j   10.j    10j     .001j   1e100j   3.14e-10j   3.14_15_93j

2.5. Opérateurs

Les lexèmes suivants sont des opérateurs :

+       -       *       **      /       //      %      @
<<      >>      &       |       ^       ~
<       >       <=      >=      ==      !=

2.6. Délimiteurs

Les lexèmes suivants servent de délimiteurs dans la grammaire :

(       )       [       ]       {       }
,       :       .       ;       @       =       ->
+=      -=      *=      /=      //=     %=      @=
&=      |=      ^=      >>=     <<=     **=

Le point peut aussi apparaître dans les littéraux de nombres à virgule flottante et imaginaires. Une suite de trois points possède une signification spéciale : c’est une ellipse littérale. La deuxième partie de la liste, les opérateurs d’assignation augmentés, servent de délimiteurs pour l’analyseur lexical mais sont aussi des opérateurs.

Les caractères ASCII suivants ont une signification spéciale en tant que partie d’autres lexèmes ou ont une signification particulière pour l’analyseur lexical :

'       "       #       \

Les caractères ASCII suivants ne sont pas utilisés en Python. S’ils apparaissent en dehors de chaines littérales ou de commentaires, ils produisent une erreur :

$       ?       `

Notes

1

http://www.unicode.org/Public/9.0.0/ucd/NameAliases.txt

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3. Modèle de données

3.1. Objets, valeurs et types

En Python, les données sont représentées sous forme d’objets. Toutes les données d’un programme Python sont représentées par des objets ou par des relations entre les objets (dans un certain sens, et en conformité avec le modèle de Von Neumann d”« ordinateur à programme enregistré », le code est aussi représenté par des objets).

Chaque objet possède un identifiant, un type et une valeur. L’identifiant d’un objet ne change jamais après sa création ; vous pouvez vous le représenter comme l’adresse de l’objet en mémoire. L’opérateur is compare les identifiants de deux objets ; la fonction id() renvoie un entier représentant cet identifiant.

CPython implementation detail: en CPython, id(x) est l’adresse mémoire où est stocké x.

Le type de l’objet détermine les opérations que l’on peut appliquer à l’objet (par exemple, « a-t-il une longueur ? ») et définit aussi les valeurs possibles pour les objets de ce type. La fonction type() renvoie le type de l’objet (qui est lui-même un objet). Comme l’identifiant, le type d’un objet ne peut pas être modifié 1.

La valeur de certains objets peut changer. Les objets dont la valeur peut changer sont dits muables (mutable en anglais) ; les objets dont la valeur est définitivement fixée à leur création sont dits immuables (immutable en anglais). La valeur d’un objet conteneur immuable qui contient une référence vers un objet muable peut varier lorsque la valeur de l’objet muable change ; cependant, le conteneur est quand même considéré comme immuable parce que l’ensemble des objets qu’il contient ne peut pas être modifié. Ainsi, l’immuabilité n’est pas strictement équivalente au fait d’avoir une valeur non modifiable, c’est plus subtil. La muabilité d’un objet est définie par son type ; par exemple, les nombres, les chaînes de caractères et les tuples sont immuables alors que les dictionnaires et les listes sont muables.

Un objet n’est jamais explicitement détruit ; cependant, lorsqu’il ne peut plus être atteint, il a vocation à être supprimé par le ramasse-miettes (garbage-collector en anglais). L’implémentation peut retarder cette opération ou même ne pas la faire du tout — la façon dont fonctionne le ramasse-miette est particulière à chaque implémentation, l’important étant qu’il ne supprime pas d’objet qui peut encore être atteint.

CPython implementation detail: CPython utilise aujourd’hui un mécanisme de compteur de références avec une détection, en temps différé et optionnelle, des cycles d’objets. Ce mécanisme supprime la plupart des objets dès qu’ils ne sont plus accessibles mais il ne garantit pas la suppression des objets où il existe des références circulaires. Consultez la documentation du module gc pour tout ce qui concerne la suppression des cycles. D’autres implémentations agissent différemment et CPython pourrait évoluer. Ne vous reposez pas sur la finalisation immédiate des objets devenus inaccessibles (ainsi, vous devez toujours fermer les fichiers explicitement).

Notez que si vous utilisez les fonctionnalités de débogage ou de trace de l’implémentation, il est possible que des références qui seraient normalement supprimées soient toujours présentes. Notez aussi que capturer une exception avec l’instruction try…except peut conserver des objets en vie.

Certains objets font référence à des ressources « externes » telles que des fichiers ouverts ou des fenêtres. Ces objets libèrent ces ressources au moment où ils sont supprimés, mais comme le ramasse-miettes ne garantit pas qu’il supprime tous les objets, ces objets fournissent également un moyen explicite de libérer la ressource externe, généralement sous la forme d’une méthode close(). Nous incitons fortement les programmeurs à fermer explicitement de tels objets. Les instructions try…finally et with sont très pratiques pour cela.

Certains objets contiennent des références à d’autres objets ; on les appelle conteneurs. Comme exemples de conteneurs, nous pouvons citer les tuples, les listes et les dictionnaires. Les références sont parties intégrantes de la valeur d’un conteneur. Dans la plupart des cas, lorsque nous parlons de la valeur d’un conteneur, nous parlons des valeurs, pas des identifiants des objets contenus ; cependant, lorsque nous parlons de la muabilité d’un conteneur, seuls les identifiants des objets immédiatement contenus sont concernés. Ainsi, si un conteneur immuable (comme un tuple) contient une référence à un objet muable, sa valeur change si cet objet muable est modifié.

Presque tous les comportements d’un objet dépendent du type de l’objet. Même son identifiant est concerné dans un certain sens : pour les types immuables, les opérations qui calculent de nouvelles valeurs peuvent en fait renvoyer une référence à n’importe quel objet existant avec le même type et la même valeur, alors que pour les objets muables cela n’est pas autorisé. Par exemple, après a = 1 ; b = 1, a et b peuvent ou non se référer au même objet avec la valeur un, en fonction de l’implémentation. Mais après c = [] ; d = [], il est garanti que c et d font référence à deux listes vides distinctes nouvellement créées. Notez que c = d = [] attribue le même objet à c et d.

3.2. Hiérarchie des types standards

Vous trouvez ci-dessous une liste des types natifs de Python. Des modules d’extension (écrits en C, Java ou d’autres langages) peuvent définir des types supplémentaires. Les futures versions de Python pourront ajouter des types à cette hiérarchie (par exemple les nombres rationnels, des tableaux d’entiers stockés efficacement, etc.), bien que de tels ajouts se trouvent souvent plutôt dans la bibliothèque standard.

Quelques descriptions des types ci-dessous contiennent un paragraphe listant des « attributs spéciaux ». Ces attributs donnent accès à l’implémentation et n’ont, en général, pas vocation à être utilisés. Leur définition peut changer dans le futur.

None

Ce type ne possède qu’une seule valeur. Il n’existe qu’un seul objet avec cette valeur. Vous accédez à cet objet avec le nom natif None. Il est utilisé pour signifier l’absence de valeur dans de nombreux cas, par exemple pour des fonctions qui ne retournent rien explicitement. Sa valeur booléenne est fausse.

NotImplemented

Ce type ne possède qu’une seule valeur. Il n’existe qu’un seul objet avec cette valeur. Vous accédez à cet objet avec le nom natif NotImplemented. Les méthodes numériques et les comparaisons riches doivent renvoyer cette valeur si elles n’implémentent pas l’opération pour les opérandes fournis (l’interpréteur essaie alors l’opération en permutant les opérandes ou tout autre stratégie de contournement, en fonction de l’opérateur). Sa valeur booléenne est vraie.

Consultez Implémentation des opérations arithmétiques pour davantage de détails.

Ellipse

Ce type ne possède qu’une seule valeur. Il n’existe qu’un seul objet avec cette valeur. Vous accédez à cet objet avec le littéral ... ou le nom natif Ellipsis. Sa valeur booléenne est vraie.

numbers.Number

Ces objets sont créés par les littéraux numériques et renvoyés en tant que résultats par les opérateurs et les fonctions arithmétiques natives. Les objets numériques sont immuables ; une fois créés, leur valeur ne change pas. Les nombres Python sont bien sûr très fortement corrélés aux nombres mathématiques mais ils sont soumis aux limitations des représentations numériques par les ordinateurs.

Python distingue les entiers, les nombres à virgule flottante et les nombres complexes :

numbers.Integral

Ils représentent des éléments de l’ensemble mathématique des entiers (positifs ou négatifs).

Il existe deux types d’entiers :

Entiers (int)

Ils représentent les nombres, sans limite de taille, sous réserve de pouvoir être stockés en mémoire (virtuelle). Afin de pouvoir effectuer des décalages et appliquer des masques, on considère qu’ils ont une représentation binaire. Les nombres négatifs sont représentés comme une variante du complément à 2, qui donne l’illusion d’une chaîne infinie de bits de signe s’étendant vers la gauche.

Booléens (bool)

Ils représentent les valeurs faux et vrai. Deux objets, False et True, sont les seuls objets booléens. Le type booléen est un sous-type du type entier et les valeurs booléennes se comportent comme les valeurs 0 (pour False) et 1 (pour True) dans presque tous les contextes. L’exception concerne la conversion en chaîne de caractères où "False" et "True" sont renvoyées.

Les règles pour la représentation des entiers ont pour objet de donner l’interprétation la plus naturelle pour les opérations de décalage et masquage qui impliquent des entiers négatifs.

numbers.Real (float)

Ils représentent les nombres à virgule flottante en double précision, tels que manipulés directement par la machine. Vous dépendez donc de l’architecture machine sous-jacente (et de l’implémentation C ou Java) pour les intervalles gérés et le traitement des débordements. Python ne gère pas les nombres à virgule flottante en précision simple ; les gains en puissance de calcul et mémoire, qui sont généralement la raison de l’utilisation des nombres en simple précision, sont annihilés par le fait que Python encapsule de toute façon ces nombres dans des objets. Il n’y a donc aucune raison de compliquer le langage avec deux types de nombres à virgule flottante.

numbers.Complex (complex)

Ils représentent les nombres complexes, sous la forme d’un couple de nombres à virgule flottante en double précision, tels que manipulés directement par la machine. Les mêmes restrictions s’appliquent que pour les nombres à virgule flottante. La partie réelle et la partie imaginaire d’un nombre complexe z peuvent être demandées par les attributs en lecture seule z.real et z.imag.

Séquences

Ils représentent des ensembles de taille finie indicés par des entiers positifs ou nuls. La fonction native len() renvoie le nombre d’éléments de la séquence. Quand la longueur d’une séquence est n, l’ensemble des indices contient les entiers 0, 1 …, n-1. On accède à l’élément d’indice i de la séquence a par a[i].

Les séquences peuvent aussi être découpées en tranches (slicing en anglais) : a[i:j] sélectionne tous les éléments d’indice k tel que i <= k < j. Quand on l’utilise dans une expression, la tranche est du même type que la séquence. Ceci veut dire que l’ensemble des indices de la tranche est renuméroté de manière à partir de 0.

Quelques séquences gèrent le « découpage étendu » (extended slicing en anglais) avec un troisième paramètre : a[i:j:k] sélectionne tous les éléments de a d’indice x où x = i + n*k, avec n >= 0 et i <= x < j.

Les séquences se différencient en fonction de leur muabilité :

Séquences immuables

Un objet de type de séquence immuable ne peut pas être modifié une fois qu’il a été créé. Si l’objet contient des références à d’autres objets, ces autres objets peuvent être muables et peuvent être modifiés ; cependant, les objets directement référencés par un objet immuable ne peuvent pas être modifiés.

Les types suivants sont des séquences immuables :

Chaînes de caractères

Une chaîne de caractères (string en anglais) est une séquence de valeurs qui représentent des caractères Unicode. Tout caractère dont le code est dans l’intervalle U+0000 - U+10FFFF peut être représenté dans une chaîne. Python ne possède pas de type char ; à la place, chaque caractère Unicode dans la chaîne est représenté par un objet chaîne de longueur 1. La fonction native ord() convertit un caractère Unicode de la représentation en chaîne vers un entier dans l’intervalle 0 - 10FFFF ; la fonction chr() convertit un entier de l’intervalle 0 - 10FFFF vers l’objet chaîne de longueur 1 correspondant. str.encode() peut être utilisée pour convertir un objet str vers bytes selon l’encodage spécifié et bytes.decode() effectue l’opération inverse.

n-uplets (ou tuples)

Les éléments d’un tuple sont n’importe quels objets Python. Les tuples de deux ou plus éléments sont formés par une liste d’expressions dont les éléments sont séparés par des virgules. Un tuple composé d’un seul élément (un « singleton ») est formé en suffixant une expression avec une virgule (une expression en tant que telle ne crée pas un tuple car les parenthèses doivent rester disponibles pour grouper les expressions). Un tuple vide peut être formé à l’aide d’une paire de parenthèses vide.

Bytes

Les objets bytes sont des tableaux immuables. Les éléments sont des octets (donc composés de 8 bits), représentés par des entiers dans l’intervalle 0 à 255 inclus. Les littéraux bytes (tels que b'abc') et la fonction native constructeur bytes() peuvent être utilisés pour créer des objets bytes. Aussi, un objet bytes peut être décodé vers une chaîne via la méthode decode().

Séquences muables

Les séquences muables peuvent être modifiées après leur création. Les notations de tranches et de sous-ensembles peuvent être utilisées en tant que cibles d’une assignation ou de l’instruction del (suppression).

Il existe aujourd’hui deux types intrinsèques de séquences muables :

Listes

N’importe quel objet Python peut être élément d’une liste. Les listes sont créées en plaçant entre crochets une liste d’expressions dont les éléments sont séparés par des virgules (notez que les listes de longueur 0 ou 1 ne sont pas des cas particuliers).

Tableaux d’octets

Un objet bytearray est un tableau muable. Il est créé par la fonction native constructeur bytearray(). À part la propriété d’être muable (et donc de ne pas pouvoir calculer son empreinte par hachage), un tableau d’octets possède la même interface et les mêmes fonctionnalités qu’un objet immuable bytes.

Le module d’extension array fournit un autre exemple de type de séquence muable, de même que le module collections.

Ensembles

Ils représentent les ensembles d’objets, non ordonnés, finis et dont les éléments sont uniques. Tels quels, ils ne peuvent pas être indicés. Cependant, il est possible d’itérer dessus et la fonction native len() renvoie le nombre d’éléments de l’ensemble. Les utilisations classiques des ensembles sont les tests d’appartenance rapides, la suppression de doublons dans une séquence et le calcul d’opérations mathématiques telles que l’intersection, l’union, la différence et le complémentaire.

Pour les éléments des ensembles, les mêmes règles concernant l’immuabilité s’appliquent que pour les clés de dictionnaires. Notez que les types numériques obéissent aux règles normales pour les comparaisons numériques : si deux nombres sont égaux (pour l’opération de comparaison, par exemple 1 et 1.0), un seul élément est conservé dans l’ensemble.

Actuellement, il existe deux types d’ensembles natifs :

Ensembles

Ils représentent les ensembles muables. Un ensemble est créé par la fonction native constructeur set() et peut être modifié par la suite à l’aide de différentes méthodes, par exemple add().

Ensembles gelés

Ils représentent les ensembles immuables. Ils sont créés par la fonction native constructeur frozenset(). Comme un ensemble gelé est immuable et hachable, il peut être utilisé comme élément d’un autre ensemble ou comme clé de dictionnaire.

Tableaux de correspondances

Ils représentent les ensembles finis d’objets indicés par des ensembles index arbitraires. La notation a[k] sélectionne l’élément indicé par k dans le tableau de correspondance a ; elle peut être utilisée dans des expressions, comme cible d’une assignation ou avec l’instruction del. La fonction native len() renvoie le nombre d’éléments du tableau de correspondances.

Il n’existe actuellement qu’un seul type natif pour les tableaux de correspondances :

Dictionnaires

Ils représentent les ensembles finis d’objets indicés par des valeurs presque arbitraires. Les seuls types de valeurs non reconnus comme clés sont les valeurs contenant des listes, des dictionnaires ou les autres types muables qui sont comparés par valeur plutôt que par l’identifiant de l’objet. La raison de cette limitation est qu’une implémentation efficace de dictionnaire requiert que l’empreinte par hachage des clés reste constante dans le temps. Les types numériques obéissent aux règles normales pour les comparaisons numériques : si deux nombres sont égaux pour l’opération de comparaison, par exemple 1 et 1.0, alors ces deux nombres peuvent être utilisés indifféremment pour désigner la même entrée du dictionnaire.

Les dictionnaires sont muables : ils peuvent être créés par la notation {...} (reportez-vous à la section Agencements de dictionnaires).

Les modules d’extensions dbm.ndbm et dbm.gnu apportent d’autres exemples de types tableaux de correspondances, de même que le module collections.

Types appelables

Ce sont les types sur lesquels on peut faire un appel de fonction (lisez la section Appels) :

Fonctions allogènes

Un objet fonction allogène (ou fonction définie par l’utilisateur, mais ce n’est pas forcément l’utilisateur courant qui a défini cette fonction) est créé par la définition d’une fonction (voir la section Définition de fonctions). Il doit être appelé avec une liste d’arguments contenant le même nombre d’éléments que la liste des paramètres formels de la fonction.

Attributs spéciaux :

Attribut

Signification

__doc__

Chaîne de documentation de la fonction ou None s’il n’en existe pas ; n’est pas héritée par les sous-classes

Accessible en écriture

__name__

Nom de la fonction

Accessible en écriture

__qualname__

qualified name de la fonction

Nouveau dans la version 3.3.

Accessible en écriture

__module__

Nom du module où la fonction est définie ou None si ce nom n’est pas disponible.

Accessible en écriture

__defaults__

Tuple contenant les valeurs des arguments par défaut pour ceux qui en sont dotés ou None si aucun argument n’a de valeur par défaut.

Accessible en écriture

__code__

Objet code représentant le corps de la fonction compilée.

Accessible en écriture

__globals__

Référence pointant vers le dictionnaire contenant les variables globales de la fonction — l’espace de noms global du module dans lequel la fonction est définie.

Accessible en lecture seule

__dict__

Espace de nommage accueillant les attributs de la fonction.

Accessible en écriture

__closure__

None ou tuple de cellules qui contient un lien pour chaque variable libre de la fonction.

Accessible en lecture seule

__annotations__

Dictionnaire contenant les annotations des paramètres. Les clés du dictionnaire sont les noms des paramètres et la clé "return" est utilisée pour les annotations de la valeur renvoyée. Les entrées du dictionnaire ne sont présentes que si les paramètres sont effectivement annotés.

Accessible en écriture

__kwdefaults__

Dictionnaire contenant les valeurs par défaut pour les paramètres passés par mot-clé.

Accessible en écriture

La plupart des attributs étiquetés « Accessible en écriture » vérifient le type de la valeur qu’on leur assigne.

Les objets fonctions acceptent également l’assignation et la lecture d’attributs arbitraires. Vous pouvez utiliser cette fonctionnalité pour, par exemple, associer des métadonnées aux fonctions. La notation classique par point est utilisée pour définir et lire de tels attributs. Notez que l’implémentation actuelle accepte seulement les attributs de fonction sur les fonctions définies par l’utilisateur. Les attributs de fonction pour les fonctions natives seront peut-être acceptés dans le futur.

Vous trouvez davantage d’informations sur la définition de fonctions dans le code de cet objet ; la description des types internes est donnée plus bas.

Méthodes d’instances

Un objet méthode d’instance combine une classe, une instance de classe et tout objet appelable (normalement une fonction définie par l’utilisateur).

Attributs spéciaux en lecture seule : __self__ est l’objet instance de classe, __func__ est l’objet fonction ; __doc__ est la documentation de la méthode (comme __func__.__doc__) ; __name__ est le nom de la méthode (comme __func__.__name__) ; __module__ est le nom du module où la méthode est définie ou None s’il n’est pas disponible.

Les méthodes savent aussi accéder (mais pas modifier) les attributs de la fonction de l’objet fonction sous-jacent.

Les objets méthodes définies par l’utilisateur peuvent être créés quand vous récupérez un attribut de classe (par exemple via une instance de cette classe) si cet attribut est un objet fonction définie par l’utilisateur ou un objet méthode de classe.

Quand un objet méthode d’instance est créé à partir d’un objet fonction définie par l’utilisateur via une des instances, son attribut __self__ est l’instance et l’objet méthode est réputé lié. Le nouvel attribut de la méthode __func__ est l’objet fonction original.

Quand un objet méthode définie par l’utilisateur est créé à partir d’un autre objet méthode de la classe ou de l’instance, son comportement est identique à l’objet fonction sauf pour l’attribut __func__ de la nouvelle instance qui n’est pas l’objet méthode original mais son attribut __func__.

Quand un objet méthode d’instance est créé à partir d’un autre objet méthode de la classe ou de l’instance, son attribut __self__ est la classe elle-même et son attribut __func__ est l’objet fonction sous-jacent la méthode de classe.

Quand un objet méthode d’instance est appelé, la fonction sous-jacente (__func__) est appelée et l’objet instance de la classe (__self__) est inséré en tête de liste des arguments. Par exemple, si C est une classe qui contient la définition d’une fonction f() et que x est une instance de C, alors appeler x.f(1) est équivalent à appeler C.f(x, 1).

Quand un objet méthode d’instance est dérivé à partir d’un objet méthode de classe, l’instance de classe stockée dans __self__ est en fait la classe elle-même. Ainsi, appeler x.f(1) ou C.f(1) est équivalent à appeler f(C, 1) où f est la fonction sous-jacente.

Notez que la transformation d’objet fonction en objet méthode d’instance se produit à chaque fois que l’attribut est récupéré à partir de l’instance. Dans certains cas, assigner l’attribut à une variable locale et appeler cette variable locale constitue une bonne optimisation. Notez aussi que cette transformation n’a lieu que pour les fonctions définies par l’utilisateur : les autres objets appelables (et les objets non appelables) sont récupérés sans transformation. Il est aussi important de noter que les fonctions définies par l’utilisateur qui sont attributs d’une instance de classe ne sont pas converties en méthodes liées ; ceci n’a lieu que pour les fonctions qui sont attributs de la classe.

Fonctions générateurs

Une fonction ou une méthode qui utilise l’instruction yield (voir la section L’instruction yield) est appelée fonction générateur. Une telle fonction, lorsqu’elle est appelée, retourne toujours un objet itérateur qui peut être utilisé pour exécuter le corps de la fonction : appeler la méthode iterator.__next__() de l’itérateur exécute la fonction jusqu’à ce qu’elle renvoie une valeur à l’aide de l’instruction yield. Quand la fonction exécute l’instruction return ou se termine, une exception StopIteration est levée et l’itérateur a atteint la fin de l’ensemble de valeurs qu’il peut renvoyer.

Fonctions coroutines

Une fonction ou méthode définie en utilisant async def est appelée fonction coroutine. Une telle fonction, quand elle est appelée, renvoie un objet coroutine. Elle peut contenir des expressions await ou async with ou des instructions async for. Voir également la section Objets coroutines.

Fonctions générateurs asynchrones

Une fonction ou une méthode définie avec async def et qui utilise l’instruction yield est appelée fonction générateur asynchrone. Une telle fonction, quand elle est appelée, renvoie un objet itérateur asynchrone qui peut être utilisé dans des instructions async for pour exécuter le corps de la fonction.

Appeler la méthode aiterator.__anext__() de l’itérateur asynchrone renvoie un awaitable qui, lorsqu’on l’attend, s’exécute jusqu’à ce qu’il fournisse une valeur à l’aide de l’expression yield. Quand la fonction exécute une instruction return (sans valeur) ou arrive à la fin, une exception StopAsynciteration est levée et l’itérateur asynchrone a atteint la fin de l’ensemble des valeurs qu’il peut produire.

Fonctions natives

Un objet fonction native est une enveloppe autour d’une fonction C. Nous pouvons citer len() et math.sin() (math est un module standard natif) comme fonctions natives. Le nombre et le type des arguments sont déterminés par la fonction C. Des attributs spéciaux en lecture seule existent : __doc__ contient la chaîne de documentation de la fonction (ou None s’il n’y en a pas) ; __name__ est le nom de la fonction ; __self__ est défini à None ; __module__ est le nom du module où la fonction est définie ou None s’il n’est pas disponible.

Méthodes natives

Ce sont des fonctions natives déguisées, contenant un objet passé à une fonction C en tant qu’argument supplémentaire implicite. Un exemple de méthode native est une_liste.append() (une_liste étant un objet liste). Dans ce cas, l’attribut spécial en lecture seule __self__ est défini à l’objet une_liste.

Classes

Les classes sont des appelables. Ces objets sont normalement utilisés pour créer des instances d’elles-mêmes mais des variations sont possibles pour les types de classes qui surchargent __new__(). Les arguments de l’appel sont passés à __new__() et, dans le cas classique, __new__() initialise une nouvelle instance.

Instances de classe

Les instances d’une classe peuvent devenir des appelables si vous définissez la méthode __call__() de leur classe.

Modules

Les modules constituent l’organisation de base du code Python et sont créés par le mécanisme d’import soit avec l’instruction import (voir import), soit en appelant des fonctions telles que importlib.import_module() ou la fonction native __import__(). Un objet module possède un espace de noms implémenté par un objet dictionnaire (c’est le dictionnaire référencé par l’attribut __globals__ des fonctions définies dans le module). Les références à un attribut sont traduites en recherches dans ce dictionnaire, par exemple m.x est équivalent à m.__dict__["x"]. Un objet module ne contient pas l’objet code utilisé pour initialiser le module (puisque celui-ci n’est plus nécessaire une fois l’initialisation terminée).

L’assignation d’un attribut met à jour le dictionnaire d’espace de nommage du module, par exemple m.x = 1 est équivalent à m.__dict__["x"] = 1.

Attributs prédéfinis (en lecture-écriture) : __name__ est le nom du module ; __doc__ est la chaîne de documentation du module (ou None s’il n’y en a pas) ; __annotations__ (optionnel) est un dictionnaire contenant les annotations de variables collectées durant l’exécution du corps du module ; __file__ est le chemin vers le fichier à partir duquel le module a été chargé, s’il a été chargé depuis un fichier. L’attribut __file__ peut être manquant pour certains types de modules, tels que les modules C qui sont statiquement liés à l’interpréteur ; pour les modules d’extension chargés dynamiquement à partir d’une bibliothèque partagée, c’est le chemin vers le fichier de la bibliothèque partagée.

Attribut spécial en lecture seule : __dict__ est l’objet dictionnaire répertoriant l’espace de nommage du module.

CPython implementation detail: en raison de la manière dont CPython nettoie les dictionnaires de modules, le dictionnaire du module est effacé quand le module n’est plus visible, même si le dictionnaire possède encore des références actives. Pour éviter ceci, copiez le dictionnaire ou gardez le module dans votre champ de visibilité tant que vous souhaitez utiliser le dictionnaire directement.

Classes déclarées par le développeur

Le type d’une classe déclarée par le développeur est créé au moment de la définition de la classe (voir la section Définition de classes). Une classe possède un espace de nommage implémenté sous la forme d’un objet dictionnaire. Les références vers les attributs de la classe sont traduits en recherches dans ce dictionnaire, par exemple C.x est traduit en C.__dict__["x"] (bien qu’il existe un certain nombre de fonctions automatiques qui permettent de trouver des attributs par d’autres moyens). Si le nom d’attribut n’est pas trouvé dans ce dictionnaire, la recherche continue dans les classes de base. Les classes de base sont trouvées en utilisant l’ordre de résolution des méthodes (method resolution order en anglais, ou MRO) C3 qui a un comportement cohérent même en présence d’héritages en « diamant », où différentes branches d’héritages conduisent vers un ancêtre commun. Vous trouverez plus de détails sur l’ordre de résolution des méthodes MRO C3 utilisé par Python dans la documentation de la version 2.3 disponible sur https://www.python.org/download/releases/2.3/mro/.

Quand une référence à un attribut de classe (disons la classe C) pointe vers un objet méthode de classe, elle est transformée en objet méthode d’instance dont l’attribut __self__ est C. Quand elle pointe vers un objet méthode statique, elle est transformée en objet encapsulé par l’objet méthode statique. Reportez-vous à la section Implémentation de descripteurs pour une autre manière dont les attributs d’une classe diffèrent de ceux réellement contenus dans son __dict__.

Les assignations d’un attribut de classe mettent à jour le dictionnaire de la classe, jamais le dictionnaire d’une classe de base.

Un objet classe peut être appelé (voir ci-dessus) pour produire une instance de classe (voir ci-dessous).

Attributs spéciaux : __name__ est le nom de la classe ; __module__ est le nom du module dans lequel la classe est définie ; __dict__ est le dictionnaire contenant l’espace de nommage de la classe ; __bases__ est un tuple contenant les classes de base, dans l’ordre d’apparition dans la liste des classes de base ; __doc__ est la chaîne de documentation de la classe (ou None si elle n’existe pas) ; __annotations__ (optionnel) est un dictionnaire contenant les annotations de variables collectées durant l’exécution du corps de la classe.

Instances de classes

Une instance de classe est créée en appelant un objet classe (voir ci-dessus). Une instance de classe possède un espace de nommage implémenté sous la forme d’un dictionnaire qui est le premier endroit où sont recherchées les références aux attributs. Quand un attribut n’est pas trouvé dans ce dictionnaire et que la classe de l’instance contient un attribut avec ce nom, la recherche continue avec les attributs de la classe. Si un attribut de classe est trouvé et que c’est un objet fonction définie par l’utilisateur, il est transformé en objet méthode d’instance dont l’attribut __self__ est l’instance. Les objets méthodes statiques et méthodes de classe sont aussi transformés ; reportez-vous ci-dessous à « Classes ». Lisez la section Implémentation de descripteurs pour une autre façon de récupérer les attributs d’une classe, où la récupération via ses instances peut différer des objets réellement stockés dans le __dict__ de la classe. Si aucun attribut de classe n’est trouvé et que la classe de l’objet possède une méthode __getattr__(), cette méthode est appelée pour rechercher une correspondance.

Les assignations et suppressions d’attributs mettent à jour le dictionnaire de l’instance, jamais le dictionnaire de la classe. Si la classe possède une méthode __setattr__() ou __delattr__(), elle est appelée au lieu de mettre à jour le dictionnaire de l’instance directement.

Les instances de classes peuvent prétendre être des nombres, des séquences ou des tableaux de correspondance si elles ont des méthodes avec des noms spéciaux. Voir la section Méthodes spéciales.

Attributs spéciaux : __dict__ est le dictionnaire des attributs ; __class__ est la classe de l’instance.

Objets Entrées-Sorties (ou objets fichiers)

Un objet fichier représente un fichier ouvert. Différents raccourcis existent pour créer des objets fichiers : la fonction native open() et aussi os.popen(), os.fdopen() ou la méthode makefile() des objets connecteurs (et sûrement d’autres fonctions ou méthodes fournies par les modules d’extensions).

Les objets sys.stdin, sys.stdout et sys.stderr sont initialisés à des objets fichiers correspondant à l’entrée standard, la sortie standard et le flux d’erreurs de l’interpréteur ; ils sont tous ouverts en mode texte et se conforment donc à l’interface définie par la classe abstraite io.TextIOBase.

Types internes

Quelques types utilisés en interne par l’interpréteur sont accessibles à l’utilisateur. Leur définition peut changer dans les futures versions de l’interpréteur mais ils sont donnés ci-dessous à fin d’exhaustivité.

Objets Code

Un objet code représente le code Python sous sa forme compilée en bytecode. La différence entre un objet code et un objet fonction est que l’objet fonction contient une référence explicite vers les globales de la fonction (le module dans lequel elle est définie) alors qu’un objet code ne contient aucun contexte ; par ailleurs, les valeurs par défaut des arguments sont stockées dans l’objet fonction, pas dans l’objet code (parce que ce sont des valeurs calculées au moment de l’exécution). Contrairement aux objets fonctions, les objets codes sont immuables et ne contiennent aucune référence (directe ou indirecte) à des objets muables.

Attributs spéciaux en lecture seule : co_name donne le nom de la fonction ; co_argcount est le nombre d’arguments positionnels (y compris les arguments avec des valeurs par défaut) ; co_nlocals est le nombre de variables locales utilisées par la fonction (y compris les arguments) ; co_varnames est un tuple contenant le nom des variables locales (en commençant par les noms des arguments) ; co_cellvars est un tuple contenant les noms des variables locales qui sont référencées par des fonctions imbriquées ; co_freevars est un tuple contenant les noms des variables libres ; co_code est une chaîne représentant la séquence des instructions de bytecode ; co_consts est un tuple contenant les littéraux utilisés par le bytecode ; co_names est un tuple contenant les noms utilisés par le bytecode ; co_filename est le nom de fichier à partir duquel le code a été compilé ; co_firstlineno est numéro de la première ligne de la fonction ; co_lnotab est une chaîne qui code la correspondance entre les différents endroits du bytecode et les numéros de lignes (pour les détails, regardez le code source de l’interpréteur) ; co_stacksize est la taille de pile nécessaire (y compris pour les variables locales) ; co_flags est un entier qui code différents drapeaux pour l’interpréteur.

Les drapeaux suivants sont codés par des bits dans co_flags : le bit 0x04 est positionné à 1 si la fonction utilise la syntaxe *arguments pour accepter un nombre arbitraire d’arguments positionnels ; le bit 0x08 est positionné à 1 si la fonction utilise la syntaxe **keywords pour accepter un nombre arbitraire d’arguments nommés ; le bit 0x20 est positionné à 1 si la fonction est un générateur.

Les déclarations de fonctionnalité future from __future__ import division utilisent aussi des bits dans co_flags pour indiquer si l’objet code a été compilé avec une fonctionnalité future : le bit 0x2000 est positionné à 1 si la fonction a été compilée avec la division future activée ; les bits 0x10 et 0x1000 étaient utilisés dans les versions antérieures de Python.

Les autres bits de co_flags sont réservés à un usage interne.

Si l’objet code représente une fonction, le premier élément dans co_consts est la chaîne de documentation de la fonction (ou None s’il n’y en a pas).

Objets cadres

Un objet cadre représente le cadre d’exécution. Ils apparaissent dans des objets traces (voir plus loin).

Attributs spéciaux en lecture seule : f_back pointe vers le cadre précédent (l’appelant) ou None si c’est le pied de la pile d’appel ; f_code est l’objet code en cours d’exécution dans ce cadre ; f_locals est le dictionnaire dans lequel sont cherchées les variables locales ; f_globals est utilisé pour les variables globales ; f_builtins est utilisé pour les noms natifs ; f_lasti donne l’instruction précise (c’est un indice dans la chaîne de bytecode de l’objet code).

Attributs spéciaux en lecture-écriture : f_trace, s’il ne vaut pas None, est une fonction appelée au début de chaque ligne de code source (c’est utilisé par le débogueur) ; f_lineno est le numéro de la ligne courante du cadre — écrire dedans depuis une fonction trace fait sauter à la ligne demandée (seulement pour le cadre le plus bas). Un débogueur peut implémenter une commande « sauter vers » en écrivant dans f_lineno.

Les objets cadres comprennent une méthode :

frame.clear()

Cette méthode efface toutes les références aux variables locales conservées dans le cadre. Par ailleurs, si le cadre est celui d’un générateur, le générateur se termine. Ceci permet de casser des références cycliques qui incluent des objets cadres (par exemple, lors de la capture d’une exception et du stockage de la pile d’appels pour une utilisation future).

RuntimeError est levée si le cadre est en cours d’exécution.

Nouveau dans la version 3.4.

Objets traces

Un objet trace représente la pile d’appels d’une exception. Il est créé au moment où l’exception est levée. Quand l’interpréteur recherche un gestionnaire d’exception en remontant la pile d’exécution, un objet trace est inséré devant l’objet trace courant à chaque nouveau niveau. Quand il entre dans le gestionnaire d’exception, la pile d’appels est rendue accessible au programme (voir la section L’instruction try). Elle est accessible par le troisième élément du tuple renvoyé par sys.exc_info(). Quand le programme ne dispose pas d’un gestionnaire adéquat, la pile d’appels est écrite (joliment formatée) sur le flux d’erreurs standard ; si l’interpréteur est interactif, la pile d’appels est rendue accessible à l’utilisateur en tant que sys.last_traceback.

Attributs spéciaux en lecture seule : tb_next est le prochain niveau dans la pile d’appels (vers le cadre où l’exception a été levée) ou None s’il n’y a pas de prochain niveau ; tb_frame pointe vers le cadre d’exécution du niveau courant ; tb_lineno donne le numéro de ligne où l’exception a été levée ; tb_lasti indique l’instruction précise. Le numéro de ligne et la dernière instruction dans la trace peuvent différer du numéro de ligne de l’objet cadre si l’exception a eu lieu dans une instruction try sans qu’il n’y ait de clause except adéquate ou sans clause finally.

Objets tranches

Un objet tranche est utilisé pour représenter des découpes des méthodes __getitem__(). Ils sont aussi créés par la fonction native slice().

Attributs spéciaux en lecture seule : start est la borne inférieure ; stop est la borne supérieure ; step est la valeur du pas ; chaque attribut vaut None s’il est omis. Ces attributs peuvent être de n’importe quel type.

Les objets tranches comprennent une méthode :

slice.indices(self, length)

Cette méthode prend un argument entier length et calcule les informations de la tranche que l’objet découpe décrit s’il est appliqué à une séquence de length éléments. Elle renvoie un tuple de trois entiers ; respectivement, ce sont les indices de début et fin ainsi que le pas de découpe. Les indices manquants ou en dehors sont gérés de manière cohérente avec les tranches normales.

Objets méthodes statiques

Les objets méthodes statiques permettent la transformation des objets fonctions en objets méthodes décrits au-dessus. Un objet méthode statique encapsule tout autre objet, souvent un objet méthode définie par l’utilisateur. Quand un objet méthode statique est récupéré depuis une classe ou une instance de classe, l’objet réellement renvoyé est un objet encapsulé, qui n’a pas vocation à être transformé encore une fois. Les objets méthodes statiques ne sont pas appelables en tant que tels, bien que les objets qu’ils encapsulent le soient souvent. Les objets méthodes statiques sont créés par le constructeur natif staticmethod().

Objets méthodes de classes

Un objet méthode de classe, comme un objet méthode statique, encapsule un autre objet afin de modifier la façon dont cet objet est récupéré depuis les classes et instances de classes. Le comportement des objets méthodes de classes dans le cas d’une telle récupération est décrit plus haut, dans « méthodes définies par l’utilisateur ». Les objets méthodes de classes sont créés par le constructeur natif classmethod().

3.3. Méthodes spéciales

Une classe peut implémenter certaines opérations que l’on invoque par une syntaxe spéciale (telles que les opérations arithmétiques ou la découpe en tranches) en définissant des méthodes aux noms particuliers. C’est l’approche utilisée par Python pour la surcharge d’opérateur, permettant à une classe de définir son propre comportement vis-à-vis des opérateurs du langage. Par exemple, si une classe définit une méthode __getitem__() et que x est une instance de cette classe, alors x[i] est globalement équivalent à type(x).__getitem__(x, i). Sauf lorsque c’est mentionné, toute tentative d’appliquer une opération alors que la méthode appropriée n’est pas définie lève une exception (typiquement AttributeError ou TypeError).

Définir une méthode spéciale à None indique que l’opération correspondante n’est pas disponible. Par exemple, si une classe assigne None à __iter__(), vous ne pouvez pas itérer sur la classe et appeler iter() sur une instance lève TypeError (sans se replier sur __getitem__()) 2.

Lorsque vous implémentez une classe qui émule un type natif, il est important que cette émulation n’implémente que ce qui fait sens pour l’objet qui est modélisé. Par exemple, la recherche d’éléments individuels d’une séquence peut faire sens, mais pas l’extraction d’une tranche (un exemple est l’interface de NodeList dans le modèle objet des documents W3C).

3.3.1. Personnalisation de base

object.__new__(cls[, ...])

Appelée pour créer une nouvelle instance de la classe cls. La méthode __new__() est statique (c’est un cas particulier, vous n’avez pas besoin de la déclarer comme telle) qui prend comme premier argument la classe pour laquelle on veut créer une instance. Les autres arguments sont ceux passés à l’expression de l’objet constructeur (l’appel à la classe). La valeur de retour de __new__() doit être l’instance du nouvel objet (classiquement une instance de cls).

Une implémentation typique crée une nouvelle instance de la classe en invoquant la méthode __new__() de la superclasse à l’aide de super().__new__(cls[, ...]) avec les arguments adéquats, puis modifie l’instance nouvellement créée en tant que de besoin avant de la renvoyer.

Si __new__() renvoie une instance de cls, alors la méthode __init__() de la nouvelle instance est invoquée avec __init__(self[, ...]) où self est la nouvelle instance et les autres arguments sont les mêmes que ceux passés à __new__().

Si __new__() ne renvoie pas une instance de cls, alors la méthode __init__() de la nouvelle instance n’est pas invoquée.

L’objectif de __new__() est principalement, pour les sous-classes de types immuables (comme int, str ou tuple), d’autoriser la création sur mesure des instances. Elle est aussi souvent surchargée dans les méta-classes pour particulariser la création des classes.

object.__init__(self[, ...])

Appelée après la création de l’instance (par __new__()), mais avant le retour vers l’appelant. Les arguments sont ceux passés à l’expression du constructeur de classe. Si une classe de base possède une méthode __init__(), la méthode __init__() de la classe dérivée, si elle existe, doit explicitement appeler cette méthode pour assurer une initialisation correcte de la partie classe de base de l’instance ; par exemple : super().__init__([args...]).

Comme __new__() et __init__() travaillent ensemble pour créer des objets (__new__() pour le créer, __init__() pour le particulariser), __init__() ne doit pas renvoyer de valeur None ; sinon une exception TypeError est levée à l’exécution.

object.__del__(self)

Appelée au moment où une instance est sur le point d’être détruite. On l’appelle aussi finaliseur ou (improprement) destructeur. Si une classe de base possède une méthode __del__(), la méthode __del__() de la classe dérivée, si elle existe, doit explicitement l’appeler pour s’assurer de l’effacement correct de la partie classe de base de l’instance.

Il est possible (mais pas recommandé) que la méthode __del__() retarde la destruction de l’instance en créant une nouvelle référence vers cet objet. Python appelle ceci la résurrection d’objet. En fonction de l’implémentation, __del__() peut être appelée une deuxième fois au moment où l’objet ressuscité va être détruit ; l’implémentation actuelle de CPython ne l’appelle qu’une fois.

Il n’est pas garanti que soient appelées les méthodes __del__() des objets qui existent toujours quand l’interpréteur termine.

Note

del x n’appelle pas directement x.__del__() — la première décrémente le compteur de références de x. La seconde n’est appelée que quand le compteur de références de x atteint zéro.

CPython implementation detail: It is possible for a reference cycle to prevent the reference count of an object from going to zero. In this case, the cycle will be later detected and deleted by the cyclic garbage collector. A common cause of reference cycles is when an exception has been caught in a local variable. The frame’s locals then reference the exception, which references its own traceback, which references the locals of all frames caught in the traceback.

Voir aussi

Documentation du module gc.

Avertissement

En raison des conditions particulières qui règnent quand __del__() est appelée, les exceptions levées pendant son exécution sont ignorées et, à la place, un avertissement est affiché sur sys.stderr. En particulier :

__del__() peut être invoquée quand du code arbitraire est en cours d’exécution, et ce dans n’importe quel fil d’exécution. Si __del__() a besoin de poser un verrou ou d’accéder à tout autre ressource bloquante, elle peut provoquer un blocage mutuel (deadlock en anglais) car la ressource peut être déjà utilisée par le code qui est interrompu pour exécuter la méthode __del__().

__del__() peut être exécutée pendant que l’interpréteur se ferme. En conséquence, les variables globales auxquelles elle souhaite accéder (y compris les autres modules) peuvent déjà être détruites ou assignées à None. Python garantit que les variables globales dont le nom commence par un tiret bas sont supprimées de leur module avant que les autres variables globales ne le soient ; si aucune autre référence vers ces variables globales n’existe, cela peut aider à s’assurer que les modules importés soient toujours accessibles au moment où la méthode __del__() est appelée.

object.__repr__(self)

Appelée par la fonction native repr() pour calculer la représentation « officielle » en chaîne de caractères d’un objet. Tout est fait pour que celle-ci ressemble à une expression Python valide pouvant être utilisée pour recréer un objet avec la même valeur (dans un environnement donné). Si ce n’est pas possible, une chaîne de la forme <...une description utile...> est renvoyée. La valeur renvoyée doit être un objet chaîne de caractères. Si une classe définit __repr__() mais pas __str__(), alors __repr__() est aussi utilisée quand une représentation « informelle » en chaîne de caractères est demandée pour une instance de cette classe.

Cette fonction est principalement utilisée à fins de débogage, il est donc important que la représentation donne beaucoup d’informations et ne soit pas ambigüe.

object.__str__(self)

Appelée par str(objet) ainsi que les fonctions natives format() et print() pour calculer une chaîne de caractères « informelle » ou joliment mise en forme de représentation de l’objet. La valeur renvoyée doit être un objet string.

Cette méthode diffère de object.__repr__() car il n’est pas attendu que __str__() renvoie une expression Python valide : une représentation plus agréable à lire ou plus concise peut être utilisée.

C’est l’implémentation par défaut des appels à object.__repr__() du type natif object.

object.__bytes__(self)

Appelée par bytes pour calculer une représentation en chaîne bytes d’un objet. Elle doit renvoyer un objet bytes.

object.__format__(self, format_spec)

Appelée par la fonction native format() et, par extension, lors de l’évaluation de formatted string literals ou de la méthode str.format(). Elle produit une chaîne de caractères « formatée » représentant un objet. L’argument format_spec est une chaîne de caractères contenant la description des options de formatage voulues. L’interprétation de l’argument format_spec est laissée au type implémentant __format__(). Cependant, la plupart des classes délèguent le formatage aux types natifs ou utilisent une syntaxe similaire d’options de formatage.

Lisez Mini-langage de spécification de format pour une description de la syntaxe standard du formatage.

La valeur renvoyée doit être un objet chaîne de caractères.

Modifié dans la version 3.4: La méthode __format__ de object lui-même lève une TypeError si vous lui passez une chaîne non vide.

object.__lt__(self, other)

object.__le__(self, other)

object.__eq__(self, other)

object.__ne__(self, other)

object.__gt__(self, other)

object.__ge__(self, other)

Ce sont les méthodes dites de « comparaisons riches ». La correspondance entre les symboles opérateurs et les noms de méthodes est la suivante : x<y appelle x.__lt__(y), x<=y appelle x.__le__(y), x==y appelle x.__eq__(y), x!=y appelle x.__ne__(y), x>y appelle x.__gt__(y) et x>=y appelle x.__ge__(y).

Une méthode de comparaison riche peut renvoyer le singleton NotImplemented si elle n’implémente pas l’opération pour une paire donnée d’arguments. Par convention, False et True sont renvoyées pour une comparaison qui a réussi. Cependant, ces méthodes peuvent renvoyer n’importe quelle valeur donc, si l’opérateur de comparaison est utilisé dans un contexte booléen (par exemple dans une condition d’une instruction if), Python appelle bool() sur la valeur pour déterminer si le résultat est faux ou vrai.

Par défaut, __ne__() délègue à __eq__() et renvoie le résultat inverse, sauf si c’est NotImplemented. Il n’y a pas d’autres relations implicites pour les opérateurs de comparaison. Par exemple, (x<y or x==y) n’implique pas x<=y. Pour obtenir une relation d’ordre total automatique à partir d’une seule opération, reportez-vous à functools.total_ordering().

Lisez le paragraphe __hash__() pour connaitre certaines notions importantes relatives à la création d’objets hashable qui acceptent les opérations de comparaison personnalisées et qui sont utilisables en tant que clés de dictionnaires.

Il n’y a pas de versions avec les arguments interchangés de ces méthodes (qui seraient utilisées quand l’argument de gauche ne connaît pas l’opération alors que l’argument de droite la connaît) ; en lieu et place, __lt__() et __gt__() sont la réflexion l’une de l’autre, __le__() et __ge__() sont la réflexion l’une de l’autre et __eq__() ainsi que __ne__() sont réflexives. Si les opérandes sont de types différents et que l’opérande de droite est d’un type qui une sous-classe directe ou indirecte du type de l’opérande de gauche, alors la méthode symétrique de l’opérande de droite est prioritaire, sinon c’est la méthode de l’opérande de gauche qui est prioritaire. Les sous-classes virtuelles ne sont pas prises en compte.

object.__hash__(self)

Appelée par la fonction native hash() et par les opérations sur les membres de collections hachées (ce qui comprend set, frozenset et dict). __hash__() doit renvoyer un entier. La seule propriété requise est que les objets qui sont égaux pour la comparaison doivent avoir la même valeur de hachage ; il est conseillé de mélanger les valeurs de hachage des composants d’un objet qui jouent un rôle de la comparaison des objets, en les plaçant un tuple dont on calcule l’empreinte. Par exemple :

def __hash__(self):
    return hash((self.name, self.nick, self.color))

Note

hash() limite la valeur renvoyée d’un objet ayant une méthode __hash__() personnalisée à la taille d’un Py_ssize_t. C’est classiquement 8 octets pour une implémentation 64 bits et 4 octets sur une implémentation 32 bits. Si la méthode __hash__() d’un objet doit être interopérable sur des plateformes ayant des implémentations différentes, assurez-vous de vérifier la taille du hachage sur toutes les plateformes. Une manière facile de le faire est la suivante : python -c "import sys; print(sys.hash_info.width)".

Si une classe ne définit pas de méthode __eq__(), elle ne doit pas définir l’opération __hash__() non plus ; si elle définit __eq__() mais pas __hash__(), les instances ne peuvent pas être utilisées en tant qu’élément dans une collection de hachables. Si une classe définit des objets mutables et implémente la méthode __eq__(), elle ne doit pas implémenter __hash__() puisque l’implémentation des collections hachables requiert que les clés soient des empreintes immuables (si l’empreinte d’un objet change, il ne sera plus trouvé correctement dans le stockage du dictionnaire).

Les classes définies par l’utilisateur possèdent des méthodes __eq__() et __hash__() par défaut ; ces méthodes répondent que tous les objets sont différents (sauf avec eux-mêmes) et x.__hash__() renvoie une valeur telle que x == y implique à la fois x is y et hash(x) == hash(y).

Une classe qui surcharge __eq__() et qui ne définit pas __hash__() a sa méthode __hash__() implicitement assignée à None. Quand la méthode __hash__() d’une classe est None, une instance de cette classe lève TypeError quand un programme essaie de demander son empreinte et elle est correctement identifiée comme non hachable quand on vérifie isinstance(obj, collections.Hashable).

Si une classe qui surcharge __eq__() a besoin de conserver l’implémentation de __hash__() de la classe parente, vous devez l’indiquer explicitement à l’interpréteur en définissant __hash__ = <ClasseParente>.__hash__.

Si une classe ne surcharge pas __eq__() et veut supprimer le calcul des empreintes, elle doit inclure __hash__ = None dans la définition de la classe. Une classe qui définit sa propre méthode __hash__() qui lève explicitement TypeError serait incorrectement identifiée comme hachable par un appel à isinstance(obj, collections.Hashable).

Note

Par défaut, les valeurs renvoyées par __hash__() pour les chaînes, bytes et objets datetime sont salées avec une valeur aléatoire non prévisible. Bien qu’une empreinte reste constante tout au long d’un processus Python, sa valeur n’est pas prévisible entre deux invocations de Python.

C’est un comportement voulu pour se protéger contre un déni de service qui utiliserait des entrées malicieusement choisies pour effectuer des insertions dans le dictionnaire dans le pire cas, avec une complexité en O(n^2). Lisez http://www.ocert.org/advisories/ocert-2011-003.html pour en obtenir les détails (article en anglais).

Modifier les empreintes obtenues par hachage modifie l’ordre d’itération sur les dictionnaires, les ensembles et les autres tableaux de correspondances. Python n’a jamais donné de garantie sur cet ordre (d’ailleurs, l’ordre n’est pas le même entre les implémentations 32 et 64 bits).

Voir aussi PYTHONHASHSEED.

Modifié dans la version 3.3: la randomisation des empreintes est activée par défaut.

object.__bool__(self)

Appelée pour implémenter les tests booléens et l’opération native bool() ; elle doit renvoyer False ou True. Quand cette méthode n’est pas définie, __len__() est appelée, si elle est définie, et l’objet est considéré vrai si le résultat est non nul. Si une classe ne définit ni __len__() ni __bool__(), toutes ses instances sont considérées comme vraies.

3.3.2. Personnalisation de l’accès aux attributs

Les méthodes suivantes peuvent être définies pour personnaliser l’accès aux attributs (utilisation, assignation, suppression de x.name) pour les instances de classes.

object.__getattr__(self, name)

Appelée lorsque l’accès par défaut à l’attribut échoue en levant AttributeError (soit __getattribute__() lève AttributeError car name n’est pas un attribut de l’instance ou un attribut dans l’arborescence de la classe de self ; ou __get__() de la propriété name lève AttributeError). Cette méthode doit retourner soit la valeur (calculée) de l’attribut, soit lever une exception AttributeError.

Notez que si l’attribut est trouvé par le mécanisme normal, __getattr__() n’est pas appelée (c’est une asymétrie voulue entre __getattr__() et __setattr__()). Ce comportement est adopté à la fois pour des raisons de performance et parce que, sinon, __getattr__() n’aurait aucun moyen d’accéder aux autres attributs de l’instance. Notez que, au moins pour ce qui concerne les variables d’instance, vous pouvez simuler un contrôle total en n’insérant aucune valeur dans le dictionnaire des attributs de l’instance (mais en les insérant dans un autre objet à la place). Lisez la partie relative à la méthode __getattribute__() ci-dessous pour obtenir un contrôle total effectif sur l’accès aux attributs.

object.__getattribute__(self, name)

Appelée de manière inconditionnelle pour implémenter l’accès aux attributs des instances de la classe. Si la classe définit également __getattr__(), cette dernière n’est pas appelée à moins que __getattribute__() ne l’appelle explicitement ou ne lève une exception AttributeError. Cette méthode doit renvoyer la valeur (calculée) de l’attribut ou lever une exception AttributeError. Afin d’éviter une récursion infinie sur cette méthode, son implémentation doit toujours appeler la méthode de la classe de base avec le même paramètre name pour accéder à n’importe quel attribut dont elle a besoin. Par exemple, object.__getattribute__(self, name).

Note

Cette méthode peut être shuntée lorsque la recherche porte sur les méthodes spéciales en tant que résultat d’une invocation implicite via la syntaxe du langage ou les fonctions natives. Lisez Recherche des méthodes spéciales.

object.__setattr__(self, name, value)

Appelée lors d’une assignation d’attribut. Elle est appelée à la place du mécanisme normal (c’est-à-dire stocker la valeur dans le dictionnaire de l’instance). name est le nom de l’attribut, value est la valeur à assigner à cet attribut.

Si __setattr__() veut assigner un attribut d’instance, elle doit appeler la méthode de la classe de base avec le même nom, par exemple object.__setattr__(self, name, value).

object.__delattr__(self, name)

Comme __setattr__() mais pour supprimer un attribut au lieu de l’assigner. Elle ne doit être implémentée que si del obj.name a du sens pour cet objet.

object.__dir__(self)

Appelée quand dir() est appelée sur l’objet. Elle doit renvoyer une séquence. dir() convertit la séquence renvoyée en liste et effectue le classement.

3.3.2.1. Personnalisation de l’accès aux attributs d’un module

Pour une personnalisation plus fine du comportement d’un module (assignation des attributs, propriétés, etc.), vous pouvez assigner l’attribut __class__ d’un objet module à une sous-classe de types.ModuleType. Par exemple :

import sys
from types import ModuleType

class VerboseModule(ModuleType):
    def __repr__(self):
        return f'Verbose {self.__name__}'

    def __setattr__(self, attr, value):
        print(f'Setting {attr}...')
        setattr(self, attr, value)

sys.modules[__name__].__class__ = VerboseModule

Note

Définir __class__ pour le module affecte uniquement les recherches qui utilisent la syntaxe d’accès aux attributs – accéder directement aux globales d’un module (soit par le code dans le module, soit via une référence au dictionnaire des variables globales du module) fonctionne toujours de la même façon.

Modifié dans la version 3.5: l’attribut __class__ du module est maintenant en lecture-écriture.

3.3.2.2. Implémentation de descripteurs

Les méthodes qui suivent s’appliquent seulement quand une instance de la classe (dite classe descripteur) contenant la méthode apparaît dans une classe propriétaire (owner en anglais) ; la classe descripteur doit figurer dans le dictionnaire de la classe propriétaire ou dans le dictionnaire de la classe d’un des parents. Dans les exemples ci-dessous, « l’attribut » fait référence à l’attribut dont le nom est une clé du __dict__ de la classe propriétaire.

object.__get__(self, instance, owner)

Appelée pour obtenir l’attribut de la classe propriétaire (accès à un attribut de classe) ou d’une instance de cette classe (accès à un attribut d’instance). owner est toujours la classe propriétaire alors que instance est l’instance par laquelle on accède à l’attribut ou None lorsque l’on accède par la classe owner. Cette méthode doit renvoyer la valeur (calculée) de l’attribut ou lever une exception AttributeError.

object.__set__(self, instance, value)

Appelée pour définir l’attribut d’une instance instance de la classe propriétaire à la nouvelle valeur value.

object.__delete__(self, instance)

Appelée pour supprimer l’attribut de l’instance instance de la classe propriétaire.

object.__set_name__(self, owner, name)

Appelée au moment où la classe propriétaire owner est créée. La classe descripteur a été assignée à name.

Nouveau dans la version 3.6.

L’attribut __objclass__ est interprété par le module inspect comme spécifiant la classe où cet objet a été défini (le définir correctement peut vous aider dans l’introspection des classes dynamiques à l’exécution). Pour les appelables, cela peut indiquer qu’une instance d’un certain type (ou d’une certaine sous-classe) est attendue ou requise comme premier argument positionnel (par exemple, CPython définit cet attribut pour les méthodes non liées qui sont implémentées en C).

3.3.2.3. Invocation des descripteurs

En général, un descripteur est un attribut d’objet dont le comportement est « lié » (binding dehavior en anglais), c’est-à-dire que les accès aux attributs ont été surchargés par des méthodes conformes au protocole des descripteurs : __get__(), __set__() et __delete__(). Si l’une de ces méthodes est définie pour un objet, il est réputé être un descripteur.

Le comportement par défaut pour la gestion d’un attribut est de définir, obtenir et supprimer cet attribut du dictionnaire de l’objet. Par exemple, pour a.x Python commence d’abord par rechercher a.__dict__['x'], puis type(a).__dict__['x'] ; ensuite Python continue en remontant les classes de base de type(a), en excluant les méta-classes.

Cependant, si la valeur cherchée est un objet qui définit une des méthodes de descripteur, alors Python modifie son comportement et invoque la méthode du descripteur à la place. Le moment où cela intervient dans la recherche citée ci-dessus dépend de l’endroit où a été définie la méthode de descripteur et comment elle a été appelée.

Le point de départ pour une invocation de descripteur est la liaison a.x. La façon dont les arguments sont assemblés dépend de a :

Appel direct

Le plus simple et le plus rare des appels est quand l’utilisateur code directement l’appel à la méthode du descripteur : x.__get__(a).

Liaison avec une instance

Si elle est liée à un objet instance, a.x est transformé en l’appel suivant : type(a).__dict__['x'].__get__(a, type(a)).

Liaison avec une classe

Si elle est liée à une classe, A.x est transformé en l’appel suivant : A.__dict__['x'].__get__(None, A).

Liaison super

Si a est une instance de super, alors super(B, obj).m() recherche obj.__class__.__mro__ pour la classe de base A immédiatement avant B puis invoque le descripteur avec l’appel suivant : A.__dict__['m'].__get__(obj, obj.__class__).

Pour des liaisons avec des instances, la priorité à l’invocation du descripteur dépend des méthodes que le descripteur a définies. Un descripteur peut définir n’importe quelle combinaison de __get__(), __set__() et __delete__(). S’il ne définit pas __get__(), alors accéder à l’attribut retourne l’objet descripteur lui-même sauf s’il existe une valeur dans le dictionnaire de l’objet instance. Si le descripteur définit __set__() ou __delete__(), c’est un descripteur de données ; s’il ne définit aucune méthode, c’est un descripteur hors-donnée. Normalement, les descripteurs de données définissent à la fois __get__() et __set__(), alors que les descripteurs hors-données définissent seulement la méthode __get__(). Les descripteurs de données qui définissent __set__() et __get__() sont toujours prioritaires face à une redéfinition du dictionnaire de l’instance. En revanche, les descripteurs hors-données peuvent être shuntés par les instances.

Les méthodes Python (y compris staticmethod() et classmethod()) sont implémentées comme des descripteurs hors-donnée. De la même manière, les instances peuvent redéfinir et surcharger les méthodes. Ceci permet à chaque instance d’avoir un comportement qui diffère des autres instances de la même classe.

La fonction property() est implémentée en tant que descripteur de données. Ainsi, les instances ne peuvent pas surcharger le comportement d’une propriété.

3.3.2.4. __slots__

Les __slots__ vous permettent de déclarer des membres d’une donnée (comme une propriété) et d’interdire la création de __dict__ ou de __weakref__ (à moins qu’ils ne soient explicitement déclarés dans le __slots__ ou présent dans le parent).

L’espace gagné par rapport à l’utilisation d’un __dict__ peut être significatif.

object.__slots__

Cette variable de classe peut être assignée avec une chaîne, un itérable ou une séquence de chaînes avec les noms de variables utilisés par les instances. __slots__ réserve de la place pour ces variables déclarées et interdit la création automatique de __dict__ et __weakref__ pour chaque instance.

3.3.2.4.1. Note sur l’utilisation de __slots__

Lorsque vous héritez d’une classe sans __slots__, les attributs __dict__ et __weakref__ des instances sont toujours accessibles.

Sans variable __dict__, les instances ne peuvent pas assigner de nouvelles variables (non listées dans la définition de __slots__). Les tentatives d’assignation sur un nom de variable non listé lève AttributeError. Si l’assignation dynamique de nouvelles variables est nécessaire, ajoutez '__dict__' à la séquence de chaînes dans la déclaration __slots__.

Sans variable __weakref__ pour chaque instance, les classes qui définissent __slots__ ne gèrent pas les références faibles vers leurs instances. Si vous avez besoin de gérer des références faibles, ajoutez '__weakref__' à la séquence de chaînes dans la déclaration de __slots__.

Les __slots__ sont implémentés au niveau de la classe en créant des descripteurs (Implémentation de descripteurs) pour chaque nom de variable. Ainsi, les attributs de classe ne peuvent pas être utilisés pour des valeurs par défaut aux variables d’instances définies par __slots__ ; sinon, l’attribut de classe surchargerait l’assignation par descripteur.

L’action de la déclaration du __slots__ ne se limite pas à la classe où il est défini. Les __slots__ déclarés par les parents sont disponibles dans les classes enfants. Cependant, les sous-classes enfants ont un __dict__ et un __weakref__ à moins qu’elles ne définissent aussi un __slots__ (qui ne doit contenir alors que les noms supplémentaires du slot).

Si une classe définit un slot déjà défini dans une classe de base, la variable d’instance définie par la classe de base est inaccessible (sauf à utiliser le descripteur de la classe de base directement). Cela rend la signification du programme indéfinie. Dans le futur, une vérification sera ajoutée pour empêcher cela.

Un __slot__ non vide ne fonctionne pas pour les classes dérivées des types natifs à longueur variable tels que int, bytes et tuple.

Tout itérable qui n’est pas une chaîne peut être assigné à un __slots__. Les tableaux de correspondance peuvent aussi être utilisés ; cependant, dans le futur, des significations spéciales pourraient être associées à chacune des clés.

Les assignations de __class__ ne fonctionnent que si les deux classes ont le même __slots__.

L’héritage multiple avec plusieurs classes parentes qui ont des __slots__ est possible, mais seul un parent peut avoir des attributs créés par __slots__ (les autres classes parentes doivent avoir des __slots__ vides). La violation de cette règle lève TypeError.

3.3.3. Personnalisation de la création de classes

Quand une classe hérite d’une classe parente, __init_subclass__ de la classe parente est appelée. Ainsi, il est possible d’écrire des classes qui modifient le comportement des sous-classes. Ce comportement est corrélé aux décorateurs de classes mais, alors que les décorateurs de classes agissent seulement sur la classe qu’ils décorent, __init_subclass__ agit uniquement sur les futures sous-classes de la classe qui définit cette méthode.

classmethod object.__init_subclass__(cls)

Cette méthode est appelée quand la classe est sous-classée. cls est alors la nouvelle sous-classe. Si elle est définie en tant que méthode d’instance normale, cette méthode est implicitement convertie en méthode de classe.

Les arguments nommés qui sont donnés à la nouvelle classe sont passés à __init_subclass__ de la classe parente. Par souci de compatibilité avec les autres classes qui utilisent __init_subclass__, vous devez enlever les arguments nommés dont vous avez besoin et passer les autres à la classe de base, comme ci-dessous :

class Philosopher:
    def __init_subclass__(cls, default_name, **kwargs):
        super().__init_subclass__(**kwargs)
        cls.default_name = default_name

class AustralianPhilosopher(Philosopher, default_name="Bruce"):
    pass

L’implémentation par défaut object.__init_subclass__ ne fait rien mais lève une erreur si elle est appelée avec un argument.

Note

L’indication de méta-classe metaclass est absorbée par le reste du mécanisme de types et n’est jamais passée à l’implémentation de __init_subclass__. La méta-classe réelle (plutôt que l’indication explicite) peut être récupérée par type(cls).

Nouveau dans la version 3.6.

3.3.3.1. Méta-classes

Par défaut, les classes sont construites en utilisant type(). Le corps de la classe est exécuté dans un nouvel espace de nommage et le nom de la classe est lié localement au résultat de type(name, bases, namespace)`.

Le déroulement de création de la classe peut être personnalisé en passant l’argument nommé metaclass dans la ligne de définition de la classe ou en héritant d’une classe existante qui comporte déjà un tel argument. Dans l’exemple qui suit, MyClass et MySubclass sont des instances de Meta :

class Meta(type):
    pass

class MyClass(metaclass=Meta):
    pass

class MySubclass(MyClass):
    pass

Tout autre argument nommé spécifié dans la définition de la classe est passé aux opérations de méta-classes décrites auparavant.

Quand la définition d’une classe est exécutée, les différentes étapes suivies sont :

la méta-classe appropriée est déterminée ;

l’espace de noms de la classe est préparé ;

le corps de la classe est exécuté ;

l’objet classe est crée.

3.3.3.2. Détermination de la méta-classe appropriée

La méta-classe appropriée pour une définition de classe est déterminée de la manière suivante :

si aucune classe et aucune méta-classe n’est donnée, alors type() est utilisée ;

si une méta-classe explicite est donnée et que ce n’est pas une instance de type(), alors elle est utilisée directement en tant que méta-classe ;

Si une instance de type() est donnée comme méta-classe explicite ou si bases est définie, alors la méta-classe la plus dérivée est utilisée.

La méta-classe la plus dérivée est choisie à partir des méta-classes explicitement spécifiées (s’il y en a) et les méta-classes (c’est-à-dire les type(cls)) de toutes les classes de base spécifiées. La méta-classe la plus dérivée est celle qui est un sous-type de toutes ces méta-classes candidates. Si aucune des méta-classes candidates ne remplit ce critère, alors la définition de la classe échoue en levant TypeError.

3.3.3.3. Préparation de l’espace de nommage de la classe

Une fois que la méta-classe appropriée est identifiée, l’espace de nommage de la classe est préparé. Si la méta-classe possède un attribut __prepare__, il est appelé avec namespace = metaclass.__prepare__(name, bases, **kwds) (où les arguments nommés supplémentaires, s’il y en a, viennent de la définition de la classe).

Si la méta-classe ne possède pas d’attribut __prepare__, alors l’espace de nommage de la classe est initialisé en tant que tableau de correspondances ordonné.

Voir aussi

PEP 3115 [https://www.python.org/dev/peps/pep-3115] — Méta-classes dans Python 3000

introduction de la fonction automatique __prepare__ de l’espace de nommage

3.3.3.4. Exécution du corps de la classe

Le corps de la classe est exécuté (approximativement) avec exec(body, globals(), namespace). La principale différence avec un appel normal à exec() est que la portée lexicale autorise le corps de la classe (y compris les méthodes) à faire référence aux noms de la portée courante et des portées externes lorsque la définition de classe a lieu dans une fonction.

Cependant, même quand une définition de classe intervient dans une fonction, les méthodes définies à l’intérieur de la classe ne peuvent pas voir les noms définis en dehors de la portée de la classe. On accède aux variables de la classe via le premier paramètre des méthodes d’instance ou de classe, ou via la référence implicite __class__ incluse dans la portée lexicale et décrite dans la section suivante.

3.3.3.5. Création de l’objet classe

Quand l’espace de nommage a été rempli en exécutant le corps de la classe, l’objet classe est créé en appelant metaclass(name, bases, namespace, **kwds) (les arguments nommés supplémentaires passés ici sont les mêmes que ceux passés à __prepare__).

Cet objet classe est celui qui est référencé par la forme sans argument de super(). __class__ est une référence implicite créée par le compilateur si une méthode du corps de la classe fait référence soit à __class__, soit à super. Ceci permet que la forme sans argument de super() identifie la classe en cours de définition en fonction de la portée lexicale, tandis que la classe ou l’instance utilisée pour effectuer l’appel en cours est identifiée en fonction du premier argument transmis à la méthode.

CPython implementation detail: Dans CPython 3.6 et suivants, la cellule __class__ est passée à la méta-classe en tant qu’entrée __classcell__ dans l’espace de nommage de la classe. Si elle est présente, elle doit être propagée à l’appel type .__ new__ pour que la classe soit correctement initialisée. Ne pas le faire se traduit par un avertissement DeprecationWarning dans Python 3.6 et un RuntimeError dans Python 3.8.

Quand vous utilisez la méta-classe par défaut type ou toute autre méta-classe qui finit par appeler type.__new__, les étapes de personnalisation supplémentaires suivantes sont suivies après la création de l’objet classe :

d’abord, type.__new__ récupère, dans l’espace de nommage de la classe, tous les descripteurs qui définissent une méthode __set_name__() ;

ensuite, toutes ces méthodes __set_name__ sont appelées avec la classe en cours de définition et le nom assigné à chaque descripteur ;

finalement, la méthode automatique __init_subclass__() est appelée sur le parent immédiat de la nouvelle classe en utilisant l’ordre de résolution des méthodes.

Après la création de l’objet classe, il est passé aux décorateurs de la classe, y compris ceux inclus dans la définition de la classe (s’il y en a) et l’objet résultant est lié à l’espace de nommage local en tant que classe définie.

Quand une nouvelle classe est créée via type.__new__, l’objet fourni en tant que paramètre d’espace de nommage est copié vers un nouveau tableau de correspondances ordonné et l’objet original est laissé de côté. La nouvelle copie est encapsulée dans un mandataire en lecture seule qui devient l’attribut __dict__ de l’objet classe.

Voir aussi

PEP 3135 [https://www.python.org/dev/peps/pep-3135] — Nouvelle méthode super

Décrit la référence à la fermeture (closure en anglais) de la __class__ implicite

3.3.3.6. Uses for metaclasses

Les utilisations possibles des méta-classes sont immenses. Quelques pistes ont déjà été explorées comme l’énumération, la gestion des traces, le contrôle des interfaces, la délégation automatique, la création automatique de propriétés, les mandataires, les frameworks ainsi que le verrouillage ou la synchronisation automatique de ressources.

3.3.4. Personnalisation des instances et vérification des sous-classes

Les méthodes suivantes sont utilisées pour surcharger le comportement par défaut des fonctions natives isinstance() et issubclass().

En particulier, la méta-classe abc.ABCMeta implémente ces méthodes pour autoriser l’ajout de classes de base abstraites (ABC pour Abstract Base Classes en anglais) en tant que « classes de base virtuelles » pour toute classe ou type (y compris les types natifs).

class.__instancecheck__(self, instance)

Renvoie True si instance doit être considérée comme une instance (directe ou indirecte) de class. Si elle est définie, elle est appelée pour implémenter isinstance(instance, class).

class.__subclasscheck__(self, subclass)

Renvoie True si subclass doit être considérée comme une sous-classe (directe ou indirecte) de class. Si elle est définie, appelée pour implémenter issubclass(subclass, class).

Notez que ces méthodes sont recherchées dans le type (la méta-classe) d’une classe. Elles ne peuvent pas être définies en tant que méthodes de classe dans la classe réelle. C’est cohérent avec la recherche des méthodes spéciales qui sont appelées pour les instances, sauf qu’ici l’instance est elle-même une classe.

Voir aussi

PEP 3119 [https://www.python.org/dev/peps/pep-3119] — Introduction aux classes de bases abstraites

Inclut la spécification pour la personnalisation du comportement de isinstance() et issubclass() à travers __instancecheck__() et __subclasscheck__(), avec comme motivation pour cette fonctionnalité l’ajout les classes de base abstraites (voir le module abc) au langage.

3.3.5. Émulation d’objets appelables

object.__call__(self[, args...])

Appelée quand l’instance est « appelée » en tant que fonction ; si la méthode est définie, x(arg1, arg2, ...) est un raccourci pour x.__call__(arg1, arg2, ...).

3.3.6. Émulation de types conteneurs

Les fonctions suivantes peuvent être définies pour implémenter des objets conteneurs. Les conteneurs sont habituellement des séquences (telles que les tuples ou les listes) ou des tableaux de correspondances (comme les dictionnaires), mais ils peuvent aussi représenter d’autres conteneurs. Le premier ensemble de méthodes est utilisé soit pour émuler une séquence, soit pour émuler un tableau de correspondances ; la différence est que, pour une séquence, les clés doivent être soit des entiers k tels que 0 <= k < N où N est la longueur de la séquence, soit des objets tranches qui définissent un intervalle d’éléments. Il est aussi recommandé que les tableaux de correspondances fournissent les méthodes keys(), values(), items(), get(), clear(), setdefault(), pop(), popitem(), copy() et update() avec un comportement similaire aux objets dictionnaires standards de Python. Le module collections fournit une classe de base abstraite MutableMapping pour aider à la création de ces méthodes à partir d’un ensemble de base composé de __getitem__(), __setitem__(), __delitem__() et keys(). Les séquences muables doivent fournir les méthodes append(), count(), index(), extend(), insert(), pop(), remove(), reverse() et sort(), comme les objets listes standards de Python. Enfin, les types séquences doivent implémenter l’addition (dans le sens de la concaténation) et la multiplication (dans le sens de la répétition) en définissant les méthodes __add__(), __radd__(), __iadd__(), __mul__(), __rmul__() et __imul__() décrites ci-dessous ; ils ne doivent pas définir d’autres opérateurs numériques. Il est recommandé que les tableaux de correspondances et les séquences implémentent la méthode __contains__() pour permettre l’utilisation efficace de l’opérateur in ; concernant les tableaux de correspondances, in doit rechercher dans les clés du tableau ; pour les séquences, il doit chercher dans les valeurs. Il est de plus recommandé que les tableaux de correspondances et les séquences implémentent la méthode __iter__() pour permettre une itération efficace dans le conteneur ; pour les tableaux de correspondances, __iter__() doit être la même que keys() ; pour les séquences, elle doit itérer sur les valeurs.

object.__len__(self)

Appelée pour implémenter la fonction native len(). Elle doit renvoyer la longueur de l’objet, un entier >= 0. Par ailleurs, un objet qui ne définit pas de méthode __bool__() et dont la méthode __len__() renvoie zéro est considéré comme valant False dans un contexte booléen.

CPython implementation detail: En CPython, la longueur doit valoir au maximum sys.maxsize. Si la longueur est plus grande que sys.maxsize, des propriétés (telles que len()) peuvent lever OverflowError. Afin d’éviter de lever OverflowError lors de tests booléens, un objet doit définir la méthode __bool__().

object.__length_hint__(self)

Appelée pour implémenter operator.length_hint(). Elle doit renvoyer une longueur estimée de l’objet (qui peut être plus grande ou plus petite que la longueur réelle). La longueur doit être un entier >= 0. Cette méthode est utilisée uniquement pour optimiser les traitements et n’est jamais tenue de renvoyer un résultat exact.

Nouveau dans la version 3.4.

Note

Le découpage est effectué uniquement à l’aide des trois méthodes suivantes. Un appel comme

a[1:2] = b

est traduit en

a[slice(1, 2, None)] = b

et ainsi de suite. Les éléments manquants sont remplacés par None.

object.__getitem__(self, key)

Appelée pour implémenter l’évaluation de self[key]. Pour les types séquences, les clés autorisées sont les entiers et les objets tranches (slice). Notez que l’interprétation spéciale des indices négatifs (si la classe souhaite émuler un type séquence) est du ressort de la méthode __getitem__(). Si key n’est pas du bon type, une TypeError peut être levée ; si la valeur est en dehors de l’ensemble des indices de la séquence (après interprétation éventuelle des valeurs négatives), une IndexError doit être levée. Pour les tableaux de correspondances, si key n’existe pas dans le conteneur, une KeyError doit être levée.

Note

for s’attend à ce qu’une IndexError soit levée en cas d’indice illégal afin de détecter correctement la fin de la séquence.

object.__setitem__(self, key, value)

Appelée pour implémenter l’assignation à self[key]. La même note que pour __getitem__() s’applique. Elle ne doit être implémentée que pour les tableaux de correspondances qui autorisent les modifications de valeurs des clés, ceux pour lesquels on peut ajouter de nouvelles clés ou, pour les séquences, celles dont les éléments peuvent être remplacés. Les mêmes exceptions que pour la méthode __getitem__() doivent être levées en cas de mauvaises valeurs de clés.

object.__delitem__(self, key)

Appelée pour implémenter la suppression de self[key]. La même note que pour __getitem__() s’applique. Elle ne doit être implémentée que pour les tableaux de correspondances qui autorisent les suppressions de clés ou pour les séquences dont les éléments peuvent être supprimés de la séquence. Les mêmes exceptions que pour la méthode __getitem__() doivent être levées en cas de mauvaises valeurs de clés.

object.__missing__(self, key)

Appelée par dict.__getitem__() pour implémenter self[key] dans les sous-classes de dictionnaires lorsque la clé n’est pas dans le dictionnaire.

object.__iter__(self)

Cette méthode est appelée quand un itérateur est requis pour un conteneur. Cette méthode doit renvoyer un nouvel objet itérateur qui peut itérer sur tous les objets du conteneur. Pour les tableaux de correspondances, elle doit itérer sur les clés du conteneur.

Les objets itérateurs doivent aussi implémenter cette méthode ; ils doivent alors se renvoyer eux-mêmes. Pour plus d’information sur les objets itérateurs, lisez Les types itérateurs.

object.__reversed__(self)

Appelée (si elle existe) par la fonction native reversed() pour implémenter l’itération en sens inverse. Elle doit renvoyer un nouvel objet itérateur qui itère sur tous les objets du conteneur en sens inverse.

Si la méthode __reversed__() n’est pas fournie, la fonction native reversed() se replie sur le protocole de séquence (__len__() et __getitem__()). Les objets qui connaissent le protocole de séquence ne doivent fournir __reversed__() que si l’implémentation qu’ils proposent est plus efficace que celle de reversed().

Les opérateurs de tests d’appartenance (in et not in) sont normalement implémentés comme des itérations sur la séquence. Cependant, les objets conteneurs peuvent fournir les méthodes spéciales suivantes avec une implémentation plus efficace, qui ne requièrent d’ailleurs pas que l’objet soit une séquence.

object.__contains__(self, item)

Appelée pour implémenter les opérateurs de test d’appartenance. Elle doit renvoyer True si item est dans self et False sinon. Pour les tableaux de correspondances, seules les clés sont considérées (pas les valeurs des paires clés-valeurs).

Pour les objets qui ne définissent pas __contains__(), les tests d’appartenance essaient d’abord d’itérer avec __iter__() puis avec le vieux protocole d’itération sur les séquences via __getitem__(), reportez-vous à cette section dans la référence du langage.

3.3.7. Émulation de types numériques

Les méthodes suivantes peuvent être définies pour émuler des objets numériques. Les méthodes correspondant à des opérations qui ne sont pas autorisées pour la catégorie de nombres considérée (par exemple, les opérations bit à bit pour les nombres qui ne sont pas entiers) doivent être laissées indéfinies.

object.__add__(self, other)

object.__sub__(self, other)

object.__mul__(self, other)

object.__matmul__(self, other)

object.__truediv__(self, other)

object.__floordiv__(self, other)

object.__mod__(self, other)

object.__divmod__(self, other)

object.__pow__(self, other[, modulo])

object.__lshift__(self, other)

object.__rshift__(self, other)

object.__and__(self, other)

object.__xor__(self, other)

object.__or__(self, other)

Ces méthodes sont appelées pour implémenter les opérations arithmétiques binaires (+, -, *, @, /, //, %, divmod(), pow(), **, <<, >>, &, ^, |). Par exemple, pour évaluer l’expression x + y, où x est une instance d’une classe qui possède une méthode __add__(), x.__add__(y) est appelée. La méthode __divmod__() doit être l’équivalent d’appeler __floordiv__() et __mod__() ; elle ne doit pas être reliée à __truediv__(). Notez que __pow__() doit être définie de manière à accepter un troisième argument optionnel si la version ternaire de la fonction native pow() est autorisée.

Si l’une de ces méthodes n’autorise pas l’opération avec les arguments donnés, elle doit renvoyer NotImplemented.

object.__radd__(self, other)

object.__rsub__(self, other)

object.__rmul__(self, other)

object.__rmatmul__(self, other)

object.__rtruediv__(self, other)

object.__rfloordiv__(self, other)

object.__rmod__(self, other)

object.__rdivmod__(self, other)

object.__rpow__(self, other)

object.__rlshift__(self, other)

object.__rrshift__(self, other)

object.__rand__(self, other)

object.__rxor__(self, other)

object.__ror__(self, other)

Ces méthodes sont appelées pour implémenter les opérations arithmétiques binaires (+, -, *, @, /, //, %, divmod(), pow(), **, <<, >>, &, ^, |) avec des opérandes renversés (intervertis). Ces fonctions ne sont appelées que si l’opérande de gauche n’autorise pas l’opération correspondante 3 et si les opérandes sont de types différents 4. Par exemple, pour évaluer l’expression x - y, où y est une instance d’une classe qui possède une méthode __rsub__(), y.__rsub__(x) est appelée si x.__sub__(y) renvoie NotImplemented.

Notez que la fonction ternaire pow() n’essaie pas d’appeler __rpow__() (les règles de coercition seraient trop compliquées).

Note

Si le type de l’opérande de droite est une sous-classe du type de l’opérande de gauche et que cette sous-classe fournit la méthode symétrique pour l’opération, cette méthode sera appelée avant la méthode originelle de l’opérande gauche. Ce comportement permet à des sous-classes de surcharger les opérations de leurs ancêtres.

object.__iadd__(self, other)

object.__isub__(self, other)

object.__imul__(self, other)

object.__imatmul__(self, other)

object.__itruediv__(self, other)

object.__ifloordiv__(self, other)

object.__imod__(self, other)

object.__ipow__(self, other[, modulo])

object.__ilshift__(self, other)

object.__irshift__(self, other)

object.__iand__(self, other)

object.__ixor__(self, other)

object.__ior__(self, other)

Ces méthodes sont appelées pour implémenter les assignations arithmétiques augmentées (+=, -=, *=, @=, /=, //=, %=, **=, <<=, >>=, &=, ^=, |=). Ces méthodes doivent essayer d’effectuer l’opération « sur place » (c’est-à-dire de modifier self) et de renvoyer le résultat (qui peut être, mais pas nécessairement, self). Si une méthode spécifique n’est pas définie, l’assignation augmentée se replie vers la méthode normale correspondante. Par exemple, si x est une instance d’une classe qui possède une méthode __iadd__(), x += y est équivalent à x = x.__iadd__(y) . Sinon, x.__add__(y) et y.__radd__(x) sont essayées, comme pour l’évaluation de x + y. Dans certaines situations, les assignations augmentées peuvent causer des erreurs inattendues (voir Pourquoi a_tuple[i] += ['item'] lève-t-il une exception alors que l’addition fonctionne ?), mais ce comportement est en fait partie intégrante du modèle de données.

object.__neg__(self)

object.__pos__(self)

object.__abs__(self)

object.__invert__(self)

Appelée pour implémenter les opérations arithmétiques unaires (-, +, abs() et ~).

object.__complex__(self)

object.__int__(self)

object.__float__(self)

Appelées pour implémenter les fonctions natives complex(), int() et float(). Elles doivent renvoyer une valeur du type approprié.

object.__index__(self)

Appelée pour implémenter operator.index() et lorsque Python a besoin de convertir sans perte un objet numérique en objet entier (pour un découpage ou dans les fonctions natives bin(), hex() et oct()). La présence de cette méthode indique que l’objet numérique est un type entier. Elle doit renvoyer un entier.

Note

Afin d’avoir un type de classe entier cohérent, lorsque __index__() est définie alors __int__() doit aussi être définie et les deux doivent renvoyer la même valeur.

object.__round__(self[, ndigits])

object.__trunc__(self)

object.__floor__(self)

object.__ceil__(self)

Appelée pour implémenter la fonction native round() et les fonctions du module math trunc(), floor() et ceil(). À moins que ndigits ne soit passé à __round__(), toutes ces méthodes doivent renvoyer la valeur de l’objet tronquée pour donner un Integral (typiquement un int).

Si __int__() n’est pas définie, alors la fonction native int() se replie sur __trunc__().

3.3.8. Gestionnaire de contexte With

Un gestionnaire de contexte est un objet qui met en place un contexte prédéfini au moment de l’exécution de l’instruction with. Le gestionnaire de contexte gère l’entrée et la sortie de ce contexte d’exécution pour tout un bloc de code. Les gestionnaires de contextes sont normalement invoqués en utilisant une instruction with (décrite dans la section L’instruction with), mais ils peuvent aussi être directement invoqués par leurs méthodes.

Les utilisations classiques des gestionnaires de contexte sont la sauvegarde et la restauration d’états divers, le verrouillage et le déverrouillage de ressources, la fermeture de fichiers ouverts, etc.

Pour plus d’informations sur les gestionnaires de contexte, lisez Le type gestionnaire de contexte.

object.__enter__(self)

Entre dans le contexte d’exécution relatif à cet objet. L’instruction with lie la valeur de retour de cette méthode à une (ou plusieurs) cible spécifiée par la clause as de l’instruction, si elle est spécifiée.

object.__exit__(self, exc_type, exc_value, traceback)

Sort du contexte d’exécution relatif à cet objet. Les paramètres décrivent l’exception qui a causé la sortie du contexte. Si l’on sort du contexte sans exception, les trois arguments sont à None.

Si une exception est indiquée et que la méthode souhaite supprimer l’exception (c’est-à-dire qu’elle ne veut pas que l’exception soit propagée), elle doit renvoyer True. Sinon, l’exception est traitée normalement à la sortie de cette méthode.

Notez qu’une méthode __exit__() ne doit pas lever à nouveau l’exception qu’elle reçoit ; c’est du ressort de l’appelant.

Voir aussi

PEP 343 [https://www.python.org/dev/peps/pep-0343] — L’instruction with

La spécification, les motivations et des exemples de l’instruction with en Python.

3.3.9. Recherche des méthodes spéciales

Pour les classes définies par le développeur, l’invocation implicite de méthodes spéciales n’est garantie que si ces méthodes sont définies par le type d’objet, pas dans le dictionnaire de l’objet instance. Ce comportement explique pourquoi le code suivant lève une exception :

>>> class C:
...     pass
...
>>> c = C()
>>> c.__len__ = lambda: 5
>>> len(c)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: object of type 'C' has no len()

La raison de ce comportement vient de certaines méthodes spéciales telles que __hash__() et __repr__() qui sont implémentées par tous les objets, y compris les objets types. Si la recherche effectuée par ces méthodes utilisait le processus normal de recherche, elles ne fonctionneraient pas si on les appelait sur l’objet type lui-même :

>>> 1 .__hash__() == hash(1)
True
>>> int.__hash__() == hash(int)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: descriptor '__hash__' of 'int' object needs an argument

Essayer d’invoquer une méthode non liée d’une classe de cette manière est parfois appelé « confusion de méta-classe » et se contourne en shuntant l’instance lors de la recherche des méthodes spéciales :

>>> type(1).__hash__(1) == hash(1)
True
>>> type(int).__hash__(int) == hash(int)
True

En plus de shunter les attributs des instances pour fonctionner correctement, la recherche des méthodes spéciales implicites shunte aussi la méthode __getattribute__() même dans la méta-classe de l’objet :

>>> class Meta(type):
...     def __getattribute__(*args):
...         print("Metaclass getattribute invoked")
...         return type.__getattribute__(*args)
...
>>> class C(object, metaclass=Meta):
...     def __len__(self):
...         return 10
...     def __getattribute__(*args):
...         print("Class getattribute invoked")
...         return object.__getattribute__(*args)
...
>>> c = C()
>>> c.__len__()                 # Explicit lookup via instance
Class getattribute invoked
10
>>> type(c).__len__(c)          # Explicit lookup via type
Metaclass getattribute invoked
10
>>> len(c)                      # Implicit lookup
10

En shuntant le mécanisme de __getattribute__() de cette façon, cela permet d’optimiser la vitesse de l’interpréteur moyennant une certaine manœuvre dans la gestion des méthodes spéciales (la méthode spéciale doit être définie sur l’objet classe lui-même afin d’être invoquée de manière cohérente par l’interpréteur).

3.4. Coroutines

3.4.1. Objets attendables (awaitables)

Un objet awaitable implémente généralement une méthode __await__(). Les objets Coroutine renvoyés par les fonctions async def sont des awaitables.

Note

Les objets itérateur de générateur renvoyés par les générateurs décorés par types.coroutine() ou asyncio.coroutine() sont aussi des awaitables, mais ils n’implémentent pas __await__().

object.__await__(self)

Doit renvoyer un itérateur. Doit être utilisé pour implémenter les objets awaitable. Par exemple, asyncio.Future implémente cette méthode pour être compatible avec les expressions await.

Nouveau dans la version 3.5.

Voir aussi

PEP 492 [https://www.python.org/dev/peps/pep-0492] pour les informations relatives aux objets awaitables.

3.4.2. Objets coroutines

Les objets Coroutine sont des objets awaitable. L’exécution d’une coroutine peut être contrôlée en appelant __await__() et en itérant sur le résultat. Quand la coroutine a fini de s’exécuter et termine, l’itérateur lève StopIteration et l’attribut value de l’exception contient la valeur de retour. Si la coroutine lève une exception, elle est propagée par l’itérateur. Les coroutines ne doivent pas lever directement des exceptions StopIteration non gérées.

Les coroutines disposent aussi des méthodes listées ci-dessous, analogues à celles des générateurs (voir Méthodes des générateurs-itérateurs). Cependant, au contraire des générateurs, vous ne pouvez pas itérer directement sur des coroutines.

Modifié dans la version 3.5.2: Utiliser await plus d’une fois sur une coroutine lève une RuntimeError.

coroutine.send(value)

Démarre ou reprend l’exécution d’une coroutine. Si value est None, c’est équivalent à avancer l’itérateur renvoyé par __await__(). Si value ne vaut pas None, cette méthode appelle la méthode send() de l’itérateur qui a causé la suspension de la coroutine. Le résultat (valeur de retour, StopIteration ou une autre exception) est le même que lorsque vous itérez sur la valeur de retour de __await__(), décrite ci-dessus.

coroutine.throw(type[, value[, traceback]])

Lève l’exception spécifiée dans la coroutine. Cette méthode délègue à la méthode throw() de l’itérateur qui a causé la suspension de la coroutine, s’il possède une telle méthode. Sinon, l’exception est levée au point de suspension. Le résultat (valeur de retour, StopIteration ou une autre exception) est le même que lorsque vous itérez sur la valeur de retour de __await__(), décrite ci-dessus. Si l’exception n’est pas gérée par la coroutine, elle est propagée à l’appelant.

coroutine.close()

Demande à la coroutine de faire le ménage et de se terminer. Si la coroutine est suspendue, cette méthode délègue d’abord à la méthode close() de l’itérateur qui a causé la suspension de la coroutine, s’il possède une telle méthode. Ensuite, elle lève GeneratorExit au point de suspension, ce qui fait le ménage dans la coroutine immédiatement. Enfin, la coroutine est marquée comme ayant terminé son exécution, même si elle n’a jamais démarré.

Les objets coroutines sont automatiquement fermés en utilisant le processus décrit au-dessus au moment où ils sont détruits.

3.4.3. Itérateurs asynchrones

Un itérateur asynchrone est capable d’appeler du code asynchrone dans l’implémentation de son __aiter__ et peut appeler du code asynchrone dans sa méthode __anext__.

Les itérateurs asynchrones peuvent être utilisés dans des instructions async for.

object.__aiter__(self)

Doit renvoyer un objet itérateur asynchrone.

object.__anext__(self)

Doit renvoyer un awaitable qui se traduit par la valeur suivante de l’itérateur. Doit lever une StopAsyncIteration quand l’itération est terminée.

Un exemple d’objet itérateur asynchrone :

class Reader:
    async def readline(self):
        ...

    def __aiter__(self):
        return self

    async def __anext__(self):
        val = await self.readline()
        if val == b'':
            raise StopAsyncIteration
        return val

Nouveau dans la version 3.5.

Note

Modifié dans la version 3.5.2: À partir de CPython 3.5.2, __aiter__ peut directement renvoyer des itérateurs asynchrones. Renvoyer un objet awaitable entraine un avertissement PendingDeprecationWarning.

La façon conseillée d’écrire du code compatible descendant en CPython 3.5.x est de continuer à renvoyer des awaitables avec __aiter__. Si vous voulez éviter l’avertissement PendingDeprecationWarning et conserver un code compatible descendant, le décorateur suivant peut être utilisé :

import functools
import sys

if sys.version_info < (3, 5, 2):
    def aiter_compat(func):
        @functools.wraps(func)
        async def wrapper(self):
            return func(self)
        return wrapper
else:
    def aiter_compat(func):
        return func

Exemple :

class AsyncIterator:

    @aiter_compat
    def __aiter__(self):
        return self

    async def __anext__(self):
        ...

À partir de CPython 3.6, le PendingDeprecationWarning est remplacé par un DeprecationWarning. Dans CPython 3.7, renvoyer un awaitable avec __aiter__ entraine une RuntimeError.

3.4.4. Gestionnaires de contexte asynchrones

Un gestionnaire de contexte asynchrone est un gestionnaire de contexte qui est capable de suspendre son exécution dans ses méthodes __aenter__ et __aexit__.

Les gestionnaires de contexte asynchrones peuvent être utilisés dans des instructions async with.

object.__aenter__(self)

Cette méthode est sémantiquement équivalente à __enter__(), à la seule différence près qu’elle doit renvoyer un awaitable.

object.__aexit__(self, exc_type, exc_value, traceback)

Cette méthode est sémantiquement équivalente à __exit__(), à la seule différence près qu’elle doit renvoyer un awaitable.

Un exemple de classe de gestionnaire de contexte asynchrone :

class AsyncContextManager:
    async def __aenter__(self):
        await log('entering context')

    async def __aexit__(self, exc_type, exc, tb):
        await log('exiting context')

Nouveau dans la version 3.5.

Notes

1

Il est possible, dans certains cas, de changer le type d’un objet, sous certaines conditions. Cependant, ce n’est généralement pas une bonne idée car cela peut conduire à un comportement très étrange si ce n’est pas géré correctement.

2

Les méthodes __hash__(), __iter__(), __reversed__() et __contains__() ont une gestion particulière pour cela ; les autres lèvent toujours TypeError, mais le font en considérant que None n’est pas un appelable.

3

n’autorise pas signifie ici que la classe ne possède pas de méthode adéquate ou que la méthode renvoie NotImplemented. N’assignez pas None à la méthode si vous voulez un repli vers la méthode symétrique de l’opérande de droite — cela aurait pour effet de bloquer un tel repli.

4

Pour des opérandes de même type, on considère que si la méthode originelle (telle que __add__()) échoue, l’opération n’est pas autorisée et donc la méthode symétrique n’est pas appelée.

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4. Modèle d’exécution

4.1. Structure d’un programme

A Python program is constructed from code blocks. A block is a piece of Python program text that is executed as a unit. The following are blocks: a module, a function body, and a class definition. Each command typed interactively is a block. A script file (a file given as standard input to the interpreter or specified as a command line argument to the interpreter) is a code block. A script command (a command specified on the interpreter command line with the -c option) is a code block. The string argument passed to the built-in functions eval() and exec() is a code block.

Un bloc de code est exécuté dans un cadre d’exécution. Un cadre contient des informations administratives (utilisées pour le débogage) et détermine où et comment l’exécution se poursuit après la fin de l’exécution du bloc de code.

4.2. Noms et liaisons

4.2.1. Liaisons des noms

Les noms sont des références aux objets. Ils sont créés lors des opérations de liaisons de noms (name binding en anglais).

Les constructions suivantes conduisent à des opérations de liaison à des noms : les paramètres formels d’une fonction, les instructions import, les définitions de fonctions et de classes (le nom de la classe ou de la fonction est lié au bloc qui la définit) et les cibles qui sont des identifiants dans les assignations, les entêtes de boucles for ou après as dans une instruction with ou une clause except. L’instruction import sous la forme from ... import * lie tous les noms définis dans le module importé, sauf ceux qui commencent par un tiret bas (“_”). Cette forme ne doit être utilisée qu’au niveau du module.

Une cible qui apparaît dans une instruction del est aussi considérée comme une liaison à un nom dans ce cadre (bien que la sémantique véritable soit de délier le nom).

Chaque assignation ou instruction import a lieu dans un bloc défini par une définition de classe ou de fonction ou au niveau du module (le bloc de code de plus haut niveau).

Si un nom est lié dans un bloc, c’est une variable locale de ce bloc, à moins qu’il ne soit déclaré nonlocal ou global. Si un nom est lié au niveau du module, c’est une variable globale (les variables du bloc de code de niveau module sont locales et globales). Si une variable est utilisée dans un bloc de code alors qu’elle n’y est pas définie, c’est une variable libre.

Chaque occurrence d’un nom dans un programme fait référence à la liaison de ce nom établie par les règles de résolution des noms suivantes.

4.2.2. Résolution des noms

La portée définit la visibilité d’un nom dans un bloc. Si une variable locale est définie dans un bloc, sa portée comprend ce bloc. Si la définition intervient dans le bloc d’une fonction, la portée s’étend à tous les blocs contenus dans celui qui comprend la définition, à moins qu’un bloc intérieur ne définisse une autre liaison pour ce nom.

Quand un nom est utilisé dans un bloc de code, la résolution utilise la portée la plus petite. L’ensemble de toutes les portées visibles dans un bloc de code s’appelle l’environnement du bloc.

Quand un nom n’est trouvé nulle part, une exception NameError est levée. Si la portée courante est celle d’une fonction et que le nom fait référence à une variable locale qui n’a pas encore été liée au moment où le nom est utilisé, une exception UnboundLocalError est levée. UnboundLocalError est une sous-classe de NameError.

Si une opération de liaison intervient dans un bloc de code, toutes les utilisations du nom dans le bloc sont considérées comme des références au bloc courant. Ceci peut conduire à des erreurs quand un nom est utilisé à l’intérieur d’un bloc avant d’être lié. La règle est subtile. Python n’attend pas de déclaration de variables et autorise les opérations de liaison n’importe où dans un bloc de code. Les variables locales d’un bloc de code peuvent être déterminées en parcourant tout le texte du bloc à la recherche des opérations de liaisons.

Si l’instruction global apparaît dans un bloc, toutes les utilisations du nom spécifié dans l’instruction font référence à la liaison de ce nom dans l’espace de noms de plus haut niveau. Les noms sont résolus dans cet espace de noms de plus haut niveau en recherchant l’espace des noms globaux, c’est-à-dire l’espace de noms du module contenant le bloc de code ainsi que dans l’espace de noms natifs, celui du module builtins. La recherche commence dans l’espace de noms globaux. Si le nom n’y est pas trouvé, la recherche se poursuit dans l’espace de noms natifs. L’instruction global doit précéder toute utilisation du nom considéré.

L’instruction global a la même porte qu’une opération de liaison du même bloc. Si la portée englobante la plus petite pour une variable libre contient une instruction global, la variable libre est considérée globale.

L’instruction nonlocal fait que les noms correspondants font référence aux variables liées précédemment dans la portée de fonction englobante la plus petite possible. SyntaxError est levée à la compilation si le nom donné n’existe dans aucune portée de fonction englobante.

L’espace de nommage pour un module est créé automatiquement la première fois que le module est importé. Le module principal d’un script s’appelle toujours __main__.

Les blocs de définition de classe et les arguments de exec() ainsi que eval() sont traités de manière spéciale dans le cadre de la résolution des noms. Une définition de classe est une instruction exécutable qui peut utiliser et définir des noms. Toutes ces références suivent les règles normales de la résolution des noms à l’exception des variables locales non liées qui sont recherchées dans l’espace des noms globaux. L’espace de nommage de la définition de classe devient le dictionnaire des attributs de la classe. La portée des noms définis dans un bloc de classe est limitée au bloc de la classe ; elle ne s’étend pas aux blocs de code des méthodes — y compris les compréhensions et les expressions générateurs puisque celles-ci sont implémentées en utilisant une portée de fonction. Ainsi, les instructions suivantes échouent :

class A:
    a = 42
    b = list(a + i for i in range(10))

4.2.3. Noms natifs et restrictions d’exécution

CPython implementation detail: L’utilisateur ne doit pas toucher à __builtins__ ; c’est et cela doit rester réservé aux besoins de l’implémentation. Les utilisateurs qui souhaitent surcharger des valeurs dans l’espace de nommage natif doivent importer le module builtins et modifier ses attributs judicieusement.

L’espace de nommage natif associé à l’exécution d’un bloc de code est effectivement trouvé en cherchant le nom __builtins__ dans l’espace de nommage globaux ; ce doit être un dictionnaire ou un module (dans ce dernier cas, le dictionnaire du module est utilisé). Par défaut, lorsque l’on se trouve dans le module __main__, __builtins__ est le module natif builtins ; lorsque l’on se trouve dans tout autre module, __builtins__ est un pseudonyme du dictionnaire du module builtins lui-même.

4.2.4. Interaction avec les fonctionnalités dynamiques

La résolution des noms de variables libres intervient à l’exécution, pas à la compilation. Cela signifie que le code suivant affiche 42 :

i = 10
def f():
    print(i)
i = 42
f()

Les fonctions eval() et exec() n’ont pas accès à l’environnement complet pour résoudre les noms. Les noms doivent être résolus dans les espaces de nommage locaux et globaux de l’appelant. Les variables libres ne sont pas résolues dans l’espace de nommage englobant le plus proche mais dans l’espace de nommage globaux 1. Les fonctions eval() et exec() possèdent des arguments optionnels pour surcharger les espaces de nommage globaux et locaux. Si seulement un espace de nommage est spécifié, il est utilisé pour les deux.

4.3. Exceptions

Les exceptions sont un moyen de sortir du flot normal d’exécution d’un bloc de code de manière à gérer des erreurs ou des conditions exceptionnelles. Une exception est levée au moment où l’erreur est détectée ; elle doit être gérée par le bloc de code qui l’entoure ou par tout bloc de code qui a, directement ou indirectement, invoqué le bloc de code où l’erreur s’est produite.

L’interpréteur Python lève une exception quand il détecte une erreur à l’exécution (telle qu’une division par zéro). Un programme Python peut aussi lever explicitement une exception avec l’instruction raise. Les gestionnaires d’exception sont spécifiés avec l’instruction try … except. La clause finally d’une telle instruction peut être utilisée pour spécifier un code de nettoyage qui ne gère pas l’exception mais qui est exécuté quoi qu’il arrive (exception ou pas).

Python utilise le modèle par terminaison de gestion des erreurs : un gestionnaire d’exception peut trouver ce qui est arrivé et continuer l’exécution à un niveau plus élevé, mais il ne peut pas réparer l’origine de l’erreur et ré-essayer l’opération qui a échoué (sauf à entrer à nouveau dans le code en question par le haut).

Quand une exception n’est gérée par aucun gestionnaire, l’interpréteur termine l’exécution du programme ou retourne à la boucle interactive. Dans ces cas, il affiche une trace de la pile d’appels, sauf si l’exception est SystemExit.

Les exceptions sont identifiées par des instances de classe. La clause except sélectionnée dépend de la classe de l’instance : elle doit faire référence à la classe de l’instance ou à une de ses classes ancêtres. L’instance peut être transmise au gestionnaire et peut apporter des informations complémentaires sur les conditions de l’exception.

Note

Les messages d’exception ne font pas partie de l’API Python. Leur contenu peut changer d’une version de Python à une autre sans avertissement et le code ne doit pas reposer sur ceux-ci s’il doit fonctionner sur plusieurs versions de l’interpréteur.

Reportez-vous aussi aux descriptions de l’instruction try dans la section L’instruction try et de l’instruction raise dans la section L’instruction raise.

Notes

1

En effet, le code qui est exécuté par ces opérations n’est pas connu au moment où le module est compilé.

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5. Le système d’importation

Le code Python d’un module peut accéder à du code d’un autre module par un mécanisme qui consiste à importer cet autre module. L’instruction import est la façon la plus courante faire appel à ce système d’importation, mais ce n’est pas la seule. Les fonctions telles que importlib.import_module() et __import__() peuvent aussi être utilisées pour mettre en œuvre le mécanisme d’importation.

L’instruction import effectue deux opérations ; elle cherche le module dont le nom a été donné puis elle lie le résultat de cette recherche à un nom dans la portée locale. L’opération de recherche de l’instruction import consiste à appeler la fonction __import__() avec les arguments adéquats. La valeur renvoyée par __import__() est utilisée pour effectuer l’opération de liaison avec le nom fourni à l’instruction import. Reportez-vous à l’instruction import pour les détails exacts de l’opération de liaison avec le nom.

Un appel direct à __import__() effectue seulement la recherche du module et, s’il est trouvé, l’opération de création du module. Bien que des effets collatéraux puissent se produire, tels que l’importation de paquets parents et la mise à jour de divers caches (y compris sys.modules), il n’y a que l’instruction import qui déclenche l’opération de liaison avec le nom.

Lors de l’appel à __import__() dans le déroulement de l’instruction d’importation, la fonction native __import__() est appelée. D’autres mécanismes d’appel au système d’importation (tels que importlib.import_module()) peuvent choisir d’ignorer __import__() et utiliser leur propre solution pour implémenter la sémantique d’importation.

Quand un module est importé pour la première fois, Python recherche le module et, s’il est trouvé, créé un objet module 1 en l’initialisant. Si le module n’est pas trouvé, une ModuleNotFoundError est levée. Python implémente plusieurs stratégies pour rechercher le module d’un nom donné quand le mécanisme d’import est invoqué. Ces stratégies peuvent être modifiées et étendues par divers moyens décrits dans les sections suivantes.

Modifié dans la version 3.3: Le système d’importation a été mis à jour pour implémenter complètement la deuxième partie de la PEP 302 [https://www.python.org/dev/peps/pep-0302]. Il n’existe plus de mécanisme implicite d’importation (le système d’importation complet est exposé via sys.meta_path). En complément, la gestion du paquet des noms natifs a été implémenté (voir la PEP 420 [https://www.python.org/dev/peps/pep-0420]).

5.1. importlib

Le module importlib fournit une API riche pour interagir avec le système d’import. Par exemple, importlib.import_module() fournit une API (que nous vous recommandons) plus simple que la fonction native __import__() pour mettre en œuvre le mécanisme d’import. Reportez-vous à la documentation de la bibliothèque importlib pour obtenir davantage de détails.

5.2. Les paquets

Python ne connait qu’un seul type d’objet module et tous les modules sont donc de ce type, que le module soit implémenté en Python, en C ou quoi que ce soit d’autre. Pour aider à l’organisation des modules et fournir une hiérarchie des noms, Python développe le concept de paquets.

Vous pouvez vous représenter les paquets comme des répertoires dans le système de fichiers et les modules comme des fichiers dans ces répertoires. Mais ne prenez pas trop cette analogie au pied de la lettre car les paquets et les modules ne proviennent pas obligatoirement du système de fichiers. Dans le cadre de cette documentation, nous utilisons cette analogie bien pratique des répertoires et des fichiers. Comme les répertoires du système de fichiers, les paquets sont organisés de manière hiérarchique et les paquets peuvent eux-mêmes contenir des sous-paquets ou des modules.

Il est important de garder à l’esprit que tous les paquets sont des modules mais que tous les modules ne sont pas des paquets. Formulé autrement, les paquets sont juste un certain type de modules. Spécifiquement, tout module qui contient un attribut __path__ est réputé être un paquet.

Tous les modules ont un nom. Les noms des sous-paquets sont séparés du nom du paquet parent par des points (.), à l’instar de la syntaxe standard d’accès aux attributs en Python. Ainsi, vous pouvez avoir un module nommé sys et un paquet nommé email, qui à son tour possède un sous-paquet nommé email.mime avec un module dans ce sous-paquet nommé email.mime.text.

5.2.1. Paquets classiques

Python définit deux types de paquets, les paquets classiques et les paquets espaces de nommage. Les paquets classiques sont les paquets traditionnels tels qu’ils existaient dans Python 3.2 et antérieurs. Un paquet classique est typiquement implémenté sous la forme d’un répertoire contenant un fichier __init__.py. Quand un paquet classique est importé, ce fichier __init__.py est implicitement exécuté.

Par exemple, l’arborescence suivante définit un paquet parent au niveau le plus haut avec trois sous-paquets :

parent/
    __init__.py
    one/
        __init__.py
    two/
        __init__.py
    three/
        __init__.py

Importer parent.one exécute implicitement parent/__init__.py et parent/one/__init__.py. Les importations postérieures de parent.two ou parent.three respectivement exécutent parent/two/__init__.py ou parent/three/__init__.py respectivement.

5.2.2. Paquets espaces de nommage

Un paquet-espace de nommage est la combinaison de plusieurs portions où chaque portion fournit un sous-paquet au paquet parent. Les portions peuvent être situées à différents endroits du système de fichiers. Les portions peuvent aussi être stockées dans des fichiers zip, sur le réseau ou à tout autre endroit dans lequel Python cherche pendant l’importation. Les paquets-espaces de nommage peuvent correspondre directement à des objets du système de fichiers, ou pas ; ils peuvent être des modules virtuels qui n’ont aucune représentation concrète.

Les paquets-espaces de nommage n’utilisent pas une liste ordinaire pour leur attribut __path__. Ils utilisent en lieu et place un type itérable personnalisé qui effectue automatiquement une nouvelle recherche de portions de paquets à la tentative suivante d’importation dans le paquet si le chemin de leur paquet parent (ou sys.path pour les paquets de plus haut niveau) change.

Pour les paquets-espaces de nommage, il n’existe pas de fichier parent/__init__.py. En fait, il peut y avoir plusieurs répertoires parent trouvés pendant le processus d’importation, où chacun est apporté par une portion différente. Ainsi, parent/one n’est pas forcément physiquement à côté de parent/two. Dans ce cas, Python crée un paquet-espace de nommage pour le paquet de plus haut niveau parent dès que lui ou l’un de ses sous-paquet est importé.

Voir aussi la PEP 420 [https://www.python.org/dev/peps/pep-0420] pour les spécifications des paquets-espaces de nommage.

5.3. Recherche

Pour commencer la recherche, Python a besoin du nom qualifié du module (ou du paquet, mais ici cela ne fait pas de différence) que vous souhaitez importer. Le nom peut être donné en argument à l’instruction import ou comme paramètre aux fonctions importlib.import_module() ou __import__().

Le nom est utilisé dans plusieurs phases de la recherche et peut être un chemin séparé par des points pour un sous-module, par exemple truc.machin.bidule. Dans ce cas, Python essaie d’abord d’importer truc puis truc.machin et enfin truc.machin.bidule. Si n’importe laquelle des importations intermédiaires échoue, une ModuleNotFoundError est levée.

5.3.1. Cache des modules

Le premier endroit vérifié pendant la recherche d’une importation est sys.modules. Ce tableau de correspondances est utilisé comme cache de tous les modules déjà importés, y compris les chemins intermédiaires. Ainsi, si truc.machin.bidule a déjà été importé, sys.modules contient les entrées correspondantes à truc, truc.machin et truc.machin.bidule. À chaque chemin correspond une clé.

Pendant l’importation, le nom de module est cherché dans sys.modules et, s’il est trouvé, la valeur associée est le module recherché et le processus est fini. Cependant, si la valeur est None, alors une ModuleNotFoundError est levée. Si le nom du module n’est pas trouvé, Python continue la recherche du module.

sys.modules est accessible en lecture-écriture. Supprimer une clé peut ne pas détruire le module associé (car d’autres modules contiennent possiblement des références vers ce module), mais cela invalide l’entrée du cache pour ce nom de module. Python cherche alors un nouveau module pour ce nom. La clé peut aussi être assignée à None de manière à forcer une ModuleNotFoundError lors de la prochaine importation du module.

Attention cependant : s’il reste une référence à l’objet module et que vous invalidez l’entrée dans le cache de sys.modules puis ré-importez le module, les deux objets modules ne seront pas les mêmes. À l’inverse, importlib.reload() ré-utilise le même objet module et ré-initialise simplement le contenu du module en ré-exécutant le code du module.

5.3.2. Chercheurs et chargeurs

Si le module n’est pas trouvé dans sys.modules, alors Python utilise son protocole d’importation pour chercher et charger le module. Ce protocole se compose de deux objets conceptuels : les chercheurs et les chargeurs. Le travail du chercheur consiste à trouver, à l’aide de différentes stratégies, le module dont le nom a été fourni. Les objets qui implémentent ces deux interfaces sont connus sous le vocable « importateurs » (ils renvoient une référence vers eux-mêmes quand ils trouvent un module qui répond aux attentes).

Python inclut plusieurs chercheurs et importateurs par défaut. Le premier sait comment trouver les modules natifs et le deuxième sait comment trouver les modules gelés. Un troisième chercheur recherche les modules dans import path. import path est une énumération sous forme de liste de chemins ou de fichiers zip. Il peut être étendu pour rechercher aussi dans toute ressource qui dispose d’un identifiant pour la localiser, une URL par exemple.

Le mécanisme d’importation est extensible, vous pouvez donc ajouter de nouveaux chercheurs pour étendre le domaine de recherche des modules.

Les chercheurs ne chargent pas les modules. S’il trouve le module demandé, un chercheur renvoie un spécificateur de module, qui contient toutes les informations nécessaires pour importer le module ; celui-ci sera alors utilisé par le mécanisme d’importation pour charger le module.

Les sections suivantes décrivent plus en détail le protocole utilisé par les chercheurs et les chargeurs, y compris la manière de les créer et les enregistrer pour étendre le mécanisme d’importation.

Modifié dans la version 3.4: Dans les versions précédentes de Python, les chercheurs renvoyaient directement les chargeurs. Dorénavant, ils renvoient des spécificateurs de modules qui contiennent les chargeurs. Les chargeurs sont encore utilisés lors de l’importation mais ont moins de responsabilités.

5.3.3. Points d’entrées automatiques pour l’importation

Le mécanisme d’importation est conçu pour être extensible ; vous pouvez y insérer des points d’entrée automatique (hooks en anglais). Il existe deux types de points d’entrée automatique pour l’importation : les méta-points d’entrée et les points d’entrée sur le chemin des importations.

Les méta-points d’entrée sont appelés au début du processus d’importation, juste après la vérification dans le cache sys.modules mais avant tout le reste. Ceci permet aux méta-points d’entrée de surcharger le traitement effectué sur sys.path, les modules gelés ou même les modules natifs. L’enregistrement des méta-points d’entrée se fait en ajoutant de nouveaux objets chercheurs à sys.meta_path, comme décrit ci-dessous.

Les points d’entrée sur le chemin des importations sont appelés pendant le traitement de sys.path (ou package.__path__), au moment où le chemin qui leur correspond est atteint. Les points d’entrée sur le chemin des importations sont enregistrés en ajoutant de nouveaux appelables à sys.path_hooks, comme décrit ci-dessous.

5.3.4. Méta-chemins

Quand le module demandé n’est pas trouvé dans sys.modules, Python recherche alors dans sys.meta_path qui contient une liste d’objets chercheurs dans des méta-chemins. Ces chercheurs sont interrogés dans l’ordre pour voir s’ils savent prendre en charge le module passé en paramètre. Les chercheurs dans les méta-chemins implémentent une méthode find_spec() qui prend trois arguments : un nom, un chemin d’import et (optionnellement) un module cible. Un chercheur dans les méta-chemins peut utiliser n’importe quelle stratégie pour déterminer s’il est apte à prendre en charge le module.

Si un chercheur dans les méta-chemins sait prendre en charge le module donné, il renvoie un objet spécificateur. S’il ne sait pas, il renvoie None. Si le traitement de sys.meta_path arrive à la fin de la liste sans qu’aucun chercheur n’a renvoyé un objet spécificateur, alors une ModuleNotFoundError est levée. Toute autre exception levée est simplement propagée à l’appelant, mettant fin au processus d’importation.

La méthode find_spec() des chercheurs dans les méta-chemins est appelée avec deux ou trois arguments. Le premier est le nom complètement qualifié du module à importer, par exemple truc.machin.bidule. Le deuxième argument est l’ensemble des chemins dans lesquels chercher. Pour les modules de plus haut niveau, le deuxième argument est None mais pour les sous-modules ou les paquets, le deuxième argument est la valeur de l’attribut __path__ du paquet parent. Si l’attribut __path__ approprié n’est pas accessible, une ModuleNotFoundError est levée. Le troisième argument est un objet module existant qui va être la cible du chargement (plus tard). Le système d’importation ne passe le module cible en paramètre que lors d’un rechargement.

Le méta-chemin peut être parcouru plusieurs fois pour une seule requête d’importation. Par exemple, si nous supposons qu’aucun des modules concernés n’a déjà été mis en cache, importer truc.machin.bidule effectue une première importation au niveau le plus haut, en appelant c_m_c.find_spec("truc", None, None) pour chaque chercheur dans les méta-chemins (c_m_c). Après que truc a été importé, truc.machin est importé en parcourant le méta-chemin une deuxième fois, appelant c_m_c.find_spec("truc.machin", truc.__path__, None). Une fois truc.machin importé, le parcours final appelle c_m_c.find_spec("truc.machin.bidule", truc.machin.__path__, None).

Quelques chercheurs dans les méta-chemins ne gèrent que les importations de plus haut niveau. Ces importateurs renvoient toujours None si on leur passe un deuxième argument autre que None.

Le sys.meta_path de Python comprend trois chercheurs par défaut : un qui sait importer les modules natifs, un qui sait importer les modules gelés et un qui sait importer les modules depuis un chemin des importations (c’est le chercheur dans path).

Modifié dans la version 3.4: La méthode find_spec() des chercheurs dans les méta-chemins a remplacé find_module(), devenue obsolète. Bien qu’elle continue de fonctionner comme avant, le mécanisme d’importation essaie find_module() uniquement si le chercheur n’implémente pas find_spec().

5.4. Chargement

Quand un spécificateur de module est trouvé, le mécanisme d’importation l’utilise (et le chargeur qu’il contient) pour charger le module. Voici à peu près ce qui se passe au sein de l’importation pendant la phase de chargement :

module = None
if spec.loader is not None and hasattr(spec.loader, 'create_module'):
    # It is assumed 'exec_module' will also be defined on the loader.
    module = spec.loader.create_module(spec)
if module is None:
    module = ModuleType(spec.name)
# The import-related module attributes get set here:
_init_module_attrs(spec, module)

if spec.loader is None:
    if spec.submodule_search_locations is not None:
        # namespace package
        sys.modules[spec.name] = module
    else:
        # unsupported
        raise ImportError
elif not hasattr(spec.loader, 'exec_module'):
    module = spec.loader.load_module(spec.name)
    # Set __loader__ and __package__ if missing.
else:
    sys.modules[spec.name] = module
    try:
        spec.loader.exec_module(module)
    except BaseException:
        try:
            del sys.modules[spec.name]
        except KeyError:
            pass
        raise
return sys.modules[spec.name]

Notez les détails suivants :

S’il existe un objet module dans sys.modules avec le même nom, import l’aurait déjà renvoyé.

Le module existe dans sys.modules avant que le chargeur exécute le code du module. C’est crucial car le code du module peut (directement ou indirectement) s’importer lui-même ; l’ajouter à sys.modules avant évite les récursions infinies dans le pire cas et le chargement multiple dans le meilleur des cas.

Si le chargement échoue, le module en cause (et seulement ce module) est enlevé de sys.modules. Tout module déjà dans le cache de sys.modules et tout module qui a été chargé avec succès par effet de bord doit rester dans le cache. C’est différent dans le cas d’un rechargement où même le module qui a échoué est conservé dans sys.modules.

Après que le module est créé mais avant son exécution, le mécanisme d’importation définit les attributs relatifs à l’importation (_init_module_attrs dans l’exemple de pseudo-code ci-dessus), comme indiqué brièvement dans une section que nous abordons ensuite.

L’exécution du module est le moment clé du chargement dans lequel l’espace de nommage du module est peuplé. L’exécution est entièrement déléguée au chargeur qui doit décider ce qui est peuplé et comment.

Le modulé créé pendant le chargement et passé à exec_module() peut ne pas être celui qui est renvoyé à la fin de l’importation 2.

Modifié dans la version 3.4: Le système d’importation a pris en charge les responsabilités des chargeurs. Celles-ci étaient auparavant effectuées par la méthode importlib.abc.Loader.load_module().

5.4.1. Chargeurs

Les chargeurs de modules fournissent la fonction critique du chargement : l’exécution du module. Le mécanisme d’importation appelle la méthode importlib.abc.Loader.exec_module() avec un unique argument, l’objet module à exécuter. Toute valeur renvoyée par exec_module() est ignorée.

Les chargeurs doivent satisfaire les conditions suivantes :

Si le module est un module Python (par opposition aux modules natifs ou aux extensions chargées dynamiquement), le chargeur doit exécuter le code du module dans l’espace des noms globaux du module (module.__dict__).

Si le chargeur ne peut pas exécuter le module, il doit lever une ImportError, alors que toute autre exception levée durant exec_module() est propagée.

Souvent, le chercheur et le chargeur sont le même objet ; dans ce cas, la méthode find_spec() doit juste renvoyer un spécificateur avec le chargeur défini à self.

Les chargeurs de modules peuvent choisir de créer l’objet module pendant le chargement en implémentant une méthode create_module(). Elle prend un argument, l’objet spécificateur du module et renvoie le nouvel objet du module à utiliser pendant le chargement. Notez que create_module() n’a besoin de définir aucun attribut sur l’objet module. Si cette méthode renvoie None, le mécanisme d’importation crée le nouveau module lui-même.

Nouveau dans la version 3.4: La méthode create_module() des chargeurs.

Modifié dans la version 3.4: La méthode load_module() a été remplacée par exec_module() et le mécanisme d’import assume toutes les responsabilités du chargement.

Par compatibilité avec les chargeurs existants, le mécanisme d’importation utilise la méthode load_module() des chargeurs si elle existe et si le chargeur n’implémente pas exec_module(). Cependant, load_module() est déclarée obsolète et les chargeurs doivent implémenter exec_module() à la place.

La méthode load_module() doit implémenter toutes les fonctionnalités de chargement décrites ci-dessus en plus de l’exécution du module. Toutes les contraintes s’appliquent aussi, avec quelques précisions supplémentaires :

S’il y a un objet module existant avec le même nom dans sys.modules, le chargeur doit utiliser le module existant (sinon, importlib.reload() ne fonctionnera pas correctement). Si le module considéré n’est pas trouvé dans sys.modules, le chargeur doit créer un nouvel objet module et l’ajouter à sys.modules.

Le module doit exister dans sys.modules avant que le chargeur n’exécute le code du module, afin d’éviter les récursions infinies ou le chargement multiple.

Si le chargement échoue, le chargeur ne doit enlever de sys.modules que le (ou les) module ayant échoué et seulement si le chargeur lui-même a chargé le module explicitement.

Modifié dans la version 3.5: Un avertissement DeprecationWarning est levé quand exec_module() est définie mais create_module() ne l’est pas.

Modifié dans la version 3.6: Une exception ImportError est levée quand exec_module() est définie mais create_module() ne l’est pas.

5.4.2. Sous-modules

Quand un sous-module est chargé, quel que soit le mécanisme (par exemple avec les instructions import, import-from ou avec la fonction native __import__()), une liaison est créée dans l’espace de nommage du module parent vers l’objet sous-module. Par exemple, si le paquet spam possède un sous-module foo, après l’importation de spam.foo, spam possède un attribut foo qui est lié au sous-module. Supposons que nous ayons l’arborescence suivante :

spam/
    __init__.py
    foo.py
    bar.py

et que le contenu de spam/__init__.py soit :

from .foo import Foo
from .bar import Bar

alors exécuter les lignes suivantes crée des liens vers foo et bar dans le module spam :

>>> import spam
>>> spam.foo
<module 'spam.foo' from '/tmp/imports/spam/foo.py'>
>>> spam.bar
<module 'spam.bar' from '/tmp/imports/spam/bar.py'>

Connaissant la façon habituelle dont Python effectue les liens, cela peut sembler surprenant. Mais c’est en fait une fonctionnalité fondamentale du système d’importation. Si vous avez quelque part sys.modules['spam'] et sys.modules['spam.foo'] (comme dans c’est le cas ci-dessus après l’importation), alors le dernier doit apparaître comme l’attribut foo du premier.

5.4.3. Spécificateurs de modules

Le mécanisme d’importation utilise diverses informations de chaque module pendant l’importation, spécialement avant le chargement. La plupart de ces informations sont communes à tous les modules. Le but d’un spécificateur de module est d’encapsuler ces informations relatives à l’importation au sein de chaque module.

Utiliser un spécificateur pendant l’importation permet de transférer l’état entre les composants du système d’importation, par exemple entre le chercheur qui crée le spécificateur de module et le chargeur qui l’exécute. Surtout, cela permet au mécanisme d’importation d’effectuer toutes les opérations classiques de chargement, alors que c’était le chargeur qui en avait la responsabilité quand il n’y avait pas de spécificateur.

Le spécificateur de module est accessible par l’attribut __spec__ de l’objet module. Lisez ModuleSpec pour davantage d’informations sur le contenu du spécificateur de module.

Nouveau dans la version 3.4.

5.4.4. Attributs des modules importés

Le mécanisme d’importation renseigne ces attributs pour chaque objet module pendant le chargement, sur la base du spécificateur de module et avant que le chargeur n’exécute le module.

__name__

L’attribut __name__ doit contenir le nom complètement qualifié du module. Ce nom est utilisé pour identifier de manière non équivoque le module dans le mécanisme d’importation.

__loader__

L’attribut __loader__ doit pointer vers l’objet chargeur que le mécanisme d’importation a utilisé pour charger le module. L’utilisation principale concerne l’introspection, mais il peut être utilisé pour d’autres fonctionnalités relatives au chargement. Par exemple, obtenir des données par l’intermédiaire du chargeur.

__package__

L’attribut __package__ du module doit être défini. Sa valeur doit être une chaîne de caractères, qui peut être la même que son attribut __name__. Quand le module est un paquet, la valeur de __package__ doit être définie à la même valeur que son __name__. Quand le module n’est pas un paquet, __package__ doit être la chaîne vide pour les modules de niveau le plus haut, et le nom du paquet parent pour les sous-modules. Voir la PEP 366 [https://www.python.org/dev/peps/pep-0366] pour plus de détails.

Cet attribut est utilisé à la place de __name__ pour calculer les importations relatives explicites des modules principaux, comme défini dans la PEP 366 [https://www.python.org/dev/peps/pep-0366]. Il devrait avoir la même valeur que __spec__.parent.

Modifié dans la version 3.6: La valeur de __package__ devrait être la même que celle de __spec__.parent.

__spec__

L’attribut __spec__ doit contenir un lien vers le spécificateur de module qui a été utilisé lors de l’importation du module. Définir __spec__ correctement s’applique aussi pour l’initialisation des modules au démarrage de l’interpréteur. La seule exception concerne __main__ où la valeur de __spec__ est None dans certains cas.

Quand __package__ n’est pas défini, __spec__.parent est utilisé par défaut.

Nouveau dans la version 3.4.

Modifié dans la version 3.6: __spec__.parent est utilisé par défaut quand __package__ n’est pas défini.

__path__

Si le module est un paquet (classique ou espace de nommage), l’attribut __path__ de l’objet module doit être défini. La valeur doit être un itérable mais peut être vide si __path__ n’a pas de sens dans le contexte. Si __path__ n’est pas vide, il doit produire des chaînes lorsque l’on itère dessus. Vous trouvez plus de détails sur la sémantique de __path__ plus loin ci-dessous.

Les modules qui ne sont pas des paquets ne doivent pas avoir d’attribut __path__.

__file__

__cached__

__file__ est optionnel. S’il est défini, la valeur de cet attribut doit être une chaîne. Le système d’importation peut décider de laisser __file__ indéfini si cela ne fait pas sens de le définir (par exemple, lorsqu’on charge un module depuis une base de données).

Si __file__ est défini, il peut être judicieux de définir l’attribut __cached__ dont la valeur est le chemin vers une version compilée du code (par exemple, le fichier bytecode). Le fichier n’a pas besoin d’exister pour définir cet attribut : le chemin peut simplement pointer vers l’endroit où le fichier compilé aurait été placé (voir la PEP 3147 [https://www.python.org/dev/peps/pep-3147]).

Vous pouvez aussi définir __cached__ quand __file__ n’est pas défini. Cependant, ce scénario semble rare. Au final, c’est le chargeur qui utilise les valeurs de __file__ ou __cached__. Donc, si le chargeur peut charger depuis un module mis en cache mais ne peut pas charger depuis un fichier, ce scénario a du sens.

5.4.5. module.__path__

Par définition, si un module possède un attribut __path__, c’est un paquet.

L’attribut __path__ d’un paquet est utilisé pendant l’importation des sous-paquets. Dans le mécanisme d’importation, son fonctionnement ressemble beaucoup à sys.path, c’est-à-dire qu’il fournit une liste d’emplacements où rechercher les modules pendant l’importation. Cependant, __path__ est beaucoup plus contraint que sys.path.

__path__ doit être un itérable de chaînes de caractères, mais il peut être vide. Les mêmes règles que pour sys.path s’appliquent au __path__ d’un paquet et sys.path_hooks (dont la description est donnée plus bas) est consulté pendant le parcours de __path__ du paquet.

Le fichier __init__.py d’un paquet peut définir ou modifier l’attribut __path__ d’un paquet, et c’est ainsi qu’étaient implémentés les paquets-espaces de nommage avant la PEP 420 [https://www.python.org/dev/peps/pep-0420]. Depuis l’adoption de la PEP 420 [https://www.python.org/dev/peps/pep-0420], les paquets-espaces de nommage n’ont plus besoin d’avoir des fichiers __init__.py qui ne font que de la manipulation de __path__ ; le mécanisme d’importation définit automatiquement __path__ correctement pour un paquet-espace de nommage.

5.4.6. Représentation textuelle d’un module

Par défaut, tous les modules ont une représentation textuelle utilisable. Cependant, en utilisant les attributs définis ci-dessus et dans le spécificateur de module, vous pouvez explicitement mieux contrôler l’affichage des objets modules.

Si le module possède un spécificateur (__spec__), le mécanisme d’importation essaie de générer une représentation avec celui-ci. S’il échoue ou s’il n’y a pas de spécificateur, le système d’importation construit une représentation par défaut en utilisant toute information disponible sur le module. Il tente d’utiliser module.__name__, module.__file__ et module.__loader__ comme entrées pour la représentation, avec des valeurs par défaut lorsque l’information est manquante.

Les règles exactes utilisées sont :

Si le module possède un attribut __spec__, la valeur est utilisée pour générer la représentation. Les attributs name, loader, origin et has_location sont consultés.

Si le module possède un attribut __file__, il est utilisé pour construire la représentation du module.

Si le module ne possède pas d’attribut __file__ mais possède un __loader__ qui n’est pas None, alors la représentation du chargeur est utilisée pour construire la représentation du module.

Sinon, il utilise juste le __name__ du module dans la représentation.

Modifié dans la version 3.4: L’utilisation de loader.module_repr() est devenue obsolète et le spécificateur de module est utilisé dorénavant par le mécanisme d’importation pour générer la représentation textuelle du module.

Par compatibilité descendante avec Python 3.3, la représentation textuelle du module est générée en appelant la méthode module_repr() du chargeur, si elle est définie, avant même d’essayer l’approche décrite ci-dessus. Cependant, cette méthode est obsolète.

5.5. Le chercheur dans path

Comme indiqué précédemment, Python est livré par défaut avec plusieurs chercheurs dans les méta-chemins. L’un deux, appelé chercheur dans path (PathFinder), recherche dans le chemin des importations qui contient une liste d’entrées dans path. Chaque entrée désigne un emplacement où rechercher des modules.

Le chercheur dans path en tant que tel ne sait pas comment importer quoi que ce soit. Il ne fait que parcourir chaque entrée de path et associe à chacune d’elle un « chercheur d’entrée dans path » qui sait comment gérer le type particulier de chemin considéré.

L’ensemble par défaut des « chercheurs d’entrée dans path » implémente toute la sémantique pour trouver des modules dans le système de fichiers, gérer des fichiers spéciaux tels que le code source Python (fichiers .py), le bytecode Python (fichiers .pyc) et les bibliothèques partagées (par exemple les fichiers .so). Quand le module zipimport de la bibliothèque standard le permet, les « chercheurs d’entrée dans path » par défaut savent aussi gérer tous ces types de fichiers (autres que les bibliothèques partagées) encapsulés dans des fichiers zip.

Les chemins ne sont pas limités au système de fichiers. Ils peuvent faire référence à des URL, des requêtes dans des bases de données ou tout autre emplacement qui peut être spécifié dans une chaîne de caractères.

Le chercheur dans path fournit aussi des points d’entrées (ou hooks) et des protocoles de manière à pouvoir étendre et personnaliser les types de chemins dans lesquels chercher. Par exemple, si vous voulez pouvoir chercher dans des URL réseau, vous pouvez écrire une fonction « point d’entrée » qui implémente la sémantique HTTP pour chercher des modules sur la toile. Ce point d’entrée (qui doit être un appelable) doit renvoyer un chercheur d’entrée dans path qui gère le protocole décrit plus bas et qui sera utilisé pour obtenir un chargeur de module sur la toile.

Avertissement : cette section et la précédente utilisent toutes les deux le terme chercheur, dans un cas chercheur dans les méta-chemins et dans l’autre chercheur d’entrée dans path. Ces deux types de chercheurs sont très similaires, gèrent des protocoles similaires et fonctionnent de manière semblable pendant le processus d’importation, mais il est important de garder à l’esprit qu’ils sont subtilement différents. En particulier, les chercheurs dans les méta-chemins opèrent au début du processus d’importation, comme clé de parcours de sys.meta_path.

Au contraire, les « chercheurs d’entrée dans path » sont, dans un sens, un détail d’implémentation du chercheur dans path et, en fait, si le chercheur dans path était enlevé de sys.meta_path, aucune des sémantiques des « chercheurs d’entrée dans path » ne serait invoquée.

5.5.1. Chercheurs d’entrée dans path

Le chercheur dans path (path based finder en anglais) est responsable de trouver et charger les modules et les paquets Python dont l’emplacement est spécifié par une chaîne dite d’entrée dans path. La plupart de ces entrées désignent des emplacements sur le système de fichiers, mais il n’y a aucune raison de les limiter à ça.

En tant que chercheur dans les méta-chemins, un chercheur dans path implémente le protocole find_spec() décrit précédemment. Cependant, il autorise des points d’entrée (hooks en anglais) supplémentaires qui peuvent être utilisés pour personnaliser la façon dont les modules sont trouvés et chargés depuis le chemin des importations.

Trois variables sont utilisées par le chercheur dans path : sys.path, sys.path_hooks et sys.path_importer_cache. L’attribut __path__ des objets paquets est aussi utilisé. Il permet de personnaliser encore davantage le mécanisme d’importation.

sys.path contient une liste de chaînes de caractères indiquant des emplacements où chercher des modules ou des paquets. Elle est initialisée à partir de la variable d’environnement PYTHONPATH et de plusieurs autres valeurs par défaut qui dépendent de l’installation et de l’implémentation. Les entrées de sys.path désignent des répertoires du système de fichiers, des fichiers zip et possiblement d’autres « endroits » (lisez le module site) tels que des URL ou des requêtes dans des bases de données où Python doit rechercher des modules. sys.path ne doit contenir que des chaînes de caractères ou d’octets ; tous les autres types sont ignorés. L’encodage des entrées de chaînes d’octets est déterminé par chaque chercheur d’entrée dans path.

Le chercheur dans path est un chercheur dans les méta-chemins, donc le mécanisme d’importation commence la recherche dans le chemin des importations par un appel à la méthode find_spec() du chercheur dans path, comme décrit précédemment. Quand l’argument path de find_spec() est donné, c’est une liste de chemins à parcourir, typiquement un attribut __path__ pour une importation à l’intérieur d’un paquet. Si l’argument path est None, cela indique une importation de niveau le plus haut et sys.path est utilisée.

Le chercheur dans path itère sur chaque entrée dans le path et, pour chacune, regarde s’il trouve un chercheur d’entrée dans path (PathEntryFinder) approprié à cette entrée. Comme cette opération est coûteuse (elle peut faire appel à plusieurs stat() pour cela), le chercheur dans path maintient un cache de correspondance entre les entrées et les « chercheurs d’entrée dans path ». Ce cache est géré par sys.path_importer_cache (en dépit de son nom, ce cache stocke les objets chercheurs plutôt que les simples objets importateurs). Ainsi, la recherche coûteuse pour une entrée de path spécifique n’a besoin d’être effectuée qu’une seule fois par le chercheur d’entrée dans path. Le code de l’utilisateur peut très bien supprimer les entrées du cache sys.path_importer_cache, forçant ainsi le chercheur dans path à effectuer une nouvelle fois la recherche sur chaque entrée 3.

Si une entrée n’est pas présente dans le cache, le chercheur dans path itère sur chaque callable de sys.path_hooks. Chaque point d’entrée sur une entrée de path de cette liste est appelé avec un unique argument, l’entrée dans laquelle chercher. L’appelable peut soit renvoyer un chercheur d’entrée dans path apte à prendre en charge l’entrée ou lever une ImportError. Une ImportError est utilisée par le chercheur dans path pour signaler que le point d’entrée n’a pas trouvé de chercheur d’entrée dans path pour cette entrée. L’exception est ignorée et l’itération sur le chemin des importations se poursuit. Le point d’entrée doit attendre qu’on lui passe soit une chaîne de caractères soit une chaîne d’octets ; l’encodage des chaînes d’octets est à la main du point d’entrée (par exemple, ce peut être l’encodage du système de fichiers, de l’UTF-8 ou autre chose) et, si le point d’entrée n’arrive pas à décoder l’argument, il doit lever une ImportError.

Si l’itération sur sys.path_hooks se termine sans qu’aucun chercheur d’entrée dans path ne soit renvoyé, alors la méthode find_spec() du chercheur dans path stocke None dans le sys.path_importer_cache (pour indiquer qu’il n’y a pas de chercheur pour cette entrée) et renvoie None, indiquant que ce chercheur dans les méta-chemins n’a pas trouvé le module.

Si un chercheur d’entrée dans path est renvoyé par un des points d’entrée de sys.path_hooks, alors le protocole suivant est utilisé pour demander un spécificateur de module au chercheur, spécificateur qui sera utilisé pour charger le module.

Le répertoire de travail courant — noté sous la forme d’une chaîne de caractères vide — est géré d’une manière légèrement différente des autres entrées de sys.path. D’abord, si le répertoire de travail courant s’avère ne pas exister, aucune valeur n’est stockée dans sys.path_importer_cache. Ensuite, la valeur pour le répertoire de travail courant est vérifiée à chaque recherche de module. Enfin, le chemin utilisé pour sys.path_importer_cache et renvoyée par importlib.machinery.PathFinder.find_spec() est le nom réel du répertoire de travail courant et non pas la chaîne vide.

5.5.2. Protocole des chercheurs d’entrée dans path

Afin de gérer les importations de modules, l’initialisation des paquets et d’être capables de contribuer aux portions des paquets-espaces de nommage, les chercheurs d’entrée dans path doivent implémenter la méthode find_spec().

La méthode find_spec() prend deux arguments, le nom complètement qualifié du module en cours d’importation et (optionnellement) le module cible. find_spec() renvoie un spécificateur de module pleinement peuplé. Ce spécificateur doit avoir son chargeur (attribut « loader » ) défini, à une exception près.

Pour indiquer au mécanisme d’importation que le spécificateur représente une portion d’un espace de nommage, le chercheur d’entrée dans path définit le chargeur du spécificateur à None et l’attribut submodule_search_locations à une liste contenant la portion.

Modifié dans la version 3.4: La méthode find_spec() remplace find_loader() et find_module(), ces deux méthodes étant dorénavant obsolètes mais restant utilisées si find_spec() n’est pas définie.

Les vieux chercheurs d’entrée dans path peuvent implémenter une des deux méthodes obsolètes à la place de find_spec(). Ces méthodes sont toujours prises en compte dans le cadre de la compatibilité descendante. Cependant, si find_spec() est implémentée par le chercheur d’entrée dans path, les méthodes historiques sont ignorées.

La méthode find_loader() prend un argument, le nom complètement qualifié du module en cours d’importation. find_loader() renvoie un couple dont le premier élément est le chargeur et le second est une portion d’espace de nommage. Quand le premier élément (c’est-à-dire le chargeur) est None, cela signifie que, bien que le chercheur d’entrée dans path n’a pas de chargeur pour le module considéré, il sait que cette entrée contribue à une portion d’espace de nommage pour le module considéré. C’est presque toujours le cas quand vous demandez à Python d’importer un paquet-espace de nommage qui n’est pas présent physiquement sur le système de fichiers. Quand un chercheur d’entrée dans path renvoie None pour le chargeur, la valeur du second élément du couple renvoyé doit être une séquence, éventuellement vide.

Si find_loader() renvoie une valeur de chargeur qui n’est pas None, la portion est ignorée et le chargeur est renvoyé par le chercheur dans path, mettant un terme à la recherche dans les chemins.

À fin de compatibilité descendante avec d’autres implémentations du protocole d’importation, beaucoup de chercheurs d’entrée dans path gèrent aussi la méthode traditionnelle find_module() que l’on trouve dans les chercheurs dans les méta-chemins. Cependant, les méthodes find_module() des chercheurs d’entrée dans path ne sont jamais appelées avec un argument path (il est convenu qu’elles enregistrent les informations relatives au chemin approprié au moment de leur appel initial au point d’entrée).

La méthode find_module() des chercheurs d’entrée dans path est obsolète car elle n’autorise pas le chercheur d’entrée dans path à contribuer aux portions d’espaces de nommage des paquets-espaces de nommage. Si à la fois find_loader() et find_module() sont définies pour un chercheur d’entrée dans path, le système d’importation utilise toujours find_loader() plutôt que find_module().

5.6. Remplacement du système d’importation standard

La manière la plus fiable de remplacer tout le système d’importation est de supprimer le contenu par défaut de sys.meta_path et de le remplacer complètement par un chercheur dans les méta-chemins sur mesure.

S’il convient juste de modifier le comportement de l’instruction import sans affecter les autres API qui utilisent le système d’importation, alors remplacer la fonction native __import__() peut être suffisant. Cette technique peut aussi être employée au niveau d’un module pour n’altérer le comportement des importations qu’à l’intérieur de ce module.

Pour empêcher sélectivement l’importation de certains modules par un point d’entrée placé en tête dans le méta-chemin (plutôt que de désactiver complètement le système d’importation), il suffit de lever une ModuleNotFoundError directement depuis find_spec() au lieu de renvoyer None. En effet, None indique que la recherche dans le méta-chemin peut continuer alors que la levée de l’exception termine immédiatement la recherche.

5.7. Cas particulier de __main__

Le module __main__ est un cas particulier pour le système d’importation de Python. Comme indiqué par ailleurs, le module __main__ est initialisé directement au démarrage de l’interpréteur, un peu comme sys et builtins. Cependant, au contraire des deux cités précédemment, ce n’est pas vraiment un module natif. Effectivement, la manière dont est initialisé __main__ dépend des drapeaux et options avec lesquels l’interpréteur est lancé.

5.7.1. __main__.__spec__

En fonction de la manière dont __main__ est initialisé, __main__.__spec__ est défini de manière conforme ou mis à None.

Quand Python est démarré avec l’option -m, __spec__ est défini à la valeur du spécificateur du module ou paquet correspondant. Python peuple aussi __spec__ quand le module __main__ est chargé en tant que partie de l’exécution d’un répertoire, d’un fichier zip ou d’une entrée de sys.path.

Dans les autres cas, __main__.__spec__ est mis à None, car le code qui peuple __main__ ne trouve pas de correspondance directe avec un module que l’on importe :

invite de commande interactive

-c option

lecture depuis l’entrée standard

lecture depuis un fichier de code source ou de bytecode

Notez que __main__.__spec__ vaut toujours None dans le dernier cas, même si le fichier pourrait techniquement être importé directement en tant que module. Utilisez l’option -m si vous souhaitez disposer de métadonnées valides du module dans __main__.

Notez aussi que même quand __main__ correspond à un module importable et que __main__.__spec__ est défini en conséquence, ils seront toujours considérés comme des modules distincts. Cela est dû au fait que le bloc encadré par if __name__ == "__main__": ne s’exécute que quand le module est utilisé pour peupler l’espace de nommage de __main__, et pas durant une importation normale.

5.8. Idées d’amélioration

XXX Ce serait vraiment bien de disposer d’un diagramme.

XXX * (import_machinery.rst) Pourquoi pas une section dédiée aux attributs des modules et paquets, développant ou remplaçant les entrées associées dans la page de référence du modèle de données ?

XXX runpy, pkgutil et autres dans le manuel de la bibliothèque devraient comporter un lien « Lisez aussi » en début de page pointant vers la section du nouveau mécanisme d’import.

XXX Ajouter des explications sur les différentes manières dont __main__ est initialisé ?

XXX Ajouter des informations sur les pièges et bizarreries de __main__ (c-à-d des extraits de la PEP 395 [https://www.python.org/dev/peps/pep-0395]).

5.9. Références

Le mécanisme d’importation a considérablement évolué depuis les débuts de Python. La spécification des paquets [https://www.python.org/doc/essays/packages/] originale est toujours disponible, bien que quelques détails ont changé depuis l’écriture de ce document.

La spécification originale de sys.meta_path se trouve dans la PEP 302 [https://www.python.org/dev/peps/pep-0302]. La PEP 420 [https://www.python.org/dev/peps/pep-0420] contient des extensions significatives.

La PEP 420 [https://www.python.org/dev/peps/pep-0420] a introduit les paquets-espaces de nommage pour Python 3.3. La PEP 420 [https://www.python.org/dev/peps/pep-0420] a aussi introduit le protocole recherche du chargeur comme une alternative à find_module().

La PEP 366 [https://www.python.org/dev/peps/pep-0366] décrit l’ajout de l’attribut __package__ pour les importations relatives explicites dans les modules principaux.

La PEP 328 [https://www.python.org/dev/peps/pep-0328] a introduit les importations absolues et les importations relatives explicites. Elle a aussi proposé __name__ pour la sémantique que la PEP 366 [https://www.python.org/dev/peps/pep-0366] attribuait à __package__.

PEP 338 [https://www.python.org/dev/peps/pep-0338] définit l’exécution de modules en tant que scripts.

PEP 451 [https://www.python.org/dev/peps/pep-0451] ajoute l’encapsulation dans les objets spécificateurs de l’état des importations, module par module. Elle reporte aussi la majorité des responsabilités des chargeurs vers le mécanisme d’import. Ces changements permettent de supprimer plusieurs API dans le système d’importation et d’ajouter de nouvelles méthodes aux chercheurs et chargeurs.

Notes

1

Voir types.ModuleType.

2

L’implémentation de importlib évite d’utiliser directement la valeur de retour. À la place, elle récupère l’objet module en recherchant le nom du module dans sys.modules. L’effet indirect est que le module importé peut remplacer le module de même nom dans sys.modules. C’est un comportement spécifique à l’implémentation dont le résultat n’est pas garanti pour les autres implémentations de Python.

3

Dans du code historique, il est possible de trouver des instances de imp.NullImporter dans sys.path_importer_cache. Il est recommandé de modifier ce code afin d’utiliser None à la place. Lisez Portage de code Python pour plus de détails.

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6. Expressions

Ce chapitre explique la signification des éléments des expressions en Python.

Notes sur la syntaxe : dans ce chapitre et le suivant, nous utilisons la notation BNF étendue pour décrire la syntaxe, pas l’analyse lexicale. Quand une règle de syntaxe est de la forme

name ::=  othername

et qu’aucune sémantique n’est donnée, la sémantique de name est la même que celle de othername.

6.1. Conversions arithmétiques

Quand la description d’un opérateur arithmétique ci-dessous utilise la phrase « les arguments numériques sont convertis vers un type commun », cela signifie que l’implémentation de l’opérateur fonctionne de la manière suivante pour les types natifs :

Si l’un des deux arguments est du type nombre complexe, l’autre est converti en nombre complexe ;

sinon, si l’un des arguments est un nombre à virgule flottante, l’autre est converti en nombre à virgule flottante ;

sinon, les deux doivent être des entiers et aucune conversion n’est nécessaire.

Des règles supplémentaires s’appliquent pour certains opérateurs (par exemple, une chaîne comme opérande de gauche pour l’opérateur %). Les extensions doivent définir leurs propres règles de conversion.

6.2. Atomes

Les atomes sont les éléments de base des expressions. Les atomes les plus simples sont les identifiants et les littéraux. Les expressions entre parenthèses, crochets ou accolades sont aussi classées syntaxiquement comme des atomes. La syntaxe pour les atomes est :

atom      ::=  identifier | literal | enclosure
enclosure ::=  parenth_form | list_display | dict_display | set_display
               | generator_expression | yield_atom

6.2.1. Identifiants (noms)

Un identifiant qui apparaît en tant qu’atome est un nom. Lisez la section Identifiants et mots-clés pour la définition lexicale et la section Noms et liaisons pour la documentation sur les noms et les liaisons afférentes.

Quand un nom est lié à un objet, l’évaluation de l’atome produit cet objet. Quand le nom n’est pas lié, toute tentative de l’évaluer lève une exception NameError.

Transformation des noms privés : lorsqu’un identificateur qui apparaît textuellement dans la définition d’une classe commence par deux (ou plus) caractères de soulignement et ne se termine pas par deux (ou plus) caractères de soulignement, il est considéré comme un nom privé <private name> de cette classe. Les noms privés sont transformés en une forme plus longue avant que le code ne soit généré pour eux. La transformation insère le nom de la classe, avec les soulignés enlevés et un seul souligné inséré devant le nom. Par exemple, l’identificateur __spam apparaissant dans une classe nommée Ham est transformé en _Ham__spam. Cette transformation est indépendante du contexte syntaxique dans lequel l’identificateur est utilisé. Si le nom transformé est extrêmement long (plus de 255 caractères), l’implémentation peut le tronquer. Si le nom de la classe est constitué uniquement de traits de soulignement, aucune transformation n’est effectuée.

6.2.2. Littéraux

Python gère les littéraux de chaînes de caractères, de chaînes d’octets et de plusieurs autres types numériques :

literal ::=  stringliteral | bytesliteral
             | integer | floatnumber | imagnumber

L’évaluation d’un littéral produit un objet du type donné (chaîne de caractères, chaîne d’octets, entier, nombre à virgule flottante, nombre complexe) avec la valeur donnée. La valeur peut être approximée dans le cas des nombres à virgule flottante et des nombres imaginaires (complexes). Reportez-vous à la section Littéraux pour les détails.

Tous les littéraux sont de types immuables et donc l’identifiant de l’objet est moins important que sa valeur. Des évaluations multiples de littéraux avec la même valeur (soit la même occurrence dans le texte du programme, soit une autre occurrence) résultent dans le même objet ou un objet différent avec la même valeur.

6.2.3. Formes parenthésées

Une forme parenthésée est une liste d’expressions (cette liste est en fait optionnelle) placée à l’intérieur de parenthèses :

parenth_form ::=  "(" [starred_expression] ")"

Une liste d’expressions entre parenthèses produit ce que la liste de ces expressions produirait : si la liste contient au moins une virgule, elle produit un n-uplet (type tuple) ; sinon, elle produit l’expression elle-même (qui constitue donc elle-même la liste d’expressions).

Une paire de parenthèses vide produit un objet tuple vide. Comme les tuples sont immuables, la règle pour les littéraux s’applique (c’est-à-dire que deux occurrences du tuple vide peuvent, ou pas, produire le même objet).

Notez que les tuples ne sont pas créés par les parenthèses mais par l’utilisation de la virgule. L’exception est le tuple vide, pour lequel les parenthèses sont requises (autoriser que « rien » ne soit pas parenthésé dans les expressions aurait généré des ambigüités et aurait permis à certaines coquilles de passer inaperçu).

6.2.4. Agencements des listes, ensembles et dictionnaires

Pour construire une liste, un ensemble ou un dictionnaire, Python fournit des syntaxes spéciales dites « agencements » (displays en anglais), chaque agencement comportant deux variantes :

soit le contenu du conteneur est listé explicitement,

soit il est calculé à l’aide de la combinaison d’une boucle et d’instructions de filtrage, appelée une compréhension (dans le sens de ce qui sert à définir un concept, par opposition à extension).

Les compréhensions sont constituées des éléments de syntaxe communs suivants :

comprehension ::=  expression comp_for
comp_for      ::=  [ASYNC] "for" target_list "in" or_test [comp_iter]
comp_iter     ::=  comp_for | comp_if
comp_if       ::=  "if" expression_nocond [comp_iter]

Une compréhension est constituée par une seule expression suivie par au moins une clause for et zéro ou plus clauses for ou if. Dans ce cas, les éléments du nouveau conteneur sont ceux qui auraient été produits si l’on avait considéré toutes les clauses for ou if comme des blocs, imbriqués de la gauche vers la droite, et évalué l’expression pour produire un élément à chaque fois que le bloc le plus imbriqué était atteint.

Notez que la compréhension est exécutée dans une portée séparée, les noms assignés dans la liste cible ne pouvant pas « fuir » en dehors de cette portée.

Depuis Python 3.6, dans une fonction async def, une clause async for peut être utilisée pour itérer sur un itérateur asynchrone. Une compréhension dans une fonction async def consiste alors à avoir une clause for or async for suivie par des clauses for or async for additionnelles facultatives et, possiblement, des expressions await. Si la compréhension contient soit des clauses async for, soit des expressions await, elle est appelée compréhension asynchrone. Une compréhension asynchrone peut suspendre l’exécution de la fonction coroutine dans laquelle elle apparaît. Voir aussi la PEP 530 [https://www.python.org/dev/peps/pep-0530].

6.2.5. Agencements de listes

Un agencement de liste est une suite (possiblement vide) d’expressions à l’intérieur de crochets :

list_display ::=  "[" [starred_list | comprehension] "]"

Un agencement de liste produit un nouvel objet liste, dont le contenu est spécifié soit par une liste d’expression soit par une compréhension. Quand une liste d’expressions (dont les éléments sont séparés par des virgules) est fournie, ces éléments sont évalués de la gauche vers la droite et placés dans l’objet liste, dans cet ordre. Quand c’est une compréhension qui est fournie, la liste est construite à partir des éléments produits par la compréhension.

6.2.6. Agencements d’ensembles

Un agencement d’ensemble (type set) est délimité par des accolades et se distingue de l’agencement d’un dictionnaire par le fait qu’il n’y a pas de « deux points » : pour séparer les clés et les valeurs :

set_display ::=  "{" (starred_list | comprehension) "}"

Un agencement d’ensemble produit un nouvel objet ensemble muable, le contenu étant spécifié soit par une séquence d’expression, soit par une compréhension. Quand une liste (dont les éléments sont séparés par des virgules) est fournie, ses éléments sont évalués de la gauche vers la droite et ajoutés à l’objet ensemble. Quand une compréhension est fournie, l’ensemble est construit à partir des éléments produits par la compréhension.

Un ensemble vide ne peut pas être construit par {} ; cette écriture construit un dictionnaire vide.

6.2.7. Agencements de dictionnaires

Un agencement de dictionnaire est une série (possiblement vide) de couples clés-valeurs entourée par des accolades :

dict_display       ::=  "{" [key_datum_list | dict_comprehension] "}"
key_datum_list     ::=  key_datum ("," key_datum)* [","]
key_datum          ::=  expression ":" expression | "**" or_expr
dict_comprehension ::=  expression ":" expression comp_for

Un agencement de dictionnaire produit un nouvel objet dictionnaire.

Si une séquence (dont les éléments sont séparés par des virgules) de couples clés-valeurs est fournie, les couples sont évalués de la gauche vers la droite pour définir les entrées du dictionnaire : chaque objet clé est utilisé comme clé dans le dictionnaire pour stocker la donnée correspondante. Cela signifie que vous pouvez spécifier la même clé plusieurs fois dans la liste des couples clés-valeurs et, dans ce cas, la valeur finalement stockée dans le dictionnaire est la dernière donnée.

Une double astérisque ** demande de dépaqueter le dictionnaire. L’opérande doit être un tableau de correspondances. Chaque élément du tableau de correspondances est ajouté au nouveau dictionnaire. Les valeurs les plus récentes remplacent les valeurs déjà définies par des couples clés-valeurs antérieurs ou par d’autres dépaquetages de dictionnaires antérieurs.

Nouveau dans la version 3.5: le dépaquetage peut se faire vers un agencement de dictionnaire, proposé à l’origine par la PEP 448 [https://www.python.org/dev/peps/pep-0448].

Une compréhension de dictionnaire, au contraire des compréhensions de listes ou d’ensembles, requiert deux expressions séparées par une virgule et suivies par les clauses usuelles « for » et « if ». Quand la compréhension est exécutée, les éléments clés-valeurs sont insérés dans le nouveau dictionnaire dans l’ordre dans lequel ils sont produits.

Les restrictions relatives aux types des clés sont données dans la section Hiérarchie des types standards (pour résumer, le type de la clé doit être hachable, ce qui exclut tous les objets muables). Les collisions entre les clés dupliquées ne sont pas détectées ; la dernière valeur (celle qui apparaît le plus à droite dans l’agencement) stockée prévaut pour une clé donnée.

6.2.8. Expressions génératrices

Une expression génératrice est une notation concise pour un générateur, entourée de parenthèses :

generator_expression ::=  "(" expression comp_for ")"

Une expression génératrice produit un nouvel objet générateur. Sa syntaxe est la même que celle des compréhensions, sauf qu’elle est entourée de parenthèses au lieu de crochets ou d’accolades.

Les variables utilisées dans une expression générateur sont évaluées paresseusement, au moment où la méthode __next__() de l’objet générateur est appelée (de la même manière que pour les générateurs classiques). Cependant, la clause for la plus à gauche est immédiatement évaluée, de manière à ce qu’une erreur dans cette partie puisse être vue avant tout autre erreur dans le code qui gère l’expression générateur. Les clauses for suivantes ne peuvent pas être évaluées immédiatement car elles peuvent dépendre de la précédente boucle for. Par exemple, (x*y for x in range(10) for y in truc(x)).

Les parenthèses peuvent être omises pour les appels qui ne possèdent qu’un seul argument. Voir la section Appels pour les détails.

Depuis Python 3.6, si le générateur apparaît dans une fonction async def, alors la clause async for et les expressions await sont permises comme pour une compréhension asynchrone. Si une expression générateur contient soit des clauses async for, soit des expressions await, alors on l’appelle expression générateur asynchrone. Une expression générateur asynchrone produit un nouvel objet générateur asynchrone qui est un itérateur asynchrone (voir Itérateurs asynchrones).

6.2.9. Expressions yield

yield_atom       ::=  "(" yield_expression ")"
yield_expression ::=  "yield" [expression_list | "from" expression]

Une expression yield est utilisée pour définir une fonction générateur ou une fonction génératrice asynchrone et ne peut donc être utilisée que dans le corps de la définition d’une fonction. L’utilisation d’une expression yield dans le corps d’une fonction entraîne que cette fonction devient un générateur et son utilisation dans le corps d’une fonction async def entraine que cette fonction coroutine devient un générateur asynchrone. Par exemple :

def gen():  # defines a generator function
    yield 123

async def agen(): # defines an asynchronous generator function
    yield 123

Les fonctions génératrices sont décrites plus loin alors que les fonctions générateurs asynchrones sont décrites séparément dans la section Fonctions génératrices asynchrones.

Lorsqu’une fonction génératrice est appelée, elle renvoie un itérateur que l’on appelle générateur. Ce générateur contrôle l’exécution de la fonction génératrice. L’exécution commence lorsque l’une des méthodes du générateur est appelée. À ce moment, l’exécution se déroule jusqu’à la première expression yield, où elle se suspend, renvoyant la valeur de expression_list à l’appelant du générateur. Cette suspension conserve tous les états locaux, y compris les liaisons en cours des variables locales, le pointeur d’instruction, la pile d’évaluation interne et l’état de tous les gestionnaires d’exceptions. Lorsque l’exécution reprend en appelant l’une des méthodes du générateur, la fonction s’exécute exactement comme si l’expression yield n’avait été qu’un simple appel externe. La valeur de l’expression yield après reprise dépend de la méthode qui a permis la reprise de l’exécution. Si c’est __next__() qui a été utilisée (typiquement via un for ou la fonction native next()) alors le résultat est None. Sinon, si c’est send() qui a été utilisée, alors le résultat est la valeur transmise à cette méthode.

Tout ceci rend les fonctions génératrices très similaires aux coroutines : elles produisent plusieurs objets via des expressions yield, elles possèdent plus qu’un seul point d’entrée et leur exécution peut être suspendue. La seule différence est qu’une fonction génératrice ne peut pas contrôler où l’exécution doit se poursuivre après une instruction yield ; ce contrôle est toujours du ressort de l’appelant au générateur.

Les expressions yield sont autorisées partout dans un bloc try. Si l’exécution du générateur ne reprend pas avant qu’il ne soit finalisé (parce que son compteur de référence est tombé à zéro ou parce qu’il est nettoyé par le ramasse-miettes), la méthode close() du générateur-itérateur est appelée, ce qui permet l’exécution de toutes les clauses finally en attente.

L’utilisation de yield from <expr> traite l’expression passée en paramètre comme un sous-itérateur. Toutes les valeurs produites par ce sous-itérateur sont directement passées à l’appelant des méthodes du générateur courant. Toute valeur passée par send() ou toute exception passée par throw() est transmise à l’itérateur sous-jacent s’il possède les méthodes appropriées. Si ce n’est pas le cas, alors send() lève une AttributeError ou une TypeError, alors que throw() ne fait que propager l’exception immédiatement.

Quand l’itérateur sous-jacent a terminé, l’attribut value de l’instance StopIteration qui a été levée devient la valeur produite par l’expression yield. Elle peut être définie explicitement quand vous levez StopIteration ou automatiquement que le sous-itérateur est un générateur (en renvoyant une valeur par le sous-générateur).

Modifié dans la version 3.3: yield from <expr> a été ajoutée pour déléguer le contrôle du flot d’exécution à un sous-itérateur.

Les parenthèses peuvent être omises quand l’expression yield est la seule expression à droite de l’instruction de l’instruction d’assignation.

Voir aussi

PEP 255 [https://www.python.org/dev/peps/pep-0255] : Générateurs simples

La proposition d’ajouter à Python des générateurs et l’instruction yield.

PEP 342 [https://www.python.org/dev/peps/pep-0342] – Coroutines via des générateurs améliorés

Proposition d’améliorer l’API et la syntaxe des générateurs, de manière à pouvoir les utiliser comme de simples coroutines.

PEP 380 [https://www.python.org/dev/peps/pep-0380] – Syntaxe pour déléguer à un sous-générateur

Proposition d’introduire la syntaxe yield_from, de manière à déléguer facilement l’exécution à un sous-générateur.

PEP 525 [https://www.python.org/dev/peps/pep-0525] - Asynchronous Generators

The proposal that expanded on PEP 492 [https://www.python.org/dev/peps/pep-0492] by adding generator capabilities to coroutine functions.

6.2.9.1. Méthodes des générateurs-itérateurs

Cette sous-section décrit les méthodes des générateurs-itérateurs. Elles peuvent être utilisées pour contrôler l’exécution des fonctions générateurs.

Notez que l’appel à une méthode ci-dessous d’un générateur alors que le générateur est déjà en cours d’exécution lève une exception ValueError.

generator.__next__()

Démarre l’exécution d’une fonction générateur ou la reprend à la dernière expression yield exécutée. Quand une fonction générateur est reprise par une méthode __next__(), l’expression yield en cours s’évalue toujours à None. L’exécution continue ensuite jusqu’à l’expression yield suivante, où le générateur est à nouveau suspendu et la valeur de expression_list est renvoyée à la méthode __next__() de l’appelant. Si le générateur termine sans donner une autre valeur, une exception StopIteration est levée.

Cette méthode est normalement appelée implicitement, par exemple par une boucle for ou par la fonction native next().

generator.send(value)

Reprend l’exécution et « envoie » une valeur à la fonction générateur. L’argument value devient le résultat de l’expression yield courante. La méthode send() renvoie la valeur suivante produite par le générateur ou lève StopIteration si le générateur termine sans produire de nouvelle valeur. Quand send() est utilisée pour démarrer le générateur, elle doit avoir None comme argument, car il n’y a aucune expression yield qui peut recevoir la valeur.

generator.throw(type[, value[, traceback]])

Lève une exception de type type à l’endroit où le générateur est en pause et renvoie la valeur suivante produite par la fonction générateur. Si le générateur termine sans produire de nouvelle valeur, une exception StopIteration est levée. Si la fonction génératrice ne gère pas l’exception passée ou lève une autre exception, alors cette exception est propagée vers l’appelant.

generator.close()

Lève une GeneratorExit à l’endroit où la fonction génératrice a été mise en pause. Si la fonction génératrice termine, est déjà fermée ou lève GeneratorExit (parce qu’elle ne gère pas l’exception), close revient vers l’appelant. Si le générateur produit une valeur, une RuntimeError est levée. Si le générateur lève une autre exception, elle est propagée à l’appelant. La méthode close() ne fait rien si le générateur a déjà terminé en raison d’une exception ou d’une fin normale.

6.2.9.2. Exemples

Voici un exemple simple qui montre le comportement des générateurs et des fonctions génératrices :

>>> def echo(value=None):
...     print("Execution starts when 'next()' is called for the first time.")
...     try:
...         while True:
...             try:
...                 value = (yield value)
...             except Exception as e:
...                 value = e
...     finally:
...         print("Don't forget to clean up when 'close()' is called.")
...
>>> generator = echo(1)
>>> print(next(generator))
Execution starts when 'next()' is called for the first time.
1
>>> print(next(generator))
None
>>> print(generator.send(2))
2
>>> generator.throw(TypeError, "spam")
TypeError('spam',)
>>> generator.close()
Don't forget to clean up when 'close()' is called.

Pour des exemples d’utilisation de yield from, lisez la PEP 380: Syntax for Delegating to a Subgenerator dans « Les nouveautés de Python ».

6.2.9.3. Fonctions génératrices asynchrones

La présence d’une expression yield dans une fonction ou une méthode définie en utilisant async def transforme cette fonction en fonction générateur asynchrone.

Quand une fonction génératrice asynchrone est appelée, elle renvoie un itérateur asynchrone, autrement appelé objet générateur asynchrone. Cet objet contrôle l’exécution de la fonction génératrice. Un objet générateur asynchrone est typiquement utilisé dans une instruction async for à l’intérieur d’une fonction coroutine de la même manière qu’un objet générateur serait utilisé dans une instruction for.

L’appel d’une méthode du générateur asynchrone renvoie un objet awaitable et l’exécution commence au moment où l’on atteint une instruction await le concernant. À ce moment, l’exécution se déroule jusqu’à la première expression yield, où elle est suspendue et renvoie la valeur de expression_list à la coroutine en attente. Comme pour un générateur, la suspension signifie que tous les états locaux sont conservés, y compris les liaisons des variables locales, le pointeur d’instruction, la pile d’évaluation interne et l’état de tous les gestionnaires d’exceptions. Lorsque l’exécution reprend parce que l’appelant a atteint une instruction await sur l’objet suivant retourné par les méthodes du générateur asynchrone, la fonction s’exécute exactement comme si l’expression yield n’avait été qu’un simple appel externe. La valeur de l’expression yield au moment de la reprise dépend de la méthode qui a relancé l’exécution. Si c’est __anext__() qui a été utilisée, alors le résultat est None. Sinon, si c’est asend() qui a été utilisée, alors le résultat est la valeur transmise à cette méthode.

Dans une fonction générateur asynchrone, les expressions yield sont autorisées n’importe où dans une construction try. Cependant, si l’exécution d’un générateur asynchrone n’a pas repris avant que le générateur ne soit finalisé (parce que son compteur de référence a atteint zéro ou parce qu’il est nettoyé par le ramasse-miettes), alors une expression yield dans une construction try pourrait ne pas atteindre la clause finally en attente. Dans ce cas, c’est la responsabilité de la boucle d’événements ou du programmateur exécutant le générateur asynchrone d’appeler la méthode aclose() du générateur asynchrone et d’exécuter l’objet coroutine résultant, permettant ainsi à toute clause finally en attente d’être exécutée.

Pour effectuer correctement la finalisation, une boucle d’événements doit définir une fonction finalizer qui prend un générateur-itérateur asynchrone, appelle sans doute aclose() et exécute la coroutine. Ce finalizer peut s’enregistrer en appelant sys.set_asyncgen_hooks(). Lors de la première itération, un générateur-itérateur asynchrone stocke le finalizer enregistré à appeler lors de la finalisation. Pour un exemple de référence relatif à une méthode de finalizer, regardez l’implémentation de asyncio.Loop.shutdown_asyncgens dans Lib/asyncio/base_events.py [https://github.com/python/cpython/tree/3.6/Lib/asyncio/base_events.py].

L’expression yield from <expr> produit une erreur de syntaxe quand elle est utilisée dans une fonction génératrice asynchrone.

6.2.9.4. Méthodes des générateurs-itérateurs asynchrones

Cette sous-section décrit les méthodes des générateurs-itérateurs asynchrones. Elles sont utilisées pour contrôler l’exécution des fonctions génératrices.

coroutine agen.__anext__()

Renvoie un awaitable qui, quand il a la main, démarre l’exécution du générateur asynchrone ou reprend son exécution à l’endroit de la dernière expression yield exécutée. Quand une fonction générateur asynchrone est reprise par une méthode __anext__(), l’expression yield en cours s’évalue toujours à None dans le awaitable renvoyé, et elle continue son exécution jusqu’à l’expression yield suivante. La valeur de expression_list de l’expression yield est la valeur de l’exception StopIteration levée par la coroutine qui termine. Si le générateur asynchrone termine sans produire d’autre valeur, le awaitable lève une exception StopAsyncIteration qui signale que l’itération asynchrone est terminée.

Cette méthode est normalement appelée implicitement par une boucle async for.

coroutine agen.asend(value)

Renvoie un awaitable qui, lorsqu’il a la main, reprend l’exécution du générateur asynchrone. Comme pour la méthode send() d’un générateur, elle « envoie » une valeur value à la fonction générateur asynchrone et cet argument devient le résultat de l’expression yield courante. Le awaitable renvoyé par la méthode asend() renvoie la valeur suivante produite par le générateur comme valeur de l’exception StopIteration levée ou lève StopAsyncIteration si le générateur asynchrone termine sans produire de nouvelle valeur. Quand asend() est appelée pour démarrer le générateur asynchrone, l’argument doit être None car il n’y a pas d’expression yield pour recevoir la valeur.

coroutine agen.athrow(type[, value[, traceback]])

Renvoie un awaitable qui lève une exception du type type à l’endroit où le générateur asynchrone a été mis en pause et renvoie la valeur suivante produite par la fonction générateur comme valeur de l’exception StopIteration qui a été levée. Si le générateur asynchrone termine sans produire de nouvelle valeur, une exception StopAsyncIteration est levée par le awaitable. Si la fonction générateur ne traite pas l’exception reçue ou lève une autre exception alors, quand le awaitable est lancé, cette exception est propagée vers l’appelant du awaitable.

coroutine agen.aclose()

Renvoie un awaitable qui, quand il s’exécute, lève une exception GeneratorExit dans la fonction génératrice asynchrone à l’endroit où le générateur était en pause. Si la fonction génératrice asynchrone termine normalement, est déjà fermée ou lève GeneratorExit (parce qu’elle ne gère pas l’exception), alors le awaitable renvoyé lève une exception StopIteration. Tout nouveau awaitable produit par un appel postérieur au générateur asynchrone lève une exception StopAsyncIteration. Si le générateur asynchrone produit une valeur, une RuntimeError est levée par le awaitable. Si le générateur asynchrone lève une autre exception, elle est propagée à l’appelant du awaitable. Si le générateur asynchrone a déjà terminé (soit par une exception, soit normalement), alors tout nouvel appel à aclose() renvoie un awaitable qui ne fait rien.

6.3. Primaires

Les primaires (primary dans la grammaire formelle ci-dessous) représentent les opérations qui se lient au plus proche dans le langage. Leur syntaxe est :

primary ::=  atom | attributeref | subscription | slicing | call

6.3.1. Références à des attributs

Une référence à un attribut (attributeref dans la grammaire formelle ci-dessous) est une primaire suivie par un point et un nom :

attributeref ::=  primary "." identifier

La primaire doit s’évaluer à un objet d’un type qui gère les références aux attributs, ce qui est le cas de la plupart des objets. Cet objet doit alors produire l’attribut dont le nom est « identifier ». Cette production peut être personnalisée en surchargeant la méthode __getattr__(). Si l’attribut n’est pas disponible, une exception AttributeError est levée. Sinon, le type et la valeur de l’objet produit sont déterminés par l’objet. Plusieurs évaluations successives d’une référence à un même attribut peuvent produire différents objets.

6.3.2. Sélections

Une sélection (subscription dans la grammaire formelle ci-dessous) désigne un élément dans un objet séquence (chaîne, n-uplet ou liste) ou tableau de correspondances (dictionnaire) :

subscription ::=  primary "[" expression_list "]"

La primaire doit s’appliquer à un objet qui gère les sélections (une liste ou un dictionnaire par exemple). Les objets définis par l’utilisateur peuvent gérer les sélections en définissant une méthode __getitem__().

Pour les objets natifs, deux types d’objets gèrent la sélection :

Si la primaire est un tableau de correspondances, la liste d’expressions (expression_list dans la grammaire formelle ci-dessous) doit pouvoir être évaluée comme un objet dont la valeur est une des clés du tableau de correspondances et la sélection désigne la valeur qui correspond à cette clé (la liste d’expressions est un n-uplet sauf si elle comporte exactement un élément).

Si la primaire est une séquence, la liste d’expressions (expression_list dans la grammaire) doit pouvoir être évaluée comme un entier ou une tranche (comme expliqué dans la section suivante).

La syntaxe formelle ne traite pas des cas d’indices négatifs dans les séquences ; cependant, toutes les séquences natives possèdent une méthode __getitem__() qui interprète les indices négatifs en ajoutant la longueur de la séquence à l’indice (de manière à ce que x[-1] sélectionne le dernier élément de x). La valeur résultante doit être un entier positif ou nul, inférieur au nombre d’éléments dans la séquence ; la sélection désigne alors l’élément dont l’indice est cette valeur (en comptant à partir de zéro). Comme la gestion des indices négatifs et des tranches est faite par la méthode __getitem__(), les sous-classes qui surchargent cette méthode doivent aussi savoir les gérer, de manière explicite.

Les éléments des chaînes sont des caractères. Un caractère n’est pas un type en tant que tel, c’est une chaîne de longueur un.

6.3.3. Tranches

Une tranche (slicing dans la grammaire formelle ci-dessous) sélectionne un intervalle d’éléments d’un objet séquence (par exemple une chaîne, un n-uplet ou une liste, respectivement les types string, tuple et list). Les tranches peuvent être utilisées comme des expressions ou des cibles dans les assignations ou les instructions del. La syntaxe est la suivante :

slicing      ::=  primary "[" slice_list "]"
slice_list   ::=  slice_item ("," slice_item)* [","]
slice_item   ::=  expression | proper_slice
proper_slice ::=  [lower_bound] ":" [upper_bound] [ ":" [stride] ]
lower_bound  ::=  expression
upper_bound  ::=  expression
stride       ::=  expression

Il existe une ambigüité dans la syntaxe formelle ci-dessus : tout ce qui ressemble à une liste d’expressions (expression_list vue avant) ressemble aussi à une liste de tranches (slice_list dans la grammaire ci-dessus). En conséquence, toute sélection (subscription dans la grammaire) peut être interprétée comme une tranche. Plutôt que de compliquer encore la syntaxe, l’ambigüité est levée en disant que, dans ce cas, l’interprétation en tant que sélection (subscription) est prioritaire sur l’interprétation en tant que tranche (c’est le cas si la liste de tranches (slice_list) ne contient aucune tranche en tant que telle).

La sémantique pour une tranche est définie comme suit. La primaire est indicée (en utilisant la même méthode __getitem__() que pour les sélections normales) avec une clé qui est construite à partir de la liste de tranches (slice_list dans la grammaire), de cette manière : si la liste de tranches contient au moins une virgule (,), la clé est un n-uplet contenant la conversion des éléments de la tranche ; sinon, la conversion du seul élément de la tranche est la clé. La conversion d’un élément de tranche qui est une expression est cette expression. La conversion d’une tranche en tant que telle est un objet slice (voir la section Hiérarchie des types standards) dont les attributs start, stop et step sont les valeurs des expressions données pour la borne inférieure (lower_bound dans la grammaire), la borne supérieure (upper_bound dans la grammaire) et le pas (stride dans la grammaire), respectivement. En cas d’expression manquante, la valeur par défaut est None.

6.3.4. Appels

Un appel (call dans la grammaire ci-dessous) appelle un objet appelable (par exemple, une fonction) avec, possiblement, une liste d”arguments :

call                 ::=  primary "(" [argument_list [","] | comprehension] ")"
argument_list        ::=  positional_arguments ["," starred_and_keywords]
                            ["," keywords_arguments]
                          | starred_and_keywords ["," keywords_arguments]
                          | keywords_arguments
positional_arguments ::=  ["*"] expression ("," ["*"] expression)*
starred_and_keywords ::=  ("*" expression | keyword_item)
                          ("," "*" expression | "," keyword_item)*
keywords_arguments   ::=  (keyword_item | "**" expression)
                          ("," keyword_item | "," "**" expression)*
keyword_item         ::=  identifier "=" expression

Une virgule finale (optionnelle) peut être présente, après les arguments positionnels et par mots-clés, mais elle n’affecte pas la sémantique.

La primaire doit s’évaluer à un objet appelable (une fonction définie par l’utilisateur, une fonction native, une méthode d’objet natif, un objet de classe, une méthode d’instance de classe ou tout objet possédant une méthode __call__() est un appelable). Toutes les expressions des arguments sont évaluées avant que l’appel ne soit exécuté. Référez-vous à la section Définition de fonctions pour la syntaxe des listes de paramètres formels.

Si des arguments par mots-clés sont présents, ils sont d’abord convertis en arguments positionnels, comme suit. Pour commencer, une liste de slots vides est créée pour les paramètres formels. S’il y a N arguments positionnels, ils sont placés dans les N premiers slots. Ensuite, pour chaque argument par mot-clé, l’identifiant est utilisé pour déterminer le slot correspondant (si l’identifiant est le même que le nom du premier paramètre formel, le premier slot est utilisé, et ainsi de suite). Si le slot est déjà rempli, une exception TypeError est levée. Sinon, la valeur de l’argument est placée dans le slot, ce qui le remplit (même si l’expression est None, cela remplit le slot). Quand tous les arguments ont été traités, les slots qui sont toujours vides sont remplis avec la valeur par défaut correspondante dans la définition de la fonction (les valeurs par défaut sont calculées, une seule fois, lorsque la fonction est définie ; ainsi, un objet mutable tel qu’une liste ou un dictionnaire utilisé en tant valeur par défaut sera partagé entre tous les appels qui ne spécifient pas de valeur d argument pour ce slot ; on évite généralement de faire ça). S’il reste des slots pour lesquels aucune valeur par défaut n’est définie, une exception TypeError est levée. Sinon, la liste des slots remplie est utilisée en tant que liste des arguments pour l’appel.

CPython implementation detail: Une implémentation peut fournir des fonctions natives dont les paramètres positionnels n’ont pas de nom, même s’ils sont « nommés » pour les besoins de la documentation. Ils ne peuvent donc pas être spécifiés par mot-clé. En CPython, les fonctions implémentées en C qui utilisent PyArg_ParseTuple() pour analyser leurs arguments en font partie.

S’il y a plus d’arguments positionnels que de slots de paramètres formels, une exception TypeError est levée, à moins qu’un paramètre formel n’utilise la syntaxe *identifier ; dans ce cas, le paramètre formel reçoit un n-uplet contenant les arguments positionnels en supplément (ou un n-uplet vide s’il n’y avait pas d’arguments positionnel en trop).

Si un argument par mot-clé ne correspond à aucun nom de paramètre formel, une exception TypeError est levée, à moins qu’un paramètre formel n’utilise la syntaxe **identifier ; dans ce cas, le paramètre formel reçoit un dictionnaire contenant les arguments par mot-clé en trop (en utilisant les mots-clés comme clés et les arguments comme valeurs pour ce dictionnaire), ou un (nouveau) dictionnaire vide s’il n’y a pas d’argument par mot-clé en trop.

Si la syntaxe *expression apparaît dans l’appel de la fonction, expression doit pouvoir s’évaluer à un itérable. Les éléments de ces itérables sont traités comme s’ils étaient des arguments positionnels supplémentaires. Pour l’appel f(x1, x2, *y, x3, x4), si y s’évalue comme une séquence y1, …, yM, c’est équivalent à un appel avec M+4 arguments positionnels x1, x2, y1, …, yM, x3, x4.

Une conséquence est que bien que la syntaxe *expression puisse apparaître après les arguments par mots-clés explicites, ils sont traités avant les arguments par mots-clés (et avant tout argument **expression – voir ci-dessous). Ainsi :

>>> def f(a, b):
...     print(a, b)
...
>>> f(b=1, *(2,))
2 1
>>> f(a=1, *(2,))
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: f() got multiple values for keyword argument 'a'
>>> f(1, *(2,))
1 2

Il est inhabituel que les syntaxes d’arguments par mots-clés et *expression soient utilisés simultanément dans un même appel, ce qui fait que la confusion reste hypothétique.

Si la syntaxe **expression apparaît dans un appel de fonction, expression doit pouvoir s’évaluer comme un tableau de correspondances, dont le contenu est traité comme des arguments par mots-clés supplémentaires. Si un mot-clé est déjà présent (en tant qu’argument par mot-clé explicite, ou venant d’un autre dépaquetage), une exception TypeError est levée.

Les paramètres formels qui utilisent la syntaxe *identifier ou **identifier ne peuvent pas être utilisés comme arguments positionnels ou comme noms d’arguments par mots-clés.

Modifié dans la version 3.5: Les appels de fonction acceptent n’importe quel nombre de dépaquetages par * ou **. Des arguments positionnels peuvent suivre les dépaquetages d’itérables (*) et les arguments par mots-clés peuvent suivre les dépaquetages de dictionnaires (**). Proposé pour la première fois par la PEP 448 [https://www.python.org/dev/peps/pep-0448].

Un appel renvoie toujours une valeur, possiblement None, à moins qu’il ne lève une exception. La façon dont celle valeur est calculée dépend du type de l’objet appelable.

Si c’est —

une fonction définie par l’utilisateur :

le bloc de code de la fonction est exécuté, il reçoit la liste des arguments. La première chose que le bloc de code fait est de lier les paramètres formels aux arguments ; ceci est décrit dans la section Définition de fonctions. Quand le bloc de code exécute l’instruction return, cela spécifie la valeur de retour de l’appel de la fonction.

une fonction ou une méthode native :

le résultat dépend de l’interpréteur ; lisez Fonctions natives pour une description des fonctions et méthodes natives.

un objet classe :

une nouvelle instance de cette classe est renvoyée.

une méthode d’instance de classe :

la fonction correspondante définie par l’utilisateur est appelée, avec la liste d’arguments qui est plus grande d’un élément que la liste des arguments de l’appel : l’instance est placée en tête des arguments.

une instance de classe :

la classe doit définir une méthode __call__() ; l’effet est le même que si cette méthode était appelée.

6.4. Expression await

Suspend l’exécution de la coroutine sur un objet awaitable. Ne peut être utilisée qu’à l’intérieur d’une coroutine function.

await_expr ::=  "await" primary

Nouveau dans la version 3.5.

6.5. L’opérateur puissance

L’opérateur puissance est plus prioritaire que les opérateurs unaires sur sa gauche ; il est moins prioritaire que les opérateurs unaires sur sa droite. La syntaxe est :

power ::=  (await_expr | primary) ["**" u_expr]

Ainsi, dans une séquence sans parenthèse de puissance et d’opérateurs unaires, les opérateurs sont évalués de droite à gauche (ceci ne contraint pas l’ordre d’évaluation des opérandes) : -1**2 donne -1.

L’opérateur puissance possède la même sémantique que la fonction native pow() lorsqu’elle est appelée avec deux arguments : il produit son argument de gauche élevé à la puissance de son argument de droite. Les arguments numériques sont d’abord convertis vers un type commun et le résultat est de ce type.

Pour les opérandes entiers, le résultat est du même type à moins que le deuxième argument ne soit négatif ; dans ce cas, tous les arguments sont convertis en nombres à virgule flottante et le résultat est un nombre à virgule flottante. Par exemple, 10**2 renvoie 100 mais 10**-2 renvoie 0.01.

Élever 0.0 à une puissance négative entraîne une ZeroDivisionError. Élever un nombre négatif à une puissance fractionnaire renvoie un nombre complexe (dans les versions antérieures, cela levait une ValueError).

6.6. Arithmétique unaire et opérations sur les bits

Toute l’arithmétique unaire et les opérations sur les bits ont la même priorité :

u_expr ::=  power | "-" u_expr | "+" u_expr | "~" u_expr

L’opérateur unaire - (moins) produit l’opposé de son argument numérique.

L’opérateur unaire + (plus) produit son argument numérique inchangé.

L’opérateur unaire ~ (inversion) produit l’inversion bit à bit de son argument entier. L’inversion bit à bit de x est définie comme -(x+1). Elle s’applique uniquement aux nombres entiers.

Dans ces trois cas, si l’argument n’est pas du bon type, une exception TypeError est levée.

6.7. Opérations arithmétiques binaires

Les opérations arithmétiques binaires suivent les conventions pour les priorités. Notez que certaines de ces opérations s’appliquent aussi à des types non numériques. À part l’opérateur puissance, il n’y a que deux niveaux, le premier pour les opérateurs multiplicatifs et le second pour les opérateurs additifs :

m_expr ::=  u_expr | m_expr "*" u_expr | m_expr "@" m_expr |
            m_expr "//" u_expr | m_expr "/" u_expr |
            m_expr "%" u_expr
a_expr ::=  m_expr | a_expr "+" m_expr | a_expr "-" m_expr

L’opérateur * (multiplication) produit le produit de ses arguments. Les deux arguments doivent être des nombres ou alors le premier argument doit être un entier et l’autre doit être une séquence. Dans le premier cas, les nombres sont convertis dans un type commun puis sont multipliés entre eux. Dans le dernier cas, la séquence est répétée ; une répétition négative produit une séquence vide.

L’opérateur @ (prononcé at en anglais) a vocation à multiplier des matrices. Aucun type Python natif n’implémente cet opérateur.

Nouveau dans la version 3.5.

Les opérateurs / (division) et // (division entière ou floor division en anglais) produisent le quotient de leurs arguments. Les arguments numériques sont d’abord convertis vers un type commun. La division d’entiers produit un nombre à virgule flottante alors que la division entière d’entiers produit un entier ; le résultat est celui de la division mathématique suivie de la fonction floor appliquée au résultat. Une division par zéro lève une exception ZeroDivisionError.

L’opérateur % (modulo) produit le reste de la division entière du premier argument par le second. Les arguments numériques sont d’abord convertis vers un type commun. Un zéro en second argument lève une exception ZeroDivisionError. Les arguments peuvent être des nombres à virgule flottante, par exemple 3.14%0.7 vaut 0.34 (puisque 3.14 égale 4*0.7+0.34). L’opérateur modulo produit toujours un résultat du même signe que le second opérande (ou zéro) ; la valeur absolue du résultat est strictement inférieure à la valeur absolue du second opérande 1.

Les opérateurs division entière et modulo sont liés par la relation suivante : x == (x//y)*y + (x%y). La division entière et le module sont aussi liés à la fonction native divmod() : divmod(x, y) == (x//y, x%y) 2.

En plus de calculer le modulo sur les nombres, l’opérateur % est aussi surchargé par les objets chaînes de caractères pour effectuer le formatage de chaîne « à l’ancienne ». La syntaxe pour le formatage de chaînes est décrit dans la référence de la bibliothèque Python, dans la section Formatage de chaines à la printf.

L’opérateur de division entière, l’opérateur modulo et la fonction divmod() ne sont pas définis pour les nombres complexes. À la place, vous pouvez, si cela a du sens pour ce que vous voulez faire, les convertir vers des nombres à virgule flottante en utilisant la fonction abs().

L’opérateur + (addition) produit la somme de ses arguments. Les arguments doivent être tous les deux des nombres ou des séquences du même type. Dans le premier cas, les nombres sont convertis vers un type commun puis sont additionnés entre eux. Dans le dernier cas, les séquences sont concaténées.

L’opérateur - (soustraction) produit la différence entre ses arguments. Les arguments numériques sont d’abord convertis vers un type commun.

6.8. Opérations de décalage

Les opérations de décalage sont moins prioritaires que les opérations arithmétiques :

shift_expr ::=  a_expr | shift_expr ("<<" | ">>") a_expr

Ces opérateurs prennent des entiers comme arguments. Ils décalent le premier argument vers la gauche ou vers la droite du nombre de bits donné par le deuxième argument.

Un décalage à droite de n bits est défini comme la division entière par pow(2,n). Un décalage à gauche de n bits est défini comme la multiplication par pow(2,n).

Note

Dans l’implémentation actuelle, l’opérande de droite doit être au maximum sys.maxsize. Si l’opérande de droite est plus grand que sys.maxsize, une exception OverflowError est levée.

6.9. Opérations binaires bit à bit

Chacune des trois opérations binaires bit à bit possède une priorité différente :

and_expr ::=  shift_expr | and_expr "&" shift_expr
xor_expr ::=  and_expr | xor_expr "^" and_expr
or_expr  ::=  xor_expr | or_expr "|" xor_expr

L’opérateur & produit le ET logique de ses arguments, qui doivent être des entiers.

L’opérateur ^ produit le OU EXCLUSIF (XOR) logique de ses arguments, qui doivent être des entiers.

L’opérateur | produit le OU logique de ses arguments, qui doivent être des entiers.

6.10. Comparaisons

Au contraire du C, toutes les opérations de comparaison en Python possèdent la même priorité, qui est plus faible que celle des opérations arithmétiques, décalages ou binaires bit à bit. Toujours contrairement au C, les expressions telles que a < b < c sont interprétées comme elles le seraient conventionnellement en mathématiques :

comparison    ::=  or_expr (comp_operator or_expr)*
comp_operator ::=  "<" | ">" | "==" | ">=" | "<=" | "!="
                   | "is" ["not"] | ["not"] "in"

Les comparaisons produisent des valeurs booléennes : True ou False.

Les comparaisons peuvent être enchaînées arbitrairement, par exemple x < y <= z est équivalent à x < y and y <= z, sauf que y est évalué seulement une fois (mais dans les deux cas, z n’est pas évalué du tout si x < y s’avère être faux).

Formellement, si a, b, c, …, y, z sont des expressions et op1, op2, …, opN sont des opérateurs de comparaison, alors a op1 b op2 c ... y opN z est équivalent à a op1 b and b op2 c and ... y opN z, sauf que chaque expression est évaluée au maximum une fois.

Notez que a op1 b op2 c n’implique aucune comparaison entre a et c. Ainsi, par exemple, x < y > z est parfaitement légal (mais peut-être pas très élégant).

6.10.1. Comparaisons de valeurs

Les opérateurs <, >, ==, >=, <= et != comparent les valeurs de deux objets. Les objets n’ont pas besoin d’être du même type.

Le chapitre Objets, valeurs et types indique que les objets ont une valeur (en plus d’un type et d’un identifiant). La valeur d’un objet est une notion plutôt abstraite en Python : par exemple, il n’existe pas de méthode canonique pour accéder à la valeur d’un objet. De la même manière, il n’y a aucune obligation concernant la construction de la valeur d’un objet, par exemple qu’elle prenne en compte toutes les données de ses attributs. Les opérateurs de comparaison implémentent une notion particulière de ce qu’est la valeur d’un objet. Vous pouvez vous le représenter comme une définition indirecte de la valeur d’un objet, via l’implémentation de leur comparaison.

Comme tous les types sont des sous-types (directs ou indirects) de la classe object, ils héritent du comportement de comparaison par défaut de object. Les types peuvent personnaliser le comportement des comparaisons en implémentant des méthodes de comparaisons riches, comme __lt__(), décrites dans Personnalisation de base.

Le comportement par défaut pour le test d’égalité (== et !=) se base sur les identifiants des objets. Ainsi, un test d’égalité entre deux instances qui ont le même identifiant est vrai, un test d’égalité entre deux instances qui ont des identifiants différents est faux. La raison de ce choix est que Python souhaite que tous les objets soient réflexifs, c’est-à-dire que x is y implique x == y.

La relation d’ordre (<, >, <= et >=) n’est pas fournie par défaut ; une tentative se solde par une TypeError. La raison de ce choix est qu’il n’existe pas d’invariant similaire à celui de l’égalité.

Le comportement du test d’égalité par défaut, à savoir que les instances avec des identités différentes ne sont jamais égales, peut être en contradiction avec les types qui définissent la « valeur » d’un objet et se basent sur cette « valeur » pour l’égalité. De tels types doivent personnaliser leurs tests de comparaison et, en fait, c’est ce qu’ont fait un certain nombre de types natifs.

La liste suivante décrit le comportement des tests d’égalité pour les types natifs les plus importants.

Beaucoup de types numériques natifs (Types numériques — int, float, complex) et de types de la bibliothèque standard fractions.Fraction ainsi que decimal.decimal peuvent être comparés, au sein de leur propre classe ou avec d’autres objets de classes différentes. Une exception notable concerne les nombres complexes qui ne gèrent pas la relation d’ordre. Dans les limites des types concernés, la comparaison mathématique équivaut à la comparaison algorithmique, sans perte de précision.

Les valeurs qui ne sont pas des nombres, float('NaN') et Decimal('NaN'), ont un traitement spécial.

Les séquences binaires (instances du type bytes ou bytearray) peuvent être comparées au sein de la classe et entre classes. La comparaison est lexicographique, en utilisant la valeur numérique des éléments.

Les chaînes de caractères (instances de str) respectent l’ordre lexicographique en utilisant la valeur Unicode (le résultat de la fonction native ord()) des caractères 3.

Les chaînes de caractères et les séquences binaires ne peuvent pas être comparées directement.

Les séquences (instances de tuple, list ou range) peuvent être comparées uniquement entre instances de même type, en sachant que les intervalles (range) ne gèrent pas la relation d’ordre. Le test d’égalité entre ces types renvoie faux et une comparaison entre instances de types différents lève une TypeError.

Les séquences suivent l’ordre lexicographique en utilisant la comparaison de leurs éléments, sachant que la réflexivité des éléments est appliquée.

Dans l’application de la réflexivité des éléments, la comparaison des collections suppose que pour un élément de collection x, x == x est toujours vrai. Sur la base de cette hypothèse, l’identité des éléments est d’abord testée, puis la comparaison des éléments n’est effectuée que pour des éléments distincts. Cette approche donne le même résultat qu’une comparaison stricte d’éléments, si les éléments comparés sont réflexifs. Pour les éléments non réflexifs, le résultat est différent de celui de la comparaison stricte des éléments, voire peut être surprenant : les valeurs non réflexives qui ne sont pas des nombres, par exemple, aboutissent au comportement suivant lorsqu’elles sont utilisées dans une liste :

>>> nan = float('NaN')
>>> nan is nan
True
>>> nan == nan
False                 <-- the defined non-reflexive behavior of NaN
>>> [nan] == [nan]
True                  <-- list enforces reflexivity and tests identity first

L’ordre lexicographique pour les collections natives fonctionne comme suit :

Deux collections sont égales si elles sont du même type, ont la même longueur et si les éléments correspondants de chaque paire sont égaux. Par exemple, [1,2] == (1,2) est faux car les types sont différents.

Les collections qui gèrent la relation d’ordre sont ordonnées comme leur premier élément différent (par exemple, [1,2,x] <= [1,2,y] a la même valeur que x <= y). Si un élément n’a pas de correspondant, la collection la plus courte est la plus petite (par exemple, [1,2] < [1,2,3] est vrai).

Les tableaux de correspondances (instances de dict) sont égales si et seulement si toutes leurs paires (clé, valeur) sont égales. L’égalité des clés et des valeurs met en œuvre la réflexivité.

Les comparaisons (<, >, <= et >=) lèvent TypeError.

Les ensembles (instances de set ou frozenset) peuvent être comparés au sein de leur propre type et entre types différents.

Les opérateurs d’inclusion et de sur-ensemble sont définis. Ces relations ne sont pas des relations d’ordre total (par exemple, les deux ensembles {1,2} et {2,3} ne sont pas égaux, l’un n’est pas inclus dans l’autre, l’un n’est pas un sur-ensemble de l’autre). Ainsi, les ensembles ne sont pas des arguments appropriés pour les fonctions qui dépendent d’un ordre total (par exemple, les fonctions min(), max() et sorted() produisent des résultats indéfinis si on leur donne des listes d’ensembles en entrée).

La comparaison des ensembles met en œuvre la réflexivité des éléments.

La plupart des autres types natifs n’implémentent pas de méthodes de comparaisons, ils héritent donc du comportement par défaut.

Les classes allogènes qui particularisent les opérations de comparaison doivent, si possible, respecter quelques règles pour la cohérence :

Le test d’égalité doit être réflexif. En d’autres termes, des objets identiques doivent être égaux :

x is y implique x == y

La comparaison doit être symétrique. En d’autres termes, les expressions suivantes doivent donner le même résultat :

x == y et y == x

x != y et y != x

x < y et y > x

x <= y et y >= x

La comparaison doit être transitive. Les exemples suivants (liste non exhaustive) illustrent ce concept :

x > y and y > z implique x > z

x < y and y <= z implique x < z

Si vous inversez la comparaison, cela doit en produire la négation booléenne. En d’autres termes, les expressions suivantes doivent produire le même résultat :

x == y et not x != y

x < y et not x >= y (pour une relation d’ordre total)

x > y et not x <= y (pour une relation d’ordre total)

Ces deux dernières expressions s’appliquent pour les collections totalement ordonnées (par exemple, les séquences mais pas les ensembles ou les tableaux de correspondances). Regardez aussi le décorateur total_ordering().

Le résultat de hash() doit être cohérent avec l’égalité. Les objets qui sont égaux doivent avoir la même empreinte ou être marqués comme non-hachables.

Python ne vérifie pas ces règles de cohérence. En fait, l’utilisation de valeurs non numériques est un exemple de non-respect de ces règles.

6.10.2. Opérations de tests d’appartenance à un ensemble

Les opérateurs in et not in testent l’appartenance. x in s s’évalue à True si x appartient à s et à False sinon. x not in s renvoie la négation de x in s. Tous les types séquences et ensembles natifs gèrent ces opérateurs, ainsi que les dictionnaires pour lesquels in teste si dictionnaire possède une clé donnée. Pour les types conteneurs tels que les listes, n-uplets (tuple), ensembles (set), ensembles gelés (frozen set), dictionnaires (dict) ou collections.deque, l’expression x in y est équivalente à any(x is e or x == e for e in y).

Pour les chaînes de caractères et chaînes d’octets, x in y vaut True si et seulement si x est une sous-chaîne de y. Un test équivalent est y.find(x) != -1. Une chaîne vide est considérée comme une sous-chaîne de toute autre chaîne, ainsi "" in "abc" renvoie True.

Pour les classes allogènes qui définissent la méthode __contains__(), x in y renvoie True si y.__contains__(x) renvoie vrai, et False sinon.

Pour les classes allogènes qui ne définissent pas __contains__() mais qui définissent __iter__(), x in y vaut True s’il existe une valeur z telle que x == z renvoie vrai lors de l’itération sur y. Si une exception est levée pendant l’itération, c’est comme si in avait levé cette exception.

Enfin, le protocole d’itération « à l’ancienne » est essayé : si la classe définit __getitem__(), x in y est True si et seulement si il existe un entier positif ou nul i, représentant l’indice, tel que x == y[i] et que tout indice inférieur ne lève pas d’exception IndexError (si toute autre exception est levée, c’est comme si in avait levé cette exception).

L’opérateur not in est défini comme produisant le contraire de in.

6.10.3. Comparaisons d’identifiants

Les opérateurs is et is not testent l’égalité des identifiants des objets : x is y est vrai si et seulement si x et y sont le même objet. L’identifiant d’un objet est déterminé en utilisant la fonction id(). x is not y renvoie le résultat contraire de l’égalité des identifiants 4.

6.11. Opérations booléennes

or_test  ::=  and_test | or_test "or" and_test
and_test ::=  not_test | and_test "and" not_test
not_test ::=  comparison | "not" not_test

Dans le contexte des opérations booléennes et quand des expressions sont utilisées par des instructions de contrôle du flux d’exécution, les valeurs suivantes sont considérées comme fausses : False, None, zéro quel que soit le type, la chaîne vide et tout conteneur vide (y compris les chaînes, n-uplets, listes, dictionnaires, ensembles, ensembles gelés). Toutes les autres valeurs sont considérées comme vraies. Les objets allogènes peuvent personnaliser leur table de vérité en implémentant une méthode __bool__().

L’opérateur not produit True si son argument est faux, False sinon.

L’expression x and y commence par évaluer x ; si x est faux, sa valeur est renvoyée ; sinon, y est évalué et la valeur résultante est renvoyée.

L’expression x or y commence par évaluer x ; si x est vrai, sa valeur est renvoyée ; sinon, y est évalué et la valeur résultante est renvoyée.

Note that neither and nor or restrict the value and type they return to False and True, but rather return the last evaluated argument. This is sometimes useful, e.g., if s is a string that should be replaced by a default value if it is empty, the expression s or 'foo' yields the desired value. Because not has to create a new value, it returns a boolean value regardless of the type of its argument (for example, not 'foo' produces False rather than ''.)

6.12. Expressions conditionnelles

conditional_expression ::=  or_test ["if" or_test "else" expression]
expression             ::=  conditional_expression | lambda_expr
expression_nocond      ::=  or_test | lambda_expr_nocond

Les expressions conditionnelles (parfois appelées « opérateur ternaire ») sont les moins prioritaires de toutes les opérations Python.

L’expression x if C else y commence par évaluer la condition C. Si C est vrai, alors x est évalué et sa valeur est renvoyée ; sinon, y est évalué et sa valeur est renvoyée.

Voir la PEP 308 [https://www.python.org/dev/peps/pep-0308] pour plus de détails sur les expressions conditionnelles.

6.13. Expressions lambda

lambda_expr        ::=  "lambda" [parameter_list] ":" expression
lambda_expr_nocond ::=  "lambda" [parameter_list] ":" expression_nocond

Les expressions lambda sont utilisées pour créer des fonctions anonymes. L’expression lambda parameters: expression produit un objet fonction. Cet objet anonyme se comporte comme un objet fonction défini par :

def <lambda>(parameters):
    return expression

Voir la section Définition de fonctions pour la syntaxe des listes de paramètres. Notez que les fonctions créées par des expressions lambda ne peuvent pas contenir d’instructions ou d’annotations.

6.14. Listes d’expressions

expression_list    ::=  expression ("," expression)* [","]
starred_list       ::=  starred_item ("," starred_item)* [","]
starred_expression ::=  expression | (starred_item ",")* [starred_item]
starred_item       ::=  expression | "*" or_expr

Sauf lorsqu’elle fait partie d’un agencement de liste ou d’ensemble, une liste d’expressions qui contient au moins une virgule produit un n-uplet (tuple). La longueur du n-uplet est le nombre d’expressions dans la liste. Les expressions sont évaluées de la gauche vers la droite.

Un astérisque * indique dépaquetage d’itérable (iterable unpacking en anglais). Son opérande doit être un iterable. L’itérable est développé en une séquence d’éléments qui sont inclus dans un nouvel objet tuple, list ou set à l’emplacement du dépaquetage.

Nouveau dans la version 3.5: dépaquetage d’itérables dans les listes d’expressions, proposé à l’origine par la PEP 448 [https://www.python.org/dev/peps/pep-0448].

La virgule finale est nécessaire pour créer un singleton (c’est-à-dire un n-uplet composé d’un seul élément) : elle est optionnelle dans tous les autres cas. Une expression seule sans virgule finale ne crée pas un n-uplet mais produit la valeur de cette expression (pour créer un tuple vide, utilisez une paire de parenthèses vide : ()).

6.15. Ordre d’évaluation

Python évalue les expressions de la gauche vers la droite. Remarquez que lors de l’évaluation d’une assignation, la partie droite de l’assignation est évaluée avant la partie gauche.

Dans les lignes qui suivent, les expressions sont évaluées suivant l’ordre arithmétique de leurs suffixes :

expr1, expr2, expr3, expr4
(expr1, expr2, expr3, expr4)
{expr1: expr2, expr3: expr4}
expr1 + expr2 * (expr3 - expr4)
expr1(expr2, expr3, *expr4, **expr5)
expr3, expr4 = expr1, expr2

6.16. Priorités des opérateurs

Le tableau suivant résume les priorités des opérateurs en Python, du moins prioritaire au plus prioritaire. Les opérateurs qui sont dans la même case ont la même priorité. À moins que la syntaxe ne soit explicitement indiquée, les opérateurs sont binaires. Les opérateurs dans la même cases regroupent de la gauche vers la droite (sauf pour la puissance qui regroupe de la droite vers la gauche).

Notez que les comparaisons, les tests d’appartenance et les tests d’identifiants possèdent tous la même priorité et s’enchaînent de la gauche vers la droite comme décrit dans la section Comparaisons.

Opérateur

Description

lambda

Expression lambda

if – else

Expressions conditionnelle

or

OR (booléen)

and

AND (booléen)

not x

NOT (booléen)

in, not in, is, is not, <, <=, >, >=, !=, ==

Comparaisons, y compris les tests d’appartenance et les tests d’identifiants

|

OR (bit à bit)

^

XOR (bit à bit)

&

AND (bit à bit)

<<, >>

décalages

+, -

Addition et soustraction

*, @, /, //, %

Multiplication, multiplication de matrices, division, division entière, reste 5

+x, -x, ~x

NOT (positif, négatif, bit à bit)

**

Puissance 6

await x

Expression await

x[indice], x[indice:indice], x(arguments...), x.attribut

indiçage, tranches, appel, référence à un attribut

(expressions...), [expressions...], {clé: valeur...}, {expressions...}

liaison ou agencement de n-uplet, agencement de liste, agencement de dictionnaire, agencement d’ensemble

Notes

1

Bien que abs(x%y) < abs(y) soit vrai mathématiquement, ce n’est pas toujours vrai pour les nombres à virgule flottante en raison des arrondis. Par exemple, en supposant que Python tourne sur une plateforme où les float sont des nombres à double précision IEEE 754, afin que -1e-100 % 1e100 soit du même signe que 1e100, le résultat calculé est -1e-100 + 1e100, qui vaut exactement 1e100 dans ce standard. Or, la fonction math.fmod() renvoie un résultat dont le signe est le signe du premier argument, c’est-à-dire -1e-100 dans ce cas. La meilleure approche dépend de l’application.

2

Si x est très proche d’un multiple entier de y, il est possible que x/y soit supérieur de un par rapport à (x-x%y)//y en raison des arrondis. Dans de tels cas, Python renvoie le second résultat afin d’avoir divmod(x,y)[0] * y + x % y le plus proche de x.

3

Le standard Unicode distingue les points codes (code points en anglais, par exemple U+0041) et les caractères abstraits (abstract characters en anglais, par exemple « LATIN CAPITAL LETTER A »). Bien que la plupart des caractères abstraits de l’Unicode ne sont représentés que par un seul point code, il y a un certain nombre de caractères abstraits qui peuvent être représentés par une séquence de plus qu’un point code. Par exemple, le caractère abstrait « LATIN CAPITAL LETTER C WITH CEDILLA » peut être représenté comme un unique caractère précomposé au point code U+00C7, ou en tant que séquence d’un caractère de base à la position U+0043 (LATIN CAPITAL LETTER C) du code, suivi par un caractère combiné à la position U+0327 (COMBINING CEDILLA) du code.

Les opérateurs de comparaison des chaînes opèrent au niveau des points codes Unicode. Cela peut être déroutant pour des humains. Par exemple, "\u00C7" == "\u0043\u0327" renvoie False, bien que les deux chaînes représentent le même caractère abstrait « LATIN CAPITAL LETTER C WITH CEDILLA ».

Pour comparer des chaînes au niveau des caractères abstraits (afin d’avoir quelque chose d’intuitif pour les humains), utilisez unicodedata.normalize().

4

En raison du ramasse-miettes automatique et de la nature dynamique des descripteurs, vous pouvez être confronté à un comportement semblant bizarre lors de certaines utilisations de l’opérateur is, par exemple si cela implique des comparaisons entre des méthodes d’instances ou des constantes. Allez vérifier dans la documentation pour plus d’informations.

5

L’opérateur % est aussi utilisé pour formater les chaînes de caractères ; il y possède la même priorité.

6

L’opérateur puissance ** est moins prioritaire qu’un opérateur unaire arithmétique ou bit à bit sur sa droite. Ainsi, 2**-1 vaut 0.5.

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7. Les instructions simples

Une instruction simple est contenue dans une seule ligne logique. Plusieurs instructions simples peuvent être écrites sur une seule ligne, séparées par des points-virgules. La syntaxe d’une instruction simple est :

simple_stmt ::=  expression_stmt
                 | assert_stmt
                 | assignment_stmt
                 | augmented_assignment_stmt
                 | annotated_assignment_stmt
                 | pass_stmt
                 | del_stmt
                 | return_stmt
                 | yield_stmt
                 | raise_stmt
                 | break_stmt
                 | continue_stmt
                 | import_stmt
                 | future_stmt
                 | global_stmt
                 | nonlocal_stmt

7.1. Les expressions

Les expressions sont utilisées (généralement de manière interactive) comme instructions pour calculer et écrire des valeurs, appeler une procédure (une fonction dont le résultat renvoyé n’a pas d’importance ; en Python, les procédures renvoient la valeur None). D’autres utilisations des expressions sont autorisées et parfois utiles. La syntaxe pour une expression en tant qu’instruction est :

expression_stmt ::=  starred_expression

Ce genre d’instruction évalue la liste d’expressions (qui peut se limiter à une seule expression).

En mode interactif, si la valeur n’est pas None, elle est convertie en chaîne en utilisant la fonction native repr() et la chaîne résultante est écrite sur la sortie standard sur sa propre ligne. Si le résultat est None, rien n’est écrit ce qui est usuel pour les appels de procédures.

7.2. Les assignations

Les assignations sont utilisées pour lier ou relier des noms à des valeurs et modifier des attributs ou des éléments d’objets muables :

assignment_stmt ::=  (target_list "=")+ (starred_expression | yield_expression)
target_list     ::=  target ("," target)* [","]
target          ::=  identifier
                     | "(" [target_list] ")"
                     | "[" [target_list] "]"
                     | attributeref
                     | subscription
                     | slicing
                     | "*" target

Voir la section Primaires pour la définition des syntaxes de attributeref, subscription et slicing.

Une assignation évalue la liste d’expressions (gardez en mémoire que ce peut être une simple expression ou une liste dont les éléments sont séparés par des virgules, cette dernière produisant un n-uplet) et assigne l’unique objet résultant à chaque liste cible, de la gauche vers la droite.

Une assignation est définie récursivement en fonction de la forme de la cible (une liste). Quand la cible est une partie d’un objet muable (une référence à un attribut, une sélection ou une tranche), l’objet muable doit effectuer l’assignation au final et décider de sa validité, voire lever une exception si l’assignation n’est pas acceptable. Les règles suivies par les différents types et les exceptions levées sont données dans les définitions des types d’objets (voir la section Hiérarchie des types standards).

L’assignation d’un objet à une liste cible, optionnellement entourée par des parenthèses ou des crochets, est définie récursivement comme suit.

If the target list is a single target with no trailing comma, optionally in parentheses, the object is assigned to that target.

Sinon : l’objet doit être un itérable avec le même nombre d’éléments qu’il y a de cibles dans la liste cible ; les éléments sont assignés, de la gauche vers la droite, vers les cibles correspondantes.

Si la liste cible contient une cible préfixée par un astérisque, appelée cible étoilée (starred target en anglais) : l’objet doit être un itérable avec au moins autant d’éléments qu’il y a de cibles dans la liste cible, moins un. Les premiers éléments de l’itérable sont assignés, de la gauche vers la droite, aux cibles avant la cible étoilée. Les éléments de queue de l’itérable sont assignés aux cibles après la cible étoilée. Une liste des éléments restants dans l’itérable est alors assignée à la cible étoilée (cette liste peut être vide).

Sinon : l’objet doit être un itérable avec le même nombre d’éléments qu’il y a de cibles dans la liste cible ; les éléments sont assignés, de la gauche vers la droite, vers les cibles correspondantes.

L’assignation d’un objet vers une cible unique est définie récursivement comme suit.

Si la cible est une variable (un nom) :

si le nom n’apparaît pas dans une instruction global ou nonlocal (respectivement) du bloc de code courant, le nom est lié à l’objet dans l’espace courant des noms locaux ;

sinon le nom est lié à l’objet dans l’espace des noms globaux ou dans un espace de nommage plus large déterminé par nonlocal, respectivement.

Le lien du nom est modifié si le nom était déjà lié. Ceci peut faire que le compteur de références de l’objet auquel le nom était précédemment lié tombe à zéro, entrainant la dé-allocation de l’objet et l’appel de son destructeur (s’il existe).

Si la cible est une référence à un attribut : l’expression primaire de la référence est évaluée. Elle doit produire un objet avec des attributs que l’on peut assigner : si ce n’est pas le cas, une TypeError est levée. Python demande alors à cet objet d’assigner l’attribut donné ; si ce n’est pas possible, une exception est levée (habituellement, mais pas nécessairement, AttributeError).

Note : si l’objet est une instance de classe et que la référence à l’attribut apparaît des deux côtés de l’opérateur d’assignation, l’expression « à droite », a.x peut accéder soit à l’attribut d’instance ou (si cet attribut d’instance n’existe pas) à l’attribut de classe. L’expression cible « à gauche » a.x est toujours définie comme un attribut d’instance, en le créant si nécessaire. Ainsi, les deux occurrences de a.x ne font pas nécessairement référence au même attribut : si l’expression « à droite » fait référence à un attribut de classe, l’expression « à gauche » crée un nouvel attribut d’instance comme cible de l’assignation :

class Cls:
    x = 3             # class variable
inst = Cls()
inst.x = inst.x + 1   # writes inst.x as 4 leaving Cls.x as 3

Cette description ne s’applique pas nécessairement aux attributs des descripteurs, telles que les propriétés créées avec property().

Si la cible est une sélection : l’expression primaire de la référence est évaluée. Elle doit produire soit un objet séquence mutable (telle qu’une liste) ou un objet tableau de correspondances (tel qu’un dictionnaire). Ensuite, l’expression de la sélection est évaluée.

Si la primaire est un objet séquence mutable (telle qu’une liste), la sélection doit produire un entier. S’il est négatif, la longueur de la séquence lui est ajoutée. La valeur résultante doit être un entier positif ou nul, plus petit que la longueur de la séquence, et Python demande à la séquence d’assigner l’objet à l’élément se trouvant à cet indice. Si l’indice est hors limites, une IndexError est levée (une assignation à une sélection dans une séquence ne peut pas ajouter de nouveaux éléments à une liste).

Si la primaire est un objet tableau de correspondances (tel qu’un dictionnaire), la sélection doit être d’un type compatible avec le type des clés ; Python demande alors au tableau de correspondances de créer un couple clé-valeur qui associe la sélection à l’objet assigné. Ceci peut remplacer une correspondance déjà existante pour une clé donnée ou insérer un nouveau couple clé-valeur.

Pour les objets allogènes, la méthode __setitem__() est appelée avec les arguments appropriés.

Si la cible est une tranche : l’expression primaire de la référence est évaluée. Elle doit produire un objet séquence mutable (telle qu’une liste). L’objet assigné doit être un objet séquence du même type. Ensuite, les expressions de la borne inférieure et de la borne supérieure sont évaluées, dans la mesure où elles sont spécifiées (les valeurs par défaut sont zéro et la longueur de la séquence). Les bornes doivent être des entiers. Si une borne est négative, la longueur de la séquence lui est ajoutée. Les bornes résultantes sont coupées pour être dans l’intervalle zéro – longueur de la séquence, inclus. Finalement, Python demande à l’objet séquence de remplacer la tranche avec les éléments de la séquence à assigner. La longueur de la tranche peut être différente de la longueur de la séquence à assigner, ce qui modifie alors la longueur de la séquence cible, si celle-ci le permet.

CPython implementation detail: Dans l’implémentation actuelle, la syntaxe pour les cibles est similaire à celle des expressions. Toute syntaxe invalide est rejetée pendant la phase de génération de code, ce qui produit des messages d’erreurs moins détaillés.

Bien que la définition de l’assignation implique que le passage entre le côté gauche et le côté droit soient « simultanés » (par exemple, a, b = b, a permute les deux variables), le passage à l’intérieur des collections de variables que l’on assigne intervient de la gauche vers la droite, ce qui peut entraîner quelques confusions. Par exemple, le programme suivant affiche [0, 2] :

x = [0, 1]
i = 0
i, x[i] = 1, 2         # i is updated, then x[i] is updated
print(x)

Voir aussi

PEP 3132 [https://www.python.org/dev/peps/pep-3132] – dépaquetage étendu d’itérable

Spécification de la fonctionnalité *cible.

7.2.1. Les assignations augmentées

Une assignation augmentée est la combinaison, dans une seule instruction, d’une opération binaire et d’une assignation :

augmented_assignment_stmt ::=  augtarget augop (expression_list | yield_expression)
augtarget                 ::=  identifier | attributeref | subscription | slicing
augop                     ::=  "+=" | "-=" | "*=" | "@=" | "/=" | "//=" | "%=" | "**="
                               | ">>=" | "<<=" | "&=" | "^=" | "|="

Voir la section Primaires pour la définition des syntaxes des trois derniers symboles.

Une assignation augmentée évalue la cible (qui, au contraire des assignations normales, ne peut pas être un dépaquetage) et la liste d’expressions, effectue l’opération binaire (spécifique au type d’assignation) sur les deux opérandes et assigne le résultat à la cible originale. La cible n’est évaluée qu’une seule fois.

Une assignation augmentée comme x += 1 peut être ré-écrite en x = x + 1 pour obtenir un effet similaire, mais pas exactement équivalent. Dans la version augmentée. x n’est évalué qu’une seule fois. Aussi, lorsque c’est possible, l’opération concrète est effectuée sur place, c’est-à-dire que plutôt que de créer un nouvel objet et l’assigner à la cible, c’est le vieil objet qui est modifié.

Au contraire des assignations normales, les assignations augmentées évaluent la partie gauche avant d’évaluer la partie droite. Par exemple, a[i] += f(x) commence par s’intéresser à a[i], puis Python évalue f(x), effectue l’addition et, enfin, écrit le résultat dans a[i].

À l’exception de l’assignation de tuples et de cibles multiples dans une seule instruction, l’assignation effectuée par une assignation augmentée est traitée de la même manière qu’une assignation normale. De même, à l’exception du comportement possible sur place, l’opération binaire effectuée par assignation augmentée est la même que les opérations binaires normales.

Pour les cibles qui sont des références à des attributs, la même mise en garde sur les attributs de classe et d’instances s’applique que pour les assignations normales.

7.2.2. Les assignations annotées

Une assignation annotée est la combinaison, dans une seule instruction, d’une annotation de variable ou d’attribut et d’une assignation optionnelle :

annotated_assignment_stmt ::=  augtarget ":" expression ["=" expression]

La différence avec une assignation normale (voir Les assignations) est qu’une seule cible et qu’une seule valeur à droite ne sont autorisées.

Pour des noms simples en tant que cibles d’assignation, dans une portée de classe ou de module, les annotations sont évaluées et stockées dans un attribut de classe ou de module spécial, __annotations__, qui est un dictionnaire dont les clés sont les noms de variables (réécrits si le nom est privé) et les valeurs sont les annotations. Cet attribut est accessible en écriture et est automatiquement créé au démarrage de l’exécution du corps de la classe ou du module, si les annotations sont trouvées statiquement.

Pour les expressions en tant que cibles d’assignations, les annotations sont évaluées dans la portée de la classe ou du module, mais ne sont pas stockées.

Si le nom est annoté dans la portée d’une fonction, alors ce nom est local à cette portée. Les annotations ne sont jamais évaluées et stockées dans les portées des fonctions.

Si la partie droite est présente, une assignation annotée effectue l’assignation en tant que telle avant d’évaluer les annotations (là où c’est possible). Si la partie droite n’est pas présente pour une cible d’expression, alors l’interpréteur évalue la cible sauf pour le dernier appel à __setitem__() ou __setattr__().

Voir aussi

PEP 526 [https://www.python.org/dev/peps/pep-0526] - Syntax for Variable Annotations

The proposal that added syntax for annotating the types of variables (including class variables and instance variables), instead of expressing them through comments.

PEP 484 [https://www.python.org/dev/peps/pep-0484] - Type hints

The proposal that added the typing module to provide a standard syntax for type annotations that can be used in static analysis tools and IDEs.

7.3. L’instruction assert

Les instructions assert sont une manière pratique d’insérer des tests de débogage au sein d’un programme :

assert_stmt ::=  "assert" expression ["," expression]

La forme la plus simple, assert expression, est équivalente à

if __debug__:
    if not expression: raise AssertionError

La forme étendue, assert expression1, expression2, est équivalente à

if __debug__:
    if not expression1: raise AssertionError(expression2)

These equivalences assume that __debug__ and AssertionError refer to the built-in variables with those names. In the current implementation, the built-in variable __debug__ is True under normal circumstances, False when optimization is requested (command line option -O). The current code generator emits no code for an assert statement when optimization is requested at compile time. Note that it is unnecessary to include the source code for the expression that failed in the error message; it will be displayed as part of the stack trace.

Assigner vers __debug__ est illégal. La valeur de cette variable native est déterminée au moment où l’interpréteur démarre.

7.4. L’instruction pass

pass_stmt ::=  "pass"

pass est une opération vide — quand elle est exécutée, rien ne se passe. Elle est utile comme bouche-trou lorsqu’une instruction est syntaxiquement requise mais qu’aucun code ne doit être exécuté. Par exemple :

def f(arg): pass    # a function that does nothing (yet)

class C: pass       # a class with no methods (yet)

7.5. L’instruction del

del_stmt ::=  "del" target_list

La suppression est récursivement définie de la même manière que l’assignation. Plutôt que de détailler cela de manière approfondie, voici quelques indices.

La suppression d’une liste cible (target_list dans la grammaire ci-dessus) supprime récursivement chaque cible, de la gauche vers la droite.

La suppression d’un nom détruit le lien entre ce nom dans l’espace des noms locaux, ou l’espace des noms globaux si ce nom apparaît dans une instruction global dans le même bloc de code. Si le nom n’est pas lié, une exception NameError est levée.

La suppression d’une référence à un attribut, une sélection ou une tranche est passée à l’objet primaire concerné : la suppression d’une tranche est en général équivalente à l’assignation d’une tranche vide du type adéquat (mais ceci est au final déterminé par l’objet que l’on tranche).

Modifié dans la version 3.2: Auparavant, il était illégal de supprimer un nom dans l’espace des noms locaux si celui-ci apparaissait comme variable libre dans un bloc imbriqué.

7.6. L’instruction return

return_stmt ::=  "return" [expression_list]

return ne peut être placée qu’à l’intérieur d’une définition de fonction, pas à l’intérieur d’une définition de classe.

Si une liste d’expressions (expression_list dans la grammaire ci-dessus) est présente, elle est évaluée, sinon None est utilisée comme valeur par défaut.

return quitte l’appel à la fonction courante avec la liste d’expressions (ou None) comme valeur de retour.

Quand return fait sortir d’une instruction try avec une clause finally, cette clause finally est exécutée avant de réellement quitter la fonction.

Dans une fonction générateur, l’instruction return indique que le générateur est terminé et provoque la levée d’une StopIteration. La valeur de retour (s’il y en a une) est utilisée comme argument pour construire l’exception StopIteration et devient l’attribut StopIteration.value.

Dans une fonction générateur asynchrone, une instruction return vide indique que le générateur asynchrone est terminé et provoque la levée d’une StopAsyncIteration. Une instruction return non vide est une erreur de syntaxe dans une fonction générateur asynchrone.

7.7. L’instruction yield

yield_stmt ::=  yield_expression

L’instruction yield est sémantiquement équivalente à une expression yield. L’instruction yield peut être utilisée pour omettre les parenthèses qui seraient autrement requises dans l’instruction équivalente d’expression yield. Par exemple, les instructions yield

yield <expr>
yield from <expr>

sont équivalentes aux instructions expressions yield

(yield <expr>)
(yield from <expr>)

Les expressions et les instructions yield sont utilisées seulement dans la définition des fonctions générateurs et apparaissent uniquement dans le corps de la fonction générateur. L’utilisation de yield dans la définition d’une fonction est suffisant pour que cette définition crée une fonction générateur au lieu d’une fonction normale.

Pour tous les détails sur la sémantique de yield, reportez-vous à la section Expressions yield.

7.8. L’instruction raise

raise_stmt ::=  "raise" [expression ["from" expression]]

Si aucune expression n’est présente, raise propage la dernière exception active dans la portée courante. Si aucune exception n’est active dans la portée courante, une exception RuntimeError est levée, indiquant que c’est une erreur.

Sinon, raise évalue la première expression en tant qu’objet exception. Ce doit être une sous-classe ou une instance de BaseException. Si c’est une classe, l’instance de l’exception est obtenue en instanciant la classe sans argument (au moment voulu).

Le type de l’exception est la classe de l’instance de l’exception, la value est l’instance elle-même.

Normalement, un objet trace d’appels est créé automatiquement quand une exception est levée et il lui est rattaché comme attribut __traceback__, en lecture-écriture. Vous pouvez créer une exception et définir votre propre trace d’appels d’un seul coup en utilisant la méthode des exceptions with_traceback() (qui renvoie la même instance d’exception avec sa trace d’appels passée en argument), comme ceci :

raise Exception("foo occurred").with_traceback(tracebackobj)

La clause from est utilisée pour chaîner les exceptions : si vous la fournissez, la seconde « expression » doit être une autre classe ou instance d’exception, qui est rattachée à l’exception levée en tant qu’attribut __cause__ (en lecture-écriture). Si l’exception levée n’est pas gérée, les deux exceptions sont affichées :

>>> try:
...     print(1 / 0)
... except Exception as exc:
...     raise RuntimeError("Something bad happened") from exc
...
Traceback (most recent call last):
  File "<stdin>", line 2, in <module>
ZeroDivisionError: division by zero

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "<stdin>", line 4, in <module>
RuntimeError: Something bad happened

Un mécanisme similaire est mis en œuvre implicitement si une exception est levée à l’intérieur d’un gestionnaire d’exception ou d’une clause finally : la première exception est rattachée à l’attribut __context__ de la nouvelle exception :

>>> try:
...     print(1 / 0)
... except:
...     raise RuntimeError("Something bad happened")
...
Traceback (most recent call last):
  File "<stdin>", line 2, in <module>
ZeroDivisionError: division by zero

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "<stdin>", line 4, in <module>
RuntimeError: Something bad happened

Le chaînage d’exceptions peut être explicitement supprimé en spécifiant None dans la clause from :

>>> try:
...     print(1 / 0)
... except:
...     raise RuntimeError("Something bad happened") from None
...
Traceback (most recent call last):
  File "<stdin>", line 4, in <module>
RuntimeError: Something bad happened

Des informations complémentaires sur les exceptions sont disponibles dans la section Exceptions et sur la gestion des exceptions dans la section L’instruction try.

Modifié dans la version 3.3: None est dorénavant autorisée en tant que Y dans raise X from Y.

Nouveau dans la version 3.3: L’attribut __suppress_context__ pour supprimer l’affichage automatique du contexte de l’exception.

7.9. L’instruction break

break_stmt ::=  "break"

Une instruction break ne peut apparaître qu’à l’intérieur d’une boucle for ou while, mais pas dans une définition de fonction ou de classe à l’intérieur de cette boucle.

Elle termine la boucle la plus imbriquée, shuntant l’éventuelle clause else de la boucle.

Si une boucle for est terminée par un break, la cible qui contrôle la boucle garde sa valeur.

Quand break passe le contrôle en dehors d’une instruction try qui comporte une clause finally, cette clause finally est exécutée avant de quitter la boucle.

7.10. L’instruction continue

continue_stmt ::=  "continue"

L’instruction continue ne peut apparaître qu’à l’intérieur d’une boucle for ou while, mais pas dans une définition de fonction ou de classe ni dans une clause finally, à l’intérieur de cette boucle. Elle fait continuer le flot d’exécution au prochain cycle de la boucle la plus imbriquée.

Quand continue passe le contrôle en dehors d’une instruction try qui comporte une clause finally, cette clause finally est exécutée avant de commencer le cycle suivant de la boucle.

7.11. L’instruction import

import_stmt     ::=  "import" module ["as" identifier] ("," module ["as" identifier])*
                     | "from" relative_module "import" identifier ["as" identifier]
                     ("," identifier ["as" identifier])*
                     | "from" relative_module "import" "(" identifier ["as" identifier]
                     ("," identifier ["as" identifier])* [","] ")"
                     | "from" module "import" "*"
module          ::=  (identifier ".")* identifier
relative_module ::=  "."* module | "."+

L’instruction de base import (sans clause from) est exécutée en deux étapes :

trouve un module, le charge et l’initialise si nécessaire

définit un ou des noms (name dans la grammaire ci-dessus) dans l’espace des noms locaux de la portée où l’instruction import apparaît.

Quand l’instruction contient plusieurs clauses (séparées par des virgules), les deux étapes sont menées séparément pour chaque clause, comme si les clauses étaient séparées dans des instructions d’importations individuelles.

Les détails de la première étape, de recherche et de chargement des modules sont décrits largement dans la section relative au système d’importation, qui décrit également les différents types de paquets et modules qui peuvent être importés, de même que les points d’entrée pouvant être utilisés pour personnaliser le système d’importation. Notez que des erreurs dans cette étape peuvent indiquer soit que le module n’a pas été trouvé, soit qu’une erreur s’est produite lors de l’initialisation du module, ce qui comprend l’exécution du code du module.

Si le module requis est bien récupéré, il est mis à disposition de l’espace de nommage local suivant l’une des trois façons suivantes :

Si le nom du module est suivi par as, alors le nom suivant as est directement lié au module importé.

si aucun autre nom n’est spécifié et que le module en cours d’importation est un module de niveau le plus haut, le nom du module est lié dans l’espace des noms locaux au module importé ;

si le module en cours d’importation n’est pas un module de plus haut niveau, alors le nom du paquet de plus haut niveau qui contient ce module est lié dans l’espace des noms locaux au paquet de plus haut niveau. Vous pouvez accéder au module importé en utilisant son nom pleinement qualifié et non directement.

La forme from utilise un processus un peu plus complexe :

trouve le module spécifié dans la clause from, le charge et l’initialise si nécessaire ;

pour chaque nom spécifié dans les clauses import :

vérifie si le module importé possède un attribut avec ce nom ;

si non, essaie d’importer un sous-module avec ce nom puis vérifie si le module importé possède lui-même cet attribut ;

si l’attribut n’est pas trouvé, une ImportError est levée.

sinon, une référence à cette valeur est stockée dans l’espace des noms locaux, en utilisant le nom de la clause as si elle est présente, sinon en utilisant le nom de l’attribut.

Exemples :

import foo                 # foo imported and bound locally
import foo.bar.baz         # foo.bar.baz imported, foo bound locally
import foo.bar.baz as fbb  # foo.bar.baz imported and bound as fbb
from foo.bar import baz    # foo.bar.baz imported and bound as baz
from foo import attr       # foo imported and foo.attr bound as attr

Si la liste des noms est remplacée par une étoile ('*'), tous les noms publics définis dans le module sont liés dans l’espace des noms locaux de la portée où apparaît l’instruction import.

Les noms publics définis par un module sont déterminés en cherchant dans l’espace de nommage du module une variable nommée __all__ ; Si elle est définie, elle doit être une séquence de chaînes désignant les noms définis ou importés par ce module. Les noms donnés dans __all__ sont tous considérés publics et doivent exister. Si __all__ n’est pas définie, l’ensemble des noms publics contient tous les noms trouvés dans l’espace des noms du module qui ne commencent pas par un caractère souligné (_). __all__ doit contenir toute l’API publique. Elle est destinée à éviter l’exportation accidentelle d’éléments qui ne font pas partie de l’API (tels que des modules de bibliothèques qui ont été importés et utilisés à l’intérieur du module).

La forme d”import avec astérisque — from module import * — est autorisée seulement au niveau du module. Si vous essayez de l’utiliser dans une définition de classe ou de fonction, cela lève une SyntaxError.

Quand vous spécifiez les modules à importer, vous n’avez pas besoin de spécifier les noms absolus des modules. Quand un module ou un paquet est contenu dans un autre paquet, il est possible d’effectuer une importation relative à l’intérieur du même paquet de plus haut niveau sans avoir à mentionner le nom du paquet. En utilisant des points en entête du module ou du paquet spécifié après from, vous pouvez spécifier combien de niveaux vous souhaitez remonter dans la hiérarchie du paquet courant sans spécifier de nom exact. Un seul point en tête signifie le paquet courant où se situe le module qui effectue l’importation. Deux points signifient de remonter d’un niveau. Trois points, remonter de deux niveaux et ainsi de suite. Ainsi, si vous exécutez from . import mod dans un module du paquet pkg, vous importez finalement pkg.mod. Et si vous exécutez from ..souspkg2 import mod depuis pkg.souspkg1, vous importez finalement pkg.souspkg2.mod. La spécification des importations relatives se situe dans la PEP 328 [https://www.python.org/dev/peps/pep-0328].

importlib.import_module() est fournie pour gérer les applications qui déterminent dynamiquement les modules à charger.

7.11.1. L’instruction future

Une instruction future est une directive à l’attention du compilateur afin qu’un module particulier soit compilé en utilisant une syntaxe ou une sémantique qui sera disponible dans une future version de Python où cette fonctionnalité est devenue un standard.

L’instruction future a vocation à faciliter les migrations vers les futures versions de Python qui introduisent des changements incompatibles au langage. Cela permet l’utilisation de nouvelles fonctionnalités module par module avant qu’une version n’officialise cette fonctionnalité comme un standard.

future_stmt ::=  "from" "__future__" "import" feature ["as" identifier]
                 ("," feature ["as" identifier])*
                 | "from" "__future__" "import" "(" feature ["as" identifier]
                 ("," feature ["as" identifier])* [","] ")"
feature     ::=  identifier

Une instruction future doit apparaître en haut du module. Les seules lignes autorisées avant une instruction future sont :

la chaîne de documentation du module (si elle existe),

des commentaires,

des lignes vides et

d’autres instructions future.

Les fonctionnalités (feature dans la grammaire ci-dessus) reconnues par Python 3.0 sont absolute_import, division, generators, unicode_literals, print_function, nested_scopes et with_statement. Elles sont toutes redondantes car elles sont de toute manière activées ; elles ne sont conservées que par souci de compatibilité descendante.

Une instruction future est reconnue et traitée spécialement au moment de la compilation : les modifications à la sémantique des constructions de base sont souvent implémentées en générant un code différent. Il peut même arriver qu’une nouvelle fonctionnalité ait une syntaxe incompatible (tel qu’un nouveau mot réservé) ; dans ce cas, le compilateur a besoin d’analyser le module de manière différente. De telles décisions ne peuvent pas être différées au moment de l’exécution.

Pour une version donnée, le compilateur sait quelles fonctionnalités ont été définies et lève une erreur à la compilation si une instruction future contient une fonctionnalité qui lui est inconnue.

La sémantique à l’exécution est la même que pour toute autre instruction d’importation : il existe un module standard __future__, décrit plus loin, qui est importé comme les autres au moment où l’instruction future est exécutée.

La sémantique particulière à l’exécution dépend des fonctionnalités apportées par l’instruction future.

Notez que l’instruction suivante est tout à fait normale :

import __future__ [as name]

Ce n’est pas une instruction future ; c’est une instruction d’importation ordinaire qui n’a aucune sémantique particulière ou restriction de syntaxe.

Le code compilé par des appels aux fonctions natives exec() et compile() dans un module M comportant une instruction future utilise, par défaut, la nouvelle syntaxe ou sémantique associée à l’instruction future. Ceci peut être contrôle par des arguments optionnels à compile() — voir la documentation de cette fonction pour les détails.

Une instruction future entrée à l’invite de l’interpréteur interactif est effective pour le reste de la session de l’interpréteur. Si l’interpréteur est démarré avec l’option -i, qu’un nom de script est passé pour être exécuté et que ce script contient une instruction future, elle est effective pour la session interactive qui démarre après l’exécution du script.

Voir aussi

PEP 236 [https://www.python.org/dev/peps/pep-0236] — retour vers le __future__

La proposition originale pour le mécanisme de __future__.

7.12. L’instruction global

global_stmt ::=  "global" identifier ("," identifier)*

L’instruction global est une déclaration qui couvre l’ensemble du bloc de code courant. Elle signifie que les noms (identifier dans la grammaire ci-dessus) listés doivent être interprétés comme globaux. Il est impossible d’assigner une variable globale sans global, mais rappelez-vous que les variables libres peuvent faire référence à des variables globales sans avoir été déclarées en tant que telles.

Les noms listés dans l’instruction global ne doivent pas être utilisés, dans le même bloc de code, avant l’instruction global.

Les noms listés dans l’instruction global ne doivent pas être définis en tant que paramètre formel, cible d’une boucle for, dans une définition de class, de fonction, d’instruction import ou une annotation de variable.

CPython implementation detail: L’implémentation actuelle ne vérifie pas toutes ces interdictions mais n’abusez pas de cette liberté car les implémentations futures pourraient faire la vérification ou modifier le comportement du programme sans vous avertir.

Note pour les programmeurs : global est une directive à l’attention de l’analyseur syntaxique. Elle s’applique uniquement au code analysé en même temps que l’instruction global. En particulier, une instruction global contenue dans une chaîne ou un objet code fourni à la fonction native exec() n’affecte pas le code contenant cet appel et le code contenu dans un telle chaîne n’est pas affecté par une instruction global placée dans le code contenant l’appel. Il en est de même pour les fonctions eval() et compile().

7.13. L’instruction nonlocal

nonlocal_stmt ::=  "nonlocal" identifier ("," identifier)*

L’instruction nonlocal fait que les noms listés font référence aux variables liées précédemment, dans la portée la plus petite entourant l’instruction, à l’exception des variables globales. C’est important car le comportement par défaut pour les liaisons consiste à chercher d’abord dans l’espace des noms locaux. Cette instruction permet à du code encapsulé de se lier à des variables en dehors de la portée locale du code mais sans avoir de portée globale (c’est-à-dire de niveau module).

Les noms (identifier dans la grammaire ci-dessus) listés dans l’instruction nonlocal, au contraire de ceux listés dans une instruction global, doivent faire référence à des liaisons pré-existantes dans les portées englobantes (en effet, la portée dans laquelle devrait être créée la liaison ne peut pas être déterminée a priori).

Les noms listés dans l’instruction nonlocal ne doivent entrer en collision avec des liaisons déjà établies dans la portée locale.

Voir aussi

PEP 3104 [https://www.python.org/dev/peps/pep-3104] – Accès à des noms en dehors de la portée locale

Les spécifications pour l’instruction nonlocal.

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8. Instructions composées

Les instructions composées contiennent d’autres (groupes d’) instructions ; elles affectent ou contrôlent l’exécution de ces autres instructions d’une manière ou d’une autre. En général, une instruction composée couvre plusieurs lignes bien que, dans sa forme la plus simple, une instruction composée peut tenir sur une seule ligne.

Les instructions if, while et for implémentent les constructions classiques de contrôle de flux. try spécifie des gestionnaires d’exception et du code de nettoyage pour un groupe d’instructions, tandis que l’instruction with permet l’exécution de code d’initialisation et de finalisation autour d’un bloc de code. Les définitions de fonctions et de classes sont également, au sens syntaxique, des instructions composées.

Une instruction composée comporte une ou plusieurs « clauses ». Une clause se compose d’un en-tête et d’une « suite ». Les en-têtes des clauses d’une instruction composée particulière sont toutes placées au même niveau d’indentation. Chaque en-tête de clause commence par un mot-clé spécifique et se termine par le caractère deux-points (:) ; une suite est un groupe d’instructions contrôlées par une clause ; une suite se compose, après les deux points de l’en-tête, soit d’une ou plusieurs instructions simples séparées par des points-virgules si elles sont sur la même ligne que l’en-tête, soit d’une ou plusieurs instructions en retrait sur les lignes suivantes. Seule cette dernière forme d’une suite peut contenir des instructions composées ; ce qui suit n’est pas licite, principalement parce qu’il ne serait pas clair de savoir à quelle clause if se rapporterait une clause else placée en fin de ligne :

if test1: if test2: print(x)

Notez également que le point-virgule se lie plus étroitement que le deux-points dans ce contexte, de sorte que dans l’exemple suivant, soit tous les appels print() sont exécutés, soit aucun ne l’est :

if x < y < z: print(x); print(y); print(z)

En résumé :

compound_stmt ::=  if_stmt
                   | while_stmt
                   | for_stmt
                   | try_stmt
                   | with_stmt
                   | funcdef
                   | classdef
                   | async_with_stmt
                   | async_for_stmt
                   | async_funcdef
suite         ::=  stmt_list NEWLINE | NEWLINE INDENT statement+ DEDENT
statement     ::=  stmt_list NEWLINE | compound_stmt
stmt_list     ::=  simple_stmt (";" simple_stmt)* [";"]

Notez que ces instructions se terminent toujours par un lexème NEWLINE suivi éventuellement d’un DEDENT. Notez également que les clauses facultatives qui suivent commencent toujours par un mot-clé qui ne peut pas commencer une instruction. Ainsi, il n’y a pas d’ambiguïté (le problème du else dont on ne sait pas à quel if il est relié est résolu en Python en exigeant que des instructions if imbriquées soient indentées les unes par rapport aux autres).

L’agencement des règles de grammaire dans les sections qui suivent place chaque clause sur une ligne séparée pour plus de clarté.

8.1. L’instruction if

L’instruction if est utilisée pour exécuter des instructions en fonction d’une condition :

if_stmt ::=  "if" expression ":" suite
             ("elif" expression ":" suite)*
             ["else" ":" suite]

Elle sélectionne exactement une des suites en évaluant les expressions une par une jusqu’à ce qu’une soit vraie (voir la section Opérations booléennes pour la définition de vrai et faux) ; ensuite cette suite est exécutée (et aucune autre partie de l’instruction if n’est exécutée ou évaluée). Si toutes les expressions sont fausses, la suite de la clause else, si elle existe, est exécutée.

8.2. L’instruction while

L’instruction while est utilisée pour exécuter des instructions de manière répétée tant qu’une expression est vraie :

while_stmt ::=  "while" expression ":" suite
                ["else" ":" suite]

Python évalue l’expression de manière répétée et, tant qu’elle est vraie, exécute la première suite ; si l’expression est fausse (ce qui peut arriver même lors du premier test), la suite de la clause else, si elle existe, est exécutée et la boucle se termine.

Une instruction break exécutée dans la première suite termine la boucle sans exécuter la suite de la clause else. Une instruction continue exécutée dans la première suite saute le reste de la suite et retourne au test de l’expression.

8.3. L’instruction for

L’instruction for est utilisée pour itérer sur les éléments d’une séquence (par exemple une chaîne, un tuple ou une liste) ou un autre objet itérable :

for_stmt ::=  "for" target_list "in" expression_list ":" suite
              ["else" ":" suite]

La liste des expressions (expression_list dans la grammaire ci-dessus) est évaluée une seule fois ; elle doit produire un objet itérable. Un itérateur est créé pour le résultat de cette liste d’expression. La suite est ensuite exécutée une fois pour chaque élément fourni par l’itérateur, dans l’ordre renvoyé par l’itérateur. Chaque élément est assigné, à tour de rôle, à la liste cible (target_list dans la grammaire ci-dessus) en utilisant les règles des assignations (voir Les assignations), et ensuite la suite est exécutée. Lorsque les éléments sont épuisés (ce qui est immédiat lorsque la séquence est vide ou si un itérateur lève une exception StopIteration), la suite de la clause else, si elle existe, est exécutée et la boucle se termine.

Une instruction break exécutée dans la première suite termine la boucle sans exécuter la suite de la clause else. Une instruction continue exécutée dans la première suite saute le reste de la suite et continue avec l’élément suivant, ou avec la clause else s’il n’y a pas d’élément suivant.

La boucle for effectue des affectations aux variables de la liste cible, ce qui écrase toutes les affectations antérieures de ces variables, y compris celles effectuées dans la suite de la boucle for :

for i in range(10):
    print(i)
    i = 5             # this will not affect the for-loop
                      # because i will be overwritten with the next
                      # index in the range

Les noms dans la liste cible ne sont pas supprimés lorsque la boucle est terminée mais, si la séquence est vide, ils n’auront pas du tout été assignés par la boucle. Petite astuce : la fonction native range() renvoie un itérateur sur des entiers approprié pour émuler la boucle classique en Pascal sur des entiers for i := a to b do ; par exemple, list(range(3)) renvoie la liste [0, 1, 2].

Note

There is a subtlety when the sequence is being modified by the loop (this can only occur for mutable sequences, e.g. lists). An internal counter is used to keep track of which item is used next, and this is incremented on each iteration. When this counter has reached the length of the sequence the loop terminates. This means that if the suite deletes the current (or a previous) item from the sequence, the next item will be skipped (since it gets the index of the current item which has already been treated). Likewise, if the suite inserts an item in the sequence before the current item, the current item will be treated again the next time through the loop. This can lead to nasty bugs that can be avoided by making a temporary copy using a slice of the whole sequence, e.g.,

for x in a[:]:
    if x < 0: a.remove(x)

8.4. L’instruction try

L’instruction try spécifie les gestionnaires d’exception ou le code de nettoyage pour un groupe d’instructions :

try_stmt  ::=  try1_stmt | try2_stmt
try1_stmt ::=  "try" ":" suite
               ("except" [expression ["as" identifier]] ":" suite)+
               ["else" ":" suite]
               ["finally" ":" suite]
try2_stmt ::=  "try" ":" suite
               "finally" ":" suite

La ou les clauses except spécifient un ou plusieurs gestionnaires d’exceptions. Si aucune exception ne se produit dans la clause try, aucun gestionnaire d’exception n’est exécuté. Lorsqu’une exception se produit dans la suite de try, Python recherche un gestionnaire d’exception. Cette recherche inspecte les clauses except, l’une après l’autre, jusqu’à trouver une correspondance. Une clause except vide (c’est-à-dire sans expression), si elle est présente, doit être la dernière ; elle correspond à toute exception. Pour une clause except avec une expression, cette expression est évaluée et la clause correspond si l’objet résultant est « compatible » avec l’exception. Un objet est réputé compatible avec une exception s’il est la classe ou une classe de base de l’objet exception ou si c’est un tuple contenant un élément qui est compatible avec l’exception.

Si aucune clause except ne correspond à l’exception, la recherche d’un gestionnaire d’exception se poursuit dans le code englobant et dans la pile d’appels. 1

Si l’évaluation d’une expression dans l’en-tête d’une clause except lève une exception, la recherche initiale d’un gestionnaire est annulée et une recherche commence pour la nouvelle exception dans le code englobant et dans la pile d’appels (c’est traité comme si l’instruction try avait levé l’exception).

Lorsqu’une clause d’exception correspond, l’exception est assignée à la cible spécifiée après le mot-clé as dans cette clause except, si cette cible existe, et la suite de clause except est exécutée. Toutes les clauses except doivent avoir un bloc exécutable. Lorsque la fin de ce bloc est atteinte, l’exécution continue normalement après l’ensemble de l’instruction try (cela signifie que si deux gestionnaires imbriqués existent pour la même exception, et que l’exception se produit dans la clause try du gestionnaire interne, le gestionnaire externe ne gère pas l’exception).

Lorsqu’une exception a été assignée en utilisant as cible, elle est effacée à la fin de la clause except. C’est comme si

except E as N:
    foo

avait été traduit en

except E as N:
    try:
        foo
    finally:
        del N

Cela veut dire que l’exception doit être assignée à un nom différent pour pouvoir s’y référer après la clause except. Les exceptions sont effacées parce qu’avec la trace de la pile d’appels qui leur est attachée, elles créent un cycle dans les pointeurs de références (avec le cadre de la pile), ce qui conduit à conserver tous les noms locaux de ce cadre en mémoire jusqu’au passage du ramasse-miettes.

Avant l’exécution de la suite d’une clause except, les détails de l’exception sont stockés dans le module sys et sont accessibles via sys.exc_info(). sys.exc_info() renvoie un triplet composé de la classe de l’exception, de l’instance d’exception et d’un objet trace (voir la section Hiérarchie des types standards) identifiant le point du programme où l’exception est survenue. Les valeurs de sys.exc_info() sont remises à leurs anciennes valeurs (celles d’avant l’appel) au retour d’une fonction qui a géré une exception.

The optional else clause is executed if the control flow leaves the try suite, no exception was raised, and no return, continue, or break statement was executed. Exceptions in the else clause are not handled by the preceding except clauses.

Si finally est présente, elle spécifie un gestionnaire de « nettoyage ». La clause try est exécutée, y compris les clauses except et else. Si une exception se produit dans l’une des clauses et n’est pas traitée, l’exception est temporairement sauvegardée. La clause finally est exécutée. S’il y a une exception sauvegardée, elle est levée à nouveau à la fin de la clause finally. Si la clause finally lève une autre exception, l’exception sauvegardée est définie comme le contexte de la nouvelle exception. Si la clause finally exécute une instruction return ou break, l’exception sauvegardée est jetée :

>>> def f():
...     try:
...         1/0
...     finally:
...         return 42
...
>>> f()
42

L’information relative à l’exception n’est pas disponible pour le programme pendant l’exécution de la clause finally.

Lorsqu’une instruction return, break ou continue est exécutée dans la suite d’une instruction try d’une construction try…finally, la clause finally est aussi exécutée à la sortie. Une instruction continue est illégale dans une clause finally (la raison est que l’implémentation actuelle pose problème — il est possible que cette restriction soit levée dans le futur).

La valeur de retour d’une fonction est déterminée par la dernière instruction return exécutée. Puisque la clause finally s’exécute toujours, une instruction return exécutée dans le finally sera toujours la dernière clause exécutée :

>>> def foo():
...     try:
...         return 'try'
...     finally:
...         return 'finally'
...
>>> foo()
'finally'

Vous trouvez des informations supplémentaires relatives aux exceptions dans la section Exceptions et, dans la section L’instruction raise, des informations relatives à l’utilisation de l’instruction raise pour produire des exceptions.

8.5. L’instruction with

L’instruction with est utilisée pour encapsuler l’exécution d’un bloc avec des méthodes définies par un gestionnaire de contexte (voir la section Gestionnaire de contexte With). Cela permet d’utiliser de manière simple le patron de conception classique try…except…finally.

with_stmt ::=  "with" with_item ("," with_item)* ":" suite
with_item ::=  expression ["as" target]

L’exécution de l’instruction with avec un seul « élément » (item dans la grammaire) se déroule comme suit :

L’expression de contexte (l’expression donnée dans le with_item) est évaluée pour obtenir un gestionnaire de contexte.

La méthode __exit__() du gestionnaire de contexte est chargée pour une utilisation ultérieure.

La méthode __enter__() du gestionnaire de contexte est invoquée.

Si une cible (target dans la grammaire ci-dessus) a été incluse dans l’instruction with, la valeur de retour de __enter__() lui est assignée.

Note

L’instruction with garantit que si la méthode __enter__() se termine sans erreur, alors la méthode __exit__() est toujours appelée. Ainsi, si une erreur se produit pendant l’assignation à la liste cible, elle est traitée de la même façon qu’une erreur se produisant dans la suite. Voir l’étape 6 ci-dessous.

La suite est exécutée.

La méthode __exit__() du gestionnaire de contexte est invoquée. Si une exception a causé la sortie de la suite, son type, sa valeur et sa pile d’appels sont passés en arguments à __exit__(). Sinon, trois arguments None sont fournis.

Si l’on est sorti de la suite en raison d’une exception et que la valeur de retour de la méthode __exit__() était fausse, l’exception est levée à nouveau. Si la valeur de retour était vraie, l’exception est supprimée et l’exécution continue avec l’instruction qui suit l’instruction with.

Si l’on est sorti de la suite pour une raison autre qu’une exception, la valeur de retour de __exit__() est ignorée et l’exécution se poursuit à l’endroit normal pour le type de sortie prise.

Avec plus d’un élément, les gestionnaires de contexte sont traités comme si plusieurs instructions with étaient imbriquées :

with A() as a, B() as b:
    suite

est équivalente à

with A() as a:
    with B() as b:
        suite

Modifié dans la version 3.1: Prise en charge de multiples expressions de contexte.

Voir aussi

PEP 343 [https://www.python.org/dev/peps/pep-0343] — L’instruction « with »

La spécification, les motivations et des exemples de l’instruction with en Python.

8.6. Définition de fonctions

Une définition de fonction définit un objet fonction allogène (voir la section Hiérarchie des types standards) :

funcdef                 ::=  [decorators] "def" funcname "(" [parameter_list] ")"
                             ["->" expression] ":" suite
decorators              ::=  decorator+
decorator               ::=  "@" dotted_name ["(" [argument_list [","]] ")"] NEWLINE
dotted_name             ::=  identifier ("." identifier)*
parameter_list          ::=  defparameter ("," defparameter)* ["," [parameter_list_starargs]]
                             | parameter_list_starargs
parameter_list_starargs ::=  "*" [parameter] ("," defparameter)* ["," ["**" parameter [","]]]
                             | "**" parameter [","]
parameter               ::=  identifier [":" expression]
defparameter            ::=  parameter ["=" expression]
funcname                ::=  identifier

Une définition de fonction est une instruction qui est exécutée. Son exécution lie le nom de la fonction, dans l’espace de nommage local courant, à un objet fonction (un objet qui encapsule le code exécutable de la fonction). Cet objet fonction contient une référence à l’espace des noms globaux courant comme espace des noms globaux à utiliser lorsque la fonction est appelée.

La définition de la fonction n’exécute pas le corps de la fonction ; elle n’est exécutée que lorsque la fonction est appelée. 2

Une définition de fonction peut être encapsulée dans une ou plusieurs expressions decorator ; les décorateurs sont évalués lorsque la fonction est définie, dans la portée qui contient la définition de fonction ; le résultat doit être un appelable, qui est invoqué avec l’objet fonction comme seul argument ; la valeur renvoyée est liée au nom de la fonction en lieu et place de l’objet fonction. Lorsqu’il y a plusieurs décorateurs, ils sont appliqués par imbrication ; par exemple, le code suivant

@f1(arg)
@f2
def func(): pass

est à peu près équivalent à

def func(): pass
func = f1(arg)(f2(func))

sauf que la fonction originale n’est pas temporairement liée au nom func.

Lorsqu’un ou plusieurs paramètres sont de la forme parameter = expression, on dit que la fonction a des « valeurs de paramètres par défaut ». Pour un paramètre avec une valeur par défaut, l’argument correspondant peut être omis lors de l’appel, la valeur par défaut du paramètre est alors utilisée. Si un paramètre a une valeur par défaut, tous les paramètres suivants jusqu’à « * » doivent aussi avoir une valeur par défaut — ceci est une restriction syntaxique qui n’est pas exprimée dans la grammaire.

Les valeurs par défaut des paramètres sont évaluées de la gauche vers la droite quand la définition de la fonction est exécutée. Cela signifie que l’expression est évaluée une fois, lorsque la fonction est définie, et que c’est la même valeur « pré-calculée » qui est utilisée à chaque appel. C’est particulièrement important à comprendre lorsqu’un paramètre par défaut est un objet mutable, tel qu’une liste ou un dictionnaire : si la fonction modifie l’objet (par exemple en ajoutant un élément à une liste), la valeur par défaut est modifiée. En général, ce n’est pas l’effet voulu. Une façon d’éviter cet écueil est d’utiliser None par défaut et de tester explicitement la valeur dans le corps de la fonction. Par exemple :

def whats_on_the_telly(penguin=None):
    if penguin is None:
        penguin = []
    penguin.append("property of the zoo")
    return penguin

La sémantique de l’appel de fonction est décrite plus en détail dans la section Appels. Un appel de fonction assigne toujours des valeurs à tous les paramètres mentionnés dans la liste des paramètres, soit à partir d’arguments positionnels, d’arguments par mots-clés ou de valeurs par défaut. S’il y a un paramètre de la forme « *identifier », il est initialisé à un tuple recevant les paramètres positionnels en surplus, la valeur par défaut étant le tuple vide. S’il y a un paramètre de la forme « **identifier », il est initialisé à un nouveau tableau associatif ordonné qui récupère tous les arguments par mot-clé en surplus, la valeur par défaut étant un tableau associatif vide. Les paramètres après « * » ou « *identifier » sont forcément des paramètres par mot-clé et ne peuvent être passés qu’en utilisant des arguments par mot-clé.

Les paramètres peuvent avoir des annotations sous la forme « : expression » après le nom du paramètre. Tout paramètre peut avoir une annotation, même ceux de la forme *identificateur ou **identificateur. Les fonctions peuvent avoir une annotation pour la valeur de retour, sous la forme « -> expression » après la liste des paramètres. Ces annotations peuvent être toute expression Python valide et sont évaluées lorsque la définition de fonction est exécutée. Les annotations peuvent être évaluées dans un ordre différent de celui où elles apparaissent dans le code source. La présence d’annotations ne modifie la sémantique d’une fonction. Les valeurs des annotations sont accessibles comme valeurs d’un dictionnaire dont les clés sont les noms des paramètres et défini comme attribut __annotations__ de l’objet fonction.

Il est aussi possible de créer des fonctions anonymes (fonctions non liées à un nom), pour une utilisation immédiate dans des expressions. Utilisez alors des expressions lambda, décrites dans la section Expressions lambda. Notez qu’une expression lambda est simplement un raccourci pour définir une fonction simple ; une fonction définie par une instruction « def » peut être passée (en argument) ou assignée à un autre nom, tout comme une fonction définie par une expression lambda. La forme « def » est en fait plus puissante puisqu’elle permet l’exécution de plusieurs instructions et les annotations.

Note pour les programmeurs : les fonctions sont des objets de première classe. Une instruction « def » exécutée à l’intérieur d’une définition de fonction définit une fonction locale qui peut être renvoyée ou passée en tant qu’argument. Les variables libres utilisées dans la fonction imbriquée ont accès aux variables locales de la fonction contenant le « def ». Voir la section Noms et liaisons pour plus de détails.

Voir aussi

PEP 3107 [https://www.python.org/dev/peps/pep-3107] — Annotations de fonctions

La spécification originale pour les annotations de fonctions.

8.7. Définition de classes

Une définition de classe définit un objet classe (voir la section Hiérarchie des types standards) :

classdef    ::=  [decorators] "class" classname [inheritance] ":" suite
inheritance ::=  "(" [argument_list] ")"
classname   ::=  identifier

Une définition de classe est une instruction qui est exécutée. La liste d’héritage (inheritance entre crochets dans la grammaire ci-dessus) donne habituellement une liste de classes de base (voir Méta-classes pour des utilisations plus avancées). Donc chaque élément de la liste doit pouvoir être évalué comme un objet classe qui autorise les sous-classes. Les classes sans liste d’héritage héritent, par défaut, de la classe de base object ; d’où

class Foo:
    pass

est équivalente à

class Foo(object):
    pass

La suite de la classe est ensuite exécutée dans un nouveau cadre d’exécution (voir Noms et liaisons), en utilisant un espace de nommage local nouvellement créé et l’espace de nommage global d’origine (habituellement, la suite contient principalement des définitions de fonctions). Lorsque la suite de la classe termine son exécution, son cadre d’exécution est abandonné mais son espace des noms locaux est sauvegardé 3. Un objet classe est alors créé en utilisant la liste d’héritage pour les classes de base et l’espace de nommage sauvegardé comme dictionnaire des attributs. Le nom de classe est lié à l’objet classe dans l’espace de nommage local original.

L’ordre dans lequel les attributs sont définis dans le corps de la classe est préservé dans le __dict__ de la nouvelle classe. Notez que ceci n’est fiable que juste après la création de la classe et seulement pour les classes qui ont été définies en utilisant la syntaxe de définition.

La création de classes peut être fortement personnalisée en utilisant les métaclasses.

Les classes peuvent aussi être décorées : comme pour les décorateurs de fonctions,

@f1(arg)
@f2
class Foo: pass

est à peu près équivalent à

class Foo: pass
Foo = f1(arg)(f2(Foo))

Les règles d’évaluation pour les expressions de décorateurs sont les mêmes que pour les décorateurs de fonctions. Le résultat est alors lié au nom de la classe.

Note pour les programmeurs : les variables définies dans la définition de classe sont des attributs de classe ; elles sont partagées par les instances. Les attributs d’instance peuvent être définis dans une méthode en utilisant self.name = value. Les attributs de classe et d’instance sont accessibles par la notation « self.name », et un attribut d’instance masque un attribut de classe de même nom lorsqu’on y accède de cette façon. Les attributs de classe peuvent être utilisés comme valeurs par défaut pour les attributs d’instances, mais l’utilisation de valeurs mutables peut conduire à des résultats inattendus. Les descripteurs peuvent être utilisés pour créer des variables d’instances avec des détails d’implémentation différents.

Voir aussi

PEP 3115 [https://www.python.org/dev/peps/pep-3115] - Metaclasses in Python 3000

The proposal that changed the declaration of metaclasses to the current syntax, and the semantics for how classes with metaclasses are constructed.

PEP 3129 [https://www.python.org/dev/peps/pep-3129] - Class Decorators

The proposal that added class decorators. Function and method decorators were introduced in PEP 318 [https://www.python.org/dev/peps/pep-0318].

8.8. Coroutines

Nouveau dans la version 3.5.

8.8.1. Définition de fonctions coroutines

async_funcdef ::=  [decorators] "async" "def" funcname "(" [parameter_list] ")"
                   ["->" expression] ":" suite

L’exécution de coroutines Python peut être suspendue et reprise à plusieurs endroits (voir coroutine). Dans le corps d’une coroutine, tout identificateur await ou async devient un mots-clé réservé ; les expressions await, async for et async with ne peuvent être utilisées que dans les corps de coroutines.

Les fonctions définies avec la syntaxe async def sont toujours des fonctions coroutines, même si elles ne contiennent aucun mot-clé await ou async.

C’est une SyntaxError d’utiliser une expression yield from dans une coroutine async def.

Un exemple de fonction coroutine :

async def func(param1, param2):
    do_stuff()
    await some_coroutine()

8.8.2. L’instruction async for

async_for_stmt ::=  "async" for_stmt

Un itérable asynchrone est capable d’appeler du code asynchrone dans l’implémentation de sa méthode iter ; un itérateur asynchrone peut appeler du code asynchrone dans sa méthode next.

L’instruction async for permet d’itérer facilement sur des itérateurs asynchrones.

Le code suivant :

async for TARGET in ITER:
    BLOCK
else:
    BLOCK2

est sémantiquement équivalent à :

iter = (ITER)
iter = type(iter).__aiter__(iter)
running = True
while running:
    try:
        TARGET = await type(iter).__anext__(iter)
    except StopAsyncIteration:
        running = False
    else:
        BLOCK
else:
    BLOCK2

Voir aussi __aiter__() et __anext__() pour plus de détails.

C’est une SyntaxError d’utiliser une instruction async for en dehors d’une fonction async def.

8.8.3. L’instruction async with

async_with_stmt ::=  "async" with_stmt

Un gestionnaire de contexte asynchrone est un gestionnaire de contexte qui est capable de suspendre l’exécution dans ses méthodes enter et exit.

Le code suivant :

async with EXPR as VAR:
    BLOCK

est sémantiquement équivalent à :

mgr = (EXPR)
aexit = type(mgr).__aexit__
aenter = type(mgr).__aenter__(mgr)

VAR = await aenter
try:
    BLOCK
except:
    if not await aexit(mgr, *sys.exc_info()):
        raise
else:
    await aexit(mgr, None, None, None)

Voir aussi __aenter__() et __aexit__() pour plus de détails.

C’est une SyntaxError d’utiliser l’instruction async with en dehors d’une fonction async def.

Voir aussi

PEP 492 [https://www.python.org/dev/peps/pep-0492] — Coroutines avec les syntaxes async et await

The proposal that made coroutines a proper standalone concept in Python, and added supporting syntax.

Notes

1

L’exception est propagée à la pile d’appels à moins qu’il n’y ait une clause finally qui lève une autre exception, ce qui entraîne la perte de l’ancienne exception. Cette nouvelle exception entraîne la perte pure et simple de l’ancienne.

2

Une chaîne littérale apparaissant comme première instruction dans le corps de la fonction est transformée en attribut __doc__ de la fonction et donc en docstring de la fonction.

3

Une chaîne littérale apparaissant comme première instruction dans le corps de la classe est transformée en élément __doc__ de l’espace de nommage et donc en docstring de la classe.

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9. Composants de plus haut niveau

L’entrée de l’interpréteur Python peut provenir d’un certain nombre de sources : d’un script passé en entrée standard ou en argument de programme, tapée de manière interactive, à partir d’un fichier source de module, etc. Ce chapitre donne la syntaxe utilisée dans ces différents cas.

9.1. Programmes Python complets

Bien que les spécifications d’un langage n’ont pas à préciser comment l’interpréteur du langage est invoqué, il est utile d’avoir des notions sur ce qu’est un programme Python complet. Un programme Python complet est exécuté dans un environnement dont l’initialisation est minimale : tous les modules intégrés et standard sont disponibles mais aucun n’a été initialisé, à l’exception de sys (divers services système), builtins (fonctions natives, exceptions et None) et __main__. Ce dernier est utilisé pour avoir des espaces de nommage locaux et globaux pour l’exécution du programme complet.

La syntaxe d’un programme Python complet est celle d’un fichier d’entrée, dont la description est donnée dans la section suivante.

L’interpréteur peut également être invoqué en mode interactif ; dans ce cas, il ne lit et n’exécute pas un programme complet mais lit et exécute une seule instruction (éventuellement composée) à la fois. L’environnement initial est identique à celui d’un programme complet ; chaque instruction est exécutée dans l’espace de nommage de __main__.

A complete program can be passed to the interpreter in three forms: with the -c string command line option, as a file passed as the first command line argument, or as standard input. If the file or standard input is a tty device, the interpreter enters interactive mode; otherwise, it executes the file as a complete program.

9.2. Fichier d’entrée

Toutes les entrées lues à partir de fichiers non interactifs sont de la même forme :

file_input ::=  (NEWLINE | statement)*

Cette syntaxe est utilisée dans les situations suivantes :

lors de l’analyse d’un programme Python complet (à partir d’un fichier ou d’une chaîne de caractères) ;

lors de l’analyse d’un module ;

lors de l’analyse d’une chaîne de caractères passée à la fonction exec().

9.3. Entrée interactive

L’entrée en mode interactif est analysée à l’aide de la grammaire suivante :

interactive_input ::=  [stmt_list] NEWLINE | compound_stmt NEWLINE

Notez qu’une instruction composée (de niveau supérieur) doit être suivie d’une ligne blanche en mode interactif ; c’est nécessaire pour aider l’analyseur à détecter la fin de l’entrée.

9.4. Entrée d’expression

eval() est utilisée pour évaluer les expressions entrées. Elle ignore les espaces en tête. L’argument de eval(), de type chaîne de caractères, doit être de la forme suivante :

eval_input ::=  expression_list NEWLINE*

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10. Spécification complète de la grammaire

Ceci est la grammaire de Python, exhaustive, telle qu’elle est lue par le générateur d’analyseur, et utilisée pour analyser des fichiers sources en Python :

# Grammar for Python

# NOTE WELL: You should also follow all the steps listed at
# https://devguide.python.org/grammar/

# Start symbols for the grammar:
#       single_input is a single interactive statement;
#       file_input is a module or sequence of commands read from an input file;
#       eval_input is the input for the eval() functions.
# NB: compound_stmt in single_input is followed by extra NEWLINE!
single_input: NEWLINE | simple_stmt | compound_stmt NEWLINE
file_input: (NEWLINE | stmt)* ENDMARKER
eval_input: testlist NEWLINE* ENDMARKER

decorator: '@' dotted_name [ '(' [arglist] ')' ] NEWLINE
decorators: decorator+
decorated: decorators (classdef | funcdef | async_funcdef)

async_funcdef: ASYNC funcdef
funcdef: 'def' NAME parameters ['->' test] ':' suite

parameters: '(' [typedargslist] ')'
typedargslist: (tfpdef ['=' test] (',' tfpdef ['=' test])* [',' [
        '*' [tfpdef] (',' tfpdef ['=' test])* [',' ['**' tfpdef [',']]]
      | '**' tfpdef [',']]]
  | '*' [tfpdef] (',' tfpdef ['=' test])* [',' ['**' tfpdef [',']]]
  | '**' tfpdef [','])
tfpdef: NAME [':' test]
varargslist: (vfpdef ['=' test] (',' vfpdef ['=' test])* [',' [
        '*' [vfpdef] (',' vfpdef ['=' test])* [',' ['**' vfpdef [',']]]
      | '**' vfpdef [',']]]
  | '*' [vfpdef] (',' vfpdef ['=' test])* [',' ['**' vfpdef [',']]]
  | '**' vfpdef [',']
)
vfpdef: NAME

stmt: simple_stmt | compound_stmt
simple_stmt: small_stmt (';' small_stmt)* [';'] NEWLINE
small_stmt: (expr_stmt | del_stmt | pass_stmt | flow_stmt |
             import_stmt | global_stmt | nonlocal_stmt | assert_stmt)
expr_stmt: testlist_star_expr (annassign | augassign (yield_expr|testlist) |
                     ('=' (yield_expr|testlist_star_expr))*)
annassign: ':' test ['=' test]
testlist_star_expr: (test|star_expr) (',' (test|star_expr))* [',']
augassign: ('+=' | '-=' | '*=' | '@=' | '/=' | '%=' | '&=' | '|=' | '^=' |
            '<<=' | '>>=' | '**=' | '//=')
# For normal and annotated assignments, additional restrictions enforced by the interpreter
del_stmt: 'del' exprlist
pass_stmt: 'pass'
flow_stmt: break_stmt | continue_stmt | return_stmt | raise_stmt | yield_stmt
break_stmt: 'break'
continue_stmt: 'continue'
return_stmt: 'return' [testlist]
yield_stmt: yield_expr
raise_stmt: 'raise' [test ['from' test]]
import_stmt: import_name | import_from
import_name: 'import' dotted_as_names
# note below: the ('.' | '...') is necessary because '...' is tokenized as ELLIPSIS
import_from: ('from' (('.' | '...')* dotted_name | ('.' | '...')+)
              'import' ('*' | '(' import_as_names ')' | import_as_names))
import_as_name: NAME ['as' NAME]
dotted_as_name: dotted_name ['as' NAME]
import_as_names: import_as_name (',' import_as_name)* [',']
dotted_as_names: dotted_as_name (',' dotted_as_name)*
dotted_name: NAME ('.' NAME)*
global_stmt: 'global' NAME (',' NAME)*
nonlocal_stmt: 'nonlocal' NAME (',' NAME)*
assert_stmt: 'assert' test [',' test]

compound_stmt: if_stmt | while_stmt | for_stmt | try_stmt | with_stmt | funcdef | classdef | decorated | async_stmt
async_stmt: ASYNC (funcdef | with_stmt | for_stmt)
if_stmt: 'if' test ':' suite ('elif' test ':' suite)* ['else' ':' suite]
while_stmt: 'while' test ':' suite ['else' ':' suite]
for_stmt: 'for' exprlist 'in' testlist ':' suite ['else' ':' suite]
try_stmt: ('try' ':' suite
           ((except_clause ':' suite)+
            ['else' ':' suite]
            ['finally' ':' suite] |
           'finally' ':' suite))
with_stmt: 'with' with_item (',' with_item)*  ':' suite
with_item: test ['as' expr]
# NB compile.c makes sure that the default except clause is last
except_clause: 'except' [test ['as' NAME]]
suite: simple_stmt | NEWLINE INDENT stmt+ DEDENT

test: or_test ['if' or_test 'else' test] | lambdef
test_nocond: or_test | lambdef_nocond
lambdef: 'lambda' [varargslist] ':' test
lambdef_nocond: 'lambda' [varargslist] ':' test_nocond
or_test: and_test ('or' and_test)*
and_test: not_test ('and' not_test)*
not_test: 'not' not_test | comparison
comparison: expr (comp_op expr)*
# <> isn't actually a valid comparison operator in Python. It's here for the
# sake of a __future__ import described in PEP 401 (which really works :-)
comp_op: '<'|'>'|'=='|'>='|'<='|'<>'|'!='|'in'|'not' 'in'|'is'|'is' 'not'
star_expr: '*' expr
expr: xor_expr ('|' xor_expr)*
xor_expr: and_expr ('^' and_expr)*
and_expr: shift_expr ('&' shift_expr)*
shift_expr: arith_expr (('<<'|'>>') arith_expr)*
arith_expr: term (('+'|'-') term)*
term: factor (('*'|'@'|'/'|'%'|'//') factor)*
factor: ('+'|'-'|'~') factor | power
power: atom_expr ['**' factor]
atom_expr: [AWAIT] atom trailer*
atom: ('(' [yield_expr|testlist_comp] ')' |
       '[' [testlist_comp] ']' |
       '{' [dictorsetmaker] '}' |
       NAME | NUMBER | STRING+ | '...' | 'None' | 'True' | 'False')
testlist_comp: (test|star_expr) ( comp_for | (',' (test|star_expr))* [','] )
trailer: '(' [arglist] ')' | '[' subscriptlist ']' | '.' NAME
subscriptlist: subscript (',' subscript)* [',']
subscript: test | [test] ':' [test] [sliceop]
sliceop: ':' [test]
exprlist: (expr|star_expr) (',' (expr|star_expr))* [',']
testlist: test (',' test)* [',']
dictorsetmaker: ( ((test ':' test | '**' expr)
                   (comp_for | (',' (test ':' test | '**' expr))* [','])) |
                  ((test | star_expr)
                   (comp_for | (',' (test | star_expr))* [','])) )

classdef: 'class' NAME ['(' [arglist] ')'] ':' suite

arglist: argument (',' argument)*  [',']

# The reason that keywords are test nodes instead of NAME is that using NAME
# results in an ambiguity. ast.c makes sure it's a NAME.
# "test '=' test" is really "keyword '=' test", but we have no such token.
# These need to be in a single rule to avoid grammar that is ambiguous
# to our LL(1) parser. Even though 'test' includes '*expr' in star_expr,
# we explicitly match '*' here, too, to give it proper precedence.
# Illegal combinations and orderings are blocked in ast.c:
# multiple (test comp_for) arguments are blocked; keyword unpackings
# that precede iterable unpackings are blocked; etc.
argument: ( test [comp_for] |
            test '=' test |
            '**' test |
            '*' test )

comp_iter: comp_for | comp_if
comp_for: [ASYNC] 'for' exprlist 'in' or_test [comp_iter]
comp_if: 'if' test_nocond [comp_iter]

# not used in grammar, but may appear in "node" passed from Parser to Compiler
encoding_decl: NAME

yield_expr: 'yield' [yield_arg]
yield_arg: 'from' test | testlist

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La bibliothèque standard

Alors que La référence du langage Python décrit exactement la syntaxe et la sémantique du langage Python, ce manuel de référence de la Bibliothèque décrit la bibliothèque standard distribuée avec Python. Il décrit aussi certains composants optionnels typiquement inclus dans les distributions de Python.

La bibliothèque standard de Python est très grande, elle offre un large éventail d’outils comme le montre la longueur de la table des matières ci-dessous. La bibliothèque contient des modules natifs (écrits en C) exposant les fonctionnalités du système telles que les interactions avec les fichiers qui autrement ne seraient pas accessibles aux développeurs Python, ainsi que des modules écrits en Python exposant des solutions standardisées à de nombreux problèmes du quotidien du développeur. Certains de ces modules sont définis explicitement pour encourager et améliorer la portabilité des programmes Python en abstrayant des spécificités sous-jacentes en API neutres.

Les installateurs de Python pour Windows incluent généralement la bibliothèque standard en entier, et y ajoutent souvent d’autres composants. Pour les systèmes d’exploitation Unix, Python est typiquement fourni sous forme d’une collection de paquets, il peut donc être nécessaire d’utiliser le gestionnaire de paquets fourni par le système d’exploitation pour obtenir certains composants optionnels.

Au delà de la bibliothèque standard, il existe une collection grandissante de plusieurs milliers de composants (des programmes, des modules, ou des frameworks), disponibles dans le Python Package Index [https://pypi.org].

1. Introduction

2. Fonctions natives

3. Constantes natives

3.1. Constantes ajoutées par le module site

4. Types natifs

4.1. Valeurs booléennes

4.2. Opérations booléennes — and, or, not

4.3. Comparaisons

4.4. Types numériques — int, float, complex

4.5. Les types itérateurs

4.6. Types séquentiels — list, tuple, range

4.7. Type Séquence de Texte — str

4.8. Séquences Binaires — bytes, bytearray, memoryview

4.9. Types d’ensembles — set, frozenset

4.10. Les types de correspondances — dict

4.11. Le type gestionnaire de contexte

4.12. Autres types natifs

4.13. Attributs spéciaux

5. Exceptions natives

5.1. Classes de base

5.2. Exceptions concrètes

5.3. Avertissements

5.4. Hiérarchie des exceptions

6. Services de Manipulation de Texte

6.1. string — Opérations usuelles sur des chaînes

6.2. re — Opérations à base d’expressions rationnelles

6.3. difflib — Helpers for computing deltas

6.4. textwrap — Encapsulation et remplissage de texte

6.5. unicodedata — Base de données Unicode

6.6. stringprep — Préparation des chaines de caractères internet

6.7. readline — interface pour GNU readline

6.8. rlcompleter — Fonction de complétion pour GNU readline

7. Services autour des Données Binaires

7.1. struct — manipulation de données agrégées sous forme binaire comme une séquence d’octets

7.2. codecs — Registre des codecs et classes de base associées

8. Types de données

8.1. datetime — Types de base pour la date et l’heure

8.2. calendar — General calendar-related functions

8.3. collections — Types de données de conteneurs

8.4. collections.abc — Classes de base abstraites pour les conteneurs

8.5. heapq — File de priorité basée sur un tas

8.6. bisect — Algorithme de bissection de listes

8.7. array — Tableaux efficaces de valeurs numériques

8.8. weakref — Weak references

8.9. types — Dynamic type creation and names for built-in types

8.10. copy — Opérations de copie superficielle et récursive

8.11. pprint — L’affichage élégant de données

8.12. reprlib — Alternate repr() implementation

8.13. enum — Énumerations

9. Modules numériques et mathématiques

9.1. numbers — Classes de base abstraites numériques

9.2. Fonctions mathématiques — math

9.3. Fonctions mathématiques pour nombres complexes — cmath

9.4. decimal — Arithmétique décimale en virgule fixe et flottante

9.5. fractions — Nombres rationnels

9.6. random — Génère des nombres pseudo-aléatoires

9.7. statistics — Mathematical statistics functions

10. Modules de programmation fonctionnelle

10.1. itertools — Fonctions créant des itérateurs pour boucler efficacement

10.2. functools — Fonctions de haut niveau et opérations sur des objets appelables

10.3. operator — Opérateurs standards en tant que fonctions

11. Accès aux Fichiers et aux Dossiers

11.1. pathlib — Chemins de système de fichiers orientés objet

11.2. os.path — manipulation courante des chemins

11.3. fileinput — Iterate over lines from multiple input streams

11.4. stat — Interpreting stat() results

11.5. filecmp – Comparaisons de fichiers et de répertoires

11.6. tempfile — Génération de fichiers et répertoires temporaires

11.7. glob — Recherche de chemins de style Unix selon certains motifs

11.8. fnmatch — Filtrage par motif des noms de fichiers Unix

11.9. linecache — Accès direct aux lignes d’un texte

11.10. shutil — Opérations de haut niveau sur les fichiers

11.11. macpath — Fonctions de manipulation de chemins pour Mac OS 9

12. Persistance des données

12.1. pickle — Module de sérialisation d’objets Python

12.2. copyreg — Enregistre les fonctions support de pickle

12.3. shelve — Objet Python persistant

12.4. marshal — Internal Python object serialization

12.5. dbm — Interfaces to Unix « databases »

12.6. sqlite3 — Interface DB-API 2.0 pour bases de données SQLite

13. Compression de donnée et archivage

13.1. zlib — Compression compatible avec gzip

13.2. gzip — Support pour les fichiers gzip

13.3. bz2 — Prise en charge de la compression bzip2

13.4. lzma — Compression via l’algorithme LZMA

13.5. zipfile — Travailler avec des archives ZIP

13.6. tarfile — Read and write tar archive files

14. Formats de fichiers

14.1. csv — Lecture et écriture de fichiers CSV

14.2. configparser — Configuration file parser

14.3. netrc — traitement de fichier netrc

14.4. xdrlib — Encode and decode XDR data

14.5. plistlib — Generate and parse Mac OS X .plist files

15. Service de cryptographie

15.1. hashlib — Algorithmes de hachage sécurisés et synthèse de messages

15.2. hmac — Authentification de messages par hachage en combinaison avec une clé secrète

15.3. secrets — Générer des nombres aléatoires de façon sécurisée pour la gestion des secrets

16. Services génériques du système d’exploitation

16.1. os — Diverses interfaces pour le système d’exploitation

16.2. io — Core tools for working with streams

16.3. time — Accès au temps et conversions

16.4. argparse – Parseur d’arguments, d’options, et de sous-commandes de ligne de commande

16.5. getopt – Analyseur de style C pour les options de ligne de commande

16.6. logging — Fonctionnalités de journalisation pour Python

16.7. logging.config — Logging configuration

16.8. logging.handlers — Logging handlers

16.9. Saisie de mot de passe portable

16.10. curses — Terminal handling for character-cell displays

16.11. curses.textpad — Text input widget for curses programs

16.12. curses.ascii — Utilities for ASCII characters

16.13. curses.panel — A panel stack extension for curses

16.14. platform — Access to underlying platform’s identifying data

16.15. errno — Symboles du système errno standard

16.16. ctypes — Bibliothèque Python d’appels à des fonctions externes

17. Exécution concourante

17.1. threading — Parallélisme basé sur les fils d’exécution (threads)

17.2. multiprocessing — Parallélisme par processus

17.3. Le paquet concurrent

17.4. concurrent.futures — Launching parallel tasks

17.5. subprocess — Gestion de sous-processus

17.6. sched — Event scheduler

17.7. queue — File synchronisée

17.8. dummy_threading — Module de substitution au module threading

17.9. _thread — API bas niveau de gestion de fils d’exécution

17.10. _dummy_thread — Module de substitution pour le module _thread

18. Communication et réseau entre processus

18.1. socket — Low-level networking interface

18.2. ssl — Emballage TLS/SSL pour les objets connecteurs

18.3. select — Waiting for I/O completion

18.4. selectors — High-level I/O multiplexing

18.5. asyncio — Entrées/Sorties asynchrone, boucle d’évènements, coroutines et tâches

18.6. asyncore — Gestionnaire de socket asynchrone

18.7. asynchat — Gestionnaire d’interfaces de connexion (socket) commande/réponse asynchrones

18.8. signal — Set handlers for asynchronous events

18.9. mmap — Memory-mapped file support

19. Traitement des données provenant d’Internet

19.1. email — Un paquet de gestion des e-mails et MIME

19.2. json — Encodage et décodage JSON

19.3. mailcap — Manipulation de fichiers Mailcap

19.4. mailbox — Manipuler les boîtes de courriels dans différents formats

19.5. mimetypes — Map filenames to MIME types

19.6. base64 — Encodages base16, base32, base64 et base85

19.7. binhex — Encode et décode les fichiers binhex4

19.8. binascii — Conversion entre binaire et ASCII

19.9. quopri — Encode et décode des données MIME quoted-printable

19.10. uu — Encode et décode les fichiers uuencode

20. Outils de traitement de balises structurées

20.1. html — Support du HyperText Markup Language

20.2. html.parser — Simple HTML and XHTML parser

20.3. html.entities — Définitions des entités HTML générales

20.4. Modules de traitement XML

20.5. xml.etree.ElementTree — The ElementTree XML API

20.6. xml.dom — L’API Document Object Model

20.7. xml.dom.minidom — Minimal DOM implementation

20.8. xml.dom.pulldom — Support for building partial DOM trees

20.9. xml.sax — Prise en charge des analyseurs SAX2

20.10. xml.sax.handler — Base classes for SAX handlers

20.11. xml.sax.saxutils — Utilitaires SAX

20.12. xml.sax.xmlreader — Interface for XML parsers

20.13. xml.parsers.expat — Fast XML parsing using Expat

21. Gestion des protocoles internet

21.1. webbrowser — Convenient Web-browser controller

21.2. cgi — Common Gateway Interface support

21.3. cgitb — Gestionnaire d’exceptions pour les scripts CGI

21.4. wsgiref — Outils et implémentation de référence de WSGI

21.5. urllib — Modules de gestion des URLs

21.6. urllib.request — Extensible library for opening URLs

21.7. urllib.response — Response classes used by urllib

21.8. urllib.parse — Parse URLs into components

21.9. urllib.error — Classes d’exceptions levées par urllib.request

21.10. urllib.robotparser — Analyseur de fichiers robots.txt

21.11. http — modules HTTP

21.12. http.client — HTTP protocol client

21.13. ftplib — FTP protocol client

21.14. poplib — POP3 protocol client

21.15. imaplib — IMAP4 protocol client

21.16. nntplib — NNTP protocol client

21.17. smtplib — SMTP protocol client

21.18. smtpd — SMTP Server

21.19. telnetlib — Telnet client

21.20. uuid — UUID objects according to RFC 4122

21.21. socketserver — A framework for network servers

21.22. http.server — HTTP servers

21.23. http.cookies — gestion d’état pour HTTP

21.24. http.cookiejar — Cookie handling for HTTP clients

21.25. xmlrpc — Modules Serveur et Client XMLRPC

21.26. xmlrpc.client — XML-RPC client access

21.27. xmlrpc.server — Basic XML-RPC servers

21.28. ipaddress — IPv4/IPv6 manipulation library

22. Services multimédia

22.1. audioloop — Manipulation de données audio brutes

22.2. aifc — Lis et écrit dans les fichiers AIFF et AIFC

22.3. sunau — Read and write Sun AU files

22.4. wave — Lecture et écriture des fichiers WAV

22.5. chunk — Read IFF chunked data

22.6. colorsys — Conversions entre les systèmes de couleurs

22.7. imghdr — Determine the type of an image

22.8. sndhdr — Détermine le type d’un fichier audio

22.9. ossaudiodev — Access to OSS-compatible audio devices

23. Internationalisation

23.1. gettext — Services d’internationalisation multilingue

23.2. locale — Services d’internationalisation

24. Frameworks d’applications

24.1. turtle — Tortue graphique

24.2. cmd — Interpréteurs en ligne de commande.

24.3. shlex — Simple lexical analysis

25. Interfaces Utilisateur Graphiques avec Tk

25.1. tkinter — Interface Python pour Tcl/Tk

25.2. tkinter.ttk — Tk themed widgets

25.3. tkinter.tix — Extension widgets for Tk

25.4. tkinter.scrolledtext — Gadget texte avec barre de défilement

25.5. IDLE

25.6. Autres paquets d’interface graphique utilisateur

26. Outils de développement

26.1. typing — Support for type hints

26.2. pydoc — Générateur de documentation et système d’aide en ligne

26.3. doctest — Test interactive Python examples

26.4. unittest — Framework de tests unitaires

26.5. unittest.mock — Bibliothèque d’objets simulacres

26.6. unittest.mock — getting started

26.7. 2to3 — Traduction automatique de code en Python 2 vers Python 3

26.8. test — Regression tests package for Python

26.9. test.support — Utilities for the Python test suite

27. Débogueur et instrumentation

27.1. bdb — Framework de débogage

27.2. faulthandler — Dump the Python traceback

27.3. pdb — Le débogueur Python

27.4. The Python Profilers

27.5. timeit — Mesurer le temps d’exécution de fragments de code

27.6. trace — Trace or track Python statement execution

27.7. tracemalloc — Trace memory allocations

28. Paquets et distribution de paquets logiciels

28.1. distutils — Création et installation des modules Python

28.2. ensurepip — Bootstrapping the pip installer

28.3. venv — Création d’environnements virtuels

28.4. zipapp — Manage executable python zip archives

29. Environnement d’exécution Python

29.1. sys — Paramètres et fonctions propres à des systèmes

29.2. sysconfig — Provide access to Python’s configuration information

29.3. builtins — Objets natifs

29.4. __main__ — Point d’entrée des scripts

29.5. warnings — Contrôle des alertes

29.6. contextlib — Utilities for with-statement contexts

29.7. abc — Classes de Base Abstraites

29.8. atexit — Gestionnaire de fin de programme

29.9. traceback — Print or retrieve a stack traceback

29.10. __future__ — Définitions des futurs

29.11. gc — Garbage Collector interface

29.12. inspect — Inspect live objects

29.13. site — Site-specific configuration hook

29.14. fpectl — Floating point exception control

30. Interpréteurs Python personnalisés

30.1. code — Interpreter base classes

30.2. codeop — Compilation de code Python

31. Importer des modules

31.1. zipimport — Importer des modules à partir d’archives Zip

31.2. pkgutil — Package extension utility

31.3. modulefinder — Identifie les modules utilisés par un script

31.4. runpy — Locating and executing Python modules

31.5. importlib — The implementation of import

32. Services du Langage Python

32.1. parser — Accès aux arbres syntaxiques

32.2. ast — Arbres Syntaxiques Abstraits

32.3. symtable — Access to the compiler’s symbol tables

32.4. symbol — Constantes utilisées dans les Arbres Syntaxiques

32.5. token — Constantes utilisées avec les arbres d’analyse Python (parse trees)

32.6. keyword — Tester si des chaînes sont des mot-clés Python

32.7. tokenize — Analyseur lexical de Python

32.8. tabnanny — Détection d’indentation ambiguë

32.9. pyclbr — Python class browser support

32.10. py_compile — Compile Python source files

32.11. compileall — Byte-compile Python libraries

32.12. dis – Désassembleur pour le code intermédiaire de Python

32.13. pickletools — Tools for pickle developers

33. Services divers

33.1. formatter — Generic output formatting

34. Services spécifiques à MS Windows

34.1. msilib — Read and write Microsoft Installer files

34.2. msvcrt — Useful routines from the MS VC++ runtime

34.3. winreg — Windows registry access

34.4. winsound — Sound-playing interface for Windows

35. Services spécifiques à Unix

35.1. posix — Les appels système POSIX les plus courants

35.2. pwd — The password database

35.3. spwd — La base de données de mots de passe shadow

35.4. grp — The group database

35.5. crypt — Function to check Unix passwords

35.6. termios — Le style POSIX le contrôle TTY

35.7. tty — Fonctions de gestion du terminal

35.8. pty — Outils de manipulation de pseudo-terminaux

35.9. fcntl — The fcntl and ioctl system calls

35.10. pipes — Interface au pipelines shell

35.11. resource — Resource usage information

35.12. nis — Interface à Sun’s NIS (pages jaunes)

35.13. syslog — Unix syslog library routines

36. Modules remplacés

36.1. optparse — Parser for command line options

36.2. imp — Access the import internals

37. Modules non Documentés

37.1. Modules spécifiques à une plateforme

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1. Introduction

La « Bibliothèque Python » contient divers composants dans différentes catégories.

Elle contient des types de données qui seraient normalement considérés comme « fondamentaux » au langage, tel que les nombres et les listes. Pour ces types, le cœur du langage en définit les écritures littérales et impose quelques contraintes sémantiques, sans les définir exhaustivement. (Cependant le cœur du langage impose quelques propriétés comme l’orthographe des attributs ou les caractéristiques des opérateurs.)

La bibliothèque contient aussi des fonctions et des exceptions natives, pouvant être utilisées par tout code Python sans import. Certaines sont définies par le noyau de Python, bien qu’elles ne soient pas toutes essentielles.

La grande majorité de la bibliothèque consiste cependant en une collection de modules. Cette collection peut être parcourue de différentes manières. Certains modules sont rédigés en C et inclus dans l’interpréteur Python, d’autres sont écrits en Python et leur source est importée. Certains modules fournissent des interfaces extrêmement spécifiques à Python, tel que l’affichage d’une pile d’appels, d’autres fournissent des interfaces spécifiques à un système d’exploitation, comme l’accès à du matériel spécifique. D’autres fournissent des interfaces spécifiques à un domaine d’application, comme le World Wide Web. Certains modules sont disponibles dans toutes les versions et implémentations de Python, d’autres ne sont disponibles que si le système sous-jacent les gère ou en a besoin. Enfin, d’autres ne sont disponibles que si Python à été compilé avec une certaine option.

Cette documentation organise les modules « de l’intérieur vers l’extérieur », documentant en premier les fonctions natives, les types de données et exceptions, puis les modules, groupés par chapitre, par thématiques.

Ça signifie que si vous commencez à lire cette documentation du début, et sautez au chapitre suivant lorsqu’elle vous ennuie, vous aurez un aperçu global des modules et domaines couverts par cette bibliothèque. Bien sûr vous n’avez pas à la lire comme un roman, vous pouvez simplement survoler la table des matières (au début), ou chercher une fonction, un module, ou un mot dans l’index (à la fin). Et si vous appréciez apprendre sur des sujets au hasard, choisissez une page au hasard (avec le module random) et lisez un chapitre ou deux. Peu importe l’ordre que vous adopterez, commencez par le chapitre Fonctions natives, car les autres chapitres présument que vous en avez une bonne connaissance.

Que le spectacle commence !

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2. Fonctions natives

L’interpréteur Python propose quelques fonctions et types natifs qui sont toujours disponibles. Ils sont listés ici par ordre alphabétique.

Fonctions natives

abs()

dict()

help()

min()

setattr()

all()

dir()

hex()

next()

slice()

any()

divmod()

id()

object()

sorted()

ascii()

enumerate()

input()

oct()

staticmethod()

bin()

eval()

int()

open()

str()

bool()

exec()

isinstance()

ord()

sum()

bytearray()

filter()

issubclass()

pow()

super()

bytes()

float()

iter()

print()

tuple()

callable()

format()

len()

property()

type()

chr()

frozenset()

list()

range()

vars()

classmethod()

getattr()

locals()

repr()

zip()

compile()

globals()

map()

reversed()

__import__()

complex()

hasattr()

max()

round()

delattr()

hash()

memoryview()

set()

abs(x)

Donne la valeur absolue d’un nombre. L’argument peut être un nombre entier ou un nombre à virgule flottante. Si l’argument est un nombre complexe, son module [https://fr.wikipedia.org/wiki/Module_d%27un_nombre_complexe] est donné.

all(iterable)

Donne True si tous les éléments de iterable sont vrais (ou s’il est vide), équivaut à :

def all(iterable):
    for element in iterable:
        if not element:
            return False
    return True

any(iterable)

Donne True si au moins un élément de iterable est vrai. Faux est aussi donné dans le cas où iterable est vide, équivaut à :

def any(iterable):
    for element in iterable:
        if element:
            return True
    return False

ascii(object)

Donne, tout comme repr(), une chaîne contenant une représentation affichable d’un objet, en transformant les caractères non ASCII donnés par repr() en utilisant des séquences d’échappement \x, \u ou \U. Cela génère une chaîne similaire à ce que renvoie repr() dans Python 2.

bin(x)

Convertit un nombre entier en binaire dans une chaîne avec le préfixe 0b. Le résultat est une expression Python valide. Si x n’est pas un int, il doit définir une méthode __index__() donnant un nombre entier, voici quelques exemples :

>>> bin(3)
'0b11'
>>> bin(-10)
'-0b1010'

Que le préfixe 0b soit souhaité ou non, vous pouvez utiliser les moyens suivants.

>>> format(14, '#b'), format(14, 'b')
('0b1110', '1110')
>>> f'{14:#b}', f'{14:b}'
('0b1110', '1110')

Voir aussi format() pour plus d’information.

class bool([x])

Donne une valeur booléenne, c’est à dire soit True, soit False. x est converti en utilisant la procédure standard d’évaluation de valeur de vérité. Si x est faux, ou omis, elle donne False, sinon, elle donne True. La classe bool hérite de la classe int (voir Types numériques — int, float, complex). Il n’est pas possible d’en hériter. Ses seules instances sont False et True (voir Valeurs booléennes).

class bytearray([source[, encoding[, errors]]])

Donne un nouveau tableau d’octets. La classe bytearray est une séquence muable de nombre entiers dans l’intervalle 0 <= x < 256. Il possède la plupart des méthodes des séquences variables, décrites dans Types de séquences muables, ainsi que la plupart des méthodes de la classe bytes, voir Opérations sur les bytes et bytearray.

Le paramètre optionnel source peut être utilisé pour initialiser l”array de quelques manières différentes :

Si c’est une chaîne, vous devez aussi donner les paramètre encoding pour l’encodage (et éventuellement errors). La fonction bytearray() convertit ensuite la chaîne en bytes via la méthode str.encode().

Si c’est un entier, l”array aura cette taille et sera initialisé de null bytes.

Si c’est un objet conforme à l’interface buffer, un buffer en lecture seule de l’objet sera utilisé pour initialiser l”array.

Si c’est un itérable, il doit itérer sur des nombres entier dans l’intervalle 0 <= x < 256, qui seront utilisés pour initialiser le contenu de l”array.

Sans argument, un array de taille vide est crée.

Voir Séquences Binaires — bytes, bytearray, memoryview et Objets bytearray.

class bytes([source[, encoding[, errors]]])

Donne un nouvel objet bytes, qui est une séquence immuable de nombre entiers dans l’intervalle 0 <= x <= 256. Les bytes est une version immuable de bytearray – avec les mêmes méthodes d’accès, et le même comportement lors de l’indexation ou la découpe.

En conséquence, les arguments du constructeur sont les mêmes que pour bytearray().

Les objets bytes peuvent aussi être créés à partir de littéraux, voir Littéraux de chaînes de caractères et de suites d’octets.

Voir aussi Séquences Binaires — bytes, bytearray, memoryview, Objets bytes, et Opérations sur les bytes et bytearray.

callable(object)

Donne True si l’argument object semble être appelable, sinon False. Lorsqu’elle donne vrai, il reste une éventualité pour qu’un appel échoue, cependant, lorsqu’elle donne faux, il ne sera jamais possible d’appeler object. Notez que les classes sont appelables (appeler une classe donne une nouvelle instance). Les instances sont appelables si leur classe définit une méthode __call__().

Nouveau dans la version 3.2: Cette fonction à d’abord été supprimée avec Python 3.0 puis elle à été remise dans Python 3.2.

chr(i)

Renvoie la chaîne représentant un caractère dont le code de caractère Unicode est le nombre entier i. Par exemple, chr(97) renvoie la chaîne de caractères 'a', tandis que chr(8364) renvoie '€'. Il s’agit de l’inverse de ord().

L’intervalle valide pour cet argument est de 0 à 1114111 (0x10FFFF en base 16). Une exception ValueError sera levée si i est en dehors de l’intervalle.

@classmethod

Transforme une méthode en méthode de classe.

Une méthode de classe reçoit implicitement la classe en premier argument, tout comme une méthode d’instance reçoit l’instance. Voici comment déclarer une méthode de classe :

class C:
    @classmethod
    def f(cls, arg1, arg2, ...): ...

La forme @classmethod est un decorator – consultez la documentation sur la définition de fonctions dans Définition de fonctions pour plus de détails.

Elle peut être appelée soit sur la classe (comme C.f()) ou sur une instance (comme C().f()). L’instance est ignorée, sauf pour déterminer sa classe. Si la méthode est appelée sur une instance de classe fille, c’est la classe fille qui sera donnée en premier argument implicite.

Les méthodes de classe sont différentes des méthodes statiques du C++ ou du Java. Si c’est elles sont vous avez besoin, regardez du côté de staticmethod().

Pour plus d’informations sur les méthodes de classe, consultez la documentation sur la hiérarchie des types standards dans Hiérarchie des types standards.

compile(source, filename, mode, flags=0, dont_inherit=False, optimize=-1)

Compile source en un objet code ou objet AST. Les objets code peuvent être exécutés par exec() ou eval(). source peut soit être une chaîne, un objet bytes, ou un objet AST. Consultez la documentation du module ast pour des informations sur la manipulation d’objets AST.

L’argument filename doit nommer le fichier duquel le code à été lu. Donnez quelque chose de reconnaissable lorsqu’il n’a pas été lu depuis un fichier (typiquement "<string>").

L’argument mode indique quel type de code doit être compilé : 'exec' si source est une suite d’instructions, 'eval' pour une seule expression, ou 'single' si il ne contient qu’une instruction interactive (dans ce dernier cas, les résultats d’expressions donnant autre chose que None seront affichés).

The optional arguments flags and dont_inherit control which future statements affect the compilation of source. If neither is present (or both are zero) the code is compiled with those future statements that are in effect in the code that is calling compile(). If the flags argument is given and dont_inherit is not (or is zero) then the future statements specified by the flags argument are used in addition to those that would be used anyway. If dont_inherit is a non-zero integer then the flags argument is it – the future statements in effect around the call to compile are ignored.

Les instructions futures sont spécifiées par des bits, il est ainsi possible d’en spécifier plusieurs en les combinant avec un ou binaire. Les bits requis pour spécifier une certaine fonctionnalité se trouvent dans l’attribut compiler_flag de la classe Feature du module __future__.

L’argument optimize indique le niveau d’optimisation du compilateur. La valeur par défaut est -1 qui prend le niveau d’optimisation de l’interpréteur tel que reçu via l’option -O. Les niveau explicites sont : 0 (pas d’optimisation, __debug__ est True), 1 (les assert sont supprimés, __debug__ est False) ou 2 (les docstrings sont également supprimés).

Cette fonction lève une SyntaxError si la source n’est pas valide, et ValueError si la source contient des octets null.

Si vous voulez transformer du code Python en sa représentation AST, voyez ast.parse().

Note

Lors de la compilation d’une chaîne de plusieurs lignes de code avec les modes 'single' ou 'eval', celle-ci doit être terminée d’au moins un retour à la ligne. Cela permet de faciliter la distinction entre les instructions complètes et incomplètes dans le module code.

Avertissement

Il est possible de faire planter l’interpréteur Python avec des chaînes suffisamment grandes ou complexes lors de la compilation d’un objet AST à cause de la limitation de la profondeur de la pile d’appels.

Modifié dans la version 3.2: Autorise l’utilisation de retours à la ligne Mac et Windows. Aussi, la chaîne donnée à 'exec' n’a plus besoin de terminer par un retour à la ligne. Ajout du paramètre optimize.

Modifié dans la version 3.5: Précédemment, l’exception TypeError était levée quand un caractère nul était rencontré dans source.

class complex([real[, imag]])

Donne un nombre complexe de valeur real + imag\*1j, ou convertit une chaîne ou un nombre en nombre complexe. Si le premier paramètre est une chaîne, il sera interprété comme un nombre complexe et la fonction doit être appelée dans second paramètre. Le second paramètre ne peut jamais être une chaîne. Chaque argument peut être de n’importe quel type numérique (même complexe). Si imag est omis, sa valeur par défaut est zéro, le constructeur effectue alors une simple conversion numérique comme le font int ou float. Si aucun argument n’est fourni, donne 0j.

Note

Lors de la conversion depuis une chaîne, elle ne doit pas contenir d’espaces autour des opérateurs binaires + ou -. Par exemple complex('1+2j') est bon, mais complex('1 + 2j') lève une ValueError.

Le type complexe est décrit dans Types numériques — int, float, complex.

Modifié dans la version 3.6: Les chiffres peuvent être groupés avec des tirets bas comme dans les expressions littérales.

delattr(object, name)

C’est un cousin de setattr(). Les arguments sont un objet et une chaîne. La chaîne doit être le nom de l’un des attributs de l’objet. La fonction supprime l’attribut nommé, si l’objet l’y autorise. Par exemple delattr(x, 'foobar') est l’équivalent de del x.foobar.

class dict(**kwarg)

class dict(mapping, **kwarg)

class dict(iterable, **kwarg)

Créé un nouveau dictionnaire. L’objet dict est la classe du dictionnaire. Voir dict et Les types de correspondances — dict pour vous documenter sur cette classe.

Pour les autres conteneurs, voir les classes natives list, set, et typle. ainsi que le module collections.

dir([object])

Sans arguments, elle donne la liste des noms dans l’espace de nommage local. Avec un argument, elle essaye de donner une liste d’attributs valides pour cet objet.

Si l’objet à une méthode __dir__(), elle est appelée et doit donner une liste d’attributs. Cela permet aux objets implémentant __getattr__() ou __getattribute__() de personnaliser ce que donnera dir().

Si l’objet ne fournit pas de méthode __dir__(), la fonction fait de son mieux en rassemblant les informations de l’attribut __dict__ de l’objet, si défini, et depuis son type. La liste résultante n’est pas nécessairement complète, et peut être inadaptée quand l’objet a un __getattr__() personnalisé.

Le mécanisme par défaut de dir() se comporte différemment avec différents types d’objets, car elle préfère donner une information pertinente plutôt qu’exhaustive :

Si l’objet est un module, la liste contiendra les noms des attributs du module.

Si l’objet est un type ou une classe, la liste contiendra les noms de ses attributs, et récursivement, des attributs de ses parents.

Autrement, la liste contient les noms des attributs de l’objet, le nom des attributs de la classe, et récursivement des attributs des parents de la classe.

La liste donnée est triée par ordre alphabétique, par exemple :

>>> import struct
>>> dir()   # show the names in the module namespace
['__builtins__', '__name__', 'struct']
>>> dir(struct)   # show the names in the struct module
['Struct', '__all__', '__builtins__', '__cached__', '__doc__', '__file__',
 '__initializing__', '__loader__', '__name__', '__package__',
 '_clearcache', 'calcsize', 'error', 'pack', 'pack_into',
 'unpack', 'unpack_from']
>>> class Shape:
...     def __dir__(self):
...         return ['area', 'perimeter', 'location']
>>> s = Shape()
>>> dir(s)
['area', 'location', 'perimeter']

Note

Étant donné que dir() est d’abord fournie pour son côté pratique en mode interactif, elle a tendance à fournir un jeu intéressant de noms plutôt qu’un ensemble consistant et rigoureusement défini, son comportement peut aussi changer d’une version à l’autre. Par exemple, les attributs de méta-classes ne sont pas données lorsque l’argument est une classe.

divmod(a, b)

Prend deux nombres (non complexes) et donne leur quotient et reste de leur division entière sous forme d’une paire de nombres. Avec des opérandes de types différents, les règles des opérateurs binaires s’appliquent. Pour deux entiers le résultat est le même que (a // b, a % b). Pour des nombres à virgule flottante le résultat est (q, a % b), où q est généralement math.floor(a / b) mais peut valoir un de moins. Dans tous les cas q * b + a % b est très proche de a. Si a % b est différent de zéro, il a le même signe que b, et 0 <= abs(a % b) < abs(b).

enumerate(iterable, start=0)

Donne un objet énumérant. iterable doit être une séquence, un iterator, ou tout autre objet supportant l’itération. La méthode __next__() de l’itérateur donné par enumerate() donne un tuple contenant un compte (démarrant à start, 0 par défaut) et les valeurs obtenues de l’itération sur iterable.

>>> seasons = ['Spring', 'Summer', 'Fall', 'Winter']
>>> list(enumerate(seasons))
[(0, 'Spring'), (1, 'Summer'), (2, 'Fall'), (3, 'Winter')]
>>> list(enumerate(seasons, start=1))
[(1, 'Spring'), (2, 'Summer'), (3, 'Fall'), (4, 'Winter')]

Équivalent à :

def enumerate(sequence, start=0):
    n = start
    for elem in sequence:
        yield n, elem
        n += 1

eval(expression, globals=None, locals=None)

Les arguments sont : une chaîne, et optionnellement des locales et des globales. S’il est fourni, globals doit être un dictionnaire. S’il est fourni, locals peut être n’importe quel objet mapping.

The expression argument is parsed and evaluated as a Python expression (technically speaking, a condition list) using the globals and locals dictionaries as global and local namespace. If the globals dictionary is present and does not contain a value for the key __builtins__, a reference to the dictionary of the built-in module builtins is inserted under that key before expression is parsed. This means that expression normally has full access to the standard builtins module and restricted environments are propagated. If the locals dictionary is omitted it defaults to the globals dictionary. If both dictionaries are omitted, the expression is executed in the environment where eval() is called. The return value is the result of the evaluated expression. Syntax errors are reported as exceptions. Example:

>>> x = 1
>>> eval('x+1')
2

Cette fonction peut aussi être utilisée pour exécuter n’importe quel objet code (tel que ceux créés par compile()). Dans ce cas, donnez un objet code plutôt qu’une chaîne. Si l’objet code à été compilé avec 'exec' en argument pour mode, eval() donnera None.

Conseils : L’exécution dynamique d’instructions est gérée par la fonction exec(). Les fonctions globals() et locals() donnent respectivement les dictionnaires globaux et locaux, qui peuvent être utiles lors de l’usage de eval() et exec().

Utilisez ast.literal_eval() si vous avez besoin d’une fonction qui peut évaluer en toute sécurité des chaînes avec des expressions ne contenant que des valeurs littérales.

exec(object[, globals[, locals]])

Cette fonction permet l’exécution dynamique de code Python. object doit être soit une chaîne soit un objet code. Si c’est une chaîne, elle est d’abord analysée en une suite d’instructions Python qui sont ensuite exécutés (sauf erreur de syntaxe). 1 Si c’est un objet code, il est simplement exécuté. dans tous les cas, le code fourni doit être valide selon les mêmes critères que s’il était un script dans un fichier (voir la section « File Input » dans le manuel). Gardez en tête que les mots clefs return et yield ne peuvent pas être utilisés en dehors d’une fonction, même dans du code passé à exec(). La fonction donne None.

Dans tous les cas, si les arguments optionnels sont omis, le code est exécuté dans le contexte actuel. Si seul globals est fourni, il doit être un dictionnaire qui sera utilisé pour les globales et les locales. Si les deux sont fournis, ils sont utilisés respectivement pour les variables globales et locales. locales peut être n’importe quel objet mapping. Souvenez vous qu’au niveau d’un module, les dictionnaires des locales et des globales ne sont qu’un. Si exec reçoit deux objets distincts dans globals et locals, le code sera exécuté comme s’il était inclus dans une définition de classe.

Si le dictionnaire globals ne contient pas de valeur pour la clef __builtins__, une référence au dictionnaire du module builtins y est inséré. Cela vous permet de contrôler quelles fonctions natives sont exposées au code exécuté en insérant votre propre dictionnaire __builtins__ dans globals avant de le donner à exec().

Note

Les fonctions natives globals() et locals() donnent respectivement les dictionnaires globaux et locaux, qui peuvent être utiles en deuxième et troisième argument de exec().

Note

La valeur par défaut pour locals se comporte comme la fonction locals(): Il est déconseillé de modifier le dictionnaire locals par défaut. Donnez un dictionnaire explicitement à locals si vous désirez observer l’effet du code sur les variables locales, après que exec() soit terminée.

filter(function, iterable)

Construit un itérateur depuis les éléments d”iterable pour lesquels function donne vrai. iterable peut aussi bien être une séquence, un conteneur qui supporte l’itération, ou un itérateur. Si function est None, la fonction identité est prise, c’est à dire que tous les éléments faux d”iterable sont supprimés.

Notez que filter(fonction, iterable) est l’équivalent du générateur (item for item in iterable if fonction(item)) si fonction n’est pas None et de (item for item in iterable if item) si function est None.

Voir itertools.filterfalse() pour la fonction complémentaire qui donne les éléments d”iterable pour lesquels fonction donne False.

class float([x])

Donne un nombre a virgule flottante depuis un nombre ou une chaîne x.

Si l’argument est une chaîne, elle devrait contenir un nombre décimal, éventuellement précédé d’un signe, et pouvant être entouré d’espaces. Le signe optionnel peut être '+' ou '-'. Un signe '+' n’a pas d’effet sur la valeur produite. L’argument peut aussi être une chaîne représentant un NaN (Not-a-Number), l’infini positif, ou l’infini négatif. Plus précisément, l’argument doit se conformer à la grammaire suivante, après que les espaces en début et fin de chaîne aient été retirés :

sign           ::=  "+" | "-"
infinity       ::=  "Infinity" | "inf"
nan            ::=  "nan"
numeric_value  ::=  floatnumber | infinity | nan
numeric_string ::=  [sign] numeric_value

Ici floatnumber est un nombre a virgule flottante littéral Python, décrit dans Nombres à virgule flottante littéraux. La casse n’y est pas significative, donc, par exemple, "inf", " Inf", "INFINITY", et " iNfiNity" sont tous des orthographes valides pour un infini positif.

Autrement, si l’argument est un entier ou un nombre à virgule flottante, un nombre à virgule flottante de même valeur (en accord avec la précision des nombres à virgule flottante de Python) est donné. Si l’argument est en dehors de l’intervalle d’un nombre a virgule flottante pour Python, OverflowError est levée.

Pour un objet Python x, float(x) est délégué à x.__float__().

Dans argument, 0.0 est donné.

Exemples :

>>> float('+1.23')
1.23
>>> float('   -12345\n')
-12345.0
>>> float('1e-003')
0.001
>>> float('+1E6')
1000000.0
>>> float('-Infinity')
-inf

Le type float est décrit dans Types numériques — int, float, complex.

Modifié dans la version 3.6: Les chiffres peuvent être groupés avec des tirets bas comme dans les expressions littérales.

format(value[, format_spec])

Convertit une valeur en sa représentation « formatée », tel que décrit par format_spec. L’interprétation de format_spec dépend du type de la valeur, cependant il existe une syntaxe standard utilisée par la plupart des types natifs : Mini-langage de spécification de format.

Par défaut, format_spec est une chaîne vide qui généralement donne le même effet qu’appeler str(value).

Un appel à format(value, format_spec) est transformé en type(value).__format__(value, format_spec), qui contourne le dictionnaire de l’instance lors de la recherche de la méthode __fornat__(). Une exception TypeError est levée si la recherche de la méthode atteint object et que format_spec n’est pas vide, ou si soit format_spec soit la le résultat ne sont pas des chaînes.

Modifié dans la version 3.4: object().__format__(format_spec) lève TypeError si format_spec n’est pas une chaîne vide.

class frozenset([iterable])

Donne un nouveau frozenset, dont les objets sont éventuellement tirés d”iterable. frozenset est une classe native. Voir frozenset et Types d’ensembles — set, frozenset pour leurs documentation.

Pour d’autres conteneurs, voyez les classes natives set, list, tuple, et dict, ainsi que le module collections.

getattr(object, name[, default])

Donne la valeur de l’attribut nommé name de l’objet object. name doit être une chaîne. Si la chaîne est le nom d’un des attributs de l’objet, le résultat est la valeur de cet attribut. Par exemple, getattr(x, 'foobar') est équivalent à x.foobar. Si l’attribut n’existe pas, et que default est fourni, il est renvoyé, sinon l’exception AttributeError est levée.

globals()

Donne une représentation de la table de symboles globaux sous forme d’un dictionnaire. C’est toujours le dictionnaire du module courant (dans une fonction ou méthode, c’est le module où elle est définie, et non le module d’où elle est appelée).

hasattr(object, name)

Les arguments sont : un objet et une chaîne. Le résultat est True si la chaîne est le nom d’un des attributs de l’objet, sinon False. (L’implémentation appelle getattr(object, name) et regarde si une exception AttributeError à été levée.)

hash(object)

Donne la valeur de hash d’un objet (s’il en a une). Les valeurs de hash sont des entiers. Elles sont utilisées pour comparer rapidement des clefs de dictionnaire lors de leur recherche. Les valeurs numériques égales ont le même hash (même si leurs types sont différents, comme pour 1 et 1.0).

Note

Pour les objets dont la méthode __hash__() est implémentée, notez que hash() tronque la valeur donnée en fonction du nombre de bits de la machine hôte. Voir __hash__() pour plus d’informations.

help([object])

Invoque le système d’aide natif. (Cette fonction est destinée à l’usage en mode interactif.) Soi aucun argument n’est fourni, le système d’aide démarre dans l’interpréteur. Si l’argument est une chaîne, un module, une fonction, une classe, une méthode, un mot clef, ou un sujet de documentation pourtant ce nom est recherché, et une page d’aide est affichée sur la console. Si l’argument est d’un autre type, une page d’aide sur cet objet est générée.

Cette fonction est ajoutée à l’espace de nommage natif par le module site.

Modifié dans la version 3.4: Les changements aux modules pydoc et inspect rendent les signatures des appelables plus compréhensible et cohérente.

hex(x)

Convertit un entier en chaîne hexadécimale préfixée de 0x. Si x n’est pas un int, il doit définir une méthode __index__() qui renvoie un entier. Quelques exemples :

>>> hex(255)
'0xff'
>>> hex(-42)
'-0x2a'

Si vous voulez convertir un nombre entier en chaîne hexadécimale, en majuscule ou non, préfixée ou non, vous pouvez utiliser les moyens suivants :

>>> '%#x' % 255, '%x' % 255, '%X' % 255
('0xff', 'ff', 'FF')
>>> format(255, '#x'), format(255, 'x'), format(255, 'X')
('0xff', 'ff', 'FF')
>>> f'{255:#x}', f'{255:x}', f'{255:X}'
('0xff', 'ff', 'FF')

Voir aussi format() pour plus d’information.

Voir aussi int() pour convertir une chaîne hexadécimale en un entier en lui spécifiant 16 comme base.

Note

Pour obtenir une représentation hexadécimale sous forme de chaîne d’un nombre à virgule flottante, utilisez la méthode float.hex().

id(object)

Donne l“« identité » d’un objet. C’est un nombre entier garanti unique et constant pour cet objet durant sa durée de vie. Deux objets sont les durées de vie ne se chevauchent pas peuvent partager le même id().

CPython implementation detail: This is the address of the object in memory.

input([prompt])

Si l’argument prompt est donné, il est écrit sur la sortie standard sans le retour à la ligne final. La fonction lis ensuite une ligne sur l’entrée standard et la convertit en chaîne (supprimant le retour à la ligne final) quelle donne. Lorsque EOF est lu, EOFError est levée. Exemple :

>>> s = input('--> ')
--> Monty Python's Flying Circus
>>> s
"Monty Python's Flying Circus"

Si le module readline est chargé, input() l’utilisera pour fournir des fonctionnalités d’édition et d’historique élaborées.

class int(x=0)

class int(x, base=10)

Donne un entier construit depuis un nombre ou une chaîne x, ou 0 si aucun argument n’est fourni. Si x définit une méthode __int__(), int(x) renvoie x.__int__(). Si x définit __trunc__(), int(x) renvoie x.__trunc__(). Les nombres à virgule flottante sont tronqués vers zéro.

Si x n’est pas un nombre ou si base est fourni, alors x doit être une chaîne, un bytes, ou un bytearray représentant un entier littéral de base base. Le littéral peut être précédé d’un + ou d’un - (sans être séparés par un espace), et peut être entouré d’espaces. Un littéral de base n est composé des symboles de 0 à n-1 où a jusqu’à z (ou A à Z) représentent les valeurs de 10 à 35. La base par défaut est 10. Les valeurs autorisées pour base sont 0 et 2–36. Les littéraux en base 2, 8, et 16 peuvent être préfixés avec 0b/0B, 0o/0O, ou 0x/0X tout comme les littéraux dans le code. Fournir 0 comme base demande d’interpréter exactement comme un littéral dans Python, donc la base sera 2, 8, 10, ou 16, ainsi int('010', 0) n’est pas légal, alors que int('010') l’est tout comme int('010', 8).

Le type des entiers est décrit dans Types numériques — int, float, complex.

Modifié dans la version 3.4: Si base n’est pas une instance d”int et que base a une méthode base.__index__, cette méthode est appelée pour obtenir un entier pour cette base. Les versions précédentes utilisaient base.__int__ au lieu de base.__index__.

Modifié dans la version 3.6: Les chiffres peuvent être groupés avec des tirets bas comme dans les expressions littérales.

isinstance(object, classinfo)

Donne True si object est une instance de classinfo, ou d’une de ses classes filles, directe, indirecte, ou virtuelle. Si object n’est pas un objet du type donné, la fonction donne toujours False. Si classinfo est un tuple de types (ou récursivement, d’autres tuples), donne True si object est une instance de n’importe quel de ces types. Si classinfo n’est ni un type ni un tuple de types (et récursivement), une exception TypeError est levée.

issubclass(class, classinfo)

Donne True si class est une classe fille (directe, indirecte, ou virtual) de classinfo. Une classe est considérée sous-classe d’elle même. classinfo peut être un tuple de classes, dans ce cas la vérification sera faite pour chaque classe de classinfo. Dans tous les autres cas, TypeError est levée.

iter(object[, sentinel])

Donne un objet iterator. Le premier argument est interprété très différemment en fonction de la présence du second argument. Sans second argument, object doit être une collection d’objets supportant le protocole d’itération (la méthode __iter__()), ou supportant le protocole des séquences (la méthode getitem(), avec des nombres entiers commençant par 0 comme argument). S’il ne supporte aucun de ces protocoles, TypeError est levée. Si le second argument sentinel est fourni, objet doit être appelable. L’itérateur créé dans ce cas appellera object dans argument à chaque appel de __next__(), si la valeur reçue est égale à sentinel StopIteration est levée, autrement la valeur est donnée.

Voir aussi Les types itérateurs.

Une autre application utile de la deuxième forme de iter() est de lire les lignes d’un fichier jusqu’à ce qu’un certaine ligne soit atteinte. L’exemple suivant lis un fichier jusqu’à ce que readline() donne une ligne vide :

with open('mydata.txt') as fp:
    for line in iter(fp.readline, ''):
        process_line(line)

len(s)

Donne la longueur (nombre d’éléments) d’un objet. L’argument peut être une séquence (tel qu’une chaîne, un objet bytes, tuple, list ou range) ou une collection (tel qu’un dict, set ou frozenset).

class list([iterable])

Plutôt qu’être une fonction, list est en fait un type de séquence variable, tel que documenté dans Listes et Types séquentiels — list, tuple, range.

locals()

Met à jour et donne un dictionnaire représentant la table des symboles locaux. Les variables libres sont données par locals() lorsqu’elle est appelée dans le corps d’une fonction, mais pas dans le corps d’une classe.

Note

Le contenu de ce dictionnaire ne devrait pas être modifié, les changements peuvent ne pas affecter les valeurs des variables locales ou libres utilisées par l’interpréteur.

map(function, iterable, ...)

Donne un itérateur appliquant function à chaque élément de iterable, et donnant ses résultats au fur et à mesure avec yield. Si d’autres iterable sont fournis, function doit prendre autant d’arguments, et sera appelée avec les éléments de tous les itérables en parallèle. Avec plusieurs itérables, l’itération s’arrête avec l’itérable le plus court. Pour les cas où les arguments seraient déjà rangés sous forme de tuples, voir itertools.starmap().

max(iterable, *[, key, default])

max(arg1, arg2, *args[, key])

Donne l’élément le plus grand dans un itérable, ou l’argument le plus grand parmi au moins deux arguments.

Si un seul argument positionnel est fourni, il doit être iterable. Le plus grand élément de l’itérable est donné. Si au moins deux arguments positionnels sont fournis, l’argument le plus grand sera donné.

Elle accepte deux arguments par mot clef optionnels. L’argument key spécifie une fonction à un argument permettant de trier comme pour list.sort(). L’argument default quant à lui fournit un objet à donner si l’itérable fourni est vide. Si l’itérable est vide et que default n’est pas fourni, ValueError est levée.

Si plusieurs éléments représentent la plus grande valeur, le premier rencontré est donné. C’est cohérent avec d’autres outils préservant une stabilité lors du tri, tel que sorted(iterable, key=keyfunc, reverse=True)[0] et heapq.nlargest(1, iterable, key=keyfunc).

Nouveau dans la version 3.4: L’argument exclusivement par mot clef default.

memoryview(obj)

Donne une « vue mémoire » (memory view) créée depuis l’argument. Voir Vues de mémoires pour plus d’informations.

min(iterable, *[, key, default])

min(arg1, arg2, *args[, key])

Donne le plus petit élément d’un itérable ou le plus petit d’au moins deux arguments.

Si un seul argument est fourni, il doit être iterable. Le plus petit élément de l’itérable est donné. Si au moins deux arguments positionnels sont fournis le plus petit argument positionnel est donné.

Elle accepte deux arguments par mot clef optionnels. L’argument key spécifie une fonction à un argument permettant de trier comme pour list.sort(). L’argument default quant à lui fournit un objet à donner si l’itérable fourni est vide. Si l’itérable est vide et que default n’est pas fourni, ValueError est levée.

Si plusieurs éléments sont minimaux, la fonction donne le premier. C’est cohérent avec d’autres outils préservant une stabilité lors du tri, tel que sorted(iterable, key=keyfunc)[0] et heapq.nsmallest(1, iterable, key=keyfunc).

Nouveau dans la version 3.4: L’argument exclusivement par mot clef default.

next(iterator[, default])

Donne l’élément suivant d”iterator en appelant sa méthode __next__(). Si default est fourni, il sera donné si l’itérateur est épuisé, sinon StopIteration est levée.

class object

Donne un objet vide. object est la classe parente de toute les classes. C’est elle qui porte les méthodes communes à toutes les instances de classes en Python. Cette fonction n’accepte aucun argument.

Note

object n’a pas d’attribut __dict__, vous ne pouvez donc pas assigner d’attributs arbitraire à une instance d”object.

oct(x)

Convertit un entier en sa représentation octale dans une chaîne préfixée de 0o. Le résultat est une expression Python valide. Si x n’est pas un objet int, il doit définir une méthode __index__() qui donne un entier, par exemple :

>>> oct(8)
'0o10'
>>> oct(-56)
'-0o70'

Si vous voulez convertir un nombre entier en chaîne octale, avec ou sans le préfixe 0o, vous pouvez utiliser les moyens suivants.

>>> '%#o' % 10, '%o' % 10
('0o12', '12')
>>> format(10, '#o'), format(10, 'o')
('0o12', '12')
>>> f'{10:#o}', f'{10:o}'
('0o12', '12')

Voir aussi format() pour plus d’information.

open(file, mode='r', buffering=-1, encoding=None, errors=None, newline=None, closefd=True, opener=None)

Ouvre file et donne un file object correspondant. Si le fichier ne peut pas être ouvert, une OSError est levée.

file est un path-like object donnant le chemin (absolu ou relatif au répertoire courant) du fichier à ouvrir ou un nombre entier représentant le descripteur de fichier à envelopper. (Si un descripteur de fichier est donné, il sera fermé en même temps que l’objet I/O renvoyé, sauf si closefd est mis à False.)

mode est une chaîne optionnelle permettant de spécifier dans quel mode le fichier est ouvert. Par défaut, mode vaut 'r' qui signifie « ouvrir en lecture pour du texte ». 'w' est aussi une valeur classique, permettant d’écrire (vidant le fichier s’il existe), ainsi que 'x' permettant une création exclusive et 'a' pour ajouter à la fin du fichier (qui sur certains systèmes Unix signifie que toutes les écritures seront des ajouts en fin de fichier peu importe la position demandée). En mode texte, si encoding n’est pas spécifié l’encodage utilisé est dépendant de la plateforme : locale.getpreferredencoding(False) est appelée pour obtenir l’encodage de la locale actuelle. (Pour lire et écrire des octets bruts, utilisez le mode binaire en laissant encoding non spécifié.) Les modes disponibles sont :

Caractère

Signification

'r'

ouvre en lecture (par défaut)

'w'

ouvre en écriture, tronquant le fichier

'x'

ouvre pour une création exclusive, échouant si le fichier existe déjà

'a'

ouvre en écriture, ajoutant à la fin du fichier s’il existe

'b'

mode binaire

't'

mode texte (par défaut)

'+'

ouvre un fichier pour le modifier (lire et écrire)

'U'

mode universal newlines (obsolète)

Les mode par défaut est 'r' (ouvrir pour lire du texte, synonyme de 'rt'). Pour un accès en lecture écriture binaire, le mode 'w+b' ouvre et vide le fichier. 'r+b' ouvre le fichier sans le vider.

Tel que mentionné dans Aperçu, Python fait la différence entre les I/O binaire et texte. Les fichiers ouverts en mode binaire (avec 'b' dans mode) donnent leur contenu sous forme de bytes sans décodage. En mode texte (par défaut, ou lorsque 't' est dans le mode), le contenu du fichier est donné sous forme de str, les octets ayant été décodés au préalable en utilisant un encodage déduit de l’environnement ou encoding s’il est donné.

Note

Python ne dépend pas de l’éventuelle notion de fichier texte du système sous-jacent, tout le traitement est effectué par Python lui même, et est ainsi indépendant de la plateforme.

buffering est un entier optionnel permettant de configurer l’espace tampon. Donnez 0 pour désactiver l’espace tampon (seulement autorisé en mode binaire), 1 pour avoir un buffer travaillant ligne par ligne (seulement disponible en mode texte), ou un entier supérieur à 1 pour donner la taille en octets d’un tampon de taille fixe. Sans l’argument buffering, les comportements par défaut sont les suivants :

Les fichiers binaires sont les dans un tampon de taille fixe, dont la taille est choisie par une heuristique essayant de déterminer la taille des blocs du système sous-jacent, ou en utilisant par défaut io.DEFAULT_BUFFER_SIZE. Sur de nombreux systèmes, le tampon sera de 4096 ou 8192 octets.

Les fichiers texte « interactifs » (fichiers pour lesquels io.IOBase.isatty() donne True) utilisent un tampon par lignes. Les autres fichiers texte sont traités comme les fichiers binaires.

encoding est le nom de l’encodage utilisé pour encoder ou décoder le fichier. Il doit seulement être utilisé en mode texte. L’encodage par défaut dépend de la plateforme (ce que locale.getpreferredencoding() donne), mais n’importe quel text encoding supporté par Python peut être utilisé. Voir codecs pour une liste des encodages supportés.

errors est une chaîne facultative spécifiant comment les erreurs d’encodage et de décodages sont gérées, ce n’est pas utilisable en mode binaire. Pléthore gestionnaires d’erreurs standards sont disponibles (listés sous Gestionnaires d’erreurs), aussi, tout nom de gestionnaire d’erreur enregistré avec codecs.register_error() est aussi un argument valide. Les noms standards sont :

'strict' pour lever une ValueError si une erreur d’encodage est rencontrée. La valeur par défaut, None, a le même effet.

'ignore' ignore les erreurs. Notez qu’ignorer les erreurs d’encodage peut mener à des pertes de données.

'replace' insère un marqueur de substitution (tel que '?') en place des données mal formées.

'surrogateescape' représentera chaque octet incorrect par un code caractère de la zone Private Use Area d’Unicode, de U+DC80 à U+DCFF. Ces codes caractères privés seront ensuite transformés dans les mêmes octets erronés si le gestionnaire d’erreur surrogateescape est utilisé lors de l’écriture de la donnée. C’est utile pour traiter des fichiers d’un encodage inconnu.

'xmlcharrefreplace' est seulement supporté à l’écriture vers un fichier. Les caractères non gérés par l’encodage sont remplacés par une référence de caractère XML &#nnn;.

'backslashreplace' remplace les données mal formées par des séquences d’échappement Python (utilisant des backslash).

'namereplace' (aussi supporté lors de l’écriture) remplace les caractères non supportés par des séquences d’échappement \N{...}.

newline contrôle comment le mode universal newlines fonctionne (seulement en mode texte). Il eut être None, '', '\n', '\r', et '\r\n'. Il fonctionne comme suit :

Lors de la lecture, si newline est None, le mode universal newlines est activé. Les lignes lues peuvent terminer par '\n', '\r', ou '\r\n', qui sont remplacés par '\n', avant d’être données à l’appelant. S’il vaut '*', le mode universal newline est activé mais les fin de lignes ne sont pas remplacés. S’il a n’importe quel autre valeur autorisée, les lignes sont seulement terminées par la chaîne donnée, qui est rendue tel qu’elle.

Lors de l’écriture, si newline est None, chaque '\n' est remplacé par le séparateur de lignes par défaut du système os.linesep. Si newline est * ou '\n' aucun remplacent n’est effectué. Si newline est un autre caractère valide, chaque '\n' sera remplacé par la chaîne donnée.

Si closefd est False et qu’un descripteur de fichier est fourni plutôt qu’un nom de fichier, le descripteur de fichier sera laissé ouvert lorsque le fichier sera fermé. Si un nom de fichier est donné, closefd doit rester True (la valeur par défaut) sans quoi une erreur est levée.

Un opener personnalisé peut être utilisé en fournissant un appelable comme opener. Le descripteur de fichier de cet objet fichier sera alors obtenu en appelant opener avec (file, flags). opener doit donner un descripteur de fichier ouvert (fournir os.open en temps qu”opener aura le même effet que donner None).

Il n’est pas possible d’hériter du fichier nouvellement créé.

L’exemple suivant utilise le paramètre dir_fd de la fonction os.open() pour ouvrir un fichier relatif au dossier courant :

>>> import os
>>> dir_fd = os.open('somedir', os.O_RDONLY)
>>> def opener(path, flags):
...     return os.open(path, flags, dir_fd=dir_fd)
...
>>> with open('spamspam.txt', 'w', opener=opener) as f:
...     print('This will be written to somedir/spamspam.txt', file=f)
...
>>> os.close(dir_fd)  # don't leak a file descriptor

Le type de file object donné par la fonction open() dépend du mode. Lorsque open() est utilisé pour ouvrir un fichier en mode texte (w, r, wt, rt, etc.), il donne une classe fille de io.TextIOBase (spécifiquement : io.TextIOWrapper). Lors de l’ouverture d’un fichier en mode binaire avec tampon, la classe donnée sera une fille de io.BufferedIOBase. La classe exacte varie : en lecture en mode binaire elle donne une io.BufferedReader, en écriture et ajout en mode binaire c’est une io.BufferedWriter, et en lecture/écriture, c’est une io.BufferedRandom. Lorsque le tampon est désactivé, le flux brut, une classe fille de io.RawIOBase, io.FileIO est donnée.

Consultez aussi les modules de gestion de fichiers tel que fileinput, io (où open() est déclarée), os, os.path, tmpfile, et shutil.

Modifié dans la version 3.3:

Le paramètre opener a été ajouté.

Le mode 'x' a été ajouté.

IOError était normalement levée, elle est maintenant un alias de OSError.

FileExistsError est maintenant levée si le fichier ouvert en mode création exclusive ('x') existe déjà.

Modifié dans la version 3.4:

Il n’est plus possible d’hériter de file.

Deprecated since version 3.4, will be removed in version 4.0: Le mode 'U'.

Modifié dans la version 3.5:

Si l’appel système est interrompu et que le gestionnaire de signal ne lève aucune exception, la fonction réessaye l’appel système au lieu de lever une InterruptedError (voir la PEP 475 [https://www.python.org/dev/peps/pep-0475] à propos du raisonnement).

Le gestionnaire d’erreurs 'namereplace' a été ajouté.

Modifié dans la version 3.6:

Ajout du support des objets implémentant os.PathLike.

Sous Windows, ouvrir un buffer du terminal peut renvoyer une sous-classe de io.RawIOBase autre que io.FileIO.

ord(c)

Renvoie le nombre entier représentant le code Unicode du caractère représenté par la chaîne donnée. Par exemple, ord('a') renvoie le nombre entier 97 et ord('€') (symbole Euro) renvoie 8364. Il s’agit de l’inverse de chr().

pow(x, y[, z])

Donne x puissance y, et si z est présent, donne x puissance y modulo z (calculé de manière plus efficiente que pow(x, y) % z). La forme à deux arguments est équivalent à x**y.

Les arguments doivent être de types numériques. Avec des opérandes de différents types, les mêmes règles de coercition que celles des opérateurs arithmétiques binaires s’appliquent. Pour des opérandes de type int, le résultat sera de même type que les opérandes (après coercition) sauf si le second argument est négatif, dans ce cas, les arguments sont convertis en float, et le résultat sera un float aussi. Par exemple, 10**2 donne 100, alors que 10**-2 donne 0.01. Si le second argument est négatif, le troisième doit être omis. Si z est fourni, x et y doivent être des entiers et y positif.

print(*objects, sep=' ', end='\n', file=sys.stdout, flush=False)

Écrit objects dans le flux texte file, séparés par sep et suivis de end. sep, end, file, et flush, s’ils sont présents, doivent être données par mot clef.

Tous les arguments positionnels sont convertis en chaîne comme le fait str(), puis écrits sur le flux, séparés par sep et terminés par end. sep et end doivent être des chaînes, ou None , indiquant de prendre les valeurs par défaut. Si aucun objects n’est donné print() écris seulement end.

L’argument file doit être un objet avec une méthode write(string); s’il n’est pas fourni, ou vaut None, sys.stdout sera utilisé. Puisque les arguments affichés sont convertis en chaîne, print() ne peut pas être utilisé avec des fichiers ouverts en mode binaire. Pour ceux ci utilisez plutôt file.write(...).

Que la sortie utilise un buffer ou non est souvent décidé par file, mais si l’argument flush est vrai, le tampon du flux est vidé explicitement.

Modifié dans la version 3.3: Ajout de l’argument par mot clef flush.

class property(fget=None, fset=None, fdel=None, doc=None)

Donne un attribut propriété.

fget est une fonction permettant d’obtenir la valeur d’un attribut. fset est une fonction pour en définir la valeur. fdel quand à elle permet de supprimer la valeur d’un attribut, et doc créé une docstring pour l’attribut.

Une utilisation typique : définir un attribut managé x :

class C:
    def __init__(self):
        self._x = None

    def getx(self):
        return self._x

    def setx(self, value):
        self._x = value

    def delx(self):
        del self._x

    x = property(getx, setx, delx, "I'm the 'x' property.")

Si c est une instance de C, c.x appellera le getter, c.x = value invoquera le setter, et del x le deleter.

S’il est donné, doc sera la docstring de l’attribut. Autrement la propriété copiera celle de fget (si elle existe). Cela rend possible la création de propriétés en lecture seule en utilisant simplement property() comme un decorator :

class Parrot:
    def __init__(self):
        self._voltage = 100000

    @property
    def voltage(self):
        """Get the current voltage."""
        return self._voltage

Le décorateur @property transforme la méthode voltage() en un getter d’un attribut du même nom, et donne « Get the current voltage » comme docstring de voltage.

Un objet propriété à les méthodes getter, setter et deleter utilisables comme décorateurs créant une copie de la propriété avec les accesseurs correspondants définis par la fonction de décoration. C’est plus clair avec un exemple :

class C:
    def __init__(self):
        self._x = None

    @property
    def x(self):
        """I'm the 'x' property."""
        return self._x

    @x.setter
    def x(self, value):
        self._x = value

    @x.deleter
    def x(self):
        del self._x

Ce code est l’exact équivalent du premier exemple. Soyez attentifs à bien donner aux fonctions additionnelles le même nom que la propriété (x dans ce cas.)

L’objet propriété donné à aussi les attributs fget, fset et fdel correspondant correspondants aux arguments du constructeur.

Modifié dans la version 3.5: Les docstrings des objets propriété peuvent maintenant être écrits.

range(stop)

range(start, stop[, step])

Plutôt qu’être une fonction, range est en fait une séquence immuable, tel que documenté dans Ranges et Types séquentiels — list, tuple, range.

repr(object)

Donne une chaîne contenant une représentation affichable de l’objet. Pour de nombreux types, cette fonction essaye de donner une chaîne qui donnera à son tour un objet de mène valeur lorsqu’elle est passée à eval(), sinon la représentation sera une chaîne entourée de chevrons contenant le nom du type et quelques informations supplémentaires souvent le nom et l’adresse de l’objet. Une classe peut contrôler ce que cette fonction donne pour ses instances en définissant une méthode __repr__().

reversed(seq)

Donne un iterator inversé. seq doit être un objet ayant une méthode __reverse__() ou supportant le protocole séquence (la méthode __len__() et la méthode __getitem__() avec des arguments entiers commençant à zéro).

round(number[, ndigits])

Renvoie number arrondi avec une précision de ndigits chiffres après la virgule. Si ndigits est omis (ou est None), l’entier le plus proche est renvoyé.

Pour les types natifs supportant round(), les valeurs sont arrondies au multiple de 10 puissance moins ndigits, si deux multiples sont équidistants, l’arrondi se fait vers la valeur paire (par exemple round(0.5) et round(-0.5) valent tous les deux 0, et round(1.5) vaut 2). ndigits accepte tout nombre entier (positif, zéro, ou négatif). La valeur renvoyée est un entier si ndigits n’est pas donné, (ou est None). Sinon elle est du même type que number.

Pour tout autre objet Python number, round délègue à number.__round__.

Note

Le comportement de round() avec les nombres à virgule flottante peut être surprenant : par exemple round(2.675, 2) donne 2.67 au lieu de 2.68. Ce n’est pas un bug, mais dû au fait que la plupart des fractions de décimaux ne peuvent pas être représentés exactement en nombre a virgule flottante. Voir Arithmétique en nombres à virgule flottante : problèmes et limites pour plus d’information.

class set([iterable])

Donne un nouveau set, dont les éléments peuvent être extraits d”iterable. set est une classe native. Voir set et Types d’ensembles — set, frozenset pour la documentation de cette classe.

D’autres conteneurs existent, typiquement : frozenset, list, tuple, et dict, ainsi que le module collections.

setattr(object, name, value)

C’est le complément de getattr(). Les arguments sont : un objet, une chaîne, et une valeur de type arbitraire. La chaîne peut nommer un attribut existant ou un nouvel attribut. La fonction assigne la valeur à l’attribut, si l’objet l’autorise. Par exemple, setattr(x, 'foobar', 123) équivaut à x.foobar = 123.

class slice(stop)

class slice(start, stop[, step])

Donne un objet slice représentant un ensemble d’indices spécifiés par range(start, stop, step). Les arguments start et step valent None par défaut. Les objets slice (tranches) ont les attributs suivants en lecture seule : start, stop, et step qui valent simplement les trois arguments (ou leurs valeur par défaut). Ils n’ont pas d’autres fonctionnalité explicite, cependant ils sont utilisés par Numerical Python et d’autres bibliothèques tierces. Les objets slice sont aussi générés par la notation par indices étendue. Par exemple a[start:stop:step] ou a[start:stop, i]. Voir itertools.islice() pour une version alternative donnant un itérateur.

sorted(iterable, *, key=None, reverse=False)

Donne une nouvelle liste triée depuis les éléments d”iterable.

A deux arguments optionnels qui doivent être fournis par mot clef.

key specifies a function of one argument that is used to extract a comparison key from each element in iterable (for example, key=str.lower). The default value is None (compare the elements directly).

reverse, une valeur booléenne. Si elle est True, la liste d’éléments est triée comme si toutes les comparaisons étaient inversées.

Utilisez functools.cmp_to_key() pour convertir l’ancienne notation cmp en une fonction key.

La fonction native sorted() est garantie stable. Un tri est stable s’il garantie de ne pas changer l’ordre relatif des éléments égaux entre eux. C’est utile pour trier en plusieurs passes, par exemple par département puis par salaire).

Pour des exemples de tris et un bref tutoriel, consultez Guide pour le tri.

@staticmethod

Transforme une méthode en méthode statique.

Une méthode statique ne reçoit pas de premier argument implicitement. Voilà comment déclarer une méthode statique :

class C:
    @staticmethod
    def f(arg1, arg2, ...): ...

La forme @staticmethod est un decorator de fonction. Voir la description des définitions de fonction dans Définition de fonctions pour plus de détails.

Elle peut être appelée soit sur une classe (tel que C.f()) ou sur une instance (tel que C().f()). L’instance est ignorée, sauf pour sa classe.

Les méthodes statiques en Python sont similaires à celles trouvées en Java ou en C++. Consultez classmethod() pour une variante utile pour créer des constructeurs alternatifs.

Comme pour tous les décorateurs, il est possible d’appeler staticmethod comme une simple fonction, et faire quelque chose de son résultat. Ça peut être nécessaire dans le cas où vous voudriez une référence à la fonction depuis le corps d’une classe, et souhaiteriez éviter sa transformation en méthode d’instance. Pour ces cas, faites comme suit :

class C:
    builtin_open = staticmethod(open)

Pour plus d’informations sur les méthodes statiques, consultez la documentation de la hiérarchie des types standards dans Hiérarchie des types standards.

class str(object='')

class str(object=b'', encoding='utf-8', errors='strict')

Donne une version sous forme de str d”object. Voir str() pour plus de détails.

str est la class native des chaînes de caractères. Pour des informations générales à propos des chaînes, consultez Type Séquence de Texte — str.

sum(iterable[, start])

Additionne start et les éléments d”iterable de gauche à droite et en donne le total. start vaut 0 par défaut. Les éléments d”iterable sont normalement des nombres, et la valeur de start ne peut pas être une chaîne.

Pour certains cas, il existe de bonnes alternatives à sum(). La bonne méthode, et rapide, de concaténer une séquence de chaînes est d’appeler ''.join(séquence). Pour additionner des nombres à virgule flottante avec une meilleure précision, voir math.fsum(). Pour concaténer une série d’itérables, utilisez plutôt itertools.chain().

super([type[, object-or-type]])

Donne un objet mandataire (proxy object en anglais) déléguant les appels de méthode à une classe parente ou sœur de type type. C’est utile pour accéder à des méthodes héritées et substituées dans la classe. L’ordre de recherche est le même que celui utilisé par getattr() sauf que type lui même est sauté.

L’attribut __mro__ de type liste l’ordre de recherche de la méthode de résolution utilisée par getattr() et super(). L’attribut est dynamique et peut changer lorsque la hiérarchie d’héritage est modifiée.

Si le second argument est omis, l’objet super obtenu n’est pas lié. Si le second argument est un objet, isinstance(obj, type) doit être vrai. Si le second argument est un type, issubclass(type2, type) doit être vrai (c’est utile pour les méthodes de classe).

Il existe deux autres cas d’usage typiques pour super. Dans une hiérarchie de classes à héritage simple, super peut être utilisé pour obtenir la classe parente sans avoir à la nommer explicitement, rendant le code plus maintenable. Cet usage se rapproche de l’usage de super dans d’autres langages de programmation.

Le second est la gestion d’héritage multiple coopératif dans un environnement d’exécution dynamique. Cet usage est unique à Python, il ne se retrouve ni dans les langages compilés statiquement, ni dans les langages ne gérant que l’héritage simple. Cela rend possible d’implémenter un héritage en diamant dans lequel plusieurs classes parentes implémentent la même méthode. Une bonne conception implique que chaque méthode doit avoir la même signature lors de leur appels dans tous les cas (parce que l’ordre des appels est déterminée à l’exécution, parce que l’ordre s’adapte aux changements dans la hiérarchie, et parce que l’ordre peut inclure des classes sœurs inconnues avant l’exécution).

Dans tous les cas, un appel typique à une classe parente ressemble à :

class C(B):
    def method(self, arg):
        super().method(arg)    # This does the same thing as:
                               # super(C, self).method(arg)

Notez que super() fait partie de l’implémentation du processus de liaison de recherche d’attributs pointés explicitement tel que super().__getitem__(name). Il le fait en implémentant sa propre méthode __getattribute__() pour rechercher les classes dans un ordre prévisible supportant l’héritage multiple coopératif. En conséquence, super() n’est pas défini pour les recherches implicites via des instructions ou des opérateurs tel que super()[name].

Notez aussi que, en dehors de sa forme sans arguments, la super() peut être utilisée en dehors des méthodes. La forme à deux arguments est précise et donne tous les arguments exactement, donnant les références appropriées. La forme sans arguments fonctionne seulement à l’intérieur d’une définition de classe, puisque c’est le compilateur qui donne les détails nécessaires à propos de la classe en cours de définition, ainsi qu’accéder à l’instance courante pour les méthodes ordinaires.

Pour des suggestions pratiques sur la conception de classes coopératives utilisant super(), consultez guide to using super() [http://rhettinger.wordpress.com/2011/05/26/super-considered-super/].

tuple([iterable])

Plutôt qu’être une fonction, tuple est en fait un type de séquence immuable, tel que documenté dans Tuples et Types séquentiels — list, tuple, range.

class type(object)

class type(name, bases, dict)

Avec un argument, donne le type d”object. La valeur donnée est un objet type et généralement la même que la valeur de l’attribut object.__class__.

La fonction native isinstance() est recommandée pour tester le type d’un objet car elle prend en compte l’héritage.

Avec trois arguments, renvoie un nouveau type. C’est essentiellement une forme dynamique de l’instruction class. La chaîne name est le nom de la classe et deviendra l’attribut __name__ ; le tuple bases contient les classes mères et deviendra l’attribut __bases__ ; et le dictionnaire dict est l’espace de nommage contenant les définitions du corps de la classe, il est copié vers un dictionnaire standard pour devenir l’attribut __dict__. Par exemple, les deux instructions suivantes créent deux instances identiques de type :

>>> class X:
...     a = 1
...
>>> X = type('X', (object,), dict(a=1))

Voir aussi Objets type.

Modifié dans la version 3.6: Les sous-classes de type qui ne redéfinissent pas type.__new__ ne devraient plus utiliser la forme à un argument pour récupérer le type d’un objet.

vars([object])

Renvoie l’attribut __dict__ d’un module, d’une classe, d’une instance ou de n’importe quel objet avec un attribut __dict__.

Les objets tels que les modules et les instances on un attribut __dict__ modifiable ; Cependant, d’autres objets peuvent avoir des restrictions en écriture sur leurs attributs __dict__ (par exemple, les classes utilisent un types.MappingProxyType pour éviter les modifications directes du dictionnaire).

Sans argument, vars() se comporte comme locals(). Notez que le dictionnaire des variables locales n’est utile qu’en lecture, car ses écritures sont ignorées.

zip(*iterables)

Construit un itérateur agrégeant les éléments de tous les itérables.

Donne un itérateur de tuples, où le i-ième tuple contiens le i-ième élément de chacune des séquences ou itérables fournis. L’itérateur s’arrête lorsque le plus petit itérable fourni est épuisé. Avec un seul argument itérable, elle donne un itérateur sur des tuples d’un élément. Sans arguments, elle donne un itérateur vide. Équivalent à :

def zip(*iterables):
    # zip('ABCD', 'xy') --> Ax By
    sentinel = object()
    iterators = [iter(it) for it in iterables]
    while iterators:
        result = []
        for it in iterators:
            elem = next(it, sentinel)
            if elem is sentinel:
                return
            result.append(elem)
        yield tuple(result)

Il est garanti que les itérables soient évalués de gauche a droite. Cela rend possible de grouper une séquence de données en groupes de taille n via zip(*[iter(s)]*n). Cela duplique le même itérateur n fois tel que le tuple obtenu contient le résultat de n appels à l’itérateur. Cela a pour effet de diviser la séquence en morceaux de taille n.

zip() ne devrait être utilisée avec des itérables de longueur différente que lorsque les dernières données des itérables les plus longs peuvent être ignorées. Si c’est valeurs sont importantes, utilisez plutôt itertools.zip_longest().

zip() peut être utilisée conjointement avec l’opérateur * pour dézipper une liste :

>>> x = [1, 2, 3]
>>> y = [4, 5, 6]
>>> zipped = zip(x, y)
>>> list(zipped)
[(1, 4), (2, 5), (3, 6)]
>>> x2, y2 = zip(*zip(x, y))
>>> x == list(x2) and y == list(y2)
True

__import__(name, globals=None, locals=None, fromlist=(), level=0)

Note

C’est une fonction avancée qui n’est pas fréquemment nécessaire, contrairement à importlib.import_module().

Cette fonction est invoquée via l’instruction import. Elle peut être remplacée (en important le module builtins et en y remplaçant builtins.__import__) afin de changer la sémantique de l’instruction import, mais c’est extrêmement déconseillé car il est plus simple d’utiliser des import hooks (voir la PEP 302 [https://www.python.org/dev/peps/pep-0302]) pour le même résultat sans gêner du code s’attendant à trouver l’implémentation par défaut. L’usage direct de __import__() est aussi déconseillé en faveur de importlib.import_module().

La fonction importe le module name, utilisant potentiellement globals et locals pour déterminer comment interpréter le nom dans le contexte d’un paquet. fromlist donne le nom des objets ou sous-modules qui devraient être importés du module name. L’implémentation standard n’utilise pas l’argument locals et n’utilise globals que pour déterminer le contexte du paquet de l’instruction import.

level permet de choisir entre importation absolue ou relative. 0 (par défaut) implique de n’effectuer que des importations absolues. Une valeur positive indique le nombre de dossiers parents relativement au dossier du module appelant __import__() (voir la PEP 328 [https://www.python.org/dev/peps/pep-0328]).

Lorsque la variable name est de la forme package.module, normalement, le paquet le plus haut (le nom jusqu’au premier point) est donné, et pas le module nommé par name. Cependant, lorsqu’un argument fromlist est fourni, le module nommé par name est donné.

Par exemple, l’instruction import spam donne un code intermédiaire (bytecode en anglais) ressemblant au code suivant :

spam = __import__('spam', globals(), locals(), [], 0)

L’instruction import ham.ham appelle :

spam = __import__('spam.ham', globals(), locals(), [], 0)

Notez comment __import__() donne le module le plus haut ici parce que c’est l’objet lié à un nom par l’instruction import.

En revanche, l’instruction from spam.ham import eggs, sausage as saus donne

_temp = __import__('spam.ham', globals(), locals(), ['eggs', 'sausage'], 0)
eggs = _temp.eggs
saus = _temp.sausage

Ici le module spam.ham est donné par __import__(). De cet objet, les noms à importer sont récupérés et assignés à leurs noms respectifs.

Si vous voulez simplement importer un module (potentiellement dans un paquet) par son nom, utilisez importlib.import_module().

Modifié dans la version 3.3: Des valeurs négatives pour level ne sont plus gérées (ce qui change la valeur par défaut pour 0).

Notes

1

Notez que l’analyseur n’accepte que des fin de lignes de style Unix. Si vous lisez le code depuis un fichier, assurez-vous d’utiliser la conversion de retours à la ligne pour convertir les fin de lignes Windows et Mac.

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3. Constantes natives

Un petit nombre de constantes existent dans le namespace natif. Elles sont :

False

La valeur fausse du type bool. Les assignations à False ne sont pas autorisées et lèvent une SyntaxError.

True

La valeur vraie du type bool. Les assignations à True ne sont pas autorisées et lèvent une SyntaxError.

None

None est l’unique valeur du type NoneType. Elle est utilisée fréquemment pour représenter l’absence de valeur, comme lorsque des arguments par défaut ne sont pas passés à une fonction. Les assignations à None ne sont pas autorisées et lèvent une SyntaxError.

NotImplemented

Valeur spéciale qui devrait être renvoyée par les méthodes magiques à deux opérandes (e.g. __eq__(), __lt__(), __add__(), __rsub__(), etc.) pour indiquer que l’opération n’est pas implémentée pour l’autre type ; peut être renvoyé par les méthodes magiques augmentées à deux opérandes (e.g. __imul__(), __iand__(), etc.) avec le même objectif. Sa valeur booléenne est True.

Note

Lorsqu’une méthode à deux opérandes renvoie NotImplemented, l’interpréteur essaye d’exécuter l’opération réfléchie sur l’autre type (il existe d’autres mécanismes de fallback, en fonction de l’opérateur). Si toutes les tentatives renvoient NotImplemented, l’interpréteur lève une exception appropriée. Renvoyer NotImplemented à tort donne lieu à un message d’erreur peu clair ou au renvoi de la valeur NotImplemented pour le code Python.

Voir Implémentation des opérations arithmétiques pour des exemples.

Note

NotImplementedError et NotImplemented ne sont pas interchangeables, même s’ils ont un nom et un objectif similaire. Voir NotImplementedError pour savoir quand l’utiliser.

Ellipsis

The same as the ellipsis literal « ... ». Special value used mostly in conjunction with extended slicing syntax for user-defined container data types.

__debug__

Cette constante est vraie si Python n’a pas été démarré avec une option -O. Voir aussi l’expression assert.

Note

Les noms None, False, True et __debug__ ne peuvent pas être réassignés (des assignations à ces noms, ou aux noms de leurs attributs, lèvent une SyntaxError), donc ils peuvent être considérés comme des « vraies » constantes.

3.1. Constantes ajoutées par le module site

Le module site (qui est importé automatiquement au démarrage, sauf si l’option de ligne de commande -S est donnée ajoute un certain nombre de constantes au namespace natif. Elles sont utiles pour l’interpréteur interactif et ne devraient pas être utilisées par des programmes.

quit(code=None)

exit(code=None)

Objets qui, lorsqu’ils sont représentés, affichent un message comme « Use quit() or Ctrl-D (i.e. EOF) to exit », et lorsqu’ils sont appelés, lèvent un SystemExit avec le code de retour spécifié.

copyright

credits

Objets qui, lorsqu’ils sont affichés ou appelés, affichent le copyright ou les crédits, respectivement.

license

Objet qui, lorsqu’il est affiché, affiche un message comme « Type license() to see the full license text », et lorsqu’il est appelé, affiche le texte complet de la licence dans un style paginé (un écran à la fois).

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4. Types natifs

Les sections suivantes décrivent les types standards intégrés à l’interpréteur.

Les principaux types natifs sont les numériques, les séquences, les dictionnaires, les classes, les instances et les exceptions.

Certaines classes de collection sont muables. Les méthodes qui ajoutent, retirent, ou réorganisent leurs éléments sur place, et qui ne renvoient pas un élément spécifique, ne renvoient jamais l’instance de la collection elle-même, mais None.

Certaines opérations sont prises en charge par plusieurs types d’objets; en particulier, pratiquement tous les objets peuvent être comparés, testés (valeur booléenne), et convertis en une chaîne (avec la fonction repr() ou la fonction légèrement différente str()). Cette dernière est implicitement utilisée quand un objet est écrit par la fonction print().

4.1. Valeurs booléennes

Tout objet peut être comparé à une valeur booléenne, typiquement dans une condition if ou while ou comme opérande des opérations booléennes ci-dessous.

Par défaut, tout objet est considéré vrai à moins que sa classe définisse soit une méthode __bool__() renvoyant False soit une méthode __len__() renvoyant zéro lorsqu’elle est appelée avec l’objet. 1 Voici la majorité des objets natifs considérés comme étant faux :

les constantes définies comme étant fausses : None et False.

zéro de tout type numérique : 0, 0.0, 0j, Decimal(0), Fraction(0, 1)

les chaînes et collections vides : '', (), [], {}, set(), range(0)

Les opérations et fonctions natives dont le résultat est booléen donnent toujours 0 ou False pour faux et 1 ou True pour vrai, sauf indication contraire. (Exception importante : les opérations booléennes or et and renvoient toujours l’une de leurs opérandes.)

4.2. Opérations booléennes — and, or, not

Ce sont les opérations booléennes, classées par priorité ascendante :

Opération

Résultat

Notes

x or y

si x est faux, alors y, sinon x

(1)

x and y

si x est faux, alors x, sinon y

(2)

not x

si x est faux, alors True, sinon False

(3)

Notes :

Ceci est un opérateur court-circuit : il n’évalue le deuxième argument que si le premier est faux.

Ceci est un opérateur court-circuit, il n’évalue le deuxième argument si le premier est vrai.

not a une priorité inférieure à celle des opérateurs non-booléens, donc not a == b est interprété comme not (a == b) et a == not b est une erreur de syntaxe.

4.3. Comparaisons

Il y a huit opérations de comparaison en Python. Elles ont toutes la même priorité (qui est supérieure à celle des opérations booléennes). Les comparaisons peuvent être enchaînées arbitrairement ; par exemple, x < y <= z est équivalent à x < y and y <= z, sauf que y n’est évalué qu’une seule fois (mais dans les deux cas z n’est pas évalué du tout quand x < y est faux).

Ce tableau résume les opérations de comparaison :

Opération

Signification

<

strictement inférieur

<=

inférieur ou égal

>

strictement supérieur

>=

supérieur ou égal

==

égal

!=

différent

is

identité d’objet

is not

contraire de l’identité d’objet

Les objets de différents types, à l’exception de différents types numériques, ne peuvent en aucun cas être égaux. En outre, certains types (par exemple, les objets fonction) ne gèrent qu’une une notion dégénérée de la comparaison où deux objets de ce type sont inégaux. Les opérateurs <, <=, > et >= lèvent une exception TypeError lorsqu’on compare un nombre complexe avec un autre type natif numérique, lorsque les objets sont de différents types qui ne peuvent pas être comparés, ou dans d’autres cas où il n’y a pas d’ordre défini.

Des instances différentes d’une classe sont normalement considérées différentes à moins que la classe ne définisse la méthode __eq__().

Les instances d’une classe ne peuvent pas être ordonnées par rapport à d’autres instances de la même classe, ou d’autres types d’objets, à moins que la classe ne définisse suffisamment de méthodes parmi __lt__(), __le__(), __gt__() et __ge__() (en général, __lt__() et __eq__() sont suffisantes, si vous voulez les significations classiques des opérateurs de comparaison).

Le comportement des opérateurs is et is not ne peut pas être personnalisé ; aussi ils peuvent être appliqués à deux objets quelconques et ne lèvent jamais d’exception.

Two more operations with the same syntactic priority, in and not in, are supported by types that are iterable or implement the __contains__() method.

4.4. Types numériques — int, float, complex

Il existe trois types numériques distincts: integers (entiers), floating point numbers (nombres flottants) et complex numbers (nombres complexes). En outre, les booléens sont un sous-type des entiers. Les entiers ont une précision illimitée. Les nombres à virgule flottante sont généralement implémentés en utilisant des double en C ; des informations sur la précision et la représentation interne des nombres à virgule flottante pour la machine sur laquelle le programme est en cours d’exécution est disponible dans sys.float_info. Les nombres complexes ont une partie réelle et une partie imaginaire, qui sont chacune des nombres à virgule flottante. Pour extraire ces parties d’un nombre complexe z, utilisez z.real et z.imag. (La bibliothèque standard comprend d’autres types numériques, fractions qui stocke des rationnels et decimal qui stocke les nombres à virgule flottante avec une précision définissable par l’utilisateur.)

Les nombres sont créés par des littéraux numériques ou sont le résultat de fonctions natives ou d’opérateurs. Les entiers littéraux basiques (y compris leur forme hexadécimale, octale et binaire) donnent des entiers. Les nombres littéraux contenant un point décimal ou un exposant donnent des nombres à virgule flottante. Suffixer 'j' ou 'J' à un nombre littéral donne un nombre imaginaire (un nombre complexe avec une partie réelle nulle) que vous pouvez ajouter à un nombre entier ou un à virgule flottante pour obtenir un nombre complexe avec une partie réelle et une partie imaginaire.

Python gère pleinement l’arithmétique mixte : quand un opérateur arithmétique binaire a des opérandes de types numériques différents, l’opérande avec le type « le plus étroit » est élargie au type de l’autre, où l’entier est plus étroit que la virgule flottante, qui est plus étroite que les complexes. Les comparaisons entre des nombres de type mixte utilisent la même règle. 2 Les constructeurs int(), float() et complex() peuvent être utilisé pour produire des nombres d’un type spécifique.

Tous les types numériques (sauf complexe) gèrent les opérations suivantes, classées par priorité ascendante (toutes les opérations numériques ont une priorité plus élevée que les opérations de comparaison) :

Opération

Résultat

Notes

Documentation complète

x + y

somme de x et y

x - y

différence de x et y

x * y

produit de x et y

x / y

quotient de x et y

x // y

quotient entier de x et y

(1)

x % y

reste de x / y

(2)

-x

négatif de x

+x

x inchangé

abs(x)

valeur absolue de x

abs()

int(x)

x converti en nombre entier

(3)(6)

int()

float(x)

x converti en nombre à virgule flottante

(4)(6)

float()

complex(re, im)

un nombre complexe avec re pour partie réelle et im pour partie imaginaire. im vaut zéro par défaut.

(6)

complex()

c.conjugate()

conjugué du nombre complexe c

divmod(x, y)

la paire (x // y, x % y)

(2)

divmod()

pow(x, y)

x à la puissance y

(5)

pow()

x ** y

x à la puissance y

(5)

Notes :

Également appelé division entière. La valeur résultante est un nombre entier, bien que le type du résultat ne soit pas nécessairement int. Le résultat est toujours arrondi vers moins l’infini : 1//2 vaut 0, (-1)//2 vaut -1, 1//(-2) vaut -1, et (-1)//(-2) vaut 0.

Pas pour les nombres complexes. Convertissez-les plutôt en nombres flottants à l’aide de abs() si c’est approprié.

La conversion de virgule flottante en entier peut arrondir ou tronquer comme en C ; voir les fonctions math.floor() et math.ceil() pour des conversions bien définies.

float accepte aussi les chaînes nan et inf avec un préfixe optionnel + ou - pour Not a Number (NaN) et les infinis positif ou négatif.

Python définit pow(0, 0) et 0 ** 0 valant 1, puisque c’est courant pour les langages de programmation, et logique.

Les littéraux numériques acceptés comprennent les chiffres 0 à 9 ou tout équivalent Unicode (caractères avec la propriété Nd).

Voir http://www.unicode.org/Public/9.0.0/ucd/extracted/DerivedNumericType.txt pour une liste complète des caractères avec la propriété Nd.

Tous types numbers.Real (int et float) comprennent également les opérations suivantes :

Opération

Résultat

math.trunc(x)

x tronqué à l”Integral

round(x[, n])

x arrondi à n chiffres, arrondissant la moitié au pair. Si n est omis, la valeur par défaut à 0.

math.floor(x)

le plus grand Integral <= x

math.ceil(x)

le plus petit Integral >= x

Pour d’autres opérations numériques voir les modules math et cmath.

4.4.1. Opérations sur les bits des nombres entiers

Bitwise operations only make sense for integers. The result of bitwise operations is calculated as though carried out in two’s complement with an infinite number of sign bits.

Les priorités de toutes les opération à deux opérandes sur des bits sont inférieures aux opérations numériques et plus élevées que les comparaisons ; l’opération unaire ~ a la même priorité que les autres opérations numériques unaires (+ et -).

Ce tableau répertorie les opérations binaires triées par priorité ascendante :

Opération

Résultat

Notes

x | y

ou <or> binaire de x et y

(4)

x ^ y

ou <or> exclusive binaire de x et y

(4)

x & y

et binaire <and> de x et y

(4)

x << n

x décalé vers la gauche de n bits

(1)(2)

x >> n

x décalé vers la droite de n bits

(1)(3)

~x

les bits de x, inversés

Notes :

Des valeurs de décalage négatives sont illégales et provoquent une exception ValueError.

Un décalage à gauche de n bits est équivalent à la multiplication par pow(2, n) sans vérification de débordement.

Un décalage à droite de n les bits est équivalent à la division par pow(2, n) sans vérification de débordement.

Performing these calculations with at least one extra sign extension bit in a finite two’s complement representation (a working bit-width of 1 + max(x.bit_length(), y.bit_length()) or more) is sufficient to get the same result as if there were an infinite number of sign bits.

4.4.2. Méthodes supplémentaires sur les entiers

Le type int implémente la classe de base abstraite numbers.Integral. Il fournit aussi quelques autres méthodes :

int.bit_length()

Renvoie le nombre de bits nécessaires pour représenter un nombre entier en binaire, à l’exclusion du signe et des zéros non significatifs :

>>> n = -37
>>> bin(n)
'-0b100101'
>>> n.bit_length()
6

Plus précisément, si x est différent de zéro, x.bit_length() est le nombre entier positif unique, k tel que 2**(k-1) <= abs(x) < 2**k. Équivalemment, quand abs(x) est assez petit pour avoir un logarithme correctement arrondi, k = 1 + int(log(abs(x), 2)). Si x est nul, alors x.bit_length() donne 0.

Équivalent à :

def bit_length(self):
    s = bin(self)       # binary representation:  bin(-37) --> '-0b100101'
    s = s.lstrip('-0b') # remove leading zeros and minus sign
    return len(s)       # len('100101') --> 6

Nouveau dans la version 3.1.

int.to_bytes(length, byteorder, *, signed=False)

Renvoie un tableau d’octets représentant un nombre entier.

>>> (1024).to_bytes(2, byteorder='big')
b'\x04\x00'
>>> (1024).to_bytes(10, byteorder='big')
b'\x00\x00\x00\x00\x00\x00\x00\x00\x04\x00'
>>> (-1024).to_bytes(10, byteorder='big', signed=True)
b'\xff\xff\xff\xff\xff\xff\xff\xff\xfc\x00'
>>> x = 1000
>>> x.to_bytes((x.bit_length() + 7) // 8, byteorder='little')
b'\xe8\x03'

L’entier est représenté par length octets. Une exception OverflowError est levée s’il n’est pas possible de représenter l’entier avec le nombre d’octets donnés.

L’argument byteorder détermine l’ordre des octets utilisé pour représenter le nombre entier. Si byteorder est "big", l’octet le plus significatif est au début du tableau d’octets. Si byteorder est "little", l’octet le plus significatif est à la fin du tableau d’octets. Pour demander l’ordre natif des octets du système hôte, donnez sys.byteorder comme byteorder.

L’argument signed détermine si le complément à deux est utilisé pour représenter le nombre entier. Si signed est False et qu’un entier négatif est donné, une exception OverflowError est levée. La valeur par défaut pour signed est False.

Nouveau dans la version 3.2.

classmethod int.from_bytes(bytes, byteorder, *, signed=False)

Donne le nombre entier représenté par le tableau d’octets fourni.

>>> int.from_bytes(b'\x00\x10', byteorder='big')
16
>>> int.from_bytes(b'\x00\x10', byteorder='little')
4096
>>> int.from_bytes(b'\xfc\x00', byteorder='big', signed=True)
-1024
>>> int.from_bytes(b'\xfc\x00', byteorder='big', signed=False)
64512
>>> int.from_bytes([255, 0, 0], byteorder='big')
16711680

L’argument bytes doit être soit un bytes-like object soit un itérable produisant des bytes.

L’argument byteorder détermine l’ordre des octets utilisé pour représenter le nombre entier. Si byteorder est "big", l’octet le plus significatif est au début du tableau d’octets. Si byteorder est "little", l’octet le plus significatif est à la fin du tableau d’octets. Pour demander l’ordre natif des octets du système hôte, donnez sys.byteorder comme byteorder.

L’argument signed indique si le complément à deux est utilisé pour représenter le nombre entier.

Nouveau dans la version 3.2.

4.4.3. Méthodes supplémentaires sur les nombres à virgule flottante

Le type float implémente la classe de base abstraite numbers.Real et a également les méthodes suivantes.

float.as_integer_ratio()

Renvoie une paire de nombres entiers dont le rapport est exactement égal au nombre d’origine et avec un dénominateur positif. Lève OverflowError avec un infini et ValueError avec un NaN.

float.is_integer()

Donne True si l’instance de float est finie avec une valeur entière, et False autrement :

>>> (-2.0).is_integer()
True
>>> (3.2).is_integer()
False

Deux méthodes prennent en charge la conversion vers et à partir de chaînes hexadécimales. Étant donné que les float de Python sont stockés en interne sous forme de nombres binaires, la conversion d’un float depuis ou vers une chaine décimale implique généralement une petite erreur d’arrondi. En revanche, les chaînes hexadécimales permettent de représenter exactement les nombres à virgule flottante. Cela peut être utile lors du débogage, et dans un travail numérique.

float.hex()

Donne une représentation d’un nombre à virgule flottante sous forme de chaîne hexadécimale. Pour les nombres à virgule flottante finis, cette représentation comprendra toujours un préfixe 0x, un suffixe p, et un exposant.

classmethod float.fromhex(s)

Méthode de classe pour obtenir le float représenté par une chaîne de caractères hexadécimale s. La chaîne s peut contenir des espaces avant et après le chiffre.

Notez que float.hex() est une méthode d’instance, alors que float.fromhex() est une méthode de classe.

Une chaîne hexadécimale prend la forme :

[sign] ['0x'] integer ['.' fraction] ['p' exponent]

où sign peut être soit + soit -, integer et fraction sont des chaînes de chiffres hexadécimales, et exponent est un entier décimal facultativement signé. La casse n’est pas significative, et il doit y avoir au moins un chiffre hexadécimal soit dans le nombre entier soit dans la fraction. Cette syntaxe est similaire à la syntaxe spécifiée dans la section 6.4.4.2 de la norme C99, et est aussi la syntaxe utilisée à partir de Java 1.5. En particulier, la sortie de float.hex() est utilisable comme valeur hexadécimale à virgule flottante littérale en C ou Java, et des chaînes hexadécimales produites en C via un format %a ou Java via Double.toHexString sont acceptées par float.fromhex().

Notez que l’exposant est écrit en décimal plutôt qu’en hexadécimal, et qu’il donne la puissance de 2 par lequel multiplier le coefficient. Par exemple, la chaîne hexadécimale 0x3.a7p10 représente le nombre à virgule flottante (3 + 10./16 + 7./16**2) *2.0**10, ou 3740.0 :

>>> float.fromhex('0x3.a7p10')
3740.0

L’application de la conversion inverse à 3740.0 donne une chaîne hexadécimale différente représentant le même nombre :

>>> float.hex(3740.0)
'0x1.d380000000000p+11'

4.4.4. Hachage des types numériques

Pour deux nombres égaux x et y (x == y), pouvant être de différents types, il est une requis que hash(x) == hash(y) (voir la documentation de __hash__()). Pour faciliter la mise en œuvre et l’efficacité à travers une variété de types numériques (y compris int, float, decimal.Decimal et fractions.Fraction) le hachage en Python pour les types numérique est basé sur une fonction mathématique unique qui est définie pour tout nombre rationnel, et donc s’applique à toutes les instances de int et fractions.Fraction, et toutes les instances finies de float et decimal.Decimal. Essentiellement, cette fonction est donnée par la réduction modulo P pour un nombre P premier fixe. La valeur de P est disponible comme attribut modulus de sys.hash_info.

CPython implementation detail: Actuellement, le premier utilisé est P = 2 ** 31 - 1 sur des machines dont les longs en C sont de 32 bits P = 2 ** 61 - 1 sur des machines dont les longs en C font 64 bits.

Voici les règles en détail :

Si x = m / n est un nombre rationnel non négatif et n n’est pas divisible par P, définir hash(x) comme m * invmod(n, P) % P, où invmod(n, P) donne l’inverse de n modulo P.

Si x = m / n est un nombre rationnel non négatif et n est divisible par P (mais m ne l’est pas), alors n n’a pas de modulo inverse P et la règle ci-dessus n’est pas applicable ; dans ce cas définir hash(x) comme étant la valeur de la constante sys.hash_info.inf.

Si x = m / n est un nombre rationnel négatif définir hash(x) comme -hash(-x). Si le résultat est -1, le remplacer par -2.

Les valeurs particulières sys.hash_info.inf, -sys.hash_info.inf et sys.hash_info.nan sont utilisées comme valeurs de hachage pour l’infini positif, l’infini négatif, ou nans (respectivement). (Tous les nans hachables ont la même valeur de hachage.)

Pour un nombre complexe z, les valeurs de hachage des parties réelles et imaginaires sont combinées en calculant hash(z.real) + sys.hash_info.imag * hash(z.imag), réduit au modulo 2**sys.hash_info.width de sorte qu’il se trouve dans range(-2**(sys.hash_info.width - 1), 2**(sys.hash_info.width - 1)). Encore une fois, si le résultat est -1, il est remplacé par -2.

Afin de clarifier les règles ci-dessus, voici quelques exemples de code Python, équivalent à la fonction de hachage native, pour calculer le hachage d’un nombre rationnel, d’un float, ou d’un complex :

import sys, math

def hash_fraction(m, n):
    """Compute the hash of a rational number m / n.

    Assumes m and n are integers, with n positive.
    Equivalent to hash(fractions.Fraction(m, n)).

    """
    P = sys.hash_info.modulus
    # Remove common factors of P.  (Unnecessary if m and n already coprime.)
    while m % P == n % P == 0:
        m, n = m // P, n // P

    if n % P == 0:
        hash_value = sys.hash_info.inf
    else:
        # Fermat's Little Theorem: pow(n, P-1, P) is 1, so
        # pow(n, P-2, P) gives the inverse of n modulo P.
        hash_value = (abs(m) % P) * pow(n, P - 2, P) % P
    if m < 0:
        hash_value = -hash_value
    if hash_value == -1:
        hash_value = -2
    return hash_value

def hash_float(x):
    """Compute the hash of a float x."""

    if math.isnan(x):
        return sys.hash_info.nan
    elif math.isinf(x):
        return sys.hash_info.inf if x > 0 else -sys.hash_info.inf
    else:
        return hash_fraction(*x.as_integer_ratio())

def hash_complex(z):
    """Compute the hash of a complex number z."""

    hash_value = hash_float(z.real) + sys.hash_info.imag * hash_float(z.imag)
    # do a signed reduction modulo 2**sys.hash_info.width
    M = 2**(sys.hash_info.width - 1)
    hash_value = (hash_value & (M - 1)) - (hash_value & M)
    if hash_value == -1:
        hash_value = -2
    return hash_value

4.5. Les types itérateurs

Python supporte un concept d’itération sur les conteneurs. C’est implémenté en utilisant deux méthodes distinctes qui permettent aux classes définies par l’utilisateur de devenir itérables. Les séquences, décrites plus bas en détail, supportent toujours les méthodes d’itération.

Une méthode doit être définie afin que les objets conteneurs supportent l’itération :

container.__iter__()

Donne un objet itérateur. L’objet doit implémenter le protocole d’itération décrit ci-dessous. Si un conteneur prend en charge différents types d’itération, d’autres méthodes peuvent être fournies pour obtenir spécifiquement les itérateurs pour ces types d’itération. (Exemple d’un objet supportant plusieurs formes d’itération : une structure d’arbre pouvant être parcourue en largeur ou en profondeur.) Cette méthode correspond à l’attribut tp_iter de la structure du type des objets Python dans l’API Python/C.

Les itérateurs eux-mêmes doivent implémenter les deux méthodes suivantes, qui forment ensemble le protocole d’itérateur <iterator protocol> :

iterator.__iter__()

Donne l’objet itérateur lui-même. Cela est nécessaire pour permettre à la fois à des conteneurs et des itérateurs d’être utilisés avec les instructions for et in. Cette méthode correspond à l’attribut tp_iter de la structure des types des objets Python dans l’API Python/C.

iterator.__next__()

Donne l’élément suivant du conteneur. S’il n’y a pas d’autres éléments, une exception StopIteration est levée. Cette méthode correspond à l’attribut PyTypeObject.tp_iternext de la structure du type des objets Python dans l’API Python/C.

Python définit plusieurs objets itérateurs pour itérer sur les types standards ou spécifiques de séquence, de dictionnaires et d’autres formes plus spécialisées. Les types spécifiques ne sont pas importants au-delà de leur implémentation du protocole d’itération.

Dès que la méthode __next__() lève une exception StopIteration, elle doit continuer à le faire lors des appels ultérieurs.Implémentations qui ne respectent pas cette propriété sont considérées cassées.

4.5.1. Types générateurs

Les generators offrent un moyen pratique d’implémenter le protocole d’itération. Si la méthode __iter__() d’un objet conteneur est implémentée comme un générateur, elle renverra automatiquement un objet iterator (techniquement, un objet générateur) fournissant les méthodes __iter__() et __next__(). Plus d’informations sur les générateurs peuvent être trouvés dans la documentation de l’expression yield.

4.6. Types séquentiels — list, tuple, range

Il existe trois types séquentiels basiques: les lists, tuples et les range. D’autres types séquentiels spécifiques au traitement de données binaires et chaînes de caractères sont décrits dans des sections dédiées.

4.6.1. Opérations communes sur les séquences

Les opérations dans le tableau ci-dessous sont pris en charge par la plupart des types séquentiels, variables et immuables. La classe de base abstraite collections.abc.Sequence est fournie pour aider à implémenter correctement ces opérations sur les types séquentiels personnalisés.

Ce tableau répertorie les opérations sur les séquences triées par priorité ascendante. Dans le tableau, s, et t sont des séquences du même type, n, i, j et k sont des nombres entiers et x est un objet arbitraire qui répond à toutes les restrictions de type et de valeur imposée par s.

Les opérations in et not in ont les mêmes priorités que les opérations de comparaison. Les opérations + (concaténation) et * (répétition) ont la même priorité que les opérations numériques correspondantes. 3

Opération

Résultat

Notes

x in s

True si un élément de s est égal à x, sinon False

(1)

x not in s

False si un élément de s est égal à x, sinon True

(1)

s + t

la concaténation de s et t

(6)(7)

s * n or n * s

équivalent à ajouter s n fois à lui même

(2)(7)

s[i]

ie élément de s en commençant par 0

(3)

s[i:j]

tranche (slice) de s de i à j

(3)(4)

s[i:j:k]

tranche (slice) de s de i à j avec un pas de k

(3)(5)

len(s)

longueur de s

min(s)

plus petit élément de s

max(s)

plus grand élément de s

s.index(x[, i[, j]])

indice de la première occurrence de x dans s (à ou après l’indice i et avant indice j)

(8)

s.count(x)

nombre total d’occurrences de x dans s

Les séquences du même type supportent également la comparaison. En particulier, les n-uplets et les listes sont comparés lexicographiquement en comparant les éléments correspondants. Cela signifie que pour que deux séquences soit égales, les éléments les constituant doivent être égaux deux à deux et les deux séquences doivent être du même type et de la même longueur. (Pour plus de détails voir Comparaisons dans la référence du langage.)

Notes :

Bien que les opérations in et not in ne soient généralement utilisées que pour les tests d’appartenance simple, certaines séquences spécialisées (telles que str, bytes et bytearray) les utilisent aussi pour tester l’existence de sous-séquences :

>>> "gg" in "eggs"
True

Les valeurs de n plus petites que 0 sont traitées comme 0 (ce qui donne une séquence vide du même type que s). Notez que les éléments de s ne sont pas copiés ; ils sont référencés plusieurs fois. Cela hante souvent de nouveaux développeurs Python, typiquement :

>>> lists = [[]] * 3
>>> lists
[[], [], []]
>>> lists[0].append(3)
>>> lists
[[3], [3], [3]]

Ce qui est arrivé est que [[]] est une liste à un élément contenant une liste vide, de sorte que les trois éléments de [[]] * 3 sont des références à cette seule liste vide. Modifier l’un des éléments de lists modifie cette liste unique. Vous pouvez créer une liste des différentes listes de cette façon :

>>> lists = [[] for i in range(3)]
>>> lists[0].append(3)
>>> lists[1].append(5)
>>> lists[2].append(7)
>>> lists
[[3], [5], [7]]

De plus amples explications sont disponibles dans la FAQ à la question Comment créer une liste à plusieurs dimensions ?.

Si i ou j sont négatifs, l’indice est relatif à la fin de la séquence s : len(s) + i ou len(s) + j est substitué. Mais notez que -0 est toujours 0.

La tranche de s de i à j est définie comme la séquence d’éléments d’indice k tels que i <= k < j. Si i ou j est supérieur à len(s), len(s) est utilisé. Si i est omis ou None, 0 est utilisé. Si j est omis ou None, len(s) est utilisé. Si i est supérieure ou égale à j, la tranche est vide.

La tranche de s de i à j avec un pas de k est définie comme la séquence d’éléments d’indice x = i + n*k tels que 0 <= n < (j-i)/k. En d’autres termes, les indices sont i, i+k, i+2*k, i+3*k et ainsi de suite, en arrêtant lorsque j est atteint (mais jamais inclus). Si k est positif, i et j sont réduits, s’ils sont plus grands, à len(s). Si k est négatif, i et j sont réduits à len(s) - 1 s’ils sont plus grands. Si i ou j sont omis ou sont None, ils deviennent des valeurs « extrêmes » (où l’ordre dépend du signe de k). Remarquez, k ne peut pas valoir zéro. Si k est None, il est traité comme 1.

Concaténer des séquences immuables donne toujours un nouvel objet. Cela signifie que la construction d’une séquence par concaténations répétées aura une durée d’exécution quadratique par rapport à la longueur de la séquence totale. Pour obtenir un temps d’exécution linéaire, vous devez utiliser l’une des alternatives suivantes :

si vous concaténez des str, vous pouvez construire une liste puis utiliser str.join() à la fin, ou bien écrire dans une instance de io.StringIO et récupérer sa valeur lorsque vous avez terminé

si vous concaténez des bytes, vous pouvez aussi utiliser bytes.join() ou io.BytesIO, ou vous pouvez faire les concaténation sur place avec un objet bytearray. Les objets bytearray sont muables et ont un mécanisme de sur-allocation efficace

si vous concaténez des tuple, utilisez plutôt extend sur une list

pour d’autres types, cherchez dans la documentation de la classe concernée

Certains types séquentiels (tels que range) ne supportent que des séquences qui suivent des modèles spécifiques, et donc ne prennent pas en charge la concaténation ou la répétition.

index lève une exception ValueError quand x ne se trouve pas dans s. Toutes les implémentations ne gèrent pas les deux paramètres supplémentaires i et j. Ces deux arguments permettent de chercher efficacement dans une sous-séquence de la séquence. Donner ces arguments est plus ou moins équivalent à s[i:j].index(x), sans copier les données ; l’indice renvoyé alors relatif au début de la séquence plutôt qu’au début de la tranche.

4.6.2. Types de séquences immuables

La seule opération que les types de séquences immuables implémentent qui n’est pas implémentée par les types de séquences muables est le support de la fonction native hash().

Cette implémentation permet d’utiliser des séquences immuables, comme les instances de tuple, en tant que clés de dict et stockées dans les instances de set et frozenset.

Essayer de hacher une séquence immuable qui contient des valeurs non-hachables lèvera une TypeError.

4.6.3. Types de séquences muables

Les opérations dans le tableau ci-dessous sont définies sur les types de séquences muables. La classe de base abstraite collections.abc.MutableSequence est prévue pour faciliter l’implémentation correcte de ces opérations sur les types de séquence personnalisées.

Dans le tableau s est une instance d’un type de séquence muable, t est un objet itérable et x est un objet arbitraire qui répond à toutes les restrictions de type et de valeur imposées par s (par exemple, bytearray accepte uniquement des nombres entiers qui répondent à la restriction de la valeur 0 <= x <= 255).

Opération

Résultat

Notes

s[i] = x

élément i de s est remplacé par x

s[i:j] = t

tranche de s de i à j est remplacée par le contenu de l’itérable t

del s[i:j]

identique à s[i:j] = []

s[i:j:k] = t

les éléments de s[i:j:k] sont remplacés par ceux de t

(1)

del s[i:j:k]

supprime les éléments de s[i:j:k] de la liste

s.append(x)

ajoute x à la fin de la séquence (identique à s[len(s):len(s)] = [x])

s.clear()

removes all items from s (same as del s[:])

(5)

s.copy()

creates a shallow copy of s (same as s[:])

(5)

s.extend(t) or s += t

étend s avec le contenu de t (proche de s[len(s):len(s)] = t)

s *= n

met à jour s avec son contenu répété n fois

(6)

s.insert(i, x)

insère x dans s à l’index donné par i (identique à s[i:i] = [x])

s.pop([i])

récupère l’élément à i et le supprime de s

(2)

s.remove(x)

supprime le premier élément de s pour qui s[i] == x

(3)

s.reverse()

inverse sur place les éléments de s

(4)

Notes :

t doit avoir la même longueur que la tranche qu’il remplace.

L’argument optionnel i vaut -1 par défaut, afin que, par défaut, le dernier élément soit retiré et renvoyé.

remove lève une exception ValueError si x ne se trouve pas dans s.

La méthode reverse() modifie les séquence sur place pour économiser de l’espace lors du traitement de grandes séquences. Pour rappeler aux utilisateurs qu’elle a un effet de bord, elle ne renvoie pas la séquence inversée.

clear() et copy() sont incluses pour la compatibilité avec les interfaces des conteneurs muables qui ne supportent pas les opérations de découpage (comme dict et set)

Nouveau dans la version 3.3: méthodes clear() et copy().

La valeur n est un entier, ou un objet implémentant __index__(). Zéro et les valeurs négatives de n permettent d’effacer la séquence. Les éléments dans la séquence ne sont pas copiés ; ils sont référencés plusieurs fois, comme expliqué pour s * n dans Opérations communes sur les séquences.

4.6.4. Listes

Les listes sont des séquences muables, généralement utilisées pour stocker des collections d’éléments homogènes (où le degré de similitude variera selon l’usage).

class list([iterable])

Les listes peuvent être construites de différentes manières :

En utilisant une paire de crochets pour indiquer une liste vide : []

Au moyen de crochets, séparant les éléments par des virgules : [a], [a, b, c]

En utilisant une liste en compréhension : [x for x in iterable]

En utilisant le constructeur du type : list() ou list(iterable)

Le constructeur crée une liste dont les éléments sont les mêmes et dans le même ordre que les éléments d”iterable. iterable peut être soit une séquence, un conteneur qui supporte l’itération, soit un itérateur. Si iterable est déjà une liste, une copie est faite et renvoyée, comme avec iterable[:]. Par exemple, list('abc') renvoie ['a', 'b', 'c'] et list( (1, 2, 3) ) renvoie [1, 2, 3]. Si aucun argument est donné, le constructeur crée une nouvelle liste vide, [].

De nombreuses autres opérations produisent des listes, tel que la fonction native sorted().

Les listes supportent toutes les opérations des séquences communes et muables. Les listes fournissent également la méthode supplémentaire suivante :

sort(*, key=None, reverse=False)

Cette méthode trie la liste sur place, en utilisant uniquement des comparaisons < entre les éléments. Les exceptions ne sont pas supprimées si n’importe quelle opération de comparaison échoue, le tri échouera (et la liste sera probablement laissée dans un état partiellement modifié).

sort() accepte deux arguments qui ne peuvent être fournis que par mot-clé (keyword-only arguments):

key spécifie une fonction d’un argument utilisée pour extraire une clé de comparaison de chaque élément de la liste (par exemple, key=str.lower). La clé correspondant à chaque élément de la liste n’est calculée qu’une seule fois, puis utilisée durant tout le processus. La valeur par défaut, None, signifie que les éléments sont triés directement sans en calculer une valeur « clé » séparée.

La fonction utilitaire functools.cmp_to_key() est disponible pour convertir une fonction cmp du style 2.x à une fonction key.

reverse, une valeur booléenne. Si elle est True, la liste d’éléments est triée comme si toutes les comparaisons étaient inversées.

Cette méthode modifie la séquence sur place pour économiser de l’espace lors du tri de grandes séquences. Pour rappeler aux utilisateurs cet effet de bord, elle ne renvoie pas la séquence triée (utilisez sorted() pour demander explicitement une nouvelle instance de liste triée).

La méthode sort() est garantie stable. Un tri est stable s’il garantit de ne pas changer l’ordre relatif des éléments égaux — cela est utile pour trier en plusieurs passes (par exemple, trier par département, puis par niveau de salaire).

CPython implementation detail: L’effet de tenter de modifier, ou même inspecter la liste pendant qu’elle se fait trier est indéfini. L’implémentation C de Python fait apparaître la liste comme vide pour la durée du traitement, et lève ValueError si elle détecte que la liste a été modifiée au cours du tri.

4.6.5. Tuples

Les tuples (n-uplets en français) sont des séquences immuables, généralement utilisées pour stocker des collections de données hétérogènes (tels que les tuples de deux éléments produits par la fonction native enumerate()). Les tuples sont également utilisés dans des cas où une séquence homogène et immuable de données est nécessaire (pour, par exemple, les stocker dans un set ou un dict).

class tuple([iterable])

Les tuples peuvent être construits de différentes façons :

En utilisant une paire de parenthèses pour désigner le tuple vide : ()

En utilisant une virgule, pour créer un tuple d’un élément : a, ou (a,)

En séparant les éléments avec des virgules : a, b, c ou (a, b, c)

En utilisant la fonction native tuple() : tuple() ou tuple(iterable)

Le constructeur construit un tuple dont les éléments sont les mêmes et dans le même ordre que les éléments de iterable. iterable peut être soit une séquence, un conteneur qui supporte l’itération, soit un itérateur. Si iterable est déjà un tuple, il est renvoyé inchangé. Par exemple, tuple('abc') renvoie ('a', 'b', 'c') et tuple( [1, 2, 3] ) renvoie (1, 2, 3). Si aucun argument est donné, le constructeur crée un nouveau tuple vide, ().

Notez que c’est en fait la virgule qui fait un tuple et non les parenthèses. Les parenthèses sont facultatives, sauf dans le cas du tuple vide, ou lorsqu’elles sont nécessaires pour éviter l’ambiguïté syntaxique. Par exemple, f(a, b, c) est un appel de fonction avec trois arguments, alors que f((a, b, c)) est un appel de fonction avec un tuple de trois éléments comme unique argument.

Les tuples implémentent toutes les opérations communes des séquences.

Pour les collections hétérogènes de données où l’accès par nom est plus clair que l’accès par index, collections.namedtuple() peut être un choix plus approprié qu’un simple tuple.

4.6.6. Ranges

Le type range représente une séquence immuable de nombres et est couramment utilisé pour itérer un certain nombre de fois dans les boucles for.

class range(stop)

class range(start, stop[, step])

Les arguments du constructeur de range doivent être des entiers (des int ou tout autre objet qui implémente la méthode spéciale __index__). La valeur par défaut de l’argument step est 1. La valeur par défaut de l’argument start est 0. Si step est égal à zéro, une exception ValueError est levée.

Pour un step positif, le contenu d’un range r est déterminé par la formule r[i] = start + step*i où i >= 0 et r[i] < stop.

Pour un step négatif, le contenu du range est toujours déterminé par la formule r[i] = start + step*i, mais les contraintes sont i >= 0 et r[i] > stop.

Un objet range sera vide si r[0] ne répond pas à la contrainte de valeur. Les range prennent en charge les indices négatifs, mais ceux-ci sont interprétées comme une indexation de la fin de la séquence déterminée par les indices positifs.

Les range contenant des valeurs absolues plus grandes que sys.maxsize sont permises, mais certaines fonctionnalités (comme len()) peuvent lever OverflowError.

Exemples avec range :

>>> list(range(10))
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
>>> list(range(1, 11))
[1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
>>> list(range(0, 30, 5))
[0, 5, 10, 15, 20, 25]
>>> list(range(0, 10, 3))
[0, 3, 6, 9]
>>> list(range(0, -10, -1))
[0, -1, -2, -3, -4, -5, -6, -7, -8, -9]
>>> list(range(0))
[]
>>> list(range(1, 0))
[]

range implémente toutes les opérations communes des séquences sauf la concaténation et la répétition (en raison du fait que les range ne peuvent représenter que des séquences qui respectent un motif strict et que la répétition et la concaténation les feraient dévier de ce motif).

start

La valeur du paramètre start (ou 0 si le paramètre n’a pas été fourni)

stop

La valeur du paramètre stop

step

La valeur du paramètre step (ou 1 si le paramètre n’a pas été fourni)

L’avantage du type range sur une list classique ou tuple est qu’un objet range prendra toujours la même (petite) quantité de mémoire, peu importe la taille de la gamme qu’elle représente (car elle ne stocke que les valeurs start, stop et step , le calcul des éléments individuels et les sous-intervalles au besoin).

Les range implémentent la classe de base abstraite collections.abc.Sequence et offrent des fonctionnalités telles que les tests d’appartenance (avec in), de recherche par index, le tranchage et ils gèrent les indices négatifs (voir Types séquentiels — list, tuple, range):

>>> r = range(0, 20, 2)
>>> r
range(0, 20, 2)
>>> 11 in r
False
>>> 10 in r
True
>>> r.index(10)
5
>>> r[5]
10
>>> r[:5]
range(0, 10, 2)
>>> r[-1]
18

Comparer des range avec == et != les compare comme des séquences. Soit deux objets range sont considérées comme égaux si ils représentent la même séquence de valeurs. (Notez que deux objets range dits égaux pourraient avoir leurs attributs start, stop et step différents, par exemple range(0) == range(2, 1, 3) ou range(0, 3, 2) == range(0, 4, 2).)

Modifié dans la version 3.2: Implémente la classe de base abstraite Sequence. Supporte le slicing et les indices négatifs. Tester l’appartenance d’un int en temps constant au lieu d’itérer tous les éléments.

Modifié dans la version 3.3: == et != comparent des range en fonction de la séquence de valeurs qu’ils définissent (au lieu d’une comparaison fondée sur l’identité de l’objet).

Nouveau dans la version 3.3: Les attributs start, stop et step.

Voir aussi

The linspace recipe [http://code.activestate.com/recipes/579000/] shows how to implement a lazy version of range suitable for floating point applications.

4.7. Type Séquence de Texte — str

Les données textuelles en Python est manipulé avec des objets str ou strings. Les chaînes sont des séquences immuables de points de code Unicode. Les chaînes littérales peuvent être écrites de différentes manières :

Les guillemets simples : 'autorisent les "guillemets"'

Les guillemets : "autorisent les guillemets 'simples'".

Guillemets triples : '''Trois guillemets simples''', """Trois guillemets"""

Les chaînes entre triple guillemets peuvent couvrir plusieurs lignes, tous les espaces associés seront inclus dans la chaîne littérale.

Les chaînes littérales qui font partie d’une seule expression et ont seulement des espaces entre elles sont implicitement converties en une seule chaîne littérale. Autrement dit, ("spam " "eggs") == "spam eggs".

Voir Littéraux de chaînes de caractères et de suites d’octets pour plus d’informations sur les différentes formes de chaînes littérales, y compris des séquences d’échappement prises en charge, et le préfixe r (raw (brut)) qui désactive la plupart des traitements de séquence d’échappement.

Les chaînes peuvent également être créés à partir d’autres objets à l’aide du constructeur str.

Comme il n’y a pas de type « caractère » distinct, l’indexation d’une chaîne produit des chaînes de longueur 1. Autrement dit, pour une chaîne non vide s, s[0] == s[0:1].

Il n’y a aucun type de chaîne muable, mais str.join() ou io.StringIO peuvent être utilisées pour construire efficacement des chaînes à partir de plusieurs fragments.

Modifié dans la version 3.3: Pour une compatibilité ascendante avec la série Python 2, le préfixe u est à nouveau autorisé sur les chaînes littérales. Elle n’a aucun effet sur le sens des chaînes littérales et ne peut être combiné avec le préfixe r.

class str(object='')

class str(object=b'', encoding='utf-8', errors='strict')

Renvoie une représentation string de object. Si object n’est pas fourni, renvoie une chaîne vide. Sinon, le comportement de str() dépend de si encoding ou errors sont donnés, voir l’exemple.

Si ni encoding ni errors ne sont donnés, str(object) renvoie object.__str__(), qui est la représentation de chaîne « informelle » ou bien affichable de object. Pour les chaînes, c’est la chaîne elle-même. Si object n’a pas de méthode __str__(), str() utilise repr(object).

Si au moins un des deux arguments encoding ou errors est donné, object doit être un bytes-like object (par exemple bytes ou bytearray). Dans ce cas, si object est un objet bytes (ou bytearray), alors str(bytes, encoding, errors) est équivalent à bytes.decode(encoding, errors). Sinon, l’objet bytes du buffer est obtenu avant d’appeler bytes.decode(). Voir Séquences Binaires — bytes, bytearray, memoryview et Protocole tampon pour plus d’informations sur les buffers.

Donner un objet bytes à str() sans ni l’argument encoding ni l’argument errors relève du premier cas, où la représentation informelle de la chaîne est renvoyé (voir aussi l’option -b de Python). Par exemple :

>>> str(b'Zoot!')
"b'Zoot!'"

Pour plus d’informations sur la classe str et ses méthodes, voir les sections Type Séquence de Texte — str et Méthodes de chaînes de caractères. Pour formater des chaînes de caractères, voir les sections Chaînes de caractères formatées littérales et Syntaxe de formatage de chaîne. La section Services de Manipulation de Texte contient aussi des informations.

4.7.1. Méthodes de chaînes de caractères

Les chaînes implémentent toutes les opérations communes des séquences, ainsi que les autres méthodes décrites ci-dessous.

Les chaînes gèrent aussi deux styles de mise en forme, l’un fournissant une grande flexibilité et de personnalisation (voir str.format(), Syntaxe de formatage de chaîne et Formatage personnalisé de chaîne) et l’autre basée sur printf du C qui gère une gamme plus étroite des types et est légèrement plus difficile à utiliser correctement, mais il est souvent plus rapide pour les cas, il peut gérer (Formatage de chaines à la printf).

La section Services de Manipulation de Texte de la bibliothèque standard couvre un certain nombre d’autres modules qui fournissent différents services relatifs au texte (y compris les expressions régulières dans le module re).

str.capitalize()

Renvoie une copie de la chaîne avec son premier caractère en majuscule et le reste en minuscule.

str.casefold()

Renvoie une copie casefolded de la chaîne. Les chaînes casefolded peuvent être utilisées dans des comparaison insensibles à la casse.

Le casefolding est une technique agressive de mise en minuscule, car il vise à éliminer toutes les distinctions de casse dans une chaîne. Par exemple, la lettre minuscule 'ß' de l’allemand équivaut à "ss". Comme il est déjà minuscule, lower() ferait rien à 'ß'; casefold() le convertit en "ss".

L’algorithme de casefolding est décrit dans la section 3.13 de la norme Unicode.

Nouveau dans la version 3.3.

str.center(width[, fillchar])

Donne la chaîne au centre d’une chaîne de longueur width. Le remplissage est fait en utilisant l’argument fillchar (qui par défaut est un espace ASCII). La chaîne d’origine est renvoyée si width est inférieur ou égale à len(s).

str.count(sub[, start[, end]])

Donne le nombre d’occurrences de sub ne se chevauchant pas dans le range [start, end]. Les arguments facultatifs start et end sont interprétés comme pour des slices.

str.encode(encoding="utf-8", errors="strict")

Donne une version encodée de la chaîne sous la forme d’un objet bytes. L’encodage par défaut est 'utf-8'. errors peut être donné pour choisir un autre système de gestion d’erreur. La valeur par défaut pour errors est 'strict', ce qui signifie que les erreurs d’encodage lèvent une UnicodeError. Les autres valeurs possibles sont 'ignore', 'replace', 'xmlcharrefreplace', 'backslashreplace' et tout autre nom enregistré via codecs.register_error(), voir la section Gestionnaires d’erreurs. Pour une liste des encodages possibles, voir la section Standard Encodings.

Modifié dans la version 3.1: Gestion des arguments par mot clef.

str.endswith(suffix[, start[, end]])

Donne True si la chaîne se termine par suffix, sinon False. suffix peut aussi être un tuple de suffixes à rechercher. Si l’argument optionnel start est donné, le test se fait à partir de cette position. Si l’argument optionnel end est fourni, la comparaison s’arrête à cette position.

str.expandtabs(tabsize=8)

Donne une copie de la chaîne où toutes les tabulations sont remplacées par un ou plusieurs espaces, en fonction de la colonne courante et de la taille de tabulation donnée. Les positions des tabulations se trouvent tous les tabsize caractères (8 par défaut, ce qui donne les positions de tabulations aux colonnes 0, 8, 16 et ainsi de suite). Pour travailler sur la chaîne, la colonne en cours est mise à zéro et la chaîne est examinée caractère par caractère. Si le caractère est une tabulation (\t), un ou plusieurs caractères d’espacement sont insérés dans le résultat jusqu’à ce que la colonne courante soit égale à la position de tabulation suivante. (Le caractère tabulation lui-même n’est pas copié.) Si le caractère est un saut de ligne (\n) ou un retour chariot (\r), il est copié et la colonne en cours est remise à zéro. Tout autre caractère est copié inchangé et la colonne en cours est incrémentée de un indépendamment de la façon dont le caractère est représenté lors de l’affichage.

>>> '01\t012\t0123\t01234'.expandtabs()
'01      012     0123    01234'
>>> '01\t012\t0123\t01234'.expandtabs(4)
'01  012 0123    01234'

str.find(sub[, start[, end]])

Donne la première la position dans la chaîne où sub est trouvé dans le slice s[start:end]. Les arguments facultatifs start et end sont interprétés comme dans la notation des slice. Donne -1 si sub n’est pas trouvé.

Note

La méthode find() ne doit être utilisée que si vous avez besoin de connaître la position de sub. Pour vérifier si sub est une sous chaine ou non, utilisez l’opérateur in :

>>> 'Py' in 'Python'
True

str.format(*args, **kwargs)

Formate une chaîne. La chaîne sur laquelle cette méthode est appelée peut contenir du texte littéral ou des emplacements de remplacement délimités par des accolades {}. Chaque champ de remplacement contient soit l’indice numérique d’un argument positionnel, ou le nom d’un argument donné par mot-clé. Renvoie une copie de la chaîne où chaque champ de remplacement est remplacé par la valeur de chaîne de l’argument correspondant.

>>> "The sum of 1 + 2 is {0}".format(1+2)
'The sum of 1 + 2 is 3'

Voir Syntaxe de formatage de chaîne pour une description des options de formatage qui peuvent être spécifiées dans les chaînes de format.

Note

When formatting a number (int, float, complex, decimal.Decimal and subclasses) with the n type (ex: '{:n}'.format(1234)), the function temporarily sets the LC_CTYPE locale to the LC_NUMERIC locale to decode decimal_point and thousands_sep fields of localeconv() if they are non-ASCII or longer than 1 byte, and the LC_NUMERIC locale is different than the LC_CTYPE locale. This temporary change affects other threads.

Modifié dans la version 3.6.5: Lors du formatage d’un nombre avec le format n, la fonction change temporairement LC_CTYPE par la valeur de LC_NUMERIC dans certains cas.

str.format_map(mapping)

Semblable à str.format(**mapping), sauf que mapping est utilisé directement et non copié dans un dict. C’est utile si, par exemple mapping est une sous-classe de dict :

>>> class Default(dict):
...     def __missing__(self, key):
...         return key
...
>>> '{name} was born in {country}'.format_map(Default(name='Guido'))
'Guido was born in country'

Nouveau dans la version 3.2.

str.index(sub[, start[, end]])

Comme find(), mais lève une ValueError lorsque la chaîne est introuvable.

str.isalnum()

Donne True si tous les caractères de la chaîne sont alphanumériques et qu’il y a au moins un caractère, sinon False. Un caractère c est alphanumérique si l’un des tests suivants est vrais : c.isalpha(), c.isdecimal(), c.isdigit() ou c.isnumeric().

str.isalpha()

Donne True si tous les caractères de la chaîne sont alphabétiques et qu’elle contient au moins un caractère, sinon False. Les caractères alphabétiques sont les caractères définis dans la base de données de caractères Unicode comme Letter, à savoir, ceux qui ont « Lm », « Lt », « Lu », « Ll », ou « Lo » comme catégorie générale. Notez que ceci est différent de la propriété Alphabetic définie dans la norme Unicode.

str.isdecimal()

Renvoie vrai si tous les caractères de la chaîne sont des caractères décimaux et qu’elle contient au moins un caractère, sinon faux. Les caractères décimaux sont ceux pouvant être utilisés pour former des nombres en base 10, tels que U+0660, ARABIC-INDIC DIGIT ZERO. Spécifiquement, un caractère décimal est un caractère dans la catégorie Unicode générale « Nd ».

str.isdigit()

Renvoie vrai si tous les caractères de la chaîne sont des chiffres et qu’elle contient au moins un caractère, faux sinon. Les chiffres incluent des caractères décimaux et des chiffres qui nécessitent une manipulation particulière, tels que les compatibility superscript digits. Ça couvre les chiffres qui ne peuvent pas être utilisés pour construire des nombres en base 10, tel que les nombres de Kharosthi. Spécifiquement, un chiffre est un caractère dont la valeur de la propriété Numeric_Type est Digit ou Decimal.

str.isidentifier()

Donne True si la chaîne est un identifiant valide selon la définition du langage, section Identifiants et mots-clés.

Utilisez keyword.iskeyword() pour savoir si un identifiant est réservé, tels que def et class.

str.islower()

Donne True si tous les caractères capitalisables 4 de la chaîne sont en minuscules et qu’elle contient au moins un caractère capitalisable. Donne False dans le cas contraire.

str.isnumeric()

Donne True si tous les caractères de la chaîne sont des caractères numériques, et qu’elle contient au moins un caractère, sinon False. Les caractères numériques comprennent les chiffres, et tous les caractères qui ont la propriété Unicode numeric value, par exemple U+2155, VULGAR FRACTION OF FIFTH. Formellement, les caractères numériques sont ceux avec les priorités Numeric_Type=Digit, Numeric_Type=Decimal, ou Numeric_Type=Numeric.

str.isprintable()

Donne True si tous les caractères de la chaîne sont affichables ou qu’elle est vide sinon, False. Les caractères non affichables sont les caractères définis dans la base de données de caractères Unicode comme « Other » ou « Separator », à l’exception de l’espace ASCII (0x20) qui est considéré comme affichable. (Notez que les caractères imprimables dans ce contexte sont ceux qui ne devraient pas être protégés quand repr() est invoquée sur une chaîne. Ça n’a aucune incidence sur le traitement des chaînes écrites sur sys.stdout ou sys.stderr.)

str.isspace()

Donne True s’il n’y a que des caractères blancs dans la chaîne et il y a au moins un caractère, sinon False. Les caractères blancs sont les caractères définis dans la base de données de caractères Unicode comme « Other » ou « Separator » ainsi que ceux ayant la propriété bidirectionnelle valant « WS », « B » ou « S ».

str.istitle()

Donne True si la chaîne est une chaîne titlecased et qu’elle contient au moins un caractère, par exemple les caractères majuscules ne peuvent suivre les caractères non capitalisables et les caractères minuscules ne peuvent suivre que des caractères capitalisables. Donne False dans le cas contraire.

str.isupper()

Donne True si tous les caractères différentiables sur la casse 4 de la chaîne sont en majuscules et il y a au moins un caractère différentiable sur la casse, sinon False.

str.join(iterable)

Donne une chaîne qui est la concaténation des chaînes contenues dans iterable. Une TypeError sera levée si une valeur d”iterable n’est pas une chaîne, y compris pour les objets bytes. Le séparateur entre les éléments est la chaîne fournissant cette méthode.

str.ljust(width[, fillchar])

Renvoie la chaîne justifiée à gauche dans une chaîne de longueur width. Le rembourrage est fait en utilisant fillchar (qui par défaut est un espace ASCII). La chaîne d’origine est renvoyée si width est inférieur ou égale à len(s).

str.lower()

Renvoie une copie de la chaîne avec tous les caractères capitalisables 4 convertis en minuscules.

L’algorithme de mise en minuscules utilisé est décrit dans la section 3.13 de la norme Unicode.

str.lstrip([chars])

Renvoie une copie de la chaîne des caractères supprimés au début. L’argument chars est une chaîne spécifiant le jeu de caractères à supprimer. En cas d’omission ou None, la valeur par défaut de chars permet de supprimer des espaces. L’argument chars n’est pas un préfixe, toutes les combinaisons de ses valeurs sont supprimées :

>>> '   spacious   '.lstrip()
'spacious   '
>>> 'www.example.com'.lstrip('cmowz.')
'example.com'

static str.maketrans(x[, y[, z]])

Cette méthode statique renvoie une table de traduction utilisable pour str.translate().

Si un seul argument est fourni, ce soit être un dictionnaire faisant correspondre des points de code Unicode (nombres entiers) ou des caractères (chaînes de longueur 1) à des points de code Unicode.

Si deux arguments sont fournis, ce doit être deux chaînes de caractères de même longueur. Le dictionnaire renvoyé fera correspondre pour chaque caractère de x un caractère de y pris à la même place. Si un troisième argument est fourni, ce doit être une chaîne dont chaque caractère correspondra à None dans le résultat.

str.partition(sep)

Divise la chaîne à la première occurrence de sep, et donne un tuple de trois éléments contenant la partie avant le séparateur, le séparateur lui-même, et la partie après le séparateur. Si le séparateur n’est pas trouvé, le tuple contiendra la chaîne elle-même, suivie de deux chaînes vides.

str.replace(old, new[, count])

Renvoie une copie de la chaîne dont toutes les occurrences de la sous-chaîne old sont remplacés par new. Si l’argument optionnel count est donné, seules les count premières occurrences sont remplacées.

str.rfind(sub[, start[, end]])

Donne l’indice le plus élevé dans la chaîne où la sous-chaîne sub se trouve, de telle sorte que sub soit contenue dans s[start:end]. Les arguments facultatifs start et end sont interprétés comme dans la notation des slices. Donne -1 en cas d’échec.

str.rindex(sub[, start[, end]])

Comme rfind() mais lève une exception ValueError lorsque la sous-chaîne sub est introuvable.

str.rjust(width[, fillchar])

Renvoie la chaîne justifié à droite dans une chaîne de longueur width. Le rembourrage est fait en utilisant le caractère spécifié par fillchar (par défaut est un espace ASCII). La chaîne d’origine est renvoyée si width est inférieure ou égale à len(s).

str.rpartition(sep)

Divise la chaîne à la dernière occurrence de sep, et donne un tuple de trois éléments contenant la partie avant le séparateur, le séparateur lui-même, et la partie après le séparateur. Si le séparateur n’est pas trouvé, le tuple contiendra deux chaînes vides, puis par la chaîne elle-même.

str.rsplit(sep=None, maxsplit=-1)

Renvoie une liste des mots de la chaîne, en utilisant sep comme séparateur. Si maxsplit est donné, c’est le nombre maximum de divisions qui pourront être faites, celles « à droite ». Si sep est pas spécifié ou est None, tout espace est un séparateur. En dehors du fait qu’il découpe par la droite, rsplit() se comporte comme split() qui est décrit en détail ci-dessous.

str.rstrip([chars])

Renvoie une copie de la chaîne avec des caractères finaux supprimés. L’argument chars est une chaîne spécifiant le jeu de caractères à supprimer. En cas d’omission ou None, les espaces sont supprimés. L’argument chars n’est pas un suffixe : toutes les combinaisons de ses valeurs sont retirées :

>>> '   spacious   '.rstrip()
'   spacious'
>>> 'mississippi'.rstrip('ipz')
'mississ'

str.split(sep=None, maxsplit=-1)

Renvoie une liste des mots de la chaîne, en utilisant sep comme séparateur de mots. Si maxsplit est donné, c’est le nombre maximum de divisions qui pourront être effectuées, (donnant ainsi une liste de longueur maxsplit+1). Si maxsplit n’est pas fourni, ou vaut -1, le nombre de découpes n’est pas limité (Toutes les découpes possibles sont faites).

Si sep est donné, les délimiteurs consécutifs ne sont pas regroupés et ainsi délimitent des chaînes vides (par exemple, '1,,2'.split(',') donne ['1', '', '2']). L’argument sep peut contenir plusieurs caractères (par exemple, '1<>2<>3'.split('<>') renvoie ['1', '2', '3']). Découper une chaîne vide en spécifiant sep donne [''].

Par exemple :

>>> '1,2,3'.split(',')
['1', '2', '3']
>>> '1,2,3'.split(',', maxsplit=1)
['1', '2,3']
>>> '1,2,,3,'.split(',')
['1', '2', '', '3', '']

Si sep n’est pas spécifié ou est None, un autre algorithme de découpage est appliqué : les espaces consécutifs sont considérés comme un seul séparateur, et le résultat ne contiendra pas les chaînes vides de début ou de la fin si la chaîne est préfixée ou suffixé d’espaces. Par conséquent, diviser une chaîne vide ou une chaîne composée d’espaces avec un séparateur None renvoie [].

Par exemple :

>>> '1 2 3'.split()
['1', '2', '3']
>>> '1 2 3'.split(maxsplit=1)
['1', '2 3']
>>> '   1   2   3   '.split()
['1', '2', '3']

str.splitlines([keepends])

Renvoie les lignes de la chaîne sous forme de liste, la découpe se fait au niveau des limites des lignes. Les sauts de ligne ne sont pas inclus dans la liste des résultats, sauf si keepends est donné, et est vrai.

Cette méthode découpe sur les limites de ligne suivantes. Ces limites sont un sur ensemble de universal newlines.

Représentation

Description

\n

Saut de ligne

\r

Retour chariot

\r\n

Retour chariot + saut de ligne

\v or \x0b

Tabulation verticale

\f or \x0c

Saut de page

\x1c

Séparateur de fichiers

\x1d

Séparateur de groupes

\x1e

Séparateur d’enregistrements

\x85

Ligne suivante (code de contrôle C1)

\u2028

Séparateur de ligne

\u2029

Séparateur de paragraphe

Modifié dans la version 3.2: \v et \f ajoutés à la liste des limites de lignes.

Par exemple :

>>> 'ab c\n\nde fg\rkl\r\n'.splitlines()
['ab c', '', 'de fg', 'kl']
>>> 'ab c\n\nde fg\rkl\r\n'.splitlines(keepends=True)
['ab c\n', '\n', 'de fg\r', 'kl\r\n']

Contrairement à split() lorsque sep est fourni, cette méthode renvoie une liste vide pour la chaîne vide, et un saut de ligne à la fin ne se traduit pas par une ligne supplémentaire :

>>> "".splitlines()
[]
>>> "One line\n".splitlines()
['One line']

À titre de comparaison, split('\n') donne :

>>> ''.split('\n')
['']
>>> 'Two lines\n'.split('\n')
['Two lines', '']

str.startswith(prefix[, start[, end]])

Donne True si la chaîne commence par prefix, sinon False. prefix peut aussi être un tuple de préfixes à rechercher. Lorsque start est donné, la comparaison commence à cette position, et lorsque end est donné, la comparaison s’arrête à celle ci.

str.strip([chars])

Donne une copie de la chaîne dont des caractères initiaux et finaux sont supprimés. L’argument chars est une chaîne spécifiant le jeu de caractères à supprimer. En cas d’omission ou None, les espaces sont supprimés. L’argument chars est pas un préfixe ni un suffixe, toutes les combinaisons de ses valeurs sont supprimées :

>>> '   spacious   '.strip()
'spacious'
>>> 'www.example.com'.strip('cmowz.')
'example'

Les caractères de char sont retirés du début et de la fin de la chaîne. Les caractères sont retirés de la gauche jusqu’à atteindre un caractère ne figurant pas dans le jeu de caractères dans chars. La même opération à lieu par la droite. Par exemple :

>>> comment_string = '#....... Section 3.2.1 Issue #32 .......'
>>> comment_string.strip('.#! ')
'Section 3.2.1 Issue #32'

str.swapcase()

Renvoie une copie de la chaîne dont les caractères majuscules sont convertis en minuscules et vice versa. Notez qu’il est pas nécessairement vrai que s.swapcase().swapcase() == s.

str.title()

Renvoie une version en initiales majuscules de la chaîne où les mots commencent par une capitale et les caractères restants sont en minuscules.

Par exemple :

>>> 'Hello world'.title()
'Hello World'

Pour l’algorithme, la notion de mot est définie simplement et indépendamment de la langue comme un groupe de lettres consécutives. La définition fonctionne dans de nombreux contextes, mais cela signifie que les apostrophes (typiquement de la forme possessive en Anglais) forment les limites de mot, ce qui n’est pas toujours le résultat souhaité :

>>> "they're bill's friends from the UK".title()
"They'Re Bill'S Friends From The Uk"

Une solution pour contourner le problème des apostrophes peut être obtenue en utilisant des expressions rationnelles :

>>> import re
>>> def titlecase(s):
...     return re.sub(r"[A-Za-z]+('[A-Za-z]+)?",
...                   lambda mo: mo.group(0)[0].upper() +
...                              mo.group(0)[1:].lower(),
...                   s)
...
>>> titlecase("they're bill's friends.")
"They're Bill's Friends."

str.translate(table)

Renvoie une copie de la chaîne dans laquelle chaque caractère a été changé selon la table de traduction donnée. La table doit être un objet qui implémente l’indexation via __getitem__(), typiquement un mapping ou une sequence. Pour un ordinal Unicode (un entier), la table peut donner soit un ordinal Unicode ou une chaîne pour faire correspondre un ou plusieurs caractère au caractère donné, soit None pour supprimer le caractère de la chaîne de renvoyée soit lever une exception LookupError pour ne pas changer le caractère.

Vous pouvez utiliser str.maketrans() pour créer une table de correspondances de caractères dans différents formats.

Voir aussi le module codecs pour une approche plus souple de changements de caractères par correspondance.

str.upper()

Return a copy of the string with all the cased characters 4 converted to uppercase. Note that s.upper().isupper() might be False if s contains uncased characters or if the Unicode category of the resulting character(s) is not « Lu » (Letter, uppercase), but e.g. « Lt » (Letter, titlecase).

L’algorithme de capitalisation utilisé est décrit dans la section 3.13 de la norme Unicode.

str.zfill(width)

Renvoie une copie de la chaîne remplie par la gauche du chiffre (le caractère ASCII) '0' pour faire une chaîne de longueur width. Un préfixe ('+' / '-') est permis par l’insertion du caractère de rembourrage après le caractère désigne plutôt qu’avant. La chaîne d’origine est renvoyée si width est inférieur ou égale à len(s).

Par exemple :

>>> "42".zfill(5)
'00042'
>>> "-42".zfill(5)
'-0042'

4.7.2. Formatage de chaines à la printf

Note

Ces opérations de mise en forme contiennent des bizarreries menant à de nombreuses erreurs classiques (tel que ne pas réussir à afficher des tuples ou des dictionnaires correctement). Utiliser les formatted string literals ou la méthode str.format() aide à éviter ces erreurs. Ces alternatives offrent aussi une approche plus puissante, flexible, et extensible de la mise en forme.

Les objets str n’exposent qu’une opération : L’opérateur % (modulo). Aussi connu sous le nom d’opérateur de formatage, ou opérateur d’interpolation. Étant donné format % values (où format est une chaîne), les marqueurs % de format sont remplacés par zéro ou plusieurs éléments de values. L’effet est similaire à la fonction sprintf() du langage C.

Si format ne nécessite qu’un seul argument, values peut être un objet unique. 5 Si values est un tuple, il doit contenir exactement le nombre d’éléments spécifiés par la chaîne de format, ou un seul objet de correspondances ( mapping object, par exemple, un dictionnaire).

Un indicateur de conversion contient deux ou plusieurs caractères et comporte les éléments suivants, qui doivent apparaître dans cet ordre :

Le caractère '%', qui marque le début du marqueur.

La clé de correspondance (facultative), composée d’une suite de caractères entre parenthèse (par exemple, (somename)).

Des options de conversion, facultatives, qui affectent le résultat de certains types de conversion.

Largeur minimum (facultative). Si elle vaut '*' (astérisque), la largeur est lue de l’élément suivant du tuple values, et l’objet à convertir vient après la largeur de champ minimale et la précision facultative.

Précision (facultatif), donnée sous la forme d’un '.' (point) suivi de la précision. Si la précision est '*' (un astérisque), la précision est lue à partir de l’élément suivant du tuple values et la valeur à convertir vient ensuite.

Modificateur de longueur (facultatif).

Type de conversion.

Lorsque l’argument de droite est un dictionnaire (ou un autre type de mapping), les marqueurs dans la chaîne doivent inclure une clé présente dans le dictionnaire, écrite entre parenthèses, immédiatement après le caractère '%'. La clé indique quelle valeur du dictionnaire doit être formatée. Par exemple :

>>> print('%(language)s has %(number)03d quote types.' %
...       {'language': "Python", "number": 2})
Python has 002 quote types.

Dans ce cas, aucune * ne peuvent se trouver dans le format (car ces * nécessitent une liste (accès séquentiel) de paramètres).

Les caractères indicateurs de conversion sont :

Option

Signification

'#'

La conversion utilisera la « forme alternative » (définie ci-dessous).

'0'

Les valeurs numériques converties seront complétée de zéros.

'-'

La valeur convertie est ajustée à gauche (remplace la conversion '0' si les deux sont données).

' '

(un espace) Un espace doit être laissé avant un nombre positif (ou chaîne vide) produite par la conversion d’une valeur signée.

'+'

Un caractère de signe ('+' ou '-') précède la valeur convertie (remplace le marqueur « espace »).

Un modificateur de longueur (h, l ou L) peut être présent, mais est ignoré car il est pas nécessaire pour Python, donc par exemple %ld est identique à %d.

Les types utilisables dans les conversion sont :

Conversion

Signification

Notes

'd'

Entier décimal signé.

'i'

Entier décimal signé.

'o'

Valeur octale signée.

(1)

'u'

Type obsolète — identique à 'd'.

(6)

'x'

Hexadécimal signé (en minuscules).

(2)

'X'

Hexadécimal signé (capitales).

(2)

'e'

Format exponentiel pour un float (minuscule).

(3)

'E'

Format exponentiel pour un float (en capitales).

(3)

'f'

Format décimal pour un float.

(3)

'F'

Format décimal pour un float.

(3)

'g'

Format float. Utilise le format exponentiel minuscules si l’exposant est inférieur à -4 ou pas plus petit que la précision, sinon le format décimal.

(4)

'G'

Format float. Utilise le format exponentiel en capitales si l’exposant est inférieur à -4 ou pas plus petit que la précision, sinon le format décimal.

(4)

'c'

Un seul caractère (accepte des entiers ou une chaîne d’un seul caractère).

'r'

String (convertit n’importe quel objet Python avec repr()).

(5)

's'

String (convertit n’importe quel objet Python avec str()).

(5)

'a'

String (convertit n’importe quel objet Python en utilisant ascii()).

(5)

'%'

Aucun argument n’est converti, donne un caractère de '%' dans le résultat.

Notes :

La forme alternative entraîne l’insertion d’un préfixe octal ('0o') avant le premier chiffre.

La forme alternative entraîne l’insertion d’un préfixe '0x' ou '0X' (respectivement pour les formats 'x' et 'X') avant le premier chiffre.

La forme alternative implique la présence d’un point décimal, même si aucun chiffre ne le suit.

La précision détermine le nombre de chiffres après la virgule, 6 par défaut.

La forme alternative implique la présence d’un point décimal et les zéros non significatifs sont conservés (ils ne le seraient pas autrement).

La précision détermine le nombre de chiffres significatifs avant et après la virgule. 6 par défaut.

Si la précision est N, la sortie est tronquée à N caractères.

Voir la PEP 237 [https://www.python.org/dev/peps/pep-0237].

Puisque les chaînes Python ont une longueur explicite, les conversions %s ne considèrent pas '\0' comme la fin de la chaîne.

Modifié dans la version 3.1: Les conversions %f pour nombres dont la valeur absolue est supérieure à 1e50 ne sont plus remplacés par des conversions %g.

4.8. Séquences Binaires — bytes, bytearray, memoryview

Les principaux types natifs pour manipuler des données binaires sont bytes et bytearray. Ils sont supportés par memoryview qui utilise le buffer protocol pour accéder à la mémoire d’autres objets binaires sans avoir besoin d’en faire une copie.

Le module array permet le stockage efficace de types basiques comme les entiers de 32 bits et les float double précision IEEE754.

4.8.1. Objets bytes

Les bytes sont des séquences immuables d’octets. Comme beaucoup de protocoles binaires utilisent l’ASCII, les objets bytes offrent plusieurs méthodes qui ne sont valables que lors de la manipulation de données ASCII et sont étroitement liés aux objets str dans bien d’autres aspects.

class bytes([source[, encoding[, errors]]])

Tout d’abord, la syntaxe des bytes littéraux est en grande partie la même que pour les chaînes littérales, en dehors du préfixe b :

Les guillemets simples : b'autorisent aussi les guillemets "doubles"'

Les guillemets doubles : b"permettent aussi les guillemets 'simples'".

Les guillemets triples : b'''3 single quotes''', b"""3 double quotes"""

Seuls les caractères ASCII sont autorisés dans les littéraux de bytes (quel que soit l’encodage du code source déclaré). Toutes les valeurs au delà de 127 doivent être entrés dans littéraux de bytes en utilisant une séquence d’échappement appropriée.

Comme avec les chaînes littérales, les bytes littéraux peuvent également utiliser un préfixe r pour désactiver le traitement des séquences d’échappement. Voir Littéraux de chaînes de caractères et de suites d’octets pour plus d’informations sur les différentes formes littérales de bytes, y compris les séquences d’échappement supportées.

While bytes literals and representations are based on ASCII text, bytes objects actually behave like immutable sequences of integers, with each value in the sequence restricted such that 0 <= x < 256 (attempts to violate this restriction will trigger ValueError). This is done deliberately to emphasise that while many binary formats include ASCII based elements and can be usefully manipulated with some text-oriented algorithms, this is not generally the case for arbitrary binary data (blindly applying text processing algorithms to binary data formats that are not ASCII compatible will usually lead to data corruption).

En plus des formes littérales, des objets bytes peuvent être créés par de nombreux moyens :

Un objet bytes rempli de zéros d’une longueur spécifiée : bytes(10)

D’un itérable d’entiers : bytes(range(20))

Copier des données binaires existantes via le buffer protocol : bytes(obj)

Voir aussi la fonction native bytes.

Puisque 2 chiffres hexadécimaux correspondent précisément à un seul octet, les nombres hexadécimaux sont un format couramment utilisé pour décrire les données binaires. Par conséquent, le type bytes a une méthode de classe pour lire des données dans ce format :

classmethod fromhex(string)

Cette méthode de la classe bytes renvoie un objet bytes, décodant la chaîne donnée. La chaîne doit contenir deux chiffres hexadécimaux par octet, les espaces ASCII sont ignorés.

>>> bytes.fromhex('2Ef0 F1f2  ')
b'.\xf0\xf1\xf2'

Une fonction de conversion inverse existe pour transformer un objet bytes en sa représentation hexadécimale.

hex()

Renvoie une chaîne contenant deux chiffres hexadécimaux pour chaque octet du byte.

>>> b'\xf0\xf1\xf2'.hex()
'f0f1f2'

Nouveau dans la version 3.5.

Comme les objets bytes sont des séquences d’entiers (semblables à un tuple), pour une instance de bytes b, b[0] sera un entier, tandis que``b[0:1]`` sera un objet bytes de longueur 1. (Cela contraste avec les chaînes, où l’indexation et le slicing donne une chaîne de longueur 1)

La représentation des bytes utilise le format littéral (b'...') car il est souvent plus utile que par exemple bytes([46, 46, 46]). Vous pouvez toujours convertir un bytes en liste d’entiers en utilisant list(b).

Note

Pour les utilisateurs de Python 2.x : Dans la série 2.x de Python, une variété de conversions implicites entre les chaînes 8-bit (la chose la plus proche d’un type natif de données binaires offert par Python 2) et des chaînes Unicode étaient permises. C’était une solution de contournement, pour garder la rétro-compatibilité, considérant que Python ne prenait initialement en charge que le texte 8 bits, le texte Unicode est un ajout ultérieur. En Python 3.x, ces conversions implicites ont disparues, les conversions entre les données binaires et texte Unicode doivent être explicites, et les bytes sont toujours différents des chaînes.

4.8.2. Objets bytearray

Les objets bytearray sont l’équivalent muable des objets bytes.

class bytearray([source[, encoding[, errors]]])

Il n’y a pas de syntaxe littérale dédiée aux bytearray, ils sont toujours créés en appelant le constructeur :

Créer une instance vide: bytearray()

Créer une instance remplie de zéros d’une longueur donnée : bytearray(10)

À partir d’un itérable d’entiers : bytearray(range(20))

Copie des données binaires existantes via le buffer protocol : bytearray(b'Hi!')

Comme les bytearray sont muables, ils prennent en charge les opérations de séquence muables en plus des opérations communes de bytes et bytearray décrites dans Opérations sur les bytes et bytearray.

Voir aussi la fonction native bytearray.

Puisque 2 chiffres hexadécimaux correspondent précisément à un octet, les nombres hexadécimaux sont un format couramment utilisé pour décrire les données binaires. Par conséquent, le type bytearray a une méthode de classe pour lire les données dans ce format :

classmethod fromhex(string)

Cette méthode de la classe bytearray renvoie un objet bytearray, décodant la chaîne donnée. La chaîne doit contenir deux chiffres hexadécimaux par octet, les espaces ASCII sont ignorés.

>>> bytearray.fromhex('2Ef0 F1f2  ')
bytearray(b'.\xf0\xf1\xf2')

Une fonction de conversion inverse existe pour transformer un objet bytearray en sa représentation hexadécimale.

hex()

Renvoie une chaîne contenant deux chiffres hexadécimaux pour chaque octet du byte.

>>> bytearray(b'\xf0\xf1\xf2').hex()
'f0f1f2'

Nouveau dans la version 3.5.

Comme les bytearray sont des séquences d’entiers (semblables à une liste), pour un objet bytearray b, b[0] sera un entier, tandis que b[0:1] sera un objet bytearray de longueur 1. (Ceci contraste avec les chaînes de texte, où l’indexation et le slicing produit une chaîne de longueur 1)

La représentation des objets bytearray utilise le format littéral des bytes (bytearray(b'...')) car il est souvent plus utile que par exemple bytearray([46, 46, 46]). Vous pouvez toujours convertir un objet bytearray en une liste de nombres entiers en utilisant list(b).

4.8.3. Opérations sur les bytes et bytearray

bytes et bytearray prennent en charge les opérations communes des séquences. Ils interagissent non seulement avec des opérandes de même type, mais aussi avec les bytes-like object. En raison de cette flexibilité, ils peuvent être mélangés librement dans des opérations sans provoquer d’erreurs. Cependant, le type du résultat peut dépendre de l’ordre des opérandes.

Note

Les méthodes sur les bytes et les bytearray n’acceptent pas les chaînes comme arguments, tout comme les méthodes sur les chaînes n’acceptent pas les bytes comme arguments. Par exemple, vous devez écrire :

a = "abc"
b = a.replace("a", "f")

et :

a = b"abc"
b = a.replace(b"a", b"f")

Quelques opérations de bytes et bytesarray supposent l’utilisation de formats binaires compatibles ASCII, et donc doivent être évités lorsque vous travaillez avec des données binaires arbitraires. Ces restrictions sont couvertes ci-dessous.

Note

Utiliser ces opérations basées sur l’ASCII pour manipuler des données binaires qui ne sont pas au format ASCII peut les corrompre.

Les méthodes suivantes sur les bytes et bytearray peuvent être utilisées avec des données binaires arbitraires.

bytes.count(sub[, start[, end]])

bytearray.count(sub[, start[, end]])

Renvoie le nombre d’occurrences qui ne se chevauchent pas de la sous-séquence sub dans l’intervalle [start, end]. Les arguments facultatifs start et end sont interprétés comme pour un slice.

La sous-séquence à rechercher peut être un quelconque bytes-like object ou un nombre entier compris entre 0 et 255.

Modifié dans la version 3.3: Accepte aussi un nombre entier compris entre 0 et 255 comme sous-séquence.

bytes.decode(encoding="utf-8", errors="strict")

bytearray.decode(encoding="utf-8", errors="strict")

Décode les octets donnés, et le renvoie sous forme d’une chaîne de caractères. L’encodage par défaut est 'utf-8'. errors peut être donné pour changer de système de gestion des erreurs. Sa valeur par défaut est 'strict', ce qui signifie que les erreurs d’encodage lèvent une UnicodeError. Les autres valeurs possibles sont 'ignore', 'replace' et tout autre nom enregistré via codecs.register_error(), voir la section Gestionnaires d’erreurs. Pour une liste des encodages possibles, voir la section Standard Encodings.

Note

Passer l’argument encoding à str permet de décoder tout bytes-like object directement, sans avoir besoin d’utiliser un bytes ou bytearray temporaire.

Modifié dans la version 3.1: Gère les arguments nommés.

bytes.endswith(suffix[, start[, end]])

bytearray.endswith(suffix[, start[, end]])

Donne True si les octets se terminent par suffix, sinon False. suffix peut aussi être un tuple de suffixes à rechercher. Avec l’argument optionnel start, la recherche se fait à partir de cette position. Avec l’argument optionnel end, la comparaison s’arrête à cette position.

Les suffixes à rechercher peuvent être n’importe quel bytes-like object.

bytes.find(sub[, start[, end]])

bytearray.find(sub[, start[, end]])

Donne la première position où le sub se trouve dans les données, de telle sorte que sub soit contenue dans s[start:end]. Les arguments facultatifs start et end sont interprétés comme dans la notation des slices. Donne -1 si sub n’est pas trouvé.

La sous-séquence à rechercher peut être un quelconque bytes-like object ou un nombre entier compris entre 0 et 255.

Note

La méthode find() ne doit être utilisée que si vous avez besoin de connaître la position de sub. Pour vérifier si sub est présent ou non, utilisez l’opérateur in :

>>> b'Py' in b'Python'
True

Modifié dans la version 3.3: Accepte aussi un nombre entier compris entre 0 et 255 comme sous-séquence.

bytes.index(sub[, start[, end]])

bytearray.index(sub[, start[, end]])

Comme find(), mais lève une ValueError lorsque la séquence est introuvable.

La sous-séquence à rechercher peut être un quelconque bytes-like object ou un nombre entier compris entre 0 et 255.

Modifié dans la version 3.3: Accepte aussi un nombre entier compris entre 0 et 255 comme sous-séquence.

bytes.join(iterable)

bytearray.join(iterable)

Donne un bytes ou bytearray qui est la concaténation des séquences de données binaires dans iterable. Une exception TypeError est levée si une valeur d”iterable n’est pas un bytes-like objects, y compris pour des str. Le séparateur entre les éléments est le contenu du bytes ou du bytearray depuis lequel cette méthode est appelée.

static bytes.maketrans(from, to)

static bytearray.maketrans(from, to)

Cette méthode statique renvoie une table de traduction utilisable par bytes.translate() qui permettra de changer chaque caractère de from par un caractère à la même position dans to; from et to doivent tous deux être des bytes-like objects et avoir la même longueur.

Nouveau dans la version 3.1.

bytes.partition(sep)

bytearray.partition(sep)

Divise la séquence à la première occurrence de sep, et renvoie un 3-tuple contenant la partie précédant le séparateur, le séparateur lui même (ou sa copie en byterray), et la partie suivant le séparateur. Si le séparateur est pas trouvé, le 3-tuple renvoyé contiendra une copie de la séquence d’origine, suivi de deux bytes ou bytearray vides.

Le séparateur à rechercher peut être tout bytes-like object.

bytes.replace(old, new[, count])

bytearray.replace(old, new[, count])

Renvoie une copie de la séquence dont toutes les occurrences de la sous-séquence old sont remplacées par new. Si l’argument optionnel count est donné, seules les count premières occurrences de sont remplacés.

La sous-séquence à rechercher et son remplacement peuvent être n’importe quel bytes-like object.

Note

La version bytearray de cette méthode ne modifie pas les octets, elle produit toujours un nouvel objet, même si aucune modification n’a été effectuée.

bytes.rfind(sub[, start[, end]])

bytearray.rfind(sub[, start[, end]])

Donne la plus grande position de sub dans la séquence, de telle sorte que sub soit dans s[start:end]. Les arguments facultatifs start et end sont interprétés comme dans la notation des slices. Donne -1 si sub n’est pas trouvable.

La sous-séquence à rechercher peut être un quelconque bytes-like object ou un nombre entier compris entre 0 et 255.

Modifié dans la version 3.3: Accepte aussi un nombre entier compris entre 0 et 255 comme sous-séquence.

bytes.rindex(sub[, start[, end]])

bytearray.rindex(sub[, start[, end]])

Semblable à rfind() mais lève une ValueError lorsque sub est introuvable.

La sous-séquence à rechercher peut être un quelconque bytes-like object ou un nombre entier compris entre 0 et 255.

Modifié dans la version 3.3: Accepte aussi un nombre entier compris entre 0 et 255 comme sous-séquence.

bytes.rpartition(sep)

bytearray.rpartition(sep)

Coupe la séquence à la dernière occurrence de sep, et renvoie un tuple de trois éléments contenant la partie précédent le séparateur, le séparateur lui même (ou sa copie, un bytearray), et la partie suivant le séparateur. Si le séparateur n’est pas trouvé, le tuple contiendra une copie de la séquence d’origine, suivi de deux bytes ou bytesarray vides.

Le séparateur à rechercher peut être tout bytes-like object.

bytes.startswith(prefix[, start[, end]])

bytearray.startswith(prefix[, start[, end]])

Donne True si les données binaires commencent par le prefix spécifié, sinon False. prefix peut aussi être un tuple de préfixes à rechercher. Avec l’argument start la recherche commence à cette position. Avec l’argument end option, la recherche s’arrête à cette position.

Le préfixe(s) à rechercher peuvent être n’importe quel bytes-like object.

bytes.translate(table, delete=b'')

bytearray.translate(table, delete=b'')

Renvoie une copie du bytes ou bytearray dont tous les octets de delete sont supprimés, et les octets restants changés par la table de correspondance donnée, qui doit être un objet bytes d’une longueur de 256.

Vous pouvez utiliser la méthode bytes.maketrans() pour créer une table de correspondance.

Donnez None comme table pour seulement supprimer des caractères :

>>> b'read this short text'.translate(None, b'aeiou')
b'rd ths shrt txt'

Modifié dans la version 3.6: delete est maintenant accepté comme argument nommé.

Les méthodes suivantes sur les bytes et bytearray supposent par défaut que les données traitées sont compatibles ASCII, mais peuvent toujours être utilisées avec des données binaires, arbitraires, en passant des arguments appropriés. Notez que toutes les méthodes de bytearray de cette section ne travaillent jamais sur l’objet lui même, mais renvoient un nouvel objet.

bytes.center(width[, fillbyte])

bytearray.center(width[, fillbyte])

Renvoie une copie de l’objet centrée dans une séquence de longueur width. Le remplissage est fait en utilisant fillbyte (qui par défaut est un espace ASCII). Pour les objets bytes, la séquence initiale est renvoyée si width est inférieur ou égal à len(s).

Note

La version bytearray de cette méthode ne modifie pas les octets, elle produit toujours un nouvel objet, même si aucune modification n’a été effectuée.

bytes.ljust(width[, fillbyte])

bytearray.ljust(width[, fillbyte])

Renvoie une copie de l’objet aligné à gauche dans une séquence de longueur width. Le remplissage est fait en utilisant fillbyte (par défaut un espace ASCII). Pour les objets bytes, la séquence initiale est renvoyée si width est inférieure ou égale à len(s).

Note

La version bytearray de cette méthode ne modifie pas les octets, elle produit toujours un nouvel objet, même si aucune modification n’a été effectuée.

bytes.lstrip([chars])

bytearray.lstrip([chars])

Renvoie une copie de la séquence dont certains préfixes ont été supprimés. L’argument chars est une séquence binaire spécifiant le jeu d’octets à supprimer. Ce nom se réfère au fait de cette méthode est généralement utilisée avec des caractères ASCII. En cas d’omission ou None, la valeur par défaut de chars permet de supprimer des espaces ASCII. L’argument chars n’est pas un préfixe, toutes les combinaisons de ses valeurs sont supprimées :

>>> b'   spacious   '.lstrip()
b'spacious   '
>>> b'www.example.com'.lstrip(b'cmowz.')
b'example.com'

La séquence de valeurs à supprimer peut être tout bytes-like object.

Note

La version bytearray de cette méthode ne modifie pas les octets, elle produit toujours un nouvel objet, même si aucune modification n’a été effectuée.

bytes.rjust(width[, fillbyte])

bytearray.rjust(width[, fillbyte])

Renvoie une copie de l’objet justifié à droite dans une séquence de longueur width. Le remplissage est fait en utilisant le caractère fillbyte (par défaut est un espace ASCII). Pour les objets bytes, la séquence d’origine est renvoyée si width est inférieure ou égale à len(s).

Note

La version bytearray de cette méthode ne modifie pas les octets, elle produit toujours un nouvel objet, même si aucune modification n’a été effectuée.

bytes.rsplit(sep=None, maxsplit=-1)

bytearray.rsplit(sep=None, maxsplit=-1)

Divise la séquence d’octets en sous-séquences du même type, en utilisant sep comme séparateur. Si maxsplit est donné, c’est le nombre maximum de divisions qui pourront être faites, celles « à droite ». Si sep est pas spécifié ou est None, toute sous-séquence composée uniquement d’espaces ASCII est un séparateur. En dehors du fait qu’il découpe par la droite, rsplit() se comporte comme split() qui est décrit en détail ci-dessous.

bytes.rstrip([chars])

bytearray.rstrip([chars])

Renvoie une copie de la séquence dont des octets finaux sont supprimés. L’argument chars est une séquence d’octets spécifiant le jeu de caractères à supprimer. En cas d’omission ou None, les espaces ASCII sont supprimés. L’argument chars n’est pas un suffixe : toutes les combinaisons de ses valeurs sont retirées :

>>> b'   spacious   '.rstrip()
b'   spacious'
>>> b'mississippi'.rstrip(b'ipz')
b'mississ'

La séquence de valeurs à supprimer peut être tout bytes-like object.

Note

La version bytearray de cette méthode ne modifie pas les octets, elle produit toujours un nouvel objet, même si aucune modification n’a été effectuée.

bytes.split(sep=None, maxsplit=-1)

bytearray.split(sep=None, maxsplit=-1)

Divise la séquence en sous-séquences du même type, en utilisant sep comme séparateur. Si maxsplit est donné, c’est le nombre maximum de divisions qui pourront être faites (la liste aura donc au plus maxsplit+1 éléments), Si maxsplit n’est pas spécifié ou faut -1, il n’y a aucune limite au nombre de découpes (elles sont toutes effectuées).

Si sep est donné, les délimiteurs consécutifs ne sont pas regroupés et ainsi délimitent ainsi des chaînes vides (par exemple, b'1,,2'.split(b',') donne [b'1', b'', b'2']). L’argument sep peut contenir plusieurs sous séquences (par exemple, b'1<>2<>3'.split(b'<>') renvoie [b'1', b'2', b'3']). Découper une chaîne vide en spécifiant sep donne [b''] ou [bytearray(b'')] en fonction du type de l’objet découpé. L’argument sep peut être n’importe quel bytes-like object.

Par exemple :

>>> b'1,2,3'.split(b',')
[b'1', b'2', b'3']
>>> b'1,2,3'.split(b',', maxsplit=1)
[b'1', b'2,3']
>>> b'1,2,,3,'.split(b',')
[b'1', b'2', b'', b'3', b'']

Si sep n’est pas spécifié ou est None, un autre algorithme de découpe est appliqué : les espaces ASCII consécutifs sont considérés comme un seul séparateur, et le résultat ne contiendra pas les chaînes vides de début ou de la fin si la chaîne est préfixée ou suffixé d’espaces. Par conséquent, diviser une séquence vide ou une séquence composée d’espaces ASCII avec un séparateur None renvoie [].

Par exemple :

>>> b'1 2 3'.split()
[b'1', b'2', b'3']
>>> b'1 2 3'.split(maxsplit=1)
[b'1', b'2 3']
>>> b'   1   2   3   '.split()
[b'1', b'2', b'3']

bytes.strip([chars])

bytearray.strip([chars])

Renvoie une copie de la séquence dont des caractères initiaux et finaux sont supprimés. L’argument chars est une séquence spécifiant le jeu d’octets à supprimer, le nom se réfère au fait de cette méthode est généralement utilisée avec des caractères ASCII. En cas d’omission ou None, les espaces ASCII sont supprimés. L’argument chars n’est ni un préfixe ni un suffixe, toutes les combinaisons de ses valeurs sont supprimées :

>>> b'   spacious   '.strip()
b'spacious'
>>> b'www.example.com'.strip(b'cmowz.')
b'example'

La séquence de valeurs à supprimer peut être tout bytes-like object.

Note

La version bytearray de cette méthode ne modifie pas les octets, elle produit toujours un nouvel objet, même si aucune modification n’a été effectuée.

Les méthodes suivantes sur les bytes et bytearray supposent l’utilisation d’un format binaire compatible ASCII, et donc doivent être évités lorsque vous travaillez avec des données binaires arbitraires. Notez que toutes les méthodes de bytearray de cette section ne modifient pas les octets, ils produisent de nouveaux objets.

bytes.capitalize()

bytearray.capitalize()

Renvoie une copie de la séquence dont chaque octet est interprété comme un caractère ASCII, le premier octet en capitale et le reste en minuscules. Les octets non ASCII ne sont pas modifiés.

Note

La version bytearray de cette méthode ne modifie pas les octets, elle produit toujours un nouvel objet, même si aucune modification n’a été effectuée.

bytes.expandtabs(tabsize=8)

bytearray.expandtabs(tabsize=8)

Renvoie une copie de la séquence où toutes les tabulations ASCII sont remplacées par un ou plusieurs espaces ASCII, en fonction de la colonne courante et de la taille de tabulation donnée. Les positions des tabulations se trouvent tous les tabsize caractères (8 par défaut, ce qui donne les positions de tabulations aux colonnes 0, 8, 16 et ainsi de suite). Pour travailler sur la séquence, la colonne en cours est mise à zéro et la séquence est examinée octets par octets. Si l’octet est une tabulation ASCII (b'   '), un ou plusieurs espaces sont insérés au résultat jusqu’à ce que la colonne courante soit égale à la position de tabulation suivante. (Le caractère tabulation lui-même n’est pas copié.) Si l’octet courant est un saut de ligne ASCII (b' ') ou un retour chariot (b'\r'), il est copié et la colonne en cours est remise à zéro. Tout autre octet est copié inchangé et la colonne en cours est incrémentée de un indépendamment de la façon dont l’octet est représenté lors de l’affichage :

>>> b'01\t012\t0123\t01234'.expandtabs()
b'01      012     0123    01234'
>>> b'01\t012\t0123\t01234'.expandtabs(4)
b'01  012 0123    01234'

Note

La version bytearray de cette méthode ne modifie pas les octets, elle produit toujours un nouvel objet, même si aucune modification n’a été effectuée.

bytes.isalnum()

bytearray.isalnum()

Donne True si tous les caractères de la chaîne sont des caractères ASCII alphabétiques ou chiffres. et que la séquence n’est pas vide, sinon False. Les caractères ASCII alphabétiques sont les suivants b'abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ' et les chiffres : b'0123456789'.

Par exemple :

>>> b'ABCabc1'.isalnum()
True
>>> b'ABC abc1'.isalnum()
False

bytes.isalpha()

bytearray.isalpha()

Donne True si tous les octets dans la séquence sont des caractères alphabétiques ASCII et la que la séquence n’est pas vide, sinon False. Les caractères ASCIIalphabétiques sont : b'abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ'.

Par exemple :

>>> b'ABCabc'.isalpha()
True
>>> b'ABCabc1'.isalpha()
False

bytes.isdigit()

bytearray.isdigit()

Donne True si tous les octets de la séquence sont des chiffres ASCII et que la séquence n’est pas vide, sinon False. Les chiffres ASCII sont b'0123456789'.

Par exemple :

>>> b'1234'.isdigit()
True
>>> b'1.23'.isdigit()
False

bytes.islower()

bytearray.islower()

Donne True s’il y a au moins un caractère ASCII minuscule dans la séquence et aucune capitale, sinon False.

Par exemple :

>>> b'hello world'.islower()
True
>>> b'Hello world'.islower()
False

Les caractères ASCII minuscules sont b'abcdefghijklmnopqrstuvwxyz'. Les capitales ASCII sont b'ABCDEFGHIJKLMNOPQRSTUVWXYZ'.

bytes.isspace()

bytearray.isspace()

Donne True si tous les octets de la séquence sont des espaces ASCII et que la séquence n’est pas vide, sinon False. Les espèces ASCII sont b' \t\n\r\x0b\f' (espace, tabulation,saut de ligne, retour chariot, tabulation verticale, form feed).

bytes.istitle()

bytearray.istitle()

Donne True si la séquence ASCII est titlecased, et qu’elle ne soit pas vide, sinon False. Voir bytes.title() pour plus de détails sur la définition de titlecase.

Par exemple :

>>> b'Hello World'.istitle()
True
>>> b'Hello world'.istitle()
False

bytes.isupper()

bytearray.isupper()

Donne True s’il y a au moins un caractère alphabétique majuscule ASCII dans la séquence et aucun caractères ASCII minuscules, sinon False.

Par exemple :

>>> b'HELLO WORLD'.isupper()
True
>>> b'Hello world'.isupper()
False

Les caractères ASCII minuscules sont b'abcdefghijklmnopqrstuvwxyz'. Les capitales ASCII sont b'ABCDEFGHIJKLMNOPQRSTUVWXYZ'.

bytes.lower()

bytearray.lower()

Renvoie une copie de la séquence dont tous les caractères ASCII en majuscules sont convertis en leur équivalent en minuscules.

Par exemple :

>>> b'Hello World'.lower()
b'hello world'

Les caractères ASCII minuscules sont b'abcdefghijklmnopqrstuvwxyz'. Les capitales ASCII sont b'ABCDEFGHIJKLMNOPQRSTUVWXYZ'.

Note

La version bytearray de cette méthode ne modifie pas les octets, elle produit toujours un nouvel objet, même si aucune modification n’a été effectuée.

bytes.splitlines(keepends=False)

bytearray.splitlines(keepends=False)

Renvoie une liste des lignes de la séquence d’octets, découpant au niveau des fin de lignes ASCII. Cette méthode utilise l’approche universal newlines pour découper les lignes. Les fins de ligne ne sont pas inclus dans la liste des résultats, sauf si keepends est donné et vrai.

Par exemple :

>>> b'ab c\n\nde fg\rkl\r\n'.splitlines()
[b'ab c', b'', b'de fg', b'kl']
>>> b'ab c\n\nde fg\rkl\r\n'.splitlines(keepends=True)
[b'ab c\n', b'\n', b'de fg\r', b'kl\r\n']

Contrairement à split() lorsque le délimiteur sep est fourni, cette méthode renvoie une liste vide pour la chaîne vide, et un saut de ligne à la fin ne se traduit pas par une ligne supplémentaire :

>>> b"".split(b'\n'), b"Two lines\n".split(b'\n')
([b''], [b'Two lines', b''])
>>> b"".splitlines(), b"One line\n".splitlines()
([], [b'One line'])

bytes.swapcase()

bytearray.swapcase()

Renvoie une copie de la séquence dont tous les caractères ASCII minuscules sont convertis en majuscules et vice-versa.

Par exemple :

>>> b'Hello World'.swapcase()
b'hELLO wORLD'

Les caractères ASCII minuscules sont b'abcdefghijklmnopqrstuvwxyz'. Les capitales ASCII sont b'ABCDEFGHIJKLMNOPQRSTUVWXYZ'.

Contrairement à str.swapcase(), bin.swapcase().swapcase() == bin est toujours vrai. Les conversions majuscule/minuscule en ASCII étant toujours symétrique, ce qui n’est pas toujours vrai avec Unicode.

Note

La version bytearray de cette méthode ne modifie pas les octets, elle produit toujours un nouvel objet, même si aucune modification n’a été effectuée.

bytes.title()

bytearray.title()

Renvoie une version titlecased de la séquence d’octets où les mots commencent par un caractère ASCII majuscule et les caractères restants sont en minuscules. Les octets non capitalisables ne sont pas modifiés.

Par exemple :

>>> b'Hello world'.title()
b'Hello World'

Les caractères ASCII minuscules sont b'abcdefghijklmnopqrstuvwxyz'. Les caractères ASCII majuscules sont b'ABCDEFGHIJKLMNOPQRSTUVWXYZ'. Aucun autre octet n’est capitalisable.

Pour l’algorithme, la notion de mot est définie simplement et indépendamment de la langue comme un groupe de lettres consécutives. La définition fonctionne dans de nombreux contextes, mais cela signifie que les apostrophes (typiquement de la forme possessive en Anglais) forment les limites de mot, ce qui n’est pas toujours le résultat souhaité :

>>> b"they're bill's friends from the UK".title()
b"They'Re Bill'S Friends From The Uk"

Une solution pour contourner le problème des apostrophes peut être obtenue en utilisant des expressions rationnelles :

>>> import re
>>> def titlecase(s):
...     return re.sub(rb"[A-Za-z]+('[A-Za-z]+)?",
...                   lambda mo: mo.group(0)[0:1].upper() +
...                              mo.group(0)[1:].lower(),
...                   s)
...
>>> titlecase(b"they're bill's friends.")
b"They're Bill's Friends."

Note

La version bytearray de cette méthode ne modifie pas les octets, elle produit toujours un nouvel objet, même si aucune modification n’a été effectuée.

bytes.upper()

bytearray.upper()

Renvoie une copie de la séquence dont tous les caractères ASCII minuscules sont convertis en leur équivalent majuscule.

Par exemple :

>>> b'Hello World'.upper()
b'HELLO WORLD'

Les caractères ASCII minuscules sont b'abcdefghijklmnopqrstuvwxyz'. Les capitales ASCII sont b'ABCDEFGHIJKLMNOPQRSTUVWXYZ'.

Note

La version bytearray de cette méthode ne modifie pas les octets, elle produit toujours un nouvel objet, même si aucune modification n’a été effectuée.

bytes.zfill(width)

bytearray.zfill(width)

Return a copy of the sequence left filled with ASCII b'0' digits to make a sequence of length width. A leading sign prefix (b'+'/ b'-') is handled by inserting the padding after the sign character rather than before. For bytes objects, the original sequence is returned if width is less than or equal to len(seq).

Par exemple :

>>> b"42".zfill(5)
b'00042'
>>> b"-42".zfill(5)
b'-0042'

Note

La version bytearray de cette méthode ne modifie pas les octets, elle produit toujours un nouvel objet, même si aucune modification n’a été effectuée.

4.8.4. Formatage de bytes a la printf

Note

Les opérations de formatage décrites ici présentent une variété de bizarreries qui conduisent à un certain nombre d’erreurs classiques (typiquement, échouer à afficher des tuples ou des dictionnaires correctement). Si la valeur à afficher peut être un tuple ou un dictionnaire, mettez le a l’intérieur d’un autre tuple.

Les objets bytes (bytes et bytearray) ont un unique opérateur : l’opérateur % (modulo). Il est aussi connu sous le nom d’opérateur de mise en forme. Avec format % values (où format est un objet bytes), les marqueurs de conversion % dans format sont remplacés par zéro ou plus de values. L’effet est similaire à la fonction sprintf() du langage C.

Si format ne nécessite qu’un seul argument, values peut être un objet unique. 5 Si values est un tuple, il doit contenir exactement le nombre d’éléments spécifiés dans le format en bytes, ou un seul objet de correspondances ( mapping object, par exemple, un dictionnaire).

Un indicateur de conversion contient deux ou plusieurs caractères et comporte les éléments suivants, qui doivent apparaître dans cet ordre :

Le caractère '%', qui marque le début du marqueur.

La clé de correspondance (facultative), composée d’une suite de caractères entre parenthèse (par exemple, (somename)).

Des options de conversion, facultatives, qui affectent le résultat de certains types de conversion.

Largeur minimum (facultative). Si elle vaut '*' (astérisque), la largeur est lue de l’élément suivant du tuple values, et l’objet à convertir vient après la largeur de champ minimale et la précision facultative.

Précision (facultatif), donnée sous la forme d’un '.' (point) suivi de la précision. Si la précision est '*' (un astérisque), la précision est lue à partir de l’élément suivant du tuple values et la valeur à convertir vient ensuite.

Modificateur de longueur (facultatif).

Type de conversion.

Lorsque l’argument de droite est un dictionnaire (ou un autre type de mapping), les marqueurs dans le bytes doivent inclure une clé présente dans le dictionnaire, écrite entre parenthèses, immédiatement après le caractère '%'. La clé indique quelle valeur du dictionnaire doit être formatée. Par exemple :

>>> print(b'%(language)s has %(number)03d quote types.' %
...       {b'language': b"Python", b"number": 2})
b'Python has 002 quote types.'

Dans ce cas, aucune * ne peuvent se trouver dans le format (car ces * nécessitent une liste (accès séquentiel) de paramètres).

Les caractères indicateurs de conversion sont :

Option

Signification

'#'

La conversion utilisera la « forme alternative » (définie ci-dessous).

'0'

Les valeurs numériques converties seront complétée de zéros.

'-'

La valeur convertie est ajustée à gauche (remplace la conversion '0' si les deux sont données).

' '

(un espace) Un espace doit être laissé avant un nombre positif (ou chaîne vide) produite par la conversion d’une valeur signée.

'+'

Un caractère de signe ('+' ou '-') précède la valeur convertie (remplace le marqueur « espace »).

Un modificateur de longueur (h, l ou L) peut être présent, mais est ignoré car il est pas nécessaire pour Python, donc par exemple %ld est identique à %d.

Les types utilisables dans les conversion sont :

Conversion

Signification

Notes

'd'

Entier décimal signé.

'i'

Entier décimal signé.

'o'

Valeur octale signée.

(1)

'u'

Type obsolète — identique à 'd'.

(8)

'x'

Hexadécimal signé (en minuscules).

(2)

'X'

Hexadécimal signé (capitales).

(2)

'e'

Format exponentiel pour un float (minuscule).

(3)

'E'

Format exponentiel pour un float (en capitales).

(3)

'f'

Format décimal pour un float.

(3)

'F'

Format décimal pour un float.

(3)

'g'

Format float. Utilise le format exponentiel minuscules si l’exposant est inférieur à -4 ou pas plus petit que la précision, sinon le format décimal.

(4)

'G'

Format float. Utilise le format exponentiel en capitales si l’exposant est inférieur à -4 ou pas plus petit que la précision, sinon le format décimal.

(4)

'c'

Octet simple (Accepte un nombre entier ou un seul objet byte).

'b'

Bytes (tout objet respectant le buffer protocol ou ayant la méthode __bytes__()).

(5)

's'

's' est un alias de 'b' et ne devrait être utilisé que pour du code Python2/3.

(6)

'a'

Bytes (convertis n’importe quel objet Python en utilisant repr(obj).encode('ascii', 'backslashreplace)).

(5)

'r'

'r' est un alias de 'a' et ne devrait être utilise que dans du code Python2/3.

(7)

'%'

Aucun argument n’est converti, donne un caractère de '%' dans le résultat.

Notes :

La forme alternative entraîne l’insertion d’un préfixe octal ('0o') avant le premier chiffre.

La forme alternative entraîne l’insertion d’un préfixe '0x' ou '0X' (respectivement pour les formats 'x' et 'X') avant le premier chiffre.

La forme alternative implique la présence d’un point décimal, même si aucun chiffre ne le suit.

La précision détermine le nombre de chiffres après la virgule, 6 par défaut.

La forme alternative implique la présence d’un point décimal et les zéros non significatifs sont conservés (ils ne le seraient pas autrement).

La précision détermine le nombre de chiffres significatifs avant et après la virgule. 6 par défaut.

Si la précision est N, la sortie est tronquée à N caractères.

b'%s' est obsolète, mais ne sera pas retiré des version 3.x.

b'%r' est obsolète mais ne sera pas retiré dans Python 3.x.

Voir la PEP 237 [https://www.python.org/dev/peps/pep-0237].

Note

La version bytearray de cette méthode ne modifie pas les octets, elle produit toujours un nouvel objet, même si aucune modification n’a été effectuée.

Voir aussi

PEP 461 [https://www.python.org/dev/peps/pep-0461] – Ajout du formatage via % aux bytes et bytesarray

Nouveau dans la version 3.5.

4.8.5. Vues de mémoires

Les memoryview permettent a du code Python d’accéder sans copie aux données internes d’un objet prenant en charge le buffer protocol.

class memoryview(obj)

Crée une memoryview faisant référence à obj. obj doit supporter le buffer protocol. Les objets natifs prenant en charge le buffer protocol sont bytes et bytearray.

Une memoryview a la notion d”element, qui est l’unité de mémoire atomique géré par l’objet obj d’origine. Pour de nombreux types simples comme bytes et bytearray, l’élément est l’octet, mais pour d’autres types tels que array.array les éléments peuvent être plus grands.

len(view) est égal à la grandeur de tolist. Si view.ndim = 0, la longueur vaut 1. Si view.ndim = 1, la longueur est égale au nombre d’éléments de la vue. Pour les dimensions plus grandes, la longueur est égale à la longueur de la sous-liste représentée par la vue. L’attribut itemsize vous donnera la taille en octets d’un élément.

Une memoryview autorise le découpage et l’indiçage de ses données. Découper sur une dimension donnera une sous-vue :

>>> v = memoryview(b'abcefg')
>>> v[1]
98
>>> v[-1]
103
>>> v[1:4]
<memory at 0x7f3ddc9f4350>
>>> bytes(v[1:4])
b'bce'

Si le format est un des formats natif du module struct, indexer avec un nombre entier ou un tuple de nombres entiers est aussi autorisé et renvoie un seul element du bon type. Les memoryview à une dimension peuvent être indexées avec un nombre entier ou un tuple d’un entier. Les memoryview multi-dimensionnelles peuvent être indexées avec des tuples d’exactement ndim entiers où ndim est le nombre de dimensions. Les memoryviews à zéro dimension peuvent être indexées avec un tuple vide.

Voici un exemple avec un autre format que byte :

>>> import array
>>> a = array.array('l', [-11111111, 22222222, -33333333, 44444444])
>>> m = memoryview(a)
>>> m[0]
-11111111
>>> m[-1]
44444444
>>> m[::2].tolist()
[-11111111, -33333333]

Si l’objet sous-jacent est accessible en écriture, la memoryview autorisera les assignations de tranches à une dimension. Redimensionner n’est cependant pas autorisé :

>>> data = bytearray(b'abcefg')
>>> v = memoryview(data)
>>> v.readonly
False
>>> v[0] = ord(b'z')
>>> data
bytearray(b'zbcefg')
>>> v[1:4] = b'123'
>>> data
bytearray(b'z123fg')
>>> v[2:3] = b'spam'
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
ValueError: memoryview assignment: lvalue and rvalue have different structures
>>> v[2:6] = b'spam'
>>> data
bytearray(b'z1spam')

Les memoryviews à une dimension de types hachables (lecture seule) avec les formats “B”, “b”, ou “c” sont aussi hachables. La fonction de hachage est définie tel que hash(m) == hash(m.tobytes()) :

>>> v = memoryview(b'abcefg')
>>> hash(v) == hash(b'abcefg')
True
>>> hash(v[2:4]) == hash(b'ce')
True
>>> hash(v[::-2]) == hash(b'abcefg'[::-2])
True

Modifié dans la version 3.3: Les memoryviews à une dimension peuvent aussi être découpées. Les memoryviews à une dimension avec les formats “B”, “b”, ou “c” sont maintenant hachables.

Modifié dans la version 3.4: memoryview est maintenant enregistrée automatiquement avec collections.abc.Sequence

Modifié dans la version 3.5: les memoryviews peut maintenant être indexées par un n-uplet d’entiers.

La memoryview dispose de plusieurs méthodes :

__eq__(exporter)

Une memoryview et un exporter de la PEP 3118 [https://www.python.org/dev/peps/pep-3118] sont égaux si leurs formes sont équivalentes et si toutes les valeurs correspondantes sont égales, le format respectifs des opérandes étant interprétés en utilisant la syntaxe de struct.

Pour le sous-ensemble des formats de struct supportés par tolist(), v et w sont égaux si v.tolist() ==w.tolist() :

>>> import array
>>> a = array.array('I', [1, 2, 3, 4, 5])
>>> b = array.array('d', [1.0, 2.0, 3.0, 4.0, 5.0])
>>> c = array.array('b', [5, 3, 1])
>>> x = memoryview(a)
>>> y = memoryview(b)
>>> x == a == y == b
True
>>> x.tolist() == a.tolist() == y.tolist() == b.tolist()
True
>>> z = y[::-2]
>>> z == c
True
>>> z.tolist() == c.tolist()
True

Si l’un des format n’est pas supporté par le module de struct, les objets seront toujours considérés différents (même si les formats et les valeurs contenues sont identiques) :

>>> from ctypes import BigEndianStructure, c_long
>>> class BEPoint(BigEndianStructure):
...     _fields_ = [("x", c_long), ("y", c_long)]
...
>>> point = BEPoint(100, 200)
>>> a = memoryview(point)
>>> b = memoryview(point)
>>> a == point
False
>>> a == b
False

Notez que pour les memoryview, comme pour les nombres à virgule flottante, v is w n’implique pas v == w.

Modifié dans la version 3.3: Les versions précédentes comparaient la mémoire brute sans tenir compte du format de l’objet ni de sa structure logique.

tobytes()

Renvoie les données du buffer sous forme de bytes. Cela équivaut à appeler le constructeur bytes sur le memoryview.

>>> m = memoryview(b"abc")
>>> m.tobytes()
b'abc'
>>> bytes(m)
b'abc'

Pour les listes non contiguës le résultat est égal à la représentation en liste aplatie dont tous les éléments sont convertis en octets. tobytes() supporte toutes les chaînes de format, y compris celles qui ne sont pas connues du module struct.

hex()

Renvoie une chaîne contenant deux chiffres hexadécimaux pour chaque octet de la mémoire.

>>> m = memoryview(b"abc")
>>> m.hex()
'616263'

Nouveau dans la version 3.5.

tolist()

Renvoie les données de la mémoire sous la forme d’une liste d’éléments.

>>> memoryview(b'abc').tolist()
[97, 98, 99]
>>> import array
>>> a = array.array('d', [1.1, 2.2, 3.3])
>>> m = memoryview(a)
>>> m.tolist()
[1.1, 2.2, 3.3]

Modifié dans la version 3.3: tolist() prend désormais en charge tous les formats d’un caractère du module struct ainsi que des représentations multidimensionnelles.

release()

Libère le tampon sous-jacent exposé par l’objet memoryview. Beaucoup d’objets prennent des initiatives particulières lorsqu’ils sont liés à une vue (par exemple, un bytearray refusera temporairement de se faire redimensionner). Par conséquent, appeler release() peut être pratique pour lever ces restrictions (et en libérer les ressources liées) aussi tôt que possible.

Après le premier appel de cette méthode, toute nouvelle opération sur la view lève une ValueError (sauf release() elle-même qui peut être appelée plusieurs fois) :

>>> m = memoryview(b'abc')
>>> m.release()
>>> m[0]
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
ValueError: operation forbidden on released memoryview object

Le protocole de gestion de contexte peut être utilisé pour obtenir un effet similaire, via l’instruction with :

>>> with memoryview(b'abc') as m:
...     m[0]
...
97
>>> m[0]
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
ValueError: operation forbidden on released memoryview object

Nouveau dans la version 3.2.

cast(format[, shape])

Change le format ou la forme d’une memoryview. Par défaut shape vaut [byte_length//new_itemsize], ce qui signifie que la vue résultante n’aura qu’une dimension. La valeur renvoyée est une nouvelle memoryview, mais la mémoire elle-même n’est pas copiée. Les changements supportés sont une dimension vers C-contiguous et C-contiguous vers une dimension.

Le format de destination est limité à un seul élément natif de la syntaxe du module struct. L’un des formats doit être un byte (“B”, “b”, ou “c”). La longueur du résultat en octets doit être la même que la longueur initiale.

Transforme 1D/long en 1D/unsigned bytes :

>>> import array
>>> a = array.array('l', [1,2,3])
>>> x = memoryview(a)
>>> x.format
'l'
>>> x.itemsize
8
>>> len(x)
3
>>> x.nbytes
24
>>> y = x.cast('B')
>>> y.format
'B'
>>> y.itemsize
1
>>> len(y)
24
>>> y.nbytes
24

Transforme 1D/unsigned bytes en 1D/char :

>>> b = bytearray(b'zyz')
>>> x = memoryview(b)
>>> x[0] = b'a'
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
ValueError: memoryview: invalid value for format "B"
>>> y = x.cast('c')
>>> y[0] = b'a'
>>> b
bytearray(b'ayz')

Transforme 1D/bytes en 3D/ints en 1D/signed char :

>>> import struct
>>> buf = struct.pack("i"*12, *list(range(12)))
>>> x = memoryview(buf)
>>> y = x.cast('i', shape=[2,2,3])
>>> y.tolist()
[[[0, 1, 2], [3, 4, 5]], [[6, 7, 8], [9, 10, 11]]]
>>> y.format
'i'
>>> y.itemsize
4
>>> len(y)
2
>>> y.nbytes
48
>>> z = y.cast('b')
>>> z.format
'b'
>>> z.itemsize
1
>>> len(z)
48
>>> z.nbytes
48

Transforme 1D/unsigned char en 2D/unsigned long :

>>> buf = struct.pack("L"*6, *list(range(6)))
>>> x = memoryview(buf)
>>> y = x.cast('L', shape=[2,3])
>>> len(y)
2
>>> y.nbytes
48
>>> y.tolist()
[[0, 1, 2], [3, 4, 5]]

Nouveau dans la version 3.3.

Modifié dans la version 3.5: Le format de la source n’est plus restreint lors de la transformation vers une vue d’octets.

Plusieurs attributs en lecture seule sont également disponibles :

obj

L’objet sous-jacent de la memoryview :

>>> b  = bytearray(b'xyz')
>>> m = memoryview(b)
>>> m.obj is b
True

Nouveau dans la version 3.3.

nbytes

nbytes == product(shape) * itemsize == len(m.tobytes()). This is the amount of space in bytes that the array would use in a contiguous representation. It is not necessarily equal to len(m):

>>> import array
>>> a = array.array('i', [1,2,3,4,5])
>>> m = memoryview(a)
>>> len(m)
5
>>> m.nbytes
20
>>> y = m[::2]
>>> len(y)
3
>>> y.nbytes
12
>>> len(y.tobytes())
12

Tableaux multidimensionnels :

>>> import struct
>>> buf = struct.pack("d"*12, *[1.5*x for x in range(12)])
>>> x = memoryview(buf)
>>> y = x.cast('d', shape=[3,4])
>>> y.tolist()
[[0.0, 1.5, 3.0, 4.5], [6.0, 7.5, 9.0, 10.5], [12.0, 13.5, 15.0, 16.5]]
>>> len(y)
3
>>> y.nbytes
96

Nouveau dans la version 3.3.

readonly

Un booléen indiquant si la mémoire est en lecture seule.

format

Une chaîne contenant le format (dans le style de struct) pour chaque élément de la vue. Une memoryview peut être crée depuis des exportateurs de formats arbitraires, mais certaines méthodes (comme tolist()) sont limitées aux formats natifs à un seul élément.

Modifié dans la version 3.3: le format 'B' est maintenant traité selon la syntaxe du module struct. Cela signifie que memoryview(b'abc')[0] == b'abc'[0] == 97.

itemsize

La taille en octets de chaque élément d’une memoryview :

>>> import array, struct
>>> m = memoryview(array.array('H', [32000, 32001, 32002]))
>>> m.itemsize
2
>>> m[0]
32000
>>> struct.calcsize('H') == m.itemsize
True

ndim

Un nombre entier indiquant le nombre de dimensions d’un tableau multi-dimensionnel représenté par la memoryview.

shape

Un tuple d’entiers de longueur ndim donnant la forme de la memoryview sous forme d’un tableau à N dimensions.

Modifié dans la version 3.3: Un tuple vide au lieu de None lorsque ndim = 0.

strides

Un tuple d’entiers de longueur ndim donnant la taille en octets permettant d’accéder à chaque dimensions du tableau.

Modifié dans la version 3.3: Un tuple vide au lieu de None lorsque ndim = 0.

suboffsets

Détail de l’implémentation des PIL-style arrays. La valeur n’est donné qu’a titre d’information.

c_contiguous

Un booléen indiquant si la mémoire est C-contiguous.

Nouveau dans la version 3.3.

f_contiguous

Un booléen indiquant si la mémoire est Fortran contiguous.

Nouveau dans la version 3.3.

contiguous

Un booléen indiquant si la mémoire est contiguous.

Nouveau dans la version 3.3.

4.9. Types d’ensembles — set, frozenset

Un objet set est une collection non-triée d’objets hashable distincts. Les utilisations classiques sont le test d’appartenance, la déduplication d’une séquence, ou le calcul d’opérations mathématiques telles que l’intersection, l’union, la différence, ou la différence symétrique. (Pour les autres conteneurs, voir les classes natives dict, list, et tuple, ainsi que le module collections.)

Comme pour les autres collections, les ensembles supportent x in set, len(set), et for x in set. En tant que collection non-triée, les ensembles n’enregistrent pas la position des éléments ou leur ordre d’insertion. En conséquence, les sets n’autorisent ni l’indexation, ni le découpage, ou tout autre comportement de séquence.

Il existe actuellement deux types natifs pour les ensembles, set et fronzenset. Le type set est muable — son contenu peut changer en utilisant des méthodes comme add() et remove(). Puisqu’il est muable, il n’a pas de valeur de hachage et ne peut donc pas être utilisé ni comme clef de dictionnaire ni comme élément d’un autre ensemble. Le type frozenset est immuable et hashable — son contenu ne peut être modifié après sa création, il peut ainsi être utilisé comme clef de dictionnaire ou élément d’un autre set.

Des sets (mais pas des frozensets) peuvent être crées par une liste d’éléments séparés par des virgules et entre accolades, par exemple : {'jack', 'sjoerd'}, en plus du constructeur de la classe set.

Les constructeurs des deux classes fonctionnent pareil :

class set([iterable])

class frozenset([iterable])

Renvoie un nouveau set ou frozenset dont les éléments viennent d”iterable. Les éléments d’un set doivent être hashable. Pour représenter des sets de sets les sets intérieurs doivent être des frozenset. Si iterable n’est pas spécifié, un nouveau set vide est renvoyé.

Les instances de set et frozenset fournissent les opérations suivantes :

len(s)

Donne le nombre d’éléments dans le set s (cardinalité de s).

x in s

Test d’appartenance de x dans s.

x not in s

Test de non-appartenance de x dans s.

isdisjoint(other)

Renvoie True si l’ensemble n’a aucun élément en commun avec other. Les ensembles sont disjoints si et seulement si leurs intersection est un ensemble vide.

issubset(other)

set <= other

Teste si tous les éléments du set sont dans other.

set < other

Teste si l’ensemble est un sous-ensemble de other, c’est-à-dire, set <= other and set != other.

issuperset(other)

set >= other

Teste si tous les éléments de other sont dans l’ensemble.

set > other

Teste si l’ensemble est un sur-ensemble de other, c’est-à-dire, set >= other and set != other.

union(*others)

set | other | ...

Renvoie un nouvel ensemble dont les éléments viennent de l’ensemble et de tous les autres.

intersection(*others)

set & other & ...

Renvoie un nouvel ensemble dont les éléments sont commun à l’ensemble et à tous les autres.

difference(*others)

set - other - ...

Renvoie un nouvel ensemble dont les éléments sont dans l’ensemble mais ne sont dans aucun des autres.

symmetric_difference(other)

set ^ other

Renvoie un nouvel ensemble dont les éléments sont soit dans l’ensemble, soit dans les autres, mais pas dans les deux.

copy()

Renvoie un nouvel ensemble, copie de surface de s.

Remarque : Les méthodes union(), intersection(), difference(), et symmetric_difference(), issubset(), et issuperset() acceptent n’importe quel itérable comme argument, contrairement aux opérateurs équivalents qui n’acceptent que des sets. Il est donc préférable d’éviter les constructions comme set('abc') & 'cbs', sources typiques d’erreurs, en faveur d’une construction plus lisible : set('abc').intersection('cbs').

Les classes set et frozenset supportent les comparaisons d’ensemble à ensemble. Deux ensembles sont égaux si et seulement si chaque éléments de chaque ensemble est contenu dans l’autre (autrement dit que chaque ensemble est un sous-ensemble de l’autre). Un ensemble est plus petit qu’un autre ensemble si et seulement si le premier est un sous-ensemble du second (un sous-ensemble, mais pas égal). Un ensemble est plus grand qu’un autre ensemble si et seulement si le premier est un sur-ensemble du second (est un sur-ensemble mais n’est pas égal).

Les instances de set se comparent aux instances de frozenset en fonction de leurs membres. Par exemple, set('abc') == frozenset('abc') envoie True, ainsi que set('abc') in set([frozenset('abc')]).

Les comparaisons de sous-ensemble et d’égalité ne se généralisent pas en une fonction donnant un ordre total. Par exemple, deux ensemble disjoints non vides ne sont ni égaux et ni des sous-ensembles l’un de l’autre, donc toutes ces comparaisons donnent False : a<b, a==b, et a>b.

Puisque les sets ne définissent qu’un ordre partiel (par leurs relations de sous-ensembles), la sortie de la méthode list.sort() n’est pas définie pour des listes d’ensembles.

Les éléments des sets, comme les clefs de dictionnaires, doivent être hashable.

Les opérations binaires mélangeant des instances de set et frozenset renvoient le type de la première opérande. Par exemple : frozenset('ab') | set('bc') renvoie une instance de frozenset.

La table suivante liste les opérations disponibles pour les set mais qui ne s’appliquent pas aux instances de frozenset :

update(*others)

set |= other | ...

Met à jour l’ensemble, ajoutant les éléments de tous les autres.

intersection_update(*others)

set &= other & ...

Met à jour l’ensemble, ne gardant que les éléments trouvés dans tous les autres.

difference_update(*others)

set -= other | ...

Met à jour l’ensemble, retirant les éléments trouvés dans les autres.

symmetric_difference_update(other)

set ^= other

Met à jour le set, ne gardant que les éléments trouvés dans un des ensembles mais pas dans les deux.

add(elem)

Ajoute l’élément elem au set.

remove(elem)

Retire l’élément elem de l’ensemble. Lève une exception KeyError si elem n’est pas dans l’ensemble.

discard(elem)

Retire l’élément elem de l’ensemble s’il y est.

pop()

Retire et renvoie un élément arbitraire de l’ensemble. Lève une exception KeyError si l’ensemble est vide.

clear()

Supprime tous les éléments du set.

Notez que les versions non-opérateurs des méthodes update(), intersection_update(), difference_update(), et symmetric_difference_update() acceptent n’importe quel itérable comme argument.

Notez que l’argument elem des méthodes __contains__(), remove(), et discard() peut être un ensemble. Pour supporter la recherche d’un frozenset équivalent, un frozenset temporaire est crée depuis elem.

4.10. Les types de correspondances — dict

Un objet mapping fait correspondre des valeurs hashable à des objets arbitraires. Les mappings sont des objets muables. Il n’existe pour le moment qu’un type de mapping standard, le dictionary. (Pour les autres conteneurs, voir les types natifs list, set, et tuple, ainsi que le module collections.)

Les clefs d’un dictionnaire sont presque des données arbitraires. Les valeurs qui ne sont pas hashable, c’est-à-dire qui contiennent les listes, des dictionnaires ou autre type muable (qui sont comparés par valeur plutôt que par leur identité) ne peuvent pas être utilisées comme clef de dictionnaire. Les types numériques utilisés comme clef obéissent aux règles classiques en ce qui concerne les comparaisons : si deux nombres sont égaux (comme 1 et 1.0) ils peuvent tous les deux être utilisés pour obtenir la même entrée d’un dictionnaire. (Notez cependant que puisque les ordinateurs stockent les nombres à virgule flottante sous forme d’approximations, il est généralement imprudent de les utiliser comme clefs de dictionnaires.)

Il est possible de créer des dictionnaires en plaçant entre accolades une liste de paires de key: value séparés par des virgules, par exemple: {'jack': 4098, 'sjoerd': 4127} ou {4098: 'jack', 4127: 'sjoerd'}, ou en utilisant le constructeur de dict.

class dict(**kwarg)

class dict(mapping, **kwarg)

class dict(iterable, **kwarg)

Renvoie un nouveau dictionnaire initialisé depuis un argument positionnel optionnel, et un ensemble (vide ou non) d’arguments par mot clef.

Si aucun argument positionnel n’est donné, un dictionnaire vide est crée. Si un argument positionnel est donné et est un mapping object, un dictionnaire est crée avec les mêmes paires de clef-valeurs que le mapping donné. Autrement, l’argument positionnel doit être un objet iterable. Chaque élément de cet itérable doit lui même être un itérable contenant exactement deux objets. Le premier objet de chaque élément devient la une clef du nouveau dictionnaire, et le second devient sa valeur correspondante. Si une clef apparaît plus d’une fois, la dernière valeur pour cette clef devient la valeur correspondante à cette clef dans le nouveau dictionnaire.

Si des arguments nommés sont donnés, ils sont ajoutés au dictionnaire créé depuis l’argument positionnel. Si une clef est déjà présente, la valeur de l’argument nommé remplace la valeur reçue par l’argument positionnel.

Typiquement, les exemples suivants renvoient tous un dictionnaire valant {"one": 1, "two": 2, "three": 3} :

>>> a = dict(one=1, two=2, three=3)
>>> b = {'one': 1, 'two': 2, 'three': 3}
>>> c = dict(zip(['one', 'two', 'three'], [1, 2, 3]))
>>> d = dict([('two', 2), ('one', 1), ('three', 3)])
>>> e = dict({'three': 3, 'one': 1, 'two': 2})
>>> a == b == c == d == e
True

Fournir les arguments nommés comme dans le premier exemple en fonctionne que pour des clefs qui sont des identifiants valide en Python. Dans les autres cas, toutes les clefs valides sont utilisables.

Voici les opérations gérées par les dictionnaires, (par conséquent, d’autres types de mapping peuvent les gérer aussi) :

len(d)

Renvoie le nombre d’éléments dans le dictionnaire d.

d[key]

Donne l’élément de d dont la clef est key. Lève une exception KeyError si key n’est pas dans le dictionnaire.

Si une sous-classe de dict définit une méthode __missing__() et que key manque, l’opération d[key] appelle cette méthode avec la clef key en argument. L’opération d[key] renverra la valeur, ou lèvera l’exception renvoyée ou levée par l’appel à __missing__(key). Aucune autre opération ni méthode n’appellent __missing__(). If __missing__() n’est pas définie, une exception KeyError est levée. __missing__() doit être une méthode; ça ne peut être une variable d’instance :

>>> class Counter(dict):
...     def __missing__(self, key):
...         return 0
>>> c = Counter()
>>> c['red']
0
>>> c['red'] += 1
>>> c['red']
1

L’exemple ci-dessus montre une partie de l’implémentation de collections.Counter. collections.defaultdict implémente aussi __missing__.

d[key] = value

Assigne d[key] à value.

del d[key]

Supprime d[key] de d. Lève une exception KeyError si key n’est pas dans le dictionnaire.

key in d

Renvoie True si d a la clef key, sinon False.

key not in d

Équivalent à not key in d.

iter(d)

Renvoie un itérateur sur les clefs du dictionnaire. C’est un raccourci pour iter(d.keys()).

clear()

Supprime tous les éléments du dictionnaire.

copy()

Renvoie une copie de surface du dictionnaire.

classmethod fromkeys(seq[, value])

Crée un nouveau dictionnaire avec les clefs de seq et les valeurs à value.

fromkeys() est une class method qui renvoie un nouveau dictionnaire. value vaut None par défaut.

get(key[, default])

Renvoie la valeur de key si key est dans le dictionnaire, sinon default. Si default n’est pas donné, il vaut None par défaut, de manière à ce que cette méthode ne lève jamais KeyError.

items()

Renvoie une nouvelle vue des éléments du dictionnaire (paires de (key, value)). Voir la documentation des vues.

keys()

Renvoie une nouvelle vue des clefs du dictionnaire. Voir la documentation des vues.

pop(key[, default])

Si key est dans le dictionnaire elle est supprimée et sa valeur est renvoyée, sinon renvoie default. Si default n’est pas donné et que key n’est pas dans le dictionnaire, une KeyError est levée.

popitem()

Supprime et renvoie une (key, value) arbitraire du dictionnaire.

popitem() est pratique pour itérer un dictionnaire de manière destructive, comme souvent dans les algorithmes sur les ensembles. Si le dictionnaire est vide, appeler popitem() lève une KeyError.

setdefault(key[, default])

Si key est dans le dictionnaire, sa valeur est renvoyée. Sinon, insère key avec comme valeur default et renvoie default. default vaut None par défaut.

update([other])

Met à jour le dictionnaire avec les paires de clef/valeur d”other, écrasant les clefs existantes. Renvoie None.

update() accepte aussi bien un autre dictionnaire qu’un itérable de clef/valeurs (sous forme de tuples ou autre itérables de longueur deux). Si des paramètres par mot-clef sont donnés, le dictionnaire et ensuite mis à jour avec ces pairs de clef/valeurs : d.update(red=1, blue=2).

values()

Renvoie une nouvelle vue des valeurs du dictionnaire. Voir la documentation des vues.

Deux dictionnaires sont égaux si et seulement si ils ont les mêmes paires de clef-valeur. Les comparaisons d’ordre (<, <=, >=, >) lèvent une TypeError.

Voir aussi

types.MappingProxyType peut être utilisé pour créer une vue en lecture seule d’un dict.

4.10.1. Les vues de dictionnaires

Les objets renvoyés par dict.keys(), dict.values() et dict.items() sont des vues. Ils fournissent une vue dynamique des éléments du dictionnaire, ce qui signifie que si le dictionnaire change, la vue reflète ces changements.

Les vues de dictionnaires peuvent être itérées et ainsi renvoyer les données du dictionnaire, elle gèrent aussi les tests de présence :

len(dictview)

Renvoie le nombre d’entrées du dictionnaire.

iter(dictview)

Renvoie un itérateur sur les clefs, les valeurs, ou les éléments (représentés par des tuples de (key, value) du dictionnaire.

Les clefs et les valeurs sont itérées dans un ordre arbitraire qui n’est pas aléatoire, qui peut varier d’une implémentation de Python à l’autre, et qui dépend de l’historique d’insertion et de suppressions d’éléments. Si les vues de clefs, de valeurs, et d’éléments sont parcourues sans que le dictionnaire ne soit modifié, l’ordre des éléments correspondra directement. Ceci permet la création de paires de (key, value) en utilisant zip() : pairs = zip(d.values(), d.keys()). Un autre moyen de construire la même liste est pairs = [(v, k) for (k, v) in d.items()].

Parcourir des vues tout en ajoutant ou supprimant des entrées dans un dictionnaire peut lever une RuntimeError ou ne pas fournir toutes les entrées.

x in dictview

Renvoie True si x est dans les clefs, les valeurs, ou les éléments du dictionnaire sous-jacent (dans le dernier cas, x doit être un tuple (key, value)).

Les vues de clefs sont semblables à des ensembles puisque leurs entrées sont uniques et hachables. Si toutes les valeurs sont hachables, et qu’ainsi toutes les paires de (key, value sont uniques et hachables, alors la vue donnée par items() est aussi semblable à un ensemble. (Les vues données par items() ne sont généralement pas traitées comme des ensembles, car leurs valeurs ne sont généralement pas uniques.) Pour les vues semblables aux ensembles, toutes les opérations définies dans la classe de base abstraite collections.abc.Set sont disponibles (comme ==, <, ou ^).

Exemple d’utilisation de vue de dictionnaire :

>>> dishes = {'eggs': 2, 'sausage': 1, 'bacon': 1, 'spam': 500}
>>> keys = dishes.keys()
>>> values = dishes.values()

>>> # iteration
>>> n = 0
>>> for val in values:
...     n += val
>>> print(n)
504

>>> # keys and values are iterated over in the same order
>>> list(keys)
['eggs', 'bacon', 'sausage', 'spam']
>>> list(values)
[2, 1, 1, 500]

>>> # view objects are dynamic and reflect dict changes
>>> del dishes['eggs']
>>> del dishes['sausage']
>>> list(keys)
['spam', 'bacon']

>>> # set operations
>>> keys & {'eggs', 'bacon', 'salad'}
{'bacon'}
>>> keys ^ {'sausage', 'juice'}
{'juice', 'sausage', 'bacon', 'spam'}

4.11. Le type gestionnaire de contexte

L’instruction with permet l’existence de contextes définis à l’exécution par des gestionnaires de contextes. C’est implémenté via une paire de méthodes permettant de définir un contexte, à l’exécution, qui est entré avant l’exécution du corps de l’instruction, et qui est quitté lorsque l’instruction se termine :

contextmanager.__enter__()

Entre dans le contexte à l’exécution, soit se renvoyant lui-même, soit en renvoyant un autre objet en lien avec ce contexte. La valeur renvoyée par cette méthode est liée à l’identifiant donné au as de l’instruction with utilisant ce gestionnaire de contexte.

Un exemple de gestionnaire de contexte se renvoyant lui-même est file object. Les file objects se renvoient eux-même depuis __enter__() et autorisent open() à être utilisé comme contexte à une instruction with.

Un exemple de gestionnaire de contexte renvoyant un objet connexe est celui renvoyé par decimal.localcontext(). Ces gestionnaires remplacent le contexte décimal courant par une copie de l’original, copie qui est renvoyée. Ça permet de changer le contexte courant dans le corps du with sans affecter le code en dehors de l’instruction with.

contextmanager.__exit__(exc_type, exc_val, exc_tb)

Sort du contexte et renvoie un booléen indiquant si une exception survenue doit être supprimée. Si une exception est survenue lors de l’exécution du corps de l’instruction with, les arguments contiennent le type de l’exception, sa valeur, et la trace de la pile (traceback). Sinon les trois arguments valent None.

L’instruction with inhibera l’exception si cette méthode renvoie une valeur vraie, l’exécution continuera ainsi à l’instruction suivant immédiatement l’instruction with. Sinon, l’exception continuera de se propager après la fin de cette méthode. Les exceptions se produisant pendant l’exécution de cette méthode remplaceront toute exception qui s’est produite dans le corps du with.

L’exception reçue ne doit jamais être relancée explicitement, cette méthode devrait plutôt renvoyer une valeur fausse pour indiquer que son exécution s’est terminée avec succès et qu’elle ne veut pas supprimer l’exception. Ceci permet au code de gestion du contexte de comprendre si une méthode __exit__() a échoué.

Python définit plusieurs gestionnaires de contexte pour faciliter la synchronisation des fils d’exécution, la fermeture des fichiers ou d’autres objets, et la configuration du contexte arithmétique décimal. Ces types spécifiques ne sont pas traités différemment, ils respectent simplement le protocole de gestion du contexte. Voir les exemples dans la documentation du module contextlib.

Les generators de Python et le décorateur contextlib.contextmanager permettent d’implémenter simplement ces protocoles. Si un générateur est décoré avec contextlib. contextmanager, elle renverra un gestionnaire de contexte implémentant les méthodes __enter__() et __exit__(), plutôt que l’itérateur produit par un générateur non décoré.

Notez qu’il n’y a pas d’emplacement spécifique pour ces méthodes dans la structure de type pour les objets Python dans l’API Python/C. Les types souhaitant définir ces méthodes doivent les fournir comme une méthode accessible en Python. Comparé au coût de la mise en place du contexte d’exécution, les le coût d’un accès au dictionnaire d’une classe unique est négligeable.

4.12. Autres types natifs

L’interpréteur gère aussi d’autres types d’objets, la plupart ne supportant cependant qu’une ou deux opérations.

4.12.1. Modules

La seule opération spéciale sur un module est l’accès à ses attributs : m.name, où m est un module et name donne accès un nom défini dans la table des symboles de m. Il est possible d’assigner un attribut de module. (Notez que l’instruction import n’est pas strictement une opération sur un objet module. import foo ne nécessite pas qu’un objet module nommé foo existe, il nécessite cependant une définition (externe) d’un module nommé foo quelque part.)

Un attribut spécial à chaque module est __dict__. C’est le dictionnaire contenant la table des symbole du module. Modifier ce dictionnaire changera la table des symboles du module, mais assigner directement __dict__ n’est pas possible (vous pouvez écrire m.__dict__['a'] = 1, qui donne 1 comme valeur pour m.a, mais vous ne pouvez pas écrire m.__dict__ = {}). Modifier __dict__ directement n’est pas recommandé.

Les modules natifs à l’interpréteur sont représentés <module 'sys' (built-in)>. S’ils sont chargés depuis un fichier, ils sont représentés <module 'os' from '/usr/local/lib/pythonX.Y/os.pyc'>.

4.12.2. Les classes et instances de classes

Voir Objets, valeurs et types et Définition de classes.

4.12.3. Fonctions

Les objets fonctions sont crées par les définitions de fonctions. La seule opération applicable à un objet fonction est de l’appeler : func(argument-list).

Il existe en fait deux catégories d’objets fonctions : Les fonctions natives et les fonctions définies par l’utilisateur. Les deux gèrent les mêmes opérations (l’appel à la fonction), mais leur implémentation est différente, d’où les deux types distincts.

Voir Définition de fonctions pour plus d’information.

4.12.4. Méthodes

Les méthodes sont des fonctions appelées via la notation d’attribut. Il en existe deux variantes : Les méthodes natives (tel que append() sur les listes), et les méthodes d’instances de classes. Les méthodes natives sont représentées avec le type qui les supporte.

Si vous accédez à une méthode (une fonction définie dans l’espace de nommage d’une classe) via une instance, vous obtenez un objet spécial, une bound method (aussi appelée instance method). Lorsqu’elle est appelée, elle ajoute l’argument self à la liste des arguments. Les méthodes liées ont deux attributs spéciaux, en lecture seule : m.__self__ est l’objet sur lequel la méthode travaille, et m.__func__ est la fonction implémentant la méthode. Appeler m(arg-1, arg-2, …, arg-n) est tout à fait équivalent à appeler m.__func__(m.__self__, arg-1, arg-2, …, arg-n).

Comme les objets fonctions, les objets méthodes, liées, acceptent des attributs arbitraires. Cependant, puisque les attributs de méthodes doivent être stockés dans la fonction sous-jacente (meth.__func__), affecter des attributs à des objets bound method est interdit. Toute tentative d’affecter un attribut sur un objet bound method lèvera une AttributeError. Pour affecter l’attribut, vous devrez explicitement l’affecter à sa fonction sous-jacente :

>>> class C:
...     def method(self):
...         pass
...
>>> c = C()
>>> c.method.whoami = 'my name is method'  # can't set on the method
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
AttributeError: 'method' object has no attribute 'whoami'
>>> c.method.__func__.whoami = 'my name is method'
>>> c.method.whoami
'my name is method'

Voir Hiérarchie des types standards pour plus d’information.

4.12.5. Objets code

Les objets code sont utilisés par l’implémentation pour représenter du code Python « pseudo-compilé », comme un corps de fonction. Ils sont différents des objets fonction dans le sens où ils ne contiennent pas de référence à leur environnement global d’exécution. Les objets code sont renvoyés par la fonction native compile() et peuvent être obtenus des objets fonction via leur attribut __code__. Voir aussi le module code.

Les objets code peuvent être exécutés ou évalués en les passant (au lieu d’une chaîne contenant du code) aux fonction natives exec() ou eval().

Voir Hiérarchie des types standards pour plus d’information.

4.12.6. Objets type

Les objets types représentent les différents types d’objets. Le type d’un objet est obtenu via la fonction native type(). Il n’existe aucune opération spéciale sur les types. Le module standard types définit les noms de tous les types natifs.

Les types sont représentés : <class 'int'>.

4.12.7. L’objet Null

Cet objet est renvoyé par les fonctions ne renvoyant pas explicitement une valeur. Il ne supporte aucune opération spéciale. Il existe exactement un objet null nommé None (c’est un nom natif). type(None)().

C’est écrit None.

4.12.8. L’objet points de suspension

Cet objet est utilisé classiquement lors des découpes (voir Tranches). Il ne supporte aucune opération spéciale. Il n’y a qu’un seul objet ellipsis, nommé Ellipsis (un nom natif). type(Ellipsis)() produit le singleton Ellipsis.

C’est écrit Ellipsis ou ....

4.12.9. L’objet NotImplemented

Cet objet est renvoyé depuis des comparaisons ou des opérations binaires effectuées sur des types qu’elles ne supportent pas. Voir Comparaisons pour plus d’informations. Il n’y a qu’un seul objet NotImplemented. type(NotImplemented)() renvoie un singleton.

C’est écrit NotImplemented.

4.12.10. Valeurs booléennes

Les valeurs booléennes sont les deux objets constants False et True. Ils sont utilisés pour représenter les valeurs de vérité (bien que d’autres valeurs peuvent être considérées vraies ou fausses). Dans des contextes numériques (par exemple en argument d’un opérateur arithmétique), ils se comportent comme les nombres entiers 0 et 1, respectivement. La fonction native bool() peut être utilisée pour convertir n’importe quelle valeur en booléen tant que la valeur peut être interprétée en une valeur de vérité (voir Valeurs booléennes au dessus).

Ils s’écrivent False et True, respectivement.

4.12.11. Objets internes

Voir Hiérarchie des types standards. Ils décrivent les objets stack frame, traceback, et slice.

4.13. Attributs spéciaux

L’implémentation ajoute quelques attributs spéciaux et en lecture seule, à certains types, lorsque ça a du sens. Certains ne sont pas listés par la fonction native dir().

object.__dict__

Un dictionnaire ou un autre mapping object utilisé pour stocker les attributs (modifiables) de l’objet.

instance.__class__

La classe de l’instance de classe.

class.__bases__

Le tuple des classes parentes d’un objet classe.

definition.__name__

Le nom de la classe, fonction, méthode, descripteur, ou générateur.

definition.__qualname__

Le qualified name de la classe, fonction, méthode, descripteur, ou générateur.

Nouveau dans la version 3.3.

class.__mro__

Cet attribut est un tuple contenant les classes parents prises en compte lors de la résolution de méthode.

class.mro()

Cette méthode peut être surchargée par une méta-classe pour personnaliser l’ordre de la recherche de méthode pour ses instances. Elle est appelée à la l’initialisation de la classe, et son résultat est stocké dans l’attribut __mro__.

class.__subclasses__()

Chaque classe garde une liste de références faibles à ses classes filles immédiates. Cette méthode renvoie la liste de toutes ces références encore valables. Exemple :

>>> int.__subclasses__()
[<class 'bool'>]

Notes

1

Plus d’informations sur ces méthodes spéciales peuvent être trouvées dans le Python Reference Manual (Personnalisation de base).

2

Par conséquent, la liste [1, 2] est considérée égale à [1.0, 2.0]. Idem avec des tuples.

3

Nécessairement, puisque l’analyseur ne peut pas discerner le type des opérandes.

4(1,2,3,4)

Les caractères capitalisables sont ceux dont la propriété Unicode general category est soit « Lu » (pour Letter, uppercase), soit « Ll » (pour Letter, lowercase), soit « Lt » (pour Letter, titlecase).

5(1,2)

Pour insérer un tuple, vous devez donc donner un tuple d’un seul élément, contenant le tuple à insérer.

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5. Exceptions natives

En python, une exception est une instance d’une classe héritée de BaseException. Dans un bloc try, la clause except traite non seulement la classe d’exception qu’elle mentionne, mais aussi toutes les classes dérivées de cette classe (contrairement à ses classes mères). Deux classes qui ne sont pas liées par héritage ne sont jamais équivalentes, même si elles ont le même nom.

Les exceptions natives présentes ci-dessous peuvent être levées par l’interpréteur ou par les fonctions natives. Sauf mention contraire, une « valeur associée » indique la cause de l’erreur. Cela peut être une chaîne ou un tuple contenant plusieurs éléments d’information (e.g., un code d’erreur ou un message explicatif). Cette valeur associée est généralement donnée en argument du constructeur de la classe.

Du code utilisateur peut lever des exceptions natives. Cela peut être utilisé pour tester un gestionnaire d’exception ou pour rapporter une condition d’erreur « comme si » c’était l’interpréteur qui levait cette exception ; mais attention car rien n’empêche du code utilisateur de lever une erreur inappropriée.

Les classes d’exception natives peuvent être héritées pour définir de nouvelles exceptions ; les programmeurs sont encouragés à faire dériver les nouvelles exceptions de la classe Exception ou d’une de ses sous-classes, et non de BaseException. Plus d’informations sur la définition des exceptions sont disponibles dans le Tutoriel Python sous Exceptions définies par l’utilisateur.

En levant (ou levant à nouveau) une exception dans une clause except ou finally, __context__ est automatiquement assigné à la dernière exception capturée ; si la nouvelle exception n’est pas gérée, la trace d’appels affichée inclut la ou les exception(s) d’origine et l’exception finale.

En levant une nouvelle exception (plutôt que d’utiliser un simple raise pour lever à nouveau l’exception en cours de traitement), le contexte implicite d’exception peut être complété par une cause explicite en utilisant from avec raise :

raise new_exc from original_exc

The expression following from must be an exception or None. It will be set as __cause__ on the raised exception. Setting __cause__ also implicitly sets the __suppress_context__ attribute to True, so that using raise new_exc from None effectively replaces the old exception with the new one for display purposes (e.g. converting KeyError to AttributeError), while leaving the old exception available in __context__ for introspection when debugging.

Le code d’affichage par défaut de la trace d’appels montre ces exceptions chaînées en plus de la trace de l’exception elle-même. Une exception chaînée explicitement dans __cause__ est toujours affichée si présente. Une exception implicitement chaînée dans __context__ n’est affichée que si __cause__ est None et __suppress_context__ est faux.

Dans les deux cas, l’exception elle-même est toujours affichée après toutes les exceptions enchaînées, de sorte que la dernière ligne de la trace d’appels montre toujours la dernière exception qui a été levée.

5.1. Classes de base

Les exceptions suivantes sont utilisées principalement en tant que classes de base pour d’autres exceptions.

exception BaseException

La classe de base pour toutes les exceptions natives. Elle n’est pas vouée à être héritée directement par des classes utilisateur (pour cela, utilisez Exception). Si str() est appelée sur une instance de cette classe, la représentation du ou des argument(s) de l’instance est retournée, ou la chaîne vide s’il n’y avait pas d’arguments.

args

Le tuple d’arguments donné au constructeur d’exception. Certaines exceptions natives (comme OSError) attendent un certain nombre d’arguments et attribuent une signification spéciale aux éléments de ce tuple, alors que d’autres ne sont généralement appelées qu’avec une seule chaîne de caractères rendant un message d’erreur.

with_traceback(tb)

Cette méthode définit tb en tant que nouvelle trace d’appels pour l’exception et retourne l’objet exception. Elle est généralement utilisée dans du code de gestion d’exceptions comme ceci :

try:
    ...
except SomeException:
    tb = sys.exc_info()[2]
    raise OtherException(...).with_traceback(tb)

exception Exception

Toutes les exceptions natives, qui n’entraînent pas une sortie du système dérivent de cette classe. Toutes les exceptions définies par l’utilisateur devraient également être dérivées de cette classe.

exception ArithmeticError

La classe de base pour les exceptions natives qui sont levées pour diverses erreurs arithmétiques : OverflowError, ZeroDivisionError, FloatingPointError.

exception BufferError

Levée lorsqu’une opération liée à un tampon ne peut pas être exécutée.

exception LookupError

La classe de base pour les exceptions qui sont levées lorsqu’une clé ou un index utilisé sur un tableau de correspondances ou une séquence est invalide : IndexError, KeyError. Peut être levée directement par codecs.lookup().

5.2. Exceptions concrètes

Les exceptions suivantes sont celles qui sont habituellement levées.

exception AssertionError

Levée lorsqu’une instruction assert échoue.

exception AttributeError

Levée lorsqu’une référence ou une assignation d’attribut (voir Références à des attributs) échoue. (Lorsqu’un objet ne supporte pas du tout la référence ou l’assignation d’attribut, TypeError est levé.)

exception EOFError

Levée lorsque la fonction input() atteint une condition de fin de fichier (EOF) sans lire aucune donnée. (N.B.: les méthodes io.IOBase.read() et io.IOBase.readline() retournent une chaîne vide lorsqu’elles atteignent EOF.)

exception FloatingPointError

Levée lorsqu’une opération en virgule flottante échoue. Cette exception est toujours définie, mais ne peut être levée que lorsque Python est configuré avec l’option --with-fpectl, ou que le symbole WANT_SIGFPE_HANDLER est défini dans le fichier pyconfig.h.

exception GeneratorExit

Levée lorsqu’un generator ou une coroutine est fermé, voir generator.close() et coroutine.close(). Elle hérite directement de BaseException au lieu de Exception puisqu’il ne s’agit pas techniquement d’une erreur.

exception ImportError

Levée lorsque l’instruction import a des problèmes pour essayer de charger un module. Également levée lorsque Python ne trouve pas un nom dans from ... import.

Les attributs name et path peuvent être définis uniquement à l’aide d’arguments mot-clef (kwargs) passés au constructeur. Lorsqu’ils sont définis, ils représentent respectivement le nom du module qui a été tenté d’être importé et le chemin d’accès au fichier qui a déclenché l’exception.

Modifié dans la version 3.3: Ajout des attributs name et path.

exception ModuleNotFoundError

Une sous-classe de ImportError qui est levée par import lorsqu’un module n’a pas pu être localisé. Elle est généralement levée quand None est trouvé dans sys.modules.

Nouveau dans la version 3.6.

exception IndexError

Levée lorsqu’un indice de séquence est hors de la plage. (Les indices de tranches (slices) sont tronqués silencieusement pour tomber dans la plage autorisée ; si un indice n’est pas un entier, TypeError est levée.)

exception KeyError

Levée lorsqu’une clef (de dictionnaire) n’est pas trouvée dans l’ensemble des clefs existantes.

exception KeyboardInterrupt

Levée lorsque l’utilisateur appuie sur la touche d’interruption (normalement Control-C or Delete). Pendant l’exécution, un contrôle des interruptions est effectué régulièrement. L’exception hérite de BaseException afin de ne pas être accidentellement capturée par du code qui capture Exception et ainsi empêcher l’interpréteur de quitter.

exception MemoryError

Levée lorsqu’une opération est à court de mémoire mais que la situation peut encore être rattrapée (en supprimant certains objets). La valeur associée est une chaîne de caractères indiquant quel type d’opération (interne) est à court de mémoire. À noter qu’en raison de l’architecture interne de gestion de la mémoire (la fonction malloc() du C), l’interpréteur peut ne pas toujours être capable de rattraper cette situation ; il lève néanmoins une exception pour qu’une pile d’appels puisse être affichée, dans le cas où un programme en cours d’exécution en était la cause.

exception NameError

Levée lorsqu’un nom local ou global n’est pas trouvé. Ceci ne s’applique qu’aux noms non qualifiés. La valeur associée est un message d’erreur qui inclut le nom qui n’a pas pu être trouvé.

exception NotImplementedError

Cette exception est dérivée de RuntimeError. Dans les classes de base définies par l’utilisateur, les méthodes abstraites devraient lever cette exception lorsqu’elles nécessitent des classes dérivées pour remplacer la méthode, ou lorsque la classe est en cours de développement pour indiquer que l’implémentation concrète doit encore être ajoutée.

Note

Elle ne devrait pas être utilisée pour indiquer qu’un opérateur ou qu’une méthode n’est pas destiné à être pris en charge du tout – dans ce cas, laissez soit l’opérateur / la méthode non défini, soit, s’il s’agit d’une sous-classe, assignez-le à None.

Note

NotImplementedError et NotImplemented ne sont pas interchangeables, même s’ils ont des noms et des objectifs similaires. Voir NotImplemented pour des détails sur la façon de les utiliser.

exception OSError([arg])

exception OSError(errno, strerror[, filename[, winerror[, filename2]]])

Cette exception est levée lorsqu’une fonction système retourne une erreur liée au système, incluant les erreurs entrées-sorties telles que « fichier non trouvé » ou « disque plein » (pas pour les types d’arguments illégaux ou d’autres erreurs accidentelles).

La deuxième forme du constructeur définit les attributs correspondants, décrits ci-dessous. Les attributs par défaut sont None si non spécifiés. Pour la rétrocompatibilité, si trois arguments sont passés, l’attribut args contient seulement un tuple à deux valeurs des deux premiers arguments du constructeur.

Le constructeur retourne souvent une sous-classe d”OSError, comme décrit dans OS exceptions ci-dessous. La sous-classe particulière dépend de la valeur finale d”errno. Ce comportement ne se produit que lors de la construction d”OSError directement ou via un alias, et n’est pas hérité lors du sous-classement.

errno

Code d’erreur numérique de la variable C errno.

winerror

Sous Windows, cela donne le code d’erreur Windows natif. L’attribut errno est alors une traduction approximative, en termes POSIX, de ce code d’erreur natif.

Sous Windows, si l’argument du constructeur winerror est un entier, l’attribut errno est déterminé à partir du code d’erreur Windows, et l’argument errno est ignoré. Sur d’autres plateformes, l’argument winerror est ignoré, et l’attribut winerror n’existe pas.

strerror

Le message d’erreur correspondant, tel que fourni par le système d’exploitation. Il est formaté par les fonctions C perror() sous POSIX, et FormatMessage() sous Windows.

filename

filename2

Pour les exceptions qui font référence à un chemin d’accès au système de fichiers (comme open() ou os.unlink()), filename est le nom du fichier transmis à la fonction. Pour les fonctions qui font référence à deux chemins d’accès au système de fichiers (comme os.rename()), filename2 correspond au deuxième nom de fichier passé à la fonction.

Modifié dans la version 3.3: EnvironmentError, IOError, WindowsError, socket.error, select.error et mmap.error ont fusionnées en OSError, et le constructeur peut renvoyer une sous-classe.

Modifié dans la version 3.4: L’attribut filename est maintenant le nom du fichier originel passé à la fonction, au lieu du nom encodé ou décodé à partir de l’encodage du système de fichiers. De plus, l’argument du constructeur et attribut filename2 a été ajouté.

exception OverflowError

Levée lorsque le résultat d’une opération arithmétique est trop grand pour être représenté. Cela ne peut pas se produire pour les entiers (qui préfèrent lever MemoryError plutôt que d’abandonner). Cependant, pour des raisons historiques, OverflowError est parfois levée pour des entiers qui sont en dehors d’une plage requise. En raison de l’absence de normalisation de la gestion des exceptions de virgule flottante en C, la plupart des opérations en virgule flottante ne sont pas vérifiées.

exception RecursionError

Cette exception est dérivée de RuntimeError. Elle est levée lorsque l’interpréteur détecte que la profondeur de récursivité maximale (voir sys.getrecursionlimit()) est dépassée.

Nouveau dans la version 3.5: Auparavant, une simple RuntimeError était levée.

exception ReferenceError

Cette exception est levée lorsqu’un pointeur faible d’un objet proxy, créé par la fonction weakref.proxy(), est utilisé pour accéder à un attribut du référent après qu’il ait été récupéré par le ramasse-miettes. Pour plus d’informations sur les pointeurs faibles, voir le module weakref.

exception RuntimeError

Levée lorsqu’une erreur qui n’appartient à aucune des autres catégories est détectée. La valeur associée est une chaîne de caractères indiquant précisément ce qui s’est mal passé.

exception StopIteration

Levée par la fonction native next() et la méthode __next__() d’un iterator (itérateur) pour signaler qu’il n’y a pas d’autres éléments produits par l’itérateur.

L’objet exception a un unique attribut value, qui est donné en argument lors de la construction de l’exception, et vaut None par défaut.

Lorsqu’une fonction de type generator ou coroutine retourne une valeur, une nouvelle instance de StopIteration est levée, et la valeur retournée par la fonction est passée au paramètre value du constructeur de l’exception.

Si une fonction de générateur définie en présence d’une directive from __future__ import generator_stop lève StopIteration, elle est convertie en RuntimeError (en conservant StopIteration comme cause de la nouvelle exception).

Modifié dans la version 3.3: Ajout de l’attribut value et de la possibilité pour les fonctions de générateur de l’utiliser pour retourner une valeur.

Modifié dans la version 3.5: Introduction de la transformation RuntimeError.

exception StopAsyncIteration

Doit être levée par la méthode __anext__() d’un objet asynchronous iterator pour arrêter l’itération.

Nouveau dans la version 3.5.

exception SyntaxError

Levée lorsque l’analyseur syntaxique rencontre une erreur de syntaxe. Cela peut se produire dans une instruction import, dans un appel aux fonctions natives exec() ou eval(), ou lors de la lecture du script initial ou de l’entrée standard (également de manière interactive).

Les instances de cette classe ont des attributs filename, lineno, offset et text pour accéder plus facilement aux détails. La représentation str() de l’instance de l’exception retourne seulement le message.

exception IndentationError

Classe de base pour les erreurs de syntaxe liées à une indentation incorrecte. C’est une sous-classe de SyntaxError.

exception TabError

Levée lorsqu’une indentation contient une utilisation incohérente des tabulations et des espaces. C’est une sous-classe de IndentationError.

exception SystemError

Levée lorsque l’interpréteur trouve une erreur interne, mais que la situation ne semble pas si grave au point de lui faire abandonner tout espoir. La valeur associée est une chaîne de caractères indiquant l’erreur qui est survenue (en termes bas niveau).

Vous devriez le signaler à l’auteur ou au responsable de votre interpréteur Python. Assurez-vous de signaler la version de l’interpréteur (sys.version ; elle est également affichée au lancement d’une session interactive), le message d’erreur exact (la valeur associée à l’exception) et si possible le code source du programme qui a déclenché l’erreur.

exception SystemExit

Cette exception est levée par la fonction sys.exit(). Elle hérite de BaseException au lieu d”Exception pour ne pas qu’elle soit accidentellement capturée par du code qui capture Exception. Cela permet à l’exception de se propager correctement et de faire quitter l’interpréteur. Lorsqu’elle n’est pas gérée, l’interpréteur Python quitte ; aucune trace d’appels n’est affichée. Le constructeur accepte le même argument optionnel passé à sys.exit(). Si la valeur est un entier, elle spécifie l’état de sortie du système (passé à la fonction C exit()) ; si elle est None, l’état de sortie est zéro ; si elle a un autre type (comme une chaîne de caractères), la valeur de l’objet est affichée et l’état de sortie est un.

Un appel à sys.exit() est traduit en une exception pour que les gestionnaires de nettoyage (les clauses finally des instructions try) puissent être exécutés, et pour qu’un débogueur puisse exécuter un script sans courir le risque de perdre le contrôle. La fonction os._exit() peut être utilisée s’il est absolument nécessaire de sortir immédiatement (par exemple, dans le processus enfant après un appel à os.fork()).

code

L’état de sortie ou le message d’erreur passé au constructeur. (None par défaut.)

exception TypeError

Levée lorsqu’une opération ou fonction est appliquée à un objet d’un type inapproprié. La valeur associée est une chaîne de caractères donnant des détails sur le type d’inadéquation.

Cette exception peut être levée par du code utilisateur pour indiquer qu’une tentative d’opération sur un objet n’est pas prise en charge, et n’est pas censée l’être. Si un objet est destiné à prendre en charge une opération donnée mais n’a pas encore fourni une implémentation, lever NotImplementedError est plus approprié.

Le passage d’arguments du mauvais type (e.g. passer une list quand un int est attendu) devrait résulter en un TypeError, mais le passage d’arguments avec la mauvaise valeur (e.g. un nombre en dehors des limites attendues) devrait résulter en une ValueError.

exception UnboundLocalError

Levée lorsqu’une référence est faite à une variable locale dans une fonction ou une méthode, mais qu’aucune valeur n’a été liée à cette variable. C’est une sous-classe de NameError.

exception UnicodeError

Levée lorsqu’une erreur d’encodage ou de décodage liée à Unicode se produit. C’est une sous-classe de ValueError.

UnicodeError a des attributs qui décrivent l’erreur d’encodage ou de décodage. Par exemple, err.object[err.start:err.end] donne l’entrée particulière invalide sur laquelle le codec a échoué.

encoding

Le nom de l’encodage qui a provoqué l’erreur.

reason

Une chaîne de caractères décrivant l’erreur de codec spécifique.

object

L’objet que le codec essayait d’encoder ou de décoder.

start

Le premier index des données invalides dans object.

end

L’index après la dernière donnée invalide dans object.

exception UnicodeEncodeError

Levée lorsqu’une erreur liée à Unicode se produit durant l’encodage. C’est une sous-classe d”UnicodeError.

exception UnicodeDecodeError

Levée lorsqu’une erreur liée à Unicode se produit durant le décodage. C’est une sous-classe d”UnicodeError.

exception UnicodeTranslateError

Levée lorsqu’une erreur liée à Unicode se produit durant la traduction. C’est une sous-classe d”UnicodeError.

exception ValueError

Raised when an operation or function receives an argument that has the right type but an inappropriate value, and the situation is not described by a more precise exception such as IndexError.

exception ZeroDivisionError

Levée lorsque le second argument d’une opération de division ou d’un modulo est zéro. La valeur associée est une chaîne indiquant le type des opérandes et de l’opération.

Les exceptions suivantes sont conservées pour la compatibilité avec les anciennes versions ; depuis Python 3.3, ce sont des alias d”OSError.

exception EnvironmentError

exception IOError

exception WindowsError

Seulement disponible sous Windows.

5.2.1. Exceptions système

Les exceptions suivantes sont des sous-classes d”OSError, elles sont levées en fonction du code d’erreur système.

exception BlockingIOError

Levée lorsqu’une opération bloque sur un objet (par exemple un connecteur) configuré pour une opération non-bloquante. Correspond à errno EAGAIN, EALREADY, EWOULDBLOCK et EINPROGRESS.

En plus de ceux de OSError, BlockingIOError peut avoir un attribut de plus :

characters_written

Un nombre entier contenant le nombre de caractères écrits dans le flux avant qu’il ne soit bloqué. Cet attribut est disponible lors de l’utilisation des classes tampon entrées-sorties du module io.

exception ChildProcessError

Levée lorsqu’une opération sur un processus enfant a échoué. Correspond à errno ECHILD.

exception ConnectionError

Une classe de base pour les problèmes de connexion.

Les sous-classes sont BrokenPipeError, ConnectionAbortedError, ConnectionRefusedError et ConnectionResetError.

exception BrokenPipeError

Une sous-classe de ConnectionError, levé en essayant d’écrire sur un pipe alors que l’autre extrémité a été fermée, ou en essayant d’écrire sur un connecteur (socket en anglais) qui a été fermé pour l’écriture. Correspond à errno EPIPE et ESHUTDOWN.

exception ConnectionAbortedError

Une sous-classe de ConnectionError, levée lorsqu’une tentative de connexion est interrompue par le pair. Correspond à errno ECONNABORTED.

exception ConnectionRefusedError

Une sous-classe de ConnectionError, levée lorsqu’une tentative de connexion est refusée par le pair. Correspond à errno ECONNREFUSED.

exception ConnectionResetError

Une sous-classe de ConnectionError, levée lorsqu’une connexion est réinitialisée par le pair. Correspond à errno ECONNRESET.

exception FileExistsError

Levée en essayant de créer un fichier ou un répertoire qui existe déjà. Correspond à errno EEXIST.

exception FileNotFoundError

Levée lorsqu’un fichier ou répertoire est demandé mais n’existe pas. Correspond à errno ENOENT.

exception InterruptedError

Levée lorsqu’un appel système est interrompu par un signal entrant. Correspond à errno EINTR.

Modifié dans la version 3.5: Python relance maintenant les appels système lorsqu’ils sont interrompus par un signal, sauf si le gestionnaire de signal lève une exception (voir PEP 475 [https://www.python.org/dev/peps/pep-0475] pour les raisons), au lieu de lever InterruptedError.

exception IsADirectoryError

Levée lorsqu’une opération sur un fichier (comme os.remove()) est demandée sur un répertoire. Correspond à errno EISDIR.

exception NotADirectoryError

Levée lorsqu’une opération sur un répertoire (comme os.listdir()) est demandée sur autre chose qu’un répertoire. Correspond à errno ENOTDIR.

exception PermissionError

Levée lorsqu’on essaye d’exécuter une opération sans les droits d’accès adéquats — par exemple les permissions du système de fichiers. Correspond à errno EACCES et EPERM.

exception ProcessLookupError

Levée lorsqu’un processus donné n’existe pas. Correspond à errno ESRCH.

exception TimeoutError

Levée lorsqu’une fonction système a expiré au niveau système. Correspond à errno ETIMEDOUT.

Nouveau dans la version 3.3: Toutes les sous-classes d”OSError ci-dessus ont été ajoutées.

Voir aussi

PEP 3151 [https://www.python.org/dev/peps/pep-3151] – Refonte de la hiérarchie des exceptions système et IO

5.3. Avertissements

Les exceptions suivantes sont utilisées comme catégories d’avertissement ; voir le module warnings pour plus d’informations.

exception Warning

Classe de base pour les catégories d’avertissement.

exception UserWarning

Classe de base pour les avertissements générés par du code utilisateur.

exception DeprecationWarning

Classe de base pour les avertissements sur les fonctionnalités obsolètes.

exception PendingDeprecationWarning

Classe de base pour les avertissements sur les fonctionnalités qui seront obsolètes dans le futur.

exception SyntaxWarning

Classe de base pour les avertissements sur de la syntaxe douteuse.

exception RuntimeWarning

Classe de base pour les avertissements sur les comportements d’exécution douteux.

exception FutureWarning

Classe de base pour les avertissements sur les constructions qui changeront sémantiquement dans le futur.

exception ImportWarning

Classe de base pour les avertissements sur des erreurs probables dans les importations de modules.

exception UnicodeWarning

Classe de base pour les avertissements liés à l’Unicode.

exception BytesWarning

Classe de base pour les avertissements liés à bytes et bytearray.

exception ResourceWarning

Classe de base pour les avertissements liés à l’utilisation de ressources.

Nouveau dans la version 3.2.

5.4. Hiérarchie des exceptions

La hiérarchie de classes pour les exceptions natives est la suivante :

BaseException
 +-- SystemExit
 +-- KeyboardInterrupt
 +-- GeneratorExit
 +-- Exception
      +-- StopIteration
      +-- StopAsyncIteration
      +-- ArithmeticError
      |    +-- FloatingPointError
      |    +-- OverflowError
      |    +-- ZeroDivisionError
      +-- AssertionError
      +-- AttributeError
      +-- BufferError
      +-- EOFError
      +-- ImportError
      |    +-- ModuleNotFoundError
      +-- LookupError
      |    +-- IndexError
      |    +-- KeyError
      +-- MemoryError
      +-- NameError
      |    +-- UnboundLocalError
      +-- OSError
      |    +-- BlockingIOError
      |    +-- ChildProcessError
      |    +-- ConnectionError
      |    |    +-- BrokenPipeError
      |    |    +-- ConnectionAbortedError
      |    |    +-- ConnectionRefusedError
      |    |    +-- ConnectionResetError
      |    +-- FileExistsError
      |    +-- FileNotFoundError
      |    +-- InterruptedError
      |    +-- IsADirectoryError
      |    +-- NotADirectoryError
      |    +-- PermissionError
      |    +-- ProcessLookupError
      |    +-- TimeoutError
      +-- ReferenceError
      +-- RuntimeError
      |    +-- NotImplementedError
      |    +-- RecursionError
      +-- SyntaxError
      |    +-- IndentationError
      |         +-- TabError
      +-- SystemError
      +-- TypeError
      +-- ValueError
      |    +-- UnicodeError
      |         +-- UnicodeDecodeError
      |         +-- UnicodeEncodeError
      |         +-- UnicodeTranslateError
      +-- Warning
           +-- DeprecationWarning
           +-- PendingDeprecationWarning
           +-- RuntimeWarning
           +-- SyntaxWarning
           +-- UserWarning
           +-- FutureWarning
           +-- ImportWarning
           +-- UnicodeWarning
           +-- BytesWarning
           +-- ResourceWarning

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6. Services de Manipulation de Texte

Les modules décrits dans ce chapitre fournissent un large ensemble d’opérations de manipulation sur les chaînes de caractères et le texte en général.

Le module codecs documenté dans Services autour des Données Binaires est aussi très pertinent pour la manipulation de texte. Consultez aussi la documentation du type str natif Python dans Type Séquence de Texte — str.

6.1. string — Opérations usuelles sur des chaînes

6.1.1. Chaînes constantes

6.1.2. Formatage personnalisé de chaîne

6.1.3. Syntaxe de formatage de chaîne

6.1.3.1. Mini-langage de spécification de format

6.1.3.2. Exemples de formats

6.1.4. Chaînes modèles

6.1.5. Fonctions d’assistance

6.2. re — Opérations à base d’expressions rationnelles

6.2.1. Syntaxe des expressions rationnelles

6.2.2. Contenu du module

6.2.3. Objets d’expressions rationnelles

6.2.4. Objets de correspondance

6.2.5. Exemples d’expressions rationnelles

6.2.5.1. Rechercher une paire

6.2.5.2. Simuler scanf()

6.2.5.3. search() vs. match()

6.2.5.4. Construire un répertoire téléphonique

6.2.5.5. Mélanger les lettres des mots

6.2.5.6. Trouver tous les adverbes

6.2.5.7. Trouver tous les adverbes et leurs positions

6.2.5.8. Notation brutes de chaînes

6.2.5.9. Écrire un analyseur lexical

6.3. difflib — Helpers for computing deltas

6.3.1. SequenceMatcher Objects

6.3.2. SequenceMatcher Examples

6.3.3. Differ Objects

6.3.4. Differ Example

6.3.5. A command-line interface to difflib

6.4. textwrap — Encapsulation et remplissage de texte

6.5. unicodedata — Base de données Unicode

6.6. stringprep — Préparation des chaines de caractères internet

6.7. readline — interface pour GNU readline

6.7.1. Fichier d’initialisation

6.7.2. Tampon de ligne

6.7.3. Fichier d’historique

6.7.4. Liste d’historique

6.7.5. Fonctions de rappel au démarrage

6.7.6. Complétion

6.7.7. Exemple

6.8. rlcompleter — Fonction de complétion pour GNU readline

6.8.1. Objets pour la complétion (Completer Objects)

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6.1. string — Opérations usuelles sur des chaînes

Code source : Lib/string.py [https://github.com/python/cpython/tree/3.6/Lib/string.py]

Voir aussi

Type Séquence de Texte — str

Méthodes de chaînes de caractères

6.1.1. Chaînes constantes

Les constantes définies dans ce module sont :

string.ascii_letters

La concaténation des constantes ascii_lowercase et ascii.uppercase décrites ci-dessous. Cette valeur n’est pas dépendante de l’environnement linguistique.

string.ascii_lowercase

Les lettres minuscules 'abcdefghijklmnopqrstuvwxyz'. Cette valeur de dépend pas de l’environnement linguistique et ne changera pas.

string.ascii_uppercase

Les lettres majuscules 'ABCDEFGHIJKLMNOPQRSTUVWXYZ'. Cette valeur de dépend pas de l’environnement linguistique et ne changera pas.

string.digits

La chaîne '0123456789'.

string.hexdigits

La chaîne '0123456789abcdefABCDEF'.

string.octdigits

La chaîne '01234567.

string.punctuation

Chaîne de caractères ASCII considérés comme ponctuation dans l’environnement linguistique C.

string.printable

Chaîne de caractères ASCII considérés comme affichables. C’est une combinaison de digits, ascii_letters, punctuation, et whitespace.

string.whitespace

Une chaîne comprenant tous les caractères ASCII considérés comme espaces. Sont inclus les caractères espace, tabulations, saut de ligne, retour du chariot, saut de page, et tabulation verticale.

6.1.2. Formatage personnalisé de chaîne

La classe primitive string fournit la possibilité de faire des substitutions de variables complexes et du formatage de valeurs via la méthode format() décrite par PEP 3101 [https://www.python.org/dev/peps/pep-3101]. La classe Formatter dans le module string permet de créer et personnaliser vos propres comportements de formatage de chaînes en utilisant la même implémentation que la méthode primitive format().

class string.Formatter

La classe Formatter a les méthodes publiques suivantes :

format(format_string, *args, **kwargs)

La méthode principale de l’API. Elle prend une chaîne de format et un ensemble arbitraire d’arguments positions et mot-clefs. C’est uniquement un conteneur qui appelle vformat().

Obsolète depuis la version 3.5: Passer la chaîne de format comme argument mot-clef format_string est obsolète.

vformat(format_string, args, kwargs)

Cette fonction fait le travail effectif du formatage. Elle existe comme méthode séparée au cas où vous voudriez passer un dictionnaire d’arguments prédéfini plutôt que décompresser et recompresser le dictionnaire en arguments individuels en utilisant la syntaxe *args et **kwargs. vformat() s’occupe de découper la chaîne de format en données de caractères et champs de remplacement. Elle appelle les différentes méthodes décrites ci-dessous.

De plus, la classe Formatter définit un certain nombre de méthodes qui ont pour vocation d’être remplacées par des sous-classes :

parse(format_string)

Boucle sur la chaîne de format et renvoie un itérable de tuples (literal_text, field_name, format_spec, conversion). Ceci est utilisé par vformat() pour découper la chaîne de format en littéraux ou en champs de remplacement.

Les valeurs dans le tuple représentent conceptuellement un ensemble de littéraux suivis d’un unique champ de remplacement. S’il n’y a pas de littéral, (ce qui peut arriver si deux champs de remplacement sont placés côte à côte), alors literal_text est une chaîne vide. S’il n’y a pas de champ de remplacement, les valeurs field_name, format_spec et conversion sont mises à None.

get_field(field_name, args, kwargs)

Récupère le champ field_name du tuple renvoyé par parse() (voir ci-dessus), le convertit en un objet à formater. Renvoie un tuple (obj, used_key). La version par défaut prend une chaîne de la forme définie par PEP 3101 [https://www.python.org/dev/peps/pep-3101], telle que « 0[name] » ou « label.title ». args et kwargs sont tels que ceux passés à vformat(). La valeur renvoyée used_key a le même sens que le paramètre key de get_value().

get_value(key, args, kwargs)

Récupère la valeur d’un champ donné. L’argument key est soit un entier, soit une chaîne. Si c’est un entier, il représente l’indice de la l’argument dans args. Si c’est une chaîne de caractères, elle représente le nom de l’argument dans kwargs.

Le paramètre args est défini par la liste des arguments positionnels de vformat(), et le paramètre kwargs est défini par le dictionnaire des arguments mot-clefs.

Pour les noms de champs composés, ces fonctions sont uniquement appelées sur la première composante du nom. Les composantes suivantes sont manipulées au travers des attributs normaux et des opérations sur les indices.

Donc par exemple, le champ-expression 0.name amènerait get_value() à être appelée avec un argument key valant 0. L’attribut name sera recherché après l’appel get_value() en faisant appel à la primitive getattr().

Si l’indice ou le mot-clef fait référence à un objet qui n’existe pas, alors une exception IndexError ou KeyError doit être levée.

check_unused_args(used_args, args, kwargs)

Implémente une vérification pour les arguments non utilisés si désiré. L’argument de cette fonction est l’ensemble des clefs qui ont été effectivement référencées dans la chaîne de format (des entiers pour les indices et des chaînes de caractères pour les arguments nommés), et une référence vers les arguments args et kwargs qui ont été passés à vformat. L’ensemble des arguments non utilisés peut être calculé sur base de ces paramètres. check_unused_args() est censée lever une exception si la vérification échoue.

format_field(value, format_spec)

La méthode format_field() fait simplement appel à la primitive globale format(). Cette méthode est fournie afin que les sous-classes puisse la redéfinir.

convert_field(value, conversion)

Convertit la valeur (renvoyée par get_field()) selon un type de conversion donné (comme dans le tuple renvoyé par la méthode parse()). La version par défaut comprend “s” (str), “r” (repr) et “a” (ASCII) comme types de conversion.

6.1.3. Syntaxe de formatage de chaîne

La méthode str.format() et la classe Formatter partagent la même syntaxe pour les chaînes de formatage (bien que dans le cas de Formatter les sous-classes puissent définir leur propre syntaxe). La syntaxe est liée à celle des chaînes de formatage littérales, mais il y a quelques différences.

Les chaînes de formatage contiennent des « champs de remplacement » entourés d’accolades {}. Tout ce qui n’est pas placé entre deux accolades est considéré comme littéral, qui est copié tel quel dans le résultat. Si vous avez besoin d’inclure une accolade en littéral, elles peuvent être échappées en les doublant : {{ et }}.

La grammaire pour un champ de remplacement est défini comme suit :

replacement_field ::=  "{" [field_name] ["!" conversion] [":" format_spec] "}"
field_name        ::=  arg_name ("." attribute_name | "[" element_index "]")*
arg_name          ::=  [identifier | digit+]
attribute_name    ::=  identifier
element_index     ::=  digit+ | index_string
index_string      ::=  <any source character except "]"> +
conversion        ::=  "r" | "s" | "a"
format_spec       ::=  <described in the next section>

En termes moins formels, un champ de remplacement peut débuter par un field_name qui spécifie l’objet dont la valeur va être formatée et insérée dans le résultat à l’endroit du champ de remplacement Le field_name peut éventuellement être suivi d’un champ conversion qui est précédé d’un point d’exclamation '!', et d’un format_spec qui est précédé par deux-points ':'. Cela définit un format personnalisé pour le remplacement d’une valeur.

Voir également la section Mini-langage de spécification de format.

Le champ field_name débute par un arg_name qui est soit un nombre, soit un mot-clef. Si c’est un nombre, il fait référence à un des arguments positionnels et si c’est un mot-clef, il fait référence à un des arguments nommés. Si les valeurs numériques de arg_name dans une chaîne de format sont 0, 1, 2, … dans l’ordre, elles peuvent être omises (toutes ou aucune), et les nombres 0, 1, 2, … seront automatiquement insérés dans cet ordre. Puisque arg_name n’est pas délimité par des guillemets, il n’est pas possible de spécifier des clefs de dictionnaire arbitraires (par exemple les chaînes '10' ou ':-]') dans une chaîne de format. La valeur arg_name peut être suivie par un nombre d’indices ou d’expressions quelconque. Une expression de la forme '.name' sélectionne l’attribut nommé en utilisant getattr() alors qu’une expression de la forme '[index]' recherche l’indice en utilisant __getitem__().

Modifié dans la version 3.1: Les spécificateurs de position d’argument peuvent être omis dans les appels à str.format(). Donc '{} {}'.format(a, b) est équivalent à '{0} {1}'.format(a, b).

Modifié dans la version 3.4: Les spécificateurs de position d’argument peuvent être omis pour Formatter.

Quelques exemples simples de formatage de chaînes :

"First, thou shalt count to {0}"  # References first positional argument
"Bring me a {}"                   # Implicitly references the first positional argument
"From {} to {}"                   # Same as "From {0} to {1}"
"My quest is {name}"              # References keyword argument 'name'
"Weight in tons {0.weight}"       # 'weight' attribute of first positional arg
"Units destroyed: {players[0]}"   # First element of keyword argument 'players'.

Le champ conversion crée une contrainte de type avant de formater. Normalement, le travail de formatage d’une valeur est fait par la méthode __format__() de la valeur elle-même. Cependant, dans certains cas, il est désirable de forcer un type à être formaté en une chaîne, en ré-définissant sa propre définition de formatage. En convertissant une valeur en chaîne de caractère avant d’appeler la méthode __format__(), on outrepasse la logique usuelle de formatage.

Actuellement, trois indicateurs sont gérés : '!s' qui appelle la fonction str() sur la valeur, '!r' qui appelle la fonction repr() et !a qui appelle la fonction ascii().

Quelques exemples :

"Harold's a clever {0!s}"        # Calls str() on the argument first
"Bring out the holy {name!r}"    # Calls repr() on the argument first
"More {!a}"                      # Calls ascii() on the argument first

Le champ format_spec contient une spécification sur la manière selon laquelle la valeur devrait être représentée : des informations telles que la longueur du champ, l’alignement, le remplissage, la précision décimale, etc. Chaque type peut définir son propre « mini-langage de formatage » ou sa propre interprétation de format_spec.

La plupart des types natifs gèrent un mini-langage de formatage usuel qui est décrit dans la section suivante.

Un champ format_spec peut contenir un champ de remplacement imbriqué. Ces champs de remplacement imbriqués peuvent contenir un nom de champ, un indicateur de conversion, mais une imbrication récursive plus profonde n’est pas permise. Les champs de remplacement au sein de format_spec sont substitués avant que la chaîne format_spec ne soit interprétée. Cela permet que le formatage d’une valeur soit dynamiquement spécifié.

Voir la section Exemples de formats pour des exemples.

6.1.3.1. Mini-langage de spécification de format

Les « Spécifications de format » sont utilisées avec les champs de remplacement contenus dans les chaînes de formatage, pour définir comment les valeurs doivent être représentées (voir Syntaxe de formatage de chaîne et Chaînes de caractères formatées littérales). Elles peuvent aussi être passées directement à la fonction native format(). Chaque type formatable peut définir comment les spécifications sur les valeurs de ce type doivent être interprétées.

La plupart des primitives implémentent les les options suivantes, même si certaines options de formatage ne sont supportées que pour les types numériques.

Une convention généralement admise est qu’une chaîne vide ("") produit le même résultat que si vous aviez appelé str() sur la valeur. Une chaîne de format non vide modifie typiquement le résultat.

La forme générale d’un spécificateur de format standard est :

format_spec     ::=  [[fill]align][sign][#][0][width][grouping_option][.precision][type]
fill            ::=  <any character>
align           ::=  "<" | ">" | "=" | "^"
sign            ::=  "+" | "-" | " "
width           ::=  digit+
grouping_option ::=  "_" | ","
precision       ::=  digit+
type            ::=  "b" | "c" | "d" | "e" | "E" | "f" | "F" | "g" | "G" | "n" | "o" | "s" | "x" | "X" | "%"

Si une valeur valide est spécifiée pour align, elle peut être précédée par un caractère fill, qui peut être n’importe quel caractère (espace par défaut si la valeur est omise). Il n’est pas possible d’utiliser une accolade littérale (« { » ou « } ») comme caractère fill dans une chaîne de formatage littérale ou avec la méthode str.format(). Cependant, il est possible d’insérer une accolade à l’aide d’un champ de remplacement imbriqué. Cette limitation n’affecte pas la fonction format().

Le sens des différentes options d’alignement est donné comme suit :

Option

Signification

'<'

Force le champ à être aligné à gauche dans l’espace disponible (c’est le spécificateur par défaut pour la plupart des objets).

'>'

Force le champ à être aligné à droite dans l’espace disponible (c’est le spécificateur par défaut pour les nombres).

'='

Force le remplissage (padding) à être placé après le signe (si signe il y a) mais avant les chiffres. L’option est utilisée pour afficher les champs sous la forme « +000000120 ». Cette option d’alignement est valide uniquement pour les types numériques. Elle devient activée par défaut quand « 0 » précède directement la largeur de champ.

'^'

Force le champ à être centré dans l’espace disponible.

Notons que la longueur du champ est toujours égale à la la taille nécessaire pour remplir le champ avec l’objet à moins que la valeur minimum ne soit précisée. Ainsi, si aucune valeur n’est précisée, l’option d’alignement n’a aucun sens.

L’option sign est uniquement valide pour les type numériques, et peut valoir :

Option

Signification

'+'

indique que le signe doit être affiché pour les nombres tant positifs que négatifs.

'-'

indique que le signe doit être affiché uniquement pour les nombres négatifs (c’est le comportement par défaut).

espace

indique qu’un espace doit précéder les nombres positifs et qu’un signe moins doit précéder les nombres négatifs.

L’option '#' impose l’utilisation de la « forme alternative » pour la conversion. La forme alternative est définie différemment pour différent types. Cette option est uniquement valide pour les types entiers flottants, complexes, et décimaux. Pour les entiers, quand l’affichage binaire, octal ou hexadécimal est utilisé, cette option ajoute le préfixe '0b', '0o', ou '0x' à la valeur affichée. Pour les flottants, les complexes, et les décimaux, la forme alternative impose que le résultat de la conversion contienne toujours une virgule, même si aucun chiffre ne vient après. Normalement, une virgule apparaît dans le résultat de ces conversions seulement si un chiffre le suit. De plus, pour les conversions 'g' et 'G', les zéros finaux ne sont pas retirés du résultat.

L’option ',' signale l’utilisation d’une virgule comme séparateur des milliers. Pour un séparateur conscient de l’environnement linguistique, utilisez plutôt le type de présentation entière 'n'.

Modifié dans la version 3.1: Ajout de l’option ',' (voir PEP 378 [https://www.python.org/dev/peps/pep-0378]).

L’option '_' demande l’utilisation d’un tiret bas comme séparateur des milliers pour les représentations de nombres flottants et pour les entiers représentés par le type 'd'. Pour les types de représentation d’entiers 'b', 'o', 'x' et 'X', les tirets bas seront insérés tous les 4 chiffres. Pour les autres types de représentation, spécifier cette option est une erreur.

Modifié dans la version 3.6: Ajout de l’option '_' (voir aussi PEP 515 [https://www.python.org/dev/peps/pep-0515]).

width est un entier en base 10 qui définit la longueur minimale du champ. Si elle n’est pas spécifiée, alors le champ width est déterminé par le contenu.

Quand aucun alignement explicite n’est donné, précéder le champs width d’un caractère zéro ('0') active le remplissage par zéro des types numériques selon leur signe. Cela est équivalent à un caractère de remplissage fill valant '0' avec le type d’alignement alignment valant '='.

La valeur precision est un nombre en base 10 indiquant combien de chiffres doivent être affichés après la virgule pour une valeur à virgule flottante formatée avec 'f' ou 'F', ou avant et après le point-décimal pour une valeur à virgule flottante formatée avec 'g' ou 'G'. Pour les types non numériques, ce champ indique la taille maximale du champ, autrement dit, combien de caractères du champ sont utilisés. Le spécificateur precision n’est pas autorisé sur les entiers.

Finalement, le spécificateur type détermine comment la donnée doit être représentée.

Les types disponibles de représentation de chaîne sont :

Type

Signification

's'

Format de chaîne. C’est le type par défaut pour les chaînes de caractères et peut être omis.

None

Pareil que 's'.

Les types disponibles de représentation d’entier sont :

Type

Signification

'b'

Format binaire. Affiche le nombre en base 2.

'c'

Caractère. Convertit l’entier en le caractère Unicode associé avant de l’afficher.

'd'

Entier décimal. Affiche le nombre en base 10.

'o'

Format octal. Affiche le nombre en base 8.

'x'

Hex format. Outputs the number in base 16, using lower-case letters for the digits above 9.

'X'

Hex format. Outputs the number in base 16, using upper-case letters for the digits above 9.

'n'

Nombre. Pareil que 'd' si ce n’est que l’environnement linguistique est utilisé afin de déterminer le séparateur de nombres approprié.

None

Pareil que 'd'.

En plus des types de représentation ci-dessus, les entiers peuvent aussi être formatés avec les types de représentation des flottants listés ci-dessous (à l’exception de 'n' et None). Dans ce cas, la fonction float() est utilisée pour convertir l’entier en flottant avant le formatage.

Les types de représentation pour les nombres flottants et les valeurs décimales sont :

Type

Signification

'e'

Notation par exposant. Affiche le nombre dans sa notation scientifique en utilisant la lettre “e” pour indiquer l’exposant. La précision par défaut est 6.

'E'

Notation par exposant. Pareil que 'e' sauf l’utilisation de la lettre majuscule “E” comme séparateur.

'f'

Fixed-point notation. Displays the number as a fixed-point number. The default precision is 6.

'F'

Fixed-point notation. Same as 'f', but converts nan to NAN and inf to INF.

'g'

Format général. Pour une précision donnée p >= 1, ceci arrondit le nombre à p chiffres significatifs et puis formate le résultat soit en virgule fixe soit en notation scientifique, en fonction de la magnitude.

Les règles précises sont les suivantes : supposons que le résultat formaté avec le type de représentation 'e' et une précision 1 ait un exposant exp. Alors, si -4 <= exp <= p, le nombre est formaté avec le type de représentation 'f' et une précision p-1-exp. Sinon, le nombre est formaté avec le type de représentation 'e' et une précision p-1. Dans les deux cas, les zéros finaux et non significatifs sont retirés, et la virgule est également retirée s’il n’y a aucun chiffre la suivant.

Les valeurs suivantes : infini négatif, infini positif, zéro positif, zéro négatif, not a number sont formatées respectivement par inf, -inf, 0, -0 et nan, peu importe la précision.

Une précision de 0 est interprétée comme une précision de 1. La précision par défaut est 6.

'G'

Format général. Pareil que 'G' si ce n’est que 'E' est utilisé si le nombre est trop grand. Également, la représentation des infinis et de Nan sont en majuscules également.

'n'

Nombre. Pareil que 'g', si ce n’est que l’environnement linguistique est pris en compte pour insérer le séparateur approprié.

'%'

Pourcentage. Multiplie le nombre par 100 et l’affiche en virgule fixe ('f'), suivi d’un symbole pourcent '%'.

None

Pareil que 'g', si ce n’est que lorsque la notation en virgule fixe est utilisée, il y a toujours au moins un chiffre derrière la virgule. La précision par défaut celle nécessaire pour afficher la valeur donnée. L’effet visé est de le faire correspondre à la valeur renvoyée par str() altérée par les autres modificateurs de format.

6.1.3.2. Exemples de formats

Cette section contient des exemples de la syntaxe de str.format() et des comparaisons avec l’ancien formatage par %.

Dans la plupart des cases, la syntaxe est similaire à l’ancien formatage par %, avec l’ajout de {} et avec : au lieu de %. Par exemple : '%03.2f' peut être changé en '{03.2f}'.

The new format syntax also supports new and different options, shown in the following examples.

Accéder à un argument par sa position :

>>> '{0}, {1}, {2}'.format('a', 'b', 'c')
'a, b, c'
>>> '{}, {}, {}'.format('a', 'b', 'c')  # 3.1+ only
'a, b, c'
>>> '{2}, {1}, {0}'.format('a', 'b', 'c')
'c, b, a'
>>> '{2}, {1}, {0}'.format(*'abc')      # unpacking argument sequence
'c, b, a'
>>> '{0}{1}{0}'.format('abra', 'cad')   # arguments' indices can be repeated
'abracadabra'

Accéder à un argument par son nom :

>>> 'Coordinates: {latitude}, {longitude}'.format(latitude='37.24N', longitude='-115.81W')
'Coordinates: 37.24N, -115.81W'
>>> coord = {'latitude': '37.24N', 'longitude': '-115.81W'}
>>> 'Coordinates: {latitude}, {longitude}'.format(**coord)
'Coordinates: 37.24N, -115.81W'

Accéder aux attributs d’un argument :

>>> c = 3-5j
>>> ('The complex number {0} is formed from the real part {0.real} '
...  'and the imaginary part {0.imag}.').format(c)
'The complex number (3-5j) is formed from the real part 3.0 and the imaginary part -5.0.'
>>> class Point:
...     def __init__(self, x, y):
...         self.x, self.y = x, y
...     def __str__(self):
...         return 'Point({self.x}, {self.y})'.format(self=self)
...
>>> str(Point(4, 2))
'Point(4, 2)'

Accéder aux éléments d’un argument :

>>> coord = (3, 5)
>>> 'X: {0[0]};  Y: {0[1]}'.format(coord)
'X: 3;  Y: 5'

Remplacer %s et %r :

>>> "repr() shows quotes: {!r}; str() doesn't: {!s}".format('test1', 'test2')
"repr() shows quotes: 'test1'; str() doesn't: test2"

Aligner le texte et spécifier une longueur minimale :

>>> '{:<30}'.format('left aligned')
'left aligned                  '
>>> '{:>30}'.format('right aligned')
'                 right aligned'
>>> '{:^30}'.format('centered')
'           centered           '
>>> '{:*^30}'.format('centered')  # use '*' as a fill char
'***********centered***********'

Remplacer %+f, %-f, et %f et spécifier un signe :

>>> '{:+f}; {:+f}'.format(3.14, -3.14)  # show it always
'+3.140000; -3.140000'
>>> '{: f}; {: f}'.format(3.14, -3.14)  # show a space for positive numbers
' 3.140000; -3.140000'
>>> '{:-f}; {:-f}'.format(3.14, -3.14)  # show only the minus -- same as '{:f}; {:f}'
'3.140000; -3.140000'

Remplacer %x et %o et convertir la valeur dans différentes bases :

>>> # format also supports binary numbers
>>> "int: {0:d};  hex: {0:x};  oct: {0:o};  bin: {0:b}".format(42)
'int: 42;  hex: 2a;  oct: 52;  bin: 101010'
>>> # with 0x, 0o, or 0b as prefix:
>>> "int: {0:d};  hex: {0:#x};  oct: {0:#o};  bin: {0:#b}".format(42)
'int: 42;  hex: 0x2a;  oct: 0o52;  bin: 0b101010'

Utiliser une virgule comme séparateur des milliers :

>>> '{:,}'.format(1234567890)
'1,234,567,890'

Exprimer un pourcentage :

>>> points = 19
>>> total = 22
>>> 'Correct answers: {:.2%}'.format(points/total)
'Correct answers: 86.36%'

Utiliser un formatage propre au type :

>>> import datetime
>>> d = datetime.datetime(2010, 7, 4, 12, 15, 58)
>>> '{:%Y-%m-%d %H:%M:%S}'.format(d)
'2010-07-04 12:15:58'

Arguments imbriqués et des exemples plus complexes :

>>> for align, text in zip('<^>', ['left', 'center', 'right']):
...     '{0:{fill}{align}16}'.format(text, fill=align, align=align)
...
'left<<<<<<<<<<<<'
'^^^^^center^^^^^'
'>>>>>>>>>>>right'
>>>
>>> octets = [192, 168, 0, 1]
>>> '{:02X}{:02X}{:02X}{:02X}'.format(*octets)
'C0A80001'
>>> int(_, 16)
3232235521
>>>
>>> width = 5
>>> for num in range(5,12):
...     for base in 'dXob':
...         print('{0:{width}{base}}'.format(num, base=base, width=width), end=' ')
...     print()
...
    5     5     5   101
    6     6     6   110
    7     7     7   111
    8     8    10  1000
    9     9    11  1001
   10     A    12  1010
   11     B    13  1011

6.1.4. Chaînes modèles

Template strings provide simpler string substitutions as described in PEP 292 [https://www.python.org/dev/peps/pep-0292]. A primary use case for template strings is for internationalization (i18n) since in that context, the simpler syntax and functionality makes it easier to translate than other built-in string formatting facilities in Python. As an example of a library built on template strings for i18n, see the flufl.i18n [http://flufli18n.readthedocs.io/en/latest/] package.

Template strings support $-based substitutions, using the following rules:

$$ est un échappement ; il est remplacé par un simple $.

$identifier dénomme un substituant lié à la clef "identifier". Par défaut, "identifier" est restreint à toute chaîne de caractères ASCII alphanumériques sensibles à la casse (avec les underscores) commençant avec un underscore ou un caractère alphanumérique. Le premier caractère n’étant pas un identifieur après le $ termine la spécification du substituant.

${identifier} est équivalent à $identifier. Cette notation est requise quand un caractère valide pour une clef de substituant suit directement le substituant mais ne fait pas partie du substituant, comme "${noun}ification".

Tout autre présence du symbole $ dans une chaîne résultera en la levée d’une ValueError.

Le module string fournit une classe Template qui implémente ces règles. Les méthodes de Template sont :

class string.Template(template)

Le constructeur prend un seul argument qui est la chaîne du template.

substitute(mapping, **kwds)

Applique les substitutions du template, et la renvoie dans une nouvelle chaîne. mapping est un objet dictionnaire-compatible qui lie les substituants dans le template. De même, vous pouvez fournir des arguments mot-clefs tels que les mot-clefs sont les substituants. Quand à la fois mapping et kwds sont donnés et qu’il y a des doublons, les substituants de kwds sont prioritaires.

safe_substitute(mapping, **kwds)

Comme substitute(), si ce n’est qu’au lieu de lever une KeyError si un substituant n’est ni dans mapping, ni dans kwds, c’est le nom du substituant inchangé qui apparaît dans la chaîne finale. Également, à l’inverse de substitute(), toute autre apparition de $ renverra simplement $ au lieu de lever une exception ValueError.

While other exceptions may still occur, this method is called « safe » because it always tries to return a usable string instead of raising an exception. In another sense, safe_substitute() may be anything other than safe, since it will silently ignore malformed templates containing dangling delimiters, unmatched braces, or placeholders that are not valid Python identifiers.

Les instances de la classe Template fournissent également un attribut public :

template

C’est l’objet template passé comme argument au constructeur. En général, vous ne devriez pas le changer, mais un accès en lecture-seule n’est pas possible à fournir.

Voici un exemple de comment utiliser un Template :

>>> from string import Template
>>> s = Template('$who likes $what')
>>> s.substitute(who='tim', what='kung pao')
'tim likes kung pao'
>>> d = dict(who='tim')
>>> Template('Give $who $100').substitute(d)
Traceback (most recent call last):
...
ValueError: Invalid placeholder in string: line 1, col 11
>>> Template('$who likes $what').substitute(d)
Traceback (most recent call last):
...
KeyError: 'what'
>>> Template('$who likes $what').safe_substitute(d)
'tim likes $what'

Usage avancé : vous pouvez faire dériver vos sous-classes de Template pour personnaliser la syntaxe des substituants, les caractères délimiteurs, ou l’entièreté de l’expression rationnelle utilisée pour analyser les chaînes templates. Pour faire cela, vous pouvez redéfinir les attributs suivants :

delimiter – La chaîne littérale décrivant le délimiteur pour introduire un substituant. Sa valeur par défaut ests $. Notez qu’il ne doit pas être une expression rationnelle, puisque l’implémentation appellera re.escape() sur cette chaîne si nécessaire.

idpattern – L’expression rationnelle décrivant le motif pour les substituants non entourés d’accolades (les accolades sont ajoutées automatiquement si c’est approprié). La valeur par défaut de cette expression rationnelle est (?-i:[_a-zA-Z][_a-zA-Z0-9]*).

Note

Puisque par défaut flags vaut re.IGNORECASE, des caractères non-ASCII peuvent correspondre au motif [a-z]. C’est pourquoi on utilise une option locale -i ici.

Bien que flags reste par défaut à re.IGNORECASE pour des raisons de compatibilité descendente, vous pouvez le mettre à 0 ou re.IGNORECASE | re.ASCII si vous en héritez.

flags – L’indicateur d’expression rationnelle qui sera appliqué lors de la compilation de l’expression rationnelle pour reconnaître les substitutions. La valeur par défaut est re.IGNORECASE. Notez que re.VERBOSE sera toujours ajouté à l’indicateur. Donc, un idpattern personnalisé doit suivre les conventions des expressions rationnelles verbose.

Nouveau dans la version 3.2.

Également, vous pouvez fournir le motif d’expression rationnelle en entier en redéfinissant l’attribut pattern. Si vous faites cela, la valeur doit être un objet “expression rationnelle” avec quatre groupes de capture de noms. Les groupes de capture correspondent aux règles données au-dessus, ainsi qu’à la règle du substituant invalide :

escaped – Ce groupe lie les séquences échappées (par exemple $$) dans le motif par défaut.

named – Ce groupe lie les substituants non entourés d’accolades ; il ne devrait pas inclure le délimiteur dans le groupe de capture.

braced – Ce groupe lie le nom entouré d’accolades ; il ne devrait inclure ni le délimiteur, ni les accolades dans le groupe de capture.

invalid – Ce groupe lie tout autre motif de délimitation (habituellement, un seul délimiteur) et il devrait apparaître en dernier dans l’expression rationnelle.

6.1.5. Fonctions d’assistance

string.capwords(s, sep=None)

Divise l’argument en mots en utilisant str.split(), capitalise chaque mot en utilisant str.capitalize() et assemble les mots capitalisés en utilisant str.join(). Si le second argument optionnel sep est absent ou vaut None, les séquences de caractères blancs sont remplacées par un seul espace et les espaces débutant et finissant la chaîne sont retirés. Sinon, sep et utilisé pour séparer et ré-assembler les mots.

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6.2. re — Opérations à base d’expressions rationnelles

Code source : Lib/re.py [https://github.com/python/cpython/tree/3.6/Lib/re.py]

Ce module fournit des opérations sur les expressions rationnelles similaires à celles que l’on trouve dans Perl.

Les motifs, comme les chaînes, à analyser peuvent aussi bien être des chaînes Unicode (str) que des chaînes 8-bits (bytes). Cependant, les chaînes Unicode et 8-bits ne peuvent pas être mélangées : c’est à dire que vous ne pouvez pas analyser une chaîne Unicode avec un motif 8-bit, et inversement ; de même, lors d’une substitution, la chaîne de remplacement doit être du même type que le motif et la chaîne analysée.

Les expressions rationnelles utilisent le caractère backslash ('\') pour indiquer des formes spéciales ou permettre d’utiliser des caractères spéciaux sans en invoquer le sens. Cela entre en conflit avec l’utilisation en Python du même caractère pour la même raison dans les chaînes littérales ; par exemple, pour rechercher un backslash littéral il faudrait écrire '\\\\' comme motif, parce que l’expression rationnelle devrait être \\ et chaque backslash doit être représenté par \\ au sein des chaînes littérales Python.

La solution est d’utiliser la notation des chaînes brutes en Python pour les expressions rationnelles ; Les backslashs ne provoquent aucun traitement spécifique dans les chaînes littérales préfixées par 'r'. Ainsi, r"\n" est une chaîne de deux caractères contenant '\' et 'n', tandis que "\n" est une chaîne contenant un unique caractère : un saut de ligne. Généralement, les motifs seront exprimés en Python à l’aide de chaînes brutes.

Il est important de noter que la plupart des opérations sur les expressions rationnelles sont disponibles comme fonctions au niveau du module et comme méthodes des expressions rationnelles compilées. Les fonctions sont des raccourcis qui ne vous obligent pas à d’abord compiler un objet regex, mais auxquelles manquent certains paramètres de configuration fine.

Voir aussi

Le module tiers regex [https://pypi.org/project/regex/], dont l’interface est compatible avec le module re de la bibliothèque standard, mais offre des fonctionnalités additionnelles et une meilleure gestion de l’Unicode.

6.2.1. Syntaxe des expressions rationnelles

Une expression rationnelle (regular expression ou RE) spécifie un ensemble de chaînes de caractères qui lui correspondent ; les fonctions de ce module vous permettent de vérifier si une chaîne particulière correspond à une expression rationnelle donnée (ou si un expression rationnelle donnée correspond à une chaîne particulière, ce qui revient à la même chose).

Les expressions rationnelles peuvent être concaténées pour former de nouvelles expressions : si A et B sont deux expressions rationnelles, alors AB est aussi une expression rationnelle. En général, si une chaîne p valide A et qu’une autre chaîne q valide B, la chaîne pq validera AB. Cela est vrai tant que A et B ne contiennent pas d’opérations de priorité ; de conditions de frontière entre A et B ; ou de références vers des groupes numérotés. Ainsi, des expressions complexes peuvent facilement être construites depuis de plus simples expressions primitives comme celles décrites ici. Pour plus de détails sur la théorie et l’implémentation des expressions rationnelles, consultez le livre de Friedl [Frie09], ou à peu près n’importe quel livre dédié à la construction de compilateurs.

Une brève explication sur le format des expressions rationnelles suit. Pour de plus amples informations et une présentation plus simple, référez-vous au Guide des expressions régulières.

Les expressions rationnelles peuvent contenir à la fois des caractères spéciaux et ordinaires. Les plus ordinaires, comme 'A', 'a' ou '0' sont les expressions rationnelles les plus simples : elles correspondent simplement à elles-mêmes. Vous pouvez concaténer des caractères ordinaires, ainsi last correspond à la chaîne 'last'. (Dans la suite de cette section, nous écrirons les expressions rationnelles dans ce style spécifique, généralement sans guillemets, et les chaînes à tester 'entourées de simples guillemets'.)

Certains caractères, comme '|' ou '(', sont spéciaux. Des caractères spéciaux peuvent aussi exister pour les classes de caractères ordinaires, ou affecter comment les expressions rationnelles autour d’eux seront interprétées.

Les caractères de répétition (*, +, ?, {m,n}, etc.) ne peuvent être directement imbriqués. Cela empêche l’ambiguïté avec le suffixe modificateur non gourmand ? et avec les autres modificateurs dans d’autres implémentations. Pour appliquer une seconde répétition à une première, des parenthèses peuvent être utilisées. Par exemple, l’expression (?:a{6})* valide toutes les chaînes composées d’un nombre de caractères 'a' multiple de six.

Les caractères spéciaux sont :

.

(Point.) Dans le mode par défaut, il valide tout caractère à l’exception du saut de ligne. Si l’option DOTALL a été spécifiée, il valide tout caractère, saut de ligne compris.

^

(Accent circonflexe.) Valide le début d’une chaîne de caractères, ainsi que ce qui suit chaque saut de ligne en mode MULTILINE.

$

Valide la fin d’une chaîne de caractères, ou juste avant le saut de ligne à la fin de la chaîne, ainsi qu’avant chaque saut de ligne en mode MULTILINE. foo valide à la fois foo et foobar, tandis que l’expression rationnelle foo$ ne correspond qu’à 'foo'. Plus intéressant, chercher foo.$ dans 'foo1\nfoo2\n' trouve normalement 'foo2', mais 'foo1' en mode MULTILINE ; chercher un simple $ dans 'foo\n' trouvera deux correspondances (vides) : une juste avant le saut de ligne, et une à la fin de la chaîne.

*

Fait valider par l’expression rationnelle résultante 0 répétition ou plus de l’expression qui précède, avec autant de répétitions que possible. ab* validera “a”, “ab” ou “a” suivi de n’importe quel nombre de “b”.

+

Fait valider par l’expression rationnelle résultante 1 répétition ou plus de l’expression qui précède. ab+ validera “a” suivi de n’importe quel nombre non nul de “b” ; cela ne validera pas la chaîne “a”.

?

Fait valider par l’expression rationnelle résultante 0 ou 1 répétition de l’expression qui précède. ab? correspondra à “a” ou “ab”.

*?, +?, ??

Les qualificateurs '*', '+' et '?' sont tous greedy (gourmands) ; ils valident autant de texte que possible. Parfois ce comportement n’est pas désiré ; si l’expression rationnelle <.*> est testée avec la chaîne '<a> b <c>', cela correspondra à la chaîne entière, et non juste à '<a>'. Ajouter ? derrière le qualificateur lui fait réaliser l’opération de façon non-greedy (ou minimal) ; le moins de caractères possibles seront validés. Utiliser l’expression rationnelle <.*?> validera uniquement '<a>'.

{m}

Spécifie qu’exactement m copies de l’expression rationnelle qui précède devront être validées ; un nombre plus faible de correspondances empêche l’expression entière de correspondre. Par exemple, a{6} correspondra exactement à six caractères 'a', mais pas à cinq.

{m,n}

Fait valider par l’expression rationnelle résultante entre m et n répétitions de l’expression qui précède, cherchant à en valider le plus possible. Par exemple, a{3,5} validera entre 3 et 5 caractères 'a'. Omettre m revient à spécifier 0 comme borne inférieure, et omettre n à avoir une borne supérieure infinie. Par exemple, a{4,}b correspondra à 'aaaab' ou à un millier de caractères 'a' suivis d’un 'b', mais pas à 'aaab'. La virgule ne doit pas être omise, auquel cas le modificateur serait confondu avec la forme décrite précédemment.

{m,n}?

Fait valider par l’expression rationnelle résultante entre m et n répétitions de l’expression qui précède, cherchant à en valider le moins possible. Il s’agit de la version non gourmande du précédent qualificateur. Par exemple, dans la chaîne de 6 caractères 'aaaaaa', a{3,5} trouvera 5 caractères 'a', alors que a{3,5}? n’en trouvera que 3.

\

Échappe les caractères spéciaux (permettant d’identifier des caractères comme '*', '?' et autres) ou signale une séquence spéciale ; les séquences spéciales sont décrites ci-dessous.

Si vous n’utilisez pas de chaînes brutes pour exprimer le motif, souvenez-vous que Python utilise aussi le backslash comme une séquence d’échappement dans les chaînes littérales ; si la séquence d’échappement n’est pas reconnue par l’interpréteur Python, le backslash et les caractères qui le suivent sont inclus dans la chaîne renvoyée. Cependant, si Python reconnait la séquence, le backslash doit être doublé (pour ne plus être reconnu). C’est assez compliqué et difficile à comprendre, c’est pourquoi il est hautement recommandé d’utiliser des chaînes brutes pour tout sauf les expressions les plus simples.

[]

Utilisé pour indiquer un ensemble de caractères. Dans un ensemble :

Les caractères peuvent être listés individuellement, e.g. [amk] correspondra à 'a', 'm' ou 'k'.

Des intervalles de caractères peuvent être indiqués en donnant deux caractères et les séparant par un '-', par exemple [a-z] correspondra à toute lettre minuscule ASCII, [0-5][0-9] à tous nombres de deux chiffres entre 00` et ``59, et [0-9A-Fa-f] correspondra à n’importe quel chiffre hexadécimal. Si '-' est échappé ([a\-z]) ou s’il est placé comme premier ou dernier caractère (e.g. [-a] ou [a-]), il correspondra à un '-' littéral.

Les caractères spéciaux perdent leur sens à l’intérieur des ensembles. Par exemple, [(+*)] validera chacun des caractères littéraux '(', '+', '*' ou ')'.

Les classes de caractères telles que \w ou \S (définies ci-dessous) sont aussi acceptées à l’intérieur d’un ensemble, bien que les caractères correspondant dépendent de quel mode est actif entre ASCII et LOCALE.

Les caractères qui ne sont pas dans un intervalle peuvent être trouvés avec l’ensemble complémentaire (complementing). Si le premier caractère de l’ensemble est '^', tous les caractères qui ne sont pas dans l’ensemble seront validés. Par exemple, [^5] correspondra à tout caractère autre que '5' et [^^] validera n’importe quel caractère excepté '^'. ^ n’a pas de sens particulier s’il n’est pas le premier caractère de l’ensemble.

Pour insérer un ']' littéral dans un ensemble, il faut le précéder d’un backslash ou le placer au début de l’ensemble. Par exemple, [()[\]{}] et []()[{}] vont tous deux correspondre à une parenthèse, un crochet ou une accolade.

|

A|B, où A et B peuvent être deux expressions rationnelles arbitraires, crée une expression rationnelle qui validera soit A soit B. Un nombre arbitraire d’expressions peuvent être séparées de cette façon par des '|'. Cela peut aussi être utilisé au sein de groupes (voir ci-dessous). Quand une chaîne cible est analysée, les expressions séparées par '|' sont essayées de la gauche vers la droite. Quand un motif correspond complètement, cette branche est acceptée. Cela signifie qu’une fois que A correspond, B ne sera pas testée plus loin, même si elle pourrait provoquer une plus ample correspondance. En d’autres termes, l’opérateur '|' n’est jamais gourmand. Pour valider un '|' littéral, utilisez \|, ou enveloppez-le dans une classe de caractères, comme [|].

(...)

Valide n’importe quelle expression rationnelle comprise entre les parenthèses, et indique le début et la fin d’un groupe ; le contenu d’un groupe peut être récupéré après qu’une analyse a été effectuée et peut être réutilisé plus loin dans la chaîne avec une séquence spéciale \number, décrite ci-dessous. Pour écrire des '(' ou ')' littéraux, utilisez \( ou \), ou enveloppez-les dans une classe de caractères : [(], [)].

(?...)

Il s’agit d’une notation pour les extensions (un '?' suivant une '(' n’a pas de sens autrement). Le premier caractère après le '?' détermine quel sens donner à l’expression. Les extensions ne créent généralement pas de nouveaux groupes ; (?P<name>...) est la seule exception à la règle. Retrouvez ci-dessous la liste des extensions actuellement supportées.

(?aiLmsux)

(Une lettre ou plus de l’ensemble 'a', 'i', 'L', 'm', 's', 'u', 'x'.) Le groupe valide la chaîne vide ; les lettres activent les modes correspondant : re.A (validation ASCII seulement), re.I (ignorer la casse)`, re.L (dépendant de la locale), re.M (multi-ligne), re.S (les points correspondent à tous les caractères), re.U (support d’Unicode) et re.X (verbeux), pour l’ensemble de l’expression rationnelle. (Les options dans décrites dans la section Contenu du module.) C’est utile si vous souhaitez préciser l’option dans l’expression rationnelle, plutôt qu’en passant un argument flag à la fonction re.compile(). Les options devraient être spécifiées en premier dans la chaîne de l’expression.

(?:...)

Une version sans capture des parenthèses habituelles. Valide n’importe quelle expression rationnelle à l’intérieur des parenthèses, mais la sous-chaîne correspondant au groupe ne peut pas être récupérée après l’analyse ou être référencée plus loin dans le motif.

(?imsx-imsx:...)

(Zéro lettres ou plus de l’ensemble 'i', 'm', 's', 'x', optionnellement suivies par '-' ainsi qu’une ou plusieurs lettres du même ensemble.) Les lettres activent ou désactivent les options correspondantes : re.I (ignorer la casse), re.M (multi-ligne), re.S (les points correspondent à tous les caractères) et re.X (verbeux), pour cette partie de l’expression. (Les options sont décrites dans la section Contenu du module.)

Nouveau dans la version 3.6.

(?P<name>...)

Similaires aux parenthèses habituelles, mais la sous-chaîne validée par le groupe est accessible via le nom name du groupe symbolique. Les noms de groupes doivent être des identifiants Python valides, et chaque nom de groupe ne doit être défini qu’une seule fois dans une expression rationnelle. Un groupe symbolique est aussi un groupe numéroté, de la même manière que si le groupe n’était pas nommé.

Les groupes nommés peuvent être référencés dans trois contextes. Si le motif est (?P<quote>['"]).*?(?P=quote) (i.e. correspondant à une chaîne entourée de guillemets simples ou doubles) :

Contexte de référence au groupe quote

Manières de le référencer

lui-même dans le même motif

(?P=quote) (comme vu)

\1

en analysant l’objet résultat m

m.group('quote')

m.end('quote') (etc.)

dans une chaîne passée à l’argument repl de re.sub()

\g<quote>

\g<1>

\1

(?P=name)

Une référence arrière à un groupe nommé ; elle correspond à n’importe quel texte validé plus tôt par le groupe nommé name.

(?#...)

Un commentaire ; le contenu des parenthèses est simplement ignoré.

(?=...)

Valide si ... valide la suite, mais ne consomme rien de la chaîne. On appelle cela une assertion lookahead. Par exemple, Isaac (?=Asimov) correspondra à la chaîne 'Isaac' `` seulement si elle est suivie par ``'Asimov'.

(?!...)

Valide si ... ne valide pas la suite. C’est une assertion negative lookahead. Par exemple, Isaac (?!Asimov) correspondra à la chaîne 'Isaac ' seulement si elle n’est pas suivie par 'Asimov'.

(?<=...)

Valide si la position courante dans la chaîne est précédée par une correspondance sur ... qui se termine à la position courante. On appelle cela une positive lookbehind assertion. (?<=abc)def cherchera une correspondance dans 'abcdef', puisque le lookbehind* mettra de côté 3 caractères et vérifiera que le motif contenu correspond. Le motif ne devra correspondre qu’à des chaînes de taille fixe, cela veut dire que abc ou a|b` sont autorisées, mais pas ``a* ou a{3,4}. Notez que les motifs qui commencent par des assertions lookbehind positives ne peuvent pas correspondre au début de la chaîne analysée ; vous préférerez sûrement utiliser la fonction search() plutôt que la fonction match() :

>>> import re
>>> m = re.search('(?<=abc)def', 'abcdef')
>>> m.group(0)
'def'

Cet exemple recherche un mot suivi d’un trait d’union :

>>> m = re.search(r'(?<=-)\w+', 'spam-egg')
>>> m.group(0)
'egg'

Modifié dans la version 3.5: Ajout du support des références aux groupes de taille fixe.

(?<!...)

Valide si la position courante dans la chaîne n’est pas précédée par une correspondance sur .... On appelle cela une negative lookbehind assertion. À la manière des assertions lookbehind positives, le motif contenu ne peut que correspondre à des chaînes de taille fixe. Les motifs débutant par une assertion lookbehind négative peuvent correspondre au début de la chaîne analysée.

(?(id/name)yes-pattern|no-pattern)

Essaiera de faire la correspondance avec yes-pattern si le groupe indiqué par id ou name existe, et avec no-pattern s’il n’existe pas. no-pattern est optionnel et peut être omis. Par exemple, (<)?(\w+@\w+(?:\.\w+)+)(?(1)>|$) est un motif simpliste pour identifier une adresse courriel, qui validera '<user@host.com>' ainsi que 'user@host.com' mais pas '<user@host.com' ni 'user@host.com>'.

Les séquences spéciales sont composées de '\' et d’un caractère de la liste qui suit. Si le caractère ordinaire n’est pas un chiffre ASCII ou une lettre ASCII, alors l’expression rationnelle résultante validera le second caractère de la séquence. Par exemple, \$ correspond au caractère '$'.

\number

Correspond au contenu du groupe du même nombre. Les groupes sont numérotés à partir de 1. Par exemple, (.+) \1 correspond à 'the the' ou '55 55', mais pas à 'thethe' (notez l’espace après le groupe). Cette séquence spéciale ne peut être utilisée que pour faire référence aux 99 premiers groupes. Si le premier chiffre de number est 0, ou si number est un nombre octal de 3 chiffres, il ne sera pas interprété comme une référence à un groupe, mais comme le caractère à la valeur octale number. À l’intérieur des '[' et ']' d’une classe de caractères, tous les échappements numériques sont traités comme des caractères.

\A

Correspond uniquement au début d’une chaîne de caractères.

\b

Correspond à la chaîne vide, mais uniquement au début ou à la fin d’un mot. Un mot est défini comme une séquence de « caractères de mots ». Notez que formellement, \b est défini comme la liaison entre \w et \W (et inversement), ou entre \w et le début/fin d’un mot. Cela signifie que r'\bfoo\b' validera 'foo', 'foo.', '(foo)' ou 'bar foo baz' mais pas 'foobar' ou 'foo3'.

Les caractères alphanumériques Unicode sont utilisés par défaut dans les motifs Unicode, mais cela peut être changé en utilisant l’option ASCII. Les délimitations de mots sont déterminées par la locale si l’option LOCALE est utilisée. À l’intérieur d’un intervalle de caractères, \b représente le caractère backspace, par compatibilité avec les chaînes littérales Python.

\B

Correspond à la chaîne vide, mais uniquement quand elle n’est pas au début ou à la fin d’un mot. Cela signifie que r'py\B' valide 'python', 'py3' ou 'py2', mais pas 'py', 'py.' ou 'py!'. \B est simplement l’opposé de \b, donc les caractères de mots dans les motifs Unicode sont les alphanumériques et tirets bas Unicode, bien que cela puisse être changé avec l’option ASCII. Les délimitations de mots sont déterminées par la locale si l’option LOCALE est utilisée.

\d

Pour les motifs Unicode (str) :

Valide n’importe quel chiffre décimal Unicode (soit tout caractère Unicode de catégorie [Nd]). Cela inclue [0-9], mais aussi bien d’autres caractères de chiffres. Si l’option ASCII est utilisée, seuls les caractères de la classe [0-9] correspondront (mais l’option affectant l’expression rationnelle entière, il peut être préférable dans ce genre de cas d’utiliser un [0-9] explicite).

Pour les motifs 8-bit (bytes) :

Valide n’importe quel chiffre décimal ; équivalent à [0-9].

\D

Valide tout caractère qui n’est pas un chiffre décimal. C’est l’opposé de \d. Si l’option ASCII est utilisée, cela devient équivalent à [^0-9] (mais l’option affectant l’expression rationnelle entière, il peut être préférable dans ce genre de cas d’utiliser explicitement [^0-9]).

\s

Pour les motifs Unicode (str) :

Valide les caractères d’espacement Unicode (qui incluent [ \t\n\r\f\v] et bien d’autres, comme les espaces insécables requises par les règles typographiques de beaucoup de langues). Si l’option ASCII est utilisée, seuls les caractères de la classe [ \t\n\r\f\v] sont validés (mais l’option affectant l’expression rationnelle entière, il peut être préférable dans ce genre de cas d’utiliser un [ \t\n\r\f\v] explicite).

Pour les motifs 8-bit (bytes) :

Valide les caractères considérés comme des espacements dans la table ASCII ; équivalent à [ \t\n\r\f\v].

\S

Valide tout caractère qui n’est pas un caractère d’espacement. c’est l’opposé de \s. Si l’option ASCII est utilisée, cela devient équivalent à [^ \t\n\r\f\v] (mais l’option affectant l’expression rationnelle entière, il peut être préférable dans ce genre de cas d’utiliser un [^ \t\n\r\f\v] explicite).

\w

Pour les motifs Unicode (str) :

Valide les caractères Unicode de mot ; cela inclut la plupart des caractères qui peuvent être compris dans un mot d’une quelconque langue, aussi bien que les nombres et les tirets bas. Si l’option ASCII est utilisée, seuls les caractères de la classe [a-zA-Z0-9_] sont validés (mais l’option affectant l’expression rationnelle entière, il peut être préférable dans ce genre de cas d’utiliser un [a-zA-Z0-9_] explicite).

Pour les motifs 8-bit (bytes) :

Valide les caractères alphanumériques de la table ASCII ; équivalent à [a-zA-Z0-9_]. Si l’option LOCALE est utilisée, les caractères considérés alphanumériques dans la locale et le tiret bas seront acceptés.

\W

Valide tout caractère qui n’est pas un caractère de mot. C’est l’opposé de \w. Si l’option ASCII est utilisée, cela devient équivalent à [^a-zA-Z0-9_] (mais l’option affectant l’expression rationnelle entière, il peut être préférable dans ce genre de cas d’utiliser un [^a-zA-Z0-9_] explicite). Si l’option LOCALE est utilisée, les caractères considérés alphanumériques dans la locale courrante, et le tiret bas, seront acceptés.

\Z

Correspond uniquement à la fin d’une chaîne de caractères.

La plupart des échappements standards supportés par les chaînes littérales sont aussi acceptés par l’analyseur d’expressions rationnelles :

\a      \b      \f      \n
\r      \t      \u      \U
\v      \x      \\

(Notez que \b est utilisé pour représenter les bornes d’un mot, et signifie « backspace » uniquement à l’intérieur d’une classe de caractères.)

Les séquences d’échappement '\u' et '\U' sont seulement reconnues dans les motifs Unicode. Dans les motifs de byte, ce sont des erreurs.

Les séquences octales d’échappement sont incluses dans une forme limitée. Si le premier chiffre est un 0, ou s’il y a trois chiffres octaux, la séquence est considérée comme octale. Autrement, il s’agit d’une référence vers un groupe. Comme pour les chaînes littérales, les séquences octales ne font jamais plus de 3 caractères de long.

Modifié dans la version 3.3: Les séquences d’échappement '\u' et '\U' ont été ajoutées.

Modifié dans la version 3.6: Les séquences inconnues composées de '\' et d’une lettre ASCII sont maintenant des erreurs.

6.2.2. Contenu du module

Le module définit plusieurs fonctions, constantes, et une exception. Certaines fonctions sont des versions simplifiées des méthodes plus complètes des expressions rationnelles compilées. La plupart des applications non triviales utilisent toujours la version compilée.

Modifié dans la version 3.6: Les constantes d’options sont maintenant des instances de RegexFlag, sous-classe de enum.IntFlag.

re.compile(pattern, flags=0)

Compile un motif vers une expression rationnelle compilée, dont les méthodes match() et search(), décrites ci-dessous, peuvent être utilisées pour analyser des textes.

Le comportement des expressions peut être modifié en spécifiant une valeur flags. Les valeurs sont comprises dans les variables suivantes, et peuvent être combinées avec un ou bit-à-bit (opérateur |).

La séquence

prog = re.compile(pattern)
result = prog.match(string)

est équivalente à

result = re.match(pattern, string)

mais utiliser re.compile() et sauvegarder l’expression rationnelle renvoyée pour la réutiliser est plus efficace quand l’expression est amenée à être utilisée plusieurs fois dans un même programme.

Note

Les versions compilées des motifs les plus récents passés à re.compile() et autres fonctions d’analyse du module sont mises en cache, ainsi les programmes qui n’utilisent que quelques expressions rationnelles en même temps n’ont pas à s’inquiéter de la compilation de ces expressions.

re.A

re.ASCII

Fait correspondre à \w, \W, \b, \B, \d, \D, \s et \s des caractères ASCII seulement, plutôt qu’Unicode. Cela n’a du sens que pour les motifs Unicode, et est ignoré pour les motifs 8-bit. Correspond à l’option de groupe (?a).

Notez que par compatibilité envers les versions précédentes, l’option re.U existe toujours (ainsi que son synonyme re.UNICODE et sa version embarquée (?u)), mais elles sont redondantes en Python 3 depuis que l’analyse est faite en Unicode par défaut pour les chaînes de caractères (et que l’analyse Unicode n’est pas permise pour les chaînes 8-bit).

re.DEBUG

Affiche des informations de débogage à propos de l’expression compilée. N’a pas d’option de groupe équivalente.

re.I

re.IGNORECASE

Effectue une analyse indépendante de la casse. Les motifs tels que [A-Z] accepteront donc les caractères minuscules. L’analyse Unicode complète (tel que Ü correspondant à ü) fonctionne aussi, tant que l’option re.ASCII n’est pas utilisée. La locale n’affecte pas cette option, tant que l’option re.LOCALE n’est pas utilisée. Correspond au marqueur de groupe (?i).

Note that when the Unicode patterns [a-z] or [A-Z] are used in combination with the IGNORECASE flag, they will match the 52 ASCII letters and 4 additional non-ASCII letters: “İ” (U+0130, Latin capital letter I with dot above), “ı” (U+0131, Latin small letter dotless i), “ſ” (U+017F, Latin small letter long s) and “K” (U+212A, Kelvin sign). If the ASCII flag is used, only letters “a” to “z” and “A” to “Z” are matched (but the flag affects the entire regular expression, so in such cases using an explicit (?-i:[a-zA-Z]) may be a better choice).

re.L

re.LOCALE

Fait dépendre de la locale courante : \w, \W, \b, \B, et l’analyse insensible à la casse. Cette option peut être utilisée avec les motifs en bytes. L’utilisation de cette option est déconseillée à cause du mécanisme de locale très peu fiable, et ne gérant qu’une « culture » à la fois, et ne fonctionnant que pour les locales 8-bits. L’analyse Unicode est déjà activée par défaut dans Python 3 pour les motifs Unicode (str), et elle est capable de gérer plusieurs locales et langages. Correspond à l’option de groupe (?L).

Modifié dans la version 3.6: re.LOCALE ne peut être utilisée qu’avec les motifs 8-bit et n’est pas compatible avec re.ASCII.

re.M

re.MULTILINE

Quand spécifiée, le caractère '^' correspond au début d’une chaîne et au début d’une ligne (caractère suivant directement le saut de ligne) ; et le caractère '$' correspond à la fin d’une chaîne et à la fin d’une ligne (juste avant le saut de ligne). Par défaut, '^' correspond uniquement au début de la chaîne, et '$' uniquement à la fin de la chaîne, ou immédiatement avant le saut de ligne (s’il y a) à la fin de la chaîne. Correspond à l’option de groupe (?m).

re.S

re.DOTALL

Fait correspondre tous les caractères possibles à '.', incluant le saut de ligne ; sans cette option, '.' correspondrait à tout caractère à l’exception du saut de ligne. Correspond à l’option de groupe (?s).

re.X

re.VERBOSE

Cette option vous autorise à écrire des expressions rationnelles qui présentent mieux et sont plus lisibles en vous permettant de séparer visuellement les sections logiques du motif et d’ajouter des commentaires. Les caractères d’espacement à l’intérieur du motif sont ignorés, sauf à l’intérieur des classes de caractères ou quand précédés d’un backslash non échappé, ou dans des séquences comme *?, (?: or (?P<...>. Quand une ligne contient un # qui n’est pas dans une classe de caractères ou précédé d’un backslash non échappé, tous les caractères depuis le # le plus à gauche jusqu’à la fin de la ligne sont ignorés.

Cela signifie que les deux expressions rationnelles suivantes qui valident un nombre décimal sont fonctionnellement égales :

a = re.compile(r"""\d +  # the integral part
                   \.    # the decimal point
                   \d *  # some fractional digits""", re.X)
b = re.compile(r"\d+\.\d*")

Correspond à l’option de groupe (?x).

re.search(pattern, string, flags=0)

Analyse string à la recherche du premier emplacement où l’expression rationnelle pattern trouve une correspondance, et renvoie l”objet de correspondance trouvé. Renvoie None si aucune position dans la chaîne ne valide le motif ; notez que cela est différent de trouver une correspondance avec une chaîne vide à un certain endroit de la chaîne.

re.match(pattern, string, flags=0)

Si zéro ou plus caractères au début de string correspondent à l’expression rationnelle pattern, renvoie l”objet de correspondance trouvé. Renvoie None si la chaîne ne correspond pas au motif ; notez que cela est différent d’une correspondance avec une chaîne vide.

Notez que même en mode MULTILINE, re.match() ne validera qu’au début de la chaîne et non au début de chaque ligne.

Si vous voulez trouver une correspondance n’importe où dans string, utilisez plutôt search() (voir aussi search() vs. match()).

re.fullmatch(pattern, string, flags=0)

Si l’entièreté de la chaîne string correspond à l’expression rationnelle pattern, renvoie l”objet de correspondance trouvé. Renvoie None si la chaîne ne correspond pas au motif ; notez que cela est différent d’une correspondance avec une chaîne vide.

Nouveau dans la version 3.4.

re.split(pattern, string, maxsplit=0, flags=0)

Sépare string selon les occurrences de pattern. Si des parenthèses de capture sont utilisées dans pattern, alors les textes des groupes du motif sont aussi renvoyés comme éléments de la liste résultante. Si maxsplit est différent de zéro, il ne pourra y avoir plus de maxsplit séparations, et le reste de la chaîne sera renvoyé comme le dernier élément de la liste.

>>> re.split(r'\W+', 'Words, words, words.')
['Words', 'words', 'words', '']
>>> re.split(r'(\W+)', 'Words, words, words.')
['Words', ', ', 'words', ', ', 'words', '.', '']
>>> re.split(r'\W+', 'Words, words, words.', 1)
['Words', 'words, words.']
>>> re.split('[a-f]+', '0a3B9', flags=re.IGNORECASE)
['0', '3', '9']

S’il y a des groupes de capture dans le séparateur et qu’ils trouvent une correspondance au début de la chaîne, le résultat commencera par une chaîne vide. La même chose se produit pour la fin de la chaîne :

>>> re.split(r'(\W+)', '...words, words...')
['', '...', 'words', ', ', 'words', '...', '']

De cette manière, les séparateurs sont toujours trouvés aux mêmes indices relatifs dans la liste résultante.

Note

split() ne sépare actuellement pas une chaîne sur une correspondance vide. Par exemple :

>>> re.split('x*', 'axbc')
['a', 'bc']

Même si 'x*' correspond aussi à 0 “x” avant “a”, entre “b” et “c”, et après “c”, ces correspondances sont actuellement ignorées. Le comportement correct (i.e. découper aussi sur les correspondances vides et renvoyer ['', 'a', 'b', 'c', '']) sera implémenté dans les futures versions de Python, mais comme cela constitue un changement incompatible avec les précédentes, une FutureWarning sera levée pendant la transition.

Les motifs qui ne peuvent correspondre qu’à des chaînes vides ne permettent actuellement pas de découper la chaîne. Puisque cela ne correspond pas au comportement voulu, une ValueError sera levée à partir de Python 3.5 :

>>> re.split("^$", "foo\n\nbar\n", flags=re.M)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  ...
ValueError: split() requires a non-empty pattern match.

Modifié dans la version 3.1: Ajout de l’argument optionnel flags.

Modifié dans la version 3.5: Découper sur un motif qui peut correspondre à une chaîne vide lève maintenant un avertissement. Les motifs qui ne peuvent correspondre qu’à des chaînes vides sont maintenant rejetés.

re.findall(pattern, string, flags=0)

Renvoie toutes les correspondances de pattern dans string qui ne se chevauchent pas, sous forme d’une liste de chaînes. Le chaîne string est analysée de la gauche vers la droite, et les correspondances sont renvoyées dans l’ordre où elles sont trouvées. Si un groupe ou plus sont présents dans le motif, renvoie une liste de groupes ; il s’agira d’une liste de tuples si le motif a plus d’un groupe. Les correspondances vides sont incluses dans le résultat.

Note

Due to the limitation of the current implementation the character following an empty match is not included in a next match, so findall(r'^|\w+', 'two words') returns ['', 'wo', 'words'] (note missed « t »). This is changed in Python 3.7.

re.finditer(pattern, string, flags=0)

Renvoie un iterator produisant des objets de correspondance pour toutes les correspondances non chevauchantes de l’expression rationnelle pattern sur la chaîne string. string est analysée de la gauche vers la droite, et les correspondances sont renvoyées dans l’ordre où elles sont trouvées. Les correspondances vides sont inclues dans le résultat. Consultez la note à propos de findall().

re.sub(pattern, repl, string, count=0, flags=0)

Renvoie la chaîne obtenue en remplaçant les occurrences (sans chevauchement) les plus à gauche de pattern dans string par le remplacement repl. Si le motif n’est pas trouvé, string est renvoyée inchangée. repl peut être une chaîne de caractères ou une fonction ; si c’est une chaîne, toutes les séquences d’échappement qu’elle contient sont traduites. Ainsi, \n est convertie en un simple saut de ligne, \r en un retour chariot, et ainsi de suite. Les séquences inconnues telles que \& sont laissées intactes. Les références arrières, telles que \6, sont remplacées par la sous-chaîne correspondant au groupe 6 dans le motif. Par exemple :

>>> re.sub(r'def\s+([a-zA-Z_][a-zA-Z_0-9]*)\s*\(\s*\):',
...        r'static PyObject*\npy_\1(void)\n{',
...        'def myfunc():')
'static PyObject*\npy_myfunc(void)\n{'

Si repl est une fonction, elle est appelée pour chaque occurrence non chevauchante de pattern. La fonction prend comme argument un objet de correspondance, et renvoie la chaîne de remplacement. Par exemple :

>>> def dashrepl(matchobj):
...     if matchobj.group(0) == '-': return ' '
...     else: return '-'
>>> re.sub('-{1,2}', dashrepl, 'pro----gram-files')
'pro--gram files'
>>> re.sub(r'\sAND\s', ' & ', 'Baked Beans And Spam', flags=re.IGNORECASE)
'Baked Beans & Spam'

Le motif peut être une chaîne de caractères ou un objet expression rationnelle.

L’argument optionnel count est le nombre maximum d’occurrences du motif à remplacer : count ne doit pas être un nombre négatif. Si omis ou nul, toutes les occurrences seront remplacées. Les correspondances vides avec le motif sont remplacées uniquement quand elles ne sont pas adjacentes à une précédente correspondance, ainsi sub('x*', '-', 'abc') renvoie '-a-b-c-'.

Dans les arguments repl de type string, en plus des séquences d’échappement et références arrières décrites au-dessus, \g<name> utilisera la sous-chaîne correspondant au groupe nommé name, comme défini par la syntaxe (?P<name>...). \g<number> utilise le groupe numéroté associé ; \g<2> est ainsi équivalent à \2, mais n’est pas ambigu dans un remplacement tel que \g<2>0, \20 serait interprété comme une référence au groupe 20, et non une référence au groupe 2 suivie par un caractère littéral '0'. La référence arrière \g<0> est remplacée par la sous-chaîne entière validée par l’expression rationnelle.

Modifié dans la version 3.1: Ajout de l’argument optionnel flags.

Modifié dans la version 3.5: Les groupes sans correspondance sont remplacés par une chaîne vide.

Modifié dans la version 3.6: Les séquences d’échappement inconnues dans pattern formées par '\' et une lettre ASCII sont maintenant des erreurs.

Deprecated since version 3.5, will be removed in version 3.7: Les séquences d’échappement dans repl formées d’un '\' et d’une lettre ASCII lèvent maintenant un avertissement de dépréciation et seront interdites en Python 3.7.

re.subn(pattern, repl, string, count=0, flags=0)

Réalise la même opération que sub(), mais renvoie un tuple (nouvelle_chaîne, nombre_de_substitutions_réalisées).

Modifié dans la version 3.1: Ajout de l’argument optionnel flags.

Modifié dans la version 3.5: Les groupes sans correspondance sont remplacés par une chaîne vide.

re.escape(pattern)

Échappe tous les caractères de pattern à l’exception des lettres ASCII, des nombres et de '_'. Cela est utile si vous voulez valider une quelconque chaîne littérale qui pourrait contenir des métacaractères d’expressions rationnelles. Par exemple :

>>> print(re.escape('python.exe'))
python\.exe

>>> legal_chars = string.ascii_lowercase + string.digits + "!#$%&'*+-.^_`|~:"
>>> print('[%s]+' % re.escape(legal_chars))
[abcdefghijklmnopqrstuvwxyz0123456789\!\#\$\%\&\'\*\+\-\.\^_\`\|\~\:]+

>>> operators = ['+', '-', '*', '/', '**']
>>> print('|'.join(map(re.escape, sorted(operators, reverse=True))))
\/|\-|\+|\*\*|\*

Ces fonctions ne doivent pas être utilisées pour la chaîne de remplacement dans sub() et subn(), seuls les antislash devraient être échappés. Par exemple :

>>> digits_re = r'\d+'
>>> sample = '/usr/sbin/sendmail - 0 errors, 12 warnings'
>>> print(re.sub(digits_re, digits_re.replace('\\', r'\\'), sample))
/usr/sbin/sendmail - \d+ errors, \d+ warnings

Modifié dans la version 3.3: Le caractère '_' n’est plus échappé.

re.purge()

Vide le cache d’expressions rationnelles.

exception re.error(msg, pattern=None, pos=None)

Exception levée quand une chaîne passée à l’une des fonctions ici présentes n’est pas une expression rationnelle valide (contenant par exemple une parenthèse non fermée) ou quand d’autres erreurs se produisent durant la compilation ou l’analyse. Il ne se produit jamais d’erreur si une chaîne ne contient aucune correspondance pour un motif. Les instances de l’erreur ont les attributs additionnels suivants :

msg

Le message d’erreur non formaté.

pattern

Le motif d’expression rationnelle.

pos

L’index dans pattern où la compilation a échoué (peut valoir None).

lineno

La ligne correspondant à pos (peut valoir None).

colno

La colonne correspondant à pos (peut valoir None).

Modifié dans la version 3.5: Ajout des attributs additionnels.

6.2.3. Objets d’expressions rationnelles

Les expressions rationnelles compilées supportent les méthodes et attributs suivants :

regex.search(string[, pos[, endpos]])

Analyse string à la recherche du premier emplacement où l’expression rationnelle trouve une correspondance, et envoie l”objet de correspondance trouvé. Renvoie None si aucune position dans la chaîne ne satisfait le motif ; notez que cela est différent que de trouver une correspondance vide dans la chaîne.

Le second paramètre pos (optionnel) donne l’index dans la chaîne où la recherche doit débuter ; il vaut 0 par défaut. Cela n’est pas complètement équivalent à un slicing sur la chaîne ; le caractère de motif '^' correspond au début réel de la chaîne et aux positions juste après un saut de ligne, mais pas nécessairement à l’index où la recherche commence.

Le paramètre optionnel endpos limite la longueur sur laquelle la chaîne sera analysée ; ce sera comme si la chaîne faisait endpos caractères de long, donc uniquement les caractères de pos à endpos - 1 seront analysés pour trouver une correspondance. Si endpos est inférieur à pos, aucune correspondance ne sera trouvée ; dit autrement, avec rx une expression rationnelle compilée, rx.search(string, 0, 50) est équivalent à rx.search(string[:50], 0).

>>> pattern = re.compile("d")
>>> pattern.search("dog")     # Match at index 0
<_sre.SRE_Match object; span=(0, 1), match='d'>
>>> pattern.search("dog", 1)  # No match; search doesn't include the "d"

regex.match(string[, pos[, endpos]])

Si zéro caractère ou plus au début de string correspondent à cette expression rationnelle, renvoie l”objet de correspondance trouvé. Renvoie None si la chaîne ne correspond pas au motif ; notez que cela est différent d’une correspondance vide.

Les paramètres optionnels pos et endpos ont le même sens que pour la méthode search().

>>> pattern = re.compile("o")
>>> pattern.match("dog")      # No match as "o" is not at the start of "dog".
>>> pattern.match("dog", 1)   # Match as "o" is the 2nd character of "dog".
<_sre.SRE_Match object; span=(1, 2), match='o'>

Si vous voulez une recherche n’importe où dans string, utilisez plutôt search() (voir aussi search() vs. match()).

regex.fullmatch(string[, pos[, endpos]])

Si la chaîne string entière valide l’expression rationnelle, renvoie l”object de correspondance associé. Renvoie None si la chaîne ne correspond pas au motif ; notez que cela est différent d’une correspondance vide.

Les paramètres optionnels pos et endpos ont le même sens que pour la méthode search().

>>> pattern = re.compile("o[gh]")
>>> pattern.fullmatch("dog")      # No match as "o" is not at the start of "dog".
>>> pattern.fullmatch("ogre")     # No match as not the full string matches.
>>> pattern.fullmatch("doggie", 1, 3)   # Matches within given limits.
<_sre.SRE_Match object; span=(1, 3), match='og'>

Nouveau dans la version 3.4.

regex.split(string, maxsplit=0)

Identique à la fonction split(), en utilisant le motif compilé.

regex.findall(string[, pos[, endpos]])

Similaire à la fonction findall(), en utilisant le motif compilé, mais accepte aussi des paramètres pos et endpos optionnels qui limitent la région de recherche comme pour search().

regex.finditer(string[, pos[, endpos]])

Similaire à la fonction finditer(), en utilisant le motif compilé, mais accepte aussi des paramètres pos et endpos optionnels qui limitent la région de recherche comme pour search().

regex.sub(repl, string, count=0)

Identique à la fonction sub(), en utilisant le motif compilé.

regex.subn(repl, string, count=0)

Identique à la fonction subn(), en utilisant le motif compilé.

regex.flags

Les options de validation de l’expression rationnelle. Il s’agit d’une combinaison des options données à compile(), des potentielles options (?...) dans le motif, et des options implicites comme UNICODE si le motif est une chaîne Unicode.

regex.groups

Le nombre de groupes de capture dans le motif.

regex.groupindex

Un dictionnaire associant les noms de groupes symboliques définis par (?P<id>) aux groupes numérotés. Le dictionnaire est vide si aucun groupe symbolique n’est utilisé dans le motif.

regex.pattern

La chaîne de motif depuis laquelle l’objet expression rationnelle a été compilé.

6.2.4. Objets de correspondance

Les objets de correspondance ont toujours une valeur booléenne True. Puisque match() et search() renvoient None quand il n’y a pas de correspondance, vous pouvez tester s’il y a eu correspondance avec une simple instruction if :

match = re.search(pattern, string)
if match:
    process(match)

Les objets de correspondance supportent les méthodes et attributs suivants :

match.expand(template)

Renvoie la chaîne obtenue en substituant les séquences d’échappement du gabarit template, comme réalisé par la méthode sub(). Les séquences comme \n sont converties vers les caractères appropriés, et les références arrières numériques (\1, \2) et nommées (\g<1>, \g<name>) sont remplacées par les contenus des groupes correspondant.

Modifié dans la version 3.5: Les groupes sans correspondance sont remplacés par une chaîne vide.

match.group([group1, ...])

Renvoie un ou plus sous-groupes de la correspondance. Si un seul argument est donné, le résultat est une chaîne simple ; s’il y a plusieurs arguments, le résultat est un tuple comprenant un élément par argument. Sans arguments, group1 vaut par défaut zéro (la correspondance entière est renvoyée). Si un argument groupN vaut zéro, l’élément associé sera la chaîne de correspondance entière ; s’il est dans l’intervalle fermé [1..99], c’est la correspondance avec le groupe de parenthèses associé. Si un numéro de groupe est négatif ou supérieur au nombre de groupes définis dans le motif, une exception indexError est levée. Si un groupe est contenu dans une partie du motif qui n’a aucune correspondance, l’élément associé sera None. Si un groupe est contenu dans une partie du motif qui a plusieurs correspondances, seule la dernière correspondance est renvoyée.

>>> m = re.match(r"(\w+) (\w+)", "Isaac Newton, physicist")
>>> m.group(0)       # The entire match
'Isaac Newton'
>>> m.group(1)       # The first parenthesized subgroup.
'Isaac'
>>> m.group(2)       # The second parenthesized subgroup.
'Newton'
>>> m.group(1, 2)    # Multiple arguments give us a tuple.
('Isaac', 'Newton')

Si l’expression rationnelle utilise la syntaxe (?P<name>...), les arguments groupN peuvent alors aussi être des chaînes identifiant les groupes par leurs noms. Si une chaîne donnée en argument n’est pas utilisée comme nom de groupe dans le motif, une exception IndexError est levée.

Un exemple modérément compliqué :

>>> m = re.match(r"(?P<first_name>\w+) (?P<last_name>\w+)", "Malcolm Reynolds")
>>> m.group('first_name')
'Malcolm'
>>> m.group('last_name')
'Reynolds'

Les groupes nommés peuvent aussi être référencés par leur index :

>>> m.group(1)
'Malcolm'
>>> m.group(2)
'Reynolds'

Si un groupe a plusieurs correspondances, seule la dernière est accessible :

>>> m = re.match(r"(..)+", "a1b2c3")  # Matches 3 times.
>>> m.group(1)                        # Returns only the last match.
'c3'

match.__getitem__(g)

Cela est identique à m.group(g). Cela permet un accès plus facile à un groupe individuel depuis une correspondance :

>>> m = re.match(r"(\w+) (\w+)", "Isaac Newton, physicist")
>>> m[0]       # The entire match
'Isaac Newton'
>>> m[1]       # The first parenthesized subgroup.
'Isaac'
>>> m[2]       # The second parenthesized subgroup.
'Newton'

Nouveau dans la version 3.6.

match.groups(default=None)

Renvoie un tuple contenant tous les sous-groupes de la correspondance, de 1 jusqu’au nombre de groupes dans le motif. L’argument default est utilisé pour les groupes sans correspondance ; il vaut None par défaut.

Par exemple :

>>> m = re.match(r"(\d+)\.(\d+)", "24.1632")
>>> m.groups()
('24', '1632')

Si on rend la partie décimale et tout ce qui la suit optionnels, tous les groupes ne figureront pas dans la correspondance. Ces groupes sans correspondance vaudront None sauf si une autre valeur est donnée à l’argument default :

>>> m = re.match(r"(\d+)\.?(\d+)?", "24")
>>> m.groups()      # Second group defaults to None.
('24', None)
>>> m.groups('0')   # Now, the second group defaults to '0'.
('24', '0')

match.groupdict(default=None)

Renvoie un dictionnaire contenant tous les sous-groupes nommés de la correspondance, accessibles par leurs noms. L’argument default est utilisé pour les groupes qui ne figurent pas dans la correspondance ; il vaut None par défaut. Par exemple :

>>> m = re.match(r"(?P<first_name>\w+) (?P<last_name>\w+)", "Malcolm Reynolds")
>>> m.groupdict()
{'first_name': 'Malcolm', 'last_name': 'Reynolds'}

match.start([group])

match.end([group])

Renvoie les indices de début et de fin de la sous-chaîne correspondant au groupe group ; group vaut par défaut zéro (pour récupérer les indices de la correspondance complète). Renvoie -1 si group existe mais ne figure pas dans la correspondance. Pour un objet de correspondance m, et un groupe g qui y figure, la sous-chaîne correspondant au groupe g (équivalente à m.group(g)) est

m.string[m.start(g):m.end(g)]

Notez que m.start(group) sera égal à m.end(group) si group correspond à une chaîne vide. Par exemple, après m = re.search('b(c?)', 'cba'), m.start(0) vaut 1, m.end(0) vaut 2, m.start(1) et m.end(1) valent tous deux 2, et m.start(2) lève une exception IndexError.

Un exemple qui supprimera remove_this d’une adresse mail :

>>> email = "tony@tiremove_thisger.net"
>>> m = re.search("remove_this", email)
>>> email[:m.start()] + email[m.end():]
'tony@tiger.net'

match.span([group])

Pour un objet de correspondance m, renvoie le tuple (m.start(group), m.end(group)). Notez que si group ne figure pas dans la correspondance, (-1, -1) est renvoyé. group vaut par défaut zéro, pour la correspondance entière.

match.pos

La valeur de pos qui a été passée à la méthode search() ou match() d’un objet expression rationnelle. C’est l’index dans la chaîne à partir duquel le moteur d’expressions rationnelles recherche une correspondance.

match.endpos

La valeur de endpos qui a été passée à la méthode search() ou match() d’un objet expression rationnelle. C’est l’index dans la chaîne que le moteur d’expressions rationnelles ne dépassera pas.

match.lastindex

L’index entier du dernier groupe de capture validé, ou None si aucun groupe ne correspondait. Par exemple, les expressions (a)b, ((a)(b)) et ((ab)) auront un lastindex == 1 si appliquées à la chaîne 'ab', alors que l’expression (a)(b) aura un lastindex == 2 si appliquée à la même chaîne.

match.lastgroup

Le nom du dernier groupe capturant validé, ou None si le groupe n’a pas de nom, ou si aucun groupe ne correspondait.

match.re

L’expression rationnelle dont la méthode match() ou search() a produit cet objet de correspondance.

match.string

La chaîne passée à match() ou search().

6.2.5. Exemples d’expressions rationnelles

6.2.5.1. Rechercher une paire

Dans cet exemple, nous utiliserons cette fonction de facilité pour afficher les objets de correspondance sous une meilleure forme :

def displaymatch(match):
    if match is None:
        return None
    return '<Match: %r, groups=%r>' % (match.group(), match.groups())

Supposez que vous écriviez un jeu de poker où la main d’un joueur est représentée par une chaîne de 5 caractères avec chaque caractère représentant une carte, « a » pour l’as, « k » pour le roi (king), « q » pour la reine (queen), « j » pour le valet (jack), « t » pour 10 (ten), et les caractères de « 2 » à « 9 » représentant les cartes avec ces valeurs.

Pour vérifier qu’une chaîne donnée est une main valide, on pourrait faire comme suit :

>>> valid = re.compile(r"^[a2-9tjqk]{5}$")
>>> displaymatch(valid.match("akt5q"))  # Valid.
"<Match: 'akt5q', groups=()>"
>>> displaymatch(valid.match("akt5e"))  # Invalid.
>>> displaymatch(valid.match("akt"))    # Invalid.
>>> displaymatch(valid.match("727ak"))  # Valid.
"<Match: '727ak', groups=()>"

La dernière main, "727ak", contenait une paire, deux cartes de la même valeur. Pour valider cela avec une expression rationnelle, on pourrait utiliser des références arrière comme :

>>> pair = re.compile(r".*(.).*\1")
>>> displaymatch(pair.match("717ak"))     # Pair of 7s.
"<Match: '717', groups=('7',)>"
>>> displaymatch(pair.match("718ak"))     # No pairs.
>>> displaymatch(pair.match("354aa"))     # Pair of aces.
"<Match: '354aa', groups=('a',)>"

Pour trouver de quelle carte est composée la paire, on pourrait utiliser la méthode group() de l’objet de correspondance de la manière suivante :

>>> pair.match("717ak").group(1)
'7'

# Error because re.match() returns None, which doesn't have a group() method:
>>> pair.match("718ak").group(1)
Traceback (most recent call last):
  File "<pyshell#23>", line 1, in <module>
    re.match(r".*(.).*\1", "718ak").group(1)
AttributeError: 'NoneType' object has no attribute 'group'

>>> pair.match("354aa").group(1)
'a'

6.2.5.2. Simuler scanf()

Python n’a actuellement pas d’équivalent à la fonction C scanf(). Les expressions rationnelles sont généralement plus puissantes, mais aussi plus verbeuses, que les chaînes de format scanf(). Le tableau suivant présente des expressions rationnelles plus ou moins équivalentes aux éléments de formats de scanf().

Élément de scanf()

Expression rationnelle

%c

.

%5c

.{5}

%d

[-+]?\d+

%e, %E, %f, %g

[-+]?(\d+(\.\d*)?|\.\d+)([eE][-+]?\d+)?

%i

[-+]?(0[xX][\dA-Fa-f]+|0[0-7]*|\d+)

%o

[-+]?[0-7]+

%s

\S+

%u

\d+

%x, %X

[-+]?(0[xX])?[\dA-Fa-f]+

Pour extraire le nom de fichier et les nombres depuis une chaîne comme

/usr/sbin/sendmail - 0 errors, 4 warnings

vous utiliseriez un format scanf() comme

%s - %d errors, %d warnings

L’expression rationnelle équivalente serait

(\S+) - (\d+) errors, (\d+) warnings

6.2.5.3. search() vs. match()

Python offre deux opérations primitives basées sur les expressions rationnelles : re.match() cherche une correspondance uniquement au début de la chaîne, tandis que re.search() en recherche une n’importe où dans la chaîne (ce que fait Perl par défaut).

Par exemple :

>>> re.match("c", "abcdef")    # No match
>>> re.search("c", "abcdef")   # Match
<_sre.SRE_Match object; span=(2, 3), match='c'>

Les expressions rationnelles commençant par '^' peuvent être utilisées avec search() pour restreindre la recherche au début de la chaîne :

>>> re.match("c", "abcdef")    # No match
>>> re.search("^c", "abcdef")  # No match
>>> re.search("^a", "abcdef")  # Match
<_sre.SRE_Match object; span=(0, 1), match='a'>

Notez cependant qu’en mode MULTILINE, match() ne recherche qu’au début de la chaîne, alors que search() avec une expression rationnelle commençant par '^' recherchera au début de chaque ligne.

>>> re.match('X', 'A\nB\nX', re.MULTILINE)  # No match
>>> re.search('^X', 'A\nB\nX', re.MULTILINE)  # Match
<_sre.SRE_Match object; span=(4, 5), match='X'>

6.2.5.4. Construire un répertoire téléphonique

split() découpe une chaîne en une liste délimitée par le motif donné. La méthode est inestimable pour convertir des données textuelles vers des structures de données qui peuvent être lues et modifiées par Python comme démontré dans l’exemple suivant qui crée un répertoire téléphonique.

Premièrement, voici l’entrée. Elle provient normalement d’un fichier, nous utilisons ici une chaîne à guillemets triples :

>>> text = """Ross McFluff: 834.345.1254 155 Elm Street
...
... Ronald Heathmore: 892.345.3428 436 Finley Avenue
... Frank Burger: 925.541.7625 662 South Dogwood Way
...
...
... Heather Albrecht: 548.326.4584 919 Park Place"""

Les entrées sont séparées par un saut de ligne ou plus. Nous convertissons maintenant la chaîne en une liste où chaque ligne non vide aura sa propre entrée :

>>> entries = re.split("\n+", text)
>>> entries
['Ross McFluff: 834.345.1254 155 Elm Street',
'Ronald Heathmore: 892.345.3428 436 Finley Avenue',
'Frank Burger: 925.541.7625 662 South Dogwood Way',
'Heather Albrecht: 548.326.4584 919 Park Place']

Finalement, on sépare chaque entrée en une liste avec prénom, nom, numéro de téléphone et adresse. Nous utilisons le paramètre maxsplit de split() parce que l’adresse contient des espaces, qui sont notre motif de séparation :

>>> [re.split(":? ", entry, 3) for entry in entries]
[['Ross', 'McFluff', '834.345.1254', '155 Elm Street'],
['Ronald', 'Heathmore', '892.345.3428', '436 Finley Avenue'],
['Frank', 'Burger', '925.541.7625', '662 South Dogwood Way'],
['Heather', 'Albrecht', '548.326.4584', '919 Park Place']]

Le motif :? trouve les deux points derrière le nom de famille, pour qu’ils n’apparaissent pas dans la liste résultante. Avec un maxsplit de 4, nous pourrions séparer le numéro du nom de la rue :

>>> [re.split(":? ", entry, 4) for entry in entries]
[['Ross', 'McFluff', '834.345.1254', '155', 'Elm Street'],
['Ronald', 'Heathmore', '892.345.3428', '436', 'Finley Avenue'],
['Frank', 'Burger', '925.541.7625', '662', 'South Dogwood Way'],
['Heather', 'Albrecht', '548.326.4584', '919', 'Park Place']]

6.2.5.5. Mélanger les lettres des mots

sub() remplace toutes les occurrences d’un motif par une chaîne ou le résultat d’une fonction. Cet exemple le montre, en utilisant sub() avec une fonction qui mélange aléatoirement les caractères de chaque mot dans une phrase (à l’exception des premiers et derniers caractères) :

>>> def repl(m):
...     inner_word = list(m.group(2))
...     random.shuffle(inner_word)
...     return m.group(1) + "".join(inner_word) + m.group(3)
>>> text = "Professor Abdolmalek, please report your absences promptly."
>>> re.sub(r"(\w)(\w+)(\w)", repl, text)
'Poefsrosr Aealmlobdk, pslaee reorpt your abnseces plmrptoy.'
>>> re.sub(r"(\w)(\w+)(\w)", repl, text)
'Pofsroser Aodlambelk, plasee reoprt yuor asnebces potlmrpy.'

6.2.5.6. Trouver tous les adverbes

findall() matches all occurrences of a pattern, not just the first one as search() does. For example, if a writer wanted to find all of the adverbs in some text, they might use findall() in the following manner:

>>> text = "He was carefully disguised but captured quickly by police."
>>> re.findall(r"\w+ly", text)
['carefully', 'quickly']

6.2.5.7. Trouver tous les adverbes et leurs positions

If one wants more information about all matches of a pattern than the matched text, finditer() is useful as it provides match objects instead of strings. Continuing with the previous example, if a writer wanted to find all of the adverbs and their positions in some text, they would use finditer() in the following manner:

>>> text = "He was carefully disguised but captured quickly by police."
>>> for m in re.finditer(r"\w+ly", text):
...     print('%02d-%02d: %s' % (m.start(), m.end(), m.group(0)))
07-16: carefully
40-47: quickly

6.2.5.8. Notation brutes de chaînes

La notation brute de chaînes (r"text") garde saines les expressions rationnelles. Sans elle, chaque backslash ('\') dans une expression rationnelle devrait être préfixé d’un autre backslash pour l’échapper. Par exemple, les deux lignes de code suivantes sont fonctionnellement identiques :

>>> re.match(r"\W(.)\1\W", " ff ")
<_sre.SRE_Match object; span=(0, 4), match=' ff '>
>>> re.match("\\W(.)\\1\\W", " ff ")
<_sre.SRE_Match object; span=(0, 4), match=' ff '>

Pour rechercher un backslash littéral, il faut l’échapper dans l’expression rationnelle. Avec la notation brute, cela signifie r"\\". Sans elle, il faudrait utiliser "\\\\", faisant que les deux lignes de code suivantes sont fonctionnellement identiques :

>>> re.match(r"\\", r"\\")
<_sre.SRE_Match object; span=(0, 1), match='\\'>
>>> re.match("\\\\", r"\\")
<_sre.SRE_Match object; span=(0, 1), match='\\'>

6.2.5.9. Écrire un analyseur lexical

Un analyseur lexical ou scanner [https://en.wikipedia.org/wiki/Lexical_analysis] analyse une chaîne pour catégoriser les groupes de caractères. C’est une première étape utile dans l’écriture d’un compilateur ou d’un interpréteur.

Les catégories de texte sont spécifiées par des expressions rationnelles. La technique est de les combiner dans une unique expression rationnelle maîtresse, et de boucler sur les correspondances successives :

import collections
import re

Token = collections.namedtuple('Token', ['type', 'value', 'line', 'column'])

def tokenize(code):
    keywords = {'IF', 'THEN', 'ENDIF', 'FOR', 'NEXT', 'GOSUB', 'RETURN'}
    token_specification = [
        ('NUMBER',   r'\d+(\.\d*)?'),  # Integer or decimal number
        ('ASSIGN',   r':='),           # Assignment operator
        ('END',      r';'),            # Statement terminator
        ('ID',       r'[A-Za-z]+'),    # Identifiers
        ('OP',       r'[+\-*/]'),      # Arithmetic operators
        ('NEWLINE',  r'\n'),           # Line endings
        ('SKIP',     r'[ \t]+'),       # Skip over spaces and tabs
        ('MISMATCH', r'.'),            # Any other character
    ]
    tok_regex = '|'.join('(?P<%s>%s)' % pair for pair in token_specification)
    line_num = 1
    line_start = 0
    for mo in re.finditer(tok_regex, code):
        kind = mo.lastgroup
        value = mo.group()
        column = mo.start() - line_start
        if kind == 'NUMBER':
            value = float(value) if '.' in value else int(value)
        elif kind == 'ID' and value in keywords:
            kind = value
        elif kind == 'NEWLINE':
            line_start = mo.end()
            line_num += 1
            continue
        elif kind == 'SKIP':
            continue
        elif kind == 'MISMATCH':
            raise RuntimeError(f'{value!r} unexpected on line {line_num}')
        yield Token(kind, value, line_num, column)

statements = '''
    IF quantity THEN
        total := total + price * quantity;
        tax := price * 0.05;
    ENDIF;
'''

for token in tokenize(statements):
    print(token)

L’analyseur produit la sortie suivante :

Token(type='IF', value='IF', line=2, column=4)
Token(type='ID', value='quantity', line=2, column=7)
Token(type='THEN', value='THEN', line=2, column=16)
Token(type='ID', value='total', line=3, column=8)
Token(type='ASSIGN', value=':=', line=3, column=14)
Token(type='ID', value='total', line=3, column=17)
Token(type='OP', value='+', line=3, column=23)
Token(type='ID', value='price', line=3, column=25)
Token(type='OP', value='*', line=3, column=31)
Token(type='ID', value='quantity', line=3, column=33)
Token(type='END', value=';', line=3, column=41)
Token(type='ID', value='tax', line=4, column=8)
Token(type='ASSIGN', value=':=', line=4, column=12)
Token(type='ID', value='price', line=4, column=15)
Token(type='OP', value='*', line=4, column=21)
Token(type='NUMBER', value=0.05, line=4, column=23)
Token(type='END', value=';', line=4, column=27)
Token(type='ENDIF', value='ENDIF', line=5, column=4)
Token(type='END', value=';', line=5, column=9)

Frie09

Friedl, Jeffrey. Mastering Regular Expressions. 3rd ed., O’Reilly Media, 2009. La troisième édition de ce livre ne couvre plus du tout Python, mais la première version explique en détails comment écrire de bonnes expressions rationnelles.

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6.3. difflib — Helpers for computing deltas

Code source: Lib/difflib.py [https://github.com/python/cpython/tree/3.6/Lib/difflib.py]

This module provides classes and functions for comparing sequences. It can be used for example, for comparing files, and can produce difference information in various formats, including HTML and context and unified diffs. For comparing directories and files, see also, the filecmp module.

class difflib.SequenceMatcher

This is a flexible class for comparing pairs of sequences of any type, so long as the sequence elements are hashable. The basic algorithm predates, and is a little fancier than, an algorithm published in the late 1980’s by Ratcliff and Obershelp under the hyperbolic name « gestalt pattern matching. » The idea is to find the longest contiguous matching subsequence that contains no « junk » elements; these « junk » elements are ones that are uninteresting in some sense, such as blank lines or whitespace. (Handling junk is an extension to the Ratcliff and Obershelp algorithm.) The same idea is then applied recursively to the pieces of the sequences to the left and to the right of the matching subsequence. This does not yield minimal edit sequences, but does tend to yield matches that « look right » to people.

Timing: The basic Ratcliff-Obershelp algorithm is cubic time in the worst case and quadratic time in the expected case. SequenceMatcher is quadratic time for the worst case and has expected-case behavior dependent in a complicated way on how many elements the sequences have in common; best case time is linear.

Automatic junk heuristic: SequenceMatcher supports a heuristic that automatically treats certain sequence items as junk. The heuristic counts how many times each individual item appears in the sequence. If an item’s duplicates (after the first one) account for more than 1% of the sequence and the sequence is at least 200 items long, this item is marked as « popular » and is treated as junk for the purpose of sequence matching. This heuristic can be turned off by setting the autojunk argument to False when creating the SequenceMatcher.

Nouveau dans la version 3.2: The autojunk parameter.

class difflib.Differ

This is a class for comparing sequences of lines of text, and producing human-readable differences or deltas. Differ uses SequenceMatcher both to compare sequences of lines, and to compare sequences of characters within similar (near-matching) lines.

Each line of a Differ delta begins with a two-letter code:

Code

Signification

'- '

line unique to sequence 1

'+ '

line unique to sequence 2

'  '

line common to both sequences

'? '

line not present in either input sequence

Lines beginning with “?” attempt to guide the eye to intraline differences, and were not present in either input sequence. These lines can be confusing if the sequences contain tab characters.

class difflib.HtmlDiff

This class can be used to create an HTML table (or a complete HTML file containing the table) showing a side by side, line by line comparison of text with inter-line and intra-line change highlights. The table can be generated in either full or contextual difference mode.

The constructor for this class is:

__init__(tabsize=8, wrapcolumn=None, linejunk=None, charjunk=IS_CHARACTER_JUNK)

Initializes instance of HtmlDiff.

tabsize is an optional keyword argument to specify tab stop spacing and defaults to 8.

wrapcolumn is an optional keyword to specify column number where lines are broken and wrapped, defaults to None where lines are not wrapped.

linejunk and charjunk are optional keyword arguments passed into ndiff() (used by HtmlDiff to generate the side by side HTML differences). See ndiff() documentation for argument default values and descriptions.

The following methods are public:

make_file(fromlines, tolines, fromdesc='', todesc='', context=False, numlines=5, *, charset='utf-8')

Compares fromlines and tolines (lists of strings) and returns a string which is a complete HTML file containing a table showing line by line differences with inter-line and intra-line changes highlighted.

fromdesc and todesc are optional keyword arguments to specify from/to file column header strings (both default to an empty string).

context and numlines are both optional keyword arguments. Set context to True when contextual differences are to be shown, else the default is False to show the full files. numlines defaults to 5. When context is True numlines controls the number of context lines which surround the difference highlights. When context is False numlines controls the number of lines which are shown before a difference highlight when using the « next » hyperlinks (setting to zero would cause the « next » hyperlinks to place the next difference highlight at the top of the browser without any leading context).

Modifié dans la version 3.5: charset keyword-only argument was added. The default charset of HTML document changed from 'ISO-8859-1' to 'utf-8'.

make_table(fromlines, tolines, fromdesc='', todesc='', context=False, numlines=5)

Compares fromlines and tolines (lists of strings) and returns a string which is a complete HTML table showing line by line differences with inter-line and intra-line changes highlighted.

The arguments for this method are the same as those for the make_file() method.

Tools/scripts/diff.py is a command-line front-end to this class and contains a good example of its use.

difflib.context_diff(a, b, fromfile='', tofile='', fromfiledate='', tofiledate='', n=3, lineterm='\n')

Compare a and b (lists of strings); return a delta (a generator generating the delta lines) in context diff format.

Context diffs are a compact way of showing just the lines that have changed plus a few lines of context. The changes are shown in a before/after style. The number of context lines is set by n which defaults to three.

By default, the diff control lines (those with *** or ---) are created with a trailing newline. This is helpful so that inputs created from io.IOBase.readlines() result in diffs that are suitable for use with io.IOBase.writelines() since both the inputs and outputs have trailing newlines.

For inputs that do not have trailing newlines, set the lineterm argument to "" so that the output will be uniformly newline free.

The context diff format normally has a header for filenames and modification times. Any or all of these may be specified using strings for fromfile, tofile, fromfiledate, and tofiledate. The modification times are normally expressed in the ISO 8601 format. If not specified, the strings default to blanks.

>>> s1 = ['bacon\n', 'eggs\n', 'ham\n', 'guido\n']
>>> s2 = ['python\n', 'eggy\n', 'hamster\n', 'guido\n']
>>> sys.stdout.writelines(context_diff(s1, s2, fromfile='before.py', tofile='after.py'))
*** before.py
--- after.py
***************
*** 1,4 ****
! bacon
! eggs
! ham
  guido
--- 1,4 ----
! python
! eggy
! hamster
  guido

See A command-line interface to difflib for a more detailed example.

difflib.get_close_matches(word, possibilities, n=3, cutoff=0.6)

Return a list of the best « good enough » matches. word is a sequence for which close matches are desired (typically a string), and possibilities is a list of sequences against which to match word (typically a list of strings).

Optional argument n (default 3) is the maximum number of close matches to return; n must be greater than 0.

Optional argument cutoff (default 0.6) is a float in the range [0, 1]. Possibilities that don’t score at least that similar to word are ignored.

The best (no more than n) matches among the possibilities are returned in a list, sorted by similarity score, most similar first.

>>> get_close_matches('appel', ['ape', 'apple', 'peach', 'puppy'])
['apple', 'ape']
>>> import keyword
>>> get_close_matches('wheel', keyword.kwlist)
['while']
>>> get_close_matches('pineapple', keyword.kwlist)
[]
>>> get_close_matches('accept', keyword.kwlist)
['except']

difflib.ndiff(a, b, linejunk=None, charjunk=IS_CHARACTER_JUNK)

Compare a and b (lists of strings); return a Differ-style delta (a generator generating the delta lines).

Optional keyword parameters linejunk and charjunk are filtering functions (or None):

linejunk: A function that accepts a single string argument, and returns true if the string is junk, or false if not. The default is None. There is also a module-level function IS_LINE_JUNK(), which filters out lines without visible characters, except for at most one pound character ('#') – however the underlying SequenceMatcher class does a dynamic analysis of which lines are so frequent as to constitute noise, and this usually works better than using this function.

charjunk: A function that accepts a character (a string of length 1), and returns if the character is junk, or false if not. The default is module-level function IS_CHARACTER_JUNK(), which filters out whitespace characters (a blank or tab; it’s a bad idea to include newline in this!).

Tools/scripts/ndiff.py is a command-line front-end to this function.

>>> diff = ndiff('one\ntwo\nthree\n'.splitlines(keepends=True),
...              'ore\ntree\nemu\n'.splitlines(keepends=True))
>>> print(''.join(diff), end="")
- one
?  ^
+ ore
?  ^
- two
- three
?  -
+ tree
+ emu

difflib.restore(sequence, which)

Return one of the two sequences that generated a delta.

Given a sequence produced by Differ.compare() or ndiff(), extract lines originating from file 1 or 2 (parameter which), stripping off line prefixes.

Exemple :

>>> diff = ndiff('one\ntwo\nthree\n'.splitlines(keepends=True),
...              'ore\ntree\nemu\n'.splitlines(keepends=True))
>>> diff = list(diff) # materialize the generated delta into a list
>>> print(''.join(restore(diff, 1)), end="")
one
two
three
>>> print(''.join(restore(diff, 2)), end="")
ore
tree
emu

difflib.unified_diff(a, b, fromfile='', tofile='', fromfiledate='', tofiledate='', n=3, lineterm='\n')

Compare a and b (lists of strings); return a delta (a generator generating the delta lines) in unified diff format.

Unified diffs are a compact way of showing just the lines that have changed plus a few lines of context. The changes are shown in an inline style (instead of separate before/after blocks). The number of context lines is set by n which defaults to three.

By default, the diff control lines (those with ---, +++, or @@) are created with a trailing newline. This is helpful so that inputs created from io.IOBase.readlines() result in diffs that are suitable for use with io.IOBase.writelines() since both the inputs and outputs have trailing newlines.

For inputs that do not have trailing newlines, set the lineterm argument to "" so that the output will be uniformly newline free.

The context diff format normally has a header for filenames and modification times. Any or all of these may be specified using strings for fromfile, tofile, fromfiledate, and tofiledate. The modification times are normally expressed in the ISO 8601 format. If not specified, the strings default to blanks.

>>> s1 = ['bacon\n', 'eggs\n', 'ham\n', 'guido\n']
>>> s2 = ['python\n', 'eggy\n', 'hamster\n', 'guido\n']
>>> sys.stdout.writelines(unified_diff(s1, s2, fromfile='before.py', tofile='after.py'))
--- before.py
+++ after.py
@@ -1,4 +1,4 @@
-bacon
-eggs
-ham
+python
+eggy
+hamster
 guido

See A command-line interface to difflib for a more detailed example.

difflib.diff_bytes(dfunc, a, b, fromfile=b'', tofile=b'', fromfiledate=b'', tofiledate=b'', n=3, lineterm=b'\n')

Compare a and b (lists of bytes objects) using dfunc; yield a sequence of delta lines (also bytes) in the format returned by dfunc. dfunc must be a callable, typically either unified_diff() or context_diff().

Allows you to compare data with unknown or inconsistent encoding. All inputs except n must be bytes objects, not str. Works by losslessly converting all inputs (except n) to str, and calling dfunc(a, b, fromfile, tofile, fromfiledate, tofiledate, n, lineterm). The output of dfunc is then converted back to bytes, so the delta lines that you receive have the same unknown/inconsistent encodings as a and b.

Nouveau dans la version 3.5.

difflib.IS_LINE_JUNK(line)

Return true for ignorable lines. The line line is ignorable if line is blank or contains a single '#', otherwise it is not ignorable. Used as a default for parameter linejunk in ndiff() in older versions.

difflib.IS_CHARACTER_JUNK(ch)

Return true for ignorable characters. The character ch is ignorable if ch is a space or tab, otherwise it is not ignorable. Used as a default for parameter charjunk in ndiff().

Voir aussi

Pattern Matching: The Gestalt Approach [http://www.drdobbs.com/database/pattern-matching-the-gestalt-approach/184407970]

Discussion of a similar algorithm by John W. Ratcliff and D. E. Metzener. This was published in Dr. Dobb’s Journal [http://www.drdobbs.com/] in July, 1988.

6.3.1. SequenceMatcher Objects

The SequenceMatcher class has this constructor:

class difflib.SequenceMatcher(isjunk=None, a='', b='', autojunk=True)

Optional argument isjunk must be None (the default) or a one-argument function that takes a sequence element and returns true if and only if the element is « junk » and should be ignored. Passing None for isjunk is equivalent to passing lambda x: 0; in other words, no elements are ignored. For example, pass:

lambda x: x in " \t"

if you’re comparing lines as sequences of characters, and don’t want to synch up on blanks or hard tabs.

The optional arguments a and b are sequences to be compared; both default to empty strings. The elements of both sequences must be hashable.

The optional argument autojunk can be used to disable the automatic junk heuristic.

Nouveau dans la version 3.2: The autojunk parameter.

SequenceMatcher objects get three data attributes: bjunk is the set of elements of b for which isjunk is True; bpopular is the set of non-junk elements considered popular by the heuristic (if it is not disabled); b2j is a dict mapping the remaining elements of b to a list of positions where they occur. All three are reset whenever b is reset with set_seqs() or set_seq2().

Nouveau dans la version 3.2: The bjunk and bpopular attributes.

SequenceMatcher objects have the following methods:

set_seqs(a, b)

Set the two sequences to be compared.

SequenceMatcher computes and caches detailed information about the second sequence, so if you want to compare one sequence against many sequences, use set_seq2() to set the commonly used sequence once and call set_seq1() repeatedly, once for each of the other sequences.

set_seq1(a)

Set the first sequence to be compared. The second sequence to be compared is not changed.

set_seq2(b)

Set the second sequence to be compared. The first sequence to be compared is not changed.

find_longest_match(alo, ahi, blo, bhi)

Find longest matching block in a[alo:ahi] and b[blo:bhi].

If isjunk was omitted or None, find_longest_match() returns (i, j, k) such that a[i:i+k] is equal to b[j:j+k], where alo <= i <= i+k <= ahi and blo <= j <= j+k <= bhi. For all (i', j', k') meeting those conditions, the additional conditions k >= k', i <= i', and if i == i', j <= j' are also met. In other words, of all maximal matching blocks, return one that starts earliest in a, and of all those maximal matching blocks that start earliest in a, return the one that starts earliest in b.

>>> s = SequenceMatcher(None, " abcd", "abcd abcd")
>>> s.find_longest_match(0, 5, 0, 9)
Match(a=0, b=4, size=5)

If isjunk was provided, first the longest matching block is determined as above, but with the additional restriction that no junk element appears in the block. Then that block is extended as far as possible by matching (only) junk elements on both sides. So the resulting block never matches on junk except as identical junk happens to be adjacent to an interesting match.

Here’s the same example as before, but considering blanks to be junk. That prevents ' abcd' from matching the ' abcd' at the tail end of the second sequence directly. Instead only the 'abcd' can match, and matches the leftmost 'abcd' in the second sequence:

>>> s = SequenceMatcher(lambda x: x==" ", " abcd", "abcd abcd")
>>> s.find_longest_match(0, 5, 0, 9)
Match(a=1, b=0, size=4)

If no blocks match, this returns (alo, blo, 0).

This method returns a named tuple Match(a, b, size).

get_matching_blocks()

Return list of triples describing non-overlapping matching subsequences. Each triple is of the form (i, j, n), and means that a[i:i+n] == b[j:j+n]. The triples are monotonically increasing in i and j.

The last triple is a dummy, and has the value (len(a), len(b), 0). It is the only triple with n == 0. If (i, j, n) and (i', j', n') are adjacent triples in the list, and the second is not the last triple in the list, then i+n < i' or j+n < j'; in other words, adjacent triples always describe non-adjacent equal blocks.

>>> s = SequenceMatcher(None, "abxcd", "abcd")
>>> s.get_matching_blocks()
[Match(a=0, b=0, size=2), Match(a=3, b=2, size=2), Match(a=5, b=4, size=0)]

get_opcodes()

Return list of 5-tuples describing how to turn a into b. Each tuple is of the form (tag, i1, i2, j1, j2). The first tuple has i1 == j1 == 0, and remaining tuples have i1 equal to the i2 from the preceding tuple, and, likewise, j1 equal to the previous j2.

The tag values are strings, with these meanings:

Valeur

Signification

'replace'

a[i1:i2] should be replaced by b[j1:j2].

'delete'

a[i1:i2] should be deleted. Note that j1 == j2 in this case.

'insert'

b[j1:j2] should be inserted at a[i1:i1]. Note that i1 == i2 in this case.

'equal'

a[i1:i2] == b[j1:j2] (the sub-sequences are equal).

Par exemple :

>>> a = "qabxcd"
>>> b = "abycdf"
>>> s = SequenceMatcher(None, a, b)
>>> for tag, i1, i2, j1, j2 in s.get_opcodes():
...     print('{:7}   a[{}:{}] --> b[{}:{}] {!r:>8} --> {!r}'.format(
...         tag, i1, i2, j1, j2, a[i1:i2], b[j1:j2]))
delete    a[0:1] --> b[0:0]      'q' --> ''
equal     a[1:3] --> b[0:2]     'ab' --> 'ab'
replace   a[3:4] --> b[2:3]      'x' --> 'y'
equal     a[4:6] --> b[3:5]     'cd' --> 'cd'
insert    a[6:6] --> b[5:6]       '' --> 'f'

get_grouped_opcodes(n=3)

Return a generator of groups with up to n lines of context.

Starting with the groups returned by get_opcodes(), this method splits out smaller change clusters and eliminates intervening ranges which have no changes.

The groups are returned in the same format as get_opcodes().

ratio()

Return a measure of the sequences” similarity as a float in the range [0, 1].

Where T is the total number of elements in both sequences, and M is the number of matches, this is 2.0*M / T. Note that this is 1.0 if the sequences are identical, and 0.0 if they have nothing in common.

This is expensive to compute if get_matching_blocks() or get_opcodes() hasn’t already been called, in which case you may want to try quick_ratio() or real_quick_ratio() first to get an upper bound.

quick_ratio()

Return an upper bound on ratio() relatively quickly.

real_quick_ratio()

Return an upper bound on ratio() very quickly.

The three methods that return the ratio of matching to total characters can give different results due to differing levels of approximation, although quick_ratio() and real_quick_ratio() are always at least as large as ratio():

>>> s = SequenceMatcher(None, "abcd", "bcde")
>>> s.ratio()
0.75
>>> s.quick_ratio()
0.75
>>> s.real_quick_ratio()
1.0

6.3.2. SequenceMatcher Examples

This example compares two strings, considering blanks to be « junk »:

>>> s = SequenceMatcher(lambda x: x == " ",
...                     "private Thread currentThread;",
...                     "private volatile Thread currentThread;")

ratio() returns a float in [0, 1], measuring the similarity of the sequences. As a rule of thumb, a ratio() value over 0.6 means the sequences are close matches:

>>> print(round(s.ratio(), 3))
0.866

If you’re only interested in where the sequences match, get_matching_blocks() is handy:

>>> for block in s.get_matching_blocks():
...     print("a[%d] and b[%d] match for %d elements" % block)
a[0] and b[0] match for 8 elements
a[8] and b[17] match for 21 elements
a[29] and b[38] match for 0 elements

Note that the last tuple returned by get_matching_blocks() is always a dummy, (len(a), len(b), 0), and this is the only case in which the last tuple element (number of elements matched) is 0.

If you want to know how to change the first sequence into the second, use get_opcodes():

>>> for opcode in s.get_opcodes():
...     print("%6s a[%d:%d] b[%d:%d]" % opcode)
 equal a[0:8] b[0:8]
insert a[8:8] b[8:17]
 equal a[8:29] b[17:38]

Voir aussi

The get_close_matches() function in this module which shows how simple code building on SequenceMatcher can be used to do useful work.

Simple version control recipe [https://code.activestate.com/recipes/576729/] for a small application built with SequenceMatcher.

6.3.3. Differ Objects

Note that Differ-generated deltas make no claim to be minimal diffs. To the contrary, minimal diffs are often counter-intuitive, because they synch up anywhere possible, sometimes accidental matches 100 pages apart. Restricting synch points to contiguous matches preserves some notion of locality, at the occasional cost of producing a longer diff.

The Differ class has this constructor:

class difflib.Differ(linejunk=None, charjunk=None)

Optional keyword parameters linejunk and charjunk are for filter functions (or None):

linejunk: A function that accepts a single string argument, and returns true if the string is junk. The default is None, meaning that no line is considered junk.

charjunk: A function that accepts a single character argument (a string of length 1), and returns true if the character is junk. The default is None, meaning that no character is considered junk.

These junk-filtering functions speed up matching to find differences and do not cause any differing lines or characters to be ignored. Read the description of the find_longest_match() method’s isjunk parameter for an explanation.

Differ objects are used (deltas generated) via a single method:

compare(a, b)

Compare two sequences of lines, and generate the delta (a sequence of lines).

Each sequence must contain individual single-line strings ending with newlines. Such sequences can be obtained from the readlines() method of file-like objects. The delta generated also consists of newline-terminated strings, ready to be printed as-is via the writelines() method of a file-like object.

6.3.4. Differ Example

This example compares two texts. First we set up the texts, sequences of individual single-line strings ending with newlines (such sequences can also be obtained from the readlines() method of file-like objects):

>>> text1 = '''  1. Beautiful is better than ugly.
...   2. Explicit is better than implicit.
...   3. Simple is better than complex.
...   4. Complex is better than complicated.
... '''.splitlines(keepends=True)
>>> len(text1)
4
>>> text1[0][-1]
'\n'
>>> text2 = '''  1. Beautiful is better than ugly.
...   3.   Simple is better than complex.
...   4. Complicated is better than complex.
...   5. Flat is better than nested.
... '''.splitlines(keepends=True)

Next we instantiate a Differ object:

>>> d = Differ()

Note that when instantiating a Differ object we may pass functions to filter out line and character « junk. » See the Differ() constructor for details.

Finally, we compare the two:

>>> result = list(d.compare(text1, text2))

result is a list of strings, so let’s pretty-print it:

>>> from pprint import pprint
>>> pprint(result)
['    1. Beautiful is better than ugly.\n',
 '-   2. Explicit is better than implicit.\n',
 '-   3. Simple is better than complex.\n',
 '+   3.   Simple is better than complex.\n',
 '?     ++\n',
 '-   4. Complex is better than complicated.\n',
 '?            ^                     ---- ^\n',
 '+   4. Complicated is better than complex.\n',
 '?           ++++ ^                      ^\n',
 '+   5. Flat is better than nested.\n']

As a single multi-line string it looks like this:

>>> import sys
>>> sys.stdout.writelines(result)
    1. Beautiful is better than ugly.
-   2. Explicit is better than implicit.
-   3. Simple is better than complex.
+   3.   Simple is better than complex.
?     ++
-   4. Complex is better than complicated.
?            ^                     ---- ^
+   4. Complicated is better than complex.
?           ++++ ^                      ^
+   5. Flat is better than nested.

6.3.5. A command-line interface to difflib

This example shows how to use difflib to create a diff-like utility. It is also contained in the Python source distribution, as Tools/scripts/diff.py.

#!/usr/bin/env python3
""" Command line interface to difflib.py providing diffs in four formats:

* ndiff:    lists every line and highlights interline changes.
* context:  highlights clusters of changes in a before/after format.
* unified:  highlights clusters of changes in an inline format.
* html:     generates side by side comparison with change highlights.

"""

import sys, os, difflib, argparse
from datetime import datetime, timezone

def file_mtime(path):
    t = datetime.fromtimestamp(os.stat(path).st_mtime,
                               timezone.utc)
    return t.astimezone().isoformat()

def main():

    parser = argparse.ArgumentParser()
    parser.add_argument('-c', action='store_true', default=False,
                        help='Produce a context format diff (default)')
    parser.add_argument('-u', action='store_true', default=False,
                        help='Produce a unified format diff')
    parser.add_argument('-m', action='store_true', default=False,
                        help='Produce HTML side by side diff '
                             '(can use -c and -l in conjunction)')
    parser.add_argument('-n', action='store_true', default=False,
                        help='Produce a ndiff format diff')
    parser.add_argument('-l', '--lines', type=int, default=3,
                        help='Set number of context lines (default 3)')
    parser.add_argument('fromfile')
    parser.add_argument('tofile')
    options = parser.parse_args()

    n = options.lines
    fromfile = options.fromfile
    tofile = options.tofile

    fromdate = file_mtime(fromfile)
    todate = file_mtime(tofile)
    with open(fromfile) as ff:
        fromlines = ff.readlines()
    with open(tofile) as tf:
        tolines = tf.readlines()

    if options.u:
        diff = difflib.unified_diff(fromlines, tolines, fromfile, tofile, fromdate, todate, n=n)
    elif options.n:
        diff = difflib.ndiff(fromlines, tolines)
    elif options.m:
        diff = difflib.HtmlDiff().make_file(fromlines,tolines,fromfile,tofile,context=options.c,numlines=n)
    else:
        diff = difflib.context_diff(fromlines, tolines, fromfile, tofile, fromdate, todate, n=n)

    sys.stdout.writelines(diff)

if __name__ == '__main__':
    main()

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6.4. textwrap — Encapsulation et remplissage de texte

Source code: Lib/textwrap.py [https://github.com/python/cpython/tree/3.6/Lib/textwrap.py]

Le module textwrap fournit quelques fonctions pratiques, comme TextWrapper, la classe qui fait tout le travail. Si vous ne faites que formater ou ajuster une ou deux chaînes de texte, les fonctions de commodité devraient être assez bonnes ; sinon, nous vous conseillons d’utiliser une instance de TextWrapper pour une meilleure efficacité.

textwrap.wrap(text, width=70, **kwargs)

Reformate le paragraphe simple dans text (une chaîne de caractères) de sorte que chaque ligne ait au maximum largeur caractères. Renvoie une liste de lignes de sortie, sans ligne vide ou caractère de fin de ligne à la fin.

Les arguments par mot-clé optionnels correspondent aux attributs d’instance de TextWrapper, documentés ci-dessous. width vaut 70 par défaut.

Consultez la méthode TextWrapper.wrap() pour plus de détails sur le comportement de wrap().

textwrap.fill(text, width=70, **kwargs)

Formate le paragraphe unique dans text et renvoie une seule chaîne dont le contenu est le paragraphe formaté. fill() est un raccourci pour

"\n".join(wrap(text, ...))

En particulier, fill() accepte exactement les mêmes arguments par mot-clé que wrap().

textwrap.shorten(text, width, **kwargs)

Réduit et tronque le text donné pour l’adapter à la largeur donnée.

Tout d’abord, les espaces dans text sont réduites (toutes les espaces blancs sont remplacées par des espaces simples). Si le résultat tient dans la width, il est renvoyé. Sinon, suffisamment de mots sont supprimés en fin de chaîne de manière à ce que les mots restants plus le placeholder tiennent dans width :

>>> textwrap.shorten("Hello  world!", width=12)
'Hello world!'
>>> textwrap.shorten("Hello  world!", width=11)
'Hello [...]'
>>> textwrap.shorten("Hello world", width=10, placeholder="...")
'Hello...'

Les arguments par mot-clé optionnels correspondent aux attributs d’instance de TextWrapper, documentés ci-dessous. Notez que l’espace blanc est réduit avant que le texte ne soit passé à la fonction fill() de TextWrapper, donc changer la valeur de tabsize, expand_tabs, drop_whitespace, et replace_whitespace est sans effet.

Nouveau dans la version 3.4.

textwrap.dedent(text)

Supprime toutes les espaces en de tête de chaque ligne dans text.

Ceci peut être utilisé pour aligner les chaînes à trois guillemets avec le bord gauche de l’affichage, tout en les présentant sous forme indentée dans le code source.

Notez que les tabulations et les espaces sont traitées comme des espaces, mais qu’elles ne sont pas égales : les lignes "  hello" et "\thello" sont considérées comme n’ayant pas d’espaces de tête communes.

Par exemple :

def test():
    # end first line with \ to avoid the empty line!
    s = '''\
    hello
      world
    '''
    print(repr(s))          # prints '    hello\n      world\n    '
    print(repr(dedent(s)))  # prints 'hello\n  world\n'

textwrap.indent(text, prefix, predicate=None)

Ajoute prefix au début des lignes sélectionnées dans text.

Les lignes sont séparées en appelant text.splitlines(True).

Par défaut, prefix est ajouté à toutes les lignes qui ne sont pas constituées uniquement d’espaces (y compris les fins de ligne).

Par exemple :

>>> s = 'hello\n\n \nworld'
>>> indent(s, '  ')
'  hello\n\n \n  world'

L’argument optionnel predicate peut être utilisé pour contrôler quelles lignes sont en retrait. Par exemple, il est facile d’ajouter prefix aux lignes vides et aux lignes blanches seulement :

>>> print(indent(s, '+ ', lambda line: True))
+ hello
+
+
+ world

Nouveau dans la version 3.3.

wrap(), fill() et shorten() travaillent en créant une instance TextWrapper et en appelant une méthode unique sur celle-ci. Cette instance n’est pas réutilisée, donc pour les applications qui traitent plusieurs chaînes de texte en utilisant wrap() et/ou fill(), il peut être plus efficace de créer votre propre objet TextWrapper.

Le formatage du texte s’effectue en priorité sur les espaces puis juste après les traits d’union dans des mots séparés par des traits d’union ; ce n’est qu’alors que les mots longs seront cassés si nécessaire, à moins que TextWrapper.break_long_words soit défini sur False.

class textwrap.TextWrapper(**kwargs)

Le constructeur TextWrapper accepte un certain nombre d’arguments par mots-clés optionnels. Chaque argument par mot-clé correspond à un attribut d’instance, donc par exemple

wrapper = TextWrapper(initial_indent="* ")

est identique à

wrapper = TextWrapper()
wrapper.initial_indent = "* "

Vous pouvez réutiliser le même objet TextWrapper plusieurs fois et vous pouvez changer n’importe laquelle de ses options par assignation directe aux attributs d’instance entre les utilisations.

Les attributs d’instance de la classe TextWrapper (et les arguments par mot-clé au constructeur) sont les suivants :

width

(par défaut : 70`) Longueur maximale des lignes reformatées. Tant qu’il n’y a pas de mots individuels dans le texte d’entrée plus longs que width, TextWrapper garantit qu’aucune ligne de sortie n’est plus longue que width caractères.

expand_tabs

(par défaut : True) Si true, alors tous les caractères de tabulation dans text sont transformés en espaces en utilisant la méthode expandtabs() de text.

tabsize

(par défaut : 8) Si expand_tabs est true, alors tous les caractères de tabulation dans text sont transformés en zéro ou plus d’espaces, selon la colonne courante et la taille de tabulation donnée.

Nouveau dans la version 3.3.

replace_whitespace

(par défaut : True) Si true, après l’expansion des tabulations mais avant le formatage, la méthode wrap() remplace chaque blanc par une espace unique. Les blancs remplacés sont les suivants : tabulation, nouvelle ligne, tabulation verticale, saut de page et retour chariot ('\t\n\v\f\r').

Note

Si expand_tabs est False et replace_whitespace est vrai, chaque caractère de tabulation est remplacé par une espace unique, ce qui n’est pas la même chose que l’extension des tabulations.

Note

Si replace_whitespace est faux, de nouvelles lignes peuvent apparaître au milieu d’une ligne et provoquer une sortie étrange. Pour cette raison, le texte doit être divisé en paragraphes (en utilisant str.splitlines() ou similaire) qui sont formatés séparément.

drop_whitespace

(par défaut : True) Si True, l’espace au début et à la fin de chaque ligne (après le formatage mais avant l’indentation) est supprimée. L’espace au début du paragraphe n’est cependant pas supprimée si elle n’est pas suivie par une espace. Si les espaces en cours de suppression occupent une ligne entière, la ligne entière est supprimée.

initial_indent

(par défaut : `''`) Chaîne qui est ajoutée à la première ligne de la sortie formatée. Elle compte pour le calcul de la longueur de la première ligne. La chaîne vide n’est pas indentée.

subsequent_indent

(par défaut : `''`) Chaîne qui préfixe toutes les lignes de la sortie formatée sauf la première. Elle compte pour le calcul de la longueur de chaque ligne à l’exception de la première.

fix_sentence_endings

(par défaut : Faux) Si true, TextWrapper tente de détecter les fins de phrases et de s’assurer que les phrases sont toujours séparées par exactement deux espaces. Ceci est généralement souhaité pour un texte en police à chasse fixe. Cependant, l’algorithme de détection de phrase est imparfait : il suppose qu’une fin de phrase consiste en une lettre minuscule suivie de l’une des lettres suivantes : '.', '!', ou '?', éventuellement suivie d’une des lettres '"' ou "'", suivie par une espace. Un problème avec cet algorithme est qu’il est incapable de détecter la différence entre « Dr » dans

[...] Dr. Frankenstein's monster [...]

et « Spot. » dans

[...] See Spot. See Spot run [...]

fix_sentence_endings est False par défaut.

Étant donné que l’algorithme de détection de phrases repose sur string.lowercase pour la définition de « lettres minuscules » et sur une convention consistant à utiliser deux espaces après un point pour séparer les phrases sur la même ligne, ceci est spécifique aux textes de langue anglaise.

break_long_words

(par défaut : True) Si True, alors les mots plus longs que width sont cassés afin de s’assurer qu’aucune ligne ne soit plus longue que width. Si c’est False, les mots longs ne sont pas cassés et certaines lignes peuvent être plus longues que width (les mots longs seront mis sur une ligne qui leur est propre, afin de minimiser le dépassement de width).

break_on_hyphens

(par défaut : True) Si c’est vrai, le formatage se fait de préférence sur les espaces et juste après sur les traits d’union des mots composés, comme il est d’usage en anglais. Si False, seuls les espaces sont considérées comme de bons endroits pour les sauts de ligne, mais vous devez définir break_long_words à False si vous voulez des mots vraiment insécables. Le comportement par défaut dans les versions précédentes était de toujours permettre de couper les mots avec trait d’union.

max_lines

(par défaut : None`) Si ce n’est pas None`, alors la sortie contient au maximum max_lines lignes, avec placeholder à la fin de la sortie.

Nouveau dans la version 3.4.

placeholder

(par défaut : '' [...]') Chaîne qui apparaît à la fin du texte de sortie s’il a été tronqué.

Nouveau dans la version 3.4.

TextWrapper fournit également quelques méthodes publiques, analogues aux fonctions de commodité au niveau du module :

wrap(text)

Formate le paragraphe unique dans text (une chaîne de caractères) de sorte que chaque ligne ait au maximum width caractères. Toutes les options de formatage sont tirées des attributs d’instance de l’instance de classe TextWrapper. Renvoie une liste de lignes de sortie, sans nouvelles lignes finales. Si la sortie formatée n’a pas de contenu, la liste vide est renvoyée.

fill(text)

Formate le paragraphe unique de text et renvoie une seule chaîne contenant le paragraphe formaté.

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6.5. unicodedata — Base de données Unicode

This module provides access to the Unicode Character Database (UCD) which defines character properties for all Unicode characters. The data contained in this database is compiled from the UCD version 9.0.0 [http://www.unicode.org/Public/9.0.0/ucd].

Ce module utilise les mêmes noms et symboles définis dans l’annexe 44 du standard Unicode (Unicode Standard Annex), « Unicode Character Database » [http://www.unicode.org/reports/tr44/tr44-6.html]. Il définit les fonctions suivantes :

unicodedata.lookup(name)

Retrouver un caractère par nom. Si un caractère avec le nom donné est trouvé, renvoyer le caractère correspondant. S’il n’est pas trouvé, KeyError est levée.

Modifié dans la version 3.3: La gestion des alias 1 et des séquences nommées 2 a été ajouté.

unicodedata.name(chr[, default])

Renvoie le nom assigné au caractère chr comme une chaîne de caractères. Si aucun nom n’est défini, default est renvoyé, ou, si ce dernier n’est pas renseigné ValueError est levée.

unicodedata.decimal(chr[, default])

Renvoie la valeur décimale assignée au caractère chr comme un entier. Si aucune valeur de ce type n’est définie, default est renvoyé, ou, si ce dernier n’est pas renseigné, ValueError est levée.

unicodedata.digit(chr[, default])

Renvoie le chiffre assigné au caractère chr comme un entier. Si aucune valeur de ce type n’est définie, default est renvoyé, ou, si ce dernier n’est pas renseigné, ValueError est levée.

unicodedata.numeric(chr[, default])

Renvoie la valeur numérique assignée au caractère chr comme un entier. Si aucune valeur de ce type n’est définie, default est renvoyé, ou, si ce dernier n’est pas renseigné, ValueError est levée.

unicodedata.category(chr)

Renvoie la catégorie générale assignée au caractère chr comme une chaîne de caractères.

unicodedata.bidirectional(chr)

Renvoie la classe bidirectionnelle assignée au caractère chr comme une chaîne de caractères. Si aucune valeur de ce type n’est définie, une chaîne de caractères vide est renvoyée.

unicodedata.combining(chr)

Renvoie la classe de combinaison canonique assignée au caractère chr comme un entier. Envoie 0 si aucune classe de combinaison n’est définie.

unicodedata.east_asian_width(chr)

Renvoie la largeur est-asiatique assignée à un caractère chr comme une chaîne de caractères.

unicodedata.mirrored(chr)

Renvoie la propriété miroir assignée au caractère chr comme un entier. Renvoie 1 si le caractère a été identifié comme un caractère « réfléchi » dans du texte bidirectionnel, sinon 0.

unicodedata.decomposition(chr)

Renvoie le tableau associatif de décomposition de caractère assigné au caractère chr comme une chaîne de caractères. Une chaîne de caractère vide est renvoyée dans le cas où aucun tableau associatif de ce type n’est défini.

unicodedata.normalize(form, unistr)

Renvoie la forme normale form de la chaîne de caractère Unicode unistr. Les valeurs valides de form sont NFC, NFKC, NFD, et NFKD.

Le standard Unicode définit les différentes variantes de normalisation d’une chaîne de caractères Unicode en se basant sur les définitions d’équivalence canonique et d’équivalence de compatibilité. En Unicode, plusieurs caractères peuvent être exprimés de différentes façons. Par exemple, le caractère U+00C7 (LATIN CAPITAL LETTER C WITH CEDILLA) peut aussi être exprimé comme la séquence U+0043 (LATIN CAPITAL LETTER C) U+0327 (COMBINING CEDILLA).

Pour chaque caractère, il existe deux formes normales: la forme normale C et la forme normale D. La forme normale D (NFD) est aussi appelée décomposition canonique, et traduit chaque caractère dans sa forme décomposée. La forme normale C (NFC) applique d’abord la décomposition canonique, puis compose à nouveau les caractères pré-combinés.

En plus de ces deux formes, il existe deux formes nominales basées sur l’équivalence de compatibilité. En Unicode, certains caractères sont gérés alors qu’ils sont normalement unifiés avec d’autres caractères. Par exemple, U+2160 (ROMAN NUMERAL ONE) est vraiment la même chose que U+0049 (LATIN CAPITAL LETTER I). Cependant, ce caractère est supporté par souci de compatibilité avec les jeux de caractères existants (par exemple gb2312).

La forme normale KD (NFKD) applique la décomposition de compatibilité, c’est-à-dire remplacer les caractères de compatibilités avec leurs équivalents. La forme normale KC (NFKC) applique d’abord la décomposition de compatibilité, puis applique la composition canonique.

Même si deux chaînes de caractères Unicode sont normalisées et ont la même apparence pour un lecteur humain , si un a des caractères combinés et l’autre n’en a pas, elles peuvent ne pas être égales lors d’une comparaison.

De plus, ce module expose la constante suivante:

unicodedata.unidata_version

La version de la base de données Unicode utilisée dans ce module.

unicodedata.ucd_3_2_0

Ceci est un objet qui a les mêmes méthodes que le module, mais qui utilise la version 3.2 de la base de données Unicode, pour les applications qui nécessitent cette version spécifique de la base de données Unicode (comme l’IDNA).

Exemples :

>>> import unicodedata
>>> unicodedata.lookup('LEFT CURLY BRACKET')
'{'
>>> unicodedata.name('/')
'SOLIDUS'
>>> unicodedata.decimal('9')
9
>>> unicodedata.decimal('a')
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
ValueError: not a decimal
>>> unicodedata.category('A')  # 'L'etter, 'u'ppercase
'Lu'
>>> unicodedata.bidirectional('\u0660') # 'A'rabic, 'N'umber
'AN'

Notes

1

http://www.unicode.org/Public/9.0.0/ucd/NameAliases.txt

2

http://www.unicode.org/Public/9.0.0/ucd/NamedSequences.txt

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6.6. stringprep — Préparation des chaines de caractères internet

Code source : Lib/stringprep.py [https://github.com/python/cpython/tree/3.6/Lib/stringprep.py]

Nommer les différentes choses d’internet (comme les hôtes) amène souvent au besoin de comparer ces identifiants, ce qui nécessite un critère d”« égalité ». La manière dont cette comparaison est effectuée dépend du domaine d’application, c’est-à-dire si elle doit être sensible à la casse ou non. Il peut être aussi nécessaire de restreindre les identifiants possibles, pour permettre uniquement les identifiants composés de caractères « imprimables ».

La RFC 3454 [https://tools.ietf.org/html/rfc3454.html] définit une procédure pour « préparer » des chaines de caractères Unicode dans les protocoles internet. Avant de passer des chaines de caractères sur le câble, elles sont traitées avec la procédure de préparation, après laquelle ils obtiennent une certaines forme normalisée. Les RFC définissent un lot de tables, qui peuvent être combinées en profils. Chaque profil doit définir quelles tables il utilise et quelles autres parties optionnelles de la procédure stringprep font partie du profil. Un exemple de profil stringprep est nameprep, qui est utilisé pour les noms de domaine internationalisés.

Le module stringprep expose uniquement les tables de la RFC 3454 [https://tools.ietf.org/html/rfc3454.html]. Comme ces tables seraient très grandes à représenter en tant que dictionnaires ou listes, le module utilise, en interne, la base de données des caractères Unicode. Le code source du module, lui-même, a été généré en utilisant l’utilitaire mkstringprep.py.

En conséquence, ces tables sont exposées en tant que fonctions et non en structures de données. Il y a deux types de tables dans la RFC : les ensemble et les mises en correspondance. Pour un ensemble, stringprep fournit la « fonction caractéristique », c’est-à-dire une fonction qui renvoie vrai si le paramètre fait partie de l’ensemble. Pour les mises en correspondance, il fournit la fonction de mise en correspondance : ayant obtenu la clé, il renvoie la valeur associée. Ci-dessous se trouve une liste de toutes les fonctions disponibles dans le module.

stringprep.in_table_a1(code)

Détermine si le code est en table A.1 (points de code non-assigné dans Unicode 3.2).

stringprep.in_table_b1(code)

Détermine si le code est en table B.1 (habituellement mis en correspondance avec rien).

stringprep.map_table_b2(code)

Renvoie la valeur correspondante à code selon la table B.2 (mise en correspondance pour la gestion de la casse utilisée avec NFKC).

stringprep.map_table_b3(code)

Renvoie la valeur correspondante à code dans la table B.3 (mise en correspondance pour la gestion de la casse utilisée sans normalisation).

stringprep.in_table_c11(code)

Détermine si le code est dans la table C.1.1 (caractères d’espacement ASCII).

stringprep.in_table_c12(code)

Détermine si le code est dans la table C.1.2 (caractères d’espacement non ASCII).

stringprep.in_table_c11_c12(code)

Détermine si le code est dans la table C.1 (caractères d’espacement, union de C.1.1 et C.1.2).

stringprep.in_table_c21(code)

Détermine si le code est dans la table C.2.1 (caractères de contrôle ASCII).

stringprep.in_table_c22(code)

Détermine si le code est en table C.2.2 (caractères de contrôle non ASCII).

stringprep.in_table_c21_c22(code)

Détermine si le code est dans la table C.2 (caractères de contrôle, union de C.2.1 et C.2.2).

stringprep.in_table_c3(code)

Détermine si le code est en table C.3 (usage privé).

stringprep.in_table_c4(code)

Détermine si le code est dans la table C.4 (points de code non-caractère).

stringprep.in_table_c5(code)

Détermine si le code est en table C.5 (codes substituts).

stringprep.in_table_c6(code)

Détermine si le code est dans la table C.6 (Inapproprié pour texte brut).

stringprep.in_table_c7(code)

Détermine si le code est dans la table C.7 (inapproprié pour les représentations canonics1).

stringprep.in_table_c8(code)

Détermine si le code est dans la table C.8 (change de propriétés d’affichage ou sont obsolètes).

stringprep.in_table_c9(code)

Détermine si le code est dans la table C.9 (caractères de marquage).

stringprep.in_table_d1(code)

Détermine si le code est en table D.1 (caractères avec propriété bidirectionnelle « R » ou « AL »).

stringprep.in_table_d2(code)

Détermine si le code est dans la table D.2 (caractères avec propriété bidirectionnelle « L »).

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6.7. readline — interface pour GNU readline

Le module readline définit des fonctions pour faciliter la complétion et la lecture/écriture des fichiers d’historique depuis l’interpréteur Python. Ce module peut être utilisé directement, ou depuis le module rlcompleter, qui gère la complétion des mots clefs dans l’invite de commande interactive. Les paramétrages faits en utilisant ce module affectent à la fois le comportement de l’invite de commande interactive et l’invite de commande fournie par la fonction native input().

Note

The underlying Readline library API may be implemented by the libedit library instead of GNU readline. On MacOS X the readline module detects which library is being used at run time.

Le fichier de configuration pour libedit est différent de celui de GNU readline. Si, dans votre programme, vous chargez les chaines de configuration vous pouvez valider le texte libedit dans readline.__doc__ pour faire la différence entre GNU readline et libedit.

L’association de touches de readline peut être configurée via un fichier d’initialisation, typiquement nommé .inputrc dans votre répertoire utilisateur. Voir Readline Init File [https://cnswww.cns.cwru.edu/php/chet/readline/rluserman.html#SEC9] dans le manuel GNU pour readline pour des information à propos du format et de la construction autorisée de ce fichier, ainsi que les possibilités de la bibliothèque readline en général.

6.7.1. Fichier d’initialisation

Les fonctions suivantes se rapportent au fichier d’initialisation et à la configuration utilisateur.

readline.parse_and_bind(string)

Exécute la ligne d’initialisation fournie dans l’argument string. Cela appelle la fonction rl_parse_and_bind() de la bibliothèque sous-jacente.

readline.read_init_file([filename])

Exécute un fichier d’initialisation readline. Le nom de fichier par défaut est le dernier nom de fichier utilisé. Cela appelle la fonction rl_read_init_file() de la bibliothèque sous-jacente.

6.7.2. Tampon de ligne

Les fonctions suivantes opèrent sur le tampon de ligne:

readline.get_line_buffer()

Renvoie le contenu courant du tampon de ligne (rl_line_buffer dans la bibliothèque sous-jacente).

readline.insert_text(string)

Insère du texte dans le tampon de ligne à la position du curseur. Cela appelle la fonction rl_insert_text() de la bibliothèque sous-jacente, mais ignore la valeur de retour.

readline.redisplay()

Change ce qui est affiché sur l’écran pour représenter le contenu courant de la ligne de tampon. Cela appelle la fonction rl_redisplay() dans la bibliothèque sous-jacente.

6.7.3. Fichier d’historique

les fonctions suivantes opèrent sur un fichier d’historique :

readline.read_history_file([filename])

Charge un fichier d’historique de readline, et l’ajoute à la liste d’historique. Le fichier par défaut est ~/.history. Cela appelle la fonction read_history() de la bibliothèque sous-jacente.

readline.write_history_file([filename])

Enregistre la liste de l’historique dans un fichier d’historique de readline, en écrasant un éventuel fichier existant. Le nom de fichier par défaut est ~/.history. Cela appelle la fonction write_history() de la bibliothèque sous-jacente.

readline.append_history_file(nelements[, filename])

Ajoute les derniers objets nelements de l’historique dans un fichier. Le nom de fichier par défaut est ~/.history. Le fichier doit déjà exister. Cela appelle la fonction append_history() de la bibliothèque sous-jacente.

Nouveau dans la version 3.5.

readline.get_history_length()

readline.set_history_length(length)

Définit ou renvoie le nombre souhaité de lignes à enregistrer dans le fichier d’historique. La fonction write_history_file() utilise cette valeur pour tronquer le fichier d’historique, en appelant history_truncate_file() de la bibliothèque sous-jacente. Les valeurs négatives impliquent une taille de fichier d’historique illimitée.

6.7.4. Liste d’historique

Les fonctions suivantes opèrent sur une liste d’historique globale :

readline.clear_history()

Effacer l’historique courant. Cela appelle la fonction clear_history() de la bibliothèque sous-jacente. La fonction Python existe seulement si Python à été compilé pour une version de la bibliothèque qui le gère.

readline.get_current_history_length()

Renvoie le nombre d’objets actuellement dans l’historique. (C’est différent de get_history_length(), qui renvoie le nombre maximum de lignes qui vont être écrites dans un fichier d’historique.)

readline.get_history_item(index)

Renvoie le contenu courant de l’objet d’historique à index. L’index de l’objet commence à 1. Cela appelle history_get() de la bibliothèque sous-jacente.

readline.remove_history_item(pos)

Supprime l’objet de l’historique défini par sa position depuis l’historique. L’index de la position commence à zéro. Cela appelle la fonction remove_history() de la bibliothèque sous-jacente.

readline.replace_history_item(pos, line)

Remplace un objet de l’historique à la position définie par line. L’index de la position commence à zéro. Cela appelle replace_history_entry() de la bibliothèque sous-jacente.

readline.add_history(line)

Ajoute line au tampon d’historique, comme si c’était la dernière ligne saisie. Cela appelle la fonction add_history() de la libraire sous-jacente.

readline.set_auto_history(enabled)

Active ou désactive les appels automatiques à la fonction add_history() lors de la lecture d’une entrée via readline. L’argument enabled doit être une valeur booléenne qui lorsqu’elle est vraie, active l’historique automatique, et qui lorsqu’elle est fausse, désactive l’historique automatique.

Nouveau dans la version 3.6.

CPython implementation detail: Auto history is enabled by default, and changes to this do not persist across multiple sessions.

6.7.5. Fonctions de rappel au démarrage

readline.set_startup_hook([function])

Définit ou supprime la fonction invoquée par le la fonction de retour rl_startup_hook de la bibliothèque sous-jacente. Si function est spécifié, il est utilisé en tant que nouvelle fonction de rappel ; si omis ou None, toute fonction déjà installée est supprimée. La fonction de rappel est appelée sans arguments juste avant que readline affiche la première invite de commande.

readline.set_pre_input_hook([function])

Définit ou supprime la fonction invoquée par la fonction de retour rl_pre_input_hook de la bibliothèque sous-jacente. Si function est spécifié, il sera utilisé par la nouvelle fonction de rappel ; si omis ou None, toute fonction déjà installée est supprimée. La fonction de rappel est appelée sans arguments après que la première invite de commande ait été affichée et juste avant que readline commence à lire les caractères saisis. Cette fonction existe seulement si Python a été compilé pour une version de la bibliothèque qui le gère.

6.7.6. Complétion

Les fonctions suivantes relatent comment implémenter une fonction de complétion d’un mot spécifique. C’est typiquement déclenché par la touche Tab, et peut suggérer et automatiquement compléter un mot en cours de saisie. Par défaut, Readline est configuré pour être utilisé par rlcompleter pour compléter les mots clefs de Python pour l’interpréteur interactif. Si le module readline doit être utilisé avec une complétion spécifique, un ensemble de mots délimiteurs doivent être définis.

readline.set_completer([function])

Définit ou supprime la fonction de complétion. Si function est spécifié, il sera utilisé en tant que nouvelle fonction de complétion; si omis ou None, toute fonction de complétion déjà installé est supprimé. La fonction de complétion est appelée telle que function(text, state), pour state valant 0, 1, 2, …, jusqu’à ce qu’elle renvoie une valeur qui n’est pas une chaîne de caractères. Elle doit renvoyer les prochaines complétions possibles commençant par text.

La fonction de complétion installée est invoquée par la fonction de retour entry_func passée à rl_completion_matches() de la bibliothèque sous-jacente. La chaîne de caractère text va du premier paramètres vers la fonction de retour rl_attempted_completion_function de la bibliothèque sous-jacente.

readline.get_completer()

Récupère la fonction de complétion, ou None si aucune fonction de complétion n’a été définie.

readline.get_completion_type()

Récupère le type de complétion essayé. Cela renvoie la variable rl_completion_type dans la bibliothèque sous-jacente en tant qu’entier.

readline.get_begidx()

readline.get_endidx()

Récupère l’indexe de début ou de fin d’un contexte de complétion. Ces indexes sont les arguments start et end passés à la fonction de retour rl_attempted_completion_function de la bibliothèque sous-jacente.

readline.set_completer_delims(string)

readline.get_completer_delims()

Définit ou récupère les mots délimitants pour la complétion. Ceux-ci déterminent le début du mot devant être considéré pour la complétion (le contexte de la complétion). Ces fonctions accèdent à la variable rl_completer_word_break_characters de la bibliothèque sous-jacente.

readline.set_completion_display_matches_hook([function])

Définit ou supprime la fonction d’affichage de la complétion. Si function est spécifié, il sera utilisé en tant que nouvelle fonction d’affichage de complétion; si omis ou None, toute fonction de complétion déjà installée est supprimée. Cela définit ou supprime la fonction de retour rl_completion_display_matches_hook dans la bibliothèque sous-jacente. La fonction d’affichage de complétion est appelée telle que function(substitution, [matches], longest_match_length) une seule fois lorsque les correspondances doivent être affichées.

6.7.7. Exemple

L’exemple suivant démontre comment utiliser les fonctions de lecture et d’écriture de l’historique du module readline pour charger ou sauvegarder automatiquement un fichier d’historique nommé .python_history depuis le répertoire d’accueil de l’utilisateur. Le code ci-dessous doit normalement être exécuté automatiquement durant une session interactive depuis le fichier de l’utilisateur PYTHONSTARTUP.

import atexit
import os
import readline

histfile = os.path.join(os.path.expanduser("~"), ".python_history")
try:
    readline.read_history_file(histfile)
    # default history len is -1 (infinite), which may grow unruly
    readline.set_history_length(1000)
except FileNotFoundError:
    pass

atexit.register(readline.write_history_file, histfile)

Ce code est en réalité automatiquement exécuté lorsque Python tourne en mode interactif (voir Readline configuration).

L’exemple suivant atteint le même objectif mais gère des sessions interactives concurrentes, en ajoutant seulement le nouvel historique.

import atexit
import os
import readline
histfile = os.path.join(os.path.expanduser("~"), ".python_history")

try:
    readline.read_history_file(histfile)
    h_len = readline.get_current_history_length()
except FileNotFoundError:
    open(histfile, 'wb').close()
    h_len = 0

def save(prev_h_len, histfile):
    new_h_len = readline.get_current_history_length()
    readline.set_history_length(1000)
    readline.append_history_file(new_h_len - prev_h_len, histfile)
atexit.register(save, h_len, histfile)

L’exemple suivant étend la classe code.InteractiveConsole pour gérer la sauvegarde/restauration de l’historique.

import atexit
import code
import os
import readline

class HistoryConsole(code.InteractiveConsole):
    def __init__(self, locals=None, filename="<console>",
                 histfile=os.path.expanduser("~/.console-history")):
        code.InteractiveConsole.__init__(self, locals, filename)
        self.init_history(histfile)

    def init_history(self, histfile):
        readline.parse_and_bind("tab: complete")
        if hasattr(readline, "read_history_file"):
            try:
                readline.read_history_file(histfile)
            except FileNotFoundError:
                pass
            atexit.register(self.save_history, histfile)

    def save_history(self, histfile):
        readline.set_history_length(1000)
        readline.write_history_file(histfile)

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6.8. rlcompleter — Fonction de complétion pour GNU readline

Code source : Lib/rlcompleter.py [https://github.com/python/cpython/tree/3.6/Lib/rlcompleter.py]

Le module rlcompleter définit une fonction de complétion appropriée pour le module readline en complétant des identifiants et mots-clés Python valides.

Quand le module est importé dans une plate-forme Unix et la méthode complete() est configurée pour assurer la complétion de readline, une instance de classe Completer est automatiquement créée et la méthode est configurée au finisseur complete()

Exemple :

>>> import rlcompleter
>>> import readline
>>> readline.parse_and_bind("tab: complete")
>>> readline. <TAB PRESSED>
readline.__doc__          readline.get_line_buffer(  readline.read_init_file(
readline.__file__         readline.insert_text(      readline.set_completer(
readline.__name__         readline.parse_and_bind(
>>> readline.

Le module rlcompleter est conçu pour être utilisé par le mode interactif de Python. À moins que Python ne soit exécuté avec l’option -S, le module est automatiquement importé et configuré (voir Readline configuration).

Sur les plate-formes sans readline, la classe Completer définie par ce module peut quand même être utilisée pour des fins personnalisées.

6.8.1. Objets pour la complétion (Completer Objects)

Les objets pour la complétion (Completer objects en anglais) disposent de la méthode suivante :

Completer.complete(text, state)

Renvoie la state-ième complétion pour text.

Si text ne contient pas un caractère point ('.'), il puise dans les noms actuellement définis dans __main__, builtins ainsi que les mots-clés (ainsi que définis par le module keyword)

Quand elle est appelée pour un nom qui comporte un point, elle ne tente d’évaluer que ce qui n’a pas d’effet secondaire (les fonctions ne sont pas évaluées, mais elle peut faire des appels à __getattr__()), jusqu’à la dernière partie, et trouve des équivalents pour le reste via la fonction dir(). Toute exception levée durant l’évaluation de l’expression est interceptée, mise sous silence, et None est renvoyé.

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7. Services autour des Données Binaires

Les modules décrits dans ce chapitre fournissent des services élémentaires pour manipuler des données binaires. Les autres manipulations sur les données binaires, particulièrement celles en relation avec les formats de fichier et les protocoles réseaux sont décrits dans leurs propres chapitres.

Certaines bibliothèques décrites dans Services de Manipulation de Texte fonctionnent aussi avec soit des formats binaires compatibles ASCII (comme le module re) soit toutes les données binaires (comme le module difflib).

En complément, consultez la documentation des types natifs binaires dans Séquences Binaires — bytes, bytearray, memoryview.

7.1. struct — manipulation de données agrégées sous forme binaire comme une séquence d’octets

7.1.1. Fonctions et exceptions

7.1.2. Chaînes de spécification du format

7.1.2.1. Boutisme, taille et alignement

7.1.2.2. Caractères de format

7.1.2.3. Exemples

7.1.3. Classes

7.2. codecs — Registre des codecs et classes de base associées

7.2.1. Classes de base de codecs

7.2.1.1. Gestionnaires d’erreurs

7.2.1.2. Stateless Encoding and Decoding

7.2.1.3. Incremental Encoding and Decoding

7.2.1.3.1. IncrementalEncoder Objects

7.2.1.3.2. IncrementalDecoder Objects

7.2.1.4. Stream Encoding and Decoding

7.2.1.4.1. StreamWriter Objects

7.2.1.4.2. StreamReader Objects

7.2.1.4.3. StreamReaderWriter Objects

7.2.1.4.4. StreamRecoder Objects

7.2.2. Encodings and Unicode

7.2.3. Standard Encodings

7.2.4. Python Specific Encodings

7.2.4.1. Text Encodings

7.2.4.2. Binary Transforms

7.2.4.3. Text Transforms

7.2.5. encodings.idna — Internationalized Domain Names in Applications

7.2.6. encodings.mbcs — Windows ANSI codepage

7.2.7. encodings.utf_8_sig — UTF-8 codec with BOM signature

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7.1. struct — manipulation de données agrégées sous forme binaire comme une séquence d’octets

Code source : Lib/struct.py [https://github.com/python/cpython/tree/3.6/Lib/struct.py]

Ce module effectue des conversions entre des valeurs Python et des structures C représentées sous la forme de bytes (séquences d’octets) Python. Cela permet, entre autres, de manipuler des données agrégées sous forme binaire dans des fichiers ou à travers des connecteurs réseau. Il utilise Chaînes de spécification du format comme description de l’agencement des structures afin de réaliser les conversions depuis et vers les valeurs Python.

Note

par défaut, le résultat de l’agrégation d’une structure C donnée comprend des octets de bourrage afin de maintenir un alignement correct des types C sous-jacents ; de la même manière, l’alignement est pris en compte lors de la dissociation. Ce comportement a été choisi de manière à ce que les octets d’une structure agrégée reproduisent exactement l’agencement en mémoire de la structure C équivalente. Pour gérer des formats de données indépendants de la plateforme ou omettre les octets implicites de bourrage, utilisez la taille et l’alignement standard en lieu et place de la taille et l’alignement native (voir Boutisme, taille et alignement pour les détails).

Plusieurs fonctions de struct (et méthodes de Struct) prennent un argument buffer. Cet argument fait référence à des objets qui implémentent Protocole tampon et qui proposent un tampon soit en lecture seule, soit en lecture-écriture. Les types les plus courants qui utilisent cette fonctionnalité sont bytes et bytearray, mais beaucoup d’autres types qui peuvent être considérés comme des tableaux d’octets implémentent le protocole tampon ; ils peuvent ainsi être lus ou remplis depuis un objet bytes sans faire de copie.

7.1.1. Fonctions et exceptions

Le module définit les exceptions et fonctions suivantes :

exception struct.error

Exception levée à plusieurs occasions ; l’argument est une chaîne qui décrit ce qui ne va pas.

struct.pack(fmt, v1, v2, ...)

Return a bytes object containing the values v1, v2, … packed according to the format string fmt. The arguments must match the values required by the format exactly.

struct.pack_into(fmt, buffer, offset, v1, v2, ...)

Pack the values v1, v2, … according to the format string fmt and write the packed bytes into the writable buffer buffer starting at position offset. Note that offset is a required argument.

struct.unpack(fmt, buffer)

Unpack from the buffer buffer (presumably packed by pack(fmt, ...)) according to the format string fmt. The result is a tuple even if it contains exactly one item. The buffer’s size in bytes must match the size required by the format, as reflected by calcsize().

struct.unpack_from(fmt, buffer, offset=0)

Unpack from buffer starting at position offset, according to the format string fmt. The result is a tuple even if it contains exactly one item. The buffer’s size in bytes, minus offset, must be at least the size required by the format, as reflected by calcsize().

struct.iter_unpack(fmt, buffer)

Iteratively unpack from the buffer buffer according to the format string fmt. This function returns an iterator which will read equally-sized chunks from the buffer until all its contents have been consumed. The buffer’s size in bytes must be a multiple of the size required by the format, as reflected by calcsize().

Chaque itération produit un n-uplet tel que spécifié par la chaîne de format.

Nouveau dans la version 3.4.

struct.calcsize(fmt)

Return the size of the struct (and hence of the bytes object produced by pack(fmt, ...)) corresponding to the format string fmt.

7.1.2. Chaînes de spécification du format

Les chaînes de spécification du format servent à définir l’agencement lors de l’agrégation et la dissociation des données. Elles sont construites à partir de Caractères de format, qui spécifient le type de donnée à agréger-dissocier. De plus, il existe des caractères spéciaux pour contrôler Boutisme, taille et alignement.

7.1.2.1. Boutisme, taille et alignement

Par défaut, les types C sont représentés dans le format et le boutisme natifs de la machine ; ils sont alignés correctement en sautant des octets si nécessaire (en fonction des règles utilisées par le compilateur C).

Cependant, le premier caractère de la chaîne de format peut être utilisé pour indiquer le boutisme, la taille et l’alignement des données agrégées, conformément à la table suivante :

Caractère

Boutisme

Taille

Alignement

@

natif

natif

natif

=

natif

standard

aucun

<

petit-boutiste

standard

aucun

>

gros-boutiste

standard

aucun

!

réseau (= gros-boutiste)

standard

aucun

Si le premier caractère n’est pas dans cette liste, le module se comporte comme si '@' avait été indiqué.

Le boutisme natif est gros-boutiste ou petit-boutiste, en fonction de la machine sur laquelle s’exécute le programme. Par exemple, les Intel x86 et les AMD64 (x86-64) sont petit-boutistes ; les Motorola 68000 et les PowerPC G5 sont gros-boutistes ; les ARM et les Intel Itanium peuvent changer de boutisme. Utilisez sys.byteorder pour vérifier le boutisme de votre système.

La taille et l’alignement natifs sont déterminés en utilisant l’expression sizeof du compilateur C. Leur valeur est toujours combinée au boutisme natif.

La taille standard dépend seulement du caractère du format ; référez-vous au tableau dans la section Caractères de format.

Notez la différence entre '@' et '=' : les deux utilisent le boutisme natif mais la taille et l’alignement du dernier sont standards.

La forme '!' existe pour les têtes en l’air qui prétendent ne pas se rappeler si le boutisme réseau est gros-boutiste ou petit-boutiste.

Il n’y a pas de moyen de spécifier le boutisme contraire au boutisme natif (c’est-à-dire forcer la permutation des octets) ; utilisez le bon caractère entre '<' et '>'.

Notes :

Le bourrage (padding en anglais) n’est automatiquement ajouté qu’entre les membres successifs de la structure. Il n’y a pas de bourrage au début ou à la fin de la structure agrégée.

Il n’y a pas d’ajout de bourrage lorsque vous utilisez une taille et un alignement non-natifs, par exemple avec <, “>”, `= ou !.

Pour aligner la fin d’une structure à l’alignement requis par un type particulier, terminez le format avec le code du type voulu et une valeur de répétition à zéro. Référez-vous à Exemples.

7.1.2.2. Caractères de format

Les caractères de format possèdent les significations suivantes ; la conversion entre les valeurs C et Python doit être évidente compte tenu des types concernés. La colonne « taille standard » fait référence à la taille en octets de la valeur agrégée avec l’utilisation de la taille standard (c’est-à-dire lorsque la chaîne de format commence par l’un des caractères suivants : '<', '>', '!' ou '='). Si vous utilisez la taille native, la taille de la valeur agrégée dépend de la plateforme.

Format

Type C

Type Python

Taille standard

Notes

x

octet de bourrage

pas de valeur

c

char

bytes (suite d’octets) de taille 1

1

b

signed char

int (entier)

1

(1),(3)

B

unsigned char

int (entier)

1

(3)

?

_Bool

bool (booléen)

1

(1)

h

short

int (entier)

2

(3)

H

unsigned short

int (entier)

2

(3)

i

int

int (entier)

4

(3)

I

unsigned int

int (entier)

4

(3)

l

long

int (entier)

4

(3)

L

unsigned long

int (entier)

4

(3)

q

long long

int (entier)

8

(2), (3)

Q

unsigned long long

int (entier)

8

(2), (3)

n

ssize_t

int (entier)

(4)

N

size_t

int (entier)

(4)

e

(7)

float (nombre à virgule flottante)

2

(5)

f

float

float (nombre à virgule flottante)

4

(5)

d

double

float (nombre à virgule flottante)

8

(5)

s

char[]

bytes (séquence d’octets)

p

char[]

bytes (séquence d’octets)

P

void *

int (entier)

(6)

Modifié dans la version 3.3: ajouté la gestion des formats 'n' et 'N'.

Modifié dans la version 3.6: ajouté la gestion du format 'e'.

Notes :

Le code de conversion '?' correspond au type _Bool de C99. Si ce type n’est pas disponible, il est simulé en utilisant un char. Dans le mode standard, il est toujours représenté par un octet.

The 'q' and 'Q' conversion codes are available in native mode only if the platform C compiler supports C long long, or, on Windows, __int64. They are always available in standard modes.

Lorsque vous essayez d’agréger un non-entier en utilisant un code de conversion pour un entier, si ce non-entier possède une méthode __index__() alors cette méthode est appelée pour convertir l’argument en entier avant l’agrégation.

Modifié dans la version 3.2: utilisation de la méthode __index__() pour les non-entiers.

Les codes de conversion 'n' et 'N' ne sont disponibles que pour la taille native (choisie par défaut ou à l’aide du caractère de boutisme '@'). Pour la taille standard, vous pouvez utiliser n’importe quel format d’entier qui convient à votre application.

Pour les codes de conversion 'f', 'd' et 'e', la représentation agrégée utilise respectivement le format IEEE 754 binaire32, binaire64 ou binaire16 (pour 'f', 'd' ou 'e' respectivement), quel que soit le format des nombres à virgule flottante de la plateforme.

Le caractère de format 'P' n’est disponible que pour le boutisme natif (choisi par défaut ou à l’aide du caractère '@' de boutisme). Le caractère de boutisme '=' choisit d’utiliser un petit ou un gros en fonction du système hôte. Le module struct ne l’interprète pas comme un boutisme natif, donc le format 'P' n’est pas disponible.

Le type IEEE 754 binaire16 « demie-précision » a été introduit en 2008 par la révision du standard IEEE 754 [https://en.wikipedia.org/wiki/IEEE_floating_point#IEEE_754-2008]. Il comprend un bit de signe, un exposant sur 5 bits et une précision de 11 bits (dont 10 bits sont explicitement stockés) ; il peut représenter les nombres entre environ 6.1e-05 et 6.5e+04 avec une précision maximale. Ce type est rarement pris en charge par les compilateurs C : sur une machine courante, un unsigned short (entier court non signé) peut être utilisé pour le stockage mais pas pour les opérations mathématiques. Lisez la page Wikipédia (NdT : non traduite en français) half-precision floating-point format [https://en.wikipedia.org/wiki/Half-precision_floating-point_format] pour davantage d’informations.

Un caractère de format peut être précédé par un entier indiquant le nombre de répétitions. Par exemple, la chaîne de format '4h' a exactement la même signification que 'hhhh'.

Les caractères d’espacement entre les indications de format sont ignorés ; cependant, le nombre de répétitions et le format associé ne doivent pas être séparés par des caractères d’espacement.

Pour le caractère de format 's', un nombre en tête est interprété comme la longueur du bytes et non comme le nombre de répétitions comme pour les autres caractères de format ; par exemple, '10s' signifie une seule chaîne de 10 octets alors que '10c' signifie 10 caractères. Si aucun nombre n’est indiqué, la valeur par défaut est 1. Pour l’agrégation, la chaîne est tronquée ou bourrée avec des octets nuls pour atteindre la taille souhaitée. Pour la dissociation, l’objet bytes résultant possède le nombre exact d’octets spécifiés. Un cas particulier est '0s' qui signifie une chaîne (et une seule) vide (alors que '0c' signifie zéro caractère).

Lors de l’agrégation d’une valeur x en utilisant l’un des formats pour les entiers ('b', 'B', 'h', 'H', 'i', 'I', 'l', 'L', 'q', 'Q'), si x est en dehors de l’intervalle du format spécifié, une struct.error est levée.

Modifié dans la version 3.1: auparavant, certains formats d’entiers absorbaient les valeurs en dehors des intervalles valides et levaient une DeprecationWarning au lieu d’une struct.error.

Le caractère de format 'p' sert à encoder une « chaîne Pascal », c’est-à-dire une courte chaîne de longueur variable, stockée dans un nombre défini d’octets dont la valeur est définie par la répétition. Le premier octet stocké est la longueur de la chaîne (dans la limite maximum de 255). Les octets composant la chaîne suivent. Si la chaîne passée à pack() est trop longue (supérieure à la valeur de la répétition moins 1), seuls les count-1 premiers octets de la chaîne sont stockés. Si la chaîne est plus courte que count-1, des octets de bourrage nuls sont insérés de manière à avoir exactement count octets au final. Notez que pour unpack(), le caractère de format 'p' consomme count octets mais que la chaîne renvoyée ne peut pas excéder 255 octets.

Pour le caractère de format '?', la valeur renvoyée est True ou False. Lors de l’agrégation, la valeur de vérité de l’objet argument est utilisée. La valeur agrégée est 0 ou 1 dans la représentation native ou standard et, lors de la dissociation, n’importe quelle valeur différente de zéro est renvoyée True.

7.1.2.3. Exemples

Note

tous les exemples présentés supposent que l’on utilise le boutisme, la taille et l’alignement natifs sur une machine gros-boutiste.

Un exemple de base d’agrégation et dissociation de trois entiers :

>>> from struct import *
>>> pack('hhl', 1, 2, 3)
b'\x00\x01\x00\x02\x00\x00\x00\x03'
>>> unpack('hhl', b'\x00\x01\x00\x02\x00\x00\x00\x03')
(1, 2, 3)
>>> calcsize('hhl')
8

Les champs dissociés peuvent être nommés en leur assignant des variables ou en encapsulant le résultat dans un n-uplet nommé :

>>> record = b'raymond   \x32\x12\x08\x01\x08'
>>> name, serialnum, school, gradelevel = unpack('<10sHHb', record)

>>> from collections import namedtuple
>>> Student = namedtuple('Student', 'name serialnum school gradelevel')
>>> Student._make(unpack('<10sHHb', record))
Student(name=b'raymond   ', serialnum=4658, school=264, gradelevel=8)

L’ordre des caractères de format peut avoir un impact sur la taille puisque le bourrage nécessaire pour réaliser l’alignement est différent :

>>> pack('ci', b'*', 0x12131415)
b'*\x00\x00\x00\x12\x13\x14\x15'
>>> pack('ic', 0x12131415, b'*')
b'\x12\x13\x14\x15*'
>>> calcsize('ci')
8
>>> calcsize('ic')
5

Le format suivant 'llh0l' spécifie deux octets de bourrage à la fin, considérant que les entiers longs sont alignés sur des espacements de 4 octets :

>>> pack('llh0l', 1, 2, 3)
b'\x00\x00\x00\x01\x00\x00\x00\x02\x00\x03\x00\x00'

Ceci ne fonctionne que quand la taille et l’alignement natifs sont utilisés ; la taille et l’alignement standards ne forcent aucun alignement.

Voir aussi

Module array

Stockage agrégé binaire de données homogènes.

Module xdrlib

Agrégation et dissociation de données XDR.

7.1.3. Classes

Le module struct définit aussi le type suivant :

class struct.Struct(format)

Renvoie un nouvel objet Struct qui écrit et lit des données binaires conformément à la chaîne de format format. Créer une fois pour toutes un objet Struct puis appeler ses méthodes est plus efficace que d’appeler les fonctions de struct avec le même format puisque la chaîne de format n’est compilée qu’une seule fois.

Les objets Struct compilés gèrent les méthodes et attributs suivants :

pack(v1, v2, ...)

Identique à la fonction pack(), en utilisant le format compilé (len(result) vaut size).

pack_into(buffer, offset, v1, v2, ...)

Identique à la fonction pack_into(), en utilisant le format compilé.

unpack(buffer)

Identique à la fonction unpack(), en utilisant le format compilé. La taille du tampon buffer en octets doit valoir size.

unpack_from(buffer, offset=0)

Identical to the unpack_from() function, using the compiled format. The buffer’s size in bytes, minus offset, must be at least size.

iter_unpack(buffer)

Identique à la fonction iter_unpack(), en utilisant le format compilé. La taille du tampon buffer en octets doit être un multiple de size.

Nouveau dans la version 3.4.

format

La chaîne de format utilisée pour construire l’objet Struct.

size

La taille calculée de la structure agrégée (et donc de l’objet bytes produit par la méthode pack()) correspondante à format.

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7.2. codecs — Registre des codecs et classes de base associées

Code source : Lib/codecs.py [https://github.com/python/cpython/tree/3.6/Lib/codecs.py]

Ce module définit les classes de base pour les codecs (encodeurs et décodeurs) standards Python et fournit l’interface avec le registre des codecs internes à Python, qui gère le processus de recherche de codecs et de gestion des erreurs. La plupart des codecs sont des encodeurs de texte, qui encode du texte vers des séquences d’octets (type bytes de Python) mais il existe aussi des codecs qui encodent du texte vers du texte et des bytes vers des bytes. Les codecs personnalisés peuvent encoder et décoder des types arbitraires, mais l’utilisation de certaines fonctionnalités du module est restreinte aux encodeurs de texte ou aux codecs qui encodent vers bytes.

Le module définit les fonctions suivantes pour encoder et décoder à l’aide de n’importe quel codec :

codecs.encode(obj, encoding='utf-8', errors='strict')

Encode obj en utilisant le codec enregistré pour encoding.

Vous pouvez spécifier errors pour définir la façon de gérer les erreurs. Le gestionnaire d’erreurs par défaut est 'strict', ce qui veut dire qu’une erreur lors de l’encodage lève ValueError (ou une sous-classe spécifique du codec, telle que UnicodeEncodeError). Référez-vous aux Classes de base de codecs pour plus d’informations sur la gestion des erreurs par les codecs.

codecs.decode(obj, encoding='utf-8', errors='strict')

Décode obj en utilisant le codec enregistré pour encoding.

Vous pouvez spécifier errors pour définir la façon de gérer les erreurs. Le gestionnaire d’erreurs par défaut est 'strict', ce qui veut dire qu’une erreur lors du décodage lève ValueError (ou une sous-classe spécifique du codec, telle que UnicodeDecodeError). Référez-vous aux Classes de base de codecs pour plus d’informations sur la gestion des erreurs par les codecs.

Les détails complets de chaque codec peuvent être examinés directement :

codecs.lookup(encoding)

Recherche les informations relatives au codec dans le registre des codecs de Python et renvoie l’objet CodecInfo tel que défini ci-dessous.

Les encodeurs sont recherchés en priorité dans le cache du registre. S’ils n’y sont pas, la liste des fonctions de recherche enregistrées est passée en revue. Si aucun objet CodecInfo n’est trouvé, une LookupError est levée. Sinon, l’objet CodecInfo est mis en cache et renvoyé vers l’appelant.

class codecs.CodecInfo(encode, decode, streamreader=None, streamwriter=None, incrementalencoder=None, incrementaldecoder=None, name=None)

Les détails d’un codec trouvé dans le registre des codecs. Les arguments du constructeur sont stockés dans les attributs éponymes :

name

Le nom de l’encodeur.

encode

decode

Les fonctions d’encodage et de décodage. Ces fonctions ou méthodes doivent avoir la même interface que les méthodes encode() et decode() des instances de Codec (voir Interface des codecs). Les fonctions et méthodes sont censées fonctionner sans état interne.

incrementalencoder

incrementaldecoder

Classes d’encodeurs et de décodeurs incrémentaux ou fonctions usines. Elles doivent avoir respectivement les mêmes interfaces que celles définies par les classes de base IncrementalEncoder et IncrementalDecoder. Les codecs incrémentaux peuvent conserver des états internes.

streamwriter

streamreader

Classes d’écriture et de lecture de flux ou fonctions usines. Elles doivent avoir les mêmes interfaces que celles définies par les classes de base StreamWriter et StreamReader, respectivement. Les codecs de flux peuvent conserver un état interne.

Pour simplifier l’accès aux différents composants du codec, le module fournit les fonctions supplémentaires suivantes qui utilisent lookup() pour la recherche du codec :

codecs.getencoder(encoding)

Recherche le codec pour l’encodage encoding et renvoie sa fonction d’encodage.

Lève une LookupError si l’encodage encoding n’est pas trouvé.

codecs.getdecoder(encoding)

Recherche le codec pour l’encodage encoding et renvoie sa fonction de décodage.

Lève une LookupError si l’encodage encoding n’est pas trouvé.

codecs.getincrementalencoder(encoding)

Recherche le codec pour l’encodage encoding et renvoie sa classe d’encodage incrémental ou la fonction usine.

Lève une LookupError si l’encodage encoding n’est pas trouvé ou si le codec ne gère pas l’encodage incrémental.

codecs.getincrementaldecoder(encoding)

Recherche le codec pour l’encodage encoding et renvoie sa classe de décodage incrémental ou la fonction usine.

Lève une LookupError si l’encodage encoding n’est pas trouvé ou si le codec ne gère pas le décodage incrémental.

codecs.getreader(encoding)

Recherche le codec pour l’encodage encoding et renvoie sa classe StreamReader ou la fonction usine.

Lève une LookupError si l’encodage encoding n’est pas trouvé.

codecs.getwriter(encoding)

Recherche le codec pour l’encodage encoding et renvoie sa classe StreamWriter ou la fonction usine.

Lève une LookupError si l’encodage encoding n’est pas trouvé.

Les codecs personnalisés sont mis à disposition en enregistrant une fonction de recherche de codecs adaptée :

codecs.register(search_function)

Enregistre une fonction de recherche de codec. Il convient qu’une fonction de recherche prenne un argument, le nom de l’encodage écrit en lettres minuscules, et renvoie un objet CodecInfo. Si la fonction de recherche ne trouve pas un encodage donné, il convient qu’elle renvoie `` None``.

Note

l’enregistrement d’une fonction de recherche n’est actuellement pas réversible, ce qui peut entraîner des problèmes dans certains cas, par exemple pour les tests unitaires ou le rechargement de module.

Alors qu’il est recommandé d’utiliser la fonction native open() et le module associé io pour travailler avec des fichiers texte encodés, le présent module fournit des fonctions et classes utilitaires supplémentaires qui permettent l’utilisation d’une plus large gamme de codecs si vous travaillez avec des fichiers binaires :

codecs.open(filename, mode='r', encoding=None, errors='strict', buffering=1)

Ouvre un fichier encodé en utilisant le mode donné et renvoie une instance de StreamReaderWriter, permettant un encodage-décodage transparent. Le mode de fichier par défaut est 'r', ce qui signifie que le fichier est ouvert en lecture.

Note

les fichiers encodés sous-jacents sont toujours ouverts en mode binaire. Aucune conversion automatique de '\n' n’est effectuée à la lecture ou à l’écriture. L’argument mode peut être n’importe quel mode binaire acceptable pour la fonction native open() ; le 'b' est automatiquement ajouté.

encoding spécifie l’encodage à utiliser pour le fichier. Tout encodage qui encode et décode des octets (type bytes) est autorisé et les types de données pris en charge par les méthodes relatives aux fichiers dépendent du codec utilisé.

errors peut être spécifié pour définir la gestion des erreurs. La valeur par défaut est 'strict', ce qui lève une ValueError en cas d’erreur lors du codage.

buffering has the same meaning as for the built-in open() function. It defaults to line buffered.

codecs.EncodedFile(file, data_encoding, file_encoding=None, errors='strict')

Renvoie une instance de StreamRecoder, version encapsulée de file qui fournit un transcodage transparent. Le fichier original est fermé quand la version encapsulée est fermée.

Les données écrites dans un fichier encapsulant sont décodées en fonction du data_encoding spécifié puis écrites vers le fichier original en tant que bytes en utilisant file_encoding. Les octets lus dans le fichier original sont décodés conformément à file_encoding et le résultat est encodé en utilisant data_encoding.

Si file_encoding n’est pas spécifié, la valeur par défaut est data_encoding.

errors peut être spécifié pour définir la gestion des erreurs. La valeur par défaut est 'strict', ce qui lève une ValueError en cas d’erreur lors du codage.

codecs.iterencode(iterator, encoding, errors='strict', **kwargs)

Utilise un encodeur incrémental pour encoder de manière itérative l’entrée fournie par iterator. Cette fonction est un générateur. L’argument errors (ainsi que tout autre argument passé par mot-clé) est transmis à l’encodeur incrémental.

Cette fonction nécessite que le codec accepte les objets texte (classe str) en entrée. Par conséquent, il ne prend pas en charge les encodeurs bytes vers bytes tels que base64_codec.

codecs.iterdecode(iterator, encoding, errors='strict', **kwargs)

Utilise un décodeur incrémental pour décoder de manière itérative l’entrée fournie par iterator. Cette fonction est un générateur. L’argument errors (ainsi que tout autre argument passé par mot-clé) est transmis au décodeur incrémental.

Cette fonction requiert que le codec accepte les objets bytes en entrée. Par conséquent, elle ne prend pas en charge les encodeurs de texte vers texte tels que rot_13, bien que rot_13 puisse être utilisé de manière équivalente avec iterencode().

Le module fournit également les constantes suivantes qui sont utiles pour lire et écrire les fichiers dépendants de la plateforme :

codecs.BOM

codecs.BOM_BE

codecs.BOM_LE

codecs.BOM_UTF8

codecs.BOM_UTF16

codecs.BOM_UTF16_BE

codecs.BOM_UTF16_LE

codecs.BOM_UTF32

codecs.BOM_UTF32_BE

codecs.BOM_UTF32_LE

Ces constantes définissent diverses séquences d’octets, les marques d’ordre d’octets (BOM pour byte order mark en anglais) Unicode pour plusieurs encodages. Elles sont utilisées dans les flux de données UTF-16 et UTF-32 pour indiquer l’ordre des octets utilisé, et dans UTF-8 comme signature Unicode. BOM_UTF16 vaut soit BOM_UTF16_BE, soit BOM_UTF16_LE selon le boutisme natif de la plateforme, BOM est un alias pour BOM_UTF16, BOM_LE pour BOM_UTF16_LE et BOM_BE pour BOM_UTF16_BE. Les autres sont les marques BOM dans les encodages UTF-8 et UTF-32.

7.2.1. Classes de base de codecs

Le module codecs définit un ensemble de classes de base qui spécifient les interfaces pour travailler avec des objets codecs et qui peuvent également être utilisées comme base pour des implémentations de codecs personnalisés.

Chaque codec doit définir quatre interfaces pour être utilisable comme codec en Python : codeur sans état, décodeur sans état, lecteur de flux et écrivain de flux. Le lecteur et l’écrivain de flux réutilisent généralement l’encodeur-décodeur sans état pour implémenter les protocoles de fichiers. Les auteurs de codecs doivent également définir comment le codec gère les erreurs d’encodage et de décodage.

7.2.1.1. Gestionnaires d’erreurs

To simplify and standardize error handling, codecs may implement different error handling schemes by accepting the errors string argument. The following string values are defined and implemented by all standard Python codecs:

Valeur

Signification

'strict'

Raise UnicodeError (or a subclass); this is the default. Implemented in strict_errors().

'ignore'

Ignore the malformed data and continue without further notice. Implemented in ignore_errors().

Les gestionnaires d’erreurs suivants ne s’appliquent que pour les encodeurs de texte :

Valeur

Signification

'replace'

Replace with a suitable replacement marker; Python will use the official U+FFFD REPLACEMENT CHARACTER for the built-in codecs on decoding, and “?” on encoding. Implemented in replace_errors().

'xmlcharrefreplace'

Replace with the appropriate XML character reference (only for encoding). Implemented in xmlcharrefreplace_errors().

'backslashreplace'

Remplace avec une séquence échappée par des antislashs. Implémenté dans backslashreplace_errors().

'namereplace'

Replace with \N{...} escape sequences (only for encoding). Implemented in namereplace_errors().

'surrogateescape'

On decoding, replace byte with individual surrogate code ranging from U+DC80 to U+DCFF. This code will then be turned back into the same byte when the 'surrogateescape' error handler is used when encoding the data. (See PEP 383 [https://www.python.org/dev/peps/pep-0383] for more.)

En plus, le gestionnaire d’erreurs suivant est spécifique aux codecs suivants :

Valeur

Codecs

Signification

'surrogatepass'

utf-8, utf-16, utf-32, utf-16-be, utf-16-le, utf-32-be, utf-32-le

Allow encoding and decoding of surrogate codes. These codecs normally treat the presence of surrogates as an error.

Nouveau dans la version 3.1: les gestionnaires d’erreurs 'surrogateescape' et 'surrogatepass'.

Modifié dans la version 3.4: le gestionnaire d’erreurs 'surrogatepass' fonctionne maintenant avec les codecs utf-16* et utf-32*.

Nouveau dans la version 3.5: le gestionnaire d’erreurs 'namereplace'.

Modifié dans la version 3.5: le gestionnaire d’erreurs 'backslashreplace' fonctionne maintenant pour le décodage et la traduction.

L’ensemble des valeurs autorisées peut être étendu en enregistrant un nouveau gestionnaire d’erreurs nommé :

codecs.register_error(name, error_handler)

Register the error handling function error_handler under the name name. The error_handler argument will be called during encoding and decoding in case of an error, when name is specified as the errors parameter.

For encoding, error_handler will be called with a UnicodeEncodeError instance, which contains information about the location of the error. The error handler must either raise this or a different exception, or return a tuple with a replacement for the unencodable part of the input and a position where encoding should continue. The replacement may be either str or bytes. If the replacement is bytes, the encoder will simply copy them into the output buffer. If the replacement is a string, the encoder will encode the replacement. Encoding continues on original input at the specified position. Negative position values will be treated as being relative to the end of the input string. If the resulting position is out of bound an IndexError will be raised.

Decoding and translating works similarly, except UnicodeDecodeError or UnicodeTranslateError will be passed to the handler and that the replacement from the error handler will be put into the output directly.

Previously registered error handlers (including the standard error handlers) can be looked up by name:

codecs.lookup_error(name)

Return the error handler previously registered under the name name.

Raises a LookupError in case the handler cannot be found.

The following standard error handlers are also made available as module level functions:

codecs.strict_errors(exception)

Implements the 'strict' error handling: each encoding or decoding error raises a UnicodeError.

codecs.replace_errors(exception)

Implements the 'replace' error handling (for text encodings only): substitutes '?' for encoding errors (to be encoded by the codec), and '\ufffd' (the Unicode replacement character) for decoding errors.

codecs.ignore_errors(exception)

Implements the 'ignore' error handling: malformed data is ignored and encoding or decoding is continued without further notice.

codecs.xmlcharrefreplace_errors(exception)

Implements the 'xmlcharrefreplace' error handling (for encoding with text encodings only): the unencodable character is replaced by an appropriate XML character reference.

codecs.backslashreplace_errors(exception)

Implements the 'backslashreplace' error handling (for text encodings only): malformed data is replaced by a backslashed escape sequence.

codecs.namereplace_errors(exception)

Implements the 'namereplace' error handling (for encoding with text encodings only): the unencodable character is replaced by a \N{...} escape sequence.

Nouveau dans la version 3.5.

7.2.1.2. Stateless Encoding and Decoding

The base Codec class defines these methods which also define the function interfaces of the stateless encoder and decoder:

Codec.encode(input[, errors])

Encodes the object input and returns a tuple (output object, length consumed). For instance, text encoding converts a string object to a bytes object using a particular character set encoding (e.g., cp1252 or iso-8859-1).

The errors argument defines the error handling to apply. It defaults to 'strict' handling.

The method may not store state in the Codec instance. Use StreamWriter for codecs which have to keep state in order to make encoding efficient.

The encoder must be able to handle zero length input and return an empty object of the output object type in this situation.

Codec.decode(input[, errors])

Decodes the object input and returns a tuple (output object, length consumed). For instance, for a text encoding, decoding converts a bytes object encoded using a particular character set encoding to a string object.

For text encodings and bytes-to-bytes codecs, input must be a bytes object or one which provides the read-only buffer interface – for example, buffer objects and memory mapped files.

The errors argument defines the error handling to apply. It defaults to 'strict' handling.

The method may not store state in the Codec instance. Use StreamReader for codecs which have to keep state in order to make decoding efficient.

The decoder must be able to handle zero length input and return an empty object of the output object type in this situation.

7.2.1.3. Incremental Encoding and Decoding

The IncrementalEncoder and IncrementalDecoder classes provide the basic interface for incremental encoding and decoding. Encoding/decoding the input isn’t done with one call to the stateless encoder/decoder function, but with multiple calls to the encode()/decode() method of the incremental encoder/decoder. The incremental encoder/decoder keeps track of the encoding/decoding process during method calls.

The joined output of calls to the encode()/decode() method is the same as if all the single inputs were joined into one, and this input was encoded/decoded with the stateless encoder/decoder.

7.2.1.3.1. IncrementalEncoder Objects

The IncrementalEncoder class is used for encoding an input in multiple steps. It defines the following methods which every incremental encoder must define in order to be compatible with the Python codec registry.

class codecs.IncrementalEncoder(errors='strict')

Constructor for an IncrementalEncoder instance.

All incremental encoders must provide this constructor interface. They are free to add additional keyword arguments, but only the ones defined here are used by the Python codec registry.

The IncrementalEncoder may implement different error handling schemes by providing the errors keyword argument. See Gestionnaires d’erreurs for possible values.

The errors argument will be assigned to an attribute of the same name. Assigning to this attribute makes it possible to switch between different error handling strategies during the lifetime of the IncrementalEncoder object.

encode(object[, final])

Encodes object (taking the current state of the encoder into account) and returns the resulting encoded object. If this is the last call to encode() final must be true (the default is false).

reset()

Reset the encoder to the initial state. The output is discarded: call .encode(object, final=True), passing an empty byte or text string if necessary, to reset the encoder and to get the output.

getstate()

Return the current state of the encoder which must be an integer. The implementation should make sure that 0 is the most common state. (States that are more complicated than integers can be converted into an integer by marshaling/pickling the state and encoding the bytes of the resulting string into an integer).

setstate(state)

Set the state of the encoder to state. state must be an encoder state returned by getstate().

7.2.1.3.2. IncrementalDecoder Objects

The IncrementalDecoder class is used for decoding an input in multiple steps. It defines the following methods which every incremental decoder must define in order to be compatible with the Python codec registry.

class codecs.IncrementalDecoder(errors='strict')

Constructor for an IncrementalDecoder instance.

All incremental decoders must provide this constructor interface. They are free to add additional keyword arguments, but only the ones defined here are used by the Python codec registry.

The IncrementalDecoder may implement different error handling schemes by providing the errors keyword argument. See Gestionnaires d’erreurs for possible values.

The errors argument will be assigned to an attribute of the same name. Assigning to this attribute makes it possible to switch between different error handling strategies during the lifetime of the IncrementalDecoder object.

decode(object[, final])

Decodes object (taking the current state of the decoder into account) and returns the resulting decoded object. If this is the last call to decode() final must be true (the default is false). If final is true the decoder must decode the input completely and must flush all buffers. If this isn’t possible (e.g. because of incomplete byte sequences at the end of the input) it must initiate error handling just like in the stateless case (which might raise an exception).

reset()

Reset the decoder to the initial state.

getstate()

Return the current state of the decoder. This must be a tuple with two items, the first must be the buffer containing the still undecoded input. The second must be an integer and can be additional state info. (The implementation should make sure that 0 is the most common additional state info.) If this additional state info is 0 it must be possible to set the decoder to the state which has no input buffered and 0 as the additional state info, so that feeding the previously buffered input to the decoder returns it to the previous state without producing any output. (Additional state info that is more complicated than integers can be converted into an integer by marshaling/pickling the info and encoding the bytes of the resulting string into an integer.)

setstate(state)

Set the state of the encoder to state. state must be a decoder state returned by getstate().

7.2.1.4. Stream Encoding and Decoding

The StreamWriter and StreamReader classes provide generic working interfaces which can be used to implement new encoding submodules very easily. See encodings.utf_8 for an example of how this is done.

7.2.1.4.1. StreamWriter Objects

The StreamWriter class is a subclass of Codec and defines the following methods which every stream writer must define in order to be compatible with the Python codec registry.

class codecs.StreamWriter(stream, errors='strict')

Constructor for a StreamWriter instance.

All stream writers must provide this constructor interface. They are free to add additional keyword arguments, but only the ones defined here are used by the Python codec registry.

The stream argument must be a file-like object open for writing text or binary data, as appropriate for the specific codec.

The StreamWriter may implement different error handling schemes by providing the errors keyword argument. See Gestionnaires d’erreurs for the standard error handlers the underlying stream codec may support.

The errors argument will be assigned to an attribute of the same name. Assigning to this attribute makes it possible to switch between different error handling strategies during the lifetime of the StreamWriter object.

write(object)

Writes the object’s contents encoded to the stream.

writelines(list)

Writes the concatenated list of strings to the stream (possibly by reusing the write() method). The standard bytes-to-bytes codecs do not support this method.

reset()

Flushes and resets the codec buffers used for keeping state.

Calling this method should ensure that the data on the output is put into a clean state that allows appending of new fresh data without having to rescan the whole stream to recover state.

In addition to the above methods, the StreamWriter must also inherit all other methods and attributes from the underlying stream.

7.2.1.4.2. StreamReader Objects

The StreamReader class is a subclass of Codec and defines the following methods which every stream reader must define in order to be compatible with the Python codec registry.

class codecs.StreamReader(stream, errors='strict')

Constructor for a StreamReader instance.

All stream readers must provide this constructor interface. They are free to add additional keyword arguments, but only the ones defined here are used by the Python codec registry.

The stream argument must be a file-like object open for reading text or binary data, as appropriate for the specific codec.

The StreamReader may implement different error handling schemes by providing the errors keyword argument. See Gestionnaires d’erreurs for the standard error handlers the underlying stream codec may support.

The errors argument will be assigned to an attribute of the same name. Assigning to this attribute makes it possible to switch between different error handling strategies during the lifetime of the StreamReader object.

The set of allowed values for the errors argument can be extended with register_error().

read([size[, chars[, firstline]]])

Decodes data from the stream and returns the resulting object.

The chars argument indicates the number of decoded code points or bytes to return. The read() method will never return more data than requested, but it might return less, if there is not enough available.

The size argument indicates the approximate maximum number of encoded bytes or code points to read for decoding. The decoder can modify this setting as appropriate. The default value -1 indicates to read and decode as much as possible. This parameter is intended to prevent having to decode huge files in one step.

The firstline flag indicates that it would be sufficient to only return the first line, if there are decoding errors on later lines.

The method should use a greedy read strategy meaning that it should read as much data as is allowed within the definition of the encoding and the given size, e.g. if optional encoding endings or state markers are available on the stream, these should be read too.

readline([size[, keepends]])

Read one line from the input stream and return the decoded data.

size, if given, is passed as size argument to the stream’s read() method.

If keepends is false line-endings will be stripped from the lines returned.

readlines([sizehint[, keepends]])

Read all lines available on the input stream and return them as a list of lines.

Line-endings are implemented using the codec’s decoder method and are included in the list entries if keepends is true.

sizehint, if given, is passed as the size argument to the stream’s read() method.

reset()

Resets the codec buffers used for keeping state.

Note that no stream repositioning should take place. This method is primarily intended to be able to recover from decoding errors.

In addition to the above methods, the StreamReader must also inherit all other methods and attributes from the underlying stream.

7.2.1.4.3. StreamReaderWriter Objects

The StreamReaderWriter is a convenience class that allows wrapping streams which work in both read and write modes.

The design is such that one can use the factory functions returned by the lookup() function to construct the instance.

class codecs.StreamReaderWriter(stream, Reader, Writer, errors='strict')

Creates a StreamReaderWriter instance. stream must be a file-like object. Reader and Writer must be factory functions or classes providing the StreamReader and StreamWriter interface resp. Error handling is done in the same way as defined for the stream readers and writers.

StreamReaderWriter instances define the combined interfaces of StreamReader and StreamWriter classes. They inherit all other methods and attributes from the underlying stream.

7.2.1.4.4. StreamRecoder Objects

The StreamRecoder translates data from one encoding to another, which is sometimes useful when dealing with different encoding environments.

The design is such that one can use the factory functions returned by the lookup() function to construct the instance.

class codecs.StreamRecoder(stream, encode, decode, Reader, Writer, errors='strict')

Creates a StreamRecoder instance which implements a two-way conversion: encode and decode work on the frontend — the data visible to code calling read() and write(), while Reader and Writer work on the backend — the data in stream.

You can use these objects to do transparent transcodings from e.g. Latin-1 to UTF-8 and back.

The stream argument must be a file-like object.

The encode and decode arguments must adhere to the Codec interface. Reader and Writer must be factory functions or classes providing objects of the StreamReader and StreamWriter interface respectively.

Error handling is done in the same way as defined for the stream readers and writers.

StreamRecoder instances define the combined interfaces of StreamReader and StreamWriter classes. They inherit all other methods and attributes from the underlying stream.

7.2.2. Encodings and Unicode

Strings are stored internally as sequences of code points in range 0x0–0x10FFFF. (See PEP 393 [https://www.python.org/dev/peps/pep-0393] for more details about the implementation.) Once a string object is used outside of CPU and memory, endianness and how these arrays are stored as bytes become an issue. As with other codecs, serialising a string into a sequence of bytes is known as encoding, and recreating the string from the sequence of bytes is known as decoding. There are a variety of different text serialisation codecs, which are collectivity referred to as text encodings.

The simplest text encoding (called 'latin-1' or 'iso-8859-1') maps the code points 0–255 to the bytes 0x0–0xff, which means that a string object that contains code points above U+00FF can’t be encoded with this codec. Doing so will raise a UnicodeEncodeError that looks like the following (although the details of the error message may differ): UnicodeEncodeError: 'latin-1' codec can't encode character '\u1234' in position 3: ordinal not in range(256).

There’s another group of encodings (the so called charmap encodings) that choose a different subset of all Unicode code points and how these code points are mapped to the bytes 0x0–0xff. To see how this is done simply open e.g. encodings/cp1252.py (which is an encoding that is used primarily on Windows). There’s a string constant with 256 characters that shows you which character is mapped to which byte value.

All of these encodings can only encode 256 of the 1114112 code points defined in Unicode. A simple and straightforward way that can store each Unicode code point, is to store each code point as four consecutive bytes. There are two possibilities: store the bytes in big endian or in little endian order. These two encodings are called UTF-32-BE and UTF-32-LE respectively. Their disadvantage is that if e.g. you use UTF-32-BE on a little endian machine you will always have to swap bytes on encoding and decoding. UTF-32 avoids this problem: bytes will always be in natural endianness. When these bytes are read by a CPU with a different endianness, then bytes have to be swapped though. To be able to detect the endianness of a UTF-16 or UTF-32 byte sequence, there’s the so called BOM (« Byte Order Mark »). This is the Unicode character U+FEFF. This character can be prepended to every UTF-16 or UTF-32 byte sequence. The byte swapped version of this character (0xFFFE) is an illegal character that may not appear in a Unicode text. So when the first character in an UTF-16 or UTF-32 byte sequence appears to be a U+FFFE the bytes have to be swapped on decoding. Unfortunately the character U+FEFF had a second purpose as a ZERO WIDTH NO-BREAK SPACE: a character that has no width and doesn’t allow a word to be split. It can e.g. be used to give hints to a ligature algorithm. With Unicode 4.0 using U+FEFF as a ZERO WIDTH NO-BREAK SPACE has been deprecated (with U+2060 (WORD JOINER) assuming this role). Nevertheless Unicode software still must be able to handle U+FEFF in both roles: as a BOM it’s a device to determine the storage layout of the encoded bytes, and vanishes once the byte sequence has been decoded into a string; as a ZERO WIDTH NO-BREAK SPACE it’s a normal character that will be decoded like any other.

There’s another encoding that is able to encoding the full range of Unicode characters: UTF-8. UTF-8 is an 8-bit encoding, which means there are no issues with byte order in UTF-8. Each byte in a UTF-8 byte sequence consists of two parts: marker bits (the most significant bits) and payload bits. The marker bits are a sequence of zero to four 1 bits followed by a 0 bit. Unicode characters are encoded like this (with x being payload bits, which when concatenated give the Unicode character):

Range

Encoding

U-00000000 … U-0000007F

0xxxxxxx

U-00000080 … U-000007FF

110xxxxx 10xxxxxx

U-00000800 … U-0000FFFF

1110xxxx 10xxxxxx 10xxxxxx

U-00010000 … U-0010FFFF

11110xxx 10xxxxxx 10xxxxxx 10xxxxxx

The least significant bit of the Unicode character is the rightmost x bit.

As UTF-8 is an 8-bit encoding no BOM is required and any U+FEFF character in the decoded string (even if it’s the first character) is treated as a ZERO WIDTH NO-BREAK SPACE.

Without external information it’s impossible to reliably determine which encoding was used for encoding a string. Each charmap encoding can decode any random byte sequence. However that’s not possible with UTF-8, as UTF-8 byte sequences have a structure that doesn’t allow arbitrary byte sequences. To increase the reliability with which a UTF-8 encoding can be detected, Microsoft invented a variant of UTF-8 (that Python 2.5 calls "utf-8-sig") for its Notepad program: Before any of the Unicode characters is written to the file, a UTF-8 encoded BOM (which looks like this as a byte sequence: 0xef, 0xbb, 0xbf) is written. As it’s rather improbable that any charmap encoded file starts with these byte values (which would e.g. map to

LATIN SMALL LETTER I WITH DIAERESIS

RIGHT-POINTING DOUBLE ANGLE QUOTATION MARK

INVERTED QUESTION MARK

in iso-8859-1), this increases the probability that a utf-8-sig encoding can be correctly guessed from the byte sequence. So here the BOM is not used to be able to determine the byte order used for generating the byte sequence, but as a signature that helps in guessing the encoding. On encoding the utf-8-sig codec will write 0xef, 0xbb, 0xbf as the first three bytes to the file. On decoding utf-8-sig will skip those three bytes if they appear as the first three bytes in the file. In UTF-8, the use of the BOM is discouraged and should generally be avoided.

7.2.3. Standard Encodings

Python comes with a number of codecs built-in, either implemented as C functions or with dictionaries as mapping tables. The following table lists the codecs by name, together with a few common aliases, and the languages for which the encoding is likely used. Neither the list of aliases nor the list of languages is meant to be exhaustive. Notice that spelling alternatives that only differ in case or use a hyphen instead of an underscore are also valid aliases; therefore, e.g. 'utf-8' is a valid alias for the 'utf_8' codec.

CPython implementation detail: Some common encodings can bypass the codecs lookup machinery to improve performance. These optimization opportunities are only recognized by CPython for a limited set of (case insensitive) aliases: utf-8, utf8, latin-1, latin1, iso-8859-1, iso8859-1, mbcs (Windows only), ascii, us-ascii, utf-16, utf16, utf-32, utf32, and the same using underscores instead of dashes. Using alternative aliases for these encodings may result in slower execution.

Modifié dans la version 3.6: Optimization opportunity recognized for us-ascii.

Many of the character sets support the same languages. They vary in individual characters (e.g. whether the EURO SIGN is supported or not), and in the assignment of characters to code positions. For the European languages in particular, the following variants typically exist:

an ISO 8859 codeset

a Microsoft Windows code page, which is typically derived from an 8859 codeset, but replaces control characters with additional graphic characters

an IBM EBCDIC code page

an IBM PC code page, which is ASCII compatible

Codec

Aliases

Languages

ascii

646, us-ascii

Anglais

big5

big5-tw, csbig5

Chinois Traditionnel

big5hkscs

big5-hkscs, hkscs

Chinois Traditionnel

cp037

IBM037, IBM039

Anglais

cp273

273, IBM273, csIBM273

Allemand

Nouveau dans la version 3.4.

cp424

EBCDIC-CP-HE, IBM424

Hébreux

cp437

437, IBM437

Anglais

cp500

EBCDIC-CP-BE, EBCDIC-CP-CH, IBM500

Europe de l’ouest

cp720

Arabe

cp737

Grec

cp775

IBM775

Langues Baltiques

cp850

850, IBM850

Europe de l’ouest

cp852

852, IBM852

Europe centrale et Europe de l’Est

cp855

855, IBM855

Bulgare, Biélorusse, Macédonien, Russe, Serbe

cp856

Hébreux

cp857

857, IBM857

Turc

cp858

858, IBM858

Europe de l’ouest

cp860

860, IBM860

Portugais

cp861

861, CP-IS, IBM861

Islandais

cp862

862, IBM862

Hébreux

cp863

863, IBM863

Canadien

cp864

IBM864

Arabe

cp865

865, IBM865

Danish, Norwegian

cp866

866, IBM866

Russe

cp869

869, CP-GR, IBM869

Grec

cp874

Thai

cp875

Grec

cp932

932, ms932, mskanji, ms-kanji

Japanese

cp949

949, ms949, uhc

Korean

cp950

950, ms950

Chinois Traditionnel

cp1006

Urdu

cp1026

ibm1026

Turc

cp1125

1125, ibm1125, cp866u, ruscii

Ukrainian

Nouveau dans la version 3.4.

cp1140

ibm1140

Europe de l’ouest

cp1250

windows-1250

Europe centrale et Europe de l’Est

cp1251

windows-1251

Bulgare, Biélorusse, Macédonien, Russe, Serbe

cp1252

windows-1252

Europe de l’ouest

cp1253

windows-1253

Grec

cp1254

windows-1254

Turc

cp1255

windows-1255

Hébreux

cp1256

windows-1256

Arabe

cp1257

windows-1257

Langues Baltiques

cp1258

windows-1258

Vietnamese

cp65001

Windows uniquement : Windows UTF-8 (CP_UTF8)

Nouveau dans la version 3.3.

euc_jp

eucjp, ujis, u-jis

Japanese

euc_jis_2004

jisx0213, eucjis2004

Japanese

euc_jisx0213

eucjisx0213

Japanese

euc_kr

euckr, korean, ksc5601, ks_c-5601, ks_c-5601-1987, ksx1001, ks_x-1001

Korean

gb2312

chinese, csiso58gb231280, euc-cn, euccn, eucgb2312-cn, gb2312-1980, gb2312-80, iso-ir-58

Simplified Chinese

gbk

936, cp936, ms936

Unified Chinese

gb18030

gb18030-2000

Unified Chinese

hz

hzgb, hz-gb, hz-gb-2312

Simplified Chinese

iso2022_jp

csiso2022jp, iso2022jp, iso-2022-jp

Japanese

iso2022_jp_1

iso2022jp-1, iso-2022-jp-1

Japanese

iso2022_jp_2

iso2022jp-2, iso-2022-jp-2

Japanese, Korean, Simplified Chinese, Western Europe, Greek

iso2022_jp_2004

iso2022jp-2004, iso-2022-jp-2004

Japanese

iso2022_jp_3

iso2022jp-3, iso-2022-jp-3

Japanese

iso2022_jp_ext

iso2022jp-ext, iso-2022-jp-ext

Japanese

iso2022_kr

csiso2022kr, iso2022kr, iso-2022-kr

Korean

latin_1

iso-8859-1, iso8859-1, 8859, cp819, latin, latin1, L1

Europe de l’Ouest

iso8859_2

iso-8859-2, latin2, L2

Europe centrale et Europe de l’Est

iso8859_3

iso-8859-3, latin3, L3

Esperanto, Maltese

iso8859_4

iso-8859-4, latin4, L4

Langues Baltiques

iso8859_5

iso-8859-5, cyrillic

Bulgare, Biélorusse, Macédonien, Russe, Serbe

iso8859_6

iso-8859-6, arabic

Arabe

iso8859_7

iso-8859-7, greek, greek8

Grec

iso8859_8

iso-8859-8, hebrew

Hébreux

iso8859_9

iso-8859-9, latin5, L5

Turc

iso8859_10

iso-8859-10, latin6, L6

Nordic languages

iso8859_11

iso-8859-11, thai

Thai languages

iso8859_13

iso-8859-13, latin7, L7

Langues Baltiques

iso8859_14

iso-8859-14, latin8, L8

Celtic languages

iso8859_15

iso-8859-15, latin9, L9

Europe de l’ouest

iso8859_16

iso-8859-16, latin10, L10

South-Eastern Europe

johab

cp1361, ms1361

Korean

koi8_r

Russe

koi8_t

Tajik

Nouveau dans la version 3.5.

koi8_u

Ukrainian

kz1048

kz_1048, strk1048_2002, rk1048

Kazakh

Nouveau dans la version 3.5.

mac_cyrillic

maccyrillic

Bulgare, Biélorusse, Macédonien, Russe, Serbe

mac_greek

macgreek

Grec

mac_iceland

maciceland

Islandais

mac_latin2

maclatin2, maccentraleurope

Europe centrale et Europe de l’Est

mac_roman

macroman, macintosh

Europe de l’ouest

mac_turkish

macturkish

Turc

ptcp154

csptcp154, pt154, cp154, cyrillic-asian

Kazakh

shift_jis

csshiftjis, shiftjis, sjis, s_jis

Japanese

shift_jis_2004

shiftjis2004, sjis_2004, sjis2004

Japanese

shift_jisx0213

shiftjisx0213, sjisx0213, s_jisx0213

Japanese

utf_32

U32, utf32

all languages

utf_32_be

UTF-32BE

all languages

utf_32_le

UTF-32LE

all languages

utf_16

U16, utf16

all languages

utf_16_be

UTF-16BE

all languages

utf_16_le

UTF-16LE

all languages

utf_7

U7, unicode-1-1-utf-7

all languages

utf_8

U8, UTF, utf8

all languages

utf_8_sig

all languages

Modifié dans la version 3.4: The utf-16* and utf-32* encoders no longer allow surrogate code points (U+D800–U+DFFF) to be encoded. The utf-32* decoders no longer decode byte sequences that correspond to surrogate code points.

7.2.4. Python Specific Encodings

A number of predefined codecs are specific to Python, so their codec names have no meaning outside Python. These are listed in the tables below based on the expected input and output types (note that while text encodings are the most common use case for codecs, the underlying codec infrastructure supports arbitrary data transforms rather than just text encodings). For asymmetric codecs, the stated purpose describes the encoding direction.

7.2.4.1. Text Encodings

The following codecs provide str to bytes encoding and bytes-like object to str decoding, similar to the Unicode text encodings.

Codec

Aliases

Objectif

idna

Implements RFC 3490 [https://tools.ietf.org/html/rfc3490.html], see also encodings.idna. Only errors='strict' is supported.

mbcs

ansi, dbcs

Windows only: Encode operand according to the ANSI codepage (CP_ACP)

oem

Windows only: Encode operand according to the OEM codepage (CP_OEMCP)

Nouveau dans la version 3.6.

palmos

Encoding of PalmOS 3.5

punycode

Implements RFC 3492 [https://tools.ietf.org/html/rfc3492.html]. Stateful codecs are not supported.

raw_unicode_escape

Latin-1 encoding with \uXXXX and \UXXXXXXXX for other code points. Existing backslashes are not escaped in any way. It is used in the Python pickle protocol.

undefined

Raise an exception for all conversions, even empty strings. The error handler is ignored.

unicode_escape

Encoding suitable as the contents of a Unicode literal in ASCII-encoded Python source code, except that quotes are not escaped. Decodes from Latin-1 source code. Beware that Python source code actually uses UTF-8 by default.

unicode_internal

Return the internal representation of the operand. Stateful codecs are not supported.

Obsolète depuis la version 3.3: This representation is obsoleted by PEP 393 [https://www.python.org/dev/peps/pep-0393].

7.2.4.2. Binary Transforms

The following codecs provide binary transforms: bytes-like object to bytes mappings. They are not supported by bytes.decode() (which only produces str output).

Codec

Aliases

Objectif

Encoder / decoder

base64_codec 1

base64, base_64

Convert operand to multiline MIME base64 (the result always includes a trailing '\n')

Modifié dans la version 3.4: accepts any bytes-like object as input for encoding and decoding

base64.encodebytes() / base64.decodebytes()

bz2_codec

bz2

Compress the operand using bz2

bz2.compress() / bz2.decompress()

hex_codec

hex

Convert operand to hexadecimal representation, with two digits per byte

binascii.b2a_hex() / binascii.a2b_hex()

quopri_codec

quopri, quotedprintable, quoted_printable

Convert operand to MIME quoted printable

quopri.encode() with quotetabs=True / quopri.decode()

uu_codec

uu

Convert the operand using uuencode

uu.encode() / uu.decode()

zlib_codec

zip, zlib

Compress the operand using gzip

zlib.compress() / zlib.decompress()

1

In addition to bytes-like objects, 'base64_codec' also accepts ASCII-only instances of str for decoding

Nouveau dans la version 3.2: Restoration of the binary transforms.

Modifié dans la version 3.4: Restoration of the aliases for the binary transforms.

7.2.4.3. Text Transforms

The following codec provides a text transform: a str to str mapping. It is not supported by str.encode() (which only produces bytes output).

Codec

Aliases

Objectif

rot_13

rot13

Returns the Caesar-cypher encryption of the operand

Nouveau dans la version 3.2: Restoration of the rot_13 text transform.

Modifié dans la version 3.4: Restoration of the rot13 alias.

7.2.5. encodings.idna — Internationalized Domain Names in Applications

This module implements RFC 3490 [https://tools.ietf.org/html/rfc3490.html] (Internationalized Domain Names in Applications) and RFC 3492 [https://tools.ietf.org/html/rfc3492.html] (Nameprep: A Stringprep Profile for Internationalized Domain Names (IDN)). It builds upon the punycode encoding and stringprep.

These RFCs together define a protocol to support non-ASCII characters in domain names. A domain name containing non-ASCII characters (such as www.Alliancefrançaise.nu) is converted into an ASCII-compatible encoding (ACE, such as www.xn--alliancefranaise-npb.nu). The ACE form of the domain name is then used in all places where arbitrary characters are not allowed by the protocol, such as DNS queries, HTTP Host fields, and so on. This conversion is carried out in the application; if possible invisible to the user: The application should transparently convert Unicode domain labels to IDNA on the wire, and convert back ACE labels to Unicode before presenting them to the user.

Python supports this conversion in several ways: the idna codec performs conversion between Unicode and ACE, separating an input string into labels based on the separator characters defined in section 3.1 of RFC 3490 [https://tools.ietf.org/html/rfc3490.html#section-3.1] and converting each label to ACE as required, and conversely separating an input byte string into labels based on the . separator and converting any ACE labels found into unicode. Furthermore, the socket module transparently converts Unicode host names to ACE, so that applications need not be concerned about converting host names themselves when they pass them to the socket module. On top of that, modules that have host names as function parameters, such as http.client and ftplib, accept Unicode host names (http.client then also transparently sends an IDNA hostname in the Host field if it sends that field at all).

When receiving host names from the wire (such as in reverse name lookup), no automatic conversion to Unicode is performed: Applications wishing to present such host names to the user should decode them to Unicode.

The module encodings.idna also implements the nameprep procedure, which performs certain normalizations on host names, to achieve case-insensitivity of international domain names, and to unify similar characters. The nameprep functions can be used directly if desired.

encodings.idna.nameprep(label)

Return the nameprepped version of label. The implementation currently assumes query strings, so AllowUnassigned is true.

encodings.idna.ToASCII(label)

Convert a label to ASCII, as specified in RFC 3490 [https://tools.ietf.org/html/rfc3490.html]. UseSTD3ASCIIRules is assumed to be false.

encodings.idna.ToUnicode(label)

Convert a label to Unicode, as specified in RFC 3490 [https://tools.ietf.org/html/rfc3490.html].

7.2.6. encodings.mbcs — Windows ANSI codepage

Encode operand according to the ANSI codepage (CP_ACP).

Availability: Windows only.

Modifié dans la version 3.3: Support any error handler.

Modifié dans la version 3.2: Before 3.2, the errors argument was ignored; 'replace' was always used to encode, and 'ignore' to decode.

7.2.7. encodings.utf_8_sig — UTF-8 codec with BOM signature

This module implements a variant of the UTF-8 codec: On encoding a UTF-8 encoded BOM will be prepended to the UTF-8 encoded bytes. For the stateful encoder this is only done once (on the first write to the byte stream). For decoding an optional UTF-8 encoded BOM at the start of the data will be skipped.

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8. Types de données

Les modules documentés dans ce chapitre fournissent une gamme de types de données spécialisés tel que les dates et les heures, les listes à type prédéfini, les heap queue, les queues synchronisées, et les ensembles.

Python fournit aussi quelques types natifs, typiquement dict, list, set, frozenset, et tuple. La classe str est utilisée pour stocker des chaînes Unicode, et la classe bytes des données binaires.

Les modules suivants sont documentés dans ce chapitre :

8.1. datetime — Types de base pour la date et l’heure

8.1.1. Types disponibles

8.1.2. Objets timedelta

8.1.3. Objets date

8.1.4. Objets datetime

8.1.5. Objets time

8.1.6. Objets tzinfo

8.1.7. Objets timezone

8.1.8. Comportement de strftime() et strptime()

8.2. calendar — General calendar-related functions

8.3. collections — Types de données de conteneurs

8.3.1. Objets ChainMap

8.3.1.1. Exemples et cas pratiques utilisant ChainMap

8.3.2. Objets Counter

8.3.3. Objets deque

8.3.3.1. Cas pratiques utilisant deque

8.3.4. Objets defaultdict

8.3.4.1. Exemples utilisant defaultdict

8.3.5. namedtuple(): fonction de construction pour n-uplets (tuples) avec des champs nommés

8.3.6. Objets OrderedDict

8.3.6.1. Exemples et cas pratiques utilisant OrderDict

8.3.7. Objets UserDict

8.3.8. Objets UserList

8.3.9. Objets UserString

8.4. collections.abc — Classes de base abstraites pour les conteneurs

8.4.1. Classes de base abstraites de collections

8.5. heapq — File de priorité basée sur un tas

8.5.1. Exemples simples

8.5.2. Notes d’implémentation de la file de priorité

8.5.3. Théorie

8.6. bisect — Algorithme de bissection de listes

8.6.1. Chercher dans des listes triées

8.6.2. Autres Exemples

8.7. array — Tableaux efficaces de valeurs numériques

8.8. weakref — Weak references

8.8.1. Objets à références faibles

8.8.2. Exemple

8.8.3. Finalizer Objects

8.8.4. Comparing finalizers with __del__() methods

8.9. types — Dynamic type creation and names for built-in types

8.9.1. Dynamic Type Creation

8.9.2. Standard Interpreter Types

8.9.3. Additional Utility Classes and Functions

8.9.4. Coroutine Utility Functions

8.10. copy — Opérations de copie superficielle et récursive

8.11. pprint — L’affichage élégant de données

8.11.1. Les Objets PrettyPrinter

8.11.2. Exemple

8.12. reprlib — Alternate repr() implementation

8.12.1. Repr Objects

8.12.2. Subclassing Repr Objects

8.13. enum — Énumerations

8.13.1. Contenu du module

8.13.2. Création d’une Enum

8.13.3. Accès dynamique aux membres et à leurs attributs

8.13.4. Duplication de membres et de valeurs

8.13.5. Coercition d’unicité des valeurs d’une énumération

8.13.6. Valeurs automatiques

8.13.7. Itération

8.13.8. Comparaisons

8.13.9. Membres et attributs autorisés dans une énumération

8.13.10. Restricted subclassing of enumerations

8.13.11. Sérialisation

8.13.12. API par fonction

8.13.13. Énumérations dérivées

8.13.13.1. IntEnum

8.13.13.2. IntFlag

8.13.13.3. Option

8.13.13.4. Autres

8.13.14. Exemples intéressants

8.13.14.1. Omettre les valeurs

8.13.14.1.1. Avec auto

8.13.14.1.2. Avec object

8.13.14.1.3. Avec une chaîne de caractères de description

8.13.14.1.4. Avec une méthode ad-hoc __new__()

8.13.14.2. OrderedEnum

8.13.14.3. DuplicateFreeEnum

8.13.14.4. Planet

8.13.15. En quoi les Enums sont différentes ?

8.13.15.1. Classes Enum

8.13.15.2. Membres d’Enum (c.-à-d. instances)

8.13.15.3. Aspects approfondis

8.13.15.3.1. Noms de la forme __dunder__ disponibles

8.13.15.3.2. Noms de la forme _sunder_ disponibles

8.13.15.3.3. Type des membres de Enum

8.13.15.3.4. Valeur booléenne des classes Enum et de leurs membres

8.13.15.3.5. Classes Enum avec des méthodes

8.13.15.3.6. Combinaison de membres de Flag

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8.1. datetime — Types de base pour la date et l’heure

Code source : Lib/datetime.py [https://github.com/python/cpython/tree/3.6/Lib/datetime.py]

Le module datetime fournit des classes pour manipuler de façon simple ou plus complexe des dates et des heures. Bien que les calculs de date et d’heure sont gérés, l’implémentation est essentiellement tournée vers l’efficacité pour extraire des attributs pour les manipuler et les formater pour l’affichage. Pour d’autres fonctionnalités associées, voir aussi les modules time et calendar.

Il y a deux sortes d’objets date et time : les « naïfs » et les « avisés ».

Un objet avisé possède suffisamment de connaissance des règles à appliquer et des politiques d’ajustement de l’heure comme les informations sur les fuseaux horaires et l’heure d’été pour se situer de façon relative par rapport à d’autres objets avisés. Un objet avisé est utilisé pour représenté un moment précis de l’histoire qui n’est pas ouvert à l’interprétation 1.

Un objet naïf ne comporte pas assez d’informations pour se situer sans ambiguïté par rapport à d’autres objets date/time. Le fait qu’un objet naïf représente un Temps universel coordonné (UTC), une heure locale ou une heure dans un autre fuseau horaire dépend complètement du programme, tout comme un nombre peut représenter une longueur, un poids ou une distance pour le programme. Les objets naïfs sont simples à comprendre et il est aisé de travailler avec, au prix de négliger certains aspects de la réalité.

Pour les applications qui nécessitent des objets avisés, les objets datetime et time ont un attribut optionnel d’information sur le fuseau horaire, tzinfo, qui peut être réglé sur une instance d’une sous-classe de la classe abstraite tzinfo. Ces objets tzinfo capturent l’information à propos du décalage avec le temps UTC, le nom du fuseau horaire, et si l’heure d’été est effective. Notez qu’une seule classe concrète tzinfo, la classe timezone, est proposée par le module datetime. La classe timezone représente des fuseaux horaires simples avec un décalage fixe par rapport à UTC, comme UTC lui-même ou les fuseaux EST et EDT d’Amérique du Nord. Gérer des fuseaux horaires d’un niveau de détails plus avancé est à la charge de l’application. Les règles d’ajustement du temps à travers le monde sont plus politiques que rationnelles, changent fréquemment, et il n’y a pas de standard qui vaille pour toute application, en dehors d’UTC.

Le module datetime exporte les constantes suivantes :

datetime.MINYEAR

Le numéro d’année le plus petit autorisé dans un objet date ou datetime. MINYEAR vaut 1.

datetime.MAXYEAR

Le numéro d’année le plus grand autorisé dans un objet date ou datetime. MAXYEAR vaut 9999.

Voir aussi

Module calendar

Fonctions génériques associées au calendrier.

Module time

Accès au données d’horaires et aux conversions associées.

8.1.1. Types disponibles

class datetime.date

Une date naïve idéalisée, en supposant que le calendrier Grégorien actuel a toujours existé et qu’il existera toujours. Attributs : year, month et day.

class datetime.time

Un temps idéalisé, indépendant d’une date particulière, en supposant qu’une journée est composée d’exactement 24*60*60 secondes (il n’y a pas ici de notion de « seconde bissextile »). Attributs : hour, minute, second, microsecond et tzinfo.

class datetime.datetime

Une combinaison d’une date et d’une heure. Attributs : year, month, day, hour, minute, second, microsecond, et tzinfo.

class datetime.timedelta

Une durée qui exprime la différence entre deux instances de date, time ou datetime en microsecondes.

class datetime.tzinfo

Une classe de base abstraite pour les objets portants des informations sur les fuseaux horaires. Ceux-ci sont utilisés par les classes datetime et time pour donner une notion personnalisable d’ajustement d’horaire (par exemple la prise en compte d’un fuseau horaire et/ou de l’heure d’été).

class datetime.timezone

Une classe qui implémente la classe de base abstraite tzinfo en tant qu’offset fixe par rapport au temps UTC.

Nouveau dans la version 3.2.

Les objets issus de ces types sont immuables.

Les objets de type date sont toujours naïfs.

Un objet de type time ou datetime peut être naïf ou avisé. Un objet datetime d est avisé si d.tzinfo ne vaut pas None et que d.tzinfo.utcoffset(d) ne renvoie pas None. Si d.tzinfo vaut None ou que d.tzinfo ne vaut pas None mais que d.tzinfo.utcoffset(d) renvoie None, alors d est naïf. Un objet time t est avisé si t.tzinfo ne vaut pas None et que t.tzinfo.utcoffset(None) ne renvoie pas None. Sinon, t est naïf.

La distinction entre naïf et avisé ne s’applique pas aux objets de type timedelta.

Relations entre les sous-classes :

object
    timedelta
    tzinfo
        timezone
    time
    date
        datetime

8.1.2. Objets timedelta

Un objet timedelta représente une durée, c’est-à-dire la différence entre deux dates ou heures.

class datetime.timedelta(days=0, seconds=0, microseconds=0, milliseconds=0, minutes=0, hours=0, weeks=0)

Tous les paramètres sont optionnels et ont 0 comme valeur par défaut. Les paramètres peuvent être des entiers ou des flottants et ils peuvent être positifs ou négatifs.

Seuls les jours, les secondes et les microsecondes sont stockés en interne. Tous les paramètres sont convertis dans ces unités :

Une milliseconde est convertie en 1000 microsecondes.

Une minute est convertie en 60 secondes.

Une heure est convertie en 3600 secondes.

Une semaine est convertie en 7 jours.

et ensuite les jours, secondes et microsecondes sont normalisés pour que la représentation soit unique avec

0 <= microseconds < 1000000

0 <= secondes < 3600*24 (le nombre de secondes dans une journée)

-999999999 <= days <= 999999999

Si l’un des arguments est un flottant et qu’il y a des microsecondes décimales, les microsecondes décimales laissées par les arguments sont combinées et leur somme est arrondie à la microseconde la plus proche (en arrondissant les demis vers le nombre pair). Si aucun argument n’est flottant, les processus de conversion et de normalisation seront exacts (pas d’informations perdues).

Si la valeur normalisée des jours déborde de l’intervalle indiqué, une OverflowError est levée.

Notez que la normalisation de valeurs négatives peut être surprenante au premier abord. Par exemple,

>>> from datetime import timedelta
>>> d = timedelta(microseconds=-1)
>>> (d.days, d.seconds, d.microseconds)
(-1, 86399, 999999)

Les attributs de la classe sont :

timedelta.min

L’objet timedelta le plus négatif, timedelta(-999999999).

timedelta.max

L’objet timedelta le plus positif, timedelta(days=999999999, hours=23, minutes=59, seconds=59, microseconds=999999).

timedelta.resolution

La plus petite différence entre des objets timedelta non égaux, timedelta(microseconds=1).

Il est à noter, du fait de la normalisation, que timedelta.max > -timedelta.min. -timedelta.max n’est pas représentable sous la forme d’un objet timedelta.

Attributs de l’instance (en lecture seule) :

Attribut

Valeur

days

Entre -999999999 et 999999999 inclus

seconds

Entre 0 et 86399 inclus

microseconds

Entre 0 et 999999 inclus

Opérations gérées :

Opération

Résultat

t1 = t2 + t3

Somme de t2 et t3. Ensuite t1 - t2 == t3 et t1 - t3 == t2 sont des expressions vraies. (1)

t1 = t2 - t3

Difference of t2 and t3. Afterwards t1 == t2 - t3 and t2 == t1 + t3 are true. (1)(6)

t1 = t2 * i or t1 = i * t2

Delta multiplié par un entier. Ensuite t1 // i == t2 est vrai, en admettant que i != 0.

De manière générale, t1 * i == t1 * (i-1) + t1 est vrai. (1)

t1 = t2 * f or t1 = f * t2

Delta multiplié par un flottant. Le résultat est arrondi au multiple le plus proche de timedelta.resolution en utilisant la règle de l’arrondi au pair le plus proche.

f = t2 / t3

Division (3) de t2 par t3. Renvoie un objet float.

t1 = t2 / f or t1 = t2 / i

Delta divisé par un flottant ou un entier. Le résultat est arrondi au multiple le plus proche de timedelta.resolution en utilisant la règle de l’arrondi au pair le plus proche.

t1 = t2 // i or t1 = t2 // t3

Le quotient est calculé et le reste (s’il y en a un) est ignoré. Dans le second cas, un entier est renvoyé. (3)

t1 = t2 % t3

Le reste est calculé comme un objet de type timedelta. (3)

q, r = divmod(t1, t2)

Calcule le quotient et le reste : q = t1 // t2 (3) et r = t1 % t2. q est un entier et r est un objet timedelta.

+t1

Renvoie un objet timedelta avec la même valeur. (2)

-t1

équivalent à timedelta(-t1.days, -t1.seconds, -t1.microseconds), et à t1 * -1. (1)(4)

abs(t)

équivalent à +t quand t.days >= 0, et à -t quand t.days < 0. (2)

str(t)

Renvoie une chaîne de la forme [D day[s], ][H]H:MM:SS[.UUUUUU], où D est négatif pour t négatif. (5)

repr(t)

Renvoie une chaîne de la forme datetime.timedelta(D[, S[, U]]), où D est négatif pour t négatif. (5)

Notes :

Ceci est exact, mais peut provoquer un débordement.

Ceci est exact, et ne peut pas provoquer un débordement.

Une division par 0 provoque ZeroDivisionError.

-timedelta.max n’est pas représentable avec un objet timedelta.

La représentation en chaîne de caractères des objets timedelta est normalisée similairement à leur représentation interne. Cela amène à des résultats inhabituels pour des timedeltas négatifs. Par exemple :

>>> timedelta(hours=-5)
datetime.timedelta(-1, 68400)
>>> print(_)
-1 day, 19:00:00

The expression t2 - t3 will always be equal to the expression t2 + (-t3) except when t3 is equal to timedelta.max; in that case the former will produce a result while the latter will overflow.

En plus des opérations listées ci-dessus, les objets timedelta implémentent certaines additions et soustractions avec des objets date et datetime (voir ci-dessous).

Modifié dans la version 3.2: La division entière et la vraie division d’un objet timedelta par un autre timedelta sont maintenant gérées, comme le sont les opérations de reste euclidien et la fonction divmod(). La vraie division et la multiplication d’un objet timedelta par un float sont maintenant implémentées.

Les comparaisons entre objets timedelta sont maintenant gérées avec le timedelta représentant la plus courte durée considéré comme le plus petit. Afin d’empêcher les comparaisons de types mixtes de retomber sur la comparaison par défaut par l’adresse de l’objet, quand un objet timedelta est comparé à un objet de type différent, une TypeError est levée à moins que la comparaison soit == ou !=. Ces derniers cas renvoient respectivement False et True.

Les objets timedelta sont hashable (utilisables comme clés de dictionnaires), implémentent le protocole pickle et, dans un contexte booléen, un timedelta est considéré vrai si et seulement si il n’est pas égal à timedelta(0).

Méthodes de l’instance :

timedelta.total_seconds()

Renvoie le nombre total de secondes contenues dans la durée. Équivalent à td / timedelta(seconds=1).

Notez que pour des intervalles de temps très larges (supérieurs à 270 ans sur la plupart des plateformes), cette méthode perdra la précision des microsecondes.

Nouveau dans la version 3.2.

Exemple d’utilisation :

>>> from datetime import timedelta
>>> year = timedelta(days=365)
>>> another_year = timedelta(weeks=40, days=84, hours=23,
...                          minutes=50, seconds=600)  # adds up to 365 days
>>> year.total_seconds()
31536000.0
>>> year == another_year
True
>>> ten_years = 10 * year
>>> ten_years, ten_years.days // 365
(datetime.timedelta(3650), 10)
>>> nine_years = ten_years - year
>>> nine_years, nine_years.days // 365
(datetime.timedelta(3285), 9)
>>> three_years = nine_years // 3;
>>> three_years, three_years.days // 365
(datetime.timedelta(1095), 3)
>>> abs(three_years - ten_years) == 2 * three_years + year
True

8.1.3. Objets date

Un objet date représente une date (année, mois et jour) dans un calendrier idéal, l’actuel calendrier grégorien étendu indéfiniment dans les deux directions. Le 1er janvier de l’an 1 est appelé le jour numéro 1, le 2 janvier de l’an 1 est appelé le jour numéro 2, et ainsi de suite. Cela correspond à la définition du calendrier « grégorien proleptique » dans le livre Calendrical Calculations de Dershowitz et Reingold, où il est la base de tous les calculs. Référez-vous au livre pour les algorithmes de conversion entre calendriers grégorien proleptique et les autres systèmes.

class datetime.date(year, month, day)

Tous les arguments sont requis. Les arguments peuvent être des entiers, dans les intervalles suivant :

MINYEAR <= year <= MAXYEAR

1 <= month <= 12

1 <= day <= nombre de jours dans le mois et l'année donnés

Si un argument est donné en dehors de ces intervalles, une valueError est levée.

Autres constructeurs, méthodes de classe :

classmethod date.today()

Renvoie la date locale courante. Cela est équivalent à date.fromtimestamp(time.time()).

classmethod date.fromtimestamp(timestamp)

Renvoie la date locale correspondant à l’horodatage (timestamp en anglais) POSIX, tel que renvoyé par time.time(). Elle peut lever une OverflowError, si l’horodatage est en dehors des bornes gérées par la fonction C localtime() de la plateforme, et une OSError en cas d’échec de localtime(). Il est commun d’être restreint aux années entre 1970 et 2038. Notez que sur les systèmes non POSIX qui incluent les secondes de décalage dans leur notion d’horodatage, ces secondes sont ignorées par fromtimestamp().

Modifié dans la version 3.3: Lève une OverflowError plutôt qu’une ValueError si l’horodatage (timestamp en anglais) est en dehors des bornes gérées par la fonction C localtime() de la plateforme. Lève une OSError plutôt qu’une ValueError en cas d’échec de localtime().

classmethod date.fromordinal(ordinal)

Renvoie la date correspondant à l’ordinal grégorien proleptique, où le 1er janvier de l’an 1 a l’ordinal 1. ValueError est levée à moins que 1 <= ordinal <= date.max.toordinal(). Pour toute date d, date.fromordinal(d.toordinal()) == d.

Attributs de la classe :

date.min

La plus vieille date représentable, date(MINYEAR, 1, 1).

date.max

La dernière date représentable, date(MAXYEAR, 12, 31).

date.resolution

La plus petite différence possible entre deux objets dates non-égaux, timedelta(days=1).

Attributs de l’instance (en lecture seule) :

date.year

Entre MINYEAR et MAXYEAR inclus.

date.month

Entre 1 et 12 inclus.

date.day

Entre 1 et le nombre de jours du mois donné de l’année donnée.

Opérations gérées :

Opération

Résultat

date2 = date1 + timedelta

date2 est décalée de timedelta.days jours par rapport à date1. (1)

date2 = date1 - timedelta

Calcule date2 de façon à avoir date2 + timedelta == date1. (2)

timedelta = date1 - date2

(3)

date1 < date2

date1 est considérée comme inférieure à date2 quand date1 précède date2 dans le temps. (4)

Notes :

date2 est déplacée en avant dans le temps si timedelta.days > 0, ou en arrière si timedelta.days < 0. Après quoi date2 - date1 == timedelta.days. timedelta.seconds et timedelta.microseconds sont ignorés. Une OverflowError est levée si date2.year devait être inférieure à MINYEAR ou supérieure à MAXYEAR.

timedelta.seconds and timedelta.microseconds are ignored.

Cela est exact, et ne peut pas dépasser les bornes. timedelta.seconds et timedelta.microseconds valent 0, et date2 + timedelta == date1 après cela.

In other words, date1 < date2 if and only if date1.toordinal() < date2.toordinal(). Date comparison raises TypeError if the other comparand isn’t also a date object. However, NotImplemented is returned instead if the other comparand has a timetuple() attribute. This hook gives other kinds of date objects a chance at implementing mixed-type comparison. If not, when a date object is compared to an object of a different type, TypeError is raised unless the comparison is == or !=. The latter cases return False or True, respectively.

Les dates peuvent être utilisées en tant que clés de dictionnaires. Dans un contexte booléen, tous les objets date sont considérés comme vrais.

Méthodes de l’instance :

date.replace(year=self.year, month=self.month, day=self.day)

Renvoie une date avec la même valeur, excepté pour les valeurs spécifiées par arguments nommés. Par exemple, si d == date(2002, 12, 31), alors d.replace(day=26) == date(2002, 12, 26).

date.timetuple()

Renvoie une time.struct_time telle que renvoyée par time.localtime(). Les heures, minutes et secondes valent 0, et le flag DST (heure d’été) est -1. d.timetuple() est équivalent à time.struct_time((d.year, d.month, d.day, 0, 0, 0, d.weekday(), yday, -1)), où yday = d.toordinal() - date(d.year, 1, 1).toordinal() + 1 est le numéro du jour dans l’année courante, commençant avec 1 pour le 1er janvier.

date.toordinal()

Renvoie l’ordinal grégorien proleptique de la date, où le 1er janvier de l’an 1 a l’ordinal 1. Pour tout objet date d, date.fromordinal(d.toordinal()) == d.

date.weekday()

Renvoie le jour de la semaine sous forme de nombre, où lundi vaut 0 et dimanche vaut 6. Par exemple, date(2002, 12, 4).weekday() == 2, un mercredi. Voir aussi isoweekday().

date.isoweekday()

Renvoie le jour de la semaine sous forme de nombre, où lundi vaut 1 et dimanche vaut 7. Par exemple, date(2002, 12, 4).isoweekday() == 3, un mercredi. Voir aussi weekday(), isocalendar().

date.isocalendar()

Renvoie un tuple de 3 éléments, (année ISO, numéro de semaine ISO, jour de la semaine ISO).

Le calendrier ISO est une variante largement utilisée du calendrier grégorien. Voir https://www.staff.science.uu.nl/~gent0113/calendar/isocalendar.htm pour une bonne explication.

Une année ISO est composée de 52 ou 53 semaines pleines, où chaque semaine débute un lundi et se termine un dimanche. La première semaine d’une année ISO est la première semaine calendaire (grégorienne) de l’année comportant un jeudi. Elle est appelée la semaine numéro 1, et l’année ISO de ce mercredi est la même que son année grégorienne.

Par exemple, l’année 2004 débute un jeudi, donc la première semaine de l’année ISO 2004 débute le lundi 29 décembre 2003 et se termine le dimanche 4 janvier 2004, ainsi date(2003, 12, 29).isocalendar() == (2004, 1, 1) et date(2004, 1, 4).isocalendar() == (2004, 1, 7).

date.isoformat()

Renvoie une chaîne de caractères représentant la date au format ISO 8601, « YYYY-MM-DD ». Par exemple, date(2002, 12, 4).isoformat() == '2002-12-04'.

date.__str__()

Pour une date d, str(d) est équivalent à d.isoformat().

date.ctime()

Renvoie une chaîne de caractères représentant la date, par exemple date(2002, 12, 4).ctime() == 'Wed Dec 4 00:00:00 2002'. d.ctime() est équivalent à time.ctime(time.mktime(d.timetuple())) sur les plateformes où la fonction C native ctime() (que time.ctime() invoque, mais pas date.ctime()) est conforme au standard C.

date.strftime(format)

Renvoie une chaîne de caractères représentant la date, contrôlée par une chaîne de formatage explicite. Les codes de formatage se référant aux heures, minutes ou secondes auront pour valeur 0. Pour une liste complète des directives de formatage, voir Comportement de strftime() et strptime().

date.__format__(format)

Identique à date.strftime(). Cela permet de spécifier une chaîne de formatage pour un objet date dans une chaîne de formatage littérale et à l’utilisation de str.format(). Pour une liste complète des directives de formatage, voir Comportement de strftime() et strptime().

Exemple de décompte des jours avant un évènement :

>>> import time
>>> from datetime import date
>>> today = date.today()
>>> today
datetime.date(2007, 12, 5)
>>> today == date.fromtimestamp(time.time())
True
>>> my_birthday = date(today.year, 6, 24)
>>> if my_birthday < today:
...     my_birthday = my_birthday.replace(year=today.year + 1)
>>> my_birthday
datetime.date(2008, 6, 24)
>>> time_to_birthday = abs(my_birthday - today)
>>> time_to_birthday.days
202

Exemple d’utilisation de la classe date :

>>> from datetime import date
>>> d = date.fromordinal(730920) # 730920th day after 1. 1. 0001
>>> d
datetime.date(2002, 3, 11)
>>> t = d.timetuple()
>>> for i in t:
...     print(i)
2002                # year
3                   # month
11                  # day
0
0
0
0                   # weekday (0 = Monday)
70                  # 70th day in the year
-1
>>> ic = d.isocalendar()
>>> for i in ic:
...     print(i)
2002                # ISO year
11                  # ISO week number
1                   # ISO day number ( 1 = Monday )
>>> d.isoformat()
'2002-03-11'
>>> d.strftime("%d/%m/%y")
'11/03/02'
>>> d.strftime("%A %d. %B %Y")
'Monday 11. March 2002'
>>> 'The {1} is {0:%d}, the {2} is {0:%B}.'.format(d, "day", "month")
'The day is 11, the month is March.'

8.1.4. Objets datetime

Un objet datetime est un objet comportant toutes les informations d’un objet date et d’un objet time. Comme un objet date, un objet datetime utilise l’actuel calendrier Grégorien étendu vers le passé et le futur ; comme un objet time, un objet datetime suppose qu’il y a exactement 3600*24 secondes chaque jour.

Constructeur :

class datetime.datetime(year, month, day, hour=0, minute=0, second=0, microsecond=0, tzinfo=None, *, fold=0)

Les arguments year, month et day sont requis. tzinfo peut être None, ou une instance d’une sous-classe de tzinfo. Les arguments restant doivent être des nombres, dans les intervalles suivants :

MINYEAR <= year <= MAXYEAR,

1 <= month <= 12,

1 <= day <= nombre de jours dans le mois donné de l'année donnée,

0 <= hour < 24,

0 <= minute < 60,

0 <= second < 60,

0 <= microsecond < 1000000,

fold in [0, 1].

Si un argument est donné en dehors de ces intervalles, une valueError est levée.

Nouveau dans la version 3.6: Ajout de l’argument fold.

Autres constructeurs, méthodes de classe :

classmethod datetime.today()

Renvoie le datetime local courant, avec tzinfo à None. Cela est équivalent à datetime.fromtimestamp(time.time()). Voir aussi now(), fromtimestamp().

classmethod datetime.now(tz=None)

Renvoie la date et l’heure courantes locales. Si l’argument optionnel tz est None ou n’est pas spécifié, la méthode est similaire à today(), mais, si possible, apporte plus de précisions que ce qui peut être trouvé à travers un horodatage time.time() (par exemple, cela peut être possible sur des plateformes fournissant la fonction C gettimeofday()).

Si tz n’est pas None, il doit être une instance d’une sous-classe tzinfo, et la date et l’heure courantes sont converties vers le fuseau horaire tz. Dans ce cas le résultat est équivalent à tz.fromutc(datetime.utcnow().replace(tzinfo=tz)). Voir aussi today(), utcnow().

classmethod datetime.utcnow()

Renvoie la date et l’heure UTC courantes, avec tzinfo à None. C’est semblable à now(), mais renvoie la date et l’heure UTC courantes, comme un objet datetime naïf. Un datetime UTC courant avisé peut être obtenu en appelant datetime.now(timezone.utc). Voir aussi now().

classmethod datetime.fromtimestamp(timestamp, tz=None)

Renvoie la date et l’heure locales correspondant à l’horodatage (timestamp en anglais) POSIX, comme renvoyé par time.time(). Si l’argument optionnel tz est None ou n’est pas spécifié, l’horodatage est converti vers la date et l’heure locales de la plateforme, et l’objet datetime renvoyé est naïf.

Si tz n’est pas None, il doit être une instance d’une sous-classe tzinfo, et l’horodatage (timestamp en anglais) est converti vers le fuseau horaire tz. Dans ce cas le résultat est équivalent à tz.fromutc(datetime.utcfromtimestamp(timestamp).replace(tzinfo=tz)).

fromtimestamp() peut lever une OverflowError, si l’horodatage est en dehors de l’intervalle de valeurs gérées par les fonctions C localtime() ou gmtime() de la plateforme, et une OSError en cas d’échec de localtime() ou gmtime(). Il est courant d’être restreint aux années de 1970 à 2038. Notez que sur les systèmes non POSIX qui incluent les secondes intercalaires dans leur notion d’horodatage, les secondes intercalaires sont ignorées par fromtimestamp(), et il est alors possible d’avoir deux horodatages différant d’une seconde produisant un objet datetime identique. Voir aussi utcfromtimestamp().

Modifié dans la version 3.3: Lève une OverflowError plutôt qu’une ValueError si l’horodatage est en dehors de l’intervalle de valeurs gérées par les fonctions C localtime() ou gmtime() de la plateforme. Lève une OSError plutôt qu’une ValueError en cas d’échec de localtime() ou gmtime().

Modifié dans la version 3.6: fromtimestamp() peut renvoyer des instances avec l’attribut fold à 1.

classmethod datetime.utcfromtimestamp(timestamp)

Renvoie le datetime UTC correspondant à l’horodatage (timestamp en anglais) POSIX, avec tzinfo à None. Cela peut lever une OverflowError, si l’horodatage est en dehors de l’intervalle de valeurs gérées par la fonction C gmtime() de la plateforme, et une OSError en cas d’échec de gmtime(). Il est courant d’être restreint aux années de 1970 à 2038.

Pour obtenir un objet datetime avisé, appelez fromtimestamp() :

datetime.fromtimestamp(timestamp, timezone.utc)

Sur les plateformes respectant POSIX, cela est équivalent à l’expression suivante :

datetime(1970, 1, 1, tzinfo=timezone.utc) + timedelta(seconds=timestamp)

excepté que la dernière formule gère l’intervalle complet des années entre MINYEAR et MAXYEAR incluses.

Modifié dans la version 3.3: Lève une OverflowError plutôt qu’une ValueError si l’horodatage est en dehors de l’intervalle de valeurs gérées par la fonction C gmtime() de la plateforme. Lève une OSError plutôt qu’une ValueError en cas d’échec de gmtime().

classmethod datetime.fromordinal(ordinal)

Renvoie le datetime correspondant à l’ordinal du calendrier grégorien proleptique, où le 1er janvier de l’an 1 a l’ordinal 1. Une ValueError est levée à moins que 1 <= ordinal <= datetime.max.toordinal(). Les heures, minutes, secondes et microsecondes du résultat valent toutes 0, et tzinfo est None.

classmethod datetime.combine(date, time, tzinfo=self.tzinfo)

Renvoie un nouvel objet datetime dont les composants de date sont égaux à ceux de l’objet date donné, et donc les composants de temps sont égaux à ceux de l’objet time donné. Si l’argument tzinfo est fourni, sa valeur est utilisée pour initialiser l’attribut tzinfo du résultat, autrement l’attribut tzinfo de l’argument time est utilisé.

Pour tout objet datetime d*`, ``d == datetime.combine(d.date(), d.time(), d.tzinfo)``. Si *date est un objet datetime, ses composants de temps et attributs tzinfo sont ignorés.

Modifié dans la version 3.6: Ajout de l’argument tzinfo.

classmethod datetime.strptime(date_string, format)

Renvoie un datetime correspondant à la chaîne date_string, analysée conformément à format. Cela est équivalent à datetime(*(time.strptime(date_string, format)[0:6])). Une ValueError est levée si date_string et format ne peuvent être analysée par time.strptime() ou si elle renvoie une valeur qui n’est pas un tuple-temps. Pour une liste complète des directives de formatage, voir Comportement de strftime() et strptime().

Attributs de la classe :

datetime.min

Le plus ancien datetime représentable, datetime(MINYEAR, 1, 1, tzinfo=None).

datetime.max

Le dernier datetime représentable, datetime(MAXYEAR, 12, 31, 23, 59, 59, 999999, tzinfo=None).

datetime.resolution

La plus petite différence possible entre deux objets datetime non-égaux, timedelta(microseconds=1).

Attributs de l’instance (en lecture seule) :

datetime.year

Entre MINYEAR et MAXYEAR inclus.

datetime.month

Entre 1 et 12 inclus.

datetime.day

Entre 1 et le nombre de jours du mois donné de l’année donnée.

datetime.hour

Dans range(24).

datetime.minute

Dans range(60).

datetime.second

Dans range(60).

datetime.microsecond

Dans range(1000000).

datetime.tzinfo

L’objet passé en tant que paramètre tzinfo du constructeur de la classe datetime ou None si aucun n’a été donné.

datetime.fold

0 ou 1. Utilisé pour désambiguïser les heures dans un intervalle répété. (Un intervalle répété apparaît quand l’horloge est retardée à la fin de l’heure d’été ou quand le décalage UTC du fuseau courant et décrémenté pour des raisons politiques.) La valeur 0 (1) représente le plus ancien (récent) des deux moments représentés par la même heure.

Nouveau dans la version 3.6.

Opérations gérées :

Opération

Résultat

datetime2 = datetime1 + timedelta

(1)

datetime2 = datetime1 - timedelta

(2)

timedelta = datetime1 - datetime2

(3)

datetime1 < datetime2

Compare datetime à datetime. (4)

datetime2 est décalé d’une durée timedelta par rapport à datetime1, en avant dans le temps si timedelta.days > 0, ou en arrière si timedelta.days < 0. Le résultat a le même attribut tzinfo que le datetime d’entrée, et datetime2 - datetime1 == timedelta après l’opération. Une OverflowError est levée si datetime2.year devait être inférieure à MINYEAR ou supérieure à MAXYEAR. Notez qu’aucun ajustement de fuseau horaire n’est réalisé même si l’entrée est avisée.

Computes the datetime2 such that datetime2 + timedelta == datetime1. As for addition, the result has the same tzinfo attribute as the input datetime, and no time zone adjustments are done even if the input is aware.

La soustraction d’un datetime à un autre datetime n’est définie que si les deux opérandes sont naïfs, ou s’ils sont les deux avisés. Si l’un est avisé et que l’autre est naïf, une TypeError est levée.

Si les deux sont naïfs, ou que les deux sont avisés et ont le même attribut tzinfo, les attributs tzinfo sont ignorés, et le résultat est un objet timedelta t tel que datetime2 + t == datetime1. Aucun ajustement de fuseau horaire n’a lieu dans ce cas.

Si les deux sont avisés mais ont des attributs tzinfo différents, a-b agit comme si a et b étaient premièrement convertis vers des datetimes UTC naïfs. Le résultat est (a.replace(tzinfo=None) - a.utcoffset()) - (b.replace(tzinfo=None) - b.utcoffset()) à l’exception que l’implémentation ne produit jamais de débordement.

datetime1 est considéré inférieur à datetime2 quand il le précède dans le temps.

Si un opérande est naïf et l’autre avisé, une TypeError est levée si une comparaison d’ordre est attendue. Pour les comparaisons d’égalité, les instances naïves ne sont jamais égales aux instances avisées.

Si les deux opérandes sont avisés, et ont le même attribut tzinfo, l’attribut commun tzinfo est ignoré et les datetimes de base sont comparés. Si les deux opérandes sont avisés et ont des attributs tzinfo différents, les opérandes sont premièrement ajustés en soustrayant leurs décalages UTC (obtenus depuis self.utcoffset()).

Modifié dans la version 3.3: Les comparaisons d’égalité entre des instances datetime naïves et avisées ne lèvent pas de TypeError.

Note

Afin d’empêcher la comparaison de retomber sur le schéma par défaut de comparaison des adresses des objets, la comparaison datetime lève normalement une TypeError si l’autre opérande n’est pas aussi un objet datetime. Cependant, NotImplemented est renvoyé à la place si l’autre opérande a un attribut timetuple(). Cela permet à d’autres types d’objets dates d’implémenter la comparaison entre types mixtes. Sinon, quand un objet datetime est comparé à un objet d’un type différent, une TypeError est levée à moins que la comparaison soit == ou !=. Ces derniers cas renvoient respectivement False et True.

Les objets datetime peuvent être utilisés comme clés de dictionnaires. Dans les contextes booléens, tous les objets datetime sont considérés vrais.

Méthodes de l’instance :

datetime.date()

Renvoie un objet date avec les mêmes année, mois et jour.

datetime.time()

Renvoie un objet time avec les mêmes heure, minute, seconde, microseconde et fold. tzinfo est None. Voir aussi la méthode timetz().

Modifié dans la version 3.6: La valeur fold est copiée vers l’objet time renvoyé.

datetime.timetz()

Renvoie un objet time avec les mêmes attributs heure, minute, seconde, microseconde, fold et tzinfo. Voir aussi la méthode time().

Modifié dans la version 3.6: La valeur fold est copiée vers l’objet time renvoyé.

datetime.replace(year=self.year, month=self.month, day=self.day, hour=self.hour, minute=self.minute, second=self.second, microsecond=self.microsecond, tzinfo=self.tzinfo, * fold=0)

Renvoie un datetime avec les mêmes attributs, exceptés ceux dont de nouvelles valeurs sont données par les arguments nommés correspondant. Notez que tzinfo=None peut être spécifié pour créer un datetime naïf depuis un datetime avisé sans conversion de la date ou de l’heure.

Nouveau dans la version 3.6: Ajout de l’argument fold.

datetime.astimezone(tz=None)

Renvoie un objet datetime avec un nouvel attribut tzinfo valant tz, ajustant la date et l’heure pour que le résultat soit le même temps UTC que self, mais dans le temps local au fuseau tz.

Si fourni, tz doit être une instance d’une sous-classe tzinfo, et ses méthodes utcoffset() et dst() ne doivent pas renvoyer None. Si self est naïf, Python considère que le temps est exprimé dans le fuseau horaire du système.

Si appelé sans arguments (ou si tz=None) le fuseau horaire local du système est utilisé comme fuseau horaire cible. L’attribut .tzinfo de l’instance datetime convertie aura pour valeur une instance de timezone avec le nom de fuseau et le décalage obtenus depuis l’OS.

Si self.tzinfo est tz, self.astimezone(tz) est égal à self : aucun ajustement de date ou d’heure n’est réalisé. Sinon le résultat est le temps local dans le fuseau tz représentant le même temps UTC que self : après astz = dt.astimezone(tz), astz - astz.utcoffset() aura les mêmes données de date et d’heure que dt - dt.utcoffset().

Si vous voulez seulement associer un fuseau horaire tz à un datetime dt sans ajustement des données de date et d’heure, utilisez dt.replace(tzinfo=tz). Si vous voulez seulement supprimer le fuseau horaire d’un datetime dt avisé sans conversion des données de date et d’heure, utilisez dt.replace(tzinfo=None).

Notez que la méthode par défaut tzinfo.fromutc() peut être redéfinie dans une sous-classe tzinfo pour affecter le résultat renvoyé par astimezone(). En ignorant les cas d’erreurs, astimezone() se comporte comme :

def astimezone(self, tz):
    if self.tzinfo is tz:
        return self
    # Convert self to UTC, and attach the new time zone object.
    utc = (self - self.utcoffset()).replace(tzinfo=tz)
    # Convert from UTC to tz's local time.
    return tz.fromutc(utc)

Modifié dans la version 3.3: tz peut maintenant être omis.

Modifié dans la version 3.6: La méthode astimezone() peut maintenant être appelée sur des instances naïves qui sont supposées représenter un temps local au système.

datetime.utcoffset()

Si tzinfo est None, renvoie None, sinon renvoie self.tzinfo.utcoffset(self), et lève une exception si l’expression précédente ne renvoie pas None ou un objet timedelta représentant un nombre entier de minutes de magnitude inférieure à un jour.

datetime.dst()

Si tzinfo est None, renvoie None, sinon renvoie self.tzinfo.dst(self), et lève une exception si l’expression précédente ne renvoie pas None ou un objet timedelta représentant un nombre entier de minutes de magnitude inférieure à un jour.

datetime.tzname()

Si tzinfo est None, renvoie None, sinon renvoie self.tzinfo.tzname(self), lève une exception si l’expression précédente ne renvoie pas None ou une chaîne de caractères,

datetime.timetuple()

Renvoie un time.struct_time comme renvoyé par time.localtime(). d.timetuple() est équivalent à time.struct_time((d.year, d.month, d.day, d.hour, d.minute, d.second, d.weekday(), yday, dst)), où yday = d.toordinal() - date(d.year, 1, 1).toordinal() + 1 est le numéro de jour dans l’année courante commençant avec 1 pour le 1er janvier. L’option tm_isdist du résultat est attribuée selon la méthode dst() : si tzinfo est None ou que dst() renvoie None, tm_isdst est mise à -1 ; sinon, si dst() renvoie une valeur non-nulle, tm_isdst est mise à 1 ; sinon tm_isdst est mise à 0.

datetime.utctimetuple()

Si l’instance de datetime d est naïve, cela est équivalent à d.timetuple(), excepté que tm_isdst est forcé à 0 sans tenir compte de ce que renvoie d.dst(). L’heure d’été n’est jamais effective pour un temps UTC.

Si d est avisé, il est normalisé vers un temps UTC, en lui soustrayant d.utcoffset(), et un time.struct_time est renvoyé pour le temps normalisé. tm_isdst est forcé à 0. Notez qu’une OverflowError peut être levée si d.year vaut MINYEAR``ou ``MAXYEAR et que l’ajustement UTC fait dépasser les bornes.

datetime.toordinal()

Renvoie l’ordinal du calendrier géorgien proleptique de cette date. Identique à self.date().toordinal().

datetime.timestamp()

Renvoie l’horodatage (timestamp en anglais) POSIX correspondant à l’instance datetime. La valeur renvoyée est un float similaire à ceux renvoyés par time.time().

Les instances naïves de datetime sont supposées représenter un temps local et cette méthode se base sur la fonction C mktime() de la plateforme pour opérer la conversion. Comme datetime gère un intervalle de valeurs plus large que mktime() sur beaucoup de plateformes, cette méthode peut lever une OverflowError pour les temps trop éloignés dans le passé ou le futur.

Pour les instances datetime avisées, la valeur renvoyée est calculée comme suit :

(dt - datetime(1970, 1, 1, tzinfo=timezone.utc)).total_seconds()

Nouveau dans la version 3.3.

Modifié dans la version 3.6: La méthode timestamp() utilise l’attribut fold pour désambiguïser le temps dans un intervalle répété.

Note

Il n’y a pas de méthode pour obtenir l’horodatage (timestamp en anglais) POSIX directement depuis une instance datetime naïve représentant un temps UTC. Si votre application utilise cette convention et que le fuseau horaire de votre système est UTC, vous pouvez obtenir l’horodatage POSIX en fournissant tzinfo=timezone.utc :

timestamp = dt.replace(tzinfo=timezone.utc).timestamp()

ou en calculant l’horodatage (timestamp en anglais) directement :

timestamp = (dt - datetime(1970, 1, 1)) / timedelta(seconds=1)

datetime.weekday()

Renvoie le jour de la semaine sous forme de nombre, où lundi vaut 0 et dimanche vaut 6. Identique à self.date().weekday(). Voir aussi isoweekday().

datetime.isoweekday()

Renvoie le jour de la semaine sous forme de nombre, où lundi vaut 1 et dimanche vaut 7. Identique à self.date().isoweekday(). Voir aussi weekday(), isocalendar().

datetime.isocalendar()

Renvoie un tuple de 3 éléments, (année ISO, numéro de semaine ISO, jour de la semaine ISO). Identique à self.date().isocalendar().

datetime.isoformat(sep='T', timespec='auto')

Renvoie une chaîne représentant la date et l’heure au format ISO 8601, YYYY-MM-DDTHH:MM:SS.mmmmmm ou, si microsecond vaut 0, YYYY-MM-DDTHH:MM:SS

Si utcoffset() ne renvoie pas None, une chaîne de 6 caractères est ajoutée, donnant le décalage UTC en heures et minutes (relatives) : YYYY-MM-DDTHH:MM:SS.mmmmmm+HH:MM ou, si microsecond vaut 0, YYYY-MM-DDTHH:MM:SS+HH:MM

L’argument optionnel sep (valant par défaut 'T') est un séparateur d’un caractère, placé entre les portions du résultat correspondant à la date et à l’heure. Par exemple,

>>> from datetime import tzinfo, timedelta, datetime
>>> class TZ(tzinfo):
...     def utcoffset(self, dt): return timedelta(minutes=-399)
...
>>> datetime(2002, 12, 25, tzinfo=TZ()).isoformat(' ')
'2002-12-25 00:00:00-06:39'

L’argument optionnel timespec spécifie le nombre de composants additionnels de temps à inclure (par défaut 'auto'). Il peut valoir l’une des valeurs suivantes :

'auto' : Identique à 'seconds' si microsecond vaut 0, à 'microseconds' sinon.

'hours' : Inclut hour au format à deux chiffres HH.

'minutes' : Inclut hour et minute au format HH:MM.

'seconds' : Inclut hour, minute et second au format HH:MM:SS.

'milliseconds' : Inclut le temps complet, mais tronque la partie fractionnaire des millisecondes, au format HH:MM:SS.sss.

'microseconds' : Inclut le temps complet, au format HH:MM:SS.mmmmmm.

Note

Les composants de temps exclus sont tronqués et non arrondis.

Une ValueError sera levée en cas d’argument timespec invalide.

>>> from datetime import datetime
>>> datetime.now().isoformat(timespec='minutes')
'2002-12-25T00:00'
>>> dt = datetime(2015, 1, 1, 12, 30, 59, 0)
>>> dt.isoformat(timespec='microseconds')
'2015-01-01T12:30:59.000000'

Nouveau dans la version 3.6: Ajout de l’argument timespec.

datetime.__str__()

Pour une instance d de datetime, str(d) est équivalent à d.isoformat(' ').

datetime.ctime()

Renvoie une chaîne représentant la date et l’heure, par exemple datetime(2002, 12, 4, 20, 30, 40).ctime() == 'Wed Dec  4 20:30:40 2002'. d.ctime() est équivalent à time.ctime(time.mktime(d.timetuple())) sur les plateformes où la fonction C native ctime() (invoquée par time.ctime() mais pas par datetime.ctime()) est conforme au standard C.

datetime.strftime(format)

Renvoie une chaîne représentant la date et l’heure, contrôlée par une chaîne de format explicite. Pour une liste complète des directives de formatage, voir Comportement de strftime() et strptime().

datetime.__format__(format)

Identique à datetime.strftime(). Cela permet de spécifier une chaîne de format pour un objet datetime dans une chaîne de formatage littérale et en utilisant str.format(). Pour une liste complète des directives de formatage, voir Comportement de strftime() et strptime().

Exemples d’utilisation des objets datetime :

>>> from datetime import datetime, date, time
>>> # Using datetime.combine()
>>> d = date(2005, 7, 14)
>>> t = time(12, 30)
>>> datetime.combine(d, t)
datetime.datetime(2005, 7, 14, 12, 30)
>>> # Using datetime.now() or datetime.utcnow()
>>> datetime.now()
datetime.datetime(2007, 12, 6, 16, 29, 43, 79043)   # GMT +1
>>> datetime.utcnow()
datetime.datetime(2007, 12, 6, 15, 29, 43, 79060)
>>> # Using datetime.strptime()
>>> dt = datetime.strptime("21/11/06 16:30", "%d/%m/%y %H:%M")
>>> dt
datetime.datetime(2006, 11, 21, 16, 30)
>>> # Using datetime.timetuple() to get tuple of all attributes
>>> tt = dt.timetuple()
>>> for it in tt:
...     print(it)
...
2006    # year
11      # month
21      # day
16      # hour
30      # minute
0       # second
1       # weekday (0 = Monday)
325     # number of days since 1st January
-1      # dst - method tzinfo.dst() returned None
>>> # Date in ISO format
>>> ic = dt.isocalendar()
>>> for it in ic:
...     print(it)
...
2006    # ISO year
47      # ISO week
2       # ISO weekday
>>> # Formatting datetime
>>> dt.strftime("%A, %d. %B %Y %I:%M%p")
'Tuesday, 21. November 2006 04:30PM'
>>> 'The {1} is {0:%d}, the {2} is {0:%B}, the {3} is {0:%I:%M%p}.'.format(dt, "day", "month", "time")
'The day is 21, the month is November, the time is 04:30PM.'

Utilisation de datetime avec tzinfo :

>>> from datetime import timedelta, datetime, tzinfo
>>> class GMT1(tzinfo):
...     def utcoffset(self, dt):
...         return timedelta(hours=1) + self.dst(dt)
...     def dst(self, dt):
...         # DST starts last Sunday in March
...         d = datetime(dt.year, 4, 1)   # ends last Sunday in October
...         self.dston = d - timedelta(days=d.weekday() + 1)
...         d = datetime(dt.year, 11, 1)
...         self.dstoff = d - timedelta(days=d.weekday() + 1)
...         if self.dston <=  dt.replace(tzinfo=None) < self.dstoff:
...             return timedelta(hours=1)
...         else:
...             return timedelta(0)
...     def tzname(self,dt):
...          return "GMT +1"
...
>>> class GMT2(tzinfo):
...     def utcoffset(self, dt):
...         return timedelta(hours=2) + self.dst(dt)
...     def dst(self, dt):
...         d = datetime(dt.year, 4, 1)
...         self.dston = d - timedelta(days=d.weekday() + 1)
...         d = datetime(dt.year, 11, 1)
...         self.dstoff = d - timedelta(days=d.weekday() + 1)
...         if self.dston <=  dt.replace(tzinfo=None) < self.dstoff:
...             return timedelta(hours=1)
...         else:
...             return timedelta(0)
...     def tzname(self,dt):
...         return "GMT +2"
...
>>> gmt1 = GMT1()
>>> # Daylight Saving Time
>>> dt1 = datetime(2006, 11, 21, 16, 30, tzinfo=gmt1)
>>> dt1.dst()
datetime.timedelta(0)
>>> dt1.utcoffset()
datetime.timedelta(0, 3600)
>>> dt2 = datetime(2006, 6, 14, 13, 0, tzinfo=gmt1)
>>> dt2.dst()
datetime.timedelta(0, 3600)
>>> dt2.utcoffset()
datetime.timedelta(0, 7200)
>>> # Convert datetime to another time zone
>>> dt3 = dt2.astimezone(GMT2())
>>> dt3
datetime.datetime(2006, 6, 14, 14, 0, tzinfo=<GMT2 object at 0x...>)
>>> dt2
datetime.datetime(2006, 6, 14, 13, 0, tzinfo=<GMT1 object at 0x...>)
>>> dt2.utctimetuple() == dt3.utctimetuple()
True

8.1.5. Objets time

Un objet time représente une heure (locale) du jour, indépendante de tout jour particulier, et sujette à des ajustements par un objet tzinfo.

class datetime.time(hour=0, minute=0, second=0, microsecond=0, tzinfo=None, *, fold=0)

Tous les arguments sont optionnels. tzinfo peut être None ou une instance d’une sous-classe tzinfo. Les autres arguments doivent être des nombres entiers, dans les intervalles suivants :

0 <= hour < 24,

0 <= minute < 60,

0 <= second < 60,

0 <= microsecond < 1000000,

fold in [0, 1].

Si un argument est fourni en dehors de ces bornes, une ValueError est levée. Ils valent tous 0 par défaut, à l’exception de tzinfo qui vaut None.

Attributs de la classe :

time.min

Le plus petit objet time représentable, time(0, 0, 0, 0).

time.max

Le plus grand objet time représentable, time(23, 59, 59, 999999).

time.resolution

La plus petite différence possible entre deux objets time non-égaux, timedelta(microseconds=1), notez cependant que les objets time n’implémentent pas d’opérations arithmétiques.

Attributs de l’instance (en lecture seule) :

time.hour

Dans range(24).

time.minute

Dans range(60).

time.second

Dans range(60).

time.microsecond

Dans range(1000000).

time.tzinfo

L’objet passé comme argument tzinfo au constructeur de time, ou None si aucune valeur n’a été passée.

time.fold

0 ou 1. Utilisé pour désambiguïser les heures dans un intervalle répété. (Un intervalle répété apparaît quand l’horloge est retardée à la fin de l’heure d’été ou quand le décalage UTC du fuseau courant et décrémenté pour des raisons politiques.) La valeur 0 (1) représente le plus ancien (récent) des deux moments représentés par la même heure.

Nouveau dans la version 3.6.

Opérations gérées :

comparaison d’un time avec un autre time, où a est considéré inférieur à b s’il le précède dans le temps. Si un opérande est naïf et l’autre avisé, et qu’une relation d’ordre est attendue, une TypeError est levée. Pour les égalités, les instances naïves ne sont jamais égales aux instances avisées.

Si les deux opérandes sont avisés, et ont le même attribut tzinfo, l’attribut commun tzinfo est ignoré et les temps de base sont comparés. Si les deux opérandes sont avisés et ont des attributs tzinfo différents, ils sont d’abord ajustés en leur soustrayant leurs décalages UTC (obtenus à l’aide de self.utcoffset()). Afin d’empêcher les comparaisons de types mixtes de retomber sur la comparaison par défaut par l’adresse de l’objet, quand un objet time est comparé à un objet de type différent, une TypeError est levée à moins que la comparaison soit == ou !=. Ces derniers cas renvoient respectivement False et True.

Modifié dans la version 3.3: Les comparaisons d’égalité entre instances de time naïves et avisées ne lèvent pas de TypeError.

hachage, utilisation comme clef de dictionnaire

sérialisation (pickling) efficace

Dans un contexte booléen, un objet time est toujours considéré comme vrai.

Modifié dans la version 3.5: Avant Python 3.5, un objet time était considéré comme faux s’il représentait minuit en UTC. Ce comportement était considéré comme obscur et propice aux erreurs, il a été supprimé en Python 3.5. Voir bpo-13936 [https://bugs.python.org/issue13936] pour les détails complets.

Méthodes de l’instance :

time.replace(hour=self.hour, minute=self.minute, second=self.second, microsecond=self.microsecond, tzinfo=self.tzinfo, * fold=0)

Renvoie un objet time avec la même valeur, à l’exception des attributs dont une nouvelle valeur est spécifiée par les arguments nommés. Notez que tzinfo=None peut être spécifié pour créer une instance time naïve à partir d’une instance time avisée, sans conversion des données de temps.

Nouveau dans la version 3.6: Ajout de l’argument fold.

time.isoformat(timespec='auto')

Renvoie une chaîne représentant l’heure au format ISO 8601, HH:MM:SS.mmmmmm ou, si microsecond vaut 0, HH:MM:SS Si utcoffset() ne renvoie pas None, une chaîne de 6 caractères est ajoutée, donnant le décalage UTC en heures et minutes (relatives) : HH:MM:SS.mmmmmm+HH:MM ou, si self.microsecond vaut 0, HH:MM:SS+HH:MM

L’argument optionnel timespec spécifie le nombre de composants additionnels de temps à inclure (par défaut 'auto'). Il peut valoir l’une des valeurs suivantes :

'auto' : Identique à 'seconds' si microsecond vaut 0, à 'microseconds' sinon.

'hours' : Inclut hour au format à deux chiffres HH.

'minutes' : Inclut hour et minute au format HH:MM.

'seconds' : Inclut hour, minute et second au format HH:MM:SS.

'milliseconds' : Inclut le temps complet, mais tronque la partie fractionnaire des millisecondes, au format HH:MM:SS.sss.

'microseconds' : Inclut le temps complet, au format HH:MM:SS.mmmmmm.

Note

Les composants de temps exclus sont tronqués et non arrondis.

Une ValueError sera levée en cas d’argument timespec invalide.

>>> from datetime import time
>>> time(hour=12, minute=34, second=56, microsecond=123456).isoformat(timespec='minutes')
'12:34'
>>> dt = time(hour=12, minute=34, second=56, microsecond=0)
>>> dt.isoformat(timespec='microseconds')
'12:34:56.000000'
>>> dt.isoformat(timespec='auto')
'12:34:56'

Nouveau dans la version 3.6: Ajout de l’argument timespec.

time.__str__()

Pour un temps t, str(t) est équivalent à t.isoformat().

time.strftime(format)

Renvoie une chaîne de caractères représentant la date, contrôlée par une chaîne de formatage explicite. Pour une liste complète des directives de formatage, voir Comportement de strftime() et strptime().

time.__format__(format)

Identique à time.strftime(). Cela permet de spécifier une chaîne de formatage pour un objet time dans une chaîne de formatage littérale et à l’utilisation de str.format(). Pour une liste complète des directives de formatage, voir Comportement de strftime() et strptime().

time.utcoffset()

Si tzinfo est None, renvoie None, sinon renvoie self.tzinfo.utcoffset(None), et lève une exception si l’expression précédente ne renvoie pas None ou un objet timedelta représentant un nombre entier de minutes de magnitude inférieure à un jour.

time.dst()

Si tzinfo est None, renvoie None, sinon renvoie self.tzinfo.dst(None), et lève une exception si l’expression précédente ne renvoie pas None ou un objet timedelta représentant un nombre entier de minutes de magnitude inférieure à un jour.

time.tzname()

Si tzinfo est None, renvoie None, sinon renvoie self.tzinfo.tzname(None), et lève une exception si l’expression précédente ne renvoie pas None ou une chaîne de caractères.

Exemple :

>>> from datetime import time, tzinfo, timedelta
>>> class GMT1(tzinfo):
...     def utcoffset(self, dt):
...         return timedelta(hours=1)
...     def dst(self, dt):
...         return timedelta(0)
...     def tzname(self,dt):
...         return "Europe/Prague"
...
>>> t = time(12, 10, 30, tzinfo=GMT1())
>>> t
datetime.time(12, 10, 30, tzinfo=<GMT1 object at 0x...>)
>>> gmt = GMT1()
>>> t.isoformat()
'12:10:30+01:00'
>>> t.dst()
datetime.timedelta(0)
>>> t.tzname()
'Europe/Prague'
>>> t.strftime("%H:%M:%S %Z")
'12:10:30 Europe/Prague'
>>> 'The {} is {:%H:%M}.'.format("time", t)
'The time is 12:10.'

8.1.6. Objets tzinfo

class datetime.tzinfo

Cette classe est une classe abstraite, signifiant qu’elle ne doit pas être instanciée directement. Vous devez en dériver une sous-classe concrète, et (au minimum) fournir des implémentations aux méthodes standard tzinfo requises par les méthodes de datetime que vous utilisez. Le module datetime fournit une simple sous-classe concrète de tzinfo, timezone, qui peut peut représenter des fuseaux horaires avec des décalages fixes par rapport à UTC, tels qu’UTC lui-même ou les nord-américains EST et EDT.

Une instance (d’une sous-classe concrète) de tzinfo peut être passée aux constructeurs des objets datetime et time. Les objets en question voient leurs attributs comme étant en temps local, et l’objet tzinfo contient des méthodes pour obtenir le décalage du temps local par rapport à UTC, le nom du fuseau horaire, le décalage d’heure d’été, tous relatifs à un objet de date ou d’heure qui leur est passé.

Prérequis spécifique au picklng : Une sous-classe tzinfo doit avoir une méthode __init__() qui peut être appelée sans arguments, sans quoi un objet sérialisé ne pourrait pas toujours être désérialisé. C’est un prérequis technique qui pourrait être assoupli dans le futur.

Une sous-classe concrète de tzinfo peut devoir implémenter les méthodes suivantes. Les méthodes réellement nécessaires dépendent de l’utilisation qui est faite des objets datetime avisés. Dans le doute, implémentez-les toutes.

tzinfo.utcoffset(dt)

Renvoie le décalage entre le temps local et UTC, en minutes vers l’est d’UTC. Si le temps local se situe à l’ouest d’UTC, le décalage devrait être négatif. Notez que cela est prévu pour être le décalage total par rapport à UTC ; par exemple, si un objet tzinfo représente à la fois un fuseau horaire et son ajustement à l’heure d’été, utcoffset() devrait renvoyer leur somme. Si le décalage UTC n’est pas connu, renvoie None. Sinon, la valeur renvoyée doit être un objet timedelta spécifiant un nombre entier de minutes dans l’intervalle de -1439 à 1439 inclus (1440 = 24*60 ; la magnitude du décalage doit être inférieure à un jour). La plupart des implémentations de utcoffset() ressembleront probablement à l’une des deux suivantes :

return CONSTANT                 # fixed-offset class
return CONSTANT + self.dst(dt)  # daylight-aware class

Si utcoffset() ne renvoie pas None, dst() ne doit pas non plus renvoyer None.

L’implémentation par défaut de utcoffset() lève une NotImplementedError.

tzinfo.dst(dt)

Renvoie l’ajustement d’heure d’été (DST, daylight saving time), en minutes vers l’est d’UTC, ou None si l’information n’est pas connue. Renvoie timedelta(0) si l’heure d’été n’est pas effective. Si elle est effective, renvoie un décalage sous forme d’un objet timedelta (voir utcoffset() pour les détails). Notez que ce décalage, si applicable, est déjà compris dans le décalage UTC renvoyé par utcoffset(), il n’est donc pas nécessaire de faire appel à dst() à moins que vous ne souhaitiez obtenir les informations séparément. Par exemple, datetime.timetuple() appelle la méthode dst() de son attribut tzinfo pour déterminer si l’option tm_isdst doit être activée, et tzinfo.fromutc() fait appel à dst() pour tenir compte des heures d’été quand elle traverse des fuseaux horaires.

Une instance tz d’une sous-classe tzinfo convenant à la fois pour une heure standard et une heure d’été doit être cohérente :

tz.utcoffset(dt) - tz.dst(dt)

doit renvoyer le même résultat pour tout objet datetime dt avec dt.tzinfo == tz Pour les sous-classes saines de tzinfo, cette expression calcule le « décalage standard » du fuseau horaire, qui ne doit pas dépendre de la date ou de l’heure, mais seulement de la position géographique. L’implémentation de datetime.astimezone() se base là-dessus, mais ne peut pas détecter les violations ; il est de la responsabilité du programmeur de l’assurer. Si une sous-classe tzinfo ne le garantit pas, il doit être possible de redéfinir l’implémentation par défaut de tzinfo.fromutc() pour tout de même fonctionner correctement avec astimezone().

La plupart des implémentations de dst() ressembleront probablement à l’une des deux suivantes :

def dst(self, dt):
    # a fixed-offset class:  doesn't account for DST
    return timedelta(0)

ou :

def dst(self, dt):
    # Code to set dston and dstoff to the time zone's DST
    # transition times based on the input dt.year, and expressed
    # in standard local time.  Then

    if dston <= dt.replace(tzinfo=None) < dstoff:
        return timedelta(hours=1)
    else:
        return timedelta(0)

L’implémentation par défaut de dst() lève une NotImplementedError.

tzinfo.tzname(dt)

Renvoie le nom du fuseau horaire correspondant à l’objet datetime dt, sous forme d’une chaîne de caractères. rien n’est défini sur les noms par le module datetime, et il n’est pas nécessaire que ces noms signifient quelque chose en particulier. Par exemple, « GMT », « UTC », « -500 », « -5:00 », « EDT », « US/Eastern » et « America/New York » sont toutes des valeurs de retour valides. Renvoie None si un nom est inconnu. Notez qu’il s’agit d’une méthode et non d’une chaîne fixée en amont, parce que les sous-classes de tzinfo peuvent souhaiter renvoyer des noms différents en fonction de valeurs de dt spécifiques, en particulier si la classe tzinfo tient compte de l’heure d’été.

L’implémentation par défaut de tzname() lève une NotImplementedError.

Ces méthodes sont appelées par les objets datetime et time, en réponse à leurs méthodes aux mêmes noms. Un objet datetime se passe lui-même en tant qu’argument, et un objet time passe None. Les méthodes des sous-classes tzinfo doivent alors être prêtes à recevoir un argument None pour dt, ou une instance de datetime.

Quand None est passé, il est de la responsabilité du designer de la classe de choisir la meilleure réponse. Par exemple, renvoyer None est approprié si la classe souhaite signaler que les objets de temps ne participent pas au protocole tzinfo. Il peut être plus utile pour utcoffset(None) de renvoyer le décalage UTC standard, comme il n’existe aucune autre convention pour obtenir ce décalage.

Quand un objet datetime est passé en réponse à une méthode de datetime, dt.tzinfo est le même objet que self. Les méthodes de tzinfo peuvent se baser là-dessus, à moins que le code utilisateur appelle directement des méthodes de tzinfo. L’intention est que les méthodes de tzinfo interprètent dt comme étant le temps local, et n’aient pas à se soucier des objets dans d’autres fuseaux horaires.

Il y a une dernière méthode de tzinfo que les sous-classes peuvent vouloir redéfinir :

tzinfo.fromutc(dt)

Elle est appelée par l’implémentation par défaut de datetime.astimezone(). Quand appelée depuis cette méthode, dt.tzinfo est self, et les données de date et d’heure de dt sont vues comme exprimant un temps UTC. Le rôle de fromutc() est d’ajuster les données de date et d’heure, renvoyant un objet datetime équivalent à self, dans le temps local.

La plupart des sous-classes tzinfo doivent être en mesure d’hériter sans problème de l’implémentation par défaut de fromutc(). Elle est suffisamment robuste pour gérer les fuseaux horaires à décalage fixe, et les fuseaux représentant à la fois des heures standards et d’été, et ce même si le décalage de l’heure d’été est différent suivant les années. Un exemple de fuseau horaire qui ne serait pas géré correctement dans tous les cas par l’implémentation par défaut de fromutc() en est un où le décalage standard (par rapport à UTC) dépend de valeurs spécifiques de date et d’heure passées, ce qui peut arriver pour des raisons politiques. Les implémentations par défaut de astimezone() et fromutc() peuvent ne pas produire les résultats attendus si le résultat est l’une des heures affectées par le changement d’heure.

En omettant le code des cas d’erreurs, l’implémentation par défaut de fromutc() se comporte comme suit :

def fromutc(self, dt):
    # raise ValueError error if dt.tzinfo is not self
    dtoff = dt.utcoffset()
    dtdst = dt.dst()
    # raise ValueError if dtoff is None or dtdst is None
    delta = dtoff - dtdst  # this is self's standard offset
    if delta:
        dt += delta   # convert to standard local time
        dtdst = dt.dst()
        # raise ValueError if dtdst is None
    if dtdst:
        return dt + dtdst
    else:
        return dt

Exemple de classes tzinfo :

from datetime import tzinfo, timedelta, datetime, timezone

ZERO = timedelta(0)
HOUR = timedelta(hours=1)
SECOND = timedelta(seconds=1)

# A class capturing the platform's idea of local time.
# (May result in wrong values on historical times in
#  timezones where UTC offset and/or the DST rules had
#  changed in the past.)
import time as _time

STDOFFSET = timedelta(seconds = -_time.timezone)
if _time.daylight:
    DSTOFFSET = timedelta(seconds = -_time.altzone)
else:
    DSTOFFSET = STDOFFSET

DSTDIFF = DSTOFFSET - STDOFFSET

class LocalTimezone(tzinfo):

    def fromutc(self, dt):
        assert dt.tzinfo is self
        stamp = (dt - datetime(1970, 1, 1, tzinfo=self)) // SECOND
        args = _time.localtime(stamp)[:6]
        dst_diff = DSTDIFF // SECOND
        # Detect fold
        fold = (args == _time.localtime(stamp - dst_diff))
        return datetime(*args, microsecond=dt.microsecond,
                        tzinfo=self, fold=fold)

    def utcoffset(self, dt):
        if self._isdst(dt):
            return DSTOFFSET
        else:
            return STDOFFSET

    def dst(self, dt):
        if self._isdst(dt):
            return DSTDIFF
        else:
            return ZERO

    def tzname(self, dt):
        return _time.tzname[self._isdst(dt)]

    def _isdst(self, dt):
        tt = (dt.year, dt.month, dt.day,
              dt.hour, dt.minute, dt.second,
              dt.weekday(), 0, 0)
        stamp = _time.mktime(tt)
        tt = _time.localtime(stamp)
        return tt.tm_isdst > 0

Local = LocalTimezone()

# A complete implementation of current DST rules for major US time zones.

def first_sunday_on_or_after(dt):
    days_to_go = 6 - dt.weekday()
    if days_to_go:
        dt += timedelta(days_to_go)
    return dt

# US DST Rules
#
# This is a simplified (i.e., wrong for a few cases) set of rules for US
# DST start and end times. For a complete and up-to-date set of DST rules
# and timezone definitions, visit the Olson Database (or try pytz):
# http://www.twinsun.com/tz/tz-link.htm
# http://sourceforge.net/projects/pytz/ (might not be up-to-date)
#
# In the US, since 2007, DST starts at 2am (standard time) on the second
# Sunday in March, which is the first Sunday on or after Mar 8.
DSTSTART_2007 = datetime(1, 3, 8, 2)
# and ends at 2am (DST time) on the first Sunday of Nov.
DSTEND_2007 = datetime(1, 11, 1, 2)
# From 1987 to 2006, DST used to start at 2am (standard time) on the first
# Sunday in April and to end at 2am (DST time) on the last
# Sunday of October, which is the first Sunday on or after Oct 25.
DSTSTART_1987_2006 = datetime(1, 4, 1, 2)
DSTEND_1987_2006 = datetime(1, 10, 25, 2)
# From 1967 to 1986, DST used to start at 2am (standard time) on the last
# Sunday in April (the one on or after April 24) and to end at 2am (DST time)
# on the last Sunday of October, which is the first Sunday
# on or after Oct 25.
DSTSTART_1967_1986 = datetime(1, 4, 24, 2)
DSTEND_1967_1986 = DSTEND_1987_2006

def us_dst_range(year):
    # Find start and end times for US DST. For years before 1967, return
    # start = end for no DST.
    if 2006 < year:
        dststart, dstend = DSTSTART_2007, DSTEND_2007
    elif 1986 < year < 2007:
        dststart, dstend = DSTSTART_1987_2006, DSTEND_1987_2006
    elif 1966 < year < 1987:
        dststart, dstend = DSTSTART_1967_1986, DSTEND_1967_1986
    else:
        return (datetime(year, 1, 1), ) * 2

    start = first_sunday_on_or_after(dststart.replace(year=year))
    end = first_sunday_on_or_after(dstend.replace(year=year))
    return start, end

class USTimeZone(tzinfo):

    def __init__(self, hours, reprname, stdname, dstname):
        self.stdoffset = timedelta(hours=hours)
        self.reprname = reprname
        self.stdname = stdname
        self.dstname = dstname

    def __repr__(self):
        return self.reprname

    def tzname(self, dt):
        if self.dst(dt):
            return self.dstname
        else:
            return self.stdname

    def utcoffset(self, dt):
        return self.stdoffset + self.dst(dt)

    def dst(self, dt):
        if dt is None or dt.tzinfo is None:
            # An exception may be sensible here, in one or both cases.
            # It depends on how you want to treat them.  The default
            # fromutc() implementation (called by the default astimezone()
            # implementation) passes a datetime with dt.tzinfo is self.
            return ZERO
        assert dt.tzinfo is self
        start, end = us_dst_range(dt.year)
        # Can't compare naive to aware objects, so strip the timezone from
        # dt first.
        dt = dt.replace(tzinfo=None)
        if start + HOUR <= dt < end - HOUR:
            # DST is in effect.
            return HOUR
        if end - HOUR <= dt < end:
            # Fold (an ambiguous hour): use dt.fold to disambiguate.
            return ZERO if dt.fold else HOUR
        if start <= dt < start + HOUR:
            # Gap (a non-existent hour): reverse the fold rule.
            return HOUR if dt.fold else ZERO
        # DST is off.
        return ZERO

    def fromutc(self, dt):
        assert dt.tzinfo is self
        start, end = us_dst_range(dt.year)
        start = start.replace(tzinfo=self)
        end = end.replace(tzinfo=self)
        std_time = dt + self.stdoffset
        dst_time = std_time + HOUR
        if end <= dst_time < end + HOUR:
            # Repeated hour
            return std_time.replace(fold=1)
        if std_time < start or dst_time >= end:
            # Standard time
            return std_time
        if start <= std_time < end - HOUR:
            # Daylight saving time
            return dst_time

Eastern  = USTimeZone(-5, "Eastern",  "EST", "EDT")
Central  = USTimeZone(-6, "Central",  "CST", "CDT")
Mountain = USTimeZone(-7, "Mountain", "MST", "MDT")
Pacific  = USTimeZone(-8, "Pacific",  "PST", "PDT")

Notez que, deux fois par an, on rencontre des subtilités inévitables dans les sous-classes de tzinfo représentant à la fois des heures standard et d’été, au passage de l’une à l’autre. Concrètement, considérez le fuseau de l’est des États-Unis (UTC -0500), où EDT (heure d’été) débute à la minute qui suit 1:59 (EST) le second dimanche de mars, et se termine à la minute qui suit 1:59 (EDT) le premier dimanche de novembre :

  UTC   3:MM  4:MM  5:MM  6:MM  7:MM  8:MM
  EST  22:MM 23:MM  0:MM  1:MM  2:MM  3:MM
  EDT  23:MM  0:MM  1:MM  2:MM  3:MM  4:MM

start  22:MM 23:MM  0:MM  1:MM  3:MM  4:MM

  end  23:MM  0:MM  1:MM  1:MM  2:MM  3:MM

Quand l’heure d’été débute (la ligne « start »), l’horloge locale passe de 1:59 à 3:00. Une heure de la forme 2:MM n’a pas vraiment de sens ce jour là, donc astimezone(Eastern) ne délivrera pas de résultat avec hour == 2 pour le jour où débute l’heure d’été. Par exemple, lors de la transition du printemps 2016, nous obtenons

>>> u0 = datetime(2016, 3, 13, 5, tzinfo=timezone.utc)
>>> for i in range(4):
...     u = u0 + i*HOUR
...     t = u.astimezone(Eastern)
...     print(u.time(), 'UTC =', t.time(), t.tzname())
...
05:00:00 UTC = 00:00:00 EST
06:00:00 UTC = 01:00:00 EST
07:00:00 UTC = 03:00:00 EDT
08:00:00 UTC = 04:00:00 EDT

Quand l’heure d’été se termine (la ligne « end »), il y a potentiellement un problème pire que cela : il y a une heure qui ne peut pas être exprimée sans ambiguïté en temps local : la dernière heure de l’heure d’été. Dans l’est des États-Unis, l’heure d’été se termine sur les heures de la forme 5:MM UTC. L’horloge locale passe de 1:59 (heure d’été) à 1:00 (heure standard) à nouveau. Les heures locales de la forme 1:MM sont ambiguës. astimezone() imite le comportement des horloges locales en associant deux heures UTC adjacentes à la même heure locale. Dans notre exemple, les temps UTC de la forme 5:MM et 6:MM sont tous deux associés à 1:MM quand convertis vers ce fuseau, mais les heures les plus anciennes ont l’attribut fold à 0 et les plus récentes l’ont à 1. Par exemple, lors de la transition de l’automne 2016, nous obtenons

>>> u0 = datetime(2016, 11, 6, 4, tzinfo=timezone.utc)
>>> for i in range(4):
...     u = u0 + i*HOUR
...     t = u.astimezone(Eastern)
...     print(u.time(), 'UTC =', t.time(), t.tzname(), t.fold)
...
04:00:00 UTC = 00:00:00 EDT 0
05:00:00 UTC = 01:00:00 EDT 0
06:00:00 UTC = 01:00:00 EST 1
07:00:00 UTC = 02:00:00 EST 0

Notez que deux instances datetime qui ne diffèrent que par la valeur de leur attribut fold sont considérées égales dans les comparaisons.

Les applications qui ne peuvent pas gérer ces ambiguïtés doivent vérifier explicitement la valeur de l’attribut fold ou éviter d’utiliser des sous-classes tzinfo hybrides ; il n’y a aucune ambiguïté lors de l’utilisation de la classe timezone, ou toute autre sous-classe de tzinfo à décalage fixe (comme une classe représentant uniquement le fuseau EST (de décalage fixe -5h) ou uniquement EDT (-4h)).

Voir aussi

dateutil.tz [https://dateutil.readthedocs.io/en/stable/tz.html]

La bibliothèque standard contient la classe timezone pour gérer des décalages fixes par rapport à UTC et timezone.utc comme instance du fuseau horaire UTC.

La bibliothèque dateutils.tz apporte à Python la base de données de fuseaux horaires IANA (IANA timezone database, aussi appelée base de données Olson) , et son utilisation est recommandée.

Base de données des fuseaux horaires de l’IANA [https://www.iana.org/time-zones]

La Time Zone Database (souvent appelée tz, tzdata ou zoneinfo) contient les codes et les données représentant l’historique du temps local pour un grand nombre d’emplacements représentatifs autour du globe. Elle est mise à jour périodiquement, pour refléter les changements opérés par des politiques sur les bornes du fuseau, les décalages UTC, et les règles de passage à l’heure d’été.

8.1.7. Objets timezone

La classe timezone est une sous-classe de tzinfo, où chaque instance représente un fuseau horaire défini par un décalage fixe par rapport à UTC. Notez que les que les objets de cette classe ne peuvent pas être utilisés pour représenter les informations de fuseaux horaires dans des emplacements où plusieurs décalages sont utilisés au cours de l’année ou où des changements historiques ont été opérés sur le temps civil.

class datetime.timezone(offset, name=None)

L’argument offset doit être spécifié comme un objet timedelta représentant la différence entre le temps local et UTC. Il doit être strictement compris entre -timedelta(hours=24) et timedelta(hours=24) et représenter un nombre entier de minutes, autrement une ValueError est levée.

L’argument name est optionnel. Si spécifié, il doit être une chaîne de caractères qui sera utilisée comme valeur de retour de la méthode datetime.tzname().

Nouveau dans la version 3.2.

timezone.utcoffset(dt)

Renvoie la valeur fixe spécifiée à la création de l’instance de timezone. L’argument dt est ignoré. La valeur de retour est une instance timedelta égale à la différence entre le temps local et UTC.

timezone.tzname(dt)

Renvoie la valeur fixe spécifiée à la création de l’instance de timezone. Si name n’est pas fourni au constructeur, le nom renvoyé par tzname(dt) est généré comme suit à partir de la valeur de offset. Si offset vaut timedelta(0), le nom sera « UTC », autrement le nom sera une chaîne de la forme « UTC±HH:MM », où ± est le signe d”offset, et HH et MM sont respectivement les représentations à deux chiffres de offset.hours et offset.minutes.

Modifié dans la version 3.6: Le nom généré à partir de offset=timedelta(0) est maintenant « UTC » plutôt que « UTC+00:00 ».

timezone.dst(dt)

Renvoie toujours None.

timezone.fromutc(dt)

Renvoie dt + offset. L’argument dt doit être une instance avisée de datetime, avec tzinfo valant self.

Attributs de la classe :

timezone.utc

Le fuseau horaire UTC, timezone(timedelta(0)).

8.1.8. Comportement de strftime() et strptime()

Les objets date, datetime et time comportent tous une méthode strftime(format), pour créer une représentation du temps sous forme d’une chaîne de caractères, contrôlée par une chaîne de formatage explicite. Grossièrement, d.strftime(fmt) se comporte comme la fonction time.strftime(fmt, d.timetuple()) du module time, bien que tous les objets ne comportent pas de méthode timetuple().

Conversely, the datetime.strptime() class method creates a datetime object from a string representing a date and time and a corresponding format string. datetime.strptime(date_string, format) is equivalent to datetime(*(time.strptime(date_string, format)[0:6])), except when the format includes sub-second components or timezone offset information, which are supported in datetime.strptime but are discarded by time.strptime.

Pour les objets time, les codes de formatage pour l’année, le mois et le jour ne devraient pas être utilisés, puisque les objets de temps ne possèdent pas de telles valeurs. S’ils sont tout de même utilisés, 1900 est substitué à l’année, et 1 au mois et au jour.

Pour les objets date, les codes de formatage pour les heures, minutes, secondes et microsecondes ne devraient pas être utilisés, puisque les objets date ne possèdent pas de telles valeurs. S’ils sont tous de même utilisés, ils sont substitués par 0.

L’ensemble complet des codes de formatage implémentés varie selon les plateformes, parce que Python appelle la fonction strftime() de la bibliothèque C de la plateforme, et les variations sont courantes. Pour voir un ensemble complet des codes de formatage implémentés par votre plateforme, consultez la documentation de strftime(3).

La liste suivante est la liste de tous les codes de formatage requis par le standard C (version 1989), ils fonctionnent sur toutes les plateformes possédant une implémentation de C standard. Notez que la version 1999 du standard C a ajouté des codes de formatage additionnels.

Directive

Signification

Exemple

Notes

%a

Jour de la semaine abrégé dans la langue locale.

Sun, Mon, …, Sat (en_US);

Lu, Ma, …, Di (fr_FR)

(1)

%A

Jour de la semaine complet dans la langue locale.

Sunday, Monday, …, Saturday (en_US);

Lundi, Mardi, …, Dimanche (fr_FR)

(1)

%w

Jour de la semaine en chiffre, avec 0 pour le dimanche et 6 pour le samedi.

0, 1, …, 6

%d

Jour du mois sur deux chiffres.

01, 02, …, 31

%b

Nom du mois abrégé dans la langue locale.

Jan, Feb, …, Dec (en_US);

janv., févr., …, déc. (fr_FR)

(1)

%B

Nom complet du mois dans la langue locale.

January, February, …, December (en_US);

janvier, février, …, décembre (fr_FR)

(1)

%m

Numéro du mois sur deux chiffres.

01, 02, …, 12

%y

Année sur deux chiffres (sans le siècle).

00, 01, …, 99

%Y

Année complète sur quatre chiffres.

0001, 0002, …, 2013, 2014, …, 9998, 9999

(2)

%H

Heure à deux chiffres de 00 à 23.

00, 01, …, 23

%I

Heure à deux chiffres pour les horloges 12h (01 à 12).

01, 02, …, 12

%p

Équivalent local à AM/PM.

AM, PM (en_US);

am, pm (de_DE)

(1), (3)

%M

Minutes sur deux chiffres.

00, 01, …, 59

%S

Secondes sur deux chiffres.

00, 01, …, 59

(4)

%f

Microsecondes sur 6 chiffres.

000000, 000001, …, 999999

(5)

%z

Décalage UTC sous la forme +HHMM ou -HHMM (chaîne vide si l’instance est naïve).

(vide), +0000, -0400, +1030

(6)

%Z

Nom du fuseau horaire (chaîne vide si l’instance est naïve).

(vide), UTC, EST, CST

%j

Numéro du jour dans l’année sur trois chiffres.

001, 002, …, 366

%U

Numéro de la semaine à deux chiffres (où dimanche est considéré comme le premier jour de la semaine). Tous les jours de l’année précédent le premier dimanche sont considérés comme appartenant à la semaine 0.

00, 01, …, 53

(7)

%W

Numéro de la semaine à deux chiffres (où lundi est considéré comme le premier jour de la semaine). Tous les jours de l’année précédent le premier lundi sont considérés comme appartenant à la semaine 0.

00, 01, …, 53

(7)

%c

Représentation locale de la date et de l’heure.

Tue Aug 16 21:30:00 1988 (en_US);

mar. 16 août 1988 21:30:00 (fr_FR)

(1)

%x

Représentation locale de la date.

08/16/88 (None);

08/16/1988 (en_US);

16/08/1988 (fr_FR)

(1)

%X

Représentation locale de l’heure.

21:30:00 (en_US) ;

21:30:00 (fr_FR)

(1)

%%

Un caractère '%' littéral.

%

Plusieurs directives additionnelles non requises par le standard C89 sont incluses par commodité. Ces paramètres correspondent tous aux valeurs de dates ISO 8601. Ils peuvent ne pas être disponibles sur toutes les plateformes quand utilisés avec la méthode strftime(). Les directives ISO 8601 d’année et de semaine ne sont pas interchangeables avec les directives d’année et de semaine précédentes. Appeler strptime() avec des directives ISO 8601 incomplètes ou ambiguës lèvera une ValueError.

Directive

Signification

Exemple

Notes

%G

Année complète ISO 8601 représentant l’année contenant la plus grande partie de la semaine ISO (%V).

0001, 0002, …, 2013, 2014, …, 9998, 9999

(8)

%u

Jour de la semaine ISO 8601 où 1 correspond au lundi.

1, 2, …, 7

%V

Numéro de la semaine ISO 8601, avec lundi étant le premier jour de la semaine. La semaine 01 est la semaine contenant le 4 janvier.

01, 02, …, 53

(8)

Nouveau dans la version 3.6: %G, %u et %V ont été ajoutés.

Notes :

Comme le format dépend de la locale courante, les assomptions sur la valeur de retour doivent être prises soigneusement. L’ordre des champs variera (par exemple, « mois/jour/année » versus « année/mois/jour »), et le retour pourrait contenir des caractères Unicode encodés en utilisant l’encodage par défaut de la locale (par exemple, si la locale courante est ja_JP, l’encodage par défaut pourrait être eucJP, SJIS ou utf-8 ; utilisez locale.getlocale() pour déterminer l’encodage de la locale courante).

La méthode strptime() peut analyser toutes les années de l’intervalle [1, 9999], mais toutes les années < 1000 doivent être représentées sur quatre chiffres.

Modifié dans la version 3.2: Dans les versions précédentes, la méthode strftime() était limitée aux années >= 1900.

Modifié dans la version 3.3: En version 3.2, la méthode strftime() était limitée aux années >= 1000.

Quand utilisée avec la méthode strptime(), la directive %p n’affecte l’heure extraite que si la directive %I est utilisée pour analyser l’heure.

À l’inverse du module time, le module datetime ne gère pas les secondes intercalaires.

Quand utilisée avec la méthode strptime(), la directive %f accepte un nombre de 1 à 6 chiffres, où des zéros seront ajoutés à droite jusqu’à former un nombre de 6 chiffres. %f est une extension de l’ensemble des caractères de formatage du standard C (mais implémentée séparément dans les objets datetime, la rendant ainsi toujours disponible).

Pour les objets naïfs, les codes de formatage %z et %Z sont remplacés par des chaînes vides.

Pour un objet avisé :

%z

Le résultat de utcoffset() est transformé en une chaîne de 5 caractères de la forme +HHMM ou -HHMM, où HH est une chaîne de deux chiffres donnant le nombre d’heures du décalage UTC, et MM est une chaîne de deux chiffres donnant le nombre de minutes de ce décalage. Par exemple, si utcoffset() renvoie timedelta(hours=-3, minutes=-30), %z est remplacé par la chaîne “-0330”`.

%Z

Si tzname() renvoie None, %Z est remplacé par une chaîne vide. Autrement %Z est remplacé par la valeur renvoyée, qui doit être une chaîne.

Modifié dans la version 3.2: Quand la directive %z est fournie à la méthode strptime(), un objet datetime avisé est construit. L’attribut tzinfo du résultat aura pour valeur une instance de timezone.

Quand ces directives sont utilisées avec la méthode strptime(), %U et %W ne sont utilisées dans les calculs que si le jour de la semaine et l’année calendaire (%Y) sont spécifiés.

De façon similaire à %U et %W, %v n’est utilisé dans les calculs que lorsque le jour de la semaine et l’année ISO (%G) sont spécifiés dans la chaîne de formatage strptime(). Notez aussi que %G et %Y ne sont pas interchangeables.

Notes

1

Si on ignore les effets de la Relativité

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8.2. calendar — General calendar-related functions

Code source : Lib/calendar.py [https://github.com/python/cpython/tree/3.6/Lib/calendar.py]

Ce module permet d’afficher un calendrier comme le fait le programme Unix cal, et il fournit des fonctions utiles relatives au calendrier. Par défaut, ces calendriers ont le lundi comme premier jour de la semaine et le dimanche comme dernier jour. Utilisez setfirstweekday() pour définir le premier jour de la semaine à dimanche (6) ou à tout autre jour de la semaine. Les paramètres pour spécifier les dates sont donnés sous forme de nombres entiers. Voir aussi les modules datetime et time.

Most of these functions and classes rely on the datetime module which uses an idealized calendar, the current Gregorian calendar extended in both directions. This matches the definition of the « proleptic Gregorian » calendar in Dershowitz and Reingold’s book « Calendrical Calculations », where it’s the base calendar for all computations.

class calendar.Calendar(firstweekday=0)

Crée un objet Calendar. firstweekday est un entier spécifiant le premier jour de la semaine, valant par défaut 0 (lundi), pouvant aller jusqu’à 6 (dimanche).

L’objet Calendar fournit plusieurs méthodes pouvant être utilisées pour préparer les données du calendrier pour le formatage. Cette classe ne fait pas de formatage elle-même. Il s’agit du travail des sous-classes.

Les instances de Calendar ont les méthodes suivantes :

iterweekdays()

Renvoie un itérateur sur les numéros des jours d’une semaine. La première valeur est donc la même que la valeur de la propriété firstweekday.

itermonthdates(year, month)

Renvoie un itérateur sur les jours du mois month (1 à 12) de l’année year. Cet itérateur renvoie tous les jours du mois (sous forme d’instances de datetime.date) ainsi que tous les jours avant le début du mois et après la fin du mois nécessaires pour obtenir des semaines complètes.

itermonthdays2(year, month)

Return an iterator for the month month in the year year similar to itermonthdates(). Days returned will be tuples consisting of a day number and a week day number.

itermonthdays(year, month)

Return an iterator for the month month in the year year similar to itermonthdates(). Days returned will simply be day numbers.

monthdatescalendar(year, month)

Renvoie la liste des semaines complètes du mois month de l’année year. Les semaines sont des listes de sept objets datetime.date.

monthdays2calendar(year, month)

Renvoie la liste des semaines complètes du mois month de l’année year. Les semaines sont des listes de sept paires contenant le numéro du jour dans le mois et du numéro du jour dans la semaine.

monthdayscalendar(year, month)

Renvoie la liste des semaines complètes du mois month de l’année year. Les semaines sont une liste de sept numéros de jours.

yeardatescalendar(year, width=3)

Renvoie ce qu’il faut pour afficher correctement une année. La valeur renvoyée est une liste de lignes de mois. Chaque ligne mensuelle contient jusqu’à width mois (avec une valeur par défaut à 3). Chaque mois contient de 4 à 6 semaines et chaque semaine 1 à 7 jours. Les jours sont des objets datetime.date.

yeardays2calendar(year, width=3)

Renvoie ce qu’il faut pour afficher correctement une année, (similaire à yeardatescalendar()). Les listes des semaines contiennent des paires contenant le numéro du jour du mois et le numéro du jour de la semaine. Les numéro des jours en dehors de ce mois sont à zéro.

yeardayscalendar(year, width=3)

Renvoie ce qu’il faut pour afficher correctement une année, (similaire à yeardatescalendar()). Les listes de semaines contiennent des numéros de jours. Les numéros de jours en dehors de ce mois sont de zéro.

class calendar.TextCalendar(firstweekday=0)

Cette classe peut être utilisée pour générer des calendriers en texte brut.

Les instances TextCalendar exposent les méthodes suivantes :

formatmonth(theyear, themonth, w=0, l=0)

Donne le calendrier d’un mois dans une chaîne multi-ligne. Si w est fourni, il spécifie la largeur des colonnes de date, qui sont centrées. Si l est donné, il spécifie le nombre de lignes que chaque semaine utilisera. Le résultat varie en fonction du premier jour de la semaine spécifié dans le constructeur ou défini par la méthode setfirstweekday().

prmonth(theyear, themonth, w=0, l=0)

Affiche le calendrier d’un mois tel que renvoyé par formatmonth().

formatyear(theyear, w=2, l=1, c=6, m=3)

Renvoie un calendrier de m colonnes pour une année entière sous forme de chaîne multi-ligne. Les paramètres facultatifs w, l et c correspondent respectivement à la largeur de la colonne date, les lignes par semaines, le nombre d’espace entre les colonnes de mois. Le résultat varie en fonction du premier jour de la semaine spécifié dans le constructeur ou défini par la méthode setfirstweekday(). La première année pour laquelle un calendrier peut être généré, dépend de la plateforme.

pryear(theyear, w=2, l=1, c=6, m=3)

Affiche le calendrier pour une année entière comme renvoyé par formatyear().

class calendar.HTMLCalendar(firstweekday=0)

Cette classe peut être utilisée pour générer des calendriers HTML.

HTMLCalendar instances have the following methods:

formatmonth(theyear, themonth, withyear=True)

Return a month’s calendar as an HTML table. If withyear is true the year will be included in the header, otherwise just the month name will be used.

formatyear(theyear, width=3)

Return a year’s calendar as an HTML table. width (defaulting to 3) specifies the number of months per row.

formatyearpage(theyear, width=3, css='calendar.css', encoding=None)

Return a year’s calendar as a complete HTML page. width (defaulting to 3) specifies the number of months per row. css is the name for the cascading style sheet to be used. None can be passed if no style sheet should be used. encoding specifies the encoding to be used for the output (defaulting to the system default encoding).

class calendar.LocaleTextCalendar(firstweekday=0, locale=None)

This subclass of TextCalendar can be passed a locale name in the constructor and will return month and weekday names in the specified locale. If this locale includes an encoding all strings containing month and weekday names will be returned as unicode.

class calendar.LocaleHTMLCalendar(firstweekday=0, locale=None)

This subclass of HTMLCalendar can be passed a locale name in the constructor and will return month and weekday names in the specified locale. If this locale includes an encoding all strings containing month and weekday names will be returned as unicode.

Note

The formatweekday() and formatmonthname() methods of these two classes temporarily change the current locale to the given locale. Because the current locale is a process-wide setting, they are not thread-safe.

For simple text calendars this module provides the following functions.

calendar.setfirstweekday(weekday)

Sets the weekday (0 is Monday, 6 is Sunday) to start each week. The values MONDAY, TUESDAY, WEDNESDAY, THURSDAY, FRIDAY, SATURDAY, and SUNDAY are provided for convenience. For example, to set the first weekday to Sunday:

import calendar
calendar.setfirstweekday(calendar.SUNDAY)

calendar.firstweekday()

Returns the current setting for the weekday to start each week.

calendar.isleap(year)

Returns True if year is a leap year, otherwise False.

calendar.leapdays(y1, y2)

Returns the number of leap years in the range from y1 to y2 (exclusive), where y1 and y2 are years.

This function works for ranges spanning a century change.

calendar.weekday(year, month, day)

Returns the day of the week (0 is Monday) for year (1970–…), month (1–12), day (1–31).

calendar.weekheader(n)

Return a header containing abbreviated weekday names. n specifies the width in characters for one weekday.

calendar.monthrange(year, month)

Returns weekday of first day of the month and number of days in month, for the specified year and month.

calendar.monthcalendar(year, month)

Returns a matrix representing a month’s calendar. Each row represents a week; days outside of the month a represented by zeros. Each week begins with Monday unless set by setfirstweekday().

calendar.prmonth(theyear, themonth, w=0, l=0)

Prints a month’s calendar as returned by month().

calendar.month(theyear, themonth, w=0, l=0)

Returns a month’s calendar in a multi-line string using the formatmonth() of the TextCalendar class.

calendar.prcal(year, w=0, l=0, c=6, m=3)

Prints the calendar for an entire year as returned by calendar().

calendar.calendar(year, w=2, l=1, c=6, m=3)

Returns a 3-column calendar for an entire year as a multi-line string using the formatyear() of the TextCalendar class.

calendar.timegm(tuple)

An unrelated but handy function that takes a time tuple such as returned by the gmtime() function in the time module, and returns the corresponding Unix timestamp value, assuming an epoch of 1970, and the POSIX encoding. In fact, time.gmtime() and timegm() are each others” inverse.

The calendar module exports the following data attributes:

calendar.day_name

An array that represents the days of the week in the current locale.

calendar.day_abbr

An array that represents the abbreviated days of the week in the current locale.

calendar.month_name

An array that represents the months of the year in the current locale. This follows normal convention of January being month number 1, so it has a length of 13 and month_name[0] is the empty string.

calendar.month_abbr

An array that represents the abbreviated months of the year in the current locale. This follows normal convention of January being month number 1, so it has a length of 13 and month_abbr[0] is the empty string.

Voir aussi

Module datetime

Object-oriented interface to dates and times with similar functionality to the time module.

Module time

Low-level time related functions.

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8.3. collections — Types de données de conteneurs

Code source : Lib/collections/__init__.py [https://github.com/python/cpython/tree/3.6/Lib/collections/__init__.py]

Ce module implémente des types de données de conteneurs spécialisés qui apportent des alternatives aux conteneurs natifs de Python plus généraux dict, list, set et tuple.

namedtuple()

fonction permettant de créer des sous-classes de tuple avec des champs nommés

deque

conteneur se comportant comme une liste avec des ajouts et retraits rapides à chaque extrémité

ChainMap

classe semblable aux dictionnaires qui crée une unique vue à partir de plusieurs dictionnaires

Counter

sous-classe de dict pour compter des objets hachables

OrderedDict

sous-classe de dict qui garde en mémoire l’ordre dans lequel les entrées ont été ajoutées

defaultdict

sous-classe de dict qui appelle une fonction de fabrication en cas de valeur manquante

UserDict

surcouche autour des objets dictionnaires pour faciliter l’héritage de dict

UserList

surcouche autour des objets listes pour faciliter l’héritage de list

UserString

surcouche autour des objets chaînes de caractères pour faciliter l’héritage de str

Modifié dans la version 3.3: Moved Classes de base abstraites de collections to the collections.abc module. For backwards compatibility, they continue to be visible in this module as well.

8.3.1. Objets ChainMap

Nouveau dans la version 3.3.

Le module fournit une classe ChainMap afin de réunir rapidement plusieurs dictionnaires en une unique entité. Cela est souvent plus rapide que de créer un nouveau dictionnaire et d’effectuer plusieurs appels de update().

Cette classe peut être utilisée pour simuler des portées imbriquées, elle est aussi utile pour le templating.

class collections.ChainMap(*maps)

Un objet ChainMap regroupe plusieurs dictionnaires (ou autres tableaux de correspondance) en une vue que l’on peut mettre à jour. Si le paramètre maps est vide, un dictionnaire vide est fourni de telle manière qu’une nouvelle chaîne possède toujours au moins un dictionnaire.

Les dictionnaires sous-jacents sont stockés dans une liste. Celle-ci est publique et peut être consultée ou mise à jour via l’attribut maps. Il n’y a pas d’autre état.

Les recherches s’effectuent successivement dans chaque dictionnaire jusqu’à la première clé correspondante. En revanche, les écritures, mises à jour et suppressions n’affectent que le premier dictionnaire.

Un objet ChainMap incorpore les dictionnaires sous-jacents par leur référence. Ainsi, si l’un d’eux est modifié, les changements affectent également la ChainMap.

Toutes les méthodes usuelles des dictionnaires sont gérées. De plus, cette classe fournit un attribut maps, une méthode pour créer de nouveaux sous-contextes et une propriété pour accéder à tous les dictionnaires sous-jacents excepté le premier :

maps

Liste de dictionnaires éditable par l’utilisateur et classée selon l’ordre de recherche. Il s’agit de l’unique état stocké et elle peut être modifiée pour changer l’ordre de recherche. La liste doit toujours contenir au moins un dictionnaire.

new_child(m=None)

Renvoie un nouvel objet ChainMap contenant un nouveau dictionnaire suivi par tous les autres de l’instance actuelle. Si m est spécifié, il devient le nouveau dictionnaire au début de la liste ; sinon, un dictionnaire vide est utilisé, de telle manière qu’appeler d.new_child() équivaut à appeler ChainMap({}, *d.maps). Cette méthode est utile pour créer des sous-contextes qui peuvent être mis à jour sans altérer les valeurs dans les dictionnaires parents.

Modifié dans la version 3.4: Ajout du paramètre optionnel m.

parents

Propriété qui renvoie un nouvel objet ChainMap contenant tous les dictionnaires de l’instance actuelle hormis le premier. Cette propriété est utile pour ignorer le premier dictionnaire dans les recherches ; son utilisation rappelle le mot-clé nonlocal (utilisé pour les portées imbriquées), ou bien la fonction native super(). Une référence à d.parents est équivalente à : ChainMap(*d.maps[1:]).

Voir aussi

La classe MultiContext [https://github.com/enthought/codetools/blob/4.0.0/codetools/contexts/multi_context.py] dans le package CodeTools [https://github.com/enthought/codetools] d’Enthought possède des options pour gérer l’écriture dans n’importe quel dictionnaire de la chaîne.

Django’s Context class [https://github.com/django/django/blob/master/django/template/context.py] for templating is a read-only chain of mappings. It also features pushing and popping of contexts similar to the new_child() method and the parents() property.

Le Cas pratique des contextes imbriqués [https://code.activestate.com/recipes/577434/] a des options pour contrôler si les écritures et autres mutations ne s’appliquent qu’au premier ou à un autre dictionnaire de la chaîne.

Une version grandement simplifiée de Chainmap en lecture seule [https://code.activestate.com/recipes/305268/].

8.3.1.1. Exemples et cas pratiques utilisant ChainMap

Cette partie montre diverses approches afin de travailler avec les dictionnaires chaînés.

Exemple 1 : simulation de la chaîne de recherche interne de Python :

import builtins
pylookup = ChainMap(locals(), globals(), vars(builtins))

Exemple 2 : spécification d’une hiérarchie pour les options : ligne de commande, variable d’environnement, valeurs par défaut :

import os, argparse

defaults = {'color': 'red', 'user': 'guest'}

parser = argparse.ArgumentParser()
parser.add_argument('-u', '--user')
parser.add_argument('-c', '--color')
namespace = parser.parse_args()
command_line_args = {k:v for k, v in vars(namespace).items() if v}

combined = ChainMap(command_line_args, os.environ, defaults)
print(combined['color'])
print(combined['user'])

Exemple 3 : modèles pour simuler des contexte imbriqués avec la classe ChainMap :

c = ChainMap()        # Create root context
d = c.new_child()     # Create nested child context
e = c.new_child()     # Child of c, independent from d
e.maps[0]             # Current context dictionary -- like Python's locals()
e.maps[-1]            # Root context -- like Python's globals()
e.parents             # Enclosing context chain -- like Python's nonlocals

d['x']                # Get first key in the chain of contexts
d['x'] = 1            # Set value in current context
del d['x']            # Delete from current context
list(d)               # All nested values
k in d                # Check all nested values
len(d)                # Number of nested values
d.items()             # All nested items
dict(d)               # Flatten into a regular dictionary

La classe ChainMap ne met à jour (écriture et suppression) que le premier dictionnaire de la chaîne, alors qu’une recherche inspecte toute la chaîne. Cependant, si l’on veut effectuer des écritures ou suppressions en profondeur, on peut facilement faire une sous-classe qui met à jour les clés trouvées de la chaîne en profondeur :

class DeepChainMap(ChainMap):
    'Variant of ChainMap that allows direct updates to inner scopes'

    def __setitem__(self, key, value):
        for mapping in self.maps:
            if key in mapping:
                mapping[key] = value
                return
        self.maps[0][key] = value

    def __delitem__(self, key):
        for mapping in self.maps:
            if key in mapping:
                del mapping[key]
                return
        raise KeyError(key)

>>> d = DeepChainMap({'zebra': 'black'}, {'elephant': 'blue'}, {'lion': 'yellow'})
>>> d['lion'] = 'orange'         # update an existing key two levels down
>>> d['snake'] = 'red'           # new keys get added to the topmost dict
>>> del d['elephant']            # remove an existing key one level down
>>> d                            # display result
DeepChainMap({'zebra': 'black', 'snake': 'red'}, {}, {'lion': 'orange'})

8.3.2. Objets Counter

Ce module fournit un outil pour effectuer rapidement et facilement des dénombrements. Par exemple :

>>> # Tally occurrences of words in a list
>>> cnt = Counter()
>>> for word in ['red', 'blue', 'red', 'green', 'blue', 'blue']:
...     cnt[word] += 1
>>> cnt
Counter({'blue': 3, 'red': 2, 'green': 1})

>>> # Find the ten most common words in Hamlet
>>> import re
>>> words = re.findall(r'\w+', open('hamlet.txt').read().lower())
>>> Counter(words).most_common(10)
[('the', 1143), ('and', 966), ('to', 762), ('of', 669), ('i', 631),
 ('you', 554),  ('a', 546), ('my', 514), ('hamlet', 471), ('in', 451)]

class collections.Counter([iterable-or-mapping])

La classe Counter est une sous-classe de dict qui permet le dénombrement d’objets hachables. Il s’agit d’une collection non ordonnée dans laquelle les éléments sont stockés comme des clés de dictionnaire et leurs nombres d’occurrences respectifs comme leurs valeurs. Ceux-ci peuvent être des entiers relatifs (positifs, négatifs ou nuls). La classe Counter est similaire aux sacs ou aux multiensembles dans d’autres langages.

Les éléments sont comptés à partir d’un itérable ou initialisés à partir d’un autre dictionnaire (ou compteur) :

>>> c = Counter()                           # a new, empty counter
>>> c = Counter('gallahad')                 # a new counter from an iterable
>>> c = Counter({'red': 4, 'blue': 2})      # a new counter from a mapping
>>> c = Counter(cats=4, dogs=8)             # a new counter from keyword args

Les objets Counter ont une interface de dictionnaire, à l’exception près qu’ils renvoient zéro au lieu de lever une exception KeyError pour des éléments manquants :

>>> c = Counter(['eggs', 'ham'])
>>> c['bacon']                              # count of a missing element is zero
0

Mettre un comptage à zéro pour un élément ne le retire pas de l’objet Counter. Il faut utiliser del pour le supprimer complètement :

>>> c['sausage'] = 0                        # counter entry with a zero count
>>> del c['sausage']                        # del actually removes the entry

Nouveau dans la version 3.1.

En plus des méthodes disponibles pour tous les dictionnaires, les objets compteurs gèrent trois méthodes supplémentaires :

elements()

Renvoie un itérateur sur chaque élément en le répétant autant de fois que la valeur du compteur associé. Les éléments sont renvoyés dans un ordre arbitraire. Si le comptage d’un élément est strictement inférieur à 1, alors elements() l’ignore.

>>> c = Counter(a=4, b=2, c=0, d=-2)
>>> sorted(c.elements())
['a', 'a', 'a', 'a', 'b', 'b']

most_common([n])

Return a list of the n most common elements and their counts from the most common to the least. If n is omitted or None, most_common() returns all elements in the counter. Elements with equal counts are ordered arbitrarily:

>>> Counter('abracadabra').most_common(3)
[('a', 5), ('r', 2), ('b', 2)]

subtract([iterable-or-mapping])

Les éléments sont soustraits à partir d’un itérable ou d’un autre dictionnaire (ou compteur). Cette méthode se comporte comme dict.update() mais soustrait les nombres d’occurrences au lieu de les remplacer. Les entrées et sorties peuvent être négatives ou nulles.

>>> c = Counter(a=4, b=2, c=0, d=-2)
>>> d = Counter(a=1, b=2, c=3, d=4)
>>> c.subtract(d)
>>> c
Counter({'a': 3, 'b': 0, 'c': -3, 'd': -6})

Nouveau dans la version 3.2.

Les méthodes usuelles des dictionnaires sont disponibles pour les objets Counter à l’exception de deux méthodes qui fonctionnent différemment pour les compteurs.

fromkeys(iterable)

Cette méthode de classe n’est pas implémentée pour les objets Counter.

update([iterable-or-mapping])

Les éléments sont comptés à partir d’un itérable ou ajoutés d’un autre dictionnaire (ou compteur). Cette méthode se comporte comme dict.update() mais additionne les nombres d’occurrences au lieu de les remplacer. De plus, l’itérable doit être une séquence d’éléments et non une séquence de paires (clé, valeur).

Opérations usuelles sur les objets Counter :

sum(c.values())                 # total of all counts
c.clear()                       # reset all counts
list(c)                         # list unique elements
set(c)                          # convert to a set
dict(c)                         # convert to a regular dictionary
c.items()                       # convert to a list of (elem, cnt) pairs
Counter(dict(list_of_pairs))    # convert from a list of (elem, cnt) pairs
c.most_common()[:-n-1:-1]       # n least common elements
+c                              # remove zero and negative counts

Quelques opérations mathématiques sont fournies pour combiner des objets Counter afin de créer des multiensembles (des compteurs dont les dénombrements des éléments sont strictement supérieurs à zéro). Les additions et soustractions combinent les compteurs en ajoutant ou retranchant les nombres d’occurrences des éléments correspondants. Les intersections et unions renvoient les minimums et maximums des comptages correspondants. Chaque opération peut accepter des entrées avec des comptages relatifs, mais la sortie exclut les résultats avec des comptages négatifs ou nuls.

>>> c = Counter(a=3, b=1)
>>> d = Counter(a=1, b=2)
>>> c + d                       # add two counters together:  c[x] + d[x]
Counter({'a': 4, 'b': 3})
>>> c - d                       # subtract (keeping only positive counts)
Counter({'a': 2})
>>> c & d                       # intersection:  min(c[x], d[x])
Counter({'a': 1, 'b': 1})
>>> c | d                       # union:  max(c[x], d[x])
Counter({'a': 3, 'b': 2})

L’addition et la soustraction unaires (avec un seul terme) sont des raccourcis pour respectivement additionner un compteur avec un compteur vide ou et pour retrancher un compteur d’un compteur vide.

>>> c = Counter(a=2, b=-4)
>>> +c
Counter({'a': 2})
>>> -c
Counter({'b': 4})

Nouveau dans la version 3.3: Ajout de la gestion des additions et soustractions unaires, et des remplacements dans les multiensembles.

Note

Les compteurs ont été conçus essentiellement pour fonctionner avec des entiers naturels pour représenter les dénombrements en cours ; cependant, les cas d’utilisation nécessitant d’autres types ou des valeurs négatives n’ont pas été écartés. Pour vous aider dans ces cas particuliers, cette section documente la plage minimale et les restrictions de type.

La classe Counter est elle-même une sous-classe de dictionnaire sans restriction particulière sur ces clés ou valeurs. Les valeurs ont vocation à être des nombres représentants des comptages, mais il est possible de stocker n’importe quel type de valeur.

The most_common() method requires only that the values be orderable.

For in-place operations such as c[key] += 1, the value type need only support addition and subtraction. So fractions, floats, and decimals would work and negative values are supported. The same is also true for update() and subtract() which allow negative and zero values for both inputs and outputs.

Les méthodes de multiensembles sont uniquement conçues pour les cas d’utilisation avec des valeurs positives. Les entrées peuvent contenir des valeurs négatives ou nulles, mais seules les sorties avec des valeurs positives sont créées. Il n’y a pas de restriction de type, mais les types des valeurs doivent gérer l’addition, la soustraction et la comparaison.

The elements() method requires integer counts. It ignores zero and negative counts.

Voir aussi

Bag class [https://www.gnu.org/software/smalltalk/manual-base/html_node/Bag.html] dans Smalltalk.

L’article Wikipédia sur les multiensembles [https://fr.wikipedia.org/wiki/Multiensemble] sur Wikipédia (ou l’article en anglais [https://en.wikipedia.org/wiki/Multiset]).

Des guides et exemples à propos des multiensembles en C++ [http://www.java2s.com/Tutorial/Cpp/0380__set-multiset/Catalog0380__set-multiset.htm].

Pour les opérations mathématiques sur les multiensembles et leurs applications, voir Knuth, Donald. The Art of Computer Programming Volume II, Section 4.6.3, Exercise 19.

To enumerate all distinct multisets of a given size over a given set of elements, see itertools.combinations_with_replacement():

map(Counter, combinations_with_replacement(“ABC”, 2)) –> AA AB AC BB BC CC

8.3.3. Objets deque

class collections.deque([iterable[, maxlen]])

Renvoie un nouvel objet deque initialisé de gauche à droite (en utilisant append()) avec les données d”iterable. Si iterable n’est pas spécifié, alors la nouvelle deque est vide.

Les deques sont une généralisation des piles et des files (deque se prononce « dèque » et est l’abréviation de l’anglais double-ended queue) : il est possible d’ajouter et retirer des éléments par les deux bouts des deques. Celles-ci gèrent des ajouts et des retraits utilisables par de multiples fils d’exécution (thread-safe) et efficients du point de vue de la mémoire des deux côtés de la deque, avec approximativement la même performance en O(1) dans les deux sens.

Bien que les les objets list gèrent des opérations similaires, ils sont optimisés pour des opérations qui ne changent pas la taille de la liste. Les opérations pop(0) et insert(0, v) qui changent la taille et la position de la représentation des données sous-jacentes entraînent des coûts de déplacement de mémoire en O(n).

Si maxlen n’est pas spécifié ou vaut None, les deques peuvent atteindre une taille arbitraire. Sinon, la deque est limitée par cette taille maximale. Une fois que celle-ci est atteinte, un ajout d’un ou plusieurs éléments engendre la suppression du nombre correspondant d’éléments à l’autre extrémité de la deque. Les deques à longueur limitée apportent des fonctionnalités similaire au filtre tail d’Unix. Elles sont aussi utiles pour le suivi de transactions et autres lots de données où seule l’activité récente est intéressante.

Les objets deques gèrent les méthodes suivantes :

append(x)

Ajoute x à l’extrémité droite de la deque.

appendleft(x)

Ajoute x à l’extrémité gauche de la deque.

clear()

Supprime tous les éléments de la deque et la laisse avec une longueur de 0.

copy()

Crée une copie superficielle de la deque.

Nouveau dans la version 3.5.

count(x)

Compte le nombre d’éléments de la deque égaux à x.

Nouveau dans la version 3.2.

extend(iterable)

Étend la deque en ajoutant les éléments de l’itérable en argument à son extrémité droite.

extendleft(iterable)

Étend la deque en ajoutant les éléments d”iterable à son extrémité gauche. Dans ce cas, notez que la série d’ajouts inverse l’ordre des éléments de l’argument itérable.

index(x[, start[, stop]])

Renvoie la position de x dans la deque (à partir de start inclus et jusqu’à stop exclus). Renvoie la première correspondance ou lève ValueError si aucune n’est trouvée.

Nouveau dans la version 3.5.

insert(i, x)

Insère x dans la deque à la position i.

Si une insertion provoque un dépassement de la taille limitée d’une deque, alors elle lève une exception IndexError.

Nouveau dans la version 3.5.

pop()

Retire et renvoie un élément de l’extrémité droite de la deque. S’il n’y a aucun élément, lève une exception IndexError.

popleft()

Retire et renvoie un élément de l’extrémité gauche de la deque. S’il n’y a aucun élément, lève une exception IndexError.

remove(value)

Supprime la première occurrence de value. Si aucune occurrence n’est trouvée, lève une exception ValueError.

reverse()

Inverse le sens des éléments de la deque sans créer de copie et renvoie None.

Nouveau dans la version 3.2.

rotate(n=1)

Décale les éléments de la deque de n places vers la droite (le dernier élément revient au début). Si n est négatif, décale vers la gauche.

Quand la deque n’est pas vide, un décalage d’une place vers la droite équivaut à d.appendleft(d.pop()) et un décalage d’une place vers la gauche est équivalent à d.append(d.popleft()).

Les objets deques fournissent également un attribut en lecture seule :

maxlen

La taille maximale d’une deque, ou None si illimitée.

Nouveau dans la version 3.1.

En plus des méthodes précédentes, les deques gèrent l’itération, la sérialisation, len(d), reversed(d), copy.copy(d), copy.deepcopy(d), le test d’appartenance avec l’opérateur in, et les références en indice comme d[-1]. L’accès par indice est en O(1) aux extrémités mais en O(n) au milieu. Pour des accès aléatoires rapides, il est préférable d’utiliser des listes.

Depuis la version 3.5, les deques gèrent __add__(), __mul__() et __imul__().

Exemple :

>>> from collections import deque
>>> d = deque('ghi')                 # make a new deque with three items
>>> for elem in d:                   # iterate over the deque's elements
...     print(elem.upper())
G
H
I

>>> d.append('j')                    # add a new entry to the right side
>>> d.appendleft('f')                # add a new entry to the left side
>>> d                                # show the representation of the deque
deque(['f', 'g', 'h', 'i', 'j'])

>>> d.pop()                          # return and remove the rightmost item
'j'
>>> d.popleft()                      # return and remove the leftmost item
'f'
>>> list(d)                          # list the contents of the deque
['g', 'h', 'i']
>>> d[0]                             # peek at leftmost item
'g'
>>> d[-1]                            # peek at rightmost item
'i'

>>> list(reversed(d))                # list the contents of a deque in reverse
['i', 'h', 'g']
>>> 'h' in d                         # search the deque
True
>>> d.extend('jkl')                  # add multiple elements at once
>>> d
deque(['g', 'h', 'i', 'j', 'k', 'l'])
>>> d.rotate(1)                      # right rotation
>>> d
deque(['l', 'g', 'h', 'i', 'j', 'k'])
>>> d.rotate(-1)                     # left rotation
>>> d
deque(['g', 'h', 'i', 'j', 'k', 'l'])

>>> deque(reversed(d))               # make a new deque in reverse order
deque(['l', 'k', 'j', 'i', 'h', 'g'])
>>> d.clear()                        # empty the deque
>>> d.pop()                          # cannot pop from an empty deque
Traceback (most recent call last):
    File "<pyshell#6>", line 1, in -toplevel-
        d.pop()
IndexError: pop from an empty deque

>>> d.extendleft('abc')              # extendleft() reverses the input order
>>> d
deque(['c', 'b', 'a'])

8.3.3.1. Cas pratiques utilisant deque

Cette partie montre diverses approches afin de travailler avec les deques.

Les deques à taille limitée apportent une fonctionnalité similaire au filtre tail d’Unix :

def tail(filename, n=10):
    'Return the last n lines of a file'
    with open(filename) as f:
        return deque(f, n)

Une autre approche d’utilisation des deques est de maintenir une séquence d’éléments récemment ajoutés en les ajoutant à droite et en retirant les anciens par la gauche :

def moving_average(iterable, n=3):
    # moving_average([40, 30, 50, 46, 39, 44]) --> 40.0 42.0 45.0 43.0
    # http://en.wikipedia.org/wiki/Moving_average
    it = iter(iterable)
    d = deque(itertools.islice(it, n-1))
    d.appendleft(0)
    s = sum(d)
    for elem in it:
        s += elem - d.popleft()
        d.append(elem)
        yield s / n

The rotate() method provides a way to implement deque slicing and deletion. For example, a pure Python implementation of del d[n] relies on the rotate() method to position elements to be popped:

def delete_nth(d, n):
    d.rotate(-n)
    d.popleft()
    d.rotate(n)

To implement deque slicing, use a similar approach applying rotate() to bring a target element to the left side of the deque. Remove old entries with popleft(), add new entries with extend(), and then reverse the rotation. With minor variations on that approach, it is easy to implement Forth style stack manipulations such as dup, drop, swap, over, pick, rot, and roll.

8.3.4. Objets defaultdict

class collections.defaultdict([default_factory[, ...]])

Renvoie un nouvel objet qui se comporte comme un dictionnaire. defaultdict est une sous-classe de la la classe native dict. Elle surcharge une méthode et ajoute une variable d’instance modifiable. Les autres fonctionnalités sont les mêmes que celles des objets dict et ne sont pas documentées ici.

Le premier argument fournit la valeur initiale de l’attribut default_factory qui doit être un objet appelable sans paramètre ou None, sa valeur par défaut. Tous les autres arguments sont traités comme si on les passait au constructeur de dict, y compris les arguments nommés.

En plus des opérations usuelles de dict, les objets defaultdict gèrent les méthodes supplémentaires suivantes :

__missing__(key)

Si l’attribut default_factory est None, lève une exception KeyError avec key comme argument.

Si default_fatory` ne vaut pas None, cet attribut est appelé sans argument pour fournir une valeur par défaut pour la key demandée. Cette valeur est insérée dans le dictionnaire avec pour clé key et est renvoyée.

Si appeler default_factory lève une exception, celle-ci est transmise inchangée.

Cette méthode est appelée par la méthode __getitem__() de la classe dict lorsque la clé demandée n’est pas trouvée. Ce qu’elle renvoie ou lève est alors renvoyé ou levé par __getitem__().

Remarquez que __missing__() n’est pas appelée pour les opérations autres que __getitem__(). Cela signifie que get() renvoie None comme les dictionnaires natifs dans les cas triviaux et n’utilise pas default_factory.

Les objets defaultdict gèrent la variable d’instance :

default_factory

Cet attribut est utilisé par la méthode __missing__() ; il est initialisé par le premier argument passé au constructeur, s’il est spécifié, sinon par None.

8.3.4.1. Exemples utilisant defaultdict

Using list as the default_factory, it is easy to group a sequence of key-value pairs into a dictionary of lists:

>>> s = [('yellow', 1), ('blue', 2), ('yellow', 3), ('blue', 4), ('red', 1)]
>>> d = defaultdict(list)
>>> for k, v in s:
...     d[k].append(v)
...
>>> sorted(d.items())
[('blue', [2, 4]), ('red', [1]), ('yellow', [1, 3])]

When each key is encountered for the first time, it is not already in the mapping; so an entry is automatically created using the default_factory function which returns an empty list. The list.append() operation then attaches the value to the new list. When keys are encountered again, the look-up proceeds normally (returning the list for that key) and the list.append() operation adds another value to the list. This technique is simpler and faster than an equivalent technique using dict.setdefault():

>>> d = {}
>>> for k, v in s:
...     d.setdefault(k, []).append(v)
...
>>> sorted(d.items())
[('blue', [2, 4]), ('red', [1]), ('yellow', [1, 3])]

Setting the default_factory to int makes the defaultdict useful for counting (like a bag or multiset in other languages):

>>> s = 'mississippi'
>>> d = defaultdict(int)
>>> for k in s:
...     d[k] += 1
...
>>> sorted(d.items())
[('i', 4), ('m', 1), ('p', 2), ('s', 4)]

When a letter is first encountered, it is missing from the mapping, so the default_factory function calls int() to supply a default count of zero. The increment operation then builds up the count for each letter.

La fonction int() qui retourne toujours zéro est simplement une fonction constante particulière. Un moyen plus flexible et rapide de créer une fonction constante est d’utiliser une fonction lambda qui peut fournir n’importe quelle valeur constante (pas seulement zéro) :

>>> def constant_factory(value):
...     return lambda: value
>>> d = defaultdict(constant_factory('<missing>'))
>>> d.update(name='John', action='ran')
>>> '%(name)s %(action)s to %(object)s' % d
'John ran to <missing>'

Setting the default_factory to set makes the defaultdict useful for building a dictionary of sets:

>>> s = [('red', 1), ('blue', 2), ('red', 3), ('blue', 4), ('red', 1), ('blue', 4)]
>>> d = defaultdict(set)
>>> for k, v in s:
...     d[k].add(v)
...
>>> sorted(d.items())
[('blue', {2, 4}), ('red', {1, 3})]

8.3.5. namedtuple(): fonction de construction pour n-uplets (tuples) avec des champs nommés

Les tuples nommés assignent une signification à chacun de leur élément, ce qui rend le code plus lisible et explicite. Ils peuvent être utilisés partout où les tuples natifs sont utilisés, et ils ajoutent la possibilité d’accéder à leurs champs grâce à leur nom au lieu de leur index de position.

collections.namedtuple(typename, field_names, *, verbose=False, rename=False, module=None)

Renvoie une nouvelle sous-classe de tuple appelée typename. Elle est utilisée pour créer des objets se comportant comme les tuples qui ont des champs accessibles par recherche d’attribut en plus d’être indexables et itérables. Les instances de cette sous-classe possèdent aussi une docstring explicite (avec type_name et les field_names) et une méthode __repr__() pratique qui liste le contenu du tuple au format nom=valeur.

field_names peut être une séquence de chaînes de caractères telle que ['x', 'y'] ou bien une unique chaîne de caractères où les noms de champs sont séparés par un espace et/ou une virgule, par exemple 'x y' ou 'x, y'.

N’importe quel identifiant Python peut être utilisé pour un nom de champ hormis ceux commençant par un tiret bas. Les identifiants valides peuvent contenir des lettres, des chiffres (sauf en première position) et des tirets bas (sauf en première position). Un identifiant ne peut pas être un keyword tel que class, for, return, global, pass ou raise.

Si rename vaut True, alors les noms de champs invalides sont automatiquement renommés en noms positionnels. Par exemple, ['abc', 'def', 'ghi', 'abc'] est converti en ['abc, '_1', 'ghi', '_3'] afin d’éliminer le mot-clé def et le doublon de abc.

If verbose is true, the class definition is printed after it is built. This option is outdated; instead, it is simpler to print the _source attribute.

Si module est spécifié, alors il est assigné à l’attribut __module__ du tuple nommé.

Les instances de tuples nommés n’ont pas de dictionnaires propres, elles sont donc légères et ne requièrent pas plus de mémoire que les tuples natifs.

Modifié dans la version 3.1: Gestion de rename.

Modifié dans la version 3.6: Les paramètres verbose et rename deviennent des arguments obligatoirement nommés.

Modifié dans la version 3.6: Ajout du paramètre module.

>>> # Basic example
>>> Point = namedtuple('Point', ['x', 'y'])
>>> p = Point(11, y=22)     # instantiate with positional or keyword arguments
>>> p[0] + p[1]             # indexable like the plain tuple (11, 22)
33
>>> x, y = p                # unpack like a regular tuple
>>> x, y
(11, 22)
>>> p.x + p.y               # fields also accessible by name
33
>>> p                       # readable __repr__ with a name=value style
Point(x=11, y=22)

Les tuples nommés sont particulièrement utiles pour associer des noms de champs à des tuples renvoyés par les modules csv ou sqlite3 :

EmployeeRecord = namedtuple('EmployeeRecord', 'name, age, title, department, paygrade')

import csv
for emp in map(EmployeeRecord._make, csv.reader(open("employees.csv", "rb"))):
    print(emp.name, emp.title)

import sqlite3
conn = sqlite3.connect('/companydata')
cursor = conn.cursor()
cursor.execute('SELECT name, age, title, department, paygrade FROM employees')
for emp in map(EmployeeRecord._make, cursor.fetchall()):
    print(emp.name, emp.title)

En plus des méthodes héritées de tuple, les tuples nommés implémentent trois méthodes et deux attributs supplémentaires. Pour éviter les conflits avec noms de champs, leurs noms commencent par un tiret bas.

classmethod somenamedtuple._make(iterable)

Méthode de classe qui construit une nouvelle instance à partir d’une séquence ou d’un itérable existant.

>>> t = [11, 22]
>>> Point._make(t)
Point(x=11, y=22)

somenamedtuple._asdict()

Renvoie un nouvel OrderedDict qui associe chaque nom de champ à sa valeur correspondante :

>>> p = Point(x=11, y=22)
>>> p._asdict()
OrderedDict([('x', 11), ('y', 22)])

Modifié dans la version 3.1: Renvoie un OrderedDict au lieu d’un dict natif.

somenamedtuple._replace(**kwargs)

Renvoie une nouvelle instance du tuple nommé en remplaçant les champs spécifiés par leurs nouvelles valeurs :

>>> p = Point(x=11, y=22)
>>> p._replace(x=33)
Point(x=33, y=22)

>>> for partnum, record in inventory.items():
...     inventory[partnum] = record._replace(price=newprices[partnum], timestamp=time.now())

somenamedtuple._source

A string with the pure Python source code used to create the named tuple class. The source makes the named tuple self-documenting. It can be printed, executed using exec(), or saved to a file and imported.

Nouveau dans la version 3.3.

somenamedtuple._fields

Tuple de chaînes de caractères listant les noms de champs. Pratique pour l’introspection et pour créer de nouveaux types de tuples nommés à partir d’existants.

>>> p._fields            # view the field names
('x', 'y')

>>> Color = namedtuple('Color', 'red green blue')
>>> Pixel = namedtuple('Pixel', Point._fields + Color._fields)
>>> Pixel(11, 22, 128, 255, 0)
Pixel(x=11, y=22, red=128, green=255, blue=0)

Pour récupérer un champ dont le nom est une chaîne de caractères, utilisez la fonction getattr() :

>>> getattr(p, 'x')
11

Pour convertir un dictionnaire en tuple nommé, utilisez l’opérateur double-étoile (comme expliqué dans Séparation des listes d’arguments) :

>>> d = {'x': 11, 'y': 22}
>>> Point(**d)
Point(x=11, y=22)

Il est aisé d’ajouter ou de modifier les fonctionnalités des tuples nommés grâce à l’héritage puisqu’il s’agit de simples classes. Voici comment ajouter un champ calculé avec une longueur fixe d’affichage :

>>> class Point(namedtuple('Point', ['x', 'y'])):
...     __slots__ = ()
...     @property
...     def hypot(self):
...         return (self.x ** 2 + self.y ** 2) ** 0.5
...     def __str__(self):
...         return 'Point: x=%6.3f  y=%6.3f  hypot=%6.3f' % (self.x, self.y, self.hypot)

>>> for p in Point(3, 4), Point(14, 5/7):
...     print(p)
Point: x= 3.000  y= 4.000  hypot= 5.000
Point: x=14.000  y= 0.714  hypot=14.018

La sous-classe ci-dessus définit __slots__ comme un tuple vide. Cela permet de garder une emprunte mémoire faible en empêchant la création de dictionnaire d’instance.

Subclassing is not useful for adding new, stored fields. Instead, simply create a new named tuple type from the _fields attribute:

>>> Point3D = namedtuple('Point3D', Point._fields + ('z',))

Les docstrings peuvent être personnalisées en modifiant directement l’attribut __doc__ :

>>> Book = namedtuple('Book', ['id', 'title', 'authors'])
>>> Book.__doc__ += ': Hardcover book in active collection'
>>> Book.id.__doc__ = '13-digit ISBN'
>>> Book.title.__doc__ = 'Title of first printing'
>>> Book.authors.__doc__ = 'List of authors sorted by last name'

Modifié dans la version 3.5: La propriété devient éditable.

Default values can be implemented by using _replace() to customize a prototype instance:

>>> Account = namedtuple('Account', 'owner balance transaction_count')
>>> default_account = Account('<owner name>', 0.0, 0)
>>> johns_account = default_account._replace(owner='John')
>>> janes_account = default_account._replace(owner='Jane')

Voir aussi

Cas pratique : classe de base abstraite de tuple nommé grâce à une métaclasse mixin [https://code.activestate.com/recipes/577629-namedtupleabc-abstract-base-class-mix-in-for-named/] par Jan Kaliszewski. En plus de fournir une abstract base class pour les tuples nommés, elle gère un constructeur de metaclass pratique dans les cas où l’on hérite de tuples nommés.

Voir types.SimpleNamespace() pour un espace de nommage muable basé sur un dictionnaire sous-jacent à la place d’un tuple.

Voir typing.NamedTuple() pour un moyen d’ajouter des indications de type pour les tuples nommés.

8.3.6. Objets OrderedDict

En plus de se comporter comme des dictionnaires natifs, les dictionnaires ordonnés mémorisent l’ordre dans lequel les éléments ont été insérés. Quand on itère sur un dictionnaire ordonné, les éléments sont renvoyés dans l’ordre d’insertion des clés.

class collections.OrderedDict([items])

Renvoie une instance d’une sous-classe de dict qui gère les méthodes usuelles de dict. Un objet OrderedDict est un dictionnaire qui mémorise l’ordre d’insertion des clés. Si une nouvelle entrée en écrase une autre, sa position reste inchangé. Si une entrée est supprimée puis réinsérée, elle est placée en dernière position.

Nouveau dans la version 3.1.

popitem(last=True)

La méthode popitem() pour les dictionnaires ordonnés retire et renvoie une paire (clé, valeur). Les paires sont renvoyées comme pour une pile, c’est-à-dire dernier entré, premier sorti (en anglais LIFO) si last vaut True. Si last vaut False, alors les paires sont renvoyées comme pour une file, c’est-à-dire premier entré, premier sorti (en anglais FIFO).

move_to_end(key, last=True)

Déplace une clé key existante à l’une des deux extrémités du dictionnaire : à droite si last vaut True (comportement par défaut) ou à gauche sinon. Lève une exception KeyError si la clé key n’est pas trouvée :

>>> d = OrderedDict.fromkeys('abcde')
>>> d.move_to_end('b')
>>> ''.join(d.keys())
'acdeb'
>>> d.move_to_end('b', last=False)
>>> ''.join(d.keys())
'bacde'

Nouveau dans la version 3.2.

En plus des méthodes usuelles des dictionnaires, les dictionnaires ordonnés gèrent l’itération en sens inverse grâce à reversed().

Les tests d’égalité entre deux objets OrderedDict sont sensibles à l’ordre et sont implémentés comme ceci : list(od1.items() == list(od2.items()). Les tests d’égalité entre un objet OrderedDict et un objet Mapping ne sont pas sensibles à l’ordre (comme les dictionnaires natifs). Cela permet substituer des objets OrderedDict partout où les dictionnaires natifs sont utilisés.

Modifié dans la version 3.5: Les vues d’éléments, de clés et de valeurs de OrderedDict gèrent maintenant l’itération en sens inverse en utilisant reversed().

Modifié dans la version 3.6: Suite à l’acceptation de la PEP 468 [https://www.python.org/dev/peps/pep-0468], l’ordre des arguments nommés passés au constructeur et à la méthode update() de OrderedDict est conservé.

8.3.6.1. Exemples et cas pratiques utilisant OrderDict

Puisqu’un dictionnaire ordonné mémorise l’ordre d’insertion de ses éléments, il peut être utilisé conjointement avec un classement pour créer un dictionnaire trié :

>>> # regular unsorted dictionary
>>> d = {'banana': 3, 'apple': 4, 'pear': 1, 'orange': 2}

>>> # dictionary sorted by key
>>> OrderedDict(sorted(d.items(), key=lambda t: t[0]))
OrderedDict([('apple', 4), ('banana', 3), ('orange', 2), ('pear', 1)])

>>> # dictionary sorted by value
>>> OrderedDict(sorted(d.items(), key=lambda t: t[1]))
OrderedDict([('pear', 1), ('orange', 2), ('banana', 3), ('apple', 4)])

>>> # dictionary sorted by length of the key string
>>> OrderedDict(sorted(d.items(), key=lambda t: len(t[0])))
OrderedDict([('pear', 1), ('apple', 4), ('orange', 2), ('banana', 3)])

Les nouveaux dictionnaires triés gardent leur classement quand des entrées sont supprimées, mais si de nouvelles clés sont ajoutées, celles-ci sont ajoutée à la fin et le classement est perdu.

Il est également facile de créer une variante de dictionnaire ordonné qui retient l’ordre dans lequel les clés ont été insérées en dernier. Si une nouvelle entrée écrase une existante, la position d’insertion d’origine est modifiée et déplacée à la fin :

class LastUpdatedOrderedDict(OrderedDict):
    'Store items in the order the keys were last added'

    def __setitem__(self, key, value):
        if key in self:
            del self[key]
        OrderedDict.__setitem__(self, key, value)

Un dictionnaire ordonné peut être combiné avec la classe Counter afin de mémoriser l’ordre dans lequel les éléments ont été ajoutés pour la première fois :

class OrderedCounter(Counter, OrderedDict):
    'Counter that remembers the order elements are first encountered'

    def __repr__(self):
        return '%s(%r)' % (self.__class__.__name__, OrderedDict(self))

    def __reduce__(self):
        return self.__class__, (OrderedDict(self),)

8.3.7. Objets UserDict

La classe UserDict se comporte comme une surcouche autour des dictionnaires. L’utilité de cette classe est réduite car on peut maintenant hériter directement de dict. Cependant, il peut être plus facile de travailler avec celle-ci car le dictionnaire sous-jacent est accessible comme attribut.

class collections.UserDict([initialdata])

Classe simulant un dictionnaire. Les instances de UserDict possèdent un attribut data où est stocké leur contenu sous forme de dictionnaire natif. Si initialdata est spécifié, alors data est initialisé avec son contenu. Remarquez qu’une référence vers initialdata n’est pas conservée, ce qui permet de l’utiliser pour d’autres tâches.

En plus de gérer les méthodes et opérations des dictionnaires, les instance de UserDict fournissent l’attribut suivant :

data

Un dictionnaire natif où est stocké le contenu de la classe UserDict.

8.3.8. Objets UserList

Cette classe agit comme une surcouche autour des objets list. C’est une classe mère utile pour vos classes listes-compatibles qui peuvent en hériter et surcharger les méthodes existantes ou en ajouter de nouvelles. Ainsi, on peut ajouter de nouveaux comportements aux listes.

L’utilité de cette classe a été partiellement réduite par la possibilité d’hériter directement de list. Cependant, il peut être plus facile de travailler avec cette classe car la liste sous-jacente est accessible via un attribut.

class collections.UserList([list])

Classe simulant une liste. Les instances de UserList possèdent un attribut UserList où est stocké leur contenu sous forme de liste native. Il est initialement une copie de list, ou [] par défaut. list peut être un itérable, par exemple une liste native ou un objet UserList.

En plus de gérer les méthodes et opérations des séquences muables, les instances de UserList possèdent l’attribut suivant :

data

Un objet list natif utilisé pour stocker le contenu de la classe UserList.

Prérequis pour l’héritage : Les sous-classe de UserList doivent implémenter un constructeur qui peut être appelé avec zéro ou un argument. Les opérations sur les listes qui renvoient une nouvelle séquence essayent de créer une instance de la classe courante. C’est pour cela que le constructeur doit pouvoir être appelé avec un unique paramètre, un objet séquence utilisé comme source de données.

Si une classe fille ne remplit pas cette condition, toutes les méthodes spéciales gérées par cette classe devront être implémentées à nouveau. Merci de consulter les sources pour obtenir des informations sur les méthodes qui doivent être fournies dans ce cas.

8.3.9. Objets UserString

La classe UserString agit comme une surcouche autour des objets str. L’utilité de cette classe a été partiellement réduite par la possibilité d’hériter directement de str. Cependant, il peut être plus facile de travailler avec cette classe car la chaîne de caractère sous-jacente est accessible via un attribut.

class collections.UserString([sequence])

Class that simulates a string or a Unicode string object. The instance’s content is kept in a regular string object, which is accessible via the data attribute of UserString instances. The instance’s contents are initially set to a copy of sequence. The sequence can be an instance of bytes, str, UserString (or a subclass) or an arbitrary sequence which can be converted into a string using the built-in str() function.

Modifié dans la version 3.5: Nouvelles méthodes __getnewargs__, __rmod__, casefold, format_map, isprintable et maketrans.

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8.4. collections.abc — Classes de base abstraites pour les conteneurs

Nouveau dans la version 3.3: Auparavant, ce module faisait partie du module collections.

Code source : Lib/_collections_abc.py [https://github.com/python/cpython/tree/3.6/Lib/_collections_abc.py]

Ce module fournit des classes de base abstraites qui peuvent être utilisées pour vérifier si une classe fournit une interface particulière (par exemple, savoir s’il s’agit d’un hachable ou d’une table de correspondance).

8.4.1. Classes de base abstraites de collections

Le module collections apporte les ABC suivantes :

ABC

Hérite de

Méthodes abstraites

Méthodes mixin

Container

__contains__

Hashable

__hash__

Iterable

__iter__

Iterator

Iterable

__next__

__iter__

Reversible

Iterable

__reversed__

Generator

Iterator

send, throw

close, __iter__, __next__

Sized

__len__

Callable

__call__

Collection

Sized, Iterable, Container

__contains__, __iter__, __len__

Sequence

Reversible, Collection

__getitem__, __len__

__contains__, __iter__, __reversed__, index et count

MutableSequence

Sequence

__getitem__, __setitem__, __delitem__, __len__, insert

Méthodes héritées de Sequence, et append, reverse, extend, pop, remove et __iadd__

ByteString

Sequence

__getitem__, __len__

Méthodes héritées de Sequence

Set

Collection

__contains__, __iter__, __len__

__le__, __lt__, __eq__, __ne__, __gt__, __ge__, __and__, __or__, __sub__, __xor__ et isdisjoint

MutableSet

Set

__contains__, __iter__, __len__, add, discard

Méthodes héritées de Set, et clear, pop, remove, __ior__, __iand__, __ixor__ et __isub__

Mapping

Collection

__getitem__, __iter__, __len__

__contains__, keys, items, values, get, __eq__ et __ne__

MutableMapping

Mapping

__getitem__, __setitem__, __delitem__, __iter__, __len__

Méthodes héritées de Mapping, et pop, popitem, clear, update et setdefault

MappingView

Sized

__len__

ItemsView

MappingView, Set

__contains__, __iter__

KeysView

MappingView, Set

__contains__, __iter__

ValuesView

MappingView

__contains__, __iter__

Awaitable

__await__

Coroutine

Awaitable

send, throw

close

AsyncIterable

__aiter__

AsyncIterator

AsyncIterable

__anext__

__aiter__

AsyncGenerator

AsyncIterator

asend, athrow

aclose, __aiter__, __anext__

class collections.abc.Container

class collections.abc.Hashable

class collections.abc.Sized

class collections.abc.Callable

ABC pour les classes qui définissent respectivement les méthodes __contains__(), __hash__(), __len__() et __call__().

class collections.abc.Iterable

ABC pour les classes qui définissent la méthode __iter__().

Évaluer isinstance(obj, Iterable) détecte les classes qui sont enregistrées comme Iterable ou qui possèdent une méthode __iter__(), mais ne détecte pas les classes qui itèrent avec la méthode __getitem__(). Le seul moyen fiable de déterminer si un objet est itérable est d’appeler iter(obj).

class collections.abc.Collection

ABC pour les classes de conteneurs itérables et sized.

Nouveau dans la version 3.6.

class collections.abc.Iterator

ABC pour les classes qui définissent les méthodes __iter__() et __next__(). Voir aussi la définition d”itérateur.

class collections.abc.Reversible

ABC pour les classes d’itérables qui implémentent également la méthode __reversed__().

Nouveau dans la version 3.6.

class collections.abc.Generator

ABC pour les classes de générateurs qui implémentent le protocole défini dans la PEP 342 [https://www.python.org/dev/peps/pep-0342] qui étend les itérateurs avec les méthodes send(), throw() et close(). Voir aussi la définition de générateur.

Nouveau dans la version 3.5.

class collections.abc.Sequence

class collections.abc.MutableSequence

class collections.abc.ByteString

ABC pour les séquences immuables et muables.

Note pour l’implémentation : quelques méthodes mixin, comme __iter__(), __reversed__() et index(), font des appels répétés à la méthode sous-jacente __getitem__(). Ainsi, si __getitem__() est implémentée avec une vitesse d’accès constante, les méthodes mixin auront une performance linéaire ; cependant, si elle est linéaire, les mixin auront une performance quadratique, il serait alors judicieux de les surcharger.

Modifié dans la version 3.5: La méthode index() a ajouté le support des arguments start et stop.

class collections.abc.Set

class collections.abc.MutableSet

ABC pour les ensembles immuables et muables.

class collections.abc.Mapping

class collections.abc.MutableMapping

ABC pour les tables de correspondances immuables et muables.

class collections.abc.MappingView

class collections.abc.ItemsView

class collections.abc.KeysView

class collections.abc.ValuesView

ABC pour les vues de mappings (tableaux de correspondances), d’éléments, de clés et de valeurs.

class collections.abc.Awaitable

ABC pour les objets awaitables, qui peuvent être utilisés dans les expressions await. Les implémentations personnalisées doivent définir la méthode __await__().

Les objets coroutines et les instances de l’ABC Coroutine sont tous des instances de cette ABC.

Note

En CPython, les coroutines basées sur les générateurs (les générateurs décorés avec types.coroutine() ou asyncio.coroutine()) sont awaitables, bien qu’elles n’aient pas de méthode __await__(). Évaluer isinstance(gencoro, Awaitable) où gencoro est un générateur décoré va renvoyer False. Utilisez inspect.isawaitable() pour les détecter.

Nouveau dans la version 3.5.

class collections.abc.Coroutine

ABC pour les classes compatibles avec les coroutines. Elles implémentent les méthodes suivantes, définies dans Objets coroutines : send(), throw() et close(). Les implémentations personnalisées doivent également fournir __await__(). Toutes les instances de Coroutine sont également des instances de Awaitable. Voir aussi la définition de coroutine.

Note

En CPython, les coroutines basées sur les générateurs (les générateurs décorés avec types.coroutine() ou asyncio.coroutine()) sont awaitables, bien qu’elles n’aient pas de méthode __await__(). Évaluer isinstance(gencoro, Corourine) où gencoro est un générateur décoré va renvoyer False. Utilisez inspect.isawaitable() pour les détecter.

Nouveau dans la version 3.5.

class collections.abc.AsyncIterable

ABC pour les classes qui définissent la méthode __aiter__. Voir aussi la définition d”itérable asynchrone.

Nouveau dans la version 3.5.

class collections.abc.AsyncIterator

ABC pour les classes qui définissent les méthodes __aiter__ et __anext__. Voir aussi la définition d”itérateur asynchrone.

Nouveau dans la version 3.5.

class collections.abc.AsyncGenerator

ABC pour les classes de générateurs asynchrones qui implémentent le protocole défini dans la PEP 525 [https://www.python.org/dev/peps/pep-0525] et dans la PEP 492 [https://www.python.org/dev/peps/pep-0492].

Nouveau dans la version 3.6.

Ces ABC permettent de demander à des classes ou à des instances si elles fournissent des fonctionnalités particulières, par exemple :

size = None
if isinstance(myvar, collections.abc.Sized):
    size = len(myvar)

Une partie des ABC sont également utiles en tant que mixins : cela rend plus facile le développement de classes qui gèrent des API de conteneurs. Par exemple, pour écrire une classe qui gère l’API entière de Set, il est uniquement nécessaire de fournir les trois méthodes sous-jacentes abstraites __contains__(), __iter__() et __len__(). L’ABC apporte les méthodes restantes, comme __and__() et isdisjoint() :

class ListBasedSet(collections.abc.Set):
    ''' Alternate set implementation favoring space over speed
        and not requiring the set elements to be hashable. '''
    def __init__(self, iterable):
        self.elements = lst = []
        for value in iterable:
            if value not in lst:
                lst.append(value)

    def __iter__(self):
        return iter(self.elements)

    def __contains__(self, value):
        return value in self.elements

    def __len__(self):
        return len(self.elements)

s1 = ListBasedSet('abcdef')
s2 = ListBasedSet('defghi')
overlap = s1 & s2            # The __and__() method is supported automatically

Notes à propos de l’utilisation de Set et MutableSet comme mixin :

Comme une partie des opérations sur les ensembles créent de nouveaux ensembles, les méthodes mixins par défaut ont besoin d’un moyen de créer de nouvelles instances à partir d’un itérable. Le constructeur de classe est supposé avoir une signature de la forme ClassName(iterable). Cette supposition est faite par une méthode de classe interne appelée _from_iterable() qui appelle cls(iterable) pour construire un nouvel ensemble. Si le Set mixin est utilisé dans une classe avec un constructeur de signature différente, vous devrez surcharger _from_iterable() avec une méthode de classe qui peut construire de nouvelles instances à partir d’un argument itérable.

Pour surcharger les comparaisons (a priori pour la rapidité, puisque la sémantique est fixe), il faut redéfinir __le__() et __ge__(), puis les autres opérations seront automatiquement adaptées.

La classe mixin Set apporte une méthode _hash() pour calculer une valeur de hachage pour l’ensemble ; cependant __hash__() n’est pas défini car tous les ensembles ne sont pas hachables ou immuables. Pour rendre un ensemble hachable en utilisant les mixins, héritez de Set() et de Hashable(), puis définissez __hash__ = Set._hash.

Voir aussi

OrderedSet recipe [https://code.activestate.com/recipes/576694/] pour un exemple construit sur MutableSet.

Pour plus d’informations à propos des ABC, voir le module abc et la PEP 3119 [https://www.python.org/dev/peps/pep-3119].

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8.5. heapq — File de priorité basée sur un tas

Code source : Lib/heapq.py [https://github.com/python/cpython/tree/3.6/Lib/heapq.py]

Ce module expose une implémentation de l’algorithme de file de priorité, basée sur un tas.

Les tas sont des arbres binaires pour lesquels chaque valeur portée par un nœud est inférieure ou égale à celle de ses deux fils. Cette implémentation utilise des tableaux pour lesquels tas[k] <= tas[2*k+1] et tas[k] <= tas[2*k+2] pour tout k, en commençant la numérotation à zéro. Pour contenter l’opérateur de comparaison, les éléments inexistants sont considérés comme porteur d’une valeur infinie. L’intérêt du tas est que son plus petit élément est toujours la racine, tas[0].

L’API ci-dessous diffère de la file de priorité classique par deux aspects : (a) L’indiçage commence à zéro. Cela complexifie légèrement la relation entre l’indice d’un nœud et les indices de ses fils mais est alignée avec l’indiçage commençant à zéro que Python utilise. (b) La méthode pop renvoie le plus petit élément et non le plus grand (appelé « tas-min » dans les manuels scolaires ; le « tas-max » étant généralement plus courant dans la littérature car il permet le classement sans tampon).

Ces deux points permettent d’aborder le tas comme une liste Python standard sans surprise : heap[0] est le plus petit élément tandis que heap.sort() ne modifie pas le tas !

Pour créer un tas, utilisez une liste initialisée à [] ou bien utilisez une liste existante et transformez la en tas à l’aide de la fonction heapify().

Les fonctions suivantes sont fournies :

heapq.heappush(heap, item)

Introduit la valeur item dans le tas heap, en conservant l’invariance du tas.

heapq.heappop(heap)

Extraie le plus petit élément de heap en préservant l’invariant du tas. Si le tas est vide, une exception IndexError est levée. Pour accéder au plus petit élément sans le retirer, utilisez heap[0].

heapq.heappushpop(heap, item)

Introduit l’élément item dans le tas, puis extraie le plus petit élément de heap. Cette action combinée est plus efficace que heappush() suivie par un appel séparé à heappop().

heapq.heapify(x)

Transforme une liste x en un tas, sans utiliser de tampon et en temps linéaire.

heapq.heapreplace(heap, item)

Extraie le plus petit élément de heap et introduit le nouvel élément item. La taille du tas ne change pas. Si le tas est vide, une exception IndexError est levée.

Cette opération en une étape est plus efficace qu’un appel à heappop() suivi d’un appel à heappush() et est plus appropriée lorsque le tas est de taille fixe. La combinaison pop/push renvoie toujours un élément du tas et le remplace par item.

La valeur renvoyée peut être plus grande que l’élément item ajouté. Si cela n’est pas souhaitable, utilisez plutôt heappushpop() à la place. Sa combinaison push/pop renvoie le plus petit élément des deux valeurs et laisse la plus grande sur le tas.

Ce module contient également trois fonctions génériques utilisant les tas.

heapq.merge(*iterables, key=None, reverse=False)

Fusionne plusieurs entrées ordonnées en une unique sortie ordonnée (par exemple, fusionne des entrées datées provenant de multiples journaux applicatifs). Renvoie un iterator sur les valeurs ordonnées.

Similaire à sorted(itertools.chain(*iterables)) mais renvoie un itérable, ne stocke pas toutes les données en mémoire en une fois et suppose que chaque flux d’entrée est déjà classé (en ordre croissant).

A deux arguments optionnels qui doivent être fournis par mot clef.

key spécifie une key function d’un argument utilisée pour extraire une clef de comparaison de chaque élément de la liste. La valeur par défaut est None (compare les éléments directement).

reverse, une valeur booléenne. Si elle est True, la liste d’éléments est triée comme si toutes les comparaisons étaient inversées.

Modifié dans la version 3.5: Ajout des paramètres optionnels key et reverse.

heapq.nlargest(n, iterable, key=None)

Return a list with the n largest elements from the dataset defined by iterable. key, if provided, specifies a function of one argument that is used to extract a comparison key from each element in iterable (for example, key=str.lower). Equivalent to: sorted(iterable, key=key, reverse=True)[:n].

heapq.nsmallest(n, iterable, key=None)

Return a list with the n smallest elements from the dataset defined by iterable. key, if provided, specifies a function of one argument that is used to extract a comparison key from each element in iterable (for example, key=str.lower). Equivalent to: sorted(iterable, key=key)[:n].

Les deux fonctions précédentes sont les plus efficaces pour des petites valeurs de n. Pour de grandes valeurs, il est préférable d’utiliser la fonction sorted(). En outre, lorsque n==1, il est plus efficace d’utiliser les fonctions natives min() et max(). Si vous devez utiliser ces fonctions de façon répétée, il est préférable de transformer l’itérable en tas.

8.5.1. Exemples simples

Un tri par tas [https://fr.wikipedia.org/wiki/Tri_par_tas] peut être implémenté en introduisant toutes les valeurs dans un tas puis en effectuant l’extraction des éléments un par un :

>>> def heapsort(iterable):
...     h = []
...     for value in iterable:
...         heappush(h, value)
...     return [heappop(h) for i in range(len(h))]
...
>>> heapsort([1, 3, 5, 7, 9, 2, 4, 6, 8, 0])
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]

Ceci est similaire à sorted(iterable) mais, contrairement à sorted(), cette implémentation n’est pas stable.

Les éléments d’un tas peuvent être des n-uplets. C’est pratique pour assigner des valeurs de comparaison (par exemple, des priorités de tâches) en plus de l’élément qui est suivi :

>>> h = []
>>> heappush(h, (5, 'write code'))
>>> heappush(h, (7, 'release product'))
>>> heappush(h, (1, 'write spec'))
>>> heappush(h, (3, 'create tests'))
>>> heappop(h)
(1, 'write spec')

8.5.2. Notes d’implémentation de la file de priorité

Une file de priorité [https://fr.wikipedia.org/wiki/File_de_priorit%C3%A9] est une application courante des tas et présente plusieurs défis d’implémentation :

Stabilité du classement : comment s’assurer que deux tâches avec la même priorité sont renvoyées dans l’ordre de leur ajout ?

La comparaison des couples (priorité, tâche) échoue si les priorités sont identiques et que les tâches n’ont pas de relation d’ordre par défaut.

Si la priorité d’une tâche change, comment la déplacer à sa nouvelle position dans le tas ?

Si une tâche en attente doit être supprimée, comment la trouver et la supprimer de la file ?

Une solution aux deux premiers problèmes consiste à stocker les entrées sous forme de liste à 3 éléments incluant la priorité, le numéro d’ajout et la tâche. Le numéro d’ajout sert à briser les égalités de telle sorte que deux tâches avec la même priorité sont renvoyées dans l’ordre de leur insertion. Puisque deux tâches ne peuvent jamais avoir le même numéro d’ajout, la comparaison des triplets ne va jamais chercher à comparer des tâches entre elles.

Le problème restant consiste à trouver une tâche en attente et modifier sa priorité ou la supprimer. Trouver une tâche peut être réalisé à l’aide d’un dictionnaire pointant vers une entrée dans la file.

Supprimer une entrée ou changer sa priorité est plus difficile puisque cela romprait l’invariant de la structure de tas. Une solution possible est de marquer l’entrée comme supprimée et d’ajouter une nouvelle entrée avec sa priorité modifiée :

pq = []                         # list of entries arranged in a heap
entry_finder = {}               # mapping of tasks to entries
REMOVED = '<removed-task>'      # placeholder for a removed task
counter = itertools.count()     # unique sequence count

def add_task(task, priority=0):
    'Add a new task or update the priority of an existing task'
    if task in entry_finder:
        remove_task(task)
    count = next(counter)
    entry = [priority, count, task]
    entry_finder[task] = entry
    heappush(pq, entry)

def remove_task(task):
    'Mark an existing task as REMOVED.  Raise KeyError if not found.'
    entry = entry_finder.pop(task)
    entry[-1] = REMOVED

def pop_task():
    'Remove and return the lowest priority task. Raise KeyError if empty.'
    while pq:
        priority, count, task = heappop(pq)
        if task is not REMOVED:
            del entry_finder[task]
            return task
    raise KeyError('pop from an empty priority queue')

8.5.3. Théorie

Les tas sont des tableaux pour lesquels a[k] <= a[2*k+1] et a[k] <= a[2*k+2] pour tout k en comptant les éléments à partir de 0. Pour simplifier la comparaison, les éléments inexistants sont considérés comme étant infinis. L’intérêt des tas est que a[0] est toujours leur plus petit élément.

L’invariant étrange ci-dessus est une représentation efficace en mémoire d’un tournoi. Les nombres ci-dessous sont k et non a[k] :

                               0

              1                                 2

      3               4                5               6

  7       8       9       10      11      12      13      14

15 16   17 18   19 20   21 22   23 24   25 26   27 28   29 30

Dans l’arbre ci-dessus, chaque nœud k a pour enfants 2*k+1 et 2*k+2. Dans les tournois binaires habituels dans les compétitions sportives, chaque nœud est le vainqueur des deux nœuds inférieurs et nous pouvons tracer le chemin du vainqueur le long de l’arbre afin de voir qui étaient ses adversaires. Cependant, dans de nombreuses applications informatiques de ces tournois, nous n’avons pas besoin de produire l’historique du vainqueur. Afin d’occuper moins de mémoire, on remplace le vainqueur lors de sa promotion par un autre élément à un plus bas niveau. La règle devient alors qu’un nœud et les deux nœuds qu’il chapeaute contiennent trois éléments différents, mais le nœud supérieur « gagne » contre les deux nœuds inférieurs.

Si cet invariant de tas est vérifié à tout instant, alors l’élément à l’indice 0 est le vainqueur global. L’algorithme le plus simple pour le retirer et trouver le vainqueur « suivant » consiste à déplacer un perdant (par exemple le nœud 30 dans le diagramme ci-dessus) à la position 0, puis à faire redescendre cette nouvelle racine dans l’arbre en échangeant sa valeur avec celle d’un de ses fils jusqu’à ce que l’invariant soit rétabli. Cette approche a un coût logarithmique par rapport au nombre total d’éléments dans l’arbre. En itérant sur tous les éléments, le classement s’effectue en O(n log n) opérations.

Une propriété agréable de cet algorithme est qu’il possible d’insérer efficacement de nouveaux éléments en cours de classement, du moment que les éléments insérés ne sont pas « meilleurs » que le dernier élément qui a été extrait. Ceci s’avère très utile dans des simulations où l’arbre contient la liste des événements arrivants et que la condition de « victoire » est le plus petit temps d’exécution planifié. Lorsqu’un événement programme l’exécution d’autres événements, ceux-ci sont planifiés pour le futur et peuvent donc rejoindre le tas. Ainsi, le tas est une bonne structure pour implémenter un ordonnanceur (et c’est ce que j’ai utilisé pour mon séquenceur MIDI ☺).

Plusieurs structures ont été étudiées en détail pour implémenter des ordonnanceurs et les tas sont bien adaptés : ils sont raisonnablement rapides, leur vitesse est presque constante et le pire cas ne diffère pas trop du cas moyen. S’il existe des représentations qui sont plus efficaces en général, les pires cas peuvent être terriblement mauvais.

Les tas sont également très utiles pour ordonner les données sur de gros disques. Vous savez probablement qu’un gros tri implique la production de séquences pré-classées (dont la taille est généralement liée à la quantité de mémoire CPU disponible), suivie par une passe de fusion qui est généralement organisée de façon très intelligente 1. Il est très important que le classement initial produise des séquences les plus longues possibles. Les tournois sont une bonne façon d’arriver à ce résultat. Si, en utilisant toute la mémoire disponible pour stocker un tournoi, vous remplacez et faites percoler les éléments qui s’avèrent acceptables pour la séquence courante, vous produirez des séquences d’une taille égale au double de la mémoire pour une entrée aléatoire et bien mieux pour une entrée approximativement triée.

Qui plus est, si vous écrivez l’élément 0 sur le disque et que vous recevez en entrée un élément qui n’est pas adapté au tournoi actuel (parce que sa valeur « gagne » par rapport à la dernière valeur de sortie), alors il ne peut pas être stocké dans le tas donc la taille de ce dernier diminue. La mémoire libérée peut être réutilisée immédiatement pour progressivement construire un deuxième tas, qui croit à la même vitesse que le premier décroît. Lorsque le premier tas a complètement disparu, vous échangez les tas et démarrez une nouvelle séquence. Malin et plutôt efficace !

Pour résumer, les tas sont des structures de données qu’il est bon de connaître. Je les utilise dans quelques applications et je pense qu’il est bon de garder le module heap sous le coude. ☺

Notes

1

Les algorithmes de répartition de charge pour les disques, courants de nos jours, sont plus embêtants qu’utiles, en raison de la capacité des disques à réaliser des accès aléatoires. Sur les périphériques qui ne peuvent faire que de la lecture séquentielle, comme les gros lecteurs à bandes, le besoin était différent et il fallait être malin pour s’assurer (bien à l’avance) que chaque mouvement de bande serait le plus efficace possible (c’est-à-dire participerait au mieux à l”« avancée » de la fusion). Certaines cassettes pouvaient même lire à l’envers et cela était aussi utilisé pour éviter de remonter dans le temps. Croyez-moi, les bons tris sur bandes étaient spectaculaires à regarder ! Depuis la nuit des temps, trier a toujours été le Grand Art ! ☺

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8.6. bisect — Algorithme de bissection de listes

Code source : Lib/bisect.py [https://github.com/python/cpython/tree/3.6/Lib/bisect.py]

Ce module fournit des outils pour maintenir une liste triée sans avoir à la trier à chaque insertion. Il pourrait être plus rapide que l’approche classique pour de longues listes d’éléments dont les opérations de comparaison sont lourdes. Le module se nomme bisect car il utilise une approche simple par bissection. Si vous voulez un exemple de cet algorithme, le mieux est d’aller lire le code source de ce module (les conditions sur les limites y étant justes !).

Les fonctions suivantes sont fournies :

bisect.bisect_left(a, x, lo=0, hi=len(a))

Trouve le point d’insertion de x dans a permettant de conserver l’ordre. Les paramètres lo et hi permettent de limiter les emplacements à vérifier dans la liste, par défaut toute la liste est utilisée. Si x est déjà présent dans a, le point d’insertion proposé sera avant (à gauche) de l’entrée existante. Si a est déjà triée, la valeur renvoyée peut directement être utilisée comme premier paramètre de list.insert().

Le point d’insertion renvoyé, i, coupe la liste a en deux moitiés telles que, pour la moitié de gauche : all(val < x for val in a[lo:i]), et pour la partie de droite : all(val >= x for val in a[i:hi]).

bisect.bisect_right(a, x, lo=0, hi=len(a))

bisect.bisect(a, x, lo=0, hi=len(a))

Semblable à bisect_left(), mais renvoie un point d’insertion après (à droite) d’une potentielle entrée existante valant x dans a.

Le point d’insertion renvoyé, i, coupe la liste a en deux moitiés telles que, pour la moitié de gauche : all(val <= x for val in a[lo:i]) et pour la moitié de droite : all(val > x for val in a[i:hi]).

bisect.insort_left(a, x, lo=0, hi=len(a))

Insère x dans a en conservant le tri. C’est l’équivalent de a.insert(bisect.bisect_left(a, x, lo, hi), x), tant que a est déjà triée. Gardez en tête que bien que la recherche ne coûte que O(log n), l’insertion coûte O(n).

bisect.insort_right(a, x, lo=0, hi=len(a))

bisect.insort(a, x, lo=0, hi=len(a))

Similaire à insort_left(), mais en insérant x dans a après une potentielle entrée existante égale à x.

Voir aussi

SortedCollection recipe [https://code.activestate.com/recipes/577197-sortedcollection/] utilise le module bisect pour construire une classe collection exposant des méthodes de recherches naturelles et gérant une fonction clef. Les clefs sont pré-calculées pour économiser des appels inutiles à la fonction clef durant les recherches.

8.6.1. Chercher dans des listes triées

Les fonctions bisect() ci-dessus sont utiles pour insérer des éléments, mais peuvent être étranges et peu naturelles à utiliser pour rechercher des éléments. Les cinq fonctions suivantes montrent comment les transformer en recherche plus classique pour les listes triées :

def index(a, x):
    'Locate the leftmost value exactly equal to x'
    i = bisect_left(a, x)
    if i != len(a) and a[i] == x:
        return i
    raise ValueError

def find_lt(a, x):
    'Find rightmost value less than x'
    i = bisect_left(a, x)
    if i:
        return a[i-1]
    raise ValueError

def find_le(a, x):
    'Find rightmost value less than or equal to x'
    i = bisect_right(a, x)
    if i:
        return a[i-1]
    raise ValueError

def find_gt(a, x):
    'Find leftmost value greater than x'
    i = bisect_right(a, x)
    if i != len(a):
        return a[i]
    raise ValueError

def find_ge(a, x):
    'Find leftmost item greater than or equal to x'
    i = bisect_left(a, x)
    if i != len(a):
        return a[i]
    raise ValueError

8.6.2. Autres Exemples

La fonction bisect() peut être utile pour des recherches dans des tableaux de nombres. Cet exemple utilise bisect() pour rechercher la note (sous forme de lettre) correspondant à un note sous forme de points, en se basant sur une échelle prédéfinie : plus de 90 vaut “A”, de 80 à 89 vaut “B”, etc… :

>>> def grade(score, breakpoints=[60, 70, 80, 90], grades='FDCBA'):
...     i = bisect(breakpoints, score)
...     return grades[i]
...
>>> [grade(score) for score in [33, 99, 77, 70, 89, 90, 100]]
['F', 'A', 'C', 'C', 'B', 'A', 'A']

Contrairement à la fonction sorted(), ça n’aurait pas de sens pour la fonction bisect() d’avoir un paramètre key ou reversed, qui conduiraient à une utilisation inefficace (des appels successifs à la fonction bisect n’auraient aucun moyen de se « souvenir » des recherches de clef précédentes).

Il est préférable d’utiliser une liste de clefs pré-calculée pour chercher l’index de l’enregistrement en question :

>>> data = [('red', 5), ('blue', 1), ('yellow', 8), ('black', 0)]
>>> data.sort(key=lambda r: r[1])
>>> keys = [r[1] for r in data]         # precomputed list of keys
>>> data[bisect_left(keys, 0)]
('black', 0)
>>> data[bisect_left(keys, 1)]
('blue', 1)
>>> data[bisect_left(keys, 5)]
('red', 5)
>>> data[bisect_left(keys, 8)]
('yellow', 8)

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8.7. array — Tableaux efficaces de valeurs numériques

Ce module définit un type d’objet qui permet de représenter de façon compacte un tableau (array) de valeurs élémentaires : caractères, entiers, flottants. Les tableaux sont de type séquence et se comportent de manière très similaire aux listes, sauf que les types d’objets qui y sont stockés sont limités. Le type est spécifié au moment de la création de l’objet en utilisant type code, qui est un caractère unique. Voir ci-dessous pour la définition des types :

Code d’indication du type

Type C

Type Python

Taille minimum en octets

Notes

'b'

signed char

int

1

'B'

unsigned char

int

1

'u'

Py_UNICODE

Caractère Unicode

2

(1)

'h'

signed short

int

2

'H'

unsigned short

int

2

'i'

signed int

int

2

'I'

unsigned int

int

2

'l'

signed long

int

4

'L'

unsigned long

int

4

'q'

signed long long

int

8

(2)

'Q'

unsigned long long

int

8

(2)

'f'

float

float

4

'd'

double

float

8

Notes :

Le code de type 'u' correspond au type obsolète de Python caractère Unicode (Py_UNICODE de type wchar_t). Selon la plateforme, il peut être 16 bits ou 32 bits.

'u' sera supprimé avec le reste de l’API Py_UNICODE.

Deprecated since version 3.3, will be removed in version 4.0.

Les codes de type 'q' et 'Q' ne sont disponibles que si le compilateur C de la plateforme utilisé pour construire Python gère le type C long long, ou, sur Windows, __int64.

Nouveau dans la version 3.3.

La représentation réelle des valeurs est déterminée par l’architecture de la machine (à proprement parler, par l’implémentation C). La taille réelle est accessible via l’attribut itemsize.

Le module définit le type suivant :

class array.array(typecode[, initializer])

Un nouveau tableau dont les éléments sont limités par typecode, et initialisés par la valeur optionnelle initializer, qui peut être une liste, un bytes-like object, ou un itérable sur des éléments du type approprié.

Si le paramètre initializer est une liste ou une chaîne de caractères, il est passé à la méthode fromlist(), frombytes() ou fromunicode() du tableau (voir ci-dessous) pour ajouter les éléments initiaux du tableau. Si c’est un itérable, il est passé à la méthode extend().

array.typecodes

Une chaîne avec tous les codes de types disponibles.

Les objets de tableau supportent les opérations classiques de séquence : indiçage, découpage, concaténation et multiplication. Lors de l’utilisation de tranche, la valeur assignée doit être un tableau du même type ; dans tous les autres cas, l’exception TypeError est levée. Les objets de tableau implémentent également l’interface tampon, et peuvent être utilisés partout où bytes-like objects sont supportés.

Les éléments de données et méthodes suivants sont également supportés :

array.typecode

Le code (de type Python caractère) utilisé pour spécifier le type des éléments du tableau.

array.itemsize

La longueur en octets d’un élément du tableau dans la représentation interne.

array.append(x)

Ajoute un nouvel élément avec la valeur x à la fin du tableau.

array.buffer_info()

Renvoie un tuple (address, length) indiquant l’adresse mémoire courante et la longueur en éléments du tampon utilisé pour contenir le contenu du tableau. La taille du tampon mémoire en octets peut être calculée par array.buffer_info()[1] * array.itemsize. Ceci est parfois utile lorsque vous travaillez sur des interfaces E/S de bas niveau (et intrinsèquement dangereuses) qui nécessitent des adresses mémoire, telles que certaines opérations ioctl(). Les nombres renvoyés sont valides tant que le tableau existe et qu’aucune opération qui modifie sa taille ne lui est appliquée.

Note

Lors de l’utilisation d’objets tableaux provenant de codes écrits en C ou C++ (le seul moyen d’utiliser efficacement ces informations), il est plus logique d’utiliser l’interface tampon supportée par les objets tableaux. Cette méthode est maintenue pour des raisons de rétrocompatibilité et devrait être évitée dans un nouveau code. L’interface tampon est documentée dans Protocole tampon.

array.byteswap()

Boutisme de tous les éléments du tableau. Ceci n’est pris en charge que pour les valeurs de 1, 2, 4 ou 8 octets ; pour les autres types de valeur, RuntimeError est levée. Il est utile lors de la lecture de données à partir d’un fichier écrit sur une machine avec un ordre d’octets différent.

array.count(x)

Renvoi le nombre d’occurrences de x dans le tableau.

array.extend(iterable)

Ajoute les éléments de iterable à la fin du tableau. Si iterable est un autre tableau, il doit le même code d’indication du type ; dans le cas contraire, TypeError sera levée. Si iterable n’est pas un tableau, il doit être itérable et ces éléments doivent être du bon type pour être ajoutés dans le tableau.

array.frombytes(s)

Ajoute des éléments de la chaîne, interprétant la chaîne comme un tableau de valeurs machine (comme si elle avait été lue depuis le fichier en utilisant la méthode from file()).

Nouveau dans la version 3.2: fromstring() est renommée en frombytes() pour plus de lisibilité.

array.fromfile(f, n)

Lit n éléments (en tant que valeurs machine) du file object f et les ajouter à la fin du tableau. Si moins de n éléments sont disponibles, EOFError est levée, mais les éléments qui étaient disponibles sont tout de même insérés dans le tableau. f doit être un objet fichier natif ; quelque chose d’autre avec une méthode read() ne suffit pas.

array.fromlist(list)

Ajoute les éléments de la liste. C’est l’équivalent de for x in list: a.append(x) sauf que s’il y a une erreur de type, le tableau est inchangé.

array.fromstring()

Alias obsolète de frombytes().

array.fromunicode(s)

Étend ce tableau avec les données de la chaîne Unicode donnée. Le tableau doit être de type 'u' ; sinon ValueError est levée. Utiliser array.frombytes(unicodestring.encode(enc)) pour ajouter des données Unicode à un tableau d’un autre type.

array.index(x)

Renvoie le plus petit i tel que i est l’index de la première occurrence de x dans le tableau.

array.insert(i, x)

Ajoute un nouvel élément avec la valeur x dans le tableau avant la position i. Les valeurs négatives sont traitées relativement à la fin du tableau.

array.pop([i])

Supprime l’élément du tableau avec l’index i et le renvoie. L’argument optionnel par défaut est à -1, de sorte que par défaut le dernier élément est supprimé et renvoyé.

array.remove(x)

Supprime la première occurrence de x du tableau.

array.reverse()

Inverse l’ordre des éléments du tableau.

array.tobytes()

Convertit le tableau en un tableau de valeurs machine et renvoie la représentation en octets (la même séquence d’octets qui serait écrite par la méthode tofile()).

Nouveau dans la version 3.2: tostring() est renommé en tobytes() pour plus de lisibilité.

array.tofile(f)

Écrit tous les éléments (en tant que valeurs machine) du file object f.

array.tolist()

Convertit le tableau en une liste ordinaire avec les mêmes éléments.

array.tostring()

Alias obsolète de tobytes().

array.tounicode()

Convertit le tableau en une chaîne Unicode. Le tableau doit être un tableau de type 'u' ; sinon ValueError est levée. Utilisez array.tobytes().decode(enc) pour obtenir une chaîne Unicode depuis un tableau de tout autre type.

Quand un objet tableau est affiché ou converti en chaîne, il est représenté en tant que array(typecode, initializer). initializer est omis si le tableau est vide, sinon c’est une chaine si le typecode est 'u', sinon c’est une liste de nombres. Il est garanti que la chaîne puisse être convertie en un tableau avec le même type et la même valeur en utilisant eval(), tant que la classe array a été importée en utilisant from array import array. Exemples :

array('l')
array('u', 'hello \u2641')
array('l', [1, 2, 3, 4, 5])
array('d', [1.0, 2.0, 3.14])

Voir aussi

Module struct

Empaquetage et dépaquetage de données binaires hétérogènes.

Module xdrlib

Empaquetage et dépaquetage des données XDR (External Data Representation) telles qu’elles sont utilisées dans certains systèmes d’appels de procédures à distance (ou RPC pour remote procedure call en anglais).

La documentation de *Numerical Python* <https://docs.scipy.org/doc/>

L’extension Numeric Python (NumPy) définit un autre type de tableau ; voir http://www.numpy.org/ pour plus d’informations sur Numeric Python.

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8.8. weakref — Weak references

Code source : Lib/weakref.py [https://github.com/python/cpython/tree/3.6/Lib/weakref.py]

The weakref module allows the Python programmer to create weak references to objects.

In the following, the term referent means the object which is referred to by a weak reference.

A weak reference to an object is not enough to keep the object alive: when the only remaining references to a referent are weak references, garbage collection is free to destroy the referent and reuse its memory for something else. However, until the object is actually destroyed the weak reference may return the object even if there are no strong references to it.

A primary use for weak references is to implement caches or mappings holding large objects, where it’s desired that a large object not be kept alive solely because it appears in a cache or mapping.

For example, if you have a number of large binary image objects, you may wish to associate a name with each. If you used a Python dictionary to map names to images, or images to names, the image objects would remain alive just because they appeared as values or keys in the dictionaries. The WeakKeyDictionary and WeakValueDictionary classes supplied by the weakref module are an alternative, using weak references to construct mappings that don’t keep objects alive solely because they appear in the mapping objects. If, for example, an image object is a value in a WeakValueDictionary, then when the last remaining references to that image object are the weak references held by weak mappings, garbage collection can reclaim the object, and its corresponding entries in weak mappings are simply deleted.

WeakKeyDictionary and WeakValueDictionary use weak references in their implementation, setting up callback functions on the weak references that notify the weak dictionaries when a key or value has been reclaimed by garbage collection. WeakSet implements the set interface, but keeps weak references to its elements, just like a WeakKeyDictionary does.

finalize provides a straight forward way to register a cleanup function to be called when an object is garbage collected. This is simpler to use than setting up a callback function on a raw weak reference, since the module automatically ensures that the finalizer remains alive until the object is collected.

Most programs should find that using one of these weak container types or finalize is all they need – it’s not usually necessary to create your own weak references directly. The low-level machinery is exposed by the weakref module for the benefit of advanced uses.

Not all objects can be weakly referenced; those objects which can include class instances, functions written in Python (but not in C), instance methods, sets, frozensets, some file objects, generators, type objects, sockets, arrays, deques, regular expression pattern objects, and code objects.

Modifié dans la version 3.2: Added support for thread.lock, threading.Lock, and code objects.

Several built-in types such as list and dict do not directly support weak references but can add support through subclassing:

class Dict(dict):
    pass

obj = Dict(red=1, green=2, blue=3)   # this object is weak referenceable

Other built-in types such as tuple and int do not support weak references even when subclassed (This is an implementation detail and may be different across various Python implementations.).

Extension types can easily be made to support weak references; see Weak Reference Support.

class weakref.ref(object[, callback])

Return a weak reference to object. The original object can be retrieved by calling the reference object if the referent is still alive; if the referent is no longer alive, calling the reference object will cause None to be returned. If callback is provided and not None, and the returned weakref object is still alive, the callback will be called when the object is about to be finalized; the weak reference object will be passed as the only parameter to the callback; the referent will no longer be available.

It is allowable for many weak references to be constructed for the same object. Callbacks registered for each weak reference will be called from the most recently registered callback to the oldest registered callback.

Exceptions raised by the callback will be noted on the standard error output, but cannot be propagated; they are handled in exactly the same way as exceptions raised from an object’s __del__() method.

Weak references are hashable if the object is hashable. They will maintain their hash value even after the object was deleted. If hash() is called the first time only after the object was deleted, the call will raise TypeError.

Weak references support tests for equality, but not ordering. If the referents are still alive, two references have the same equality relationship as their referents (regardless of the callback). If either referent has been deleted, the references are equal only if the reference objects are the same object.

This is a subclassable type rather than a factory function.

__callback__

This read-only attribute returns the callback currently associated to the weakref. If there is no callback or if the referent of the weakref is no longer alive then this attribute will have value None.

Modifié dans la version 3.4: Added the __callback__ attribute.

weakref.proxy(object[, callback])

Return a proxy to object which uses a weak reference. This supports use of the proxy in most contexts instead of requiring the explicit dereferencing used with weak reference objects. The returned object will have a type of either ProxyType or CallableProxyType, depending on whether object is callable. Proxy objects are not hashable regardless of the referent; this avoids a number of problems related to their fundamentally mutable nature, and prevent their use as dictionary keys. callback is the same as the parameter of the same name to the ref() function.

weakref.getweakrefcount(object)

Return the number of weak references and proxies which refer to object.

weakref.getweakrefs(object)

Return a list of all weak reference and proxy objects which refer to object.

class weakref.WeakKeyDictionary([dict])

Mapping class that references keys weakly. Entries in the dictionary will be discarded when there is no longer a strong reference to the key. This can be used to associate additional data with an object owned by other parts of an application without adding attributes to those objects. This can be especially useful with objects that override attribute accesses.

Note

Caution: Because a WeakKeyDictionary is built on top of a Python dictionary, it must not change size when iterating over it. This can be difficult to ensure for a WeakKeyDictionary because actions performed by the program during iteration may cause items in the dictionary to vanish « by magic » (as a side effect of garbage collection).

WeakKeyDictionary objects have an additional method that exposes the internal references directly. The references are not guaranteed to be « live » at the time they are used, so the result of calling the references needs to be checked before being used. This can be used to avoid creating references that will cause the garbage collector to keep the keys around longer than needed.

WeakKeyDictionary.keyrefs()

Return an iterable of the weak references to the keys.

class weakref.WeakValueDictionary([dict])

Mapping class that references values weakly. Entries in the dictionary will be discarded when no strong reference to the value exists any more.

Note

Caution: Because a WeakValueDictionary is built on top of a Python dictionary, it must not change size when iterating over it. This can be difficult to ensure for a WeakValueDictionary because actions performed by the program during iteration may cause items in the dictionary to vanish « by magic » (as a side effect of garbage collection).

WeakValueDictionary objects have an additional method that has the same issues as the keyrefs() method of WeakKeyDictionary objects.

WeakValueDictionary.valuerefs()

Return an iterable of the weak references to the values.

class weakref.WeakSet([elements])

Set class that keeps weak references to its elements. An element will be discarded when no strong reference to it exists any more.

class weakref.WeakMethod(method)

A custom ref subclass which simulates a weak reference to a bound method (i.e., a method defined on a class and looked up on an instance). Since a bound method is ephemeral, a standard weak reference cannot keep hold of it. WeakMethod has special code to recreate the bound method until either the object or the original function dies:

>>> class C:
...     def method(self):
...         print("method called!")
...
>>> c = C()
>>> r = weakref.ref(c.method)
>>> r()
>>> r = weakref.WeakMethod(c.method)
>>> r()
<bound method C.method of <__main__.C object at 0x7fc859830220>>
>>> r()()
method called!
>>> del c
>>> gc.collect()
0
>>> r()
>>>

Nouveau dans la version 3.4.

class weakref.finalize(obj, func, *args, **kwargs)

Return a callable finalizer object which will be called when obj is garbage collected. Unlike an ordinary weak reference, a finalizer will always survive until the reference object is collected, greatly simplifying lifecycle management.

A finalizer is considered alive until it is called (either explicitly or at garbage collection), and after that it is dead. Calling a live finalizer returns the result of evaluating func(*arg, **kwargs), whereas calling a dead finalizer returns None.

Exceptions raised by finalizer callbacks during garbage collection will be shown on the standard error output, but cannot be propagated. They are handled in the same way as exceptions raised from an object’s __del__() method or a weak reference’s callback.

When the program exits, each remaining live finalizer is called unless its atexit attribute has been set to false. They are called in reverse order of creation.

A finalizer will never invoke its callback during the later part of the interpreter shutdown when module globals are liable to have been replaced by None.

__call__()

If self is alive then mark it as dead and return the result of calling func(*args, **kwargs). If self is dead then return None.

detach()

If self is alive then mark it as dead and return the tuple (obj, func, args, kwargs). If self is dead then return None.

peek()

If self is alive then return the tuple (obj, func, args, kwargs). If self is dead then return None.

alive

Property which is true if the finalizer is alive, false otherwise.

atexit

A writable boolean property which by default is true. When the program exits, it calls all remaining live finalizers for which atexit is true. They are called in reverse order of creation.

Note

It is important to ensure that func, args and kwargs do not own any references to obj, either directly or indirectly, since otherwise obj will never be garbage collected. In particular, func should not be a bound method of obj.

Nouveau dans la version 3.4.

weakref.ReferenceType

The type object for weak references objects.

weakref.ProxyType

The type object for proxies of objects which are not callable.

weakref.CallableProxyType

The type object for proxies of callable objects.

weakref.ProxyTypes

Sequence containing all the type objects for proxies. This can make it simpler to test if an object is a proxy without being dependent on naming both proxy types.

exception weakref.ReferenceError

Exception raised when a proxy object is used but the underlying object has been collected. This is the same as the standard ReferenceError exception.

Voir aussi

PEP 205 [https://www.python.org/dev/peps/pep-0205] - Weak References

The proposal and rationale for this feature, including links to earlier implementations and information about similar features in other languages.

8.8.1. Objets à références faibles

Weak reference objects have no methods and no attributes besides ref.__callback__. A weak reference object allows the referent to be obtained, if it still exists, by calling it:

>>> import weakref
>>> class Object:
...     pass
...
>>> o = Object()
>>> r = weakref.ref(o)
>>> o2 = r()
>>> o is o2
True

If the referent no longer exists, calling the reference object returns None:

>>> del o, o2
>>> print(r())
None

Testing that a weak reference object is still live should be done using the expression ref() is not None. Normally, application code that needs to use a reference object should follow this pattern:

# r is a weak reference object
o = r()
if o is None:
    # referent has been garbage collected
    print("Object has been deallocated; can't frobnicate.")
else:
    print("Object is still live!")
    o.do_something_useful()

Using a separate test for « liveness » creates race conditions in threaded applications; another thread can cause a weak reference to become invalidated before the weak reference is called; the idiom shown above is safe in threaded applications as well as single-threaded applications.

Specialized versions of ref objects can be created through subclassing. This is used in the implementation of the WeakValueDictionary to reduce the memory overhead for each entry in the mapping. This may be most useful to associate additional information with a reference, but could also be used to insert additional processing on calls to retrieve the referent.

This example shows how a subclass of ref can be used to store additional information about an object and affect the value that’s returned when the referent is accessed:

import weakref

class ExtendedRef(weakref.ref):
    def __init__(self, ob, callback=None, **annotations):
        super(ExtendedRef, self).__init__(ob, callback)
        self.__counter = 0
        for k, v in annotations.items():
            setattr(self, k, v)

    def __call__(self):
        """Return a pair containing the referent and the number of
        times the reference has been called.
        """
        ob = super(ExtendedRef, self).__call__()
        if ob is not None:
            self.__counter += 1
            ob = (ob, self.__counter)
        return ob

8.8.2. Exemple

This simple example shows how an application can use object IDs to retrieve objects that it has seen before. The IDs of the objects can then be used in other data structures without forcing the objects to remain alive, but the objects can still be retrieved by ID if they do.

import weakref

_id2obj_dict = weakref.WeakValueDictionary()

def remember(obj):
    oid = id(obj)
    _id2obj_dict[oid] = obj
    return oid

def id2obj(oid):
    return _id2obj_dict[oid]

8.8.3. Finalizer Objects

The main benefit of using finalize is that it makes it simple to register a callback without needing to preserve the returned finalizer object. For instance

>>> import weakref
>>> class Object:
...     pass
...
>>> kenny = Object()
>>> weakref.finalize(kenny, print, "You killed Kenny!")
<finalize object at ...; for 'Object' at ...>
>>> del kenny
You killed Kenny!

The finalizer can be called directly as well. However the finalizer will invoke the callback at most once.

>>> def callback(x, y, z):
...     print("CALLBACK")
...     return x + y + z
...
>>> obj = Object()
>>> f = weakref.finalize(obj, callback, 1, 2, z=3)
>>> assert f.alive
>>> assert f() == 6
CALLBACK
>>> assert not f.alive
>>> f()                     # callback not called because finalizer dead
>>> del obj                 # callback not called because finalizer dead

You can unregister a finalizer using its detach() method. This kills the finalizer and returns the arguments passed to the constructor when it was created.

>>> obj = Object()
>>> f = weakref.finalize(obj, callback, 1, 2, z=3)
>>> f.detach()
(<__main__.Object object ...>, <function callback ...>, (1, 2), {'z': 3})
>>> newobj, func, args, kwargs = _
>>> assert not f.alive
>>> assert newobj is obj
>>> assert func(*args, **kwargs) == 6
CALLBACK

Unless you set the atexit attribute to False, a finalizer will be called when the program exits if it is still alive. For instance

>>> obj = Object()
>>> weakref.finalize(obj, print, "obj dead or exiting")
<finalize object at ...; for 'Object' at ...>
>>> exit()
obj dead or exiting

8.8.4. Comparing finalizers with __del__() methods

Suppose we want to create a class whose instances represent temporary directories. The directories should be deleted with their contents when the first of the following events occurs:

the object is garbage collected,

the object’s remove() method is called, or

the program exits.

We might try to implement the class using a __del__() method as follows:

class TempDir:
    def __init__(self):
        self.name = tempfile.mkdtemp()

    def remove(self):
        if self.name is not None:
            shutil.rmtree(self.name)
            self.name = None

    @property
    def removed(self):
        return self.name is None

    def __del__(self):
        self.remove()

Starting with Python 3.4, __del__() methods no longer prevent reference cycles from being garbage collected, and module globals are no longer forced to None during interpreter shutdown. So this code should work without any issues on CPython.

However, handling of __del__() methods is notoriously implementation specific, since it depends on internal details of the interpreter’s garbage collector implementation.

A more robust alternative can be to define a finalizer which only references the specific functions and objects that it needs, rather than having access to the full state of the object:

class TempDir:
    def __init__(self):
        self.name = tempfile.mkdtemp()
        self._finalizer = weakref.finalize(self, shutil.rmtree, self.name)

    def remove(self):
        self._finalizer()

    @property
    def removed(self):
        return not self._finalizer.alive

Defined like this, our finalizer only receives a reference to the details it needs to clean up the directory appropriately. If the object never gets garbage collected the finalizer will still be called at exit.

The other advantage of weakref based finalizers is that they can be used to register finalizers for classes where the definition is controlled by a third party, such as running code when a module is unloaded:

import weakref, sys
def unloading_module():
    # implicit reference to the module globals from the function body
weakref.finalize(sys.modules[__name__], unloading_module)

Note

If you create a finalizer object in a daemonic thread just as the program exits then there is the possibility that the finalizer does not get called at exit. However, in a daemonic thread atexit.register(), try: ... finally: ... and with: ... do not guarantee that cleanup occurs either.

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8.9. types — Dynamic type creation and names for built-in types

Code source : Lib/types.py [https://github.com/python/cpython/tree/3.6/Lib/types.py]

This module defines utility function to assist in dynamic creation of new types.

It also defines names for some object types that are used by the standard Python interpreter, but not exposed as builtins like int or str are.

Finally, it provides some additional type-related utility classes and functions that are not fundamental enough to be builtins.

8.9.1. Dynamic Type Creation

types.new_class(name, bases=(), kwds=None, exec_body=None)

Creates a class object dynamically using the appropriate metaclass.

The first three arguments are the components that make up a class definition header: the class name, the base classes (in order), the keyword arguments (such as metaclass).

The exec_body argument is a callback that is used to populate the freshly created class namespace. It should accept the class namespace as its sole argument and update the namespace directly with the class contents. If no callback is provided, it has the same effect as passing in lambda ns: ns.

Nouveau dans la version 3.3.

types.prepare_class(name, bases=(), kwds=None)

Calculates the appropriate metaclass and creates the class namespace.

The arguments are the components that make up a class definition header: the class name, the base classes (in order) and the keyword arguments (such as metaclass).

The return value is a 3-tuple: metaclass, namespace, kwds

metaclass is the appropriate metaclass, namespace is the prepared class namespace and kwds is an updated copy of the passed in kwds argument with any 'metaclass' entry removed. If no kwds argument is passed in, this will be an empty dict.

Nouveau dans la version 3.3.

Modifié dans la version 3.6: The default value for the namespace element of the returned tuple has changed. Now an insertion-order-preserving mapping is used when the metaclass does not have a __prepare__ method,

Voir aussi

Méta-classes

Full details of the class creation process supported by these functions

PEP 3115 [https://www.python.org/dev/peps/pep-3115] — Méta-classes dans Python 3000

introduction de la fonction automatique __prepare__ de l’espace de nommage

8.9.2. Standard Interpreter Types

This module provides names for many of the types that are required to implement a Python interpreter. It deliberately avoids including some of the types that arise only incidentally during processing such as the listiterator type.

Typical use of these names is for isinstance() or issubclass() checks.

Standard names are defined for the following types:

types.FunctionType

types.LambdaType

The type of user-defined functions and functions created by lambda expressions.

types.GeneratorType

The type of generator-iterator objects, created by generator functions.

types.CoroutineType

The type of coroutine objects, created by async def functions.

Nouveau dans la version 3.5.

types.AsyncGeneratorType

The type of asynchronous generator-iterator objects, created by asynchronous generator functions.

Nouveau dans la version 3.6.

types.CodeType

The type for code objects such as returned by compile().

types.MethodType

The type of methods of user-defined class instances.

types.BuiltinFunctionType

types.BuiltinMethodType

The type of built-in functions like len() or sys.exit(), and methods of built-in classes. (Here, the term « built-in » means « written in C ».)

class types.ModuleType(name, doc=None)

The type of modules. Constructor takes the name of the module to be created and optionally its docstring.

Note

Use importlib.util.module_from_spec() to create a new module if you wish to set the various import-controlled attributes.

__doc__

The docstring of the module. Defaults to None.

__loader__

The loader which loaded the module. Defaults to None.

Modifié dans la version 3.4: Defaults to None. Previously the attribute was optional.

__name__

The name of the module.

__package__

Which package a module belongs to. If the module is top-level (i.e. not a part of any specific package) then the attribute should be set to '', else it should be set to the name of the package (which can be __name__ if the module is a package itself). Defaults to None.

Modifié dans la version 3.4: Defaults to None. Previously the attribute was optional.

types.TracebackType

The type of traceback objects such as found in sys.exc_info()[2].

types.FrameType

The type of frame objects such as found in tb.tb_frame if tb is a traceback object.

types.GetSetDescriptorType

The type of objects defined in extension modules with PyGetSetDef, such as FrameType.f_locals or array.array.typecode. This type is used as descriptor for object attributes; it has the same purpose as the property type, but for classes defined in extension modules.

types.MemberDescriptorType

The type of objects defined in extension modules with PyMemberDef, such as datetime.timedelta.days. This type is used as descriptor for simple C data members which use standard conversion functions; it has the same purpose as the property type, but for classes defined in extension modules.

CPython implementation detail: In other implementations of Python, this type may be identical to GetSetDescriptorType.

class types.MappingProxyType(mapping)

Read-only proxy of a mapping. It provides a dynamic view on the mapping’s entries, which means that when the mapping changes, the view reflects these changes.

Nouveau dans la version 3.3.

key in proxy

Return True if the underlying mapping has a key key, else False.

proxy[key]

Return the item of the underlying mapping with key key. Raises a KeyError if key is not in the underlying mapping.

iter(proxy)

Return an iterator over the keys of the underlying mapping. This is a shortcut for iter(proxy.keys()).

len(proxy)

Return the number of items in the underlying mapping.

copy()

Return a shallow copy of the underlying mapping.

get(key[, default])

Return the value for key if key is in the underlying mapping, else default. If default is not given, it defaults to None, so that this method never raises a KeyError.

items()

Return a new view of the underlying mapping’s items ((key, value) pairs).

keys()

Return a new view of the underlying mapping’s keys.

values()

Return a new view of the underlying mapping’s values.

8.9.3. Additional Utility Classes and Functions

class types.SimpleNamespace

A simple object subclass that provides attribute access to its namespace, as well as a meaningful repr.

Unlike object, with SimpleNamespace you can add and remove attributes. If a SimpleNamespace object is initialized with keyword arguments, those are directly added to the underlying namespace.

The type is roughly equivalent to the following code:

class SimpleNamespace:
    def __init__(self, **kwargs):
        self.__dict__.update(kwargs)

    def __repr__(self):
        keys = sorted(self.__dict__)
        items = ("{}={!r}".format(k, self.__dict__[k]) for k in keys)
        return "{}({})".format(type(self).__name__, ", ".join(items))

    def __eq__(self, other):
        return self.__dict__ == other.__dict__

SimpleNamespace may be useful as a replacement for class NS: pass. However, for a structured record type use namedtuple() instead.

Nouveau dans la version 3.3.

types.DynamicClassAttribute(fget=None, fset=None, fdel=None, doc=None)

Route attribute access on a class to __getattr__.

This is a descriptor, used to define attributes that act differently when accessed through an instance and through a class. Instance access remains normal, but access to an attribute through a class will be routed to the class’s __getattr__ method; this is done by raising AttributeError.

This allows one to have properties active on an instance, and have virtual attributes on the class with the same name (see Enum for an example).

Nouveau dans la version 3.4.

8.9.4. Coroutine Utility Functions

types.coroutine(gen_func)

This function transforms a generator function into a coroutine function which returns a generator-based coroutine. The generator-based coroutine is still a generator iterator, but is also considered to be a coroutine object and is awaitable. However, it may not necessarily implement the __await__() method.

If gen_func is a generator function, it will be modified in-place.

If gen_func is not a generator function, it will be wrapped. If it returns an instance of collections.abc.Generator, the instance will be wrapped in an awaitable proxy object. All other types of objects will be returned as is.

Nouveau dans la version 3.5.

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8.10. copy — Opérations de copie superficielle et récursive

Code source : Lib/copy.py [https://github.com/python/cpython/tree/3.6/Lib/copy.py]

Les instructions d’affectation en Python ne copient pas les objets, elles créent des liens entre la cible et l’objet. Concernant les collections qui sont muables ou contiennent des éléments muables, une copie est parfois nécessaire, pour pouvoir modifier une copie sans modifier l’autre. Ce module met à disposition des opérations de copie génériques superficielle et récursive (comme expliqué ci-dessous).

Résumé de l’interface :

copy.copy(x)

Renvoie une copie superficielle de x.

copy.deepcopy(x[, memo])

Renvoie une copie récursive de x.

exception copy.error

Levée pour les erreurs spécifiques au module.

La différence entre copie superficielle et récursive n’est pertinente que pour les objets composés (objets contenant d’autres objets, comme des listes ou des instances de classe) :

Une copie superficielle construit un nouvel objet composé puis (dans la mesure du possible) insère dans l’objet composé des références aux objets trouvés dans l’original.

Une copie récursive (ou profonde) construit un nouvel objet composé puis, récursivement, insère dans l’objet composé des copies des objets trouvés dans l’objet original.

On rencontre souvent deux problèmes avec les opérations de copie récursive qui n’existent pas avec les opérations de copie superficielle :

Les objets récursifs (objets composés qui, directement ou indirectement, contiennent une référence à eux-mêmes) peuvent causer une boucle récursive.

Comme une copie récursive copie tout, elle peut en copier trop, par exemple des données qui sont destinées à être partagées entre différentes copies.

La fonction deepcopy() évite ces problèmes en :

keeping a memo dictionary of objects already copied during the current copying pass; and

laissant les classes créées par l’utilisateur écraser l’opération de copie ou l’ensemble de composants copiés.

Ce module ne copie pas les types tels que module, méthode, trace d’appels, cadre de pile, fichier, socket, fenêtre, tableau, ou tout autre type similaire. Il « copie » les fonctions et les classes (superficiellement et récursivement), en retournant l’objet original inchangé ; c’est compatible avec la manière dont ils sont traités par le module pickle.

Les copies superficielles de dictionnaires peuvent être faites en utilisant dict.copy(), et de listes en affectant un slice de la liste, par exemple, copied_list = original_list[:].

Les classes peuvent utiliser les mêmes interfaces de contrôle que celles utilisées pour la sérialisation. Voir la description du module pickle pour plus d’informations sur ces méthodes. En effet, le module copy utilise les fonctions de sérialisation enregistrées à partir du module copyreg.

In order for a class to define its own copy implementation, it can define special methods __copy__() and __deepcopy__(). The former is called to implement the shallow copy operation; no additional arguments are passed. The latter is called to implement the deep copy operation; it is passed one argument, the memo dictionary. If the __deepcopy__() implementation needs to make a deep copy of a component, it should call the deepcopy() function with the component as first argument and the memo dictionary as second argument.

Voir aussi

Module pickle

Discussion sur les méthodes spéciales utilisées pour gérer la récupération et la restauration de l’état d’un objet.

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8.11. pprint — L’affichage élégant de données

Code source : Lib/pprint.py [https://github.com/python/cpython/tree/3.6/Lib/pprint.py]

Le module pprint permet « d’afficher élégamment » des structures de données Python arbitraires sous une forme qui peut être utilisée ensuite comme une entrée dans l’interpréteur. Si les structures formatées incluent des objets qui ne sont pas des types Python fondamentaux, leurs représentations peuvent ne pas être acceptables en tant que telles par l’interpréteur. Cela peut être le cas si des objets tels que des fichiers, des interfaces de connexion (sockets en anglais) ou des classes sont inclus, c’est aussi valable pour beaucoup d’autres types d’objets qui ne peuvent être représentés sous forme littérale en Python.

L’affichage formaté affiche tant que possible les objets sur une seule ligne, et les sépare sur plusieurs lignes s’ils dépassent la largeur autorisée par l’interpréteur. Créez explicitement des objets PrettyPrinter si vous avez besoin de modifier les limites de largeur.

Les dictionnaires sont classés par clés avant que l’affichage ne soit calculé.

Le module pprint définit une seule classe :

class pprint.PrettyPrinter(indent=1, width=80, depth=None, stream=None, *, compact=False)

Crée une instance de PrettyPrinter. Ce constructeur accepte plusieurs paramètres nommés. Un flux de sortie peut être défini par le mot clé stream; la seule méthode utilisée sur l’objet stream est la méthode write() du protocole de fichiers. Si rien n’est spécifié, la classe PrettyPrinter utilise sys.stdout. La taille de l’indentation ajoutée à chaque niveau récursif est spécifiée par indent; la valeur par défaut vaut 1`.  D’autres valeurs pourraient donner des résultats surprenants, mais peuvent aider à mieux visualiser les imbrications.  Le nombre de niveaux qui peuvent être affichés est contrôlé par *depth*; si la structure de données est trop profonde, le niveau suivant est remplacé par ``…. Par défaut il n’y a pas de contraintes sur la profondeur des objets formatés. Vous pouvez limiter la largeur de la sortie à l’aide du paramètre width; la valeur par défaut est de 80 caractères. Si une structure ne peut pas être formatée dans les limites de la largeur contrainte, le module fait au mieux. SI compact est initialisé à False (la valeur par défaut), chaque élément d’une longue séquence est formaté sur une ligne séparée. Si compact est initialisé à True, tous les éléments qui peuvent tenir dans la largeur définie sont formatés sur chaque ligne de sortie.

Modifié dans la version 3.4: Ajout du paramètre compact.

>>> import pprint
>>> stuff = ['spam', 'eggs', 'lumberjack', 'knights', 'ni']
>>> stuff.insert(0, stuff[:])
>>> pp = pprint.PrettyPrinter(indent=4)
>>> pp.pprint(stuff)
[   ['spam', 'eggs', 'lumberjack', 'knights', 'ni'],
    'spam',
    'eggs',
    'lumberjack',
    'knights',
    'ni']
>>> pp = pprint.PrettyPrinter(width=41, compact=True)
>>> pp.pprint(stuff)
[['spam', 'eggs', 'lumberjack',
  'knights', 'ni'],
 'spam', 'eggs', 'lumberjack', 'knights',
 'ni']
>>> tup = ('spam', ('eggs', ('lumberjack', ('knights', ('ni', ('dead',
... ('parrot', ('fresh fruit',))))))))
>>> pp = pprint.PrettyPrinter(depth=6)
>>> pp.pprint(tup)
('spam', ('eggs', ('lumberjack', ('knights', ('ni', ('dead', (...)))))))

Le module pprint fournit aussi quelques fonctions de raccourcis :

pprint.pformat(object, indent=1, width=80, depth=None, *, compact=False)

Renvoie une représentation formatée de object sous forme de chaine de caractères. indent, width, depth et compact sont passés au constructeur de PrettyPrinter comme paramètres de formatage.

Modifié dans la version 3.4: Ajout du paramètre compact.

pprint.pprint(object, stream=None, indent=1, width=80, depth=None, *, compact=False)

Affiche la représentation formatée de object sur stream, suivie d’un retour à la ligne. Si stream vaut None, sys.stdout est alors utilisé. Vous pouvez l’utiliser dans l’interpréteur interactif de Python au lieu de la fonction print() pour inspecter les valeurs (vous pouvez même réassigner print = pprint.pprint pour une utilisation au sein de sa portée). indent, width, depth et compact sont passés au constructeur de classe PrettyPrinter comme paramètres de formatage.

Modifié dans la version 3.4: Ajout du paramètre compact.

>>> import pprint
>>> stuff = ['spam', 'eggs', 'lumberjack', 'knights', 'ni']
>>> stuff.insert(0, stuff)
>>> pprint.pprint(stuff)
[<Recursion on list with id=...>,
 'spam',
 'eggs',
 'lumberjack',
 'knights',
 'ni']

pprint.isreadable(object)

Détermine si la représentation formatée de object est « lisible », ou s’il peut être utilisé pour recomposer sa valeur en utilisant la fonction eval(). Cela renvoie toujours False pour les objets récursifs.

>>> pprint.isreadable(stuff)
False

pprint.isrecursive(object)

Détermine si object requiert une représentation récursive.

Une dernière fonction de support est définie ainsi :

pprint.saferepr(object)

Renvoie une représentation de object sous forme de chaîne de caractère, celle-ci est protégée contre les structures de données récursives. Si la représentation de object présente une entrée récursive, celle-ci sera représentée telle que <Recursion on typename with id=number>. Par ailleurs, la représentation de l’objet n’est pas formatée.

>>> pprint.saferepr(stuff)
"[<Recursion on list with id=...>, 'spam', 'eggs', 'lumberjack', 'knights', 'ni']"

8.11.1. Les Objets PrettyPrinter

Les instances de la classe PrettyPrinter ont les méthodes suivantes :

PrettyPrinter.pformat(object)

Renvoie la représentation formatée de object. Cela prend en compte les options passées au constructeur de la classe PrettyPrinter.

PrettyPrinter.pprint(object)

Affiche sur le flux configuré la représentation formatée de object, suivie d’une fin de ligne.

Les méthodes suivantes fournissent les implémentations pour les fonctions correspondantes de mêmes noms. L’utilisation de ces méthodes sur une instance est légèrement plus efficace, car les nouveaux objets PrettyPrinter n’ont pas besoin d’être créés.

PrettyPrinter.isreadable(object)

Détermine si la représentation formatée de object est « lisible », ou si elle peut être utilisée pour recomposer sa valeur en utilisant la fonction eval(). Cela renvoie toujours False pour les objets récursifs. Si le paramètre depth de la classe PrettyPrinter est initialisé et que l’objet est plus « profond » que permis, cela renvoie False.

PrettyPrinter.isrecursive(object)

Détermine si l’objet nécessite une représentation récursive.

Cette méthode est fournie sous forme de point d’entrée ou méthode (à déclenchement) automatique (hook en anglais) pour permettre aux sous-classes de modifier la façon dont les objets sont convertis en chaînes. L’implémentation par défaut est celle de la fonction saferepr().

PrettyPrinter.format(object, context, maxlevels, level)

Renvoie trois valeurs : la version formatée de object sous forme de chaîne de caractères, une option indiquant si le résultat est « lisible », et une option indiquant si une récursion a été détectée. Le premier argument est l’objet à représenter. Le deuxième est un dictionnaire qui contient l”id() des objets (conteneurs directs ou indirects de objet qui affectent sa représentation) qui font partie du contexte de représentation courant tel que les clés; si un objet doit être représenté, mais l’a déjà été dans ce contexte, le troisième argument renvoie True. Des appels récursifs à la méthode format() doivent ajouter des entrés additionnelles aux conteneurs de ce dictionnaire. Le troisième argument maxlevels, donne la limite maximale de récursivité; la valeur par défaut est 0. Cet argument doit être passé non modifié pour des appels non récursifs. Le quatrième argument, level, donne le niveau de récursivité courant; les appels récursifs doivent être passés à une valeur inférieure à celle de l’appel courant.

8.11.2. Exemple

Pour illustrer quelques cas pratiques de l’utilisation de la fonction pprint() et de ses paramètres, allons chercher des informations sur un projet PyPI [https://pypi.org] :

>>> import json
>>> import pprint
>>> from urllib.request import urlopen
>>> with urlopen('https://pypi.org/pypi/sampleproject/json') as resp:
...     project_info = json.load(resp)['info']

Dans sa forme basique, la fonction pprint() affiche l’intégralité de l’objet :

>>> pprint.pprint(project_info)
{'author': 'The Python Packaging Authority',
 'author_email': 'pypa-dev@googlegroups.com',
 'bugtrack_url': None,
 'classifiers': ['Development Status :: 3 - Alpha',
                 'Intended Audience :: Developers',
                 'License :: OSI Approved :: MIT License',
                 'Programming Language :: Python :: 2',
                 'Programming Language :: Python :: 2.6',
                 'Programming Language :: Python :: 2.7',
                 'Programming Language :: Python :: 3',
                 'Programming Language :: Python :: 3.2',
                 'Programming Language :: Python :: 3.3',
                 'Programming Language :: Python :: 3.4',
                 'Topic :: Software Development :: Build Tools'],
 'description': 'A sample Python project\n'
                '=======================\n'
                '\n'
                'This is the description file for the project.\n'
                '\n'
                'The file should use UTF-8 encoding and be written using '
                'ReStructured Text. It\n'
                'will be used to generate the project webpage on PyPI, and '
                'should be written for\n'
                'that purpose.\n'
                '\n'
                'Typical contents for this file would include an overview of '
                'the project, basic\n'
                'usage examples, etc. Generally, including the project '
                'changelog in here is not\n'
                'a good idea, although a simple "What\'s New" section for the '
                'most recent version\n'
                'may be appropriate.',
 'description_content_type': None,
 'docs_url': None,
 'download_url': 'UNKNOWN',
 'downloads': {'last_day': -1, 'last_month': -1, 'last_week': -1},
 'home_page': 'https://github.com/pypa/sampleproject',
 'keywords': 'sample setuptools development',
 'license': 'MIT',
 'maintainer': None,
 'maintainer_email': None,
 'name': 'sampleproject',
 'package_url': 'https://pypi.org/project/sampleproject/',
 'platform': 'UNKNOWN',
 'project_url': 'https://pypi.org/project/sampleproject/',
 'project_urls': {'Download': 'UNKNOWN',
                  'Homepage': 'https://github.com/pypa/sampleproject'},
 'release_url': 'https://pypi.org/project/sampleproject/1.2.0/',
 'requires_dist': None,
 'requires_python': None,
 'summary': 'A sample Python project',
 'version': '1.2.0'}

Le résultat peut être limité à une certaine profondeur en initialisant depth. ( … est utilisé pour des contenus plus « profonds ») :

>>> pprint.pprint(project_info, depth=1)
{'author': 'The Python Packaging Authority',
 'author_email': 'pypa-dev@googlegroups.com',
 'bugtrack_url': None,
 'classifiers': [...],
 'description': 'A sample Python project\n'
                '=======================\n'
                '\n'
                'This is the description file for the project.\n'
                '\n'
                'The file should use UTF-8 encoding and be written using '
                'ReStructured Text. It\n'
                'will be used to generate the project webpage on PyPI, and '
                'should be written for\n'
                'that purpose.\n'
                '\n'
                'Typical contents for this file would include an overview of '
                'the project, basic\n'
                'usage examples, etc. Generally, including the project '
                'changelog in here is not\n'
                'a good idea, although a simple "What\'s New" section for the '
                'most recent version\n'
                'may be appropriate.',
 'description_content_type': None,
 'docs_url': None,
 'download_url': 'UNKNOWN',
 'downloads': {...},
 'home_page': 'https://github.com/pypa/sampleproject',
 'keywords': 'sample setuptools development',
 'license': 'MIT',
 'maintainer': None,
 'maintainer_email': None,
 'name': 'sampleproject',
 'package_url': 'https://pypi.org/project/sampleproject/',
 'platform': 'UNKNOWN',
 'project_url': 'https://pypi.org/project/sampleproject/',
 'project_urls': {...},
 'release_url': 'https://pypi.org/project/sampleproject/1.2.0/',
 'requires_dist': None,
 'requires_python': None,
 'summary': 'A sample Python project',
 'version': '1.2.0'}

De plus, une valeur maximale de caractères sur une ligne peut être définie en initialisant le paramètre width. Si un long objet ne peut être scindé, la valeur donnée à width sera outrepassée :

>>> pprint.pprint(project_info, depth=1, width=60)
{'author': 'The Python Packaging Authority',
 'author_email': 'pypa-dev@googlegroups.com',
 'bugtrack_url': None,
 'classifiers': [...],
 'description': 'A sample Python project\n'
                '=======================\n'
                '\n'
                'This is the description file for the '
                'project.\n'
                '\n'
                'The file should use UTF-8 encoding and be '
                'written using ReStructured Text. It\n'
                'will be used to generate the project '
                'webpage on PyPI, and should be written '
                'for\n'
                'that purpose.\n'
                '\n'
                'Typical contents for this file would '
                'include an overview of the project, '
                'basic\n'
                'usage examples, etc. Generally, including '
                'the project changelog in here is not\n'
                'a good idea, although a simple "What\'s '
                'New" section for the most recent version\n'
                'may be appropriate.',
 'description_content_type': None,
 'docs_url': None,
 'download_url': 'UNKNOWN',
 'downloads': {...},
 'home_page': 'https://github.com/pypa/sampleproject',
 'keywords': 'sample setuptools development',
 'license': 'MIT',
 'maintainer': None,
 'maintainer_email': None,
 'name': 'sampleproject',
 'package_url': 'https://pypi.org/project/sampleproject/',
 'platform': 'UNKNOWN',
 'project_url': 'https://pypi.org/project/sampleproject/',
 'project_urls': {...},
 'release_url': 'https://pypi.org/project/sampleproject/1.2.0/',
 'requires_dist': None,
 'requires_python': None,
 'summary': 'A sample Python project',
 'version': '1.2.0'}

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8.12. reprlib — Alternate repr() implementation

Code source : Lib/reprlib.py [https://github.com/python/cpython/tree/3.6/Lib/reprlib.py]

The reprlib module provides a means for producing object representations with limits on the size of the resulting strings. This is used in the Python debugger and may be useful in other contexts as well.

This module provides a class, an instance, and a function:

class reprlib.Repr

Class which provides formatting services useful in implementing functions similar to the built-in repr(); size limits for different object types are added to avoid the generation of representations which are excessively long.

reprlib.aRepr

This is an instance of Repr which is used to provide the repr() function described below. Changing the attributes of this object will affect the size limits used by repr() and the Python debugger.

reprlib.repr(obj)

This is the repr() method of aRepr. It returns a string similar to that returned by the built-in function of the same name, but with limits on most sizes.

In addition to size-limiting tools, the module also provides a decorator for detecting recursive calls to __repr__() and substituting a placeholder string instead.

@reprlib.recursive_repr(fillvalue="...")

Decorator for __repr__() methods to detect recursive calls within the same thread. If a recursive call is made, the fillvalue is returned, otherwise, the usual __repr__() call is made. For example:

>>> class MyList(list):
...     @recursive_repr()
...     def __repr__(self):
...         return '<' + '|'.join(map(repr, self)) + '>'
...
>>> m = MyList('abc')
>>> m.append(m)
>>> m.append('x')
>>> print(m)
<'a'|'b'|'c'|...|'x'>

Nouveau dans la version 3.2.

8.12.1. Repr Objects

Repr instances provide several attributes which can be used to provide size limits for the representations of different object types, and methods which format specific object types.

Repr.maxlevel

Depth limit on the creation of recursive representations. The default is 6.

Repr.maxdict

Repr.maxlist

Repr.maxtuple

Repr.maxset

Repr.maxfrozenset

Repr.maxdeque

Repr.maxarray

Limits on the number of entries represented for the named object type. The default is 4 for maxdict, 5 for maxarray, and 6 for the others.

Repr.maxlong

Maximum number of characters in the representation for an integer. Digits are dropped from the middle. The default is 40.

Repr.maxstring

Limit on the number of characters in the representation of the string. Note that the « normal » representation of the string is used as the character source: if escape sequences are needed in the representation, these may be mangled when the representation is shortened. The default is 30.

Repr.maxother

This limit is used to control the size of object types for which no specific formatting method is available on the Repr object. It is applied in a similar manner as maxstring. The default is 20.

Repr.repr(obj)

The equivalent to the built-in repr() that uses the formatting imposed by the instance.

Repr.repr1(obj, level)

Recursive implementation used by repr(). This uses the type of obj to determine which formatting method to call, passing it obj and level. The type-specific methods should call repr1() to perform recursive formatting, with level - 1 for the value of level in the recursive call.

Repr.repr_TYPE(obj, level)

Formatting methods for specific types are implemented as methods with a name based on the type name. In the method name, TYPE is replaced by '_'.join(type(obj).__name__.split()). Dispatch to these methods is handled by repr1(). Type-specific methods which need to recursively format a value should call self.repr1(subobj, level - 1).

8.12.2. Subclassing Repr Objects

The use of dynamic dispatching by Repr.repr1() allows subclasses of Repr to add support for additional built-in object types or to modify the handling of types already supported. This example shows how special support for file objects could be added:

import reprlib
import sys

class MyRepr(reprlib.Repr):

    def repr_TextIOWrapper(self, obj, level):
        if obj.name in {'<stdin>', '<stdout>', '<stderr>'}:
            return obj.name
        return repr(obj)

aRepr = MyRepr()
print(aRepr.repr(sys.stdin))         # prints '<stdin>'

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8.13. enum — Énumerations

Nouveau dans la version 3.4.

Code source : Lib/enum.py [https://github.com/python/cpython/tree/3.6/Lib/enum.py]

Une énumération est un ensemble de noms symboliques, appelés membres, liés à des valeurs constantes et uniques. Au sein d’une énumération, les membres peuvent être comparés entre eux et il est possible d’itérer sur l’énumération elle-même.

8.13.1. Contenu du module

Ce module définit quatre classes d’énumération qui permettent de définir des ensembles uniques de noms et de valeurs : Enum, IntEnum, Flag et IntFlag. Il fournit également un décorateur, unique(), ainsi qu’une classe utilitaire, auto.

class enum.Enum

Classe de base pour créer une énumération de constantes. Voir la section API par fonction pour une syntaxe alternative de construction.

class enum.IntEnum

Classe de base pour créer une énumération de constantes qui sont également des sous-classes de int.

class enum.IntFlag

Classe de base pour créer une énumération de constantes pouvant être combinées avec des opérateurs de comparaison bit-à-bit, sans perdre leur qualité de IntFlag. Les membres de IntFlag sont aussi des sous-classes de int.

class enum.Flag

Classe de base pour créer une énumération de constantes pouvant être combinées avec des opérateurs de comparaison bit-à-bit, sans perdre leur qualité de Flag.

enum.unique()

Décorateur de classe qui garantit qu’une valeur ne puisse être associée qu’à un seul nom.

class enum.auto

Les instances de cette classe remplacent les membres d’une Enum par une valeur appropriée.

Nouveau dans la version 3.6: Flag, IntFlag, auto

8.13.2. Création d’une Enum

Une énumération est créée comme une class, ce qui la rend facile à lire et à écrire. Une autre méthode de création est décrite dans API par fonction. Pour définir une énumération, il faut hériter de Enum de la manière suivante :

>>> from enum import Enum
>>> class Color(Enum):
...     RED = 1
...     GREEN = 2
...     BLUE = 3
...

Note

Valeurs des membres d’une Enum

La valeur d’un membre peut être de n’importe quel type : int, str, etc. Si la valeur exacte n’a pas d’importance, utilisez des instances de auto et une valeur appropriée sera choisie pour vous. Soyez vigilant si vous mélangez auto avec d’autres valeurs.

Note

Nomenclature

La classe Color est une énumération (ou un enum).

Les attributs Color.RED, Color.GREEN, etc., sont les membres de l’énumération (ou les membres de l’enum) et sont fonctionnellement des constantes.

Les membres de l’enum ont chacun un nom et une valeur ; le nom de Color.RED est RED, la valeur de Color.BLUE est 3, etc.

Note

Même si on utilise la syntaxe en class pour créer des énumérations, les Enums ne sont pas des vraies classes Python. Voir En quoi les Enums sont différentes ? pour plus de détails.

Les membres d’une énumération ont une représentation en chaîne de caractères compréhensible par un humain :

>>> print(Color.RED)
Color.RED

… tandis que leur repr contient plus d’informations :

>>> print(repr(Color.RED))
<Color.RED: 1>

Le type d’un membre est l’énumération auquel ce membre appartient :

>>> type(Color.RED)
<enum 'Color'>
>>> isinstance(Color.GREEN, Color)
True
>>>

Les membres ont également un attribut qui contient leur nom :

>>> print(Color.RED.name)
RED

Les énumérations sont itérables, l’ordre d’itération est celui dans lequel les membres sont déclarés :

>>> class Shake(Enum):
...     VANILLA = 7
...     CHOCOLATE = 4
...     COOKIES = 9
...     MINT = 3
...
>>> for shake in Shake:
...     print(shake)
...
Shake.VANILLA
Shake.CHOCOLATE
Shake.COOKIES
Shake.MINT

Les membres d’une énumération sont hachables, ils peuvent ainsi être utilisés dans des dictionnaires ou des ensembles :

>>> apples = {}
>>> apples[Color.RED] = 'red delicious'
>>> apples[Color.GREEN] = 'granny smith'
>>> apples == {Color.RED: 'red delicious', Color.GREEN: 'granny smith'}
True

8.13.3. Accès dynamique aux membres et à leurs attributs

Il est parfois utile de pouvoir accéder dynamiquement aux membres d’une énumération (p. ex. dans des situations où il ne suffit pas d’utiliser Color.RED car la couleur précise n’est pas connue à l’écriture du programme). Enum permet de tels accès :

>>> Color(1)
<Color.RED: 1>
>>> Color(3)
<Color.BLUE: 3>

Pour accéder aux membres par leur nom, utilisez l’accès par indexation :

>>> Color['RED']
<Color.RED: 1>
>>> Color['GREEN']
<Color.GREEN: 2>

Pour obtenir l’attribut name ou value d’un membre :

>>> member = Color.RED
>>> member.name
'RED'
>>> member.value
1

8.13.4. Duplication de membres et de valeurs

Il n’est pas possible d’avoir deux membres du même nom dans un enum :

>>> class Shape(Enum):
...     SQUARE = 2
...     SQUARE = 3
...
Traceback (most recent call last):
...
TypeError: Attempted to reuse key: 'SQUARE'

Cependant deux membres peuvent avoir la même valeur. Si deux membres A et B ont la même valeur (et que A est défini en premier), B sera un alias de A. Un accès par valeur avec la valeur commune à A et B renverra A. Un accès à B par nom renverra aussi A :

>>> class Shape(Enum):
...     SQUARE = 2
...     DIAMOND = 1
...     CIRCLE = 3
...     ALIAS_FOR_SQUARE = 2
...
>>> Shape.SQUARE
<Shape.SQUARE: 2>
>>> Shape.ALIAS_FOR_SQUARE
<Shape.SQUARE: 2>
>>> Shape(2)
<Shape.SQUARE: 2>

Note

Il est interdit de créer un membre avec le même nom qu’un attribut déjà défini (un autre membre, une méthode, etc.) ou de créer un attribut avec le nom d’un membre.

8.13.5. Coercition d’unicité des valeurs d’une énumération

Par défaut, les énumérations autorisent les alias de nom pour une même valeur. Quand ce comportement n’est pas désiré, il faut utiliser le décorateur suivant pour s’assurer que chaque valeur n’est utilisée qu’une seule fois au sein de l’énumération :

@enum.unique

Un décorateur de class spécifique aux énumérations. Il examine l’attribut __members__ d’une énumération et recherche des alias ; s’il en trouve, l’exception ValueError est levée avec des détails :

>>> from enum import Enum, unique
>>> @unique
... class Mistake(Enum):
...     ONE = 1
...     TWO = 2
...     THREE = 3
...     FOUR = 3
...
Traceback (most recent call last):
...
ValueError: duplicate values found in <enum 'Mistake'>: FOUR -> THREE

8.13.6. Valeurs automatiques

Si la valeur exacte n’a pas d’importance, vous pouvez utiliser auto :

>>> from enum import Enum, auto
>>> class Color(Enum):
...     RED = auto()
...     BLUE = auto()
...     GREEN = auto()
...
>>> list(Color)
[<Color.RED: 1>, <Color.BLUE: 2>, <Color.GREEN: 3>]

Les valeurs sont déterminées par _generate_next_value_(), qui peut être redéfinie :

>>> class AutoName(Enum):
...     def _generate_next_value_(name, start, count, last_values):
...         return name
...
>>> class Ordinal(AutoName):
...     NORTH = auto()
...     SOUTH = auto()
...     EAST = auto()
...     WEST = auto()
...
>>> list(Ordinal)
[<Ordinal.NORTH: 'NORTH'>, <Ordinal.SOUTH: 'SOUTH'>, <Ordinal.EAST: 'EAST'>, <Ordinal.WEST: 'WEST'>]

Note

La méthode par défaut _generate_next_value_() doit fournir le int suivant de la séquence en fonction du dernier int fourni, mais la séquence générée dépend de l’implémentation Python.

8.13.7. Itération

Itérer sur les membres d’une énumération ne parcourt pas les alias :

>>> list(Shape)
[<Shape.SQUARE: 2>, <Shape.DIAMOND: 1>, <Shape.CIRCLE: 3>]

L’attribut spécial __members__ est un dictionnaire ordonné qui fait correspondre les noms aux membres. Il inclut tous les noms définis dans l’énumération, alias compris :

>>> for name, member in Shape.__members__.items():
...     name, member
...
('SQUARE', <Shape.SQUARE: 2>)
('DIAMOND', <Shape.DIAMOND: 1>)
('CIRCLE', <Shape.CIRCLE: 3>)
('ALIAS_FOR_SQUARE', <Shape.SQUARE: 2>)

L’attribut __members__ peut servir à accéder dynamiquement aux membres de l’énumération. Par exemple, pour trouver tous les alias :

>>> [name for name, member in Shape.__members__.items() if member.name != name]
['ALIAS_FOR_SQUARE']

8.13.8. Comparaisons

Les membres d’une énumération sont comparés par identité :

>>> Color.RED is Color.RED
True
>>> Color.RED is Color.BLUE
False
>>> Color.RED is not Color.BLUE
True

Les comparaisons d’ordre entre les valeurs d’une énumération n’existent pas ; les membres d’un enum ne sont pas des entiers (voir cependant IntEnum ci-dessous) :

>>> Color.RED < Color.BLUE
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: '<' not supported between instances of 'Color' and 'Color'

A contrario, les comparaisons d’égalité existent :

>>> Color.BLUE == Color.RED
False
>>> Color.BLUE != Color.RED
True
>>> Color.BLUE == Color.BLUE
True

Les comparaisons avec des valeurs ne provenant pas d’énumérations sont toujours fausses (ici encore, IntEnum a été conçue pour fonctionner différemment, voir ci-dessous) :

>>> Color.BLUE == 2
False

8.13.9. Membres et attributs autorisés dans une énumération

Les exemples précédents utilisent des entiers pour énumérer les valeurs. C’est un choix concis et pratique (et implémenté par défaut dans l”API par fonction), mais ce n’est pas une obligation. Dans la majorité des cas, il importe peu de connaître la valeur réelle d’une énumération. Il est toutefois possible de donner une valeur arbitraire aux énumérations, si cette valeur est vraiment significative.

Les énumérations sont des classes Python et peuvent donc avoir des méthodes et des méthodes spéciales. L’énumération suivante :

>>> class Mood(Enum):
...     FUNKY = 1
...     HAPPY = 3
...
...     def describe(self):
...         # self is the member here
...         return self.name, self.value
...
...     def __str__(self):
...         return 'my custom str! {0}'.format(self.value)
...
...     @classmethod
...     def favorite_mood(cls):
...         # cls here is the enumeration
...         return cls.HAPPY
...

amène :

>>> Mood.favorite_mood()
<Mood.HAPPY: 3>
>>> Mood.HAPPY.describe()
('HAPPY', 3)
>>> str(Mood.FUNKY)
'my custom str! 1'

The rules for what is allowed are as follows: names that start and end with a single underscore are reserved by enum and cannot be used; all other attributes defined within an enumeration will become members of this enumeration, with the exception of special methods (__str__(), __add__(), etc.) and descriptors (methods are also descriptors).

Remarque : si l’énumération définit __new__() ou __init__(), alors la (ou les) valeur affectée au membre sera passée à ces méthodes. Voir l’exemple de Planet.

8.13.10. Restricted subclassing of enumerations

Subclassing an enumeration is allowed only if the enumeration does not define any members. So this is forbidden:

>>> class MoreColor(Color):
...     PINK = 17
...
Traceback (most recent call last):
...
TypeError: Cannot extend enumerations

Mais celui-ci est correct :

>>> class Foo(Enum):
...     def some_behavior(self):
...         pass
...
>>> class Bar(Foo):
...     HAPPY = 1
...     SAD = 2
...

Autoriser l’héritage d”enums définissant des membres violerait des invariants sur les types et les instances. D’un autre côté, il est logique d’autoriser un groupe d’énumérations à partager un comportement commun (voir par exemple OrderedEnum).

8.13.11. Sérialisation

Les énumérations peuvent être sérialisées et déserialisées :

>>> from test.test_enum import Fruit
>>> from pickle import dumps, loads
>>> Fruit.TOMATO is loads(dumps(Fruit.TOMATO))
True

Les restrictions habituelles de sérialisation s’appliquent : les enums à sérialiser doivent être déclarés dans l’espace de nom de haut niveau du module car la déserialisation nécessite que ces enums puissent être importés depuis ce module.

Note

Depuis la version 4 du protocole de pickle, il est possible de sérialiser facilement des enums imbriqués dans d’autres classes.

Redéfinir la méthode __reduce_ex__() permet de modifier la sérialisation ou la dé-sérialisation des membres d’une énumération.

8.13.12. API par fonction

La Enum est appelable et implémente l’API par fonction suivante :

>>> Animal = Enum('Animal', 'ANT BEE CAT DOG')
>>> Animal
<enum 'Animal'>
>>> Animal.ANT
<Animal.ANT: 1>
>>> Animal.ANT.value
1
>>> list(Animal)
[<Animal.ANT: 1>, <Animal.BEE: 2>, <Animal.CAT: 3>, <Animal.DOG: 4>]

La sémantique de cette API est similaire à namedtuple. Le premier argument de l’appel à Enum est le nom de l’énumération.

Le second argument est la source des noms des membres de l’énumération. Il peut être une chaîne de caractères contenant les noms séparés par des espaces, une séquence de noms, une séquence de couples clé / valeur ou un dictionnaire (p. ex. un dict) de valeurs indexées par des noms. Les deux dernières options permettent d’affecter des valeurs arbitraires aux énumérations ; les autres affectent automatiquement des entiers en commençant par 1 (le paramètre start permet de changer la valeur de départ). Ceci renvoie une nouvelle classe dérivée de Enum. En d’autres termes, la déclaration de Animal ci-dessus équivaut à :

>>> class Animal(Enum):
...     ANT = 1
...     BEE = 2
...     CAT = 3
...     DOG = 4
...

La valeur de départ par défaut est 1 et non 0 car 0 au sens booléen vaut False alors que tous les membres d’une enum valent True.

La sérialisation d’énumérations créées avec l’API en fonction peut être source de problèmes, car celle-ci repose sur des détails d’implémentation de l’affichage de la pile d’appel pour tenter de déterminer dans quel module l’énumération est créée (p. ex. elle échouera avec les fonctions utilitaires provenant d’un module séparé et peut ne pas fonctionner avec IronPython ou Jython). La solution consiste à préciser explicitement le nom du module comme ceci :

>>> Animal = Enum('Animal', 'ANT BEE CAT DOG', module=__name__)

Avertissement

Si module n’est pas fourni et que Enum ne peut pas le deviner, les nouveaux membres de l’Enum ne seront pas déserialisables ; pour garder les erreurs au plus près de leur origine, la sérialisation sera désactivée.

Le nouveau protocole version 4 de pickle se base lui aussi, dans certains cas, sur le fait que __qualname__ pointe sur l’endroit où pickle peut trouver la classe. Par exemple, si la classe était disponible depuis la classe SomeData dans l’espace de nom de plus haut niveau :

>>> Animal = Enum('Animal', 'ANT BEE CAT DOG', qualname='SomeData.Animal')

La signature complète est la suivante :

Enum(value='NewEnumName', names=<...>, *, module='...', qualname='...', type=<mixed-in class>, start=1)

value

Le nom de la la nouvelle classe Enum.

names

Les membres de l’énumération. Une chaîne de caractères séparés par des espaces ou des virgules (la valeur de départ est fixée à 1, sauf si spécifiée autrement) :

'RED GREEN BLUE' | 'RED,GREEN,BLUE' | 'RED, GREEN, BLUE'

ou un itérateur sur les noms :

['RED', 'GREEN', 'BLUE']

ou un itérateur sur les tuples (nom, valeur) :

[('CYAN', 4), ('MAGENTA', 5), ('YELLOW', 6)]

ou une correspondance :

{'CHARTREUSE': 7, 'SEA_GREEN': 11, 'ROSEMARY': 42}

module

nom du module dans lequel la classe Enum se trouve.

qualname

localisation de la nouvelle classe Enum dans le module.

type

le type à mélanger dans la nouvelle classe Enum.

start

index de départ si uniquement des noms sont passés.

Modifié dans la version 3.5: Ajout du paramètre start.

8.13.13. Énumérations dérivées

8.13.13.1. IntEnum

La première version dérivée de Enum qui existe est aussi une sous-classe de int. Les membres de IntEnum peuvent être comparés à des entiers et, par extension, les comparaisons entre des énumérations entières de type différent sont possibles :

>>> from enum import IntEnum
>>> class Shape(IntEnum):
...     CIRCLE = 1
...     SQUARE = 2
...
>>> class Request(IntEnum):
...     POST = 1
...     GET = 2
...
>>> Shape == 1
False
>>> Shape.CIRCLE == 1
True
>>> Shape.CIRCLE == Request.POST
True

Elles ne peuvent cependant toujours pas être comparées à des énumérations standards de Enum :

>>> class Shape(IntEnum):
...     CIRCLE = 1
...     SQUARE = 2
...
>>> class Color(Enum):
...     RED = 1
...     GREEN = 2
...
>>> Shape.CIRCLE == Color.RED
False

Les valeurs de IntEnum se comportent comme des entiers, comme on pouvait s’y attendre :

>>> int(Shape.CIRCLE)
1
>>> ['a', 'b', 'c'][Shape.CIRCLE]
'b'
>>> [i for i in range(Shape.SQUARE)]
[0, 1]

8.13.13.2. IntFlag

La version dérivée suivante de Enum est IntFlag. Elle est aussi basée sur int, à la différence près que les membres de IntFlag peuvent être combinés en utilisant les opérateurs bit-à-bit (&, |, ^, ~) et que le résultat reste un membre de IntFlag. Cependant, comme le nom l’indique, les membres d’une classe IntFlag héritent aussi de int et peuvent être utilisés là où un int est utilisé. Toute opération sur un membre d’une classe IntFlag, autre qu’un opérateur bit-à-bit lui fait perdre sa qualité de IntFlag.

Nouveau dans la version 3.6.

Exemple d’une classe IntFlag :

>>> from enum import IntFlag
>>> class Perm(IntFlag):
...     R = 4
...     W = 2
...     X = 1
...
>>> Perm.R | Perm.W
<Perm.R|W: 6>
>>> Perm.R + Perm.W
6
>>> RW = Perm.R | Perm.W
>>> Perm.R in RW
True

Il est aussi possible de nommer les combinaisons :

>>> class Perm(IntFlag):
...     R = 4
...     W = 2
...     X = 1
...     RWX = 7
>>> Perm.RWX
<Perm.RWX: 7>
>>> ~Perm.RWX
<Perm.-8: -8>

Une autre différence importante entre IntFlag et Enum est que, si aucune option n’est activée (la valeur vaut 0), son évaluation booléenne est False :

>>> Perm.R & Perm.X
<Perm.0: 0>
>>> bool(Perm.R & Perm.X)
False

Comme les membres d’une classe IntFlag héritent aussi de int, ils peuvent être combinés avec eux :

>>> Perm.X | 8
<Perm.8|X: 9>

8.13.13.3. Option

La dernière version dérivée est la classe Flag. Comme IntFlag, les membres d’une classe Flag peuvent être combinés en utilisant les opérateurs de comparaison bit-à-bit. Cependant, à la différence de IntFlag, ils ne peuvent ni être combinés, ni être comparés avec une autre énumération Flag, ni avec int. Bien qu’il soit possible de définir directement les valeurs, il est recommandé d’utiliser auto comme valeur et de laisser Flag choisir une valeur appropriée.

Nouveau dans la version 3.6.

Comme avec IntFlag, si une combinaison de membres d’une classe Flag n’active aucune option, l’évaluation booléenne de la comparaison est False :

>>> from enum import Flag, auto
>>> class Color(Flag):
...     RED = auto()
...     BLUE = auto()
...     GREEN = auto()
...
>>> Color.RED & Color.GREEN
<Color.0: 0>
>>> bool(Color.RED & Color.GREEN)
False

Les options de base doivent avoir des puissances de deux pour valeurs (1, 2, 4, 8, …) mais pas les combinaisons :

>>> class Color(Flag):
...     RED = auto()
...     BLUE = auto()
...     GREEN = auto()
...     WHITE = RED | BLUE | GREEN
...
>>> Color.WHITE
<Color.WHITE: 7>

Donner un nom à la valeur « aucune option activée » ne change pas sa valeur booléenne :

>>> class Color(Flag):
...     BLACK = 0
...     RED = auto()
...     BLUE = auto()
...     GREEN = auto()
...
>>> Color.BLACK
<Color.BLACK: 0>
>>> bool(Color.BLACK)
False

Note

Dans la plupart des cas, il est fortement recommandé d’utiliser Enum et Flag pour écrire du code nouveau, car IntEnum et IntFlag violent certains principes sémantiques d’une énumération (en pouvant être comparées à des entiers et donc, par transitivité, à d’autres énumérations). IntEnum et IntFlag ne doivent être utilisées que dans les cas où Enum et Flag ne suffisent pas ; par exemple quand des constantes entières sont remplacées par des énumérations, ou pour l’interopérabilité avec d’autres systèmes.

8.13.13.4. Autres

Bien que IntEnum fasse partie du module enum, elle serait très simple à implémenter hors de ce module :

class IntEnum(int, Enum):
    pass

Ceci montre comment définir des énumérations dérivées similaires ; par exemple une classe StrEnum qui dériverait de str au lieu de int.

Quelques règles :

Pour hériter de Enum, les types de mélange doivent être placés avant la classe Enum elle-même dans la liste des classes de base, comme dans l’exemple de IntEnum ci-dessus.

Même si une classe Enum peut avoir des membres de n’importe quel type, dès lors qu’un type de mélange est ajouté, tous les membres doivent être de ce type, p. ex. int ci-dessus. Cette restriction ne s’applique pas aux types de mélange qui ne font qu’ajouter des méthodes et ne définissent pas de type de données, tels int ou str.

Quand un autre type de données est mélangé, l’attribut value n’est pas identique au membre de l’énumération lui-même, bien qu’ils soient équivalents et égaux en comparaison.

Formatage de style % : %s et %r appellent respectivement les méthodes __str__() et __repr__() de la classe Enum ; les autres codes, comme %i ou %h pour IntEnum, s’appliquent au membre comme si celui-ci était converti en son type de mélange.

Chaînes de caractères formatées littérales : str.format() et format() appellent la méthode __format__() du type de mélange. Pour appeler les fonctions str() ou repr() de la classe Enum, il faut utiliser les codes de formatage !s ou !r.

8.13.14. Exemples intéressants

Bien que Enum, IntEnum, IntFlag et Flag soient conçues pour répondre à la majorité des besoins, elles ne peuvent répondre à tous. Voici quelques recettes d’énumération qui peuvent être réutilisées telles quelles, ou peuvent servir d’exemple pour développer vos propres énumérations.

8.13.14.1. Omettre les valeurs

Dans de nombreux cas, la valeur réelle de l’énumération n’a pas d’importance. Il y a plusieurs façons de définir ce type d’énumération simple :

affecter des instances de auto aux valeurs

affecter des instances de object aux valeurs

affecter des chaînes de caractères aux valeurs pour les décrire

affecter un n-uplet aux valeurs et définir une méthode __new__() pour remplacer les n-uplets avec un int

Utiliser une de ces méthodes indique à l’utilisateur que les valeurs n’ont pas d’importance. Cela permet aussi d’ajouter, de supprimer ou de ré-ordonner les membres sans avoir à ré-énumérer les membres existants.

Quelle que soit la méthode choisie, il faut fournir une méthode repr() qui masque les valeurs (pas importantes de toute façon) :

>>> class NoValue(Enum):
...     def __repr__(self):
...         return '<%s.%s>' % (self.__class__.__name__, self.name)
...

8.13.14.1.1. Avec auto

On utilise auto de la manière suivante :

>>> class Color(NoValue):
...     RED = auto()
...     BLUE = auto()
...     GREEN = auto()
...
>>> Color.GREEN
<Color.GREEN>

8.13.14.1.2. Avec object

On utilise object de la manière suivante :

>>> class Color(NoValue):
...     RED = object()
...     GREEN = object()
...     BLUE = object()
...
>>> Color.GREEN
<Color.GREEN>

8.13.14.1.3. Avec une chaîne de caractères de description

On utilise une chaîne de caractères de la manière suivante :

>>> class Color(NoValue):
...     RED = 'stop'
...     GREEN = 'go'
...     BLUE = 'too fast!'
...
>>> Color.GREEN
<Color.GREEN>
>>> Color.GREEN.value
'go'

8.13.14.1.4. Avec une méthode ad-hoc __new__()

On utilise une méthode __new__() d’énumération de la manière suivante :

>>> class AutoNumber(NoValue):
...     def __new__(cls):
...         value = len(cls.__members__) + 1
...         obj = object.__new__(cls)
...         obj._value_ = value
...         return obj
...
>>> class Color(AutoNumber):
...     RED = ()
...     GREEN = ()
...     BLUE = ()
...
>>> Color.GREEN
<Color.GREEN>
>>> Color.GREEN.value
2

Note

La méthode __new__(), si définie, est appelée à la création des membres de l’énumération ; elle est ensuite remplacée par la méthode __new__() de Enum, qui est utilisée après la création de la classe pour la recherche des membres existants.

8.13.14.2. OrderedEnum

Une énumération ordonnée qui n’est pas basée sur IntEnum et qui, par conséquent, respecte les invariants classiques de Enum (comme par exemple l’impossibilité de pouvoir être comparée à d’autres énumérations) :

>>> class OrderedEnum(Enum):
...     def __ge__(self, other):
...         if self.__class__ is other.__class__:
...             return self.value >= other.value
...         return NotImplemented
...     def __gt__(self, other):
...         if self.__class__ is other.__class__:
...             return self.value > other.value
...         return NotImplemented
...     def __le__(self, other):
...         if self.__class__ is other.__class__:
...             return self.value <= other.value
...         return NotImplemented
...     def __lt__(self, other):
...         if self.__class__ is other.__class__:
...             return self.value < other.value
...         return NotImplemented
...
>>> class Grade(OrderedEnum):
...     A = 5
...     B = 4
...     C = 3
...     D = 2
...     F = 1
...
>>> Grade.C < Grade.A
True

8.13.14.3. DuplicateFreeEnum

Lève une erreur si un membre est dupliqué, plutôt que de créer un alias :

>>> class DuplicateFreeEnum(Enum):
...     def __init__(self, *args):
...         cls = self.__class__
...         if any(self.value == e.value for e in cls):
...             a = self.name
...             e = cls(self.value).name
...             raise ValueError(
...                 "aliases not allowed in DuplicateFreeEnum:  %r --> %r"
...                 % (a, e))
...
>>> class Color(DuplicateFreeEnum):
...     RED = 1
...     GREEN = 2
...     BLUE = 3
...     GRENE = 2
...
Traceback (most recent call last):
...
ValueError: aliases not allowed in DuplicateFreeEnum:  'GRENE' --> 'GREEN'

Note

Cet exemple d’héritage de Enum est intéressant pour ajouter ou modifier des comportements comme interdire les alias. Si vous ne souhaitez qu’interdire les alias, il suffit d’utiliser le décorateur unique().

8.13.14.4. Planet

Si __new__() ou __init__() sont définies, la valeur du membre de l’énumération sera passée à ces méthodes :

>>> class Planet(Enum):
...     MERCURY = (3.303e+23, 2.4397e6)
...     VENUS   = (4.869e+24, 6.0518e6)
...     EARTH   = (5.976e+24, 6.37814e6)
...     MARS    = (6.421e+23, 3.3972e6)
...     JUPITER = (1.9e+27,   7.1492e7)
...     SATURN  = (5.688e+26, 6.0268e7)
...     URANUS  = (8.686e+25, 2.5559e7)
...     NEPTUNE = (1.024e+26, 2.4746e7)
...     def __init__(self, mass, radius):
...         self.mass = mass       # in kilograms
...         self.radius = radius   # in meters
...     @property
...     def surface_gravity(self):
...         # universal gravitational constant  (m3 kg-1 s-2)
...         G = 6.67300E-11
...         return G * self.mass / (self.radius * self.radius)
...
>>> Planet.EARTH.value
(5.976e+24, 6378140.0)
>>> Planet.EARTH.surface_gravity
9.802652743337129

8.13.15. En quoi les Enums sont différentes ?

Les enums ont une métaclasse spéciale qui affecte de nombreux aspects des classes dérivées de Enum et de leur instances (membres).

8.13.15.1. Classes Enum

The EnumMeta metaclass is responsible for providing the __contains__(), __dir__(), __iter__() and other methods that allow one to do things with an Enum class that fail on a typical class, such as list(Color) or some_var in Color. EnumMeta is responsible for ensuring that various other methods on the final Enum class are correct (such as __new__(), __getnewargs__(), __str__() and __repr__()).

8.13.15.2. Membres d’Enum (c.-à-d. instances)

Il est intéressant de souligner que les membres d’une Enum sont des singletons. La classe EnumMeta les crée tous au moment de la création de la classe Enum elle-même et implémente une méthode __new__() spécifique. Cette méthode renvoie toujours les instances de membres déjà existantes pour être sûr de ne jamais en instancier de nouvelles.

8.13.15.3. Aspects approfondis

8.13.15.3.1. Noms de la forme __dunder__ disponibles

__members__ est une OrderedDict de correspondances nom_du_membre / membre. Elle n’est disponible que depuis la classe.

La méthode __new__(), si elle est définie, doit créer et renvoyer les membres de l’énumération ; affecter correctement l’attribut _value_ du membre est également conseillé. Une fois que tous les membres ont été créés, cette méthode n’est plus utilisée.

8.13.15.3.2. Noms de la forme _sunder_ disponibles

_name_ – nom du membre

_value_ – valeur du membre ; il est possible d’y accéder ou de la muer dans __new__

_missing_ – une fonction de recherche qui est appelée quand la valeur n’est pas trouvée ; elle peut être redéfinie

_order_ – utilisé en Python 2 ou 3 pour s’assurer que l’ordre des membres est cohérent (attribut de classe, supprimé durant la création de la classe)

_generate_next_value_ – utilisée par l” API par fonction et par auto pour obtenir une valeur appropriée à affecter à un membre de l’enum ; elle peut être redéfinie

Nouveau dans la version 3.6: _missing_, _order_, _generate_next_value_

Pour faciliter la transition de Python 2 en Python 3, l’attribut _order_ peut être défini. Il sera comparé au véritable ordre de l’énumération et lève une erreur si les deux ne correspondent pas :

>>> class Color(Enum):
...     _order_ = 'RED GREEN BLUE'
...     RED = 1
...     BLUE = 3
...     GREEN = 2
...
Traceback (most recent call last):
...
TypeError: member order does not match _order_

Note

En Python 2, l’attribut _order_ est indispensable car l’ordre de la définition est perdu avant de pouvoir être enregistré.

8.13.15.3.3. Type des membres de Enum

Les membres de Enum sont des instances de leur classe Enum. On y accède normalement par ClasseEnum.membre. Dans certains cas, on peut également y accéder par ClasseEnum.membre.membre, mais ceci est fortement déconseillé car cette indirection est susceptible d’échouer, ou pire, de ne pas renvoyer le membre de la classe Enum désiré (c’est une autre bonne raison pour définir tous les noms des membres en majuscules) :

>>> class FieldTypes(Enum):
...     name = 0
...     value = 1
...     size = 2
...
>>> FieldTypes.value.size
<FieldTypes.size: 2>
>>> FieldTypes.size.value
2

Modifié dans la version 3.5.

8.13.15.3.4. Valeur booléenne des classes Enum et de leurs membres

Les membres d’une classe Enum mélangée avec un type non dérivé de Enum (comme int, str, etc.) sont évalués selon les règles du type de mélange. Sinon, tous les membres valent True. Pour faire dépendre l’évaluation booléenne de votre propre Enum de la valeur du membre, il faut ajouter le code suivant à votre classe :

def __bool__(self):
    return bool(self.value)

Les classes Enum valent toujours True.

8.13.15.3.5. Classes Enum avec des méthodes

Si votre classe Enum contient des méthodes supplémentaires, comme la classe Planet ci-dessus, elles s’afficheront avec un appel à dir() sur le membre, mais pas avec un appel sur la classe :

>>> dir(Planet)
['EARTH', 'JUPITER', 'MARS', 'MERCURY', 'NEPTUNE', 'SATURN', 'URANUS', 'VENUS', '__class__', '__doc__', '__members__', '__module__']
>>> dir(Planet.EARTH)
['__class__', '__doc__', '__module__', 'name', 'surface_gravity', 'value']

8.13.15.3.6. Combinaison de membres de Flag

Si une valeur issue de la combinaison de membres de Flag n’est pas associée explicitement à un membre, la fonction repr() inclut tous les membres et toutes les combinaisons de membres présents dans cette valeur :

>>> class Color(Flag):
...     RED = auto()
...     GREEN = auto()
...     BLUE = auto()
...     MAGENTA = RED | BLUE
...     YELLOW = RED | GREEN
...     CYAN = GREEN | BLUE
...
>>> Color(3)  # named combination
<Color.YELLOW: 3>
>>> Color(7)      # not named combination
<Color.CYAN|MAGENTA|BLUE|YELLOW|GREEN|RED: 7>

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9. Modules numériques et mathématiques

Les modules documentés dans ce chapitre fournissent des fonctions et des types autour des nombres et des mathématiques. Le module numbers définit une hiérarchie abstraite des types numériques. Les modules math et cmath contiennent des fonctions mathématiques pour les nombres à virgule flottante ou les nombres complexes. Le module decimal permet de représenter des nombres décimaux de manière exacte, et utilise une arithmétique de précision arbitraire.

Les modules suivants sont documentés dans ce chapitre :

9.1. numbers — Classes de base abstraites numériques

9.1.1. La tour numérique

9.1.2. Notes pour implémenter des types

9.1.2.1. Ajouter plus d’ABC numériques

9.1.2.2. Implémentation des opérations arithmétiques

9.2. Fonctions mathématiques — math

9.2.1. Fonctions arithmétiques et de représentation

9.2.2. Fonctions logarithme et exponentielle

9.2.3. Fonctions trigonométriques

9.2.4. Conversion angulaire

9.2.5. Fonctions hyperboliques

9.2.6. Fonctions spéciales

9.2.7. Constantes

9.3. Fonctions mathématiques pour nombres complexes — cmath

9.3.1. Conversion vers et à partir de coordonnées polaires

9.3.2. Fonctions logarithme et exponentielle

9.3.3. Fonctions trigonométriques

9.3.4. Fonctions hyperboliques

9.3.5. Fonctions de classifications

9.3.6. Constantes

9.4. decimal — Arithmétique décimale en virgule fixe et flottante

9.4.1. Introduction pratique

9.4.2. Les objets Decimal

9.4.2.1. Logical operands

9.4.3. Context objects

9.4.4. Constantes

9.4.5. Rounding modes

9.4.6. Signals

9.4.7. Floating Point Notes

9.4.7.1. Mitigating round-off error with increased precision

9.4.7.2. Special values

9.4.8. Working with threads

9.4.9. Cas pratiques

9.4.10. FAQ decimal

9.5. fractions — Nombres rationnels

9.6. random — Génère des nombres pseudo-aléatoires

9.6.1. Fonctions de gestion d’état

9.6.2. Fonctions pour les entiers

9.6.3. Fonctions pour les séquences

9.6.4. Distributions pour les nombre réels

9.6.5. Générateur alternatif

9.6.6. Remarques sur la reproductibilité

9.6.7. Exemples et recettes

9.7. statistics — Mathematical statistics functions

9.7.1. Averages and measures of central location

9.7.2. Measures of spread

9.7.3. Function details

9.7.4. Exceptions

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9.1. numbers — Classes de base abstraites numériques

Code source : Lib/numbers.py [https://github.com/python/cpython/tree/3.6/Lib/numbers.py]

Le module numbers (PEP 3141 [https://www.python.org/dev/peps/pep-3141]) définit une hiérarchie de classes de base abstraites numériques qui définissent progressivement plus d’opérations. Aucun des types définis dans ce module ne peut être instancié.

class numbers.Number

La base de la hiérarchie numérique. Si vous voulez juste vérifier qu’un argument x est un nombre, peu importe le type, utilisez isinstance(x, Number).

9.1.1. La tour numérique

class numbers.Complex

Les sous-classes de ce type décrivent des nombres complexes et incluent les opérations qui fonctionnent sur le type natif complex. Ce sont : les conversions vers complex et bool, real, imag, +, -, *, /, abs(), conjugate(), == et !=. Toutes sauf - et != sont abstraites.

real

Abstrait. Récupère la partie réelle de ce nombre.

imag

Abstrait. Retrouve la partie imaginaire de ce nombre.

abstractmethod conjugate()

Abstrait. Renvoie le complexe conjugué. Par exemple, (1+3j).conjugate() == (1-3j).

class numbers.Real

Real ajoute les opérations qui fonctionnent sur les nombres réels à Complex.

En bref, celles-ci sont : une conversion vers float, math.trunc(), round(), math.floor(), math.ceil(), divmod(), //, %, <, <=, > et >=.

Real fournit également des valeurs par défaut pour complex(), real, imag et conjugate().

class numbers.Rational

Dérive Real et ajoute les propriétés numerator et denominator qui doivent être les plus petits possible. Avec celles-ci, il fournit une valeur par défaut pour float().

numerator

Abstrait.

denominator

Abstrait.

class numbers.Integral

Dérive Rational et ajoute une conversion en int. Fournit des valeurs par défaut pour float(), numerator et denominator. Ajoute des méthodes abstraites pour ** et les opérations au niveau des bits: <<, >>, &, ^, |, ~.

9.1.2. Notes pour implémenter des types

Les développeurs doivent veiller à ce que des nombres égaux soient bien égaux lors de comparaisons et à ce qu’ils soient hachés aux mêmes valeurs. Cela peut être subtil s’il y a deux dérivations différentes des nombres réels. Par exemple, fractions.Fraction implémente hash() comme suit :

def __hash__(self):
    if self.denominator == 1:
        # Get integers right.
        return hash(self.numerator)
    # Expensive check, but definitely correct.
    if self == float(self):
        return hash(float(self))
    else:
        # Use tuple's hash to avoid a high collision rate on
        # simple fractions.
        return hash((self.numerator, self.denominator))

9.1.2.1. Ajouter plus d’ABC numériques

Il est bien entendu possible de créer davantage d’ABC pour les nombres et cette hiérarchie serait médiocre si elle excluait la possibilité d’en ajouter. Vous pouvez ajouter MyFoo entre Complex et Real ainsi :

class MyFoo(Complex): ...
MyFoo.register(Real)

9.1.2.2. Implémentation des opérations arithmétiques

Nous voulons implémenter les opérations arithmétiques de sorte que les opérations en mode mixte appellent une implémentation dont l’auteur connaît les types des deux arguments, ou convertissent chacun dans le type natif le plus proche et effectuent l’opération sur ces types. Pour les sous-types de Integral, cela signifie que __add__() et __radd__() devraient être définis comme suit :

class MyIntegral(Integral):

    def __add__(self, other):
        if isinstance(other, MyIntegral):
            return do_my_adding_stuff(self, other)
        elif isinstance(other, OtherTypeIKnowAbout):
            return do_my_other_adding_stuff(self, other)
        else:
            return NotImplemented

    def __radd__(self, other):
        if isinstance(other, MyIntegral):
            return do_my_adding_stuff(other, self)
        elif isinstance(other, OtherTypeIKnowAbout):
            return do_my_other_adding_stuff(other, self)
        elif isinstance(other, Integral):
            return int(other) + int(self)
        elif isinstance(other, Real):
            return float(other) + float(self)
        elif isinstance(other, Complex):
            return complex(other) + complex(self)
        else:
            return NotImplemented

Il existe 5 cas différents pour une opération de type mixte sur des sous-classes de Complex. Nous nous référerons à tout le code ci-dessus qui ne se réfère pas à MyIntegral et OtherTypeIKnowAbout comme « expression générique ». a est une instance de A, qui est un sous-type de Complex (a : A <: Complex) et b : B <: Complex. Considérons a + b:

Si A définit une __add__() qui accepte b, tout va bien.

Si A fait appel au code générique et que celui-ci renvoie une valeur de __add__(), nous manquons la possibilité que B définisse une __radd__() plus intelligent, donc le code générique devrait retourner NotImplemented dans __add__() (ou alors A ne doit pas implémenter __add__() du tout.)

Alors __radd__() de B a une chance. si elle accepte a, tout va bien.

Si elle fait appel au code générique, il n’y a plus de méthode possible à essayer, c’est donc ici que l’implémentation par défaut intervient.

Si B < : A`, Python essaie B.__radd__ avant A.__add__. C’est valable parce qu’elle est implémentée avec la connaissance de A, donc elle peut gérer ces instances avant de déléguer à Complex.

Si A <: Complex et B <: Real sans autre information, alors l’opération commune appropriée est celle impliquant complex et les deux __radd__() atterrissent à cet endroit, donc a+b == b+a.

Comme la plupart des opérations sur un type donné seront très similaires, il peut être utile de définir une fonction accessoire qui génère les instances résultantes et inverses d’un opérateur donné. Par exemple, fractions.Fraction utilise :

def _operator_fallbacks(monomorphic_operator, fallback_operator):
    def forward(a, b):
        if isinstance(b, (int, Fraction)):
            return monomorphic_operator(a, b)
        elif isinstance(b, float):
            return fallback_operator(float(a), b)
        elif isinstance(b, complex):
            return fallback_operator(complex(a), b)
        else:
            return NotImplemented
    forward.__name__ = '__' + fallback_operator.__name__ + '__'
    forward.__doc__ = monomorphic_operator.__doc__

    def reverse(b, a):
        if isinstance(a, Rational):
            # Includes ints.
            return monomorphic_operator(a, b)
        elif isinstance(a, numbers.Real):
            return fallback_operator(float(a), float(b))
        elif isinstance(a, numbers.Complex):
            return fallback_operator(complex(a), complex(b))
        else:
            return NotImplemented
    reverse.__name__ = '__r' + fallback_operator.__name__ + '__'
    reverse.__doc__ = monomorphic_operator.__doc__

    return forward, reverse

def _add(a, b):
    """a + b"""
    return Fraction(a.numerator * b.denominator +
                    b.numerator * a.denominator,
                    a.denominator * b.denominator)

__add__, __radd__ = _operator_fallbacks(_add, operator.add)

# ...

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9.2. Fonctions mathématiques — math

Ce module est toujours disponible. Il fournit l’accès aux fonctions mathématiques définies par le standard C.

Ces fonctions ne peuvent pas être utilisées avec les nombres complexes ; si vous avez besoin de la prise en charge des nombres complexes, utilisez les fonctions du même nom du module cmath. La séparation entre les fonctions qui gèrent les nombres complexes et les autres vient du constat que tous les utilisateurs ne souhaitent pas acquérir le niveau mathématique nécessaire à la compréhension des nombres complexes. Recevoir une exception plutôt qu’un nombre complexe en retour d’une fonction permet au programmeur de déterminer immédiatement comment et pourquoi ce nombre a été généré, avant que celui-ci ne soit passé involontairement en paramètre d’une autre fonction.

Les fonctions suivantes sont fournies dans ce module. Sauf mention contraire explicite, toutes les valeurs de retour sont des flottants.

9.2.1. Fonctions arithmétiques et de représentation

math.ceil(x)

Renvoie la partie entière par excès de x, le plus petit entier supérieur ou égal à x. Si x est un flottant, délègue à x.__ceil()__, qui doit renvoyer une valeur Integral.

math.copysign(x, y)

Renvoie un flottant contenant la magnitude (valeur absolue) de x mais avec le signe de y. Sur les plates-formes prenant en charge les zéros signés, copysign(1.0, -0.0) renvoie -1.0.

math.fabs(x)

Renvoie la valeur absolue de x.

math.factorial(x)

Renvoie la factorielle de x. Lève une ValueError si x n’est pas entier ou s’il est négatif.

math.floor(x)

Renvoie la partie entière (par défaut) de x, le plus grand entier inférieur ou égal à x. Si x n’est pas un flottant, délègue à x.__floor()__, qui doit renvoyer une valeur Integral.

math.fmod(x, y)

Renvoie fmod(x, y), tel que défini par la bibliothèque C de la plate-forme. Notez que l’expression Python x % y peut ne pas renvoyer le même résultat. Le sens du standard C pour fmod(x, y) est d’être exactement (mathématiquement, à une précision infinie) égal à x - n*y pour un entier n tel que le résultat a le signe de x et une magnitude inférieure à abs(y). L’expression Python x % y renvoie un résultat avec le signe de y, et peut ne pas être calculable exactement pour des arguments flottants. Par exemple : fmod(-1e-100, 1e100) est -1e-100, mais le résultat de l’expression Python -1e-100 % 1e100 est 1e100-1e-100, qui ne peut pas être représenté exactement par un flottant et donc qui est arrondi à 1e100. Pour cette raison, la fonction fmod() est généralement privilégiée quand des flottants sont manipulés, alors que l’expression Python x % y est privilégiée quand des entiers sont manipulés.

math.frexp(x)

Renvoie la mantisse et l’exposant de x dans un couple (m, e). m est un flottant et e est un entier tels que x == m * 2**e exactement. Si x vaut zéro, renvoie (0, 0), sinon 0.5 <= abs(m) < 1. Ceci est utilisé pour « extraire » la représentation interne d’un flottant de manière portable.

math.fsum(iterable)

Renvoie une somme flottante exacte des valeurs dans l’itérable. Évite la perte de précision en gardant plusieurs sommes partielles intermédiaires :

>>> sum([.1, .1, .1, .1, .1, .1, .1, .1, .1, .1])
0.9999999999999999
>>> fsum([.1, .1, .1, .1, .1, .1, .1, .1, .1, .1])
1.0

La précision de cet algorithme dépend des garanties arithmétiques de IEEE-754 et des cas standards où le mode d’arrondi est half-even. Sur certaines versions non Windows, la bibliothèque C sous-jacente utilise une addition par précision étendue et peut occasionnellement effectuer un double-arrondi sur une somme intermédiaire causant la prise d’une mauvaise valeur du bit de poids faible.

Pour de plus amples discussions et deux approches alternatives, voir ASPN cookbook recipes for accurate floating point summation [https://code.activestate.com/recipes/393090/].

math.gcd(a, b)

Renvoie le plus grand diviseur commun des entiers a et b. Si a ou b est différent de zéro, la valeur de gcd(a, b) est le plus grand entier positif qui divise à la fois a et b. gcd(0, 0) renvoie 0.

Nouveau dans la version 3.5.

math.isclose(a, b, *, rel_tol=1e-09, abs_tol=0.0)

Renvoie True si les valeurs a et b sont proches l’une de l’autre, et False sinon.

Déterminer si deux valeurs sont considérées comme « proches » se fait à l’aide des tolérances absolues et relatives passées en paramètres.

rel_tol est la tolérance relative — c’est la différence maximale permise entre a et b, relativement à la plus grande valeur de a ou de b. Par exemple, pour définir une tolérance de 5%,, précisez rel_tol=0.05. La tolérance par défaut est 1e-09, ce qui assure que deux valeurs sont les mêmes à partir de la 9e décimale. rel_tol doit être supérieur à zéro.

abs_tol est la tolérance absolue minimale — utile pour les comparaisons proches de zéro. abs_tol doit valoir au moins zéro.

Si aucune erreur n’est rencontrée, le résultat sera : abs(a-b) <= max(rel_tol * max(abs(a), abs(b)), abs_tol).

Les valeurs spécifiques suivantes : NaN, inf, et -inf définies dans la norme IEEE 754 seront manipulées selon les règles du standard IEEE. En particulier, NaN n’est considéré proche d’aucune autre valeur, NaN inclus. inf et -inf ne sont considérées proches que d’elles-mêmes.

Nouveau dans la version 3.5.

Voir aussi

PEP 485 [https://www.python.org/dev/peps/pep-0485] — Une fonction pour tester des quasi-égalités

math.isfinite(x)

Renvoie True si n n’est ni infini, ni NaN, et False sinon. (Notez que 0.0 est considéré comme fini.)

Nouveau dans la version 3.2.

math.isinf(x)

Renvoie True si x vaut l’infini positif ou négatif, et False sinon.

math.isnan(x)

Renvoie True si x est NaN (Not a Number, ou Pas un Nombre en français), et False sinon.

math.ldexp(x, i)

Renvoie x * (2**i). C’est essentiellement l’inverse de la fonction frexp().

math.modf(x)

Renvoie les parties entière et fractionnelle de x. Les deux résultats ont le signe de x et sont flottants.

math.trunc(x)

Renvoie la valeur Real x tronquée en un Integral (habituellement un entier). Délègue à x.__trunc__().

Notez que les fonctions frexp() et modf() ont un système d’appel différent de leur homologue C : elles prennent un seul argument et renvoient une paire de valeurs au lieu de placer la seconde valeur de retour dans un paramètre de sortie (cela n’existe pas en Python).

Pour les fonctions ceil(), floor(), et modf(), notez que tous les nombres flottants de magnitude suffisamment grande sont des entiers exacts. Les flottants de Python n’ont généralement pas plus de 53 bits de précision (tels que le type C double de la plate-forme), en quel cas tout flottant x tel que abs(x) >= 2**52 n’a aucun bit fractionnel.

9.2.2. Fonctions logarithme et exponentielle

math.exp(x)

Renvoie e**x.

math.expm1(x)

Renvoie e**x - 1. Pour de petits flottants, la soustraction exp(x) - 1 peut résulter en une perte significative de précision [https://en.wikipedia.org/wiki/Loss_of_significance]; la fonction expm1() fournit un moyen de calculer cette quantité en précision complète :

>>> from math import exp, expm1
>>> exp(1e-5) - 1  # gives result accurate to 11 places
1.0000050000069649e-05
>>> expm1(1e-5)    # result accurate to full precision
1.0000050000166668e-05

Nouveau dans la version 3.2.

math.log(x[, base])

Avec un argument, renvoie le logarithme naturel de x (en base e).

Avec deux arguments, renvoie le logarithme de x en la base donnée, calculé par log(x)/log(base).

math.log1p(x)

Renvoie le logarithme naturel de 1+x (en base e). Le résultat est calculé par un moyen qui reste exact pour x proche de zéro.

math.log2(x)

Renvoie le logarithme en base 2 de x. C’est en général plus précis que log(x, 2).

Nouveau dans la version 3.3.

Voir aussi

int.bit_length() renvoie le nombre de bits nécessaires pour représenter un entier en binaire, en excluant le signe et les zéros de début.

math.log10(x)

Renvoie le logarithme de x en base 10. C’est habituellement plus exact que log(x, 10).

math.pow(x, y)

Renvoie x élevé à la puissance y. Les cas exceptionnels suivent l’annexe “F” du standard C99 autant que possible. En particulier, pow(1.0, x) et pow(x, 0.0) renvoient toujours 1.0, même si x est zéro ou NaN. Si à la fois x et y sont finis, x est négatif et y n’est pas entier, alors pow(x, y) est non défini et lève une ValueError.

À l’inverse de l’opérateur interne **, la fonction math.pow() convertit ses deux arguments en float. Utilisez ** ou la primitive pow() pour calculer des puissances exactes d’entiers.

math.sqrt(x)

Renvoie la racine carrée de x.

9.2.3. Fonctions trigonométriques

math.acos(x)

Renvoie l’arc cosinus de x, en radians.

math.asin(x)

Renvoie l’arc sinus de x, en radians.

math.atan(x)

Renvoie l’arc tangente de x, en radians.

math.atan2(y, x)

Renvoie atan(y / x), en radians. Le résultat est entre -pi et pi. Le vecteur du plan allant de l’origine vers le point (x, y) forme cet angle avec l’axe X positif. L’intérêt de atan2() est que le signe des deux entrées est connu. Donc elle peut calculer le bon quadrant pour l’angle. par exemple atan(1) et atan2(1, 1) donnent tous deux pi/4, mais atan2(-1, -1) donne -3*pi/4.

math.cos(x)

Renvoie le cosinus de x radians.

math.hypot(x, y)

Renvoie la norme euclidienne sqrt(x*x + y*y). C’est la longueur du vecteur allant de l’origine au point (x, y).

math.sin(x)

Renvoie le sinus de x radians.

math.tan(x)

Renvoie la tangente de x radians.

9.2.4. Conversion angulaire

math.degrees(x)

Convertit l’angle x de radians en degrés.

math.radians(x)

Convertit l’ange x de degrés en radians.

9.2.5. Fonctions hyperboliques

Les fonctions hyperboliques [https://fr.wikipedia.org/wiki/Fonction_hyperbolique] sont analogues à des fonctions trigonométriques qui sont basées sur des hyperboles au lieu de cercles.

math.acosh(x)

Renvoie l’arc cosinus hyperbolique de x.

math.asinh(x)

Renvoie l’arc sinus hyperbolique de x.

math.atanh(x)

Renvoie l’arc tangente hyperbolique de x.

math.cosh(x)

Renvoie le cosinus hyperbolique de x.

math.sinh(x)

Renvoie le sinus hyperbolique de x.

math.tanh(x)

Renvoie la tangente hyperbolique de x.

9.2.6. Fonctions spéciales

math.erf(x)

Renvoie la fonction d’erreur [https://en.wikipedia.org/wiki/Error_function] en x.

La fonction erf() peut être utilisée pour calculer des fonctions statistiques usuelles telles que la répartition de la loi normale [https://fr.wikipedia.org/wiki/Loi_normale#D.C3.A9finition_par_la_fonction_de_r.C3.A9partition] :

def phi(x):
    'Cumulative distribution function for the standard normal distribution'
    return (1.0 + erf(x / sqrt(2.0))) / 2.0

Nouveau dans la version 3.2.

math.erfc(x)

Renvoie la fonction d’erreur complémentaire en x. La fonction d’erreur complémentaire [https://fr.wikipedia.org/wiki/Fonction_d'erreur] est définie par 1.0 - erf(x). Elle est utilisée pour les grandes valeurs de x, où la soustraction en partant de 1,0 entraînerait une perte de précision [https://en.wikipedia.org/wiki/Loss_of_significance].

Nouveau dans la version 3.2.

math.gamma(x)

Renvoie la fonction Gamma [https://fr.wikipedia.org/wiki/Fonction_gamma] en x.

Nouveau dans la version 3.2.

math.lgamma(x)

Renvoie le logarithme naturel de la valeur absolue de la fonction gamma en x.

Nouveau dans la version 3.2.

9.2.7. Constantes

math.pi

La constante mathématique π = 3.141592…, à la précision disponile.

math.e

La constante mathématique e = 2.718281…, à la précision disponible.

math.tau

La constante mathématique τ = 6.283185…, à la précision disponible. Tau est une constante du cercle égale à 2π, le ratio entre la circonférence d’un cercle et son rayon. Pour en apprendre plus sur Tau, regardez la vidéo de Vi Hart, Pi is (still) Wrong [https://www.youtube.com/watch?v=jG7vhMMXagQ], et proffitez-en (ou pas) pour céléberer (ou pas) le Jour de Tau [http://tauday.com/] en mangeant (ou pas) deux fois plus camembert. (Y’a un jeu de mot, en anglais, avec le Tau day, c’est eating twice as much pie! (« deux fois plus de π » ?).

Nouveau dans la version 3.6.

math.inf

Un flottant positif infini. (Pour un infini négatif, utilisez -math.inf.) Équivalent au résultat de float('inf').

Nouveau dans la version 3.5.

math.nan

Un flottant valant NaN. Équivalent au résultat de float('nan').

Nouveau dans la version 3.5.

CPython implementation detail: Le module math consiste majoritairement en un conteneur pour les fonctions mathématiques de la bibliothèque C de la plate-forme. Le comportement dans les cas spéciaux suit l’annexe “F” du standard C99 quand c’est approprié. L’implémentation actuelle lève une ValueError pour les opérations invalides telles que sqrt(-1.0) ou log(0.0) (où le standard C99 recommande de signaler que l’opération est invalide ou qu’il y a division par zéro), et une OverflowError pour les résultats qui débordent (par exemple exp(1000.0)). NaN ne sera renvoyé pour aucune des fonctions ci-dessus, sauf si au moins un des arguments de la fonction vaut NaN. Dans ce cas, la plupart des fonctions renvoient NaN, mais (à nouveau, selon l’annexe “F” du standard C99) il y a quelques exceptions à cette règle, par exemple pow(float('nan'), 0.0) ou hypot(float('nan'), float('inf')).

Notez que Python ne fait aucun effort pour distinguer les NaNs signalétiques des NaNs silencieux, et le comportement de signalement des NaNs reste non-spécifié. Le comportement standard est de traiter tous les NaNs comme s’ils étaient silencieux.

Voir aussi

Module cmath

Version complexe de beaucoup de ces fonctions.

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9.3. Fonctions mathématiques pour nombres complexes — cmath

Ce module est toujours disponible. Il fournit l’accès aux fonctions mathématiques pour les nombres complexes.Les fonctions de ce module acceptent les entiers, les nombres flottants ou les nombres complexes comme arguments. Elles accepteront également tout objet Python ayant une méthode __complex__() ou __float__() : ces méthodes sont utilisées pour convertir l’objet en un nombre complexe ou respectivement un nombre flottant, et la fonction est ensuite appliquée sur le résultat de la conversion.

Note

Sur les plate-formes avec un support système et matériel des zéros signés, les fonctions incluant une coupure complexe sont continues de chaque côté de la coupure : le signe du zéro distingue les deux extrémités de la coupure. Sur les plate-formes ne supportant pas les zéros signés, la continuité est spécifiée en-dessous.

9.3.1. Conversion vers et à partir de coordonnées polaires

Un nombre complexe Python z est stocké de manière interne en coordonnées cartésiennes. Il est entièrement défini par sa partie réelle z.real et sa partie complexe z.imag. En d’autres termes :

z == z.real + z.imag*1j

Les coordonnées polaires donnent une manière alternative de représenter un nombre complexe. En coordonnées polaires, un nombre complexe z est défini par son module r et par son argument (angle de phase) phi. Le module r est la distance entre z et l’origine, alors que l’argument phi est l’angle (dans le sens inverse des aiguilles d’une montre, ou sens trigonométrique), mesuré en radians, à partir de l’axe X positif, et vers le segment de droite joignant z à l’origine.

Les fonctions suivantes peuvent être utilisées pour convertir à partir des coordonnées rectangulaires natives vers les coordonnées polaires, et vice-versa.

cmath.phase(x)

Renvoie l’argument de x, dans un nombre flottant. phase(x) est équivalent à math.atan2(x.imag, x.real). Le résultat se situe dans l’intervalle [-π, +π], et la coupure par cette opération se situe sur l’axe X négatif, continue par au-dessus. Sur les systèmes supportant les zéros signés (ce qui inclut la plupart des systèmes utilisés actuellement), cela signifie que le signe du résultat est le même que x.imag même quand x.imag vaut zéro :

>>> phase(complex(-1.0, 0.0))
3.141592653589793
>>> phase(complex(-1.0, -0.0))
-3.141592653589793

Note

Le module (valeur absolue) d’un nombre complexe x peut être calculé en utilisant la primitive abs(). Il n’y a pas de fonction spéciale du module cmath pour cette opération.

cmath.polar(x)

Renvoie la représentation de x en coordonnées polaires. Renvoie une paire (r, phi) où r est le module de x et phi est l’argument de x. polar(x) est équivalent à (abs(x), phase(x)).

cmath.rect(r, phi)

Renvoie le nombre complexe x dont les coordonnées polaires sont r et phi. Équivalent à r * (math.cos(phi) + math.sin(phi)*1j).

9.3.2. Fonctions logarithme et exponentielle

cmath.exp(x)

Renvoie la valeur exponentielle e**x.

cmath.log(x[, base])

Renvoie le logarithme de x dans la base précisée. Si la base n’est pas spécifiée, le logarithme naturel (népérien) de x est renvoyé. Il y a une coupure, partant de 0 sur l’axe réel négatif et vers -∞, continue par au-dessus.

cmath.log10(x)

Renvoie le logarithme en base 10 de x. Elle a la même coupure que log().

cmath.sqrt(x)

Renvoie la racine carrée de x. Elle a la même coupure que log().

9.3.3. Fonctions trigonométriques

cmath.acos(x)

Renvoie l’arc cosinus de x. Il y a deux coupures : une allant de 1 sur l’axe réel vers ∞, continue par en-dessous ; l’autre allant de -1 sur l’axe réel vers -∞, continue par au-dessus.

cmath.asin(x)

Renvoie l’arc sinus de x. Elle a les mêmes coupures que acos().

cmath.atan(x)

Renvoie la tangente de x. l y a deux coupures : une allant de 1j sur l’axe imaginaire vers ∞j, continue par la droite ; l’autre allant de -1j sur l’axe imaginaire vers -∞j, continue par la gauche.

cmath.cos(x)

Renvoie le cosinus de x.

cmath.sin(x)

Renvoie le sinus de x.

cmath.tan(x)

Renvoie la tangente de x.

9.3.4. Fonctions hyperboliques

cmath.acosh(x)

Renvoie l’arc cosinus hyperbolique de x. Il y a une coupure, allant de 1 sur l’axe réel vers -∞, continue par au-dessus.

cmath.asinh(x)

Renvoie l’arc sinus hyperbolique de x. Il y a deux coupures : une allant de 1j sur l’axe imaginaire vers ∞j, continue par la droite ; l’autre allant de -1j sur l’axe imaginaire vers ∞j, continue par la gauche.

cmath.atanh(x)

Renvoie l’arc tangente hyperbolique de x. Il y a deux coupures : une allant de 1 sur l’axe réel allant vers ∞, continue par en-dessous ; l’autre allant de -1 sur l’axe réel vers -∞, continue par au-dessus.

cmath.cosh(x)

Renvoie le cosinus hyperbolique de x.

cmath.sinh(x)

Renvoie le sinus hyperbolique de x.

cmath.tanh(x)

Renvoie la tangente hyperbolique de x.

9.3.5. Fonctions de classifications

cmath.isfinite(x)

Renvoie True si la partie réelle et la partie imaginaire de x sont finies, et False sinon.

Nouveau dans la version 3.2.

cmath.isinf(x)

Renvoie True si soit la partie réelle ou la partie imaginaire de x est infinie, et False sinon.

cmath.isnan(x)

Renvoie True si soit la partie réelle ou la partie imaginaire de x est NaN, et False sinon.

cmath.isclose(a, b, *, rel_tol=1e-09, abs_tol=0.0)

Renvoie True si les valeurs a et b sont proches l’une de l’autre, et False sinon.

Déterminer si deux valeurs sont proches se fait à l’aide des tolérances absolues et relatives données en paramètres.

rel_tol est la tolérance relative – c’est la différence maximale permise entre a et b, relativement à la plus grande valeur de a ou de b. Par exemple, pour définir une tolérance de 5%,, précisez rel_tol=0.05. La tolérance par défaut est 1e-09, ce qui assure que deux valeurs sont les mêmes à partir de la 9e décimale. rel_tol doit être supérieur à zéro.

abs_tol est la tolérance absolue minimale – utile pour les comparaisons proches de zéro. abs_tol doit valoir au moins zéro.

Si aucune erreur n’est rencontrée, le résultat sera : abs(a-b) <= max(rel_tol * max(abs(a), abs(b)), abs_tol).

Les valeurs spécifiques suivantes : NaN, inf, et -inf définies dans la norme IEEE 754 seront manipulées selon les règles du standard IEEE. En particulier, NaN n’est considéré proche d’aucune autre valeur, NaN inclus. inf et -inf ne sont considérés proches que d’eux-mêmes.

Nouveau dans la version 3.5.

Voir aussi

PEP 485 [https://www.python.org/dev/peps/pep-0485] – Une fonction pour tester des égalités approximées

9.3.6. Constantes

cmath.pi

La constante mathématique π, en tant que flottant.

cmath.e

La constante mathématique e, en tant que flottant.

cmath.tau

La constante mathématique τ, sous forme de flottant.

Nouveau dans la version 3.6.

cmath.inf

Nombre à virgule flottante positif infini. Équivaut à float('inf').

Nouveau dans la version 3.6.

cmath.infj

Nombre complexe dont la partie réelle vaut zéro et la partie imaginaire un infini positif. Équivalent à complex(0.0, float('inf')).

Nouveau dans la version 3.6.

cmath.nan

Un nombre à virgule flottante NaN (Not a number). Équivalent à float('nan').

Nouveau dans la version 3.6.

cmath.nanj

Nombre complexe dont la partie réelle vaut zéro et la partie imaginaire vaut un NaN. Équivalent à complex(0.0, float('nan')).

Nouveau dans la version 3.6.

Notez que la sélection de fonctions est similaire, mais pas identique, à celles du module math. La raison d’avoir deux modules est que certains utilisateurs ne sont pas intéressés par les nombres complexes, et peut-être ne savent même pas ce qu’ils sont. Ils préféreraient alors que math.sqrt(-1) lève une exception au lieu de renvoyer un nombre complexe. Également, notez que les fonctions définies dans cmath renvoient toujours un nombre complexe, même si le résultat peut être exprimé à l’aide d’un nombre réel (en quel cas la partie imaginaire du complexe vaut zéro).

Une note sur les coupures : ce sont des courbes sur lesquelles la fonction n’est pas continue. Ce sont des caractéristiques nécessaires de beaucoup de fonctions complexes. Il est supposé que si vous avez besoin d’utiliser des fonctions complexes, vous comprendrez ce que sont les coupures. Consultez n’importe quel livre (pas trop élémentaire) sur les variables complexes pour plus d’informations. Pour des informations sur les choix des coupures à des fins numériques, voici une bonne référence :

Voir aussi

Kahan, W: Branch cuts for complex elementary functions; or, Much ado about nothing’s sign bit. In Iserles, A., and Powell, M. (eds.), The state of the art in numerical analysis. Clarendon Press (1987) pp165–211.

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9.4. decimal — Arithmétique décimale en virgule fixe et flottante

Code source : Lib/decimal.py [https://github.com/python/cpython/tree/3.6/Lib/decimal.py]

Le module decimal fournit une arithmétique en virgule flottante rapide et produisant des arrondis mathématiquement corrects. Il possède plusieurs avantages en comparaison au type float :

Le module decimal « est basé sur un modèle en virgule flottante conçu pour les humains, qui suit ce principe directeur : l’ordinateur doit fournir un modèle de calcul qui fonctionne de la même manière que le calcul qu’on apprend à l’école » – extrait (traduit) de la spécification de l’arithmétique décimale.

Les nombres décimaux peuvent être représentés exactement en base décimale flottante. En revanche, des nombres tels que 1.1 ou 1.2 n’ont pas de représentation exacte en base binaire flottante. L’utilisateur final ne s’attend typiquement pas à obtenir 3.3000000000000003 lorsqu’il saisit 1.1 + 2.2, ce qui se passe en arithmétique binaire à virgule flottante.

Ces inexactitudes ont des conséquences en arithmétique. En base décimale à virgule flottante, 0.1 + 0.1 + 0.1 - 0.3 est exactement égal à zéro. En virgule flottante binaire, l’ordinateur l’évalue à 5.5511151231257827e-017. Bien que très proche de zéro, cette différence induit des erreurs lors des tests d’égalité, erreurs qui peuvent s’accumuler. Pour ces raisons decimal est le module utilisé pour des applications comptables ayant des contraintes strictes de fiabilité.

Le module decimal incorpore la notion de chiffres significatifs, tels que 1.30 + 1.20 est égal à 2.50. Le dernier zéro n’est conservé que pour respecter le nombre de chiffres significatifs. C’est également l’affichage préféré pour représenter des sommes d’argent. Pour la multiplication, l’approche « scolaire » utilise tout les chiffres présents dans les facteurs. Par exemple, 1.3 * 1.2 donnerait 1.56 tandis que 1.30 * 1.20 donnerait 1.5600.

Contrairement à l’arithmétique en virgule flottante binaire, le module decimal possède un paramètre de précision ajustable (par défaut à 28 chiffres significatifs) qui peut être aussi élevée que nécessaire pour un problème donné :

>>> from decimal import *
>>> getcontext().prec = 6
>>> Decimal(1) / Decimal(7)
Decimal('0.142857')
>>> getcontext().prec = 28
>>> Decimal(1) / Decimal(7)
Decimal('0.1428571428571428571428571429')

L’arithmétique binaire et décimale en virgule flottante sont implémentées selon des standards publiés. Alors que le type float n’expose qu’une faible portion de ses capacités, le module decimal expose tous les composants nécessaires du standard. Lorsque nécessaire, le développeur a un contrôle total de la gestion de signal et de l’arrondi. Cela inclut la possibilité de forcer une arithmétique exacte en utilisant des exceptions pour bloquer toute opération inexacte.

Le module decimal a été conçu pour gérer « sans préjugé, à la fois une arithmétique décimale non-arrondie (aussi appelée arithmétique en virgule fixe) et à la fois une arithmétique en virgule flottante. » (extrait traduit de la spécification de l’arithmétique décimale).

Le module est conçu autour de trois concepts : le nombre décimal, le contexte arithmétique et les signaux.

Un Decimal est immuable. Il a un signe, un coefficient, et un exposant. Pour préserver le nombre de chiffres significatifs, les zéros en fin de chaîne ne sont pas tronqués. Les décimaux incluent aussi des valeurs spéciales telles que Infinity, -Infinity, et NaN. Le standard fait également la différence entre -0 et +0.

Le contexte de l’arithmétique est un environnement qui permet de configurer une précision, une règle pour l’arrondi, des limites sur l’exposant, des options indiquant le résultat des opérations et si les signaux (remontés lors d’opérations illégales) sont traités comme des exceptions Python. Les options d’arrondi incluent ROUND_CEILING, ROUND_DOWN, ROUND_FLOOR, ROUND_HALF_DOWN, ROUND_HALF_EVEN, ROUND_HALF_UP, ROUND_UP, et ROUND_05UP.

Les signaux sont des groupes de conditions exceptionnelles qui surviennent durant le calcul. Selon les besoins de l’application, les signaux peuvent être ignorés, considérés comme de l’information, ou bien traités comme des exceptions. Les signaux dans le module decimal sont : Clamped, InvalidOperation, DivisionByZero, Inexact, Rounded, Subnormal, Overflow, Underflow et FloatOperation.

Chaque signal est configurable indépendamment. Quand une opération illégale survient, le signal est mis à 1, puis s’il est configuré pour, une exception est levée. La mise à 1 est persistante, l’utilisateur doit donc les remettre à zéro avant de commencer un calcul qu’il souhaite surveiller.

Voir aussi

La spécification d’IBM sur l’arithmétique décimale : The General Decimal Arithmetic Specification [http://speleotrove.com/decimal/decarith.html].

9.4.1. Introduction pratique

Commençons par importer le module, regarder le contexte actuel avec getcontext(), et si nécessaire configurer la précision, l’arrondi, et la gestion des signaux :

>>> from decimal import *
>>> getcontext()
Context(prec=28, rounding=ROUND_HALF_EVEN, Emin=-999999, Emax=999999,
        capitals=1, clamp=0, flags=[], traps=[Overflow, DivisionByZero,
        InvalidOperation])

>>> getcontext().prec = 7       # Set a new precision

Les instances de Decimal peuvent être construites avec des int, des str, des floats ou des tuples. La construction depuis un entier ou un float effectue la conversion exacte de cet entier ou de ce float. Les nombres décimaux incluent des valeurs spéciales telles que NaN qui signifie en anglais « Not a number », en français « pas un nombre », des Infinity positifs ou négatifs et -0 :

>>> getcontext().prec = 28
>>> Decimal(10)
Decimal('10')
>>> Decimal('3.14')
Decimal('3.14')
>>> Decimal(3.14)
Decimal('3.140000000000000124344978758017532527446746826171875')
>>> Decimal((0, (3, 1, 4), -2))
Decimal('3.14')
>>> Decimal(str(2.0 ** 0.5))
Decimal('1.4142135623730951')
>>> Decimal(2) ** Decimal('0.5')
Decimal('1.414213562373095048801688724')
>>> Decimal('NaN')
Decimal('NaN')
>>> Decimal('-Infinity')
Decimal('-Infinity')

Si un signal FloatOperation est détecté, un mélange accidentel d’objets Decimal et de float dans les constructeurs ou des opérations de comparaisons, une exception est levée :

>>> c = getcontext()
>>> c.traps[FloatOperation] = True
>>> Decimal(3.14)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
decimal.FloatOperation: [<class 'decimal.FloatOperation'>]
>>> Decimal('3.5') < 3.7
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
decimal.FloatOperation: [<class 'decimal.FloatOperation'>]
>>> Decimal('3.5') == 3.5
True

Nouveau dans la version 3.3.

Le nombre de chiffres significatifs d’un nouvel objet Decimal est déterminé entièrement par le nombre de chiffres saisis. La précision et les règles d’arrondis n’interviennent que lors d’opérations arithmétiques.

>>> getcontext().prec = 6
>>> Decimal('3.0')
Decimal('3.0')
>>> Decimal('3.1415926535')
Decimal('3.1415926535')
>>> Decimal('3.1415926535') + Decimal('2.7182818285')
Decimal('5.85987')
>>> getcontext().rounding = ROUND_UP
>>> Decimal('3.1415926535') + Decimal('2.7182818285')
Decimal('5.85988')

Si les limites internes de la version en C sont dépassées, la construction d’un objet décimal lève l’exception InvalidOperation :

>>> Decimal("1e9999999999999999999")
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
decimal.InvalidOperation: [<class 'decimal.InvalidOperation'>]

Modifié dans la version 3.3.

Les objets Decimal interagissent très bien avec le reste de Python. Voici quelques exemple d’opérations avec des décimaux :

>>> data = list(map(Decimal, '1.34 1.87 3.45 2.35 1.00 0.03 9.25'.split()))
>>> max(data)
Decimal('9.25')
>>> min(data)
Decimal('0.03')
>>> sorted(data)
[Decimal('0.03'), Decimal('1.00'), Decimal('1.34'), Decimal('1.87'),
 Decimal('2.35'), Decimal('3.45'), Decimal('9.25')]
>>> sum(data)
Decimal('19.29')
>>> a,b,c = data[:3]
>>> str(a)
'1.34'
>>> float(a)
1.34
>>> round(a, 1)
Decimal('1.3')
>>> int(a)
1
>>> a * 5
Decimal('6.70')
>>> a * b
Decimal('2.5058')
>>> c % a
Decimal('0.77')

Et certaines fonctions mathématiques sont également disponibles sur des instances de Decimal :

>>> getcontext().prec = 28
>>> Decimal(2).sqrt()
Decimal('1.414213562373095048801688724')
>>> Decimal(1).exp()
Decimal('2.718281828459045235360287471')
>>> Decimal('10').ln()
Decimal('2.302585092994045684017991455')
>>> Decimal('10').log10()
Decimal('1')

La méthode quantize() arrondit un nombre à un exposant fixe. Cette méthode est utile pour des applications monétaires qui arrondissent souvent un résultat à un nombre de chiffres significatifs exact :

>>> Decimal('7.325').quantize(Decimal('.01'), rounding=ROUND_DOWN)
Decimal('7.32')
>>> Decimal('7.325').quantize(Decimal('1.'), rounding=ROUND_UP)
Decimal('8')

Comme montré plus haut, la fonction getcontext() accède au contexte actuel et permet de modifier les paramètres. Cette approche répond aux besoins de la plupart des applications.

Pour un travail plus avancé, il peut être utile de créer des contextes alternatifs en utilisant le constructeur de Context. Pour activer cet objet Context, utilisez la fonction setcontext().

En accord avec le standard, le module decimal fournit des objets Context standards, BasicContext et ExtendedContext. Le premier est particulièrement utile pour le débogage car beaucoup des pièges sont activés dans cet objet.

>>> myothercontext = Context(prec=60, rounding=ROUND_HALF_DOWN)
>>> setcontext(myothercontext)
>>> Decimal(1) / Decimal(7)
Decimal('0.142857142857142857142857142857142857142857142857142857142857')

>>> ExtendedContext
Context(prec=9, rounding=ROUND_HALF_EVEN, Emin=-999999, Emax=999999,
        capitals=1, clamp=0, flags=[], traps=[])
>>> setcontext(ExtendedContext)
>>> Decimal(1) / Decimal(7)
Decimal('0.142857143')
>>> Decimal(42) / Decimal(0)
Decimal('Infinity')

>>> setcontext(BasicContext)
>>> Decimal(42) / Decimal(0)
Traceback (most recent call last):
  File "<pyshell#143>", line 1, in -toplevel-
    Decimal(42) / Decimal(0)
DivisionByZero: x / 0

Les objets Context ont aussi des options pour détecter des opérations illégales lors des calculs. Ces options restent activées jusqu’à ce qu’elles soit remises à zéro de manière explicite. Il convient donc de remettre à zéro ces options avant chaque inspection de chaque calcul, avec la méthode clear_flags().

>>> setcontext(ExtendedContext)
>>> getcontext().clear_flags()
>>> Decimal(355) / Decimal(113)
Decimal('3.14159292')
>>> getcontext()
Context(prec=9, rounding=ROUND_HALF_EVEN, Emin=-999999, Emax=999999,
        capitals=1, clamp=0, flags=[Inexact, Rounded], traps=[])

Les options montrent que l’approximation de Pi par une fraction a été arrondie (les chiffres au delà de la précision spécifiée par l’objet Context ont été tronqués) et que le résultat est différent (certains des chiffres tronqués étaient différents de zéro).

L’activation des pièges se fait en utilisant un dictionnaire dans l’attribut traps de l’objet Context :

>>> setcontext(ExtendedContext)
>>> Decimal(1) / Decimal(0)
Decimal('Infinity')
>>> getcontext().traps[DivisionByZero] = 1
>>> Decimal(1) / Decimal(0)
Traceback (most recent call last):
  File "<pyshell#112>", line 1, in -toplevel-
    Decimal(1) / Decimal(0)
DivisionByZero: x / 0

La plupart des applications n’ajustent l’objet Context qu’une seule fois, au démarrage. Et, dans beaucoup d’applications, les données sont convertie une fois pour toutes en Decimal. Une fois le Context initialisé, et les objets Decimal créés, l’essentiel du programme manipule la donnée de la même manière qu’avec les autres types numériques Python.

9.4.2. Les objets Decimal

class decimal.Decimal(value="0", context=None)

Construire un nouvel objet Decimal à partir de value.

value peut être un entier, une chaîne de caractères, un tuple, float, ou une autre instance de Decimal. Si value n’est pas fourni, le constructeur renvoie Decimal('0'). Si value est une chaîne de caractère, elle doit correspondre à la syntaxe décimale en dehors des espaces de début et de fin, ou des tirets bas, qui sont enlevés :

sign           ::=  '+' | '-'
digit          ::=  '0' | '1' | '2' | '3' | '4' | '5' | '6' | '7' | '8' | '9'
indicator      ::=  'e' | 'E'
digits         ::=  digit [digit]...
decimal-part   ::=  digits '.' [digits] | ['.'] digits
exponent-part  ::=  indicator [sign] digits
infinity       ::=  'Infinity' | 'Inf'
nan            ::=  'NaN' [digits] | 'sNaN' [digits]
numeric-value  ::=  decimal-part [exponent-part] | infinity
numeric-string ::=  [sign] numeric-value | [sign] nan

Les chiffres codés en Unicode sont aussi autorisés, là ou digit apparaît. Cela inclut des chiffres décimaux venant d’autres alphabets (par exemple les chiffres indo-arabes ou Devanagari) ainsi que les chiffres de pleine largeur '\uff10' jusqu’à '\uff19'.

Si value est un tuple, il doit avoir 3 éléments, le signe (0 pour positif ou 1 pour négatif), un tuple de chiffres, et un entier représentant l’exposant. Par exemple, Decimal((0, (1, 4, 1, 4), -3)) construit l’objet Decimal('1.414').

Si value est un float, la valeur en binaire flottant est convertie exactement à son équivalent décimal. Cette conversion peut parfois nécessiter 53 chiffres significatifs ou plus. Par exemple, Decimal(float('1.1')) devient Decimal('1.100000000000000088817841970012523233890533447265625').

La précision spécifiée dans Context n’affecte pas le nombre de chiffres stockés. Cette valeur est déterminée exclusivement par le nombre de chiffres dans value. Par exemple, Decimal('3.00000') enregistre les 5 zéros même si la précision du contexte est de 3.

L’objectif de l’argument context est de déterminer ce que Python doit faire si value est une chaîne avec un mauvais format. Si l’option InvalidOperation est activée, une exception est levée, sinon le constructeur renvoie un objet Decimal avec la valeur NaN.

Une fois construit, les objets Decimal sont immuables.

Modifié dans la version 3.2: L’argument du constructeur peut désormais être un objet float.

Modifié dans la version 3.3: Un argument float lève une exception si l’option FloatOperation est activé. Par défaut l’option ne l’est pas.

Modifié dans la version 3.6: Les tirets bas sont autorisés pour regrouper, tout comme pour l’arithmétique en virgule fixe et flottante.

Les objets Decimal partagent beaucoup de propriétés avec les autres types numériques natifs tels que float et int. Toutes les opérations mathématiques et méthodes sont conservées. De même les objets Decimal peuvent être copiés, sérialisés via le module pickle, affichés, utilisés comme clé de dictionnaire, éléments d’ensembles, comparés, classés, et convertis vers un autre type (tel que float ou int).

Il existe quelques différences mineures entre l’arithmétique entre les objets décimaux et l’arithmétique avec les entiers et les float. Quand l’opérateur modulo % est appliqué sur des objets décimaux, le signe du résultat est le signe du dividend plutôt que le signe du diviseur :

>>> (-7) % 4
1
>>> Decimal(-7) % Decimal(4)
Decimal('-3')

L’opérateur division entière, // se comporte de la même manière, retournant la partie entière du quotient, plutôt que son arrondi, de manière à préserver l’identité d’Euclide x == (x // y) * y + x % y :

>>> -7 // 4
-2
>>> Decimal(-7) // Decimal(4)
Decimal('-1')

Les opérateurs // et % implémentent la division entière et le reste (ou modulo), respectivement, tel que décrit dans la spécification.

Les objets Decimal ne peuvent généralement pas être combinés avec des float ou des objets fractions.Fraction lors d’opérations arithmétiques : tout addition entre un Decimal avec un float, par exemple, lève une exception TypeError. Cependant, il est possible d’utiliser les opérateurs de comparaison entre instances de Decimal avec les autres types numériques. Cela évite d’avoir des résultats absurdes lors des tests d’égalité entre différents types.

Modifié dans la version 3.2: Les comparaisons inter-types entre Decimal et les autres types numériques sont désormais intégralement gérés.

In addition to the standard numeric properties, decimal floating point objects also have a number of specialized methods:

adjusted()

Return the adjusted exponent after shifting out the coefficient’s rightmost digits until only the lead digit remains: Decimal('321e+5').adjusted() returns seven. Used for determining the position of the most significant digit with respect to the decimal point.

as_integer_ratio()

Return a pair (n, d) of integers that represent the given Decimal instance as a fraction, in lowest terms and with a positive denominator:

>>> Decimal('-3.14').as_integer_ratio()
(-157, 50)

La conversion est exacte. Lève une OverflowError sur l’infini et ValueError sur les Nan’s.

Nouveau dans la version 3.6.

as_tuple()

Return a named tuple representation of the number: DecimalTuple(sign, digits, exponent).

canonical()

Return the canonical encoding of the argument. Currently, the encoding of a Decimal instance is always canonical, so this operation returns its argument unchanged.

compare(other, context=None)

Compare the values of two Decimal instances. compare() returns a Decimal instance, and if either operand is a NaN then the result is a NaN:

a or b is a NaN  ==> Decimal('NaN')
a < b            ==> Decimal('-1')
a == b           ==> Decimal('0')
a > b            ==> Decimal('1')

compare_signal(other, context=None)

This operation is identical to the compare() method, except that all NaNs signal. That is, if neither operand is a signaling NaN then any quiet NaN operand is treated as though it were a signaling NaN.

compare_total(other, context=None)

Compare two operands using their abstract representation rather than their numerical value. Similar to the compare() method, but the result gives a total ordering on Decimal instances. Two Decimal instances with the same numeric value but different representations compare unequal in this ordering:

>>> Decimal('12.0').compare_total(Decimal('12'))
Decimal('-1')

Quiet and signaling NaNs are also included in the total ordering. The result of this function is Decimal('0') if both operands have the same representation, Decimal('-1') if the first operand is lower in the total order than the second, and Decimal('1') if the first operand is higher in the total order than the second operand. See the specification for details of the total order.

This operation is unaffected by context and is quiet: no flags are changed and no rounding is performed. As an exception, the C version may raise InvalidOperation if the second operand cannot be converted exactly.

compare_total_mag(other, context=None)

Compare two operands using their abstract representation rather than their value as in compare_total(), but ignoring the sign of each operand. x.compare_total_mag(y) is equivalent to x.copy_abs().compare_total(y.copy_abs()).

This operation is unaffected by context and is quiet: no flags are changed and no rounding is performed. As an exception, the C version may raise InvalidOperation if the second operand cannot be converted exactly.

conjugate()

Just returns self, this method is only to comply with the Decimal Specification.

copy_abs()

Return the absolute value of the argument. This operation is unaffected by the context and is quiet: no flags are changed and no rounding is performed.

copy_negate()

Return the negation of the argument. This operation is unaffected by the context and is quiet: no flags are changed and no rounding is performed.

copy_sign(other, context=None)

Return a copy of the first operand with the sign set to be the same as the sign of the second operand. For example:

>>> Decimal('2.3').copy_sign(Decimal('-1.5'))
Decimal('-2.3')

This operation is unaffected by context and is quiet: no flags are changed and no rounding is performed. As an exception, the C version may raise InvalidOperation if the second operand cannot be converted exactly.

exp(context=None)

Return the value of the (natural) exponential function e**x at the given number. The result is correctly rounded using the ROUND_HALF_EVEN rounding mode.

>>> Decimal(1).exp()
Decimal('2.718281828459045235360287471')
>>> Decimal(321).exp()
Decimal('2.561702493119680037517373933E+139')

from_float(f)

Classmethod that converts a float to a decimal number, exactly.

Note Decimal.from_float(0.1) is not the same as Decimal(“0.1”). Since 0.1 is not exactly representable in binary floating point, the value is stored as the nearest representable value which is 0x1.999999999999ap-4. That equivalent value in decimal is 0.1000000000000000055511151231257827021181583404541015625.

Note

From Python 3.2 onwards, a Decimal instance can also be constructed directly from a float.

>>> Decimal.from_float(0.1)
Decimal('0.1000000000000000055511151231257827021181583404541015625')
>>> Decimal.from_float(float('nan'))
Decimal('NaN')
>>> Decimal.from_float(float('inf'))
Decimal('Infinity')
>>> Decimal.from_float(float('-inf'))
Decimal('-Infinity')

Nouveau dans la version 3.1.

fma(other, third, context=None)

Fused multiply-add. Return self*other+third with no rounding of the intermediate product self*other.

>>> Decimal(2).fma(3, 5)
Decimal('11')

is_canonical()

Return True if the argument is canonical and False otherwise. Currently, a Decimal instance is always canonical, so this operation always returns True.

is_finite()

Return True if the argument is a finite number, and False if the argument is an infinity or a NaN.

is_infinite()

Return True if the argument is either positive or negative infinity and False otherwise.

is_nan()

Return True if the argument is a (quiet or signaling) NaN and False otherwise.

is_normal(context=None)

Return True if the argument is a normal finite number. Return False if the argument is zero, subnormal, infinite or a NaN.

is_qnan()

Return True if the argument is a quiet NaN, and False otherwise.

is_signed()

Return True if the argument has a negative sign and False otherwise. Note that zeros and NaNs can both carry signs.

is_snan()

Return True if the argument is a signaling NaN and False otherwise.

is_subnormal(context=None)

Return True if the argument is subnormal, and False otherwise.

is_zero()

Return True if the argument is a (positive or negative) zero and False otherwise.

ln(context=None)

Return the natural (base e) logarithm of the operand. The result is correctly rounded using the ROUND_HALF_EVEN rounding mode.

log10(context=None)

Return the base ten logarithm of the operand. The result is correctly rounded using the ROUND_HALF_EVEN rounding mode.

logb(context=None)

For a nonzero number, return the adjusted exponent of its operand as a Decimal instance. If the operand is a zero then Decimal('-Infinity') is returned and the DivisionByZero flag is raised. If the operand is an infinity then Decimal('Infinity') is returned.

logical_and(other, context=None)

logical_and() is a logical operation which takes two logical operands (see Logical operands). The result is the digit-wise and of the two operands.

logical_invert(context=None)

logical_invert() is a logical operation. The result is the digit-wise inversion of the operand.

logical_or(other, context=None)

logical_or() is a logical operation which takes two logical operands (see Logical operands). The result is the digit-wise or of the two operands.

logical_xor(other, context=None)

logical_xor() is a logical operation which takes two logical operands (see Logical operands). The result is the digit-wise exclusive or of the two operands.

max(other, context=None)

Like max(self, other) except that the context rounding rule is applied before returning and that NaN values are either signaled or ignored (depending on the context and whether they are signaling or quiet).

max_mag(other, context=None)

Similar to the max() method, but the comparison is done using the absolute values of the operands.

min(other, context=None)

Like min(self, other) except that the context rounding rule is applied before returning and that NaN values are either signaled or ignored (depending on the context and whether they are signaling or quiet).

min_mag(other, context=None)

Similar to the min() method, but the comparison is done using the absolute values of the operands.

next_minus(context=None)

Return the largest number representable in the given context (or in the current thread’s context if no context is given) that is smaller than the given operand.

next_plus(context=None)

Return the smallest number representable in the given context (or in the current thread’s context if no context is given) that is larger than the given operand.

next_toward(other, context=None)

If the two operands are unequal, return the number closest to the first operand in the direction of the second operand. If both operands are numerically equal, return a copy of the first operand with the sign set to be the same as the sign of the second operand.

normalize(context=None)

Normalize the number by stripping the rightmost trailing zeros and converting any result equal to Decimal('0') to Decimal('0e0'). Used for producing canonical values for attributes of an equivalence class. For example, Decimal('32.100') and Decimal('0.321000e+2') both normalize to the equivalent value Decimal('32.1').

number_class(context=None)

Return a string describing the class of the operand. The returned value is one of the following ten strings.

"-Infinity", indicating that the operand is negative infinity.

"-Normal", indicating that the operand is a negative normal number.

"-Subnormal", indicating that the operand is negative and subnormal.

"-Zero", indicating that the operand is a negative zero.

"+Zero", indicating that the operand is a positive zero.

"+Subnormal", indicating that the operand is positive and subnormal.

"+Normal", indicating that the operand is a positive normal number.

"+Infinity", indicating that the operand is positive infinity.

"NaN", indicating that the operand is a quiet NaN (Not a Number).

"sNaN", indicating that the operand is a signaling NaN.

quantize(exp, rounding=None, context=None)

Return a value equal to the first operand after rounding and having the exponent of the second operand.

>>> Decimal('1.41421356').quantize(Decimal('1.000'))
Decimal('1.414')

Unlike other operations, if the length of the coefficient after the quantize operation would be greater than precision, then an InvalidOperation is signaled. This guarantees that, unless there is an error condition, the quantized exponent is always equal to that of the right-hand operand.

Also unlike other operations, quantize never signals Underflow, even if the result is subnormal and inexact.

If the exponent of the second operand is larger than that of the first then rounding may be necessary. In this case, the rounding mode is determined by the rounding argument if given, else by the given context argument; if neither argument is given the rounding mode of the current thread’s context is used.

An error is returned whenever the resulting exponent is greater than Emax or less than Etiny.

radix()

Return Decimal(10), the radix (base) in which the Decimal class does all its arithmetic. Included for compatibility with the specification.

remainder_near(other, context=None)

Return the remainder from dividing self by other. This differs from self % other in that the sign of the remainder is chosen so as to minimize its absolute value. More precisely, the return value is self - n * other where n is the integer nearest to the exact value of self / other, and if two integers are equally near then the even one is chosen.

If the result is zero then its sign will be the sign of self.

>>> Decimal(18).remainder_near(Decimal(10))
Decimal('-2')
>>> Decimal(25).remainder_near(Decimal(10))
Decimal('5')
>>> Decimal(35).remainder_near(Decimal(10))
Decimal('-5')

rotate(other, context=None)

Return the result of rotating the digits of the first operand by an amount specified by the second operand. The second operand must be an integer in the range -precision through precision. The absolute value of the second operand gives the number of places to rotate. If the second operand is positive then rotation is to the left; otherwise rotation is to the right. The coefficient of the first operand is padded on the left with zeros to length precision if necessary. The sign and exponent of the first operand are unchanged.

same_quantum(other, context=None)

Test whether self and other have the same exponent or whether both are NaN.

This operation is unaffected by context and is quiet: no flags are changed and no rounding is performed. As an exception, the C version may raise InvalidOperation if the second operand cannot be converted exactly.

scaleb(other, context=None)

Return the first operand with exponent adjusted by the second. Equivalently, return the first operand multiplied by 10**other. The second operand must be an integer.

shift(other, context=None)

Return the result of shifting the digits of the first operand by an amount specified by the second operand. The second operand must be an integer in the range -precision through precision. The absolute value of the second operand gives the number of places to shift. If the second operand is positive then the shift is to the left; otherwise the shift is to the right. Digits shifted into the coefficient are zeros. The sign and exponent of the first operand are unchanged.

sqrt(context=None)

Return the square root of the argument to full precision.

to_eng_string(context=None)

Convert to a string, using engineering notation if an exponent is needed.

Engineering notation has an exponent which is a multiple of 3. This can leave up to 3 digits to the left of the decimal place and may require the addition of either one or two trailing zeros.

For example, this converts Decimal('123E+1') to Decimal('1.23E+3').

to_integral(rounding=None, context=None)

Identical to the to_integral_value() method. The to_integral name has been kept for compatibility with older versions.

to_integral_exact(rounding=None, context=None)

Round to the nearest integer, signaling Inexact or Rounded as appropriate if rounding occurs. The rounding mode is determined by the rounding parameter if given, else by the given context. If neither parameter is given then the rounding mode of the current context is used.

to_integral_value(rounding=None, context=None)

Round to the nearest integer without signaling Inexact or Rounded. If given, applies rounding; otherwise, uses the rounding method in either the supplied context or the current context.

9.4.2.1. Logical operands

The logical_and(), logical_invert(), logical_or(), and logical_xor() methods expect their arguments to be logical operands. A logical operand is a Decimal instance whose exponent and sign are both zero, and whose digits are all either 0 or 1.

9.4.3. Context objects

Contexts are environments for arithmetic operations. They govern precision, set rules for rounding, determine which signals are treated as exceptions, and limit the range for exponents.

Each thread has its own current context which is accessed or changed using the getcontext() and setcontext() functions:

decimal.getcontext()

Return the current context for the active thread.

decimal.setcontext(c)

Set the current context for the active thread to c.

You can also use the with statement and the localcontext() function to temporarily change the active context.

decimal.localcontext(ctx=None)

Return a context manager that will set the current context for the active thread to a copy of ctx on entry to the with-statement and restore the previous context when exiting the with-statement. If no context is specified, a copy of the current context is used.

For example, the following code sets the current decimal precision to 42 places, performs a calculation, and then automatically restores the previous context:

from decimal import localcontext

with localcontext() as ctx:
    ctx.prec = 42   # Perform a high precision calculation
    s = calculate_something()
s = +s  # Round the final result back to the default precision

New contexts can also be created using the Context constructor described below. In addition, the module provides three pre-made contexts:

class decimal.BasicContext

This is a standard context defined by the General Decimal Arithmetic Specification. Precision is set to nine. Rounding is set to ROUND_HALF_UP. All flags are cleared. All traps are enabled (treated as exceptions) except Inexact, Rounded, and Subnormal.

Because many of the traps are enabled, this context is useful for debugging.

class decimal.ExtendedContext

This is a standard context defined by the General Decimal Arithmetic Specification. Precision is set to nine. Rounding is set to ROUND_HALF_EVEN. All flags are cleared. No traps are enabled (so that exceptions are not raised during computations).

Because the traps are disabled, this context is useful for applications that prefer to have result value of NaN or Infinity instead of raising exceptions. This allows an application to complete a run in the presence of conditions that would otherwise halt the program.

class decimal.DefaultContext

This context is used by the Context constructor as a prototype for new contexts. Changing a field (such a precision) has the effect of changing the default for new contexts created by the Context constructor.

This context is most useful in multi-threaded environments. Changing one of the fields before threads are started has the effect of setting system-wide defaults. Changing the fields after threads have started is not recommended as it would require thread synchronization to prevent race conditions.

In single threaded environments, it is preferable to not use this context at all. Instead, simply create contexts explicitly as described below.

The default values are prec=28, rounding=ROUND_HALF_EVEN, and enabled traps for Overflow, InvalidOperation, and DivisionByZero.

In addition to the three supplied contexts, new contexts can be created with the Context constructor.

class decimal.Context(prec=None, rounding=None, Emin=None, Emax=None, capitals=None, clamp=None, flags=None, traps=None)

Creates a new context. If a field is not specified or is None, the default values are copied from the DefaultContext. If the flags field is not specified or is None, all flags are cleared.

prec is an integer in the range [1, MAX_PREC] that sets the precision for arithmetic operations in the context.

The rounding option is one of the constants listed in the section Rounding Modes.

The traps and flags fields list any signals to be set. Generally, new contexts should only set traps and leave the flags clear.

The Emin and Emax fields are integers specifying the outer limits allowable for exponents. Emin must be in the range [MIN_EMIN, 0], Emax in the range [0, MAX_EMAX].

The capitals field is either 0 or 1 (the default). If set to 1, exponents are printed with a capital E; otherwise, a lowercase e is used: Decimal('6.02e+23').

The clamp field is either 0 (the default) or 1. If set to 1, the exponent e of a Decimal instance representable in this context is strictly limited to the range Emin - prec + 1 <= e <= Emax - prec + 1. If clamp is 0 then a weaker condition holds: the adjusted exponent of the Decimal instance is at most Emax. When clamp is 1, a large normal number will, where possible, have its exponent reduced and a corresponding number of zeros added to its coefficient, in order to fit the exponent constraints; this preserves the value of the number but loses information about significant trailing zeros. For example:

>>> Context(prec=6, Emax=999, clamp=1).create_decimal('1.23e999')
Decimal('1.23000E+999')

A clamp value of 1 allows compatibility with the fixed-width decimal interchange formats specified in IEEE 754.

The Context class defines several general purpose methods as well as a large number of methods for doing arithmetic directly in a given context. In addition, for each of the Decimal methods described above (with the exception of the adjusted() and as_tuple() methods) there is a corresponding Context method. For example, for a Context instance C and Decimal instance x, C.exp(x) is equivalent to x.exp(context=C). Each Context method accepts a Python integer (an instance of int) anywhere that a Decimal instance is accepted.

clear_flags()

Resets all of the flags to 0.

clear_traps()

Resets all of the traps to 0.

Nouveau dans la version 3.3.

copy()

Return a duplicate of the context.

copy_decimal(num)

Return a copy of the Decimal instance num.

create_decimal(num)

Creates a new Decimal instance from num but using self as context. Unlike the Decimal constructor, the context precision, rounding method, flags, and traps are applied to the conversion.

This is useful because constants are often given to a greater precision than is needed by the application. Another benefit is that rounding immediately eliminates unintended effects from digits beyond the current precision. In the following example, using unrounded inputs means that adding zero to a sum can change the result:

>>> getcontext().prec = 3
>>> Decimal('3.4445') + Decimal('1.0023')
Decimal('4.45')
>>> Decimal('3.4445') + Decimal(0) + Decimal('1.0023')
Decimal('4.44')

This method implements the to-number operation of the IBM specification. If the argument is a string, no leading or trailing whitespace or underscores are permitted.

create_decimal_from_float(f)

Creates a new Decimal instance from a float f but rounding using self as the context. Unlike the Decimal.from_float() class method, the context precision, rounding method, flags, and traps are applied to the conversion.

>>> context = Context(prec=5, rounding=ROUND_DOWN)
>>> context.create_decimal_from_float(math.pi)
Decimal('3.1415')
>>> context = Context(prec=5, traps=[Inexact])
>>> context.create_decimal_from_float(math.pi)
Traceback (most recent call last):
    ...
decimal.Inexact: None

Nouveau dans la version 3.1.

Etiny()

Returns a value equal to Emin - prec + 1 which is the minimum exponent value for subnormal results. When underflow occurs, the exponent is set to Etiny.

Etop()

Returns a value equal to Emax - prec + 1.

The usual approach to working with decimals is to create Decimal instances and then apply arithmetic operations which take place within the current context for the active thread. An alternative approach is to use context methods for calculating within a specific context. The methods are similar to those for the Decimal class and are only briefly recounted here.

abs(x)

Renvoie la valeur absolue de x.

add(x, y)

Return the sum of x and y.

canonical(x)

Returns the same Decimal object x.

compare(x, y)

Compares x and y numerically.

compare_signal(x, y)

Compares the values of the two operands numerically.

compare_total(x, y)

Compares two operands using their abstract representation.

compare_total_mag(x, y)

Compares two operands using their abstract representation, ignoring sign.

copy_abs(x)

Returns a copy of x with the sign set to 0.

copy_negate(x)

Returns a copy of x with the sign inverted.

copy_sign(x, y)

Copies the sign from y to x.

divide(x, y)

Return x divided by y.

divide_int(x, y)

Return x divided by y, truncated to an integer.

divmod(x, y)

Divides two numbers and returns the integer part of the result.

exp(x)

Returns e ** x.

fma(x, y, z)

Returns x multiplied by y, plus z.

is_canonical(x)

Returns True if x is canonical; otherwise returns False.

is_finite(x)

Returns True if x is finite; otherwise returns False.

is_infinite(x)

Returns True if x is infinite; otherwise returns False.

is_nan(x)

Returns True if x is a qNaN or sNaN; otherwise returns False.

is_normal(x)

Returns True if x is a normal number; otherwise returns False.

is_qnan(x)

Returns True if x is a quiet NaN; otherwise returns False.

is_signed(x)

Returns True if x is negative; otherwise returns False.

is_snan(x)

Returns True if x is a signaling NaN; otherwise returns False.

is_subnormal(x)

Returns True if x is subnormal; otherwise returns False.

is_zero(x)

Returns True if x is a zero; otherwise returns False.

ln(x)

Returns the natural (base e) logarithm of x.

log10(x)

Returns the base 10 logarithm of x.

logb(x)

Returns the exponent of the magnitude of the operand’s MSD.

logical_and(x, y)

Applies the logical operation and between each operand’s digits.

logical_invert(x)

Invert all the digits in x.

logical_or(x, y)

Applies the logical operation or between each operand’s digits.

logical_xor(x, y)

Applies the logical operation xor between each operand’s digits.

max(x, y)

Compares two values numerically and returns the maximum.

max_mag(x, y)

Compares the values numerically with their sign ignored.

min(x, y)

Compares two values numerically and returns the minimum.

min_mag(x, y)

Compares the values numerically with their sign ignored.

minus(x)

Minus corresponds to the unary prefix minus operator in Python.

multiply(x, y)

Return the product of x and y.

next_minus(x)

Returns the largest representable number smaller than x.

next_plus(x)

Returns the smallest representable number larger than x.

next_toward(x, y)

Returns the number closest to x, in direction towards y.

normalize(x)

Reduces x to its simplest form.

number_class(x)

Returns an indication of the class of x.

plus(x)

Plus corresponds to the unary prefix plus operator in Python. This operation applies the context precision and rounding, so it is not an identity operation.

power(x, y, modulo=None)

Return x to the power of y, reduced modulo modulo if given.

With two arguments, compute x**y. If x is negative then y must be integral. The result will be inexact unless y is integral and the result is finite and can be expressed exactly in “precision” digits. The rounding mode of the context is used. Results are always correctly-rounded in the Python version.

Modifié dans la version 3.3: The C module computes power() in terms of the correctly-rounded exp() and ln() functions. The result is well-defined but only « almost always correctly-rounded ».

With three arguments, compute (x**y) % modulo. For the three argument form, the following restrictions on the arguments hold:

all three arguments must be integral

y must be nonnegative

at least one of x or y must be nonzero

modulo must be nonzero and have at most “precision” digits

The value resulting from Context.power(x, y, modulo) is equal to the value that would be obtained by computing (x**y) % modulo with unbounded precision, but is computed more efficiently. The exponent of the result is zero, regardless of the exponents of x, y and modulo. The result is always exact.

quantize(x, y)

Returns a value equal to x (rounded), having the exponent of y.

radix()

Just returns 10, as this is Decimal, :)

remainder(x, y)

Returns the remainder from integer division.

The sign of the result, if non-zero, is the same as that of the original dividend.

remainder_near(x, y)

Returns x - y * n, where n is the integer nearest the exact value of x / y (if the result is 0 then its sign will be the sign of x).

rotate(x, y)

Returns a rotated copy of x, y times.

same_quantum(x, y)

Returns True if the two operands have the same exponent.

scaleb(x, y)

Returns the first operand after adding the second value its exp.

shift(x, y)

Returns a shifted copy of x, y times.

sqrt(x)

Square root of a non-negative number to context precision.

subtract(x, y)

Return the difference between x and y.

to_eng_string(x)

Convert to a string, using engineering notation if an exponent is needed.

Engineering notation has an exponent which is a multiple of 3. This can leave up to 3 digits to the left of the decimal place and may require the addition of either one or two trailing zeros.

to_integral_exact(x)

Rounds to an integer.

to_sci_string(x)

Converts a number to a string using scientific notation.

9.4.4. Constantes

The constants in this section are only relevant for the C module. They are also included in the pure Python version for compatibility.

32-bit

64-bit

decimal.MAX_PREC

425000000

999999999999999999

decimal.MAX_EMAX

425000000

999999999999999999

decimal.MIN_EMIN

-425000000

-999999999999999999

decimal.MIN_ETINY

-849999999

-1999999999999999997

decimal.HAVE_THREADS

The default value is True. If Python is compiled without threads, the C version automatically disables the expensive thread local context machinery. In this case, the value is False.

9.4.5. Rounding modes

decimal.ROUND_CEILING

Round towards Infinity.

decimal.ROUND_DOWN

Round towards zero.

decimal.ROUND_FLOOR

Round towards -Infinity.

decimal.ROUND_HALF_DOWN

Round to nearest with ties going towards zero.

decimal.ROUND_HALF_EVEN

Round to nearest with ties going to nearest even integer.

decimal.ROUND_HALF_UP

Round to nearest with ties going away from zero.

decimal.ROUND_UP

Round away from zero.

decimal.ROUND_05UP

Round away from zero if last digit after rounding towards zero would have been 0 or 5; otherwise round towards zero.

9.4.6. Signals

Signals represent conditions that arise during computation. Each corresponds to one context flag and one context trap enabler.

The context flag is set whenever the condition is encountered. After the computation, flags may be checked for informational purposes (for instance, to determine whether a computation was exact). After checking the flags, be sure to clear all flags before starting the next computation.

If the context’s trap enabler is set for the signal, then the condition causes a Python exception to be raised. For example, if the DivisionByZero trap is set, then a DivisionByZero exception is raised upon encountering the condition.

class decimal.Clamped

Altered an exponent to fit representation constraints.

Typically, clamping occurs when an exponent falls outside the context’s Emin and Emax limits. If possible, the exponent is reduced to fit by adding zeros to the coefficient.

class decimal.DecimalException

Base class for other signals and a subclass of ArithmeticError.

class decimal.DivisionByZero

Signals the division of a non-infinite number by zero.

Can occur with division, modulo division, or when raising a number to a negative power. If this signal is not trapped, returns Infinity or -Infinity with the sign determined by the inputs to the calculation.

class decimal.Inexact

Indicates that rounding occurred and the result is not exact.

Signals when non-zero digits were discarded during rounding. The rounded result is returned. The signal flag or trap is used to detect when results are inexact.

class decimal.InvalidOperation

An invalid operation was performed.

Indicates that an operation was requested that does not make sense. If not trapped, returns NaN. Possible causes include:

Infinity - Infinity
0 * Infinity
Infinity / Infinity
x % 0
Infinity % x
sqrt(-x) and x > 0
0 ** 0
x ** (non-integer)
x ** Infinity

class decimal.Overflow

Numerical overflow.

Indicates the exponent is larger than Emax after rounding has occurred. If not trapped, the result depends on the rounding mode, either pulling inward to the largest representable finite number or rounding outward to Infinity. In either case, Inexact and Rounded are also signaled.

class decimal.Rounded

Rounding occurred though possibly no information was lost.

Signaled whenever rounding discards digits; even if those digits are zero (such as rounding 5.00 to 5.0). If not trapped, returns the result unchanged. This signal is used to detect loss of significant digits.

class decimal.Subnormal

Exponent was lower than Emin prior to rounding.

Occurs when an operation result is subnormal (the exponent is too small). If not trapped, returns the result unchanged.

class decimal.Underflow

Numerical underflow with result rounded to zero.

Occurs when a subnormal result is pushed to zero by rounding. Inexact and Subnormal are also signaled.

class decimal.FloatOperation

Enable stricter semantics for mixing floats and Decimals.

If the signal is not trapped (default), mixing floats and Decimals is permitted in the Decimal constructor, create_decimal() and all comparison operators. Both conversion and comparisons are exact. Any occurrence of a mixed operation is silently recorded by setting FloatOperation in the context flags. Explicit conversions with from_float() or create_decimal_from_float() do not set the flag.

Otherwise (the signal is trapped), only equality comparisons and explicit conversions are silent. All other mixed operations raise FloatOperation.

The following table summarizes the hierarchy of signals:

exceptions.ArithmeticError(exceptions.Exception)
    DecimalException
        Clamped
        DivisionByZero(DecimalException, exceptions.ZeroDivisionError)
        Inexact
            Overflow(Inexact, Rounded)
            Underflow(Inexact, Rounded, Subnormal)
        InvalidOperation
        Rounded
        Subnormal
        FloatOperation(DecimalException, exceptions.TypeError)

9.4.7. Floating Point Notes

9.4.7.1. Mitigating round-off error with increased precision

The use of decimal floating point eliminates decimal representation error (making it possible to represent 0.1 exactly); however, some operations can still incur round-off error when non-zero digits exceed the fixed precision.

The effects of round-off error can be amplified by the addition or subtraction of nearly offsetting quantities resulting in loss of significance. Knuth provides two instructive examples where rounded floating point arithmetic with insufficient precision causes the breakdown of the associative and distributive properties of addition:

# Examples from Seminumerical Algorithms, Section 4.2.2.
>>> from decimal import Decimal, getcontext
>>> getcontext().prec = 8

>>> u, v, w = Decimal(11111113), Decimal(-11111111), Decimal('7.51111111')
>>> (u + v) + w
Decimal('9.5111111')
>>> u + (v + w)
Decimal('10')

>>> u, v, w = Decimal(20000), Decimal(-6), Decimal('6.0000003')
>>> (u*v) + (u*w)
Decimal('0.01')
>>> u * (v+w)
Decimal('0.0060000')

The decimal module makes it possible to restore the identities by expanding the precision sufficiently to avoid loss of significance:

>>> getcontext().prec = 20
>>> u, v, w = Decimal(11111113), Decimal(-11111111), Decimal('7.51111111')
>>> (u + v) + w
Decimal('9.51111111')
>>> u + (v + w)
Decimal('9.51111111')
>>>
>>> u, v, w = Decimal(20000), Decimal(-6), Decimal('6.0000003')
>>> (u*v) + (u*w)
Decimal('0.0060000')
>>> u * (v+w)
Decimal('0.0060000')

9.4.7.2. Special values

The number system for the decimal module provides special values including NaN, sNaN, -Infinity, Infinity, and two zeros, +0 and -0.

Infinities can be constructed directly with: Decimal('Infinity'). Also, they can arise from dividing by zero when the DivisionByZero signal is not trapped. Likewise, when the Overflow signal is not trapped, infinity can result from rounding beyond the limits of the largest representable number.

The infinities are signed (affine) and can be used in arithmetic operations where they get treated as very large, indeterminate numbers. For instance, adding a constant to infinity gives another infinite result.

Some operations are indeterminate and return NaN, or if the InvalidOperation signal is trapped, raise an exception. For example, 0/0 returns NaN which means « not a number ». This variety of NaN is quiet and, once created, will flow through other computations always resulting in another NaN. This behavior can be useful for a series of computations that occasionally have missing inputs — it allows the calculation to proceed while flagging specific results as invalid.

A variant is sNaN which signals rather than remaining quiet after every operation. This is a useful return value when an invalid result needs to interrupt a calculation for special handling.

The behavior of Python’s comparison operators can be a little surprising where a NaN is involved. A test for equality where one of the operands is a quiet or signaling NaN always returns False (even when doing Decimal('NaN')==Decimal('NaN')), while a test for inequality always returns True. An attempt to compare two Decimals using any of the <, <=, > or >= operators will raise the InvalidOperation signal if either operand is a NaN, and return False if this signal is not trapped. Note that the General Decimal Arithmetic specification does not specify the behavior of direct comparisons; these rules for comparisons involving a NaN were taken from the IEEE 854 standard (see Table 3 in section 5.7). To ensure strict standards-compliance, use the compare() and compare-signal() methods instead.

The signed zeros can result from calculations that underflow. They keep the sign that would have resulted if the calculation had been carried out to greater precision. Since their magnitude is zero, both positive and negative zeros are treated as equal and their sign is informational.

In addition to the two signed zeros which are distinct yet equal, there are various representations of zero with differing precisions yet equivalent in value. This takes a bit of getting used to. For an eye accustomed to normalized floating point representations, it is not immediately obvious that the following calculation returns a value equal to zero:

>>> 1 / Decimal('Infinity')
Decimal('0E-1000026')

9.4.8. Working with threads

The getcontext() function accesses a different Context object for each thread. Having separate thread contexts means that threads may make changes (such as getcontext().prec=10) without interfering with other threads.

Likewise, the setcontext() function automatically assigns its target to the current thread.

If setcontext() has not been called before getcontext(), then getcontext() will automatically create a new context for use in the current thread.

The new context is copied from a prototype context called DefaultContext. To control the defaults so that each thread will use the same values throughout the application, directly modify the DefaultContext object. This should be done before any threads are started so that there won’t be a race condition between threads calling getcontext(). For example:

# Set applicationwide defaults for all threads about to be launched
DefaultContext.prec = 12
DefaultContext.rounding = ROUND_DOWN
DefaultContext.traps = ExtendedContext.traps.copy()
DefaultContext.traps[InvalidOperation] = 1
setcontext(DefaultContext)

# Afterwards, the threads can be started
t1.start()
t2.start()
t3.start()
 . . .

9.4.9. Cas pratiques

Here are a few recipes that serve as utility functions and that demonstrate ways to work with the Decimal class:

def moneyfmt(value, places=2, curr='', sep=',', dp='.',
             pos='', neg='-', trailneg=''):
    """Convert Decimal to a money formatted string.

    places:  required number of places after the decimal point
    curr:    optional currency symbol before the sign (may be blank)
    sep:     optional grouping separator (comma, period, space, or blank)
    dp:      decimal point indicator (comma or period)
             only specify as blank when places is zero
    pos:     optional sign for positive numbers: '+', space or blank
    neg:     optional sign for negative numbers: '-', '(', space or blank
    trailneg:optional trailing minus indicator:  '-', ')', space or blank

    >>> d = Decimal('-1234567.8901')
    >>> moneyfmt(d, curr='$')
    '-$1,234,567.89'
    >>> moneyfmt(d, places=0, sep='.', dp='', neg='', trailneg='-')
    '1.234.568-'
    >>> moneyfmt(d, curr='$', neg='(', trailneg=')')
    '($1,234,567.89)'
    >>> moneyfmt(Decimal(123456789), sep=' ')
    '123 456 789.00'
    >>> moneyfmt(Decimal('-0.02'), neg='<', trailneg='>')
    '<0.02>'

    """
    q = Decimal(10) ** -places      # 2 places --> '0.01'
    sign, digits, exp = value.quantize(q).as_tuple()
    result = []
    digits = list(map(str, digits))
    build, next = result.append, digits.pop
    if sign:
        build(trailneg)
    for i in range(places):
        build(next() if digits else '0')
    if places:
        build(dp)
    if not digits:
        build('0')
    i = 0
    while digits:
        build(next())
        i += 1
        if i == 3 and digits:
            i = 0
            build(sep)
    build(curr)
    build(neg if sign else pos)
    return ''.join(reversed(result))

def pi():
    """Compute Pi to the current precision.

    >>> print(pi())
    3.141592653589793238462643383

    """
    getcontext().prec += 2  # extra digits for intermediate steps
    three = Decimal(3)      # substitute "three=3.0" for regular floats
    lasts, t, s, n, na, d, da = 0, three, 3, 1, 0, 0, 24
    while s != lasts:
        lasts = s
        n, na = n+na, na+8
        d, da = d+da, da+32
        t = (t * n) / d
        s += t
    getcontext().prec -= 2
    return +s               # unary plus applies the new precision

def exp(x):
    """Return e raised to the power of x.  Result type matches input type.

    >>> print(exp(Decimal(1)))
    2.718281828459045235360287471
    >>> print(exp(Decimal(2)))
    7.389056098930650227230427461
    >>> print(exp(2.0))
    7.38905609893
    >>> print(exp(2+0j))
    (7.38905609893+0j)

    """
    getcontext().prec += 2
    i, lasts, s, fact, num = 0, 0, 1, 1, 1
    while s != lasts:
        lasts = s
        i += 1
        fact *= i
        num *= x
        s += num / fact
    getcontext().prec -= 2
    return +s

def cos(x):
    """Return the cosine of x as measured in radians.

    The Taylor series approximation works best for a small value of x.
    For larger values, first compute x = x % (2 * pi).

    >>> print(cos(Decimal('0.5')))
    0.8775825618903727161162815826
    >>> print(cos(0.5))
    0.87758256189
    >>> print(cos(0.5+0j))
    (0.87758256189+0j)

    """
    getcontext().prec += 2
    i, lasts, s, fact, num, sign = 0, 0, 1, 1, 1, 1
    while s != lasts:
        lasts = s
        i += 2
        fact *= i * (i-1)
        num *= x * x
        sign *= -1
        s += num / fact * sign
    getcontext().prec -= 2
    return +s

def sin(x):
    """Return the sine of x as measured in radians.

    The Taylor series approximation works best for a small value of x.
    For larger values, first compute x = x % (2 * pi).

    >>> print(sin(Decimal('0.5')))
    0.4794255386042030002732879352
    >>> print(sin(0.5))
    0.479425538604
    >>> print(sin(0.5+0j))
    (0.479425538604+0j)

    """
    getcontext().prec += 2
    i, lasts, s, fact, num, sign = 1, 0, x, 1, x, 1
    while s != lasts:
        lasts = s
        i += 2
        fact *= i * (i-1)
        num *= x * x
        sign *= -1
        s += num / fact * sign
    getcontext().prec -= 2
    return +s

9.4.10. FAQ decimal

Q. C’est fastidieux de taper decimal.Decimal('1234.5'). Y a-t-il un moyen de réduire la frappe quand on utilise l’interpréteur interactif ?

R. Certains utilisateurs abrègent le constructeur en une seule lettre :

>>> D = decimal.Decimal
>>> D('1.23') + D('3.45')
Decimal('4.68')

Q. In a fixed-point application with two decimal places, some inputs have many places and need to be rounded. Others are not supposed to have excess digits and need to be validated. What methods should be used?

A. The quantize() method rounds to a fixed number of decimal places. If the Inexact trap is set, it is also useful for validation:

>>> TWOPLACES = Decimal(10) ** -2       # same as Decimal('0.01')

>>> # Round to two places
>>> Decimal('3.214').quantize(TWOPLACES)
Decimal('3.21')

>>> # Validate that a number does not exceed two places
>>> Decimal('3.21').quantize(TWOPLACES, context=Context(traps=[Inexact]))
Decimal('3.21')

>>> Decimal('3.214').quantize(TWOPLACES, context=Context(traps=[Inexact]))
Traceback (most recent call last):
   ...
Inexact: None

Q. Once I have valid two place inputs, how do I maintain that invariant throughout an application?

A. Some operations like addition, subtraction, and multiplication by an integer will automatically preserve fixed point. Others operations, like division and non-integer multiplication, will change the number of decimal places and need to be followed-up with a quantize() step:

>>> a = Decimal('102.72')           # Initial fixed-point values
>>> b = Decimal('3.17')
>>> a + b                           # Addition preserves fixed-point
Decimal('105.89')
>>> a - b
Decimal('99.55')
>>> a * 42                          # So does integer multiplication
Decimal('4314.24')
>>> (a * b).quantize(TWOPLACES)     # Must quantize non-integer multiplication
Decimal('325.62')
>>> (b / a).quantize(TWOPLACES)     # And quantize division
Decimal('0.03')

In developing fixed-point applications, it is convenient to define functions to handle the quantize() step:

>>> def mul(x, y, fp=TWOPLACES):
...     return (x * y).quantize(fp)
>>> def div(x, y, fp=TWOPLACES):
...     return (x / y).quantize(fp)

>>> mul(a, b)                       # Automatically preserve fixed-point
Decimal('325.62')
>>> div(b, a)
Decimal('0.03')

Q. There are many ways to express the same value. The numbers 200, 200.000, 2E2, and 02E+4 all have the same value at various precisions. Is there a way to transform them to a single recognizable canonical value?

A. The normalize() method maps all equivalent values to a single representative:

>>> values = map(Decimal, '200 200.000 2E2 .02E+4'.split())
>>> [v.normalize() for v in values]
[Decimal('2E+2'), Decimal('2E+2'), Decimal('2E+2'), Decimal('2E+2')]

Q. Some decimal values always print with exponential notation. Is there a way to get a non-exponential representation?

A. For some values, exponential notation is the only way to express the number of significant places in the coefficient. For example, expressing 5.0E+3 as 5000 keeps the value constant but cannot show the original’s two-place significance.

If an application does not care about tracking significance, it is easy to remove the exponent and trailing zeroes, losing significance, but keeping the value unchanged:

>>> def remove_exponent(d):
...     return d.quantize(Decimal(1)) if d == d.to_integral() else d.normalize()

>>> remove_exponent(Decimal('5E+3'))
Decimal('5000')

Q. Is there a way to convert a regular float to a Decimal?

A. Yes, any binary floating point number can be exactly expressed as a Decimal though an exact conversion may take more precision than intuition would suggest:

>>> Decimal(math.pi)
Decimal('3.141592653589793115997963468544185161590576171875')

Q. Within a complex calculation, how can I make sure that I haven’t gotten a spurious result because of insufficient precision or rounding anomalies.

A. The decimal module makes it easy to test results. A best practice is to re-run calculations using greater precision and with various rounding modes. Widely differing results indicate insufficient precision, rounding mode issues, ill-conditioned inputs, or a numerically unstable algorithm.

Q. I noticed that context precision is applied to the results of operations but not to the inputs. Is there anything to watch out for when mixing values of different precisions?

A. Yes. The principle is that all values are considered to be exact and so is the arithmetic on those values. Only the results are rounded. The advantage for inputs is that « what you type is what you get ». A disadvantage is that the results can look odd if you forget that the inputs haven’t been rounded:

>>> getcontext().prec = 3
>>> Decimal('3.104') + Decimal('2.104')
Decimal('5.21')
>>> Decimal('3.104') + Decimal('0.000') + Decimal('2.104')
Decimal('5.20')

The solution is either to increase precision or to force rounding of inputs using the unary plus operation:

>>> getcontext().prec = 3
>>> +Decimal('1.23456789')      # unary plus triggers rounding
Decimal('1.23')

Alternatively, inputs can be rounded upon creation using the Context.create_decimal() method:

>>> Context(prec=5, rounding=ROUND_DOWN).create_decimal('1.2345678')
Decimal('1.2345')

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9.5. fractions — Nombres rationnels

Code source : Lib/fractions.py [https://github.com/python/cpython/tree/3.6/Lib/fractions.py]

Le module fractions fournit un support de l’arithmétique des nombres rationnels.

Une instance de Fraction peut être construite depuis une paire d’entiers, depuis un autre nombre rationnel, ou depuis une chaîne de caractères.

class fractions.Fraction(numerator=0, denominator=1)

class fractions.Fraction(other_fraction)

class fractions.Fraction(float)

class fractions.Fraction(decimal)

class fractions.Fraction(string)

La première version demande que numerator et denominator soient des instance de numbers.Rational et renvoie une instance de Fraction valant numerator/denominator. Si denominator vaut 0, une ZeroDivisionError est levée. La seconde version demande que other_fraction soit une instance de numbers.Rational et renvoie une instance de Fraction avec la même valeur. Les deux versions suivantes acceptent un float ou une instance de decimal.Decimal, et renvoient une instance de Fraction avec exactement la même valeur. Notez que les problèmes usuels des virgules flottantes binaires (voir Arithmétique en nombres à virgule flottante : problèmes et limites) font que Fraction(1.1) n’est pas exactement égal à 11/10, et donc Fraction(1.1) ne renvoie pas Fraction(11, 10) comme on pourrait le penser. (Mais référez-vous à la documentation de la méthode limit_denominator() ci-dessous.) La dernière version du constructeur attend une chaîne de caractères ou Unicode. La représentation habituelle de cette forme est :

[sign] numerator ['/' denominator]

où le sign optionnel peut être soit + soit -, et numerator et denominator (si présent) sont des chaînes de chiffres décimaux. De plus, toute chaîne qui représente une valeur finie et acceptée par le constructeur de float est aussi acceptée par celui de Fraction. Dans ces deux formes, la chaîne d’entrée peut aussi contenir des espaces en début ou en fin de chaîne. Voici quelques exemples :

>>> from fractions import Fraction
>>> Fraction(16, -10)
Fraction(-8, 5)
>>> Fraction(123)
Fraction(123, 1)
>>> Fraction()
Fraction(0, 1)
>>> Fraction('3/7')
Fraction(3, 7)
>>> Fraction(' -3/7 ')
Fraction(-3, 7)
>>> Fraction('1.414213 \t\n')
Fraction(1414213, 1000000)
>>> Fraction('-.125')
Fraction(-1, 8)
>>> Fraction('7e-6')
Fraction(7, 1000000)
>>> Fraction(2.25)
Fraction(9, 4)
>>> Fraction(1.1)
Fraction(2476979795053773, 2251799813685248)
>>> from decimal import Decimal
>>> Fraction(Decimal('1.1'))
Fraction(11, 10)

La classe Fraction hérite de la classe abstraite numbers.Rational, et implémente toutes les méthodes et opérations de cette classe. Les instances de Fraction sont hachables, et doivent être traitées comme immuables. En plus de cela, Fraction possède les propriétés et méthodes suivantes :

Modifié dans la version 3.2: Le constructeur de Fraction accepte maintenant des instances de float et decimal.Decimal.

numerator

Numérateur de la fraction irréductible.

denominator

Dénominateur de la fraction irréductible.

from_float(flt)

Cette méthode de classe construit un objet Fraction représentant la valeur exacte de flt, qui doit être de type float. Attention, Fraction.from_float(0.3) n’est pas la même valeur que Fraction(3, 10).

Note

Depuis Python 3.2, vous pouvez aussi construire une instance de Fraction directement depuis un float.

from_decimal(dec)

Cette méthode de classe construit un objet Fraction représentant la valeur exacte de dec, qui doit être de type decimal.Decimal.

Note

Depuis Python 3.2, vous pouvez aussi construire une instance de Fraction directement depuis une instance de decimal.Decimal.

limit_denominator(max_denominator=1000000)

Trouve et renvoie la Fraction la plus proche de self qui a au plus max_denominator comme dénominateur. Cette méthode est utile pour trouver des approximations rationnelles de nombres flottants donnés :

>>> from fractions import Fraction
>>> Fraction('3.1415926535897932').limit_denominator(1000)
Fraction(355, 113)

ou pour retrouver un nombre rationnel représenté par un flottant :

>>> from math import pi, cos
>>> Fraction(cos(pi/3))
Fraction(4503599627370497, 9007199254740992)
>>> Fraction(cos(pi/3)).limit_denominator()
Fraction(1, 2)
>>> Fraction(1.1).limit_denominator()
Fraction(11, 10)

__floor__()

Renvoie le plus grand int <= self. Cette méthode peut aussi être utilisée à travers la fonction math.floor().

>>> from math import floor
>>> floor(Fraction(355, 113))
3

__ceil__()

Renvoie le plus petit int >= self. Cette méthode peut aussi être utilisée à travers la fonction math.ceil().

__round__()

__round__(ndigits)

La première version renvoie l”int le plus proche de self, arrondissant les demis au nombre pair le plus proche. La seconde version arrondit self au plus proche multiple de Fraction(1, 10**ndigits) (logiquement, si ndigits est négatif), arrondissant toujours les demis au nombre pair le plus proche. Cette méthode peut aussi être utilisée à via la fonction round().

fractions.gcd(a, b)

Renvoie le plus grand diviseur commun (PGCD) des entiers a et b. Si a et b sont tous deux non nuls, alors la valeur absolue de gcd(a, b) est le plus grand entier qui divise à la fois a et b. gcd(a,b) a le même signe que b si b n’est pas nul ; autrement il prend le signe de a. gcd(0, 0) renvoie 0.

Obsolète depuis la version 3.5: Utilisez plutôt math.gcd().

Voir aussi

Module numbers

Les classes abstraites représentant la hiérarchie des nombres.

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9.6. random — Génère des nombres pseudo-aléatoires

Code source : Lib/random.py [https://github.com/python/cpython/tree/3.6/Lib/random.py]

Ce module implémente des générateurs de nombres pseudo-aléatoires pour différentes distributions.

Pour les entiers, il existe une sélection uniforme à partir d’une plage. Pour les séquences, il existe une sélection uniforme d’un élément aléatoire, une fonction pour générer une permutation aléatoire d’une liste sur place et une fonction pour un échantillonnage aléatoire sans remplacement.

Pour l’ensemble des réels, il y a des fonctions pour calculer des distributions uniformes, normales (gaussiennes), log-normales, exponentielles négatives, gamma et bêta. Pour générer des distributions d’angles, la distribution de von Mises est disponible.

Presque toutes les fonctions du module dépendent de la fonction de base random(), qui génère un nombre à virgule flottante aléatoire de façon uniforme dans la plage semi-ouverte [0.0, 1.0). Python utilise l’algorithme Mersenne Twister comme générateur de base. Il produit des flottants de précision de 53 bits et a une période de 2***19937-1. L’implémentation sous-jacente en C est à la fois rapide et compatible avec les programmes ayant de multiples fils d’exécution. Le Mersenne Twister est l’un des générateurs de nombres aléatoires les plus largement testés qui existent. Cependant, étant complètement déterministe, il n’est pas adapté à tous les usages et est totalement inadapté à des fins cryptographiques.

Les fonctions fournies par ce module dépendent en réalité de méthodes d’une instance cachée de la classe random.Random. Vous pouvez créer vos propres instances de Random pour obtenir des générateurs sans états partagés.

La classe Random peut également être sous-classée si vous voulez utiliser un générateur de base différent, de votre propre conception. Dans ce cas, remplacez les méthodes random(), seed(), gettsate() et setstate(). En option, un nouveau générateur peut fournir une méthode getrandbits() — ce qui permet à randrange() de produire des sélections sur une plage de taille arbitraire.

Le module random fournit également la classe SystemRandom qui utilise la fonction système os.urandom() pour générer des nombres aléatoires à partir de sources fournies par le système d’exploitation.

Avertissement

Les générateurs pseudo-aléatoires de ce module ne doivent pas être utilisés à des fins de sécurité. Pour des utilisations de sécurité ou cryptographiques, voir le module secrets.

Voir aussi

M. Matsumoto and T. Nishimura, « Mersenne Twister: A 623-dimensionally equidistributed uniform pseudorandom number generator », ACM Transactions on Modeling and Computer Simulation Vol. 8, No. 1, Janvier pp.3–30 1998.

Complementary-Multiply-with-Carry recipe [https://code.activestate.com/recipes/576707/] pour un autre générateur de nombres aléatoires avec une longue période et des opérations de mise à jour relativement simples.

9.6.1. Fonctions de gestion d’état

random.seed(a=None, version=2)

Initialise le générateur de nombres aléatoires.

Si a est omis ou None, l’heure système actuelle est utilisée. Si des sources aléatoires sont fournies par le système d’exploitation, elles sont utilisées à la place de l’heure système (voir la fonction os.urandom() pour les détails sur la disponibilité).

Si a est un entier, il est utilisé directement.

Avec la version 2 (par défaut), un objet str, bytes ou bytearray est converti en int et tous ses bits sont utilisés.

Avec la version 1 (fournie pour reproduire des séquences aléatoires produites par d’anciennes versions de Python), l’algorithme pour str et bytes génère une gamme plus étroite de graines.

Modifié dans la version 3.2: Passée à la version 2 du schéma qui utilise tous les bits d’une graine de chaîne de caractères.

random.getstate()

Renvoie un objet capturant l’état interne actuel du générateur. Cet objet peut être passé à setstate() pour restaurer cet état.

random.setstate(state)

Il convient que state ait été obtenu à partir d’un appel précédent à getstate(), et setstate() restaure l’état interne du générateur à ce qu’il était au moment où getstate() a été appelé.

random.getrandbits(k)

Renvoie un entier Python avec k bits aléatoires. Cette méthode est fournie avec le générateur MersenneTwister. Quelques autres générateurs peuvent également la fournir en option comme partie de l’API. Lorsqu’elle est disponible, getrandbits() permet à randrange() de gérer des gammes arbitrairement larges.

9.6.2. Fonctions pour les entiers

random.randrange(stop)

random.randrange(start, stop[, step])

Renvoie un élément sélectionné aléatoirement à partir de range(start, stop, step). C’est équivalent à choice(range(start, stop, step)), mais ne construit pas réellement un objet range.

Le motif d’argument positionnel correspond à celui de range(). N’utilisez pas d’arguments nommés parce que la fonction peut les utiliser de manière inattendue.

Modifié dans la version 3.2: randrange() est plus sophistiquée dans la production de valeurs uniformément distribuées. Auparavant, elle utilisait un style comme int(random()*n) qui pouvait produire des distributions légèrement inégales.

random.randint(a, b)

Renvoie un entier aléatoire N tel que a <= N <= b. Alias pour randrange(a, b+1).

9.6.3. Fonctions pour les séquences

random.choice(seq)

Renvoie un élément aléatoire de la séquence non vide seq. Si seq est vide, lève IndexError.

random.choices(population, weights=None, *, cum_weights=None, k=1)

Renvoie une liste de taille k d’éléments choisis dans la population avec remise. Si la population est vide, lève IndexError.

Si une séquence de poids est spécifiée, les tirages sont effectués en fonction des poids relatifs. Alternativement, si une séquence cum_weights est donnée, les tirages sont faits en fonction des poids cumulés (peut-être calculés en utilisant itertools.accumulate()). Par exemple, les poids relatifs [10, 5, 30, 5] sont équivalents aux poids cumulatifs [10, 15, 45, 50]. En interne, les poids relatifs sont convertis en poids cumulatifs avant d’effectuer les tirages, ce qui vous permet d’économiser du travail en fournissant des pondérations cumulatives.

Si ni weights ni cum_weights ne sont spécifiés, les tirages sont effectués avec une probabilité uniforme. Si une séquence de poids est fournie, elle doit être de la même longueur que la séquence population. Spécifier à la fois weights et cum_weights lève une TypeError.

The weights or cum_weights can use any numeric type that interoperates with the float values returned by random() (that includes integers, floats, and fractions but excludes decimals).

Nouveau dans la version 3.6.

random.shuffle(x[, random])

Mélange la séquence x sans créer de nouvelle instance (« sur place »).

L’argument optionnel random est une fonction sans argument renvoyant un nombre aléatoire à virgule flottante dans [0.0, 1.0); par défaut, c’est la fonction random().

Pour mélanger une séquence immuable et renvoyer une nouvelle liste mélangée, utilisez sample(x, k=len(x)) à la place.

Notez que même pour les petits len(x), le nombre total de permutations de x peut rapidement devenir plus grand que la période de la plupart des générateurs de nombres aléatoires. Cela implique que la plupart des permutations d’une longue séquence ne peuvent jamais être générées. Par exemple, une séquence de longueur 2080 est la plus grande qui puisse tenir dans la période du générateur de nombres aléatoires Mersenne Twister.

random.sample(population, k)

Renvoie une liste de k éléments uniques choisis dans la séquence ou l’ensemble de la population. Utilisé pour un tirage aléatoire sans remise.

Renvoie une nouvelle liste contenant des éléments de la population tout en laissant la population originale inchangée. La liste résultante est classée par ordre de sélection de sorte que toutes les sous-tranches soient également des échantillons aléatoires valides. Cela permet aux gagnants du tirage (l’échantillon) d’être divisés en gagnants du grand prix et en gagnants de la deuxième place (les sous-tranches).

Les membres de la population n’ont pas besoin d’être hachables ou uniques. Si la population contient des répétitions, alors chaque occurrence est un tirage possible dans l’échantillon.

Pour choisir un échantillon parmi un intervalle d’entiers, utilisez un objet range() comme argument. Ceci est particulièrement rapide et économe en mémoire pour un tirage dans une grande population : échantillon(range(10000000), k=60).

Si la taille de l’échantillon est supérieure à la taille de la population, une ValueError est levée.

9.6.4. Distributions pour les nombre réels

Les fonctions suivantes génèrent des distributions spécifiques en nombre réels. Les paramètres de fonction sont nommés d’après les variables correspondantes de l’équation de la distribution, telles qu’elles sont utilisées dans la pratique mathématique courante ; la plupart de ces équations peuvent être trouvées dans tout document traitant de statistiques.

random.random()

Renvoie le nombre aléatoire à virgule flottante suivant dans la plage [0.0, 1.0).

random.uniform(a, b)

Renvoie un nombre aléatoire à virgule flottante N tel que a <= N <= b pour a <= b et b <= N <= a pour b < a.

La valeur finale b peut ou non être incluse dans la plage selon l’arrondi à virgule flottante dans l’équation a + (b-a) * random().

random.triangular(low, high, mode)

Renvoie un nombre aléatoire en virgule flottante N tel que low <= N <= high et avec le mode spécifié entre ces bornes. Les limites low et high par défaut sont zéro et un. L’argument mode est par défaut le point médian entre les bornes, ce qui donne une distribution symétrique.

random.betavariate(alpha, beta)

Distribution bêta. Les conditions sur les paramètres sont alpha > 0 et beta > 0. Les valeurs renvoyées varient entre 0 et 1.

random.expovariate(lambd)

Distribution exponentielle. lambd est 1,0 divisé par la moyenne désirée. Ce ne doit pas être zéro. (Le paramètre aurait dû s’appeler « lambda », mais c’est un mot réservé en Python.) Les valeurs renvoyées vont de 0 à plus l’infini positif si lambd est positif, et de moins l’infini à 0 si lambd est négatif.

random.gammavariate(alpha, beta)

Distribution gamma. (Ce n’est pas la fonction gamma !) Les conditions sur les paramètres sont alpha > 0 et beta > 0.

La fonction de distribution de probabilité est :

          x ** (alpha - 1) * math.exp(-x / beta)
pdf(x) =  --------------------------------------
            math.gamma(alpha) * beta ** alpha

random.gauss(mu, sigma)

Distribution gaussienne. mu est la moyenne et sigma est la écart type. C’est légèrement plus rapide que la fonction normalvariate() définie ci-dessous.

random.lognormvariate(mu, sigma)

Logarithme de la distribution normale. Si vous prenez le logarithme naturel de cette distribution, vous obtiendrez une distribution normale avec mu moyen et écart-type sigma. mu peut avoir n’importe quelle valeur et sigma doit être supérieur à zéro.

random.normalvariate(mu, sigma)

Distribution normale. mu est la moyenne et sigma est l’écart type.

random.vonmisesvariate(mu, kappa)

mu est l’angle moyen, exprimé en radians entre 0 et 2*pi, et kappa est le paramètre de concentration, qui doit être supérieur ou égal à zéro. Si kappa est égal à zéro, cette distribution se réduit à un angle aléatoire uniforme sur la plage de 0 à 2*pi.

random.paretovariate(alpha)

Distribution de Pareto. alpha est le paramètre de forme.

random.weibullvariate(alpha, beta)

Distribution de Weibull. alpha est le paramètre de l’échelle et beta est le paramètre de forme.

9.6.5. Générateur alternatif

class random.SystemRandom([seed])

Classe qui utilise la fonction os.urandom() pour générer des nombres aléatoires à partir de sources fournies par le système d’exploitation. Non disponible sur tous les systèmes. Ne repose pas sur un état purement logiciel et les séquences ne sont pas reproductibles. Par conséquent, la méthode seed() n’a aucun effet et est ignorée. Les méthodes getstate() et setstate() lèvent NotImplementedError si vous les appelez.

9.6.6. Remarques sur la reproductibilité

Il est parfois utile de pouvoir reproduire les séquences données par un générateur de nombres pseudo-aléatoires. En réutilisant la même graine, la même séquence devrait être reproductible d’une exécution à l’autre tant que plusieurs processus ne sont pas en cours.

La plupart des algorithmes et des fonctions de génération de graine du module aléatoire sont susceptibles d’être modifiés d’une version à l’autre de Python, mais deux aspects sont garantis de ne pas changer :

Si une nouvelle méthode de génération de graine est ajoutée, une fonction rétro-compatible sera offerte.

La méthode random() du générateur continuera à produire la même séquence lorsque la fonction de génération de graine compatible recevra la même semence.

9.6.7. Exemples et recettes

Exemples de base :

>>> random()                             # Random float:  0.0 <= x < 1.0
0.37444887175646646

>>> uniform(2.5, 10.0)                   # Random float:  2.5 <= x < 10.0
3.1800146073117523

>>> expovariate(1 / 5)                   # Interval between arrivals averaging 5 seconds
5.148957571865031

>>> randrange(10)                        # Integer from 0 to 9 inclusive
7

>>> randrange(0, 101, 2)                 # Even integer from 0 to 100 inclusive
26

>>> choice(['win', 'lose', 'draw'])      # Single random element from a sequence
'draw'

>>> deck = 'ace two three four'.split()
>>> shuffle(deck)                        # Shuffle a list
>>> deck
['four', 'two', 'ace', 'three']

>>> sample([10, 20, 30, 40, 50], k=4)    # Four samples without replacement
[40, 10, 50, 30]

Simulations :

>>> # Six roulette wheel spins (weighted sampling with replacement)
>>> choices(['red', 'black', 'green'], [18, 18, 2], k=6)
['red', 'green', 'black', 'black', 'red', 'black']

>>> # Deal 20 cards without replacement from a deck of 52 playing cards
>>> # and determine the proportion of cards with a ten-value
>>> # (a ten, jack, queen, or king).
>>> deck = collections.Counter(tens=16, low_cards=36)
>>> seen = sample(list(deck.elements()), k=20)
>>> seen.count('tens') / 20
0.15

>>> # Estimate the probability of getting 5 or more heads from 7 spins
>>> # of a biased coin that settles on heads 60% of the time.
>>> trial = lambda: choices('HT', cum_weights=(0.60, 1.00), k=7).count('H') >= 5
>>> sum(trial() for i in range(10000)) / 10000
0.4169

>>> # Probability of the median of 5 samples being in middle two quartiles
>>> trial = lambda : 2500 <= sorted(choices(range(10000), k=5))[2]  < 7500
>>> sum(trial() for i in range(10000)) / 10000
0.7958

Exemple de *bootstrapping* statistique [https://fr.wikipedia.org/wiki/Bootstrap_(statistiques)] utilisant le ré-échantillonnage avec remise pour estimer un intervalle de confiance pour la moyenne d’un échantillon de taille cinq :

# http://statistics.about.com/od/Applications/a/Example-Of-Bootstrapping.htm
from statistics import mean
from random import choices

data = 1, 2, 4, 4, 10
means = sorted(mean(choices(data, k=5)) for i in range(20))
print(f'The sample mean of {mean(data):.1f} has a 90% confidence '
      f'interval from {means[1]:.1f} to {means[-2]:.1f}')

Exemple d’un *resampling permutation test* [https://en.wikipedia.org/wiki/Resampling_(statistics)#Permutation_tests] pour déterminer la signification statistique ou valeur p [https://fr.wikipedia.org/wiki/Valeur_p] d’une différence observée entre les effets d’un médicament et ceux d’un placebo :

# Example from "Statistics is Easy" by Dennis Shasha and Manda Wilson
from statistics import mean
from random import shuffle

drug = [54, 73, 53, 70, 73, 68, 52, 65, 65]
placebo = [54, 51, 58, 44, 55, 52, 42, 47, 58, 46]
observed_diff = mean(drug) - mean(placebo)

n = 10000
count = 0
combined = drug + placebo
for i in range(n):
    shuffle(combined)
    new_diff = mean(combined[:len(drug)]) - mean(combined[len(drug):])
    count += (new_diff >= observed_diff)

print(f'{n} label reshufflings produced only {count} instances with a difference')
print(f'at least as extreme as the observed difference of {observed_diff:.1f}.')
print(f'The one-sided p-value of {count / n:.4f} leads us to reject the null')
print(f'hypothesis that there is no difference between the drug and the placebo.')

Simulation des heures d’arrivée et des livraisons de services dans une seule file d’attente de serveurs :

from random import expovariate, gauss
from statistics import mean, median, stdev

average_arrival_interval = 5.6
average_service_time = 5.0
stdev_service_time = 0.5

num_waiting = 0
arrivals = []
starts = []
arrival = service_end = 0.0
for i in range(20000):
    if arrival <= service_end:
        num_waiting += 1
        arrival += expovariate(1.0 / average_arrival_interval)
        arrivals.append(arrival)
    else:
        num_waiting -= 1
        service_start = service_end if num_waiting else arrival
        service_time = gauss(average_service_time, stdev_service_time)
        service_end = service_start + service_time
        starts.append(service_start)

waits = [start - arrival for arrival, start in zip(arrivals, starts)]
print(f'Mean wait: {mean(waits):.1f}.  Stdev wait: {stdev(waits):.1f}.')
print(f'Median wait: {median(waits):.1f}.  Max wait: {max(waits):.1f}.')

Voir aussi

Statistics for Hackers [https://www.youtube.com/watch?v=Iq9DzN6mvYA] un tutoriel vidéo par Jake Vanderplas [https://us.pycon.org/2016/speaker/profile/295/] sur l’analyse statistique en utilisant seulement quelques concepts fondamentaux dont la simulation, l’échantillonnage, le brassage et la validation croisée.

Economics Simulation [http://nbviewer.jupyter.org/url/norvig.com/ipython/Economics.ipynb] simulation d’un marché par Peter Norvig [http://norvig.com/bio.html] qui montre l’utilisation efficace de plusieurs des outils et distributions fournis par ce module (gauss, uniform, sample, betavariate, choice, triangular, et randrange).

A Concrete Introduction to Probability (using Python) [http://nbviewer.jupyter.org/url/norvig.com/ipython/Probability.ipynb] un tutoriel par Peter Norvig [http://norvig.com/bio.html] couvrant les bases de la théorie des probabilités, comment écrire des simulations, et comment effectuer des analyses de données avec Python.

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9.7. statistics — Mathematical statistics functions

Nouveau dans la version 3.4.

Code source : Lib/statistics.py [https://github.com/python/cpython/tree/3.6/Lib/statistics.py]

This module provides functions for calculating mathematical statistics of numeric (Real-valued) data.

Note

Unless explicitly noted otherwise, these functions support int, float, decimal.Decimal and fractions.Fraction. Behaviour with other types (whether in the numeric tower or not) is currently unsupported. Mixed types are also undefined and implementation-dependent. If your input data consists of mixed types, you may be able to use map() to ensure a consistent result, e.g. map(float, input_data).

9.7.1. Averages and measures of central location

These functions calculate an average or typical value from a population or sample.

mean()

Arithmetic mean (« average ») of data.

harmonic_mean()

Harmonic mean of data.

median()

Median (middle value) of data.

median_low()

Low median of data.

median_high()

High median of data.

median_grouped()

Median, or 50th percentile, of grouped data.

mode()

Mode (most common value) of discrete data.

9.7.2. Measures of spread

These functions calculate a measure of how much the population or sample tends to deviate from the typical or average values.

pstdev()

Population standard deviation of data.

pvariance()

Population variance of data.

stdev()

Sample standard deviation of data.

variance()

Sample variance of data.

9.7.3. Function details

Note: The functions do not require the data given to them to be sorted. However, for reading convenience, most of the examples show sorted sequences.

statistics.mean(data)

Return the sample arithmetic mean of data which can be a sequence or iterator.

The arithmetic mean is the sum of the data divided by the number of data points. It is commonly called « the average », although it is only one of many different mathematical averages. It is a measure of the central location of the data.

If data is empty, StatisticsError will be raised.

Some examples of use:

>>> mean([1, 2, 3, 4, 4])
2.8
>>> mean([-1.0, 2.5, 3.25, 5.75])
2.625

>>> from fractions import Fraction as F
>>> mean([F(3, 7), F(1, 21), F(5, 3), F(1, 3)])
Fraction(13, 21)

>>> from decimal import Decimal as D
>>> mean([D("0.5"), D("0.75"), D("0.625"), D("0.375")])
Decimal('0.5625')

Note

The mean is strongly affected by outliers and is not a robust estimator for central location: the mean is not necessarily a typical example of the data points. For more robust, although less efficient, measures of central location, see median() and mode(). (In this case, « efficient » refers to statistical efficiency rather than computational efficiency.)

The sample mean gives an unbiased estimate of the true population mean, which means that, taken on average over all the possible samples, mean(sample) converges on the true mean of the entire population. If data represents the entire population rather than a sample, then mean(data) is equivalent to calculating the true population mean μ.

statistics.harmonic_mean(data)

Return the harmonic mean of data, a sequence or iterator of real-valued numbers.

The harmonic mean, sometimes called the subcontrary mean, is the reciprocal of the arithmetic mean() of the reciprocals of the data. For example, the harmonic mean of three values a, b and c will be equivalent to 3/(1/a + 1/b + 1/c).

The harmonic mean is a type of average, a measure of the central location of the data. It is often appropriate when averaging quantities which are rates or ratios, for example speeds. For example:

Suppose an investor purchases an equal value of shares in each of three companies, with P/E (price/earning) ratios of 2.5, 3 and 10. What is the average P/E ratio for the investor’s portfolio?

>>> harmonic_mean([2.5, 3, 10])  # For an equal investment portfolio.
3.6

Using the arithmetic mean would give an average of about 5.167, which is too high.

StatisticsError is raised if data is empty, or any element is less than zero.

Nouveau dans la version 3.6.

statistics.median(data)

Return the median (middle value) of numeric data, using the common « mean of middle two » method. If data is empty, StatisticsError is raised. data can be a sequence or iterator.

The median is a robust measure of central location, and is less affected by the presence of outliers in your data. When the number of data points is odd, the middle data point is returned:

>>> median([1, 3, 5])
3

When the number of data points is even, the median is interpolated by taking the average of the two middle values:

>>> median([1, 3, 5, 7])
4.0

This is suited for when your data is discrete, and you don’t mind that the median may not be an actual data point.

If your data is ordinal (supports order operations) but not numeric (doesn’t support addition), you should use median_low() or median_high() instead.

Voir aussi

median_low(), median_high(), median_grouped()

statistics.median_low(data)

Return the low median of numeric data. If data is empty, StatisticsError is raised. data can be a sequence or iterator.

The low median is always a member of the data set. When the number of data points is odd, the middle value is returned. When it is even, the smaller of the two middle values is returned.

>>> median_low([1, 3, 5])
3
>>> median_low([1, 3, 5, 7])
3

Use the low median when your data are discrete and you prefer the median to be an actual data point rather than interpolated.

statistics.median_high(data)

Return the high median of data. If data is empty, StatisticsError is raised. data can be a sequence or iterator.

The high median is always a member of the data set. When the number of data points is odd, the middle value is returned. When it is even, the larger of the two middle values is returned.

>>> median_high([1, 3, 5])
3
>>> median_high([1, 3, 5, 7])
5

Use the high median when your data are discrete and you prefer the median to be an actual data point rather than interpolated.

statistics.median_grouped(data, interval=1)

Return the median of grouped continuous data, calculated as the 50th percentile, using interpolation. If data is empty, StatisticsError is raised. data can be a sequence or iterator.

>>> median_grouped([52, 52, 53, 54])
52.5

In the following example, the data are rounded, so that each value represents the midpoint of data classes, e.g. 1 is the midpoint of the class 0.5–1.5, 2 is the midpoint of 1.5–2.5, 3 is the midpoint of 2.5–3.5, etc. With the data given, the middle value falls somewhere in the class 3.5–4.5, and interpolation is used to estimate it:

>>> median_grouped([1, 2, 2, 3, 4, 4, 4, 4, 4, 5])
3.7

Optional argument interval represents the class interval, and defaults to 1. Changing the class interval naturally will change the interpolation:

>>> median_grouped([1, 3, 3, 5, 7], interval=1)
3.25
>>> median_grouped([1, 3, 3, 5, 7], interval=2)
3.5

This function does not check whether the data points are at least interval apart.

CPython implementation detail: Under some circumstances, median_grouped() may coerce data points to floats. This behaviour is likely to change in the future.

Voir aussi

« Statistics for the Behavioral Sciences », Frederick J Gravetter and Larry B Wallnau (8th Edition).

Calculating the median [https://www.ualberta.ca/~opscan/median.html].

The SSMEDIAN [https://help.gnome.org/users/gnumeric/stable/gnumeric.html#gnumeric-function-SSMEDIAN] function in the Gnome Gnumeric spreadsheet, including this discussion [https://mail.gnome.org/archives/gnumeric-list/2011-April/msg00018.html].

statistics.mode(data)

Return the most common data point from discrete or nominal data. The mode (when it exists) is the most typical value, and is a robust measure of central location.

If data is empty, or if there is not exactly one most common value, StatisticsError is raised.

mode assumes discrete data, and returns a single value. This is the standard treatment of the mode as commonly taught in schools:

>>> mode([1, 1, 2, 3, 3, 3, 3, 4])
3

The mode is unique in that it is the only statistic which also applies to nominal (non-numeric) data:

>>> mode(["red", "blue", "blue", "red", "green", "red", "red"])
'red'

statistics.pstdev(data, mu=None)

Return the population standard deviation (the square root of the population variance). See pvariance() for arguments and other details.

>>> pstdev([1.5, 2.5, 2.5, 2.75, 3.25, 4.75])
0.986893273527251

statistics.pvariance(data, mu=None)

Return the population variance of data, a non-empty iterable of real-valued numbers. Variance, or second moment about the mean, is a measure of the variability (spread or dispersion) of data. A large variance indicates that the data is spread out; a small variance indicates it is clustered closely around the mean.

If the optional second argument mu is given, it should be the mean of data. If it is missing or None (the default), the mean is automatically calculated.

Use this function to calculate the variance from the entire population. To estimate the variance from a sample, the variance() function is usually a better choice.

Raises StatisticsError if data is empty.

Exemples :

>>> data = [0.0, 0.25, 0.25, 1.25, 1.5, 1.75, 2.75, 3.25]
>>> pvariance(data)
1.25

If you have already calculated the mean of your data, you can pass it as the optional second argument mu to avoid recalculation:

>>> mu = mean(data)
>>> pvariance(data, mu)
1.25

This function does not attempt to verify that you have passed the actual mean as mu. Using arbitrary values for mu may lead to invalid or impossible results.

Decimals and Fractions are supported:

>>> from decimal import Decimal as D
>>> pvariance([D("27.5"), D("30.25"), D("30.25"), D("34.5"), D("41.75")])
Decimal('24.815')

>>> from fractions import Fraction as F
>>> pvariance([F(1, 4), F(5, 4), F(1, 2)])
Fraction(13, 72)

Note

When called with the entire population, this gives the population variance σ². When called on a sample instead, this is the biased sample variance s², also known as variance with N degrees of freedom.

If you somehow know the true population mean μ, you may use this function to calculate the variance of a sample, giving the known population mean as the second argument. Provided the data points are representative (e.g. independent and identically distributed), the result will be an unbiased estimate of the population variance.

statistics.stdev(data, xbar=None)

Return the sample standard deviation (the square root of the sample variance). See variance() for arguments and other details.

>>> stdev([1.5, 2.5, 2.5, 2.75, 3.25, 4.75])
1.0810874155219827

statistics.variance(data, xbar=None)

Return the sample variance of data, an iterable of at least two real-valued numbers. Variance, or second moment about the mean, is a measure of the variability (spread or dispersion) of data. A large variance indicates that the data is spread out; a small variance indicates it is clustered closely around the mean.

If the optional second argument xbar is given, it should be the mean of data. If it is missing or None (the default), the mean is automatically calculated.

Use this function when your data is a sample from a population. To calculate the variance from the entire population, see pvariance().

Raises StatisticsError if data has fewer than two values.

Exemples :

>>> data = [2.75, 1.75, 1.25, 0.25, 0.5, 1.25, 3.5]
>>> variance(data)
1.3720238095238095

If you have already calculated the mean of your data, you can pass it as the optional second argument xbar to avoid recalculation:

>>> m = mean(data)
>>> variance(data, m)
1.3720238095238095

This function does not attempt to verify that you have passed the actual mean as xbar. Using arbitrary values for xbar can lead to invalid or impossible results.

Decimal and Fraction values are supported:

>>> from decimal import Decimal as D
>>> variance([D("27.5"), D("30.25"), D("30.25"), D("34.5"), D("41.75")])
Decimal('31.01875')

>>> from fractions import Fraction as F
>>> variance([F(1, 6), F(1, 2), F(5, 3)])
Fraction(67, 108)

Note

This is the sample variance s² with Bessel’s correction, also known as variance with N-1 degrees of freedom. Provided that the data points are representative (e.g. independent and identically distributed), the result should be an unbiased estimate of the true population variance.

If you somehow know the actual population mean μ you should pass it to the pvariance() function as the mu parameter to get the variance of a sample.

9.7.4. Exceptions

A single exception is defined:

exception statistics.StatisticsError

Subclass of ValueError for statistics-related exceptions.

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10. Modules de programmation fonctionnelle

Les modules décrits dans ce chapitre fournissent des fonctions et des classes permettant d’adopter un style fonctionnel, ainsi que des manipulations sur des appelables.

Les modules suivants sont documentés dans ce chapitre :

10.1. itertools — Fonctions créant des itérateurs pour boucler efficacement

10.1.1. Fonctions d”itertool

10.1.2. Recettes itertools

10.2. functools — Fonctions de haut niveau et opérations sur des objets appelables

10.2.1. Objets partial

10.3. operator — Opérateurs standards en tant que fonctions

10.3.1. Correspondances entre opérateurs et fonctions

10.3.2. Inplace Operators

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10.1. itertools — Fonctions créant des itérateurs pour boucler efficacement

Ce module implémente de nombreuses briques d’itérateurs inspirées par des éléments de APL, Haskell et SML. Toutes ont été retravaillées dans un format adapté à Python.

Ce module standardise un ensemble de base d’outils rapides et efficaces en mémoire qui peuvent être utilisés individuellement ou en les combinant. Ensemble, ils forment une « algèbre d’itérateurs » rendant possible la construction rapide et efficace d’outils spécialisés en Python.

Par exemple, SML fournit un outil de tabulation tabulate(f) qui produit une séquence f(0), f(1), .... Le même résultat peut être obtenu en Python en combinant map() et count() pour former map(f, count()).

Ces outils et leurs équivalents natifs fonctionnent également bien avec les fonctions optimisées du module operator. Par exemple, l’opérateur de multiplication peut être appliqué à deux vecteurs pour créer un produit scalaire efficace : sum(map(operator.mul, vecteur1, vecteur2)).

Itérateurs infinis :

Itérateur

Arguments

Résultats

Exemple

count()

start, [step]

start, start+step, start+2*step, …

count(10) --> 10 11 12 13 14 ...

cycle()

p

p0, p1, … plast, p0, p1, …

cycle('ABCD') --> A B C D A B C D ...

repeat()

elem [,n]

elem, elem, elem, … à l’infini ou jusqu’à n fois

repeat(10, 3) --> 10 10 10

Itérateurs se terminant par la séquence d’entrée la plus courte :

Itérateur

Arguments

Résultats

Exemple

accumulate()

p [,func]

p0, p0+p1, p0+p1+p2, …

accumulate([1,2,3,4,5]) --> 1 3 6 10 15

chain()

p, q, …

p0, p1, … plast, q0, q1, …

chain('ABC', 'DEF') --> A B C D E F

chain.from_iterable()

itérable

p0, p1, … plast, q0, q1, …

chain.from_iterable(['ABC', 'DEF']) --> A B C D E F

compress()

data, selectors

(d[0] if s[0]), (d[1] if s[1]), …

compress('ABCDEF', [1,0,1,0,1,1]) --> A C E F

dropwhile()

pred, seq

seq[n], seq[n+1], commençant quand pred échoue

dropwhile(lambda x: x<5, [1,4,6,4,1]) --> 6 4 1

filterfalse()

pred, seq

éléments de seq pour lesquels pred(elem) est faux

filterfalse(lambda x: x%2, range(10)) --> 0 2 4 6 8

groupby()

iterable[, key]

sous-itérateurs groupés par la valeur de key(v)

islice()

seq, [start,] stop [, step]

éléments de seq[start:stop:step]

islice('ABCDEFG', 2, None) --> C D E F G

starmap()

func, seq

func(*seq[0]), func(*seq[1]), …

starmap(pow, [(2,5), (3,2), (10,3)]) --> 32 9 1000

takewhile()

pred, seq

seq[0], seq[1], jusqu’à ce que pred échoue

takewhile(lambda x: x<5, [1,4,6,4,1]) --> 1 4

tee()

it, n

it1, it2, … itn sépare un itérateur en n

zip_longest()

p, q, …

(p[0], q[0]), (p[1], q[1]), …

zip_longest('ABCD', 'xy', fillvalue='-') --> Ax By C- D-

Itérateurs combinatoires :

Itérateur

Arguments

Résultats

product()

p, q, … [repeat=1]

produit cartésien, équivalent à une boucle for imbriquée

permutations()

p[, r]

n-uplets de longueur r, tous les ré-arrangements possibles, sans répétition d’éléments

combinations()

p, r

n-uplets de longueur r, ordonnés, sans répétition d’éléments

combinations_with_replacement()

p, r

n-uplets de longueur r, ordonnés, avec répétition d’éléments

product('ABCD', repeat=2)

AA AB AC AD BA BB BC BD CA CB CC CD DA DB DC DD

permutations('ABCD', 2)

AB AC AD BA BC BD CA CB CD DA DB DC

combinations('ABCD', 2)

AB AC AD BC BD CD

combinations_with_replacement('ABCD', 2)

AA AB AC AD BB BC BD CC CD DD

10.1.1. Fonctions d”itertool

Toutes les fonctions du module qui suivent construisent et renvoient des itérateurs. Certaines produisent des flux de longueur infinie ; celles-ci ne doivent donc être contrôlées que par des fonctions ou boucles qui interrompent le flux.

itertools.accumulate(iterable[, func])

Créer un itérateur qui renvoie les sommes accumulées, ou les résultats accumulés d’autres fonctions binaires (spécifiées par l’argument optionnel func). Si func est renseigné, il doit être une fonction à deux arguments. Les éléments de l’itérable d’entrée peuvent être de n’importe quel type qui peuvent être acceptés comme arguments de func. (Par exemple, avec l’opération par défaut d’addition, les éléments peuvent être de n’importe quel type additionnable incluant Decimal ou Fraction.) Si l’itérable d’entrée est vide, l’itérable de sortie sera aussi vide.

À peu près équivalent à :

def accumulate(iterable, func=operator.add):
    'Return running totals'
    # accumulate([1,2,3,4,5]) --> 1 3 6 10 15
    # accumulate([1,2,3,4,5], operator.mul) --> 1 2 6 24 120
    it = iter(iterable)
    try:
        total = next(it)
    except StopIteration:
        return
    yield total
    for element in it:
        total = func(total, element)
        yield total

Il y a de nombreuses utilisations à l’argument func. Celui-ci peut être min() pour calculer un minimum glissant, max() pour un maximum glissant ou operator.mul() pour un produit glissant. Des tableaux de remboursements peuvent être construits en ajoutant les intérêts et en soustrayant les paiements. Des suites par récurrence [https://fr.wikipedia.org/wiki/Suite_d%C3%A9finie_par_r%C3%A9currence] de premier ordre peuvent être modélisées en en passant la valeur initiale dans iterable et en n’utilisant que le premier argument de func, qui contient le résultat des évaluations précédentes :

>>> data = [3, 4, 6, 2, 1, 9, 0, 7, 5, 8]
>>> list(accumulate(data, operator.mul))     # running product
[3, 12, 72, 144, 144, 1296, 0, 0, 0, 0]
>>> list(accumulate(data, max))              # running maximum
[3, 4, 6, 6, 6, 9, 9, 9, 9, 9]

# Amortize a 5% loan of 1000 with 4 annual payments of 90
>>> cashflows = [1000, -90, -90, -90, -90]
>>> list(accumulate(cashflows, lambda bal, pmt: bal*1.05 + pmt))
[1000, 960.0, 918.0, 873.9000000000001, 827.5950000000001]

# Chaotic recurrence relation https://en.wikipedia.org/wiki/Logistic_map
>>> logistic_map = lambda x, _:  r * x * (1 - x)
>>> r = 3.8
>>> x0 = 0.4
>>> inputs = repeat(x0, 36)     # only the initial value is used
>>> [format(x, '.2f') for x in accumulate(inputs, logistic_map)]
['0.40', '0.91', '0.30', '0.81', '0.60', '0.92', '0.29', '0.79', '0.63',
 '0.88', '0.39', '0.90', '0.33', '0.84', '0.52', '0.95', '0.18', '0.57',
 '0.93', '0.25', '0.71', '0.79', '0.63', '0.88', '0.39', '0.91', '0.32',
 '0.83', '0.54', '0.95', '0.20', '0.60', '0.91', '0.30', '0.80', '0.60']

Voir functools.reduce() pour une fonction similaire qui ne renvoie que la valeur accumulée finale.

Nouveau dans la version 3.2.

Modifié dans la version 3.3: Ajout du paramètre optionnel func.

itertools.chain(*iterables)

Crée un itérateur qui renvoie les éléments du premier itérable jusqu’à son épuisement, puis continue avec l’itérable suivant jusqu’à ce que tous les itérables soient épuisés. Utilisée pour traiter des séquences consécutives comme une seule séquence. À peu près équivalent à :

def chain(*iterables):
    # chain('ABC', 'DEF') --> A B C D E F
    for it in iterables:
        for element in it:
            yield element

classmethod chain.from_iterable(iterable)

Constructeur alternatif pour chain(). Récupère des entrées chaînées depuis un unique itérable passé en argument, qui est évalué de manière paresseuse. À peu près équivalent à :

def from_iterable(iterables):
    # chain.from_iterable(['ABC', 'DEF']) --> A B C D E F
    for it in iterables:
        for element in it:
            yield element

itertools.combinations(iterable, r)

Renvoie les combinaisons de longueur r de iterable.

Les combinaisons sont produites dans l’ordre lexicographique. Ainsi, si l’itérable iterable est ordonné, les n-uplets de combinaison produits le sont aussi.

Les éléments sont considérés comme uniques en fonction de leur position, et non pas de leur valeur. Ainsi, si les éléments en entrée sont uniques, il n’y aura pas de valeurs répétées dans chaque combinaison.

À peu près équivalent à :

def combinations(iterable, r):
    # combinations('ABCD', 2) --> AB AC AD BC BD CD
    # combinations(range(4), 3) --> 012 013 023 123
    pool = tuple(iterable)
    n = len(pool)
    if r > n:
        return
    indices = list(range(r))
    yield tuple(pool[i] for i in indices)
    while True:
        for i in reversed(range(r)):
            if indices[i] != i + n - r:
                break
        else:
            return
        indices[i] += 1
        for j in range(i+1, r):
            indices[j] = indices[j-1] + 1
        yield tuple(pool[i] for i in indices)

Un appel à combinations() peut aussi être vu comme à un appel à permutations() en excluant les sorties dans lesquelles les éléments ne sont pas ordonnés (avec la même relation d’ordre que pour l’entrée) :

def combinations(iterable, r):
    pool = tuple(iterable)
    n = len(pool)
    for indices in permutations(range(n), r):
        if sorted(indices) == list(indices):
            yield tuple(pool[i] for i in indices)

Le nombre d’éléments renvoyés est n! / r! / (n-r)! quand 0 <= r <= n ou zéro quand r > n.

itertools.combinations_with_replacement(iterable, r)

Renvoyer les sous-séquences de longueur r des éléments de l’itérable iterable d’entrée, permettant aux éléments individuels d’être répétés plus d’une fois.

Les combinaisons sont produites dans l’ordre lexicographique. Ainsi, si l’itérable iterable est ordonné, les n-uplets de combinaison produits le sont aussi.

Les éléments sont considérés comme uniques en fonction de leur position, et non pas de leur valeur. Ainsi si les éléments d’entrée sont uniques, les combinaisons générées seront aussi uniques.

À peu près équivalent à :

def combinations_with_replacement(iterable, r):
    # combinations_with_replacement('ABC', 2) --> AA AB AC BB BC CC
    pool = tuple(iterable)
    n = len(pool)
    if not n and r:
        return
    indices = [0] * r
    yield tuple(pool[i] for i in indices)
    while True:
        for i in reversed(range(r)):
            if indices[i] != n - 1:
                break
        else:
            return
        indices[i:] = [indices[i] + 1] * (r - i)
        yield tuple(pool[i] for i in indices)

Un appel à combinations_with_replacement() peut aussi être vu comme un appel à product() en excluant les sorties dans lesquelles les éléments ne sont pas dans ordonnés (avec la même relation d’ordre que pour l’entrée) :

def combinations_with_replacement(iterable, r):
    pool = tuple(iterable)
    n = len(pool)
    for indices in product(range(n), repeat=r):
        if sorted(indices) == list(indices):
            yield tuple(pool[i] for i in indices)

Le nombre d’éléments renvoyés est (n+r-1)! / r! / (n-1)! quand n > 0.

Nouveau dans la version 3.1.

itertools.compress(data, selectors)

Crée un itérateur qui filtre les éléments de data, en ne renvoyant que ceux dont l’élément correspondant dans selectors s’évalue à True. S’arrête quand l’itérable data ou selectors a été épuisé. À peu près équivalent à :

def compress(data, selectors):
    # compress('ABCDEF', [1,0,1,0,1,1]) --> A C E F
    return (d for d, s in zip(data, selectors) if s)

Nouveau dans la version 3.1.

itertools.count(start=0, step=1)

Crée un itérateur qui renvoie des valeurs espacées régulièrement, en commençant par le nombre start. Souvent utilisé comme un argument de map() pour générer des points de données consécutifs. Aussi utilisé avec zip() pour ajouter des nombres de séquence. À peu près équivalent à :

def count(start=0, step=1):
    # count(10) --> 10 11 12 13 14 ...
    # count(2.5, 0.5) -> 2.5 3.0 3.5 ...
    n = start
    while True:
        yield n
        n += step

Pour compter avec des nombres à virgule flottante, il est parfois préférable d’utiliser le code : (start + step * i for i in count()) pour obtenir une meilleure précision.

Modifié dans la version 3.1: Ajout de l’argument step et ajout du support pour les arguments non-entiers.

itertools.cycle(iterable)

Crée un itérateur qui renvoie les éléments de l’itérable en en sauvegardant une copie. Quand l’itérable est épuisé, renvoie les éléments depuis la sauvegarde. Répète à l’infini. À peu près équivalent à :

def cycle(iterable):
    # cycle('ABCD') --> A B C D A B C D A B C D ...
    saved = []
    for element in iterable:
        yield element
        saved.append(element)
    while saved:
        for element in saved:
              yield element

Note, cette fonction peut avoir besoin d’un stockage auxiliaire important (en fonction de la longueur de l’itérable).

itertools.dropwhile(predicate, iterable)

Crée un itérateur qui saute les éléments de l’itérable tant que le prédicat est vrai ; renvoie ensuite chaque élément. Notez que l’itérateur ne produit aucune sortie avant que le prédicat ne devienne faux, il peut donc avoir un temps de démarrage long. À peu près équivalent à :

def dropwhile(predicate, iterable):
    # dropwhile(lambda x: x<5, [1,4,6,4,1]) --> 6 4 1
    iterable = iter(iterable)
    for x in iterable:
        if not predicate(x):
            yield x
            break
    for x in iterable:
        yield x

itertools.filterfalse(predicate, iterable)

Crée un itérateur qui filtre les éléments de iterable, ne renvoyant seulement ceux pour lesquels le prédicat est False. Si predicate vaut None, renvoie les éléments qui sont faux. À peu près équivalent à :

def filterfalse(predicate, iterable):
    # filterfalse(lambda x: x%2, range(10)) --> 0 2 4 6 8
    if predicate is None:
        predicate = bool
    for x in iterable:
        if not predicate(x):
            yield x

itertools.groupby(iterable, key=None)

Crée un itérateur qui renvoie les clés et les groupes de l’itérable iterable. La clé key est une fonction qui génère une clé pour chaque élément. Si key n’est pas spécifiée ou est None, elle vaut par défaut une fonction d’identité qui renvoie l’élément sans le modifier. Généralement, l’itérable a besoin d’avoir ses éléments déjà classés selon cette même fonction de clé.

L’opération de groupby() est similaire au filtre uniq dans Unix. Elle génère un nouveau groupe à chaque fois que la valeur de la fonction key change (ce pourquoi il est souvent nécessaire d’avoir trié les données selon la même fonction de clé). Ce comportement est différent de celui de GROUP BY de SQL qui agrège les éléments sans prendre compte de leur ordre d’entrée.

Le groupe renvoyé est lui-même un itérateur qui partage l’itérable sous-jacent avec groupby(). Puisque que la source est partagée, quand l’objet groupby() est avancé, le groupe précédent n’est plus visible. Ainsi, si cette donnée doit être utilisée plus tard, elle doit être stockée comme une liste :

groups = []
uniquekeys = []
data = sorted(data, key=keyfunc)
for k, g in groupby(data, keyfunc):
    groups.append(list(g))      # Store group iterator as a list
    uniquekeys.append(k)

groupby() est à peu près équivalente à :

class groupby:
    # [k for k, g in groupby('AAAABBBCCDAABBB')] --> A B C D A B
    # [list(g) for k, g in groupby('AAAABBBCCD')] --> AAAA BBB CC D
    def __init__(self, iterable, key=None):
        if key is None:
            key = lambda x: x
        self.keyfunc = key
        self.it = iter(iterable)
        self.tgtkey = self.currkey = self.currvalue = object()
    def __iter__(self):
        return self
    def __next__(self):
        while self.currkey == self.tgtkey:
            self.currvalue = next(self.it)    # Exit on StopIteration
            self.currkey = self.keyfunc(self.currvalue)
        self.tgtkey = self.currkey
        return (self.currkey, self._grouper(self.tgtkey))
    def _grouper(self, tgtkey):
        while self.currkey == tgtkey:
            yield self.currvalue
            try:
                self.currvalue = next(self.it)
            except StopIteration:
                return
            self.currkey = self.keyfunc(self.currvalue)

itertools.islice(iterable, stop)

itertools.islice(iterable, start, stop[, step])

Crée un itérateur qui renvoie les élément sélectionnés de l’itérable. Si start est différent de zéro, alors les éléments de l’itérable sont ignorés jusqu’à ce que start soit atteint. Ensuite, les éléments sont renvoyés consécutivement sauf si step est plus grand que 1, auquel cas certains éléments seront ignorés. Si stop est None, alors l’itération continue jusqu’à ce que l’itérateur soit épuisé s’il ne l’est pas déjà ; sinon, il s’arrête à la position spécifiée. À la différence des tranches standards, slice() ne gère pas les valeurs négatives pour start, stop ou step. Peut être utilisée pour extraire les champs consécutifs depuis des données dont la structure interne a été aplatie (par exemple, un rapport multi-lignes pourrait lister un nom de champ toutes les trois lignes). À peu près similaire à :

def islice(iterable, *args):
    # islice('ABCDEFG', 2) --> A B
    # islice('ABCDEFG', 2, 4) --> C D
    # islice('ABCDEFG', 2, None) --> C D E F G
    # islice('ABCDEFG', 0, None, 2) --> A C E G
    s = slice(*args)
    start, stop, step = s.start or 0, s.stop or sys.maxsize, s.step or 1
    it = iter(range(start, stop, step))
    try:
        nexti = next(it)
    except StopIteration:
        # Consume *iterable* up to the *start* position.
        for i, element in zip(range(start), iterable):
            pass
        return
    try:
        for i, element in enumerate(iterable):
            if i == nexti:
                yield element
                nexti = next(it)
    except StopIteration:
        # Consume to *stop*.
        for i, element in zip(range(i + 1, stop), iterable):
            pass

Si start vaut None, alors l’itération commence à zéro. Si step vaut None, alors le pas est à 1 par défaut.

itertools.permutations(iterable, r=None)

Renvoie les arrangements successifs de longueur r des éléments de iterable.

Si r n’est pas spécifié ou vaut None, alors r a pour valeur la longueur de iterable et toutes les permutations de longueur r possibles sont générées.

Les permutations sont émises dans l’ordre lexicographique. Ainsi, si l’itérable d’entrée iterable est classé, les n-uplets de permutation sont produits dans ce même ordre.

Les éléments sont considérés comme uniques en fonction de leur position, et non pas de leur valeur. Ainsi, si l’élément est unique, il n’y aura pas de valeurs répétées dans chaque permutation.

À peu près équivalent à :

def permutations(iterable, r=None):
    # permutations('ABCD', 2) --> AB AC AD BA BC BD CA CB CD DA DB DC
    # permutations(range(3)) --> 012 021 102 120 201 210
    pool = tuple(iterable)
    n = len(pool)
    r = n if r is None else r
    if r > n:
        return
    indices = list(range(n))
    cycles = list(range(n, n-r, -1))
    yield tuple(pool[i] for i in indices[:r])
    while n:
        for i in reversed(range(r)):
            cycles[i] -= 1
            if cycles[i] == 0:
                indices[i:] = indices[i+1:] + indices[i:i+1]
                cycles[i] = n - i
            else:
                j = cycles[i]
                indices[i], indices[-j] = indices[-j], indices[i]
                yield tuple(pool[i] for i in indices[:r])
                break
        else:
            return

Un appel à permutations() peut aussi être vu un appel à product() en excluant les sorties avec des doublons (avec la même relation d’ordre que pour l’entrée) :

def permutations(iterable, r=None):
    pool = tuple(iterable)
    n = len(pool)
    r = n if r is None else r
    for indices in product(range(n), repeat=r):
        if len(set(indices)) == r:
            yield tuple(pool[i] for i in indices)

Le nombre d’éléments renvoyés est n! / (n-r)! quand 0 <= r <= n ou zéro quand r > n.

itertools.product(*iterables, repeat=1)

Produit cartésien des itérables d’entrée.

À peu près équivalent à des boucles for imbriquées dans une expression de générateur. Par exemple product(A, B) renvoie la même chose que ((x, y) for x in A for y in B).

Les boucles imbriquées tournent comme un compteur kilométrique avec l’élément le plus à droite avançant à chaque itération. Ce motif défini un ordre lexicographique afin que, si les éléments des itérables en l’entrée sont ordonnés, les n-uplets produits le sont aussi.

Pour générer le produit d’un itérable avec lui-même, spécifiez le nombre de répétitions avec le paramètre nommé optionnel repeat. Par exemple, product(A, repeat=4) est équivalent à product(A, A, A, A).

Cette fonction est à peu près équivalente au code suivant, à la différence près que la vraie implémentation ne crée pas de résultats intermédiaires en mémoire :

def product(*args, repeat=1):
    # product('ABCD', 'xy') --> Ax Ay Bx By Cx Cy Dx Dy
    # product(range(2), repeat=3) --> 000 001 010 011 100 101 110 111
    pools = [tuple(pool) for pool in args] * repeat
    result = [[]]
    for pool in pools:
        result = [x+[y] for x in result for y in pool]
    for prod in result:
        yield tuple(prod)

itertools.repeat(object[, times])

Crée un itérateur qui renvoie object à l’infini. S’exécute indéfiniment sauf si l’argument times est spécifié. Utilisée comme argument de map() pour les paramètres invariants de la fonction appelée. Aussi utilisée avec zip() pour créer une partie invariante d’un n-uplet.

À peu près équivalent à :

def repeat(object, times=None):
    # repeat(10, 3) --> 10 10 10
    if times is None:
        while True:
            yield object
    else:
        for i in range(times):
            yield object

Une utilisation courante de repeat est de fournir un flux constant de valeurs à map ou zip :

>>> list(map(pow, range(10), repeat(2)))
[0, 1, 4, 9, 16, 25, 36, 49, 64, 81]

itertools.starmap(function, iterable)

Crée un itérateur qui exécute la fonction avec les arguments obtenus depuis l’itérable. Utilisée à la place de map() quand les arguments sont déjà groupés en n-uplets depuis un seul itérable — la donnée a déjà été « pré-zippée ». La différence entre map() et starmap() est similaire à la différence entre fonction(a,b) et fonction(*c). À peu près équivalent à :

def starmap(function, iterable):
    # starmap(pow, [(2,5), (3,2), (10,3)]) --> 32 9 1000
    for args in iterable:
        yield function(*args)

itertools.takewhile(predicate, iterable)

Crée un itérateur qui renvoie les éléments d’un itérable tant que le prédicat est vrai. À peu près équivalent à :

def takewhile(predicate, iterable):
    # takewhile(lambda x: x<5, [1,4,6,4,1]) --> 1 4
    for x in iterable:
        if predicate(x):
            yield x
        else:
            break

itertools.tee(iterable, n=2)

Renvoie n itérateurs indépendants depuis un unique itérable.

Le code Python qui suit aide à expliquer ce que fait tee, bien que la vraie implémentation soit plus complexe et n’utilise qu’une file FIFO.

À peu près équivalent à :

def tee(iterable, n=2):
    it = iter(iterable)
    deques = [collections.deque() for i in range(n)]
    def gen(mydeque):
        while True:
            if not mydeque:             # when the local deque is empty
                try:
                    newval = next(it)   # fetch a new value and
                except StopIteration:
                    return
                for d in deques:        # load it to all the deques
                    d.append(newval)
            yield mydeque.popleft()
    return tuple(gen(d) for d in deques)

Une fois que tee() a créé un branchement, l’itérable iterable ne doit être utilisé nulle part ailleurs ; sinon, iterable pourrait être avancé sans que les objets tee ne soient informés.

Cet outil peut avoir besoin d’un stockage auxiliaire important (en fonction de la taille des données temporaires nécessaires). En général, si un itérateur utilise la majorité ou toute la donnée avant qu’un autre itérateur ne commence, il est plus rapide d’utiliser list() à la place de tee().

itertools.zip_longest(*iterables, fillvalue=None)

Crée un itérateur qui agrège les éléments de chacun des itérables. Si les itérables sont de longueurs différentes, les valeurs manquantes sont remplacées par fillvalue. L’itération continue jusqu’à ce que l’itérable le plus long soit épuisé. À peu près équivalent à :

class ZipExhausted(Exception):
    pass

def zip_longest(*args, **kwds):
    # zip_longest('ABCD', 'xy', fillvalue='-') --> Ax By C- D-
    fillvalue = kwds.get('fillvalue')
    counter = len(args) - 1
    def sentinel():
        nonlocal counter
        if not counter:
            raise ZipExhausted
        counter -= 1
        yield fillvalue
    fillers = repeat(fillvalue)
    iterators = [chain(it, sentinel(), fillers) for it in args]
    try:
        while iterators:
            yield tuple(map(next, iterators))
    except ZipExhausted:
        pass

Si un des itérables est potentiellement infini, alors la fonction zip_longest() doit être encapsulée dans un code qui limite le nombre d’appels (par exemple, islice() ou takewhile()). Si fillvalue n’est pas spécifié, il vaut None par défaut.

10.1.2. Recettes itertools

Cette section présente des recettes pour créer une vaste boîte à outils en se servant des itertools existants comme des briques.

Ces outils dérivés offrent la même bonne performance que les outils sous-jacents. La performance mémoire supérieure est gardée en traitant les éléments un à la fois plutôt que de charger tout l’itérable en mémoire en même temps. Le volume de code reste bas grâce à un chaînage de style fonctionnel qui aide à éliminer les variables temporaires. La grande vitesse est gardée en préférant les briques « vectorisées » plutôt que les boucles for et les générateurs qui engendrent un surcoût de traitement.

def take(n, iterable):
    "Return first n items of the iterable as a list"
    return list(islice(iterable, n))

def prepend(value, iterator):
    "Prepend a single value in front of an iterator"
    # prepend(1, [2, 3, 4]) -> 1 2 3 4
    return chain([value], iterator)

def tabulate(function, start=0):
    "Return function(0), function(1), ..."
    return map(function, count(start))

def tail(n, iterable):
    "Return an iterator over the last n items"
    # tail(3, 'ABCDEFG') --> E F G
    return iter(collections.deque(iterable, maxlen=n))

def consume(iterator, n=None):
    "Advance the iterator n-steps ahead. If n is None, consume entirely."
    # Use functions that consume iterators at C speed.
    if n is None:
        # feed the entire iterator into a zero-length deque
        collections.deque(iterator, maxlen=0)
    else:
        # advance to the empty slice starting at position n
        next(islice(iterator, n, n), None)

def nth(iterable, n, default=None):
    "Returns the nth item or a default value"
    return next(islice(iterable, n, None), default)

def all_equal(iterable):
    "Returns True if all the elements are equal to each other"
    g = groupby(iterable)
    return next(g, True) and not next(g, False)

def quantify(iterable, pred=bool):
    "Count how many times the predicate is true"
    return sum(map(pred, iterable))

def padnone(iterable):
    """Returns the sequence elements and then returns None indefinitely.

    Useful for emulating the behavior of the built-in map() function.
    """
    return chain(iterable, repeat(None))

def ncycles(iterable, n):
    "Returns the sequence elements n times"
    return chain.from_iterable(repeat(tuple(iterable), n))

def dotproduct(vec1, vec2):
    return sum(map(operator.mul, vec1, vec2))

def flatten(listOfLists):
    "Flatten one level of nesting"
    return chain.from_iterable(listOfLists)

def repeatfunc(func, times=None, *args):
    """Repeat calls to func with specified arguments.

    Example:  repeatfunc(random.random)
    """
    if times is None:
        return starmap(func, repeat(args))
    return starmap(func, repeat(args, times))

def pairwise(iterable):
    "s -> (s0,s1), (s1,s2), (s2, s3), ..."
    a, b = tee(iterable)
    next(b, None)
    return zip(a, b)

def grouper(iterable, n, fillvalue=None):
    "Collect data into fixed-length chunks or blocks"
    # grouper('ABCDEFG', 3, 'x') --> ABC DEF Gxx"
    args = [iter(iterable)] * n
    return zip_longest(*args, fillvalue=fillvalue)

def roundrobin(*iterables):
    "roundrobin('ABC', 'D', 'EF') --> A D E B F C"
    # Recipe credited to George Sakkis
    num_active = len(iterables)
    nexts = cycle(iter(it).__next__ for it in iterables)
    while num_active:
        try:
            for next in nexts:
                yield next()
        except StopIteration:
            # Remove the iterator we just exhausted from the cycle.
            num_active -= 1
            nexts = cycle(islice(nexts, num_active))

def partition(pred, iterable):
    'Use a predicate to partition entries into false entries and true entries'
    # partition(is_odd, range(10)) --> 0 2 4 6 8   and  1 3 5 7 9
    t1, t2 = tee(iterable)
    return filterfalse(pred, t1), filter(pred, t2)

def powerset(iterable):
    "powerset([1,2,3]) --> () (1,) (2,) (3,) (1,2) (1,3) (2,3) (1,2,3)"
    s = list(iterable)
    return chain.from_iterable(combinations(s, r) for r in range(len(s)+1))

def unique_everseen(iterable, key=None):
    "List unique elements, preserving order. Remember all elements ever seen."
    # unique_everseen('AAAABBBCCDAABBB') --> A B C D
    # unique_everseen('ABBCcAD', str.lower) --> A B C D
    seen = set()
    seen_add = seen.add
    if key is None:
        for element in filterfalse(seen.__contains__, iterable):
            seen_add(element)
            yield element
    else:
        for element in iterable:
            k = key(element)
            if k not in seen:
                seen_add(k)
                yield element

def unique_justseen(iterable, key=None):
    "List unique elements, preserving order. Remember only the element just seen."
    # unique_justseen('AAAABBBCCDAABBB') --> A B C D A B
    # unique_justseen('ABBCcAD', str.lower) --> A B C A D
    return map(next, map(itemgetter(1), groupby(iterable, key)))

def iter_except(func, exception, first=None):
    """ Call a function repeatedly until an exception is raised.

    Converts a call-until-exception interface to an iterator interface.
    Like builtins.iter(func, sentinel) but uses an exception instead
    of a sentinel to end the loop.

    Examples:
        iter_except(functools.partial(heappop, h), IndexError)   # priority queue iterator
        iter_except(d.popitem, KeyError)                         # non-blocking dict iterator
        iter_except(d.popleft, IndexError)                       # non-blocking deque iterator
        iter_except(q.get_nowait, Queue.Empty)                   # loop over a producer Queue
        iter_except(s.pop, KeyError)                             # non-blocking set iterator

    """
    try:
        if first is not None:
            yield first()            # For database APIs needing an initial cast to db.first()
        while True:
            yield func()
    except exception:
        pass

def first_true(iterable, default=False, pred=None):
    """Returns the first true value in the iterable.

    If no true value is found, returns *default*

    If *pred* is not None, returns the first item
    for which pred(item) is true.

    """
    # first_true([a,b,c], x) --> a or b or c or x
    # first_true([a,b], x, f) --> a if f(a) else b if f(b) else x
    return next(filter(pred, iterable), default)

def random_product(*args, repeat=1):
    "Random selection from itertools.product(*args, **kwds)"
    pools = [tuple(pool) for pool in args] * repeat
    return tuple(random.choice(pool) for pool in pools)

def random_permutation(iterable, r=None):
    "Random selection from itertools.permutations(iterable, r)"
    pool = tuple(iterable)
    r = len(pool) if r is None else r
    return tuple(random.sample(pool, r))

def random_combination(iterable, r):
    "Random selection from itertools.combinations(iterable, r)"
    pool = tuple(iterable)
    n = len(pool)
    indices = sorted(random.sample(range(n), r))
    return tuple(pool[i] for i in indices)

def random_combination_with_replacement(iterable, r):
    "Random selection from itertools.combinations_with_replacement(iterable, r)"
    pool = tuple(iterable)
    n = len(pool)
    indices = sorted(random.randrange(n) for i in range(r))
    return tuple(pool[i] for i in indices)

def nth_combination(iterable, r, index):
    'Equivalent to list(combinations(iterable, r))[index]'
    pool = tuple(iterable)
    n = len(pool)
    if r < 0 or r > n:
        raise ValueError
    c = 1
    k = min(r, n-r)
    for i in range(1, k+1):
        c = c * (n - k + i) // i
    if index < 0:
        index += c
    if index < 0 or index >= c:
        raise IndexError
    result = []
    while r:
        c, n, r = c*r//n, n-1, r-1
        while index >= c:
            index -= c
            c, n = c*(n-r)//n, n-1
        result.append(pool[-1-n])
    return tuple(result)

Note, beaucoup des recettes ci-dessus peuvent être optimisées en replaçant les recherches globales par des recherches locales avec des variables locales définies comme des valeurs par défaut. Par exemple, la recette dotproduct peut être écrite comme :

def dotproduct(vec1, vec2, sum=sum, map=map, mul=operator.mul):
    return sum(map(mul, vec1, vec2))

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10.2. functools — Fonctions de haut niveau et opérations sur des objets appelables

Code source : Lib/functools.py [https://github.com/python/cpython/tree/3.6/Lib/functools.py]

Le module functools est utilisé pour des fonctions de haut niveau : des fonctions qui agissent sur ou revoient d’autres fonctions. En général, tout objet appelable peut être utilisé comme une fonction pour les besoins de ce module.

Le module functools définit les fonctions suivantes :

functools.cmp_to_key(func)

Transforme une fonction de comparaison à l’ancienne en une fonction clé. Utilisé avec des outils qui acceptent des fonctions clef (comme sorted(), min(), max(), heapq.nlargest(), heapq.nsmallest(), itertools.groupby()). Cette fonction est destinée au portage de fonctions python 2 utilisant des fonctions de comparaison vers Python 3.

Une fonction de comparaison est un appelable qui prend deux arguments, les compare, et renvoie un nombre négatif pour l’infériorité, zéro pour l’égalité ou un nombre positif pour la supériorité. Une fonction de clé est un appelable qui prend un argument et retourne une autre valeur qui sera utilisée comme clé de tri.

Exemple :

sorted(iterable, key=cmp_to_key(locale.strcoll))  # locale-aware sort order

Pour des exemples de tris et un bref tutoriel, consultez Guide pour le tri.

Nouveau dans la version 3.2.

@functools.lru_cache(maxsize=128, typed=False)

Décorateur qui englobe une fonction avec un appelable mémoïsant qui enregistre jusqu’à maxsize appels récents. Cela peut gagner du temps quand une fonction coûteuse en ressources est souvent appelée avec les mêmes arguments.

Comme un dictionnaire est utilisé pour mettre en cache les résultats, les arguments positionnels et nommés de la fonction doivent être hachables.

Si maxsize est à None, la fonctionnalité LRU est désactivée et le cache peut grossir sans limite. La fonctionnalité LRU fonctionne mieux quand maxsize est une puissance de deux.

Si typed est vrai, les arguments de différents types seront mis en cache séparément. Par exemple, f(3) et f(3.0) seront considérés comme des appels distincts avec des résultats distincts.

Pour aider à mesurer l’efficacité du cache et ajuster le paramètre maxsize, la fonction englobée est surveillée avec une fonction cache_info() qui renvoie un named tuple affichant les hits, misses, maxsize et currsize. Dans un environnement multithread, les succès et échecs d’appel du cache sont approximatifs.

Le décorateur fournit également une fonction cache_clear() pour vider ou invalider le cache.

La fonction sous-jacente originale est accessible à travers l’attribut __wrapped__. Ceci est utile pour l’introspection, pour outrepasser le cache, ou pour ré-englober la fonction avec un cache différent.

Un cache LRU (*least recently used*) [https://fr.wikipedia.org/wiki/Algorithmes_de_remplacement_des_lignes_de_cache#LRU_.28Least_Recently_Used.29] fonctionne très bien lorsque les appels récents sont les prochains appels les plus probables (par exemple, les articles les plus lus d’un serveur d’actualités ont tendance à ne changer que d’un jour à l’autre). La taille limite du cache permet de s’assurer que le cache ne grossisse pas sans limite sur les processus longs comme les serveurs web.

In general, the LRU cache should only be used when you want to reuse previously computed values. Accordingly, it doesn’t make sense to cache functions with side-effects, functions that need to create distinct mutable objects on each call, or impure functions such as time() or random().

Exemple d’un cache LRU pour du contenu web statique :

@lru_cache(maxsize=32)
def get_pep(num):
    'Retrieve text of a Python Enhancement Proposal'
    resource = 'http://www.python.org/dev/peps/pep-%04d/' % num
    try:
        with urllib.request.urlopen(resource) as s:
            return s.read()
    except urllib.error.HTTPError:
        return 'Not Found'

>>> for n in 8, 290, 308, 320, 8, 218, 320, 279, 289, 320, 9991:
...     pep = get_pep(n)
...     print(n, len(pep))

>>> get_pep.cache_info()
CacheInfo(hits=3, misses=8, maxsize=32, currsize=8)

Exemple de calcul efficace de la suite de Fibonacci [https://fr.wikipedia.org/wiki/Suite_de_Fibonacci] en utilisant un cache pour implémenter la technique de programmation dynamique [https://fr.wikipedia.org/wiki/Programmation_dynamique] :

@lru_cache(maxsize=None)
def fib(n):
    if n < 2:
        return n
    return fib(n-1) + fib(n-2)

>>> [fib(n) for n in range(16)]
[0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144, 233, 377, 610]

>>> fib.cache_info()
CacheInfo(hits=28, misses=16, maxsize=None, currsize=16)

Nouveau dans la version 3.2.

Modifié dans la version 3.3: L’option typed a été ajoutée.

@functools.total_ordering

A partir d’une classe définissant une ou plusieurs méthodes de comparaison riches, ce décorateur de classe fournit le reste. Ceci simplifie l’effort à fournir dans la spécification de toutes les opérations de comparaison riche :

La classe doit définir au moins une de ces méthodes __lt__(), __le__(), __gt__(), or __ge__(). De plus, la classe doit fournir une méthode __eq__().

Par exemple :

@total_ordering
class Student:
    def _is_valid_operand(self, other):
        return (hasattr(other, "lastname") and
                hasattr(other, "firstname"))
    def __eq__(self, other):
        if not self._is_valid_operand(other):
            return NotImplemented
        return ((self.lastname.lower(), self.firstname.lower()) ==
                (other.lastname.lower(), other.firstname.lower()))
    def __lt__(self, other):
        if not self._is_valid_operand(other):
            return NotImplemented
        return ((self.lastname.lower(), self.firstname.lower()) <
                (other.lastname.lower(), other.firstname.lower()))

Note

Même si ce décorateur permet de créer des types ordonnables facilement, cela vient avec un coût d’exécution et des traces d’exécution complexes pour les méthodes de comparaison dérivées. Si des tests de performances le révèlent comme un goulot d’étranglement, l’implémentation manuelle des six méthodes de comparaison riches résoudra normalement vos problèmes de rapidité.

Nouveau dans la version 3.2.

Modifié dans la version 3.4: Retourner NotImplemented dans les fonction de comparaison sous-jacentes pour les types non reconnus est maintenant supporté.

functools.partial(func, *args, **keywords)

Return a new partial object which when called will behave like func called with the positional arguments args and keyword arguments keywords. If more arguments are supplied to the call, they are appended to args. If additional keyword arguments are supplied, they extend and override keywords. Roughly equivalent to:

def partial(func, *args, **keywords):
    def newfunc(*fargs, **fkeywords):
        newkeywords = keywords.copy()
        newkeywords.update(fkeywords)
        return func(*args, *fargs, **newkeywords)
    newfunc.func = func
    newfunc.args = args
    newfunc.keywords = keywords
    return newfunc

partial() est utilisé pour une application de fonction partielle qui « gèle » une portion des arguments et/ou mots-clés d’une fonction donnant un nouvel objet avec une signature simplifiée. Par exemple, partial() peut être utilisé pour créer un appelable qui se comporte comme la fonction int() ou l’argument base est deux par défaut :

>>> from functools import partial
>>> basetwo = partial(int, base=2)
>>> basetwo.__doc__ = 'Convert base 2 string to an int.'
>>> basetwo('10010')
18

class functools.partialmethod(func, *args, **keywords)

Retourne un nouveau descripteur partialmethod qui se comporte comme partial sauf qu’il est fait pour être utilisé comme une définition de méthode plutôt que d’être appelé directement.

func doit être un descriptor ou un appelable (les objets qui sont les deux, comme les fonction normales, sont gérés comme des descripteurs).

When func is a descriptor (such as a normal Python function, classmethod(), staticmethod(), abstractmethod() or another instance of partialmethod), calls to __get__ are delegated to the underlying descriptor, and an appropriate partial object returned as the result.

Quand func est un appelable non-descripteur, une méthode liée appropriée est crée dynamiquement. Elle se comporte comme une fonction Python normale quand elle est utilisée comme méthode : l’argument self sera inséré comme premier argument positionnel, avant les args et keywords fournis au constructeur partialmethod.

Exemple :

>>> class Cell(object):
...     def __init__(self):
...         self._alive = False
...     @property
...     def alive(self):
...         return self._alive
...     def set_state(self, state):
...         self._alive = bool(state)
...     set_alive = partialmethod(set_state, True)
...     set_dead = partialmethod(set_state, False)
...
>>> c = Cell()
>>> c.alive
False
>>> c.set_alive()
>>> c.alive
True

Nouveau dans la version 3.4.

functools.reduce(function, iterable[, initializer])

Applique function avec deux arguments cumulativement aux éléments de sequence, de gauche à droite, pour réduire la séquence à une valeur unique. Par exemple, reduce(lambda x, y: x+y, [1, 2, 3, 4, 5]) calcule ((((1+2)+3)+4)+5). Le premier argument, x, et la valeur de cumul et le deuxième, y, est la valeur de mise à jour depuis sequence. Si l’argument optionnel initializer est présent, il est placé avant les éléments de la séquence dans le calcul, et sert de valeur par défaut quand la séquence est vide. Si initializer n’est pas renseigné et que sequence ne contient qu’un élément, le premier élément est retourné.

Sensiblement équivalent à :

def reduce(function, iterable, initializer=None):
    it = iter(iterable)
    if initializer is None:
        value = next(it)
    else:
        value = initializer
    for element in it:
        value = function(value, element)
    return value

@functools.singledispatch

Transforme une fonction en une fonction générique single-dispatch.

Pour définir une fonction générique, il faut la décorer avec le décorateur @singledispatch. Noter que la distribution est effectuée sur le type du premier argument, donc la fonction doit être créée en conséquence :

>>> from functools import singledispatch
>>> @singledispatch
... def fun(arg, verbose=False):
...     if verbose:
...         print("Let me just say,", end=" ")
...     print(arg)

Pour ajouter des surcharges d’implémentation à la fonction, utiliser l’attribut register() de la fonction générique. C’est un décorateur, prenant un type en paramètre et décorant une fonction implémentant l’opération pour ce type :

>>> @fun.register(int)
... def _(arg, verbose=False):
...     if verbose:
...         print("Strength in numbers, eh?", end=" ")
...     print(arg)
...
>>> @fun.register(list)
... def _(arg, verbose=False):
...     if verbose:
...         print("Enumerate this:")
...     for i, elem in enumerate(arg):
...         print(i, elem)

Pour permettre l’enregistrement de lambdas et de fonctions pré-existantes, l’attribut register() peut être utilisé sous forme fonctionnelle :

>>> def nothing(arg, verbose=False):
...     print("Nothing.")
...
>>> fun.register(type(None), nothing)

L’attribut register() renvoie la fonction non décorée ce qui permet d’empiler les décorateurs, la sérialisation, et la création de tests unitaires pour chaque variante indépendamment :

>>> @fun.register(float)
... @fun.register(Decimal)
... def fun_num(arg, verbose=False):
...     if verbose:
...         print("Half of your number:", end=" ")
...     print(arg / 2)
...
>>> fun_num is fun
False

Quand elle est appelée, la fonction générique distribue sur le type du premier argument :

>>> fun("Hello, world.")
Hello, world.
>>> fun("test.", verbose=True)
Let me just say, test.
>>> fun(42, verbose=True)
Strength in numbers, eh? 42
>>> fun(['spam', 'spam', 'eggs', 'spam'], verbose=True)
Enumerate this:
0 spam
1 spam
2 eggs
3 spam
>>> fun(None)
Nothing.
>>> fun(1.23)
0.615

Quand il n’y a pas d’implémentation enregistrée pour un type spécifique, son ordre de résolution de méthode est utilisé pour trouver une implémentation plus générique. La fonction originale est décorée avec @singledispatch est enregistrée pour le type d”object, et elle sera utilisée si aucune implémentation n’est trouvée.

Pour vérifier quelle implémentation la fonction générique choisira pour un type donné, utiliser l’attribut dispatch() :

>>> fun.dispatch(float)
<function fun_num at 0x1035a2840>
>>> fun.dispatch(dict)    # note: default implementation
<function fun at 0x103fe0000>

Pour accéder à toutes les implémentations enregistrées, utiliser l’attribut en lecture seule registry :

>>> fun.registry.keys()
dict_keys([<class 'NoneType'>, <class 'int'>, <class 'object'>,
          <class 'decimal.Decimal'>, <class 'list'>,
          <class 'float'>])
>>> fun.registry[float]
<function fun_num at 0x1035a2840>
>>> fun.registry[object]
<function fun at 0x103fe0000>

Nouveau dans la version 3.4.

functools.update_wrapper(wrapper, wrapped, assigned=WRAPPER_ASSIGNMENTS, updated=WRAPPER_UPDATES)

Met à jour la fonction wrapper pour ressembler à la fonction wrapped. Les arguments optionnels sont des tuples pour spécifier quels attributs de la fonction originale sont assignés directement aux attributs correspondants sur la fonction englobante et quels attributs de la fonction englobante sont mis à jour avec les attributs de la fonction originale. Les valeurs par défaut de ces arguments sont les constantes au niveau du module WRAPPER_ASSIGNMENTS (qui assigne __module__, __name__, __qualname__, __annotations__ et __doc__, la chaîne de documentation, depuis la fonction englobante) et WRAPPER_UPDATES (qui met à jour le __dict__ de la fonction englobante, c’est-à-dire le dictionnaire de l’instance).

Pour autoriser l’accès à la fonction originale pour l’introspection ou à d’autres fins (par ex. outrepasser l’accès à un décorateur de cache comme lru_cache()), cette fonction ajoute automatiquement un attribut __wrapped__ qui référence la fonction englobée.

La principale utilisation de cette fonction est dans les décorateurs qui renvoient une nouvelle fonction. Si la fonction crée n’est pas mise à jour, ses métadonnées refléteront sa définition dans le décorateur, au lieu de la définition originale, métadonnées souvent bien moins utiles.

update_wrapper() peut être utilisé avec des appelables autres que des fonctions. Tout attribut défini dans assigned ou updated qui ne sont pas l’objet englobé sont ignorés (cette fonction n’essaiera pas de les définir dans la fonction englobante). AttributeError est toujours levée si le fonction englobante elle même a des attributs non existants dans updated.

Nouveau dans la version 3.2: Ajout automatique de l’attribut __wrapped__.

Nouveau dans la version 3.2: Copie de l’attribut __annotations__ par défaut.

Modifié dans la version 3.2: Les attributs manquants ne lèvent plus d’exception AttributeError.

Modifié dans la version 3.4: L’attribut __wrapped__ renvoie toujours la fonction englobée, même si cette fonction définit un attribut __wrapped__. (voir bpo-17482 [https://bugs.python.org/issue17482])

@functools.wraps(wrapped, assigned=WRAPPER_ASSIGNMENTS, updated=WRAPPER_UPDATES)

Ceci est une fonction d’aide pour appeler update_wrapper() comme décorateur de fonction lors de la définition d’une fonction englobante. C’est équivalent à partial(update_wrapper, wrapped=wrapped, assigned=assigned, updated=updated). Par exemple :

>>> from functools import wraps
>>> def my_decorator(f):
...     @wraps(f)
...     def wrapper(*args, **kwds):
...         print('Calling decorated function')
...         return f(*args, **kwds)
...     return wrapper
...
>>> @my_decorator
... def example():
...     """Docstring"""
...     print('Called example function')
...
>>> example()
Calling decorated function
Called example function
>>> example.__name__
'example'
>>> example.__doc__
'Docstring'

Sans l’utilisation de cette usine à décorateur, le nom de la fonction d’exemple aurait été 'wrapper', et la chaîne de documentation de la fonction example() originale aurait été perdue.

10.2.1. Objets partial

Les objets partial sont des objets appelables créés par partial(). Ils ont trois attributs en lecture seule :

partial.func

Un objet ou une fonction appelable. Les appels à l’objet partial seront transmis à func avec les nouveaux arguments et mots-clés.

partial.args

Les arguments positionnels qui seront ajoutés avant les arguments fournis lors de l’appel d’un objet partial.

partial.keywords

Les arguments nommés qui seront fournis quand l’objet partial est appelé.

Les objets partial sont comme des objets function de par le fait qu’il sont appelables, référençables, et peuvent avoir des attributs. Il y a cependant des différences importantes. Par exemple, les attributs __name__ et __doc__ ne sont pas créés automatiquement. De plus, les objets partial définis dans les classes se comportent comme des méthodes statiques et ne se transforment pas en méthodes liées durant la recherche d’attributs dans l’instance.

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10.3. operator — Opérateurs standards en tant que fonctions

Code source : Lib/operator.py [https://github.com/python/cpython/tree/3.6/Lib/operator.py]

Le module operator fournit un ensemble de fonctions correspondant aux opérateurs natifs de Python. Par exemple, operator.add(x, y) correspond à l’expression x+y. Les noms de la plupart de ces fonctions sont ceux utilisés par les méthodes spéciales, sans les doubles tirets bas. Pour assurer la rétrocompatibilité, la plupart de ces noms ont une variante avec les doubles tirets bas ; la forme simple est cependant à privilégier pour des raisons de clarté.

Les fonctions sont divisées en différentes catégories selon l’opération effectuée : comparaison entre objets, opérations logiques, opérations mathématiques ou opérations sur séquences.

Les fonctions de comparaison s’appliquent à tous les objets, et leur nom vient des opérateurs de comparaison qu’elles implémentent :

operator.lt(a, b)

operator.le(a, b)

operator.eq(a, b)

operator.ne(a, b)

operator.ge(a, b)

operator.gt(a, b)

operator.__lt__(a, b)

operator.__le__(a, b)

operator.__eq__(a, b)

operator.__ne__(a, b)

operator.__ge__(a, b)

operator.__gt__(a, b)

Effectue une « comparaison riche » entre a et b. Plus précisément, lt(a, b) équivaut à a < b, le(a, b) équivaut à a <= b, eq(a, b) équivaut à a == b, ne(a, b) équivaut à a != b, gt(a, b) équivaut à a > b et ge(a, b) équivaut à a >= b. Notez que ces fonctions peuvent renvoyer n’importe quelle valeur, convertible ou non en booléen. Voir Comparaisons pour plus d’informations sur les méthodes de comparaison riches.

En général, les opérations logiques s’appliquent aussi à tous les objets et implémentent les tests de vérité, d’identité et les opérations booléennes :

operator.not_(obj)

operator.__not__(obj)

Renvoie le résultat de not obj. (Notez qu’il n’existe pas de méthode __not__() pour les instances d’objet; seul le cœur de l’interpréteur définit cette opération. Le résultat dépend des méthodes __bool__() et __len__().)

operator.truth(obj)

Renvoie True si obj est vrai, et False dans le cas contraire. Équivaut à utiliser le constructeur de bool.

operator.is_(a, b)

Renvoie a is b. Vérifie si les deux paramètres sont le même objet.

operator.is_not(a, b)

Renvoie a is not b. Vérifie si les deux paramètres sont deux objets distincts.

Les opérations mathématiques ou bit à bit sont les plus nombreuses :

operator.abs(obj)

operator.__abs__(obj)

Renvoie la valeur absolue de obj.

operator.add(a, b)

operator.__add__(a, b)

Renvoie a + b où a et b sont des nombres.

operator.and_(a, b)

operator.__and__(a, b)

Renvoie le et bit à bit de a et b.

operator.floordiv(a, b)

operator.__floordiv__(a, b)

Renvoie a // b.

operator.index(a)

operator.__index__(a)

Renvoie a converti en entier. Équivaut à a.__index__().

operator.inv(obj)

operator.invert(obj)

operator.__inv__(obj)

operator.__invert__(obj)

Renvoie l’inverse bit à bit du nombre obj. Équivaut à ~obj.

operator.lshift(a, b)

operator.__lshift__(a, b)

Renvoie le décalage de b bits vers la gauche de a.

operator.mod(a, b)

operator.__mod__(a, b)

Renvoie``a % b``.

operator.mul(a, b)

operator.__mul__(a, b)

Renvoie a * b où a et b sont des nombres.

operator.matmul(a, b)

operator.__matmul__(a, b)

Renvoie a @ b.

Nouveau dans la version 3.5.

operator.neg(obj)

operator.__neg__(obj)

Renvoie l’opposé de obj (-obj).

operator.or_(a, b)

operator.__or__(a, b)

Renvoie le ou bit à bit de a et b.

operator.pos(obj)

operator.__pos__(obj)

Renvoie la valeur positive de obj (+obj).

operator.pow(a, b)

operator.__pow__(a, b)

Renvoie a ** b où a et b sont des nombres.

operator.rshift(a, b)

operator.__rshift__(a, b)

Renvoie le décalage de b bits vers la droite de a.

operator.sub(a, b)

operator.__sub__(a, b)

Renvoie a - b.

operator.truediv(a, b)

operator.__truediv__(a, b)

Renvoie a / b où 2/3 est 0.66 et non 0. Appelée aussi division « réelle ».

operator.xor(a, b)

operator.__xor__(a, b)

Renvoie le ou exclusif bit à bit de a et b.

Les opérations sur séquences (et pour certaines, sur correspondances) sont :

operator.concat(a, b)

operator.__concat__(a, b)

Renvoie a + b où a et b sont des séquences.

operator.contains(a, b)

operator.__contains__(a, b)

Renvoie le résultat du test b in a. Notez que les opérandes sont inversées.

operator.countOf(a, b)

Renvoie le nombre d’occurrences de b dans a.

operator.delitem(a, b)

operator.__delitem__(a, b)

Renvoie la valeur de a à l’indice b.

operator.getitem(a, b)

operator.__getitem__(a, b)

Renvoie la valeur de a à l’indice b.

operator.indexOf(a, b)

Renvoie l’indice de la première occurrence de b dans a.

operator.setitem(a, b, c)

operator.__setitem__(a, b, c)

Affecte c dans a à l’indice b.

operator.length_hint(obj, default=0)

Renvoie une estimation de la taille de l’objet o. Tente d’abord de renvoyer la taille réelle, puis une estimation en appelant object.__length_hint__(), ou sinon la valeur par défaut.

Nouveau dans la version 3.4.

Le module operator définit aussi des fonctions pour la recherche générique d’attributs ou d’objets. Elles sont particulièrement utiles pour construire rapidement des accesseurs d’attributs à passer en paramètre à map(), sorted(), itertools.groupby() ou à toute autre fonction prenant une fonction en paramètre.

operator.attrgetter(attr)

operator.attrgetter(*attrs)

Renvoie un objet appelable qui récupère attr de son opérande. Si plus d’un attribut est demandé, renvoie un n-uplet d’attributs. Les noms des attributs peuvent aussi comporter des points. Par exemple :

Avec f = attrgetter('name'), l’appel f(b) renvoie b.name.

Avec f = attrgetter('name', 'date'), l’appel f(b) renvoie (b.name, b.date).

Après f = attrgetter('name.first', 'name.last'), l’appel f(b) renvoie (b.name.first, b.name.last).

Équivalent à :

def attrgetter(*items):
    if any(not isinstance(item, str) for item in items):
        raise TypeError('attribute name must be a string')
    if len(items) == 1:
        attr = items[0]
        def g(obj):
            return resolve_attr(obj, attr)
    else:
        def g(obj):
            return tuple(resolve_attr(obj, attr) for attr in items)
    return g

def resolve_attr(obj, attr):
    for name in attr.split("."):
        obj = getattr(obj, name)
    return obj

operator.itemgetter(item)

operator.itemgetter(*items)

Renvoie un objet appelable qui récupère item de l’opérande en utilisant la méthode __getitem__(). Si plusieurs item sont passés en paramètre, renvoie un n-uplet des valeurs récupérées. Par exemple :

Avec f = itemgetter(2), f(r) renvoie r[2].

Avec g = itemgetter(2, 5, 3), g(r) renvoie (r[2], r[5], r[3]).

Équivalent à :

def itemgetter(*items):
    if len(items) == 1:
        item = items[0]
        def g(obj):
            return obj[item]
    else:
        def g(obj):
            return tuple(obj[item] for item in items)
    return g

Les items en entrée peuvent être de n’importe quel type tant que celui-ci est géré par la méthode __getitem__() de l’opérande. Les dictionnaires acceptent toute valeur hachable. Les listes, n-uplets et chaînes de caractères acceptent un index ou une tranche :

>>> itemgetter(1)('ABCDEFG')
'B'
>>> itemgetter(1,3,5)('ABCDEFG')
('B', 'D', 'F')
>>> itemgetter(slice(2,None))('ABCDEFG')
'CDEFG'

Exemple d’utilisation de itemgetter() pour récupérer des champs spécifiques d’un n-uplet :

>>> inventory = [('apple', 3), ('banana', 2), ('pear', 5), ('orange', 1)]
>>> getcount = itemgetter(1)
>>> list(map(getcount, inventory))
[3, 2, 5, 1]
>>> sorted(inventory, key=getcount)
[('orange', 1), ('banana', 2), ('apple', 3), ('pear', 5)]

operator.methodcaller(name[, args...])

Renvoie un objet appelable qui appelle la méthode name de son opérande. Si des paramètres supplémentaires et/ou des paramètres nommés sont donnés, ils seront aussi passés à la méthode. Par exemple :

Avec f = methodcaller('name'), f(b) renvoie b.name().

Avec f = methodcaller('name', 'foo', bar=1), f(b) renvoie b.name('foo', bar=1).

Équivalent à :

def methodcaller(name, *args, **kwargs):
    def caller(obj):
        return getattr(obj, name)(*args, **kwargs)
    return caller

10.3.1. Correspondances entre opérateurs et fonctions

Le tableau montre la correspondance entre les symboles des opérateurs Python et les fonctions du module operator.

Opération

Syntaxe

Fonction

Addition

a + b

add(a, b)

Concaténation

seq1 + seq2

concat(seq1, seq2)

Test d’inclusion

obj in seq

contains(seq, obj)

Division

a / b

truediv(a, b)

Division

a // b

floordiv(a, b)

Et bit à bit

a & b

and_(a, b)

Ou exclusif bit à bit

a ^ b

xor(a, b)

Inversion bit à bit

~ a

invert(a)

Ou bit à bit

a | b

or_(a, b)

Exponentiation

a ** b

pow(a, b)

Identité

a is b

is_(a, b)

Identité

a is not b

is_not(a, b)

Affectation par index

obj[k] = v

setitem(obj, k, v)

Suppression par index

del obj[k]

delitem(obj, k)

Indexation

obj[k]

getitem(obj, k)

Décalage bit à bit gauche

a << b

lshift(a, b)

Modulo

a % b

mod(a, b)

Multiplication

a * b

mul(a, b)

Multiplication matricielle

a @ b

matmul(a, b)

Opposé

- a

neg(a)

Négation (logique)

not a

not_(a)

Valeur positive

+ a

pos(a)

Décalage bit à bit droite

a >> b

rshift(a, b)

Affectation par tranche

seq[i:j] = values

setitem(seq, slice(i, j), values)

Suppression par tranche

del seq[i:j]

delitem(seq, slice(i, j))

Tranche

seq[i:j]

getitem(seq, slice(i, j))

Formatage de chaînes de caractères

s % obj

mod(s, obj)

Soustraction

a - b

sub(a, b)

Test de véracité

obj

truth(obj)

Ordre

a < b

lt(a, b)

Ordre

a <= b

le(a, b)

Égalité

a == b

eq(a, b)

Inégalité

a != b

ne(a, b)

Ordre

a >= b

ge(a, b)

Ordre

a > b

gt(a, b)

10.3.2. Inplace Operators

Beaucoup d’opérations ont une version travaillant « en-place ». Les fonctions listées ci-dessous fournissent un accès plus direct aux opérateurs en-place que la syntaxe Python habituelle ; par exemple, l’expression statement x += y équivaut à x = operator.iadd(x, y). Autrement dit, l’expression z = operator.iadd(x, y) équivaut à l’expression composée z = x; z += y.

Dans ces exemples, notez que lorsqu’une méthode en-place est appelée, le calcul et l’affectation sont effectués en deux étapes distinctes. Les fonctions en-place de la liste ci-dessous ne font que la première, en appelant la méthode en-place. La seconde étape, l’affectation, n’est pas effectuée.

Pour des paramètres non-mutables comme les chaînes de caractères, les nombres et les n-uplets, la nouvelle valeur est calculée, mais pas affectée à la variable d’entrée:

>>> a = 'hello'
>>> iadd(a, ' world')
'hello world'
>>> a
'hello'

For mutable targets such as lists and dictionaries, the inplace method will perform the update, so no subsequent assignment is necessary:

>>> s = ['h', 'e', 'l', 'l', 'o']
>>> iadd(s, [' ', 'w', 'o', 'r', 'l', 'd'])
['h', 'e', 'l', 'l', 'o', ' ', 'w', 'o', 'r', 'l', 'd']
>>> s
['h', 'e', 'l', 'l', 'o', ' ', 'w', 'o', 'r', 'l', 'd']

operator.iadd(a, b)

operator.__iadd__(a, b)

a = iadd(a, b) équivaut à a += b.

operator.iand(a, b)

operator.__iand__(a, b)

a = iand(a, b) équivaut à a &= b.

operator.iconcat(a, b)

operator.__iconcat__(a, b)

a = iconcat(a, b) équivaut à a += b où a et b sont des séquences.

operator.ifloordiv(a, b)

operator.__ifloordiv__(a, b)

a = ifloordiv(a, b)``équivaut à ``a //= b.

operator.ilshift(a, b)

operator.__ilshift__(a, b)

a = ilshift(a, b) équivaut à a <<= b.

operator.imod(a, b)

operator.__imod__(a, b)

a = imod(a, b) équivaut à a %= b.

operator.imul(a, b)

operator.__imul__(a, b)

a = imul(a, b) équivaut à a *= b.

operator.imatmul(a, b)

operator.__imatmul__(a, b)

a = imatmul(a, b) équivaut à a @= b.

Nouveau dans la version 3.5.

operator.ior(a, b)

operator.__ior__(a, b)

a = ior(a, b) équivaut à a |= b.

operator.ipow(a, b)

operator.__ipow__(a, b)

a = ipow(a, b) équivaut à a **= b.

operator.irshift(a, b)

operator.__irshift__(a, b)

a = irshift(a, b) équivaut à a >>= b.

operator.isub(a, b)

operator.__isub__(a, b)

a = isub(a, b) équivaut à a -= b.

operator.itruediv(a, b)

operator.__itruediv__(a, b)

a = itruediv(a, b) équivaut à a /= b.

operator.ixor(a, b)

operator.__ixor__(a, b)

a = ixor(a, b) équivaut à a ^= b.

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11. Accès aux Fichiers et aux Dossiers

Les modules décrits dans ce chapitre servent à accéder aux fichiers et aux dossiers. Des modules, par exemple, pour lire les propriétés des fichiers, manipuler des chemins de manière portable, et créer des fichiers temporaires. La liste exhaustive des modules de ce chapitre est :

11.1. pathlib — Chemins de système de fichiers orientés objet

11.1.1. Utilisation basique

11.1.2. Chemins purs

11.1.2.1. Propriétés générales

11.1.2.2. Opérateurs

11.1.2.3. Accéder aux parties individuelles

11.1.2.4. Méthodes et propriétés

11.1.3. Chemins concrets

11.1.3.1. Méthodes

11.2. os.path — manipulation courante des chemins

11.3. fileinput — Iterate over lines from multiple input streams

11.4. stat — Interpreting stat() results

11.5. filecmp – Comparaisons de fichiers et de répertoires

11.5.1. La classe dircmp

11.6. tempfile — Génération de fichiers et répertoires temporaires

11.6.1. Exemples

11.6.2. Fonctions et variables obsolètes

11.7. glob — Recherche de chemins de style Unix selon certains motifs

11.8. fnmatch — Filtrage par motif des noms de fichiers Unix

11.9. linecache — Accès direct aux lignes d’un texte

11.10. shutil — Opérations de haut niveau sur les fichiers

11.10.1. Opérations sur les répertoires et les fichiers

11.10.1.1. copytree example

11.10.1.2. rmtree example

11.10.2. Archiving operations

11.10.2.1. Archiving example

11.10.3. Querying the size of the output terminal

11.11. macpath — Fonctions de manipulation de chemins pour Mac OS 9

Voir aussi

Module os

Interfaces du système d’exploitation, incluant des fonctions pour travailler avec des fichiers dans un niveau plus bas que les objets fichiers de Python.

Module io

Bibliothèque d’entrées/sorties native de Python, incluant des classes abstraites et concrètes tel que les I/O sur les fichiers.

Fonction native open()

Le moyen classique pour ouvrir des fichiers pour les lire ou y écrire avec Python.

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11.1. pathlib — Chemins de système de fichiers orientés objet

Nouveau dans la version 3.4.

Code source : Lib/pathlib.py [https://github.com/python/cpython/tree/3.6/Lib/pathlib.py]

Ce module offre des classes représentant le système de fichiers avec la sémantique appropriée pour différents systèmes d’exploitation. Les classes de chemins sont divisées en chemins purs, qui fournissent purement du calcul sans entrées/sorties, et chemins concrets, qui héritent des chemins purs et fournissent également les opérations d’entrées/sorties.

Si vous n’avez jamais utilisé ce module précédemment, ou si vous n’êtes pas sûr de quelle classe est faite pour votre tâche, Path est très certainement ce dont vous avez besoin. Elle instancie un chemin concret pour la plateforme sur laquelle s’exécute le code.

Les chemins purs sont utiles dans certains cas particuliers ; par exemple :

Si vous voulez manipuler des chemins Windows sur une machine Unix (ou vice versa). Vous ne pouvez pas instancier un WindowsPath quand vous êtes sous Unix, mais vous pouvez instancier PureWindowsPath.

Vous voulez être sûr que votre code manipule des chemins sans réellement accéder au système d’exploitation. Dans ce cas, instancier une de ces classes pures peut être utile puisqu’elle ne possède tout simplement aucune opération permettant d’accéder au système d’exploitation.

Voir aussi

PEP 428 [https://www.python.org/dev/peps/pep-0428] : Le module pathlib – chemins de système de fichiers orientés objet.

Voir aussi

Pour de la manipulation de chemins bas-niveau avec des chaînes de caractères, vous pouvez aussi utiliser le module os.path.

11.1.1. Utilisation basique

Importer la classe principale :

>>> from pathlib import Path

Lister les sous-dossiers :

>>> p = Path('.')
>>> [x for x in p.iterdir() if x.is_dir()]
[PosixPath('.hg'), PosixPath('docs'), PosixPath('dist'),
 PosixPath('__pycache__'), PosixPath('build')]

Lister les fichiers source Python dans cette arborescence de dossiers :

>>> list(p.glob('**/*.py'))
[PosixPath('test_pathlib.py'), PosixPath('setup.py'),
 PosixPath('pathlib.py'), PosixPath('docs/conf.py'),
 PosixPath('build/lib/pathlib.py')]

Naviguer à l’intérieur d’une arborescence de dossiers :

>>> p = Path('/etc')
>>> q = p / 'init.d' / 'reboot'
>>> q
PosixPath('/etc/init.d/reboot')
>>> q.resolve()
PosixPath('/etc/rc.d/init.d/halt')

Récupérer les propriétés de chemin :

>>> q.exists()
True
>>> q.is_dir()
False

Ouvrir un fichier :

>>> with q.open() as f: f.readline()
...
'#!/bin/bash\n'

11.1.2. Chemins purs

Les objets chemins purs fournissent les opérations de gestion de chemin qui n’accèdent pas réellement au système de fichiers. Il y a trois façons d’accéder à ces classes que nous appelons aussi familles :

class pathlib.PurePath(*pathsegments)

Une classe générique qui représente la famille de chemin du système (l’instancier crée soit un PurePosixPath soit un PureWindowsPath) :

>>> PurePath('setup.py')      # Running on a Unix machine
PurePosixPath('setup.py')

Chaque élément de pathsegments peut soit être une chaîne de caractères représentant un segment de chemin, un objet implémentant l’interface os.PathLike qui renvoie une chaîne de caractères, soit un autre objet chemin :

>>> PurePath('foo', 'some/path', 'bar')
PurePosixPath('foo/some/path/bar')
>>> PurePath(Path('foo'), Path('bar'))
PurePosixPath('foo/bar')

Quand pathsegments est vide, le dossier courant est utilisé :

>>> PurePath()
PurePosixPath('.')

Quand plusieurs chemins absolus sont fournis, le dernier est pris comme ancre (recopiant le comportement de os.path.join()) :

>>> PurePath('/etc', '/usr', 'lib64')
PurePosixPath('/usr/lib64')
>>> PureWindowsPath('c:/Windows', 'd:bar')
PureWindowsPath('d:bar')

Cependant, dans un chemin Windows, changer la racine locale ne supprime pas la précédente configuration de lecteur :

>>> PureWindowsPath('c:/Windows', '/Program Files')
PureWindowsPath('c:/Program Files')

Les points et slashs malencontreux sont supprimés, mais les doubles points ('..') ne le sont pas, puisque cela changerait la signification du chemin dans le cas de liens symboliques :

>>> PurePath('foo//bar')
PurePosixPath('foo/bar')
>>> PurePath('foo/./bar')
PurePosixPath('foo/bar')
>>> PurePath('foo/../bar')
PurePosixPath('foo/../bar')

(une analyse naïve considérerait PurePosixPath('foo/../bar') équivalent à PurePosixPath('bar'), ce qui est faux si foo est un lien symbolique vers un autre dossier)

Les objets chemins purs implémentent l’interface os.PathLike, leur permettant d’être utilisés n’importe où l’interface est acceptée.

Modifié dans la version 3.6: Ajout de la gestion de l’interface os.PathLike.

class pathlib.PurePosixPath(*pathsegments)

Une sous-classe de PurePath, cette famille de chemin représente les chemins de systèmes de fichiers en dehors des chemins Windows :

>>> PurePosixPath('/etc')
PurePosixPath('/etc')

pathsegments est spécifié de manière similaire à PurePath.

class pathlib.PureWindowsPath(*pathsegments)

Une sous-classe de PurePath, cette famille de chemin représente les chemins de systèmes de fichiers Windows :

>>> PureWindowsPath('c:/Program Files/')
PureWindowsPath('c:/Program Files')

pathsegments est spécifié de manière similaire à PurePath.

Sans tenir compte du système sur lequel vous êtes, vous pouvez instancier toutes ces classes, puisqu’elles ne fournissent aucune opération qui appelle le système d’exploitation.

11.1.2.1. Propriétés générales

Les chemins sont immuables et hachables. Les chemins d’une même famille sont comparables et ordonnables. Ces propriétés respectent l’ordre lexicographique défini par la famille :

>>> PurePosixPath('foo') == PurePosixPath('FOO')
False
>>> PureWindowsPath('foo') == PureWindowsPath('FOO')
True
>>> PureWindowsPath('FOO') in { PureWindowsPath('foo') }
True
>>> PureWindowsPath('C:') < PureWindowsPath('d:')
True

Les chemins de différentes familles ne sont pas égaux et ne peuvent être ordonnés :

>>> PureWindowsPath('foo') == PurePosixPath('foo')
False
>>> PureWindowsPath('foo') < PurePosixPath('foo')
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: '<' not supported between instances of 'PureWindowsPath' and 'PurePosixPath'

11.1.2.2. Opérateurs

L’opérateur slash aide à créer les chemins enfants, de manière similaire à os.path.join() :

>>> p = PurePath('/etc')
>>> p
PurePosixPath('/etc')
>>> p / 'init.d' / 'apache2'
PurePosixPath('/etc/init.d/apache2')
>>> q = PurePath('bin')
>>> '/usr' / q
PurePosixPath('/usr/bin')

Un objet chemin peut être utilisé n’importe où un objet implémentant os.PathLike est accepté :

>>> import os
>>> p = PurePath('/etc')
>>> os.fspath(p)
'/etc'

La représentation d’un chemin en chaîne de caractères est celle du chemin brut du système de fichiers lui-même (dans sa forme native, i.e. avec des antislashs sous Windows), et que vous pouvez passer à n’importe quelle fonction prenant un chemin en tant que chaîne de caractères :

>>> p = PurePath('/etc')
>>> str(p)
'/etc'
>>> p = PureWindowsPath('c:/Program Files')
>>> str(p)
'c:\\Program Files'

De manière similaire, appeler bytes sur un chemin donne le chemin brut du système de fichiers en tant que bytes, tel qu’encodé par os.fsencode() :

>>> bytes(p)
b'/etc'

Note

Appeler bytes est seulement recommandé sous Unix. Sous Windows, la forme Unicode est la représentation canonique des chemins du système de fichiers.

11.1.2.3. Accéder aux parties individuelles

Pour accéder aux parties individuelles (composantes) d’un chemin, utilisez les propriétés suivantes :

PurePath.parts

Un tuple donnant accès aux différentes composantes du chemin :

>>> p = PurePath('/usr/bin/python3')
>>> p.parts
('/', 'usr', 'bin', 'python3')

>>> p = PureWindowsPath('c:/Program Files/PSF')
>>> p.parts
('c:\\', 'Program Files', 'PSF')

(notez comme le lecteur et la racine locale sont regroupés en une seule partie)

11.1.2.4. Méthodes et propriétés

Les chemins purs fournissent les méthodes et propriétés suivantes :

PurePath.drive

Une chaîne représentant la lettre du lecteur ou le nom, s’il y en a un :

>>> PureWindowsPath('c:/Program Files/').drive
'c:'
>>> PureWindowsPath('/Program Files/').drive
''
>>> PurePosixPath('/etc').drive
''

Les partages UNC sont aussi considérés comme des lecteurs :

>>> PureWindowsPath('//host/share/foo.txt').drive
'\\\\host\\share'

PurePath.root

Une chaîne de caractères représentant la racine (locale ou globale), s’il y en a une :

>>> PureWindowsPath('c:/Program Files/').root
'\\'
>>> PureWindowsPath('c:Program Files/').root
''
>>> PurePosixPath('/etc').root
'/'

Les partages UNC ont toujours une racine :

>>> PureWindowsPath('//host/share').root
'\\'

PurePath.anchor

La concaténation du lecteur et de la racine :

>>> PureWindowsPath('c:/Program Files/').anchor
'c:\\'
>>> PureWindowsPath('c:Program Files/').anchor
'c:'
>>> PurePosixPath('/etc').anchor
'/'
>>> PureWindowsPath('//host/share').anchor
'\\\\host\\share\\'

PurePath.parents

Une séquence immuable fournissant accès aux ancêtres logiques du chemin :

>>> p = PureWindowsPath('c:/foo/bar/setup.py')
>>> p.parents[0]
PureWindowsPath('c:/foo/bar')
>>> p.parents[1]
PureWindowsPath('c:/foo')
>>> p.parents[2]
PureWindowsPath('c:/')

PurePath.parent

Le parent logique du chemin :

>>> p = PurePosixPath('/a/b/c/d')
>>> p.parent
PurePosixPath('/a/b/c')

Vous ne pouvez pas aller au-delà d’une ancre, ou d’un chemin vide :

>>> p = PurePosixPath('/')
>>> p.parent
PurePosixPath('/')
>>> p = PurePosixPath('.')
>>> p.parent
PurePosixPath('.')

Note

C’est une opération purement lexicale, d’où le comportement suivant :

>>> p = PurePosixPath('foo/..')
>>> p.parent
PurePosixPath('foo')

Si vous voulez parcourir un chemin arbitraire du système de fichiers, il est recommandé de d’abord appeler Path.resolve() de manière à résoudre les liens symboliques et éliminer les composantes « .. ».

PurePath.name

Une chaîne représentant la composante finale du chemin, en excluant le lecteur et la racine, si présent :

>>> PurePosixPath('my/library/setup.py').name
'setup.py'

Les noms de lecteur UNC ne sont pas pris en compte :

>>> PureWindowsPath('//some/share/setup.py').name
'setup.py'
>>> PureWindowsPath('//some/share').name
''

PurePath.suffix

L’extension du fichier de la composante finale, si présente :

>>> PurePosixPath('my/library/setup.py').suffix
'.py'
>>> PurePosixPath('my/library.tar.gz').suffix
'.gz'
>>> PurePosixPath('my/library').suffix
''

PurePath.suffixes

Une liste des extensions du chemin de fichier :

>>> PurePosixPath('my/library.tar.gar').suffixes
['.tar', '.gar']
>>> PurePosixPath('my/library.tar.gz').suffixes
['.tar', '.gz']
>>> PurePosixPath('my/library').suffixes
[]

PurePath.stem

La composante finale du chemin, sans son suffixe :

>>> PurePosixPath('my/library.tar.gz').stem
'library.tar'
>>> PurePosixPath('my/library.tar').stem
'library'
>>> PurePosixPath('my/library').stem
'library'

PurePath.as_posix()

Renvoie une représentation en chaîne de caractères du chemin avec des slashs (/) :

>>> p = PureWindowsPath('c:\\windows')
>>> str(p)
'c:\\windows'
>>> p.as_posix()
'c:/windows'

PurePath.as_uri()

Représente le chemin en tant qu’URI de fichier. ValueError est levée si le chemin n’est pas absolu.

>>> p = PurePosixPath('/etc/passwd')
>>> p.as_uri()
'file:///etc/passwd'
>>> p = PureWindowsPath('c:/Windows')
>>> p.as_uri()
'file:///c:/Windows'

PurePath.is_absolute()

Renvoie si le chemin est absolu ou non. Un chemin est considéré absolu s’il a une racine et un lecteur (si la famille le permet) :

>>> PurePosixPath('/a/b').is_absolute()
True
>>> PurePosixPath('a/b').is_absolute()
False

>>> PureWindowsPath('c:/a/b').is_absolute()
True
>>> PureWindowsPath('/a/b').is_absolute()
False
>>> PureWindowsPath('c:').is_absolute()
False
>>> PureWindowsPath('//some/share').is_absolute()
True

PurePath.is_reserved()

Avec PureWindowsPath, renvoie True si le chemin est considéré réservé sous Windows, False sinon. Avec PurePosixPath, False est systématiquement renvoyé.

>>> PureWindowsPath('nul').is_reserved()
True
>>> PurePosixPath('nul').is_reserved()
False

Les appels au système de fichier sur des chemins réservés peuvent échouer mystérieusement ou avoir des effets inattendus.

PurePath.joinpath(*other)

Appeler cette méthode équivaut à combiner le chemin avec chacun des arguments other :

>>> PurePosixPath('/etc').joinpath('passwd')
PurePosixPath('/etc/passwd')
>>> PurePosixPath('/etc').joinpath(PurePosixPath('passwd'))
PurePosixPath('/etc/passwd')
>>> PurePosixPath('/etc').joinpath('init.d', 'apache2')
PurePosixPath('/etc/init.d/apache2')
>>> PureWindowsPath('c:').joinpath('/Program Files')
PureWindowsPath('c:/Program Files')

PurePath.match(pattern)

Fait correspondre ce chemin avec le motif (glob pattern) fourni. Renvoie True si la correspondance a réussi, False sinon.

Si pattern est relatif, le chemin peut être soit relatif, soit absolu, et la correspondance est faite à partir de la droite :

>>> PurePath('a/b.py').match('*.py')
True
>>> PurePath('/a/b/c.py').match('b/*.py')
True
>>> PurePath('/a/b/c.py').match('a/*.py')
False

Si pattern est absolu, le chemin doit être absolu, et la correspondance doit être totale avec le chemin :

>>> PurePath('/a.py').match('/*.py')
True
>>> PurePath('a/b.py').match('/*.py')
False

Comme avec les autres méthodes, la casse est prise en compte :

>>> PureWindowsPath('b.py').match('*.PY')
True

PurePath.relative_to(*other)

Calcule une version du chemin en relatif au chemin représenté par other. Si c’est impossible, ValueError est levée :

>>> p = PurePosixPath('/etc/passwd')
>>> p.relative_to('/')
PurePosixPath('etc/passwd')
>>> p.relative_to('/etc')
PurePosixPath('passwd')
>>> p.relative_to('/usr')
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "pathlib.py", line 694, in relative_to
    .format(str(self), str(formatted)))
ValueError: '/etc/passwd' does not start with '/usr'

PurePath.with_name(name)

Renvoie un nouveau chemin avec name changé. Si le chemin original n’a pas de nom, ValueError est levée :

>>> p = PureWindowsPath('c:/Downloads/pathlib.tar.gz')
>>> p.with_name('setup.py')
PureWindowsPath('c:/Downloads/setup.py')
>>> p = PureWindowsPath('c:/')
>>> p.with_name('setup.py')
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/home/antoine/cpython/default/Lib/pathlib.py", line 751, in with_name
    raise ValueError("%r has an empty name" % (self,))
ValueError: PureWindowsPath('c:/') has an empty name

PurePath.with_suffix(suffix)

Return a new path with the suffix changed. If the original path doesn’t have a suffix, the new suffix is appended instead. If the suffix is an empty string, the original suffix is removed:

>>> p = PureWindowsPath('c:/Downloads/pathlib.tar.gz')
>>> p.with_suffix('.bz2')
PureWindowsPath('c:/Downloads/pathlib.tar.bz2')
>>> p = PureWindowsPath('README')
>>> p.with_suffix('.txt')
PureWindowsPath('README.txt')
>>> p = PureWindowsPath('README.txt')
>>> p.with_suffix('')
PureWindowsPath('README')

11.1.3. Chemins concrets

Les chemins concrets sont des sous-classes des chemins purs. En plus des opérations fournies par ces derniers, ils fournissent aussi des méthodes pour faire appel au système sur des objets chemin. Il y a trois façons d’instancier des chemins concrets :

class pathlib.Path(*pathsegments)

Une sous-classe de PurePath, cette classe représente les chemins concrets d’une famille de chemins de système de fichiers (l’instancier créé soit un PosixPath, soit un WindowsPath) :

>>> Path('setup.py')
PosixPath('setup.py')

pathsegments est spécifié de manière similaire à PurePath.

class pathlib.PosixPath(*pathsegments)

Une sous-classe de Path et PurePosixPath, cette classe représente les chemins concrets de systèmes de fichiers non Windows :

>>> PosixPath('/etc')
PosixPath('/etc')

pathsegments est spécifié de manière similaire à PurePath.

class pathlib.WindowsPath(*pathsegments)

Une sous-classe de Path et PureWindowsPath, cette classe représente les chemins concrets de systèmes de fichiers Windows :

>>> WindowsPath('c:/Program Files/')
WindowsPath('c:/Program Files')

pathsegments est spécifié de manière similaire à PurePath.

Vous ne pouvez instancier la classe de la famille qui correspond à votre système (permettre des appels au système pour des familles de chemins non compatible pourrait mener à des bogues ou à des pannes de votre application) :

>>> import os
>>> os.name
'posix'
>>> Path('setup.py')
PosixPath('setup.py')
>>> PosixPath('setup.py')
PosixPath('setup.py')
>>> WindowsPath('setup.py')
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "pathlib.py", line 798, in __new__
    % (cls.__name__,))
NotImplementedError: cannot instantiate 'WindowsPath' on your system

11.1.3.1. Méthodes

Les chemins concrets fournissent les méthodes suivantes en plus des méthodes des chemins purs. Beaucoup de ces méthodes peuvent lever OSError si un appel au système échoue (par exemple car le chemin n’existe pas) :

classmethod Path.cwd()

Renvoie un nouveau chemin représentant le dossier courant (comme renvoyé par os.getcwd()) :

>>> Path.cwd()
PosixPath('/home/antoine/pathlib')

classmethod Path.home()

Renvoie un nouveau chemin représentant le dossier d’accueil de l’utilisateur (comme renvoyé par os.path.expanduser() avec la construction ~ ) :

>>> Path.home()
PosixPath('/home/antoine')

Nouveau dans la version 3.5.

Path.stat()

Renvoie les informations à propos de ce chemin (de manière similaire à os.stat()). Le résultat est récupéré à chaque appel à cette méthode.

>>> p = Path('setup.py')
>>> p.stat().st_size
956
>>> p.stat().st_mtime
1327883547.852554

Path.chmod(mode)

Change le mode et les permissions du fichier, comme os.chmod() :

>>> p = Path('setup.py')
>>> p.stat().st_mode
33277
>>> p.chmod(0o444)
>>> p.stat().st_mode
33060

Path.exists()

Si le chemin pointe sur un fichier ou dossier existant :

>>> Path('.').exists()
True
>>> Path('setup.py').exists()
True
>>> Path('/etc').exists()
True
>>> Path('nonexistentfile').exists()
False

Note

Si le chemin pointe sur un lien symbolique, exists() renvoie si le lien symbolique pointe vers un fichier ou un dossier existant.

Path.expanduser()

Renvoie un nouveau chemin avec les résolutions des constructions ~ et ~user, comme retourné par os.path.expanduser() :

>>> p = PosixPath('~/films/Monty Python')
>>> p.expanduser()
PosixPath('/home/eric/films/Monty Python')

Nouveau dans la version 3.5.

Path.glob(pattern)

Globalise le pattern fourni dans le dossier représenté par ce chemin, donnant tous les fichiers correspondants (de n’importe quelle sorte) :

>>> sorted(Path('.').glob('*.py'))
[PosixPath('pathlib.py'), PosixPath('setup.py'), PosixPath('test_pathlib.py')]
>>> sorted(Path('.').glob('*/*.py'))
[PosixPath('docs/conf.py')]

Le motif « ** » signifie que « ce dossier et ses sous-dossiers, récursivement ». En d’autres mots, il active la récursivité de la globalisation :

>>> sorted(Path('.').glob('**/*.py'))
[PosixPath('build/lib/pathlib.py'),
 PosixPath('docs/conf.py'),
 PosixPath('pathlib.py'),
 PosixPath('setup.py'),
 PosixPath('test_pathlib.py')]

Note

Utiliser le motif « ** » dans de grandes arborescences de dossier peut consommer une quantité de temps démesurée.

Path.group()

Renvoie le nom du groupe auquel appartient le fichier. KeyError est levée si l’identifiant de groupe du fichier n’est pas trouvé dans la base de données système.

Path.is_dir()

Renvoie True si le chemin pointe vers un dossier (ou un lien symbolique pointant vers un dossier), False s’il pointe vers une autre sorte de fichier.

False est aussi renvoyé si le chemin n’existe pas ou est un lien symbolique cassé ; d’autres erreurs (telles que les erreurs de permission) sont propagées.

Path.is_file()

Renvoie True si le chemin pointe vers un fichier normal (ou un lien symbolique pointe vers un fichier normal), False s’il pointe vers une autre sorte de fichier.

False est aussi renvoyé si le chemin n’existe pas ou est un lien symbolique cassé ; d’autres erreurs (telles que les erreurs de permission) sont propagées.

Path.is_symlink()

Renvoie True si le chemin pointe sur un lien symbolique, False sinon.

False est aussi renvoyé si le chemin n’existe pas ; d’autres erreurs (telles que les erreurs de permission) sont propagées.

Path.is_socket()

Renvoie True si le chemin pointe vers un connecteur Unix (ou un lien symbolique pointant vers un connecteur Unix), False s’il pointe vers une autre sorte de fichier.

False est aussi renvoyé si le chemin n’existe pas ou est un lien symbolique cassé ; d’autres erreurs (telles que les erreurs de permission) sont propagées.

Path.is_fifo()

Renvoie True si le chemin pointe vers une FIFO (ou un lien symbolique pointant vers une FIFO), False s’il pointe vers une autre sorte de fichier.

False est aussi renvoyé si le chemin n’existe pas ou est un lien symbolique cassé ; d’autres erreurs (telles que les erreurs de permission) sont propagées.

Path.is_block_device()

Renvoie True si le chemin pointe vers un périphérique (ou un lien symbolique pointant vers un périphérique), False s’il pointe vers une autre sorte de fichier.

False est aussi renvoyé si le chemin n’existe pas ou est un lien symbolique cassé ; d’autres erreurs (telles que les erreurs de permission) sont propagées.

Path.is_char_device()

Renvoie True si le chemin pointe vers un périphérique à caractères (ou un lien symbolique pointant vers un périphérique à caractères), False s’il pointe vers une autre sorte de fichier.

False est aussi renvoyé si le chemin n’existe pas ou est un lien symbolique cassé ; d’autres erreurs (telles que les erreurs de permission) sont propagées.

Path.iterdir()

Quand le chemin pointe vers un dossier, donne les chemins du contenu du dossier :

>>> p = Path('docs')
>>> for child in p.iterdir(): child
...
PosixPath('docs/conf.py')
PosixPath('docs/_templates')
PosixPath('docs/make.bat')
PosixPath('docs/index.rst')
PosixPath('docs/_build')
PosixPath('docs/_static')
PosixPath('docs/Makefile')

Path.lchmod(mode)

Comme Path.chmod(), mais, si le chemin pointe vers un lien symbolique, le mode du lien symbolique est changé plutôt que celui de sa cible.

Path.lstat()

Comme Path.stat(), mais, si le chemin pointe vers un lien symbolique, renvoie les informations du lien symbolique plutôt que celui de sa cible.

Path.mkdir(mode=0o777, parents=False, exist_ok=False)

Créer un nouveau dossier au chemin fourni. Si mode est fourni, il est combiné avec la valeur de l”umask du processus pour déterminer le mode de fichier et les droits d’accès. Si le chemin existe déjà, FileExistsError est levée.

Si parents est vrai, chaque parent de ce chemin est créé si besoin ; ils sont créés avec les permissions par défaut sans prendre en compte mode (reproduisant la commande POSIX mkdir -p).

Si parents est faux (valeur par défaut), un parent manquant lève FileNotFoundError.

Si exist_ok est faux (valeur par défaut), FileExistsError est levé si le dossier cible existe déjà.

If exist_ok est vrai, les exceptions FileExistsError seront ignorées (même comportement que la commande POSIX mkdir -p), mais seulement si le dernier segment de chemin existe et n’est pas un dossier.

Modifié dans la version 3.5: Le paramètre exist_ok a été ajouté.

Path.open(mode='r', buffering=-1, encoding=None, errors=None, newline=None)

Ouvre le fichier pointé par le chemin, comme la fonction native open() le fait :

>>> p = Path('setup.py')
>>> with p.open() as f:
...     f.readline()
...
'#!/usr/bin/env python3\n'

Path.owner()

Renvoie le nom de l’utilisateur auquel appartient le fichier. KeyError est levée si l’identifiant utilisateur du fichier n’est pas trouvé dans la base de données du système.

Path.read_bytes()

Renvoie le contenu binaire du fichier pointé en tant que bytes :

>>> p = Path('my_binary_file')
>>> p.write_bytes(b'Binary file contents')
20
>>> p.read_bytes()
b'Binary file contents'

Nouveau dans la version 3.5.

Path.read_text(encoding=None, errors=None)

Renvoie le contenu décodé du fichier pointé en tant que chaîne de caractères :

>>> p = Path('my_text_file')
>>> p.write_text('Text file contents')
18
>>> p.read_text()
'Text file contents'

The file is opened and then closed. The optional parameters have the same meaning as in open().

Nouveau dans la version 3.5.

Path.rename(target)

Renomme ce fichier ou dossier vers la cible target fournie. Sur Unix, si target existe et que c’est un fichier, il sera remplacé silencieusement si l’utilisateur a la permission. target peut être soit une chaîne de caractères, soit un autre chemin :

>>> p = Path('foo')
>>> p.open('w').write('some text')
9
>>> target = Path('bar')
>>> p.rename(target)
>>> target.open().read()
'some text'

Path.replace(target)

Renomme ce fichier ou dossier vers la cible target fournie. Si target pointe sur un fichier ou un dossier existant, il sera remplacé de manière inconditionnelle.

Path.resolve(strict=False)

Rend le chemin absolu, résolvant les liens symboliques. Un nouveau chemin est renvoyé :

>>> p = Path()
>>> p
PosixPath('.')
>>> p.resolve()
PosixPath('/home/antoine/pathlib')

Les composantes « .. » sont aussi éliminées (c’est la seule méthode pour le faire) :

>>> p = Path('docs/../setup.py')
>>> p.resolve()
PosixPath('/home/antoine/pathlib/setup.py')

Si le chemin n’existe pas et que strict est True, FileNotFoundError est levée. Si strict est False, le chemin est résolu aussi loin que possible et le reste potentiel est ajouté à la fin sans vérifier s’il existe. Si une boucle infinie est rencontrée lors de la résolution du chemin, RuntimeError est levée.

Nouveau dans la version 3.6: L’argument strict.

Path.rglob(pattern)

This is like calling Path.glob() with « ** » added in front of the given pattern:

>>> sorted(Path().rglob("*.py"))
[PosixPath('build/lib/pathlib.py'),
 PosixPath('docs/conf.py'),
 PosixPath('pathlib.py'),
 PosixPath('setup.py'),
 PosixPath('test_pathlib.py')]

Path.rmdir()

Supprime ce dossier. Le dossier doit être vide.

Path.samefile(other_path)

Renvoie si ce chemin pointe vers le même fichier que other_path, qui peut être soit un chemin, soit une chaîne de caractères. La sémantique est similaire à os.path.samefile() et os.path.samestat().

OSError peut être levée si l’un des fichiers ne peut être accédé pour quelque raison.

>>> p = Path('spam')
>>> q = Path('eggs')
>>> p.samefile(q)
False
>>> p.samefile('spam')
True

Nouveau dans la version 3.5.

Path.symlink_to(target, target_is_directory=False)

Fait de ce chemin un lien symbolique vers target. Sous Windows, target_is_directory doit être vrai (la valeur par défaut étant False) si la cible du lien est un dossier. Sous POSIX, la valeur de target_is_directory est ignorée.

>>> p = Path('mylink')
>>> p.symlink_to('setup.py')
>>> p.resolve()
PosixPath('/home/antoine/pathlib/setup.py')
>>> p.stat().st_size
956
>>> p.lstat().st_size
8

Note

L’ordre des arguments (lien, cible) est l’opposé de ceux de os.symlink().

Path.touch(mode=0o666, exist_ok=True)

Créer un fichier au chemin donné. Si mode est fourni, il est combiné avec la valeur de l”umask du processus pour déterminer le mode du fichier et les drapeaux d’accès. Si le fichier existe déjà, la fonction réussit si exist_ok est vrai (et si l’heure de modification est mise à jour avec l’heure courante), sinon FileExistsError est levée.

Path.unlink()

Supprime ce fichier ou lien symbolique. Si le chemin pointe vers un dossier, utilisez Path.rmdir() à la place.

Path.write_bytes(data)

Ouvre le fichier pointé en mode binaire, écrit data dedans, et ferme le fichier :

>>> p = Path('my_binary_file')
>>> p.write_bytes(b'Binary file contents')
20
>>> p.read_bytes()
b'Binary file contents'

Le fichier du même nom, s’il existe, est écrasé.

Nouveau dans la version 3.5.

Path.write_text(data, encoding=None, errors=None)

Ouvre le fichier pointé en mode texte, écrit data dedans, et ferme le fichier :

>>> p = Path('my_text_file')
>>> p.write_text('Text file contents')
18
>>> p.read_text()
'Text file contents'

Nouveau dans la version 3.5.

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11.2. os.path — manipulation courante des chemins

Code source : Lib/posixpath.py [https://github.com/python/cpython/tree/3.6/Lib/posixpath.py] (pour POSIX), Lib/ntpath.py [https://github.com/python/cpython/tree/3.6/Lib/ntpath.py] (pour Windows NT), et Lib/macpath.py [https://github.com/python/cpython/tree/3.6/Lib/macpath.py] (pour Macintosh)

Ce module implémente certaines fonctions utiles sur le nom des chemins. Pour lire ou écrire des fichiers, voir open(), et pour accéder au système de fichier, voir le module os. Les paramètres de chemin d’accès peuvent être passés sous forme de chaînes de caractères ou de chaîne d’octets. Les programmes sont encouragés à représenter les noms de fichiers en tant que chaînes de caractères Unicode. Malheureusement, certains noms de fichiers peuvent ne pas être représentés sous forme de chaînes de caractères sous UNIX, ainsi, les programmes qui doivent prendre en charge les noms de fichiers arbitraires sur UNIX doivent utiliser des chaînes d’octets pour représenter leurs chemins d’accès. Inversement, l’utilisation de chaîne d’octets ne peut pas représenter tous les noms de fichiers sous Windows (dans le codage mbcs standard), par conséquent les applications Windows doivent utiliser des chaînes de caractères Unicode pour accéder à tous les fichiers.

Contrairement à une invite de commandes Unix, Python ne fait aucune extension de chemin automatique. Des fonctions telles que expanduser() et expandvars() peuvent être appelées explicitement lorsqu’une application souhaite une extension de chemin semblable à celui d’une invite de commande (voir aussi le module glob).

Voir aussi

Le module pathlib offre une représentation objet de haut niveau des chemins.

Note

Toutes ces fonctions n’acceptent que des chaînes d’octets ou des chaînes de caractères en tant que paramètres. Le résultat est un objet du même type si un chemin ou un nom de fichier est renvoyé.

Note

Comme les différents systèmes d’exploitation ont des conventions de noms de chemins différentes, il existe plusieurs versions de ce module dans la bibliothèque standard. Le module os.path est toujours le module de chemin adapté au système d’exploitation sur lequel Python tourne, et donc adapté pour les chemins locaux. Cependant, vous pouvez également importer et utiliser les modules individuels si vous voulez manipuler un chemin qui est toujours dans l’un des différents formats. Ils ont tous la même interface :

posixpath pour les chemins de type UNIX

ntpath pour les chemins Windows

macpath pour l’ancienne forme des chemins MacOS

os.path.abspath(path)

Renvoie une version absolue et normalisée du chemin d’accès path. Sur la plupart des plates-formes, cela équivaut à appeler la fonction normpath() comme suit : normpath(join(os.getcwd(), chemin))`.

Modifié dans la version 3.6: Accepte un path-like object.

os.path.basename(path)

Renvoie le nom de base du chemin d’accès path. C’est le second élément de la paire renvoyée en passant path à la fonction split(). Notez que le résultat de cette fonction est différent de celui du programme Unix basename ; là où basename pour '/foo/bar/' renvoie 'bar', la fonction basename() renvoie une chaîne vide ('').

Modifié dans la version 3.6: Accepte un path-like object.

os.path.commonpath(paths)

Return the longest common sub-path of each pathname in the sequence paths. Raise ValueError if paths contains both absolute and relative pathnames, or if paths is empty. Unlike commonprefix(), this returns a valid path.

Disponibilité Unix, Windows

Nouveau dans la version 3.5.

Modifié dans la version 3.6: Accepts a sequence of path-like objects.

os.path.commonprefix(list)

Return the longest path prefix (taken character-by-character) that is a prefix of all paths in list. If list is empty, return the empty string ('').

Note

This function may return invalid paths because it works a character at a time. To obtain a valid path, see commonpath().

>>> os.path.commonprefix(['/usr/lib', '/usr/local/lib'])
'/usr/l'

>>> os.path.commonpath(['/usr/lib', '/usr/local/lib'])
'/usr'

Modifié dans la version 3.6: Accepte un path-like object.

os.path.dirname(path)

Return the directory name of pathname path. This is the first element of the pair returned by passing path to the function split().

Modifié dans la version 3.6: Accepte un path-like object.

os.path.exists(path)

Return True if path refers to an existing path or an open file descriptor. Returns False for broken symbolic links. On some platforms, this function may return False if permission is not granted to execute os.stat() on the requested file, even if the path physically exists.

Modifié dans la version 3.3: path can now be an integer: True is returned if it is an open file descriptor, False otherwise.

Modifié dans la version 3.6: Accepte un path-like object.

os.path.lexists(path)

Return True if path refers to an existing path. Returns True for broken symbolic links. Equivalent to exists() on platforms lacking os.lstat().

Modifié dans la version 3.6: Accepte un path-like object.

os.path.expanduser(path)

On Unix and Windows, return the argument with an initial component of ~ or ~user replaced by that user’s home directory.

On Unix, an initial ~ is replaced by the environment variable HOME if it is set; otherwise the current user’s home directory is looked up in the password directory through the built-in module pwd. An initial ~user is looked up directly in the password directory.

On Windows, HOME and USERPROFILE will be used if set, otherwise a combination of HOMEPATH and HOMEDRIVE will be used. An initial ~user is handled by stripping the last directory component from the created user path derived above.

If the expansion fails or if the path does not begin with a tilde, the path is returned unchanged.

Modifié dans la version 3.6: Accepte un path-like object.

os.path.expandvars(path)

Return the argument with environment variables expanded. Substrings of the form $name or ${name} are replaced by the value of environment variable name. Malformed variable names and references to non-existing variables are left unchanged.

On Windows, %name% expansions are supported in addition to $name and ${name}.

Modifié dans la version 3.6: Accepte un path-like object.

os.path.getatime(path)

Return the time of last access of path. The return value is a number giving the number of seconds since the epoch (see the time module). Raise OSError if the file does not exist or is inaccessible.

If os.stat_float_times() returns True, the result is a floating point number.

os.path.getmtime(path)

Return the time of last modification of path. The return value is a number giving the number of seconds since the epoch (see the time module). Raise OSError if the file does not exist or is inaccessible.

If os.stat_float_times() returns True, the result is a floating point number.

Modifié dans la version 3.6: Accepte un path-like object.

os.path.getctime(path)

Return the system’s ctime which, on some systems (like Unix) is the time of the last metadata change, and, on others (like Windows), is the creation time for path. The return value is a number giving the number of seconds since the epoch (see the time module). Raise OSError if the file does not exist or is inaccessible.

Modifié dans la version 3.6: Accepte un path-like object.

os.path.getsize(path)

Return the size, in bytes, of path. Raise OSError if the file does not exist or is inaccessible.

Modifié dans la version 3.6: Accepte un path-like object.

os.path.isabs(path)

Return True if path is an absolute pathname. On Unix, that means it begins with a slash, on Windows that it begins with a (back)slash after chopping off a potential drive letter.

Modifié dans la version 3.6: Accepte un path-like object.

os.path.isfile(path)

Return True if path is an existing regular file. This follows symbolic links, so both islink() and isfile() can be true for the same path.

Modifié dans la version 3.6: Accepte un path-like object.

os.path.isdir(path)

Return True if path is an existing directory. This follows symbolic links, so both islink() and isdir() can be true for the same path.

Modifié dans la version 3.6: Accepte un path-like object.

os.path.islink(path)

Return True if path refers to an existing directory entry that is a symbolic link. Always False if symbolic links are not supported by the Python runtime.

Modifié dans la version 3.6: Accepte un path-like object.

os.path.ismount(path)

Return True if pathname path is a mount point: a point in a file system where a different file system has been mounted. On POSIX, the function checks whether path’s parent, path/.., is on a different device than path, or whether path/.. and path point to the same i-node on the same device — this should detect mount points for all Unix and POSIX variants. On Windows, a drive letter root and a share UNC are always mount points, and for any other path GetVolumePathName is called to see if it is different from the input path.

Nouveau dans la version 3.4: Support for detecting non-root mount points on Windows.

Modifié dans la version 3.6: Accepte un path-like object.

os.path.join(path, *paths)

Join one or more path components intelligently. The return value is the concatenation of path and any members of *paths with exactly one directory separator (os.sep) following each non-empty part except the last, meaning that the result will only end in a separator if the last part is empty. If a component is an absolute path, all previous components are thrown away and joining continues from the absolute path component.

On Windows, the drive letter is not reset when an absolute path component (e.g., r'\foo') is encountered. If a component contains a drive letter, all previous components are thrown away and the drive letter is reset. Note that since there is a current directory for each drive, os.path.join("c:", "foo") represents a path relative to the current directory on drive C: (c:foo), not c:\foo.

Modifié dans la version 3.6: Accepts a path-like object for path and paths.

os.path.normcase(path)

Normalize the case of a pathname. On Unix and Mac OS X, this returns the path unchanged; on case-insensitive filesystems, it converts the path to lowercase. On Windows, it also converts forward slashes to backward slashes. Raise a TypeError if the type of path is not str or bytes (directly or indirectly through the os.PathLike interface).

Modifié dans la version 3.6: Accepte un path-like object.

os.path.normpath(path)

Normalize a pathname by collapsing redundant separators and up-level references so that A//B, A/B/, A/./B and A/foo/../B all become A/B. This string manipulation may change the meaning of a path that contains symbolic links. On Windows, it converts forward slashes to backward slashes. To normalize case, use normcase().

Modifié dans la version 3.6: Accepte un path-like object.

os.path.realpath(path)

Return the canonical path of the specified filename, eliminating any symbolic links encountered in the path (if they are supported by the operating system).

Modifié dans la version 3.6: Accepte un path-like object.

os.path.relpath(path, start=os.curdir)

Return a relative filepath to path either from the current directory or from an optional start directory. This is a path computation: the filesystem is not accessed to confirm the existence or nature of path or start.

start defaults to os.curdir.

Disponibilité : Unix, Windows.

Modifié dans la version 3.6: Accepte un path-like object.

os.path.samefile(path1, path2)

Return True if both pathname arguments refer to the same file or directory. This is determined by the device number and i-node number and raises an exception if an os.stat() call on either pathname fails.

Disponibilité : Unix, Windows.

Modifié dans la version 3.2: Prise en charge de Windows.

Modifié dans la version 3.4: Windows now uses the same implementation as all other platforms.

Modifié dans la version 3.6: Accepte un path-like object.

os.path.sameopenfile(fp1, fp2)

Return True if the file descriptors fp1 and fp2 refer to the same file.

Disponibilité : Unix, Windows.

Modifié dans la version 3.2: Prise en charge de Windows.

Modifié dans la version 3.6: Accepte un path-like object.

os.path.samestat(stat1, stat2)

Return True if the stat tuples stat1 and stat2 refer to the same file. These structures may have been returned by os.fstat(), os.lstat(), or os.stat(). This function implements the underlying comparison used by samefile() and sameopenfile().

Disponibilité : Unix, Windows.

Modifié dans la version 3.4: Prise en charge de Windows.

Modifié dans la version 3.6: Accepte un path-like object.

os.path.split(path)

Split the pathname path into a pair, (head, tail) where tail is the last pathname component and head is everything leading up to that. The tail part will never contain a slash; if path ends in a slash, tail will be empty. If there is no slash in path, head will be empty. If path is empty, both head and tail are empty. Trailing slashes are stripped from head unless it is the root (one or more slashes only). In all cases, join(head, tail) returns a path to the same location as path (but the strings may differ). Also see the functions dirname() and basename().

Modifié dans la version 3.6: Accepte un path-like object.

os.path.splitdrive(path)

Split the pathname path into a pair (drive, tail) where drive is either a mount point or the empty string. On systems which do not use drive specifications, drive will always be the empty string. In all cases, drive + tail will be the same as path.

On Windows, splits a pathname into drive/UNC sharepoint and relative path.

If the path contains a drive letter, drive will contain everything up to and including the colon. e.g. splitdrive("c:/dir") returns ("c:", "/dir")

If the path contains a UNC path, drive will contain the host name and share, up to but not including the fourth separator. e.g. splitdrive("//host/computer/dir") returns ("//host/computer", "/dir")

Modifié dans la version 3.6: Accepte un path-like object.

os.path.splitext(path)

Split the pathname path into a pair (root, ext) such that root + ext == path, and ext is empty or begins with a period and contains at most one period. Leading periods on the basename are ignored; splitext('.cshrc') returns ('.cshrc', '').

Modifié dans la version 3.6: Accepte un path-like object.

os.path.splitunc(path)

Obsolète depuis la version 3.1: Use splitdrive instead.

Split the pathname path into a pair (unc, rest) so that unc is the UNC mount point (such as r'\\host\mount'), if present, and rest the rest of the path (such as r'\path\file.ext'). For paths containing drive letters, unc will always be the empty string.

Disponibilité : Windows.

os.path.supports_unicode_filenames

True if arbitrary Unicode strings can be used as file names (within limitations imposed by the file system).

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11.3. fileinput — Iterate over lines from multiple input streams

Code source : Lib/fileinput.py [https://github.com/python/cpython/tree/3.6/Lib/fileinput.py]

This module implements a helper class and functions to quickly write a loop over standard input or a list of files. If you just want to read or write one file see open().

The typical use is:

import fileinput
for line in fileinput.input():
    process(line)

This iterates over the lines of all files listed in sys.argv[1:], defaulting to sys.stdin if the list is empty. If a filename is '-', it is also replaced by sys.stdin. To specify an alternative list of filenames, pass it as the first argument to input(). A single file name is also allowed.

All files are opened in text mode by default, but you can override this by specifying the mode parameter in the call to input() or FileInput. If an I/O error occurs during opening or reading a file, OSError is raised.

Modifié dans la version 3.3: IOError used to be raised; it is now an alias of OSError.

If sys.stdin is used more than once, the second and further use will return no lines, except perhaps for interactive use, or if it has been explicitly reset (e.g. using sys.stdin.seek(0)).

Empty files are opened and immediately closed; the only time their presence in the list of filenames is noticeable at all is when the last file opened is empty.

Lines are returned with any newlines intact, which means that the last line in a file may not have one.

You can control how files are opened by providing an opening hook via the openhook parameter to fileinput.input() or FileInput(). The hook must be a function that takes two arguments, filename and mode, and returns an accordingly opened file-like object. Two useful hooks are already provided by this module.

The following function is the primary interface of this module:

fileinput.input(files=None, inplace=False, backup='', bufsize=0, mode='r', openhook=None)

Create an instance of the FileInput class. The instance will be used as global state for the functions of this module, and is also returned to use during iteration. The parameters to this function will be passed along to the constructor of the FileInput class.

The FileInput instance can be used as a context manager in the with statement. In this example, input is closed after the with statement is exited, even if an exception occurs:

with fileinput.input(files=('spam.txt', 'eggs.txt')) as f:
    for line in f:
        process(line)

Modifié dans la version 3.2: Can be used as a context manager.

Deprecated since version 3.6, will be removed in version 3.8: The bufsize parameter.

The following functions use the global state created by fileinput.input(); if there is no active state, RuntimeError is raised.

fileinput.filename()

Return the name of the file currently being read. Before the first line has been read, returns None.

fileinput.fileno()

Return the integer « file descriptor » for the current file. When no file is opened (before the first line and between files), returns -1.

fileinput.lineno()

Return the cumulative line number of the line that has just been read. Before the first line has been read, returns 0. After the last line of the last file has been read, returns the line number of that line.

fileinput.filelineno()

Return the line number in the current file. Before the first line has been read, returns 0. After the last line of the last file has been read, returns the line number of that line within the file.

fileinput.isfirstline()

Returns true if the line just read is the first line of its file, otherwise returns false.

fileinput.isstdin()

Returns true if the last line was read from sys.stdin, otherwise returns false.

fileinput.nextfile()

Close the current file so that the next iteration will read the first line from the next file (if any); lines not read from the file will not count towards the cumulative line count. The filename is not changed until after the first line of the next file has been read. Before the first line has been read, this function has no effect; it cannot be used to skip the first file. After the last line of the last file has been read, this function has no effect.

fileinput.close()

Close the sequence.

The class which implements the sequence behavior provided by the module is available for subclassing as well:

class fileinput.FileInput(files=None, inplace=False, backup='', bufsize=0, mode='r', openhook=None)

Class FileInput is the implementation; its methods filename(), fileno(), lineno(), filelineno(), isfirstline(), isstdin(), nextfile() and close() correspond to the functions of the same name in the module. In addition it has a readline() method which returns the next input line, and a __getitem__() method which implements the sequence behavior. The sequence must be accessed in strictly sequential order; random access and readline() cannot be mixed.

With mode you can specify which file mode will be passed to open(). It must be one of 'r', 'rU', 'U' and 'rb'.

The openhook, when given, must be a function that takes two arguments, filename and mode, and returns an accordingly opened file-like object. You cannot use inplace and openhook together.

A FileInput instance can be used as a context manager in the with statement. In this example, input is closed after the with statement is exited, even if an exception occurs:

with FileInput(files=('spam.txt', 'eggs.txt')) as input:
    process(input)

Modifié dans la version 3.2: Can be used as a context manager.

Obsolète depuis la version 3.4: The 'rU' and 'U' modes.

Deprecated since version 3.6, will be removed in version 3.8: The bufsize parameter.

Optional in-place filtering: if the keyword argument inplace=True is passed to fileinput.input() or to the FileInput constructor, the file is moved to a backup file and standard output is directed to the input file (if a file of the same name as the backup file already exists, it will be replaced silently). This makes it possible to write a filter that rewrites its input file in place. If the backup parameter is given (typically as backup='.<some extension>'), it specifies the extension for the backup file, and the backup file remains around; by default, the extension is '.bak' and it is deleted when the output file is closed. In-place filtering is disabled when standard input is read.

The two following opening hooks are provided by this module:

fileinput.hook_compressed(filename, mode)

Transparently opens files compressed with gzip and bzip2 (recognized by the extensions '.gz' and '.bz2') using the gzip and bz2 modules. If the filename extension is not '.gz' or '.bz2', the file is opened normally (ie, using open() without any decompression).

Usage example: fi = fileinput.FileInput(openhook=fileinput.hook_compressed)

fileinput.hook_encoded(encoding, errors=None)

Returns a hook which opens each file with open(), using the given encoding and errors to read the file.

Usage example: fi = fileinput.FileInput(openhook=fileinput.hook_encoded("utf-8", "surrogateescape"))

Modifié dans la version 3.6: Added the optional errors parameter.

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11.4. stat — Interpreting stat() results

Source code: Lib/stat.py [https://github.com/python/cpython/tree/3.6/Lib/stat.py]

The stat module defines constants and functions for interpreting the results of os.stat(), os.fstat() and os.lstat() (if they exist). For complete details about the stat(), fstat() and lstat() calls, consult the documentation for your system.

Modifié dans la version 3.4: The stat module is backed by a C implementation.

The stat module defines the following functions to test for specific file types:

stat.S_ISDIR(mode)

Return non-zero if the mode is from a directory.

stat.S_ISCHR(mode)

Return non-zero if the mode is from a character special device file.

stat.S_ISBLK(mode)

Return non-zero if the mode is from a block special device file.

stat.S_ISREG(mode)

Return non-zero if the mode is from a regular file.

stat.S_ISFIFO(mode)

Return non-zero if the mode is from a FIFO (named pipe).

stat.S_ISLNK(mode)

Return non-zero if the mode is from a symbolic link.

stat.S_ISSOCK(mode)

Return non-zero if the mode is from a socket.

stat.S_ISDOOR(mode)

Return non-zero if the mode is from a door.

Nouveau dans la version 3.4.

stat.S_ISPORT(mode)

Return non-zero if the mode is from an event port.

Nouveau dans la version 3.4.

stat.S_ISWHT(mode)

Return non-zero if the mode is from a whiteout.

Nouveau dans la version 3.4.

Two additional functions are defined for more general manipulation of the file’s mode:

stat.S_IMODE(mode)

Return the portion of the file’s mode that can be set by os.chmod()—that is, the file’s permission bits, plus the sticky bit, set-group-id, and set-user-id bits (on systems that support them).

stat.S_IFMT(mode)

Return the portion of the file’s mode that describes the file type (used by the S_IS*() functions above).

Normally, you would use the os.path.is*() functions for testing the type of a file; the functions here are useful when you are doing multiple tests of the same file and wish to avoid the overhead of the stat() system call for each test. These are also useful when checking for information about a file that isn’t handled by os.path, like the tests for block and character devices.

Exemple :

import os, sys
from stat import *

def walktree(top, callback):
    '''recursively descend the directory tree rooted at top,
       calling the callback function for each regular file'''

    for f in os.listdir(top):
        pathname = os.path.join(top, f)
        mode = os.stat(pathname).st_mode
        if S_ISDIR(mode):
            # It's a directory, recurse into it
            walktree(pathname, callback)
        elif S_ISREG(mode):
            # It's a file, call the callback function
            callback(pathname)
        else:
            # Unknown file type, print a message
            print('Skipping %s' % pathname)

def visitfile(file):
    print('visiting', file)

if __name__ == '__main__':
    walktree(sys.argv[1], visitfile)

An additional utility function is provided to convert a file’s mode in a human readable string:

stat.filemode(mode)

Convert a file’s mode to a string of the form “-rwxrwxrwx”.

Nouveau dans la version 3.3.

Modifié dans la version 3.4: The function supports S_IFDOOR, S_IFPORT and S_IFWHT.

All the variables below are simply symbolic indexes into the 10-tuple returned by os.stat(), os.fstat() or os.lstat().

stat.ST_MODE

Inode protection mode.

stat.ST_INO

Numéro d”inode.

stat.ST_DEV

Device inode resides on.

stat.ST_NLINK

Number of links to the inode.

stat.ST_UID

User id of the owner.

stat.ST_GID

Group id of the owner.

stat.ST_SIZE

Size in bytes of a plain file; amount of data waiting on some special files.

stat.ST_ATIME

Time of last access.

stat.ST_MTIME

Time of last modification.

stat.ST_CTIME

The « ctime » as reported by the operating system. On some systems (like Unix) is the time of the last metadata change, and, on others (like Windows), is the creation time (see platform documentation for details).

The interpretation of « file size » changes according to the file type. For plain files this is the size of the file in bytes. For FIFOs and sockets under most flavors of Unix (including Linux in particular), the « size » is the number of bytes waiting to be read at the time of the call to os.stat(), os.fstat(), or os.lstat(); this can sometimes be useful, especially for polling one of these special files after a non-blocking open. The meaning of the size field for other character and block devices varies more, depending on the implementation of the underlying system call.

The variables below define the flags used in the ST_MODE field.

Use of the functions above is more portable than use of the first set of flags:

stat.S_IFSOCK

Socket.

stat.S_IFLNK

Symbolic link.

stat.S_IFREG

Regular file.

stat.S_IFBLK

Block device.

stat.S_IFDIR

Dossier.

stat.S_IFCHR

Character device.

stat.S_IFIFO

FIFO.

stat.S_IFDOOR

Door.

Nouveau dans la version 3.4.

stat.S_IFPORT

Event port.

Nouveau dans la version 3.4.

stat.S_IFWHT

Whiteout.

Nouveau dans la version 3.4.

Note

S_IFDOOR, S_IFPORT or S_IFWHT are defined as 0 when the platform does not have support for the file types.

The following flags can also be used in the mode argument of os.chmod():

stat.S_ISUID

Set UID bit.

stat.S_ISGID

Set-group-ID bit. This bit has several special uses. For a directory it indicates that BSD semantics is to be used for that directory: files created there inherit their group ID from the directory, not from the effective group ID of the creating process, and directories created there will also get the S_ISGID bit set. For a file that does not have the group execution bit (S_IXGRP) set, the set-group-ID bit indicates mandatory file/record locking (see also S_ENFMT).

stat.S_ISVTX

Sticky bit. When this bit is set on a directory it means that a file in that directory can be renamed or deleted only by the owner of the file, by the owner of the directory, or by a privileged process.

stat.S_IRWXU

Mask for file owner permissions.

stat.S_IRUSR

Owner has read permission.

stat.S_IWUSR

Owner has write permission.

stat.S_IXUSR

Owner has execute permission.

stat.S_IRWXG

Mask for group permissions.

stat.S_IRGRP

Group has read permission.

stat.S_IWGRP

Group has write permission.

stat.S_IXGRP

Group has execute permission.

stat.S_IRWXO

Mask for permissions for others (not in group).

stat.S_IROTH

Others have read permission.

stat.S_IWOTH

Others have write permission.

stat.S_IXOTH

Others have execute permission.

stat.S_ENFMT

System V file locking enforcement. This flag is shared with S_ISGID: file/record locking is enforced on files that do not have the group execution bit (S_IXGRP) set.

stat.S_IREAD

Unix V7 synonym for S_IRUSR.

stat.S_IWRITE

Unix V7 synonym for S_IWUSR.

stat.S_IEXEC

Unix V7 synonym for S_IXUSR.

The following flags can be used in the flags argument of os.chflags():

stat.UF_NODUMP

Do not dump the file.

stat.UF_IMMUTABLE

The file may not be changed.

stat.UF_APPEND

The file may only be appended to.

stat.UF_OPAQUE

The directory is opaque when viewed through a union stack.

stat.UF_NOUNLINK

The file may not be renamed or deleted.

stat.UF_COMPRESSED

The file is stored compressed (Mac OS X 10.6+).

stat.UF_HIDDEN

The file should not be displayed in a GUI (Mac OS X 10.5+).

stat.SF_ARCHIVED

The file may be archived.

stat.SF_IMMUTABLE

The file may not be changed.

stat.SF_APPEND

The file may only be appended to.

stat.SF_NOUNLINK

The file may not be renamed or deleted.

stat.SF_SNAPSHOT

The file is a snapshot file.

See the *BSD or Mac OS systems man page chflags(2) for more information.

On Windows, the following file attribute constants are available for use when testing bits in the st_file_attributes member returned by os.stat(). See the Windows API documentation [https://msdn.microsoft.com/en-us/library/windows/desktop/gg258117.aspx] for more detail on the meaning of these constants.

stat.FILE_ATTRIBUTE_ARCHIVE

stat.FILE_ATTRIBUTE_COMPRESSED

stat.FILE_ATTRIBUTE_DEVICE

stat.FILE_ATTRIBUTE_DIRECTORY

stat.FILE_ATTRIBUTE_ENCRYPTED

stat.FILE_ATTRIBUTE_HIDDEN

stat.FILE_ATTRIBUTE_INTEGRITY_STREAM

stat.FILE_ATTRIBUTE_NORMAL

stat.FILE_ATTRIBUTE_NOT_CONTENT_INDEXED

stat.FILE_ATTRIBUTE_NO_SCRUB_DATA

stat.FILE_ATTRIBUTE_OFFLINE

stat.FILE_ATTRIBUTE_READONLY

stat.FILE_ATTRIBUTE_REPARSE_POINT

stat.FILE_ATTRIBUTE_SPARSE_FILE

stat.FILE_ATTRIBUTE_SYSTEM

stat.FILE_ATTRIBUTE_TEMPORARY

stat.FILE_ATTRIBUTE_VIRTUAL

Nouveau dans la version 3.5.

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11.5. filecmp – Comparaisons de fichiers et de répertoires

Code source : Lib/filecmp.py [https://github.com/python/cpython/tree/3.6/Lib/filecmp.py]

Le module filecmp définit les fonctions permettant de comparer les fichiers et les répertoires, avec différents compromis optionnels durée / exactitude. Pour comparer des fichiers, voir aussi le module difflib.

Le module filecmp définit les fonctions suivantes :

filecmp.cmp(f1, f2, shallow=True)

Compare les fichiers nommés f1 et f2 , renvoie True s’ils semblent égaux, False sinon.

Si shallow est vrai, les fichiers avec des signatures os.stat() identiques sont considérés comme égaux. Sinon, le contenu des fichiers est comparé.

Notez qu’aucun programme externe n’est appelé à partir de cette fonction, ce qui lui confère des qualités de portabilité et d’efficacité.

Cette fonction utilise un cache pour les comparaisons antérieures et les résultats, les entrées du cache étant invalidées si les informations os.stat() du fichier sont modifiées. La totalité du cache peut être effacée avec clear_cache().

filecmp.cmpfiles(dir1, dir2, common, shallow=True)

Compare les fichiers des deux répertoires dir1 et dir2 dont les noms sont donnés par common.

Renvoie trois listes de noms de fichiers : match , mismatch, errors. match contient la liste des fichiers qui correspondent, mismatch contient les noms de ceux qui ne correspondent pas et errors répertorie les noms des fichiers qui n’ont pas pu être comparés. Les fichiers sont répertoriés dans errors s’ils n’existent pas dans l’un des répertoires, si l’utilisateur ne dispose pas de l’autorisation nécessaire pour les lire ou si la comparaison n’a pas pu être effectuée pour une autre raison.

Le paramètre shallow a la même signification et la même valeur par défaut que pour filecmp.cmp().

Par exemple, cmpfiles('a', 'b', ['c', 'd/e']) compare a/c et b/c et a/d/e avec b/d/e. 'c' et 'd/e' seront chacun dans l’une des trois listes renvoyées.

filecmp.clear_cache()

Efface le cache filecmp. Cela peut être utile si un fichier est comparé juste après avoir été modifié (dans un délai inférieur à la résolution mtime du système de fichiers sous-jacent).

Nouveau dans la version 3.4.

11.5.1. La classe dircmp

class filecmp.dircmp(a, b, ignore=None, hide=None)

Construit un nouvel objet de comparaison de répertoires, pour comparer les répertoires a et b. ignore est une liste de noms à ignorer, par défaut à filecmp.DEFAULT_IGNORES. hide est une liste de noms à cacher, par défaut à [os.curdir, os.pardir].

La classe dircmp compare les fichiers en faisant des comparaisons superficielles comme décrit pour filecmp.cmp().

La classe dircmp fournit les méthodes suivantes :

report()

Affiche (sur sys.stdout) une comparaison entre a et b.

report_partial_closure()

Affiche une comparaison entre a et b et les sous-répertoires immédiats communs.

report_full_closure()

Affiche une comparaison entre a et b et les sous-répertoires communs (récursivement).

La classe dircmp offre un certain nombre d’attributs intéressants qui peuvent être utilisés pour obtenir diverses informations sur les arborescences de répertoires comparées.

Notez que, via les points d’ancrage __getattr__(), tous les attributs sont calculés de manière paresseuse. Il n’y a donc pas de pénalité en vitesse si seuls les attributs rapides à calculer sont utilisés.

left

Le répertoire a.

right

Le répertoire b.

left_list

Fichiers et sous-répertoires dans a , filtrés par hide et ignore.

right_list

Fichiers et sous-répertoires dans b , filtrés par hide et ignore.

common

Fichiers et sous-répertoires à la fois dans a et b.

left_only

Fichiers et sous-répertoires uniquement dans a.

right_only

Fichiers et sous-répertoires uniquement dans b.

common_dirs

Sous-répertoires à la fois dans a et b.

common_files

Fichiers à la fois dans a et b.

common_funny

Noms dans a et b , tels que le type diffère entre les répertoires, ou noms pour lesquels os.stat() signale une erreur.

same_files

Fichiers identiques dans a et b, en utilisant l’opérateur de comparaison de fichiers de la classe.

diff_files

Fichiers figurant à la fois dans a et dans b , dont le contenu diffère en fonction de l’opérateur de comparaison de fichiers de la classe.

funny_files

Fichiers à la fois dans a et dans b , mais ne pouvant pas être comparés.

subdirs

Un dictionnaire faisant correspondre les noms dans common_dirs vers des objets dircmp.

filecmp.DEFAULT_IGNORES

Nouveau dans la version 3.4.

Liste des répertoires ignorés par défaut par dircmp.

Voici un exemple simplifié d’utilisation de l’attribut subdirs pour effectuer une recherche récursive dans deux répertoires afin d’afficher des fichiers communs différents :

>>> from filecmp import dircmp
>>> def print_diff_files(dcmp):
...     for name in dcmp.diff_files:
...         print("diff_file %s found in %s and %s" % (name, dcmp.left,
...               dcmp.right))
...     for sub_dcmp in dcmp.subdirs.values():
...         print_diff_files(sub_dcmp)
...
>>> dcmp = dircmp('dir1', 'dir2')
>>> print_diff_files(dcmp)

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11.6. tempfile — Génération de fichiers et répertoires temporaires

Code source : Lib/tempfile.py [https://github.com/python/cpython/tree/3.6/Lib/tempfile.py]

Ce module crée des fichiers et répertoires temporaires. Il fonctionne sur toutes les plateformes supportées. TemporaryFile, NamedTemporaryFile, TemporaryDirectory, et SpooledTemporaryFile sont des interfaces haut-niveau qui fournissent un nettoyage automatique et peuvent être utilisées comme gestionnaire de contexte. mkstemp() et mkdtemp() sont des fonctions bas-niveau qui nécessitent un nettoyage manuel.

Toutes les fonctions et constructeurs appelables par l’utilisateur ont des arguments additionnels qui permettent de contrôler directement le chemin et le nom des répertoires et fichiers. Les noms de fichiers utilisés par ce module incluent une chaîne de caractères aléatoires qui leur permet d’être créés de manière sécurisée dans des répertoires temporaires partagés. Afin de maintenir la compatibilité descendante, l’ordre des arguments est quelque peu étrange ; pour des questions de clarté, il est recommandé d’utiliser les arguments nommés.

Le module définit les éléments suivants pouvant être appelés par l’utilisateur :

tempfile.TemporaryFile(mode='w+b', buffering=None, encoding=None, newline=None, suffix=None, prefix=None, dir=None)

Renvoie un objet fichier qui peut être utilisé comme une zone de stockage temporaire. Le fichier est créé de manière sécurisé, utilisant les mêmes règles que mkstemp(). Il sera détruit dès qu’il sera fermé (y compris lorsque le fichier est implicitement fermé quand il est collecté par le ramasse-miette). Sous Unix, l’entrée du répertoire n’est soit pas du tout créée, ou est supprimée immédiatement après sa création. Les autres plateformes ne gèrent pas cela, votre code ne doit pas compter sur un fichier temporaire créé en utilisant cette fonction ayant ou non un nom visible sur le système de fichier.

L’objet résultat peut être utilisé comme un gestionnaire de contexte (voir Exemples). Une fois le contexte ou la destruction de l’objet fichier terminé, le fichier temporaire sera supprimé du système de fichiers.

Le paramètre mode vaut par défaut 'w+b' afin que le fichier créé puisse être lu et écrit sans être fermé. Le mode binaire est utilisé afin que le comportement soit le même sur toutes les plateformes quelque soit la donnée qui est stockée. buffering, encoding et newline sont interprétés de la même façon que pour open().

Les paramètres dir, prefix et suffix ont la même signification et même valeur par défaut que mkstemp().

L’objet renvoyé est un véritable fichier sur les plateformes POSIX. Sur les autres plateformes, un objet fichier-compatible est retourné où l’attribut file est le véritable fichier.

L’option os.O_TMPFILE est utilisé s’il est disponible et fonctionne (Linux exclusivement, nécessite un noyau Linux 3.11 ou plus).

Modifié dans la version 3.5: L’option os.O_TMPFILE est maintenant utilisé si disponible.

tempfile.NamedTemporaryFile(mode='w+b', buffering=None, encoding=None, newline=None, suffix=None, prefix=None, dir=None, delete=True)

Cette fonction fonctionne exactement comme TemporaryFile(), à la différence qu’il est garanti que le fichier soit visible dans le système de fichier (sur Unix, l’entrée du répertoire est supprimée). Le nom peut être récupéré depuis l’attribut name de l’objet fichier-compatible retourné. Le fait que le nom puisse être utilisé pour ouvrir le fichier une seconde fois, tant que le fichier temporaire nommé est toujours ouvert, varie entre les plateformes (cela peut l’être sur Unix, mais c’est impossible sur Windows NT et plus). Si delete est vrai (valeur par défaut), le fichier est supprimé dès qu’il est fermé. L’objet retourné est toujours un objet fichier-compatible où l’attribut file est le véritable fichier. L’objet fichier-compatible peut être utilisé dans un gestionnaire de contexte (instruction with), juste comme un fichier normal.

tempfile.SpooledTemporaryFile(max_size=0, mode='w+b', buffering=None, encoding=None, newline=None, suffix=None, prefix=None, dir=None)

Cette fonction se comporte exactement comme TemporaryFile(), à l’exception que les données sont stockées en mémoire jusqu’à ce que leur taille dépasse max_size, ou que la méthode fileno() soit appelée. À ce moment, le contenu est écrit sur disque et le fonctionnement redevient similaire à celui de TemporaryFile().

Le fichier renvoyé a une méthode supplémentaire, rollover(), qui provoque la mise en écriture sur disque quelque soit la taille du fichier.

L’objet renvoyé est un objet fichier-compatible où l’attribut _file est soit un objet io.BytesIO soit un objet io.StringIO (en fonction du mode) soit un véritable fichier, si la fonction rollover() a été appelée. Cet objet fichier-compatible peut être utilisé dans un gestionnaire de contexte (instruction with), comme un fichier normal.

Modifié dans la version 3.3: la méthode de troncature accepte maintenant un argument size.

tempfile.TemporaryDirectory(suffix=None, prefix=None, dir=None)

Cette fonction crée un répertoire temporaire de manière sécurisée utilisant les mêmes règles que mkdtemp(). L’objet renvoyé peut être utilisé comme un gestionnaire de contexte (voir Exemples). À la sortie du contexte d’exécution ou à la destruction de l’objet, le répertoire temporaire et tout son contenu sont supprimés du système de fichiers.

The directory name can be retrieved from the name attribute of the returned object. When the returned object is used as a context manager, the name will be assigned to the target of the as clause in the with statement, if there is one.

Le répertoire peut être explicitement nettoyé en appelant la méthode cleanup().

Nouveau dans la version 3.2.

tempfile.mkstemp(suffix=None, prefix=None, dir=None, text=False)

Crée un fichier temporaire de la manière la plus sécurisée qui soit. Il n’y a pas d’accès concurrent (race condition) au moment de la création du fichier, en supposant que la plateforme implémente correctement l’option os.O_EXCL pour os.open(). Le fichier est seulement accessible en lecture et écriture par l’ID de l’utilisateur créateur. Si la plateforme utilise des bits de permissions pour indiquer si le fichier est exécutable, alors le fichier n’est exécutable par personne. Le descripteur de fichier n’est pas hérité par les processus fils.

À la différence de TemporaryFile(), l’utilisateur de mkstemp() est responsable de la suppression du fichier temporaire quand il n’en a plus besoin.

Si suffix ne vaut pas None, le nom de fichier se terminera avec ce suffixe, sinon il n’y aura pas de suffixe. mkstemp() ne met pas de point entre le nom du fichier et le suffixe. Si vous en avez besoin, mettez le point au début de suffix.

Si prefix ne vaut pas None, le nom de fichier commencera avec ce préfixe, sinon un préfixe par défaut est utilisé. La valeur par défaut est la valeur retournée par gettempprefix() ou gettempprefixb().

Si dir ne vaut pas None, le fichier sera créé dans ce répertoire, autrement, un répertoire par défaut sera utilisé. Le répertoire par défaut est choisi depuis une liste dépendante de la plateforme, mais l’utilisateur de l’application peut contrôler l’emplacement du répertoire en spécifiant les variables d’environnement TMPDIR, TEMP ou TMP. Il n’y a pas de garantie que le nom de fichier généré aura de bonnes propriétés telles que ne pas avoir besoin de le mettre entre guillemets lorsque celui-ci est passé à des commandes externes via os.popen().

Si l’un des paramètres suffix, prefix et dir n’est pas None, ils doivent être du même type. S’ils sont de type bytes, le nom renvoyée sera de type bytes plutôt que de type str. Si vous voulez forcer la valeur renvoyée en bytes, passez suffix=b''.

Si text est spécifié, cela indique si le fichier doit être ouvert en mode binaire (par défaut) ou en mode texte. Sur certaines plateformes, cela ne fait aucune différence.

mkstemp() renvoie un n-uplet contenant un descripteur (handle en anglais) au niveau du système d’exploitation vers un fichier ouvert (le même que renvoie os.open()) et le chemin d’accès absolu de ce fichier, dans cet ordre.

Modifié dans la version 3.5: suffix, prefix, et dir peuvent maintenant être spécifiés en bytes pour obtenir un résultat en bytes. Avant cela, le type str était le seul autorisé. suffix et prefix acceptent maintenant la valeur par défaut None pour que la valeur par défaut appropriée soit utilisée.

tempfile.mkdtemp(suffix=None, prefix=None, dir=None)

Crée un répertoire temporaire de la manière la plus sécurisée qu’il soit. Il n’y a pas d’accès concurrent (race condition) au moment de la création du répertoire. Le répertoire est accessible en lecture, en écriture, et son contenu lisible uniquement pour l’ID de l’utilisateur créateur.

L’utilisateur de mkdtemp() est responsable de la suppression du répertoire temporaire et de son contenu lorsqu’il n’en a plus besoin.

Les arguments prefix, suffix, et dir sont les mêmes que pour mkstemp().

mkdtemp() renvoie le chemin absolu du nouveau répertoire.

Modifié dans la version 3.5: suffix, prefix, et dir peuvent maintenant être spécifiés en bytes pour obtenir un résultat en bytes. Avant cela, le type str était le seul autorisé. suffix et prefix acceptent maintenant la valeur par défaut None pour que la valeur par défaut appropriée soit utilisée.

tempfile.gettempdir()

Renvoie le nom du répertoire utilisé pour les fichiers temporaires. C’est la valeur par défaut pour l’argument dir de toutes les fonctions de ce module.

Python cherche un répertoire parmi une liste standard de répertoires dans lequel l’utilisateur final peut créer des fichiers. La liste est :

Le répertoire correspondant à la variable d’environnement TMPDIR.

Le répertoire correspondant à la variable d’environnement TEMP.

Le répertoire correspondant à la variable d’environnement TMP.

Un emplacement dépendant à la plateforme :

Sur Windows, les répertoires C:\TEMP, C:\TMP, \TEMP, et \TMP, dans cet ordre.

Sur toutes les autres plate-formes, les répertoires /tmp, /var/tmp, et /usr/tmp, dans cet ordre.

En dernier ressort, le répertoire de travail courant.

Le résultat de cette recherche est mis en cache, voir la description de tempdir dessous.

tempfile.gettempdirb()

Similaire à gettempdir() mais la valeur retournée est en bytes.

Nouveau dans la version 3.5.

tempfile.gettempprefix()

Renvoie le préfixe de nom de fichier utilisé pour créer les fichiers temporaires. Cela ne contient pas le nom du répertoire.

tempfile.gettempprefixb()

Similaire à gettempprefix() mais la valeur retournée est en bytes.

Nouveau dans la version 3.5.

Le module utilise une variable globale pour stocker le nom du répertoire utilisé pour les fichiers temporaires renvoyés par gettempdir(). Vous pouvez directement utiliser la variable globale pour surcharger le processus de sélection, mais ceci est déconseillé. Toutes les fonctions de ce module prennent un argument dir qui peut être utilisé pour spécifier le répertoire. Il s’agit de la méthode recommandée.

tempfile.tempdir

Quand une valeur autre que None est spécifiée, cette variable définit la valeur par défaut pour l’argument dir des fonctions définies dans ce module.

If tempdir is None (the default) at any call to any of the above functions except gettempprefix() it is initialized following the algorithm described in gettempdir().

11.6.1. Exemples

Voici quelques exemples classiques d’utilisation du module tempfile :

>>> import tempfile

# create a temporary file and write some data to it
>>> fp = tempfile.TemporaryFile()
>>> fp.write(b'Hello world!')
# read data from file
>>> fp.seek(0)
>>> fp.read()
b'Hello world!'
# close the file, it will be removed
>>> fp.close()

# create a temporary file using a context manager
>>> with tempfile.TemporaryFile() as fp:
...     fp.write(b'Hello world!')
...     fp.seek(0)
...     fp.read()
b'Hello world!'
>>>
# file is now closed and removed

# create a temporary directory using the context manager
>>> with tempfile.TemporaryDirectory() as tmpdirname:
...     print('created temporary directory', tmpdirname)
>>>
# directory and contents have been removed

11.6.2. Fonctions et variables obsolètes

Historiquement, la méthode pour créer des fichiers temporaires consistait à générer un nom de fichier avec la fonction mktemp() puis créer un fichier en utilisant ce nom. Malheureusement, cette méthode n’est pas fiable car un autre processus peut créer un fichier avec ce nom entre l’appel à la fonction mktemp() et la tentative de création de fichier par le premier processus en cours. La solution est de combiner les deux étapes et de créer le fichier immédiatement. Cette approche est utilisée par mkstemp() et les autres fonctions décrites plus haut.

tempfile.mktemp(suffix='', prefix='tmp', dir=None)

Obsolète depuis la version 2.3: Utilisez mkstemp() à la place.

Renvoie le chemin absolu d’un fichier qui n’existe pas lorsque l’appel est fait. Les arguments prefix, suffix, et dir sont similaires à ceux de mkstemp() mais les noms de fichiers en bytes, sufix=None et prefix=None ne sont pas implémentées.

Avertissement

Utiliser cette fonction peut introduire une faille de sécurité dans votre programme. Avant que vous n’ayez le temps de faire quoi que ce soit avec le nom de fichier renvoyé, quelqu’un peut l’utiliser. L’utilisation de mktemp() peut être remplacée facilement avec NamedTemporaryFile() en y passant le paramètre delete=False :

>>> f = NamedTemporaryFile(delete=False)
>>> f.name
'/tmp/tmptjujjt'
>>> f.write(b"Hello World!\n")
13
>>> f.close()
>>> os.unlink(f.name)
>>> os.path.exists(f.name)
False

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11.7. glob — Recherche de chemins de style Unix selon certains motifs

Code source : Lib/glob.py [https://github.com/python/cpython/tree/3.6/Lib/glob.py]

Le module glob recherche tous les chemins correspondant à un motif particulier selon les règles utilisées par le shell Unix, les résultats sont renvoyés dans un ordre arbitraire. Aucun remplacement du tilde n’est réalisé, mais les caractères *, ?, et les caractères [] exprimant un intervalle sont correctement renvoyés. Cette opération est réalisée en utilisant les fonctions os.scandir() et fnmatch.fnmatch() de concert, et sans invoquer une sous-commande. Notons qu’à la différence de fnmatch.fnmatch(), glob traite les noms de fichiers commençant par un point (.) comme des cas spéciaux. (Pour remplacer le tilde et les variables shell, nous vous conseillons d’utiliser les fonctions os.path.expanduser() et os.path.expandvars().)

Pour une correspondance littérale, il faut entourer le métacaractère par des crochets. Par exemple, '[?]' reconnaît le caractère '?'.

Voir aussi

Le module pathlib offre une représentation objet de haut niveau des chemins.

glob.glob(pathname, *, recursive=False)

Renvoie une liste, potentiellement vide, de chemins correspondant au motif pathname, qui doit être une chaîne de caractères contenant la spécification du chemin. pathname peut être soit absolu (comme /usr/src/Python-1.5/Makefile) soit relatif (comme ../../Tools/*/*.gif), et contenir un caractère de remplacement de style shell. Les liens symboliques cassés sont aussi inclus dans les résultats (comme pour le shell).

Si recursive est vrai, le motif « ** » reconnaît tous les fichiers et, zéro ou plus répertoires et sous-répertoires. Si le motif est suivi par un caractère de séparation os.sep, seuls les répertoires et sous-répertoires sont reconnus.

Note

Utiliser le motif « ** » dans de grandes arborescences de dossier peut consommer une quantité de temps démesurée.

Modifié dans la version 3.5: Gestion des chemins récursifs utilisant le motif « ** ».

glob.iglob(pathname, *, recursive=False)

Renvoie un iterator qui produit les mêmes valeurs que glob(), sans toutes les charger en mémoire simultanément.

glob.escape(pathname)

Échappe tous les caractères spéciaux ('?', '*' et '['). Cela est utile pour reconnaître une chaîne de caractère littérale arbitraire qui contiendrait ce type de caractères. Les caractères spéciaux dans les disques et répertoires partagés (chemins UNC) ne sont pas échappés, e.g. sous Windows escape('//?/c:/Quo vadis?.txt') renvoie '//?/c:/Quo vadis[?].txt'.

Nouveau dans la version 3.4.

Par exemple, considérons un répertoire contenant les fichiers suivants : 1.gif, 2.txt, card.gif et un sous-répertoire sub contenant seulement le fichier 3.txt. glob() produit les résultats suivants. Notons que les composantes principales des chemins sont préservées.

>>> import glob
>>> glob.glob('./[0-9].*')
['./1.gif', './2.txt']
>>> glob.glob('*.gif')
['1.gif', 'card.gif']
>>> glob.glob('?.gif')
['1.gif']
>>> glob.glob('**/*.txt', recursive=True)
['2.txt', 'sub/3.txt']
>>> glob.glob('./**/', recursive=True)
['./', './sub/']

Si le répertoire contient des fichiers commençant par ., ils ne sont pas reconnus par défaut. Par exemple, considérons un répertoire contenant card.gif et .card.gif :

>>> import glob
>>> glob.glob('*.gif')
['card.gif']
>>> glob.glob('.c*')
['.card.gif']

Voir aussi

Module fnmatch

Recherche de noms de fichiers de style shell (ne concerne pas les chemins)

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11.8. fnmatch — Filtrage par motif des noms de fichiers Unix

Code source : Lib/fnmatch.py [https://github.com/python/cpython/tree/3.6/Lib/fnmatch.py]

Ce module fournit la gestion des caractères de remplacement de style shell Unix, qui ne sont pas identiques à ceux utilisés dans les expressions régulières (documentés dans le module re). Les caractères spéciaux utilisés comme caractères de remplacement de style shell sont :

Motif

Signification

*

reconnaît n’importe quoi

?

reconnaît n’importe quel caractère unique

[seq]

reconnaît n’importe quel caractère dans seq

[!seq]

reconnaît n’importe quel caractère qui n’est pas dans seq

Pour une correspondance littérale, il faut entourer le métacaractère par des crochets. Par exemple, '[?]' reconnaît le caractère '?'.

Note that the filename separator ('/' on Unix) is not special to this module. See module glob for pathname expansion (glob uses filter() to match pathname segments). Similarly, filenames starting with a period are not special for this module, and are matched by the * and ? patterns.

fnmatch.fnmatch(filename, pattern)

Teste si la chaîne de caractères filename correspond au motif pattern, en renvoyant True ou False. La casse de chacun des paramètres peut être normalisée en utilisant os.path.normcase(). fnmatchcase() peut être utilisée pour réaliser une comparaison sensible à la casse, indépendamment du système d’exploitation.

Cet exemple affiche tous les noms de fichiers du répertoire courant ayant pour extension .txt :

import fnmatch
import os

for file in os.listdir('.'):
    if fnmatch.fnmatch(file, '*.txt'):
        print(file)

fnmatch.fnmatchcase(filename, pattern)

Teste si filename correspond au motif pattern, en renvoyant True ou False ; la comparaison est sensible à la casse et n’utilise pas la fonction os.path.normcase().

fnmatch.filter(names, pattern)

Renvoie un sous-ensemble de la liste names correspondant au motif pattern. Similaire à [n for n in names if fnmatch(n, pattern)], mais implémenté plus efficacement.

fnmatch.translate(pattern)

Renvoie le motif pattern, de style shell, converti en une expression régulière utilisable avec re.match().

Exemple :

>>> import fnmatch, re
>>>
>>> regex = fnmatch.translate('*.txt')
>>> regex
'(?s:.*\\.txt)\\Z'
>>> reobj = re.compile(regex)
>>> reobj.match('foobar.txt')
<_sre.SRE_Match object; span=(0, 10), match='foobar.txt'>

Voir aussi

Module glob

Recherche de chemins de style shell Unix

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11.9. linecache — Accès direct aux lignes d’un texte

Code source : Lib/linecache.py [https://github.com/python/cpython/tree/3.6/Lib/linecache.py]

Le module linecache permet d’obtenir n’importe quelle ligne d’un fichier source Python. Le cas classique où de nombreuses lignes sont accédées est optimisé en utilisant un cache interne. C’est utilisé par le module traceback pour récupérer les lignes à afficher dans les piles d’appels.

Les fichiers sont ouverts par la fonction tokenize.open(). Cette fonction utilise tokenize.detect_encoding() pour obtenir l’encodage du fichier. En l’absence d’un BOM et d’un cookie d’encodage, c’est l’encodage UTF-8 qui sera utilisé.

Le module linecache définit les fonctions suivantes :

linecache.getline(filename, lineno, module_globals=None)

Récupère la ligne lineno du fichier filename. Cette fonction ne lèvera jamais d’exception, elle préfèrera renvoyer '' en cas d’erreur (le caractère de retour à la ligne sera inclus pour les lignes existantes).

Si le fichier filename n’est pas trouvé, la fonction le cherchera dans les chemins de recherche de modules, sys.path`, après avoir vérifié si un ``__loader__ (de la PEP 302 [https://www.python.org/dev/peps/pep-0302]) se trouve dans module_globals, dans le cas où le module a été importé depuis un fichier zip, ou une autre source hors du système de fichier.

linecache.clearcache()

Nettoie le cache. Utilisez cette fonction si vous n’avez plus besoin des lignes des fichiers précédemment lus via getline().

linecache.checkcache(filename=None)

Vérifie la validité du cache. Utilisez cette fonction si les fichiers du cache pourraient avoir changé sur le disque, et que vous en voudriez une version à jour. Sans filename, toutes les entrées du cache seront vérifiées.

linecache.lazycache(filename, module_globals)

Récupère suffisamment d’informations sur un module situé hors du système de fichiers pour récupérer ses lignes plus tard via getline(), même si module_globals devient None. Cela évite de lire le fichier avant d’avoir besoin d’une ligne, tout en évitant de conserver les globales du module indéfiniment.

Nouveau dans la version 3.5.

Exemple :

>>> import linecache
>>> linecache.getline(linecache.__file__, 8)
'import sys\n'

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11.10. shutil — Opérations de haut niveau sur les fichiers

Code source : Lib/shutil.py [https://github.com/python/cpython/tree/3.6/Lib/shutil.py]

Le module shutil propose des opérations de haut niveau sur les fichiers et ensembles de fichiers. En particulier, des fonctions pour copier et déplacer les fichiers sont proposées. Pour les opérations individuelles sur les fichiers, reportez-vous au module os.

Avertissement

Même les fonctions de copie haut niveau (shutil.copy(), shutil.copy2()) ne peuvent copier toutes les métadonnées des fichiers.

Sur les plateformes POSIX, cela signifie que le propriétaire et le groupe du fichier sont perdus, ainsi que les ACLs. Sur Mac OS, le clonage de ressource et autres métadonnées ne sont pas utilisés. Cela signifie que les ressources seront perdues et que le type de fichier et les codes créateur ne seront pas corrects. Sur Windows, les propriétaires des fichiers, ACLs et flux de données alternatifs ne sont pas copiés.

11.10.1. Opérations sur les répertoires et les fichiers

shutil.copyfileobj(fsrc, fdst[, length])

Copie le contenu de l’objet fichier fsrc dans l’objet fichier fdst. L’entier length, si spécifié, est la taille du tampon. En particulier, une valeur de length négative signifie la copie des données sans découper la source en morceaux ; par défaut les données sont lues par morceaux pour éviter la consommation mémoire non-contrôlée. À noter que si la position courante dans l’objet fsrc n’est pas 0, seul le contenu depuis la position courante jusqu’à la fin est copié.

shutil.copyfile(src, dst, *, follow_symlinks=True)

Copie le contenu (sans métadonnées) du fichier nommé src dans un fichier nommé dst et renvoie dst. src et dst sont des chemins sous forme de chaînes de caractères. dst doit être le chemin complet de la cible ; voir dans shutil.copy() pour une copie acceptant le chemin du dossier cible. Si src et dst désignent le même fichier SameFileError est levée.

La cible doit être accessible en écriture, sinon l’exception OSError est levée. Si dst existe déjà, il est remplacé. Les fichiers spéciaux comme les périphériques caractères ou bloc ainsi que les tubes (pipes) ne peuvent pas être copiés avec cette fonction.

Si follow_symlinks est faux et src est un lien symbolique, un nouveau lien symbolique est créé au lieu de copier le fichier pointé par src.

Modifié dans la version 3.3: IOError était levée au lieu de OSError. Ajout de l’argument follow_symlinks. Maintenant renvoie dst.

Modifié dans la version 3.4: Lève SameFileError au lieu de Error. Puisque la première est une sous-classe de la seconde, le changement assure la rétrocompatibilité.

exception shutil.SameFileError

Cette exception est levée si la source et la destination dans copyfile() sont le même fichier.

Nouveau dans la version 3.4.

shutil.copymode(src, dst, *, follow_symlinks=True)

Copie les octets de permission de src vers dst. Le contenu du fichier, le propriétaire et le groupe ne sont pas modifiés. src et dst sont des chaînes spécifiant les chemins. Si follow_symlinks est faux, et src et dst sont des liens symboliques, copymode() tente de modifier le mode de dst (au lieu du fichier vers lequel il pointe). Cette fonctionnalité n’est pas disponible sur toutes les plateformes ; voir copystat() pour plus d’informations. Si copymode() ne peut pas modifier les liens symboliques sur la plateforme cible alors que c’est demandé, il ne fait rien.

Modifié dans la version 3.3: L’argument follow_symlinks a été ajouté.

shutil.copystat(src, dst, *, follow_symlinks=True)

Copie les bits définissant les droits d’accès, la date du dernier accès, de la dernière modification et les drapeaux (flags en anglais) de src vers dst. Sur Linux, copystat() copie également, si possible, les « extended attributes ». Le contenu du fichier, le propriétaire et le groupe ne sont pas affectés. src et dst sont des chaînes spécifiant les chemins.

Si follow_symlinks est faux et src et dst représentent des liens symboliques, copystat() agit sur les liens symboliques au lieu des fichiers cibles — elle lit les informations du lien symbolique de src et les écrit vers la destination pointée par dst.

Note

Toutes les plateformes n’offrent pas la possibilité d’examiner et modifier les liens symboliques. Python peut vous informer des fonctionnalités effectivement disponibles.

Si os.chmod in os.supports_follow_symlinks est True, copystat() peut modifier les octets de droits d’accès du lien symbolique.

If os.utime in os.supports_follow_symlinks is True, copystat() can modify the last access and modification times of a symbolic link.

If os.chflags in os.supports_follow_symlinks is True, copystat() can modify the flags of a symbolic link. (os.chflags is not available on all platforms.)

On platforms where some or all of this functionality is unavailable, when asked to modify a symbolic link, copystat() will copy everything it can. copystat() never returns failure.

Please see os.supports_follow_symlinks for more information.

Modifié dans la version 3.3: Added follow_symlinks argument and support for Linux extended attributes.

shutil.copy(src, dst, *, follow_symlinks=True)

Copies the file src to the file or directory dst. src and dst should be strings. If dst specifies a directory, the file will be copied into dst using the base filename from src. Returns the path to the newly created file.

If follow_symlinks is false, and src is a symbolic link, dst will be created as a symbolic link. If follow_symlinks is true and src is a symbolic link, dst will be a copy of the file src refers to.

copy() copies the file data and the file’s permission mode (see os.chmod()). Other metadata, like the file’s creation and modification times, is not preserved. To preserve all file metadata from the original, use copy2() instead.

Modifié dans la version 3.3: Added follow_symlinks argument. Now returns path to the newly created file.

shutil.copy2(src, dst, *, follow_symlinks=True)

Identical to copy() except that copy2() also attempts to preserve file metadata.

When follow_symlinks is false, and src is a symbolic link, copy2() attempts to copy all metadata from the src symbolic link to the newly-created dst symbolic link. However, this functionality is not available on all platforms. On platforms where some or all of this functionality is unavailable, copy2() will preserve all the metadata it can; copy2() never returns failure.

copy2() uses copystat() to copy the file metadata. Please see copystat() for more information about platform support for modifying symbolic link metadata.

Modifié dans la version 3.3: Added follow_symlinks argument, try to copy extended file system attributes too (currently Linux only). Now returns path to the newly created file.

shutil.ignore_patterns(*patterns)

This factory function creates a function that can be used as a callable for copytree()”s ignore argument, ignoring files and directories that match one of the glob-style patterns provided. See the example below.

shutil.copytree(src, dst, symlinks=False, ignore=None, copy_function=copy2, ignore_dangling_symlinks=False)

Recursively copy an entire directory tree rooted at src, returning the destination directory. The destination directory, named by dst, must not already exist; it will be created as well as missing parent directories. Permissions and times of directories are copied with copystat(), individual files are copied using shutil.copy2().

If symlinks is true, symbolic links in the source tree are represented as symbolic links in the new tree and the metadata of the original links will be copied as far as the platform allows; if false or omitted, the contents and metadata of the linked files are copied to the new tree.

When symlinks is false, if the file pointed by the symlink doesn’t exist, an exception will be added in the list of errors raised in an Error exception at the end of the copy process. You can set the optional ignore_dangling_symlinks flag to true if you want to silence this exception. Notice that this option has no effect on platforms that don’t support os.symlink().

If ignore is given, it must be a callable that will receive as its arguments the directory being visited by copytree(), and a list of its contents, as returned by os.listdir(). Since copytree() is called recursively, the ignore callable will be called once for each directory that is copied. The callable must return a sequence of directory and file names relative to the current directory (i.e. a subset of the items in its second argument); these names will then be ignored in the copy process. ignore_patterns() can be used to create such a callable that ignores names based on glob-style patterns.

If exception(s) occur, an Error is raised with a list of reasons.

If copy_function is given, it must be a callable that will be used to copy each file. It will be called with the source path and the destination path as arguments. By default, shutil.copy2() is used, but any function that supports the same signature (like shutil.copy()) can be used.

Modifié dans la version 3.3: Copy metadata when symlinks is false. Now returns dst.

Modifié dans la version 3.2: Added the copy_function argument to be able to provide a custom copy function. Added the ignore_dangling_symlinks argument to silent dangling symlinks errors when symlinks is false.

shutil.rmtree(path, ignore_errors=False, onerror=None)

Delete an entire directory tree; path must point to a directory (but not a symbolic link to a directory). If ignore_errors is true, errors resulting from failed removals will be ignored; if false or omitted, such errors are handled by calling a handler specified by onerror or, if that is omitted, they raise an exception.

Note

On platforms that support the necessary fd-based functions a symlink attack resistant version of rmtree() is used by default. On other platforms, the rmtree() implementation is susceptible to a symlink attack: given proper timing and circumstances, attackers can manipulate symlinks on the filesystem to delete files they wouldn’t be able to access otherwise. Applications can use the rmtree.avoids_symlink_attacks function attribute to determine which case applies.

If onerror is provided, it must be a callable that accepts three parameters: function, path, and excinfo.

The first parameter, function, is the function which raised the exception; it depends on the platform and implementation. The second parameter, path, will be the path name passed to function. The third parameter, excinfo, will be the exception information returned by sys.exc_info(). Exceptions raised by onerror will not be caught.

Modifié dans la version 3.3: Added a symlink attack resistant version that is used automatically if platform supports fd-based functions.

rmtree.avoids_symlink_attacks

Indicates whether the current platform and implementation provides a symlink attack resistant version of rmtree(). Currently this is only true for platforms supporting fd-based directory access functions.

Nouveau dans la version 3.3.

shutil.move(src, dst, copy_function=copy2)

Recursively move a file or directory (src) to another location (dst) and return the destination.

If the destination is an existing directory, then src is moved inside that directory. If the destination already exists but is not a directory, it may be overwritten depending on os.rename() semantics.

If the destination is on the current filesystem, then os.rename() is used. Otherwise, src is copied to dst using copy_function and then removed. In case of symlinks, a new symlink pointing to the target of src will be created in or as dst and src will be removed.

If copy_function is given, it must be a callable that takes two arguments src and dst, and will be used to copy src to dest if os.rename() cannot be used. If the source is a directory, copytree() is called, passing it the copy_function(). The default copy_function is copy2(). Using copy() as the copy_function allows the move to succeed when it is not possible to also copy the metadata, at the expense of not copying any of the metadata.

Modifié dans la version 3.3: Added explicit symlink handling for foreign filesystems, thus adapting it to the behavior of GNU’s mv. Now returns dst.

Modifié dans la version 3.5: Added the copy_function keyword argument.

shutil.disk_usage(path)

Return disk usage statistics about the given path as a named tuple with the attributes total, used and free, which are the amount of total, used and free space, in bytes. On Windows, path must be a directory; on Unix, it can be a file or directory.

Nouveau dans la version 3.3.

Disponibilité : Unix, Windows.

shutil.chown(path, user=None, group=None)

Change owner user and/or group of the given path.

user can be a system user name or a uid; the same applies to group. At least one argument is required.

See also os.chown(), the underlying function.

Disponibilité : Unix.

Nouveau dans la version 3.3.

shutil.which(cmd, mode=os.F_OK | os.X_OK, path=None)

Return the path to an executable which would be run if the given cmd was called. If no cmd would be called, return None.

mode is a permission mask passed to os.access(), by default determining if the file exists and executable.

When no path is specified, the results of os.environ() are used, returning either the « PATH » value or a fallback of os.defpath.

On Windows, the current directory is always prepended to the path whether or not you use the default or provide your own, which is the behavior the command shell uses when finding executables. Additionally, when finding the cmd in the path, the PATHEXT environment variable is checked. For example, if you call shutil.which("python"), which() will search PATHEXT to know that it should look for python.exe within the path directories. For example, on Windows:

>>> shutil.which("python")
'C:\\Python33\\python.EXE'

Nouveau dans la version 3.3.

exception shutil.Error

This exception collects exceptions that are raised during a multi-file operation. For copytree(), the exception argument is a list of 3-tuples (srcname, dstname, exception).

11.10.1.1. copytree example

This example is the implementation of the copytree() function, described above, with the docstring omitted. It demonstrates many of the other functions provided by this module.

def copytree(src, dst, symlinks=False):
    names = os.listdir(src)
    os.makedirs(dst)
    errors = []
    for name in names:
        srcname = os.path.join(src, name)
        dstname = os.path.join(dst, name)
        try:
            if symlinks and os.path.islink(srcname):
                linkto = os.readlink(srcname)
                os.symlink(linkto, dstname)
            elif os.path.isdir(srcname):
                copytree(srcname, dstname, symlinks)
            else:
                copy2(srcname, dstname)
            # XXX What about devices, sockets etc.?
        except OSError as why:
            errors.append((srcname, dstname, str(why)))
        # catch the Error from the recursive copytree so that we can
        # continue with other files
        except Error as err:
            errors.extend(err.args[0])
    try:
        copystat(src, dst)
    except OSError as why:
        # can't copy file access times on Windows
        if why.winerror is None:
            errors.extend((src, dst, str(why)))
    if errors:
        raise Error(errors)

Another example that uses the ignore_patterns() helper:

from shutil import copytree, ignore_patterns

copytree(source, destination, ignore=ignore_patterns('*.pyc', 'tmp*'))

This will copy everything except .pyc files and files or directories whose name starts with tmp.

Another example that uses the ignore argument to add a logging call:

from shutil import copytree
import logging

def _logpath(path, names):
    logging.info('Working in %s', path)
    return []   # nothing will be ignored

copytree(source, destination, ignore=_logpath)

11.10.1.2. rmtree example

This example shows how to remove a directory tree on Windows where some of the files have their read-only bit set. It uses the onerror callback to clear the readonly bit and reattempt the remove. Any subsequent failure will propagate.

import os, stat
import shutil

def remove_readonly(func, path, _):
    "Clear the readonly bit and reattempt the removal"
    os.chmod(path, stat.S_IWRITE)
    func(path)

shutil.rmtree(directory, onerror=remove_readonly)

11.10.2. Archiving operations

Nouveau dans la version 3.2.

Modifié dans la version 3.5: Added support for the xztar format.

High-level utilities to create and read compressed and archived files are also provided. They rely on the zipfile and tarfile modules.

shutil.make_archive(base_name, format[, root_dir[, base_dir[, verbose[, dry_run[, owner[, group[, logger]]]]]]])

Create an archive file (such as zip or tar) and return its name.

base_name is the name of the file to create, including the path, minus any format-specific extension. format is the archive format: one of « zip » (if the zlib module is available), « tar », « gztar » (if the zlib module is available), « bztar » (if the bz2 module is available), or « xztar » (if the lzma module is available).

root_dir is a directory that will be the root directory of the archive; for example, we typically chdir into root_dir before creating the archive.

base_dir is the directory where we start archiving from; i.e. base_dir will be the common prefix of all files and directories in the archive.

root_dir and base_dir both default to the current directory.

If dry_run is true, no archive is created, but the operations that would be executed are logged to logger.

owner and group are used when creating a tar archive. By default, uses the current owner and group.

logger must be an object compatible with PEP 282 [https://www.python.org/dev/peps/pep-0282], usually an instance of logging.Logger.

The verbose argument is unused and deprecated.

shutil.get_archive_formats()

Return a list of supported formats for archiving. Each element of the returned sequence is a tuple (name, description).

By default shutil provides these formats:

zip: ZIP file (if the zlib module is available).

tar: uncompressed tar file.

gztar: gzip’ed tar-file (if the zlib module is available).

bztar: bzip2’ed tar-file (if the bz2 module is available).

xztar: xz’ed tar-file (if the lzma module is available).

You can register new formats or provide your own archiver for any existing formats, by using register_archive_format().

shutil.register_archive_format(name, function[, extra_args[, description]])

Register an archiver for the format name.

function is the callable that will be used to unpack archives. The callable will receive the base_name of the file to create, followed by the base_dir (which defaults to os.curdir) to start archiving from. Further arguments are passed as keyword arguments: owner, group, dry_run and logger (as passed in make_archive()).

If given, extra_args is a sequence of (name, value) pairs that will be used as extra keywords arguments when the archiver callable is used.

description is used by get_archive_formats() which returns the list of archivers. Defaults to an empty string.

shutil.unregister_archive_format(name)

Remove the archive format name from the list of supported formats.

shutil.unpack_archive(filename[, extract_dir[, format]])

Unpack an archive. filename is the full path of the archive.

extract_dir is the name of the target directory where the archive is unpacked. If not provided, the current working directory is used.

format is the archive format: one of « zip », « tar », « gztar », « bztar », or « xztar ». Or any other format registered with register_unpack_format(). If not provided, unpack_archive() will use the archive file name extension and see if an unpacker was registered for that extension. In case none is found, a ValueError is raised.

shutil.register_unpack_format(name, extensions, function[, extra_args[, description]])

Registers an unpack format. name is the name of the format and extensions is a list of extensions corresponding to the format, like .zip for Zip files.

function is the callable that will be used to unpack archives. The callable will receive the path of the archive, followed by the directory the archive must be extracted to.

When provided, extra_args is a sequence of (name, value) tuples that will be passed as keywords arguments to the callable.

description can be provided to describe the format, and will be returned by the get_unpack_formats() function.

shutil.unregister_unpack_format(name)

Unregister an unpack format. name is the name of the format.

shutil.get_unpack_formats()

Return a list of all registered formats for unpacking. Each element of the returned sequence is a tuple (name, extensions, description).

By default shutil provides these formats:

zip: ZIP file (unpacking compressed files works only if the corresponding module is available).

tar: uncompressed tar file.

gztar: gzip’ed tar-file (if the zlib module is available).

bztar: bzip2’ed tar-file (if the bz2 module is available).

xztar: xz’ed tar-file (if the lzma module is available).

You can register new formats or provide your own unpacker for any existing formats, by using register_unpack_format().

11.10.2.1. Archiving example

In this example, we create a gzip’ed tar-file archive containing all files found in the .ssh directory of the user:

>>> from shutil import make_archive
>>> import os
>>> archive_name = os.path.expanduser(os.path.join('~', 'myarchive'))
>>> root_dir = os.path.expanduser(os.path.join('~', '.ssh'))
>>> make_archive(archive_name, 'gztar', root_dir)
'/Users/tarek/myarchive.tar.gz'

The resulting archive contains:

$ tar -tzvf /Users/tarek/myarchive.tar.gz
drwx------ tarek/staff       0 2010-02-01 16:23:40 ./
-rw-r--r-- tarek/staff     609 2008-06-09 13:26:54 ./authorized_keys
-rwxr-xr-x tarek/staff      65 2008-06-09 13:26:54 ./config
-rwx------ tarek/staff     668 2008-06-09 13:26:54 ./id_dsa
-rwxr-xr-x tarek/staff     609 2008-06-09 13:26:54 ./id_dsa.pub
-rw------- tarek/staff    1675 2008-06-09 13:26:54 ./id_rsa
-rw-r--r-- tarek/staff     397 2008-06-09 13:26:54 ./id_rsa.pub
-rw-r--r-- tarek/staff   37192 2010-02-06 18:23:10 ./known_hosts

11.10.3. Querying the size of the output terminal

shutil.get_terminal_size(fallback=(columns, lines))

Get the size of the terminal window.

For each of the two dimensions, the environment variable, COLUMNS and LINES respectively, is checked. If the variable is defined and the value is a positive integer, it is used.

When COLUMNS or LINES is not defined, which is the common case, the terminal connected to sys.__stdout__ is queried by invoking os.get_terminal_size().

If the terminal size cannot be successfully queried, either because the system doesn’t support querying, or because we are not connected to a terminal, the value given in fallback parameter is used. fallback defaults to (80, 24) which is the default size used by many terminal emulators.

The value returned is a named tuple of type os.terminal_size.

See also: The Single UNIX Specification, Version 2, Other Environment Variables [http://pubs.opengroup.org/onlinepubs/7908799/xbd/envvar.html#tag_002_003].

Nouveau dans la version 3.3.

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11.11. macpath — Fonctions de manipulation de chemins pour Mac OS 9

Code source: Lib/macpath.py [https://github.com/python/cpython/tree/3.6/Lib/macpath.py]

Ce module est une implémentation du module os.path pour Mac OS 9 (ou plus ancien). Il peut être utilisé pour manipuler des chemins dans l’ancien style Macintosh sur Mac OS X (ou n’importe quelle autre plateforme).

Les fonctions suivantes sont disponibles dans ce module : normcase(), normpath(), isabs(), join(), split(), isdir(), isfile(), walk(), exists(). Toutes les autres fonctions d”os.path sont aussi disponibles, mais vides, pour garder la compatibilité.

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12. Persistance des données

Les modules décrits dans ce chapitre permettent de stocker des données Python de manière persistante typiquement sur disque. Les modules pickle et marshal peuvent transformer n’importe quel type Python en une séquence d’octets, puis recréer les objets depuis ces octets. Les différents modules du paquet dbm gèrent une catégorie de formats de fichier basée sur des hach, stockant des correspondances entre chaînes de caractères.

La liste des modules documentés dans ce chapitre est :

12.1. pickle — Module de sérialisation d’objets Python

12.1.1. Relations aux autres modules python

12.1.1.1. Comparaison avec marshal

12.1.1.2. Comparison with json

12.1.2. Data stream format

12.1.3. Module Interface

12.1.4. What can be pickled and unpickled?

12.1.5. Pickling Class Instances

12.1.5.1. Persistence of External Objects

12.1.5.2. Dispatch Tables

12.1.5.3. Handling Stateful Objects

12.1.6. Restricting Globals

12.1.7. Performances

12.1.8. Exemples

12.2. copyreg — Enregistre les fonctions support de pickle

12.2.1. Exemple

12.3. shelve — Objet Python persistant

12.3.1. Limites

12.3.2. Exemple

12.4. marshal — Internal Python object serialization

12.5. dbm — Interfaces to Unix « databases »

12.5.1. dbm.gnu — GNU’s reinterpretation of dbm

12.5.2. dbm.ndbm — Interface based on ndbm

12.5.3. dbm.dumb — Portable DBM implementation

12.6. sqlite3 — Interface DB-API 2.0 pour bases de données SQLite

12.6.1. Fonctions et constantes du module

12.6.2. Objets de connexions

12.6.3. Cursor Objects

12.6.4. Row Objects

12.6.5. Exceptions

12.6.6. SQLite and Python types

12.6.6.1. Introduction

12.6.6.2. Using adapters to store additional Python types in SQLite databases

12.6.6.2.1. Letting your object adapt itself

12.6.6.2.2. Registering an adapter callable

12.6.6.3. Converting SQLite values to custom Python types

12.6.6.4. Default adapters and converters

12.6.7. Controlling Transactions

12.6.8. Using sqlite3 efficiently

12.6.8.1. Using shortcut methods

12.6.8.2. Accessing columns by name instead of by index

12.6.8.3. Using the connection as a context manager

12.6.9. Common issues

12.6.9.1. Fils d’exécution

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12.1. pickle — Module de sérialisation d’objets Python

Code source : Lib/pickle.py [https://github.com/python/cpython/tree/3.6/Lib/pickle.py]

Le module pickle implémente des protocoles binaires de sérialisation et dé-sérialisation d’objets Python. Le pickling est le procédé par lequel une hiérarchie d’objets Python est convertie en flux d’octets. unpickling est l’opération inverse, par laquelle un flux d’octets (à partir d’un binary file ou bytes-like object) est converti en hiérarchie d’objets. Pickling (et unpickling) sont alternativement connus sous les termes de « sérialisation », de « marshalling » 1 ou encore de « flattening ». Cependant pour éviter la confusion les termes utilisés ici sont pickling et unpickling.

Avertissement

Le module pickle n’est pas sécurisé contre les données erronées et malicieusement construites. Ne jamais unpickle la donnée reçue à partir d’une source non fiable ou non authentifiée.

12.1.1. Relations aux autres modules python

12.1.1.1. Comparaison avec marshal

Python possède un module de bas niveau en sérialisation appelé marshal, mais en général il est préférable d’utiliser pickle pour sérialiser des objets Python. marshal existe principalement pour gérer les fichiers Python en .pyc.

Le module pickle diffère du module marshal sur plusieurs aspects :

Le module pickle garde la trace des objets qu’il a déjà sérialisés, pour faire en sorte que les prochaines références à cet objet ne soient pas sérialisées à nouveau. marshal ne le fait pas.

Ça a des implications sur les objets partagés et les objets récursifs. Les objets récursifs sont des objets qui contiennent des références à eux-mêmes. Ceux-ci ne sont pas gérées par marshal : lui donner un objet récursif va le faire planter. Un objet est partagé lorsque que plusieurs références pointent dessus, depuis différents endroits dans la hiérarchie sérialisée. Le module pickle repère ces partages et ne stocke ces objets qu’une seule fois. Les objets partagés restent ainsi partagés, ce qui peut être très important pour les objets muables.

marshal ne peut être utilisé pour la sérialisation et l’instanciation de classes définies par les utilisateurs. pickle peut sauvegarder et restaurer les instances de classes de manière transparente. Cependant la définition de classe doit être importable et lancée dans le même module et de la même manière que lors de son importation.

The marshal serialization format is not guaranteed to be portable across Python versions. Because its primary job in life is to support .pyc files, the Python implementers reserve the right to change the serialization format in non-backwards compatible ways should the need arise. The pickle serialization format is guaranteed to be backwards compatible across Python releases.

12.1.1.2. Comparison with json

There are fundamental differences between the pickle protocols and JSON (JavaScript Object Notation) [http://json.org]:

JSON is a text serialization format (it outputs unicode text, although most of the time it is then encoded to utf-8), while pickle is a binary serialization format;

JSON is human-readable, while pickle is not;

JSON is interoperable and widely used outside of the Python ecosystem, while pickle is Python-specific;

JSON, by default, can only represent a subset of the Python built-in types, and no custom classes; pickle can represent an extremely large number of Python types (many of them automatically, by clever usage of Python’s introspection facilities; complex cases can be tackled by implementing specific object APIs).

Voir aussi

The json module: a standard library module allowing JSON serialization and deserialization.

12.1.2. Data stream format

The data format used by pickle is Python-specific. This has the advantage that there are no restrictions imposed by external standards such as JSON or XDR (which can’t represent pointer sharing); however it means that non-Python programs may not be able to reconstruct pickled Python objects.

By default, the pickle data format uses a relatively compact binary representation. If you need optimal size characteristics, you can efficiently compress pickled data.

The module pickletools contains tools for analyzing data streams generated by pickle. pickletools source code has extensive comments about opcodes used by pickle protocols.

There are currently 5 different protocols which can be used for pickling. The higher the protocol used, the more recent the version of Python needed to read the pickle produced.

Protocol version 0 is the original « human-readable » protocol and is backwards compatible with earlier versions of Python.

Protocol version 1 is an old binary format which is also compatible with earlier versions of Python.

Protocol version 2 was introduced in Python 2.3. It provides much more efficient pickling of new-style classes. Refer to PEP 307 [https://www.python.org/dev/peps/pep-0307] for information about improvements brought by protocol 2.

Protocol version 3 was added in Python 3.0. It has explicit support for bytes objects and cannot be unpickled by Python 2.x. This is the default protocol, and the recommended protocol when compatibility with other Python 3 versions is required.

Protocol version 4 was added in Python 3.4. It adds support for very large objects, pickling more kinds of objects, and some data format optimizations. Refer to PEP 3154 [https://www.python.org/dev/peps/pep-3154] for information about improvements brought by protocol 4.

Note

Serialization is a more primitive notion than persistence; although pickle reads and writes file objects, it does not handle the issue of naming persistent objects, nor the (even more complicated) issue of concurrent access to persistent objects. The pickle module can transform a complex object into a byte stream and it can transform the byte stream into an object with the same internal structure. Perhaps the most obvious thing to do with these byte streams is to write them onto a file, but it is also conceivable to send them across a network or store them in a database. The shelve module provides a simple interface to pickle and unpickle objects on DBM-style database files.

12.1.3. Module Interface

To serialize an object hierarchy, you simply call the dumps() function. Similarly, to de-serialize a data stream, you call the loads() function. However, if you want more control over serialization and de-serialization, you can create a Pickler or an Unpickler object, respectively.

The pickle module provides the following constants:

pickle.HIGHEST_PROTOCOL

An integer, the highest protocol version available. This value can be passed as a protocol value to functions dump() and dumps() as well as the Pickler constructor.

pickle.DEFAULT_PROTOCOL

An integer, the default protocol version used for pickling. May be less than HIGHEST_PROTOCOL. Currently the default protocol is 3, a new protocol designed for Python 3.

The pickle module provides the following functions to make the pickling process more convenient:

pickle.dump(obj, file, protocol=None, *, fix_imports=True)

Write a pickled representation of obj to the open file object file. This is equivalent to Pickler(file, protocol).dump(obj).

The optional protocol argument, an integer, tells the pickler to use the given protocol; supported protocols are 0 to HIGHEST_PROTOCOL. If not specified, the default is DEFAULT_PROTOCOL. If a negative number is specified, HIGHEST_PROTOCOL is selected.

The file argument must have a write() method that accepts a single bytes argument. It can thus be an on-disk file opened for binary writing, an io.BytesIO instance, or any other custom object that meets this interface.

If fix_imports is true and protocol is less than 3, pickle will try to map the new Python 3 names to the old module names used in Python 2, so that the pickle data stream is readable with Python 2.

pickle.dumps(obj, protocol=None, *, fix_imports=True)

Return the pickled representation of the object as a bytes object, instead of writing it to a file.

Arguments protocol and fix_imports have the same meaning as in dump().

pickle.load(file, *, fix_imports=True, encoding="ASCII", errors="strict")

Read a pickled object representation from the open file object file and return the reconstituted object hierarchy specified therein. This is equivalent to Unpickler(file).load().

The protocol version of the pickle is detected automatically, so no protocol argument is needed. Bytes past the pickled object’s representation are ignored.

The argument file must have two methods, a read() method that takes an integer argument, and a readline() method that requires no arguments. Both methods should return bytes. Thus file can be an on-disk file opened for binary reading, an io.BytesIO object, or any other custom object that meets this interface.

Optional keyword arguments are fix_imports, encoding and errors, which are used to control compatibility support for pickle stream generated by Python 2. If fix_imports is true, pickle will try to map the old Python 2 names to the new names used in Python 3. The encoding and errors tell pickle how to decode 8-bit string instances pickled by Python 2; these default to “ASCII” and “strict”, respectively. The encoding can be “bytes” to read these 8-bit string instances as bytes objects. Using encoding='latin1' is required for unpickling NumPy arrays and instances of datetime, date and time pickled by Python 2.

pickle.loads(bytes_object, *, fix_imports=True, encoding="ASCII", errors="strict")

Read a pickled object hierarchy from a bytes object and return the reconstituted object hierarchy specified therein.

The protocol version of the pickle is detected automatically, so no protocol argument is needed. Bytes past the pickled object’s representation are ignored.

Optional keyword arguments are fix_imports, encoding and errors, which are used to control compatibility support for pickle stream generated by Python 2. If fix_imports is true, pickle will try to map the old Python 2 names to the new names used in Python 3. The encoding and errors tell pickle how to decode 8-bit string instances pickled by Python 2; these default to “ASCII” and “strict”, respectively. The encoding can be “bytes” to read these 8-bit string instances as bytes objects. Using encoding='latin1' is required for unpickling NumPy arrays and instances of datetime, date and time pickled by Python 2.

The pickle module defines three exceptions:

exception pickle.PickleError

Common base class for the other pickling exceptions. It inherits Exception.

exception pickle.PicklingError

Error raised when an unpicklable object is encountered by Pickler. It inherits PickleError.

Refer to What can be pickled and unpickled? to learn what kinds of objects can be pickled.

exception pickle.UnpicklingError

Error raised when there is a problem unpickling an object, such as a data corruption or a security violation. It inherits PickleError.

Note that other exceptions may also be raised during unpickling, including (but not necessarily limited to) AttributeError, EOFError, ImportError, and IndexError.

The pickle module exports two classes, Pickler and Unpickler:

class pickle.Pickler(file, protocol=None, *, fix_imports=True)

This takes a binary file for writing a pickle data stream.

The optional protocol argument, an integer, tells the pickler to use the given protocol; supported protocols are 0 to HIGHEST_PROTOCOL. If not specified, the default is DEFAULT_PROTOCOL. If a negative number is specified, HIGHEST_PROTOCOL is selected.

The file argument must have a write() method that accepts a single bytes argument. It can thus be an on-disk file opened for binary writing, an io.BytesIO instance, or any other custom object that meets this interface.

If fix_imports is true and protocol is less than 3, pickle will try to map the new Python 3 names to the old module names used in Python 2, so that the pickle data stream is readable with Python 2.

dump(obj)

Write a pickled representation of obj to the open file object given in the constructor.

persistent_id(obj)

Do nothing by default. This exists so a subclass can override it.

If persistent_id() returns None, obj is pickled as usual. Any other value causes Pickler to emit the returned value as a persistent ID for obj. The meaning of this persistent ID should be defined by Unpickler.persistent_load(). Note that the value returned by persistent_id() cannot itself have a persistent ID.

See Persistence of External Objects for details and examples of uses.

dispatch_table

A pickler object’s dispatch table is a registry of reduction functions of the kind which can be declared using copyreg.pickle(). It is a mapping whose keys are classes and whose values are reduction functions. A reduction function takes a single argument of the associated class and should conform to the same interface as a __reduce__() method.

By default, a pickler object will not have a dispatch_table attribute, and it will instead use the global dispatch table managed by the copyreg module. However, to customize the pickling for a specific pickler object one can set the dispatch_table attribute to a dict-like object. Alternatively, if a subclass of Pickler has a dispatch_table attribute then this will be used as the default dispatch table for instances of that class.

See Dispatch Tables for usage examples.

Nouveau dans la version 3.3.

fast

Deprecated. Enable fast mode if set to a true value. The fast mode disables the usage of memo, therefore speeding the pickling process by not generating superfluous PUT opcodes. It should not be used with self-referential objects, doing otherwise will cause Pickler to recurse infinitely.

Use pickletools.optimize() if you need more compact pickles.

class pickle.Unpickler(file, *, fix_imports=True, encoding="ASCII", errors="strict")

This takes a binary file for reading a pickle data stream.

The protocol version of the pickle is detected automatically, so no protocol argument is needed.

The argument file must have two methods, a read() method that takes an integer argument, and a readline() method that requires no arguments. Both methods should return bytes. Thus file can be an on-disk file object opened for binary reading, an io.BytesIO object, or any other custom object that meets this interface.

Optional keyword arguments are fix_imports, encoding and errors, which are used to control compatibility support for pickle stream generated by Python 2. If fix_imports is true, pickle will try to map the old Python 2 names to the new names used in Python 3. The encoding and errors tell pickle how to decode 8-bit string instances pickled by Python 2; these default to “ASCII” and “strict”, respectively. The encoding can be “bytes” to read these 8-bit string instances as bytes objects.

load()

Read a pickled object representation from the open file object given in the constructor, and return the reconstituted object hierarchy specified therein. Bytes past the pickled object’s representation are ignored.

persistent_load(pid)

Raise an UnpicklingError by default.

If defined, persistent_load() should return the object specified by the persistent ID pid. If an invalid persistent ID is encountered, an UnpicklingError should be raised.

See Persistence of External Objects for details and examples of uses.

find_class(module, name)

Import module if necessary and return the object called name from it, where the module and name arguments are str objects. Note, unlike its name suggests, find_class() is also used for finding functions.

Subclasses may override this to gain control over what type of objects and how they can be loaded, potentially reducing security risks. Refer to Restricting Globals for details.

12.1.4. What can be pickled and unpickled?

The following types can be pickled:

None, True, and False

integers, floating point numbers, complex numbers

strings, bytes, bytearrays

tuples, lists, sets, and dictionaries containing only picklable objects

functions defined at the top level of a module (using def, not lambda)

built-in functions defined at the top level of a module

classes that are defined at the top level of a module

instances of such classes whose __dict__ or the result of calling __getstate__() is picklable (see section Pickling Class Instances for details).

Attempts to pickle unpicklable objects will raise the PicklingError exception; when this happens, an unspecified number of bytes may have already been written to the underlying file. Trying to pickle a highly recursive data structure may exceed the maximum recursion depth, a RecursionError will be raised in this case. You can carefully raise this limit with sys.setrecursionlimit().

Note that functions (built-in and user-defined) are pickled by « fully qualified » name reference, not by value. 2 This means that only the function name is pickled, along with the name of the module the function is defined in. Neither the function’s code, nor any of its function attributes are pickled. Thus the defining module must be importable in the unpickling environment, and the module must contain the named object, otherwise an exception will be raised. 3

Similarly, classes are pickled by named reference, so the same restrictions in the unpickling environment apply. Note that none of the class’s code or data is pickled, so in the following example the class attribute attr is not restored in the unpickling environment:

class Foo:
    attr = 'A class attribute'

picklestring = pickle.dumps(Foo)

These restrictions are why picklable functions and classes must be defined in the top level of a module.

Similarly, when class instances are pickled, their class’s code and data are not pickled along with them. Only the instance data are pickled. This is done on purpose, so you can fix bugs in a class or add methods to the class and still load objects that were created with an earlier version of the class. If you plan to have long-lived objects that will see many versions of a class, it may be worthwhile to put a version number in the objects so that suitable conversions can be made by the class’s __setstate__() method.

12.1.5. Pickling Class Instances

In this section, we describe the general mechanisms available to you to define, customize, and control how class instances are pickled and unpickled.

In most cases, no additional code is needed to make instances picklable. By default, pickle will retrieve the class and the attributes of an instance via introspection. When a class instance is unpickled, its __init__() method is usually not invoked. The default behaviour first creates an uninitialized instance and then restores the saved attributes. The following code shows an implementation of this behaviour:

def save(obj):
    return (obj.__class__, obj.__dict__)

def load(cls, attributes):
    obj = cls.__new__(cls)
    obj.__dict__.update(attributes)
    return obj

Classes can alter the default behaviour by providing one or several special methods:

object.__getnewargs_ex__()

In protocols 2 and newer, classes that implements the __getnewargs_ex__() method can dictate the values passed to the __new__() method upon unpickling. The method must return a pair (args, kwargs) where args is a tuple of positional arguments and kwargs a dictionary of named arguments for constructing the object. Those will be passed to the __new__() method upon unpickling.

You should implement this method if the __new__() method of your class requires keyword-only arguments. Otherwise, it is recommended for compatibility to implement __getnewargs__().

Modifié dans la version 3.6: __getnewargs_ex__() is now used in protocols 2 and 3.

object.__getnewargs__()

This method serves a similar purpose as __getnewargs_ex__(), but supports only positional arguments. It must return a tuple of arguments args which will be passed to the __new__() method upon unpickling.

__getnewargs__() will not be called if __getnewargs_ex__() is defined.

Modifié dans la version 3.6: Before Python 3.6, __getnewargs__() was called instead of __getnewargs_ex__() in protocols 2 and 3.

object.__getstate__()

Classes can further influence how their instances are pickled; if the class defines the method __getstate__(), it is called and the returned object is pickled as the contents for the instance, instead of the contents of the instance’s dictionary. If the __getstate__() method is absent, the instance’s __dict__ is pickled as usual.

object.__setstate__(state)

Upon unpickling, if the class defines __setstate__(), it is called with the unpickled state. In that case, there is no requirement for the state object to be a dictionary. Otherwise, the pickled state must be a dictionary and its items are assigned to the new instance’s dictionary.

Note

If __getstate__() returns a false value, the __setstate__() method will not be called upon unpickling.

Refer to the section Handling Stateful Objects for more information about how to use the methods __getstate__() and __setstate__().

Note

At unpickling time, some methods like __getattr__(), __getattribute__(), or __setattr__() may be called upon the instance. In case those methods rely on some internal invariant being true, the type should implement __getnewargs__() or __getnewargs_ex__() to establish such an invariant; otherwise, neither __new__() nor __init__() will be called.

As we shall see, pickle does not use directly the methods described above. In fact, these methods are part of the copy protocol which implements the __reduce__() special method. The copy protocol provides a unified interface for retrieving the data necessary for pickling and copying objects. 4

Although powerful, implementing __reduce__() directly in your classes is error prone. For this reason, class designers should use the high-level interface (i.e., __getnewargs_ex__(), __getstate__() and __setstate__()) whenever possible. We will show, however, cases where using __reduce__() is the only option or leads to more efficient pickling or both.

object.__reduce__()

The interface is currently defined as follows. The __reduce__() method takes no argument and shall return either a string or preferably a tuple (the returned object is often referred to as the « reduce value »).

If a string is returned, the string should be interpreted as the name of a global variable. It should be the object’s local name relative to its module; the pickle module searches the module namespace to determine the object’s module. This behaviour is typically useful for singletons.

When a tuple is returned, it must be between two and five items long. Optional items can either be omitted, or None can be provided as their value. The semantics of each item are in order:

A callable object that will be called to create the initial version of the object.

A tuple of arguments for the callable object. An empty tuple must be given if the callable does not accept any argument.

Optionally, the object’s state, which will be passed to the object’s __setstate__() method as previously described. If the object has no such method then, the value must be a dictionary and it will be added to the object’s __dict__ attribute.

Optionally, an iterator (and not a sequence) yielding successive items. These items will be appended to the object either using obj.append(item) or, in batch, using obj.extend(list_of_items). This is primarily used for list subclasses, but may be used by other classes as long as they have append() and extend() methods with the appropriate signature. (Whether append() or extend() is used depends on which pickle protocol version is used as well as the number of items to append, so both must be supported.)

Optionally, an iterator (not a sequence) yielding successive key-value pairs. These items will be stored to the object using obj[key] = value. This is primarily used for dictionary subclasses, but may be used by other classes as long as they implement __setitem__().

object.__reduce_ex__(protocol)

Alternatively, a __reduce_ex__() method may be defined. The only difference is this method should take a single integer argument, the protocol version. When defined, pickle will prefer it over the __reduce__() method. In addition, __reduce__() automatically becomes a synonym for the extended version. The main use for this method is to provide backwards-compatible reduce values for older Python releases.

12.1.5.1. Persistence of External Objects

For the benefit of object persistence, the pickle module supports the notion of a reference to an object outside the pickled data stream. Such objects are referenced by a persistent ID, which should be either a string of alphanumeric characters (for protocol 0) 5 or just an arbitrary object (for any newer protocol).

The resolution of such persistent IDs is not defined by the pickle module; it will delegate this resolution to the user defined methods on the pickler and unpickler, persistent_id() and persistent_load() respectively.

To pickle objects that have an external persistent id, the pickler must have a custom persistent_id() method that takes an object as an argument and returns either None or the persistent id for that object. When None is returned, the pickler simply pickles the object as normal. When a persistent ID string is returned, the pickler will pickle that object, along with a marker so that the unpickler will recognize it as a persistent ID.

To unpickle external objects, the unpickler must have a custom persistent_load() method that takes a persistent ID object and returns the referenced object.

Here is a comprehensive example presenting how persistent ID can be used to pickle external objects by reference.

# Simple example presenting how persistent ID can be used to pickle
# external objects by reference.

import pickle
import sqlite3
from collections import namedtuple

# Simple class representing a record in our database.
MemoRecord = namedtuple("MemoRecord", "key, task")

class DBPickler(pickle.Pickler):

    def persistent_id(self, obj):
        # Instead of pickling MemoRecord as a regular class instance, we emit a
        # persistent ID.
        if isinstance(obj, MemoRecord):
            # Here, our persistent ID is simply a tuple, containing a tag and a
            # key, which refers to a specific record in the database.
            return ("MemoRecord", obj.key)
        else:
            # If obj does not have a persistent ID, return None. This means obj
            # needs to be pickled as usual.
            return None

class DBUnpickler(pickle.Unpickler):

    def __init__(self, file, connection):
        super().__init__(file)
        self.connection = connection

    def persistent_load(self, pid):
        # This method is invoked whenever a persistent ID is encountered.
        # Here, pid is the tuple returned by DBPickler.
        cursor = self.connection.cursor()
        type_tag, key_id = pid
        if type_tag == "MemoRecord":
            # Fetch the referenced record from the database and return it.
            cursor.execute("SELECT * FROM memos WHERE key=?", (str(key_id),))
            key, task = cursor.fetchone()
            return MemoRecord(key, task)
        else:
            # Always raises an error if you cannot return the correct object.
            # Otherwise, the unpickler will think None is the object referenced
            # by the persistent ID.
            raise pickle.UnpicklingError("unsupported persistent object")

def main():
    import io
    import pprint

    # Initialize and populate our database.
    conn = sqlite3.connect(":memory:")
    cursor = conn.cursor()
    cursor.execute("CREATE TABLE memos(key INTEGER PRIMARY KEY, task TEXT)")
    tasks = (
        'give food to fish',
        'prepare group meeting',
        'fight with a zebra',
        )
    for task in tasks:
        cursor.execute("INSERT INTO memos VALUES(NULL, ?)", (task,))

    # Fetch the records to be pickled.
    cursor.execute("SELECT * FROM memos")
    memos = [MemoRecord(key, task) for key, task in cursor]
    # Save the records using our custom DBPickler.
    file = io.BytesIO()
    DBPickler(file).dump(memos)

    print("Pickled records:")
    pprint.pprint(memos)

    # Update a record, just for good measure.
    cursor.execute("UPDATE memos SET task='learn italian' WHERE key=1")

    # Load the records from the pickle data stream.
    file.seek(0)
    memos = DBUnpickler(file, conn).load()

    print("Unpickled records:")
    pprint.pprint(memos)

if __name__ == '__main__':
    main()

12.1.5.2. Dispatch Tables

If one wants to customize pickling of some classes without disturbing any other code which depends on pickling, then one can create a pickler with a private dispatch table.

The global dispatch table managed by the copyreg module is available as copyreg.dispatch_table. Therefore, one may choose to use a modified copy of copyreg.dispatch_table as a private dispatch table.

Par exemple

f = io.BytesIO()
p = pickle.Pickler(f)
p.dispatch_table = copyreg.dispatch_table.copy()
p.dispatch_table[SomeClass] = reduce_SomeClass

creates an instance of pickle.Pickler with a private dispatch table which handles the SomeClass class specially. Alternatively, the code

class MyPickler(pickle.Pickler):
    dispatch_table = copyreg.dispatch_table.copy()
    dispatch_table[SomeClass] = reduce_SomeClass
f = io.BytesIO()
p = MyPickler(f)

does the same, but all instances of MyPickler will by default share the same dispatch table. The equivalent code using the copyreg module is

copyreg.pickle(SomeClass, reduce_SomeClass)
f = io.BytesIO()
p = pickle.Pickler(f)

12.1.5.3. Handling Stateful Objects

Here’s an example that shows how to modify pickling behavior for a class. The TextReader class opens a text file, and returns the line number and line contents each time its readline() method is called. If a TextReader instance is pickled, all attributes except the file object member are saved. When the instance is unpickled, the file is reopened, and reading resumes from the last location. The __setstate__() and __getstate__() methods are used to implement this behavior.

class TextReader:
    """Print and number lines in a text file."""

    def __init__(self, filename):
        self.filename = filename
        self.file = open(filename)
        self.lineno = 0

    def readline(self):
        self.lineno += 1
        line = self.file.readline()
        if not line:
            return None
        if line.endswith('\n'):
            line = line[:-1]
        return "%i: %s" % (self.lineno, line)

    def __getstate__(self):
        # Copy the object's state from self.__dict__ which contains
        # all our instance attributes. Always use the dict.copy()
        # method to avoid modifying the original state.
        state = self.__dict__.copy()
        # Remove the unpicklable entries.
        del state['file']
        return state

    def __setstate__(self, state):
        # Restore instance attributes (i.e., filename and lineno).
        self.__dict__.update(state)
        # Restore the previously opened file's state. To do so, we need to
        # reopen it and read from it until the line count is restored.
        file = open(self.filename)
        for _ in range(self.lineno):
            file.readline()
        # Finally, save the file.
        self.file = file

A sample usage might be something like this:

>>> reader = TextReader("hello.txt")
>>> reader.readline()
'1: Hello world!'
>>> reader.readline()
'2: I am line number two.'
>>> new_reader = pickle.loads(pickle.dumps(reader))
>>> new_reader.readline()
'3: Goodbye!'

12.1.6. Restricting Globals

By default, unpickling will import any class or function that it finds in the pickle data. For many applications, this behaviour is unacceptable as it permits the unpickler to import and invoke arbitrary code. Just consider what this hand-crafted pickle data stream does when loaded:

>>> import pickle
>>> pickle.loads(b"cos\nsystem\n(S'echo hello world'\ntR.")
hello world
0

In this example, the unpickler imports the os.system() function and then apply the string argument « echo hello world ». Although this example is inoffensive, it is not difficult to imagine one that could damage your system.

For this reason, you may want to control what gets unpickled by customizing Unpickler.find_class(). Unlike its name suggests, Unpickler.find_class() is called whenever a global (i.e., a class or a function) is requested. Thus it is possible to either completely forbid globals or restrict them to a safe subset.

Here is an example of an unpickler allowing only few safe classes from the builtins module to be loaded:

import builtins
import io
import pickle

safe_builtins = {
    'range',
    'complex',
    'set',
    'frozenset',
    'slice',
}

class RestrictedUnpickler(pickle.Unpickler):

    def find_class(self, module, name):
        # Only allow safe classes from builtins.
        if module == "builtins" and name in safe_builtins:
            return getattr(builtins, name)
        # Forbid everything else.
        raise pickle.UnpicklingError("global '%s.%s' is forbidden" %
                                     (module, name))

def restricted_loads(s):
    """Helper function analogous to pickle.loads()."""
    return RestrictedUnpickler(io.BytesIO(s)).load()

A sample usage of our unpickler working has intended:

>>> restricted_loads(pickle.dumps([1, 2, range(15)]))
[1, 2, range(0, 15)]
>>> restricted_loads(b"cos\nsystem\n(S'echo hello world'\ntR.")
Traceback (most recent call last):
  ...
pickle.UnpicklingError: global 'os.system' is forbidden
>>> restricted_loads(b'cbuiltins\neval\n'
...                  b'(S\'getattr(__import__("os"), "system")'
...                  b'("echo hello world")\'\ntR.')
Traceback (most recent call last):
  ...
pickle.UnpicklingError: global 'builtins.eval' is forbidden

As our examples shows, you have to be careful with what you allow to be unpickled. Therefore if security is a concern, you may want to consider alternatives such as the marshalling API in xmlrpc.client or third-party solutions.

12.1.7. Performances

Recent versions of the pickle protocol (from protocol 2 and upwards) feature efficient binary encodings for several common features and built-in types. Also, the pickle module has a transparent optimizer written in C.

12.1.8. Exemples

For the simplest code, use the dump() and load() functions.

import pickle

# An arbitrary collection of objects supported by pickle.
data = {
    'a': [1, 2.0, 3, 4+6j],
    'b': ("character string", b"byte string"),
    'c': {None, True, False}
}

with open('data.pickle', 'wb') as f:
    # Pickle the 'data' dictionary using the highest protocol available.
    pickle.dump(data, f, pickle.HIGHEST_PROTOCOL)

The following example reads the resulting pickled data.

import pickle

with open('data.pickle', 'rb') as f:
    # The protocol version used is detected automatically, so we do not
    # have to specify it.
    data = pickle.load(f)

Voir aussi

Module copyreg

Pickle interface constructor registration for extension types.

Module pickletools

Tools for working with and analyzing pickled data.

Module shelve

Indexed databases of objects; uses pickle.

Module copy

Shallow and deep object copying.

Module marshal

High-performance serialization of built-in types.

Notes

1

Don’t confuse this with the marshal module

2

This is why lambda functions cannot be pickled: all lambda functions share the same name: <lambda>.

3

The exception raised will likely be an ImportError or an AttributeError but it could be something else.

4

The copy module uses this protocol for shallow and deep copying operations.

5

The limitation on alphanumeric characters is due to the fact the persistent IDs, in protocol 0, are delimited by the newline character. Therefore if any kind of newline characters occurs in persistent IDs, the resulting pickle will become unreadable.

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12.2. copyreg — Enregistre les fonctions support de pickle

Code source : Lib/copyreg.py [https://github.com/python/cpython/tree/3.6/Lib/copyreg.py]

Le module copyreg permet de définir des fonctions utilisées durant la sérialisation avec pickle de certains objets. Les modules pickle et copy utilisent ces fonctions lors d’une sérialisation ou d’une copie de ces objets. Le module propose alors des informations de configuration à propos de constructeurs d’objets qui ne sont pas des classes. De tels constructeurs peuvent être des instances de classes ou des fonctions.

copyreg.constructor(object)

Déclare object comme étant un constructeur valide. Si object n’est pas appelable (et n’est donc pas un constructeur valide), l’erreur TypeError est levée.

copyreg.pickle(type, function, constructor=None)

Déclare que function devrait être utilisée en tant que fonction de réduction pour des objets de type type. function doit soit retourner une chaîne de caractères soit un tuple qui contiens deux ou trois éléments.

Le paramètre optionnel contructor, s’il est donné, est un objet appelable qui peux être utilisé pour reconstruire l’objet lorsqu’il est appelé avec un tuple d’arguments retournés par function durant la sérialisation avec pickle. Une exception TypeError sera levée si object est une classe ou si constructor n’est pas appelable.

Voir le module pickle pour plus de détails sur l’interface attendue de function et constructor. Notez que l’attribut dispatch_table d’un objet pickler ou d’une sous-classe de pickle.Pickler peut aussi être utilisée pour déclarer des fonctions réductrices.

12.2.1. Exemple

L’exemple si-dessous essaye de démontrer comment enregistrer une fonction pickle et comment elle sera utilisée :

>>> import copyreg, copy, pickle
>>> class C(object):
...     def __init__(self, a):
...         self.a = a
...
>>> def pickle_c(c):
...     print("pickling a C instance...")
...     return C, (c.a,)
...
>>> copyreg.pickle(C, pickle_c)
>>> c = C(1)
>>> d = copy.copy(c)
pickling a C instance...
>>> p = pickle.dumps(c)
pickling a C instance...

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12.3. shelve — Objet Python persistant

Code source : Lib/shelve.py [https://github.com/python/cpython/tree/3.6/Lib/shelve.py]

Un shelf est un objet persistant, dictionnaire-compatible. La différence avec les bases de données dbm est que les valeurs (pas les clés !) dans un shelf peuvent être des objets Python arbitraires — n’importe quoi que le module pickle peut gérer. Cela inclut la plupart des instances de classe, des types de données récursives, et les objets contenant beaucoup de sous-objets partagés. Les clés sont des chaînes de caractères ordinaires.

shelve.open(filename, flag='c', protocol=None, writeback=False)

Ouvre un dictionnaire persistant. Le nom de fichier spécifié est le nom de fichier sans (son) extension pour la base de données sous-jacente. Comme effet de bord, une extension peut être ajoutée au nom de fichier et plus d’un fichier peut être créé. Par défaut, le fichier de base de données sous-jacente est ouvert en lecture et en écriture. Le paramètre optionnel flag possède la même interprétation que le paramètre flag de dbm.open().

Par défaut, les pickles de version 3 sont utilisés pour sérialiser des valeurs. La version du protocole de pickle peut être spécifiée avec le paramètre protocol.

À cause de la sémantique Python, un shelf ne peut pas savoir lorsqu’une entrée modifiable de dictionnaire persistant est modifiée. Par défaut les objets modifiés sont écrits seulement lorsqu’ils sont assignés à une shelf (voir Exemple). Si le paramètre optionnel writeback est mis à True, toutes les entrées déjà accédées sont aussi mises en cache en mémoire, et ré-écrites sur sync() et close() ; cela peut faciliter la modification des entrées modifiables dans le dictionnaire persistant, mais, si vous accédez à beaucoup d’entrées, cela peut consommer beaucoup de mémoire cache, et cela peut rendre l’opération de fermeture très lente puisque toutes les entrées déjà accédées sont ré-écrites (il n’y a aucun moyen de savoir quelles entrées déjà accédées sont mutables, ni lesquelles ont été vraiment modifiées).

Note

Ne pas se fier à la fermeture automatique de shelf ; appelez toujours close() explicitement quand vous n’en avez plus besoin, ou utilisez shelve.open() comme un gestionnaire de contexte :

with shelve.open('spam') as db:
    db['eggs'] = 'eggs'

Avertissement

Puisque le module shelve utilise en arrière plan pickle, il n’est pas sûr de charger un shelf depuis une source non fiable. Comme avec pickle, charger un shelf peut exécuter du code arbitraire.

Les objets shelf gèrent toutes les méthodes des dictionnaires. Cela facilite la transition depuis les scripts utilisant des dictionnaires à ceux nécessitant un stockage persistant.

Deux méthodes supplémentaires sont supportées :

Shelf.sync()

Réécrit toutes les entrées dans le cache si le shelf a été ouvert avec writeback passé à True. Vide le cache et synchronise le dictionnaire persistant sur le disque, si faisable. Elle est appelée automatiquement quand le shelf est fermé avec close().

Shelf.close()

Synchronise et ferme l’objet dict persistant. Les opérations sur un shelf fermé échouent avec une ValueError.

Voir aussi

Recette pour un dictionnaire persistant [https://code.activestate.com/recipes/576642/] avec un large panel de formats de stockage et ayant la vitesse des dictionnaires natifs.

12.3.1. Limites

Le choix du paquet de base de données à utiliser (comme dbm.ndbm ou dbm.gnu) dépend de l’interface disponible. Donc c’est risqué d’ouvrir la base de données directement en utilisant dbm. La base de données est également (malheureusement) sujette à des limitations de dbm, si c’est utilisé — cela signifie que (la représentation pickled de) l’objet stocké dans la base de données doit être assez petit et, dans de rare cas des collisions de clés peuvent entraîner le refus de mises à jour de la base de données.

Le module shelve ne gère pas l’accès concurrent en lecture/écriture sur les objets stockés (les accès simultanés en lecture sont sûrs). Lorsqu’un programme a un shelf ouvert en écriture, aucun autre programme ne doit l’avoir ouvert en écriture ou lecture. Le verrouillage des fichier Unix peut être utilisé pour résoudre ce problème, mais cela dépend de la version Unix et nécessite des connaissances à propos de l’implémentation de la base de données utilisée.

class shelve.Shelf(dict, protocol=None, writeback=False, keyencoding='utf-8')

Sous-classe de collections.abc.MutableMapping qui stocke les valeurs sérialisées par pickle dans l’objet dict.

Par défaut, les pickles de version 3 sont utilisés pour sérialiser les valeurs. La version du protocole pickle peut être spécifiée avec le paramètre protocol. Voir la documentation de pickle pour plus d’informations sur les protocoles pickle.

Si le paramètre writeback est True, l’objet garde en cache toutes les entrées accédées et les écrit dans le dict aux moments de synchronisation et de fermeture. Cela permet des opérations naturelles sur les entrées modifiables, mais peut consommer beaucoup plus de mémoire et rendre les temps de synchronisation et de fermeture très longs.

Le paramètre keyencoding est l’encodage utilisé pour encoder les clés avant qu’elles soient utilisées avec le dictionnaire sous-jacent.

Un objet Shelf peut également être utilisé comme un gestionnaire de contexte ; il est automatiquement fermé lorsque le bloc with est terminé.

Modifié dans la version 3.2: Ajout du paramètre keyencoding ; précédemment, les clés étaient toujours encodées en UTF-8.

Modifié dans la version 3.4: Ajout de la gestion des gestionnaires de contexte.

class shelve.BsdDbShelf(dict, protocol=None, writeback=False, keyencoding='utf-8')

Sous-classe de Shelf qui propose first(), next(), previous(), last() et set_location() qui sont disponibles dans le module tiers bsddb de pybsddb [https://www.jcea.es/programacion/pybsddb.htm] mais non dans les autres modules de base de données. L’objet dict passé au constructeur doit savoir gérer ces méthodes. Cela est généralement fait en appelant une des fonctions suivantes : bsddb.hashopen(), bsddb.btopen() ou bsddb.rnopen(). Les paramètres optionnels protocol, writeback, et keyencoding ont la même signification que pour la classe Shelf.

class shelve.DbfilenameShelf(filename, flag='c', protocol=None, writeback=False)

Sous-classe de Shelf qui accepte un filename au lieu d’un objet dictionnaire-compatible. Le fichier sous-jacent est ouvert avec dbm.open(). Par défaut le fichier est créé en lecture et en écriture. Le paramètre optionnel flag peut être interprété de la même manière que pour la fonction open(). Les paramètres optionnels protocol et writeback s’interprètent de la même manière que pour la classe Shelf.

12.3.2. Exemple

Pour résumer l’interface (key est une chaîne de caractère, data est un objet arbitraire) :

import shelve

d = shelve.open(filename)  # open -- file may get suffix added by low-level
                           # library

d[key] = data              # store data at key (overwrites old data if
                           # using an existing key)
data = d[key]              # retrieve a COPY of data at key (raise KeyError
                           # if no such key)
del d[key]                 # delete data stored at key (raises KeyError
                           # if no such key)

flag = key in d            # true if the key exists
klist = list(d.keys())     # a list of all existing keys (slow!)

# as d was opened WITHOUT writeback=True, beware:
d['xx'] = [0, 1, 2]        # this works as expected, but...
d['xx'].append(3)          # *this doesn't!* -- d['xx'] is STILL [0, 1, 2]!

# having opened d without writeback=True, you need to code carefully:
temp = d['xx']             # extracts the copy
temp.append(5)             # mutates the copy
d['xx'] = temp             # stores the copy right back, to persist it

# or, d=shelve.open(filename,writeback=True) would let you just code
# d['xx'].append(5) and have it work as expected, BUT it would also
# consume more memory and make the d.close() operation slower.

d.close()                  # close it

Voir aussi

Module dbm

Interface générique de base de données style dbm.

Module pickle

Sérialisation d’objet utilisé par shelve.

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12.4. marshal — Internal Python object serialization

This module contains functions that can read and write Python values in a binary format. The format is specific to Python, but independent of machine architecture issues (e.g., you can write a Python value to a file on a PC, transport the file to a Sun, and read it back there). Details of the format are undocumented on purpose; it may change between Python versions (although it rarely does). 1

This is not a general « persistence » module. For general persistence and transfer of Python objects through RPC calls, see the modules pickle and shelve. The marshal module exists mainly to support reading and writing the « pseudo-compiled » code for Python modules of .pyc files. Therefore, the Python maintainers reserve the right to modify the marshal format in backward incompatible ways should the need arise. If you’re serializing and de-serializing Python objects, use the pickle module instead – the performance is comparable, version independence is guaranteed, and pickle supports a substantially wider range of objects than marshal.

Avertissement

The marshal module is not intended to be secure against erroneous or maliciously constructed data. Never unmarshal data received from an untrusted or unauthenticated source.

Not all Python object types are supported; in general, only objects whose value is independent from a particular invocation of Python can be written and read by this module. The following types are supported: booleans, integers, floating point numbers, complex numbers, strings, bytes, bytearrays, tuples, lists, sets, frozensets, dictionaries, and code objects, where it should be understood that tuples, lists, sets, frozensets and dictionaries are only supported as long as the values contained therein are themselves supported. The singletons None, Ellipsis and StopIteration can also be marshalled and unmarshalled. For format version lower than 3, recursive lists, sets and dictionaries cannot be written (see below).

There are functions that read/write files as well as functions operating on bytes-like objects.

The module defines these functions:

marshal.dump(value, file[, version])

Write the value on the open file. The value must be a supported type. The file must be a writeable binary file.

If the value has (or contains an object that has) an unsupported type, a ValueError exception is raised — but garbage data will also be written to the file. The object will not be properly read back by load().

The version argument indicates the data format that dump should use (see below).

marshal.load(file)

Read one value from the open file and return it. If no valid value is read (e.g. because the data has a different Python version’s incompatible marshal format), raise EOFError, ValueError or TypeError. The file must be a readable binary file.

Note

If an object containing an unsupported type was marshalled with dump(), load() will substitute None for the unmarshallable type.

marshal.dumps(value[, version])

Return the bytes object that would be written to a file by dump(value, file). The value must be a supported type. Raise a ValueError exception if value has (or contains an object that has) an unsupported type.

The version argument indicates the data format that dumps should use (see below).

marshal.loads(bytes)

Convert the bytes-like object to a value. If no valid value is found, raise EOFError, ValueError or TypeError. Extra bytes in the input are ignored.

In addition, the following constants are defined:

marshal.version

Indicates the format that the module uses. Version 0 is the historical format, version 1 shares interned strings and version 2 uses a binary format for floating point numbers. Version 3 adds support for object instancing and recursion. The current version is 4.

Notes

1

The name of this module stems from a bit of terminology used by the designers of Modula-3 (amongst others), who use the term « marshalling » for shipping of data around in a self-contained form. Strictly speaking, « to marshal » means to convert some data from internal to external form (in an RPC buffer for instance) and « unmarshalling » for the reverse process.

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12.5. dbm — Interfaces to Unix « databases »

Source code: Lib/dbm/__init__.py [https://github.com/python/cpython/tree/3.6/Lib/dbm/__init__.py]

dbm is a generic interface to variants of the DBM database — dbm.gnu or dbm.ndbm. If none of these modules is installed, the slow-but-simple implementation in module dbm.dumb will be used. There is a third party interface [https://www.jcea.es/programacion/pybsddb.htm] to the Oracle Berkeley DB.

exception dbm.error

A tuple containing the exceptions that can be raised by each of the supported modules, with a unique exception also named dbm.error as the first item — the latter is used when dbm.error is raised.

dbm.whichdb(filename)

This function attempts to guess which of the several simple database modules available — dbm.gnu, dbm.ndbm or dbm.dumb — should be used to open a given file.

Returns one of the following values: None if the file can’t be opened because it’s unreadable or doesn’t exist; the empty string ('') if the file’s format can’t be guessed; or a string containing the required module name, such as 'dbm.ndbm' or 'dbm.gnu'.

dbm.open(file, flag='r', mode=0o666)

Open the database file file and return a corresponding object.

If the database file already exists, the whichdb() function is used to determine its type and the appropriate module is used; if it does not exist, the first module listed above that can be imported is used.

The optional flag argument can be:

Valeur

Signification

'r'

Open existing database for reading only (default)

'w'

Open existing database for reading and writing

'c'

Open database for reading and writing, creating it if it doesn’t exist

'n'

Always create a new, empty database, open for reading and writing

The optional mode argument is the Unix mode of the file, used only when the database has to be created. It defaults to octal 0o666 (and will be modified by the prevailing umask).

The object returned by open() supports the same basic functionality as dictionaries; keys and their corresponding values can be stored, retrieved, and deleted, and the in operator and the keys() method are available, as well as get() and setdefault().

Modifié dans la version 3.2: get() and setdefault() are now available in all database modules.

Key and values are always stored as bytes. This means that when strings are used they are implicitly converted to the default encoding before being stored.

These objects also support being used in a with statement, which will automatically close them when done.

Modifié dans la version 3.4: Added native support for the context management protocol to the objects returned by open().

The following example records some hostnames and a corresponding title, and then prints out the contents of the database:

import dbm

# Open database, creating it if necessary.
with dbm.open('cache', 'c') as db:

    # Record some values
    db[b'hello'] = b'there'
    db['www.python.org'] = 'Python Website'
    db['www.cnn.com'] = 'Cable News Network'

    # Note that the keys are considered bytes now.
    assert db[b'www.python.org'] == b'Python Website'
    # Notice how the value is now in bytes.
    assert db['www.cnn.com'] == b'Cable News Network'

    # Often-used methods of the dict interface work too.
    print(db.get('python.org', b'not present'))

    # Storing a non-string key or value will raise an exception (most
    # likely a TypeError).
    db['www.yahoo.com'] = 4

# db is automatically closed when leaving the with statement.

Voir aussi

Module shelve

Persistence module which stores non-string data.

The individual submodules are described in the following sections.

12.5.1. dbm.gnu — GNU’s reinterpretation of dbm

Source code: Lib/dbm/gnu.py [https://github.com/python/cpython/tree/3.6/Lib/dbm/gnu.py]

This module is quite similar to the dbm module, but uses the GNU library gdbm instead to provide some additional functionality. Please note that the file formats created by dbm.gnu and dbm.ndbm are incompatible.

The dbm.gnu module provides an interface to the GNU DBM library. dbm.gnu.gdbm objects behave like mappings (dictionaries), except that keys and values are always converted to bytes before storing. Printing a gdbm object doesn’t print the keys and values, and the items() and values() methods are not supported.

exception dbm.gnu.error

Raised on dbm.gnu-specific errors, such as I/O errors. KeyError is raised for general mapping errors like specifying an incorrect key.

dbm.gnu.open(filename[, flag[, mode]])

Open a gdbm database and return a gdbm object. The filename argument is the name of the database file.

The optional flag argument can be:

Valeur

Signification

'r'

Open existing database for reading only (default)

'w'

Open existing database for reading and writing

'c'

Open database for reading and writing, creating it if it doesn’t exist

'n'

Always create a new, empty database, open for reading and writing

The following additional characters may be appended to the flag to control how the database is opened:

Valeur

Signification

'f'

Open the database in fast mode. Writes to the database will not be synchronized.

's'

Synchronized mode. This will cause changes to the database to be immediately written to the file.

'u'

Do not lock database.

Not all flags are valid for all versions of gdbm. The module constant open_flags is a string of supported flag characters. The exception error is raised if an invalid flag is specified.

The optional mode argument is the Unix mode of the file, used only when the database has to be created. It defaults to octal 0o666.

In addition to the dictionary-like methods, gdbm objects have the following methods:

gdbm.firstkey()

It’s possible to loop over every key in the database using this method and the nextkey() method. The traversal is ordered by gdbm’s internal hash values, and won’t be sorted by the key values. This method returns the starting key.

gdbm.nextkey(key)

Returns the key that follows key in the traversal. The following code prints every key in the database db, without having to create a list in memory that contains them all:

k = db.firstkey()
while k != None:
    print(k)
    k = db.nextkey(k)

gdbm.reorganize()

If you have carried out a lot of deletions and would like to shrink the space used by the gdbm file, this routine will reorganize the database. gdbm objects will not shorten the length of a database file except by using this reorganization; otherwise, deleted file space will be kept and reused as new (key, value) pairs are added.

gdbm.sync()

When the database has been opened in fast mode, this method forces any unwritten data to be written to the disk.

gdbm.close()

Close the gdbm database.

12.5.2. dbm.ndbm — Interface based on ndbm

Source code: Lib/dbm/ndbm.py [https://github.com/python/cpython/tree/3.6/Lib/dbm/ndbm.py]

The dbm.ndbm module provides an interface to the Unix « (n)dbm » library. Dbm objects behave like mappings (dictionaries), except that keys and values are always stored as bytes. Printing a dbm object doesn’t print the keys and values, and the items() and values() methods are not supported.

This module can be used with the « classic » ndbm interface or the GNU GDBM compatibility interface. On Unix, the configure script will attempt to locate the appropriate header file to simplify building this module.

exception dbm.ndbm.error

Raised on dbm.ndbm-specific errors, such as I/O errors. KeyError is raised for general mapping errors like specifying an incorrect key.

dbm.ndbm.library

Name of the ndbm implementation library used.

dbm.ndbm.open(filename[, flag[, mode]])

Open a dbm database and return a ndbm object. The filename argument is the name of the database file (without the .dir or .pag extensions).

The optional flag argument must be one of these values:

Valeur

Signification

'r'

Open existing database for reading only (default)

'w'

Open existing database for reading and writing

'c'

Open database for reading and writing, creating it if it doesn’t exist

'n'

Always create a new, empty database, open for reading and writing

The optional mode argument is the Unix mode of the file, used only when the database has to be created. It defaults to octal 0o666 (and will be modified by the prevailing umask).

In addition to the dictionary-like methods, ndbm objects provide the following method:

ndbm.close()

Close the ndbm database.

12.5.3. dbm.dumb — Portable DBM implementation

Source code: Lib/dbm/dumb.py [https://github.com/python/cpython/tree/3.6/Lib/dbm/dumb.py]

Note

The dbm.dumb module is intended as a last resort fallback for the dbm module when a more robust module is not available. The dbm.dumb module is not written for speed and is not nearly as heavily used as the other database modules.

The dbm.dumb module provides a persistent dictionary-like interface which is written entirely in Python. Unlike other modules such as dbm.gnu no external library is required. As with other persistent mappings, the keys and values are always stored as bytes.

Le module définit :

exception dbm.dumb.error

Raised on dbm.dumb-specific errors, such as I/O errors. KeyError is raised for general mapping errors like specifying an incorrect key.

dbm.dumb.open(filename[, flag[, mode]])

Open a dumbdbm database and return a dumbdbm object. The filename argument is the basename of the database file (without any specific extensions). When a dumbdbm database is created, files with .dat and .dir extensions are created.

The optional flag argument supports only the semantics of 'c' and 'n' values. Other values will default to database being always opened for update, and will be created if it does not exist.

The optional mode argument is the Unix mode of the file, used only when the database has to be created. It defaults to octal 0o666 (and will be modified by the prevailing umask).

Modifié dans la version 3.5: open() always creates a new database when the flag has the value 'n'.

Deprecated since version 3.6, will be removed in version 3.8: Creating database in 'r' and 'w' modes. Modifying database in 'r' mode.

In addition to the methods provided by the collections.abc.MutableMapping class, dumbdbm objects provide the following methods:

dumbdbm.sync()

Synchronize the on-disk directory and data files. This method is called by the Shelve.sync() method.

dumbdbm.close()

Close the dumbdbm database.

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12.6. sqlite3 — Interface DB-API 2.0 pour bases de données SQLite

Code source : Lib/sqlite3/ [https://github.com/python/cpython/tree/3.6/Lib/sqlite3/]

SQLite est une bibliothèque C qui fournit une base de données légère sur disque ne nécessitant pas de processus serveur et qui utilise une variante (non standard) du langage de requête SQL pour accéder aux données. Certaines applications peuvent utiliser SQLite pour le stockage de données internes. Il est également possible de créer une application prototype utilisant SQLite, puis de modifier le code pour utiliser une base de données plus robuste telle que PostgreSQL ou Oracle.

Le module sqlite3 a été écrit par Gerhard Häring. Il fournit une interface SQL conforme à la spécification DB-API 2.0 décrite par PEP 249 [https://www.python.org/dev/peps/pep-0249].

Pour utiliser le module, vous devez d’abord créer une Connection qui représente la base de données. Dans cet exemple, les données sont stockées dans le fichier example.db :

import sqlite3
conn = sqlite3.connect('example.db')

Vous pouvez également fournir le nom spécial :memory: pour créer une base de données dans la mémoire vive.

Une fois que vous avez une instance de Connection, vous pouvez créer un objet Cursor et appeler sa méthode execute() pour exécuter les commandes SQL :

c = conn.cursor()

# Create table
c.execute('''CREATE TABLE stocks
             (date text, trans text, symbol text, qty real, price real)''')

# Insert a row of data
c.execute("INSERT INTO stocks VALUES ('2006-01-05','BUY','RHAT',100,35.14)")

# Save (commit) the changes
conn.commit()

# We can also close the connection if we are done with it.
# Just be sure any changes have been committed or they will be lost.
conn.close()

Les données que vous avez sauvegardées sont persistantes et disponibles dans les sessions suivantes :

import sqlite3
conn = sqlite3.connect('example.db')
c = conn.cursor()

Habituellement, vos opérations SQL utilisent les valeurs de variables Python. Vous ne devez pas assembler votre requête à l’aide des opérations sur les chaînes de caractères de Python, car cela n’est pas sûr. Cela rend votre programme vulnérable à une attaque par injection SQL (voir https://xkcd.com/327/ pour un exemple amusant de ce qui peut mal tourner).

À la place, utilisez la capacité DB-API de substitution des paramètres. Placez un ? comme indicateur partout où vous voulez utiliser une valeur, puis fournissez un tuple de valeurs comme second argument de la méthode execute(). D’autres modules de base de données peuvent utiliser un espace réservé différent, tel que %s ou :1. Par exemple :

# Never do this -- insecure!
symbol = 'RHAT'
c.execute("SELECT * FROM stocks WHERE symbol = '%s'" % symbol)

# Do this instead
t = ('RHAT',)
c.execute('SELECT * FROM stocks WHERE symbol=?', t)
print(c.fetchone())

# Larger example that inserts many records at a time
purchases = [('2006-03-28', 'BUY', 'IBM', 1000, 45.00),
             ('2006-04-05', 'BUY', 'MSFT', 1000, 72.00),
             ('2006-04-06', 'SELL', 'IBM', 500, 53.00),
            ]
c.executemany('INSERT INTO stocks VALUES (?,?,?,?,?)', purchases)

Pour récupérer des données après avoir exécuté une instruction SELECT, vous pouvez considérer le curseur comme un itérateur, appeler la méthode du curseur fetchone() pour récupérer une seule ligne correspondante ou appeler fetchall() pour obtenir une liste des lignes correspondantes.

Cet exemple utilise la forme itérateur :

>>> for row in c.execute('SELECT * FROM stocks ORDER BY price'):
        print(row)

('2006-01-05', 'BUY', 'RHAT', 100, 35.14)
('2006-03-28', 'BUY', 'IBM', 1000, 45.0)
('2006-04-06', 'SELL', 'IBM', 500, 53.0)
('2006-04-05', 'BUY', 'MSFT', 1000, 72.0)

Voir aussi

https://github.com/ghaering/pysqlite

La page web de pysqlite — sqlite3 est développée sur un site tiers sous le nom pysqlite.

https://www.sqlite.org

Dans la page Web de SQLite, la documentation décrit la syntaxe et les types de données disponibles qui sont pris en charge par cette variante SQL.

http://www.w3schools.com/sql/

Tutoriel, référence et exemples pour apprendre la syntaxe SQL.

PEP 249 [https://www.python.org/dev/peps/pep-0249] — Spécifications de l’API 2.0 pour la base de données

PEP écrite par Marc-André Lemburg.

12.6.1. Fonctions et constantes du module

sqlite3.version

Le numéro de version de ce module, sous forme de chaîne. Ce n’est pas la version de la bibliothèque SQLite.

sqlite3.version_info

Le numéro de version de ce module, sous forme d’un n-uplet d’entiers. Ce n’est pas la version de la bibliothèque SQLite.

sqlite3.sqlite_version

Le numéro de version de la bibliothèque d’exécution SQLite, sous forme de chaîne.

sqlite3.sqlite_version_info

Le numéro de version de la bibliothèque d’exécution SQLite, sous forme d’entier.

sqlite3.PARSE_DECLTYPES

Cette constante est destinée à être utilisée avec le paramètre detect_types de la fonction connect().

Si elle est définie, le module sqlite3 analyse le type de donnée déclarée pour chaque colonne. Il déduit le type du premier mot de la déclaration, par exemple de integer primary key il gardera integer, ou de number(10) il gardera number. Ensuite, pour cette colonne, il utilisera une fonction de conversion du dictionnaire des convertisseurs.

sqlite3.PARSE_COLNAMES

Cette constante est destinée à être utilisée avec le paramètre detect_types de la fonction connect().

Permet à l’interface SQLite d’analyser le nom pour chaque colonne. Il y cherchera une chaîne comme [mytype] indiquant que la colonne est de type mytype. Il essaiera de trouver une entrée mytype dans le dictionnaire, puis utilisera la fonction de conversion qui s’y trouve pour renvoyer la valeur. Le nom de colonne donnée à Cursor.description n’est alors que le premier mot du nom de la colonne, par exemple si vous utilisez 'as \"x [datetime]\"' dans votre code SQL, le nom de la colonne sera simplement x.

sqlite3.connect(database[, timeout, detect_types, isolation_level, check_same_thread, factory, cached_statements, uri])

Opens a connection to the SQLite database file database. You can use ":memory:" to open a database connection to a database that resides in RAM instead of on disk.

When a database is accessed by multiple connections, and one of the processes modifies the database, the SQLite database is locked until that transaction is committed. The timeout parameter specifies how long the connection should wait for the lock to go away until raising an exception. The default for the timeout parameter is 5.0 (five seconds).

For the isolation_level parameter, please see the isolation_level property of Connection objects.

SQLite natively supports only the types TEXT, INTEGER, REAL, BLOB and NULL. If you want to use other types you must add support for them yourself. The detect_types parameter and the using custom converters registered with the module-level register_converter() function allow you to easily do that.

detect_types defaults to 0 (i. e. off, no type detection), you can set it to any combination of PARSE_DECLTYPES and PARSE_COLNAMES to turn type detection on.

By default, check_same_thread is True and only the creating thread may use the connection. If set False, the returned connection may be shared across multiple threads. When using multiple threads with the same connection writing operations should be serialized by the user to avoid data corruption.

By default, the sqlite3 module uses its Connection class for the connect call. You can, however, subclass the Connection class and make connect() use your class instead by providing your class for the factory parameter.

Consult the section SQLite and Python types of this manual for details.

The sqlite3 module internally uses a statement cache to avoid SQL parsing overhead. If you want to explicitly set the number of statements that are cached for the connection, you can set the cached_statements parameter. The currently implemented default is to cache 100 statements.

If uri is true, database is interpreted as a URI. This allows you to specify options. For example, to open a database in read-only mode you can use:

db = sqlite3.connect('file:path/to/database?mode=ro', uri=True)

More information about this feature, including a list of recognized options, can be found in the SQLite URI documentation [https://www.sqlite.org/uri.html].

Modifié dans la version 3.4: Added the uri parameter.

sqlite3.register_converter(typename, callable)

Registers a callable to convert a bytestring from the database into a custom Python type. The callable will be invoked for all database values that are of the type typename. Confer the parameter detect_types of the connect() function for how the type detection works. Note that typename and the name of the type in your query are matched in case-insensitive manner.

sqlite3.register_adapter(type, callable)

Registers a callable to convert the custom Python type type into one of SQLite’s supported types. The callable callable accepts as single parameter the Python value, and must return a value of the following types: int, float, str or bytes.

sqlite3.complete_statement(sql)

Returns True if the string sql contains one or more complete SQL statements terminated by semicolons. It does not verify that the SQL is syntactically correct, only that there are no unclosed string literals and the statement is terminated by a semicolon.

This can be used to build a shell for SQLite, as in the following example:

# A minimal SQLite shell for experiments

import sqlite3

con = sqlite3.connect(":memory:")
con.isolation_level = None
cur = con.cursor()

buffer = ""

print("Enter your SQL commands to execute in sqlite3.")
print("Enter a blank line to exit.")

while True:
    line = input()
    if line == "":
        break
    buffer += line
    if sqlite3.complete_statement(buffer):
        try:
            buffer = buffer.strip()
            cur.execute(buffer)

            if buffer.lstrip().upper().startswith("SELECT"):
                print(cur.fetchall())
        except sqlite3.Error as e:
            print("An error occurred:", e.args[0])
        buffer = ""

con.close()

sqlite3.enable_callback_tracebacks(flag)

By default you will not get any tracebacks in user-defined functions, aggregates, converters, authorizer callbacks etc. If you want to debug them, you can call this function with flag set to True. Afterwards, you will get tracebacks from callbacks on sys.stderr. Use False to disable the feature again.

12.6.2. Objets de connexions

class sqlite3.Connection

A SQLite database connection has the following attributes and methods:

isolation_level

Get or set the current default isolation level. None for autocommit mode or one of « DEFERRED », « IMMEDIATE » or « EXCLUSIVE ». See section Controlling Transactions for a more detailed explanation.

in_transaction

True if a transaction is active (there are uncommitted changes), False otherwise. Read-only attribute.

Nouveau dans la version 3.2.

cursor(factory=Cursor)

The cursor method accepts a single optional parameter factory. If supplied, this must be a callable returning an instance of Cursor or its subclasses.

commit()

This method commits the current transaction. If you don’t call this method, anything you did since the last call to commit() is not visible from other database connections. If you wonder why you don’t see the data you’ve written to the database, please check you didn’t forget to call this method.

rollback()

This method rolls back any changes to the database since the last call to commit().

close()

This closes the database connection. Note that this does not automatically call commit(). If you just close your database connection without calling commit() first, your changes will be lost!

execute(sql[, parameters])

This is a nonstandard shortcut that creates a cursor object by calling the cursor() method, calls the cursor’s execute() method with the parameters given, and returns the cursor.

executemany(sql[, parameters])

This is a nonstandard shortcut that creates a cursor object by calling the cursor() method, calls the cursor’s executemany() method with the parameters given, and returns the cursor.

executescript(sql_script)

This is a nonstandard shortcut that creates a cursor object by calling the cursor() method, calls the cursor’s executescript() method with the given sql_script, and returns the cursor.

create_function(name, num_params, func)

Creates a user-defined function that you can later use from within SQL statements under the function name name. num_params is the number of parameters the function accepts (if num_params is -1, the function may take any number of arguments), and func is a Python callable that is called as the SQL function.

The function can return any of the types supported by SQLite: bytes, str, int, float and None.

Exemple :

import sqlite3
import hashlib

def md5sum(t):
    return hashlib.md5(t).hexdigest()

con = sqlite3.connect(":memory:")
con.create_function("md5", 1, md5sum)
cur = con.cursor()
cur.execute("select md5(?)", (b"foo",))
print(cur.fetchone()[0])

create_aggregate(name, num_params, aggregate_class)

Creates a user-defined aggregate function.

The aggregate class must implement a step method, which accepts the number of parameters num_params (if num_params is -1, the function may take any number of arguments), and a finalize method which will return the final result of the aggregate.

The finalize method can return any of the types supported by SQLite: bytes, str, int, float and None.

Exemple :

import sqlite3

class MySum:
    def __init__(self):
        self.count = 0

    def step(self, value):
        self.count += value

    def finalize(self):
        return self.count

con = sqlite3.connect(":memory:")
con.create_aggregate("mysum", 1, MySum)
cur = con.cursor()
cur.execute("create table test(i)")
cur.execute("insert into test(i) values (1)")
cur.execute("insert into test(i) values (2)")
cur.execute("select mysum(i) from test")
print(cur.fetchone()[0])

create_collation(name, callable)

Creates a collation with the specified name and callable. The callable will be passed two string arguments. It should return -1 if the first is ordered lower than the second, 0 if they are ordered equal and 1 if the first is ordered higher than the second. Note that this controls sorting (ORDER BY in SQL) so your comparisons don’t affect other SQL operations.

Note that the callable will get its parameters as Python bytestrings, which will normally be encoded in UTF-8.

The following example shows a custom collation that sorts « the wrong way »:

import sqlite3

def collate_reverse(string1, string2):
    if string1 == string2:
        return 0
    elif string1 < string2:
        return 1
    else:
        return -1

con = sqlite3.connect(":memory:")
con.create_collation("reverse", collate_reverse)

cur = con.cursor()
cur.execute("create table test(x)")
cur.executemany("insert into test(x) values (?)", [("a",), ("b",)])
cur.execute("select x from test order by x collate reverse")
for row in cur:
    print(row)
con.close()

To remove a collation, call create_collation with None as callable:

con.create_collation("reverse", None)

interrupt()

You can call this method from a different thread to abort any queries that might be executing on the connection. The query will then abort and the caller will get an exception.

set_authorizer(authorizer_callback)

This routine registers a callback. The callback is invoked for each attempt to access a column of a table in the database. The callback should return SQLITE_OK if access is allowed, SQLITE_DENY if the entire SQL statement should be aborted with an error and SQLITE_IGNORE if the column should be treated as a NULL value. These constants are available in the sqlite3 module.

The first argument to the callback signifies what kind of operation is to be authorized. The second and third argument will be arguments or None depending on the first argument. The 4th argument is the name of the database (« main », « temp », etc.) if applicable. The 5th argument is the name of the inner-most trigger or view that is responsible for the access attempt or None if this access attempt is directly from input SQL code.

Please consult the SQLite documentation about the possible values for the first argument and the meaning of the second and third argument depending on the first one. All necessary constants are available in the sqlite3 module.

set_progress_handler(handler, n)

This routine registers a callback. The callback is invoked for every n instructions of the SQLite virtual machine. This is useful if you want to get called from SQLite during long-running operations, for example to update a GUI.

If you want to clear any previously installed progress handler, call the method with None for handler.

Returning a non-zero value from the handler function will terminate the currently executing query and cause it to raise an OperationalError exception.

set_trace_callback(trace_callback)

Registers trace_callback to be called for each SQL statement that is actually executed by the SQLite backend.

The only argument passed to the callback is the statement (as string) that is being executed. The return value of the callback is ignored. Note that the backend does not only run statements passed to the Cursor.execute() methods. Other sources include the transaction management of the Python module and the execution of triggers defined in the current database.

Passing None as trace_callback will disable the trace callback.

Nouveau dans la version 3.3.

enable_load_extension(enabled)

This routine allows/disallows the SQLite engine to load SQLite extensions from shared libraries. SQLite extensions can define new functions, aggregates or whole new virtual table implementations. One well-known extension is the fulltext-search extension distributed with SQLite.

Loadable extensions are disabled by default. See 1.

Nouveau dans la version 3.2.

import sqlite3

con = sqlite3.connect(":memory:")

# enable extension loading
con.enable_load_extension(True)

# Load the fulltext search extension
con.execute("select load_extension('./fts3.so')")

# alternatively you can load the extension using an API call:
# con.load_extension("./fts3.so")

# disable extension loading again
con.enable_load_extension(False)

# example from SQLite wiki
con.execute("create virtual table recipe using fts3(name, ingredients)")
con.executescript("""
    insert into recipe (name, ingredients) values ('broccoli stew', 'broccoli peppers cheese tomatoes');
    insert into recipe (name, ingredients) values ('pumpkin stew', 'pumpkin onions garlic celery');
    insert into recipe (name, ingredients) values ('broccoli pie', 'broccoli cheese onions flour');
    insert into recipe (name, ingredients) values ('pumpkin pie', 'pumpkin sugar flour butter');
    """)
for row in con.execute("select rowid, name, ingredients from recipe where name match 'pie'"):
    print(row)

load_extension(path)

This routine loads a SQLite extension from a shared library. You have to enable extension loading with enable_load_extension() before you can use this routine.

Loadable extensions are disabled by default. See 1.

Nouveau dans la version 3.2.

row_factory

You can change this attribute to a callable that accepts the cursor and the original row as a tuple and will return the real result row. This way, you can implement more advanced ways of returning results, such as returning an object that can also access columns by name.

Exemple :

import sqlite3

def dict_factory(cursor, row):
    d = {}
    for idx, col in enumerate(cursor.description):
        d[col[0]] = row[idx]
    return d

con = sqlite3.connect(":memory:")
con.row_factory = dict_factory
cur = con.cursor()
cur.execute("select 1 as a")
print(cur.fetchone()["a"])

If returning a tuple doesn’t suffice and you want name-based access to columns, you should consider setting row_factory to the highly-optimized sqlite3.Row type. Row provides both index-based and case-insensitive name-based access to columns with almost no memory overhead. It will probably be better than your own custom dictionary-based approach or even a db_row based solution.

text_factory

Using this attribute you can control what objects are returned for the TEXT data type. By default, this attribute is set to str and the sqlite3 module will return Unicode objects for TEXT. If you want to return bytestrings instead, you can set it to bytes.

You can also set it to any other callable that accepts a single bytestring parameter and returns the resulting object.

See the following example code for illustration:

import sqlite3

con = sqlite3.connect(":memory:")
cur = con.cursor()

AUSTRIA = "\xd6sterreich"

# by default, rows are returned as Unicode
cur.execute("select ?", (AUSTRIA,))
row = cur.fetchone()
assert row[0] == AUSTRIA

# but we can make sqlite3 always return bytestrings ...
con.text_factory = bytes
cur.execute("select ?", (AUSTRIA,))
row = cur.fetchone()
assert type(row[0]) is bytes
# the bytestrings will be encoded in UTF-8, unless you stored garbage in the
# database ...
assert row[0] == AUSTRIA.encode("utf-8")

# we can also implement a custom text_factory ...
# here we implement one that appends "foo" to all strings
con.text_factory = lambda x: x.decode("utf-8") + "foo"
cur.execute("select ?", ("bar",))
row = cur.fetchone()
assert row[0] == "barfoo"

total_changes

Returns the total number of database rows that have been modified, inserted, or deleted since the database connection was opened.

iterdump()

Returns an iterator to dump the database in an SQL text format. Useful when saving an in-memory database for later restoration. This function provides the same capabilities as the .dump command in the sqlite3 shell.

Exemple :

# Convert file existing_db.db to SQL dump file dump.sql
import sqlite3

con = sqlite3.connect('existing_db.db')
with open('dump.sql', 'w') as f:
    for line in con.iterdump():
        f.write('%s\n' % line)

12.6.3. Cursor Objects

class sqlite3.Cursor

A Cursor instance has the following attributes and methods.

execute(sql[, parameters])

Executes an SQL statement. The SQL statement may be parameterized (i. e. placeholders instead of SQL literals). The sqlite3 module supports two kinds of placeholders: question marks (qmark style) and named placeholders (named style).

Here’s an example of both styles:

import sqlite3

con = sqlite3.connect(":memory:")
cur = con.cursor()
cur.execute("create table people (name_last, age)")

who = "Yeltsin"
age = 72

# This is the qmark style:
cur.execute("insert into people values (?, ?)", (who, age))

# And this is the named style:
cur.execute("select * from people where name_last=:who and age=:age", {"who": who, "age": age})

print(cur.fetchone())

execute() will only execute a single SQL statement. If you try to execute more than one statement with it, it will raise a Warning. Use executescript() if you want to execute multiple SQL statements with one call.

executemany(sql, seq_of_parameters)

Executes an SQL command against all parameter sequences or mappings found in the sequence seq_of_parameters. The sqlite3 module also allows using an iterator yielding parameters instead of a sequence.

import sqlite3

class IterChars:
    def __init__(self):
        self.count = ord('a')

    def __iter__(self):
        return self

    def __next__(self):
        if self.count > ord('z'):
            raise StopIteration
        self.count += 1
        return (chr(self.count - 1),) # this is a 1-tuple

con = sqlite3.connect(":memory:")
cur = con.cursor()
cur.execute("create table characters(c)")

theIter = IterChars()
cur.executemany("insert into characters(c) values (?)", theIter)

cur.execute("select c from characters")
print(cur.fetchall())

Here’s a shorter example using a generator:

import sqlite3
import string

def char_generator():
    for c in string.ascii_lowercase:
        yield (c,)

con = sqlite3.connect(":memory:")
cur = con.cursor()
cur.execute("create table characters(c)")

cur.executemany("insert into characters(c) values (?)", char_generator())

cur.execute("select c from characters")
print(cur.fetchall())

executescript(sql_script)

This is a nonstandard convenience method for executing multiple SQL statements at once. It issues a COMMIT statement first, then executes the SQL script it gets as a parameter.

sql_script can be an instance of str.

Exemple :

import sqlite3

con = sqlite3.connect(":memory:")
cur = con.cursor()
cur.executescript("""
    create table person(
        firstname,
        lastname,
        age
    );

    create table book(
        title,
        author,
        published
    );

    insert into book(title, author, published)
    values (
        'Dirk Gently''s Holistic Detective Agency',
        'Douglas Adams',
        1987
    );
    """)

fetchone()

Fetches the next row of a query result set, returning a single sequence, or None when no more data is available.

fetchmany(size=cursor.arraysize)

Fetches the next set of rows of a query result, returning a list. An empty list is returned when no more rows are available.

The number of rows to fetch per call is specified by the size parameter. If it is not given, the cursor’s arraysize determines the number of rows to be fetched. The method should try to fetch as many rows as indicated by the size parameter. If this is not possible due to the specified number of rows not being available, fewer rows may be returned.

Note there are performance considerations involved with the size parameter. For optimal performance, it is usually best to use the arraysize attribute. If the size parameter is used, then it is best for it to retain the same value from one fetchmany() call to the next.

fetchall()

Fetches all (remaining) rows of a query result, returning a list. Note that the cursor’s arraysize attribute can affect the performance of this operation. An empty list is returned when no rows are available.

close()

Close the cursor now (rather than whenever __del__ is called).

The cursor will be unusable from this point forward; a ProgrammingError exception will be raised if any operation is attempted with the cursor.

rowcount

Although the Cursor class of the sqlite3 module implements this attribute, the database engine’s own support for the determination of « rows affected »/ »rows selected » is quirky.

For executemany() statements, the number of modifications are summed up into rowcount.

As required by the Python DB API Spec, the rowcount attribute « is -1 in case no executeXX() has been performed on the cursor or the rowcount of the last operation is not determinable by the interface ». This includes SELECT statements because we cannot determine the number of rows a query produced until all rows were fetched.

With SQLite versions before 3.6.5, rowcount is set to 0 if you make a DELETE FROM table without any condition.

lastrowid

This read-only attribute provides the rowid of the last modified row. It is only set if you issued an INSERT or a REPLACE statement using the execute() method. For operations other than INSERT or REPLACE or when executemany() is called, lastrowid is set to None.

If the INSERT or REPLACE statement failed to insert the previous successful rowid is returned.

Modifié dans la version 3.6: Added support for the REPLACE statement.

arraysize

Read/write attribute that controls the number of rows returned by fetchmany(). The default value is 1 which means a single row would be fetched per call.

description

This read-only attribute provides the column names of the last query. To remain compatible with the Python DB API, it returns a 7-tuple for each column where the last six items of each tuple are None.

It is set for SELECT statements without any matching rows as well.

connection

This read-only attribute provides the SQLite database Connection used by the Cursor object. A Cursor object created by calling con.cursor() will have a connection attribute that refers to con:

>>> con = sqlite3.connect(":memory:")
>>> cur = con.cursor()
>>> cur.connection == con
True

12.6.4. Row Objects

class sqlite3.Row

A Row instance serves as a highly optimized row_factory for Connection objects. It tries to mimic a tuple in most of its features.

It supports mapping access by column name and index, iteration, representation, equality testing and len().

If two Row objects have exactly the same columns and their members are equal, they compare equal.

keys()

This method returns a list of column names. Immediately after a query, it is the first member of each tuple in Cursor.description.

Modifié dans la version 3.5: Added support of slicing.

Let’s assume we initialize a table as in the example given above:

conn = sqlite3.connect(":memory:")
c = conn.cursor()
c.execute('''create table stocks
(date text, trans text, symbol text,
 qty real, price real)''')
c.execute("""insert into stocks
          values ('2006-01-05','BUY','RHAT',100,35.14)""")
conn.commit()
c.close()

Now we plug Row in:

>>> conn.row_factory = sqlite3.Row
>>> c = conn.cursor()
>>> c.execute('select * from stocks')
<sqlite3.Cursor object at 0x7f4e7dd8fa80>
>>> r = c.fetchone()
>>> type(r)
<class 'sqlite3.Row'>
>>> tuple(r)
('2006-01-05', 'BUY', 'RHAT', 100.0, 35.14)
>>> len(r)
5
>>> r[2]
'RHAT'
>>> r.keys()
['date', 'trans', 'symbol', 'qty', 'price']
>>> r['qty']
100.0
>>> for member in r:
...     print(member)
...
2006-01-05
BUY
RHAT
100.0
35.14

12.6.5. Exceptions

exception sqlite3.Warning

A subclass of Exception.

exception sqlite3.Error

The base class of the other exceptions in this module. It is a subclass of Exception.

exception sqlite3.DatabaseError

Exception raised for errors that are related to the database.

exception sqlite3.IntegrityError

Exception raised when the relational integrity of the database is affected, e.g. a foreign key check fails. It is a subclass of DatabaseError.

exception sqlite3.ProgrammingError

Exception raised for programming errors, e.g. table not found or already exists, syntax error in the SQL statement, wrong number of parameters specified, etc. It is a subclass of DatabaseError.

exception sqlite3.OperationalError

Exception raised for errors that are related to the database’s operation and not necessarily under the control of the programmer, e.g. an unexpected disconnect occurs, the data source name is not found, a transaction could not be processed, etc. It is a subclass of DatabaseError.

exception sqlite3.NotSupportedError

Exception raised in case a method or database API was used which is not supported by the database, e.g. calling the rollback() method on a connection that does not support transaction or has transactions turned off. It is a subclass of DatabaseError.

12.6.6. SQLite and Python types

12.6.6.1. Introduction

SQLite natively supports the following types: NULL, INTEGER, REAL, TEXT, BLOB.

The following Python types can thus be sent to SQLite without any problem:

Type Python

SQLite type

None

NULL

int

INTEGER

float

REAL

str

TEXT

bytes

BLOB

This is how SQLite types are converted to Python types by default:

SQLite type

Type Python

NULL

None

INTEGER

int

REAL

float

TEXT

depends on text_factory, str by default

BLOB

bytes

The type system of the sqlite3 module is extensible in two ways: you can store additional Python types in a SQLite database via object adaptation, and you can let the sqlite3 module convert SQLite types to different Python types via converters.

12.6.6.2. Using adapters to store additional Python types in SQLite databases

As described before, SQLite supports only a limited set of types natively. To use other Python types with SQLite, you must adapt them to one of the sqlite3 module’s supported types for SQLite: one of NoneType, int, float, str, bytes.

There are two ways to enable the sqlite3 module to adapt a custom Python type to one of the supported ones.

12.6.6.2.1. Letting your object adapt itself

This is a good approach if you write the class yourself. Let’s suppose you have a class like this:

class Point:
    def __init__(self, x, y):
        self.x, self.y = x, y

Now you want to store the point in a single SQLite column. First you’ll have to choose one of the supported types first to be used for representing the point. Let’s just use str and separate the coordinates using a semicolon. Then you need to give your class a method __conform__(self, protocol) which must return the converted value. The parameter protocol will be PrepareProtocol.

import sqlite3

class Point:
    def __init__(self, x, y):
        self.x, self.y = x, y

    def __conform__(self, protocol):
        if protocol is sqlite3.PrepareProtocol:
            return "%f;%f" % (self.x, self.y)

con = sqlite3.connect(":memory:")
cur = con.cursor()

p = Point(4.0, -3.2)
cur.execute("select ?", (p,))
print(cur.fetchone()[0])

12.6.6.2.2. Registering an adapter callable

The other possibility is to create a function that converts the type to the string representation and register the function with register_adapter().

import sqlite3

class Point:
    def __init__(self, x, y):
        self.x, self.y = x, y

def adapt_point(point):
    return "%f;%f" % (point.x, point.y)

sqlite3.register_adapter(Point, adapt_point)

con = sqlite3.connect(":memory:")
cur = con.cursor()

p = Point(4.0, -3.2)
cur.execute("select ?", (p,))
print(cur.fetchone()[0])

The sqlite3 module has two default adapters for Python’s built-in datetime.date and datetime.datetime types. Now let’s suppose we want to store datetime.datetime objects not in ISO representation, but as a Unix timestamp.

import sqlite3
import datetime
import time

def adapt_datetime(ts):
    return time.mktime(ts.timetuple())

sqlite3.register_adapter(datetime.datetime, adapt_datetime)

con = sqlite3.connect(":memory:")
cur = con.cursor()

now = datetime.datetime.now()
cur.execute("select ?", (now,))
print(cur.fetchone()[0])

12.6.6.3. Converting SQLite values to custom Python types

Writing an adapter lets you send custom Python types to SQLite. But to make it really useful we need to make the Python to SQLite to Python roundtrip work.

Enter converters.

Let’s go back to the Point class. We stored the x and y coordinates separated via semicolons as strings in SQLite.

First, we’ll define a converter function that accepts the string as a parameter and constructs a Point object from it.

Note

Converter functions always get called with a bytes object, no matter under which data type you sent the value to SQLite.

def convert_point(s):
    x, y = map(float, s.split(b";"))
    return Point(x, y)

Now you need to make the sqlite3 module know that what you select from the database is actually a point. There are two ways of doing this:

Implicitly via the declared type

Explicitly via the column name

Both ways are described in section Fonctions et constantes du module, in the entries for the constants PARSE_DECLTYPES and PARSE_COLNAMES.

The following example illustrates both approaches.

import sqlite3

class Point:
    def __init__(self, x, y):
        self.x, self.y = x, y

    def __repr__(self):
        return "(%f;%f)" % (self.x, self.y)

def adapt_point(point):
    return ("%f;%f" % (point.x, point.y)).encode('ascii')

def convert_point(s):
    x, y = list(map(float, s.split(b";")))
    return Point(x, y)

# Register the adapter
sqlite3.register_adapter(Point, adapt_point)

# Register the converter
sqlite3.register_converter("point", convert_point)

p = Point(4.0, -3.2)

#########################
# 1) Using declared types
con = sqlite3.connect(":memory:", detect_types=sqlite3.PARSE_DECLTYPES)
cur = con.cursor()
cur.execute("create table test(p point)")

cur.execute("insert into test(p) values (?)", (p,))
cur.execute("select p from test")
print("with declared types:", cur.fetchone()[0])
cur.close()
con.close()

#######################
# 1) Using column names
con = sqlite3.connect(":memory:", detect_types=sqlite3.PARSE_COLNAMES)
cur = con.cursor()
cur.execute("create table test(p)")

cur.execute("insert into test(p) values (?)", (p,))
cur.execute('select p as "p [point]" from test')
print("with column names:", cur.fetchone()[0])
cur.close()
con.close()

12.6.6.4. Default adapters and converters

There are default adapters for the date and datetime types in the datetime module. They will be sent as ISO dates/ISO timestamps to SQLite.

The default converters are registered under the name « date » for datetime.date and under the name « timestamp » for datetime.datetime.

This way, you can use date/timestamps from Python without any additional fiddling in most cases. The format of the adapters is also compatible with the experimental SQLite date/time functions.

The following example demonstrates this.

import sqlite3
import datetime

con = sqlite3.connect(":memory:", detect_types=sqlite3.PARSE_DECLTYPES|sqlite3.PARSE_COLNAMES)
cur = con.cursor()
cur.execute("create table test(d date, ts timestamp)")

today = datetime.date.today()
now = datetime.datetime.now()

cur.execute("insert into test(d, ts) values (?, ?)", (today, now))
cur.execute("select d, ts from test")
row = cur.fetchone()
print(today, "=>", row[0], type(row[0]))
print(now, "=>", row[1], type(row[1]))

cur.execute('select current_date as "d [date]", current_timestamp as "ts [timestamp]"')
row = cur.fetchone()
print("current_date", row[0], type(row[0]))
print("current_timestamp", row[1], type(row[1]))

If a timestamp stored in SQLite has a fractional part longer than 6 numbers, its value will be truncated to microsecond precision by the timestamp converter.

12.6.7. Controlling Transactions

The underlying sqlite3 library operates in autocommit mode by default, but the Python sqlite3 module by default does not.

autocommit mode means that statements that modify the database take effect immediately. A BEGIN or SAVEPOINT statement disables autocommit mode, and a COMMIT, a ROLLBACK, or a RELEASE that ends the outermost transaction, turns autocommit mode back on.

The Python sqlite3 module by default issues a BEGIN statement implicitly before a Data Modification Language (DML) statement (i.e. INSERT/UPDATE/DELETE/REPLACE).

You can control which kind of BEGIN statements sqlite3 implicitly executes via the isolation_level parameter to the connect() call, or via the isolation_level property of connections. If you specify no isolation_level, a plain BEGIN is used, which is equivalent to specifying DEFERRED. Other possible values are IMMEDIATE and EXCLUSIVE.

You can disable the sqlite3 module’s implicit transaction management by setting isolation_level to None. This will leave the underlying sqlite3 library operating in autocommit mode. You can then completely control the transaction state by explicitly issuing BEGIN, ROLLBACK, SAVEPOINT, and RELEASE statements in your code.

Modifié dans la version 3.6: sqlite3 used to implicitly commit an open transaction before DDL statements. This is no longer the case.

12.6.8. Using sqlite3 efficiently

12.6.8.1. Using shortcut methods

Using the nonstandard execute(), executemany() and executescript() methods of the Connection object, your code can be written more concisely because you don’t have to create the (often superfluous) Cursor objects explicitly. Instead, the Cursor objects are created implicitly and these shortcut methods return the cursor objects. This way, you can execute a SELECT statement and iterate over it directly using only a single call on the Connection object.

import sqlite3

persons = [
    ("Hugo", "Boss"),
    ("Calvin", "Klein")
    ]

con = sqlite3.connect(":memory:")

# Create the table
con.execute("create table person(firstname, lastname)")

# Fill the table
con.executemany("insert into person(firstname, lastname) values (?, ?)", persons)

# Print the table contents
for row in con.execute("select firstname, lastname from person"):
    print(row)

print("I just deleted", con.execute("delete from person").rowcount, "rows")

12.6.8.2. Accessing columns by name instead of by index

One useful feature of the sqlite3 module is the built-in sqlite3.Row class designed to be used as a row factory.

Rows wrapped with this class can be accessed both by index (like tuples) and case-insensitively by name:

import sqlite3

con = sqlite3.connect(":memory:")
con.row_factory = sqlite3.Row

cur = con.cursor()
cur.execute("select 'John' as name, 42 as age")
for row in cur:
    assert row[0] == row["name"]
    assert row["name"] == row["nAmE"]
    assert row[1] == row["age"]
    assert row[1] == row["AgE"]

12.6.8.3. Using the connection as a context manager

Connection objects can be used as context managers that automatically commit or rollback transactions. In the event of an exception, the transaction is rolled back; otherwise, the transaction is committed:

import sqlite3

con = sqlite3.connect(":memory:")
con.execute("create table person (id integer primary key, firstname varchar unique)")

# Successful, con.commit() is called automatically afterwards
with con:
    con.execute("insert into person(firstname) values (?)", ("Joe",))

# con.rollback() is called after the with block finishes with an exception, the
# exception is still raised and must be caught
try:
    with con:
        con.execute("insert into person(firstname) values (?)", ("Joe",))
except sqlite3.IntegrityError:
    print("couldn't add Joe twice")

12.6.9. Common issues

12.6.9.1. Fils d’exécution

Older SQLite versions had issues with sharing connections between threads. That’s why the Python module disallows sharing connections and cursors between threads. If you still try to do so, you will get an exception at runtime.

The only exception is calling the interrupt() method, which only makes sense to call from a different thread.

Notes

1(1,2)

The sqlite3 module is not built with loadable extension support by default, because some platforms (notably Mac OS X) have SQLite libraries which are compiled without this feature. To get loadable extension support, you must pass –enable-loadable-sqlite-extensions to configure.

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13. Compression de donnée et archivage

Les modules documentés dans ce chapitre implémentent les algorithmes de compression zlib, gzip, bzip2 et lzma, ainsi que la création d’archives ZIP et tar. Voir aussi Archiving operations fourni par le module shutil.

13.1. zlib — Compression compatible avec gzip

13.2. gzip — Support pour les fichiers gzip

13.2.1. Exemples d’utilisation

13.3. bz2 — Prise en charge de la compression bzip2

13.3.1. (Dé)compression de fichiers

13.3.2. (Dé)compression incrémentielle

13.3.3. (Dé)compression en une fois

13.4. lzma — Compression via l’algorithme LZMA

13.4.1. Lire et écrire des fichiers compressés

13.4.2. Compresser et décompresser une donnée en mémoire

13.4.3. Divers

13.4.4. Préciser des chaînes de filtre personnalisées

13.4.5. Exemples

13.5. zipfile — Travailler avec des archives ZIP

13.5.1. Objets ZipFile

13.5.2. Objets PyZipFile

13.5.3. Objets ZipInfo

13.5.4. Interface en ligne de commande

13.5.4.1. Options de la ligne de commande

13.6. tarfile — Read and write tar archive files

13.6.1. TarFile Objects

13.6.2. TarInfo Objects

13.6.3. Interface en ligne de commande

13.6.3.1. Options de la ligne de commande

13.6.4. Exemples

13.6.5. Supported tar formats

13.6.6. Unicode issues

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13.1. zlib — Compression compatible avec gzip

Pour des applications nécessitant de compresser des données, les fonctions de ce module permettent la compression et la décompression via la bibliothèque zlib. La bibliothèque zlib a sa propre page web sur http://www.zlib.net. Il existe des incompatibilités connues entre le module Python et les versions de la bibliothèque zlib plus anciennes que la 1.1.3 ; 1.1.3 contient des failles de sécurité et nous recommandons d’utiliser plutôt la version 1.14 ou plus récente.

Les fonctions zlib recèlent de nombreuses options et il est nécessaire de suivre un ordre précis. Cette documentation n’a pas pour but de couvrir la globalité des possibilités. Aussi, veuillez consulter le manuel zlib en ligne sur http://www.zlib.net/manual.html pour compléter davantage son utilisation.

Pour lire ou écrire des fichiers .gz veuillez consulter le module gzip.

Les exceptions et fonctions disponibles dans ce module sont :

exception zlib.error

Exception levée lors d’erreurs de compression et de décompression.

zlib.adler32(data[, value])

Calcule une somme de contrôle Adler-32 de data (une somme de contrôle Adler-32 est aussi fiable qu’un CRC32 mais peut être calculée bien plus rapidement). Le résultat produit est un entier non signé de 32-bit. Si value est défini, il devient la valeur initiale de la somme de contrôle ; sinon une valeur par défaut de 1 est utilisée. Définir value permet de calculer une somme de contrôle continue pendant la concaténation de plusieurs entrées. Cet algorithme n’a aucune garantie cryptographique puissante, et ne doit pas être utilisé ni pour l’authentification, ni pour des signatures numériques. Conçu comme un algorithme de somme de contrôle, il n’est pas adapté pour une utilisation sous forme de clé de hachage générique.

Modifié dans la version 3.0: Renvoie une valeur non-signée. Pour produire la même valeur avec toutes les versions de Python sur différentes plateformes, utilisez adler32(data) & 0xffffffff.

zlib.compress(data, level=-1)

Compresse les octets contenus dans data, renvoie un objet bytes contenant les données compressées. level permet d’ajuster le niveau de compression, ce doit être un nombre entier compris entre 0 et 9 ou -1 ; 1 étant plus rapide et procède à une compression légère, 9 est plus lent mais compresse plus fortement. 0 n’effectue aucune compression. La valeur par défaut est -1 (Z_DEFAULT_COMPRESSION). Z_DEFAULT_COMPRESSION donne une valeur par défaut proposant un équilibre entre vitesse et taux de compression (actuellement équivalente à 6). Si une erreur surgit, l’exception error est levée.

Modifié dans la version 3.6: level peut maintenant être passé par son nom.

zlib.compressobj(level=-1, method=DEFLATED, wbits=MAX_WBITS, memLevel=DEF_MEM_LEVEL, strategy=Z_DEFAULT_STRATEGY[, zdict])

Renvoie un objet « compresseur », à utiliser pour compresser des flux de données qui ne peuvent pas être stockés entièrement en mémoire.

level est le taux de compression – un entier compris entre 0 et 9 ou -1. La valeur 1 est la plus rapide avec taux de compression minimal, tandis que la valeur 9 est la plus lente mais produit une compression maximale. 0 ne produit aucune compression. La valeur par défaut est -1 (Z_DEFAULT_COMPRESSION). La constante Z_DEFAULT_COMPRESSION équivaut à un bon compromis par défaut entre rapidité et bonne compression (valeur équivalente au niveau 6).

method définit l’algorithme de compression. Pour le moment, la seule valeur acceptée est DEFLATED.

L’argument wbits contrôle la taille du tampon d’historique (« window size ») utilisé lors de la compression, et si un en-tête et un bloc final seront inclus. Il accepte plusieurs intervalles de valeurs, et vaut 15 (MAX_WBITS) par défaut :

De +9 à +15 : le logarithme binaire de la taille du tampon, par conséquent compris entre 512 et 32 768. Des valeurs plus grandes produisent de meilleures compressions aux dépens d’une utilisation mémoire plus grande. Le résultat final inclus des en-têtes et des blocs spécifiques à zlib.

De -9 à -15 : utilise la valeur absolue de wbits comme logarithme binaire de la taille du tampon, et ne produit pas d’entêtes ni de bloc final.

De +25 à +31 = 16 + (9 à 15) : utilise les 4 bits de poids faible comme logarithme binaire de la taille du tampon, tout en incluant un entête gzip et une somme de contrôle finale.

L’argument memLevel permet d’ajuster la quantité de mémoire utilisée pour stocker l’état interne de la compression. Les valeurs valides sont comprises entre 1 et 9. Des valeurs plus élevées occupent davantage de mémoire, mais sont plus rapides et produisent des sorties plus compressées.

strategy permet d’ajuster l’algorithme de compression. Les valeurs possibles sont Z_DEFAULT_STRATEGY, Z_FILTERED, et Z_HUFFMAN_ONLY, Z_RLE (zlib 1.2.0.1) et Z_FIXED (zlib 1.2.2.2).

zdict est un dictionnaire de compression prédéfini. C’est une séquence d’octets (tel qu’un objet bytes) contenant des sous-séquences attendues régulièrement dans les données à compresser. Les sous-séquences les plus fréquentes sont à placer à la fin du dictionnaire.

Modifié dans la version 3.3: Ajout du paramètre zdict.

zlib.crc32(data[, value])

Calcule la somme de contrôle CRC (Cyclic Redundancy Check en anglais) de l’argument data. Il renvoie un entier non signé de 32 bits. Si l’argument value est présent, il permet de définir la valeur de départ de la somme de contrôle. Sinon, la valeur par défaut est 0. L’argument value permet de calculer la somme de contrôle glissante d’une concaténation de données. L’algorithme n’est pas fort d’un point de vue cryptographique, et ne doit pas être utilisé pour l’authentification ou des signatures numériques. Cet algorithme a été conçu pour être exploité comme un algorithme de somme de contrôle, ce n’est pas un algorithme de hachage générique.

Modifié dans la version 3.0: Renvoie une valeur non-signée. Pour obtenir la même valeur sur n’importe quelle version de Python et n’importe quelle plateforme, utilisez crc32(data) & 0xffffffff.

zlib.decompress(data, wbits=MAX_WBITS, bufsize=DEF_BUF_SIZE)

Décompresse les octets de data, renvoyant un objet bytes contenant les données décompressées. Le paramètre wbits dépend du format des données compressées, et est abordé plus loin. Si l’argument bufsize est défini, il est utilisé comme taille initiale du tampon de sortie. En cas d’erreur, l’exception error est levée.

L’argument wbits contrôle la taille du tampon d’historique (« window size ») utilisé lors de la compression, et si un en-tête et un bloc final sont attendus. Similaire au paramètre de compressobj(), mais accepte une gamme plus large de valeurs :

De +8 à +15 : logarithme binaire pour la taille du tampon. L’entrée doit contenir un en-tête et un bloc zlib.

0 : détermine automatiquement la taille du tampon à partir de l’en-tête zlib. Géré uniquement depuis zlib 1.2.3.5.

De -8 à -15 : utilise la valeur absolue de wbits comme logarithme binaire pour la taille du tampon. L’entrée doit être un flux brut, sans en-tête ni bloc final.

De +24 à +31 = 16 + (8 à 15) : utilise les 4 de poids faible comme logarithme binaire pour la taille du tampon. L’entrée doit contenir un en-tête gzip et son bloc final.

De +40 à +47 = 32 + (8 à 15) : utilise les 4 bits de poids faible comme logarithme binaire pour la taille du tampon, et accepte automatiquement les formats zlib ou gzip.

Lors de la décompression d’un flux, la taille du tampon ne doit pas être inférieure à la taille initialement utilisée pour compresser le flux. L’utilisation d’une valeur trop petite peut déclencher une exception error. La valeur par défaut wbits correspond à une taille élevée du tampon et nécessite d’y adjoindre un en-tête zlib et son bloc final.

L’argument bufsize correspond à la taille initiale du tampon utilisé pour contenir les données décompressées. Si plus d’espace est nécessaire, la taille du tampon sera augmentée au besoin, donc vous n’avez pas besoin de deviner la valeur exacte. Un réglage précis n’économisera que quelques appels à malloc().

Modifié dans la version 3.6: wbits et bufsize peuvent être utilisés comme arguments nommés.

zlib.decompressobj(wbits=MAX_WBITS[, zdict])

Renvoie un objet « décompresseur », à utiliser pour décompresser des flux de données qui ne rentrent pas entièrement en mémoire.

Le paramètre wbits contrôle la taille du tampon, et détermine quel format d’en-tête et de bloc sont prévus. Il a la même signification que décrit pour decompress().

Le paramètre zdict définit un dictionnaire de compression prédéfini. S’il est fourni, il doit être identique au dictionnaire utilisé par le compresseur, à l’origine des données à décompresser.

Note

Si zdict est un objet modifiable (tel qu’un bytearray, par exemple), vous ne devez pas modifier son contenu entre l’appel à la fonction decompressobj() et le premier appel à la méthode decompress() du décompresseur.

Modifié dans la version 3.3: Ajout du paramètre zdict.

Les objets de compression gèrent les méthodes suivantes :

Compress.compress(data)

Compresse data et renvoie au moins une partie des données compressées sous forme d’objet bytes. Ces données doivent être concaténées à la suite des appels précédant à compress(). Certaines entrées peuvent être conservées dans des tampons internes pour un traitement ultérieur.

Compress.flush([mode])

Toutes les entrées mises en attente sont traitées et un objet bytes contenant la sortie des données compressées restantes est renvoyé. L’argument mode accepte l’une des constantes suivantes : Z_NO_FLUSH, Z_PARTIAL_FLUSH, Z_SYNC_FLUSH, Z_FULL_FLUSH, Z_BLOCK (zlib 1.2.3.4), et Z_FINISH, par défaut Z_FINISH. Sauf Z_FINISH, toutes les constantes permettent de compresser d’autres chaînes d’octets, tandis que Z_FINISH finalise le flux compressé et bloque toute autre tentative de compression. Suite à l’appel de la méthode flush() avec l’argument mode défini à Z_FINISH, la méthode compress() ne peut plus être rappelée. Il ne reste plus qu’à supprimer l’objet.

Compress.copy()

Renvoie une copie de l’objet « compresseur ». Utile pour compresser efficacement un ensemble de données qui partagent un préfixe initial commun.

Les objets décompresseurs prennent en charge les méthodes et attributs suivants :

Decompress.unused_data

Un objet bytes contenant tous les octets restants après les données compressées. Il vaut donc b"" tant que des données compressées sont disponibles. Si toute la chaîne d’octets ne contient que des données compressées, il vaut toujours b"", un objet bytes vide.

Decompress.unconsumed_tail

Un objet bytes contenant toutes les données non-traitées par le dernier appel à la méthode decompress(), à cause d’un dépassement de la limite du tampon de données décompressées. Ces données n’ont pas encore été traitées par la bibliothèque zlib, vous devez donc les envoyer (potentiellement en y concaténant encore des données) par un appel à la méthode decompress() pour obtenir une sortie correcte.

Decompress.eof

Booléen qui signale si la fin du flux compressé est atteint.

Ceci rend possible la distinction entre un flux correctement compressé et un flux incomplet.

Nouveau dans la version 3.3.

Decompress.decompress(data, max_length=0)

Décompresse data, renvoie un objet bytes, contenant au moins une partie des données décompressées. Ce résultat doit être concaténé aux résultats des appels précédents à decompress(). Des données d’entrée peuvent être conservées dans les tampons internes pour un traitement ultérieur.

Si le paramètre optionnel max_length est différent de zéro alors la valeur renvoyée n’est pas plus grande que max_length. Cela peut amener à une décompression partielle. Les données non-encore décompressées sont stockées dans l’attribut unconsumed_tail. Cette chaîne d’octets doit être transmise à un appel ultérieur à decompress(). Si max_length vaut zéro, la totalité de l’entrée est décompressée, et l’attribut unconsumed_tail reste vide.

Modifié dans la version 3.6: max_length peut être utilisé comme un argument nommé.

Decompress.flush([length])

Toutes les entrées en attente sont traitées, et un objet bytes est renvoyé, contenant le reste des données à décompresser. Après l’appel à flush(), la méthode decompress() ne peut pas être rappelée. Il ne reste qu’à détruire l’objet.

Le paramètre optionnel length définit la taille initiale du tampon de sortie.

Decompress.copy()

Renvoie une copie du décompresseur. Vous pouvez l’utiliser pour sauvegarder l’état de la décompression en cours, afin de pouvoir revenir rapidement à cet endroit plus tard.

Des informations relatives à la version de la bibliothèque zlib utilisée sont disponibles via les constantes suivantes :

zlib.ZLIB_VERSION

Version de la bibliothèque zlib utilisée lors de la compilation du module. Elle peut être différente de la bibliothèque zlib actuellement utilisée par le système, qui est consultable par ZLIB_RUNTIME_VERSION.

zlib.ZLIB_RUNTIME_VERSION

Chaîne contenant la version de la bibliothèque zlib actuellement utilisée par l’interpréteur.

Nouveau dans la version 3.3.

Voir aussi

Module gzip

Lire et écrire des fichiers au format gzip.

http://www.zlib.net

Page officielle de la bibliothèque zlib.

http://www.zlib.net/manual.html

La documentation de zlib explique le sens et l’utilisation des nombreuses fonctions fournies par la bibliothèque.

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13.2. gzip — Support pour les fichiers gzip

Code source : Lib/gzip.py [https://github.com/python/cpython/tree/3.6/Lib/gzip.py]

Ce module fournit une interface simple pour compresser et décompresser des fichiers tout comme le font les programmes GNU gzip et gunzip.

La compression de données est fournie par le module zlib.

Le module gzip fournit la classe GzipFile ainsi que les fonctions pratiques open(), compress() et decompress(). La classe GzipFile lit et écrit des fichiers au format gzip, compressant et décompressant automatiquement les données pour qu’elles aient l’apparence d’un objet file object ordinaire.

Notez que les formats de fichier supplémentaires qui peuvent être décompressés par les programmes gzip et gunzip, comme ceux produits par le programmes compress et pack, ne sont pas gérés par ce module.

Le module définit les éléments suivants :

gzip.open(filename, mode='rb', compresslevel=9, encoding=None, errors=None, newline=None)

Ouvre un fichier compressé en gzip en mode binaire ou texte, renvoie un objet file object.

L’argument filename peut être un nom de fichier (un objet str ou bytes) ou un objet fichier existant que l’on peut lire, ou où l’on peut écrire.

L’argument mode peut-être 'r', 'rb', 'a', 'ab', 'w', 'wb', 'x' ou 'xb' pour le mode binaire ou 'rt', 'at', 'wt', ou 'xt' pour le mode texte. Le mode par défaut est 'rb'.

L’argument compresslevel est un entier de 0 à 9, comme pour le constructeur de la classe GzipFile.

En mode binaire, cette fonction est équivalente au constructeur de la classe GzipFile : GzipFile(filename, mode, compresslevel). Dans ce cas, les arguments encoding, errors et newline ne doivent pas être fournis.

En mode texte, un objet GzipFile est créé et empaqueté dans une instance de io.TextIOWrapper avec l’encodage, la gestion d’erreur et les fins de ligne spécifiés.

Modifié dans la version 3.3: Ajout de la prise en charge de filename en tant qu’objet file, du mode texte et des arguments encoding, errors et newline.

Modifié dans la version 3.4: Ajout de la prise en charge des modes 'x', 'xb' et 'xt'.

Modifié dans la version 3.6: Accepte un path-like object.

class gzip.GzipFile(filename=None, mode=None, compresslevel=9, fileobj=None, mtime=None)

Constructeur de la classe GzipFile qui simule la plupart des méthodes d’un objet file object à l’exception de la méthode truncate(). Au moins un des arguments fileobj et filename doit avoir une valeur non triviale.

La nouvelle instance de classe est basée sur fileobj qui peut être un fichier usuel, un objet io.BytesIO ou tout autre objet qui simule un fichier. fileobj est par défaut à None, dans ce cas filename est ouvert afin de fournir un objet fichier.

Quand fileobj n’est pas à None, l’argument filename est uniquement utilisé pour être inclus dans l’entête du fichier gzip, qui peut inclure le nom original du fichier décompressé. Il est par défaut défini avec le nom de fichier de fileobj s’il est discernable, sinon il est par défaut défini à une chaîne de caractères vide et dans ce cas le nom du fichier orignal n’est pas inclus dans l’entête.

L’argument mode peut-être 'r', 'rb', 'a', 'ab', 'w', 'wb', 'x', ou 'xb', selon que le fichier va être lu ou écrit. Par défaut prend la valeur du mode de fileobj si discernable ; sinon, la valeur par défaut est 'rb'.

Notez que le fichier est toujours ouvert en mode binaire. Pour ouvrir un fichier compressé en mode texte, utilisez la fonction open() (ou empaquetez votre classe GzipFile avec un io.TextIOWrapper).

L’argument compresslevel est un entier de 0 à 9 contrôlant le niveau de compression,``1`` est le plus rapide et produit la compression la plus faible et 9 est le plus rapide et produit la compression la plus élevée. 0 désactive la compression. Par défaut à 9.

L’argument mtime est un timestamp numérique optionnel à écrire dans le champ de date de dernière modification du flux durant la compression. Il ne doit être défini qu’en mode compression. S’il est omis ou None, la date courante est utilisée. Voir l’attribut mtime pour plus de détails.

Appeler la méthode close() d’un objet GzipFile ne ferme pas fileobj, puisque vous pourriez avoir besoin d’ajouter des informations après les données compressées. Cela vous permet aussi de passer un objet io.BytesIO ouvert en écriture en tant que fileobj et récupérer le tampon mémoire final en utilisant la méthode getvalue() de l’objet io.BytesIO.

:La classe GzipFile implémente l’interface io.BufferedIOBase, incluant l’itération, la déclaration with. La méthode truncate() est la seule non implémentée.

La classe GzipFile fournit aussi la méthode et l’attribut suivant :

peek(n)

Lit n octets non compressés sans avancer la position dans le fichier. Au plus une seule lecture sur le flux compressé est faite pour satisfaire l’appel. Le nombre d’octets retournés peut être supérieur ou inférieur au nombre demandé.

Note

Bien que l’appel à peek() ne change pas la position dans le fichier de l’objet GzipFile, il peut changer la position de l’objet de fichier sous-jacent (par exemple, si l’instance de GzipFile a été construite avec le paramètre fileobj).

Nouveau dans la version 3.2.

mtime

Lors de la décompression, la valeur du champ de date de dernière modification dans le dernier en-tête lu peut être lue à partir de cet attribut, comme un entier. La valeur initiale avant lecture d’un en-tête est None.

Tous les flux compressés en gzip doivent contenir ce champ timestamp. Certains programmes, comme gunzip, utilisent ce timestamp. Ce format est le même que la valeur retour de time.time() et l’attribut st_mtime de l’objet retourné par os.stat().

Modifié dans la version 3.1: Ajout de la prise en charge du mot-clef with, ainsi que de l’argument mtime du constructeur et de l’attribut mtime.

Modifié dans la version 3.2: Ajout de la prise en charge des fichiers non navigables ou commençant par des octets nuls.

Modifié dans la version 3.3: La méthode io.BufferedIOBase.read1() est désormais implémentée.

Modifié dans la version 3.4: Ajout de la prise en charge des modes 'x' et 'xb'.

Modifié dans la version 3.5: Ajout de la prise en charge de l’écriture d’objets bytes-like objects arbitraires. La méthode read() accepte désormais un argument de valeur None.

Modifié dans la version 3.6: Accepte un path-like object.

gzip.compress(data, compresslevel=9)

Compresse les données data, renvoie un objet bytes contenant les données compressées. L’argument compresslevel a la même signification que dans le constructeur de la classe GzipFile ci-dessus.

Nouveau dans la version 3.2.

gzip.decompress(data)

Décompresse les données data, retourne un objet bytes contenant les données décompressées.

Nouveau dans la version 3.2.

13.2.1. Exemples d’utilisation

Exemple montrant comment lire un fichier compressé :

import gzip
with gzip.open('/home/joe/file.txt.gz', 'rb') as f:
    file_content = f.read()

Exemple montrant comment créer un fichier GZIP :

import gzip
content = b"Lots of content here"
with gzip.open('/home/joe/file.txt.gz', 'wb') as f:
    f.write(content)

Exemple montrant comment compresser dans un GZIP un fichier existant :

import gzip
import shutil
with open('/home/joe/file.txt', 'rb') as f_in:
    with gzip.open('/home/joe/file.txt.gz', 'wb') as f_out:
        shutil.copyfileobj(f_in, f_out)

Exemple montrant comment compresser dans un GZIP un binaire dans une chaîne :

import gzip
s_in = b"Lots of content here"
s_out = gzip.compress(s_in)

Voir aussi

Module zlib

Le module de compression de données de base nécessaire pour gérer le format de fichier gzip.

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13.3. bz2 — Prise en charge de la compression bzip2

Code Source : Lib/bz2.py [https://github.com/python/cpython/tree/3.6/Lib/bz2.py]

Ce module fournit une interface complète pour compresser et décompresser les données en utilisant l’algorithme de compression bzip2.

Le module bz2 contient :

La fonction open() et la classe BZ2File pour lire et écrire des fichiers compressés.

Les classes BZ2Compressor et BZ2Decompressor pour la (dé)compression incrémentielle.

Les fonctions compress() et decompress() pour la (dé)compression en une seule fois.

Toutes les classes de ce module peuvent en toute sécurité être accédées depuis de multiples fils d’exécution.

13.3.1. (Dé)compression de fichiers

bz2.open(filename, mode='r', compresslevel=9, encoding=None, errors=None, newline=None)

Ouvre un fichier compressé par bzip2 en mode binaire ou texte, le renvoyant en file object.

Tout comme avec le constructeur pour la classe BZ2File, l’argument filename peut être un nom de fichier réel (un objet str ou bytes), ou un objet fichier existant à lire ou à écrire.

L’argument mode peut valoir 'r', 'rb', 'w', 'wb', 'x', 'xb', 'a' ou 'ab' pour le mode binaire, ou 'rt', 'wt', 'xt' ou 'at' pour le mode texte. Il vaut par défaut 'rb'.

L’argument compresslevel est un entier de 1 à 9, comme pour le constructeur BZ2File.

Pour le mode binaire, cette fonction est équivalente au constructeur BZ2File : BZ2File(filename, mode, compresslevel=compresslevel). Dans ce cas, les arguments encoding, errors et newline arguments ne doivent pas être fournis.

Pour le mode texte, un objet BZ2File est créé et encapsulé dans une instance io.TextIOWrapper avec l’encodage spécifié, le comportement de gestion des erreurs et les fins de ligne.

Nouveau dans la version 3.3.

Modifié dans la version 3.4: Le mode 'x' (création exclusive) est ajouté.

Modifié dans la version 3.6: Accepte un path-like object.

class bz2.BZ2File(filename, mode='r', buffering=None, compresslevel=9)

Ouvre un fichier bzip2 en mode binaire.

Si filename est un objet str ou bytes, ouvre le nom de fichier directement. Autrement, filename doit être un file object, qui est utilisé pour lire ou écrire les données compressées.

L’argument mode peut être soit 'r' pour lire (par défaut), 'w' pour écraser, 'x' pour créer exclusivement, ou 'a' pour ajouter. Ils peuvent également être écrits respectivement comme 'rb', 'wb', 'xb' et 'ab'.

Si filename est un objet fichier (plutôt que le nom de fichier réel), le mode 'w' ne tronque pas le fichier, mais équivaut à 'a'.

The buffering argument is ignored. Its use is deprecated.

If mode is 'w' or 'a', compresslevel can be a number between 1 and 9 specifying the level of compression: 1 produces the least compression, and 9 (default) produces the most compression.

Si mode est 'r', le fichier d’entrée peut être la concaténation de plusieurs flux compressés.

BZ2File fournit tous les membres spécifiés par la classe io.BufferedIOBase, excepté les méthodes detach() et truncate(). L’itération et l’instruction with sont prises en charge.

BZ2File fournit aussi la méthode suivante :

peek([n])

Renvoie des données en mémoire tampon sans avancer la position du fichier. Au moins un octet de donnée (sauf l’EOF) est renvoyé. Le nombre exact d’octets renvoyés n’est pas spécifié.

Note

Bien que l’appel à la méthode peek() ne change pas la position du fichier de la classe BZ2File, il peut changer la position de l’objet fichier sous-jacent (e.g. si la classe BZ2File a été construite en passant un objet fichier à filename).

Nouveau dans la version 3.3.

Modifié dans la version 3.1: La prise en charge de l’instruction with a été ajoutée.

Modifié dans la version 3.3: Les méthodes fileno(), readable(), seekable(), writable(), read1() et readinto() ont été ajoutées.

Modifié dans la version 3.3: La gestion de filename comme file object au lieu d’un nom de fichier réel a été ajoutée.

Modifié dans la version 3.3: Le mode 'a' (ajout) a été ajouté, avec la prise en charge de la lecture des fichiers multiflux.

Modifié dans la version 3.4: Le mode 'x' (création exclusive) est ajouté.

Modifié dans la version 3.5: La méthode read() accepte maintenant un argument None.

Modifié dans la version 3.6: Accepte un path-like object.

13.3.2. (Dé)compression incrémentielle

class bz2.BZ2Compressor(compresslevel=9)

Crée un nouvel objet compresseur. Cet objet peut être utilisé pour compresser les données de manière incrémentielle. Pour une compression en une seule fois, utilisez à la place la fonction compress().

compresslevel, if given, must be a number between 1 and 9. The default is 9.

compress(data)

Fournit la donnée à l’objet compresseur. Renvoie un bloc de données compressées si possible, ou autrement une chaîne d’octet vide.

Quand vous avez fini de fournir des données au compresseur, appelez la méthode flush() pour finir le processus de compression.

flush()

Finit le processus de compression. Renvoie la donnée compressée restante dans les tampons internes.

L’objet compresseur ne peut pas être utilisé après que cette méthode a été appelée.

class bz2.BZ2Decompressor

Crée un nouvel objet décompresseur. Cet objet peut être utilisé pour décompresser les données de manière incrémentielle. Pour une compression en une seule fois, utilisez à la place la fonction decompress().

Note

Cette classe ne gère pas de manière transparente les entrées contenant plusieurs flux compressés, à la différence de decompress() et BZ2File. Si vous avez besoin de décompresser une entrée multiflux avec la classe BZ2Decompressor, vous devez utiliser un nouveau décompresseur pour chaque flux.

decompress(data, max_length=-1)

Décompresse data (un bytes-like object), renvoyant une donnée non compressée en tant que chaîne d’octets. Certaines de ces data peuvent être mises en interne en tampon, pour un usage lors d’appels ultérieurs par la méthode decompress(). La donnée renvoyée doit être concaténée avec la sortie des appels précédents à la méthode decompress().

Si max_length est positif, renvoie au plus max_length octets de données compressées. Si la limite est atteinte et que d’autres sorties peuvent être produites, l’attribut needs_input est positionné sur False. Dans ce cas, lors de l’appel suivant à la méthode decompress(), vous pouvez fournir b'' dans data afin d’obtenir la suite de la sortie.

Si toutes les données entrées ont été décompressées et renvoyées (soit parce qu’il y avait moins de max_length octets, ou parce que max_length était négatif), l’attribut needs_input sera configuré sur True.

Essayer de décompresser des données après que la fin du flux soit atteinte lève une erreur EOFError. Toute donnée trouvée après la fin du flux est ignorée et sauvegardée dans l’attribut unused_data.

Modifié dans la version 3.5: Ajout du paramètre max_length.

eof

True si le marqueur de fin de flux a été atteint.

Nouveau dans la version 3.3.

unused_data

Donnée trouvée après la fin du flux compressé.

Si l’attribut est accédé avant que la fin du flux ait été atteint, sa valeur sera b''.

needs_input

False si la méthode decompress() peut fournir plus de données décompressées avant l’acquisition d’une nouvelle entrée non compressée.

Nouveau dans la version 3.5.

13.3.3. (Dé)compression en une fois

bz2.compress(data, compresslevel=9)

Compresse data.

compresslevel, if given, must be a number between 1 and 9. The default is 9.

Pour la compression incrémentielle, utilisez à la place la classe BZ2Compressor.

bz2.decompress(data)

Décompresse data.

Si data est la concaténation de multiples flux compressés, décompresse tous les flux.

Pour une décompression incrémentielle, utilisez à la place la classe BZ2Decompressor.

Modifié dans la version 3.3: Prise en charge des entrées multiflux.

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13.4. lzma — Compression via l’algorithme LZMA

Nouveau dans la version 3.3.

Code source : Lib/lzma.py [https://github.com/python/cpython/tree/3.6/Lib/lzma.py]

Ce module fournit des classes et des fonctions utiles pour compresser et décompresser des données en utilisant l’algorithme de compression LZMA. Ce module inclut aussi aussi une interface prenant en charge les fichiers .xz et son format originel .lzma utilisés par l’utilitaire xz, ainsi que les flux bruts compressés.

L’interface disponible par ce module ressemble en de nombreux points à celle du module bz2. Cependant, notez que la LZMAFile n’est pas thread-safe, comme l’est la bz2.BZ2File. Donc, si vous souhaitez utiliser une seule instance de LZMAFile pour plusieurs fils, il sera alors nécessaire de la protéger avec un verrou (lock).

exception lzma.LZMAError

Cette exception est levée dès lors qu’une erreur survient pendant la compression ou la décompression, ou pendant l’initialisation de l’état de la compression/décompression.

13.4.1. Lire et écrire des fichiers compressés

lzma.open(filename, mode="rb", *, format=None, check=-1, preset=None, filters=None, encoding=None, errors=None, newline=None)

Ouvre un fichier compressé sous LZMA en mode binaire ou texte, retourne un file object.

L’argument nom de fichier peut être soit le nom d’un fichier à créer (donné pour str, bytes ou un objet path-like), dont le fichier nommé reste ouvert, ou soit un objet fichier existant à lire ou à écrire.

L’argument mode peut être n’importe quel argument suivant : "r", "rb", "w", "wb", "x", "xb", "a" ou "ab" pour le mode binaire, ou "rt", "wt", "xt", ou "at" pour le mode texte. La valeur par défaut est "rb".

Quand un fichier est ouvert pour le lire, les arguments format et filters ont les mêmes significations que pour la LZMADecompressor. Par conséquent, les arguments check et preset ne devront pas être sollicités.

Dès ouverture d’un fichier pour l’écriture, les arguments format, check, preset et filters ont le même sens que dans la LZMACompressor.

Pour le mode binaire, cette fonction équivaut à la LZMAFile constructor: LZMAFile(filename, mode, ...). Dans ce cas précis, les arguments encoding, errors et newline ne sont pas accessibles.

Pour le mode texte, un objet de LZMAFile est créé, et enveloppé dans une instance de io.TextIOWrapper avec son encodage spécifique, son gestionnaire d’erreur, et ses signes pour les renvois à la ligne.

Modifié dans la version 3.4: Support ajouté pour les modes "x", "xb" and "xt".

Modifié dans la version 3.6: Accepte un path-like object.

class lzma.LZMAFile(filename=None, mode="r", *, format=None, check=-1, preset=None, filters=None)

Ouvre un fichier LZMA compressé en mode binaire.

An LZMAFile can wrap an already-open file object, or operate directly on a named file. The filename argument specifies either the file object to wrap, or the name of the file to open (as a str, bytes or path-like object). When wrapping an existing file object, the wrapped file will not be closed when the LZMAFile is closed.

L’argument mode peut être soit "r" pour la lecture (défaut), "w" pour la ré-écriture, "x" pour la création exclusive, ou "a" pour l’insertion. Elles epuvent aussi être écrites de la façon suivante : "rb", "wb", "xb" et "ab" respectivement.

Si l’argument filename est un objet fichier (plutôt qu’un nom de fichier courant), un mode`` »w »`` ne tronquera aucunement le fichier, et sera équivalent à "a".

Dès l’ouverture d’un fichier pour être lu, le fichier d’entrée peut être le résultat d’une concaténation de plusieurs flux distincts et compressés. Ceux-ci sont décodés de manière transparente en un seul flux logique.

Quand un fichier est ouvert pour le lire, les arguments format et filters ont les mêmes significations que pour la LZMADecompressor. Par conséquent, les arguments check et preset ne devront pas être sollicités.

Dès ouverture d’un fichier pour l’écriture, les arguments format, check, preset et filters ont le même sens que dans la LZMACompressor.

La LZMAFile supporte tous les attributs précisés dans io.BufferedIOBase, sauf detach() et truncate(). Le with et son itération sont également supportés.

Les méthodes suivantes sont aussi disponibles :

peek(size=-1)

Renvoie la donnée en mémoire-tampon sans progression de la position du fichier. Au moins un octet de donnée sera renvoyé, jusqu’à ce que l’EOF soit atteinte. Le nombre exact d’octets renvoyés demeure indéterminé (l’argument taille est ignoré).

Note

Alors que l’exécution de peek() ne change pas la position du fichier de la classe LZMAFile, la position de l’objet sous-jacent peut être modifiée (ex. : si la classe LZMAFile est construite en lui transmettant un fichier-objet comme filename).

Modifié dans la version 3.4: Support ajouté pour les modes "x" and "xb".

Modifié dans la version 3.5: La méthode read() accepte maintenant un argument None.

Modifié dans la version 3.6: Accepte un path-like object.

13.4.2. Compresser et décompresser une donnée en mémoire

class lzma.LZMACompressor(format=FORMAT_XZ, check=-1, preset=None, filters=None)

Créé un objet compresseur, qui peut être utilisé pour compresser incrémentalement une donnée.

Pour une façon plus adaptée de compresser un seul extrait de donnée, voir compress().

L’argument format définit quel format de conteneur sera mis en œuvre. Les valeurs possibles sont :

FORMAT_XZ: Le format du conteneur .xz.

C’est le format par défaut.

FORMAT_ALONE: L’ancien format du conteneur .lzma.

Ce format est davantage limité que .xz –il ne supporte pas les vérifications d’intégrité ou les filtres multiples.

FORMAT_RAW: Un flux de données brut, n’utilisant aucun format de conteneur.

Ce format spécifique ne prend pas en charge les vérifications d’intégrité et exige systématiquement la définition d’une chaîne de filtrage personnalisée (à la fois pour la compression et la décompression). Par ailleurs, les données compressées par ce biais ne peuvent pas être décompressées par l’usage de FORMAT_AUTO (voir : LZMADecompressor).

L’argument check détermine le type de vérification d’intégrité à exploiter avec la donnée compressée. Cette vérification est déclenchée lors de la décompression, pour garantir que la donnée n’a pas été corrompue. Les valeurs possibles sont :

CHECK_NONE: Pas de vérification d’intégrité. C’est la valeur par défaut (et la seule valeur acceptable) pour FORMAT_ALONE et FORMAT_RAW.

CHECK_CRC32: Vérification par Redondance Cyclique 32-bit (Cyclic Redundancy Check).

CHECK_CRC64: Vérification par Redondance Cyclique 64-bit (Cyclic Redundancy Check). Valeur par défaut pour FORMAT_XZ.

CHECK_SHA256: Algorithme de Hachage Sécurisé 256-bit (Secure Hash Algorithm).

Si le type de vérification n’est pas supporté par le système, une erreur de type LZMAError est levée.

Les réglages de compression peuvent être définis soit comme un pré-réglage de niveau de compression (avec l’argument preset) ; soit de façon détaillée comme une chaîne particulière de filtres (avec l’argument filters).

L’argument preset (s’il est fourni) doit être un entier compris entre 0` et 9 (inclus), éventuellement relié à OR avec la constante PRESET_EXTREME. Si aucun preset ni filters ne ont définis, le comportement par défaut consiste à utiliser la PRESET_DEFAULT (niveau par défaut : 6). Des pré-réglages plus élevés entraîne une sortie plus petite, mais rend le processus de compression plus lent.

Note

En plus d’être plus gourmande en CPU, la compression avec des préréglages plus élevés nécessite beaucoup plus de mémoire (et produit des résultats qui nécessitent plus de mémoire pour décompresser). Par exemple, avec le préréglage 9, l’objet d’une LZMACompressor peut dépasser largement les 800 Mo. Pour cette raison, il est généralement préférable de respecter le préréglage par défaut.

L’argument filters (s’il est défini) doit être un critère de la chaîne de filtrage. Voir Préciser des chaînes de filtre personnalisées pour plus de précisions.

compress(data)

Une data compressée (un objet bytes), renvoie un objet bytes contenant une donnée compressée pour au moins une partie de l’entrée. Certaine data peuvent être mise en tampon, pour être utiliser lors de prochains appels par compress() et flush(). La donnée renvoyée pourra être concaténée avec la sortie d’appels précédents vers la méthode compress().

flush()

Conclut l’opération de compression, en renvoyant l’objet bytes constitué de toutes les données stockées dans les tampons interne du compresseur.

Le compresseur ne pourra pas être sollicité après l’appel de cette méthode.

class lzma.LZMADecompressor(format=FORMAT_AUTO, memlimit=None, filters=None)

Créé un objet de décompression, pour décompresser de façon incrémentale une donnée.

Pour un moyen plus pratique de décompresser un flux compressé complet en une seule fois, voir decompress().

L’argument format spécifie le format du conteneur à utiliser. La valeur par défaut est FORMAT_AUTO pouvant à la fois décompresser les fichiers .xz and .lzma. D’autres valeurs sont possibles comme FORMAT_XZ, FORMAT_ALONE, et FORMAT_RAW.

L’argument memlimit spécifie une limite (en octets) sur la quantité de mémoire que le décompresseur peut utiliser. Lorsque cet argument est utilisé, la décompression échouera avec une LZMAError s’il n’est pas possible de décompresser l’entrée dans la limite mémoire disponible.

L’argument filters spécifie la chaîne de filtrage utilisée pour créer le flux décompressé. Cet argument est requis si format est FORMAT_RAW, mais ne doit pas être utilisé pour d’autres formats. Voir Préciser des chaînes de filtre personnalisées pour plus d’informations sur les chaînes de filtrage.

Note

Cette classe ne gère pas de manière transparente les entrées contenant plusieurs flux compressés, contrairement à decompress() et LZMAFile. Pour décompresser une entrée multi-flux avec LZMADecompressor, vous devez créer un nouveau décompresseur à chaque flux.

decompress(data, max_length=-1)

Décompresse data (un bytes-like object), renvoyant une donnée non compressée en tant que chaîne d’octets. Certaines de ces data peuvent être mises en interne en tampon, pour un usage lors d’appels ultérieurs par la méthode decompress(). La donnée renvoyée doit être concaténée avec la sortie des appels précédents à la méthode decompress().

Si max_length est positif, renvoie au plus max_length octets de données compressées. Si la limite est atteinte et que d’autres sorties peuvent être produites, l’attribut needs_input est positionné sur False. Dans ce cas, lors de l’appel suivant à la méthode decompress(), vous pouvez fournir b'' dans data afin d’obtenir la suite de la sortie.

Si toutes les données entrées ont été décompressées et renvoyées (soit parce qu’il y avait moins de max_length octets, ou parce que max_length était négatif), l’attribut needs_input sera configuré sur True.

Essayer de décompresser des données après que la fin du flux soit atteinte lève une erreur EOFError. Toute donnée trouvée après la fin du flux est ignorée et sauvegardée dans l’attribut unused_data.

Modifié dans la version 3.5: Ajout du paramètre max_length.

check

L’ID de la vérification d’intégrité exploité par le flux entrant. Il s’agit de CHECK_UNKNOWN tant que ce flux a été décodé pour déterminer quel type de vérification d’intégrité à été utilisé.

eof

True si le marqueur de fin de flux a été atteint.

unused_data

Donnée trouvée après la fin du flux compressé.

Avant d’atteindre la fin du flux, ce sera b"".

needs_input

False si la méthode decompress() peut fournir plus de données décompressées avant l’acquisition d’une nouvelle entrée non compressée.

Nouveau dans la version 3.5.

lzma.compress(data, format=FORMAT_XZ, check=-1, preset=None, filters=None)

data compressée (un objet bytes), renvoyant une donnée compressée comme un objet bytes.

Voir LZMACompressor ci-dessus pour une description des arguments format, check, preset and filters.

lzma.decompress(data, format=FORMAT_AUTO, memlimit=None, filters=None)

Décopresse data (un objet bytes ), et retourne la donnée décompressée sous la forme d’un objet bytes.

Si data est le résultat de la concaténation de plusieurs fluxcompressés et distincts , il les décompresse tous, et retourne les résultats concaténés.

Voir LZMADecompressor ci-dessus pour une description des arguments format, memlimit et filters.

13.4.3. Divers

lzma.is_check_supported(check)

Renvoie vrai si le contrôle d’intégrité donné est supporté par le système.

CHECK_NONE et CHECK_CRC32 sont toujours suppportés. CHECK_CRC64 et CHECK_SHA256 peuvent être indisponibles si vous utlisez une version de liblzma compilée avec des possibilités restreintes.

13.4.4. Préciser des chaînes de filtre personnalisées

Une chaîne de filtres est une séquence de dictionnaires, où chaque dictionnaire contient l’ID et les options pour chaque filtre. Le moindre dictionnaire contient la clé "id" et peut aussicontenir d’autres clés pour préciser chaque options relative au filtre déclaré. Les ID valides des filtres sont définies comme suit :

Filtres de compression:

FILTER_LZMA1 (à utiliser avec FORMAT_ALONE)

FILTER_LZMA2 (à utiliser avec FORMAT_XZ et FORMAT_RAW)

Filtre Delta:

FILTER_DELTA

Filtres Branch-Call-Jump (BCJ):

FILTER_X86

FILTER_IA64

FILTER_ARM

FILTER_ARMTHUMB

FILTER_POWERPC

FILTER_SPARC

Une chaîne de filtres peut contenir jusqu’à 4 filtres, et ne peut pas être vide. Le dernier filtre de cette chaîne devra être un filtre de compression, et tous les autres doivent être des filtres delta ou BCJ.

Les filtres de compression contiennent les options suivantes (définies comme entrées additionnelles dans le dictionnaire qui représente le filtre) :

preset: Un pré-réglage à exploiter comme une source de valeurs par défaut pour les options qui ne sont pas explicitement définies.

dict_size: La taille du dictionnaire en octets. Comprise entre 4 Ko et 1.5 Go (inclus).

lc: Nombre de bits dans le contexte litéral.

lp: Nombre de bits dans la position litérale. La somme lc + lp devra être au moins 4.

pb: Nombre de bits à cette position ; au moins 4.

mode: MODE_FAST ou MODE_NORMAL.

nice_len: Ce qui devra être pris en compte comme « longueur appréciable » pour une recherche. Il devra être 273 ou moins.

mf: Quel type d’index de recherche à utiliser – MF_HC3, MF_HC4, MF_BT2, MF_BT3, ou MF_BT4.

depth: Profondeur maximum de la recherche, utilisée par l’index de recherche. 0 (défaut) signifie une sélection automatique basée sur des options de filtres différents.

Le filtre delta stocke les différences entre octets, induisant davantage d’entrées répétitives pour le compresseur, selon les circonstances. Il support une option, dist. Ce paramètre définit la distance entre les octets à soustraire. Par défaut : 1, soit la différence entre des octets adjacents.

Les filtres BCJ sont conçus pour être appliqués sur du langage machine. Ils convertissent les branches relatives, les appels et les sauts dans le code à des fins d’adressage strict, dans le but d’augmenter la redondance mise en jeu par le compresseur. Ils ne supportent qu’une seule option : start_offset, pour définir l’adresse où sera déclenché le début de la donnée d’entrée. Par défaut : 0.

13.4.5. Exemples

Lire un fichier compressé:

import lzma
with lzma.open("file.xz") as f:
    file_content = f.read()

Créer un fichier compressé:

import lzma
data = b"Insert Data Here"
with lzma.open("file.xz", "w") as f:
    f.write(data)

Compresser des données en mémoire:

import lzma
data_in = b"Insert Data Here"
data_out = lzma.compress(data_in)

Compression incrémentale:

import lzma
lzc = lzma.LZMACompressor()
out1 = lzc.compress(b"Some data\n")
out2 = lzc.compress(b"Another piece of data\n")
out3 = lzc.compress(b"Even more data\n")
out4 = lzc.flush()
# Concatenate all the partial results:
result = b"".join([out1, out2, out3, out4])

Ecrire des données compressées dans un fichier préalablement ouvert:

import lzma
with open("file.xz", "wb") as f:
    f.write(b"This data will not be compressed\n")
    with lzma.open(f, "w") as lzf:
        lzf.write(b"This *will* be compressed\n")
    f.write(b"Not compressed\n")

Créer un fichier compressé en utilisant une chaîne de filtre personnalisée:

import lzma
my_filters = [
    {"id": lzma.FILTER_DELTA, "dist": 5},
    {"id": lzma.FILTER_LZMA2, "preset": 7 | lzma.PRESET_EXTREME},
]
with lzma.open("file.xz", "w", filters=my_filters) as f:
    f.write(b"blah blah blah")

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13.5. zipfile — Travailler avec des archives ZIP

Code source : Lib/zipfile.py [https://github.com/python/cpython/tree/3.6/Lib/zipfile.py]

Le format de fichier ZIP est une archive et un standard de compression couramment utilisés. Ce module fournit des outils pour créer, écrire, ajouter des données à et lister un fichier ZIP. L’utilisation avancée de ce module requiert une certaine compréhension du format, comme défini dans PKZIP Application Note [https://pkware.cachefly.net/webdocs/casestudies/APPNOTE.TXT].

Ce module ne gère pas pour l’instant les fichiers ZIP multi-disque. Il gère les fichiers ZIP qui utilisent les extensions ZIP64 (c’est-à-dire des fichiers d’une taille supérieure à 4 Go). Il gère le chiffrement d’archives ZIP chiffrées, mais il ne peut pas pour l’instant créer de fichier chiffré. Le déchiffrement est extrêmement lent car il est implémenté uniquement en Python plutôt qu’en C.

Le module définit les éléments suivants :

exception zipfile.BadZipFile

Erreur levée en cas de fichier ZIP non valide.

Nouveau dans la version 3.2.

exception zipfile.BadZipfile

Alias de BadZipFile, pour la compatibilité avec les versions de Python précédentes.

Obsolète depuis la version 3.2.

exception zipfile.LargeZipFile

Erreur levée quand un fichier ZIP nécessite la fonctionnalité ZIP64 mais qu’elle n’a pas été activée.

class zipfile.ZipFile

Classe pour lire et écrire des fichiers ZIP. Voir la section Objets ZipFile pour les détails du constructeur.

class zipfile.PyZipFile

Classe pour créer des archives ZIP contenant des bibliothèques Python.

class zipfile.ZipInfo(filename='NoName', date_time=(1980, 1, 1, 0, 0, 0))

Classe utilisée pour représenter les informations d’un membre d’une archive. Les instances de cette classe sont retournées par les méthodes getinfo() et infolist() des objets ZipFile. La plupart des utilisateurs du module zipfile n’ont pas besoin de créer ces instances mais d’utiliser celles créées par ce module. filename doit être le nom complet du membre de l’archive et date_time doit être un tuple contenant six champs qui décrit la date de dernière modification du fichier ; les champs sont décrits dans la section Objets ZipInfo.

zipfile.is_zipfile(filename)

Retourne True si filename est un fichier ZIP valide basé sur son nombre magique, sinon retourne False. filename peut aussi être un fichier ou un objet fichier-compatible.

Modifié dans la version 3.1: Gestion des objets fichier et fichier-compatibles.

zipfile.ZIP_STORED

Constante numérique pour un membre d’une archive décompressée.

zipfile.ZIP_DEFLATED

Constante numérique pour la méthode habituelle de compression de ZIP. Nécessite le module zlib.

zipfile.ZIP_BZIP2

Constante numérique pour la méthode de compressions BZIP2. Nécessite le module bz2.

Nouveau dans la version 3.3.

zipfile.ZIP_LZMA

Constante numérique pour la méthode de compressions LZMA. Nécessite le module lzma.

Nouveau dans la version 3.3.

Note

La spécification du format de fichier ZIP inclut la gestion de la compression BZIP2 depuis 2001 et LZMA depuis 2006. Néanmoins, certains outils (comme certaines versions de Python) ne gèrent pas ces méthodes de compression et peuvent soit totalement refuser de traiter le fichier ZIP soit ne pas extraire certains fichiers.

Voir aussi

PKZIP Application Note [https://pkware.cachefly.net/webdocs/casestudies/APPNOTE.TXT]

Documentation sur le format de fichier ZIP par Phil Katz, créateur du format et des algorithmes utilisés.

Info-ZIP Home Page [http://www.info-zip.org/]

Informations sur les programmes et les bibliothèques de développement d’archivage ZIP du projet Info-ZIP.

13.5.1. Objets ZipFile

class zipfile.ZipFile(file, mode='r', compression=ZIP_STORED, allowZip64=True)

Open a ZIP file, where file can be a path to a file (a string), a file-like object or a path-like object. The mode parameter should be 'r' to read an existing file, 'w' to truncate and write a new file, 'a' to append to an existing file, or 'x' to exclusively create and write a new file. If mode is 'x' and file refers to an existing file, a FileExistsError will be raised. If mode is 'a' and file refers to an existing ZIP file, then additional files are added to it. If file does not refer to a ZIP file, then a new ZIP archive is appended to the file. This is meant for adding a ZIP archive to another file (such as python.exe). If mode is 'a' and the file does not exist at all, it is created. If mode is 'r' or 'a', the file should be seekable. compression is the ZIP compression method to use when writing the archive, and should be ZIP_STORED, ZIP_DEFLATED, ZIP_BZIP2 or ZIP_LZMA; unrecognized values will cause NotImplementedError to be raised. If ZIP_DEFLATED, ZIP_BZIP2 or ZIP_LZMA is specified but the corresponding module (zlib, bz2 or lzma) is not available, RuntimeError is raised. The default is ZIP_STORED. If allowZip64 is True (the default) zipfile will create ZIP files that use the ZIP64 extensions when the zipfile is larger than 4 GiB. If it is false zipfile will raise an exception when the ZIP file would require ZIP64 extensions.

Si le fichier est créé avec le mode 'w', 'x' ou 'a' et ensuite fermé sans ajouter de fichiers à l’archive, la structure appropriée pour un fichier archive ZIP vide sera écrite dans le fichier.

ZipFile is also a context manager and therefore supports the with statement. In the example, myzip is closed after the with statement’s suite is finished—even if an exception occurs:

with ZipFile('spam.zip', 'w') as myzip:
    myzip.write('eggs.txt')

Nouveau dans la version 3.2: Ajout de la possibilité d’utiliser ZipFile comme un gestionnaire de contexte.

Modifié dans la version 3.3: Ajout de la gestion de la compression bzip2 et lzma.

Modifié dans la version 3.4: Les extensions ZIP64 sont activées par défaut.

Modifié dans la version 3.5: Ajout de la gestion de l’écriture dans des flux non navigables. Ajout de la gestion du mode x.

Modifié dans la version 3.6: Auparavant, une simple exception RuntimeError était levée pour des valeurs de compression non reconnues.

Modifié dans la version 3.6.2: Le paramètre file accepte un objet fichier-compatible path-like object.

ZipFile.close()

Ferme l’archive. Vous devez appeler close() avant de terminer votre programme ou des informations essentielles n’y seront pas enregistrées.

ZipFile.getinfo(name)

Retourne un objet ZipInfo avec les informations du membre name de l’archive. Appeler getinfo() pour un nom non contenu dans l’archive lève une exception KeyError.

ZipFile.infolist()

Retourne une liste contenant un objet ZipInfo pour chaque membre de l’archive. Les objets ont le même ordre que leurs entrées dans le fichier ZIP présent sur disque s’il s’agissait d’une archive préexistante.

ZipFile.namelist()

Retourne une liste des membres de l’archive indexés par leur nom.

ZipFile.open(name, mode='r', pwd=None, *, force_zip64=False)

Accède un membre de l’archive en tant qu’objet fichier-compatible binaire. name peut être soit le nom d’un fichier au sein de l’archive soit un objet ZipInfo. Le paramètre mode, si inclus, doit être défini à 'r' (valeur par défaut) ou 'w'. pwd est le mot de passe utilisé pour déchiffrer des fichiers ZIP chiffrés.

open() est aussi un gestionnaire de contexte et gère ainsi la déclaration with :

with ZipFile('spam.zip') as myzip:
    with myzip.open('eggs.txt') as myfile:
        print(myfile.read())

With mode 'r' the file-like object (ZipExtFile) is read-only and provides the following methods: read(), readline(), readlines(), __iter__(), __next__(). These objects can operate independently of the ZipFile.

Avec mode='w' un descripteur de fichier en écriture est retourné, gérant la méthode write(). Quand le descripteur d’un fichier inscriptible est ouvert, tenter de lire ou écrire d’autres fichiers dans le fichier ZIP lève une exception ValueError.

Lors de l’écriture d’un fichier, si la taille du fichier n’est pas connue mais peut être supérieure à 2 GiO, spécifiez force_zip64=True afin de vous assurer que le format d’en-tête est capable de supporter des fichiers volumineux. Si la taille du fichier est connue à l’avance, instanciez un objet ZipInfo avec l’attribut file_size défini et utilisez-le en tant que paramètre name.

Note

Les méthodes open(), read() et extract() peuvent prendre un nom de fichier ou un objet ZipInfo. Cela est appréciable lorsqu’on essaie de lire un fichier ZIP qui contient des membres avec des noms en double.

Modifié dans la version 3.6: Suppression de la gestion de mode='U'. Utilisez io.TextIOWrapper pour lire des fichiers texte compressés en mode universal newlines.

Modifié dans la version 3.6: La méthode open() peut désormais être utilisée pour écrire des fichiers dans l’archive avec l’option mode='w'.

Modifié dans la version 3.6: Appeler open() sur un fichier ZipFile fermé lève une erreur ValueError. Précédemment, une erreur RuntimeError était levée.

ZipFile.extract(member, path=None, pwd=None)

Extrait un membre de l’archive dans le répertoire courant ; member doit être son nom complet ou un objet ZipInfo. Ses propriétés de fichier sont extraites le plus fidèlement possible. path spécifie un répertoire différent où l’extraire. member peut être un nom de fichier ou un objet ZipInfo. pwd est le mot de passe utilisé pour les fichiers chiffrés.

Retourne le chemin normalisé créé (un dossier ou un nouveau fichier).

Note

Si le nom de fichier d’un membre est un chemin absolu, le disque/partage UNC et les (anti)slashes de départ seront supprimés, par exemple ///foo/bar` devient foo/bar sous Unix et C:\foo\bar devient foo\bar sous Windows. Et tous les composants ".." dans le nom de fichier d’un membre seront supprimés, par exemple ../../foo../../ba..r devient foo../ba..r. Sous Windows les caractères illégaux (:, <, >, |, ", ? et *) sont remplacés par un underscore (_).

Modifié dans la version 3.6: Appeler extract() sur un fichier ZipFile fermé lève une erreur ValueError. Précédemment, une erreur RuntimeError était levée.

Modifié dans la version 3.6.2: Le paramètre path accepte un objet chemin-compatible path-like object.

ZipFile.extractall(path=None, members=None, pwd=None)

Extrait tous les membres de l’archive dans le répertoire courant. path spécifie un dossier de destination différent. members est optionnel et doit être un sous-ensemble de la liste retournée par namelist(). pwd est le mot de passe utilisé pour les fichiers chiffrés.

Avertissement

N’extrayez jamais d’archives depuis des sources non fiables sans inspection préalable. Il est possible que des fichiers soient créés en dehors de path, par exemple des membres qui ont des chemins de fichier absolus commençant par "/" ou des noms de fichier avec deux points "..". Ce module essaie de prévenir ceci. Voir la note de extract().

Modifié dans la version 3.6: Appeler extractall() sur un fichier ZipFile fermé lève une erreur ValueError. Précédemment, une erreur RuntimeError était levée.

Modifié dans la version 3.6.2: Le paramètre path accepte un objet chemin-compatible path-like object.

ZipFile.printdir()

Affiche la liste des contenus de l’archive sur sys.stdout.

ZipFile.setpassword(pwd)

Définit pwd comme mot de passe par défait pour extraire des fichiers chiffrés.

ZipFile.read(name, pwd=None)

Retourne les octets du fichier name dans l’archive. name est le nom du fichier dans l’archive ou un objet ZipInfo. L’archive doit être ouverte en mode lecture ou ajout de données. pwd est le mot de passe utilisé pour les fichiers chiffrés et, si spécifié, écrase le mot de passe par défaut défini avec setpassword(). Appeler read() sur un fichier ZipFile qui utilise une méthode de compression différente de ZIP_STORED, ZIP_DEFLATED, ZIP_BZIP2 ou ZIP_LZMA lève une erreur NotImplementedError. Une erreur est également levée si le module de compression n’est pas disponible.

Modifié dans la version 3.6: Appeler read() sur un fichier ZipFile fermé lève une erreur ValueError. Précédemment, une erreur RuntimeError était levée.

ZipFile.testzip()

Lit tous les fichiers de l’archive et vérifie leurs sommes CRC et leurs en-têtes. Retourne le nom du premier fichier mauvais ou retourne None sinon.

Modifié dans la version 3.6: Calling testzip() on a closed ZipFile will raise a ValueError. Previously, a RuntimeError was raised.

ZipFile.write(filename, arcname=None, compress_type=None)

Write the file named filename to the archive, giving it the archive name arcname (by default, this will be the same as filename, but without a drive letter and with leading path separators removed). If given, compress_type overrides the value given for the compression parameter to the constructor for the new entry. The archive must be open with mode 'w', 'x' or 'a'.

Note

Les noms d’archive doivent être relatifs à la racine de l’archive, c’est-à-dire qu’ils ne doivent pas commencer par un séparateur de chemin.

Note

Si arcname (ou filename si arcname n’est pas donné) contient un octet nul, le nom du fichier dans l’archive sera tronqué à l’octet nul.

Modifié dans la version 3.6: Appeler write() sur un fichier ZipFile fermé lève une erreur ValueError. Précédemment, une erreur RuntimeError était levée.

ZipFile.writestr(zinfo_or_arcname, data[, compress_type])

Write a file into the archive. The contents is data, which may be either a str or a bytes instance; if it is a str, it is encoded as UTF-8 first. zinfo_or_arcname is either the file name it will be given in the archive, or a ZipInfo instance. If it’s an instance, at least the filename, date, and time must be given. If it’s a name, the date and time is set to the current date and time. The archive must be opened with mode 'w', 'x' or 'a'.

If given, compress_type overrides the value given for the compression parameter to the constructor for the new entry, or in the zinfo_or_arcname (if that is a ZipInfo instance).

Note

Lorsque l’on passe une instance de ZipInfo dans le paramètre zinfo_or_arcname, la méthode de compression utilisée sera celle spécifiée dans le membre compress_type de l’instance ZipInfo donnée. Par défaut, le constructeur de la classe ZipInfo définit ce membre à ZIP_STORED.

Modifié dans la version 3.2: L’argument compress_type.

Modifié dans la version 3.6: Appeler writestr() sur un fichier ZipFile fermé lève une erreur ValueError. Précédemment, une erreur RuntimeError était levée.

Les attributs suivants sont aussi disponibles :

ZipFile.filename

Nom du fichier ZIP.

ZipFile.debug

Le niveau d’affichage de debug à utiliser. Peut être défini de 0 (par défaut, pas d’affichage) à 3 (affichage le plus bavard). Les informations de débogage sont affichées sur sys.stdout.

ZipFile.comment

The comment associated with the ZIP file as a bytes object. If assigning a comment to a ZipFile instance created with mode 'w', 'x' or 'a', it should be no longer than 65535 bytes. Comments longer than this will be truncated.

13.5.2. Objets PyZipFile

Le constructeur de PyZipFile prend les mêmes paramètres que le constructeur de ZipFile avec un paramètre additionnel optimize.

class zipfile.PyZipFile(file, mode='r', compression=ZIP_STORED, allowZip64=True, optimize=-1)

Nouveau dans la version 3.2: Le paramètre optimize.

Modifié dans la version 3.4: Les extensions ZIP64 sont activées par défaut.

Les instances ont une méthode supplémentaire par rapport aux objets ZipFile :

writepy(pathname, basename='', filterfunc=None)

Cherche les fichiers *.py et ajoute le fichier correspondant à l’archive.

Si le paramètre optimize du constructeur de PyZipFile n’a pas été donné ou est à -1, le fichier correspondant est un fichier *.pyc, à compiler si nécessaire.

Si le paramètre optimize du constructeur de PyZipFile est à 0, 1 ou 2, ne sont ajoutés dans l’archive que les fichiers avec ce niveau d’optimisation (voir compile()), à compiler si nécessaire.

If pathname is a file, the filename must end with .py, and just the (corresponding *.pyc) file is added at the top level (no path information). If pathname is a file that does not end with .py, a RuntimeError will be raised. If it is a directory, and the directory is not a package directory, then all the files *.pyc are added at the top level. If the directory is a package directory, then all *.pyc are added under the package name as a file path, and if any subdirectories are package directories, all of these are added recursively.

basename n’est sensé être utilisé qu’en interne.

filterfunc, si donné, doit être une fonction prenant une seule chaîne de caractères en argument. Il lui sera passé chaque chemin (incluant chaque chemin de fichier complet individuel) avant d’être ajouté à l’archive. Si filterfunc retourne une valeur fausse, le chemin n’est pas ajouté et si c’est un répertoire son contenu est ignoré. Par exemple, si nos fichiers de test sont tous soit dans des répertoires test ou commencent par test_, nous pouvons utiliser une fonction filterfunc pour les exclure :

>>> zf = PyZipFile('myprog.zip')
>>> def notests(s):
...     fn = os.path.basename(s)
...     return (not (fn == 'test' or fn.startswith('test_')))
>>> zf.writepy('myprog', filterfunc=notests)

La méthode writepy() crée des archives avec des noms de fichier comme suit :

string.pyc                   # Top level name
test/__init__.pyc            # Package directory
test/testall.pyc             # Module test.testall
test/bogus/__init__.pyc      # Subpackage directory
test/bogus/myfile.pyc        # Submodule test.bogus.myfile

Nouveau dans la version 3.4: Le paramètre filterfunc.

Modifié dans la version 3.6.2: Le paramètre pathname accepte un objet chemin-compatible path-like object.

13.5.3. Objets ZipInfo

Des instances de la classe ZipInfo sont retournées par les méthodes getinfo() et infolist() des objets ZipFile. Chaque objet stocke des informations sur un seul membre de l’archive ZIP.

Il y a une méthode de classe pour créer une instance de ZipInfo pour un fichier du système de fichiers :

classmethod ZipInfo.from_file(filename, arcname=None)

Construit une instance de ZipInfo pour le fichier du système de fichiers, en préparation de l’ajouter à un fichier ZIP.

filename doit être un chemin vers un fichier ou un répertoire dans le système de fichiers.

Si arcname est spécifié, il est utilisé en tant que nom dans l’archive. Si arcname n’est pas spécifié, le nom sera le même que filename mais sans lettre de disque et sans séparateur de chemin en première position.

Nouveau dans la version 3.6.

Modifié dans la version 3.6.2: Le paramètre filename accepte un objet chemin-compatible path-like object.

Les instances ont les méthodes et attributs suivants :

ZipInfo.is_dir()

Retourne True si le membre d’archive est un répertoire.

Utilise le nom de l’entrée : les répertoires doivent toujours se terminer par /.

Nouveau dans la version 3.6.

ZipInfo.filename

Nom du fichier dans l’archive.

ZipInfo.date_time

Date et heure de dernière modification pour le membre de l’archive. Tuple de six valeurs :

Index

Valeur

0

Année (>= 1980)

1

Mois (indexé à partir de 1)

2

Jour du mois (indexé à partir de 1)

3

Heures (indexées à partir de 0)

4

Minutes (indexées à partir de 0)

5

Secondes (indexées à partir de 0)

Note

Le format de fichier ZIP ne gère pas les horodatages avant 1980.

ZipInfo.compress_type

Type de compression du membre d’archive.

ZipInfo.comment

Comment for the individual archive member as a bytes object.

ZipInfo.extra

Expansion field data. The PKZIP Application Note [https://pkware.cachefly.net/webdocs/casestudies/APPNOTE.TXT] contains some comments on the internal structure of the data contained in this bytes object.

ZipInfo.create_system

Système ayant créé l’archive ZIP.

ZipInfo.create_version

Version de PKZIP ayant créé l’archive ZIP.

ZipInfo.extract_version

Version de PKZIP nécessaire à l’extraction de l’archive ZIP.

ZipInfo.reserved

Doit être à zéro.

ZipInfo.flag_bits

Bits d’options ZIP.

ZipInfo.volume

Numéro de volume de l’entête du fichier.

ZipInfo.internal_attr

Attributs internes.

ZipInfo.external_attr

Attributs de fichier externes.

ZipInfo.header_offset

Longueur de l’entête du fichier en octets.

ZipInfo.CRC

CRC-32 du fichier décompressé.

ZipInfo.compress_size

Taille des données décompressées.

ZipInfo.file_size

Taille du fichier décompressé.

13.5.4. Interface en ligne de commande

Le module zipfile fournit une interface en ligne de commande simple pour interagir avec des archives ZIP.

Si vous voulez créer une nouvelle archive ZIP, spécifiez son nom après l’option -c et listez ensuite le(s) nom(s) de fichier à inclure :

$ python -m zipfile -c monty.zip spam.txt eggs.txt

Passer un répertoire est aussi possible :

$ python -m zipfile -c monty.zip life-of-brian_1979/

Si vous voulez extraire une archive ZIP dans un répertoire donné, utilisez l’option -e :

$ python -m zipfile -e monty.zip target-dir/

Pour une liste des fichiers dans une archive ZIP, utilisez l’option -l :

$ python -m zipfile -l monty.zip

13.5.4.1. Options de la ligne de commande

-l <zipfile>

Liste les fichiers dans un fichier ZIP zipfile.

-c <zipfile> <source1> ... <sourceN>

Crée un fichier ZIP zipfile à partir des fichiers source.

-e <zipfile> <output_dir>

Extrait le fichier ZIP zipfile vers le répertoire cible output_dir.

-t <zipfile>

Teste si le fichier zip est valide.

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13.6. tarfile — Read and write tar archive files

Code source : Lib/tarfile.py [https://github.com/python/cpython/tree/3.6/Lib/tarfile.py]

The tarfile module makes it possible to read and write tar archives, including those using gzip, bz2 and lzma compression. Use the zipfile module to read or write .zip files, or the higher-level functions in shutil.

Some facts and figures:

reads and writes gzip, bz2 and lzma compressed archives if the respective modules are available.

read/write support for the POSIX.1-1988 (ustar) format.

read/write support for the GNU tar format including longname and longlink extensions, read-only support for all variants of the sparse extension including restoration of sparse files.

read/write support for the POSIX.1-2001 (pax) format.

handles directories, regular files, hardlinks, symbolic links, fifos, character devices and block devices and is able to acquire and restore file information like timestamp, access permissions and owner.

Modifié dans la version 3.3: Added support for lzma compression.

tarfile.open(name=None, mode='r', fileobj=None, bufsize=10240, **kwargs)

Return a TarFile object for the pathname name. For detailed information on TarFile objects and the keyword arguments that are allowed, see TarFile Objects.

mode has to be a string of the form 'filemode[:compression]', it defaults to 'r'. Here is a full list of mode combinations:

mode

action

'r' ou 'r:*'

Open for reading with transparent compression (recommended).

'r:'

Open for reading exclusively without compression.

'r:gz'

Open for reading with gzip compression.

'r:bz2'

Open for reading with bzip2 compression.

'r:xz'

Open for reading with lzma compression.

'x' ou 'x:'

Create a tarfile exclusively without compression. Raise an FileExistsError exception if it already exists.

'x:gz'

Create a tarfile with gzip compression. Raise an FileExistsError exception if it already exists.

'x:bz2'

Create a tarfile with bzip2 compression. Raise an FileExistsError exception if it already exists.

'x:xz'

Create a tarfile with lzma compression. Raise an FileExistsError exception if it already exists.

'a' ou 'a:'

Open for appending with no compression. The file is created if it does not exist.

'w' ou 'w:'

Open for uncompressed writing.

'w:gz'

Open for gzip compressed writing.

'w:bz2'

Open for bzip2 compressed writing.

'w:xz'

Open for lzma compressed writing.

Note that 'a:gz', 'a:bz2' or 'a:xz' is not possible. If mode is not suitable to open a certain (compressed) file for reading, ReadError is raised. Use mode 'r' to avoid this. If a compression method is not supported, CompressionError is raised.

If fileobj is specified, it is used as an alternative to a file object opened in binary mode for name. It is supposed to be at position 0.

For modes 'w:gz', 'r:gz', 'w:bz2', 'r:bz2', 'x:gz', 'x:bz2', tarfile.open() accepts the keyword argument compresslevel (default 9) to specify the compression level of the file.

For special purposes, there is a second format for mode: 'filemode|[compression]'. tarfile.open() will return a TarFile object that processes its data as a stream of blocks. No random seeking will be done on the file. If given, fileobj may be any object that has a read() or write() method (depending on the mode). bufsize specifies the blocksize and defaults to 20 * 512 bytes. Use this variant in combination with e.g. sys.stdin, a socket file object or a tape device. However, such a TarFile object is limited in that it does not allow random access, see Exemples. The currently possible modes:

Mode

Action

'r|*'

Open a stream of tar blocks for reading with transparent compression.

'r|'

Open a stream of uncompressed tar blocks for reading.

'r|gz'

Open a gzip compressed stream for reading.

'r|bz2'

Open a bzip2 compressed stream for reading.

'r|xz'

Open an lzma compressed stream for reading.

'w|'

Open an uncompressed stream for writing.

'w|gz'

Open a gzip compressed stream for writing.

'w|bz2'

Open a bzip2 compressed stream for writing.

'w|xz'

Open an lzma compressed stream for writing.

Modifié dans la version 3.5: Le mode 'x' (création exclusive) est créé.

Modifié dans la version 3.6: The name parameter accepts a path-like object.

class tarfile.TarFile

Class for reading and writing tar archives. Do not use this class directly: use tarfile.open() instead. See TarFile Objects.

tarfile.is_tarfile(name)

Return True if name is a tar archive file, that the tarfile module can read.

The tarfile module defines the following exceptions:

exception tarfile.TarError

Base class for all tarfile exceptions.

exception tarfile.ReadError

Is raised when a tar archive is opened, that either cannot be handled by the tarfile module or is somehow invalid.

exception tarfile.CompressionError

Is raised when a compression method is not supported or when the data cannot be decoded properly.

exception tarfile.StreamError

Is raised for the limitations that are typical for stream-like TarFile objects.

exception tarfile.ExtractError

Is raised for non-fatal errors when using TarFile.extract(), but only if TarFile.errorlevel== 2.

exception tarfile.HeaderError

Is raised by TarInfo.frombuf() if the buffer it gets is invalid.

The following constants are available at the module level:

tarfile.ENCODING

The default character encoding: 'utf-8' on Windows, the value returned by sys.getfilesystemencoding() otherwise.

Each of the following constants defines a tar archive format that the tarfile module is able to create. See section Supported tar formats for details.

tarfile.USTAR_FORMAT

POSIX.1-1988 (ustar) format.

tarfile.GNU_FORMAT

GNU tar format.

tarfile.PAX_FORMAT

POSIX.1-2001 (pax) format.

tarfile.DEFAULT_FORMAT

The default format for creating archives. This is currently GNU_FORMAT.

Voir aussi

Module zipfile

Documentation of the zipfile standard module.

Archiving operations

Documentation of the higher-level archiving facilities provided by the standard shutil module.

GNU tar manual, Basic Tar Format [https://www.gnu.org/software/tar/manual/html_node/Standard.html]

Documentation for tar archive files, including GNU tar extensions.

13.6.1. TarFile Objects

The TarFile object provides an interface to a tar archive. A tar archive is a sequence of blocks. An archive member (a stored file) is made up of a header block followed by data blocks. It is possible to store a file in a tar archive several times. Each archive member is represented by a TarInfo object, see TarInfo Objects for details.

A TarFile object can be used as a context manager in a with statement. It will automatically be closed when the block is completed. Please note that in the event of an exception an archive opened for writing will not be finalized; only the internally used file object will be closed. See the Exemples section for a use case.

Nouveau dans la version 3.2: Added support for the context management protocol.

class tarfile.TarFile(name=None, mode='r', fileobj=None, format=DEFAULT_FORMAT, tarinfo=TarInfo, dereference=False, ignore_zeros=False, encoding=ENCODING, errors='surrogateescape', pax_headers=None, debug=0, errorlevel=0)

All following arguments are optional and can be accessed as instance attributes as well.

name is the pathname of the archive. name may be a path-like object. It can be omitted if fileobj is given. In this case, the file object’s name attribute is used if it exists.

mode is either 'r' to read from an existing archive, 'a' to append data to an existing file, 'w' to create a new file overwriting an existing one, or 'x' to create a new file only if it does not already exist.

If fileobj is given, it is used for reading or writing data. If it can be determined, mode is overridden by fileobj’s mode. fileobj will be used from position 0.

Note

fileobj is not closed, when TarFile is closed.

format controls the archive format. It must be one of the constants USTAR_FORMAT, GNU_FORMAT or PAX_FORMAT that are defined at module level.

The tarinfo argument can be used to replace the default TarInfo class with a different one.

If dereference is False, add symbolic and hard links to the archive. If it is True, add the content of the target files to the archive. This has no effect on systems that do not support symbolic links.

If ignore_zeros is False, treat an empty block as the end of the archive. If it is True, skip empty (and invalid) blocks and try to get as many members as possible. This is only useful for reading concatenated or damaged archives.

debug can be set from 0 (no debug messages) up to 3 (all debug messages). The messages are written to sys.stderr.

If errorlevel is 0, all errors are ignored when using TarFile.extract(). Nevertheless, they appear as error messages in the debug output, when debugging is enabled. If 1, all fatal errors are raised as OSError exceptions. If 2, all non-fatal errors are raised as TarError exceptions as well.

The encoding and errors arguments define the character encoding to be used for reading or writing the archive and how conversion errors are going to be handled. The default settings will work for most users. See section Unicode issues for in-depth information.

The pax_headers argument is an optional dictionary of strings which will be added as a pax global header if format is PAX_FORMAT.

Modifié dans la version 3.2: Use 'surrogateescape' as the default for the errors argument.

Modifié dans la version 3.5: Le mode 'x' (création exclusive) est créé.

Modifié dans la version 3.6: The name parameter accepts a path-like object.

classmethod TarFile.open(...)

Alternative constructor. The tarfile.open() function is actually a shortcut to this classmethod.

TarFile.getmember(name)

Return a TarInfo object for member name. If name can not be found in the archive, KeyError is raised.

Note

If a member occurs more than once in the archive, its last occurrence is assumed to be the most up-to-date version.

TarFile.getmembers()

Return the members of the archive as a list of TarInfo objects. The list has the same order as the members in the archive.

TarFile.getnames()

Return the members as a list of their names. It has the same order as the list returned by getmembers().

TarFile.list(verbose=True, *, members=None)

Print a table of contents to sys.stdout. If verbose is False, only the names of the members are printed. If it is True, output similar to that of ls -l is produced. If optional members is given, it must be a subset of the list returned by getmembers().

Modifié dans la version 3.5: Added the members parameter.

TarFile.next()

Return the next member of the archive as a TarInfo object, when TarFile is opened for reading. Return None if there is no more available.

TarFile.extractall(path=".", members=None, *, numeric_owner=False)

Extract all members from the archive to the current working directory or directory path. If optional members is given, it must be a subset of the list returned by getmembers(). Directory information like owner, modification time and permissions are set after all members have been extracted. This is done to work around two problems: A directory’s modification time is reset each time a file is created in it. And, if a directory’s permissions do not allow writing, extracting files to it will fail.

If numeric_owner is True, the uid and gid numbers from the tarfile are used to set the owner/group for the extracted files. Otherwise, the named values from the tarfile are used.

Avertissement

Never extract archives from untrusted sources without prior inspection. It is possible that files are created outside of path, e.g. members that have absolute filenames starting with "/" or filenames with two dots "..".

Modifié dans la version 3.5: Added the numeric_owner parameter.

Modifié dans la version 3.6: Le paramètre path accepte un objet chemin-compatible path-like object.

TarFile.extract(member, path="", set_attrs=True, *, numeric_owner=False)

Extract a member from the archive to the current working directory, using its full name. Its file information is extracted as accurately as possible. member may be a filename or a TarInfo object. You can specify a different directory using path. path may be a path-like object. File attributes (owner, mtime, mode) are set unless set_attrs is false.

If numeric_owner is True, the uid and gid numbers from the tarfile are used to set the owner/group for the extracted files. Otherwise, the named values from the tarfile are used.

Note

The extract() method does not take care of several extraction issues. In most cases you should consider using the extractall() method.

Avertissement

See the warning for extractall().

Modifié dans la version 3.2: Added the set_attrs parameter.

Modifié dans la version 3.5: Added the numeric_owner parameter.

Modifié dans la version 3.6: Le paramètre path accepte un objet chemin-compatible path-like object.

TarFile.extractfile(member)

Extract a member from the archive as a file object. member may be a filename or a TarInfo object. If member is a regular file or a link, an io.BufferedReader object is returned. Otherwise, None is returned.

Modifié dans la version 3.3: Return an io.BufferedReader object.

TarFile.add(name, arcname=None, recursive=True, exclude=None, *, filter=None)

Add the file name to the archive. name may be any type of file (directory, fifo, symbolic link, etc.). If given, arcname specifies an alternative name for the file in the archive. Directories are added recursively by default. This can be avoided by setting recursive to False. If exclude is given, it must be a function that takes one filename argument and returns a boolean value. Depending on this value the respective file is either excluded (True) or added (False). If filter is specified it must be a keyword argument. It should be a function that takes a TarInfo object argument and returns the changed TarInfo object. If it instead returns None the TarInfo object will be excluded from the archive. See Exemples for an example.

Modifié dans la version 3.2: Added the filter parameter.

Obsolète depuis la version 3.2: The exclude parameter is deprecated, please use the filter parameter instead.

TarFile.addfile(tarinfo, fileobj=None)

Add the TarInfo object tarinfo to the archive. If fileobj is given, it should be a binary file, and tarinfo.size bytes are read from it and added to the archive. You can create TarInfo objects directly, or by using gettarinfo().

TarFile.gettarinfo(name=None, arcname=None, fileobj=None)

Create a TarInfo object from the result of os.stat() or equivalent on an existing file. The file is either named by name, or specified as a file object fileobj with a file descriptor. name may be a path-like object. If given, arcname specifies an alternative name for the file in the archive, otherwise, the name is taken from fileobj’s name attribute, or the name argument. The name should be a text string.

You can modify some of the TarInfo’s attributes before you add it using addfile(). If the file object is not an ordinary file object positioned at the beginning of the file, attributes such as size may need modifying. This is the case for objects such as GzipFile. The name may also be modified, in which case arcname could be a dummy string.

Modifié dans la version 3.6: The name parameter accepts a path-like object.

TarFile.close()

Close the TarFile. In write mode, two finishing zero blocks are appended to the archive.

TarFile.pax_headers

A dictionary containing key-value pairs of pax global headers.

13.6.2. TarInfo Objects

A TarInfo object represents one member in a TarFile. Aside from storing all required attributes of a file (like file type, size, time, permissions, owner etc.), it provides some useful methods to determine its type. It does not contain the file’s data itself.

TarInfo objects are returned by TarFile’s methods getmember(), getmembers() and gettarinfo().

class tarfile.TarInfo(name="")

Create a TarInfo object.

classmethod TarInfo.frombuf(buf, encoding, errors)

Create and return a TarInfo object from string buffer buf.

Raises HeaderError if the buffer is invalid.

classmethod TarInfo.fromtarfile(tarfile)

Read the next member from the TarFile object tarfile and return it as a TarInfo object.

TarInfo.tobuf(format=DEFAULT_FORMAT, encoding=ENCODING, errors='surrogateescape')

Create a string buffer from a TarInfo object. For information on the arguments see the constructor of the TarFile class.

Modifié dans la version 3.2: Use 'surrogateescape' as the default for the errors argument.

A TarInfo object has the following public data attributes:

TarInfo.name

Name of the archive member.

TarInfo.size

Size in bytes.

TarInfo.mtime

Time of last modification.

TarInfo.mode

Permission bits.

TarInfo.type

File type. type is usually one of these constants: REGTYPE, AREGTYPE, LNKTYPE, SYMTYPE, DIRTYPE, FIFOTYPE, CONTTYPE, CHRTYPE, BLKTYPE, GNUTYPE_SPARSE. To determine the type of a TarInfo object more conveniently, use the is*() methods below.

TarInfo.linkname

Name of the target file name, which is only present in TarInfo objects of type LNKTYPE and SYMTYPE.

TarInfo.uid

User ID of the user who originally stored this member.

TarInfo.gid

Group ID of the user who originally stored this member.

TarInfo.uname

User name.

TarInfo.gname

Group name.

TarInfo.pax_headers

A dictionary containing key-value pairs of an associated pax extended header.

A TarInfo object also provides some convenient query methods:

TarInfo.isfile()

Return True if the Tarinfo object is a regular file.

TarInfo.isreg()

Same as isfile().

TarInfo.isdir()

Return True if it is a directory.

TarInfo.issym()

Return True if it is a symbolic link.

TarInfo.islnk()

Return True if it is a hard link.

TarInfo.ischr()

Return True if it is a character device.

TarInfo.isblk()

Return True if it is a block device.

TarInfo.isfifo()

Return True if it is a FIFO.

TarInfo.isdev()

Return True if it is one of character device, block device or FIFO.

13.6.3. Interface en ligne de commande

Nouveau dans la version 3.4.

The tarfile module provides a simple command-line interface to interact with tar archives.

If you want to create a new tar archive, specify its name after the -c option and then list the filename(s) that should be included:

$ python -m tarfile -c monty.tar  spam.txt eggs.txt

Passer un répertoire est aussi possible :

$ python -m tarfile -c monty.tar life-of-brian_1979/

If you want to extract a tar archive into the current directory, use the -e option:

$ python -m tarfile -e monty.tar

You can also extract a tar archive into a different directory by passing the directory’s name:

$ python -m tarfile -e monty.tar  other-dir/

For a list of the files in a tar archive, use the -l option:

$ python -m tarfile -l monty.tar

13.6.3.1. Options de la ligne de commande

-l <tarfile>

--list <tarfile>

List files in a tarfile.

-c <tarfile> <source1> ... <sourceN>

--create <tarfile> <source1> ... <sourceN>

Create tarfile from source files.

-e <tarfile> [<output_dir>]

--extract <tarfile> [<output_dir>]

Extract tarfile into the current directory if output_dir is not specified.

-t <tarfile>

--test <tarfile>

Test whether the tarfile is valid or not.

-v, --verbose

Verbose output.

13.6.4. Exemples

How to extract an entire tar archive to the current working directory:

import tarfile
tar = tarfile.open("sample.tar.gz")
tar.extractall()
tar.close()

How to extract a subset of a tar archive with TarFile.extractall() using a generator function instead of a list:

import os
import tarfile

def py_files(members):
    for tarinfo in members:
        if os.path.splitext(tarinfo.name)[1] == ".py":
            yield tarinfo

tar = tarfile.open("sample.tar.gz")
tar.extractall(members=py_files(tar))
tar.close()

How to create an uncompressed tar archive from a list of filenames:

import tarfile
tar = tarfile.open("sample.tar", "w")
for name in ["foo", "bar", "quux"]:
    tar.add(name)
tar.close()

The same example using the with statement:

import tarfile
with tarfile.open("sample.tar", "w") as tar:
    for name in ["foo", "bar", "quux"]:
        tar.add(name)

How to read a gzip compressed tar archive and display some member information:

import tarfile
tar = tarfile.open("sample.tar.gz", "r:gz")
for tarinfo in tar:
    print(tarinfo.name, "is", tarinfo.size, "bytes in size and is", end="")
    if tarinfo.isreg():
        print("a regular file.")
    elif tarinfo.isdir():
        print("a directory.")
    else:
        print("something else.")
tar.close()

How to create an archive and reset the user information using the filter parameter in TarFile.add():

import tarfile
def reset(tarinfo):
    tarinfo.uid = tarinfo.gid = 0
    tarinfo.uname = tarinfo.gname = "root"
    return tarinfo
tar = tarfile.open("sample.tar.gz", "w:gz")
tar.add("foo", filter=reset)
tar.close()

13.6.5. Supported tar formats

There are three tar formats that can be created with the tarfile module:

The POSIX.1-1988 ustar format (USTAR_FORMAT). It supports filenames up to a length of at best 256 characters and linknames up to 100 characters. The maximum file size is 8 GiB. This is an old and limited but widely supported format.

The GNU tar format (GNU_FORMAT). It supports long filenames and linknames, files bigger than 8 GiB and sparse files. It is the de facto standard on GNU/Linux systems. tarfile fully supports the GNU tar extensions for long names, sparse file support is read-only.

The POSIX.1-2001 pax format (PAX_FORMAT). It is the most flexible format with virtually no limits. It supports long filenames and linknames, large files and stores pathnames in a portable way. However, not all tar implementations today are able to handle pax archives properly.

The pax format is an extension to the existing ustar format. It uses extra headers for information that cannot be stored otherwise. There are two flavours of pax headers: Extended headers only affect the subsequent file header, global headers are valid for the complete archive and affect all following files. All the data in a pax header is encoded in UTF-8 for portability reasons.

There are some more variants of the tar format which can be read, but not created:

The ancient V7 format. This is the first tar format from Unix Seventh Edition, storing only regular files and directories. Names must not be longer than 100 characters, there is no user/group name information. Some archives have miscalculated header checksums in case of fields with non-ASCII characters.

The SunOS tar extended format. This format is a variant of the POSIX.1-2001 pax format, but is not compatible.

13.6.6. Unicode issues

The tar format was originally conceived to make backups on tape drives with the main focus on preserving file system information. Nowadays tar archives are commonly used for file distribution and exchanging archives over networks. One problem of the original format (which is the basis of all other formats) is that there is no concept of supporting different character encodings. For example, an ordinary tar archive created on a UTF-8 system cannot be read correctly on a Latin-1 system if it contains non-ASCII characters. Textual metadata (like filenames, linknames, user/group names) will appear damaged. Unfortunately, there is no way to autodetect the encoding of an archive. The pax format was designed to solve this problem. It stores non-ASCII metadata using the universal character encoding UTF-8.

The details of character conversion in tarfile are controlled by the encoding and errors keyword arguments of the TarFile class.

encoding defines the character encoding to use for the metadata in the archive. The default value is sys.getfilesystemencoding() or 'ascii' as a fallback. Depending on whether the archive is read or written, the metadata must be either decoded or encoded. If encoding is not set appropriately, this conversion may fail.

The errors argument defines how characters are treated that cannot be converted. Possible values are listed in section Gestionnaires d’erreurs. The default scheme is 'surrogateescape' which Python also uses for its file system calls, see Noms de fichiers, arguments en ligne de commande, et variables d’environnement.

In case of PAX_FORMAT archives, encoding is generally not needed because all the metadata is stored using UTF-8. encoding is only used in the rare cases when binary pax headers are decoded or when strings with surrogate characters are stored.

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14. Formats de fichiers

Les modules décrits dans ce chapitre lisent divers formats de fichier qui ne sont ni des langages balisés ni relatifs aux e-mails.

14.1. csv — Lecture et écriture de fichiers CSV

14.1.1. Contenu du module

14.1.2. Dialectes et paramètres de formatage

14.1.3. Objets lecteurs

14.1.4. Objets transcripteurs

14.1.5. Exemples

14.2. configparser — Configuration file parser

14.2.1. Quick Start

14.2.2. Supported Datatypes

14.2.3. Fallback Values

14.2.4. Supported INI File Structure

14.2.5. Interpolation of values

14.2.6. Mapping Protocol Access

14.2.7. Customizing Parser Behaviour

14.2.8. Legacy API Examples

14.2.9. ConfigParser Objects

14.2.10. RawConfigParser Objects

14.2.11. Exceptions

14.3. netrc — traitement de fichier netrc

14.3.1. Objets netrc

14.4. xdrlib — Encode and decode XDR data

14.4.1. Packer Objects

14.4.2. Unpacker Objects

14.4.3. Exceptions

14.5. plistlib — Generate and parse Mac OS X .plist files

14.5.1. Exemples

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14.1. csv — Lecture et écriture de fichiers CSV

Code source : Lib/csv.py [https://github.com/python/cpython/tree/3.6/Lib/csv.py]

Le format CSV (Comma Separated Values, valeurs séparées par des virgules) est le format le plus commun dans l’importation et l’exportation de feuilles de calculs et de bases de données. Le format fut utilisé pendant des années avant qu’aient lieu des tentatives de standardisation avec la RFC 4180 [https://tools.ietf.org/html/rfc4180.html]. L’absence de format bien défini signifie que des différences subtiles existent dans la production et la consommation de données par différentes applications. Ces différences peuvent gêner lors du traitement de fichiers CSV depuis des sources multiples. Cependant, bien que les séparateurs et délimiteurs varient, le format global est suffisamment similaire pour qu’un module unique puisse manipuler efficacement ces données, masquant au programmeur les détails de lecture/écriture des données.

Le module csv implémente des classes pour lire et écrire des données tabulaires au format CSV. Il vous permet de dire « écris ces données dans le format préféré par Excel » ou « lis les données de ce fichier généré par Excel », sans connaître les détails précis du format CSV utilisé par Excel. Vous pouvez aussi décrire les formats CSV utilisés par d’autres application ou définir vos propres spécialisations.

Les objets reader et writer du module csv lisent et écrivent des séquences. Vous pouvez aussi lire/écrire les données dans un dictionnaire en utilisant les classes DictReader et DictWriter.

Voir aussi

PEP 305 [https://www.python.org/dev/peps/pep-0305] — Interface des fichiers CSV

La proposition d’amélioration de Python (PEP) qui a proposé cet ajout au langage.

14.1.1. Contenu du module

Le module csv définit les fonctions suivantes :

csv.reader(csvfile, dialect='excel', **fmtparams)

Renvoie un objet lecteur, qui itérera sur les lignes de l’objet csvfile donné. csvfile peut être n’importe quel objet supportant le protocole itérateur et renvoyant une chaîne de caractères chaque fois que sa méthode __next__() est appelée — les fichiers objets et les listes sont tous deux valables. Si csvfile est un fichier, il doit être ouvert avec newline=''. 1 Un paramètre dialect optionnel peut être fourni pour définir un ensemble de paramètres spécifiques à un dialecte CSV particulier. Il peut s’agir d’une instance de sous-classe de Dialect ou de l’une des chaînes renvoyées par la fonction list_dialects(). Les autres arguments nommés optionnels (fmtparams) peuvent être spécifiés pour redéfinir des paramètres de formatage particuliers dans le dialecte courant. Pour des détails complets sur les dialectes et paramètres de formatage, voir la section Dialectes et paramètres de formatage.

Chaque ligne lue depuis le fichier CSV est renvoyée comme une liste de chaînes de caractères. Aucune conversion automatique de type des données n’est effectuée à moins que l’option de formatage QUOTE_NONNUMERIC soit spécifiée (dans ce cas, les champs sans guillemets sont transformés en nombres flottants).

Un court exemple d’utilisation :

>>> import csv
>>> with open('eggs.csv', newline='') as csvfile:
...     spamreader = csv.reader(csvfile, delimiter=' ', quotechar='|')
...     for row in spamreader:
...         print(', '.join(row))
Spam, Spam, Spam, Spam, Spam, Baked Beans
Spam, Lovely Spam, Wonderful Spam

csv.writer(csvfile, dialect='excel', **fmtparams)

Renvoie un objet transcripteur responsable de convertir les données de l’utilisateur en chaînes délimitées sur l’objet fichier-compatible donné. csvfile peut être n’importe quel objet avec une méthode write(). Si csvfile est un fichier, il doit être ouvert avec newline=''. 1 Un paramètre dialect optionnel peut être fourni pour définir un ensemble de paramètres spécifiques à un dialecte CSV particulier. Il peut s’agir d’une instance de sous-classe de Dialect ou de l’une des chaînes renvoyées par la fonction list_dialects(). Les autres arguments nommés optionnels (fmtparams) peuvent être spécifiés pour redéfinir des paramètres de formatage particuliers dans le dialecte courant. Pour des détails complets sur les dialectes et paramètres de formatage, voir la section Dialectes et paramètres de formatage. Pour faciliter au mieux l’interfaçage avec d’autres modules implémentant l’interface DB, la valeur None est écrite comme une chaîne vide. Bien que ce ne soit pas une transformation réversible, cela simplifie l’exportation de données SQL NULL vers des fichiers CSV sans pré-traiter les données renvoyées par un appel à cursor.fetch*. Toutes les autres données qui ne sont pas des chaînes de caractères sont transformées en chaînes par un appel à str() avant d’être écrites.

Un court exemple d’utilisation :

import csv
with open('eggs.csv', 'w', newline='') as csvfile:
    spamwriter = csv.writer(csvfile, delimiter=' ',
                            quotechar='|', quoting=csv.QUOTE_MINIMAL)
    spamwriter.writerow(['Spam'] * 5 + ['Baked Beans'])
    spamwriter.writerow(['Spam', 'Lovely Spam', 'Wonderful Spam'])

csv.register_dialect(name[, dialect[, **fmtparams]])

Associe dialect avec name. name doit être une chaîne de caractères. Le dialecte peut être spécifié en passant une instance d’une sous-classe de Dialect, des arguments nommés fmtparams, ou les deux, avec les arguments nommés redéfinissant les paramètres du dialecte. Pour des détails complets sur les dialectes et paramètres de formatage, voir la section Dialectes et paramètres de formatage.

csv.unregister_dialect(name)

Supprime le dialecte associé à name depuis le registre des dialectes. Une Error est levée si name n’est pas un nom de dialecte enregistré.

csv.get_dialect(name)

Renvoie le dialecte associé à name. Une Error est levée si name n’est pas un nom de dialecte enregistré. Cette fonction renvoie un objet Dialect immuable.

csv.list_dialects()

Renvoie les noms de tous les dialectes enregistrés.

csv.field_size_limit([new_limit])

Renvoie la taille de champ maximale courante autorisée par l’analyseur. Si new_limit est donnée, elle devient la nouvelle limite.

Le module csv définit les classes suivantes :

class csv.DictReader(f, fieldnames=None, restkey=None, restval=None, dialect='excel', *args, **kwds)

Crée un objet qui opère comme un lecteur ordinaire mais assemble les informations de chaque ligne dans un OrderedDict dont les clés sont données par le paramètre optionnel fieldnames.

Le paramètre fieldnames est une sequence. Si fieldnames est omis, les valeurs de la première ligne du fichier f seront utilisées comme noms de champs. Sans se soucier de comment sont déterminés les noms de champs, le dictionnaire ordonné préserve leur ordre original.

Si une ligne a plus de champs que fieldnames, les données excédentaires sont mises dans une liste stockée dans le champ spécifié par restkey (None par défaut). Si une ligne non-vide a moins de champs que fieldnames, les valeurs manquantes sont mises à None.

Tous les autres arguments optionnels ou nommés sont passés à l’instance reader sous-jacente.

Modifié dans la version 3.6: Les lignes renvoyées sont maintenant de type OrderedDict.

Un court exemple d’utilisation :

>>> import csv
>>> with open('names.csv', newline='') as csvfile:
...     reader = csv.DictReader(csvfile)
...     for row in reader:
...         print(row['first_name'], row['last_name'])
...
Eric Idle
John Cleese

>>> print(row)
OrderedDict([('first_name', 'John'), ('last_name', 'Cleese')])

class csv.DictWriter(f, fieldnames, restval='', extrasaction='raise', dialect='excel', *args, **kwds)

Crée un objet qui opère comme un transcripteur ordinaire mais qui produit les lignes de sortie depuis des dictionnaires. Le paramètre fieldnames est une séquence de clés qui indique l’ordre dans lequel les valeurs du dictionnaire passé à la méthode writerow() doivent être écrites vers le fichier f. Le paramètre optionnel restval spécifie la valeur à écrire si une clé de fieldnames manque dans le dictionnaire. Si le dictionnaire passé à writerow() possède une clé non présente dans fieldnames, le paramètre optionnel extrasaction indique quelle action réaliser. S’il vaut 'raise', sa valeur par défaut, une ValueError est levée. S’il faut 'ignore', les valeurs excédentaires du dictionnaire sont ignorées. Les autres arguments optionnels ou nommés sont passés à l’instance writer sous-jacente.

Notez que contrairement à la classe DictReader, le paramètre fieldnames de DictWriter n’est pas optionnel. Puisque les objets dict de Python ne sont pas ordonnés, il n’y a pas d’information suffisante pour déduire l’ordre dans lequel la ligne devrait être transcrite vers le fichier f.

Un court exemple d’utilisation :

import csv

with open('names.csv', 'w', newline='') as csvfile:
    fieldnames = ['first_name', 'last_name']
    writer = csv.DictWriter(csvfile, fieldnames=fieldnames)

    writer.writeheader()
    writer.writerow({'first_name': 'Baked', 'last_name': 'Beans'})
    writer.writerow({'first_name': 'Lovely', 'last_name': 'Spam'})
    writer.writerow({'first_name': 'Wonderful', 'last_name': 'Spam'})

class csv.Dialect

La classe Dialect est une classe de conteneurs utilisée principalement pour ses attributs, qui servent à définir des paramètres pour des instances spécifiques de reader ou writer.

class csv.excel

La classe excel définit les propriétés usuelles d’un fichier CSV généré par Excel. Elle est enregistrée avec le nom de dialecte 'excel'.

class csv.excel_tab

La classe excel_tab définit les propriétés usuelles d’un fichier CSV généré par Excel avec des tabulations comme séparateurs. Elle est enregistrée avec le nom de dialecte 'excel-tab'.

class csv.unix_dialect

La classe unix_dialect définit les propriétés usuelles d’un fichier CSV généré sur un système Unix, c’est-à-dire utilisant '\n' comme marqueur de fin de ligne et délimitant tous les champs par des guillemets. Elle est enregistrée avec le nom de dialecte 'unix'.

Nouveau dans la version 3.2.

class csv.Sniffer

La classe Sniffer est utilisée pour déduire le format d’un fichier CSV.

La classe Sniffer fournit deux méthodes :

sniff(sample, delimiters=None)

Analyse l’extrait donné (sample) et renvoie une sous-classe Dialect reflétant les paramètres trouvés. Si le paramètre optionnel delimiters est donné, il est interprété comme une chaîne contenant tous les caractères valides de séparation possibles.

has_header(sample)

Analyse l’extrait de texte (présumé être au format CSV) et renvoie True si la première ligne semble être une série d’en-têtes de colonnes.

Un exemple d’utilisation de Sniffer :

with open('example.csv', newline='') as csvfile:
    dialect = csv.Sniffer().sniff(csvfile.read(1024))
    csvfile.seek(0)
    reader = csv.reader(csvfile, dialect)
    # ... process CSV file contents here ...

Le module csv définit les constantes suivantes :

csv.QUOTE_ALL

Indique aux objets writer de délimiter tous les champs par des guillemets.

csv.QUOTE_MINIMAL

Indique aux objets writer de ne délimiter ainsi que les champs contenant un caractère spécial comme delimiter, quotechar ou n’importe quel caractère de lineterminator.

csv.QUOTE_NONNUMERIC

Indique aux objets writer de délimiter ainsi tous les champs non-numériques.

Indique au lecteur de convertir tous les champs non délimités par des guillemets vers des float.

csv.QUOTE_NONE

Indique aux objets writer de ne jamais délimiter les champs par des guillemets. Quand le delimiter courant apparaît dans les données, il est précédé sur la sortie par un caractère escapechar. Si escapechar n’est pas précisé, le transcripteur lèvera une Error si un caractère nécessitant un échappement est rencontré.

Indique au reader de ne pas opérer de traitement spécial sur les guillemets.

Le module csv définit les exceptions suivantes :

exception csv.Error

Levée par les fonctions du module quand une erreur détectée.

14.1.2. Dialectes et paramètres de formatage

Pour faciliter la spécification du format des entrées et sorties, les paramètres de formatage spécifiques sont regroupés en dialectes. Un dialecte est une sous-classe de Dialect avec un ensemble de méthodes spécifiques et une méthode validate(). Quand un objet reader ou writer est créé, vous pouvez spécifier une chaîne ou une sous-classe de Dialect comme paramètre dialect. En plus du paramètre dialect, ou à sa place, vous pouvez aussi préciser des paramètres de formatage individuels, qui ont les mêmes noms que les attributs de Dialect définis ci-dessous.

Les dialectes supportent les attributs suivants :

Dialect.delimiter

Une chaîne d’un seul caractère utilisée pour séparer les champs. Elle vaut ',' par défaut.

Dialect.doublequote

Contrôle comment les caractères quotechar dans le champ doivent être retranscrits. Quand ce paramètre vaut True, le caractère est doublé. Quand il vaut False, le caractère escapechar est utilisé comme préfixe à quotechar. Il vaut True par défaut.

En écriture, si doublequote vaut False et qu’aucun escapechar n’est précisé, une Error est levée si un quotechar est trouvé dans le champ.

Dialect.escapechar

Une chaîne d’un seul caractère utilisée par le transcripteur pour échapper delimiter si quoting vaut QUOTE_NONE, et pour échapper quotechar si doublequote vaut False. À la lecture, escapechar retire toute signification spéciale au caractère qui le suit. Elle vaut par défaut None, ce qui désactive l’échappement.

Dialect.lineterminator

La chaîne utilisée pour terminer les lignes produites par un writer. Elle vaut par défaut '\r\n'.

Note

La classe reader est codée en dur pour reconnaître '\r' et '\n' comme marqueurs de fin de ligne, et ignorer lineterminator. Ce comportement pourrait changer dans le futur.

Dialect.quotechar

Une chaîne d’un seul caractère utilisée pour délimiter les champs contenant des caractères spéciaux, comme delimiter ou quotechar, ou contenant un caractère de fin de ligne. Elle vaut '"' par défaut.

Dialect.quoting

Contrôle quand les guillemets doivent être générés par le transcripteur et reconnus par le lecteur. Il peut prendre comme valeur l’une des constantes QUOTE_* (voir la section Contenu du module) et vaut par défaut QUOTE_MINIMAL.

Dialect.skipinitialspace

Quand il vaut True, les espaces suivant directement delimiter sont ignorés. Il vaut False par défaut.

Dialect.strict

Quand il vaut True, une exception Error est levée lors de mauvaises entrées CSV. Il vaut False par défaut.

14.1.3. Objets lecteurs

Les objets lecteurs (instances de DictReader ou objets renvoyés par la fonction reader()) ont les méthodes publiques suivantes :

csvreader.__next__()

Renvoie la ligne suivante de l’objet itérable du lecteur en tant que liste (si l’objet est renvoyé depuis reader()) ou dictionnaire (si l’objet est un DictReader), analysé suivant le dialecte courant. Généralement, vous devez appeler la méthode à l’aide de next(reader).

Les objets lecteurs ont les attributs publics suivants :

csvreader.dialect

Une description en lecture seule du dialecte utilisé par l’analyseur.

csvreader.line_num

Le nombre de lignes lues depuis l’itérateur source. Ce n’est pas équivalent au nombre d’enregistrements renvoyés, puisque certains enregistrements peuvent s’étendre sur plusieurs lignes.

Les objets DictReader ont les attributs publics suivants :

csvreader.fieldnames

S’il n’est pas passé comme paramètre à la création de l’objet, cet attribut est initialisé lors du premier accès ou quand le premier enregistrement est lu depuis le fichier.

14.1.4. Objets transcripteurs

Les objets Writer (instances de DictWriter ou objets renvoyés par la fonction writer()) ont les méthodes publiques suivantes. Une row doit être un itérable de chaînes de caractères ou de nombres pour les objets Writer, et un dictionnaire associant des noms de champs à des chaînes ou des nombres (en les faisant d’abord passer par str()) pour les objets DictWriter. Notez que les nombres complexes sont retranscrits entourés de parenthèses. Cela peut causer quelques problèmes pour d’autres programmes qui liraient ces fichiers CSV (en supposant qu’ils supportent les nombres complexes).

csvwriter.writerow(row)

Écrit le paramètre row vers le fichier associé au transcripteur, formaté selon le dialecte courant.

Modifié dans la version 3.5: Ajout du support d’itérables arbitraires.

csvwriter.writerows(rows)

Écrit tous les éléments de rows (itérable d’objets row comme décrits précédemment) vers le fichier associé au transcripteur, formatés selon le dialecte courant.

Les objets transcripteurs ont les attributs publics suivants :

csvwriter.dialect

Une description en lecture seule du dialecte utilisé par le transcripteur.

Les objets DictWriter ont les attributs publics suivants :

DictWriter.writeheader()

Écrit une ligne contenant les noms de champs (comme spécifiés au constructeur).

Nouveau dans la version 3.2.

14.1.5. Exemples

Le plus simple exemple de lecture d’un fichier CSV :

import csv
with open('some.csv', newline='') as f:
    reader = csv.reader(f)
    for row in reader:
        print(row)

Lire un fichier avec un format alternatif :

import csv
with open('passwd', newline='') as f:
    reader = csv.reader(f, delimiter=':', quoting=csv.QUOTE_NONE)
    for row in reader:
        print(row)

Le plus simple exemple d’écriture correspondant est :

import csv
with open('some.csv', 'w', newline='') as f:
    writer = csv.writer(f)
    writer.writerows(someiterable)

Puisque open() est utilisée pour ouvrir un fichier CSV en lecture, le fichier sera par défaut décodé vers Unicode en utilisant l’encodage par défaut (voir locale.getpreferredencoding()). Pour décoder un fichier utilisant un encodage différent, utilisez l’argument encoding de open :

import csv
with open('some.csv', newline='', encoding='utf-8') as f:
    reader = csv.reader(f)
    for row in reader:
        print(row)

La même chose s’applique lors de l’écriture dans un autre encodage que celui par défaut du système : spécifiez l’encodage en argument lors de l’ouverture du fichier de sortie.

Enregistrer un nouveau dialecte :

import csv
csv.register_dialect('unixpwd', delimiter=':', quoting=csv.QUOTE_NONE)
with open('passwd', newline='') as f:
    reader = csv.reader(f, 'unixpwd')

Un exemple d’utilisation un peu plus avancé du lecteur — attrapant et notifiant les erreurs :

import csv, sys
filename = 'some.csv'
with open(filename, newline='') as f:
    reader = csv.reader(f)
    try:
        for row in reader:
            print(row)
    except csv.Error as e:
        sys.exit('file {}, line {}: {}'.format(filename, reader.line_num, e))

Et bien que le module ne permette pas d’analyser directement des chaînes, cela peut être fait facilement :

import csv
for row in csv.reader(['one,two,three']):
    print(row)

Notes

1(1,2)

Si newline='' n’est pas spécifié, les caractères de fin de ligne embarqués dans des champs délimités par des guillemets ne seront pas interprétés correctement, et sur les plateformes qui utilisent \r\n comme marqueur de fin de ligne, un \r sera ajouté. Vous devriez toujours spécifier sans crainte newline='', puisque le module csv gère lui-même les fins de lignes (universelles).

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14.2. configparser — Configuration file parser

Code source : Lib/configparser.py [https://github.com/python/cpython/tree/3.6/Lib/configparser.py]

This module provides the ConfigParser class which implements a basic configuration language which provides a structure similar to what’s found in Microsoft Windows INI files. You can use this to write Python programs which can be customized by end users easily.

Note

This library does not interpret or write the value-type prefixes used in the Windows Registry extended version of INI syntax.

Voir aussi

Module shlex

Support for creating Unix shell-like mini-languages which can be used as an alternate format for application configuration files.

Module json

The json module implements a subset of JavaScript syntax which can also be used for this purpose.

14.2.1. Quick Start

Let’s take a very basic configuration file that looks like this:

[DEFAULT]
ServerAliveInterval = 45
Compression = yes
CompressionLevel = 9
ForwardX11 = yes

[bitbucket.org]
User = hg

[topsecret.server.com]
Port = 50022
ForwardX11 = no

The structure of INI files is described in the following section. Essentially, the file consists of sections, each of which contains keys with values. configparser classes can read and write such files. Let’s start by creating the above configuration file programmatically.

>>> import configparser
>>> config = configparser.ConfigParser()
>>> config['DEFAULT'] = {'ServerAliveInterval': '45',
...                      'Compression': 'yes',
...                      'CompressionLevel': '9'}
>>> config['bitbucket.org'] = {}
>>> config['bitbucket.org']['User'] = 'hg'
>>> config['topsecret.server.com'] = {}
>>> topsecret = config['topsecret.server.com']
>>> topsecret['Port'] = '50022'     # mutates the parser
>>> topsecret['ForwardX11'] = 'no'  # same here
>>> config['DEFAULT']['ForwardX11'] = 'yes'
>>> with open('example.ini', 'w') as configfile:
...   config.write(configfile)
...

As you can see, we can treat a config parser much like a dictionary. There are differences, outlined later, but the behavior is very close to what you would expect from a dictionary.

Now that we have created and saved a configuration file, let’s read it back and explore the data it holds.

>>> import configparser
>>> config = configparser.ConfigParser()
>>> config.sections()
[]
>>> config.read('example.ini')
['example.ini']
>>> config.sections()
['bitbucket.org', 'topsecret.server.com']
>>> 'bitbucket.org' in config
True
>>> 'bytebong.com' in config
False
>>> config['bitbucket.org']['User']
'hg'
>>> config['DEFAULT']['Compression']
'yes'
>>> topsecret = config['topsecret.server.com']
>>> topsecret['ForwardX11']
'no'
>>> topsecret['Port']
'50022'
>>> for key in config['bitbucket.org']: print(key)
...
user
compressionlevel
serveraliveinterval
compression
forwardx11
>>> config['bitbucket.org']['ForwardX11']
'yes'

As we can see above, the API is pretty straightforward. The only bit of magic involves the DEFAULT section which provides default values for all other sections 1. Note also that keys in sections are case-insensitive and stored in lowercase 1.

14.2.2. Supported Datatypes

Config parsers do not guess datatypes of values in configuration files, always storing them internally as strings. This means that if you need other datatypes, you should convert on your own:

>>> int(topsecret['Port'])
50022
>>> float(topsecret['CompressionLevel'])
9.0

Since this task is so common, config parsers provide a range of handy getter methods to handle integers, floats and booleans. The last one is the most interesting because simply passing the value to bool() would do no good since bool('False') is still True. This is why config parsers also provide getboolean(). This method is case-insensitive and recognizes Boolean values from 'yes'/'no', 'on'/'off', 'true'/'false' and '1'/'0' 1. For example:

>>> topsecret.getboolean('ForwardX11')
False
>>> config['bitbucket.org'].getboolean('ForwardX11')
True
>>> config.getboolean('bitbucket.org', 'Compression')
True

Apart from getboolean(), config parsers also provide equivalent getint() and getfloat() methods. You can register your own converters and customize the provided ones. 1

14.2.3. Fallback Values

As with a dictionary, you can use a section’s get() method to provide fallback values:

>>> topsecret.get('Port')
'50022'
>>> topsecret.get('CompressionLevel')
'9'
>>> topsecret.get('Cipher')
>>> topsecret.get('Cipher', '3des-cbc')
'3des-cbc'

Please note that default values have precedence over fallback values. For instance, in our example the 'CompressionLevel' key was specified only in the 'DEFAULT' section. If we try to get it from the section 'topsecret.server.com', we will always get the default, even if we specify a fallback:

>>> topsecret.get('CompressionLevel', '3')
'9'

One more thing to be aware of is that the parser-level get() method provides a custom, more complex interface, maintained for backwards compatibility. When using this method, a fallback value can be provided via the fallback keyword-only argument:

>>> config.get('bitbucket.org', 'monster',
...            fallback='No such things as monsters')
'No such things as monsters'

The same fallback argument can be used with the getint(), getfloat() and getboolean() methods, for example:

>>> 'BatchMode' in topsecret
False
>>> topsecret.getboolean('BatchMode', fallback=True)
True
>>> config['DEFAULT']['BatchMode'] = 'no'
>>> topsecret.getboolean('BatchMode', fallback=True)
False

14.2.4. Supported INI File Structure

A configuration file consists of sections, each led by a [section] header, followed by key/value entries separated by a specific string (= or : by default 1). By default, section names are case sensitive but keys are not 1. Leading and trailing whitespace is removed from keys and values. Values can be omitted, in which case the key/value delimiter may also be left out. Values can also span multiple lines, as long as they are indented deeper than the first line of the value. Depending on the parser’s mode, blank lines may be treated as parts of multiline values or ignored.

Configuration files may include comments, prefixed by specific characters (# and ; by default 1). Comments may appear on their own on an otherwise empty line, possibly indented. 1

Par exemple :

[Simple Values]
key=value
spaces in keys=allowed
spaces in values=allowed as well
spaces around the delimiter = obviously
you can also use : to delimit keys from values

[All Values Are Strings]
values like this: 1000000
or this: 3.14159265359
are they treated as numbers? : no
integers, floats and booleans are held as: strings
can use the API to get converted values directly: true

[Multiline Values]
chorus: I'm a lumberjack, and I'm okay
    I sleep all night and I work all day

[No Values]
key_without_value
empty string value here =

[You can use comments]
# like this
; or this

# By default only in an empty line.
# Inline comments can be harmful because they prevent users
# from using the delimiting characters as parts of values.
# That being said, this can be customized.

    [Sections Can Be Indented]
        can_values_be_as_well = True
        does_that_mean_anything_special = False
        purpose = formatting for readability
        multiline_values = are
            handled just fine as
            long as they are indented
            deeper than the first line
            of a value
        # Did I mention we can indent comments, too?

14.2.5. Interpolation of values

On top of the core functionality, ConfigParser supports interpolation. This means values can be preprocessed before returning them from get() calls.

class configparser.BasicInterpolation

The default implementation used by ConfigParser. It enables values to contain format strings which refer to other values in the same section, or values in the special default section 1. Additional default values can be provided on initialization.

Par exemple :

[Paths]
home_dir: /Users
my_dir: %(home_dir)s/lumberjack
my_pictures: %(my_dir)s/Pictures

In the example above, ConfigParser with interpolation set to BasicInterpolation() would resolve %(home_dir)s to the value of home_dir (/Users in this case). %(my_dir)s in effect would resolve to /Users/lumberjack. All interpolations are done on demand so keys used in the chain of references do not have to be specified in any specific order in the configuration file.

With interpolation set to None, the parser would simply return %(my_dir)s/Pictures as the value of my_pictures and %(home_dir)s/lumberjack as the value of my_dir.

class configparser.ExtendedInterpolation

An alternative handler for interpolation which implements a more advanced syntax, used for instance in zc.buildout. Extended interpolation is using ${section:option} to denote a value from a foreign section. Interpolation can span multiple levels. For convenience, if the section: part is omitted, interpolation defaults to the current section (and possibly the default values from the special section).

For example, the configuration specified above with basic interpolation, would look like this with extended interpolation:

[Paths]
home_dir: /Users
my_dir: ${home_dir}/lumberjack
my_pictures: ${my_dir}/Pictures

Values from other sections can be fetched as well:

[Common]
home_dir: /Users
library_dir: /Library
system_dir: /System
macports_dir: /opt/local

[Frameworks]
Python: 3.2
path: ${Common:system_dir}/Library/Frameworks/

[Arthur]
nickname: Two Sheds
last_name: Jackson
my_dir: ${Common:home_dir}/twosheds
my_pictures: ${my_dir}/Pictures
python_dir: ${Frameworks:path}/Python/Versions/${Frameworks:Python}

14.2.6. Mapping Protocol Access

Nouveau dans la version 3.2.

Mapping protocol access is a generic name for functionality that enables using custom objects as if they were dictionaries. In case of configparser, the mapping interface implementation is using the parser['section']['option'] notation.

parser['section'] in particular returns a proxy for the section’s data in the parser. This means that the values are not copied but they are taken from the original parser on demand. What’s even more important is that when values are changed on a section proxy, they are actually mutated in the original parser.

configparser objects behave as close to actual dictionaries as possible. The mapping interface is complete and adheres to the MutableMapping ABC. However, there are a few differences that should be taken into account:

By default, all keys in sections are accessible in a case-insensitive manner 1. E.g. for option in parser["section"] yields only optionxform’ed option key names. This means lowercased keys by default. At the same time, for a section that holds the key 'a', both expressions return True:

"a" in parser["section"]
"A" in parser["section"]

All sections include DEFAULTSECT values as well which means that .clear() on a section may not leave the section visibly empty. This is because default values cannot be deleted from the section (because technically they are not there). If they are overridden in the section, deleting causes the default value to be visible again. Trying to delete a default value causes a KeyError.

DEFAULTSECT cannot be removed from the parser:

trying to delete it raises ValueError,

parser.clear() leaves it intact,

parser.popitem() never returns it.

parser.get(section, option, **kwargs) - the second argument is not a fallback value. Note however that the section-level get() methods are compatible both with the mapping protocol and the classic configparser API.

parser.items() is compatible with the mapping protocol (returns a list of section_name, section_proxy pairs including the DEFAULTSECT). However, this method can also be invoked with arguments: parser.items(section, raw, vars). The latter call returns a list of option, value pairs for a specified section, with all interpolations expanded (unless raw=True is provided).

The mapping protocol is implemented on top of the existing legacy API so that subclasses overriding the original interface still should have mappings working as expected.

14.2.7. Customizing Parser Behaviour

There are nearly as many INI format variants as there are applications using it. configparser goes a long way to provide support for the largest sensible set of INI styles available. The default functionality is mainly dictated by historical background and it’s very likely that you will want to customize some of the features.

The most common way to change the way a specific config parser works is to use the __init__() options:

defaults, default value: None

This option accepts a dictionary of key-value pairs which will be initially put in the DEFAULT section. This makes for an elegant way to support concise configuration files that don’t specify values which are the same as the documented default.

Hint: if you want to specify default values for a specific section, use read_dict() before you read the actual file.

dict_type, default value: collections.OrderedDict

This option has a major impact on how the mapping protocol will behave and how the written configuration files look. With the default ordered dictionary, every section is stored in the order they were added to the parser. Same goes for options within sections.

An alternative dictionary type can be used for example to sort sections and options on write-back. You can also use a regular dictionary for performance reasons.

Please note: there are ways to add a set of key-value pairs in a single operation. When you use a regular dictionary in those operations, the order of the keys may be random. For example:

>>> parser = configparser.ConfigParser()
>>> parser.read_dict({'section1': {'key1': 'value1',
...                                'key2': 'value2',
...                                'key3': 'value3'},
...                   'section2': {'keyA': 'valueA',
...                                'keyB': 'valueB',
...                                'keyC': 'valueC'},
...                   'section3': {'foo': 'x',
...                                'bar': 'y',
...                                'baz': 'z'}
... })
>>> parser.sections()
['section3', 'section2', 'section1']
>>> [option for option in parser['section3']]
['baz', 'foo', 'bar']

In these operations you need to use an ordered dictionary as well:

>>> from collections import OrderedDict
>>> parser = configparser.ConfigParser()
>>> parser.read_dict(
...   OrderedDict((
...     ('s1',
...      OrderedDict((
...        ('1', '2'),
...        ('3', '4'),
...        ('5', '6'),
...      ))
...     ),
...     ('s2',
...      OrderedDict((
...        ('a', 'b'),
...        ('c', 'd'),
...        ('e', 'f'),
...      ))
...     ),
...   ))
... )
>>> parser.sections()
['s1', 's2']
>>> [option for option in parser['s1']]
['1', '3', '5']
>>> [option for option in parser['s2'].values()]
['b', 'd', 'f']

allow_no_value, default value: False

Some configuration files are known to include settings without values, but which otherwise conform to the syntax supported by configparser. The allow_no_value parameter to the constructor can be used to indicate that such values should be accepted:

>>> import configparser

>>> sample_config = """
... [mysqld]
...   user = mysql
...   pid-file = /var/run/mysqld/mysqld.pid
...   skip-external-locking
...   old_passwords = 1
...   skip-bdb
...   # we don't need ACID today
...   skip-innodb
... """
>>> config = configparser.ConfigParser(allow_no_value=True)
>>> config.read_string(sample_config)

>>> # Settings with values are treated as before:
>>> config["mysqld"]["user"]
'mysql'

>>> # Settings without values provide None:
>>> config["mysqld"]["skip-bdb"]

>>> # Settings which aren't specified still raise an error:
>>> config["mysqld"]["does-not-exist"]
Traceback (most recent call last):
  ...
KeyError: 'does-not-exist'

delimiters, default value: ('=', ':')

Delimiters are substrings that delimit keys from values within a section. The first occurrence of a delimiting substring on a line is considered a delimiter. This means values (but not keys) can contain the delimiters.

See also the space_around_delimiters argument to ConfigParser.write().

comment_prefixes, default value: ('#', ';')

inline_comment_prefixes, default value: None

Comment prefixes are strings that indicate the start of a valid comment within a config file. comment_prefixes are used only on otherwise empty lines (optionally indented) whereas inline_comment_prefixes can be used after every valid value (e.g. section names, options and empty lines as well). By default inline comments are disabled and '#' and ';' are used as prefixes for whole line comments.

Modifié dans la version 3.2: In previous versions of configparser behaviour matched comment_prefixes=('#',';') and inline_comment_prefixes=(';',).

Please note that config parsers don’t support escaping of comment prefixes so using inline_comment_prefixes may prevent users from specifying option values with characters used as comment prefixes. When in doubt, avoid setting inline_comment_prefixes. In any circumstances, the only way of storing comment prefix characters at the beginning of a line in multiline values is to interpolate the prefix, for example:

>>> from configparser import ConfigParser, ExtendedInterpolation
>>> parser = ConfigParser(interpolation=ExtendedInterpolation())
>>> # the default BasicInterpolation could be used as well
>>> parser.read_string("""
... [DEFAULT]
... hash = #
...
... [hashes]
... shebang =
...   ${hash}!/usr/bin/env python
...   ${hash} -*- coding: utf-8 -*-
...
... extensions =
...   enabled_extension
...   another_extension
...   #disabled_by_comment
...   yet_another_extension
...
... interpolation not necessary = if # is not at line start
... even in multiline values = line #1
...   line #2
...   line #3
... """)
>>> print(parser['hashes']['shebang'])

#!/usr/bin/env python
# -*- coding: utf-8 -*-
>>> print(parser['hashes']['extensions'])

enabled_extension
another_extension
yet_another_extension
>>> print(parser['hashes']['interpolation not necessary'])
if # is not at line start
>>> print(parser['hashes']['even in multiline values'])
line #1
line #2
line #3

strict, default value: True

When set to True, the parser will not allow for any section or option duplicates while reading from a single source (using read_file(), read_string() or read_dict()). It is recommended to use strict parsers in new applications.

Modifié dans la version 3.2: In previous versions of configparser behaviour matched strict=False.

empty_lines_in_values, default value: True

In config parsers, values can span multiple lines as long as they are indented more than the key that holds them. By default parsers also let empty lines to be parts of values. At the same time, keys can be arbitrarily indented themselves to improve readability. In consequence, when configuration files get big and complex, it is easy for the user to lose track of the file structure. Take for instance:

[Section]
key = multiline
  value with a gotcha

 this = is still a part of the multiline value of 'key'

This can be especially problematic for the user to see if she’s using a proportional font to edit the file. That is why when your application does not need values with empty lines, you should consider disallowing them. This will make empty lines split keys every time. In the example above, it would produce two keys, key and this.

default_section, default value: configparser.DEFAULTSECT (that is: "DEFAULT")

The convention of allowing a special section of default values for other sections or interpolation purposes is a powerful concept of this library, letting users create complex declarative configurations. This section is normally called "DEFAULT" but this can be customized to point to any other valid section name. Some typical values include: "general" or "common". The name provided is used for recognizing default sections when reading from any source and is used when writing configuration back to a file. Its current value can be retrieved using the parser_instance.default_section attribute and may be modified at runtime (i.e. to convert files from one format to another).

interpolation, default value: configparser.BasicInterpolation

Interpolation behaviour may be customized by providing a custom handler through the interpolation argument. None can be used to turn off interpolation completely, ExtendedInterpolation() provides a more advanced variant inspired by zc.buildout. More on the subject in the dedicated documentation section. RawConfigParser has a default value of None.

converters, default value: not set

Config parsers provide option value getters that perform type conversion. By default getint(), getfloat(), and getboolean() are implemented. Should other getters be desirable, users may define them in a subclass or pass a dictionary where each key is a name of the converter and each value is a callable implementing said conversion. For instance, passing {'decimal': decimal.Decimal} would add getdecimal() on both the parser object and all section proxies. In other words, it will be possible to write both parser_instance.getdecimal('section', 'key', fallback=0) and parser_instance['section'].getdecimal('key', 0).

If the converter needs to access the state of the parser, it can be implemented as a method on a config parser subclass. If the name of this method starts with get, it will be available on all section proxies, in the dict-compatible form (see the getdecimal() example above).

More advanced customization may be achieved by overriding default values of these parser attributes. The defaults are defined on the classes, so they may be overridden by subclasses or by attribute assignment.

ConfigParser.BOOLEAN_STATES

By default when using getboolean(), config parsers consider the following values True: '1', 'yes', 'true', 'on' and the following values False: '0', 'no', 'false', 'off'. You can override this by specifying a custom dictionary of strings and their Boolean outcomes. For example:

>>> custom = configparser.ConfigParser()
>>> custom['section1'] = {'funky': 'nope'}
>>> custom['section1'].getboolean('funky')
Traceback (most recent call last):
...
ValueError: Not a boolean: nope
>>> custom.BOOLEAN_STATES = {'sure': True, 'nope': False}
>>> custom['section1'].getboolean('funky')
False

Other typical Boolean pairs include accept/reject or enabled/disabled.

ConfigParser.optionxform(option)

This method transforms option names on every read, get, or set operation. The default converts the name to lowercase. This also means that when a configuration file gets written, all keys will be lowercase. Override this method if that’s unsuitable. For example:

>>> config = """
... [Section1]
... Key = Value
...
... [Section2]
... AnotherKey = Value
... """
>>> typical = configparser.ConfigParser()
>>> typical.read_string(config)
>>> list(typical['Section1'].keys())
['key']
>>> list(typical['Section2'].keys())
['anotherkey']
>>> custom = configparser.RawConfigParser()
>>> custom.optionxform = lambda option: option
>>> custom.read_string(config)
>>> list(custom['Section1'].keys())
['Key']
>>> list(custom['Section2'].keys())
['AnotherKey']

ConfigParser.SECTCRE

A compiled regular expression used to parse section headers. The default matches [section] to the name "section". Whitespace is considered part of the section name, thus [  larch  ] will be read as a section of name "  larch  ". Override this attribute if that’s unsuitable. For example:

>>> config = """
... [Section 1]
... option = value
...
... [  Section 2  ]
... another = val
... """
>>> typical = ConfigParser()
>>> typical.read_string(config)
>>> typical.sections()
['Section 1', '  Section 2  ']
>>> custom = ConfigParser()
>>> custom.SECTCRE = re.compile(r"\[ *(?P<header>[^]]+?) *\]")
>>> custom.read_string(config)
>>> custom.sections()
['Section 1', 'Section 2']

Note

While ConfigParser objects also use an OPTCRE attribute for recognizing option lines, it’s not recommended to override it because that would interfere with constructor options allow_no_value and delimiters.

14.2.8. Legacy API Examples

Mainly because of backwards compatibility concerns, configparser provides also a legacy API with explicit get/set methods. While there are valid use cases for the methods outlined below, mapping protocol access is preferred for new projects. The legacy API is at times more advanced, low-level and downright counterintuitive.

An example of writing to a configuration file:

import configparser

config = configparser.RawConfigParser()

# Please note that using RawConfigParser's set functions, you can assign
# non-string values to keys internally, but will receive an error when
# attempting to write to a file or when you get it in non-raw mode. Setting
# values using the mapping protocol or ConfigParser's set() does not allow
# such assignments to take place.
config.add_section('Section1')
config.set('Section1', 'an_int', '15')
config.set('Section1', 'a_bool', 'true')
config.set('Section1', 'a_float', '3.1415')
config.set('Section1', 'baz', 'fun')
config.set('Section1', 'bar', 'Python')
config.set('Section1', 'foo', '%(bar)s is %(baz)s!')

# Writing our configuration file to 'example.cfg'
with open('example.cfg', 'w') as configfile:
    config.write(configfile)

An example of reading the configuration file again:

import configparser

config = configparser.RawConfigParser()
config.read('example.cfg')

# getfloat() raises an exception if the value is not a float
# getint() and getboolean() also do this for their respective types
a_float = config.getfloat('Section1', 'a_float')
an_int = config.getint('Section1', 'an_int')
print(a_float + an_int)

# Notice that the next output does not interpolate '%(bar)s' or '%(baz)s'.
# This is because we are using a RawConfigParser().
if config.getboolean('Section1', 'a_bool'):
    print(config.get('Section1', 'foo'))

To get interpolation, use ConfigParser:

import configparser

cfg = configparser.ConfigParser()
cfg.read('example.cfg')

# Set the optional *raw* argument of get() to True if you wish to disable
# interpolation in a single get operation.
print(cfg.get('Section1', 'foo', raw=False))  # -> "Python is fun!"
print(cfg.get('Section1', 'foo', raw=True))   # -> "%(bar)s is %(baz)s!"

# The optional *vars* argument is a dict with members that will take
# precedence in interpolation.
print(cfg.get('Section1', 'foo', vars={'bar': 'Documentation',
                                       'baz': 'evil'}))

# The optional *fallback* argument can be used to provide a fallback value
print(cfg.get('Section1', 'foo'))
      # -> "Python is fun!"

print(cfg.get('Section1', 'foo', fallback='Monty is not.'))
      # -> "Python is fun!"

print(cfg.get('Section1', 'monster', fallback='No such things as monsters.'))
      # -> "No such things as monsters."

# A bare print(cfg.get('Section1', 'monster')) would raise NoOptionError
# but we can also use:

print(cfg.get('Section1', 'monster', fallback=None))
      # -> None

Default values are available in both types of ConfigParsers. They are used in interpolation if an option used is not defined elsewhere.

import configparser

# New instance with 'bar' and 'baz' defaulting to 'Life' and 'hard' each
config = configparser.ConfigParser({'bar': 'Life', 'baz': 'hard'})
config.read('example.cfg')

print(config.get('Section1', 'foo'))     # -> "Python is fun!"
config.remove_option('Section1', 'bar')
config.remove_option('Section1', 'baz')
print(config.get('Section1', 'foo'))     # -> "Life is hard!"

14.2.9. ConfigParser Objects

class configparser.ConfigParser(defaults=None, dict_type=collections.OrderedDict, allow_no_value=False, delimiters=('=', ':'), comment_prefixes=('#', ';'), inline_comment_prefixes=None, strict=True, empty_lines_in_values=True, default_section=configparser.DEFAULTSECT, interpolation=BasicInterpolation(), converters={})

The main configuration parser. When defaults is given, it is initialized into the dictionary of intrinsic defaults. When dict_type is given, it will be used to create the dictionary objects for the list of sections, for the options within a section, and for the default values.

When delimiters is given, it is used as the set of substrings that divide keys from values. When comment_prefixes is given, it will be used as the set of substrings that prefix comments in otherwise empty lines. Comments can be indented. When inline_comment_prefixes is given, it will be used as the set of substrings that prefix comments in non-empty lines.

When strict is True (the default), the parser won’t allow for any section or option duplicates while reading from a single source (file, string or dictionary), raising DuplicateSectionError or DuplicateOptionError. When empty_lines_in_values is False (default: True), each empty line marks the end of an option. Otherwise, internal empty lines of a multiline option are kept as part of the value. When allow_no_value is True (default: False), options without values are accepted; the value held for these is None and they are serialized without the trailing delimiter.

When default_section is given, it specifies the name for the special section holding default values for other sections and interpolation purposes (normally named "DEFAULT"). This value can be retrieved and changed on runtime using the default_section instance attribute.

Interpolation behaviour may be customized by providing a custom handler through the interpolation argument. None can be used to turn off interpolation completely, ExtendedInterpolation() provides a more advanced variant inspired by zc.buildout. More on the subject in the dedicated documentation section.

All option names used in interpolation will be passed through the optionxform() method just like any other option name reference. For example, using the default implementation of optionxform() (which converts option names to lower case), the values foo %(bar)s and foo %(BAR)s are equivalent.

When converters is given, it should be a dictionary where each key represents the name of a type converter and each value is a callable implementing the conversion from string to the desired datatype. Every converter gets its own corresponding get*() method on the parser object and section proxies.

Modifié dans la version 3.1: The default dict_type is collections.OrderedDict.

Modifié dans la version 3.2: allow_no_value, delimiters, comment_prefixes, strict, empty_lines_in_values, default_section and interpolation were added.

Modifié dans la version 3.5: The converters argument was added.

defaults()

Return a dictionary containing the instance-wide defaults.

sections()

Return a list of the sections available; the default section is not included in the list.

add_section(section)

Add a section named section to the instance. If a section by the given name already exists, DuplicateSectionError is raised. If the default section name is passed, ValueError is raised. The name of the section must be a string; if not, TypeError is raised.

Modifié dans la version 3.2: Non-string section names raise TypeError.

has_section(section)

Indicates whether the named section is present in the configuration. The default section is not acknowledged.

options(section)

Return a list of options available in the specified section.

has_option(section, option)

If the given section exists, and contains the given option, return True; otherwise return False. If the specified section is None or an empty string, DEFAULT is assumed.

read(filenames, encoding=None)

Attempt to read and parse an iterable of filenames, returning a list of filenames which were successfully parsed.

If filenames is a string or path-like object, it is treated as a single filename. If a file named in filenames cannot be opened, that file will be ignored. This is designed so that you can specify an iterable of potential configuration file locations (for example, the current directory, the user’s home directory, and some system-wide directory), and all existing configuration files in the iterable will be read.

If none of the named files exist, the ConfigParser instance will contain an empty dataset. An application which requires initial values to be loaded from a file should load the required file or files using read_file() before calling read() for any optional files:

import configparser, os

config = configparser.ConfigParser()
config.read_file(open('defaults.cfg'))
config.read(['site.cfg', os.path.expanduser('~/.myapp.cfg')],
            encoding='cp1250')

Nouveau dans la version 3.2: The encoding parameter. Previously, all files were read using the default encoding for open().

Nouveau dans la version 3.6.1: The filenames parameter accepts a path-like object.

read_file(f, source=None)

Read and parse configuration data from f which must be an iterable yielding Unicode strings (for example files opened in text mode).

Optional argument source specifies the name of the file being read. If not given and f has a name attribute, that is used for source; the default is '<???>'.

Nouveau dans la version 3.2: Replaces readfp().

read_string(string, source='<string>')

Parse configuration data from a string.

Optional argument source specifies a context-specific name of the string passed. If not given, '<string>' is used. This should commonly be a filesystem path or a URL.

Nouveau dans la version 3.2.

read_dict(dictionary, source='<dict>')

Load configuration from any object that provides a dict-like items() method. Keys are section names, values are dictionaries with keys and values that should be present in the section. If the used dictionary type preserves order, sections and their keys will be added in order. Values are automatically converted to strings.

Optional argument source specifies a context-specific name of the dictionary passed. If not given, <dict> is used.

This method can be used to copy state between parsers.

Nouveau dans la version 3.2.

get(section, option, *, raw=False, vars=None[, fallback])

Get an option value for the named section. If vars is provided, it must be a dictionary. The option is looked up in vars (if provided), section, and in DEFAULTSECT in that order. If the key is not found and fallback is provided, it is used as a fallback value. None can be provided as a fallback value.

All the '%' interpolations are expanded in the return values, unless the raw argument is true. Values for interpolation keys are looked up in the same manner as the option.

Modifié dans la version 3.2: Arguments raw, vars and fallback are keyword only to protect users from trying to use the third argument as the fallback fallback (especially when using the mapping protocol).

getint(section, option, *, raw=False, vars=None[, fallback])

A convenience method which coerces the option in the specified section to an integer. See get() for explanation of raw, vars and fallback.

getfloat(section, option, *, raw=False, vars=None[, fallback])

A convenience method which coerces the option in the specified section to a floating point number. See get() for explanation of raw, vars and fallback.

getboolean(section, option, *, raw=False, vars=None[, fallback])

A convenience method which coerces the option in the specified section to a Boolean value. Note that the accepted values for the option are '1', 'yes', 'true', and 'on', which cause this method to return True, and '0', 'no', 'false', and 'off', which cause it to return False. These string values are checked in a case-insensitive manner. Any other value will cause it to raise ValueError. See get() for explanation of raw, vars and fallback.

items(raw=False, vars=None)

items(section, raw=False, vars=None)

When section is not given, return a list of section_name, section_proxy pairs, including DEFAULTSECT.

Otherwise, return a list of name, value pairs for the options in the given section. Optional arguments have the same meaning as for the get() method.

set(section, option, value)

If the given section exists, set the given option to the specified value; otherwise raise NoSectionError. option and value must be strings; if not, TypeError is raised.

write(fileobject, space_around_delimiters=True)

Write a representation of the configuration to the specified file object, which must be opened in text mode (accepting strings). This representation can be parsed by a future read() call. If space_around_delimiters is true, delimiters between keys and values are surrounded by spaces.

remove_option(section, option)

Remove the specified option from the specified section. If the section does not exist, raise NoSectionError. If the option existed to be removed, return True; otherwise return False.

remove_section(section)

Remove the specified section from the configuration. If the section in fact existed, return True. Otherwise return False.

optionxform(option)

Transforms the option name option as found in an input file or as passed in by client code to the form that should be used in the internal structures. The default implementation returns a lower-case version of option; subclasses may override this or client code can set an attribute of this name on instances to affect this behavior.

You don’t need to subclass the parser to use this method, you can also set it on an instance, to a function that takes a string argument and returns a string. Setting it to str, for example, would make option names case sensitive:

cfgparser = ConfigParser()
cfgparser.optionxform = str

Note that when reading configuration files, whitespace around the option names is stripped before optionxform() is called.

readfp(fp, filename=None)

Obsolète depuis la version 3.2: Use read_file() instead.

Modifié dans la version 3.2: readfp() now iterates on fp instead of calling fp.readline().

For existing code calling readfp() with arguments which don’t support iteration, the following generator may be used as a wrapper around the file-like object:

def readline_generator(fp):
    line = fp.readline()
    while line:
        yield line
        line = fp.readline()

Instead of parser.readfp(fp) use parser.read_file(readline_generator(fp)).

configparser.MAX_INTERPOLATION_DEPTH

The maximum depth for recursive interpolation for get() when the raw parameter is false. This is relevant only when the default interpolation is used.

14.2.10. RawConfigParser Objects

class configparser.RawConfigParser(defaults=None, dict_type=collections.OrderedDict, allow_no_value=False, *, delimiters=('=', ':'), comment_prefixes=('#', ';'), inline_comment_prefixes=None, strict=True, empty_lines_in_values=True, default_section=configparser.DEFAULTSECT[, interpolation])

Legacy variant of the ConfigParser with interpolation disabled by default and unsafe add_section and set methods.

Note

Consider using ConfigParser instead which checks types of the values to be stored internally. If you don’t want interpolation, you can use ConfigParser(interpolation=None).

add_section(section)

Add a section named section to the instance. If a section by the given name already exists, DuplicateSectionError is raised. If the default section name is passed, ValueError is raised.

Type of section is not checked which lets users create non-string named sections. This behaviour is unsupported and may cause internal errors.

set(section, option, value)

If the given section exists, set the given option to the specified value; otherwise raise NoSectionError. While it is possible to use RawConfigParser (or ConfigParser with raw parameters set to true) for internal storage of non-string values, full functionality (including interpolation and output to files) can only be achieved using string values.

This method lets users assign non-string values to keys internally. This behaviour is unsupported and will cause errors when attempting to write to a file or get it in non-raw mode. Use the mapping protocol API which does not allow such assignments to take place.

14.2.11. Exceptions

exception configparser.Error

Base class for all other configparser exceptions.

exception configparser.NoSectionError

Exception raised when a specified section is not found.

exception configparser.DuplicateSectionError

Exception raised if add_section() is called with the name of a section that is already present or in strict parsers when a section if found more than once in a single input file, string or dictionary.

Nouveau dans la version 3.2: Optional source and lineno attributes and arguments to __init__() were added.

exception configparser.DuplicateOptionError

Exception raised by strict parsers if a single option appears twice during reading from a single file, string or dictionary. This catches misspellings and case sensitivity-related errors, e.g. a dictionary may have two keys representing the same case-insensitive configuration key.

exception configparser.NoOptionError

Exception raised when a specified option is not found in the specified section.

exception configparser.InterpolationError

Base class for exceptions raised when problems occur performing string interpolation.

exception configparser.InterpolationDepthError

Exception raised when string interpolation cannot be completed because the number of iterations exceeds MAX_INTERPOLATION_DEPTH. Subclass of InterpolationError.

exception configparser.InterpolationMissingOptionError

Exception raised when an option referenced from a value does not exist. Subclass of InterpolationError.

exception configparser.InterpolationSyntaxError

Exception raised when the source text into which substitutions are made does not conform to the required syntax. Subclass of InterpolationError.

exception configparser.MissingSectionHeaderError

Exception raised when attempting to parse a file which has no section headers.

exception configparser.ParsingError

Exception raised when errors occur attempting to parse a file.

Modifié dans la version 3.2: The filename attribute and __init__() argument were renamed to source for consistency.

Notes

1(1,2,3,4,5,6,7,8,9,10)

Config parsers allow for heavy customization. If you are interested in changing the behaviour outlined by the footnote reference, consult the Customizing Parser Behaviour section.

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14.3. netrc — traitement de fichier netrc

Code source : Lib/netrc.py [https://github.com/python/cpython/tree/3.6/Lib/netrc.py]

La classe netrc analyse et encapsule le format de fichier netrc utilisé par le programme Unix ftp et d’autres clients FTP.

class netrc.netrc([file])

A netrc instance or subclass instance encapsulates data from a netrc file. The initialization argument, if present, specifies the file to parse. If no argument is given, the file .netrc in the user’s home directory will be read. Parse errors will raise NetrcParseError with diagnostic information including the file name, line number, and terminating token. If no argument is specified on a POSIX system, the presence of passwords in the .netrc file will raise a NetrcParseError if the file ownership or permissions are insecure (owned by a user other than the user running the process, or accessible for read or write by any other user). This implements security behavior equivalent to that of ftp and other programs that use .netrc.

Modifié dans la version 3.4: Ajout de la vérification d’autorisations POSIX.

exception netrc.NetrcParseError

Exception levée par la classe netrc lorsque des erreurs syntaxiques sont rencontrées dans le texte source. Les instances de cette exception fournissent trois attributs intéressants : msg est une explication textuelle de l’erreur, filename est le nom du fichier source et lineno donne le numéro de la ligne sur laquelle l’erreur a été trouvée.

14.3.1. Objets netrc

Une instance netrc a les méthodes suivantes :

netrc.authenticators(host)

Renvoie un triplet (login, account, password) pour s’authentifier auprès de l’hôte host. Si le fichier netrc ne contient pas d’entrée pour l’hôte donné, renvoie le tuple associé à l’entrée par défaut. Si aucun hôte correspondant ni aucune entrée par défaut n’est disponible, renvoie None.

netrc.__repr__()

Déverse les données de la classe sous forme de chaîne dans le format d’un fichier netrc. (Ceci ignore les commentaires et peut réorganiser les entrées).

Les instances de netrc ont des variables d’instance publiques :

netrc.hosts

Dictionnaire faisant correspondre les noms d’hôtes dans des tuples (login, account, password). L’entrée par défaut, le cas échéant, est représentée en tant que pseudo-hôte par ce nom.

netrc.macros

Dictionnaire faisant correspondre les noms de macro en listes de chaînes.

Note

Les mots de passe sont limités à un sous-ensemble du jeu de caractères ASCII. Toute ponctuation ASCII est autorisée dans les mots de passe, cependant notez que les espaces et les caractères non imprimables ne sont pas autorisés dans les mots de passe. C’est une limitation de la façon dont le fichier .netrc est analysé et pourra être supprimée à l’avenir.

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14.4. xdrlib — Encode and decode XDR data

Code source : Lib/xdrlib.py [https://github.com/python/cpython/tree/3.6/Lib/xdrlib.py]

The xdrlib module supports the External Data Representation Standard as described in RFC 1014 [https://tools.ietf.org/html/rfc1014.html], written by Sun Microsystems, Inc. June 1987. It supports most of the data types described in the RFC.

The xdrlib module defines two classes, one for packing variables into XDR representation, and another for unpacking from XDR representation. There are also two exception classes.

class xdrlib.Packer

Packer is the class for packing data into XDR representation. The Packer class is instantiated with no arguments.

class xdrlib.Unpacker(data)

Unpacker is the complementary class which unpacks XDR data values from a string buffer. The input buffer is given as data.

Voir aussi

RFC 1014 [https://tools.ietf.org/html/rfc1014.html] - XDR: External Data Representation Standard

This RFC defined the encoding of data which was XDR at the time this module was originally written. It has apparently been obsoleted by RFC 1832 [https://tools.ietf.org/html/rfc1832.html].

RFC 1832 [https://tools.ietf.org/html/rfc1832.html] - XDR: External Data Representation Standard

Newer RFC that provides a revised definition of XDR.

14.4.1. Packer Objects

Packer instances have the following methods:

Packer.get_buffer()

Returns the current pack buffer as a string.

Packer.reset()

Resets the pack buffer to the empty string.

In general, you can pack any of the most common XDR data types by calling the appropriate pack_type() method. Each method takes a single argument, the value to pack. The following simple data type packing methods are supported: pack_uint(), pack_int(), pack_enum(), pack_bool(), pack_uhyper(), and pack_hyper().

Packer.pack_float(value)

Packs the single-precision floating point number value.

Packer.pack_double(value)

Packs the double-precision floating point number value.

The following methods support packing strings, bytes, and opaque data:

Packer.pack_fstring(n, s)

Packs a fixed length string, s. n is the length of the string but it is not packed into the data buffer. The string is padded with null bytes if necessary to guaranteed 4 byte alignment.

Packer.pack_fopaque(n, data)

Packs a fixed length opaque data stream, similarly to pack_fstring().

Packer.pack_string(s)

Packs a variable length string, s. The length of the string is first packed as an unsigned integer, then the string data is packed with pack_fstring().

Packer.pack_opaque(data)

Packs a variable length opaque data string, similarly to pack_string().

Packer.pack_bytes(bytes)

Packs a variable length byte stream, similarly to pack_string().

The following methods support packing arrays and lists:

Packer.pack_list(list, pack_item)

Packs a list of homogeneous items. This method is useful for lists with an indeterminate size; i.e. the size is not available until the entire list has been walked. For each item in the list, an unsigned integer 1 is packed first, followed by the data value from the list. pack_item is the function that is called to pack the individual item. At the end of the list, an unsigned integer 0 is packed.

For example, to pack a list of integers, the code might appear like this:

import xdrlib
p = xdrlib.Packer()
p.pack_list([1, 2, 3], p.pack_int)

Packer.pack_farray(n, array, pack_item)

Packs a fixed length list (array) of homogeneous items. n is the length of the list; it is not packed into the buffer, but a ValueError exception is raised if len(array) is not equal to n. As above, pack_item is the function used to pack each element.

Packer.pack_array(list, pack_item)

Packs a variable length list of homogeneous items. First, the length of the list is packed as an unsigned integer, then each element is packed as in pack_farray() above.

14.4.2. Unpacker Objects

The Unpacker class offers the following methods:

Unpacker.reset(data)

Resets the string buffer with the given data.

Unpacker.get_position()

Returns the current unpack position in the data buffer.

Unpacker.set_position(position)

Sets the data buffer unpack position to position. You should be careful about using get_position() and set_position().

Unpacker.get_buffer()

Returns the current unpack data buffer as a string.

Unpacker.done()

Indicates unpack completion. Raises an Error exception if all of the data has not been unpacked.

In addition, every data type that can be packed with a Packer, can be unpacked with an Unpacker. Unpacking methods are of the form unpack_type(), and take no arguments. They return the unpacked object.

Unpacker.unpack_float()

Unpacks a single-precision floating point number.

Unpacker.unpack_double()

Unpacks a double-precision floating point number, similarly to unpack_float().

In addition, the following methods unpack strings, bytes, and opaque data:

Unpacker.unpack_fstring(n)

Unpacks and returns a fixed length string. n is the number of characters expected. Padding with null bytes to guaranteed 4 byte alignment is assumed.

Unpacker.unpack_fopaque(n)

Unpacks and returns a fixed length opaque data stream, similarly to unpack_fstring().

Unpacker.unpack_string()

Unpacks and returns a variable length string. The length of the string is first unpacked as an unsigned integer, then the string data is unpacked with unpack_fstring().

Unpacker.unpack_opaque()

Unpacks and returns a variable length opaque data string, similarly to unpack_string().

Unpacker.unpack_bytes()

Unpacks and returns a variable length byte stream, similarly to unpack_string().

The following methods support unpacking arrays and lists:

Unpacker.unpack_list(unpack_item)

Unpacks and returns a list of homogeneous items. The list is unpacked one element at a time by first unpacking an unsigned integer flag. If the flag is 1, then the item is unpacked and appended to the list. A flag of 0 indicates the end of the list. unpack_item is the function that is called to unpack the items.

Unpacker.unpack_farray(n, unpack_item)

Unpacks and returns (as a list) a fixed length array of homogeneous items. n is number of list elements to expect in the buffer. As above, unpack_item is the function used to unpack each element.

Unpacker.unpack_array(unpack_item)

Unpacks and returns a variable length list of homogeneous items. First, the length of the list is unpacked as an unsigned integer, then each element is unpacked as in unpack_farray() above.

14.4.3. Exceptions

Exceptions in this module are coded as class instances:

exception xdrlib.Error

The base exception class. Error has a single public attribute msg containing the description of the error.

exception xdrlib.ConversionError

Class derived from Error. Contains no additional instance variables.

Here is an example of how you would catch one of these exceptions:

import xdrlib
p = xdrlib.Packer()
try:
    p.pack_double(8.01)
except xdrlib.ConversionError as instance:
    print('packing the double failed:', instance.msg)

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14.5. plistlib — Generate and parse Mac OS X .plist files

Code source : Lib/plistlib.py [https://github.com/python/cpython/tree/3.6/Lib/plistlib.py]

This module provides an interface for reading and writing the « property list » files used mainly by Mac OS X and supports both binary and XML plist files.

The property list (.plist) file format is a simple serialization supporting basic object types, like dictionaries, lists, numbers and strings. Usually the top level object is a dictionary.

To write out and to parse a plist file, use the dump() and load() functions.

To work with plist data in bytes objects, use dumps() and loads().

Values can be strings, integers, floats, booleans, tuples, lists, dictionaries (but only with string keys), Data, bytes, bytesarray or datetime.datetime objects.

Modifié dans la version 3.4: New API, old API deprecated. Support for binary format plists added.

Voir aussi

PList manual page [https://developer.apple.com/library/mac/documentation/Darwin/Reference/ManPages/man5/plist.5.html]

Apple’s documentation of the file format.

Ce module définit les fonctions suivantes :

plistlib.load(fp, *, fmt=None, use_builtin_types=True, dict_type=dict)

Read a plist file. fp should be a readable and binary file object. Return the unpacked root object (which usually is a dictionary).

The fmt is the format of the file and the following values are valid:

None: Autodetect the file format

FMT_XML: XML file format

FMT_BINARY: Binary plist format

If use_builtin_types is true (the default) binary data will be returned as instances of bytes, otherwise it is returned as instances of Data.

The dict_type is the type used for dictionaries that are read from the plist file. The exact structure of the plist can be recovered by using collections.OrderedDict (although the order of keys shouldn’t be important in plist files).

XML data for the FMT_XML format is parsed using the Expat parser from xml.parsers.expat – see its documentation for possible exceptions on ill-formed XML. Unknown elements will simply be ignored by the plist parser.

The parser for the binary format raises InvalidFileException when the file cannot be parsed.

Nouveau dans la version 3.4.

plistlib.loads(data, *, fmt=None, use_builtin_types=True, dict_type=dict)

Load a plist from a bytes object. See load() for an explanation of the keyword arguments.

Nouveau dans la version 3.4.

plistlib.dump(value, fp, *, fmt=FMT_XML, sort_keys=True, skipkeys=False)

Write value to a plist file. Fp should be a writable, binary file object.

The fmt argument specifies the format of the plist file and can be one of the following values:

FMT_XML: XML formatted plist file

FMT_BINARY: Binary formatted plist file

When sort_keys is true (the default) the keys for dictionaries will be written to the plist in sorted order, otherwise they will be written in the iteration order of the dictionary.

When skipkeys is false (the default) the function raises TypeError when a key of a dictionary is not a string, otherwise such keys are skipped.

A TypeError will be raised if the object is of an unsupported type or a container that contains objects of unsupported types.

An OverflowError will be raised for integer values that cannot be represented in (binary) plist files.

Nouveau dans la version 3.4.

plistlib.dumps(value, *, fmt=FMT_XML, sort_keys=True, skipkeys=False)

Return value as a plist-formatted bytes object. See the documentation for dump() for an explanation of the keyword arguments of this function.

Nouveau dans la version 3.4.

The following functions are deprecated:

plistlib.readPlist(pathOrFile)

Read a plist file. pathOrFile may be either a file name or a (readable and binary) file object. Returns the unpacked root object (which usually is a dictionary).

This function calls load() to do the actual work, see the documentation of that function for an explanation of the keyword arguments.

Note

Dict values in the result have a __getattr__ method that defers to __getitem_. This means that you can use attribute access to access items of these dictionaries.

Obsolète depuis la version 3.4: Use load() instead.

plistlib.writePlist(rootObject, pathOrFile)

Write rootObject to an XML plist file. pathOrFile may be either a file name or a (writable and binary) file object

Obsolète depuis la version 3.4: Use dump() instead.

plistlib.readPlistFromBytes(data)

Read a plist data from a bytes object. Return the root object.

See load() for a description of the keyword arguments.

Note

Dict values in the result have a __getattr__ method that defers to __getitem_. This means that you can use attribute access to access items of these dictionaries.

Obsolète depuis la version 3.4: Use loads() instead.

plistlib.writePlistToBytes(rootObject)

Return rootObject as an XML plist-formatted bytes object.

Obsolète depuis la version 3.4: Use dumps() instead.

The following classes are available:

Dict([dict]):

Return an extended mapping object with the same value as dictionary dict.

This class is a subclass of dict where attribute access can be used to access items. That is, aDict.key is the same as aDict['key'] for getting, setting and deleting items in the mapping.

Obsolète depuis la version 3.0.

class plistlib.Data(data)

Return a « data » wrapper object around the bytes object data. This is used in functions converting from/to plists to represent the <data> type available in plists.

It has one attribute, data, that can be used to retrieve the Python bytes object stored in it.

Obsolète depuis la version 3.4: Use a bytes object instead.

The following constants are available:

plistlib.FMT_XML

The XML format for plist files.

Nouveau dans la version 3.4.

plistlib.FMT_BINARY

The binary format for plist files

Nouveau dans la version 3.4.

14.5.1. Exemples

Generating a plist:

pl = dict(
    aString = "Doodah",
    aList = ["A", "B", 12, 32.1, [1, 2, 3]],
    aFloat = 0.1,
    anInt = 728,
    aDict = dict(
        anotherString = "<hello & hi there!>",
        aThirdString = "M\xe4ssig, Ma\xdf",
        aTrueValue = True,
        aFalseValue = False,
    ),
    someData = b"<binary gunk>",
    someMoreData = b"<lots of binary gunk>" * 10,
    aDate = datetime.datetime.fromtimestamp(time.mktime(time.gmtime())),
)
with open(fileName, 'wb') as fp:
    dump(pl, fp)

Parsing a plist:

with open(fileName, 'rb') as fp:
    pl = load(fp)
print(pl["aKey"])

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15. Service de cryptographie

Les modules décrits dans ce chapitre mettent en œuvre divers algorithmes cryptographiques. Ils peuvent, ou pas, être disponibles, en fonction de l’installation Sur les systèmes Unix, le module crypt peut aussi être disponible. Voici une vue d’ensemble:

15.1. hashlib — Algorithmes de hachage sécurisés et synthèse de messages

15.1.1. Algorithmes de hachage

15.1.2. Synthèse de messages de taille variable SHAKE

15.1.3. Dérivation de clé

15.1.4. BLAKE2

15.1.4.1. Création d’objets hachés

15.1.4.2. Constantes

15.1.4.3. Exemples

15.1.4.3.1. Hachage simple

15.1.4.3.2. Usage de tailles d’empreintes différentes

15.1.4.3.3. Code d’authentification de message

15.1.4.3.4. Hachage randomisé

15.1.4.3.5. Personnalisation

15.1.4.3.6. Mode Arbre

15.1.4.4. Crédits

15.2. hmac — Authentification de messages par hachage en combinaison avec une clé secrète

15.3. secrets — Générer des nombres aléatoires de façon sécurisée pour la gestion des secrets

15.3.1. Nombres aléatoires

15.3.2. Génération de jetons

15.3.2.1. Combien d’octets mon jeton doit-il comporter ?

15.3.3. Autres fonctions

15.3.4. Recettes et bonnes pratiques

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15.1. hashlib — Algorithmes de hachage sécurisés et synthèse de messages

Code source : Lib/hashlib.py [https://github.com/python/cpython/tree/3.6/Lib/hashlib.py]

Ce module implémente une interface commune à différents algorithmes de hachage sécurisés et de synthèse de messages. Sont inclus les algorithmes standards FIPS de hachage SHA1, SHA224, SHA256, SHA384, et SHA512 (définis dans FIPS 180-2) ainsi que l’algorithme MD5 de RSA (défini par la RFC 1321 [https://tools.ietf.org/html/rfc1321.html]). Les termes « algorithmes de hachage sécurisé » et « algorithme de synthèse de message » sont interchangeables. Les anciens algorithmes étaient appelés » algorithmes de synthèse de messages ». Le terme moderne est « algorithme de hachage sécurisé ».

Note

Si vous préférez utiliser les fonctions de hachage adler32 ou crc32, elles sont disponibles dans le module zlib.

Avertissement

Certains algorithmes ont des faiblesses connues relatives à la collision, se référer à la section « Voir aussi » à la fin.

15.1.1. Algorithmes de hachage

Il y a un constructeur nommé selon chaque type de hash. Tous retournent un objet haché avec la même interface. Par exemple : utilisez sha256() pour créer un objet haché de type SHA-256. Vous pouvez maintenant utiliser cet objet bytes-like objects (normalement des bytes) en utilisant la méthode update(). À tout moment vous pouvez demander le digest de la concaténation des données fournies en utilisant les méthodes digest() ou hexdigest().

Note

Pour de meilleures performances avec de multiples fils d’exécution, le GIL Python est relâché pour des données dont la taille est supérieure à 2047 octets lors de leur création ou leur mise à jour.

Note

Fournir des objets chaînes de caractères à la méthode update() n’est pas implémenté, comme les fonctions de hachages travaillent sur des bytes et pas sur des caractères.

Les constructeurs pour les algorithmes de hachage qui sont toujours présents dans ce module sont sha1(), sha224(), sha256(), sha384(), sha512(), blake2b(), et blake2s(). md5() est normalement disponible aussi, mais il peut être manquant si vous utilisez une forme rare de Python « conforme FIPS » . Des algorithmes additionnels peuvent aussi être disponibles dépendant de la librairie OpenSSL que Python utilise sur votre plate-forme. Sur la plupart des plates-formes les fonctions sha3_224(), sha3_256(), sha3_384(), sha3_512(), shake_128(), shake_256() sont aussi disponibles.

Nouveau dans la version 3.6: Les constructeurs SHA3 (Keccak) et SHAKE sha3_224(), sha3_256(), sha3_384(), sha3_512(), shake_128(), shake_256().

Nouveau dans la version 3.6: Les fonctions blake2b() et blake2s() ont été ajoutées.

Par exemple, pour obtenir l’empreinte de la chaîne b'Nobody inspects the spammish repetition' :

>>> import hashlib
>>> m = hashlib.sha256()
>>> m.update(b"Nobody inspects")
>>> m.update(b" the spammish repetition")
>>> m.digest()
b'\x03\x1e\xdd}Ae\x15\x93\xc5\xfe\\\x00o\xa5u+7\xfd\xdf\xf7\xbcN\x84:\xa6\xaf\x0c\x95\x0fK\x94\x06'
>>> m.digest_size
32
>>> m.block_size
64

En plus condensé :

>>> hashlib.sha224(b"Nobody inspects the spammish repetition").hexdigest()
'a4337bc45a8fc544c03f52dc550cd6e1e87021bc896588bd79e901e2'

hashlib.new(name[, data])

Is a generic constructor that takes the string name of the desired algorithm as its first parameter. It also exists to allow access to the above listed hashes as well as any other algorithms that your OpenSSL library may offer. The named constructors are much faster than new() and should be preferred.

En utilisant new() avec un algorithme fourni par OpenSSL :

>>> h = hashlib.new('ripemd160')
>>> h.update(b"Nobody inspects the spammish repetition")
>>> h.hexdigest()
'cc4a5ce1b3df48aec5d22d1f16b894a0b894eccc'

Hashlib fournit les constantes suivantes :

hashlib.algorithms_guaranteed

Un ensemble contenant les noms des algorithmes de hachage garantis d’être implémentés par ce module sur toutes les plate-formes. Notez que md5 est dans cette liste malgré certains éditeurs qui offrent une implémentation Python de la librairie compatible FIPS l’excluant.

Nouveau dans la version 3.2.

hashlib.algorithms_available

Un ensemble contenant les noms des algorithmes de hachage disponibles dans l’interpréteur Python. Ces noms sont reconnus lorsqu’ils sont passés à la fonction new(). algorithms_guaranteed est toujours un sous-ensemble. Le même algorithme peut apparaître plusieurs fois dans cet ensemble sous un nom différent (grâce à OpenSSL).

Nouveau dans la version 3.2.

Les valeurs suivantes sont fournis en tant qu’attributs constants des objets hachés retournés par les constructeurs :

hash.digest_size

La taille du hash résultant en octets.

hash.block_size

La taille interne d’un bloc de l’algorithme de hachage en octets.

L’objet haché possède les attributs suivants :

hash.name

Le nom canonique de cet objet haché, toujours en minuscule et toujours transmissible à la fonction new() pour créer un autre objet haché de ce type.

Modifié dans la version 3.4: L’attribut name est présent dans CPython depuis sa création, mais n’était pas spécifié formellement jusqu’à Python 3.4, il peut ne pas exister sur certaines plate-formes.

L’objet haché possède les méthodes suivantes :

hash.update(data)

Update the hash object with the bytes-like object. Repeated calls are equivalent to a single call with the concatenation of all the arguments: m.update(a); m.update(b) is equivalent to m.update(a+b).

Modifié dans la version 3.1: Le GIL Python est relâché pour permettre aux autres fils d’exécution de tourner pendant que la fonction de hachage met à jour des données plus larges que 2047 octets, lorsque les algorithmes fournis par OpenSSL sont utilisés.

hash.digest()

Renvoie le digest des données passées à la méthode update(). C’est un objet de type bytes de taille digest_size qui contient des octets dans l’intervalle 0 à 255.

hash.hexdigest()

Comme la méthode digest() sauf que le digest renvoyé est une chaîne de caractères de longueur double, contenant seulement des chiffres hexadécimaux. Cela peut être utilisé pour échanger sans risque des valeurs dans les e-mails ou dans les environnements non binaires.

hash.copy()

Renvoie une copie (« clone ») de l’objet haché. Cela peut être utilisé pour calculer efficacement les digests de données partageant des sous-chaînes communes.

15.1.2. Synthèse de messages de taille variable SHAKE

Les algorithmes shake_128() et shake_256() fournissent des messages de longueur variable avec des longueurs_en_bits // 2 jusqu’à 128 ou 256 bits de sécurité. Leurs méthodes digests requièrent une longueur. Les longueurs maximales ne sont pas limitées par l’algorithme SHAKE.

shake.digest(length)

Return the digest of the data passed to the update() method so far. This is a bytes object of size length which may contain bytes in the whole range from 0 to 255.

shake.hexdigest(length)

Comme la méthode digest() sauf que le digest renvoyé est une chaîne de caractères de longueur double, contenant seulement des chiffres hexadécimaux. Cela peut être utilisé pour échanger sans risque des valeurs dans les e-mails ou dans les environnements non binaires.

15.1.3. Dérivation de clé

Les algorithmes de dérivation de clés et d’étirement de clés sont conçus pour le hachage sécurisé de mots de passe. Des algorithmes naïfs comme sha1(password) ne sont pas résistants aux attaques par force brute. Une bonne fonction de hachage doit être paramétrable, lente, et inclure un sel [https://en.wikipedia.org/wiki/Salt_%28cryptography%29].

hashlib.pbkdf2_hmac(hash_name, password, salt, iterations, dklen=None)

La fonction fournit une fonction de dérivation PKCS#5 (Public Key Cryptographic Standards #5 v2.0). Elle utilise HMAC comme fonction de pseudo-aléatoire.

La chaîne de caractères hash_name est le nom de l’algorithme de hachage désiré pour le HMAC, par exemple "sha1" ou "sha256". password et salt sont interprétés comme des tampons d’octets. Les applications et bibliothèques doivent limiter password à une longueur raisonnable (comme 1024). salt doit être de 16 octets ou plus provenant d’une source correcte, e.g. os.urandom().

Le nombre d”iterations doit être choisi sur la base de l’algorithme de hachage et de la puissance de calcul. En 2013, au moins 100000 itérations de SHA-256 sont recommandées.

dklen est la longueur de la clé dérivée. Si dklen vaut None alors la taille du message de l’algorithme de hachage hash_name est utilisé, e.g. 64 pour SHA-512.

>>> import hashlib, binascii
>>> dk = hashlib.pbkdf2_hmac('sha256', b'password', b'salt', 100000)
>>> binascii.hexlify(dk)
b'0394a2ede332c9a13eb82e9b24631604c31df978b4e2f0fbd2c549944f9d79a5'

Nouveau dans la version 3.4.

Note

Une implémentation rapide de pbkdf2_hmac est disponible avec OpenSSL. L’implémentation Python utilise une version anonyme de hmac. Elle est trois fois plus lente et ne libère pas le GIL.

hashlib.scrypt(password, *, salt, n, r, p, maxmem=0, dklen=64)

La fonction fournit la fonction de dérivation de clé scrypt comme définie dans RFC 7914 [https://tools.ietf.org/html/rfc7914.html].

password and salt must be bytes-like objects. Applications and libraries should limit password to a sensible length (e.g. 1024). salt should be about 16 or more bytes from a proper source, e.g. os.urandom().

n is the CPU/Memory cost factor, r the block size, p parallelization factor and maxmem limits memory (OpenSSL 1.1.0 defaults to 32 MB). dklen is the length of the derived key.

Availability: OpenSSL 1.1+

Nouveau dans la version 3.6.

15.1.4. BLAKE2

BLAKE2 [https://blake2.net] est une fonction de hachage cryptographique définie dans la RFC 7693 [https://tools.ietf.org/html/rfc7693.html] et disponible en deux versions :

BLAKE2b, optimisée pour les plates-formes 64-bit et produisant des messages de toutes tailles entre 1 et 64 octets,

BLAKE2s, optimisée pour les plates-formes de 8 à 32-bit et produisant des messages de toutes tailles entre 1 et 32 octets.

BLAKE2 gère diverses fonctionnalités keyed mode (un remplacement plus rapide et plus simple pour HMAC [https://en.wikipedia.org/wiki/Hash-based_message_authentication_code]), salted hashing, personalization, et tree hashing.

Les objets hachés de ce module suivent l’API des objets du module hashlib de la librairie standard.

15.1.4.1. Création d’objets hachés

Les nouveaux objets hachés sont créés en appelant les constructeurs :

hashlib.blake2b(data=b'', *, digest_size=64, key=b'', salt=b'', person=b'', fanout=1, depth=1, leaf_size=0, node_offset=0, node_depth=0, inner_size=0, last_node=False)

hashlib.blake2s(data=b'', *, digest_size=32, key=b'', salt=b'', person=b'', fanout=1, depth=1, leaf_size=0, node_offset=0, node_depth=0, inner_size=0, last_node=False)

Ces fonctions produisent l’objet haché correspondant aux calculs de BLAKE2b ou BLAKE2s. Elles prennent ces paramètres optionnels :

data: initial chunk of data to hash, which must be bytes-like object. It can be passed only as positional argument.

digest_size: taille en sortie du message en octets.

key: clé pour les code d’authentification de message keyed hashing (jusqu’à 64 octets pour BLAKE2b, jusqu’à 32 octets pour BLAKE2s).

salt: sel pour le hachage randomisé randomized hashing (jusqu’à 16 octets pour BLAKE2b, jusqu’à 8 octets pour BLAKE2s).

person: chaîne de personnalisation (jusqu’à 16 octets pour BLAKE2b, jusqu’à 8 octets pour BLAKE2s).

Le tableau suivant présente les limites des paramètres généraux (en octets) :

Hash

digest_size

len(key)

len(salt)

len(person)

BLAKE2b

64

64

16

16

BLAKE2s

32

32

8

8

Note

Les spécifications de BLAKE2 définissent des longueurs constantes pour les sel et chaînes de personnalisation, toutefois, par commodité, cette implémentation accepte des chaînes byte de n’importe quelle taille jusqu’à la longueur spécifiée. Si la longueur du paramètre est moindre par rapport à celle spécifiée, il est complété par des zéros, ainsi, par exemple, b'salt' et b'salt\x00' sont la même valeur (Ce n’est pas le cas pour key.)

Ces tailles sont disponibles comme constants du module et décrites ci-dessous.

Les fonctions constructeur acceptent aussi les paramètres suivants pour le tree hashing :

fanout: fanout (0 à 255, 0 si illimité, 1 en mode séquentiel).

depth: profondeur maximale de l’arbre (1 à 255, 255 si illimité, 1 en mode séquentiel).

leaf_size: taille maximale en octets d’une feuille (0 à 2**32-1, 0 si illimité ou en mode séquentiel).

node_offset: décalage de nœud (0 à 2**64-1 pour BLAKE2b, 0 à 2**48-1 pour BLAKE2s, 0 pour la première feuille la plus à gauche, ou en mode séquentiel).

node_depth: profondeur de nœuds (0 à 255, 0 pour les feuilles, ou en mode séquentiel).

inner_size: taille interne du message (0 à 64 pour BLAKE2b, 0 à 32 pour BLAKE2s, 0 en mode séquentiel).

last_node: booléen indiquant si le nœud traité est le dernier (False pour le mode séquentiel).

Voir section 2.10 dans BLAKE2 specification [https://blake2.net/blake2_20130129.pdf] pour une approche compréhensive du tree hashing.

15.1.4.2. Constantes

blake2b.SALT_SIZE

blake2s.SALT_SIZE

Longueur du sel (longueur maximale acceptée par les constructeurs).

blake2b.PERSON_SIZE

blake2s.PERSON_SIZE

Longueur de la chaîne de personnalisation (longueur maximale acceptée par les constructeurs).

blake2b.MAX_KEY_SIZE

blake2s.MAX_KEY_SIZE

Taille maximale de clé.

blake2b.MAX_DIGEST_SIZE

blake2s.MAX_DIGEST_SIZE

Taille maximale du message que peut fournir la fonction de hachage.

15.1.4.3. Exemples

15.1.4.3.1. Hachage simple

Pour calculer les hash de certaines données, vous devez d’abord construire un objet haché en appelant la fonction constructeur appropriée (blake2b() or blake2s()), ensuite le mettre à jour avec les données en appelant la méthode update() sur l’objet, et, pour finir, récupérer l’empreinte du message en appelant la méthode digest() (ou hexdigest() pour les chaînes hexadécimales).

>>> from hashlib import blake2b
>>> h = blake2b()
>>> h.update(b'Hello world')
>>> h.hexdigest()
'6ff843ba685842aa82031d3f53c48b66326df7639a63d128974c5c14f31a0f33343a8c65551134ed1ae0f2b0dd2bb495dc81039e3eeb0aa1bb0388bbeac29183'

As a shortcut, you can pass the first chunk of data to update directly to the constructor as the positional argument:

>>> from hashlib import blake2b
>>> blake2b(b'Hello world').hexdigest()
'6ff843ba685842aa82031d3f53c48b66326df7639a63d128974c5c14f31a0f33343a8c65551134ed1ae0f2b0dd2bb495dc81039e3eeb0aa1bb0388bbeac29183'

Vous pouvez appeler la méthode hash.update() autant de fois que nécessaire pour mettre à jour le hash de manière itérative :

>>> from hashlib import blake2b
>>> items = [b'Hello', b' ', b'world']
>>> h = blake2b()
>>> for item in items:
...     h.update(item)
>>> h.hexdigest()
'6ff843ba685842aa82031d3f53c48b66326df7639a63d128974c5c14f31a0f33343a8c65551134ed1ae0f2b0dd2bb495dc81039e3eeb0aa1bb0388bbeac29183'

15.1.4.3.2. Usage de tailles d’empreintes différentes

BLAKE2 permet de configurer la taille des empreintes jusqu’à 64 octets pour BLAKE2b et jusqu’à 32 octets pour BLAKE2s. Par exemple, pour remplacer SHA-1 par BLAKE2b sans changer la taille de la sortie, nous pouvons dire à BLAKE2b de produire une empreinte de 20 octets :

>>> from hashlib import blake2b
>>> h = blake2b(digest_size=20)
>>> h.update(b'Replacing SHA1 with the more secure function')
>>> h.hexdigest()
'd24f26cf8de66472d58d4e1b1774b4c9158b1f4c'
>>> h.digest_size
20
>>> len(h.digest())
20

Les objets hachés avec différentes tailles d’empreintes ont des sorties complètement différentes (les hash plus courts ne sont pas des préfixes de hash plus longs); BLAKE2b et BLAKE2s produisent des sorties différentes même si les longueurs des sorties sont les mêmes :

>>> from hashlib import blake2b, blake2s
>>> blake2b(digest_size=10).hexdigest()
'6fa1d8fcfd719046d762'
>>> blake2b(digest_size=11).hexdigest()
'eb6ec15daf9546254f0809'
>>> blake2s(digest_size=10).hexdigest()
'1bf21a98c78a1c376ae9'
>>> blake2s(digest_size=11).hexdigest()
'567004bf96e4a25773ebf4'

15.1.4.3.3. Code d’authentification de message

Keyed hashing can be used for authentication as a faster and simpler replacement for Hash-based message authentication code [http://en.wikipedia.org/wiki/Hash-based_message_authentication_code] (HMAC). BLAKE2 can be securely used in prefix-MAC mode thanks to the indifferentiability property inherited from BLAKE.

Cet exemple montre comment obtenir un code d’authentification de message de 128-bit (en hexadécimal) pour un message b'message data' avec la clé b'pseudorandom key' :

>>> from hashlib import blake2b
>>> h = blake2b(key=b'pseudorandom key', digest_size=16)
>>> h.update(b'message data')
>>> h.hexdigest()
'3d363ff7401e02026f4a4687d4863ced'

Comme exemple pratique, une application web peut chiffrer symétriquement les cookies envoyés aux utilisateurs et les vérifier plus tard pour être certaine qu’ils n’aient pas été altérés :

>>> from hashlib import blake2b
>>> from hmac import compare_digest
>>>
>>> SECRET_KEY = b'pseudorandomly generated server secret key'
>>> AUTH_SIZE = 16
>>>
>>> def sign(cookie):
...     h = blake2b(digest_size=AUTH_SIZE, key=SECRET_KEY)
...     h.update(cookie)
...     return h.hexdigest().encode('utf-8')
>>>
>>> def verify(cookie, sig):
...     good_sig = sign(cookie)
...     return compare_digest(good_sig, sig)
>>>
>>> cookie = b'user-alice'
>>> sig = sign(cookie)
>>> print("{0},{1}".format(cookie.decode('utf-8'), sig))
user-alice,b'43b3c982cf697e0c5ab22172d1ca7421'
>>> verify(cookie, sig)
True
>>> verify(b'user-bob', sig)
False
>>> verify(cookie, b'0102030405060708090a0b0c0d0e0f00')
False

Même s’il possède en natif la création de code d’authentification de message (MAC), BLAKE2 peut, bien sûr, être utilisé pour construire un HMAC en combinaison du module hmac :

>>> import hmac, hashlib
>>> m = hmac.new(b'secret key', digestmod=hashlib.blake2s)
>>> m.update(b'message')
>>> m.hexdigest()
'e3c8102868d28b5ff85fc35dda07329970d1a01e273c37481326fe0c861c8142'

15.1.4.3.4. Hachage randomisé

En définissant le paramètre salt les utilisateurs peuvent introduire de l’aléatoire dans la fonction de hachage. Le hachage randomisé est utile pour se protéger des attaques par collisions sur les fonctions de hachage utilisées dans les signatures numériques.

Randomized hashing is designed for situations where one party, the message preparer, generates all or part of a message to be signed by a second party, the message signer. If the message preparer is able to find cryptographic hash function collisions (i.e., two messages producing the same hash value), then they might prepare meaningful versions of the message that would produce the same hash value and digital signature, but with different results (e.g., transferring $1,000,000 to an account, rather than $10). Cryptographic hash functions have been designed with collision resistance as a major goal, but the current concentration on attacking cryptographic hash functions may result in a given cryptographic hash function providing less collision resistance than expected. Randomized hashing offers the signer additional protection by reducing the likelihood that a preparer can generate two or more messages that ultimately yield the same hash value during the digital signature generation process — even if it is practical to find collisions for the hash function. However, the use of randomized hashing may reduce the amount of security provided by a digital signature when all portions of the message are prepared by the signer.

(NIST SP-800-106 « Randomized Hashing for Digital Signatures » [http://csrc.nist.gov/publications/nistpubs/800-106/NIST-SP-800-106.pdf])

Dans BLAKE2, le sel est passé une seule fois lors de l’initialisation de la fonction de hachage, plutôt qu’à chaque appel d’une fonction de compression.

Avertissement

Salted hashing (ou juste hachage) avec BLAKE2 ou toute autre fonction de hachage générique, comme SHA-256, ne convient pas pour le chiffrement des mots de passe. Voir BLAKE2 FAQ [https://blake2.net/#qa] pour plus d’informations.

>>> import os
>>> from hashlib import blake2b
>>> msg = b'some message'
>>> # Calculate the first hash with a random salt.
>>> salt1 = os.urandom(blake2b.SALT_SIZE)
>>> h1 = blake2b(salt=salt1)
>>> h1.update(msg)
>>> # Calculate the second hash with a different random salt.
>>> salt2 = os.urandom(blake2b.SALT_SIZE)
>>> h2 = blake2b(salt=salt2)
>>> h2.update(msg)
>>> # The digests are different.
>>> h1.digest() != h2.digest()
True

15.1.4.3.5. Personnalisation

Parfois il est utile de forcer une fonction de hachage à produire différentes empreintes de message d’une même entrée pour différentes utilisations. Pour citer les auteurs de la fonction de hachage Skein  :

Nous recommandons que tous les développeurs d’application considèrent sérieusement de faire cela ; nous avons vu de nombreux protocoles où un hash était calculé à un endroit du protocole pour être utilisé à un autre endroit car deux calculs de hash étaient réalisés sur des données similaires ou liées, et qu’un attaquant peut forcer une application à prendre en entrée le même hash. Personnaliser chaque fonction de hachage utilisée dans le protocole stoppe immédiatement ce genre d’attaque.

(The Skein Hash Function Family [http://www.skein-hash.info/sites/default/files/skein1.3.pdf], p. 21, article en anglais)

BLAKE2 peut être personnalisé en passant des bytes à l’argument person :

>>> from hashlib import blake2b
>>> FILES_HASH_PERSON = b'MyApp Files Hash'
>>> BLOCK_HASH_PERSON = b'MyApp Block Hash'
>>> h = blake2b(digest_size=32, person=FILES_HASH_PERSON)
>>> h.update(b'the same content')
>>> h.hexdigest()
'20d9cd024d4fb086aae819a1432dd2466de12947831b75c5a30cf2676095d3b4'
>>> h = blake2b(digest_size=32, person=BLOCK_HASH_PERSON)
>>> h.update(b'the same content')
>>> h.hexdigest()
'cf68fb5761b9c44e7878bfb2c4c9aea52264a80b75005e65619778de59f383a3'

La personnalisation et le keyed mode peuvent être utilisés ensemble pour dériver différentes clés à partir d’une seule.

>>> from hashlib import blake2s
>>> from base64 import b64decode, b64encode
>>> orig_key = b64decode(b'Rm5EPJai72qcK3RGBpW3vPNfZy5OZothY+kHY6h21KM=')
>>> enc_key = blake2s(key=orig_key, person=b'kEncrypt').digest()
>>> mac_key = blake2s(key=orig_key, person=b'kMAC').digest()
>>> print(b64encode(enc_key).decode('utf-8'))
rbPb15S/Z9t+agffno5wuhB77VbRi6F9Iv2qIxU7WHw=
>>> print(b64encode(mac_key).decode('utf-8'))
G9GtHFE1YluXY1zWPlYk1e/nWfu0WSEb0KRcjhDeP/o=

15.1.4.3.6. Mode Arbre

L’exemple ci-dessous présente comment hacher un arbre minimal avec deux nœuds terminaux :

  10
 /  \
00  01

Cet exemple utilise en interne des empreintes de 64 octets, et produit finalement des empreintes 32 octets :

>>> from hashlib import blake2b
>>>
>>> FANOUT = 2
>>> DEPTH = 2
>>> LEAF_SIZE = 4096
>>> INNER_SIZE = 64
>>>
>>> buf = bytearray(6000)
>>>
>>> # Left leaf
... h00 = blake2b(buf[0:LEAF_SIZE], fanout=FANOUT, depth=DEPTH,
...               leaf_size=LEAF_SIZE, inner_size=INNER_SIZE,
...               node_offset=0, node_depth=0, last_node=False)
>>> # Right leaf
... h01 = blake2b(buf[LEAF_SIZE:], fanout=FANOUT, depth=DEPTH,
...               leaf_size=LEAF_SIZE, inner_size=INNER_SIZE,
...               node_offset=1, node_depth=0, last_node=True)
>>> # Root node
... h10 = blake2b(digest_size=32, fanout=FANOUT, depth=DEPTH,
...               leaf_size=LEAF_SIZE, inner_size=INNER_SIZE,
...               node_offset=0, node_depth=1, last_node=True)
>>> h10.update(h00.digest())
>>> h10.update(h01.digest())
>>> h10.hexdigest()
'3ad2a9b37c6070e374c7a8c508fe20ca86b6ed54e286e93a0318e95e881db5aa'

15.1.4.4. Crédits

BLAKE2 [https://blake2.net] a été conçu par Jean-Philippe Aumasson, Samuel Neves, Zooko Wilcox-O’Hearn, et Christian Winnerlein basé sur SHA-3 [https://en.wikipedia.org/wiki/NIST_hash_function_competition] finaliste BLAKE [https://131002.net/blake/] créé par Jean-Philippe Aumasson, Luca Henzen, Willi Meier, et Raphael C.-W. Phan.

Il utilise le cœur de l’algorithme de chiffrement de ChaCha [https://cr.yp.to/chacha.html] conçu par Daniel J. Bernstein.

L’implémentation dans la librairie standard est basée sur le module pyblake2 [https://pythonhosted.org/pyblake2/]. Il a été écrit par Dmitry Chestnykh et basé sur l’implémentation C écrite par Samuel Neves. La documentation a été copiée depuis pyblake2 [https://pythonhosted.org/pyblake2/] et écrite par Dmitry Chestnykh.

Le code C a été partiellement réécrit pour Python par Christian Heimes.

Le transfert dans le domaine publique s’applique pour l’implémentation C de la fonction de hachage, ses extensions et cette documentation :

Tout en restant dans les limites de la loi, le(s) auteur(s) a (ont) consacré tous les droits d’auteur et droits connexes et voisins de ce logiciel au domaine public dans le monde entier. Ce logiciel est distribué sans aucune garantie.

You should have received a copy of the CC0 Public Domain Dedication along with this software. If not, see http://creativecommons.org/publicdomain/zero/1.0/.

Les personnes suivantes ont aidé au développement ou contribué aux modification du projet et au domaine public selon la licence Creative Commons Public Domain Dedication 1.0 Universal :

Alexandr Sokolovskiy

Voir aussi

Module hmac

Un module pour générer des codes d’authentification utilisant des hash.

Module base64

Un autre moyen d’encoder des hash binaires dans des environnements non binaires.

https://blake2.net

Site officiel de BLAKE2.

http://csrc.nist.gov/publications/fips/fips180-2/fips180-2.pdf

La publication FIPS 180-2 sur les algorithmes de hachage sécurisés.

https://en.wikipedia.org/wiki/Cryptographic_hash_function#Cryptographic_hash_algorithms

Article Wikipedia contenant les informations relatives aux algorithmes ayant des problèmes et leur interprétation au regard de leur utilisation.

https://www.ietf.org/rfc/rfc2898.txt

PKCS #5: Password-Based Cryptography Specification Version 2.0

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15.2. hmac — Authentification de messages par hachage en combinaison avec une clé secrète

Code source : Lib/hmac.py [https://github.com/python/cpython/tree/3.6/Lib/hmac.py]

Ce module implémente l’algorithme HMAC tel que décrit par la RFC 2104 [https://tools.ietf.org/html/rfc2104.html].

hmac.new(key, msg=None, digestmod=None)

Return a new hmac object. key is a bytes or bytearray object giving the secret key. If msg is present, the method call update(msg) is made. digestmod is the digest name, digest constructor or module for the HMAC object to use. It supports any name suitable to hashlib.new() and defaults to the hashlib.md5 constructor.

Modifié dans la version 3.4: Le paramètre key peut être un byte ou un objet bytearray. Le paramètre msg peut être de n’importe quel type pris en charge par hashlib. Le paramètre digestmod peut être le nom d’un algorithme de hachage.

Obsolète depuis la version 3.4: MD5 as implicit default digest for digestmod is deprecated.

Un objet HMAC a les méthodes suivantes :

HMAC.update(msg)

Met à jour l’objet HMAC avec msg. Des appels répétés sont équivalents à un seul appel avec la concaténation de tous les arguments : m.update(a); m.update(b) est équivalent à m.update(a + b).

Modifié dans la version 3.4: Le paramètre msg peut être de n’importe quel type géré par hashlib.

HMAC.digest()

Renvoie le condensat des octets passés à la méthode update() jusque là. L’objet bytes renvoyé sera de la même longueur que la digest_size de la fonction de hachage donnée au constructeur. Il peut contenir des octets qui ne sont pas dans la table ASCII, y compris des octets NUL.

Avertissement

Si vous devez vérifier la sortie de digest() avec un condensat obtenu par ailleurs par un service extérieur durant une routine de vérification, il est recommandé d’utiliser la fonction compare_digest() au lieu de l’opérateur == afin de réduire la vulnérabilité aux attaques temporelles.

HMAC.hexdigest()

Comme digest() sauf que ce condensat est renvoyé en tant que chaîne de caractères de taille doublée contenant seulement des chiffres hexadécimaux. Cela permet d’échanger le résultat sans problèmes par e-mail ou dans d’autres environnements ne gérant pas les données binaires.

Avertissement

Si l’on compare la sortie de hexdigest() avec celle d’un condensat connu obtenu par un service extérieur durant une routine de vérification, il est recommandé d’utiliser la fonction compare_digest() au lieu de l’opérateur == afin de réduire la vulnérabilité aux attaques basées sur les temps de réponse.

HMAC.copy()

Renvoie une copie (un clone) de l’objet HMAC. C’est utile pour calculer de manière efficace les empreintes cryptographiques de chaînes de caractères qui ont en commun une sous-chaîne initiale.

Un objet code d’authentification de message (HMAC) possède les attributs suivants :

HMAC.digest_size

La taille du code d’authentification (c-à-d de l’empreinte cryptographique) en octets.

HMAC.block_size

La taille interne d’un bloc de l’algorithme de hachage en octets.

Nouveau dans la version 3.4.

HMAC.name

Le nom canonique de ce HMAC, toujours en lettres minuscules, par exemple hmac-md5.

Nouveau dans la version 3.4.

Ce module fournit également la fonction utilitaire suivante :

hmac.compare_digest(a, b)

Renvoie a == b. Cette fonction a été conçue pour prévenir les attaques temporelles en évitant l’implémentation de courts-circuits basés sur le contenu, ce qui la rend appropriée pour de la cryptographie. a et b doivent être du même type : soit str (caractères ASCII seulement, comme retourné par HMAC.hexdigest() par exemple), ou bytes-like object.

Note

Si a et b sont de longueurs différentes ou si une erreur se produit, une attaque temporelle pourrait en théorie obtenir des informations sur les types et longueurs de a et de b, mais pas sur leurs valeurs.

Nouveau dans la version 3.3.

Voir aussi

Module hashlib

Le module Python fournissant des fonctions de hachage sécurisé.

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15.3. secrets — Générer des nombres aléatoires de façon sécurisée pour la gestion des secrets

Nouveau dans la version 3.6.

Code source : Lib/secrets.py [https://github.com/python/cpython/tree/3.6/Lib/secrets.py]

Le module secrets permet de générer des nombres aléatoires forts au sens de la cryptographie, adaptés à la gestion des mots de passe, à l’authentification des comptes, à la gestion des jetons de sécurité et des secrets associés.

Il faut préférer secrets par rapport au générateur pseudo-aléatoire du module random, ce dernier étant conçu pour la modélisation et la simulation, et non pour la sécurité ou la cryptographie.

Voir aussi

PEP 506 [https://www.python.org/dev/peps/pep-0506]

15.3.1. Nombres aléatoires

Le module secrets fournit un accès à la source d’aléa la plus sûre disponible sur votre système d’exploitation.

class secrets.SystemRandom

Classe permettant de générer des nombres aléatoires à partir des sources d’aléa les plus sûres fournies par le système d’exploitation. Se référer à random.SystemRandom pour plus de détails.

secrets.choice(sequence)

Renvoie un élément choisi aléatoirement dans une séquence non-vide.

secrets.randbelow(n)

Renvoie un entier aléatoire dans l’intervalle [0, n).

secrets.randbits(k)

Renvoie un entier de k bits aléatoires.

15.3.2. Génération de jetons

Le module secrets fournit des fonctions pour la génération sécurisée de jetons adaptés à la réinitialisation de mots de passe, à la production d’URLs difficiles à deviner, etc.

secrets.token_bytes([nbytes=None])

Renvoie une chaîne d’octets aléatoire contenant nbytes octets. Si nbytes est None ou omis, une valeur par défaut raisonnable est utilisée.

>>> token_bytes(16)
b'\xebr\x17D*t\xae\xd4\xe3S\xb6\xe2\xebP1\x8b'

secrets.token_hex([nbytes=None])

Renvoie une chaîne de caractères aléatoire en hexadécimal. La chaîne comporte nbytes octets aléatoires, chaque octet étant écrit sous la forme de deux chiffres hexadécimaux. Si nbytes est None ou omis, une valeur par défaut raisonnable est utilisée.

>>> token_hex(16)
'f9bf78b9a18ce6d46a0cd2b0b86df9da'

secrets.token_urlsafe([nbytes=None])

Renvoie une chaîne de caractères aléatoire adaptée au format URL, contenant nbytes octets aléatoires. Le texte est encodé en base64, chaque octet produisant en moyenne 1,3 caractères. Si nbytes est None ou omis, une valeur par défaut raisonnable est utilisée.

>>> token_urlsafe(16)
'Drmhze6EPcv0fN_81Bj-nA'

15.3.2.1. Combien d’octets mon jeton doit-il comporter ?

Afin de se prémunir des attaques par force brute [https://fr.wikipedia.org/wiki/Attaque_par_force_brute], les jetons doivent être suffisamment aléatoires. Malheureusement, l’augmentation de la puissance de calcul des ordinateurs leur permet de réaliser plus de tentatives dans le même laps de temps. De ce fait, le nombre de bits recommandé pour l’aléa augmente aussi. En 2015, une longueur de 32 octets (256 bits) aléatoires est généralement considérée suffisante pour les usages typiques du module secrets.

Si vous souhaitez gérer la longueur des jetons par vous-même, vous pouvez spécifier la quantité d’aléa à introduire dans les jetons en passant un argument int aux différentes fonctions token_*. Cet argument indique alors le nombre d’octets aléatoires utilisés pour la création du jeton.

Sinon, si aucun argument n’est passé ou si celui-ci est None, les fonctions token_* utilisent une valeur par défaut raisonnable à la place.

Note

Cette valeur par défaut est susceptible de changer à n’importe quel moment, y compris lors des mises à jour de maintenance.

15.3.3. Autres fonctions

secrets.compare_digest(a, b)

Return True if strings a and b are equal, otherwise False, in such a way as to reduce the risk of timing attacks [http://codahale.com/a-lesson-in-timing-attacks/]. See hmac.compare_digest() for additional details.

15.3.4. Recettes et bonnes pratiques

Cette section expose les recettes et les bonnes pratiques d’utilisation de secrets pour gérer un niveau minimal de sécurité.

Générer un mot de passe à huit caractères alphanumériques :

import string
alphabet = string.ascii_letters + string.digits
password = ''.join(choice(alphabet) for i in range(8))

Note

Les applications ne doivent jamais stocker des mots de passe dans un format permettant leur récupération [http://cwe.mitre.org/data/definitions/257.html], que ce soit en texte brut ou chiffré. Il convient que les mots de passe soient salés et transformés de façon irréversible par une fonction de hachage cryptographique.

Générer un mot de passe alphanumérique à dix caractères contenant au moins un caractère en minuscule, au moins un caractère en majuscule et au moins trois chiffres :

import string
alphabet = string.ascii_letters + string.digits
while True:
    password = ''.join(choice(alphabet) for i in range(10))
    if (any(c.islower() for c in password)
            and any(c.isupper() for c in password)
            and sum(c.isdigit() for c in password) >= 3):
        break

Generate an XKCD-style passphrase [http://xkcd.com/936/]:

# On standard Linux systems, use a convenient dictionary file.
# Other platforms may need to provide their own word-list.
with open('/usr/share/dict/words') as f:
    words = [word.strip() for word in f]
    password = ' '.join(choice(words) for i in range(4))

Générer une URL temporaire difficile à deviner contenant un jeton de sécurité adapté à réinitialisation d’un mot de passe :

url = 'https://mydomain.com/reset=' + token_urlsafe()

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16. Services génériques du système d’exploitation

Les modules documentés dans ce chapitre fournissent des interfaces vers des fonctionnalités communes à la grande majorité des systèmes d’exploitation, telles que les fichiers et l’horloge. Bien que ces interfaces soient classiquement calquées sur les interfaces Unix ou C, elles sont aussi disponibles sur la plupart des autres systèmes. En voici un aperçu.

16.1. os — Diverses interfaces pour le système d’exploitation

16.1.1. Noms de fichiers, arguments en ligne de commande, et variables d’environnement

16.1.2. Paramètres de processus

16.1.3. Création de fichiers objets

16.1.4. Opérations sur les descripteurs de fichiers

16.1.4.1. Demander la taille d’un terminal

16.1.4.2. Héritage de descripteurs de fichiers

16.1.5. Fichiers et répertoires

16.1.5.1. Attributs étendus pour Linux

16.1.6. Gestion des processus

16.1.7. Interface pour l’ordonnanceur

16.1.8. Diverses informations sur le système

16.1.9. Nombres aléatoires

16.2. io — Core tools for working with streams

16.2.1. Aperçu

16.2.1.1. Text I/O

16.2.1.2. Binary I/O

16.2.1.3. Raw I/O

16.2.2. High-level Module Interface

16.2.2.1. In-memory streams

16.2.3. Class hierarchy

16.2.3.1. I/O Base Classes

16.2.3.2. Raw File I/O

16.2.3.3. Buffered Streams

16.2.3.4. Text I/O

16.2.4. Performances

16.2.4.1. Binary I/O

16.2.4.2. Text I/O

16.2.4.3. Fils d’exécution

16.2.4.4. Reentrancy

16.3. time — Accès au temps et conversions

16.3.1. Fonctions

16.3.2. Constantes d’identification d’horloge

16.3.3. Constantes de fuseau horaire

16.4. argparse – Parseur d’arguments, d’options, et de sous-commandes de ligne de commande

16.4.1. Exemple

16.4.1.1. Créer un analyseur (parser en anglais)

16.4.1.2. Ajouter des arguments

16.4.1.3. Analyse des arguments

16.4.2. Objets ArgumentParser

16.4.2.1. Le paramètre prog

16.4.2.2. Le paramètre usage

16.4.2.3. Le paramètre description

16.4.2.4. Le paramètre epilog

16.4.2.5. Le paramètre parents

16.4.2.6. Le paramètre formatter_class

16.4.2.7. Le paramètre prefix_chars

16.4.2.8. Le paramètre fromfile_prefix_chars

16.4.2.9. Le paramètre argument_default

16.4.2.10. Le paramètre allow_abbrev

16.4.2.11. Le paramètre conflict_handler

16.4.2.12. Le paramètre add_help

16.4.3. La méthode add_argument()

16.4.3.1. Les paramètres name et flags

16.4.3.2. Le paramètre action

16.4.3.3. Le paramètre nargs

16.4.3.4. Le paramètre const

16.4.3.5. Le paramètre default

16.4.3.6. Le paramètre type

16.4.3.7. Le paramètre choices

16.4.3.8. Le paramètre required

16.4.3.9. Le paramètre help

16.4.3.10. Le paramètre metavar

16.4.3.11. Le paramètre dest

16.4.3.12. Classes Action

16.4.4. La méthode parse_args()

16.4.4.1. Option value syntax

16.4.4.2. Arguments invalides

16.4.4.3. Arguments contenant -

16.4.4.4. Arguments abrégés (Par comparaison de leurs préfixes)

16.4.4.5. Au-delà de sys.argv

16.4.4.6. L’objet namespace

16.4.5. Autres outils

16.4.5.1. Sous commandes

16.4.5.2. Objets FileType

16.4.5.3. Groupes d’arguments

16.4.5.4. Exclusion mutuelle

16.4.5.5. Valeurs par défaut de l’analyseur

16.4.5.6. Afficher l’aide

16.4.5.7. Parsing partiel

16.4.5.8. Personnaliser le parsing de fichiers

16.4.5.9. Exiting methods

16.4.6. Mettre à jour du code optparse

16.5. getopt – Analyseur de style C pour les options de ligne de commande

16.6. logging — Fonctionnalités de journalisation pour Python

16.6.1. Objets Enregistreurs

16.6.2. Niveaux de journalisation

16.6.3. Handler Objects

16.6.4. Formatter Objects

16.6.5. Filter Objects

16.6.6. LogRecord Objects

16.6.7. LogRecord attributes

16.6.8. LoggerAdapter Objects

16.6.9. Thread Safety

16.6.10. Fonctions de niveau module

16.6.11. Module-Level Attributes

16.6.12. Integration with the warnings module

16.7. logging.config — Logging configuration

16.7.1. Configuration functions

16.7.2. Configuration dictionary schema

16.7.2.1. Dictionary Schema Details

16.7.2.2. Incremental Configuration

16.7.2.3. Object connections

16.7.2.4. User-defined objects

16.7.2.5. Access to external objects

16.7.2.6. Access to internal objects

16.7.2.7. Import resolution and custom importers

16.7.3. Configuration file format

16.8. logging.handlers — Logging handlers

16.8.1. StreamHandler

16.8.2. FileHandler

16.8.3. NullHandler

16.8.4. WatchedFileHandler

16.8.5. BaseRotatingHandler

16.8.6. RotatingFileHandler

16.8.7. TimedRotatingFileHandler

16.8.8. SocketHandler

16.8.9. DatagramHandler

16.8.10. SysLogHandler

16.8.11. NTEventLogHandler

16.8.12. SMTPHandler

16.8.13. MemoryHandler

16.8.14. HTTPHandler

16.8.15. QueueHandler

16.8.16. QueueListener

16.9. Saisie de mot de passe portable

16.10. curses — Terminal handling for character-cell displays

16.10.1. Fonctions

16.10.2. Window Objects

16.10.3. Constantes

16.11. curses.textpad — Text input widget for curses programs

16.11.1. Textbox objects

16.12. curses.ascii — Utilities for ASCII characters

16.13. curses.panel — A panel stack extension for curses

16.13.1. Fonctions

16.13.2. Panel Objects

16.14. platform — Access to underlying platform’s identifying data

16.14.1. Cross Platform

16.14.2. Java Platform

16.14.3. Windows Platform

16.14.3.1. Win95/98 specific

16.14.4. Mac OS Platform

16.14.5. Unix Platforms

16.15. errno — Symboles du système errno standard

16.16. ctypes — Bibliothèque Python d’appels à des fonctions externes

16.16.1. Didacticiel de ctypes

16.16.1.1. Chargement des DLL

16.16.1.2. Accès aux fonctions des DLL chargées

16.16.1.3. Appel de fonctions

16.16.1.4. Types de données fondamentaux

16.16.1.5. Appel de fonctions, suite

16.16.1.6. Appel de fonctions avec des types de données personnalisés

16.16.1.7. Définition du type des arguments nécessaires (prototypes de fonction)

16.16.1.8. Types de sortie

16.16.1.9. Passage de pointeurs (passage de paramètres par référence)

16.16.1.10. Structures et unions

16.16.1.11. Alignement et boutisme des structures et des unions

16.16.1.12. Champs de bits dans les structures et les unions

16.16.1.13. Tableaux

16.16.1.14. Pointeurs

16.16.1.15. Conversions de type

16.16.1.16. Types incomplets

16.16.1.17. Fonctions de rappel

16.16.1.18. Accès aux variables exportées depuis une DLL

16.16.1.19. Pièges

16.16.1.20. Types de données à taille flottante

16.16.2. Référence du module

16.16.2.1. Recherche de bibliothèques partagées

16.16.2.2. Chargement des bibliothèques partagées

16.16.2.3. Fonctions externes

16.16.2.4. Prototypes de fonction

16.16.2.5. Fonctions utilitaires

16.16.2.6. Types de données

16.16.2.7. Types de données fondamentaux

16.16.2.8. Types de donnée dérivés de Structure

16.16.2.9. Tableaux et pointeurs

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16.1. os — Diverses interfaces pour le système d’exploitation

Code source: Lib/os.py [https://github.com/python/cpython/tree/3.6/Lib/os.py]

Ce module fournit une manière portable d’utiliser les fonctionnalités dépendantes du système d’exploitation. Si vous voulez uniquement lire ou écrire dans un fichier, voir open(), si vous voulez manipuler des chemins, voir le module os.path, et si vous voulez lire toutes les lignes de tous les fichiers listés par l’invite de commande, voir le module fileinput. Pour créer des fichiers temporaires, voir le module tempfile, et pour une manipulation haut niveau des fichiers et dossiers, voir le module shutil.

Notes sur la disponibilité de ces fonctions :

La conception des modules natifs Python dépendants du système d’exploitation est qu’une même fonctionnalité utilise une même interface. Par exemple, la fonction os.stat(path) renvoie des informations sur les statistiques de path dans le même format (qui est originaire de l’interface POSIX).

Les extensions propres à un certain système d’exploitation sont également disponible par le module os, mais les utiliser est bien entendu une menace pour la portabilité.

Toutes les fonctions acceptant les chemins ou noms de fichiers acceptent aussi bien des bytes que des string, et si un chemin ou un nom de fichier est renvoyé, il sera du même type.

Une note « Disponibilité : Unix  » signifie que cette fonction est communément implémentée dans les systèmes Unix. Une telle note ne prétend pas l’existence de la fonction sur un système d’exploitation particulier.

Si ce n’est pas mentionné séparément, toutes les fonctions se réclamant « Disponibilité : Unix » sont gérées sur Mac OS X, qui est basé sur Unix.

Note

Toutes les fonctions de ce module lèvent une OSError dans le cas d’un chemin ou nom de fichier invalide ou inaccessible, ou si d’autres arguments sont de type correct mais non géré par le système d’exploitation.

exception os.error

Un alias pour les exceptions natives OSError.

os.name

Le nom du module importé dépendant du système d’exploitation. Les noms suivants ont actuellement été enregistrés : 'posix', 'nt', 'java'.

Voir aussi

sys.platform a une granularité plus fine. os.uname() donne des informations de version dépendantes de système.

Le module platform fournit des vérifications détaillées pour l’identité du système.

16.1.1. Noms de fichiers, arguments en ligne de commande, et variables d’environnement

En Python, les noms de fichiers, les arguments en ligne de commandes, et les variables d’environnement sont représentées en utilisant le type string. Sur certains systèmes, décoder ces chaînes de caractères depuis et vers des bytes est nécessaire avant de les passer au système d’exploitation. Python utilise l’encodage du système de fichiers pour réaliser ces conversions (voir sys.getfilesystemencoding()).

Modifié dans la version 3.1: Sur certains systèmes, les conversions utilisant l’encodage du système de fichiers peut échouer. Dans ce cas, Python utilise le surrogateescape encoding error handler (le gestionnaire d’erreurs d’encodage surrogateescape), ce qui veut dire que les bytes indécodables sont replacés par un caractère Unicode U+DCxx au décodage, et ceux-ci sont retraduits en le bon octet à l’encodage.

L’encodage du système de fichiers doit garantir de pouvoir décoder correctement tous les octets en dessous de 128. Si l’encodage du système de fichiers ne peut garantir cela, les fonctions de l’API peuvent lever une UnicodeError.

16.1.2. Paramètres de processus

Ces fonctions et valeurs fournissent des informations et agissent sur le processus actuel et sur l’utilisateur.

os.ctermid()

Renvoie l’identifiant de fichier correspondant au terminal contrôlant le processus.

Disponibilité : Unix.

os.environ

Un objet mapping représentant les variables d’environnement. Par exemple environ['HOME'] est le chemin vers votre répertoire d’accueil (sur certaines plate-formes), et est équivalent à getenv("HOME") en C.

Ce mapping est capturé la première fois que le module os est importé, typiquement pendant le démarrage de Python, lors de l’exécution de site.py. Les changements de l’environnement opérés après cette capture ne sont pas répercutés dans os.environ, à part les modifications directes de os.environ.

Si la plate-forme prend en charge la fonction putenv(), ce mapping peut être utilisé pour modifier l’environnement autant que pour l’interroger. putenv() sera appelée automatiquement quand le mapping sera modifié.

Sur Unix, les clefs et les valeurs utilisent sys.getfilesystemencoding() et le gestionnaire d’erreurs surrogateescape. Utilisez environb si vous désirez utiliser un encodage différent.

Note

Appeler putenv() ne change pas directement os.environ, donc il est préférable de modifier os.environ.

Note

Sur certaines plate-formes, dont FreeBSD et Mac OS X, procéder à des assignations sur environ peut causer des fuites de mémoire. Referez-vous à la documentation système de putenv().

Si putenv() n’est pas fourni, une copie modifiée de ce dictionnaire peut être passé aux fonctions appropriées de création de processus pour forcer l’utilisation d’un environnement modifié pour le processus fils.

Si la plate-forme prend en charge la fonction unsetenv(), vous pouvez supprimer des éléments de ce dictionnaire pour supprimer des variables d’environnement. La fonction unsetenv() sera appelée automatiquement quand un élément est supprimé de os.environ, ou quand l’une des méthodes pop() ou clear() est appelée.

os.environb

Une version en bytes de environ : un mapping d’objets représentant l’environnement par des chaîne de bytes. environ et environb sont synchronisés (modifier environ modifie environb, et vice-versa).

environb n’est disponible que si supports_byte_environ vaut True.

Nouveau dans la version 3.2.

os.chdir(path)

os.fchdir(fd)

os.getcwd()

Ces fonctions sont décrites dans Fichiers et répertoires.

os.fsencode(filename)

Encode le chemin-compatible filename vers l’encodage du système de fichiers avec une gestion d’erreurs 'surrogateescape', ou 'strict' sous Windows ; renvoie un objet bytes inchangé.

fsdecode() est la fonction inverse.

Nouveau dans la version 3.2.

Modifié dans la version 3.6: Ajout de la prise en charge des objets implémentant l’interface os.PathLike.

os.fsdecode(filename)

Encode le chemin-compatible filename depuis l’encodage du système de fichiers avec une gestion d’erreurs 'surrogateescape', ou 'strict' sous Windows ; renvoie un objet str inchangé.

fsencode() est la fonction inverse.

Nouveau dans la version 3.2.

Modifié dans la version 3.6: Ajout de la prise en charge des objets implémentant l’interface os.PathLike.

os.fspath(path)

Renvoie la représentation par le système de fichiers du chemin.

Si un objet str ou bytes est passé, il est renvoyé inchangé. Autrement, __fspath__() est appelée et sa valeur renvoyée tant qu’elle est un objet str ou bytes. Dans tous les autres cas, une TypeError est levée.

Nouveau dans la version 3.6.

class os.PathLike

Une abstract base class pour les objets représentant un chemin du système de fichiers, comme pathlib.PurePath.

Nouveau dans la version 3.6.

abstractmethod __fspath__()

Renvoie la représentation du chemin du système de fichiers de l’objet.

La méthode ne devrait renvoyer que des objets str ou bytes, avec une préférence pour les str.

os.getenv(key, default=None)

Renvoie la valeur de la variable d’environnement key si elle existe, ou default si elle n’existe pas. key, default, et la valeur de retour sont des str.

Sur Unix, les clefs et les valeurs sont décodées avec sys.getfilesystemencoding() et le gestionnaire d’erreurs surrogateescape. Utilisez os.getenvb() si vous voulez utiliser un encodage différent.

Disponibilité : la plupart des dérivés Unix, Windows.

os.getenvb(key, default=None)

Renvoie la valeur de la variable d’environnement key si elle existe, ou default si elle n’existe pas. key, default, et la valeur de retour sont des bytes.

getenvb() n’est disponible que si supports_byte_environ vaut True.

Disponibilité : la plupart des dérivés Unix.

Nouveau dans la version 3.2.

os.get_exec_path(env=None)

Renvoie la liste des dossier qui seront parcouru pour trouver un exécutable, similaire à un shell lorsque il lance un processus. env, quand spécifié, doit être un dictionnaire de variable d’environnement afin d’y rechercher le PATH. Par défaut quand env est None, environ est utilisé.

Nouveau dans la version 3.2.

os.getegid()

Renvoie l’identifiant du groupe effectif du processus actuel. Ça correspond au bit « set id » du fichier qui s’exécute dans le processus actuel.

Disponibilité : Unix.

os.geteuid()

Renvoie l’identifiant de l’utilisateur effectif du processus actuel.

Disponibilité : Unix.

os.getgid()

Renvoie l’identifiant de groupe réel du processus actuel.

Disponibilité : Unix.

os.getgrouplist(user, group)

Renvoie la liste d’identifiants de groupes auxquels user appartient. Si group n’est pas dans la liste, il y est inclus. Typiquement, group vaut le group ID de l’enregistrement passwd de user.

Disponibilité : Unix.

Nouveau dans la version 3.3.

os.getgroups()

Renvoie une liste d’identifiants de groupes additionnels associés au processus actuel.

Disponibilité : Unix.

Note

Sur Mac OS X, le comportement de getgroups() diffère légèrement des autres plate-formes Unix. Si l’interpréteur Python était compilé avec une cible de déploiement de 10.5 ou moins, getgroups() renverrait la liste des identifiants de groupes effectifs associés au processus courant de l’utilisateur ; le nombre d’éléments de cette liste est limité par le système, typiquement 16, et peut être modifié par des appels à setgroups() si les privilèges ont été convenablement assignés. Si compilé avec une cible de déploiement supérieure à 10.5, la fonction getgroups() renvoie la liste des accès du groupe actuel pour l’utilisateur associé à l’identifiant utilisateur du processus ; la liste d’accès du groupe peut changer durant la vie du processus, elle n’est pas affectée par les appels à setgroups() et sa longueur n’est pas limitée à 16. La valeur de la cible de déploiement, MACOSX_DEPLOYMENT_TARGET, peut être obtenue par la fonction sysconfig.get_config_var().

os.getlogin()

Renvoie le nom de l’utilisateur connecté sur le terminal contrôlant le processus. Dans la plupart des cas, il est plus utile d’utiliser getpass.getuser() puisque cette fonction consulte les variables d’environnement LOGNAME et USERNAME pour savoir qui est l’utilisateur, et se replie finalement sur pwd.getpwduid(os.getuid())[0] pour avoir le nom de connexion lié à l’identifiant de l’utilisateur courant.

Disponibilité : Unix, Windows.

os.getpgid(pid)

Renvoie l’identifiant de groupe de processus du processus de PID pid. Si pid vaut 0, l’identifiant de groupe de processus du processus actuel est renvoyé.

Disponibilité : Unix.

os.getpgrp()

Renvoie l’identifiant du groupe de processus actuel.

Disponibilité : Unix.

os.getpid()

Renvoie l’identifiant du processus actuel.

os.getppid()

Renvoie l’identifiant du processus parent. Quand le processus parent est terminé, sur Unix, l’identifiant renvoyé est 1 pour le processus init, sur Windows, c’est toujours le même id, qui peut déjà avoir été réutilisé par un autre processus.

Disponibilité : Unix, Windows.

Modifié dans la version 3.2: Prise en charge sur Windows.

os.getpriority(which, who)

Récupère la priorité d’ordonnancement des programmes. La valeur which est une des constantes suivantes : PRIO_PROCESS, PRIO_PGRP, ou PRIO_USER, et la valeur who est interprétée par rapport à which (un id de processus pour PRIO_PROCESS, un id de groupe de processus pour PRIO_PGRP, et un id d’utilisateur pour PRIO_USER). Une valeur nulle pour who dénote (respectivement) le processus appelant, le groupe de processus du processus appelant, ou l’identifiant d’utilisateur réel du processus appelant.

Disponibilité : Unix.

Nouveau dans la version 3.3.

os.PRIO_PROCESS

os.PRIO_PGRP

os.PRIO_USER

Paramètres pour les fonctions getpriority() et setpriority().

Disponibilité : Unix.

Nouveau dans la version 3.3.

os.getresuid()

Renvoie un tuple (ruid, euid, suid) dénotant les identifiants de l’utilisateur réel, effectif et sauvé du processus actuel.

Disponibilité : Unix.

Nouveau dans la version 3.2.

os.getresgid()

Renvoie un tuple (rgid, egid, sgid) dénotant les identifiants des groupes de processus réel effectif, et sauvé du processus actuel.

Disponibilité : Unix.

Nouveau dans la version 3.2.

os.getuid()

Renvoie l’identifiant réel du processus actuel.

Disponibilité : Unix.

os.initgroups(username, gid)

Appelle la fonction système initgroups pour initialiser la liste des groupes d’accès des groupes dont username est membre, plus le groupe spécifié par gid.

Disponibilité : Unix.

Nouveau dans la version 3.2.

os.putenv(key, value)

Assigne la chaîne de caractères value à la variable d’environnement key. De tels changements à l’environnement affectent les sous-processus lancés par os.system(), popen() ou fork() et execv().

Disponibilité : la plupart des dérivés Unix, Windows.

Note

Sur certaines plate-formes, incluant FreeBSD et Mac OS X, assigner environ peut causer des fuites de mémoire. Referez-vous à la documentation système de putenv.

Quand putenv() est géré, les assignations d’éléments dans os.environ sont automatiquement traduites en appels correspondants à putenv(). Cependant, des appels à putenv() ne mettent pas os.environ à jour. Il est donc préférable d’assigner les éléments de os.environ.

os.setegid(egid)

Définit l’identifiant du groupe de processus effectif du processus actuel.

Disponibilité : Unix.

os.seteuid(euid)

Définit l’identifiant de l’utilisateur effectif du processus actuel.

Disponibilité : Unix.

os.setgid(gid)

Définit l’identifiant du groupe de processus actuel.

Disponibilité : Unix.

os.setgroups(groups)

Place groups dans la liste d’identifiants de groupes additionnels associée. groups doit être une séquence, et chaque élément doit être un nombre entier identifiant un groupe. Cette opération est typiquement disponible uniquement pour le super utilisateur.

Disponibilité : Unix.

Note

Sur Mac OS X, la longueur de groups ne peut pas dépasser le nombre maximum d’identifiants effectifs de groupes défini par le système, typiquement 16. Voir la documentation de getgroups() pour les cas où getgroups ne renvoie pas la même liste de groupes que celle définie par l’appel à setgroups.

os.setpgrp()

Produit l’appel système setpgrp() ou setpgrp(0, 0) selon la version implémentée (s’il y en a une). Voir le manuel Unix pour la sémantique de l’opération.

Disponibilité : Unix.

os.setpgid(pid, pgrp)

Produit l’appel système setpgid() pour placer l’identifiant du groupe de processus contenant le processus d’identifiant pid dans le groupe de processus d’identifiant pgrp. Voir le manuel Unix pour la sémantique.

Disponibilité : Unix.

os.setpriority(which, who, priority)

Définit la priorité d’ordonnancement des programmes. La valeur which est une des constantes suivantes : PRIO_PROCESS, PRIO_PGRP, ou PRIO_USER, et who est interprété en fonction de which (un PID pour PRIO_PROCESS, un identifiant de groupe de processus pour PRIO_PGRP, et un identifiant d’utilisateur pour PRIO_USER). Une valeur nulle pour who dénote (respectivement) le processus appelant, le groupe de processus du processus appelant, ou l’identifiant de l’utilisateur réel du processus appelant. priority est une valeur comprise entre -20 et 19. La priorité par défaut est 0 ; les priorités plus faibles amènent à un ordonnancement plus favorable.

Disponibilité : Unix

Nouveau dans la version 3.3.

os.setregid(rgid, egid)

Définit l’identifiant des groupes réel et effectif du processus actuel.

Disponibilité : Unix.

os.setresgid(rgid, egid, sgid)

Définit l’identifiant des groupes réel, effectif et sauvé du processus actuel.

Disponibilité : Unix.

Nouveau dans la version 3.2.

os.setresuid(ruid, euid, suid)

Définit l’identifiant des utilisateurs réel, effectif et sauvé du processus actuel.

Disponibilité : Unix.

Nouveau dans la version 3.2.

os.setreuid(ruid, euid)

Définit l’identifiant des utilisateurs réel et effectif du processus actuel.

Disponibilité : Unix.

os.getsid(pid)

Produit l’appel système getsid(). Voir le manuel Unix pour la sémantique.

Disponibilité : Unix.

os.setsid()

Produit l’appel système setsid(). Voir le manuel Unix pour la sémantique.

Disponibilité : Unix.

os.setuid(uid)

Définit l’identifiant de l’utilisateur du processus actuel.

Disponibilité : Unix.

os.strerror(code)

Renvoie le message d’erreur correspondant au code d’erreur code. Sur les plate-formes où strerror() renvoie NULL quand un numéro d’erreur inconnu est donné, une ValueError est levée.

os.supports_bytes_environ

True si le type natif de l’environnement du système d’exploitation est bytes (par exemple : False sur Windows).

Nouveau dans la version 3.2.

os.umask(mask)

Définit le umask actuel et renvoie la valeur précédente.

os.uname()

Renvoie des informations identifiant le système d’exploitation actuel. La valeur de retour est un objet à cinq attributs :

sysname — nom du système d’exploitation

noedname — nom de la machine sur le réseau (dépendant de l’implémentation)

release — release du système d’exploitation

version — version du système d’exploitation

machine — identifiant du matériel

Pour la rétrocompatibilité, cet objet est également itérable, se comportant comme un quintuplet contenant sysname, nodename, release, version, et machine dans cet ordre.

Certains systèmes tronquent nodename à 8 caractères ou à la composante dominante. Un meilleur moyen de récupérer le nom de l’hôte est socket.gethostname() ou encore socket.gethostbyaddre(socket.gethostname()).

Disponibilité : dérivés récents de Unix.

Modifié dans la version 3.3: Type de retour changé d’un tuple en un objet compatible avec le type tuple, avec des attributs nommés.

os.unsetenv(key)

Supprime la variable d’environnement appelée key. De tels changements à l’environnement affectent les sous-processus lancés avec os.system(), popen() ou fork() et execv().

Quand unsetenv() est gérée, la suppression d’éléments dans os.environ est automatiquement interprétée en un appel correspondant à unsetenv(), mais les appels à unsetenv() ne mettent pas os.environ à jour. Donc il est préférable de supprimer les éléments de os.environ.

Disponibilité : la plupart des dérivés Unix, Windows.

16.1.3. Création de fichiers objets

Cette fonction crée de nouveaux fichiers objets. (Voir aussi open() pour ouvrir des descripteurs de fichiers).

os.fdopen(fd, *args, **kwargs)

Renvoie un fichier objet ouvert connecté au descripteur de fichier fd. C’est un alias de la primitive open() et accepte les mêmes arguments. La seule différence est que le premier argument de fdopen() doit toujours être un entier.

16.1.4. Opérations sur les descripteurs de fichiers

Ces fonctions opèrent sur des flux d’entrées/sorties référencés par des descripteurs de fichiers.

Les descripteurs de fichiers sont de petits entiers correspondant à un fichier qui a été ouvert par le processus courant. Par exemple, l’entrée standard est habituellement le descripteur de fichier 0, la sortie standard est 1, et le flux standard d’erreur est 2. Les autres fichiers ouverts par un processus vont se voir assigner 3, 4, 5, etc. Le nom « descripteur de fichier » est légèrement trompeur : sur les plate-formes Unix, les connecteurs (socket en anglais) et les tubes (pipe en anglais) sont également référencés par des descripteurs.

La méthode fileno() peut être utilisée pour obtenir le descripteur de fichier associé à un file object quand nécessaire. Notez qu’utiliser le descripteur directement outrepasse les méthodes du fichier objet, ignorant donc des aspects tels que la mise en tampon interne des données.

os.close(fd)

Ferme le descripteur de fichier fd.

Note

Cette fonction est destinée aux opérations d’entrées/sorties de bas niveau et doit être appliquée à un descripteur de fichier comme ceux donnés par os.open() ou pipe(). Pour fermer un « fichier objet » renvoyé par la primitive open(), popen() ou fdopen(), il faut utiliser sa méthode close().

os.closerange(fd_low, fd_high)

Ferme tous les descripteurs de fichiers entre fd_low (inclus) jusque fd_high (exclus), en ignorant les erreurs. Équivalent (mais beaucoup plus rapide) à :

for fd in range(fd_low, fd_high):
    try:
        os.close(fd)
    except OSError:
        pass

os.device_encoding(fd)

Renvoie une chaîne de caractères décrivant l’encodage du périphérique associé à fd s’il est connecté à un terminal, sinon renvoie None.

os.dup(fd)

Renvoie une copie du descripteur de fichier fd. Le nouveau descripteur de fichier est non-héritable.

Sur Windows, quand un flux standard est dupliqué (0 : stdin, 1 : stdout, 2 : stderr), le nouveau descripteur de fichier est héritable.

Modifié dans la version 3.4: Le nouveau descripteur de fichier est maintenant non-héritable.

os.dup2(fd, fd2, inheritable=True)

Copie le descripteur de fichier fd dans fd2, en fermant le premier si nécessaire. Le descripteur de fichier fd2 est héritable par défaut, ou non-héritable si inheritable vaut False.

Modifié dans la version 3.4: Ajout du paramètre optionnel inheritable.

os.fchmod(fd, mode)

Change le mode du fichier donné par fd en la valeur numérique mode. Voir la documentation de chmod() pour les valeurs possibles de mode. Depuis Python 3.3, c’est équivalent à os.chmod(fd, mode).

Disponibilité : Unix.

os.fchown(fd, uid, gid)

Change le propriétaire et l’identifiant de groupe du fichier donné par fd en les valeurs numériques uid et gid. Pour laisser l’un des identifiants inchangés, mettez-le à -1. Voir chown(). Depuis Python 3.3, c’est équivalent à os.chown(fd, uid, gid).

Disponibilité : Unix.

os.fdatasync(fd)

Force l’écriture du fichier ayant le descripteur fd sur le disque. Ne force pas la mise à jour des méta-données.

Disponibilité : Unix.

Note

Cette fonction n’est pas disponible sur MacOS.

os.fpathconf(fd, name)

Renvoie les informations de la configuration du système pour un fichier ouvert. name spécifie la valeur de la configuration à récupérer, ça peut être une chaîne de caractères avec le nom d’une valeur système définie ; ces valeurs sont spécifiées dans certains standards (POSIX.1, Unix 95, Unix 98, et d’autres). Certaines plate-formes définissent des noms additionnels également. Les noms connus par le système d’exploitation sont donnés dans le dictionnaire pathconf_names. Pour les variables de configuration qui ne sont pas inclues dans ce mapping, passer un entier pour name est également accepté.

Si name est une chaîne de caractères et n’est pas connu, une ValueError est levée. Si une valeur spécifique de name n’est pas gérée par le système hôte, même si elle est incluse dans pathconf_names, une OSError est levée avec errno.EINVAL pour code d’erreur.

Depuis Python 3.3, c’est équivalent à os.pathconf(fd, name).

Disponibilité : Unix.

os.fstat(fd)

Récupère le statut du descripteur de fichier fd. Renvoie un objet stat_result.

Depuis Python 3.3, c’est équivalent à os.stat(fd).

Voir aussi

La fonction stat().

os.fstatvfs(fd)

Renvoie des informations sur le système de fichier contenant le fichier associé au descripteur fd, comme statvfs(). Depuis Python 3.3, c’est équivalent à os.statvfs(fd).

Disponibilité : Unix.

os.fsync(fd)

Force l’écriture du fichier ayant le descripteur fd sur le disque. Sur Unix, cet appel appel la fonction native fsync(), sur Windows, la fonction MS _commit().

Si vous débutez avec un file object Python mis en tampon f, commencez par faire f.flush() et seulement ensuite os.fsync(f.fileno()) pour être sûr que tous les tampons internes associés à f soient écrits sur le disque.

Disponibilité : Unix, Windows.

os.ftruncate(fd, length)

Tronque le fichier correspondant au descripteur fd pour qu’il soit maximum long de length bytes. Depuis Python 3.3, c’est équivalent à os.truncate(fd, length).

Disponibilité : Unix, Windows.

Modifié dans la version 3.5: Prise en charge de Windows

os.get_blocking(fd)

Récupère le mode bloquant du descripteur de fichier : False si l’indicateur O_NONBLOCK est mis, et True si l’indicateur est effacé.

Voir également set_blocking() et socket.socket.setblocking().

Disponibilité : Unix.

Nouveau dans la version 3.5.

os.isatty(fd)

Renvoie True si le descripteur de fichier fd est ouvert et connecté à un périphérique TTY (ou compatible), sinon False.

os.lockf(fd, cmd, len)

Applique, teste, ou retire un verrou POSIX sur un descripteur de fichier ouvert. fd est un descripteur de fichier ouvert. cmd spécifie la commande à utiliser (une des valeurs suivantes : F_LOCK, F_TLOCK, F_ULOCK, ou F_TEST). len spécifie la section du fichier à verrouiller.

Disponibilité : Unix.

Nouveau dans la version 3.3.

os.F_LOCK

os.F_TLOCK

os.F_ULOCK

os.F_TEST

Indicateurs spécifiant quelle action lockf() va prendre.

Disponibilité : Unix.

Nouveau dans la version 3.3.

os.lseek(fd, pos, how)

Place la position actuelle du descripteur de fichier fd à la position pos, modifié par how : SEEK_SET ou 0 pour placer la position à partir du début du fichier, SEEK_CUR ou 1 pour la placer à partir de la position actuelle, et SEEK_END ou 2 pour la placer par rapport à la fin du fichier. Renvoie la nouvelle position du curseur en bytes, à partir du début.

os.SEEK_SET

os.SEEK_CUR

os.SEEK_END

Paramètres de la fonction lseek(). Leur valeur est respectivement 0, 1, et 2.

Nouveau dans la version 3.3: Certains systèmes d’exploitation pourraient gérer des valeurs additionnelles telles que os.SEEK_HOLE ou os.SEEK_DATA.

os.open(path, flags, mode=0o777, *, dir_fd=None)

Ouvre le fichier path et met certains indicateurs selon flags et éventuellement son mode selon mode. Lors de l’évaluation de code, ce umask actuel est d’abord masquée. Renvoie le descripteur de fichier du fichier nouvellement ouvert. Le nouveau descripteur de fichier est non-héritable.

Pour une description des indicateurs et des valeurs des modes, voir la documentation de la bibliothèque standard du C. Les constantes d’indicateurs (telles que O_RDONLY et O_WRONLY) sont définies dans le module os. En particulier, sur Windows, ajouter O_BINARY est nécessaire pour ouvrir des fichiers en binaire.

Cette fonction prend en charge des chemins relatifs à des descripteurs de répertoires avec le paramètre dir_fd.

Modifié dans la version 3.4: Le nouveau descripteur de fichier est maintenant non-héritable.

Note

Cette fonction est destinée aux E/S de bas-niveau. Pour un usage normal, utilisez la primitive open() qui renvoie un file object avec les méthodes read() et write() (et plein d’autres). Pour envelopper un descripteur de fichier dans un fichier objet, utilisez fdopen().

Nouveau dans la version 3.3: L’argument dir_fd.

Modifié dans la version 3.5: Si l’appel système est interrompu et que le gestionnaire de signal ne lève aucune exception, la fonction réessaye l’appel système au lieu de lever une InterruptedError (voir la PEP 475 [https://www.python.org/dev/peps/pep-0475] à propos du raisonnement).

Modifié dans la version 3.6: Accepte un path-like object.

Les constantes suivantes sont optionnelles pour le paramètre flag à la fonction open(). Elles peuvent être combinées en utilisant l’opérateur bit-à-bit OR |. certains ne sont pas disponibles sur toutes les plate-formes. Pour une description sur leur disponibilité et leur usage, consultez la page de manuel Unix open(2) ou la MSDN [https://msdn.microsoft.com/en-us/library/z0kc8e3z.aspx] sur Windows.

os.O_RDONLY

os.O_WRONLY

os.O_RDWR

os.O_APPEND

os.O_CREAT

os.O_EXCL

os.O_TRUNC

Les constantes ci-dessus sont disponibles sur Unix et Windows.

os.O_DSYNC

os.O_RSYNC

os.O_SYNC

os.O_NDELAY

os.O_NONBLOCK

os.O_NOCTTY

os.O_CLOEXEC

Les constantes ci-dessus sont uniquement disponibles sur Unix.

Modifié dans la version 3.3: Ajout de la constante O_CLOCEXEC.

os.O_BINARY

os.O_NOINHERIT

os.O_SHORT_LIVED

os.O_TEMPORARY

os.O_RANDOM

os.O_SEQUENTIAL

os.O_TEXT

Les constantes ci-dessus sont uniquement disponibles sur Windows.

os.O_ASYNC

os.O_DIRECT

os.O_DIRECTORY

os.O_NOFOLLOW

os.O_NOATIME

os.O_PATH

os.O_TMPFILE

os.O_SHLOCK

os.O_EXLOCK

Les constantes ci-dessus sont des extensions et ne sont pas présentes si elles ne sont pas définies par la bibliothèque C.

Modifié dans la version 3.4: Ajout de O_PATH sur les systèmes qui le gèrent. Ajout de O_TMPFILE, uniquement disponible sur Linux Kernel 3.11 ou plus récent.

os.openpty()

Ouvre une nouvelle paire pseudo-terminal. Renvoie une paire de descripteurs de fichiers (master, slave) pour le PTY et le TTY respectivement. Les nouveaux descripteurs de fichiers sont non-héritables. Pour une approche (légèrement) plus portable, utilisez le module pty.

Disponibilité : certains dérivés Unix.

Modifié dans la version 3.4: Les nouveaux descripteurs de fichiers sont maintenant non-héritables.

os.pipe()

Crée un pipe (un tube). Renvoie une paire de descripteurs de fichiers (r, w) utilisables respectivement pour lire et pour écrire. Les nouveaux descripteurs de fichiers sont non-héritables.

Disponibilité : Unix, Windows.

Modifié dans la version 3.4: Les nouveaux descripteurs de fichiers sont maintenant non-héritables.

os.pipe2(flags)

Crée un pipe avec flags mis atomiquement. flags peut être construit en appliquant l’opérateur | (OU) sur une ou plus de ces valeurs : O_NONBLOCK, O_CLOEXEC. Renvoie une paire de descripteurs de fichiers (r, w) utilisables respectivement pour lire et pour écrire.

Disponibilité : certains dérivés Unix.

Nouveau dans la version 3.3.

os.posix_fallocate(fd, offset, len)

Assure que suffisamment d’espace sur le disque est alloué pour le fichier spécifié par fd partant de offset et continuant sur len bytes.

Disponibilité : Unix.

Nouveau dans la version 3.3.

os.posix_fadvise(fd, offset, len, advice)

Annonce une intention d’accéder à des données selon un motif spécifique, et donc permettant au noyau de faire des optimisations. Le conseil advice s’applique à la région spécifiée par fd, démarrant à offset et continuant sur len bytes. advice est une des valeurs suivantes : POSIX_FADV_NORMAL, POSIX_FADV_SEQUENTIAL, POSIX_FADV_RANDOM, POSIX_FADV_NOREUSE, POSIX_FADV_WILLNEED, ou POSIX_FADV_DONTNEED.

Disponibilité : Unix.

Nouveau dans la version 3.3.

os.POSIX_FADV_NORMAL

os.POSIX_FADV_SEQUENTIAL

os.POSIX_FADV_RANDOM

os.POSIX_FADV_NOREUSE

os.POSIX_FADV_WILLNEED

os.POSIX_FADV_DONTNEED

Indicateurs qui peuvent être utilisés dans advice dans la fonction posix_fadvise() et qui spécifient le motif d’accès qui est censé être utilisé.

Disponibilité : Unix.

Nouveau dans la version 3.3.

os.pread(fd, buffersize, offset)

Lit depuis un descripteur de fichier fd à la position de l”offset. Cela va lire jusqu’à buffersize bytes. L’offset du fichier ne sera pas changé.

Disponibilité : Unix.

Nouveau dans la version 3.3.

os.pwrite(fd, str, offset)

Écrit bytestring dans un descripteur de fichier fd à une position offset en laissant le décalage du fichier inchangé.

Disponibilité : Unix.

Nouveau dans la version 3.3.

os.read(fd, n)

Lit au plus n bytes depuis le descripteur fd. Renvoie une chaîne de bytes contenant les bytes lus. Si la fin du fichier référencé par fd est atteinte, un objet vide de bytes est renvoyé.

Note

Cette fonction est destinée aux E/S bas niveau et doit être appliquée à un descripteur de fichier comme renvoyé par os.open() ou pipe(). Pour lire dans un « fichier objet » renvoyé par la primitive open(), popen() ou fdopen(), ou par stdin, utilisez sa méthode read() ou readline().

Modifié dans la version 3.5: Si l’appel système est interrompu et que le gestionnaire de signal ne lève aucune exception, la fonction réessaye l’appel système au lieu de lever une InterruptedError (voir la PEP 475 [https://www.python.org/dev/peps/pep-0475] à propos du raisonnement).

os.sendfile(out, in, offset, count)

os.sendfile(out, in, offset, count, [headers, ][trailers, ]flags=0)

Copie count bytes depuis un descripteur de fichier in dans un descripteur de fichier out en démarrant à offset. Renvoie le nombre de bytes envoyés. Quand EOF est atteint, renvoie 0.

La première notation de fonction est prise en charge par toutes les plate-formes qui définissent sendfile().

Sur Linux, si offset est donné par None, les bytes sont lus depuis la position actuelle de in et la position de in est mise à jour.

Le second cas peut être utilisé sur Mac OS X et FreeBSD où headers et trailers sont des séquences arbitraires de tampons qui sont écrites avant et après que les données de in ne soient écrites. Renvoie la même chose que le premier cas.

Sur Mac OS X et FreeBSD, une valeur de 0 pour count spécifié d’envoyer jusqu’à ce que la fin de in ne soit atteinte.

Toutes les plate-formes gèrent les connecteurs comme des descripteurs de fichier out, et certaines plate-formes autorisent d’autres types (par exemple, un fichier normal ou un tube) également.

Les applications multiplate-formes ne devraient pas utiliser les arguments headers, trailers, et flags.

Disponibilité : Unix.

Note

Pour une interface de plus haut niveau de sendfile(), voir socket.socket.setfile().

Nouveau dans la version 3.3.

os.set_blocking(fd, blocking)

Définit le mode bloquant d’un descripteur de fichier spécifié. Assigne l’indicateur O_NONBLOCK si blocking vaut False, efface l’indicateur sinon.

Voir aussi get_blocking() et socket;socket.setblocking().

Disponibilité : Unix.

Nouveau dans la version 3.5.

os.SF_NODISKIO

os.SF_MNOWAIT

os.SF_SYNC

Paramètres de la fonction sendfile(), si l’implémentation les gère.

Disponibilité : Unix.

Nouveau dans la version 3.3.

os.readv(fd, buffers)

Lit depuis un descripteur de fichier fd dans un nombre d” objets bytes-compatibles muables : buffers. readv() va transférer les données dans chaque tampon jusqu’à ce qu’il soit plein et puis passer au tampon suivant dans la séquence pour y placer le reste de la donnée. readv() renvoie le nombre total de bytes lus (qui peut être moins que la capacité totale de tous les objets).

Disponibilité : Unix.

Nouveau dans la version 3.3.

os.tcgetpgrp(fd)

Renvoie le groupe de processus associé au terminal donné par fd (un descripteur de fichier ouvert comme renvoyé par os.open()).

Disponibilité : Unix.

os.tcsetpgrp(fd, pg)

Place pg dans le groupe de processus associé au terminal donné par fd (un descripteur de fichier ouvert comme renvoyé par os.open()).

Disponibilité : Unix.

os.ttyname(fd)

Renvoie une chaîne de caractères spécifiant le périphérique terminal associé au descripteur de fichier fd. Si fd n’est pas associé à un périphérique terminal, une exception est levée.

Disponibilité : Unix.

os.write(fd, str)

Écrit la chaîne de bytes de str dans le descripteur de fichier fd. Renvoie le nombre de bytes réellement écrits.

Note

Cette fonction est destinée aux entrées-sorties bas niveau et doit être appliquée à un descripteur de fichier comme renvoyé par os.open() ou pipe(). Pour écrire dans un « fichier objet » renvoyé par la primitive open(), popen(), ou par fdopen(), ou par sys.stdout ou sys.stderr, utilisez sa méthode write().

Modifié dans la version 3.5: Si l’appel système est interrompu et que le gestionnaire de signal ne lève aucune exception, la fonction réessaye l’appel système au lieu de lever une InterruptedError (voir la PEP 475 [https://www.python.org/dev/peps/pep-0475] à propos du raisonnement).

os.writev(fd, buffers)

Écrit le contenu de buffers vers le descripteur de fichier fd. buffers doit être une séquence d”objets bytes-compatibles. Les tampons sont traités dans l’ordre du tableau. Le contenu entier du premier tampon est écrit avant le traitement du second, etc. Le système d’exploitation peut avoir une limite (valeur sysconf() SC_IOV_MAX) sur le nombre de tampons qui peuvent être utilisés.

writev() écrit le contenu de chaque objet vers le descripteur de fichier et renvoie le nombre total d’octets écrits.

Disponibilité : Unix.

Nouveau dans la version 3.3.

16.1.4.1. Demander la taille d’un terminal

Nouveau dans la version 3.3.

os.get_terminal_size(fd=STDOUT_FILENO)

Renvoie la taille du terminal comme un couple (columns, lines) de type terminal_size.

L’argument optionnel fd (par défaut : STDOUT_FILENO, ou la sortie standard) spécifie le descripteur de fichier auquel la requête doit être envoyée.

Si le descripteur de fichier n’est pas connecté à un terminal, une OSError est levée.

shutil.get_terminal_size() est la fonction haut-niveau qui devrait normalement être utilisée, os.get_terminal_size en est l’implémentation bas-niveau.

Disponibilité : Unix, Windows.

class os.terminal_size

Une sous-classe de tuple, contenant (columns, lines), la taille du terminal.

columns

Longueur du terminal en caractères.

lines

Hauteur du terminal en caractères.

16.1.4.2. Héritage de descripteurs de fichiers

Nouveau dans la version 3.4.

Un descripteur de fichier a un indicateur indiquant s’il peut être hérité par les processus-fils. Depuis Python 3.4, les descripteurs de fichiers créés par Python ne sont pas héritable par défaut.

Sur UNIX, les descripteurs de fichiers non-héritables sont fermés dans les processus-fils à l’exécution, les autres descripteurs sont hérités.

Sur Windows, les fichiers et identificateurs non-héritables sont fermés dans les processus-fils, à part les flux standards (descripteurs 0, 1, et 2 : stdin, stdout et stderr) qui sont toujours hérités. En utilisant les fonctions spawn*, tous les identificateurs héritables et les descripteurs de fichiers héritables sont hérités. En utilisant le module subprocess, tous les descripteurs de fichiers (à part les flux standards) sont fermés, et les identificateurs héritables sont hérités seulement si le paramètre close_fds vaut False.

os.get_inheritable(fd)

Récupère le marqueur « héritable » (booléen) du descripteur de fichier spécifié.

os.set_inheritable(fd, inheritable)

Définit le marqueur « héritable » du descripteur de fichier spécifié.

os.get_handle_inheritable(handle)

Récupère le marqueur « héritable » (booléen) de l’identificateur spécifié.

Disponibilité : Windows.

os.set_handle_inheritable(handle, inheritable)

Définit le marqueur « héritable » de l’identificateur spécifié.

Disponibilité : Windows.

16.1.5. Fichiers et répertoires

Sur certaines plate-formes Unix, beaucoup de ces fonctions gèrent une ou plusieurs des fonctionnalités suivantes :

spécifier un descripteur de fichier : pour certaines fonctions, l’argument path peut être non seulement une chaîne de caractères donnant le chemin vers le fichier, mais également un descripteur de fichier. La fonction opérera alors sur le fichier référencé par le descripteur. (Pour les systèmes POSIX, Python appellera la version f... de la fonction.)

Vous pouvez vérifier si path peut être donné par un descripteur de fichier sur votre plate-forme en utilisant os.supports_fd. Si c’est indisponible, l’utiliser lèvera une NotImplementedError.

Si la fonction gère également les arguments dir_fd ou follow_symlinks, spécifier l’un de ces arguments est une erreur quand path est donné en tant que descripteur de fichier.

Chemins relatifs vers des descripteurs de répertoires : si dir_fd n’est pas None, il devrait être un descripteur de fichier référençant un répertoire, et le chemin sur lequel opérer devrait être relatif. Le chemin est donc relatif à ce répertoire. Si le chemin est absolu, dir_fd est ignoré. (Pour les systèmes POSIX, Python appellera la version ...at ou f...at de la fonction.)

Vous pouvez vérifier si dir_fd est géré sur votre plate-forme en utilisant os.supports_dir_fd. Si c’est indisponible, l’utiliser lèvera une NotImplementedError.

Non-suivi des symlinks (liens symboliques) : si follow_symlinks vaut False et le dernier élément du chemin sur lequel opérer est un lien symbolique, la fonction opérera sur le lien symbolique et pas sur le fichier pointé par le lien. (Pour les systèmes POSIX, Python appellera la version l... de la fonction.)

Vous pouvez voir si follow_symlinks est géré sur votre plate-forme en utilisant os.supports_follow_symlinks. Si c’est indisponible, l’utiliser lèvera une NotImplementedError.

os.access(path, mode, *, dir_fd=None, effective_ids=False, follow_symlinks=True)

Utilise l”uid/gid réel pour tester l’accès à path. Notez que la plupart des opérations utiliseront l”uid/gid effectif, dès lors cette méthode peut être utilisée dans un environnement suid/sgid pour tester si l’utilisateur invoquant a les droits d’accès pour accéder à path. mode devrait être F_OK pour tester l’existence de path, ou il peut être le OR (OU inclusif) d’une ou plusieurs des constantes suivantes : R_OK, W_OK, et X_OK pour tester les permissions. Renvoie True si l’accès est permis, et False s’il ne l’est pas. Voir la page de manuel Unix access(2) pour plus d’informations.

Cette fonction peut gérer la spécification de chemins relatifs vers des descripteurs de fichiers et le suivi des liens symboliques.

Si effective_id vaut True, access() effectuera ses vérifications d’accès en utilisant l”uid/gid effectif à la place de l”uid/gid réel. effective_ids peut ne pas être géré sur votre plate-forme, vous pouvez vérifier s’il est disponible en utilisant os.supports_effective_ids. S’il est indisponible, l’utiliser lèvera une NotImplementedError.

Note

Utiliser access() pour vérifier si un utilisateur est autorisé (par exemple) à ouvrir un fichier avant d’effectivement le faire en utilisant open() crée une faille de sécurité : l’utilisateur peut exploiter le court intervalle de temps entre la vérification et l’ouverture du fichier pour le manipuler. Il est préférable d’utiliser les techniques EAFP. Par exemple :

if os.access("myfile", os.R_OK):
    with open("myfile") as fp:
        return fp.read()
return "some default data"

est mieux écrit comme suit :

try:
    fp = open("myfile")
except PermissionError:
    return "some default data"
else:
    with fp:
        return fp.read()

Note

Les opérations d’entrées/sorties peuvent échouer même quand access() indique qu’elles devraient réussir, particulièrement pour les opérations sur les systèmes de fichiers réseaux qui peuvent avoir une sémantique de permissions au-delà du modèle de bits de permission usuel POSIX.

Modifié dans la version 3.3: Paramètres dir_fd, effective_ids, et follow_symlinks ajoutés.

Modifié dans la version 3.6: Accepte un path-like object.

os.F_OK

os.R_OK

os.W_OK

os.X_OK

Valeurs à passer au paramètre mode de access() pour tester respectivement l’existence, les droits de lecture, d’écriture et d’exécution.

os.chdir(path)

Change le répertoire de travail actuel par path.

Cette fonction prend en charge la spécification d’un descripteur de fichier. Le descripteur doit référencer un répertoire ouvert, pas un fichier ouvert.

Nouveau dans la version 3.3: Prise en charge de la spécification de path par un descripteur de fichier sur certaines plate-formes.

Modifié dans la version 3.6: Accepte un path-like object.

os.chflags(path, flags, *, follow_symlinks=True)

Définit les marqueurs de path par la valeur numérique flags. flags peut prendre une combinaison (OU bit-à-bit) des valeurs suivantes (comme défini dans le module stat) :

stat.UF_NODUMP

stat.UF_IMMUTABLE

stat.UF_APPEND

stat.UF_OPAQUE

stat.UF_NOUNLINK

stat.UF_COMPRESSED

stat.UF_HIDDEN

stat.SF_ARCHIVED

stat.SF_IMMUTABLE

stat.SF_APPEND

stat.SF_NOUNLINK

stat.SF_SNAPSHOT

Cette fonction prend en charge le suivi des liens symboliques.

Disponibilité : Unix.

Nouveau dans la version 3.3: L’argument follow_symlinks.

Modifié dans la version 3.6: Accepte un path-like object.

os.chmod(path, mode, *, dir_fd=None, follow_symlinks=True)

Change le mode de path par la valeur numérique mode. mode peut prendre une des valeurs suivantes (comme défini dans le module stat) ou une combinaison (OU bit-à-bit) de ces valeurs :

stat.S_ISUID

stat.S_ISGID

stat.S_ENFMT

stat.S_ISVTX

stat.S_IREAD

stat.S_IWRITE

stat.S_IEXEC

stat.S_IRWXU

stat.S_IRUSR

stat.S_IWUSR

stat.S_IXUSR

stat.S_IRWXG

stat.S_IRGRP

stat.S_IWGRP

stat.S_IXGRP

stat.S_IRWXO

stat.S_IROTH

stat.S_IWOTH

stat.S_IXOTH

Cette fonction prend en charge la spécification d’un descripteur de fichier, les chemins relatifs à des descripteurs de répertoires, et le non-suivi des liens symboliques.

Note

Bien que Windows gère chmod(), vous ne pouvez y définir que le marqueur de lecture-seule du fichier (via les constantes stat.S_IWRITE et stat.S_IREAD ou une constante entière correspondante). Tous les autres bits sont ignorés.

Nouveau dans la version 3.3: Prise en charge de la spécification de path par un répertoire ouvert et des arguments dir_fd et follow_symlinks ajoutés.

Modifié dans la version 3.6: Accepte un path-like object.

os.chown(path, uid, gid, *, dir_fd=None, follow_symlinks=True)

Change l’identifiant du propriétaire et du groupe de path par les valeurs numériques uid et gid. Pour laisser l’un de ces identifiants inchangé, le définir à -1.

Cette fonction prend en charge la spécification d’un descripteur de fichier, les chemins relatifs à des descripteurs de répertoires, et le non-suivi des liens symboliques.

Voir shutil.chown() pour une fonction de plus haut-niveau qui accepte des noms en plus des identifiants numériques.

Disponibilité : Unix.

Nouveau dans la version 3.3: Prise en charge de la spécification de path par un descripteur de fichier ouvert et des arguments dir_fd et follow_symlinks ajoutés.

Modifié dans la version 3.6: Accepte un path-like object.

os.chroot(path)

Change le répertoire racine du processus actuel par path.

Disponibilité : Unix.

Modifié dans la version 3.6: Accepte un path-like object.

os.fchdir(fd)

Change le répertoire de travail actuel par le répertoire représenté par le descripteur de fichier fd. Le descripteur doit référencer un répertoire ouvert, pas un fichier ouvert. Depuis Python 3.3, c’est équivalent à os.chdir(fd).

Disponibilité : Unix.

os.getcwd()

Renvoie une chaîne de caractères représentant le répertoire de travail actuel.

os.getcwdb()

Renvoie une chaîne de bytes représentant le répertoire de travail actuel.

os.lchflags(path, flags)

Définit les marqueurs de path par la valeur numérique flags, comme chflags(), mais ne suit pas les liens symboliques. Depuis Python 3.3, c’est équivalent à os.chflags(path, flags, follow_symlinks=False).

Disponibilité : Unix.

Modifié dans la version 3.6: Accepte un path-like object.

os.lchmod(path, mode)

Change le mode de path par la valeur numérique mode. Si path est un lien symbolique, ça affecte le lien symbolique à la place de la cible. Voir la documentation pour les valeurs possibles de mode pour chmod(). Depuis Python 3.3, c’est équivalent à os.chmod(path, mode, follow_symlinks=False).

Disponibilité : Unix.

Modifié dans la version 3.6: Accepte un path-like object.

os.lchown(path, uid, gid)

Change les identifiants du propriétaire et du groupe de path par uid et gid. Cette fonction ne suivra pas les liens symboliques. Depuis Python 3.3, c’est équivalent à os.chown(path, uid, gid, follow_symlinks=False).

Disponibilité : Unix.

Modifié dans la version 3.6: Accepte un path-like object.

os.link(src, dst, *, src_dir_fd=None, dst_dir_fd=None, follow_symlinks=True)

Crée un lien matériel appelé dst pointant sur src.

Cette fonction prend en charge la spécification src_dir_fd et/ou dst_dir_fd pour préciser des chemins relatifs à des descripteurs de répertoires, et le non-suivi des liens symboliques.

Disponibilité : Unix, Windows.

Modifié dans la version 3.2: Prise en charge de Windows.

Nouveau dans la version 3.3: Arguments src_dir_fd, dst_dir_fd, et follow_symlinks ajoutés.

Modifié dans la version 3.6: Accepte un path-like object pour src et dst.

os.listdir(path='.')

Renvoie une liste contenant le nom des entrées dans le répertoire donné par path. La liste est dans un ordre arbitraire et n’inclut pas les entrées spéciales '.' et '..' même si elles sont présentes dans le répertoire.

path peut être un path-like object. Si path est de type bytes (directement ou indirectement à travers une interface PathLike), les noms de fichiers renvoyés seront aussi de type bytes ; dans toutes les autres circonstances, ils seront de type str.

Cette fonction peut également gérer la spécification de descripteurs de fichiers. Le descripteur doit référencer un répertoire.

Note

Pour encoder des noms de fichiers de type str en bytes, utilisez la fonction encode().

Voir aussi

La fonction scandir() renvoie les entrées du répertoire ainsi que leurs attributs , offrant une meilleure performance pour beaucoup de cas utilisés fréquemment.

Modifié dans la version 3.2: Le paramètre path est devenu optionnel.

Nouveau dans la version 3.3: Prise en charge de la spécification d’un descripteur de répertoire pour path ajouté.

Modifié dans la version 3.6: Accepte un path-like object.

os.lstat(path, *, dir_fd=None)

Effectue l’équivalent d’un appel système lstat() sur le chemin donné. Similaire à stat() mais ne suit pas les liens symboliques. Renvoie un objet de type stat_result.

Sur les plate-formes qui ne gérant pas les liens symboliques, c’est un alias pour stat().

Depuis Python 3.3, c’est équivalent à os.stat(path, dir_fd=dir_fd, follow_symlinks=False).

Cette fonction peut également gérer des chemins relatifs à des descripteurs de répertoires.

Voir aussi

La fonction stat().

Modifié dans la version 3.2: Prise en charge des les liens symboliques sur Windows 6.0 (Vista).

Modifié dans la version 3.3: Paramètre dir_fd ajouté.

Modifié dans la version 3.6: Accepte un path-like object pour src et dst.

os.mkdir(path, mode=0o777, *, dir_fd=None)

Crée un répertoire appelé path avec pour mode, la valeur numérique mode.

Si le répertoire existe déjà, FileExistsError est levée.

Sous certains systèmes, mode est ignoré. Quand il est utilisé, il lui est premièrement appliqué le masque courant umask. Si des bits autres que les 9 derniers sont activés (i.e. les 3 derniers chiffres de la représentation octale de mode), leur signification sera dépendante de la plate-forme. Sous certaines plate-formes, ils seront ignorés et vous devrez appeler explicitement chmod() pour les modifier.

Cette fonction peut également gérer des chemins relatifs à des descripteurs de répertoires.

Il est également possible de créer des répertoires temporaires, voir la fonction tempfile.mkdtemp() du module tempfile.

Nouveau dans la version 3.3: L’argument dir_fd.

Modifié dans la version 3.6: Accepte un path-like object.

os.makedirs(name, mode=0o777, exist_ok=False)

Fonction de création récursive de répertoires. Comme mkdir() mais crée tous les répertoires de niveau intermédiaire nécessaires pour contenir le répertoire « feuille ».

Le paramètre mode est passé à mkdir() ; voir la description de mkdir() pour comprendre comment cela est interprété.

Si exist_ok vaut False (valeur par défaut), une OSError est levée si le répertoire cible existe déjà.

Note

Un appel à makedirs() est confus si les éléments du chemin à créer contiennent pardir (par exemple, « .. » sur les systèmes UNIX).

Cette fonction gère les chemins UNC correctement.

Nouveau dans la version 3.2: Le paramètre exist_ok.

Modifié dans la version 3.4.1: Avant Python 3.4.1, si exist_ok valait True et le répertoire à créer existait, makedirs() aurait levé une erreur si mode n’était pas équivalent au mode du répertoire existant. Puisque ce comportement n’était pas possible ) implémenter de manière sécurisée, il a été retiré pour Python 3.4.1. Voir bpo-21082 [https://bugs.python.org/issue21082].

Modifié dans la version 3.6: Accepte un path-like object.

os.mkfifo(path, mode=0o666, *, dir_fd=None)

Crée un FIFO (First In, First Out, ou un tube (pipe en anglais) nommé) appelé path avec le mode numérique mode. La valeur actuelle de umask est d’abord masquée du mode.

Cette fonction peut également gérer des chemins relatifs à des descripteurs de répertoires.

Les FIFOs sont des tubes qui peuvent être accédés comme des fichiers normaux. Les FIFOs existent jusqu’à ce qu’ils soient retirés (par exemple, à l’aide de os.unlink()). Généralement, les FIFOs sont utilisé comme communication entre des processus de type « client » et « serveur » : le serveur ouvre le FIFO pour le lire, et le client l’ouvre pour écrire dedans. Notez que mkfifo() n’ouvre pas le FIFO — il crée juste un point de rendez-vous.

Disponibilité : Unix.

Nouveau dans la version 3.3: L’argument dir_fd.

Modifié dans la version 3.6: Accepte un path-like object.

os.mknod(path, mode=0o600, device=0, *, dir_fd=None)

Crée un nœud du système de fichiers (fichier, périphérique, fichier spécial, ou tuyau nommé) appelée path. mode spécifie à la fois les permissions à utiliser et le type de nœud à créer, en étant combiné (OR bit-à-bit) avec l’une des valeurs suivantes : stat.S_IFREG, stat.S_IFCHR, stat.S_IFBLK, et stat.S_IFIFO (ces constantes sont disponibles dans le module stat). Pour stat.S_IFCHR et stat.S_IFBLK, device définit le fichier spécial de périphérique tout juste créé (probablement en utilisant os.makedev()), sinon, cet argument est ignoré.

Cette fonction peut également gérer des chemins relatifs à des descripteurs de répertoires.

Disponibilité : Unix.

Nouveau dans la version 3.3: L’argument dir_fd.

Modifié dans la version 3.6: Accepte un path-like object.

os.major(device)

Extrait le nombre majeur de périphérique d’un nombre de périphérique brut (habituellement le champ st_dev ou st_rdev de stat).

os.minor(device)

Extrait le nombre mineur de périphérique d’un nombre de périphérique brut (habituellement le champ st_dev ou st_rdev de stat).

os.makedev(major, minor)

Compose un nombre de périphérique brut à partir des nombres de périphérique mineur et majeur.

os.pathconf(path, name)

Renvoie des informations sur la configurations relatives à un fichier déterminé. name spécifie la valeur de configuration à récupérer ; ce peut être une chaîne de caractères qui est le nom d’une valeur système particulière. Ces noms sont spécifiés dans certains standards (POSIX.1, Unix 95, Unix 98, etc). Certaines plate-formes définissent des noms supplémentaires également. Les noms connus du système d’exploitation hôte sont donnés dans le dictionnaire pathconf_names. Pour les variables de configuration non incluses dans ce mapping, passer un entier pour name est également accepté.

Si name est une chaîne de caractères et n’est pas connu, une ValueError est levée. Si une valeur spécifique de name n’est pas gérée par le système hôte, même si elle est incluse dans pathconf_names, une OSError est levée avec errno.EINVAL pour code d’erreur.

Cette fonction prend en charge la spécification d’un descripteur de fichier.

Disponibilité : Unix.

Modifié dans la version 3.6: Accepte un path-like object.

os.pathconf_names

Dictionnaire liant les noms acceptés par les fonctions pathconf() et fpathconf() aux valeurs entières définies pour ces noms par le système d’exploitation hôte. Cette variable peut être utilisée pour déterminer l’ensemble des noms connus du système d’exploitation.

Disponibilité : Unix.

os.readlink(path, *, dir_fd=None)

Renvoie une chaîne de caractères représentant le chemin vers lequel le lien symbolique pointe. Le résultat peut être soit un chemin relatif, soit un chemin absolu. S’il est relatif, il peut être converti en chemin absolu en utilisant os.path.join(os.path.dirname(path), result).

Si path est une chaîne de caractères (directement ou indirectement à travers une interface PathLike), le résultat sera aussi une chaîne de caractères, et l’appel pourra lever une UnicodeDecodeError. Si path est une chaîne d’octets (directement ou indirectement), le résultat sera une chaîne d’octets.

Cette fonction peut également gérer des chemins relatifs à des descripteurs de répertoires.

Disponibilité Unix, Windows

Modifié dans la version 3.2: Prise en charge des les liens symboliques sur Windows 6.0 (Vista).

Nouveau dans la version 3.3: L’argument dir_fd.

Modifié dans la version 3.6: Accepte un path-like object.

os.remove(path, *, dir_fd=None)

Supprime (retire) le fichier représenté par path. Si path est un répertoire, une OSError est levée. Utilisez la fonction rmdir() pour supprimer un répertoire.

Cette fonction prend en charge des chemins relatifs à des descripteurs de répertories.

Sur Windows, tenter de retirer un fichier en cours d’utilisation cause la levée d’une exception, sur Unix, l’entrée du répertoire est supprimé mais l’espace de stockage alloué au fichier ne sera pas disponible avant que le fichier original ne soit plus utilisé.

La fonction est sémantiquement identique à unlink().

Nouveau dans la version 3.3: L’argument dir_fd.

Modifié dans la version 3.6: Accepte un path-like object.

os.removedirs(name)

Supprime des répertoires récursivement. Fonctionne comme rmdir() si ce n’est que si le répertoire feuille est retiré avec succès, removedirs() essaye de supprimer successivement chaque répertoire parent mentionné dans path jusqu’à ce qu’un erreur ne soit levée (ce qui est ignoré car la signification générale en est qu’un répertoire parent n’est pas vide). Par exemple, os.removedirs('foo/bar/baz') supprimera d’abord le répertoire 'foo/bar/baz', et ensuite supprimera 'foo/bar' et puis 'foo' s’ils sont vides. Lève une OSError si le répertoire feuille n’a pas pu être supprimé avec succès.

Modifié dans la version 3.6: Accepte un path-like object.

os.rename(src, dst, *, src_dir_fd=None, dst_dir_fd=None)

Renomme le fichier ou le répertoire src en dst. Si dst est un répertoire, une OSError est levée. Sur Unix, si dst existe, il sera remplacé silencieusement si l’utilisateur en a la permission. L’opération peut échouer sur certaines distributions Unix si src et dst sont sur des systèmes de fichiers séparés. Si le renommage est effectué avec succès, il est une opération atomique (nécessité POSIX). Sur Window, si dst existe déjà, une OSError est levée même s’il est un fichier.

Cette fonction prend en charge les spécifications src_dir_fd et/ou dst_dir_fd pour fournir des chemins relatifs à des descripteurs de fichiers.

Si cous désirez un écrasement multiplate-forme de la destination, utilisez la fonction replace().

Nouveau dans la version 3.3: Les arguments src_dir_fd et dst_dir_fd.

Modifié dans la version 3.6: Accepte un path-like object pour src et dst.

os.renames(old, new)

Fonction récursive de renommage de fichiers ou répertoires. Fonctionne comme rename(), si ce n’est que la création d’un répertoire intermédiaire nécessaire pour rendre le nouveau chemin correct est essayé en premier. Après le renommage, les répertoires correspondant aux segments de chemin les plus à droite de l’ancien nom seront élagués en utilisant removedirs().

Note

Cette fonction peut échouer avec la nouvelle structure de dictionnaire définie si vous n’avez pas les permissions nécessaires pour supprimer le répertoire ou fichier feuille.

Modifié dans la version 3.6: Accepte un path-like object pour old et new.

os.replace(src, dst, *, src_dir_fd=None, dst_dir_fd=None)

Renomme le fichier ou le répertoire src en dst. Si dst est un répertoire, une OSError est levée. Si dst existe et est un fichier, il sera remplacé silencieusement si l’utilisateur en a les permissions. L’opération peut échouer si src et dst sont sur un système de fichiers différent. Si le renommage est effectué avec succès, il est une opération atomique (nécessité POSIX).

Cette fonction prend en charge les spécifications src_dir_fd et/ou dst_dir_fd pour fournir des chemins relatifs à des descripteurs de fichiers.

Nouveau dans la version 3.3.

Modifié dans la version 3.6: Accepte un path-like object pour src et dst.

os.rmdir(path, *, dir_fd=None)

Supprime (retire) le répertoire path. Ne fonctionne que lorsque le répertoire est vide, sinon une OSError est levée. Afin de supprimer toute la hiérarchie de dossier, la fonction shutil.rmtree() peut être utilisée.

Cette fonction prend en charge des chemins relatifs à des descripteurs de répertories.

Nouveau dans la version 3.3: Le paramètre dir_fd.

Modifié dans la version 3.6: Accepte un path-like object.

os.scandir(path='.')

Renvoie un itérateur d’objets os.DirEntry correspondant aux entrées dans le répertoire indiqué par path. Les entrées sont produites dans un ordre arbitraire, et les entrées spéciales '.' et '..' ne sont pas incluses.

Utiliser scandir() plutôt que listdir() peut significativement améliorer les performances des codes qui nécessitent aussi l’accès aux types des fichiers ou à leurs attributs, puisque les objets os.DirEntry exposent ces informations si le système d’exploitation les fournit en scannant le répertoire. Toutes les méthodes de os.DirEntry peuvent réaliser un appel système, mais is_dir() et is_file() n’en requièrent normalement un que pour les liens symboliques ; os.DirEntry.stat() nécessite toujours un appel système sous Unix, mais seulement pour les liens symboliques sous Windows.

path peut être un path-like object. Si path est de type bytes (directement ou indirectement à travers une interface PathLike), le type des attributs name et path de chaque os.DirEntry sera bytes ; dans toutes les autres circonstances, ils seront de type str.

L’itérateur scandir() gère le protocole context manager et possède la méthode suivante :

scandir.close()

Ferme l’itérateur et libère les ressources acquises.

Elle est appelée automatiquement quand l’itérateur est entièrement consommé ou collecté par le ramasse-miettes, ou quand une erreur survient durant l’itération. Il est cependant conseillé de l’appeler explicitement ou d’utiliser l’instruction with.

Nouveau dans la version 3.6.

L’exemple suivant montre une utilisation simple de scandir() pour afficher tous les fichiers (à part les répertoires) dans le chemin donné par path et ne débutant pas par '.'. L’appel entry.is_file() ne va généralement pas faire d’appel système supplémentaire :

with os.scandir(path) as it:
    for entry in it:
        if not entry.name.startswith('.') and entry.is_file():
            print(entry.name)

Note

Sur les systèmes inspirés de Unix, scandir() utilise les fonctions système opendir() [http://pubs.opengroup.org/onlinepubs/009695399/functions/opendir.html] et readdir() [http://pubs.opengroup.org/onlinepubs/009695399/functions/readdir_r.html] Sur Windows, la fonction utilise les fonctions Win32 FindFirstFileW [https://msdn.microsoft.com/en-us/library/windows/desktop/aa364418(v=vs.85).aspx] et FindNextFileW [https://msdn.microsoft.com/en-us/library/windows/desktop/aa364428(v=vs.85).aspx].

Nouveau dans la version 3.5.

Nouveau dans la version 3.6: Prise en charge du protocole context manager et de la méthode close(). Si un itérateur sur scandir() n’est ni entièrement consommé ni explicitement fermé, un ResourceWarning sera émis dans son destructeur.

La fonction accepte un path-like object.

class os.DirEntry

Objet donné par scandir() pour exposer le chemin du fichier et d’autres attributs de fichier d’une entrée du répertoire.

scandir() fournira autant d’informations que possible sans faire d’appels système additionnels. Quand un appel système stat() ou lstat() est réalisé, l’objet os.DirEntry mettra le résultat en cache.

Les instances os.DirEntry ne sont pas censées être stockées dans des structures de données à longue durée de vie ; si vous savez que les métadonnées du fichier ont changé ou si un certain temps s’est écoulé depuis l’appel à scandir(), appelez os.stat(entry.path) pour mettre à jour ces informations.

Puisque les méthodes de os.DirEntry peuvent réaliser des appels système, elles peuvent aussi lever des OSError. Si vous avez besoin d’un contrôle fin des erreurs, vous pouvez attraper les OSError en appelant les méthodes de os.DirEntry et les traiter comme il vous semble.

Pour être directement utilisable comme un path-like object, os.DirEntry implémente l’interface PathLike.

Les attributs et méthodes des instances de os.DirEntry sont les suivants :

name

Le nom de fichier de base de l’entrée, relatif à l’argument path de scandir().

L’attribut name sera de type bytes si l’argument path de scandir() est de type bytes, sinon il sera de type str. Utilisez fsdecode() pour décoder des noms de fichiers de types byte.

path

Le nom entier de l’entrée : équivalent à os.path.join(scandir_path, entry.name) où scandir_path est l’argument path de scandir(). Le chemin est absolu uniquement si l’argument path de scandir() était absolu.

L’attribut path sera de type bytes si l’argument path de la fonction scandir() est de type bytes, sinon il sera de type str. Utilisez fsdecode() pour décoder des noms de fichiers de type bytes.

inode()

Renvoie le numéro d”inode de l’entrée.

Le résultat est mis en cache dans l’objet os.DirEntry. Utilisez os.stat(entry.path, follow_symlinks=False).st_ino pour obtenir l’information à jour.

Au premier appel non mis en cache, un appel système est requis sur Windows, mais pas sur Unix.

is_dir(*, follow_symlinks=True)

Renvoie True si cette entrée est un répertoire ou un lien symbolique pointant vers un répertoire ; renvoie False si l’entrée est (ou pointe vers) un autre type de fichier, ou s’il n’existe plus.

Si follow_symlinks vaut False, renvoie True uniquement si l’entrée est un répertoire (sans suivre les liens symboliques) ; renvoie False si l’entrée est n’importe quel autre type de fichier ou s’il n’existe plus.

Le résultat est mis en cache dans l’objet os.DirEntry, avec un cache séparé pour les valeurs True ou False de follow_symlinks. Appelez os.stat() avec stat.S_ISDIR() pour obtenir l’information à jour.

Au premier appel non mis en cache, aucun appel système n’est requis dans la plupart du temps. Spécifiquement, sans les liens symboliques, ni Windows, ni Unix ne requiert l’appel système, sauf sur certains systèmes de fichiers sur Unix, comme les système de fichiers de réseau qui renvoient dirent.d_type == DT_UNKNOWN. Si l’entrée est un lien symbolique, un appel système sera requis pour suivre le lien symbolique, à moins que follow_symlinks vaille False.

Cette méthode peut lever une OSError tout comme une PermissionError, mais FileNotFoundError est attrapé et pas levé.

is_file(*, follow_symlinks=True)

Renvoie True si l’entrée est un fichier ou un lien symbolique pointant vers un fichier, renvoie False si l’entrée pointe est (ou pointe sur) sur un dossier ou sur un répertoire ou autre entrée non-fichier, ou s’il n’existe plus.

Si follow_symlinks vaut False, renvoie True uniquement si cette entrée est un fichier (sans suivre les liens symboliques). Renvoie False si l’entrée est un répertoire ou une autre entrée non-fichier, ou s’il n’existe plus.

Le résultat est mis en cache dans l’objet os.DirEntry. La mise en cache, les appels système réalisés, et les exceptions levées sont les mêmes que pour is_dir().

is_symlink()

Renvoie True si l’entrée est un lien symbolique (même cassé). Renvoie False si l’entrée pinte vers un répertoire ou tout autre type de fichier, ou s’il n’existe plus.

Le résultat est mis en cache dans l’objet os.DirEntry. Appelez os.path.islink() pour obtenir l’information à jour.

Au premier appel non mis en cache, aucun appel système n’est requis. Spécifiquement, ni Windows ni Unix ne requiert d’appel système, excepté sur certains systèmes de fichiers Unix qui renvoient dirent.d_type == DT_UNKNOWN.

Cette méthode peut lever une OSError tout comme une PermissionError, mais FileNotFoundError est attrapé et pas levé.

stat(*, follow_symlinks=True)

Renvoie un objet de type stat.result pour cette entrée. Cette méthode suit les liens symboliques par défaut. Pour avoir les statistiques sur un lien symbolique, ajouter l’argument follow_symlinks=False.

Sur Unix, cette méthode requiert toujours un appel système. Sur Windows, cela requiert uniquement un appel système si follow_symlinks vaut True et l’entrée n’est pas un lien symbolique.

Sur Windows, les attributs st_ino, st_dev et st_nlink de la classe stat_result sont toujours définis à 0. Appelez la fonction os.stat() pour avoir ces attributs.

Le résultat est mis en cache dans l’objet os.DirEntry, avec un cache séparé pour les valeurs True ou False de follow_symlinks. Appelez os.stat() pour obtenir l’information à jour.

Notez qu’il y a une correspondance entre différents attributs et méthodes de os.DirEntry et pathlib.Path. En particulier, l’attribut name a la même signification, ainsi que les méthodes is_dir(), is_file(), is_symlink() et stat().

Nouveau dans la version 3.5.

Modifié dans la version 3.6: Prise en charge de l’interface PathLike. Ajout du support des chemins bytes sous Windows.

os.stat(path, *, dir_fd=None, follow_symlinks=True)

Récupère le statut d’un fichier ou d’un descripteur de fichier. Réalise l’équivalent d’un appel système stat() sur le chemin donné. path peut être exprimé comme une chaîne de caractères ou d’octets – directement ou indirectement à travers une interface PathLike – ou comme un descripteur de fichier ouvert. Renvoie un objet stat_result.

Cette fonction suit normalement les liens symboliques. Pour récupérer les informations d’un lien symbolique, ajoutez l’argument follow_symlinks=False ou utilisez la fonction lstat().

Cette fonction peut supporter la spécification d’un descripteur de fichier et le non-suivi des liens symboliques.

Exemple :

>>> import os
>>> statinfo = os.stat('somefile.txt')
>>> statinfo
os.stat_result(st_mode=33188, st_ino=7876932, st_dev=234881026,
st_nlink=1, st_uid=501, st_gid=501, st_size=264, st_atime=1297230295,
st_mtime=1297230027, st_ctime=1297230027)
>>> statinfo.st_size
264

Voir aussi

les fonctions fstat() et lstat().

Nouveau dans la version 3.3: Les arguments dir_fd et follow_symlinks ont été ajoutés, spécification d’un descripteur de fichier à la place d’un chemin ajoutée également.

Modifié dans la version 3.6: Accepte un path-like object.

class os.stat_result

Objet dont les attributs correspondent globalement aux membres de la structure stat(). Utilisé pour le résultat des fonctions os.stat(), os.fstat(), et os.lstat().

Attributs :

st_mode

Mode du fichier : type du fichier et bits de mode du fichier (permissions).

st_ino

Dépendant de la plateforme, mais lorsqu’il ne vaut pas zéro il identifie de manière unique le fichier pour une certaine valeur de st_dev. Typiquement :

le numéro d”inode sur Unix,

l’index de fichier [https://msdn.microsoft.com/fr-fr/library/aa363788] sur Windows

st_dev

Identifiant du périphérique sur lequel ce fichier se trouve.

st_nlink

Nombre de liens matériels.

st_uid

Identifiant d’utilisateur du propriétaire du fichier.

st_gid

Identifiant de groupe du propriétaire du fichier.

st_size

Taille du fichier en bytes si c’est un fichier normal ou un lien symbolique. La taille d’un lien symbolique est la longueur du nom de chemin qu’il contient sans le byte nul final.

Horodatages :

st_atime

Moment de l’accès le plus récent, exprimé en secondes.

st_mtime

Moment de la modification de contenu la plus récente, exprimé en secondes.

st_ctime

Dépendant de la plate-forme :

le moment du changement de méta-données le plus récent sur Unix,

le moment de création sur Windows, exprimé en secondes.

st_atime_ns

Moment de l’accès le plus récent, exprimé en nanosecondes, par un entier.

st_mtime_ns

Moment de la modification de contenu la plus récente, exprimé en nanosecondes, par un entier.

st_ctime_ns

Dépendant de la plate-forme :

le moment du changement de méta-données le plus récent sur Unix,

le moment de création sur Windows, exprimé en nanosecondes, par un entier.

Voir aussi la fonction stat_float_times().

Note

La signification et la précision exacte des attributs st_atime, st_mtime, et st_ctime dépendent du système d’exploitation et du système de fichier. Par exemple sur les systèmes Windows qui utilisent un système de fichier FAT ou FAT32, st_mtime a une précision de 2 secondes, et st_atime a une précision de 1 jour. Regardez la documentation de votre système d’exploitation pour plus de détails.

De manière similaire, bien que st_atime_ns, st_mtime_ns, et st_ctime_ns soient toujours exprimés en nanosecondes, beaucoup de systèmes ne fournissent pas une précision à la nanoseconde près.Sur les systèmes qui fournissent une telle précision, l’objet à virgule flottante utilisé pour stocker st_atime, st_mtime, et st_ctime ne peut pas le contenir en entier, et donc sera légèrement inexact. Si vous avez besoin d’horodatages exacts, vous devriez toujours utiliser st_atime_ns, st_mtime_ns, et st_ctime_ns.

Sur certains systèmes Unix (tels que Linux), les attributs suivants peuvent également être disponibles :

st_blocks

Nombre de blocs de 512 bytes alloués pour le fichier. Cette valeur peut être inférieure à st_size/512 quand le fichier a des trous.

st_blksize

Taille de bloc « préférée » pour des E/S efficaces avec le système de fichiers. Écrire dans un fichier avec des blocs plus petits peut causer des modifications (lecture-écriture-réécriture) inefficaces.

st_rdev

Type de périphérique si l”inode représente un périphérique.

st_flags

Marqueurs définis par l’utilisateur pour le fichier.

Sur d’autres systèmes Unix (tels que FreeBSD), les attributs suivants peuvent être disponibles (mais peuvent être complétés uniquement lorsque le super-utilisateur root tente de les utiliser) :

st_gen

Nombre de génération de fichier.

st_birthtime

Moment de la création du fichier.

Sur les systèmes Mac OS, les attributs suivants peuvent également être disponibles :

st_rsize

Taillé réelle du fichier.

st_creator

Créateur du fichier.

st_type

Type du fichier.

Sur les systèmes Windows, les attributs suivants sont également disponibles :

st_file_attributes

Attributs de fichiers Windows : membre dwFileAttributes de la structure BY_HANDLE_FILE_INFORMATION renvoyée par GetileInformationByHandle(). Soir les constantes FILE_ATTRIBUTE_* du module stat.

Le module standard stat définit des fonctions et des constantes qui sont utiles pour l’extraction d’informations d’une structure stat. (Sur Windows, certains éléments sont remplis avec des valeurs factices.)

Pour des raisons de rétro-compatibilité, une instance du stat_result est également accessible comme un tuple d’au moins 10 valeurs entières donnant les membres les plus importants (et portables) de la structure stat, dans l’ordre : st_mode, st_ino, st_dev, st_nlink, st_uid, st_gid, st_size, st_atime, st_mtime, st_ctime. Plus d’éléments peuvent être ajoutés à la fin par certaines implémentations. Pour une compatibilité avec les anciennes versions de Python, accéder à un élément de type stat_result comme un tuple donne toujours des entiers.

Nouveau dans la version 3.3: Les attributs st_atime_ns, st_mtime_ns, et st_ctime_ns ont été ajoutés.

Nouveau dans la version 3.5: L’attribut st_file_attributes a été ajouté sur Windows.

Modifié dans la version 3.5: Windows renvoie maintenant l’index du fichier dans l’attribut st_ino, lorsqu’il est disponible.

os.stat_float_times([newvalue])

Détermine si stat_result représente les horodatages par des objets à virgule flottante. Si newvalue vaut True, les appels à stat() qui suivront renvoieront des flottants. Si newvalue vaut False, les appels qui suivront renverront des entiers. Si newvalue est omise, la valeur actuelle est renvoyée.

Pour des raisons de compatibilité avec les anciennes versions de Python, accéder un objet de type stat_result renvoie toujours des entiers.

Python renvoie des valeurs flottantes par défaut maintenant. Les applications qui ne fonctionnent pas correctement avec des horodatages flottants peuvent utiliser cette fonction pour restaurer l’ancien comportement.

La précision des horodatages (qui est la plus petite fraction possible) dépend du système. Certains systèmes supportent uniquement une précision à la seconde ; sur ces systèmes, la fraction sera toujours zéro.

Il est recommandé que cette option ne soit changée qu’au lancement du programme dans le module __main__. Les bibliothèques ne devraient jamais changer cette option. Si une application utilise une bibliothèque qui fonctionne mal avec les horodatages en nombres flottants, cette application devrait temporairement retirer cette possibilité jusqu’à ce que la bibliothèque ait été corrigée.

Obsolète depuis la version 3.3.

os.statvfs(path)

Exécute un appel système statvfs() sur le chemin donné par path. La valeur de retour est un objet dont les attributs décrivent le système de fichier sur le chemin donné, et correspondent auxmembres de la structure statvfs nommés : f_bsize, f_frsize, f_blocks, f_bfree, f_bavail, f_files, f_ffree, f_favail, f_flag, f_namemax.

Deux constantes de module sont définies pour le champ-de-bits de l’attribut f_flag : si SR_RDONLY est activé, le système de fichiers est monté en lecture-seule, et si ST_NOSUID est activé, la sémantique des bits de setuid / getuid est désactivée ou non gérée.

Des constantes de module supplémentaires sont définies pour les systèmes basés sur GNU/glibc. Ces constantes sont ST_NODEV (interdit l’accès aux fichiers spéciaux du périphérique), ST_NOEXEC (interdit l’exécution de programmes), ST_SYNCHRONOUS (les écritures sont synchronisées en une fois), ST_MANDLOCK (permet les verrous impératifs sur un système de fichiers), ST_WRITE (écrit sur les fichiers/répertoires/liens symboliques), ST_APPEND (fichiers en ajout-seul), ST_IMMUTABLE (fichiers immuables), ST_NOATIME (ne met pas à jour les moments d’accès), ST_NODIRATIME (ne met pas à jour les moments d’accès aux répertoires), ST_REALTIME (Met atime à jour relativement à mtime / ctime).

Cette fonction prend en charge la spécification d’un descripteur de fichier.

Disponibilité : Unix.

Modifié dans la version 3.2: Ajout des constantes ST_RDONLY et ST_NOSUID.

Nouveau dans la version 3.3: Prise en charge de la spécification d’un descripteur de répertoire pour path ajouté.

Modifié dans la version 3.4: Ajout des constantes ST_NODEV, ST_NOEXEC, ST_SYNCHRONOUS, ST_MANDLOCK, ST_WRITE, ST_APPEND, ST_IMMUTABLE, ST_NOATIME, ST_NODIRATIME, et ST_RELATIME.

Modifié dans la version 3.6: Accepte un path-like object.

os.supports_dir_fd

Un objet de type Set indiquant quels fonctions du module os permettent l’utilisation du paramètre dir_fd. Des plate-formes différentes fournissent des fonctionnalités différentes, et une option qui peut fonctionner sur l’une peut ne pas être gérée sur une autre. Pour des raisons de cohérence, les fonctions qui gèrent dir_fd permettent toujours de spécifier le paramètre, mais lèvent une exception si la fonctionnalité n’est pas réellement accessible.

Pour vérifier si une fonction en particulier permet de l’utilisation de son paramètre dir_fd, utilisez l’opérateur in sur supports_dir_fd. Par exemple, l’expression détermine si le paramètre dir_fd de la fonction os.stat() est disponible :

os.stat in os.supports_dir_fd

Actuellement, le paramètre dir_fd ne fonctionne que sur les plate-formes Unix. Il ne fonctionne jamais sur Windows.

Nouveau dans la version 3.3.

os.supports_effective_ids

Un objet de type collections.abc.Set indiquant quelles fonction du module ps permettent l’utilisation du paramètre effective_ids pour os.access(). Si la plate-forme le gère, la collection contiendra os.access(), sinon elle sera vide.

Pour vérifier si vous pouvez utiliser le paramètre effective_ids pour os.access(), utilisez l’opérateur in sur supports_effective_ids, comme tel :

os.access in os.supports_effective_ids

Actuellement, effective_ids ne fonctionne que sur les plate-formes Unix, ça ne fonctionne pas sur Windows.

Nouveau dans la version 3.3.

os.supports_fd

Un objet de type Set indiquant quelles fonctions du module os permettent de spécifier le paramètre de chemin path par un descripteur de fichier ouvert. Différentes plate-formes fournissent différentes fonctionnalités, et une option qui peut fonctionner sur l’une peut ne pas être gérée sur une autre. Pour des raisons de cohérence, les fonctions qui gèrent fd permettent toujours de spécifier le paramètre, mais elles lèveront une exception si la fonctionnalité n’est pas réellement disponible.

Pour vérifier si une fonction en particulier permet de spécifier un descripteur de fichier ouvert pour son paramètre path, utilisez l’opérateur in sur supports_fd. Par exemple, cette expression détermine si os.chdir() accepte un descripteur de fichier ouvert quand appelée sur votre plate-forme actuelle :

os.chdir in os.supports_fd

Nouveau dans la version 3.3.

os.supports_follow_symlinks

Un objet de type collections.abc.Set indiquant quelles fonctions du module os permettent d’utiliser leur paramètre follow_symlinks. Différentes plate-formes fournissent des fonctionnalités différentes, et une option qui fonctionne sur l’une peut ne pas fonctionner sur une autre. Pour des raisons de cohérence, les fonctions qui gèrent follow_symlinks permettent toujours de spécifier le paramètre, mais lèvent une exception si la fonctionnalité n’est pas réellement disponible.

Pour vérifier s une fonction en particulier permet l’utilisation du paramètre follow_symlinks, utilisez l’opérateur in sur supports_follow_symlinks. Par exemple, cette expression détermine si le paramètre follow_symlink de os.stat() est disponible :

os.stat in os.supports_follow_symlinks

Nouveau dans la version 3.3.

os.symlink(src, dst, target_is_directory=False, *, dir_fd=None)

Crée un lien symbolique pointant vers src et appelé dst.

On Windows, a symlink represents either a file or a directory, and does not morph to the target dynamically. If the target is present, the type of the symlink will be created to match. Otherwise, the symlink will be created as a directory if target_is_directory is True or a file symlink (the default) otherwise. On non-Windows platforms, target_is_directory is ignored.

Introduction de la prise en charge des liens symboliques dans Windows 6.0 (Vista). symlink() lèvera une exception NotImplementedError sur les versions de Windows inférieures à 6.0.

Cette fonction prend en charge des chemins relatifs à des descripteurs de répertories.

Note

Sur Windows, le SeCreateSymbolicLinkPrivilege est requis pour créer des liens symboliques avec succès. Ce privilège n’est pas typiquement garanti aux utilisateurs réguliers mais est disponible aux comptes qui peuvent escalader les privilèges jusqu’au niveau administrateur. Tant obtenir le privilège que lancer votre application en administrateur sont des moyens de créer des liens symboliques avec succès.

OSError est levée quand la fonction est appelée par un utilisateur sans privilèges.

Disponibilité : Unix, Windows.

Modifié dans la version 3.2: Prise en charge des les liens symboliques sur Windows 6.0 (Vista).

Nouveau dans la version 3.3: Ajout de l’argument dir_fd et maintenant, permission de target_is_directory sur les plate-formes non Windows.

Modifié dans la version 3.6: Accepte un path-like object pour src et dst.

os.sync()

Force l’écriture de tout sur le disque.

Disponibilité : Unix.

Nouveau dans la version 3.3.

os.truncate(path, length)

Tronque le fichier correspondant à path, afin qu’il soit au maximum long de length bytes.

Cette fonction prend en charge la spécification d’un descripteur de fichier.

Disponibilité : Unix, Windows.

Nouveau dans la version 3.3.

Modifié dans la version 3.5: Prise en charge de Windows

Modifié dans la version 3.6: Accepte un path-like object.

os.unlink(path, *, dir_fd=None)

Supprime (retire) le fichier path. Cette fonction est sémantiquement identique à remove(). Le nom unlink est un nom Unix traditionnel. Veuillez voir la documentation de remove() pour plus d’informations.

Nouveau dans la version 3.3: Le paramètre dir_fd.

Modifié dans la version 3.6: Accepte un path-like object.

os.utime(path, times=None, *, [ns, ]dir_fd=None, follow_symlinks=True)

Voir les derniers moments d’accès et de modification du fichier spécifiés par path.

La fonction utime() prend deux paramètres optionnels, times et ns. Ils spécifient le temps mis pour path et est utilisé comme suit :

Si ns est spécifié, ce doit être un couple de la forme (atime_ns, mtime_ns) où chaque membre est un entier qui exprime des nanosecondes.

Si times ne vaut pas None, ce doit être un couple de la forme (atime, mtime) où chaque membre est un entier ou une expression à virgule flottante.

Si times vaut None, et ns est non-spécifié. C’est équivalent à spécifier ns = (atime_ns, mtime_ns) où les deux moments sont le moment actuel.

Il est erroné de spécifier des tuples pour times et ns à la fois.

Le fait qu’un répertoire puisse être donné pour path dépend du fait que le système d’exploitation implémente les répertoires comme des fichiers (par exemple, Windows ne le fait pas). Notez que l’instant exact que vous définissez ici peut ne pas être renvoyé lors d’un futur appel à stat(), selon la précision avec laquelle votre système d’exploitation mémorise les moments d’accès et de modification ; voir stat(). Le meilleur moyen de préserver des moments exacts est d’utiliser les champs st_atime_ns et st_mtime_ns de l’objet résultat de la fonction os.stat() avec le paramètre ns valant utime.

Cette fonction prend en charge la spécification d’un descripteur de fichier, les chemins relatifs à des descripteurs de répertoires, et le non-suivi des liens symboliques.

Nouveau dans la version 3.3: Prise en charge de la spécification d’un descripteur de fichier pour path et les paramètres dir_fd, follow_symlinks, et ns ajoutés.

Modifié dans la version 3.6: Accepte un path-like object.

os.walk(top, topdown=True, onerror=None, followlinks=False)

Génère les noms de fichier dans un arbre de répertoire en parcourant l’arbre soit de bas-en-haut, soit de haut-en-bas. Pour chaque répertoire dans l’arbre enraciné en le répertoire rop (incluant ledit répertoire top), fournit un triplet (dirpath, dirnames, filenames).

dirpath est une chaîne de caractères contenant le chemin vers le répertoire. dirnames est une liste de noms de sous-répertoires dans dirpath (en excluant '.' et '..'). filenames est une liste de fichiers (non-répertoires) dans dirpath. Notez que les noms dans la liste ne contiennent aucune composante de chemin. Pour récupérer le chemin complet (qui commence à top) vers un répertoire dans dirpath, faites os.path.join(dirpath, name).

Si l’argument optionnel topdown vaut True ou n’est pas spécifié, le triplet pour un répertoire est généré avant les triplets de tous ses sous-répertoires (les répertoires sont générés de haut-en-bas). Si topdown vaut False, le triplet pour un répertoire est généré après les triplets de tous ses sous-répertoires (les répertoires sont générés de bas-en-haut). Peu importe la valeur de topdown, la liste des sous-répertoires est récupérée avant que les tuples pour le répertoires et ses sous-répertoires ne soient générés.

Quand topdown vaut True, l’appelant peut modifier la liste dirnames en place (par exemple en utilisant del ou l’assignation par slicing (par tranches)) et walk() ne fera sa récursion que dans les sous-répertoires dont le nom reste dans dirnames ; cela peut être utilisé pour élaguer la recherche, imposer un ordre particulier de visite, ou encore pour informer walk() des répertoires créés par l’appelant ou renommés avant qu’il quitte walk() à nouveau. Modifier dirnames quand topdown vaut False n’a aucun effet dur le comportement du parcours parce qu’en mode bas-en-haut, les répertoires dans dirnames sont générés avant que dirpath ne soit lui-même généré.

Par défaut, les erreurs d’un appel à scandir() sont ignorées. Si l’argument optionnel onerror est spécifié, il doit être une fonction qui sera appelée avec un seul argument, une instance de OSError. Elle peut rapporter l’erreur et continuer le parcours, ou lever l’exception pour avorter le parcours. Notez que le nom de fichier est disponible dans l’attribut filename de l’objet exception.

Par défaut, walk() ne parcourra pas les liens symboliques qui mènent à un répertoire. Définissez followlinks avec True pour visiter les répertoires pointés par des liens symboliques sur les systèmes qui le gère.

Note

Soyez au courant que définir followlinks avec True peut mener à une récursion infinie si un lien pointe vers un répertoire parent de lui-même. walk() ne garde pas de trace des répertoires qu’il a déjà visité.

Note

Si vous passez un chemin relatif, ne changer pas le répertoire de travail actuel entre deux exécutions de walk(). walk() ne change jamais le répertoire actuel, et suppose que l’appelant ne le fait pas non plus.

Cet exemple affiche le nombre de bytes pris par des fichiers non-répertoires dans chaque répertoire à partir du répertoire de départ, si ce n’est qu’il ne cherche pas après un sous-répertoire CSV :

import os
from os.path import join, getsize
for root, dirs, files in os.walk('python/Lib/email'):
    print(root, "consumes", end=" ")
    print(sum(getsize(join(root, name)) for name in files), end=" ")
    print("bytes in", len(files), "non-directory files")
    if 'CVS' in dirs:
        dirs.remove('CVS')  # don't visit CVS directories

Dans l’exemple suivant (simple implémentation d’un shutil.rmtree()), parcourir l’arbre de bas-en-haut est essentiel : rmdir() ne permet pas de supprimer un répertoire avant qu’un ne soit vide :

# Delete everything reachable from the directory named in "top",
# assuming there are no symbolic links.
# CAUTION:  This is dangerous!  For example, if top == '/', it
# could delete all your disk files.
import os
for root, dirs, files in os.walk(top, topdown=False):
    for name in files:
        os.remove(os.path.join(root, name))
    for name in dirs:
        os.rmdir(os.path.join(root, name))

Modifié dans la version 3.5: Cette fonction appelle maintenant os.scandir() au lieu de os.listdir(), ce qui la rend plus rapide en réduisant le nombre d’appels à os.stat().

Modifié dans la version 3.6: Accepte un path-like object.

os.fwalk(top='.', topdown=True, onerror=None, *, follow_symlinks=False, dir_fd=None)

Se comporte exactement comme walk(), si ce n’est qu’il fournit un quadruplet (dirpath, dirnames, filenames, dirfd), et gère dir_fd.

dirpath, dirnames et filenames sont identiques à la sortie de walk() et dirfd est un descripteur de fichier faisant référence au répertoire dirpath.

Cette fonction prend toujours en charge les chemins relatifs à des descripteurs de fichiers et le non-suivi des liens symboliques. Notez cependant qu’à l’inverse des autres fonctions, la valeur par défaut de follow_symlinks pour walk() est False.

Note

Puisque fwalk() fournit des descripteurs de fichiers, ils ne sont valides que jusque la prochaine itération. Donc vous devriez les dupliquer (par exemple avec dup()) si vous désirez les garder plus longtemps.

Cet exemple affiche le nombre de bytes pris par des fichiers non-répertoires dans chaque répertoire à partir du répertoire de départ, si ce n’est qu’il ne cherche pas après un sous-répertoire CSV :

import os
for root, dirs, files, rootfd in os.fwalk('python/Lib/email'):
    print(root, "consumes", end="")
    print(sum([os.stat(name, dir_fd=rootfd).st_size for name in files]),
          end="")
    print("bytes in", len(files), "non-directory files")
    if 'CVS' in dirs:
        dirs.remove('CVS')  # don't visit CVS directories

Dans le prochain exemple, parcourir l’arbre de bas-en-haut est essentiel : rmdir() ne permet pas de supprimer un répertoire avant qu’il ne soit vide :

# Delete everything reachable from the directory named in "top",
# assuming there are no symbolic links.
# CAUTION:  This is dangerous!  For example, if top == '/', it
# could delete all your disk files.
import os
for root, dirs, files, rootfd in os.fwalk(top, topdown=False):
    for name in files:
        os.unlink(name, dir_fd=rootfd)
    for name in dirs:
        os.rmdir(name, dir_fd=rootfd)

Disponibilité : Unix.

Nouveau dans la version 3.3.

Modifié dans la version 3.6: Accepte un path-like object.

16.1.5.1. Attributs étendus pour Linux

Nouveau dans la version 3.3.

Toutes ces fonctions ne sont disponibles que sur Linux.

os.getxattr(path, attribute, *, follow_symlinks=True)

Renvoie la valeur de l’attribut étendu attribute du système de fichiers pour le chemin path. attribute peut être une chaîne de caractères ou d’octets (directement ou indirectement à travers une interface PathLike). Si c’est une chaîne de caractères, elle est encodée avec l’encodage du système de fichiers.

Cette fonction peut supporter la spécification d’un descripteur de fichier et le non-suivi des liens symboliques.

Modifié dans la version 3.6: Accepte un path-like object pour path et attribute.

os.listxattr(path=None, *, follow_symlinks=True)

Renvoie une liste d’attributs du système de fichiers étendu pour path. Les attributs dans le liste sont représentés par des chaînes de caractères et sont décodés avec l’encodage du système de fichier. Si path vaut None, listxattr() examinera le répertoire actuel.

Cette fonction peut supporter la spécification d’un descripteur de fichier et le non-suivi des liens symboliques.

Modifié dans la version 3.6: Accepte un path-like object.

os.removexattr(path, attribute, *, follow_symlinks=True)

Supprime l’attribut étendu attribute du système de fichier pour le chemin path. attribute devrait être une chaîne de caractères ou d’octets (directement ou indirectement à travers une interface PathLike). Si c’est une chaîne de caractères, elle est encodée avec l’encodage du système de fichiers.

Cette fonction peut supporter la spécification d’un descripteur de fichier et le non-suivi des liens symboliques.

Modifié dans la version 3.6: Accepte un path-like object pour path et attribute.

os.setxattr(path, attribute, value, flags=0, *, follow_symlinks=True)

Règle l’attribut étendu attribute du système de fichier pour le chemin path à value. attribute doit être une chaîne de caractères ou d’octets sans caractères nuls (directement ou indirectement à travers une interface PathLike). Si c’est une chaîne de caractères, elle est encodée avec l’encodage du système de fichiers. flags peut être XATTR_REPLACE ou XATTR_CREATE. Si XATTR_REPLACE est donné et que l’attribut n’existe pas, EEXISTS sera levée. Si XATTR_CREATE est donné et que l’attribut existe déjà, l’attribut ne sera pas créé et ENODATA sera levée.

Cette fonction peut supporter la spécification d’un descripteur de fichier et le non-suivi des liens symboliques.

Note

Un bug des versions inférieures à 2.6.39 du noyau Linux faisait que les marqueurs de flags étaient ignorés sur certains systèmes.

Modifié dans la version 3.6: Accepte un path-like object pour path et attribute.

os.XATTR_SIZE_MAX

La taille maximum que peut faire la valeur d’un attribut étendu. Actuellement, c’est 64 KiB sur Lniux.

os.XATTR_CREATE

C’est une valeur possible pour l’argument flags de setxattr(). Elle indique que l’opération doit créer un attribut.

os.XATTR_REPLACE

C’est une valeur possible pour l’argument flags de setxattr().Elle indique que l’opération doit remplacer un attribut existant.

16.1.6. Gestion des processus

Ces fonctions peuvent être utilisées pour créer et gérer des processus.

Les variantes des fonctions exec* prennent une liste d’arguments pour le nouveau programme chargé dans le processus. Dans tous les cas, le premier de ces arguments est passé au nouveau programme comme son propre nom plutôt que comme un argument qu’un utilisateur peut avoir tapé en ligne de commande. Pour les programmeurs C, c’est l’argument argv[0] qui est passé à la fonction main() du programme. Par exemple, os.execv('/bin/echo/', ['foo', 'bar']) affichera uniquement bar sur la sortie standard ; foo semblera être ignoré.

os.abort()

Génère un signal SIGABRT au processus actuel. Sur Linux, le comportement par défaut est de produire un vidage système (Core Dump) ; sur Windows, le processus renvoie immédiatement un code d’erreur 3. Attention : appeler cette fonction n’appellera pas le gestionnaire de signal Python enregistré par SIGABRT à l’aide de signal.signal().

os.execl(path, arg0, arg1, ...)

os.execle(path, arg0, arg1, ..., env)

os.execlp(file, arg0, arg1, ...)

os.execlpe(file, arg0, arg1, ..., env)

os.execv(path, args)

os.execve(path, args, env)

os.execvp(file, args)

os.execvpe(file, args, env)

Ces fonctions exécutent toutes un nouveau programme, remplaçant le processus actuel, elles ne renvoient pas. Sur Unix, le nouvel exécutable est chargé dans le processus actuel, et aura le même identifiant de processus (PID) que l’appelant. Les erreurs seront reportées par des exceptions OSError.

Le processus actuel est remplacé immédiatement. Les fichiers objets et descripteurs de fichiers ne sont pas purgés, donc s’il est possible que des données aient été mises en tampon pour ces fichiers, vous devriez les purger manuellement en utilisant sys.stdout.flush() ou os.fsync() avant d’appeler une fonction exec*.

Les variantes « l » et « v » des fonctions exec* différent sur la manière de passer les arguments de ligne de commande. Les variantes « l » sont probablement les plus simples à utiliser si le nombre de paramètres est fixé lors de l’écriture du code. Les paramètres individuels deviennent alors des paramètres additionnels aux fonctions exec*(). Les variantes « v » sont préférables quand le nombre de paramètres est variable et qu’ils sont passés dans une liste ou un tuple dans le paramètre args. Dans tous les cas, les arguments aux processus fils devraient commencer avec le nom de la commande à lancer, mais ce n’est pas obligatoire.

Les variantes qui incluent un « p »vers la fin (execlp(), execlpe(), execvp(), et execvpe()) utiliseront la variable d’environnement PATH pour localiser le programme file. Quand l’environnement est remplacé (en utilisant une des variantes exec*e, discutées dans le paragraphe suivant), le nouvel environnement est utilisé comme source de la variable d’environnement PATH. Les autres variantes execl(), execle(), execv(), et execve() n’utiliseront pas la variable d’environnement PATH pour localiser l’exécutable. path doit contenir un chemin absolue ou relatif approprié.

Pour les fonctions execle(), execlpe(), execve(), et execvpe() (notez qu’elle finissent toutes par « e »), le paramètre env doit être un mapping qui est utilisé pour définir les variables d’environnement du nouveau processus (celles-ci sont utilisées à la place de l’environnement du nouveau processus). Les fonctions execl(), execlp(), execv(), et execvp() causent toutes un héritage de l’environnement du processus actuel par le processus fils.

Pour execve(), sur certaines plate-formes, path peut également être spécifié par un descripteur de fichier ouvert. Cette fonctionnalité peut ne pas être gérée sur votre plate-forme. Vous pouvez vérifier si c’est disponible en utilisant os._supports_fd. Si c’est indisponible, l’utiliser lèvera une NotImplementedError.

Disponibilité : Unix, Windows.

Nouveau dans la version 3.3: Prise en charge de la spécification d’un descripteur de fichier ouvert pour path pour execve().

Modifié dans la version 3.6: Accepte un path-like object.

os._exit(n)

Quitte le processus avec le statut n, sans appeler les gestionnaires de nettoyage, sans purger les tampons des fichiers, etc.

Note

La méthode standard pour quitter est sys.exit(n). _exit() devrait normalement être utilisé uniquement par le processus fils après un fork().

Les codes de sortie suivants sont définis et peuvent être utilisés avec _exit(), mais ils ne sont pas nécessaires. Ils sont typiquement utilisés pour les programmes systèmes écrits en Python, comme un programme de gestion de l’exécution des commandes d’un serveur de mails.

Note

Certaines de ces valeurs peuvent ne pas être disponibles sur toutes les plate-formes Unix étant donné qu’il en existe des variations. Ces constantes sont définies là où elles sont définies par la plate-forme sous-jacente.

os.EX_OK

Code de sortie signifiant qu’aucune erreur n’est arrivée.

Disponibilité : Unix.

os.EX_USAGE

Code de sortie signifiant que les commandes n’ont pas été utilisées correctement, comme quand le mauvais nombre d’arguments a été donné.

Disponibilité : Unix.

os.EX_DATAERR

Code de sortie signifiant que les données en entrées étaient incorrectes.

Disponibilité : Unix.

os.EX_NOINPUT

Code de sortie signifiant qu’un des fichiers d’entrée n’existe pas ou n’est pas lisible.

Disponibilité : Unix.

os.EX_NOUSER

Code de sortie signifiant qu’un utilisateur spécifié n’existe pas.

Disponibilité : Unix.

os.EX_NOHOST

Code de sortie signifiant qu’un hôte spécifié n’existe pas.

Disponibilité : Unix.

os.EX_UNAVAILABLE

Code de sortie signifiant qu’un service requis n’est pas disponible.

Disponibilité : Unix.

os.EX_SOFTWARE

Code de sortie signifiant qu’une erreur interne d’un programme a été détectée.

Disponibilité : Unix.

os.EX_OSERR

Code de sortie signifiant qu’une erreur du système d’exploitation a été détectée, comme l’incapacité à réaliser un fork ou à créer un tuyau (pipe).

Disponibilité : Unix.

os.EX_OSFILE

Code de sortie signifiant qu’un fichier n’existe pas, n’a pas pu être ouvert, ou avait une autre erreur.

Disponibilité : Unix.

os.EX_CANTCREAT

Code de sortie signifiant qu’un fichier spécifié par l’utilisateur n’a pas pu être créé.

Disponibilité : Unix.

os.EX_IOERR

Code de sortie signifiant qu’une erreur est apparue pendant une E/S sur un fichier.

Disponibilité : Unix.

os.EX_TEMPFAIL

Code de sortie signifiant qu’un échec temporaire est apparu. Cela indique quelque chose qui pourrait ne pas être une erreur, comme une connexion au réseau qui n’a pas pu être établie pendant une opération réessayable.

Disponibilité : Unix.

os.EX_PROTOCOL

Code de sortie signifiant qu’un protocole d’échange est illégal, invalide, ou non-compris.

Disponibilité : Unix.

os.EX_NOPERM

Code de sortie signifiant qu’il manque certaines permissions pour réaliser une opération (mais n’est pas destiné au problèmes de système de fichiers).

Disponibilité : Unix.

os.EX_CONFIG

Code de sortie signifiant qu’une erreur de configuration est apparue.

Disponibilité : Unix.

os.EX_NOTFOUND

Code de sortie signifiant quelque chose comme « une entrée n’a pas été trouvée ».

Disponibilité : Unix.

os.fork()

Fork un processus fils. Renvoie 0 dans le processus fils et le PID du processus fils dans le processus père. Si une erreur apparaît, une OSError est levée.

Notez que certaines plate-formes (dont FreeBSD <= 6.3 et Cygwin) ont des problèmes connus lors d’utilisation de fork() depuis un fil d’exécution.

Avertissement

Voit ssl pour les application qui utilisent le module SSL avec fork().

Disponibilité : Unix.

os.forkpty()

Fork un processus fils, en utilisant un nouveau pseudo-terminal comme terminal contrôlant le fils. Renvoie une paire (pid, fd) où pid vaut 0 dans le fils et le PID du processus fils dans le parent, et fd est le descripteur de fichier de la partie maître du pseudo-terminal. Pour une approche plus portable, utilisez le module pty. Si une erreur apparaît, une OSError est levée.

Disponibilité : certains dérivés Unix.

os.kill(pid, sig)

Envoie le signal sig au processus pid. Les constantes pour les signaux spécifiques à la plate-forme hôte sont définies dans le module signal.

Windows : les signaux signal.CTRL_C_EVENT et signal.CTRL_BREAK_EVENT sont des signaux spéciaux qui ne peuvent être envoyés qu’aux processus consoles qui partagent une console commune (par exemple, certains sous-processus). Toute autre valeur pour sig amènera le processus a être tué sans condition par l’API TerminateProcess, et le code de retour sera mis à sig. La version Windows de kill() prend en plus les identificateurs de processus à tuer.

Voir également signal.pthread_kill().

Nouveau dans la version 3.2: Prise en charge de Windows.

os.killpg(pgid, sig)

Envoie le signal sig au groupe de processus pgid.

Disponibilité : Unix.

os.nice(increment)

Ajoute increment à la priorité du processus. Renvoie la nouvelle priorité.

Disponibilité : Unix.

os.plock(op)

Verrouille les segments du programme en mémoire. La valeur de op (définie dans <sys/lock.h>) détermine quels segments sont verrouillés.

Disponibilité : Unix.

os.popen(cmd, mode='r', buffering=-1)

Ouvre un tuyau vers ou depuis la commande cmd. La valeur de retour est un fichier objet ouvert relié au tuyau qui peut être lu ou écrit selon la valeur de mode qui est 'r' (par défaut) ou 'w'. L’argument buffering a le même sens que l’argument correspondant de la fonction open(). L’objet fichier renvoyé écrit (ou lit) des chaînes de caractères et non de bytes.

La méthode close renvoie None si le sous-processus s’est terminé avec succès, ou le code de retour du sous-processus s’il y a eu une erreur. Sur les systèmes POSIX, si le code de retour est positif, il représente la valeur de retour du processus décalée d’un byte sur la gauche. Si le code de retour est négatif, le processus le processus s’est terminé avec le signal donné par la négation de la valeur de retour. (Par exemple, la valeur de retour pourrait être -signal.SIGKILL si le sous-processus a été tué). Sur les systèmes Windows, la valeur de retour contient le code de retour du processus fils dans un entier signé .

Ceci est implémenté en utilisant subprocess.Popen. Lisez la documentation de cette classe pour des méthodes plus puissantes pour gérer et communiquer avec des sous-processus.

os.spawnl(mode, path, ...)

os.spawnle(mode, path, ..., env)

os.spawnlp(mode, file, ...)

os.spawnlpe(mode, file, ..., env)

os.spawnv(mode, path, args)

os.spawnve(mode, path, args, env)

os.spawnvp(mode, file, args)

os.spawnvpe(mode, file, args, env)

Exécute le programme path dans un nouveau processus.

(Notez que le module subprocess fournit des outils plus puissants pour générer de nouveaux processus et récupérer leur valeur de retour. Il est préférable d’utiliser ce module que ces fonctions. Voyez surtout la section Remplacer les fonctions plus anciennes par le module subprocess.)

Si mode vaut P_NOWAIT, cette fonction renvoie le PID du nouveau processus, et si mode vaut P_WAIT, la fonction renvoie le code de sortie du processus s’il se termine normalement, ou -signal où signal est le signal qui a tué le processus. Sur Windows, le PID du processus sera en fait l’identificateur du processus (process handle) et peut donc être utilisé avec la fonction waitpid().

Les variantes « l » et « v » des fonctions spawn* diffèrent sur la manière de passer les arguments de ligne de commande. Les variantes « l » sont probablement les plus simples à utiliser si le nombre de paramètres est fixé lors de l’écriture du code. Les paramètres individuels deviennent alors des paramètres additionnels aux fonctions spawn*(). Les variantes « v » sont préférables quand le nombre de paramètres est variable et qu’ils sont passés dans une liste ou un tuple dans le paramètre args. Dans tous les cas, les arguments aux processus fils devraient commencer avec le nom de la commande à lancer, mais ce n’est pas obligatoire.

Les variantes qui incluent un « p »vers la fin (spawnlp(), spawnlpe(), spawnvp(), et spawnvpe()) utiliseront la variable d’environnement PATH pour localiser le programme file. Quand l’environnement est remplacé (en utilisant une des variantes spawn*e, discutées dans le paragraphe suivant), le nouvel environnement est utilisé comme source de la variable d’environnement PATH. Les autres variantes spawnl(), spawnle(), spawnv(), et spawnve() n’utiliseront pas la variable d’environnement PATH pour localiser l’exécutable. path doit contenir un chemin absolue ou relatif approprié.

Pour les fonctions spawnle(), spawnlpe(), spawnve(), et spawnvpe() (notez qu’elles finissent toutes par « e »), le paramètre env doit être un mapping qui est utilisé pour définir les variables d’environnement du nouveau processus (celles-ci sont utilisées à la place de l’environnement du nouveau processus). Les fonctions spawnl(), spawnlp(), spawnv(), et spawnvp() causent toutes un héritage de l’environnement du processus actuel par le processus fils. Notez que les clefs et les valeurs du dictionnaire env doivent être des chaînes de caractères. Des valeurs invalides pour les clefs ou les valeurs met la fonction en échec et renvoie 127.

Par exemple, les appels suivants à spawnlp() et spawnvpe() sont équivalents :

import os
os.spawnlp(os.P_WAIT, 'cp', 'cp', 'index.html', '/dev/null')

L = ['cp', 'index.html', '/dev/null']
os.spawnvpe(os.P_WAIT, 'cp', L, os.environ)

Disponibilité : Unix, Windows. spawnlp(), spawnlpe(), spawnvp(), et spawnvpe() ne sont pas disponibles sur Windows. spawnle() et spawnve() ne sont pas sécurisés pour les appels concurrents (thread-safe) sur Windows, il est conseillé d’utiliser le module subprocess à la place.

Modifié dans la version 3.6: Accepte un path-like object.

os.P_NOWAIT

os.P_NOWAITO

Valeurs possibles pour le paramètre mode de la famille de fonctions spawn*. Si l’une de ces valeurs est donnée, les fonctions spawn*() sortiront dès que le nouveau processus est créé, avec le PID du processus comme valeur de retour.

Disponibilité : Unix, Windows.

os.P_WAIT

Valeur possible pour le paramètre mode de la famille de fonctions spawn*. Si mode est défini par cette valeur, les fonctions spawn* ne se terminent pas tant que le nouveau processus n’a pas été complété et renvoient le code de sortie du processus si l’exécution est effectuée avec succès, ou -signal si un signal tue le processus.

Disponibilité : Unix, Windows.

os.P_DETACH

os.P_OVERLAY

Valeurs possibles pour le paramètre mode de la famille de fonctions spawn*. Ces valeurs sont moins portables que celles listées plus haut. P_DETACH est similaire à P_NOWAIT, mais le nouveau processus est détaché de la console du processus appelant. Si P_OVERLAY est utilisé, le processus actuel sera remplacé. La fonction spawn* ne sort jamais.

Disponibilité : Windows.

os.startfile(path[, operation])

Lance un fichier avec son application associée.

Quand operation n’est pas spécifié ou vaut 'open', l’effet est le même qu’un double clic sur le fichier dans Windows Explorer, ou que de passer le nom du fichier en argument du programme start depuis l’invite de commande interactif : le fichier est ouvert avec l’application associée à l’extension (s’il y en a une).

Quand une autre operation est donnée, ce doit être une « commande-verbe » qui spécifie ce qui devrait être fait avec le fichier. Les verbes habituels documentés par Microsoft sont 'print' et 'edit' (qui doivent être utilisés sur des fichiers) ainsi que 'explore' et 'find' (qui doivent être utilisés sur des répertoires).

startfile() termine dès que l’application associée est lancée.Il n’y a aucune option permettant d’attendre que l’application ne se ferme et aucun moyen de récupérer le statu de sortie de l’application. Le paramètre path est relatif au répertoire actuel. Si vous voulez utiliser un chemin absolu, assurez-vous que le premier caractère ne soit pas un slash ('/'). La fonction Win32 ShellExecute() sous-jacente ne fonctionne pas sinon. Utilisez la fonction os.path.normpath() pour vous assurer que le chemin est encodé correctement pour Win32.

Pour réduire Pour réduire le temps système de démarrage de l’interpréteur, la fonction Win32 ShellExecute() ne se finit pas tant que cette fonction na pas été appelée. Si la fonction ne peut être interprétée, une NotImplementedError est levée.

Disponibilité : Windows.

os.system(command)

Exécute la commande (une chaîne de caractères) dans un sous-invite de commandes. C’est implémenté en appelant la fonction standard C system() et a les mêmes limitations. les changements sur sys.stdin, etc. ne sont pas reflétés dans l’environnement de la commande exécutée. Si command génère une sortie, elle sera envoyée à l’interpréteur standard de flux.

Sur Unix, la valeur de retour est le statut de sortie du processus encodé dans le format spécifié pour wait(). Notez que POSIX ne spécifie pas le sens de la valeur de retour de la fonction C system(), donc la valeur de retour de la fonction Python est dépendante du système.

Sur Windows, la valeur de retour est celle renvoyée par l’invite de commande système après avoir lancé command. L’invite de commande est donné par la variable d’environnement Windows COMSPEC. Elle vaut habituellement cmd.exe, qui renvoie l’état de sortie de la commande lancée. Sur les systèmes qui utilisent un invite de commande non-natif, consultez la documentation propre à l’invite.

Le module subprocess fournit des outils plus puissants pour générer de nouveaux processus et pour récupérer leur résultat. Il est préférable d’utiliser ce module plutôt que d’utiliser cette fonction. Voir la section Remplacer les fonctions plus anciennes par le module subprocess de la documentation du module subprocess pour des informations plus précises et utiles.

Disponibilité : Unix, Windows.

os.times()

Renvoie les temps globaux actuels d’exécution du processus. La valeur de retour est un objet avec cinq attributs :

user — le temps utilisateur

system — le temps système

children_user — temps utilisateur de tous les processus fils

children_system — le temps système de tous les processus fils

elapsed — temps écoulé réel depuis un point fixé dans le passé

Pour des raisons de rétro-compatibilité, cet objet se comporte également comme un tuple contenant user, system, children_user, children_system, et elapsed dans cet ordre.

Voir la page de manuel Unix times(2) ou la documentation de l’API Windows correspondante. Sur Windows, seuls user et system sont connus. Les autres attributs sont nuls.

Disponibilité : Unix, Windows.

Modifié dans la version 3.3: Type de retour changé d’un tuple en un objet compatible avec le type tuple, avec des attributs nommés.

os.wait()

Attend qu’un processus fils soit complété, et renvoie un tuple contenant son PID et son état de sortie : un nombre de 16 bits dont le byte de poids faible est le nombre correspondant au signal qui a tué le processus, et dont le byte de poids fort est le statut de sortie (si la signal vaut 0). Le bit de poids fort du byte de poids faible est mis à 1 si un (fichier système) core file a été produit.

Disponibilité : Unix.

os.waitid(idtype, id, options)

Attend qu’un ou plusieurs processus fils soient complétés. idtypes peut être P_PID, P_PGID, ou P_ALL. id spécifie le PID à attendre. options est construit en combinant (avec le OR bit-à-bit) une ou plusieurs des valeurs suivantes : WEXITED, WSTOPPED, ou WCONTINUED et peut additionnellement être combiné avec WNOHANG ou WNOWAIT. La valeur de retour est un objet représentant les données contenue dans la structure siginfo_t, nommées si_pid, si_uid, si_signo, si_status, si_code ou None si WNOHANG est spécifié et qu’il n’y a pas d’enfant dans un état que l’on peut attendre.

Disponibilité : Unix.

Nouveau dans la version 3.3.

os.P_PID

os.P_PGID

os.P_ALL

Les valeurs possibles pour idtypes pour la fonction waitid(). Elles affectent l’interprétation de id.

Disponibilité : Unix.

Nouveau dans la version 3.3.

os.WEXITED

os.WSTOPPED

os.WNOWAIT

Marqueurs qui peuvent être utilisés pour la fonction waitid() qui spécifient quel signal attendre du fils.

Disponibilité : Unix.

Nouveau dans la version 3.3.

os.CLD_EXITED

os.CLD_DUMPED

os.CLD_TRAPPED

os.CLD_CONTINUED

Les valeurs possibles pour si_code dans le résultat renvoyé par waitid().

Disponibilité : Unix.

Nouveau dans la version 3.3.

os.waitpid(pid, options)

Les détails de cette fonction diffèrent sur Unix et Windows.

Sur Unix : attend qu’un processus fils donné par son id de processus pid soit terminé, et renvoie un tuple contenant son PID et son statut de sortie (encodé comme pour wait()). La sémantique de cet appel est affecté par la valeur de l’argument entier options, qui devrait valoir 0 pour les opérations normales.

Si pid est plus grand que 0, waitpid() introduit une requête pour des informations sur le statut du processus spécifié. Si pid vaut 0, la requête est pour le statut de tous les fils dans le groupe de processus du processus actuel. Si pid vaut -1, la requête concerne tous les processus fils du processus actuel. Si pid est inférieur à -1, une requête est faite pour le statut de chaque processus du groupe de processus donné par -pid (la valeur absolue de pid).

Une OSError est levée avec la valeur de errno quand l’appel système renvoie -1.

Sur Windows : attend que qu’un processus donné par l’identificateur de processus (process handle) pid soi complété, et renvoie un tuple contenant pid et son statut de sortir décalé de 8 bits bers la gauche (le décalage rend l’utilisation multiplate-forme plus facile). Un pid inférieur ou égal à 0 n’a aucune signification particulière sur Windows, et lève une exception. L’argument entier options n’a aucun effet. pid peut faire référence à tout processus dont l’identifiant est connue pas nécessairement un processus fils. Les fonctions spawn* appelées avec P_NOWAIT renvoient des identificateurs de processus appropriés.

Modifié dans la version 3.5: Si l’appel système est interrompu et que le gestionnaire de signal ne lève aucune exception, la fonction réessaye l’appel système au lieu de lever une InterruptedError (voir la PEP 475 [https://www.python.org/dev/peps/pep-0475] à propos du raisonnement).

os.wait3(options)

Similaire à la fonction waitpid(), si ce n’est que qu’aucun argument id n’est donné, et qu’un triplet contenant l’identifiant du processus fils, son statut de sortie, et une information sur l’utilisation des ressources est renvoyé. Référez-vous à resource.getrusage() pour des détails sur les informations d’utilisation des ressources. L’argument options est le même que celui fourni à waitpid() et wait4().

Disponibilité : Unix.

os.wait4(pid, options)

Similaire à waitpid(), si ce n’est qu’un triplet contenant l’identifiant du processus fils, son statut de sortie, et des informations d’utilisation des ressources est renvoyé. Référez-vous à resource.getrusage() pour des détails sur les informations d’utilisation des ressources. Les arguments de wait4() sont les mêmes que ceux fournis à waitpid().

Disponibilité : Unix.

os.WNOHANG

L’option de waitpid() pour terminer immédiatement si aucun statut de processus fils n’est disponible dans l’immédiat. La fonction renvoie (0, 0) dans ce cas.

Disponibilité : Unix.

os.WCONTINUED

Cette option cause les processus fils à être reportés s’ils ont été continués après un arrêt du job control depuis leurs derniers reports de statuts.

Disponibilité : certains systèmes Unix.

os.WUNTRACED

Cette option cause les processus fils à être reportés s’ils ont été stoppés mais que leur état actuel n’a pas été reporté depuis qu’ils ont été stoppés.

Disponibilité : Unix.

Les fonctions suivantes prennent un code de statu tel que renvoyé par system(), wait(), ou waitpid() en paramètre. Ils peuvent être utilisés pour déterminer la disposition d’un processus.

os.WCOREDUMP(status)

Renvoie True si un vidage système (core dump) a été généré pour le processus, sinon, renvoie False.

Disponibilité : Unix.

os.WIFCONTINUED(status)

Renvoie True si le processus a été continué après un arrêt du job control, renvoie False autrement.

Disponibilité : Unix.

os.WIFSTOPPED(status)

Renvoie True si le processus a été arrête, sinon renvoie False.

Disponibilité : Unix.

os.WIFSIGNALED(status)

Renvoie True si le processus s’est terminé à cause d’un signal, sinon, renvoie False.

Disponibilité : Unix.

os.WIFEXITED(status)

Renvoie True si le processus s’est terminé en faisant un appel système exit(2), sinon, renvoie False.

Disponibilité : Unix.

os.WEXITSTATUS(status)

Si WIFEXITED(status) vaut True, renvoie le paramètre entier de l’appel système exit(2). Sinon, la valeur de retour n’a pas de signification.

Disponibilité : Unix.

os.WSTOPSIG(status)

Renvoie le signal qui a causé l’arrêt du processus.

Disponibilité : Unix.

os.WTERMSIG(status)

Renvoie le signal qui a amené le processus à quitter.

Disponibilité : Unix.

16.1.7. Interface pour l’ordonnanceur

Ces fonctions contrôlent un processus se voit allouer du temps de processus par le système d’exploitation. Elles ne sont disponibles que sur certaines plate-formes Unix. Pour des informations plus détaillées, consultez les pages de manuels Unix.

Nouveau dans la version 3.3.

Les polices d’ordonnancement suivantes sont exposées si elles sont gérées par le système d’exploitation.

os.SCHED_OTHER

La police d’ordonnancement par défaut.

os.SCHED_BATCH

Police d’ordonnancement pour les processus intensifs en utilisation du processeur. Cette police essaye de préserver l’interactivité pour le reste de l’ordinateur.

os.SCHED_IDLE

Police d’ordonnancement pour les tâches de fond avec une priorité extrêmement faible.

os.SCHED_SPORADIC

Police d’ordonnancement pour des programmes serveurs sporadiques.

os.SCHED_FIFO

Une police d’ordonnancement FIFO (dernier arrivé, premier servi).

os.SCHED_RR

Une police d’ordonnancement round-robin (tourniquet).

os.SCHED_RESET_ON_FORK

Cette option peut combiner différentes politiques d’ordonnancement avec un OU bit-à-bit. Quand un processus avec cette option se dédouble, la politique d’ordonnancement et la priorité du processus fils sont remises aux valeurs par défaut.

class os.sched_param(sched_priority)

Cette classe représente des paramètres d’ordonnancement réglables utilisés pour sched_setparam(), sched_setscheduler(), et sched_getparam(). Un objet de ce type est immuable.

Pour le moment, il n’y a qu’un seul paramètre possible :

sched_priority

La priorité d’ordonnancement pour une police d’ordonnancement.

os.sched_get_priority_min(policy)

Récupère la valeur minimum pour une priorité pour la police policy. policy est une des constantes de police définies ci-dessus.

os.sched_get_priority_max(policy)

Récupère la valeur maximum pour une priorité pour la police policy. policy est une des constantes de police définies ci-dessus.

os.sched_setscheduler(pid, policy, param)

Définit la police d’ordonnancement pour le processus de PID pid. Un pid de 0 signifie le processus appelant. policy est une des constantes de police définies ci-dessus. param est une instance de la classe sched_param.

os.sched_getscheduler(pid)

Renvoie la police d’ordonnancement pour le processus de PID pid. Un pid de 0 signifie le processus appelant. Le résultat est une des constantes de police définies ci-dessus.

os.sched_setparam(pid, param)

Définit un paramètre d’ordonnancement pour le processus de PID pid. Un pid de 0 signifie le processus appelant. param est une instance de sched_param.

os.sched_getparam(pid)

Renvoie les paramètres d’ordonnancement dans une de sched_param pour le processus de PID pid. Un pid de 0 signifie le processus appelant.

os.sched_rr_get_interval(pid)

Renvoie le quantum de temps du round-robin (en secondes) pour le processus de PID pid. Un pid de 0 signifie le processus appelant.

os.sched_yield()

Abandonne volontairement le processeur.

os.sched_setaffinity(pid, mask)

Restreint le processus de PID pid (ou le processus actuel si pid vaut 0) à un ensemble de CPUs. mask est un itérable d’entiers représentant l’ensemble de CPUs auquel le processus doit être restreint.

os.sched_getaffinity(pid)

Renvoie l’ensemble de CPUs auquel le processus de PID pid (ou le processus actuel si pid vaut 0) est restreint.

16.1.8. Diverses informations sur le système

os.confstr(name)

Renvoie les valeurs de configuration en chaînes de caractères. name spécifie la valeur de configuration à récupérer. Ce peut être une chaîne de caractères représentant le nom d’une valeur système définie dans un nombre de standards (POSIX, Unix 95, Unix 98, et d’autres). Certaines plate-formes définissent des noms supplémentaires également. Les noms connus par le système d’exploitation hôte sont données dans les clefs du dictionnaire confstr_names. Pour les variables de configuration qui ne sont pas incluses dans ce mapping, passer un entier pour name est également accepté.

Si la valeur de configuration spécifiée par name n’est pas définie, None est renvoyé.

Si name est une chaîne de caractères et n’est pas connue, une ValueError est levée. Si une valeur spécifique pour name n’est pas gérée par le système hôte, même si elle est incluse dans confstr_names, une OSError est levée avec errno.EINVAL pour numéro d’erreur.

Disponibilité : Unix.

os.confstr_names

Dictionnaire liant les noms acceptés par confstr() aux valeurs entières définies pour ces noms par le système d’exploitation hôte. Cela peut être utilisé pour déterminer l’ensemble des noms connus du système.

Disponibilité : Unix.

os.cpu_count()

Renvoie le nombre de CPUs dans le système. Renvoie None si indéterminé.

Ce nombre n’est pas équivalent au nombre de CPUs que le processus courant peut utiliser. Le nombre de CPUs utilisables peut être obtenu avec len(os.sched_getaffinity(0))

Nouveau dans la version 3.4.

os.getloadavg()

Renvoie le nombre de processus dans la file d’exécution du système en moyenne dans les dernières 1, 5, et 15 minutes, ou lève une OSError si la charge moyenne est impossible à récupérer.

Disponibilité : Unix.

os.sysconf(name)

Renvoie les valeurs de configuration en nombres entiers. Si la valeur de configuration définie par name n’est pas spécifiée, -1 est renvoyé. Les commentaires concernant le paramètre name de confstr() s’appliquent également ici, le dictionnaire qui fournit les informations sur les noms connus est donné par sysconf_names.

Disponibilité : Unix.

os.sysconf_names

Dictionnaire liant les noms acceptés par sysconf() aux valeurs entières définies pour ces noms par le système d’exploitation hôte. Cela peut être utilisé pour déterminer l’ensemble des noms connus du système.

Disponibilité : Unix.

Les valeurs suivantes sont utilisées pour gérer les opérations de manipulations de chemins. Elles sont définies pour toutes les plate-formes.

Des opérations de plus haut niveau sur les chemins sont définies dans le module os.path.

os.curdir

La chaîne de caractère constante utilisée par le système d’exploitation pour référencer le répertoire actuel. Ça vaut '.' pour Windows et POSIX. Également disponible par os.path.

os.pardir

La chaîne de caractère constante utilisée par le système d’exploitation pour référencer le répertoire parent. Ça vaut '..' pour Windows et POSIX. Également disponible par os.path.

os.sep

Le caractère utilisé par le système d’exploitation pour séparer les composantes des chemins. C’est '/' pour POSIX, et '\\' pour Windows. Notez que ce n’est pas suffisant pour pouvoir analyser ou concaténer correctement des chemins (utilisez alors os.path.split() et os.path.join()), mais ça peut s’avérer utile occasionnellement. Également disponible par os.path.

os.altsep

Un caractère alternatif utilisé par le système d’exploitation pour séparer les composantes des chemins, ou None si un seul séparateur existe. Ça vaut '/' sur Windows où sep est un antislash '\'. Également disponible par os.path.

os.extsep

Le caractère qui sépare la base du nom d’un fichier et son extension. Par exemple, le '.' de os.py. Également disponible par os.path.

os.pathsep

Le caractère conventionnellement utilisé par le système d’exploitation pour séparer la recherche des composantes de chemin (comme dans la variable d’environnement PATH). Cela vaut ':' pour POSIX, ou ';' pour Windows. Également disponible par os.path.

os.defpath

Le chemin de recherche par défaut utilisé par exec* et spawn* si l’environnement n’a pas une clef 'PATH'. Également disponible par os.path.

os.linesep

La chaîne de caractères utilisée pour séparer (ou plutôt pour terminer) les lignes sur la plate-forme actuelle. Ce peut être un caractère unique (comme '\n' pour POSIX,) ou plusieurs caractères (comme '\r\n' pour Windows). N’utilisez pas os.linesep comme terminateur de ligne quand vous écrivez dans un fichier ouvert en mode texte (par défaut). Utilisez un unique '\n' à la place, sur toutes les plate-formes.

os.devnull

Le chemin de fichier du périphérique null. Par exemple : '/dev/null' pour POSIX, 'nul' pour Windows. Également disponible par os.path.

os.RTLD_LAZY

os.RTLD_NOW

os.RTLD_GLOBAL

os.RTLD_LOCAL

os.RTLD_NODELETE

os.RTLD_NOLOAD

os.RTLD_DEEPBIND

Marqueurs à utiliser avec les fonctions setdlopenflags() et getdlopenflags(). Voir les pages de manuel Unix dlopen(3) pour les différences de significations entre les marqueurs.

Nouveau dans la version 3.3.

16.1.9. Nombres aléatoires

os.getrandom(size, flags=0)

Obtient size octets aléatoires. La fonction renvoie éventuellement moins d’octets que demandé.

Ces octets peuvent être utilisés pour initialiser un générateur de nombres aléatoires dans l’espace utilisateur ou pour des raisons cryptographiques.

getrandom() se base sur l’entropie rassemblée depuis les pilotes des périphériques et autres sources de bruits de l’environnement. La lecture de grosses quantités de données aura un impact négatif sur les autres utilisateurs des périphériques /dev/random et /dev/urandom.

L’argument flags est un champ de bits qui peut contenir zéro ou plus des valeurs suivantes combinées avec un OU bit-à-bit : os.GRND_RANDOM et GRND_NONBLOCK.

Voir aussi la page de manuel Linux pour getrandom() [http://man7.org/linux/man-pages/man2/getrandom.2.html].

Disponibilité : Linux 3.17 et ultérieures.

Nouveau dans la version 3.6.

os.urandom(size)

Renvoie une chaîne de size octets aléatoires utilisable dans un cadre cryptographique.

Cette fonction renvoie des octets aléatoires depuis un source spécifique à l’OS. Les données renvoyées sont censées être suffisamment imprévisibles pour les applications cryptographiques, bien que la qualité dépende de l’implémentation du système.

Sous Linux, si l’appel système getrandom() est disponible, il est utilisé en mode bloquant : il bloque jusqu’à ce que la réserve d’entropie d”urandom soit initialisée (128 bits d’entropie sont collectés par le noyau). Voir la PEP 524 [https://www.python.org/dev/peps/pep-0524] pour plus d’explications. Sous Linux, la fonction getrandom() peut être utilisée pour obtenir des octets aléatoires en mode non-bloquant (avec l’option GRND_NONBLOCK) ou attendre jusqu’à ce que la réserve d’entropie d”urandom soit initialisée.

Sur un système de type UNIX, les octets aléatoires sont lus depuis le périphérique /dev/urandom. Si le périphérique /dev/urandom n’est pas disponible ou n’est pas lisible, l’exception NotImplementedError est levée.

Sous Windows, CryptGenRandom() est utilisée.

Voir aussi

Le module secrets fournit des fonctions de plus haut niveau. Pour une interface facile à utiliser du générateur de nombres aléatoires fourni par votre plate-forme, veuillez regarder random.SystemRandom.

Modifié dans la version 3.6.0: Sous Linux, getrandom() est maintenant utilisé en mode bloquant pour renforcer la sécurité.

Modifié dans la version 3.5.2: Sous Linux, si l’appel système getrandom() bloque (la réserve d’entropie d”urandom n’est pas encore initialisée), réalise à la place une lecture de /dev/urandom.

Modifié dans la version 3.5: Sur Linux 3.17 et plus récent, l’appel système getrandom() est maintenant utilisé quand il est disponible. Sur OpenBSD 5.6 et plus récent, la fonction C getentropy() est utilisée. Ces fonctions évitent l’utilisation interne d’un descripteur de fichier.

os.GRND_NONBLOCK

Par défaut, quand elle lit depuis /dev/random, getrandom() bloque si aucun octet aléatoire n’est disponible, et quand elle lit depuis /dev/urandom, elle bloque si la réserve d’entropie n’a pas encore été initialisée.

Si l’option GRND_NONBLOCK est activée, getrandom() ne bloque pas dans ces cas, mais lève immédiatement une BlockingIOError.

Nouveau dans la version 3.6.

os.GRND_RANDOM

Si ce bit est activé, les octets aléatoires sont puisés depuis /dev/random plutôt que /dev/urandom.

Nouveau dans la version 3.6.

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16.2. io — Core tools for working with streams

Source code: Lib/io.py [https://github.com/python/cpython/tree/3.6/Lib/io.py]

16.2.1. Aperçu

The io module provides Python’s main facilities for dealing with various types of I/O. There are three main types of I/O: text I/O, binary I/O and raw I/O. These are generic categories, and various backing stores can be used for each of them. A concrete object belonging to any of these categories is called a file object. Other common terms are stream and file-like object.

Independent of its category, each concrete stream object will also have various capabilities: it can be read-only, write-only, or read-write. It can also allow arbitrary random access (seeking forwards or backwards to any location), or only sequential access (for example in the case of a socket or pipe).

All streams are careful about the type of data you give to them. For example giving a str object to the write() method of a binary stream will raise a TypeError. So will giving a bytes object to the write() method of a text stream.

Modifié dans la version 3.3: Operations that used to raise IOError now raise OSError, since IOError is now an alias of OSError.

16.2.1.1. Text I/O

Text I/O expects and produces str objects. This means that whenever the backing store is natively made of bytes (such as in the case of a file), encoding and decoding of data is made transparently as well as optional translation of platform-specific newline characters.

The easiest way to create a text stream is with open(), optionally specifying an encoding:

f = open("myfile.txt", "r", encoding="utf-8")

In-memory text streams are also available as StringIO objects:

f = io.StringIO("some initial text data")

The text stream API is described in detail in the documentation of TextIOBase.

16.2.1.2. Binary I/O

Binary I/O (also called buffered I/O) expects bytes-like objects and produces bytes objects. No encoding, decoding, or newline translation is performed. This category of streams can be used for all kinds of non-text data, and also when manual control over the handling of text data is desired.

The easiest way to create a binary stream is with open() with 'b' in the mode string:

f = open("myfile.jpg", "rb")

In-memory binary streams are also available as BytesIO objects:

f = io.BytesIO(b"some initial binary data: \x00\x01")

The binary stream API is described in detail in the docs of BufferedIOBase.

Other library modules may provide additional ways to create text or binary streams. See socket.socket.makefile() for example.

16.2.1.3. Raw I/O

Raw I/O (also called unbuffered I/O) is generally used as a low-level building-block for binary and text streams; it is rarely useful to directly manipulate a raw stream from user code. Nevertheless, you can create a raw stream by opening a file in binary mode with buffering disabled:

f = open("myfile.jpg", "rb", buffering=0)

The raw stream API is described in detail in the docs of RawIOBase.

16.2.2. High-level Module Interface

io.DEFAULT_BUFFER_SIZE

An int containing the default buffer size used by the module’s buffered I/O classes. open() uses the file’s blksize (as obtained by os.stat()) if possible.

io.open(file, mode='r', buffering=-1, encoding=None, errors=None, newline=None, closefd=True, opener=None)

This is an alias for the builtin open() function.

exception io.BlockingIOError

This is a compatibility alias for the builtin BlockingIOError exception.

exception io.UnsupportedOperation

An exception inheriting OSError and ValueError that is raised when an unsupported operation is called on a stream.

16.2.2.1. In-memory streams

It is also possible to use a str or bytes-like object as a file for both reading and writing. For strings StringIO can be used like a file opened in text mode. BytesIO can be used like a file opened in binary mode. Both provide full read-write capabilities with random access.

Voir aussi

sys

contains the standard IO streams: sys.stdin, sys.stdout, and sys.stderr.

16.2.3. Class hierarchy

The implementation of I/O streams is organized as a hierarchy of classes. First abstract base classes (ABCs), which are used to specify the various categories of streams, then concrete classes providing the standard stream implementations.

Note

The abstract base classes also provide default implementations of some methods in order to help implementation of concrete stream classes. For example, BufferedIOBase provides unoptimized implementations of readinto() and readline().

At the top of the I/O hierarchy is the abstract base class IOBase. It defines the basic interface to a stream. Note, however, that there is no separation between reading and writing to streams; implementations are allowed to raise UnsupportedOperation if they do not support a given operation.

The RawIOBase ABC extends IOBase. It deals with the reading and writing of bytes to a stream. FileIO subclasses RawIOBase to provide an interface to files in the machine’s file system.

The BufferedIOBase ABC deals with buffering on a raw byte stream (RawIOBase). Its subclasses, BufferedWriter, BufferedReader, and BufferedRWPair buffer streams that are readable, writable, and both readable and writable. BufferedRandom provides a buffered interface to random access streams. Another BufferedIOBase subclass, BytesIO, is a stream of in-memory bytes.

The TextIOBase ABC, another subclass of IOBase, deals with streams whose bytes represent text, and handles encoding and decoding to and from strings. TextIOWrapper, which extends it, is a buffered text interface to a buffered raw stream (BufferedIOBase). Finally, StringIO is an in-memory stream for text.

Argument names are not part of the specification, and only the arguments of open() are intended to be used as keyword arguments.

The following table summarizes the ABCs provided by the io module:

ABC

Inherits

Stub Methods

Mixin Methods and Properties

IOBase

fileno, seek, et truncate

close, closed, __enter__, __exit__, flush, isatty, __iter__, __next__, readable, readline, readlines, seekable, tell, writable, and writelines

RawIOBase

IOBase

readinto et write

Inherited IOBase methods, read, and readall

BufferedIOBase

IOBase

detach, read, read1, et write

Inherited IOBase methods, readinto, and readinto1

TextIOBase

IOBase

detach, read, readline, et write

Inherited IOBase methods, encoding, errors, and newlines

16.2.3.1. I/O Base Classes

class io.IOBase

The abstract base class for all I/O classes, acting on streams of bytes. There is no public constructor.

This class provides empty abstract implementations for many methods that derived classes can override selectively; the default implementations represent a file that cannot be read, written or seeked.

Even though IOBase does not declare read(), readinto(), or write() because their signatures will vary, implementations and clients should consider those methods part of the interface. Also, implementations may raise a ValueError (or UnsupportedOperation) when operations they do not support are called.

The basic type used for binary data read from or written to a file is bytes. Other bytes-like objects are accepted as method arguments too. In some cases, such as readinto(), a writable object such as bytearray is required. Text I/O classes work with str data.

Note that calling any method (even inquiries) on a closed stream is undefined. Implementations may raise ValueError in this case.

IOBase (and its subclasses) supports the iterator protocol, meaning that an IOBase object can be iterated over yielding the lines in a stream. Lines are defined slightly differently depending on whether the stream is a binary stream (yielding bytes), or a text stream (yielding character strings). See readline() below.

IOBase is also a context manager and therefore supports the with statement. In this example, file is closed after the with statement’s suite is finished—even if an exception occurs:

with open('spam.txt', 'w') as file:
    file.write('Spam and eggs!')

IOBase provides these data attributes and methods:

close()

Flush and close this stream. This method has no effect if the file is already closed. Once the file is closed, any operation on the file (e.g. reading or writing) will raise a ValueError.

As a convenience, it is allowed to call this method more than once; only the first call, however, will have an effect.

closed

True if the stream is closed.

fileno()

Return the underlying file descriptor (an integer) of the stream if it exists. An OSError is raised if the IO object does not use a file descriptor.

flush()

Flush the write buffers of the stream if applicable. This does nothing for read-only and non-blocking streams.

isatty()

Return True if the stream is interactive (i.e., connected to a terminal/tty device).

readable()

Return True if the stream can be read from. If False, read() will raise OSError.

readline(size=-1)

Read and return one line from the stream. If size is specified, at most size bytes will be read.

The line terminator is always b'\n' for binary files; for text files, the newline argument to open() can be used to select the line terminator(s) recognized.

readlines(hint=-1)

Read and return a list of lines from the stream. hint can be specified to control the number of lines read: no more lines will be read if the total size (in bytes/characters) of all lines so far exceeds hint.

Note that it’s already possible to iterate on file objects using for line in file: ... without calling file.readlines().

seek(offset[, whence])

Change the stream position to the given byte offset. offset is interpreted relative to the position indicated by whence. The default value for whence is SEEK_SET. Values for whence are:

SEEK_SET or 0 – start of the stream (the default); offset should be zero or positive

SEEK_CUR or 1 – current stream position; offset may be negative

SEEK_END or 2 – end of the stream; offset is usually negative

Return the new absolute position.

Nouveau dans la version 3.1: The SEEK_* constants.

Nouveau dans la version 3.3: Some operating systems could support additional values, like os.SEEK_HOLE or os.SEEK_DATA. The valid values for a file could depend on it being open in text or binary mode.

seekable()

Return True if the stream supports random access. If False, seek(), tell() and truncate() will raise OSError.

tell()

Return the current stream position.

truncate(size=None)

Resize the stream to the given size in bytes (or the current position if size is not specified). The current stream position isn’t changed. This resizing can extend or reduce the current file size. In case of extension, the contents of the new file area depend on the platform (on most systems, additional bytes are zero-filled). The new file size is returned.

Modifié dans la version 3.5: Windows will now zero-fill files when extending.

writable()

Return True if the stream supports writing. If False, write() and truncate() will raise OSError.

writelines(lines)

Write a list of lines to the stream. Line separators are not added, so it is usual for each of the lines provided to have a line separator at the end.

__del__()

Prepare for object destruction. IOBase provides a default implementation of this method that calls the instance’s close() method.

class io.RawIOBase

Base class for raw binary I/O. It inherits IOBase. There is no public constructor.

Raw binary I/O typically provides low-level access to an underlying OS device or API, and does not try to encapsulate it in high-level primitives (this is left to Buffered I/O and Text I/O, described later in this page).

In addition to the attributes and methods from IOBase, RawIOBase provides the following methods:

read(size=-1)

Read up to size bytes from the object and return them. As a convenience, if size is unspecified or -1, all bytes until EOF are returned. Otherwise, only one system call is ever made. Fewer than size bytes may be returned if the operating system call returns fewer than size bytes.

If 0 bytes are returned, and size was not 0, this indicates end of file. If the object is in non-blocking mode and no bytes are available, None is returned.

The default implementation defers to readall() and readinto().

readall()

Read and return all the bytes from the stream until EOF, using multiple calls to the stream if necessary.

readinto(b)

Read bytes into a pre-allocated, writable bytes-like object b, and return the number of bytes read. If the object is in non-blocking mode and no bytes are available, None is returned.

write(b)

Write the given bytes-like object, b, to the underlying raw stream, and return the number of bytes written. This can be less than the length of b in bytes, depending on specifics of the underlying raw stream, and especially if it is in non-blocking mode. None is returned if the raw stream is set not to block and no single byte could be readily written to it. The caller may release or mutate b after this method returns, so the implementation should only access b during the method call.

class io.BufferedIOBase

Base class for binary streams that support some kind of buffering. It inherits IOBase. There is no public constructor.

The main difference with RawIOBase is that methods read(), readinto() and write() will try (respectively) to read as much input as requested or to consume all given output, at the expense of making perhaps more than one system call.

In addition, those methods can raise BlockingIOError if the underlying raw stream is in non-blocking mode and cannot take or give enough data; unlike their RawIOBase counterparts, they will never return None.

Besides, the read() method does not have a default implementation that defers to readinto().

A typical BufferedIOBase implementation should not inherit from a RawIOBase implementation, but wrap one, like BufferedWriter and BufferedReader do.

BufferedIOBase provides or overrides these methods and attribute in addition to those from IOBase:

raw

The underlying raw stream (a RawIOBase instance) that BufferedIOBase deals with. This is not part of the BufferedIOBase API and may not exist on some implementations.

detach()

Separate the underlying raw stream from the buffer and return it.

After the raw stream has been detached, the buffer is in an unusable state.

Some buffers, like BytesIO, do not have the concept of a single raw stream to return from this method. They raise UnsupportedOperation.

Nouveau dans la version 3.1.

read(size=-1)

Read and return up to size bytes. If the argument is omitted, None, or negative, data is read and returned until EOF is reached. An empty bytes object is returned if the stream is already at EOF.

If the argument is positive, and the underlying raw stream is not interactive, multiple raw reads may be issued to satisfy the byte count (unless EOF is reached first). But for interactive raw streams, at most one raw read will be issued, and a short result does not imply that EOF is imminent.

A BlockingIOError is raised if the underlying raw stream is in non blocking-mode, and has no data available at the moment.

read1(size=-1)

Read and return up to size bytes, with at most one call to the underlying raw stream’s read() (or readinto()) method. This can be useful if you are implementing your own buffering on top of a BufferedIOBase object.

readinto(b)

Read bytes into a pre-allocated, writable bytes-like object b and return the number of bytes read.

Like read(), multiple reads may be issued to the underlying raw stream, unless the latter is interactive.

A BlockingIOError is raised if the underlying raw stream is in non blocking-mode, and has no data available at the moment.

readinto1(b)

Read bytes into a pre-allocated, writable bytes-like object b, using at most one call to the underlying raw stream’s read() (or readinto()) method. Return the number of bytes read.

A BlockingIOError is raised if the underlying raw stream is in non blocking-mode, and has no data available at the moment.

Nouveau dans la version 3.5.

write(b)

Write the given bytes-like object, b, and return the number of bytes written (always equal to the length of b in bytes, since if the write fails an OSError will be raised). Depending on the actual implementation, these bytes may be readily written to the underlying stream, or held in a buffer for performance and latency reasons.

When in non-blocking mode, a BlockingIOError is raised if the data needed to be written to the raw stream but it couldn’t accept all the data without blocking.

The caller may release or mutate b after this method returns, so the implementation should only access b during the method call.

16.2.3.2. Raw File I/O

class io.FileIO(name, mode='r', closefd=True, opener=None)

FileIO represents an OS-level file containing bytes data. It implements the RawIOBase interface (and therefore the IOBase interface, too).

The name can be one of two things:

a character string or bytes object representing the path to the file which will be opened. In this case closefd must be True (the default) otherwise an error will be raised.

an integer representing the number of an existing OS-level file descriptor to which the resulting FileIO object will give access. When the FileIO object is closed this fd will be closed as well, unless closefd is set to False.

The mode can be 'r', 'w', 'x' or 'a' for reading (default), writing, exclusive creation or appending. The file will be created if it doesn’t exist when opened for writing or appending; it will be truncated when opened for writing. FileExistsError will be raised if it already exists when opened for creating. Opening a file for creating implies writing, so this mode behaves in a similar way to 'w'. Add a '+' to the mode to allow simultaneous reading and writing.

The read() (when called with a positive argument), readinto() and write() methods on this class will only make one system call.

Un opener personnalisé peut être utilisé en fournissant un appelable à opener. Le descripteur de fichier de cet objet fichier sera alors obtenu en appelant opener avec (file, flags). opener doit donner un descripteur de fichier ouvert (fournir os.open en temps qu”opener aura le même effet que donner None).

Il n’est pas possible d’hériter du fichier nouvellement créé.

See the open() built-in function for examples on using the opener parameter.

Modifié dans la version 3.3: The opener parameter was added. The 'x' mode was added.

Modifié dans la version 3.4: Il n’est plus possible d’hériter de file.

In addition to the attributes and methods from IOBase and RawIOBase, FileIO provides the following data attributes:

mode

The mode as given in the constructor.

name

The file name. This is the file descriptor of the file when no name is given in the constructor.

16.2.3.3. Buffered Streams

Buffered I/O streams provide a higher-level interface to an I/O device than raw I/O does.

class io.BytesIO([initial_bytes])

A stream implementation using an in-memory bytes buffer. It inherits BufferedIOBase. The buffer is discarded when the close() method is called.

The optional argument initial_bytes is a bytes-like object that contains initial data.

BytesIO provides or overrides these methods in addition to those from BufferedIOBase and IOBase:

getbuffer()

Return a readable and writable view over the contents of the buffer without copying them. Also, mutating the view will transparently update the contents of the buffer:

>>> b = io.BytesIO(b"abcdef")
>>> view = b.getbuffer()
>>> view[2:4] = b"56"
>>> b.getvalue()
b'ab56ef'

Note

As long as the view exists, the BytesIO object cannot be resized or closed.

Nouveau dans la version 3.2.

getvalue()

Return bytes containing the entire contents of the buffer.

read1()

In BytesIO, this is the same as read().

readinto1()

In BytesIO, this is the same as readinto().

Nouveau dans la version 3.5.

class io.BufferedReader(raw, buffer_size=DEFAULT_BUFFER_SIZE)

A buffer providing higher-level access to a readable, sequential RawIOBase object. It inherits BufferedIOBase. When reading data from this object, a larger amount of data may be requested from the underlying raw stream, and kept in an internal buffer. The buffered data can then be returned directly on subsequent reads.

The constructor creates a BufferedReader for the given readable raw stream and buffer_size. If buffer_size is omitted, DEFAULT_BUFFER_SIZE is used.

BufferedReader provides or overrides these methods in addition to those from BufferedIOBase and IOBase:

peek([size])

Return bytes from the stream without advancing the position. At most one single read on the raw stream is done to satisfy the call. The number of bytes returned may be less or more than requested.

read([size])

Read and return size bytes, or if size is not given or negative, until EOF or if the read call would block in non-blocking mode.

read1(size)

Read and return up to size bytes with only one call on the raw stream. If at least one byte is buffered, only buffered bytes are returned. Otherwise, one raw stream read call is made.

class io.BufferedWriter(raw, buffer_size=DEFAULT_BUFFER_SIZE)

A buffer providing higher-level access to a writeable, sequential RawIOBase object. It inherits BufferedIOBase. When writing to this object, data is normally placed into an internal buffer. The buffer will be written out to the underlying RawIOBase object under various conditions, including:

when the buffer gets too small for all pending data;

when flush() is called;

when a seek() is requested (for BufferedRandom objects);

when the BufferedWriter object is closed or destroyed.

The constructor creates a BufferedWriter for the given writeable raw stream. If the buffer_size is not given, it defaults to DEFAULT_BUFFER_SIZE.

BufferedWriter provides or overrides these methods in addition to those from BufferedIOBase and IOBase:

flush()

Force bytes held in the buffer into the raw stream. A BlockingIOError should be raised if the raw stream blocks.

write(b)

Write the bytes-like object, b, and return the number of bytes written. When in non-blocking mode, a BlockingIOError is raised if the buffer needs to be written out but the raw stream blocks.

class io.BufferedRandom(raw, buffer_size=DEFAULT_BUFFER_SIZE)

A buffered interface to random access streams. It inherits BufferedReader and BufferedWriter, and further supports seek() and tell() functionality.

The constructor creates a reader and writer for a seekable raw stream, given in the first argument. If the buffer_size is omitted it defaults to DEFAULT_BUFFER_SIZE.

BufferedRandom is capable of anything BufferedReader or BufferedWriter can do.

class io.BufferedRWPair(reader, writer, buffer_size=DEFAULT_BUFFER_SIZE)

A buffered I/O object combining two unidirectional RawIOBase objects – one readable, the other writeable – into a single bidirectional endpoint. It inherits BufferedIOBase.

reader and writer are RawIOBase objects that are readable and writeable respectively. If the buffer_size is omitted it defaults to DEFAULT_BUFFER_SIZE.

BufferedRWPair implements all of BufferedIOBase’s methods except for detach(), which raises UnsupportedOperation.

Avertissement

BufferedRWPair does not attempt to synchronize accesses to its underlying raw streams. You should not pass it the same object as reader and writer; use BufferedRandom instead.

16.2.3.4. Text I/O

class io.TextIOBase

Base class for text streams. This class provides a character and line based interface to stream I/O. There is no readinto() method because Python’s character strings are immutable. It inherits IOBase. There is no public constructor.

TextIOBase provides or overrides these data attributes and methods in addition to those from IOBase:

encoding

The name of the encoding used to decode the stream’s bytes into strings, and to encode strings into bytes.

errors

The error setting of the decoder or encoder.

newlines

A string, a tuple of strings, or None, indicating the newlines translated so far. Depending on the implementation and the initial constructor flags, this may not be available.

buffer

The underlying binary buffer (a BufferedIOBase instance) that TextIOBase deals with. This is not part of the TextIOBase API and may not exist in some implementations.

detach()

Separate the underlying binary buffer from the TextIOBase and return it.

After the underlying buffer has been detached, the TextIOBase is in an unusable state.

Some TextIOBase implementations, like StringIO, may not have the concept of an underlying buffer and calling this method will raise UnsupportedOperation.

Nouveau dans la version 3.1.

read(size=-1)

Read and return at most size characters from the stream as a single str. If size is negative or None, reads until EOF.

readline(size=-1)

Read until newline or EOF and return a single str. If the stream is already at EOF, an empty string is returned.

If size is specified, at most size characters will be read.

seek(offset[, whence])

Change the stream position to the given offset. Behaviour depends on the whence parameter. The default value for whence is SEEK_SET.

SEEK_SET or 0: seek from the start of the stream (the default); offset must either be a number returned by TextIOBase.tell(), or zero. Any other offset value produces undefined behaviour.

SEEK_CUR or 1: « seek » to the current position; offset must be zero, which is a no-operation (all other values are unsupported).

SEEK_END or 2: seek to the end of the stream; offset must be zero (all other values are unsupported).

Return the new absolute position as an opaque number.

Nouveau dans la version 3.1: The SEEK_* constants.

tell()

Return the current stream position as an opaque number. The number does not usually represent a number of bytes in the underlying binary storage.

write(s)

Write the string s to the stream and return the number of characters written.

class io.TextIOWrapper(buffer, encoding=None, errors=None, newline=None, line_buffering=False, write_through=False)

A buffered text stream over a BufferedIOBase binary stream. It inherits TextIOBase.

encoding gives the name of the encoding that the stream will be decoded or encoded with. It defaults to locale.getpreferredencoding(False).

errors is an optional string that specifies how encoding and decoding errors are to be handled. Pass 'strict' to raise a ValueError exception if there is an encoding error (the default of None has the same effect), or pass 'ignore' to ignore errors. (Note that ignoring encoding errors can lead to data loss.) 'replace' causes a replacement marker (such as '?') to be inserted where there is malformed data. 'backslashreplace' causes malformed data to be replaced by a backslashed escape sequence. When writing, 'xmlcharrefreplace' (replace with the appropriate XML character reference) or 'namereplace' (replace with \N{...} escape sequences) can be used. Any other error handling name that has been registered with codecs.register_error() is also valid.

newline controls how line endings are handled. It can be None, '', '\n', '\r', and '\r\n'. It works as follows:

Lors de la lecture, si newline est None, le mode universal newlines est activé. Les lignes lues peuvent terminer par '\n', '\r', ou '\r\n', qui sont remplacés par '\n', avant d’être données à l’appelant. S’il vaut '', le mode universal newline est activé mais les fin de lignes ne sont pas remplacés. S’il a n’importe quel autre valeur autorisée, les lignes sont seulement terminées par la chaîne donnée, qui est rendue tel qu’elle.

Lors de l’écriture, si newline est None, chaque '\n' est remplacé par le séparateur de lignes par défaut du système os.linesep. Si newline est * ou '\n' aucun remplacent n’est effectué. Si newline est un autre caractère valide, chaque '\n' sera remplacé par la chaîne donnée.

If line_buffering is True, flush() is implied when a call to write contains a newline character or a carriage return.

If write_through is True, calls to write() are guaranteed not to be buffered: any data written on the TextIOWrapper object is immediately handled to its underlying binary buffer.

Modifié dans la version 3.3: The write_through argument has been added.

Modifié dans la version 3.3: The default encoding is now locale.getpreferredencoding(False) instead of locale.getpreferredencoding(). Don’t change temporary the locale encoding using locale.setlocale(), use the current locale encoding instead of the user preferred encoding.

TextIOWrapper provides one attribute in addition to those of TextIOBase and its parents:

line_buffering

Whether line buffering is enabled.

class io.StringIO(initial_value='', newline='\n')

An in-memory stream for text I/O. The text buffer is discarded when the close() method is called.

The initial value of the buffer can be set by providing initial_value. If newline translation is enabled, newlines will be encoded as if by write(). The stream is positioned at the start of the buffer.

The newline argument works like that of TextIOWrapper. The default is to consider only \n characters as ends of lines and to do no newline translation. If newline is set to None, newlines are written as \n on all platforms, but universal newline decoding is still performed when reading.

StringIO provides this method in addition to those from TextIOBase and its parents:

getvalue()

Return a str containing the entire contents of the buffer. Newlines are decoded as if by read(), although the stream position is not changed.

Exemple d’utilisation :

import io

output = io.StringIO()
output.write('First line.\n')
print('Second line.', file=output)

# Retrieve file contents -- this will be
# 'First line.\nSecond line.\n'
contents = output.getvalue()

# Close object and discard memory buffer --
# .getvalue() will now raise an exception.
output.close()

class io.IncrementalNewlineDecoder

A helper codec that decodes newlines for universal newlines mode. It inherits codecs.IncrementalDecoder.

16.2.4. Performances

This section discusses the performance of the provided concrete I/O implementations.

16.2.4.1. Binary I/O

By reading and writing only large chunks of data even when the user asks for a single byte, buffered I/O hides any inefficiency in calling and executing the operating system’s unbuffered I/O routines. The gain depends on the OS and the kind of I/O which is performed. For example, on some modern OSes such as Linux, unbuffered disk I/O can be as fast as buffered I/O. The bottom line, however, is that buffered I/O offers predictable performance regardless of the platform and the backing device. Therefore, it is almost always preferable to use buffered I/O rather than unbuffered I/O for binary data.

16.2.4.2. Text I/O

Text I/O over a binary storage (such as a file) is significantly slower than binary I/O over the same storage, because it requires conversions between unicode and binary data using a character codec. This can become noticeable handling huge amounts of text data like large log files. Also, TextIOWrapper.tell() and TextIOWrapper.seek() are both quite slow due to the reconstruction algorithm used.

StringIO, however, is a native in-memory unicode container and will exhibit similar speed to BytesIO.

16.2.4.3. Fils d’exécution

FileIO objects are thread-safe to the extent that the operating system calls (such as read(2) under Unix) they wrap are thread-safe too.

Binary buffered objects (instances of BufferedReader, BufferedWriter, BufferedRandom and BufferedRWPair) protect their internal structures using a lock; it is therefore safe to call them from multiple threads at once.

TextIOWrapper objects are not thread-safe.

16.2.4.4. Reentrancy

Binary buffered objects (instances of BufferedReader, BufferedWriter, BufferedRandom and BufferedRWPair) are not reentrant. While reentrant calls will not happen in normal situations, they can arise from doing I/O in a signal handler. If a thread tries to re-enter a buffered object which it is already accessing, a RuntimeError is raised. Note this doesn’t prohibit a different thread from entering the buffered object.

The above implicitly extends to text files, since the open() function will wrap a buffered object inside a TextIOWrapper. This includes standard streams and therefore affects the built-in function print() as well.

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16.3. time — Accès au temps et conversions

Ce module fournit différentes fonctions liées au temps. Pour les fonctionnalités associées, voir aussi les modules datetime et calendar.

Bien que ce module soit toujours disponible, toutes les fonctions ne sont pas disponibles sur toutes les plateformes. La plupart des fonctions définies dans ce module délèguent à des fonctions de même nom de la bibliothèque C. Il peut parfois être utile de consulter la documentation de la plate-forme, car la sémantique de ces fonctions peut varier.

Vous trouvez ci-dessous, mises en ordre, quelques explications relative à la terminologie et aux conventions.

L”epoch est le point de départ du temps et dépend de la plate-forme. Pour Unix, epoch est le 1er janvier 1970 à 00:00:00 (UTC). Pour savoir comment est définie epoch sur une plate-forme donnée, regardez time.gmtime(0).

Le terme secondes depuis *epoch* désigne le nombre total de secondes écoulées depuis epoch, souvent en excluant les secondes intercalaires (leap seconds [https://en.wikipedia.org/wiki/Leap_second]). Les secondes intercalaires sont exclues de ce total sur toutes les plates-formes conformes POSIX.

Les fonctions de ce module peuvent ne pas gérer les dates et heures antérieures à epoch ou dans un avenir lointain. Le seuil du futur est déterminé par la bibliothèque C ; pour les systèmes 32 bits, il s’agit généralement de 2038.

Problèmes liés à l’an 2000 (Y2K) : Python dépend de la bibliothèque C de la plate-forme, qui n’a généralement pas de problèmes liés à l’an 2000, étant donné que toutes les dates et heures sont représentées en interne en secondes depuis epoch. La fonction strptime() peut analyser des années à 2 chiffres lorsque le format %y est spécifié. Lorsque les années à deux chiffres sont analysées, elles sont converties conformément aux normes POSIX et ISO C : les valeurs 69—99 correspondent à 1969—1999 et les valeurs 0—68 à 2000—2068.

UTC désigne le temps universel coordonné (Coordinated Universal Time en anglais), anciennement l’heure de Greenwich (ou GMT). L’acronyme UTC n’est pas une erreur mais un compromis entre l’anglais et le français.

Le DST (Daylight Saving Time) correspond à l’heure d’été, un ajustement du fuseau horaire d’une heure (généralement) pendant une partie de l’année. Les règles de DST sont magiques (déterminées par la loi locale) et peuvent changer d’année en année. La bibliothèque C possède une table contenant les règles locales (souvent, elle est lue dans un fichier système par souci de souplesse) et constitue la seule source fiable.

La précision des diverses fonctions en temps réel peut être inférieure à celle suggérée par les unités dans lesquelles leur valeur ou leur argument est exprimé. Par exemple, sur la plupart des systèmes Unix, l’horloge ne « bat » que 50 ou 100 fois par seconde.

D’autre part, la précision de time() et sleep() est meilleure que leurs équivalents Unix : les temps sont exprimés en nombres à virgule flottante, time() renvoie le temps le plus précis disponible (en utilisant gettimeofday() d’Unix si elle est disponible), et sleep() accepte le temps avec une fraction non nulle (select() d’Unix est utilisée pour l’implémenter, si elle est disponible).

La valeur temporelle renvoyée par gmtime(), localtime() et strptime(), et acceptée par asctime(), mktime() et strftime(), est une séquence de 9 nombres entiers. Les valeurs de retour de gmtime(), localtime() et strptime() proposent également des noms d’attributs pour des champs individuels.

Voir struct_time pour une description de ces objets.

Modifié dans la version 3.3: Le type struct_time a été étendu pour fournir les attributs tm_gmtoff et tm_zone lorsque la plateforme prend en charge les membres struct tm correspondants.

Modifié dans la version 3.6: Les attributs struct_time tm_gmtoff et tm_zone sont maintenant disponibles sur toutes les plateformes.

Utilisez les fonctions suivantes pour convertir des représentations temporelles :

De

À

Utilisez

secondes depuis epoch

struct_time en UTC

gmtime()

secondes depuis epoch

struct_time en heure locale

localtime()

struct_time en UTC

secondes depuis epoch

calendar.timegm()

struct_time en heure locale

secondes depuis epoch

mktime()

16.3.1. Fonctions

time.asctime([t])

Convertit un tuple ou struct_time représentant une heure renvoyée par gmtime() ou localtime() en une chaîne de la forme suivante : 'Sun Jun 20 23:21:05 1993'. Si t n’est pas fourni, l’heure actuelle renvoyée par localtime() est utilisée. Les informations sur les paramètres régionaux ne sont pas utilisées par asctime().

Note

Contrairement à la fonction C du même nom, asctime() n’ajoute pas de caractère de fin de ligne.

time.clock()

Sous UNIX, renvoie le temps processeur actuel, en secondes, sous la forme d’un nombre à virgule flottante exprimé en secondes. La précision, et en fait la définition même de la signification de « temps processeur », dépend de celle de la fonction C du même nom.

Sous Windows, cette fonction renvoie les secondes réelles (type horloge murale) écoulées depuis le premier appel à cette fonction, en tant que nombre à virgule flottante, en fonction de la fonction Win32 QueryPerformanceCounter(). La résolution est généralement meilleure qu’une microseconde.

Obsolète depuis la version 3.3: Le comportement de cette fonction dépend de la plate-forme : utilisez plutôt perf_counter() ou process_time(), selon vos besoins, pour avoir un comportement bien défini.

time.clock_getres(clk_id)

Renvoie la résolution (précision) de l’horloge clk_id. Référez-vous à Constantes d’identification d’horloge pour une liste des valeurs acceptées pour clk_id.

Disponibilité : Unix.

Nouveau dans la version 3.3.

time.clock_gettime(clk_id)

Renvoie l’heure de l’horloge clk_id. Référez-vous à Constantes d’identification d’horloge pour une liste des valeurs acceptées pour clk_id.

Disponibilité : Unix.

Nouveau dans la version 3.3.

time.clock_settime(clk_id, time)

Définit l’heure de l’horloge clk_id. Actuellement, CLOCK_REALTIME est la seule valeur acceptée pour clk_id.

Disponibilité : Unix.

Nouveau dans la version 3.3.

time.ctime([secs])

Convertit une heure exprimée en secondes depuis epoch en une chaîne représentant l’heure locale. Si secs n’est pas fourni ou vaut None, l’heure actuelle renvoyée par time() est utilisée. ctime(secs) est équivalent à asctime(localtime(secs)). Les informations sur les paramètres régionaux ne sont pas utilisées par ctime().

time.get_clock_info(name)

Renvoie des informations sur l’horloge spécifiée en tant qu’objet d’espace de nom. Les noms d’horloge pris en charge et les fonctions correspondantes permettant de lire leur valeur sont les suivants :

'clock': time.clock()

'monotonic': time.monotonic()

'perf_counter': time.perf_counter()

'process_time': time.process_time()

'time': time.time()

Le résultat a les attributs suivants :

adjustable : True si l’horloge peut être changée automatiquement (par exemple par un démon NTP) ou manuellement par l’administrateur système, False autrement

implementation : nom de la fonction C sous-jacente utilisée pour obtenir la valeur d’horloge. Voir Constantes d’identification d’horloge pour les valeurs possibles.

monotonic : True si l’horloge ne peut pas revenir en arrière, False autrement

resolution : La résolution de l’horloge en secondes (float)

Nouveau dans la version 3.3.

time.gmtime([secs])

Convertit un temps exprimé en secondes depuis epoch en un struct_time au format UTC dans lequel le drapeau dst est toujours égal à zéro. Si secs n’est pas fourni ou vaut None, l’heure actuelle renvoyée par time() est utilisée. Les fractions de seconde sont ignorées. Voir ci-dessus pour une description de l’objet struct_time. Voir calendar.timegm() pour l’inverse de cette fonction.

time.localtime([secs])

Comme gmtime() mais convertit le résultat en heure locale. Si secs n’est pas fourni ou vaut None, l’heure actuelle renvoyée par time() est utilisée. Le drapeau dst est mis à 1 lorsque l’heure d’été s’applique à l’heure indiquée.

time.mktime(t)

C’est la fonction inverse de localtime(). Son argument est soit un struct_time soit un 9-tuple (puisque le drapeau dst est nécessaire ; utilisez -1 comme drapeau dst s’il est inconnu) qui exprime le temps local, pas UTC. Il retourne un nombre à virgule flottante, pour compatibilité avec time(). Si la valeur d’entrée ne peut pas être représentée comme une heure valide, soit OverflowError ou ValueError sera levée (selon que la valeur non valide est interceptée par Python ou par les bibliothèque C sous-jacentes). La date la plus proche pour laquelle il peut générer une heure dépend de la plate-forme.

time.monotonic()

Renvoie la valeur (en quelques fractions de secondes) d’une horloge monotone, c’est-à-dire une horloge qui ne peut pas revenir en arrière. L’horloge n’est pas affectée par les mises à jour de l’horloge système. Le point de référence de la valeur renvoyée n’est pas défini, de sorte que seule la différence entre les résultats d’appels consécutifs est valide.

On Windows versions older than Vista, monotonic() detects GetTickCount() integer overflow (32 bits, roll-over after 49.7 days). It increases an internal epoch (reference time) by 2³² each time that an overflow is detected. The epoch is stored in the process-local state and so the value of monotonic() may be different in two Python processes running for more than 49 days. On more recent versions of Windows and on other operating systems, monotonic() is system-wide.

Nouveau dans la version 3.3.

Modifié dans la version 3.5: The function is now always available.

time.perf_counter()

Renvoie la valeur (en quelques fractions de secondes) d’un compteur de performance, c’est-à-dire une horloge avec la résolution disponible la plus élevée possible pour mesurer une courte durée. Cela inclut le temps écoulé pendant le sommeil et concerne l’ensemble du système. Le point de référence de la valeur renvoyée n’est pas défini, de sorte que seule la différence entre les résultats d’appels consécutifs est valide.

Nouveau dans la version 3.3.

time.process_time()

Renvoie la valeur (en quelques fractions de secondes) de la somme des temps système et utilisateur du processus en cours. Il ne comprend pas le temps écoulé pendant le sommeil. C’est un processus par définition. Le point de référence de la valeur renvoyée n’est pas défini, de sorte que seule la différence entre les résultats d’appels consécutifs est valide.

Nouveau dans la version 3.3.

time.sleep(secs)

Suspend l’exécution du thread appelant pendant le nombre de secondes indiqué. L’argument peut être un nombre à virgule flottante pour indiquer un temps de sommeil plus précis. Le temps de suspension réel peut être inférieur à celui demandé, car tout signal capturé mettra fin à la commande sleep() après l’exécution de la routine de capture de ce signal. En outre, le temps de suspension peut être plus long que celui demandé par un montant arbitraire en raison de la planification d’une autre activité dans le système.

Modifié dans la version 3.5: La fonction dort maintenant au moins secondes même si le sommeil est interrompu par un signal, sauf si le gestionnaire de signaux lève une exception (voir PEP 475 [https://www.python.org/dev/peps/pep-0475] pour la justification).

time.strftime(format[, t])

Convertit un tuple ou struct_time représentant une heure renvoyée par gmtime() ou localtime() en une chaîne spécifiée par l’argument format. Si t n’est pas fourni, l’heure actuelle renvoyée par localtime() est utilisée. format doit être une chaîne. Si l’un des champs de t se situe en dehors de la plage autorisée, une ValueError est levée .

0 est un argument légal pour toute position dans le tuple temporel ; s’il est normalement illégal, la valeur est forcée à une valeur correcte.

Les directives suivantes peuvent être incorporées dans la chaîne format. Ils sont affichés sans la spécification facultative de largeur de champ ni de précision, et sont remplacés par les caractères indiqués dans le résultat de strftime() :

Directive

Signification

Notes

%a

Nom abrégé du jour de la semaine selon les paramètres régionaux.

%A

Le nom de semaine complet de la région.

%b

Nom abrégé du mois de la région.

%B

Nom complet du mois de la région.

%c

Représentation appropriée de la date et de l’heure selon les paramètres régionaux.

%d

Jour du mois sous forme décimale [01,31].

%H

Heure (horloge sur 24 heures) sous forme de nombre décimal [00,23].

%I

Heure (horloge sur 12 heures) sous forme de nombre décimal [01,12].

%j

Jour de l’année sous forme de nombre décimal [001,366].

%m

Mois sous forme décimale [01,12].

%M

Minutes sous forme décimale [00,59].

%p

L’équivalent local de AM ou PM.

(1)

%S

Deuxième sous forme de nombre décimal [00,61].

(2)

%U

Numéro de semaine de l’année (dimanche en tant que premier jour de la semaine) sous forme décimale [00,53]. Tous les jours d’une nouvelle année précédant le premier dimanche sont considérés comme appartenant à la semaine 0.

(3)

%w

Jour de la semaine sous forme de nombre décimal [0 (dimanche), 6].

%W

Numéro de semaine de l’année (lundi comme premier jour de la semaine) sous forme décimale [00,53]. Tous les jours d’une nouvelle année précédant le premier lundi sont considérés comme appartenant à la semaine 0.

(3)

%x

Représentation de la date appropriée par les paramètres régionaux.

%X

Représentation locale de l’heure.

%y

Année sans siècle comme un nombre décimal [00, 99].

%Y

Année complète sur quatre chiffres.

%z

Décalage de fuseau horaire indiquant une différence de temps positive ou négative par rapport à UTC / GMT de la forme +HHMM ou -HHMM, où H représente les chiffres des heures décimales et M, les chiffres des minutes décimales [-23:59, +23:59].

%Z

Nom du fuseau horaire (pas de caractères s’il n’y a pas de fuseau horaire).

%%

Un caractère '%' littéral.

Notes :

Lorsqu’elle est utilisée avec la fonction strptime(), la directive %p n’affecte le champ d’heure en sortie que si la directive %I est utilisée pour analyser l’heure.

La plage est en réalité de 0 à 61 ; La valeur 60 est valide dans les timestamps représentant des leap seconds [https://en.wikipedia.org/wiki/Leap_second] et la valeur 61 est prise en charge pour des raisons historiques.

Lorsqu’elles sont utilisées avec la fonction strptime(), %U et %W ne sont utilisées que dans les calculs lorsque le jour de la semaine et l’année sont spécifiés.

Voici un exemple de format de date compatible avec celui spécifié dans la norme de courrier électronique Internet suivante RFC 2822 [https://tools.ietf.org/html/rfc2822.html]. 1

>>> from time import gmtime, strftime
>>> strftime("%a, %d %b %Y %H:%M:%S +0000", gmtime())
'Thu, 28 Jun 2001 14:17:15 +0000'

Des directives supplémentaires peuvent être prises en charge sur certaines plates-formes, mais seules celles énumérées ici ont une signification normalisée par ANSI C. Pour voir la liste complète des codes de format pris en charge sur votre plate-forme, consultez la documentation strftime(3).

Sur certaines plates-formes, une spécification facultative de largeur et de précision de champ peut suivre immédiatement le '%' initial d’une directive dans l’ordre suivant ; ce n’est pas non plus portable. La largeur du champ est normalement 2 sauf pour %j où il est 3.

time.strptime(string[, format])

Analyse une chaîne représentant une heure selon un format. La valeur renvoyée est une struct_time tel que renvoyé par gmtime() ou localtime().

Le paramètre format utilise les mêmes directives que celles utilisées par strftime(); La valeur par défaut est "%a %b %d %H:%M:%S %Y" qui correspond à la mise en forme renvoyée par ctime(). Si string ne peut pas être analysé selon format, ou s’il contient trop de données après l’analyse, une exception ValueError est levée. Les valeurs par défaut utilisées pour renseigner les données manquantes lorsque des valeurs plus précises ne peuvent pas être inférées sont (1900, 1, 1, 0, 0, 0, 0, 1, -1). string et format doivent être des chaînes.

Par exemple :

>>> import time
>>> time.strptime("30 Nov 00", "%d %b %y")
time.struct_time(tm_year=2000, tm_mon=11, tm_mday=30, tm_hour=0, tm_min=0,
                 tm_sec=0, tm_wday=3, tm_yday=335, tm_isdst=-1)

La prise en charge de la directive %Z est basée sur les valeurs contenues dans tzname et sur le fait de savoir si daylight est vrai. Pour cette raison, il est spécifique à la plate-forme, à l’exception de la reconnaissance des heures UTC et GMT, qui sont toujours connues (et considérées comme des fuseaux horaires ne respectant pas l’heure d’été).

Seules les directives spécifiées dans la documentation sont prises en charge. Parce que strftime() peut être implémenté différemment sur chaque plate-forme, il peut parfois offrir plus de directives que celles listées. Mais strptime() est indépendant de toute plate-forme et ne supporte donc pas nécessairement toutes les directives disponibles qui ne sont pas documentées comme gérées.

class time.struct_time

Le type de la séquence de valeur temporelle renvoyé par gmtime(), localtime() et strptime(). Semblable à un named tuple : ses valeurs sont accessibles par index et par nom d’attribut. Les valeurs suivantes sont présentes :

Index

Attribut

Valeurs

0

tm_year

(par exemple, 1993)

1

tm_mon

plage [1, 12]

2

tm_mday

plage [1, 31]

3

tm_hour

plage [0, 23]

4

tm_min

plage [0, 59]

5

tm_sec

plage [0, 61]; voir (2) dans la description strftime()

6

tm_wday

plage [0, 6], Lundi valant 0

7

tm_yday

plage [1, 366]

8

tm_isdst

0, 1 or -1 ; voir en bas

N/A

tm_zone

abréviation du nom du fuseau horaire

N/A

tm_gmtoff

décalage à l’est de UTC en secondes

Notez que contrairement à la structure C, la valeur du mois est une plage de [1, 12], pas de [0, 11].

Dans les appels à mktime(), tm_isdst peut être défini sur 1 lorsque l’heure d’été est en vigueur et sur 0 lorsque ce n’est pas le cas. Une valeur de -1 indique que cela n’est pas connu et entraînera généralement le remplissage de l’état correct.

Lorsqu’un tuple de longueur incorrecte est passé à une fonction acceptant une struct_time, ou comportant des éléments de type incorrect, une exception TypeError est levé.

time.time()

Renvoie le temps en secondes depuis epoch sous forme de nombre à virgule flottante. La date spécifique de epoch et le traitement des secondes intercalaires (leap seconds [https://en.wikipedia.org/wiki/Leap_second]) dépendent de la plate-forme. Sous Windows et la plupart des systèmes Unix, epoch est le 1er janvier 1970, 00:00:00 (UTC) et les secondes intercalaires ne sont pas comptées dans le temps en secondes depuis epoch. Ceci est communément appelé Heure Unix [https://en.wikipedia.org/wiki/Unix_time]. Pour savoir quelle est epoch sur une plate-forme donnée, consultez gmtime(0).

Notez que même si l’heure est toujours renvoyée sous forme de nombre à virgule flottante, tous les systèmes ne fournissent pas l’heure avec une précision supérieure à 1 seconde. Bien que cette fonction renvoie normalement des valeurs croissantes, elle peut renvoyer une valeur inférieure à celle d’un appel précédent si l’horloge système a été réglée entre les deux appels.

Le nombre renvoyé par time() peut être converti en un format d’heure plus courant (année, mois, jour, heure, etc.) en UTC en le transmettant à la fonction gmtime() ou dans heure locale en le transmettant à la fonction localtime(). Dans les deux cas, un objet struct_time est renvoyé, à partir duquel les composants de la date du calendrier peuvent être consultés en tant qu’attributs.

time.tzset()

Resets the time conversion rules used by the library routines. The environment variable TZ specifies how this is done.

Disponibilité : Unix.

Note

Bien que dans de nombreux cas, la modification de la variable d’environnement TZ puisse affecter la sortie de fonctions telles que localtime() sans appeler tzset(), ce comportement n’est pas garanti.

La variable d’environnement TZ ne doit contenir aucun espace.

Le format standard de la variable d’environnement TZ est (espaces ajoutés pour plus de clarté) :

std offset [dst [offset [,start[/time], end[/time]]]]

Où les composants sont :

std et dst

Trois alphanumériques ou plus donnant les abréviations du fuseau horaire. Ceux-ci seront propagés dans time.tzname

offset

Le décalage a la forme suivante : ± hh[:mm[:ss]]. Cela indique la valeur ajoutée à l’heure locale pour arriver à UTC. S’il est précédé d’un '-', le fuseau horaire est à l’est du Premier Méridien ; sinon, c’est l’ouest. Si aucun décalage ne suit dst, l’heure d’été est supposée être en avance d’une heure sur l’heure standard.

start[/time], end[/time]

Indique quand passer à DST et en revenir. Le format des dates de début et de fin est l’un des suivants :

Jn

Le jour Julien n (1 <= n <= 365). Les jours bissextiles ne sont pas comptabilisés. Par conséquent, le 28 février est le 59e jour et le 1er Mars est le 60e jour de toutes les années.

n

Le jour Julien de base zéro (0 <= n <= 365). Les jours bissextiles sont comptés et il est possible de se référer au 29 février.

Mm.n.d

Le d jour (0 <= d <= 6) de la semaine n du mois m de l’année (1 <= n <= 5, 1 <= m <= 12, où semaine 5 signifie “le dernier jour du mois m” pouvant se produire au cours de la quatrième ou de la cinquième semaine). La semaine 1 est la première semaine au cours de laquelle le jour se produit. Le jour zéro est un dimanche.

time a le même format que offset sauf qu’aucun signe de direction ('-' ou '+') n’est autorisé. La valeur par défaut, si l’heure n’est pas spécifiée, est 02:00:00.

>>> os.environ['TZ'] = 'EST+05EDT,M4.1.0,M10.5.0'
>>> time.tzset()
>>> time.strftime('%X %x %Z')
'02:07:36 05/08/03 EDT'
>>> os.environ['TZ'] = 'AEST-10AEDT-11,M10.5.0,M3.5.0'
>>> time.tzset()
>>> time.strftime('%X %x %Z')
'16:08:12 05/08/03 AEST'

Sur de nombreux systèmes Unix (y compris *BSD, Linux, Solaris et Darwin), il est plus pratique d’utiliser la base de données zoneinfo (tzfile (5)) du système pour spécifier les règles de fuseau horaire. Pour ce faire, définissez la variable d’environnement TZ sur le chemin du fichier de fuseau horaire requis, par rapport à la racine de la base de données du système zoneinfo, généralement situé à /usr/share/zoneinfo. Par exemple, 'US/Eastern', 'Australia/Melbourne', 'Egypt' ou 'Europe/Amsterdam'.

>>> os.environ['TZ'] = 'US/Eastern'
>>> time.tzset()
>>> time.tzname
('EST', 'EDT')
>>> os.environ['TZ'] = 'Egypt'
>>> time.tzset()
>>> time.tzname
('EET', 'EEST')

16.3.2. Constantes d’identification d’horloge

Ces constantes sont utilisées comme paramètres pour clock_getres() et clock_gettime().

time.CLOCK_HIGHRES

Le système d’exploitation Solaris dispose d’une horloge CLOCK_HIGHRES qui tente d’utiliser une source matérielle optimale et peut donner une résolution proche de la nanoseconde. CLOCK_HIGHRES est l’horloge haute résolution non ajustable.

Availability: Solaris.

Nouveau dans la version 3.3.

time.CLOCK_MONOTONIC

Horloge qui ne peut pas être réglée et représente l’heure monotone depuis un point de départ non spécifié.

Disponibilité : Unix.

Nouveau dans la version 3.3.

time.CLOCK_MONOTONIC_RAW

Similaire à CLOCK_MONOTONIC, mais donne accès à une heure matérielle brute qui n’est pas soumise aux ajustements NTP.

Availability: Linux 2.6.28 or later.

Nouveau dans la version 3.3.

time.CLOCK_PROCESS_CPUTIME_ID

Minuterie haute résolution par processus du CPU.

Disponibilité : Unix.

Nouveau dans la version 3.3.

time.CLOCK_THREAD_CPUTIME_ID

Horloge de temps CPU spécifique au thread.

Disponibilité : Unix.

Nouveau dans la version 3.3.

La constante suivante est le seul paramètre pouvant être envoyé à clock_settime().

time.CLOCK_REALTIME

Horloge en temps réel à l’échelle du système. Le réglage de cette horloge nécessite des privilèges appropriés.

Disponibilité : Unix.

Nouveau dans la version 3.3.

16.3.3. Constantes de fuseau horaire

time.altzone

Décalage du fuseau horaire DST local, en secondes à l’ouest de UTC, s’il en est défini un. Cela est négatif si le fuseau horaire DST local est à l’est de UTC (comme en Europe occidentale, y compris le Royaume-Uni). Utilisez ceci uniquement si daylight est différent de zéro. Voir note ci-dessous.

time.daylight

Non nul si un fuseau horaire DST est défini. Voir note ci-dessous.

time.timezone

Décalage du fuseau horaire local (hors heure d’été), en secondes à l’ouest de l’UTC (négatif dans la plupart des pays d’Europe occidentale, positif aux États-Unis, nul au Royaume-Uni). Voir note ci-dessous.

time.tzname

Un tuple de deux chaînes : la première est le nom du fuseau horaire local autre que DST, la seconde est le nom du fuseau horaire DST local. Si aucun fuseau horaire DST n’est défini, la deuxième chaîne ne doit pas être utilisée. Voir note ci-dessous.

Note

Pour les constantes de fuseau horaire ci-dessus ( altzone, daylight, timezone et tzname), la valeur est déterminée par les règles de fuseau horaire en vigueur au moment du chargement du module ou la dernière fois tzset() est appelé et peut être incorrect pour des temps passés. Il est recommandé d’utiliser tm_gmtoff et tm_zone résulte de localtime() pour obtenir des informations sur le fuseau horaire.

Voir aussi

Module datetime

Interface plus orientée objet vers les dates et les heures.

Module locale

Services d’internationalisation. Les paramètres régionaux affectent l’interprétation de nombreux spécificateurs de format dans strftime() et strptime().

Module calendar

Fonctions générales liées au calendrier. timegm() est l’inverse de gmtime() à partir de ce module.

Notes

1

L’utilisation de %Z est maintenant obsolète, mais l’échappement %z qui donne le décalage horaire jusqu’à la minute et dépendant des paramètres régionaux n’est pas pris en charge par toutes les bibliothèques C ANSI. En outre, une lecture stricte du standard RFC 822 [https://tools.ietf.org/html/rfc822.html] de 1982 milite pour une année à deux chiffres (%y plutôt que %Y), mais la pratique a migré vers des années à 4 chiffres de long avant l’année 2000. Après cela, la RFC 822 [https://tools.ietf.org/html/rfc822.html] est devenue obsolète et l’année à 4 chiffres a été recommandée pour la première fois par la RFC 1123 [https://tools.ietf.org/html/rfc1123.html] puis rendue obligatoire par la RFC 2822 [https://tools.ietf.org/html/rfc2822.html].

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16.4. argparse – Parseur d’arguments, d’options, et de sous-commandes de ligne de commande

Nouveau dans la version 3.2.

Code source: Lib/argparse.py [https://github.com/python/cpython/tree/3.6/Lib/argparse.py]

Tutoriel

Cette page est la référence de l’API. Pour une introduction plus en douceur à l’analyse des arguments de la ligne de commande, regardez le tutoriel argparse.

Le module argparse facilite l’écriture d’interfaces en ligne de commande agréables à l’emploi. Le programme définit les arguments requis et argparse s’arrange pour analyser ceux provenant de sys.argv. Le module argparse génère aussi automatiquement les messages d’aide, le mode d’emploi, et lève des erreurs lorsque les utilisateurs fournissent au programme des arguments invalides.

16.4.1. Exemple

Le code suivant est un programme Python acceptant une liste de nombre entiers et en donnant soit la somme, soit le maximum :

import argparse

parser = argparse.ArgumentParser(description='Process some integers.')
parser.add_argument('integers', metavar='N', type=int, nargs='+',
                    help='an integer for the accumulator')
parser.add_argument('--sum', dest='accumulate', action='store_const',
                    const=sum, default=max,
                    help='sum the integers (default: find the max)')

args = parser.parse_args()
print(args.accumulate(args.integers))

En supposant que le code Python ci-dessus est sauvegardé dans un fichier nommé prog.py, il peut être lancé en ligne de commande et fournit des messages d’aide utiles :

$ python prog.py -h
usage: prog.py [-h] [--sum] N [N ...]

Process some integers.

positional arguments:
 N           an integer for the accumulator

optional arguments:
 -h, --help  show this help message and exit
 --sum       sum the integers (default: find the max)

Lorsqu’il est lancé avec les arguments appropriés, il affiche la somme ou le maximum des entiers fournis en ligne de commande :

$ python prog.py 1 2 3 4
4

$ python prog.py 1 2 3 4 --sum
10

Si des arguments invalides sont passés, il lève une erreur :

$ python prog.py a b c
usage: prog.py [-h] [--sum] N [N ...]
prog.py: error: argument N: invalid int value: 'a'

Les sections suivantes vous guident au travers de cet exemple.

16.4.1.1. Créer un analyseur (parser en anglais)

La première étape dans l’utilisation de argparse est de créer un objet ArgumentParser :

>>> parser = argparse.ArgumentParser(description='Process some integers.')

L’objet ArgumentParser contiendra toutes les informations nécessaires pour interpréter la ligne de commande comme des types de données de Python.

16.4.1.2. Ajouter des arguments

Alimenter un ArgumentParser avec des informations sur les arguments du programme s’effectue en faisant des appels à la méthode add_argument(). En général ces appels disent à l”ArgumentParser comment prendre les chaînes de caractères de la ligne de commande et les transformer en objets. Cette information est stockée et utilisée lorsque parse_args() est appelée. Par exemple :

>>> parser.add_argument('integers', metavar='N', type=int, nargs='+',
...                     help='an integer for the accumulator')
>>> parser.add_argument('--sum', dest='accumulate', action='store_const',
...                     const=sum, default=max,
...                     help='sum the integers (default: find the max)')

Ensuite, appeler parse_args() va renvoyer un objet avec deux attributs, integers et accumulate. L’attribut integers est une liste d’un ou plusieurs entiers, et l’attribut accumulate est soit la fonction sum(), si --sum était fourni à la ligne de commande, soit la fonction max() dans le cas contraire.

16.4.1.3. Analyse des arguments

ArgumentParser parses arguments through the parse_args() method. This will inspect the command line, convert each argument to the appropriate type and then invoke the appropriate action. In most cases, this means a simple Namespace object will be built up from attributes parsed out of the command line:

>>> parser.parse_args(['--sum', '7', '-1', '42'])
Namespace(accumulate=<built-in function sum>, integers=[7, -1, 42])

In a script, parse_args() will typically be called with no arguments, and the ArgumentParser will automatically determine the command-line arguments from sys.argv.

16.4.2. Objets ArgumentParser

class argparse.ArgumentParser(prog=None, usage=None, description=None, epilog=None, parents=[], formatter_class=argparse.HelpFormatter, prefix_chars='-', fromfile_prefix_chars=None, argument_default=None, conflict_handler='error', add_help=True, allow_abbrev=True)

Create a new ArgumentParser object. All parameters should be passed as keyword arguments. Each parameter has its own more detailed description below, but in short they are:

prog - The name of the program (default: sys.argv[0])

usage - The string describing the program usage (default: generated from arguments added to parser)

description - Text to display before the argument help (default: none)

epilog - Text to display after the argument help (default: none)

parents - A list of ArgumentParser objects whose arguments should also be included

formatter_class - A class for customizing the help output

prefix_chars - The set of characters that prefix optional arguments (default: “-“)

fromfile_prefix_chars - The set of characters that prefix files from which additional arguments should be read (default: None)

argument_default - The global default value for arguments (default: None)

conflict_handler - The strategy for resolving conflicting optionals (usually unnecessary)

add_help - Add a -h/--help option to the parser (default: True)

allow_abbrev - Allows long options to be abbreviated if the abbreviation is unambiguous. (default: True)

Modifié dans la version 3.5: Le paramètre allow_abbrev est ajouté.

The following sections describe how each of these are used.

16.4.2.1. Le paramètre prog

By default, ArgumentParser objects use sys.argv[0] to determine how to display the name of the program in help messages. This default is almost always desirable because it will make the help messages match how the program was invoked on the command line. For example, consider a file named myprogram.py with the following code:

import argparse
parser = argparse.ArgumentParser()
parser.add_argument('--foo', help='foo help')
args = parser.parse_args()

The help for this program will display myprogram.py as the program name (regardless of where the program was invoked from):

$ python myprogram.py --help
usage: myprogram.py [-h] [--foo FOO]

optional arguments:
 -h, --help  show this help message and exit
 --foo FOO   foo help
$ cd ..
$ python subdir/myprogram.py --help
usage: myprogram.py [-h] [--foo FOO]

optional arguments:
 -h, --help  show this help message and exit
 --foo FOO   foo help

To change this default behavior, another value can be supplied using the prog= argument to ArgumentParser:

>>> parser = argparse.ArgumentParser(prog='myprogram')
>>> parser.print_help()
usage: myprogram [-h]

optional arguments:
 -h, --help  show this help message and exit

Note that the program name, whether determined from sys.argv[0] or from the prog= argument, is available to help messages using the %(prog)s format specifier.

>>> parser = argparse.ArgumentParser(prog='myprogram')
>>> parser.add_argument('--foo', help='foo of the %(prog)s program')
>>> parser.print_help()
usage: myprogram [-h] [--foo FOO]

optional arguments:
 -h, --help  show this help message and exit
 --foo FOO   foo of the myprogram program

16.4.2.2. Le paramètre usage

By default, ArgumentParser calculates the usage message from the arguments it contains:

>>> parser = argparse.ArgumentParser(prog='PROG')
>>> parser.add_argument('--foo', nargs='?', help='foo help')
>>> parser.add_argument('bar', nargs='+', help='bar help')
>>> parser.print_help()
usage: PROG [-h] [--foo [FOO]] bar [bar ...]

positional arguments:
 bar          bar help

optional arguments:
 -h, --help   show this help message and exit
 --foo [FOO]  foo help

The default message can be overridden with the usage= keyword argument:

>>> parser = argparse.ArgumentParser(prog='PROG', usage='%(prog)s [options]')
>>> parser.add_argument('--foo', nargs='?', help='foo help')
>>> parser.add_argument('bar', nargs='+', help='bar help')
>>> parser.print_help()
usage: PROG [options]

positional arguments:
 bar          bar help

optional arguments:
 -h, --help   show this help message and exit
 --foo [FOO]  foo help

The %(prog)s format specifier is available to fill in the program name in your usage messages.

16.4.2.3. Le paramètre description

Most calls to the ArgumentParser constructor will use the description= keyword argument. This argument gives a brief description of what the program does and how it works. In help messages, the description is displayed between the command-line usage string and the help messages for the various arguments:

>>> parser = argparse.ArgumentParser(description='A foo that bars')
>>> parser.print_help()
usage: argparse.py [-h]

A foo that bars

optional arguments:
 -h, --help  show this help message and exit

By default, the description will be line-wrapped so that it fits within the given space. To change this behavior, see the formatter_class argument.

16.4.2.4. Le paramètre epilog

Some programs like to display additional description of the program after the description of the arguments. Such text can be specified using the epilog= argument to ArgumentParser:

>>> parser = argparse.ArgumentParser(
...     description='A foo that bars',
...     epilog="And that's how you'd foo a bar")
>>> parser.print_help()
usage: argparse.py [-h]

A foo that bars

optional arguments:
 -h, --help  show this help message and exit

And that's how you'd foo a bar

As with the description argument, the epilog= text is by default line-wrapped, but this behavior can be adjusted with the formatter_class argument to ArgumentParser.

16.4.2.5. Le paramètre parents

Sometimes, several parsers share a common set of arguments. Rather than repeating the definitions of these arguments, a single parser with all the shared arguments and passed to parents= argument to ArgumentParser can be used. The parents= argument takes a list of ArgumentParser objects, collects all the positional and optional actions from them, and adds these actions to the ArgumentParser object being constructed:

>>> parent_parser = argparse.ArgumentParser(add_help=False)
>>> parent_parser.add_argument('--parent', type=int)

>>> foo_parser = argparse.ArgumentParser(parents=[parent_parser])
>>> foo_parser.add_argument('foo')
>>> foo_parser.parse_args(['--parent', '2', 'XXX'])
Namespace(foo='XXX', parent=2)

>>> bar_parser = argparse.ArgumentParser(parents=[parent_parser])
>>> bar_parser.add_argument('--bar')
>>> bar_parser.parse_args(['--bar', 'YYY'])
Namespace(bar='YYY', parent=None)

Note that most parent parsers will specify add_help=False. Otherwise, the ArgumentParser will see two -h/--help options (one in the parent and one in the child) and raise an error.

Note

You must fully initialize the parsers before passing them via parents=. If you change the parent parsers after the child parser, those changes will not be reflected in the child.

16.4.2.6. Le paramètre formatter_class

ArgumentParser objects allow the help formatting to be customized by specifying an alternate formatting class. Currently, there are four such classes:

class argparse.RawDescriptionHelpFormatter

class argparse.RawTextHelpFormatter

class argparse.ArgumentDefaultsHelpFormatter

class argparse.MetavarTypeHelpFormatter

RawDescriptionHelpFormatter and RawTextHelpFormatter give more control over how textual descriptions are displayed. By default, ArgumentParser objects line-wrap the description and epilog texts in command-line help messages:

>>> parser = argparse.ArgumentParser(
...     prog='PROG',
...     description='''this description
...         was indented weird
...             but that is okay''',
...     epilog='''
...             likewise for this epilog whose whitespace will
...         be cleaned up and whose words will be wrapped
...         across a couple lines''')
>>> parser.print_help()
usage: PROG [-h]

this description was indented weird but that is okay

optional arguments:
 -h, --help  show this help message and exit

likewise for this epilog whose whitespace will be cleaned up and whose words
will be wrapped across a couple lines

Passing RawDescriptionHelpFormatter as formatter_class= indicates that description and epilog are already correctly formatted and should not be line-wrapped:

>>> parser = argparse.ArgumentParser(
...     prog='PROG',
...     formatter_class=argparse.RawDescriptionHelpFormatter,
...     description=textwrap.dedent('''\
...         Please do not mess up this text!
...         --------------------------------
...             I have indented it
...             exactly the way
...             I want it
...         '''))
>>> parser.print_help()
usage: PROG [-h]

Please do not mess up this text!
--------------------------------
   I have indented it
   exactly the way
   I want it

optional arguments:
 -h, --help  show this help message and exit

RawTextHelpFormatter maintains whitespace for all sorts of help text, including argument descriptions. However, multiple new lines are replaced with one. If you wish to preserve multiple blank lines, add spaces between the newlines.

ArgumentDefaultsHelpFormatter automatically adds information about default values to each of the argument help messages:

>>> parser = argparse.ArgumentParser(
...     prog='PROG',
...     formatter_class=argparse.ArgumentDefaultsHelpFormatter)
>>> parser.add_argument('--foo', type=int, default=42, help='FOO!')
>>> parser.add_argument('bar', nargs='*', default=[1, 2, 3], help='BAR!')
>>> parser.print_help()
usage: PROG [-h] [--foo FOO] [bar [bar ...]]

positional arguments:
 bar         BAR! (default: [1, 2, 3])

optional arguments:
 -h, --help  show this help message and exit
 --foo FOO   FOO! (default: 42)

MetavarTypeHelpFormatter uses the name of the type argument for each argument as the display name for its values (rather than using the dest as the regular formatter does):

>>> parser = argparse.ArgumentParser(
...     prog='PROG',
...     formatter_class=argparse.MetavarTypeHelpFormatter)
>>> parser.add_argument('--foo', type=int)
>>> parser.add_argument('bar', type=float)
>>> parser.print_help()
usage: PROG [-h] [--foo int] float

positional arguments:
  float

optional arguments:
  -h, --help  show this help message and exit
  --foo int

16.4.2.7. Le paramètre prefix_chars

Most command-line options will use - as the prefix, e.g. -f/--foo. Parsers that need to support different or additional prefix characters, e.g. for options like +f or /foo, may specify them using the prefix_chars= argument to the ArgumentParser constructor:

>>> parser = argparse.ArgumentParser(prog='PROG', prefix_chars='-+')
>>> parser.add_argument('+f')
>>> parser.add_argument('++bar')
>>> parser.parse_args('+f X ++bar Y'.split())
Namespace(bar='Y', f='X')

The prefix_chars= argument defaults to '-'. Supplying a set of characters that does not include - will cause -f/--foo options to be disallowed.

16.4.2.8. Le paramètre fromfile_prefix_chars

Sometimes, for example when dealing with a particularly long argument lists, it may make sense to keep the list of arguments in a file rather than typing it out at the command line. If the fromfile_prefix_chars= argument is given to the ArgumentParser constructor, then arguments that start with any of the specified characters will be treated as files, and will be replaced by the arguments they contain. For example:

>>> with open('args.txt', 'w') as fp:
...     fp.write('-f\nbar')
>>> parser = argparse.ArgumentParser(fromfile_prefix_chars='@')
>>> parser.add_argument('-f')
>>> parser.parse_args(['-f', 'foo', '@args.txt'])
Namespace(f='bar')

Arguments read from a file must by default be one per line (but see also convert_arg_line_to_args()) and are treated as if they were in the same place as the original file referencing argument on the command line. So in the example above, the expression ['-f', 'foo', '@args.txt'] is considered equivalent to the expression ['-f', 'foo', '-f', 'bar'].

The fromfile_prefix_chars= argument defaults to None, meaning that arguments will never be treated as file references.

16.4.2.9. Le paramètre argument_default

Generally, argument defaults are specified either by passing a default to add_argument() or by calling the set_defaults() methods with a specific set of name-value pairs. Sometimes however, it may be useful to specify a single parser-wide default for arguments. This can be accomplished by passing the argument_default= keyword argument to ArgumentParser. For example, to globally suppress attribute creation on parse_args() calls, we supply argument_default=SUPPRESS:

>>> parser = argparse.ArgumentParser(argument_default=argparse.SUPPRESS)
>>> parser.add_argument('--foo')
>>> parser.add_argument('bar', nargs='?')
>>> parser.parse_args(['--foo', '1', 'BAR'])
Namespace(bar='BAR', foo='1')
>>> parser.parse_args([])
Namespace()

16.4.2.10. Le paramètre allow_abbrev

Normally, when you pass an argument list to the parse_args() method of an ArgumentParser, it recognizes abbreviations of long options.

This feature can be disabled by setting allow_abbrev to False:

>>> parser = argparse.ArgumentParser(prog='PROG', allow_abbrev=False)
>>> parser.add_argument('--foobar', action='store_true')
>>> parser.add_argument('--foonley', action='store_false')
>>> parser.parse_args(['--foon'])
usage: PROG [-h] [--foobar] [--foonley]
PROG: error: unrecognized arguments: --foon

Nouveau dans la version 3.5.

16.4.2.11. Le paramètre conflict_handler

ArgumentParser objects do not allow two actions with the same option string. By default, ArgumentParser objects raise an exception if an attempt is made to create an argument with an option string that is already in use:

>>> parser = argparse.ArgumentParser(prog='PROG')
>>> parser.add_argument('-f', '--foo', help='old foo help')
>>> parser.add_argument('--foo', help='new foo help')
Traceback (most recent call last):
 ..
ArgumentError: argument --foo: conflicting option string(s): --foo

Sometimes (e.g. when using parents) it may be useful to simply override any older arguments with the same option string. To get this behavior, the value 'resolve' can be supplied to the conflict_handler= argument of ArgumentParser:

>>> parser = argparse.ArgumentParser(prog='PROG', conflict_handler='resolve')
>>> parser.add_argument('-f', '--foo', help='old foo help')
>>> parser.add_argument('--foo', help='new foo help')
>>> parser.print_help()
usage: PROG [-h] [-f FOO] [--foo FOO]

optional arguments:
 -h, --help  show this help message and exit
 -f FOO      old foo help
 --foo FOO   new foo help

Note that ArgumentParser objects only remove an action if all of its option strings are overridden. So, in the example above, the old -f/--foo action is retained as the -f action, because only the --foo option string was overridden.

16.4.2.12. Le paramètre add_help

By default, ArgumentParser objects add an option which simply displays the parser’s help message. For example, consider a file named myprogram.py containing the following code:

import argparse
parser = argparse.ArgumentParser()
parser.add_argument('--foo', help='foo help')
args = parser.parse_args()

If -h or --help is supplied at the command line, the ArgumentParser help will be printed:

$ python myprogram.py --help
usage: myprogram.py [-h] [--foo FOO]

optional arguments:
 -h, --help  show this help message and exit
 --foo FOO   foo help

Occasionally, it may be useful to disable the addition of this help option. This can be achieved by passing False as the add_help= argument to ArgumentParser:

>>> parser = argparse.ArgumentParser(prog='PROG', add_help=False)
>>> parser.add_argument('--foo', help='foo help')
>>> parser.print_help()
usage: PROG [--foo FOO]

optional arguments:
 --foo FOO  foo help

The help option is typically -h/--help. The exception to this is if the prefix_chars= is specified and does not include -, in which case -h and --help are not valid options. In this case, the first character in prefix_chars is used to prefix the help options:

>>> parser = argparse.ArgumentParser(prog='PROG', prefix_chars='+/')
>>> parser.print_help()
usage: PROG [+h]

optional arguments:
  +h, ++help  show this help message and exit

16.4.3. La méthode add_argument()

ArgumentParser.add_argument(name or flags...[, action][, nargs][, const][, default][, type][, choices][, required][, help][, metavar][, dest])

Define how a single command-line argument should be parsed. Each parameter has its own more detailed description below, but in short they are:

name or flags - Either a name or a list of option strings, e.g. foo or -f, --foo.

action - The basic type of action to be taken when this argument is encountered at the command line.

nargs - The number of command-line arguments that should be consumed.

const - A constant value required by some action and nargs selections.

default - The value produced if the argument is absent from the command line.

type - The type to which the command-line argument should be converted.

choices - A container of the allowable values for the argument.

required - Whether or not the command-line option may be omitted (optionals only).

help - A brief description of what the argument does.

metavar - A name for the argument in usage messages.

dest - The name of the attribute to be added to the object returned by parse_args().

The following sections describe how each of these are used.

16.4.3.1. Les paramètres name et flags

The add_argument() method must know whether an optional argument, like -f or --foo, or a positional argument, like a list of filenames, is expected. The first arguments passed to add_argument() must therefore be either a series of flags, or a simple argument name. For example, an optional argument could be created like:

>>> parser.add_argument('-f', '--foo')

while a positional argument could be created like:

>>> parser.add_argument('bar')

When parse_args() is called, optional arguments will be identified by the - prefix, and the remaining arguments will be assumed to be positional:

>>> parser = argparse.ArgumentParser(prog='PROG')
>>> parser.add_argument('-f', '--foo')
>>> parser.add_argument('bar')
>>> parser.parse_args(['BAR'])
Namespace(bar='BAR', foo=None)
>>> parser.parse_args(['BAR', '--foo', 'FOO'])
Namespace(bar='BAR', foo='FOO')
>>> parser.parse_args(['--foo', 'FOO'])
usage: PROG [-h] [-f FOO] bar
PROG: error: the following arguments are required: bar

16.4.3.2. Le paramètre action

ArgumentParser objects associate command-line arguments with actions. These actions can do just about anything with the command-line arguments associated with them, though most actions simply add an attribute to the object returned by parse_args(). The action keyword argument specifies how the command-line arguments should be handled. The supplied actions are:

'store' - This just stores the argument’s value. This is the default action. For example:

>>> parser = argparse.ArgumentParser()
>>> parser.add_argument('--foo')
>>> parser.parse_args('--foo 1'.split())
Namespace(foo='1')

'store_const' - This stores the value specified by the const keyword argument. The 'store_const' action is most commonly used with optional arguments that specify some sort of flag. For example:

>>> parser = argparse.ArgumentParser()
>>> parser.add_argument('--foo', action='store_const', const=42)
>>> parser.parse_args(['--foo'])
Namespace(foo=42)

'store_true' and 'store_false' - These are special cases of 'store_const' used for storing the values True and False respectively. In addition, they create default values of False and True respectively. For example:

>>> parser = argparse.ArgumentParser()
>>> parser.add_argument('--foo', action='store_true')
>>> parser.add_argument('--bar', action='store_false')
>>> parser.add_argument('--baz', action='store_false')
>>> parser.parse_args('--foo --bar'.split())
Namespace(foo=True, bar=False, baz=True)

'append' - This stores a list, and appends each argument value to the list. This is useful to allow an option to be specified multiple times. Example usage:

>>> parser = argparse.ArgumentParser()
>>> parser.add_argument('--foo', action='append')
>>> parser.parse_args('--foo 1 --foo 2'.split())
Namespace(foo=['1', '2'])

'append_const' - This stores a list, and appends the value specified by the const keyword argument to the list. (Note that the const keyword argument defaults to None.) The 'append_const' action is typically useful when multiple arguments need to store constants to the same list. For example:

>>> parser = argparse.ArgumentParser()
>>> parser.add_argument('--str', dest='types', action='append_const', const=str)
>>> parser.add_argument('--int', dest='types', action='append_const', const=int)
>>> parser.parse_args('--str --int'.split())
Namespace(types=[<class 'str'>, <class 'int'>])

'count' - This counts the number of times a keyword argument occurs. For example, this is useful for increasing verbosity levels:

>>> parser = argparse.ArgumentParser()
>>> parser.add_argument('--verbose', '-v', action='count')
>>> parser.parse_args(['-vvv'])
Namespace(verbose=3)

'help' - This prints a complete help message for all the options in the current parser and then exits. By default a help action is automatically added to the parser. See ArgumentParser for details of how the output is created.

'version' - This expects a version= keyword argument in the add_argument() call, and prints version information and exits when invoked:

>>> import argparse
>>> parser = argparse.ArgumentParser(prog='PROG')
>>> parser.add_argument('--version', action='version', version='%(prog)s 2.0')
>>> parser.parse_args(['--version'])
PROG 2.0

You may also specify an arbitrary action by passing an Action subclass or other object that implements the same interface. The recommended way to do this is to extend Action, overriding the __call__ method and optionally the __init__ method.

Un exemple d’action personnalisée :

>>> class FooAction(argparse.Action):
...     def __init__(self, option_strings, dest, nargs=None, **kwargs):
...         if nargs is not None:
...             raise ValueError("nargs not allowed")
...         super(FooAction, self).__init__(option_strings, dest, **kwargs)
...     def __call__(self, parser, namespace, values, option_string=None):
...         print('%r %r %r' % (namespace, values, option_string))
...         setattr(namespace, self.dest, values)
...
>>> parser = argparse.ArgumentParser()
>>> parser.add_argument('--foo', action=FooAction)
>>> parser.add_argument('bar', action=FooAction)
>>> args = parser.parse_args('1 --foo 2'.split())
Namespace(bar=None, foo=None) '1' None
Namespace(bar='1', foo=None) '2' '--foo'
>>> args
Namespace(bar='1', foo='2')

Pour plus d’information, voir Action.

16.4.3.3. Le paramètre nargs

ArgumentParser objects usually associate a single command-line argument with a single action to be taken. The nargs keyword argument associates a different number of command-line arguments with a single action. The supported values are:

N (an integer). N arguments from the command line will be gathered together into a list. For example:

>>> parser = argparse.ArgumentParser()
>>> parser.add_argument('--foo', nargs=2)
>>> parser.add_argument('bar', nargs=1)
>>> parser.parse_args('c --foo a b'.split())
Namespace(bar=['c'], foo=['a', 'b'])

Note that nargs=1 produces a list of one item. This is different from the default, in which the item is produced by itself.

'?'. One argument will be consumed from the command line if possible, and produced as a single item. If no command-line argument is present, the value from default will be produced. Note that for optional arguments, there is an additional case - the option string is present but not followed by a command-line argument. In this case the value from const will be produced. Some examples to illustrate this:

>>> parser = argparse.ArgumentParser()
>>> parser.add_argument('--foo', nargs='?', const='c', default='d')
>>> parser.add_argument('bar', nargs='?', default='d')
>>> parser.parse_args(['XX', '--foo', 'YY'])
Namespace(bar='XX', foo='YY')
>>> parser.parse_args(['XX', '--foo'])
Namespace(bar='XX', foo='c')
>>> parser.parse_args([])
Namespace(bar='d', foo='d')

One of the more common uses of nargs='?' is to allow optional input and output files:

>>> parser = argparse.ArgumentParser()
>>> parser.add_argument('infile', nargs='?', type=argparse.FileType('r'),
...                     default=sys.stdin)
>>> parser.add_argument('outfile', nargs='?', type=argparse.FileType('w'),
...                     default=sys.stdout)
>>> parser.parse_args(['input.txt', 'output.txt'])
Namespace(infile=<_io.TextIOWrapper name='input.txt' encoding='UTF-8'>,
          outfile=<_io.TextIOWrapper name='output.txt' encoding='UTF-8'>)
>>> parser.parse_args([])
Namespace(infile=<_io.TextIOWrapper name='<stdin>' encoding='UTF-8'>,
          outfile=<_io.TextIOWrapper name='<stdout>' encoding='UTF-8'>)

'*'. All command-line arguments present are gathered into a list. Note that it generally doesn’t make much sense to have more than one positional argument with nargs='*', but multiple optional arguments with nargs='*' is possible. For example:

>>> parser = argparse.ArgumentParser()
>>> parser.add_argument('--foo', nargs='*')
>>> parser.add_argument('--bar', nargs='*')
>>> parser.add_argument('baz', nargs='*')
>>> parser.parse_args('a b --foo x y --bar 1 2'.split())
Namespace(bar=['1', '2'], baz=['a', 'b'], foo=['x', 'y'])

'+'. Just like '*', all command-line args present are gathered into a list. Additionally, an error message will be generated if there wasn’t at least one command-line argument present. For example:

>>> parser = argparse.ArgumentParser(prog='PROG')
>>> parser.add_argument('foo', nargs='+')
>>> parser.parse_args(['a', 'b'])
Namespace(foo=['a', 'b'])
>>> parser.parse_args([])
usage: PROG [-h] foo [foo ...]
PROG: error: the following arguments are required: foo

argparse.REMAINDER. All the remaining command-line arguments are gathered into a list. This is commonly useful for command line utilities that dispatch to other command line utilities:

>>> parser = argparse.ArgumentParser(prog='PROG')
>>> parser.add_argument('--foo')
>>> parser.add_argument('command')
>>> parser.add_argument('args', nargs=argparse.REMAINDER)
>>> print(parser.parse_args('--foo B cmd --arg1 XX ZZ'.split()))
Namespace(args=['--arg1', 'XX', 'ZZ'], command='cmd', foo='B')

If the nargs keyword argument is not provided, the number of arguments consumed is determined by the action. Generally this means a single command-line argument will be consumed and a single item (not a list) will be produced.

16.4.3.4. Le paramètre const

The const argument of add_argument() is used to hold constant values that are not read from the command line but are required for the various ArgumentParser actions. The two most common uses of it are:

When add_argument() is called with action='store_const' or action='append_const'. These actions add the const value to one of the attributes of the object returned by parse_args(). See the action description for examples.

When add_argument() is called with option strings (like -f or --foo) and nargs='?'. This creates an optional argument that can be followed by zero or one command-line arguments. When parsing the command line, if the option string is encountered with no command-line argument following it, the value of const will be assumed instead. See the nargs description for examples.

With the 'store_const' and 'append_const' actions, the const keyword argument must be given. For other actions, it defaults to None.

16.4.3.5. Le paramètre default

All optional arguments and some positional arguments may be omitted at the command line. The default keyword argument of add_argument(), whose value defaults to None, specifies what value should be used if the command-line argument is not present. For optional arguments, the default value is used when the option string was not present at the command line:

>>> parser = argparse.ArgumentParser()
>>> parser.add_argument('--foo', default=42)
>>> parser.parse_args(['--foo', '2'])
Namespace(foo='2')
>>> parser.parse_args([])
Namespace(foo=42)

If the default value is a string, the parser parses the value as if it were a command-line argument. In particular, the parser applies any type conversion argument, if provided, before setting the attribute on the Namespace return value. Otherwise, the parser uses the value as is:

>>> parser = argparse.ArgumentParser()
>>> parser.add_argument('--length', default='10', type=int)
>>> parser.add_argument('--width', default=10.5, type=int)
>>> parser.parse_args()
Namespace(length=10, width=10.5)

For positional arguments with nargs equal to ? or *, the default value is used when no command-line argument was present:

>>> parser = argparse.ArgumentParser()
>>> parser.add_argument('foo', nargs='?', default=42)
>>> parser.parse_args(['a'])
Namespace(foo='a')
>>> parser.parse_args([])
Namespace(foo=42)

Providing default=argparse.SUPPRESS causes no attribute to be added if the command-line argument was not present:

>>> parser = argparse.ArgumentParser()
>>> parser.add_argument('--foo', default=argparse.SUPPRESS)
>>> parser.parse_args([])
Namespace()
>>> parser.parse_args(['--foo', '1'])
Namespace(foo='1')

16.4.3.6. Le paramètre type

By default, ArgumentParser objects read command-line arguments in as simple strings. However, quite often the command-line string should instead be interpreted as another type, like a float or int. The type keyword argument of add_argument() allows any necessary type-checking and type conversions to be performed. Common built-in types and functions can be used directly as the value of the type argument:

>>> parser = argparse.ArgumentParser()
>>> parser.add_argument('foo', type=int)
>>> parser.add_argument('bar', type=open)
>>> parser.parse_args('2 temp.txt'.split())
Namespace(bar=<_io.TextIOWrapper name='temp.txt' encoding='UTF-8'>, foo=2)

See the section on the default keyword argument for information on when the type argument is applied to default arguments.

To ease the use of various types of files, the argparse module provides the factory FileType which takes the mode=, bufsize=, encoding= and errors= arguments of the open() function. For example, FileType('w') can be used to create a writable file:

>>> parser = argparse.ArgumentParser()
>>> parser.add_argument('bar', type=argparse.FileType('w'))
>>> parser.parse_args(['out.txt'])
Namespace(bar=<_io.TextIOWrapper name='out.txt' encoding='UTF-8'>)

type= can take any callable that takes a single string argument and returns the converted value:

>>> def perfect_square(string):
...     value = int(string)
...     sqrt = math.sqrt(value)
...     if sqrt != int(sqrt):
...         msg = "%r is not a perfect square" % string
...         raise argparse.ArgumentTypeError(msg)
...     return value
...
>>> parser = argparse.ArgumentParser(prog='PROG')
>>> parser.add_argument('foo', type=perfect_square)
>>> parser.parse_args(['9'])
Namespace(foo=9)
>>> parser.parse_args(['7'])
usage: PROG [-h] foo
PROG: error: argument foo: '7' is not a perfect square

The choices keyword argument may be more convenient for type checkers that simply check against a range of values:

>>> parser = argparse.ArgumentParser(prog='PROG')
>>> parser.add_argument('foo', type=int, choices=range(5, 10))
>>> parser.parse_args(['7'])
Namespace(foo=7)
>>> parser.parse_args(['11'])
usage: PROG [-h] {5,6,7,8,9}
PROG: error: argument foo: invalid choice: 11 (choose from 5, 6, 7, 8, 9)

Voir le chapitre choices pour plus de détails.

16.4.3.7. Le paramètre choices

Some command-line arguments should be selected from a restricted set of values. These can be handled by passing a container object as the choices keyword argument to add_argument(). When the command line is parsed, argument values will be checked, and an error message will be displayed if the argument was not one of the acceptable values:

>>> parser = argparse.ArgumentParser(prog='game.py')
>>> parser.add_argument('move', choices=['rock', 'paper', 'scissors'])
>>> parser.parse_args(['rock'])
Namespace(move='rock')
>>> parser.parse_args(['fire'])
usage: game.py [-h] {rock,paper,scissors}
game.py: error: argument move: invalid choice: 'fire' (choose from 'rock',
'paper', 'scissors')

Note that inclusion in the choices container is checked after any type conversions have been performed, so the type of the objects in the choices container should match the type specified:

>>> parser = argparse.ArgumentParser(prog='doors.py')
>>> parser.add_argument('door', type=int, choices=range(1, 4))
>>> print(parser.parse_args(['3']))
Namespace(door=3)
>>> parser.parse_args(['4'])
usage: doors.py [-h] {1,2,3}
doors.py: error: argument door: invalid choice: 4 (choose from 1, 2, 3)

Any object that supports the in operator can be passed as the choices value, so dict objects, set objects, custom containers, etc. are all supported.

16.4.3.8. Le paramètre required

In general, the argparse module assumes that flags like -f and --bar indicate optional arguments, which can always be omitted at the command line. To make an option required, True can be specified for the required= keyword argument to add_argument():

>>> parser = argparse.ArgumentParser()
>>> parser.add_argument('--foo', required=True)
>>> parser.parse_args(['--foo', 'BAR'])
Namespace(foo='BAR')
>>> parser.parse_args([])
usage: argparse.py [-h] [--foo FOO]
argparse.py: error: option --foo is required

As the example shows, if an option is marked as required, parse_args() will report an error if that option is not present at the command line.

Note

Required options are generally considered bad form because users expect options to be optional, and thus they should be avoided when possible.

16.4.3.9. Le paramètre help

The help value is a string containing a brief description of the argument. When a user requests help (usually by using -h or --help at the command line), these help descriptions will be displayed with each argument:

>>> parser = argparse.ArgumentParser(prog='frobble')
>>> parser.add_argument('--foo', action='store_true',
...                     help='foo the bars before frobbling')
>>> parser.add_argument('bar', nargs='+',
...                     help='one of the bars to be frobbled')
>>> parser.parse_args(['-h'])
usage: frobble [-h] [--foo] bar [bar ...]

positional arguments:
 bar     one of the bars to be frobbled

optional arguments:
 -h, --help  show this help message and exit
 --foo   foo the bars before frobbling

The help strings can include various format specifiers to avoid repetition of things like the program name or the argument default. The available specifiers include the program name, %(prog)s and most keyword arguments to add_argument(), e.g. %(default)s, %(type)s, etc.:

>>> parser = argparse.ArgumentParser(prog='frobble')
>>> parser.add_argument('bar', nargs='?', type=int, default=42,
...                     help='the bar to %(prog)s (default: %(default)s)')
>>> parser.print_help()
usage: frobble [-h] [bar]

positional arguments:
 bar     the bar to frobble (default: 42)

optional arguments:
 -h, --help  show this help message and exit

As the help string supports %-formatting, if you want a literal % to appear in the help string, you must escape it as %%.

argparse supports silencing the help entry for certain options, by setting the help value to argparse.SUPPRESS:

>>> parser = argparse.ArgumentParser(prog='frobble')
>>> parser.add_argument('--foo', help=argparse.SUPPRESS)
>>> parser.print_help()
usage: frobble [-h]

optional arguments:
  -h, --help  show this help message and exit

16.4.3.10. Le paramètre metavar

When ArgumentParser generates help messages, it needs some way to refer to each expected argument. By default, ArgumentParser objects use the dest value as the « name » of each object. By default, for positional argument actions, the dest value is used directly, and for optional argument actions, the dest value is uppercased. So, a single positional argument with dest='bar' will be referred to as bar. A single optional argument --foo that should be followed by a single command-line argument will be referred to as FOO. An example:

>>> parser = argparse.ArgumentParser()
>>> parser.add_argument('--foo')
>>> parser.add_argument('bar')
>>> parser.parse_args('X --foo Y'.split())
Namespace(bar='X', foo='Y')
>>> parser.print_help()
usage:  [-h] [--foo FOO] bar

positional arguments:
 bar

optional arguments:
 -h, --help  show this help message and exit
 --foo FOO

An alternative name can be specified with metavar:

>>> parser = argparse.ArgumentParser()
>>> parser.add_argument('--foo', metavar='YYY')
>>> parser.add_argument('bar', metavar='XXX')
>>> parser.parse_args('X --foo Y'.split())
Namespace(bar='X', foo='Y')
>>> parser.print_help()
usage:  [-h] [--foo YYY] XXX

positional arguments:
 XXX

optional arguments:
 -h, --help  show this help message and exit
 --foo YYY

Note that metavar only changes the displayed name - the name of the attribute on the parse_args() object is still determined by the dest value.

Different values of nargs may cause the metavar to be used multiple times. Providing a tuple to metavar specifies a different display for each of the arguments:

>>> parser = argparse.ArgumentParser(prog='PROG')
>>> parser.add_argument('-x', nargs=2)
>>> parser.add_argument('--foo', nargs=2, metavar=('bar', 'baz'))
>>> parser.print_help()
usage: PROG [-h] [-x X X] [--foo bar baz]

optional arguments:
 -h, --help     show this help message and exit
 -x X X
 --foo bar baz

16.4.3.11. Le paramètre dest

Most ArgumentParser actions add some value as an attribute of the object returned by parse_args(). The name of this attribute is determined by the dest keyword argument of add_argument(). For positional argument actions, dest is normally supplied as the first argument to add_argument():

>>> parser = argparse.ArgumentParser()
>>> parser.add_argument('bar')
>>> parser.parse_args(['XXX'])
Namespace(bar='XXX')

For optional argument actions, the value of dest is normally inferred from the option strings. ArgumentParser generates the value of dest by taking the first long option string and stripping away the initial -- string. If no long option strings were supplied, dest will be derived from the first short option string by stripping the initial - character. Any internal - characters will be converted to _ characters to make sure the string is a valid attribute name. The examples below illustrate this behavior:

>>> parser = argparse.ArgumentParser()
>>> parser.add_argument('-f', '--foo-bar', '--foo')
>>> parser.add_argument('-x', '-y')
>>> parser.parse_args('-f 1 -x 2'.split())
Namespace(foo_bar='1', x='2')
>>> parser.parse_args('--foo 1 -y 2'.split())
Namespace(foo_bar='1', x='2')

dest allows a custom attribute name to be provided:

>>> parser = argparse.ArgumentParser()
>>> parser.add_argument('--foo', dest='bar')
>>> parser.parse_args('--foo XXX'.split())
Namespace(bar='XXX')

16.4.3.12. Classes Action

Action classes implement the Action API, a callable which returns a callable which processes arguments from the command-line. Any object which follows this API may be passed as the action parameter to add_argument().

class argparse.Action(option_strings, dest, nargs=None, const=None, default=None, type=None, choices=None, required=False, help=None, metavar=None)

Action objects are used by an ArgumentParser to represent the information needed to parse a single argument from one or more strings from the command line. The Action class must accept the two positional arguments plus any keyword arguments passed to ArgumentParser.add_argument() except for the action itself.

Instances of Action (or return value of any callable to the action parameter) should have attributes « dest », « option_strings », « default », « type », « required », « help », etc. defined. The easiest way to ensure these attributes are defined is to call Action.__init__.

Action instances should be callable, so subclasses must override the __call__ method, which should accept four parameters:

parser - The ArgumentParser object which contains this action.

namespace - The Namespace object that will be returned by parse_args(). Most actions add an attribute to this object using setattr().

values - The associated command-line arguments, with any type conversions applied. Type conversions are specified with the type keyword argument to add_argument().

option_string - The option string that was used to invoke this action. The option_string argument is optional, and will be absent if the action is associated with a positional argument.

The __call__ method may perform arbitrary actions, but will typically set attributes on the namespace based on dest and values.

16.4.4. La méthode parse_args()

ArgumentParser.parse_args(args=None, namespace=None)

Convert argument strings to objects and assign them as attributes of the namespace. Return the populated namespace.

Previous calls to add_argument() determine exactly what objects are created and how they are assigned. See the documentation for add_argument() for details.

args - List of strings to parse. The default is taken from sys.argv.

namespace - An object to take the attributes. The default is a new empty Namespace object.

16.4.4.1. Option value syntax

The parse_args() method supports several ways of specifying the value of an option (if it takes one). In the simplest case, the option and its value are passed as two separate arguments:

>>> parser = argparse.ArgumentParser(prog='PROG')
>>> parser.add_argument('-x')
>>> parser.add_argument('--foo')
>>> parser.parse_args(['-x', 'X'])
Namespace(foo=None, x='X')
>>> parser.parse_args(['--foo', 'FOO'])
Namespace(foo='FOO', x=None)

For long options (options with names longer than a single character), the option and value can also be passed as a single command-line argument, using = to separate them:

>>> parser.parse_args(['--foo=FOO'])
Namespace(foo='FOO', x=None)

For short options (options only one character long), the option and its value can be concatenated:

>>> parser.parse_args(['-xX'])
Namespace(foo=None, x='X')

Several short options can be joined together, using only a single - prefix, as long as only the last option (or none of them) requires a value:

>>> parser = argparse.ArgumentParser(prog='PROG')
>>> parser.add_argument('-x', action='store_true')
>>> parser.add_argument('-y', action='store_true')
>>> parser.add_argument('-z')
>>> parser.parse_args(['-xyzZ'])
Namespace(x=True, y=True, z='Z')

16.4.4.2. Arguments invalides

While parsing the command line, parse_args() checks for a variety of errors, including ambiguous options, invalid types, invalid options, wrong number of positional arguments, etc. When it encounters such an error, it exits and prints the error along with a usage message:

>>> parser = argparse.ArgumentParser(prog='PROG')
>>> parser.add_argument('--foo', type=int)
>>> parser.add_argument('bar', nargs='?')

>>> # invalid type
>>> parser.parse_args(['--foo', 'spam'])
usage: PROG [-h] [--foo FOO] [bar]
PROG: error: argument --foo: invalid int value: 'spam'

>>> # invalid option
>>> parser.parse_args(['--bar'])
usage: PROG [-h] [--foo FOO] [bar]
PROG: error: no such option: --bar

>>> # wrong number of arguments
>>> parser.parse_args(['spam', 'badger'])
usage: PROG [-h] [--foo FOO] [bar]
PROG: error: extra arguments found: badger

16.4.4.3. Arguments contenant -

The parse_args() method attempts to give errors whenever the user has clearly made a mistake, but some situations are inherently ambiguous. For example, the command-line argument -1 could either be an attempt to specify an option or an attempt to provide a positional argument. The parse_args() method is cautious here: positional arguments may only begin with - if they look like negative numbers and there are no options in the parser that look like negative numbers:

>>> parser = argparse.ArgumentParser(prog='PROG')
>>> parser.add_argument('-x')
>>> parser.add_argument('foo', nargs='?')

>>> # no negative number options, so -1 is a positional argument
>>> parser.parse_args(['-x', '-1'])
Namespace(foo=None, x='-1')

>>> # no negative number options, so -1 and -5 are positional arguments
>>> parser.parse_args(['-x', '-1', '-5'])
Namespace(foo='-5', x='-1')

>>> parser = argparse.ArgumentParser(prog='PROG')
>>> parser.add_argument('-1', dest='one')
>>> parser.add_argument('foo', nargs='?')

>>> # negative number options present, so -1 is an option
>>> parser.parse_args(['-1', 'X'])
Namespace(foo=None, one='X')

>>> # negative number options present, so -2 is an option
>>> parser.parse_args(['-2'])
usage: PROG [-h] [-1 ONE] [foo]
PROG: error: no such option: -2

>>> # negative number options present, so both -1s are options
>>> parser.parse_args(['-1', '-1'])
usage: PROG [-h] [-1 ONE] [foo]
PROG: error: argument -1: expected one argument

If you have positional arguments that must begin with - and don’t look like negative numbers, you can insert the pseudo-argument '--' which tells parse_args() that everything after that is a positional argument:

>>> parser.parse_args(['--', '-f'])
Namespace(foo='-f', one=None)

16.4.4.4. Arguments abrégés (Par comparaison de leurs préfixes)

The parse_args() method by default allows long options to be abbreviated to a prefix, if the abbreviation is unambiguous (the prefix matches a unique option):

>>> parser = argparse.ArgumentParser(prog='PROG')
>>> parser.add_argument('-bacon')
>>> parser.add_argument('-badger')
>>> parser.parse_args('-bac MMM'.split())
Namespace(bacon='MMM', badger=None)
>>> parser.parse_args('-bad WOOD'.split())
Namespace(bacon=None, badger='WOOD')
>>> parser.parse_args('-ba BA'.split())
usage: PROG [-h] [-bacon BACON] [-badger BADGER]
PROG: error: ambiguous option: -ba could match -badger, -bacon

An error is produced for arguments that could produce more than one options. This feature can be disabled by setting Le paramètre allow_abbrev to False.

16.4.4.5. Au-delà de sys.argv

Sometimes it may be useful to have an ArgumentParser parse arguments other than those of sys.argv. This can be accomplished by passing a list of strings to parse_args(). This is useful for testing at the interactive prompt:

>>> parser = argparse.ArgumentParser()
>>> parser.add_argument(
...     'integers', metavar='int', type=int, choices=range(10),
...     nargs='+', help='an integer in the range 0..9')
>>> parser.add_argument(
...     '--sum', dest='accumulate', action='store_const', const=sum,
...     default=max, help='sum the integers (default: find the max)')
>>> parser.parse_args(['1', '2', '3', '4'])
Namespace(accumulate=<built-in function max>, integers=[1, 2, 3, 4])
>>> parser.parse_args(['1', '2', '3', '4', '--sum'])
Namespace(accumulate=<built-in function sum>, integers=[1, 2, 3, 4])

16.4.4.6. L’objet namespace

class argparse.Namespace

Simple class used by default by parse_args() to create an object holding attributes and return it.

This class is deliberately simple, just an object subclass with a readable string representation. If you prefer to have dict-like view of the attributes, you can use the standard Python idiom, vars():

>>> parser = argparse.ArgumentParser()
>>> parser.add_argument('--foo')
>>> args = parser.parse_args(['--foo', 'BAR'])
>>> vars(args)
{'foo': 'BAR'}

It may also be useful to have an ArgumentParser assign attributes to an already existing object, rather than a new Namespace object. This can be achieved by specifying the namespace= keyword argument:

>>> class C:
...     pass
...
>>> c = C()
>>> parser = argparse.ArgumentParser()
>>> parser.add_argument('--foo')
>>> parser.parse_args(args=['--foo', 'BAR'], namespace=c)
>>> c.foo
'BAR'

16.4.5. Autres outils

16.4.5.1. Sous commandes

ArgumentParser.add_subparsers([title][, description][, prog][, parser_class][, action][, option_string][, dest][, help][, metavar])

Many programs split up their functionality into a number of sub-commands, for example, the svn program can invoke sub-commands like svn checkout, svn update, and svn commit. Splitting up functionality this way can be a particularly good idea when a program performs several different functions which require different kinds of command-line arguments. ArgumentParser supports the creation of such sub-commands with the add_subparsers() method. The add_subparsers() method is normally called with no arguments and returns a special action object. This object has a single method, add_parser(), which takes a command name and any ArgumentParser constructor arguments, and returns an ArgumentParser object that can be modified as usual.

Description des paramètres

title - title for the sub-parser group in help output; by default « subcommands » if description is provided, otherwise uses title for positional arguments

description - description for the sub-parser group in help output, by default None

prog - usage information that will be displayed with sub-command help, by default the name of the program and any positional arguments before the subparser argument

parser_class - class which will be used to create sub-parser instances, by default the class of the current parser (e.g. ArgumentParser)

action - the basic type of action to be taken when this argument is encountered at the command line

dest - name of the attribute under which sub-command name will be stored; by default None and no value is stored

help - help for sub-parser group in help output, by default None

metavar - string presenting available sub-commands in help; by default it is None and presents sub-commands in form {cmd1, cmd2, ..}

Quelques exemples d’utilisation :

>>> # create the top-level parser
>>> parser = argparse.ArgumentParser(prog='PROG')
>>> parser.add_argument('--foo', action='store_true', help='foo help')
>>> subparsers = parser.add_subparsers(help='sub-command help')
>>>
>>> # create the parser for the "a" command
>>> parser_a = subparsers.add_parser('a', help='a help')
>>> parser_a.add_argument('bar', type=int, help='bar help')
>>>
>>> # create the parser for the "b" command
>>> parser_b = subparsers.add_parser('b', help='b help')
>>> parser_b.add_argument('--baz', choices='XYZ', help='baz help')
>>>
>>> # parse some argument lists
>>> parser.parse_args(['a', '12'])
Namespace(bar=12, foo=False)
>>> parser.parse_args(['--foo', 'b', '--baz', 'Z'])
Namespace(baz='Z', foo=True)

Note that the object returned by parse_args() will only contain attributes for the main parser and the subparser that was selected by the command line (and not any other subparsers). So in the example above, when the a command is specified, only the foo and bar attributes are present, and when the b command is specified, only the foo and baz attributes are present.

Similarly, when a help message is requested from a subparser, only the help for that particular parser will be printed. The help message will not include parent parser or sibling parser messages. (A help message for each subparser command, however, can be given by supplying the help= argument to add_parser() as above.)

>>> parser.parse_args(['--help'])
usage: PROG [-h] [--foo] {a,b} ...

positional arguments:
  {a,b}   sub-command help
    a     a help
    b     b help

optional arguments:
  -h, --help  show this help message and exit
  --foo   foo help

>>> parser.parse_args(['a', '--help'])
usage: PROG a [-h] bar

positional arguments:
  bar     bar help

optional arguments:
  -h, --help  show this help message and exit

>>> parser.parse_args(['b', '--help'])
usage: PROG b [-h] [--baz {X,Y,Z}]

optional arguments:
  -h, --help     show this help message and exit
  --baz {X,Y,Z}  baz help

The add_subparsers() method also supports title and description keyword arguments. When either is present, the subparser’s commands will appear in their own group in the help output. For example:

>>> parser = argparse.ArgumentParser()
>>> subparsers = parser.add_subparsers(title='subcommands',
...                                    description='valid subcommands',
...                                    help='additional help')
>>> subparsers.add_parser('foo')
>>> subparsers.add_parser('bar')
>>> parser.parse_args(['-h'])
usage:  [-h] {foo,bar} ...

optional arguments:
  -h, --help  show this help message and exit

subcommands:
  valid subcommands

  {foo,bar}   additional help

Furthermore, add_parser supports an additional aliases argument, which allows multiple strings to refer to the same subparser. This example, like svn, aliases co as a shorthand for checkout:

>>> parser = argparse.ArgumentParser()
>>> subparsers = parser.add_subparsers()
>>> checkout = subparsers.add_parser('checkout', aliases=['co'])
>>> checkout.add_argument('foo')
>>> parser.parse_args(['co', 'bar'])
Namespace(foo='bar')

One particularly effective way of handling sub-commands is to combine the use of the add_subparsers() method with calls to set_defaults() so that each subparser knows which Python function it should execute. For example:

>>> # sub-command functions
>>> def foo(args):
...     print(args.x * args.y)
...
>>> def bar(args):
...     print('((%s))' % args.z)
...
>>> # create the top-level parser
>>> parser = argparse.ArgumentParser()
>>> subparsers = parser.add_subparsers()
>>>
>>> # create the parser for the "foo" command
>>> parser_foo = subparsers.add_parser('foo')
>>> parser_foo.add_argument('-x', type=int, default=1)
>>> parser_foo.add_argument('y', type=float)
>>> parser_foo.set_defaults(func=foo)
>>>
>>> # create the parser for the "bar" command
>>> parser_bar = subparsers.add_parser('bar')
>>> parser_bar.add_argument('z')
>>> parser_bar.set_defaults(func=bar)
>>>
>>> # parse the args and call whatever function was selected
>>> args = parser.parse_args('foo 1 -x 2'.split())
>>> args.func(args)
2.0
>>>
>>> # parse the args and call whatever function was selected
>>> args = parser.parse_args('bar XYZYX'.split())
>>> args.func(args)
((XYZYX))

This way, you can let parse_args() do the job of calling the appropriate function after argument parsing is complete. Associating functions with actions like this is typically the easiest way to handle the different actions for each of your subparsers. However, if it is necessary to check the name of the subparser that was invoked, the dest keyword argument to the add_subparsers() call will work:

>>> parser = argparse.ArgumentParser()
>>> subparsers = parser.add_subparsers(dest='subparser_name')
>>> subparser1 = subparsers.add_parser('1')
>>> subparser1.add_argument('-x')
>>> subparser2 = subparsers.add_parser('2')
>>> subparser2.add_argument('y')
>>> parser.parse_args(['2', 'frobble'])
Namespace(subparser_name='2', y='frobble')

16.4.5.2. Objets FileType

class argparse.FileType(mode='r', bufsize=-1, encoding=None, errors=None)

The FileType factory creates objects that can be passed to the type argument of ArgumentParser.add_argument(). Arguments that have FileType objects as their type will open command-line arguments as files with the requested modes, buffer sizes, encodings and error handling (see the open() function for more details):

>>> parser = argparse.ArgumentParser()
>>> parser.add_argument('--raw', type=argparse.FileType('wb', 0))
>>> parser.add_argument('out', type=argparse.FileType('w', encoding='UTF-8'))
>>> parser.parse_args(['--raw', 'raw.dat', 'file.txt'])
Namespace(out=<_io.TextIOWrapper name='file.txt' mode='w' encoding='UTF-8'>, raw=<_io.FileIO name='raw.dat' mode='wb'>)

FileType objects understand the pseudo-argument '-' and automatically convert this into sys.stdin for readable FileType objects and sys.stdout for writable FileType objects:

>>> parser = argparse.ArgumentParser()
>>> parser.add_argument('infile', type=argparse.FileType('r'))
>>> parser.parse_args(['-'])
Namespace(infile=<_io.TextIOWrapper name='<stdin>' encoding='UTF-8'>)

Nouveau dans la version 3.4: Les arguments nommés encodings et errors.

16.4.5.3. Groupes d’arguments

ArgumentParser.add_argument_group(title=None, description=None)

By default, ArgumentParser groups command-line arguments into « positional arguments » and « optional arguments » when displaying help messages. When there is a better conceptual grouping of arguments than this default one, appropriate groups can be created using the add_argument_group() method:

>>> parser = argparse.ArgumentParser(prog='PROG', add_help=False)
>>> group = parser.add_argument_group('group')
>>> group.add_argument('--foo', help='foo help')
>>> group.add_argument('bar', help='bar help')
>>> parser.print_help()
usage: PROG [--foo FOO] bar

group:
  bar    bar help
  --foo FOO  foo help

The add_argument_group() method returns an argument group object which has an add_argument() method just like a regular ArgumentParser. When an argument is added to the group, the parser treats it just like a normal argument, but displays the argument in a separate group for help messages. The add_argument_group() method accepts title and description arguments which can be used to customize this display:

>>> parser = argparse.ArgumentParser(prog='PROG', add_help=False)
>>> group1 = parser.add_argument_group('group1', 'group1 description')
>>> group1.add_argument('foo', help='foo help')
>>> group2 = parser.add_argument_group('group2', 'group2 description')
>>> group2.add_argument('--bar', help='bar help')
>>> parser.print_help()
usage: PROG [--bar BAR] foo

group1:
  group1 description

  foo    foo help

group2:
  group2 description

  --bar BAR  bar help

Note that any arguments not in your user-defined groups will end up back in the usual « positional arguments » and « optional arguments » sections.

16.4.5.4. Exclusion mutuelle

ArgumentParser.add_mutually_exclusive_group(required=False)

Create a mutually exclusive group. argparse will make sure that only one of the arguments in the mutually exclusive group was present on the command line:

>>> parser = argparse.ArgumentParser(prog='PROG')
>>> group = parser.add_mutually_exclusive_group()
>>> group.add_argument('--foo', action='store_true')
>>> group.add_argument('--bar', action='store_false')
>>> parser.parse_args(['--foo'])
Namespace(bar=True, foo=True)
>>> parser.parse_args(['--bar'])
Namespace(bar=False, foo=False)
>>> parser.parse_args(['--foo', '--bar'])
usage: PROG [-h] [--foo | --bar]
PROG: error: argument --bar: not allowed with argument --foo

The add_mutually_exclusive_group() method also accepts a required argument, to indicate that at least one of the mutually exclusive arguments is required:

>>> parser = argparse.ArgumentParser(prog='PROG')
>>> group = parser.add_mutually_exclusive_group(required=True)
>>> group.add_argument('--foo', action='store_true')
>>> group.add_argument('--bar', action='store_false')
>>> parser.parse_args([])
usage: PROG [-h] (--foo | --bar)
PROG: error: one of the arguments --foo --bar is required

Note that currently mutually exclusive argument groups do not support the title and description arguments of add_argument_group().

16.4.5.5. Valeurs par défaut de l’analyseur

ArgumentParser.set_defaults(**kwargs)

Most of the time, the attributes of the object returned by parse_args() will be fully determined by inspecting the command-line arguments and the argument actions. set_defaults() allows some additional attributes that are determined without any inspection of the command line to be added:

>>> parser = argparse.ArgumentParser()
>>> parser.add_argument('foo', type=int)
>>> parser.set_defaults(bar=42, baz='badger')
>>> parser.parse_args(['736'])
Namespace(bar=42, baz='badger', foo=736)

Note that parser-level defaults always override argument-level defaults:

>>> parser = argparse.ArgumentParser()
>>> parser.add_argument('--foo', default='bar')
>>> parser.set_defaults(foo='spam')
>>> parser.parse_args([])
Namespace(foo='spam')

Parser-level defaults can be particularly useful when working with multiple parsers. See the add_subparsers() method for an example of this type.

ArgumentParser.get_default(dest)

Get the default value for a namespace attribute, as set by either add_argument() or by set_defaults():

>>> parser = argparse.ArgumentParser()
>>> parser.add_argument('--foo', default='badger')
>>> parser.get_default('foo')
'badger'

16.4.5.6. Afficher l’aide

In most typical applications, parse_args() will take care of formatting and printing any usage or error messages. However, several formatting methods are available:

ArgumentParser.print_usage(file=None)

Print a brief description of how the ArgumentParser should be invoked on the command line. If file is None, sys.stdout is assumed.

ArgumentParser.print_help(file=None)

Print a help message, including the program usage and information about the arguments registered with the ArgumentParser. If file is None, sys.stdout is assumed.

There are also variants of these methods that simply return a string instead of printing it:

ArgumentParser.format_usage()

Return a string containing a brief description of how the ArgumentParser should be invoked on the command line.

ArgumentParser.format_help()

Return a string containing a help message, including the program usage and information about the arguments registered with the ArgumentParser.

16.4.5.7. Parsing partiel

ArgumentParser.parse_known_args(args=None, namespace=None)

Sometimes a script may only parse a few of the command-line arguments, passing the remaining arguments on to another script or program. In these cases, the parse_known_args() method can be useful. It works much like parse_args() except that it does not produce an error when extra arguments are present. Instead, it returns a two item tuple containing the populated namespace and the list of remaining argument strings.

>>> parser = argparse.ArgumentParser()
>>> parser.add_argument('--foo', action='store_true')
>>> parser.add_argument('bar')
>>> parser.parse_known_args(['--foo', '--badger', 'BAR', 'spam'])
(Namespace(bar='BAR', foo=True), ['--badger', 'spam'])

Avertissement

Prefix matching rules apply to parse_known_args(). The parser may consume an option even if it’s just a prefix of one of its known options, instead of leaving it in the remaining arguments list.

16.4.5.8. Personnaliser le parsing de fichiers

ArgumentParser.convert_arg_line_to_args(arg_line)

Arguments that are read from a file (see the fromfile_prefix_chars keyword argument to the ArgumentParser constructor) are read one argument per line. convert_arg_line_to_args() can be overridden for fancier reading.

This method takes a single argument arg_line which is a string read from the argument file. It returns a list of arguments parsed from this string. The method is called once per line read from the argument file, in order.

A useful override of this method is one that treats each space-separated word as an argument. The following example demonstrates how to do this:

class MyArgumentParser(argparse.ArgumentParser):
    def convert_arg_line_to_args(self, arg_line):
        return arg_line.split()

16.4.5.9. Exiting methods

ArgumentParser.exit(status=0, message=None)

This method terminates the program, exiting with the specified status and, if given, it prints a message before that.

ArgumentParser.error(message)

This method prints a usage message including the message to the standard error and terminates the program with a status code of 2.

16.4.6. Mettre à jour du code optparse

Originally, the argparse module had attempted to maintain compatibility with optparse. However, optparse was difficult to extend transparently, particularly with the changes required to support the new nargs= specifiers and better usage messages. When most everything in optparse had either been copy-pasted over or monkey-patched, it no longer seemed practical to try to maintain the backwards compatibility.

The argparse module improves on the standard library optparse module in a number of ways including:

Gère les arguments positionnels.

Prise en charge des sous commandes.

Permet d’utiliser les alternatives + ou / comme préfixes d’option.

Prend en charge la répétition de valeurs (zéro ou plus, un ou plus).

Fournit des messages d’aide plus complets.

Fournit une interface plus simple pour les types et actions personnalisés

A partial upgrade path from optparse to argparse:

Replace all optparse.OptionParser.add_option() calls with ArgumentParser.add_argument() calls.

Replace (options, args) = parser.parse_args() with args = parser.parse_args() and add additional ArgumentParser.add_argument() calls for the positional arguments. Keep in mind that what was previously called options, now in the argparse context is called args.

Replace optparse.OptionParser.disable_interspersed_args() by setting nargs of a positional argument to argparse.REMAINDER, or use parse_known_args() to collect unparsed argument strings in a separate list.

Replace callback actions and the callback_* keyword arguments with type or action arguments.

Replace string names for type keyword arguments with the corresponding type objects (e.g. int, float, complex, etc).

Replace optparse.Values with Namespace and optparse.OptionError and optparse.OptionValueError with ArgumentError.

Replace strings with implicit arguments such as %default or %prog with the standard Python syntax to use dictionaries to format strings, that is, %(default)s and %(prog)s.

Replace the OptionParser constructor version argument with a call to parser.add_argument('--version', action='version', version='<the version>').

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16.5. getopt – Analyseur de style C pour les options de ligne de commande

Code source : Lib/getopt.py [https://github.com/python/cpython/tree/3.6/Lib/getopt.py]

Note

Le module getopt est un analyseur pour les options de ligne de commande dont l’API est conçue pour être familière aux utilisateurs de la fonction C getopt(). Les utilisateurs qui ne connaissent pas la fonction getopt() ou qui aimeraient écrire moins de code, obtenir une meilleure aide et de meilleurs messages d’erreur devraient utiliser le module argparse.

Ce module aide les scripts à analyser les arguments de ligne de commande contenus dans sys.argv. Il prend en charge les mêmes conventions que la fonction UNIX getopt() (y compris les significations spéciales des arguments de la forme - et --). De longues options similaires à celles prises en charge par le logiciel GNU peuvent également être utilisées via un troisième argument facultatif.

Ce module fournit deux fonctions et une exception :

getopt.getopt(args, shortopts, longopts=[])

Analyse les options de ligne de commande et la liste des paramètres. args est la liste d’arguments à analyser, sans la référence principale au programme en cours d’exécution. En général, cela signifie sys.argv[1:] (donc que le premier argument contenant le nom du programme n’est pas dans la liste). shortopts est la chaîne de lettres d’options que le script doit reconnaître, avec des options qui requièrent un argument suivi d’un signe deux-points (:, donc le même format que la version Unix de getopt() utilise).

Note

Contrairement au getopt() GNU, après un argument n’appartenant pas à une option, aucun argument ne sera considéré comme appartenant à une option. Ceci est similaire à la façon dont les systèmes UNIX non-GNU fonctionnent.

longopts, si spécifié, doit être une liste de chaînes avec les noms des options longues qui doivent être prises en charge. Le premier '--' ne dois pas figurer dans le nom de l’option. Les options longues qui requièrent un argument doivent être suivies d’un signe égal ('='). Les arguments facultatifs ne sont pas pris en charge. Pour accepter uniquement les options longues, shortopts doit être une chaîne vide. Les options longues sur la ligne de commande peuvent être reconnues tant qu’elles fournissent un préfixe du nom de l’option qui correspond exactement à l’une des options acceptées. Par exemple, si longopts est ['foo', 'frob'], l’option --fo correspondra à --foo, mais --f ne correspondra pas de façon unique, donc GetoptError sera levé.

La valeur de retour se compose de deux éléments : le premier est une liste de paires (option, value), la deuxième est la liste des arguments de programme laissés après que la liste d’options est été dépouillée (il s’agit d’une tranche de fin de args). Chaque paire option-valeur retournée a l’option comme premier élément, préfixée avec un trait d’union pour les options courtes (par exemple, '-x') ou deux tirets pour les options longues (par exemple, '--long-option'), et l’argument option comme deuxième élément, ou une chaîne vide si le option n’a aucun argument. Les options se trouvent dans la liste dans l’ordre dans lequel elles ont été trouvées, permettant ainsi plusieurs occurrences. Les options longues et courtes peuvent être mélangées.

getopt.gnu_getopt(args, shortopts, longopts=[])

Cette fonction fonctionne comme getopt(), sauf que le mode de scan GNU est utilisé par défaut. Cela signifie que les arguments option et non-option peuvent être intermixés. La fonction getopt() arrête le traitement des options dès qu’un argument de non-option est rencontré.

Si le premier caractère de la chaîne d’options est +, ou si la variable d’environnement POSIXLY_CORRECT est définie, le traitement des options s’arrête dès qu’un argument non-option est rencontré.

exception getopt.GetoptError

Cette exception est levée lorsqu’une option non reconnue est trouvée dans la liste d’arguments ou lorsqu’une option nécessitant un argument n’en a pas reçu. L’argument de l’exception est une chaîne de caractères indiquant la cause de l’erreur. Pour les options longues, un argument donné à une option qui n’en exige pas un entraîne également le levage de cette exception. Les attributs msg et opt donnent le message d’erreur et l’option connexe. S’il n’existe aucune option spécifique à laquelle l’exception se rapporte, opt est une chaîne vide.

exception getopt.error

Alias pour GetoptError ; pour la rétrocompatibilité.

Un exemple utilisant uniquement les options de style UNIX :

>>> import getopt
>>> args = '-a -b -cfoo -d bar a1 a2'.split()
>>> args
['-a', '-b', '-cfoo', '-d', 'bar', 'a1', 'a2']
>>> optlist, args = getopt.getopt(args, 'abc:d:')
>>> optlist
[('-a', ''), ('-b', ''), ('-c', 'foo'), ('-d', 'bar')]
>>> args
['a1', 'a2']

L’utilisation de noms d’options longs est tout aussi simple :

>>> s = '--condition=foo --testing --output-file abc.def -x a1 a2'
>>> args = s.split()
>>> args
['--condition=foo', '--testing', '--output-file', 'abc.def', '-x', 'a1', 'a2']
>>> optlist, args = getopt.getopt(args, 'x', [
...     'condition=', 'output-file=', 'testing'])
>>> optlist
[('--condition', 'foo'), ('--testing', ''), ('--output-file', 'abc.def'), ('-x', '')]
>>> args
['a1', 'a2']

Dans un script, l’utilisation typique ressemble à ceci :

import getopt, sys

def main():
    try:
        opts, args = getopt.getopt(sys.argv[1:], "ho:v", ["help", "output="])
    except getopt.GetoptError as err:
        # print help information and exit:
        print(err)  # will print something like "option -a not recognized"
        usage()
        sys.exit(2)
    output = None
    verbose = False
    for o, a in opts:
        if o == "-v":
            verbose = True
        elif o in ("-h", "--help"):
            usage()
            sys.exit()
        elif o in ("-o", "--output"):
            output = a
        else:
            assert False, "unhandled option"
    # ...

if __name__ == "__main__":
    main()

Notez qu’une interface de ligne de commande équivalente peut être produite avec moins de code et des messages d’erreur et d’aide plus informatifs à l’aide du module argparse module :

import argparse

if __name__ == '__main__':
    parser = argparse.ArgumentParser()
    parser.add_argument('-o', '--output')
    parser.add_argument('-v', dest='verbose', action='store_true')
    args = parser.parse_args()
    # ... do something with args.output ...
    # ... do something with args.verbose ..

Voir aussi

Module argparse

Option de ligne de commande alternative et bibliothèque d’analyse d’arguments.

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16.6. logging — Fonctionnalités de journalisation pour Python

Code source : Lib/logging/__init__.py [https://github.com/python/cpython/tree/3.6/Lib/logging/__init__.py]

Important

Cette page contient les informations de référence de l’API. Pour des tutoriels et des discussions sur des sujets plus avancés, voir

Tutoriel basique

Tutoriel avancé

Recettes pour la journalisation

Ce module définit les fonctions et les classes qui mettent en œuvre un système flexible d’enregistrement des événements pour les applications et les bibliothèques.

Le principal avantage de l’API de journalisation fournie par un module de bibliothèque standard est que tous les modules Python peuvent participer à la journalisation, de sorte que le journal de votre application peut inclure vos propres messages intégrés aux messages de modules tiers.

Le module offre beaucoup de fonctionnalités et de flexibilité. Si vous n’êtes pas familiarisé avec la journalisation, la meilleure façon de vous y familiariser est de consulter les tutoriels (voir les liens à droite).

Les classes de base définies par le module, ainsi que leurs fonctions, sont énumérées ci-dessous.

Les enregistreurs (loggers en anglais) exposent l’interface que le code de l’application utilise directement.

Les gestionnaires (handlers) envoient les entrées de journal (créées par les loggers) vers les destinations voulues.

Les filtres (filters) fournissent un moyen de choisir finement quelles entrées de journal doivent être sorties.

Les formateurs (formatters) spécifient la structure de l’entrée de journal dans la sortie finale.

16.6.1. Objets Enregistreurs

Loggers have the following attributes and methods. Note that Loggers are never instantiated directly, but always through the module-level function logging.getLogger(name). Multiple calls to getLogger() with the same name will always return a reference to the same Logger object.

Le nom name est potentiellement une valeur avec plusieurs niveaux de hiérarchie, séparés par des points, comme truc.machin.bidule (bien qu’il puisse aussi être simplement truc, par exemple). Les enregistreurs qui sont plus bas dans la liste hiérarchique sont les enfants des enregistreurs plus haut dans la liste. Par exemple, pour un enregistreur nommé truc, les enregistreurs portant les noms truc.machin, truc.machin.bidule et truc.chose sont tous des descendants de truc. La hiérarchie des noms d’enregistreurs est analogue à la hiérarchie des paquets Python, et est identique à celle-ci si vous organisez vos enregistreurs par module en utilisant la construction recommandée logging.getLogger(__name__). C’est ainsi parce que dans un module, __name__ est le nom du module dans l’espace de noms des paquets Python.

class logging.Logger

propagate

Si cet attribut est évalué comme vrai, les événements enregistrés dans cet enregistreur seront transmis aux gestionnaires des enregistreurs de niveau supérieur (parents), en plus des gestionnaires attachés à cet enregistreur. Les messages sont transmis directement aux gestionnaires des enregistreurs parents — ni le niveau ni les filtres des enregistreurs ancestraux en question ne sont pris en compte.

S’il s’évalue comme faux, les messages de journalisation ne sont pas transmis aux gestionnaires des enregistreurs parents.

Le constructeur fixe cet attribut à True.

Note

Si vous associez un gestionnaire à un enregistreur et à un ou plusieurs de ses parents, il peut émettre le même enregistrement plusieurs fois. En général, vous ne devriez pas avoir besoin d’attacher un gestionnaire à plus d’un enregistreur — si vous l’attachez simplement à l’enregistreur approprié qui est le plus haut dans la hiérarchie des enregistreurs, alors il voit tous les événements enregistrés par tous les enregistreurs descendants, à condition que leur paramètre de propagation soit laissé à True. Un scénario courant est d’attacher les gestionnaires uniquement à l’enregistreur racine, et de laisser la propagation s’occuper du reste.

setLevel(level)

Fixe le seuil de cet enregistreur au niveau level. Les messages de journalisation qui sont moins graves que level sont ignorés ; les messages qui ont une gravité égale à level ou plus élevée sont émis par le ou les gestionnaires de cet enregistreur, à moins que le niveau d’un gestionnaire n’ait été fixé à un niveau de gravité plus élevé que level.

Lorsqu’un enregistreur est créé, le niveau est fixé à NOTSET (ce qui entraîne le traitement de tous les messages lorsque l’enregistreur est l’enregistreur racine, ou la délégation au parent lorsque l’enregistreur est un enregistreur non racine). Notez que l’enregistreur racine est créé avec le niveau WARNING.

Le terme « délégation au parent » signifie que si un enregistreur a un niveau de NOTSET, sa chaîne d’enregistreurs parents est parcourue jusqu’à ce qu’un parent ayant un niveau autre que NOTSET soit trouvé, ou que la racine soit atteinte.

Si un ancêtre est trouvé avec un niveau autre que NOTSET, alors le niveau de ce parent est traité comme le niveau effectif de l’enregistreur où la recherche de l’ancêtre a commencé, et est utilisé pour déterminer comment un événement d’enregistrement est traité.

Si la racine est atteinte, et qu’elle a un niveau de NOTSET, alors tous les messages sont traités. Sinon, le niveau de la racine est utilisé comme niveau effectif.

Voir Niveaux de journalisation pour la liste des niveaux.

Modifié dans la version 3.2: Le paramètre level accepte maintenant une représentation du niveau en chaîne de caractères (comme 'INFO') en alternative aux constantes entières comme INFO. Notez, cependant, que les niveaux sont stockés en interne sous forme d’entiers, et des méthodes telles que getEffectiveLevel() et isEnabledFor() renvoient/s’attendent à recevoir des entiers.

isEnabledFor(lvl)

Indicates if a message of severity lvl would be processed by this logger. This method checks first the module-level level set by logging.disable(lvl) and then the logger’s effective level as determined by getEffectiveLevel().

getEffectiveLevel()

Indique le niveau effectif pour cet enregistreur. Si une valeur autre que NOTSET a été définie en utilisant setLevel(), elle est renvoyée. Sinon, la hiérarchie est parcourue vers la racine jusqu’à ce qu’une valeur autre que NOTSET soit trouvée, et cette valeur est renvoyée. La valeur renvoyée est un entier, généralement l’un de logging.DEBUG, logging.INFO, etc.

getChild(suffix)

Renvoie un enregistreur qui est un enfant de cet enregistreur, tel que déterminé par le suffixe. Ainsi, logging.getLogger('abc').getChild('def.ghi') renvoie le même enregistreur que celui renvoyé par logging.getLogger('abc.def.ghi'). C’est une méthode de pure commodité, utile lorsque l’enregistreur parent est nommé en utilisant par exemple __name__ plutôt qu’une chaîne de caractères littérale.

Nouveau dans la version 3.2.

debug(msg, *args, **kwargs)

Logs a message with level DEBUG on this logger. The msg is the message format string, and the args are the arguments which are merged into msg using the string formatting operator. (Note that this means that you can use keywords in the format string, together with a single dictionary argument.)

There are three keyword arguments in kwargs which are inspected: exc_info, stack_info, and extra.

If exc_info does not evaluate as false, it causes exception information to be added to the logging message. If an exception tuple (in the format returned by sys.exc_info()) or an exception instance is provided, it is used; otherwise, sys.exc_info() is called to get the exception information.

The second optional keyword argument is stack_info, which defaults to False. If true, stack information is added to the logging message, including the actual logging call. Note that this is not the same stack information as that displayed through specifying exc_info: The former is stack frames from the bottom of the stack up to the logging call in the current thread, whereas the latter is information about stack frames which have been unwound, following an exception, while searching for exception handlers.

You can specify stack_info independently of exc_info, e.g. to just show how you got to a certain point in your code, even when no exceptions were raised. The stack frames are printed following a header line which says:

Stack (most recent call last):

This mimics the Traceback (most recent call last): which is used when displaying exception frames.

The third keyword argument is extra which can be used to pass a dictionary which is used to populate the __dict__ of the LogRecord created for the logging event with user-defined attributes. These custom attributes can then be used as you like. For example, they could be incorporated into logged messages. For example:

FORMAT = '%(asctime)-15s %(clientip)s %(user)-8s %(message)s'
logging.basicConfig(format=FORMAT)
d = {'clientip': '192.168.0.1', 'user': 'fbloggs'}
logger = logging.getLogger('tcpserver')
logger.warning('Protocol problem: %s', 'connection reset', extra=d)

would print something like

2006-02-08 22:20:02,165 192.168.0.1 fbloggs  Protocol problem: connection reset

The keys in the dictionary passed in extra should not clash with the keys used by the logging system. (See the Formatter documentation for more information on which keys are used by the logging system.)

If you choose to use these attributes in logged messages, you need to exercise some care. In the above example, for instance, the Formatter has been set up with a format string which expects “clientip” and “user” in the attribute dictionary of the LogRecord. If these are missing, the message will not be logged because a string formatting exception will occur. So in this case, you always need to pass the extra dictionary with these keys.

While this might be annoying, this feature is intended for use in specialized circumstances, such as multi-threaded servers where the same code executes in many contexts, and interesting conditions which arise are dependent on this context (such as remote client IP address and authenticated user name, in the above example). In such circumstances, it is likely that specialized Formatters would be used with particular Handlers.

Nouveau dans la version 3.2: The stack_info parameter was added.

Modifié dans la version 3.5: The exc_info parameter can now accept exception instances.

info(msg, *args, **kwargs)

Logs a message with level INFO on this logger. The arguments are interpreted as for debug().

warning(msg, *args, **kwargs)

Logs a message with level WARNING on this logger. The arguments are interpreted as for debug().

Note

There is an obsolete method warn which is functionally identical to warning. As warn is deprecated, please do not use it - use warning instead.

error(msg, *args, **kwargs)

Logs a message with level ERROR on this logger. The arguments are interpreted as for debug().

critical(msg, *args, **kwargs)

Logs a message with level CRITICAL on this logger. The arguments are interpreted as for debug().

log(lvl, msg, *args, **kwargs)

Logs a message with integer level lvl on this logger. The other arguments are interpreted as for debug().

exception(msg, *args, **kwargs)

Logs a message with level ERROR on this logger. The arguments are interpreted as for debug(). Exception info is added to the logging message. This method should only be called from an exception handler.

addFilter(filter)

Adds the specified filter filter to this logger.

removeFilter(filter)

Removes the specified filter filter from this logger.

filter(record)

Applies this logger’s filters to the record and returns a true value if the record is to be processed. The filters are consulted in turn, until one of them returns a false value. If none of them return a false value, the record will be processed (passed to handlers). If one returns a false value, no further processing of the record occurs.

addHandler(hdlr)

Adds the specified handler hdlr to this logger.

removeHandler(hdlr)

Removes the specified handler hdlr from this logger.

findCaller(stack_info=False)

Finds the caller’s source filename and line number. Returns the filename, line number, function name and stack information as a 4-element tuple. The stack information is returned as None unless stack_info is True.

handle(record)

Handles a record by passing it to all handlers associated with this logger and its ancestors (until a false value of propagate is found). This method is used for unpickled records received from a socket, as well as those created locally. Logger-level filtering is applied using filter().

makeRecord(name, lvl, fn, lno, msg, args, exc_info, func=None, extra=None, sinfo=None)

This is a factory method which can be overridden in subclasses to create specialized LogRecord instances.

hasHandlers()

Checks to see if this logger has any handlers configured. This is done by looking for handlers in this logger and its parents in the logger hierarchy. Returns True if a handler was found, else False. The method stops searching up the hierarchy whenever a logger with the “propagate” attribute set to false is found - that will be the last logger which is checked for the existence of handlers.

Nouveau dans la version 3.2.

Modifié dans la version 3.7: Loggers can now be picked and unpickled.

16.6.2. Niveaux de journalisation

Les valeurs numériques des niveaux de journalisation sont données dans le tableau suivant. Celles-ci n’ont d’intérêt que si vous voulez définir vos propres niveaux, avec des valeurs spécifiques par rapport aux niveaux prédéfinis. Si vous définissez un niveau avec la même valeur numérique, il écrase la valeur prédéfinie ; le nom prédéfini est perdu.

Niveau

Valeur numérique

CRITICAL

50

ERROR

40

WARNING

30

INFO

20

DEBUG

10

NOTSET

0

16.6.3. Handler Objects

Handlers have the following attributes and methods. Note that Handler is never instantiated directly; this class acts as a base for more useful subclasses. However, the __init__() method in subclasses needs to call Handler.__init__().

class logging.Handler

__init__(level=NOTSET)

Initializes the Handler instance by setting its level, setting the list of filters to the empty list and creating a lock (using createLock()) for serializing access to an I/O mechanism.

createLock()

Initializes a thread lock which can be used to serialize access to underlying I/O functionality which may not be threadsafe.

acquire()

Acquires the thread lock created with createLock().

release()

Releases the thread lock acquired with acquire().

setLevel(level)

Sets the threshold for this handler to level. Logging messages which are less severe than level will be ignored. When a handler is created, the level is set to NOTSET (which causes all messages to be processed).

Voir Niveaux de journalisation pour la liste des niveaux.

Modifié dans la version 3.2: The level parameter now accepts a string representation of the level such as “INFO” as an alternative to the integer constants such as INFO.

setFormatter(fmt)

Sets the Formatter for this handler to fmt.

addFilter(filter)

Adds the specified filter filter to this handler.

removeFilter(filter)

Removes the specified filter filter from this handler.

filter(record)

Applies this handler’s filters to the record and returns a true value if the record is to be processed. The filters are consulted in turn, until one of them returns a false value. If none of them return a false value, the record will be emitted. If one returns a false value, the handler will not emit the record.

flush()

Ensure all logging output has been flushed. This version does nothing and is intended to be implemented by subclasses.

close()

Tidy up any resources used by the handler. This version does no output but removes the handler from an internal list of handlers which is closed when shutdown() is called. Subclasses should ensure that this gets called from overridden close() methods.

handle(record)

Conditionally emits the specified logging record, depending on filters which may have been added to the handler. Wraps the actual emission of the record with acquisition/release of the I/O thread lock.

handleError(record)

This method should be called from handlers when an exception is encountered during an emit() call. If the module-level attribute raiseExceptions is False, exceptions get silently ignored. This is what is mostly wanted for a logging system - most users will not care about errors in the logging system, they are more interested in application errors. You could, however, replace this with a custom handler if you wish. The specified record is the one which was being processed when the exception occurred. (The default value of raiseExceptions is True, as that is more useful during development).

format(record)

Do formatting for a record - if a formatter is set, use it. Otherwise, use the default formatter for the module.

emit(record)

Do whatever it takes to actually log the specified logging record. This version is intended to be implemented by subclasses and so raises a NotImplementedError.

For a list of handlers included as standard, see logging.handlers.

16.6.4. Formatter Objects

Formatter objects have the following attributes and methods. They are responsible for converting a LogRecord to (usually) a string which can be interpreted by either a human or an external system. The base Formatter allows a formatting string to be specified. If none is supplied, the default value of '%(message)s' is used, which just includes the message in the logging call. To have additional items of information in the formatted output (such as a timestamp), keep reading.

A Formatter can be initialized with a format string which makes use of knowledge of the LogRecord attributes - such as the default value mentioned above making use of the fact that the user’s message and arguments are pre-formatted into a LogRecord’s message attribute. This format string contains standard Python %-style mapping keys. See section Formatage de chaines à la printf for more information on string formatting.

The useful mapping keys in a LogRecord are given in the section on LogRecord attributes.

class logging.Formatter(fmt=None, datefmt=None, style='%')

Returns a new instance of the Formatter class. The instance is initialized with a format string for the message as a whole, as well as a format string for the date/time portion of a message. If no fmt is specified, '%(message)s' is used. If no datefmt is specified, a format is used which is described in the formatTime() documentation.

The style parameter can be one of “%”, “{“ or “$” and determines how the format string will be merged with its data: using one of %-formatting, str.format() or string.Template. See Using particular formatting styles throughout your application for more information on using {- and $-formatting for log messages.

Modifié dans la version 3.2: The style parameter was added.

format(record)

The record’s attribute dictionary is used as the operand to a string formatting operation. Returns the resulting string. Before formatting the dictionary, a couple of preparatory steps are carried out. The message attribute of the record is computed using msg % args. If the formatting string contains '(asctime)', formatTime() is called to format the event time. If there is exception information, it is formatted using formatException() and appended to the message. Note that the formatted exception information is cached in attribute exc_text. This is useful because the exception information can be pickled and sent across the wire, but you should be careful if you have more than one Formatter subclass which customizes the formatting of exception information. In this case, you will have to clear the cached value after a formatter has done its formatting, so that the next formatter to handle the event doesn’t use the cached value but recalculates it afresh.

If stack information is available, it’s appended after the exception information, using formatStack() to transform it if necessary.

formatTime(record, datefmt=None)

This method should be called from format() by a formatter which wants to make use of a formatted time. This method can be overridden in formatters to provide for any specific requirement, but the basic behavior is as follows: if datefmt (a string) is specified, it is used with time.strftime() to format the creation time of the record. Otherwise, the format “%Y-%m-%d %H:%M:%S,uuu” is used, where the uuu part is a millisecond value and the other letters are as per the time.strftime() documentation. An example time in this format is 2003-01-23 00:29:50,411. The resulting string is returned.

This function uses a user-configurable function to convert the creation time to a tuple. By default, time.localtime() is used; to change this for a particular formatter instance, set the converter attribute to a function with the same signature as time.localtime() or time.gmtime(). To change it for all formatters, for example if you want all logging times to be shown in GMT, set the converter attribute in the Formatter class.

Modifié dans la version 3.3: Previously, the default format was hard-coded as in this example: 2010-09-06 22:38:15,292 where the part before the comma is handled by a strptime format string ('%Y-%m-%d %H:%M:%S'), and the part after the comma is a millisecond value. Because strptime does not have a format placeholder for milliseconds, the millisecond value is appended using another format string, '%s,%03d' — and both of these format strings have been hardcoded into this method. With the change, these strings are defined as class-level attributes which can be overridden at the instance level when desired. The names of the attributes are default_time_format (for the strptime format string) and default_msec_format (for appending the millisecond value).

formatException(exc_info)

Formats the specified exception information (a standard exception tuple as returned by sys.exc_info()) as a string. This default implementation just uses traceback.print_exception(). The resulting string is returned.

formatStack(stack_info)

Formats the specified stack information (a string as returned by traceback.print_stack(), but with the last newline removed) as a string. This default implementation just returns the input value.

16.6.5. Filter Objects

Filters can be used by Handlers and Loggers for more sophisticated filtering than is provided by levels. The base filter class only allows events which are below a certain point in the logger hierarchy. For example, a filter initialized with “A.B” will allow events logged by loggers “A.B”, “A.B.C”, “A.B.C.D”, “A.B.D” etc. but not “A.BB”, “B.A.B” etc. If initialized with the empty string, all events are passed.

class logging.Filter(name='')

Returns an instance of the Filter class. If name is specified, it names a logger which, together with its children, will have its events allowed through the filter. If name is the empty string, allows every event.

filter(record)

Is the specified record to be logged? Returns zero for no, nonzero for yes. If deemed appropriate, the record may be modified in-place by this method.

Note that filters attached to handlers are consulted before an event is emitted by the handler, whereas filters attached to loggers are consulted whenever an event is logged (using debug(), info(), etc.), before sending an event to handlers. This means that events which have been generated by descendant loggers will not be filtered by a logger’s filter setting, unless the filter has also been applied to those descendant loggers.

You don’t actually need to subclass Filter: you can pass any instance which has a filter method with the same semantics.

Modifié dans la version 3.2: You don’t need to create specialized Filter classes, or use other classes with a filter method: you can use a function (or other callable) as a filter. The filtering logic will check to see if the filter object has a filter attribute: if it does, it’s assumed to be a Filter and its filter() method is called. Otherwise, it’s assumed to be a callable and called with the record as the single parameter. The returned value should conform to that returned by filter().

Although filters are used primarily to filter records based on more sophisticated criteria than levels, they get to see every record which is processed by the handler or logger they’re attached to: this can be useful if you want to do things like counting how many records were processed by a particular logger or handler, or adding, changing or removing attributes in the LogRecord being processed. Obviously changing the LogRecord needs to be done with some care, but it does allow the injection of contextual information into logs (see Using Filters to impart contextual information).

16.6.6. LogRecord Objects

LogRecord instances are created automatically by the Logger every time something is logged, and can be created manually via makeLogRecord() (for example, from a pickled event received over the wire).

class logging.LogRecord(name, level, pathname, lineno, msg, args, exc_info, func=None, sinfo=None)

Contains all the information pertinent to the event being logged.

The primary information is passed in msg and args, which are combined using msg % args to create the message field of the record.

Paramètres

name – The name of the logger used to log the event represented by this LogRecord. Note that this name will always have this value, even though it may be emitted by a handler attached to a different (ancestor) logger.

level – The numeric level of the logging event (one of DEBUG, INFO etc.) Note that this is converted to two attributes of the LogRecord: levelno for the numeric value and levelname for the corresponding level name.

pathname – The full pathname of the source file where the logging call was made.

lineno – The line number in the source file where the logging call was made.

msg – The event description message, possibly a format string with placeholders for variable data.

args – Variable data to merge into the msg argument to obtain the event description.

exc_info – An exception tuple with the current exception information, or None if no exception information is available.

func – The name of the function or method from which the logging call was invoked.

sinfo – A text string representing stack information from the base of the stack in the current thread, up to the logging call.

getMessage()

Returns the message for this LogRecord instance after merging any user-supplied arguments with the message. If the user-supplied message argument to the logging call is not a string, str() is called on it to convert it to a string. This allows use of user-defined classes as messages, whose __str__ method can return the actual format string to be used.

Modifié dans la version 3.2: The creation of a LogRecord has been made more configurable by providing a factory which is used to create the record. The factory can be set using getLogRecordFactory() and setLogRecordFactory() (see this for the factory’s signature).

This functionality can be used to inject your own values into a LogRecord at creation time. You can use the following pattern:

old_factory = logging.getLogRecordFactory()

def record_factory(*args, **kwargs):
    record = old_factory(*args, **kwargs)
    record.custom_attribute = 0xdecafbad
    return record

logging.setLogRecordFactory(record_factory)

With this pattern, multiple factories could be chained, and as long as they don’t overwrite each other’s attributes or unintentionally overwrite the standard attributes listed above, there should be no surprises.

16.6.7. LogRecord attributes

The LogRecord has a number of attributes, most of which are derived from the parameters to the constructor. (Note that the names do not always correspond exactly between the LogRecord constructor parameters and the LogRecord attributes.) These attributes can be used to merge data from the record into the format string. The following table lists (in alphabetical order) the attribute names, their meanings and the corresponding placeholder in a %-style format string.

If you are using {}-formatting (str.format()), you can use {attrname} as the placeholder in the format string. If you are using $-formatting (string.Template), use the form ${attrname}. In both cases, of course, replace attrname with the actual attribute name you want to use.

In the case of {}-formatting, you can specify formatting flags by placing them after the attribute name, separated from it with a colon. For example: a placeholder of {msecs:03d} would format a millisecond value of 4 as 004. Refer to the str.format() documentation for full details on the options available to you.

Attribute name

Format

Description

args

You shouldn’t need to format this yourself.

The tuple of arguments merged into msg to produce message, or a dict whose values are used for the merge (when there is only one argument, and it is a dictionary).

asctime

%(asctime)s

Human-readable time when the LogRecord was created. By default this is of the form “2003-07-08 16:49:45,896” (the numbers after the comma are millisecond portion of the time).

created

%(created)f

Time when the LogRecord was created (as returned by time.time()).

exc_info

You shouldn’t need to format this yourself.

Exception tuple (à la sys.exc_info) or, if no exception has occurred, None.

filename

%(filename)s

Filename portion of pathname.

funcName

%(funcName)s

Name of function containing the logging call.

levelname

%(levelname)s

Text logging level for the message ('DEBUG', 'INFO', 'WARNING', 'ERROR', 'CRITICAL').

levelno

%(levelno)s

Numeric logging level for the message (DEBUG, INFO, WARNING, ERROR, CRITICAL).

lineno

%(lineno)d

Source line number where the logging call was issued (if available).

message

%(message)s

The logged message, computed as msg % args. This is set when Formatter.format() is invoked.

module

%(module)s

Module (name portion of filename).

msecs

%(msecs)d

Millisecond portion of the time when the LogRecord was created.

msg

You shouldn’t need to format this yourself.

The format string passed in the original logging call. Merged with args to produce message, or an arbitrary object (see Utilisation d’objets arbitraires comme messages).

name

%(name)s

Name of the logger used to log the call.

pathname

%(pathname)s

Full pathname of the source file where the logging call was issued (if available).

process

%(process)d

Process ID (if available).

processName

%(processName)s

Process name (if available).

relativeCreated

%(relativeCreated)d

Time in milliseconds when the LogRecord was created, relative to the time the logging module was loaded.

stack_info

You shouldn’t need to format this yourself.

Stack frame information (where available) from the bottom of the stack in the current thread, up to and including the stack frame of the logging call which resulted in the creation of this record.

thread

%(thread)d

Thread ID (if available).

threadName

%(threadName)s

Thread name (if available).

Modifié dans la version 3.1: processName was added.

16.6.8. LoggerAdapter Objects

LoggerAdapter instances are used to conveniently pass contextual information into logging calls. For a usage example, see the section on adding contextual information to your logging output.

class logging.LoggerAdapter(logger, extra)

Returns an instance of LoggerAdapter initialized with an underlying Logger instance and a dict-like object.

process(msg, kwargs)

Modifies the message and/or keyword arguments passed to a logging call in order to insert contextual information. This implementation takes the object passed as extra to the constructor and adds it to kwargs using key “extra”. The return value is a (msg, kwargs) tuple which has the (possibly modified) versions of the arguments passed in.

In addition to the above, LoggerAdapter supports the following methods of Logger: debug(), info(), warning(), error(), exception(), critical(), log(), isEnabledFor(), getEffectiveLevel(), setLevel() and hasHandlers(). These methods have the same signatures as their counterparts in Logger, so you can use the two types of instances interchangeably.

Modifié dans la version 3.2: The isEnabledFor(), getEffectiveLevel(), setLevel() and hasHandlers() methods were added to LoggerAdapter. These methods delegate to the underlying logger.

16.6.9. Thread Safety

The logging module is intended to be thread-safe without any special work needing to be done by its clients. It achieves this though using threading locks; there is one lock to serialize access to the module’s shared data, and each handler also creates a lock to serialize access to its underlying I/O.

If you are implementing asynchronous signal handlers using the signal module, you may not be able to use logging from within such handlers. This is because lock implementations in the threading module are not always re-entrant, and so cannot be invoked from such signal handlers.

16.6.10. Fonctions de niveau module

In addition to the classes described above, there are a number of module-level functions.

logging.getLogger(name=None)

Return a logger with the specified name or, if name is None, return a logger which is the root logger of the hierarchy. If specified, the name is typically a dot-separated hierarchical name like “a”, “a.b” or “a.b.c.d”. Choice of these names is entirely up to the developer who is using logging.

All calls to this function with a given name return the same logger instance. This means that logger instances never need to be passed between different parts of an application.

logging.getLoggerClass()

Return either the standard Logger class, or the last class passed to setLoggerClass(). This function may be called from within a new class definition, to ensure that installing a customized Logger class will not undo customizations already applied by other code. For example:

class MyLogger(logging.getLoggerClass()):
    # ... override behaviour here

logging.getLogRecordFactory()

Return a callable which is used to create a LogRecord.

Nouveau dans la version 3.2: This function has been provided, along with setLogRecordFactory(), to allow developers more control over how the LogRecord representing a logging event is constructed.

See setLogRecordFactory() for more information about the how the factory is called.

logging.debug(msg, *args, **kwargs)

Logs a message with level DEBUG on the root logger. The msg is the message format string, and the args are the arguments which are merged into msg using the string formatting operator. (Note that this means that you can use keywords in the format string, together with a single dictionary argument.)

There are three keyword arguments in kwargs which are inspected: exc_info which, if it does not evaluate as false, causes exception information to be added to the logging message. If an exception tuple (in the format returned by sys.exc_info()) or an exception instance is provided, it is used; otherwise, sys.exc_info() is called to get the exception information.

The second optional keyword argument is stack_info, which defaults to False. If true, stack information is added to the logging message, including the actual logging call. Note that this is not the same stack information as that displayed through specifying exc_info: The former is stack frames from the bottom of the stack up to the logging call in the current thread, whereas the latter is information about stack frames which have been unwound, following an exception, while searching for exception handlers.

You can specify stack_info independently of exc_info, e.g. to just show how you got to a certain point in your code, even when no exceptions were raised. The stack frames are printed following a header line which says:

Stack (most recent call last):

This mimics the Traceback (most recent call last): which is used when displaying exception frames.

The third optional keyword argument is extra which can be used to pass a dictionary which is used to populate the __dict__ of the LogRecord created for the logging event with user-defined attributes. These custom attributes can then be used as you like. For example, they could be incorporated into logged messages. For example:

FORMAT = '%(asctime)-15s %(clientip)s %(user)-8s %(message)s'
logging.basicConfig(format=FORMAT)
d = {'clientip': '192.168.0.1', 'user': 'fbloggs'}
logging.warning('Protocol problem: %s', 'connection reset', extra=d)

would print something like:

2006-02-08 22:20:02,165 192.168.0.1 fbloggs  Protocol problem: connection reset

The keys in the dictionary passed in extra should not clash with the keys used by the logging system. (See the Formatter documentation for more information on which keys are used by the logging system.)

If you choose to use these attributes in logged messages, you need to exercise some care. In the above example, for instance, the Formatter has been set up with a format string which expects “clientip” and “user” in the attribute dictionary of the LogRecord. If these are missing, the message will not be logged because a string formatting exception will occur. So in this case, you always need to pass the extra dictionary with these keys.

While this might be annoying, this feature is intended for use in specialized circumstances, such as multi-threaded servers where the same code executes in many contexts, and interesting conditions which arise are dependent on this context (such as remote client IP address and authenticated user name, in the above example). In such circumstances, it is likely that specialized Formatters would be used with particular Handlers.

Nouveau dans la version 3.2: The stack_info parameter was added.

logging.info(msg, *args, **kwargs)

Logs a message with level INFO on the root logger. The arguments are interpreted as for debug().

logging.warning(msg, *args, **kwargs)

Logs a message with level WARNING on the root logger. The arguments are interpreted as for debug().

Note

There is an obsolete function warn which is functionally identical to warning. As warn is deprecated, please do not use it - use warning instead.

logging.error(msg, *args, **kwargs)

Logs a message with level ERROR on the root logger. The arguments are interpreted as for debug().

logging.critical(msg, *args, **kwargs)

Logs a message with level CRITICAL on the root logger. The arguments are interpreted as for debug().

logging.exception(msg, *args, **kwargs)

Logs a message with level ERROR on the root logger. The arguments are interpreted as for debug(). Exception info is added to the logging message. This function should only be called from an exception handler.

logging.log(level, msg, *args, **kwargs)

Logs a message with level level on the root logger. The other arguments are interpreted as for debug().

Note

The above module-level convenience functions, which delegate to the root logger, call basicConfig() to ensure that at least one handler is available. Because of this, they should not be used in threads, in versions of Python earlier than 2.7.1 and 3.2, unless at least one handler has been added to the root logger before the threads are started. In earlier versions of Python, due to a thread safety shortcoming in basicConfig(), this can (under rare circumstances) lead to handlers being added multiple times to the root logger, which can in turn lead to multiple messages for the same event.

logging.disable(lvl=CRITICAL)

Provides an overriding level lvl for all loggers which takes precedence over the logger’s own level. When the need arises to temporarily throttle logging output down across the whole application, this function can be useful. Its effect is to disable all logging calls of severity lvl and below, so that if you call it with a value of INFO, then all INFO and DEBUG events would be discarded, whereas those of severity WARNING and above would be processed according to the logger’s effective level. If logging.disable(logging.NOTSET) is called, it effectively removes this overriding level, so that logging output again depends on the effective levels of individual loggers.

Note that if you have defined any custom logging level higher than CRITICAL (this is not recommended), you won’t be able to rely on the default value for the lvl parameter, but will have to explicitly supply a suitable value.

Modifié dans la version 3.7: The lvl parameter was defaulted to level CRITICAL. See Issue #28524 for more information about this change.

logging.addLevelName(lvl, levelName)

Associates level lvl with text levelName in an internal dictionary, which is used to map numeric levels to a textual representation, for example when a Formatter formats a message. This function can also be used to define your own levels. The only constraints are that all levels used must be registered using this function, levels should be positive integers and they should increase in increasing order of severity.

Note

If you are thinking of defining your own levels, please see the section on Niveaux personnalisés.

logging.getLevelName(lvl)

Returns the textual representation of logging level lvl. If the level is one of the predefined levels CRITICAL, ERROR, WARNING, INFO or DEBUG then you get the corresponding string. If you have associated levels with names using addLevelName() then the name you have associated with lvl is returned. If a numeric value corresponding to one of the defined levels is passed in, the corresponding string representation is returned. Otherwise, the string “Level %s” % lvl is returned.

Note

Levels are internally integers (as they need to be compared in the logging logic). This function is used to convert between an integer level and the level name displayed in the formatted log output by means of the %(levelname)s format specifier (see LogRecord attributes).

Modifié dans la version 3.4: In Python versions earlier than 3.4, this function could also be passed a text level, and would return the corresponding numeric value of the level. This undocumented behaviour was considered a mistake, and was removed in Python 3.4, but reinstated in 3.4.2 due to retain backward compatibility.

logging.makeLogRecord(attrdict)

Creates and returns a new LogRecord instance whose attributes are defined by attrdict. This function is useful for taking a pickled LogRecord attribute dictionary, sent over a socket, and reconstituting it as a LogRecord instance at the receiving end.

logging.basicConfig(**kwargs)

Does basic configuration for the logging system by creating a StreamHandler with a default Formatter and adding it to the root logger. The functions debug(), info(), warning(), error() and critical() will call basicConfig() automatically if no handlers are defined for the root logger.

This function does nothing if the root logger already has handlers configured for it.

Note

This function should be called from the main thread before other threads are started. In versions of Python prior to 2.7.1 and 3.2, if this function is called from multiple threads, it is possible (in rare circumstances) that a handler will be added to the root logger more than once, leading to unexpected results such as messages being duplicated in the log.

The following keyword arguments are supported.

Format

Description

filename

Specifies that a FileHandler be created, using the specified filename, rather than a StreamHandler.

filemode

If filename is specified, open the file in this mode. Defaults to 'a'.

format

Use the specified format string for the handler.

datefmt

Use the specified date/time format, as accepted by time.strftime().

style

If format is specified, use this style for the format string. One of '%', '{' or '$' for printf-style, str.format() or string.Template respectively. Defaults to '%'.

level

Set the root logger level to the specified level.

stream

Use the specified stream to initialize the StreamHandler. Note that this argument is incompatible with filename - if both are present, a ValueError is raised.

handlers

If specified, this should be an iterable of already created handlers to add to the root logger. Any handlers which don’t already have a formatter set will be assigned the default formatter created in this function. Note that this argument is incompatible with filename or stream - if both are present, a ValueError is raised.

Modifié dans la version 3.2: The style argument was added.

Modifié dans la version 3.3: The handlers argument was added. Additional checks were added to catch situations where incompatible arguments are specified (e.g. handlers together with stream or filename, or stream together with filename).

logging.shutdown()

Informs the logging system to perform an orderly shutdown by flushing and closing all handlers. This should be called at application exit and no further use of the logging system should be made after this call.

logging.setLoggerClass(klass)

Tells the logging system to use the class klass when instantiating a logger. The class should define __init__() such that only a name argument is required, and the __init__() should call Logger.__init__(). This function is typically called before any loggers are instantiated by applications which need to use custom logger behavior.

logging.setLogRecordFactory(factory)

Set a callable which is used to create a LogRecord.

Paramètres

factory – The factory callable to be used to instantiate a log record.

Nouveau dans la version 3.2: This function has been provided, along with getLogRecordFactory(), to allow developers more control over how the LogRecord representing a logging event is constructed.

The factory has the following signature:

factory(name, level, fn, lno, msg, args, exc_info, func=None, sinfo=None, **kwargs)

name

The logger name.

level

The logging level (numeric).

fn

The full pathname of the file where the logging call was made.

lno

The line number in the file where the logging call was made.

msg

The logging message.

args

The arguments for the logging message.

exc_info

An exception tuple, or None.

func

The name of the function or method which invoked the logging call.

sinfo

A stack traceback such as is provided by traceback.print_stack(), showing the call hierarchy.

kwargs

Additional keyword arguments.

16.6.11. Module-Level Attributes

logging.lastResort

A « handler of last resort » is available through this attribute. This is a StreamHandler writing to sys.stderr with a level of WARNING, and is used to handle logging events in the absence of any logging configuration. The end result is to just print the message to sys.stderr. This replaces the earlier error message saying that « no handlers could be found for logger XYZ ». If you need the earlier behaviour for some reason, lastResort can be set to None.

Nouveau dans la version 3.2.

16.6.12. Integration with the warnings module

The captureWarnings() function can be used to integrate logging with the warnings module.

logging.captureWarnings(capture)

This function is used to turn the capture of warnings by logging on and off.

If capture is True, warnings issued by the warnings module will be redirected to the logging system. Specifically, a warning will be formatted using warnings.formatwarning() and the resulting string logged to a logger named 'py.warnings' with a severity of WARNING.

If capture is False, the redirection of warnings to the logging system will stop, and warnings will be redirected to their original destinations (i.e. those in effect before captureWarnings(True) was called).

Voir aussi

Module logging.config

API de configuration pour le module de journalisation.

Module logging.handlers

Gestionnaires utiles inclus avec le module de journalisation.

PEP 282 [https://www.python.org/dev/peps/pep-0282] - A Logging System

The proposal which described this feature for inclusion in the Python standard library.

Original Python logging package [https://www.red-dove.com/python_logging.html]

This is the original source for the logging package. The version of the package available from this site is suitable for use with Python 1.5.2, 2.1.x and 2.2.x, which do not include the logging package in the standard library.

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16.7. logging.config — Logging configuration

Source code: Lib/logging/config.py [https://github.com/python/cpython/tree/3.6/Lib/logging/config.py]

Important

This page contains only reference information. For tutorials, please see

Basic Tutorial

Advanced Tutorial

Logging Cookbook

This section describes the API for configuring the logging module.

16.7.1. Configuration functions

The following functions configure the logging module. They are located in the logging.config module. Their use is optional — you can configure the logging module using these functions or by making calls to the main API (defined in logging itself) and defining handlers which are declared either in logging or logging.handlers.

logging.config.dictConfig(config)

Takes the logging configuration from a dictionary. The contents of this dictionary are described in Configuration dictionary schema below.

If an error is encountered during configuration, this function will raise a ValueError, TypeError, AttributeError or ImportError with a suitably descriptive message. The following is a (possibly incomplete) list of conditions which will raise an error:

A level which is not a string or which is a string not corresponding to an actual logging level.

A propagate value which is not a boolean.

An id which does not have a corresponding destination.

A non-existent handler id found during an incremental call.

An invalid logger name.

Inability to resolve to an internal or external object.

Parsing is performed by the DictConfigurator class, whose constructor is passed the dictionary used for configuration, and has a configure() method. The logging.config module has a callable attribute dictConfigClass which is initially set to DictConfigurator. You can replace the value of dictConfigClass with a suitable implementation of your own.

dictConfig() calls dictConfigClass passing the specified dictionary, and then calls the configure() method on the returned object to put the configuration into effect:

def dictConfig(config):
    dictConfigClass(config).configure()

For example, a subclass of DictConfigurator could call DictConfigurator.__init__() in its own __init__(), then set up custom prefixes which would be usable in the subsequent configure() call. dictConfigClass would be bound to this new subclass, and then dictConfig() could be called exactly as in the default, uncustomized state.

Nouveau dans la version 3.2.

logging.config.fileConfig(fname, defaults=None, disable_existing_loggers=True)

Reads the logging configuration from a configparser-format file. The format of the file should be as described in Configuration file format. This function can be called several times from an application, allowing an end user to select from various pre-canned configurations (if the developer provides a mechanism to present the choices and load the chosen configuration).

Paramètres

fname – A filename, or a file-like object, or an instance derived from RawConfigParser. If a RawConfigParser-derived instance is passed, it is used as is. Otherwise, a Configparser is instantiated, and the configuration read by it from the object passed in fname. If that has a readline() method, it is assumed to be a file-like object and read using read_file(); otherwise, it is assumed to be a filename and passed to read().

defaults – Defaults to be passed to the ConfigParser can be specified in this argument.

disable_existing_loggers – If specified as False, loggers which exist when this call is made are left enabled. The default is True because this enables old behaviour in a backward-compatible way. This behaviour is to disable any existing loggers unless they or their ancestors are explicitly named in the logging configuration.

Modifié dans la version 3.4: An instance of a subclass of RawConfigParser is now accepted as a value for fname. This facilitates:

Use of a configuration file where logging configuration is just part of the overall application configuration.

Use of a configuration read from a file, and then modified by the using application (e.g. based on command-line parameters or other aspects of the runtime environment) before being passed to fileConfig.

logging.config.listen(port=DEFAULT_LOGGING_CONFIG_PORT, verify=None)

Starts up a socket server on the specified port, and listens for new configurations. If no port is specified, the module’s default DEFAULT_LOGGING_CONFIG_PORT is used. Logging configurations will be sent as a file suitable for processing by dictConfig() or fileConfig(). Returns a Thread instance on which you can call start() to start the server, and which you can join() when appropriate. To stop the server, call stopListening().

The verify argument, if specified, should be a callable which should verify whether bytes received across the socket are valid and should be processed. This could be done by encrypting and/or signing what is sent across the socket, such that the verify callable can perform signature verification and/or decryption. The verify callable is called with a single argument - the bytes received across the socket - and should return the bytes to be processed, or None to indicate that the bytes should be discarded. The returned bytes could be the same as the passed in bytes (e.g. when only verification is done), or they could be completely different (perhaps if decryption were performed).

To send a configuration to the socket, read in the configuration file and send it to the socket as a sequence of bytes preceded by a four-byte length string packed in binary using struct.pack('>L', n).

Note

Because portions of the configuration are passed through eval(), use of this function may open its users to a security risk. While the function only binds to a socket on localhost, and so does not accept connections from remote machines, there are scenarios where untrusted code could be run under the account of the process which calls listen(). Specifically, if the process calling listen() runs on a multi-user machine where users cannot trust each other, then a malicious user could arrange to run essentially arbitrary code in a victim user’s process, simply by connecting to the victim’s listen() socket and sending a configuration which runs whatever code the attacker wants to have executed in the victim’s process. This is especially easy to do if the default port is used, but not hard even if a different port is used). To avoid the risk of this happening, use the verify argument to listen() to prevent unrecognised configurations from being applied.

Modifié dans la version 3.4: The verify argument was added.

Note

If you want to send configurations to the listener which don’t disable existing loggers, you will need to use a JSON format for the configuration, which will use dictConfig() for configuration. This method allows you to specify disable_existing_loggers as False in the configuration you send.

logging.config.stopListening()

Stops the listening server which was created with a call to listen(). This is typically called before calling join() on the return value from listen().

16.7.2. Configuration dictionary schema

Describing a logging configuration requires listing the various objects to create and the connections between them; for example, you may create a handler named “console” and then say that the logger named “startup” will send its messages to the “console” handler. These objects aren’t limited to those provided by the logging module because you might write your own formatter or handler class. The parameters to these classes may also need to include external objects such as sys.stderr. The syntax for describing these objects and connections is defined in Object connections below.

16.7.2.1. Dictionary Schema Details

The dictionary passed to dictConfig() must contain the following keys:

version - to be set to an integer value representing the schema version. The only valid value at present is 1, but having this key allows the schema to evolve while still preserving backwards compatibility.

All other keys are optional, but if present they will be interpreted as described below. In all cases below where a “configuring dict” is mentioned, it will be checked for the special '()' key to see if a custom instantiation is required. If so, the mechanism described in User-defined objects below is used to create an instance; otherwise, the context is used to determine what to instantiate.

formatters - the corresponding value will be a dict in which each key is a formatter id and each value is a dict describing how to configure the corresponding Formatter instance.

The configuring dict is searched for keys format and datefmt (with defaults of None) and these are used to construct a Formatter instance.

filters - the corresponding value will be a dict in which each key is a filter id and each value is a dict describing how to configure the corresponding Filter instance.

The configuring dict is searched for the key name (defaulting to the empty string) and this is used to construct a logging.Filter instance.

handlers - the corresponding value will be a dict in which each key is a handler id and each value is a dict describing how to configure the corresponding Handler instance.

The configuring dict is searched for the following keys:

class (mandatory). This is the fully qualified name of the handler class.

level (optional). The level of the handler.

formatter (optional). The id of the formatter for this handler.

filters (optional). A list of ids of the filters for this handler.

All other keys are passed through as keyword arguments to the handler’s constructor. For example, given the snippet:

handlers:
  console:
    class : logging.StreamHandler
    formatter: brief
    level   : INFO
    filters: [allow_foo]
    stream  : ext://sys.stdout
  file:
    class : logging.handlers.RotatingFileHandler
    formatter: precise
    filename: logconfig.log
    maxBytes: 1024
    backupCount: 3

the handler with id console is instantiated as a logging.StreamHandler, using sys.stdout as the underlying stream. The handler with id file is instantiated as a logging.handlers.RotatingFileHandler with the keyword arguments filename='logconfig.log', maxBytes=1024, backupCount=3.

loggers - the corresponding value will be a dict in which each key is a logger name and each value is a dict describing how to configure the corresponding Logger instance.

The configuring dict is searched for the following keys:

level (optional). The level of the logger.

propagate (optional). The propagation setting of the logger.

filters (optional). A list of ids of the filters for this logger.

handlers (optional). A list of ids of the handlers for this logger.

The specified loggers will be configured according to the level, propagation, filters and handlers specified.

root - this will be the configuration for the root logger. Processing of the configuration will be as for any logger, except that the propagate setting will not be applicable.

incremental - whether the configuration is to be interpreted as incremental to the existing configuration. This value defaults to False, which means that the specified configuration replaces the existing configuration with the same semantics as used by the existing fileConfig() API.

If the specified value is True, the configuration is processed as described in the section on Incremental Configuration.

disable_existing_loggers - whether any existing loggers are to be disabled. This setting mirrors the parameter of the same name in fileConfig(). If absent, this parameter defaults to True. This value is ignored if incremental is True.

16.7.2.2. Incremental Configuration

It is difficult to provide complete flexibility for incremental configuration. For example, because objects such as filters and formatters are anonymous, once a configuration is set up, it is not possible to refer to such anonymous objects when augmenting a configuration.

Furthermore, there is not a compelling case for arbitrarily altering the object graph of loggers, handlers, filters, formatters at run-time, once a configuration is set up; the verbosity of loggers and handlers can be controlled just by setting levels (and, in the case of loggers, propagation flags). Changing the object graph arbitrarily in a safe way is problematic in a multi-threaded environment; while not impossible, the benefits are not worth the complexity it adds to the implementation.

Thus, when the incremental key of a configuration dict is present and is True, the system will completely ignore any formatters and filters entries, and process only the level settings in the handlers entries, and the level and propagate settings in the loggers and root entries.

Using a value in the configuration dict lets configurations to be sent over the wire as pickled dicts to a socket listener. Thus, the logging verbosity of a long-running application can be altered over time with no need to stop and restart the application.

16.7.2.3. Object connections

The schema describes a set of logging objects - loggers, handlers, formatters, filters - which are connected to each other in an object graph. Thus, the schema needs to represent connections between the objects. For example, say that, once configured, a particular logger has attached to it a particular handler. For the purposes of this discussion, we can say that the logger represents the source, and the handler the destination, of a connection between the two. Of course in the configured objects this is represented by the logger holding a reference to the handler. In the configuration dict, this is done by giving each destination object an id which identifies it unambiguously, and then using the id in the source object’s configuration to indicate that a connection exists between the source and the destination object with that id.

So, for example, consider the following YAML snippet:

formatters:
  brief:
    # configuration for formatter with id 'brief' goes here
  precise:
    # configuration for formatter with id 'precise' goes here
handlers:
  h1: #This is an id
   # configuration of handler with id 'h1' goes here
   formatter: brief
  h2: #This is another id
   # configuration of handler with id 'h2' goes here
   formatter: precise
loggers:
  foo.bar.baz:
    # other configuration for logger 'foo.bar.baz'
    handlers: [h1, h2]

(Note: YAML used here because it’s a little more readable than the equivalent Python source form for the dictionary.)

The ids for loggers are the logger names which would be used programmatically to obtain a reference to those loggers, e.g. foo.bar.baz. The ids for Formatters and Filters can be any string value (such as brief, precise above) and they are transient, in that they are only meaningful for processing the configuration dictionary and used to determine connections between objects, and are not persisted anywhere when the configuration call is complete.

The above snippet indicates that logger named foo.bar.baz should have two handlers attached to it, which are described by the handler ids h1 and h2. The formatter for h1 is that described by id brief, and the formatter for h2 is that described by id precise.

16.7.2.4. User-defined objects

The schema supports user-defined objects for handlers, filters and formatters. (Loggers do not need to have different types for different instances, so there is no support in this configuration schema for user-defined logger classes.)

Objects to be configured are described by dictionaries which detail their configuration. In some places, the logging system will be able to infer from the context how an object is to be instantiated, but when a user-defined object is to be instantiated, the system will not know how to do this. In order to provide complete flexibility for user-defined object instantiation, the user needs to provide a “factory” - a callable which is called with a configuration dictionary and which returns the instantiated object. This is signalled by an absolute import path to the factory being made available under the special key '()'. Here’s a concrete example:

formatters:
  brief:
    format: '%(message)s'
  default:
    format: '%(asctime)s %(levelname)-8s %(name)-15s %(message)s'
    datefmt: '%Y-%m-%d %H:%M:%S'
  custom:
      (): my.package.customFormatterFactory
      bar: baz
      spam: 99.9
      answer: 42

The above YAML snippet defines three formatters. The first, with id brief, is a standard logging.Formatter instance with the specified format string. The second, with id default, has a longer format and also defines the time format explicitly, and will result in a logging.Formatter initialized with those two format strings. Shown in Python source form, the brief and default formatters have configuration sub-dictionaries:

{
  'format' : '%(message)s'
}

et :

{
  'format' : '%(asctime)s %(levelname)-8s %(name)-15s %(message)s',
  'datefmt' : '%Y-%m-%d %H:%M:%S'
}

respectively, and as these dictionaries do not contain the special key '()', the instantiation is inferred from the context: as a result, standard logging.Formatter instances are created. The configuration sub-dictionary for the third formatter, with id custom, is:

{
  '()' : 'my.package.customFormatterFactory',
  'bar' : 'baz',
  'spam' : 99.9,
  'answer' : 42
}

and this contains the special key '()', which means that user-defined instantiation is wanted. In this case, the specified factory callable will be used. If it is an actual callable it will be used directly - otherwise, if you specify a string (as in the example) the actual callable will be located using normal import mechanisms. The callable will be called with the remaining items in the configuration sub-dictionary as keyword arguments. In the above example, the formatter with id custom will be assumed to be returned by the call:

my.package.customFormatterFactory(bar='baz', spam=99.9, answer=42)

The key '()' has been used as the special key because it is not a valid keyword parameter name, and so will not clash with the names of the keyword arguments used in the call. The '()' also serves as a mnemonic that the corresponding value is a callable.

16.7.2.5. Access to external objects

There are times where a configuration needs to refer to objects external to the configuration, for example sys.stderr. If the configuration dict is constructed using Python code, this is straightforward, but a problem arises when the configuration is provided via a text file (e.g. JSON, YAML). In a text file, there is no standard way to distinguish sys.stderr from the literal string 'sys.stderr'. To facilitate this distinction, the configuration system looks for certain special prefixes in string values and treat them specially. For example, if the literal string 'ext://sys.stderr' is provided as a value in the configuration, then the ext:// will be stripped off and the remainder of the value processed using normal import mechanisms.

The handling of such prefixes is done in a way analogous to protocol handling: there is a generic mechanism to look for prefixes which match the regular expression ^(?P<prefix>[a-z]+)://(?P<suffix>.*)$ whereby, if the prefix is recognised, the suffix is processed in a prefix-dependent manner and the result of the processing replaces the string value. If the prefix is not recognised, then the string value will be left as-is.

16.7.2.6. Access to internal objects

As well as external objects, there is sometimes also a need to refer to objects in the configuration. This will be done implicitly by the configuration system for things that it knows about. For example, the string value 'DEBUG' for a level in a logger or handler will automatically be converted to the value logging.DEBUG, and the handlers, filters and formatter entries will take an object id and resolve to the appropriate destination object.

However, a more generic mechanism is needed for user-defined objects which are not known to the logging module. For example, consider logging.handlers.MemoryHandler, which takes a target argument which is another handler to delegate to. Since the system already knows about this class, then in the configuration, the given target just needs to be the object id of the relevant target handler, and the system will resolve to the handler from the id. If, however, a user defines a my.package.MyHandler which has an alternate handler, the configuration system would not know that the alternate referred to a handler. To cater for this, a generic resolution system allows the user to specify:

handlers:
  file:
    # configuration of file handler goes here

  custom:
    (): my.package.MyHandler
    alternate: cfg://handlers.file

The literal string 'cfg://handlers.file' will be resolved in an analogous way to strings with the ext:// prefix, but looking in the configuration itself rather than the import namespace. The mechanism allows access by dot or by index, in a similar way to that provided by str.format. Thus, given the following snippet:

handlers:
  email:
    class: logging.handlers.SMTPHandler
    mailhost: localhost
    fromaddr: my_app@domain.tld
    toaddrs:
      - support_team@domain.tld
      - dev_team@domain.tld
    subject: Houston, we have a problem.

in the configuration, the string 'cfg://handlers' would resolve to the dict with key handlers, the string 'cfg://handlers.email would resolve to the dict with key email in the handlers dict, and so on. The string 'cfg://handlers.email.toaddrs[1] would resolve to 'dev_team.domain.tld' and the string 'cfg://handlers.email.toaddrs[0]' would resolve to the value 'support_team@domain.tld'. The subject value could be accessed using either 'cfg://handlers.email.subject' or, equivalently, 'cfg://handlers.email[subject]'. The latter form only needs to be used if the key contains spaces or non-alphanumeric characters. If an index value consists only of decimal digits, access will be attempted using the corresponding integer value, falling back to the string value if needed.

Given a string cfg://handlers.myhandler.mykey.123, this will resolve to config_dict['handlers']['myhandler']['mykey']['123']. If the string is specified as cfg://handlers.myhandler.mykey[123], the system will attempt to retrieve the value from config_dict['handlers']['myhandler']['mykey'][123], and fall back to config_dict['handlers']['myhandler']['mykey']['123'] if that fails.

16.7.2.7. Import resolution and custom importers

Import resolution, by default, uses the builtin __import__() function to do its importing. You may want to replace this with your own importing mechanism: if so, you can replace the importer attribute of the DictConfigurator or its superclass, the BaseConfigurator class. However, you need to be careful because of the way functions are accessed from classes via descriptors. If you are using a Python callable to do your imports, and you want to define it at class level rather than instance level, you need to wrap it with staticmethod(). For example:

from importlib import import_module
from logging.config import BaseConfigurator

BaseConfigurator.importer = staticmethod(import_module)

You don’t need to wrap with staticmethod() if you’re setting the import callable on a configurator instance.

16.7.3. Configuration file format

The configuration file format understood by fileConfig() is based on configparser functionality. The file must contain sections called [loggers], [handlers] and [formatters] which identify by name the entities of each type which are defined in the file. For each such entity, there is a separate section which identifies how that entity is configured. Thus, for a logger named log01 in the [loggers] section, the relevant configuration details are held in a section [logger_log01]. Similarly, a handler called hand01 in the [handlers] section will have its configuration held in a section called [handler_hand01], while a formatter called form01 in the [formatters] section will have its configuration specified in a section called [formatter_form01]. The root logger configuration must be specified in a section called [logger_root].

Note

The fileConfig() API is older than the dictConfig() API and does not provide functionality to cover certain aspects of logging. For example, you cannot configure Filter objects, which provide for filtering of messages beyond simple integer levels, using fileConfig(). If you need to have instances of Filter in your logging configuration, you will need to use dictConfig(). Note that future enhancements to configuration functionality will be added to dictConfig(), so it’s worth considering transitioning to this newer API when it’s convenient to do so.

Examples of these sections in the file are given below.

[loggers]
keys=root,log02,log03,log04,log05,log06,log07

[handlers]
keys=hand01,hand02,hand03,hand04,hand05,hand06,hand07,hand08,hand09

[formatters]
keys=form01,form02,form03,form04,form05,form06,form07,form08,form09

The root logger must specify a level and a list of handlers. An example of a root logger section is given below.

[logger_root]
level=NOTSET
handlers=hand01

The level entry can be one of DEBUG, INFO, WARNING, ERROR, CRITICAL or NOTSET. For the root logger only, NOTSET means that all messages will be logged. Level values are eval()uated in the context of the logging package’s namespace.

The handlers entry is a comma-separated list of handler names, which must appear in the [handlers] section. These names must appear in the [handlers] section and have corresponding sections in the configuration file.

For loggers other than the root logger, some additional information is required. This is illustrated by the following example.

[logger_parser]
level=DEBUG
handlers=hand01
propagate=1
qualname=compiler.parser

The level and handlers entries are interpreted as for the root logger, except that if a non-root logger’s level is specified as NOTSET, the system consults loggers higher up the hierarchy to determine the effective level of the logger. The propagate entry is set to 1 to indicate that messages must propagate to handlers higher up the logger hierarchy from this logger, or 0 to indicate that messages are not propagated to handlers up the hierarchy. The qualname entry is the hierarchical channel name of the logger, that is to say the name used by the application to get the logger.

Sections which specify handler configuration are exemplified by the following.

[handler_hand01]
class=StreamHandler
level=NOTSET
formatter=form01
args=(sys.stdout,)

The class entry indicates the handler’s class (as determined by eval() in the logging package’s namespace). The level is interpreted as for loggers, and NOTSET is taken to mean “log everything”.

The formatter entry indicates the key name of the formatter for this handler. If blank, a default formatter (logging._defaultFormatter) is used. If a name is specified, it must appear in the [formatters] section and have a corresponding section in the configuration file.

The args entry, when eval()uated in the context of the logging package’s namespace, is the list of arguments to the constructor for the handler class. Refer to the constructors for the relevant handlers, or to the examples below, to see how typical entries are constructed.

[handler_hand02]
class=FileHandler
level=DEBUG
formatter=form02
args=('python.log', 'w')

[handler_hand03]
class=handlers.SocketHandler
level=INFO
formatter=form03
args=('localhost', handlers.DEFAULT_TCP_LOGGING_PORT)

[handler_hand04]
class=handlers.DatagramHandler
level=WARN
formatter=form04
args=('localhost', handlers.DEFAULT_UDP_LOGGING_PORT)

[handler_hand05]
class=handlers.SysLogHandler
level=ERROR
formatter=form05
args=(('localhost', handlers.SYSLOG_UDP_PORT), handlers.SysLogHandler.LOG_USER)

[handler_hand06]
class=handlers.NTEventLogHandler
level=CRITICAL
formatter=form06
args=('Python Application', '', 'Application')

[handler_hand07]
class=handlers.SMTPHandler
level=WARN
formatter=form07
args=('localhost', 'from@abc', ['user1@abc', 'user2@xyz'], 'Logger Subject')

[handler_hand08]
class=handlers.MemoryHandler
level=NOTSET
formatter=form08
target=
args=(10, ERROR)

[handler_hand09]
class=handlers.HTTPHandler
level=NOTSET
formatter=form09
args=('localhost:9022', '/log', 'GET')

Sections which specify formatter configuration are typified by the following.

[formatter_form01]
format=F1 %(asctime)s %(levelname)s %(message)s
datefmt=
class=logging.Formatter

The format entry is the overall format string, and the datefmt entry is the strftime()-compatible date/time format string. If empty, the package substitutes something which is almost equivalent to specifying the date format string '%Y-%m-%d %H:%M:%S'. This format also specifies milliseconds, which are appended to the result of using the above format string, with a comma separator. An example time in this format is 2003-01-23 00:29:50,411.

The class entry is optional. It indicates the name of the formatter’s class (as a dotted module and class name.) This option is useful for instantiating a Formatter subclass. Subclasses of Formatter can present exception tracebacks in an expanded or condensed format.

Note

Due to the use of eval() as described above, there are potential security risks which result from using the listen() to send and receive configurations via sockets. The risks are limited to where multiple users with no mutual trust run code on the same machine; see the listen() documentation for more information.

Voir aussi

Module logging

Référence d’API pour le module de journalisation.

Module logging.handlers

Gestionnaires utiles inclus avec le module de journalisation.

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16.8. logging.handlers — Logging handlers

Source code: Lib/logging/handlers.py [https://github.com/python/cpython/tree/3.6/Lib/logging/handlers.py]

Important

This page contains only reference information. For tutorials, please see

Basic Tutorial

Advanced Tutorial

Logging Cookbook

The following useful handlers are provided in the package. Note that three of the handlers (StreamHandler, FileHandler and NullHandler) are actually defined in the logging module itself, but have been documented here along with the other handlers.

16.8.1. StreamHandler

The StreamHandler class, located in the core logging package, sends logging output to streams such as sys.stdout, sys.stderr or any file-like object (or, more precisely, any object which supports write() and flush() methods).

class logging.StreamHandler(stream=None)

Returns a new instance of the StreamHandler class. If stream is specified, the instance will use it for logging output; otherwise, sys.stderr will be used.

emit(record)

If a formatter is specified, it is used to format the record. The record is then written to the stream with a terminator. If exception information is present, it is formatted using traceback.print_exception() and appended to the stream.

flush()

Flushes the stream by calling its flush() method. Note that the close() method is inherited from Handler and so does no output, so an explicit flush() call may be needed at times.

Modifié dans la version 3.2: The StreamHandler class now has a terminator attribute, default value '\n', which is used as the terminator when writing a formatted record to a stream. If you don’t want this newline termination, you can set the handler instance’s terminator attribute to the empty string. In earlier versions, the terminator was hardcoded as '\n'.

16.8.2. FileHandler

The FileHandler class, located in the core logging package, sends logging output to a disk file. It inherits the output functionality from StreamHandler.

class logging.FileHandler(filename, mode='a', encoding=None, delay=False)

Returns a new instance of the FileHandler class. The specified file is opened and used as the stream for logging. If mode is not specified, 'a' is used. If encoding is not None, it is used to open the file with that encoding. If delay is true, then file opening is deferred until the first call to emit(). By default, the file grows indefinitely.

Modifié dans la version 3.6: As well as string values, Path objects are also accepted for the filename argument.

close()

Closes the file.

emit(record)

Outputs the record to the file.

16.8.3. NullHandler

Nouveau dans la version 3.1.

The NullHandler class, located in the core logging package, does not do any formatting or output. It is essentially a “no-op” handler for use by library developers.

class logging.NullHandler

Returns a new instance of the NullHandler class.

emit(record)

This method does nothing.

handle(record)

This method does nothing.

createLock()

This method returns None for the lock, since there is no underlying I/O to which access needs to be serialized.

See Configuration de la journalisation pour une bibliothèque for more information on how to use NullHandler.

16.8.4. WatchedFileHandler

The WatchedFileHandler class, located in the logging.handlers module, is a FileHandler which watches the file it is logging to. If the file changes, it is closed and reopened using the file name.

A file change can happen because of usage of programs such as newsyslog and logrotate which perform log file rotation. This handler, intended for use under Unix/Linux, watches the file to see if it has changed since the last emit. (A file is deemed to have changed if its device or inode have changed.) If the file has changed, the old file stream is closed, and the file opened to get a new stream.

This handler is not appropriate for use under Windows, because under Windows open log files cannot be moved or renamed - logging opens the files with exclusive locks - and so there is no need for such a handler. Furthermore, ST_INO is not supported under Windows; stat() always returns zero for this value.

class logging.handlers.WatchedFileHandler(filename, mode='a', encoding=None, delay=False)

Returns a new instance of the WatchedFileHandler class. The specified file is opened and used as the stream for logging. If mode is not specified, 'a' is used. If encoding is not None, it is used to open the file with that encoding. If delay is true, then file opening is deferred until the first call to emit(). By default, the file grows indefinitely.

Modifié dans la version 3.6: As well as string values, Path objects are also accepted for the filename argument.

reopenIfNeeded()

Checks to see if the file has changed. If it has, the existing stream is flushed and closed and the file opened again, typically as a precursor to outputting the record to the file.

Nouveau dans la version 3.6.

emit(record)

Outputs the record to the file, but first calls reopenIfNeeded() to reopen the file if it has changed.

16.8.5. BaseRotatingHandler

The BaseRotatingHandler class, located in the logging.handlers module, is the base class for the rotating file handlers, RotatingFileHandler and TimedRotatingFileHandler. You should not need to instantiate this class, but it has attributes and methods you may need to override.

class logging.handlers.BaseRotatingHandler(filename, mode, encoding=None, delay=False)

The parameters are as for FileHandler. The attributes are:

namer

If this attribute is set to a callable, the rotation_filename() method delegates to this callable. The parameters passed to the callable are those passed to rotation_filename().

Note

The namer function is called quite a few times during rollover, so it should be as simple and as fast as possible. It should also return the same output every time for a given input, otherwise the rollover behaviour may not work as expected.

Nouveau dans la version 3.3.

rotator

If this attribute is set to a callable, the rotate() method delegates to this callable. The parameters passed to the callable are those passed to rotate().

Nouveau dans la version 3.3.

rotation_filename(default_name)

Modify the filename of a log file when rotating.

This is provided so that a custom filename can be provided.

The default implementation calls the “namer” attribute of the handler, if it’s callable, passing the default name to it. If the attribute isn’t callable (the default is None), the name is returned unchanged.

Paramètres

default_name – The default name for the log file.

Nouveau dans la version 3.3.

rotate(source, dest)

When rotating, rotate the current log.

The default implementation calls the “rotator” attribute of the handler, if it’s callable, passing the source and dest arguments to it. If the attribute isn’t callable (the default is None), the source is simply renamed to the destination.

Paramètres

source – The source filename. This is normally the base filename, e.g. “test.log”.

dest – The destination filename. This is normally what the source is rotated to, e.g. “test.log.1”.

Nouveau dans la version 3.3.

The reason the attributes exist is to save you having to subclass - you can use the same callables for instances of RotatingFileHandler and TimedRotatingFileHandler. If either the namer or rotator callable raises an exception, this will be handled in the same way as any other exception during an emit() call, i.e. via the handleError() method of the handler.

If you need to make more significant changes to rotation processing, you can override the methods.

For an example, see Using a rotator and namer to customize log rotation processing.

16.8.6. RotatingFileHandler

The RotatingFileHandler class, located in the logging.handlers module, supports rotation of disk log files.

class logging.handlers.RotatingFileHandler(filename, mode='a', maxBytes=0, backupCount=0, encoding=None, delay=False)

Returns a new instance of the RotatingFileHandler class. The specified file is opened and used as the stream for logging. If mode is not specified, 'a' is used. If encoding is not None, it is used to open the file with that encoding. If delay is true, then file opening is deferred until the first call to emit(). By default, the file grows indefinitely.

You can use the maxBytes and backupCount values to allow the file to rollover at a predetermined size. When the size is about to be exceeded, the file is closed and a new file is silently opened for output. Rollover occurs whenever the current log file is nearly maxBytes in length; but if either of maxBytes or backupCount is zero, rollover never occurs, so you generally want to set backupCount to at least 1, and have a non-zero maxBytes. When backupCount is non-zero, the system will save old log files by appending the extensions “.1”, “.2” etc., to the filename. For example, with a backupCount of 5 and a base file name of app.log, you would get app.log, app.log.1, app.log.2, up to app.log.5. The file being written to is always app.log. When this file is filled, it is closed and renamed to app.log.1, and if files app.log.1, app.log.2, etc. exist, then they are renamed to app.log.2, app.log.3 etc. respectively.

Modifié dans la version 3.6: As well as string values, Path objects are also accepted for the filename argument.

doRollover()

Does a rollover, as described above.

emit(record)

Outputs the record to the file, catering for rollover as described previously.

16.8.7. TimedRotatingFileHandler

The TimedRotatingFileHandler class, located in the logging.handlers module, supports rotation of disk log files at certain timed intervals.

class logging.handlers.TimedRotatingFileHandler(filename, when='h', interval=1, backupCount=0, encoding=None, delay=False, utc=False, atTime=None)

Returns a new instance of the TimedRotatingFileHandler class. The specified file is opened and used as the stream for logging. On rotating it also sets the filename suffix. Rotating happens based on the product of when and interval.

You can use the when to specify the type of interval. The list of possible values is below. Note that they are not case sensitive.

Valeur

Type of interval

If/how atTime is used

'S'

Seconds

Ignoré

'M'

Minutes

Ignoré

'H'

Hours

Ignoré

'D'

Days

Ignoré

'W0'-'W6'

Weekday (0=Monday)

Used to compute initial rollover time

'midnight'

Roll over at midnight, if atTime not specified, else at time atTime

Used to compute initial rollover time

When using weekday-based rotation, specify “W0” for Monday, “W1” for Tuesday, and so on up to “W6” for Sunday. In this case, the value passed for interval isn’t used.

The system will save old log files by appending extensions to the filename. The extensions are date-and-time based, using the strftime format %Y-%m-%d_%H-%M-%S or a leading portion thereof, depending on the rollover interval.

When computing the next rollover time for the first time (when the handler is created), the last modification time of an existing log file, or else the current time, is used to compute when the next rotation will occur.

If the utc argument is true, times in UTC will be used; otherwise local time is used.

If backupCount is nonzero, at most backupCount files will be kept, and if more would be created when rollover occurs, the oldest one is deleted. The deletion logic uses the interval to determine which files to delete, so changing the interval may leave old files lying around.

If delay is true, then file opening is deferred until the first call to emit().

If atTime is not None, it must be a datetime.time instance which specifies the time of day when rollover occurs, for the cases where rollover is set to happen « at midnight » or « on a particular weekday ». Note that in these cases, the atTime value is effectively used to compute the initial rollover, and subsequent rollovers would be calculated via the normal interval calculation.

Note

Calculation of the initial rollover time is done when the handler is initialised. Calculation of subsequent rollover times is done only when rollover occurs, and rollover occurs only when emitting output. If this is not kept in mind, it might lead to some confusion. For example, if an interval of « every minute » is set, that does not mean you will always see log files with times (in the filename) separated by a minute; if, during application execution, logging output is generated more frequently than once a minute, then you can expect to see log files with times separated by a minute. If, on the other hand, logging messages are only output once every five minutes (say), then there will be gaps in the file times corresponding to the minutes where no output (and hence no rollover) occurred.

Modifié dans la version 3.4: atTime parameter was added.

Modifié dans la version 3.6: As well as string values, Path objects are also accepted for the filename argument.

doRollover()

Does a rollover, as described above.

emit(record)

Outputs the record to the file, catering for rollover as described above.

16.8.8. SocketHandler

The SocketHandler class, located in the logging.handlers module, sends logging output to a network socket. The base class uses a TCP socket.

class logging.handlers.SocketHandler(host, port)

Returns a new instance of the SocketHandler class intended to communicate with a remote machine whose address is given by host and port.

Modifié dans la version 3.4: If port is specified as None, a Unix domain socket is created using the value in host - otherwise, a TCP socket is created.

close()

Closes the socket.

emit()

Pickles the record’s attribute dictionary and writes it to the socket in binary format. If there is an error with the socket, silently drops the packet. If the connection was previously lost, re-establishes the connection. To unpickle the record at the receiving end into a LogRecord, use the makeLogRecord() function.

handleError()

Handles an error which has occurred during emit(). The most likely cause is a lost connection. Closes the socket so that we can retry on the next event.

makeSocket()

This is a factory method which allows subclasses to define the precise type of socket they want. The default implementation creates a TCP socket (socket.SOCK_STREAM).

makePickle(record)

Pickles the record’s attribute dictionary in binary format with a length prefix, and returns it ready for transmission across the socket.

Note that pickles aren’t completely secure. If you are concerned about security, you may want to override this method to implement a more secure mechanism. For example, you can sign pickles using HMAC and then verify them on the receiving end, or alternatively you can disable unpickling of global objects on the receiving end.

send(packet)

Send a pickled string packet to the socket. This function allows for partial sends which can happen when the network is busy.

createSocket()

Tries to create a socket; on failure, uses an exponential back-off algorithm. On initial failure, the handler will drop the message it was trying to send. When subsequent messages are handled by the same instance, it will not try connecting until some time has passed. The default parameters are such that the initial delay is one second, and if after that delay the connection still can’t be made, the handler will double the delay each time up to a maximum of 30 seconds.

This behaviour is controlled by the following handler attributes:

retryStart (initial delay, defaulting to 1.0 seconds).

retryFactor (multiplier, defaulting to 2.0).

retryMax (maximum delay, defaulting to 30.0 seconds).

This means that if the remote listener starts up after the handler has been used, you could lose messages (since the handler won’t even attempt a connection until the delay has elapsed, but just silently drop messages during the delay period).

16.8.9. DatagramHandler

The DatagramHandler class, located in the logging.handlers module, inherits from SocketHandler to support sending logging messages over UDP sockets.

class logging.handlers.DatagramHandler(host, port)

Returns a new instance of the DatagramHandler class intended to communicate with a remote machine whose address is given by host and port.

Modifié dans la version 3.4: If port is specified as None, a Unix domain socket is created using the value in host - otherwise, a UDP socket is created.

emit()

Pickles the record’s attribute dictionary and writes it to the socket in binary format. If there is an error with the socket, silently drops the packet. To unpickle the record at the receiving end into a LogRecord, use the makeLogRecord() function.

makeSocket()

The factory method of SocketHandler is here overridden to create a UDP socket (socket.SOCK_DGRAM).

send(s)

Send a pickled string to a socket.

16.8.10. SysLogHandler

The SysLogHandler class, located in the logging.handlers module, supports sending logging messages to a remote or local Unix syslog.

class logging.handlers.SysLogHandler(address=('localhost', SYSLOG_UDP_PORT), facility=LOG_USER, socktype=socket.SOCK_DGRAM)

Returns a new instance of the SysLogHandler class intended to communicate with a remote Unix machine whose address is given by address in the form of a (host, port) tuple. If address is not specified, ('localhost', 514) is used. The address is used to open a socket. An alternative to providing a (host, port) tuple is providing an address as a string, for example “/dev/log”. In this case, a Unix domain socket is used to send the message to the syslog. If facility is not specified, LOG_USER is used. The type of socket opened depends on the socktype argument, which defaults to socket.SOCK_DGRAM and thus opens a UDP socket. To open a TCP socket (for use with the newer syslog daemons such as rsyslog), specify a value of socket.SOCK_STREAM.

Note that if your server is not listening on UDP port 514, SysLogHandler may appear not to work. In that case, check what address you should be using for a domain socket - it’s system dependent. For example, on Linux it’s usually “/dev/log” but on OS/X it’s “/var/run/syslog”. You’ll need to check your platform and use the appropriate address (you may need to do this check at runtime if your application needs to run on several platforms). On Windows, you pretty much have to use the UDP option.

Modifié dans la version 3.2: socktype was added.

close()

Closes the socket to the remote host.

emit(record)

The record is formatted, and then sent to the syslog server. If exception information is present, it is not sent to the server.

Modifié dans la version 3.2.1: (See: bpo-12168 [https://bugs.python.org/issue12168].) In earlier versions, the message sent to the syslog daemons was always terminated with a NUL byte, because early versions of these daemons expected a NUL terminated message - even though it’s not in the relevant specification (RFC 5424 [https://tools.ietf.org/html/rfc5424.html]). More recent versions of these daemons don’t expect the NUL byte but strip it off if it’s there, and even more recent daemons (which adhere more closely to RFC 5424) pass the NUL byte on as part of the message.

To enable easier handling of syslog messages in the face of all these differing daemon behaviours, the appending of the NUL byte has been made configurable, through the use of a class-level attribute, append_nul. This defaults to True (preserving the existing behaviour) but can be set to False on a SysLogHandler instance in order for that instance to not append the NUL terminator.

Modifié dans la version 3.3: (See: bpo-12419 [https://bugs.python.org/issue12419].) In earlier versions, there was no facility for an « ident » or « tag » prefix to identify the source of the message. This can now be specified using a class-level attribute, defaulting to "" to preserve existing behaviour, but which can be overridden on a SysLogHandler instance in order for that instance to prepend the ident to every message handled. Note that the provided ident must be text, not bytes, and is prepended to the message exactly as is.

encodePriority(facility, priority)

Encodes the facility and priority into an integer. You can pass in strings or integers - if strings are passed, internal mapping dictionaries are used to convert them to integers.

The symbolic LOG_ values are defined in SysLogHandler and mirror the values defined in the sys/syslog.h header file.

Priorities

Name (string)

Symbolic value

alert

LOG_ALERT

crit ou critical

LOG_CRIT

debug

LOG_DEBUG

emerg ou panic

LOG_EMERG

err ou error

LOG_ERR

info

LOG_INFO

notice

LOG_NOTICE

warn ou warning

LOG_WARNING

Facilities

Name (string)

Symbolic value

auth

LOG_AUTH

authpriv

LOG_AUTHPRIV

cron

LOG_CRON

daemon

LOG_DAEMON

ftp

LOG_FTP

kern

LOG_KERN

lpr

LOG_LPR

mail

LOG_MAIL

news

LOG_NEWS

syslog

LOG_SYSLOG

user

LOG_USER

uucp

LOG_UUCP

local0

LOG_LOCAL0

local1

LOG_LOCAL1

local2

LOG_LOCAL2

local3

LOG_LOCAL3

local4

LOG_LOCAL4

local5

LOG_LOCAL5

local6

LOG_LOCAL6

local7

LOG_LOCAL7

mapPriority(levelname)

Maps a logging level name to a syslog priority name. You may need to override this if you are using custom levels, or if the default algorithm is not suitable for your needs. The default algorithm maps DEBUG, INFO, WARNING, ERROR and CRITICAL to the equivalent syslog names, and all other level names to “warning”.

16.8.11. NTEventLogHandler

The NTEventLogHandler class, located in the logging.handlers module, supports sending logging messages to a local Windows NT, Windows 2000 or Windows XP event log. Before you can use it, you need Mark Hammond’s Win32 extensions for Python installed.

class logging.handlers.NTEventLogHandler(appname, dllname=None, logtype='Application')

Returns a new instance of the NTEventLogHandler class. The appname is used to define the application name as it appears in the event log. An appropriate registry entry is created using this name. The dllname should give the fully qualified pathname of a .dll or .exe which contains message definitions to hold in the log (if not specified, 'win32service.pyd' is used - this is installed with the Win32 extensions and contains some basic placeholder message definitions. Note that use of these placeholders will make your event logs big, as the entire message source is held in the log. If you want slimmer logs, you have to pass in the name of your own .dll or .exe which contains the message definitions you want to use in the event log). The logtype is one of 'Application', 'System' or 'Security', and defaults to 'Application'.

close()

At this point, you can remove the application name from the registry as a source of event log entries. However, if you do this, you will not be able to see the events as you intended in the Event Log Viewer - it needs to be able to access the registry to get the .dll name. The current version does not do this.

emit(record)

Determines the message ID, event category and event type, and then logs the message in the NT event log.

getEventCategory(record)

Returns the event category for the record. Override this if you want to specify your own categories. This version returns 0.

getEventType(record)

Returns the event type for the record. Override this if you want to specify your own types. This version does a mapping using the handler’s typemap attribute, which is set up in __init__() to a dictionary which contains mappings for DEBUG, INFO, WARNING, ERROR and CRITICAL. If you are using your own levels, you will either need to override this method or place a suitable dictionary in the handler’s typemap attribute.

getMessageID(record)

Returns the message ID for the record. If you are using your own messages, you could do this by having the msg passed to the logger being an ID rather than a format string. Then, in here, you could use a dictionary lookup to get the message ID. This version returns 1, which is the base message ID in win32service.pyd.

16.8.12. SMTPHandler

The SMTPHandler class, located in the logging.handlers module, supports sending logging messages to an email address via SMTP.

class logging.handlers.SMTPHandler(mailhost, fromaddr, toaddrs, subject, credentials=None, secure=None, timeout=1.0)

Returns a new instance of the SMTPHandler class. The instance is initialized with the from and to addresses and subject line of the email. The toaddrs should be a list of strings. To specify a non-standard SMTP port, use the (host, port) tuple format for the mailhost argument. If you use a string, the standard SMTP port is used. If your SMTP server requires authentication, you can specify a (username, password) tuple for the credentials argument.

To specify the use of a secure protocol (TLS), pass in a tuple to the secure argument. This will only be used when authentication credentials are supplied. The tuple should be either an empty tuple, or a single-value tuple with the name of a keyfile, or a 2-value tuple with the names of the keyfile and certificate file. (This tuple is passed to the smtplib.SMTP.starttls() method.)

A timeout can be specified for communication with the SMTP server using the timeout argument.

Nouveau dans la version 3.3: The timeout argument was added.

emit(record)

Formats the record and sends it to the specified addressees.

getSubject(record)

If you want to specify a subject line which is record-dependent, override this method.

16.8.13. MemoryHandler

The MemoryHandler class, located in the logging.handlers module, supports buffering of logging records in memory, periodically flushing them to a target handler. Flushing occurs whenever the buffer is full, or when an event of a certain severity or greater is seen.

MemoryHandler is a subclass of the more general BufferingHandler, which is an abstract class. This buffers logging records in memory. Whenever each record is added to the buffer, a check is made by calling shouldFlush() to see if the buffer should be flushed. If it should, then flush() is expected to do the flushing.

class logging.handlers.BufferingHandler(capacity)

Initializes the handler with a buffer of the specified capacity.

emit(record)

Appends the record to the buffer. If shouldFlush() returns true, calls flush() to process the buffer.

flush()

You can override this to implement custom flushing behavior. This version just zaps the buffer to empty.

shouldFlush(record)

Returns true if the buffer is up to capacity. This method can be overridden to implement custom flushing strategies.

class logging.handlers.MemoryHandler(capacity, flushLevel=ERROR, target=None, flushOnClose=True)

Returns a new instance of the MemoryHandler class. The instance is initialized with a buffer size of capacity. If flushLevel is not specified, ERROR is used. If no target is specified, the target will need to be set using setTarget() before this handler does anything useful. If flushOnClose is specified as False, then the buffer is not flushed when the handler is closed. If not specified or specified as True, the previous behaviour of flushing the buffer will occur when the handler is closed.

Modifié dans la version 3.6: The flushOnClose parameter was added.

close()

Calls flush(), sets the target to None and clears the buffer.

flush()

For a MemoryHandler, flushing means just sending the buffered records to the target, if there is one. The buffer is also cleared when this happens. Override if you want different behavior.

setTarget(target)

Sets the target handler for this handler.

shouldFlush(record)

Checks for buffer full or a record at the flushLevel or higher.

16.8.14. HTTPHandler

The HTTPHandler class, located in the logging.handlers module, supports sending logging messages to a Web server, using either GET or POST semantics.

class logging.handlers.HTTPHandler(host, url, method='GET', secure=False, credentials=None, context=None)

Returns a new instance of the HTTPHandler class. The host can be of the form host:port, should you need to use a specific port number. If no method is specified, GET is used. If secure is true, a HTTPS connection will be used. The context parameter may be set to a ssl.SSLContext instance to configure the SSL settings used for the HTTPS connection. If credentials is specified, it should be a 2-tuple consisting of userid and password, which will be placed in a HTTP “Authorization” header using Basic authentication. If you specify credentials, you should also specify secure=True so that your userid and password are not passed in cleartext across the wire.

Modifié dans la version 3.5: The context parameter was added.

mapLogRecord(record)

Provides a dictionary, based on record, which is to be URL-encoded and sent to the web server. The default implementation just returns record.__dict__. This method can be overridden if e.g. only a subset of LogRecord is to be sent to the web server, or if more specific customization of what’s sent to the server is required.

emit(record)

Sends the record to the Web server as a URL-encoded dictionary. The mapLogRecord() method is used to convert the record to the dictionary to be sent.

Note

Since preparing a record for sending it to a Web server is not the same as a generic formatting operation, using setFormatter() to specify a Formatter for a HTTPHandler has no effect. Instead of calling format(), this handler calls mapLogRecord() and then urllib.parse.urlencode() to encode the dictionary in a form suitable for sending to a Web server.

16.8.15. QueueHandler

Nouveau dans la version 3.2.

The QueueHandler class, located in the logging.handlers module, supports sending logging messages to a queue, such as those implemented in the queue or multiprocessing modules.

Along with the QueueListener class, QueueHandler can be used to let handlers do their work on a separate thread from the one which does the logging. This is important in Web applications and also other service applications where threads servicing clients need to respond as quickly as possible, while any potentially slow operations (such as sending an email via SMTPHandler) are done on a separate thread.

class logging.handlers.QueueHandler(queue)

Returns a new instance of the QueueHandler class. The instance is initialized with the queue to send messages to. The queue can be any queue-like object; it’s used as-is by the enqueue() method, which needs to know how to send messages to it.

emit(record)

Enqueues the result of preparing the LogRecord.

prepare(record)

Prepares a record for queuing. The object returned by this method is enqueued.

The base implementation formats the record to merge the message and arguments, and removes unpickleable items from the record in-place.

You might want to override this method if you want to convert the record to a dict or JSON string, or send a modified copy of the record while leaving the original intact.

enqueue(record)

Enqueues the record on the queue using put_nowait(); you may want to override this if you want to use blocking behaviour, or a timeout, or a customized queue implementation.

16.8.16. QueueListener

Nouveau dans la version 3.2.

The QueueListener class, located in the logging.handlers module, supports receiving logging messages from a queue, such as those implemented in the queue or multiprocessing modules. The messages are received from a queue in an internal thread and passed, on the same thread, to one or more handlers for processing. While QueueListener is not itself a handler, it is documented here because it works hand-in-hand with QueueHandler.

Along with the QueueHandler class, QueueListener can be used to let handlers do their work on a separate thread from the one which does the logging. This is important in Web applications and also other service applications where threads servicing clients need to respond as quickly as possible, while any potentially slow operations (such as sending an email via SMTPHandler) are done on a separate thread.

class logging.handlers.QueueListener(queue, *handlers, respect_handler_level=False)

Returns a new instance of the QueueListener class. The instance is initialized with the queue to send messages to and a list of handlers which will handle entries placed on the queue. The queue can be any queue-like object; it’s passed as-is to the dequeue() method, which needs to know how to get messages from it. If respect_handler_level is True, a handler’s level is respected (compared with the level for the message) when deciding whether to pass messages to that handler; otherwise, the behaviour is as in previous Python versions - to always pass each message to each handler.

Modifié dans la version 3.5: The respect_handler_levels argument was added.

dequeue(block)

Dequeues a record and return it, optionally blocking.

The base implementation uses get(). You may want to override this method if you want to use timeouts or work with custom queue implementations.

prepare(record)

Prepare a record for handling.

This implementation just returns the passed-in record. You may want to override this method if you need to do any custom marshalling or manipulation of the record before passing it to the handlers.

handle(record)

Handle a record.

This just loops through the handlers offering them the record to handle. The actual object passed to the handlers is that which is returned from prepare().

start()

Starts the listener.

This starts up a background thread to monitor the queue for LogRecords to process.

stop()

Stops the listener.

This asks the thread to terminate, and then waits for it to do so. Note that if you don’t call this before your application exits, there may be some records still left on the queue, which won’t be processed.

enqueue_sentinel()

Writes a sentinel to the queue to tell the listener to quit. This implementation uses put_nowait(). You may want to override this method if you want to use timeouts or work with custom queue implementations.

Nouveau dans la version 3.3.

Voir aussi

Module logging

Référence d’API pour le module de journalisation.

Module logging.config

API de configuration pour le module de journalisation.

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16.9. Saisie de mot de passe portable

Source code: Lib/getpass.py [https://github.com/python/cpython/tree/3.6/Lib/getpass.py]

Le module getpass fournit 2 fonctions:

getpass.getpass(prompt='Password: ', stream=None)

Affiche une demande de mot de passe sans renvoyer d’écho. L’utilisateur est invité en utilisant la string prompt, avec en valeur par défaut 'Password: '. Avec Unix, l’invite est écrite dans l’objet fichier stream en utilisant si besoin le replace error handler. stream sera par défaut le terminal de contrôle (/dev/tty), ou si celui ci n’est pas disponible ce sera sys.stderr (cet argument sera ignoré sur Windows).

Si aucune saisie en mode sans affichage n’est disponible, getpass() se résoudra à afficher un message d’avertissement vers stream, puis lire l’entrée depuis sys.stdin, en levant une GetPassWarning.

Note

Si vous appelez getpass depuis IDLE, la saisie peut être faite dans le terminal depuis lequel IDLE a été lancé, plutôt que dans la fenêtre d’IDLE.

exception getpass.GetPassWarning

Une sous classe d’exception UserWarning est levée quand le mot de passe saisi pourrait être affiché.

getpass.getuser()

Renvoie le login name de l’utilisateur.

Cette fonction examine les variables d’environnement LOGNAME, USER, LNAME et USERNAME, dans cet ordre, et renvoie la valeur de la première qui a comme valeur une string non vide. Si aucune des variables n’est renseignée, dans le cas de systèmes qui prennent en charge le module pwd, le login name de la base de données des mots de passes est renvoyé, pour les autres systèmes une exception est levée.

En général, préférez cette fonction à os.getlogin().

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16.10. curses — Terminal handling for character-cell displays

The curses module provides an interface to the curses library, the de-facto standard for portable advanced terminal handling.

While curses is most widely used in the Unix environment, versions are available for Windows, DOS, and possibly other systems as well. This extension module is designed to match the API of ncurses, an open-source curses library hosted on Linux and the BSD variants of Unix.

Note

Whenever the documentation mentions a character it can be specified as an integer, a one-character Unicode string or a one-byte byte string.

Whenever the documentation mentions a character string it can be specified as a Unicode string or a byte string.

Note

Since version 5.4, the ncurses library decides how to interpret non-ASCII data using the nl_langinfo function. That means that you have to call locale.setlocale() in the application and encode Unicode strings using one of the system’s available encodings. This example uses the system’s default encoding:

import locale
locale.setlocale(locale.LC_ALL, '')
code = locale.getpreferredencoding()

Then use code as the encoding for str.encode() calls.

Voir aussi

Module curses.ascii

Utilities for working with ASCII characters, regardless of your locale settings.

Module curses.panel

A panel stack extension that adds depth to curses windows.

Module curses.textpad

Editable text widget for curses supporting Emacs-like bindings.

Curses Programming with Python

Tutorial material on using curses with Python, by Andrew Kuchling and Eric Raymond.

The Tools/demo/ [https://github.com/python/cpython/tree/3.6/Tools/demo/] directory in the Python source distribution contains some example programs using the curses bindings provided by this module.

16.10.1. Fonctions

The module curses defines the following exception:

exception curses.error

Exception raised when a curses library function returns an error.

Note

Whenever x or y arguments to a function or a method are optional, they default to the current cursor location. Whenever attr is optional, it defaults to A_NORMAL.

The module curses defines the following functions:

curses.baudrate()

Return the output speed of the terminal in bits per second. On software terminal emulators it will have a fixed high value. Included for historical reasons; in former times, it was used to write output loops for time delays and occasionally to change interfaces depending on the line speed.

curses.beep()

Emit a short attention sound.

curses.can_change_color()

Return True or False, depending on whether the programmer can change the colors displayed by the terminal.

curses.cbreak()

Enter cbreak mode. In cbreak mode (sometimes called « rare » mode) normal tty line buffering is turned off and characters are available to be read one by one. However, unlike raw mode, special characters (interrupt, quit, suspend, and flow control) retain their effects on the tty driver and calling program. Calling first raw() then cbreak() leaves the terminal in cbreak mode.

curses.color_content(color_number)

Return the intensity of the red, green, and blue (RGB) components in the color color_number, which must be between 0 and COLORS. Return a 3-tuple, containing the R,G,B values for the given color, which will be between 0 (no component) and 1000 (maximum amount of component).

curses.color_pair(color_number)

Return the attribute value for displaying text in the specified color. This attribute value can be combined with A_STANDOUT, A_REVERSE, and the other A_* attributes. pair_number() is the counterpart to this function.

curses.curs_set(visibility)

Set the cursor state. visibility can be set to 0, 1, or 2, for invisible, normal, or very visible. If the terminal supports the visibility requested, return the previous cursor state; otherwise raise an exception. On many terminals, the « visible » mode is an underline cursor and the « very visible » mode is a block cursor.

curses.def_prog_mode()

Save the current terminal mode as the « program » mode, the mode when the running program is using curses. (Its counterpart is the « shell » mode, for when the program is not in curses.) Subsequent calls to reset_prog_mode() will restore this mode.

curses.def_shell_mode()

Save the current terminal mode as the « shell » mode, the mode when the running program is not using curses. (Its counterpart is the « program » mode, when the program is using curses capabilities.) Subsequent calls to reset_shell_mode() will restore this mode.

curses.delay_output(ms)

Insert an ms millisecond pause in output.

curses.doupdate()

Update the physical screen. The curses library keeps two data structures, one representing the current physical screen contents and a virtual screen representing the desired next state. The doupdate() ground updates the physical screen to match the virtual screen.

The virtual screen may be updated by a noutrefresh() call after write operations such as addstr() have been performed on a window. The normal refresh() call is simply noutrefresh() followed by doupdate(); if you have to update multiple windows, you can speed performance and perhaps reduce screen flicker by issuing noutrefresh() calls on all windows, followed by a single doupdate().

curses.echo()

Enter echo mode. In echo mode, each character input is echoed to the screen as it is entered.

curses.endwin()

De-initialize the library, and return terminal to normal status.

curses.erasechar()

Return the user’s current erase character as a one-byte bytes object. Under Unix operating systems this is a property of the controlling tty of the curses program, and is not set by the curses library itself.

curses.filter()

The filter() routine, if used, must be called before initscr() is called. The effect is that, during those calls, LINES is set to 1; the capabilities clear, cup, cud, cud1, cuu1, cuu, vpa are disabled; and the home string is set to the value of cr. The effect is that the cursor is confined to the current line, and so are screen updates. This may be used for enabling character-at-a-time line editing without touching the rest of the screen.

curses.flash()

Flash the screen. That is, change it to reverse-video and then change it back in a short interval. Some people prefer such as “visible bell” to the audible attention signal produced by beep().

curses.flushinp()

Flush all input buffers. This throws away any typeahead that has been typed by the user and has not yet been processed by the program.

curses.getmouse()

After getch() returns KEY_MOUSE to signal a mouse event, this method should be call to retrieve the queued mouse event, represented as a 5-tuple (id, x, y, z, bstate). id is an ID value used to distinguish multiple devices, and x, y, z are the event’s coordinates. (z is currently unused.) bstate is an integer value whose bits will be set to indicate the type of event, and will be the bitwise OR of one or more of the following constants, where n is the button number from 1 to 4: BUTTONn_PRESSED, BUTTONn_RELEASED, BUTTONn_CLICKED, BUTTONn_DOUBLE_CLICKED, BUTTONn_TRIPLE_CLICKED, BUTTON_SHIFT, BUTTON_CTRL, BUTTON_ALT.

curses.getsyx()

Return the current coordinates of the virtual screen cursor as a tuple (y, x). If leaveok is currently True, then return (-1, -1).

curses.getwin(file)

Read window related data stored in the file by an earlier putwin() call. The routine then creates and initializes a new window using that data, returning the new window object.

curses.has_colors()

Return True if the terminal can display colors; otherwise, return False.

curses.has_ic()

Return True if the terminal has insert- and delete-character capabilities. This function is included for historical reasons only, as all modern software terminal emulators have such capabilities.

curses.has_il()

Return True if the terminal has insert- and delete-line capabilities, or can simulate them using scrolling regions. This function is included for historical reasons only, as all modern software terminal emulators have such capabilities.

curses.has_key(ch)

Take a key value ch, and return True if the current terminal type recognizes a key with that value.

curses.halfdelay(tenths)

Used for half-delay mode, which is similar to cbreak mode in that characters typed by the user are immediately available to the program. However, after blocking for tenths tenths of seconds, raise an exception if nothing has been typed. The value of tenths must be a number between 1 and 255. Use nocbreak() to leave half-delay mode.

curses.init_color(color_number, r, g, b)

Change the definition of a color, taking the number of the color to be changed followed by three RGB values (for the amounts of red, green, and blue components). The value of color_number must be between 0 and COLORS. Each of r, g, b, must be a value between 0 and 1000. When init_color() is used, all occurrences of that color on the screen immediately change to the new definition. This function is a no-op on most terminals; it is active only if can_change_color() returns True.

curses.init_pair(pair_number, fg, bg)

Change the definition of a color-pair. It takes three arguments: the number of the color-pair to be changed, the foreground color number, and the background color number. The value of pair_number must be between 1 and COLOR_PAIRS - 1 (the 0 color pair is wired to white on black and cannot be changed). The value of fg and bg arguments must be between 0 and COLORS. If the color-pair was previously initialized, the screen is refreshed and all occurrences of that color-pair are changed to the new definition.

curses.initscr()

Initialize the library. Return a window object which represents the whole screen.

Note

If there is an error opening the terminal, the underlying curses library may cause the interpreter to exit.

curses.is_term_resized(nlines, ncols)

Return True if resize_term() would modify the window structure, False otherwise.

curses.isendwin()

Return True if endwin() has been called (that is, the curses library has been deinitialized).

curses.keyname(k)

Return the name of the key numbered k as a bytes object. The name of a key generating printable ASCII character is the key’s character. The name of a control-key combination is a two-byte bytes object consisting of a caret (b'^') followed by the corresponding printable ASCII character. The name of an alt-key combination (128–255) is a bytes object consisting of the prefix b'M-' followed by the name of the corresponding ASCII character.

curses.killchar()

Return the user’s current line kill character as a one-byte bytes object. Under Unix operating systems this is a property of the controlling tty of the curses program, and is not set by the curses library itself.

curses.longname()

Return a bytes object containing the terminfo long name field describing the current terminal. The maximum length of a verbose description is 128 characters. It is defined only after the call to initscr().

curses.meta(flag)

If flag is True, allow 8-bit characters to be input. If flag is False, allow only 7-bit chars.

curses.mouseinterval(interval)

Set the maximum time in milliseconds that can elapse between press and release events in order for them to be recognized as a click, and return the previous interval value. The default value is 200 msec, or one fifth of a second.

curses.mousemask(mousemask)

Set the mouse events to be reported, and return a tuple (availmask, oldmask). availmask indicates which of the specified mouse events can be reported; on complete failure it returns 0. oldmask is the previous value of the given window’s mouse event mask. If this function is never called, no mouse events are ever reported.

curses.napms(ms)

Sleep for ms milliseconds.

curses.newpad(nlines, ncols)

Create and return a pointer to a new pad data structure with the given number of lines and columns. Return a pad as a window object.

A pad is like a window, except that it is not restricted by the screen size, and is not necessarily associated with a particular part of the screen. Pads can be used when a large window is needed, and only a part of the window will be on the screen at one time. Automatic refreshes of pads (such as from scrolling or echoing of input) do not occur. The refresh() and noutrefresh() methods of a pad require 6 arguments to specify the part of the pad to be displayed and the location on the screen to be used for the display. The arguments are pminrow, pmincol, sminrow, smincol, smaxrow, smaxcol; the p arguments refer to the upper left corner of the pad region to be displayed and the s arguments define a clipping box on the screen within which the pad region is to be displayed.

curses.newwin(nlines, ncols)

curses.newwin(nlines, ncols, begin_y, begin_x)

Return a new window, whose left-upper corner is at (begin_y, begin_x), and whose height/width is nlines/ncols.

By default, the window will extend from the specified position to the lower right corner of the screen.

curses.nl()

Enter newline mode. This mode translates the return key into newline on input, and translates newline into return and line-feed on output. Newline mode is initially on.

curses.nocbreak()

Leave cbreak mode. Return to normal « cooked » mode with line buffering.

curses.noecho()

Leave echo mode. Echoing of input characters is turned off.

curses.nonl()

Leave newline mode. Disable translation of return into newline on input, and disable low-level translation of newline into newline/return on output (but this does not change the behavior of addch('\n'), which always does the equivalent of return and line feed on the virtual screen). With translation off, curses can sometimes speed up vertical motion a little; also, it will be able to detect the return key on input.

curses.noqiflush()

When the noqiflush() routine is used, normal flush of input and output queues associated with the INTR, QUIT and SUSP characters will not be done. You may want to call noqiflush() in a signal handler if you want output to continue as though the interrupt had not occurred, after the handler exits.

curses.noraw()

Leave raw mode. Return to normal « cooked » mode with line buffering.

curses.pair_content(pair_number)

Return a tuple (fg, bg) containing the colors for the requested color pair. The value of pair_number must be between 1 and COLOR_PAIRS - 1.

curses.pair_number(attr)

Return the number of the color-pair set by the attribute value attr. color_pair() is the counterpart to this function.

curses.putp(str)

Equivalent to tputs(str, 1, putchar); emit the value of a specified terminfo capability for the current terminal. Note that the output of putp() always goes to standard output.

curses.qiflush([flag])

If flag is False, the effect is the same as calling noqiflush(). If flag is True, or no argument is provided, the queues will be flushed when these control characters are read.

curses.raw()

Enter raw mode. In raw mode, normal line buffering and processing of interrupt, quit, suspend, and flow control keys are turned off; characters are presented to curses input functions one by one.

curses.reset_prog_mode()

Restore the terminal to « program » mode, as previously saved by def_prog_mode().

curses.reset_shell_mode()

Restore the terminal to « shell » mode, as previously saved by def_shell_mode().

curses.resetty()

Restore the state of the terminal modes to what it was at the last call to savetty().

curses.resize_term(nlines, ncols)

Backend function used by resizeterm(), performing most of the work; when resizing the windows, resize_term() blank-fills the areas that are extended. The calling application should fill in these areas with appropriate data. The resize_term() function attempts to resize all windows. However, due to the calling convention of pads, it is not possible to resize these without additional interaction with the application.

curses.resizeterm(nlines, ncols)

Resize the standard and current windows to the specified dimensions, and adjusts other bookkeeping data used by the curses library that record the window dimensions (in particular the SIGWINCH handler).

curses.savetty()

Save the current state of the terminal modes in a buffer, usable by resetty().

curses.setsyx(y, x)

Set the virtual screen cursor to y, x. If y and x are both -1, then leaveok is set True.

curses.setupterm(term=None, fd=-1)

Initialize the terminal. term is a string giving the terminal name, or None; if omitted or None, the value of the TERM environment variable will be used. fd is the file descriptor to which any initialization sequences will be sent; if not supplied or -1, the file descriptor for sys.stdout will be used.

curses.start_color()

Must be called if the programmer wants to use colors, and before any other color manipulation routine is called. It is good practice to call this routine right after initscr().

start_color() initializes eight basic colors (black, red, green, yellow, blue, magenta, cyan, and white), and two global variables in the curses module, COLORS and COLOR_PAIRS, containing the maximum number of colors and color-pairs the terminal can support. It also restores the colors on the terminal to the values they had when the terminal was just turned on.

curses.termattrs()

Return a logical OR of all video attributes supported by the terminal. This information is useful when a curses program needs complete control over the appearance of the screen.

curses.termname()

Return the value of the environment variable TERM, as a bytes object, truncated to 14 characters.

curses.tigetflag(capname)

Return the value of the Boolean capability corresponding to the terminfo capability name capname as an integer. Return the value -1 if capname is not a Boolean capability, or 0 if it is canceled or absent from the terminal description.

curses.tigetnum(capname)

Return the value of the numeric capability corresponding to the terminfo capability name capname as an integer. Return the value -2 if capname is not a numeric capability, or -1 if it is canceled or absent from the terminal description.

curses.tigetstr(capname)

Return the value of the string capability corresponding to the terminfo capability name capname as a bytes object. Return None if capname is not a terminfo « string capability », or is canceled or absent from the terminal description.

curses.tparm(str[, ...])

Instantiate the bytes object str with the supplied parameters, where str should be a parameterized string obtained from the terminfo database. E.g. tparm(tigetstr("cup"), 5, 3) could result in b'\033[6;4H', the exact result depending on terminal type.

curses.typeahead(fd)

Specify that the file descriptor fd be used for typeahead checking. If fd is -1, then no typeahead checking is done.

The curses library does « line-breakout optimization » by looking for typeahead periodically while updating the screen. If input is found, and it is coming from a tty, the current update is postponed until refresh or doupdate is called again, allowing faster response to commands typed in advance. This function allows specifying a different file descriptor for typeahead checking.

curses.unctrl(ch)

Return a bytes object which is a printable representation of the character ch. Control characters are represented as a caret followed by the character, for example as b'^C'. Printing characters are left as they are.

curses.ungetch(ch)

Push ch so the next getch() will return it.

Note

Only one ch can be pushed before getch() is called.

curses.update_lines_cols()

Update LINES and COLS. Useful for detecting manual screen resize.

Nouveau dans la version 3.5.

curses.unget_wch(ch)

Push ch so the next get_wch() will return it.

Note

Only one ch can be pushed before get_wch() is called.

Nouveau dans la version 3.3.

curses.ungetmouse(id, x, y, z, bstate)

Push a KEY_MOUSE event onto the input queue, associating the given state data with it.

curses.use_env(flag)

If used, this function should be called before initscr() or newterm are called. When flag is False, the values of lines and columns specified in the terminfo database will be used, even if environment variables LINES and COLUMNS (used by default) are set, or if curses is running in a window (in which case default behavior would be to use the window size if LINES and COLUMNS are not set).

curses.use_default_colors()

Allow use of default values for colors on terminals supporting this feature. Use this to support transparency in your application. The default color is assigned to the color number -1. After calling this function, init_pair(x, curses.COLOR_RED, -1) initializes, for instance, color pair x to a red foreground color on the default background.

curses.wrapper(func, ...)

Initialize curses and call another callable object, func, which should be the rest of your curses-using application. If the application raises an exception, this function will restore the terminal to a sane state before re-raising the exception and generating a traceback. The callable object func is then passed the main window “stdscr” as its first argument, followed by any other arguments passed to wrapper(). Before calling func, wrapper() turns on cbreak mode, turns off echo, enables the terminal keypad, and initializes colors if the terminal has color support. On exit (whether normally or by exception) it restores cooked mode, turns on echo, and disables the terminal keypad.

16.10.2. Window Objects

Window objects, as returned by initscr() and newwin() above, have the following methods and attributes:

window.addch(ch[, attr])

window.addch(y, x, ch[, attr])

Paint character ch at (y, x) with attributes attr, overwriting any character previously painter at that location. By default, the character position and attributes are the current settings for the window object.

Note

Writing outside the window, subwindow, or pad raises a curses.error. Attempting to write to the lower right corner of a window, subwindow, or pad will cause an exception to be raised after the character is printed.

window.addnstr(str, n[, attr])

window.addnstr(y, x, str, n[, attr])

Paint at most n characters of the character string str at (y, x) with attributes attr, overwriting anything previously on the display.

window.addstr(str[, attr])

window.addstr(y, x, str[, attr])

Paint the character string str at (y, x) with attributes attr, overwriting anything previously on the display.

Note

Writing outside the window, subwindow, or pad raises curses.error. Attempting to write to the lower right corner of a window, subwindow, or pad will cause an exception to be raised after the string is printed.

window.attroff(attr)

Remove attribute attr from the « background » set applied to all writes to the current window.

window.attron(attr)

Add attribute attr from the « background » set applied to all writes to the current window.

window.attrset(attr)

Set the « background » set of attributes to attr. This set is initially 0 (no attributes).

window.bkgd(ch[, attr])

Set the background property of the window to the character ch, with attributes attr. The change is then applied to every character position in that window:

The attribute of every character in the window is changed to the new background attribute.

Wherever the former background character appears, it is changed to the new background character.

window.bkgdset(ch[, attr])

Set the window’s background. A window’s background consists of a character and any combination of attributes. The attribute part of the background is combined (OR’ed) with all non-blank characters that are written into the window. Both the character and attribute parts of the background are combined with the blank characters. The background becomes a property of the character and moves with the character through any scrolling and insert/delete line/character operations.

window.border([ls[, rs[, ts[, bs[, tl[, tr[, bl[, br]]]]]]]])

Draw a border around the edges of the window. Each parameter specifies the character to use for a specific part of the border; see the table below for more details.

Note

A 0 value for any parameter will cause the default character to be used for that parameter. Keyword parameters can not be used. The defaults are listed in this table:

Paramètre

Description

Valeur par défaut

ls

Left side

ACS_VLINE

rs

Right side

ACS_VLINE

ts

Top

ACS_HLINE

bs

Bottom

ACS_HLINE

tl

Upper-left corner

ACS_ULCORNER

tr

Upper-right corner

ACS_URCORNER

bl

Bottom-left corner

ACS_LLCORNER

br

Bottom-right corner

ACS_LRCORNER

window.box([vertch, horch])

Similar to border(), but both ls and rs are vertch and both ts and bs are horch. The default corner characters are always used by this function.

window.chgat(attr)

window.chgat(num, attr)

window.chgat(y, x, attr)

window.chgat(y, x, num, attr)

Set the attributes of num characters at the current cursor position, or at position (y, x) if supplied. If num is not given or is -1, the attribute will be set on all the characters to the end of the line. This function moves cursor to position (y, x) if supplied. The changed line will be touched using the touchline() method so that the contents will be redisplayed by the next window refresh.

window.clear()

Like erase(), but also cause the whole window to be repainted upon next call to refresh().

window.clearok(flag)

If flag is True, the next call to refresh() will clear the window completely.

window.clrtobot()

Erase from cursor to the end of the window: all lines below the cursor are deleted, and then the equivalent of clrtoeol() is performed.

window.clrtoeol()

Erase from cursor to the end of the line.

window.cursyncup()

Update the current cursor position of all the ancestors of the window to reflect the current cursor position of the window.

window.delch([y, x])

Delete any character at (y, x).

window.deleteln()

Delete the line under the cursor. All following lines are moved up by one line.

window.derwin(begin_y, begin_x)

window.derwin(nlines, ncols, begin_y, begin_x)

An abbreviation for « derive window », derwin() is the same as calling subwin(), except that begin_y and begin_x are relative to the origin of the window, rather than relative to the entire screen. Return a window object for the derived window.

window.echochar(ch[, attr])

Add character ch with attribute attr, and immediately call refresh() on the window.

window.enclose(y, x)

Test whether the given pair of screen-relative character-cell coordinates are enclosed by the given window, returning True or False. It is useful for determining what subset of the screen windows enclose the location of a mouse event.

window.encoding

Encoding used to encode method arguments (Unicode strings and characters). The encoding attribute is inherited from the parent window when a subwindow is created, for example with window.subwin(). By default, the locale encoding is used (see locale.getpreferredencoding()).

Nouveau dans la version 3.3.

window.erase()

Clear the window.

window.getbegyx()

Return a tuple (y, x) of co-ordinates of upper-left corner.

window.getbkgd()

Return the given window’s current background character/attribute pair.

window.getch([y, x])

Get a character. Note that the integer returned does not have to be in ASCII range: function keys, keypad keys and so on are represented by numbers higher than 255. In no-delay mode, return -1 if there is no input, otherwise wait until a key is pressed.

window.get_wch([y, x])

Get a wide character. Return a character for most keys, or an integer for function keys, keypad keys, and other special keys. In no-delay mode, raise an exception if there is no input.

Nouveau dans la version 3.3.

window.getkey([y, x])

Get a character, returning a string instead of an integer, as getch() does. Function keys, keypad keys and other special keys return a multibyte string containing the key name. In no-delay mode, raise an exception if there is no input.

window.getmaxyx()

Return a tuple (y, x) of the height and width of the window.

window.getparyx()

Return the beginning coordinates of this window relative to its parent window as a tuple (y, x). Return (-1, -1) if this window has no parent.

window.getstr()

window.getstr(n)

window.getstr(y, x)

window.getstr(y, x, n)

Read a bytes object from the user, with primitive line editing capacity.

window.getyx()

Return a tuple (y, x) of current cursor position relative to the window’s upper-left corner.

window.hline(ch, n)

window.hline(y, x, ch, n)

Display a horizontal line starting at (y, x) with length n consisting of the character ch.

window.idcok(flag)

If flag is False, curses no longer considers using the hardware insert/delete character feature of the terminal; if flag is True, use of character insertion and deletion is enabled. When curses is first initialized, use of character insert/delete is enabled by default.

window.idlok(flag)

If flag is True, curses will try and use hardware line editing facilities. Otherwise, line insertion/deletion are disabled.

window.immedok(flag)

If flag is True, any change in the window image automatically causes the window to be refreshed; you no longer have to call refresh() yourself. However, it may degrade performance considerably, due to repeated calls to wrefresh. This option is disabled by default.

window.inch([y, x])

Return the character at the given position in the window. The bottom 8 bits are the character proper, and upper bits are the attributes.

window.insch(ch[, attr])

window.insch(y, x, ch[, attr])

Paint character ch at (y, x) with attributes attr, moving the line from position x right by one character.

window.insdelln(nlines)

Insert nlines lines into the specified window above the current line. The nlines bottom lines are lost. For negative nlines, delete nlines lines starting with the one under the cursor, and move the remaining lines up. The bottom nlines lines are cleared. The current cursor position remains the same.

window.insertln()

Insert a blank line under the cursor. All following lines are moved down by one line.

window.insnstr(str, n[, attr])

window.insnstr(y, x, str, n[, attr])

Insert a character string (as many characters as will fit on the line) before the character under the cursor, up to n characters. If n is zero or negative, the entire string is inserted. All characters to the right of the cursor are shifted right, with the rightmost characters on the line being lost. The cursor position does not change (after moving to y, x, if specified).

window.insstr(str[, attr])

window.insstr(y, x, str[, attr])

Insert a character string (as many characters as will fit on the line) before the character under the cursor. All characters to the right of the cursor are shifted right, with the rightmost characters on the line being lost. The cursor position does not change (after moving to y, x, if specified).

window.instr([n])

window.instr(y, x[, n])

Return a bytes object of characters, extracted from the window starting at the current cursor position, or at y, x if specified. Attributes are stripped from the characters. If n is specified, instr() returns a string at most n characters long (exclusive of the trailing NUL).

window.is_linetouched(line)

Return True if the specified line was modified since the last call to refresh(); otherwise return False. Raise a curses.error exception if line is not valid for the given window.

window.is_wintouched()

Return True if the specified window was modified since the last call to refresh(); otherwise return False.

window.keypad(flag)

If flag is True, escape sequences generated by some keys (keypad, function keys) will be interpreted by curses. If flag is False, escape sequences will be left as is in the input stream.

window.leaveok(flag)

If flag is True, cursor is left where it is on update, instead of being at « cursor position. » This reduces cursor movement where possible. If possible the cursor will be made invisible.

If flag is False, cursor will always be at « cursor position » after an update.

window.move(new_y, new_x)

Move cursor to (new_y, new_x).

window.mvderwin(y, x)

Move the window inside its parent window. The screen-relative parameters of the window are not changed. This routine is used to display different parts of the parent window at the same physical position on the screen.

window.mvwin(new_y, new_x)

Move the window so its upper-left corner is at (new_y, new_x).

window.nodelay(flag)

If flag is True, getch() will be non-blocking.

window.notimeout(flag)

If flag is True, escape sequences will not be timed out.

If flag is False, after a few milliseconds, an escape sequence will not be interpreted, and will be left in the input stream as is.

window.noutrefresh()

Mark for refresh but wait. This function updates the data structure representing the desired state of the window, but does not force an update of the physical screen. To accomplish that, call doupdate().

window.overlay(destwin[, sminrow, smincol, dminrow, dmincol, dmaxrow, dmaxcol])

Overlay the window on top of destwin. The windows need not be the same size, only the overlapping region is copied. This copy is non-destructive, which means that the current background character does not overwrite the old contents of destwin.

To get fine-grained control over the copied region, the second form of overlay() can be used. sminrow and smincol are the upper-left coordinates of the source window, and the other variables mark a rectangle in the destination window.

window.overwrite(destwin[, sminrow, smincol, dminrow, dmincol, dmaxrow, dmaxcol])

Overwrite the window on top of destwin. The windows need not be the same size, in which case only the overlapping region is copied. This copy is destructive, which means that the current background character overwrites the old contents of destwin.

To get fine-grained control over the copied region, the second form of overwrite() can be used. sminrow and smincol are the upper-left coordinates of the source window, the other variables mark a rectangle in the destination window.

window.putwin(file)

Write all data associated with the window into the provided file object. This information can be later retrieved using the getwin() function.

window.redrawln(beg, num)

Indicate that the num screen lines, starting at line beg, are corrupted and should be completely redrawn on the next refresh() call.

window.redrawwin()

Touch the entire window, causing it to be completely redrawn on the next refresh() call.

window.refresh([pminrow, pmincol, sminrow, smincol, smaxrow, smaxcol])

Update the display immediately (sync actual screen with previous drawing/deleting methods).

The 6 optional arguments can only be specified when the window is a pad created with newpad(). The additional parameters are needed to indicate what part of the pad and screen are involved. pminrow and pmincol specify the upper left-hand corner of the rectangle to be displayed in the pad. sminrow, smincol, smaxrow, and smaxcol specify the edges of the rectangle to be displayed on the screen. The lower right-hand corner of the rectangle to be displayed in the pad is calculated from the screen coordinates, since the rectangles must be the same size. Both rectangles must be entirely contained within their respective structures. Negative values of pminrow, pmincol, sminrow, or smincol are treated as if they were zero.

window.resize(nlines, ncols)

Reallocate storage for a curses window to adjust its dimensions to the specified values. If either dimension is larger than the current values, the window’s data is filled with blanks that have the current background rendition (as set by bkgdset()) merged into them.

window.scroll([lines=1])

Scroll the screen or scrolling region upward by lines lines.

window.scrollok(flag)

Control what happens when the cursor of a window is moved off the edge of the window or scrolling region, either as a result of a newline action on the bottom line, or typing the last character of the last line. If flag is False, the cursor is left on the bottom line. If flag is True, the window is scrolled up one line. Note that in order to get the physical scrolling effect on the terminal, it is also necessary to call idlok().

window.setscrreg(top, bottom)

Set the scrolling region from line top to line bottom. All scrolling actions will take place in this region.

window.standend()

Turn off the standout attribute. On some terminals this has the side effect of turning off all attributes.

window.standout()

Turn on attribute A_STANDOUT.

window.subpad(begin_y, begin_x)

window.subpad(nlines, ncols, begin_y, begin_x)

Return a sub-window, whose upper-left corner is at (begin_y, begin_x), and whose width/height is ncols/nlines.

window.subwin(begin_y, begin_x)

window.subwin(nlines, ncols, begin_y, begin_x)

Return a sub-window, whose upper-left corner is at (begin_y, begin_x), and whose width/height is ncols/nlines.

By default, the sub-window will extend from the specified position to the lower right corner of the window.

window.syncdown()

Touch each location in the window that has been touched in any of its ancestor windows. This routine is called by refresh(), so it should almost never be necessary to call it manually.

window.syncok(flag)

If flag is True, then syncup() is called automatically whenever there is a change in the window.

window.syncup()

Touch all locations in ancestors of the window that have been changed in the window.

window.timeout(delay)

Set blocking or non-blocking read behavior for the window. If delay is negative, blocking read is used (which will wait indefinitely for input). If delay is zero, then non-blocking read is used, and getch() will return -1 if no input is waiting. If delay is positive, then getch() will block for delay milliseconds, and return -1 if there is still no input at the end of that time.

window.touchline(start, count[, changed])

Pretend count lines have been changed, starting with line start. If changed is supplied, it specifies whether the affected lines are marked as having been changed (changed=True) or unchanged (changed=False).

window.touchwin()

Pretend the whole window has been changed, for purposes of drawing optimizations.

window.untouchwin()

Mark all lines in the window as unchanged since the last call to refresh().

window.vline(ch, n)

window.vline(y, x, ch, n)

Display a vertical line starting at (y, x) with length n consisting of the character ch.

16.10.3. Constantes

The curses module defines the following data members:

curses.ERR

Some curses routines that return an integer, such as getch(), return ERR upon failure.

curses.OK

Some curses routines that return an integer, such as napms(), return OK upon success.

curses.version

A bytes object representing the current version of the module. Also available as __version__.

Some constants are available to specify character cell attributes. The exact constants available are system dependent.

Attribut

Signification

A_ALTCHARSET

Alternate character set mode

A_BLINK

Blink mode

A_BOLD

Bold mode

A_DIM

Dim mode

A_INVIS

Invisible or blank mode

A_NORMAL

Attribut normal

A_PROTECT

Protected mode

A_REVERSE

Reverse background and foreground colors

A_STANDOUT

Standout mode

A_UNDERLINE

Underline mode

A_HORIZONTAL

Horizontal highlight

A_LEFT

Left highlight

A_LOW

Low highlight

A_RIGHT

Right highlight

A_TOP

Top highlight

A_VERTICAL

Vertical highlight

A_CHARTEXT

Bit-mask to extract a character

Several constants are available to extract corresponding attributes returned by some methods.

Bit-mask

Signification

A_ATTRIBUTES

Bit-mask to extract attributes

A_CHARTEXT

Bit-mask to extract a character

A_COLOR

Bit-mask to extract color-pair field information

Keys are referred to by integer constants with names starting with KEY_. The exact keycaps available are system dependent.

Key constant

Key

KEY_MIN

Minimum key value

KEY_BREAK

Break key (unreliable)

KEY_DOWN

Down-arrow

KEY_UP

Up-arrow

KEY_LEFT

Left-arrow

KEY_RIGHT

Right-arrow

KEY_HOME

Home key (upward+left arrow)

KEY_BACKSPACE

Backspace (unreliable)

KEY_F0

Function keys. Up to 64 function keys are supported.

KEY_Fn

Value of function key n

KEY_DL

Delete line

KEY_IL

Insert line

KEY_DC

Delete character

KEY_IC

Insert char or enter insert mode

KEY_EIC

Exit insert char mode

KEY_CLEAR

Clear screen

KEY_EOS

Clear to end of screen

KEY_EOL

Clear to end of line

KEY_SF

Scroll 1 line forward

KEY_SR

Scroll 1 line backward (reverse)

KEY_NPAGE

Next page

KEY_PPAGE

Previous page

KEY_STAB

Set tab

KEY_CTAB

Clear tab

KEY_CATAB

Clear all tabs

KEY_ENTER

Enter or send (unreliable)

KEY_SRESET

Soft (partial) reset (unreliable)

KEY_RESET

Reset or hard reset (unreliable)

KEY_PRINT

Print

KEY_LL

Home down or bottom (lower left)

KEY_A1

Upper left of keypad

KEY_A3

Upper right of keypad

KEY_B2

Center of keypad

KEY_C1

Lower left of keypad

KEY_C3

Lower right of keypad

KEY_BTAB

Back tab

KEY_BEG

Beg (beginning)

KEY_CANCEL

Cancel

KEY_CLOSE

Close

KEY_COMMAND

Cmd (command)

KEY_COPY

Copy

KEY_CREATE

Create

KEY_END

End

KEY_EXIT

Exit

KEY_FIND

Find

KEY_HELP

Help

KEY_MARK

Mark

KEY_MESSAGE

Message

KEY_MOVE

Move

KEY_NEXT

Next

KEY_OPEN

Open

KEY_OPTIONS

Options

KEY_PREVIOUS

Prev (previous)

KEY_REDO

Redo

KEY_REFERENCE

Ref (reference)

KEY_REFRESH

Refresh

KEY_REPLACE

Replace

KEY_RESTART

Restart

KEY_RESUME

Resume

KEY_SAVE

Save

KEY_SBEG

Shifted Beg (beginning)

KEY_SCANCEL

Shifted Cancel

KEY_SCOMMAND

Shifted Command

KEY_SCOPY

Shifted Copy

KEY_SCREATE

Shifted Create

KEY_SDC

Shifted Delete char

KEY_SDL

Shifted Delete line

KEY_SELECT

Select

KEY_SEND

Shifted End

KEY_SEOL

Shifted Clear line

KEY_SEXIT

Shifted Exit

KEY_SFIND

Shifted Find

KEY_SHELP

Shifted Help

KEY_SHOME

Shifted Home

KEY_SIC

Shifted Input

KEY_SLEFT

Shifted Left arrow

KEY_SMESSAGE

Shifted Message

KEY_SMOVE

Shifted Move

KEY_SNEXT

Shifted Next

KEY_SOPTIONS

Shifted Options

KEY_SPREVIOUS

Shifted Prev

KEY_SPRINT

Shifted Print

KEY_SREDO

Shifted Redo

KEY_SREPLACE

Shifted Replace

KEY_SRIGHT

Shifted Right arrow

KEY_SRSUME

Shifted Resume

KEY_SSAVE

Shifted Save

KEY_SSUSPEND

Shifted Suspend

KEY_SUNDO

Shifted Undo

KEY_SUSPEND

Suspend

KEY_UNDO

Undo

KEY_MOUSE

Mouse event has occurred

KEY_RESIZE

Terminal resize event

KEY_MAX

Maximum key value

On VT100s and their software emulations, such as X terminal emulators, there are normally at least four function keys (KEY_F1, KEY_F2, KEY_F3, KEY_F4) available, and the arrow keys mapped to KEY_UP, KEY_DOWN, KEY_LEFT and KEY_RIGHT in the obvious way. If your machine has a PC keyboard, it is safe to expect arrow keys and twelve function keys (older PC keyboards may have only ten function keys); also, the following keypad mappings are standard:

Keycap

Constante

Insert

KEY_IC

Delete

KEY_DC

Home

KEY_HOME

End

KEY_END

Page Up

KEY_PPAGE

Page Down

KEY_NPAGE

The following table lists characters from the alternate character set. These are inherited from the VT100 terminal, and will generally be available on software emulations such as X terminals. When there is no graphic available, curses falls back on a crude printable ASCII approximation.

Note

These are available only after initscr() has been called.

ACS code

Signification

ACS_BBSS

alternate name for upper right corner

ACS_BLOCK

solid square block

ACS_BOARD

board of squares

ACS_BSBS

alternate name for horizontal line

ACS_BSSB

alternate name for upper left corner

ACS_BSSS

alternate name for top tee

ACS_BTEE

bottom tee

ACS_BULLET

bullet

ACS_CKBOARD

checker board (stipple)

ACS_DARROW

arrow pointing down

ACS_DEGREE

degree symbol

ACS_DIAMOND

diamond

ACS_GEQUAL

greater-than-or-equal-to

ACS_HLINE

horizontal line

ACS_LANTERN

lantern symbol

ACS_LARROW

left arrow

ACS_LEQUAL

less-than-or-equal-to

ACS_LLCORNER

lower left-hand corner

ACS_LRCORNER

lower right-hand corner

ACS_LTEE

left tee

ACS_NEQUAL

not-equal sign

ACS_PI

letter pi

ACS_PLMINUS

plus-or-minus sign

ACS_PLUS

big plus sign

ACS_RARROW

right arrow

ACS_RTEE

right tee

ACS_S1

scan line 1

ACS_S3

scan line 3

ACS_S7

scan line 7

ACS_S9

scan line 9

ACS_SBBS

alternate name for lower right corner

ACS_SBSB

alternate name for vertical line

ACS_SBSS

alternate name for right tee

ACS_SSBB

alternate name for lower left corner

ACS_SSBS

alternate name for bottom tee

ACS_SSSB

alternate name for left tee

ACS_SSSS

alternate name for crossover or big plus

ACS_STERLING

pound sterling

ACS_TTEE

top tee

ACS_UARROW

up arrow

ACS_ULCORNER

upper left corner

ACS_URCORNER

upper right corner

ACS_VLINE

vertical line

The following table lists the predefined colors:

Constante

Color

COLOR_BLACK

Black

COLOR_BLUE

Blue

COLOR_CYAN

Cyan (light greenish blue)

COLOR_GREEN

Green

COLOR_MAGENTA

Magenta (purplish red)

COLOR_RED

Red

COLOR_WHITE

White

COLOR_YELLOW

Yellow

16.11. curses.textpad — Text input widget for curses programs

The curses.textpad module provides a Textbox class that handles elementary text editing in a curses window, supporting a set of keybindings resembling those of Emacs (thus, also of Netscape Navigator, BBedit 6.x, FrameMaker, and many other programs). The module also provides a rectangle-drawing function useful for framing text boxes or for other purposes.

The module curses.textpad defines the following function:

curses.textpad.rectangle(win, uly, ulx, lry, lrx)

Draw a rectangle. The first argument must be a window object; the remaining arguments are coordinates relative to that window. The second and third arguments are the y and x coordinates of the upper left hand corner of the rectangle to be drawn; the fourth and fifth arguments are the y and x coordinates of the lower right hand corner. The rectangle will be drawn using VT100/IBM PC forms characters on terminals that make this possible (including xterm and most other software terminal emulators). Otherwise it will be drawn with ASCII dashes, vertical bars, and plus signs.

16.11.1. Textbox objects

You can instantiate a Textbox object as follows:

class curses.textpad.Textbox(win)

Return a textbox widget object. The win argument should be a curses window object in which the textbox is to be contained. The edit cursor of the textbox is initially located at the upper left hand corner of the containing window, with coordinates (0, 0). The instance’s stripspaces flag is initially on.

Textbox objects have the following methods:

edit([validator])

This is the entry point you will normally use. It accepts editing keystrokes until one of the termination keystrokes is entered. If validator is supplied, it must be a function. It will be called for each keystroke entered with the keystroke as a parameter; command dispatch is done on the result. This method returns the window contents as a string; whether blanks in the window are included is affected by the stripspaces attribute.

do_command(ch)

Process a single command keystroke. Here are the supported special keystrokes:

Keystroke

Action

Control-A

Go to left edge of window.

Control-B

Cursor left, wrapping to previous line if appropriate.

Control-D

Delete character under cursor.

Control-E

Go to right edge (stripspaces off) or end of line (stripspaces on).

Control-F

Cursor right, wrapping to next line when appropriate.

Control-G

Terminate, returning the window contents.

Control-H

Delete character backward.

Control-J

Terminate if the window is 1 line, otherwise insert newline.

Control-K

If line is blank, delete it, otherwise clear to end of line.

Control-L

Refresh screen.

Control-N

Cursor down; move down one line.

Control-O

Insert a blank line at cursor location.

Control-P

Cursor up; move up one line.

Move operations do nothing if the cursor is at an edge where the movement is not possible. The following synonyms are supported where possible:

Constante

Keystroke

KEY_LEFT

Control-B

KEY_RIGHT

Control-F

KEY_UP

Control-P

KEY_DOWN

Control-N

KEY_BACKSPACE

Control-h

All other keystrokes are treated as a command to insert the given character and move right (with line wrapping).

gather()

Return the window contents as a string; whether blanks in the window are included is affected by the stripspaces member.

stripspaces

This attribute is a flag which controls the interpretation of blanks in the window. When it is on, trailing blanks on each line are ignored; any cursor motion that would land the cursor on a trailing blank goes to the end of that line instead, and trailing blanks are stripped when the window contents are gathered.

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16.12. curses.ascii — Utilities for ASCII characters

The curses.ascii module supplies name constants for ASCII characters and functions to test membership in various ASCII character classes. The constants supplied are names for control characters as follows:

Nom

Signification

NUL

SOH

Start of heading, console interrupt

STX

Start of text

ETX

End of text

EOT

End of transmission

ENQ

Enquiry, goes with ACK flow control

ACK

Acknowledgement

BEL

Bell

BS

Backspace

TAB

Tab

HT

Alias for TAB: « Horizontal tab »

LF

Line feed

NL

Alias for LF: « New line »

VT

Vertical tab

FF

Form feed

CR

Retour chariot

SO

Shift-out, begin alternate character set

SI

Shift-in, resume default character set

DLE

Data-link escape

DC1

XON, for flow control

DC2

Device control 2, block-mode flow control

DC3

XOFF, for flow control

DC4

Device control 4

NAK

Negative acknowledgement

SYN

Synchronous idle

ETB

End transmission block

CAN

Cancel

EM

End of medium

SUB

Substitute

ESC

Escape

FS

Séparateur de fichiers

GS

Séparateur de groupe

RS

Record separator, block-mode terminator

US

Unit separator

SP

Space

DEL

Delete

Note that many of these have little practical significance in modern usage. The mnemonics derive from teleprinter conventions that predate digital computers.

The module supplies the following functions, patterned on those in the standard C library:

curses.ascii.isalnum(c)

Checks for an ASCII alphanumeric character; it is equivalent to isalpha(c) or isdigit(c).

curses.ascii.isalpha(c)

Checks for an ASCII alphabetic character; it is equivalent to isupper(c) or islower(c).

curses.ascii.isascii(c)

Checks for a character value that fits in the 7-bit ASCII set.

curses.ascii.isblank(c)

Checks for an ASCII whitespace character; space or horizontal tab.

curses.ascii.iscntrl(c)

Checks for an ASCII control character (in the range 0x00 to 0x1f or 0x7f).

curses.ascii.isdigit(c)

Checks for an ASCII decimal digit, '0' through '9'. This is equivalent to c in string.digits.

curses.ascii.isgraph(c)

Checks for ASCII any printable character except space.

curses.ascii.islower(c)

Checks for an ASCII lower-case character.

curses.ascii.isprint(c)

Checks for any ASCII printable character including space.

curses.ascii.ispunct(c)

Checks for any printable ASCII character which is not a space or an alphanumeric character.

curses.ascii.isspace(c)

Checks for ASCII white-space characters; space, line feed, carriage return, form feed, horizontal tab, vertical tab.

curses.ascii.isupper(c)

Checks for an ASCII uppercase letter.

curses.ascii.isxdigit(c)

Checks for an ASCII hexadecimal digit. This is equivalent to c in string.hexdigits.

curses.ascii.isctrl(c)

Checks for an ASCII control character (ordinal values 0 to 31).

curses.ascii.ismeta(c)

Checks for a non-ASCII character (ordinal values 0x80 and above).

These functions accept either integers or single-character strings; when the argument is a string, it is first converted using the built-in function ord().

Note that all these functions check ordinal bit values derived from the character of the string you pass in; they do not actually know anything about the host machine’s character encoding.

The following two functions take either a single-character string or integer byte value; they return a value of the same type.

curses.ascii.ascii(c)

Return the ASCII value corresponding to the low 7 bits of c.

curses.ascii.ctrl(c)

Return the control character corresponding to the given character (the character bit value is bitwise-anded with 0x1f).

curses.ascii.alt(c)

Return the 8-bit character corresponding to the given ASCII character (the character bit value is bitwise-ored with 0x80).

The following function takes either a single-character string or integer value; it returns a string.

curses.ascii.unctrl(c)

Return a string representation of the ASCII character c. If c is printable, this string is the character itself. If the character is a control character (0x00–0x1f) the string consists of a caret ('^') followed by the corresponding uppercase letter. If the character is an ASCII delete (0x7f) the string is '^?'. If the character has its meta bit (0x80) set, the meta bit is stripped, the preceding rules applied, and '!' prepended to the result.

curses.ascii.controlnames

A 33-element string array that contains the ASCII mnemonics for the thirty-two ASCII control characters from 0 (NUL) to 0x1f (US), in order, plus the mnemonic SP for the space character.

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16.13. curses.panel — A panel stack extension for curses

Panels are windows with the added feature of depth, so they can be stacked on top of each other, and only the visible portions of each window will be displayed. Panels can be added, moved up or down in the stack, and removed.

16.13.1. Fonctions

The module curses.panel defines the following functions:

curses.panel.bottom_panel()

Returns the bottom panel in the panel stack.

curses.panel.new_panel(win)

Returns a panel object, associating it with the given window win. Be aware that you need to keep the returned panel object referenced explicitly. If you don’t, the panel object is garbage collected and removed from the panel stack.

curses.panel.top_panel()

Returns the top panel in the panel stack.

curses.panel.update_panels()

Updates the virtual screen after changes in the panel stack. This does not call curses.doupdate(), so you’ll have to do this yourself.

16.13.2. Panel Objects

Panel objects, as returned by new_panel() above, are windows with a stacking order. There’s always a window associated with a panel which determines the content, while the panel methods are responsible for the window’s depth in the panel stack.

Panel objects have the following methods:

Panel.above()

Returns the panel above the current panel.

Panel.below()

Returns the panel below the current panel.

Panel.bottom()

Push the panel to the bottom of the stack.

Panel.hidden()

Returns True if the panel is hidden (not visible), False otherwise.

Panel.hide()

Hide the panel. This does not delete the object, it just makes the window on screen invisible.

Panel.move(y, x)

Move the panel to the screen coordinates (y, x).

Panel.replace(win)

Change the window associated with the panel to the window win.

Panel.set_userptr(obj)

Set the panel’s user pointer to obj. This is used to associate an arbitrary piece of data with the panel, and can be any Python object.

Panel.show()

Display the panel (which might have been hidden).

Panel.top()

Push panel to the top of the stack.

Panel.userptr()

Returns the user pointer for the panel. This might be any Python object.

Panel.window()

Returns the window object associated with the panel.

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16.14. platform — Access to underlying platform’s identifying data

Code source : Lib/platform.py [https://github.com/python/cpython/tree/3.6/Lib/platform.py]

Note

Specific platforms listed alphabetically, with Linux included in the Unix section.

16.14.1. Cross Platform

platform.architecture(executable=sys.executable, bits='', linkage='')

Queries the given executable (defaults to the Python interpreter binary) for various architecture information.

Returns a tuple (bits, linkage) which contain information about the bit architecture and the linkage format used for the executable. Both values are returned as strings.

Values that cannot be determined are returned as given by the parameter presets. If bits is given as '', the sizeof(pointer) (or sizeof(long) on Python version < 1.5.2) is used as indicator for the supported pointer size.

The function relies on the system’s file command to do the actual work. This is available on most if not all Unix platforms and some non-Unix platforms and then only if the executable points to the Python interpreter. Reasonable defaults are used when the above needs are not met.

Note

On Mac OS X (and perhaps other platforms), executable files may be universal files containing multiple architectures.

To get at the « 64-bitness » of the current interpreter, it is more reliable to query the sys.maxsize attribute:

is_64bits = sys.maxsize > 2**32

platform.machine()

Returns the machine type, e.g. 'i386'. An empty string is returned if the value cannot be determined.

platform.node()

Returns the computer’s network name (may not be fully qualified!). An empty string is returned if the value cannot be determined.

platform.platform(aliased=0, terse=0)

Returns a single string identifying the underlying platform with as much useful information as possible.

The output is intended to be human readable rather than machine parseable. It may look different on different platforms and this is intended.

If aliased is true, the function will use aliases for various platforms that report system names which differ from their common names, for example SunOS will be reported as Solaris. The system_alias() function is used to implement this.

Setting terse to true causes the function to return only the absolute minimum information needed to identify the platform.

platform.processor()

Returns the (real) processor name, e.g. 'amdk6'.

An empty string is returned if the value cannot be determined. Note that many platforms do not provide this information or simply return the same value as for machine(). NetBSD does this.

platform.python_build()

Returns a tuple (buildno, builddate) stating the Python build number and date as strings.

platform.python_compiler()

Returns a string identifying the compiler used for compiling Python.

platform.python_branch()

Returns a string identifying the Python implementation SCM branch.

platform.python_implementation()

Returns a string identifying the Python implementation. Possible return values are: “CPython”, “IronPython”, “Jython”, “PyPy”.

platform.python_revision()

Returns a string identifying the Python implementation SCM revision.

platform.python_version()

Returns the Python version as string 'major.minor.patchlevel'.

Note that unlike the Python sys.version, the returned value will always include the patchlevel (it defaults to 0).

platform.python_version_tuple()

Returns the Python version as tuple (major, minor, patchlevel) of strings.

Note that unlike the Python sys.version, the returned value will always include the patchlevel (it defaults to '0').

platform.release()

Returns the system’s release, e.g. '2.2.0' or 'NT' An empty string is returned if the value cannot be determined.

platform.system()

Returns the system/OS name, e.g. 'Linux', 'Windows', or 'Java'. An empty string is returned if the value cannot be determined.

platform.system_alias(system, release, version)

Returns (system, release, version) aliased to common marketing names used for some systems. It also does some reordering of the information in some cases where it would otherwise cause confusion.

platform.version()

Returns the system’s release version, e.g. '#3 on degas'. An empty string is returned if the value cannot be determined.

platform.uname()

Fairly portable uname interface. Returns a namedtuple() containing six attributes: system, node, release, version, machine, and processor.

Note that this adds a sixth attribute (processor) not present in the os.uname() result. Also, the attribute names are different for the first two attributes; os.uname() names them sysname and nodename.

Entries which cannot be determined are set to ''.

Modifié dans la version 3.3: Le type renvoyé passe d’un tuple à un namedtuple.

16.14.2. Java Platform

platform.java_ver(release='', vendor='', vminfo=('', '', ''), osinfo=('', '', ''))

Version interface for Jython.

Returns a tuple (release, vendor, vminfo, osinfo) with vminfo being a tuple (vm_name, vm_release, vm_vendor) and osinfo being a tuple (os_name, os_version, os_arch). Values which cannot be determined are set to the defaults given as parameters (which all default to '').

16.14.3. Windows Platform

platform.win32_ver(release='', version='', csd='', ptype='')

Get additional version information from the Windows Registry and return a tuple (release, version, csd, ptype) referring to OS release, version number, CSD level (service pack) and OS type (multi/single processor).

As a hint: ptype is 'Uniprocessor Free' on single processor NT machines and 'Multiprocessor Free' on multi processor machines. The “Free” refers to the OS version being free of debugging code. It could also state “Checked” which means the OS version uses debugging code, i.e. code that checks arguments, ranges, etc.

Note

This function works best with Mark Hammond’s win32all package installed, but also on Python 2.3 and later (support for this was added in Python 2.6). It obviously only runs on Win32 compatible platforms.

16.14.3.1. Win95/98 specific

platform.popen(cmd, mode='r', bufsize=-1)

Portable popen() interface. Find a working popen implementation preferring win32pipe.popen(). On Windows NT, win32pipe.popen() should work; on Windows 9x it hangs due to bugs in the MS C library.

Obsolète depuis la version 3.3: This function is obsolete. Use the subprocess module. Check especially the Remplacer les fonctions plus anciennes par le module subprocess section.

16.14.4. Mac OS Platform

platform.mac_ver(release='', versioninfo=('', '', ''), machine='')

Get Mac OS version information and return it as tuple (release, versioninfo, machine) with versioninfo being a tuple (version, dev_stage, non_release_version).

Entries which cannot be determined are set to ''. All tuple entries are strings.

16.14.5. Unix Platforms

platform.dist(distname='', version='', id='', supported_dists=('SuSE', 'debian', 'redhat', 'mandrake', ...))

This is another name for linux_distribution().

Deprecated since version 3.5, will be removed in version 3.8: See alternative like the distro [https://pypi.org/project/distro] package.

platform.linux_distribution(distname='', version='', id='', supported_dists=('SuSE', 'debian', 'redhat', 'mandrake', ...), full_distribution_name=1)

Tries to determine the name of the Linux OS distribution name.

supported_dists may be given to define the set of Linux distributions to look for. It defaults to a list of currently supported Linux distributions identified by their release file name.

If full_distribution_name is true (default), the full distribution read from the OS is returned. Otherwise the short name taken from supported_dists is used.

Returns a tuple (distname,version,id) which defaults to the args given as parameters. id is the item in parentheses after the version number. It is usually the version codename.

Deprecated since version 3.5, will be removed in version 3.8: See alternative like the distro [https://pypi.org/project/distro] package.

platform.libc_ver(executable=sys.executable, lib='', version='', chunksize=16384)

Tries to determine the libc version against which the file executable (defaults to the Python interpreter) is linked. Returns a tuple of strings (lib, version) which default to the given parameters in case the lookup fails.

Note that this function has intimate knowledge of how different libc versions add symbols to the executable is probably only usable for executables compiled using gcc.

The file is read and scanned in chunks of chunksize bytes.

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16.15. errno — Symboles du système errno standard

Ce module met à disposition des symboles du système standard errno. La valeur de chaque symbole est la valeur entière correspondante. Les noms et les descriptions sont empruntés à linux/include/errno.h, qui devrait être assez exhaustif.

errno.errorcode

Dictionnaire associant la valeur errno au nom de chaîne dans le système sous-jacent. Par exemple, errno.errorcode[errno.EPERM] correspond à 'EPERM'.

Pour traduire un code d’erreur en message d’erreur, utilisez os.strerror().

De la liste suivante, les symboles qui ne sont pas utilisés dans la plateforme actuelle ne sont pas définis par le module. La liste spécifique des symboles définis est disponible comme errno.errorcode.keys(). Les symboles disponibles font partie de cette liste :

errno.EPERM

Opération interdite

errno.ENOENT

Fichier ou répertoire inexistant

errno.ESRCH

Processus inexistant

errno.EINTR

Appel système interrompu

Voir aussi

Cette erreur est associée à l’exception InterruptedError.

errno.EIO

Erreur d’entrée-sortie

errno.ENXIO

Dispositif ou adresse inexistant

errno.E2BIG

Liste d’arguments trop longue

errno.ENOEXEC

Erreur de format d’exécution

errno.EBADF

Mauvais descripteur de fichier

errno.ECHILD

Pas de processus fils

errno.EAGAIN

Ressource temporairement indisponible (réessayez)

errno.ENOMEM

Mémoire insuffisante

errno.EACCES

Autorisation refusée

errno.EFAULT

Mauvaise adresse

errno.ENOTBLK

Dispositif de bloc requis

errno.EBUSY

Dispositif ou ressource occupé

errno.EEXIST

Fichier déjà existant

errno.EXDEV

Lien inapproprié

errno.ENODEV

Dispositif inexistant

errno.ENOTDIR

Pas un répertoire

errno.EISDIR

Est un répertoire

errno.EINVAL

Argument invalide

errno.ENFILE

Plus de descripteur de fichier disponible

errno.EMFILE

Trop de fichiers ouverts

errno.ENOTTY

Opération de contrôle d’entrée-sortie invalide

errno.ETXTBSY

Fichier texte occupé

errno.EFBIG

Fichier trop grand

errno.ENOSPC

Plus de place sur le dispositif

errno.ESPIPE

Recherche invalide

errno.EROFS

Système de fichiers en lecture seule

errno.EMLINK

Trop de liens symboliques

errno.EPIPE

Tube brisé

errno.EDOM

Argument mathématique hors du domaine de définition de la fonction

errno.ERANGE

Résultat mathématique non représentable

errno.EDEADLK

Un interblocage se produirait sur cette ressource

errno.ENAMETOOLONG

Nom de fichier trop long

errno.ENOLCK

Plus de verrou de fichier disponible

errno.ENOSYS

Fonction non implémentée

errno.ENOTEMPTY

Dossier non vide

errno.ELOOP

Trop de liens symboliques trouvés

errno.EWOULDBLOCK

L’opération bloquerait

errno.ENOMSG

Pas de message du type voulu

errno.EIDRM

Identifiant supprimé

errno.ECHRNG

Le numéro de canal est hors des limites

errno.EL2NSYNC

Le niveau 2 n’est pas synchronisé

errno.EL3HLT

Niveau 3 stoppé

errno.EL3RST

Niveau 3 réinitialisé

errno.ELNRNG

Le numéro du lien est hors des limites

errno.EUNATCH

Le pilote de protocole n’est pas attaché

errno.ENOCSI

Pas de structure CSI disponible

errno.EL2HLT

Niveau 2 stoppé

errno.EBADE

Échange invalide

errno.EBADR

Descripteur de requête invalide

errno.EXFULL

Échange complet

errno.ENOANO

Pas de anode

errno.EBADRQC

Code de requête invalide

errno.EBADSLT

Slot invalide

errno.EDEADLOCK

Interblocage lors du verrouillage de fichier

errno.EBFONT

Mauvais format de fichier de police

errno.ENOSTR

Le périphérique n’est pas un flux

errno.ENODATA

Pas de donnée disponible

errno.ETIME

Délai maximal atteint

errno.ENOSR

Pas assez de ressources de type flux

errno.ENONET

Machine hors réseau

errno.ENOPKG

Paquet non installé

errno.EREMOTE

L’objet est distant

errno.ENOLINK

Lien coupé

errno.EADV

Erreur d’annonce

errno.ESRMNT

Erreur Srmount

errno.ECOMM

Erreur de communication lors de l’envoi

errno.EPROTO

Erreur de protocole

errno.EMULTIHOP

Transfert à sauts multiples essayé

errno.EDOTDOT

erreur spécifique RFS

errno.EBADMSG

Pas un message de données

errno.EOVERFLOW

Valeur trop grande pour être stockée dans ce type de donnée

errno.ENOTUNIQ

Nom non-unique dans le réseau

errno.EBADFD

Descripteur de fichier en mauvais état

errno.EREMCHG

Adresse distante changée

errno.ELIBACC

Accès impossible à une bibliothèque partagée nécessaire

errno.ELIBBAD

Accès à une bibliothèque partagée corrompue

errno.ELIBSCN

Section .lib de a.out corrompue

errno.ELIBMAX

Tentative de liaison entre trop de bibliothèques partagées

errno.ELIBEXEC

Impossible d’exécuter directement une bibliothèque partagée

errno.EILSEQ

Séquence de bytes illégale

errno.ERESTART

Appel système interrompu qui devrait être relancé

errno.ESTRPIPE

Erreur d’enchaînement de flux

errno.EUSERS

Trop d’utilisateurs

errno.ENOTSOCK

Opération d’interface de connexion alors que ce n’est pas une interface de connexion

errno.EDESTADDRREQ

Adresse de destination obligatoire

errno.EMSGSIZE

Message trop long

errno.EPROTOTYPE

Mauvais type de protocole pour ce connecteur

errno.ENOPROTOOPT

Protocole pas disponible

errno.EPROTONOSUPPORT

Protocole non géré

errno.ESOCKTNOSUPPORT

Type de connecteur non géré

errno.EOPNOTSUPP

Opération non gérée par cette fin de lien

errno.EPFNOSUPPORT

Famille de protocole non gérée

errno.EAFNOSUPPORT

Famille d’adresses non gérée par ce protocole

errno.EADDRINUSE

Adresse déjà utilisée

errno.EADDRNOTAVAIL

Impossible d’assigner l’adresse demandée

errno.ENETDOWN

Le réseau est désactivé

errno.ENETUNREACH

Réseau inaccessible

errno.ENETRESET

Connexion annulée par le réseau

errno.ECONNABORTED

Connexion abandonnée

errno.ECONNRESET

Connexion réinitialisée

errno.ENOBUFS

Plus d’espace tampon disponible

errno.EISCONN

L’interface de connexion est déjà connectée

errno.ENOTCONN

L’interface de connexion n’est pas connectée

errno.ESHUTDOWN

Impossible d’envoyer après l’arrêt du point final du transport

errno.ETOOMANYREFS

Trop de descripteurs : impossible d’effectuer la liaison

errno.ETIMEDOUT

Délai maximal de connexion écoulé

errno.ECONNREFUSED

Connexion refusée

errno.EHOSTDOWN

Hôte éteint

errno.EHOSTUNREACH

Pas de route vers l’hôte

errno.EALREADY

Connexion déjà en cours

errno.EINPROGRESS

Opération en cours

errno.ESTALE

Descripteur de fichier NFS corrompu

errno.EUCLEAN

La structure a besoin d’être nettoyée

errno.ENOTNAM

N’est pas un fichier nommé du type XENIX

errno.ENAVAIL

Pas de sémaphore XENIX disponible

errno.EISNAM

Est un fichier nommé

errno.EREMOTEIO

Erreur d’entrées-sorties distante

errno.EDQUOT

Quota dépassé

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16.16. ctypes — Bibliothèque Python d’appels à des fonctions externes

ctypes est une bibliothèque d’appel à des fonctions externes en python. Elle fournit des types de données compatibles avec le langage C et permet d’appeler des fonctions depuis des DLL ou des bibliothèques partagées, rendant ainsi possible l’interfaçage de ces bibliothèques avec du pur code Python.

16.16.1. Didacticiel de ctypes

Remarque : Les exemples de code de ce didacticiel utilisent doctest pour s’assurer de leur propre bon fonctionnement. Vu que certains de ces exemples ont un comportement différent en Linux, Windows ou Mac OS X, ils contiennent des directives doctest dans les commentaires.

Remarque : Le type c_int du module apparaît dans certains de ces exemples. Sur les plates-formes où sizeof(long) == sizeof(int), ce type est un alias de c_long. Ne soyez donc pas surpris si c_long s’affiche là où vous vous attendiez à c_int — il s’agit bien du même type.

16.16.1.1. Chargement des DLL

ctypes fournit l’objet cdll pour charger des bibliothèques à liens dynamiques (et les objets windll et oledll en Windows).

Une bibliothèque se charge en y accédant comme un attribut de ces objets. cdll charge les bibliothèques qui exportent des fonctions utilisant la convention d’appel standard cdecl, alors que les bibliothèques qui se chargent avec windll utilisent la convention d’appel stdcall. oledll utilise elle aussi la convention stdcall et suppose que les fonctions renvoient un code d’erreur HRESULT de Windows. Ce code d’erreur est utilisé pour lever automatiquement une OSError quand l’appel de la fonction échoue.

Modifié dans la version 3.3: En Windows, les erreurs levaient auparavant une WindowsError, qui est maintenant un alias de OSError.

Voici quelques exemples Windows. msvcrt est la bibliothèque standard C de Microsoft qui contient la plupart des fonctions standards C. Elle suit la convention d’appel cdecl :

>>> from ctypes import *
>>> print(windll.kernel32)
<WinDLL 'kernel32', handle ... at ...>
>>> print(cdll.msvcrt)
<CDLL 'msvcrt', handle ... at ...>
>>> libc = cdll.msvcrt
>>>

Windows ajoute le suffixe habituel .dll automatiquement.

Note

Accéder à la bibliothèque standard C par cdll.msvcrt utilise une version obsolète de la bibliothèque qui peut avoir des problèmes de compatibilité avec celle que Python utilise. Si possible, mieux vaut utiliser la fonctionnalité native de Python, ou bien importer et utiliser le module msvcrt.

Pour charger une bibliothèque en Linux, il faut passer le nom du fichier avec son extension. Il est donc impossible de charger une bibliothèque en accédant à un attribut. Il faut utiliser la méthode LoadLibrary() des chargeurs de DLL, ou bien charger la bibliothèque en créant une instance de CDLL en appelant son constructeur :

>>> cdll.LoadLibrary("libc.so.6")
<CDLL 'libc.so.6', handle ... at ...>
>>> libc = CDLL("libc.so.6")
>>> libc
<CDLL 'libc.so.6', handle ... at ...>
>>>

16.16.1.2. Accès aux fonctions des DLL chargées

Les fonctions sont alors des attributs des objets DLL :

>>> from ctypes import *
>>> libc.printf
<_FuncPtr object at 0x...>
>>> print(windll.kernel32.GetModuleHandleA)
<_FuncPtr object at 0x...>
>>> print(windll.kernel32.MyOwnFunction)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "ctypes.py", line 239, in __getattr__
    func = _StdcallFuncPtr(name, self)
AttributeError: function 'MyOwnFunction' not found
>>>

Les DLL des systèmes win32 comme kernel32 et user32 exportent souvent une version ANSI et une version UNICODE d’une fonction. La version UNICODE est exportée avec un W à la fin, et la version ANSI avec un A. La fonction win32 GetModuleHandle, qui renvoie un gestionnaire de module à partir de son nom, a le prototype C suivant (c’est une macro qui décide d’exporter l’une ou l’autre à travers GetModuleHandle, selon qu’UNICODE est définie ou non) :

/* ANSI version */
HMODULE GetModuleHandleA(LPCSTR lpModuleName);
/* UNICODE version */
HMODULE GetModuleHandleW(LPCWSTR lpModuleName);

windll n’en choisit pas une par magie, il faut accéder à la bonne en écrivant explicitement GetModuleHandleA ou GetModuleHandleW et en les appelant ensuite avec des objets octets ou avec des chaînes de caractères, respectivement.

Les DLL exportent parfois des fonctions dont les noms ne sont pas des identifiants Python valides, comme "??2@YAPAXI@Z". Dans ce cas, il faut utiliser getattr() pour accéder à la fonction :

>>> getattr(cdll.msvcrt, "??2@YAPAXI@Z")
<_FuncPtr object at 0x...>
>>>

Sous Windows, certaines DLL exportent des fonctions à travers un indice plutôt qu’à travers un nom. On accède à une fonction en indiçant l’objet DLL avec son index :

>>> cdll.kernel32[1]
<_FuncPtr object at 0x...>
>>> cdll.kernel32[0]
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "ctypes.py", line 310, in __getitem__
    func = _StdcallFuncPtr(name, self)
AttributeError: function ordinal 0 not found
>>>

16.16.1.3. Appel de fonctions

Ces fonctions s’appellent comme n’importe quel appelable Python. Cet exemple utilise la fonction time(), qui renvoie le temps en secondes du système depuis l”epoch Unix, et la fonction GetModuleHandleA(), qui renvoie un gestionnaire de module win32.

This example calls both functions with a NULL pointer (None should be used as the NULL pointer):

>>> print(libc.time(None))
1150640792
>>> print(hex(windll.kernel32.GetModuleHandleA(None)))
0x1d000000
>>>

Note

ctypes may raise a ValueError after calling the function, if it detects that an invalid number of arguments were passed. This behavior should not be relied upon. It is deprecated in 3.6.2, and will be removed in 3.7.

Une ValueError est levée quand on appelle une fonction stdcall avec la convention d’appel cdecl et vice-versa :

>>> cdll.kernel32.GetModuleHandleA(None)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
ValueError: Procedure probably called with not enough arguments (4 bytes missing)
>>>

>>> windll.msvcrt.printf(b"spam")
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
ValueError: Procedure probably called with too many arguments (4 bytes in excess)
>>>

Pour déterminer la convention d’appel, il faut consulter l’en-tête C ou la documentation de la fonction à appeler.

En Windows, ctypes tire profit de la gestion structurée des exceptions (structured exception handling) win32 pour empêcher les plantages dus à des interruptions, afin de préserver la protection globale (general protection faults) du système, lorsque des fonctions sont appelées avec un nombre incorrect d’arguments :

>>> windll.kernel32.GetModuleHandleA(32)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
OSError: exception: access violation reading 0x00000020
>>>

Cependant, il y a suffisamment de façons de faire planter Python avec ctypes, donc il faut être prudent dans tous les cas. Le module faulthandler est pratique pour déboguer les plantages (p. ex. dus à des erreurs de segmentation produites par des appels erronés à la bibliothèque C).

None, les entiers, les objets octets et les chaînes de caractères (Unicode) sont les seuls types natifs de Python qui peuvent être directement passés en paramètres de ces appels de fonctions. None est passé comme le pointeur C NULL, les objets octets et les chaînes de caractères sont passés comme un pointeur sur le bloc mémoire qui contient la donnée (char * ou wchar_t *). Les entiers Python sont passés comme le type C int par défaut de la plate-forme, un masque étant appliqué pour qu’ils tiennent dans le type C.

Avant de poursuivre sur l’appel de fonctions avec d’autres types de paramètres, apprenons-en un peu plus sur les types de données de ctypes.

16.16.1.4. Types de données fondamentaux

ctypes définit plusieurs types de donnée de base compatibles avec le C :

Types de ctypes

Type C

Type Python

c_bool

_Bool

bool (1)

c_char

char

objet octet (bytes) de 1 caractère

c_wchar

wchar_t

chaîne de caractères (string) de longueur 1

c_byte

char

int

c_ubyte

unsigned char

int

c_short

short

int

c_ushort

unsigned short

int

c_int

int

int

c_uint

unsigned int

int

c_long

long

int

c_ulong

unsigned long

int

c_longlong

__int64 ou long long

int

c_ulonglong

unsigned __int64 ou unsigned long long

int

c_size_t

size_t

int

c_ssize_t

ssize_t ou Py_ssize_t

int

c_float

float

float

c_double

double

float

c_longdouble

long double

float

c_char_p

char * (terminé par NUL)

objet octet (bytes) ou None

c_wchar_p

wchar_t * (terminé par NUL)

chaîne de caractères (string) ou None

c_void_p

void *

int ou None

Le constructeur accepte n’importe quel objet convertible en booléen.

Il est possible de créer chacun de ces types en les appelant avec une valeur d’initialisation du bon type et avec une valeur cohérente :

>>> c_int()
c_long(0)
>>> c_wchar_p("Hello, World")
c_wchar_p(140018365411392)
>>> c_ushort(-3)
c_ushort(65533)
>>>

Ces types étant des muables, leur valeur peut aussi être modifiée après coup :

>>> i = c_int(42)
>>> print(i)
c_long(42)
>>> print(i.value)
42
>>> i.value = -99
>>> print(i.value)
-99
>>>

Affecter une nouvelle valeur à une instance de type pointeur — c_char_p, c_wchar_p et c_void_p — change la zone mémoire sur laquelle elle pointe, et non le contenu de ce bloc mémoire (c’est logique parce que les objets octets sont immuables en Python) :

>>> s = "Hello, World"
>>> c_s = c_wchar_p(s)
>>> print(c_s)
c_wchar_p(139966785747344)
>>> print(c_s.value)
Hello World
>>> c_s.value = "Hi, there"
>>> print(c_s)              # the memory location has changed
c_wchar_p(139966783348904)
>>> print(c_s.value)
Hi, there
>>> print(s)                # first object is unchanged
Hello, World
>>>

Cependant, prenez garde à ne pas en passer à des fonctions qui prennent en paramètre des pointeurs sur de la mémoire modifiable. S’il vous faut de la mémoire modifiable, ctypes fournit la fonction create_string_buffer() qui en crée de plusieurs façons. L’attribut raw permet d’accéder à (ou de modifier) un bloc mémoire ; l’attribut value permet d’y accéder comme à une chaîne de caractères terminée par NUL :

>>> from ctypes import *
>>> p = create_string_buffer(3)            # create a 3 byte buffer, initialized to NUL bytes
>>> print(sizeof(p), repr(p.raw))
3 b'\x00\x00\x00'
>>> p = create_string_buffer(b"Hello")     # create a buffer containing a NUL terminated string
>>> print(sizeof(p), repr(p.raw))
6 b'Hello\x00'
>>> print(repr(p.value))
b'Hello'
>>> p = create_string_buffer(b"Hello", 10) # create a 10 byte buffer
>>> print(sizeof(p), repr(p.raw))
10 b'Hello\x00\x00\x00\x00\x00'
>>> p.value = b"Hi"
>>> print(sizeof(p), repr(p.raw))
10 b'Hi\x00lo\x00\x00\x00\x00\x00'
>>>

La fonction create_string_buffer() remplace les fonctions c_buffer() (qui en reste un alias) et c_string() des versions antérieures de ctypes. La fonction create_unicode_buffer() crée un bloc mémoire modifiable contenant des caractères Unicode du type C wchar_t.

16.16.1.5. Appel de fonctions, suite

printf utilise la vraie sortie standard, et non sys.stdout ; les exemples suivants ne fonctionnent donc que dans une invite de commande et non depuis IDLE or PythonWin :

>>> printf = libc.printf
>>> printf(b"Hello, %s\n", b"World!")
Hello, World!
14
>>> printf(b"Hello, %S\n", "World!")
Hello, World!
14
>>> printf(b"%d bottles of beer\n", 42)
42 bottles of beer
19
>>> printf(b"%f bottles of beer\n", 42.5)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
ArgumentError: argument 2: exceptions.TypeError: Don't know how to convert parameter 2
>>>

Comme mentionné plus haut, tous les types Python (les entiers, les chaînes de caractères et les objets octet exceptés) doivent être encapsulés dans leur type ctypes correspondant pour pouvoir être convertis dans le type C requis :

>>> printf(b"An int %d, a double %f\n", 1234, c_double(3.14))
An int 1234, a double 3.140000
31
>>>

16.16.1.6. Appel de fonctions avec des types de données personnalisés

Il est possible de personnaliser la conversion des arguments effectuée par ctypes pour permettre de passer en argument des instances de vos propres classes. ctypes recherche un attribut _as_parameter_ et le prend comme argument à la fonction. Bien entendu, cet attribut doit être un entier, une chaîne de caractères ou des octets :

>>> class Bottles:
...     def __init__(self, number):
...         self._as_parameter_ = number
...
>>> bottles = Bottles(42)
>>> printf(b"%d bottles of beer\n", bottles)
42 bottles of beer
19
>>>

Si vous ne souhaitez pas stocker les données de l’instance dans la variable _as_parameter_ de l’instance, vous pouvez toujours définir une propriété qui rend cet attribut disponible sur demande.

16.16.1.7. Définition du type des arguments nécessaires (prototypes de fonction)

Il est possible de définir le type des arguments demandés par une fonction exportée depuis une DLL en définissant son attribut argtypes.

argtypes doit être une séquence de types de données C (la fonction printf n’est probablement pas le meilleur exemple pour l’illustrer, car elle accepte un nombre variable d’arguments de types eux aussi variables, selon la chaîne de formatage ; cela dit, elle se révèle pratique pour tester cette fonctionnalité) :

>>> printf.argtypes = [c_char_p, c_char_p, c_int, c_double]
>>> printf(b"String '%s', Int %d, Double %f\n", b"Hi", 10, 2.2)
String 'Hi', Int 10, Double 2.200000
37
>>>

Définir un format empêche de passer des arguments de type incompatible (comme le fait le prototype d’une fonction C) et tente de convertir les arguments en des types valides :

>>> printf(b"%d %d %d", 1, 2, 3)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
ArgumentError: argument 2: exceptions.TypeError: wrong type
>>> printf(b"%s %d %f\n", b"X", 2, 3)
X 2 3.000000
13
>>>

Pour appeler une fonction avec votre propre classe définie dans la séquence argtypes, il est nécessaire d’implémenter une méthode de classe from_param(). La méthode de classe from_param() récupère l’objet Python passé à la fonction et doit faire une vérification de type ou tout ce qui est nécessaire pour s’assurer que l’objet est valide, puis renvoie l’objet lui-même, son attribut _as_parameter_, ou tout ce que vous voulez passer comme argument fonction C dans ce cas. Encore une fois, il convient que le résultat soit un entier, une chaîne, des octets, une instance ctypes ou un objet avec un attribut _as_parameter_.

16.16.1.8. Types de sortie

Le module suppose que toutes les fonctions renvoient par défaut un int C. Pour préciser un autre type de sortie, il faut définir l’attribut restype de l’objet encapsulant la fonction.

Voici un exemple plus poussé. Celui-ci utilise la fonction strchr, qui prend en paramètres un pointeur vers une chaîne et un caractère. Elle renvoie un pointeur sur une chaîne de caractères :

>>> strchr = libc.strchr
>>> strchr(b"abcdef", ord("d"))
8059983
>>> strchr.restype = c_char_p    # c_char_p is a pointer to a string
>>> strchr(b"abcdef", ord("d"))
b'def'
>>> print(strchr(b"abcdef", ord("x")))
None
>>>

Pour économiser l’appel ord("x"), il est possible de définir l’attribut argtypes ; le second argument, un objet octet à un seul caractère, sera automatiquement converti en un caractère C :

>>> strchr.restype = c_char_p
>>> strchr.argtypes = [c_char_p, c_char]
>>> strchr(b"abcdef", b"d")
'def'
>>> strchr(b"abcdef", b"def")
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
ArgumentError: argument 2: exceptions.TypeError: one character string expected
>>> print(strchr(b"abcdef", b"x"))
None
>>> strchr(b"abcdef", b"d")
'def'
>>>

Si la fonction à interfacer renvoie un entier, l’attribut restype peut aussi être un appelable (une fonction ou une classe par exemple). Dans ce cas, l’appelable sera appelé avec l’entier renvoyé par la fonction et le résultat de cet appel sera le résultat final de l’appel à la fonction. C’est pratique pour vérifier les codes d’erreurs des valeurs de retour et lever automatiquement des exceptions :

>>> GetModuleHandle = windll.kernel32.GetModuleHandleA
>>> def ValidHandle(value):
...     if value == 0:
...         raise WinError()
...     return value
...
>>>
>>> GetModuleHandle.restype = ValidHandle
>>> GetModuleHandle(None)
486539264
>>> GetModuleHandle("something silly")
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "<stdin>", line 3, in ValidHandle
OSError: [Errno 126] The specified module could not be found.
>>>

WinError appelle l’API Windows FormatMessage() pour obtenir une représentation de la chaîne de caractères qui correspond au code d’erreur, et renvoie une exception. WinError prend en paramètre — optionnel — le code d’erreur. Si celui-ci n’est pas passé, elle appelle GetLastError() pour le récupérer.

Notez cependant que l’attribut errcheck permet de vérifier bien plus efficacement les erreurs ; référez-vous au manuel de référence pour plus de précisions.

16.16.1.9. Passage de pointeurs (passage de paramètres par référence)

Il arrive qu’une fonction C du code à interfacer requière un pointeur vers un certain type de donnée en paramètre, typiquement pour écrire à l’endroit correspondant ou si la donnée est trop grande pour pouvoir être passée par valeur. Ce mécanisme est appelé passage de paramètres par référence.

ctypes contient la fonction byref() qui permet de passer des paramètres par référence. La fonction pointer() a la même utilité, mais fait plus de travail car pointer() construit un véritable objet pointeur. Ainsi, si vous n’avez pas besoin de cet objet dans votre code Python, utiliser byref() est plus performant :

>>> i = c_int()
>>> f = c_float()
>>> s = create_string_buffer(b'\000' * 32)
>>> print(i.value, f.value, repr(s.value))
0 0.0 b''
>>> libc.sscanf(b"1 3.14 Hello", b"%d %f %s",
...             byref(i), byref(f), s)
3
>>> print(i.value, f.value, repr(s.value))
1 3.1400001049 b'Hello'
>>>

16.16.1.10. Structures et unions

Les structures et les unions doivent hériter des classes de base Structure et Union définies dans le module ctypes. Chaque sous-classe doit définir un attribut _fields_. _fields_ doit être une liste de paires, contenant un nom de champ et un type de champ.

Le type de champ doit être un type ctypes comme c_int ou un type ctypes dérivé : structure, union, tableau ou pointeur.

Voici un exemple simple : une structure POINT qui contient deux entiers x et y et qui montre également comment instancier une structure avec le constructeur :

>>> from ctypes import *
>>> class POINT(Structure):
...     _fields_ = [("x", c_int),
...                 ("y", c_int)]
...
>>> point = POINT(10, 20)
>>> print(point.x, point.y)
10 20
>>> point = POINT(y=5)
>>> print(point.x, point.y)
0 5
>>> POINT(1, 2, 3)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
ValueError: too many initializers
>>>

Il est bien entendu possible de créer des structures plus complexes. Une structure peut elle-même contenir d’autres structures en prenant une structure comme type de champ.

Voici une structure RECT qui contient deux POINTs upperleft et lowerright :

>>> class RECT(Structure):
...     _fields_ = [("upperleft", POINT),
...                 ("lowerright", POINT)]
...
>>> rc = RECT(point)
>>> print(rc.upperleft.x, rc.upperleft.y)
0 5
>>> print(rc.lowerright.x, rc.lowerright.y)
0 0
>>>

Une structure encapsulée peut être instanciée par un constructeur de plusieurs façons :

>>> r = RECT(POINT(1, 2), POINT(3, 4))
>>> r = RECT((1, 2), (3, 4))

Il est possible de récupérer les descripteurs des champs depuis la classe. Ils sont importants pour déboguer car ils contiennent des informations utiles :

>>> print(POINT.x)
<Field type=c_long, ofs=0, size=4>
>>> print(POINT.y)
<Field type=c_long, ofs=4, size=4>
>>>

Avertissement

ctypes ne prend pas en charge le passage par valeur des unions ou des structures avec des champs de bits. Bien que cela puisse fonctionner sur des architectures 32 bits avec un jeu d’instructions x86, ce n’est pas garanti par la bibliothèque en général. Les unions et les structures avec des champs de bits doivent toujours être passées par pointeur.

16.16.1.11. Alignement et boutisme des structures et des unions

By default, Structure and Union fields are aligned in the same way the C compiler does it. It is possible to override this behavior be specifying a _pack_ class attribute in the subclass definition. This must be set to a positive integer and specifies the maximum alignment for the fields. This is what #pragma pack(n) also does in MSVC.

ctypes suit le boutisme natif pour les Structure et les Union. Pour construire des structures avec un boutisme différent, utilisez les classes de base BigEndianStructure, LittleEndianStructure, BigEndianUnion ou LittleEndianUnion. Ces classes ne peuvent pas avoir de champ pointeur.

16.16.1.12. Champs de bits dans les structures et les unions

Il est possible de créer des structures et des unions contenant des champs de bits. Seuls les entiers peuvent être des champs de bits, le nombre de bits est défini dans le troisième champ du n-uplet _fields_ :

>>> class Int(Structure):
...     _fields_ = [("first_16", c_int, 16),
...                 ("second_16", c_int, 16)]
...
>>> print(Int.first_16)
<Field type=c_long, ofs=0:0, bits=16>
>>> print(Int.second_16)
<Field type=c_long, ofs=0:16, bits=16>
>>>

16.16.1.13. Tableaux

Les tableaux sont des séquences qui contiennent un nombre fixe d’instances du même type.

La meilleure façon de créer des tableaux consiste à multiplier le type de donnée par un entier positif :

TenPointsArrayType = POINT * 10

Voici un exemple — un peu artificiel — d’une structure contenant, entre autres, 4 POINTs :

>>> from ctypes import *
>>> class POINT(Structure):
...     _fields_ = ("x", c_int), ("y", c_int)
...
>>> class MyStruct(Structure):
...     _fields_ = [("a", c_int),
...                 ("b", c_float),
...                 ("point_array", POINT * 4)]
>>>
>>> print(len(MyStruct().point_array))
4
>>>

Comme d’habitude, on crée les instances en appelant la classe :

arr = TenPointsArrayType()
for pt in arr:
    print(pt.x, pt.y)

Le code précédent affiche une suite de 0 0 car le contenu du tableau est initialisé avec des zéros.

Des valeurs d’initialisation du bon type peuvent être passées :

>>> from ctypes import *
>>> TenIntegers = c_int * 10
>>> ii = TenIntegers(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)
>>> print(ii)
<c_long_Array_10 object at 0x...>
>>> for i in ii: print(i, end=" ")
...
1 2 3 4 5 6 7 8 9 10
>>>

16.16.1.14. Pointeurs

On crée une instance de pointeur en appelant la fonction pointer() sur un type ctypes :

>>> from ctypes import *
>>> i = c_int(42)
>>> pi = pointer(i)
>>>

Les instances de pointeurs ont un attribut contents qui renvoie l’objet pointé (l’objet i ci-dessus) :

>>> pi.contents
c_long(42)
>>>

Attention, ctypes ne fait pas de ROI (retour de l’objet initial). Il crée un nouvel objet à chaque fois qu’on accède à un attribut :

>>> pi.contents is i
False
>>> pi.contents is pi.contents
False
>>>

Affecter une autre instance de c_int à l’attribut contents du pointeur fait pointer le pointeur vers l’adresse mémoire de cette nouvelle instance :

>>> i = c_int(99)
>>> pi.contents = i
>>> pi.contents
c_long(99)
>>>

Il est possible d’indexer les pointeurs par des entiers :

>>> pi[0]
99
>>>

Affecter à travers un indice change la valeur pointée :

>>> print(i)
c_long(99)
>>> pi[0] = 22
>>> print(i)
c_long(22)
>>>

Si vous êtes sûr de vous, vous pouvez utiliser d’autres valeurs que 0, comme en C : il est ainsi possible de modifier une zone mémoire de votre choix. De manière générale cette fonctionnalité ne s’utilise que sur un pointeur renvoyé par une fonction C, pointeur que vous savez pointer vers un tableau et non sur un seul élément.

Sous le capot, la fonction pointer() fait plus que simplement créer une instance de pointeur ; elle doit d’abord créer un type « pointeur sur… ». Cela s’effectue avec la fonction POINTER(), qui prend en paramètre n’importe quel type ctypes et renvoie un nouveau type :

>>> PI = POINTER(c_int)
>>> PI
<class 'ctypes.LP_c_long'>
>>> PI(42)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: expected c_long instead of int
>>> PI(c_int(42))
<ctypes.LP_c_long object at 0x...>
>>>

Appeler le pointeur sur type sans arguments crée un pointeur NULL. Les pointeurs NULL s’évaluent à False :

>>> null_ptr = POINTER(c_int)()
>>> print(bool(null_ptr))
False
>>>

ctypes vérifie que le pointeur n’est pas NULL quand il en déréférence un (mais déréférencer des pointeurs non NULL invalides fait planter Python) :

>>> null_ptr[0]
Traceback (most recent call last):
    ....
ValueError: NULL pointer access
>>>

>>> null_ptr[0] = 1234
Traceback (most recent call last):
    ....
ValueError: NULL pointer access
>>>

16.16.1.15. Conversions de type

En général, ctypes respecte un typage fort. Cela signifie que si un POINTER(c_int) est présent dans la liste des argtypes d’une fonction ou est le type d’un attribut membre dans une définition de structure, seules des instances de ce type seront valides. Cette règle comporte quelques exceptions pour lesquelles ctypes accepte d’autres objets. Par exemple il est possible de passer des instances de tableau à place de pointeurs, s’ils sont compatibles. Dans le cas de POINTER(c_int), ctypes accepte des tableaux de c_int :

>>> class Bar(Structure):
...     _fields_ = [("count", c_int), ("values", POINTER(c_int))]
...
>>> bar = Bar()
>>> bar.values = (c_int * 3)(1, 2, 3)
>>> bar.count = 3
>>> for i in range(bar.count):
...     print(bar.values[i])
...
1
2
3
>>>

De plus, si un paramètre de fonction est déclaré explicitement de type pointeur (comme POINTER(c_int)) dans les argtypes, il est aussi possible de passer un objet du type pointé — ici, c_int — à la fonction. ctypes appelle alors automatiquement la fonction de conversion byref().

Pour mettre un champ de type POINTER à NULL, il faut lui affecter None :

>>> bar.values = None
>>>

Parfois il faut gérer des incompatibilités entre les types. En C, il est possible de convertir un type en un autre. ctypes fournit la fonction cast() qui permet la même chose. La structure Bar ci-dessus accepte des pointeurs POINTER(c_int) ou des tableaux de c_int comme valeur pour le champ values, mais pas des instances d’autres types :

>>> bar.values = (c_byte * 4)()
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: incompatible types, c_byte_Array_4 instance instead of LP_c_long instance
>>>

C’est là que la fonction cast() intervient.

La fonction cast() permet de convertir une instance de ctypes en un pointeur vers un type de données ctypes différent. cast() prend deux paramètres : un objet ctypes qui est, ou qui peut être converti en, un certain pointeur et un type pointeur de ctypes. Elle renvoie une instance du second argument, qui pointe sur le même bloc mémoire que le premier argument :

>>> a = (c_byte * 4)()
>>> cast(a, POINTER(c_int))
<ctypes.LP_c_long object at ...>
>>>

Ainsi, la fonction cast() permet de remplir le champ values de la structure Bar :

>>> bar = Bar()
>>> bar.values = cast((c_byte * 4)(), POINTER(c_int))
>>> print(bar.values[0])
0
>>>

16.16.1.16. Types incomplets

Un type incomplet est une structure, une union ou un tableau dont les membres ne sont pas encore définis. C’est l’équivalent d’une déclaration avancée en C, où la définition est fournie plus tard :

struct cell; /* forward declaration */

struct cell {
    char *name;
    struct cell *next;
};

Une traduction naïve, mais invalide, en code ctypes ressemblerait à ça :

>>> class cell(Structure):
...     _fields_ = [("name", c_char_p),
...                 ("next", POINTER(cell))]
...
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "<stdin>", line 2, in cell
NameError: name 'cell' is not defined
>>>

Cela ne fonctionne pas parce que la nouvelle class cell n’est pas accessible dans la définition de la classe elle-même. Dans le module ctypes, on définit la classe cell et on définira les _fields_ plus tard, après avoir défini la classe :

>>> from ctypes import *
>>> class cell(Structure):
...     pass
...
>>> cell._fields_ = [("name", c_char_p),
...                  ("next", POINTER(cell))]
>>>

Lets try it. We create two instances of cell, and let them point to each other, and finally follow the pointer chain a few times:

>>> c1 = cell()
>>> c1.name = "foo"
>>> c2 = cell()
>>> c2.name = "bar"
>>> c1.next = pointer(c2)
>>> c2.next = pointer(c1)
>>> p = c1
>>> for i in range(8):
...     print(p.name, end=" ")
...     p = p.next[0]
...
foo bar foo bar foo bar foo bar
>>>

16.16.1.17. Fonctions de rappel

ctypes permet de créer des pointeurs de fonctions appelables par des appelables Python. On les appelle parfois fonctions de rappel.

Tout d’abord, il faut créer une classe pour la fonction de rappel. La classe connaît la convention d’appel, le type de retour ainsi que le nombre et le type de paramètres que la fonction accepte.

La fabrique CFUNCTYPE() crée un type pour les fonctions de rappel qui suivent la convention d’appel cdecl. En Windows, c’est la fabrique WINFUNCTYPE() qui crée un type pour les fonctions de rappel qui suivent la convention d’appel stdcall.

Le premier paramètre de ces deux fonctions est le type de retour, et les suivants sont les types des arguments qu’attend la fonction de rappel.

Intéressons-nous à un exemple tiré de la bibliothèque standard C : la fonction qsort(). Celle-ci permet de classer des éléments par l’emploi d’une fonction de rappel. Nous allons utiliser qsort() pour ordonner un tableau d’entiers :

>>> IntArray5 = c_int * 5
>>> ia = IntArray5(5, 1, 7, 33, 99)
>>> qsort = libc.qsort
>>> qsort.restype = None
>>>

qsort() doit être appelée avec un pointeur vers la donnée à ordonner, le nombre d’éléments dans la donnée, la taille d’un élément et un pointeur vers le comparateur, c-à-d la fonction de rappel. Cette fonction sera invoquée avec deux pointeurs sur deux éléments et doit renvoyer un entier négatif si le premier élément est plus petit que le second, zéro s’ils sont égaux et un entier positif sinon.

Ainsi notre fonction de rappel reçoit des pointeurs vers des entiers et doit renvoyer un entier. Créons d’abord le type pour la fonction de rappel :

>>> CMPFUNC = CFUNCTYPE(c_int, POINTER(c_int), POINTER(c_int))
>>>

Pour commencer, voici une fonction de rappel simple qui affiche les valeurs qu’on lui passe :

>>> def py_cmp_func(a, b):
...     print("py_cmp_func", a[0], b[0])
...     return 0
...
>>> cmp_func = CMPFUNC(py_cmp_func)
>>>

Résultat :

>>> qsort(ia, len(ia), sizeof(c_int), cmp_func)
py_cmp_func 5 1
py_cmp_func 33 99
py_cmp_func 7 33
py_cmp_func 5 7
py_cmp_func 1 7
>>>

À présent, comparons pour de vrai les deux entiers et renvoyons un résultat utile :

>>> def py_cmp_func(a, b):
...     print("py_cmp_func", a[0], b[0])
...     return a[0] - b[0]
...
>>>
>>> qsort(ia, len(ia), sizeof(c_int), CMPFUNC(py_cmp_func))
py_cmp_func 5 1
py_cmp_func 33 99
py_cmp_func 7 33
py_cmp_func 1 7
py_cmp_func 5 7
>>>

Et comme il est facile de le voir, notre tableau est désormais classé :

>>> for i in ia: print(i, end=" ")
...
1 5 7 33 99
>>>

The function factories can be used as decorator factories, so we may as well write:

>>> @CFUNCTYPE(c_int, POINTER(c_int), POINTER(c_int))
... def py_cmp_func(a, b):
...     print("py_cmp_func", a[0], b[0])
...     return a[0] - b[0]
...
>>> qsort(ia, len(ia), sizeof(c_int), py_cmp_func)
py_cmp_func 5 1
py_cmp_func 33 99
py_cmp_func 7 33
py_cmp_func 1 7
py_cmp_func 5 7
>>>

Note

Prenez garde à bien conserver une référence à un objet CFUNCTYPE() tant que celui-ci est utilisé par le code C. ctypes ne le fait pas tout seul et, si vous ne le faites pas, le ramasse-miette pourrait les libérer, ce qui fera planter votre programme quand un appel sera fait.

Notez aussi que si la fonction de rappel est appelée dans un fil d’exécution créé hors de Python (p. ex. par du code externe qui appelle la fonction de rappel), ctypes crée un nouveau fil Python « creux » à chaque fois. Ce comportement est acceptable pour la plupart des cas d’utilisation, mais cela implique que les valeurs stockées avec threading.local ne seront pas persistantes d’un appel à l’autre, même si les appels proviennent du même fil d’exécution C.

16.16.1.18. Accès aux variables exportées depuis une DLL

Certaines bibliothèques ne se contentent pas d’exporter des fonctions, elles exportent aussi des variables. Par exemple, la bibliothèque Python exporte Py_OptimizeFlag, un entier valant 0, 1, ou 2 selon que l’option -O ou -OO soit donnée au démarrage.

ctypes peut accéder à ce type de valeurs avec les méthodes de classe in_dll() du type considéré. pythonapi est un symbole prédéfini qui donne accès à l’API C Python :

>>> opt_flag = c_int.in_dll(pythonapi, "Py_OptimizeFlag")
>>> print(opt_flag)
c_long(0)
>>>

Si l’interpréteur est lancé avec -O, l’exemple affiche c_long(1) et c_long(2) avec -OO.

Le pointeur PyImport_FrozenModules exposé par Python est un autre exemple complet de l’utilisation de pointeurs.

Citons la documentation :

This pointer is initialized to point to an array of struct _frozen records, terminated by one whose members are all NULL or zero. When a frozen module is imported, it is searched in this table. Third-party code could play tricks with this to provide a dynamically created collection of frozen modules.

Donc manipuler ce pointeur peut même se révéler utile. Pour limiter la taille de l’exemple, nous nous bornons à montrer comment lire ce tableau avec ctypes :

>>> from ctypes import *
>>>
>>> class struct_frozen(Structure):
...     _fields_ = [("name", c_char_p),
...                 ("code", POINTER(c_ubyte)),
...                 ("size", c_int)]
...
>>>

Le type de donnée struct _frozen ayant été défini, nous pouvons récupérer le pointeur vers le tableau :

>>> FrozenTable = POINTER(struct_frozen)
>>> table = FrozenTable.in_dll(pythonapi, "PyImport_FrozenModules")
>>>

Since table is a pointer to the array of struct_frozen records, we can iterate over it, but we just have to make sure that our loop terminates, because pointers have no size. Sooner or later it would probably crash with an access violation or whatever, so it’s better to break out of the loop when we hit the NULL entry:

>>> for item in table:
...     if item.name is None:
...         break
...     print(item.name.decode("ascii"), item.size)
...
_frozen_importlib 31764
_frozen_importlib_external 41499
__hello__ 161
__phello__ -161
__phello__.spam 161
>>>

The fact that standard Python has a frozen module and a frozen package (indicated by the negative size member) is not well known, it is only used for testing. Try it out with import __hello__ for example.

16.16.1.19. Pièges

Il y a quelques cas tordus dans ctypes où on peut s’attendre à un résultat différent de la réalité.

Examinons l’exemple suivant :

>>> from ctypes import *
>>> class POINT(Structure):
...     _fields_ = ("x", c_int), ("y", c_int)
...
>>> class RECT(Structure):
...     _fields_ = ("a", POINT), ("b", POINT)
...
>>> p1 = POINT(1, 2)
>>> p2 = POINT(3, 4)
>>> rc = RECT(p1, p2)
>>> print(rc.a.x, rc.a.y, rc.b.x, rc.b.y)
1 2 3 4
>>> # now swap the two points
>>> rc.a, rc.b = rc.b, rc.a
>>> print(rc.a.x, rc.a.y, rc.b.x, rc.b.y)
3 4 3 4
>>>

Diantre. On s’attendait certainement à ce que le dernier résultat affiche 3 4 1 2. Que s’est-il passé ? Les étapes de la ligne rc.a, rc.b = rc.b, rc.a ci-dessus sont les suivantes :

>>> temp0, temp1 = rc.b, rc.a
>>> rc.a = temp0
>>> rc.b = temp1
>>>

Les objets temp0 et temp1 utilisent encore le tampon interne de l’objet rc ci-dessus. Donc exécuter rc.a = temp0 copie le contenu du tampon de temp0 dans celui de rc. Ce qui, par ricochet, modifie le contenu de temp1. Et donc, la dernière affectation, rc.b = temp1, n’a pas l’effet escompté.

Gardez en tête qu’accéder au sous-objet depuis une Structure, une Union ou un Array ne copie pas le sous-objet, mais crée un objet interface qui accède au tampon sous-jacent de l’objet initial.

Another example that may behave different from what one would expect is this:

>>> s = c_char_p()
>>> s.value = "abc def ghi"
>>> s.value
'abc def ghi'
>>> s.value is s.value
False
>>>

Pourquoi cela affiche-t’il False ? Les instances ctypes sont des objets qui contiennent un bloc mémoire et des descriptor qui donnent accès au contenu du ce bloc. Stocker un objet Python dans le bloc mémoire ne stocke pas l’objet même ; seuls ses contents le sont. Accéder au contents crée un nouvel objet Python à chaque fois !

16.16.1.20. Types de données à taille flottante

ctypes assure la prise en charge des tableaux et des structures à taille flottante.

La fonction resize() permet de redimensionner la taille du tampon mémoire d’un objet ctypes existant. Cette fonction prend l’objet comme premier argument et la taille en octets désirée comme second. La taille du tampon mémoire ne peut pas être inférieure à celle occupée par un objet unitaire du type considéré. Une ValueError est levée si c’est le cas :

>>> short_array = (c_short * 4)()
>>> print(sizeof(short_array))
8
>>> resize(short_array, 4)
Traceback (most recent call last):
    ...
ValueError: minimum size is 8
>>> resize(short_array, 32)
>>> sizeof(short_array)
32
>>> sizeof(type(short_array))
8
>>>

Cela dit, comment accéder aux éléments supplémentaires contenus dans le tableau ? Vu que le type ne connaît que 4 éléments, on obtient une erreur si l’on accède aux suivants :

>>> short_array[:]
[0, 0, 0, 0]
>>> short_array[7]
Traceback (most recent call last):
    ...
IndexError: invalid index
>>>

Une autre approche pour utiliser des types de donnée à taille flottante avec ctypes consiste à tirer profit de la nature intrinsèquement dynamique de Python et de (re)définir le type de donnée une fois que la taille demandée est connue, au cas-par-cas.

16.16.2. Référence du module

16.16.2.1. Recherche de bibliothèques partagées

When programming in a compiled language, shared libraries are accessed when compiling/linking a program, and when the program is run.

The purpose of the find_library() function is to locate a library in a way similar to what the compiler or runtime loader does (on platforms with several versions of a shared library the most recent should be loaded), while the ctypes library loaders act like when a program is run, and call the runtime loader directly.

The ctypes.util module provides a function which can help to determine the library to load.

ctypes.util.find_library(name)

Try to find a library and return a pathname. name is the library name without any prefix like lib, suffix like .so, .dylib or version number (this is the form used for the posix linker option -l). If no library can be found, returns None.

The exact functionality is system dependent.

On Linux, find_library() tries to run external programs (/sbin/ldconfig, gcc, objdump and ld) to find the library file. It returns the filename of the library file.

Modifié dans la version 3.6: On Linux, the value of the environment variable LD_LIBRARY_PATH is used when searching for libraries, if a library cannot be found by any other means.

Here are some examples:

>>> from ctypes.util import find_library
>>> find_library("m")
'libm.so.6'
>>> find_library("c")
'libc.so.6'
>>> find_library("bz2")
'libbz2.so.1.0'
>>>

On OS X, find_library() tries several predefined naming schemes and paths to locate the library, and returns a full pathname if successful:

>>> from ctypes.util import find_library
>>> find_library("c")
'/usr/lib/libc.dylib'
>>> find_library("m")
'/usr/lib/libm.dylib'
>>> find_library("bz2")
'/usr/lib/libbz2.dylib'
>>> find_library("AGL")
'/System/Library/Frameworks/AGL.framework/AGL'
>>>

On Windows, find_library() searches along the system search path, and returns the full pathname, but since there is no predefined naming scheme a call like find_library("c") will fail and return None.

If wrapping a shared library with ctypes, it may be better to determine the shared library name at development time, and hardcode that into the wrapper module instead of using find_library() to locate the library at runtime.

16.16.2.2. Chargement des bibliothèques partagées

There are several ways to load shared libraries into the Python process. One way is to instantiate one of the following classes:

class ctypes.CDLL(name, mode=DEFAULT_MODE, handle=None, use_errno=False, use_last_error=False)

Instances of this class represent loaded shared libraries. Functions in these libraries use the standard C calling convention, and are assumed to return int.

class ctypes.OleDLL(name, mode=DEFAULT_MODE, handle=None, use_errno=False, use_last_error=False)

Windows only: Instances of this class represent loaded shared libraries, functions in these libraries use the stdcall calling convention, and are assumed to return the windows specific HRESULT code. HRESULT values contain information specifying whether the function call failed or succeeded, together with additional error code. If the return value signals a failure, an OSError is automatically raised.

Modifié dans la version 3.3: WindowsError était levée auparavant.

class ctypes.WinDLL(name, mode=DEFAULT_MODE, handle=None, use_errno=False, use_last_error=False)

Windows only: Instances of this class represent loaded shared libraries, functions in these libraries use the stdcall calling convention, and are assumed to return int by default.

On Windows CE only the standard calling convention is used, for convenience the WinDLL and OleDLL use the standard calling convention on this platform.

The Python global interpreter lock is released before calling any function exported by these libraries, and reacquired afterwards.

class ctypes.PyDLL(name, mode=DEFAULT_MODE, handle=None)

Instances of this class behave like CDLL instances, except that the Python GIL is not released during the function call, and after the function execution the Python error flag is checked. If the error flag is set, a Python exception is raised.

Thus, this is only useful to call Python C api functions directly.

All these classes can be instantiated by calling them with at least one argument, the pathname of the shared library. If you have an existing handle to an already loaded shared library, it can be passed as the handle named parameter, otherwise the underlying platforms dlopen or LoadLibrary function is used to load the library into the process, and to get a handle to it.

The mode parameter can be used to specify how the library is loaded. For details, consult the dlopen(3) manpage. On Windows, mode is ignored. On posix systems, RTLD_NOW is always added, and is not configurable.

The use_errno parameter, when set to true, enables a ctypes mechanism that allows accessing the system errno error number in a safe way. ctypes maintains a thread-local copy of the systems errno variable; if you call foreign functions created with use_errno=True then the errno value before the function call is swapped with the ctypes private copy, the same happens immediately after the function call.

The function ctypes.get_errno() returns the value of the ctypes private copy, and the function ctypes.set_errno() changes the ctypes private copy to a new value and returns the former value.

The use_last_error parameter, when set to true, enables the same mechanism for the Windows error code which is managed by the GetLastError() and SetLastError() Windows API functions; ctypes.get_last_error() and ctypes.set_last_error() are used to request and change the ctypes private copy of the windows error code.

ctypes.RTLD_GLOBAL

Flag to use as mode parameter. On platforms where this flag is not available, it is defined as the integer zero.

ctypes.RTLD_LOCAL

Flag to use as mode parameter. On platforms where this is not available, it is the same as RTLD_GLOBAL.

ctypes.DEFAULT_MODE

The default mode which is used to load shared libraries. On OSX 10.3, this is RTLD_GLOBAL, otherwise it is the same as RTLD_LOCAL.

Instances of these classes have no public methods. Functions exported by the shared library can be accessed as attributes or by index. Please note that accessing the function through an attribute caches the result and therefore accessing it repeatedly returns the same object each time. On the other hand, accessing it through an index returns a new object each time:

>>> libc.time == libc.time
True
>>> libc['time'] == libc['time']
False

The following public attributes are available, their name starts with an underscore to not clash with exported function names:

PyDLL._handle

The system handle used to access the library.

PyDLL._name

The name of the library passed in the constructor.

Shared libraries can also be loaded by using one of the prefabricated objects, which are instances of the LibraryLoader class, either by calling the LoadLibrary() method, or by retrieving the library as attribute of the loader instance.

class ctypes.LibraryLoader(dlltype)

Class which loads shared libraries. dlltype should be one of the CDLL, PyDLL, WinDLL, or OleDLL types.

__getattr__() has special behavior: It allows loading a shared library by accessing it as attribute of a library loader instance. The result is cached, so repeated attribute accesses return the same library each time.

LoadLibrary(name)

Load a shared library into the process and return it. This method always returns a new instance of the library.

These prefabricated library loaders are available:

ctypes.cdll

Creates CDLL instances.

ctypes.windll

Windows only: Creates WinDLL instances.

ctypes.oledll

Windows only: Creates OleDLL instances.

ctypes.pydll

Creates PyDLL instances.

For accessing the C Python api directly, a ready-to-use Python shared library object is available:

ctypes.pythonapi

An instance of PyDLL that exposes Python C API functions as attributes. Note that all these functions are assumed to return C int, which is of course not always the truth, so you have to assign the correct restype attribute to use these functions.

16.16.2.3. Fonctions externes

As explained in the previous section, foreign functions can be accessed as attributes of loaded shared libraries. The function objects created in this way by default accept any number of arguments, accept any ctypes data instances as arguments, and return the default result type specified by the library loader. They are instances of a private class:

class ctypes._FuncPtr

Base class for C callable foreign functions.

Instances of foreign functions are also C compatible data types; they represent C function pointers.

This behavior can be customized by assigning to special attributes of the foreign function object.

restype

Assign a ctypes type to specify the result type of the foreign function. Use None for void, a function not returning anything.

It is possible to assign a callable Python object that is not a ctypes type, in this case the function is assumed to return a C int, and the callable will be called with this integer, allowing further processing or error checking. Using this is deprecated, for more flexible post processing or error checking use a ctypes data type as restype and assign a callable to the errcheck attribute.

argtypes

Assign a tuple of ctypes types to specify the argument types that the function accepts. Functions using the stdcall calling convention can only be called with the same number of arguments as the length of this tuple; functions using the C calling convention accept additional, unspecified arguments as well.

When a foreign function is called, each actual argument is passed to the from_param() class method of the items in the argtypes tuple, this method allows adapting the actual argument to an object that the foreign function accepts. For example, a c_char_p item in the argtypes tuple will convert a string passed as argument into a bytes object using ctypes conversion rules.

New: It is now possible to put items in argtypes which are not ctypes types, but each item must have a from_param() method which returns a value usable as argument (integer, string, ctypes instance). This allows defining adapters that can adapt custom objects as function parameters.

errcheck

Assign a Python function or another callable to this attribute. The callable will be called with three or more arguments:

callable(result, func, arguments)

result is what the foreign function returns, as specified by the restype attribute.

func is the foreign function object itself, this allows reusing the same callable object to check or post process the results of several functions.

arguments is a tuple containing the parameters originally passed to the function call, this allows specializing the behavior on the arguments used.

The object that this function returns will be returned from the foreign function call, but it can also check the result value and raise an exception if the foreign function call failed.

exception ctypes.ArgumentError

This exception is raised when a foreign function call cannot convert one of the passed arguments.

16.16.2.4. Prototypes de fonction

Foreign functions can also be created by instantiating function prototypes. Function prototypes are similar to function prototypes in C; they describe a function (return type, argument types, calling convention) without defining an implementation. The factory functions must be called with the desired result type and the argument types of the function, and can be used as decorator factories, and as such, be applied to functions through the @wrapper syntax. See Fonctions de rappel for examples.

ctypes.CFUNCTYPE(restype, *argtypes, use_errno=False, use_last_error=False)

The returned function prototype creates functions that use the standard C calling convention. The function will release the GIL during the call. If use_errno is set to true, the ctypes private copy of the system errno variable is exchanged with the real errno value before and after the call; use_last_error does the same for the Windows error code.

ctypes.WINFUNCTYPE(restype, *argtypes, use_errno=False, use_last_error=False)

Windows only: The returned function prototype creates functions that use the stdcall calling convention, except on Windows CE where WINFUNCTYPE() is the same as CFUNCTYPE(). The function will release the GIL during the call. use_errno and use_last_error have the same meaning as above.

ctypes.PYFUNCTYPE(restype, *argtypes)

The returned function prototype creates functions that use the Python calling convention. The function will not release the GIL during the call.

Function prototypes created by these factory functions can be instantiated in different ways, depending on the type and number of the parameters in the call:

prototype(address)

Returns a foreign function at the specified address which must be an integer.

prototype(callable)

Create a C callable function (a callback function) from a Python callable.

prototype(func_spec[, paramflags])

Returns a foreign function exported by a shared library. func_spec must be a 2-tuple (name_or_ordinal, library). The first item is the name of the exported function as string, or the ordinal of the exported function as small integer. The second item is the shared library instance.

prototype(vtbl_index, name[, paramflags[, iid]])

Returns a foreign function that will call a COM method. vtbl_index is the index into the virtual function table, a small non-negative integer. name is name of the COM method. iid is an optional pointer to the interface identifier which is used in extended error reporting.

COM methods use a special calling convention: They require a pointer to the COM interface as first argument, in addition to those parameters that are specified in the argtypes tuple.

The optional paramflags parameter creates foreign function wrappers with much more functionality than the features described above.

paramflags must be a tuple of the same length as argtypes.

Each item in this tuple contains further information about a parameter, it must be a tuple containing one, two, or three items.

The first item is an integer containing a combination of direction flags for the parameter:

1

Specifies an input parameter to the function.

2

Output parameter. The foreign function fills in a value.

4

Input parameter which defaults to the integer zero.

The optional second item is the parameter name as string. If this is specified, the foreign function can be called with named parameters.

The optional third item is the default value for this parameter.

This example demonstrates how to wrap the Windows MessageBoxW function so that it supports default parameters and named arguments. The C declaration from the windows header file is this:

WINUSERAPI int WINAPI
MessageBoxW(
    HWND hWnd,
    LPCWSTR lpText,
    LPCWSTR lpCaption,
    UINT uType);

Here is the wrapping with ctypes:

>>> from ctypes import c_int, WINFUNCTYPE, windll
>>> from ctypes.wintypes import HWND, LPCWSTR, UINT
>>> prototype = WINFUNCTYPE(c_int, HWND, LPCWSTR, LPCWSTR, UINT)
>>> paramflags = (1, "hwnd", 0), (1, "text", "Hi"), (1, "caption", "Hello from ctypes"), (1, "flags", 0)
>>> MessageBox = prototype(("MessageBoxW", windll.user32), paramflags)

The MessageBox foreign function can now be called in these ways:

>>> MessageBox()
>>> MessageBox(text="Spam, spam, spam")
>>> MessageBox(flags=2, text="foo bar")

A second example demonstrates output parameters. The win32 GetWindowRect function retrieves the dimensions of a specified window by copying them into RECT structure that the caller has to supply. Here is the C declaration:

WINUSERAPI BOOL WINAPI
GetWindowRect(
     HWND hWnd,
     LPRECT lpRect);

Here is the wrapping with ctypes:

>>> from ctypes import POINTER, WINFUNCTYPE, windll, WinError
>>> from ctypes.wintypes import BOOL, HWND, RECT
>>> prototype = WINFUNCTYPE(BOOL, HWND, POINTER(RECT))
>>> paramflags = (1, "hwnd"), (2, "lprect")
>>> GetWindowRect = prototype(("GetWindowRect", windll.user32), paramflags)
>>>

Functions with output parameters will automatically return the output parameter value if there is a single one, or a tuple containing the output parameter values when there are more than one, so the GetWindowRect function now returns a RECT instance, when called.

Output parameters can be combined with the errcheck protocol to do further output processing and error checking. The win32 GetWindowRect api function returns a BOOL to signal success or failure, so this function could do the error checking, and raises an exception when the api call failed:

>>> def errcheck(result, func, args):
...     if not result:
...         raise WinError()
...     return args
...
>>> GetWindowRect.errcheck = errcheck
>>>

If the errcheck function returns the argument tuple it receives unchanged, ctypes continues the normal processing it does on the output parameters. If you want to return a tuple of window coordinates instead of a RECT instance, you can retrieve the fields in the function and return them instead, the normal processing will no longer take place:

>>> def errcheck(result, func, args):
...     if not result:
...         raise WinError()
...     rc = args[1]
...     return rc.left, rc.top, rc.bottom, rc.right
...
>>> GetWindowRect.errcheck = errcheck
>>>

16.16.2.5. Fonctions utilitaires

ctypes.addressof(obj)

Returns the address of the memory buffer as integer. obj must be an instance of a ctypes type.

ctypes.alignment(obj_or_type)

Returns the alignment requirements of a ctypes type. obj_or_type must be a ctypes type or instance.

ctypes.byref(obj[, offset])

Returns a light-weight pointer to obj, which must be an instance of a ctypes type. offset defaults to zero, and must be an integer that will be added to the internal pointer value.

byref(obj, offset) corresponds to this C code:

(((char *)&obj) + offset)

The returned object can only be used as a foreign function call parameter. It behaves similar to pointer(obj), but the construction is a lot faster.

ctypes.cast(obj, type)

This function is similar to the cast operator in C. It returns a new instance of type which points to the same memory block as obj. type must be a pointer type, and obj must be an object that can be interpreted as a pointer.

ctypes.create_string_buffer(init_or_size, size=None)

This function creates a mutable character buffer. The returned object is a ctypes array of c_char.

init_or_size must be an integer which specifies the size of the array, or a bytes object which will be used to initialize the array items.

If a bytes object is specified as first argument, the buffer is made one item larger than its length so that the last element in the array is a NUL termination character. An integer can be passed as second argument which allows specifying the size of the array if the length of the bytes should not be used.

ctypes.create_unicode_buffer(init_or_size, size=None)

This function creates a mutable unicode character buffer. The returned object is a ctypes array of c_wchar.

init_or_size must be an integer which specifies the size of the array, or a string which will be used to initialize the array items.

If a string is specified as first argument, the buffer is made one item larger than the length of the string so that the last element in the array is a NUL termination character. An integer can be passed as second argument which allows specifying the size of the array if the length of the string should not be used.

ctypes.DllCanUnloadNow()

Windows only: This function is a hook which allows implementing in-process COM servers with ctypes. It is called from the DllCanUnloadNow function that the _ctypes extension dll exports.

ctypes.DllGetClassObject()

Windows only: This function is a hook which allows implementing in-process COM servers with ctypes. It is called from the DllGetClassObject function that the _ctypes extension dll exports.

ctypes.util.find_library(name)

Try to find a library and return a pathname. name is the library name without any prefix like lib, suffix like .so, .dylib or version number (this is the form used for the posix linker option -l). If no library can be found, returns None.

The exact functionality is system dependent.

ctypes.util.find_msvcrt()

Windows only: return the filename of the VC runtime library used by Python, and by the extension modules. If the name of the library cannot be determined, None is returned.

If you need to free memory, for example, allocated by an extension module with a call to the free(void *), it is important that you use the function in the same library that allocated the memory.

ctypes.FormatError([code])

Windows only: Returns a textual description of the error code code. If no error code is specified, the last error code is used by calling the Windows api function GetLastError.

ctypes.GetLastError()

Windows only: Returns the last error code set by Windows in the calling thread. This function calls the Windows GetLastError() function directly, it does not return the ctypes-private copy of the error code.

ctypes.get_errno()

Returns the current value of the ctypes-private copy of the system errno variable in the calling thread.

ctypes.get_last_error()

Windows only: returns the current value of the ctypes-private copy of the system LastError variable in the calling thread.

ctypes.memmove(dst, src, count)

Same as the standard C memmove library function: copies count bytes from src to dst. dst and src must be integers or ctypes instances that can be converted to pointers.

ctypes.memset(dst, c, count)

Same as the standard C memset library function: fills the memory block at address dst with count bytes of value c. dst must be an integer specifying an address, or a ctypes instance.

ctypes.POINTER(type)

This factory function creates and returns a new ctypes pointer type. Pointer types are cached and reused internally, so calling this function repeatedly is cheap. type must be a ctypes type.

ctypes.pointer(obj)

This function creates a new pointer instance, pointing to obj. The returned object is of the type POINTER(type(obj)).

Note: If you just want to pass a pointer to an object to a foreign function call, you should use byref(obj) which is much faster.

ctypes.resize(obj, size)

This function resizes the internal memory buffer of obj, which must be an instance of a ctypes type. It is not possible to make the buffer smaller than the native size of the objects type, as given by sizeof(type(obj)), but it is possible to enlarge the buffer.

ctypes.set_errno(value)

Set the current value of the ctypes-private copy of the system errno variable in the calling thread to value and return the previous value.

ctypes.set_last_error(value)

Windows only: set the current value of the ctypes-private copy of the system LastError variable in the calling thread to value and return the previous value.

ctypes.sizeof(obj_or_type)

Returns the size in bytes of a ctypes type or instance memory buffer. Does the same as the C sizeof operator.

ctypes.string_at(address, size=-1)

This function returns the C string starting at memory address address as a bytes object. If size is specified, it is used as size, otherwise the string is assumed to be zero-terminated.

ctypes.WinError(code=None, descr=None)

Windows only: this function is probably the worst-named thing in ctypes. It creates an instance of OSError. If code is not specified, GetLastError is called to determine the error code. If descr is not specified, FormatError() is called to get a textual description of the error.

Modifié dans la version 3.3: An instance of WindowsError used to be created.

ctypes.wstring_at(address, size=-1)

This function returns the wide character string starting at memory address address as a string. If size is specified, it is used as the number of characters of the string, otherwise the string is assumed to be zero-terminated.

16.16.2.6. Types de données

class ctypes._CData

This non-public class is the common base class of all ctypes data types. Among other things, all ctypes type instances contain a memory block that hold C compatible data; the address of the memory block is returned by the addressof() helper function. Another instance variable is exposed as _objects; this contains other Python objects that need to be kept alive in case the memory block contains pointers.

Common methods of ctypes data types, these are all class methods (to be exact, they are methods of the metaclass):

from_buffer(source[, offset])

This method returns a ctypes instance that shares the buffer of the source object. The source object must support the writeable buffer interface. The optional offset parameter specifies an offset into the source buffer in bytes; the default is zero. If the source buffer is not large enough a ValueError is raised.

from_buffer_copy(source[, offset])

This method creates a ctypes instance, copying the buffer from the source object buffer which must be readable. The optional offset parameter specifies an offset into the source buffer in bytes; the default is zero. If the source buffer is not large enough a ValueError is raised.

from_address(address)

This method returns a ctypes type instance using the memory specified by address which must be an integer.

from_param(obj)

This method adapts obj to a ctypes type. It is called with the actual object used in a foreign function call when the type is present in the foreign function’s argtypes tuple; it must return an object that can be used as a function call parameter.

All ctypes data types have a default implementation of this classmethod that normally returns obj if that is an instance of the type. Some types accept other objects as well.

in_dll(library, name)

This method returns a ctypes type instance exported by a shared library. name is the name of the symbol that exports the data, library is the loaded shared library.

Common instance variables of ctypes data types:

_b_base_

Sometimes ctypes data instances do not own the memory block they contain, instead they share part of the memory block of a base object. The _b_base_ read-only member is the root ctypes object that owns the memory block.

_b_needsfree_

This read-only variable is true when the ctypes data instance has allocated the memory block itself, false otherwise.

_objects

This member is either None or a dictionary containing Python objects that need to be kept alive so that the memory block contents is kept valid. This object is only exposed for debugging; never modify the contents of this dictionary.

16.16.2.7. Types de données fondamentaux

class ctypes._SimpleCData

This non-public class is the base class of all fundamental ctypes data types. It is mentioned here because it contains the common attributes of the fundamental ctypes data types. _SimpleCData is a subclass of _CData, so it inherits their methods and attributes. ctypes data types that are not and do not contain pointers can now be pickled.

Instances have a single attribute:

value

This attribute contains the actual value of the instance. For integer and pointer types, it is an integer, for character types, it is a single character bytes object or string, for character pointer types it is a Python bytes object or string.

When the value attribute is retrieved from a ctypes instance, usually a new object is returned each time. ctypes does not implement original object return, always a new object is constructed. The same is true for all other ctypes object instances.

Fundamental data types, when returned as foreign function call results, or, for example, by retrieving structure field members or array items, are transparently converted to native Python types. In other words, if a foreign function has a restype of c_char_p, you will always receive a Python bytes object, not a c_char_p instance.

Subclasses of fundamental data types do not inherit this behavior. So, if a foreign functions restype is a subclass of c_void_p, you will receive an instance of this subclass from the function call. Of course, you can get the value of the pointer by accessing the value attribute.

These are the fundamental ctypes data types:

class ctypes.c_byte

Represents the C signed char datatype, and interprets the value as small integer. The constructor accepts an optional integer initializer; no overflow checking is done.

class ctypes.c_char

Represents the C char datatype, and interprets the value as a single character. The constructor accepts an optional string initializer, the length of the string must be exactly one character.

class ctypes.c_char_p

Represents the C char * datatype when it points to a zero-terminated string. For a general character pointer that may also point to binary data, POINTER(c_char) must be used. The constructor accepts an integer address, or a bytes object.

class ctypes.c_double

Represents the C double datatype. The constructor accepts an optional float initializer.

class ctypes.c_longdouble

Represents the C long double datatype. The constructor accepts an optional float initializer. On platforms where sizeof(long double) == sizeof(double) it is an alias to c_double.

class ctypes.c_float

Represents the C float datatype. The constructor accepts an optional float initializer.

class ctypes.c_int

Represents the C signed int datatype. The constructor accepts an optional integer initializer; no overflow checking is done. On platforms where sizeof(int) == sizeof(long) it is an alias to c_long.

class ctypes.c_int8

Represents the C 8-bit signed int datatype. Usually an alias for c_byte.

class ctypes.c_int16

Represents the C 16-bit signed int datatype. Usually an alias for c_short.

class ctypes.c_int32

Represents the C 32-bit signed int datatype. Usually an alias for c_int.

class ctypes.c_int64

Represents the C 64-bit signed int datatype. Usually an alias for c_longlong.

class ctypes.c_long

Represents the C signed long datatype. The constructor accepts an optional integer initializer; no overflow checking is done.

class ctypes.c_longlong

Represents the C signed long long datatype. The constructor accepts an optional integer initializer; no overflow checking is done.

class ctypes.c_short

Represents the C signed short datatype. The constructor accepts an optional integer initializer; no overflow checking is done.

class ctypes.c_size_t

Represents the C size_t datatype.

class ctypes.c_ssize_t

Represents the C ssize_t datatype.

Nouveau dans la version 3.2.

class ctypes.c_ubyte

Represents the C unsigned char datatype, it interprets the value as small integer. The constructor accepts an optional integer initializer; no overflow checking is done.

class ctypes.c_uint

Represents the C unsigned int datatype. The constructor accepts an optional integer initializer; no overflow checking is done. On platforms where sizeof(int) == sizeof(long) it is an alias for c_ulong.

class ctypes.c_uint8

Represents the C 8-bit unsigned int datatype. Usually an alias for c_ubyte.

class ctypes.c_uint16

Represents the C 16-bit unsigned int datatype. Usually an alias for c_ushort.

class ctypes.c_uint32

Represents the C 32-bit unsigned int datatype. Usually an alias for c_uint.

class ctypes.c_uint64

Represents the C 64-bit unsigned int datatype. Usually an alias for c_ulonglong.

class ctypes.c_ulong

Represents the C unsigned long datatype. The constructor accepts an optional integer initializer; no overflow checking is done.

class ctypes.c_ulonglong

Represents the C unsigned long long datatype. The constructor accepts an optional integer initializer; no overflow checking is done.

class ctypes.c_ushort

Represents the C unsigned short datatype. The constructor accepts an optional integer initializer; no overflow checking is done.

class ctypes.c_void_p

Represents the C void * type. The value is represented as integer. The constructor accepts an optional integer initializer.

class ctypes.c_wchar

Represents the C wchar_t datatype, and interprets the value as a single character unicode string. The constructor accepts an optional string initializer, the length of the string must be exactly one character.

class ctypes.c_wchar_p

Represents the C wchar_t * datatype, which must be a pointer to a zero-terminated wide character string. The constructor accepts an integer address, or a string.

class ctypes.c_bool

Represent the C bool datatype (more accurately, _Bool from C99). Its value can be True or False, and the constructor accepts any object that has a truth value.

class ctypes.HRESULT

Windows only: Represents a HRESULT value, which contains success or error information for a function or method call.

class ctypes.py_object

Represents the C PyObject * datatype. Calling this without an argument creates a NULL PyObject * pointer.

The ctypes.wintypes module provides quite some other Windows specific data types, for example HWND, WPARAM, or DWORD. Some useful structures like MSG or RECT are also defined.

16.16.2.8. Types de donnée dérivés de Structure

class ctypes.Union(*args, **kw)

Abstract base class for unions in native byte order.

class ctypes.BigEndianStructure(*args, **kw)

Abstract base class for structures in big endian byte order.

class ctypes.LittleEndianStructure(*args, **kw)

Abstract base class for structures in little endian byte order.

Structures with non-native byte order cannot contain pointer type fields, or any other data types containing pointer type fields.

class ctypes.Structure(*args, **kw)

Abstract base class for structures in native byte order.

Concrete structure and union types must be created by subclassing one of these types, and at least define a _fields_ class variable. ctypes will create descriptors which allow reading and writing the fields by direct attribute accesses. These are the

_fields_

A sequence defining the structure fields. The items must be 2-tuples or 3-tuples. The first item is the name of the field, the second item specifies the type of the field; it can be any ctypes data type.

For integer type fields like c_int, a third optional item can be given. It must be a small positive integer defining the bit width of the field.

Field names must be unique within one structure or union. This is not checked, only one field can be accessed when names are repeated.

It is possible to define the _fields_ class variable after the class statement that defines the Structure subclass, this allows creating data types that directly or indirectly reference themselves:

class List(Structure):
    pass
List._fields_ = [("pnext", POINTER(List)),
                 ...
                ]

The _fields_ class variable must, however, be defined before the type is first used (an instance is created, sizeof() is called on it, and so on). Later assignments to the _fields_ class variable will raise an AttributeError.

It is possible to defined sub-subclasses of structure types, they inherit the fields of the base class plus the _fields_ defined in the sub-subclass, if any.

_pack_

An optional small integer that allows overriding the alignment of structure fields in the instance. _pack_ must already be defined when _fields_ is assigned, otherwise it will have no effect.

_anonymous_

An optional sequence that lists the names of unnamed (anonymous) fields. _anonymous_ must be already defined when _fields_ is assigned, otherwise it will have no effect.

The fields listed in this variable must be structure or union type fields. ctypes will create descriptors in the structure type that allows accessing the nested fields directly, without the need to create the structure or union field.

Here is an example type (Windows):

class _U(Union):
    _fields_ = [("lptdesc", POINTER(TYPEDESC)),
                ("lpadesc", POINTER(ARRAYDESC)),
                ("hreftype", HREFTYPE)]

class TYPEDESC(Structure):
    _anonymous_ = ("u",)
    _fields_ = [("u", _U),
                ("vt", VARTYPE)]

The TYPEDESC structure describes a COM data type, the vt field specifies which one of the union fields is valid. Since the u field is defined as anonymous field, it is now possible to access the members directly off the TYPEDESC instance. td.lptdesc and td.u.lptdesc are equivalent, but the former is faster since it does not need to create a temporary union instance:

td = TYPEDESC()
td.vt = VT_PTR
td.lptdesc = POINTER(some_type)
td.u.lptdesc = POINTER(some_type)

It is possible to defined sub-subclasses of structures, they inherit the fields of the base class. If the subclass definition has a separate _fields_ variable, the fields specified in this are appended to the fields of the base class.

Structure and union constructors accept both positional and keyword arguments. Positional arguments are used to initialize member fields in the same order as they are appear in _fields_. Keyword arguments in the constructor are interpreted as attribute assignments, so they will initialize _fields_ with the same name, or create new attributes for names not present in _fields_.

16.16.2.9. Tableaux et pointeurs

class ctypes.Array(*args)

Classe de base abstraite pour les arrays.

The recommended way to create concrete array types is by multiplying any ctypes data type with a positive integer. Alternatively, you can subclass this type and define _length_ and _type_ class variables. Array elements can be read and written using standard subscript and slice accesses; for slice reads, the resulting object is not itself an Array.

_length_

A positive integer specifying the number of elements in the array. Out-of-range subscripts result in an IndexError. Will be returned by len().

_type_

Spécifie le type de chaque élément de l”array.

Array subclass constructors accept positional arguments, used to initialize the elements in order.

class ctypes._Pointer

Private, abstract base class for pointers.

Concrete pointer types are created by calling POINTER() with the type that will be pointed to; this is done automatically by pointer().

If a pointer points to an array, its elements can be read and written using standard subscript and slice accesses. Pointer objects have no size, so len() will raise TypeError. Negative subscripts will read from the memory before the pointer (as in C), and out-of-range subscripts will probably crash with an access violation (if you’re lucky).

_type_

Specifies the type pointed to.

contents

Returns the object to which to pointer points. Assigning to this attribute changes the pointer to point to the assigned object.

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17. Exécution concourante

Les modules documentés dans ce chapitre fournissent des outils d’exécution concourante de code. Le choix de l’outil approprié dépend de la tâche à exécuter (limitée par le CPU (CPU bound), ou limitée la vitesse des entrées-sorties (IO bound)) et du style de développement désiré (coopération gérée par des évènements ou multitâche préemptif). En voici un survol :

17.1. threading — Parallélisme basé sur les fils d’exécution (threads)

17.1.1. Données locales au fil d’exécution

17.1.2. Objets Threads

17.1.3. Verrous

17.1.4. RLock Objects

17.1.5. Condition Objects

17.1.6. Semaphore Objects

17.1.6.1. Semaphore Example

17.1.7. Event Objects

17.1.8. Timer Objects

17.1.9. Barrier Objects

17.1.10. Using locks, conditions, and semaphores in the with statement

17.2. multiprocessing — Parallélisme par processus

17.2.1. Introduction

17.2.1.1. La classe Process

17.2.1.2. Contextes et méthodes de démarrage

17.2.1.3. Échange d’objets entre les processus

17.2.1.4. Synchronisation entre processus

17.2.1.5. Partager un état entre les processus

17.2.1.6. Utiliser un réservoir de workers

17.2.2. Référence

17.2.2.1. Process et exceptions

17.2.2.2. Tubes (pipes) et Queues

17.2.2.3. Divers

17.2.2.4. Objets de connexions

17.2.2.5. Primitives de synchronisation

17.2.2.6. Objets ctypes partagés

17.2.2.6.1. Le module multiprocessing.sharedctypes

17.2.2.7. Gestionnaires

17.2.2.7.1. Gestionnaires personnalisés

17.2.2.7.2. Utiliser un gestionnaire distant

17.2.2.8. Objets mandataires

17.2.2.8.1. Nettoyage

17.2.2.9. Bassins de processus

17.2.2.10. Auditeurs et Clients

17.2.2.10.1. Formats d’adresses

17.2.2.11. Clés d’authentification

17.2.2.12. Journalisation

17.2.2.13. Le module multiprocessing.dummy

17.2.3. Lignes directrices de programmation

17.2.3.1. Toutes les méthodes de démarrage

17.2.3.2. Les méthodes de démarrage spawn et forkserver

17.2.4. Exemples

17.3. Le paquet concurrent

17.4. concurrent.futures — Launching parallel tasks

17.4.1. Executor Objects

17.4.2. ThreadPoolExecutor

17.4.2.1. ThreadPoolExecutor Example

17.4.3. ProcessPoolExecutor

17.4.3.1. ProcessPoolExecutor Example

17.4.4. Future Objects

17.4.5. Module Functions

17.4.6. Exception classes

17.5. subprocess — Gestion de sous-processus

17.5.1. Utiliser le module subprocess

17.5.1.1. Arguments fréquemment utilisés

17.5.1.2. Constructeur de Popen

17.5.1.3. Exceptions

17.5.2. Considérations de sécurité

17.5.3. Objets Popen

17.5.4. Utilitaires Popen pour Windows

17.5.4.1. Constantes

17.5.5. Ancienne interface (API) haut-niveau

17.5.6. Remplacer les fonctions plus anciennes par le module subprocess

17.5.6.1. Remplacement des backquotes des shells /bin/sh

17.5.6.2. Remplacer les pipes du shell

17.5.6.3. Remplacer os.system()

17.5.6.4. Remplacer les fonctions de la famille os.spawn

17.5.6.5. Remplacer os.popen(), os.popen2(), os.popen3()

17.5.6.6. Remplacer les fonctions du module popen2

17.5.7. Remplacement des fonctions originales d’invocation du shell

17.5.8. Notes

17.5.8.1. Convertir une séquence d’arguments vers une chaîne de caractères sous Windows

17.6. sched — Event scheduler

17.6.1. Scheduler Objects

17.7. queue — File synchronisée

17.7.1. Objets Queue

Les modules suivants servent de fondation pour certains services cités ci-dessus.

17.8. dummy_threading — Module de substitution au module threading

17.9. _thread — API bas niveau de gestion de fils d’exécution

17.10. _dummy_thread — Module de substitution pour le module _thread

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17.1. threading — Parallélisme basé sur les fils d’exécution (threads)

Code source : Lib/threading.py [https://github.com/python/cpython/tree/3.6/Lib/threading.py]

Ce module élabore des interfaces haut-niveau de fils d’exécutions multiples (threading) conçues en s’appuyant sur le module bas-niveau _thread. Voir aussi le module queue.

The dummy_threading module is provided for situations where threading cannot be used because _thread is missing.

Note

Bien qu’ils ne soient pas listés ci-dessous, ce module gère toujours les noms en camelCase utilisés pour certaines méthodes et fonctions de ce module dans la série Python 2.x.

Ce module définit les fonctions suivantes :

threading.active_count()

Renvoie le nombre d’objets Thread actuellement vivants. Le compte renvoyé est égal à la longueur de la liste renvoyée par enumerate().

threading.current_thread()

Renvoie l’objet Thread courant, correspondant au fil de contrôle de l’appelant. Si le fil de contrôle de l’appelant n’a pas été créé via le module Thread, un objet thread factice aux fonctionnalités limitées est renvoyé.

threading.get_ident()

Renvoie l”« identifiant de fil » du fil d’exécution courant. C’est un entier non nul. Sa valeur n’a pas de signification directe ; il est destiné à être utilisé comme valeur magique opaque, par exemple comme clef de dictionnaire de données pour chaque fil. Les identificateurs de fils peuvent être recyclés lorsqu’un fil se termine et qu’un autre fil est créé.

Nouveau dans la version 3.3.

threading.enumerate()

Renvoie une liste de tous les objets fil d’exécution Thread actuellement vivants. La liste inclut les fils démons, les fils factices créés par current_thread() et le fil principal. Elle exclut les fils terminés et les fils qui n’ont pas encore été lancés.

threading.main_thread()

Renvoie l’objet fil d’exécution Thread principal. Dans des conditions normales, le fil principal est le fil à partir duquel l’interpréteur Python a été lancé.

Nouveau dans la version 3.4.

threading.settrace(func)

Attache une fonction de traçage pour tous les fils d’exécution démarrés depuis le module Thread. La fonction func est passée à sys.settrace() pour chaque fil, avant que sa méthode run() soit appelée.

threading.setprofile(func)

Attache une fonction de profilage pour tous les fils d’exécution démarrés depuis le module Threading. La fonction func est passée à sys.setprofile() pour chaque fil, avant que sa méthode run() soit appelée.

threading.stack_size([size])

Return the thread stack size used when creating new threads. The optional size argument specifies the stack size to be used for subsequently created threads, and must be 0 (use platform or configured default) or a positive integer value of at least 32,768 (32 KiB). If size is not specified, 0 is used. If changing the thread stack size is unsupported, a RuntimeError is raised. If the specified stack size is invalid, a ValueError is raised and the stack size is unmodified. 32 KiB is currently the minimum supported stack size value to guarantee sufficient stack space for the interpreter itself. Note that some platforms may have particular restrictions on values for the stack size, such as requiring a minimum stack size > 32 KiB or requiring allocation in multiples of the system memory page size - platform documentation should be referred to for more information (4 KiB pages are common; using multiples of 4096 for the stack size is the suggested approach in the absence of more specific information). Availability: Windows, systems with POSIX threads.

Ce module définit également la constante suivante :

threading.TIMEOUT_MAX

La valeur maximale autorisée pour le paramètre timeout des fonctions bloquantes (Lock.acquire(), RLock.acquire(), Condition.wait(), etc.). Spécifier un délai d’attente supérieur à cette valeur lève une OverflowError.

Nouveau dans la version 3.2.

Ce module définit un certain nombre de classes, qui sont détaillées dans les sections ci-dessous.

La conception de ce module est librement basée sur le modèle des fils d’exécution de Java. Cependant, là où Java fait des verrous et des variables de condition le comportement de base de chaque objet, ils sont des objets séparés en Python. La classe Python Thread prend en charge un sous-ensemble du comportement de la classe Thread de Java ; actuellement, il n’y a aucune priorité, aucun groupe de fils d’exécution, et les fils ne peuvent être détruits, arrêtés, suspendus, repris ni interrompus. Les méthodes statiques de la classe Thread de Java, lorsqu’elles sont implémentées, correspondent à des fonctions au niveau du module.

Toutes les méthodes décrites ci-dessous sont exécutées de manière atomique.

17.1.1. Données locales au fil d’exécution

Les données locales au fil d’exécution (thread-local data) sont des données dont les valeurs sont propres à chaque fil. Pour gérer les données locales au fil, il suffit de créer une instance de local (ou une sous-classe) et d’y stocker des données :

mydata = threading.local()
mydata.x = 1

Les valeurs dans l’instance sont différentes pour des threads différents.

class threading.local

Classe qui représente les données locales au fil d’exécution.

Pour plus de détails et de nombreux exemples, voir la chaîne de documentation du module _threading_local.

17.1.2. Objets Threads

La classe fil d’exécution Thread représente une activité qui est exécutée dans un fil d’exécution séparé. Il y a deux façons de spécifier l’activité : en passant un objet appelable au constructeur, ou en ré-implémentant la méthode run() dans une sous-classe. Aucune autre méthode (à l’exception du constructeur) ne doit être remplacée dans une sous-classe. En d’autres termes, réimplémentez seulement les méthodes __init__() et run() de cette classe.

Une fois qu’un objet fil d’exécution est créé, son activité doit être lancée en appelant la méthode start() du fil. Ceci invoque la méthode run() dans un fil d’exécution séparé.

Une fois que l’activité du fil d’exécution est lancée, le fil est considéré comme « vivant ». Il cesse d’être vivant lorsque sa méthode run() se termine – soit normalement, soit en levant une exception non gérée. La méthode is_alive() teste si le fil est vivant.

D’autres fils d’exécution peuvent appeler la méthode join() d’un fil. Ceci bloque le fil appelant jusqu’à ce que le fil dont la méthode join() est appelée soit terminé.

Un fil d’exécution a un nom. Le nom peut être passé au constructeur, et lu ou modifié via l’attribut name.

Un fil d’exécution peut être marqué comme « fil démon ». Un programme Python se termine quand il ne reste plus que des fils démons. La valeur initiale est héritée du fil d’exécution qui l’a créé. Cette option peut être définie par la propriété daemon ou par l’argument daemon du constructeur.

Note

Les fils d’exécution démons sont brusquement terminés à l’arrêt du programme Python. Leurs ressources (fichiers ouverts, transactions de base de données, etc.) peuvent ne pas être libérées correctement. Si vous voulez que vos fils s’arrêtent proprement, faites en sorte qu’ils ne soient pas démoniques et utilisez un mécanisme de signalisation approprié tel qu’un objet évènement Event.

Il y a un objet « fil principal », qui correspond au fil de contrôle initial dans le programme Python. Ce n’est pas un fil démon.

Il y a une possibilité que des objets fil d’exécution « fictifs » soient créés. Ce sont des objets correspondant à des fils d’exécution « étrangers », qui sont des fils de contrôle démarrés en dehors du module de threading, par exemple directement depuis du code C. Les objets fils d’exécution fictifs ont des fonctionnalités limitées ; ils sont toujours considérés comme vivants et démoniques, et ne peuvent pas être attendus via join(). Ils ne sont jamais supprimés, car il est impossible de détecter la fin des fils d’exécution étrangers.

class threading.Thread(group=None, target=None, name=None, args=(), kwargs={}, *, daemon=None)

Ce constructeur doit toujours être appelé avec des arguments nommés. Les arguments sont :

group doit être None ; cet argument est réservé pour une extension future lorsqu’une classe ThreadGroup sera implémentée.

target est l’objet appelable qui doit être invoqué par la méthode run(). La valeur par défaut est None, ce qui signifie que rien n’est appelé.

name est le nom du fil d’exécution. Par défaut, un nom unique est construit de la forme « Thread–N » où N est un petit nombre décimal.

args est le tuple d’arguments pour l’invocation de l’objet appelable. La valeur par défaut est ().

kwargs est un dictionnaire d’arguments nommés pour l’invocation de l’objet appelable. La valeur par défaut est {}.

S’il ne vaut pas None, daemon définit explicitement si le fil d’exécution est démonique ou pas. S’il vaut None (par défaut), la valeur est héritée du fil courant.

Si la sous-classe réimplémente le constructeur, elle doit s’assurer d’appeler le constructeur de la classe de base (Thread.__init__()) avant de faire autre chose au fil d’exécution.

Modifié dans la version 3.3: Ajout de l’argument daemon.

start()

Lance l’activité du fil d’exécution.

Elle ne doit être appelée qu’une fois par objet de fil. Elle fait en sorte que la méthode run() de l’objet soit invoquée dans un fil d’exécution.

Cette méthode lève une RuntimeError si elle est appelée plus d’une fois sur le même objet fil d’exécution.

run()

Méthode représentant l’activité du fil d’exécution.

You may override this method in a subclass. The standard run() method invokes the callable object passed to the object’s constructor as the target argument, if any, with sequential and keyword arguments taken from the args and kwargs arguments, respectively.

join(timeout=None)

Attend que le fil d’exécution se termine. Ceci bloque le fil appelant jusqu’à ce que le fil dont la méthode join() est appelée se termine – soit normalement, soit par une exception non gérée – ou jusqu’à ce que le délai optionnel timeout soit atteint.

Lorsque l’argument timeout est présent et ne vaut pas None, il doit être un nombre en virgule flottante spécifiant un délai pour l’opération en secondes (ou fractions de secondes). Comme join() renvoie toujours None, vous devez appeler is_alive() après join() pour déterminer si le délai a expiré – si le fil d’exécution est toujours vivant, c’est que l’appel à join() a expiré.

Lorsque l’argument timeout n’est pas présent ou vaut None, l’opération se bloque jusqu’à ce que le fil d’exécution se termine.

Un fil d’exécution peut être attendu via join() de nombreuses fois.

join() lève une RuntimeError si une tentative est faite pour attendre le fil d’exécution courant car cela conduirait à un interblocage (deadlock en anglais). Attendre via join() un fil d’exécution avant son lancement est aussi une erreur et, si vous tentez de le faire, lève la même exception.

name

Une chaîne de caractères utilisée à des fins d’identification seulement. Elle n’a pas de sémantique. Plusieurs fils d’exécution peuvent porter le même nom. Le nom initial est défini par le constructeur.

getName()

setName()

Anciens accesseur et mutateur pour name ; utilisez plutôt ce dernier directement.

ident

« L’identificateur de fil d’exécution » de ce fil ou None si le fil n’a pas été lancé. C’est un entier non nul. Voyez également la fonction get_ident(). Les identificateurs de fils peuvent être recyclés lorsqu’un fil se termine et qu’un autre fil est créé. L’identifiant est disponible même après que le fil ait terminé.

is_alive()

Renvoie si le fil d’exécution est vivant ou pas.

Cette méthode renvoie True depuis juste avant le démarrage de la méthode run() et jusqu’à juste après la terminaison de la méthode run(). La fonction enumerate() du module renvoie une liste de tous les fils d’exécution vivants.

daemon

Booléen indiquant si ce fil d’exécution est un fil démon (True) ou non (False). Celui-ci doit être défini avant que start() ne soit appelé, sinon RuntimeError est levée. Sa valeur initiale est héritée du fil d’exécution créateur ; le fil principal n’est pas un fil démon et donc tous les fils créés dans ce fil principal ont par défaut la valeur daemon = False.

Le programme Python se termine lorsqu’il ne reste plus de fils d’exécution non-démons vivants.

isDaemon()

setDaemon()

Anciens accesseur et mutateur pour daemon ; utilisez plutôt ce dernier directement.

CPython implementation detail: En CPython, en raison du verrou global de l’interpréteur (Global Interpreter Lock), un seul fil d’exécution peut exécuter du code Python à la fois (même si certaines bibliothèques orientées performance peuvent surmonter cette limitation). Si vous voulez que votre application fasse un meilleur usage des ressources de calcul des machines multi-cœurs, nous vous conseillons d’utiliser multiprocessing ou concurrent.futures.ProcessPoolExecutor. Néanmoins, les fils d’exécutions multiples restent un modèle approprié si vous souhaitez exécuter simultanément plusieurs tâches limitées par les performances des entrées-sorties.

17.1.3. Verrous

Un verrou primitif n’appartient pas à un fil d’exécution lorsqu’il est verrouillé. En Python, c’est actuellement la méthode de synchronisation la plus bas-niveau qui soit disponible, implémentée directement par le module d’extension _thread.

Un verrou primitif est soit « verrouillé » soit « déverrouillé ». Il est créé dans un état déverrouillé. Il a deux méthodes, acquire() et release(). Lorsque l’état est déverrouillé, acquire() verrouille et se termine immédiatement. Lorsque l’état est verrouillé, acquire() bloque jusqu’à ce qu’un appel à release() provenant d’un autre fil d’exécution le déverrouille. À ce moment acquire() le verrouille à nouveau et rend la main. La méthode release() ne doit être appelée que si le verrou est verrouillé, elle le déverrouille alors et se termine immédiatement. Déverrouiller un verrou qui n’est pas verrouillé provoque une RuntimeError.

Locks also support the context management protocol.

When more than one thread is blocked in acquire() waiting for the state to turn to unlocked, only one thread proceeds when a release() call resets the state to unlocked; which one of the waiting threads proceeds is not defined, and may vary across implementations.

All methods are executed atomically.

class threading.Lock

The class implementing primitive lock objects. Once a thread has acquired a lock, subsequent attempts to acquire it block, until it is released; any thread may release it.

Note that Lock is actually a factory function which returns an instance of the most efficient version of the concrete Lock class that is supported by the platform.

acquire(blocking=True, timeout=-1)

Acquiert un verrou, bloquant ou non bloquant.

When invoked with the blocking argument set to True (the default), block until the lock is unlocked, then set it to locked and return True.

When invoked with the blocking argument set to False, do not block. If a call with blocking set to True would block, return False immediately; otherwise, set the lock to locked and return True.

When invoked with the floating-point timeout argument set to a positive value, block for at most the number of seconds specified by timeout and as long as the lock cannot be acquired. A timeout argument of -1 specifies an unbounded wait. It is forbidden to specify a timeout when blocking is false.

The return value is True if the lock is acquired successfully, False if not (for example if the timeout expired).

Modifié dans la version 3.2: Le paramètre timeout est nouveau.

Modifié dans la version 3.2: Lock acquisition can now be interrupted by signals on POSIX if the underlying threading implementation supports it.

release()

Release a lock. This can be called from any thread, not only the thread which has acquired the lock.

When the lock is locked, reset it to unlocked, and return. If any other threads are blocked waiting for the lock to become unlocked, allow exactly one of them to proceed.

When invoked on an unlocked lock, a RuntimeError is raised.

Il n’y a pas de valeur de retour.

17.1.4. RLock Objects

A reentrant lock is a synchronization primitive that may be acquired multiple times by the same thread. Internally, it uses the concepts of « owning thread » and « recursion level » in addition to the locked/unlocked state used by primitive locks. In the locked state, some thread owns the lock; in the unlocked state, no thread owns it.

To lock the lock, a thread calls its acquire() method; this returns once the thread owns the lock. To unlock the lock, a thread calls its release() method. acquire()/release() call pairs may be nested; only the final release() (the release() of the outermost pair) resets the lock to unlocked and allows another thread blocked in acquire() to proceed.

Reentrant locks also support the context management protocol.

class threading.RLock

This class implements reentrant lock objects. A reentrant lock must be released by the thread that acquired it. Once a thread has acquired a reentrant lock, the same thread may acquire it again without blocking; the thread must release it once for each time it has acquired it.

Note that RLock is actually a factory function which returns an instance of the most efficient version of the concrete RLock class that is supported by the platform.

acquire(blocking=True, timeout=-1)

Acquiert un verrou, bloquant ou non bloquant.

When invoked without arguments: if this thread already owns the lock, increment the recursion level by one, and return immediately. Otherwise, if another thread owns the lock, block until the lock is unlocked. Once the lock is unlocked (not owned by any thread), then grab ownership, set the recursion level to one, and return. If more than one thread is blocked waiting until the lock is unlocked, only one at a time will be able to grab ownership of the lock. There is no return value in this case.

When invoked with the blocking argument set to true, do the same thing as when called without arguments, and return true.

When invoked with the blocking argument set to false, do not block. If a call without an argument would block, return false immediately; otherwise, do the same thing as when called without arguments, and return true.

When invoked with the floating-point timeout argument set to a positive value, block for at most the number of seconds specified by timeout and as long as the lock cannot be acquired. Return true if the lock has been acquired, false if the timeout has elapsed.

Modifié dans la version 3.2: Le paramètre timeout est nouveau.

release()

Release a lock, decrementing the recursion level. If after the decrement it is zero, reset the lock to unlocked (not owned by any thread), and if any other threads are blocked waiting for the lock to become unlocked, allow exactly one of them to proceed. If after the decrement the recursion level is still nonzero, the lock remains locked and owned by the calling thread.

Only call this method when the calling thread owns the lock. A RuntimeError is raised if this method is called when the lock is unlocked.

Il n’y a pas de valeur de retour.

17.1.5. Condition Objects

A condition variable is always associated with some kind of lock; this can be passed in or one will be created by default. Passing one in is useful when several condition variables must share the same lock. The lock is part of the condition object: you don’t have to track it separately.

A condition variable obeys the context management protocol: using the with statement acquires the associated lock for the duration of the enclosed block. The acquire() and release() methods also call the corresponding methods of the associated lock.

Other methods must be called with the associated lock held. The wait() method releases the lock, and then blocks until another thread awakens it by calling notify() or notify_all(). Once awakened, wait() re-acquires the lock and returns. It is also possible to specify a timeout.

The notify() method wakes up one of the threads waiting for the condition variable, if any are waiting. The notify_all() method wakes up all threads waiting for the condition variable.

Note: the notify() and notify_all() methods don’t release the lock; this means that the thread or threads awakened will not return from their wait() call immediately, but only when the thread that called notify() or notify_all() finally relinquishes ownership of the lock.

The typical programming style using condition variables uses the lock to synchronize access to some shared state; threads that are interested in a particular change of state call wait() repeatedly until they see the desired state, while threads that modify the state call notify() or notify_all() when they change the state in such a way that it could possibly be a desired state for one of the waiters. For example, the following code is a generic producer-consumer situation with unlimited buffer capacity:

# Consume one item
with cv:
    while not an_item_is_available():
        cv.wait()
    get_an_available_item()

# Produce one item
with cv:
    make_an_item_available()
    cv.notify()

The while loop checking for the application’s condition is necessary because wait() can return after an arbitrary long time, and the condition which prompted the notify() call may no longer hold true. This is inherent to multi-threaded programming. The wait_for() method can be used to automate the condition checking, and eases the computation of timeouts:

# Consume an item
with cv:
    cv.wait_for(an_item_is_available)
    get_an_available_item()

To choose between notify() and notify_all(), consider whether one state change can be interesting for only one or several waiting threads. E.g. in a typical producer-consumer situation, adding one item to the buffer only needs to wake up one consumer thread.

class threading.Condition(lock=None)

This class implements condition variable objects. A condition variable allows one or more threads to wait until they are notified by another thread.

If the lock argument is given and not None, it must be a Lock or RLock object, and it is used as the underlying lock. Otherwise, a new RLock object is created and used as the underlying lock.

Modifié dans la version 3.3: changed from a factory function to a class.

acquire(*args)

Acquire the underlying lock. This method calls the corresponding method on the underlying lock; the return value is whatever that method returns.

release()

Release the underlying lock. This method calls the corresponding method on the underlying lock; there is no return value.

wait(timeout=None)

Wait until notified or until a timeout occurs. If the calling thread has not acquired the lock when this method is called, a RuntimeError is raised.

This method releases the underlying lock, and then blocks until it is awakened by a notify() or notify_all() call for the same condition variable in another thread, or until the optional timeout occurs. Once awakened or timed out, it re-acquires the lock and returns.

When the timeout argument is present and not None, it should be a floating point number specifying a timeout for the operation in seconds (or fractions thereof).

When the underlying lock is an RLock, it is not released using its release() method, since this may not actually unlock the lock when it was acquired multiple times recursively. Instead, an internal interface of the RLock class is used, which really unlocks it even when it has been recursively acquired several times. Another internal interface is then used to restore the recursion level when the lock is reacquired.

The return value is True unless a given timeout expired, in which case it is False.

Modifié dans la version 3.2: Previously, the method always returned None.

wait_for(predicate, timeout=None)

Wait until a condition evaluates to true. predicate should be a callable which result will be interpreted as a boolean value. A timeout may be provided giving the maximum time to wait.

This utility method may call wait() repeatedly until the predicate is satisfied, or until a timeout occurs. The return value is the last return value of the predicate and will evaluate to False if the method timed out.

Ignoring the timeout feature, calling this method is roughly equivalent to writing:

while not predicate():
    cv.wait()

Therefore, the same rules apply as with wait(): The lock must be held when called and is re-acquired on return. The predicate is evaluated with the lock held.

Nouveau dans la version 3.2.

notify(n=1)

By default, wake up one thread waiting on this condition, if any. If the calling thread has not acquired the lock when this method is called, a RuntimeError is raised.

This method wakes up at most n of the threads waiting for the condition variable; it is a no-op if no threads are waiting.

The current implementation wakes up exactly n threads, if at least n threads are waiting. However, it’s not safe to rely on this behavior. A future, optimized implementation may occasionally wake up more than n threads.

Note: an awakened thread does not actually return from its wait() call until it can reacquire the lock. Since notify() does not release the lock, its caller should.

notify_all()

Wake up all threads waiting on this condition. This method acts like notify(), but wakes up all waiting threads instead of one. If the calling thread has not acquired the lock when this method is called, a RuntimeError is raised.

17.1.6. Semaphore Objects

This is one of the oldest synchronization primitives in the history of computer science, invented by the early Dutch computer scientist Edsger W. Dijkstra (he used the names P() and V() instead of acquire() and release()).

A semaphore manages an internal counter which is decremented by each acquire() call and incremented by each release() call. The counter can never go below zero; when acquire() finds that it is zero, it blocks, waiting until some other thread calls release().

Semaphores also support the context management protocol.

class threading.Semaphore(value=1)

This class implements semaphore objects. A semaphore manages an atomic counter representing the number of release() calls minus the number of acquire() calls, plus an initial value. The acquire() method blocks if necessary until it can return without making the counter negative. If not given, value defaults to 1.

The optional argument gives the initial value for the internal counter; it defaults to 1. If the value given is less than 0, ValueError is raised.

Modifié dans la version 3.3: changed from a factory function to a class.

acquire(blocking=True, timeout=None)

Acquire a semaphore.

When invoked without arguments:

If the internal counter is larger than zero on entry, decrement it by one and return true immediately.

If the internal counter is zero on entry, block until awoken by a call to release(). Once awoken (and the counter is greater than 0), decrement the counter by 1 and return true. Exactly one thread will be awoken by each call to release(). The order in which threads are awoken should not be relied on.

When invoked with blocking set to false, do not block. If a call without an argument would block, return false immediately; otherwise, do the same thing as when called without arguments, and return true.

When invoked with a timeout other than None, it will block for at most timeout seconds. If acquire does not complete successfully in that interval, return false. Return true otherwise.

Modifié dans la version 3.2: Le paramètre timeout est nouveau.

release()

Release a semaphore, incrementing the internal counter by one. When it was zero on entry and another thread is waiting for it to become larger than zero again, wake up that thread.

class threading.BoundedSemaphore(value=1)

Class implementing bounded semaphore objects. A bounded semaphore checks to make sure its current value doesn’t exceed its initial value. If it does, ValueError is raised. In most situations semaphores are used to guard resources with limited capacity. If the semaphore is released too many times it’s a sign of a bug. If not given, value defaults to 1.

Modifié dans la version 3.3: changed from a factory function to a class.

17.1.6.1. Semaphore Example

Semaphores are often used to guard resources with limited capacity, for example, a database server. In any situation where the size of the resource is fixed, you should use a bounded semaphore. Before spawning any worker threads, your main thread would initialize the semaphore:

maxconnections = 5
# ...
pool_sema = BoundedSemaphore(value=maxconnections)

Once spawned, worker threads call the semaphore’s acquire and release methods when they need to connect to the server:

with pool_sema:
    conn = connectdb()
    try:
        # ... use connection ...
    finally:
        conn.close()

The use of a bounded semaphore reduces the chance that a programming error which causes the semaphore to be released more than it’s acquired will go undetected.

17.1.7. Event Objects

This is one of the simplest mechanisms for communication between threads: one thread signals an event and other threads wait for it.

An event object manages an internal flag that can be set to true with the set() method and reset to false with the clear() method. The wait() method blocks until the flag is true.

class threading.Event

Class implementing event objects. An event manages a flag that can be set to true with the set() method and reset to false with the clear() method. The wait() method blocks until the flag is true. The flag is initially false.

Modifié dans la version 3.3: changed from a factory function to a class.

is_set()

Return true if and only if the internal flag is true.

set()

Set the internal flag to true. All threads waiting for it to become true are awakened. Threads that call wait() once the flag is true will not block at all.

clear()

Reset the internal flag to false. Subsequently, threads calling wait() will block until set() is called to set the internal flag to true again.

wait(timeout=None)

Block until the internal flag is true. If the internal flag is true on entry, return immediately. Otherwise, block until another thread calls set() to set the flag to true, or until the optional timeout occurs.

When the timeout argument is present and not None, it should be a floating point number specifying a timeout for the operation in seconds (or fractions thereof).

This method returns true if and only if the internal flag has been set to true, either before the wait call or after the wait starts, so it will always return True except if a timeout is given and the operation times out.

Modifié dans la version 3.1: Previously, the method always returned None.

17.1.8. Timer Objects

This class represents an action that should be run only after a certain amount of time has passed — a timer. Timer is a subclass of Thread and as such also functions as an example of creating custom threads.

Timers are started, as with threads, by calling their start() method. The timer can be stopped (before its action has begun) by calling the cancel() method. The interval the timer will wait before executing its action may not be exactly the same as the interval specified by the user.

Par exemple :

def hello():
    print("hello, world")

t = Timer(30.0, hello)
t.start()  # after 30 seconds, "hello, world" will be printed

class threading.Timer(interval, function, args=None, kwargs=None)

Create a timer that will run function with arguments args and keyword arguments kwargs, after interval seconds have passed. If args is None (the default) then an empty list will be used. If kwargs is None (the default) then an empty dict will be used.

Modifié dans la version 3.3: changed from a factory function to a class.

cancel()

Stop the timer, and cancel the execution of the timer’s action. This will only work if the timer is still in its waiting stage.

17.1.9. Barrier Objects

Nouveau dans la version 3.2.

This class provides a simple synchronization primitive for use by a fixed number of threads that need to wait for each other. Each of the threads tries to pass the barrier by calling the wait() method and will block until all of the threads have made their wait() calls. At this point, the threads are released simultaneously.

The barrier can be reused any number of times for the same number of threads.

As an example, here is a simple way to synchronize a client and server thread:

b = Barrier(2, timeout=5)

def server():
    start_server()
    b.wait()
    while True:
        connection = accept_connection()
        process_server_connection(connection)

def client():
    b.wait()
    while True:
        connection = make_connection()
        process_client_connection(connection)

class threading.Barrier(parties, action=None, timeout=None)

Create a barrier object for parties number of threads. An action, when provided, is a callable to be called by one of the threads when they are released. timeout is the default timeout value if none is specified for the wait() method.

wait(timeout=None)

Pass the barrier. When all the threads party to the barrier have called this function, they are all released simultaneously. If a timeout is provided, it is used in preference to any that was supplied to the class constructor.

The return value is an integer in the range 0 to parties – 1, different for each thread. This can be used to select a thread to do some special housekeeping, e.g.:

i = barrier.wait()
if i == 0:
    # Only one thread needs to print this
    print("passed the barrier")

If an action was provided to the constructor, one of the threads will have called it prior to being released. Should this call raise an error, the barrier is put into the broken state.

If the call times out, the barrier is put into the broken state.

This method may raise a BrokenBarrierError exception if the barrier is broken or reset while a thread is waiting.

reset()

Return the barrier to the default, empty state. Any threads waiting on it will receive the BrokenBarrierError exception.

Note that using this function may can require some external synchronization if there are other threads whose state is unknown. If a barrier is broken it may be better to just leave it and create a new one.

abort()

Put the barrier into a broken state. This causes any active or future calls to wait() to fail with the BrokenBarrierError. Use this for example if one of the needs to abort, to avoid deadlocking the application.

It may be preferable to simply create the barrier with a sensible timeout value to automatically guard against one of the threads going awry.

parties

The number of threads required to pass the barrier.

n_waiting

The number of threads currently waiting in the barrier.

broken

A boolean that is True if the barrier is in the broken state.

exception threading.BrokenBarrierError

This exception, a subclass of RuntimeError, is raised when the Barrier object is reset or broken.

17.1.10. Using locks, conditions, and semaphores in the with statement

All of the objects provided by this module that have acquire() and release() methods can be used as context managers for a with statement. The acquire() method will be called when the block is entered, and release() will be called when the block is exited. Hence, the following snippet:

with some_lock:
    # do something...

est équivalente à :

some_lock.acquire()
try:
    # do something...
finally:
    some_lock.release()

Currently, Lock, RLock, Condition, Semaphore, and BoundedSemaphore objects may be used as with statement context managers.

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17.2. multiprocessing — Parallélisme par processus

Code source : Lib/multiprocessing/ [https://github.com/python/cpython/tree/3.6/Lib/multiprocessing/]

17.2.1. Introduction

multiprocessing est un paquet qui permet l’instanciation de processus via la même API que le module threading. Le paquet multiprocessing offre à la fois des possibilités de programmation concurrente locale ou à distance, contournant les problèmes du Global Interpreter Lock en utilisant des processus plutôt que des fils d’exécution. Ainsi, le module multiprocessing permet au développeur de bénéficier entièrement des multiples processeurs sur une machine. Il tourne à la fois sur les systèmes Unix et Windows.

Le module multiprocessing introduit aussi des API sans analogues dans le module threading. Un exemple est l’objet Pool qui offre une manière pratique de paralléliser l’exécution d’une fonction sur de multiples valeurs d’entrée, distribuant ces valeurs entre les processus (parallélisme de données). L’exemple suivant présente la manière classique de définir une telle fonction dans un module afin que les processus fils puissent importer ce module avec succès. L’exemple basique de parallélisme de données utilise Pool,

from multiprocessing import Pool

def f(x):
    return x*x

if __name__ == '__main__':
    with Pool(5) as p:
        print(p.map(f, [1, 2, 3]))

affiche sur la sortie standard

[1, 4, 9]

17.2.1.1. La classe Process

Dans le module multiprocessing, les processus sont instanciés en créant un objet Process et en appelant sa méthode start(). La classe Process suit la même API que threading.Thread. Un exemple trivial d’un programme multi-processus est

from multiprocessing import Process

def f(name):
    print('hello', name)

if __name__ == '__main__':
    p = Process(target=f, args=('bob',))
    p.start()
    p.join()

Pour afficher les IDs des processus impliqués, voici un exemple plus étoffé :

from multiprocessing import Process
import os

def info(title):
    print(title)
    print('module name:', __name__)
    print('parent process:', os.getppid())
    print('process id:', os.getpid())

def f(name):
    info('function f')
    print('hello', name)

if __name__ == '__main__':
    info('main line')
    p = Process(target=f, args=('bob',))
    p.start()
    p.join()

La nécessité de la ligne if __name__ == '__main__' est expliquée par Lignes directrices de programmation.

17.2.1.2. Contextes et méthodes de démarrage

Suivant la plateforme, multiprocessing gère trois manières de démarrer un processus. Ces méthodes de démarrage sont

spawn

Le processus parent démarre un processus neuf avec un interpréteur Python. Le processus fils hérite uniquement des ressources nécessaires pour exécuter la méthode run() de l’objet associé au processus. En particulier, les descripteurs de fichiers superflus et gérés par le processus parent ne sont pas hérités. Démarrer un processus en utilisant cette méthode est plutôt lent par rapport à fork ou forkserver.

Disponible sur Unix et Windows. Par défaut sur Windows.

fork

Le processus parent utilise os.fork() pour forker l’interpréteur Python. Le processus fils, quand il démarre, est effectivement identique au processus parent. Toutes les ressources du parent sont héritées par le fils. Notez qu’il est problématique de forker sans danger un processus multi-threadé.

Disponible uniquement sous Unix. Par défaut sous Unix.

forkserver

Quand le programme démarre et choisit la méthode de démarrage forkserver, un processus serveur est lancé. Dès lors, chaque fois qu’un nouveau processus est nécessaire, le processus parent se connecte au serveur et lui demande de forker un nouveau processus. Le processus serveur de fork n’utilisant qu’un seul fil d’exécution, il peut utiliser os.fork() sans danger. Les ressources superflues ne sont pas héritées.

Disponible sur les plateformes Unix qui acceptent le passage de descripteurs de fichiers à travers des tubes (pipes) Unix.

Modifié dans la version 3.4: spawn ajouté à toutes les plateformes Unix, et forkserver ajouté à certaines plateformes Unix. Les processus fils n’héritent plus de tous les descripteurs héritables du parent sous Windows.

Sous Unix, utiliser les méthodes de démarrage spawn ou forkserver démarre aussi un processus semaphore tracker qui traque les sémaphores nommés non libérés créés par les processus du programme. Quand tous les processus sont terminés, le traqueur de sémaphores libère les sémaphores restants. Généralement il ne devrait pas y en avoir, mais si un processus a été tué par un signal, certains sémaphores ont pu « fuiter ». (Libérer les sémaphores nommés est une affaire sérieuse puisque le système n’en autorise qu’un certain nombre, et qu’ils ne seront pas automatiquement libérés avant le prochain redémarrage.)

Pour sélectionner une méthode de démarrage, utilisez la fonction set_start_method() dans la clause if __name__ == '__main__' du module principal. Par exemple :

import multiprocessing as mp

def foo(q):
    q.put('hello')

if __name__ == '__main__':
    mp.set_start_method('spawn')
    q = mp.Queue()
    p = mp.Process(target=foo, args=(q,))
    p.start()
    print(q.get())
    p.join()

set_start_method() ne doit pas être utilisée plus d’une fois dans le programme.

Alternativement, vous pouvez utiliser get_context() pour obtenir un contexte. Les contextes ont la même API que le module multiprocessing, et permettent l’utilisation de plusieurs méthodes de démarrage dans un même programme.

import multiprocessing as mp

def foo(q):
    q.put('hello')

if __name__ == '__main__':
    ctx = mp.get_context('spawn')
    q = ctx.Queue()
    p = ctx.Process(target=foo, args=(q,))
    p.start()
    print(q.get())
    p.join()

Notez que les objets relatifs à un contexte ne sont pas forcément compatibles avec les processus d’un contexte différent. En particulier, les verrous créés avec le contexte fork ne peuvent pas être passés aux processus lancés avec les méthodes spawn ou forkserver.

Une bibliothèque qui veut utiliser une méthode de démarrage particulière devrait probablement faire appel à get_context() pour éviter d’interférer avec le choix de l’utilisateur de la bibliothèque.

17.2.1.3. Échange d’objets entre les processus

multiprocessing gère deux types de canaux de communication entre les processus :

Queues

La classe Queue est un clone assez proche de queue.Queue. Par exemple :

from multiprocessing import Process, Queue

def f(q):
    q.put([42, None, 'hello'])

if __name__ == '__main__':
    q = Queue()
    p = Process(target=f, args=(q,))
    p.start()
    print(q.get())    # prints "[42, None, 'hello']"
    p.join()

Les queues peuvent être utilisées par plusieurs fils d’exécution ou processus.

Tubes (pipes)

La fonction Pipe() renvoie une paire d’objets de connexion connectés à un tube qui est par défaut à double-sens. Par exemple :

from multiprocessing import Process, Pipe

def f(conn):
    conn.send([42, None, 'hello'])
    conn.close()

if __name__ == '__main__':
    parent_conn, child_conn = Pipe()
    p = Process(target=f, args=(child_conn,))
    p.start()
    print(parent_conn.recv())   # prints "[42, None, 'hello']"
    p.join()

Les deux objets de connexion renvoyés par Pipe() représentent les deux bouts d’un tube. Chaque objet de connexion possède (entre autres) des méthodes send() et recv(). Notez que les données d’un tube peuvent être corrompues si deux processus (ou fils d’exécution) essaient de lire ou d’écrire sur le même bout du tube en même temps. Évidemment il n’y a pas de risque de corruption si les processus utilisent deux bouts différents en même temps.

17.2.1.4. Synchronisation entre processus

multiprocessing contient des équivalents à toutes les primitives de synchronisation de threading. Par exemple il est possible d’utiliser un verrou pour s’assurer qu’un seul processus à la fois écrit sur la sortie standard :

from multiprocessing import Process, Lock

def f(l, i):
    l.acquire()
    try:
        print('hello world', i)
    finally:
        l.release()

if __name__ == '__main__':
    lock = Lock()

    for num in range(10):
        Process(target=f, args=(lock, num)).start()

Sans le verrou, les sorties des différents processus risquent d’être mélangées.

17.2.1.5. Partager un état entre les processus

Comme mentionné plus haut, il est généralement préférable d’éviter autant que possible d’utiliser des états partagés en programmation concurrente. C’est particulièrement vrai quand plusieurs processus sont utilisés.

Cependant, si vous devez réellement partager des données, multiprocessing permet de le faire de deux manières.

Mémoire partagée

Les données peuvent être stockées dans une mémoire partagée en utilisant des Value ou des Array. Par exemple, le code suivant

from multiprocessing import Process, Value, Array

def f(n, a):
    n.value = 3.1415927
    for i in range(len(a)):
        a[i] = -a[i]

if __name__ == '__main__':
    num = Value('d', 0.0)
    arr = Array('i', range(10))

    p = Process(target=f, args=(num, arr))
    p.start()
    p.join()

    print(num.value)
    print(arr[:])

affiche

3.1415927
[0, -1, -2, -3, -4, -5, -6, -7, -8, -9]

Les arguments 'd' et 'i' utilisés à la création des num et arr` sont des codes de types tels qu’utilisés par le module array : 'd' indique un flottant double-précision et 'i' indique un entier signé. Ces objets partagés seront sûr d’utilisation entre processus et fils d’exécution.

Pour plus de flexibilité dans l’utilisation de mémoire partagée, vous pouvez utiliser le module multiprocessing.sharedctypes qui permet la création d’objets arbitraires ctypes alloués depuis la mémoire partagée.

Processus serveur

Un objet gestionnaire renvoyé par Manager() contrôle un processus serveur qui détient les objets Python et autorise les autres processus à les manipuler à l’aide de mandataires.

Un gestionnaire renvoyé par Manager() supportera les types list, dict, Namespace, Lock, RLock, Semaphore, BoundedSemaphore, Condition, Event, Barrier, Queue, Value et Array. Par exemple,

from multiprocessing import Process, Manager

def f(d, l):
    d[1] = '1'
    d['2'] = 2
    d[0.25] = None
    l.reverse()

if __name__ == '__main__':
    with Manager() as manager:
        d = manager.dict()
        l = manager.list(range(10))

        p = Process(target=f, args=(d, l))
        p.start()
        p.join()

        print(d)
        print(l)

affiche

{0.25: None, 1: '1', '2': 2}
[9, 8, 7, 6, 5, 4, 3, 2, 1, 0]

Les processus serveurs de gestionnaires sont plus flexibles que les mémoires partagées parce qu’ils peuvent gérer des types d’objets arbitraires. Aussi, un gestionnaire unique peut être partagé par les processus sur différentes machines à travers le réseau. Cependant, ils sont plus lents que les mémoires partagées.

17.2.1.6. Utiliser un réservoir de workers

La classe Pool représente une pool de processus de travail. Elle possède des méthodes qui permettent aux tâches d’être déchargées vers les processus de travail de différentes manières.

Par exemple :

from multiprocessing import Pool, TimeoutError
import time
import os

def f(x):
    return x*x

if __name__ == '__main__':
    # start 4 worker processes
    with Pool(processes=4) as pool:

        # print "[0, 1, 4,..., 81]"
        print(pool.map(f, range(10)))

        # print same numbers in arbitrary order
        for i in pool.imap_unordered(f, range(10)):
            print(i)

        # evaluate "f(20)" asynchronously
        res = pool.apply_async(f, (20,))      # runs in *only* one process
        print(res.get(timeout=1))             # prints "400"

        # evaluate "os.getpid()" asynchronously
        res = pool.apply_async(os.getpid, ()) # runs in *only* one process
        print(res.get(timeout=1))             # prints the PID of that process

        # launching multiple evaluations asynchronously *may* use more processes
        multiple_results = [pool.apply_async(os.getpid, ()) for i in range(4)]
        print([res.get(timeout=1) for res in multiple_results])

        # make a single worker sleep for 10 secs
        res = pool.apply_async(time.sleep, (10,))
        try:
            print(res.get(timeout=1))
        except TimeoutError:
            print("We lacked patience and got a multiprocessing.TimeoutError")

        print("For the moment, the pool remains available for more work")

    # exiting the 'with'-block has stopped the pool
    print("Now the pool is closed and no longer available")

Notez que les méthodes d’une pool ne devraient être utilisées que par le processus qui l’a créée.

Note

Fonctionnellement ce paquet exige que que le module __main__ soit importable par les fils. Cela est expliqué sur la page Lignes directrices de programmation, il est cependant utile de le rappeler ici. Cela signifie que certains exemples, comme les exemples utilisant multiprocessing.pool.Pool, ne fonctionnent pas dans l’interpréteur interactif. Par exemple :

>>> from multiprocessing import Pool
>>> p = Pool(5)
>>> def f(x):
...     return x*x
...
>>> p.map(f, [1,2,3])
Process PoolWorker-1:
Process PoolWorker-2:
Process PoolWorker-3:
Traceback (most recent call last):
AttributeError: 'module' object has no attribute 'f'
AttributeError: 'module' object has no attribute 'f'
AttributeError: 'module' object has no attribute 'f'

(Si vous essayez ce code, il affichera trois traces d’appels complètes entrelacées de manière semi-aléatoire, et vous aurez alors à stopper le processus maître.)

17.2.2. Référence

Le paquet multiprocessing reproduit en grande partie l’API du module threading.

17.2.2.1. Process et exceptions

class multiprocessing.Process(group=None, target=None, name=None, args=(), kwargs={}, *, daemon=None)

Les objets process représentent une activité exécutée dans un processus séparé. La classe Process a des équivalents à toutes les méthodes de threading.Thread.

Le constructeur doit toujours être appelé avec des arguments nommés. group devrait toujours être None ; il existe uniquement pour la compatibilité avec threading.Thread. target est l’objet appelable qui est invoqué par la méthode run(). Il vaut ``None`() par défaut, signifiant que rien n’est appelé. name est le nom du processus (voir name pour plus de détails). args est le tuple d’arguments pour l’invocation de la cible. kwargs est le dictionnaire des arguments nommés pour l’invocation de la cible. S’il est fourni, l’argument nommé daemon met l’option daemon du processus à True ou False. S’il est None (par défaut), l’option est héritée par le processus créateur.

Par défaut, aucun argument n’est passé à target.

Si une sous-classe redéfinit le constructeur, elle doit s’assurer d’invoquer le constructeur de la classe de base (Process.__init__()) avant de faire autre chose du processus.

Modifié dans la version 3.3: Ajout de l’argument daemon.

run()

Méthode représentant l’activité du processus.

Vous pouvez redéfinir cette méthode dans une sous-classe. La méthode standard run() invoque l’objet appelable passé au constructeur comme argument target, si fourni, avec les arguments séquentiels et nommés respectivement pris depuis les paramètres args et kwargs.

start()

Démarre l’activité du processus.

Elle doit être appelée au plus une fois par objet processus. Elle s’arrange pour que la méthode run() de l’objet soit invoquée dans un processus séparé.

join([timeout])

Si l’argument optionnel timeout est None (par défaut), la méthode bloque jusqu’à ce que le processus dont la méthode join() a été appelée se termine. Si timeout est un nombre positif, elle bloque au maximum pendant timeout secondes. Notez que la méthode renvoie None si le processus se termine ou si le temps d’exécution expire. Vérifiez l’attribut exitcode du processus pour déterminer s’il s’est terminé.

join peut être appelée plusieurs fois sur un même processus.

Un processus ne peut pas s’attendre lui-même car cela causerait un interblocage. C’est une erreur d’essayer d’attendre un processus avant qu’il ne soit démarré.

name

Le nom du processus. Le nom est une chaîne de caractères utilisée uniquement pour l’identification du processus. Il n’a pas de sémantique. Plusieurs processus peuvent avoir le même nom.

Le nom initial est déterminé par le constructeur. Si aucun nom explicite n’est fourni au constructeur, un nom de la forme « Process-N₁:N₂:…:Nk » est construit, où chaque Nk est le N-ième enfant de son parent.

is_alive()

Renvoie vrai si le processus est en vie, faux sinon.

Grossièrement, un objet processus est en vie depuis le moment où la méthode start() finit de s’exécuter jusqu’à ce que le processus fils se termine.

daemon

L’option daemon du processus, une valeur booléenne. L’option doit être réglée avant que la méthode start() ne soit appelée.

La valeur initiale est héritée par le processus créateur.

Quand un processus se ferme, il tente de terminer tous ses processus enfants daemon.

Notez qu’un processus daemon n’est pas autorisé à créer des processus fils. Sinon un processus daemon laisserait ses enfants orphelins lorsqu’il se termine par la fermeture de son parent. De plus, ce ne sont pas des daemons ou services Unix, ce sont des processus normaux qui seront terminés (et non attendus) si un processus non daemon se ferme.

En plus de l’API threading.Thread, les objets Process supportent aussi les attributs et méthodes suivants :

pid

Renvoie l’ID du processus. Avant que le processus ne soit lancé, la valeur est None.

exitcode

Le code de fermeture de l’enfant. La valeur est None si le processus ne s’est pas encore terminé. Une valeur négative -N indique que le fils a été terminé par un signal N.

authkey

La clé d’authentification du processus (une chaîne d’octets).

Quand multiprocessing est initialisé, une chaîne aléatoire est assignée au processus principal, en utilisant os.urandom().

Quand un objet Process est créé, il hérité de la clé d’authentification de son parent, bien que cela puisse être changé à l’aide du paramètre authkey pour une autre chaîne d’octets.

Voir Clés d’authentification.

sentinel

Un identifiant numérique de l’objet système qui devient « prêt » quand le processus se termine.

Vous pouvez utiliser cette valeur si vous voulez attendre plusieurs événements à la fois en utilisant multiprocessing.connection.wait(). Autrement appeler join() est plus simple.

Sous Windows, c’est un mécanisme de l’OS utilisable avec les familles d’appels API WaitForSingleObject et WaitForMultipleObjects. Sous Unix, c’est un descripteur de fichier utilisable avec les primitives sur module select.

Nouveau dans la version 3.3.

terminate()

Termine le processus. Sous Unix cela est réalisé à l’aide d’un signal SIGTERM, sous Windows TerminateProcess() est utilisé. Notez que les gestionnaires de sortie, les clauses finally etc. ne sont pas exécutées.

Notez que les descendants du processus ne seront pas terminés – ils deviendront simplement orphelins.

Avertissement

Si cette méthode est utilisée quand le processus associé utilise un tube ou une queue, alors le tube ou la queue sont susceptibles d’être corrompus et peuvent devenir inutilisables par les autres processus. De façon similaire, si le processus a acquis un verrou, un sémaphore ou autre, alors le terminer est susceptible de provoquer des blocages dans les autres processus.

Notez que les méthodes start(), join(), is_alive(), terminate() et exitcode ne devraient être appelées que par le processus ayant créé l’objet process.

Exemple d’utilisation de quelques méthodes de Process :

>>> import multiprocessing, time, signal
>>> p = multiprocessing.Process(target=time.sleep, args=(1000,))
>>> print(p, p.is_alive())
<Process(Process-1, initial)> False
>>> p.start()
>>> print(p, p.is_alive())
<Process(Process-1, started)> True
>>> p.terminate()
>>> time.sleep(0.1)
>>> print(p, p.is_alive())
<Process(Process-1, stopped[SIGTERM])> False
>>> p.exitcode == -signal.SIGTERM
True

exception multiprocessing.ProcessError

La classe de base de toutes les exceptions de multiprocessing.

exception multiprocessing.BufferTooShort

Exception levée par Connection.recv_bytes_into() quand l’objet tampon fourni est trop petit pour le message à lire.

Si e est une instance de BufferTooShort alors e.args[0] donnera un message sous forme d’une chaîne d’octets.

exception multiprocessing.AuthenticationError

Levée quand il y a une erreur d’authentification.

exception multiprocessing.TimeoutError

Levée par les méthodes avec temps d’exécution limité, quand ce temps expire.

17.2.2.2. Tubes (pipes) et Queues

Quand de multiples processus sont utilisés, de l’échange de messages est souvent mis en place pour la communication entre processus et éviter d’avoir à utiliser des primitives de synchronisation telles que des verrous.

Pour échanger des messages vous pouvez utiliser un Pipe() (pour une connexion entre deux processus) ou une queue (qui autorise de multiples producteurs et consommateurs).

Les types Queue, SimpleQueue et JoinableQueue sont des queues FIFO multi-producteurs et multi-consommateurs modelées sur la classe queue.Queue de la bibliothèque standard. Elles diffèrent par l’absence dans Queue des méthodes task_done() et join() introduites dans la classe queue.Queue par Python 2.5.

Si vous utilisez JoinableQueue alors vous devez appeler JoinableQueue.task_done() pour chaque tâche retirée de la queue, sans quoi le sémaphore utilisé pour compter le nombre de tâches non accomplies pourra éventuellement déborder, levant une exception.

Notez que vous pouvez aussi créer une queue partagée en utilisant un objet gestionnaire – voir Gestionnaires.

Note

multiprocessing utilise les exceptions habituelles queue.Empty et queue.Full pour signaler un dépassement du temps maximal autorisé. Elles ne sont pas disponibles dans l’espace de nommage multiprocessing donc vous devez les importer depuis le module queue.

Note

Quand un objet est placé dans une queue, l’objet est sérialisé par pickle et un fil d’exécution en arrière-plan transmettra ensuite les données sérialisées sur un tube sous-jacent. Cela a certaines conséquences qui peuvent être un peu surprenantes, mais ne devrait causer aucune difficultés pratiques – si elles vous embêtent vraiment, alors vous pouvez à la place utiliser une queue créée avec un manager.

Après avoir placé un objet dans une queue vide il peut y avoir un délai infinitésimal avant que la méthode empty() de la queue renvoie False et que get_nowait() renvoie une valeur sans lever de queue.Empty.

Si plusieurs processus placent des objets dans la queue, il est possible pour les objets d’être reçus de l’autre côté dans le désordre. Cependant, les objets placés par un même processus seront toujours récupérés dans l’ordre attendu.

Avertissement

Si un processus est tué à l’aide de Process.terminate() ou os.kill() pendant qu’il tente d’utiliser une Queue, alors les données de la queue peuvent être corrompues. Cela peut par la suite causer des levées d’exceptions dans les autres processus quand ils tenteront d’utiliser la queue.

Avertissement

Comme mentionné plus haut, si un processus fils a placé des éléments dans la queue (et qu’il n’a pas utilisé JoinableQueue.cancel_join_thread), alors le processus ne se terminera pas tant que les éléments placés dans le tampon n’auront pas été transmis au tube.

Cela signifie que si vous essayez d’attendre ce processus vous pouvez obtenir un interblocage, à moins que vous ne soyez sûr que tous les éléments placés dans la queue ont été consommés. De même, si le processus fils n’est pas un daemon alors le processus parent pourrait bloquer à la fermeture quand il tentera d’attendre tous ses enfants non daemons.

Notez que la queue créée à l’aide d’un gestionnaire n’a pas ce problème. Voir Lignes directrices de programmation.

Pour un exemple d’utilisation de queues pour de la communication entre les processus, voir Exemples.

multiprocessing.Pipe([duplex])

Renvoie une paire (conn1, conn2) d’objets Connection représentant les bouts d’un tube.

Si duplex vaut True (par défaut), alors le tube est bidirectionnel. Si duplex vaut False il est unidirectionnel : conn1 ne peut être utilisé que pour recevoir des messages et conn2 que pour en envoyer.

class multiprocessing.Queue([maxsize])

Renvoie une queue partagée entre les processus utilisant un tube et quelques verrous/sémaphores. Quand un processus place initialement un élément sur la queue, un fil d’exécution feeder est démarré pour transférer les objets du tampon vers le tube.

Les exceptions habituelles queue.Empty et queue.Full du module queue de la bibliothèque standard sont levées pour signaler les timeouts.

Queue implémente toutes les méthodes de queue.Queue à l’exception de task_done() et join().

qsize()

Renvoie la taille approximative de la queue. Ce nombre n’est pas fiable en raison des problématiques de multithreading et multiprocessing.

Notez que cela peut lever une NotImplementedError sous les plateformes Unix telles que Mac OS X où sem_getvalue() n’est pas implémentée.

empty()

Renvoie True si la queue est vide, False sinon. Cette valeur n’est pas fiable en raison des problématiques de multithreading et multiprocessing.

full()

Renvoie True si la queue est pleine, False sinon. Cette valeur n’est pas fiable en raison des problématiques de multithreading et multiprocessing.

put(obj[, block[, timeout]])

Place obj dans la queue. Si l’argument optionnel block vaut True (par défaut) est que timeout est None (par défaut), bloque jusqu’à ce qu’un slot libre soit disponible. Si timeout est un nombre positif, la méthode bloquera au maximum timeout secondes et lèvera une exception queue.Full si aucun slot libre n’a été trouvé dans le temps imparti. Autrement (block vaut False), place un élément dans la queue si un slot libre est immédiatement disponible, ou lève une exception queue.Full dans le cas contraire (timeout est ignoré dans ce cas).

put_nowait(obj)

Équivalent à put(obj, False).

get([block[, timeout]])

Retire et renvoie un élément de la queue. Si l’argument optionnel block vaut True (par défaut) et que timeout est None (par défaut), bloque jusqu’à ce qu’un élément soit disponible. Si timeout (le délai maximal autorisé) est un nombre positif, la méthode bloquera au maximum timeout secondes et lèvera une exception queue.Empty si aucun élément n’est disponible dans le temps imparti. Autrement (block vaut False), renvoie un élément s’il est immédiatement disponible, ou lève une exception queue.Empty dans le cas contraire (timeout est ignoré dans ce cas).

get_nowait()

Équivalent à get(False).

multiprocessing.Queue possède quelques méthodes additionnelles non présentes dans queue.Queue. Ces méthodes ne sont habituellement pas nécessaires pour la plupart des codes :

close()

Indique que plus aucune donnée ne peut être placée sur la queue par le processus courant. Le fil d’exécution en arrière-plan se terminera quand il aura transféré toutes les données du tampon vers le tube. Elle est appelée automatiquement quand la queue est collectée par le ramasse-miettes.

join_thread()

Attend le fil d’exécution d’arrière-plan. Elle peut seulement être utilisée une fois que close() a été appelée. Elle bloque jusqu’à ce que le fil d’arrière-plan se termine, assurant que toutes les données du tampon ont été transmises au tube.

Par défaut si un processus n’est pas le créateur de la queue alors à la fermeture elle essaiera d’attendre le fil d’exécution d’arrière-plan de la queue. Le processus peut appeler cancel_join_thread() pour que join_thread() ne fasse rien.

cancel_join_thread()

Empêche join_thread() de bloquer. En particulier, cela empêche le fil d’arrière-plan d’être attendu automatiquement quand le processus se ferme – voir join_thread().

Un meilleur nom pour cette méthode pourrait être allow_exit_without_flush(). Cela peut provoquer des pertes de données placées dans la queue, et vous ne devriez certainement pas avoir besoin de l’utiliser. Elle n’est là que si vous souhaitez terminer immédiatement le processus sans transférer les données du tampon, et que vous ne vous inquiétez pas de perdre des données.

Note

Le fonctionnement de cette classe requiert une implémentation de sémaphore partagé sur le système d’exploitation hôte. Sans cela, la fonctionnalité sera désactivée et la tentative d’instancier une Queue lèvera une ImportError. Voir bpo-3770 [https://bugs.python.org/issue3770] pour plus d’informations. Cette remarque reste valable pour les autres types de queues spécialisées définies par la suite.

class multiprocessing.SimpleQueue

Un type de Queue simplifié, très proche d’un Pipe avec verrou.

empty()

Renvoie True si la queue est vide, False sinon.

get()

Supprime et renvoie un élément de la queue.

put(item)

Place item dans la queue.

class multiprocessing.JoinableQueue([maxsize])

JoinableQueue, une sous-classe de Queue, est une queue qui ajoute des méthodes task_done() et join().

task_done()

Indique qu’une tâche précédemment placée dans la queue est complétée. Utilisé par les consommateurs de la queue. Pour chaque get() utilisé pour récupérer une tâche, un appel ultérieur à task_done() indique à la queue que le traitement de la tâche est terminé.

Si un join() est actuellement bloquant, il se débloquera quand tous les éléments auront été traités (signifiant qu’un appel à task_done() a été reçu pour chaque élément ayant été placé via put() dans la queue).

Lève une exception ValueError si appelée plus de fois qu’il y avait d’éléments dans la file.

join()

Bloque jusqu’à ce que tous les éléments de la queue aient été récupérés et traités.

Le compteur des tâches non accomplies augmente chaque fois qu’un élément est ajouté à la queue. Le compteur redescend chaque fois qu’un consommateur appelle task_done() pour indiquer qu’un élément a été récupéré et que tout le travail qui le concerne est complété. Quand le compteur des tâches non accomplies atteint zéro, join() est débloquée.

17.2.2.3. Divers

multiprocessing.active_children()

Renvoie la liste de tous les enfants vivants du processus courant.

Appeler cette méthode provoque l’effet de bord d’attendre tout processus qui n’a pas encore terminé.

multiprocessing.cpu_count()

Renvoie le nombre de CPU sur le système.

Ce nombre n’est pas équivalent au nombre de CPUs que le processus courant peut utiliser. Le nombre de CPUs utilisables peut être obtenu avec len(os.sched_getaffinity(0))

Peut lever une NotImplementedError.

Voir aussi

os.cpu_count()

multiprocessing.current_process()

Renvoie l’objet Process correspondant au processus courant.

Un analogue à threading.current_thread().

multiprocessing.freeze_support()

Ajoute le support des programmes utilisant multiprocessing qui ont été gelés pour produire un exécutable Windows. (Testé avec py2exe, PyInstaller et cx_Freeze.)

Cette fonction doit être appelée juste après la ligne if __name__ == '__main__' du module principal. Par exemple :

from multiprocessing import Process, freeze_support

def f():
    print('hello world!')

if __name__ == '__main__':
    freeze_support()
    Process(target=f).start()

Si la ligne freeze_support() est omise, alors tenter de lancer l’exécutable gelé lèvera une RuntimeError.

Appeler freeze_support() n’a pas d’effet quand elle est invoquée sur un système d’exploitation autre que Windows. De plus, si le module est lancé normalement par l’interpréteur Python sous Windows (le programme n’a pas été gelé), alors freeze_support() n’a pas d’effet.

multiprocessing.get_all_start_methods()

Renvoie la liste des méthodes de démarrage supportées, la première étant celle par défaut. Les méthodes de démarrage possibles sont 'fork', 'spawn' et 'forkserver'. Sous Windows seule 'spawn' est disponible. Sous Unix 'fork' et 'spawn' sont disponibles, 'fork' étant celle par défaut.

Nouveau dans la version 3.4.

multiprocessing.get_context(method=None)

Renvoie un contexte ayant les mêmes attributs que le module multiprocessing.

Si method est None le contexte par défaut est renvoyé. Sinon method doit valoir 'fork', 'spawn' ou 'forkserver'. Une ValueError est levée si la méthode de démarrage spécifiée n’est pas disponible.

Nouveau dans la version 3.4.

multiprocessing.get_start_method(allow_none=False)

Renvoie le nom de la méthode de démarrage utilisée pour démarrer le processus.

Si le nom de la méthode n’a pas été fixé et que allow_none est faux, alors la méthode de démarrage est réglée à celle par défaut et son nom est renvoyé. Si la méthode n’a pas été fixée et que allow_none est vrai, None est renvoyé.

La valeur de retour peut être 'fork', 'spawn', 'forkserver' ou None. 'fork' est la valeur par défaut sous Unix, 'spawn' est celle sous Windows.

Nouveau dans la version 3.4.

multiprocessing.set_executable()

Définit le chemin de l’interpréteur Python à utiliser pour démarrer un processus fils. (Par défaut sys.executable est utilisé). Les intégrateurs devront probablement faire quelque chose comme

set_executable(os.path.join(sys.exec_prefix, 'pythonw.exe'))

avant de pouvoir créer des processus fils.

Modifié dans la version 3.4: Maintenant supporté sous Unix quand la méthode de démarrage 'spawn' est utilisée.

multiprocessing.set_start_method(method)

Règle la méthode qui doit être utilisée pour démarrer un processus fils. method peut être 'fork', 'spawn' ou 'forkserver'.

Notez que cette fonction ne devrait être appelée qu’une fois au plus, et l’appel devrait être protégé à l’intérieur d’une clause if __name__ == '__main__' dans le module principal.

Nouveau dans la version 3.4.

Note

multiprocessing ne contient pas d’analogues à threading.active_count(), threading.enumerate(), threading.settrace(), threading.setprofile(), threading.Timer, ou threading.local.

17.2.2.4. Objets de connexions

Les objets de connexion autorisent l’envoi et la réception d’objets sérialisables ou de chaînes de caractères. Ils peuvent être vus comme des interfaces de connexion (sockets) connectées orientées messages.

Les objets de connexion sont habituellement créés via Pipe – voir aussi Auditeurs et Clients.

class multiprocessing.connection.Connection

send(obj)

Envoie un objet sur l’autre bout de la connexion, qui devra être lu avec recv().

The object must be picklable. Very large pickles (approximately 32 MB+, though it depends on the OS) may raise a ValueError exception.

recv()

Renvoie un objet envoyé depuis l’autre bout de la connexion en utilisant send(). Bloque jusqu’à ce que quelque chose soit reçu. Lève une EOFError s’il n’y a plus rien à recevoir et que l’autre bout a été fermé.

fileno()

Renvoie le descripteur de fichier ou identifiant utilisé par la connexion.

close()

Ferme la connexion.

Elle est appelée automatiquement quand la connexion est collectée par le ramasse-miettes.

poll([timeout])

Renvoie vrai ou faux selon si des données sont disponibles à la lecture.

Si timeout n’est pas spécifié la méthode renverra immédiatement. Si timeout est un nombre alors il spécifie le temps maximum de blocage en secondes. Si timeout est None, un temps d’attente infini est utilisé.

Notez que plusieurs objets de connexions peuvent être attendus en même temps à l’aide de multiprocessing.connection.wait().

send_bytes(buffer[, offset[, size]])

Envoie des données binaires depuis un bytes-like object comme un message complet.

If offset is given then data is read from that position in buffer. If size is given then that many bytes will be read from buffer. Very large buffers (approximately 32 MB+, though it depends on the OS) may raise a ValueError exception

recv_bytes([maxlength])

Renvoie un message complet de données binaires envoyées depuis l’autre bout de la connexion comme une chaîne de caractères. Bloque jusqu’à ce qu’il y ait quelque chose à recevoir. Lève une EOFError s’il ne reste rien à recevoir et que l’autre côté de la connexion a été fermé.

Si maxlength est précisé que que le message est plus long que maxlength alors une OSError est levée et la connexion n’est plus lisible.

Modifié dans la version 3.3: Cette fonction levait auparavant une IOError, qui est maintenant un alias pour OSError.

recv_bytes_into(buffer[, offset])

Lit et stocke dans buffer un message complet de données binaires envoyées depuis l’autre bout de la connexion et renvoie le nombre d’octets du message. Bloque jusqu’à ce qu’il y ait quelque chose à recevoir. Lève une EOFError s’il ne reste rien à recevoir et que l’autre côté de la connexion a été fermé.

buffer doit être un bytes-like object accessible en écriture. Si offset est donné, le message sera écrit dans le tampon à partir de cette position. offset doit être un entier positif, inférieur à la taille de buffer (en octets).

Si le tampon est trop petit une exception BufferTooShort est levée et le message complet est accessible via e.args[0] où e est l’instance de l’exception.

Modifié dans la version 3.3: Les objets de connexions eux-mêmes peuvent maintenant être transférés entre les processus en utilisant Connection.send() et Connection.recv().

Nouveau dans la version 3.3: Les objets de connexions supportent maintenant le protocole des gestionnaires de contexte – voir Le type gestionnaire de contexte. __enter__() renvoie l’objet de connexion, et __exit__() appelle close().

Par exemple :

>>> from multiprocessing import Pipe
>>> a, b = Pipe()
>>> a.send([1, 'hello', None])
>>> b.recv()
[1, 'hello', None]
>>> b.send_bytes(b'thank you')
>>> a.recv_bytes()
b'thank you'
>>> import array
>>> arr1 = array.array('i', range(5))
>>> arr2 = array.array('i', [0] * 10)
>>> a.send_bytes(arr1)
>>> count = b.recv_bytes_into(arr2)
>>> assert count == len(arr1) * arr1.itemsize
>>> arr2
array('i', [0, 1, 2, 3, 4, 0, 0, 0, 0, 0])

Avertissement

La méthode Connection.recv() désérialise automatiquement les données qu’elle reçoit, ce qui peut être un risque de sécurité à moins que vous ne fassiez réellement confiance au processus émetteur du message.

Par conséquent, à moins que l’objet de connexion soit instancié par Pipe(), vous ne devriez uniquement utiliser les méthodes recv() et send() après avoir effectué une quelconque forme d’authentification. Voir Clés d’authentification.

Avertissement

Si un processus est tué pendant qu’il essaye de lire ou écrire sur le tube, alors les données du tube ont des chances d’être corrompues, parce qu’il devient impossible d’être sûr d’où se trouvent les bornes du message.

17.2.2.5. Primitives de synchronisation

Généralement les primitives de synchronisation ne sont pas nécessaire dans un programme multi-processus comme elles le sont dans un programme multi-fils d’exécution. Voir la documentation du module threading.

Notez que vous pouvez aussi créer des primitives de synchronisation en utilisant un objet gestionnaire – voir Gestionnaires.

class multiprocessing.Barrier(parties[, action[, timeout]])

Un objet barrière : un clone de threading.Barrier.

Nouveau dans la version 3.3.

class multiprocessing.BoundedSemaphore([value])

Un objet sémaphore lié : un analogue proche de threading.BoundedSemaphore.

Une seule différence existe avec son proche analogue : le premier argument de sa méthode acquire est appelé block, pour la cohérence avec Lock.acquire().

Note

Sur Mac OS X, elle n’est pas distinguable de la classe Semaphore parce que sem_getvalue() n’est pas implémentée sur cette plateforme.

class multiprocessing.Condition([lock])

Une variable conditionnelle : un alias pour threading.Condition.

Si lock est spécifié il doit être un objet Lock ou RLock du module multiprocessing.

Modifié dans la version 3.3: La méthode wait_for() a été ajoutée.

class multiprocessing.Event

Un clone de threading.Event.

class multiprocessing.Lock

Un verrou non récursif : un analogue proche de threading.Lock. Une fois que le processus ou le fil d’exécution a acquis un verrou, les tentatives suivantes d’acquisition depuis n’importe quel processus ou fil d’exécution bloqueront jusqu’à ce qu’il soit libéré ; n’importe quel processus ou fil peut le libérer. Les concepts et comportements de threading.Lock qui s’appliquent aux fils d’exécution sont répliqués ici dans multiprocessing.Lock et s’appliquent aux processus et aux fils d’exécution, à l’exception de ce qui est indiqué.

Notez que Lock est en fait une fonction factory qui renvoie une instance de multiprocessing.synchronize.Lock initialisée avec un contexte par défaut.

Lock supporte le protocole context manager et peut ainsi être utilisé avec une instruction with.

acquire(block=True, timeout=None)

Acquiert un verrou, bloquant ou non bloquant.

Avec l’argument block à True (par défaut), l’appel de méthode bloquera jusqu’à ce que le verrou soit dans déverrouillé, puis le verrouillera avant de renvoyer True. Notez que le nom de ce premier argument diffère de celui de threading.Lock.acquire().

Avec l’argument block à False, l’appel de méthode ne bloque pas. Si le verrou est actuellement verrouillé, renvoie False ; autrement verrouille le verrou et renvoie True.

Quand invoqué avec un nombre flottant positif comme timeout, bloque au maximum pendant ce nombre spécifié de secondes, tant que le verrou ne peut être acquis. Les invocations avec une valeur de timeout négatives sont équivalents à zéro. Les invocations avec un timeout à None (par défaut) correspondent à un délai d’attente infini. Notez que le traitement des valeurs de timeout négatives et None diffère du comportement implémenté dans threading.Lock.acquire(). L’argument timeout n’a pas d’implication pratique si l’argument block est mis ) False et est alors ignoré. Renvoie True si le verrou a été acquis et False si le temps de timeout a expiré.

release()

Libère un verrou. Elle peut être appelée depuis n’importe quel processus ou fil d’exécution, pas uniquement le processus ou le fil qui a acquis le verrou à l’origine.

Le comportement est le même que threading.Lock.release() excepté que lorsque la méthode est appelée sur un verrou déverrouillé, une ValueError est levée.

class multiprocessing.RLock

Un objet verrou récursif : un analogue proche de threading.RLock. Un verrou récursif doit être libéré par le processus ou le fil d’exécution qui l’a acquis. Quand un processus ou un fil acquiert un verrou récursif, le même processus/fil peut l’acquérir à nouveau sans bloquer ; le processus/fil doit le libérer autant de fois qu’il l’acquiert.

Notez que RLock est en fait une fonction factory qui renvoie une instance de multiprocessing.synchronize.RLock initialisée avec un contexte par défaut.

RLock supporte le protocole context manager et peut ainsi être utilisée avec une instruction with.

acquire(block=True, timeout=None)

Acquiert un verrou, bloquant ou non bloquant.

Quand invoqué avec l’argument block à True, bloque jusqu’à ce que le verrou soit déverrouillé (n’appartenant à aucun processus ou fil d’exécution) sauf s’il appartient déjà au processus ou fil d’exécution courant. Le processus ou fil d’exécution courant prend la possession du verrou (s’il ne l’a pas déjà) et incrémente d’un le niveau de récursion du verrou, renvoyant ainsi True. Notez qu’il y a plusieurs différences dans le comportement de ce premier argument comparé à l’implémentation de threading.RLock.acquire(), à commencer par le nom de l’argument lui-même.

Quand invoqué avec l’argument block à False, ne bloque pas. Si le verrou est déjà acquis (et possédé) par un autre processus ou fil d’exécution, le processus/fil courant n’en prend pas la possession et le niveau de récursion n’est pas incrémenté, résultant en une valeur de retour à False. Si le verrou est déverrouillé, le processus/fil courant en prend possession et incrémente son niveau de récursion, renvoyant True.

L’usage et les comportements de l’argument timeout sont les mêmes que pour Lock.acquire(). Notez que certains de ces comportements diffèrent par rapport à ceux implémentés par threading.RLock.acquire().

release()

Libère un verrou, décrémentant son niveau de récursion. Si après la décrémentation le niveau de récursion est zéro, réinitialise le verrou à un état déverrouillé (n’appartenant à aucun processus ou fil d’exécution) et si des processus/fils attendent que le verrou se déverrouillé, autorise un seul d’entre-eux à continuer. Si après cette décrémentation le niveau de récursion est toujours strictement positif, le verrou reste verrouillé et propriété du processus/fil appelant.

N’appelez cette méthode que si le processus ou fil d’exécution appelant est propriétaire du verrou. Une AssertionError est levée si cette méthode est appelée par un processus/fil autre que le propriétaire ou si le verrou n’est pas verrouillé (possédé). Notez que le type d’exception levé dans cette situation diffère du comportement de threading.RLock.release().

class multiprocessing.Semaphore([value])

Un objet sémaphore, proche analogue de threading.Semaphore.

Une seule différence existe avec son proche analogue : le premier argument de sa méthode acquire est appelé block, pour la cohérence avec Lock.acquire().

Note

Sous Mac OS X, sem_timedwait n’est pas supporté, donc appeler acquire() avec un temps d’exécution limité émulera le comportement de cette fonction en utilisant une boucle d’attente.

Note

Si le signal SIGINT généré par un Ctrl-C survient pendant que le fil d’exécution principal est bloqué par un appel à BoundedSemaphore.acquire(), Lock.acquire(), RLock.acquire(), Semaphore.acquire(), Condition.acquire() ou Condition.wait(), l’appel sera immédiatement interrompu et une KeyboardInterrupt sera levée.

Cela diffère du comportement de threading où le SIGINT est ignoré tant que les appels bloquants sont en cours.

Note

Certaines des fonctionnalités de ce paquet requièrent une implémentation fonctionnelle de sémaphores partagés sur le système hôte. Sans cela, le module multiprocessing.synchronize sera désactivé, et les tentatives de l’importer lèveront une ImportError. Voir bpo-3770 [https://bugs.python.org/issue3770] pour plus d’informations.

17.2.2.6. Objets ctypes partagés

Il est possible de créer des objets partagés utilisant une mémoire partagée pouvant être héritée par les processus enfants.

multiprocessing.Value(typecode_or_type, *args, lock=True)

Renvoie un objet ctypes alloué depuis la mémoire partagée. Par défaut la valeur de retour est en fait un wrapper synchronisé autour de l’objet. L’objet en lui-même est accessible par l’attribut value de l’une Value.

typecode_or_type détermine le type de l’objet renvoyé : il s’agit soit d’un type ctype soit d’un caractère typecode tel qu’utilisé par le module array. *args est passé au constructeur de ce type.

Si lock vaut True (par défaut), alors un nouveau verrou récursif est créé pour synchroniser l’accès à la valeur. Si lock est un objet Lock ou RLock alors il sera utilisé pour synchroniser l’accès à la valeur. Si lock vaut False, l’accès à l’objet renvoyé ne sera pas automatiquement protégé par un verrou, donc il ne sera pas forcément « process-safe ».

Les opérations telles que += qui impliquent une lecture et une écriture ne sont pas atomique. Ainsi si vous souhaitez par exemple réaliser une incrémentation atomique sur une valeur partagée, vous ne pouvez pas simplement faire

counter.value += 1

En supposant que le verrou associé est récursif (ce qui est le cas par défaut), vous pouvez à la place faire

with counter.get_lock():
    counter.value += 1

Notez que lock est un argument keyword-only.

multiprocessing.Array(typecode_or_type, size_or_initializer, *, lock=True)

Renvoie un tableau ctypes alloué depuis la mémoire partagée. Par défaut la valeur de retour est en fait un wrapper synchronisé autour du tableau.

typecode_or_type détermine le type des éléments du tableau renvoyé : il s’agit soit d’un type ctype soit d’un caractère typecode tel qu’utilisé par le module array. Si size_or_initialize est un entier, alors il détermine la taille du tableau, et le tableau sera initialisé avec des zéros. Autrement, size*or_initializer est une séquence qui sera utilisée pour initialiser le tableau et dont la taille détermine celle du tableau.

Si lock vaut True (par défaut), alors un nouveau verrou est créé pour synchroniser l’accès à la valeur. Si lock est un objet Lock ou RLock alors il sera utilisé pour synchroniser l’accès à la valeur. Si lock vaut False, l’accès à l’objet renvoyé ne sera pas automatiquement protégé par un verrou, donc il ne sera pas forcément « process-safe ».

Notez que lock est un argument keyword-only.

Notez qu’un tableau de ctypes.c_char a ses attributs value et raw qui permettent de l’utiliser pour stocker et récupérer des chaînes de caractères.

17.2.2.6.1. Le module multiprocessing.sharedctypes

Le module multiprocessing.sharedctypes fournit des fonctions pour allouer des objets ctypes depuis la mémoire partagée, qui peuvent être hérités par les processus fils.

Note

Bien qu’il soit possible de stocker un pointeur en mémoire partagée, rappelez-vous qu’un pointer référence un emplacement dans l’espace d’adressage d’un processus particulier. Ainsi, ce pointeur a de fortes chances d’être invalide dans le contexte d’un autre processus et déréférencer le pointeur depuis ce second processus peut causer un plantage.

multiprocessing.sharedctypes.RawArray(typecode_or_type, size_or_initializer)

Renvoie un tableau ctypes alloué depuis la mémoire partagée.

typecode_or_type détermine le type des éléments du tableau renvoyé : il s’agit soit d’un type ctype soit d’un caractère codant le type des éléments du tableau (typecode) tel qu’utilisé par le module array. Si size_or_initialize est un entier, alors il détermine la taille du tableau, et le tableau sera initialisé avec des zéros. Autrement, size_or_initializer est une séquence qui sera utilisée pour initialiser le tableau et dont la taille détermine celle du tableau.

Notez que définir ou récupérer un élément est potentiellement non atomique – utilisez plutôt Array() pour vous assurer de synchroniser automatiquement avec un verrou.

multiprocessing.sharedctypes.RawValue(typecode_or_type, *args)

Renvoie un objet ctypes alloué depuis la mémoire partagée.

typecode_or_type détermine le type de l’objet renvoyé : il s’agit soit d’un type ctype soit d’un caractère typecode tel qu’utilisé par le module array. *args est passé au constructeur de ce type.

Notez que définir ou récupérer un élément est potentiellement non atomique – utilisez plutôt Value() pour vous assurer de synchroniser automatiquement avec un verrou.

Notez qu’un tableau de ctypes.c_char a ses attributs value et raw qui permettent de l’utiliser pour stocker et récupérer des chaînes de caractères – voir la documentation de ctypes.

multiprocessing.sharedctypes.Array(typecode_or_type, size_or_initializer, *, lock=True)

Identique à RawArray() à l’exception que suivant la valeur de lock un wrapper de synchronisation process-safe pourra être renvoyé à la place d’un tableau ctypes brut.

Si lock vaut True (par défaut), alors un nouveau verrou est créé pour synchroniser l’accès à la valeur. Si lock est un objet Lock ou RLock alors il sera utilisé pour synchroniser l’accès à la valeur. Si lock vaut False, l’accès à l’objet renvoyé ne sera pas automatiquement protégé par un verrou, donc il ne sera pas forcément « process-safe ».

Notez que lock est un argument keyword-only.

multiprocessing.sharedctypes.Value(typecode_or_type, *args, lock=True)

Identique à RawValue() à l’exception que suivant la valeur de lock un wrapper de synchronisation process-safe pourra être renvoyé à la place d’un objet ctypes brut.

Si lock vaut True (par défaut), alors un nouveau verrou est créé pour synchroniser l’accès à la valeur. Si lock est un objet Lock ou RLock alors il sera utilisé pour synchroniser l’accès à la valeur. Si lock vaut False, l’accès à l’objet renvoyé ne sera pas automatiquement protégé par un verrou, donc il ne sera pas forcément « process-safe ».

Notez que lock est un argument keyword-only.

multiprocessing.sharedctypes.copy(obj)

Renvoie un objet ctypes alloué depuis la mémoire partagée, qui est une copie de l’objet ctypes obj.

multiprocessing.sharedctypes.synchronized(obj[, lock])

Renvoie un wrapper process-safe autour de l’objet ctypes qui utilise lock pour synchroniser l’accès. Si lock est None (par défaut), un objet multiprocessing.RLock est créé automatiquement.

Un wrapper synchronisé aura deux méthodes en plus de celles de l’objet qu’il enveloppe : get_obj() renvoie l’objet wrappé et get_lock() renvoie le verrou utilisé pour la synchronisation.

Notez qu’accéder à l’objet ctypes à travers le wrapper peut s’avérer beaucoup plus lent qu’accéder directement à l’objet ctypes brut.

Modifié dans la version 3.5: Les objets synchronisés supportent le protocole context manager.

Le tableau ci-dessous compare la syntaxe de création des objets ctypes partagés depuis une mémoire partagée avec la syntaxe normale ctypes. (Dans le tableau, MyStruct est une sous-classe quelconque de ctypes.Structure.)

ctypes

sharedctypes utilisant un type

sharedctypes utilisant un typecode

c_double(2.4)

RawValue(c_double, 2.4)

RawValue(“d”, 2.4)

MyStruct(4, 6)

RawValue(MyStruct, 4, 6)

(c_short * 7)()

RawArray(c_short, 7)

RawArray(“h”, 7)

(c_int * 3)(9, 2, 8)

RawArray(c_int, (9, 2, 8))

RawArray(“i”, (9, 2, 8))

Ci-dessous un exemple où des objets ctypes sont modifiés par un processus fils :

from multiprocessing import Process, Lock
from multiprocessing.sharedctypes import Value, Array
from ctypes import Structure, c_double

class Point(Structure):
    _fields_ = [('x', c_double), ('y', c_double)]

def modify(n, x, s, A):
    n.value **= 2
    x.value **= 2
    s.value = s.value.upper()
    for a in A:
        a.x **= 2
        a.y **= 2

if __name__ == '__main__':
    lock = Lock()

    n = Value('i', 7)
    x = Value(c_double, 1.0/3.0, lock=False)
    s = Array('c', b'hello world', lock=lock)
    A = Array(Point, [(1.875,-6.25), (-5.75,2.0), (2.375,9.5)], lock=lock)

    p = Process(target=modify, args=(n, x, s, A))
    p.start()
    p.join()

    print(n.value)
    print(x.value)
    print(s.value)
    print([(a.x, a.y) for a in A])

Les résultats affichés sont

49
0.1111111111111111
HELLO WORLD
[(3.515625, 39.0625), (33.0625, 4.0), (5.640625, 90.25)]

17.2.2.7. Gestionnaires

Les gestionnaires fournissent un moyen de créer des données qui peuvent être partagées entre les différents processus, incluant le partage à travers le réseau entre des processus tournant sur des machines différentes. Un objet gestionnaire contrôle un processus serveur qui gère les shared objects. Les autres processus peuvent accéder aux objets partagés à l’aide de mandataires.

multiprocessing.Manager()

Renvoie un objet SyncManager démarré qui peut être utilisé pour partager des objets entre les processus. L’objet gestionnaire renvoyé correspond à un processus enfant instancié et possède des méthodes pour créer des objets partagés et renvoyer les mandataires correspondants.

Les processus gestionnaires seront arrêtés dès qu’ils seront collectés par le ramasse-miettes ou que leur processus parent se terminera. Les classes gestionnaires sont définies dans le module multiprocessing.managers :

class multiprocessing.managers.BaseManager([address[, authkey]])

Crée un objet BaseManager.

Une fois créé il faut appeler start() ou get_server().serve_forever() pour assurer que l’objet gestionnaire référence un processus gestionnaire démarré.

address est l’adresse sur laquelle le processus gestionnaire écoute pour de nouvelles connexions. Si address est None, une adresse arbitraire est choisie.

authkey est la clé d’authentification qui sera utilisée pour vérifier la validité des connexions entrantes sur le processus serveur. Si authkey est None alors current_process().authkey est utilisée. Autrement authkey est utilisée et doit être une chaîne d’octets.

start([initializer[, initargs]])

Démarre un sous-processus pour démarrer le gestionnaire. Si initializer n’est pas None alors le sous-processus appellera initializer(*initargs) quand il démarrera.

get_server()

Renvoie un objet Server qui représente le serveur sous le contrôle du gestionnaire. L’objet Server supporte la méthode serve_forever() :

>>> from multiprocessing.managers import BaseManager
>>> manager = BaseManager(address=('', 50000), authkey=b'abc')
>>> server = manager.get_server()
>>> server.serve_forever()

Server possède en plus un attribut address.

connect()

Connecte un objet gestionnaire local au processus gestionnaire distant :

>>> from multiprocessing.managers import BaseManager
>>> m = BaseManager(address=('127.0.0.1', 5000), authkey=b'abc')
>>> m.connect()

shutdown()

Stoppe le processus utilisé par le gestionnaire. Cela est disponible uniquement si start() a été utilisée pour démarrer le processus serveur.

Cette méthode peut être appelée plusieurs fois.

register(typeid[, callable[, proxytype[, exposed[, method_to_typeid[, create_method]]]]])

Une méthode de classe qui peut être utilisée pour enregistrer un type ou un appelable avec la classe gestionnaire.

typeif est un « type identifier » qui est utilisé pour identifier un type particulier d’objet partagé. Cela doit être une chaîne de caractères.

callable est un objet appelable utilisé pour créer les objets avec cet identifiant de type. Si une instance de gestionnaire prévoit de se connecter au serveur en utilisant sa méthode connect() ou si l’argument create_method vaut False alors cet argument peut être laissé à None.

proxytype est une sous-classe de BaseProxy utilisée pour créer des mandataires autour des objets partagés avec ce typeid. S’il est None, une classe mandataire sera créée automatiquement.

exposed est utilisé pour préciser une séquence de noms de méthodes dont les mandataires pour ce typeid doivent être autorisés à accéder via BaseProxy._callmethod(). (Si exposed est None alors proxytype._exposed_ est utilisé à la place s’il existe.) Dans le cas où aucune liste exposed n’est précisée, toutes les « méthodes publiques » de l’objet partagé seront accessibles. (Ici une « méthode publique » signifie n’importe quel attribut qui possède une méthode __call__() et dont le nom ne commence pas par un '_'.)

method_to_typeid est un tableau associatif utilisé pour préciser le type de retour de ces méthodes exposées qui doivent renvoyer un mandataire. Il associé un nom de méthode à une chaîne de caractères typeid. (Si method_to_typeid est None, proxytype._method_to_typeid_ est utilisé à la place s’il existe). Si le nom d’une méthode n’est pas une clé de ce tableau associatif ou si la valeur associée est None, l’objet renvoyé par la méthode sera une copie de la valeur.

create_method détermine si une méthode devrait être créée avec le nom typeid, qui peut être utilisée pour indiquer au processus serveur de créer un nouvel objet partagé et d’en renvoyer un mandataire. a valeur par défaut est True.

Les instances de BaseManager ont aussi une propriété en lecture seule :

address

L’adresse utilisée par le gestionnaire.

Modifié dans la version 3.3: Les objets gestionnaires supportent le protocole des gestionnaires de contexte – voir Le type gestionnaire de contexte. __enter__() démarre le processus serveur (s’il n’a pas déjà été démarré) et renvoie l’objet gestionnaire. __exit__() appelle shutdown().

Dans les versions précédentes __enter__() ne démarrait pas le processus serveur du gestionnaire s’il n’était pas déjà démarré.

class multiprocessing.managers.SyncManager

Une sous-classe de BaseManager qui peut être utilisée pour la synchronisation entre processus. Des objets de ce type sont renvoyés par multiprocessing.Manager().

Ces méthodes créent et renvoient des Objets mandataires pour un certain nombre de types de données communément utilisés pour être synchronisés entre les processus. Elles incluent notamment des listes et dictionnaires partagés.

Barrier(parties[, action[, timeout]])

Crée un objet threading.Barrier partagé et renvoie un mandataire pour cet objet.

Nouveau dans la version 3.3.

BoundedSemaphore([value])

Crée un objet threading.BoundedSemaphore partagé et renvoie un mandataire pour cet objet.

Condition([lock])

Crée un objet threading.Condition partagé et renvoie un mandataire pour cet objet.

Si lock est fourni alors il doit être un mandataire pour un objet threading.Lock ou threading.RLock.

Modifié dans la version 3.3: La méthode wait_for() a été ajoutée.

Event()

Crée un objet threading.Event partagé et renvoie un mandataire pour cet objet.

Lock()

Crée un objet threading.Lock partagé et renvoie un mandataire pour cet objet.

Namespace()

Crée un objet Namespace partagé et renvoie un mandataire pour cet objet.

Queue([maxsize])

Crée un objet queue.Queue partagé et renvoie un mandataire pour cet objet.

RLock()

Crée un objet threading.RLock partagé et renvoie un mandataire pour cet objet.

Semaphore([value])

Crée un objet threading.Semaphore partagé et renvoie un mandataire pour cet objet.

Array(typecode, sequence)

Crée un tableau et renvoie un mandataire pour cet objet.

Value(typecode, value)

Crée un objet avec un attribut value accessible en écriture et renvoie un mandataire pour cet objet.

dict()

dict(mapping)

dict(sequence)

Crée un objet dict partagé et renvoie un mandataire pour cet objet.

list()

list(sequence)

Crée un objet list partagé et renvoie un mandataire pour cet objet.

Modifié dans la version 3.6: Les objets partagés peuvent être imbriqués. Par exemple, un conteneur partagé tel qu’une liste partagée peu contenir d’autres objets partagés qui seront aussi gérés et synchronisés par le SyncManager.

class multiprocessing.managers.Namespace

Un type qui peut être enregistré avec SyncManager.

Un espace de nommage n’a pas de méthodes publiques, mais possède des attributs accessibles en écriture. Sa représentation montre les valeurs de ses attributs.

Cependant, en utilisant un mandataire pour un espace de nommage, un attribut débutant par '_' est un attribut du mandataire et non de l’objet cible :

>>> manager = multiprocessing.Manager()
>>> Global = manager.Namespace()
>>> Global.x = 10
>>> Global.y = 'hello'
>>> Global._z = 12.3    # this is an attribute of the proxy
>>> print(Global)
Namespace(x=10, y='hello')

17.2.2.7.1. Gestionnaires personnalisés

Pour créer son propre gestionnaire, il faut créer une sous-classe de BaseManager et utiliser la méthode de classe register() pour enregistrer de nouveaux types ou callables au gestionnaire. Par exemple :

from multiprocessing.managers import BaseManager

class MathsClass:
    def add(self, x, y):
        return x + y
    def mul(self, x, y):
        return x * y

class MyManager(BaseManager):
    pass

MyManager.register('Maths', MathsClass)

if __name__ == '__main__':
    with MyManager() as manager:
        maths = manager.Maths()
        print(maths.add(4, 3))         # prints 7
        print(maths.mul(7, 8))         # prints 56

17.2.2.7.2. Utiliser un gestionnaire distant

Il est possible de lancer un serveur gestionnaire sur une machine et d’avoir des clients l’utilisant sur d’autres machines (en supposant que les pare-feus impliqués l’autorisent).

Exécuter les commandes suivantes crée un serveur pour une simple queue partagée à laquelle des clients distants peuvent accéder :

>>> from multiprocessing.managers import BaseManager
>>> from queue import Queue
>>> queue = Queue()
>>> class QueueManager(BaseManager): pass
>>> QueueManager.register('get_queue', callable=lambda:queue)
>>> m = QueueManager(address=('', 50000), authkey=b'abracadabra')
>>> s = m.get_server()
>>> s.serve_forever()

Un client peut accéder au serveur comme suit :

>>> from multiprocessing.managers import BaseManager
>>> class QueueManager(BaseManager): pass
>>> QueueManager.register('get_queue')
>>> m = QueueManager(address=('foo.bar.org', 50000), authkey=b'abracadabra')
>>> m.connect()
>>> queue = m.get_queue()
>>> queue.put('hello')

Un autre client peut aussi l’utiliser :

>>> from multiprocessing.managers import BaseManager
>>> class QueueManager(BaseManager): pass
>>> QueueManager.register('get_queue')
>>> m = QueueManager(address=('foo.bar.org', 50000), authkey=b'abracadabra')
>>> m.connect()
>>> queue = m.get_queue()
>>> queue.get()
'hello'

Les processus locaux peuvent aussi accéder à cette queue, utilisant le code précédent sur le client pour y accéder à distance :

>>> from multiprocessing import Process, Queue
>>> from multiprocessing.managers import BaseManager
>>> class Worker(Process):
...     def __init__(self, q):
...         self.q = q
...         super(Worker, self).__init__()
...     def run(self):
...         self.q.put('local hello')
...
>>> queue = Queue()
>>> w = Worker(queue)
>>> w.start()
>>> class QueueManager(BaseManager): pass
...
>>> QueueManager.register('get_queue', callable=lambda: queue)
>>> m = QueueManager(address=('', 50000), authkey=b'abracadabra')
>>> s = m.get_server()
>>> s.serve_forever()

17.2.2.8. Objets mandataires

Un mandataire est un objet qui référence un objet partagé appartenant (supposément) à un processus différent. L’objet partagé est appelé le référent du mandataire. Plusieurs mandataires peuvent avoir un même référent.

Un mandataire possède des méthodes qui appellent les méthodes correspondantes du référent (bien que toutes les méthodes du référent ne soient pas nécessairement accessibles à travers le mandataire). De cette manière, un mandataire peut être utilisé comme le serait sont référent :

>>> from multiprocessing import Manager
>>> manager = Manager()
>>> l = manager.list([i*i for i in range(10)])
>>> print(l)
[0, 1, 4, 9, 16, 25, 36, 49, 64, 81]
>>> print(repr(l))
<ListProxy object, typeid 'list' at 0x...>
>>> l[4]
16
>>> l[2:5]
[4, 9, 16]

Notez qu’appliquer str() à un mandataire renvoie la représentation du référent, alors que repr() renvoie celle du mandataire.

Une fonctionnalité importantes des objets mandataires est qu’ils sont sérialisables et peuvent donc être échangés entre les processus. Ainsi, un référent peut contenir des Objets mandataires. Cela permet d’imbriquer des listes et dictionnaires gérés ainsi que d’autres Objets mandataires :

>>> a = manager.list()
>>> b = manager.list()
>>> a.append(b)         # referent of a now contains referent of b
>>> print(a, b)
[<ListProxy object, typeid 'list' at ...>] []
>>> b.append('hello')
>>> print(a[0], b)
['hello'] ['hello']

De même, les mandataires de listes et dictionnaires peuvent être imbriqués dans d’autres :

>>> l_outer = manager.list([ manager.dict() for i in range(2) ])
>>> d_first_inner = l_outer[0]
>>> d_first_inner['a'] = 1
>>> d_first_inner['b'] = 2
>>> l_outer[1]['c'] = 3
>>> l_outer[1]['z'] = 26
>>> print(l_outer[0])
{'a': 1, 'b': 2}
>>> print(l_outer[1])
{'c': 3, 'z': 26}

Si des objets standards (non proxyfiés) list ou dict sont contenus dans un référent, les modifications sur ces valeurs mutables ne seront pas propagées à travers le gestionnaire parce que le mandataire n’a aucun moyen de savoir quand les valeurs contenues sont modifiées. Cependant, stocker une valeur dans un conteneur mandataire (qui déclenche un appel à __setitem__ sur le mandataire) propage bien la modification à travers le gestionnaire et modifie effectivement l’élément, il est ainsi possible de réassigner la valeur modifiée au conteneur mandataire :

# create a list proxy and append a mutable object (a dictionary)
lproxy = manager.list()
lproxy.append({})
# now mutate the dictionary
d = lproxy[0]
d['a'] = 1
d['b'] = 2
# at this point, the changes to d are not yet synced, but by
# updating the dictionary, the proxy is notified of the change
lproxy[0] = d

Cette approche est peut-être moins pratique que d’utiliser des Objets mandataires imbriqués pour la majorité des cas d’utilisation, mais démontre aussi un certain niveau de contrôle sur la synchronisation.

Note

Les types de mandataires de multiprocessing n’implémentent rien pour la comparaison par valeurs. Par exemple, on a :

>>> manager.list([1,2,3]) == [1,2,3]
False

Il faut à la place simplement utiliser une copie du référent pour faire les comparaisons.

class multiprocessing.managers.BaseProxy

Les objets mandataires sont des instances de sous-classes de BaseProxy.

_callmethod(methodname[, args[, kwds]])

Appelle et renvoie le résultat d’une méthode du référent du mandataire.

Si proxy est un mandataire sont le référent est obj, alors l’expression

proxy._callmethod(methodname, args, kwds)

s’évalue comme

getattr(obj, methodname)(*args, **kwds)

dans le processus du gestionnaire.

La valeur renvoyée sera une copie du résultat de l’appel ou un mandataire sur un nouvel objet partagé – voir l’a documentation de l’argument method_to_typeid de BaseManager.register().

Si une exception est levée par l’appel, elle est relayée par _callmethod(). Si une autre exception est levée par le processus du gestionnaire, elle est convertie en une RemoteError et est levée par _callmethod().

Notez en particulier qu’une exception est levée si methodname n’est pas exposée.

Un exemple d’utilisation de _callmethod() :

>>> l = manager.list(range(10))
>>> l._callmethod('__len__')
10
>>> l._callmethod('__getitem__', (slice(2, 7),)) # equivalent to l[2:7]
[2, 3, 4, 5, 6]
>>> l._callmethod('__getitem__', (20,))          # equivalent to l[20]
Traceback (most recent call last):
...
IndexError: list index out of range

_getvalue()

Renvoie une copie du référent.

Si le référent n’est pas sérialisable, une exception est levée.

__repr__()

Renvoie la représentation de l’objet mandataire.

__str__()

Renvoie la représentation du référent.

17.2.2.8.1. Nettoyage

Un mandataire utilise un callback sous une référence faible de façon à ce que quand il est collecté par le ramasse-miettes, il se désenregistre auprès du gestionnaire qui possède le référent.

Un objet partagé est supprimé par le processus gestionnaire quand plus aucun mandataire ne le référence.

17.2.2.9. Bassins de processus

On peut créer un bassin de processus qui exécuteront les tâches qui lui seront soumises avec la classe Pool.

class multiprocessing.pool.Pool([processes[, initializer[, initargs[, maxtasksperchild[, context]]]]])

Un objet process pool qui contrôle un bassin de processus workers auquel sont soumises des tâches. Il supporte les résultats asynchrones avec des timeouts et des callabacks et possède une implémentation parallèle de map.

processes est le nombre de processus workers à utiliser. Si processes est None, le nombre renvoyé par os.cpu_count() est utilisé.

Si initializer n’est pas None, chaque processus worker appellera initializer(*initargs) en démarrant.

maxtasksperchild est le nombre de tâches qu’un processus worker peut accomplir avant de se fermer et d’être remplacé par un worker frais, pour permettre aux ressources inutilisées d’être libérées. Par défaut maxtasksperchild est None, ce qui signifie que le worker vit aussi longtemps que le bassin.

context peut être utilisé pour préciser le contexte utilisé pour démarrer les processus workers. Habituellement un bassin est créé à l’aide de la fonction multiprocessing.Pool() ou de la méthode Pool() d’un objet de contexte. Dans les deux cas context est réglé de façon appropriée.

Notez que les méthodes de l’objet pool ne doivent être appelées que par le processus qui l’a créé.

Nouveau dans la version 3.2: maxtasksperchild

Nouveau dans la version 3.4: context

Note

Les processus workers à l’intérieur d’une Pool vivent par défaut aussi longtemps que la queue de travail du bassin. Un modèle fréquent chez d’autres systèmes (tels qu’Apache, mod_wsgi, etc.) pour libérer les ressources détenues par les workers est d’autoriser un worker dans le bassin à accomplir seulement une certaine charge de travail avant de se fermer, se retrouvant nettoyé et remplacé par un nouvelle processus fraîchement lancé. L’argument maxtasksperchild de Pool expose cette fonctionnalité à l’utilisateur final.

apply(func[, args[, kwds]])

Appelle func avec les arguments args et les arguments nommés kwds. Bloque jusqu’à ce que que le résultat soit prêt. En raison de ce blocage, apply_async() est préférable pour exécuter du travail en parallèle. De plus, func est exécutée sur un seul des workers du bassin.

apply_async(func[, args[, kwds[, callback[, error_callback]]]])

Une variante de la méthode apply() qui renvoie un objet résultat.

Si callback est précisé alors ce doit être un objet appelable qui accepte un seul argument. Quand le résultat est prêt, callback est appelé avec ce résultat, si l’appel n’échoue pas auquel cas error_callback est appelé à la place.

Si error_callback est précisé alors ce doit être un objet appelable qui accepte un seul argument. Si la fonction cible échoue, alors error_callback est appelé avec l’instance de l’exception.

Les callbacks doivent se terminer immédiatement, autrement le fil d’exécution qui gère les résultats se retrouverait bloqué.

map(func, iterable[, chunksize])

Un équivalent parallèle à la fonction built-in map() (qui ne supporte cependant qu’un itérable en argument). Elle bloque jusqu’à ce que le résultat soit prêt.

La méthode découpe l’itérable en un nombre de morceaux qu’elle envoie au bassin de processus comme des tâches séparées. La taille (approximative) de ces morceaux peut être précisée en passant à chunksize un entier positif.

map_async(func, iterable[, chunksize[, callback[, error_callback]]])

Une variante de la méthode map() qui renvoie un objet résultat.

Si callback est précisé alors ce doit être un objet appelable qui accepte un seul argument. Quand le résultat est prêt, callback est appelé avec ce résultat, si l’appel n’échoue pas auquel cas error_callback est appelé à la place.

Si error_callback est précisé alors ce doit être un objet appelable qui accepte un seul argument. Si la fonction cible échoue, alors error_callback est appelé avec l’instance de l’exception.

Les callbacks doivent se terminer immédiatement, autrement le fil d’exécution qui gère les résultats se retrouverait bloqué.

imap(func, iterable[, chunksize])

A lazier version of map().

L’argument chunksize est le même que celui utilisé par la méthode map(). Pour de très longs itérables, utiliser une grande valeur pour chunksize peut faire s’exécuter la tâche beaucoup plus rapidement qu’en utilisant la valeur par défaut de 1.

Aussi, si chucksize vaut 1 alors la méthode next() de l’itérateur renvoyé par imap() prend un paramètre optionnel timeout : next(timeout) lève une multiprocessing.TimeoutError si le résultat ne peut pas être renvoyé avant timeout secondes.

imap_unordered(func, iterable[, chunksize])

Identique à imap() si ce n’est que l’ordre des résultats de l’itérateur renvoyé doit être considéré comme arbitraire. (L’ordre n’est garanti que quand il n’y a qu’un worker.)

starmap(func, iterable[, chunksize])

Semblable à map() à l’exception que les éléments d”iterable doivent être des itérables qui seront dépaquetés comme arguments pour la fonction.

Par conséquent un iterable [(1,2), (3, 4)] donnera pour résultat [func(1,2), func(3,4)].

Nouveau dans la version 3.3.

starmap_async(func, iterable[, chunksize[, callback[, error_callback]]])

Une combinaison de starmap() et map_async() qui itère sur iterable (composé d’itérables) et appelle func pour chaque itérable dépaqueté. Renvoie l’objet résultat.

Nouveau dans la version 3.3.

close()

Empêche de nouvelles tâches d’être envoyées à la pool. Les processus workers se terminent une fois que toutes les tâches ont été complétées.

terminate()

Stoppe immédiatement les processus workers sans finaliser les travaux courants. Quand l’objet pool est collecté par le ramasse-miettes, sa méthode terminate() est appelée immédiatement.

join()

Attend que les processus workers se terminent. Il est nécessaire d’appeler close() ou terminate() avant d’utiliser join().

Nouveau dans la version 3.3: Les bassins de workers supportent maintenant le protocole des gestionnaires de contexte – voir Le type gestionnaire de contexte. __enter__() renvoie l’objet pool et __exit__() appelle terminate().

class multiprocessing.pool.AsyncResult

La classe des résultats renvoyés par Pool.apply_async() et Pool.map_async().

get([timeout])

Renvoie le résultat quand il arrive. Si timeout n’est pas None et que le résultat n’arrive pas avant timeout secondes, une multiprocessing.TimeoutError est levée. Si l’appel distance lève une exception, alors elle est relayée par get().

wait([timeout])

Attend que le résultat soit disponible ou que timeout secondes s’écoulent.

ready()

Renvoie True ou False suivant si la tâche est accomplie.

successful()

Renvoie True ou False suivant si la tâche est accomplie sans lever d’exception. Lève une AssertionError si le résultat n’est pas prêt.

Les exemples suivants présentent l’utilisation d’un bassin de workers :

from multiprocessing import Pool
import time

def f(x):
    return x*x

if __name__ == '__main__':
    with Pool(processes=4) as pool:         # start 4 worker processes
        result = pool.apply_async(f, (10,)) # evaluate "f(10)" asynchronously in a single process
        print(result.get(timeout=1))        # prints "100" unless your computer is *very* slow

        print(pool.map(f, range(10)))       # prints "[0, 1, 4,..., 81]"

        it = pool.imap(f, range(10))
        print(next(it))                     # prints "0"
        print(next(it))                     # prints "1"
        print(it.next(timeout=1))           # prints "4" unless your computer is *very* slow

        result = pool.apply_async(time.sleep, (10,))
        print(result.get(timeout=1))        # raises multiprocessing.TimeoutError

17.2.2.10. Auditeurs et Clients

Habituellement l’échange de messages entre processus est réalisé en utilisant des queues ou des objets Connection renvoyés par Pipe().

Cependant, le module multiprocessing.connection permet un peu plus de flexibilité. Il fournit un message de plus haut-niveau orienté API pour gérer des connecteurs ou des tubes nommés sous Windows. Il gère aussi l’authentification par condensat (digest authentication en anglais) en utilisant le module hmac, et pour interroger de multiples connexions en même temps.

multiprocessing.connection.deliver_challenge(connection, authkey)

Envoie un message généré aléatoirement à l’autre bout de la connexion et attend une réponse.

Si la réponse correspond au condensat du message avec la clé authkey, alors un message de bienvenue est envoyé à l’autre bout de la connexion. Autrement, une AuthenticationError est levée.

multiprocessing.connection.answer_challenge(connection, authkey)

Reçoit un message, calcule le condensat du message en utilisant la clé authkey, et envoie le condensat en réponse.

Si un message de bienvenue n’est pas reçu, une AuthenticationError est levée.

multiprocessing.connection.Client(address[, family[, authkey]])

Essaie d’établir une connexion avec l’auditeur qui utilise l’adresse address, renvoie une Connection.

Le type de la connexion est déterminé par l’argument family, mais il peut généralement être omis puisqu’il peut être inféré depuis le format d”address. (Voir Formats d’adresses)

Si authkey est passée et n’est pas None, elle doit être une chaîne d’octets et sera utilisée comme clé secrète pour le défi d’authentification basé sur HMAC. Aucune authentification n’est réalisée si authkey est None. Une AuthenticationError est levée si l’authentification échoue. Voir Clés d’authentification.

class multiprocessing.connection.Listener([address[, family[, backlog[, authkey]]]])

Une enveloppe autour d’un connecteur lié ou un tube nommé sous Windows qui écoute pour des connexions.

address est l’adresse à utiliser par le connecteur lié ou le tube nommé de l’objet auditeur.

Note

Si une adresse “0.0.0.0” est utilisée, l’adresse ne sera pas un point d’accès connectable sous Windows. Si vous avez besoin d’un point d’accès connectable, utilisez “127.0.0.1”.

family est le type de connecteur (ou tube nommé) à utiliser. Cela peut être l’une des chaînes 'AF_INET' (pour un connecteur TCP), 'AF_UNIX' (pour un connecteur Unix) ou 'AF_PIPE' (pour un tube nommé sous Windows). Seulement le premier d’entre eux est garanti d’être disponible. Si family est None, la famille est inférée depuis le format d”address. Si address est aussi None, la famille par défaut est utilisée. La famille par défaut est supposée être la plus rapide disponible. Voir Formats d’adresses. Notez que si la family est 'AF_UNIX' et qu”address est None, le connecteur est créé dans un répertoire temporaire privé créé avec tempfile.mkstemp().

Si l’objet auditeur utilise un connecteur alors backlog (1 par défaut) est passé à la méthode listen() du connecteur une fois qu’il a été lié.

Si authkey est passée et n’est pas None, elle doit être une chaîne d’octets et sera utilisée comme clé secrète pour le défi d’authentification basé sur HMAC. Aucune authentification n’est réalisée si authkey est None. Une AuthenticationError est levée si l’authentification échoue. Voir Clés d’authentification.

accept()

Accepte une connexion sur le connecteur lié ou le tube nommé de l’objet auditeur et renvoie un objet Connection. Si la tentative d’authentification échoue, une AuthenticationError est levée.

close()

Ferme le connecteur lié ou le tube nommé de l’objet auditeur. La méthode est appelée automatiquement quand l’auditeur est collecté par le ramasse-miettes. Il est cependant conseillé de l’appeler explicitement.

Les objets auditeurs ont aussi les propriétés en lecture seule suivantes :

address

L’adresse utilisée par l’objet auditeur.

last_accepted

L’adresse depuis laquelle a été établie la dernière connexion. None si aucune n’est disponible.

Nouveau dans la version 3.3: Les objets auditeurs supportent maintenant le protocole des gestionnaires de contexte – voir Le type gestionnaire de contexte. __enter__() renvoie l’objet auditeur, et __exit__() appelle close().

multiprocessing.connection.wait(object_list, timeout=None)

Attend qu’un objet d”object_list soit prêt. Renvoie la liste de ces objets d”object_list qui sont prêts. Si timeout est un nombre flottant, l’appel bloquera au maximum ce nombre de secondes. Si timeout est None, l’appelle bloquera pour une durée non limitée. Un timeout négatif est équivalent à un timeout nul.

Pour Unix et Windows, un objet peut apparaître dans object_list s’il est

un objet Connection accessible en lecture ;

un objet socket.socket connecté et accessible en lecture ; ou

l’attribut sentinel d’un objet Process.

Une connexion (socket en anglais) est prête quand il y a des données disponibles en lecture dessus, ou que l’autre bout a été fermé.

Unix: wait(object_list, timeout) est en grande partie équivalente à select.select(object_list, [], [], timeout). La différence est que, si select.select() est interrompue par un signal, elle peut lever une OSError avec un numéro d’erreur EINTR, alors que wait() ne le fera pas.

Windows : un élément d”object_list doit être soit un identifiant waitable (en accord avec la définition utilisée par la documentation de la fonction Win32 WaitForMultipleObjects()), soit un objet avec une méthode fileno() qui renvoie un identifiant de connecteur ou de tube (notez que les identifiants de tubes et de connecteurs ne sont pas des identifiants waitables).

Nouveau dans la version 3.3.

Exemples

Le code serveur suivant crée un auditeur qui utilise 'secret password' comme clé d’authentification. Il attend ensuite une connexion et envoie les données au client :

from multiprocessing.connection import Listener
from array import array

address = ('localhost', 6000)     # family is deduced to be 'AF_INET'

with Listener(address, authkey=b'secret password') as listener:
    with listener.accept() as conn:
        print('connection accepted from', listener.last_accepted)

        conn.send([2.25, None, 'junk', float])

        conn.send_bytes(b'hello')

        conn.send_bytes(array('i', [42, 1729]))

Le code suivant se connecte au serveur et en reçoit des données :

from multiprocessing.connection import Client
from array import array

address = ('localhost', 6000)

with Client(address, authkey=b'secret password') as conn:
    print(conn.recv())                  # => [2.25, None, 'junk', float]

    print(conn.recv_bytes())            # => 'hello'

    arr = array('i', [0, 0, 0, 0, 0])
    print(conn.recv_bytes_into(arr))    # => 8
    print(arr)                          # => array('i', [42, 1729, 0, 0, 0])

Le code suivant utilise wait() pour attendre des messages depuis plusieurs processus à la fois :

import time, random
from multiprocessing import Process, Pipe, current_process
from multiprocessing.connection import wait

def foo(w):
    for i in range(10):
        w.send((i, current_process().name))
    w.close()

if __name__ == '__main__':
    readers = []

    for i in range(4):
        r, w = Pipe(duplex=False)
        readers.append(r)
        p = Process(target=foo, args=(w,))
        p.start()
        # We close the writable end of the pipe now to be sure that
        # p is the only process which owns a handle for it.  This
        # ensures that when p closes its handle for the writable end,
        # wait() will promptly report the readable end as being ready.
        w.close()

    while readers:
        for r in wait(readers):
            try:
                msg = r.recv()
            except EOFError:
                readers.remove(r)
            else:
                print(msg)

17.2.2.10.1. Formats d’adresses

Une adresse 'AF_INET' est un tuple de la forme (hostname, port) où hostname est une chaîne et port un entier.

Une adresse 'AF_UNIX' est une chaîne représentant un nom de fichier sur le système de fichiers.

Une adresse 'AF_PIPE' est une chaîne de la forme

r'\.\pipe{PipeName}'. Pour utiliser un Client() pour se connecter à un tube nommé sur une machine distante appelée ServerName, il faut plutôt utiliser une adresse de la forme r'\ServerName\pipe{PipeName}'.

Notez que toute chaîne commençant par deux antislashs est considérée par défaut comme l’adresse d’un 'AF_PIPE' plutôt qu’une adresse 'AF_UNIX'.

17.2.2.11. Clés d’authentification

Quand Connection.recv est utilisée, les données reçues sont automatiquement désérialisées par pickle. Malheureusement désérialiser des données depuis une source non sûre constitue un risque de sécurité. Par conséquent Listener et Client() utilisent le module hmac pour fournir une authentification par condensat.

Une clé d’authentification est une chaîne d’octets qui peut être vue comme un mot de passe : quand une connexion est établie, les deux interlocuteurs vont demander à l’autre une preuve qu’il connaît la clé d’authentification. (Démontrer que les deux utilisent la même clé n’implique pas d’échanger la clé sur la connexion.)

Si l’authentification est requise et qu’aucune clé n’est spécifiée alors la valeur de retour de current_process().authkey est utilisée (voir Process). Celle valeur est automatiquement héritée par tout objet Process créé par le processus courant. Cela signifie que (par défaut) tous les processus d’un programme multi-processus partageront une clé d’authentification unique qui peut être utilisée pour mettre en place des connexions entre-eux.

Des clés d’authentification adaptées peuvent aussi être générées par os.urandom().

17.2.2.12. Journalisation

Un certain support de la journalisation est disponible. Notez cependant que le le paquet logging n’utilise pas de verrous partagés entre les processus et il est donc possible (dépendant du type de gestionnaire) que les messages de différents processus soient mélangés.

multiprocessing.get_logger()

Renvoie le journaliseur utilisé par multiprocessing. Si nécessaire, un nouveau sera créé.

À sa première création le journaliseur a pour niveau logging.NOTSET et pas de gestionnaire par défaut. Les messages envoyés à ce journaliseur ne seront pas propagés par défaut au journaliseur principal.

Notez que sous Windows les processus fils n’hériteront que du niveau du journaliseur du processus parent – toute autre personnalisation du journaliseur ne sera pas héritée.

multiprocessing.log_to_stderr()

Cette fonction effectue un appel à get_logger() mais en plus de renvoyer le journaliseur créé par get_logger, elle ajoute un gestionnaire qui envoie la sortie sur sys.stderr en utilisant le format '[%(levelname)s/%(processName)s] %(message)s'.

L’exemple ci-dessous présente une session avec la journalisation activée :

>>> import multiprocessing, logging
>>> logger = multiprocessing.log_to_stderr()
>>> logger.setLevel(logging.INFO)
>>> logger.warning('doomed')
[WARNING/MainProcess] doomed
>>> m = multiprocessing.Manager()
[INFO/SyncManager-...] child process calling self.run()
[INFO/SyncManager-...] created temp directory /.../pymp-...
[INFO/SyncManager-...] manager serving at '/.../listener-...'
>>> del m
[INFO/MainProcess] sending shutdown message to manager
[INFO/SyncManager-...] manager exiting with exitcode 0

Pour un tableau complet des niveaux de journalisation, voir le module logging.

17.2.2.13. Le module multiprocessing.dummy

multiprocessing.dummy réplique toute l’API de multiprocessing mais n’est rien de plus qu’un wrapper autour du module threading.

17.2.3. Lignes directrices de programmation

Il y a certaines lignes directrices et idiomes auxquels il faut adhérer en utilisant multiprocessing.

17.2.3.1. Toutes les méthodes de démarrage

Les règles suivantes s’appliquent aux méthodes de démarrage.

Éviter les états partagés

Autant que possible, vous devriez éviter de déplacer de larges données entre les processus.

Il est probablement meilleur de s’en tenir à l’utilisation de queues et tubes pour la communication entre processus plutôt que d’utiliser des primitives de synchronisation plus bas-niveau.

Sérialisation

Assurez-vous que les arguments passés aux méthodes des mandataires soient sérialisables (pickables).

Sûreté des mandataires à travers les fils d’exécution

N’utilisez pas d’objet mandataire depuis plus d’un fil d’exécution à moins que vous ne le protégiez avec un verrou.

(Il n’y a jamais de problème avec plusieurs processus utilisant un même mandataire.)

Attendre les processus zombies

Sous Unix quand un processus se termine mais n’est pas attendu, il devient un zombie. Il ne devrait jamais y en avoir beaucoup parce que chaque fois qu’un nouveau processus démarre (ou que active_children() est appelée) tous les processus complétés qui n’ont pas été attendus le seront. Aussi appeler la méthode Process.is_alive d’un processus terminé attendra le processus. Toutefois il est probablement une bonne pratique d’attendre explicitement tous les processus que vous démarrez.

Préférez hériter que sérialiser/désérialiser

Quand vous utilisez les méthodes de démarrage spawn ou forkserver, de nombreux types de multiprocessing nécessitent d’être sérialisées pour que les processus enfants puissent les utiliser. Cependant, il faut généralement éviter d’envoyer des objets partagés aux autres processus en utilisant des tubes ou des queues. Vous devriez plutôt vous arranger pour qu’un processus qui nécessite l’accès à une ressource partagée créée autre part qu’il en hérite depuis un de ses processus ancêtres.

Éviter de terminer les processus

Utiliser la méthode Process.terminate pour stopper un processus risque de casser ou de rendre indisponible aux autres processus des ressources partagées (comme des verrous, sémaphores, tubes et queues) actuellement utilisée par le processus.

Il est donc probablement préférable de n’utiliser Process.terminate que sur les processus qui n’utilisent jamais de ressources partagées.

Attendre les processus qui utilisent des queues

Gardez à l’esprit qu’un processus qui a placé des éléments dans une queue attendra que tous les éléments mis en tampon soient consommés par le fil d’exécution « consommateur » du tube sous-jacent avant de se terminer. (Le processus enfant peut appeler la méthode Queue.cancel_join_thread de la queue pour éviter ce comportement.)

Cela signifie que chaque fois que vous utilisez une queue vous devez vous assurer que tous les éléments qui y ont été placés seront effectivement supprimés avant que le processus ne soit attendu. Autrement vous ne pouvez pas être sûr que les processus qui ont placé des éléments dans la queue se termineront. Souvenez-vous aussi que tous les processus non daemons seront attendus automatiquement.

L’exemple suivant provoquera un interblocage :

from multiprocessing import Process, Queue

def f(q):
    q.put('X' * 1000000)

if __name__ == '__main__':
    queue = Queue()
    p = Process(target=f, args=(queue,))
    p.start()
    p.join()                    # this deadlocks
    obj = queue.get()

Une solution ici serait d’intervertir les deux dernières lignes (ou simplement supprimer la ligne p.join()).

Passer explicitement les ressources aux processus fils

Sous Unix en utilisant la méthode de démarrage fork, un processus fils peut utiliser une ressource partagée créée par un processus parent en utilisant une ressource globale. Cependant, il est préférable de passer l’objet en argument au constructeur du processus fils.

En plus de rendre le code (potentiellement) compatible avec Windows et les autres méthodes de démarrage, cela assure aussi que tant que le processus fils est en vie, l’objet ne sera pas collecté par le ramasse-miettes du processus parent. Cela peut être important si certaines ressources sont libérées quand l’objet est collecté par le ramasse-miettes du processus parent.

Donc par exemple

from multiprocessing import Process, Lock

def f():
    ... do something using "lock" ...

if __name__ == '__main__':
    lock = Lock()
    for i in range(10):
        Process(target=f).start()

devrait être réécrit comme

from multiprocessing import Process, Lock

def f(l):
    ... do something using "l" ...

if __name__ == '__main__':
    lock = Lock()
    for i in range(10):
        Process(target=f, args=(lock,)).start()

Faire attention à remplacer sys.stdin par un objet « file-like »

À l’origine, multiprocessing appelait inconditionnellement :

os.close(sys.stdin.fileno())

dans la méthode multiprocessing.Process._bootstrap() — cela provoquait des problèmes avec les processus imbriqués. Cela peut être changé en :

sys.stdin.close()
sys.stdin = open(os.open(os.devnull, os.O_RDONLY), closefd=False)

Qui résout le problème fondamental des collisions entre processus provoquant des erreurs de mauvais descripteurs de fichiers, mais introduit un potentiel danger pour les applications qui remplacent sys.stdin() avec un « file-like object » ayant une sortie bufferisée. Ce danger est que si plusieurs processus appellent close() sur cet objet file-like, cela peut amener les données à être transmises à l’objet à plusieurs reprises, résultant en une corruption.

Si vous écrivez un objet file-like et implémentez votre propre cache, vous pouvez le rendre sûr pour les forks en stockant le pid chaque fois que vous ajoutez des données au cache, et annulez le cache quand le pip change. Par exemple :

@property
def cache(self):
    pid = os.getpid()
    if pid != self._pid:
        self._pid = pid
        self._cache = []
    return self._cache

Pour plus d’informations, voir bpo-5155 [https://bugs.python.org/issue5155], bpo-5313 [https://bugs.python.org/issue5313] et bpo-5331 [https://bugs.python.org/issue5331]

17.2.3.2. Les méthodes de démarrage spawn et forkserver

Certaines restrictions ne s’appliquent pas à la méthode de démarrage fork.

Plus de sérialisation

Assurez-vous que tous les argument de Process.__init__() sont sérialisables avec pickle. Aussi, si vous héritez de Process, assurez-vous que toutes les instances sont sérialisables quand la méthode Process.start est appelée.

Variables globales

Gardez en tête que si le code exécuté dans un processus fils essaie d’accéder à une variable globale, alors la valeur qu’il voit (s’il y en a une) pourrait ne pas être la même que la valeur du processus parent au moment même où Process.start est appelée.

Cependant, les variables globales qui sont juste des constantes de modules ne posent pas de problèmes.

Importation sûre du module principal

Assurez-vous que le module principal peut être importé en toute sécurité par un nouvel interpréteur Python sans causer d’effets de bord inattendus (comme le démarrage d’un nouveau processus).

Par exemple, utiliser la méthode de démarrage spawn ou forkserver pour lancer le module suivant échouerait avec une RuntimeError :

from multiprocessing import Process

def foo():
    print('hello')

p = Process(target=foo)
p.start()

Vous devriez plutôt protéger le « point d’entrée » du programme en utilisant if __name__ == '__main__': comme suit :

from multiprocessing import Process, freeze_support, set_start_method

def foo():
    print('hello')

if __name__ == '__main__':
    freeze_support()
    set_start_method('spawn')
    p = Process(target=foo)
    p.start()

(La ligne freeze_support() peut être omise si le programme est uniquement lancé normalement et pas gelé.)

Cela permet aux interpréteurs Python fraîchement instanciés d’importer en toute sécurité le module et d’exécution ensuite la fonction foo().

Des restrictions similaires s’appliquent si une pool ou un gestionnaire est créé dans le module principal.

17.2.4. Exemples

Démonstration de comment créer et utiliser des gestionnaires et mandataires personnalisés :

from multiprocessing import freeze_support
from multiprocessing.managers import BaseManager, BaseProxy
import operator

##

class Foo:
    def f(self):
        print('you called Foo.f()')
    def g(self):
        print('you called Foo.g()')
    def _h(self):
        print('you called Foo._h()')

# A simple generator function
def baz():
    for i in range(10):
        yield i*i

# Proxy type for generator objects
class GeneratorProxy(BaseProxy):
    _exposed_ = ['__next__']
    def __iter__(self):
        return self
    def __next__(self):
        return self._callmethod('__next__')

# Function to return the operator module
def get_operator_module():
    return operator

##

class MyManager(BaseManager):
    pass

# register the Foo class; make `f()` and `g()` accessible via proxy
MyManager.register('Foo1', Foo)

# register the Foo class; make `g()` and `_h()` accessible via proxy
MyManager.register('Foo2', Foo, exposed=('g', '_h'))

# register the generator function baz; use `GeneratorProxy` to make proxies
MyManager.register('baz', baz, proxytype=GeneratorProxy)

# register get_operator_module(); make public functions accessible via proxy
MyManager.register('operator', get_operator_module)

##

def test():
    manager = MyManager()
    manager.start()

    print('-' * 20)

    f1 = manager.Foo1()
    f1.f()
    f1.g()
    assert not hasattr(f1, '_h')
    assert sorted(f1._exposed_) == sorted(['f', 'g'])

    print('-' * 20)

    f2 = manager.Foo2()
    f2.g()
    f2._h()
    assert not hasattr(f2, 'f')
    assert sorted(f2._exposed_) == sorted(['g', '_h'])

    print('-' * 20)

    it = manager.baz()
    for i in it:
        print('<%d>' % i, end=' ')
    print()

    print('-' * 20)

    op = manager.operator()
    print('op.add(23, 45) =', op.add(23, 45))
    print('op.pow(2, 94) =', op.pow(2, 94))
    print('op._exposed_ =', op._exposed_)

##

if __name__ == '__main__':
    freeze_support()
    test()

En utilisant Pool :

import multiprocessing
import time
import random
import sys

#
# Functions used by test code
#

def calculate(func, args):
    result = func(*args)
    return '%s says that %s%s = %s' % (
        multiprocessing.current_process().name,
        func.__name__, args, result
        )

def calculatestar(args):
    return calculate(*args)

def mul(a, b):
    time.sleep(0.5 * random.random())
    return a * b

def plus(a, b):
    time.sleep(0.5 * random.random())
    return a + b

def f(x):
    return 1.0 / (x - 5.0)

def pow3(x):
    return x ** 3

def noop(x):
    pass

#
# Test code
#

def test():
    PROCESSES = 4
    print('Creating pool with %d processes\n' % PROCESSES)

    with multiprocessing.Pool(PROCESSES) as pool:
        #
        # Tests
        #

        TASKS = [(mul, (i, 7)) for i in range(10)] + \
                [(plus, (i, 8)) for i in range(10)]

        results = [pool.apply_async(calculate, t) for t in TASKS]
        imap_it = pool.imap(calculatestar, TASKS)
        imap_unordered_it = pool.imap_unordered(calculatestar, TASKS)

        print('Ordered results using pool.apply_async():')
        for r in results:
            print('\t', r.get())
        print()

        print('Ordered results using pool.imap():')
        for x in imap_it:
            print('\t', x)
        print()

        print('Unordered results using pool.imap_unordered():')
        for x in imap_unordered_it:
            print('\t', x)
        print()

        print('Ordered results using pool.map() --- will block till complete:')
        for x in pool.map(calculatestar, TASKS):
            print('\t', x)
        print()

        #
        # Test error handling
        #

        print('Testing error handling:')

        try:
            print(pool.apply(f, (5,)))
        except ZeroDivisionError:
            print('\tGot ZeroDivisionError as expected from pool.apply()')
        else:
            raise AssertionError('expected ZeroDivisionError')

        try:
            print(pool.map(f, list(range(10))))
        except ZeroDivisionError:
            print('\tGot ZeroDivisionError as expected from pool.map()')
        else:
            raise AssertionError('expected ZeroDivisionError')

        try:
            print(list(pool.imap(f, list(range(10)))))
        except ZeroDivisionError:
            print('\tGot ZeroDivisionError as expected from list(pool.imap())')
        else:
            raise AssertionError('expected ZeroDivisionError')

        it = pool.imap(f, list(range(10)))
        for i in range(10):
            try:
                x = next(it)
            except ZeroDivisionError:
                if i == 5:
                    pass
            except StopIteration:
                break
            else:
                if i == 5:
                    raise AssertionError('expected ZeroDivisionError')

        assert i == 9
        print('\tGot ZeroDivisionError as expected from IMapIterator.next()')
        print()

        #
        # Testing timeouts
        #

        print('Testing ApplyResult.get() with timeout:', end=' ')
        res = pool.apply_async(calculate, TASKS[0])
        while 1:
            sys.stdout.flush()
            try:
                sys.stdout.write('\n\t%s' % res.get(0.02))
                break
            except multiprocessing.TimeoutError:
                sys.stdout.write('.')
        print()
        print()

        print('Testing IMapIterator.next() with timeout:', end=' ')
        it = pool.imap(calculatestar, TASKS)
        while 1:
            sys.stdout.flush()
            try:
                sys.stdout.write('\n\t%s' % it.next(0.02))
            except StopIteration:
                break
            except multiprocessing.TimeoutError:
                sys.stdout.write('.')
        print()
        print()

if __name__ == '__main__':
    multiprocessing.freeze_support()
    test()

Un exemple montrant comment utiliser des queues pour alimenter en tâches une collection de processus workers et collecter les résultats :

import time
import random

from multiprocessing import Process, Queue, current_process, freeze_support

#
# Function run by worker processes
#

def worker(input, output):
    for func, args in iter(input.get, 'STOP'):
        result = calculate(func, args)
        output.put(result)

#
# Function used to calculate result
#

def calculate(func, args):
    result = func(*args)
    return '%s says that %s%s = %s' % \
        (current_process().name, func.__name__, args, result)

#
# Functions referenced by tasks
#

def mul(a, b):
    time.sleep(0.5*random.random())
    return a * b

def plus(a, b):
    time.sleep(0.5*random.random())
    return a + b

#
#
#

def test():
    NUMBER_OF_PROCESSES = 4
    TASKS1 = [(mul, (i, 7)) for i in range(20)]
    TASKS2 = [(plus, (i, 8)) for i in range(10)]

    # Create queues
    task_queue = Queue()
    done_queue = Queue()

    # Submit tasks
    for task in TASKS1:
        task_queue.put(task)

    # Start worker processes
    for i in range(NUMBER_OF_PROCESSES):
        Process(target=worker, args=(task_queue, done_queue)).start()

    # Get and print results
    print('Unordered results:')
    for i in range(len(TASKS1)):
        print('\t', done_queue.get())

    # Add more tasks using `put()`
    for task in TASKS2:
        task_queue.put(task)

    # Get and print some more results
    for i in range(len(TASKS2)):
        print('\t', done_queue.get())

    # Tell child processes to stop
    for i in range(NUMBER_OF_PROCESSES):
        task_queue.put('STOP')

if __name__ == '__main__':
    freeze_support()
    test()

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17.3. Le paquet concurrent

Il n’y a actuellement qu’un module dans ce paquet :

concurrent.futures – Lancer des tâches en parallèle

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17.4. concurrent.futures — Launching parallel tasks

Nouveau dans la version 3.2.

Source code: Lib/concurrent/futures/thread.py [https://github.com/python/cpython/tree/3.6/Lib/concurrent/futures/thread.py] and Lib/concurrent/futures/process.py [https://github.com/python/cpython/tree/3.6/Lib/concurrent/futures/process.py]

The concurrent.futures module provides a high-level interface for asynchronously executing callables.

The asynchronous execution can be performed with threads, using ThreadPoolExecutor, or separate processes, using ProcessPoolExecutor. Both implement the same interface, which is defined by the abstract Executor class.

17.4.1. Executor Objects

class concurrent.futures.Executor

An abstract class that provides methods to execute calls asynchronously. It should not be used directly, but through its concrete subclasses.

submit(fn, *args, **kwargs)

Schedules the callable, fn, to be executed as fn(*args **kwargs) and returns a Future object representing the execution of the callable.

with ThreadPoolExecutor(max_workers=1) as executor:
    future = executor.submit(pow, 323, 1235)
    print(future.result())

map(func, *iterables, timeout=None, chunksize=1)

Similar to map(func, *iterables) except:

the iterables are collected immediately rather than lazily;

func is executed asynchronously and several calls to func may be made concurrently.

The returned iterator raises a concurrent.futures.TimeoutError if __next__() is called and the result isn’t available after timeout seconds from the original call to Executor.map(). timeout can be an int or a float. If timeout is not specified or None, there is no limit to the wait time.

If a func call raises an exception, then that exception will be raised when its value is retrieved from the iterator.

When using ProcessPoolExecutor, this method chops iterables into a number of chunks which it submits to the pool as separate tasks. The (approximate) size of these chunks can be specified by setting chunksize to a positive integer. For very long iterables, using a large value for chunksize can significantly improve performance compared to the default size of 1. With ThreadPoolExecutor, chunksize has no effect.

Modifié dans la version 3.5: Added the chunksize argument.

shutdown(wait=True)

Signal the executor that it should free any resources that it is using when the currently pending futures are done executing. Calls to Executor.submit() and Executor.map() made after shutdown will raise RuntimeError.

If wait is True then this method will not return until all the pending futures are done executing and the resources associated with the executor have been freed. If wait is False then this method will return immediately and the resources associated with the executor will be freed when all pending futures are done executing. Regardless of the value of wait, the entire Python program will not exit until all pending futures are done executing.

You can avoid having to call this method explicitly if you use the with statement, which will shutdown the Executor (waiting as if Executor.shutdown() were called with wait set to True):

import shutil
with ThreadPoolExecutor(max_workers=4) as e:
    e.submit(shutil.copy, 'src1.txt', 'dest1.txt')
    e.submit(shutil.copy, 'src2.txt', 'dest2.txt')
    e.submit(shutil.copy, 'src3.txt', 'dest3.txt')
    e.submit(shutil.copy, 'src4.txt', 'dest4.txt')

17.4.2. ThreadPoolExecutor

ThreadPoolExecutor is an Executor subclass that uses a pool of threads to execute calls asynchronously.

Deadlocks can occur when the callable associated with a Future waits on the results of another Future. For example:

import time
def wait_on_b():
    time.sleep(5)
    print(b.result())  # b will never complete because it is waiting on a.
    return 5

def wait_on_a():
    time.sleep(5)
    print(a.result())  # a will never complete because it is waiting on b.
    return 6

executor = ThreadPoolExecutor(max_workers=2)
a = executor.submit(wait_on_b)
b = executor.submit(wait_on_a)

Et :

def wait_on_future():
    f = executor.submit(pow, 5, 2)
    # This will never complete because there is only one worker thread and
    # it is executing this function.
    print(f.result())

executor = ThreadPoolExecutor(max_workers=1)
executor.submit(wait_on_future)

class concurrent.futures.ThreadPoolExecutor(max_workers=None, thread_name_prefix='')

An Executor subclass that uses a pool of at most max_workers threads to execute calls asynchronously.

Modifié dans la version 3.5: If max_workers is None or not given, it will default to the number of processors on the machine, multiplied by 5, assuming that ThreadPoolExecutor is often used to overlap I/O instead of CPU work and the number of workers should be higher than the number of workers for ProcessPoolExecutor.

Nouveau dans la version 3.6: The thread_name_prefix argument was added to allow users to control the threading.Thread names for worker threads created by the pool for easier debugging.

17.4.2.1. ThreadPoolExecutor Example

import concurrent.futures
import urllib.request

URLS = ['http://www.foxnews.com/',
        'http://www.cnn.com/',
        'http://europe.wsj.com/',
        'http://www.bbc.co.uk/',
        'http://some-made-up-domain.com/']

# Retrieve a single page and report the URL and contents
def load_url(url, timeout):
    with urllib.request.urlopen(url, timeout=timeout) as conn:
        return conn.read()

# We can use a with statement to ensure threads are cleaned up promptly
with concurrent.futures.ThreadPoolExecutor(max_workers=5) as executor:
    # Start the load operations and mark each future with its URL
    future_to_url = {executor.submit(load_url, url, 60): url for url in URLS}
    for future in concurrent.futures.as_completed(future_to_url):
        url = future_to_url[future]
        try:
            data = future.result()
        except Exception as exc:
            print('%r generated an exception: %s' % (url, exc))
        else:
            print('%r page is %d bytes' % (url, len(data)))

17.4.3. ProcessPoolExecutor

The ProcessPoolExecutor class is an Executor subclass that uses a pool of processes to execute calls asynchronously. ProcessPoolExecutor uses the multiprocessing module, which allows it to side-step the Global Interpreter Lock but also means that only picklable objects can be executed and returned.

The __main__ module must be importable by worker subprocesses. This means that ProcessPoolExecutor will not work in the interactive interpreter.

Calling Executor or Future methods from a callable submitted to a ProcessPoolExecutor will result in deadlock.

class concurrent.futures.ProcessPoolExecutor(max_workers=None)

An Executor subclass that executes calls asynchronously using a pool of at most max_workers processes. If max_workers is None or not given, it will default to the number of processors on the machine. If max_workers is lower or equal to 0, then a ValueError will be raised.

Modifié dans la version 3.3: When one of the worker processes terminates abruptly, a BrokenProcessPool error is now raised. Previously, behaviour was undefined but operations on the executor or its futures would often freeze or deadlock.

17.4.3.1. ProcessPoolExecutor Example

import concurrent.futures
import math

PRIMES = [
    112272535095293,
    112582705942171,
    112272535095293,
    115280095190773,
    115797848077099,
    1099726899285419]

def is_prime(n):
    if n % 2 == 0:
        return False

    sqrt_n = int(math.floor(math.sqrt(n)))
    for i in range(3, sqrt_n + 1, 2):
        if n % i == 0:
            return False
    return True

def main():
    with concurrent.futures.ProcessPoolExecutor() as executor:
        for number, prime in zip(PRIMES, executor.map(is_prime, PRIMES)):
            print('%d is prime: %s' % (number, prime))

if __name__ == '__main__':
    main()

17.4.4. Future Objects

The Future class encapsulates the asynchronous execution of a callable. Future instances are created by Executor.submit().

class concurrent.futures.Future

Encapsulates the asynchronous execution of a callable. Future instances are created by Executor.submit() and should not be created directly except for testing.

cancel()

Attempt to cancel the call. If the call is currently being executed and cannot be cancelled then the method will return False, otherwise the call will be cancelled and the method will return True.

cancelled()

Return True if the call was successfully cancelled.

running()

Return True if the call is currently being executed and cannot be cancelled.

done()

Return True if the call was successfully cancelled or finished running.

result(timeout=None)

Return the value returned by the call. If the call hasn’t yet completed then this method will wait up to timeout seconds. If the call hasn’t completed in timeout seconds, then a concurrent.futures.TimeoutError will be raised. timeout can be an int or float. If timeout is not specified or None, there is no limit to the wait time.

If the future is cancelled before completing then CancelledError will be raised.

If the call raised, this method will raise the same exception.

exception(timeout=None)

Return the exception raised by the call. If the call hasn’t yet completed then this method will wait up to timeout seconds. If the call hasn’t completed in timeout seconds, then a concurrent.futures.TimeoutError will be raised. timeout can be an int or float. If timeout is not specified or None, there is no limit to the wait time.

If the future is cancelled before completing then CancelledError will be raised.

If the call completed without raising, None is returned.

add_done_callback(fn)

Attaches the callable fn to the future. fn will be called, with the future as its only argument, when the future is cancelled or finishes running.

Added callables are called in the order that they were added and are always called in a thread belonging to the process that added them. If the callable raises an Exception subclass, it will be logged and ignored. If the callable raises a BaseException subclass, the behavior is undefined.

If the future has already completed or been cancelled, fn will be called immediately.

The following Future methods are meant for use in unit tests and Executor implementations.

set_running_or_notify_cancel()

This method should only be called by Executor implementations before executing the work associated with the Future and by unit tests.

If the method returns False then the Future was cancelled, i.e. Future.cancel() was called and returned True. Any threads waiting on the Future completing (i.e. through as_completed() or wait()) will be woken up.

If the method returns True then the Future was not cancelled and has been put in the running state, i.e. calls to Future.running() will return True.

This method can only be called once and cannot be called after Future.set_result() or Future.set_exception() have been called.

set_result(result)

Sets the result of the work associated with the Future to result.

This method should only be used by Executor implementations and unit tests.

set_exception(exception)

Sets the result of the work associated with the Future to the Exception exception.

This method should only be used by Executor implementations and unit tests.

17.4.5. Module Functions

concurrent.futures.wait(fs, timeout=None, return_when=ALL_COMPLETED)

Wait for the Future instances (possibly created by different Executor instances) given by fs to complete. Returns a named 2-tuple of sets. The first set, named done, contains the futures that completed (finished or were cancelled) before the wait completed. The second set, named not_done, contains uncompleted futures.

timeout can be used to control the maximum number of seconds to wait before returning. timeout can be an int or float. If timeout is not specified or None, there is no limit to the wait time.

return_when indique quand la fonction doit se terminer. Il peut prendre les valeurs suivantes :

Constante

Description

FIRST_COMPLETED

La fonction se termine lorsque n’importe quel futur se termine ou est annulé.

FIRST_EXCEPTION

La fonction se termine lorsque n’importe quel futur se termine en levant une exception. Si aucun futur ne lève d’exception, équivaut à ALL_COMPLETED.

ALL_COMPLETED

La fonction se termine lorsque les futurs sont tous finis ou annulés.

concurrent.futures.as_completed(fs, timeout=None)

Returns an iterator over the Future instances (possibly created by different Executor instances) given by fs that yields futures as they complete (finished or were cancelled). Any futures given by fs that are duplicated will be returned once. Any futures that completed before as_completed() is called will be yielded first. The returned iterator raises a concurrent.futures.TimeoutError if __next__() is called and the result isn’t available after timeout seconds from the original call to as_completed(). timeout can be an int or float. If timeout is not specified or None, there is no limit to the wait time.

Voir aussi

PEP 3148 [https://www.python.org/dev/peps/pep-3148] – futures - execute computations asynchronously

The proposal which described this feature for inclusion in the Python standard library.

17.4.6. Exception classes

exception concurrent.futures.CancelledError

Raised when a future is cancelled.

exception concurrent.futures.TimeoutError

Raised when a future operation exceeds the given timeout.

exception concurrent.futures.process.BrokenProcessPool

Derived from RuntimeError, this exception class is raised when one of the workers of a ProcessPoolExecutor has terminated in a non-clean fashion (for example, if it was killed from the outside).

Nouveau dans la version 3.3.

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17.5. subprocess — Gestion de sous-processus

Code source : Lib/subprocess.py [https://github.com/python/cpython/tree/3.6/Lib/subprocess.py]

Le module subprocess vous permet de lancer de nouveaux processus, les connecter à des tubes d’entrée/sortie/erreur, et d’obtenir leurs codes de retour. Ce module a l’intention de remplacer plusieurs anciens modules et fonctions :

os.system
os.spawn*

De plus amples informations sur comment le module subprocess peut être utilisé pour remplacer ces modules et fonctions peuvent être trouvées dans les sections suivantes.

Voir aussi

PEP 324 [https://www.python.org/dev/peps/pep-0324] – PEP proposant le module subprocess

17.5.1. Utiliser le module subprocess

L’approche recommandée pour invoquer un sous-processus et d’utiliser la fonction run() pour tous les cas d’utilisation qu’il gère. Pour les cas d’utilisation plus avancés, l’interface inhérente Popen peut être utilisée directement.

La fonction run() a été ajoutée avec Python 3.5 ; si vous avez besoin d’une compatibilité avec des versions plus anciennes, référez-vous à la section Ancienne interface (API) haut-niveau.

subprocess.run(args, *, stdin=None, input=None, stdout=None, stderr=None, shell=False, cwd=None, timeout=None, check=False, encoding=None, errors=None, env=None)

Lance la commande décrite par args. Attend que la commande se termine, puis renvoie une instance CompletedProcess.

Les arguments présentés ci-dessus sont simplement les plus utilisés, décrits ci-dessous dans la section Arguments fréquemment utilisés (d’où l’utilisation de la notation keyword-only dans la signature abrégée). La signature complète de la fonction est sensiblement la même que celle du constructeur de Popen - à l’exception de timeout, input et check, tous les arguments donnés à cette fonction passent à travers cette interface.

Les sorties standard (stdout) et d’erreur (stderr) ne sont pas capturées par défaut. Pour les capturer, utilisez PIPE comme valeur des arguments stdout et/ou stderr.

L’argument timeout est passé à Popen.communicate(). Si le timeout expire, le processus enfant sera tué et attendu. Une exception TimeoutExpired sera levée une fois que le processus enfant se sera terminé.

L’argument input est passé à Popen.communicate() et donc à l’entrée standard (stdin) du sous-processus. Si l’argument est utilisé, il doit contenir une séquence de bytes, ou une chaîne de caractères si encoding ou errors son spécifiés, ou si universal_newlines est vrai. Quand utilisé, l’objet interne Popen est automatiquement créé avec stdin=PIPE, et l’argument stdin ne doit donc pas être utilisé.

Si check est vrai, et que le processus s’arrête avec un code de statut non nul, une exception CalledProcessError est levée. Les attributs de cette exception contiennent les arguments, le code de statut, et les sorties standard et d’erreur si elles ont été capturées.

Si encoding ou errors sont spécifiés, ou universal_newlines est vrai, les fichiers pour les entrées et sorties sont ouverts en mode texte en utilisant les paramètres encoding et errors spécifiés, ou les valeurs par défaut de io.TextIOWrapper. Autrement, les fichiers sont ouverts en mode binaire.

Si env n’est pas None, il doit être un tableau associatif définissant les variables d’environnement du nouveau processus ; elles seront utilisées à la place du comportement par défaut qui est d’hériter de l’environnement du processus courant. Il est passé directement à Popen.

Exemples :

>>> subprocess.run(["ls", "-l"])  # doesn't capture output
CompletedProcess(args=['ls', '-l'], returncode=0)

>>> subprocess.run("exit 1", shell=True, check=True)
Traceback (most recent call last):
  ...
subprocess.CalledProcessError: Command 'exit 1' returned non-zero exit status 1

>>> subprocess.run(["ls", "-l", "/dev/null"], stdout=subprocess.PIPE)
CompletedProcess(args=['ls', '-l', '/dev/null'], returncode=0,
stdout=b'crw-rw-rw- 1 root root 1, 3 Jan 23 16:23 /dev/null\n')

Nouveau dans la version 3.5.

Modifié dans la version 3.6: Ajout des paramètres encoding et errors

class subprocess.CompletedProcess

La valeur de retour de run(), représentant un processus qui s’est terminé.

args

Les arguments utilisés pour lancer le processus. Cela peut être une liste ou une chaîne de caractères.

returncode

Le code de statut du processus fils. Typiquement, un code de statut de 0 indique qu’il s’est exécuté avec succès.

Une valeur négative -N indique que le processus enfant a été terminé par un signal N (seulement sur les systèmes POSIX).

stdout

La sortie standard capturée du processus enfant. Une séquence de bytes, ou une chaîne de caractères si run() a été appelée avec encoding ou errors. Vaut None si la sortie standard n’était pas capturée.

Si vous avez lancé le processus avec stderr=subprocess.STDOUT, les sorties standard et d’erreur seront combinées dans cet attribut, et stderr sera mis à None.

stderr

La sortie d’erreur capturée du processus enfant. Une séquence de bytes, ou une chaîne de caractères si run() a été appelée avec encoding ou errors. Vaut None si la sortie d’erreur n’était pas capturée.

check_returncode()

Si returncode n’est pas nul, lève une CalledProcessError.

Nouveau dans la version 3.5.

subprocess.DEVNULL

Valeur spéciale qui peut être utilisée pour les arguments stdin, stdout ou stderr de Popen et qui indique que le fichier spécial os.devnull sera utilisé.

Nouveau dans la version 3.3.

subprocess.PIPE

Valeur spéciale qui peut être utilisée pour les arguments stdin, stdout ou stderr de Popen et qui indique qu’un tube vers le flux standard doit être ouvert. Surtout utile avec Popen.communicate().

subprocess.STDOUT

Valeur spéciale qui peut être utilisée pour l’argument stderr de Popen et qui indique que la sortie d’erreur doit être redirigée vers le même descripteur que la sortie standard.

exception subprocess.SubprocessError

Classe de base à toutes les autres exceptions du module.

Nouveau dans la version 3.3.

exception subprocess.TimeoutExpired

Sous-classe de SubprocessError, levée quand un timeout expire pendant l’attente d’un processus enfant.

cmd

La commande utilisée pour instancier le processus fils.

timeout

Le timeout en secondes.

output

La sortie du processus fils, si capturée par run() ou check_output(). Autrement, None.

stdout

Alias pour output, afin d’avoir une symétrie avec stderr.

stderr

La sortie d’erreur du processus fils, si capturée par run(). Autrement, None.

Nouveau dans la version 3.3.

Modifié dans la version 3.5: Ajout des attributs stdout et stderr

exception subprocess.CalledProcessError

Sous-classe de SubprocessError, levée quand un processus lancé par check_call() ou check_output() renvoie un code de statut non nul.

returncode

Code de statut du processus fils. Si le processus a été arrêté par un signal, le code sera négatif et correspondra à l’opposé du numéro de signal.

cmd

La commande utilisée pour instancier le processus fils.

output

La sortie du processus fils, si capturée par run() ou check_output(). Autrement, None.

stdout

Alias pour output, afin d’avoir une symétrie avec stderr.

stderr

La sortie d’erreur du processus fils, si capturée par run(). Autrement, None.

Modifié dans la version 3.5: Ajout des attributs stdout et stderr

17.5.1.1. Arguments fréquemment utilisés

Pour gérer un large ensemble de cas, le constructeur de Popen (et les fonctions de convenance) acceptent de nombreux arguments optionnels. Pour les cas d’utilisation les plus typiques, beaucoup de ces arguments peuvent sans problème être laissés à leurs valeurs par défaut. Les arguments les plus communément nécessaires sont :

args est requis pour tous les appels et doit être une chaîne de caractères ou une séquence d’arguments du programme. Il est généralement préférable de fournir une séquence d’arguments, puisque cela permet au module de s’occuper des potentiels échappements ou guillemets autour des arguments (p. ex. pour permettre des espaces dans des noms de fichiers). Si l’argument est passé comme une simple chaîne, soit shell doit valoir True (voir ci-dessous) soit la chaîne doit simplement contenir le nom du programme à exécuter sans spécifier d’arguments supplémentaires.

stdin, stdout et stderr spécifient respectivement les descripteurs d’entrée standard, de sortie standard et de sortie d’erreur du programme exécuté. Les valeurs acceptées sont PIPE, DEVNULL, un descripteur de fichier existant (nombre entier positif), un objet de fichier, et None. PIPE indique qu’un nouveau tube vers le processus enfant sera créé. DEVNULL indique que le fichier spécial os.devnull sera utilisé. Avec les paramètres None par défaut, aucune redirection ne se produira, les descripteurs de fichiers du fils seront hérités du parent. Additionnellement, stderr peut valoir STDOUT, qui indique que les données de la sortie d’erreur du processus fils doivent être capturées dans le même descripteur de fichier que la sortie standard.

Si encoding ou errors sont spécifiés, ou si universal_newlines est vrai, les fichiers stdin, stdout et stderr seront ouverts en mode texte en utilisant les encoding et errors spécifiés à l’appel, ou les valeurs par défaut de io.TextIOWrapper.

Pour stdin, les caractères de fin de ligne '\n' de l’entrée seront convertis vers des séparateurs de ligne par défaut os.linesep. Pour stdout et stderr, toutes les fins de lignes des sorties seront converties vers '\n'. Pour plus d’informations, voir la documentation de la classe io.TextIOWrapper quand l’argument newline du constructeur est None.

Si le mode texte n’est pas utilisé, stdin, stdout et stderr seront ouverts comme des flux binaires. Aucune conversion d’encodage ou de fins de ligne ne sera réalisée.

Nouveau dans la version 3.6: Ajout des paramètres encoding et errors.

Note

L’attribut newlines des objets Popen.stdin, Popen.stdout et Popen.stderr ne sont pas mis à jour par la méthode Popen.communicate().

Si shell vaut True, la commande spécifiée sera exécutée à travers un shell. Cela peut être utile si vous utilisez Python pour le contrôle de flot qu’il propose par rapport à beaucoup de shells système et voulez tout de même profiter des autres fonctionnalités des shells telles que les tubes (pipes), les motifs de fichiers, l’expansion des variables d’environnement, et l’expansion du ~ vers le répertoire d’accueil de l’utilisateur. Cependant, notez que Python lui-même propose l’implémentation de beaucoup de ces fonctionnalités (en particulier glob, fnmatch, os.walk(), os.path.expandvars(), os.path.expanduser() et shutil).

Modifié dans la version 3.3: Quand universal_newlines vaut True, la classe utilise l’encodage locale.getpreferredencoding(False) plutôt que locale.getpreferredencoding(). Voir la classe io.TextIOWrapper pour plus d’informations sur ce changement.

Note

Lire la section Security Considerations avant d’utiliser shell=True.

Ces options, ainsi que toutes les autres, sont décrites plus en détails dans la documentation du constructeur de Popen.

17.5.1.2. Constructeur de Popen

La création et la gestion sous-jacentes des processus est gérée par la classe Popen. Elle offre beaucoup de flexibilité de façon à ce que les développeurs soient capables de gérer les cas d’utilisation les moins communs, non couverts par les fonctions de convenance.

class subprocess.Popen(args, bufsize=-1, executable=None, stdin=None, stdout=None, stderr=None, preexec_fn=None, close_fds=True, shell=False, cwd=None, env=None, universal_newlines=False, startupinfo=None, creationflags=0, restore_signals=True, start_new_session=False, pass_fds=(), *, encoding=None, errors=None)

Exécute un programme fils dans un nouveau processus. Sur les systèmes POSIX, la classe utilise un comportement similaire à os.execvp() pour exécuter le programme. Sur Windows, la classe utilise la fonction Windows CreateProcess(). Les arguments de Popen sont les suivants.

args doit être une séquence d’arguments du programme ou une chaîne seule. Par défaut, le programme à exécuter est le premier élément de args si args est une séquence. Si args est une chaîne, l’interprétation dépend de la plateforme et est décrite plus bas. Voir les arguments shell et executable pour d’autres différences avec le comportement par défaut. Sans autre indication, il est recommandé de passer args comme une séquence.

Sur les systèmes POSIX, si args est une chaîne, elle est interprétée comme le nom ou le chemin du programme à exécuter. Cependant, cela ne peut être fait que si le programme est passé sans arguments.

Note

shlex.split() peut être utilisée pour déterminer le découpage correct de args, spécifiquement dans les cas complexes :

>>> import shlex, subprocess
>>> command_line = input()
/bin/vikings -input eggs.txt -output "spam spam.txt" -cmd "echo '$MONEY'"
>>> args = shlex.split(command_line)
>>> print(args)
['/bin/vikings', '-input', 'eggs.txt', '-output', 'spam spam.txt', '-cmd', "echo '$MONEY'"]
>>> p = subprocess.Popen(args) # Success!

Notez en particulier que les options (comme -input) et arguments (comme eggs.txt) qui sont séparés par des espaces dans le shell iront dans des éléments séparés de la liste, alors que les arguments qui nécessitent des guillemets et échappements quand utilisés dans le shell (comme les noms de fichiers contenant des espaces ou la commande echo montrée plus haut) forment des éléments uniques.

Sous Windows, si args est une séquence, elle sera convertie vers une chaîne de caractères de la manière décrite dans Convertir une séquence d’arguments vers une chaîne de caractères sous Windows. Cela fonctionne ainsi parce que la fonction CreateProcess() opère sur des chaînes.

L’argument shell (qui vaut False par défaut) spécifie s’il faut utiliser un shell comme programme à exécuter. Si shell vaut True, il est recommandé de passer args comme une chaîne de caractères plutôt qu’une séquence.

Sur les systèmes POSIX avec shell=True, le shell par défaut est /bin/sh. Si args est une chaîne de caractères, la chaîne spécifie la commande à exécuter à travers le shell. Cela signifie que la chaîne doit être formatée exactement comme elle le serait si elle était tapée dans l’invite de commandes du shell. Cela inclut, par exemple, les guillemets ou les backslashs échappant les noms de fichiers contenant des espaces. Si args est une séquence, le premier élément spécifie la commande, et les éléments supplémentaires seront traités comme des arguments additionnels à passer au shell lui-même. Pour ainsi dire, Popen réalise l’équivalent de :

Popen(['/bin/sh', '-c', args[0], args[1], ...])

Sous Windows avec shell=True, la variable d’environnement COMSPEC spécifie le shell par défaut. La seule raison pour laquelle vous devriez spécifier shell=True sous Windows est quand la commande que vous souhaitez exécuter est une built-in du shell (p. ex. dir ou copy). Vous n’avez pas besoin de shell=True pour lancer un fichier batch ou un exécutable console.

Note

Lire la section Security Considerations avant d’utiliser shell=True.

bufsize sera fourni comme l’argument correspondant à la fonction open(), lors de la création des objets de fichiers pour les tubes stdin/stdout/stderr :

0 indique de ne pas utiliser de tampon (les lectures et écritures sont des appels systèmes et peuvent renvoyer des données incomplètes) ;

1 indique une mise en cache par ligne (utilisable seulement si universal_newlines=True, c’est-à-dire en mode texte) ;

toutes les autres valeurs positives indiquent d’utiliser un tampon d’approximativement cette taille ;

un bufsize négatif (par défaut) indique au système d’utiliser la valeur par défaut io.DEFAULT_BUFFER_SIZE.

Modifié dans la version 3.3.1: bufsize vaut maintenant -1 par défaut, pour activer par défaut la mise en cache et correspondre au comportement attendu par la plupart des codes. Dans les versions de Python antérieures à 3.2.4 et 3.3.1, par erreur, la valeur par défaut était 0 qui ne réalisait aucune mise en cache et autorisait les lectures incomplètes. Cela n’était pas intentionnel et ne correspondait pas au comportement de Python 2 attendu par la plupart des codes.

L’argument executable spécifie un programme de remplacement à exécuter. Il est très rarement nécessaire. Quand shell=False, executable remplace le programme à exécuter spécifié par args. Cependant, les arguments originels d”args` sont toujours passés au programme. La plupart des programmes traitent le programme spécifié par *args comme le nom de la commande, qui peut être différent du programme réellement exécuté. Sur les systèmes POSIX, le nom tiré d”args devient le nom affiché pour l’exécutable dans des utilitaires tels que ps. Si shell=True, sur les systèmes POSIX, l’argument executable précise le shell à utiliser plutôt que /bin/sh par défaut.

stdin, stdout et stderr spécifient respectivement les descripteurs d’entrée standard, de sortie standard et de sortie d’erreur du programme exécuté. Les valeurs acceptées sont PIPE, DEVNULL, un descripteur de fichier existant (nombre entier positif), un file object, et None. PIPE indique qu’un nouveau tube vers le processus enfant sera créé. DEVNULL indique que le fichier spécial os.devnull sera utilisé. Avec les paramètres None par défaut, aucune redirection ne se produira, les descripteurs de fichiers du fils seront hérités du parent. Additionnellement, stderr peut valoir STDOUT, qui indique que les données de la sortie d’erreur du processus fils doivent être capturées dans le même descripteur de fichier que la sortie standard.

Si un objet appelable est passé à preexec_fn, cet objet sera appelé dans le processus enfant juste avant d’exécuter le programme. (POSIX seulement)

Avertissement

Le paramètre preexec_fn n’est pas sain à utiliser en présence d’autres fils d’exécution dans votre application. Le processus fils pourrait être bloqué (deadlock) avant qu”exec ne soit appelée. Si vous devez utiliser ce paramètre, gardez son utilisation triviale ! Minimisez le nombre de bibliothèques que vous y appelez.

Note

Si vous devez modifier l’environnement du fils, utilisez le paramètre env plutôt que faire cela dans une preexec_fn. Le paramètre start_new_session peut prendre la place de preexec_fn qui était autrefois communément utilisé pour appeler os.setsid() dans le fils.

Si close_fds est vrai, tous les descripteurs de fichiers à l’exception de 0, 1 et 2 seront fermés avant que le processus fils ne soit exécuté. (POSIX seulement). La valeur par défaut varie selon les plateformes : il est toujours vrai sur les systèmes POSIX. Sous Windows, il est vrai quand stdin/stdout/stderr sont None, faux autrement. Sous Windows, si close_fds est vrai, aucun gestionnaire ne sera hérité par le processus fils. Notez que sous Windows, vous ne pouvez pas mettre close_fds à true et en même temps rediriger les entrées/sorties standards avec les paramètres stdin/stdout/stderr.

Modifié dans la version 3.2: La valeur par défaut de close_fds n’est plus False, comme décrit ci-dessus.

pass_fds est une séquence optionnelle de descripteurs de fichiers à garder ouverts entre le parent et l’enfant. Fournir pass_fds force close_fds à valoir True. (POSIX seulement)

Nouveau dans la version 3.2: Ajout du paramètre pass_fds.

Si cwd n’est pas None, la fonction change de répertoire courant pour cwd avant d’exécuter le fils. cwd peut être un objet str ou un chemin-compatible. En particulier, la fonction recherche executable (ou le premier élément d”args) relativement à cwd si le chemin d’exécution est relatif.

Modifié dans la version 3.6: le paramètre cwd accepte un path-like object.

Si restore_signals est vrai (par défaut), tous les signaux que Python a mis à SIG_IGN sont restaurés à SIG_DFL dans le processus fils avant l’appel à exec. Actuellement, cela inclut les signaux SIGPIPE, SIGXFZ et SIGXFSZ. (POSIX seulement)

Modifié dans la version 3.2: Ajout de restore_signals.

Si start_new_session est vrai, l’appel système à setsid() sera réalisé dans le processus fils avant l’exécution du sous-processus. (POSIX seulement)

Modifié dans la version 3.2: Ajout de start_new_session.

Si env n’est pas None, il doit être un tableau associatif définissant les variables d’environnement du nouveau processus ; elles seront utilisées à la place du comportement par défaut qui est d’hériter de l’environnement du processus courant.

Note

Si spécifié, env doit fournir chaque variable requise pour l’exécution du programme. Sous Windows, afin d’exécuter un side-by-side assembly [https://en.wikipedia.org/wiki/Side-by-Side_Assembly], l’environnement env spécifié doit contenir une variable SystemRoot valide.

Si encoding ou errors sont spécifiés, les fichiers stdin, stdout et stderr sont ouverts en mode texte, avec l’encodage et la valeur d”errors spécifiés, comme décrit ci-dessus dans Arguments fréquemment utilisés. Si universal_newlines vaut True, ils sont ouverts en mode texte avec l’encodage par défaut. Autrement, ils sont ouverts comme des flux binaires.

Nouveau dans la version 3.6: Ajout d”encoding et errors.

Si fourni, startupinfo sera un objet STARTUPINFO, qui sera passé à la fonction CreateProcess inhérente. creationflags, si fourni, peut valoir CREATE_NEW_CONSOLE ou CREATE_NEW_PROCESS_GROUP. (Windows seulement)

Les objets Popen sont gérés comme gestionnaires de contexte avec l’instruction with : à la sortie, les descripteurs de fichiers standards sont fermés, et le processus est attendu

with Popen(["ifconfig"], stdout=PIPE) as proc:
    log.write(proc.stdout.read())

Modifié dans la version 3.2: Ajout de la gestion des gestionnaires de contexte.

Modifié dans la version 3.6: Le destructeur de Popen émet maintenant un avertissement ResourceWarning si le processus fils est toujours en cours d’exécution.

17.5.1.3. Exceptions

Les exceptions levées dans le processus fils, avant que le nouveau programme n’ait commencé son exécution, seront relayées dans le parent. Additionnellement, l’objet de l’exception aura un attribut supplémentaire appelé child_traceback, une chaîne de caractères contenant la trace de l’exception du point de vue du fils.

L’exception la plus communément levée est OSError. Elle survient, par exemple, si vous essayez d’exécuter un fichier inexistant. Les applications doivent se préparer à traiter des exceptions OSError.

Une ValueError sera levée si Popen est appelé avec des arguments invalides.

check_call() et check_output() lèveront une CalledProcessError si le processus appelé renvoie un code de retour non nul.

Toutes les fonctions et méthodes qui acceptent un paramètre timeout, telles que call() et Popen.communicate() lèveront une TImeoutExpired si le timeout expire avant la fin du processus.

Toutes les exceptions définies dans ce module héritent de SubprocessError.

Nouveau dans la version 3.3: Ajout de la classe de base SubprocessError.

17.5.2. Considérations de sécurité

Contrairement à quelques autres fonctions popen, cette implémentation n’appellera jamais implicitement le shell du système. Cela signifie que tous les caractères, incluant les métacaractères des shells, peuvent être passés aux processus fils en toute sécurité. Si le shell est invoqué explicitement, avec shell=True, il est de la responsabilité de l’application d’assurer que les espaces et métacaractères sont échappés correctement pour éviter les vulnérabilités de type shell injection [https://en.wikipedia.org/wiki/Shell_injection#Shell_injection].

Avec shell=True, la fonction shlex.quote() peut être utilisée pour échapper proprement les espaces et métacaractères dans les chaînes qui seront utilisées pour construire les commandes shell.

17.5.3. Objets Popen

Les instances de la classe Popen possèdent les méthodes suivantes :

Popen.poll()

Vérifie que le processus enfant s’est terminé. Modifie et renvoie l’attribut returncode, sinon, renvoie None.

Popen.wait(timeout=None)

Attend qu’un processus enfant se termine. Modifie l’attribut returncode et le renvoie.

Si le processus ne se termine pas après le nombre de secondes spécifié par timeout, une exception TimeoutExpired est levée. Cela ne pose aucun problème d’attraper cette exception et de réessayer d’attendre.

Note

Cela provoquera un blocage (deadlock) lors de l’utilisation de stdout=PIPE ou stderr=PIPE si le processus fils génère tellement de données sur le tube qu’il le bloque, en attente que le système d’exploitation permette au tampon du tube d’accepter plus de données. Utilisez Popen.communicate() pour éviter ce problème lors de l’utilisation de tubes.

Note

Cette fonction est implémentée avec une attente active (appels non bloquants et sleep courts). Utilisez le module asyncio pour une attente asynchrone : voir asyncio.create_subprocess_exec.

Modifié dans la version 3.3: Ajout de timeout.

Obsolète depuis la version 3.4: N’utilisez pas le paramètre endtime. Il a été par mégarde exposé dans la version 3.3 mais laissé non-documenté, et était destiné à rester privé pour un usage interne. Utilisez plutôt timeout.

Popen.communicate(input=None, timeout=None)

Interagit avec le processus : envoie des données sur l’entrée standard, lit en retour les données sur les sorties standard et d’erreur, et attend que le processus se termine. L’argument optionnel input contient les données à envoyer au processus fils, ou None s’il n’y a aucune donnée à lui transmettre. Si les flux sont ouverts en mode texte, input doit être une chaîne de caractère. Autrement, ce doit être un objet bytes.

communicate() renvoie un tuple (stdout_data, stderr_data). Les données seront des chaînes de caractères si les flux sont ouverts en mode texte, et des objets bytes dans le cas contraire.

Notez que si vous souhaitez envoyer des données sur l’entrée standard du processus, vous devez créer l’objet Popen avec stdin=PIPE. Similairement, pour obtenir autre chose que None dans le tuple résultant, vous devez aussi préciser stdout=PIPE et/ou stderr=PIPE.

Si le processus ne se termine pas après timeout secondes, une exception TimeoutExpired est levée. Attraper cette exception et retenter la communication ne fait perdre aucune donnée de sortie.

Le processus enfant n’est pas tué si le timeout expire, donc afin de nettoyer proprement le tout, une application polie devrait tuer le processus fils et terminer la communication :

proc = subprocess.Popen(...)
try:
    outs, errs = proc.communicate(timeout=15)
except TimeoutExpired:
    proc.kill()
    outs, errs = proc.communicate()

Note

Les données lues sont mises en cache en mémoire, donc n’utilisez pas cette méthode si la taille des données est importante voire illimitée.

Modifié dans la version 3.3: Ajout de timeout.

Popen.send_signal(signal)

Envoie le signal signal au fils.

Note

Sous Windows, SIGTERM est un alias pour terminate(). CTRL_C_EVENT et CTRL_BREAK_EVENT peuvent être envoyés aux processus démarrés avec un paramètre creationflags incluant CREATE_NEW_PROCESS_GROUP.

Popen.terminate()

Stoppe le processus fils. Sur les systèmes POSIX, la méthode envoie un signal SIGTERM au fils. Sous Windows, la fonction TerminateProcess() de l’API Win32 est appelée pour arrêter le fils.

Popen.kill()

Tue le processus fils. Sur les systèmes POSIX, la fonction envoie un signal SIGKILL au fils. Sous Windows, kill() est un alias pour terminate().

Les attributs suivants sont aussi disponibles :

Popen.args

L’argument args tel que passé à Popen – une séquence d’arguments du programme ou une simple chaîne de caractères.

Nouveau dans la version 3.3.

Popen.stdin

Si l’argument stdin valait PIPE, cet attribut est un flux accessible en écriture comme renvoyé par open(). Si les arguments encoding ou errors ont été spécifiés, ou si universal_newlines valait True, le flux est textuel, il est autrement binaire. Si l’argument stdin ne valait pas PIPE, cet attribut est None.

Popen.stdout

Si l’argument stdout valait PIPE, cet attribut est un flux accessible en lecture comme renvoyé par open(). Lire depuis le flux fournit la sortie du processus fils. Si les arguments encoding ou errors ont été spécifiés, ou si universal_newlines valait True, le flux est textuel, il est autrement binaire. Si l’argument stdout ne valait pas PIPE, cet attribut est None.

Popen.stderr

Si l’argument stderr valait PIPE, cet attribut est un flux accessible en lecture comme renvoyé par open(). Lire depuis le flux fournit la sortie d’erreur du processus fils. Si les arguments encoding ou errors ont été spécifiés, ou si universal_newlines valait True, le flux est textuel, il est autrement binaire. Si l’argument stderr ne valait pas PIPE, cet attribut est None.

Avertissement

Utilisez communicate() plutôt que .stdin.write, .stdout.read ou .stderr.read pour empêcher les deadlocks dus au remplissage des tampons des tubes de l’OS et bloquant le processus enfant.

Popen.pid

L’identifiant de processus du processus enfant.

Notez que si vous passez l’argument shell à True, il s’agit alors de l’identifiant du shell instancié.

Popen.returncode

Le code de retour de l’enfant, attribué par poll() et wait() (et indirectement par communicate()). Une valeur None indique que le processus ne s’est pas encore terminé.

Une valeur négative -N indique que le processus enfant a été terminé par un signal N (seulement sur les systèmes POSIX).

17.5.4. Utilitaires Popen pour Windows

La classe STARTUPINFO et les constantes suivantes sont seulement disponibles sous Windows.

class subprocess.STARTUPINFO

Un support partiel de la structure STARTUPINFO [https://msdn.microsoft.com/en-us/library/ms686331(v=vs.85).aspx] de Windows est utilisé lors de la création d’un objet Popen.

dwFlags

Un champ de bits déterminant si certains attributs STARTUPINFO sont utilisés quand le processus crée une fenêtre

si = subprocess.STARTUPINFO()
si.dwFlags = subprocess.STARTF_USESTDHANDLES | subprocess.STARTF_USESHOWWINDOW

hStdInput

Si dwFlags spécifie STARTF_USESTDHANDLES, cet attribut est le descripteur d’entrée standard du processus. Si STARTF_USESTDHANDLES n’est pas spécifié, l’entrée standard par défaut est le tampon du clavier.

hStdOutput

Si dwFlags spécifie STARTF_USESTDHANDLES, cet attribut est le descripteur de sortie standard du processus. Autrement, l’attribut est ignoré et la sortie standard par défaut est le tampon de la console.

hStdError

Si dwFlags spécifie STARTF_USESTDHANDLES, cet attribut est le descripteur de sortie d’erreur du processus. Autrement, l’attribut est ignoré et la sortie d’erreur par défaut est le tampon de la console.

wShowWindow

Si dwFlags spécifie STARTF_USESHOWWINDOW, cet attribut peut-être n’importe quel attribut valide pour le paramètre nCmdShow de la fonction ShowWindow [https://msdn.microsoft.com/en-us/library/ms633548(v=vs.85).aspx], à l’exception de SW_SHOWDEFAULT. Autrement, cet attribut est ignoré.

SW_HIDE est fourni pour cet attribut. Il est utilisé quand Popen est appelée avec shell=True.

17.5.4.1. Constantes

Le module subprocess expose les constantes suivantes.

subprocess.STD_INPUT_HANDLE

Le périphérique d’entrée standard. Initialement, il s’agit du tampon de la console d’entrée, CONIN$.

subprocess.STD_OUTPUT_HANDLE

Le périphérique de sortie standard. Initialement, il s’agit du tampon de l’écran de console actif, CONOUT$.

subprocess.STD_ERROR_HANDLE

Le périphérique de sortie d’erreur. Initialement, il s’agit du tampon de l’écran de console actif, CONOUT$.

subprocess.SW_HIDE

Cache la fenêtre. Une autre fenêtre sera activée.

subprocess.STARTF_USESTDHANDLES

Spécifie que les attributs STARTUPINFO.hStdInput, STARTUPINFO.hStdOutput et STARTUPINFO.hStdError contiennent des informations additionnelles.

subprocess.STARTF_USESHOWWINDOW

Spécifie que l’attribut STARTUPINFO.wShowWindow contient des informations additionnelles.

subprocess.CREATE_NEW_CONSOLE

Le nouveau processus instancie une nouvelle console, plutôt que d’hériter de celle de son père (par défaut).

subprocess.CREATE_NEW_PROCESS_GROUP

Paramètre creationflags de Popen pour spécifier si un nouveau groupe de processus doit être créé. Cette option est nécessaire pour utiliser os.kill() sur le sous-processus.

L’option est ignorée si CREATE_NEW_CONSOLE est spécifié.

17.5.5. Ancienne interface (API) haut-niveau

Avant Python 3.5, ces trois fonctions représentaient l’API haut-niveau de subprocess. Vous pouvez maintenant utiliser run() dans de nombreux cas, mais beaucoup de codes existant font appel à ces trois fonctions.

subprocess.call(args, *, stdin=None, stdout=None, stderr=None, shell=False, cwd=None, timeout=None)

Lance la commande décrite par args, attend qu’elle se termine, et renvoie son attribut returncode.

C’est équivalent à :

run(...).returncode

(excepté que les paramètres input et check ne sont pas supportés)

Les arguments montrés plus haut sont sûrement les plus communs. La signature complète de la fonction est en grande partie la même que le constructeur de Popen : cette fonction passe tous les arguments fournis autre que timeout directement à travers cette interface.

Note

N’utilisez pas stdout=PIPE ou stderr=PIPE avec cette fonction. Le processus enfant bloquera s’il génère assez de données pour remplir le tampon du tube de l’OS, puisque les tubes ne seront jamais lus.

Modifié dans la version 3.3: Ajout de timeout.

subprocess.check_call(args, *, stdin=None, stdout=None, stderr=None, shell=False, cwd=None, timeout=None)

Lance la commande avec les arguments et attend qu’elle se termine. Se termine normalement si le code de retour est zéro, et lève une CalledProcessError autrement. L’objet CalledProcessError contiendra le code de retour dans son attribut returncode.

C’est équivalent à :

run(..., check=True)

(excepté que le paramètre input n’est pas pris en charge)

Les arguments montrés plus haut sont sûrement les plus communs. La signature complète de la fonction est en grande partie la même que le constructeur de Popen : cette fonction passe tous les arguments fournis autre que timeout directement à travers cette interface.

Note

N’utilisez pas stdout=PIPE ou stderr=PIPE avec cette fonction. Le processus enfant bloquera s’il génère assez de données pour remplir le tampon du tube de l’OS, puisque les tubes ne seront jamais lus.

Modifié dans la version 3.3: Ajout de timeout.

subprocess.check_output(args, *, stdin=None, stderr=None, shell=False, cwd=None, encoding=None, errors=None, universal_newlines=False, timeout=None)

Lance la commande avec les arguments et renvoie sa sortie.

Si le code de retour est non-nul, la fonction lève une CalledProcessError. L’objet CalledProcessError contiendra le code de retour dans son attribut returncode, et la sortie du programme dans son attribut output.

C’est équivalent à :

run(..., check=True, stdout=PIPE).stdout

Les arguments montrés plus haut sont sûrement les plus communs. La signature complète de la fonction est en grande partie la même que run() : la plupart des arguments sont passés directement par cette interface. Cependant, passer explicitement input=None pour hériter du gestionnaire d’entrée standard du parent n’est pas supporté.

Par défaut, cette fonction renvoie les données encodées sous forme de bytes. Le réel encodage des données de sortie peut dépendre de la commande invoquée, donc le décodage du texte devra souvent être géré au niveau de l’application.

Ce comportement peut être redéfini en mettant universal_newlines à True comme décrit ci-dessus dans Arguments fréquemment utilisés.

Pour capturer aussi la sortie d’erreur dans le résultat, utilisez stderr=subprocess.STDOUT :

>>> subprocess.check_output(
...     "ls non_existent_file; exit 0",
...     stderr=subprocess.STDOUT,
...     shell=True)
'ls: non_existent_file: No such file or directory\n'

Nouveau dans la version 3.1.

Modifié dans la version 3.3: Ajout de timeout.

Modifié dans la version 3.4: Ajout de la gestion de l’argument nommé input.

Modifié dans la version 3.6: Ajout d”encoding et errors. Consultez run() pour plus d’informations.

17.5.6. Remplacer les fonctions plus anciennes par le module subprocess

Dans cette section, « a devient b » signifie que b peut être utilisée en remplacement de a.

Note

Toutes les fonctions « a » dans cette section échouent (plus ou moins) silencieusement si le programme à exécuter ne peut être trouvé ; les fonctions « b » de remplacement lèvent à la place une OSError.

De plus, les remplacements utilisant check_output() échoueront avec une CalledProcessError si l’opération requise produit un code de retour non-nul. La sortie est toujours disponible par l’attribut output de l’exception levée.

Dans les exemples suivants, nous supposons que les fonctions utilisées ont déjà été importées depuis le module subprocess.

17.5.6.1. Remplacement des backquotes des shells /bin/sh

output=`mycmd myarg`

devient :

output = check_output(["mycmd", "myarg"])

17.5.6.2. Remplacer les pipes du shell

output=`dmesg | grep hda`

devient :

p1 = Popen(["dmesg"], stdout=PIPE)
p2 = Popen(["grep", "hda"], stdin=p1.stdout, stdout=PIPE)
p1.stdout.close()  # Allow p1 to receive a SIGPIPE if p2 exits.
output = p2.communicate()[0]

L’appel à p1.stdout.close() après le démarrage de p2 est important pour que p1 reçoive un SIGPIPE si p2 se termine avant lui.

Alternativement, pour des entrées fiables, la gestion des tubes du shell peut directement être utilisé :

output=`dmesg | grep hda`

devient :

output=check_output("dmesg | grep hda", shell=True)

17.5.6.3. Remplacer os.system()

sts = os.system("mycmd" + " myarg")
# becomes
sts = call("mycmd" + " myarg", shell=True)

Notes :

Appeler le programme à travers un shell n’est habituellement pas requis.

Un exemple plus réaliste ressemblerait à cela :

try:
    retcode = call("mycmd" + " myarg", shell=True)
    if retcode < 0:
        print("Child was terminated by signal", -retcode, file=sys.stderr)
    else:
        print("Child returned", retcode, file=sys.stderr)
except OSError as e:
    print("Execution failed:", e, file=sys.stderr)

17.5.6.4. Remplacer les fonctions de la famille os.spawn

Exemple avec P_NOWAIT :

pid = os.spawnlp(os.P_NOWAIT, "/bin/mycmd", "mycmd", "myarg")
==>
pid = Popen(["/bin/mycmd", "myarg"]).pid

Exemple avec P_WAIT :

retcode = os.spawnlp(os.P_WAIT, "/bin/mycmd", "mycmd", "myarg")
==>
retcode = call(["/bin/mycmd", "myarg"])

Exemple avec un tableau :

os.spawnvp(os.P_NOWAIT, path, args)
==>
Popen([path] + args[1:])

Exemple en passant un environnement :

os.spawnlpe(os.P_NOWAIT, "/bin/mycmd", "mycmd", "myarg", env)
==>
Popen(["/bin/mycmd", "myarg"], env={"PATH": "/usr/bin"})

17.5.6.5. Remplacer os.popen(), os.popen2(), os.popen3()

(child_stdin, child_stdout) = os.popen2(cmd, mode, bufsize)
==>
p = Popen(cmd, shell=True, bufsize=bufsize,
          stdin=PIPE, stdout=PIPE, close_fds=True)
(child_stdin, child_stdout) = (p.stdin, p.stdout)

(child_stdin,
 child_stdout,
 child_stderr) = os.popen3(cmd, mode, bufsize)
==>
p = Popen(cmd, shell=True, bufsize=bufsize,
          stdin=PIPE, stdout=PIPE, stderr=PIPE, close_fds=True)
(child_stdin,
 child_stdout,
 child_stderr) = (p.stdin, p.stdout, p.stderr)

(child_stdin, child_stdout_and_stderr) = os.popen4(cmd, mode, bufsize)
==>
p = Popen(cmd, shell=True, bufsize=bufsize,
          stdin=PIPE, stdout=PIPE, stderr=STDOUT, close_fds=True)
(child_stdin, child_stdout_and_stderr) = (p.stdin, p.stdout)

La gestion du code de retour se traduit comme suit :

pipe = os.popen(cmd, 'w')
...
rc = pipe.close()
if rc is not None and rc >> 8:
    print("There were some errors")
==>
process = Popen(cmd, stdin=PIPE)
...
process.stdin.close()
if process.wait() != 0:
    print("There were some errors")

17.5.6.6. Remplacer les fonctions du module popen2

Note

Si l’argument cmd des fonctions de popen2 est une chaîne de caractères, la commande est exécutée à travers /bin/sh. Si c’est une liste, la commande est directement exécutée.

(child_stdout, child_stdin) = popen2.popen2("somestring", bufsize, mode)
==>
p = Popen("somestring", shell=True, bufsize=bufsize,
          stdin=PIPE, stdout=PIPE, close_fds=True)
(child_stdout, child_stdin) = (p.stdout, p.stdin)

(child_stdout, child_stdin) = popen2.popen2(["mycmd", "myarg"], bufsize, mode)
==>
p = Popen(["mycmd", "myarg"], bufsize=bufsize,
          stdin=PIPE, stdout=PIPE, close_fds=True)
(child_stdout, child_stdin) = (p.stdout, p.stdin)

popen2.Popen3 et popen2.Popen4 fonctionnent basiquement comme subprocess.Popen, excepté que :

Popen lève une exception si l’exécution échoue.

L’argument capturestderr est remplacé par stderr.

stdin=PIPE et stdout=PIPE doivent être spécifiés.

popen2 ferme tous les descripteurs de fichiers par défaut, mais vous devez spécifier close_fds=True avec Popen pour garantir ce comportement sur toutes les plateformes ou les anciennes versions de Python.

17.5.7. Remplacement des fonctions originales d’invocation du shell

Ce module fournit aussi les fonctions suivantes héritées du module commands de Python 2.x. Ces opérations invoquent implicitement le shell du système et n’apportent aucune des garanties décrites ci-dessus par rapport à la sécurité ou la cohérence de la gestion des exceptions.

subprocess.getstatusoutput(cmd)

Renvoie les valeurs (exitcode, output) de l’exécution de cmd dans un shell.

Exécute la chaîne cmd dans un shell avec Popen.check_output() et renvoie un tuple de 2 éléments (exitcode, output). L’encodage local est utilisé, voir les notes de la section Arguments fréquemment utilisés pour plus de détails.

Si la sortie se termine par un caractère de fin de ligne, ce dernier est supprimé. Le code de statut de la commande peut être interprété comme le code de retour de subprocess. Par exemple :

>>> subprocess.getstatusoutput('ls /bin/ls')
(0, '/bin/ls')
>>> subprocess.getstatusoutput('cat /bin/junk')
(1, 'cat: /bin/junk: No such file or directory')
>>> subprocess.getstatusoutput('/bin/junk')
(127, 'sh: /bin/junk: not found')
>>> subprocess.getstatusoutput('/bin/kill $$')
(-15, '')

Disponibilité : POSIX et Windows

Modifié dans la version 3.3.4: Ajout de la gestion de Windows.

The function now returns (exitcode, output) instead of (status, output) as it did in Python 3.3.3 and earlier. exitcode has the same value as returncode.

subprocess.getoutput(cmd)

Renvoie la sortie (standard et d’erreur) de l’exécution de cmd dans un shell.

Like getstatusoutput(), except the exit code is ignored and the return value is a string containing the command’s output. Example:

>>> subprocess.getoutput('ls /bin/ls')
'/bin/ls'

Disponibilité : POSIX et Windows

Modifié dans la version 3.3.4: Ajout de la gestion de Windows

17.5.8. Notes

17.5.8.1. Convertir une séquence d’arguments vers une chaîne de caractères sous Windows

Sous Windows, une séquence args est convertie vers une chaîne qui peut être analysée avec les règles suivantes (qui correspondent aux règles utilisées par l’environnement MS C) :

Les arguments sont délimités par des espacements, qui peuvent être des espaces ou des tabulations.

Une chaîne entourée de double guillemets est interprétée comme un argument seul, qu’elle contienne ou non des espacements. Une chaîne entre guillemets peut être intégrée dans un argument.

Un guillemet double précédé d’un backslash est interprété comme un guillemet double littéral.

Les backslashs sont interprétés littéralement, à moins qu’ils précèdent immédiatement un guillemet double.

Si des backslashs précèdent directement un guillemet double, toute paire de backslashs est interprétée comme un backslash littéral. Si le nombre de backslashs est impair, le dernier backslash échappe le prochain guillemet double comme décrit en règle 3.

Voir aussi

shlex

Module qui fournit des fonctions pour analyser et échapper les lignes de commandes.

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17.6. sched — Event scheduler

Code source : Lib/sched.py [https://github.com/python/cpython/tree/3.6/Lib/sched.py]

The sched module defines a class which implements a general purpose event scheduler:

class sched.scheduler(timefunc=time.monotonic, delayfunc=time.sleep)

The scheduler class defines a generic interface to scheduling events. It needs two functions to actually deal with the « outside world » — timefunc should be callable without arguments, and return a number (the « time », in any units whatsoever). If time.monotonic is not available, the timefunc default is time.time instead. The delayfunc function should be callable with one argument, compatible with the output of timefunc, and should delay that many time units. delayfunc will also be called with the argument 0 after each event is run to allow other threads an opportunity to run in multi-threaded applications.

Modifié dans la version 3.3: timefunc and delayfunc parameters are optional.

Modifié dans la version 3.3: scheduler class can be safely used in multi-threaded environments.

Exemple :

>>> import sched, time
>>> s = sched.scheduler(time.time, time.sleep)
>>> def print_time(a='default'):
...     print("From print_time", time.time(), a)
...
>>> def print_some_times():
...     print(time.time())
...     s.enter(10, 1, print_time)
...     s.enter(5, 2, print_time, argument=('positional',))
...     s.enter(5, 1, print_time, kwargs={'a': 'keyword'})
...     s.run()
...     print(time.time())
...
>>> print_some_times()
930343690.257
From print_time 930343695.274 positional
From print_time 930343695.275 keyword
From print_time 930343700.273 default
930343700.276

17.6.1. Scheduler Objects

scheduler instances have the following methods and attributes:

scheduler.enterabs(time, priority, action, argument=(), kwargs={})

Schedule a new event. The time argument should be a numeric type compatible with the return value of the timefunc function passed to the constructor. Events scheduled for the same time will be executed in the order of their priority. A lower number represents a higher priority.

Executing the event means executing action(*argument, **kwargs). argument is a sequence holding the positional arguments for action. kwargs is a dictionary holding the keyword arguments for action.

Return value is an event which may be used for later cancellation of the event (see cancel()).

Modifié dans la version 3.3: argument parameter is optional.

Nouveau dans la version 3.3: kwargs parameter was added.

scheduler.enter(delay, priority, action, argument=(), kwargs={})

Schedule an event for delay more time units. Other than the relative time, the other arguments, the effect and the return value are the same as those for enterabs().

Modifié dans la version 3.3: argument parameter is optional.

Nouveau dans la version 3.3: kwargs parameter was added.

scheduler.cancel(event)

Remove the event from the queue. If event is not an event currently in the queue, this method will raise a ValueError.

scheduler.empty()

Return true if the event queue is empty.

scheduler.run(blocking=True)

Run all scheduled events. This method will wait (using the delayfunc() function passed to the constructor) for the next event, then execute it and so on until there are no more scheduled events.

If blocking is false executes the scheduled events due to expire soonest (if any) and then return the deadline of the next scheduled call in the scheduler (if any).

Either action or delayfunc can raise an exception. In either case, the scheduler will maintain a consistent state and propagate the exception. If an exception is raised by action, the event will not be attempted in future calls to run().

If a sequence of events takes longer to run than the time available before the next event, the scheduler will simply fall behind. No events will be dropped; the calling code is responsible for canceling events which are no longer pertinent.

Nouveau dans la version 3.3: blocking parameter was added.

scheduler.queue

Read-only attribute returning a list of upcoming events in the order they will be run. Each event is shown as a named tuple with the following fields: time, priority, action, argument, kwargs.

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17.7. queue — File synchronisée

Code source : Lib/queue.py [https://github.com/python/cpython/tree/3.6/Lib/queue.py]

Le module queue implémente des files multi-productrices et multi-consommatrices. C’est particulièrement utile en programmation multi-thread, lorsque les informations doivent être échangées sans risques entre plusieurs threads. La classe Queue de ce module implémente tout le verrouillage nécessaire. Cela dépend de la disponibilité du support des fils d’exécution en Python; voir le module threading.

Le module implémente trois types de files qui différent par l’ordre dans lequel les éléments en sont extraits. Dans une file FIFO, les premiers éléments ajoutés sont les premiers extraits. Dans une file LIFO, le dernier élément ajouté est le premier élément extrait (se comporte comme une pile). Avec une file de priorité, les entrées restent triés (en utilisant le module heapq) et l’élément ayant la valeur la plus faible est extrait en premier.

En interne, le module utilise des verrous pour bloquer temporairement des fils d’exécution concurrents. Cependant, il n’a pas été conçu pour être réentrant au sein d’un fil d’exécution.

Le module queue définit les classes et les exceptions suivantes :

class queue.Queue(maxsize=0)

Constructeur pour une file FIFO. maxsize est un entier définissant le nombre maximal d’éléments pouvant être mis dans la file. L’insertion sera bloquée lorsque cette borne supérieure sera atteinte, jusqu’à ce que des éléments de la file soient consommés. Si maxsize est inférieur ou égal à 0, la taille de la file sera infinie.

class queue.LifoQueue(maxsize=0)

Constructeur pour une file LIFO. maxsize est un entier définissant le nombre maximal d’éléments pouvant être mis dans la file. L’insertion sera bloquée lorsque cette borne supérieure sera atteinte, jusqu’à ce que des éléments de la file soient consommés. Si maxsize est inférieur ou égal à 0, la taille de la file sera infinie.

class queue.PriorityQueue(maxsize=0)

Constructeur pour une file de priorité. maxsize est un entier définissant le nombre maximal d’éléments pouvant être mis dans la file. L’insertion sera bloquée lorsque cette borne supérieure sera atteinte, jusqu’à ce que des éléments soient consommés. Si maxsize est inférieur ou égal à 0, la taille de la file sera infinie.

Les éléments de valeurs les plus faibles sont extraits en premier (l’élément de valeur la plus faible est celui renvoyé par sorted(list(entries))[0]). Un cas typique est d’utiliser des tuple de la forme : (priority_number, data).

exception queue.Empty

Exception levée lorsque la méthode non bloquante get() (ou get_nowait()) est appelée sur l’objet Queue vide.

exception queue.Full

Exception levée lorsque la méthode non bloquante put() (ou put_nowait()) est appelée sur un objet Queue plein.

17.7.1. Objets Queue

Les objets Queue (Queue, LifoQueue ou PriorityQueue) fournissent les méthodes publiques décrites ci-dessous.

Queue.qsize()

Renvoie la taille approximative de la file. Notez que qsize() > 0 ne garantit pas qu’un get() ultérieur ne sera pas bloquant et que qsize() < maxsize ne garantit pas non plus qu’un put() ne sera pas bloquant.

Queue.empty()

Renvoie True si la file est vide, False sinon. Si empty() renvoie True, cela ne garantit pas qu’un appel ultérieur à put() ne sera pas bloquant. Similairement, si empty() renvoie False, cela ne garantit pas qu’un appel ultérieur à get() ne sera pas bloquant.

Queue.full()

Renvoie True si la file est pleine, False sinon. Si full() renvoie``True``, cela ne garantit pas qu’un appel ultérieur à get() ne sera pas bloquant. Similairement, si full() retourne False, cela ne garantit pas qu’un appel ultérieur à put() ne sera pas bloquant.

Queue.put(item, block=True, timeout=None)

Met item dans la file. Si les arguments optionnels block et timeout sont respectivement True et None (les valeurs par défaut), la méthode bloque si nécessaire jusqu’à ce qu’un emplacement libre soit disponible. Si timeout est un nombre positif, elle bloque au plus timeout secondes et lève l’exception Full s’il n’y avait pas d’emplacement libre pendant cette période de temps. Sinon (block est False), elle met un élément dans la file s’il y a un emplacement libre immédiatement disponible. Si ce n’est pas le cas, elle lève l’exception Full (timeout est ignoré dans ce cas).

Queue.put_nowait(item)

Équivalent à put(item, False).

Queue.get(block=True, timeout=None)

Retire et renvoie un élément de la file. Si les arguments optionnels block et timeout valent respectivement True et None (les valeurs par défaut), la méthode bloque si nécessaire jusqu’à ce qu’un élément soit disponible. Si timeout est un entier positif, elle bloque au plus timeout secondes et lève l’exception Empty s’il n’y avait pas d’élément disponible pendant cette période de temps. Sinon (block vaut False), elle renvoie un élément s’il y en a un immédiatement disponible. Si ce n’est pas le cas, elle lève l’exception Empty (timeout est ignoré dans ce cas).

Queue.get_nowait()

Équivalent à get(False).

Deux méthodes sont proposées afin de savoir si les tâches mises dans la file ont été entièrement traitées par les fils d’exécution consommateurs du démon.

Queue.task_done()

Indique qu’une tâche précédemment mise dans la file est terminée. Utilisé par les fils d’exécution consommateurs de la file. Pour chaque appel à get() effectué afin de récupérer une tâche, un appel ultérieur à task_done() informe la file que le traitement de la tâche est terminé.

Si un join() est actuellement bloquant, on reprendra lorsque tous les éléments auront été traités (ce qui signifie qu’un appel à task_done() a été effectué pour chaque élément qui a été put() dans la file).

Lève une exception ValueError si appelée plus de fois qu’il y avait d’éléments dans la file.

Queue.join()

Bloque jusqu’à ce que tous les éléments de la file aient été obtenus et traités.

Le nombre de tâches inachevées augmente chaque fois qu’un élément est ajouté à la file. Ce nombre diminue chaque fois qu’un fil d’exécution consommateur appelle task_done() pour indiquer que l’élément a été extrait et que tout le travail à effectuer dessus est terminé. Lorsque le nombre de tâches non terminées devient nul, join() débloque.

Exemple montrant comment attendre que les tâches mises dans la file soient terminées :

def worker():
    while True:
        item = q.get()
        if item is None:
            break
        do_work(item)
        q.task_done()

q = queue.Queue()
threads = []
for i in range(num_worker_threads):
    t = threading.Thread(target=worker)
    t.start()
    threads.append(t)

for item in source():
    q.put(item)

# block until all tasks are done
q.join()

# stop workers
for i in range(num_worker_threads):
    q.put(None)
for t in threads:
    t.join()

Voir aussi

Classe multiprocessing.Queue

Une file à utiliser dans un contexte multi-processus (plutôt que multi-thread).

collections.deque est une implémentation alternative de file non bornée avec des méthodes append() et popleft() rapides et atomiques ne nécessitant pas de verrouillage.

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17.8. dummy_threading — Module de substitution au module threading

Code source : Lib/dummy_threading.py [https://github.com/python/cpython/tree/3.6/Lib/dummy_threading.py]

Ce module fournit un duplicat de l’interface du module threading. Son but est d’être importé lorsque le module _thread n’est pas fournit par la plateforme.

Utilisation suggérée :

try:
    import threading
except ImportError:
    import dummy_threading as threading

Soyez prudent de ne pas utiliser ce module lorsqu’un interblocage (deadlock en anglais) peut se produire à partir d’un fil d’exécution en cours de création qui bloque en attentant qu’un autre fil d’exécution soit créé. Cela se produit souvent avec des I/O bloquants.

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17.9. _thread — API bas niveau de gestion de fils d’exécution

Ce module fournit les primitives de bas niveau pour travailler avec de multiples fils d’exécution (aussi appelés light-weight processes ou tasks) — plusieurs fils d’exécution de contrôle partagent leur espace de données global. Pour la synchronisation, de simples verrous (aussi appelés des mutexes ou des binary semaphores) sont fournis. Le module threading fournit une API de fils d’exécution de haut niveau, plus facile à utiliser et construite à partir de ce module.

The module is optional. It is supported on Windows, Linux, SGI IRIX, Solaris 2.x, as well as on systems that have a POSIX thread (a.k.a. « pthread ») implementation. For systems lacking the _thread module, the _dummy_thread module is available. It duplicates this module’s interface and can be used as a drop-in replacement.

Elle définit les constantes et fonctions suivantes :

exception _thread.error

Levée lors d’erreurs spécifiques aux fils d’exécution.

Modifié dans la version 3.3: Ceci est à présent un synonyme de l’exception native RuntimeError.

_thread.LockType

C’est le type d’objets verrous.

_thread.start_new_thread(function, args[, kwargs])

Démarre un nouveau fils d’exécution et renvoie son identifiant. Ce fil d’exécution exécute la fonction function avec la liste d’arguments args (qui doit être un tuple). L’argument optionnel kwargs spécifie un dictionnaire d’arguments de mots clés. Quand la fonction se termine, le fil d’exécution se termine silencieusement. Quand la fonction termine avec une exception non gérée, une trace de la pile est affichée et ensuite le fil d’exécution s’arrête (mais les autres fils d’exécutions continuent de s’exécuter).

_thread.interrupt_main()

Raise a KeyboardInterrupt exception in the main thread. A subthread can use this function to interrupt the main thread.

_thread.exit()

Lève une exception SystemExit. Quand elle n’est pas interceptée, le fil d’exécution se terminera silencieusement.

_thread.allocate_lock()

Renvoie un nouveau verrou. Les méthodes des verrous sont décrites ci-dessous. Le verrou est initialement déverrouillé.

_thread.get_ident()

Renvoie l”« identifiant de fil » du fil d’exécution courant. C’est un entier non nul. Sa valeur n’a pas de signification directe ; il est destiné à être utilisé comme cookie magique, par exemple pour indexer un dictionnaire de données pour chaque fil. Les identifiants de fils peuvent être recyclés lorsqu’un fil d’exécution se termine et qu’un autre fil est créé.

_thread.stack_size([size])

Return the thread stack size used when creating new threads. The optional size argument specifies the stack size to be used for subsequently created threads, and must be 0 (use platform or configured default) or a positive integer value of at least 32,768 (32 KiB). If size is not specified, 0 is used. If changing the thread stack size is unsupported, a RuntimeError is raised. If the specified stack size is invalid, a ValueError is raised and the stack size is unmodified. 32 KiB is currently the minimum supported stack size value to guarantee sufficient stack space for the interpreter itself. Note that some platforms may have particular restrictions on values for the stack size, such as requiring a minimum stack size > 32 KiB or requiring allocation in multiples of the system memory page size - platform documentation should be referred to for more information (4 KiB pages are common; using multiples of 4096 for the stack size is the suggested approach in the absence of more specific information). Availability: Windows, systems with POSIX threads.

_thread.TIMEOUT_MAX

La valeur maximale autorisée pour le paramètre timeout de la méthode Lock.acquire(). Préciser un délai d’attente supérieur à cette valeur lève une exception OverflowError.

Nouveau dans la version 3.2.

Les verrous ont les méthodes suivantes :

lock.acquire(waitflag=1, timeout=-1)

Sans aucun argument optionnel, cette méthode acquiert le verrou inconditionnellement, et si nécessaire attend jusqu’à ce qu’il soit relâché par un autre fil d’exécution (un seul fil d’exécution à la fois peut acquérir le verrou — c’est leur raison d’être).

Si l’argument waitflag, un entier, est présent, l’action dépend de sa valeur : si elle est de zéro, le verrou est seulement acquis s’il peut être acquis immédiatement, sans attendre, sinon le verrou est acquis inconditionnellement comme ci-dessus.

Si l’argument timeout, en virgule flottante, est présent et positif, il spécifie le temps d’attente maximum en secondes avant de renvoyer. Un argument timeout négatif spécifie une attente illimitée. Vous ne pouvez pas spécifier un timeout si waitflag est à zéro.

La valeur renvoyée est True si le verrou est acquis avec succès, sinon False.

Modifié dans la version 3.2: Le paramètre timeout est nouveau.

Modifié dans la version 3.2: Le verrou acquis peut maintenant être interrompu par des signaux sur POSIX.

lock.release()

Relâche le verrou. Le verrou doit avoir été acquis plus tôt, mais pas nécessairement par le même fil d’exécution.

lock.locked()

Renvoie le statut du verrou : True s’il a été acquis par certains fils d’exécution, sinon False.

En plus de ces méthodes, les objets verrous peuvent aussi être utilisés via l’instruction with, e.g. :

import _thread

a_lock = _thread.allocate_lock()

with a_lock:
    print("a_lock is locked while this executes")

Avertissements :

Les fils d’exécution interagissent étrangement avec les interruptions : l’exception KeyboardInterrupt sera reçue par un fil d’exécution arbitraire. (Quand le module signal est disponible, les interruptions vont toujours au fil d’exécution principal).

Appeler la fonction sys.exit() ou lever l’exception SystemExit est équivalent à appeler la fonction _thread.exit().

Il n’est pas possible d’interrompre la méthode acquire() sur un verrou — l’exception KeyboardInterrupt surviendra après que le verrou a été acquis.

Quand le fil d’exécution principal s’arrête, il est défini par le système si les autres fils d’exécution survivent. Sur beaucoup de systèmes, ils sont tués sans l’exécution des clauses try… finally ou l’exécution des destructeurs d’objets.

Quand le fil d’exécution principal s’arrête, il ne fait pas son nettoyage habituel (excepté que les clauses try… finally sont honorées) et les fichiers d’entrée/sortie standards ne sont pas nettoyés.

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17.10. _dummy_thread — Module de substitution pour le module _thread

Code source: Lib/_dummy_thread.py [https://github.com/python/cpython/tree/3.6/Lib/_dummy_thread.py]

Ce module fournit un réplicat de l’interface du module _thread. Son but est d’être importé lorsque le module _thread n’est pas fournit par la plateforme.

Utilisation suggérée :

try:
    import _thread
except ImportError:
    import _dummy_thread as _thread

Soyez prudent de ne pas utiliser ce module lorsqu’un interblocage (deadlock en anglais) peut se produire à partir d’un fil d’exécution en cours de création qui bloque en attentant qu’un autre fil d’exécution soit créé. Cela se produit souvent avec des I/O bloquants.

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18. Communication et réseau entre processus

Les modules décrits dans ce chapitre fournissent différents mécanismes permettant à des processus de communiquer.

Certains de ces modules ne fonctionnent que pour deux processus sur une seule machine, comme les modules signal et mmap. D’autres gèrent des protocoles réseaux que deux processus, ou plus, peuvent utiliser pour communiquer entre différentes machines.

La liste des modules documentés dans ce chapitre est :

18.1. socket — Low-level networking interface

18.1.1. Socket families

18.1.2. Module contents

18.1.2.1. Exceptions

18.1.2.2. Constantes

18.1.2.3. Fonctions

18.1.2.3.1. Creating sockets

18.1.2.3.2. Autres fonctions

18.1.3. Socket Objects

18.1.4. Notes on socket timeouts

18.1.4.1. Timeouts and the connect method

18.1.4.2. Timeouts and the accept method

18.1.5. Exemple

18.2. ssl — Emballage TLS/SSL pour les objets connecteurs

18.2.1. Fonctions, constantes et exceptions

18.2.1.1. Création de connecteurs

18.2.1.2. Création de contexte

18.2.1.3. Random generation

18.2.1.4. Certificate handling

18.2.1.5. Constantes

18.2.2. SSL Sockets

18.2.3. SSL Contexts

18.2.4. Certificates

18.2.4.1. Certificate chains

18.2.4.2. CA certificates

18.2.4.3. Combined key and certificate

18.2.4.4. Self-signed certificates

18.2.5. Exemples

18.2.5.1. Testing for SSL support

18.2.5.2. Client-side operation

18.2.5.3. Server-side operation

18.2.6. Notes on non-blocking sockets

18.2.7. Memory BIO Support

18.2.8. SSL session

18.2.9. Security considerations

18.2.9.1. Best defaults

18.2.9.2. Manual settings

18.2.9.2.1. Verifying certificates

18.2.9.2.2. Protocol versions

18.2.9.2.3. Cipher selection

18.2.9.3. Multi-processing

18.2.10. LibreSSL support

18.3. select — Waiting for I/O completion

18.3.1. /dev/poll Polling Objects

18.3.2. Edge and Level Trigger Polling (epoll) Objects

18.3.3. Polling Objects

18.3.4. Kqueue Objects

18.3.5. Kevent Objects

18.4. selectors — High-level I/O multiplexing

18.4.1. Introduction

18.4.2. Classes

18.4.3. Exemples

18.5. asyncio — Entrées/Sorties asynchrone, boucle d’évènements, coroutines et tâches

18.5.1. Base Event Loop

18.5.1.1. Exécuter une boucle d’évènements

18.5.1.2. Appels

18.5.1.3. Appels différés

18.5.1.4. Futurs

18.5.1.5. Tâches

18.5.1.6. Créer des connections

18.5.1.7. Attendre des connections

18.5.1.8. Surveiller des descripteurs de fichiers

18.5.1.9. Opérations bas niveau sur les socket

18.5.1.10. Résout le nom d’hôte

18.5.1.11. Connect pipes

18.5.1.12. Signaux UNIX

18.5.1.13. Exécuteur

18.5.1.14. API de gestion d’erreur

18.5.1.15. Mode débogage

18.5.1.16. Serveur

18.5.1.17. Handle

18.5.1.18. Exemples de boucles d’évènements

18.5.1.18.1. « Hello World » avec call_soon()

18.5.1.18.2. Afficher la date actuelle avec call_later()

18.5.1.18.3. Watch a file descriptor for read events

18.5.1.18.4. Définit les gestionnaires de signaux pour SIGINT et SIGTERM

18.5.2. Boucles d’évènements

18.5.2.1. Fonctions des boucles d’évènements

18.5.2.2. Boucles d’évènements disponibles

18.5.2.3. Support des plateformes

18.5.2.3.1. Windows

18.5.2.3.2. Mac OS X

18.5.2.4. Event loop policies and the default policy

18.5.2.5. Event loop policy interface

18.5.2.6. Access to the global loop policy

18.5.2.7. Customizing the event loop policy

18.5.3. Tâches et coroutines

18.5.3.1. Coroutines

18.5.3.1.1. Exemple : Coroutine « Hello World »

18.5.3.1.2. Exemple : Coroutine affichant la date actuelle

18.5.3.1.3. Exemple : Chaîner des coroutines

18.5.3.2. InvalidStateError

18.5.3.3. TimeoutError

18.5.3.4. Future

18.5.3.4.1. Exemple : Futur avec run_until_complete()

18.5.3.4.2. Exemple : Futur avec run_forever()

18.5.3.5. Task

18.5.3.5.1. Exemple : Exécution parallèle de tâches

18.5.3.6. Task functions

18.5.4. Transports et protocoles (APi basée sur des fonctions de rappel)

18.5.4.1. Transports

18.5.4.1.1. BaseTransport

18.5.4.1.2. ReadTransport

18.5.4.1.3. WriteTransport

18.5.4.1.4. DatagramTransport

18.5.4.1.5. BaseSubprocessTransport

18.5.4.2. Protocols

18.5.4.2.1. Protocol classes

18.5.4.2.2. Connection callbacks

18.5.4.2.3. Streaming protocols

18.5.4.2.4. Protocoles de datagrammes

18.5.4.2.5. Flow control callbacks

18.5.4.2.6. Coroutines et protocoles

18.5.4.3. Exemples de protocole

18.5.4.3.1. Protocole « echo client » en TCP

18.5.4.3.2. Protocole « echo serveur » en TCP

18.5.4.3.3. Protocole « echo client » en UDP

18.5.4.3.4. Protocole « echo serveur » en UDP

18.5.4.3.5. Register an open socket to wait for data using a protocol

18.5.5. Streams (coroutine based API)

18.5.5.1. Stream functions

18.5.5.2. StreamReader

18.5.5.3. StreamWriter

18.5.5.4. StreamReaderProtocol

18.5.5.5. IncompleteReadError

18.5.5.6. LimitOverrunError

18.5.5.7. Stream examples

18.5.5.7.1. TCP echo client using streams

18.5.5.7.2. TCP echo server using streams

18.5.5.7.3. Récupère les en-têtes HTTP

18.5.5.7.4. Register an open socket to wait for data using streams

18.5.6. Subprocess

18.5.6.1. Boucle d’évènements Windows

18.5.6.2. Créer un processus fils : API de haut niveau utilisant Process

18.5.6.3. Create a subprocess: low-level API using subprocess.Popen

18.5.6.4. Constantes

18.5.6.5. Process

18.5.6.6. Processus fils et fils d’exécution

18.5.6.7. Subprocess examples

18.5.6.7.1. Subprocess using transport and protocol

18.5.6.7.2. Subprocess using streams

18.5.7. Primitives de synchronisation

18.5.7.1. Locks

18.5.7.1.1. Lock

18.5.7.1.2. Event

18.5.7.1.3. Condition

18.5.7.2. Sémaphores

18.5.7.2.1. Sémaphore

18.5.7.2.2. BoundedSemaphore

18.5.8. Queues

18.5.8.1. Queue

18.5.8.2. PriorityQueue

18.5.8.3. LifoQueue

18.5.8.3.1. Exceptions

18.5.9. Programmer avec asyncio

18.5.9.1. Mode de débogage d”asyncio

18.5.9.2. Annulation

18.5.9.3. Concourance et multithreading

18.5.9.4. Gérer les fonctions bloquantes correctement

18.5.9.5. Journalisation

18.5.9.6. Détecte les coroutines qui ne sont jamais exécutées

18.5.9.7. Detect exceptions never consumed

18.5.9.8. Chaîner les coroutines correctement

18.5.9.9. Pending task destroyed

18.5.9.10. Close transports and event loops

18.6. asyncore — Gestionnaire de socket asynchrone

18.6.1. Exemple de client HTTP basique avec asyncore

18.6.2. Serveur echo basique avec asyncore

18.7. asynchat — Gestionnaire d’interfaces de connexion (socket) commande/réponse asynchrones

18.7.1. Exemple asynchat

18.8. signal — Set handlers for asynchronous events

18.8.1. General rules

18.8.1.1. Execution of Python signal handlers

18.8.1.2. Signals and threads

18.8.2. Module contents

18.8.3. Exemple

18.9. mmap — Memory-mapped file support

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18.1. socket — Low-level networking interface

Source code: Lib/socket.py [https://github.com/python/cpython/tree/3.6/Lib/socket.py]

This module provides access to the BSD socket interface. It is available on all modern Unix systems, Windows, MacOS, and probably additional platforms.

Note

Some behavior may be platform dependent, since calls are made to the operating system socket APIs.

The Python interface is a straightforward transliteration of the Unix system call and library interface for sockets to Python’s object-oriented style: the socket() function returns a socket object whose methods implement the various socket system calls. Parameter types are somewhat higher-level than in the C interface: as with read() and write() operations on Python files, buffer allocation on receive operations is automatic, and buffer length is implicit on send operations.

Voir aussi

Module socketserver

Classes that simplify writing network servers.

Module ssl

A TLS/SSL wrapper for socket objects.

18.1.1. Socket families

Depending on the system and the build options, various socket families are supported by this module.

The address format required by a particular socket object is automatically selected based on the address family specified when the socket object was created. Socket addresses are represented as follows:

The address of an AF_UNIX socket bound to a file system node is represented as a string, using the file system encoding and the 'surrogateescape' error handler (see PEP 383 [https://www.python.org/dev/peps/pep-0383]). An address in Linux’s abstract namespace is returned as a bytes-like object with an initial null byte; note that sockets in this namespace can communicate with normal file system sockets, so programs intended to run on Linux may need to deal with both types of address. A string or bytes-like object can be used for either type of address when passing it as an argument.

Modifié dans la version 3.3: Previously, AF_UNIX socket paths were assumed to use UTF-8 encoding.

Modifié dans la version 3.5: N’importe quel bytes-like object est maintenant accepté.

A pair (host, port) is used for the AF_INET address family, where host is a string representing either a hostname in Internet domain notation like 'daring.cwi.nl' or an IPv4 address like '100.50.200.5', and port is an integer.

For IPv4 addresses, two special forms are accepted instead of a host address: '' represents INADDR_ANY, which is used to bind to all interfaces, and the string '<broadcast>' represents INADDR_BROADCAST. This behavior is not compatible with IPv6, therefore, you may want to avoid these if you intend to support IPv6 with your Python programs.

For AF_INET6 address family, a four-tuple (host, port, flowinfo, scopeid) is used, where flowinfo and scopeid represent the sin6_flowinfo and sin6_scope_id members in struct sockaddr_in6 in C. For socket module methods, flowinfo and scopeid can be omitted just for backward compatibility. Note, however, omission of scopeid can cause problems in manipulating scoped IPv6 addresses.

AF_NETLINK sockets are represented as pairs (pid, groups).

Linux-only support for TIPC is available using the AF_TIPC address family. TIPC is an open, non-IP based networked protocol designed for use in clustered computer environments. Addresses are represented by a tuple, and the fields depend on the address type. The general tuple form is (addr_type, v1, v2, v3 [, scope]), where:

addr_type is one of TIPC_ADDR_NAMESEQ, TIPC_ADDR_NAME, or TIPC_ADDR_ID.

scope is one of TIPC_ZONE_SCOPE, TIPC_CLUSTER_SCOPE, and TIPC_NODE_SCOPE.

If addr_type is TIPC_ADDR_NAME, then v1 is the server type, v2 is the port identifier, and v3 should be 0.

If addr_type is TIPC_ADDR_NAMESEQ, then v1 is the server type, v2 is the lower port number, and v3 is the upper port number.

If addr_type is TIPC_ADDR_ID, then v1 is the node, v2 is the reference, and v3 should be set to 0.

A tuple (interface, ) is used for the AF_CAN address family, where interface is a string representing a network interface name like 'can0'. The network interface name '' can be used to receive packets from all network interfaces of this family.

A string or a tuple (id, unit) is used for the SYSPROTO_CONTROL protocol of the PF_SYSTEM family. The string is the name of a kernel control using a dynamically-assigned ID. The tuple can be used if ID and unit number of the kernel control are known or if a registered ID is used.

Nouveau dans la version 3.3.

AF_BLUETOOTH supports the following protocols and address formats:

BTPROTO_L2CAP accepts (bdaddr, psm) where bdaddr is the Bluetooth address as a string and psm is an integer.

BTPROTO_RFCOMM accepts (bdaddr, channel) where bdaddr is the Bluetooth address as a string and channel is an integer.

BTPROTO_HCI accepts (device_id,) where device_id is either an integer or a string with the Bluetooth address of the interface. (This depends on your OS; NetBSD and DragonFlyBSD expect a Bluetooth address while everything else expects an integer.)

Modifié dans la version 3.2: NetBSD and DragonFlyBSD support added.

BTPROTO_SCO accepts bdaddr where bdaddr is a bytes object containing the Bluetooth address in a string format. (ex. b'12:23:34:45:56:67') This protocol is not supported under FreeBSD.

AF_ALG is a Linux-only socket based interface to Kernel cryptography. An algorithm socket is configured with a tuple of two to four elements (type, name [, feat [, mask]]), where:

type is the algorithm type as string, e.g. aead, hash, skcipher or rng.

name is the algorithm name and operation mode as string, e.g. sha256, hmac(sha256), cbc(aes) or drbg_nopr_ctr_aes256.

feat and mask are unsigned 32bit integers.

Availability Linux 2.6.38, some algorithm types require more recent Kernels.

Nouveau dans la version 3.6.

AF_PACKET is a low-level interface directly to network devices. The packets are represented by the tuple (ifname, proto[, pkttype[, hatype[, addr]]]) where:

ifname - String specifying the device name.

proto - An in network-byte-order integer specifying the Ethernet protocol number.

pkttype - Optional integer specifying the packet type:

PACKET_HOST (the default) - Packet addressed to the local host.

PACKET_BROADCAST - Physical-layer broadcast packet.

PACKET_MULTIHOST - Packet sent to a physical-layer multicast address.

PACKET_OTHERHOST - Packet to some other host that has been caught by a device driver in promiscuous mode.

PACKET_OUTGOING - Packet originating from the local host that is looped back to a packet socket.

hatype - Optional integer specifying the ARP hardware address type.

addr - Optional bytes-like object specifying the hardware physical address, whose interpretation depends on the device.

If you use a hostname in the host portion of IPv4/v6 socket address, the program may show a nondeterministic behavior, as Python uses the first address returned from the DNS resolution. The socket address will be resolved differently into an actual IPv4/v6 address, depending on the results from DNS resolution and/or the host configuration. For deterministic behavior use a numeric address in host portion.

All errors raise exceptions. The normal exceptions for invalid argument types and out-of-memory conditions can be raised; starting from Python 3.3, errors related to socket or address semantics raise OSError or one of its subclasses (they used to raise socket.error).

Non-blocking mode is supported through setblocking(). A generalization of this based on timeouts is supported through settimeout().

18.1.2. Module contents

The module socket exports the following elements.

18.1.2.1. Exceptions

exception socket.error

A deprecated alias of OSError.

Modifié dans la version 3.3: Following PEP 3151 [https://www.python.org/dev/peps/pep-3151], this class was made an alias of OSError.

exception socket.herror

A subclass of OSError, this exception is raised for address-related errors, i.e. for functions that use h_errno in the POSIX C API, including gethostbyname_ex() and gethostbyaddr(). The accompanying value is a pair (h_errno, string) representing an error returned by a library call. h_errno is a numeric value, while string represents the description of h_errno, as returned by the hstrerror() C function.

Modifié dans la version 3.3: This class was made a subclass of OSError.

exception socket.gaierror

A subclass of OSError, this exception is raised for address-related errors by getaddrinfo() and getnameinfo(). The accompanying value is a pair (error, string) representing an error returned by a library call. string represents the description of error, as returned by the gai_strerror() C function. The numeric error value will match one of the EAI_* constants defined in this module.

Modifié dans la version 3.3: This class was made a subclass of OSError.

exception socket.timeout

A subclass of OSError, this exception is raised when a timeout occurs on a socket which has had timeouts enabled via a prior call to settimeout() (or implicitly through setdefaulttimeout()). The accompanying value is a string whose value is currently always « timed out ».

Modifié dans la version 3.3: This class was made a subclass of OSError.

18.1.2.2. Constantes

The AF_* and SOCK_* constants are now AddressFamily and SocketKind IntEnum collections.

Nouveau dans la version 3.4.

socket.AF_UNIX

socket.AF_INET

socket.AF_INET6

These constants represent the address (and protocol) families, used for the first argument to socket(). If the AF_UNIX constant is not defined then this protocol is unsupported. More constants may be available depending on the system.

socket.SOCK_STREAM

socket.SOCK_DGRAM

socket.SOCK_RAW

socket.SOCK_RDM

socket.SOCK_SEQPACKET

These constants represent the socket types, used for the second argument to socket(). More constants may be available depending on the system. (Only SOCK_STREAM and SOCK_DGRAM appear to be generally useful.)

socket.SOCK_CLOEXEC

socket.SOCK_NONBLOCK

These two constants, if defined, can be combined with the socket types and allow you to set some flags atomically (thus avoiding possible race conditions and the need for separate calls).

Voir aussi

Secure File Descriptor Handling [http://udrepper.livejournal.com/20407.html] for a more thorough explanation.

Availability: Linux >= 2.6.27.

Nouveau dans la version 3.2.

SO_*

socket.SOMAXCONN

MSG_*

SOL_*

SCM_*

IPPROTO_*

IPPORT_*

INADDR_*

IP_*

IPV6_*

EAI_*

AI_*

NI_*

TCP_*

Many constants of these forms, documented in the Unix documentation on sockets and/or the IP protocol, are also defined in the socket module. They are generally used in arguments to the setsockopt() and getsockopt() methods of socket objects. In most cases, only those symbols that are defined in the Unix header files are defined; for a few symbols, default values are provided.

Modifié dans la version 3.6: SO_DOMAIN, SO_PROTOCOL, SO_PEERSEC, SO_PASSSEC, TCP_USER_TIMEOUT, TCP_CONGESTION were added.

Modifié dans la version 3.6.5: On Windows, TCP_FASTOPEN, TCP_KEEPCNT appear if run-time Windows supports.

socket.AF_CAN

socket.PF_CAN

SOL_CAN_*

CAN_*

Many constants of these forms, documented in the Linux documentation, are also defined in the socket module.

Availability: Linux >= 2.6.25.

Nouveau dans la version 3.3.

socket.CAN_BCM

CAN_BCM_*

CAN_BCM, in the CAN protocol family, is the broadcast manager (BCM) protocol. Broadcast manager constants, documented in the Linux documentation, are also defined in the socket module.

Availability: Linux >= 2.6.25.

Nouveau dans la version 3.4.

socket.CAN_RAW_FD_FRAMES

Enables CAN FD support in a CAN_RAW socket. This is disabled by default. This allows your application to send both CAN and CAN FD frames; however, you one must accept both CAN and CAN FD frames when reading from the socket.

This constant is documented in the Linux documentation.

Availability: Linux >= 3.6.

Nouveau dans la version 3.5.

socket.AF_PACKET

socket.PF_PACKET

PACKET_*

Many constants of these forms, documented in the Linux documentation, are also defined in the socket module.

Availability: Linux >= 2.2.

socket.AF_RDS

socket.PF_RDS

socket.SOL_RDS

RDS_*

Many constants of these forms, documented in the Linux documentation, are also defined in the socket module.

Availability: Linux >= 2.6.30.

Nouveau dans la version 3.3.

socket.SIO_RCVALL

socket.SIO_KEEPALIVE_VALS

socket.SIO_LOOPBACK_FAST_PATH

RCVALL_*

Constants for Windows” WSAIoctl(). The constants are used as arguments to the ioctl() method of socket objects.

Modifié dans la version 3.6: SIO_LOOPBACK_FAST_PATH was added.

TIPC_*

TIPC related constants, matching the ones exported by the C socket API. See the TIPC documentation for more information.

socket.AF_ALG

socket.SOL_ALG

ALG_*

Constants for Linux Kernel cryptography.

Availability: Linux >= 2.6.38.

Nouveau dans la version 3.6.

socket.AF_LINK

Availability: BSD, OSX.

Nouveau dans la version 3.4.

socket.has_ipv6

This constant contains a boolean value which indicates if IPv6 is supported on this platform.

socket.BDADDR_ANY

socket.BDADDR_LOCAL

These are string constants containing Bluetooth addresses with special meanings. For example, BDADDR_ANY can be used to indicate any address when specifying the binding socket with BTPROTO_RFCOMM.

socket.HCI_FILTER

socket.HCI_TIME_STAMP

socket.HCI_DATA_DIR

For use with BTPROTO_HCI. HCI_FILTER is not available for NetBSD or DragonFlyBSD. HCI_TIME_STAMP and HCI_DATA_DIR are not available for FreeBSD, NetBSD, or DragonFlyBSD.

18.1.2.3. Fonctions

18.1.2.3.1. Creating sockets

The following functions all create socket objects.

socket.socket(family=AF_INET, type=SOCK_STREAM, proto=0, fileno=None)

Create a new socket using the given address family, socket type and protocol number. The address family should be AF_INET (the default), AF_INET6, AF_UNIX, AF_CAN, AF_PACKET, or AF_RDS. The socket type should be SOCK_STREAM (the default), SOCK_DGRAM, SOCK_RAW or perhaps one of the other SOCK_ constants. The protocol number is usually zero and may be omitted or in the case where the address family is AF_CAN the protocol should be one of CAN_RAW or CAN_BCM. If fileno is specified, the other arguments are ignored, causing the socket with the specified file descriptor to return. Unlike socket.fromfd(), fileno will return the same socket and not a duplicate. This may help close a detached socket using socket.close().

Il n’est pas possible d’hériter du connecteur nouvellement créé.

Modifié dans la version 3.3: The AF_CAN family was added. The AF_RDS family was added.

Modifié dans la version 3.4: The CAN_BCM protocol was added.

Modifié dans la version 3.4: The returned socket is now non-inheritable.

socket.socketpair([family[, type[, proto]]])

Build a pair of connected socket objects using the given address family, socket type, and protocol number. Address family, socket type, and protocol number are as for the socket() function above. The default family is AF_UNIX if defined on the platform; otherwise, the default is AF_INET.

The newly created sockets are non-inheritable.

Modifié dans la version 3.2: The returned socket objects now support the whole socket API, rather than a subset.

Modifié dans la version 3.4: The returned sockets are now non-inheritable.

Modifié dans la version 3.5: Windows support added.

socket.create_connection(address[, timeout[, source_address]])

Connect to a TCP service listening on the Internet address (a 2-tuple (host, port)), and return the socket object. This is a higher-level function than socket.connect(): if host is a non-numeric hostname, it will try to resolve it for both AF_INET and AF_INET6, and then try to connect to all possible addresses in turn until a connection succeeds. This makes it easy to write clients that are compatible to both IPv4 and IPv6.

Passing the optional timeout parameter will set the timeout on the socket instance before attempting to connect. If no timeout is supplied, the global default timeout setting returned by getdefaulttimeout() is used.

If supplied, source_address must be a 2-tuple (host, port) for the socket to bind to as its source address before connecting. If host or port are “” or 0 respectively the OS default behavior will be used.

Modifié dans la version 3.2: source_address was added.

socket.fromfd(fd, family, type, proto=0)

Duplicate the file descriptor fd (an integer as returned by a file object’s fileno() method) and build a socket object from the result. Address family, socket type and protocol number are as for the socket() function above. The file descriptor should refer to a socket, but this is not checked — subsequent operations on the object may fail if the file descriptor is invalid. This function is rarely needed, but can be used to get or set socket options on a socket passed to a program as standard input or output (such as a server started by the Unix inet daemon). The socket is assumed to be in blocking mode.

Il n’est pas possible d’hériter du connecteur nouvellement créé.

Modifié dans la version 3.4: The returned socket is now non-inheritable.

socket.fromshare(data)

Instantiate a socket from data obtained from the socket.share() method. The socket is assumed to be in blocking mode.

Disponibilité : Windows.

Nouveau dans la version 3.3.

socket.SocketType

This is a Python type object that represents the socket object type. It is the same as type(socket(...)).

18.1.2.3.2. Autres fonctions

The socket module also offers various network-related services:

socket.getaddrinfo(host, port, family=0, type=0, proto=0, flags=0)

Translate the host/port argument into a sequence of 5-tuples that contain all the necessary arguments for creating a socket connected to that service. host is a domain name, a string representation of an IPv4/v6 address or None. port is a string service name such as 'http', a numeric port number or None. By passing None as the value of host and port, you can pass NULL to the underlying C API.

The family, type and proto arguments can be optionally specified in order to narrow the list of addresses returned. Passing zero as a value for each of these arguments selects the full range of results. The flags argument can be one or several of the AI_* constants, and will influence how results are computed and returned. For example, AI_NUMERICHOST will disable domain name resolution and will raise an error if host is a domain name.

The function returns a list of 5-tuples with the following structure:

(family, type, proto, canonname, sockaddr)

In these tuples, family, type, proto are all integers and are meant to be passed to the socket() function. canonname will be a string representing the canonical name of the host if AI_CANONNAME is part of the flags argument; else canonname will be empty. sockaddr is a tuple describing a socket address, whose format depends on the returned family (a (address, port) 2-tuple for AF_INET, a (address, port, flow info, scope id) 4-tuple for AF_INET6), and is meant to be passed to the socket.connect() method.

The following example fetches address information for a hypothetical TCP connection to example.org on port 80 (results may differ on your system if IPv6 isn’t enabled):

>>> socket.getaddrinfo("example.org", 80, proto=socket.IPPROTO_TCP)
[(<AddressFamily.AF_INET6: 10>, <SocketType.SOCK_STREAM: 1>,
 6, '', ('2606:2800:220:1:248:1893:25c8:1946', 80, 0, 0)),
 (<AddressFamily.AF_INET: 2>, <SocketType.SOCK_STREAM: 1>,
 6, '', ('93.184.216.34', 80))]

Modifié dans la version 3.2: parameters can now be passed using keyword arguments.

socket.getfqdn([name])

Return a fully qualified domain name for name. If name is omitted or empty, it is interpreted as the local host. To find the fully qualified name, the hostname returned by gethostbyaddr() is checked, followed by aliases for the host, if available. The first name which includes a period is selected. In case no fully qualified domain name is available, the hostname as returned by gethostname() is returned.

socket.gethostbyname(hostname)

Translate a host name to IPv4 address format. The IPv4 address is returned as a string, such as '100.50.200.5'. If the host name is an IPv4 address itself it is returned unchanged. See gethostbyname_ex() for a more complete interface. gethostbyname() does not support IPv6 name resolution, and getaddrinfo() should be used instead for IPv4/v6 dual stack support.

socket.gethostbyname_ex(hostname)

Translate a host name to IPv4 address format, extended interface. Return a triple (hostname, aliaslist, ipaddrlist) where hostname is the primary host name responding to the given ip_address, aliaslist is a (possibly empty) list of alternative host names for the same address, and ipaddrlist is a list of IPv4 addresses for the same interface on the same host (often but not always a single address). gethostbyname_ex() does not support IPv6 name resolution, and getaddrinfo() should be used instead for IPv4/v6 dual stack support.

socket.gethostname()

Return a string containing the hostname of the machine where the Python interpreter is currently executing.

Note: gethostname() doesn’t always return the fully qualified domain name; use getfqdn() for that.

socket.gethostbyaddr(ip_address)

Return a triple (hostname, aliaslist, ipaddrlist) where hostname is the primary host name responding to the given ip_address, aliaslist is a (possibly empty) list of alternative host names for the same address, and ipaddrlist is a list of IPv4/v6 addresses for the same interface on the same host (most likely containing only a single address). To find the fully qualified domain name, use the function getfqdn(). gethostbyaddr() supports both IPv4 and IPv6.

socket.getnameinfo(sockaddr, flags)

Translate a socket address sockaddr into a 2-tuple (host, port). Depending on the settings of flags, the result can contain a fully-qualified domain name or numeric address representation in host. Similarly, port can contain a string port name or a numeric port number.

socket.getprotobyname(protocolname)

Translate an Internet protocol name (for example, 'icmp') to a constant suitable for passing as the (optional) third argument to the socket() function. This is usually only needed for sockets opened in « raw » mode (SOCK_RAW); for the normal socket modes, the correct protocol is chosen automatically if the protocol is omitted or zero.

socket.getservbyname(servicename[, protocolname])

Translate an Internet service name and protocol name to a port number for that service. The optional protocol name, if given, should be 'tcp' or 'udp', otherwise any protocol will match.

socket.getservbyport(port[, protocolname])

Translate an Internet port number and protocol name to a service name for that service. The optional protocol name, if given, should be 'tcp' or 'udp', otherwise any protocol will match.

socket.ntohl(x)

Convert 32-bit positive integers from network to host byte order. On machines where the host byte order is the same as network byte order, this is a no-op; otherwise, it performs a 4-byte swap operation.

socket.ntohs(x)

Convert 16-bit positive integers from network to host byte order. On machines where the host byte order is the same as network byte order, this is a no-op; otherwise, it performs a 2-byte swap operation.

socket.htonl(x)

Convert 32-bit positive integers from host to network byte order. On machines where the host byte order is the same as network byte order, this is a no-op; otherwise, it performs a 4-byte swap operation.

socket.htons(x)

Convert 16-bit positive integers from host to network byte order. On machines where the host byte order is the same as network byte order, this is a no-op; otherwise, it performs a 2-byte swap operation.

socket.inet_aton(ip_string)

Convert an IPv4 address from dotted-quad string format (for example, “123.45.67.89”) to 32-bit packed binary format, as a bytes object four characters in length. This is useful when conversing with a program that uses the standard C library and needs objects of type struct in_addr, which is the C type for the 32-bit packed binary this function returns.

inet_aton() also accepts strings with less than three dots; see the Unix manual page inet(3) for details.

If the IPv4 address string passed to this function is invalid, OSError will be raised. Note that exactly what is valid depends on the underlying C implementation of inet_aton().

inet_aton() does not support IPv6, and inet_pton() should be used instead for IPv4/v6 dual stack support.

socket.inet_ntoa(packed_ip)

Convert a 32-bit packed IPv4 address (a bytes-like object four bytes in length) to its standard dotted-quad string representation (for example, “123.45.67.89”). This is useful when conversing with a program that uses the standard C library and needs objects of type struct in_addr, which is the C type for the 32-bit packed binary data this function takes as an argument.

If the byte sequence passed to this function is not exactly 4 bytes in length, OSError will be raised. inet_ntoa() does not support IPv6, and inet_ntop() should be used instead for IPv4/v6 dual stack support.

Modifié dans la version 3.5: N’importe quel bytes-like object est maintenant accepté.

socket.inet_pton(address_family, ip_string)

Convert an IP address from its family-specific string format to a packed, binary format. inet_pton() is useful when a library or network protocol calls for an object of type struct in_addr (similar to inet_aton()) or struct in6_addr.

Supported values for address_family are currently AF_INET and AF_INET6. If the IP address string ip_string is invalid, OSError will be raised. Note that exactly what is valid depends on both the value of address_family and the underlying implementation of inet_pton().

Availability: Unix (maybe not all platforms), Windows.

Modifié dans la version 3.4: Ajout de la gestion de Windows.

socket.inet_ntop(address_family, packed_ip)

Convert a packed IP address (a bytes-like object of some number of bytes) to its standard, family-specific string representation (for example, '7.10.0.5' or '5aef:2b::8'). inet_ntop() is useful when a library or network protocol returns an object of type struct in_addr (similar to inet_ntoa()) or struct in6_addr.

Supported values for address_family are currently AF_INET and AF_INET6. If the bytes object packed_ip is not the correct length for the specified address family, ValueError will be raised. OSError is raised for errors from the call to inet_ntop().

Availability: Unix (maybe not all platforms), Windows.

Modifié dans la version 3.4: Ajout de la gestion de Windows.

Modifié dans la version 3.5: N’importe quel bytes-like object est maintenant accepté.

socket.CMSG_LEN(length)

Return the total length, without trailing padding, of an ancillary data item with associated data of the given length. This value can often be used as the buffer size for recvmsg() to receive a single item of ancillary data, but RFC 3542 [https://tools.ietf.org/html/rfc3542.html] requires portable applications to use CMSG_SPACE() and thus include space for padding, even when the item will be the last in the buffer. Raises OverflowError if length is outside the permissible range of values.

Availability: most Unix platforms, possibly others.

Nouveau dans la version 3.3.

socket.CMSG_SPACE(length)

Return the buffer size needed for recvmsg() to receive an ancillary data item with associated data of the given length, along with any trailing padding. The buffer space needed to receive multiple items is the sum of the CMSG_SPACE() values for their associated data lengths. Raises OverflowError if length is outside the permissible range of values.

Note that some systems might support ancillary data without providing this function. Also note that setting the buffer size using the results of this function may not precisely limit the amount of ancillary data that can be received, since additional data may be able to fit into the padding area.

Availability: most Unix platforms, possibly others.

Nouveau dans la version 3.3.

socket.getdefaulttimeout()

Return the default timeout in seconds (float) for new socket objects. A value of None indicates that new socket objects have no timeout. When the socket module is first imported, the default is None.

socket.setdefaulttimeout(timeout)

Set the default timeout in seconds (float) for new socket objects. When the socket module is first imported, the default is None. See settimeout() for possible values and their respective meanings.

socket.sethostname(name)

Set the machine’s hostname to name. This will raise an OSError if you don’t have enough rights.

Disponibilité : Unix.

Nouveau dans la version 3.3.

socket.if_nameindex()

Return a list of network interface information (index int, name string) tuples. OSError if the system call fails.

Disponibilité : Unix.

Nouveau dans la version 3.3.

socket.if_nametoindex(if_name)

Return a network interface index number corresponding to an interface name. OSError if no interface with the given name exists.

Disponibilité : Unix.

Nouveau dans la version 3.3.

socket.if_indextoname(if_index)

Return a network interface name corresponding to an interface index number. OSError if no interface with the given index exists.

Disponibilité : Unix.

Nouveau dans la version 3.3.

18.1.3. Socket Objects

Socket objects have the following methods. Except for makefile(), these correspond to Unix system calls applicable to sockets.

Modifié dans la version 3.2: Support for the context manager protocol was added. Exiting the context manager is equivalent to calling close().

socket.accept()

Accept a connection. The socket must be bound to an address and listening for connections. The return value is a pair (conn, address) where conn is a new socket object usable to send and receive data on the connection, and address is the address bound to the socket on the other end of the connection.

Il n’est pas possible d’hériter du connecteur nouvellement créé.

Modifié dans la version 3.4: The socket is now non-inheritable.

Modifié dans la version 3.5: Si l’appel système est interrompu et que le gestionnaire de signal ne lève aucune exception, la fonction réessaye l’appel système au lieu de lever une InterruptedError (voir la PEP 475 [https://www.python.org/dev/peps/pep-0475] à propos du raisonnement).

socket.bind(address)

Bind the socket to address. The socket must not already be bound. (The format of address depends on the address family — see above.)

socket.close()

Mark the socket closed. The underlying system resource (e.g. a file descriptor) is also closed when all file objects from makefile() are closed. Once that happens, all future operations on the socket object will fail. The remote end will receive no more data (after queued data is flushed).

Sockets are automatically closed when they are garbage-collected, but it is recommended to close() them explicitly, or to use a with statement around them.

Modifié dans la version 3.6: OSError is now raised if an error occurs when the underlying close() call is made.

Note

close() releases the resource associated with a connection but does not necessarily close the connection immediately. If you want to close the connection in a timely fashion, call shutdown() before close().

socket.connect(address)

Connect to a remote socket at address. (The format of address depends on the address family — see above.)

If the connection is interrupted by a signal, the method waits until the connection completes, or raise a socket.timeout on timeout, if the signal handler doesn’t raise an exception and the socket is blocking or has a timeout. For non-blocking sockets, the method raises an InterruptedError exception if the connection is interrupted by a signal (or the exception raised by the signal handler).

Modifié dans la version 3.5: The method now waits until the connection completes instead of raising an InterruptedError exception if the connection is interrupted by a signal, the signal handler doesn’t raise an exception and the socket is blocking or has a timeout (see the PEP 475 [https://www.python.org/dev/peps/pep-0475] for the rationale).

socket.connect_ex(address)

Like connect(address), but return an error indicator instead of raising an exception for errors returned by the C-level connect() call (other problems, such as « host not found, » can still raise exceptions). The error indicator is 0 if the operation succeeded, otherwise the value of the errno variable. This is useful to support, for example, asynchronous connects.

socket.detach()

Put the socket object into closed state without actually closing the underlying file descriptor. The file descriptor is returned, and can be reused for other purposes.

Nouveau dans la version 3.2.

socket.dup()

Duplicate the socket.

Il n’est pas possible d’hériter du connecteur nouvellement créé.

Modifié dans la version 3.4: The socket is now non-inheritable.

socket.fileno()

Return the socket’s file descriptor (a small integer), or -1 on failure. This is useful with select.select().

Under Windows the small integer returned by this method cannot be used where a file descriptor can be used (such as os.fdopen()). Unix does not have this limitation.

socket.get_inheritable()

Get the inheritable flag of the socket’s file descriptor or socket’s handle: True if the socket can be inherited in child processes, False if it cannot.

Nouveau dans la version 3.4.

socket.getpeername()

Return the remote address to which the socket is connected. This is useful to find out the port number of a remote IPv4/v6 socket, for instance. (The format of the address returned depends on the address family — see above.) On some systems this function is not supported.

socket.getsockname()

Return the socket’s own address. This is useful to find out the port number of an IPv4/v6 socket, for instance. (The format of the address returned depends on the address family — see above.)

socket.getsockopt(level, optname[, buflen])

Return the value of the given socket option (see the Unix man page getsockopt(2)). The needed symbolic constants (SO_* etc.) are defined in this module. If buflen is absent, an integer option is assumed and its integer value is returned by the function. If buflen is present, it specifies the maximum length of the buffer used to receive the option in, and this buffer is returned as a bytes object. It is up to the caller to decode the contents of the buffer (see the optional built-in module struct for a way to decode C structures encoded as byte strings).

socket.gettimeout()

Return the timeout in seconds (float) associated with socket operations, or None if no timeout is set. This reflects the last call to setblocking() or settimeout().

socket.ioctl(control, option)

Platform

Windows

The ioctl() method is a limited interface to the WSAIoctl system interface. Please refer to the Win32 documentation [https://msdn.microsoft.com/en-us/library/ms741621%28VS.85%29.aspx] for more information.

On other platforms, the generic fcntl.fcntl() and fcntl.ioctl() functions may be used; they accept a socket object as their first argument.

Currently only the following control codes are supported: SIO_RCVALL, SIO_KEEPALIVE_VALS, and SIO_LOOPBACK_FAST_PATH.

Modifié dans la version 3.6: SIO_LOOPBACK_FAST_PATH was added.

socket.listen([backlog])

Enable a server to accept connections. If backlog is specified, it must be at least 0 (if it is lower, it is set to 0); it specifies the number of unaccepted connections that the system will allow before refusing new connections. If not specified, a default reasonable value is chosen.

Modifié dans la version 3.5: The backlog parameter is now optional.

socket.makefile(mode='r', buffering=None, *, encoding=None, errors=None, newline=None)

Return a file object associated with the socket. The exact returned type depends on the arguments given to makefile(). These arguments are interpreted the same way as by the built-in open() function, except the only supported mode values are 'r' (default), 'w' and 'b'.

The socket must be in blocking mode; it can have a timeout, but the file object’s internal buffer may end up in an inconsistent state if a timeout occurs.

Closing the file object returned by makefile() won’t close the original socket unless all other file objects have been closed and socket.close() has been called on the socket object.

Note

On Windows, the file-like object created by makefile() cannot be used where a file object with a file descriptor is expected, such as the stream arguments of subprocess.Popen().

socket.recv(bufsize[, flags])

Receive data from the socket. The return value is a bytes object representing the data received. The maximum amount of data to be received at once is specified by bufsize. See the Unix manual page recv(2) for the meaning of the optional argument flags; it defaults to zero.

Note

For best match with hardware and network realities, the value of bufsize should be a relatively small power of 2, for example, 4096.

Modifié dans la version 3.5: Si l’appel système est interrompu et que le gestionnaire de signal ne lève aucune exception, la fonction réessaye l’appel système au lieu de lever une InterruptedError (voir la PEP 475 [https://www.python.org/dev/peps/pep-0475] à propos du raisonnement).

socket.recvfrom(bufsize[, flags])

Receive data from the socket. The return value is a pair (bytes, address) where bytes is a bytes object representing the data received and address is the address of the socket sending the data. See the Unix manual page recv(2) for the meaning of the optional argument flags; it defaults to zero. (The format of address depends on the address family — see above.)

Modifié dans la version 3.5: Si l’appel système est interrompu et que le gestionnaire de signal ne lève aucune exception, la fonction réessaye l’appel système au lieu de lever une InterruptedError (voir la PEP 475 [https://www.python.org/dev/peps/pep-0475] à propos du raisonnement).

socket.recvmsg(bufsize[, ancbufsize[, flags]])

Receive normal data (up to bufsize bytes) and ancillary data from the socket. The ancbufsize argument sets the size in bytes of the internal buffer used to receive the ancillary data; it defaults to 0, meaning that no ancillary data will be received. Appropriate buffer sizes for ancillary data can be calculated using CMSG_SPACE() or CMSG_LEN(), and items which do not fit into the buffer might be truncated or discarded. The flags argument defaults to 0 and has the same meaning as for recv().

The return value is a 4-tuple: (data, ancdata, msg_flags, address). The data item is a bytes object holding the non-ancillary data received. The ancdata item is a list of zero or more tuples (cmsg_level, cmsg_type, cmsg_data) representing the ancillary data (control messages) received: cmsg_level and cmsg_type are integers specifying the protocol level and protocol-specific type respectively, and cmsg_data is a bytes object holding the associated data. The msg_flags item is the bitwise OR of various flags indicating conditions on the received message; see your system documentation for details. If the receiving socket is unconnected, address is the address of the sending socket, if available; otherwise, its value is unspecified.

On some systems, sendmsg() and recvmsg() can be used to pass file descriptors between processes over an AF_UNIX socket. When this facility is used (it is often restricted to SOCK_STREAM sockets), recvmsg() will return, in its ancillary data, items of the form (socket.SOL_SOCKET, socket.SCM_RIGHTS, fds), where fds is a bytes object representing the new file descriptors as a binary array of the native C int type. If recvmsg() raises an exception after the system call returns, it will first attempt to close any file descriptors received via this mechanism.

Some systems do not indicate the truncated length of ancillary data items which have been only partially received. If an item appears to extend beyond the end of the buffer, recvmsg() will issue a RuntimeWarning, and will return the part of it which is inside the buffer provided it has not been truncated before the start of its associated data.

On systems which support the SCM_RIGHTS mechanism, the following function will receive up to maxfds file descriptors, returning the message data and a list containing the descriptors (while ignoring unexpected conditions such as unrelated control messages being received). See also sendmsg().

import socket, array

def recv_fds(sock, msglen, maxfds):
    fds = array.array("i")   # Array of ints
    msg, ancdata, flags, addr = sock.recvmsg(msglen, socket.CMSG_LEN(maxfds * fds.itemsize))
    for cmsg_level, cmsg_type, cmsg_data in ancdata:
        if (cmsg_level == socket.SOL_SOCKET and cmsg_type == socket.SCM_RIGHTS):
            # Append data, ignoring any truncated integers at the end.
            fds.fromstring(cmsg_data[:len(cmsg_data) - (len(cmsg_data) % fds.itemsize)])
    return msg, list(fds)

Availability: most Unix platforms, possibly others.

Nouveau dans la version 3.3.

Modifié dans la version 3.5: Si l’appel système est interrompu et que le gestionnaire de signal ne lève aucune exception, la fonction réessaye l’appel système au lieu de lever une InterruptedError (voir la PEP 475 [https://www.python.org/dev/peps/pep-0475] à propos du raisonnement).

socket.recvmsg_into(buffers[, ancbufsize[, flags]])

Receive normal data and ancillary data from the socket, behaving as recvmsg() would, but scatter the non-ancillary data into a series of buffers instead of returning a new bytes object. The buffers argument must be an iterable of objects that export writable buffers (e.g. bytearray objects); these will be filled with successive chunks of the non-ancillary data until it has all been written or there are no more buffers. The operating system may set a limit (sysconf() value SC_IOV_MAX) on the number of buffers that can be used. The ancbufsize and flags arguments have the same meaning as for recvmsg().

The return value is a 4-tuple: (nbytes, ancdata, msg_flags, address), where nbytes is the total number of bytes of non-ancillary data written into the buffers, and ancdata, msg_flags and address are the same as for recvmsg().

Exemple :

>>> import socket
>>> s1, s2 = socket.socketpair()
>>> b1 = bytearray(b'----')
>>> b2 = bytearray(b'0123456789')
>>> b3 = bytearray(b'--------------')
>>> s1.send(b'Mary had a little lamb')
22
>>> s2.recvmsg_into([b1, memoryview(b2)[2:9], b3])
(22, [], 0, None)
>>> [b1, b2, b3]
[bytearray(b'Mary'), bytearray(b'01 had a 9'), bytearray(b'little lamb---')]

Availability: most Unix platforms, possibly others.

Nouveau dans la version 3.3.

socket.recvfrom_into(buffer[, nbytes[, flags]])

Receive data from the socket, writing it into buffer instead of creating a new bytestring. The return value is a pair (nbytes, address) where nbytes is the number of bytes received and address is the address of the socket sending the data. See the Unix manual page recv(2) for the meaning of the optional argument flags; it defaults to zero. (The format of address depends on the address family — see above.)

socket.recv_into(buffer[, nbytes[, flags]])

Receive up to nbytes bytes from the socket, storing the data into a buffer rather than creating a new bytestring. If nbytes is not specified (or 0), receive up to the size available in the given buffer. Returns the number of bytes received. See the Unix manual page recv(2) for the meaning of the optional argument flags; it defaults to zero.

socket.send(bytes[, flags])

Send data to the socket. The socket must be connected to a remote socket. The optional flags argument has the same meaning as for recv() above. Returns the number of bytes sent. Applications are responsible for checking that all data has been sent; if only some of the data was transmitted, the application needs to attempt delivery of the remaining data. For further information on this topic, consult the Socket Programming HOWTO.

Modifié dans la version 3.5: Si l’appel système est interrompu et que le gestionnaire de signal ne lève aucune exception, la fonction réessaye l’appel système au lieu de lever une InterruptedError (voir la PEP 475 [https://www.python.org/dev/peps/pep-0475] à propos du raisonnement).

socket.sendall(bytes[, flags])

Send data to the socket. The socket must be connected to a remote socket. The optional flags argument has the same meaning as for recv() above. Unlike send(), this method continues to send data from bytes until either all data has been sent or an error occurs. None is returned on success. On error, an exception is raised, and there is no way to determine how much data, if any, was successfully sent.

Modifié dans la version 3.5: The socket timeout is no more reset each time data is sent successfully. The socket timeout is now the maximum total duration to send all data.

Modifié dans la version 3.5: Si l’appel système est interrompu et que le gestionnaire de signal ne lève aucune exception, la fonction réessaye l’appel système au lieu de lever une InterruptedError (voir la PEP 475 [https://www.python.org/dev/peps/pep-0475] à propos du raisonnement).

socket.sendto(bytes, address)

socket.sendto(bytes, flags, address)

Send data to the socket. The socket should not be connected to a remote socket, since the destination socket is specified by address. The optional flags argument has the same meaning as for recv() above. Return the number of bytes sent. (The format of address depends on the address family — see above.)

Modifié dans la version 3.5: Si l’appel système est interrompu et que le gestionnaire de signal ne lève aucune exception, la fonction réessaye l’appel système au lieu de lever une InterruptedError (voir la PEP 475 [https://www.python.org/dev/peps/pep-0475] à propos du raisonnement).

socket.sendmsg(buffers[, ancdata[, flags[, address]]])

Send normal and ancillary data to the socket, gathering the non-ancillary data from a series of buffers and concatenating it into a single message. The buffers argument specifies the non-ancillary data as an iterable of bytes-like objects (e.g. bytes objects); the operating system may set a limit (sysconf() value SC_IOV_MAX) on the number of buffers that can be used. The ancdata argument specifies the ancillary data (control messages) as an iterable of zero or more tuples (cmsg_level, cmsg_type, cmsg_data), where cmsg_level and cmsg_type are integers specifying the protocol level and protocol-specific type respectively, and cmsg_data is a bytes-like object holding the associated data. Note that some systems (in particular, systems without CMSG_SPACE()) might support sending only one control message per call. The flags argument defaults to 0 and has the same meaning as for send(). If address is supplied and not None, it sets a destination address for the message. The return value is the number of bytes of non-ancillary data sent.

The following function sends the list of file descriptors fds over an AF_UNIX socket, on systems which support the SCM_RIGHTS mechanism. See also recvmsg().

import socket, array

def send_fds(sock, msg, fds):
    return sock.sendmsg([msg], [(socket.SOL_SOCKET, socket.SCM_RIGHTS, array.array("i", fds))])

Availability: most Unix platforms, possibly others.

Nouveau dans la version 3.3.

Modifié dans la version 3.5: Si l’appel système est interrompu et que le gestionnaire de signal ne lève aucune exception, la fonction réessaye l’appel système au lieu de lever une InterruptedError (voir la PEP 475 [https://www.python.org/dev/peps/pep-0475] à propos du raisonnement).

socket.sendmsg_afalg([msg, ]*, op[, iv[, assoclen[, flags]]])

Specialized version of sendmsg() for AF_ALG socket. Set mode, IV, AEAD associated data length and flags for AF_ALG socket.

Availability: Linux >= 2.6.38

Nouveau dans la version 3.6.

socket.sendfile(file, offset=0, count=None)

Send a file until EOF is reached by using high-performance os.sendfile and return the total number of bytes which were sent. file must be a regular file object opened in binary mode. If os.sendfile is not available (e.g. Windows) or file is not a regular file send() will be used instead. offset tells from where to start reading the file. If specified, count is the total number of bytes to transmit as opposed to sending the file until EOF is reached. File position is updated on return or also in case of error in which case file.tell() can be used to figure out the number of bytes which were sent. The socket must be of SOCK_STREAM type. Non-blocking sockets are not supported.

Nouveau dans la version 3.5.

socket.set_inheritable(inheritable)

Set the inheritable flag of the socket’s file descriptor or socket’s handle.

Nouveau dans la version 3.4.

socket.setblocking(flag)

Set blocking or non-blocking mode of the socket: if flag is false, the socket is set to non-blocking, else to blocking mode.

This method is a shorthand for certain settimeout() calls:

sock.setblocking(True) is equivalent to sock.settimeout(None)

sock.setblocking(False) is equivalent to sock.settimeout(0.0)

socket.settimeout(value)

Set a timeout on blocking socket operations. The value argument can be a nonnegative floating point number expressing seconds, or None. If a non-zero value is given, subsequent socket operations will raise a timeout exception if the timeout period value has elapsed before the operation has completed. If zero is given, the socket is put in non-blocking mode. If None is given, the socket is put in blocking mode.

For further information, please consult the notes on socket timeouts.

socket.setsockopt(level, optname, value: int)

socket.setsockopt(level, optname, value: buffer)

socket.setsockopt(level, optname, None, optlen: int)

Set the value of the given socket option (see the Unix manual page setsockopt(2)). The needed symbolic constants are defined in the socket module (SO_* etc.). The value can be an integer, None or a bytes-like object representing a buffer. In the later case it is up to the caller to ensure that the bytestring contains the proper bits (see the optional built-in module struct for a way to encode C structures as bytestrings). When value is set to None, optlen argument is required. It’s equivalent to call setsockopt C function with optval=NULL and optlen=optlen.

Modifié dans la version 3.5: N’importe quel bytes-like object est maintenant accepté.

Modifié dans la version 3.6: setsockopt(level, optname, None, optlen: int) form added.

socket.shutdown(how)

Shut down one or both halves of the connection. If how is SHUT_RD, further receives are disallowed. If how is SHUT_WR, further sends are disallowed. If how is SHUT_RDWR, further sends and receives are disallowed.

socket.share(process_id)

Duplicate a socket and prepare it for sharing with a target process. The target process must be provided with process_id. The resulting bytes object can then be passed to the target process using some form of interprocess communication and the socket can be recreated there using fromshare(). Once this method has been called, it is safe to close the socket since the operating system has already duplicated it for the target process.

Disponibilité : Windows.

Nouveau dans la version 3.3.

Note that there are no methods read() or write(); use recv() and send() without flags argument instead.

Socket objects also have these (read-only) attributes that correspond to the values given to the socket constructor.

socket.family

The socket family.

socket.type

The socket type.

socket.proto

The socket protocol.

18.1.4. Notes on socket timeouts

A socket object can be in one of three modes: blocking, non-blocking, or timeout. Sockets are by default always created in blocking mode, but this can be changed by calling setdefaulttimeout().

In blocking mode, operations block until complete or the system returns an error (such as connection timed out).

In non-blocking mode, operations fail (with an error that is unfortunately system-dependent) if they cannot be completed immediately: functions from the select can be used to know when and whether a socket is available for reading or writing.

In timeout mode, operations fail if they cannot be completed within the timeout specified for the socket (they raise a timeout exception) or if the system returns an error.

Note

At the operating system level, sockets in timeout mode are internally set in non-blocking mode. Also, the blocking and timeout modes are shared between file descriptors and socket objects that refer to the same network endpoint. This implementation detail can have visible consequences if e.g. you decide to use the fileno() of a socket.

18.1.4.1. Timeouts and the connect method

The connect() operation is also subject to the timeout setting, and in general it is recommended to call settimeout() before calling connect() or pass a timeout parameter to create_connection(). However, the system network stack may also return a connection timeout error of its own regardless of any Python socket timeout setting.

18.1.4.2. Timeouts and the accept method

If getdefaulttimeout() is not None, sockets returned by the accept() method inherit that timeout. Otherwise, the behaviour depends on settings of the listening socket:

if the listening socket is in blocking mode or in timeout mode, the socket returned by accept() is in blocking mode;

if the listening socket is in non-blocking mode, whether the socket returned by accept() is in blocking or non-blocking mode is operating system-dependent. If you want to ensure cross-platform behaviour, it is recommended you manually override this setting.

18.1.5. Exemple

Here are four minimal example programs using the TCP/IP protocol: a server that echoes all data that it receives back (servicing only one client), and a client using it. Note that a server must perform the sequence socket(), bind(), listen(), accept() (possibly repeating the accept() to service more than one client), while a client only needs the sequence socket(), connect(). Also note that the server does not sendall()/recv() on the socket it is listening on but on the new socket returned by accept().

The first two examples support IPv4 only.

# Echo server program
import socket

HOST = ''                 # Symbolic name meaning all available interfaces
PORT = 50007              # Arbitrary non-privileged port
with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s:
    s.bind((HOST, PORT))
    s.listen(1)
    conn, addr = s.accept()
    with conn:
        print('Connected by', addr)
        while True:
            data = conn.recv(1024)
            if not data: break
            conn.sendall(data)

# Echo client program
import socket

HOST = 'daring.cwi.nl'    # The remote host
PORT = 50007              # The same port as used by the server
with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s:
    s.connect((HOST, PORT))
    s.sendall(b'Hello, world')
    data = s.recv(1024)
print('Received', repr(data))

The next two examples are identical to the above two, but support both IPv4 and IPv6. The server side will listen to the first address family available (it should listen to both instead). On most of IPv6-ready systems, IPv6 will take precedence and the server may not accept IPv4 traffic. The client side will try to connect to the all addresses returned as a result of the name resolution, and sends traffic to the first one connected successfully.

# Echo server program
import socket
import sys

HOST = None               # Symbolic name meaning all available interfaces
PORT = 50007              # Arbitrary non-privileged port
s = None
for res in socket.getaddrinfo(HOST, PORT, socket.AF_UNSPEC,
                              socket.SOCK_STREAM, 0, socket.AI_PASSIVE):
    af, socktype, proto, canonname, sa = res
    try:
        s = socket.socket(af, socktype, proto)
    except OSError as msg:
        s = None
        continue
    try:
        s.bind(sa)
        s.listen(1)
    except OSError as msg:
        s.close()
        s = None
        continue
    break
if s is None:
    print('could not open socket')
    sys.exit(1)
conn, addr = s.accept()
with conn:
    print('Connected by', addr)
    while True:
        data = conn.recv(1024)
        if not data: break
        conn.send(data)

# Echo client program
import socket
import sys

HOST = 'daring.cwi.nl'    # The remote host
PORT = 50007              # The same port as used by the server
s = None
for res in socket.getaddrinfo(HOST, PORT, socket.AF_UNSPEC, socket.SOCK_STREAM):
    af, socktype, proto, canonname, sa = res
    try:
        s = socket.socket(af, socktype, proto)
    except OSError as msg:
        s = None
        continue
    try:
        s.connect(sa)
    except OSError as msg:
        s.close()
        s = None
        continue
    break
if s is None:
    print('could not open socket')
    sys.exit(1)
with s:
    s.sendall(b'Hello, world')
    data = s.recv(1024)
print('Received', repr(data))

The next example shows how to write a very simple network sniffer with raw sockets on Windows. The example requires administrator privileges to modify the interface:

import socket

# the public network interface
HOST = socket.gethostbyname(socket.gethostname())

# create a raw socket and bind it to the public interface
s = socket.socket(socket.AF_INET, socket.SOCK_RAW, socket.IPPROTO_IP)
s.bind((HOST, 0))

# Include IP headers
s.setsockopt(socket.IPPROTO_IP, socket.IP_HDRINCL, 1)

# receive all packages
s.ioctl(socket.SIO_RCVALL, socket.RCVALL_ON)

# receive a package
print(s.recvfrom(65565))

# disabled promiscuous mode
s.ioctl(socket.SIO_RCVALL, socket.RCVALL_OFF)

The last example shows how to use the socket interface to communicate to a CAN network using the raw socket protocol. To use CAN with the broadcast manager protocol instead, open a socket with:

socket.socket(socket.AF_CAN, socket.SOCK_DGRAM, socket.CAN_BCM)

After binding (CAN_RAW) or connecting (CAN_BCM) the socket, you can use the socket.send(), and the socket.recv() operations (and their counterparts) on the socket object as usual.

This example might require special privileges:

import socket
import struct

# CAN frame packing/unpacking (see 'struct can_frame' in <linux/can.h>)

can_frame_fmt = "=IB3x8s"
can_frame_size = struct.calcsize(can_frame_fmt)

def build_can_frame(can_id, data):
    can_dlc = len(data)
    data = data.ljust(8, b'\x00')
    return struct.pack(can_frame_fmt, can_id, can_dlc, data)

def dissect_can_frame(frame):
    can_id, can_dlc, data = struct.unpack(can_frame_fmt, frame)
    return (can_id, can_dlc, data[:can_dlc])

# create a raw socket and bind it to the 'vcan0' interface
s = socket.socket(socket.AF_CAN, socket.SOCK_RAW, socket.CAN_RAW)
s.bind(('vcan0',))

while True:
    cf, addr = s.recvfrom(can_frame_size)

    print('Received: can_id=%x, can_dlc=%x, data=%s' % dissect_can_frame(cf))

    try:
        s.send(cf)
    except OSError:
        print('Error sending CAN frame')

    try:
        s.send(build_can_frame(0x01, b'\x01\x02\x03'))
    except OSError:
        print('Error sending CAN frame')

Running an example several times with too small delay between executions, could lead to this error:

OSError: [Errno 98] Address already in use

This is because the previous execution has left the socket in a TIME_WAIT state, and can’t be immediately reused.

There is a socket flag to set, in order to prevent this, socket.SO_REUSEADDR:

s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
s.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)
s.bind((HOST, PORT))

the SO_REUSEADDR flag tells the kernel to reuse a local socket in TIME_WAIT state, without waiting for its natural timeout to expire.

Voir aussi

For an introduction to socket programming (in C), see the following papers:

An Introductory 4.3BSD Interprocess Communication Tutorial, by Stuart Sechrest

An Advanced 4.3BSD Interprocess Communication Tutorial, by Samuel J. Leffler et al,

both in the UNIX Programmer’s Manual, Supplementary Documents 1 (sections PS1:7 and PS1:8). The platform-specific reference material for the various socket-related system calls are also a valuable source of information on the details of socket semantics. For Unix, refer to the manual pages; for Windows, see the WinSock (or Winsock 2) specification. For IPv6-ready APIs, readers may want to refer to RFC 3493 [https://tools.ietf.org/html/rfc3493.html] titled Basic Socket Interface Extensions for IPv6.

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18.2. ssl — Emballage TLS/SSL pour les objets connecteurs

Code source : Lib/ssl.py [https://github.com/python/cpython/tree/3.6/Lib/ssl.py]

Ce module fournit un accès aux fonctions de chiffrement et d’authentification entre pairs : « Transport Layer Security » (souvent appelé « Secure Sockets Layer ») pour les connecteurs réseau, côté client et côté serveur. Ce module utilise la bibliothèque OpenSSL. Il est disponible sur tous les systèmes Unix modernes, Windows, Mac OS X et probablement sur d’autres plates-formes, à condition qu’OpenSSL soit installé sur cette plate-forme.

Note

Certains comportements peuvent dépendre de la plate-forme, car des appels sont passés aux API de connexions du système d’exploitation. La version installée de OpenSSL peut également entraîner des variations de comportement. Par exemple, TLSv1.1 et TLSv1.2 sont livrés avec la version 1.0.1 de OpenSSL.

Avertissement

N’utilisez pas ce module sans lire Security considerations. Cela pourrait créer un faux sentiment de sécurité, car les paramètres par défaut du module ssl ne sont pas nécessairement appropriés pour votre application.

Cette section documente les objets et les fonctions du module ssl. Pour des informations plus générales sur TLS, SSL et les certificats, le lecteur est prié de se référer aux documents de la section « Voir Aussi » au bas de cette page.

Ce module fournit une classe ssl.SSLSocket, dérivée du type socket.socket, ainsi qu’une enveloppe (wrapper en anglais) qui mime un connecteur qui chiffre et déchiffre les données passant sur le connecteur utilisant SSL. Il prend en charge des méthodes supplémentaires telles que getpeercert() qui récupère le certificat de l’autre coté de la connexion et cipher(), qui récupère le chiffrement utilisé pour la connexion.

Pour les applications plus sophistiquées, la classe ssl.SSLContext facilite la gestion des paramètres et des certificats, qui peuvent ensuite être hérités par les connecteurs SSL créés via la méthode SSLContext.wrap_socket().

Modifié dans la version 3.5.3: Mise à jour pour prendre en charge la liaison avec OpenSSL 1.1.0

Modifié dans la version 3.6: OpenSSL 0.9.8, 1.0.0 et 1.0.1 sont obsolètes et ne sont plus prises en charge. Dans l’avenir, le module ssl nécessitera au minimum OpenSSL 1.0.2 ou 1.1.0.

18.2.1. Fonctions, constantes et exceptions

exception ssl.SSLError

Levée pour signaler une erreur de l’implémentation SSL sous-jacente (actuellement fournie par la bibliothèque OpenSSL). Cela signifie qu’un problème est apparu dans la couche d’authentification et de chiffrement de niveau supérieur qui s’appuie sur la connexion réseau sous-jacente. Cette erreur est un sous-type de OSError. Le code d’erreur et le message des instances de SSLError sont fournis par la bibliothèque OpenSSL.

Modifié dans la version 3.3: SSLError était un sous-type de socket.error.

library

Une chaîne de caractères mnémonique désignant le sous-module OpenSSL dans lequel l’erreur s’est produite, telle que SSL, PEM ou X509. L’étendue des valeurs possibles dépend de la version d’OpenSSL.

Nouveau dans la version 3.3.

reason

A string mnemonic designating the reason this error occurred, for example CERTIFICATE_VERIFY_FAILED. The range of possible values depends on the OpenSSL version.

Nouveau dans la version 3.3.

exception ssl.SSLZeroReturnError

A subclass of SSLError raised when trying to read or write and the SSL connection has been closed cleanly. Note that this doesn’t mean that the underlying transport (read TCP) has been closed.

Nouveau dans la version 3.3.

exception ssl.SSLWantReadError

Sous-classe de SSLError levée par un connecteur SSL non bloquant lors d’une tentative de lecture ou d’écriture de données, alors que davantage de données doivent être reçues sur la couche TCP sous-jacente avant que la demande puisse être satisfaite.

Nouveau dans la version 3.3.

exception ssl.SSLWantWriteError

A subclass of SSLError raised by a non-blocking SSL socket when trying to read or write data, but more data needs to be sent on the underlying TCP transport before the request can be fulfilled.

Nouveau dans la version 3.3.

exception ssl.SSLSyscallError

A subclass of SSLError raised when a system error was encountered while trying to fulfill an operation on a SSL socket. Unfortunately, there is no easy way to inspect the original errno number.

Nouveau dans la version 3.3.

exception ssl.SSLEOFError

A subclass of SSLError raised when the SSL connection has been terminated abruptly. Generally, you shouldn’t try to reuse the underlying transport when this error is encountered.

Nouveau dans la version 3.3.

exception ssl.CertificateError

Raised to signal an error with a certificate (such as mismatching hostname). Certificate errors detected by OpenSSL, though, raise an SSLError.

18.2.1.1. Création de connecteurs

The following function allows for standalone socket creation. Starting from Python 3.2, it can be more flexible to use SSLContext.wrap_socket() instead.

ssl.wrap_socket(sock, keyfile=None, certfile=None, server_side=False, cert_reqs=CERT_NONE, ssl_version={see docs}, ca_certs=None, do_handshake_on_connect=True, suppress_ragged_eofs=True, ciphers=None)

Takes an instance sock of socket.socket, and returns an instance of ssl.SSLSocket, a subtype of socket.socket, which wraps the underlying socket in an SSL context. sock must be a SOCK_STREAM socket; other socket types are unsupported.

For client-side sockets, the context construction is lazy; if the underlying socket isn’t connected yet, the context construction will be performed after connect() is called on the socket. For server-side sockets, if the socket has no remote peer, it is assumed to be a listening socket, and the server-side SSL wrapping is automatically performed on client connections accepted via the accept() method. wrap_socket() may raise SSLError.

The keyfile and certfile parameters specify optional files which contain a certificate to be used to identify the local side of the connection. See the discussion of Certificates for more information on how the certificate is stored in the certfile.

The parameter server_side is a boolean which identifies whether server-side or client-side behavior is desired from this socket.

The parameter cert_reqs specifies whether a certificate is required from the other side of the connection, and whether it will be validated if provided. It must be one of the three values CERT_NONE (certificates ignored), CERT_OPTIONAL (not required, but validated if provided), or CERT_REQUIRED (required and validated). If the value of this parameter is not CERT_NONE, then the ca_certs parameter must point to a file of CA certificates.

The ca_certs file contains a set of concatenated « certification authority » certificates, which are used to validate certificates passed from the other end of the connection. See the discussion of Certificates for more information about how to arrange the certificates in this file.

The parameter ssl_version specifies which version of the SSL protocol to use. Typically, the server chooses a particular protocol version, and the client must adapt to the server’s choice. Most of the versions are not interoperable with the other versions. If not specified, the default is PROTOCOL_TLS; it provides the most compatibility with other versions.

Here’s a table showing which versions in a client (down the side) can connect to which versions in a server (along the top):

client / server

SSLv2

SSLv3

TLS 3

TLSv1

TLSv1.1

TLSv1.2

SSLv2

oui

non

no 1

non

non

non

SSLv3

non

oui

no 2

non

non

non

TLS (SSLv23) 3

no 1

no 2

oui

oui

oui

oui

TLSv1

non

non

oui

oui

non

non

TLSv1.1

non

non

oui

non

oui

non

TLSv1.2

non

non

oui

non

non

oui

Notes

1(1,2)

SSLContext disables SSLv2 with OP_NO_SSLv2 by default.

2(1,2)

SSLContext disables SSLv3 with OP_NO_SSLv3 by default.

3(1,2)

TLS 1.3 protocol will be available with PROTOCOL_TLS in OpenSSL >= 1.1.1. There is no dedicated PROTOCOL constant for just TLS 1.3.

Note

Which connections succeed will vary depending on the version of OpenSSL. For example, before OpenSSL 1.0.0, an SSLv23 client would always attempt SSLv2 connections.

The ciphers parameter sets the available ciphers for this SSL object. It should be a string in the OpenSSL cipher list format [https://www.openssl.org/docs/manmaster/man1/ciphers.html].

The parameter do_handshake_on_connect specifies whether to do the SSL handshake automatically after doing a socket.connect(), or whether the application program will call it explicitly, by invoking the SSLSocket.do_handshake() method. Calling SSLSocket.do_handshake() explicitly gives the program control over the blocking behavior of the socket I/O involved in the handshake.

The parameter suppress_ragged_eofs specifies how the SSLSocket.recv() method should signal unexpected EOF from the other end of the connection. If specified as True (the default), it returns a normal EOF (an empty bytes object) in response to unexpected EOF errors raised from the underlying socket; if False, it will raise the exceptions back to the caller.

Modifié dans la version 3.2: New optional argument ciphers.

18.2.1.2. Création de contexte

Une fonction utilitaire permettant de créer facilement des objets SSLContext pour des usages classiques.

ssl.create_default_context(purpose=Purpose.SERVER_AUTH, cafile=None, capath=None, cadata=None)

Renvoie un nouvel objet SSLContext. Le paramètre purpose permet de choisir parmi un ensemble de paramètres par défaut en fonction de l’usage souhaité. Les paramètres sont choisis par le module ssl et représentent généralement un niveau de sécurité supérieur à celui utilisé lorsque vous appelez directement le constructeur SSLContext.

cafile, capath, cadata représentent des certificats d’autorité de certification facultatifs approuvés pour la vérification de certificats, comme dans SSLContext.load_verify_locations(). Si les trois sont à None, cette fonction peut choisir de faire confiance aux certificats d’autorité de certification par défaut du système.

Les paramètres sont : PROTOCOL_TLS, OP_NO_SSLv2 et OP_NO_SSLv3 avec des algorithmes de chiffrement de grande robustesse, n’utilisant pas RC4 et n’utilisant pas les suites cryptographiques sans authentification. Passer SERVER_AUTH en tant que purpose définit verify_mode sur CERT_REQUIRED et charge les certificats de l’autorité de certification (lorsqu’au moins un des paramètres cafile, capath ou cadata est renseigné) ou utilise SSLContext.load_default_certs() pour charger les certificats des autorités de certification par défaut.

Note

Le protocole, les options, l’algorithme de chiffrement et d’autres paramètres peuvent changer pour des valeurs plus restrictives à tout moment sans avertissement préalable. Les valeurs représentent un juste équilibre entre compatibilité et sécurité.

Si votre application nécessite des paramètres spécifiques, vous devez créer une classe SSLContext et appliquer les paramètres vous-même.

Note

Si vous constatez que, lorsque certains clients ou serveurs plus anciens tentent de se connecter avec une classe SSLContext créée par cette fonction, une erreur indiquant « Protocol or cipher suite mismatch » (« Non concordance de protocole ou d’algorithme de chiffrement ») est détectée, il se peut qu’ils ne prennent en charge que SSL 3.0 que cette fonction exclut en utilisant OP_NO_SSLv3. SSL3.0 est notoirement considéré comme totalement déficient [https://fr.wikipedia.org/wiki/POODLE]. Si vous souhaitez toujours continuer à utiliser cette fonction tout en autorisant les connexions SSL 3.0, vous pouvez les réactiver à l’aide de :

ctx = ssl.create_default_context(Purpose.CLIENT_AUTH)
ctx.options &= ~ssl.OP_NO_SSLv3

Nouveau dans la version 3.4.

Modifié dans la version 3.4.4: RC4 a été supprimé de la liste des algorithmes de chiffrement par défaut.

Modifié dans la version 3.6: ChaCha20/Poly1305 a été ajouté à la liste des algorithmes de chiffrement par défaut.

3DES a été supprimé de la liste des algorithmes de chiffrement par défaut.

18.2.1.3. Random generation

ssl.RAND_bytes(num)

Return num cryptographically strong pseudo-random bytes. Raises an SSLError if the PRNG has not been seeded with enough data or if the operation is not supported by the current RAND method. RAND_status() can be used to check the status of the PRNG and RAND_add() can be used to seed the PRNG.

For almost all applications os.urandom() is preferable.

Read the Wikipedia article, Cryptographically secure pseudorandom number generator (CSPRNG) [https://en.wikipedia.org/wiki/Cryptographically_secure_pseudorandom_number_generator], to get the requirements of a cryptographically generator.

Nouveau dans la version 3.3.

ssl.RAND_pseudo_bytes(num)

Return (bytes, is_cryptographic): bytes are num pseudo-random bytes, is_cryptographic is True if the bytes generated are cryptographically strong. Raises an SSLError if the operation is not supported by the current RAND method.

Generated pseudo-random byte sequences will be unique if they are of sufficient length, but are not necessarily unpredictable. They can be used for non-cryptographic purposes and for certain purposes in cryptographic protocols, but usually not for key generation etc.

For almost all applications os.urandom() is preferable.

Nouveau dans la version 3.3.

Obsolète depuis la version 3.6: OpenSSL has deprecated ssl.RAND_pseudo_bytes(), use ssl.RAND_bytes() instead.

ssl.RAND_status()

Return True if the SSL pseudo-random number generator has been seeded with “enough” randomness, and False otherwise. You can use ssl.RAND_egd() and ssl.RAND_add() to increase the randomness of the pseudo-random number generator.

ssl.RAND_egd(path)

If you are running an entropy-gathering daemon (EGD) somewhere, and path is the pathname of a socket connection open to it, this will read 256 bytes of randomness from the socket, and add it to the SSL pseudo-random number generator to increase the security of generated secret keys. This is typically only necessary on systems without better sources of randomness.

See http://egd.sourceforge.net/ or http://prngd.sourceforge.net/ for sources of entropy-gathering daemons.

Availability: not available with LibreSSL and OpenSSL > 1.1.0

ssl.RAND_add(bytes, entropy)

Mix the given bytes into the SSL pseudo-random number generator. The parameter entropy (a float) is a lower bound on the entropy contained in string (so you can always use 0.0). See RFC 1750 [https://tools.ietf.org/html/rfc1750.html] for more information on sources of entropy.

Modifié dans la version 3.5: N’importe quel bytes-like object est maintenant accepté.

18.2.1.4. Certificate handling

ssl.match_hostname(cert, hostname)

Verify that cert (in decoded format as returned by SSLSocket.getpeercert()) matches the given hostname. The rules applied are those for checking the identity of HTTPS servers as outlined in RFC 2818 [https://tools.ietf.org/html/rfc2818.html], RFC 5280 [https://tools.ietf.org/html/rfc5280.html] and RFC 6125 [https://tools.ietf.org/html/rfc6125.html]. In addition to HTTPS, this function should be suitable for checking the identity of servers in various SSL-based protocols such as FTPS, IMAPS, POPS and others.

CertificateError is raised on failure. On success, the function returns nothing:

>>> cert = {'subject': ((('commonName', 'example.com'),),)}
>>> ssl.match_hostname(cert, "example.com")
>>> ssl.match_hostname(cert, "example.org")
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/home/py3k/Lib/ssl.py", line 130, in match_hostname
ssl.CertificateError: hostname 'example.org' doesn't match 'example.com'

Nouveau dans la version 3.2.

Modifié dans la version 3.3.3: The function now follows RFC 6125 [https://tools.ietf.org/html/rfc6125.html], section 6.4.3 and does neither match multiple wildcards (e.g. *.*.com or *a*.example.org) nor a wildcard inside an internationalized domain names (IDN) fragment. IDN A-labels such as www*.xn--pthon-kva.org are still supported, but x*.python.org no longer matches xn--tda.python.org.

Modifié dans la version 3.5: Matching of IP addresses, when present in the subjectAltName field of the certificate, is now supported.

ssl.cert_time_to_seconds(cert_time)

Return the time in seconds since the Epoch, given the cert_time string representing the « notBefore » or « notAfter » date from a certificate in "%b %d %H:%M:%S %Y %Z" strptime format (C locale).

Here’s an example:

>>> import ssl
>>> timestamp = ssl.cert_time_to_seconds("Jan  5 09:34:43 2018 GMT")
>>> timestamp
1515144883
>>> from datetime import datetime
>>> print(datetime.utcfromtimestamp(timestamp))
2018-01-05 09:34:43

« notBefore » or « notAfter » dates must use GMT (RFC 5280 [https://tools.ietf.org/html/rfc5280.html]).

Modifié dans la version 3.5: Interpret the input time as a time in UTC as specified by “GMT” timezone in the input string. Local timezone was used previously. Return an integer (no fractions of a second in the input format)

ssl.get_server_certificate(addr, ssl_version=PROTOCOL_TLS, ca_certs=None)

Given the address addr of an SSL-protected server, as a (hostname, port-number) pair, fetches the server’s certificate, and returns it as a PEM-encoded string. If ssl_version is specified, uses that version of the SSL protocol to attempt to connect to the server. If ca_certs is specified, it should be a file containing a list of root certificates, the same format as used for the same parameter in wrap_socket(). The call will attempt to validate the server certificate against that set of root certificates, and will fail if the validation attempt fails.

Modifié dans la version 3.3: This function is now IPv6-compatible.

Modifié dans la version 3.5: The default ssl_version is changed from PROTOCOL_SSLv3 to PROTOCOL_TLS for maximum compatibility with modern servers.

ssl.DER_cert_to_PEM_cert(DER_cert_bytes)

Given a certificate as a DER-encoded blob of bytes, returns a PEM-encoded string version of the same certificate.

ssl.PEM_cert_to_DER_cert(PEM_cert_string)

Given a certificate as an ASCII PEM string, returns a DER-encoded sequence of bytes for that same certificate.

ssl.get_default_verify_paths()

Returns a named tuple with paths to OpenSSL’s default cafile and capath. The paths are the same as used by SSLContext.set_default_verify_paths(). The return value is a named tuple DefaultVerifyPaths:

cafile - resolved path to cafile or None if the file doesn’t exist,

capath - resolved path to capath or None if the directory doesn’t exist,

openssl_cafile_env - OpenSSL’s environment key that points to a cafile,

openssl_cafile - hard coded path to a cafile,

openssl_capath_env - OpenSSL’s environment key that points to a capath,

openssl_capath - hard coded path to a capath directory

Availability: LibreSSL ignores the environment vars openssl_cafile_env and openssl_capath_env

Nouveau dans la version 3.4.

ssl.enum_certificates(store_name)

Retrieve certificates from Windows” system cert store. store_name may be one of CA, ROOT or MY. Windows may provide additional cert stores, too.

The function returns a list of (cert_bytes, encoding_type, trust) tuples. The encoding_type specifies the encoding of cert_bytes. It is either x509_asn for X.509 ASN.1 data or pkcs_7_asn for PKCS#7 ASN.1 data. Trust specifies the purpose of the certificate as a set of OIDS or exactly True if the certificate is trustworthy for all purposes.

Exemple :

>>> ssl.enum_certificates("CA")
[(b'data...', 'x509_asn', {'1.3.6.1.5.5.7.3.1', '1.3.6.1.5.5.7.3.2'}),
 (b'data...', 'x509_asn', True)]

Disponibilité : Windows.

Nouveau dans la version 3.4.

ssl.enum_crls(store_name)

Retrieve CRLs from Windows” system cert store. store_name may be one of CA, ROOT or MY. Windows may provide additional cert stores, too.

The function returns a list of (cert_bytes, encoding_type, trust) tuples. The encoding_type specifies the encoding of cert_bytes. It is either x509_asn for X.509 ASN.1 data or pkcs_7_asn for PKCS#7 ASN.1 data.

Disponibilité : Windows.

Nouveau dans la version 3.4.

18.2.1.5. Constantes

All constants are now enum.IntEnum or enum.IntFlag collections.

Nouveau dans la version 3.6.

ssl.CERT_NONE

Possible value for SSLContext.verify_mode, or the cert_reqs parameter to wrap_socket(). Except for PROTOCOL_TLS_CLIENT, it is the default mode. With client-side sockets, just about any cert is accepted. Validation errors, such as untrusted or expired cert, are ignored and do not abort the TLS/SSL handshake.

In server mode, no certificate is requested from the client, so the client does not send any for client cert authentication.

See the discussion of Security considerations below.

ssl.CERT_OPTIONAL

Possible value for SSLContext.verify_mode, or the cert_reqs parameter to wrap_socket(). In client mode, CERT_OPTIONAL has the same meaning as CERT_REQUIRED. It is recommended to use CERT_REQUIRED for client-side sockets instead.

In server mode, a client certificate request is sent to the client. The client may either ignore the request or send a certificate in order perform TLS client cert authentication. If the client chooses to send a certificate, it is verified. Any verification error immediately aborts the TLS handshake.

Use of this setting requires a valid set of CA certificates to be passed, either to SSLContext.load_verify_locations() or as a value of the ca_certs parameter to wrap_socket().

ssl.CERT_REQUIRED

Possible value for SSLContext.verify_mode, or the cert_reqs parameter to wrap_socket(). In this mode, certificates are required from the other side of the socket connection; an SSLError will be raised if no certificate is provided, or if its validation fails. This mode is not sufficient to verify a certificate in client mode as it does not match hostnames. check_hostname must be enabled as well to verify the authenticity of a cert. PROTOCOL_TLS_CLIENT uses CERT_REQUIRED and enables check_hostname by default.

With server socket, this mode provides mandatory TLS client cert authentication. A client certificate request is sent to the client and the client must provide a valid and trusted certificate.

Use of this setting requires a valid set of CA certificates to be passed, either to SSLContext.load_verify_locations() or as a value of the ca_certs parameter to wrap_socket().

class ssl.VerifyMode

enum.IntEnum collection of CERT_* constants.

Nouveau dans la version 3.6.

ssl.VERIFY_DEFAULT

Possible value for SSLContext.verify_flags. In this mode, certificate revocation lists (CRLs) are not checked. By default OpenSSL does neither require nor verify CRLs.

Nouveau dans la version 3.4.

ssl.VERIFY_CRL_CHECK_LEAF

Possible value for SSLContext.verify_flags. In this mode, only the peer cert is check but non of the intermediate CA certificates. The mode requires a valid CRL that is signed by the peer cert’s issuer (its direct ancestor CA). If no proper has been loaded SSLContext.load_verify_locations, validation will fail.

Nouveau dans la version 3.4.

ssl.VERIFY_CRL_CHECK_CHAIN

Possible value for SSLContext.verify_flags. In this mode, CRLs of all certificates in the peer cert chain are checked.

Nouveau dans la version 3.4.

ssl.VERIFY_X509_STRICT

Possible value for SSLContext.verify_flags to disable workarounds for broken X.509 certificates.

Nouveau dans la version 3.4.

ssl.VERIFY_X509_TRUSTED_FIRST

Possible value for SSLContext.verify_flags. It instructs OpenSSL to prefer trusted certificates when building the trust chain to validate a certificate. This flag is enabled by default.

Nouveau dans la version 3.4.4.

class ssl.VerifyFlags

enum.IntFlag collection of VERIFY_* constants.

Nouveau dans la version 3.6.

ssl.PROTOCOL_TLS

Selects the highest protocol version that both the client and server support. Despite the name, this option can select both « SSL » and « TLS » protocols.

Nouveau dans la version 3.6.

ssl.PROTOCOL_TLS_CLIENT

Auto-negotiate the highest protocol version like PROTOCOL_TLS, but only support client-side SSLSocket connections. The protocol enables CERT_REQUIRED and check_hostname by default.

Nouveau dans la version 3.6.

ssl.PROTOCOL_TLS_SERVER

Auto-negotiate the highest protocol version like PROTOCOL_TLS, but only support server-side SSLSocket connections.

Nouveau dans la version 3.6.

ssl.PROTOCOL_SSLv23

Alias for data:PROTOCOL_TLS.

Obsolète depuis la version 3.6: Use PROTOCOL_TLS instead.

ssl.PROTOCOL_SSLv2

Selects SSL version 2 as the channel encryption protocol.

This protocol is not available if OpenSSL is compiled with the OPENSSL_NO_SSL2 flag.

Avertissement

SSL version 2 is insecure. Its use is highly discouraged.

Obsolète depuis la version 3.6: OpenSSL has removed support for SSLv2.

ssl.PROTOCOL_SSLv3

Selects SSL version 3 as the channel encryption protocol.

This protocol is not be available if OpenSSL is compiled with the OPENSSL_NO_SSLv3 flag.

Avertissement

SSL version 3 is insecure. Its use is highly discouraged.

Obsolète depuis la version 3.6: OpenSSL has deprecated all version specific protocols. Use the default protocol PROTOCOL_TLS with flags like OP_NO_SSLv3 instead.

ssl.PROTOCOL_TLSv1

Selects TLS version 1.0 as the channel encryption protocol.

Obsolète depuis la version 3.6: OpenSSL has deprecated all version specific protocols. Use the default protocol PROTOCOL_TLS with flags like OP_NO_SSLv3 instead.

ssl.PROTOCOL_TLSv1_1

Selects TLS version 1.1 as the channel encryption protocol. Available only with openssl version 1.0.1+.

Nouveau dans la version 3.4.

Obsolète depuis la version 3.6: OpenSSL has deprecated all version specific protocols. Use the default protocol PROTOCOL_TLS with flags like OP_NO_SSLv3 instead.

ssl.PROTOCOL_TLSv1_2

Selects TLS version 1.2 as the channel encryption protocol. This is the most modern version, and probably the best choice for maximum protection, if both sides can speak it. Available only with openssl version 1.0.1+.

Nouveau dans la version 3.4.

Obsolète depuis la version 3.6: OpenSSL has deprecated all version specific protocols. Use the default protocol PROTOCOL_TLS with flags like OP_NO_SSLv3 instead.

ssl.OP_ALL

Enables workarounds for various bugs present in other SSL implementations. This option is set by default. It does not necessarily set the same flags as OpenSSL’s SSL_OP_ALL constant.

Nouveau dans la version 3.2.

ssl.OP_NO_SSLv2

Prevents an SSLv2 connection. This option is only applicable in conjunction with PROTOCOL_TLS. It prevents the peers from choosing SSLv2 as the protocol version.

Nouveau dans la version 3.2.

Obsolète depuis la version 3.6: SSLv2 is deprecated

ssl.OP_NO_SSLv3

Prevents an SSLv3 connection. This option is only applicable in conjunction with PROTOCOL_TLS. It prevents the peers from choosing SSLv3 as the protocol version.

Nouveau dans la version 3.2.

Obsolète depuis la version 3.6: SSLv3 is deprecated

ssl.OP_NO_TLSv1

Prevents a TLSv1 connection. This option is only applicable in conjunction with PROTOCOL_TLS. It prevents the peers from choosing TLSv1 as the protocol version.

Nouveau dans la version 3.2.

ssl.OP_NO_TLSv1_1

Prevents a TLSv1.1 connection. This option is only applicable in conjunction with PROTOCOL_TLS. It prevents the peers from choosing TLSv1.1 as the protocol version. Available only with openssl version 1.0.1+.

Nouveau dans la version 3.4.

ssl.OP_NO_TLSv1_2

Prevents a TLSv1.2 connection. This option is only applicable in conjunction with PROTOCOL_TLS. It prevents the peers from choosing TLSv1.2 as the protocol version. Available only with openssl version 1.0.1+.

Nouveau dans la version 3.4.

ssl.OP_NO_TLSv1_3

Prevents a TLSv1.3 connection. This option is only applicable in conjunction with PROTOCOL_TLS. It prevents the peers from choosing TLSv1.3 as the protocol version. TLS 1.3 is available with OpenSSL 1.1.1 or later. When Python has been compiled against an older version of OpenSSL, the flag defaults to 0.

Nouveau dans la version 3.6.3.

ssl.OP_CIPHER_SERVER_PREFERENCE

Use the server’s cipher ordering preference, rather than the client’s. This option has no effect on client sockets and SSLv2 server sockets.

Nouveau dans la version 3.3.

ssl.OP_SINGLE_DH_USE

Prevents re-use of the same DH key for distinct SSL sessions. This improves forward secrecy but requires more computational resources. This option only applies to server sockets.

Nouveau dans la version 3.3.

ssl.OP_SINGLE_ECDH_USE

Prevents re-use of the same ECDH key for distinct SSL sessions. This improves forward secrecy but requires more computational resources. This option only applies to server sockets.

Nouveau dans la version 3.3.

ssl.OP_ENABLE_MIDDLEBOX_COMPAT

Send dummy Change Cipher Spec (CCS) messages in TLS 1.3 handshake to make a TLS 1.3 connection look more like a TLS 1.2 connection.

This option is only available with OpenSSL 1.1.1 and later.

Nouveau dans la version 3.6.7.

ssl.OP_NO_COMPRESSION

Disable compression on the SSL channel. This is useful if the application protocol supports its own compression scheme.

This option is only available with OpenSSL 1.0.0 and later.

Nouveau dans la version 3.3.

class ssl.Options

enum.IntFlag collection of OP_* constants.

ssl.OP_NO_TICKET

Prevent client side from requesting a session ticket.

Nouveau dans la version 3.6.

ssl.HAS_ALPN

Whether the OpenSSL library has built-in support for the Application-Layer Protocol Negotiation TLS extension as described in RFC 7301 [https://tools.ietf.org/html/rfc7301.html].

Nouveau dans la version 3.5.

ssl.HAS_ECDH

Whether the OpenSSL library has built-in support for Elliptic Curve-based Diffie-Hellman key exchange. This should be true unless the feature was explicitly disabled by the distributor.

Nouveau dans la version 3.3.

ssl.HAS_SNI

Whether the OpenSSL library has built-in support for the Server Name Indication extension (as defined in RFC 6066 [https://tools.ietf.org/html/rfc6066.html]).

Nouveau dans la version 3.2.

ssl.HAS_NPN

Whether the OpenSSL library has built-in support for Next Protocol Negotiation as described in the NPN draft specification [https://tools.ietf.org/html/draft-agl-tls-nextprotoneg]. When true, you can use the SSLContext.set_npn_protocols() method to advertise which protocols you want to support.

Nouveau dans la version 3.3.

ssl.HAS_TLSv1_3

Whether the OpenSSL library has built-in support for the TLS 1.3 protocol.

Nouveau dans la version 3.6.3.

ssl.CHANNEL_BINDING_TYPES

List of supported TLS channel binding types. Strings in this list can be used as arguments to SSLSocket.get_channel_binding().

Nouveau dans la version 3.3.

ssl.OPENSSL_VERSION

The version string of the OpenSSL library loaded by the interpreter:

>>> ssl.OPENSSL_VERSION
'OpenSSL 1.0.2k  26 Jan 2017'

Nouveau dans la version 3.2.

ssl.OPENSSL_VERSION_INFO

A tuple of five integers representing version information about the OpenSSL library:

>>> ssl.OPENSSL_VERSION_INFO
(1, 0, 2, 11, 15)

Nouveau dans la version 3.2.

ssl.OPENSSL_VERSION_NUMBER

The raw version number of the OpenSSL library, as a single integer:

>>> ssl.OPENSSL_VERSION_NUMBER
268443839
>>> hex(ssl.OPENSSL_VERSION_NUMBER)
'0x100020bf'

Nouveau dans la version 3.2.

ssl.ALERT_DESCRIPTION_HANDSHAKE_FAILURE

ssl.ALERT_DESCRIPTION_INTERNAL_ERROR

ALERT_DESCRIPTION_*

Alert Descriptions from RFC 5246 [https://tools.ietf.org/html/rfc5246.html] and others. The IANA TLS Alert Registry [https://www.iana.org/assignments/tls-parameters/tls-parameters.xml#tls-parameters-6] contains this list and references to the RFCs where their meaning is defined.

Used as the return value of the callback function in SSLContext.set_servername_callback().

Nouveau dans la version 3.4.

class ssl.AlertDescription

enum.IntEnum collection of ALERT_DESCRIPTION_* constants.

Nouveau dans la version 3.6.

Purpose.SERVER_AUTH

Option for create_default_context() and SSLContext.load_default_certs(). This value indicates that the context may be used to authenticate Web servers (therefore, it will be used to create client-side sockets).

Nouveau dans la version 3.4.

Purpose.CLIENT_AUTH

Option for create_default_context() and SSLContext.load_default_certs(). This value indicates that the context may be used to authenticate Web clients (therefore, it will be used to create server-side sockets).

Nouveau dans la version 3.4.

class ssl.SSLErrorNumber

enum.IntEnum collection of SSL_ERROR_* constants.

Nouveau dans la version 3.6.

18.2.2. SSL Sockets

class ssl.SSLSocket(socket.socket)

SSL sockets provide the following methods of Socket Objects:

accept()

bind()

close()

connect()

detach()

fileno()

getpeername(), getsockname()

getsockopt(), setsockopt()

gettimeout(), settimeout(), setblocking()

listen()

makefile()

recv(), recv_into() (but passing a non-zero flags argument is not allowed)

send(), sendall() (with the same limitation)

sendfile() (but os.sendfile will be used for plain-text sockets only, else send() will be used)

shutdown()

However, since the SSL (and TLS) protocol has its own framing atop of TCP, the SSL sockets abstraction can, in certain respects, diverge from the specification of normal, OS-level sockets. See especially the notes on non-blocking sockets.

Usually, SSLSocket are not created directly, but using the SSLContext.wrap_socket() method.

Modifié dans la version 3.5: The sendfile() method was added.

Modifié dans la version 3.5: The shutdown() does not reset the socket timeout each time bytes are received or sent. The socket timeout is now to maximum total duration of the shutdown.

Obsolète depuis la version 3.6: It is deprecated to create a SSLSocket instance directly, use SSLContext.wrap_socket() to wrap a socket.

SSL sockets also have the following additional methods and attributes:

SSLSocket.read(len=1024, buffer=None)

Read up to len bytes of data from the SSL socket and return the result as a bytes instance. If buffer is specified, then read into the buffer instead, and return the number of bytes read.

Raise SSLWantReadError or SSLWantWriteError if the socket is non-blocking and the read would block.

As at any time a re-negotiation is possible, a call to read() can also cause write operations.

Modifié dans la version 3.5: The socket timeout is no more reset each time bytes are received or sent. The socket timeout is now to maximum total duration to read up to len bytes.

Obsolète depuis la version 3.6: Use recv() instead of read().

SSLSocket.write(buf)

Write buf to the SSL socket and return the number of bytes written. The buf argument must be an object supporting the buffer interface.

Raise SSLWantReadError or SSLWantWriteError if the socket is non-blocking and the write would block.

As at any time a re-negotiation is possible, a call to write() can also cause read operations.

Modifié dans la version 3.5: The socket timeout is no more reset each time bytes are received or sent. The socket timeout is now to maximum total duration to write buf.

Obsolète depuis la version 3.6: Use send() instead of write().

Note

The read() and write() methods are the low-level methods that read and write unencrypted, application-level data and decrypt/encrypt it to encrypted, wire-level data. These methods require an active SSL connection, i.e. the handshake was completed and SSLSocket.unwrap() was not called.

Normally you should use the socket API methods like recv() and send() instead of these methods.

SSLSocket.do_handshake()

Perform the SSL setup handshake.

Modifié dans la version 3.4: The handshake method also performs match_hostname() when the check_hostname attribute of the socket’s context is true.

Modifié dans la version 3.5: The socket timeout is no more reset each time bytes are received or sent. The socket timeout is now to maximum total duration of the handshake.

SSLSocket.getpeercert(binary_form=False)

If there is no certificate for the peer on the other end of the connection, return None. If the SSL handshake hasn’t been done yet, raise ValueError.

If the binary_form parameter is False, and a certificate was received from the peer, this method returns a dict instance. If the certificate was not validated, the dict is empty. If the certificate was validated, it returns a dict with several keys, amongst them subject (the principal for which the certificate was issued) and issuer (the principal issuing the certificate). If a certificate contains an instance of the Subject Alternative Name extension (see RFC 3280 [https://tools.ietf.org/html/rfc3280.html]), there will also be a subjectAltName key in the dictionary.

The subject and issuer fields are tuples containing the sequence of relative distinguished names (RDNs) given in the certificate’s data structure for the respective fields, and each RDN is a sequence of name-value pairs. Here is a real-world example:

{'issuer': ((('countryName', 'IL'),),
            (('organizationName', 'StartCom Ltd.'),),
            (('organizationalUnitName',
              'Secure Digital Certificate Signing'),),
            (('commonName',
              'StartCom Class 2 Primary Intermediate Server CA'),)),
 'notAfter': 'Nov 22 08:15:19 2013 GMT',
 'notBefore': 'Nov 21 03:09:52 2011 GMT',
 'serialNumber': '95F0',
 'subject': ((('description', '571208-SLe257oHY9fVQ07Z'),),
             (('countryName', 'US'),),
             (('stateOrProvinceName', 'California'),),
             (('localityName', 'San Francisco'),),
             (('organizationName', 'Electronic Frontier Foundation, Inc.'),),
             (('commonName', '*.eff.org'),),
             (('emailAddress', 'hostmaster@eff.org'),)),
 'subjectAltName': (('DNS', '*.eff.org'), ('DNS', 'eff.org')),
 'version': 3}

Note

To validate a certificate for a particular service, you can use the match_hostname() function.

If the binary_form parameter is True, and a certificate was provided, this method returns the DER-encoded form of the entire certificate as a sequence of bytes, or None if the peer did not provide a certificate. Whether the peer provides a certificate depends on the SSL socket’s role:

for a client SSL socket, the server will always provide a certificate, regardless of whether validation was required;

for a server SSL socket, the client will only provide a certificate when requested by the server; therefore getpeercert() will return None if you used CERT_NONE (rather than CERT_OPTIONAL or CERT_REQUIRED).

Modifié dans la version 3.2: The returned dictionary includes additional items such as issuer and notBefore.

Modifié dans la version 3.4: ValueError is raised when the handshake isn’t done. The returned dictionary includes additional X509v3 extension items such as crlDistributionPoints, caIssuers and OCSP URIs.

SSLSocket.cipher()

Returns a three-value tuple containing the name of the cipher being used, the version of the SSL protocol that defines its use, and the number of secret bits being used. If no connection has been established, returns None.

SSLSocket.shared_ciphers()

Return the list of ciphers shared by the client during the handshake. Each entry of the returned list is a three-value tuple containing the name of the cipher, the version of the SSL protocol that defines its use, and the number of secret bits the cipher uses. shared_ciphers() returns None if no connection has been established or the socket is a client socket.

Nouveau dans la version 3.5.

SSLSocket.compression()

Return the compression algorithm being used as a string, or None if the connection isn’t compressed.

If the higher-level protocol supports its own compression mechanism, you can use OP_NO_COMPRESSION to disable SSL-level compression.

Nouveau dans la version 3.3.

SSLSocket.get_channel_binding(cb_type="tls-unique")

Get channel binding data for current connection, as a bytes object. Returns None if not connected or the handshake has not been completed.

The cb_type parameter allow selection of the desired channel binding type. Valid channel binding types are listed in the CHANNEL_BINDING_TYPES list. Currently only the “tls-unique” channel binding, defined by RFC 5929 [https://tools.ietf.org/html/rfc5929.html], is supported. ValueError will be raised if an unsupported channel binding type is requested.

Nouveau dans la version 3.3.

SSLSocket.selected_alpn_protocol()

Return the protocol that was selected during the TLS handshake. If SSLContext.set_alpn_protocols() was not called, if the other party does not support ALPN, if this socket does not support any of the client’s proposed protocols, or if the handshake has not happened yet, None is returned.

Nouveau dans la version 3.5.

SSLSocket.selected_npn_protocol()

Return the higher-level protocol that was selected during the TLS/SSL handshake. If SSLContext.set_npn_protocols() was not called, or if the other party does not support NPN, or if the handshake has not yet happened, this will return None.

Nouveau dans la version 3.3.

SSLSocket.unwrap()

Performs the SSL shutdown handshake, which removes the TLS layer from the underlying socket, and returns the underlying socket object. This can be used to go from encrypted operation over a connection to unencrypted. The returned socket should always be used for further communication with the other side of the connection, rather than the original socket.

SSLSocket.verify_client_post_handshake()

Requests post-handshake authentication (PHA) from a TLS 1.3 client. PHA can only be initiated for a TLS 1.3 connection from a server-side socket, after the initial TLS handshake and with PHA enabled on both sides, see SSLContext.post_handshake_auth.

The method does not perform a cert exchange immediately. The server-side sends a CertificateRequest during the next write event and expects the client to respond with a certificate on the next read event.

If any precondition isn’t met (e.g. not TLS 1.3, PHA not enabled), an SSLError is raised.

Nouveau dans la version 3.6.7.

Note

Only available with OpenSSL 1.1.1 and TLS 1.3 enabled. Without TLS 1.3 support, the method raises NotImplementedError.

SSLSocket.version()

Return the actual SSL protocol version negotiated by the connection as a string, or None is no secure connection is established. As of this writing, possible return values include "SSLv2", "SSLv3", "TLSv1", "TLSv1.1" and "TLSv1.2". Recent OpenSSL versions may define more return values.

Nouveau dans la version 3.5.

SSLSocket.pending()

Returns the number of already decrypted bytes available for read, pending on the connection.

SSLSocket.context

The SSLContext object this SSL socket is tied to. If the SSL socket was created using the top-level wrap_socket() function (rather than SSLContext.wrap_socket()), this is a custom context object created for this SSL socket.

Nouveau dans la version 3.2.

SSLSocket.server_side

A boolean which is True for server-side sockets and False for client-side sockets.

Nouveau dans la version 3.2.

SSLSocket.server_hostname

Hostname of the server: str type, or None for server-side socket or if the hostname was not specified in the constructor.

Nouveau dans la version 3.2.

SSLSocket.session

The SSLSession for this SSL connection. The session is available for client and server side sockets after the TLS handshake has been performed. For client sockets the session can be set before do_handshake() has been called to reuse a session.

Nouveau dans la version 3.6.

SSLSocket.session_reused

Nouveau dans la version 3.6.

18.2.3. SSL Contexts

Nouveau dans la version 3.2.

An SSL context holds various data longer-lived than single SSL connections, such as SSL configuration options, certificate(s) and private key(s). It also manages a cache of SSL sessions for server-side sockets, in order to speed up repeated connections from the same clients.

class ssl.SSLContext(protocol=PROTOCOL_TLS)

Create a new SSL context. You may pass protocol which must be one of the PROTOCOL_* constants defined in this module. PROTOCOL_TLS is currently recommended for maximum interoperability and default value.

Voir aussi

create_default_context() lets the ssl module choose security settings for a given purpose.

Modifié dans la version 3.6: The context is created with secure default values. The options OP_NO_COMPRESSION, OP_CIPHER_SERVER_PREFERENCE, OP_SINGLE_DH_USE, OP_SINGLE_ECDH_USE, OP_NO_SSLv2 (except for PROTOCOL_SSLv2), and OP_NO_SSLv3 (except for PROTOCOL_SSLv3) are set by default. The initial cipher suite list contains only HIGH ciphers, no NULL ciphers and no MD5 ciphers (except for PROTOCOL_SSLv2).

SSLContext objects have the following methods and attributes:

SSLContext.cert_store_stats()

Get statistics about quantities of loaded X.509 certificates, count of X.509 certificates flagged as CA certificates and certificate revocation lists as dictionary.

Example for a context with one CA cert and one other cert:

>>> context.cert_store_stats()
{'crl': 0, 'x509_ca': 1, 'x509': 2}

Nouveau dans la version 3.4.

SSLContext.load_cert_chain(certfile, keyfile=None, password=None)

Load a private key and the corresponding certificate. The certfile string must be the path to a single file in PEM format containing the certificate as well as any number of CA certificates needed to establish the certificate’s authenticity. The keyfile string, if present, must point to a file containing the private key in. Otherwise the private key will be taken from certfile as well. See the discussion of Certificates for more information on how the certificate is stored in the certfile.

The password argument may be a function to call to get the password for decrypting the private key. It will only be called if the private key is encrypted and a password is necessary. It will be called with no arguments, and it should return a string, bytes, or bytearray. If the return value is a string it will be encoded as UTF-8 before using it to decrypt the key. Alternatively a string, bytes, or bytearray value may be supplied directly as the password argument. It will be ignored if the private key is not encrypted and no password is needed.

If the password argument is not specified and a password is required, OpenSSL’s built-in password prompting mechanism will be used to interactively prompt the user for a password.

An SSLError is raised if the private key doesn’t match with the certificate.

Modifié dans la version 3.3: New optional argument password.

SSLContext.load_default_certs(purpose=Purpose.SERVER_AUTH)

Load a set of default « certification authority » (CA) certificates from default locations. On Windows it loads CA certs from the CA and ROOT system stores. On other systems it calls SSLContext.set_default_verify_paths(). In the future the method may load CA certificates from other locations, too.

The purpose flag specifies what kind of CA certificates are loaded. The default settings Purpose.SERVER_AUTH loads certificates, that are flagged and trusted for TLS web server authentication (client side sockets). Purpose.CLIENT_AUTH loads CA certificates for client certificate verification on the server side.

Nouveau dans la version 3.4.

SSLContext.load_verify_locations(cafile=None, capath=None, cadata=None)

Load a set of « certification authority » (CA) certificates used to validate other peers” certificates when verify_mode is other than CERT_NONE. At least one of cafile or capath must be specified.

This method can also load certification revocation lists (CRLs) in PEM or DER format. In order to make use of CRLs, SSLContext.verify_flags must be configured properly.

The cafile string, if present, is the path to a file of concatenated CA certificates in PEM format. See the discussion of Certificates for more information about how to arrange the certificates in this file.

The capath string, if present, is the path to a directory containing several CA certificates in PEM format, following an OpenSSL specific layout [https://www.openssl.org/docs/man1.1.0/ssl/SSL_CTX_load_verify_locations.html].

The cadata object, if present, is either an ASCII string of one or more PEM-encoded certificates or a bytes-like object of DER-encoded certificates. Like with capath extra lines around PEM-encoded certificates are ignored but at least one certificate must be present.

Modifié dans la version 3.4: New optional argument cadata

SSLContext.get_ca_certs(binary_form=False)

Get a list of loaded « certification authority » (CA) certificates. If the binary_form parameter is False each list entry is a dict like the output of SSLSocket.getpeercert(). Otherwise the method returns a list of DER-encoded certificates. The returned list does not contain certificates from capath unless a certificate was requested and loaded by a SSL connection.

Note

Certificates in a capath directory aren’t loaded unless they have been used at least once.

Nouveau dans la version 3.4.

SSLContext.get_ciphers()

Get a list of enabled ciphers. The list is in order of cipher priority. See SSLContext.set_ciphers().

Exemple :

>>> ctx = ssl.SSLContext(ssl.PROTOCOL_SSLv23)
>>> ctx.set_ciphers('ECDHE+AESGCM:!ECDSA')
>>> ctx.get_ciphers()  # OpenSSL 1.0.x
[{'alg_bits': 256,
  'description': 'ECDHE-RSA-AES256-GCM-SHA384 TLSv1.2 Kx=ECDH     Au=RSA  '
                 'Enc=AESGCM(256) Mac=AEAD',
  'id': 50380848,
  'name': 'ECDHE-RSA-AES256-GCM-SHA384',
  'protocol': 'TLSv1/SSLv3',
  'strength_bits': 256},
 {'alg_bits': 128,
  'description': 'ECDHE-RSA-AES128-GCM-SHA256 TLSv1.2 Kx=ECDH     Au=RSA  '
                 'Enc=AESGCM(128) Mac=AEAD',
  'id': 50380847,
  'name': 'ECDHE-RSA-AES128-GCM-SHA256',
  'protocol': 'TLSv1/SSLv3',
  'strength_bits': 128}]

On OpenSSL 1.1 and newer the cipher dict contains additional fields::

>>> ctx.get_ciphers()  # OpenSSL 1.1+
[{'aead': True,
  'alg_bits': 256,
  'auth': 'auth-rsa',
  'description': 'ECDHE-RSA-AES256-GCM-SHA384 TLSv1.2 Kx=ECDH     Au=RSA  '
                 'Enc=AESGCM(256) Mac=AEAD',
  'digest': None,
  'id': 50380848,
  'kea': 'kx-ecdhe',
  'name': 'ECDHE-RSA-AES256-GCM-SHA384',
  'protocol': 'TLSv1.2',
  'strength_bits': 256,
  'symmetric': 'aes-256-gcm'},
 {'aead': True,
  'alg_bits': 128,
  'auth': 'auth-rsa',
  'description': 'ECDHE-RSA-AES128-GCM-SHA256 TLSv1.2 Kx=ECDH     Au=RSA  '
                 'Enc=AESGCM(128) Mac=AEAD',
  'digest': None,
  'id': 50380847,
  'kea': 'kx-ecdhe',
  'name': 'ECDHE-RSA-AES128-GCM-SHA256',
  'protocol': 'TLSv1.2',
  'strength_bits': 128,
  'symmetric': 'aes-128-gcm'}]

Availability: OpenSSL 1.0.2+

Nouveau dans la version 3.6.

SSLContext.set_default_verify_paths()

Load a set of default « certification authority » (CA) certificates from a filesystem path defined when building the OpenSSL library. Unfortunately, there’s no easy way to know whether this method succeeds: no error is returned if no certificates are to be found. When the OpenSSL library is provided as part of the operating system, though, it is likely to be configured properly.

SSLContext.set_ciphers(ciphers)

Set the available ciphers for sockets created with this context. It should be a string in the OpenSSL cipher list format [https://www.openssl.org/docs/manmaster/man1/ciphers.html]. If no cipher can be selected (because compile-time options or other configuration forbids use of all the specified ciphers), an SSLError will be raised.

Note

when connected, the SSLSocket.cipher() method of SSL sockets will give the currently selected cipher.

OpenSSL 1.1.1 has TLS 1.3 cipher suites enabled by default. The suites cannot be disabled with set_ciphers().

SSLContext.set_alpn_protocols(protocols)

Specify which protocols the socket should advertise during the SSL/TLS handshake. It should be a list of ASCII strings, like ['http/1.1', 'spdy/2'], ordered by preference. The selection of a protocol will happen during the handshake, and will play out according to RFC 7301 [https://tools.ietf.org/html/rfc7301.html]. After a successful handshake, the SSLSocket.selected_alpn_protocol() method will return the agreed-upon protocol.

This method will raise NotImplementedError if HAS_ALPN is False.

OpenSSL 1.1.0 to 1.1.0e will abort the handshake and raise SSLError when both sides support ALPN but cannot agree on a protocol. 1.1.0f+ behaves like 1.0.2, SSLSocket.selected_alpn_protocol() returns None.

Nouveau dans la version 3.5.

SSLContext.set_npn_protocols(protocols)

Specify which protocols the socket should advertise during the SSL/TLS handshake. It should be a list of strings, like ['http/1.1', 'spdy/2'], ordered by preference. The selection of a protocol will happen during the handshake, and will play out according to the NPN draft specification [https://tools.ietf.org/html/draft-agl-tls-nextprotoneg]. After a successful handshake, the SSLSocket.selected_npn_protocol() method will return the agreed-upon protocol.

This method will raise NotImplementedError if HAS_NPN is False.

Nouveau dans la version 3.3.

SSLContext.set_servername_callback(server_name_callback)

Register a callback function that will be called after the TLS Client Hello handshake message has been received by the SSL/TLS server when the TLS client specifies a server name indication. The server name indication mechanism is specified in RFC 6066 [https://tools.ietf.org/html/rfc6066.html] section 3 - Server Name Indication.

Only one callback can be set per SSLContext. If server_name_callback is None then the callback is disabled. Calling this function a subsequent time will disable the previously registered callback.

The callback function, server_name_callback, will be called with three arguments; the first being the ssl.SSLSocket, the second is a string that represents the server name that the client is intending to communicate (or None if the TLS Client Hello does not contain a server name) and the third argument is the original SSLContext. The server name argument is the IDNA decoded server name.

A typical use of this callback is to change the ssl.SSLSocket’s SSLSocket.context attribute to a new object of type SSLContext representing a certificate chain that matches the server name.

Due to the early negotiation phase of the TLS connection, only limited methods and attributes are usable like SSLSocket.selected_alpn_protocol() and SSLSocket.context. SSLSocket.getpeercert(), SSLSocket.getpeercert(), SSLSocket.cipher() and SSLSocket.compress() methods require that the TLS connection has progressed beyond the TLS Client Hello and therefore will not contain return meaningful values nor can they be called safely.

The server_name_callback function must return None to allow the TLS negotiation to continue. If a TLS failure is required, a constant ALERT_DESCRIPTION_* can be returned. Other return values will result in a TLS fatal error with ALERT_DESCRIPTION_INTERNAL_ERROR.

If there is an IDNA decoding error on the server name, the TLS connection will terminate with an ALERT_DESCRIPTION_INTERNAL_ERROR fatal TLS alert message to the client.

If an exception is raised from the server_name_callback function the TLS connection will terminate with a fatal TLS alert message ALERT_DESCRIPTION_HANDSHAKE_FAILURE.

This method will raise NotImplementedError if the OpenSSL library had OPENSSL_NO_TLSEXT defined when it was built.

Nouveau dans la version 3.4.

SSLContext.load_dh_params(dhfile)

Load the key generation parameters for Diffie-Hellman (DH) key exchange. Using DH key exchange improves forward secrecy at the expense of computational resources (both on the server and on the client). The dhfile parameter should be the path to a file containing DH parameters in PEM format.

This setting doesn’t apply to client sockets. You can also use the OP_SINGLE_DH_USE option to further improve security.

Nouveau dans la version 3.3.

SSLContext.set_ecdh_curve(curve_name)

Set the curve name for Elliptic Curve-based Diffie-Hellman (ECDH) key exchange. ECDH is significantly faster than regular DH while arguably as secure. The curve_name parameter should be a string describing a well-known elliptic curve, for example prime256v1 for a widely supported curve.

This setting doesn’t apply to client sockets. You can also use the OP_SINGLE_ECDH_USE option to further improve security.

This method is not available if HAS_ECDH is False.

Nouveau dans la version 3.3.

Voir aussi

SSL/TLS & Perfect Forward Secrecy [http://vincent.bernat.im/en/blog/2011-ssl-perfect-forward-secrecy.html]

Vincent Bernat.

SSLContext.wrap_socket(sock, server_side=False, do_handshake_on_connect=True, suppress_ragged_eofs=True, server_hostname=None, session=None)

Wrap an existing Python socket sock and return an SSLSocket object. sock must be a SOCK_STREAM socket; other socket types are unsupported.

The returned SSL socket is tied to the context, its settings and certificates. The parameters server_side, do_handshake_on_connect and suppress_ragged_eofs have the same meaning as in the top-level wrap_socket() function.

On client connections, the optional parameter server_hostname specifies the hostname of the service which we are connecting to. This allows a single server to host multiple SSL-based services with distinct certificates, quite similarly to HTTP virtual hosts. Specifying server_hostname will raise a ValueError if server_side is true.

session, see session.

Modifié dans la version 3.5: Always allow a server_hostname to be passed, even if OpenSSL does not have SNI.

Modifié dans la version 3.6: session argument was added.

SSLContext.wrap_bio(incoming, outgoing, server_side=False, server_hostname=None, session=None)

Create a new SSLObject instance by wrapping the BIO objects incoming and outgoing. The SSL routines will read input data from the incoming BIO and write data to the outgoing BIO.

The server_side, server_hostname and session parameters have the same meaning as in SSLContext.wrap_socket().

Modifié dans la version 3.6: session argument was added.

SSLContext.session_stats()

Get statistics about the SSL sessions created or managed by this context. A dictionary is returned which maps the names of each piece of information [https://www.openssl.org/docs/man1.1.0/ssl/SSL_CTX_sess_number.html] to their numeric values. For example, here is the total number of hits and misses in the session cache since the context was created:

>>> stats = context.session_stats()
>>> stats['hits'], stats['misses']
(0, 0)

SSLContext.check_hostname

Whether to match the peer cert’s hostname with match_hostname() in SSLSocket.do_handshake(). The context’s verify_mode must be set to CERT_OPTIONAL or CERT_REQUIRED, and you must pass server_hostname to wrap_socket() in order to match the hostname.

Exemple :

import socket, ssl

context = ssl.SSLContext()
context.verify_mode = ssl.CERT_REQUIRED
context.check_hostname = True
context.load_default_certs()

s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
ssl_sock = context.wrap_socket(s, server_hostname='www.verisign.com')
ssl_sock.connect(('www.verisign.com', 443))

Nouveau dans la version 3.4.

Note

This features requires OpenSSL 0.9.8f or newer.

SSLContext.options

An integer representing the set of SSL options enabled on this context. The default value is OP_ALL, but you can specify other options such as OP_NO_SSLv2 by ORing them together.

Note

With versions of OpenSSL older than 0.9.8m, it is only possible to set options, not to clear them. Attempting to clear an option (by resetting the corresponding bits) will raise a ValueError.

Modifié dans la version 3.6: SSLContext.options returns Options flags:

>>> ssl.create_default_context().options
<Options.OP_ALL|OP_NO_SSLv3|OP_NO_SSLv2|OP_NO_COMPRESSION: 2197947391>

SSLContext.post_handshake_auth

Enable TLS 1.3 post-handshake client authentication. Post-handshake auth is disabled by default and a server can only request a TLS client certificate during the initial handshake. When enabled, a server may request a TLS client certificate at any time after the handshake.

When enabled on client-side sockets, the client signals the server that it supports post-handshake authentication.

When enabled on server-side sockets, SSLContext.verify_mode must be set to CERT_OPTIONAL or CERT_REQUIRED, too. The actual client cert exchange is delayed until SSLSocket.verify_client_post_handshake() is called and some I/O is performed.

Nouveau dans la version 3.6.7.

Note

Only available with OpenSSL 1.1.1 and TLS 1.3 enabled. Without TLS 1.3 support, the property value is None and can’t be modified

SSLContext.protocol

The protocol version chosen when constructing the context. This attribute is read-only.

SSLContext.verify_flags

The flags for certificate verification operations. You can set flags like VERIFY_CRL_CHECK_LEAF by ORing them together. By default OpenSSL does neither require nor verify certificate revocation lists (CRLs). Available only with openssl version 0.9.8+.

Nouveau dans la version 3.4.

Modifié dans la version 3.6: SSLContext.verify_flags returns VerifyFlags flags:

>>> ssl.create_default_context().verify_flags
<VerifyFlags.VERIFY_X509_TRUSTED_FIRST: 32768>

SSLContext.verify_mode

Whether to try to verify other peers” certificates and how to behave if verification fails. This attribute must be one of CERT_NONE, CERT_OPTIONAL or CERT_REQUIRED.

Modifié dans la version 3.6: SSLContext.verify_mode returns VerifyMode enum:

>>> ssl.create_default_context().verify_mode
<VerifyMode.CERT_REQUIRED: 2>

18.2.4. Certificates

Certificates in general are part of a public-key / private-key system. In this system, each principal, (which may be a machine, or a person, or an organization) is assigned a unique two-part encryption key. One part of the key is public, and is called the public key; the other part is kept secret, and is called the private key. The two parts are related, in that if you encrypt a message with one of the parts, you can decrypt it with the other part, and only with the other part.

A certificate contains information about two principals. It contains the name of a subject, and the subject’s public key. It also contains a statement by a second principal, the issuer, that the subject is who they claim to be, and that this is indeed the subject’s public key. The issuer’s statement is signed with the issuer’s private key, which only the issuer knows. However, anyone can verify the issuer’s statement by finding the issuer’s public key, decrypting the statement with it, and comparing it to the other information in the certificate. The certificate also contains information about the time period over which it is valid. This is expressed as two fields, called « notBefore » and « notAfter ».

In the Python use of certificates, a client or server can use a certificate to prove who they are. The other side of a network connection can also be required to produce a certificate, and that certificate can be validated to the satisfaction of the client or server that requires such validation. The connection attempt can be set to raise an exception if the validation fails. Validation is done automatically, by the underlying OpenSSL framework; the application need not concern itself with its mechanics. But the application does usually need to provide sets of certificates to allow this process to take place.

Python uses files to contain certificates. They should be formatted as « PEM » (see RFC 1422 [https://tools.ietf.org/html/rfc1422.html]), which is a base-64 encoded form wrapped with a header line and a footer line:

-----BEGIN CERTIFICATE-----
... (certificate in base64 PEM encoding) ...
-----END CERTIFICATE-----

18.2.4.1. Certificate chains

The Python files which contain certificates can contain a sequence of certificates, sometimes called a certificate chain. This chain should start with the specific certificate for the principal who « is » the client or server, and then the certificate for the issuer of that certificate, and then the certificate for the issuer of that certificate, and so on up the chain till you get to a certificate which is self-signed, that is, a certificate which has the same subject and issuer, sometimes called a root certificate. The certificates should just be concatenated together in the certificate file. For example, suppose we had a three certificate chain, from our server certificate to the certificate of the certification authority that signed our server certificate, to the root certificate of the agency which issued the certification authority’s certificate:

-----BEGIN CERTIFICATE-----
... (certificate for your server)...
-----END CERTIFICATE-----
-----BEGIN CERTIFICATE-----
... (the certificate for the CA)...
-----END CERTIFICATE-----
-----BEGIN CERTIFICATE-----
... (the root certificate for the CA's issuer)...
-----END CERTIFICATE-----

18.2.4.2. CA certificates

If you are going to require validation of the other side of the connection’s certificate, you need to provide a « CA certs » file, filled with the certificate chains for each issuer you are willing to trust. Again, this file just contains these chains concatenated together. For validation, Python will use the first chain it finds in the file which matches. The platform’s certificates file can be used by calling SSLContext.load_default_certs(), this is done automatically with create_default_context().

18.2.4.3. Combined key and certificate

Often the private key is stored in the same file as the certificate; in this case, only the certfile parameter to SSLContext.load_cert_chain() and wrap_socket() needs to be passed. If the private key is stored with the certificate, it should come before the first certificate in the certificate chain:

-----BEGIN RSA PRIVATE KEY-----
... (private key in base64 encoding) ...
-----END RSA PRIVATE KEY-----
-----BEGIN CERTIFICATE-----
... (certificate in base64 PEM encoding) ...
-----END CERTIFICATE-----

18.2.4.4. Self-signed certificates

If you are going to create a server that provides SSL-encrypted connection services, you will need to acquire a certificate for that service. There are many ways of acquiring appropriate certificates, such as buying one from a certification authority. Another common practice is to generate a self-signed certificate. The simplest way to do this is with the OpenSSL package, using something like the following:

% openssl req -new -x509 -days 365 -nodes -out cert.pem -keyout cert.pem
Generating a 1024 bit RSA private key
.......++++++
.............................++++++
writing new private key to 'cert.pem'
-----
You are about to be asked to enter information that will be incorporated
into your certificate request.
What you are about to enter is what is called a Distinguished Name or a DN.
There are quite a few fields but you can leave some blank
For some fields there will be a default value,
If you enter '.', the field will be left blank.
-----
Country Name (2 letter code) [AU]:US
State or Province Name (full name) [Some-State]:MyState
Locality Name (eg, city) []:Some City
Organization Name (eg, company) [Internet Widgits Pty Ltd]:My Organization, Inc.
Organizational Unit Name (eg, section) []:My Group
Common Name (eg, YOUR name) []:myserver.mygroup.myorganization.com
Email Address []:ops@myserver.mygroup.myorganization.com
%

The disadvantage of a self-signed certificate is that it is its own root certificate, and no one else will have it in their cache of known (and trusted) root certificates.

18.2.5. Exemples

18.2.5.1. Testing for SSL support

To test for the presence of SSL support in a Python installation, user code should use the following idiom:

try:
    import ssl
except ImportError:
    pass
else:
    ...  # do something that requires SSL support

18.2.5.2. Client-side operation

This example creates a SSL context with the recommended security settings for client sockets, including automatic certificate verification:

>>> context = ssl.create_default_context()

If you prefer to tune security settings yourself, you might create a context from scratch (but beware that you might not get the settings right):

>>> context = ssl.SSLContext()
>>> context.verify_mode = ssl.CERT_REQUIRED
>>> context.check_hostname = True
>>> context.load_verify_locations("/etc/ssl/certs/ca-bundle.crt")

(this snippet assumes your operating system places a bundle of all CA certificates in /etc/ssl/certs/ca-bundle.crt; if not, you’ll get an error and have to adjust the location)

When you use the context to connect to a server, CERT_REQUIRED validates the server certificate: it ensures that the server certificate was signed with one of the CA certificates, and checks the signature for correctness:

>>> conn = context.wrap_socket(socket.socket(socket.AF_INET),
...                            server_hostname="www.python.org")
>>> conn.connect(("www.python.org", 443))

You may then fetch the certificate:

>>> cert = conn.getpeercert()

Visual inspection shows that the certificate does identify the desired service (that is, the HTTPS host www.python.org):

>>> pprint.pprint(cert)
{'OCSP': ('http://ocsp.digicert.com',),
 'caIssuers': ('http://cacerts.digicert.com/DigiCertSHA2ExtendedValidationServerCA.crt',),
 'crlDistributionPoints': ('http://crl3.digicert.com/sha2-ev-server-g1.crl',
                           'http://crl4.digicert.com/sha2-ev-server-g1.crl'),
 'issuer': ((('countryName', 'US'),),
            (('organizationName', 'DigiCert Inc'),),
            (('organizationalUnitName', 'www.digicert.com'),),
            (('commonName', 'DigiCert SHA2 Extended Validation Server CA'),)),
 'notAfter': 'Sep  9 12:00:00 2016 GMT',
 'notBefore': 'Sep  5 00:00:00 2014 GMT',
 'serialNumber': '01BB6F00122B177F36CAB49CEA8B6B26',
 'subject': ((('businessCategory', 'Private Organization'),),
             (('1.3.6.1.4.1.311.60.2.1.3', 'US'),),
             (('1.3.6.1.4.1.311.60.2.1.2', 'Delaware'),),
             (('serialNumber', '3359300'),),
             (('streetAddress', '16 Allen Rd'),),
             (('postalCode', '03894-4801'),),
             (('countryName', 'US'),),
             (('stateOrProvinceName', 'NH'),),
             (('localityName', 'Wolfeboro,'),),
             (('organizationName', 'Python Software Foundation'),),
             (('commonName', 'www.python.org'),)),
 'subjectAltName': (('DNS', 'www.python.org'),
                    ('DNS', 'python.org'),
                    ('DNS', 'pypi.org'),
                    ('DNS', 'docs.python.org'),
                    ('DNS', 'testpypi.org'),
                    ('DNS', 'bugs.python.org'),
                    ('DNS', 'wiki.python.org'),
                    ('DNS', 'hg.python.org'),
                    ('DNS', 'mail.python.org'),
                    ('DNS', 'packaging.python.org'),
                    ('DNS', 'pythonhosted.org'),
                    ('DNS', 'www.pythonhosted.org'),
                    ('DNS', 'test.pythonhosted.org'),
                    ('DNS', 'us.pycon.org'),
                    ('DNS', 'id.python.org')),
 'version': 3}

Now the SSL channel is established and the certificate verified, you can proceed to talk with the server:

>>> conn.sendall(b"HEAD / HTTP/1.0\r\nHost: linuxfr.org\r\n\r\n")
>>> pprint.pprint(conn.recv(1024).split(b"\r\n"))
[b'HTTP/1.1 200 OK',
 b'Date: Sat, 18 Oct 2014 18:27:20 GMT',
 b'Server: nginx',
 b'Content-Type: text/html; charset=utf-8',
 b'X-Frame-Options: SAMEORIGIN',
 b'Content-Length: 45679',
 b'Accept-Ranges: bytes',
 b'Via: 1.1 varnish',
 b'Age: 2188',
 b'X-Served-By: cache-lcy1134-LCY',
 b'X-Cache: HIT',
 b'X-Cache-Hits: 11',
 b'Vary: Cookie',
 b'Strict-Transport-Security: max-age=63072000; includeSubDomains',
 b'Connection: close',
 b'',
 b'']

See the discussion of Security considerations below.

18.2.5.3. Server-side operation

For server operation, typically you’ll need to have a server certificate, and private key, each in a file. You’ll first create a context holding the key and the certificate, so that clients can check your authenticity. Then you’ll open a socket, bind it to a port, call listen() on it, and start waiting for clients to connect:

import socket, ssl

context = ssl.create_default_context(ssl.Purpose.CLIENT_AUTH)
context.load_cert_chain(certfile="mycertfile", keyfile="mykeyfile")

bindsocket = socket.socket()
bindsocket.bind(('myaddr.mydomain.com', 10023))
bindsocket.listen(5)

When a client connects, you’ll call accept() on the socket to get the new socket from the other end, and use the context’s SSLContext.wrap_socket() method to create a server-side SSL socket for the connection:

while True:
    newsocket, fromaddr = bindsocket.accept()
    connstream = context.wrap_socket(newsocket, server_side=True)
    try:
        deal_with_client(connstream)
    finally:
        connstream.shutdown(socket.SHUT_RDWR)
        connstream.close()

Then you’ll read data from the connstream and do something with it till you are finished with the client (or the client is finished with you):

def deal_with_client(connstream):
    data = connstream.recv(1024)
    # empty data means the client is finished with us
    while data:
        if not do_something(connstream, data):
            # we'll assume do_something returns False
            # when we're finished with client
            break
        data = connstream.recv(1024)
    # finished with client

And go back to listening for new client connections (of course, a real server would probably handle each client connection in a separate thread, or put the sockets in non-blocking mode and use an event loop).

18.2.6. Notes on non-blocking sockets

SSL sockets behave slightly different than regular sockets in non-blocking mode. When working with non-blocking sockets, there are thus several things you need to be aware of:

Most SSLSocket methods will raise either SSLWantWriteError or SSLWantReadError instead of BlockingIOError if an I/O operation would block. SSLWantReadError will be raised if a read operation on the underlying socket is necessary, and SSLWantWriteError for a write operation on the underlying socket. Note that attempts to write to an SSL socket may require reading from the underlying socket first, and attempts to read from the SSL socket may require a prior write to the underlying socket.

Modifié dans la version 3.5: In earlier Python versions, the SSLSocket.send() method returned zero instead of raising SSLWantWriteError or SSLWantReadError.

Calling select() tells you that the OS-level socket can be read from (or written to), but it does not imply that there is sufficient data at the upper SSL layer. For example, only part of an SSL frame might have arrived. Therefore, you must be ready to handle SSLSocket.recv() and SSLSocket.send() failures, and retry after another call to select().

Conversely, since the SSL layer has its own framing, a SSL socket may still have data available for reading without select() being aware of it. Therefore, you should first call SSLSocket.recv() to drain any potentially available data, and then only block on a select() call if still necessary.

(of course, similar provisions apply when using other primitives such as poll(), or those in the selectors module)

The SSL handshake itself will be non-blocking: the SSLSocket.do_handshake() method has to be retried until it returns successfully. Here is a synopsis using select() to wait for the socket’s readiness:

while True:
    try:
        sock.do_handshake()
        break
    except ssl.SSLWantReadError:
        select.select([sock], [], [])
    except ssl.SSLWantWriteError:
        select.select([], [sock], [])

Voir aussi

The asyncio module supports non-blocking SSL sockets and provides a higher level API. It polls for events using the selectors module and handles SSLWantWriteError, SSLWantReadError and BlockingIOError exceptions. It runs the SSL handshake asynchronously as well.

18.2.7. Memory BIO Support

Nouveau dans la version 3.5.

Ever since the SSL module was introduced in Python 2.6, the SSLSocket class has provided two related but distinct areas of functionality:

SSL protocol handling

Network IO

The network IO API is identical to that provided by socket.socket, from which SSLSocket also inherits. This allows an SSL socket to be used as a drop-in replacement for a regular socket, making it very easy to add SSL support to an existing application.

Combining SSL protocol handling and network IO usually works well, but there are some cases where it doesn’t. An example is async IO frameworks that want to use a different IO multiplexing model than the « select/poll on a file descriptor » (readiness based) model that is assumed by socket.socket and by the internal OpenSSL socket IO routines. This is mostly relevant for platforms like Windows where this model is not efficient. For this purpose, a reduced scope variant of SSLSocket called SSLObject is provided.

class ssl.SSLObject

A reduced-scope variant of SSLSocket representing an SSL protocol instance that does not contain any network IO methods. This class is typically used by framework authors that want to implement asynchronous IO for SSL through memory buffers.

This class implements an interface on top of a low-level SSL object as implemented by OpenSSL. This object captures the state of an SSL connection but does not provide any network IO itself. IO needs to be performed through separate « BIO » objects which are OpenSSL’s IO abstraction layer.

An SSLObject instance can be created using the wrap_bio() method. This method will create the SSLObject instance and bind it to a pair of BIOs. The incoming BIO is used to pass data from Python to the SSL protocol instance, while the outgoing BIO is used to pass data the other way around.

The following methods are available:

context

server_side

server_hostname

session

session_reused

read()

write()

getpeercert()

selected_npn_protocol()

cipher()

shared_ciphers()

compression()

pending()

do_handshake()

unwrap()

get_channel_binding()

When compared to SSLSocket, this object lacks the following features:

Any form of network IO; recv() and send() read and write only to the underlying MemoryBIO buffers.

There is no do_handshake_on_connect machinery. You must always manually call do_handshake() to start the handshake.

There is no handling of suppress_ragged_eofs. All end-of-file conditions that are in violation of the protocol are reported via the SSLEOFError exception.

The method unwrap() call does not return anything, unlike for an SSL socket where it returns the underlying socket.

The server_name_callback callback passed to SSLContext.set_servername_callback() will get an SSLObject instance instead of a SSLSocket instance as its first parameter.

Some notes related to the use of SSLObject:

All IO on an SSLObject is non-blocking. This means that for example read() will raise an SSLWantReadError if it needs more data than the incoming BIO has available.

There is no module-level wrap_bio() call like there is for wrap_socket(). An SSLObject is always created via an SSLContext.

An SSLObject communicates with the outside world using memory buffers. The class MemoryBIO provides a memory buffer that can be used for this purpose. It wraps an OpenSSL memory BIO (Basic IO) object:

class ssl.MemoryBIO

A memory buffer that can be used to pass data between Python and an SSL protocol instance.

pending

Return the number of bytes currently in the memory buffer.

eof

A boolean indicating whether the memory BIO is current at the end-of-file position.

read(n=-1)

Read up to n bytes from the memory buffer. If n is not specified or negative, all bytes are returned.

write(buf)

Write the bytes from buf to the memory BIO. The buf argument must be an object supporting the buffer protocol.

The return value is the number of bytes written, which is always equal to the length of buf.

write_eof()

Write an EOF marker to the memory BIO. After this method has been called, it is illegal to call write(). The attribute eof will become true after all data currently in the buffer has been read.

18.2.8. SSL session

Nouveau dans la version 3.6.

class ssl.SSLSession

Session object used by session.

id

time

timeout

ticket_lifetime_hint

has_ticket

18.2.9. Security considerations

18.2.9.1. Best defaults

For client use, if you don’t have any special requirements for your security policy, it is highly recommended that you use the create_default_context() function to create your SSL context. It will load the system’s trusted CA certificates, enable certificate validation and hostname checking, and try to choose reasonably secure protocol and cipher settings.

For example, here is how you would use the smtplib.SMTP class to create a trusted, secure connection to a SMTP server:

>>> import ssl, smtplib
>>> smtp = smtplib.SMTP("mail.python.org", port=587)
>>> context = ssl.create_default_context()
>>> smtp.starttls(context=context)
(220, b'2.0.0 Ready to start TLS')

If a client certificate is needed for the connection, it can be added with SSLContext.load_cert_chain().

By contrast, if you create the SSL context by calling the SSLContext constructor yourself, it will not have certificate validation nor hostname checking enabled by default. If you do so, please read the paragraphs below to achieve a good security level.

18.2.9.2. Manual settings

18.2.9.2.1. Verifying certificates

When calling the SSLContext constructor directly, CERT_NONE is the default. Since it does not authenticate the other peer, it can be insecure, especially in client mode where most of time you would like to ensure the authenticity of the server you’re talking to. Therefore, when in client mode, it is highly recommended to use CERT_REQUIRED. However, it is in itself not sufficient; you also have to check that the server certificate, which can be obtained by calling SSLSocket.getpeercert(), matches the desired service. For many protocols and applications, the service can be identified by the hostname; in this case, the match_hostname() function can be used. This common check is automatically performed when SSLContext.check_hostname is enabled.

In server mode, if you want to authenticate your clients using the SSL layer (rather than using a higher-level authentication mechanism), you’ll also have to specify CERT_REQUIRED and similarly check the client certificate.

18.2.9.2.2. Protocol versions

SSL versions 2 and 3 are considered insecure and are therefore dangerous to use. If you want maximum compatibility between clients and servers, it is recommended to use PROTOCOL_TLS_CLIENT or PROTOCOL_TLS_SERVER as the protocol version. SSLv2 and SSLv3 are disabled by default.

>>> client_context = ssl.SSLContext(ssl.PROTOCOL_TLS_CLIENT)
>>> client_context.options |= ssl.OP_NO_TLSv1
>>> client_context.options |= ssl.OP_NO_TLSv1_1

The SSL context created above will only allow TLSv1.2 and later (if supported by your system) connections to a server. PROTOCOL_TLS_CLIENT implies certificate validation and hostname checks by default. You have to load certificates into the context.

18.2.9.2.3. Cipher selection

If you have advanced security requirements, fine-tuning of the ciphers enabled when negotiating a SSL session is possible through the SSLContext.set_ciphers() method. Starting from Python 3.2.3, the ssl module disables certain weak ciphers by default, but you may want to further restrict the cipher choice. Be sure to read OpenSSL’s documentation about the cipher list format [https://www.openssl.org/docs/apps/ciphers.html#CIPHER-LIST-FORMAT]. If you want to check which ciphers are enabled by a given cipher list, use SSLContext.get_ciphers() or the openssl ciphers command on your system.

18.2.9.3. Multi-processing

If using this module as part of a multi-processed application (using, for example the multiprocessing or concurrent.futures modules), be aware that OpenSSL’s internal random number generator does not properly handle forked processes. Applications must change the PRNG state of the parent process if they use any SSL feature with os.fork(). Any successful call of RAND_add(), RAND_bytes() or RAND_pseudo_bytes() is sufficient.

18.2.10. LibreSSL support

LibreSSL is a fork of OpenSSL 1.0.1. The ssl module has limited support for LibreSSL. Some features are not available when the ssl module is compiled with LibreSSL.

LibreSSL >= 2.6.1 no longer supports NPN. The methods SSLContext.set_npn_protocols() and SSLSocket.selected_npn_protocol() are not available.

SSLContext.set_default_verify_paths() ignores the env vars SSL_CERT_FILE and SSL_CERT_PATH although get_default_verify_paths() still reports them.

Voir aussi

Class socket.socket

Documentation of underlying socket class

SSL/TLS Strong Encryption: An Introduction [https://httpd.apache.org/docs/trunk/en/ssl/ssl_intro.html]

Intro from the Apache HTTP Server documentation

RFC 1422: Privacy Enhancement for Internet Electronic Mail: Part II: Certificate-Based Key Management [https://tools.ietf.org/html/rfc1422.html]

Steve Kent

RFC 4086: Randomness Requirements for Security [https://tools.ietf.org/html/rfc4086.html]

Donald E., Jeffrey I. Schiller

RFC 5280: Internet X.509 Public Key Infrastructure Certificate and Certificate Revocation List (CRL) Profile [https://tools.ietf.org/html/rfc5280.html]

D. Cooper

RFC 5246: The Transport Layer Security (TLS) Protocol Version 1.2 [https://tools.ietf.org/html/rfc5246.html]

T. Dierks et. al.

RFC 6066: Transport Layer Security (TLS) Extensions [https://tools.ietf.org/html/rfc6066.html]

D. Eastlake

IANA TLS: Transport Layer Security (TLS) Parameters [https://www.iana.org/assignments/tls-parameters/tls-parameters.xml]

IANA

RFC 7525: Recommendations for Secure Use of Transport Layer Security (TLS) and Datagram Transport Layer Security (DTLS) [https://tools.ietf.org/html/rfc7525.html]

IETF

Mozilla’s Server Side TLS recommendations [https://wiki.mozilla.org/Security/Server_Side_TLS]

Mozilla

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18.3. select — Waiting for I/O completion

This module provides access to the select() and poll() functions available in most operating systems, devpoll() available on Solaris and derivatives, epoll() available on Linux 2.5+ and kqueue() available on most BSD. Note that on Windows, it only works for sockets; on other operating systems, it also works for other file types (in particular, on Unix, it works on pipes). It cannot be used on regular files to determine whether a file has grown since it was last read.

Note

The selectors module allows high-level and efficient I/O multiplexing, built upon the select module primitives. Users are encouraged to use the selectors module instead, unless they want precise control over the OS-level primitives used.

Le module définit :

exception select.error

A deprecated alias of OSError.

Modifié dans la version 3.3: Following PEP 3151 [https://www.python.org/dev/peps/pep-3151], this class was made an alias of OSError.

select.devpoll()

(Only supported on Solaris and derivatives.) Returns a /dev/poll polling object; see section /dev/poll Polling Objects below for the methods supported by devpoll objects.

devpoll() objects are linked to the number of file descriptors allowed at the time of instantiation. If your program reduces this value, devpoll() will fail. If your program increases this value, devpoll() may return an incomplete list of active file descriptors.

The new file descriptor is non-inheritable.

Nouveau dans la version 3.3.

Modifié dans la version 3.4: Le nouveau descripteur de fichier est maintenant non-héritable.

select.epoll(sizehint=-1, flags=0)

(Only supported on Linux 2.5.44 and newer.) Return an edge polling object, which can be used as Edge or Level Triggered interface for I/O events.

sizehint informs epoll about the expected number of events to be registered. It must be positive, or -1 to use the default. It is only used on older systems where epoll_create1() is not available; otherwise it has no effect (though its value is still checked).

flags is deprecated and completely ignored. However, when supplied, its value must be 0 or select.EPOLL_CLOEXEC, otherwise OSError is raised.

See the Edge and Level Trigger Polling (epoll) Objects section below for the methods supported by epolling objects.

epoll objects support the context management protocol: when used in a with statement, the new file descriptor is automatically closed at the end of the block.

The new file descriptor is non-inheritable.

Modifié dans la version 3.3: Added the flags parameter.

Modifié dans la version 3.4: Support for the with statement was added. The new file descriptor is now non-inheritable.

Obsolète depuis la version 3.4: The flags parameter. select.EPOLL_CLOEXEC is used by default now. Use os.set_inheritable() to make the file descriptor inheritable.

select.poll()

(Not supported by all operating systems.) Returns a polling object, which supports registering and unregistering file descriptors, and then polling them for I/O events; see section Polling Objects below for the methods supported by polling objects.

select.kqueue()

(Only supported on BSD.) Returns a kernel queue object; see section Kqueue Objects below for the methods supported by kqueue objects.

The new file descriptor is non-inheritable.

Modifié dans la version 3.4: Le nouveau descripteur de fichier est maintenant non-héritable.

select.kevent(ident, filter=KQ_FILTER_READ, flags=KQ_EV_ADD, fflags=0, data=0, udata=0)

(Only supported on BSD.) Returns a kernel event object; see section Kevent Objects below for the methods supported by kevent objects.

select.select(rlist, wlist, xlist[, timeout])

This is a straightforward interface to the Unix select() system call. The first three arguments are sequences of “waitable objects”: either integers representing file descriptors or objects with a parameterless method named fileno() returning such an integer:

rlist: wait until ready for reading

wlist: wait until ready for writing

xlist: wait for an « exceptional condition » (see the manual page for what your system considers such a condition)

Empty sequences are allowed, but acceptance of three empty sequences is platform-dependent. (It is known to work on Unix but not on Windows.) The optional timeout argument specifies a time-out as a floating point number in seconds. When the timeout argument is omitted the function blocks until at least one file descriptor is ready. A time-out value of zero specifies a poll and never blocks.

The return value is a triple of lists of objects that are ready: subsets of the first three arguments. When the time-out is reached without a file descriptor becoming ready, three empty lists are returned.

Among the acceptable object types in the sequences are Python file objects (e.g. sys.stdin, or objects returned by open() or os.popen()), socket objects returned by socket.socket(). You may also define a wrapper class yourself, as long as it has an appropriate fileno() method (that really returns a file descriptor, not just a random integer).

Note

File objects on Windows are not acceptable, but sockets are. On Windows, the underlying select() function is provided by the WinSock library, and does not handle file descriptors that don’t originate from WinSock.

Modifié dans la version 3.5: The function is now retried with a recomputed timeout when interrupted by a signal, except if the signal handler raises an exception (see PEP 475 [https://www.python.org/dev/peps/pep-0475] for the rationale), instead of raising InterruptedError.

select.PIPE_BUF

The minimum number of bytes which can be written without blocking to a pipe when the pipe has been reported as ready for writing by select(), poll() or another interface in this module. This doesn’t apply to other kind of file-like objects such as sockets.

This value is guaranteed by POSIX to be at least 512. Availability: Unix.

Nouveau dans la version 3.2.

18.3.1. /dev/poll Polling Objects

Solaris and derivatives have /dev/poll. While select() is O(highest file descriptor) and poll() is O(number of file descriptors), /dev/poll is O(active file descriptors).

/dev/poll behaviour is very close to the standard poll() object.

devpoll.close()

Close the file descriptor of the polling object.

Nouveau dans la version 3.4.

devpoll.closed

True if the polling object is closed.

Nouveau dans la version 3.4.

devpoll.fileno()

Return the file descriptor number of the polling object.

Nouveau dans la version 3.4.

devpoll.register(fd[, eventmask])

Register a file descriptor with the polling object. Future calls to the poll() method will then check whether the file descriptor has any pending I/O events. fd can be either an integer, or an object with a fileno() method that returns an integer. File objects implement fileno(), so they can also be used as the argument.

eventmask is an optional bitmask describing the type of events you want to check for. The constants are the same that with poll() object. The default value is a combination of the constants POLLIN, POLLPRI, and POLLOUT.

Avertissement

Registering a file descriptor that’s already registered is not an error, but the result is undefined. The appropriate action is to unregister or modify it first. This is an important difference compared with poll().

devpoll.modify(fd[, eventmask])

This method does an unregister() followed by a register(). It is (a bit) more efficient that doing the same explicitly.

devpoll.unregister(fd)

Remove a file descriptor being tracked by a polling object. Just like the register() method, fd can be an integer or an object with a fileno() method that returns an integer.

Attempting to remove a file descriptor that was never registered is safely ignored.

devpoll.poll([timeout])

Polls the set of registered file descriptors, and returns a possibly-empty list containing (fd, event) 2-tuples for the descriptors that have events or errors to report. fd is the file descriptor, and event is a bitmask with bits set for the reported events for that descriptor — POLLIN for waiting input, POLLOUT to indicate that the descriptor can be written to, and so forth. An empty list indicates that the call timed out and no file descriptors had any events to report. If timeout is given, it specifies the length of time in milliseconds which the system will wait for events before returning. If timeout is omitted, -1, or None, the call will block until there is an event for this poll object.

Modifié dans la version 3.5: The function is now retried with a recomputed timeout when interrupted by a signal, except if the signal handler raises an exception (see PEP 475 [https://www.python.org/dev/peps/pep-0475] for the rationale), instead of raising InterruptedError.

18.3.2. Edge and Level Trigger Polling (epoll) Objects

http://linux.die.net/man/4/epoll

eventmask

Constante

Signification

EPOLLIN

Available for read

EPOLLOUT

Available for write

EPOLLPRI

Urgent data for read

EPOLLERR

Error condition happened on the assoc. fd

EPOLLHUP

Hang up happened on the assoc. fd

EPOLLET

Set Edge Trigger behavior, the default is Level Trigger behavior

EPOLLONESHOT

Set one-shot behavior. After one event is pulled out, the fd is internally disabled

EPOLLEXCLUSIVE

Wake only one epoll object when the associated fd has an event. The default (if this flag is not set) is to wake all epoll objects polling on a fd.

EPOLLRDHUP

Stream socket peer closed connection or shut down writing half of connection.

EPOLLRDNORM

Equivalent to EPOLLIN

EPOLLRDBAND

Priority data band can be read.

EPOLLWRNORM

Equivalent to EPOLLOUT

EPOLLWRBAND

Priority data may be written.

EPOLLMSG

Ignored.

epoll.close()

Close the control file descriptor of the epoll object.

epoll.closed

True if the epoll object is closed.

epoll.fileno()

Return the file descriptor number of the control fd.

epoll.fromfd(fd)

Create an epoll object from a given file descriptor.

epoll.register(fd[, eventmask])

Register a fd descriptor with the epoll object.

epoll.modify(fd, eventmask)

Modify a registered file descriptor.

epoll.unregister(fd)

Remove a registered file descriptor from the epoll object.

epoll.poll(timeout=-1, maxevents=-1)

Wait for events. timeout in seconds (float)

Modifié dans la version 3.5: The function is now retried with a recomputed timeout when interrupted by a signal, except if the signal handler raises an exception (see PEP 475 [https://www.python.org/dev/peps/pep-0475] for the rationale), instead of raising InterruptedError.

18.3.3. Polling Objects

The poll() system call, supported on most Unix systems, provides better scalability for network servers that service many, many clients at the same time. poll() scales better because the system call only requires listing the file descriptors of interest, while select() builds a bitmap, turns on bits for the fds of interest, and then afterward the whole bitmap has to be linearly scanned again. select() is O(highest file descriptor), while poll() is O(number of file descriptors).

poll.register(fd[, eventmask])

Register a file descriptor with the polling object. Future calls to the poll() method will then check whether the file descriptor has any pending I/O events. fd can be either an integer, or an object with a fileno() method that returns an integer. File objects implement fileno(), so they can also be used as the argument.

eventmask is an optional bitmask describing the type of events you want to check for, and can be a combination of the constants POLLIN, POLLPRI, and POLLOUT, described in the table below. If not specified, the default value used will check for all 3 types of events.

Constante

Signification

POLLIN

There is data to read

POLLPRI

There is urgent data to read

POLLOUT

Ready for output: writing will not block

POLLERR

Error condition of some sort

POLLHUP

Hung up

POLLRDHUP

Stream socket peer closed connection, or shut down writing half of connection

POLLNVAL

Invalid request: descriptor not open

Registering a file descriptor that’s already registered is not an error, and has the same effect as registering the descriptor exactly once.

poll.modify(fd, eventmask)

Modifies an already registered fd. This has the same effect as register(fd, eventmask). Attempting to modify a file descriptor that was never registered causes an OSError exception with errno ENOENT to be raised.

poll.unregister(fd)

Remove a file descriptor being tracked by a polling object. Just like the register() method, fd can be an integer or an object with a fileno() method that returns an integer.

Attempting to remove a file descriptor that was never registered causes a KeyError exception to be raised.

poll.poll([timeout])

Polls the set of registered file descriptors, and returns a possibly-empty list containing (fd, event) 2-tuples for the descriptors that have events or errors to report. fd is the file descriptor, and event is a bitmask with bits set for the reported events for that descriptor — POLLIN for waiting input, POLLOUT to indicate that the descriptor can be written to, and so forth. An empty list indicates that the call timed out and no file descriptors had any events to report. If timeout is given, it specifies the length of time in milliseconds which the system will wait for events before returning. If timeout is omitted, negative, or None, the call will block until there is an event for this poll object.

Modifié dans la version 3.5: The function is now retried with a recomputed timeout when interrupted by a signal, except if the signal handler raises an exception (see PEP 475 [https://www.python.org/dev/peps/pep-0475] for the rationale), instead of raising InterruptedError.

18.3.4. Kqueue Objects

kqueue.close()

Close the control file descriptor of the kqueue object.

kqueue.closed

True if the kqueue object is closed.

kqueue.fileno()

Return the file descriptor number of the control fd.

kqueue.fromfd(fd)

Create a kqueue object from a given file descriptor.

kqueue.control(changelist, max_events[, timeout=None]) → eventlist

Low level interface to kevent

changelist must be an iterable of kevent object or None

max_events must be 0 or a positive integer

timeout in seconds (floats possible)

Modifié dans la version 3.5: The function is now retried with a recomputed timeout when interrupted by a signal, except if the signal handler raises an exception (see PEP 475 [https://www.python.org/dev/peps/pep-0475] for the rationale), instead of raising InterruptedError.

18.3.5. Kevent Objects

https://www.freebsd.org/cgi/man.cgi?query=kqueue&sektion=2

kevent.ident

Value used to identify the event. The interpretation depends on the filter but it’s usually the file descriptor. In the constructor ident can either be an int or an object with a fileno() method. kevent stores the integer internally.

kevent.filter

Name of the kernel filter.

Constante

Signification

KQ_FILTER_READ

Takes a descriptor and returns whenever there is data available to read

KQ_FILTER_WRITE

Takes a descriptor and returns whenever there is data available to write

KQ_FILTER_AIO

AIO requests

KQ_FILTER_VNODE

Returns when one or more of the requested events watched in fflag occurs

KQ_FILTER_PROC

Watch for events on a process id

KQ_FILTER_NETDEV

Watch for events on a network device [not available on Mac OS X]

KQ_FILTER_SIGNAL

Returns whenever the watched signal is delivered to the process

KQ_FILTER_TIMER

Establishes an arbitrary timer

kevent.flags

Filter action.

Constante

Signification

KQ_EV_ADD

Adds or modifies an event

KQ_EV_DELETE

Removes an event from the queue

KQ_EV_ENABLE

Permitscontrol() to returns the event

KQ_EV_DISABLE

Disablesevent

KQ_EV_ONESHOT

Removes event after first occurrence

KQ_EV_CLEAR

Reset the state after an event is retrieved

KQ_EV_SYSFLAGS

internal event

KQ_EV_FLAG1

internal event

KQ_EV_EOF

Filter specific EOF condition

KQ_EV_ERROR

See return values

kevent.fflags

Filter specific flags.

KQ_FILTER_READ and KQ_FILTER_WRITE filter flags:

Constante

Signification

KQ_NOTE_LOWAT

low water mark of a socket buffer

KQ_FILTER_VNODE filter flags:

Constante

Signification

KQ_NOTE_DELETE

unlink() was called

KQ_NOTE_WRITE

a write occurred

KQ_NOTE_EXTEND

the file was extended

KQ_NOTE_ATTRIB

an attribute was changed

KQ_NOTE_LINK

the link count has changed

KQ_NOTE_RENAME

the file was renamed

KQ_NOTE_REVOKE

access to the file was revoked

KQ_FILTER_PROC filter flags:

Constante

Signification

KQ_NOTE_EXIT

the process has exited

KQ_NOTE_FORK

the process has called fork()

KQ_NOTE_EXEC

the process has executed a new process

KQ_NOTE_PCTRLMASK

internal filter flag

KQ_NOTE_PDATAMASK

internal filter flag

KQ_NOTE_TRACK

follow a process across fork()

KQ_NOTE_CHILD

returned on the child process for NOTE_TRACK

KQ_NOTE_TRACKERR

unable to attach to a child

KQ_FILTER_NETDEV filter flags (not available on Mac OS X):

Constante

Signification

KQ_NOTE_LINKUP

link is up

KQ_NOTE_LINKDOWN

link is down

KQ_NOTE_LINKINV

link state is invalid

kevent.data

Filter specific data.

kevent.udata

User defined value.

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18.4. selectors — High-level I/O multiplexing

Nouveau dans la version 3.4.

Source code: Lib/selectors.py [https://github.com/python/cpython/tree/3.6/Lib/selectors.py]

18.4.1. Introduction

This module allows high-level and efficient I/O multiplexing, built upon the select module primitives. Users are encouraged to use this module instead, unless they want precise control over the OS-level primitives used.

It defines a BaseSelector abstract base class, along with several concrete implementations (KqueueSelector, EpollSelector…), that can be used to wait for I/O readiness notification on multiple file objects. In the following, « file object » refers to any object with a fileno() method, or a raw file descriptor. See file object.

DefaultSelector is an alias to the most efficient implementation available on the current platform: this should be the default choice for most users.

Note

The type of file objects supported depends on the platform: on Windows, sockets are supported, but not pipes, whereas on Unix, both are supported (some other types may be supported as well, such as fifos or special file devices).

Voir aussi

select

Low-level I/O multiplexing module.

18.4.2. Classes

Classes hierarchy:

BaseSelector
+-- SelectSelector
+-- PollSelector
+-- EpollSelector
+-- DevpollSelector
+-- KqueueSelector

In the following, events is a bitwise mask indicating which I/O events should be waited for on a given file object. It can be a combination of the modules constants below:

Constante

Signification

EVENT_READ

Available for read

EVENT_WRITE

Available for write

class selectors.SelectorKey

A SelectorKey is a namedtuple used to associate a file object to its underlying file descriptor, selected event mask and attached data. It is returned by several BaseSelector methods.

fileobj

File object registered.

fd

Underlying file descriptor.

events

Events that must be waited for on this file object.

data

Optional opaque data associated to this file object: for example, this could be used to store a per-client session ID.

class selectors.BaseSelector

A BaseSelector is used to wait for I/O event readiness on multiple file objects. It supports file stream registration, unregistration, and a method to wait for I/O events on those streams, with an optional timeout. It’s an abstract base class, so cannot be instantiated. Use DefaultSelector instead, or one of SelectSelector, KqueueSelector etc. if you want to specifically use an implementation, and your platform supports it. BaseSelector and its concrete implementations support the context manager protocol.

abstractmethod register(fileobj, events, data=None)

Register a file object for selection, monitoring it for I/O events.

fileobj is the file object to monitor. It may either be an integer file descriptor or an object with a fileno() method. events is a bitwise mask of events to monitor. data is an opaque object.

This returns a new SelectorKey instance, or raises a ValueError in case of invalid event mask or file descriptor, or KeyError if the file object is already registered.

abstractmethod unregister(fileobj)

Unregister a file object from selection, removing it from monitoring. A file object shall be unregistered prior to being closed.

fileobj must be a file object previously registered.

This returns the associated SelectorKey instance, or raises a KeyError if fileobj is not registered. It will raise ValueError if fileobj is invalid (e.g. it has no fileno() method or its fileno() method has an invalid return value).

modify(fileobj, events, data=None)

Change a registered file object’s monitored events or attached data.

This is equivalent to BaseSelector.unregister(fileobj)() followed by BaseSelector.register(fileobj, events, data)(), except that it can be implemented more efficiently.

This returns a new SelectorKey instance, or raises a ValueError in case of invalid event mask or file descriptor, or KeyError if the file object is not registered.

abstractmethod select(timeout=None)

Wait until some registered file objects become ready, or the timeout expires.

If timeout > 0, this specifies the maximum wait time, in seconds. If timeout <= 0, the call won’t block, and will report the currently ready file objects. If timeout is None, the call will block until a monitored file object becomes ready.

This returns a list of (key, events) tuples, one for each ready file object.

key is the SelectorKey instance corresponding to a ready file object. events is a bitmask of events ready on this file object.

Note

This method can return before any file object becomes ready or the timeout has elapsed if the current process receives a signal: in this case, an empty list will be returned.

Modifié dans la version 3.5: The selector is now retried with a recomputed timeout when interrupted by a signal if the signal handler did not raise an exception (see PEP 475 [https://www.python.org/dev/peps/pep-0475] for the rationale), instead of returning an empty list of events before the timeout.

close()

Close the selector.

This must be called to make sure that any underlying resource is freed. The selector shall not be used once it has been closed.

get_key(fileobj)

Return the key associated with a registered file object.

This returns the SelectorKey instance associated to this file object, or raises KeyError if the file object is not registered.

abstractmethod get_map()

Return a mapping of file objects to selector keys.

This returns a Mapping instance mapping registered file objects to their associated SelectorKey instance.

class selectors.DefaultSelector

The default selector class, using the most efficient implementation available on the current platform. This should be the default choice for most users.

class selectors.SelectSelector

select.select()-based selector.

class selectors.PollSelector

select.poll()-based selector.

class selectors.EpollSelector

select.epoll()-based selector.

fileno()

This returns the file descriptor used by the underlying select.epoll() object.

class selectors.DevpollSelector

select.devpoll()-based selector.

fileno()

This returns the file descriptor used by the underlying select.devpoll() object.

Nouveau dans la version 3.5.

class selectors.KqueueSelector

select.kqueue()-based selector.

fileno()

This returns the file descriptor used by the underlying select.kqueue() object.

18.4.3. Exemples

Here is a simple echo server implementation:

import selectors
import socket

sel = selectors.DefaultSelector()

def accept(sock, mask):
    conn, addr = sock.accept()  # Should be ready
    print('accepted', conn, 'from', addr)
    conn.setblocking(False)
    sel.register(conn, selectors.EVENT_READ, read)

def read(conn, mask):
    data = conn.recv(1000)  # Should be ready
    if data:
        print('echoing', repr(data), 'to', conn)
        conn.send(data)  # Hope it won't block
    else:
        print('closing', conn)
        sel.unregister(conn)
        conn.close()

sock = socket.socket()
sock.bind(('localhost', 1234))
sock.listen(100)
sock.setblocking(False)
sel.register(sock, selectors.EVENT_READ, accept)

while True:
    events = sel.select()
    for key, mask in events:
        callback = key.data
        callback(key.fileobj, mask)

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18.5. asyncio — Entrées/Sorties asynchrone, boucle d’évènements, coroutines et tâches

Nouveau dans la version 3.4.

Code source : Lib/asyncio/ [https://github.com/python/cpython/tree/3.6/Lib/asyncio/]

Ce module fournit l’infrastructure pour écrire des programmes à fil d’exécution unique (single-thread en anglais) mais permettant l’exécution de code concurrent en utilisant les coroutines, les accès multiplexés aux entrées-sorties par l’intermédiaire de sockets ou autres ressources, la gestion de clients et serveurs réseaux et d’autres fonctions primitives associées. Voici une liste plus détaillée du contenu du paquet :

une boucle d’évènements prête à l’emploi dont les implémentations sont spécifiques à leur plateforme ;

Des abstractions pour les couches transport et protocole (similaire à celles proposées par Twisted [https://twistedmatrix.com/trac/]) ;

pour la gestion effective de TCP, UDP, SSL, la communication inter-processus par tubes, les appels différés, et autres (certains peuvent être dépendant du système) ;

une classe Future qui imite celle du concurrent.futures module, mais qui est adaptée pour fonctionner avec la boucle d’évènements ;

des coroutines et tâches qui se basent sur yield from (PEP 380 [https://www.python.org/dev/peps/pep-0380]), pour écrire du code concurrent de manière séquentielle ;

annulation de la gestion de la classe Futures et coroutines ;

des primitives de synchronisation à utiliser entre des coroutines dans un fil d’exécution unique, en imitant celles présentes dans le module threading ;

une interface pour déléguer des tâches à un groupe de fils d’exécutions, lorsque vous avez absolument besoin d’utiliser une bibliothèque qui effectue des entrées-sorties bloquantes.

Programmer de façon asynchrone est plus complexe que programmer d’une façon séquentielle : lisez la page Develop with asyncio qui liste les pièges fréquents et explique la manière de les éviter. Activer le mode de débogage d’asyncio pendant le développement afin de détecter les problèmes courants.

Table des matières :

18.5.1. Base Event Loop

18.5.1.1. Exécuter une boucle d’évènements

18.5.1.2. Appels

18.5.1.3. Appels différés

18.5.1.4. Futurs

18.5.1.5. Tâches

18.5.1.6. Créer des connections

18.5.1.7. Attendre des connections

18.5.1.8. Surveiller des descripteurs de fichiers

18.5.1.9. Opérations bas niveau sur les socket

18.5.1.10. Résout le nom d’hôte

18.5.1.11. Connect pipes

18.5.1.12. Signaux UNIX

18.5.1.13. Exécuteur

18.5.1.14. API de gestion d’erreur

18.5.1.15. Mode débogage

18.5.1.16. Serveur

18.5.1.17. Handle

18.5.1.18. Exemples de boucles d’évènements

18.5.1.18.1. « Hello World » avec call_soon()

18.5.1.18.2. Afficher la date actuelle avec call_later()

18.5.1.18.3. Watch a file descriptor for read events

18.5.1.18.4. Définit les gestionnaires de signaux pour SIGINT et SIGTERM

18.5.2. Boucles d’évènements

18.5.2.1. Fonctions des boucles d’évènements

18.5.2.2. Boucles d’évènements disponibles

18.5.2.3. Support des plateformes

18.5.2.3.1. Windows

18.5.2.3.2. Mac OS X

18.5.2.4. Event loop policies and the default policy

18.5.2.5. Event loop policy interface

18.5.2.6. Access to the global loop policy

18.5.2.7. Customizing the event loop policy

18.5.3. Tâches et coroutines

18.5.3.1. Coroutines

18.5.3.1.1. Exemple : Coroutine « Hello World »

18.5.3.1.2. Exemple : Coroutine affichant la date actuelle

18.5.3.1.3. Exemple : Chaîner des coroutines

18.5.3.2. InvalidStateError

18.5.3.3. TimeoutError

18.5.3.4. Future

18.5.3.4.1. Exemple : Futur avec run_until_complete()

18.5.3.4.2. Exemple : Futur avec run_forever()

18.5.3.5. Task

18.5.3.5.1. Exemple : Exécution parallèle de tâches

18.5.3.6. Task functions

18.5.4. Transports et protocoles (APi basée sur des fonctions de rappel)

18.5.4.1. Transports

18.5.4.1.1. BaseTransport

18.5.4.1.2. ReadTransport

18.5.4.1.3. WriteTransport

18.5.4.1.4. DatagramTransport

18.5.4.1.5. BaseSubprocessTransport

18.5.4.2. Protocols

18.5.4.2.1. Protocol classes

18.5.4.2.2. Connection callbacks

18.5.4.2.3. Streaming protocols

18.5.4.2.4. Protocoles de datagrammes

18.5.4.2.5. Flow control callbacks

18.5.4.2.6. Coroutines et protocoles

18.5.4.3. Exemples de protocole

18.5.4.3.1. Protocole « echo client » en TCP

18.5.4.3.2. Protocole « echo serveur » en TCP

18.5.4.3.3. Protocole « echo client » en UDP

18.5.4.3.4. Protocole « echo serveur » en UDP

18.5.4.3.5. Register an open socket to wait for data using a protocol

18.5.5. Streams (coroutine based API)

18.5.5.1. Stream functions

18.5.5.2. StreamReader

18.5.5.3. StreamWriter

18.5.5.4. StreamReaderProtocol

18.5.5.5. IncompleteReadError

18.5.5.6. LimitOverrunError

18.5.5.7. Stream examples

18.5.5.7.1. TCP echo client using streams

18.5.5.7.2. TCP echo server using streams

18.5.5.7.3. Récupère les en-têtes HTTP

18.5.5.7.4. Register an open socket to wait for data using streams

18.5.6. Subprocess

18.5.6.1. Boucle d’évènements Windows

18.5.6.2. Créer un processus fils : API de haut niveau utilisant Process

18.5.6.3. Create a subprocess: low-level API using subprocess.Popen

18.5.6.4. Constantes

18.5.6.5. Process

18.5.6.6. Processus fils et fils d’exécution

18.5.6.7. Subprocess examples

18.5.6.7.1. Subprocess using transport and protocol

18.5.6.7.2. Subprocess using streams

18.5.7. Primitives de synchronisation

18.5.7.1. Locks

18.5.7.1.1. Lock

18.5.7.1.2. Event

18.5.7.1.3. Condition

18.5.7.2. Sémaphores

18.5.7.2.1. Sémaphore

18.5.7.2.2. BoundedSemaphore

18.5.8. Queues

18.5.8.1. Queue

18.5.8.2. PriorityQueue

18.5.8.3. LifoQueue

18.5.8.3.1. Exceptions

18.5.9. Programmer avec asyncio

18.5.9.1. Mode de débogage d”asyncio

18.5.9.2. Annulation

18.5.9.3. Concourance et multithreading

18.5.9.4. Gérer les fonctions bloquantes correctement

18.5.9.5. Journalisation

18.5.9.6. Détecte les coroutines qui ne sont jamais exécutées

18.5.9.7. Detect exceptions never consumed

18.5.9.8. Chaîner les coroutines correctement

18.5.9.9. Pending task destroyed

18.5.9.10. Close transports and event loops

Voir aussi

Le module asyncio a été présenté dans la PEP 3156 [https://www.python.org/dev/peps/pep-3156]. La PEP 3153 [https://www.python.org/dev/peps/pep-3153] décrit les motivations premières concernant les couches transports et protocoles.

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18.5. asyncio — Entrées/Sorties asynchrone, boucle d’évènements, coroutines et tâches »

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18.5.1. Base Event Loop

Source code: Lib/asyncio/events.py [https://github.com/python/cpython/tree/3.6/Lib/asyncio/events.py]

The event loop is the central execution device provided by asyncio. It provides multiple facilities, including:

Registering, executing and cancelling delayed calls (timeouts).

Creating client and server transports for various kinds of communication.

Launching subprocesses and the associated transports for communication with an external program.

Delegating costly function calls to a pool of threads.

class asyncio.BaseEventLoop

This class is an implementation detail. It is a subclass of AbstractEventLoop and may be a base class of concrete event loop implementations found in asyncio. It should not be used directly; use AbstractEventLoop instead. BaseEventLoop should not be subclassed by third-party code; the internal interface is not stable.

class asyncio.AbstractEventLoop

Abstract base class of event loops.

This class is not thread safe.

18.5.1.1. Exécuter une boucle d’évènements

AbstractEventLoop.run_forever()

Run until stop() is called. If stop() is called before run_forever() is called, this polls the I/O selector once with a timeout of zero, runs all callbacks scheduled in response to I/O events (and those that were already scheduled), and then exits. If stop() is called while run_forever() is running, this will run the current batch of callbacks and then exit. Note that callbacks scheduled by callbacks will not run in that case; they will run the next time run_forever() is called.

Modifié dans la version 3.5.1.

AbstractEventLoop.run_until_complete(future)

Exécuter jusqu’à ce que Future soit terminé.

If the argument is a coroutine object, it is wrapped by ensure_future().

Return the Future’s result, or raise its exception.

AbstractEventLoop.is_running()

Donne le status d’exécution de la boucle d’évènements.

AbstractEventLoop.stop()

Arrête l’exécution de la boucle d’évènements.

This causes run_forever() to exit at the next suitable opportunity (see there for more details).

Modifié dans la version 3.5.1.

AbstractEventLoop.is_closed()

Donne True si la boucle d’évènements est fermée.

Nouveau dans la version 3.4.2.

AbstractEventLoop.close()

Close the event loop. The loop must not be running. Pending callbacks will be lost.

This clears the queues and shuts down the executor, but does not wait for the executor to finish.

This is idempotent and irreversible. No other methods should be called after this one.

coroutine AbstractEventLoop.shutdown_asyncgens()

Schedule all currently open asynchronous generator objects to close with an aclose() call. After calling this method, the event loop will issue a warning whenever a new asynchronous generator is iterated. Should be used to finalize all scheduled asynchronous generators reliably. Example:

try:
    loop.run_forever()
finally:
    loop.run_until_complete(loop.shutdown_asyncgens())
    loop.close()

Nouveau dans la version 3.6.

18.5.1.2. Appels

Most asyncio functions don’t accept keywords. If you want to pass keywords to your callback, use functools.partial(). For example, loop.call_soon(functools.partial(print, "Hello", flush=True)) will call print("Hello", flush=True).

Note

functools.partial() is better than lambda functions, because asyncio can inspect functools.partial() object to display parameters in debug mode, whereas lambda functions have a poor representation.

AbstractEventLoop.call_soon(callback, *args)

Arrange for a callback to be called as soon as possible. The callback is called after call_soon() returns, when control returns to the event loop.

This operates as a FIFO queue, callbacks are called in the order in which they are registered. Each callback will be called exactly once.

Any positional arguments after the callback will be passed to the callback when it is called.

An instance of asyncio.Handle is returned, which can be used to cancel the callback.

Use functools.partial to pass keywords to the callback.

AbstractEventLoop.call_soon_threadsafe(callback, *args)

Comme call_soon() mais thread safe.

Voir la section exécution concurrente et multi-fils d’exécution de la documentation.

18.5.1.3. Appels différés

The event loop has its own internal clock for computing timeouts. Which clock is used depends on the (platform-specific) event loop implementation; ideally it is a monotonic clock. This will generally be a different clock than time.time().

Note

Timeouts (relative delay or absolute when) should not exceed one day.

AbstractEventLoop.call_later(delay, callback, *args)

Arrange for the callback to be called after the given delay seconds (either an int or float).

An instance of asyncio.Handle is returned, which can be used to cancel the callback.

callback will be called exactly once per call to call_later(). If two callbacks are scheduled for exactly the same time, it is undefined which will be called first.

The optional positional args will be passed to the callback when it is called. If you want the callback to be called with some named arguments, use a closure or functools.partial().

Use functools.partial to pass keywords to the callback.

AbstractEventLoop.call_at(when, callback, *args)

Arrange for the callback to be called at the given absolute timestamp when (an int or float), using the same time reference as AbstractEventLoop.time().

This method’s behavior is the same as call_later().

An instance of asyncio.Handle is returned, which can be used to cancel the callback.

Use functools.partial to pass keywords to the callback.

AbstractEventLoop.time()

Return the current time, as a float value, according to the event loop’s internal clock.

Voir aussi

La fonction asyncio.sleep().

18.5.1.4. Futurs

AbstractEventLoop.create_future()

Create an asyncio.Future object attached to the loop.

This is a preferred way to create futures in asyncio, as event loop implementations can provide alternative implementations of the Future class (with better performance or instrumentation).

Nouveau dans la version 3.5.2.

18.5.1.5. Tâches

AbstractEventLoop.create_task(coro)

Schedule the execution of a coroutine object: wrap it in a future. Return a Task object.

Third-party event loops can use their own subclass of Task for interoperability. In this case, the result type is a subclass of Task.

This method was added in Python 3.4.2. Use the async() function to support also older Python versions.

Nouveau dans la version 3.4.2.

AbstractEventLoop.set_task_factory(factory)

Set a task factory that will be used by AbstractEventLoop.create_task().

If factory is None the default task factory will be set.

If factory is a callable, it should have a signature matching (loop, coro), where loop will be a reference to the active event loop, coro will be a coroutine object. The callable must return an asyncio.Future compatible object.

Nouveau dans la version 3.4.4.

AbstractEventLoop.get_task_factory()

Return a task factory, or None if the default one is in use.

Nouveau dans la version 3.4.4.

18.5.1.6. Créer des connections

coroutine AbstractEventLoop.create_connection(protocol_factory, host=None, port=None, *, ssl=None, family=0, proto=0, flags=0, sock=None, local_addr=None, server_hostname=None)

Create a streaming transport connection to a given Internet host and port: socket family AF_INET or AF_INET6 depending on host (or family if specified), socket type SOCK_STREAM. protocol_factory must be a callable returning a protocol instance.

This method is a coroutine which will try to establish the connection in the background. When successful, the coroutine returns a (transport, protocol) pair.

The chronological synopsis of the underlying operation is as follows:

The connection is established, and a transport is created to represent it.

protocol_factory is called without arguments and must return a protocol instance.

The protocol instance is tied to the transport, and its connection_made() method is called.

The coroutine returns successfully with the (transport, protocol) pair.

The created transport is an implementation-dependent bidirectional stream.

Note

protocol_factory can be any kind of callable, not necessarily a class. For example, if you want to use a pre-created protocol instance, you can pass lambda: my_protocol.

Options modifiant la création de la connexion :

ssl: if given and not false, a SSL/TLS transport is created (by default a plain TCP transport is created). If ssl is a ssl.SSLContext object, this context is used to create the transport; if ssl is True, a context with some unspecified default settings is used.

Voir aussi

SSL/TLS security considerations

server_hostname, is only for use together with ssl, and sets or overrides the hostname that the target server’s certificate will be matched against. By default the value of the host argument is used. If host is empty, there is no default and you must pass a value for server_hostname. If server_hostname is an empty string, hostname matching is disabled (which is a serious security risk, allowing for man-in-the-middle-attacks).

family, proto, flags are the optional address family, protocol and flags to be passed through to getaddrinfo() for host resolution. If given, these should all be integers from the corresponding socket module constants.

sock, if given, should be an existing, already connected socket.socket object to be used by the transport. If sock is given, none of host, port, family, proto, flags and local_addr should be specified.

local_addr, if given, is a (local_host, local_port) tuple used to bind the socket to locally. The local_host and local_port are looked up using getaddrinfo(), similarly to host and port.

Modifié dans la version 3.5: On Windows with ProactorEventLoop, SSL/TLS is now supported.

Voir aussi

The open_connection() function can be used to get a pair of (StreamReader, StreamWriter) instead of a protocol.

coroutine AbstractEventLoop.create_datagram_endpoint(protocol_factory, local_addr=None, remote_addr=None, *, family=0, proto=0, flags=0, reuse_address=None, reuse_port=None, allow_broadcast=None, sock=None)

Note

The parameter reuse_address is no longer supported, as using SO_REUSEADDR poses a significant security concern for UDP. Explicitly passing reuse_address=True will raise an exception.

When multiple processes with differing UIDs assign sockets to an indentical UDP socket address with SO_REUSEADDR, incoming packets can become randomly distributed among the sockets.

For supported platforms, reuse_port can be used as a replacement for similar functionality. With reuse_port, SO_REUSEPORT is used instead, which specifically prevents processes with differing UIDs from assigning sockets to the same socket address.

Create a datagram connection.

Create datagram connection: socket family AF_INET or AF_INET6 depending on host (or family if specified), socket type SOCK_DGRAM. protocol_factory must be a callable returning a protocol instance.

This method is a coroutine which will try to establish the connection in the background. When successful, the coroutine returns a (transport, protocol) pair.

Options modifiant la création de la connexion :

local_addr, if given, is a (local_host, local_port) tuple used to bind the socket to locally. The local_host and local_port are looked up using getaddrinfo().

remote_addr, if given, is a (remote_host, remote_port) tuple used to connect the socket to a remote address. The remote_host and remote_port are looked up using getaddrinfo().

family, proto, flags are the optional address family, protocol and flags to be passed through to getaddrinfo() for host resolution. If given, these should all be integers from the corresponding socket module constants.

reuse_port tells the kernel to allow this endpoint to be bound to the same port as other existing endpoints are bound to, so long as they all set this flag when being created. This option is not supported on Windows and some UNIX’s. If the SO_REUSEPORT constant is not defined then this capability is unsupported.

allow_broadcast tells the kernel to allow this endpoint to send messages to the broadcast address.

sock can optionally be specified in order to use a preexisting, already connected, socket.socket object to be used by the transport. If specified, local_addr and remote_addr should be omitted (must be None).

On Windows with ProactorEventLoop, this method is not supported.

See UDP echo client protocol and UDP echo server protocol examples.

Modifié dans la version 3.4.4: The family, proto, flags, reuse_address, reuse_port, *allow_broadcast, and sock parameters were added.

Modifié dans la version 3.6.10: The reuse_address parameter is no longer supporter due to security concerns

coroutine AbstractEventLoop.create_unix_connection(protocol_factory, path, *, ssl=None, sock=None, server_hostname=None)

Create UNIX connection: socket family AF_UNIX, socket type SOCK_STREAM. The AF_UNIX socket family is used to communicate between processes on the same machine efficiently.

This method is a coroutine which will try to establish the connection in the background. When successful, the coroutine returns a (transport, protocol) pair.

path is the name of a UNIX domain socket, and is required unless a sock parameter is specified. Abstract UNIX sockets, str, and bytes paths are supported.

See the AbstractEventLoop.create_connection() method for parameters.

Disponible sur : UNIX.

18.5.1.7. Attendre des connections

coroutine AbstractEventLoop.create_server(protocol_factory, host=None, port=None, *, family=socket.AF_UNSPEC, flags=socket.AI_PASSIVE, sock=None, backlog=100, ssl=None, reuse_address=None, reuse_port=None)

Create a TCP server (socket type SOCK_STREAM) bound to host and port.

Return a Server object, its sockets attribute contains created sockets. Use the Server.close() method to stop the server: close listening sockets.

Paramètres :

The host parameter can be a string, in that case the TCP server is bound to host and port. The host parameter can also be a sequence of strings and in that case the TCP server is bound to all hosts of the sequence. If host is an empty string or None, all interfaces are assumed and a list of multiple sockets will be returned (most likely one for IPv4 and another one for IPv6).

family can be set to either socket.AF_INET or AF_INET6 to force the socket to use IPv4 or IPv6. If not set it will be determined from host (defaults to socket.AF_UNSPEC).

flags est un masque de bits pour getaddrinfo().

sock can optionally be specified in order to use a preexisting socket object. If specified, host and port should be omitted (must be None).

backlog is the maximum number of queued connections passed to listen() (defaults to 100).

ssl can be set to an SSLContext to enable SSL over the accepted connections.

reuse_address tells the kernel to reuse a local socket in TIME_WAIT state, without waiting for its natural timeout to expire. If not specified will automatically be set to True on UNIX.

reuse_port tells the kernel to allow this endpoint to be bound to the same port as other existing endpoints are bound to, so long as they all set this flag when being created. This option is not supported on Windows.

Cette méthode est une coroutine.

Modifié dans la version 3.5: On Windows with ProactorEventLoop, SSL/TLS is now supported.

Voir aussi

The function start_server() creates a (StreamReader, StreamWriter) pair and calls back a function with this pair.

Modifié dans la version 3.5.1: The host parameter can now be a sequence of strings.

coroutine AbstractEventLoop.create_unix_server(protocol_factory, path=None, *, sock=None, backlog=100, ssl=None)

Similar to AbstractEventLoop.create_server(), but specific to the socket family AF_UNIX.

Cette méthode est une coroutine.

Disponible sur : UNIX.

coroutine BaseEventLoop.connect_accepted_socket(protocol_factory, sock, *, ssl=None)

Handle an accepted connection.

This is used by servers that accept connections outside of asyncio but that use asyncio to handle them.

Paramètres :

sock is a preexisting socket object returned from an accept call.

ssl can be set to an SSLContext to enable SSL over the accepted connections.

This method is a coroutine. When completed, the coroutine returns a (transport, protocol) pair.

Nouveau dans la version 3.5.3.

18.5.1.8. Surveiller des descripteurs de fichiers

On Windows with SelectorEventLoop, only socket handles are supported (ex: pipe file descriptors are not supported).

On Windows with ProactorEventLoop, these methods are not supported.

AbstractEventLoop.add_reader(fd, callback, *args)

Start watching the file descriptor for read availability and then call the callback with specified arguments.

Use functools.partial to pass keywords to the callback.

AbstractEventLoop.remove_reader(fd)

Stop watching the file descriptor for read availability.

AbstractEventLoop.add_writer(fd, callback, *args)

Start watching the file descriptor for write availability and then call the callback with specified arguments.

Use functools.partial to pass keywords to the callback.

AbstractEventLoop.remove_writer(fd)

Stop watching the file descriptor for write availability.

The watch a file descriptor for read events example uses the low-level AbstractEventLoop.add_reader() method to register the file descriptor of a socket.

18.5.1.9. Opérations bas niveau sur les socket

coroutine AbstractEventLoop.sock_recv(sock, nbytes)

Receive data from the socket. Modeled after blocking socket.socket.recv() method.

The return value is a bytes object representing the data received. The maximum amount of data to be received at once is specified by nbytes.

With SelectorEventLoop event loop, the socket sock must be non-blocking.

Cette méthode est une coroutine.

coroutine AbstractEventLoop.sock_sendall(sock, data)

Send data to the socket. Modeled after blocking socket.socket.sendall() method.

The socket must be connected to a remote socket. This method continues to send data from data until either all data has been sent or an error occurs. None is returned on success. On error, an exception is raised, and there is no way to determine how much data, if any, was successfully processed by the receiving end of the connection.

With SelectorEventLoop event loop, the socket sock must be non-blocking.

Cette méthode est une coroutine.

coroutine AbstractEventLoop.sock_connect(sock, address)

Connect to a remote socket at address. Modeled after blocking socket.socket.connect() method.

With SelectorEventLoop event loop, the socket sock must be non-blocking.

Cette méthode est une coroutine.

Modifié dans la version 3.5.2: address no longer needs to be resolved. sock_connect will try to check if the address is already resolved by calling socket.inet_pton(). If not, AbstractEventLoop.getaddrinfo() will be used to resolve the address.

Voir aussi

AbstractEventLoop.create_connection() and asyncio.open_connection().

coroutine AbstractEventLoop.sock_accept(sock)

Accept a connection. Modeled after blocking socket.socket.accept().

The socket must be bound to an address and listening for connections. The return value is a pair (conn, address) where conn is a new socket object usable to send and receive data on the connection, and address is the address bound to the socket on the other end of the connection.

La socket sock ne soit pas être bloquante.

Cette méthode est une coroutine.

Voir aussi

AbstractEventLoop.create_server() and start_server().

18.5.1.10. Résout le nom d’hôte

coroutine AbstractEventLoop.getaddrinfo(host, port, *, family=0, type=0, proto=0, flags=0)

This method is a coroutine, similar to socket.getaddrinfo() function but non-blocking.

coroutine AbstractEventLoop.getnameinfo(sockaddr, flags=0)

This method is a coroutine, similar to socket.getnameinfo() function but non-blocking.

18.5.1.11. Connect pipes

On Windows with SelectorEventLoop, these methods are not supported. Use ProactorEventLoop to support pipes on Windows.

coroutine AbstractEventLoop.connect_read_pipe(protocol_factory, pipe)

Register read pipe in eventloop.

protocol_factory should instantiate object with Protocol interface. pipe is a file-like object. Return pair (transport, protocol), where transport supports the ReadTransport interface.

With SelectorEventLoop event loop, the pipe is set to non-blocking mode.

Cette méthode est une coroutine.

coroutine AbstractEventLoop.connect_write_pipe(protocol_factory, pipe)

Register write pipe in eventloop.

protocol_factory should instantiate object with BaseProtocol interface. pipe is file-like object. Return pair (transport, protocol), where transport supports WriteTransport interface.

With SelectorEventLoop event loop, the pipe is set to non-blocking mode.

Cette méthode est une coroutine.

Voir aussi

The AbstractEventLoop.subprocess_exec() and AbstractEventLoop.subprocess_shell() methods.

18.5.1.12. Signaux UNIX

Disponibilité : UNIX seulement.

AbstractEventLoop.add_signal_handler(signum, callback, *args)

Ajouter un gestionnaire (handler) pour un signal.

Raise ValueError if the signal number is invalid or uncatchable. Raise RuntimeError if there is a problem setting up the handler.

Use functools.partial to pass keywords to the callback.

AbstractEventLoop.remove_signal_handler(sig)

Supprimer un handler pour un signal.

Return True if a signal handler was removed, False if not.

Voir aussi

Le module signal.

18.5.1.13. Exécuteur

Call a function in an Executor (pool of threads or pool of processes). By default, an event loop uses a thread pool executor (ThreadPoolExecutor).

coroutine AbstractEventLoop.run_in_executor(executor, func, *args)

Arrange for a func to be called in the specified executor.

The executor argument should be an Executor instance. The default executor is used if executor is None.

Use functools.partial to pass keywords to the *func*.

Cette méthode est une coroutine.

Modifié dans la version 3.5.3: BaseEventLoop.run_in_executor() no longer configures the max_workers of the thread pool executor it creates, instead leaving it up to the thread pool executor (ThreadPoolExecutor) to set the default.

AbstractEventLoop.set_default_executor(executor)

Set the default executor used by run_in_executor().

18.5.1.14. API de gestion d’erreur

Allows customizing how exceptions are handled in the event loop.

AbstractEventLoop.set_exception_handler(handler)

Set handler as the new event loop exception handler.

If handler is None, the default exception handler will be set.

If handler is a callable object, it should have a matching signature to (loop, context), where loop will be a reference to the active event loop, context will be a dict object (see call_exception_handler() documentation for details about context).

AbstractEventLoop.get_exception_handler()

Return the exception handler, or None if the default one is in use.

Nouveau dans la version 3.5.2.

AbstractEventLoop.default_exception_handler(context)

Gestionnaire d’exception par défaut.

This is called when an exception occurs and no exception handler is set, and can be called by a custom exception handler that wants to defer to the default behavior.

context parameter has the same meaning as in call_exception_handler().

AbstractEventLoop.call_exception_handler(context)

Appelle le gestionnaire d’exception de la boucle d’évènements actuelle.

context is a dict object containing the following keys (new keys may be introduced later):

message : Message d’erreur ;

exception (optionnel): Un objet exception ;

“future” (optional): asyncio.Future instance;

“handle” (optional): asyncio.Handle instance;

“protocol” (optional): Protocol instance;

“transport” (optional): Transport instance;

“socket” (optional): socket.socket instance.

Note

Note: this method should not be overloaded in subclassed event loops. For any custom exception handling, use set_exception_handler() method.

18.5.1.15. Mode débogage

AbstractEventLoop.get_debug()

Get the debug mode (bool) of the event loop.

The default value is True if the environment variable PYTHONASYNCIODEBUG is set to a non-empty string, False otherwise.

Nouveau dans la version 3.4.2.

AbstractEventLoop.set_debug(enabled: bool)

Active le mode débogage pour la boucle d’évènements.

Nouveau dans la version 3.4.2.

Voir aussi

The debug mode of asyncio.

18.5.1.16. Serveur

class asyncio.Server

Serveur écoutant sur des sockets.

Object created by the AbstractEventLoop.create_server() method and the start_server() function. Don’t instantiate the class directly.

close()

Stop serving: close listening sockets and set the sockets attribute to None.

The sockets that represent existing incoming client connections are left open.

The server is closed asynchronously, use the wait_closed() coroutine to wait until the server is closed.

coroutine wait_closed()

Attends que la méthode close() se termine.

Cette méthode est une coroutine.

sockets

List of socket.socket objects the server is listening to, or None if the server is closed.

18.5.1.17. Handle

class asyncio.Handle

A callback wrapper object returned by AbstractEventLoop.call_soon(), AbstractEventLoop.call_soon_threadsafe(), AbstractEventLoop.call_later(), and AbstractEventLoop.call_at().

cancel()

Cancel the call. If the callback is already canceled or executed, this method has no effect.

18.5.1.18. Exemples de boucles d’évènements

18.5.1.18.1. « Hello World » avec call_soon()

Example using the AbstractEventLoop.call_soon() method to schedule a callback. The callback displays "Hello World" and then stops the event loop:

import asyncio

def hello_world(loop):
    print('Hello World')
    loop.stop()

loop = asyncio.get_event_loop()

# Schedule a call to hello_world()
loop.call_soon(hello_world, loop)

# Blocking call interrupted by loop.stop()
loop.run_forever()
loop.close()

Voir aussi

The Hello World coroutine example uses a coroutine.

18.5.1.18.2. Afficher la date actuelle avec call_later()

Example of callback displaying the current date every second. The callback uses the AbstractEventLoop.call_later() method to reschedule itself during 5 seconds, and then stops the event loop:

import asyncio
import datetime

def display_date(end_time, loop):
    print(datetime.datetime.now())
    if (loop.time() + 1.0) < end_time:
        loop.call_later(1, display_date, end_time, loop)
    else:
        loop.stop()

loop = asyncio.get_event_loop()

# Schedule the first call to display_date()
end_time = loop.time() + 5.0
loop.call_soon(display_date, end_time, loop)

# Blocking call interrupted by loop.stop()
loop.run_forever()
loop.close()

Voir aussi

The coroutine displaying the current date example uses a coroutine.

18.5.1.18.3. Watch a file descriptor for read events

Wait until a file descriptor received some data using the AbstractEventLoop.add_reader() method and then close the event loop:

import asyncio
try:
    from socket import socketpair
except ImportError:
    from asyncio.windows_utils import socketpair

# Create a pair of connected file descriptors
rsock, wsock = socketpair()
loop = asyncio.get_event_loop()

def reader():
    data = rsock.recv(100)
    print("Received:", data.decode())
    # We are done: unregister the file descriptor
    loop.remove_reader(rsock)
    # Stop the event loop
    loop.stop()

# Register the file descriptor for read event
loop.add_reader(rsock, reader)

# Simulate the reception of data from the network
loop.call_soon(wsock.send, 'abc'.encode())

# Run the event loop
loop.run_forever()

# We are done, close sockets and the event loop
rsock.close()
wsock.close()
loop.close()

Voir aussi

The register an open socket to wait for data using a protocol example uses a low-level protocol created by the AbstractEventLoop.create_connection() method.

The register an open socket to wait for data using streams example uses high-level streams created by the open_connection() function in a coroutine.

18.5.1.18.4. Définit les gestionnaires de signaux pour SIGINT et SIGTERM

Register handlers for signals SIGINT and SIGTERM using the AbstractEventLoop.add_signal_handler() method:

import asyncio
import functools
import os
import signal

def ask_exit(signame):
    print("got signal %s: exit" % signame)
    loop.stop()

loop = asyncio.get_event_loop()
for signame in ('SIGINT', 'SIGTERM'):
    loop.add_signal_handler(getattr(signal, signame),
                            functools.partial(ask_exit, signame))

print("Event loop running forever, press Ctrl+C to interrupt.")
print("pid %s: send SIGINT or SIGTERM to exit." % os.getpid())
try:
    loop.run_forever()
finally:
    loop.close()

Cet exemple fonctionne seulement sur Unix.

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18.5.2. Boucles d’évènements

Source code: Lib/asyncio/events.py [https://github.com/python/cpython/tree/3.6/Lib/asyncio/events.py]

18.5.2.1. Fonctions des boucles d’évènements

The following functions are convenient shortcuts to accessing the methods of the global policy. Note that this provides access to the default policy, unless an alternative policy was set by calling set_event_loop_policy() earlier in the execution of the process.

asyncio.get_event_loop()

Equivalent to calling get_event_loop_policy().get_event_loop().

asyncio.set_event_loop(loop)

Equivalent to calling get_event_loop_policy().set_event_loop(loop).

asyncio.new_event_loop()

Equivalent to calling get_event_loop_policy().new_event_loop().

18.5.2.2. Boucles d’évènements disponibles

asyncio currently provides two implementations of event loops: SelectorEventLoop and ProactorEventLoop.

class asyncio.SelectorEventLoop

Event loop based on the selectors module. Subclass of AbstractEventLoop.

Use the most efficient selector available on the platform.

On Windows, only sockets are supported (ex: pipes are not supported): see the MSDN documentation of select [https://msdn.microsoft.com/en-us/library/windows/desktop/ms740141%28v=vs.85%29.aspx].

class asyncio.ProactorEventLoop

Proactor event loop for Windows using « I/O Completion Ports » aka IOCP. Subclass of AbstractEventLoop.

Disponibilité : Windows.

Voir aussi

MSDN documentation on I/O Completion Ports [https://msdn.microsoft.com/en-us/library/windows/desktop/aa365198%28v=vs.85%29.aspx].

Example to use a ProactorEventLoop on Windows:

import asyncio, sys

if sys.platform == 'win32':
    loop = asyncio.ProactorEventLoop()
    asyncio.set_event_loop(loop)

18.5.2.3. Support des plateformes

The asyncio module has been designed to be portable, but each platform still has subtle differences and may not support all asyncio features.

18.5.2.3.1. Windows

Common limits of Windows event loops:

create_unix_connection() and create_unix_server() are not supported: the socket family socket.AF_UNIX is specific to UNIX

add_signal_handler() and remove_signal_handler() are not supported

EventLoopPolicy.set_child_watcher() is not supported. ProactorEventLoop supports subprocesses. It has only one implementation to watch child processes, there is no need to configure it.

Limites spécifiques à SelectorEventLoop :

SelectSelector is used which only supports sockets and is limited to 512 sockets.

add_reader() and add_writer() only accept file descriptors of sockets

Pipes are not supported (ex: connect_read_pipe(), connect_write_pipe())

Subprocesses are not supported (ex: subprocess_exec(), subprocess_shell())

Limites spécifiques à ProactorEventLoop :

create_datagram_endpoint() (UDP) is not supported

add_reader() and add_writer() are not supported

The resolution of the monotonic clock on Windows is usually around 15.6 msec. The best resolution is 0.5 msec. The resolution depends on the hardware (availability of HPET [https://en.wikipedia.org/wiki/High_Precision_Event_Timer]) and on the Windows configuration. See asyncio delayed calls.

Modifié dans la version 3.5: La classe ProactorEventLoop gère maintenant le SSL.

18.5.2.3.2. Mac OS X

Character devices like PTY are only well supported since Mavericks (Mac OS 10.9). They are not supported at all on Mac OS 10.5 and older.

On Mac OS 10.6, 10.7 and 10.8, the default event loop is SelectorEventLoop which uses selectors.KqueueSelector. selectors.KqueueSelector does not support character devices on these versions. The SelectorEventLoop can be used with SelectSelector or PollSelector to support character devices on these versions of Mac OS X. Example:

import asyncio
import selectors

selector = selectors.SelectSelector()
loop = asyncio.SelectorEventLoop(selector)
asyncio.set_event_loop(loop)

18.5.2.4. Event loop policies and the default policy

Event loop management is abstracted with a policy pattern, to provide maximal flexibility for custom platforms and frameworks. Throughout the execution of a process, a single global policy object manages the event loops available to the process based on the calling context. A policy is an object implementing the AbstractEventLoopPolicy interface.

For most users of asyncio, policies never have to be dealt with explicitly, since the default global policy is sufficient (see below).

The module-level functions get_event_loop() and set_event_loop() provide convenient access to event loops managed by the default policy.

18.5.2.5. Event loop policy interface

An event loop policy must implement the following interface:

class asyncio.AbstractEventLoopPolicy

Event loop policy.

get_event_loop()

Récupère la boucle d’évènements pour le contexte actuel.

Returns an event loop object implementing the AbstractEventLoop interface. In case called from coroutine, it returns the currently running event loop.

Raises an exception in case no event loop has been set for the current context and the current policy does not specify to create one. It must never return None.

Modifié dans la version 3.6.

set_event_loop(loop)

Définit la boucle d’événements du contexte actuel sur loop.

new_event_loop()

Create and return a new event loop object according to this policy’s rules.

If there’s need to set this loop as the event loop for the current context, set_event_loop() must be called explicitly.

The default policy defines context as the current thread, and manages an event loop per thread that interacts with asyncio. If the current thread doesn’t already have an event loop associated with it, the default policy’s get_event_loop() method creates one when called from the main thread, but raises RuntimeError otherwise.

18.5.2.6. Access to the global loop policy

asyncio.get_event_loop_policy()

Get the current event loop policy.

asyncio.set_event_loop_policy(policy)

Set the current event loop policy. If policy is None, the default policy is restored.

18.5.2.7. Customizing the event loop policy

To implement a new event loop policy, it is recommended you subclass the concrete default event loop policy DefaultEventLoopPolicy and override the methods for which you want to change behavior, for example:

class MyEventLoopPolicy(asyncio.DefaultEventLoopPolicy):

    def get_event_loop(self):
        """Get the event loop.

        This may be None or an instance of EventLoop.
        """
        loop = super().get_event_loop()
        # Do something with loop ...
        return loop

asyncio.set_event_loop_policy(MyEventLoopPolicy())

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18.5.3. Tâches et coroutines

Source code: Lib/asyncio/tasks.py [https://github.com/python/cpython/tree/3.6/Lib/asyncio/tasks.py]

Source code: Lib/asyncio/coroutines.py [https://github.com/python/cpython/tree/3.6/Lib/asyncio/coroutines.py]

18.5.3.1. Coroutines

Coroutines used with asyncio may be implemented using the async def statement, or by using generators. The async def type of coroutine was added in Python 3.5, and is recommended if there is no need to support older Python versions.

Generator-based coroutines should be decorated with @asyncio.coroutine, although this is not strictly enforced. The decorator enables compatibility with async def coroutines, and also serves as documentation. Generator-based coroutines use the yield from syntax introduced in PEP 380 [https://www.python.org/dev/peps/pep-0380], instead of the original yield syntax.

The word « coroutine », like the word « generator », is used for two different (though related) concepts:

The function that defines a coroutine (a function definition using async def or decorated with @asyncio.coroutine). If disambiguation is needed we will call this a coroutine function (iscoroutinefunction() returns True).

The object obtained by calling a coroutine function. This object represents a computation or an I/O operation (usually a combination) that will complete eventually. If disambiguation is needed we will call it a coroutine object (iscoroutine() returns True).

Les choses que les coroutines peuvent faire :

result = await future or result = yield from future – suspends the coroutine until the future is done, then returns the future’s result, or raises an exception, which will be propagated. (If the future is cancelled, it will raise a CancelledError exception.) Note that tasks are futures, and everything said about futures also applies to tasks.

result = await coroutine or result = yield from coroutine – wait for another coroutine to produce a result (or raise an exception, which will be propagated). The coroutine expression must be a call to another coroutine.

return expression – produce a result to the coroutine that is waiting for this one using await or yield from.

raise exception – raise an exception in the coroutine that is waiting for this one using await or yield from.

Calling a coroutine does not start its code running – the coroutine object returned by the call doesn’t do anything until you schedule its execution. There are two basic ways to start it running: call await coroutine or yield from coroutine from another coroutine (assuming the other coroutine is already running!), or schedule its execution using the ensure_future() function or the AbstractEventLoop.create_task() method.

Coroutines (and tasks) can only run when the event loop is running.

@asyncio.coroutine

Decorator to mark generator-based coroutines. This enables the generator use yield from to call async def coroutines, and also enables the generator to be called by async def coroutines, for instance using an await expression.

There is no need to decorate async def coroutines themselves.

If the generator is not yielded from before it is destroyed, an error message is logged. See Detect coroutines never scheduled.

Note

In this documentation, some methods are documented as coroutines, even if they are plain Python functions returning a Future. This is intentional to have a freedom of tweaking the implementation of these functions in the future. If such a function is needed to be used in a callback-style code, wrap its result with ensure_future().

18.5.3.1.1. Exemple : Coroutine « Hello World »

Example of coroutine displaying "Hello World":

import asyncio

async def hello_world():
    print("Hello World!")

loop = asyncio.get_event_loop()
# Blocking call which returns when the hello_world() coroutine is done
loop.run_until_complete(hello_world())
loop.close()

Voir aussi

The Hello World with call_soon() example uses the AbstractEventLoop.call_soon() method to schedule a callback.

18.5.3.1.2. Exemple : Coroutine affichant la date actuelle

Example of coroutine displaying the current date every second during 5 seconds using the sleep() function:

import asyncio
import datetime

async def display_date(loop):
    end_time = loop.time() + 5.0
    while True:
        print(datetime.datetime.now())
        if (loop.time() + 1.0) >= end_time:
            break
        await asyncio.sleep(1)

loop = asyncio.get_event_loop()
# Blocking call which returns when the display_date() coroutine is done
loop.run_until_complete(display_date(loop))
loop.close()

Voir aussi

The display the current date with call_later() example uses a callback with the AbstractEventLoop.call_later() method.

18.5.3.1.3. Exemple : Chaîner des coroutines

Example chaining coroutines:

import asyncio

async def compute(x, y):
    print("Compute %s + %s ..." % (x, y))
    await asyncio.sleep(1.0)
    return x + y

async def print_sum(x, y):
    result = await compute(x, y)
    print("%s + %s = %s" % (x, y, result))

loop = asyncio.get_event_loop()
loop.run_until_complete(print_sum(1, 2))
loop.close()

compute() is chained to print_sum(): print_sum() coroutine waits until compute() is completed before returning its result.

Sequence diagram of the example:

The « Task » is created by the AbstractEventLoop.run_until_complete() method when it gets a coroutine object instead of a task.

The diagram shows the control flow, it does not describe exactly how things work internally. For example, the sleep coroutine creates an internal future which uses AbstractEventLoop.call_later() to wake up the task in 1 second.

18.5.3.2. InvalidStateError

exception asyncio.InvalidStateError

L’opération n’est pas autorisée dans cet état.

18.5.3.3. TimeoutError

exception asyncio.TimeoutError

L’opération a dépassé le délai donné.

Note

This exception is different from the builtin TimeoutError exception!

18.5.3.4. Future

class asyncio.Future(*, loop=None)

This class is almost compatible with concurrent.futures.Future.

Différences :

result() and exception() do not take a timeout argument and raise an exception when the future isn’t done yet.

Callbacks registered with add_done_callback() are always called via the event loop’s call_soon().

This class is not compatible with the wait() and as_completed() functions in the concurrent.futures package.

This class is not thread safe.

cancel()

Cancel the future and schedule callbacks.

If the future is already done or cancelled, return False. Otherwise, change the future’s state to cancelled, schedule the callbacks and return True.

cancelled()

Return True if the future was cancelled.

done()

Return True if the future is done.

Done means either that a result / exception are available, or that the future was cancelled.

result()

Return the result this future represents.

If the future has been cancelled, raises CancelledError. If the future’s result isn’t yet available, raises InvalidStateError. If the future is done and has an exception set, this exception is raised.

exception()

Return the exception that was set on this future.

The exception (or None if no exception was set) is returned only if the future is done. If the future has been cancelled, raises CancelledError. If the future isn’t done yet, raises InvalidStateError.

add_done_callback(fn)

Add a callback to be run when the future becomes done.

The callback is called with a single argument - the future object. If the future is already done when this is called, the callback is scheduled with call_soon().

Use functools.partial to pass parameters to the callback. For example, fut.add_done_callback(functools.partial(print, "Future:", flush=True)) will call print("Future:", fut, flush=True).

remove_done_callback(fn)

Remove all instances of a callback from the « call when done » list.

Donne le nombre de fonctions de rappel supprimées.

set_result(result)

Marque le futur comme terminé et définit son résultat.

If the future is already done when this method is called, raises InvalidStateError.

set_exception(exception)

Marque le futur comme terminé et définit une exception.

If the future is already done when this method is called, raises InvalidStateError.

18.5.3.4.1. Exemple : Futur avec run_until_complete()

Example combining a Future and a coroutine function:

import asyncio

async def slow_operation(future):
    await asyncio.sleep(1)
    future.set_result('Future is done!')

loop = asyncio.get_event_loop()
future = asyncio.Future()
asyncio.ensure_future(slow_operation(future))
loop.run_until_complete(future)
print(future.result())
loop.close()

The coroutine function is responsible for the computation (which takes 1 second) and it stores the result into the future. The run_until_complete() method waits for the completion of the future.

Note

The run_until_complete() method uses internally the add_done_callback() method to be notified when the future is done.

18.5.3.4.2. Exemple : Futur avec run_forever()

The previous example can be written differently using the Future.add_done_callback() method to describe explicitly the control flow:

import asyncio

async def slow_operation(future):
    await asyncio.sleep(1)
    future.set_result('Future is done!')

def got_result(future):
    print(future.result())
    loop.stop()

loop = asyncio.get_event_loop()
future = asyncio.Future()
asyncio.ensure_future(slow_operation(future))
future.add_done_callback(got_result)
try:
    loop.run_forever()
finally:
    loop.close()

In this example, the future is used to link slow_operation() to got_result(): when slow_operation() is done, got_result() is called with the result.

18.5.3.5. Task

class asyncio.Task(coro, *, loop=None)

Schedule the execution of a coroutine: wrap it in a future. A task is a subclass of Future.

A task is responsible for executing a coroutine object in an event loop. If the wrapped coroutine yields from a future, the task suspends the execution of the wrapped coroutine and waits for the completion of the future. When the future is done, the execution of the wrapped coroutine restarts with the result or the exception of the future.

Event loops use cooperative scheduling: an event loop only runs one task at a time. Other tasks may run in parallel if other event loops are running in different threads. While a task waits for the completion of a future, the event loop executes a new task.

The cancellation of a task is different from the cancelation of a future. Calling cancel() will throw a CancelledError to the wrapped coroutine. cancelled() only returns True if the wrapped coroutine did not catch the CancelledError exception, or raised a CancelledError exception.

If a pending task is destroyed, the execution of its wrapped coroutine did not complete. It is probably a bug and a warning is logged: see Pending task destroyed.

Don’t directly create Task instances: use the ensure_future() function or the AbstractEventLoop.create_task() method.

This class is not thread safe.

classmethod all_tasks(loop=None)

Renvoie l’ensemble des tâches d’une boucle d’évènements.

By default all tasks for the current event loop are returned.

classmethod current_task(loop=None)

Return the currently running task in an event loop or None.

By default the current task for the current event loop is returned.

None is returned when called not in the context of a Task.

cancel()

Demande à ce qu’une tâche s’annule elle même.

This arranges for a CancelledError to be thrown into the wrapped coroutine on the next cycle through the event loop. The coroutine then has a chance to clean up or even deny the request using try/except/finally.

Unlike Future.cancel(), this does not guarantee that the task will be cancelled: the exception might be caught and acted upon, delaying cancellation of the task or preventing cancellation completely. The task may also return a value or raise a different exception.

Immediately after this method is called, cancelled() will not return True (unless the task was already cancelled). A task will be marked as cancelled when the wrapped coroutine terminates with a CancelledError exception (even if cancel() was not called).

get_stack(*, limit=None)

Return the list of stack frames for this task’s coroutine.

If the coroutine is not done, this returns the stack where it is suspended. If the coroutine has completed successfully or was cancelled, this returns an empty list. If the coroutine was terminated by an exception, this returns the list of traceback frames.

La pile est toujours affichée de l’appelant à l’appelé.

The optional limit gives the maximum number of frames to return; by default all available frames are returned. Its meaning differs depending on whether a stack or a traceback is returned: the newest frames of a stack are returned, but the oldest frames of a traceback are returned. (This matches the behavior of the traceback module.)

For reasons beyond our control, only one stack frame is returned for a suspended coroutine.

print_stack(*, limit=None, file=None)

Print the stack or traceback for this task’s coroutine.

This produces output similar to that of the traceback module, for the frames retrieved by get_stack(). The limit argument is passed to get_stack(). The file argument is an I/O stream to which the output is written; by default output is written to sys.stderr.

18.5.3.5.1. Exemple : Exécution parallèle de tâches

Exemple d’exécution de trois tâches (A, B, C) en parallèle :

import asyncio

async def factorial(name, number):
    f = 1
    for i in range(2, number+1):
        print("Task %s: Compute factorial(%s)..." % (name, i))
        await asyncio.sleep(1)
        f *= i
    print("Task %s: factorial(%s) = %s" % (name, number, f))

loop = asyncio.get_event_loop()
loop.run_until_complete(asyncio.gather(
    factorial("A", 2),
    factorial("B", 3),
    factorial("C", 4),
))
loop.close()

Sortie :

Task A: Compute factorial(2)...
Task B: Compute factorial(2)...
Task C: Compute factorial(2)...
Task A: factorial(2) = 2
Task B: Compute factorial(3)...
Task C: Compute factorial(3)...
Task B: factorial(3) = 6
Task C: Compute factorial(4)...
Task C: factorial(4) = 24

A task is automatically scheduled for execution when it is created. The event loop stops when all tasks are done.

18.5.3.6. Task functions

Note

In the functions below, the optional loop argument allows explicitly setting the event loop object used by the underlying task or coroutine. If it’s not provided, the default event loop is used.

asyncio.as_completed(fs, *, loop=None, timeout=None)

Return an iterator whose values, when waited for, are Future instances.

Lève une exception asyncio.TimeoutError si le délai d’attente est dépassé avant que tous les futurs ne soient achevés.

Exemple :

for f in as_completed(fs):
    result = yield from f  # The 'yield from' may raise
    # Use result

Note

The futures f are not necessarily members of fs.

asyncio.ensure_future(coro_or_future, *, loop=None)

Schedule the execution of a coroutine object: wrap it in a future. Return a Task object.

If the argument is a Future, it is returned directly.

Nouveau dans la version 3.4.4.

Modifié dans la version 3.5.1: La fonction accepte n’importe quel objet awaitable.

Voir aussi

The AbstractEventLoop.create_task() method.

asyncio.async(coro_or_future, *, loop=None)

Un alias obsolète de ensure_future().

Obsolète depuis la version 3.4.4.

asyncio.wrap_future(future, *, loop=None)

Wrap a concurrent.futures.Future object in a Future object.

asyncio.gather(*coros_or_futures, loop=None, return_exceptions=False)

Return a future aggregating results from the given coroutine objects or futures.

All futures must share the same event loop. If all the tasks are done successfully, the returned future’s result is the list of results (in the order of the original sequence, not necessarily the order of results arrival). If return_exceptions is true, exceptions in the tasks are treated the same as successful results, and gathered in the result list; otherwise, the first raised exception will be immediately propagated to the returned future.

Cancellation: if the outer Future is cancelled, all children (that have not completed yet) are also cancelled. If any child is cancelled, this is treated as if it raised CancelledError – the outer Future is not cancelled in this case. (This is to prevent the cancellation of one child to cause other children to be cancelled.)

Modifié dans la version 3.6.6: Si gather est lui-même annulé, l’annulation est propagée indépendamment de return_exceptions.

asyncio.iscoroutine(obj)

Return True if obj is a coroutine object, which may be based on a generator or an async def coroutine.

asyncio.iscoroutinefunction(func)

Return True if func is determined to be a coroutine function, which may be a decorated generator function or an async def function.

asyncio.run_coroutine_threadsafe(coro, loop)

Submit a coroutine object to a given event loop.

Return a concurrent.futures.Future to access the result.

This function is meant to be called from a different thread than the one where the event loop is running. Usage:

# Create a coroutine
coro = asyncio.sleep(1, result=3)
# Submit the coroutine to a given loop
future = asyncio.run_coroutine_threadsafe(coro, loop)
# Wait for the result with an optional timeout argument
assert future.result(timeout) == 3

If an exception is raised in the coroutine, the returned future will be notified. It can also be used to cancel the task in the event loop:

try:
    result = future.result(timeout)
except asyncio.TimeoutError:
    print('The coroutine took too long, cancelling the task...')
    future.cancel()
except Exception as exc:
    print('The coroutine raised an exception: {!r}'.format(exc))
else:
    print('The coroutine returned: {!r}'.format(result))

Voir la section exécution concurrente et multi-fils d’exécution de la documentation.

Note

Unlike other functions from the module, run_coroutine_threadsafe() requires the loop argument to be passed explicitly.

Nouveau dans la version 3.5.1.

coroutine asyncio.sleep(delay, result=None, *, loop=None)

Create a coroutine that completes after a given time (in seconds). If result is provided, it is produced to the caller when the coroutine completes.

The resolution of the sleep depends on the granularity of the event loop.

Cette fonction est une coroutine.

coroutine asyncio.shield(arg, *, loop=None)

Attends un future, en le protégeant des annulations.

L’instruction :

res = yield from shield(something())

est exactement équivalente à l’instruction :

res = yield from something()

except that if the coroutine containing it is cancelled, the task running in something() is not cancelled. From the point of view of something(), the cancellation did not happen. But its caller is still cancelled, so the yield-from expression still raises CancelledError. Note: If something() is cancelled by other means this will still cancel shield().

If you want to completely ignore cancellation (not recommended) you can combine shield() with a try/except clause, as follows:

try:
    res = yield from shield(something())
except CancelledError:
    res = None

coroutine asyncio.wait(futures, *, loop=None, timeout=None, return_when=ALL_COMPLETED)

Wait for the Futures and coroutine objects given by the sequence futures to complete. Coroutines will be wrapped in Tasks. Returns two sets of Future: (done, pending).

The sequence futures must not be empty.

timeout can be used to control the maximum number of seconds to wait before returning. timeout can be an int or float. If timeout is not specified or None, there is no limit to the wait time.

return_when indicates when this function should return. It must be one of the following constants of the concurrent.futures module:

Constante

Description

FIRST_COMPLETED

La fonction se termine lorsque n’importe quel futur se termine ou est annulé.

FIRST_EXCEPTION

La fonction se termine lorsque n’importe quel futur se termine en levant une exception. Si aucun futur ne lève d’exception, équivaut à ALL_COMPLETED.

ALL_COMPLETED

La fonction se termine lorsque les futurs sont tous finis ou annulés.

Cette fonction est une coroutine.

Utilisation :

done, pending = yield from asyncio.wait(fs)

Note

This does not raise asyncio.TimeoutError! Futures that aren’t done when the timeout occurs are returned in the second set.

coroutine asyncio.wait_for(fut, timeout, *, loop=None)

Wait for the single Future or coroutine object to complete with timeout. If timeout is None, block until the future completes.

Coroutine will be wrapped in Task.

Returns result of the Future or coroutine. When a timeout occurs, it cancels the task and raises asyncio.TimeoutError. To avoid the task cancellation, wrap it in shield().

If the wait is cancelled, the future fut is also cancelled.

Cette fonction est une coroutine, utilisation :

result = yield from asyncio.wait_for(fut, 60.0)

Modifié dans la version 3.4.3: If the wait is cancelled, the future fut is now also cancelled.

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18.5.4. Transports et protocoles (APi basée sur des fonctions de rappel)

Source code: Lib/asyncio/transports.py [https://github.com/python/cpython/tree/3.6/Lib/asyncio/transports.py]

Source code: Lib/asyncio/protocols.py [https://github.com/python/cpython/tree/3.6/Lib/asyncio/protocols.py]

18.5.4.1. Transports

Transports are classes provided by asyncio in order to abstract various kinds of communication channels. You generally won’t instantiate a transport yourself; instead, you will call an AbstractEventLoop method which will create the transport and try to initiate the underlying communication channel, calling you back when it succeeds.

Once the communication channel is established, a transport is always paired with a protocol instance. The protocol can then call the transport’s methods for various purposes.

asyncio currently implements transports for TCP, UDP, SSL, and subprocess pipes. The methods available on a transport depend on the transport’s kind.

The transport classes are not thread safe.

Modifié dans la version 3.6: The socket option TCP_NODELAY is now set by default.

18.5.4.1.1. BaseTransport

class asyncio.BaseTransport

Classe de base des transports.

close()

Close the transport. If the transport has a buffer for outgoing data, buffered data will be flushed asynchronously. No more data will be received. After all buffered data is flushed, the protocol’s connection_lost() method will be called with None as its argument.

is_closing()

Return True if the transport is closing or is closed.

Nouveau dans la version 3.5.1.

get_extra_info(name, default=None)

Return optional transport information. name is a string representing the piece of transport-specific information to get, default is the value to return if the information doesn’t exist.

This method allows transport implementations to easily expose channel-specific information.

socket:

'peername': the remote address to which the socket is connected, result of socket.socket.getpeername() (None on error)

'socket' : Instance de socket.socket

'sockname': the socket’s own address, result of socket.socket.getsockname()

Connecteur (socket en anglais) SSL :

'compression': the compression algorithm being used as a string, or None if the connection isn’t compressed; result of ssl.SSLSocket.compression()

'cipher': a three-value tuple containing the name of the cipher being used, the version of the SSL protocol that defines its use, and the number of secret bits being used; result of ssl.SSLSocket.cipher()

'peercert': peer certificate; result of ssl.SSLSocket.getpeercert()

sslcontext' : Instance de ssl.SSLContext

'ssl_object': ssl.SSLObject or ssl.SSLSocket instance

pipe:

'pipe' : objet pipe

sous-processus :

'subprocess': subprocess.Popen instance

set_protocol(protocol)

Set a new protocol. Switching protocol should only be done when both protocols are documented to support the switch.

Nouveau dans la version 3.5.3.

get_protocol()

Renvoie le protocole courant.

Nouveau dans la version 3.5.3.

Modifié dans la version 3.5.1: 'ssl_object' est ajouté aux sockets SSL.

18.5.4.1.2. ReadTransport

class asyncio.ReadTransport

Interface pour les transports en lecture seule.

pause_reading()

Pause the receiving end of the transport. No data will be passed to the protocol’s data_received() method until resume_reading() is called.

Modifié dans la version 3.6.7: The method is idempotent, i.e. it can be called when the transport is already paused or closed.

resume_reading()

Resume the receiving end. The protocol’s data_received() method will be called once again if some data is available for reading.

Modifié dans la version 3.6.7: The method is idempotent, i.e. it can be called when the transport is already reading.

18.5.4.1.3. WriteTransport

class asyncio.WriteTransport

Interface pour les transports en écriture seule.

abort()

Close the transport immediately, without waiting for pending operations to complete. Buffered data will be lost. No more data will be received. The protocol’s connection_lost() method will eventually be called with None as its argument.

can_write_eof()

Return True if the transport supports write_eof(), False if not.

get_write_buffer_size()

Return the current size of the output buffer used by the transport.

get_write_buffer_limits()

Get the high- and low-water limits for write flow control. Return a tuple (low, high) where low and high are positive number of bytes.

Use set_write_buffer_limits() to set the limits.

Nouveau dans la version 3.4.2.

set_write_buffer_limits(high=None, low=None)

Set the high- and low-water limits for write flow control.

These two values (measured in number of bytes) control when the protocol’s pause_writing() and resume_writing() methods are called. If specified, the low-water limit must be less than or equal to the high-water limit. Neither high nor low can be negative.

pause_writing() is called when the buffer size becomes greater than or equal to the high value. If writing has been paused, resume_writing() is called when the buffer size becomes less than or equal to the low value.

The defaults are implementation-specific. If only the high-water limit is given, the low-water limit defaults to an implementation-specific value less than or equal to the high-water limit. Setting high to zero forces low to zero as well, and causes pause_writing() to be called whenever the buffer becomes non-empty. Setting low to zero causes resume_writing() to be called only once the buffer is empty. Use of zero for either limit is generally sub-optimal as it reduces opportunities for doing I/O and computation concurrently.

Use get_write_buffer_limits() to get the limits.

write(data)

Écrit des octets de data sur le transport.

This method does not block; it buffers the data and arranges for it to be sent out asynchronously.

writelines(list_of_data)

Write a list (or any iterable) of data bytes to the transport. This is functionally equivalent to calling write() on each element yielded by the iterable, but may be implemented more efficiently.

write_eof()

Close the write end of the transport after flushing buffered data. Data may still be received.

This method can raise NotImplementedError if the transport (e.g. SSL) doesn’t support half-closes.

18.5.4.1.4. DatagramTransport

DatagramTransport.sendto(data, addr=None)

Send the data bytes to the remote peer given by addr (a transport-dependent target address). If addr is None, the data is sent to the target address given on transport creation.

This method does not block; it buffers the data and arranges for it to be sent out asynchronously.

DatagramTransport.abort()

Close the transport immediately, without waiting for pending operations to complete. Buffered data will be lost. No more data will be received. The protocol’s connection_lost() method will eventually be called with None as its argument.

18.5.4.1.5. BaseSubprocessTransport

class asyncio.BaseSubprocessTransport

get_pid()

Donne l’identifiant du sous processus sous la forme d’un nombre entier.

get_pipe_transport(fd)

Return the transport for the communication pipe corresponding to the integer file descriptor fd:

0: readable streaming transport of the standard input (stdin), or None if the subprocess was not created with stdin=PIPE

1: writable streaming transport of the standard output (stdout), or None if the subprocess was not created with stdout=PIPE

2: writable streaming transport of the standard error (stderr), or None if the subprocess was not created with stderr=PIPE

autre fd : None

get_returncode()

Return the subprocess returncode as an integer or None if it hasn’t returned, similarly to the subprocess.Popen.returncode attribute.

kill()

Kill the subprocess, as in subprocess.Popen.kill().

On POSIX systems, the function sends SIGKILL to the subprocess. On Windows, this method is an alias for terminate().

send_signal(signal)

Send the signal number to the subprocess, as in subprocess.Popen.send_signal().

terminate()

Ask the subprocess to stop, as in subprocess.Popen.terminate(). This method is an alias for the close() method.

On POSIX systems, this method sends SIGTERM to the subprocess. On Windows, the Windows API function TerminateProcess() is called to stop the subprocess.

close()

Ask the subprocess to stop by calling the terminate() method if the subprocess hasn’t returned yet, and close transports of all pipes (stdin, stdout and stderr).

18.5.4.2. Protocols

asyncio provides base classes that you can subclass to implement your network protocols. Those classes are used in conjunction with transports (see below): the protocol parses incoming data and asks for the writing of outgoing data, while the transport is responsible for the actual I/O and buffering.

When subclassing a protocol class, it is recommended you override certain methods. Those methods are callbacks: they will be called by the transport on certain events (for example when some data is received); you shouldn’t call them yourself, unless you are implementing a transport.

Note

All callbacks have default implementations, which are empty. Therefore, you only need to implement the callbacks for the events in which you are interested.

18.5.4.2.1. Protocol classes

class asyncio.Protocol

The base class for implementing streaming protocols (for use with e.g. TCP and SSL transports).

class asyncio.DatagramProtocol

The base class for implementing datagram protocols (for use with e.g. UDP transports).

class asyncio.SubprocessProtocol

The base class for implementing protocols communicating with child processes (through a set of unidirectional pipes).

18.5.4.2.2. Connection callbacks

These callbacks may be called on Protocol, DatagramProtocol and SubprocessProtocol instances:

BaseProtocol.connection_made(transport)

Appelé lorsqu’une connexion est établie.

The transport argument is the transport representing the connection. You are responsible for storing it somewhere (e.g. as an attribute) if you need to.

BaseProtocol.connection_lost(exc)

Appelé lorsqu’une connexion est perdue ou fermée.

The argument is either an exception object or None. The latter means a regular EOF is received, or the connection was aborted or closed by this side of the connection.

connection_made() and connection_lost() are called exactly once per successful connection. All other callbacks will be called between those two methods, which allows for easier resource management in your protocol implementation.

The following callbacks may be called only on SubprocessProtocol instances:

SubprocessProtocol.pipe_data_received(fd, data)

Called when the child process writes data into its stdout or stderr pipe. fd is the integer file descriptor of the pipe. data is a non-empty bytes object containing the data.

SubprocessProtocol.pipe_connection_lost(fd, exc)

Called when one of the pipes communicating with the child process is closed. fd is the integer file descriptor that was closed.

SubprocessProtocol.process_exited()

Appelé lorsqu’un processus enfant se termine.

18.5.4.2.3. Streaming protocols

The following callbacks are called on Protocol instances:

Protocol.data_received(data)

Called when some data is received. data is a non-empty bytes object containing the incoming data.

Note

Whether the data is buffered, chunked or reassembled depends on the transport. In general, you shouldn’t rely on specific semantics and instead make your parsing generic and flexible enough. However, data is always received in the correct order.

Protocol.eof_received()

Called when the other end signals it won’t send any more data (for example by calling write_eof(), if the other end also uses asyncio).

This method may return a false value (including None), in which case the transport will close itself. Conversely, if this method returns a true value, closing the transport is up to the protocol. Since the default implementation returns None, it implicitly closes the connection.

Note

Some transports such as SSL don’t support half-closed connections, in which case returning true from this method will not prevent closing the connection.

data_received() can be called an arbitrary number of times during a connection. However, eof_received() is called at most once and, if called, data_received() won’t be called after it.

Machine à états :

start -> connection_made() [-> data_received() *] [-> eof_received() ?] -> connection_lost() -> end

18.5.4.2.4. Protocoles de datagrammes

The following callbacks are called on DatagramProtocol instances.

DatagramProtocol.datagram_received(data, addr)

Called when a datagram is received. data is a bytes object containing the incoming data. addr is the address of the peer sending the data; the exact format depends on the transport.

DatagramProtocol.error_received(exc)

Called when a previous send or receive operation raises an OSError. exc is the OSError instance.

This method is called in rare conditions, when the transport (e.g. UDP) detects that a datagram couldn’t be delivered to its recipient. In many conditions though, undeliverable datagrams will be silently dropped.

18.5.4.2.5. Flow control callbacks

These callbacks may be called on Protocol, DatagramProtocol and SubprocessProtocol instances:

BaseProtocol.pause_writing()

Called when the transport’s buffer goes over the high-water mark.

BaseProtocol.resume_writing()

Called when the transport’s buffer drains below the low-water mark.

pause_writing() and resume_writing() calls are paired – pause_writing() is called once when the buffer goes strictly over the high-water mark (even if subsequent writes increases the buffer size even more), and eventually resume_writing() is called once when the buffer size reaches the low-water mark.

Note

If the buffer size equals the high-water mark, pause_writing() is not called – it must go strictly over. Conversely, resume_writing() is called when the buffer size is equal or lower than the low-water mark. These end conditions are important to ensure that things go as expected when either mark is zero.

Note

On BSD systems (OS X, FreeBSD, etc.) flow control is not supported for DatagramProtocol, because send failures caused by writing too many packets cannot be detected easily. The socket always appears “ready” and excess packets are dropped; an OSError with errno set to errno.ENOBUFS may or may not be raised; if it is raised, it will be reported to DatagramProtocol.error_received() but otherwise ignored.

18.5.4.2.6. Coroutines et protocoles

Coroutines can be scheduled in a protocol method using ensure_future(), but there is no guarantee made about the execution order. Protocols are not aware of coroutines created in protocol methods and so will not wait for them.

To have a reliable execution order, use stream objects in a coroutine with yield from. For example, the StreamWriter.drain() coroutine can be used to wait until the write buffer is flushed.

18.5.4.3. Exemples de protocole

18.5.4.3.1. Protocole « echo client » en TCP

TCP echo client using the AbstractEventLoop.create_connection() method, send data and wait until the connection is closed:

import asyncio

class EchoClientProtocol(asyncio.Protocol):
    def __init__(self, message, loop):
        self.message = message
        self.loop = loop

    def connection_made(self, transport):
        transport.write(self.message.encode())
        print('Data sent: {!r}'.format(self.message))

    def data_received(self, data):
        print('Data received: {!r}'.format(data.decode()))

    def connection_lost(self, exc):
        print('The server closed the connection')
        print('Stop the event loop')
        self.loop.stop()

loop = asyncio.get_event_loop()
message = 'Hello World!'
coro = loop.create_connection(lambda: EchoClientProtocol(message, loop),
                              '127.0.0.1', 8888)
loop.run_until_complete(coro)
loop.run_forever()
loop.close()

The event loop is running twice. The run_until_complete() method is preferred in this short example to raise an exception if the server is not listening, instead of having to write a short coroutine to handle the exception and stop the running loop. At run_until_complete() exit, the loop is no longer running, so there is no need to stop the loop in case of an error.

Voir aussi

The TCP echo client using streams example uses the asyncio.open_connection() function.

18.5.4.3.2. Protocole « echo serveur » en TCP

TCP echo server using the AbstractEventLoop.create_server() method, send back received data and close the connection:

import asyncio

class EchoServerClientProtocol(asyncio.Protocol):
    def connection_made(self, transport):
        peername = transport.get_extra_info('peername')
        print('Connection from {}'.format(peername))
        self.transport = transport

    def data_received(self, data):
        message = data.decode()
        print('Data received: {!r}'.format(message))

        print('Send: {!r}'.format(message))
        self.transport.write(data)

        print('Close the client socket')
        self.transport.close()

loop = asyncio.get_event_loop()
# Each client connection will create a new protocol instance
coro = loop.create_server(EchoServerClientProtocol, '127.0.0.1', 8888)
server = loop.run_until_complete(coro)

# Serve requests until Ctrl+C is pressed
print('Serving on {}'.format(server.sockets[0].getsockname()))
try:
    loop.run_forever()
except KeyboardInterrupt:
    pass

# Close the server
server.close()
loop.run_until_complete(server.wait_closed())
loop.close()

Transport.close() can be called immediately after WriteTransport.write() even if data are not sent yet on the socket: both methods are asynchronous. yield from is not needed because these transport methods are not coroutines.

Voir aussi

The TCP echo server using streams example uses the asyncio.start_server() function.

18.5.4.3.3. Protocole « echo client » en UDP

UDP echo client using the AbstractEventLoop.create_datagram_endpoint() method, send data and close the transport when we received the answer:

import asyncio

class EchoClientProtocol:
    def __init__(self, message, loop):
        self.message = message
        self.loop = loop
        self.transport = None

    def connection_made(self, transport):
        self.transport = transport
        print('Send:', self.message)
        self.transport.sendto(self.message.encode())

    def datagram_received(self, data, addr):
        print("Received:", data.decode())

        print("Close the socket")
        self.transport.close()

    def error_received(self, exc):
        print('Error received:', exc)

    def connection_lost(self, exc):
        print("Socket closed, stop the event loop")
        loop = asyncio.get_event_loop()
        loop.stop()

loop = asyncio.get_event_loop()
message = "Hello World!"
connect = loop.create_datagram_endpoint(
    lambda: EchoClientProtocol(message, loop),
    remote_addr=('127.0.0.1', 9999))
transport, protocol = loop.run_until_complete(connect)
loop.run_forever()
transport.close()
loop.close()

18.5.4.3.4. Protocole « echo serveur » en UDP

UDP echo server using the AbstractEventLoop.create_datagram_endpoint() method, send back received data:

import asyncio

class EchoServerProtocol:
    def connection_made(self, transport):
        self.transport = transport

    def datagram_received(self, data, addr):
        message = data.decode()
        print('Received %r from %s' % (message, addr))
        print('Send %r to %s' % (message, addr))
        self.transport.sendto(data, addr)

loop = asyncio.get_event_loop()
print("Starting UDP server")
# One protocol instance will be created to serve all client requests
listen = loop.create_datagram_endpoint(
    EchoServerProtocol, local_addr=('127.0.0.1', 9999))
transport, protocol = loop.run_until_complete(listen)

try:
    loop.run_forever()
except KeyboardInterrupt:
    pass

transport.close()
loop.close()

18.5.4.3.5. Register an open socket to wait for data using a protocol

Wait until a socket receives data using the AbstractEventLoop.create_connection() method with a protocol, and then close the event loop

import asyncio
try:
    from socket import socketpair
except ImportError:
    from asyncio.windows_utils import socketpair

# Create a pair of connected sockets
rsock, wsock = socketpair()
loop = asyncio.get_event_loop()

class MyProtocol(asyncio.Protocol):
    transport = None

    def connection_made(self, transport):
        self.transport = transport

    def data_received(self, data):
        print("Received:", data.decode())

        # We are done: close the transport (it will call connection_lost())
        self.transport.close()

    def connection_lost(self, exc):
        # The socket has been closed, stop the event loop
        loop.stop()

# Register the socket to wait for data
connect_coro = loop.create_connection(MyProtocol, sock=rsock)
transport, protocol = loop.run_until_complete(connect_coro)

# Simulate the reception of data from the network
loop.call_soon(wsock.send, 'abc'.encode())

# Run the event loop
loop.run_forever()

# We are done, close sockets and the event loop
rsock.close()
wsock.close()
loop.close()

Voir aussi

The watch a file descriptor for read events example uses the low-level AbstractEventLoop.add_reader() method to register the file descriptor of a socket.

The register an open socket to wait for data using streams example uses high-level streams created by the open_connection() function in a coroutine.

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18.5.5. Streams (coroutine based API)

Source code: Lib/asyncio/streams.py [https://github.com/python/cpython/tree/3.6/Lib/asyncio/streams.py]

18.5.5.1. Stream functions

Note

The top-level functions in this module are meant as convenience wrappers only; there’s really nothing special there, and if they don’t do exactly what you want, feel free to copy their code.

coroutine asyncio.open_connection(host=None, port=None, *, loop=None, limit=None, **kwds)

A wrapper for create_connection() returning a (reader, writer) pair.

The reader returned is a StreamReader instance; the writer is a StreamWriter instance.

The arguments are all the usual arguments to AbstractEventLoop.create_connection() except protocol_factory; most common are positional host and port, with various optional keyword arguments following.

Additional optional keyword arguments are loop (to set the event loop instance to use) and limit (to set the buffer limit passed to the StreamReader).

Cette fonction est une coroutine.

coroutine asyncio.start_server(client_connected_cb, host=None, port=None, *, loop=None, limit=None, **kwds)

Start a socket server, with a callback for each client connected. The return value is the same as create_server().

The client_connected_cb parameter is called with two parameters: client_reader, client_writer. client_reader is a StreamReader object, while client_writer is a StreamWriter object. The client_connected_cb parameter can either be a plain callback function or a coroutine function; if it is a coroutine function, it will be automatically converted into a Task.

The rest of the arguments are all the usual arguments to create_server() except protocol_factory; most common are positional host and port, with various optional keyword arguments following.

Additional optional keyword arguments are loop (to set the event loop instance to use) and limit (to set the buffer limit passed to the StreamReader).

Cette fonction est une coroutine.

coroutine asyncio.open_unix_connection(path=None, *, loop=None, limit=None, **kwds)

A wrapper for create_unix_connection() returning a (reader, writer) pair.

See open_connection() for information about return value and other details.

Cette fonction est une coroutine.

Disponible sur : UNIX.

coroutine asyncio.start_unix_server(client_connected_cb, path=None, *, loop=None, limit=None, **kwds)

Start a UNIX Domain Socket server, with a callback for each client connected.

See start_server() for information about return value and other details.

Cette fonction est une coroutine.

Disponible sur : UNIX.

18.5.5.2. StreamReader

class asyncio.StreamReader(limit=_DEFAULT_LIMIT, loop=None)

This class is not thread safe.

The limit argument’s default value is set to _DEFAULT_LIMIT which is 2**16 (64 KiB)

exception()

Récupère l’exception.

feed_eof()

Acknowledge the EOF.

feed_data(data)

Feed data bytes in the internal buffer. Any operations waiting for the data will be resumed.

set_exception(exc)

Set the exception.

set_transport(transport)

Set the transport.

coroutine read(n=-1)

Read up to n bytes. If n is not provided, or set to -1, read until EOF and return all read bytes.

If the EOF was received and the internal buffer is empty, return an empty bytes object.

Cette méthode est une coroutine.

coroutine readline()

Read one line, where « line » is a sequence of bytes ending with \n.

If EOF is received, and \n was not found, the method will return the partial read bytes.

If the EOF was received and the internal buffer is empty, return an empty bytes object.

Cette méthode est une coroutine.

coroutine readexactly(n)

Read exactly n bytes. Raise an IncompleteReadError if the end of the stream is reached before n can be read, the IncompleteReadError.partial attribute of the exception contains the partial read bytes.

Cette méthode est une coroutine.

coroutine readuntil(separator=b'\n')

Read data from the stream until separator is found.

On success, the data and separator will be removed from the internal buffer (consumed). Returned data will include the separator at the end.

Configured stream limit is used to check result. Limit sets the maximal length of data that can be returned, not counting the separator.

If an EOF occurs and the complete separator is still not found, an IncompleteReadError exception will be raised, and the internal buffer will be reset. The IncompleteReadError.partial attribute may contain the separator partially.

If the data cannot be read because of over limit, a LimitOverrunError exception will be raised, and the data will be left in the internal buffer, so it can be read again.

Nouveau dans la version 3.5.2.

at_eof()

Return True if the buffer is empty and feed_eof() was called.

18.5.5.3. StreamWriter

class asyncio.StreamWriter(transport, protocol, reader, loop)

Wraps a Transport.

This exposes write(), writelines(), can_write_eof(), write_eof(), get_extra_info() and close(). It adds drain() which returns an optional Future on which you can wait for flow control. It also adds a transport attribute which references the Transport directly.

This class is not thread safe.

transport

Transport.

can_write_eof()

Return True if the transport supports write_eof(), False if not. See WriteTransport.can_write_eof().

close()

Close the transport: see BaseTransport.close().

coroutine drain()

Let the write buffer of the underlying transport a chance to be flushed.

The intended use is to write:

w.write(data)
yield from w.drain()

When the size of the transport buffer reaches the high-water limit (the protocol is paused), block until the size of the buffer is drained down to the low-water limit and the protocol is resumed. When there is nothing to wait for, the yield-from continues immediately.

Yielding from drain() gives the opportunity for the loop to schedule the write operation and flush the buffer. It should especially be used when a possibly large amount of data is written to the transport, and the coroutine does not yield-from between calls to write().

Cette méthode est une coroutine.

get_extra_info(name, default=None)

Return optional transport information: see BaseTransport.get_extra_info().

write(data)

Write some data bytes to the transport: see WriteTransport.write().

writelines(data)

Write a list (or any iterable) of data bytes to the transport: see WriteTransport.writelines().

write_eof()

Close the write end of the transport after flushing buffered data: see WriteTransport.write_eof().

18.5.5.4. StreamReaderProtocol

class asyncio.StreamReaderProtocol(stream_reader, client_connected_cb=None, loop=None)

Trivial helper class to adapt between Protocol and StreamReader. Subclass of Protocol.

stream_reader is a StreamReader instance, client_connected_cb is an optional function called with (stream_reader, stream_writer) when a connection is made, loop is the event loop instance to use.

(This is a helper class instead of making StreamReader itself a Protocol subclass, because the StreamReader has other potential uses, and to prevent the user of the StreamReader from accidentally calling inappropriate methods of the protocol.)

18.5.5.5. IncompleteReadError

exception asyncio.IncompleteReadError

Incomplete read error, subclass of EOFError.

expected

Nombre total d’octets attendus (int).

partial

Read bytes string before the end of stream was reached (bytes).

18.5.5.6. LimitOverrunError

exception asyncio.LimitOverrunError

Reached the buffer limit while looking for a separator.

consumed

Total number of to be consumed bytes.

18.5.5.7. Stream examples

18.5.5.7.1. TCP echo client using streams

TCP echo client using the asyncio.open_connection() function:

import asyncio

@asyncio.coroutine
def tcp_echo_client(message, loop):
    reader, writer = yield from asyncio.open_connection('127.0.0.1', 8888,
                                                        loop=loop)

    print('Send: %r' % message)
    writer.write(message.encode())

    data = yield from reader.read(100)
    print('Received: %r' % data.decode())

    print('Close the socket')
    writer.close()

message = 'Hello World!'
loop = asyncio.get_event_loop()
loop.run_until_complete(tcp_echo_client(message, loop))
loop.close()

Voir aussi

The TCP echo client protocol example uses the AbstractEventLoop.create_connection() method.

18.5.5.7.2. TCP echo server using streams

TCP echo server using the asyncio.start_server() function:

import asyncio

@asyncio.coroutine
def handle_echo(reader, writer):
    data = yield from reader.read(100)
    message = data.decode()
    addr = writer.get_extra_info('peername')
    print("Received %r from %r" % (message, addr))

    print("Send: %r" % message)
    writer.write(data)
    yield from writer.drain()

    print("Close the client socket")
    writer.close()

loop = asyncio.get_event_loop()
coro = asyncio.start_server(handle_echo, '127.0.0.1', 8888, loop=loop)
server = loop.run_until_complete(coro)

# Serve requests until Ctrl+C is pressed
print('Serving on {}'.format(server.sockets[0].getsockname()))
try:
    loop.run_forever()
except KeyboardInterrupt:
    pass

# Close the server
server.close()
loop.run_until_complete(server.wait_closed())
loop.close()

Voir aussi

The TCP echo server protocol example uses the AbstractEventLoop.create_server() method.

18.5.5.7.3. Récupère les en-têtes HTTP

Simple example querying HTTP headers of the URL passed on the command line:

import asyncio
import urllib.parse
import sys

@asyncio.coroutine
def print_http_headers(url):
    url = urllib.parse.urlsplit(url)
    if url.scheme == 'https':
        connect = asyncio.open_connection(url.hostname, 443, ssl=True)
    else:
        connect = asyncio.open_connection(url.hostname, 80)
    reader, writer = yield from connect
    query = ('HEAD {path} HTTP/1.0\r\n'
             'Host: {hostname}\r\n'
             '\r\n').format(path=url.path or '/', hostname=url.hostname)
    writer.write(query.encode('latin-1'))
    while True:
        line = yield from reader.readline()
        if not line:
            break
        line = line.decode('latin1').rstrip()
        if line:
            print('HTTP header> %s' % line)

    # Ignore the body, close the socket
    writer.close()

url = sys.argv[1]
loop = asyncio.get_event_loop()
task = asyncio.ensure_future(print_http_headers(url))
loop.run_until_complete(task)
loop.close()

Utilisation :

python example.py http://example.com/path/page.html

ou avec HTTPS :

python example.py https://example.com/path/page.html

18.5.5.7.4. Register an open socket to wait for data using streams

Coroutine waiting until a socket receives data using the open_connection() function:

import asyncio
try:
    from socket import socketpair
except ImportError:
    from asyncio.windows_utils import socketpair

@asyncio.coroutine
def wait_for_data(loop):
    # Create a pair of connected sockets
    rsock, wsock = socketpair()

    # Register the open socket to wait for data
    reader, writer = yield from asyncio.open_connection(sock=rsock, loop=loop)

    # Simulate the reception of data from the network
    loop.call_soon(wsock.send, 'abc'.encode())

    # Wait for data
    data = yield from reader.read(100)

    # Got data, we are done: close the socket
    print("Received:", data.decode())
    writer.close()

    # Close the second socket
    wsock.close()

loop = asyncio.get_event_loop()
loop.run_until_complete(wait_for_data(loop))
loop.close()

Voir aussi

The register an open socket to wait for data using a protocol example uses a low-level protocol created by the AbstractEventLoop.create_connection() method.

The watch a file descriptor for read events example uses the low-level AbstractEventLoop.add_reader() method to register the file descriptor of a socket.

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18.5.6. Subprocess

Source code: Lib/asyncio/subprocess.py [https://github.com/python/cpython/tree/3.6/Lib/asyncio/subprocess.py]

18.5.6.1. Boucle d’évènements Windows

On Windows, the default event loop is SelectorEventLoop which does not support subprocesses. ProactorEventLoop should be used instead. Example to use it on Windows:

import asyncio, sys

if sys.platform == 'win32':
    loop = asyncio.ProactorEventLoop()
    asyncio.set_event_loop(loop)

Voir aussi

Available event loops and Platform support.

18.5.6.2. Créer un processus fils : API de haut niveau utilisant Process

coroutine asyncio.create_subprocess_exec(*args, stdin=None, stdout=None, stderr=None, loop=None, limit=None, **kwds)

Create a subprocess.

The limit parameter sets the buffer limit passed to the StreamReader. See AbstractEventLoop.subprocess_exec() for other parameters.

Return a Process instance.

Cette fonction est une coroutine.

coroutine asyncio.create_subprocess_shell(cmd, stdin=None, stdout=None, stderr=None, loop=None, limit=None, **kwds)

Exécute la commande shell cmd.

The limit parameter sets the buffer limit passed to the StreamReader. See AbstractEventLoop.subprocess_shell() for other parameters.

Return a Process instance.

It is the application’s responsibility to ensure that all whitespace and metacharacters are quoted appropriately to avoid shell injection [https://en.wikipedia.org/wiki/Shell_injection#Shell_injection] vulnerabilities. The shlex.quote() function can be used to properly escape whitespace and shell metacharacters in strings that are going to be used to construct shell commands.

Cette fonction est une coroutine.

Use the AbstractEventLoop.connect_read_pipe() and AbstractEventLoop.connect_write_pipe() methods to connect pipes.

18.5.6.3. Create a subprocess: low-level API using subprocess.Popen

Run subprocesses asynchronously using the subprocess module.

coroutine AbstractEventLoop.subprocess_exec(protocol_factory, *args, stdin=subprocess.PIPE, stdout=subprocess.PIPE, stderr=subprocess.PIPE, **kwargs)

Create a subprocess from one or more string arguments (character strings or bytes strings encoded to the filesystem encoding), where the first string specifies the program to execute, and the remaining strings specify the program’s arguments. (Thus, together the string arguments form the sys.argv value of the program, assuming it is a Python script.) This is similar to the standard library subprocess.Popen class called with shell=False and the list of strings passed as the first argument; however, where Popen takes a single argument which is list of strings, subprocess_exec() takes multiple string arguments.

The protocol_factory must instantiate a subclass of the asyncio.SubprocessProtocol class.

Autres paramètres :

stdin: Either a file-like object representing the pipe to be connected to the subprocess’s standard input stream using connect_write_pipe(), or the constant subprocess.PIPE (the default). By default a new pipe will be created and connected.

stdout: Either a file-like object representing the pipe to be connected to the subprocess’s standard output stream using connect_read_pipe(), or the constant subprocess.PIPE (the default). By default a new pipe will be created and connected.

stderr: Either a file-like object representing the pipe to be connected to the subprocess’s standard error stream using connect_read_pipe(), or one of the constants subprocess.PIPE (the default) or subprocess.STDOUT. By default a new pipe will be created and connected. When subprocess.STDOUT is specified, the subprocess’s standard error stream will be connected to the same pipe as the standard output stream.

All other keyword arguments are passed to subprocess.Popen without interpretation, except for bufsize, universal_newlines and shell, which should not be specified at all.

Returns a pair of (transport, protocol), where transport is an instance of BaseSubprocessTransport.

Cette méthode est une coroutine.

See the constructor of the subprocess.Popen class for parameters.

coroutine AbstractEventLoop.subprocess_shell(protocol_factory, cmd, *, stdin=subprocess.PIPE, stdout=subprocess.PIPE, stderr=subprocess.PIPE, **kwargs)

Create a subprocess from cmd, which is a character string or a bytes string encoded to the filesystem encoding, using the platform’s « shell » syntax. This is similar to the standard library subprocess.Popen class called with shell=True.

The protocol_factory must instantiate a subclass of the asyncio.SubprocessProtocol class.

See subprocess_exec() for more details about the remaining arguments.

Returns a pair of (transport, protocol), where transport is an instance of BaseSubprocessTransport.

It is the application’s responsibility to ensure that all whitespace and metacharacters are quoted appropriately to avoid shell injection [https://en.wikipedia.org/wiki/Shell_injection#Shell_injection] vulnerabilities. The shlex.quote() function can be used to properly escape whitespace and shell metacharacters in strings that are going to be used to construct shell commands.

Cette méthode est une coroutine.

Voir aussi

The AbstractEventLoop.connect_read_pipe() and AbstractEventLoop.connect_write_pipe() methods.

18.5.6.4. Constantes

asyncio.subprocess.PIPE

Special value that can be used as the stdin, stdout or stderr argument to create_subprocess_shell() and create_subprocess_exec() and indicates that a pipe to the standard stream should be opened.

asyncio.subprocess.STDOUT

Special value that can be used as the stderr argument to create_subprocess_shell() and create_subprocess_exec() and indicates that standard error should go into the same handle as standard output.

asyncio.subprocess.DEVNULL

Special value that can be used as the stdin, stdout or stderr argument to create_subprocess_shell() and create_subprocess_exec() and indicates that the special file os.devnull will be used.

18.5.6.5. Process

class asyncio.subprocess.Process

A subprocess created by the create_subprocess_exec() or the create_subprocess_shell() function.

The API of the Process class was designed to be close to the API of the subprocess.Popen class, but there are some differences:

There is no explicit poll() method

The communicate() and wait() methods don’t take a timeout parameter: use the wait_for() function

The universal_newlines parameter is not supported (only bytes strings are supported)

The wait() method of the Process class is asynchronous whereas the wait() method of the Popen class is implemented as a busy loop.

This class is not thread safe. See also the Subprocess and threads section.

coroutine wait()

Wait for child process to terminate. Set and return returncode attribute.

Cette méthode est une coroutine.

Note

This will deadlock when using stdout=PIPE or stderr=PIPE and the child process generates enough output to a pipe such that it blocks waiting for the OS pipe buffer to accept more data. Use the communicate() method when using pipes to avoid that.

coroutine communicate(input=None)

Interact with process: Send data to stdin. Read data from stdout and stderr, until end-of-file is reached. Wait for process to terminate. The optional input argument should be data to be sent to the child process, or None, if no data should be sent to the child. The type of input must be bytes.

communicate() returns a tuple (stdout_data, stderr_data).

If a BrokenPipeError or ConnectionResetError exception is raised when writing input into stdin, the exception is ignored. It occurs when the process exits before all data are written into stdin.

Note that if you want to send data to the process’s stdin, you need to create the Process object with stdin=PIPE. Similarly, to get anything other than None in the result tuple, you need to give stdout=PIPE and/or stderr=PIPE too.

Cette méthode est une coroutine.

Note

Les données lues sont mises en cache en mémoire, donc n’utilisez pas cette méthode si la taille des données est importante voire illimitée.

Modifié dans la version 3.4.2: The method now ignores BrokenPipeError and ConnectionResetError.

send_signal(signal)

Envoie le signal signal au sous-processus.

Note

On Windows, SIGTERM is an alias for terminate(). CTRL_C_EVENT and CTRL_BREAK_EVENT can be sent to processes started with a creationflags parameter which includes CREATE_NEW_PROCESS_GROUP.

terminate()

Stop the child. On Posix OSs the method sends signal.SIGTERM to the child. On Windows the Win32 API function TerminateProcess() is called to stop the child.

kill()

Kills the child. On Posix OSs the function sends SIGKILL to the child. On Windows kill() is an alias for terminate().

stdin

Standard input stream (StreamWriter), None if the process was created with stdin=None.

stdout

Standard output stream (StreamReader), None if the process was created with stdout=None.

stderr

Standard error stream (StreamReader), None if the process was created with stderr=None.

Avertissement

Use the communicate() method rather than .stdin.write, .stdout.read or .stderr.read to avoid deadlocks due to streams pausing reading or writing and blocking the child process.

pid

L’identifiant du processus.

Note that for processes created by the create_subprocess_shell() function, this attribute is the process identifier of the spawned shell.

returncode

Return code of the process when it exited. A None value indicates that the process has not terminated yet.

A negative value -N indicates that the child was terminated by signal N (Unix only).

18.5.6.6. Processus fils et fils d’exécution

asyncio supports running subprocesses from different threads, but there are limits:

Une boucle d’évènements doit être exécutée sur le fil d’exécution principal

The child watcher must be instantiated in the main thread, before executing subprocesses from other threads. Call the get_child_watcher() function in the main thread to instantiate the child watcher.

The asyncio.subprocess.Process class is not thread safe.

Voir aussi

The Concurrency and multithreading in asyncio section.

18.5.6.7. Subprocess examples

18.5.6.7.1. Subprocess using transport and protocol

Example of a subprocess protocol using to get the output of a subprocess and to wait for the subprocess exit. The subprocess is created by the AbstractEventLoop.subprocess_exec() method:

import asyncio
import sys

class DateProtocol(asyncio.SubprocessProtocol):
    def __init__(self, exit_future):
        self.exit_future = exit_future
        self.output = bytearray()

    def pipe_data_received(self, fd, data):
        self.output.extend(data)

    def process_exited(self):
        self.exit_future.set_result(True)

@asyncio.coroutine
def get_date(loop):
    code = 'import datetime; print(datetime.datetime.now())'
    exit_future = asyncio.Future(loop=loop)

    # Create the subprocess controlled by the protocol DateProtocol,
    # redirect the standard output into a pipe
    create = loop.subprocess_exec(lambda: DateProtocol(exit_future),
                                  sys.executable, '-c', code,
                                  stdin=None, stderr=None)
    transport, protocol = yield from create

    # Wait for the subprocess exit using the process_exited() method
    # of the protocol
    yield from exit_future

    # Close the stdout pipe
    transport.close()

    # Read the output which was collected by the pipe_data_received()
    # method of the protocol
    data = bytes(protocol.output)
    return data.decode('ascii').rstrip()

if sys.platform == "win32":
    loop = asyncio.ProactorEventLoop()
    asyncio.set_event_loop(loop)
else:
    loop = asyncio.get_event_loop()

date = loop.run_until_complete(get_date(loop))
print("Current date: %s" % date)
loop.close()

18.5.6.7.2. Subprocess using streams

Example using the Process class to control the subprocess and the StreamReader class to read from the standard output. The subprocess is created by the create_subprocess_exec() function:

import asyncio.subprocess
import sys

@asyncio.coroutine
def get_date():
    code = 'import datetime; print(datetime.datetime.now())'

    # Create the subprocess, redirect the standard output into a pipe
    create = asyncio.create_subprocess_exec(sys.executable, '-c', code,
                                            stdout=asyncio.subprocess.PIPE)
    proc = yield from create

    # Read one line of output
    data = yield from proc.stdout.readline()
    line = data.decode('ascii').rstrip()

    # Wait for the subprocess exit
    yield from proc.wait()
    return line

if sys.platform == "win32":
    loop = asyncio.ProactorEventLoop()
    asyncio.set_event_loop(loop)
else:
    loop = asyncio.get_event_loop()

date = loop.run_until_complete(get_date())
print("Current date: %s" % date)
loop.close()

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18.5.7. Primitives de synchronisation

Source code: Lib/asyncio/locks.py [https://github.com/python/cpython/tree/3.6/Lib/asyncio/locks.py]

Locks:

Lock

Event

Condition

Sémaphores :

Semaphore

BoundedSemaphore

asyncio lock API was designed to be close to classes of the threading module (Lock, Event, Condition, Semaphore, BoundedSemaphore), but it has no timeout parameter. The asyncio.wait_for() function can be used to cancel a task after a timeout.

18.5.7.1. Locks

18.5.7.1.1. Lock

class asyncio.Lock(*, loop=None)

Primitive lock objects.

A primitive lock is a synchronization primitive that is not owned by a particular coroutine when locked. A primitive lock is in one of two states, “locked” or “unlocked”.

It is created in the unlocked state. It has two basic methods, acquire() and release(). When the state is unlocked, acquire() changes the state to locked and returns immediately. When the state is locked, acquire() blocks until a call to release() in another coroutine changes it to unlocked, then the acquire() call resets it to locked and returns. The release() method should only be called in the locked state; it changes the state to unlocked and returns immediately. If an attempt is made to release an unlocked lock, a RuntimeError will be raised.

When more than one coroutine is blocked in acquire() waiting for the state to turn to unlocked, only one coroutine proceeds when a release() call resets the state to unlocked; first coroutine which is blocked in acquire() is being processed.

acquire() is a coroutine and should be called with yield from.

Locks also support the context management protocol. (yield from lock) should be used as the context manager expression.

This class is not thread safe.

Utilisation :

lock = Lock()
...
yield from lock
try:
    ...
finally:
    lock.release()

Context manager usage:

lock = Lock()
...
with (yield from lock):
    ...

Lock objects can be tested for locking state:

if not lock.locked():
    yield from lock
else:
    # lock is acquired
    ...

locked()

Donne True si le verrou est acquis.

coroutine acquire()

Acquire a lock.

This method blocks until the lock is unlocked, then sets it to locked and returns True.

Cette méthode est une coroutine.

release()

Libère un verrou.

When the lock is locked, reset it to unlocked, and return. If any other coroutines are blocked waiting for the lock to become unlocked, allow exactly one of them to proceed.

When invoked on an unlocked lock, a RuntimeError is raised.

Il n’y a pas de valeur de retour.

18.5.7.1.2. Event

class asyncio.Event(*, loop=None)

An Event implementation, asynchronous equivalent to threading.Event.

Class implementing event objects. An event manages a flag that can be set to true with the set() method and reset to false with the clear() method. The wait() method blocks until the flag is true. The flag is initially false.

This class is not thread safe.

clear()

Reset the internal flag to false. Subsequently, coroutines calling wait() will block until set() is called to set the internal flag to true again.

is_set()

Return True if and only if the internal flag is true.

set()

Set the internal flag to true. All coroutines waiting for it to become true are awakened. Coroutine that call wait() once the flag is true will not block at all.

coroutine wait()

Block until the internal flag is true.

If the internal flag is true on entry, return True immediately. Otherwise, block until another coroutine calls set() to set the flag to true, then return True.

Cette méthode est une coroutine.

18.5.7.1.3. Condition

class asyncio.Condition(lock=None, *, loop=None)

A Condition implementation, asynchronous equivalent to threading.Condition.

This class implements condition variable objects. A condition variable allows one or more coroutines to wait until they are notified by another coroutine.

If the lock argument is given and not None, it must be a Lock object, and it is used as the underlying lock. Otherwise, a new Lock object is created and used as the underlying lock.

This class is not thread safe.

coroutine acquire()

Acquire the underlying lock.

This method blocks until the lock is unlocked, then sets it to locked and returns True.

Cette méthode est une coroutine.

notify(n=1)

By default, wake up one coroutine waiting on this condition, if any. If the calling coroutine has not acquired the lock when this method is called, a RuntimeError is raised.

This method wakes up at most n of the coroutines waiting for the condition variable; it is a no-op if no coroutines are waiting.

Note

An awakened coroutine does not actually return from its wait() call until it can reacquire the lock. Since notify() does not release the lock, its caller should.

locked()

Return True if the underlying lock is acquired.

notify_all()

Wake up all coroutines waiting on this condition. This method acts like notify(), but wakes up all waiting coroutines instead of one. If the calling coroutine has not acquired the lock when this method is called, a RuntimeError is raised.

release()

Libère le verrou sous-jacent.

When the lock is locked, reset it to unlocked, and return. If any other coroutines are blocked waiting for the lock to become unlocked, allow exactly one of them to proceed.

When invoked on an unlocked lock, a RuntimeError is raised.

Il n’y a pas de valeur de retour.

coroutine wait()

Attends d’être notifié.

If the calling coroutine has not acquired the lock when this method is called, a RuntimeError is raised.

This method releases the underlying lock, and then blocks until it is awakened by a notify() or notify_all() call for the same condition variable in another coroutine. Once awakened, it re-acquires the lock and returns True.

Cette méthode est une coroutine.

coroutine wait_for(predicate)

Attends jusqu’à ce qu’un prédicat devienne vrai.

The predicate should be a callable which result will be interpreted as a boolean value. The final predicate value is the return value.

Cette méthode est une coroutine.

18.5.7.2. Sémaphores

18.5.7.2.1. Sémaphore

class asyncio.Semaphore(value=1, *, loop=None)

A Semaphore implementation.

A semaphore manages an internal counter which is decremented by each acquire() call and incremented by each release() call. The counter can never go below zero; when acquire() finds that it is zero, it blocks, waiting until some other coroutine calls release().

Semaphores also support the context management protocol.

The optional argument gives the initial value for the internal counter; it defaults to 1. If the value given is less than 0, ValueError is raised.

This class is not thread safe.

coroutine acquire()

Acquire a semaphore.

If the internal counter is larger than zero on entry, decrement it by one and return True immediately. If it is zero on entry, block, waiting until some other coroutine has called release() to make it larger than 0, and then return True.

Cette méthode est une coroutine.

locked()

Returns True if semaphore can not be acquired immediately.

release()

Release a semaphore, incrementing the internal counter by one. When it was zero on entry and another coroutine is waiting for it to become larger than zero again, wake up that coroutine.

18.5.7.2.2. BoundedSemaphore

class asyncio.BoundedSemaphore(value=1, *, loop=None)

A bounded semaphore implementation. Inherit from Semaphore.

This raises ValueError in release() if it would increase the value above the initial value.

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18.5.8. Queues

Source code: Lib/asyncio/queues.py [https://github.com/python/cpython/tree/3.6/Lib/asyncio/queues.py]

Queues:

Queue

PriorityQueue

LifoQueue

asyncio queue API was designed to be close to classes of the queue module (Queue, PriorityQueue, LifoQueue), but it has no timeout parameter. The asyncio.wait_for() function can be used to cancel a task after a timeout.

18.5.8.1. Queue

class asyncio.Queue(maxsize=0, *, loop=None)

A queue, useful for coordinating producer and consumer coroutines.

If maxsize is less than or equal to zero, the queue size is infinite. If it is an integer greater than 0, then yield from put() will block when the queue reaches maxsize, until an item is removed by get().

Unlike the standard library queue, you can reliably know this Queue’s size with qsize(), since your single-threaded asyncio application won’t be interrupted between calling qsize() and doing an operation on the Queue.

This class is not thread safe.

Modifié dans la version 3.4.4: Les nouvelles méthodes join() et task_done().

empty()

Renvoie True si la queue est vide, False sinon.

full()

Return True if there are maxsize items in the queue.

Note

If the Queue was initialized with maxsize=0 (the default), then full() is never True.

coroutine get()

Remove and return an item from the queue. If queue is empty, wait until an item is available.

Cette méthode est une coroutine.

Voir aussi

La méthode empty().

get_nowait()

Supprime et donne un élément de la queue.

Return an item if one is immediately available, else raise QueueEmpty.

coroutine join()

Bloque jusqu’à ce que tous les éléments de la queue aient été récupérés et traités.

The count of unfinished tasks goes up whenever an item is added to the queue. The count goes down whenever a consumer thread calls task_done() to indicate that the item was retrieved and all work on it is complete. When the count of unfinished tasks drops to zero, join() unblocks.

Cette méthode est une coroutine.

Nouveau dans la version 3.4.4.

coroutine put(item)

Put an item into the queue. If the queue is full, wait until a free slot is available before adding item.

Cette méthode est une coroutine.

Voir aussi

La méthode full().

put_nowait(item)

Ajoute un élément dans la queue sans bloquer.

If no free slot is immediately available, raise QueueFull.

qsize()

Nombre d’éléments dans la queue.

task_done()

Indicate that a formerly enqueued task is complete.

Used by queue consumers. For each get() used to fetch a task, a subsequent call to task_done() tells the queue that the processing on the task is complete.

If a join() is currently blocking, it will resume when all items have been processed (meaning that a task_done() call was received for every item that had been put() into the queue).

Raises ValueError if called more times than there were items placed in the queue.

Nouveau dans la version 3.4.4.

maxsize

Nombre d’éléments autorisés dans la queue.

18.5.8.2. PriorityQueue

class asyncio.PriorityQueue

A subclass of Queue; retrieves entries in priority order (lowest first).

Entries are typically tuples of the form: (priority number, data).

18.5.8.3. LifoQueue

class asyncio.LifoQueue

A subclass of Queue that retrieves most recently added entries first.

18.5.8.3.1. Exceptions

exception asyncio.QueueEmpty

Exception raised when the get_nowait() method is called on a Queue object which is empty.

exception asyncio.QueueFull

Exception raised when the put_nowait() method is called on a Queue object which is full.

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18.5.9. Programmer avec asyncio

Asynchronous programming is different than classical « sequential » programming. This page lists common traps and explains how to avoid them.

18.5.9.1. Mode de débogage d”asyncio

The implementation of asyncio has been written for performance. In order to ease the development of asynchronous code, you may wish to enable debug mode.

Pour activer toutes les vérifications de débogage pour une application :

Enable the asyncio debug mode globally by setting the environment variable PYTHONASYNCIODEBUG to 1, or by calling AbstractEventLoop.set_debug().

Set the log level of the asyncio logger to logging.DEBUG. For example, call logging.basicConfig(level=logging.DEBUG) at startup.

Configure the warnings module to display ResourceWarning warnings. For example, use the -Wdefault command line option of Python to display them.

Exemples de vérifications de débogage :

Log coroutines defined but never « yielded from »

call_soon() and call_at() methods raise an exception if they are called from the wrong thread.

Enregistre le temps d’exécution du sélecteur dans le journal

Log callbacks taking more than 100 ms to be executed. The AbstractEventLoop.slow_callback_duration attribute is the minimum duration in seconds of « slow » callbacks.

ResourceWarning warnings are emitted when transports and event loops are not closed explicitly.

Voir aussi

The AbstractEventLoop.set_debug() method and the asyncio logger.

18.5.9.2. Annulation

Cancellation of tasks is not common in classic programming. In asynchronous programming, not only is it something common, but you have to prepare your code to handle it.

Futures and tasks can be cancelled explicitly with their Future.cancel() method. The wait_for() function cancels the waited task when the timeout occurs. There are many other cases where a task can be cancelled indirectly.

Don’t call set_result() or set_exception() method of Future if the future is cancelled: it would fail with an exception. For example, write:

if not fut.cancelled():
    fut.set_result('done')

Don’t schedule directly a call to the set_result() or the set_exception() method of a future with AbstractEventLoop.call_soon(): the future can be cancelled before its method is called.

If you wait for a future, you should check early if the future was cancelled to avoid useless operations. Example:

@coroutine
def slow_operation(fut):
    if fut.cancelled():
        return
    # ... slow computation ...
    yield from fut
    # ...

The shield() function can also be used to ignore cancellation.

18.5.9.3. Concourance et multithreading

An event loop runs in a thread and executes all callbacks and tasks in the same thread. While a task is running in the event loop, no other task is running in the same thread. But when the task uses yield from, the task is suspended and the event loop executes the next task.

To schedule a callback from a different thread, the AbstractEventLoop.call_soon_threadsafe() method should be used. Example:

loop.call_soon_threadsafe(callback, *args)

Most asyncio objects are not thread safe. You should only worry if you access objects outside the event loop. For example, to cancel a future, don’t call directly its Future.cancel() method, but:

loop.call_soon_threadsafe(fut.cancel)

To handle signals and to execute subprocesses, the event loop must be run in the main thread.

To schedule a coroutine object from a different thread, the run_coroutine_threadsafe() function should be used. It returns a concurrent.futures.Future to access the result:

future = asyncio.run_coroutine_threadsafe(coro_func(), loop)
result = future.result(timeout)  # Wait for the result with a timeout

The AbstractEventLoop.run_in_executor() method can be used with a thread pool executor to execute a callback in different thread to not block the thread of the event loop.

Voir aussi

The Synchronization primitives section describes ways to synchronize tasks.

The Subprocess and threads section lists asyncio limitations to run subprocesses from different threads.

18.5.9.4. Gérer les fonctions bloquantes correctement

Blocking functions should not be called directly. For example, if a function blocks for 1 second, other tasks are delayed by 1 second which can have an important impact on reactivity.

For networking and subprocesses, the asyncio module provides high-level APIs like protocols.

An executor can be used to run a task in a different thread or even in a different process, to not block the thread of the event loop. See the AbstractEventLoop.run_in_executor() method.

Voir aussi

The Delayed calls section details how the event loop handles time.

18.5.9.5. Journalisation

The asyncio module logs information with the logging module in the logger 'asyncio'.

The default log level for the asyncio module is logging.INFO. For those not wanting such verbosity from asyncio the log level can be changed. For example, to change the level to logging.WARNING:

logging.getLogger('asyncio').setLevel(logging.WARNING)

18.5.9.6. Détecte les coroutines qui ne sont jamais exécutées

When a coroutine function is called and its result is not passed to ensure_future() or to the AbstractEventLoop.create_task() method, the execution of the coroutine object will never be scheduled which is probably a bug. Enable the debug mode of asyncio to log a warning to detect it.

Exemple avec le bug :

import asyncio

@asyncio.coroutine
def test():
    print("never scheduled")

test()

Affichage en mode débogage :

Coroutine test() at test.py:3 was never yielded from
Coroutine object created at (most recent call last):
  File "test.py", line 7, in <module>
    test()

The fix is to call the ensure_future() function or the AbstractEventLoop.create_task() method with the coroutine object.

Voir aussi

Pending task destroyed.

18.5.9.7. Detect exceptions never consumed

Python usually calls sys.excepthook() on unhandled exceptions. If Future.set_exception() is called, but the exception is never consumed, sys.excepthook() is not called. Instead, a log is emitted when the future is deleted by the garbage collector, with the traceback where the exception was raised.

Example of unhandled exception:

import asyncio

@asyncio.coroutine
def bug():
    raise Exception("not consumed")

loop = asyncio.get_event_loop()
asyncio.ensure_future(bug())
loop.run_forever()
loop.close()

Sortie :

Task exception was never retrieved
future: <Task finished coro=<coro() done, defined at asyncio/coroutines.py:139> exception=Exception('not consumed',)>
Traceback (most recent call last):
  File "asyncio/tasks.py", line 237, in _step
    result = next(coro)
  File "asyncio/coroutines.py", line 141, in coro
    res = func(*args, **kw)
  File "test.py", line 5, in bug
    raise Exception("not consumed")
Exception: not consumed

Enable the debug mode of asyncio to get the traceback where the task was created. Output in debug mode:

Task exception was never retrieved
future: <Task finished coro=<bug() done, defined at test.py:3> exception=Exception('not consumed',) created at test.py:8>
source_traceback: Object created at (most recent call last):
  File "test.py", line 8, in <module>
    asyncio.ensure_future(bug())
Traceback (most recent call last):
  File "asyncio/tasks.py", line 237, in _step
    result = next(coro)
  File "asyncio/coroutines.py", line 79, in __next__
    return next(self.gen)
  File "asyncio/coroutines.py", line 141, in coro
    res = func(*args, **kw)
  File "test.py", line 5, in bug
    raise Exception("not consumed")
Exception: not consumed

There are different options to fix this issue. The first option is to chain the coroutine in another coroutine and use classic try/except:

@asyncio.coroutine
def handle_exception():
    try:
        yield from bug()
    except Exception:
        print("exception consumed")

loop = asyncio.get_event_loop()
asyncio.ensure_future(handle_exception())
loop.run_forever()
loop.close()

Another option is to use the AbstractEventLoop.run_until_complete() function:

task = asyncio.ensure_future(bug())
try:
    loop.run_until_complete(task)
except Exception:
    print("exception consumed")

Voir aussi

La méthode Future.exception().

18.5.9.8. Chaîner les coroutines correctement

When a coroutine function calls other coroutine functions and tasks, they should be chained explicitly with yield from. Otherwise, the execution is not guaranteed to be sequential.

Example with different bugs using asyncio.sleep() to simulate slow operations:

import asyncio

@asyncio.coroutine
def create():
    yield from asyncio.sleep(3.0)
    print("(1) create file")

@asyncio.coroutine
def write():
    yield from asyncio.sleep(1.0)
    print("(2) write into file")

@asyncio.coroutine
def close():
    print("(3) close file")

@asyncio.coroutine
def test():
    asyncio.ensure_future(create())
    asyncio.ensure_future(write())
    asyncio.ensure_future(close())
    yield from asyncio.sleep(2.0)
    loop.stop()

loop = asyncio.get_event_loop()
asyncio.ensure_future(test())
loop.run_forever()
print("Pending tasks at exit: %s" % asyncio.Task.all_tasks(loop))
loop.close()

Expected output:

(1) create file
(2) write into file
(3) close file
Pending tasks at exit: set()

Affichage obtenu :

(3) close file
(2) write into file
Pending tasks at exit: {<Task pending create() at test.py:7 wait_for=<Future pending cb=[Task._wakeup()]>>}
Task was destroyed but it is pending!
task: <Task pending create() done at test.py:5 wait_for=<Future pending cb=[Task._wakeup()]>>

The loop stopped before the create() finished, close() has been called before write(), whereas coroutine functions were called in this order: create(), write(), close().

To fix the example, tasks must be marked with yield from:

@asyncio.coroutine
def test():
    yield from asyncio.ensure_future(create())
    yield from asyncio.ensure_future(write())
    yield from asyncio.ensure_future(close())
    yield from asyncio.sleep(2.0)
    loop.stop()

Ou sans asyncio.ensure_future() :

@asyncio.coroutine
def test():
    yield from create()
    yield from write()
    yield from close()
    yield from asyncio.sleep(2.0)
    loop.stop()

18.5.9.9. Pending task destroyed

If a pending task is destroyed, the execution of its wrapped coroutine did not complete. It is probably a bug and so a warning is logged.

Example of log:

Task was destroyed but it is pending!
task: <Task pending coro=<kill_me() done, defined at test.py:5> wait_for=<Future pending cb=[Task._wakeup()]>>

Enable the debug mode of asyncio to get the traceback where the task was created. Example of log in debug mode:

Task was destroyed but it is pending!
source_traceback: Object created at (most recent call last):
  File "test.py", line 15, in <module>
    task = asyncio.ensure_future(coro, loop=loop)
task: <Task pending coro=<kill_me() done, defined at test.py:5> wait_for=<Future pending cb=[Task._wakeup()] created at test.py:7> created at test.py:15>

Voir aussi

Detect coroutine objects never scheduled.

18.5.9.10. Close transports and event loops

When a transport is no more needed, call its close() method to release resources. Event loops must also be closed explicitly.

If a transport or an event loop is not closed explicitly, a ResourceWarning warning will be emitted in its destructor. By default, ResourceWarning warnings are ignored. The Debug mode of asyncio section explains how to display them.

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18.6. asyncore — Gestionnaire de socket asynchrone

Code source : Lib/asyncore.py [https://github.com/python/cpython/tree/3.6/Lib/asyncore.py]

Obsolète depuis la version 3.6: Utilisez asyncio à la place.

Note

Ce module n’existe que pour des raisons de rétrocompatibilité. Pour du code nouveau, l’utilisation de asyncio est recommandée.

This module provides the basic infrastructure for writing asynchronous socket service clients and servers.

There are only two ways to have a program on a single processor do « more than one thing at a time. » Multi-threaded programming is the simplest and most popular way to do it, but there is another very different technique, that lets you have nearly all the advantages of multi-threading, without actually using multiple threads. It’s really only practical if your program is largely I/O bound. If your program is processor bound, then pre-emptive scheduled threads are probably what you really need. Network servers are rarely processor bound, however.

If your operating system supports the select() system call in its I/O library (and nearly all do), then you can use it to juggle multiple communication channels at once; doing other work while your I/O is taking place in the « background. » Although this strategy can seem strange and complex, especially at first, it is in many ways easier to understand and control than multi-threaded programming. The asyncore module solves many of the difficult problems for you, making the task of building sophisticated high-performance network servers and clients a snap. For « conversational » applications and protocols the companion asynchat module is invaluable.

The basic idea behind both modules is to create one or more network channels, instances of class asyncore.dispatcher and asynchat.async_chat. Creating the channels adds them to a global map, used by the loop() function if you do not provide it with your own map.

Once the initial channel(s) is(are) created, calling the loop() function activates channel service, which continues until the last channel (including any that have been added to the map during asynchronous service) is closed.

asyncore.loop([timeout[, use_poll[, map[, count]]]])

Enter a polling loop that terminates after count passes or all open channels have been closed. All arguments are optional. The count parameter defaults to None, resulting in the loop terminating only when all channels have been closed. The timeout argument sets the timeout parameter for the appropriate select() or poll() call, measured in seconds; the default is 30 seconds. The use_poll parameter, if true, indicates that poll() should be used in preference to select() (the default is False).

The map parameter is a dictionary whose items are the channels to watch. As channels are closed they are deleted from their map. If map is omitted, a global map is used. Channels (instances of asyncore.dispatcher, asynchat.async_chat and subclasses thereof) can freely be mixed in the map.

class asyncore.dispatcher

The dispatcher class is a thin wrapper around a low-level socket object. To make it more useful, it has a few methods for event-handling which are called from the asynchronous loop. Otherwise, it can be treated as a normal non-blocking socket object.

The firing of low-level events at certain times or in certain connection states tells the asynchronous loop that certain higher-level events have taken place. For example, if we have asked for a socket to connect to another host, we know that the connection has been made when the socket becomes writable for the first time (at this point you know that you may write to it with the expectation of success). The implied higher-level events are:

Event

Description

handle_connect()

Implied by the first read or write event

handle_close()

Implied by a read event with no data available

handle_accepted()

Implied by a read event on a listening socket

During asynchronous processing, each mapped channel’s readable() and writable() methods are used to determine whether the channel’s socket should be added to the list of channels select()ed or poll()ed for read and write events.

Thus, the set of channel events is larger than the basic socket events. The full set of methods that can be overridden in your subclass follows:

handle_read()

Called when the asynchronous loop detects that a read() call on the channel’s socket will succeed.

handle_write()

Called when the asynchronous loop detects that a writable socket can be written. Often this method will implement the necessary buffering for performance. For example:

def handle_write(self):
    sent = self.send(self.buffer)
    self.buffer = self.buffer[sent:]

handle_expt()

Called when there is out of band (OOB) data for a socket connection. This will almost never happen, as OOB is tenuously supported and rarely used.

handle_connect()

Called when the active opener’s socket actually makes a connection. Might send a « welcome » banner, or initiate a protocol negotiation with the remote endpoint, for example.

handle_close()

Appelé lorsque la socket est fermée.

handle_error()

Called when an exception is raised and not otherwise handled. The default version prints a condensed traceback.

handle_accept()

Called on listening channels (passive openers) when a connection can be established with a new remote endpoint that has issued a connect() call for the local endpoint. Deprecated in version 3.2; use handle_accepted() instead.

Obsolète depuis la version 3.2.

handle_accepted(sock, addr)

Called on listening channels (passive openers) when a connection has been established with a new remote endpoint that has issued a connect() call for the local endpoint. sock is a new socket object usable to send and receive data on the connection, and addr is the address bound to the socket on the other end of the connection.

Nouveau dans la version 3.2.

readable()

Called each time around the asynchronous loop to determine whether a channel’s socket should be added to the list on which read events can occur. The default method simply returns True, indicating that by default, all channels will be interested in read events.

writable()

Called each time around the asynchronous loop to determine whether a channel’s socket should be added to the list on which write events can occur. The default method simply returns True, indicating that by default, all channels will be interested in write events.

In addition, each channel delegates or extends many of the socket methods. Most of these are nearly identical to their socket partners.

create_socket(family=socket.AF_INET, type=socket.SOCK_STREAM)

This is identical to the creation of a normal socket, and will use the same options for creation. Refer to the socket documentation for information on creating sockets.

Modifié dans la version 3.3: Les arguments family et type sont optionnels.

connect(address)

As with the normal socket object, address is a tuple with the first element the host to connect to, and the second the port number.

send(data)

Envoie data à l’autre bout de la socket.

recv(buffer_size)

Read at most buffer_size bytes from the socket’s remote end-point. An empty bytes object implies that the channel has been closed from the other end.

Note that recv() may raise BlockingIOError , even though select.select() or select.poll() has reported the socket ready for reading.

listen(backlog)

Listen for connections made to the socket. The backlog argument specifies the maximum number of queued connections and should be at least 1; the maximum value is system-dependent (usually 5).

bind(address)

Bind the socket to address. The socket must not already be bound. (The format of address depends on the address family — refer to the socket documentation for more information.) To mark the socket as re-usable (setting the SO_REUSEADDR option), call the dispatcher object’s set_reuse_addr() method.

accept()

Accept a connection. The socket must be bound to an address and listening for connections. The return value can be either None or a pair (conn, address) where conn is a new socket object usable to send and receive data on the connection, and address is the address bound to the socket on the other end of the connection. When None is returned it means the connection didn’t take place, in which case the server should just ignore this event and keep listening for further incoming connections.

close()

Close the socket. All future operations on the socket object will fail. The remote end-point will receive no more data (after queued data is flushed). Sockets are automatically closed when they are garbage-collected.

class asyncore.dispatcher_with_send

A dispatcher subclass which adds simple buffered output capability, useful for simple clients. For more sophisticated usage use asynchat.async_chat.

class asyncore.file_dispatcher

A file_dispatcher takes a file descriptor or file object along with an optional map argument and wraps it for use with the poll() or loop() functions. If provided a file object or anything with a fileno() method, that method will be called and passed to the file_wrapper constructor. Availability: UNIX.

class asyncore.file_wrapper

A file_wrapper takes an integer file descriptor and calls os.dup() to duplicate the handle so that the original handle may be closed independently of the file_wrapper. This class implements sufficient methods to emulate a socket for use by the file_dispatcher class. Availability: UNIX.

18.6.1. Exemple de client HTTP basique avec asyncore

Here is a very basic HTTP client that uses the dispatcher class to implement its socket handling:

import asyncore

class HTTPClient(asyncore.dispatcher):

    def __init__(self, host, path):
        asyncore.dispatcher.__init__(self)
        self.create_socket()
        self.connect( (host, 80) )
        self.buffer = bytes('GET %s HTTP/1.0\r\nHost: %s\r\n\r\n' %
                            (path, host), 'ascii')

    def handle_connect(self):
        pass

    def handle_close(self):
        self.close()

    def handle_read(self):
        print(self.recv(8192))

    def writable(self):
        return (len(self.buffer) > 0)

    def handle_write(self):
        sent = self.send(self.buffer)
        self.buffer = self.buffer[sent:]

client = HTTPClient('www.python.org', '/')
asyncore.loop()

18.6.2. Serveur echo basique avec asyncore

Here is a basic echo server that uses the dispatcher class to accept connections and dispatches the incoming connections to a handler:

import asyncore

class EchoHandler(asyncore.dispatcher_with_send):

    def handle_read(self):
        data = self.recv(8192)
        if data:
            self.send(data)

class EchoServer(asyncore.dispatcher):

    def __init__(self, host, port):
        asyncore.dispatcher.__init__(self)
        self.create_socket()
        self.set_reuse_addr()
        self.bind((host, port))
        self.listen(5)

    def handle_accepted(self, sock, addr):
        print('Incoming connection from %s' % repr(addr))
        handler = EchoHandler(sock)

server = EchoServer('localhost', 8080)
asyncore.loop()

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18.7. asynchat — Gestionnaire d’interfaces de connexion (socket) commande/réponse asynchrones

Code source :* Lib/asynchat.py [https://github.com/python/cpython/tree/3.6/Lib/asynchat.py]

Obsolète depuis la version 3.6: Utilisez asyncio à la place.

Note

Ce module n’existe que pour des raisons de rétrocompatibilité. Pour du code nouveau, l’utilisation de asyncio est recommandée.

Ce module s’appuie sur l’infrastructure de asyncore, en simplifiant les clients et serveurs asynchrones et en rendant plus facile la gestion de protocoles dont les éléments finissent par une chaine arbitraire, ou sont de longueur variable. asynchat définit une classe abstraite async_chat dont vous héritez, et qui fournit des implémentations des méthodes collect_incoming_data() et found_terminator(). Il utilise la même boucle asynchrone que asyncore, et deux types de canaux, asyncore.dispatcher et asynchat.async_chat, qui peuvent être librement mélangés dans la carte des canaux. Habituellement, un canal de serveur asyncore.dispatcher génère de nouveaux canaux d’objets asynchat.async_chat à la réception de requêtes de connexion.

class asynchat.async_chat

Cette classe est une sous-classe abstraite de asyncore.dispatcher. Pour en faire un usage pratique, vous devez créer une classe héritant de async_chat, et implémentant des méthodes collect_incoming_data() et found_terminator() sensées. Les méthodes de asyncore.dispatcher peuvent être utilisées, même si toutes n’ont pas de sens dans un contexte de messages/réponse.

Comme asyncore.dispatcher, async_chat définit un ensemble d’événements générés par une analyse de l’état des interfaces de connexion (socket en anglais) après un appel à select(). Une fois que la boucle de scrutation (polling en anglais) a été lancée, les méthodes des objets async_chat sont appelées par le framework de traitement d’événements sans que le programmeur n’ait à le spécifier.

Deux attributs de classe peuvent être modifiés, pour améliorer la performance, ou potentiellement pour économiser de la mémoire.

ac_in_buffer_size

La taille du tampon d’entrées asynchrones (4096 par défaut).

ac_out_buffer_size

La taille du tampon de sorties asynchrones (4096 par défaut).

Contrairement à asyncore.dispatcher, async_chat permet de définir une queue FIFO de producteurs. Un producteur nécessite seulement une méthode, more(), qui renvoie la donnée à transmettre au canal. Le producteur indique son épuisement (c.-à-d. qu’il ne contiens plus de données) en ne retournant avec sa méthode more() l’objet bytes vide. L’objet async_chat retire alors le producteur de la queue et commence à utiliser le producteur suivant, si il y en à un. Quand la queue de producteurs est vide, la méthode handle_write() ne fait rien. La méthode set_terminator() de l’objet du canal est utilisé pour décrire comment reconnaître la fin, ou la présence d’un point d’arrêt, dans in transmission entrante depuis le point d’accès distant.

Pour construire une sous classe fonctionnelle de async_chat pour vos méthodes d’entrées collect_incoming_data() et found_terminator() doivent gérer la donnée que le canal reçoit de manière asynchrone. Ces méthodes sont décrites ci-dessous.

async_chat.close_when_done()

Pousse un None sur la pile de producteurs. Quand ce producteur est récupéré dans la queue, le canal est fermé.

async_chat.collect_incoming_data(data)

Appelé avec data contenant une quantité arbitraire de données. La méthode par défaut, qui doit être écrasée, lève une NotImplementedError.

async_chat.discard_buffers()

En cas d’urgence, cette méthode va supprimer tout donnée présente dans les tampons d’entrée et/ou de sortie dans la queue de producteurs.

async_chat.found_terminator()

Appelée quand le flux de donné corresponds à la condition de fin décrite par set_terminator(). La méthode par défaut, qui doit être écrasée, lève une NotImplementedError. Les données entrantes mise en tampon devraient être disponible via un attribut de l’instance.

async_chat.get_terminator()

Renvoie le terminateur courant pour le canal.

async_chat.push(data)

Pousse data sur la pile du canal pour assurer sa transmission. C’est tout ce dont on a besoin pour que le canal envoie des données sur le réseau. Cependant, il est possible d’utiliser vos propres producteurs dans des schémas plus complexes qui implémentent de la cryptographie et du chunking par exemple.

async_chat.push_with_producer(producer)

Prends un objet producteur l’ajoute à la queue de producteurs associée au canal. Quand tout les producteurs actuellement poussés ont été épuisé, le canal consomme les données de ce producteur en appelant sa méthode more() et envoie les données au point d’accès distant.

async_chat.set_terminator(term)

Définit le marqueur de fin que le canal doit reconnaître. term peut être n’importe lequel des trois types de valeurs, correspondant aux trois différentes manières de gérer les données entrantes.

term

Description

string

Appellera found_terminator() quand la chaîne est trouvée dans le flux d’entré

integer

Appellera found_terminator() quand le nombre de caractère indiqué à été reçu

None

Le canal continue de collecter des informations indéfiniment

Notez que toute donnée située après le marqueur de fin sera accessible en lecture par le canal après que found_terminator() ai été appelé.

18.7.1. Exemple asynchat

L’exemple partiel suivant montre comment des requêtes HTTP peuvent être lues avec async_chat. Un serveur web pourrait créer un objet http_request_handler pour chaque connections lient entrantes. Notez que initialement, le marqueur de fin du canal est défini pour reconnaître les lignes vides à la fin des entêtes HTTP, et une option indique que les entêtes sont en train d’être lues.

Une fois que les entêtes ont été lues, si la requête est de type POST (ce qui indique que davantage de données sont présent dans dans le flux entrant) alors l’entête Content-Length: est utilisé pour définir un marqueur de fin numérique pour lire la bonne quantité de donné depuis le canal.

La méthode handle_request() est appelée une fois que toutes les données pertinentes ont été rassemblées, après avoir définit le marqueur de fin à None pour s’assurer que toute données étrangères envoyées par le client web sont ignorées.

import asynchat

class http_request_handler(asynchat.async_chat):

    def __init__(self, sock, addr, sessions, log):
        asynchat.async_chat.__init__(self, sock=sock)
        self.addr = addr
        self.sessions = sessions
        self.ibuffer = []
        self.obuffer = b""
        self.set_terminator(b"\r\n\r\n")
        self.reading_headers = True
        self.handling = False
        self.cgi_data = None
        self.log = log

    def collect_incoming_data(self, data):
        """Buffer the data"""
        self.ibuffer.append(data)

    def found_terminator(self):
        if self.reading_headers:
            self.reading_headers = False
            self.parse_headers(b"".join(self.ibuffer))
            self.ibuffer = []
            if self.op.upper() == b"POST":
                clen = self.headers.getheader("content-length")
                self.set_terminator(int(clen))
            else:
                self.handling = True
                self.set_terminator(None)
                self.handle_request()
        elif not self.handling:
            self.set_terminator(None)  # browsers sometimes over-send
            self.cgi_data = parse(self.headers, b"".join(self.ibuffer))
            self.handling = True
            self.ibuffer = []
            self.handle_request()

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18.8. signal — Set handlers for asynchronous events

This module provides mechanisms to use signal handlers in Python.

18.8.1. General rules

The signal.signal() function allows defining custom handlers to be executed when a signal is received. A small number of default handlers are installed: SIGPIPE is ignored (so write errors on pipes and sockets can be reported as ordinary Python exceptions) and SIGINT is translated into a KeyboardInterrupt exception.

A handler for a particular signal, once set, remains installed until it is explicitly reset (Python emulates the BSD style interface regardless of the underlying implementation), with the exception of the handler for SIGCHLD, which follows the underlying implementation.

18.8.1.1. Execution of Python signal handlers

A Python signal handler does not get executed inside the low-level (C) signal handler. Instead, the low-level signal handler sets a flag which tells the virtual machine to execute the corresponding Python signal handler at a later point(for example at the next bytecode instruction). This has consequences:

It makes little sense to catch synchronous errors like SIGFPE or SIGSEGV that are caused by an invalid operation in C code. Python will return from the signal handler to the C code, which is likely to raise the same signal again, causing Python to apparently hang. From Python 3.3 onwards, you can use the faulthandler module to report on synchronous errors.

A long-running calculation implemented purely in C (such as regular expression matching on a large body of text) may run uninterrupted for an arbitrary amount of time, regardless of any signals received. The Python signal handlers will be called when the calculation finishes.

18.8.1.2. Signals and threads

Python signal handlers are always executed in the main Python thread, even if the signal was received in another thread. This means that signals can’t be used as a means of inter-thread communication. You can use the synchronization primitives from the threading module instead.

Besides, only the main thread is allowed to set a new signal handler.

18.8.2. Module contents

Modifié dans la version 3.5: signal (SIG*), handler (SIG_DFL, SIG_IGN) and sigmask (SIG_BLOCK, SIG_UNBLOCK, SIG_SETMASK) related constants listed below were turned into enums. getsignal(), pthread_sigmask(), sigpending() and sigwait() functions return human-readable enums.

The variables defined in the signal module are:

signal.SIG_DFL

This is one of two standard signal handling options; it will simply perform the default function for the signal. For example, on most systems the default action for SIGQUIT is to dump core and exit, while the default action for SIGCHLD is to simply ignore it.

signal.SIG_IGN

This is another standard signal handler, which will simply ignore the given signal.

SIG*

All the signal numbers are defined symbolically. For example, the hangup signal is defined as signal.SIGHUP; the variable names are identical to the names used in C programs, as found in <signal.h>. The Unix man page for “signal()” lists the existing signals (on some systems this is signal(2), on others the list is in signal(7)). Note that not all systems define the same set of signal names; only those names defined by the system are defined by this module.

signal.CTRL_C_EVENT

The signal corresponding to the Ctrl+C keystroke event. This signal can only be used with os.kill().

Disponibilité : Windows.

Nouveau dans la version 3.2.

signal.CTRL_BREAK_EVENT

The signal corresponding to the Ctrl+Break keystroke event. This signal can only be used with os.kill().

Disponibilité : Windows.

Nouveau dans la version 3.2.

signal.NSIG

One more than the number of the highest signal number.

signal.ITIMER_REAL

Decrements interval timer in real time, and delivers SIGALRM upon expiration.

signal.ITIMER_VIRTUAL

Decrements interval timer only when the process is executing, and delivers SIGVTALRM upon expiration.

signal.ITIMER_PROF

Decrements interval timer both when the process executes and when the system is executing on behalf of the process. Coupled with ITIMER_VIRTUAL, this timer is usually used to profile the time spent by the application in user and kernel space. SIGPROF is delivered upon expiration.

signal.SIG_BLOCK

A possible value for the how parameter to pthread_sigmask() indicating that signals are to be blocked.

Nouveau dans la version 3.3.

signal.SIG_UNBLOCK

A possible value for the how parameter to pthread_sigmask() indicating that signals are to be unblocked.

Nouveau dans la version 3.3.

signal.SIG_SETMASK

A possible value for the how parameter to pthread_sigmask() indicating that the signal mask is to be replaced.

Nouveau dans la version 3.3.

The signal module defines one exception:

exception signal.ItimerError

Raised to signal an error from the underlying setitimer() or getitimer() implementation. Expect this error if an invalid interval timer or a negative time is passed to setitimer(). This error is a subtype of OSError.

Nouveau dans la version 3.3: This error used to be a subtype of IOError, which is now an alias of OSError.

The signal module defines the following functions:

signal.alarm(time)

If time is non-zero, this function requests that a SIGALRM signal be sent to the process in time seconds. Any previously scheduled alarm is canceled (only one alarm can be scheduled at any time). The returned value is then the number of seconds before any previously set alarm was to have been delivered. If time is zero, no alarm is scheduled, and any scheduled alarm is canceled. If the return value is zero, no alarm is currently scheduled. (See the Unix man page alarm(2).) Availability: Unix.

signal.getsignal(signalnum)

Return the current signal handler for the signal signalnum. The returned value may be a callable Python object, or one of the special values signal.SIG_IGN, signal.SIG_DFL or None. Here, signal.SIG_IGN means that the signal was previously ignored, signal.SIG_DFL means that the default way of handling the signal was previously in use, and None means that the previous signal handler was not installed from Python.

signal.pause()

Cause the process to sleep until a signal is received; the appropriate handler will then be called. Returns nothing. Not on Windows. (See the Unix man page signal(2).)

See also sigwait(), sigwaitinfo(), sigtimedwait() and sigpending().

signal.pthread_kill(thread_id, signalnum)

Send the signal signalnum to the thread thread_id, another thread in the same process as the caller. The target thread can be executing any code (Python or not). However, if the target thread is executing the Python interpreter, the Python signal handlers will be executed by the main thread. Therefore, the only point of sending a signal to a particular Python thread would be to force a running system call to fail with InterruptedError.

Use threading.get_ident() or the ident attribute of threading.Thread objects to get a suitable value for thread_id.

If signalnum is 0, then no signal is sent, but error checking is still performed; this can be used to check if the target thread is still running.

Availability: Unix (see the man page pthread_kill(3) for further information).

See also os.kill().

Nouveau dans la version 3.3.

signal.pthread_sigmask(how, mask)

Fetch and/or change the signal mask of the calling thread. The signal mask is the set of signals whose delivery is currently blocked for the caller. Return the old signal mask as a set of signals.

The behavior of the call is dependent on the value of how, as follows.

SIG_BLOCK: The set of blocked signals is the union of the current set and the mask argument.

SIG_UNBLOCK: The signals in mask are removed from the current set of blocked signals. It is permissible to attempt to unblock a signal which is not blocked.

SIG_SETMASK: The set of blocked signals is set to the mask argument.

mask is a set of signal numbers (e.g. {signal.SIGINT, signal.SIGTERM}). Use range(1, signal.NSIG) for a full mask including all signals.

For example, signal.pthread_sigmask(signal.SIG_BLOCK, []) reads the signal mask of the calling thread.

Availability: Unix. See the man page sigprocmask(3) and pthread_sigmask(3) for further information.

See also pause(), sigpending() and sigwait().

Nouveau dans la version 3.3.

signal.setitimer(which, seconds[, interval])

Sets given interval timer (one of signal.ITIMER_REAL, signal.ITIMER_VIRTUAL or signal.ITIMER_PROF) specified by which to fire after seconds (float is accepted, different from alarm()) and after that every interval seconds. The interval timer specified by which can be cleared by setting seconds to zero.

When an interval timer fires, a signal is sent to the process. The signal sent is dependent on the timer being used; signal.ITIMER_REAL will deliver SIGALRM, signal.ITIMER_VIRTUAL sends SIGVTALRM, and signal.ITIMER_PROF will deliver SIGPROF.

The old values are returned as a tuple: (delay, interval).

Attempting to pass an invalid interval timer will cause an ItimerError. Availability: Unix.

signal.getitimer(which)

Returns current value of a given interval timer specified by which. Availability: Unix.

signal.set_wakeup_fd(fd)

Set the wakeup file descriptor to fd. When a signal is received, the signal number is written as a single byte into the fd. This can be used by a library to wakeup a poll or select call, allowing the signal to be fully processed.

The old wakeup fd is returned (or -1 if file descriptor wakeup was not enabled). If fd is -1, file descriptor wakeup is disabled. If not -1, fd must be non-blocking. It is up to the library to remove any bytes from fd before calling poll or select again.

Use for example struct.unpack('%uB' % len(data), data) to decode the signal numbers list.

When threads are enabled, this function can only be called from the main thread; attempting to call it from other threads will cause a ValueError exception to be raised.

Modifié dans la version 3.5: On Windows, the function now also supports socket handles.

signal.siginterrupt(signalnum, flag)

Change system call restart behaviour: if flag is False, system calls will be restarted when interrupted by signal signalnum, otherwise system calls will be interrupted. Returns nothing. Availability: Unix (see the man page siginterrupt(3) for further information).

Note that installing a signal handler with signal() will reset the restart behaviour to interruptible by implicitly calling siginterrupt() with a true flag value for the given signal.

signal.signal(signalnum, handler)

Set the handler for signal signalnum to the function handler. handler can be a callable Python object taking two arguments (see below), or one of the special values signal.SIG_IGN or signal.SIG_DFL. The previous signal handler will be returned (see the description of getsignal() above). (See the Unix man page signal(2).)

When threads are enabled, this function can only be called from the main thread; attempting to call it from other threads will cause a ValueError exception to be raised.

The handler is called with two arguments: the signal number and the current stack frame (None or a frame object; for a description of frame objects, see the description in the type hierarchy or see the attribute descriptions in the inspect module).

On Windows, signal() can only be called with SIGABRT, SIGFPE, SIGILL, SIGINT, SIGSEGV, SIGTERM, or SIGBREAK. A ValueError will be raised in any other case. Note that not all systems define the same set of signal names; an AttributeError will be raised if a signal name is not defined as SIG* module level constant.

signal.sigpending()

Examine the set of signals that are pending for delivery to the calling thread (i.e., the signals which have been raised while blocked). Return the set of the pending signals.

Availability: Unix (see the man page sigpending(2) for further information).

See also pause(), pthread_sigmask() and sigwait().

Nouveau dans la version 3.3.

signal.sigwait(sigset)

Suspend execution of the calling thread until the delivery of one of the signals specified in the signal set sigset. The function accepts the signal (removes it from the pending list of signals), and returns the signal number.

Availability: Unix (see the man page sigwait(3) for further information).

See also pause(), pthread_sigmask(), sigpending(), sigwaitinfo() and sigtimedwait().

Nouveau dans la version 3.3.

signal.sigwaitinfo(sigset)

Suspend execution of the calling thread until the delivery of one of the signals specified in the signal set sigset. The function accepts the signal and removes it from the pending list of signals. If one of the signals in sigset is already pending for the calling thread, the function will return immediately with information about that signal. The signal handler is not called for the delivered signal. The function raises an InterruptedError if it is interrupted by a signal that is not in sigset.

The return value is an object representing the data contained in the siginfo_t structure, namely: si_signo, si_code, si_errno, si_pid, si_uid, si_status, si_band.

Availability: Unix (see the man page sigwaitinfo(2) for further information).

See also pause(), sigwait() and sigtimedwait().

Nouveau dans la version 3.3.

Modifié dans la version 3.5: The function is now retried if interrupted by a signal not in sigset and the signal handler does not raise an exception (see PEP 475 [https://www.python.org/dev/peps/pep-0475] for the rationale).

signal.sigtimedwait(sigset, timeout)

Like sigwaitinfo(), but takes an additional timeout argument specifying a timeout. If timeout is specified as 0, a poll is performed. Returns None if a timeout occurs.

Availability: Unix (see the man page sigtimedwait(2) for further information).

See also pause(), sigwait() and sigwaitinfo().

Nouveau dans la version 3.3.

Modifié dans la version 3.5: The function is now retried with the recomputed timeout if interrupted by a signal not in sigset and the signal handler does not raise an exception (see PEP 475 [https://www.python.org/dev/peps/pep-0475] for the rationale).

18.8.3. Exemple

Here is a minimal example program. It uses the alarm() function to limit the time spent waiting to open a file; this is useful if the file is for a serial device that may not be turned on, which would normally cause the os.open() to hang indefinitely. The solution is to set a 5-second alarm before opening the file; if the operation takes too long, the alarm signal will be sent, and the handler raises an exception.

import signal, os

def handler(signum, frame):
    print('Signal handler called with signal', signum)
    raise OSError("Couldn't open device!")

# Set the signal handler and a 5-second alarm
signal.signal(signal.SIGALRM, handler)
signal.alarm(5)

# This open() may hang indefinitely
fd = os.open('/dev/ttyS0', os.O_RDWR)

signal.alarm(0)          # Disable the alarm

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18.9. mmap — Memory-mapped file support

Memory-mapped file objects behave like both bytearray and like file objects. You can use mmap objects in most places where bytearray are expected; for example, you can use the re module to search through a memory-mapped file. You can also change a single byte by doing obj[index] = 97, or change a subsequence by assigning to a slice: obj[i1:i2] = b'...'. You can also read and write data starting at the current file position, and seek() through the file to different positions.

A memory-mapped file is created by the mmap constructor, which is different on Unix and on Windows. In either case you must provide a file descriptor for a file opened for update. If you wish to map an existing Python file object, use its fileno() method to obtain the correct value for the fileno parameter. Otherwise, you can open the file using the os.open() function, which returns a file descriptor directly (the file still needs to be closed when done).

Note

If you want to create a memory-mapping for a writable, buffered file, you should flush() the file first. This is necessary to ensure that local modifications to the buffers are actually available to the mapping.

For both the Unix and Windows versions of the constructor, access may be specified as an optional keyword parameter. access accepts one of three values: ACCESS_READ, ACCESS_WRITE, or ACCESS_COPY to specify read-only, write-through or copy-on-write memory respectively. access can be used on both Unix and Windows. If access is not specified, Windows mmap returns a write-through mapping. The initial memory values for all three access types are taken from the specified file. Assignment to an ACCESS_READ memory map raises a TypeError exception. Assignment to an ACCESS_WRITE memory map affects both memory and the underlying file. Assignment to an ACCESS_COPY memory map affects memory but does not update the underlying file.

To map anonymous memory, -1 should be passed as the fileno along with the length.

class mmap.mmap(fileno, length, tagname=None, access=ACCESS_DEFAULT[, offset])

(Windows version) Maps length bytes from the file specified by the file handle fileno, and creates a mmap object. If length is larger than the current size of the file, the file is extended to contain length bytes. If length is 0, the maximum length of the map is the current size of the file, except that if the file is empty Windows raises an exception (you cannot create an empty mapping on Windows).

tagname, if specified and not None, is a string giving a tag name for the mapping. Windows allows you to have many different mappings against the same file. If you specify the name of an existing tag, that tag is opened, otherwise a new tag of this name is created. If this parameter is omitted or None, the mapping is created without a name. Avoiding the use of the tag parameter will assist in keeping your code portable between Unix and Windows.

offset may be specified as a non-negative integer offset. mmap references will be relative to the offset from the beginning of the file. offset defaults to 0. offset must be a multiple of the ALLOCATIONGRANULARITY.

class mmap.mmap(fileno, length, flags=MAP_SHARED, prot=PROT_WRITE|PROT_READ, access=ACCESS_DEFAULT[, offset])

(Unix version) Maps length bytes from the file specified by the file descriptor fileno, and returns a mmap object. If length is 0, the maximum length of the map will be the current size of the file when mmap is called.

flags specifies the nature of the mapping. MAP_PRIVATE creates a private copy-on-write mapping, so changes to the contents of the mmap object will be private to this process, and MAP_SHARED creates a mapping that’s shared with all other processes mapping the same areas of the file. The default value is MAP_SHARED.

prot, if specified, gives the desired memory protection; the two most useful values are PROT_READ and PROT_WRITE, to specify that the pages may be read or written. prot defaults to PROT_READ | PROT_WRITE.

access may be specified in lieu of flags and prot as an optional keyword parameter. It is an error to specify both flags, prot and access. See the description of access above for information on how to use this parameter.

offset may be specified as a non-negative integer offset. mmap references will be relative to the offset from the beginning of the file. offset defaults to 0. offset must be a multiple of ALLOCATIONGRANULARITY which is equal to PAGESIZE on Unix systems.

To ensure validity of the created memory mapping the file specified by the descriptor fileno is internally automatically synchronized with physical backing store on Mac OS X and OpenVMS.

This example shows a simple way of using mmap:

import mmap

# write a simple example file
with open("hello.txt", "wb") as f:
    f.write(b"Hello Python!\n")

with open("hello.txt", "r+b") as f:
    # memory-map the file, size 0 means whole file
    mm = mmap.mmap(f.fileno(), 0)
    # read content via standard file methods
    print(mm.readline())  # prints b"Hello Python!\n"
    # read content via slice notation
    print(mm[:5])  # prints b"Hello"
    # update content using slice notation;
    # note that new content must have same size
    mm[6:] = b" world!\n"
    # ... and read again using standard file methods
    mm.seek(0)
    print(mm.readline())  # prints b"Hello  world!\n"
    # close the map
    mm.close()

mmap can also be used as a context manager in a with statement:

import mmap

with mmap.mmap(-1, 13) as mm:
    mm.write(b"Hello world!")

Nouveau dans la version 3.2: Context manager support.

The next example demonstrates how to create an anonymous map and exchange data between the parent and child processes:

import mmap
import os

mm = mmap.mmap(-1, 13)
mm.write(b"Hello world!")

pid = os.fork()

if pid == 0:  # In a child process
    mm.seek(0)
    print(mm.readline())

    mm.close()

Memory-mapped file objects support the following methods:

close()

Closes the mmap. Subsequent calls to other methods of the object will result in a ValueError exception being raised. This will not close the open file.

closed

True if the file is closed.

Nouveau dans la version 3.2.

find(sub[, start[, end]])

Returns the lowest index in the object where the subsequence sub is found, such that sub is contained in the range [start, end]. Optional arguments start and end are interpreted as in slice notation. Returns -1 on failure.

Modifié dans la version 3.5: N’importe quel bytes-like object est maintenant accepté.

flush([offset[, size]])

Flushes changes made to the in-memory copy of a file back to disk. Without use of this call there is no guarantee that changes are written back before the object is destroyed. If offset and size are specified, only changes to the given range of bytes will be flushed to disk; otherwise, the whole extent of the mapping is flushed. offset must be a multiple of the PAGESIZE or ALLOCATIONGRANULARITY.

(Windows version) A nonzero value returned indicates success; zero indicates failure.

(Unix version) A zero value is returned to indicate success. An exception is raised when the call failed.

move(dest, src, count)

Copy the count bytes starting at offset src to the destination index dest. If the mmap was created with ACCESS_READ, then calls to move will raise a TypeError exception.

read([n])

Return a bytes containing up to n bytes starting from the current file position. If the argument is omitted, None or negative, return all bytes from the current file position to the end of the mapping. The file position is updated to point after the bytes that were returned.

Modifié dans la version 3.3: Argument can be omitted or None.

read_byte()

Returns a byte at the current file position as an integer, and advances the file position by 1.

readline()

Returns a single line, starting at the current file position and up to the next newline.

resize(newsize)

Resizes the map and the underlying file, if any. If the mmap was created with ACCESS_READ or ACCESS_COPY, resizing the map will raise a TypeError exception.

rfind(sub[, start[, end]])

Returns the highest index in the object where the subsequence sub is found, such that sub is contained in the range [start, end]. Optional arguments start and end are interpreted as in slice notation. Returns -1 on failure.

Modifié dans la version 3.5: N’importe quel bytes-like object est maintenant accepté.

seek(pos[, whence])

Set the file’s current position. whence argument is optional and defaults to os.SEEK_SET or 0 (absolute file positioning); other values are os.SEEK_CUR or 1 (seek relative to the current position) and os.SEEK_END or 2 (seek relative to the file’s end).

size()

Return the length of the file, which can be larger than the size of the memory-mapped area.

tell()

Returns the current position of the file pointer.

write(bytes)

Write the bytes in bytes into memory at the current position of the file pointer and return the number of bytes written (never less than len(bytes), since if the write fails, a ValueError will be raised). The file position is updated to point after the bytes that were written. If the mmap was created with ACCESS_READ, then writing to it will raise a TypeError exception.

Modifié dans la version 3.5: N’importe quel bytes-like object est maintenant accepté.

Modifié dans la version 3.6: The number of bytes written is now returned.

write_byte(byte)

Write the integer byte into memory at the current position of the file pointer; the file position is advanced by 1. If the mmap was created with ACCESS_READ, then writing to it will raise a TypeError exception.

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19. Traitement des données provenant d’Internet

Ce chapitre décrit les modules qui prennent en charge le traitement des formats de données couramment utilisés sur Internet.

19.1. email — Un paquet de gestion des e-mails et MIME

19.1.1. email.message: Representing an email message

19.1.2. email.parser : Analyser des e-mails

19.1.2.1. API FeedParser

19.1.2.2. API de Parser

19.1.2.3. Notes complémentaires

19.1.3. email.generator: Generating MIME documents

19.1.4. email.policy: Policy Objects

19.1.5. email.errors: Exception and Defect classes

19.1.6. email.headerregistry: Custom Header Objects

19.1.7. email.contentmanager: Managing MIME Content

19.1.7.1. Content Manager Instances

19.1.8. email: Exemples

19.1.9. email.message.Message: Representing an email message using the compat32 API

19.1.10. email.mime: Creating email and MIME objects from scratch

19.1.11. email.header: Internationalized headers

19.1.12. email.charset: Representing character sets

19.1.13. email.encoders : Encodeurs

19.1.14. email.utils: Miscellaneous utilities

19.1.15. email.iterators: Itérateurs

19.2. json — Encodage et décodage JSON

19.2.1. Utilisation basique

19.2.2. Encodeurs et décodeurs

19.2.3. Exceptions

19.2.4. Conformité au standard et Interopérabilité

19.2.4.1. Encodage des caractères

19.2.4.2. Valeurs numériques infinies et NaN

19.2.4.3. Noms répétés au sein d’un objet

19.2.4.4. Valeurs de plus haut niveau autres qu’objets ou tableaux

19.2.4.5. Limitations de l’implémentation

19.2.5. Interface en ligne de commande

19.2.5.1. Options de la ligne de commande

19.3. mailcap — Manipulation de fichiers Mailcap

19.4. mailbox — Manipuler les boîtes de courriels dans différents formats

19.4.1. Objets Mailbox

19.4.1.1. Maildir

19.4.1.2. mbox

19.4.1.3. MH

19.4.1.4. Babyl

19.4.1.5. MMDF

19.4.2. Message objects

19.4.2.1. MaildirMessage

19.4.2.2. mboxMessage

19.4.2.3. MHMessage

19.4.2.4. BabylMessage

19.4.2.5. MMDFMessage

19.4.3. Exceptions

19.4.4. Exemples

19.5. mimetypes — Map filenames to MIME types

19.5.1. MimeTypes Objects

19.6. base64 — Encodages base16, base32, base64 et base85

19.7. binhex — Encode et décode les fichiers binhex4

19.7.1. Notes

19.8. binascii — Conversion entre binaire et ASCII

19.9. quopri — Encode et décode des données MIME quoted-printable

19.10. uu — Encode et décode les fichiers uuencode

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19.1. email — Un paquet de gestion des e-mails et MIME

Code source: Lib/email/__init__.py [https://github.com/python/cpython/tree/3.6/Lib/email/__init__.py]

Le paquet email est une bibliothèque pour gérer les e-mails. Il est spécifiquement conçu pour ne pas gérer les envois d’e-mails vers SMTP (RFC 2821 [https://tools.ietf.org/html/rfc2821.html]), NNTP, ou autres serveurs ; ces fonctions sont du ressort des modules comme smtplib et nntplib. Le paquet email tente de respecter les RFC autant que possible, il gère RFC 5233 [https://tools.ietf.org/html/rfc5233.html] et RFC 6532 [https://tools.ietf.org/html/rfc6532.html], ainsi que les RFCs en rapport avec les MIME comme RFC 2045 [https://tools.ietf.org/html/rfc2045.html], RFC 2046 [https://tools.ietf.org/html/rfc2046.html], RFC 2047 [https://tools.ietf.org/html/rfc2047.html], RFC 2183 [https://tools.ietf.org/html/rfc2183.html], et RFC 2231 [https://tools.ietf.org/html/rfc2231.html].

Ce paquet peut être divisé entre trois composants majeurs, et un quatrième composant qui contrôle le comportement des trois autres.

Le composant central du paquet est un « modèle d’objet » qui représente les messages. Une application interagit avec le paquet, dans un premier temps, à travers l’interface de modèle d’objet définie dans le sous-module message. L’application peut utiliser cette API pour poser des questions à propos d’un mail existant, pour créer un nouvel e-mail, ou ajouter ou retirer des sous-composants d’e-mail qui utilisent la même interface de modèle d’objet. Suivant la nature des messages et leurs sous-composants MIME, le modèle d’objet d’e-mail est une structure arborescente d’objets qui fournit tout à l’API de EmailMessage.

Les deux autres composants majeurs de ce paquet sont l’analyseur (parser) et le générateur (generator). L’analyseur prend la version sérialisée d’un e-mail (un flux d’octets) et le convertit en une arborescence d’objets EmailMessage. Le générateur prend un objet EmailMessage et le retransforme en un flux d’octets sérialisé (l’analyseur et le générateur gèrent aussi des suites de caractères textuels, mais cette utilisation est déconseillée car il est très facile de finir avec des messages invalides d’une manière ou d’une autre).

Le composant de contrôle est le module policy. Chaque EmailMessage, chaque generator et chaque parser possède un objet associé policy qui contrôle son comportement. Habituellement une application n’a besoin de spécifier la politique que quand un EmailMessage est créé, soit en instanciant directement un EmailMessage pour créer un nouvel e-mail, soit lors de l’analyse d’un flux entrant en utilisant un parser. Mais la politique peut être changée quand le message est sérialisé en utilisant un generator. Cela permet, par exemple, d’analyser un message e-mail générique du disque, puis de le sérialiser en utilisant une configuration SMTP standard quand on l’envoie vers un serveur d’e-mail.

Le paquet email fait son maximum pour cacher les détails des différentes RFCs de référence à l’application. Conceptuellement, l’application doit être capable de traiter l’e-mail comme une arborescence structurée de texte Unicode et de pièces jointes binaires, sans avoir à se préoccuper de leur représentation sérialisée. Dans la pratique, cependant, il est souvent nécessaire d’être conscient d’au moins quelques règles relatives aux messages MIME et à leur structure, en particulier les noms et natures des « types de contenus » et comment ils identifient les documents à plusieurs parties. Pour la plupart, cette connaissance devrait seulement être nécessaire pour des applications plus complexes, et même là, il devrait être question des structures de haut niveau et non des détails sur la manière dont elles sont représentées. Comme les types de contenus MIME sont couramment utilisés dans les logiciels internet modernes (et non uniquement les e-mails), les développeurs sont généralement familiers de ce concept.

La section suivante décrit les fonctionnalités du paquet email. Nous commençons avec le modèle d’objet message, qui est la principale interface qu’une application utilise, et continuons avec les composants parser et generator. Ensuite, nous couvrons les contrôles policy, qui complètent le traitement des principaux composants de la bibliothèque.

Les trois prochaines sections couvrent les exceptions que le paquet peut rencontrer et les imperfections (non-respect des RFCs) que le module parser peut détecter. Ensuite nous couvrons les sous-composants headerregistry et contentmanager, qui fournissent des outils pour faire des manipulations plus détaillées des en-têtes et du contenu, respectivement. Les deux composants contiennent des fonctionnalités adaptées pour traiter et produire des messages qui sortent de l’ordinaire, et elles documentent aussi leurs API pour pouvoir les étendre, ce qui ne manquera pas d’intéresser les applications avancées.

Ci-dessous se trouve un ensemble d’exemples d’utilisations des éléments fondamentaux des API couvertes dans les sections précédentes.

The foregoing represent the modern (unicode friendly) API of the email package. The remaining sections, starting with the Message class, cover the legacy compat32 API that deals much more directly with the details of how email messages are represented. The compat32 API does not hide the details of the RFCs from the application, but for applications that need to operate at that level, they can be useful tools. This documentation is also relevant for applications that are still using the compat32 API for backward compatibility reasons.

Modifié dans la version 3.6: Documents réorganisés et réécrits pour promouvoir la nouvelle API EmailMessage/EmailPolicy.

Contenus de la documentation du paquet email :

19.1.1. email.message: Representing an email message

19.1.2. email.parser : Analyser des e-mails

19.1.2.1. API FeedParser

19.1.2.2. API de Parser

19.1.2.3. Notes complémentaires

19.1.3. email.generator: Generating MIME documents

19.1.4. email.policy: Policy Objects

19.1.5. email.errors: Exception and Defect classes

19.1.6. email.headerregistry: Custom Header Objects

19.1.7. email.contentmanager: Managing MIME Content

19.1.7.1. Content Manager Instances

19.1.8. email: Exemples

API héritée :

19.1.9. email.message.Message: Representing an email message using the compat32 API

19.1.10. email.mime: Creating email and MIME objects from scratch

19.1.11. email.header: Internationalized headers

19.1.12. email.charset: Representing character sets

19.1.13. email.encoders : Encodeurs

19.1.14. email.utils: Miscellaneous utilities

19.1.15. email.iterators: Itérateurs

Voir aussi

Module smtplib

Client SMTP (Simple Mail Transport Protocol)

Module poplib

Client POP (Post Office Protocol)

Module imaplib

Client IMAP (Internet Message Access Protocol)

Module nntplib

Client NNTP (Net News Transport Protocol)

Module mailbox

Outils pour créer, lire et gérer des messages regroupés sur disque en utilisant des formats standards variés.

Module smtpd

Cadriciel pour serveur SMTP (principalement utile pour tester)

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19.1.1. email.message: Representing an email message

Source code: Lib/email/message.py [https://github.com/python/cpython/tree/3.6/Lib/email/message.py]

Nouveau dans la version 3.6: 1

The central class in the email package is the EmailMessage class, imported from the email.message module. It is the base class for the email object model. EmailMessage provides the core functionality for setting and querying header fields, for accessing message bodies, and for creating or modifying structured messages.

An email message consists of headers and a payload (which is also referred to as the content). Headers are RFC 5322 [https://tools.ietf.org/html/rfc5322.html] or RFC 6532 [https://tools.ietf.org/html/rfc6532.html] style field names and values, where the field name and value are separated by a colon. The colon is not part of either the field name or the field value. The payload may be a simple text message, or a binary object, or a structured sequence of sub-messages each with their own set of headers and their own payload. The latter type of payload is indicated by the message having a MIME type such as multipart/* or message/rfc822.

The conceptual model provided by an EmailMessage object is that of an ordered dictionary of headers coupled with a payload that represents the RFC 5322 [https://tools.ietf.org/html/rfc5322.html] body of the message, which might be a list of sub-EmailMessage objects. In addition to the normal dictionary methods for accessing the header names and values, there are methods for accessing specialized information from the headers (for example the MIME content type), for operating on the payload, for generating a serialized version of the message, and for recursively walking over the object tree.

The EmailMessage dictionary-like interface is indexed by the header names, which must be ASCII values. The values of the dictionary are strings with some extra methods. Headers are stored and returned in case-preserving form, but field names are matched case-insensitively. Unlike a real dict, there is an ordering to the keys, and there can be duplicate keys. Additional methods are provided for working with headers that have duplicate keys.

The payload is either a string or bytes object, in the case of simple message objects, or a list of EmailMessage objects, for MIME container documents such as multipart/* and message/rfc822 message objects.

class email.message.EmailMessage(policy=default)

If policy is specified use the rules it specifies to update and serialize the representation of the message. If policy is not set, use the default policy, which follows the rules of the email RFCs except for line endings (instead of the RFC mandated \r\n, it uses the Python standard \n line endings). For more information see the policy documentation.

as_string(unixfrom=False, maxheaderlen=None, policy=None)

Return the entire message flattened as a string. When optional unixfrom is true, the envelope header is included in the returned string. unixfrom defaults to False. For backward compatibility with the base Message class maxheaderlen is accepted, but defaults to None, which means that by default the line length is controlled by the max_line_length of the policy. The policy argument may be used to override the default policy obtained from the message instance. This can be used to control some of the formatting produced by the method, since the specified policy will be passed to the Generator.

Flattening the message may trigger changes to the EmailMessage if defaults need to be filled in to complete the transformation to a string (for example, MIME boundaries may be generated or modified).

Note that this method is provided as a convenience and may not be the most useful way to serialize messages in your application, especially if you are dealing with multiple messages. See email.generator.Generator for a more flexible API for serializing messages. Note also that this method is restricted to producing messages serialized as « 7 bit clean » when utf8 is False, which is the default.

Modifié dans la version 3.6: the default behavior when maxheaderlen is not specified was changed from defaulting to 0 to defaulting to the value of max_line_length from the policy.

__str__()

Equivalent to as_string(policy=self.policy.clone(utf8=True)). Allows str(msg) to produce a string containing the serialized message in a readable format.

Modifié dans la version 3.4: the method was changed to use utf8=True, thus producing an RFC 6531 [https://tools.ietf.org/html/rfc6531.html]-like message representation, instead of being a direct alias for as_string().

as_bytes(unixfrom=False, policy=None)

Return the entire message flattened as a bytes object. When optional unixfrom is true, the envelope header is included in the returned string. unixfrom defaults to False. The policy argument may be used to override the default policy obtained from the message instance. This can be used to control some of the formatting produced by the method, since the specified policy will be passed to the BytesGenerator.

Flattening the message may trigger changes to the EmailMessage if defaults need to be filled in to complete the transformation to a string (for example, MIME boundaries may be generated or modified).

Note that this method is provided as a convenience and may not be the most useful way to serialize messages in your application, especially if you are dealing with multiple messages. See email.generator.BytesGenerator for a more flexible API for serializing messages.

__bytes__()

Equivalent to as_bytes(). Allows bytes(msg) to produce a bytes object containing the serialized message.

is_multipart()

Return True if the message’s payload is a list of sub-EmailMessage objects, otherwise return False. When is_multipart() returns False, the payload should be a string object (which might be a CTE encoded binary payload). Note that is_multipart() returning True does not necessarily mean that « msg.get_content_maintype() == “multipart” » will return the True. For example, is_multipart will return True when the EmailMessage is of type message/rfc822.

set_unixfrom(unixfrom)

Set the message’s envelope header to unixfrom, which should be a string. (See mboxMessage for a brief description of this header.)

get_unixfrom()

Return the message’s envelope header. Defaults to None if the envelope header was never set.

The following methods implement the mapping-like interface for accessing the message’s headers. Note that there are some semantic differences between these methods and a normal mapping (i.e. dictionary) interface. For example, in a dictionary there are no duplicate keys, but here there may be duplicate message headers. Also, in dictionaries there is no guaranteed order to the keys returned by keys(), but in an EmailMessage object, headers are always returned in the order they appeared in the original message, or in which they were added to the message later. Any header deleted and then re-added is always appended to the end of the header list.

These semantic differences are intentional and are biased toward convenience in the most common use cases.

Note that in all cases, any envelope header present in the message is not included in the mapping interface.

__len__()

Return the total number of headers, including duplicates.

__contains__(name)

Return true if the message object has a field named name. Matching is done without regard to case and name does not include the trailing colon. Used for the in operator. For example:

if 'message-id' in myMessage:
   print('Message-ID:', myMessage['message-id'])

__getitem__(name)

Return the value of the named header field. name does not include the colon field separator. If the header is missing, None is returned; a KeyError is never raised.

Note that if the named field appears more than once in the message’s headers, exactly which of those field values will be returned is undefined. Use the get_all() method to get the values of all the extant headers named name.

Using the standard (non-compat32) policies, the returned value is an instance of a subclass of email.headerregistry.BaseHeader.

__setitem__(name, val)

Add a header to the message with field name name and value val. The field is appended to the end of the message’s existing headers.

Note that this does not overwrite or delete any existing header with the same name. If you want to ensure that the new header is the only one present in the message with field name name, delete the field first, e.g.:

del msg['subject']
msg['subject'] = 'Python roolz!'

If the policy defines certain headers to be unique (as the standard policies do), this method may raise a ValueError when an attempt is made to assign a value to such a header when one already exists. This behavior is intentional for consistency’s sake, but do not depend on it as we may choose to make such assignments do an automatic deletion of the existing header in the future.

__delitem__(name)

Delete all occurrences of the field with name name from the message’s headers. No exception is raised if the named field isn’t present in the headers.

keys()

Return a list of all the message’s header field names.

values()

Return a list of all the message’s field values.

items()

Return a list of 2-tuples containing all the message’s field headers and values.

get(name, failobj=None)

Return the value of the named header field. This is identical to __getitem__() except that optional failobj is returned if the named header is missing (failobj defaults to None).

Here are some additional useful header related methods:

get_all(name, failobj=None)

Return a list of all the values for the field named name. If there are no such named headers in the message, failobj is returned (defaults to None).

add_header(_name, _value, **_params)

Extended header setting. This method is similar to __setitem__() except that additional header parameters can be provided as keyword arguments. _name is the header field to add and _value is the primary value for the header.

For each item in the keyword argument dictionary _params, the key is taken as the parameter name, with underscores converted to dashes (since dashes are illegal in Python identifiers). Normally, the parameter will be added as key="value" unless the value is None, in which case only the key will be added.

If the value contains non-ASCII characters, the charset and language may be explicitly controlled by specifying the value as a three tuple in the format (CHARSET, LANGUAGE, VALUE), where CHARSET is a string naming the charset to be used to encode the value, LANGUAGE can usually be set to None or the empty string (see RFC 2231 [https://tools.ietf.org/html/rfc2231.html] for other possibilities), and VALUE is the string value containing non-ASCII code points. If a three tuple is not passed and the value contains non-ASCII characters, it is automatically encoded in RFC 2231 [https://tools.ietf.org/html/rfc2231.html] format using a CHARSET of utf-8 and a LANGUAGE of None.

Voici un exemple :

msg.add_header('Content-Disposition', 'attachment', filename='bud.gif')

This will add a header that looks like

Content-Disposition: attachment; filename="bud.gif"

An example of the extended interface with non-ASCII characters:

msg.add_header('Content-Disposition', 'attachment',
               filename=('iso-8859-1', '', 'Fußballer.ppt'))

replace_header(_name, _value)

Replace a header. Replace the first header found in the message that matches _name, retaining header order and field name case of the original header. If no matching header is found, raise a KeyError.

get_content_type()

Return the message’s content type, coerced to lower case of the form maintype/subtype. If there is no Content-Type header in the message return the value returned by get_default_type(). If the Content-Type header is invalid, return text/plain.

(According to RFC 2045 [https://tools.ietf.org/html/rfc2045.html], messages always have a default type, get_content_type() will always return a value. RFC 2045 [https://tools.ietf.org/html/rfc2045.html] defines a message’s default type to be text/plain unless it appears inside a multipart/digest container, in which case it would be message/rfc822. If the Content-Type header has an invalid type specification, RFC 2045 [https://tools.ietf.org/html/rfc2045.html] mandates that the default type be text/plain.)

get_content_maintype()

Return the message’s main content type. This is the maintype part of the string returned by get_content_type().

get_content_subtype()

Return the message’s sub-content type. This is the subtype part of the string returned by get_content_type().

get_default_type()

Return the default content type. Most messages have a default content type of text/plain, except for messages that are subparts of multipart/digest containers. Such subparts have a default content type of message/rfc822.

set_default_type(ctype)

Set the default content type. ctype should either be text/plain or message/rfc822, although this is not enforced. The default content type is not stored in the Content-Type header, so it only affects the return value of the get_content_type methods when no Content-Type header is present in the message.

set_param(param, value, header='Content-Type', requote=True, charset=None, language='', replace=False)

Set a parameter in the Content-Type header. If the parameter already exists in the header, replace its value with value. When header is Content-Type (the default) and the header does not yet exist in the message, add it, set its value to text/plain, and append the new parameter value. Optional header specifies an alternative header to Content-Type.

If the value contains non-ASCII characters, the charset and language may be explicitly specified using the optional charset and language parameters. Optional language specifies the RFC 2231 [https://tools.ietf.org/html/rfc2231.html] language, defaulting to the empty string. Both charset and language should be strings. The default is to use the utf8 charset and None for the language.

If replace is False (the default) the header is moved to the end of the list of headers. If replace is True, the header will be updated in place.

Use of the requote parameter with EmailMessage objects is deprecated.

Note that existing parameter values of headers may be accessed through the params attribute of the header value (for example, msg['Content-Type'].params['charset']).

Modifié dans la version 3.4: replace keyword was added.

del_param(param, header='content-type', requote=True)

Remove the given parameter completely from the Content-Type header. The header will be re-written in place without the parameter or its value. Optional header specifies an alternative to Content-Type.

Use of the requote parameter with EmailMessage objects is deprecated.

get_filename(failobj=None)

Return the value of the filename parameter of the Content-Disposition header of the message. If the header does not have a filename parameter, this method falls back to looking for the name parameter on the Content-Type header. If neither is found, or the header is missing, then failobj is returned. The returned string will always be unquoted as per email.utils.unquote().

get_boundary(failobj=None)

Return the value of the boundary parameter of the Content-Type header of the message, or failobj if either the header is missing, or has no boundary parameter. The returned string will always be unquoted as per email.utils.unquote().

set_boundary(boundary)

Set the boundary parameter of the Content-Type header to boundary. set_boundary() will always quote boundary if necessary. A HeaderParseError is raised if the message object has no Content-Type header.

Note that using this method is subtly different from deleting the old Content-Type header and adding a new one with the new boundary via add_header(), because set_boundary() preserves the order of the Content-Type header in the list of headers.

get_content_charset(failobj=None)

Return the charset parameter of the Content-Type header, coerced to lower case. If there is no Content-Type header, or if that header has no charset parameter, failobj is returned.

get_charsets(failobj=None)

Return a list containing the character set names in the message. If the message is a multipart, then the list will contain one element for each subpart in the payload, otherwise, it will be a list of length 1.

Each item in the list will be a string which is the value of the charset parameter in the Content-Type header for the represented subpart. If the subpart has no Content-Type header, no charset parameter, or is not of the text main MIME type, then that item in the returned list will be failobj.

is_attachment()

Return True if there is a Content-Disposition header and its (case insensitive) value is attachment, False otherwise.

Modifié dans la version 3.4.2: is_attachment is now a method instead of a property, for consistency with is_multipart().

get_content_disposition()

Return the lowercased value (without parameters) of the message’s Content-Disposition header if it has one, or None. The possible values for this method are inline, attachment or None if the message follows RFC 2183 [https://tools.ietf.org/html/rfc2183.html].

Nouveau dans la version 3.5.

The following methods relate to interrogating and manipulating the content (payload) of the message.

walk()

The walk() method is an all-purpose generator which can be used to iterate over all the parts and subparts of a message object tree, in depth-first traversal order. You will typically use walk() as the iterator in a for loop; each iteration returns the next subpart.

Here’s an example that prints the MIME type of every part of a multipart message structure:

>>> for part in msg.walk():
...     print(part.get_content_type())
multipart/report
text/plain
message/delivery-status
text/plain
text/plain
message/rfc822
text/plain

walk iterates over the subparts of any part where is_multipart() returns True, even though msg.get_content_maintype() == 'multipart' may return False. We can see this in our example by making use of the _structure debug helper function:

>>> for part in msg.walk():
...     print(part.get_content_maintype() == 'multipart',
...           part.is_multipart())
True True
False False
False True
False False
False False
False True
False False
>>> _structure(msg)
multipart/report
    text/plain
    message/delivery-status
        text/plain
        text/plain
    message/rfc822
        text/plain

Here the message parts are not multiparts, but they do contain subparts. is_multipart() returns True and walk descends into the subparts.

get_body(preferencelist=('related', 'html', 'plain'))

Return the MIME part that is the best candidate to be the « body » of the message.

preferencelist must be a sequence of strings from the set related, html, and plain, and indicates the order of preference for the content type of the part returned.

Start looking for candidate matches with the object on which the get_body method is called.

If related is not included in preferencelist, consider the root part (or subpart of the root part) of any related encountered as a candidate if the (sub-)part matches a preference.

When encountering a multipart/related, check the start parameter and if a part with a matching Content-ID is found, consider only it when looking for candidate matches. Otherwise consider only the first (default root) part of the multipart/related.

If a part has a Content-Disposition header, only consider the part a candidate match if the value of the header is inline.

If none of the candidates matches any of the preferences in preferencelist, return None.

Notes: (1) For most applications the only preferencelist combinations that really make sense are ('plain',), ('html', 'plain'), and the default ('related', 'html', 'plain'). (2) Because matching starts with the object on which get_body is called, calling get_body on a multipart/related will return the object itself unless preferencelist has a non-default value. (3) Messages (or message parts) that do not specify a Content-Type or whose Content-Type header is invalid will be treated as if they are of type text/plain, which may occasionally cause get_body to return unexpected results.

iter_attachments()

Return an iterator over all of the immediate sub-parts of the message that are not candidate « body » parts. That is, skip the first occurrence of each of text/plain, text/html, multipart/related, or multipart/alternative (unless they are explicitly marked as attachments via Content-Disposition: attachment), and return all remaining parts. When applied directly to a multipart/related, return an iterator over the all the related parts except the root part (ie: the part pointed to by the start parameter, or the first part if there is no start parameter or the start parameter doesn’t match the Content-ID of any of the parts). When applied directly to a multipart/alternative or a non-multipart, return an empty iterator.

iter_parts()

Return an iterator over all of the immediate sub-parts of the message, which will be empty for a non-multipart. (See also walk().)

get_content(*args, content_manager=None, **kw)

Call the get_content() method of the content_manager, passing self as the message object, and passing along any other arguments or keywords as additional arguments. If content_manager is not specified, use the content_manager specified by the current policy.

set_content(*args, content_manager=None, **kw)

Call the set_content() method of the content_manager, passing self as the message object, and passing along any other arguments or keywords as additional arguments. If content_manager is not specified, use the content_manager specified by the current policy.

make_related(boundary=None)

Convert a non-multipart message into a multipart/related message, moving any existing Content- headers and payload into a (new) first part of the multipart. If boundary is specified, use it as the boundary string in the multipart, otherwise leave the boundary to be automatically created when it is needed (for example, when the message is serialized).

make_alternative(boundary=None)

Convert a non-multipart or a multipart/related into a multipart/alternative, moving any existing Content- headers and payload into a (new) first part of the multipart. If boundary is specified, use it as the boundary string in the multipart, otherwise leave the boundary to be automatically created when it is needed (for example, when the message is serialized).

make_mixed(boundary=None)

Convert a non-multipart, a multipart/related, or a multipart-alternative into a multipart/mixed, moving any existing Content- headers and payload into a (new) first part of the multipart. If boundary is specified, use it as the boundary string in the multipart, otherwise leave the boundary to be automatically created when it is needed (for example, when the message is serialized).

add_related(*args, content_manager=None, **kw)

If the message is a multipart/related, create a new message object, pass all of the arguments to its set_content() method, and attach() it to the multipart. If the message is a non-multipart, call make_related() and then proceed as above. If the message is any other type of multipart, raise a TypeError. If content_manager is not specified, use the content_manager specified by the current policy. If the added part has no Content-Disposition header, add one with the value inline.

add_alternative(*args, content_manager=None, **kw)

If the message is a multipart/alternative, create a new message object, pass all of the arguments to its set_content() method, and attach() it to the multipart. If the message is a non-multipart or multipart/related, call make_alternative() and then proceed as above. If the message is any other type of multipart, raise a TypeError. If content_manager is not specified, use the content_manager specified by the current policy.

add_attachment(*args, content_manager=None, **kw)

If the message is a multipart/mixed, create a new message object, pass all of the arguments to its set_content() method, and attach() it to the multipart. If the message is a non-multipart, multipart/related, or multipart/alternative, call make_mixed() and then proceed as above. If content_manager is not specified, use the content_manager specified by the current policy. If the added part has no Content-Disposition header, add one with the value attachment. This method can be used both for explicit attachments (Content-Disposition: attachment) and inline attachments (Content-Disposition: inline), by passing appropriate options to the content_manager.

clear()

Remove the payload and all of the headers.

clear_content()

Remove the payload and all of the Content- headers, leaving all other headers intact and in their original order.

EmailMessage objects have the following instance attributes:

preamble

The format of a MIME document allows for some text between the blank line following the headers, and the first multipart boundary string. Normally, this text is never visible in a MIME-aware mail reader because it falls outside the standard MIME armor. However, when viewing the raw text of the message, or when viewing the message in a non-MIME aware reader, this text can become visible.

The preamble attribute contains this leading extra-armor text for MIME documents. When the Parser discovers some text after the headers but before the first boundary string, it assigns this text to the message’s preamble attribute. When the Generator is writing out the plain text representation of a MIME message, and it finds the message has a preamble attribute, it will write this text in the area between the headers and the first boundary. See email.parser and email.generator for details.

Note that if the message object has no preamble, the preamble attribute will be None.

epilogue

The epilogue attribute acts the same way as the preamble attribute, except that it contains text that appears between the last boundary and the end of the message. As with the preamble, if there is no epilog text this attribute will be None.

defects

The defects attribute contains a list of all the problems found when parsing this message. See email.errors for a detailed description of the possible parsing defects.

class email.message.MIMEPart(policy=default)

This class represents a subpart of a MIME message. It is identical to EmailMessage, except that no MIME-Version headers are added when set_content() is called, since sub-parts do not need their own MIME-Version headers.

Notes

1

Originally added in 3.4 as a provisional module. Docs for legacy message class moved to email.message.Message: Representing an email message using the compat32 API.

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19.1.2. email.parser : Analyser des e-mails

Code source : Lib/email/parser.py [https://github.com/python/cpython/tree/3.6/Lib/email/parser.py]

Les instances de messages peuvent être créées de deux façons : elles peuvent être créées de toutes pièces en créant un objet EmailMessage, en ajoutant des en-têtes en utilisant l’interface de dictionnaire, et en ajoutant un ou plusieurs corps de message en utilisant set_content() et les méthodes associées, ou ils peuvent être créées en analysant une représentation sérialisée de l’e-mail.

The email package provides a standard parser that understands most email document structures, including MIME documents. You can pass the parser a bytes, string or file object, and the parser will return to you the root EmailMessage instance of the object structure. For simple, non-MIME messages the payload of this root object will likely be a string containing the text of the message. For MIME messages, the root object will return True from its is_multipart() method, and the subparts can be accessed via the payload manipulation methods, such as get_body(), iter_parts(), and walk().

There are actually two parser interfaces available for use, the Parser API and the incremental FeedParser API. The Parser API is most useful if you have the entire text of the message in memory, or if the entire message lives in a file on the file system. FeedParser is more appropriate when you are reading the message from a stream which might block waiting for more input (such as reading an email message from a socket). The FeedParser can consume and parse the message incrementally, and only returns the root object when you close the parser.

Note that the parser can be extended in limited ways, and of course you can implement your own parser completely from scratch. All of the logic that connects the email package’s bundled parser and the EmailMessage class is embodied in the policy class, so a custom parser can create message object trees any way it finds necessary by implementing custom versions of the appropriate policy methods.

19.1.2.1. API FeedParser

The BytesFeedParser, imported from the email.feedparser module, provides an API that is conducive to incremental parsing of email messages, such as would be necessary when reading the text of an email message from a source that can block (such as a socket). The BytesFeedParser can of course be used to parse an email message fully contained in a bytes-like object, string, or file, but the BytesParser API may be more convenient for such use cases. The semantics and results of the two parser APIs are identical.

The BytesFeedParser’s API is simple; you create an instance, feed it a bunch of bytes until there’s no more to feed it, then close the parser to retrieve the root message object. The BytesFeedParser is extremely accurate when parsing standards-compliant messages, and it does a very good job of parsing non-compliant messages, providing information about how a message was deemed broken. It will populate a message object’s defects attribute with a list of any problems it found in a message. See the email.errors module for the list of defects that it can find.

Voici l’API pour BytesFeedParser :

class email.parser.BytesFeedParser(_factory=None, *, policy=policy.compat32)

Create a BytesFeedParser instance. Optional _factory is a no-argument callable; if not specified use the message_factory from the policy. Call _factory whenever a new message object is needed.

If policy is specified use the rules it specifies to update the representation of the message. If policy is not set, use the compat32 policy, which maintains backward compatibility with the Python 3.2 version of the email package and provides Message as the default factory. All other policies provide EmailMessage as the default _factory. For more information on what else policy controls, see the policy documentation.

Note: The policy keyword should always be specified; The default will change to email.policy.default in a future version of Python.

Nouveau dans la version 3.2.

Modifié dans la version 3.3: Added the policy keyword.

Modifié dans la version 3.6: _factory defaults to the policy message_factory.

feed(data)

Feed the parser some more data. data should be a bytes-like object containing one or more lines. The lines can be partial and the parser will stitch such partial lines together properly. The lines can have any of the three common line endings: carriage return, newline, or carriage return and newline (they can even be mixed).

close()

Complete the parsing of all previously fed data and return the root message object. It is undefined what happens if feed() is called after this method has been called.

class email.parser.FeedParser(_factory=None, *, policy=policy.compat32)

Works like BytesFeedParser except that the input to the feed() method must be a string. This is of limited utility, since the only way for such a message to be valid is for it to contain only ASCII text or, if utf8 is True, no binary attachments.

Modifié dans la version 3.3: Added the policy keyword.

19.1.2.2. API de Parser

The BytesParser class, imported from the email.parser module, provides an API that can be used to parse a message when the complete contents of the message are available in a bytes-like object or file. The email.parser module also provides Parser for parsing strings, and header-only parsers, BytesHeaderParser and HeaderParser, which can be used if you’re only interested in the headers of the message. BytesHeaderParser and HeaderParser can be much faster in these situations, since they do not attempt to parse the message body, instead setting the payload to the raw body.

class email.parser.BytesParser(_class=None, *, policy=policy.compat32)

Create a BytesParser instance. The _class and policy arguments have the same meaning and semantics as the _factory and policy arguments of BytesFeedParser.

Note: The policy keyword should always be specified; The default will change to email.policy.default in a future version of Python.

Modifié dans la version 3.3: Removed the strict argument that was deprecated in 2.4. Added the policy keyword.

Modifié dans la version 3.6: _class defaults to the policy message_factory.

parse(fp, headersonly=False)

Read all the data from the binary file-like object fp, parse the resulting bytes, and return the message object. fp must support both the readline() and the read() methods.

The bytes contained in fp must be formatted as a block of RFC 5322 [https://tools.ietf.org/html/rfc5322.html] (or, if utf8 is True, RFC 6532 [https://tools.ietf.org/html/rfc6532.html]) style headers and header continuation lines, optionally preceded by an envelope header. The header block is terminated either by the end of the data or by a blank line. Following the header block is the body of the message (which may contain MIME-encoded subparts, including subparts with a Content-Transfer-Encoding of 8bit).

Optional headersonly is a flag specifying whether to stop parsing after reading the headers or not. The default is False, meaning it parses the entire contents of the file.

parsebytes(bytes, headersonly=False)

Similar to the parse() method, except it takes a bytes-like object instead of a file-like object. Calling this method on a bytes-like object is equivalent to wrapping bytes in a BytesIO instance first and calling parse().

Optional headersonly is as with the parse() method.

Nouveau dans la version 3.2.

class email.parser.BytesHeaderParser(_class=None, *, policy=policy.compat32)

Exactly like BytesParser, except that headersonly defaults to True.

Nouveau dans la version 3.3.

class email.parser.Parser(_class=None, *, policy=policy.compat32)

This class is parallel to BytesParser, but handles string input.

Modifié dans la version 3.3: Removed the strict argument. Added the policy keyword.

Modifié dans la version 3.6: _class defaults to the policy message_factory.

parse(fp, headersonly=False)

Read all the data from the text-mode file-like object fp, parse the resulting text, and return the root message object. fp must support both the readline() and the read() methods on file-like objects.

Other than the text mode requirement, this method operates like BytesParser.parse().

parsestr(text, headersonly=False)

Similar to the parse() method, except it takes a string object instead of a file-like object. Calling this method on a string is equivalent to wrapping text in a StringIO instance first and calling parse().

Optional headersonly is as with the parse() method.

class email.parser.HeaderParser(_class=None, *, policy=policy.compat32)

Exactly like Parser, except that headersonly defaults to True.

Since creating a message object structure from a string or a file object is such a common task, four functions are provided as a convenience. They are available in the top-level email package namespace.

email.message_from_bytes(s, _class=None, *, policy=policy.compat32)

Return a message object structure from a bytes-like object. This is equivalent to BytesParser().parsebytes(s). Optional _class and policy are interpreted as with the BytesParser class constructor.

Nouveau dans la version 3.2.

Modifié dans la version 3.3: Removed the strict argument. Added the policy keyword.

email.message_from_binary_file(fp, _class=None, *, policy=policy.compat32)

Return a message object structure tree from an open binary file object. This is equivalent to BytesParser().parse(fp). _class and policy are interpreted as with the BytesParser class constructor.

Nouveau dans la version 3.2.

Modifié dans la version 3.3: Removed the strict argument. Added the policy keyword.

email.message_from_string(s, _class=None, *, policy=policy.compat32)

Return a message object structure from a string. This is equivalent to Parser().parsestr(s). _class and policy are interpreted as with the Parser class constructor.

Modifié dans la version 3.3: Removed the strict argument. Added the policy keyword.

email.message_from_file(fp, _class=None, *, policy=policy.compat32)

Return a message object structure tree from an open file object. This is equivalent to Parser().parse(fp). _class and policy are interpreted as with the Parser class constructor.

Modifié dans la version 3.3: Removed the strict argument. Added the policy keyword.

Modifié dans la version 3.6: _class defaults to the policy message_factory.

Here’s an example of how you might use message_from_bytes() at an interactive Python prompt:

>>> import email
>>> msg = email.message_from_bytes(myBytes)

19.1.2.3. Notes complémentaires

Voici des remarques sur la sémantique d’analyse :

Most non-multipart type messages are parsed as a single message object with a string payload. These objects will return False for is_multipart(), and iter_parts() will yield an empty list.

All multipart type messages will be parsed as a container message object with a list of sub-message objects for their payload. The outer container message will return True for is_multipart(), and iter_parts() will yield a list of subparts.

Most messages with a content type of message/* (such as message/delivery-status and message/rfc822) will also be parsed as container object containing a list payload of length 1. Their is_multipart() method will return True. The single element yielded by iter_parts() will be a sub-message object.

Some non-standards-compliant messages may not be internally consistent about their multipart-edness. Such messages may have a Content-Type header of type multipart, but their is_multipart() method may return False. If such messages were parsed with the FeedParser, they will have an instance of the MultipartInvariantViolationDefect class in their defects attribute list. See email.errors for details.

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19.1.3. email.generator: Generating MIME documents

Source code: Lib/email/generator.py [https://github.com/python/cpython/tree/3.6/Lib/email/generator.py]

One of the most common tasks is to generate the flat (serialized) version of the email message represented by a message object structure. You will need to do this if you want to send your message via smtplib.SMTP.sendmail() or the nntplib module, or print the message on the console. Taking a message object structure and producing a serialized representation is the job of the generator classes.

As with the email.parser module, you aren’t limited to the functionality of the bundled generator; you could write one from scratch yourself. However the bundled generator knows how to generate most email in a standards-compliant way, should handle MIME and non-MIME email messages just fine, and is designed so that the bytes-oriented parsing and generation operations are inverses, assuming the same non-transforming policy is used for both. That is, parsing the serialized byte stream via the BytesParser class and then regenerating the serialized byte stream using BytesGenerator should produce output identical to the input 1. (On the other hand, using the generator on an EmailMessage constructed by program may result in changes to the EmailMessage object as defaults are filled in.)

The Generator class can be used to flatten a message into a text (as opposed to binary) serialized representation, but since Unicode cannot represent binary data directly, the message is of necessity transformed into something that contains only ASCII characters, using the standard email RFC Content Transfer Encoding techniques for encoding email messages for transport over channels that are not « 8 bit clean ».

class email.generator.BytesGenerator(outfp, mangle_from_=None, maxheaderlen=None, *, policy=None)

Return a BytesGenerator object that will write any message provided to the flatten() method, or any surrogateescape encoded text provided to the write() method, to the file-like object outfp. outfp must support a write method that accepts binary data.

If optional mangle_from_ is True, put a > character in front of any line in the body that starts with the exact string "From ", that is From followed by a space at the beginning of a line. mangle_from_ defaults to the value of the mangle_from_ setting of the policy (which is True for the compat32 policy and False for all others). mangle_from_ is intended for use when messages are stored in unix mbox format (see mailbox and WHY THE CONTENT-LENGTH FORMAT IS BAD [http://www.jwz.org/doc/content-length.html]).

If maxheaderlen is not None, refold any header lines that are longer than maxheaderlen, or if 0, do not rewrap any headers. If manheaderlen is None (the default), wrap headers and other message lines according to the policy settings.

If policy is specified, use that policy to control message generation. If policy is None (the default), use the policy associated with the Message or EmailMessage object passed to flatten to control the message generation. See email.policy for details on what policy controls.

Nouveau dans la version 3.2.

Modifié dans la version 3.3: Added the policy keyword.

Modifié dans la version 3.6: The default behavior of the mangle_from_ and maxheaderlen parameters is to follow the policy.

flatten(msg, unixfrom=False, linesep=None)

Print the textual representation of the message object structure rooted at msg to the output file specified when the BytesGenerator instance was created.

If the policy option cte_type is 8bit (the default), copy any headers in the original parsed message that have not been modified to the output with any bytes with the high bit set reproduced as in the original, and preserve the non-ASCII Content-Transfer-Encoding of any body parts that have them. If cte_type is 7bit, convert the bytes with the high bit set as needed using an ASCII-compatible Content-Transfer-Encoding. That is, transform parts with non-ASCII Content-Transfer-Encoding (Content-Transfer-Encoding: 8bit) to an ASCII compatible Content-Transfer-Encoding, and encode RFC-invalid non-ASCII bytes in headers using the MIME unknown-8bit character set, thus rendering them RFC-compliant.

If unixfrom is True, print the envelope header delimiter used by the Unix mailbox format (see mailbox) before the first of the RFC 5322 [https://tools.ietf.org/html/rfc5322.html] headers of the root message object. If the root object has no envelope header, craft a standard one. The default is False. Note that for subparts, no envelope header is ever printed.

If linesep is not None, use it as the separator character between all the lines of the flattened message. If linesep is None (the default), use the value specified in the policy.

clone(fp)

Return an independent clone of this BytesGenerator instance with the exact same option settings, and fp as the new outfp.

write(s)

Encode s using the ASCII codec and the surrogateescape error handler, and pass it to the write method of the outfp passed to the BytesGenerator’s constructor.

As a convenience, EmailMessage provides the methods as_bytes() and bytes(aMessage) (a.k.a. __bytes__()), which simplify the generation of a serialized binary representation of a message object. For more detail, see email.message.

Because strings cannot represent binary data, the Generator class must convert any binary data in any message it flattens to an ASCII compatible format, by converting them to an ASCII compatible Content-Transfer_Encoding. Using the terminology of the email RFCs, you can think of this as Generator serializing to an I/O stream that is not « 8 bit clean ». In other words, most applications will want to be using BytesGenerator, and not Generator.

class email.generator.Generator(outfp, mangle_from_=None, maxheaderlen=None, *, policy=None)

Return a Generator object that will write any message provided to the flatten() method, or any text provided to the write() method, to the file-like object outfp. outfp must support a write method that accepts string data.

If optional mangle_from_ is True, put a > character in front of any line in the body that starts with the exact string "From ", that is From followed by a space at the beginning of a line. mangle_from_ defaults to the value of the mangle_from_ setting of the policy (which is True for the compat32 policy and False for all others). mangle_from_ is intended for use when messages are stored in unix mbox format (see mailbox and WHY THE CONTENT-LENGTH FORMAT IS BAD [http://www.jwz.org/doc/content-length.html]).

If maxheaderlen is not None, refold any header lines that are longer than maxheaderlen, or if 0, do not rewrap any headers. If manheaderlen is None (the default), wrap headers and other message lines according to the policy settings.

If policy is specified, use that policy to control message generation. If policy is None (the default), use the policy associated with the Message or EmailMessage object passed to flatten to control the message generation. See email.policy for details on what policy controls.

Modifié dans la version 3.3: Added the policy keyword.

Modifié dans la version 3.6: The default behavior of the mangle_from_ and maxheaderlen parameters is to follow the policy.

flatten(msg, unixfrom=False, linesep=None)

Print the textual representation of the message object structure rooted at msg to the output file specified when the Generator instance was created.

If the policy option cte_type is 8bit, generate the message as if the option were set to 7bit. (This is required because strings cannot represent non-ASCII bytes.) Convert any bytes with the high bit set as needed using an ASCII-compatible Content-Transfer-Encoding. That is, transform parts with non-ASCII Cotnent-Transfer-Encoding (Content-Transfer-Encoding: 8bit) to an ASCII compatible Content-Transfer-Encoding, and encode RFC-invalid non-ASCII bytes in headers using the MIME unknown-8bit character set, thus rendering them RFC-compliant.

If unixfrom is True, print the envelope header delimiter used by the Unix mailbox format (see mailbox) before the first of the RFC 5322 [https://tools.ietf.org/html/rfc5322.html] headers of the root message object. If the root object has no envelope header, craft a standard one. The default is False. Note that for subparts, no envelope header is ever printed.

If linesep is not None, use it as the separator character between all the lines of the flattened message. If linesep is None (the default), use the value specified in the policy.

Modifié dans la version 3.2: Added support for re-encoding 8bit message bodies, and the linesep argument.

clone(fp)

Return an independent clone of this Generator instance with the exact same options, and fp as the new outfp.

write(s)

Write s to the write method of the outfp passed to the Generator’s constructor. This provides just enough file-like API for Generator instances to be used in the print() function.

As a convenience, EmailMessage provides the methods as_string() and str(aMessage) (a.k.a. __str__()), which simplify the generation of a formatted string representation of a message object. For more detail, see email.message.

The email.generator module also provides a derived class, DecodedGenerator, which is like the Generator base class, except that non-text parts are not serialized, but are instead represented in the output stream by a string derived from a template filled in with information about the part.

class email.generator.DecodedGenerator(outfp, mangle_from_=None, maxheaderlen=None, fmt=None, *, policy=None)

Act like Generator, except that for any subpart of the message passed to Generator.flatten(), if the subpart is of main type text, print the decoded payload of the subpart, and if the main type is not text, instead of printing it fill in the string fmt using information from the part and print the resulting filled-in string.

To fill in fmt, execute fmt % part_info, where part_info is a dictionary composed of the following keys and values:

type – Full MIME type of the non-text part

maintype – Main MIME type of the non-text part

subtype – Sub-MIME type of the non-text part

filename – Filename of the non-text part

description – Description associated with the non-text part

encoding – Content transfer encoding of the non-text part

If fmt is None, use the following default fmt:

« [Non-text (%(type)s) part of message omitted, filename %(filename)s] »

Optional _mangle_from_ and maxheaderlen are as with the Generator base class.

Notes

1

This statement assumes that you use the appropriate setting for unixfrom, and that there are no policy settings calling for automatic adjustments (for example, refold_source must be none, which is not the default). It is also not 100% true, since if the message does not conform to the RFC standards occasionally information about the exact original text is lost during parsing error recovery. It is a goal to fix these latter edge cases when possible.

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19.1.4. email.policy: Policy Objects

Nouveau dans la version 3.3.

Source code: Lib/email/policy.py [https://github.com/python/cpython/tree/3.6/Lib/email/policy.py]

The email package’s prime focus is the handling of email messages as described by the various email and MIME RFCs. However, the general format of email messages (a block of header fields each consisting of a name followed by a colon followed by a value, the whole block followed by a blank line and an arbitrary “body”), is a format that has found utility outside of the realm of email. Some of these uses conform fairly closely to the main email RFCs, some do not. Even when working with email, there are times when it is desirable to break strict compliance with the RFCs, such as generating emails that interoperate with email servers that do not themselves follow the standards, or that implement extensions you want to use in ways that violate the standards.

Policy objects give the email package the flexibility to handle all these disparate use cases.

A Policy object encapsulates a set of attributes and methods that control the behavior of various components of the email package during use. Policy instances can be passed to various classes and methods in the email package to alter the default behavior. The settable values and their defaults are described below.

There is a default policy used by all classes in the email package. For all of the parser classes and the related convenience functions, and for the Message class, this is the Compat32 policy, via its corresponding pre-defined instance compat32. This policy provides for complete backward compatibility (in some cases, including bug compatibility) with the pre-Python3.3 version of the email package.

This default value for the policy keyword to EmailMessage is the EmailPolicy policy, via its pre-defined instance default.

When a Message or EmailMessage object is created, it acquires a policy. If the message is created by a parser, a policy passed to the parser will be the policy used by the message it creates. If the message is created by the program, then the policy can be specified when it is created. When a message is passed to a generator, the generator uses the policy from the message by default, but you can also pass a specific policy to the generator that will override the one stored on the message object.

The default value for the policy keyword for the email.parser classes and the parser convenience functions will be changing in a future version of Python. Therefore you should always specify explicitly which policy you want to use when calling any of the classes and functions described in the parser module.

The first part of this documentation covers the features of Policy, an abstract base class that defines the features that are common to all policy objects, including compat32. This includes certain hook methods that are called internally by the email package, which a custom policy could override to obtain different behavior. The second part describes the concrete classes EmailPolicy and Compat32, which implement the hooks that provide the standard behavior and the backward compatible behavior and features, respectively.

Policy instances are immutable, but they can be cloned, accepting the same keyword arguments as the class constructor and returning a new Policy instance that is a copy of the original but with the specified attributes values changed.

As an example, the following code could be used to read an email message from a file on disk and pass it to the system sendmail program on a Unix system:

>>> from email import message_from_binary_file
>>> from email.generator import BytesGenerator
>>> from email import policy
>>> from subprocess import Popen, PIPE
>>> with open('mymsg.txt', 'rb') as f:
...     msg = message_from_binary_file(f, policy=policy.default)
>>> p = Popen(['sendmail', msg['To'].addresses[0]], stdin=PIPE)
>>> g = BytesGenerator(p.stdin, policy=msg.policy.clone(linesep='\r\n'))
>>> g.flatten(msg)
>>> p.stdin.close()
>>> rc = p.wait()

Here we are telling BytesGenerator to use the RFC correct line separator characters when creating the binary string to feed into sendmail's stdin, where the default policy would use \n line separators.

Some email package methods accept a policy keyword argument, allowing the policy to be overridden for that method. For example, the following code uses the as_bytes() method of the msg object from the previous example and writes the message to a file using the native line separators for the platform on which it is running:

>>> import os
>>> with open('converted.txt', 'wb') as f:
...     f.write(msg.as_bytes(policy=msg.policy.clone(linesep=os.linesep)))
17

Policy objects can also be combined using the addition operator, producing a policy object whose settings are a combination of the non-default values of the summed objects:

>>> compat_SMTP = policy.compat32.clone(linesep='\r\n')
>>> compat_strict = policy.compat32.clone(raise_on_defect=True)
>>> compat_strict_SMTP = compat_SMTP + compat_strict

This operation is not commutative; that is, the order in which the objects are added matters. To illustrate:

>>> policy100 = policy.compat32.clone(max_line_length=100)
>>> policy80 = policy.compat32.clone(max_line_length=80)
>>> apolicy = policy100 + policy80
>>> apolicy.max_line_length
80
>>> apolicy = policy80 + policy100
>>> apolicy.max_line_length
100

class email.policy.Policy(**kw)

This is the abstract base class for all policy classes. It provides default implementations for a couple of trivial methods, as well as the implementation of the immutability property, the clone() method, and the constructor semantics.

The constructor of a policy class can be passed various keyword arguments. The arguments that may be specified are any non-method properties on this class, plus any additional non-method properties on the concrete class. A value specified in the constructor will override the default value for the corresponding attribute.

This class defines the following properties, and thus values for the following may be passed in the constructor of any policy class:

max_line_length

The maximum length of any line in the serialized output, not counting the end of line character(s). Default is 78, per RFC 5322 [https://tools.ietf.org/html/rfc5322.html]. A value of 0 or None indicates that no line wrapping should be done at all.

linesep

The string to be used to terminate lines in serialized output. The default is \n because that’s the internal end-of-line discipline used by Python, though \r\n is required by the RFCs.

cte_type

Controls the type of Content Transfer Encodings that may be or are required to be used. The possible values are:

7bit

all data must be « 7 bit clean » (ASCII-only). This means that where necessary data will be encoded using either quoted-printable or base64 encoding.

8bit

data is not constrained to be 7 bit clean. Data in headers is still required to be ASCII-only and so will be encoded (see fold_binary() and utf8 below for exceptions), but body parts may use the 8bit CTE.

A cte_type value of 8bit only works with BytesGenerator, not Generator, because strings cannot contain binary data. If a Generator is operating under a policy that specifies cte_type=8bit, it will act as if cte_type is 7bit.

raise_on_defect

If True, any defects encountered will be raised as errors. If False (the default), defects will be passed to the register_defect() method.

mangle_from_

If True, lines starting with « From «  in the body are escaped by putting a > in front of them. This parameter is used when the message is being serialized by a generator. Default: False.

Nouveau dans la version 3.5: The mangle_from_ parameter.

message_factory

A factory function for constructing a new empty message object. Used by the parser when building messages. Defaults to None, in which case Message is used.

Nouveau dans la version 3.6.

The following Policy method is intended to be called by code using the email library to create policy instances with custom settings:

clone(**kw)

Return a new Policy instance whose attributes have the same values as the current instance, except where those attributes are given new values by the keyword arguments.

The remaining Policy methods are called by the email package code, and are not intended to be called by an application using the email package. A custom policy must implement all of these methods.

handle_defect(obj, defect)

Handle a defect found on obj. When the email package calls this method, defect will always be a subclass of Defect.

The default implementation checks the raise_on_defect flag. If it is True, defect is raised as an exception. If it is False (the default), obj and defect are passed to register_defect().

register_defect(obj, defect)

Register a defect on obj. In the email package, defect will always be a subclass of Defect.

The default implementation calls the append method of the defects attribute of obj. When the email package calls handle_defect, obj will normally have a defects attribute that has an append method. Custom object types used with the email package (for example, custom Message objects) should also provide such an attribute, otherwise defects in parsed messages will raise unexpected errors.

header_max_count(name)

Return the maximum allowed number of headers named name.

Called when a header is added to an EmailMessage or Message object. If the returned value is not 0 or None, and there are already a number of headers with the name name greater than or equal to the value returned, a ValueError is raised.

Because the default behavior of Message.__setitem__ is to append the value to the list of headers, it is easy to create duplicate headers without realizing it. This method allows certain headers to be limited in the number of instances of that header that may be added to a Message programmatically. (The limit is not observed by the parser, which will faithfully produce as many headers as exist in the message being parsed.)

The default implementation returns None for all header names.

header_source_parse(sourcelines)

The email package calls this method with a list of strings, each string ending with the line separation characters found in the source being parsed. The first line includes the field header name and separator. All whitespace in the source is preserved. The method should return the (name, value) tuple that is to be stored in the Message to represent the parsed header.

If an implementation wishes to retain compatibility with the existing email package policies, name should be the case preserved name (all characters up to the “:” separator), while value should be the unfolded value (all line separator characters removed, but whitespace kept intact), stripped of leading whitespace.

sourcelines may contain surrogateescaped binary data.

There is no default implementation

header_store_parse(name, value)

The email package calls this method with the name and value provided by the application program when the application program is modifying a Message programmatically (as opposed to a Message created by a parser). The method should return the (name, value) tuple that is to be stored in the Message to represent the header.

If an implementation wishes to retain compatibility with the existing email package policies, the name and value should be strings or string subclasses that do not change the content of the passed in arguments.

There is no default implementation

header_fetch_parse(name, value)

The email package calls this method with the name and value currently stored in the Message when that header is requested by the application program, and whatever the method returns is what is passed back to the application as the value of the header being retrieved. Note that there may be more than one header with the same name stored in the Message; the method is passed the specific name and value of the header destined to be returned to the application.

value may contain surrogateescaped binary data. There should be no surrogateescaped binary data in the value returned by the method.

There is no default implementation

fold(name, value)

The email package calls this method with the name and value currently stored in the Message for a given header. The method should return a string that represents that header « folded » correctly (according to the policy settings) by composing the name with the value and inserting linesep characters at the appropriate places. See RFC 5322 [https://tools.ietf.org/html/rfc5322.html] for a discussion of the rules for folding email headers.

value may contain surrogateescaped binary data. There should be no surrogateescaped binary data in the string returned by the method.

fold_binary(name, value)

The same as fold(), except that the returned value should be a bytes object rather than a string.

value may contain surrogateescaped binary data. These could be converted back into binary data in the returned bytes object.

class email.policy.EmailPolicy(**kw)

This concrete Policy provides behavior that is intended to be fully compliant with the current email RFCs. These include (but are not limited to) RFC 5322 [https://tools.ietf.org/html/rfc5322.html], RFC 2047 [https://tools.ietf.org/html/rfc2047.html], and the current MIME RFCs.

This policy adds new header parsing and folding algorithms. Instead of simple strings, headers are str subclasses with attributes that depend on the type of the field. The parsing and folding algorithm fully implement RFC 2047 [https://tools.ietf.org/html/rfc2047.html] and RFC 5322 [https://tools.ietf.org/html/rfc5322.html].

The default value for the message_factory attribute is EmailMessage.

In addition to the settable attributes listed above that apply to all policies, this policy adds the following additional attributes:

Nouveau dans la version 3.6: 1

utf8

If False, follow RFC 5322 [https://tools.ietf.org/html/rfc5322.html], supporting non-ASCII characters in headers by encoding them as « encoded words ». If True, follow RFC 6532 [https://tools.ietf.org/html/rfc6532.html] and use utf-8 encoding for headers. Messages formatted in this way may be passed to SMTP servers that support the SMTPUTF8 extension (RFC 6531 [https://tools.ietf.org/html/rfc6531.html]).

refold_source

If the value for a header in the Message object originated from a parser (as opposed to being set by a program), this attribute indicates whether or not a generator should refold that value when transforming the message back into serialized form. The possible values are:

none

all source values use original folding

long

source values that have any line that is longer than max_line_length will be refolded

all

all values are refolded.

The default is long.

header_factory

A callable that takes two arguments, name and value, where name is a header field name and value is an unfolded header field value, and returns a string subclass that represents that header. A default header_factory (see headerregistry) is provided that supports custom parsing for the various address and date RFC 5322 [https://tools.ietf.org/html/rfc5322.html] header field types, and the major MIME header field stypes. Support for additional custom parsing will be added in the future.

content_manager

An object with at least two methods: get_content and set_content. When the get_content() or set_content() method of an EmailMessage object is called, it calls the corresponding method of this object, passing it the message object as its first argument, and any arguments or keywords that were passed to it as additional arguments. By default content_manager is set to raw_data_manager.

Nouveau dans la version 3.4.

The class provides the following concrete implementations of the abstract methods of Policy:

header_max_count(name)

Returns the value of the max_count attribute of the specialized class used to represent the header with the given name.

header_source_parse(sourcelines)

The name is parsed as everything up to the “:” and returned unmodified. The value is determined by stripping leading whitespace off the remainder of the first line, joining all subsequent lines together, and stripping any trailing carriage return or linefeed characters.

header_store_parse(name, value)

The name is returned unchanged. If the input value has a name attribute and it matches name ignoring case, the value is returned unchanged. Otherwise the name and value are passed to header_factory, and the resulting header object is returned as the value. In this case a ValueError is raised if the input value contains CR or LF characters.

header_fetch_parse(name, value)

If the value has a name attribute, it is returned to unmodified. Otherwise the name, and the value with any CR or LF characters removed, are passed to the header_factory, and the resulting header object is returned. Any surrogateescaped bytes get turned into the unicode unknown-character glyph.

fold(name, value)

Header folding is controlled by the refold_source policy setting. A value is considered to be a “source value” if and only if it does not have a name attribute (having a name attribute means it is a header object of some sort). If a source value needs to be refolded according to the policy, it is converted into a header object by passing the name and the value with any CR and LF characters removed to the header_factory. Folding of a header object is done by calling its fold method with the current policy.

Source values are split into lines using splitlines(). If the value is not to be refolded, the lines are rejoined using the linesep from the policy and returned. The exception is lines containing non-ascii binary data. In that case the value is refolded regardless of the refold_source setting, which causes the binary data to be CTE encoded using the unknown-8bit charset.

fold_binary(name, value)

The same as fold() if cte_type is 7bit, except that the returned value is bytes.

If cte_type is 8bit, non-ASCII binary data is converted back into bytes. Headers with binary data are not refolded, regardless of the refold_header setting, since there is no way to know whether the binary data consists of single byte characters or multibyte characters.

The following instances of EmailPolicy provide defaults suitable for specific application domains. Note that in the future the behavior of these instances (in particular the HTTP instance) may be adjusted to conform even more closely to the RFCs relevant to their domains.

email.policy.default

An instance of EmailPolicy with all defaults unchanged. This policy uses the standard Python \n line endings rather than the RFC-correct \r\n.

email.policy.SMTP

Suitable for serializing messages in conformance with the email RFCs. Like default, but with linesep set to \r\n, which is RFC compliant.

email.policy.SMTPUTF8

The same as SMTP except that utf8 is True. Useful for serializing messages to a message store without using encoded words in the headers. Should only be used for SMTP transmission if the sender or recipient addresses have non-ASCII characters (the smtplib.SMTP.send_message() method handles this automatically).

email.policy.HTTP

Suitable for serializing headers with for use in HTTP traffic. Like SMTP except that max_line_length is set to None (unlimited).

email.policy.strict

Convenience instance. The same as default except that raise_on_defect is set to True. This allows any policy to be made strict by writing:

somepolicy + policy.strict

With all of these EmailPolicies, the effective API of the email package is changed from the Python 3.2 API in the following ways:

Setting a header on a Message results in that header being parsed and a header object created.

Fetching a header value from a Message results in that header being parsed and a header object created and returned.

Any header object, or any header that is refolded due to the policy settings, is folded using an algorithm that fully implements the RFC folding algorithms, including knowing where encoded words are required and allowed.

From the application view, this means that any header obtained through the EmailMessage is a header object with extra attributes, whose string value is the fully decoded unicode value of the header. Likewise, a header may be assigned a new value, or a new header created, using a unicode string, and the policy will take care of converting the unicode string into the correct RFC encoded form.

The header objects and their attributes are described in headerregistry.

class email.policy.Compat32(**kw)

This concrete Policy is the backward compatibility policy. It replicates the behavior of the email package in Python 3.2. The policy module also defines an instance of this class, compat32, that is used as the default policy. Thus the default behavior of the email package is to maintain compatibility with Python 3.2.

The following attributes have values that are different from the Policy default:

mangle_from_

The default is True.

The class provides the following concrete implementations of the abstract methods of Policy:

header_source_parse(sourcelines)

The name is parsed as everything up to the “:” and returned unmodified. The value is determined by stripping leading whitespace off the remainder of the first line, joining all subsequent lines together, and stripping any trailing carriage return or linefeed characters.

header_store_parse(name, value)

The name and value are returned unmodified.

header_fetch_parse(name, value)

If the value contains binary data, it is converted into a Header object using the unknown-8bit charset. Otherwise it is returned unmodified.

fold(name, value)

Headers are folded using the Header folding algorithm, which preserves existing line breaks in the value, and wraps each resulting line to the max_line_length. Non-ASCII binary data are CTE encoded using the unknown-8bit charset.

fold_binary(name, value)

Headers are folded using the Header folding algorithm, which preserves existing line breaks in the value, and wraps each resulting line to the max_line_length. If cte_type is 7bit, non-ascii binary data is CTE encoded using the unknown-8bit charset. Otherwise the original source header is used, with its existing line breaks and any (RFC invalid) binary data it may contain.

email.policy.compat32

An instance of Compat32, providing backward compatibility with the behavior of the email package in Python 3.2.

Notes

1

Originally added in 3.3 as a provisional feature.

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19.1.5. email.errors: Exception and Defect classes

Source code: Lib/email/errors.py [https://github.com/python/cpython/tree/3.6/Lib/email/errors.py]

The following exception classes are defined in the email.errors module:

exception email.errors.MessageError

This is the base class for all exceptions that the email package can raise. It is derived from the standard Exception class and defines no additional methods.

exception email.errors.MessageParseError

This is the base class for exceptions raised by the Parser class. It is derived from MessageError. This class is also used internally by the parser used by headerregistry.

exception email.errors.HeaderParseError

Raised under some error conditions when parsing the RFC 5322 [https://tools.ietf.org/html/rfc5322.html] headers of a message, this class is derived from MessageParseError. The set_boundary() method will raise this error if the content type is unknown when the method is called. Header may raise this error for certain base64 decoding errors, and when an attempt is made to create a header that appears to contain an embedded header (that is, there is what is supposed to be a continuation line that has no leading whitespace and looks like a header).

exception email.errors.BoundaryError

Deprecated and no longer used.

exception email.errors.MultipartConversionError

Raised when a payload is added to a Message object using add_payload(), but the payload is already a scalar and the message’s Content-Type main type is not either multipart or missing. MultipartConversionError multiply inherits from MessageError and the built-in TypeError.

Since Message.add_payload() is deprecated, this exception is rarely raised in practice. However the exception may also be raised if the attach() method is called on an instance of a class derived from MIMENonMultipart (e.g. MIMEImage).

Here is the list of the defects that the FeedParser can find while parsing messages. Note that the defects are added to the message where the problem was found, so for example, if a message nested inside a multipart/alternative had a malformed header, that nested message object would have a defect, but the containing messages would not.

All defect classes are subclassed from email.errors.MessageDefect.

NoBoundaryInMultipartDefect – A message claimed to be a multipart, but had no boundary parameter.

StartBoundaryNotFoundDefect – The start boundary claimed in the Content-Type header was never found.

CloseBoundaryNotFoundDefect – A start boundary was found, but no corresponding close boundary was ever found.

Nouveau dans la version 3.3.

FirstHeaderLineIsContinuationDefect – The message had a continuation line as its first header line.

MisplacedEnvelopeHeaderDefect - A « Unix From » header was found in the middle of a header block.

MissingHeaderBodySeparatorDefect - A line was found while parsing headers that had no leading white space but contained no “:”. Parsing continues assuming that the line represents the first line of the body.

Nouveau dans la version 3.3.

MalformedHeaderDefect – A header was found that was missing a colon, or was otherwise malformed.

Obsolète depuis la version 3.3: This defect has not been used for several Python versions.

MultipartInvariantViolationDefect – A message claimed to be a multipart, but no subparts were found. Note that when a message has this defect, its is_multipart() method may return false even though its content type claims to be multipart.

InvalidBase64PaddingDefect – When decoding a block of base64 encoded bytes, the padding was not correct. Enough padding is added to perform the decode, but the resulting decoded bytes may be invalid.

InvalidBase64CharactersDefect – When decoding a block of base64 encoded bytes, characters outside the base64 alphabet were encountered. The characters are ignored, but the resulting decoded bytes may be invalid.

InvalidBase64LengthDefect – When decoding a block of base64 encoded bytes, the number of non-padding base64 characters was invalid (1 more than a multiple of 4). The encoded block was kept as-is.

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19.1.6. email.headerregistry: Custom Header Objects

Source code: Lib/email/headerregistry.py [https://github.com/python/cpython/tree/3.6/Lib/email/headerregistry.py]

Nouveau dans la version 3.6: 1

Headers are represented by customized subclasses of str. The particular class used to represent a given header is determined by the header_factory of the policy in effect when the headers are created. This section documents the particular header_factory implemented by the email package for handling RFC 5322 [https://tools.ietf.org/html/rfc5322.html] compliant email messages, which not only provides customized header objects for various header types, but also provides an extension mechanism for applications to add their own custom header types.

When using any of the policy objects derived from EmailPolicy, all headers are produced by HeaderRegistry and have BaseHeader as their last base class. Each header class has an additional base class that is determined by the type of the header. For example, many headers have the class UnstructuredHeader as their other base class. The specialized second class for a header is determined by the name of the header, using a lookup table stored in the HeaderRegistry. All of this is managed transparently for the typical application program, but interfaces are provided for modifying the default behavior for use by more complex applications.

The sections below first document the header base classes and their attributes, followed by the API for modifying the behavior of HeaderRegistry, and finally the support classes used to represent the data parsed from structured headers.

class email.headerregistry.BaseHeader(name, value)

name and value are passed to BaseHeader from the header_factory call. The string value of any header object is the value fully decoded to unicode.

This base class defines the following read-only properties:

name

The name of the header (the portion of the field before the “:”). This is exactly the value passed in the header_factory call for name; that is, case is preserved.

defects

A tuple of HeaderDefect instances reporting any RFC compliance problems found during parsing. The email package tries to be complete about detecting compliance issues. See the errors module for a discussion of the types of defects that may be reported.

max_count

The maximum number of headers of this type that can have the same name. A value of None means unlimited. The BaseHeader value for this attribute is None; it is expected that specialized header classes will override this value as needed.

BaseHeader also provides the following method, which is called by the email library code and should not in general be called by application programs:

fold(*, policy)

Return a string containing linesep characters as required to correctly fold the header according to policy. A cte_type of 8bit will be treated as if it were 7bit, since headers may not contain arbitrary binary data. If utf8 is False, non-ASCII data will be RFC 2047 [https://tools.ietf.org/html/rfc2047.html] encoded.

BaseHeader by itself cannot be used to create a header object. It defines a protocol that each specialized header cooperates with in order to produce the header object. Specifically, BaseHeader requires that the specialized class provide a classmethod() named parse. This method is called as follows:

parse(string, kwds)

kwds is a dictionary containing one pre-initialized key, defects. defects is an empty list. The parse method should append any detected defects to this list. On return, the kwds dictionary must contain values for at least the keys decoded and defects. decoded should be the string value for the header (that is, the header value fully decoded to unicode). The parse method should assume that string may contain content-transfer-encoded parts, but should correctly handle all valid unicode characters as well so that it can parse un-encoded header values.

BaseHeader’s __new__ then creates the header instance, and calls its init method. The specialized class only needs to provide an init method if it wishes to set additional attributes beyond those provided by BaseHeader itself. Such an init method should look like this:

def init(self, *args, **kw):
    self._myattr = kw.pop('myattr')
    super().init(*args, **kw)

That is, anything extra that the specialized class puts in to the kwds dictionary should be removed and handled, and the remaining contents of kw (and args) passed to the BaseHeader init method.

class email.headerregistry.UnstructuredHeader

An « unstructured » header is the default type of header in RFC 5322 [https://tools.ietf.org/html/rfc5322.html]. Any header that does not have a specified syntax is treated as unstructured. The classic example of an unstructured header is the Subject header.

In RFC 5322 [https://tools.ietf.org/html/rfc5322.html], an unstructured header is a run of arbitrary text in the ASCII character set. RFC 2047 [https://tools.ietf.org/html/rfc2047.html], however, has an RFC 5322 [https://tools.ietf.org/html/rfc5322.html] compatible mechanism for encoding non-ASCII text as ASCII characters within a header value. When a value containing encoded words is passed to the constructor, the UnstructuredHeader parser converts such encoded words into unicode, following the RFC 2047 [https://tools.ietf.org/html/rfc2047.html] rules for unstructured text. The parser uses heuristics to attempt to decode certain non-compliant encoded words. Defects are registered in such cases, as well as defects for issues such as invalid characters within the encoded words or the non-encoded text.

This header type provides no additional attributes.

class email.headerregistry.DateHeader

RFC 5322 [https://tools.ietf.org/html/rfc5322.html] specifies a very specific format for dates within email headers. The DateHeader parser recognizes that date format, as well as recognizing a number of variant forms that are sometimes found « in the wild ».

This header type provides the following additional attributes:

datetime

If the header value can be recognized as a valid date of one form or another, this attribute will contain a datetime instance representing that date. If the timezone of the input date is specified as -0000 (indicating it is in UTC but contains no information about the source timezone), then datetime will be a naive datetime. If a specific timezone offset is found (including +0000), then datetime will contain an aware datetime that uses datetime.timezone to record the timezone offset.

The decoded value of the header is determined by formatting the datetime according to the RFC 5322 [https://tools.ietf.org/html/rfc5322.html] rules; that is, it is set to:

email.utils.format_datetime(self.datetime)

When creating a DateHeader, value may be datetime instance. This means, for example, that the following code is valid and does what one would expect:

msg['Date'] = datetime(2011, 7, 15, 21)

Because this is a naive datetime it will be interpreted as a UTC timestamp, and the resulting value will have a timezone of -0000. Much more useful is to use the localtime() function from the utils module:

msg['Date'] = utils.localtime()

This example sets the date header to the current time and date using the current timezone offset.

class email.headerregistry.AddressHeader

Address headers are one of the most complex structured header types. The AddressHeader class provides a generic interface to any address header.

This header type provides the following additional attributes:

groups

A tuple of Group objects encoding the addresses and groups found in the header value. Addresses that are not part of a group are represented in this list as single-address Groups whose display_name is None.

addresses

A tuple of Address objects encoding all of the individual addresses from the header value. If the header value contains any groups, the individual addresses from the group are included in the list at the point where the group occurs in the value (that is, the list of addresses is « flattened » into a one dimensional list).

The decoded value of the header will have all encoded words decoded to unicode. idna encoded domain names are also decoded to unicode. The decoded value is set by joining the str value of the elements of the groups attribute with ', '.

A list of Address and Group objects in any combination may be used to set the value of an address header. Group objects whose display_name is None will be interpreted as single addresses, which allows an address list to be copied with groups intact by using the list obtained from the groups attribute of the source header.

class email.headerregistry.SingleAddressHeader

A subclass of AddressHeader that adds one additional attribute:

address

The single address encoded by the header value. If the header value actually contains more than one address (which would be a violation of the RFC under the default policy), accessing this attribute will result in a ValueError.

Many of the above classes also have a Unique variant (for example, UniqueUnstructuredHeader). The only difference is that in the Unique variant, max_count is set to 1.

class email.headerregistry.MIMEVersionHeader

There is really only one valid value for the MIME-Version header, and that is 1.0. For future proofing, this header class supports other valid version numbers. If a version number has a valid value per RFC 2045 [https://tools.ietf.org/html/rfc2045.html], then the header object will have non-None values for the following attributes:

version

The version number as a string, with any whitespace and/or comments removed.

major

The major version number as an integer

minor

The minor version number as an integer

class email.headerregistry.ParameterizedMIMEHeader

MIME headers all start with the prefix “Content-“. Each specific header has a certain value, described under the class for that header. Some can also take a list of supplemental parameters, which have a common format. This class serves as a base for all the MIME headers that take parameters.

params

A dictionary mapping parameter names to parameter values.

class email.headerregistry.ContentTypeHeader

A ParameterizedMIMEHeader class that handles the Content-Type header.

content_type

The content type string, in the form maintype/subtype.

maintype

subtype

class email.headerregistry.ContentDispositionHeader

A ParameterizedMIMEHeader class that handles the Content-Disposition header.

content-disposition

inline and attachment are the only valid values in common use.

class email.headerregistry.ContentTransferEncoding

Handles the Content-Transfer-Encoding header.

cte

Valid values are 7bit, 8bit, base64, and quoted-printable. See RFC 2045 [https://tools.ietf.org/html/rfc2045.html] for more information.

class email.headerregistry.HeaderRegistry(base_class=BaseHeader, default_class=UnstructuredHeader, use_default_map=True)

This is the factory used by EmailPolicy by default. HeaderRegistry builds the class used to create a header instance dynamically, using base_class and a specialized class retrieved from a registry that it holds. When a given header name does not appear in the registry, the class specified by default_class is used as the specialized class. When use_default_map is True (the default), the standard mapping of header names to classes is copied in to the registry during initialization. base_class is always the last class in the generated class’s __bases__ list.

The default mappings are:

subject

UniqueUnstructuredHeader

date

UniqueDateHeader

resent-date

DateHeader

orig-date

UniqueDateHeader

sender

UniqueSingleAddressHeader

resent-sender

SingleAddressHeader

to

UniqueAddressHeader

resent-to

AddressHeader

cc

UniqueAddressHeader

resent-cc

AddressHeader

from

UniqueAddressHeader

resent-from

AddressHeader

reply-to

UniqueAddressHeader

HeaderRegistry has the following methods:

map_to_type(self, name, cls)

name is the name of the header to be mapped. It will be converted to lower case in the registry. cls is the specialized class to be used, along with base_class, to create the class used to instantiate headers that match name.

__getitem__(name)

Construct and return a class to handle creating a name header.

__call__(name, value)

Retrieves the specialized header associated with name from the registry (using default_class if name does not appear in the registry) and composes it with base_class to produce a class, calls the constructed class’s constructor, passing it the same argument list, and finally returns the class instance created thereby.

The following classes are the classes used to represent data parsed from structured headers and can, in general, be used by an application program to construct structured values to assign to specific headers.

class email.headerregistry.Address(display_name='', username='', domain='', addr_spec=None)

The class used to represent an email address. The general form of an address is:

[display_name] <username@domain>

ou :

username@domain

where each part must conform to specific syntax rules spelled out in RFC 5322 [https://tools.ietf.org/html/rfc5322.html].

As a convenience addr_spec can be specified instead of username and domain, in which case username and domain will be parsed from the addr_spec. An addr_spec must be a properly RFC quoted string; if it is not Address will raise an error. Unicode characters are allowed and will be property encoded when serialized. However, per the RFCs, unicode is not allowed in the username portion of the address.

display_name

The display name portion of the address, if any, with all quoting removed. If the address does not have a display name, this attribute will be an empty string.

username

The username portion of the address, with all quoting removed.

domain

The domain portion of the address.

addr_spec

The username@domain portion of the address, correctly quoted for use as a bare address (the second form shown above). This attribute is not mutable.

__str__()

The str value of the object is the address quoted according to RFC 5322 [https://tools.ietf.org/html/rfc5322.html] rules, but with no Content Transfer Encoding of any non-ASCII characters.

To support SMTP (RFC 5321 [https://tools.ietf.org/html/rfc5321.html]), Address handles one special case: if username and domain are both the empty string (or None), then the string value of the Address is <>.

class email.headerregistry.Group(display_name=None, addresses=None)

The class used to represent an address group. The general form of an address group is:

display_name: [address-list];

As a convenience for processing lists of addresses that consist of a mixture of groups and single addresses, a Group may also be used to represent single addresses that are not part of a group by setting display_name to None and providing a list of the single address as addresses.

display_name

The display_name of the group. If it is None and there is exactly one Address in addresses, then the Group represents a single address that is not in a group.

addresses

A possibly empty tuple of Address objects representing the addresses in the group.

__str__()

The str value of a Group is formatted according to RFC 5322 [https://tools.ietf.org/html/rfc5322.html], but with no Content Transfer Encoding of any non-ASCII characters. If display_name is none and there is a single Address in the addresses list, the str value will be the same as the str of that single Address.

Notes

1

Originally added in 3.3 as a provisional module

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19.1.7. email.contentmanager: Managing MIME Content

Source code: Lib/email/contentmanager.py [https://github.com/python/cpython/tree/3.6/Lib/email/contentmanager.py]

Nouveau dans la version 3.6: 1

class email.contentmanager.ContentManager

Base class for content managers. Provides the standard registry mechanisms to register converters between MIME content and other representations, as well as the get_content and set_content dispatch methods.

get_content(msg, *args, **kw)

Look up a handler function based on the mimetype of msg (see next paragraph), call it, passing through all arguments, and return the result of the call. The expectation is that the handler will extract the payload from msg and return an object that encodes information about the extracted data.

To find the handler, look for the following keys in the registry, stopping with the first one found:

the string representing the full MIME type (maintype/subtype)

the string representing the maintype

the empty string

If none of these keys produce a handler, raise a KeyError for the full MIME type.

set_content(msg, obj, *args, **kw)

If the maintype is multipart, raise a TypeError; otherwise look up a handler function based on the type of obj (see next paragraph), call clear_content() on the msg, and call the handler function, passing through all arguments. The expectation is that the handler will transform and store obj into msg, possibly making other changes to msg as well, such as adding various MIME headers to encode information needed to interpret the stored data.

To find the handler, obtain the type of obj (typ = type(obj)), and look for the following keys in the registry, stopping with the first one found:

the type itself (typ)

the type’s fully qualified name (typ.__module__ + '.' + typ.__qualname__).

the type’s qualname (typ.__qualname__)

the type’s name (typ.__name__).

If none of the above match, repeat all of the checks above for each of the types in the MRO (typ.__mro__). Finally, if no other key yields a handler, check for a handler for the key None. If there is no handler for None, raise a KeyError for the fully qualified name of the type.

Also add a MIME-Version header if one is not present (see also MIMEPart).

add_get_handler(key, handler)

Record the function handler as the handler for key. For the possible values of key, see get_content().

add_set_handler(typekey, handler)

Record handler as the function to call when an object of a type matching typekey is passed to set_content(). For the possible values of typekey, see set_content().

19.1.7.1. Content Manager Instances

Currently the email package provides only one concrete content manager, raw_data_manager, although more may be added in the future. raw_data_manager is the content_manager provided by EmailPolicy and its derivatives.

email.contentmanager.raw_data_manager

This content manager provides only a minimum interface beyond that provided by Message itself: it deals only with text, raw byte strings, and Message objects. Nevertheless, it provides significant advantages compared to the base API: get_content on a text part will return a unicode string without the application needing to manually decode it, set_content provides a rich set of options for controlling the headers added to a part and controlling the content transfer encoding, and it enables the use of the various add_ methods, thereby simplifying the creation of multipart messages.

email.contentmanager.get_content(msg, errors='replace')

Return the payload of the part as either a string (for text parts), an EmailMessage object (for message/rfc822 parts), or a bytes object (for all other non-multipart types). Raise a KeyError if called on a multipart. If the part is a text part and errors is specified, use it as the error handler when decoding the payload to unicode. The default error handler is replace.

email.contentmanager.set_content(msg, <'str'>, subtype="plain", charset='utf-8' cte=None, disposition=None, filename=None, cid=None, params=None, headers=None)

email.contentmanager.set_content(msg, <'bytes'>, maintype, subtype, cte="base64", disposition=None, filename=None, cid=None, params=None, headers=None)

email.contentmanager.set_content(msg, <'EmailMessage'>, cte=None, disposition=None, filename=None, cid=None, params=None, headers=None)

Add headers and payload to msg:

Add a Content-Type header with a maintype/subtype value.

For str, set the MIME maintype to text, and set the subtype to subtype if it is specified, or plain if it is not.

For bytes, use the specified maintype and subtype, or raise a TypeError if they are not specified.

For EmailMessage objects, set the maintype to message, and set the subtype to subtype if it is specified or rfc822 if it is not. If subtype is partial, raise an error (bytes objects must be used to construct message/partial parts).

If charset is provided (which is valid only for str), encode the string to bytes using the specified character set. The default is utf-8. If the specified charset is a known alias for a standard MIME charset name, use the standard charset instead.

If cte is set, encode the payload using the specified content transfer encoding, and set the Content-Transfer-Encoding header to that value. Possible values for cte are quoted-printable, base64, 7bit, 8bit, and binary. If the input cannot be encoded in the specified encoding (for example, specifying a cte of 7bit for an input that contains non-ASCII values), raise a ValueError.

For str objects, if cte is not set use heuristics to determine the most compact encoding.

For EmailMessage, per RFC 2046 [https://tools.ietf.org/html/rfc2046.html], raise an error if a cte of quoted-printable or base64 is requested for subtype rfc822, and for any cte other than 7bit for subtype external-body. For message/rfc822, use 8bit if cte is not specified. For all other values of subtype, use 7bit.

Note

A cte of binary does not actually work correctly yet. The EmailMessage object as modified by set_content is correct, but BytesGenerator does not serialize it correctly.

If disposition is set, use it as the value of the Content-Disposition header. If not specified, and filename is specified, add the header with the value attachment. If disposition is not specified and filename is also not specified, do not add the header. The only valid values for disposition are attachment and inline.

If filename is specified, use it as the value of the filename parameter of the Content-Disposition header.

If cid is specified, add a Content-ID header with cid as its value.

If params is specified, iterate its items method and use the resulting (key, value) pairs to set additional parameters on the Content-Type header.

If headers is specified and is a list of strings of the form headername: headervalue or a list of header objects (distinguished from strings by having a name attribute), add the headers to msg.

Notes

1

Originally added in 3.4 as a provisional module

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19.1.8. email: Exemples

Cette page contient quelques exemples de l’utilisation du package email pour lire, écrire, et envoyer de simples messages mail, ainsi que des messages MIME plus complexes.

Premièrement, regardons comment créer et envoyer un message avec simplement du texte (le contenu textuel et les adresses peuvent tous deux contenir des caractères Unicodes) :

# Import smtplib for the actual sending function
import smtplib

# Import the email modules we'll need
from email.message import EmailMessage

# Open the plain text file whose name is in textfile for reading.
with open(textfile) as fp:
    # Create a text/plain message
    msg = EmailMessage()
    msg.set_content(fp.read())

# me == the sender's email address
# you == the recipient's email address
msg['Subject'] = 'The contents of %s' % textfile
msg['From'] = me
msg['To'] = you

# Send the message via our own SMTP server.
s = smtplib.SMTP('localhost')
s.send_message(msg)
s.quit()

Analyser des entêtes RFC 822 [https://tools.ietf.org/html/rfc822.html] peut être aisément réalisé en utilisant les classes du module parser :

# Import the email modules we'll need
from email.parser import BytesParser, Parser
from email.policy import default

# If the e-mail headers are in a file, uncomment these two lines:
# with open(messagefile, 'rb') as fp:
#     headers = BytesParser(policy=default).parse(fp)

#  Or for parsing headers in a string (this is an uncommon operation), use:
headers = Parser(policy=default).parsestr(
        'From: Foo Bar <user@example.com>\n'
        'To: <someone_else@example.com>\n'
        'Subject: Test message\n'
        '\n'
        'Body would go here\n')

#  Now the header items can be accessed as a dictionary:
print('To: {}'.format(headers['to']))
print('From: {}'.format(headers['from']))
print('Subject: {}'.format(headers['subject']))

# You can also access the parts of the addresses:
print('Recipient username: {}'.format(headers['to'].addresses[0].username))
print('Sender name: {}'.format(headers['from'].addresses[0].display_name))

Voici un exemple de l’envoi d’un message MIME contenant une série de photos de famille qui sont stockés ensemble dans un dossier :

# Import smtplib for the actual sending function
import smtplib

# And imghdr to find the types of our images
import imghdr

# Here are the email package modules we'll need
from email.message import EmailMessage

# Create the container email message.
msg = EmailMessage()
msg['Subject'] = 'Our family reunion'
# me == the sender's email address
# family = the list of all recipients' email addresses
msg['From'] = me
msg['To'] = ', '.join(family)
msg.preamble = 'Our family reunion'

# Open the files in binary mode.  Use imghdr to figure out the
# MIME subtype for each specific image.
for file in pngfiles:
    with open(file, 'rb') as fp:
        img_data = fp.read()
    msg.add_attachment(img_data, maintype='image',
                                 subtype=imghdr.what(None, img_data))

# Send the email via our own SMTP server.
with smtplib.SMTP('localhost') as s:
    s.send_message(msg)

Voici un exemple d’envoi du contenu d’un dossier entier en tant que message mail : 1

#!/usr/bin/env python3

"""Send the contents of a directory as a MIME message."""

import os
import smtplib
# For guessing MIME type based on file name extension
import mimetypes

from argparse import ArgumentParser

from email.message import EmailMessage
from email.policy import SMTP

def main():
    parser = ArgumentParser(description="""\
Send the contents of a directory as a MIME message.
Unless the -o option is given, the email is sent by forwarding to your local
SMTP server, which then does the normal delivery process.  Your local machine
must be running an SMTP server.
""")
    parser.add_argument('-d', '--directory',
                        help="""Mail the contents of the specified directory,
                        otherwise use the current directory.  Only the regular
                        files in the directory are sent, and we don't recurse to
                        subdirectories.""")
    parser.add_argument('-o', '--output',
                        metavar='FILE',
                        help="""Print the composed message to FILE instead of
                        sending the message to the SMTP server.""")
    parser.add_argument('-s', '--sender', required=True,
                        help='The value of the From: header (required)')
    parser.add_argument('-r', '--recipient', required=True,
                        action='append', metavar='RECIPIENT',
                        default=[], dest='recipients',
                        help='A To: header value (at least one required)')
    args = parser.parse_args()
    directory = args.directory
    if not directory:
        directory = '.'
    # Create the message
    msg = EmailMessage()
    msg['Subject'] = 'Contents of directory %s' % os.path.abspath(directory)
    msg['To'] = ', '.join(args.recipients)
    msg['From'] = args.sender
    msg.preamble = 'You will not see this in a MIME-aware mail reader.\n'

    for filename in os.listdir(directory):
        path = os.path.join(directory, filename)
        if not os.path.isfile(path):
            continue
        # Guess the content type based on the file's extension.  Encoding
        # will be ignored, although we should check for simple things like
        # gzip'd or compressed files.
        ctype, encoding = mimetypes.guess_type(path)
        if ctype is None or encoding is not None:
            # No guess could be made, or the file is encoded (compressed), so
            # use a generic bag-of-bits type.
            ctype = 'application/octet-stream'
        maintype, subtype = ctype.split('/', 1)
        with open(path, 'rb') as fp:
            msg.add_attachment(fp.read(),
                               maintype=maintype,
                               subtype=subtype,
                               filename=filename)
    # Now send or store the message
    if args.output:
        with open(args.output, 'wb') as fp:
            fp.write(msg.as_bytes(policy=SMTP))
    else:
        with smtplib.SMTP('localhost') as s:
            s.send_message(msg)

if __name__ == '__main__':
    main()

Voici un message de comment décomposer un message MIME comme celui ci dessus en tant que fichiers dans un dossier :

#!/usr/bin/env python3

"""Unpack a MIME message into a directory of files."""

import os
import email
import mimetypes

from email.policy import default

from argparse import ArgumentParser

def main():
    parser = ArgumentParser(description="""\
Unpack a MIME message into a directory of files.
""")
    parser.add_argument('-d', '--directory', required=True,
                        help="""Unpack the MIME message into the named
                        directory, which will be created if it doesn't already
                        exist.""")
    parser.add_argument('msgfile')
    args = parser.parse_args()

    with open(args.msgfile, 'rb') as fp:
        msg = email.message_from_binary_file(fp, policy=default)

    try:
        os.mkdir(args.directory)
    except FileExistsError:
        pass

    counter = 1
    for part in msg.walk():
        # multipart/* are just containers
        if part.get_content_maintype() == 'multipart':
            continue
        # Applications should really sanitize the given filename so that an
        # email message can't be used to overwrite important files
        filename = part.get_filename()
        if not filename:
            ext = mimetypes.guess_extension(part.get_content_type())
            if not ext:
                # Use a generic bag-of-bits extension
                ext = '.bin'
            filename = 'part-%03d%s' % (counter, ext)
        counter += 1
        with open(os.path.join(args.directory, filename), 'wb') as fp:
            fp.write(part.get_payload(decode=True))

if __name__ == '__main__':
    main()

Voici un exemple de création d’un message HTML avec une version en texte comme alternative. Pour rendre les choses un peu plus intéressantes, nous incluons aussi une image dans la partie HTML, nous sauvons une copie du message sur le disque, et nous l’envoyons.

#!/usr/bin/env python3

import smtplib

from email.message import EmailMessage
from email.headerregistry import Address
from email.utils import make_msgid

# Create the base text message.
msg = EmailMessage()
msg['Subject'] = "Ayons asperges pour le déjeuner"
msg['From'] = Address("Pepé Le Pew", "pepe", "example.com")
msg['To'] = (Address("Penelope Pussycat", "penelope", "example.com"),
             Address("Fabrette Pussycat", "fabrette", "example.com"))
msg.set_content("""\
Salut!

Cela ressemble à un excellent recipie[1] déjeuner.

[1] http://www.yummly.com/recipe/Roasted-Asparagus-Epicurious-203718

--Pepé
""")

# Add the html version.  This converts the message into a multipart/alternative
# container, with the original text message as the first part and the new html
# message as the second part.
asparagus_cid = make_msgid()
msg.add_alternative("""\
<html>
  <head></head>
  <body>
    <p>Salut!</p>
    <p>Cela ressemble à un excellent
        <a href="http://www.yummly.com/recipe/Roasted-Asparagus-Epicurious-203718">
            recipie
        </a> déjeuner.
    </p>
    <img src="cid:{asparagus_cid}" />
  </body>
</html>
""".format(asparagus_cid=asparagus_cid[1:-1]), subtype='html')
# note that we needed to peel the <> off the msgid for use in the html.

# Now add the related image to the html part.
with open("roasted-asparagus.jpg", 'rb') as img:
    msg.get_payload()[1].add_related(img.read(), 'image', 'jpeg',
                                     cid=asparagus_cid)

# Make a local copy of what we are going to send.
with open('outgoing.msg', 'wb') as f:
    f.write(bytes(msg))

# Send the message via local SMTP server.
with smtplib.SMTP('localhost') as s:
    s.send_message(msg)

Si on nous avait envoyé le message de l’exemple précédent, voici la manière avec laquelle nous pourrions le traiter :

import os
import sys
import tempfile
import mimetypes
import webbrowser

# Import the email modules we'll need
from email import policy
from email.parser import BytesParser

# An imaginary module that would make this work and be safe.
from imaginary import magic_html_parser

# In a real program you'd get the filename from the arguments.
with open('outgoing.msg', 'rb') as fp:
    msg = BytesParser(policy=policy.default).parse(fp)

# Now the header items can be accessed as a dictionary, and any non-ASCII will
# be converted to unicode:
print('To:', msg['to'])
print('From:', msg['from'])
print('Subject:', msg['subject'])

# If we want to print a preview of the message content, we can extract whatever
# the least formatted payload is and print the first three lines.  Of course,
# if the message has no plain text part printing the first three lines of html
# is probably useless, but this is just a conceptual example.
simplest = msg.get_body(preferencelist=('plain', 'html'))
print()
print(''.join(simplest.get_content().splitlines(keepends=True)[:3]))

ans = input("View full message?")
if ans.lower()[0] == 'n':
    sys.exit()

# We can extract the richest alternative in order to display it:
richest = msg.get_body()
partfiles = {}
if richest['content-type'].maintype == 'text':
    if richest['content-type'].subtype == 'plain':
        for line in richest.get_content().splitlines():
            print(line)
        sys.exit()
    elif richest['content-type'].subtype == 'html':
        body = richest
    else:
        print("Don't know how to display {}".format(richest.get_content_type()))
        sys.exit()
elif richest['content-type'].content_type == 'multipart/related':
    body = richest.get_body(preferencelist=('html'))
    for part in richest.iter_attachments():
        fn = part.get_filename()
        if fn:
            extension = os.path.splitext(part.get_filename())[1]
        else:
            extension = mimetypes.guess_extension(part.get_content_type())
        with tempfile.NamedTemporaryFile(suffix=extension, delete=False) as f:
            f.write(part.get_content())
            # again strip the <> to go from email form of cid to html form.
            partfiles[part['content-id'][1:-1]] = f.name
else:
    print("Don't know how to display {}".format(richest.get_content_type()))
    sys.exit()
with tempfile.NamedTemporaryFile(mode='w', delete=False) as f:
    # The magic_html_parser has to rewrite the href="cid:...." attributes to
    # point to the filenames in partfiles.  It also has to do a safety-sanitize
    # of the html.  It could be written using html.parser.
    f.write(magic_html_parser(body.get_content(), partfiles))
webbrowser.open(f.name)
os.remove(f.name)
for fn in partfiles.values():
    os.remove(fn)

# Of course, there are lots of email messages that could break this simple
# minded program, but it will handle the most common ones.

La sortie textuelle du code ci dessus est :

To: Penelope Pussycat <penelope@example.com>, Fabrette Pussycat <fabrette@example.com>
From: Pepé Le Pew <pepe@example.com>
Subject: Ayons asperges pour le déjeuner

Salut!

Cela ressemble à un excellent recipie[1] déjeuner.

Notes

1

Merci à Matthew Dixon Cowles pour l’inspiration originale et les exemples.

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19.1.9. email.message.Message: Representing an email message using the compat32 API

The Message class is very similar to the EmailMessage class, without the methods added by that class, and with the default behavior of certain other methods being slightly different. We also document here some methods that, while supported by the EmailMessage class, are not recommended unless you are dealing with legacy code.

The philosophy and structure of the two classes is otherwise the same.

This document describes the behavior under the default (for Message) policy Compat32. If you are going to use another policy, you should be using the EmailMessage class instead.

An email message consists of headers and a payload. Headers must be RFC 5233 [https://tools.ietf.org/html/rfc5233.html] style names and values, where the field name and value are separated by a colon. The colon is not part of either the field name or the field value. The payload may be a simple text message, or a binary object, or a structured sequence of sub-messages each with their own set of headers and their own payload. The latter type of payload is indicated by the message having a MIME type such as multipart/* or message/rfc822.

The conceptual model provided by a Message object is that of an ordered dictionary of headers with additional methods for accessing both specialized information from the headers, for accessing the payload, for generating a serialized version of the message, and for recursively walking over the object tree. Note that duplicate headers are supported but special methods must be used to access them.

The Message pseudo-dictionary is indexed by the header names, which must be ASCII values. The values of the dictionary are strings that are supposed to contain only ASCII characters; there is some special handling for non-ASCII input, but it doesn’t always produce the correct results. Headers are stored and returned in case-preserving form, but field names are matched case-insensitively. There may also be a single envelope header, also known as the Unix-From header or the From_ header. The payload is either a string or bytes, in the case of simple message objects, or a list of Message objects, for MIME container documents (e.g. multipart/* and message/rfc822).

Here are the methods of the Message class:

class email.message.Message(policy=compat32)

If policy is specified (it must be an instance of a policy class) use the rules it specifies to update and serialize the representation of the message. If policy is not set, use the compat32 policy, which maintains backward compatibility with the Python 3.2 version of the email package. For more information see the policy documentation.

Modifié dans la version 3.3: The policy keyword argument was added.

as_string(unixfrom=False, maxheaderlen=0, policy=None)

Return the entire message flattened as a string. When optional unixfrom is true, the envelope header is included in the returned string. unixfrom defaults to False. For backward compatibility reasons, maxheaderlen defaults to 0, so if you want a different value you must override it explicitly (the value specified for max_line_length in the policy will be ignored by this method). The policy argument may be used to override the default policy obtained from the message instance. This can be used to control some of the formatting produced by the method, since the specified policy will be passed to the Generator.

Flattening the message may trigger changes to the Message if defaults need to be filled in to complete the transformation to a string (for example, MIME boundaries may be generated or modified).

Note that this method is provided as a convenience and may not always format the message the way you want. For example, by default it does not do the mangling of lines that begin with From that is required by the unix mbox format. For more flexibility, instantiate a Generator instance and use its flatten() method directly. For example:

from io import StringIO
from email.generator import Generator
fp = StringIO()
g = Generator(fp, mangle_from_=True, maxheaderlen=60)
g.flatten(msg)
text = fp.getvalue()

If the message object contains binary data that is not encoded according to RFC standards, the non-compliant data will be replaced by unicode « unknown character » code points. (See also as_bytes() and BytesGenerator.)

Modifié dans la version 3.4: the policy keyword argument was added.

__str__()

Equivalent to as_string(). Allows str(msg) to produce a string containing the formatted message.

as_bytes(unixfrom=False, policy=None)

Return the entire message flattened as a bytes object. When optional unixfrom is true, the envelope header is included in the returned string. unixfrom defaults to False. The policy argument may be used to override the default policy obtained from the message instance. This can be used to control some of the formatting produced by the method, since the specified policy will be passed to the BytesGenerator.

Flattening the message may trigger changes to the Message if defaults need to be filled in to complete the transformation to a string (for example, MIME boundaries may be generated or modified).

Note that this method is provided as a convenience and may not always format the message the way you want. For example, by default it does not do the mangling of lines that begin with From that is required by the unix mbox format. For more flexibility, instantiate a BytesGenerator instance and use its flatten() method directly. For example:

from io import BytesIO
from email.generator import BytesGenerator
fp = BytesIO()
g = BytesGenerator(fp, mangle_from_=True, maxheaderlen=60)
g.flatten(msg)
text = fp.getvalue()

Nouveau dans la version 3.4.

__bytes__()

Equivalent to as_bytes(). Allows bytes(msg) to produce a bytes object containing the formatted message.

Nouveau dans la version 3.4.

is_multipart()

Return True if the message’s payload is a list of sub-Message objects, otherwise return False. When is_multipart() returns False, the payload should be a string object (which might be a CTE encoded binary payload). (Note that is_multipart() returning True does not necessarily mean that « msg.get_content_maintype() == “multipart” » will return the True. For example, is_multipart will return True when the Message is of type message/rfc822.)

set_unixfrom(unixfrom)

Set the message’s envelope header to unixfrom, which should be a string.

get_unixfrom()

Return the message’s envelope header. Defaults to None if the envelope header was never set.

attach(payload)

Add the given payload to the current payload, which must be None or a list of Message objects before the call. After the call, the payload will always be a list of Message objects. If you want to set the payload to a scalar object (e.g. a string), use set_payload() instead.

This is a legacy method. On the EmailMessage class its functionality is replaced by set_content() and the related make and add methods.

get_payload(i=None, decode=False)

Return the current payload, which will be a list of Message objects when is_multipart() is True, or a string when is_multipart() is False. If the payload is a list and you mutate the list object, you modify the message’s payload in place.

With optional argument i, get_payload() will return the i-th element of the payload, counting from zero, if is_multipart() is True. An IndexError will be raised if i is less than 0 or greater than or equal to the number of items in the payload. If the payload is a string (i.e. is_multipart() is False) and i is given, a TypeError is raised.

Optional decode is a flag indicating whether the payload should be decoded or not, according to the Content-Transfer-Encoding header. When True and the message is not a multipart, the payload will be decoded if this header’s value is quoted-printable or base64. If some other encoding is used, or Content-Transfer-Encoding header is missing, the payload is returned as-is (undecoded). In all cases the returned value is binary data. If the message is a multipart and the decode flag is True, then None is returned. If the payload is base64 and it was not perfectly formed (missing padding, characters outside the base64 alphabet), then an appropriate defect will be added to the message’s defect property (InvalidBase64PaddingDefect or InvalidBase64CharactersDefect, respectively).

When decode is False (the default) the body is returned as a string without decoding the Content-Transfer-Encoding. However, for a Content-Transfer-Encoding of 8bit, an attempt is made to decode the original bytes using the charset specified by the Content-Type header, using the replace error handler. If no charset is specified, or if the charset given is not recognized by the email package, the body is decoded using the default ASCII charset.

This is a legacy method. On the EmailMessage class its functionality is replaced by get_content() and iter_parts().

set_payload(payload, charset=None)

Set the entire message object’s payload to payload. It is the client’s responsibility to ensure the payload invariants. Optional charset sets the message’s default character set; see set_charset() for details.

This is a legacy method. On the EmailMessage class its functionality is replaced by set_content().

set_charset(charset)

Set the character set of the payload to charset, which can either be a Charset instance (see email.charset), a string naming a character set, or None. If it is a string, it will be converted to a Charset instance. If charset is None, the charset parameter will be removed from the Content-Type header (the message will not be otherwise modified). Anything else will generate a TypeError.

If there is no existing MIME-Version header one will be added. If there is no existing Content-Type header, one will be added with a value of text/plain. Whether the Content-Type header already exists or not, its charset parameter will be set to charset.output_charset. If charset.input_charset and charset.output_charset differ, the payload will be re-encoded to the output_charset. If there is no existing Content-Transfer-Encoding header, then the payload will be transfer-encoded, if needed, using the specified Charset, and a header with the appropriate value will be added. If a Content-Transfer-Encoding header already exists, the payload is assumed to already be correctly encoded using that Content-Transfer-Encoding and is not modified.

This is a legacy method. On the EmailMessage class its functionality is replaced by the charset parameter of the email.emailmessage.EmailMessage.set_content() method.

get_charset()

Return the Charset instance associated with the message’s payload.

This is a legacy method. On the EmailMessage class it always returns None.

The following methods implement a mapping-like interface for accessing the message’s RFC 2822 [https://tools.ietf.org/html/rfc2822.html] headers. Note that there are some semantic differences between these methods and a normal mapping (i.e. dictionary) interface. For example, in a dictionary there are no duplicate keys, but here there may be duplicate message headers. Also, in dictionaries there is no guaranteed order to the keys returned by keys(), but in a Message object, headers are always returned in the order they appeared in the original message, or were added to the message later. Any header deleted and then re-added are always appended to the end of the header list.

These semantic differences are intentional and are biased toward maximal convenience.

Note that in all cases, any envelope header present in the message is not included in the mapping interface.

In a model generated from bytes, any header values that (in contravention of the RFCs) contain non-ASCII bytes will, when retrieved through this interface, be represented as Header objects with a charset of unknown-8bit.

__len__()

Return the total number of headers, including duplicates.

__contains__(name)

Return true if the message object has a field named name. Matching is done case-insensitively and name should not include the trailing colon. Used for the in operator, e.g.:

if 'message-id' in myMessage:
   print('Message-ID:', myMessage['message-id'])

__getitem__(name)

Return the value of the named header field. name should not include the colon field separator. If the header is missing, None is returned; a KeyError is never raised.

Note that if the named field appears more than once in the message’s headers, exactly which of those field values will be returned is undefined. Use the get_all() method to get the values of all the extant named headers.

__setitem__(name, val)

Add a header to the message with field name name and value val. The field is appended to the end of the message’s existing fields.

Note that this does not overwrite or delete any existing header with the same name. If you want to ensure that the new header is the only one present in the message with field name name, delete the field first, e.g.:

del msg['subject']
msg['subject'] = 'Python roolz!'

__delitem__(name)

Delete all occurrences of the field with name name from the message’s headers. No exception is raised if the named field isn’t present in the headers.

keys()

Return a list of all the message’s header field names.

values()

Return a list of all the message’s field values.

items()

Return a list of 2-tuples containing all the message’s field headers and values.

get(name, failobj=None)

Return the value of the named header field. This is identical to __getitem__() except that optional failobj is returned if the named header is missing (defaults to None).

Here are some additional useful methods:

get_all(name, failobj=None)

Return a list of all the values for the field named name. If there are no such named headers in the message, failobj is returned (defaults to None).

add_header(_name, _value, **_params)

Extended header setting. This method is similar to __setitem__() except that additional header parameters can be provided as keyword arguments. _name is the header field to add and _value is the primary value for the header.

For each item in the keyword argument dictionary _params, the key is taken as the parameter name, with underscores converted to dashes (since dashes are illegal in Python identifiers). Normally, the parameter will be added as key="value" unless the value is None, in which case only the key will be added. If the value contains non-ASCII characters, it can be specified as a three tuple in the format (CHARSET, LANGUAGE, VALUE), where CHARSET is a string naming the charset to be used to encode the value, LANGUAGE can usually be set to None or the empty string (see RFC 2231 [https://tools.ietf.org/html/rfc2231.html] for other possibilities), and VALUE is the string value containing non-ASCII code points. If a three tuple is not passed and the value contains non-ASCII characters, it is automatically encoded in RFC 2231 [https://tools.ietf.org/html/rfc2231.html] format using a CHARSET of utf-8 and a LANGUAGE of None.

Here’s an example:

msg.add_header('Content-Disposition', 'attachment', filename='bud.gif')

This will add a header that looks like

Content-Disposition: attachment; filename="bud.gif"

An example with non-ASCII characters:

msg.add_header('Content-Disposition', 'attachment',
               filename=('iso-8859-1', '', 'Fußballer.ppt'))

Which produces

Content-Disposition: attachment; filename*="iso-8859-1''Fu%DFballer.ppt"

replace_header(_name, _value)

Replace a header. Replace the first header found in the message that matches _name, retaining header order and field name case. If no matching header was found, a KeyError is raised.

get_content_type()

Return the message’s content type. The returned string is coerced to lower case of the form maintype/subtype. If there was no Content-Type header in the message the default type as given by get_default_type() will be returned. Since according to RFC 2045 [https://tools.ietf.org/html/rfc2045.html], messages always have a default type, get_content_type() will always return a value.

RFC 2045 [https://tools.ietf.org/html/rfc2045.html] defines a message’s default type to be text/plain unless it appears inside a multipart/digest container, in which case it would be message/rfc822. If the Content-Type header has an invalid type specification, RFC 2045 [https://tools.ietf.org/html/rfc2045.html] mandates that the default type be text/plain.

get_content_maintype()

Return the message’s main content type. This is the maintype part of the string returned by get_content_type().

get_content_subtype()

Return the message’s sub-content type. This is the subtype part of the string returned by get_content_type().

get_default_type()

Return the default content type. Most messages have a default content type of text/plain, except for messages that are subparts of multipart/digest containers. Such subparts have a default content type of message/rfc822.

set_default_type(ctype)

Set the default content type. ctype should either be text/plain or message/rfc822, although this is not enforced. The default content type is not stored in the Content-Type header.

get_params(failobj=None, header='content-type', unquote=True)

Return the message’s Content-Type parameters, as a list. The elements of the returned list are 2-tuples of key/value pairs, as split on the '=' sign. The left hand side of the '=' is the key, while the right hand side is the value. If there is no '=' sign in the parameter the value is the empty string, otherwise the value is as described in get_param() and is unquoted if optional unquote is True (the default).

Optional failobj is the object to return if there is no Content-Type header. Optional header is the header to search instead of Content-Type.

This is a legacy method. On the EmailMessage class its functionality is replaced by the params property of the individual header objects returned by the header access methods.

get_param(param, failobj=None, header='content-type', unquote=True)

Return the value of the Content-Type header’s parameter param as a string. If the message has no Content-Type header or if there is no such parameter, then failobj is returned (defaults to None).

Optional header if given, specifies the message header to use instead of Content-Type.

Parameter keys are always compared case insensitively. The return value can either be a string, or a 3-tuple if the parameter was RFC 2231 [https://tools.ietf.org/html/rfc2231.html] encoded. When it’s a 3-tuple, the elements of the value are of the form (CHARSET, LANGUAGE, VALUE). Note that both CHARSET and LANGUAGE can be None, in which case you should consider VALUE to be encoded in the us-ascii charset. You can usually ignore LANGUAGE.

If your application doesn’t care whether the parameter was encoded as in RFC 2231 [https://tools.ietf.org/html/rfc2231.html], you can collapse the parameter value by calling email.utils.collapse_rfc2231_value(), passing in the return value from get_param(). This will return a suitably decoded Unicode string when the value is a tuple, or the original string unquoted if it isn’t. For example:

rawparam = msg.get_param('foo')
param = email.utils.collapse_rfc2231_value(rawparam)

In any case, the parameter value (either the returned string, or the VALUE item in the 3-tuple) is always unquoted, unless unquote is set to False.

This is a legacy method. On the EmailMessage class its functionality is replaced by the params property of the individual header objects returned by the header access methods.

set_param(param, value, header='Content-Type', requote=True, charset=None, language='', replace=False)

Set a parameter in the Content-Type header. If the parameter already exists in the header, its value will be replaced with value. If the Content-Type header as not yet been defined for this message, it will be set to text/plain and the new parameter value will be appended as per RFC 2045 [https://tools.ietf.org/html/rfc2045.html].

Optional header specifies an alternative header to Content-Type, and all parameters will be quoted as necessary unless optional requote is False (the default is True).

If optional charset is specified, the parameter will be encoded according to RFC 2231 [https://tools.ietf.org/html/rfc2231.html]. Optional language specifies the RFC 2231 language, defaulting to the empty string. Both charset and language should be strings.

If replace is False (the default) the header is moved to the end of the list of headers. If replace is True, the header will be updated in place.

Modifié dans la version 3.4: replace keyword was added.

del_param(param, header='content-type', requote=True)

Remove the given parameter completely from the Content-Type header. The header will be re-written in place without the parameter or its value. All values will be quoted as necessary unless requote is False (the default is True). Optional header specifies an alternative to Content-Type.

set_type(type, header='Content-Type', requote=True)

Set the main type and subtype for the Content-Type header. type must be a string in the form maintype/subtype, otherwise a ValueError is raised.

This method replaces the Content-Type header, keeping all the parameters in place. If requote is False, this leaves the existing header’s quoting as is, otherwise the parameters will be quoted (the default).

An alternative header can be specified in the header argument. When the Content-Type header is set a MIME-Version header is also added.

This is a legacy method. On the EmailMessage class its functionality is replaced by the make_ and add_ methods.

get_filename(failobj=None)

Return the value of the filename parameter of the Content-Disposition header of the message. If the header does not have a filename parameter, this method falls back to looking for the name parameter on the Content-Type header. If neither is found, or the header is missing, then failobj is returned. The returned string will always be unquoted as per email.utils.unquote().

get_boundary(failobj=None)

Return the value of the boundary parameter of the Content-Type header of the message, or failobj if either the header is missing, or has no boundary parameter. The returned string will always be unquoted as per email.utils.unquote().

set_boundary(boundary)

Set the boundary parameter of the Content-Type header to boundary. set_boundary() will always quote boundary if necessary. A HeaderParseError is raised if the message object has no Content-Type header.

Note that using this method is subtly different than deleting the old Content-Type header and adding a new one with the new boundary via add_header(), because set_boundary() preserves the order of the Content-Type header in the list of headers. However, it does not preserve any continuation lines which may have been present in the original Content-Type header.

get_content_charset(failobj=None)

Return the charset parameter of the Content-Type header, coerced to lower case. If there is no Content-Type header, or if that header has no charset parameter, failobj is returned.

Note that this method differs from get_charset() which returns the Charset instance for the default encoding of the message body.

get_charsets(failobj=None)

Return a list containing the character set names in the message. If the message is a multipart, then the list will contain one element for each subpart in the payload, otherwise, it will be a list of length 1.

Each item in the list will be a string which is the value of the charset parameter in the Content-Type header for the represented subpart. However, if the subpart has no Content-Type header, no charset parameter, or is not of the text main MIME type, then that item in the returned list will be failobj.

get_content_disposition()

Return the lowercased value (without parameters) of the message’s Content-Disposition header if it has one, or None. The possible values for this method are inline, attachment or None if the message follows RFC 2183 [https://tools.ietf.org/html/rfc2183.html].

Nouveau dans la version 3.5.

walk()

The walk() method is an all-purpose generator which can be used to iterate over all the parts and subparts of a message object tree, in depth-first traversal order. You will typically use walk() as the iterator in a for loop; each iteration returns the next subpart.

Here’s an example that prints the MIME type of every part of a multipart message structure:

>>> for part in msg.walk():
...     print(part.get_content_type())
multipart/report
text/plain
message/delivery-status
text/plain
text/plain
message/rfc822
text/plain

walk iterates over the subparts of any part where is_multipart() returns True, even though msg.get_content_maintype() == 'multipart' may return False. We can see this in our example by making use of the _structure debug helper function:

>>> for part in msg.walk():
...     print(part.get_content_maintype() == 'multipart'),
...           part.is_multipart())
True True
False False
False True
False False
False False
False True
False False
>>> _structure(msg)
multipart/report
    text/plain
message/delivery-status
    text/plain
    text/plain
message/rfc822
    text/plain

Here the message parts are not multiparts, but they do contain subparts. is_multipart() returns True and walk descends into the subparts.

Message objects can also optionally contain two instance attributes, which can be used when generating the plain text of a MIME message.

preamble

The format of a MIME document allows for some text between the blank line following the headers, and the first multipart boundary string. Normally, this text is never visible in a MIME-aware mail reader because it falls outside the standard MIME armor. However, when viewing the raw text of the message, or when viewing the message in a non-MIME aware reader, this text can become visible.

The preamble attribute contains this leading extra-armor text for MIME documents. When the Parser discovers some text after the headers but before the first boundary string, it assigns this text to the message’s preamble attribute. When the Generator is writing out the plain text representation of a MIME message, and it finds the message has a preamble attribute, it will write this text in the area between the headers and the first boundary. See email.parser and email.generator for details.

Note that if the message object has no preamble, the preamble attribute will be None.

epilogue

The epilogue attribute acts the same way as the preamble attribute, except that it contains text that appears between the last boundary and the end of the message.

You do not need to set the epilogue to the empty string in order for the Generator to print a newline at the end of the file.

defects

The defects attribute contains a list of all the problems found when parsing this message. See email.errors for a detailed description of the possible parsing defects.

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19.1.10. email.mime: Creating email and MIME objects from scratch

Source code: Lib/email/mime/ [https://github.com/python/cpython/tree/3.6/Lib/email/mime/]

This module is part of the legacy (Compat32) email API. Its functionality is partially replaced by the contentmanager in the new API, but in certain applications these classes may still be useful, even in non-legacy code.

Ordinarily, you get a message object structure by passing a file or some text to a parser, which parses the text and returns the root message object. However you can also build a complete message structure from scratch, or even individual Message objects by hand. In fact, you can also take an existing structure and add new Message objects, move them around, etc. This makes a very convenient interface for slicing-and-dicing MIME messages.

You can create a new object structure by creating Message instances, adding attachments and all the appropriate headers manually. For MIME messages though, the email package provides some convenient subclasses to make things easier.

Here are the classes:

class email.mime.base.MIMEBase(_maintype, _subtype, *, policy=compat32, **_params)

Module : email.mime.base

This is the base class for all the MIME-specific subclasses of Message. Ordinarily you won’t create instances specifically of MIMEBase, although you could. MIMEBase is provided primarily as a convenient base class for more specific MIME-aware subclasses.

_maintype is the Content-Type major type (e.g. text or image), and _subtype is the Content-Type minor type (e.g. plain or gif). _params is a parameter key/value dictionary and is passed directly to Message.add_header.

If policy is specified, (defaults to the compat32 policy) it will be passed to Message.

The MIMEBase class always adds a Content-Type header (based on _maintype, _subtype, and _params), and a MIME-Version header (always set to 1.0).

Modifié dans la version 3.6: Added policy keyword-only parameter.

class email.mime.nonmultipart.MIMENonMultipart

Module : email.mime.nonmultipart

A subclass of MIMEBase, this is an intermediate base class for MIME messages that are not multipart. The primary purpose of this class is to prevent the use of the attach() method, which only makes sense for multipart messages. If attach() is called, a MultipartConversionError exception is raised.

class email.mime.multipart.MIMEMultipart(_subtype='mixed', boundary=None, _subparts=None, *, policy=compat32, **_params)

Module : email.mime.multipart

A subclass of MIMEBase, this is an intermediate base class for MIME messages that are multipart. Optional _subtype defaults to mixed, but can be used to specify the subtype of the message. A Content-Type header of multipart/_subtype will be added to the message object. A MIME-Version header will also be added.

Optional boundary is the multipart boundary string. When None (the default), the boundary is calculated when needed (for example, when the message is serialized).

_subparts is a sequence of initial subparts for the payload. It must be possible to convert this sequence to a list. You can always attach new subparts to the message by using the Message.attach method.

Optional policy argument defaults to compat32.

Additional parameters for the Content-Type header are taken from the keyword arguments, or passed into the _params argument, which is a keyword dictionary.

Modifié dans la version 3.6: Added policy keyword-only parameter.

class email.mime.application.MIMEApplication(_data, _subtype='octet-stream', _encoder=email.encoders.encode_base64, *, policy=compat32, **_params)

Module : email.mime.application

A subclass of MIMENonMultipart, the MIMEApplication class is used to represent MIME message objects of major type application. _data is a string containing the raw byte data. Optional _subtype specifies the MIME subtype and defaults to octet-stream.

Optional _encoder is a callable (i.e. function) which will perform the actual encoding of the data for transport. This callable takes one argument, which is the MIMEApplication instance. It should use get_payload() and set_payload() to change the payload to encoded form. It should also add any Content-Transfer-Encoding or other headers to the message object as necessary. The default encoding is base64. See the email.encoders module for a list of the built-in encoders.

Optional policy argument defaults to compat32.

_params are passed straight through to the base class constructor.

Modifié dans la version 3.6: Added policy keyword-only parameter.

class email.mime.audio.MIMEAudio(_audiodata, _subtype=None, _encoder=email.encoders.encode_base64, *, policy=compat32, **_params)

Module : email.mime.audio

A subclass of MIMENonMultipart, the MIMEAudio class is used to create MIME message objects of major type audio. _audiodata is a string containing the raw audio data. If this data can be decoded by the standard Python module sndhdr, then the subtype will be automatically included in the Content-Type header. Otherwise you can explicitly specify the audio subtype via the _subtype argument. If the minor type could not be guessed and _subtype was not given, then TypeError is raised.

Optional _encoder is a callable (i.e. function) which will perform the actual encoding of the audio data for transport. This callable takes one argument, which is the MIMEAudio instance. It should use get_payload() and set_payload() to change the payload to encoded form. It should also add any Content-Transfer-Encoding or other headers to the message object as necessary. The default encoding is base64. See the email.encoders module for a list of the built-in encoders.

Optional policy argument defaults to compat32.

_params are passed straight through to the base class constructor.

Modifié dans la version 3.6: Added policy keyword-only parameter.

class email.mime.image.MIMEImage(_imagedata, _subtype=None, _encoder=email.encoders.encode_base64, *, policy=compat32, **_params)

Module : email.mime.image

A subclass of MIMENonMultipart, the MIMEImage class is used to create MIME message objects of major type image. _imagedata is a string containing the raw image data. If this data can be decoded by the standard Python module imghdr, then the subtype will be automatically included in the Content-Type header. Otherwise you can explicitly specify the image subtype via the _subtype argument. If the minor type could not be guessed and _subtype was not given, then TypeError is raised.

Optional _encoder is a callable (i.e. function) which will perform the actual encoding of the image data for transport. This callable takes one argument, which is the MIMEImage instance. It should use get_payload() and set_payload() to change the payload to encoded form. It should also add any Content-Transfer-Encoding or other headers to the message object as necessary. The default encoding is base64. See the email.encoders module for a list of the built-in encoders.

Optional policy argument defaults to compat32.

_params are passed straight through to the MIMEBase constructor.

Modifié dans la version 3.6: Added policy keyword-only parameter.

class email.mime.message.MIMEMessage(_msg, _subtype='rfc822', *, policy=compat32)

Module : email.mime.message

A subclass of MIMENonMultipart, the MIMEMessage class is used to create MIME objects of main type message. _msg is used as the payload, and must be an instance of class Message (or a subclass thereof), otherwise a TypeError is raised.

Optional _subtype sets the subtype of the message; it defaults to rfc822.

Optional policy argument defaults to compat32.

Modifié dans la version 3.6: Added policy keyword-only parameter.

class email.mime.text.MIMEText(_text, _subtype='plain', _charset=None, *, policy=compat32)

Module : email.mime.text

A subclass of MIMENonMultipart, the MIMEText class is used to create MIME objects of major type text. _text is the string for the payload. _subtype is the minor type and defaults to plain. _charset is the character set of the text and is passed as an argument to the MIMENonMultipart constructor; it defaults to us-ascii if the string contains only ascii code points, and utf-8 otherwise. The _charset parameter accepts either a string or a Charset instance.

Unless the _charset argument is explicitly set to None, the MIMEText object created will have both a Content-Type header with a charset parameter, and a Content-Transfer-Encoding header. This means that a subsequent set_payload call will not result in an encoded payload, even if a charset is passed in the set_payload command. You can « reset » this behavior by deleting the Content-Transfer-Encoding header, after which a set_payload call will automatically encode the new payload (and add a new Content-Transfer-Encoding header).

Optional policy argument defaults to compat32.

Modifié dans la version 3.5: _charset also accepts Charset instances.

Modifié dans la version 3.6: Added policy keyword-only parameter.

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19.1.11. email.header: Internationalized headers

Source code: Lib/email/header.py [https://github.com/python/cpython/tree/3.6/Lib/email/header.py]

This module is part of the legacy (Compat32) email API. In the current API encoding and decoding of headers is handled transparently by the dictionary-like API of the EmailMessage class. In addition to uses in legacy code, this module can be useful in applications that need to completely control the character sets used when encoding headers.

Le texte restant de cette section est la documentation originale de ce module.

RFC 2822 [https://tools.ietf.org/html/rfc2822.html] is the base standard that describes the format of email messages. It derives from the older RFC 822 [https://tools.ietf.org/html/rfc822.html] standard which came into widespread use at a time when most email was composed of ASCII characters only. RFC 2822 [https://tools.ietf.org/html/rfc2822.html] is a specification written assuming email contains only 7-bit ASCII characters.

Of course, as email has been deployed worldwide, it has become internationalized, such that language specific character sets can now be used in email messages. The base standard still requires email messages to be transferred using only 7-bit ASCII characters, so a slew of RFCs have been written describing how to encode email containing non-ASCII characters into RFC 2822 [https://tools.ietf.org/html/rfc2822.html]-compliant format. These RFCs include RFC 2045 [https://tools.ietf.org/html/rfc2045.html], RFC 2046 [https://tools.ietf.org/html/rfc2046.html], RFC 2047 [https://tools.ietf.org/html/rfc2047.html], and RFC 2231 [https://tools.ietf.org/html/rfc2231.html]. The email package supports these standards in its email.header and email.charset modules.

If you want to include non-ASCII characters in your email headers, say in the Subject or To fields, you should use the Header class and assign the field in the Message object to an instance of Header instead of using a string for the header value. Import the Header class from the email.header module. For example:

>>> from email.message import Message
>>> from email.header import Header
>>> msg = Message()
>>> h = Header('p\xf6stal', 'iso-8859-1')
>>> msg['Subject'] = h
>>> msg.as_string()
'Subject: =?iso-8859-1?q?p=F6stal?=\n\n'

Notice here how we wanted the Subject field to contain a non-ASCII character? We did this by creating a Header instance and passing in the character set that the byte string was encoded in. When the subsequent Message instance was flattened, the Subject field was properly RFC 2047 [https://tools.ietf.org/html/rfc2047.html] encoded. MIME-aware mail readers would show this header using the embedded ISO-8859-1 character.

Here is the Header class description:

class email.header.Header(s=None, charset=None, maxlinelen=None, header_name=None, continuation_ws=' ', errors='strict')

Create a MIME-compliant header that can contain strings in different character sets.

Optional s is the initial header value. If None (the default), the initial header value is not set. You can later append to the header with append() method calls. s may be an instance of bytes or str, but see the append() documentation for semantics.

Optional charset serves two purposes: it has the same meaning as the charset argument to the append() method. It also sets the default character set for all subsequent append() calls that omit the charset argument. If charset is not provided in the constructor (the default), the us-ascii character set is used both as s’s initial charset and as the default for subsequent append() calls.

The maximum line length can be specified explicitly via maxlinelen. For splitting the first line to a shorter value (to account for the field header which isn’t included in s, e.g. Subject) pass in the name of the field in header_name. The default maxlinelen is 76, and the default value for header_name is None, meaning it is not taken into account for the first line of a long, split header.

Optional continuation_ws must be RFC 2822 [https://tools.ietf.org/html/rfc2822.html]-compliant folding whitespace, and is usually either a space or a hard tab character. This character will be prepended to continuation lines. continuation_ws defaults to a single space character.

Optional errors is passed straight through to the append() method.

append(s, charset=None, errors='strict')

Append the string s to the MIME header.

Optional charset, if given, should be a Charset instance (see email.charset) or the name of a character set, which will be converted to a Charset instance. A value of None (the default) means that the charset given in the constructor is used.

s may be an instance of bytes or str. If it is an instance of bytes, then charset is the encoding of that byte string, and a UnicodeError will be raised if the string cannot be decoded with that character set.

If s is an instance of str, then charset is a hint specifying the character set of the characters in the string.

In either case, when producing an RFC 2822 [https://tools.ietf.org/html/rfc2822.html]-compliant header using RFC 2047 [https://tools.ietf.org/html/rfc2047.html] rules, the string will be encoded using the output codec of the charset. If the string cannot be encoded using the output codec, a UnicodeError will be raised.

Optional errors is passed as the errors argument to the decode call if s is a byte string.

encode(splitchars=';, \t', maxlinelen=None, linesep='\n')

Encode a message header into an RFC-compliant format, possibly wrapping long lines and encapsulating non-ASCII parts in base64 or quoted-printable encodings.

Optional splitchars is a string containing characters which should be given extra weight by the splitting algorithm during normal header wrapping. This is in very rough support of RFC 2822 [https://tools.ietf.org/html/rfc2822.html]’s “higher level syntactic breaks”: split points preceded by a splitchar are preferred during line splitting, with the characters preferred in the order in which they appear in the string. Space and tab may be included in the string to indicate whether preference should be given to one over the other as a split point when other split chars do not appear in the line being split. Splitchars does not affect RFC 2047 [https://tools.ietf.org/html/rfc2047.html] encoded lines.

maxlinelen, if given, overrides the instance’s value for the maximum line length.

linesep specifies the characters used to separate the lines of the folded header. It defaults to the most useful value for Python application code (\n), but \r\n can be specified in order to produce headers with RFC-compliant line separators.

Modifié dans la version 3.2: Added the linesep argument.

The Header class also provides a number of methods to support standard operators and built-in functions.

__str__()

Returns an approximation of the Header as a string, using an unlimited line length. All pieces are converted to unicode using the specified encoding and joined together appropriately. Any pieces with a charset of 'unknown-8bit' are decoded as ASCII using the 'replace' error handler.

Modifié dans la version 3.2: Added handling for the 'unknown-8bit' charset.

__eq__(other)

This method allows you to compare two Header instances for equality.

__ne__(other)

This method allows you to compare two Header instances for inequality.

The email.header module also provides the following convenient functions.

email.header.decode_header(header)

Decode a message header value without converting the character set. The header value is in header.

This function returns a list of (decoded_string, charset) pairs containing each of the decoded parts of the header. charset is None for non-encoded parts of the header, otherwise a lower case string containing the name of the character set specified in the encoded string.

Here’s an example:

>>> from email.header import decode_header
>>> decode_header('=?iso-8859-1?q?p=F6stal?=')
[(b'p\xf6stal', 'iso-8859-1')]

email.header.make_header(decoded_seq, maxlinelen=None, header_name=None, continuation_ws=' ')

Create a Header instance from a sequence of pairs as returned by decode_header().

decode_header() takes a header value string and returns a sequence of pairs of the format (decoded_string, charset) where charset is the name of the character set.

This function takes one of those sequence of pairs and returns a Header instance. Optional maxlinelen, header_name, and continuation_ws are as in the Header constructor.

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19.1.12. email.charset: Representing character sets

Source code: Lib/email/charset.py [https://github.com/python/cpython/tree/3.6/Lib/email/charset.py]

This module is part of the legacy (Compat32) email API. In the new API only the aliases table is used.

Le texte restant de cette section est la documentation originale de ce module.

This module provides a class Charset for representing character sets and character set conversions in email messages, as well as a character set registry and several convenience methods for manipulating this registry. Instances of Charset are used in several other modules within the email package.

Import this class from the email.charset module.

class email.charset.Charset(input_charset=DEFAULT_CHARSET)

Map character sets to their email properties.

This class provides information about the requirements imposed on email for a specific character set. It also provides convenience routines for converting between character sets, given the availability of the applicable codecs. Given a character set, it will do its best to provide information on how to use that character set in an email message in an RFC-compliant way.

Certain character sets must be encoded with quoted-printable or base64 when used in email headers or bodies. Certain character sets must be converted outright, and are not allowed in email.

Optional input_charset is as described below; it is always coerced to lower case. After being alias normalized it is also used as a lookup into the registry of character sets to find out the header encoding, body encoding, and output conversion codec to be used for the character set. For example, if input_charset is iso-8859-1, then headers and bodies will be encoded using quoted-printable and no output conversion codec is necessary. If input_charset is euc-jp, then headers will be encoded with base64, bodies will not be encoded, but output text will be converted from the euc-jp character set to the iso-2022-jp character set.

Charset instances have the following data attributes:

input_charset

The initial character set specified. Common aliases are converted to their official email names (e.g. latin_1 is converted to iso-8859-1). Defaults to 7-bit us-ascii.

header_encoding

If the character set must be encoded before it can be used in an email header, this attribute will be set to Charset.QP (for quoted-printable), Charset.BASE64 (for base64 encoding), or Charset.SHORTEST for the shortest of QP or BASE64 encoding. Otherwise, it will be None.

body_encoding

Same as header_encoding, but describes the encoding for the mail message’s body, which indeed may be different than the header encoding. Charset.SHORTEST is not allowed for body_encoding.

output_charset

Some character sets must be converted before they can be used in email headers or bodies. If the input_charset is one of them, this attribute will contain the name of the character set output will be converted to. Otherwise, it will be None.

input_codec

The name of the Python codec used to convert the input_charset to Unicode. If no conversion codec is necessary, this attribute will be None.

output_codec

The name of the Python codec used to convert Unicode to the output_charset. If no conversion codec is necessary, this attribute will have the same value as the input_codec.

Charset instances also have the following methods:

get_body_encoding()

Return the content transfer encoding used for body encoding.

This is either the string quoted-printable or base64 depending on the encoding used, or it is a function, in which case you should call the function with a single argument, the Message object being encoded. The function should then set the Content-Transfer-Encoding header itself to whatever is appropriate.

Returns the string quoted-printable if body_encoding is QP, returns the string base64 if body_encoding is BASE64, and returns the string 7bit otherwise.

get_output_charset()

Return the output character set.

This is the output_charset attribute if that is not None, otherwise it is input_charset.

header_encode(string)

Header-encode the string string.

The type of encoding (base64 or quoted-printable) will be based on the header_encoding attribute.

header_encode_lines(string, maxlengths)

Header-encode a string by converting it first to bytes.

This is similar to header_encode() except that the string is fit into maximum line lengths as given by the argument maxlengths, which must be an iterator: each element returned from this iterator will provide the next maximum line length.

body_encode(string)

Body-encode the string string.

The type of encoding (base64 or quoted-printable) will be based on the body_encoding attribute.

The Charset class also provides a number of methods to support standard operations and built-in functions.

__str__()

Returns input_charset as a string coerced to lower case. __repr__() is an alias for __str__().

__eq__(other)

This method allows you to compare two Charset instances for equality.

__ne__(other)

This method allows you to compare two Charset instances for inequality.

The email.charset module also provides the following functions for adding new entries to the global character set, alias, and codec registries:

email.charset.add_charset(charset, header_enc=None, body_enc=None, output_charset=None)

Add character properties to the global registry.

charset is the input character set, and must be the canonical name of a character set.

Optional header_enc and body_enc is either Charset.QP for quoted-printable, Charset.BASE64 for base64 encoding, Charset.SHORTEST for the shortest of quoted-printable or base64 encoding, or None for no encoding. SHORTEST is only valid for header_enc. The default is None for no encoding.

Optional output_charset is the character set that the output should be in. Conversions will proceed from input charset, to Unicode, to the output charset when the method Charset.convert() is called. The default is to output in the same character set as the input.

Both input_charset and output_charset must have Unicode codec entries in the module’s character set-to-codec mapping; use add_codec() to add codecs the module does not know about. See the codecs module’s documentation for more information.

The global character set registry is kept in the module global dictionary CHARSETS.

email.charset.add_alias(alias, canonical)

Add a character set alias. alias is the alias name, e.g. latin-1. canonical is the character set’s canonical name, e.g. iso-8859-1.

The global charset alias registry is kept in the module global dictionary ALIASES.

email.charset.add_codec(charset, codecname)

Add a codec that map characters in the given character set to and from Unicode.

charset is the canonical name of a character set. codecname is the name of a Python codec, as appropriate for the second argument to the str’s encode() method.

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19.1.13. email.encoders : Encodeurs

Code source : Lib/email/encoders.py [https://github.com/python/cpython/tree/3.6/Lib/email/encoders.py]

Ce module fait partie du code patrimonial (Compat32) de l’API mail. Dans la nouvelle API la fonctionnalité est fournie par le paramètre cte de la méthode set_content().

Le texte restant de cette section est la documentation originale de ce module.

Au moment de la création d’objets Message à la main, il est souvent nécessaire d’encoder les charges utiles pour le transport à travers des serveurs mail conformes. C’est particulièrement vrai pour les messages de type image/* et text/* contenant des données binaires.

Le paquet email fournit quelques encodeurs pratiques dans son module encoders. Ces encodeurs sont d’ailleurs utilisés par les constructeurs des classes MIMEAudio et MIMEImage afin de fournir des encodages par défaut. Toutes les fonctions d’encodage prennent exactement un argument, l’objet message à encoder. Généralement, elles extraient la charge utile, l’encode, puis change la charge utile pour la nouvelle valeur encodée. Elles devraient également assigner l’en-tête Content-Transfer-Encoding si besoin.

À noter que ces fonctions n’ont pas de sens dans le cadre d’un message en plusieurs parties. Elles doivent à la place être appliquées aux sous-parties individuelles, et lèvent TypeError si on leur passe un message en plusieurs parties.

Voici les fonctions d’encodages fournies :

email.encoders.encode_quopri(msg)

Encode la charge utile au format Quoted-Printable, et assigne quoted-printable 1 à l’en-tête Content-Transfer-Encoding. C’est un bon encodage à utiliser quand la majorité de la charge utile contient essentiellement des données imprimables, à l’exceptions de quelques caractères.

email.encoders.encode_base64(msg)

Encode la charge utile au format base64, et assigne base64 à l’en-tête Content-Transfer-Encoding. C’est un bon encodage à utiliser quand la majorité de la charge utile est non imprimable puisque c’est une forme plus compacte que quoted-printable.

email.encoders.encode_7or8bit(msg)

Ceci ne modifie pas effectivement la charge utile du message, mais va bien en revanche assigner la valeur 7bit ou 8bit à l’en-tête Content-Transfer-Encoding selon la nature de la charge utile.

email.encoders.encode_noop(msg)

Ceci ne fait rien; et ne va même pas changer la valeur de l’en-tête Content-Transfer-Encoding.

Notes

1

À noter que l’encodage avec encode_quopri() encode également tous les caractères tabulation et espace.

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19.1.14. email.utils: Miscellaneous utilities

Source code: Lib/email/utils.py [https://github.com/python/cpython/tree/3.6/Lib/email/utils.py]

There are a couple of useful utilities provided in the email.utils module:

email.utils.localtime(dt=None)

Return local time as an aware datetime object. If called without arguments, return current time. Otherwise dt argument should be a datetime instance, and it is converted to the local time zone according to the system time zone database. If dt is naive (that is, dt.tzinfo is None), it is assumed to be in local time. In this case, a positive or zero value for isdst causes localtime to presume initially that summer time (for example, Daylight Saving Time) is or is not (respectively) in effect for the specified time. A negative value for isdst causes the localtime to attempt to divine whether summer time is in effect for the specified time.

Nouveau dans la version 3.3.

email.utils.make_msgid(idstring=None, domain=None)

Returns a string suitable for an RFC 2822 [https://tools.ietf.org/html/rfc2822.html]-compliant Message-ID header. Optional idstring if given, is a string used to strengthen the uniqueness of the message id. Optional domain if given provides the portion of the msgid after the “@”. The default is the local hostname. It is not normally necessary to override this default, but may be useful certain cases, such as a constructing distributed system that uses a consistent domain name across multiple hosts.

Modifié dans la version 3.2: Added the domain keyword.

The remaining functions are part of the legacy (Compat32) email API. There is no need to directly use these with the new API, since the parsing and formatting they provide is done automatically by the header parsing machinery of the new API.

email.utils.quote(str)

Return a new string with backslashes in str replaced by two backslashes, and double quotes replaced by backslash-double quote.

email.utils.unquote(str)

Return a new string which is an unquoted version of str. If str ends and begins with double quotes, they are stripped off. Likewise if str ends and begins with angle brackets, they are stripped off.

email.utils.parseaddr(address)

Parse address – which should be the value of some address-containing field such as To or Cc – into its constituent realname and email address parts. Returns a tuple of that information, unless the parse fails, in which case a 2-tuple of ('', '') is returned.

email.utils.formataddr(pair, charset='utf-8')

The inverse of parseaddr(), this takes a 2-tuple of the form (realname, email_address) and returns the string value suitable for a To or Cc header. If the first element of pair is false, then the second element is returned unmodified.

Optional charset is the character set that will be used in the RFC 2047 [https://tools.ietf.org/html/rfc2047.html] encoding of the realname if the realname contains non-ASCII characters. Can be an instance of str or a Charset. Defaults to utf-8.

Modifié dans la version 3.3: Added the charset option.

email.utils.getaddresses(fieldvalues)

This method returns a list of 2-tuples of the form returned by parseaddr(). fieldvalues is a sequence of header field values as might be returned by Message.get_all. Here’s a simple example that gets all the recipients of a message:

from email.utils import getaddresses

tos = msg.get_all('to', [])
ccs = msg.get_all('cc', [])
resent_tos = msg.get_all('resent-to', [])
resent_ccs = msg.get_all('resent-cc', [])
all_recipients = getaddresses(tos + ccs + resent_tos + resent_ccs)

email.utils.parsedate(date)

Attempts to parse a date according to the rules in RFC 2822 [https://tools.ietf.org/html/rfc2822.html]. however, some mailers don’t follow that format as specified, so parsedate() tries to guess correctly in such cases. date is a string containing an RFC 2822 [https://tools.ietf.org/html/rfc2822.html] date, such as "Mon, 20 Nov 1995 19:12:08 -0500". If it succeeds in parsing the date, parsedate() returns a 9-tuple that can be passed directly to time.mktime(); otherwise None will be returned. Note that indexes 6, 7, and 8 of the result tuple are not usable.

email.utils.parsedate_tz(date)

Performs the same function as parsedate(), but returns either None or a 10-tuple; the first 9 elements make up a tuple that can be passed directly to time.mktime(), and the tenth is the offset of the date’s timezone from UTC (which is the official term for Greenwich Mean Time) 1. If the input string has no timezone, the last element of the tuple returned is None. Note that indexes 6, 7, and 8 of the result tuple are not usable.

email.utils.parsedate_to_datetime(date)

The inverse of format_datetime(). Performs the same function as parsedate(), but on success returns a datetime. If the input date has a timezone of -0000, the datetime will be a naive datetime, and if the date is conforming to the RFCs it will represent a time in UTC but with no indication of the actual source timezone of the message the date comes from. If the input date has any other valid timezone offset, the datetime will be an aware datetime with the corresponding a timezone tzinfo.

Nouveau dans la version 3.3.

email.utils.mktime_tz(tuple)

Turn a 10-tuple as returned by parsedate_tz() into a UTC timestamp (seconds since the Epoch). If the timezone item in the tuple is None, assume local time.

email.utils.formatdate(timeval=None, localtime=False, usegmt=False)

Returns a date string as per RFC 2822 [https://tools.ietf.org/html/rfc2822.html], e.g.:

Fri, 09 Nov 2001 01:08:47 -0000

Optional timeval if given is a floating point time value as accepted by time.gmtime() and time.localtime(), otherwise the current time is used.

Optional localtime is a flag that when True, interprets timeval, and returns a date relative to the local timezone instead of UTC, properly taking daylight savings time into account. The default is False meaning UTC is used.

Optional usegmt is a flag that when True, outputs a date string with the timezone as an ascii string GMT, rather than a numeric -0000. This is needed for some protocols (such as HTTP). This only applies when localtime is False. The default is False.

email.utils.format_datetime(dt, usegmt=False)

Like formatdate, but the input is a datetime instance. If it is a naive datetime, it is assumed to be « UTC with no information about the source timezone », and the conventional -0000 is used for the timezone. If it is an aware datetime, then the numeric timezone offset is used. If it is an aware timezone with offset zero, then usegmt may be set to True, in which case the string GMT is used instead of the numeric timezone offset. This provides a way to generate standards conformant HTTP date headers.

Nouveau dans la version 3.3.

email.utils.decode_rfc2231(s)

Decode the string s according to RFC 2231 [https://tools.ietf.org/html/rfc2231.html].

email.utils.encode_rfc2231(s, charset=None, language=None)

Encode the string s according to RFC 2231 [https://tools.ietf.org/html/rfc2231.html]. Optional charset and language, if given is the character set name and language name to use. If neither is given, s is returned as-is. If charset is given but language is not, the string is encoded using the empty string for language.

email.utils.collapse_rfc2231_value(value, errors='replace', fallback_charset='us-ascii')

When a header parameter is encoded in RFC 2231 [https://tools.ietf.org/html/rfc2231.html] format, Message.get_param may return a 3-tuple containing the character set, language, and value. collapse_rfc2231_value() turns this into a unicode string. Optional errors is passed to the errors argument of str’s encode() method; it defaults to 'replace'. Optional fallback_charset specifies the character set to use if the one in the RFC 2231 [https://tools.ietf.org/html/rfc2231.html] header is not known by Python; it defaults to 'us-ascii'.

For convenience, if the value passed to collapse_rfc2231_value() is not a tuple, it should be a string and it is returned unquoted.

email.utils.decode_params(params)

Decode parameters list according to RFC 2231 [https://tools.ietf.org/html/rfc2231.html]. params is a sequence of 2-tuples containing elements of the form (content-type, string-value).

Notes

1

Note that the sign of the timezone offset is the opposite of the sign of the time.timezone variable for the same timezone; the latter variable follows the POSIX standard while this module follows RFC 2822 [https://tools.ietf.org/html/rfc2822.html].

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19.1.15. email.iterators: Itérateurs

Code source : Lib/email/iterators.py [https://github.com/python/cpython/tree/3.6/Lib/email/iterators.py]

Itérer sur l’arborescence d’un objet message est plutôt simple avec la méthode Message.walk. Le module email.iterators fournit des fonctionnalités d’itérations de plus haut niveau sur les arbres d’objets messages.

email.iterators.body_line_iterator(msg, decode=False)

Cette fonction permet d’itérer sur tous les contenus de tous les éléments de msg, en retournant les contenus sous forme de chaînes de caractères ligne par ligne. Il saute les entêtes des sous éléments, et tous les sous éléments dont le contenu n’est pas une chaîne de caractères Python. C’est en quelque sorte équivalent à une lecture plate d’une représentation textuelle du message à partir d’un fichier en utilisant readline(), et en sautant toutes les entêtes intermédiaires.

Le paramètre optionnel decode est transmis à la méthode Message.get_payload.

email.iterators.typed_subpart_iterator(msg, maintype='text', subtype=None)

Cette fonction permet d’itérer sur tous les sous éléments de msg, en retournant seulement les sous éléments qui correspondent au type MIME spécifié par maintype et subtype.

Notez que le paramètre subtype est optionnel ; s’il n’est pas présent, alors le type MIME du sous élément est seulement composé du type principal. maintype est également optionnel ; sa valeur par défaut est text.

En conséquence, par défaut, typed_subpart_iterator() retourne chaque sous élément qui a un type MIME de type text/*.

La fonction suivante a été ajouté en tant qu’un outil de débogage. Elle ne devrait pas être considérée comme une interface publique supportée pour ce paquet.

email.iterators._structure(msg, fp=None, level=0, include_default=False)

Affiche une représentation indentée des types de contenu de la structure de l’objet message. Par exemple :

>>> msg = email.message_from_file(somefile)
>>> _structure(msg)
multipart/mixed
    text/plain
    text/plain
    multipart/digest
        message/rfc822
            text/plain
        message/rfc822
            text/plain
        message/rfc822
            text/plain
        message/rfc822
            text/plain
        message/rfc822
            text/plain
    text/plain

Le paramètre optionnel fp est un objet fichier-compatible dans lequel on peut écrire le flux de sortie. Il doit être approprié pour la fonction de Python print(). level est utilisé en interne. include_default, si vrai, affiche aussi le type par défaut.

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19.2. json — Encodage et décodage JSON

Code source : Lib/json/__init__.py [https://github.com/python/cpython/tree/3.6/Lib/json/__init__.py]

JSON (JavaScript Object Notation) [http://json.org], spécifié par la RFC 7159 [https://tools.ietf.org/html/rfc7159.html] (qui rend la RFC 4627 [https://tools.ietf.org/html/rfc4627.html] obsolète) et par le standard ECMA-404 [http://www.ecma-international.org/publications/standards/Ecma-404.htm], est une interface légère d’échange de données inspirée par la syntaxe des objets littéraux JavaScript [https://fr.wikipedia.org/wiki/JavaScript] (bien que ce ne soit pas un sous-ensemble strict de Javascript 1 ).

json expose une API familière aux utilisateurs des modules de la bibliothèque standard marshal et pickle.

Encodage d’objets Python basiques :

>>> import json
>>> json.dumps(['foo', {'bar': ('baz', None, 1.0, 2)}])
'["foo", {"bar": ["baz", null, 1.0, 2]}]'
>>> print(json.dumps("\"foo\bar"))
"\"foo\bar"
>>> print(json.dumps('\u1234'))
"\u1234"
>>> print(json.dumps('\\'))
"\\"
>>> print(json.dumps({"c": 0, "b": 0, "a": 0}, sort_keys=True))
{"a": 0, "b": 0, "c": 0}
>>> from io import StringIO
>>> io = StringIO()
>>> json.dump(['streaming API'], io)
>>> io.getvalue()
'["streaming API"]'

Encodage compact :

>>> import json
>>> json.dumps([1, 2, 3, {'4': 5, '6': 7}], separators=(',', ':'))
'[1,2,3,{"4":5,"6":7}]'

Affichage élégant :

>>> import json
>>> print(json.dumps({'4': 5, '6': 7}, sort_keys=True, indent=4))
{
    "4": 5,
    "6": 7
}

Décodage JSON :

>>> import json
>>> json.loads('["foo", {"bar":["baz", null, 1.0, 2]}]')
['foo', {'bar': ['baz', None, 1.0, 2]}]
>>> json.loads('"\\"foo\\bar"')
'"foo\x08ar'
>>> from io import StringIO
>>> io = StringIO('["streaming API"]')
>>> json.load(io)
['streaming API']

Spécialisation du décodage JSON pour un objet :

>>> import json
>>> def as_complex(dct):
...     if '__complex__' in dct:
...         return complex(dct['real'], dct['imag'])
...     return dct
...
>>> json.loads('{"__complex__": true, "real": 1, "imag": 2}',
...     object_hook=as_complex)
(1+2j)
>>> import decimal
>>> json.loads('1.1', parse_float=decimal.Decimal)
Decimal('1.1')

Étendre la classe JSONEncoder :

>>> import json
>>> class ComplexEncoder(json.JSONEncoder):
...     def default(self, obj):
...         if isinstance(obj, complex):
...             return [obj.real, obj.imag]
...         # Let the base class default method raise the TypeError
...         return json.JSONEncoder.default(self, obj)
...
>>> json.dumps(2 + 1j, cls=ComplexEncoder)
'[2.0, 1.0]'
>>> ComplexEncoder().encode(2 + 1j)
'[2.0, 1.0]'
>>> list(ComplexEncoder().iterencode(2 + 1j))
['[2.0', ', 1.0', ']']

Utiliser json.tool depuis le shell pour valider et afficher élégamment :

$ echo '{"json":"obj"}' | python -m json.tool
{
    "json": "obj"
}
$ echo '{1.2:3.4}' | python -m json.tool
Expecting property name enclosed in double quotes: line 1 column 2 (char 1)

Voir Interface en ligne de commande pour une documentation détaillée.

Note

JSON est un sous-ensemble de YAML [http://yaml.org/] 1.2. Le JSON produit par les paramètres par défaut de ce module (en particulier, la valeur par défaut de separators) est aussi un sous ensemble de YAML 1.0 et 1.1. Ce module peut alors aussi être utilisé comme sérialiseur YAML.

19.2.1. Utilisation basique

json.dump(obj, fp, *, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, cls=None, indent=None, separators=None, default=None, sort_keys=False, **kw)

Sérialise obj comme un flux JSON formaté vers fp (un file-like object gérant .write()) utilisant cette table de conversion.

Si skipkeys est vrai (faux par défaut), alors les clefs de dictionnaires qui ne sont pas de types basiques (str, int, float, bool, None) seront ignorées, elles provoquent normalement la levée d’une TypeError.

Le module json produit toujours des objets str, et non des objets bytes. fp.write() doit ainsi supporter un objet str en entrée.

Si ensure_ascii est vrai (par défaut), il est garanti que les caractères non ASCII soient tous échappés sur la sortie. Si ensure_ascii est faux, ces caractères seront écrits comme tels.

Si check_circular est faux (vrai par défaut), la vérification des références circulaires pour les conteneurs sera ignorée, et une référence circulaire résultera en une OverflowError (ou pire).

Si allow_nan est faux (vrai par défaut), une ValueError sera levée lors de la sérialisation de valeurs float extérieures aux bornes (nan, inf, -inf), en respect strict de la spécification JSON. Si allow_nan est vrai, leurs équivalents JavaScript (NaN, Infinity, -Infinity) seront utilisés.

Si indent est un nombre entier positif ou une chaîne de caractères, les éléments de tableaux et les membres d’objets JSON seront affichés élégamment avec ce niveau d’indentation. Un niveau d’indentation de 0, négatif, ou "" n’insérera que des retours à la ligne. None (la valeur par défaut) choisit la représentation la plus compacte. Utiliser un entier positif comme indentation indente d’autant d’espaces par niveau. Si indent est une chaîne (telle que "\t"), cette chaîne est utilisée pour indenter à chaque niveau.

Modifié dans la version 3.2: Autorise les chaînes en plus des nombres entiers pour indent.

Si spécifié, separators doit être un tuple (item_separator, key_separator). Sa valeur par défaut est (', ', ': ') si indent est None, et (',', ': ') autrement. Pour obtenir la représentation JSON la plus compacte possible, vous devriez spécifier (',', ':') pour éliminer les espacements.

Modifié dans la version 3.4: Utilise (',', ': ') par défaut si indent n’est pas None.

Si spécifié, default doit être une fonction qui sera appelée pour les objets qui ne peuvent être sérialisés autrement. Elle doit renvoyer une représentation de l’objet sérialisable en JSON ou lever une TypeError. Si non spécifié, une TypeError sera levée pour les types non sérialisables.

Si sort_keys est vrai (faux par défaut), les dictionnaires seront retranscrits triés selon leurs clés.

Pour utiliser une sous-classe JSONEncoder personnalisée (p. ex. une qui redéfinit la méthode default() pour sérialiser des types additionnels), spécifiez-la avec le paramètre nommé cls ; autrement, JSONEncoder est utilisée.

Modifié dans la version 3.6: Tous les paramètres optionnels sont maintenant des keyword-only.

Note

À l’inverse de pickle et marshal, JSON n’est pas un protocole par trames, donc essayer de sérialiser de multiples objets par des appels répétés à dump() en utilisant le même fp résultera en un fichier JSON invalide.

json.dumps(obj, *, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, cls=None, indent=None, separators=None, default=None, sort_keys=False, **kw)

Sérialise obj vers un JSON formaté str, en utilisant cette table de conversion. Les arguments ont la même signification que ceux de dump().

Note

Les clés dans les couples JSON clé/valeur sont toujours de type str. Quand un dictionnaire est converti en JSON, toutes les clés du dictionnaire sont transformées en chaînes de caractères. Ce qui fait que si un dictionnaire est converti en JSON et reconverti en dictionnaire, le résultat peut ne pas être égal à l’original. Ainsi, loads(dumps(x)) != x si x contient des clés qui ne sont pas des chaînes.

json.load(fp, *, cls=None, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, object_pairs_hook=None, **kw)

Déserialise fp (un text file ou un binary file supportant .read() et contenant un document JSON) vers un objet Python en utilisant cette table de conversion.

object_hook est une fonction optionnelle qui sera appelée avec le résultat de chaque objet littéral décodé (chaque dict). La valeur de retour de object_hook sera utilisée à la place du dict. Cette fonctionnalité peut être utilisée pour implémenter des décodeurs personnalisés (p. ex. les class hinting de JSON-RPC [http://www.jsonrpc.org]).

object_pairs_hook est une fonction optionnelle qui sera appelé pour chaque objet littéral décodé, avec une liste ordonnée de couples. La valeur de retour de object_pairs_hook sera utilisée à la place du dict. Cette fonctionnalité peut être utilisée pour implémenter des décodeurs personnalisés qui s’appuient sur l’ordre dans lequel les couples clé/valeur sont décodés (par exemple, collections.OrderedDict() mémorisera l’ordre d’insertion). object_pairs_hook prend la priorité sur object_hook, si cette dernière est aussi définie.

Modifié dans la version 3.1: Ajout du support de object_pairs_hook.

parse_float, si spécifiée, sera appelée pour chaque nombre réel JSON à décoder sous forme d’une chaîne de caractères. Par défaut, elle est équivalente à float(num_str). Cela peut servir à utiliser un autre type de données ou un autre analyseur pour les nombres réels JSON (p. ex. decimal.Decimal).

parse_int, si spécifiée, sera appelée pour chaque nombre entier JSON à décoder sous forme d’une chaîne de caractères. Par défaut, elle est équivalente à int(num_str). Cela peut servir à utiliser un autre type de données ou un autre analyseur pour les nombres entiers JSON (p. ex. float).

parse_constant, si spécifiée, sera appelée avec l’une des chaînes de caractères suivantes : '-Infinity', 'Infinity' ou 'NaN'. Cela peut servir à lever une exception si des nombres JSON invalides sont rencontrés.

Modifié dans la version 3.1: parse_constant n’est plus appelée pour null, true ou false.

Pour utiliser une sous-classe JSONDecoder personnalisée, spécifiez-la avec l’argument nommé cls ; autrement, JSONDecoder est utilisée. Les arguments nommés additionnels seront passés au constructeur de cette classe.

Si les données à déserialiser ne sont pas un document JSON valide, une JSONDecodeError sera levée.

Modifié dans la version 3.6: Tous les paramètres optionnels sont maintenant des keyword-only.

Modifié dans la version 3.6: fp peut maintenant être un binary file. Son encodage doit être UTF-8, UTF-16 ou UTF-32.

json.loads(s, *, encoding=None, cls=None, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, object_pairs_hook=None, **kw)

Déserialise s (une instance de str, bytes ou bytearray contenant un document JSON) vers un objet Python en utilisant cette table de conversion.

Les autres arguments ont la même signification que pour load(), à l’exception d”encoding qui est ignoré et obsolète.

Si les données à déserialiser ne sont pas un document JSON valide, une JSONDecodeError sera levée.

Modifié dans la version 3.6: s peut maintenant être de type bytes ou bytearray. L’encodage d’entrée doit être UTF-8, UTF-16 ou UTF-32.

19.2.2. Encodeurs et décodeurs

class json.JSONDecoder(*, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, strict=True, object_pairs_hook=None)

Décodeur simple JSON.

Applique par défaut les conversions suivantes en décodant :

JSON

Python

objet

dict

array

list

string

str

number (nombre entier)

int

number (nombre réel)

float

true

True

false

False

null

None

Les valeurs NaN, Infinity et -Infinity sont aussi comprises comme leurs valeurs float correspondantes, bien que ne faisant pas partie de la spécification JSON.

object_hook, si spécifiée, sera appelée avec le résultat de chaque objet JSON décodé et sa valeur de retour sera utilisée à la place du dict donné. Cela peut être utilisé pour apporter des déserialisations personnalisées (p. ex. pour supporter les class hinting de JSON-RPC).

object_pairs_hook, si spécifiée, sera appelée avec le résultat de chaque objet JSON décodé avec une liste ordonnée de couples. Sa valeur de retour sera utilisée à la place du dict. Cette fonctionnalité peut être utilisée pour implémenter des décodeurs personnalisés se basant sur l’ordre dans lequel les couples clé/valeur sont décodés (par exemple, collections.OrderedDict() mémorisera l’ordre d’insertion). object_pairs_hook prend la priorité sur object_hook, si cette dernière est aussi définie.

Modifié dans la version 3.1: Ajout du support de object_pairs_hook.

parse_float, si spécifiée, sera appelée pour chaque nombre réel JSON à décoder sous forme d’une chaîne de caractères. Par défaut, elle est équivalente à float(num_str). Cela peut servir à utiliser un autre type de données ou un autre analyseur pour les nombres réels JSON (p. ex. decimal.Decimal).

parse_int, si spécifiée, sera appelée pour chaque nombre entier JSON à décoder sous forme d’une chaîne de caractères. Par défaut, elle est équivalente à int(num_str). Cela peut servir à utiliser un autre type de données ou un autre analyseur pour les nombres entiers JSON (p. ex. float).

parse_constant, si spécifiée, sera appelée avec l’une des chaînes de caractères suivantes : '-Infinity', 'Infinity' ou 'NaN'. Cela peut servir à lever une exception si des nombres JSON invalides sont rencontrés.

Si strict est faux (True par défaut), alors les caractères de contrôle seront autorisés à l’intérieur des chaînes. Les caractères de contrôle dans ce contexte sont ceux dont les codes sont dans l’intervalle 0–31, incluant '\t' (tabulation), '\n', '\r' et '\0'.

Si les données à déserialiser ne sont pas un document JSON valide, une JSONDecodeError sera levée.

Modifié dans la version 3.6: Tous les paramètres sont maintenant des keyword-only.

decode(s)

Renvoie la représentation Python de s (une instance str contenant un document JSON).

Une JSONDecodeError sera levée si le document JSON donné n’est pas valide.

raw_decode(s)

Décode en document JSON depuis s (une instance str débutant par un document JSON) et renvoie un tuple de 2 éléments contenant la représentation Python de l’objet et l’index dans s où le document se terminait.

Elle peut être utilisée pour décoder un document JSON depuis une chaîne qui peut contenir des données supplémentaires à la fin.

class json.JSONEncoder(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, sort_keys=False, indent=None, separators=None, default=None)

Encodeur JSON extensible pour les structures de données Python.

Supporte par défaut les objets et types suivants :

Python

JSON

dict

objet

list, tuple

array

str

string

int, float, et Enums dérivées d”int ou de float

number

True

true

False

false

None

null

Modifié dans la version 3.4: Ajout du support des classes Enum dérivées d”int ou de float.

Pour l’étendre afin de reconnaître d’autres types d’objets, il suffit d’en créer une sous-classe et d’implémenter une nouvelle méthode default() qui renverrait si possible un objet sérialisable pour o, ou ferait appel à l’implémentation de la classe mère (qui lèverait une TypeError).

Si skipkeys est faux (par défaut), une TypeError sera levée lors de l’encodage de clés autres que des str, des int, des float ou None. Si skipkeys est vrai, ces éléments sont simplement ignorés.

Si ensure_ascii est vrai (par défaut), il est garanti que les caractères non ASCII soient tous échappés sur la sortie. Si ensure_ascii est faux, ces caractères seront écrits comme tels.

Si check_circular est vrai (par défaut), une vérification aura lieu sur les listes, dictionnaires et objets personnalisés, afin de détecter les références circulaires et éviter les récursions infinies (qui causeraient une OverflowError). Autrement, la vérification n’a pas lieu.

Si allow_nan est vrai (par défaut), alors NaN, Infinity et -Infinity seront encodés comme tels. Ce comportement ne respecte pas la spécification JSON, mais est cohérent avec le majorité des encodeurs/décodeurs JavaScript. Autrement, une ValueError sera levée pour de telles valeurs.

Si sort_keys est vrai (False par défaut), alors les dictionnaires seront triés par clés en sortie ; cela est utile lors de tests de régression pour pouvoir comparer les sérialisations JSON au jour le jour.

Si indent est un nombre entier positif ou une chaîne de caractères, les éléments de tableaux et les membres d’objets JSON seront affichés élégamment avec ce niveau d’indentation. Un niveau d’indentation de 0, négatif, ou "" n’insérera que des retours à la ligne. None (la valeur par défaut) choisit la représentation la plus compacte. Utiliser un entier positif comme indentation indente d’autant d’espaces par niveau. Si indent est une chaîne (telle que "\t"), cette chaîne est utilisée pour indenter à chaque niveau.

Modifié dans la version 3.2: Autorise les chaînes en plus des nombres entiers pour indent.

Si spécifié, separators doit être un tuple (item_separator, key_separator). Sa valeur par défaut est (', ', ': ') si indent est None, et (',', ': ') autrement. Pour obtenir la représentation JSON la plus compacte possible, vous devriez spécifier (',', ':') pour éliminer les espacements.

Modifié dans la version 3.4: Utilise (',', ': ') par défaut si indent n’est pas None.

Si spécifié, default doit être une fonction qui sera appelée pour les objets qui ne peuvent être sérialisés autrement. Elle doit renvoyer une représentation de l’objet sérialisable en JSON ou lever une TypeError. Si non spécifié, une TypeError sera levée pour les types non sérialisables.

Modifié dans la version 3.6: Tous les paramètres sont maintenant des keyword-only.

default(o)

Implémentez cette méthode dans une sous-classe afin qu’elle renvoie un objet sérialisable pour o, ou appelle l’implémentation de base (qui lèvera une TypeError).

Par exemple, pour supporter des itérateurs arbitraires, vous pourriez implémenter default comme cela :

def default(self, o):
   try:
       iterable = iter(o)
   except TypeError:
       pass
   else:
       return list(iterable)
   # Let the base class default method raise the TypeError
   return json.JSONEncoder.default(self, o)

encode(o)

Renvoie une chaîne JSON représentant la structure de données Python o. Par exemple :

>>> json.JSONEncoder().encode({"foo": ["bar", "baz"]})
'{"foo": ["bar", "baz"]}'

iterencode(o)

Encode l’objet o donné, et produit chaque chaîne représentant l’objet selon disponibilité. Par exemple :

for chunk in json.JSONEncoder().iterencode(bigobject):
    mysocket.write(chunk)

19.2.3. Exceptions

exception json.JSONDecodeError(msg, doc, pos)

Sous-classe de ValueError avec les attributs additionnels suivants :

msg

Le message d’erreur non formaté.

doc

Le document JSON actuellement traité.

pos

L’index de doc à partir duquel l’analyse a échoué.

lineno

La ligne correspondant à pos.

colno

La colonne correspondant à pos.

Nouveau dans la version 3.5.

19.2.4. Conformité au standard et Interopérabilité

Le format JSON est spécifié par la RFC 7159 [https://tools.ietf.org/html/rfc7159.html] et le standard ECMA-404 [http://www.ecma-international.org/publications/standards/Ecma-404.htm]. Cette section détaille la conformité à la RFC au niveau du module. Pour faire simple, les sous-classes de JSONEncoder et JSONDecoder, et les paramètres autres que ceux explicitement mentionnés ne sont pas considérés.

Ce module ne se conforme pas strictement à la RFC, implémentant quelques extensions qui sont valides en JavaScript mais pas en JSON. En particulier :

Les nombres infinis et NaN sont acceptés et retranscrits ;

Les noms répétés au sein d’un objet sont acceptés, seule la valeur du dernier couple nom/valeur sera utilisée.

Comme la RFC permet aux analyseurs conformes d’accepter des textes en entrée non conformes, le déserialiseur de ce module avec ses paramètres par défaut est techniquement conforme à la RFC.

19.2.4.1. Encodage des caractères

La RFC requiert que le JSON soit représenté en utilisant l’encodage UTF-8, UTF-16 ou UTF-32, avec UTF-8 recommandé par défaut pour une interopérabilité maximale.

Comme cela est permis par la RFC, bien que non requis, le sérialiseur du module active ensure_ascii=True par défaut, échappant ainsi la sortie de façon à ce que les chaînes résultants ne contiennent que des caractères ASCII.

Outre le paramètre ensure_ascii, les conversions entre objets Python et chaînes Unicode de ce module sont strictement définies, et ne rencontrent donc pas directement le problème de l’encodage des caractères.

La RFC interdit d’ajouter un byte marqueur d’ordre (BOM) au début du texte JSON, et le sérialiseur de ce module n’ajoute pas de tel BOM. La RFC permet, mais ne requiert pas, que les déserialiseurs JSON ignorent ces BOM. Le déserialiseur de ce module lève une ValueError quand un BOM est présent au début du fichier.

La RFC n’interdit pas explicitement les chaînes JSON contenant des séquences de bytes ne correspondant à aucun caractère Unicode valide (p. ex. les surrogates UTF-16 sans correspondance), mais précise que cela peut causer des problèmes d’interopérabilité. Par défaut, ce module accepte et retranscrit (quand présents dans la str originale) les code points de telles séquences.

19.2.4.2. Valeurs numériques infinies et NaN

La RFC ne permet pas la représentation des nombres infinis ou des NaN. Néanmoins, par défaut, ce module accepte et retranscrit Infinity, -Infinity et NaN comme s’ils étaient des valeurs numériques littérales JSON valides :

>>> # Neither of these calls raises an exception, but the results are not valid JSON
>>> json.dumps(float('-inf'))
'-Infinity'
>>> json.dumps(float('nan'))
'NaN'
>>> # Same when deserializing
>>> json.loads('-Infinity')
-inf
>>> json.loads('NaN')
nan

Dans le sérialiseur, le paramètre allow_nan peut être utilisé pour altérer ce comportement. Dans le déserialiseur, le paramètre parse_constant peut être utilisé pour altérer ce comportement.

19.2.4.3. Noms répétés au sein d’un objet

La RFC spécifie que les noms au sein d’un objet JSON doivent être uniques, mais ne décrit pas comment les noms répétés doivent être gérés. Par défaut, ce module ne lève pas d’exception ; à la place, il ignore tous les couples nom/valeur sauf le dernier pour un nom donné :

>>> weird_json = '{"x": 1, "x": 2, "x": 3}'
>>> json.loads(weird_json)
{'x': 3}

Le paramètre object_pairs_hook peut être utilisé pour altérer ce comportement.

19.2.4.4. Valeurs de plus haut niveau autres qu’objets ou tableaux

L’ancienne version de JSON spécifiée par l’obsolète RFC 4627 [https://tools.ietf.org/html/rfc4627.html] demandait à ce que la valeur de plus haut niveau du texte JSON soit un objet ou un tableau JSON (dict ou list Python), et ne soit pas null, un nombre, ou une chaîne de caractères. La RFC 7159 [https://tools.ietf.org/html/rfc7159.html] a supprimé cette restriction, jamais implémentée par ce module, que ce soit dans le sérialiseur ou le déserialiseur.

Cependant, pour une interopérabilité maximale, vous pourriez volontairement souhaiter adhérer à cette restriction par vous-même.

19.2.4.5. Limitations de l’implémentation

Certaines implémentations de déserialiseurs JSON peuvent avoir des limites sur :

la taille des textes JSON acceptés ;

le niveau maximum d’objets et tableaux JSON imbriqués ;

l’intervalle et la précision des nombres JSON ;

le contenu et la longueur maximale des chaînes JSON.

Ce module n’impose pas de telles limites si ce n’est celles inhérentes aux types de données Python ou à l’interpréteur.

Lors d’une sérialisation JSON, faites attention à ces limitations dans les applications qui utiliseraient votre JSON. En particulier, il est commun pour les nombres JSON d’être déserialisés vers des nombres IEEE 754 à précision double, et donc sujets à l’intervalle et aux limitations sur la précision de cette représentation. Cela est d’autant plus important lors de la sérialisation de valeurs int Python de forte magnitude, ou d’instances de types numériques « exotiques » comme decimal.Decimal.

19.2.5. Interface en ligne de commande

Code source : Lib/json/tool.py [https://github.com/python/cpython/tree/3.6/Lib/json/tool.py]

Le module json.tool fournit une simple interface en ligne de commande pour valider et réécrire élégamment des objets JSON.

Si les arguments optionnels infile et outfile ne sont pas spécifiés, sys.stdin et sys.stdout seront utilisés respectivement :

$ echo '{"json": "obj"}' | python -m json.tool
{
    "json": "obj"
}
$ echo '{1.2:3.4}' | python -m json.tool
Expecting property name enclosed in double quotes: line 1 column 2 (char 1)

Modifié dans la version 3.5: La sortie conserve maintenant l’ordre des données de l’entrée. Utilisez l’option --sort-keys pour sortir des dictionnaires triés alphabétiquement par clés.

19.2.5.1. Options de la ligne de commande

infile

Le fichier JSON à valider ou réécrire élégamment :

$ python -m json.tool mp_films.json
[
    {
        "title": "And Now for Something Completely Different",
        "year": 1971
    },
    {
        "title": "Monty Python and the Holy Grail",
        "year": 1975
    }
]

Si infile n’est pas spécifié, lit le document depuis sys.stdin.

outfile

Écrit la sortie générée par infile vers le fichier outfile donné. Autrement, écrit sur sys.stdout.

--sort-keys

Trie alphabétiquement les dictionnaires par clés.

Nouveau dans la version 3.5.

-h, --help

Affiche le message d’aide.

Notes

1

Comme noté dans l’errata de la RFC 7159 [https://www.rfc-editor.org/errata_search.php?rfc=7159], JSON autorise les caractères littéraux U+2028 (LINE SEPARATOR) et U+2029 (PARAGRAPH SEPARATOR) dans les chaînes de caractères, alors que Javascript (selon le standard ECMAScript édition 5.1) ne le permet pas.

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19.3. mailcap — Manipulation de fichiers Mailcap

Code source : Lib/mailcap.py [https://github.com/python/cpython/tree/3.6/Lib/mailcap.py]

Les fichiers mailcap sont utilisés pour configurer la façon dont les applications compatibles avec MIME, comme les clients mails ou les navigateurs, réagissent aux différents fichiers de types MIME. (Le nom mailcap est une contraction de l’expression « mail capability ».) Par exemple, un fichier mailcap peut contenir une ligne de type video/mpeg; xmpeg %s. Ensuite, si l’utilisateur récupère un message mail ou un document web avec un type MIME video/mpeg, %s est remplacé par un nom de fichier (généralement celui d’un fichier temporaire) et le programme xmpeg peut automatiquement débuter la lecture de ce dernier.

Le format mailcap est documenté dans la RFC 1524 [https://tools.ietf.org/html/rfc1524.html] « A User Agent Configuration Mechanism For Multimedia Mail Format Information », mais n’est pas un standard Internet. Cependant, la plupart des systèmes Unix savent gérer les fichiers mailcap.

mailcap.findmatch(caps, MIMEtype, key='view', filename='/dev/null', plist=[])

Renvoie un tuple à deux éléments ; le premier élément est une chaîne de caractères (string) contenant la ligne de commande à exécuter (qui peut être passée à os.system()), et le second élément est l’entrée mailcap pour un type de MIME donné. Si le type MIME n’est pas identifié, (None, None) est renvoyé.

key est le nom de champ souhaité, qui représente le type d’action à exécuter ; la valeur par défaut est 'view', puisque dans la majorité des cas le besoin consiste juste à lire le corps (body) de la donnée de type MIME. Les autres valeurs possibles peuvent être 'compose' et 'edit', si le besoin consiste à créer un nouveau corps de données (body) ou modifier celui existant. Voir la RFC 1524 [https://tools.ietf.org/html/rfc1524.html] pour une liste complète des champs.

filename est le nom de fichier à remplacer pour %s en ligne de commande ; la valeur par défaut est ’/dev/null’ qui n’est certainement pas celle que vous attendez. Donc la plupart du temps, le nom de fichier doit être indiqué.

plist peut être une liste contenant des noms de paramètres ; la valeur par défaut est une simple liste vide. Chaque entrée dans la liste doit être une chaîne de caractères contenant le nom du paramètre, un signe égal (’=‘), ainsi que la valeur du paramètre. Les entrées mailcap peuvent contenir des noms de paramètres tels que %{foo}, remplacé par la valeur du paramètre nommé foo. Par exemple, si la ligne de commande showpartial %{id} %{number} %{total} est un fichier mailcap, et plist configuré à [‘id=1’, ‘number=2’, ‘total=3’], la ligne de commande qui en résulte est ’showpartial 1 2 3’.

Dans un fichier mailcap, le champ « test » peut être renseigné de façon optionnelle afin de tester certaines conditions externes (comme l’architecture machine, ou le gestionnaire de fenêtre utilisé) afin de déterminer si la ligne mailcap est pertinente ou non. findmatch() vérifie automatiquement ces conditions et ignore l’entrée si la vérification échoue.

mailcap.getcaps()

Renvoie un dictionnaire qui associe les types MIME à une liste d’entrées de fichier mailcap. Ce dictionnaire doit être transmis à la fonction findmatch(). Une entrée est enregistrée en tant qu’une liste de dictionnaires, mais il n’est pas nécessaire de connaitre les détails de cette représentation.

L’information provient de tous les fichiers mailcap trouvés dans le système. Les configurations réalisées dans le fichier mailcap du répertoire utilisateur $HOME/.mailcap outrepasse les configurations systèmes des fichiers mailcap /etc/mailcap, /usr/etc/mailcap, et /usr/local/etc/mailcap.

Un exemple d’utilisation :

>>> import mailcap
>>> d = mailcap.getcaps()
>>> mailcap.findmatch(d, 'video/mpeg', filename='tmp1223')
('xmpeg tmp1223', {'view': 'xmpeg %s'})

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19.4. mailbox — Manipuler les boîtes de courriels dans différents formats

Code source : Lib/mailbox.py [https://github.com/python/cpython/tree/3.6/Lib/mailbox.py]

Ce module définit deux classes, Mailbox et Message, pour accéder et manipuler les boîtes de courriel sur le disque et les messages qu’elles contiennent. Mailbox offre une interface ressemblant aux dictionnaires avec des clés et des messages. La classe Message étend le module email.message de la classe Message avec un état et un comportement spécifiques à son format. Les formats de boîtes de courriel gérés sont Maildir, mbox, MH, Babyl et MMDF.

Voir aussi

Module email

Représente et manipule des messages.

19.4.1. Objets Mailbox

class mailbox.Mailbox

Une boîte mail, qui peut être inspectée et modifiée.

La classe Mailbox définit une interface et n’est pas destinée à être instanciée. Les sous-classes de format spécifique doivent plutôt hériter de Mailbox et votre code doit instancier une sous-classe particulière.

L’interface Mailbox est un compatible avec celle des dictionnaires, avec de courtes clés correspondant aux messages. Les clés sont générées par l’instance Mailbox avec laquelle elles sont utilisées et n’ont de sens que pour cette instance Mailbox. Une clé continue d’identifier un message même si le message correspondant est modifié ou remplacé par un autre message.

Les messages peuvent être ajoutés à une instance Mailbox en utilisant la méthode add() (comme pour les ensembles), et supprimés en utilisant soit l’instruction del soit les méthodes remove() et discard() (comme pour les ensembles).

La sémantique de l’interface Mailbox diffère de la sémantique des dictionnaires sur plusieurs aspects. À chaque fois qu’un message est demandé, une nouvelle représentation (généralement une instance Message) est générée en se basant sur l’état actuel de la boîte mail. De la même manière, lorsqu’un message est ajouté à l’instance Mailbox, le contenu de la représentation du message donné est copié. En aucun cas une référence vers la représentation du message n’est gardée par l’instance Mailbox.

L’itérateur par défaut de Mailbox itère sur les représentations des messages et pas sur les clés (comme le fait par défaut l’itérateur des dictionnaires). De plus, les modifications sur une boîte mail durant l’itération sont sûres et clairement définies. Les messages ajoutés à la boîte mail après la création d’un itérateur ne sont pas vus par l’itérateur. Les messages supprimés de la boîte mail avant que l’itérateur les traite seront ignorés silencieusement. Toutefois, utiliser une clé depuis un itérateur peut aboutir à une exception KeyError si le message correspondant est supprimé par la suite.

Avertissement

Soyez très prudent lorsque vous éditez des boîtes mail qui peuvent être modifiées par d’autres processus. Le format de boîte mail le plus sûr à utiliser pour ces tâches est Maildir, essayez d’éviter les formats à fichier unique tels que mbox afin d’empêcher les écritures concurrentes. Si vous modifiez une boîte mail, vous devez la verrouiller en appelant les méthodes lock() et unlock() avant de lire les messages dans le fichier ou d’y appliquer des changements en y ajoutant ou supprimant des messages. Ne pas verrouiller la boîte mail vous fait prendre le risque de perdre des messages ou de corrompre la boîte mail entière.

Les instances Mailbox contiennent les méthodes suivantes :

add(message)

Ajoute message à la boîte mail et renvoie la clé qui lui a été assigné.

Le paramètre message peut être une instance Message, une instance email.message.Message, une chaîne de caractères, une séquence d’octets ou un objet fichier-compatible (qui doit être ouvert en mode binaire). Si message est une instance de la sous-classe Message au format correspondant (par exemple s’il s’agit d’une instance mboxMessage et d’une instance mbox), les informations spécifiques à son format sont utilisées. Sinon, des valeurs par défaut raisonnables pour son format sont utilisées.

Modifié dans la version 3.2: Ajout de la gestion des messages binaires.

remove(key)

__delitem__(key)

discard(key)

Supprime le message correspondant à key dans la boîte mail.

Si ce message n’existe pas, une exception KeyError est levée si la méthode a été appelée en tant que remove() ou __delitem__() mais aucune exception n’est levée si la méthode a été appelée en tant que discard(). Vous préférerez sûrement le comportement de discard() si le format de boîte mail sous-jacent accepte la modification concurrente par les autres processus.

__setitem__(key, message)

Remplace le message correspondant à key par message. Lève une exception KeyError s’il n’y a pas déjà de message correspondant à key.

Comme pour add(), le paramètre message peut être une instance Message, une instance email.message.Message, une chaîne de caractères, une chaîne d’octets ou un objet fichier-compatible (qui doit être ouvert en mode binaire). Si message est une instance de la sous-classe Message au format correspondant (par exemple s’il s’agit d’une instance mboxMessage et d’une instance mbox), les informations spécifiques à son format sont utilisées. Sinon, les informations spécifiques au format du message qui correspond à key ne sont modifiées.

iterkeys()

keys()

Renvoie un itérateur sur toutes les clés s’il est appelé en tant que iterkeys() ou renvoie une liste de clés s’il est appelé en tant que keys().

itervalues()

__iter__()

values()

Renvoie un itérateur sur les représentations de tous les messages s’il est appelé en tant que itervalues() ou __iter__() et renvoie une liste de ces représentations s’il est appelé en tant que values(). Les messages sont représentés en tant qu’instances de la sous-classe Message au format correspondant à moins qu’une fabrique de messages personnalisée soit spécifiée lorsque l’instance Mailbox a été initialisée.

Note

The behavior of __iter__() is unlike that of dictionaries, which iterate over keys.

iteritems()

items()

Return an iterator over (key, message) pairs, where key is a key and message is a message representation, if called as iteritems() or return a list of such pairs if called as items(). The messages are represented as instances of the appropriate format-specific Message subclass unless a custom message factory was specified when the Mailbox instance was initialized.

get(key, default=None)

__getitem__(key)

Return a representation of the message corresponding to key. If no such message exists, default is returned if the method was called as get() and a KeyError exception is raised if the method was called as __getitem__(). The message is represented as an instance of the appropriate format-specific Message subclass unless a custom message factory was specified when the Mailbox instance was initialized.

get_message(key)

Return a representation of the message corresponding to key as an instance of the appropriate format-specific Message subclass, or raise a KeyError exception if no such message exists.

get_bytes(key)

Return a byte representation of the message corresponding to key, or raise a KeyError exception if no such message exists.

Nouveau dans la version 3.2.

get_string(key)

Return a string representation of the message corresponding to key, or raise a KeyError exception if no such message exists. The message is processed through email.message.Message to convert it to a 7bit clean representation.

get_file(key)

Return a file-like representation of the message corresponding to key, or raise a KeyError exception if no such message exists. The file-like object behaves as if open in binary mode. This file should be closed once it is no longer needed.

Modifié dans la version 3.2: The file object really is a binary file; previously it was incorrectly returned in text mode. Also, the file-like object now supports the context management protocol: you can use a with statement to automatically close it.

Note

Unlike other representations of messages, file-like representations are not necessarily independent of the Mailbox instance that created them or of the underlying mailbox. More specific documentation is provided by each subclass.

__contains__(key)

Return True if key corresponds to a message, False otherwise.

__len__()

Return a count of messages in the mailbox.

clear()

Delete all messages from the mailbox.

pop(key, default=None)

Return a representation of the message corresponding to key and delete the message. If no such message exists, return default. The message is represented as an instance of the appropriate format-specific Message subclass unless a custom message factory was specified when the Mailbox instance was initialized.

popitem()

Return an arbitrary (key, message) pair, where key is a key and message is a message representation, and delete the corresponding message. If the mailbox is empty, raise a KeyError exception. The message is represented as an instance of the appropriate format-specific Message subclass unless a custom message factory was specified when the Mailbox instance was initialized.

update(arg)

Parameter arg should be a key-to-message mapping or an iterable of (key, message) pairs. Updates the mailbox so that, for each given key and message, the message corresponding to key is set to message as if by using __setitem__(). As with __setitem__(), each key must already correspond to a message in the mailbox or else a KeyError exception will be raised, so in general it is incorrect for arg to be a Mailbox instance.

Note

Unlike with dictionaries, keyword arguments are not supported.

flush()

Write any pending changes to the filesystem. For some Mailbox subclasses, changes are always written immediately and flush() does nothing, but you should still make a habit of calling this method.

lock()

Acquire an exclusive advisory lock on the mailbox so that other processes know not to modify it. An ExternalClashError is raised if the lock is not available. The particular locking mechanisms used depend upon the mailbox format. You should always lock the mailbox before making any modifications to its contents.

unlock()

Release the lock on the mailbox, if any.

close()

Flush the mailbox, unlock it if necessary, and close any open files. For some Mailbox subclasses, this method does nothing.

19.4.1.1. Maildir

class mailbox.Maildir(dirname, factory=None, create=True)

A subclass of Mailbox for mailboxes in Maildir format. Parameter factory is a callable object that accepts a file-like message representation (which behaves as if opened in binary mode) and returns a custom representation. If factory is None, MaildirMessage is used as the default message representation. If create is True, the mailbox is created if it does not exist.

It is for historical reasons that dirname is named as such rather than path.

Maildir is a directory-based mailbox format invented for the qmail mail transfer agent and now widely supported by other programs. Messages in a Maildir mailbox are stored in separate files within a common directory structure. This design allows Maildir mailboxes to be accessed and modified by multiple unrelated programs without data corruption, so file locking is unnecessary.

Maildir mailboxes contain three subdirectories, namely: tmp, new, and cur. Messages are created momentarily in the tmp subdirectory and then moved to the new subdirectory to finalize delivery. A mail user agent may subsequently move the message to the cur subdirectory and store information about the state of the message in a special « info » section appended to its file name.

Folders of the style introduced by the Courier mail transfer agent are also supported. Any subdirectory of the main mailbox is considered a folder if '.' is the first character in its name. Folder names are represented by Maildir without the leading '.'. Each folder is itself a Maildir mailbox but should not contain other folders. Instead, a logical nesting is indicated using '.' to delimit levels, e.g., « Archived.2005.07 ».

Note

The Maildir specification requires the use of a colon (':') in certain message file names. However, some operating systems do not permit this character in file names, If you wish to use a Maildir-like format on such an operating system, you should specify another character to use instead. The exclamation point ('!') is a popular choice. For example:

import mailbox
mailbox.Maildir.colon = '!'

The colon attribute may also be set on a per-instance basis.

Maildir instances have all of the methods of Mailbox in addition to the following:

list_folders()

Return a list of the names of all folders.

get_folder(folder)

Return a Maildir instance representing the folder whose name is folder. A NoSuchMailboxError exception is raised if the folder does not exist.

add_folder(folder)

Create a folder whose name is folder and return a Maildir instance representing it.

remove_folder(folder)

Delete the folder whose name is folder. If the folder contains any messages, a NotEmptyError exception will be raised and the folder will not be deleted.

clean()

Delete temporary files from the mailbox that have not been accessed in the last 36 hours. The Maildir specification says that mail-reading programs should do this occasionally.

Some Mailbox methods implemented by Maildir deserve special remarks:

add(message)

__setitem__(key, message)

update(arg)

Avertissement

These methods generate unique file names based upon the current process ID. When using multiple threads, undetected name clashes may occur and cause corruption of the mailbox unless threads are coordinated to avoid using these methods to manipulate the same mailbox simultaneously.

flush()

All changes to Maildir mailboxes are immediately applied, so this method does nothing.

lock()

unlock()

Maildir mailboxes do not support (or require) locking, so these methods do nothing.

close()

Maildir instances do not keep any open files and the underlying mailboxes do not support locking, so this method does nothing.

get_file(key)

Depending upon the host platform, it may not be possible to modify or remove the underlying message while the returned file remains open.

Voir aussi

maildir man page from qmail [http://www.qmail.org/man/man5/maildir.html]

The original specification of the format.

Using maildir format [https://cr.yp.to/proto/maildir.html]

Notes on Maildir by its inventor. Includes an updated name-creation scheme and details on « info » semantics.

maildir man page from Courier [http://www.courier-mta.org/maildir.html]

Another specification of the format. Describes a common extension for supporting folders.

19.4.1.2. mbox

class mailbox.mbox(path, factory=None, create=True)

A subclass of Mailbox for mailboxes in mbox format. Parameter factory is a callable object that accepts a file-like message representation (which behaves as if opened in binary mode) and returns a custom representation. If factory is None, mboxMessage is used as the default message representation. If create is True, the mailbox is created if it does not exist.

The mbox format is the classic format for storing mail on Unix systems. All messages in an mbox mailbox are stored in a single file with the beginning of each message indicated by a line whose first five characters are « From « .

Several variations of the mbox format exist to address perceived shortcomings in the original. In the interest of compatibility, mbox implements the original format, which is sometimes referred to as mboxo. This means that the Content-Length header, if present, is ignored and that any occurrences of « From  » at the beginning of a line in a message body are transformed to « >From  » when storing the message, although occurrences of « >From  » are not transformed to « From  » when reading the message.

Some Mailbox methods implemented by mbox deserve special remarks:

get_file(key)

Using the file after calling flush() or close() on the mbox instance may yield unpredictable results or raise an exception.

lock()

unlock()

Three locking mechanisms are used—dot locking and, if available, the flock() and lockf() system calls.

Voir aussi

mbox man page from qmail [http://www.qmail.org/man/man5/mbox.html]

A specification of the format and its variations.

mbox man page from tin [http://www.tin.org/bin/man.cgi?section=5&topic=mbox]

Another specification of the format, with details on locking.

Configuring Netscape Mail on Unix: Why The Content-Length Format is Bad [https://www.jwz.org/doc/content-length.html]

An argument for using the original mbox format rather than a variation.

« mbox » is a family of several mutually incompatible mailbox formats [https://www.loc.gov/preservation/digital/formats/fdd/fdd000383.shtml]

A history of mbox variations.

19.4.1.3. MH

class mailbox.MH(path, factory=None, create=True)

A subclass of Mailbox for mailboxes in MH format. Parameter factory is a callable object that accepts a file-like message representation (which behaves as if opened in binary mode) and returns a custom representation. If factory is None, MHMessage is used as the default message representation. If create is True, the mailbox is created if it does not exist.

MH is a directory-based mailbox format invented for the MH Message Handling System, a mail user agent. Each message in an MH mailbox resides in its own file. An MH mailbox may contain other MH mailboxes (called folders) in addition to messages. Folders may be nested indefinitely. MH mailboxes also support sequences, which are named lists used to logically group messages without moving them to sub-folders. Sequences are defined in a file called .mh_sequences in each folder.

The MH class manipulates MH mailboxes, but it does not attempt to emulate all of mh’s behaviors. In particular, it does not modify and is not affected by the context or .mh_profile files that are used by mh to store its state and configuration.

MH instances have all of the methods of Mailbox in addition to the following:

list_folders()

Return a list of the names of all folders.

get_folder(folder)

Return an MH instance representing the folder whose name is folder. A NoSuchMailboxError exception is raised if the folder does not exist.

add_folder(folder)

Create a folder whose name is folder and return an MH instance representing it.

remove_folder(folder)

Delete the folder whose name is folder. If the folder contains any messages, a NotEmptyError exception will be raised and the folder will not be deleted.

get_sequences()

Return a dictionary of sequence names mapped to key lists. If there are no sequences, the empty dictionary is returned.

set_sequences(sequences)

Re-define the sequences that exist in the mailbox based upon sequences, a dictionary of names mapped to key lists, like returned by get_sequences().

pack()

Rename messages in the mailbox as necessary to eliminate gaps in numbering. Entries in the sequences list are updated correspondingly.

Note

Already-issued keys are invalidated by this operation and should not be subsequently used.

Some Mailbox methods implemented by MH deserve special remarks:

remove(key)

__delitem__(key)

discard(key)

These methods immediately delete the message. The MH convention of marking a message for deletion by prepending a comma to its name is not used.

lock()

unlock()

Three locking mechanisms are used—dot locking and, if available, the flock() and lockf() system calls. For MH mailboxes, locking the mailbox means locking the .mh_sequences file and, only for the duration of any operations that affect them, locking individual message files.

get_file(key)

Depending upon the host platform, it may not be possible to remove the underlying message while the returned file remains open.

flush()

All changes to MH mailboxes are immediately applied, so this method does nothing.

close()

MH instances do not keep any open files, so this method is equivalent to unlock().

Voir aussi

nmh - Message Handling System [http://www.nongnu.org/nmh/]

Home page of nmh, an updated version of the original mh.

MH & nmh: Email for Users & Programmers [http://rand-mh.sourceforge.net/book/]

A GPL-licensed book on mh and nmh, with some information on the mailbox format.

19.4.1.4. Babyl

class mailbox.Babyl(path, factory=None, create=True)

A subclass of Mailbox for mailboxes in Babyl format. Parameter factory is a callable object that accepts a file-like message representation (which behaves as if opened in binary mode) and returns a custom representation. If factory is None, BabylMessage is used as the default message representation. If create is True, the mailbox is created if it does not exist.

Babyl is a single-file mailbox format used by the Rmail mail user agent included with Emacs. The beginning of a message is indicated by a line containing the two characters Control-Underscore ('\037') and Control-L ('\014'). The end of a message is indicated by the start of the next message or, in the case of the last message, a line containing a Control-Underscore ('\037') character.

Messages in a Babyl mailbox have two sets of headers, original headers and so-called visible headers. Visible headers are typically a subset of the original headers that have been reformatted or abridged to be more attractive. Each message in a Babyl mailbox also has an accompanying list of labels, or short strings that record extra information about the message, and a list of all user-defined labels found in the mailbox is kept in the Babyl options section.

Babyl instances have all of the methods of Mailbox in addition to the following:

get_labels()

Return a list of the names of all user-defined labels used in the mailbox.

Note

The actual messages are inspected to determine which labels exist in the mailbox rather than consulting the list of labels in the Babyl options section, but the Babyl section is updated whenever the mailbox is modified.

Some Mailbox methods implemented by Babyl deserve special remarks:

get_file(key)

In Babyl mailboxes, the headers of a message are not stored contiguously with the body of the message. To generate a file-like representation, the headers and body are copied together into an io.BytesIO instance, which has an API identical to that of a file. As a result, the file-like object is truly independent of the underlying mailbox but does not save memory compared to a string representation.

lock()

unlock()

Three locking mechanisms are used—dot locking and, if available, the flock() and lockf() system calls.

Voir aussi

Format of Version 5 Babyl Files [https://quimby.gnus.org/notes/BABYL]

A specification of the Babyl format.

Reading Mail with Rmail [https://www.gnu.org/software/emacs/manual/html_node/emacs/Rmail.html]

The Rmail manual, with some information on Babyl semantics.

19.4.1.5. MMDF

class mailbox.MMDF(path, factory=None, create=True)

A subclass of Mailbox for mailboxes in MMDF format. Parameter factory is a callable object that accepts a file-like message representation (which behaves as if opened in binary mode) and returns a custom representation. If factory is None, MMDFMessage is used as the default message representation. If create is True, the mailbox is created if it does not exist.

MMDF is a single-file mailbox format invented for the Multichannel Memorandum Distribution Facility, a mail transfer agent. Each message is in the same form as an mbox message but is bracketed before and after by lines containing four Control-A ('\001') characters. As with the mbox format, the beginning of each message is indicated by a line whose first five characters are « From « , but additional occurrences of « From  » are not transformed to « >From  » when storing messages because the extra message separator lines prevent mistaking such occurrences for the starts of subsequent messages.

Some Mailbox methods implemented by MMDF deserve special remarks:

get_file(key)

Using the file after calling flush() or close() on the MMDF instance may yield unpredictable results or raise an exception.

lock()

unlock()

Three locking mechanisms are used—dot locking and, if available, the flock() and lockf() system calls.

Voir aussi

mmdf man page from tin [http://www.tin.org/bin/man.cgi?section=5&topic=mmdf]

A specification of MMDF format from the documentation of tin, a newsreader.

MMDF [https://en.wikipedia.org/wiki/MMDF]

A Wikipedia article describing the Multichannel Memorandum Distribution Facility.

19.4.2. Message objects

class mailbox.Message(message=None)

A subclass of the email.message module’s Message. Subclasses of mailbox.Message add mailbox-format-specific state and behavior.

If message is omitted, the new instance is created in a default, empty state. If message is an email.message.Message instance, its contents are copied; furthermore, any format-specific information is converted insofar as possible if message is a Message instance. If message is a string, a byte string, or a file, it should contain an RFC 2822 [https://tools.ietf.org/html/rfc2822.html]-compliant message, which is read and parsed. Files should be open in binary mode, but text mode files are accepted for backward compatibility.

The format-specific state and behaviors offered by subclasses vary, but in general it is only the properties that are not specific to a particular mailbox that are supported (although presumably the properties are specific to a particular mailbox format). For example, file offsets for single-file mailbox formats and file names for directory-based mailbox formats are not retained, because they are only applicable to the original mailbox. But state such as whether a message has been read by the user or marked as important is retained, because it applies to the message itself.

There is no requirement that Message instances be used to represent messages retrieved using Mailbox instances. In some situations, the time and memory required to generate Message representations might not be acceptable. For such situations, Mailbox instances also offer string and file-like representations, and a custom message factory may be specified when a Mailbox instance is initialized.

19.4.2.1. MaildirMessage

class mailbox.MaildirMessage(message=None)

A message with Maildir-specific behaviors. Parameter message has the same meaning as with the Message constructor.

Typically, a mail user agent application moves all of the messages in the new subdirectory to the cur subdirectory after the first time the user opens and closes the mailbox, recording that the messages are old whether or not they’ve actually been read. Each message in cur has an « info » section added to its file name to store information about its state. (Some mail readers may also add an « info » section to messages in new.) The « info » section may take one of two forms: it may contain « 2, » followed by a list of standardized flags (e.g., « 2,FR ») or it may contain « 1, » followed by so-called experimental information. Standard flags for Maildir messages are as follows:

Option

Signification

Explication

D

Draft

Under composition

F

Flagged

Marked as important

P

Passed

Forwarded, resent, or bounced

R

Replied

Replied to

S

Seen

Read

T

Trashed

Marked for subsequent deletion

MaildirMessage instances offer the following methods:

get_subdir()

Return either « new » (if the message should be stored in the new subdirectory) or « cur » (if the message should be stored in the cur subdirectory).

Note

A message is typically moved from new to cur after its mailbox has been accessed, whether or not the message is has been read. A message msg has been read if "S" in msg.get_flags() is True.

set_subdir(subdir)

Set the subdirectory the message should be stored in. Parameter subdir must be either « new » or « cur ».

get_flags()

Return a string specifying the flags that are currently set. If the message complies with the standard Maildir format, the result is the concatenation in alphabetical order of zero or one occurrence of each of 'D', 'F', 'P', 'R', 'S', and 'T'. The empty string is returned if no flags are set or if « info » contains experimental semantics.

set_flags(flags)

Set the flags specified by flags and unset all others.

add_flag(flag)

Set the flag(s) specified by flag without changing other flags. To add more than one flag at a time, flag may be a string of more than one character. The current « info » is overwritten whether or not it contains experimental information rather than flags.

remove_flag(flag)

Unset the flag(s) specified by flag without changing other flags. To remove more than one flag at a time, flag maybe a string of more than one character. If « info » contains experimental information rather than flags, the current « info » is not modified.

get_date()

Return the delivery date of the message as a floating-point number representing seconds since the epoch.

set_date(date)

Set the delivery date of the message to date, a floating-point number representing seconds since the epoch.

get_info()

Return a string containing the « info » for a message. This is useful for accessing and modifying « info » that is experimental (i.e., not a list of flags).

set_info(info)

Set « info » to info, which should be a string.

When a MaildirMessage instance is created based upon an mboxMessage or MMDFMessage instance, the Status and X-Status headers are omitted and the following conversions take place:

Resulting state

mboxMessage or MMDFMessage state

« cur » subdirectory

O flag

F flag

F flag

R flag

A flag

S flag

R flag

T flag

D flag

When a MaildirMessage instance is created based upon an MHMessage instance, the following conversions take place:

Resulting state

MHMessage state

« cur » subdirectory

« unseen » sequence

« cur » subdirectory and S flag

no « unseen » sequence

F flag

« flagged » sequence

R flag

« replied » sequence

When a MaildirMessage instance is created based upon a BabylMessage instance, the following conversions take place:

Resulting state

BabylMessage state

« cur » subdirectory

« unseen » label

« cur » subdirectory and S flag

no « unseen » label

P flag

« forwarded » or « resent » label

R flag

« answered » label

T flag

« deleted » label

19.4.2.2. mboxMessage

class mailbox.mboxMessage(message=None)

A message with mbox-specific behaviors. Parameter message has the same meaning as with the Message constructor.

Messages in an mbox mailbox are stored together in a single file. The sender’s envelope address and the time of delivery are typically stored in a line beginning with « From  » that is used to indicate the start of a message, though there is considerable variation in the exact format of this data among mbox implementations. Flags that indicate the state of the message, such as whether it has been read or marked as important, are typically stored in Status and X-Status headers.

Conventional flags for mbox messages are as follows:

Option

Signification

Explication

R

Read

Read

O

Old

Previously detected by MUA

D

Deleted

Marked for subsequent deletion

F

Flagged

Marked as important

A

Answered

Replied to

The « R » and « O » flags are stored in the Status header, and the « D », « F », and « A » flags are stored in the X-Status header. The flags and headers typically appear in the order mentioned.

mboxMessage instances offer the following methods:

get_from()

Return a string representing the « From  » line that marks the start of the message in an mbox mailbox. The leading « From  » and the trailing newline are excluded.

set_from(from_, time_=None)

Set the « From  » line to from_, which should be specified without a leading « From  » or trailing newline. For convenience, time_ may be specified and will be formatted appropriately and appended to from_. If time_ is specified, it should be a time.struct_time instance, a tuple suitable for passing to time.strftime(), or True (to use time.gmtime()).

get_flags()

Return a string specifying the flags that are currently set. If the message complies with the conventional format, the result is the concatenation in the following order of zero or one occurrence of each of 'R', 'O', 'D', 'F', and 'A'.

set_flags(flags)

Set the flags specified by flags and unset all others. Parameter flags should be the concatenation in any order of zero or more occurrences of each of 'R', 'O', 'D', 'F', and 'A'.

add_flag(flag)

Set the flag(s) specified by flag without changing other flags. To add more than one flag at a time, flag may be a string of more than one character.

remove_flag(flag)

Unset the flag(s) specified by flag without changing other flags. To remove more than one flag at a time, flag maybe a string of more than one character.

When an mboxMessage instance is created based upon a MaildirMessage instance, a « From  » line is generated based upon the MaildirMessage instance’s delivery date, and the following conversions take place:

Resulting state

MaildirMessage state

R flag

S flag

O flag

« cur » subdirectory

D flag

T flag

F flag

F flag

A flag

R flag

When an mboxMessage instance is created based upon an MHMessage instance, the following conversions take place:

Resulting state

MHMessage state

R flag and O flag

no « unseen » sequence

O flag

« unseen » sequence

F flag

« flagged » sequence

A flag

« replied » sequence

When an mboxMessage instance is created based upon a BabylMessage instance, the following conversions take place:

Resulting state

BabylMessage state

R flag and O flag

no « unseen » label

O flag

« unseen » label

D flag

« deleted » label

A flag

« answered » label

When a Message instance is created based upon an MMDFMessage instance, the « From  » line is copied and all flags directly correspond:

Resulting state

MMDFMessage state

R flag

R flag

O flag

O flag

D flag

D flag

F flag

F flag

A flag

A flag

19.4.2.3. MHMessage

class mailbox.MHMessage(message=None)

A message with MH-specific behaviors. Parameter message has the same meaning as with the Message constructor.

MH messages do not support marks or flags in the traditional sense, but they do support sequences, which are logical groupings of arbitrary messages. Some mail reading programs (although not the standard mh and nmh) use sequences in much the same way flags are used with other formats, as follows:

Sequence

Explication

unseen

Not read, but previously detected by MUA

replied

Replied to

flagged

Marked as important

MHMessage instances offer the following methods:

get_sequences()

Return a list of the names of sequences that include this message.

set_sequences(sequences)

Set the list of sequences that include this message.

add_sequence(sequence)

Add sequence to the list of sequences that include this message.

remove_sequence(sequence)

Remove sequence from the list of sequences that include this message.

When an MHMessage instance is created based upon a MaildirMessage instance, the following conversions take place:

Resulting state

MaildirMessage state

« unseen » sequence

no S flag

« replied » sequence

R flag

« flagged » sequence

F flag

When an MHMessage instance is created based upon an mboxMessage or MMDFMessage instance, the Status and X-Status headers are omitted and the following conversions take place:

Resulting state

mboxMessage or MMDFMessage state

« unseen » sequence

no R flag

« replied » sequence

A flag

« flagged » sequence

F flag

When an MHMessage instance is created based upon a BabylMessage instance, the following conversions take place:

Resulting state

BabylMessage state

« unseen » sequence

« unseen » label

« replied » sequence

« answered » label

19.4.2.4. BabylMessage

class mailbox.BabylMessage(message=None)

A message with Babyl-specific behaviors. Parameter message has the same meaning as with the Message constructor.

Certain message labels, called attributes, are defined by convention to have special meanings. The attributes are as follows:

Label

Explication

unseen

Not read, but previously detected by MUA

deleted

Marked for subsequent deletion

filed

Copied to another file or mailbox

answered

Replied to

forwarded

Forwarded

edited

Modified by the user

resent

Resent

By default, Rmail displays only visible headers. The BabylMessage class, though, uses the original headers because they are more complete. Visible headers may be accessed explicitly if desired.

BabylMessage instances offer the following methods:

get_labels()

Return a list of labels on the message.

set_labels(labels)

Set the list of labels on the message to labels.

add_label(label)

Add label to the list of labels on the message.

remove_label(label)

Remove label from the list of labels on the message.

get_visible()

Return an Message instance whose headers are the message’s visible headers and whose body is empty.

set_visible(visible)

Set the message’s visible headers to be the same as the headers in message. Parameter visible should be a Message instance, an email.message.Message instance, a string, or a file-like object (which should be open in text mode).

update_visible()

When a BabylMessage instance’s original headers are modified, the visible headers are not automatically modified to correspond. This method updates the visible headers as follows: each visible header with a corresponding original header is set to the value of the original header, each visible header without a corresponding original header is removed, and any of Date, From, Reply-To, To, CC, and Subject that are present in the original headers but not the visible headers are added to the visible headers.

When a BabylMessage instance is created based upon a MaildirMessage instance, the following conversions take place:

Resulting state

MaildirMessage state

« unseen » label

no S flag

« deleted » label

T flag

« answered » label

R flag

« forwarded » label

P flag

When a BabylMessage instance is created based upon an mboxMessage or MMDFMessage instance, the Status and X-Status headers are omitted and the following conversions take place:

Resulting state

mboxMessage or MMDFMessage state

« unseen » label

no R flag

« deleted » label

D flag

« answered » label

A flag

When a BabylMessage instance is created based upon an MHMessage instance, the following conversions take place:

Resulting state

MHMessage state

« unseen » label

« unseen » sequence

« answered » label

« replied » sequence

19.4.2.5. MMDFMessage

class mailbox.MMDFMessage(message=None)

A message with MMDF-specific behaviors. Parameter message has the same meaning as with the Message constructor.

As with message in an mbox mailbox, MMDF messages are stored with the sender’s address and the delivery date in an initial line beginning with « From « . Likewise, flags that indicate the state of the message are typically stored in Status and X-Status headers.

Conventional flags for MMDF messages are identical to those of mbox message and are as follows:

Option

Signification

Explication

R

Read

Read

O

Old

Previously detected by MUA

D

Deleted

Marked for subsequent deletion

F

Flagged

Marked as important

A

Answered

Replied to

The « R » and « O » flags are stored in the Status header, and the « D », « F », and « A » flags are stored in the X-Status header. The flags and headers typically appear in the order mentioned.

MMDFMessage instances offer the following methods, which are identical to those offered by mboxMessage:

get_from()

Return a string representing the « From  » line that marks the start of the message in an mbox mailbox. The leading « From  » and the trailing newline are excluded.

set_from(from_, time_=None)

Set the « From  » line to from_, which should be specified without a leading « From  » or trailing newline. For convenience, time_ may be specified and will be formatted appropriately and appended to from_. If time_ is specified, it should be a time.struct_time instance, a tuple suitable for passing to time.strftime(), or True (to use time.gmtime()).

get_flags()

Return a string specifying the flags that are currently set. If the message complies with the conventional format, the result is the concatenation in the following order of zero or one occurrence of each of 'R', 'O', 'D', 'F', and 'A'.

set_flags(flags)

Set the flags specified by flags and unset all others. Parameter flags should be the concatenation in any order of zero or more occurrences of each of 'R', 'O', 'D', 'F', and 'A'.

add_flag(flag)

Set the flag(s) specified by flag without changing other flags. To add more than one flag at a time, flag may be a string of more than one character.

remove_flag(flag)

Unset the flag(s) specified by flag without changing other flags. To remove more than one flag at a time, flag maybe a string of more than one character.

When an MMDFMessage instance is created based upon a MaildirMessage instance, a « From  » line is generated based upon the MaildirMessage instance’s delivery date, and the following conversions take place:

Resulting state

MaildirMessage state

R flag

S flag

O flag

« cur » subdirectory

D flag

T flag

F flag

F flag

A flag

R flag

When an MMDFMessage instance is created based upon an MHMessage instance, the following conversions take place:

Resulting state

MHMessage state

R flag and O flag

no « unseen » sequence

O flag

« unseen » sequence

F flag

« flagged » sequence

A flag

« replied » sequence

When an MMDFMessage instance is created based upon a BabylMessage instance, the following conversions take place:

Resulting state

BabylMessage state

R flag and O flag

no « unseen » label

O flag

« unseen » label

D flag

« deleted » label

A flag

« answered » label

When an MMDFMessage instance is created based upon an mboxMessage instance, the « From  » line is copied and all flags directly correspond:

Resulting state

mboxMessage state

R flag

R flag

O flag

O flag

D flag

D flag

F flag

F flag

A flag

A flag

19.4.3. Exceptions

The following exception classes are defined in the mailbox module:

exception mailbox.Error

The based class for all other module-specific exceptions.

exception mailbox.NoSuchMailboxError

Raised when a mailbox is expected but is not found, such as when instantiating a Mailbox subclass with a path that does not exist (and with the create parameter set to False), or when opening a folder that does not exist.

exception mailbox.NotEmptyError

Raised when a mailbox is not empty but is expected to be, such as when deleting a folder that contains messages.

exception mailbox.ExternalClashError

Raised when some mailbox-related condition beyond the control of the program causes it to be unable to proceed, such as when failing to acquire a lock that another program already holds a lock, or when a uniquely-generated file name already exists.

exception mailbox.FormatError

Raised when the data in a file cannot be parsed, such as when an MH instance attempts to read a corrupted .mh_sequences file.

19.4.4. Exemples

A simple example of printing the subjects of all messages in a mailbox that seem interesting:

import mailbox
for message in mailbox.mbox('~/mbox'):
    subject = message['subject']       # Could possibly be None.
    if subject and 'python' in subject.lower():
        print(subject)

To copy all mail from a Babyl mailbox to an MH mailbox, converting all of the format-specific information that can be converted:

import mailbox
destination = mailbox.MH('~/Mail')
destination.lock()
for message in mailbox.Babyl('~/RMAIL'):
    destination.add(mailbox.MHMessage(message))
destination.flush()
destination.unlock()

This example sorts mail from several mailing lists into different mailboxes, being careful to avoid mail corruption due to concurrent modification by other programs, mail loss due to interruption of the program, or premature termination due to malformed messages in the mailbox:

import mailbox
import email.errors

list_names = ('python-list', 'python-dev', 'python-bugs')

boxes = {name: mailbox.mbox('~/email/%s' % name) for name in list_names}
inbox = mailbox.Maildir('~/Maildir', factory=None)

for key in inbox.iterkeys():
    try:
        message = inbox[key]
    except email.errors.MessageParseError:
        continue                # The message is malformed. Just leave it.

    for name in list_names:
        list_id = message['list-id']
        if list_id and name in list_id:
            # Get mailbox to use
            box = boxes[name]

            # Write copy to disk before removing original.
            # If there's a crash, you might duplicate a message, but
            # that's better than losing a message completely.
            box.lock()
            box.add(message)
            box.flush()
            box.unlock()

            # Remove original message
            inbox.lock()
            inbox.discard(key)
            inbox.flush()
            inbox.unlock()
            break               # Found destination, so stop looking.

for box in boxes.itervalues():
    box.close()

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19.5. mimetypes — Map filenames to MIME types

Source code: Lib/mimetypes.py [https://github.com/python/cpython/tree/3.6/Lib/mimetypes.py]

The mimetypes module converts between a filename or URL and the MIME type associated with the filename extension. Conversions are provided from filename to MIME type and from MIME type to filename extension; encodings are not supported for the latter conversion.

The module provides one class and a number of convenience functions. The functions are the normal interface to this module, but some applications may be interested in the class as well.

The functions described below provide the primary interface for this module. If the module has not been initialized, they will call init() if they rely on the information init() sets up.

mimetypes.guess_type(url, strict=True)

Guess the type of a file based on its filename or URL, given by url. The return value is a tuple (type, encoding) where type is None if the type can’t be guessed (missing or unknown suffix) or a string of the form 'type/subtype', usable for a MIME content-type header.

encoding is None for no encoding or the name of the program used to encode (e.g. compress or gzip). The encoding is suitable for use as a Content-Encoding header, not as a Content-Transfer-Encoding header. The mappings are table driven. Encoding suffixes are case sensitive; type suffixes are first tried case sensitively, then case insensitively.

The optional strict argument is a flag specifying whether the list of known MIME types is limited to only the official types registered with IANA [https://www.iana.org/assignments/media-types/media-types.xhtml]. When strict is True (the default), only the IANA types are supported; when strict is False, some additional non-standard but commonly used MIME types are also recognized.

mimetypes.guess_all_extensions(type, strict=True)

Guess the extensions for a file based on its MIME type, given by type. The return value is a list of strings giving all possible filename extensions, including the leading dot ('.'). The extensions are not guaranteed to have been associated with any particular data stream, but would be mapped to the MIME type type by guess_type().

The optional strict argument has the same meaning as with the guess_type() function.

mimetypes.guess_extension(type, strict=True)

Guess the extension for a file based on its MIME type, given by type. The return value is a string giving a filename extension, including the leading dot ('.'). The extension is not guaranteed to have been associated with any particular data stream, but would be mapped to the MIME type type by guess_type(). If no extension can be guessed for type, None is returned.

The optional strict argument has the same meaning as with the guess_type() function.

Some additional functions and data items are available for controlling the behavior of the module.

mimetypes.init(files=None)

Initialize the internal data structures. If given, files must be a sequence of file names which should be used to augment the default type map. If omitted, the file names to use are taken from knownfiles; on Windows, the current registry settings are loaded. Each file named in files or knownfiles takes precedence over those named before it. Calling init() repeatedly is allowed.

Specifying an empty list for files will prevent the system defaults from being applied: only the well-known values will be present from a built-in list.

Modifié dans la version 3.2: Previously, Windows registry settings were ignored.

mimetypes.read_mime_types(filename)

Load the type map given in the file filename, if it exists. The type map is returned as a dictionary mapping filename extensions, including the leading dot ('.'), to strings of the form 'type/subtype'. If the file filename does not exist or cannot be read, None is returned.

mimetypes.add_type(type, ext, strict=True)

Add a mapping from the MIME type type to the extension ext. When the extension is already known, the new type will replace the old one. When the type is already known the extension will be added to the list of known extensions.

When strict is True (the default), the mapping will be added to the official MIME types, otherwise to the non-standard ones.

mimetypes.inited

Flag indicating whether or not the global data structures have been initialized. This is set to True by init().

mimetypes.knownfiles

List of type map file names commonly installed. These files are typically named mime.types and are installed in different locations by different packages.

mimetypes.suffix_map

Dictionary mapping suffixes to suffixes. This is used to allow recognition of encoded files for which the encoding and the type are indicated by the same extension. For example, the .tgz extension is mapped to .tar.gz to allow the encoding and type to be recognized separately.

mimetypes.encodings_map

Dictionary mapping filename extensions to encoding types.

mimetypes.types_map

Dictionary mapping filename extensions to MIME types.

mimetypes.common_types

Dictionary mapping filename extensions to non-standard, but commonly found MIME types.

Un exemple d’utilisation du module :

>>> import mimetypes
>>> mimetypes.init()
>>> mimetypes.knownfiles
['/etc/mime.types', '/etc/httpd/mime.types', ... ]
>>> mimetypes.suffix_map['.tgz']
'.tar.gz'
>>> mimetypes.encodings_map['.gz']
'gzip'
>>> mimetypes.types_map['.tgz']
'application/x-tar-gz'

19.5.1. MimeTypes Objects

The MimeTypes class may be useful for applications which may want more than one MIME-type database; it provides an interface similar to the one of the mimetypes module.

class mimetypes.MimeTypes(filenames=(), strict=True)

This class represents a MIME-types database. By default, it provides access to the same database as the rest of this module. The initial database is a copy of that provided by the module, and may be extended by loading additional mime.types-style files into the database using the read() or readfp() methods. The mapping dictionaries may also be cleared before loading additional data if the default data is not desired.

The optional filenames parameter can be used to cause additional files to be loaded « on top » of the default database.

suffix_map

Dictionary mapping suffixes to suffixes. This is used to allow recognition of encoded files for which the encoding and the type are indicated by the same extension. For example, the .tgz extension is mapped to .tar.gz to allow the encoding and type to be recognized separately. This is initially a copy of the global suffix_map defined in the module.

encodings_map

Dictionary mapping filename extensions to encoding types. This is initially a copy of the global encodings_map defined in the module.

types_map

Tuple containing two dictionaries, mapping filename extensions to MIME types: the first dictionary is for the non-standards types and the second one is for the standard types. They are initialized by common_types and types_map.

types_map_inv

Tuple containing two dictionaries, mapping MIME types to a list of filename extensions: the first dictionary is for the non-standards types and the second one is for the standard types. They are initialized by common_types and types_map.

guess_extension(type, strict=True)

Similar to the guess_extension() function, using the tables stored as part of the object.

guess_type(url, strict=True)

Similar to the guess_type() function, using the tables stored as part of the object.

guess_all_extensions(type, strict=True)

Similar to the guess_all_extensions() function, using the tables stored as part of the object.

read(filename, strict=True)

Load MIME information from a file named filename. This uses readfp() to parse the file.

If strict is True, information will be added to list of standard types, else to the list of non-standard types.

readfp(fp, strict=True)

Load MIME type information from an open file fp. The file must have the format of the standard mime.types files.

If strict is True, information will be added to the list of standard types, else to the list of non-standard types.

read_windows_registry(strict=True)

Load MIME type information from the Windows registry. Availability: Windows.

If strict is True, information will be added to the list of standard types, else to the list of non-standard types.

Nouveau dans la version 3.2.

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19.6. base64 — Encodages base16, base32, base64 et base85

Code source : Lib/base64.py [https://github.com/python/cpython/tree/3.6/Lib/base64.py]

Ce module fournit des fonctions permettant de coder des données binaires en caractères ASCII affichables ainsi que de décoder ces caractères vers des données binaires en retour. Il fournit des fonctions d’encodage et de décodage pour les codages spécifiés par la RFC 3548 [https://tools.ietf.org/html/rfc3548.html] qui définit les algorithmes base16, base32 et base64, ainsi que les encodages standards de facto Ascii85 et base85.

Les encodages définis par la RFC 3548 [https://tools.ietf.org/html/rfc3548.html] sont adaptés au codage des données binaires pour leur transfert par courriel, comme éléments d’une URL ou d’une requête HTTP POST. L’algorithme d’encodage ne doit pas être confondu avec le programme uuencode.

Ce module présente deux interfaces. L’interface moderne gère l’encodage d”objets octet-compatibles en bytes ASCII ainsi que le décodage d”objets octet-compatibles ou de chaînes de caractères contenant de l’ASCII en bytes. Les deux alphabets de l’algorithme base64 définis par la RFC 3548 [https://tools.ietf.org/html/rfc3548.html] (normal et sûr pour les systèmes de fichiers ou URL) sont gérés.

L’interface historique ne permet pas le décodage des chaînes de caractères mais fournit des fonctions permettant d’encoder et décoder depuis et vers des objets fichiers. Elle ne gère que l’alphabet base64 standard et ajoute une nouvelle ligne tous les 76 caractères, comme spécifié par la RFC 2045 [https://tools.ietf.org/html/rfc2045.html]. Notez que le paquet email est probablement ce que vous cherchez si vous souhaitez une implémentation de la RFC 2045 [https://tools.ietf.org/html/rfc2045.html].

Modifié dans la version 3.3: Les chaînes de caractères Unicode contenant uniquement des caractères ASCII sont désormais acceptées par les fonctions de décodage de l’interface moderne.

Modifié dans la version 3.4: Tous les objets octet-compatibles sont désormais acceptés par l’ensemble des fonctions d’encodage et de décodage de ce module. La gestion de Ascii85/base85 a été ajoutée.

L’interface moderne propose :

base64.b64encode(s, altchars=None)

Encode un objet octet-compatible s en utilisant l’algorithme base64 et renvoie les bytes encodés.

L’option altchars doit être un bytes-like object de longueur au moins 2 (les caractères additionnels sont ignorés) qui spécifie un alphabet alternatif pour les délimiteurs + et /. Cela permet de générer des chaînes de caractères base64 pouvant être utilisées pour une URL ou dans un système de fichiers. La valeur par défaut est None, auquel cas l’alphabet standard base64 est utilisé.

base64.b64decode(s, altchars=None, validate=False)

Décode un objet octet-compatible ou une chaîne de caractères ASCII s encodée en base64 et renvoie les bytes décodés.

L’option altchars doit être un bytes-like object de longueur au moins égale à 2 (les caractères additionnels sont ignorés) qui spécifie un alphabet alternatif pour les délimiteurs + et /.

Une exception binascii.Error est levée si s n’est pas remplie à une longueur attendue.

Si validate est False (par défaut), les caractères qui ne sont ni dans l’alphabet base64 normal, ni dans l’alphabet alternatif, sont ignorés avant la vérification de la longueur du remplissage. Si validate est True, les caractères hors de l’alphabet de l’entrée produisent une binascii.Error.

base64.standard_b64encode(s)

Encode un objet octet-compatible s en utilisant l’alphabet standard base64 et renvoie les bytes encodés.

base64.standard_b64decode(s)

Décode un objet octet-compatible ou une chaîne de caractères ASCII s utilisant l’alphabet base64 standard et renvoie les bytes décodés.

base64.urlsafe_b64encode(s)

Encode un objet byte-compatible s en utilisant un alphabet sûr pour les URL et systèmes de fichiers qui substitue - et _ à + et / dans l’alphabet standard base64 et renvoie les bytes encodés.

base64.urlsafe_b64decode(s)

Décode un objet octet-compatible ou une chaîne de caractères ASCII s utilisant un alphabet sûr pour les URL et systèmes de fichiers qui substitue - et _ à + et / dans l’alphabet standard base64 et renvoie les bytes décodés.

base64.b32encode(s)

Encode un objet byte-compatible s en utilisant l’algorithme base32 et renvoie les bytes encodés.

base64.b32decode(s, casefold=False, map01=None)

Décode un objet octet-compatible ou une chaîne de caractères ASCII s encodé en base32 et renvoie les bytes décodés.

L’option casefold est un drapeau spécifiant si l’utilisation d’un alphabet en minuscules est acceptable comme entrée. Pour des raisons de sécurité, cette option est à False par défaut.

La RFC 3548 [https://tools.ietf.org/html/rfc3548.html] autorise une correspondance optionnelle du chiffre 0 (zéro) vers la lettre O (/o/) ainsi que du chiffre 1 (un) vers soit la lettre I (/i/) ou la lettre L (/l/). L’argument optionnel map01, lorsqu’il diffère de None, spécifie en quelle lettre le chiffre 1 doit être transformé (lorsque map01 n’est pas None, le chiffre 0 est toujours transformé en la lettre O). Pour des raisons de sécurité, le défaut est None, de telle sorte que 0 et 1 ne sont pas autorisés dans l’entrée.

Une exception binascii.Error est levée si s n’est pas remplie à une longueur attendue ou si elle contient des caractères hors de l’alphabet.

base64.b16encode(s)

Encode un objet byte-compatible s en utilisant l’algorithme base16 et renvoie les bytes encodés.

base64.b16decode(s, casefold=False)

Décode un objet octet-compatible ou une chaîne de caractères ASCII s encodé en base16 et renvoie les bytes décodés.

L’option casefold est un drapeau spécifiant si l’utilisation d’un alphabet en minuscules est acceptable comme entrée. Pour des raisons de sécurité, cette option est à False par défaut.

Une exception binascii.Error est levée si s n’est pas remplie à une longueur attendue ou si elle contient des caractères hors de l’alphabet.

base64.a85encode(b, *, foldspaces=False, wrapcol=0, pad=False, adobe=False)

Encode un objet byte-compatible s en utilisant l’algorithme Ascii85 et renvoie les bytes encodés.

L’option foldspaces permet d’utiliser la séquence spéciale “y” à la place de quatre espaces consécutives (ASCII 0x20) comme pris en charge par btoa. Cette fonctionnalité n’est pas gérée par l’encodage « standard » Ascii85.

wrapcol contrôle l’ajout de caractères de saut de ligne (b'\n') à la sortie. Chaque ligne de sortie contient au maximum wrapcol caractères si cette option diffère de zéro.

pad spécifie l’ajout de caractères de remplissage (padding en anglais) à l’entrée jusqu’à ce que sa longueur soit un multiple de 4 avant encodage. Notez que l’implémentation btoa effectue systématiquement ce remplissage.

adobe contrôle si oui ou non la séquence encodée d’octets est encadrée par <~ et ~> comme utilisé dans l’implémentation Adobe.

Nouveau dans la version 3.4.

base64.a85decode(b, *, foldspaces=False, adobe=False, ignorechars=b' \t\n\r\v')

Décode un objet octet-compatible ou une chaîne de caractères ASCII s encodé en Ascii85 et renvoie les bytes décodés.

L’option foldspaces permet d’utiliser la séquence spéciale “y” à la place de quatre espaces consécutives (ASCII 0x20) comme pris en charge par btoa. Cette fonctionnalité n’est pas gérée par l’encodage « standard » Ascii85.

adobe indique si la séquence d’entrée utilise le format Adobe Ascii85 (c’est-à-dire utilise l’encadrement par <~ et ~>).

ignorechars doit être un bytes-like object ou une chaîne ASCII contenant des caractères à ignorer dans l’entrée. Il ne doit contenir que des caractères d’espacement et contient par défaut l’ensemble des caractères d’espacement de l’alphabet ASCII.

Nouveau dans la version 3.4.

base64.b85encode(b, pad=False)

Encode un objet byte-compatible s en utilisant l’algorithme base85 (tel qu’utilisé par exemple par le programme git-diff sur des données binaires) et renvoie les bytes encodés.

Si pad est vrai, des caractères de remplissage b'``0' (padding en anglais) sont ajoutés à l’entrée jusqu’à ce que sa longueur soit un multiple de 4 octets avant encodage.

Nouveau dans la version 3.4.

base64.b85decode(b)

Décode un objet octet-compatible ou une chaîne de caractères ASCII b encodé en base85 et renvoie les bytes décodés. Les caractères de remplissage sont implicitement retirés si nécessaire.

Nouveau dans la version 3.4.

L’interface historique :

base64.decode(input, output)

Décode le contenu d’un fichier binaire input et écrit les données binaires résultantes dans le fichier output. input et output doivent être des objets fichiers. input est lu jusqu’à ce que input.readline() renvoie un objet bytes vide.

base64.decodebytes(s)

Décode un objet octet-compatible s devant contenir une ou plusieurs lignes de données encodées en base64 et renvoie les bytes décodés.

Nouveau dans la version 3.1.

base64.decodestring(s)

Alias obsolète de decodebytes().

Obsolète depuis la version 3.1.

base64.encode(input, output)

Encode le contenu du fichier binaire input et écrit les données encodées en base64 résultantes dans le fichier output. *input et output doivent être des objets fichiers. input est lu jusqu’à ce que input.readline() renvoie un objet bytes vide. encode() insère un caractère de saut de ligne (b'\n') tous les 76 octets de sortie et assure que celle-ci se termine par une nouvelle ligne, comme spécifié par la RFC 2045 [https://tools.ietf.org/html/rfc2045.html] (MIME).

base64.encodebytes(s)

Encode un objet octet-compatible s pouvant contenir des données binaires arbitraires et renvoie les bytes contenant les données encodées en base64. Un caractère de saut de ligne (b'\n') est inséré tous les 76 octets de sortie et celle-ci se termine par une nouvelle ligne, comme spécifié par la RFC 2045 [https://tools.ietf.org/html/rfc2045.html] (MIME).

Nouveau dans la version 3.1.

base64.encodestring(s)

Alias obsolète de encodebytes().

Obsolète depuis la version 3.1.

Un exemple d’utilisation du module :

>>> import base64
>>> encoded = base64.b64encode(b'data to be encoded')
>>> encoded
b'ZGF0YSB0byBiZSBlbmNvZGVk'
>>> data = base64.b64decode(encoded)
>>> data
b'data to be encoded'

Voir aussi

Module binascii

Module secondaire contenant les conversions ASCII vers binaire et binaire vers ASCII.

RFC 1521 [https://tools.ietf.org/html/rfc1521.html] — MIME (Multipurpose Internet Mail Extensions) Part One: Mechanisms for Specifying and Describing the Format of Internet Message Bodies

La Section 5.2, « Base64 Content-Transfer-Encoding », donne la définition de l’encodage base64.

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19.7. binhex — Encode et décode les fichiers binhex4

Code source : Lib/binhex.py [https://github.com/python/cpython/tree/3.6/Lib/binhex.py]

Ce module encode et décode les fichiers au format binhex4, un format permettant la représentation de fichier Macintosh au format ASCII. Seulement la fourchette de donnée est supportée.

Le module binhex définit les fonctions suivantes :

binhex.binhex(input, output)

Convertit un fichier binaire avec comme nom input en fichier binhex output. Le paramètre output peut être soit un nom de fichier, soit un objet s’apparentant à un fichier (tout objet supportant les méthodes write() et close()).

binhex.hexbin(input, output)

Décode un fichier binhex input. input peut être soit un nom de fichier, soit un objet s’apparentant à un fichier supportant les méthodes write() et close(). Le résultat est écrit dans un fichier nommé output, sauf si l’argument est None, dans ce cas le fichier de sortie est lu depuis le fichier binhex.

L’exception suivante est aussi définie :

exception binhex.Error

Exception levée quand quelque chose ne peut être encodé en utilisant le format binhex (par exemple, un nom de fichier trop long pour rentrer dans le champ filename) ou quand les données d’entrée ne sont pas encodées correctement en binhex.

Voir aussi

Module binascii

Module secondaire contenant les conversions ASCII vers binaire et binaire vers ASCII.

19.7.1. Notes

Il y a une alternative, une interface plus puissante pour le codeur et décodeur, voir les sources pour les détails.

Si vous codez ou décodez sur des plateformes autres que Macintosh, elles utiliseront l’ancienne convention Macintosh pour les retours à la ligne (retour-chariot comme fin de ligne).

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19.8. binascii — Conversion entre binaire et ASCII

Le module binascii contient des méthodes pour convertir entre binaire et diverses représentations binaires encodées en ASCII. Normalement, vous n’allez pas utiliser ces fonctions directement mais vous utiliserez des modules d’encapsulage comme uu, base64, or binhex à la place. Le module binascii contient des fonctions bas-niveau écrites en C plus rapides qui sont utilisées par des modules haut-niveau.

Note

La fonction a2b_* accepte des chaînes de caractères contenant seulement des caractères ASCII. D’autres fonctions acceptent seulement des objets bytes et similaire (tel que bytes, bytearray et autres objets qui supportent le protocole tampon).

Modifié dans la version 3.3: Les chaines de caractères unicode seulement composées de caractères ASCII sont désormais acceptées par les fonctions a2b_*.

Le module binascii définit les fonctions suivantes :

binascii.a2b_uu(string)

Convertit une seule ligne de donnée uuencoded en binaire et renvoie la donnée binaire. Les lignes contiennent normalement 45 octets (binaire), sauf pour la dernière ligne. Il se peut que la ligne de donnée soit suivie d’un espace blanc.

binascii.b2a_uu(data)

Convert binary data to a line of ASCII characters, the return value is the converted line, including a newline char. The length of data should be at most 45.

binascii.a2b_base64(string)

Convertit un bloc de donnée en base64 en binaire et renvoie la donnée binaire. Plus d’une ligne peut être passé à la fois.

binascii.b2a_base64(data, *, newline=True)

Convertit les données binaires en une ligne de caractères ASCII en codage base 64. La valeur de renvoyée et la ligne convertie, incluant un caractère de nouvelle ligne si newline est vraie. La sortie de cette fonction se conforme à RFC 3548 [https://tools.ietf.org/html/rfc3548.html].

Modifié dans la version 3.6: Ajout du paramètre newline.

binascii.a2b_qp(data, header=False)

Convertit un bloc de données quoted-printable en binaire et renvoie les données binaires. Plus d’une ligne peut être passée à la fois. Si l’argument optionnel header est présent et vrai, les traits soulignés seront décodés en espaces.

binascii.b2a_qp(data, quotetabs=False, istext=True, header=False)

Convertit les données binaires en ligne(s) de caractères ASCII en codage imprimable entre guillemets. La valeur de retour est lales lignes(s) convertie(s). Si l’argument optionnel quotetabs est présent et vrai, toutes les tabulations et espaces seront encodés. Si l’argument optionnel istext est présent et faux, les nouvelles lignes ne sont pas encodées mais les espaces de fin de ligne le seront. Si l’argument optionnel header est présent et vrai, les espaces vont être encodés comme de traits soulignés selon RFC 1522 [https://tools.ietf.org/html/rfc1522.html]. Si l’argument optionnel header est présent et faux, les caractères de nouvelle ligne seront également encodés ; sinon la conversion de saut de ligne pourrait corrompre le flux de données binaire.

binascii.a2b_hqx(string)

Convertit un bloc de donnée ASCII au format binhex4 en binaire, sans faire de décompression RLE. La chaîne de caractères doit contenir un nombre complet d’octet binaires ou (au cas où la dernière portion de donnée est au format binhex4) avoir les bits restants à 0.

binascii.rledecode_hqx(data)

Réalise une décompression RLE sur la donnée, d’après la norme binhex4. L’algorithme utilise 0x90 après un octet comme un indicateur de répétition, suivi d’un décompte. Un décompte de 0 définit une valeur d’octet de 0x90. La routine renvoie la donnée décompressée, sauf si la donnée entrante se finit sur un indicateur de répétition orphelin. Dans ce cas l’exception Incomplete est levée.

Modifié dans la version 3.2: Accepte seulement des objets bytestring ou bytearray en entrée.

binascii.rlecode_hqx(data)

Réalise une compression RLE de type binhex4 sur data et renvoie le résultat.

binascii.b2a_hqx(data)

Réalise une traduction hexbin4 de binaire à ASCII et renvoie la chaîne de caractères résultante. L’argument doit être RLE-coded, et avoir une longueur divisible par 3 (sauf, éventuellement, le dernier fragment).

binascii.crc_hqx(data, value)

Calcule une valeur en CRC 16-bit de data, commençant par value comme CRC initial et renvoie le résultat. Ceci utilise le CRC-CCITT polynomial x¹⁶ + x¹² + x⁵ + 1, souvent représenté comme 0x1021. Ce CRC est utilisé dans le format binhex4.

binascii.crc32(data[, value])

Calcule CRC-32, la somme de contrôle 32-bit de data, commençant par un CRC initial de value. Le CRC initial par défaut est zéro. L’algorithme est cohérent avec la somme de contrôle du fichier ZIP. Comme l’algorithme est conçu pour être utilisé comme un algorithme de somme de contrôle, il ne convient pas comme algorithme de hachage général. Utiliser comme suit :

print(binascii.crc32(b"hello world"))
# Or, in two pieces:
crc = binascii.crc32(b"hello")
crc = binascii.crc32(b" world", crc)
print('crc32 = {:#010x}'.format(crc))

Modifié dans la version 3.0: Le résultat est toujours non signé. Pour générer la même valeur numérique sur toutes les versions de Python et plateformes, utilisez crc32(data) & 0xffffffff.

binascii.b2a_hex(data)

binascii.hexlify(data)

Renvoie la représentation hexadécimale du binaire data. Chaque octet de data est converti en la représentation 2 chiffres correspondante. L’objet octets renvoyé est donc deux fois plus long que la longueur de data.

binascii.a2b_hex(hexstr)

binascii.unhexlify(hexstr)

Renvoie la donnée binaire représentée par la chaîne de caractères hexadécimale hexstr. Cette fonction est l’inverse de b2a_hex(). hexstr doit contenir un nombre pair de chiffres hexadécimaux (qui peuvent être en majuscule ou minuscule), sinon une exception Error est levée.

exception binascii.Error

Exception levée en cas d’erreurs. Ce sont typiquement des erreurs de programmation.

exception binascii.Incomplete

Exception levée par des données incomplète. Il ne s’agit généralement pas d’erreurs de programmation, mais elles peuvent être traitées en lisant un peu plus de données et en réessayant.

Voir aussi

Module base64

Support de l’encodage base64-style conforme RFC en base 16, 32, 64 et 85.

Module binhex

Support pour le format binhex utilisé sur Macintosh.

Module uu

Gestion de l’encodage UU utilisé sur Unix.

Module quopri

Support de l’encodage quote-printable utilisé par les messages email MIME.

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19.9. quopri — Encode et décode des données MIME quoted-printable

Code source : Lib/quopri.py [https://github.com/python/cpython/tree/3.6/Lib/quopri.py]

Ce module effectue des encodages et décodages de transport quoted-printable, tel que définis dans la RFC 1521 [https://tools.ietf.org/html/rfc1521.html] : « MIME (Multipurpose Internet Mail Extensions) Part One Mechanisms for Specifying and Describing the Format of Internet Message Bodies ». L’encodage quoted-printable est adapté aux données dans lesquelles peu de données ne sont pas affichables. L’encodage base64 disponible dans le module base64 est plus compact dans les cas où ces caractères sont nombreux, typiquement pour encoder des images.

quopri.decode(input, output, header=False)

Décode le contenu du fichier input et écrit le résultat décodé, binaire, dans le fichier output. input et output doivent être des objets fichiers binaires. Si l’argument facultatif header est fourni et vrai, les underscore seront décodés en espaces. C’est utilisé pour décoder des entêtes encodées « Q » décrits dans la RFC RFC 1522 [https://tools.ietf.org/html/rfc1522.html] : « MIME (Multipurpose Internet Mail Extensions) Part Two: Message Header Extensions for Non-ASCII Text ».

quopri.encode(input, output, quotetabs, header=False)

Encode le contenu du fichier input et écrit le résultat dans le fichier output. input et output doivent être des objets fichiers binaires. quotetabs (paramètre obligatoire) permet de choisir le style d’encodage des espaces et des tabulations, si vrai les espaces seront encodées, sinon elles seront laissées inchangées. Notez que les espaces et tabulations en fin de ligne sont toujours encodées, tel que spécifié par la RFC 1521 [https://tools.ietf.org/html/rfc1521.html]. header est une option permettant d’encoder les espace en underscores, tel que spécifié par la RFC 1522 [https://tools.ietf.org/html/rfc1522.html].

quopri.decodestring(s, header=False)

Fonctionne comme decode(), sauf qu’elle accepte des bytes comme source, et renvoie les bytes décodés correspondants.

quopri.encodestring(s, quotetabs=False, header=False)

Fonctionne comme encode(), sauf qu’elle accepte des bytes comme source et renvoie les bytes encodés correspondants. Par défaut, False est donné au paramètre quotetabs de la fonction encode().

Voir aussi

Module base64

Encode et décode des données MIME en base64

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19.10. uu — Encode et décode les fichiers uuencode

Code source : Lib/uu.py [https://github.com/python/cpython/tree/3.6/Lib/uu.py]

Ce module encode et décode les fichiers au format uuencode, permettant à des données binaires d’être transférées lors de connexion ASCII. Pour tous les arguments où un fichier est attendu, les fonctions acceptent un « objet fichier-compatible ». Pour des raisons de compatibilité avec les anciennes versions de Python, une chaîne de caractères contenant un chemin est aussi acceptée, et le fichier correspondant sera ouvert en lecture et écriture ; le chemin '-' est considéré comme l’entrée ou la sortie standard. Cependant cette interface est obsolète ; il vaut mieux que l’appelant ouvre le fichier lui-même, en s’assurant si nécessaire que le mode d’ouverture soit 'rb' ou 'wb' sur Windows.

Ce code provient d’une contribution de Lance Ellinghouse et a été modifié par Jack Jansen.

Le module uu définit les fonctions suivantes :

uu.encode(in_file, out_file, name=None, mode=None)

Uuencode le fichier in_file dans le fichier out_file. Le fichier uuencodé contiendra une entête spécifiant les valeurs de name et mode par défaut pour le décodage du fichier. Par défaut ces valeurs sont prises de in_file ou valent respectivement '-' et 0o666.

uu.decode(in_file, out_file=None, mode=None, quiet=False)

Décode le fichier in_file et écrit le résultat dans out_file. Si out_file est un chemin, mode est utilisé pour les permissions du fichier lors de sa création. Les valeurs par défaut pour out_file et mode sont récupérées des entêtes uuencode. Cependant, si le fichier spécifié par les entêtes est déjà existant, une exception uu.Error est levée.

La fonction decode() écrit un avertissement sur la sortie d’erreur si l’entrée contient des erreurs mais que Python a pu s’en sortir. Mettre quiet à True empêche l’écriture de cet avertissement.

exception uu.Error

Classe fille d”Exception, elle peut être levée par uu.decode() dans différentes situations, tel que décrit plus haut, mais aussi en cas d’entête mal formatée ou d’entrée tronquée.

Voir aussi

Module binascii

Module secondaire contenant les conversions ASCII vers binaire et binaire vers ASCII.

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20. Outils de traitement de balises structurées

Python intègre une variété de modules pour fonctionner avec différentes formes de données structurées et balisées, comme le SGML (Standard Generalized Markup Language), le HTML (Hypert Markup Language), et quelques interfaces pour travailler avec du XML (eXtensible Markup Language).

20.1. html — Support du HyperText Markup Language

20.2. html.parser — Simple HTML and XHTML parser

20.2.1. Example HTML Parser Application

20.2.2. HTMLParser Methods

20.2.3. Exemples

20.3. html.entities — Définitions des entités HTML générales

20.4. Modules de traitement XML

20.4.1. Vulnérabilités XML

20.4.2. Les paquets defusedxml et defusedexpat

20.5. xml.etree.ElementTree — The ElementTree XML API

20.5.1. Tutoriel

20.5.1.1. XML tree and elements

20.5.1.2. Parsing XML

20.5.1.3. Pull API for non-blocking parsing

20.5.1.4. Finding interesting elements

20.5.1.5. Modifying an XML File

20.5.1.6. Building XML documents

20.5.1.7. Parsing XML with Namespaces

20.5.1.8. Additional resources

20.5.2. XPath support

20.5.2.1. Exemple

20.5.2.2. Supported XPath syntax

20.5.3. Référence

20.5.3.1. Fonctions

20.5.3.2. Objets Elements

20.5.3.3. ElementTree Objects

20.5.3.4. QName Objects

20.5.3.5. TreeBuilder Objects

20.5.3.6. XMLParser Objects

20.5.3.7. XMLPullParser Objects

20.5.3.8. Exceptions

20.6. xml.dom — L’API Document Object Model

20.6.1. Contenu du module

20.6.2. Objets dans le DOM

20.6.2.1. Objets DOMImplementation

20.6.2.2. Objets nœuds

20.6.2.3. Objet NodeList

20.6.2.4. Objets DocumnentType

20.6.2.5. Objets Document

20.6.2.6. Objets Elements

20.6.2.7. Objets Attr

20.6.2.8. Objets NameNodeMap

20.6.2.9. Objets Comment

20.6.2.10. Objets Text et CDATASection

20.6.2.11. Objets ProcessingInstruction

20.6.2.12. Exceptions

20.6.3. Conformité

20.6.3.1. Correspondance des types

20.6.3.2. Méthodes d’accès

20.7. xml.dom.minidom — Minimal DOM implementation

20.7.1. DOM Objects

20.7.2. DOM Example

20.7.3. minidom and the DOM standard

20.8. xml.dom.pulldom — Support for building partial DOM trees

20.8.1. DOMEventStream Objects

20.9. xml.sax — Prise en charge des analyseurs SAX2

20.9.1. Les objets SAXException

20.10. xml.sax.handler — Base classes for SAX handlers

20.10.1. ContentHandler Objects

20.10.2. DTDHandler Objects

20.10.3. EntityResolver Objects

20.10.4. ErrorHandler Objects

20.11. xml.sax.saxutils — Utilitaires SAX

20.12. xml.sax.xmlreader — Interface for XML parsers

20.12.1. XMLReader Objects

20.12.2. IncrementalParser Objects

20.12.3. Locator Objects

20.12.4. InputSource Objects

20.12.5. The Attributes Interface

20.12.6. The AttributesNS Interface

20.13. xml.parsers.expat — Fast XML parsing using Expat

20.13.1. XMLParser Objects

20.13.2. ExpatError Exceptions

20.13.3. Exemple

20.13.4. Content Model Descriptions

20.13.5. Expat error constants

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20.1. html — Support du HyperText Markup Language

Source code: Lib/html/__init__.py [https://github.com/python/cpython/tree/3.6/Lib/html/__init__.py]

Ce module définit des outils permettant la manipulation d’HTML.

html.escape(s, quote=True)

Convertit les caractères &, < et > de la chaîne de caractères s en séquences HTML valides. À utiliser si le texte à afficher pourrait contenir de tels caractères dans le HTML. Si le paramètre optionnel quote est vrai, les caractères (") et (') sont également traduits; cela est utile pour les inclusions dans des valeurs d’attributs HTML délimitées par des guillemets, comme dans <a href="...">.

Nouveau dans la version 3.2.

html.unescape(s)

Convert all named and numeric character references (e.g. &gt;, &#62;, &#x3e;) in the string s to the corresponding Unicode characters. This function uses the rules defined by the HTML 5 standard for both valid and invalid character references, and the list of HTML 5 named character references.

Nouveau dans la version 3.4.

Les sous-modules dans le paquet html sont :

html.parser – Parseur HTML/XHTML avec un mode de parsing tolérant

html.entities – Définitions d’entités HTML

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20.2. html.parser — Simple HTML and XHTML parser

Source code: Lib/html/parser.py [https://github.com/python/cpython/tree/3.6/Lib/html/parser.py]

This module defines a class HTMLParser which serves as the basis for parsing text files formatted in HTML (HyperText Mark-up Language) and XHTML.

class html.parser.HTMLParser(*, convert_charrefs=True)

Create a parser instance able to parse invalid markup.

If convert_charrefs is True (the default), all character references (except the ones in script/style elements) are automatically converted to the corresponding Unicode characters.

An HTMLParser instance is fed HTML data and calls handler methods when start tags, end tags, text, comments, and other markup elements are encountered. The user should subclass HTMLParser and override its methods to implement the desired behavior.

This parser does not check that end tags match start tags or call the end-tag handler for elements which are closed implicitly by closing an outer element.

Modifié dans la version 3.4: convert_charrefs keyword argument added.

Modifié dans la version 3.5: The default value for argument convert_charrefs is now True.

20.2.1. Example HTML Parser Application

As a basic example, below is a simple HTML parser that uses the HTMLParser class to print out start tags, end tags, and data as they are encountered:

from html.parser import HTMLParser

class MyHTMLParser(HTMLParser):
    def handle_starttag(self, tag, attrs):
        print("Encountered a start tag:", tag)

    def handle_endtag(self, tag):
        print("Encountered an end tag :", tag)

    def handle_data(self, data):
        print("Encountered some data  :", data)

parser = MyHTMLParser()
parser.feed('<html><head><title>Test</title></head>'
            '<body><h1>Parse me!</h1></body></html>')

The output will then be:

Encountered a start tag: html
Encountered a start tag: head
Encountered a start tag: title
Encountered some data  : Test
Encountered an end tag : title
Encountered an end tag : head
Encountered a start tag: body
Encountered a start tag: h1
Encountered some data  : Parse me!
Encountered an end tag : h1
Encountered an end tag : body
Encountered an end tag : html

20.2.2. HTMLParser Methods

HTMLParser instances have the following methods:

HTMLParser.feed(data)

Feed some text to the parser. It is processed insofar as it consists of complete elements; incomplete data is buffered until more data is fed or close() is called. data must be str.

HTMLParser.close()

Force processing of all buffered data as if it were followed by an end-of-file mark. This method may be redefined by a derived class to define additional processing at the end of the input, but the redefined version should always call the HTMLParser base class method close().

HTMLParser.reset()

Reset the instance. Loses all unprocessed data. This is called implicitly at instantiation time.

HTMLParser.getpos()

Return current line number and offset.

HTMLParser.get_starttag_text()

Return the text of the most recently opened start tag. This should not normally be needed for structured processing, but may be useful in dealing with HTML « as deployed » or for re-generating input with minimal changes (whitespace between attributes can be preserved, etc.).

The following methods are called when data or markup elements are encountered and they are meant to be overridden in a subclass. The base class implementations do nothing (except for handle_startendtag()):

HTMLParser.handle_starttag(tag, attrs)

This method is called to handle the start of a tag (e.g. <div id="main">).

The tag argument is the name of the tag converted to lower case. The attrs argument is a list of (name, value) pairs containing the attributes found inside the tag’s <> brackets. The name will be translated to lower case, and quotes in the value have been removed, and character and entity references have been replaced.

For instance, for the tag <A HREF="https://www.cwi.nl/">, this method would be called as handle_starttag('a', [('href', 'https://www.cwi.nl/')]).

All entity references from html.entities are replaced in the attribute values.

HTMLParser.handle_endtag(tag)

This method is called to handle the end tag of an element (e.g. </div>).

The tag argument is the name of the tag converted to lower case.

HTMLParser.handle_startendtag(tag, attrs)

Similar to handle_starttag(), but called when the parser encounters an XHTML-style empty tag (<img ... />). This method may be overridden by subclasses which require this particular lexical information; the default implementation simply calls handle_starttag() and handle_endtag().

HTMLParser.handle_data(data)

This method is called to process arbitrary data (e.g. text nodes and the content of <script>...</script> and <style>...</style>).

HTMLParser.handle_entityref(name)

This method is called to process a named character reference of the form &name; (e.g. &gt;), where name is a general entity reference (e.g. 'gt'). This method is never called if convert_charrefs is True.

HTMLParser.handle_charref(name)

This method is called to process decimal and hexadecimal numeric character references of the form &#NNN; and &#xNNN;. For example, the decimal equivalent for &gt; is &#62;, whereas the hexadecimal is &#x3E;; in this case the method will receive '62' or 'x3E'. This method is never called if convert_charrefs is True.

HTMLParser.handle_comment(data)

This method is called when a comment is encountered (e.g. <!--comment-->).

For example, the comment <!-- comment --> will cause this method to be called with the argument ' comment '.

The content of Internet Explorer conditional comments (condcoms) will also be sent to this method, so, for <!--[if IE 9]>IE9-specific content<![endif]-->, this method will receive '[if IE 9]>IE9-specific content<![endif]'.

HTMLParser.handle_decl(decl)

This method is called to handle an HTML doctype declaration (e.g. <!DOCTYPE html>).

The decl parameter will be the entire contents of the declaration inside the <!...> markup (e.g. 'DOCTYPE html').

HTMLParser.handle_pi(data)

Method called when a processing instruction is encountered. The data parameter will contain the entire processing instruction. For example, for the processing instruction <?proc color='red'>, this method would be called as handle_pi("proc color='red'"). It is intended to be overridden by a derived class; the base class implementation does nothing.

Note

The HTMLParser class uses the SGML syntactic rules for processing instructions. An XHTML processing instruction using the trailing '?' will cause the '?' to be included in data.

HTMLParser.unknown_decl(data)

This method is called when an unrecognized declaration is read by the parser.

The data parameter will be the entire contents of the declaration inside the <![...]> markup. It is sometimes useful to be overridden by a derived class. The base class implementation does nothing.

20.2.3. Exemples

The following class implements a parser that will be used to illustrate more examples:

from html.parser import HTMLParser
from html.entities import name2codepoint

class MyHTMLParser(HTMLParser):
    def handle_starttag(self, tag, attrs):
        print("Start tag:", tag)
        for attr in attrs:
            print("     attr:", attr)

    def handle_endtag(self, tag):
        print("End tag  :", tag)

    def handle_data(self, data):
        print("Data     :", data)

    def handle_comment(self, data):
        print("Comment  :", data)

    def handle_entityref(self, name):
        c = chr(name2codepoint[name])
        print("Named ent:", c)

    def handle_charref(self, name):
        if name.startswith('x'):
            c = chr(int(name[1:], 16))
        else:
            c = chr(int(name))
        print("Num ent  :", c)

    def handle_decl(self, data):
        print("Decl     :", data)

parser = MyHTMLParser()

Parsing a doctype:

>>> parser.feed('<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01//EN" '
...             '"http://www.w3.org/TR/html4/strict.dtd">')
Decl     : DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01//EN" "http://www.w3.org/TR/html4/strict.dtd"

Parsing an element with a few attributes and a title:

>>> parser.feed('<img src="python-logo.png" alt="The Python logo">')
Start tag: img
     attr: ('src', 'python-logo.png')
     attr: ('alt', 'The Python logo')
>>>
>>> parser.feed('<h1>Python</h1>')
Start tag: h1
Data     : Python
End tag  : h1

The content of script and style elements is returned as is, without further parsing:

>>> parser.feed('<style type="text/css">#python { color: green }</style>')
Start tag: style
     attr: ('type', 'text/css')
Data     : #python { color: green }
End tag  : style

>>> parser.feed('<script type="text/javascript">'
...             'alert("<strong>hello!</strong>");</script>')
Start tag: script
     attr: ('type', 'text/javascript')
Data     : alert("<strong>hello!</strong>");
End tag  : script

Parsing comments:

>>> parser.feed('<!-- a comment -->'
...             '<!--[if IE 9]>IE-specific content<![endif]-->')
Comment  :  a comment
Comment  : [if IE 9]>IE-specific content<![endif]

Parsing named and numeric character references and converting them to the correct char (note: these 3 references are all equivalent to '>'):

>>> parser.feed('&gt;&#62;&#x3E;')
Named ent: >
Num ent  : >
Num ent  : >

Feeding incomplete chunks to feed() works, but handle_data() might be called more than once (unless convert_charrefs is set to True):

>>> for chunk in ['<sp', 'an>buff', 'ered ', 'text</s', 'pan>']:
...     parser.feed(chunk)
...
Start tag: span
Data     : buff
Data     : ered
Data     : text
End tag  : span

Parsing invalid HTML (e.g. unquoted attributes) also works:

>>> parser.feed('<p><a class=link href=#main>tag soup</p ></a>')
Start tag: p
Start tag: a
     attr: ('class', 'link')
     attr: ('href', '#main')
Data     : tag soup
End tag  : p
End tag  : a

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20.3. html.entities — Définitions des entités HTML générales

Source code: Lib/html/entities.py [https://github.com/python/cpython/tree/3.6/Lib/html/entities.py]

Ce module définit quatre dictionnaires, html5, name2codepoint, codepoint2name, et entitydefs.

html.entities.html5

Un dictionnaire qui fait correspondre les références de caractères nommés HTML5 1 aux caractères Unicode équivalents, e.g. html5['gt;'] == '>'. À noter que le point-virgule en fin de chaîne est inclus dans le nom (e.g. 'gt;'), toutefois certains noms sont acceptés par le standard même sans le point-virgule: dans ce cas, le nom est présent à la fois avec et sans le ;. Voir aussi html.unescape().

Nouveau dans la version 3.3.

html.entities.entitydefs

Un dictionnaire qui fait correspondre les définitions d’entités XHTML 1.0 avec leur remplacement en ISO Latin-1.

html.entities.name2codepoint

Un dictionnaire qui fait correspondre les noms d’entités HTML avec les points de code Unicode.

html.entities.codepoint2name

Un dictionnaire qui fait correspondre les points de code Unicode avec les noms d’entités HTML.

Notes

1

Voir https://www.w3.org/TR/html5/syntax.html#named-character-references

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20.4. Modules de traitement XML

Code source: Lib/xml/ [https://github.com/python/cpython/tree/3.6/Lib/xml/]

Les interfaces de Python de traitement de XML sont regroupées dans le paquet xml.

Avertissement

Les modules XML ne sont pas protégés contre les données mal construites ou malicieuses. Si vous devez parcourir des données douteuses non authentifiées voir les sections Vulnérabilités XML et Les paquets defusedxml et defusedexpat.

Il est important de noter que les modules dans le paquet xml nécessitent qu’au moins un analyseur compatible SAX soit disponible. L’analyseur Expat est inclus dans Python, ainsi le module xml.parsers.expat est toujours disponible.

La documentation des bindings des interfaces DOM et SAX se trouve dans xml.dom et xml.sax.

Les sous-modules de traitement XML sont :

xml.etree.ElementTree: l’API ElementTree, un processeur simple et léger

xml.dom: la définition de l’API DOM

xml.dom.minidom: une implémentation minimale de DOM

xml.dom.pulldom: gestion de la construction partiel des arbres DOM

xml.sax: classes de bases SAX2 base et fonctions utilitaires

xml.parsers.expat: le binding de l’analyseur Expat

20.4.1. Vulnérabilités XML

Les modules de traitement XML ne sont pas sécurisés contre les données construite malicieusement. Un attaquant peut abuser des fonctionnalités XML pour exécuter des attaques par déni de service, accéder des fichiers locaux, générer des connexions réseaux à d’autres machines ou contourner des pare-feux.

Le tableau suivant donne une vue d’ensemble des attaques connues et indique si les différents modules y sont vulnérables.

type

sax

etree

minidom

pulldom

xmlrpc

billion laughs

Vulnérable

Vulnérable

Vulnérable

Vulnérable

Vulnérable

quadratic blowup

Vulnérable

Vulnérable

Vulnérable

Vulnérable

Vulnérable

external entity expansion

Safe (4)

Sûr (1)

Sûr (2)

Safe (4)

Sûr (3)

Récupération de DTD [https://en.wikipedia.org/wiki/Document_type_definition]

Safe (4)

Sûr

Sûr

Safe (4)

Sûr

decompression bomb

Sûr

Sûr

Sûr

Sûr

Vulnérable

xml.etree.ElementTree n’étend pas les entités externes et lève une exception ParserError quand une telle entité est rencontrée.

xml.dom.minidom n’étend pas les entités externe et renvoie simplement le verbatim de l’entité non étendu.

xmlrpclib n’étend pas les entités externes et les omet.

Since Python 3.8.0, external general entities are no longer processed by default since Python.

billion laughs / exponential entity expansion

L’attaque Billion Laughs [https://en.wikipedia.org/wiki/Billion_laughs] – aussi connue comme exponential entity expansion – utilise de multiples niveaux d’entités imbriquées. Chaque entité se réfère à une autre entité de multiple fois. L’entité finale contiens une chaîne courte. Le résultat de l’expansion exponentielle génère plusieurs gigaoctet de texte et consomme beaucoup de mémoire et de temps processeur.

quadratic blowup entity expansion

Une attaque quadratic blowup est similaire à l’attaque Billion Laughs [https://en.wikipedia.org/wiki/Billion_laughs] ; il s’agit également d’un abus d’extension d’entités. Au lieu d’utiliser des entités imbriquées, cette attaque répète encore et encore une seule entité de plusieurs milliers de caractères. Cette attaque n’est pas aussi efficace que la version exponentielle mais contourne les contre-mesures de l’analyseur qui interdit les entités imbriquées de multiples fois.

external entity expansion

Les déclarations d’entités peuvent contenir plus que du texte de substitution. Elles peuvent également référencer des ressources externes ou des fichiers locaux. L’analyseur XML accède à ces fichiers et inclut les contenus dans le document XML.

Récupération de DTD [https://en.wikipedia.org/wiki/Document_type_definition]

Certaines bibliothèques XML comme xml.dom.pulldom de Python récupère les documents de définitions de types (DTD) depuis des emplacements distants ou locaux. La fonctionnalité a des implications similaires que le problème d’extension d’entités externes.

decompression bomb

Des bombes de décompression (ou ZIP bomb [https://en.wikipedia.org/wiki/Zip_bomb]) sont valables pour toutes les bibliothèques XML qui peuvent analyser des flux XML compressés comme des flux HTTP gzip ou des fichiers compressés LZMA. Pour L’attaquant, cela permet de réduire d’une magnitude d’ordre 3 ou plus la quantité de données transmises.

La documentation de defusedxml [https://pypi.org/project/defusedxml/] sur PyPI contient plus d’informations sur tous les vecteurs d’attaques connus ainsi que des exemples et des références.

20.4.2. Les paquets defusedxml et defusedexpat

defusedxml [https://pypi.org/project/defusedxml/] est un paquet écrit exclusivement en Python avec des sous-classe modifiées de tous les analyseurs de la stdlib XML qui empêche toutes opérations potentiellement malicieuses. L’utilisation de ce paquet est recommandé pour tous serveurs qui analyseraient des donnés XML non fiables. Le paquet inclut également des exemples d’attaques et une documentation plus fournie sur plus d’attaques XML comme XPath injection.

defusedexpat [https://pypi.org/project/defusedexpat/] fournit une version modifiée de libexpat et le module pyexpat modifiée embarquant des contre-mesures contre les attaques DoS par entity expansion. Le module defusedexpat autorise un nombre configurable et raisonnable d’extension d’entités. Ces modifications pourraient être incluses dans des futures version de Python mais ne seront incluses dans aucune version corrective de Python pour éviter de casser la compatibilité rétrograde.

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20.5. xml.etree.ElementTree — The ElementTree XML API

Source code: Lib/xml/etree/ElementTree.py [https://github.com/python/cpython/tree/3.6/Lib/xml/etree/ElementTree.py]

The xml.etree.ElementTree module implements a simple and efficient API for parsing and creating XML data.

Modifié dans la version 3.3: This module will use a fast implementation whenever available. The xml.etree.cElementTree module is deprecated.

Avertissement

The xml.etree.ElementTree module is not secure against maliciously constructed data. If you need to parse untrusted or unauthenticated data see Vulnérabilités XML.

20.5.1. Tutoriel

This is a short tutorial for using xml.etree.ElementTree (ET in short). The goal is to demonstrate some of the building blocks and basic concepts of the module.

20.5.1.1. XML tree and elements

XML is an inherently hierarchical data format, and the most natural way to represent it is with a tree. ET has two classes for this purpose - ElementTree represents the whole XML document as a tree, and Element represents a single node in this tree. Interactions with the whole document (reading and writing to/from files) are usually done on the ElementTree level. Interactions with a single XML element and its sub-elements are done on the Element level.

20.5.1.2. Parsing XML

We’ll be using the following XML document as the sample data for this section:

<?xml version="1.0"?>
<data>
    <country name="Liechtenstein">
        <rank>1</rank>
        <year>2008</year>
        <gdppc>141100</gdppc>
        <neighbor name="Austria" direction="E"/>
        <neighbor name="Switzerland" direction="W"/>
    </country>
    <country name="Singapore">
        <rank>4</rank>
        <year>2011</year>
        <gdppc>59900</gdppc>
        <neighbor name="Malaysia" direction="N"/>
    </country>
    <country name="Panama">
        <rank>68</rank>
        <year>2011</year>
        <gdppc>13600</gdppc>
        <neighbor name="Costa Rica" direction="W"/>
        <neighbor name="Colombia" direction="E"/>
    </country>
</data>

We can import this data by reading from a file:

import xml.etree.ElementTree as ET
tree = ET.parse('country_data.xml')
root = tree.getroot()

Or directly from a string:

root = ET.fromstring(country_data_as_string)

fromstring() parses XML from a string directly into an Element, which is the root element of the parsed tree. Other parsing functions may create an ElementTree. Check the documentation to be sure.

As an Element, root has a tag and a dictionary of attributes:

>>> root.tag
'data'
>>> root.attrib
{}

It also has children nodes over which we can iterate:

>>> for child in root:
...     print(child.tag, child.attrib)
...
country {'name': 'Liechtenstein'}
country {'name': 'Singapore'}
country {'name': 'Panama'}

Children are nested, and we can access specific child nodes by index:

>>> root[0][1].text
'2008'

Note

Not all elements of the XML input will end up as elements of the parsed tree. Currently, this module skips over any XML comments, processing instructions, and document type declarations in the input. Nevertheless, trees built using this module’s API rather than parsing from XML text can have comments and processing instructions in them; they will be included when generating XML output. A document type declaration may be accessed by passing a custom TreeBuilder instance to the XMLParser constructor.

20.5.1.3. Pull API for non-blocking parsing

Most parsing functions provided by this module require the whole document to be read at once before returning any result. It is possible to use an XMLParser and feed data into it incrementally, but it is a push API that calls methods on a callback target, which is too low-level and inconvenient for most needs. Sometimes what the user really wants is to be able to parse XML incrementally, without blocking operations, while enjoying the convenience of fully constructed Element objects.

The most powerful tool for doing this is XMLPullParser. It does not require a blocking read to obtain the XML data, and is instead fed with data incrementally with XMLPullParser.feed() calls. To get the parsed XML elements, call XMLPullParser.read_events(). Here is an example:

>>> parser = ET.XMLPullParser(['start', 'end'])
>>> parser.feed('<mytag>sometext')
>>> list(parser.read_events())
[('start', <Element 'mytag' at 0x7fa66db2be58>)]
>>> parser.feed(' more text</mytag>')
>>> for event, elem in parser.read_events():
...     print(event)
...     print(elem.tag, 'text=', elem.text)
...
end

The obvious use case is applications that operate in a non-blocking fashion where the XML data is being received from a socket or read incrementally from some storage device. In such cases, blocking reads are unacceptable.

Because it’s so flexible, XMLPullParser can be inconvenient to use for simpler use-cases. If you don’t mind your application blocking on reading XML data but would still like to have incremental parsing capabilities, take a look at iterparse(). It can be useful when you’re reading a large XML document and don’t want to hold it wholly in memory.

20.5.1.4. Finding interesting elements

Element has some useful methods that help iterate recursively over all the sub-tree below it (its children, their children, and so on). For example, Element.iter():

>>> for neighbor in root.iter('neighbor'):
...     print(neighbor.attrib)
...
{'name': 'Austria', 'direction': 'E'}
{'name': 'Switzerland', 'direction': 'W'}
{'name': 'Malaysia', 'direction': 'N'}
{'name': 'Costa Rica', 'direction': 'W'}
{'name': 'Colombia', 'direction': 'E'}

Element.findall() finds only elements with a tag which are direct children of the current element. Element.find() finds the first child with a particular tag, and Element.text accesses the element’s text content. Element.get() accesses the element’s attributes:

>>> for country in root.findall('country'):
...     rank = country.find('rank').text
...     name = country.get('name')
...     print(name, rank)
...
Liechtenstein 1
Singapore 4
Panama 68

More sophisticated specification of which elements to look for is possible by using XPath.

20.5.1.5. Modifying an XML File

ElementTree provides a simple way to build XML documents and write them to files. The ElementTree.write() method serves this purpose.

Once created, an Element object may be manipulated by directly changing its fields (such as Element.text), adding and modifying attributes (Element.set() method), as well as adding new children (for example with Element.append()).

Let’s say we want to add one to each country’s rank, and add an updated attribute to the rank element:

>>> for rank in root.iter('rank'):
...     new_rank = int(rank.text) + 1
...     rank.text = str(new_rank)
...     rank.set('updated', 'yes')
...
>>> tree.write('output.xml')

Our XML now looks like this:

<?xml version="1.0"?>
<data>
    <country name="Liechtenstein">
        <rank updated="yes">2</rank>
        <year>2008</year>
        <gdppc>141100</gdppc>
        <neighbor name="Austria" direction="E"/>
        <neighbor name="Switzerland" direction="W"/>
    </country>
    <country name="Singapore">
        <rank updated="yes">5</rank>
        <year>2011</year>
        <gdppc>59900</gdppc>
        <neighbor name="Malaysia" direction="N"/>
    </country>
    <country name="Panama">
        <rank updated="yes">69</rank>
        <year>2011</year>
        <gdppc>13600</gdppc>
        <neighbor name="Costa Rica" direction="W"/>
        <neighbor name="Colombia" direction="E"/>
    </country>
</data>

We can remove elements using Element.remove(). Let’s say we want to remove all countries with a rank higher than 50:

>>> for country in root.findall('country'):
...     rank = int(country.find('rank').text)
...     if rank > 50:
...         root.remove(country)
...
>>> tree.write('output.xml')

Our XML now looks like this:

<?xml version="1.0"?>
<data>
    <country name="Liechtenstein">
        <rank updated="yes">2</rank>
        <year>2008</year>
        <gdppc>141100</gdppc>
        <neighbor name="Austria" direction="E"/>
        <neighbor name="Switzerland" direction="W"/>
    </country>
    <country name="Singapore">
        <rank updated="yes">5</rank>
        <year>2011</year>
        <gdppc>59900</gdppc>
        <neighbor name="Malaysia" direction="N"/>
    </country>
</data>

20.5.1.6. Building XML documents

The SubElement() function also provides a convenient way to create new sub-elements for a given element:

>>> a = ET.Element('a')
>>> b = ET.SubElement(a, 'b')
>>> c = ET.SubElement(a, 'c')
>>> d = ET.SubElement(c, 'd')
>>> ET.dump(a)
<a><b /><c><d /></c></a>

20.5.1.7. Parsing XML with Namespaces

If the XML input has namespaces [https://en.wikipedia.org/wiki/XML_namespace], tags and attributes with prefixes in the form prefix:sometag get expanded to {uri}sometag where the prefix is replaced by the full URI. Also, if there is a default namespace [https://www.w3.org/TR/xml-names/#defaulting], that full URI gets prepended to all of the non-prefixed tags.

Here is an XML example that incorporates two namespaces, one with the prefix « fictional » and the other serving as the default namespace:

<?xml version="1.0"?>
<actors xmlns:fictional="http://characters.example.com"
        xmlns="http://people.example.com">
    <actor>
        <name>John Cleese</name>
        <fictional:character>Lancelot</fictional:character>
        <fictional:character>Archie Leach</fictional:character>
    </actor>
    <actor>
        <name>Eric Idle</name>
        <fictional:character>Sir Robin</fictional:character>
        <fictional:character>Gunther</fictional:character>
        <fictional:character>Commander Clement</fictional:character>
    </actor>
</actors>

One way to search and explore this XML example is to manually add the URI to every tag or attribute in the xpath of a find() or findall():

root = fromstring(xml_text)
for actor in root.findall('{http://people.example.com}actor'):
    name = actor.find('{http://people.example.com}name')
    print(name.text)
    for char in actor.findall('{http://characters.example.com}character'):
        print(' |-->', char.text)

A better way to search the namespaced XML example is to create a dictionary with your own prefixes and use those in the search functions:

ns = {'real_person': 'http://people.example.com',
      'role': 'http://characters.example.com'}

for actor in root.findall('real_person:actor', ns):
    name = actor.find('real_person:name', ns)
    print(name.text)
    for char in actor.findall('role:character', ns):
        print(' |-->', char.text)

These two approaches both output:

John Cleese
 |--> Lancelot
 |--> Archie Leach
Eric Idle
 |--> Sir Robin
 |--> Gunther
 |--> Commander Clement

20.5.1.8. Additional resources

See http://effbot.org/zone/element-index.htm for tutorials and links to other docs.

20.5.2. XPath support

This module provides limited support for XPath expressions [https://www.w3.org/TR/xpath] for locating elements in a tree. The goal is to support a small subset of the abbreviated syntax; a full XPath engine is outside the scope of the module.

20.5.2.1. Exemple

Here’s an example that demonstrates some of the XPath capabilities of the module. We’ll be using the countrydata XML document from the Parsing XML section:

import xml.etree.ElementTree as ET

root = ET.fromstring(countrydata)

# Top-level elements
root.findall(".")

# All 'neighbor' grand-children of 'country' children of the top-level
# elements
root.findall("./country/neighbor")

# Nodes with name='Singapore' that have a 'year' child
root.findall(".//year/..[@name='Singapore']")

# 'year' nodes that are children of nodes with name='Singapore'
root.findall(".//*[@name='Singapore']/year")

# All 'neighbor' nodes that are the second child of their parent
root.findall(".//neighbor[2]")

20.5.2.2. Supported XPath syntax

Syntaxe

Signification

tag

Selects all child elements with the given tag. For example, spam selects all child elements named spam, and spam/egg selects all grandchildren named egg in all children named spam.

*

Selects all child elements. For example, */egg selects all grandchildren named egg.

.

Selects the current node. This is mostly useful at the beginning of the path, to indicate that it’s a relative path.

//

Selects all subelements, on all levels beneath the current element. For example, .//egg selects all egg elements in the entire tree.

..

Selects the parent element. Returns None if the path attempts to reach the ancestors of the start element (the element find was called on).

[@attrib]

Selects all elements that have the given attribute.

[@attrib='value']

Selects all elements for which the given attribute has the given value. The value cannot contain quotes.

[tag]

Selects all elements that have a child named tag. Only immediate children are supported.

[tag='text']

Selects all elements that have a child named tag whose complete text content, including descendants, equals the given text.

[position]

Selects all elements that are located at the given position. The position can be either an integer (1 is the first position), the expression last() (for the last position), or a position relative to the last position (e.g. last()-1).

Predicates (expressions within square brackets) must be preceded by a tag name, an asterisk, or another predicate. position predicates must be preceded by a tag name.

20.5.3. Référence

20.5.3.1. Fonctions

xml.etree.ElementTree.Comment(text=None)

Comment element factory. This factory function creates a special element that will be serialized as an XML comment by the standard serializer. The comment string can be either a bytestring or a Unicode string. text is a string containing the comment string. Returns an element instance representing a comment.

Note that XMLParser skips over comments in the input instead of creating comment objects for them. An ElementTree will only contain comment nodes if they have been inserted into to the tree using one of the Element methods.

xml.etree.ElementTree.dump(elem)

Writes an element tree or element structure to sys.stdout. This function should be used for debugging only.

The exact output format is implementation dependent. In this version, it’s written as an ordinary XML file.

elem is an element tree or an individual element.

xml.etree.ElementTree.fromstring(text)

Parses an XML section from a string constant. Same as XML(). text is a string containing XML data. Returns an Element instance.

xml.etree.ElementTree.fromstringlist(sequence, parser=None)

Parses an XML document from a sequence of string fragments. sequence is a list or other sequence containing XML data fragments. parser is an optional parser instance. If not given, the standard XMLParser parser is used. Returns an Element instance.

Nouveau dans la version 3.2.

xml.etree.ElementTree.iselement(element)

Checks if an object appears to be a valid element object. element is an element instance. Returns a true value if this is an element object.

xml.etree.ElementTree.iterparse(source, events=None, parser=None)

Parses an XML section into an element tree incrementally, and reports what’s going on to the user. source is a filename or file object containing XML data. events is a sequence of events to report back. The supported events are the strings "start", "end", "start-ns" and "end-ns" (the « ns » events are used to get detailed namespace information). If events is omitted, only "end" events are reported. parser is an optional parser instance. If not given, the standard XMLParser parser is used. parser must be a subclass of XMLParser and can only use the default TreeBuilder as a target. Returns an iterator providing (event, elem) pairs.

Note that while iterparse() builds the tree incrementally, it issues blocking reads on source (or the file it names). As such, it’s unsuitable for applications where blocking reads can’t be made. For fully non-blocking parsing, see XMLPullParser.

Note

iterparse() only guarantees that it has seen the « > » character of a starting tag when it emits a « start » event, so the attributes are defined, but the contents of the text and tail attributes are undefined at that point. The same applies to the element children; they may or may not be present.

If you need a fully populated element, look for « end » events instead.

Obsolète depuis la version 3.4: The parser argument.

xml.etree.ElementTree.parse(source, parser=None)

Parses an XML section into an element tree. source is a filename or file object containing XML data. parser is an optional parser instance. If not given, the standard XMLParser parser is used. Returns an ElementTree instance.

xml.etree.ElementTree.ProcessingInstruction(target, text=None)

PI element factory. This factory function creates a special element that will be serialized as an XML processing instruction. target is a string containing the PI target. text is a string containing the PI contents, if given. Returns an element instance, representing a processing instruction.

Note that XMLParser skips over processing instructions in the input instead of creating comment objects for them. An ElementTree will only contain processing instruction nodes if they have been inserted into to the tree using one of the Element methods.

xml.etree.ElementTree.register_namespace(prefix, uri)

Registers a namespace prefix. The registry is global, and any existing mapping for either the given prefix or the namespace URI will be removed. prefix is a namespace prefix. uri is a namespace uri. Tags and attributes in this namespace will be serialized with the given prefix, if at all possible.

Nouveau dans la version 3.2.

xml.etree.ElementTree.SubElement(parent, tag, attrib={}, **extra)

Subelement factory. This function creates an element instance, and appends it to an existing element.

The element name, attribute names, and attribute values can be either bytestrings or Unicode strings. parent is the parent element. tag is the subelement name. attrib is an optional dictionary, containing element attributes. extra contains additional attributes, given as keyword arguments. Returns an element instance.

xml.etree.ElementTree.tostring(element, encoding="us-ascii", method="xml", *, short_empty_elements=True)

Generates a string representation of an XML element, including all subelements. element is an Element instance. encoding 1 is the output encoding (default is US-ASCII). Use encoding="unicode" to generate a Unicode string (otherwise, a bytestring is generated). method is either "xml", "html" or "text" (default is "xml"). short_empty_elements has the same meaning as in ElementTree.write(). Returns an (optionally) encoded string containing the XML data.

Nouveau dans la version 3.4: Le paramètre short_empty_elements.

xml.etree.ElementTree.tostringlist(element, encoding="us-ascii", method="xml", *, short_empty_elements=True)

Generates a string representation of an XML element, including all subelements. element is an Element instance. encoding 1 is the output encoding (default is US-ASCII). Use encoding="unicode" to generate a Unicode string (otherwise, a bytestring is generated). method is either "xml", "html" or "text" (default is "xml"). short_empty_elements has the same meaning as in ElementTree.write(). Returns a list of (optionally) encoded strings containing the XML data. It does not guarantee any specific sequence, except that b"".join(tostringlist(element)) == tostring(element).

Nouveau dans la version 3.2.

Nouveau dans la version 3.4: Le paramètre short_empty_elements.

xml.etree.ElementTree.XML(text, parser=None)

Parses an XML section from a string constant. This function can be used to embed « XML literals » in Python code. text is a string containing XML data. parser is an optional parser instance. If not given, the standard XMLParser parser is used. Returns an Element instance.

xml.etree.ElementTree.XMLID(text, parser=None)

Parses an XML section from a string constant, and also returns a dictionary which maps from element id:s to elements. text is a string containing XML data. parser is an optional parser instance. If not given, the standard XMLParser parser is used. Returns a tuple containing an Element instance and a dictionary.

20.5.3.2. Objets Elements

class xml.etree.ElementTree.Element(tag, attrib={}, **extra)

Element class. This class defines the Element interface, and provides a reference implementation of this interface.

The element name, attribute names, and attribute values can be either bytestrings or Unicode strings. tag is the element name. attrib is an optional dictionary, containing element attributes. extra contains additional attributes, given as keyword arguments.

tag

A string identifying what kind of data this element represents (the element type, in other words).

text

tail

These attributes can be used to hold additional data associated with the element. Their values are usually strings but may be any application-specific object. If the element is created from an XML file, the text attribute holds either the text between the element’s start tag and its first child or end tag, or None, and the tail attribute holds either the text between the element’s end tag and the next tag, or None. For the XML data

<a><b>1<c>2<d/>3</c></b>4</a>

the a element has None for both text and tail attributes, the b element has text "1" and tail "4", the c element has text "2" and tail None, and the d element has text None and tail "3".

To collect the inner text of an element, see itertext(), for example "".join(element.itertext()).

Applications may store arbitrary objects in these attributes.

attrib

A dictionary containing the element’s attributes. Note that while the attrib value is always a real mutable Python dictionary, an ElementTree implementation may choose to use another internal representation, and create the dictionary only if someone asks for it. To take advantage of such implementations, use the dictionary methods below whenever possible.

The following dictionary-like methods work on the element attributes.

clear()

Resets an element. This function removes all subelements, clears all attributes, and sets the text and tail attributes to None.

get(key, default=None)

Gets the element attribute named key.

Returns the attribute value, or default if the attribute was not found.

items()

Returns the element attributes as a sequence of (name, value) pairs. The attributes are returned in an arbitrary order.

keys()

Returns the elements attribute names as a list. The names are returned in an arbitrary order.

set(key, value)

Set the attribute key on the element to value.

The following methods work on the element’s children (subelements).

append(subelement)

Adds the element subelement to the end of this element’s internal list of subelements. Raises TypeError if subelement is not an Element.

extend(subelements)

Appends subelements from a sequence object with zero or more elements. Raises TypeError if a subelement is not an Element.

Nouveau dans la version 3.2.

find(match, namespaces=None)

Finds the first subelement matching match. match may be a tag name or a path. Returns an element instance or None. namespaces is an optional mapping from namespace prefix to full name.

findall(match, namespaces=None)

Finds all matching subelements, by tag name or path. Returns a list containing all matching elements in document order. namespaces is an optional mapping from namespace prefix to full name.

findtext(match, default=None, namespaces=None)

Finds text for the first subelement matching match. match may be a tag name or a path. Returns the text content of the first matching element, or default if no element was found. Note that if the matching element has no text content an empty string is returned. namespaces is an optional mapping from namespace prefix to full name.

getchildren()

Obsolète depuis la version 3.2: Use list(elem) or iteration.

getiterator(tag=None)

Obsolète depuis la version 3.2: Use method Element.iter() instead.

insert(index, subelement)

Inserts subelement at the given position in this element. Raises TypeError if subelement is not an Element.

iter(tag=None)

Creates a tree iterator with the current element as the root. The iterator iterates over this element and all elements below it, in document (depth first) order. If tag is not None or '*', only elements whose tag equals tag are returned from the iterator. If the tree structure is modified during iteration, the result is undefined.

Nouveau dans la version 3.2.

iterfind(match, namespaces=None)

Finds all matching subelements, by tag name or path. Returns an iterable yielding all matching elements in document order. namespaces is an optional mapping from namespace prefix to full name.

Nouveau dans la version 3.2.

itertext()

Creates a text iterator. The iterator loops over this element and all subelements, in document order, and returns all inner text.

Nouveau dans la version 3.2.

makeelement(tag, attrib)

Creates a new element object of the same type as this element. Do not call this method, use the SubElement() factory function instead.

remove(subelement)

Removes subelement from the element. Unlike the find* methods this method compares elements based on the instance identity, not on tag value or contents.

Element objects also support the following sequence type methods for working with subelements: __delitem__(), __getitem__(), __setitem__(), __len__().

Caution: Elements with no subelements will test as False. This behavior will change in future versions. Use specific len(elem) or elem is None test instead.

element = root.find('foo')

if not element:  # careful!
    print("element not found, or element has no subelements")

if element is None:
    print("element not found")

20.5.3.3. ElementTree Objects

class xml.etree.ElementTree.ElementTree(element=None, file=None)

ElementTree wrapper class. This class represents an entire element hierarchy, and adds some extra support for serialization to and from standard XML.

element is the root element. The tree is initialized with the contents of the XML file if given.

_setroot(element)

Replaces the root element for this tree. This discards the current contents of the tree, and replaces it with the given element. Use with care. element is an element instance.

find(match, namespaces=None)

Same as Element.find(), starting at the root of the tree.

findall(match, namespaces=None)

Same as Element.findall(), starting at the root of the tree.

findtext(match, default=None, namespaces=None)

Same as Element.findtext(), starting at the root of the tree.

getiterator(tag=None)

Obsolète depuis la version 3.2: Use method ElementTree.iter() instead.

getroot()

Returns the root element for this tree.

iter(tag=None)

Creates and returns a tree iterator for the root element. The iterator loops over all elements in this tree, in section order. tag is the tag to look for (default is to return all elements).

iterfind(match, namespaces=None)

Same as Element.iterfind(), starting at the root of the tree.

Nouveau dans la version 3.2.

parse(source, parser=None)

Loads an external XML section into this element tree. source is a file name or file object. parser is an optional parser instance. If not given, the standard XMLParser parser is used. Returns the section root element.

write(file, encoding="us-ascii", xml_declaration=None, default_namespace=None, method="xml", *, short_empty_elements=True)

Writes the element tree to a file, as XML. file is a file name, or a file object opened for writing. encoding 1 is the output encoding (default is US-ASCII). xml_declaration controls if an XML declaration should be added to the file. Use False for never, True for always, None for only if not US-ASCII or UTF-8 or Unicode (default is None). default_namespace sets the default XML namespace (for « xmlns »). method is either "xml", "html" or "text" (default is "xml"). The keyword-only short_empty_elements parameter controls the formatting of elements that contain no content. If True (the default), they are emitted as a single self-closed tag, otherwise they are emitted as a pair of start/end tags.

The output is either a string (str) or binary (bytes). This is controlled by the encoding argument. If encoding is "unicode", the output is a string; otherwise, it’s binary. Note that this may conflict with the type of file if it’s an open file object; make sure you do not try to write a string to a binary stream and vice versa.

Nouveau dans la version 3.4: Le paramètre short_empty_elements.

This is the XML file that is going to be manipulated:

<html>
    <head>
        <title>Example page</title>
    </head>
    <body>
        <p>Moved to <a href="http://example.org/">example.org</a>
        or <a href="http://example.com/">example.com</a>.</p>
    </body>
</html>

Example of changing the attribute « target » of every link in first paragraph:

>>> from xml.etree.ElementTree import ElementTree
>>> tree = ElementTree()
>>> tree.parse("index.xhtml")
<Element 'html' at 0xb77e6fac>
>>> p = tree.find("body/p")     # Finds first occurrence of tag p in body
>>> p
<Element 'p' at 0xb77ec26c>
>>> links = list(p.iter("a"))   # Returns list of all links
>>> links
[<Element 'a' at 0xb77ec2ac>, <Element 'a' at 0xb77ec1cc>]
>>> for i in links:             # Iterates through all found links
...     i.attrib["target"] = "blank"
>>> tree.write("output.xhtml")

20.5.3.4. QName Objects

class xml.etree.ElementTree.QName(text_or_uri, tag=None)

QName wrapper. This can be used to wrap a QName attribute value, in order to get proper namespace handling on output. text_or_uri is a string containing the QName value, in the form {uri}local, or, if the tag argument is given, the URI part of a QName. If tag is given, the first argument is interpreted as a URI, and this argument is interpreted as a local name. QName instances are opaque.

20.5.3.5. TreeBuilder Objects

class xml.etree.ElementTree.TreeBuilder(element_factory=None)

Generic element structure builder. This builder converts a sequence of start, data, and end method calls to a well-formed element structure. You can use this class to build an element structure using a custom XML parser, or a parser for some other XML-like format. element_factory, when given, must be a callable accepting two positional arguments: a tag and a dict of attributes. It is expected to return a new element instance.

close()

Flushes the builder buffers, and returns the toplevel document element. Returns an Element instance.

data(data)

Adds text to the current element. data is a string. This should be either a bytestring, or a Unicode string.

end(tag)

Closes the current element. tag is the element name. Returns the closed element.

start(tag, attrs)

Opens a new element. tag is the element name. attrs is a dictionary containing element attributes. Returns the opened element.

In addition, a custom TreeBuilder object can provide the following method:

doctype(name, pubid, system)

Handles a doctype declaration. name is the doctype name. pubid is the public identifier. system is the system identifier. This method does not exist on the default TreeBuilder class.

Nouveau dans la version 3.2.

20.5.3.6. XMLParser Objects

class xml.etree.ElementTree.XMLParser(html=0, target=None, encoding=None)

This class is the low-level building block of the module. It uses xml.parsers.expat for efficient, event-based parsing of XML. It can be fed XML data incrementally with the feed() method, and parsing events are translated to a push API - by invoking callbacks on the target object. If target is omitted, the standard TreeBuilder is used. The html argument was historically used for backwards compatibility and is now deprecated. If encoding 1 is given, the value overrides the encoding specified in the XML file.

Obsolète depuis la version 3.4: The html argument. The remaining arguments should be passed via keyword to prepare for the removal of the html argument.

close()

Finishes feeding data to the parser. Returns the result of calling the close() method of the target passed during construction; by default, this is the toplevel document element.

doctype(name, pubid, system)

Obsolète depuis la version 3.2: Define the TreeBuilder.doctype() method on a custom TreeBuilder target.

feed(data)

Feeds data to the parser. data is encoded data.

XMLParser.feed() calls target’s start(tag, attrs_dict) method for each opening tag, its end(tag) method for each closing tag, and data is processed by method data(data). XMLParser.close() calls target’s method close(). XMLParser can be used not only for building a tree structure. This is an example of counting the maximum depth of an XML file:

>>> from xml.etree.ElementTree import XMLParser
>>> class MaxDepth:                     # The target object of the parser
...     maxDepth = 0
...     depth = 0
...     def start(self, tag, attrib):   # Called for each opening tag.
...         self.depth += 1
...         if self.depth > self.maxDepth:
...             self.maxDepth = self.depth
...     def end(self, tag):             # Called for each closing tag.
...         self.depth -= 1
...     def data(self, data):
...         pass            # We do not need to do anything with data.
...     def close(self):    # Called when all data has been parsed.
...         return self.maxDepth
...
>>> target = MaxDepth()
>>> parser = XMLParser(target=target)
>>> exampleXml = """
... <a>
...   <b>
...   </b>
...   <b>
...     <c>
...       <d>
...       </d>
...     </c>
...   </b>
... </a>"""
>>> parser.feed(exampleXml)
>>> parser.close()
4

20.5.3.7. XMLPullParser Objects

class xml.etree.ElementTree.XMLPullParser(events=None)

A pull parser suitable for non-blocking applications. Its input-side API is similar to that of XMLParser, but instead of pushing calls to a callback target, XMLPullParser collects an internal list of parsing events and lets the user read from it. events is a sequence of events to report back. The supported events are the strings "start", "end", "start-ns" and "end-ns" (the « ns » events are used to get detailed namespace information). If events is omitted, only "end" events are reported.

feed(data)

Feed the given bytes data to the parser.

close()

Signal the parser that the data stream is terminated. Unlike XMLParser.close(), this method always returns None. Any events not yet retrieved when the parser is closed can still be read with read_events().

read_events()

Return an iterator over the events which have been encountered in the data fed to the parser. The iterator yields (event, elem) pairs, where event is a string representing the type of event (e.g. "end") and elem is the encountered Element object.

Events provided in a previous call to read_events() will not be yielded again. Events are consumed from the internal queue only when they are retrieved from the iterator, so multiple readers iterating in parallel over iterators obtained from read_events() will have unpredictable results.

Note

XMLPullParser only guarantees that it has seen the « > » character of a starting tag when it emits a « start » event, so the attributes are defined, but the contents of the text and tail attributes are undefined at that point. The same applies to the element children; they may or may not be present.

If you need a fully populated element, look for « end » events instead.

Nouveau dans la version 3.4.

20.5.3.8. Exceptions

class xml.etree.ElementTree.ParseError

XML parse error, raised by the various parsing methods in this module when parsing fails. The string representation of an instance of this exception will contain a user-friendly error message. In addition, it will have the following attributes available:

code

A numeric error code from the expat parser. See the documentation of xml.parsers.expat for the list of error codes and their meanings.

position

A tuple of line, column numbers, specifying where the error occurred.

Notes

1(1,2,3,4)

The encoding string included in XML output should conform to the appropriate standards. For example, « UTF-8 » is valid, but « UTF8 » is not. See https://www.w3.org/TR/2006/REC-xml11-20060816/#NT-EncodingDecl and https://www.iana.org/assignments/character-sets/character-sets.xhtml.

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20.6. xml.dom — L’API Document Object Model

Code source: Lib/xml/dom/__init__.py [https://github.com/python/cpython/tree/3.6/Lib/xml/dom/__init__.py]

Le Document Object Model, ou « DOM, » est une API inter-langage du World Wide Web Consortium (W3C) pour accéder et modifier les documents XML. Une implémentation DOM présente le document XML comme un arbre ou autorise le code client à construire une telle structure depuis zéro. Il permet alors d’accéder à la structure à l’aide d’un ensemble d’objet qui fournissent des interfaces bien connues.

Le DOM est extrêmement utile pour les applications à accès aléatoire. SAX ne vous permet de visualiser qu’un seul morceau du document à la fois. Si vous regardez un élément SAX, vous n’avez pas accès à un autre. Si vous regardez un nœud de texte, vous n’avez pas accès à un élément parent. Lorsque vous écrivez une application SAX, vous devez suivre la position de votre programme dans le document quelque part dans votre propre code. SAX ne le fait pas pour vous. De plus, si vous devez examiner un nœud plus lus loin dans le document XML, vous n’avez pas de chance.

Il est tout simplement impossible d’implémenter certains algorithmes avec un modèle évènementiel, sans un accès à un arbre. Bien sûr, vous pourriez construire vous même un arbre à partir des événements SAX mais DOM vous permet d’éviter d’écrire ce code. Le DOM est représentation standard en arbre pour des données XML.

Le DOM (Document Object Model) est défini par le W3C en étapes ou « levels » (niveaux) selon leur terminologie. Le couplage de l’API de Python est essentiellement basée sur la recommandation DOM Level 2.

Typiquement, les applications DOM commencent par analyser du XML dans du DOM. Comment cela doit être exposé n’est absolument pas décrit par DOM Level 1 et Level 2 ne fournit que des améliorations limités. Il existe une classe DOMImplementation qui fournit un accès à des méthodes de création de Document mais il n’y a pas de moyen d’accéder à un lecteur/analyseur/constructeur de document de façon indépendante de l’implémentation. Il n’est pas également très bien définis comment accéder à ces méthodes sans un objet Document. En Python, chaque implémentation fournira une fonction getDOMImplementation() . DOM Level 3 ajoute une spécification Load/Store (charge/stocke) qui définie une interface pour le lecteur mais qui n’est pas disponible dans la bibliothèque standard de Python.

Une fois que vous avez un objet document DOM, vous pouvez accéder aux parties de votre document XML à travers ses méthodes et propriétés. Ces propriétés sont définis dans les spécifications DOM ; cette portion du manuel de références décrit l’interprétation des ces spécifications en Python.

Les spécifications fournies par le W3C définissent les API DOM pour Java, ECMAScript, et OMG IDL. Les correspondances de Python définies ici sont basées pour une grande part sur la version IDL de la spécification mais une conformité stricte n’est pas requise (bien que ces implémentations soient libre d’implémenter le support strict des correspondances de IDL). Voir la section Conformité pour une discussion détaillée des pré-requis des correspondances.

Voir aussi

Spécification Level 2 Document Object Model (DOM) [https://www.w3.org/TR/DOM-Level-2-Core/]

La recommandation W3C sur laquelle l’API DOM de Python est basée.

Spécification Level 1 Document Object Model (DOM) [https://www.w3.org/TR/REC-DOM-Level-1/]

La recommandation du W3C pour le DOM supporté par xml.dom.minidom.

Python Language Mapping Specification [http://www.omg.org/spec/PYTH/1.2/PDF]

Ceci spécifies les correspondances depuis OMG IDL vers Python.

20.6.1. Contenu du module

Le xml.dom contient les fonctions suivantes :

xml.dom.registerDOMImplementation(name, factory)

Enregistre la fonction factory avec le nom name. La fonction factory doit renvoyer un objet qui implémente l’interface de DOMImplementation. La fonction factory peut renvoyer le même objet à chaque fois ou un nouveau à chaque appel en accord avec les spécificités de l’implémentation (Par exemple si l’implémentation supporte certaines personnalisations).

xml.dom.getDOMImplementation(name=None, features=())

Renvoie une implémentation DOM appropriée. Le name est soit connu, soit le nom du module d’une implémentation DOM, soit None. Si ce n’est pas None, le module correspondant est importé et retourne un objet DOMImplementation si l’importation réussit. Si Aucun name n’est donné et que la variable d’environnement PYTHON_DOM est positionnée, cette variable est utilisée pour trouver l’implémentation.

Si name n’est pas donné, la fonction examine les implémentations disponibles pour en trouver une avec l’ensemble des fonctionnalités requises. Si aucune implémentation n’est trouvée, une ImportError est levée. La liste de fonctionnalité doit être une séquence de paires (feature, version) qui est passée à la méthode hasFeature() disponible dans les objets DOMImplementation.

Quelques constantes pratiques sont également fournies :

xml.dom.EMPTY_NAMESPACE

La valeur utilisée pour indiquer qu’aucun espace de noms n’est associé à un nœud dans le DOM. Typiquement, ceci est trouvé comme namespaceURI dans un nœud ou utilisé comme le paramètre namespaceURI dans une méthode spécifique aux espaces de noms.

xml.dom.XML_NAMESPACE

L’URI de l’espace de noms associé avec le préfixe réservé xml comme défini par Namespaces in XML [https://www.w3.org/TR/REC-xml-names/] (section 4).

xml.dom.XMLNS_NAMESPACE

L’URI de l’espace de noms pour la déclaration des espaces de noms, tel que défini par Document Object Model (DOM) Level 2 Core Specification [https://www.w3.org/TR/DOM-Level-2-Core/core.html] (section 1.1.8).

xml.dom.XHTML_NAMESPACE

L’URI de l’espace de noms XHTML tel que défini par XHTML 1.0: The Extensible HyperText Markup Language [https://www.w3.org/TR/xhtml1/] (section 3.1.1).

Par ailleurs, xml.dom contient une classe de base Node et les exceptions de DOM. La classe Node fournie par ce module n’implémente aucune des méthodes ou des attributs définis par les spécifications DOM ; les implémentations concrètes des DOM doivent fournir les informations suivantes. La classe Node fournie part ce modules fournit les constantes utilisées pour l’attribut nodeType pour des objets concrets Node ; ils sont situés dans les classes plutôt qu’au niveau du module en accord avec les spécifications DOM.

20.6.2. Objets dans le DOM

La documentation finale pour le DOM est la spécification DOM du W3C.

Notez que les attributs DOM peuvent également être manipulés comme des nœuds au lieu de simples chaînes. Il est relativement rare que vous ayez besoin de faire cela, cependant, cet usage n’est pas encore documenté.

Interface

Section

Objectif

DOMImplementation

Objets DOMImplementation

Interface de l’implémentation sous-jacente.

Node

Objets nœuds

Interface de base pour la majorité des objets dans un document.

NodeList

Objet NodeList

Interface pour une séquence de nœuds.

DocumentType

Objets DocumnentType

Informations sur les déclarations nécessaires au traitement d’un document.

Document

Objets Document

Objet représentant un document entier.

Element

Objets Elements

Nœuds éléments dans la hiérarchie d’un document.

Attr

Objets Attr

Valeur des nœuds attributs sur dans des nœuds éléments.

Comment

Objets Comment

Représentation des commentaires dans le fichier source du document.

Text

Objets Text et CDATASection

Nœud contenant un contenu texte du document.

ProcessingInstruction

Objets ProcessingInstruction

Représentation des Processing Instructions.

Une Section additionnelle décrit les exceptions définis pour travailler avec le DOM en Python.

20.6.2.1. Objets DOMImplementation

L’interface DOMImplementation fournit un moyen pour les applications de déterminer la disponibilité de fonctionnalités particulières dans le DOM qu’elles utilisent. DOM Level 2 ajoute la capacité de créer des nouveaux objets Document et DocumentType utilisant également DOMImplementation.

DOMImplementation.hasFeature(feature, version)

Renvoie vrai si la fonctionnalité identifiée par une paire de chaîne feature et version est implémentée.

DOMImplementation.createDocument(namespaceUri, qualifiedName, doctype)

Renvoie un nouvel objet Document (la racine du DOM), avec un objet fils Element ayant les namespaceUri et qualifiedName passés en paramètre. Le doctype doit être un objet DocumentType créé par createDocumentType() ou None. Dans l’API DOM de Python, les deux premiers arguments peuvent également être à None de manière à indiquer qu’aucun enfant Element ne soit crée.

DOMImplementation.createDocumentType(qualifiedName, publicId, systemId)

Renvoie un nouvel objet DocumentType qui encapsule les chaînes qualifiedName, publicId, et systemId passées en paramètre représentant les informations contenues dans dans la déclaration du document XML.

20.6.2.2. Objets nœuds

Tous les composants d’un document XML sont des sous-classes de Node.

Node.nodeType

Un entier représentant le type de nœud. Pour l’objet Node, les constantes symboliques pour les types sont ELEMENT_NODE, ATTRIBUTE_NODE, TEXT_NODE, CDATA_SECTION_NODE, ENTITY_NODE, PROCESSING_INSTRUCTION_NODE, COMMENT_NODE, DOCUMENT_NODE, DOCUMENT_TYPE_NODE, NOTATION_NODE. Ceci est un attribut en lecture seule.

Node.parentNode

Le parent du nœud courant ou None dans le cas du nœud document. La valeur est toujours un objet Node ou None. Pour les nœuds Element, ce sera le parent de l’élément sauf si l’élément est la racine, dans ce cas ce sera l’objet Document. Pour les nœuds Attr, cela sera toujours None. Ceci est un attribut en lecture seule.

Node.attributes

Un objet NamedNodeMap d’objet attributs. Seulement les éléments ayant des valeurs seront listés, les autres renverront None pour cet attribut. Cet attribut est en lecture seule.

Node.previousSibling

Le nœud avec le même parent qui précède immédiatement le nœud courant. Par exemple, l’élément avec la balise fermente qui est juste avant la balise ouvrante de l’élément self. Naturellement, les documents XML sont fait de plus que juste des éléments ; donc le previous sibling peut être du texte, un commentaire ou autre chose. Si le nœud courant est le premier fils du parent, cet attribut vaudra None. Cet attribut est en lecture seule.

Node.nextSibling

Le nœud qui suit immédiatement le nœud courant dans le même parent. Voir également previousSibling. Si ce nœud est le dernier de son parent, alors l’attribut sera None. Cet attribut est en lecture seule.

Node.childNodes

Une liste de nœuds contenu dans le nœud courant. Cet attribut est en lecture seule.

Node.firstChild

S’il y a des fils, premier fils du nœud courant, sinon None. Cet attribut est en lecture seule.

Node.lastChild

S’il y a des fils, le dernier nœud fils du nœud courant. Sinon None. Cet attribut est en lecture seule.

Node.localName

S’il y a un :, contient la partie suivante de tagName ce : sinon la valeur complète de tagName. Cette valeur est une chaîne.

Node.prefix

La partie de tagName précédent le : s’il y en a un. sinon une chaîne vide. La valeur est une chaîne ou None.

Node.namespaceURI

L’espace de noms associé (namespace en anglais) au nom de l’élément. Cette valeur est une chaîne ou None. Cet attribut est en lecture seule.

Node.nodeName

L’attribut a un sens différent pour chaque type de nœud ; se reporter à la spécification DOM pour les détails. Vous obtiendrez toujours l’information que vous obtiendrez à l’aide d’une autre propriété comme tagName pour les éléments ou name pour les attributs. Pour tous les types de nœuds, la valeur sera soit une chaîne soit None. Cet attribut est en lecture seule.

Node.nodeValue

L’attribut a un sens différent pour chaque type de nœud ; se reporter à la spécification DOM pour les détails. La situation est similaire à nodeName. La valeur est une chaîne ou None.

Node.hasAttributes()

Renvoi vrai si le nœud a des attributs.

Node.hasChildNodes()

Renvoi vrai si le nœud a des nœuds fils.

Node.isSameNode(other)

Renvoi vrai si other fait référence au même nœud que le nœud courant. Ceci est particulièrement pratique pour implémentation de DOM qui utilise une architecture proxy (car plus d’un objet peut se référer au même nœud).

Note

Ceci est basé sur l’API proposé par * DOM Level 3* qui est toujours à l’étape « working draft » mais cette interface particulière ne parait pas controversée. Les changement du W3C n’affecteront pas nécessairement cette méthode dans l’interface DOM de Python. (bien que toute nouvelle API W3C à cet effet soit également supportée).

Node.appendChild(newChild)

Ajoute un nouveau nœud fils à ce nœud à la fin de la liste des fils renvoyant newChild. Si ce nœud est déjà dans l’arbre, il sera d’abord retiré.

Node.insertBefore(newChild, refChild)

Insère un nouveau nœud fils avant un fils existant. Il est impératif que refChild soit un fils du nœud, sinon ValueError sera levée. newChild est renvoyé. Si refChild est None, newChild est inséré à la fin de la liste des fils.

Node.removeChild(oldChild)

Retire un nœud fils. oldChild doit être un fils de ce nœud ; sinon ValueError sera levée. En cas de succès, oldChild est renvoyé. Si oldChild n’est plus utilisé, sa méthode unlink() doit être appelée.

Node.replaceChild(newChild, oldChild)

Remplace un nœud existant avec un nouveau. oldChild doit être un fils de ce nœud ; sinon ValueError sera levée.

Node.normalize()

Jointe les nœuds texte adjacents de manière à ce que tous les segments de texte soient stockés dans une seule instance de Text. Ceci simplifie le traitement du texte d’un arbre DOM pour de nombreuses applications.

Node.cloneNode(deep)

Clone ce nœud. Positionner deep signifie que tous les nœuds fils seront également clonés. La méthode renvoi le clone.

20.6.2.3. Objet NodeList

NodeList représente une séquence de nœuds. Ces objets sont utilisés de deux manières dans la recommandation Dom Core : un objet Element fournit en fournis liste des nœud fils et les méthodes getElementsByTagName() et getElementsByTagNameNS() de Node renvoient des objet avec cette interface pour représenter les résultats des requêtes.

La recommandation DOM Level 2 définit un attribut et une méthode pour ces objets :

NodeList.item(i)

Renvoie le i*ème élément de la séquence s’il existe ou ``None``. L’index *i ne peut pas être inférieur à 0 ou supérieur ou égale à la longueur de la séquence.

NodeList.length

Le nombre d’éléments dans la séquence.

En plus, l’interface DOM de Python requiert quelques ajouts supplémentaires pour permettre que les objet NodeList puissent être utilisés comme des séquences Python. Toutes les implémentations de NodeList doivent inclure le support de __len__() et de __getitem__() ; ceci permet l’itération sur NodeList avec l’instruction for et un support de la fonction native len().

Si une implémentation de DOM support les modifications du document, l’implémentation de NodeList doit également supporter les méthodes __setitem__() et __delitem__() .

20.6.2.4. Objets DocumnentType

Les objets de type DocumentType fournissent des informations sur les notations et les entités déclarées par un document (incluant les données externes si l’analyseur les utilise et peut les fournir). Le DocumentType d’un Document est accessible via l’attribut doctype. Si le document ne déclare pas de DOCTYPE, l’attribut doctype vaudra None plutôt qu’une instance de cette interface.

DocumentType est une spécialisation de Node et ajoute les attributs suivants :

DocumentType.publicId

L’identifiant publique pour un sous ensemble de la définition type de document (DTD). Cela sera une chaîne ou None.

DocumentType.systemId

L’identifiant système pour un sous ensemble du document de définition type (DTD). Cela sera une URI sous la forme d’une chaîne ou None.

DocumentType.internalSubset

Un chaîne donnant le sous ensemble complet du document. Ceci n’inclut pas les chevrons qui englobe le sous ensemble. Si le document n’a pas de sous ensemble, cela devrait être None.

DocumentType.name

Le nom de l’élément racine donné dans la déclaration DOCTYPE si présente.

DocumentType.entities

Ceci est un NamedNodeMap donnant les définitions des entités externes. Pour les entités définies plusieurs fois seule la première définition est fournie (les suivantes sont ignorées comme requis par la recommandation XML). Ceci peut retourner None si l’information n’est pas fournie à l’analyseur ou si aucune entités n’est définis.

DocumentType.notations

Ceci est un NamedNodeMap donnant la définition des notations. Pour les notations définies plus d’une fois, seule la première est fournie (les suivante sont ignorées comme requis par la recommandation XML). Ceci peut retourner None si l’information n’est pas fournie à l’analyseur ou si aucune entités n’est définis.

20.6.2.5. Objets Document

Un Document représente un document XML en son entier, incluant les éléments qui le constitue, les attributs, les processing instructions, commentaires, etc. Rappelez vous qu’il hérite des propriété de Node.

Document.documentElement

Le seul et unique élément racine du document.

Document.createElement(tagName)

Créé et renvoi un nouveau nœud élément. Ce n’est pas inséré dans le document quand il est créé. Vous avez besoin de l’insérer explicitement avec l’une des autres méthodes comme insertBefore() ou appendChild().

Document.createElementNS(namespaceURI, tagName)

Créé et renvoi un nouvel élément avec un namespace. Le tagName peut avoir un préfixe. L’élément ne sera pas insérer dans le document quand il est créé. Vous avez besoin de l’insérer explicitement avec l’une des autres méthodes comme insertBefore() ou appendChild().

Document.createTextNode(data)

Créé et renvoi un nœud texte contenant les data passées en paramètre. Comme pour les autres méthodes de création, la méthode n’insère pas le nœud dans l’arbre.

Document.createComment(data)

Créé et renvoi un nœud commentaire contenant les data passé en commentaire. Comme pour les autres méthodes de création, la méthode n’insère pas le nœud dans l’arbre.

Document.createProcessingInstruction(target, data)

Créé et retourne un nœud processing instruction contenant les target et data passés en paramètres. Comme pour les autres méthodes de création, la méthode n’insère pas le nœud dans l’arbre.

Document.createAttribute(name)

Créé et renvoi un nœud attribut. Cette méthode n’associe le nœud attribut aucun nœud en particulier. Vous devez utiliser la méthode setAttributeNode() sur un objet Element approprié pour utiliser une instance d’attribut nouvellement créé.

Document.createAttributeNS(namespaceURI, qualifiedName)

Créé et renvoi un nœud attribut avec un namespace. Le tagName peut avoir un préfixe. Cette méthode n’associe le nœud attribut à aucun nœud en particulier. Vous devez utiliser la méthode setAttributeNode() sur un objet Element approprié pour utiliser une instance d’attribut nouvellement créé.

Document.getElementsByTagName(tagName)

Cherche tout les descendants (fils directs, fils de fils, etc.) avec un nom de balise particulier.

Document.getElementsByTagNameNS(namespaceURI, localName)

Cherche tous les descendants (fils directs, fils de fils, etc.) avec un namespace URI particulier et un localName. Le localName fait parti du namespace après le préfixe.

20.6.2.6. Objets Elements

Element est une une sous classe de Node et donc hérite de tout les éléments de cette classe.

Element.tagName

Le nom de l’élément type. Dans un document utilisant des namespace, il pourrait y avoir des : dedans. La valeur est une chaîne.

Element.getElementsByTagName(tagName)

Identique à la méthode équivalente de la classe Document.

Element.getElementsByTagNameNS(namespaceURI, localName)

Identique à la méthode équivalente de la classe Document.

Element.hasAttribute(name)

Renvoi vrai si l’élément a un attribut nommé name.

Element.hasAttributeNS(namespaceURI, localName)

Renvoi vrai si l’élément a un nommé par namespaceURI et localName.

Element.getAttribute(name)

Retourne la valeur de l’attribut nommé par name comme une chaîne. Si un tel attribue n’existe pas, une chaîne vide est retournée comme si l’attribut n’avait aucune valeur.

Element.getAttributeNode(attrname)

Retourne le nœud Attr pour l’attribut nommé par attrname.

Element.getAttributeNS(namespaceURI, localName)

Renvoi la valeur de l’attribut nommé par namespaceURI et localName comme une chaîne. Si un tel attribue n’existe pas, une chaîne vide est retournée comme si l’attribut n’avait aucune valeur.

Element.getAttributeNodeNS(namespaceURI, localName)

Renvoi la valeur de l’attribue comme un nœud étant donné namespaceURI et localName.

Element.removeAttribute(name)

Retire un attribut nommé name. S’il n’y a aucun attribut correspondant une NotFoundErr est levée.

Element.removeAttributeNode(oldAttr)

Supprime et renvoi oldAttr de la liste des attributs si présent. Si oldAttr n’est pas présent, NotFoundErr est levée.

Element.removeAttributeNS(namespaceURI, localName)

Retire un attribut selon son nom. Notez qu’il utilise un localName et nom un qname. Aucune exception n’est levée s’il n’y a pas d’attribut correspondant.

Element.setAttribute(name, value)

Assigne la valeur à un attribut pour la chaîne.

Element.setAttributeNode(newAttr)

Ajoute un nouveau nœud attribut à l’élément, remplaçant un attribut existant si nécessaire si name corresponds à un attribut. Si l’attribut en remplace un précédent, l’ancien attribut sera retourné. Si newAttr est déjà utilisé, InuseAttributeErr sera levée.

Element.setAttributeNodeNS(newAttr)

Ajoute un nouveau nœud attribut, remplaçant un attribut existant si namespaceURI et localName corresponds à un attribut. S’il y a remplacement, l’ancien nœud sera renvoyé. Si newAttr est déjà utilisé, InuseAttributeErr sera levée.

Element.setAttributeNS(namespaceURI, qname, value)

Assigne la valeur d’un attribut depuis une chaîne étant donnée un namespaceURI et un qname. Notez que qname est le nom de l’attribut en entier. Ceci est différent d’au dessus.

20.6.2.7. Objets Attr

Attr hérite Node et donc hérite de tout ces attributs.

Attr.name

Le nom de l’attribut. Dans un document utilisant des namespaces, il pourra inclure un :.

Attr.localName

La partie du nom suivant le : s’il y en a un ou le nom entier sinon. Ceci est un attribut en lecture seule.

Attr.prefix

La partie du nom précédent le : s’il y en a un ou une chaîne vide.

Attr.value

La valeur texte de l’attribut. C’est un synonyme de l’attribut nodeValue.

20.6.2.8. Objets NameNodeMap

NamedNodeMap n’hérite pas de Node.

NamedNodeMap.length

La longueur de la liste d’attributs.

NamedNodeMap.item(index)

Renvoi un attribut à un index particulier. L’ordre des attribut est arbitraire mais sera constant durant toute la vie du DOM. Chacun des item sera un nœud attribut. Obtenez sa valeur avec value de l’attribut.

Il y existe également des méthodes expérimentales qui donne à cette classe un comportement plus mappable. Vous pouvez les utiliser ou utiliser la famille de méthode standardisés getAttribute*() des objets Element.

20.6.2.9. Objets Comment

Comment représente un commentaire dans le document XML. C’est une sous classe Node mais n’a aucune nœuds fils.

Comment.data

Le contenu du commentaire comme une chaîne. L’attribut contient tous les caractères entre <!-- et --> mais ne les inclues pas.

20.6.2.10. Objets Text et CDATASection

L’interface Text représente le texte dans un document XML. Si l’analyseur et l’implémentation DOM supporte les extensions XML du DOM, les portion de texte encapsulées dans des section marquées CDATA seront stockées dans des objets CDATASection. Ces deux interfaces sont identiques mais fournissent des valeurs différentes pour l’attribut nodeType.

Ces interfaces étendent l’interface Node. Elles ne peuvent pas avoir de nœuds fils.

Text.data

Le contenu du nœud texte comme une chaîne.

Note

L’utilisation d’un nœud CDATASection n’indique pas que le nœud représente une section complète marquée CDATA, seulement que le contenu du nœud est le contenu d’une section CDATA. Une seule section CDATA peut représenter plus d’un nœud dans l’arbre du document. Il n’y a aucun moyen de déterminer si deux nœuds CDATASection adjacents représentent différentes sections CDATA.

20.6.2.11. Objets ProcessingInstruction

Représente une processing instruction dans un document XML. Hérite de l’interface Node et ne peut avoir aucun nœud fils.

ProcessingInstruction.target

Le contenu de la processing instruction jusqu’au premier caractère blanc. Cet attribut est en lecture seule.

ProcessingInstruction.data

Le contenu de la processing instruction après le premier caractère blanc.

20.6.2.12. Exceptions

La recommandation DOM Level 2 définie une seule exception DOMException et un nombre de constantes qui permettent aux applications à déterminer quelle type d’erreur s’est produit. Les instances de DOMException ont un attribut code qui fourni une valeur approprié pour une exception spécifique.

L’interface DOM de Python fournit des constant mais également étends un ensemble d’exception pour qu’il existe une exception spécifique pour chaque code d’exception défini par le DOM. L’implémentation doit lever l’exception spécifique appropriée. Chacune ayant la valeur appropriée pour l’attribut code.

exception xml.dom.DOMException

Exception de base utilisée pour toutes les exceptions spécifiques du DOM. Cette classe ne peut pas être instanciée directement.

exception xml.dom.DomstringSizeErr

Levée quand un intervalle spécifique de texte ne rentre pas dans une chaîne. Cette exception n’est pas réputée être utilisée par les implémentations DOM de Python mais elle peur être levée par des implémentations de DOM qui ne sont pas écrite en Python.

exception xml.dom.HierarchyRequestErr

Levée quand l’insertion d’un nœud est tentée dans un type de nœud incompatible.

exception xml.dom.IndexSizeErr

Levée quand un index ou la taille d’un paramètre d’une méthode est négatif ou excède les valeurs autorisées.

exception xml.dom.InuseAttributeErr

Levée quand l’insertion d’un nœud Attr est tenté alors que ce nœud est déjà présent ailleurs dans le document.

exception xml.dom.InvalidAccessErr

Levée si un paramètre ou une opération n’est pas supporté par l’objet sous-jacent.

exception xml.dom.InvalidCharacterErr

Cette exception est levée quand un paramètre chaîne contient un caractère qui n’est pas autorisé dans le contexte utilisé par la recommandation XML 1.0. Par exemple, lors la tentative de création d’un nœud Element avec un espace dans le nom de l’élément.

exception xml.dom.InvalidModificationErr

Levée lors de la tentative de modifier le type de nœud.

exception xml.dom.InvalidStateErr

Levée quand une tentative est faite d’utiliser un objet non défini ou qui ne sont plus utilisables.

exception xml.dom.NamespaceErr

Si une tentative est faite de changer un objet d’une manière qui n’est pas autorisée selon la recommandation Namespaces in XML [https://www.w3.org/TR/REC-xml-names/] , cette exception est levée.

exception xml.dom.NotFoundErr

Exception quand un nœud n’existe pas dans le contexte référencé. Par exemple, NamedNodeMap.removeNamedItem() lèvera cette exception si le nœud passé n’appartient pas à la séquence.

exception xml.dom.NotSupportedErr

Levée si l’implémentation ne supporte pas le type d’objet requis ou l’opération.

exception xml.dom.NoDataAllowedErr

Levée si la donnée spécifiée pour un nœud n’est pas supportée.

exception xml.dom.NoModificationAllowedErr

Levée lors de la tentative de modification sur objet où les modifications ne sont pas autorisées (tels que les nœuds en lecture seule).

exception xml.dom.SyntaxErr

Levée quand une chaîne invalide ou illégale est spécifiée.

exception xml.dom.WrongDocumentErr

Levée quand un nœud est inséré dans un document différent de celui auquel il appartient et que l’implémentation ne supporte pas la migration d’un document à un autre.

Les codes d’exceptions définis par la recommandation DOM avec leurs correspondances décrites si dessous selon ce tableau :

Constante

Exception

DOMSTRING_SIZE_ERR

DomstringSizeErr

HIERARCHY_REQUEST_ERR

HierarchyRequestErr

INDEX_SIZE_ERR

IndexSizeErr

INUSE_ATTRIBUTE_ERR

InuseAttributeErr

INVALID_ACCESS_ERR

InvalidAccessErr

INVALID_CHARACTER_ERR

InvalidCharacterErr

INVALID_MODIFICATION_ERR

InvalidModificationErr

INVALID_STATE_ERR

InvalidStateErr

NAMESPACE_ERR

NamespaceErr

NOT_FOUND_ERR

NotFoundErr

NOT_SUPPORTED_ERR

NotSupportedErr

NO_DATA_ALLOWED_ERR

NoDataAllowedErr

NO_MODIFICATION_ALLOWED_ERR

NoModificationAllowedErr

SYNTAX_ERR

SyntaxErr

WRONG_DOCUMENT_ERR

WrongDocumentErr

20.6.3. Conformité

Cette section décrit la conformité des pré requis et des relations entre l’API DOM de Python, les recommandations W3C DOM et les correspondances OMG IDL pour Python.

20.6.3.1. Correspondance des types

Les types IDL utilisés dans la spécification DOM correspondent aux types Python selon le tableau suivant.

Type IDL

Type Python

boolean

bool ou int

int

int

long int

int

unsigned int

int

DOMString

str or bytes

null

None

20.6.3.2. Méthodes d’accès

Les correspondance de OMG IDL vers Python définissent des fonction d’accès pour les déclarations attribut d’IDL à la manière dont Java le fait. Correspondance des déclarations IDL

readonly attribute string someValue;
         attribute string anotherValue;

Donne trois fonctions d’accès : une méthode get pour someValue (_get_someValue()) et des méthodes get et set pour anotherValue (_get_anotherValue() et _set_anotherValue()). Le mapping, en particulier, ne requiert pas que les attributs IDL soient accessible comme des attributs Python normaux : object.someValue n’est pas requis de fonctionner et peut lever une AttributeError.

Cependant, l’API DOM de Python impose que les accès par attributs classiques fonctionnent. Par conséquent, les substituts générés par le compilateur IDL de Python ne fonctionneront probablement pas, et des objets façade pourraient être nécessaires côté client si les objets DOM sont manipulés via CORBA. Bien qu’utiliser un client DOM CORBA nécessite une bonne réflexion, les développeurs habitués et expérimentés à l’utilisation de CORBA ne considèrent pas que c’est un problème. Les attributs déclarés readonly pourraient ne pas voir leur accès en écriture restreint dans toutes les implémentations du DOM.

Dans l’API DOM de Python, les fonctions d’accès ne sont pas requises. Si elles sont fournies, elles doivent prendre la forme définie par le mapping de Python IDL, mais ces méthodes sont considérées inutiles car les attributs sont directement accessible depuis Python. Les fonctions d’accès « Set » ne devraient jamais être fournies pour les attributs readonly (en lecture seule).

Les définitions IDL n’embarquent pas entièrement les pré-requis de l’API de DOM API telle que la notion de objets ou que la valeur de retour de getElementsByTagName() est dynamique. L’API DOM de Python ne requiert pas des implémentations d’avoir de tel pré-requis.

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20.7. xml.dom.minidom — Minimal DOM implementation

Source code: Lib/xml/dom/minidom.py [https://github.com/python/cpython/tree/3.6/Lib/xml/dom/minidom.py]

xml.dom.minidom is a minimal implementation of the Document Object Model interface, with an API similar to that in other languages. It is intended to be simpler than the full DOM and also significantly smaller. Users who are not already proficient with the DOM should consider using the xml.etree.ElementTree module for their XML processing instead.

Avertissement

The xml.dom.minidom module is not secure against maliciously constructed data. If you need to parse untrusted or unauthenticated data see Vulnérabilités XML.

DOM applications typically start by parsing some XML into a DOM. With xml.dom.minidom, this is done through the parse functions:

from xml.dom.minidom import parse, parseString

dom1 = parse('c:\\temp\\mydata.xml')  # parse an XML file by name

datasource = open('c:\\temp\\mydata.xml')
dom2 = parse(datasource)  # parse an open file

dom3 = parseString('<myxml>Some data<empty/> some more data</myxml>')

The parse() function can take either a filename or an open file object.

xml.dom.minidom.parse(filename_or_file, parser=None, bufsize=None)

Return a Document from the given input. filename_or_file may be either a file name, or a file-like object. parser, if given, must be a SAX2 parser object. This function will change the document handler of the parser and activate namespace support; other parser configuration (like setting an entity resolver) must have been done in advance.

If you have XML in a string, you can use the parseString() function instead:

xml.dom.minidom.parseString(string, parser=None)

Return a Document that represents the string. This method creates an io.StringIO object for the string and passes that on to parse().

Both functions return a Document object representing the content of the document.

What the parse() and parseString() functions do is connect an XML parser with a « DOM builder » that can accept parse events from any SAX parser and convert them into a DOM tree. The name of the functions are perhaps misleading, but are easy to grasp when learning the interfaces. The parsing of the document will be completed before these functions return; it’s simply that these functions do not provide a parser implementation themselves.

You can also create a Document by calling a method on a « DOM Implementation » object. You can get this object either by calling the getDOMImplementation() function in the xml.dom package or the xml.dom.minidom module. Once you have a Document, you can add child nodes to it to populate the DOM:

from xml.dom.minidom import getDOMImplementation

impl = getDOMImplementation()

newdoc = impl.createDocument(None, "some_tag", None)
top_element = newdoc.documentElement
text = newdoc.createTextNode('Some textual content.')
top_element.appendChild(text)

Once you have a DOM document object, you can access the parts of your XML document through its properties and methods. These properties are defined in the DOM specification. The main property of the document object is the documentElement property. It gives you the main element in the XML document: the one that holds all others. Here is an example program:

dom3 = parseString("<myxml>Some data</myxml>")
assert dom3.documentElement.tagName == "myxml"

When you are finished with a DOM tree, you may optionally call the unlink() method to encourage early cleanup of the now-unneeded objects. unlink() is an xml.dom.minidom-specific extension to the DOM API that renders the node and its descendants are essentially useless. Otherwise, Python’s garbage collector will eventually take care of the objects in the tree.

Voir aussi

Spécification Level 1 Document Object Model (DOM) [https://www.w3.org/TR/REC-DOM-Level-1/]

La recommandation du W3C pour le DOM supporté par xml.dom.minidom.

20.7.1. DOM Objects

The definition of the DOM API for Python is given as part of the xml.dom module documentation. This section lists the differences between the API and xml.dom.minidom.

Node.unlink()

Break internal references within the DOM so that it will be garbage collected on versions of Python without cyclic GC. Even when cyclic GC is available, using this can make large amounts of memory available sooner, so calling this on DOM objects as soon as they are no longer needed is good practice. This only needs to be called on the Document object, but may be called on child nodes to discard children of that node.

You can avoid calling this method explicitly by using the with statement. The following code will automatically unlink dom when the with block is exited:

with xml.dom.minidom.parse(datasource) as dom:
    ... # Work with dom.

Node.writexml(writer, indent="", addindent="", newl="")

Write XML to the writer object. The writer should have a write() method which matches that of the file object interface. The indent parameter is the indentation of the current node. The addindent parameter is the incremental indentation to use for subnodes of the current one. The newl parameter specifies the string to use to terminate newlines.

For the Document node, an additional keyword argument encoding can be used to specify the encoding field of the XML header.

Node.toxml(encoding=None)

Return a string or byte string containing the XML represented by the DOM node.

With an explicit encoding 1 argument, the result is a byte string in the specified encoding. With no encoding argument, the result is a Unicode string, and the XML declaration in the resulting string does not specify an encoding. Encoding this string in an encoding other than UTF-8 is likely incorrect, since UTF-8 is the default encoding of XML.

Node.toprettyxml(indent="\t", newl="\n", encoding=None)

Return a pretty-printed version of the document. indent specifies the indentation string and defaults to a tabulator; newl specifies the string emitted at the end of each line and defaults to \n.

The encoding argument behaves like the corresponding argument of toxml().

20.7.2. DOM Example

This example program is a fairly realistic example of a simple program. In this particular case, we do not take much advantage of the flexibility of the DOM.

import xml.dom.minidom

document = """\
<slideshow>
<title>Demo slideshow</title>
<slide><title>Slide title</title>
<point>This is a demo</point>
<point>Of a program for processing slides</point>
</slide>

<slide><title>Another demo slide</title>
<point>It is important</point>
<point>To have more than</point>
<point>one slide</point>
</slide>
</slideshow>
"""

dom = xml.dom.minidom.parseString(document)

def getText(nodelist):
    rc = []
    for node in nodelist:
        if node.nodeType == node.TEXT_NODE:
            rc.append(node.data)
    return ''.join(rc)

def handleSlideshow(slideshow):
    print("<html>")
    handleSlideshowTitle(slideshow.getElementsByTagName("title")[0])
    slides = slideshow.getElementsByTagName("slide")
    handleToc(slides)
    handleSlides(slides)
    print("</html>")

def handleSlides(slides):
    for slide in slides:
        handleSlide(slide)

def handleSlide(slide):
    handleSlideTitle(slide.getElementsByTagName("title")[0])
    handlePoints(slide.getElementsByTagName("point"))

def handleSlideshowTitle(title):
    print("<title>%s</title>" % getText(title.childNodes))

def handleSlideTitle(title):
    print("<h2>%s</h2>" % getText(title.childNodes))

def handlePoints(points):
    print("<ul>")
    for point in points:
        handlePoint(point)
    print("</ul>")

def handlePoint(point):
    print("<li>%s</li>" % getText(point.childNodes))

def handleToc(slides):
    for slide in slides:
        title = slide.getElementsByTagName("title")[0]
        print("<p>%s</p>" % getText(title.childNodes))

handleSlideshow(dom)

20.7.3. minidom and the DOM standard

The xml.dom.minidom module is essentially a DOM 1.0-compatible DOM with some DOM 2 features (primarily namespace features).

Usage of the DOM interface in Python is straight-forward. The following mapping rules apply:

Interfaces are accessed through instance objects. Applications should not instantiate the classes themselves; they should use the creator functions available on the Document object. Derived interfaces support all operations (and attributes) from the base interfaces, plus any new operations.

Operations are used as methods. Since the DOM uses only in parameters, the arguments are passed in normal order (from left to right). There are no optional arguments. void operations return None.

IDL attributes map to instance attributes. For compatibility with the OMG IDL language mapping for Python, an attribute foo can also be accessed through accessor methods _get_foo() and _set_foo(). readonly attributes must not be changed; this is not enforced at runtime.

The types short int, unsigned int, unsigned long long, and boolean all map to Python integer objects.

The type DOMString maps to Python strings. xml.dom.minidom supports either bytes or strings, but will normally produce strings. Values of type DOMString may also be None where allowed to have the IDL null value by the DOM specification from the W3C.

const declarations map to variables in their respective scope (e.g. xml.dom.minidom.Node.PROCESSING_INSTRUCTION_NODE); they must not be changed.

DOMException is currently not supported in xml.dom.minidom. Instead, xml.dom.minidom uses standard Python exceptions such as TypeError and AttributeError.

NodeList objects are implemented using Python’s built-in list type. These objects provide the interface defined in the DOM specification, but with earlier versions of Python they do not support the official API. They are, however, much more « Pythonic » than the interface defined in the W3C recommendations.

The following interfaces have no implementation in xml.dom.minidom:

DOMTimeStamp

DocumentType

DOMImplementation

CharacterData

CDATASection

Notation

Entity

EntityReference

DocumentFragment

Most of these reflect information in the XML document that is not of general utility to most DOM users.

Notes

1

The encoding name included in the XML output should conform to the appropriate standards. For example, « UTF-8 » is valid, but « UTF8 » is not valid in an XML document’s declaration, even though Python accepts it as an encoding name. See https://www.w3.org/TR/2006/REC-xml11-20060816/#NT-EncodingDecl and https://www.iana.org/assignments/character-sets/character-sets.xhtml.

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20.8. xml.dom.pulldom — Support for building partial DOM trees

Source code: Lib/xml/dom/pulldom.py [https://github.com/python/cpython/tree/3.6/Lib/xml/dom/pulldom.py]

The xml.dom.pulldom module provides a « pull parser » which can also be asked to produce DOM-accessible fragments of the document where necessary. The basic concept involves pulling « events » from a stream of incoming XML and processing them. In contrast to SAX which also employs an event-driven processing model together with callbacks, the user of a pull parser is responsible for explicitly pulling events from the stream, looping over those events until either processing is finished or an error condition occurs.

Avertissement

The xml.dom.pulldom module is not secure against maliciously constructed data. If you need to parse untrusted or unauthenticated data see Vulnérabilités XML.

Modifié dans la version 3.6.7: The SAX parser no longer processes general external entities by default to increase security by default. To enable processing of external entities, pass a custom parser instance in:

from xml.dom.pulldom import parse
from xml.sax import make_parser
from xml.sax.handler import feature_external_ges

parser = make_parser()
parser.setFeature(feature_external_ges, True)
parse(filename, parser=parser)

Exemple :

from xml.dom import pulldom

doc = pulldom.parse('sales_items.xml')
for event, node in doc:
    if event == pulldom.START_ELEMENT and node.tagName == 'item':
        if int(node.getAttribute('price')) > 50:
            doc.expandNode(node)
            print(node.toxml())

event is a constant and can be one of:

START_ELEMENT

END_ELEMENT

COMMENT

START_DOCUMENT

END_DOCUMENT

CHARACTERS

PROCESSING_INSTRUCTION

IGNORABLE_WHITESPACE

node is an object of type xml.dom.minidom.Document, xml.dom.minidom.Element or xml.dom.minidom.Text.

Since the document is treated as a « flat » stream of events, the document « tree » is implicitly traversed and the desired elements are found regardless of their depth in the tree. In other words, one does not need to consider hierarchical issues such as recursive searching of the document nodes, although if the context of elements were important, one would either need to maintain some context-related state (i.e. remembering where one is in the document at any given point) or to make use of the DOMEventStream.expandNode() method and switch to DOM-related processing.

class xml.dom.pulldom.PullDom(documentFactory=None)

Subclass of xml.sax.handler.ContentHandler.

class xml.dom.pulldom.SAX2DOM(documentFactory=None)

Subclass of xml.sax.handler.ContentHandler.

xml.dom.pulldom.parse(stream_or_string, parser=None, bufsize=None)

Return a DOMEventStream from the given input. stream_or_string may be either a file name, or a file-like object. parser, if given, must be an XMLReader object. This function will change the document handler of the parser and activate namespace support; other parser configuration (like setting an entity resolver) must have been done in advance.

If you have XML in a string, you can use the parseString() function instead:

xml.dom.pulldom.parseString(string, parser=None)

Return a DOMEventStream that represents the (Unicode) string.

xml.dom.pulldom.default_bufsize

Default value for the bufsize parameter to parse().

The value of this variable can be changed before calling parse() and the new value will take effect.

20.8.1. DOMEventStream Objects

class xml.dom.pulldom.DOMEventStream(stream, parser, bufsize)

getEvent()

Return a tuple containing event and the current node as xml.dom.minidom.Document if event equals START_DOCUMENT, xml.dom.minidom.Element if event equals START_ELEMENT or END_ELEMENT or xml.dom.minidom.Text if event equals CHARACTERS. The current node does not contain information about its children, unless expandNode() is called.

expandNode(node)

Expands all children of node into node. Example:

from xml.dom import pulldom

xml = '<html><title>Foo</title> <p>Some text <div>and more</div></p> </html>'
doc = pulldom.parseString(xml)
for event, node in doc:
    if event == pulldom.START_ELEMENT and node.tagName == 'p':
        # Following statement only prints '<p/>'
        print(node.toxml())
        doc.expandNode(node)
        # Following statement prints node with all its children '<p>Some text <div>and more</div></p>'
        print(node.toxml())

reset()

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20.9. xml.sax — Prise en charge des analyseurs SAX2

Code source : Lib/xml/sax/__init__.py [https://github.com/python/cpython/tree/3.6/Lib/xml/sax/__init__.py]

Le paquet xml.sax fournit des modules qui implémentent l’interface Simple API for XML (SAX) pour Python. Le paquet en lui même fournit les exceptions SAX et les fonctions les plus utiles qui seront le plus utilisées par les utilisateurs de SAX API.

Avertissement

Le module xml.sax n’est pas sécurisé contre les données construites de façon malveillante. Si vous avez besoin d’analyser des données non sécurisées ou non authentifiées, voir Vulnérabilités XML.

Modifié dans la version 3.6.7: The SAX parser no longer processes general external entities by default to increase security. Before, the parser created network connections to fetch remote files or loaded local files from the file system for DTD and entities. The feature can be enabled again with method setFeature() on the parser object and argument feature_external_ges.

Les fonctions les plus utiles sont:

xml.sax.make_parser(parser_list=[])

Create and return a SAX XMLReader object. The first parser found will be used. If parser_list is provided, it must be a list of strings which name modules that have a function named create_parser(). Modules listed in parser_list will be used before modules in the default list of parsers.

xml.sax.parse(filename_or_stream, handler, error_handler=handler.ErrorHandler())

Crée un analyseur SAX et l’utilise pour analyser un document. Le document transmis comme filename_or_stream, peut être un nom de fichier ou un objet fichier. Le paramètre handler doit être une instance SAX ContentHandler. Si un error_handler est donné, il doit être un SAX ErrorHandler ; si omis, SAXParseException sera levé sur toutes les erreurs. Il n’y a pas de valeur de retour, tout le travail doit être fait par le handler transmis.

xml.sax.parseString(string, handler, error_handler=handler.ErrorHandler())

Similaire à parse(), mais qui analyse à partir d’un espace mémoire string reçu en tant que paramètre. string doit être une instance str ou un objet bytes-like object.

Modifié dans la version 3.5: Ajout du support des instances str.

Une application SAX typique utilise trois types d’objets: les readers, les handlers et les sources d’entrée. « Reader » dans ce contexte est un autre terme pour le analyseur, c’est-à-dire un morceau de code qui lit les octets ou les caractères de la source d’entrée et qui produit une séquence d’événements. Les événements sont ensuite distribués aux objets du handler, c’est-à-dire que le lecteur appelle une méthode sur le handler. L’application doit donc obtenir un objet reader, créer ou ouvrir les sources d’entrée, créer les handlers et connecter ces objets tous ensemble. La dernière étape de la préparation, le reader est appelé à analyser l’entrée. Pendant l’analyse, les méthodes sur les objets du handler sont appelées en fonction d’événements structurels et syntaxiques à partir des données d’entrée.

Pour ces objets, seules les interfaces sont pertinentes; elles ne sont pas normalement instanciées par l’application elle-même. Puisque Python n’a pas de notion explicite d’interface, elles sont formellement introduites en tant que classes, mais les applications peuvent utiliser des implémentations qui n’héritent pas des classes fournies. Les interfaces InputSource, Locator, Attributes, AttributesNS, et XMLReader sont définies dans le module xml.sax.xmlreader. Les interfaces du handler sont définies dans xml.sax.handler. Pour plus de commodité, xml.sax.xmlreader.InputSource (qui est souvent instancié directement) et les classes du handler sont également disponibles à partir de xml.sax. Ces interfaces sont décrites ci-dessous.

En plus de ces classes, xml.sax fournit les classes d’exceptions suivantes.

exception xml.sax.SAXException(msg, exception=None)

Encapsule une erreur ou un avertissement XML. Cette classe peut contenir une erreur de base ou une information d’avertissement soit du analyseur XML ou de l’application: elle peut être sous-classée pour fournir des fonctionnalités supplémentaires ou pour ajouter une localisation. Noter que même si les handlers définis dans l’interface ErrorHandler reçoivent des instances de cette exception, ce n’est pas nécessaire de lever l’exception — il est également utile en tant que conteneur pour l’information.

Quand instancié, msg devrait être une description lisible par l’homme de l’erreur. Le paramètre optionnel exception, s’il est donné, devrait être None ou une exception qui a été interceptée par le code d’analyse et qui est transmise comme information.

Ceci est la classe de base pour les autres classes d’exception SAX.

exception xml.sax.SAXParseException(msg, exception, locator)

Sous-classe de SAXException élevée sur les erreurs d’analyse. Les instances de cette classe sont passées aux méthodes de l’interface SAX ErrorHandler pour fournir des informations sur l’erreur d’analyse. Cette classe supporte aussi l’interface SAX Locator comme l’interface SAXException.

exception xml.sax.SAXNotRecognizedException(msg, exception=None)

Sous-classe de SAXException levée quand un SAX XMLReader est confronté à une caractéristique ou à une propriété non reconnue. Les applications et les extensions SAX peuvent utiliser cette classe à des fins similaires.

exception xml.sax.SAXNotSupportedException(msg, exception=None)

Sous-classe de SAXException levée quand un SAX XMLReader est demandé pour activer une fonctionnalité qui n’est pas supportée, ou pour définir une propriété à une valeur que l’implémentation ne prend pas en charge. Les applications et les extensions SAX peuvent utiliser cette classe à des fins similaires.

Voir aussi

SAX: L’API simple pour XML [http://www.saxproject.org/]

Ce site est le point focal pour la définition de l’API SAX. Il offre une implémentation Java et une documentation en ligne. Des liens pour l’implémentation et des informations historiques sont également disponibles.

Module xml.sax.handler

Définitions des interfaces pour les objets fournis par l’application.

Module xml.sax.saxutils

Fonctions pratiques pour une utilisation dans les applications SAX.

Module xml.sax.xmlreader

Définitions des interfaces pour les objets fournis par l’analyseur.

20.9.1. Les objets SAXException

La classe d’exception SAXException supporte les méthodes suivantes :

SAXException.getMessage()

Renvoyer un message lisible par l’homme décrivant la condition d’erreur.

SAXException.getException()

Renvoie un objet d’exception encapsulé, ou``None``.

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20.10. xml.sax.handler — Base classes for SAX handlers

Source code: Lib/xml/sax/handler.py [https://github.com/python/cpython/tree/3.6/Lib/xml/sax/handler.py]

The SAX API defines four kinds of handlers: content handlers, DTD handlers, error handlers, and entity resolvers. Applications normally only need to implement those interfaces whose events they are interested in; they can implement the interfaces in a single object or in multiple objects. Handler implementations should inherit from the base classes provided in the module xml.sax.handler, so that all methods get default implementations.

class xml.sax.handler.ContentHandler

This is the main callback interface in SAX, and the one most important to applications. The order of events in this interface mirrors the order of the information in the document.

class xml.sax.handler.DTDHandler

Handle DTD events.

This interface specifies only those DTD events required for basic parsing (unparsed entities and attributes).

class xml.sax.handler.EntityResolver

Basic interface for resolving entities. If you create an object implementing this interface, then register the object with your Parser, the parser will call the method in your object to resolve all external entities.

class xml.sax.handler.ErrorHandler

Interface used by the parser to present error and warning messages to the application. The methods of this object control whether errors are immediately converted to exceptions or are handled in some other way.

In addition to these classes, xml.sax.handler provides symbolic constants for the feature and property names.

xml.sax.handler.feature_namespaces

value: "http://xml.org/sax/features/namespaces"

true: Perform Namespace processing.

false: Optionally do not perform Namespace processing (implies namespace-prefixes; default).

access: (parsing) read-only; (not parsing) read/write

xml.sax.handler.feature_namespace_prefixes

value: "http://xml.org/sax/features/namespace-prefixes"

true: Report the original prefixed names and attributes used for Namespace declarations.

false: Do not report attributes used for Namespace declarations, and optionally do not report original prefixed names (default).

access: (parsing) read-only; (not parsing) read/write

xml.sax.handler.feature_string_interning

value: "http://xml.org/sax/features/string-interning"

true: All element names, prefixes, attribute names, Namespace URIs, and local names are interned using the built-in intern function.

false: Names are not necessarily interned, although they may be (default).

access: (parsing) read-only; (not parsing) read/write

xml.sax.handler.feature_validation

value: "http://xml.org/sax/features/validation"

true: Report all validation errors (implies external-general-entities and external-parameter-entities).

false: Do not report validation errors.

access: (parsing) read-only; (not parsing) read/write

xml.sax.handler.feature_external_ges

value: "http://xml.org/sax/features/external-general-entities"

true: Include all external general (text) entities.

false: Do not include external general entities.

access: (parsing) read-only; (not parsing) read/write

xml.sax.handler.feature_external_pes

value: "http://xml.org/sax/features/external-parameter-entities"

true: Include all external parameter entities, including the external DTD subset.

false: Do not include any external parameter entities, even the external DTD subset.

access: (parsing) read-only; (not parsing) read/write

xml.sax.handler.all_features

List of all features.

xml.sax.handler.property_lexical_handler

value: "http://xml.org/sax/properties/lexical-handler"

data type: xml.sax.sax2lib.LexicalHandler (not supported in Python 2)

description: An optional extension handler for lexical events like comments.

access: read/write

xml.sax.handler.property_declaration_handler

value: "http://xml.org/sax/properties/declaration-handler"

data type: xml.sax.sax2lib.DeclHandler (not supported in Python 2)

description: An optional extension handler for DTD-related events other than notations and unparsed entities.

access: read/write

xml.sax.handler.property_dom_node

value: "http://xml.org/sax/properties/dom-node"

data type: org.w3c.dom.Node (not supported in Python 2)

description: When parsing, the current DOM node being visited if this is a DOM iterator; when not parsing, the root DOM node for iteration.

access: (parsing) read-only; (not parsing) read/write

xml.sax.handler.property_xml_string

value: "http://xml.org/sax/properties/xml-string"

data type: String

description: The literal string of characters that was the source for the current event.

access: read-only

xml.sax.handler.all_properties

List of all known property names.

20.10.1. ContentHandler Objects

Users are expected to subclass ContentHandler to support their application. The following methods are called by the parser on the appropriate events in the input document:

ContentHandler.setDocumentLocator(locator)

Called by the parser to give the application a locator for locating the origin of document events.

SAX parsers are strongly encouraged (though not absolutely required) to supply a locator: if it does so, it must supply the locator to the application by invoking this method before invoking any of the other methods in the DocumentHandler interface.

The locator allows the application to determine the end position of any document-related event, even if the parser is not reporting an error. Typically, the application will use this information for reporting its own errors (such as character content that does not match an application’s business rules). The information returned by the locator is probably not sufficient for use with a search engine.

Note that the locator will return correct information only during the invocation of the events in this interface. The application should not attempt to use it at any other time.

ContentHandler.startDocument()

Receive notification of the beginning of a document.

The SAX parser will invoke this method only once, before any other methods in this interface or in DTDHandler (except for setDocumentLocator()).

ContentHandler.endDocument()

Receive notification of the end of a document.

The SAX parser will invoke this method only once, and it will be the last method invoked during the parse. The parser shall not invoke this method until it has either abandoned parsing (because of an unrecoverable error) or reached the end of input.

ContentHandler.startPrefixMapping(prefix, uri)

Begin the scope of a prefix-URI Namespace mapping.

The information from this event is not necessary for normal Namespace processing: the SAX XML reader will automatically replace prefixes for element and attribute names when the feature_namespaces feature is enabled (the default).

There are cases, however, when applications need to use prefixes in character data or in attribute values, where they cannot safely be expanded automatically; the startPrefixMapping() and endPrefixMapping() events supply the information to the application to expand prefixes in those contexts itself, if necessary.

Note that startPrefixMapping() and endPrefixMapping() events are not guaranteed to be properly nested relative to each-other: all startPrefixMapping() events will occur before the corresponding startElement() event, and all endPrefixMapping() events will occur after the corresponding endElement() event, but their order is not guaranteed.

ContentHandler.endPrefixMapping(prefix)

End the scope of a prefix-URI mapping.

See startPrefixMapping() for details. This event will always occur after the corresponding endElement() event, but the order of endPrefixMapping() events is not otherwise guaranteed.

ContentHandler.startElement(name, attrs)

Signals the start of an element in non-namespace mode.

The name parameter contains the raw XML 1.0 name of the element type as a string and the attrs parameter holds an object of the Attributes interface (see The Attributes Interface) containing the attributes of the element. The object passed as attrs may be re-used by the parser; holding on to a reference to it is not a reliable way to keep a copy of the attributes. To keep a copy of the attributes, use the copy() method of the attrs object.

ContentHandler.endElement(name)

Signals the end of an element in non-namespace mode.

The name parameter contains the name of the element type, just as with the startElement() event.

ContentHandler.startElementNS(name, qname, attrs)

Signals the start of an element in namespace mode.

The name parameter contains the name of the element type as a (uri, localname) tuple, the qname parameter contains the raw XML 1.0 name used in the source document, and the attrs parameter holds an instance of the AttributesNS interface (see The AttributesNS Interface) containing the attributes of the element. If no namespace is associated with the element, the uri component of name will be None. The object passed as attrs may be re-used by the parser; holding on to a reference to it is not a reliable way to keep a copy of the attributes. To keep a copy of the attributes, use the copy() method of the attrs object.

Parsers may set the qname parameter to None, unless the feature_namespace_prefixes feature is activated.

ContentHandler.endElementNS(name, qname)

Signals the end of an element in namespace mode.

The name parameter contains the name of the element type, just as with the startElementNS() method, likewise the qname parameter.

ContentHandler.characters(content)

Receive notification of character data.

The Parser will call this method to report each chunk of character data. SAX parsers may return all contiguous character data in a single chunk, or they may split it into several chunks; however, all of the characters in any single event must come from the same external entity so that the Locator provides useful information.

content may be a string or bytes instance; the expat reader module always produces strings.

Note

The earlier SAX 1 interface provided by the Python XML Special Interest Group used a more Java-like interface for this method. Since most parsers used from Python did not take advantage of the older interface, the simpler signature was chosen to replace it. To convert old code to the new interface, use content instead of slicing content with the old offset and length parameters.

ContentHandler.ignorableWhitespace(whitespace)

Receive notification of ignorable whitespace in element content.

Validating Parsers must use this method to report each chunk of ignorable whitespace (see the W3C XML 1.0 recommendation, section 2.10): non-validating parsers may also use this method if they are capable of parsing and using content models.

SAX parsers may return all contiguous whitespace in a single chunk, or they may split it into several chunks; however, all of the characters in any single event must come from the same external entity, so that the Locator provides useful information.

ContentHandler.processingInstruction(target, data)

Receive notification of a processing instruction.

The Parser will invoke this method once for each processing instruction found: note that processing instructions may occur before or after the main document element.

A SAX parser should never report an XML declaration (XML 1.0, section 2.8) or a text declaration (XML 1.0, section 4.3.1) using this method.

ContentHandler.skippedEntity(name)

Receive notification of a skipped entity.

The Parser will invoke this method once for each entity skipped. Non-validating processors may skip entities if they have not seen the declarations (because, for example, the entity was declared in an external DTD subset). All processors may skip external entities, depending on the values of the feature_external_ges and the feature_external_pes properties.

20.10.2. DTDHandler Objects

DTDHandler instances provide the following methods:

DTDHandler.notationDecl(name, publicId, systemId)

Handle a notation declaration event.

DTDHandler.unparsedEntityDecl(name, publicId, systemId, ndata)

Handle an unparsed entity declaration event.

20.10.3. EntityResolver Objects

EntityResolver.resolveEntity(publicId, systemId)

Resolve the system identifier of an entity and return either the system identifier to read from as a string, or an InputSource to read from. The default implementation returns systemId.

20.10.4. ErrorHandler Objects

Objects with this interface are used to receive error and warning information from the XMLReader. If you create an object that implements this interface, then register the object with your XMLReader, the parser will call the methods in your object to report all warnings and errors. There are three levels of errors available: warnings, (possibly) recoverable errors, and unrecoverable errors. All methods take a SAXParseException as the only parameter. Errors and warnings may be converted to an exception by raising the passed-in exception object.

ErrorHandler.error(exception)

Called when the parser encounters a recoverable error. If this method does not raise an exception, parsing may continue, but further document information should not be expected by the application. Allowing the parser to continue may allow additional errors to be discovered in the input document.

ErrorHandler.fatalError(exception)

Called when the parser encounters an error it cannot recover from; parsing is expected to terminate when this method returns.

ErrorHandler.warning(exception)

Called when the parser presents minor warning information to the application. Parsing is expected to continue when this method returns, and document information will continue to be passed to the application. Raising an exception in this method will cause parsing to end.

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20.11. xml.sax.saxutils — Utilitaires SAX

Code source : Lib/xml/sax/saxutils.py [https://github.com/python/cpython/tree/3.6/Lib/xml/sax/saxutils.py]

Le module xml.sax.saxutils contient des classes et fonctions qui sont fréquemment utiles en créant des applications SAX, soit en utilisation directe, soit en classes de base.

xml.sax.saxutils.escape(data, entities={})

Échappe '&', '<', et '>' dans une chaine de caractères de données.

Vous pouvez échapper d’autres chaines de caractères de données en passant un dictionnaire au paramètre optionnel entities. Les clés et valeurs doivent toutes être des chaines de caractères ; chaque clé sera remplacée par sa valeur correspondante. Les caractères '&', '<' et '>' sont toujours échappés même si entities est donné en paramètre.

xml.sax.saxutils.unescape(data, entities={})

Parse '&amp;', '&lt;', et '&gt;' dans une chaine de caractères de données.

Vous pouvez dé-échapper d’autres chaines de caractères de données en passant un dictionnaire au paramètre optionnel entities. Les clés et valeurs doivent toutes être des chaines de caractères ; chaque clé sera remplacée par sa valeur correspondante. Les caractères '&', '<' et '>' sont toujours dé-échappés même si entities est donné en paramètre.

xml.sax.saxutils.quoteattr(data, entities={})

Similaire à escape(), mais prépare aussi data pour être utilisé comme une valeur d’attribut. La valeur renvoyée est une version entre guillemets de data avec tous les remplacements supplémentaires nécessaires. quoteattr() va sélectionner un caractère guillemet basé sur le contenu de data, en essayant d’éviter d’encoder tous les caractères guillemets dans la chaine de caractères. Si les caractères guillemet simple et guillemets sont déjà dans data, les caractères guillemets simples seront encodés et data sera entouré de guillemets. La chaine de caractères résultante pourra être utilisée en tant que valeur d’attribut :

>>> print("<element attr=%s>" % quoteattr("ab ' cd \" ef"))
<element attr="ab ' cd &quot; ef">

Cette fonction est utile quand vous générez des valeurs d’attributs pour du HTML ou n’importe quel SGML en utilisant la syntaxe concrète de référence.

class xml.sax.saxutils.XMLGenerator(out=None, encoding='iso-8859-1', short_empty_elements=False)

Cette classe implémente l’interface ContentHandler en écrivant les événements SAX dans un document XML. En d’autres termes, utiliser un XMLGenerator en tant que gestionnaire de contenu reproduira le document original qui était analysé. out devrait être un objet de type fichier qui est par défaut sys.stdout. encoding est l’encodage du flux de sortie qui est par défaut 'iso-8859-1'. short_empty_elements contrôle le formatage des éléments qui ne contiennent rien : si False (par défaut), ils sont émis comme une paire de balises (début, fin). Si la valeur est True, ils sont émis comme une balise seule auto-fermante.

Nouveau dans la version 3.2: Le paramètre short_empty_elements.

class xml.sax.saxutils.XMLFilterBase(base)

Cette classe est faite pour être entre XMLReader et le gestionnaire des événements de l’application client. Par défaut, elle ne fait rien mais passe les requêtes au lecteur et les événements au gestionnaire sans les modifier, mais des sous-classes peuvent surcharger des méthodes spécifiques pour modifier le flux d’événements ou la configuration des requêtes à leur passage.

xml.sax.saxutils.prepare_input_source(source, base='')

Cette fonction prend en entrée une source et une URL de base optionnelle et retourne un objet complétement résolue InputSource prêt pour être lu. La source d’entrée peut être donnée comme une chaine de caractère, un objet type fichier, ou un objet InputSource ; Les analyseurs utiliseront cette fonction pour gérer le polymorphisme de l’argument source à leur méthode parse().

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20.12. xml.sax.xmlreader — Interface for XML parsers

Source code: Lib/xml/sax/xmlreader.py [https://github.com/python/cpython/tree/3.6/Lib/xml/sax/xmlreader.py]

SAX parsers implement the XMLReader interface. They are implemented in a Python module, which must provide a function create_parser(). This function is invoked by xml.sax.make_parser() with no arguments to create a new parser object.

class xml.sax.xmlreader.XMLReader

Base class which can be inherited by SAX parsers.

class xml.sax.xmlreader.IncrementalParser

In some cases, it is desirable not to parse an input source at once, but to feed chunks of the document as they get available. Note that the reader will normally not read the entire file, but read it in chunks as well; still parse() won’t return until the entire document is processed. So these interfaces should be used if the blocking behaviour of parse() is not desirable.

When the parser is instantiated it is ready to begin accepting data from the feed method immediately. After parsing has been finished with a call to close the reset method must be called to make the parser ready to accept new data, either from feed or using the parse method.

Note that these methods must not be called during parsing, that is, after parse has been called and before it returns.

By default, the class also implements the parse method of the XMLReader interface using the feed, close and reset methods of the IncrementalParser interface as a convenience to SAX 2.0 driver writers.

class xml.sax.xmlreader.Locator

Interface for associating a SAX event with a document location. A locator object will return valid results only during calls to DocumentHandler methods; at any other time, the results are unpredictable. If information is not available, methods may return None.

class xml.sax.xmlreader.InputSource(system_id=None)

Encapsulation of the information needed by the XMLReader to read entities.

This class may include information about the public identifier, system identifier, byte stream (possibly with character encoding information) and/or the character stream of an entity.

Applications will create objects of this class for use in the XMLReader.parse() method and for returning from EntityResolver.resolveEntity.

An InputSource belongs to the application, the XMLReader is not allowed to modify InputSource objects passed to it from the application, although it may make copies and modify those.

class xml.sax.xmlreader.AttributesImpl(attrs)

This is an implementation of the Attributes interface (see section The Attributes Interface). This is a dictionary-like object which represents the element attributes in a startElement() call. In addition to the most useful dictionary operations, it supports a number of other methods as described by the interface. Objects of this class should be instantiated by readers; attrs must be a dictionary-like object containing a mapping from attribute names to attribute values.

class xml.sax.xmlreader.AttributesNSImpl(attrs, qnames)

Namespace-aware variant of AttributesImpl, which will be passed to startElementNS(). It is derived from AttributesImpl, but understands attribute names as two-tuples of namespaceURI and localname. In addition, it provides a number of methods expecting qualified names as they appear in the original document. This class implements the AttributesNS interface (see section The AttributesNS Interface).

20.12.1. XMLReader Objects

The XMLReader interface supports the following methods:

XMLReader.parse(source)

Process an input source, producing SAX events. The source object can be a system identifier (a string identifying the input source – typically a file name or a URL), a file-like object, or an InputSource object. When parse() returns, the input is completely processed, and the parser object can be discarded or reset.

Modifié dans la version 3.5: Added support of character streams.

XMLReader.getContentHandler()

Return the current ContentHandler.

XMLReader.setContentHandler(handler)

Set the current ContentHandler. If no ContentHandler is set, content events will be discarded.

XMLReader.getDTDHandler()

Return the current DTDHandler.

XMLReader.setDTDHandler(handler)

Set the current DTDHandler. If no DTDHandler is set, DTD events will be discarded.

XMLReader.getEntityResolver()

Return the current EntityResolver.

XMLReader.setEntityResolver(handler)

Set the current EntityResolver. If no EntityResolver is set, attempts to resolve an external entity will result in opening the system identifier for the entity, and fail if it is not available.

XMLReader.getErrorHandler()

Return the current ErrorHandler.

XMLReader.setErrorHandler(handler)

Set the current error handler. If no ErrorHandler is set, errors will be raised as exceptions, and warnings will be printed.

XMLReader.setLocale(locale)

Allow an application to set the locale for errors and warnings.

SAX parsers are not required to provide localization for errors and warnings; if they cannot support the requested locale, however, they must raise a SAX exception. Applications may request a locale change in the middle of a parse.

XMLReader.getFeature(featurename)

Return the current setting for feature featurename. If the feature is not recognized, SAXNotRecognizedException is raised. The well-known featurenames are listed in the module xml.sax.handler.

XMLReader.setFeature(featurename, value)

Set the featurename to value. If the feature is not recognized, SAXNotRecognizedException is raised. If the feature or its setting is not supported by the parser, SAXNotSupportedException is raised.

XMLReader.getProperty(propertyname)

Return the current setting for property propertyname. If the property is not recognized, a SAXNotRecognizedException is raised. The well-known propertynames are listed in the module xml.sax.handler.

XMLReader.setProperty(propertyname, value)

Set the propertyname to value. If the property is not recognized, SAXNotRecognizedException is raised. If the property or its setting is not supported by the parser, SAXNotSupportedException is raised.

20.12.2. IncrementalParser Objects

Instances of IncrementalParser offer the following additional methods:

IncrementalParser.feed(data)

Process a chunk of data.

IncrementalParser.close()

Assume the end of the document. That will check well-formedness conditions that can be checked only at the end, invoke handlers, and may clean up resources allocated during parsing.

IncrementalParser.reset()

This method is called after close has been called to reset the parser so that it is ready to parse new documents. The results of calling parse or feed after close without calling reset are undefined.

20.12.3. Locator Objects

Instances of Locator provide these methods:

Locator.getColumnNumber()

Return the column number where the current event begins.

Locator.getLineNumber()

Return the line number where the current event begins.

Locator.getPublicId()

Return the public identifier for the current event.

Locator.getSystemId()

Return the system identifier for the current event.

20.12.4. InputSource Objects

InputSource.setPublicId(id)

Sets the public identifier of this InputSource.

InputSource.getPublicId()

Returns the public identifier of this InputSource.

InputSource.setSystemId(id)

Sets the system identifier of this InputSource.

InputSource.getSystemId()

Returns the system identifier of this InputSource.

InputSource.setEncoding(encoding)

Sets the character encoding of this InputSource.

The encoding must be a string acceptable for an XML encoding declaration (see section 4.3.3 of the XML recommendation).

The encoding attribute of the InputSource is ignored if the InputSource also contains a character stream.

InputSource.getEncoding()

Get the character encoding of this InputSource.

InputSource.setByteStream(bytefile)

Set the byte stream (a binary file) for this input source.

The SAX parser will ignore this if there is also a character stream specified, but it will use a byte stream in preference to opening a URI connection itself.

If the application knows the character encoding of the byte stream, it should set it with the setEncoding method.

InputSource.getByteStream()

Get the byte stream for this input source.

The getEncoding method will return the character encoding for this byte stream, or None if unknown.

InputSource.setCharacterStream(charfile)

Set the character stream (a text file) for this input source.

If there is a character stream specified, the SAX parser will ignore any byte stream and will not attempt to open a URI connection to the system identifier.

InputSource.getCharacterStream()

Get the character stream for this input source.

20.12.5. The Attributes Interface

Attributes objects implement a portion of the mapping protocol, including the methods copy(), get(), __contains__(), items(), keys(), and values(). The following methods are also provided:

Attributes.getLength()

Return the number of attributes.

Attributes.getNames()

Return the names of the attributes.

Attributes.getType(name)

Returns the type of the attribute name, which is normally 'CDATA'.

Attributes.getValue(name)

Return the value of attribute name.

20.12.6. The AttributesNS Interface

This interface is a subtype of the Attributes interface (see section The Attributes Interface). All methods supported by that interface are also available on AttributesNS objects.

The following methods are also available:

AttributesNS.getValueByQName(name)

Return the value for a qualified name.

AttributesNS.getNameByQName(name)

Return the (namespace, localname) pair for a qualified name.

AttributesNS.getQNameByName(name)

Return the qualified name for a (namespace, localname) pair.

AttributesNS.getQNames()

Return the qualified names of all attributes.

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20.13. xml.parsers.expat — Fast XML parsing using Expat

Avertissement

The pyexpat module is not secure against maliciously constructed data. If you need to parse untrusted or unauthenticated data see Vulnérabilités XML.

The xml.parsers.expat module is a Python interface to the Expat non-validating XML parser. The module provides a single extension type, xmlparser, that represents the current state of an XML parser. After an xmlparser object has been created, various attributes of the object can be set to handler functions. When an XML document is then fed to the parser, the handler functions are called for the character data and markup in the XML document.

This module uses the pyexpat module to provide access to the Expat parser. Direct use of the pyexpat module is deprecated.

This module provides one exception and one type object:

exception xml.parsers.expat.ExpatError

The exception raised when Expat reports an error. See section ExpatError Exceptions for more information on interpreting Expat errors.

exception xml.parsers.expat.error

Alias for ExpatError.

xml.parsers.expat.XMLParserType

The type of the return values from the ParserCreate() function.

The xml.parsers.expat module contains two functions:

xml.parsers.expat.ErrorString(errno)

Returns an explanatory string for a given error number errno.

xml.parsers.expat.ParserCreate(encoding=None, namespace_separator=None)

Creates and returns a new xmlparser object. encoding, if specified, must be a string naming the encoding used by the XML data. Expat doesn’t support as many encodings as Python does, and its repertoire of encodings can’t be extended; it supports UTF-8, UTF-16, ISO-8859-1 (Latin1), and ASCII. If encoding 1 is given it will override the implicit or explicit encoding of the document.

Expat can optionally do XML namespace processing for you, enabled by providing a value for namespace_separator. The value must be a one-character string; a ValueError will be raised if the string has an illegal length (None is considered the same as omission). When namespace processing is enabled, element type names and attribute names that belong to a namespace will be expanded. The element name passed to the element handlers StartElementHandler and EndElementHandler will be the concatenation of the namespace URI, the namespace separator character, and the local part of the name. If the namespace separator is a zero byte (chr(0)) then the namespace URI and the local part will be concatenated without any separator.

For example, if namespace_separator is set to a space character (' ') and the following document is parsed:

<?xml version="1.0"?>
<root xmlns    = "http://default-namespace.org/"
      xmlns:py = "http://www.python.org/ns/">
  <py:elem1 />
  <elem2 xmlns="" />
</root>

StartElementHandler will receive the following strings for each element:

http://default-namespace.org/ root
http://www.python.org/ns/ elem1
elem2

Due to limitations in the Expat library used by pyexpat, the xmlparser instance returned can only be used to parse a single XML document. Call ParserCreate for each document to provide unique parser instances.

Voir aussi

The Expat XML Parser [http://www.libexpat.org/]

Home page of the Expat project.

20.13.1. XMLParser Objects

xmlparser objects have the following methods:

xmlparser.Parse(data[, isfinal])

Parses the contents of the string data, calling the appropriate handler functions to process the parsed data. isfinal must be true on the final call to this method; it allows the parsing of a single file in fragments, not the submission of multiple files. data can be the empty string at any time.

xmlparser.ParseFile(file)

Parse XML data reading from the object file. file only needs to provide the read(nbytes) method, returning the empty string when there’s no more data.

xmlparser.SetBase(base)

Sets the base to be used for resolving relative URIs in system identifiers in declarations. Resolving relative identifiers is left to the application: this value will be passed through as the base argument to the ExternalEntityRefHandler(), NotationDeclHandler(), and UnparsedEntityDeclHandler() functions.

xmlparser.GetBase()

Returns a string containing the base set by a previous call to SetBase(), or None if SetBase() hasn’t been called.

xmlparser.GetInputContext()

Returns the input data that generated the current event as a string. The data is in the encoding of the entity which contains the text. When called while an event handler is not active, the return value is None.

xmlparser.ExternalEntityParserCreate(context[, encoding])

Create a « child » parser which can be used to parse an external parsed entity referred to by content parsed by the parent parser. The context parameter should be the string passed to the ExternalEntityRefHandler() handler function, described below. The child parser is created with the ordered_attributes and specified_attributes set to the values of this parser.

xmlparser.SetParamEntityParsing(flag)

Control parsing of parameter entities (including the external DTD subset). Possible flag values are XML_PARAM_ENTITY_PARSING_NEVER, XML_PARAM_ENTITY_PARSING_UNLESS_STANDALONE and XML_PARAM_ENTITY_PARSING_ALWAYS. Return true if setting the flag was successful.

xmlparser.UseForeignDTD([flag])

Calling this with a true value for flag (the default) will cause Expat to call the ExternalEntityRefHandler with None for all arguments to allow an alternate DTD to be loaded. If the document does not contain a document type declaration, the ExternalEntityRefHandler will still be called, but the StartDoctypeDeclHandler and EndDoctypeDeclHandler will not be called.

Passing a false value for flag will cancel a previous call that passed a true value, but otherwise has no effect.

This method can only be called before the Parse() or ParseFile() methods are called; calling it after either of those have been called causes ExpatError to be raised with the code attribute set to errors.codes[errors.XML_ERROR_CANT_CHANGE_FEATURE_ONCE_PARSING].

xmlparser objects have the following attributes:

xmlparser.buffer_size

The size of the buffer used when buffer_text is true. A new buffer size can be set by assigning a new integer value to this attribute. When the size is changed, the buffer will be flushed.

xmlparser.buffer_text

Setting this to true causes the xmlparser object to buffer textual content returned by Expat to avoid multiple calls to the CharacterDataHandler() callback whenever possible. This can improve performance substantially since Expat normally breaks character data into chunks at every line ending. This attribute is false by default, and may be changed at any time.

xmlparser.buffer_used

If buffer_text is enabled, the number of bytes stored in the buffer. These bytes represent UTF-8 encoded text. This attribute has no meaningful interpretation when buffer_text is false.

xmlparser.ordered_attributes

Setting this attribute to a non-zero integer causes the attributes to be reported as a list rather than a dictionary. The attributes are presented in the order found in the document text. For each attribute, two list entries are presented: the attribute name and the attribute value. (Older versions of this module also used this format.) By default, this attribute is false; it may be changed at any time.

xmlparser.specified_attributes

If set to a non-zero integer, the parser will report only those attributes which were specified in the document instance and not those which were derived from attribute declarations. Applications which set this need to be especially careful to use what additional information is available from the declarations as needed to comply with the standards for the behavior of XML processors. By default, this attribute is false; it may be changed at any time.

The following attributes contain values relating to the most recent error encountered by an xmlparser object, and will only have correct values once a call to Parse() or ParseFile() has raised an xml.parsers.expat.ExpatError exception.

xmlparser.ErrorByteIndex

Byte index at which an error occurred.

xmlparser.ErrorCode

Numeric code specifying the problem. This value can be passed to the ErrorString() function, or compared to one of the constants defined in the errors object.

xmlparser.ErrorColumnNumber

Column number at which an error occurred.

xmlparser.ErrorLineNumber

Line number at which an error occurred.

The following attributes contain values relating to the current parse location in an xmlparser object. During a callback reporting a parse event they indicate the location of the first of the sequence of characters that generated the event. When called outside of a callback, the position indicated will be just past the last parse event (regardless of whether there was an associated callback).

xmlparser.CurrentByteIndex

Current byte index in the parser input.

xmlparser.CurrentColumnNumber

Current column number in the parser input.

xmlparser.CurrentLineNumber

Current line number in the parser input.

Here is the list of handlers that can be set. To set a handler on an xmlparser object o, use o.handlername = func. handlername must be taken from the following list, and func must be a callable object accepting the correct number of arguments. The arguments are all strings, unless otherwise stated.

xmlparser.XmlDeclHandler(version, encoding, standalone)

Called when the XML declaration is parsed. The XML declaration is the (optional) declaration of the applicable version of the XML recommendation, the encoding of the document text, and an optional « standalone » declaration. version and encoding will be strings, and standalone will be 1 if the document is declared standalone, 0 if it is declared not to be standalone, or -1 if the standalone clause was omitted. This is only available with Expat version 1.95.0 or newer.

xmlparser.StartDoctypeDeclHandler(doctypeName, systemId, publicId, has_internal_subset)

Called when Expat begins parsing the document type declaration (<!DOCTYPE ...). The doctypeName is provided exactly as presented. The systemId and publicId parameters give the system and public identifiers if specified, or None if omitted. has_internal_subset will be true if the document contains and internal document declaration subset. This requires Expat version 1.2 or newer.

xmlparser.EndDoctypeDeclHandler()

Called when Expat is done parsing the document type declaration. This requires Expat version 1.2 or newer.

xmlparser.ElementDeclHandler(name, model)

Called once for each element type declaration. name is the name of the element type, and model is a representation of the content model.

xmlparser.AttlistDeclHandler(elname, attname, type, default, required)

Called for each declared attribute for an element type. If an attribute list declaration declares three attributes, this handler is called three times, once for each attribute. elname is the name of the element to which the declaration applies and attname is the name of the attribute declared. The attribute type is a string passed as type; the possible values are 'CDATA', 'ID', 'IDREF', … default gives the default value for the attribute used when the attribute is not specified by the document instance, or None if there is no default value (#IMPLIED values). If the attribute is required to be given in the document instance, required will be true. This requires Expat version 1.95.0 or newer.

xmlparser.StartElementHandler(name, attributes)

Called for the start of every element. name is a string containing the element name, and attributes is the element attributes. If ordered_attributes is true, this is a list (see ordered_attributes for a full description). Otherwise it’s a dictionary mapping names to values.

xmlparser.EndElementHandler(name)

Called for the end of every element.

xmlparser.ProcessingInstructionHandler(target, data)

Called for every processing instruction.

xmlparser.CharacterDataHandler(data)

Called for character data. This will be called for normal character data, CDATA marked content, and ignorable whitespace. Applications which must distinguish these cases can use the StartCdataSectionHandler, EndCdataSectionHandler, and ElementDeclHandler callbacks to collect the required information.

xmlparser.UnparsedEntityDeclHandler(entityName, base, systemId, publicId, notationName)

Called for unparsed (NDATA) entity declarations. This is only present for version 1.2 of the Expat library; for more recent versions, use EntityDeclHandler instead. (The underlying function in the Expat library has been declared obsolete.)

xmlparser.EntityDeclHandler(entityName, is_parameter_entity, value, base, systemId, publicId, notationName)

Called for all entity declarations. For parameter and internal entities, value will be a string giving the declared contents of the entity; this will be None for external entities. The notationName parameter will be None for parsed entities, and the name of the notation for unparsed entities. is_parameter_entity will be true if the entity is a parameter entity or false for general entities (most applications only need to be concerned with general entities). This is only available starting with version 1.95.0 of the Expat library.

xmlparser.NotationDeclHandler(notationName, base, systemId, publicId)

Called for notation declarations. notationName, base, and systemId, and publicId are strings if given. If the public identifier is omitted, publicId will be None.

xmlparser.StartNamespaceDeclHandler(prefix, uri)

Called when an element contains a namespace declaration. Namespace declarations are processed before the StartElementHandler is called for the element on which declarations are placed.

xmlparser.EndNamespaceDeclHandler(prefix)

Called when the closing tag is reached for an element that contained a namespace declaration. This is called once for each namespace declaration on the element in the reverse of the order for which the StartNamespaceDeclHandler was called to indicate the start of each namespace declaration’s scope. Calls to this handler are made after the corresponding EndElementHandler for the end of the element.

xmlparser.CommentHandler(data)

Called for comments. data is the text of the comment, excluding the leading '<!--' and trailing '-->'.

xmlparser.StartCdataSectionHandler()

Called at the start of a CDATA section. This and EndCdataSectionHandler are needed to be able to identify the syntactical start and end for CDATA sections.

xmlparser.EndCdataSectionHandler()

Called at the end of a CDATA section.

xmlparser.DefaultHandler(data)

Called for any characters in the XML document for which no applicable handler has been specified. This means characters that are part of a construct which could be reported, but for which no handler has been supplied.

xmlparser.DefaultHandlerExpand(data)

This is the same as the DefaultHandler(), but doesn’t inhibit expansion of internal entities. The entity reference will not be passed to the default handler.

xmlparser.NotStandaloneHandler()

Called if the XML document hasn’t been declared as being a standalone document. This happens when there is an external subset or a reference to a parameter entity, but the XML declaration does not set standalone to yes in an XML declaration. If this handler returns 0, then the parser will raise an XML_ERROR_NOT_STANDALONE error. If this handler is not set, no exception is raised by the parser for this condition.

xmlparser.ExternalEntityRefHandler(context, base, systemId, publicId)

Called for references to external entities. base is the current base, as set by a previous call to SetBase(). The public and system identifiers, systemId and publicId, are strings if given; if the public identifier is not given, publicId will be None. The context value is opaque and should only be used as described below.

For external entities to be parsed, this handler must be implemented. It is responsible for creating the sub-parser using ExternalEntityParserCreate(context), initializing it with the appropriate callbacks, and parsing the entity. This handler should return an integer; if it returns 0, the parser will raise an XML_ERROR_EXTERNAL_ENTITY_HANDLING error, otherwise parsing will continue.

If this handler is not provided, external entities are reported by the DefaultHandler callback, if provided.

20.13.2. ExpatError Exceptions

ExpatError exceptions have a number of interesting attributes:

ExpatError.code

Expat’s internal error number for the specific error. The errors.messages dictionary maps these error numbers to Expat’s error messages. For example:

from xml.parsers.expat import ParserCreate, ExpatError, errors

p = ParserCreate()
try:
    p.Parse(some_xml_document)
except ExpatError as err:
    print("Error:", errors.messages[err.code])

The errors module also provides error message constants and a dictionary codes mapping these messages back to the error codes, see below.

ExpatError.lineno

Line number on which the error was detected. The first line is numbered 1.

ExpatError.offset

Character offset into the line where the error occurred. The first column is numbered 0.

20.13.3. Exemple

The following program defines three handlers that just print out their arguments.

import xml.parsers.expat

# 3 handler functions
def start_element(name, attrs):
    print('Start element:', name, attrs)
def end_element(name):
    print('End element:', name)
def char_data(data):
    print('Character data:', repr(data))

p = xml.parsers.expat.ParserCreate()

p.StartElementHandler = start_element
p.EndElementHandler = end_element
p.CharacterDataHandler = char_data

p.Parse("""<?xml version="1.0"?>
<parent id="top"><child1 name="paul">Text goes here</child1>
<child2 name="fred">More text</child2>
</parent>""", 1)

The output from this program is:

Start element: parent {'id': 'top'}
Start element: child1 {'name': 'paul'}
Character data: 'Text goes here'
End element: child1
Character data: '\n'
Start element: child2 {'name': 'fred'}
Character data: 'More text'
End element: child2
Character data: '\n'
End element: parent

20.13.4. Content Model Descriptions

Content models are described using nested tuples. Each tuple contains four values: the type, the quantifier, the name, and a tuple of children. Children are simply additional content model descriptions.

The values of the first two fields are constants defined in the xml.parsers.expat.model module. These constants can be collected in two groups: the model type group and the quantifier group.

The constants in the model type group are:

xml.parsers.expat.model.XML_CTYPE_ANY

The element named by the model name was declared to have a content model of ANY.

xml.parsers.expat.model.XML_CTYPE_CHOICE

The named element allows a choice from a number of options; this is used for content models such as (A | B | C).

xml.parsers.expat.model.XML_CTYPE_EMPTY

Elements which are declared to be EMPTY have this model type.

xml.parsers.expat.model.XML_CTYPE_MIXED

xml.parsers.expat.model.XML_CTYPE_NAME

xml.parsers.expat.model.XML_CTYPE_SEQ

Models which represent a series of models which follow one after the other are indicated with this model type. This is used for models such as (A, B, C).

The constants in the quantifier group are:

xml.parsers.expat.model.XML_CQUANT_NONE

No modifier is given, so it can appear exactly once, as for A.

xml.parsers.expat.model.XML_CQUANT_OPT

The model is optional: it can appear once or not at all, as for A?.

xml.parsers.expat.model.XML_CQUANT_PLUS

The model must occur one or more times (like A+).

xml.parsers.expat.model.XML_CQUANT_REP

The model must occur zero or more times, as for A*.

20.13.5. Expat error constants

The following constants are provided in the xml.parsers.expat.errors module. These constants are useful in interpreting some of the attributes of the ExpatError exception objects raised when an error has occurred. Since for backwards compatibility reasons, the constants” value is the error message and not the numeric error code, you do this by comparing its code attribute with errors.codes[errors.XML_ERROR_CONSTANT_NAME].

The errors module has the following attributes:

xml.parsers.expat.errors.codes

A dictionary mapping numeric error codes to their string descriptions.

Nouveau dans la version 3.2.

xml.parsers.expat.errors.messages

A dictionary mapping string descriptions to their error codes.

Nouveau dans la version 3.2.

xml.parsers.expat.errors.XML_ERROR_ASYNC_ENTITY

xml.parsers.expat.errors.XML_ERROR_ATTRIBUTE_EXTERNAL_ENTITY_REF

An entity reference in an attribute value referred to an external entity instead of an internal entity.

xml.parsers.expat.errors.XML_ERROR_BAD_CHAR_REF

A character reference referred to a character which is illegal in XML (for example, character 0, or “&#0;”).

xml.parsers.expat.errors.XML_ERROR_BINARY_ENTITY_REF

An entity reference referred to an entity which was declared with a notation, so cannot be parsed.

xml.parsers.expat.errors.XML_ERROR_DUPLICATE_ATTRIBUTE

An attribute was used more than once in a start tag.

xml.parsers.expat.errors.XML_ERROR_INCORRECT_ENCODING

xml.parsers.expat.errors.XML_ERROR_INVALID_TOKEN

Raised when an input byte could not properly be assigned to a character; for example, a NUL byte (value 0) in a UTF-8 input stream.

xml.parsers.expat.errors.XML_ERROR_JUNK_AFTER_DOC_ELEMENT

Something other than whitespace occurred after the document element.

xml.parsers.expat.errors.XML_ERROR_MISPLACED_XML_PI

An XML declaration was found somewhere other than the start of the input data.

xml.parsers.expat.errors.XML_ERROR_NO_ELEMENTS

The document contains no elements (XML requires all documents to contain exactly one top-level element)..

xml.parsers.expat.errors.XML_ERROR_NO_MEMORY

Expat was not able to allocate memory internally.

xml.parsers.expat.errors.XML_ERROR_PARAM_ENTITY_REF

A parameter entity reference was found where it was not allowed.

xml.parsers.expat.errors.XML_ERROR_PARTIAL_CHAR

An incomplete character was found in the input.

xml.parsers.expat.errors.XML_ERROR_RECURSIVE_ENTITY_REF

An entity reference contained another reference to the same entity; possibly via a different name, and possibly indirectly.

xml.parsers.expat.errors.XML_ERROR_SYNTAX

Some unspecified syntax error was encountered.

xml.parsers.expat.errors.XML_ERROR_TAG_MISMATCH

An end tag did not match the innermost open start tag.

xml.parsers.expat.errors.XML_ERROR_UNCLOSED_TOKEN

Some token (such as a start tag) was not closed before the end of the stream or the next token was encountered.

xml.parsers.expat.errors.XML_ERROR_UNDEFINED_ENTITY

A reference was made to an entity which was not defined.

xml.parsers.expat.errors.XML_ERROR_UNKNOWN_ENCODING

The document encoding is not supported by Expat.

xml.parsers.expat.errors.XML_ERROR_UNCLOSED_CDATA_SECTION

A CDATA marked section was not closed.

xml.parsers.expat.errors.XML_ERROR_EXTERNAL_ENTITY_HANDLING

xml.parsers.expat.errors.XML_ERROR_NOT_STANDALONE

The parser determined that the document was not « standalone » though it declared itself to be in the XML declaration, and the NotStandaloneHandler was set and returned 0.

xml.parsers.expat.errors.XML_ERROR_UNEXPECTED_STATE

xml.parsers.expat.errors.XML_ERROR_ENTITY_DECLARED_IN_PE

xml.parsers.expat.errors.XML_ERROR_FEATURE_REQUIRES_XML_DTD

An operation was requested that requires DTD support to be compiled in, but Expat was configured without DTD support. This should never be reported by a standard build of the xml.parsers.expat module.

xml.parsers.expat.errors.XML_ERROR_CANT_CHANGE_FEATURE_ONCE_PARSING

A behavioral change was requested after parsing started that can only be changed before parsing has started. This is (currently) only raised by UseForeignDTD().

xml.parsers.expat.errors.XML_ERROR_UNBOUND_PREFIX

An undeclared prefix was found when namespace processing was enabled.

xml.parsers.expat.errors.XML_ERROR_UNDECLARING_PREFIX

The document attempted to remove the namespace declaration associated with a prefix.

xml.parsers.expat.errors.XML_ERROR_INCOMPLETE_PE

A parameter entity contained incomplete markup.

xml.parsers.expat.errors.XML_ERROR_XML_DECL

The document contained no document element at all.

xml.parsers.expat.errors.XML_ERROR_TEXT_DECL

There was an error parsing a text declaration in an external entity.

xml.parsers.expat.errors.XML_ERROR_PUBLICID

Characters were found in the public id that are not allowed.

xml.parsers.expat.errors.XML_ERROR_SUSPENDED

The requested operation was made on a suspended parser, but isn’t allowed. This includes attempts to provide additional input or to stop the parser.

xml.parsers.expat.errors.XML_ERROR_NOT_SUSPENDED

An attempt to resume the parser was made when the parser had not been suspended.

xml.parsers.expat.errors.XML_ERROR_ABORTED

This should not be reported to Python applications.

xml.parsers.expat.errors.XML_ERROR_FINISHED

The requested operation was made on a parser which was finished parsing input, but isn’t allowed. This includes attempts to provide additional input or to stop the parser.

xml.parsers.expat.errors.XML_ERROR_SUSPEND_PE

Notes

1

The encoding string included in XML output should conform to the appropriate standards. For example, « UTF-8 » is valid, but « UTF8 » is not. See https://www.w3.org/TR/2006/REC-xml11-20060816/#NT-EncodingDecl and https://www.iana.org/assignments/character-sets/character-sets.xhtml.

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21. Gestion des protocoles internet

Les modules documentés dans ce chapitre implémentent des protocoles relatifs à Internet et à ses technologies relatives. Ils sont tous implémentés en Python. La majorité de ces modules nécessitent la présence du module socket lui même dépendant du système, mais fourni sur la plupart des plateformes populaires. Voici une vue d’ensemble :

21.1. webbrowser — Convenient Web-browser controller

21.1.1. Browser Controller Objects

21.2. cgi — Common Gateway Interface support

21.2.1. Introduction

21.2.2. Using the cgi module

21.2.3. Higher Level Interface

21.2.4. Fonctions

21.2.5. Caring about security

21.2.6. Installing your CGI script on a Unix system

21.2.7. Testing your CGI script

21.2.8. Debugging CGI scripts

21.2.9. Common problems and solutions

21.3. cgitb — Gestionnaire d’exceptions pour les scripts CGI

21.4. wsgiref — Outils et implémentation de référence de WSGI

21.4.1. wsgiref.util — outils pour les environnements WSGI

21.4.2. wsgiref.headers – WSGI response header tools

21.4.3. wsgiref.simple_server – a simple WSGI HTTP server

21.4.4. wsgiref.validate — WSGI conformance checker

21.4.5. wsgiref.handlers – server/gateway base classes

21.4.6. Exemples

21.5. urllib — Modules de gestion des URLs

21.6. urllib.request — Extensible library for opening URLs

21.6.1. Request Objects

21.6.2. OpenerDirector Objects

21.6.3. BaseHandler Objects

21.6.4. HTTPRedirectHandler Objects

21.6.5. HTTPCookieProcessor Objects

21.6.6. ProxyHandler Objects

21.6.7. HTTPPasswordMgr Objects

21.6.8. HTTPPasswordMgrWithPriorAuth Objects

21.6.9. AbstractBasicAuthHandler Objects

21.6.10. HTTPBasicAuthHandler Objects

21.6.11. ProxyBasicAuthHandler Objects

21.6.12. AbstractDigestAuthHandler Objects

21.6.13. HTTPDigestAuthHandler Objects

21.6.14. ProxyDigestAuthHandler Objects

21.6.15. HTTPHandler Objects

21.6.16. HTTPSHandler Objects

21.6.17. FileHandler Objects

21.6.18. DataHandler Objects

21.6.19. FTPHandler Objects

21.6.20. CacheFTPHandler Objects

21.6.21. UnknownHandler Objects

21.6.22. HTTPErrorProcessor Objects

21.6.23. Exemples

21.6.24. Legacy interface

21.6.25. urllib.request Restrictions

21.7. urllib.response — Response classes used by urllib

21.8. urllib.parse — Parse URLs into components

21.8.1. URL Parsing

21.8.2. Parsing ASCII Encoded Bytes

21.8.3. Structured Parse Results

21.8.4. URL Quoting

21.9. urllib.error — Classes d’exceptions levées par urllib.request

21.10. urllib.robotparser — Analyseur de fichiers robots.txt

21.11. http — modules HTTP

21.11.1. Codes d’état HTTP

21.12. http.client — HTTP protocol client

21.12.1. HTTPConnection Objects

21.12.2. HTTPResponse Objects

21.12.3. Exemples

21.12.4. HTTPMessage Objects

21.13. ftplib — FTP protocol client

21.13.1. FTP Objects

21.13.2. FTP_TLS Objects

21.14. poplib — POP3 protocol client

21.14.1. POP3 Objects

21.14.2. POP3 Example

21.15. imaplib — IMAP4 protocol client

21.15.1. IMAP4 Objects

21.15.2. IMAP4 Example

21.16. nntplib — NNTP protocol client

21.16.1. NNTP Objects

21.16.1.1. Attributes

21.16.1.2. Méthodes

21.16.2. Fonctions utilitaires

21.17. smtplib — SMTP protocol client

21.17.1. SMTP Objects

21.17.2. SMTP Example

21.18. smtpd — SMTP Server

21.18.1. SMTPServer Objects

21.18.2. DebuggingServer Objects

21.18.3. PureProxy Objects

21.18.4. MailmanProxy Objects

21.18.5. SMTPChannel Objects

21.19. telnetlib — Telnet client

21.19.1. Telnet Objects

21.19.2. Telnet Example

21.20. uuid — UUID objects according to RFC 4122

21.20.1. Exemple

21.21. socketserver — A framework for network servers

21.21.1. Server Creation Notes

21.21.2. Objets Serveur

21.21.3. Request Handler Objects

21.21.4. Exemples

21.21.4.1. socketserver.TCPServer Example

21.21.4.2. socketserver.UDPServer Example

21.21.4.3. Asynchronous Mixins

21.22. http.server — HTTP servers

21.23. http.cookies — gestion d’état pour HTTP

21.23.1. Objets Cookie

21.23.2. Objets Morsel

21.23.3. Exemple

21.24. http.cookiejar — Cookie handling for HTTP clients

21.24.1. CookieJar and FileCookieJar Objects

21.24.2. FileCookieJar subclasses and co-operation with web browsers

21.24.3. CookiePolicy Objects

21.24.4. DefaultCookiePolicy Objects

21.24.5. Objets Cookie

21.24.6. Exemples

21.25. xmlrpc — Modules Serveur et Client XMLRPC

21.26. xmlrpc.client — XML-RPC client access

21.26.1. ServerProxy Objects

21.26.2. Objets DateTime

21.26.3. Binary Objects

21.26.4. Fault Objects

21.26.5. ProtocolError Objects

21.26.6. MultiCall Objects

21.26.7. Convenience Functions

21.26.8. Example of Client Usage

21.26.9. Example of Client and Server Usage

21.27. xmlrpc.server — Basic XML-RPC servers

21.27.1. SimpleXMLRPCServer Objects

21.27.1.1. SimpleXMLRPCServer Example

21.27.2. CGIXMLRPCRequestHandler

21.27.3. Documenting XMLRPC server

21.27.4. DocXMLRPCServer Objects

21.27.5. DocCGIXMLRPCRequestHandler

21.28. ipaddress — IPv4/IPv6 manipulation library

21.28.1. Convenience factory functions

21.28.2. IP Addresses

21.28.2.1. Address objects

21.28.2.2. Conversion to Strings and Integers

21.28.2.3. Opérateurs

21.28.2.3.1. Comparison operators

21.28.2.3.2. Arithmetic operators

21.28.3. IP Network definitions

21.28.3.1. Prefix, net mask and host mask

21.28.3.2. Network objects

21.28.3.3. Opérateurs

21.28.3.3.1. Logical operators

21.28.3.3.2. Itération

21.28.3.3.3. Networks as containers of addresses

21.28.4. Interface objects

21.28.4.1. Opérateurs

21.28.4.1.1. Logical operators

21.28.5. Other Module Level Functions

21.28.6. Custom Exceptions

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21.1. webbrowser — Convenient Web-browser controller

Source code: Lib/webbrowser.py [https://github.com/python/cpython/tree/3.6/Lib/webbrowser.py]

The webbrowser module provides a high-level interface to allow displaying Web-based documents to users. Under most circumstances, simply calling the open() function from this module will do the right thing.

Under Unix, graphical browsers are preferred under X11, but text-mode browsers will be used if graphical browsers are not available or an X11 display isn’t available. If text-mode browsers are used, the calling process will block until the user exits the browser.

If the environment variable BROWSER exists, it is interpreted as the os.pathsep-separated list of browsers to try ahead of the platform defaults. When the value of a list part contains the string %s, then it is interpreted as a literal browser command line to be used with the argument URL substituted for %s; if the part does not contain %s, it is simply interpreted as the name of the browser to launch. 1

For non-Unix platforms, or when a remote browser is available on Unix, the controlling process will not wait for the user to finish with the browser, but allow the remote browser to maintain its own windows on the display. If remote browsers are not available on Unix, the controlling process will launch a new browser and wait.

The script webbrowser can be used as a command-line interface for the module. It accepts a URL as the argument. It accepts the following optional parameters: -n opens the URL in a new browser window, if possible; -t opens the URL in a new browser page (« tab »). The options are, naturally, mutually exclusive. Usage example:

python -m webbrowser -t "http://www.python.org"

L’exception suivante est définie :

exception webbrowser.Error

Exception raised when a browser control error occurs.

Les fonctions suivantes sont définies :

webbrowser.open(url, new=0, autoraise=True)

Display url using the default browser. If new is 0, the url is opened in the same browser window if possible. If new is 1, a new browser window is opened if possible. If new is 2, a new browser page (« tab ») is opened if possible. If autoraise is True, the window is raised if possible (note that under many window managers this will occur regardless of the setting of this variable).

Note that on some platforms, trying to open a filename using this function, may work and start the operating system’s associated program. However, this is neither supported nor portable.

webbrowser.open_new(url)

Open url in a new window of the default browser, if possible, otherwise, open url in the only browser window.

webbrowser.open_new_tab(url)

Open url in a new page (« tab ») of the default browser, if possible, otherwise equivalent to open_new().

webbrowser.get(using=None)

Return a controller object for the browser type using. If using is None, return a controller for a default browser appropriate to the caller’s environment.

webbrowser.register(name, constructor, instance=None)

Register the browser type name. Once a browser type is registered, the get() function can return a controller for that browser type. If instance is not provided, or is None, constructor will be called without parameters to create an instance when needed. If instance is provided, constructor will never be called, and may be None.

This entry point is only useful if you plan to either set the BROWSER variable or call get() with a nonempty argument matching the name of a handler you declare.

A number of browser types are predefined. This table gives the type names that may be passed to the get() function and the corresponding instantiations for the controller classes, all defined in this module.

Type Name

Class Name

Notes

'mozilla'

Mozilla('mozilla')

'firefox'

Mozilla('mozilla')

'netscape'

Mozilla('netscape')

'galeon'

Galeon('galeon')

'epiphany'

Galeon('epiphany')

'skipstone'

BackgroundBrowser('skipstone')

'kfmclient'

Konqueror()

(1)

'konqueror'

Konqueror()

(1)

'kfm'

Konqueror()

(1)

'mosaic'

BackgroundBrowser('mosaic')

'opera'

Opera()

'grail'

Grail()

'links'

GenericBrowser('links')

'elinks'

Elinks('elinks')

'lynx'

GenericBrowser('lynx')

'w3m'

GenericBrowser('w3m')

'windows-default'

WindowsDefault

(2)

'macosx'

MacOSX('default')

(3)

'safari'

MacOSX('safari')

(3)

'google-chrome'

Chrome('google-chrome')

'chrome'

Chrome('chrome')

'chromium'

Chromium('chromium')

'chromium-browser'

Chromium('chromium-browser')

Notes :

« Konqueror » is the file manager for the KDE desktop environment for Unix, and only makes sense to use if KDE is running. Some way of reliably detecting KDE would be nice; the KDEDIR variable is not sufficient. Note also that the name « kfm » is used even when using the konqueror command with KDE 2 — the implementation selects the best strategy for running Konqueror.

Only on Windows platforms.

Only on Mac OS X platform.

Nouveau dans la version 3.3: Support for Chrome/Chromium has been added.

Here are some simple examples:

url = 'http://docs.python.org/'

# Open URL in a new tab, if a browser window is already open.
webbrowser.open_new_tab(url)

# Open URL in new window, raising the window if possible.
webbrowser.open_new(url)

21.1.1. Browser Controller Objects

Browser controllers provide these methods which parallel three of the module-level convenience functions:

controller.open(url, new=0, autoraise=True)

Display url using the browser handled by this controller. If new is 1, a new browser window is opened if possible. If new is 2, a new browser page (« tab ») is opened if possible.

controller.open_new(url)

Open url in a new window of the browser handled by this controller, if possible, otherwise, open url in the only browser window. Alias open_new().

controller.open_new_tab(url)

Open url in a new page (« tab ») of the browser handled by this controller, if possible, otherwise equivalent to open_new().

Notes

1

Executables named here without a full path will be searched in the directories given in the PATH environment variable.

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21.2. cgi — Common Gateway Interface support

Code source : Lib/cgi.py [https://github.com/python/cpython/tree/3.6/Lib/cgi.py]

Support module for Common Gateway Interface (CGI) scripts.

This module defines a number of utilities for use by CGI scripts written in Python.

21.2.1. Introduction

A CGI script is invoked by an HTTP server, usually to process user input submitted through an HTML <FORM> or <ISINDEX> element.

Most often, CGI scripts live in the server’s special cgi-bin directory. The HTTP server places all sorts of information about the request (such as the client’s hostname, the requested URL, the query string, and lots of other goodies) in the script’s shell environment, executes the script, and sends the script’s output back to the client.

The script’s input is connected to the client too, and sometimes the form data is read this way; at other times the form data is passed via the « query string » part of the URL. This module is intended to take care of the different cases and provide a simpler interface to the Python script. It also provides a number of utilities that help in debugging scripts, and the latest addition is support for file uploads from a form (if your browser supports it).

The output of a CGI script should consist of two sections, separated by a blank line. The first section contains a number of headers, telling the client what kind of data is following. Python code to generate a minimal header section looks like this:

print("Content-Type: text/html")    # HTML is following
print()                             # blank line, end of headers

The second section is usually HTML, which allows the client software to display nicely formatted text with header, in-line images, etc. Here’s Python code that prints a simple piece of HTML:

print("<TITLE>CGI script output</TITLE>")
print("<H1>This is my first CGI script</H1>")
print("Hello, world!")

21.2.2. Using the cgi module

Begin by writing import cgi.

When you write a new script, consider adding these lines:

import cgitb
cgitb.enable()

This activates a special exception handler that will display detailed reports in the Web browser if any errors occur. If you’d rather not show the guts of your program to users of your script, you can have the reports saved to files instead, with code like this:

import cgitb
cgitb.enable(display=0, logdir="/path/to/logdir")

It’s very helpful to use this feature during script development. The reports produced by cgitb provide information that can save you a lot of time in tracking down bugs. You can always remove the cgitb line later when you have tested your script and are confident that it works correctly.

To get at submitted form data, use the FieldStorage class. If the form contains non-ASCII characters, use the encoding keyword parameter set to the value of the encoding defined for the document. It is usually contained in the META tag in the HEAD section of the HTML document or by the Content-Type header). This reads the form contents from the standard input or the environment (depending on the value of various environment variables set according to the CGI standard). Since it may consume standard input, it should be instantiated only once.

The FieldStorage instance can be indexed like a Python dictionary. It allows membership testing with the in operator, and also supports the standard dictionary method keys() and the built-in function len(). Form fields containing empty strings are ignored and do not appear in the dictionary; to keep such values, provide a true value for the optional keep_blank_values keyword parameter when creating the FieldStorage instance.

For instance, the following code (which assumes that the Content-Type header and blank line have already been printed) checks that the fields name and addr are both set to a non-empty string:

form = cgi.FieldStorage()
if "name" not in form or "addr" not in form:
    print("<H1>Error</H1>")
    print("Please fill in the name and addr fields.")
    return
print("<p>name:", form["name"].value)
print("<p>addr:", form["addr"].value)
...further form processing here...

Here the fields, accessed through form[key], are themselves instances of FieldStorage (or MiniFieldStorage, depending on the form encoding). The value attribute of the instance yields the string value of the field. The getvalue() method returns this string value directly; it also accepts an optional second argument as a default to return if the requested key is not present.

If the submitted form data contains more than one field with the same name, the object retrieved by form[key] is not a FieldStorage or MiniFieldStorage instance but a list of such instances. Similarly, in this situation, form.getvalue(key) would return a list of strings. If you expect this possibility (when your HTML form contains multiple fields with the same name), use the getlist() method, which always returns a list of values (so that you do not need to special-case the single item case). For example, this code concatenates any number of username fields, separated by commas:

value = form.getlist("username")
usernames = ",".join(value)

If a field represents an uploaded file, accessing the value via the value attribute or the getvalue() method reads the entire file in memory as bytes. This may not be what you want. You can test for an uploaded file by testing either the filename attribute or the file attribute. You can then read the data from the file attribute before it is automatically closed as part of the garbage collection of the FieldStorage instance (the read() and readline() methods will return bytes):

fileitem = form["userfile"]
if fileitem.file:
    # It's an uploaded file; count lines
    linecount = 0
    while True:
        line = fileitem.file.readline()
        if not line: break
        linecount = linecount + 1

FieldStorage objects also support being used in a with statement, which will automatically close them when done.

If an error is encountered when obtaining the contents of an uploaded file (for example, when the user interrupts the form submission by clicking on a Back or Cancel button) the done attribute of the object for the field will be set to the value -1.

The file upload draft standard entertains the possibility of uploading multiple files from one field (using a recursive multipart/* encoding). When this occurs, the item will be a dictionary-like FieldStorage item. This can be determined by testing its type attribute, which should be multipart/form-data (or perhaps another MIME type matching multipart/*). In this case, it can be iterated over recursively just like the top-level form object.

When a form is submitted in the « old » format (as the query string or as a single data part of type application/x-www-form-urlencoded), the items will actually be instances of the class MiniFieldStorage. In this case, the list, file, and filename attributes are always None.

A form submitted via POST that also has a query string will contain both FieldStorage and MiniFieldStorage items.

Modifié dans la version 3.4: The file attribute is automatically closed upon the garbage collection of the creating FieldStorage instance.

Modifié dans la version 3.5: Added support for the context management protocol to the FieldStorage class.

21.2.3. Higher Level Interface

The previous section explains how to read CGI form data using the FieldStorage class. This section describes a higher level interface which was added to this class to allow one to do it in a more readable and intuitive way. The interface doesn’t make the techniques described in previous sections obsolete — they are still useful to process file uploads efficiently, for example.

The interface consists of two simple methods. Using the methods you can process form data in a generic way, without the need to worry whether only one or more values were posted under one name.

In the previous section, you learned to write following code anytime you expected a user to post more than one value under one name:

item = form.getvalue("item")
if isinstance(item, list):
    # The user is requesting more than one item.
else:
    # The user is requesting only one item.

This situation is common for example when a form contains a group of multiple checkboxes with the same name:

<input type="checkbox" name="item" value="1" />
<input type="checkbox" name="item" value="2" />

In most situations, however, there’s only one form control with a particular name in a form and then you expect and need only one value associated with this name. So you write a script containing for example this code:

user = form.getvalue("user").upper()

The problem with the code is that you should never expect that a client will provide valid input to your scripts. For example, if a curious user appends another user=foo pair to the query string, then the script would crash, because in this situation the getvalue("user") method call returns a list instead of a string. Calling the upper() method on a list is not valid (since lists do not have a method of this name) and results in an AttributeError exception.

Therefore, the appropriate way to read form data values was to always use the code which checks whether the obtained value is a single value or a list of values. That’s annoying and leads to less readable scripts.

A more convenient approach is to use the methods getfirst() and getlist() provided by this higher level interface.

FieldStorage.getfirst(name, default=None)

This method always returns only one value associated with form field name. The method returns only the first value in case that more values were posted under such name. Please note that the order in which the values are received may vary from browser to browser and should not be counted on. 1 If no such form field or value exists then the method returns the value specified by the optional parameter default. This parameter defaults to None if not specified.

FieldStorage.getlist(name)

This method always returns a list of values associated with form field name. The method returns an empty list if no such form field or value exists for name. It returns a list consisting of one item if only one such value exists.

Using these methods you can write nice compact code:

import cgi
form = cgi.FieldStorage()
user = form.getfirst("user", "").upper()    # This way it's safe.
for item in form.getlist("item"):
    do_something(item)

21.2.4. Fonctions

These are useful if you want more control, or if you want to employ some of the algorithms implemented in this module in other circumstances.

cgi.parse(fp=None, environ=os.environ, keep_blank_values=False, strict_parsing=False)

Parse a query in the environment or from a file (the file defaults to sys.stdin). The keep_blank_values and strict_parsing parameters are passed to urllib.parse.parse_qs() unchanged.

cgi.parse_qs(qs, keep_blank_values=False, strict_parsing=False)

This function is deprecated in this module. Use urllib.parse.parse_qs() instead. It is maintained here only for backward compatibility.

cgi.parse_qsl(qs, keep_blank_values=False, strict_parsing=False)

This function is deprecated in this module. Use urllib.parse.parse_qsl() instead. It is maintained here only for backward compatibility.

cgi.parse_multipart(fp, pdict)

Parse input of type multipart/form-data (for file uploads). Arguments are fp for the input file and pdict for a dictionary containing other parameters in the Content-Type header.

Returns a dictionary just like urllib.parse.parse_qs() keys are the field names, each value is a list of values for that field. This is easy to use but not much good if you are expecting megabytes to be uploaded — in that case, use the FieldStorage class instead which is much more flexible.

Note that this does not parse nested multipart parts — use FieldStorage for that.

cgi.parse_header(string)

Parse a MIME header (such as Content-Type) into a main value and a dictionary of parameters.

cgi.test()

Robust test CGI script, usable as main program. Writes minimal HTTP headers and formats all information provided to the script in HTML form.

cgi.print_environ()

Format the shell environment in HTML.

cgi.print_form(form)

Format a form in HTML.

cgi.print_directory()

Format the current directory in HTML.

cgi.print_environ_usage()

Print a list of useful (used by CGI) environment variables in HTML.

cgi.escape(s, quote=False)

Convert the characters '&', '<' and '>' in string s to HTML-safe sequences. Use this if you need to display text that might contain such characters in HTML. If the optional flag quote is true, the quotation mark character (") is also translated; this helps for inclusion in an HTML attribute value delimited by double quotes, as in <a href="...">. Note that single quotes are never translated.

Obsolète depuis la version 3.2: This function is unsafe because quote is false by default, and therefore deprecated. Use html.escape() instead.

21.2.5. Caring about security

There’s one important rule: if you invoke an external program (via the os.system() or os.popen() functions. or others with similar functionality), make very sure you don’t pass arbitrary strings received from the client to the shell. This is a well-known security hole whereby clever hackers anywhere on the Web can exploit a gullible CGI script to invoke arbitrary shell commands. Even parts of the URL or field names cannot be trusted, since the request doesn’t have to come from your form!

To be on the safe side, if you must pass a string gotten from a form to a shell command, you should make sure the string contains only alphanumeric characters, dashes, underscores, and periods.

21.2.6. Installing your CGI script on a Unix system

Read the documentation for your HTTP server and check with your local system administrator to find the directory where CGI scripts should be installed; usually this is in a directory cgi-bin in the server tree.

Make sure that your script is readable and executable by « others »; the Unix file mode should be 0o755 octal (use chmod 0755 filename). Make sure that the first line of the script contains #! starting in column 1 followed by the pathname of the Python interpreter, for instance:

#!/usr/local/bin/python

Make sure the Python interpreter exists and is executable by « others ».

Make sure that any files your script needs to read or write are readable or writable, respectively, by « others » — their mode should be 0o644 for readable and 0o666 for writable. This is because, for security reasons, the HTTP server executes your script as user « nobody », without any special privileges. It can only read (write, execute) files that everybody can read (write, execute). The current directory at execution time is also different (it is usually the server’s cgi-bin directory) and the set of environment variables is also different from what you get when you log in. In particular, don’t count on the shell’s search path for executables (PATH) or the Python module search path (PYTHONPATH) to be set to anything interesting.

If you need to load modules from a directory which is not on Python’s default module search path, you can change the path in your script, before importing other modules. For example:

import sys
sys.path.insert(0, "/usr/home/joe/lib/python")
sys.path.insert(0, "/usr/local/lib/python")

(This way, the directory inserted last will be searched first!)

Instructions for non-Unix systems will vary; check your HTTP server’s documentation (it will usually have a section on CGI scripts).

21.2.7. Testing your CGI script

Unfortunately, a CGI script will generally not run when you try it from the command line, and a script that works perfectly from the command line may fail mysteriously when run from the server. There’s one reason why you should still test your script from the command line: if it contains a syntax error, the Python interpreter won’t execute it at all, and the HTTP server will most likely send a cryptic error to the client.

Assuming your script has no syntax errors, yet it does not work, you have no choice but to read the next section.

21.2.8. Debugging CGI scripts

First of all, check for trivial installation errors — reading the section above on installing your CGI script carefully can save you a lot of time. If you wonder whether you have understood the installation procedure correctly, try installing a copy of this module file (cgi.py) as a CGI script. When invoked as a script, the file will dump its environment and the contents of the form in HTML form. Give it the right mode etc, and send it a request. If it’s installed in the standard cgi-bin directory, it should be possible to send it a request by entering a URL into your browser of the form:

http://yourhostname/cgi-bin/cgi.py?name=Joe+Blow&addr=At+Home

If this gives an error of type 404, the server cannot find the script – perhaps you need to install it in a different directory. If it gives another error, there’s an installation problem that you should fix before trying to go any further. If you get a nicely formatted listing of the environment and form content (in this example, the fields should be listed as « addr » with value « At Home » and « name » with value « Joe Blow »), the cgi.py script has been installed correctly. If you follow the same procedure for your own script, you should now be able to debug it.

The next step could be to call the cgi module’s test() function from your script: replace its main code with the single statement

cgi.test()

This should produce the same results as those gotten from installing the cgi.py file itself.

When an ordinary Python script raises an unhandled exception (for whatever reason: of a typo in a module name, a file that can’t be opened, etc.), the Python interpreter prints a nice traceback and exits. While the Python interpreter will still do this when your CGI script raises an exception, most likely the traceback will end up in one of the HTTP server’s log files, or be discarded altogether.

Fortunately, once you have managed to get your script to execute some code, you can easily send tracebacks to the Web browser using the cgitb module. If you haven’t done so already, just add the lines:

import cgitb
cgitb.enable()

to the top of your script. Then try running it again; when a problem occurs, you should see a detailed report that will likely make apparent the cause of the crash.

If you suspect that there may be a problem in importing the cgitb module, you can use an even more robust approach (which only uses built-in modules):

import sys
sys.stderr = sys.stdout
print("Content-Type: text/plain")
print()
...your code here...

This relies on the Python interpreter to print the traceback. The content type of the output is set to plain text, which disables all HTML processing. If your script works, the raw HTML will be displayed by your client. If it raises an exception, most likely after the first two lines have been printed, a traceback will be displayed. Because no HTML interpretation is going on, the traceback will be readable.

21.2.9. Common problems and solutions

Most HTTP servers buffer the output from CGI scripts until the script is completed. This means that it is not possible to display a progress report on the client’s display while the script is running.

Check the installation instructions above.

Check the HTTP server’s log files. (tail -f logfile in a separate window may be useful!)

Always check a script for syntax errors first, by doing something like python script.py.

If your script does not have any syntax errors, try adding import cgitb; cgitb.enable() to the top of the script.

When invoking external programs, make sure they can be found. Usually, this means using absolute path names — PATH is usually not set to a very useful value in a CGI script.

When reading or writing external files, make sure they can be read or written by the userid under which your CGI script will be running: this is typically the userid under which the web server is running, or some explicitly specified userid for a web server’s suexec feature.

Don’t try to give a CGI script a set-uid mode. This doesn’t work on most systems, and is a security liability as well.

Notes

1

Note that some recent versions of the HTML specification do state what order the field values should be supplied in, but knowing whether a request was received from a conforming browser, or even from a browser at all, is tedious and error-prone.

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21.3. cgitb — Gestionnaire d’exceptions pour les scripts CGI

Code source : Lib/cgitb.py [https://github.com/python/cpython/tree/3.6/Lib/cgitb.py]

Le module cgitb fournit un gestionnaire d’exceptions spécifique pour les scripts Python. (Son nom est trompeur : Il a été conçu à l’origine pour afficher des pile d’appels en HTML pour les scripts CGI, puis a été généralisé par la suite pour afficher cette information en texte brut.) Une fois ce module activé, si une exception remonte jusqu’à l’interpréteur, un rapport détaillé sera affiché. Le rapport affiche la pile d’appels, montrant des extraits de code pour chaque niveau, ainsi que les arguments et les variables locales des fonctions appelantes pour vous aider à résoudre le problème. Il est aussi possible de sauvegarder cette information dans un fichier plutôt que de l’envoyer dans le navigateur.

Pour activer cette fonctionnalité, ajoutez simplement ceci au début de votre script CGI :

import cgitb
cgitb.enable()

Les paramètres optionnels de la fonction enable() permettent de choisir si le rapport est envoyé au navigateur ou si le rapport est écrit dans un fichier pour analyse ultérieure.

cgitb.enable(display=1, logdir=None, context=5, format="html")

Appeler cette fonction remplace le gestionnaire d’exceptions par défaut de l’interpréteur par celui du module cgitb, en configurant sys.excepthook.

Le paramètre optionnel display vaut 1 par défaut, et peut être mis à 0 pour désactiver l’envoi des piles d’appels au navigateur. Si l’argument logdir est donné les piles d’appels seront écrites dans des fichiers placés dans le dossier logdir. L’argument optionnel context est le nombre de lignes de code à afficher autour de la ligne courante dans le code source à chaque niveau de la pile d’appel, il vaut 5 par défaut. Si l’argument optionnel format est "html", le rapport sera rédigé en HTML. Le rapport sera écrit en texte brut pour toute autre valeur. La valeur par défaut est "html".

cgitb.handler(info=None)

Cette fonction gère les exceptions en utilisant la configuration par défaut (c’est à dire envoyer un rapport HTML au navigateur sans l’enregistrer dans un fichier). Il peut être utilisé lorsque vous avez attrapé une exception et que vous en voulez un rapport généré par cgitb. L’argument optionnel info doit être un tuple de trois éléments contenant le type de l’exception, l’exception, et la pile d’appels, tel que le tuple renvoyé par sys.exc_info(). Si l’argument info n’est pas donné, l’exception courante est obtenue via sys.exc_info().

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21.4. wsgiref — Outils et implémentation de référence de WSGI

WSGI (Web Server Gateway Interface) est une interface standard entre le serveur web et une application web écrite en Python. Avoir une interface standardisée permet de faciliter l’usage de ces applications avec un certain nombre de serveurs web différents.

Seules les personnes programmant des serveurs web et des cadriciels ont besoin de connaître les détails d’implémentation et les cas particuliers de l’architecture de WSGI. En tant qu’utilisateur WSGI vous avez uniquement besoin d’installer WSGI ou d’utiliser un cadriciel existant.

wsgiref est une implémentation de référence de la spécification WSGI qui peut être utilisée pour ajouter la prise en charge de WSGI par un serveur web ou par un cadriciel. Elle fournit des outils pour manipuler les variables d’environnement WSGI, les en-têtes de réponse, les classes de base pour implémenter des serveurs WSGI, un serveur de démonstration d’application WSGI et un outil de validation qui vérifie que les serveurs et les applications WSGI sont conformes à la spécification WSGI (PEP 3333 [https://www.python.org/dev/peps/pep-3333]).

See https://wsgi.readthedocs.org/ for more information about WSGI, and links to tutorials and other resources.

21.4.1. wsgiref.util — outils pour les environnements WSGI

Ce module fournit un certain nombre de fonctions pour manipuler des environnements WSGI. Un environnement WSGI est un dictionnaire contenant les variables de la requête HTTP comme décrit dans la PEP 3333 [https://www.python.org/dev/peps/pep-3333]. Toutes les fonctions ayant comme argument environ s’attendent à ce qu’un dictionnaire compatible WSGI soit fourni ; voir la PEP 3333 [https://www.python.org/dev/peps/pep-3333] pour la spécification détaillée.

wsgiref.util.guess_scheme(environ)

Tente de déterminer s’il faut assigner « http » ou « https » à wsgi.url_sheme, en vérifiant si une variable d’environnement HTTPS est dans le dictionnaire environ. La valeur renvoyée est une chaîne de caractères.

This function is useful when creating a gateway that wraps CGI or a CGI-like protocol such as FastCGI. Typically, servers providing such protocols will include a HTTPS variable with a value of « 1 » « yes », or « on » when a request is received via SSL. So, this function returns « https » if such a value is found, and « http » otherwise.

wsgiref.util.request_uri(environ, include_query=True)

Return the full request URI, optionally including the query string, using the algorithm found in the « URL Reconstruction » section of PEP 3333 [https://www.python.org/dev/peps/pep-3333]. If include_query is false, the query string is not included in the resulting URI.

wsgiref.util.application_uri(environ)

Similar to request_uri(), except that the PATH_INFO and QUERY_STRING variables are ignored. The result is the base URI of the application object addressed by the request.

wsgiref.util.shift_path_info(environ)

Shift a single name from PATH_INFO to SCRIPT_NAME and return the name. The environ dictionary is modified in-place; use a copy if you need to keep the original PATH_INFO or SCRIPT_NAME intact.

If there are no remaining path segments in PATH_INFO, None is returned.

Typically, this routine is used to process each portion of a request URI path, for example to treat the path as a series of dictionary keys. This routine modifies the passed-in environment to make it suitable for invoking another WSGI application that is located at the target URI. For example, if there is a WSGI application at /foo, and the request URI path is /foo/bar/baz, and the WSGI application at /foo calls shift_path_info(), it will receive the string « bar », and the environment will be updated to be suitable for passing to a WSGI application at /foo/bar. That is, SCRIPT_NAME will change from /foo to /foo/bar, and PATH_INFO will change from /bar/baz to /baz.

When PATH_INFO is just a « / », this routine returns an empty string and appends a trailing slash to SCRIPT_NAME, even though empty path segments are normally ignored, and SCRIPT_NAME doesn’t normally end in a slash. This is intentional behavior, to ensure that an application can tell the difference between URIs ending in /x from ones ending in /x/ when using this routine to do object traversal.

wsgiref.util.setup_testing_defaults(environ)

Met à jour environ avec des valeurs par défaut pour des cas de tests.

Cette fonction ajoute des paramètres requis pour WSGI, en particulier HTTP_HOST, SERVER_NAME, SERVER_PORT, REQUEST_METHOD, SCRIPT_NAME, PATH_INFO et toutes les autres variables WSGI définies dans la PEP 3333 [https://www.python.org/dev/peps/pep-3333]. Elle ne fournit que des valeurs par défaut sans toucher aux valeurs déjà définies de ces variables.

Cette fonction a pour but de faciliter les tests unitaires des serveurs et des applications WSGI dans des environnements factices. Elle ne devrait pas être utilisée dans une application ou un serveur WSGI, étant donné que les données sont factices !

Exemple d’utilisation :

from wsgiref.util import setup_testing_defaults
from wsgiref.simple_server import make_server

# A relatively simple WSGI application. It's going to print out the
# environment dictionary after being updated by setup_testing_defaults
def simple_app(environ, start_response):
    setup_testing_defaults(environ)

    status = '200 OK'
    headers = [('Content-type', 'text/plain; charset=utf-8')]

    start_response(status, headers)

    ret = [("%s: %s\n" % (key, value)).encode("utf-8")
           for key, value in environ.items()]
    return ret

with make_server('', 8000, simple_app) as httpd:
    print("Serving on port 8000...")
    httpd.serve_forever()

In addition to the environment functions above, the wsgiref.util module also provides these miscellaneous utilities:

wsgiref.util.is_hop_by_hop(header_name)

Return true if “header_name” is an HTTP/1.1 « Hop-by-Hop » header, as defined by RFC 2616 [https://tools.ietf.org/html/rfc2616.html].

class wsgiref.util.FileWrapper(filelike, blksize=8192)

A wrapper to convert a file-like object to an iterator. The resulting objects support both __getitem__() and __iter__() iteration styles, for compatibility with Python 2.1 and Jython. As the object is iterated over, the optional blksize parameter will be repeatedly passed to the filelike object’s read() method to obtain bytestrings to yield. When read() returns an empty bytestring, iteration is ended and is not resumable.

If filelike has a close() method, the returned object will also have a close() method, and it will invoke the filelike object’s close() method when called.

Exemple d’utilisation :

from io import StringIO
from wsgiref.util import FileWrapper

# We're using a StringIO-buffer for as the file-like object
filelike = StringIO("This is an example file-like object"*10)
wrapper = FileWrapper(filelike, blksize=5)

for chunk in wrapper:
    print(chunk)

21.4.2. wsgiref.headers – WSGI response header tools

This module provides a single class, Headers, for convenient manipulation of WSGI response headers using a mapping-like interface.

class wsgiref.headers.Headers([headers])

Create a mapping-like object wrapping headers, which must be a list of header name/value tuples as described in PEP 3333 [https://www.python.org/dev/peps/pep-3333]. The default value of headers is an empty list.

Headers objects support typical mapping operations including __getitem__(), get(), __setitem__(), setdefault(), __delitem__() and __contains__(). For each of these methods, the key is the header name (treated case-insensitively), and the value is the first value associated with that header name. Setting a header deletes any existing values for that header, then adds a new value at the end of the wrapped header list. Headers” existing order is generally maintained, with new headers added to the end of the wrapped list.

Unlike a dictionary, Headers objects do not raise an error when you try to get or delete a key that isn’t in the wrapped header list. Getting a nonexistent header just returns None, and deleting a nonexistent header does nothing.

Headers objects also support keys(), values(), and items() methods. The lists returned by keys() and items() can include the same key more than once if there is a multi-valued header. The len() of a Headers object is the same as the length of its items(), which is the same as the length of the wrapped header list. In fact, the items() method just returns a copy of the wrapped header list.

Calling bytes() on a Headers object returns a formatted bytestring suitable for transmission as HTTP response headers. Each header is placed on a line with its value, separated by a colon and a space. Each line is terminated by a carriage return and line feed, and the bytestring is terminated with a blank line.

In addition to their mapping interface and formatting features, Headers objects also have the following methods for querying and adding multi-valued headers, and for adding headers with MIME parameters:

get_all(name)

Renvoie une liste de toutes les valeurs pour l’en-tête name.

The returned list will be sorted in the order they appeared in the original header list or were added to this instance, and may contain duplicates. Any fields deleted and re-inserted are always appended to the header list. If no fields exist with the given name, returns an empty list.

add_header(name, value, **_params)

Add a (possibly multi-valued) header, with optional MIME parameters specified via keyword arguments.

name is the header field to add. Keyword arguments can be used to set MIME parameters for the header field. Each parameter must be a string or None. Underscores in parameter names are converted to dashes, since dashes are illegal in Python identifiers, but many MIME parameter names include dashes. If the parameter value is a string, it is added to the header value parameters in the form name="value". If it is None, only the parameter name is added. (This is used for MIME parameters without a value.) Example usage:

h.add_header('content-disposition', 'attachment', filename='bud.gif')

Le code ci-dessus ajoute un en-tête qui ressemble à ceci :

Content-Disposition: attachment; filename="bud.gif"

Modifié dans la version 3.5: Le paramètre headers est optionnel.

21.4.3. wsgiref.simple_server – a simple WSGI HTTP server

This module implements a simple HTTP server (based on http.server) that serves WSGI applications. Each server instance serves a single WSGI application on a given host and port. If you want to serve multiple applications on a single host and port, you should create a WSGI application that parses PATH_INFO to select which application to invoke for each request. (E.g., using the shift_path_info() function from wsgiref.util.)

wsgiref.simple_server.make_server(host, port, app, server_class=WSGIServer, handler_class=WSGIRequestHandler)

Create a new WSGI server listening on host and port, accepting connections for app. The return value is an instance of the supplied server_class, and will process requests using the specified handler_class. app must be a WSGI application object, as defined by PEP 3333 [https://www.python.org/dev/peps/pep-3333].

Exemple d’utilisation :

from wsgiref.simple_server import make_server, demo_app

with make_server('', 8000, demo_app) as httpd:
    print("Serving HTTP on port 8000...")

    # Respond to requests until process is killed
    httpd.serve_forever()

    # Alternative: serve one request, then exit
    httpd.handle_request()

wsgiref.simple_server.demo_app(environ, start_response)

This function is a small but complete WSGI application that returns a text page containing the message « Hello world! » and a list of the key/value pairs provided in the environ parameter. It’s useful for verifying that a WSGI server (such as wsgiref.simple_server) is able to run a simple WSGI application correctly.

class wsgiref.simple_server.WSGIServer(server_address, RequestHandlerClass)

Create a WSGIServer instance. server_address should be a (host,port) tuple, and RequestHandlerClass should be the subclass of http.server.BaseHTTPRequestHandler that will be used to process requests.

You do not normally need to call this constructor, as the make_server() function can handle all the details for you.

WSGIServer is a subclass of http.server.HTTPServer, so all of its methods (such as serve_forever() and handle_request()) are available. WSGIServer also provides these WSGI-specific methods:

set_app(application)

Sets the callable application as the WSGI application that will receive requests.

get_app()

Returns the currently-set application callable.

Normally, however, you do not need to use these additional methods, as set_app() is normally called by make_server(), and the get_app() exists mainly for the benefit of request handler instances.

class wsgiref.simple_server.WSGIRequestHandler(request, client_address, server)

Create an HTTP handler for the given request (i.e. a socket), client_address (a (host,port) tuple), and server (WSGIServer instance).

You do not need to create instances of this class directly; they are automatically created as needed by WSGIServer objects. You can, however, subclass this class and supply it as a handler_class to the make_server() function. Some possibly relevant methods for overriding in subclasses:

get_environ()

Returns a dictionary containing the WSGI environment for a request. The default implementation copies the contents of the WSGIServer object’s base_environ dictionary attribute and then adds various headers derived from the HTTP request. Each call to this method should return a new dictionary containing all of the relevant CGI environment variables as specified in PEP 3333 [https://www.python.org/dev/peps/pep-3333].

get_stderr()

Return the object that should be used as the wsgi.errors stream. The default implementation just returns sys.stderr.

handle()

Process the HTTP request. The default implementation creates a handler instance using a wsgiref.handlers class to implement the actual WSGI application interface.

21.4.4. wsgiref.validate — WSGI conformance checker

When creating new WSGI application objects, frameworks, servers, or middleware, it can be useful to validate the new code’s conformance using wsgiref.validate. This module provides a function that creates WSGI application objects that validate communications between a WSGI server or gateway and a WSGI application object, to check both sides for protocol conformance.

Note that this utility does not guarantee complete PEP 3333 [https://www.python.org/dev/peps/pep-3333] compliance; an absence of errors from this module does not necessarily mean that errors do not exist. However, if this module does produce an error, then it is virtually certain that either the server or application is not 100% compliant.

This module is based on the paste.lint module from Ian Bicking’s « Python Paste » library.

wsgiref.validate.validator(application)

Wrap application and return a new WSGI application object. The returned application will forward all requests to the original application, and will check that both the application and the server invoking it are conforming to the WSGI specification and to RFC 2616 [https://tools.ietf.org/html/rfc2616.html].

Any detected nonconformance results in an AssertionError being raised; note, however, that how these errors are handled is server-dependent. For example, wsgiref.simple_server and other servers based on wsgiref.handlers (that don’t override the error handling methods to do something else) will simply output a message that an error has occurred, and dump the traceback to sys.stderr or some other error stream.

This wrapper may also generate output using the warnings module to indicate behaviors that are questionable but which may not actually be prohibited by PEP 3333 [https://www.python.org/dev/peps/pep-3333]. Unless they are suppressed using Python command-line options or the warnings API, any such warnings will be written to sys.stderr (not wsgi.errors, unless they happen to be the same object).

Exemple d’utilisation :

from wsgiref.validate import validator
from wsgiref.simple_server import make_server

# Our callable object which is intentionally not compliant to the
# standard, so the validator is going to break
def simple_app(environ, start_response):
    status = '200 OK'  # HTTP Status
    headers = [('Content-type', 'text/plain')]  # HTTP Headers
    start_response(status, headers)

    # This is going to break because we need to return a list, and
    # the validator is going to inform us
    return b"Hello World"

# This is the application wrapped in a validator
validator_app = validator(simple_app)

with make_server('', 8000, validator_app) as httpd:
    print("Listening on port 8000....")
    httpd.serve_forever()

21.4.5. wsgiref.handlers – server/gateway base classes

This module provides base handler classes for implementing WSGI servers and gateways. These base classes handle most of the work of communicating with a WSGI application, as long as they are given a CGI-like environment, along with input, output, and error streams.

class wsgiref.handlers.CGIHandler

CGI-based invocation via sys.stdin, sys.stdout, sys.stderr and os.environ. This is useful when you have a WSGI application and want to run it as a CGI script. Simply invoke CGIHandler().run(app), where app is the WSGI application object you wish to invoke.

This class is a subclass of BaseCGIHandler that sets wsgi.run_once to true, wsgi.multithread to false, and wsgi.multiprocess to true, and always uses sys and os to obtain the necessary CGI streams and environment.

class wsgiref.handlers.IISCGIHandler

A specialized alternative to CGIHandler, for use when deploying on Microsoft’s IIS web server, without having set the config allowPathInfo option (IIS>=7) or metabase allowPathInfoForScriptMappings (IIS<7).

By default, IIS gives a PATH_INFO that duplicates the SCRIPT_NAME at the front, causing problems for WSGI applications that wish to implement routing. This handler strips any such duplicated path.

IIS can be configured to pass the correct PATH_INFO, but this causes another bug where PATH_TRANSLATED is wrong. Luckily this variable is rarely used and is not guaranteed by WSGI. On IIS<7, though, the setting can only be made on a vhost level, affecting all other script mappings, many of which break when exposed to the PATH_TRANSLATED bug. For this reason IIS<7 is almost never deployed with the fix. (Even IIS7 rarely uses it because there is still no UI for it.)

There is no way for CGI code to tell whether the option was set, so a separate handler class is provided. It is used in the same way as CGIHandler, i.e., by calling IISCGIHandler().run(app), where app is the WSGI application object you wish to invoke.

Nouveau dans la version 3.2.

class wsgiref.handlers.BaseCGIHandler(stdin, stdout, stderr, environ, multithread=True, multiprocess=False)

Similar to CGIHandler, but instead of using the sys and os modules, the CGI environment and I/O streams are specified explicitly. The multithread and multiprocess values are used to set the wsgi.multithread and wsgi.multiprocess flags for any applications run by the handler instance.

This class is a subclass of SimpleHandler intended for use with software other than HTTP « origin servers ». If you are writing a gateway protocol implementation (such as CGI, FastCGI, SCGI, etc.) that uses a Status: header to send an HTTP status, you probably want to subclass this instead of SimpleHandler.

class wsgiref.handlers.SimpleHandler(stdin, stdout, stderr, environ, multithread=True, multiprocess=False)

Similar to BaseCGIHandler, but designed for use with HTTP origin servers. If you are writing an HTTP server implementation, you will probably want to subclass this instead of BaseCGIHandler.

This class is a subclass of BaseHandler. It overrides the __init__(), get_stdin(), get_stderr(), add_cgi_vars(), _write(), and _flush() methods to support explicitly setting the environment and streams via the constructor. The supplied environment and streams are stored in the stdin, stdout, stderr, and environ attributes.

The write() method of stdout should write each chunk in full, like io.BufferedIOBase.

class wsgiref.handlers.BaseHandler

This is an abstract base class for running WSGI applications. Each instance will handle a single HTTP request, although in principle you could create a subclass that was reusable for multiple requests.

BaseHandler instances have only one method intended for external use:

run(app)

Run the specified WSGI application, app.

All of the other BaseHandler methods are invoked by this method in the process of running the application, and thus exist primarily to allow customizing the process.

The following methods MUST be overridden in a subclass:

_write(data)

Buffer the bytes data for transmission to the client. It’s okay if this method actually transmits the data; BaseHandler just separates write and flush operations for greater efficiency when the underlying system actually has such a distinction.

_flush()

Force buffered data to be transmitted to the client. It’s okay if this method is a no-op (i.e., if _write() actually sends the data).

get_stdin()

Return an input stream object suitable for use as the wsgi.input of the request currently being processed.

get_stderr()

Return an output stream object suitable for use as the wsgi.errors of the request currently being processed.

add_cgi_vars()

Insert CGI variables for the current request into the environ attribute.

Here are some other methods and attributes you may wish to override. This list is only a summary, however, and does not include every method that can be overridden. You should consult the docstrings and source code for additional information before attempting to create a customized BaseHandler subclass.

Attributes and methods for customizing the WSGI environment:

wsgi_multithread

The value to be used for the wsgi.multithread environment variable. It defaults to true in BaseHandler, but may have a different default (or be set by the constructor) in the other subclasses.

wsgi_multiprocess

The value to be used for the wsgi.multiprocess environment variable. It defaults to true in BaseHandler, but may have a different default (or be set by the constructor) in the other subclasses.

wsgi_run_once

The value to be used for the wsgi.run_once environment variable. It defaults to false in BaseHandler, but CGIHandler sets it to true by default.

os_environ

The default environment variables to be included in every request’s WSGI environment. By default, this is a copy of os.environ at the time that wsgiref.handlers was imported, but subclasses can either create their own at the class or instance level. Note that the dictionary should be considered read-only, since the default value is shared between multiple classes and instances.

server_software

If the origin_server attribute is set, this attribute’s value is used to set the default SERVER_SOFTWARE WSGI environment variable, and also to set a default Server: header in HTTP responses. It is ignored for handlers (such as BaseCGIHandler and CGIHandler) that are not HTTP origin servers.

Modifié dans la version 3.3: The term « Python » is replaced with implementation specific term like « CPython », « Jython » etc.

get_scheme()

Return the URL scheme being used for the current request. The default implementation uses the guess_scheme() function from wsgiref.util to guess whether the scheme should be « http » or « https », based on the current request’s environ variables.

setup_environ()

Set the environ attribute to a fully-populated WSGI environment. The default implementation uses all of the above methods and attributes, plus the get_stdin(), get_stderr(), and add_cgi_vars() methods and the wsgi_file_wrapper attribute. It also inserts a SERVER_SOFTWARE key if not present, as long as the origin_server attribute is a true value and the server_software attribute is set.

Methods and attributes for customizing exception handling:

log_exception(exc_info)

Log the exc_info tuple in the server log. exc_info is a (type, value, traceback) tuple. The default implementation simply writes the traceback to the request’s wsgi.errors stream and flushes it. Subclasses can override this method to change the format or retarget the output, mail the traceback to an administrator, or whatever other action may be deemed suitable.

traceback_limit

The maximum number of frames to include in tracebacks output by the default log_exception() method. If None, all frames are included.

error_output(environ, start_response)

This method is a WSGI application to generate an error page for the user. It is only invoked if an error occurs before headers are sent to the client.

This method can access the current error information using sys.exc_info(), and should pass that information to start_response when calling it (as described in the « Error Handling » section of PEP 3333 [https://www.python.org/dev/peps/pep-3333]).

The default implementation just uses the error_status, error_headers, and error_body attributes to generate an output page. Subclasses can override this to produce more dynamic error output.

Note, however, that it’s not recommended from a security perspective to spit out diagnostics to any old user; ideally, you should have to do something special to enable diagnostic output, which is why the default implementation doesn’t include any.

error_status

The HTTP status used for error responses. This should be a status string as defined in PEP 3333 [https://www.python.org/dev/peps/pep-3333]; it defaults to a 500 code and message.

error_headers

The HTTP headers used for error responses. This should be a list of WSGI response headers ((name, value) tuples), as described in PEP 3333 [https://www.python.org/dev/peps/pep-3333]. The default list just sets the content type to text/plain.

error_body

The error response body. This should be an HTTP response body bytestring. It defaults to the plain text, « A server error occurred. Please contact the administrator. »

Methods and attributes for PEP 3333 [https://www.python.org/dev/peps/pep-3333]’s « Optional Platform-Specific File Handling » feature:

wsgi_file_wrapper

A wsgi.file_wrapper factory, or None. The default value of this attribute is the wsgiref.util.FileWrapper class.

sendfile()

Override to implement platform-specific file transmission. This method is called only if the application’s return value is an instance of the class specified by the wsgi_file_wrapper attribute. It should return a true value if it was able to successfully transmit the file, so that the default transmission code will not be executed. The default implementation of this method just returns a false value.

Miscellaneous methods and attributes:

origin_server

This attribute should be set to a true value if the handler’s _write() and _flush() are being used to communicate directly to the client, rather than via a CGI-like gateway protocol that wants the HTTP status in a special Status: header.

This attribute’s default value is true in BaseHandler, but false in BaseCGIHandler and CGIHandler.

http_version

If origin_server is true, this string attribute is used to set the HTTP version of the response set to the client. It defaults to "1.0".

wsgiref.handlers.read_environ()

Transcode CGI variables from os.environ to PEP 3333 « bytes in unicode » strings, returning a new dictionary. This function is used by CGIHandler and IISCGIHandler in place of directly using os.environ, which is not necessarily WSGI-compliant on all platforms and web servers using Python 3 – specifically, ones where the OS’s actual environment is Unicode (i.e. Windows), or ones where the environment is bytes, but the system encoding used by Python to decode it is anything other than ISO-8859-1 (e.g. Unix systems using UTF-8).

If you are implementing a CGI-based handler of your own, you probably want to use this routine instead of just copying values out of os.environ directly.

Nouveau dans la version 3.2.

21.4.6. Exemples

This is a working « Hello World » WSGI application:

from wsgiref.simple_server import make_server

# Every WSGI application must have an application object - a callable
# object that accepts two arguments. For that purpose, we're going to
# use a function (note that you're not limited to a function, you can
# use a class for example). The first argument passed to the function
# is a dictionary containing CGI-style environment variables and the
# second variable is the callable object (see PEP 333).
def hello_world_app(environ, start_response):
    status = '200 OK'  # HTTP Status
    headers = [('Content-type', 'text/plain; charset=utf-8')]  # HTTP Headers
    start_response(status, headers)

    # The returned object is going to be printed
    return [b"Hello World"]

with make_server('', 8000, hello_world_app) as httpd:
    print("Serving on port 8000...")

    # Serve until process is killed
    httpd.serve_forever()

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21.5. urllib — Modules de gestion des URLs

Code source : Lib/urllib/ [https://github.com/python/cpython/tree/3.6/Lib/urllib/]

urllib est un paquet qui collecte plusieurs modules travaillant avec les URLs :

urllib.request pour ouvrir et lire des URLs ;

urllib.error contenant les exceptions levées par urllib.request ;

urllib.parse pour analyser les URLs ;

urllib.robotparser pour analyser les fichiers robots.txt.

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21.6. urllib.request — Extensible library for opening URLs

Source code: Lib/urllib/request.py [https://github.com/python/cpython/tree/3.6/Lib/urllib/request.py]

The urllib.request module defines functions and classes which help in opening URLs (mostly HTTP) in a complex world — basic and digest authentication, redirections, cookies and more.

Voir aussi

The Requests package [http://docs.python-requests.org/] is recommended for a higher-level HTTP client interface.

The urllib.request module defines the following functions:

urllib.request.urlopen(url, data=None, [timeout, ]*, cafile=None, capath=None, cadefault=False, context=None)

Open the URL url, which can be either a string or a Request object.

data must be an object specifying additional data to be sent to the server, or None if no such data is needed. See Request for details.

urllib.request module uses HTTP/1.1 and includes Connection:close header in its HTTP requests.

The optional timeout parameter specifies a timeout in seconds for blocking operations like the connection attempt (if not specified, the global default timeout setting will be used). This actually only works for HTTP, HTTPS and FTP connections.

If context is specified, it must be a ssl.SSLContext instance describing the various SSL options. See HTTPSConnection for more details.

The optional cafile and capath parameters specify a set of trusted CA certificates for HTTPS requests. cafile should point to a single file containing a bundle of CA certificates, whereas capath should point to a directory of hashed certificate files. More information can be found in ssl.SSLContext.load_verify_locations().

The cadefault parameter is ignored.

This function always returns an object which can work as a context manager and has methods such as

geturl() — return the URL of the resource retrieved, commonly used to determine if a redirect was followed

info() — return the meta-information of the page, such as headers, in the form of an email.message_from_string() instance (see Quick Reference to HTTP Headers [https://www.cs.tut.fi/~jkorpela/http.html])

getcode() – return the HTTP status code of the response.

For HTTP and HTTPS URLs, this function returns a http.client.HTTPResponse object slightly modified. In addition to the three new methods above, the msg attribute contains the same information as the reason attribute — the reason phrase returned by server — instead of the response headers as it is specified in the documentation for HTTPResponse.

For FTP, file, and data URLs and requests explicitly handled by legacy URLopener and FancyURLopener classes, this function returns a urllib.response.addinfourl object.

Raises URLError on protocol errors.

Note that None may be returned if no handler handles the request (though the default installed global OpenerDirector uses UnknownHandler to ensure this never happens).

In addition, if proxy settings are detected (for example, when a *_proxy environment variable like http_proxy is set), ProxyHandler is default installed and makes sure the requests are handled through the proxy.

The legacy urllib.urlopen function from Python 2.6 and earlier has been discontinued; urllib.request.urlopen() corresponds to the old urllib2.urlopen. Proxy handling, which was done by passing a dictionary parameter to urllib.urlopen, can be obtained by using ProxyHandler objects.

Modifié dans la version 3.2: cafile and capath were added.

Modifié dans la version 3.2: HTTPS virtual hosts are now supported if possible (that is, if ssl.HAS_SNI is true).

Nouveau dans la version 3.2: data can be an iterable object.

Modifié dans la version 3.3: cadefault was added.

Modifié dans la version 3.4.3: context was added.

Obsolète depuis la version 3.6: cafile, capath and cadefault are deprecated in favor of context. Please use ssl.SSLContext.load_cert_chain() instead, or let ssl.create_default_context() select the system’s trusted CA certificates for you.

urllib.request.install_opener(opener)

Install an OpenerDirector instance as the default global opener. Installing an opener is only necessary if you want urlopen to use that opener; otherwise, simply call OpenerDirector.open() instead of urlopen(). The code does not check for a real OpenerDirector, and any class with the appropriate interface will work.

urllib.request.build_opener([handler, ...])

Return an OpenerDirector instance, which chains the handlers in the order given. handlers can be either instances of BaseHandler, or subclasses of BaseHandler (in which case it must be possible to call the constructor without any parameters). Instances of the following classes will be in front of the handlers, unless the handlers contain them, instances of them or subclasses of them: ProxyHandler (if proxy settings are detected), UnknownHandler, HTTPHandler, HTTPDefaultErrorHandler, HTTPRedirectHandler, FTPHandler, FileHandler, HTTPErrorProcessor.

If the Python installation has SSL support (i.e., if the ssl module can be imported), HTTPSHandler will also be added.

A BaseHandler subclass may also change its handler_order attribute to modify its position in the handlers list.

urllib.request.pathname2url(path)

Convert the pathname path from the local syntax for a path to the form used in the path component of a URL. This does not produce a complete URL. The return value will already be quoted using the quote() function.

urllib.request.url2pathname(path)

Convert the path component path from a percent-encoded URL to the local syntax for a path. This does not accept a complete URL. This function uses unquote() to decode path.

urllib.request.getproxies()

This helper function returns a dictionary of scheme to proxy server URL mappings. It scans the environment for variables named <scheme>_proxy, in a case insensitive approach, for all operating systems first, and when it cannot find it, looks for proxy information from Mac OSX System Configuration for Mac OS X and Windows Systems Registry for Windows. If both lowercase and uppercase environment variables exist (and disagree), lowercase is preferred.

Note

If the environment variable REQUEST_METHOD is set, which usually indicates your script is running in a CGI environment, the environment variable HTTP_PROXY (uppercase _PROXY) will be ignored. This is because that variable can be injected by a client using the « Proxy: » HTTP header. If you need to use an HTTP proxy in a CGI environment, either use ProxyHandler explicitly, or make sure the variable name is in lowercase (or at least the _proxy suffix).

The following classes are provided:

class urllib.request.Request(url, data=None, headers={}, origin_req_host=None, unverifiable=False, method=None)

This class is an abstraction of a URL request.

url should be a string containing a valid URL.

data must be an object specifying additional data to send to the server, or None if no such data is needed. Currently HTTP requests are the only ones that use data. The supported object types include bytes, file-like objects, and iterables. If no Content-Length nor Transfer-Encoding header field has been provided, HTTPHandler will set these headers according to the type of data. Content-Length will be used to send bytes objects, while Transfer-Encoding: chunked as specified in RFC 7230 [https://tools.ietf.org/html/rfc7230.html], Section 3.3.1 will be used to send files and other iterables.

For an HTTP POST request method, data should be a buffer in the standard application/x-www-form-urlencoded format. The urllib.parse.urlencode() function takes a mapping or sequence of 2-tuples and returns an ASCII string in this format. It should be encoded to bytes before being used as the data parameter.

headers should be a dictionary, and will be treated as if add_header() was called with each key and value as arguments. This is often used to « spoof » the User-Agent header value, which is used by a browser to identify itself – some HTTP servers only allow requests coming from common browsers as opposed to scripts. For example, Mozilla Firefox may identify itself as "Mozilla/5.0 (X11; U; Linux i686) Gecko/20071127 Firefox/2.0.0.11", while urllib’s default user agent string is "Python-urllib/2.6" (on Python 2.6).

An appropriate Content-Type header should be included if the data argument is present. If this header has not been provided and data is not None, Content-Type: application/x-www-form-urlencoded will be added as a default.

The final two arguments are only of interest for correct handling of third-party HTTP cookies:

origin_req_host should be the request-host of the origin transaction, as defined by RFC 2965 [https://tools.ietf.org/html/rfc2965.html]. It defaults to http.cookiejar.request_host(self). This is the host name or IP address of the original request that was initiated by the user. For example, if the request is for an image in an HTML document, this should be the request-host of the request for the page containing the image.

unverifiable should indicate whether the request is unverifiable, as defined by RFC 2965 [https://tools.ietf.org/html/rfc2965.html]. It defaults to False. An unverifiable request is one whose URL the user did not have the option to approve. For example, if the request is for an image in an HTML document, and the user had no option to approve the automatic fetching of the image, this should be true.

method should be a string that indicates the HTTP request method that will be used (e.g. 'HEAD'). If provided, its value is stored in the method attribute and is used by get_method(). The default is 'GET' if data is None or 'POST' otherwise. Subclasses may indicate a different default method by setting the method attribute in the class itself.

Note

The request will not work as expected if the data object is unable to deliver its content more than once (e.g. a file or an iterable that can produce the content only once) and the request is retried for HTTP redirects or authentication. The data is sent to the HTTP server right away after the headers. There is no support for a 100-continue expectation in the library.

Modifié dans la version 3.3: Request.method argument is added to the Request class.

Modifié dans la version 3.4: Default Request.method may be indicated at the class level.

Modifié dans la version 3.6: Do not raise an error if the Content-Length has not been provided and data is neither None nor a bytes object. Fall back to use chunked transfer encoding instead.

class urllib.request.OpenerDirector

The OpenerDirector class opens URLs via BaseHandlers chained together. It manages the chaining of handlers, and recovery from errors.

class urllib.request.BaseHandler

This is the base class for all registered handlers — and handles only the simple mechanics of registration.

class urllib.request.HTTPDefaultErrorHandler

A class which defines a default handler for HTTP error responses; all responses are turned into HTTPError exceptions.

class urllib.request.HTTPRedirectHandler

A class to handle redirections.

class urllib.request.HTTPCookieProcessor(cookiejar=None)

A class to handle HTTP Cookies.

class urllib.request.ProxyHandler(proxies=None)

Cause requests to go through a proxy. If proxies is given, it must be a dictionary mapping protocol names to URLs of proxies. The default is to read the list of proxies from the environment variables <protocol>_proxy. If no proxy environment variables are set, then in a Windows environment proxy settings are obtained from the registry’s Internet Settings section, and in a Mac OS X environment proxy information is retrieved from the OS X System Configuration Framework.

To disable autodetected proxy pass an empty dictionary.

The no_proxy environment variable can be used to specify hosts which shouldn’t be reached via proxy; if set, it should be a comma-separated list of hostname suffixes, optionally with :port appended, for example cern.ch,ncsa.uiuc.edu,some.host:8080.

Note

HTTP_PROXY will be ignored if a variable REQUEST_METHOD is set; see the documentation on getproxies().

class urllib.request.HTTPPasswordMgr

Keep a database of (realm, uri) -> (user, password) mappings.

class urllib.request.HTTPPasswordMgrWithDefaultRealm

Keep a database of (realm, uri) -> (user, password) mappings. A realm of None is considered a catch-all realm, which is searched if no other realm fits.

class urllib.request.HTTPPasswordMgrWithPriorAuth

A variant of HTTPPasswordMgrWithDefaultRealm that also has a database of uri -> is_authenticated mappings. Can be used by a BasicAuth handler to determine when to send authentication credentials immediately instead of waiting for a 401 response first.

Nouveau dans la version 3.5.

class urllib.request.AbstractBasicAuthHandler(password_mgr=None)

This is a mixin class that helps with HTTP authentication, both to the remote host and to a proxy. password_mgr, if given, should be something that is compatible with HTTPPasswordMgr; refer to section HTTPPasswordMgr Objects for information on the interface that must be supported. If passwd_mgr also provides is_authenticated and update_authenticated methods (see HTTPPasswordMgrWithPriorAuth Objects), then the handler will use the is_authenticated result for a given URI to determine whether or not to send authentication credentials with the request. If is_authenticated returns True for the URI, credentials are sent. If is_authenticated is False, credentials are not sent, and then if a 401 response is received the request is re-sent with the authentication credentials. If authentication succeeds, update_authenticated is called to set is_authenticated True for the URI, so that subsequent requests to the URI or any of its super-URIs will automatically include the authentication credentials.

Nouveau dans la version 3.5: Added is_authenticated support.

class urllib.request.HTTPBasicAuthHandler(password_mgr=None)

Handle authentication with the remote host. password_mgr, if given, should be something that is compatible with HTTPPasswordMgr; refer to section HTTPPasswordMgr Objects for information on the interface that must be supported. HTTPBasicAuthHandler will raise a ValueError when presented with a wrong Authentication scheme.

class urllib.request.ProxyBasicAuthHandler(password_mgr=None)

Handle authentication with the proxy. password_mgr, if given, should be something that is compatible with HTTPPasswordMgr; refer to section HTTPPasswordMgr Objects for information on the interface that must be supported.

class urllib.request.AbstractDigestAuthHandler(password_mgr=None)

This is a mixin class that helps with HTTP authentication, both to the remote host and to a proxy. password_mgr, if given, should be something that is compatible with HTTPPasswordMgr; refer to section HTTPPasswordMgr Objects for information on the interface that must be supported.

class urllib.request.HTTPDigestAuthHandler(password_mgr=None)

Handle authentication with the remote host. password_mgr, if given, should be something that is compatible with HTTPPasswordMgr; refer to section HTTPPasswordMgr Objects for information on the interface that must be supported. When both Digest Authentication Handler and Basic Authentication Handler are both added, Digest Authentication is always tried first. If the Digest Authentication returns a 40x response again, it is sent to Basic Authentication handler to Handle. This Handler method will raise a ValueError when presented with an authentication scheme other than Digest or Basic.

Modifié dans la version 3.3: Raise ValueError on unsupported Authentication Scheme.

class urllib.request.ProxyDigestAuthHandler(password_mgr=None)

Handle authentication with the proxy. password_mgr, if given, should be something that is compatible with HTTPPasswordMgr; refer to section HTTPPasswordMgr Objects for information on the interface that must be supported.

class urllib.request.HTTPHandler

A class to handle opening of HTTP URLs.

class urllib.request.HTTPSHandler(debuglevel=0, context=None, check_hostname=None)

A class to handle opening of HTTPS URLs. context and check_hostname have the same meaning as in http.client.HTTPSConnection.

Modifié dans la version 3.2: context and check_hostname were added.

class urllib.request.FileHandler

Open local files.

class urllib.request.DataHandler

Open data URLs.

Nouveau dans la version 3.4.

class urllib.request.FTPHandler

Open FTP URLs.

class urllib.request.CacheFTPHandler

Open FTP URLs, keeping a cache of open FTP connections to minimize delays.

class urllib.request.UnknownHandler

A catch-all class to handle unknown URLs.

class urllib.request.HTTPErrorProcessor

Process HTTP error responses.

21.6.1. Request Objects

The following methods describe Request’s public interface, and so all may be overridden in subclasses. It also defines several public attributes that can be used by clients to inspect the parsed request.

Request.full_url

The original URL passed to the constructor.

Modifié dans la version 3.4.

Request.full_url is a property with setter, getter and a deleter. Getting full_url returns the original request URL with the fragment, if it was present.

Request.type

The URI scheme.

Request.host

The URI authority, typically a host, but may also contain a port separated by a colon.

Request.origin_req_host

The original host for the request, without port.

Request.selector

The URI path. If the Request uses a proxy, then selector will be the full URL that is passed to the proxy.

Request.data

The entity body for the request, or None if not specified.

Modifié dans la version 3.4: Changing value of Request.data now deletes « Content-Length » header if it was previously set or calculated.

Request.unverifiable

boolean, indicates whether the request is unverifiable as defined by RFC 2965 [https://tools.ietf.org/html/rfc2965.html].

Request.method

The HTTP request method to use. By default its value is None, which means that get_method() will do its normal computation of the method to be used. Its value can be set (thus overriding the default computation in get_method()) either by providing a default value by setting it at the class level in a Request subclass, or by passing a value in to the Request constructor via the method argument.

Nouveau dans la version 3.3.

Modifié dans la version 3.4: A default value can now be set in subclasses; previously it could only be set via the constructor argument.

Request.get_method()

Return a string indicating the HTTP request method. If Request.method is not None, return its value, otherwise return 'GET' if Request.data is None, or 'POST' if it’s not. This is only meaningful for HTTP requests.

Modifié dans la version 3.3: get_method now looks at the value of Request.method.

Request.add_header(key, val)

Add another header to the request. Headers are currently ignored by all handlers except HTTP handlers, where they are added to the list of headers sent to the server. Note that there cannot be more than one header with the same name, and later calls will overwrite previous calls in case the key collides. Currently, this is no loss of HTTP functionality, since all headers which have meaning when used more than once have a (header-specific) way of gaining the same functionality using only one header.

Request.add_unredirected_header(key, header)

Add a header that will not be added to a redirected request.

Request.has_header(header)

Return whether the instance has the named header (checks both regular and unredirected).

Request.remove_header(header)

Remove named header from the request instance (both from regular and unredirected headers).

Nouveau dans la version 3.4.

Request.get_full_url()

Return the URL given in the constructor.

Modifié dans la version 3.4.

Returns Request.full_url

Request.set_proxy(host, type)

Prepare the request by connecting to a proxy server. The host and type will replace those of the instance, and the instance’s selector will be the original URL given in the constructor.

Request.get_header(header_name, default=None)

Return the value of the given header. If the header is not present, return the default value.

Request.header_items()

Return a list of tuples (header_name, header_value) of the Request headers.

Modifié dans la version 3.4: The request methods add_data, has_data, get_data, get_type, get_host, get_selector, get_origin_req_host and is_unverifiable that were deprecated since 3.3 have been removed.

21.6.2. OpenerDirector Objects

OpenerDirector instances have the following methods:

OpenerDirector.add_handler(handler)

handler should be an instance of BaseHandler. The following methods are searched, and added to the possible chains (note that HTTP errors are a special case).

protocol_open() — signal that the handler knows how to open protocol URLs.

http_error_type() — signal that the handler knows how to handle HTTP errors with HTTP error code type.

protocol_error() — signal that the handler knows how to handle errors from (non-http) protocol.

protocol_request() — signal that the handler knows how to pre-process protocol requests.

protocol_response() — signal that the handler knows how to post-process protocol responses.

OpenerDirector.open(url, data=None[, timeout])

Open the given url (which can be a request object or a string), optionally passing the given data. Arguments, return values and exceptions raised are the same as those of urlopen() (which simply calls the open() method on the currently installed global OpenerDirector). The optional timeout parameter specifies a timeout in seconds for blocking operations like the connection attempt (if not specified, the global default timeout setting will be used). The timeout feature actually works only for HTTP, HTTPS and FTP connections).

OpenerDirector.error(proto, *args)

Handle an error of the given protocol. This will call the registered error handlers for the given protocol with the given arguments (which are protocol specific). The HTTP protocol is a special case which uses the HTTP response code to determine the specific error handler; refer to the http_error_*() methods of the handler classes.

Return values and exceptions raised are the same as those of urlopen().

OpenerDirector objects open URLs in three stages:

The order in which these methods are called within each stage is determined by sorting the handler instances.

Every handler with a method named like protocol_request() has that method called to pre-process the request.

Handlers with a method named like protocol_open() are called to handle the request. This stage ends when a handler either returns a non-None value (ie. a response), or raises an exception (usually URLError). Exceptions are allowed to propagate.

In fact, the above algorithm is first tried for methods named default_open(). If all such methods return None, the algorithm is repeated for methods named like protocol_open(). If all such methods return None, the algorithm is repeated for methods named unknown_open().

Note that the implementation of these methods may involve calls of the parent OpenerDirector instance’s open() and error() methods.

Every handler with a method named like protocol_response() has that method called to post-process the response.

21.6.3. BaseHandler Objects

BaseHandler objects provide a couple of methods that are directly useful, and others that are meant to be used by derived classes. These are intended for direct use:

BaseHandler.add_parent(director)

Add a director as parent.

BaseHandler.close()

Remove any parents.

The following attribute and methods should only be used by classes derived from BaseHandler.

Note

The convention has been adopted that subclasses defining protocol_request() or protocol_response() methods are named *Processor; all others are named *Handler.

BaseHandler.parent

A valid OpenerDirector, which can be used to open using a different protocol, or handle errors.

BaseHandler.default_open(req)

This method is not defined in BaseHandler, but subclasses should define it if they want to catch all URLs.

This method, if implemented, will be called by the parent OpenerDirector. It should return a file-like object as described in the return value of the open() of OpenerDirector, or None. It should raise URLError, unless a truly exceptional thing happens (for example, MemoryError should not be mapped to URLError).

This method will be called before any protocol-specific open method.

BaseHandler.protocol_open(req)

This method is not defined in BaseHandler, but subclasses should define it if they want to handle URLs with the given protocol.

This method, if defined, will be called by the parent OpenerDirector. Return values should be the same as for default_open().

BaseHandler.unknown_open(req)

This method is not defined in BaseHandler, but subclasses should define it if they want to catch all URLs with no specific registered handler to open it.

This method, if implemented, will be called by the parent OpenerDirector. Return values should be the same as for default_open().

BaseHandler.http_error_default(req, fp, code, msg, hdrs)

This method is not defined in BaseHandler, but subclasses should override it if they intend to provide a catch-all for otherwise unhandled HTTP errors. It will be called automatically by the OpenerDirector getting the error, and should not normally be called in other circumstances.

req will be a Request object, fp will be a file-like object with the HTTP error body, code will be the three-digit code of the error, msg will be the user-visible explanation of the code and hdrs will be a mapping object with the headers of the error.

Return values and exceptions raised should be the same as those of urlopen().

BaseHandler.http_error_nnn(req, fp, code, msg, hdrs)

nnn should be a three-digit HTTP error code. This method is also not defined in BaseHandler, but will be called, if it exists, on an instance of a subclass, when an HTTP error with code nnn occurs.

Subclasses should override this method to handle specific HTTP errors.

Arguments, return values and exceptions raised should be the same as for http_error_default().

BaseHandler.protocol_request(req)

This method is not defined in BaseHandler, but subclasses should define it if they want to pre-process requests of the given protocol.

This method, if defined, will be called by the parent OpenerDirector. req will be a Request object. The return value should be a Request object.

BaseHandler.protocol_response(req, response)

This method is not defined in BaseHandler, but subclasses should define it if they want to post-process responses of the given protocol.

This method, if defined, will be called by the parent OpenerDirector. req will be a Request object. response will be an object implementing the same interface as the return value of urlopen(). The return value should implement the same interface as the return value of urlopen().

21.6.4. HTTPRedirectHandler Objects

Note

Some HTTP redirections require action from this module’s client code. If this is the case, HTTPError is raised. See RFC 2616 [https://tools.ietf.org/html/rfc2616.html] for details of the precise meanings of the various redirection codes.

An HTTPError exception raised as a security consideration if the HTTPRedirectHandler is presented with a redirected URL which is not an HTTP, HTTPS or FTP URL.

HTTPRedirectHandler.redirect_request(req, fp, code, msg, hdrs, newurl)

Return a Request or None in response to a redirect. This is called by the default implementations of the http_error_30*() methods when a redirection is received from the server. If a redirection should take place, return a new Request to allow http_error_30*() to perform the redirect to newurl. Otherwise, raise HTTPError if no other handler should try to handle this URL, or return None if you can’t but another handler might.

Note

The default implementation of this method does not strictly follow RFC 2616 [https://tools.ietf.org/html/rfc2616.html], which says that 301 and 302 responses to POST requests must not be automatically redirected without confirmation by the user. In reality, browsers do allow automatic redirection of these responses, changing the POST to a GET, and the default implementation reproduces this behavior.

HTTPRedirectHandler.http_error_301(req, fp, code, msg, hdrs)

Redirect to the Location: or URI: URL. This method is called by the parent OpenerDirector when getting an HTTP “moved permanently” response.

HTTPRedirectHandler.http_error_302(req, fp, code, msg, hdrs)

The same as http_error_301(), but called for the “found” response.

HTTPRedirectHandler.http_error_303(req, fp, code, msg, hdrs)

The same as http_error_301(), but called for the “see other” response.

HTTPRedirectHandler.http_error_307(req, fp, code, msg, hdrs)

The same as http_error_301(), but called for the “temporary redirect” response.

21.6.5. HTTPCookieProcessor Objects

HTTPCookieProcessor instances have one attribute:

HTTPCookieProcessor.cookiejar

The http.cookiejar.CookieJar in which cookies are stored.

21.6.6. ProxyHandler Objects

ProxyHandler.protocol_open(request)

The ProxyHandler will have a method protocol_open() for every protocol which has a proxy in the proxies dictionary given in the constructor. The method will modify requests to go through the proxy, by calling request.set_proxy(), and call the next handler in the chain to actually execute the protocol.

21.6.7. HTTPPasswordMgr Objects

These methods are available on HTTPPasswordMgr and HTTPPasswordMgrWithDefaultRealm objects.

HTTPPasswordMgr.add_password(realm, uri, user, passwd)

uri can be either a single URI, or a sequence of URIs. realm, user and passwd must be strings. This causes (user, passwd) to be used as authentication tokens when authentication for realm and a super-URI of any of the given URIs is given.

HTTPPasswordMgr.find_user_password(realm, authuri)

Get user/password for given realm and URI, if any. This method will return (None, None) if there is no matching user/password.

For HTTPPasswordMgrWithDefaultRealm objects, the realm None will be searched if the given realm has no matching user/password.

21.6.8. HTTPPasswordMgrWithPriorAuth Objects

This password manager extends HTTPPasswordMgrWithDefaultRealm to support tracking URIs for which authentication credentials should always be sent.

HTTPPasswordMgrWithPriorAuth.add_password(realm, uri, user, passwd, is_authenticated=False)

realm, uri, user, passwd are as for HTTPPasswordMgr.add_password(). is_authenticated sets the initial value of the is_authenticated flag for the given URI or list of URIs. If is_authenticated is specified as True, realm is ignored.

HTTPPasswordMgr.find_user_password(realm, authuri)

Same as for HTTPPasswordMgrWithDefaultRealm objects

HTTPPasswordMgrWithPriorAuth.update_authenticated(self, uri, is_authenticated=False)

Update the is_authenticated flag for the given uri or list of URIs.

HTTPPasswordMgrWithPriorAuth.is_authenticated(self, authuri)

Returns the current state of the is_authenticated flag for the given URI.

21.6.9. AbstractBasicAuthHandler Objects

AbstractBasicAuthHandler.http_error_auth_reqed(authreq, host, req, headers)

Handle an authentication request by getting a user/password pair, and re-trying the request. authreq should be the name of the header where the information about the realm is included in the request, host specifies the URL and path to authenticate for, req should be the (failed) Request object, and headers should be the error headers.

host is either an authority (e.g. "python.org") or a URL containing an authority component (e.g. "http://python.org/"). In either case, the authority must not contain a userinfo component (so, "python.org" and "python.org:80" are fine, "joe:password@python.org" is not).

21.6.10. HTTPBasicAuthHandler Objects

HTTPBasicAuthHandler.http_error_401(req, fp, code, msg, hdrs)

Retry the request with authentication information, if available.

21.6.11. ProxyBasicAuthHandler Objects

ProxyBasicAuthHandler.http_error_407(req, fp, code, msg, hdrs)

Retry the request with authentication information, if available.

21.6.12. AbstractDigestAuthHandler Objects

AbstractDigestAuthHandler.http_error_auth_reqed(authreq, host, req, headers)

authreq should be the name of the header where the information about the realm is included in the request, host should be the host to authenticate to, req should be the (failed) Request object, and headers should be the error headers.

21.6.13. HTTPDigestAuthHandler Objects

HTTPDigestAuthHandler.http_error_401(req, fp, code, msg, hdrs)

Retry the request with authentication information, if available.

21.6.14. ProxyDigestAuthHandler Objects

ProxyDigestAuthHandler.http_error_407(req, fp, code, msg, hdrs)

Retry the request with authentication information, if available.

21.6.15. HTTPHandler Objects

HTTPHandler.http_open(req)

Send an HTTP request, which can be either GET or POST, depending on req.has_data().

21.6.16. HTTPSHandler Objects

HTTPSHandler.https_open(req)

Send an HTTPS request, which can be either GET or POST, depending on req.has_data().

21.6.17. FileHandler Objects

FileHandler.file_open(req)

Open the file locally, if there is no host name, or the host name is 'localhost'.

Modifié dans la version 3.2: This method is applicable only for local hostnames. When a remote hostname is given, an URLError is raised.

21.6.18. DataHandler Objects

DataHandler.data_open(req)

Read a data URL. This kind of URL contains the content encoded in the URL itself. The data URL syntax is specified in RFC 2397 [https://tools.ietf.org/html/rfc2397.html]. This implementation ignores white spaces in base64 encoded data URLs so the URL may be wrapped in whatever source file it comes from. But even though some browsers don’t mind about a missing padding at the end of a base64 encoded data URL, this implementation will raise an ValueError in that case.

21.6.19. FTPHandler Objects

FTPHandler.ftp_open(req)

Open the FTP file indicated by req. The login is always done with empty username and password.

21.6.20. CacheFTPHandler Objects

CacheFTPHandler objects are FTPHandler objects with the following additional methods:

CacheFTPHandler.setTimeout(t)

Set timeout of connections to t seconds.

CacheFTPHandler.setMaxConns(m)

Set maximum number of cached connections to m.

21.6.21. UnknownHandler Objects

UnknownHandler.unknown_open()

Raise a URLError exception.

21.6.22. HTTPErrorProcessor Objects

HTTPErrorProcessor.http_response(request, response)

Process HTTP error responses.

For 200 error codes, the response object is returned immediately.

For non-200 error codes, this simply passes the job on to the protocol_error_code() handler methods, via OpenerDirector.error(). Eventually, HTTPDefaultErrorHandler will raise an HTTPError if no other handler handles the error.

HTTPErrorProcessor.https_response(request, response)

Process HTTPS error responses.

The behavior is same as http_response().

21.6.23. Exemples

In addition to the examples below, more examples are given in HOWTO Fetch Internet Resources Using The urllib Package.

This example gets the python.org main page and displays the first 300 bytes of it.

>>> import urllib.request
>>> with urllib.request.urlopen('http://www.python.org/') as f:
...     print(f.read(300))
...
b'<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN"
"http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd">\n\n\n<html
xmlns="http://www.w3.org/1999/xhtml" xml:lang="en" lang="en">\n\n<head>\n
<meta http-equiv="content-type" content="text/html; charset=utf-8" />\n
<title>Python Programming '

Note that urlopen returns a bytes object. This is because there is no way for urlopen to automatically determine the encoding of the byte stream it receives from the HTTP server. In general, a program will decode the returned bytes object to string once it determines or guesses the appropriate encoding.

The following W3C document, https://www.w3.org/International/O-charset, lists the various ways in which an (X)HTML or an XML document could have specified its encoding information.

As the python.org website uses utf-8 encoding as specified in its meta tag, we will use the same for decoding the bytes object.

>>> with urllib.request.urlopen('http://www.python.org/') as f:
...     print(f.read(100).decode('utf-8'))
...
<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN"
"http://www.w3.org/TR/xhtml1/DTD/xhtm

It is also possible to achieve the same result without using the context manager approach.

>>> import urllib.request
>>> f = urllib.request.urlopen('http://www.python.org/')
>>> print(f.read(100).decode('utf-8'))
<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN"
"http://www.w3.org/TR/xhtml1/DTD/xhtm

In the following example, we are sending a data-stream to the stdin of a CGI and reading the data it returns to us. Note that this example will only work when the Python installation supports SSL.

>>> import urllib.request
>>> req = urllib.request.Request(url='https://localhost/cgi-bin/test.cgi',
...                       data=b'This data is passed to stdin of the CGI')
>>> with urllib.request.urlopen(req) as f:
...     print(f.read().decode('utf-8'))
...
Got Data: "This data is passed to stdin of the CGI"

The code for the sample CGI used in the above example is:

#!/usr/bin/env python
import sys
data = sys.stdin.read()
print('Content-type: text/plain\n\nGot Data: "%s"' % data)

Here is an example of doing a PUT request using Request:

import urllib.request
DATA = b'some data'
req = urllib.request.Request(url='http://localhost:8080', data=DATA,method='PUT')
with urllib.request.urlopen(req) as f:
    pass
print(f.status)
print(f.reason)

Use of Basic HTTP Authentication:

import urllib.request
# Create an OpenerDirector with support for Basic HTTP Authentication...
auth_handler = urllib.request.HTTPBasicAuthHandler()
auth_handler.add_password(realm='PDQ Application',
                          uri='https://mahler:8092/site-updates.py',
                          user='klem',
                          passwd='kadidd!ehopper')
opener = urllib.request.build_opener(auth_handler)
# ...and install it globally so it can be used with urlopen.
urllib.request.install_opener(opener)
urllib.request.urlopen('http://www.example.com/login.html')

build_opener() provides many handlers by default, including a ProxyHandler. By default, ProxyHandler uses the environment variables named <scheme>_proxy, where <scheme> is the URL scheme involved. For example, the http_proxy environment variable is read to obtain the HTTP proxy’s URL.

This example replaces the default ProxyHandler with one that uses programmatically-supplied proxy URLs, and adds proxy authorization support with ProxyBasicAuthHandler.

proxy_handler = urllib.request.ProxyHandler({'http': 'http://www.example.com:3128/'})
proxy_auth_handler = urllib.request.ProxyBasicAuthHandler()
proxy_auth_handler.add_password('realm', 'host', 'username', 'password')

opener = urllib.request.build_opener(proxy_handler, proxy_auth_handler)
# This time, rather than install the OpenerDirector, we use it directly:
opener.open('http://www.example.com/login.html')

Adding HTTP headers:

Use the headers argument to the Request constructor, or:

import urllib.request
req = urllib.request.Request('http://www.example.com/')
req.add_header('Referer', 'http://www.python.org/')
# Customize the default User-Agent header value:
req.add_header('User-Agent', 'urllib-example/0.1 (Contact: . . .)')
r = urllib.request.urlopen(req)

OpenerDirector automatically adds a User-Agent header to every Request. To change this:

import urllib.request
opener = urllib.request.build_opener()
opener.addheaders = [('User-agent', 'Mozilla/5.0')]
opener.open('http://www.example.com/')

Also, remember that a few standard headers (Content-Length, Content-Type and Host) are added when the Request is passed to urlopen() (or OpenerDirector.open()).

Here is an example session that uses the GET method to retrieve a URL containing parameters:

>>> import urllib.request
>>> import urllib.parse
>>> params = urllib.parse.urlencode({'spam': 1, 'eggs': 2, 'bacon': 0})
>>> url = "http://www.musi-cal.com/cgi-bin/query?%s" % params
>>> with urllib.request.urlopen(url) as f:
...     print(f.read().decode('utf-8'))
...

The following example uses the POST method instead. Note that params output from urlencode is encoded to bytes before it is sent to urlopen as data:

>>> import urllib.request
>>> import urllib.parse
>>> data = urllib.parse.urlencode({'spam': 1, 'eggs': 2, 'bacon': 0})
>>> data = data.encode('ascii')
>>> with urllib.request.urlopen("http://requestb.in/xrbl82xr", data) as f:
...     print(f.read().decode('utf-8'))
...

The following example uses an explicitly specified HTTP proxy, overriding environment settings:

>>> import urllib.request
>>> proxies = {'http': 'http://proxy.example.com:8080/'}
>>> opener = urllib.request.FancyURLopener(proxies)
>>> with opener.open("http://www.python.org") as f:
...     f.read().decode('utf-8')
...

The following example uses no proxies at all, overriding environment settings:

>>> import urllib.request
>>> opener = urllib.request.FancyURLopener({})
>>> with opener.open("http://www.python.org/") as f:
...     f.read().decode('utf-8')
...

21.6.24. Legacy interface

The following functions and classes are ported from the Python 2 module urllib (as opposed to urllib2). They might become deprecated at some point in the future.

urllib.request.urlretrieve(url, filename=None, reporthook=None, data=None)

Copy a network object denoted by a URL to a local file. If the URL points to a local file, the object will not be copied unless filename is supplied. Return a tuple (filename, headers) where filename is the local file name under which the object can be found, and headers is whatever the info() method of the object returned by urlopen() returned (for a remote object). Exceptions are the same as for urlopen().

The second argument, if present, specifies the file location to copy to (if absent, the location will be a tempfile with a generated name). The third argument, if present, is a callable that will be called once on establishment of the network connection and once after each block read thereafter. The callable will be passed three arguments; a count of blocks transferred so far, a block size in bytes, and the total size of the file. The third argument may be -1 on older FTP servers which do not return a file size in response to a retrieval request.

The following example illustrates the most common usage scenario:

>>> import urllib.request
>>> local_filename, headers = urllib.request.urlretrieve('http://python.org/')
>>> html = open(local_filename)
>>> html.close()

If the url uses the http: scheme identifier, the optional data argument may be given to specify a POST request (normally the request type is GET). The data argument must be a bytes object in standard application/x-www-form-urlencoded format; see the urllib.parse.urlencode() function.

urlretrieve() will raise ContentTooShortError when it detects that the amount of data available was less than the expected amount (which is the size reported by a Content-Length header). This can occur, for example, when the download is interrupted.

The Content-Length is treated as a lower bound: if there’s more data to read, urlretrieve reads more data, but if less data is available, it raises the exception.

You can still retrieve the downloaded data in this case, it is stored in the content attribute of the exception instance.

If no Content-Length header was supplied, urlretrieve can not check the size of the data it has downloaded, and just returns it. In this case you just have to assume that the download was successful.

urllib.request.urlcleanup()

Cleans up temporary files that may have been left behind by previous calls to urlretrieve().

class urllib.request.URLopener(proxies=None, **x509)

Obsolète depuis la version 3.3.

Base class for opening and reading URLs. Unless you need to support opening objects using schemes other than http:, ftp:, or file:, you probably want to use FancyURLopener.

By default, the URLopener class sends a User-Agent header of urllib/VVV, where VVV is the urllib version number. Applications can define their own User-Agent header by subclassing URLopener or FancyURLopener and setting the class attribute version to an appropriate string value in the subclass definition.

The optional proxies parameter should be a dictionary mapping scheme names to proxy URLs, where an empty dictionary turns proxies off completely. Its default value is None, in which case environmental proxy settings will be used if present, as discussed in the definition of urlopen(), above.

Additional keyword parameters, collected in x509, may be used for authentication of the client when using the https: scheme. The keywords key_file and cert_file are supported to provide an SSL key and certificate; both are needed to support client authentication.

URLopener objects will raise an OSError exception if the server returns an error code.

open(fullurl, data=None)

Open fullurl using the appropriate protocol. This method sets up cache and proxy information, then calls the appropriate open method with its input arguments. If the scheme is not recognized, open_unknown() is called. The data argument has the same meaning as the data argument of urlopen().

open_unknown(fullurl, data=None)

Overridable interface to open unknown URL types.

retrieve(url, filename=None, reporthook=None, data=None)

Retrieves the contents of url and places it in filename. The return value is a tuple consisting of a local filename and either an email.message.Message object containing the response headers (for remote URLs) or None (for local URLs). The caller must then open and read the contents of filename. If filename is not given and the URL refers to a local file, the input filename is returned. If the URL is non-local and filename is not given, the filename is the output of tempfile.mktemp() with a suffix that matches the suffix of the last path component of the input URL. If reporthook is given, it must be a function accepting three numeric parameters: A chunk number, the maximum size chunks are read in and the total size of the download (-1 if unknown). It will be called once at the start and after each chunk of data is read from the network. reporthook is ignored for local URLs.

If the url uses the http: scheme identifier, the optional data argument may be given to specify a POST request (normally the request type is GET). The data argument must in standard application/x-www-form-urlencoded format; see the urllib.parse.urlencode() function.

version

Variable that specifies the user agent of the opener object. To get urllib to tell servers that it is a particular user agent, set this in a subclass as a class variable or in the constructor before calling the base constructor.

class urllib.request.FancyURLopener(...)

Obsolète depuis la version 3.3.

FancyURLopener subclasses URLopener providing default handling for the following HTTP response codes: 301, 302, 303, 307 and 401. For the 30x response codes listed above, the Location header is used to fetch the actual URL. For 401 response codes (authentication required), basic HTTP authentication is performed. For the 30x response codes, recursion is bounded by the value of the maxtries attribute, which defaults to 10.

For all other response codes, the method http_error_default() is called which you can override in subclasses to handle the error appropriately.

Note

According to the letter of RFC 2616 [https://tools.ietf.org/html/rfc2616.html], 301 and 302 responses to POST requests must not be automatically redirected without confirmation by the user. In reality, browsers do allow automatic redirection of these responses, changing the POST to a GET, and urllib reproduces this behaviour.

The parameters to the constructor are the same as those for URLopener.

Note

When performing basic authentication, a FancyURLopener instance calls its prompt_user_passwd() method. The default implementation asks the users for the required information on the controlling terminal. A subclass may override this method to support more appropriate behavior if needed.

The FancyURLopener class offers one additional method that should be overloaded to provide the appropriate behavior:

prompt_user_passwd(host, realm)

Return information needed to authenticate the user at the given host in the specified security realm. The return value should be a tuple, (user, password), which can be used for basic authentication.

The implementation prompts for this information on the terminal; an application should override this method to use an appropriate interaction model in the local environment.

21.6.25. urllib.request Restrictions

Currently, only the following protocols are supported: HTTP (versions 0.9 and 1.0), FTP, local files, and data URLs.

Modifié dans la version 3.4: Added support for data URLs.

The caching feature of urlretrieve() has been disabled until someone finds the time to hack proper processing of Expiration time headers.

There should be a function to query whether a particular URL is in the cache.

For backward compatibility, if a URL appears to point to a local file but the file can’t be opened, the URL is re-interpreted using the FTP protocol. This can sometimes cause confusing error messages.

The urlopen() and urlretrieve() functions can cause arbitrarily long delays while waiting for a network connection to be set up. This means that it is difficult to build an interactive Web client using these functions without using threads.

The data returned by urlopen() or urlretrieve() is the raw data returned by the server. This may be binary data (such as an image), plain text or (for example) HTML. The HTTP protocol provides type information in the reply header, which can be inspected by looking at the Content-Type header. If the returned data is HTML, you can use the module html.parser to parse it.

The code handling the FTP protocol cannot differentiate between a file and a directory. This can lead to unexpected behavior when attempting to read a URL that points to a file that is not accessible. If the URL ends in a /, it is assumed to refer to a directory and will be handled accordingly. But if an attempt to read a file leads to a 550 error (meaning the URL cannot be found or is not accessible, often for permission reasons), then the path is treated as a directory in order to handle the case when a directory is specified by a URL but the trailing / has been left off. This can cause misleading results when you try to fetch a file whose read permissions make it inaccessible; the FTP code will try to read it, fail with a 550 error, and then perform a directory listing for the unreadable file. If fine-grained control is needed, consider using the ftplib module, subclassing FancyURLopener, or changing _urlopener to meet your needs.

21.7. urllib.response — Response classes used by urllib

The urllib.response module defines functions and classes which define a minimal file like interface, including read() and readline(). The typical response object is an addinfourl instance, which defines an info() method and that returns headers and a geturl() method that returns the url. Functions defined by this module are used internally by the urllib.request module.

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21.8. urllib.parse — Parse URLs into components

Code source : Lib/urllib/parse.py [https://github.com/python/cpython/tree/3.6/Lib/urllib/parse.py]

This module defines a standard interface to break Uniform Resource Locator (URL) strings up in components (addressing scheme, network location, path etc.), to combine the components back into a URL string, and to convert a « relative URL » to an absolute URL given a « base URL. »

The module has been designed to match the Internet RFC on Relative Uniform Resource Locators. It supports the following URL schemes: file, ftp, gopher, hdl, http, https, imap, mailto, mms, news, nntp, prospero, rsync, rtsp, rtspu, sftp, shttp, sip, sips, snews, svn, svn+ssh, telnet, wais, ws, wss.

The urllib.parse module defines functions that fall into two broad categories: URL parsing and URL quoting. These are covered in detail in the following sections.

21.8.1. URL Parsing

The URL parsing functions focus on splitting a URL string into its components, or on combining URL components into a URL string.

urllib.parse.urlparse(urlstring, scheme='', allow_fragments=True)

Parse a URL into six components, returning a 6-tuple. This corresponds to the general structure of a URL: scheme://netloc/path;parameters?query#fragment. Each tuple item is a string, possibly empty. The components are not broken up in smaller parts (for example, the network location is a single string), and % escapes are not expanded. The delimiters as shown above are not part of the result, except for a leading slash in the path component, which is retained if present. For example:

>>> from urllib.parse import urlparse
>>> o = urlparse('http://www.cwi.nl:80/%7Eguido/Python.html')
>>> o
ParseResult(scheme='http', netloc='www.cwi.nl:80', path='/%7Eguido/Python.html',
            params='', query='', fragment='')
>>> o.scheme
'http'
>>> o.port
80
>>> o.geturl()
'http://www.cwi.nl:80/%7Eguido/Python.html'

Following the syntax specifications in RFC 1808 [https://tools.ietf.org/html/rfc1808.html], urlparse recognizes a netloc only if it is properly introduced by “//”. Otherwise the input is presumed to be a relative URL and thus to start with a path component.

>>> from urllib.parse import urlparse
>>> urlparse('//www.cwi.nl:80/%7Eguido/Python.html')
ParseResult(scheme='', netloc='www.cwi.nl:80', path='/%7Eguido/Python.html',
           params='', query='', fragment='')
>>> urlparse('www.cwi.nl/%7Eguido/Python.html')
ParseResult(scheme='', netloc='', path='www.cwi.nl/%7Eguido/Python.html',
           params='', query='', fragment='')
>>> urlparse('help/Python.html')
ParseResult(scheme='', netloc='', path='help/Python.html', params='',
           query='', fragment='')

The scheme argument gives the default addressing scheme, to be used only if the URL does not specify one. It should be the same type (text or bytes) as urlstring, except that the default value '' is always allowed, and is automatically converted to b'' if appropriate.

If the allow_fragments argument is false, fragment identifiers are not recognized. Instead, they are parsed as part of the path, parameters or query component, and fragment is set to the empty string in the return value.

The return value is actually an instance of a subclass of tuple. This class has the following additional read-only convenience attributes:

Attribut

Index

Valeur

Value if not present

scheme

0

URL scheme specifier

scheme parameter

netloc

1

Network location part

empty string

path

2

Hierarchical path

empty string

params

3

Parameters for last path element

empty string

query

4

Query component

empty string

fragment

5

Fragment identifier

empty string

username

User name

None

password

Password

None

hostname

Host name (lower case)

None

port

Port number as integer, if present

None

Reading the port attribute will raise a ValueError if an invalid port is specified in the URL. See section Structured Parse Results for more information on the result object.

Unmatched square brackets in the netloc attribute will raise a ValueError.

Characters in the netloc attribute that decompose under NFKC normalization (as used by the IDNA encoding) into any of /, ?, #, @, or : will raise a ValueError. If the URL is decomposed before parsing, no error will be raised.

Modifié dans la version 3.2: Added IPv6 URL parsing capabilities.

Modifié dans la version 3.3: The fragment is now parsed for all URL schemes (unless allow_fragment is false), in accordance with RFC 3986 [https://tools.ietf.org/html/rfc3986.html]. Previously, a whitelist of schemes that support fragments existed.

Modifié dans la version 3.6: Out-of-range port numbers now raise ValueError, instead of returning None.

Modifié dans la version 3.6.9: Characters that affect netloc parsing under NFKC normalization will now raise ValueError.

urllib.parse.parse_qs(qs, keep_blank_values=False, strict_parsing=False, encoding='utf-8', errors='replace', max_num_fields=None)

Parse a query string given as a string argument (data of type application/x-www-form-urlencoded). Data are returned as a dictionary. The dictionary keys are the unique query variable names and the values are lists of values for each name.

The optional argument keep_blank_values is a flag indicating whether blank values in percent-encoded queries should be treated as blank strings. A true value indicates that blanks should be retained as blank strings. The default false value indicates that blank values are to be ignored and treated as if they were not included.

The optional argument strict_parsing is a flag indicating what to do with parsing errors. If false (the default), errors are silently ignored. If true, errors raise a ValueError exception.

The optional encoding and errors parameters specify how to decode percent-encoded sequences into Unicode characters, as accepted by the bytes.decode() method.

The optional argument max_num_fields is the maximum number of fields to read. If set, then throws a ValueError if there are more than max_num_fields fields read.

Use the urllib.parse.urlencode() function (with the doseq parameter set to True) to convert such dictionaries into query strings.

Modifié dans la version 3.2: Add encoding and errors parameters.

Modifié dans la version 3.6.8: Added max_num_fields parameter.

urllib.parse.parse_qsl(qs, keep_blank_values=False, strict_parsing=False, encoding='utf-8', errors='replace', max_num_fields=None)

Parse a query string given as a string argument (data of type application/x-www-form-urlencoded). Data are returned as a list of name, value pairs.

The optional argument keep_blank_values is a flag indicating whether blank values in percent-encoded queries should be treated as blank strings. A true value indicates that blanks should be retained as blank strings. The default false value indicates that blank values are to be ignored and treated as if they were not included.

The optional argument strict_parsing is a flag indicating what to do with parsing errors. If false (the default), errors are silently ignored. If true, errors raise a ValueError exception.

The optional encoding and errors parameters specify how to decode percent-encoded sequences into Unicode characters, as accepted by the bytes.decode() method.

The optional argument max_num_fields is the maximum number of fields to read. If set, then throws a ValueError if there are more than max_num_fields fields read.

Use the urllib.parse.urlencode() function to convert such lists of pairs into query strings.

Modifié dans la version 3.2: Add encoding and errors parameters.

Modifié dans la version 3.6.8: Added max_num_fields parameter.

urllib.parse.urlunparse(parts)

Construct a URL from a tuple as returned by urlparse(). The parts argument can be any six-item iterable. This may result in a slightly different, but equivalent URL, if the URL that was parsed originally had unnecessary delimiters (for example, a ? with an empty query; the RFC states that these are equivalent).

urllib.parse.urlsplit(urlstring, scheme='', allow_fragments=True)

This is similar to urlparse(), but does not split the params from the URL. This should generally be used instead of urlparse() if the more recent URL syntax allowing parameters to be applied to each segment of the path portion of the URL (see RFC 2396 [https://tools.ietf.org/html/rfc2396.html]) is wanted. A separate function is needed to separate the path segments and parameters. This function returns a 5-tuple: (addressing scheme, network location, path, query, fragment identifier).

The return value is actually an instance of a subclass of tuple. This class has the following additional read-only convenience attributes:

Attribut

Index

Valeur

Value if not present

scheme

0

URL scheme specifier

scheme parameter

netloc

1

Network location part

empty string

path

2

Hierarchical path

empty string

query

3

Query component

empty string

fragment

4

Fragment identifier

empty string

username

User name

None

password

Password

None

hostname

Host name (lower case)

None

port

Port number as integer, if present

None

Reading the port attribute will raise a ValueError if an invalid port is specified in the URL. See section Structured Parse Results for more information on the result object.

Unmatched square brackets in the netloc attribute will raise a ValueError.

Characters in the netloc attribute that decompose under NFKC normalization (as used by the IDNA encoding) into any of /, ?, #, @, or : will raise a ValueError. If the URL is decomposed before parsing, no error will be raised.

Modifié dans la version 3.6: Out-of-range port numbers now raise ValueError, instead of returning None.

Modifié dans la version 3.6.9: Characters that affect netloc parsing under NFKC normalization will now raise ValueError.

urllib.parse.urlunsplit(parts)

Combine the elements of a tuple as returned by urlsplit() into a complete URL as a string. The parts argument can be any five-item iterable. This may result in a slightly different, but equivalent URL, if the URL that was parsed originally had unnecessary delimiters (for example, a ? with an empty query; the RFC states that these are equivalent).

urllib.parse.urljoin(base, url, allow_fragments=True)

Construct a full (« absolute ») URL by combining a « base URL » (base) with another URL (url). Informally, this uses components of the base URL, in particular the addressing scheme, the network location and (part of) the path, to provide missing components in the relative URL. For example:

>>> from urllib.parse import urljoin
>>> urljoin('http://www.cwi.nl/%7Eguido/Python.html', 'FAQ.html')
'http://www.cwi.nl/%7Eguido/FAQ.html'

The allow_fragments argument has the same meaning and default as for urlparse().

Note

If url is an absolute URL (that is, starting with // or scheme://), the url’s host name and/or scheme will be present in the result. For example:

>>> urljoin('http://www.cwi.nl/%7Eguido/Python.html',
...         '//www.python.org/%7Eguido')
'http://www.python.org/%7Eguido'

If you do not want that behavior, preprocess the url with urlsplit() and urlunsplit(), removing possible scheme and netloc parts.

Modifié dans la version 3.5: Behaviour updated to match the semantics defined in RFC 3986 [https://tools.ietf.org/html/rfc3986.html].

urllib.parse.urldefrag(url)

If url contains a fragment identifier, return a modified version of url with no fragment identifier, and the fragment identifier as a separate string. If there is no fragment identifier in url, return url unmodified and an empty string.

The return value is actually an instance of a subclass of tuple. This class has the following additional read-only convenience attributes:

Attribut

Index

Valeur

Value if not present

url

0

URL with no fragment

empty string

fragment

1

Fragment identifier

empty string

See section Structured Parse Results for more information on the result object.

Modifié dans la version 3.2: Result is a structured object rather than a simple 2-tuple.

21.8.2. Parsing ASCII Encoded Bytes

The URL parsing functions were originally designed to operate on character strings only. In practice, it is useful to be able to manipulate properly quoted and encoded URLs as sequences of ASCII bytes. Accordingly, the URL parsing functions in this module all operate on bytes and bytearray objects in addition to str objects.

If str data is passed in, the result will also contain only str data. If bytes or bytearray data is passed in, the result will contain only bytes data.

Attempting to mix str data with bytes or bytearray in a single function call will result in a TypeError being raised, while attempting to pass in non-ASCII byte values will trigger UnicodeDecodeError.

To support easier conversion of result objects between str and bytes, all return values from URL parsing functions provide either an encode() method (when the result contains str data) or a decode() method (when the result contains bytes data). The signatures of these methods match those of the corresponding str and bytes methods (except that the default encoding is 'ascii' rather than 'utf-8'). Each produces a value of a corresponding type that contains either bytes data (for encode() methods) or str data (for decode() methods).

Applications that need to operate on potentially improperly quoted URLs that may contain non-ASCII data will need to do their own decoding from bytes to characters before invoking the URL parsing methods.

The behaviour described in this section applies only to the URL parsing functions. The URL quoting functions use their own rules when producing or consuming byte sequences as detailed in the documentation of the individual URL quoting functions.

Modifié dans la version 3.2: URL parsing functions now accept ASCII encoded byte sequences

21.8.3. Structured Parse Results

The result objects from the urlparse(), urlsplit() and urldefrag() functions are subclasses of the tuple type. These subclasses add the attributes listed in the documentation for those functions, the encoding and decoding support described in the previous section, as well as an additional method:

urllib.parse.SplitResult.geturl()

Return the re-combined version of the original URL as a string. This may differ from the original URL in that the scheme may be normalized to lower case and empty components may be dropped. Specifically, empty parameters, queries, and fragment identifiers will be removed.

For urldefrag() results, only empty fragment identifiers will be removed. For urlsplit() and urlparse() results, all noted changes will be made to the URL returned by this method.

The result of this method remains unchanged if passed back through the original parsing function:

>>> from urllib.parse import urlsplit
>>> url = 'HTTP://www.Python.org/doc/#'
>>> r1 = urlsplit(url)
>>> r1.geturl()
'http://www.Python.org/doc/'
>>> r2 = urlsplit(r1.geturl())
>>> r2.geturl()
'http://www.Python.org/doc/'

The following classes provide the implementations of the structured parse results when operating on str objects:

class urllib.parse.DefragResult(url, fragment)

Concrete class for urldefrag() results containing str data. The encode() method returns a DefragResultBytes instance.

Nouveau dans la version 3.2.

class urllib.parse.ParseResult(scheme, netloc, path, params, query, fragment)

Concrete class for urlparse() results containing str data. The encode() method returns a ParseResultBytes instance.

class urllib.parse.SplitResult(scheme, netloc, path, query, fragment)

Concrete class for urlsplit() results containing str data. The encode() method returns a SplitResultBytes instance.

The following classes provide the implementations of the parse results when operating on bytes or bytearray objects:

class urllib.parse.DefragResultBytes(url, fragment)

Concrete class for urldefrag() results containing bytes data. The decode() method returns a DefragResult instance.

Nouveau dans la version 3.2.

class urllib.parse.ParseResultBytes(scheme, netloc, path, params, query, fragment)

Concrete class for urlparse() results containing bytes data. The decode() method returns a ParseResult instance.

Nouveau dans la version 3.2.

class urllib.parse.SplitResultBytes(scheme, netloc, path, query, fragment)

Concrete class for urlsplit() results containing bytes data. The decode() method returns a SplitResult instance.

Nouveau dans la version 3.2.

21.8.4. URL Quoting

The URL quoting functions focus on taking program data and making it safe for use as URL components by quoting special characters and appropriately encoding non-ASCII text. They also support reversing these operations to recreate the original data from the contents of a URL component if that task isn’t already covered by the URL parsing functions above.

urllib.parse.quote(string, safe='/', encoding=None, errors=None)

Replace special characters in string using the %xx escape. Letters, digits, and the characters '_.-' are never quoted. By default, this function is intended for quoting the path section of URL. The optional safe parameter specifies additional ASCII characters that should not be quoted — its default value is '/'.

string may be either a str or a bytes.

The optional encoding and errors parameters specify how to deal with non-ASCII characters, as accepted by the str.encode() method. encoding defaults to 'utf-8'. errors defaults to 'strict', meaning unsupported characters raise a UnicodeEncodeError. encoding and errors must not be supplied if string is a bytes, or a TypeError is raised.

Note that quote(string, safe, encoding, errors) is equivalent to quote_from_bytes(string.encode(encoding, errors), safe).

Example: quote('/El Niño/') yields '/El%20Ni%C3%B1o/'.

urllib.parse.quote_plus(string, safe='', encoding=None, errors=None)

Like quote(), but also replace spaces by plus signs, as required for quoting HTML form values when building up a query string to go into a URL. Plus signs in the original string are escaped unless they are included in safe. It also does not have safe default to '/'.

Example: quote_plus('/El Niño/') yields '%2FEl+Ni%C3%B1o%2F'.

urllib.parse.quote_from_bytes(bytes, safe='/')

Like quote(), but accepts a bytes object rather than a str, and does not perform string-to-bytes encoding.

Example: quote_from_bytes(b'a&\xef') yields 'a%26%EF'.

urllib.parse.unquote(string, encoding='utf-8', errors='replace')

Replace %xx escapes by their single-character equivalent. The optional encoding and errors parameters specify how to decode percent-encoded sequences into Unicode characters, as accepted by the bytes.decode() method.

string must be a str.

encoding defaults to 'utf-8'. errors defaults to 'replace', meaning invalid sequences are replaced by a placeholder character.

Example: unquote('/El%20Ni%C3%B1o/') yields '/El Niño/'.

urllib.parse.unquote_plus(string, encoding='utf-8', errors='replace')

Like unquote(), but also replace plus signs by spaces, as required for unquoting HTML form values.

string must be a str.

Example: unquote_plus('/El+Ni%C3%B1o/') yields '/El Niño/'.

urllib.parse.unquote_to_bytes(string)

Replace %xx escapes by their single-octet equivalent, and return a bytes object.

string may be either a str or a bytes.

If it is a str, unescaped non-ASCII characters in string are encoded into UTF-8 bytes.

Example: unquote_to_bytes('a%26%EF') yields b'a&\xef'.

urllib.parse.urlencode(query, doseq=False, safe='', encoding=None, errors=None, quote_via=quote_plus)

Convert a mapping object or a sequence of two-element tuples, which may contain str or bytes objects, to a percent-encoded ASCII text string. If the resultant string is to be used as a data for POST operation with the urlopen() function, then it should be encoded to bytes, otherwise it would result in a TypeError.

The resulting string is a series of key=value pairs separated by '&' characters, where both key and value are quoted using the quote_via function. By default, quote_plus() is used to quote the values, which means spaces are quoted as a '+' character and “/” characters are encoded as %2F, which follows the standard for GET requests (application/x-www-form-urlencoded). An alternate function that can be passed as quote_via is quote(), which will encode spaces as %20 and not encode “/” characters. For maximum control of what is quoted, use quote and specify a value for safe.

When a sequence of two-element tuples is used as the query argument, the first element of each tuple is a key and the second is a value. The value element in itself can be a sequence and in that case, if the optional parameter doseq is evaluates to True, individual key=value pairs separated by '&' are generated for each element of the value sequence for the key. The order of parameters in the encoded string will match the order of parameter tuples in the sequence.

The safe, encoding, and errors parameters are passed down to quote_via (the encoding and errors parameters are only passed when a query element is a str).

To reverse this encoding process, parse_qs() and parse_qsl() are provided in this module to parse query strings into Python data structures.

Refer to urllib examples to find out how urlencode method can be used for generating query string for a URL or data for POST.

Modifié dans la version 3.2: Query parameter supports bytes and string objects.

Nouveau dans la version 3.5: quote_via parameter.

Voir aussi

RFC 3986 [https://tools.ietf.org/html/rfc3986.html] - Uniform Resource Identifiers

This is the current standard (STD66). Any changes to urllib.parse module should conform to this. Certain deviations could be observed, which are mostly for backward compatibility purposes and for certain de-facto parsing requirements as commonly observed in major browsers.

RFC 2732 [https://tools.ietf.org/html/rfc2732.html] - Format for Literal IPv6 Addresses in URL’s.

This specifies the parsing requirements of IPv6 URLs.

RFC 2396 [https://tools.ietf.org/html/rfc2396.html] - Uniform Resource Identifiers (URI): Generic Syntax

Document describing the generic syntactic requirements for both Uniform Resource Names (URNs) and Uniform Resource Locators (URLs).

RFC 2368 [https://tools.ietf.org/html/rfc2368.html] - The mailto URL scheme.

Parsing requirements for mailto URL schemes.

RFC 1808 [https://tools.ietf.org/html/rfc1808.html] - Relative Uniform Resource Locators

This Request For Comments includes the rules for joining an absolute and a relative URL, including a fair number of « Abnormal Examples » which govern the treatment of border cases.

RFC 1738 [https://tools.ietf.org/html/rfc1738.html] - Uniform Resource Locators (URL)

This specifies the formal syntax and semantics of absolute URLs.

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21.9. urllib.error — Classes d’exceptions levées par urllib.request

Code source : Lib/urllib/error.py [https://github.com/python/cpython/tree/3.6/Lib/urllib/error.py]

Le module urllib.error définit les classes des exceptions levées par urllib.request. La classe de base de ces exceptions est URLError.

Les exceptions suivantes sont levées par urllib.error aux cas appropriés :

exception urllib.error.URLError

Les gestionnaires lèvent cette exception (ou des exceptions dérivées) quand ils rencontrent un problème. Elle est une sous-classe de OSError.

reason

La raison de cette erreur. Il peut s’agir d’un message textuel ou d’une autre instance d’exception.

Modifié dans la version 3.3: URLError est maintenant une sous-classe de OSError plutôt que IOError.

exception urllib.error.HTTPError

Bien qu’étant une exception (une sous-classe de URLError), une HTTPError peut aussi fonctionner comme une valeur de retour normale et fichier-compatible (la même chose que renvoyé par urlopen()). Cela est utile pour gérer les erreurs HTTP exotiques, comme les requêtes d’authentification.

code

Un statut HTTP comme défini dans la RFC 2616 [https://tools.ietf.org/html/rfc2616.html]. Cette valeur numérique correspond à une valeur trouvée dans le dictionnaire des codes comme dans http.server.BaseHTTPRequestHandler.responses.

reason

Il s’agit habituellement d’une chaîne de caractères expliquant la raison de l’erreur.

headers

Les en-têtes de la réponse HTTP correspondant à la requête HTTP qui a causé la HTTPError.

Nouveau dans la version 3.4.

exception urllib.error.ContentTooShortError(msg, content)

Cette exception est levée quand la fonction urlretrieve() détecte que le montant des données téléchargées est inférieur au montant attendu (donné par l’en-tête Content-Length). L’attribut content stocke les données téléchargées (et supposément tronquées).

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21.10. urllib.robotparser — Analyseur de fichiers robots.txt

Code source : Lib/urllib/robotparser.py [https://github.com/python/cpython/tree/3.6/Lib/urllib/robotparser.py]

Ce module fournit une simple classe, RobotFileParser, qui permet de savoir si un user-agent particulier peut accéder à une URL du site web qui a publié ce fichier robots.txt. Pour plus de détails sur la structure des fichiers robots.txt, voir http://www.robotstxt.org/orig.html.

class urllib.robotparser.RobotFileParser(url='')

Cette classe fournit des méthodes pour lire, analyser et répondre aux questions à propos du fichier robots.txt disponible à l’adresse url.

set_url(url)

Modifie l’URL référençant le fichier robots.txt.

read()

Lit le fichier robots.txt depuis son URL et envoie le contenu à l’analyseur.

parse(lines)

Analyse les lignes données en argument.

can_fetch(useragent, url)

Renvoie True si useragent est autorisé à accéder à url selon les règles contenues dans le fichier robots.txt analysé.

mtime()

Renvoie le temps auquel le fichier robots.txt a été téléchargé pour la dernière fois. Cela est utile pour des web spiders de longue durée qui doivent vérifier périodiquement si le fichier est mis à jour.

modified()

Indique que le fichier robots.txt a été téléchargé pour la dernière fois au temps courant.

crawl_delay(useragent)

Renvoie la valeur du paramètre Crawl-delay du robots.txt pour le useragent en question. S’il n’y a pas de tel paramètre ou qu’il ne s’applique pas au useragent spécifié ou si l’entrée du robots.txt pour ce paramètre a une syntaxe invalide, renvoie None.

Nouveau dans la version 3.6.

request_rate(useragent)

Renvoie le contenu du paramètre Request-rate du robots.txt sous la forme d’un named tuple RequestRate(requests, seconds). S’il n’y a pas de tel paramètre ou qu’il ne s’applique pas au useragent spécifié ou si l’entrée du robots.txt pour ce paramètre a une syntaxe invalide, None est renvoyé.

Nouveau dans la version 3.6.

L’exemple suivant présente une utilisation basique de la classe RobotFileParser :

>>> import urllib.robotparser
>>> rp = urllib.robotparser.RobotFileParser()
>>> rp.set_url("http://www.musi-cal.com/robots.txt")
>>> rp.read()
>>> rrate = rp.request_rate("*")
>>> rrate.requests
3
>>> rrate.seconds
20
>>> rp.crawl_delay("*")
6
>>> rp.can_fetch("*", "http://www.musi-cal.com/cgi-bin/search?city=San+Francisco")
False
>>> rp.can_fetch("*", "http://www.musi-cal.com/")
True

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21.11. http — modules HTTP

Code source : Lib/http/__init__.py [https://github.com/python/cpython/tree/3.6/Lib/http/__init__.py]

http est un paquet qui rassemble plusieurs modules servant à travailler avec le protocole HTTP (HyperText Transfer Procotol) :

Le module http.client est un client HTTP bas niveau. Pour accéder à des ressources web, utiliser le module haut niveau urllib.request

Le module http.server contient des classes serveur HTTP basiques basées sur socketserver

Le module http.cookies contient des utilitaires liés à la gestion d’état HTTP via les cookies

Le module http.cookiejar fournit un mécanisme de persistance des cookies

http est aussi un module qui définit une liste de codes d’état HTTP et les messages associés par le biais de l’énumération http.HTTPStatus :

class http.HTTPStatus

Nouveau dans la version 3.5.

Sous-classe de enum.IntEnum qui définit un ensemble de codes d’état HTTP, messages explicatifs et descriptions complètes écrites en anglais.

Utilisation :

>>> from http import HTTPStatus
>>> HTTPStatus.OK
<HTTPStatus.OK: 200>
>>> HTTPStatus.OK == 200
True
>>> http.HTTPStatus.OK.value
200
>>> HTTPStatus.OK.phrase
'OK'
>>> HTTPStatus.OK.description
'Request fulfilled, document follows'
>>> list(HTTPStatus)
[<HTTPStatus.CONTINUE: 100>, <HTTPStatus.SWITCHING_PROTOCOLS: 101>, ...]

21.11.1. Codes d’état HTTP

Les codes d’état disponibles (enregistrés auprès de l’IANA [https://www.iana.org/assignments/http-status-codes/http-status-codes.xhtml]) dans http.HTTPStatus sont :

Code

Message

Détails

100

CONTINUE

HTTP/1.1 RFC 7231 [https://tools.ietf.org/html/rfc7231.html], Section 6.2.1

101

SWITCHING_PROTOCOLS

HTTP/1.1 RFC 7231 [https://tools.ietf.org/html/rfc7231.html], Section 6.2.2

102

PROCESSING

WebDAV RFC 2518 [https://tools.ietf.org/html/rfc2518.html], Section 10.1

200

OK

HTTP/1.1 RFC 7231 [https://tools.ietf.org/html/rfc7231.html], Section 6.3.1

201

CREATED

HTTP/1.1 RFC 7231 [https://tools.ietf.org/html/rfc7231.html], Section 6.3.2

202

ACCEPTED

HTTP/1.1 RFC 7231 [https://tools.ietf.org/html/rfc7231.html], Section 6.3.3

203

NON_AUTHORITATIVE_INFORMATION

HTTP/1.1 RFC 7231 [https://tools.ietf.org/html/rfc7231.html], Section 6.3.4

204

NO_CONTENT

HTTP/1.1 RFC 7231 [https://tools.ietf.org/html/rfc7231.html], Section 6.3.5

205

RESET_CONTENT

HTTP/1.1 RFC 7231 [https://tools.ietf.org/html/rfc7231.html], Section 6.3.6

206

PARTIAL_CONTENT

HTTP/1.1 RFC 7233 [https://tools.ietf.org/html/rfc7233.html], Section 4.1

207

MULTI_STATUS

WebDAV RFC 4918 [https://tools.ietf.org/html/rfc4918.html], Section 11.1

208

ALREADY_REPORTED

WebDAV Binding Extensions RFC 5842 [https://tools.ietf.org/html/rfc5842.html], Section 7.1 (Expérimental)

226

IM_USED

Delta Encoding in HTTP RFC 3229 [https://tools.ietf.org/html/rfc3229.html], Section 10.4.1

300

MULTIPLE_CHOICES

HTTP/1.1 RFC 7231 [https://tools.ietf.org/html/rfc7231.html], Section 6.4.1

301

MOVED_PERMANENTLY

HTTP/1.1 RFC 7231 [https://tools.ietf.org/html/rfc7231.html], Section 6.4.2

302

FOUND

HTTP/1.1 RFC 7231 [https://tools.ietf.org/html/rfc7231.html], Section 6.4.3

303

SEE_OTHER

HTTP/1.1 RFC 7231 [https://tools.ietf.org/html/rfc7231.html], Section 6.4.4

304

NOT_MODIFIED

HTTP/1.1 RFC 7232 [https://tools.ietf.org/html/rfc7232.html], Section 4.1

305

USE_PROXY

HTTP/1.1 RFC 7231 [https://tools.ietf.org/html/rfc7231.html], Section 6.4.5

307

TEMPORARY_REDIRECT

HTTP/1.1 RFC 7231 [https://tools.ietf.org/html/rfc7231.html], Section 6.4.7

308

PERMANENT_REDIRECT

Permanent Redirect RFC 7238 [https://tools.ietf.org/html/rfc7238.html], Section 3 (Expérimental)

400

BAD_REQUEST

HTTP/1.1 RFC 7231 [https://tools.ietf.org/html/rfc7231.html], Section 6.5.1

401

UNAUTHORIZED

HTTP/1.1 Authentication RFC 7235 [https://tools.ietf.org/html/rfc7235.html], Section 3.1

402

PAYMENT_REQUIRED

HTTP/1.1 RFC 7231 [https://tools.ietf.org/html/rfc7231.html], Section 6.5.2

403

FORBIDDEN

HTTP/1.1 RFC 7231 [https://tools.ietf.org/html/rfc7231.html], Section 6.5.3

404

NOT_FOUND

HTTP/1.1 RFC 7231 [https://tools.ietf.org/html/rfc7231.html], Section 6.5.4

405

METHOD_NOT_ALLOWED

HTTP/1.1 RFC 7231 [https://tools.ietf.org/html/rfc7231.html], Section 6.5.5

406

NOT_ACCEPTABLE

HTTP/1.1 RFC 7231 [https://tools.ietf.org/html/rfc7231.html], Section 6.5.6

407

PROXY_AUTHENTICATION_REQUIRED

HTTP/1.1 Authentication RFC 7235 [https://tools.ietf.org/html/rfc7235.html], Section 3.2

408

REQUEST_TIMEOUT

HTTP/1.1 RFC 7231 [https://tools.ietf.org/html/rfc7231.html], Section 6.5.7

409

CONFLICT

HTTP/1.1 RFC 7231 [https://tools.ietf.org/html/rfc7231.html], Section 6.5.8

410

GONE

HTTP/1.1 RFC 7231 [https://tools.ietf.org/html/rfc7231.html], Section 6.5.9

411

LENGTH_REQUIRED

HTTP/1.1 RFC 7231 [https://tools.ietf.org/html/rfc7231.html], Section 6.5.10

412

PRECONDITION_FAILED

HTTP/1.1 RFC 7232 [https://tools.ietf.org/html/rfc7232.html], Section 4.2

413

REQUEST_ENTITY_TOO_LARGE

HTTP/1.1 RFC 7231 [https://tools.ietf.org/html/rfc7231.html], Section 6.5.11

414

REQUEST_URI_TOO_LONG

HTTP/1.1 RFC 7231 [https://tools.ietf.org/html/rfc7231.html], Section 6.5.12

415

UNSUPPORTED_MEDIA_TYPE

HTTP/1.1 RFC 7231 [https://tools.ietf.org/html/rfc7231.html], Section 6.5.13

416

REQUEST_RANGE_NOT_SATISFIABLE

HTTP/1.1 Range Requests RFC 7233 [https://tools.ietf.org/html/rfc7233.html], Section 4.4

417

EXPECTATION_FAILED

HTTP/1.1 RFC 7231 [https://tools.ietf.org/html/rfc7231.html], Section 6.5.14

422

UNPROCESSABLE_ENTITY

WebDAV RFC 4918 [https://tools.ietf.org/html/rfc4918.html], Section 11.2

423

LOCKED

WebDAV RFC 4918 [https://tools.ietf.org/html/rfc4918.html], Section 11.3

424

FAILED_DEPENDENCY

WebDAV RFC 4918 [https://tools.ietf.org/html/rfc4918.html], Section 11.4

426

UPGRADE_REQUIRED

HTTP/1.1 RFC 7231 [https://tools.ietf.org/html/rfc7231.html], Section 6.5.15

428

PRECONDITION_REQUIRED

Additional HTTP Status Codes RFC 6585 [https://tools.ietf.org/html/rfc6585.html]

429

TOO_MANY_REQUESTS

Additional HTTP Status Codes RFC 6585 [https://tools.ietf.org/html/rfc6585.html]

431

REQUEST_HEADER_FIELDS_TOO_LARGE

Additional HTTP Status Codes RFC 6585 [https://tools.ietf.org/html/rfc6585.html]

500

INTERNAL_SERVER_ERROR

HTTP/1.1 RFC 7231 [https://tools.ietf.org/html/rfc7231.html], Section 6.6.1

501

NOT_IMPLEMENTED

HTTP/1.1 RFC 7231 [https://tools.ietf.org/html/rfc7231.html], Section 6.6.2

502

BAD_GATEWAY

HTTP/1.1 RFC 7231 [https://tools.ietf.org/html/rfc7231.html], Section 6.6.3

503

SERVICE_UNAVAILABLE

HTTP/1.1 RFC 7231 [https://tools.ietf.org/html/rfc7231.html], Section 6.6.4

504

GATEWAY_TIMEOUT

HTTP/1.1 RFC 7231 [https://tools.ietf.org/html/rfc7231.html], Section 6.6.5

505

HTTP_VERSION_NOT_SUPPORTED

HTTP/1.1 RFC 7231 [https://tools.ietf.org/html/rfc7231.html], Section 6.6.6

506

VARIANT_ALSO_NEGOTIATES

Transparent Content Negotiation in HTTP RFC 2295 [https://tools.ietf.org/html/rfc2295.html], Section 8.1 (Expérimental)

507

INSUFFICIENT_STORAGE

WebDAV RFC 4918 [https://tools.ietf.org/html/rfc4918.html], Section 11.5

508

LOOP_DETECTED

WebDAV Binding Extensions RFC 5842 [https://tools.ietf.org/html/rfc5842.html], Section 7.2 (Expérimental)

510

NOT_EXTENDED

An HTTP Extension Framework RFC 2774 [https://tools.ietf.org/html/rfc2774.html], Section 7 (Expérimental)

511

NETWORK_AUTHENTICATION_REQUIRED

Codes d’état HTTP supplémentaires RFC 6585 [https://tools.ietf.org/html/rfc6585.html], Section 6

Dans le but de préserver la compatibilité descendante, les valeurs d’énumération sont aussi présentes dans le module http.client sous forme de constantes. Les noms de valeurs de l’énumération sont accessibles de deux manières : par exemple, le code HTTP 200 est accessible sous les noms http.HTTPStatus.OK et http.client.OK.

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21.12. http.client — HTTP protocol client

Code source : Lib/http/client.py [https://github.com/python/cpython/tree/3.6/Lib/http/client.py]

This module defines classes which implement the client side of the HTTP and HTTPS protocols. It is normally not used directly — the module urllib.request uses it to handle URLs that use HTTP and HTTPS.

Voir aussi

The Requests package [http://docs.python-requests.org/] is recommended for a higher-level HTTP client interface.

Note

HTTPS support is only available if Python was compiled with SSL support (through the ssl module).

The module provides the following classes:

class http.client.HTTPConnection(host, port=None, [timeout, ]source_address=None)

An HTTPConnection instance represents one transaction with an HTTP server. It should be instantiated passing it a host and optional port number. If no port number is passed, the port is extracted from the host string if it has the form host:port, else the default HTTP port (80) is used. If the optional timeout parameter is given, blocking operations (like connection attempts) will timeout after that many seconds (if it is not given, the global default timeout setting is used). The optional source_address parameter may be a tuple of a (host, port) to use as the source address the HTTP connection is made from.

For example, the following calls all create instances that connect to the server at the same host and port:

>>> h1 = http.client.HTTPConnection('www.python.org')
>>> h2 = http.client.HTTPConnection('www.python.org:80')
>>> h3 = http.client.HTTPConnection('www.python.org', 80)
>>> h4 = http.client.HTTPConnection('www.python.org', 80, timeout=10)

Modifié dans la version 3.2: source_address was added.

Modifié dans la version 3.4: The strict parameter was removed. HTTP 0.9-style « Simple Responses » are not longer supported.

class http.client.HTTPSConnection(host, port=None, key_file=None, cert_file=None, [timeout, ]source_address=None, *, context=None, check_hostname=None)

A subclass of HTTPConnection that uses SSL for communication with secure servers. Default port is 443. If context is specified, it must be a ssl.SSLContext instance describing the various SSL options.

Please read Security considerations for more information on best practices.

Modifié dans la version 3.2: source_address, context and check_hostname were added.

Modifié dans la version 3.2: This class now supports HTTPS virtual hosts if possible (that is, if ssl.HAS_SNI is true).

Modifié dans la version 3.4: The strict parameter was removed. HTTP 0.9-style « Simple Responses » are no longer supported.

Modifié dans la version 3.4.3: This class now performs all the necessary certificate and hostname checks by default. To revert to the previous, unverified, behavior ssl._create_unverified_context() can be passed to the context parameter.

Obsolète depuis la version 3.6: key_file and cert_file are deprecated in favor of context. Please use ssl.SSLContext.load_cert_chain() instead, or let ssl.create_default_context() select the system’s trusted CA certificates for you.

The check_hostname parameter is also deprecated; the ssl.SSLContext.check_hostname attribute of context should be used instead.

class http.client.HTTPResponse(sock, debuglevel=0, method=None, url=None)

Class whose instances are returned upon successful connection. Not instantiated directly by user.

Modifié dans la version 3.4: The strict parameter was removed. HTTP 0.9 style « Simple Responses » are no longer supported.

The following exceptions are raised as appropriate:

exception http.client.HTTPException

The base class of the other exceptions in this module. It is a subclass of Exception.

exception http.client.NotConnected

A subclass of HTTPException.

exception http.client.InvalidURL

A subclass of HTTPException, raised if a port is given and is either non-numeric or empty.

exception http.client.UnknownProtocol

A subclass of HTTPException.

exception http.client.UnknownTransferEncoding

A subclass of HTTPException.

exception http.client.UnimplementedFileMode

A subclass of HTTPException.

exception http.client.IncompleteRead

A subclass of HTTPException.

exception http.client.ImproperConnectionState

A subclass of HTTPException.

exception http.client.CannotSendRequest

A subclass of ImproperConnectionState.

exception http.client.CannotSendHeader

A subclass of ImproperConnectionState.

exception http.client.ResponseNotReady

A subclass of ImproperConnectionState.

exception http.client.BadStatusLine

A subclass of HTTPException. Raised if a server responds with a HTTP status code that we don’t understand.

exception http.client.LineTooLong

A subclass of HTTPException. Raised if an excessively long line is received in the HTTP protocol from the server.

exception http.client.RemoteDisconnected

A subclass of ConnectionResetError and BadStatusLine. Raised by HTTPConnection.getresponse() when the attempt to read the response results in no data read from the connection, indicating that the remote end has closed the connection.

Nouveau dans la version 3.5: Previously, BadStatusLine('') was raised.

Les constantes définies dans ce module sont :

http.client.HTTP_PORT

The default port for the HTTP protocol (always 80).

http.client.HTTPS_PORT

The default port for the HTTPS protocol (always 443).

http.client.responses

This dictionary maps the HTTP 1.1 status codes to the W3C names.

Example: http.client.responses[http.client.NOT_FOUND] is 'Not Found'.

See Codes d’état HTTP for a list of HTTP status codes that are available in this module as constants.

21.12.1. HTTPConnection Objects

HTTPConnection instances have the following methods:

HTTPConnection.request(method, url, body=None, headers={}, *, encode_chunked=False)

This will send a request to the server using the HTTP request method method and the selector url.

If body is specified, the specified data is sent after the headers are finished. It may be a str, a bytes-like object, an open file object, or an iterable of bytes. If body is a string, it is encoded as ISO-8859-1, the default for HTTP. If it is a bytes-like object, the bytes are sent as is. If it is a file object, the contents of the file is sent; this file object should support at least the read() method. If the file object is an instance of io.TextIOBase, the data returned by the read() method will be encoded as ISO-8859-1, otherwise the data returned by read() is sent as is. If body is an iterable, the elements of the iterable are sent as is until the iterable is exhausted.

The headers argument should be a mapping of extra HTTP headers to send with the request.

If headers contains neither Content-Length nor Transfer-Encoding, but there is a request body, one of those header fields will be added automatically. If body is None, the Content-Length header is set to 0 for methods that expect a body (PUT, POST, and PATCH). If body is a string or a bytes-like object that is not also a file, the Content-Length header is set to its length. Any other type of body (files and iterables in general) will be chunk-encoded, and the Transfer-Encoding header will automatically be set instead of Content-Length.

The encode_chunked argument is only relevant if Transfer-Encoding is specified in headers. If encode_chunked is False, the HTTPConnection object assumes that all encoding is handled by the calling code. If it is True, the body will be chunk-encoded.

Note

Chunked transfer encoding has been added to the HTTP protocol version 1.1. Unless the HTTP server is known to handle HTTP 1.1, the caller must either specify the Content-Length, or must pass a str or bytes-like object that is not also a file as the body representation.

Nouveau dans la version 3.2: body can now be an iterable.

Modifié dans la version 3.6: If neither Content-Length nor Transfer-Encoding are set in headers, file and iterable body objects are now chunk-encoded. The encode_chunked argument was added. No attempt is made to determine the Content-Length for file objects.

HTTPConnection.getresponse()

Should be called after a request is sent to get the response from the server. Returns an HTTPResponse instance.

Note

Note that you must have read the whole response before you can send a new request to the server.

Modifié dans la version 3.5: If a ConnectionError or subclass is raised, the HTTPConnection object will be ready to reconnect when a new request is sent.

HTTPConnection.set_debuglevel(level)

Set the debugging level. The default debug level is 0, meaning no debugging output is printed. Any value greater than 0 will cause all currently defined debug output to be printed to stdout. The debuglevel is passed to any new HTTPResponse objects that are created.

Nouveau dans la version 3.1.

HTTPConnection.set_tunnel(host, port=None, headers=None)

Set the host and the port for HTTP Connect Tunnelling. This allows running the connection through a proxy server.

The host and port arguments specify the endpoint of the tunneled connection (i.e. the address included in the CONNECT request, not the address of the proxy server).

The headers argument should be a mapping of extra HTTP headers to send with the CONNECT request.

For example, to tunnel through a HTTPS proxy server running locally on port 8080, we would pass the address of the proxy to the HTTPSConnection constructor, and the address of the host that we eventually want to reach to the set_tunnel() method:

>>> import http.client
>>> conn = http.client.HTTPSConnection("localhost", 8080)
>>> conn.set_tunnel("www.python.org")
>>> conn.request("HEAD","/index.html")

Nouveau dans la version 3.2.

HTTPConnection.connect()

Connect to the server specified when the object was created. By default, this is called automatically when making a request if the client does not already have a connection.

HTTPConnection.close()

Close the connection to the server.

As an alternative to using the request() method described above, you can also send your request step by step, by using the four functions below.

HTTPConnection.putrequest(method, url, skip_host=False, skip_accept_encoding=False)

This should be the first call after the connection to the server has been made. It sends a line to the server consisting of the method string, the url string, and the HTTP version (HTTP/1.1). To disable automatic sending of Host: or Accept-Encoding: headers (for example to accept additional content encodings), specify skip_host or skip_accept_encoding with non-False values.

HTTPConnection.putheader(header, argument[, ...])

Send an RFC 822 [https://tools.ietf.org/html/rfc822.html]-style header to the server. It sends a line to the server consisting of the header, a colon and a space, and the first argument. If more arguments are given, continuation lines are sent, each consisting of a tab and an argument.

HTTPConnection.endheaders(message_body=None, *, encode_chunked=False)

Send a blank line to the server, signalling the end of the headers. The optional message_body argument can be used to pass a message body associated with the request.

If encode_chunked is True, the result of each iteration of message_body will be chunk-encoded as specified in RFC 7230 [https://tools.ietf.org/html/rfc7230.html], Section 3.3.1. How the data is encoded is dependent on the type of message_body. If message_body implements the buffer interface the encoding will result in a single chunk. If message_body is a collections.Iterable, each iteration of message_body will result in a chunk. If message_body is a file object, each call to .read() will result in a chunk. The method automatically signals the end of the chunk-encoded data immediately after message_body.

Note

Due to the chunked encoding specification, empty chunks yielded by an iterator body will be ignored by the chunk-encoder. This is to avoid premature termination of the read of the request by the target server due to malformed encoding.

Nouveau dans la version 3.6: Chunked encoding support. The encode_chunked parameter was added.

HTTPConnection.send(data)

Send data to the server. This should be used directly only after the endheaders() method has been called and before getresponse() is called.

21.12.2. HTTPResponse Objects

An HTTPResponse instance wraps the HTTP response from the server. It provides access to the request headers and the entity body. The response is an iterable object and can be used in a with statement.

Modifié dans la version 3.5: The io.BufferedIOBase interface is now implemented and all of its reader operations are supported.

HTTPResponse.read([amt])

Reads and returns the response body, or up to the next amt bytes.

HTTPResponse.readinto(b)

Reads up to the next len(b) bytes of the response body into the buffer b. Returns the number of bytes read.

Nouveau dans la version 3.3.

HTTPResponse.getheader(name, default=None)

Return the value of the header name, or default if there is no header matching name. If there is more than one header with the name name, return all of the values joined by “, “. If “default” is any iterable other than a single string, its elements are similarly returned joined by commas.

HTTPResponse.getheaders()

Return a list of (header, value) tuples.

HTTPResponse.fileno()

Return the fileno of the underlying socket.

HTTPResponse.msg

A http.client.HTTPMessage instance containing the response headers. http.client.HTTPMessage is a subclass of email.message.Message.

HTTPResponse.version

HTTP protocol version used by server. 10 for HTTP/1.0, 11 for HTTP/1.1.

HTTPResponse.status

Status code returned by server.

HTTPResponse.reason

Reason phrase returned by server.

HTTPResponse.debuglevel

A debugging hook. If debuglevel is greater than zero, messages will be printed to stdout as the response is read and parsed.

HTTPResponse.closed

Is True if the stream is closed.

21.12.3. Exemples

Here is an example session that uses the GET method:

>>> import http.client
>>> conn = http.client.HTTPSConnection("www.python.org")
>>> conn.request("GET", "/")
>>> r1 = conn.getresponse()
>>> print(r1.status, r1.reason)
200 OK
>>> data1 = r1.read()  # This will return entire content.
>>> # The following example demonstrates reading data in chunks.
>>> conn.request("GET", "/")
>>> r1 = conn.getresponse()
>>> while not r1.closed:
...     print(r1.read(200))  # 200 bytes
b'<!doctype html>\n<!--[if"...
...
>>> # Example of an invalid request
>>> conn.request("GET", "/parrot.spam")
>>> r2 = conn.getresponse()
>>> print(r2.status, r2.reason)
404 Not Found
>>> data2 = r2.read()
>>> conn.close()

Here is an example session that uses the HEAD method. Note that the HEAD method never returns any data.

>>> import http.client
>>> conn = http.client.HTTPSConnection("www.python.org")
>>> conn.request("HEAD", "/")
>>> res = conn.getresponse()
>>> print(res.status, res.reason)
200 OK
>>> data = res.read()
>>> print(len(data))
0
>>> data == b''
True

Here is an example session that shows how to POST requests:

>>> import http.client, urllib.parse
>>> params = urllib.parse.urlencode({'@number': 12524, '@type': 'issue', '@action': 'show'})
>>> headers = {"Content-type": "application/x-www-form-urlencoded",
...            "Accept": "text/plain"}
>>> conn = http.client.HTTPConnection("bugs.python.org")
>>> conn.request("POST", "", params, headers)
>>> response = conn.getresponse()
>>> print(response.status, response.reason)
302 Found
>>> data = response.read()
>>> data
b'Redirecting to <a href="http://bugs.python.org/issue12524">http://bugs.python.org/issue12524</a>'
>>> conn.close()

Client side HTTP PUT requests are very similar to POST requests. The difference lies only the server side where HTTP server will allow resources to be created via PUT request. It should be noted that custom HTTP methods +are also handled in urllib.request.Request by sending the appropriate +method attribute.Here is an example session that shows how to do PUT request using http.client:

>>> # This creates an HTTP message
>>> # with the content of BODY as the enclosed representation
>>> # for the resource http://localhost:8080/file
...
>>> import http.client
>>> BODY = "***filecontents***"
>>> conn = http.client.HTTPConnection("localhost", 8080)
>>> conn.request("PUT", "/file", BODY)
>>> response = conn.getresponse()
>>> print(response.status, response.reason)
200, OK

21.12.4. HTTPMessage Objects

An http.client.HTTPMessage instance holds the headers from an HTTP response. It is implemented using the email.message.Message class.

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21.13. ftplib — FTP protocol client

Code source : Lib/ftplib.py [https://github.com/python/cpython/tree/3.6/Lib/ftplib.py]

This module defines the class FTP and a few related items. The FTP class implements the client side of the FTP protocol. You can use this to write Python programs that perform a variety of automated FTP jobs, such as mirroring other FTP servers. It is also used by the module urllib.request to handle URLs that use FTP. For more information on FTP (File Transfer Protocol), see Internet RFC 959 [https://tools.ietf.org/html/rfc959.html].

Here’s a sample session using the ftplib module:

>>> from ftplib import FTP
>>> ftp = FTP('ftp.debian.org')     # connect to host, default port
>>> ftp.login()                     # user anonymous, passwd anonymous@
'230 Login successful.'
>>> ftp.cwd('debian')               # change into "debian" directory
>>> ftp.retrlines('LIST')           # list directory contents
-rw-rw-r--    1 1176     1176         1063 Jun 15 10:18 README
...
drwxr-sr-x    5 1176     1176         4096 Dec 19  2000 pool
drwxr-sr-x    4 1176     1176         4096 Nov 17  2008 project
drwxr-xr-x    3 1176     1176         4096 Oct 10  2012 tools
'226 Directory send OK.'
>>> ftp.retrbinary('RETR README', open('README', 'wb').write)
'226 Transfer complete.'
>>> ftp.quit()

Le module définit les éléments suivants :

class ftplib.FTP(host='', user='', passwd='', acct='', timeout=None, source_address=None)

Return a new instance of the FTP class. When host is given, the method call connect(host) is made. When user is given, additionally the method call login(user, passwd, acct) is made (where passwd and acct default to the empty string when not given). The optional timeout parameter specifies a timeout in seconds for blocking operations like the connection attempt (if is not specified, the global default timeout setting will be used). source_address is a 2-tuple (host, port) for the socket to bind to as its source address before connecting.

The FTP class supports the with statement, e.g.:

>>> from ftplib import FTP
>>> with FTP("ftp1.at.proftpd.org") as ftp:
...     ftp.login()
...     ftp.dir()
...
'230 Anonymous login ok, restrictions apply.'
dr-xr-xr-x   9 ftp      ftp           154 May  6 10:43 .
dr-xr-xr-x   9 ftp      ftp           154 May  6 10:43 ..
dr-xr-xr-x   5 ftp      ftp          4096 May  6 10:43 CentOS
dr-xr-xr-x   3 ftp      ftp            18 Jul 10  2008 Fedora
>>>

Modifié dans la version 3.2: La prise en charge de l’instruction with a été ajoutée.

Modifié dans la version 3.3: source_address parameter was added.

class ftplib.FTP_TLS(host='', user='', passwd='', acct='', keyfile=None, certfile=None, context=None, timeout=None, source_address=None)

A FTP subclass which adds TLS support to FTP as described in RFC 4217 [https://tools.ietf.org/html/rfc4217.html]. Connect as usual to port 21 implicitly securing the FTP control connection before authenticating. Securing the data connection requires the user to explicitly ask for it by calling the prot_p() method. context is a ssl.SSLContext object which allows bundling SSL configuration options, certificates and private keys into a single (potentially long-lived) structure. Please read Security considerations for best practices.

keyfile and certfile are a legacy alternative to context – they can point to PEM-formatted private key and certificate chain files (respectively) for the SSL connection.

Nouveau dans la version 3.2.

Modifié dans la version 3.3: source_address parameter was added.

Modifié dans la version 3.4: The class now supports hostname check with ssl.SSLContext.check_hostname and Server Name Indication (see ssl.HAS_SNI).

Obsolète depuis la version 3.6: keyfile and certfile are deprecated in favor of context. Please use ssl.SSLContext.load_cert_chain() instead, or let ssl.create_default_context() select the system’s trusted CA certificates for you.

Here’s a sample session using the FTP_TLS class:

>>> ftps = FTP_TLS('ftp.pureftpd.org')
>>> ftps.login()
'230 Anonymous user logged in'
>>> ftps.prot_p()
'200 Data protection level set to "private"'
>>> ftps.nlst()
['6jack', 'OpenBSD', 'antilink', 'blogbench', 'bsdcam', 'clockspeed', 'djbdns-jedi', 'docs', 'eaccelerator-jedi', 'favicon.ico', 'francotone', 'fugu', 'ignore', 'libpuzzle', 'metalog', 'minidentd', 'misc', 'mysql-udf-global-user-variables', 'php-jenkins-hash', 'php-skein-hash', 'php-webdav', 'phpaudit', 'phpbench', 'pincaster', 'ping', 'posto', 'pub', 'public', 'public_keys', 'pure-ftpd', 'qscan', 'qtc', 'sharedance', 'skycache', 'sound', 'tmp', 'ucarp']

exception ftplib.error_reply

Exception raised when an unexpected reply is received from the server.

exception ftplib.error_temp

Exception raised when an error code signifying a temporary error (response codes in the range 400–499) is received.

exception ftplib.error_perm

Exception raised when an error code signifying a permanent error (response codes in the range 500–599) is received.

exception ftplib.error_proto

Exception raised when a reply is received from the server that does not fit the response specifications of the File Transfer Protocol, i.e. begin with a digit in the range 1–5.

ftplib.all_errors

The set of all exceptions (as a tuple) that methods of FTP instances may raise as a result of problems with the FTP connection (as opposed to programming errors made by the caller). This set includes the four exceptions listed above as well as OSError.

Voir aussi

Module netrc

Parser for the .netrc file format. The file .netrc is typically used by FTP clients to load user authentication information before prompting the user.

21.13.1. FTP Objects

Several methods are available in two flavors: one for handling text files and another for binary files. These are named for the command which is used followed by lines for the text version or binary for the binary version.

FTP instances have the following methods:

FTP.set_debuglevel(level)

Set the instance’s debugging level. This controls the amount of debugging output printed. The default, 0, produces no debugging output. A value of 1 produces a moderate amount of debugging output, generally a single line per request. A value of 2 or higher produces the maximum amount of debugging output, logging each line sent and received on the control connection.

FTP.connect(host='', port=0, timeout=None, source_address=None)

Connect to the given host and port. The default port number is 21, as specified by the FTP protocol specification. It is rarely needed to specify a different port number. This function should be called only once for each instance; it should not be called at all if a host was given when the instance was created. All other methods can only be used after a connection has been made. The optional timeout parameter specifies a timeout in seconds for the connection attempt. If no timeout is passed, the global default timeout setting will be used. source_address is a 2-tuple (host, port) for the socket to bind to as its source address before connecting.

Modifié dans la version 3.3: source_address parameter was added.

FTP.getwelcome()

Return the welcome message sent by the server in reply to the initial connection. (This message sometimes contains disclaimers or help information that may be relevant to the user.)

FTP.login(user='anonymous', passwd='', acct='')

Log in as the given user. The passwd and acct parameters are optional and default to the empty string. If no user is specified, it defaults to 'anonymous'. If user is 'anonymous', the default passwd is 'anonymous@'. This function should be called only once for each instance, after a connection has been established; it should not be called at all if a host and user were given when the instance was created. Most FTP commands are only allowed after the client has logged in. The acct parameter supplies « accounting information »; few systems implement this.

FTP.abort()

Abort a file transfer that is in progress. Using this does not always work, but it’s worth a try.

FTP.sendcmd(cmd)

Send a simple command string to the server and return the response string.

FTP.voidcmd(cmd)

Send a simple command string to the server and handle the response. Return nothing if a response code corresponding to success (codes in the range 200–299) is received. Raise error_reply otherwise.

FTP.retrbinary(cmd, callback, blocksize=8192, rest=None)

Retrieve a file in binary transfer mode. cmd should be an appropriate RETR command: 'RETR filename'. The callback function is called for each block of data received, with a single bytes argument giving the data block. The optional blocksize argument specifies the maximum chunk size to read on the low-level socket object created to do the actual transfer (which will also be the largest size of the data blocks passed to callback). A reasonable default is chosen. rest means the same thing as in the transfercmd() method.

FTP.retrlines(cmd, callback=None)

Retrieve a file or directory listing in ASCII transfer mode. cmd should be an appropriate RETR command (see retrbinary()) or a command such as LIST or NLST (usually just the string 'LIST'). LIST retrieves a list of files and information about those files. NLST retrieves a list of file names. The callback function is called for each line with a string argument containing the line with the trailing CRLF stripped. The default callback prints the line to sys.stdout.

FTP.set_pasv(val)

Enable « passive » mode if val is true, otherwise disable passive mode. Passive mode is on by default.

FTP.storbinary(cmd, fp, blocksize=8192, callback=None, rest=None)

Store a file in binary transfer mode. cmd should be an appropriate STOR command: "STOR filename". fp is a file object (opened in binary mode) which is read until EOF using its read() method in blocks of size blocksize to provide the data to be stored. The blocksize argument defaults to 8192. callback is an optional single parameter callable that is called on each block of data after it is sent. rest means the same thing as in the transfercmd() method.

Modifié dans la version 3.2: rest parameter added.

FTP.storlines(cmd, fp, callback=None)

Store a file in ASCII transfer mode. cmd should be an appropriate STOR command (see storbinary()). Lines are read until EOF from the file object fp (opened in binary mode) using its readline() method to provide the data to be stored. callback is an optional single parameter callable that is called on each line after it is sent.

FTP.transfercmd(cmd, rest=None)

Initiate a transfer over the data connection. If the transfer is active, send an EPRT or PORT command and the transfer command specified by cmd, and accept the connection. If the server is passive, send an EPSV or PASV command, connect to it, and start the transfer command. Either way, return the socket for the connection.

If optional rest is given, a REST command is sent to the server, passing rest as an argument. rest is usually a byte offset into the requested file, telling the server to restart sending the file’s bytes at the requested offset, skipping over the initial bytes. Note however that RFC 959 [https://tools.ietf.org/html/rfc959.html] requires only that rest be a string containing characters in the printable range from ASCII code 33 to ASCII code 126. The transfercmd() method, therefore, converts rest to a string, but no check is performed on the string’s contents. If the server does not recognize the REST command, an error_reply exception will be raised. If this happens, simply call transfercmd() without a rest argument.

FTP.ntransfercmd(cmd, rest=None)

Like transfercmd(), but returns a tuple of the data connection and the expected size of the data. If the expected size could not be computed, None will be returned as the expected size. cmd and rest means the same thing as in transfercmd().

FTP.mlsd(path="", facts=[])

List a directory in a standardized format by using MLSD command (RFC 3659 [https://tools.ietf.org/html/rfc3659.html]). If path is omitted the current directory is assumed. facts is a list of strings representing the type of information desired (e.g. ["type", "size", "perm"]). Return a generator object yielding a tuple of two elements for every file found in path. First element is the file name, the second one is a dictionary containing facts about the file name. Content of this dictionary might be limited by the facts argument but server is not guaranteed to return all requested facts.

Nouveau dans la version 3.3.

FTP.nlst(argument[, ...])

Return a list of file names as returned by the NLST command. The optional argument is a directory to list (default is the current server directory). Multiple arguments can be used to pass non-standard options to the NLST command.

Note

If your server supports the command, mlsd() offers a better API.

FTP.dir(argument[, ...])

Produce a directory listing as returned by the LIST command, printing it to standard output. The optional argument is a directory to list (default is the current server directory). Multiple arguments can be used to pass non-standard options to the LIST command. If the last argument is a function, it is used as a callback function as for retrlines(); the default prints to sys.stdout. This method returns None.

Note

If your server supports the command, mlsd() offers a better API.

FTP.rename(fromname, toname)

Rename file fromname on the server to toname.

FTP.delete(filename)

Remove the file named filename from the server. If successful, returns the text of the response, otherwise raises error_perm on permission errors or error_reply on other errors.

FTP.cwd(pathname)

Set the current directory on the server.

FTP.mkd(pathname)

Create a new directory on the server.

FTP.pwd()

Return the pathname of the current directory on the server.

FTP.rmd(dirname)

Remove the directory named dirname on the server.

FTP.size(filename)

Request the size of the file named filename on the server. On success, the size of the file is returned as an integer, otherwise None is returned. Note that the SIZE command is not standardized, but is supported by many common server implementations.

FTP.quit()

Send a QUIT command to the server and close the connection. This is the « polite » way to close a connection, but it may raise an exception if the server responds with an error to the QUIT command. This implies a call to the close() method which renders the FTP instance useless for subsequent calls (see below).

FTP.close()

Close the connection unilaterally. This should not be applied to an already closed connection such as after a successful call to quit(). After this call the FTP instance should not be used any more (after a call to close() or quit() you cannot reopen the connection by issuing another login() method).

21.13.2. FTP_TLS Objects

FTP_TLS class inherits from FTP, defining these additional objects:

FTP_TLS.ssl_version

The SSL version to use (defaults to ssl.PROTOCOL_SSLv23).

FTP_TLS.auth()

Set up a secure control connection by using TLS or SSL, depending on what is specified in the ssl_version attribute.

Modifié dans la version 3.4: The method now supports hostname check with ssl.SSLContext.check_hostname and Server Name Indication (see ssl.HAS_SNI).

FTP_TLS.ccc()

Revert control channel back to plaintext. This can be useful to take advantage of firewalls that know how to handle NAT with non-secure FTP without opening fixed ports.

Nouveau dans la version 3.3.

FTP_TLS.prot_p()

Set up secure data connection.

FTP_TLS.prot_c()

Set up clear text data connection.

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21.14. poplib — POP3 protocol client

Code source : Lib/poplib.py [https://github.com/python/cpython/tree/3.6/Lib/poplib.py]

This module defines a class, POP3, which encapsulates a connection to a POP3 server and implements the protocol as defined in RFC 1939 [https://tools.ietf.org/html/rfc1939.html]. The POP3 class supports both the minimal and optional command sets from RFC 1939 [https://tools.ietf.org/html/rfc1939.html]. The POP3 class also supports the STLS command introduced in RFC 2595 [https://tools.ietf.org/html/rfc2595.html] to enable encrypted communication on an already established connection.

Additionally, this module provides a class POP3_SSL, which provides support for connecting to POP3 servers that use SSL as an underlying protocol layer.

Note that POP3, though widely supported, is obsolescent. The implementation quality of POP3 servers varies widely, and too many are quite poor. If your mailserver supports IMAP, you would be better off using the imaplib.IMAP4 class, as IMAP servers tend to be better implemented.

The poplib module provides two classes:

class poplib.POP3(host, port=POP3_PORT[, timeout])

This class implements the actual POP3 protocol. The connection is created when the instance is initialized. If port is omitted, the standard POP3 port (110) is used. The optional timeout parameter specifies a timeout in seconds for the connection attempt (if not specified, the global default timeout setting will be used).

class poplib.POP3_SSL(host, port=POP3_SSL_PORT, keyfile=None, certfile=None, timeout=None, context=None)

This is a subclass of POP3 that connects to the server over an SSL encrypted socket. If port is not specified, 995, the standard POP3-over-SSL port is used. timeout works as in the POP3 constructor. context is an optional ssl.SSLContext object which allows bundling SSL configuration options, certificates and private keys into a single (potentially long-lived) structure. Please read Security considerations for best practices.

keyfile and certfile are a legacy alternative to context - they can point to PEM-formatted private key and certificate chain files, respectively, for the SSL connection.

Modifié dans la version 3.2: context parameter added.

Modifié dans la version 3.4: The class now supports hostname check with ssl.SSLContext.check_hostname and Server Name Indication (see ssl.HAS_SNI).

Obsolète depuis la version 3.6: keyfile and certfile are deprecated in favor of context. Please use ssl.SSLContext.load_cert_chain() instead, or let ssl.create_default_context() select the system’s trusted CA certificates for you.

One exception is defined as an attribute of the poplib module:

exception poplib.error_proto

Exception raised on any errors from this module (errors from socket module are not caught). The reason for the exception is passed to the constructor as a string.

Voir aussi

Module imaplib

The standard Python IMAP module.

Frequently Asked Questions About Fetchmail [http://www.catb.org/~esr/fetchmail/fetchmail-FAQ.html]

The FAQ for the fetchmail POP/IMAP client collects information on POP3 server variations and RFC noncompliance that may be useful if you need to write an application based on the POP protocol.

21.14.1. POP3 Objects

All POP3 commands are represented by methods of the same name, in lower-case; most return the response text sent by the server.

An POP3 instance has the following methods:

POP3.set_debuglevel(level)

Set the instance’s debugging level. This controls the amount of debugging output printed. The default, 0, produces no debugging output. A value of 1 produces a moderate amount of debugging output, generally a single line per request. A value of 2 or higher produces the maximum amount of debugging output, logging each line sent and received on the control connection.

POP3.getwelcome()

Returns the greeting string sent by the POP3 server.

POP3.capa()

Query the server’s capabilities as specified in RFC 2449 [https://tools.ietf.org/html/rfc2449.html]. Returns a dictionary in the form {'name': ['param'...]}.

Nouveau dans la version 3.4.

POP3.user(username)

Send user command, response should indicate that a password is required.

POP3.pass_(password)

Send password, response includes message count and mailbox size. Note: the mailbox on the server is locked until quit() is called.

POP3.apop(user, secret)

Use the more secure APOP authentication to log into the POP3 server.

POP3.rpop(user)

Use RPOP authentication (similar to UNIX r-commands) to log into POP3 server.

POP3.stat()

Get mailbox status. The result is a tuple of 2 integers: (message count, mailbox size).

POP3.list([which])

Request message list, result is in the form (response, ['mesg_num octets', ...], octets). If which is set, it is the message to list.

POP3.retr(which)

Retrieve whole message number which, and set its seen flag. Result is in form (response, ['line', ...], octets).

POP3.dele(which)

Flag message number which for deletion. On most servers deletions are not actually performed until QUIT (the major exception is Eudora QPOP, which deliberately violates the RFCs by doing pending deletes on any disconnect).

POP3.rset()

Remove any deletion marks for the mailbox.

POP3.noop()

Do nothing. Might be used as a keep-alive.

POP3.quit()

Signoff: commit changes, unlock mailbox, drop connection.

POP3.top(which, howmuch)

Retrieves the message header plus howmuch lines of the message after the header of message number which. Result is in form (response, ['line', ...], octets).

The POP3 TOP command this method uses, unlike the RETR command, doesn’t set the message’s seen flag; unfortunately, TOP is poorly specified in the RFCs and is frequently broken in off-brand servers. Test this method by hand against the POP3 servers you will use before trusting it.

POP3.uidl(which=None)

Return message digest (unique id) list. If which is specified, result contains the unique id for that message in the form 'response mesgnum uid, otherwise result is list (response, ['mesgnum uid', ...], octets).

POP3.utf8()

Try to switch to UTF-8 mode. Returns the server response if successful, raises error_proto if not. Specified in RFC 6856 [https://tools.ietf.org/html/rfc6856.html].

Nouveau dans la version 3.5.

POP3.stls(context=None)

Start a TLS session on the active connection as specified in RFC 2595 [https://tools.ietf.org/html/rfc2595.html]. This is only allowed before user authentication

context parameter is a ssl.SSLContext object which allows bundling SSL configuration options, certificates and private keys into a single (potentially long-lived) structure. Please read Security considerations for best practices.

This method supports hostname checking via ssl.SSLContext.check_hostname and Server Name Indication (see ssl.HAS_SNI).

Nouveau dans la version 3.4.

Instances of POP3_SSL have no additional methods. The interface of this subclass is identical to its parent.

21.14.2. POP3 Example

Here is a minimal example (without error checking) that opens a mailbox and retrieves and prints all messages:

import getpass, poplib

M = poplib.POP3('localhost')
M.user(getpass.getuser())
M.pass_(getpass.getpass())
numMessages = len(M.list()[1])
for i in range(numMessages):
    for j in M.retr(i+1)[1]:
        print(j)

At the end of the module, there is a test section that contains a more extensive example of usage.

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21.15. imaplib — IMAP4 protocol client

Code source : Lib/imaplib.py [https://github.com/python/cpython/tree/3.6/Lib/imaplib.py]

This module defines three classes, IMAP4, IMAP4_SSL and IMAP4_stream, which encapsulate a connection to an IMAP4 server and implement a large subset of the IMAP4rev1 client protocol as defined in RFC 2060 [https://tools.ietf.org/html/rfc2060.html]. It is backward compatible with IMAP4 (RFC 1730 [https://tools.ietf.org/html/rfc1730.html]) servers, but note that the STATUS command is not supported in IMAP4.

Three classes are provided by the imaplib module, IMAP4 is the base class:

class imaplib.IMAP4(host='', port=IMAP4_PORT)

This class implements the actual IMAP4 protocol. The connection is created and protocol version (IMAP4 or IMAP4rev1) is determined when the instance is initialized. If host is not specified, '' (the local host) is used. If port is omitted, the standard IMAP4 port (143) is used.

The IMAP4 class supports the with statement. When used like this, the IMAP4 LOGOUT command is issued automatically when the with statement exits. E.g.:

>>> from imaplib import IMAP4
>>> with IMAP4("domain.org") as M:
...     M.noop()
...
('OK', [b'Nothing Accomplished. d25if65hy903weo.87'])

Modifié dans la version 3.5: La prise en charge de l’instruction with a été ajoutée.

Three exceptions are defined as attributes of the IMAP4 class:

exception IMAP4.error

Exception raised on any errors. The reason for the exception is passed to the constructor as a string.

exception IMAP4.abort

IMAP4 server errors cause this exception to be raised. This is a sub-class of IMAP4.error. Note that closing the instance and instantiating a new one will usually allow recovery from this exception.

exception IMAP4.readonly

This exception is raised when a writable mailbox has its status changed by the server. This is a sub-class of IMAP4.error. Some other client now has write permission, and the mailbox will need to be re-opened to re-obtain write permission.

There’s also a subclass for secure connections:

class imaplib.IMAP4_SSL(host='', port=IMAP4_SSL_PORT, keyfile=None, certfile=None, ssl_context=None)

This is a subclass derived from IMAP4 that connects over an SSL encrypted socket (to use this class you need a socket module that was compiled with SSL support). If host is not specified, '' (the local host) is used. If port is omitted, the standard IMAP4-over-SSL port (993) is used. ssl_context is a ssl.SSLContext object which allows bundling SSL configuration options, certificates and private keys into a single (potentially long-lived) structure. Please read Security considerations for best practices.

keyfile and certfile are a legacy alternative to ssl_context - they can point to PEM-formatted private key and certificate chain files for the SSL connection. Note that the keyfile/certfile parameters are mutually exclusive with ssl_context, a ValueError is raised if keyfile/certfile is provided along with ssl_context.

Modifié dans la version 3.3: ssl_context parameter added.

Modifié dans la version 3.4: The class now supports hostname check with ssl.SSLContext.check_hostname and Server Name Indication (see ssl.HAS_SNI).

Obsolète depuis la version 3.6: keyfile and certfile are deprecated in favor of ssl_context. Please use ssl.SSLContext.load_cert_chain() instead, or let ssl.create_default_context() select the system’s trusted CA certificates for you.

The second subclass allows for connections created by a child process:

class imaplib.IMAP4_stream(command)

This is a subclass derived from IMAP4 that connects to the stdin/stdout file descriptors created by passing command to subprocess.Popen().

The following utility functions are defined:

imaplib.Internaldate2tuple(datestr)

Parse an IMAP4 INTERNALDATE string and return corresponding local time. The return value is a time.struct_time tuple or None if the string has wrong format.

imaplib.Int2AP(num)

Converts an integer into a string representation using characters from the set [A .. P].

imaplib.ParseFlags(flagstr)

Converts an IMAP4 FLAGS response to a tuple of individual flags.

imaplib.Time2Internaldate(date_time)

Convert date_time to an IMAP4 INTERNALDATE representation. The return value is a string in the form: "DD-Mmm-YYYY HH:MM:SS +HHMM" (including double-quotes). The date_time argument can be a number (int or float) representing seconds since epoch (as returned by time.time()), a 9-tuple representing local time an instance of time.struct_time (as returned by time.localtime()), an aware instance of datetime.datetime, or a double-quoted string. In the last case, it is assumed to already be in the correct format.

Note that IMAP4 message numbers change as the mailbox changes; in particular, after an EXPUNGE command performs deletions the remaining messages are renumbered. So it is highly advisable to use UIDs instead, with the UID command.

At the end of the module, there is a test section that contains a more extensive example of usage.

Voir aussi

Documents describing the protocol, and sources and binaries for servers implementing it, can all be found at the University of Washington’s IMAP Information Center (https://www.washington.edu/imap/).

21.15.1. IMAP4 Objects

All IMAP4rev1 commands are represented by methods of the same name, either upper-case or lower-case.

All arguments to commands are converted to strings, except for AUTHENTICATE, and the last argument to APPEND which is passed as an IMAP4 literal. If necessary (the string contains IMAP4 protocol-sensitive characters and isn’t enclosed with either parentheses or double quotes) each string is quoted. However, the password argument to the LOGIN command is always quoted. If you want to avoid having an argument string quoted (eg: the flags argument to STORE) then enclose the string in parentheses (eg: r'(\Deleted)').

Each command returns a tuple: (type, [data, ...]) where type is usually 'OK' or 'NO', and data is either the text from the command response, or mandated results from the command. Each data is either a string, or a tuple. If a tuple, then the first part is the header of the response, and the second part contains the data (ie: “literal” value).

The message_set options to commands below is a string specifying one or more messages to be acted upon. It may be a simple message number ('1'), a range of message numbers ('2:4'), or a group of non-contiguous ranges separated by commas ('1:3,6:9'). A range can contain an asterisk to indicate an infinite upper bound ('3:*').

An IMAP4 instance has the following methods:

IMAP4.append(mailbox, flags, date_time, message)

Append message to named mailbox.

IMAP4.authenticate(mechanism, authobject)

Authenticate command — requires response processing.

mechanism specifies which authentication mechanism is to be used - it should appear in the instance variable capabilities in the form AUTH=mechanism.

authobject must be a callable object:

data = authobject(response)

It will be called to process server continuation responses; the response argument it is passed will be bytes. It should return bytes data that will be base64 encoded and sent to the server. It should return None if the client abort response * should be sent instead.

Modifié dans la version 3.5: string usernames and passwords are now encoded to utf-8 instead of being limited to ASCII.

IMAP4.check()

Checkpoint mailbox on server.

IMAP4.close()

Close currently selected mailbox. Deleted messages are removed from writable mailbox. This is the recommended command before LOGOUT.

IMAP4.copy(message_set, new_mailbox)

Copy message_set messages onto end of new_mailbox.

IMAP4.create(mailbox)

Create new mailbox named mailbox.

IMAP4.delete(mailbox)

Delete old mailbox named mailbox.

IMAP4.deleteacl(mailbox, who)

Delete the ACLs (remove any rights) set for who on mailbox.

IMAP4.enable(capability)

Enable capability (see RFC 5161 [https://tools.ietf.org/html/rfc5161.html]). Most capabilities do not need to be enabled. Currently only the UTF8=ACCEPT capability is supported (see RFC 6855 [https://tools.ietf.org/html/rfc6855.html]).

Nouveau dans la version 3.5: The enable() method itself, and RFC 6855 [https://tools.ietf.org/html/rfc6855.html] support.

IMAP4.expunge()

Permanently remove deleted items from selected mailbox. Generates an EXPUNGE response for each deleted message. Returned data contains a list of EXPUNGE message numbers in order received.

IMAP4.fetch(message_set, message_parts)

Fetch (parts of) messages. message_parts should be a string of message part names enclosed within parentheses, eg: "(UID BODY[TEXT])". Returned data are tuples of message part envelope and data.

IMAP4.getacl(mailbox)

Get the ACLs for mailbox. The method is non-standard, but is supported by the Cyrus server.

IMAP4.getannotation(mailbox, entry, attribute)

Retrieve the specified ANNOTATIONs for mailbox. The method is non-standard, but is supported by the Cyrus server.

IMAP4.getquota(root)

Get the quota root’s resource usage and limits. This method is part of the IMAP4 QUOTA extension defined in rfc2087.

IMAP4.getquotaroot(mailbox)

Get the list of quota roots for the named mailbox. This method is part of the IMAP4 QUOTA extension defined in rfc2087.

IMAP4.list([directory[, pattern]])

List mailbox names in directory matching pattern. directory defaults to the top-level mail folder, and pattern defaults to match anything. Returned data contains a list of LIST responses.

IMAP4.login(user, password)

Identify the client using a plaintext password. The password will be quoted.

IMAP4.login_cram_md5(user, password)

Force use of CRAM-MD5 authentication when identifying the client to protect the password. Will only work if the server CAPABILITY response includes the phrase AUTH=CRAM-MD5.

IMAP4.logout()

Shutdown connection to server. Returns server BYE response.

IMAP4.lsub(directory='""', pattern='*')

List subscribed mailbox names in directory matching pattern. directory defaults to the top level directory and pattern defaults to match any mailbox. Returned data are tuples of message part envelope and data.

IMAP4.myrights(mailbox)

Show my ACLs for a mailbox (i.e. the rights that I have on mailbox).

IMAP4.namespace()

Returns IMAP namespaces as defined in RFC 2342 [https://tools.ietf.org/html/rfc2342.html].

IMAP4.noop()

Send NOOP to server.

IMAP4.open(host, port)

Opens socket to port at host. This method is implicitly called by the IMAP4 constructor. The connection objects established by this method will be used in the IMAP4.read(), IMAP4.readline(), IMAP4.send(), and IMAP4.shutdown() methods. You may override this method.

IMAP4.partial(message_num, message_part, start, length)

Fetch truncated part of a message. Returned data is a tuple of message part envelope and data.

IMAP4.proxyauth(user)

Assume authentication as user. Allows an authorised administrator to proxy into any user’s mailbox.

IMAP4.read(size)

Reads size bytes from the remote server. You may override this method.

IMAP4.readline()

Reads one line from the remote server. You may override this method.

IMAP4.recent()

Prompt server for an update. Returned data is None if no new messages, else value of RECENT response.

IMAP4.rename(oldmailbox, newmailbox)

Rename mailbox named oldmailbox to newmailbox.

IMAP4.response(code)

Return data for response code if received, or None. Returns the given code, instead of the usual type.

IMAP4.search(charset, criterion[, ...])

Search mailbox for matching messages. charset may be None, in which case no CHARSET will be specified in the request to the server. The IMAP protocol requires that at least one criterion be specified; an exception will be raised when the server returns an error. charset must be None if the UTF8=ACCEPT capability was enabled using the enable() command.

Exemple :

# M is a connected IMAP4 instance...
typ, msgnums = M.search(None, 'FROM', '"LDJ"')

# or:
typ, msgnums = M.search(None, '(FROM "LDJ")')

IMAP4.select(mailbox='INBOX', readonly=False)

Select a mailbox. Returned data is the count of messages in mailbox (EXISTS response). The default mailbox is 'INBOX'. If the readonly flag is set, modifications to the mailbox are not allowed.

IMAP4.send(data)

Sends data to the remote server. You may override this method.

IMAP4.setacl(mailbox, who, what)

Set an ACL for mailbox. The method is non-standard, but is supported by the Cyrus server.

IMAP4.setannotation(mailbox, entry, attribute[, ...])

Set ANNOTATIONs for mailbox. The method is non-standard, but is supported by the Cyrus server.

IMAP4.setquota(root, limits)

Set the quota root’s resource limits. This method is part of the IMAP4 QUOTA extension defined in rfc2087.

IMAP4.shutdown()

Close connection established in open. This method is implicitly called by IMAP4.logout(). You may override this method.

IMAP4.socket()

Returns socket instance used to connect to server.

IMAP4.sort(sort_criteria, charset, search_criterion[, ...])

The sort command is a variant of search with sorting semantics for the results. Returned data contains a space separated list of matching message numbers.

Sort has two arguments before the search_criterion argument(s); a parenthesized list of sort_criteria, and the searching charset. Note that unlike search, the searching charset argument is mandatory. There is also a uid sort command which corresponds to sort the way that uid search corresponds to search. The sort command first searches the mailbox for messages that match the given searching criteria using the charset argument for the interpretation of strings in the searching criteria. It then returns the numbers of matching messages.

This is an IMAP4rev1 extension command.

IMAP4.starttls(ssl_context=None)

Send a STARTTLS command. The ssl_context argument is optional and should be a ssl.SSLContext object. This will enable encryption on the IMAP connection. Please read Security considerations for best practices.

Nouveau dans la version 3.2.

Modifié dans la version 3.4: The method now supports hostname check with ssl.SSLContext.check_hostname and Server Name Indication (see ssl.HAS_SNI).

IMAP4.status(mailbox, names)

Request named status conditions for mailbox.

IMAP4.store(message_set, command, flag_list)

Alters flag dispositions for messages in mailbox. command is specified by section 6.4.6 of RFC 2060 [https://tools.ietf.org/html/rfc2060.html] as being one of « FLAGS », « +FLAGS », or « -FLAGS », optionally with a suffix of « .SILENT ».

For example, to set the delete flag on all messages:

typ, data = M.search(None, 'ALL')
for num in data[0].split():
   M.store(num, '+FLAGS', '\\Deleted')
M.expunge()

Note

Creating flags containing “]” (for example: « [test] ») violates RFC 3501 [https://tools.ietf.org/html/rfc3501.html] (the IMAP protocol). However, imaplib has historically allowed creation of such tags, and popular IMAP servers, such as Gmail, accept and produce such flags. There are non-Python programs which also create such tags. Although it is an RFC violation and IMAP clients and servers are supposed to be strict, imaplib nonetheless continues to allow such tags to be created for backward compatibility reasons, and as of python 3.6, handles them if they are sent from the server, since this improves real-world compatibility.

IMAP4.subscribe(mailbox)

Subscribe to new mailbox.

IMAP4.thread(threading_algorithm, charset, search_criterion[, ...])

The thread command is a variant of search with threading semantics for the results. Returned data contains a space separated list of thread members.

Thread members consist of zero or more messages numbers, delimited by spaces, indicating successive parent and child.

Thread has two arguments before the search_criterion argument(s); a threading_algorithm, and the searching charset. Note that unlike search, the searching charset argument is mandatory. There is also a uid thread command which corresponds to thread the way that uid search corresponds to search. The thread command first searches the mailbox for messages that match the given searching criteria using the charset argument for the interpretation of strings in the searching criteria. It then returns the matching messages threaded according to the specified threading algorithm.

This is an IMAP4rev1 extension command.

IMAP4.uid(command, arg[, ...])

Execute command args with messages identified by UID, rather than message number. Returns response appropriate to command. At least one argument must be supplied; if none are provided, the server will return an error and an exception will be raised.

IMAP4.unsubscribe(mailbox)

Unsubscribe from old mailbox.

IMAP4.xatom(name[, ...])

Allow simple extension commands notified by server in CAPABILITY response.

The following attributes are defined on instances of IMAP4:

IMAP4.PROTOCOL_VERSION

The most recent supported protocol in the CAPABILITY response from the server.

IMAP4.debug

Integer value to control debugging output. The initialize value is taken from the module variable Debug. Values greater than three trace each command.

IMAP4.utf8_enabled

Boolean value that is normally False, but is set to True if an enable() command is successfully issued for the UTF8=ACCEPT capability.

Nouveau dans la version 3.5.

21.15.2. IMAP4 Example

Here is a minimal example (without error checking) that opens a mailbox and retrieves and prints all messages:

import getpass, imaplib

M = imaplib.IMAP4()
M.login(getpass.getuser(), getpass.getpass())
M.select()
typ, data = M.search(None, 'ALL')
for num in data[0].split():
    typ, data = M.fetch(num, '(RFC822)')
    print('Message %s\n%s\n' % (num, data[0][1]))
M.close()
M.logout()

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21.16. nntplib — NNTP protocol client

Code source : Lib/nntplib.py [https://github.com/python/cpython/tree/3.6/Lib/nntplib.py]

This module defines the class NNTP which implements the client side of the Network News Transfer Protocol. It can be used to implement a news reader or poster, or automated news processors. It is compatible with RFC 3977 [https://tools.ietf.org/html/rfc3977.html] as well as the older RFC 977 [https://tools.ietf.org/html/rfc977.html] and RFC 2980 [https://tools.ietf.org/html/rfc2980.html].

Here are two small examples of how it can be used. To list some statistics about a newsgroup and print the subjects of the last 10 articles:

>>> s = nntplib.NNTP('news.gmane.org')
>>> resp, count, first, last, name = s.group('gmane.comp.python.committers')
>>> print('Group', name, 'has', count, 'articles, range', first, 'to', last)
Group gmane.comp.python.committers has 1096 articles, range 1 to 1096
>>> resp, overviews = s.over((last - 9, last))
>>> for id, over in overviews:
...     print(id, nntplib.decode_header(over['subject']))
...
1087 Re: Commit privileges for Łukasz Langa
1088 Re: 3.2 alpha 2 freeze
1089 Re: 3.2 alpha 2 freeze
1090 Re: Commit privileges for Łukasz Langa
1091 Re: Commit privileges for Łukasz Langa
1092 Updated ssh key
1093 Re: Updated ssh key
1094 Re: Updated ssh key
1095 Hello fellow committers!
1096 Re: Hello fellow committers!
>>> s.quit()
'205 Bye!'

To post an article from a binary file (this assumes that the article has valid headers, and that you have right to post on the particular newsgroup):

>>> s = nntplib.NNTP('news.gmane.org')
>>> f = open('article.txt', 'rb')
>>> s.post(f)
'240 Article posted successfully.'
>>> s.quit()
'205 Bye!'

The module itself defines the following classes:

class nntplib.NNTP(host, port=119, user=None, password=None, readermode=None, usenetrc=False[, timeout])

Return a new NNTP object, representing a connection to the NNTP server running on host host, listening at port port. An optional timeout can be specified for the socket connection. If the optional user and password are provided, or if suitable credentials are present in /.netrc and the optional flag usenetrc is true, the AUTHINFO USER and AUTHINFO PASS commands are used to identify and authenticate the user to the server. If the optional flag readermode is true, then a mode reader command is sent before authentication is performed. Reader mode is sometimes necessary if you are connecting to an NNTP server on the local machine and intend to call reader-specific commands, such as group. If you get unexpected NNTPPermanentErrors, you might need to set readermode. The NNTP class supports the with statement to unconditionally consume OSError exceptions and to close the NNTP connection when done, e.g.:

>>> from nntplib import NNTP
>>> with NNTP('news.gmane.org') as n:
...     n.group('gmane.comp.python.committers')
...
('211 1755 1 1755 gmane.comp.python.committers', 1755, 1, 1755, 'gmane.comp.python.committers')
>>>

Modifié dans la version 3.2: usenetrc is now False by default.

Modifié dans la version 3.3: La prise en charge de l’instruction with a été ajoutée.

class nntplib.NNTP_SSL(host, port=563, user=None, password=None, ssl_context=None, readermode=None, usenetrc=False[, timeout])

Return a new NNTP_SSL object, representing an encrypted connection to the NNTP server running on host host, listening at port port. NNTP_SSL objects have the same methods as NNTP objects. If port is omitted, port 563 (NNTPS) is used. ssl_context is also optional, and is a SSLContext object. Please read Security considerations for best practices. All other parameters behave the same as for NNTP.

Note that SSL-on-563 is discouraged per RFC 4642 [https://tools.ietf.org/html/rfc4642.html], in favor of STARTTLS as described below. However, some servers only support the former.

Nouveau dans la version 3.2.

Modifié dans la version 3.4: The class now supports hostname check with ssl.SSLContext.check_hostname and Server Name Indication (see ssl.HAS_SNI).

exception nntplib.NNTPError

Derived from the standard exception Exception, this is the base class for all exceptions raised by the nntplib module. Instances of this class have the following attribute:

response

The response of the server if available, as a str object.

exception nntplib.NNTPReplyError

Exception raised when an unexpected reply is received from the server.

exception nntplib.NNTPTemporaryError

Exception raised when a response code in the range 400–499 is received.

exception nntplib.NNTPPermanentError

Exception raised when a response code in the range 500–599 is received.

exception nntplib.NNTPProtocolError

Exception raised when a reply is received from the server that does not begin with a digit in the range 1–5.

exception nntplib.NNTPDataError

Exception raised when there is some error in the response data.

21.16.1. NNTP Objects

When connected, NNTP and NNTP_SSL objects support the following methods and attributes.

21.16.1.1. Attributes

NNTP.nntp_version

An integer representing the version of the NNTP protocol supported by the server. In practice, this should be 2 for servers advertising RFC 3977 [https://tools.ietf.org/html/rfc3977.html] compliance and 1 for others.

Nouveau dans la version 3.2.

NNTP.nntp_implementation

A string describing the software name and version of the NNTP server, or None if not advertised by the server.

Nouveau dans la version 3.2.

21.16.1.2. Méthodes

The response that is returned as the first item in the return tuple of almost all methods is the server’s response: a string beginning with a three-digit code. If the server’s response indicates an error, the method raises one of the above exceptions.

Many of the following methods take an optional keyword-only argument file. When the file argument is supplied, it must be either a file object opened for binary writing, or the name of an on-disk file to be written to. The method will then write any data returned by the server (except for the response line and the terminating dot) to the file; any list of lines, tuples or objects that the method normally returns will be empty.

Modifié dans la version 3.2: Many of the following methods have been reworked and fixed, which makes them incompatible with their 3.1 counterparts.

NNTP.quit()

Send a QUIT command and close the connection. Once this method has been called, no other methods of the NNTP object should be called.

NNTP.getwelcome()

Return the welcome message sent by the server in reply to the initial connection. (This message sometimes contains disclaimers or help information that may be relevant to the user.)

NNTP.getcapabilities()

Return the RFC 3977 [https://tools.ietf.org/html/rfc3977.html] capabilities advertised by the server, as a dict instance mapping capability names to (possibly empty) lists of values. On legacy servers which don’t understand the CAPABILITIES command, an empty dictionary is returned instead.

>>> s = NNTP('news.gmane.org')
>>> 'POST' in s.getcapabilities()
True

Nouveau dans la version 3.2.

NNTP.login(user=None, password=None, usenetrc=True)

Send AUTHINFO commands with the user name and password. If user and password are None and usenetrc is true, credentials from ~/.netrc will be used if possible.

Unless intentionally delayed, login is normally performed during the NNTP object initialization and separately calling this function is unnecessary. To force authentication to be delayed, you must not set user or password when creating the object, and must set usenetrc to False.

Nouveau dans la version 3.2.

NNTP.starttls(context=None)

Send a STARTTLS command. This will enable encryption on the NNTP connection. The context argument is optional and should be a ssl.SSLContext object. Please read Security considerations for best practices.

Note that this may not be done after authentication information has been transmitted, and authentication occurs by default if possible during a NNTP object initialization. See NNTP.login() for information on suppressing this behavior.

Nouveau dans la version 3.2.

Modifié dans la version 3.4: The method now supports hostname check with ssl.SSLContext.check_hostname and Server Name Indication (see ssl.HAS_SNI).

NNTP.newgroups(date, *, file=None)

Send a NEWGROUPS command. The date argument should be a datetime.date or datetime.datetime object. Return a pair (response, groups) where groups is a list representing the groups that are new since the given date. If file is supplied, though, then groups will be empty.

>>> from datetime import date, timedelta
>>> resp, groups = s.newgroups(date.today() - timedelta(days=3))
>>> len(groups)
85
>>> groups[0]
GroupInfo(group='gmane.network.tor.devel', last='4', first='1', flag='m')

NNTP.newnews(group, date, *, file=None)

Send a NEWNEWS command. Here, group is a group name or '*', and date has the same meaning as for newgroups(). Return a pair (response, articles) where articles is a list of message ids.

This command is frequently disabled by NNTP server administrators.

NNTP.list(group_pattern=None, *, file=None)

Send a LIST or LIST ACTIVE command. Return a pair (response, list) where list is a list of tuples representing all the groups available from this NNTP server, optionally matching the pattern string group_pattern. Each tuple has the form (group, last, first, flag), where group is a group name, last and first are the last and first article numbers, and flag usually takes one of these values:

y: Local postings and articles from peers are allowed.

m: The group is moderated and all postings must be approved.

n: No local postings are allowed, only articles from peers.

j: Articles from peers are filed in the junk group instead.

x: No local postings, and articles from peers are ignored.

=foo.bar: Articles are filed in the foo.bar group instead.

If flag has another value, then the status of the newsgroup should be considered unknown.

This command can return very large results, especially if group_pattern is not specified. It is best to cache the results offline unless you really need to refresh them.

Modifié dans la version 3.2: group_pattern was added.

NNTP.descriptions(grouppattern)

Send a LIST NEWSGROUPS command, where grouppattern is a wildmat string as specified in RFC 3977 [https://tools.ietf.org/html/rfc3977.html] (it’s essentially the same as DOS or UNIX shell wildcard strings). Return a pair (response, descriptions), where descriptions is a dictionary mapping group names to textual descriptions.

>>> resp, descs = s.descriptions('gmane.comp.python.*')
>>> len(descs)
295
>>> descs.popitem()
('gmane.comp.python.bio.general', 'BioPython discussion list (Moderated)')

NNTP.description(group)

Get a description for a single group group. If more than one group matches (if “group” is a real wildmat string), return the first match. If no group matches, return an empty string.

This elides the response code from the server. If the response code is needed, use descriptions().

NNTP.group(name)

Send a GROUP command, where name is the group name. The group is selected as the current group, if it exists. Return a tuple (response, count, first, last, name) where count is the (estimated) number of articles in the group, first is the first article number in the group, last is the last article number in the group, and name is the group name.

NNTP.over(message_spec, *, file=None)

Send an OVER command, or an XOVER command on legacy servers. message_spec can be either a string representing a message id, or a (first, last) tuple of numbers indicating a range of articles in the current group, or a (first, None) tuple indicating a range of articles starting from first to the last article in the current group, or None to select the current article in the current group.

Return a pair (response, overviews). overviews is a list of (article_number, overview) tuples, one for each article selected by message_spec. Each overview is a dictionary with the same number of items, but this number depends on the server. These items are either message headers (the key is then the lower-cased header name) or metadata items (the key is then the metadata name prepended with ":"). The following items are guaranteed to be present by the NNTP specification:

the subject, from, date, message-id and references headers

the :bytes metadata: the number of bytes in the entire raw article (including headers and body)

the :lines metadata: the number of lines in the article body

The value of each item is either a string, or None if not present.

It is advisable to use the decode_header() function on header values when they may contain non-ASCII characters:

>>> _, _, first, last, _ = s.group('gmane.comp.python.devel')
>>> resp, overviews = s.over((last, last))
>>> art_num, over = overviews[0]
>>> art_num
117216
>>> list(over.keys())
['xref', 'from', ':lines', ':bytes', 'references', 'date', 'message-id', 'subject']
>>> over['from']
'=?UTF-8?B?Ik1hcnRpbiB2LiBMw7Z3aXMi?= <martin@v.loewis.de>'
>>> nntplib.decode_header(over['from'])
'"Martin v. Löwis" <martin@v.loewis.de>'

Nouveau dans la version 3.2.

NNTP.help(*, file=None)

Send a HELP command. Return a pair (response, list) where list is a list of help strings.

NNTP.stat(message_spec=None)

Send a STAT command, where message_spec is either a message id (enclosed in '<' and '>') or an article number in the current group. If message_spec is omitted or None, the current article in the current group is considered. Return a triple (response, number, id) where number is the article number and id is the message id.

>>> _, _, first, last, _ = s.group('gmane.comp.python.devel')
>>> resp, number, message_id = s.stat(first)
>>> number, message_id
(9099, '<20030112190404.GE29873@epoch.metaslash.com>')

NNTP.next()

Send a NEXT command. Return as for stat().

NNTP.last()

Send a LAST command. Return as for stat().

NNTP.article(message_spec=None, *, file=None)

Send an ARTICLE command, where message_spec has the same meaning as for stat(). Return a tuple (response, info) where info is a namedtuple with three attributes number, message_id and lines (in that order). number is the article number in the group (or 0 if the information is not available), message_id the message id as a string, and lines a list of lines (without terminating newlines) comprising the raw message including headers and body.

>>> resp, info = s.article('<20030112190404.GE29873@epoch.metaslash.com>')
>>> info.number
0
>>> info.message_id
'<20030112190404.GE29873@epoch.metaslash.com>'
>>> len(info.lines)
65
>>> info.lines[0]
b'Path: main.gmane.org!not-for-mail'
>>> info.lines[1]
b'From: Neal Norwitz <neal@metaslash.com>'
>>> info.lines[-3:]
[b'There is a patch for 2.3 as well as 2.2.', b'', b'Neal']

NNTP.head(message_spec=None, *, file=None)

Same as article(), but sends a HEAD command. The lines returned (or written to file) will only contain the message headers, not the body.

NNTP.body(message_spec=None, *, file=None)

Same as article(), but sends a BODY command. The lines returned (or written to file) will only contain the message body, not the headers.

NNTP.post(data)

Post an article using the POST command. The data argument is either a file object opened for binary reading, or any iterable of bytes objects (representing raw lines of the article to be posted). It should represent a well-formed news article, including the required headers. The post() method automatically escapes lines beginning with . and appends the termination line.

If the method succeeds, the server’s response is returned. If the server refuses posting, a NNTPReplyError is raised.

NNTP.ihave(message_id, data)

Send an IHAVE command. message_id is the id of the message to send to the server (enclosed in '<' and '>'). The data parameter and the return value are the same as for post().

NNTP.date()

Return a pair (response, date). date is a datetime object containing the current date and time of the server.

NNTP.slave()

Send a SLAVE command. Return the server’s response.

NNTP.set_debuglevel(level)

Set the instance’s debugging level. This controls the amount of debugging output printed. The default, 0, produces no debugging output. A value of 1 produces a moderate amount of debugging output, generally a single line per request or response. A value of 2 or higher produces the maximum amount of debugging output, logging each line sent and received on the connection (including message text).

The following are optional NNTP extensions defined in RFC 2980 [https://tools.ietf.org/html/rfc2980.html]. Some of them have been superseded by newer commands in RFC 3977 [https://tools.ietf.org/html/rfc3977.html].

NNTP.xhdr(hdr, str, *, file=None)

Send an XHDR command. The hdr argument is a header keyword, e.g. 'subject'. The str argument should have the form 'first-last' where first and last are the first and last article numbers to search. Return a pair (response, list), where list is a list of pairs (id, text), where id is an article number (as a string) and text is the text of the requested header for that article. If the file parameter is supplied, then the output of the XHDR command is stored in a file. If file is a string, then the method will open a file with that name, write to it then close it. If file is a file object, then it will start calling write() on it to store the lines of the command output. If file is supplied, then the returned list is an empty list.

NNTP.xover(start, end, *, file=None)

Send an XOVER command. start and end are article numbers delimiting the range of articles to select. The return value is the same of for over(). It is recommended to use over() instead, since it will automatically use the newer OVER command if available.

NNTP.xpath(id)

Return a pair (resp, path), where path is the directory path to the article with message ID id. Most of the time, this extension is not enabled by NNTP server administrators.

Obsolète depuis la version 3.3: The XPATH extension is not actively used.

21.16.2. Fonctions utilitaires

The module also defines the following utility function:

nntplib.decode_header(header_str)

Decode a header value, un-escaping any escaped non-ASCII characters. header_str must be a str object. The unescaped value is returned. Using this function is recommended to display some headers in a human readable form:

>>> decode_header("Some subject")
'Some subject'
>>> decode_header("=?ISO-8859-15?Q?D=E9buter_en_Python?=")
'Débuter en Python'
>>> decode_header("Re: =?UTF-8?B?cHJvYmzDqG1lIGRlIG1hdHJpY2U=?=")
'Re: problème de matrice'

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21.17. smtplib — SMTP protocol client

Code source : Lib/smtplib.py [https://github.com/python/cpython/tree/3.6/Lib/smtplib.py]

The smtplib module defines an SMTP client session object that can be used to send mail to any Internet machine with an SMTP or ESMTP listener daemon. For details of SMTP and ESMTP operation, consult RFC 821 [https://tools.ietf.org/html/rfc821.html] (Simple Mail Transfer Protocol) and RFC 1869 [https://tools.ietf.org/html/rfc1869.html] (SMTP Service Extensions).

class smtplib.SMTP(host='', port=0, local_hostname=None, [timeout, ]source_address=None)

An SMTP instance encapsulates an SMTP connection. It has methods that support a full repertoire of SMTP and ESMTP operations. If the optional host and port parameters are given, the SMTP connect() method is called with those parameters during initialization. If specified, local_hostname is used as the FQDN of the local host in the HELO/EHLO command. Otherwise, the local hostname is found using socket.getfqdn(). If the connect() call returns anything other than a success code, an SMTPConnectError is raised. The optional timeout parameter specifies a timeout in seconds for blocking operations like the connection attempt (if not specified, the global default timeout setting will be used). If the timeout expires, socket.timeout is raised. The optional source_address parameter allows binding to some specific source address in a machine with multiple network interfaces, and/or to some specific source TCP port. It takes a 2-tuple (host, port), for the socket to bind to as its source address before connecting. If omitted (or if host or port are '' and/or 0 respectively) the OS default behavior will be used.

For normal use, you should only require the initialization/connect, sendmail(), and SMTP.quit() methods. An example is included below.

The SMTP class supports the with statement. When used like this, the SMTP QUIT command is issued automatically when the with statement exits. E.g.:

>>> from smtplib import SMTP
>>> with SMTP("domain.org") as smtp:
...     smtp.noop()
...
(250, b'Ok')
>>>

Modifié dans la version 3.3: La prise en charge de l’instruction with a été ajoutée.

Modifié dans la version 3.3: source_address argument was added.

Nouveau dans la version 3.5: The SMTPUTF8 extension (RFC 6531 [https://tools.ietf.org/html/rfc6531.html]) is now supported.

class smtplib.SMTP_SSL(host='', port=0, local_hostname=None, keyfile=None, certfile=None, [timeout, ]context=None, source_address=None)

An SMTP_SSL instance behaves exactly the same as instances of SMTP. SMTP_SSL should be used for situations where SSL is required from the beginning of the connection and using starttls() is not appropriate. If host is not specified, the local host is used. If port is zero, the standard SMTP-over-SSL port (465) is used. The optional arguments local_hostname, timeout and source_address have the same meaning as they do in the SMTP class. context, also optional, can contain a SSLContext and allows configuring various aspects of the secure connection. Please read Security considerations for best practices.

keyfile and certfile are a legacy alternative to context, and can point to a PEM formatted private key and certificate chain file for the SSL connection.

Modifié dans la version 3.3: context was added.

Modifié dans la version 3.3: source_address argument was added.

Modifié dans la version 3.4: The class now supports hostname check with ssl.SSLContext.check_hostname and Server Name Indication (see ssl.HAS_SNI).

Obsolète depuis la version 3.6: keyfile and certfile are deprecated in favor of context. Please use ssl.SSLContext.load_cert_chain() instead, or let ssl.create_default_context() select the system’s trusted CA certificates for you.

class smtplib.LMTP(host='', port=LMTP_PORT, local_hostname=None, source_address=None)

The LMTP protocol, which is very similar to ESMTP, is heavily based on the standard SMTP client. It’s common to use Unix sockets for LMTP, so our connect() method must support that as well as a regular host:port server. The optional arguments local_hostname and source_address have the same meaning as they do in the SMTP class. To specify a Unix socket, you must use an absolute path for host, starting with a “/”.

Authentication is supported, using the regular SMTP mechanism. When using a Unix socket, LMTP generally don’t support or require any authentication, but your mileage might vary.

A nice selection of exceptions is defined as well:

exception smtplib.SMTPException

Subclass of OSError that is the base exception class for all the other exceptions provided by this module.

Modifié dans la version 3.4: SMTPException became subclass of OSError

exception smtplib.SMTPServerDisconnected

This exception is raised when the server unexpectedly disconnects, or when an attempt is made to use the SMTP instance before connecting it to a server.

exception smtplib.SMTPResponseException

Base class for all exceptions that include an SMTP error code. These exceptions are generated in some instances when the SMTP server returns an error code. The error code is stored in the smtp_code attribute of the error, and the smtp_error attribute is set to the error message.

exception smtplib.SMTPSenderRefused

Sender address refused. In addition to the attributes set by on all SMTPResponseException exceptions, this sets “sender” to the string that the SMTP server refused.

exception smtplib.SMTPRecipientsRefused

All recipient addresses refused. The errors for each recipient are accessible through the attribute recipients, which is a dictionary of exactly the same sort as SMTP.sendmail() returns.

exception smtplib.SMTPDataError

The SMTP server refused to accept the message data.

exception smtplib.SMTPConnectError

Error occurred during establishment of a connection with the server.

exception smtplib.SMTPHeloError

The server refused our HELO message.

exception smtplib.SMTPNotSupportedError

The command or option attempted is not supported by the server.

Nouveau dans la version 3.5.

exception smtplib.SMTPAuthenticationError

SMTP authentication went wrong. Most probably the server didn’t accept the username/password combination provided.

Voir aussi

RFC 821 [https://tools.ietf.org/html/rfc821.html] - Simple Mail Transfer Protocol

Protocol definition for SMTP. This document covers the model, operating procedure, and protocol details for SMTP.

RFC 1869 [https://tools.ietf.org/html/rfc1869.html] - SMTP Service Extensions

Definition of the ESMTP extensions for SMTP. This describes a framework for extending SMTP with new commands, supporting dynamic discovery of the commands provided by the server, and defines a few additional commands.

21.17.1. SMTP Objects

An SMTP instance has the following methods:

SMTP.set_debuglevel(level)

Set the debug output level. A value of 1 or True for level results in debug messages for connection and for all messages sent to and received from the server. A value of 2 for level results in these messages being timestamped.

Modifié dans la version 3.5: Added debuglevel 2.

SMTP.docmd(cmd, args='')

Send a command cmd to the server. The optional argument args is simply concatenated to the command, separated by a space.

This returns a 2-tuple composed of a numeric response code and the actual response line (multiline responses are joined into one long line.)

In normal operation it should not be necessary to call this method explicitly. It is used to implement other methods and may be useful for testing private extensions.

If the connection to the server is lost while waiting for the reply, SMTPServerDisconnected will be raised.

SMTP.connect(host='localhost', port=0)

Connect to a host on a given port. The defaults are to connect to the local host at the standard SMTP port (25). If the hostname ends with a colon (':') followed by a number, that suffix will be stripped off and the number interpreted as the port number to use. This method is automatically invoked by the constructor if a host is specified during instantiation. Returns a 2-tuple of the response code and message sent by the server in its connection response.

SMTP.helo(name='')

Identify yourself to the SMTP server using HELO. The hostname argument defaults to the fully qualified domain name of the local host. The message returned by the server is stored as the helo_resp attribute of the object.

In normal operation it should not be necessary to call this method explicitly. It will be implicitly called by the sendmail() when necessary.

SMTP.ehlo(name='')

Identify yourself to an ESMTP server using EHLO. The hostname argument defaults to the fully qualified domain name of the local host. Examine the response for ESMTP option and store them for use by has_extn(). Also sets several informational attributes: the message returned by the server is stored as the ehlo_resp attribute, does_esmtp is set to true or false depending on whether the server supports ESMTP, and esmtp_features will be a dictionary containing the names of the SMTP service extensions this server supports, and their parameters (if any).

Unless you wish to use has_extn() before sending mail, it should not be necessary to call this method explicitly. It will be implicitly called by sendmail() when necessary.

SMTP.ehlo_or_helo_if_needed()

This method calls ehlo() and/or helo() if there has been no previous EHLO or HELO command this session. It tries ESMTP EHLO first.

SMTPHeloError

The server didn’t reply properly to the HELO greeting.

SMTP.has_extn(name)

Return True if name is in the set of SMTP service extensions returned by the server, False otherwise. Case is ignored.

SMTP.verify(address)

Check the validity of an address on this server using SMTP VRFY. Returns a tuple consisting of code 250 and a full RFC 822 [https://tools.ietf.org/html/rfc822.html] address (including human name) if the user address is valid. Otherwise returns an SMTP error code of 400 or greater and an error string.

Note

Many sites disable SMTP VRFY in order to foil spammers.

SMTP.login(user, password, *, initial_response_ok=True)

Log in on an SMTP server that requires authentication. The arguments are the username and the password to authenticate with. If there has been no previous EHLO or HELO command this session, this method tries ESMTP EHLO first. This method will return normally if the authentication was successful, or may raise the following exceptions:

SMTPHeloError

The server didn’t reply properly to the HELO greeting.

SMTPAuthenticationError

The server didn’t accept the username/password combination.

SMTPNotSupportedError

The AUTH command is not supported by the server.

SMTPException

No suitable authentication method was found.

Each of the authentication methods supported by smtplib are tried in turn if they are advertised as supported by the server. See auth() for a list of supported authentication methods. initial_response_ok is passed through to auth().

Optional keyword argument initial_response_ok specifies whether, for authentication methods that support it, an « initial response » as specified in RFC 4954 [https://tools.ietf.org/html/rfc4954.html] can be sent along with the AUTH command, rather than requiring a challenge/response.

Modifié dans la version 3.5: SMTPNotSupportedError may be raised, and the initial_response_ok parameter was added.

SMTP.auth(mechanism, authobject, *, initial_response_ok=True)

Issue an SMTP AUTH command for the specified authentication mechanism, and handle the challenge response via authobject.

mechanism specifies which authentication mechanism is to be used as argument to the AUTH command; the valid values are those listed in the auth element of esmtp_features.

authobject must be a callable object taking an optional single argument:

data = authobject(challenge=None)

If optional keyword argument initial_response_ok is true, authobject() will be called first with no argument. It can return the RFC 4954 [https://tools.ietf.org/html/rfc4954.html] « initial response » ASCII str which will be encoded and sent with the AUTH command as below. If the authobject() does not support an initial response (e.g. because it requires a challenge), it should return None when called with challenge=None. If initial_response_ok is false, then authobject() will not be called first with None.

If the initial response check returns None, or if initial_response_ok is false, authobject() will be called to process the server’s challenge response; the challenge argument it is passed will be a bytes. It should return ASCII str data that will be base64 encoded and sent to the server.

The SMTP class provides authobjects for the CRAM-MD5, PLAIN, and LOGIN mechanisms; they are named SMTP.auth_cram_md5, SMTP.auth_plain, and SMTP.auth_login respectively. They all require that the user and password properties of the SMTP instance are set to appropriate values.

User code does not normally need to call auth directly, but can instead call the login() method, which will try each of the above mechanisms in turn, in the order listed. auth is exposed to facilitate the implementation of authentication methods not (or not yet) supported directly by smtplib.

Nouveau dans la version 3.5.

SMTP.starttls(keyfile=None, certfile=None, context=None)

Put the SMTP connection in TLS (Transport Layer Security) mode. All SMTP commands that follow will be encrypted. You should then call ehlo() again.

If keyfile and certfile are provided, they are used to create an ssl.SSLContext.

Optional context parameter is an ssl.SSLContext object; This is an alternative to using a keyfile and a certfile and if specified both keyfile and certfile should be None.

If there has been no previous EHLO or HELO command this session, this method tries ESMTP EHLO first.

Obsolète depuis la version 3.6: keyfile and certfile are deprecated in favor of context. Please use ssl.SSLContext.load_cert_chain() instead, or let ssl.create_default_context() select the system’s trusted CA certificates for you.

SMTPHeloError

The server didn’t reply properly to the HELO greeting.

SMTPNotSupportedError

The server does not support the STARTTLS extension.

RuntimeError

SSL/TLS support is not available to your Python interpreter.

Modifié dans la version 3.3: context was added.

Modifié dans la version 3.4: The method now supports hostname check with SSLContext.check_hostname and Server Name Indicator (see HAS_SNI).

Modifié dans la version 3.5: The error raised for lack of STARTTLS support is now the SMTPNotSupportedError subclass instead of the base SMTPException.

SMTP.sendmail(from_addr, to_addrs, msg, mail_options=(), rcpt_options=())

Send mail. The required arguments are an RFC 822 [https://tools.ietf.org/html/rfc822.html] from-address string, a list of RFC 822 [https://tools.ietf.org/html/rfc822.html] to-address strings (a bare string will be treated as a list with 1 address), and a message string. The caller may pass a list of ESMTP options (such as 8bitmime) to be used in MAIL FROM commands as mail_options. ESMTP options (such as DSN commands) that should be used with all RCPT commands can be passed as rcpt_options. (If you need to use different ESMTP options to different recipients you have to use the low-level methods such as mail(), rcpt() and data() to send the message.)

Note

The from_addr and to_addrs parameters are used to construct the message envelope used by the transport agents. sendmail does not modify the message headers in any way.

msg may be a string containing characters in the ASCII range, or a byte string. A string is encoded to bytes using the ascii codec, and lone \r and \n characters are converted to \r\n characters. A byte string is not modified.

If there has been no previous EHLO or HELO command this session, this method tries ESMTP EHLO first. If the server does ESMTP, message size and each of the specified options will be passed to it (if the option is in the feature set the server advertises). If EHLO fails, HELO will be tried and ESMTP options suppressed.

This method will return normally if the mail is accepted for at least one recipient. Otherwise it will raise an exception. That is, if this method does not raise an exception, then someone should get your mail. If this method does not raise an exception, it returns a dictionary, with one entry for each recipient that was refused. Each entry contains a tuple of the SMTP error code and the accompanying error message sent by the server.

If SMTPUTF8 is included in mail_options, and the server supports it, from_addr and to_addrs may contain non-ASCII characters.

This method may raise the following exceptions:

SMTPRecipientsRefused

All recipients were refused. Nobody got the mail. The recipients attribute of the exception object is a dictionary with information about the refused recipients (like the one returned when at least one recipient was accepted).

SMTPHeloError

The server didn’t reply properly to the HELO greeting.

SMTPSenderRefused

The server didn’t accept the from_addr.

SMTPDataError

The server replied with an unexpected error code (other than a refusal of a recipient).

SMTPNotSupportedError

SMTPUTF8 was given in the mail_options but is not supported by the server.

Unless otherwise noted, the connection will be open even after an exception is raised.

Modifié dans la version 3.2: msg may be a byte string.

Modifié dans la version 3.5: SMTPUTF8 support added, and SMTPNotSupportedError may be raised if SMTPUTF8 is specified but the server does not support it.

SMTP.send_message(msg, from_addr=None, to_addrs=None, mail_options=(), rcpt_options=())

This is a convenience method for calling sendmail() with the message represented by an email.message.Message object. The arguments have the same meaning as for sendmail(), except that msg is a Message object.

If from_addr is None or to_addrs is None, send_message fills those arguments with addresses extracted from the headers of msg as specified in RFC 5322 [https://tools.ietf.org/html/rfc5322.html]: from_addr is set to the Sender field if it is present, and otherwise to the From field. to_addrs combines the values (if any) of the To, Cc, and Bcc fields from msg. If exactly one set of Resent-* headers appear in the message, the regular headers are ignored and the Resent-* headers are used instead. If the message contains more than one set of Resent-* headers, a ValueError is raised, since there is no way to unambiguously detect the most recent set of Resent- headers.

send_message serializes msg using BytesGenerator with \r\n as the linesep, and calls sendmail() to transmit the resulting message. Regardless of the values of from_addr and to_addrs, send_message does not transmit any Bcc or Resent-Bcc headers that may appear in msg. If any of the addresses in from_addr and to_addrs contain non-ASCII characters and the server does not advertise SMTPUTF8 support, an SMTPNotSupported error is raised. Otherwise the Message is serialized with a clone of its policy with the utf8 attribute set to True, and SMTPUTF8 and BODY=8BITMIME are added to mail_options.

Nouveau dans la version 3.2.

Nouveau dans la version 3.5: Support for internationalized addresses (SMTPUTF8).

SMTP.quit()

Terminate the SMTP session and close the connection. Return the result of the SMTP QUIT command.

Low-level methods corresponding to the standard SMTP/ESMTP commands HELP, RSET, NOOP, MAIL, RCPT, and DATA are also supported. Normally these do not need to be called directly, so they are not documented here. For details, consult the module code.

21.17.2. SMTP Example

This example prompts the user for addresses needed in the message envelope (“To” and “From” addresses), and the message to be delivered. Note that the headers to be included with the message must be included in the message as entered; this example doesn’t do any processing of the RFC 822 [https://tools.ietf.org/html/rfc822.html] headers. In particular, the “To” and “From” addresses must be included in the message headers explicitly.

import smtplib

def prompt(prompt):
    return input(prompt).strip()

fromaddr = prompt("From: ")
toaddrs  = prompt("To: ").split()
print("Enter message, end with ^D (Unix) or ^Z (Windows):")

# Add the From: and To: headers at the start!
msg = ("From: %s\r\nTo: %s\r\n\r\n"
       % (fromaddr, ", ".join(toaddrs)))
while True:
    try:
        line = input()
    except EOFError:
        break
    if not line:
        break
    msg = msg + line

print("Message length is", len(msg))

server = smtplib.SMTP('localhost')
server.set_debuglevel(1)
server.sendmail(fromaddr, toaddrs, msg)
server.quit()

Note

In general, you will want to use the email package’s features to construct an email message, which you can then send via send_message(); see email: Exemples.

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21.18. smtpd — SMTP Server

Code source : Lib/smtpd.py [https://github.com/python/cpython/tree/3.6/Lib/smtpd.py]

This module offers several classes to implement SMTP (email) servers.

Voir aussi

The aiosmtpd [http://aiosmtpd.readthedocs.io/] package is a recommended replacement for this module. It is based on asyncio and provides a more straightforward API. smtpd should be considered deprecated.

Several server implementations are present; one is a generic do-nothing implementation, which can be overridden, while the other two offer specific mail-sending strategies.

Additionally the SMTPChannel may be extended to implement very specific interaction behaviour with SMTP clients.

The code supports RFC 5321 [https://tools.ietf.org/html/rfc5321.html], plus the RFC 1870 [https://tools.ietf.org/html/rfc1870.html] SIZE and RFC 6531 [https://tools.ietf.org/html/rfc6531.html] SMTPUTF8 extensions.

21.18.1. SMTPServer Objects

class smtpd.SMTPServer(localaddr, remoteaddr, data_size_limit=33554432, map=None, enable_SMTPUTF8=False, decode_data=False)

Create a new SMTPServer object, which binds to local address localaddr. It will treat remoteaddr as an upstream SMTP relayer. Both localaddr and remoteaddr should be a (host, port) tuple. The object inherits from asyncore.dispatcher, and so will insert itself into asyncore’s event loop on instantiation.

data_size_limit specifies the maximum number of bytes that will be accepted in a DATA command. A value of None or 0 means no limit.

map is the socket map to use for connections (an initially empty dictionary is a suitable value). If not specified the asyncore global socket map is used.

enable_SMTPUTF8 determines whether the SMTPUTF8 extension (as defined in RFC 6531 [https://tools.ietf.org/html/rfc6531.html]) should be enabled. The default is False. When True, SMTPUTF8 is accepted as a parameter to the MAIL command and when present is passed to process_message() in the kwargs['mail_options'] list. decode_data and enable_SMTPUTF8 cannot be set to True at the same time.

decode_data specifies whether the data portion of the SMTP transaction should be decoded using UTF-8. When decode_data is False (the default), the server advertises the 8BITMIME extension (RFC 6152 [https://tools.ietf.org/html/rfc6152.html]), accepts the BODY=8BITMIME parameter to the MAIL command, and when present passes it to process_message() in the kwargs['mail_options'] list. decode_data and enable_SMTPUTF8 cannot be set to True at the same time.

process_message(peer, mailfrom, rcpttos, data, **kwargs)

Raise a NotImplementedError exception. Override this in subclasses to do something useful with this message. Whatever was passed in the constructor as remoteaddr will be available as the _remoteaddr attribute. peer is the remote host’s address, mailfrom is the envelope originator, rcpttos are the envelope recipients and data is a string containing the contents of the e-mail (which should be in RFC 5321 [https://tools.ietf.org/html/rfc5321.html] format).

If the decode_data constructor keyword is set to True, the data argument will be a unicode string. If it is set to False, it will be a bytes object.

kwargs is a dictionary containing additional information. It is empty if decode_data=True was given as an init argument, otherwise it contains the following keys:

mail_options:

a list of all received parameters to the MAIL command (the elements are uppercase strings; example: ['BODY=8BITMIME', 'SMTPUTF8']).

rcpt_options:

same as mail_options but for the RCPT command. Currently no RCPT TO options are supported, so for now this will always be an empty list.

Implementations of process_message should use the **kwargs signature to accept arbitrary keyword arguments, since future feature enhancements may add keys to the kwargs dictionary.

Return None to request a normal 250 Ok response; otherwise return the desired response string in RFC 5321 [https://tools.ietf.org/html/rfc5321.html] format.

channel_class

Override this in subclasses to use a custom SMTPChannel for managing SMTP clients.

Nouveau dans la version 3.4: The map constructor argument.

Modifié dans la version 3.5: localaddr and remoteaddr may now contain IPv6 addresses.

Nouveau dans la version 3.5: The decode_data and enable_SMTPUTF8 constructor parameters, and the kwargs parameter to process_message() when decode_data is False.

Modifié dans la version 3.6: decode_data is now False by default.

21.18.2. DebuggingServer Objects

class smtpd.DebuggingServer(localaddr, remoteaddr)

Create a new debugging server. Arguments are as per SMTPServer. Messages will be discarded, and printed on stdout.

21.18.3. PureProxy Objects

class smtpd.PureProxy(localaddr, remoteaddr)

Create a new pure proxy server. Arguments are as per SMTPServer. Everything will be relayed to remoteaddr. Note that running this has a good chance to make you into an open relay, so please be careful.

21.18.4. MailmanProxy Objects

class smtpd.MailmanProxy(localaddr, remoteaddr)

Create a new pure proxy server. Arguments are as per SMTPServer. Everything will be relayed to remoteaddr, unless local mailman configurations knows about an address, in which case it will be handled via mailman. Note that running this has a good chance to make you into an open relay, so please be careful.

21.18.5. SMTPChannel Objects

class smtpd.SMTPChannel(server, conn, addr, data_size_limit=33554432, map=None, enable_SMTPUTF8=False, decode_data=False)

Create a new SMTPChannel object which manages the communication between the server and a single SMTP client.

conn and addr are as per the instance variables described below.

data_size_limit specifies the maximum number of bytes that will be accepted in a DATA command. A value of None or 0 means no limit.

enable_SMTPUTF8 determines whether the SMTPUTF8 extension (as defined in RFC 6531 [https://tools.ietf.org/html/rfc6531.html]) should be enabled. The default is False. decode_data and enable_SMTPUTF8 cannot be set to True at the same time.

A dictionary can be specified in map to avoid using a global socket map.

decode_data specifies whether the data portion of the SMTP transaction should be decoded using UTF-8. The default is False. decode_data and enable_SMTPUTF8 cannot be set to True at the same time.

To use a custom SMTPChannel implementation you need to override the SMTPServer.channel_class of your SMTPServer.

Modifié dans la version 3.5: The decode_data and enable_SMTPUTF8 parameters were added.

Modifié dans la version 3.6: decode_data is now False by default.

The SMTPChannel has the following instance variables:

smtp_server

Holds the SMTPServer that spawned this channel.

conn

Holds the socket object connecting to the client.

addr

Holds the address of the client, the second value returned by socket.accept

received_lines

Holds a list of the line strings (decoded using UTF-8) received from the client. The lines have their "\r\n" line ending translated to "\n".

smtp_state

Holds the current state of the channel. This will be either COMMAND initially and then DATA after the client sends a « DATA » line.

seen_greeting

Holds a string containing the greeting sent by the client in its « HELO ».

mailfrom

Holds a string containing the address identified in the « MAIL FROM: » line from the client.

rcpttos

Holds a list of strings containing the addresses identified in the « RCPT TO: » lines from the client.

received_data

Holds a string containing all of the data sent by the client during the DATA state, up to but not including the terminating "\r\n.\r\n".

fqdn

Holds the fully-qualified domain name of the server as returned by socket.getfqdn().

peer

Holds the name of the client peer as returned by conn.getpeername() where conn is conn.

The SMTPChannel operates by invoking methods named smtp_<command> upon reception of a command line from the client. Built into the base SMTPChannel class are methods for handling the following commands (and responding to them appropriately):

Commande

Action taken

HELO

Accepts the greeting from the client and stores it in seen_greeting. Sets server to base command mode.

EHLO

Accepts the greeting from the client and stores it in seen_greeting. Sets server to extended command mode.

NOOP

Takes no action.

QUIT

Closes the connection cleanly.

MAIL

Accepts the « MAIL FROM: » syntax and stores the supplied address as mailfrom. In extended command mode, accepts the RFC 1870 [https://tools.ietf.org/html/rfc1870.html] SIZE attribute and responds appropriately based on the value of data_size_limit.

RCPT

Accepts the « RCPT TO: » syntax and stores the supplied addresses in the rcpttos list.

RSET

Resets the mailfrom, rcpttos, and received_data, but not the greeting.

DATA

Sets the internal state to DATA and stores remaining lines from the client in received_data until the terminator "\r\n.\r\n" is received.

HELP

Returns minimal information on command syntax

VRFY

Returns code 252 (the server doesn’t know if the address is valid)

EXPN

Reports that the command is not implemented.

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21.19. telnetlib — Telnet client

Code source : Lib/telnetlib.py [https://github.com/python/cpython/tree/3.6/Lib/telnetlib.py]

The telnetlib module provides a Telnet class that implements the Telnet protocol. See RFC 854 [https://tools.ietf.org/html/rfc854.html] for details about the protocol. In addition, it provides symbolic constants for the protocol characters (see below), and for the telnet options. The symbolic names of the telnet options follow the definitions in arpa/telnet.h, with the leading TELOPT_ removed. For symbolic names of options which are traditionally not included in arpa/telnet.h, see the module source itself.

The symbolic constants for the telnet commands are: IAC, DONT, DO, WONT, WILL, SE (Subnegotiation End), NOP (No Operation), DM (Data Mark), BRK (Break), IP (Interrupt process), AO (Abort output), AYT (Are You There), EC (Erase Character), EL (Erase Line), GA (Go Ahead), SB (Subnegotiation Begin).

class telnetlib.Telnet(host=None, port=0[, timeout])

Telnet represents a connection to a Telnet server. The instance is initially not connected by default; the open() method must be used to establish a connection. Alternatively, the host name and optional port number can be passed to the constructor too, in which case the connection to the server will be established before the constructor returns. The optional timeout parameter specifies a timeout in seconds for blocking operations like the connection attempt (if not specified, the global default timeout setting will be used).

Do not reopen an already connected instance.

This class has many read_*() methods. Note that some of them raise EOFError when the end of the connection is read, because they can return an empty string for other reasons. See the individual descriptions below.

A Telnet object is a context manager and can be used in a with statement. When the with block ends, the close() method is called:

>>> from telnetlib import Telnet
>>> with Telnet('localhost', 23) as tn:
...     tn.interact()
...

Modifié dans la version 3.6: Context manager support added

Voir aussi

RFC 854 [https://tools.ietf.org/html/rfc854.html] - Telnet Protocol Specification

Definition of the Telnet protocol.

21.19.1. Telnet Objects

Telnet instances have the following methods:

Telnet.read_until(expected, timeout=None)

Read until a given byte string, expected, is encountered or until timeout seconds have passed.

When no match is found, return whatever is available instead, possibly empty bytes. Raise EOFError if the connection is closed and no cooked data is available.

Telnet.read_all()

Read all data until EOF as bytes; block until connection closed.

Telnet.read_some()

Read at least one byte of cooked data unless EOF is hit. Return b'' if EOF is hit. Block if no data is immediately available.

Telnet.read_very_eager()

Read everything that can be without blocking in I/O (eager).

Raise EOFError if connection closed and no cooked data available. Return b'' if no cooked data available otherwise. Do not block unless in the midst of an IAC sequence.

Telnet.read_eager()

Read readily available data.

Raise EOFError if connection closed and no cooked data available. Return b'' if no cooked data available otherwise. Do not block unless in the midst of an IAC sequence.

Telnet.read_lazy()

Process and return data already in the queues (lazy).

Raise EOFError if connection closed and no data available. Return b'' if no cooked data available otherwise. Do not block unless in the midst of an IAC sequence.

Telnet.read_very_lazy()

Return any data available in the cooked queue (very lazy).

Raise EOFError if connection closed and no data available. Return b'' if no cooked data available otherwise. This method never blocks.

Telnet.read_sb_data()

Return the data collected between a SB/SE pair (suboption begin/end). The callback should access these data when it was invoked with a SE command. This method never blocks.

Telnet.open(host, port=0[, timeout])

Connect to a host. The optional second argument is the port number, which defaults to the standard Telnet port (23). The optional timeout parameter specifies a timeout in seconds for blocking operations like the connection attempt (if not specified, the global default timeout setting will be used).

Do not try to reopen an already connected instance.

Telnet.msg(msg, *args)

Print a debug message when the debug level is > 0. If extra arguments are present, they are substituted in the message using the standard string formatting operator.

Telnet.set_debuglevel(debuglevel)

Set the debug level. The higher the value of debuglevel, the more debug output you get (on sys.stdout).

Telnet.close()

Ferme la connexion.

Telnet.get_socket()

Return the socket object used internally.

Telnet.fileno()

Return the file descriptor of the socket object used internally.

Telnet.write(buffer)

Write a byte string to the socket, doubling any IAC characters. This can block if the connection is blocked. May raise OSError if the connection is closed.

Modifié dans la version 3.3: This method used to raise socket.error, which is now an alias of OSError.

Telnet.interact()

Interaction function, emulates a very dumb Telnet client.

Telnet.mt_interact()

Multithreaded version of interact().

Telnet.expect(list, timeout=None)

Read until one from a list of a regular expressions matches.

The first argument is a list of regular expressions, either compiled (regex objects) or uncompiled (byte strings). The optional second argument is a timeout, in seconds; the default is to block indefinitely.

Return a tuple of three items: the index in the list of the first regular expression that matches; the match object returned; and the bytes read up till and including the match.

If end of file is found and no bytes were read, raise EOFError. Otherwise, when nothing matches, return (-1, None, data) where data is the bytes received so far (may be empty bytes if a timeout happened).

If a regular expression ends with a greedy match (such as .*) or if more than one expression can match the same input, the results are non-deterministic, and may depend on the I/O timing.

Telnet.set_option_negotiation_callback(callback)

Each time a telnet option is read on the input flow, this callback (if set) is called with the following parameters: callback(telnet socket, command (DO/DONT/WILL/WONT), option). No other action is done afterwards by telnetlib.

21.19.2. Telnet Example

A simple example illustrating typical use:

import getpass
import telnetlib

HOST = "localhost"
user = input("Enter your remote account: ")
password = getpass.getpass()

tn = telnetlib.Telnet(HOST)

tn.read_until(b"login: ")
tn.write(user.encode('ascii') + b"\n")
if password:
    tn.read_until(b"Password: ")
    tn.write(password.encode('ascii') + b"\n")

tn.write(b"ls\n")
tn.write(b"exit\n")

print(tn.read_all().decode('ascii'))

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21.20. uuid — UUID objects according to RFC 4122 [https://tools.ietf.org/html/rfc4122.html]

Source code: Lib/uuid.py [https://github.com/python/cpython/tree/3.6/Lib/uuid.py]

This module provides immutable UUID objects (the UUID class) and the functions uuid1(), uuid3(), uuid4(), uuid5() for generating version 1, 3, 4, and 5 UUIDs as specified in RFC 4122 [https://tools.ietf.org/html/rfc4122.html].

If all you want is a unique ID, you should probably call uuid1() or uuid4(). Note that uuid1() may compromise privacy since it creates a UUID containing the computer’s network address. uuid4() creates a random UUID.

class uuid.UUID(hex=None, bytes=None, bytes_le=None, fields=None, int=None, version=None)

Create a UUID from either a string of 32 hexadecimal digits, a string of 16 bytes in big-endian order as the bytes argument, a string of 16 bytes in little-endian order as the bytes_le argument, a tuple of six integers (32-bit time_low, 16-bit time_mid, 16-bit time_hi_version, 8-bit clock_seq_hi_variant, 8-bit clock_seq_low, 48-bit node) as the fields argument, or a single 128-bit integer as the int argument. When a string of hex digits is given, curly braces, hyphens, and a URN prefix are all optional. For example, these expressions all yield the same UUID:

UUID('{12345678-1234-5678-1234-567812345678}')
UUID('12345678123456781234567812345678')
UUID('urn:uuid:12345678-1234-5678-1234-567812345678')
UUID(bytes=b'\x12\x34\x56\x78'*4)
UUID(bytes_le=b'\x78\x56\x34\x12\x34\x12\x78\x56' +
              b'\x12\x34\x56\x78\x12\x34\x56\x78')
UUID(fields=(0x12345678, 0x1234, 0x5678, 0x12, 0x34, 0x567812345678))
UUID(int=0x12345678123456781234567812345678)

Exactly one of hex, bytes, bytes_le, fields, or int must be given. The version argument is optional; if given, the resulting UUID will have its variant and version number set according to RFC 4122 [https://tools.ietf.org/html/rfc4122.html], overriding bits in the given hex, bytes, bytes_le, fields, or int.

Comparison of UUID objects are made by way of comparing their UUID.int attributes. Comparison with a non-UUID object raises a TypeError.

str(uuid) returns a string in the form 12345678-1234-5678-1234-567812345678 where the 32 hexadecimal digits represent the UUID.

UUID instances have these read-only attributes:

UUID.bytes

The UUID as a 16-byte string (containing the six integer fields in big-endian byte order).

UUID.bytes_le

The UUID as a 16-byte string (with time_low, time_mid, and time_hi_version in little-endian byte order).

UUID.fields

A tuple of the six integer fields of the UUID, which are also available as six individual attributes and two derived attributes:

Field

Signification

time_low

the first 32 bits of the UUID

time_mid

the next 16 bits of the UUID

time_hi_version

the next 16 bits of the UUID

clock_seq_hi_variant

the next 8 bits of the UUID

clock_seq_low

the next 8 bits of the UUID

node

the last 48 bits of the UUID

time

the 60-bit timestamp

clock_seq

the 14-bit sequence number

UUID.hex

The UUID as a 32-character hexadecimal string.

UUID.int

The UUID as a 128-bit integer.

UUID.urn

The UUID as a URN as specified in RFC 4122 [https://tools.ietf.org/html/rfc4122.html].

UUID.variant

The UUID variant, which determines the internal layout of the UUID. This will be one of the constants RESERVED_NCS, RFC_4122, RESERVED_MICROSOFT, or RESERVED_FUTURE.

UUID.version

The UUID version number (1 through 5, meaningful only when the variant is RFC_4122).

The uuid module defines the following functions:

uuid.getnode()

Get the hardware address as a 48-bit positive integer. The first time this runs, it may launch a separate program, which could be quite slow. If all attempts to obtain the hardware address fail, we choose a random 48-bit number with its eighth bit set to 1 as recommended in RFC 4122 [https://tools.ietf.org/html/rfc4122.html]. « Hardware address » means the MAC address of a network interface, and on a machine with multiple network interfaces the MAC address of any one of them may be returned.

uuid.uuid1(node=None, clock_seq=None)

Generate a UUID from a host ID, sequence number, and the current time. If node is not given, getnode() is used to obtain the hardware address. If clock_seq is given, it is used as the sequence number; otherwise a random 14-bit sequence number is chosen.

uuid.uuid3(namespace, name)

Generate a UUID based on the MD5 hash of a namespace identifier (which is a UUID) and a name (which is a string).

uuid.uuid4()

Generate a random UUID.

uuid.uuid5(namespace, name)

Generate a UUID based on the SHA-1 hash of a namespace identifier (which is a UUID) and a name (which is a string).

The uuid module defines the following namespace identifiers for use with uuid3() or uuid5().

uuid.NAMESPACE_DNS

When this namespace is specified, the name string is a fully-qualified domain name.

uuid.NAMESPACE_URL

When this namespace is specified, the name string is a URL.

uuid.NAMESPACE_OID

When this namespace is specified, the name string is an ISO OID.

uuid.NAMESPACE_X500

When this namespace is specified, the name string is an X.500 DN in DER or a text output format.

The uuid module defines the following constants for the possible values of the variant attribute:

uuid.RESERVED_NCS

Reserved for NCS compatibility.

uuid.RFC_4122

Specifies the UUID layout given in RFC 4122 [https://tools.ietf.org/html/rfc4122.html].

uuid.RESERVED_MICROSOFT

Reserved for Microsoft compatibility.

uuid.RESERVED_FUTURE

Reserved for future definition.

Voir aussi

RFC 4122 [https://tools.ietf.org/html/rfc4122.html] - A Universally Unique IDentifier (UUID) URN Namespace

This specification defines a Uniform Resource Name namespace for UUIDs, the internal format of UUIDs, and methods of generating UUIDs.

21.20.1. Exemple

Here are some examples of typical usage of the uuid module:

>>> import uuid

>>> # make a UUID based on the host ID and current time
>>> uuid.uuid1()
UUID('a8098c1a-f86e-11da-bd1a-00112444be1e')

>>> # make a UUID using an MD5 hash of a namespace UUID and a name
>>> uuid.uuid3(uuid.NAMESPACE_DNS, 'python.org')
UUID('6fa459ea-ee8a-3ca4-894e-db77e160355e')

>>> # make a random UUID
>>> uuid.uuid4()
UUID('16fd2706-8baf-433b-82eb-8c7fada847da')

>>> # make a UUID using a SHA-1 hash of a namespace UUID and a name
>>> uuid.uuid5(uuid.NAMESPACE_DNS, 'python.org')
UUID('886313e1-3b8a-5372-9b90-0c9aee199e5d')

>>> # make a UUID from a string of hex digits (braces and hyphens ignored)
>>> x = uuid.UUID('{00010203-0405-0607-0809-0a0b0c0d0e0f}')

>>> # convert a UUID to a string of hex digits in standard form
>>> str(x)
'00010203-0405-0607-0809-0a0b0c0d0e0f'

>>> # get the raw 16 bytes of the UUID
>>> x.bytes
b'\x00\x01\x02\x03\x04\x05\x06\x07\x08\t\n\x0b\x0c\r\x0e\x0f'

>>> # make a UUID from a 16-byte string
>>> uuid.UUID(bytes=x.bytes)
UUID('00010203-0405-0607-0809-0a0b0c0d0e0f')

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21.21. socketserver — A framework for network servers

Source code: Lib/socketserver.py [https://github.com/python/cpython/tree/3.6/Lib/socketserver.py]

The socketserver module simplifies the task of writing network servers.

There are four basic concrete server classes:

class socketserver.TCPServer(server_address, RequestHandlerClass, bind_and_activate=True)

This uses the Internet TCP protocol, which provides for continuous streams of data between the client and server. If bind_and_activate is true, the constructor automatically attempts to invoke server_bind() and server_activate(). The other parameters are passed to the BaseServer base class.

class socketserver.UDPServer(server_address, RequestHandlerClass, bind_and_activate=True)

This uses datagrams, which are discrete packets of information that may arrive out of order or be lost while in transit. The parameters are the same as for TCPServer.

class socketserver.UnixStreamServer(server_address, RequestHandlerClass, bind_and_activate=True)

class socketserver.UnixDatagramServer(server_address, RequestHandlerClass, bind_and_activate=True)

These more infrequently used classes are similar to the TCP and UDP classes, but use Unix domain sockets; they’re not available on non-Unix platforms. The parameters are the same as for TCPServer.

These four classes process requests synchronously; each request must be completed before the next request can be started. This isn’t suitable if each request takes a long time to complete, because it requires a lot of computation, or because it returns a lot of data which the client is slow to process. The solution is to create a separate process or thread to handle each request; the ForkingMixIn and ThreadingMixIn mix-in classes can be used to support asynchronous behaviour.

Creating a server requires several steps. First, you must create a request handler class by subclassing the BaseRequestHandler class and overriding its handle() method; this method will process incoming requests. Second, you must instantiate one of the server classes, passing it the server’s address and the request handler class. It is recommended to use the server in a with statement. Then call the handle_request() or serve_forever() method of the server object to process one or many requests. Finally, call server_close() to close the socket (unless you used a with statement).

When inheriting from ThreadingMixIn for threaded connection behavior, you should explicitly declare how you want your threads to behave on an abrupt shutdown. The ThreadingMixIn class defines an attribute daemon_threads, which indicates whether or not the server should wait for thread termination. You should set the flag explicitly if you would like threads to behave autonomously; the default is False, meaning that Python will not exit until all threads created by ThreadingMixIn have exited.

Server classes have the same external methods and attributes, no matter what network protocol they use.

21.21.1. Server Creation Notes

There are five classes in an inheritance diagram, four of which represent synchronous servers of four types:

+------------+
| BaseServer |
+------------+
      |
      v
+-----------+        +------------------+
| TCPServer |------->| UnixStreamServer |
+-----------+        +------------------+
      |
      v
+-----------+        +--------------------+
| UDPServer |------->| UnixDatagramServer |
+-----------+        +--------------------+

Note that UnixDatagramServer derives from UDPServer, not from UnixStreamServer — the only difference between an IP and a Unix stream server is the address family, which is simply repeated in both Unix server classes.

class socketserver.ForkingMixIn

class socketserver.ThreadingMixIn

Forking and threading versions of each type of server can be created using these mix-in classes. For instance, ThreadingUDPServer is created as follows:

class ThreadingUDPServer(ThreadingMixIn, UDPServer):
    pass

The mix-in class comes first, since it overrides a method defined in UDPServer. Setting the various attributes also changes the behavior of the underlying server mechanism.

ForkingMixIn and the Forking classes mentioned below are only available on POSIX platforms that support fork().

class socketserver.ForkingTCPServer

class socketserver.ForkingUDPServer

class socketserver.ThreadingTCPServer

class socketserver.ThreadingUDPServer

These classes are pre-defined using the mix-in classes.

To implement a service, you must derive a class from BaseRequestHandler and redefine its handle() method. You can then run various versions of the service by combining one of the server classes with your request handler class. The request handler class must be different for datagram or stream services. This can be hidden by using the handler subclasses StreamRequestHandler or DatagramRequestHandler.

Of course, you still have to use your head! For instance, it makes no sense to use a forking server if the service contains state in memory that can be modified by different requests, since the modifications in the child process would never reach the initial state kept in the parent process and passed to each child. In this case, you can use a threading server, but you will probably have to use locks to protect the integrity of the shared data.

On the other hand, if you are building an HTTP server where all data is stored externally (for instance, in the file system), a synchronous class will essentially render the service « deaf » while one request is being handled – which may be for a very long time if a client is slow to receive all the data it has requested. Here a threading or forking server is appropriate.

In some cases, it may be appropriate to process part of a request synchronously, but to finish processing in a forked child depending on the request data. This can be implemented by using a synchronous server and doing an explicit fork in the request handler class handle() method.

Another approach to handling multiple simultaneous requests in an environment that supports neither threads nor fork() (or where these are too expensive or inappropriate for the service) is to maintain an explicit table of partially finished requests and to use selectors to decide which request to work on next (or whether to handle a new incoming request). This is particularly important for stream services where each client can potentially be connected for a long time (if threads or subprocesses cannot be used). See asyncore for another way to manage this.

21.21.2. Objets Serveur

class socketserver.BaseServer(server_address, RequestHandlerClass)

This is the superclass of all Server objects in the module. It defines the interface, given below, but does not implement most of the methods, which is done in subclasses. The two parameters are stored in the respective server_address and RequestHandlerClass attributes.

fileno()

Return an integer file descriptor for the socket on which the server is listening. This function is most commonly passed to selectors, to allow monitoring multiple servers in the same process.

handle_request()

Process a single request. This function calls the following methods in order: get_request(), verify_request(), and process_request(). If the user-provided handle() method of the handler class raises an exception, the server’s handle_error() method will be called. If no request is received within timeout seconds, handle_timeout() will be called and handle_request() will return.

serve_forever(poll_interval=0.5)

Handle requests until an explicit shutdown() request. Poll for shutdown every poll_interval seconds. Ignores the timeout attribute. It also calls service_actions(), which may be used by a subclass or mixin to provide actions specific to a given service. For example, the ForkingMixIn class uses service_actions() to clean up zombie child processes.

Modifié dans la version 3.3: Added service_actions call to the serve_forever method.

service_actions()

This is called in the serve_forever() loop. This method can be overridden by subclasses or mixin classes to perform actions specific to a given service, such as cleanup actions.

Nouveau dans la version 3.3.

shutdown()

Tell the serve_forever() loop to stop and wait until it does.

server_close()

Clean up the server. May be overridden.

address_family

The family of protocols to which the server’s socket belongs. Common examples are socket.AF_INET and socket.AF_UNIX.

RequestHandlerClass

The user-provided request handler class; an instance of this class is created for each request.

server_address

The address on which the server is listening. The format of addresses varies depending on the protocol family; see the documentation for the socket module for details. For Internet protocols, this is a tuple containing a string giving the address, and an integer port number: ('127.0.0.1', 80), for example.

socket

The socket object on which the server will listen for incoming requests.

The server classes support the following class variables:

allow_reuse_address

Whether the server will allow the reuse of an address. This defaults to False, and can be set in subclasses to change the policy.

request_queue_size

The size of the request queue. If it takes a long time to process a single request, any requests that arrive while the server is busy are placed into a queue, up to request_queue_size requests. Once the queue is full, further requests from clients will get a « Connection denied » error. The default value is usually 5, but this can be overridden by subclasses.

socket_type

The type of socket used by the server; socket.SOCK_STREAM and socket.SOCK_DGRAM are two common values.

timeout

Timeout duration, measured in seconds, or None if no timeout is desired. If handle_request() receives no incoming requests within the timeout period, the handle_timeout() method is called.

There are various server methods that can be overridden by subclasses of base server classes like TCPServer; these methods aren’t useful to external users of the server object.

finish_request(request, client_address)

Actually processes the request by instantiating RequestHandlerClass and calling its handle() method.

get_request()

Must accept a request from the socket, and return a 2-tuple containing the new socket object to be used to communicate with the client, and the client’s address.

handle_error(request, client_address)

This function is called if the handle() method of a RequestHandlerClass instance raises an exception. The default action is to print the traceback to standard error and continue handling further requests.

Modifié dans la version 3.6: Now only called for exceptions derived from the Exception class.

handle_timeout()

This function is called when the timeout attribute has been set to a value other than None and the timeout period has passed with no requests being received. The default action for forking servers is to collect the status of any child processes that have exited, while in threading servers this method does nothing.

process_request(request, client_address)

Calls finish_request() to create an instance of the RequestHandlerClass. If desired, this function can create a new process or thread to handle the request; the ForkingMixIn and ThreadingMixIn classes do this.

server_activate()

Called by the server’s constructor to activate the server. The default behavior for a TCP server just invokes listen() on the server’s socket. May be overridden.

server_bind()

Called by the server’s constructor to bind the socket to the desired address. May be overridden.

verify_request(request, client_address)

Must return a Boolean value; if the value is True, the request will be processed, and if it’s False, the request will be denied. This function can be overridden to implement access controls for a server. The default implementation always returns True.

Modifié dans la version 3.6: Support for the context manager protocol was added. Exiting the context manager is equivalent to calling server_close().

21.21.3. Request Handler Objects

class socketserver.BaseRequestHandler

This is the superclass of all request handler objects. It defines the interface, given below. A concrete request handler subclass must define a new handle() method, and can override any of the other methods. A new instance of the subclass is created for each request.

setup()

Called before the handle() method to perform any initialization actions required. The default implementation does nothing.

handle()

This function must do all the work required to service a request. The default implementation does nothing. Several instance attributes are available to it; the request is available as self.request; the client address as self.client_address; and the server instance as self.server, in case it needs access to per-server information.

The type of self.request is different for datagram or stream services. For stream services, self.request is a socket object; for datagram services, self.request is a pair of string and socket.

finish()

Called after the handle() method to perform any clean-up actions required. The default implementation does nothing. If setup() raises an exception, this function will not be called.

class socketserver.StreamRequestHandler

class socketserver.DatagramRequestHandler

These BaseRequestHandler subclasses override the setup() and finish() methods, and provide self.rfile and self.wfile attributes. The self.rfile and self.wfile attributes can be read or written, respectively, to get the request data or return data to the client.

The rfile attributes of both classes support the io.BufferedIOBase readable interface, and DatagramRequestHandler.wfile supports the io.BufferedIOBase writable interface.

Modifié dans la version 3.6: StreamRequestHandler.wfile also supports the io.BufferedIOBase writable interface.

21.21.4. Exemples

21.21.4.1. socketserver.TCPServer Example

This is the server side:

import socketserver

class MyTCPHandler(socketserver.BaseRequestHandler):
    """
    The request handler class for our server.

    It is instantiated once per connection to the server, and must
    override the handle() method to implement communication to the
    client.
    """

    def handle(self):
        # self.request is the TCP socket connected to the client
        self.data = self.request.recv(1024).strip()
        print("{} wrote:".format(self.client_address[0]))
        print(self.data)
        # just send back the same data, but upper-cased
        self.request.sendall(self.data.upper())

if __name__ == "__main__":
    HOST, PORT = "localhost", 9999

    # Create the server, binding to localhost on port 9999
    with socketserver.TCPServer((HOST, PORT), MyTCPHandler) as server:
        # Activate the server; this will keep running until you
        # interrupt the program with Ctrl-C
        server.serve_forever()

An alternative request handler class that makes use of streams (file-like objects that simplify communication by providing the standard file interface):

class MyTCPHandler(socketserver.StreamRequestHandler):

    def handle(self):
        # self.rfile is a file-like object created by the handler;
        # we can now use e.g. readline() instead of raw recv() calls
        self.data = self.rfile.readline().strip()
        print("{} wrote:".format(self.client_address[0]))
        print(self.data)
        # Likewise, self.wfile is a file-like object used to write back
        # to the client
        self.wfile.write(self.data.upper())

The difference is that the readline() call in the second handler will call recv() multiple times until it encounters a newline character, while the single recv() call in the first handler will just return what has been sent from the client in one sendall() call.

This is the client side:

import socket
import sys

HOST, PORT = "localhost", 9999
data = " ".join(sys.argv[1:])

# Create a socket (SOCK_STREAM means a TCP socket)
with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as sock:
    # Connect to server and send data
    sock.connect((HOST, PORT))
    sock.sendall(bytes(data + "\n", "utf-8"))

    # Receive data from the server and shut down
    received = str(sock.recv(1024), "utf-8")

print("Sent:     {}".format(data))
print("Received: {}".format(received))

The output of the example should look something like this:

Serveur :

$ python TCPServer.py
127.0.0.1 wrote:
b'hello world with TCP'
127.0.0.1 wrote:
b'python is nice'

Client :

$ python TCPClient.py hello world with TCP
Sent:     hello world with TCP
Received: HELLO WORLD WITH TCP
$ python TCPClient.py python is nice
Sent:     python is nice
Received: PYTHON IS NICE

21.21.4.2. socketserver.UDPServer Example

This is the server side:

import socketserver

class MyUDPHandler(socketserver.BaseRequestHandler):
    """
    This class works similar to the TCP handler class, except that
    self.request consists of a pair of data and client socket, and since
    there is no connection the client address must be given explicitly
    when sending data back via sendto().
    """

    def handle(self):
        data = self.request[0].strip()
        socket = self.request[1]
        print("{} wrote:".format(self.client_address[0]))
        print(data)
        socket.sendto(data.upper(), self.client_address)

if __name__ == "__main__":
    HOST, PORT = "localhost", 9999
    with socketserver.UDPServer((HOST, PORT), MyUDPHandler) as server:
        server.serve_forever()

This is the client side:

import socket
import sys

HOST, PORT = "localhost", 9999
data = " ".join(sys.argv[1:])

# SOCK_DGRAM is the socket type to use for UDP sockets
sock = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)

# As you can see, there is no connect() call; UDP has no connections.
# Instead, data is directly sent to the recipient via sendto().
sock.sendto(bytes(data + "\n", "utf-8"), (HOST, PORT))
received = str(sock.recv(1024), "utf-8")

print("Sent:     {}".format(data))
print("Received: {}".format(received))

The output of the example should look exactly like for the TCP server example.

21.21.4.3. Asynchronous Mixins

To build asynchronous handlers, use the ThreadingMixIn and ForkingMixIn classes.

An example for the ThreadingMixIn class:

import socket
import threading
import socketserver

class ThreadedTCPRequestHandler(socketserver.BaseRequestHandler):

    def handle(self):
        data = str(self.request.recv(1024), 'ascii')
        cur_thread = threading.current_thread()
        response = bytes("{}: {}".format(cur_thread.name, data), 'ascii')
        self.request.sendall(response)

class ThreadedTCPServer(socketserver.ThreadingMixIn, socketserver.TCPServer):
    pass

def client(ip, port, message):
    with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as sock:
        sock.connect((ip, port))
        sock.sendall(bytes(message, 'ascii'))
        response = str(sock.recv(1024), 'ascii')
        print("Received: {}".format(response))

if __name__ == "__main__":
    # Port 0 means to select an arbitrary unused port
    HOST, PORT = "localhost", 0

    server = ThreadedTCPServer((HOST, PORT), ThreadedTCPRequestHandler)
    with server:
        ip, port = server.server_address

        # Start a thread with the server -- that thread will then start one
        # more thread for each request
        server_thread = threading.Thread(target=server.serve_forever)
        # Exit the server thread when the main thread terminates
        server_thread.daemon = True
        server_thread.start()
        print("Server loop running in thread:", server_thread.name)

        client(ip, port, "Hello World 1")
        client(ip, port, "Hello World 2")
        client(ip, port, "Hello World 3")

        server.shutdown()

The output of the example should look something like this:

$ python ThreadedTCPServer.py
Server loop running in thread: Thread-1
Received: Thread-2: Hello World 1
Received: Thread-3: Hello World 2
Received: Thread-4: Hello World 3

The ForkingMixIn class is used in the same way, except that the server will spawn a new process for each request. Available only on POSIX platforms that support fork().

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21.22. http.server — HTTP servers

Source code: Lib/http/server.py [https://github.com/python/cpython/tree/3.6/Lib/http/server.py]

This module defines classes for implementing HTTP servers (Web servers).

Avertissement

http.server is not recommended for production. It only implements only basic security checks.

One class, HTTPServer, is a socketserver.TCPServer subclass. It creates and listens at the HTTP socket, dispatching the requests to a handler. Code to create and run the server looks like this:

def run(server_class=HTTPServer, handler_class=BaseHTTPRequestHandler):
    server_address = ('', 8000)
    httpd = server_class(server_address, handler_class)
    httpd.serve_forever()

class http.server.HTTPServer(server_address, RequestHandlerClass)

This class builds on the TCPServer class by storing the server address as instance variables named server_name and server_port. The server is accessible by the handler, typically through the handler’s server instance variable.

The HTTPServer must be given a RequestHandlerClass on instantiation, of which this module provides three different variants:

class http.server.BaseHTTPRequestHandler(request, client_address, server)

This class is used to handle the HTTP requests that arrive at the server. By itself, it cannot respond to any actual HTTP requests; it must be subclassed to handle each request method (e.g. GET or POST). BaseHTTPRequestHandler provides a number of class and instance variables, and methods for use by subclasses.

The handler will parse the request and the headers, then call a method specific to the request type. The method name is constructed from the request. For example, for the request method SPAM, the do_SPAM() method will be called with no arguments. All of the relevant information is stored in instance variables of the handler. Subclasses should not need to override or extend the __init__() method.

BaseHTTPRequestHandler has the following instance variables:

client_address

Contains a tuple of the form (host, port) referring to the client’s address.

server

Contains the server instance.

close_connection

Boolean that should be set before handle_one_request() returns, indicating if another request may be expected, or if the connection should be shut down.

requestline

Contains the string representation of the HTTP request line. The terminating CRLF is stripped. This attribute should be set by handle_one_request(). If no valid request line was processed, it should be set to the empty string.

command

Contains the command (request type). For example, 'GET'.

path

Contains the request path.

request_version

Contains the version string from the request. For example, 'HTTP/1.0'.

headers

Holds an instance of the class specified by the MessageClass class variable. This instance parses and manages the headers in the HTTP request. The parse_headers() function from http.client is used to parse the headers and it requires that the HTTP request provide a valid RFC 2822 [https://tools.ietf.org/html/rfc2822.html] style header.

rfile

An io.BufferedIOBase input stream, ready to read from the start of the optional input data.

wfile

Contains the output stream for writing a response back to the client. Proper adherence to the HTTP protocol must be used when writing to this stream in order to achieve successful interoperation with HTTP clients.

Modifié dans la version 3.6: This is an io.BufferedIOBase stream.

BaseHTTPRequestHandler has the following attributes:

server_version

Specifies the server software version. You may want to override this. The format is multiple whitespace-separated strings, where each string is of the form name[/version]. For example, 'BaseHTTP/0.2'.

sys_version

Contains the Python system version, in a form usable by the version_string method and the server_version class variable. For example, 'Python/1.4'.

error_message_format

Specifies a format string that should be used by send_error() method for building an error response to the client. The string is filled by default with variables from responses based on the status code that passed to send_error().

error_content_type

Specifies the Content-Type HTTP header of error responses sent to the client. The default value is 'text/html'.

protocol_version

This specifies the HTTP protocol version used in responses. If set to 'HTTP/1.1', the server will permit HTTP persistent connections; however, your server must then include an accurate Content-Length header (using send_header()) in all of its responses to clients. For backwards compatibility, the setting defaults to 'HTTP/1.0'.

MessageClass

Specifies an email.message.Message-like class to parse HTTP headers. Typically, this is not overridden, and it defaults to http.client.HTTPMessage.

responses

This attribute contains a mapping of error code integers to two-element tuples containing a short and long message. For example, {code: (shortmessage, longmessage)}. The shortmessage is usually used as the message key in an error response, and longmessage as the explain key. It is used by send_response_only() and send_error() methods.

A BaseHTTPRequestHandler instance has the following methods:

handle()

Calls handle_one_request() once (or, if persistent connections are enabled, multiple times) to handle incoming HTTP requests. You should never need to override it; instead, implement appropriate do_*() methods.

handle_one_request()

This method will parse and dispatch the request to the appropriate do_*() method. You should never need to override it.

handle_expect_100()

When a HTTP/1.1 compliant server receives an Expect: 100-continue request header it responds back with a 100 Continue followed by 200 OK headers. This method can be overridden to raise an error if the server does not want the client to continue. For e.g. server can chose to send 417 Expectation Failed as a response header and return False.

Nouveau dans la version 3.2.

send_error(code, message=None, explain=None)

Sends and logs a complete error reply to the client. The numeric code specifies the HTTP error code, with message as an optional, short, human readable description of the error. The explain argument can be used to provide more detailed information about the error; it will be formatted using the error_message_format attribute and emitted, after a complete set of headers, as the response body. The responses attribute holds the default values for message and explain that will be used if no value is provided; for unknown codes the default value for both is the string ???. The body will be empty if the method is HEAD or the response code is one of the following: 1xx, 204 No Content, 205 Reset Content, 304 Not Modified.

Modifié dans la version 3.4: The error response includes a Content-Length header. Added the explain argument.

send_response(code, message=None)

Adds a response header to the headers buffer and logs the accepted request. The HTTP response line is written to the internal buffer, followed by Server and Date headers. The values for these two headers are picked up from the version_string() and date_time_string() methods, respectively. If the server does not intend to send any other headers using the send_header() method, then send_response() should be followed by an end_headers() call.

Modifié dans la version 3.3: Headers are stored to an internal buffer and end_headers() needs to be called explicitly.

send_header(keyword, value)

Adds the HTTP header to an internal buffer which will be written to the output stream when either end_headers() or flush_headers() is invoked. keyword should specify the header keyword, with value specifying its value. Note that, after the send_header calls are done, end_headers() MUST BE called in order to complete the operation.

Modifié dans la version 3.2: Headers are stored in an internal buffer.

send_response_only(code, message=None)

Sends the response header only, used for the purposes when 100 Continue response is sent by the server to the client. The headers not buffered and sent directly the output stream.If the message is not specified, the HTTP message corresponding the response code is sent.

Nouveau dans la version 3.2.

end_headers()

Adds a blank line (indicating the end of the HTTP headers in the response) to the headers buffer and calls flush_headers().

Modifié dans la version 3.2: The buffered headers are written to the output stream.

flush_headers()

Finally send the headers to the output stream and flush the internal headers buffer.

Nouveau dans la version 3.3.

log_request(code='-', size='-')

Logs an accepted (successful) request. code should specify the numeric HTTP code associated with the response. If a size of the response is available, then it should be passed as the size parameter.

log_error(...)

Logs an error when a request cannot be fulfilled. By default, it passes the message to log_message(), so it takes the same arguments (format and additional values).

log_message(format, ...)

Logs an arbitrary message to sys.stderr. This is typically overridden to create custom error logging mechanisms. The format argument is a standard printf-style format string, where the additional arguments to log_message() are applied as inputs to the formatting. The client ip address and current date and time are prefixed to every message logged.

version_string()

Returns the server software’s version string. This is a combination of the server_version and sys_version attributes.

date_time_string(timestamp=None)

Returns the date and time given by timestamp (which must be None or in the format returned by time.time()), formatted for a message header. If timestamp is omitted, it uses the current date and time.

The result looks like 'Sun, 06 Nov 1994 08:49:37 GMT'.

log_date_time_string()

Returns the current date and time, formatted for logging.

address_string()

Returns the client address.

Modifié dans la version 3.3: Previously, a name lookup was performed. To avoid name resolution delays, it now always returns the IP address.

class http.server.SimpleHTTPRequestHandler(request, client_address, server)

This class serves files from the current directory and below, directly mapping the directory structure to HTTP requests.

A lot of the work, such as parsing the request, is done by the base class BaseHTTPRequestHandler. This class implements the do_GET() and do_HEAD() functions.

The following are defined as class-level attributes of SimpleHTTPRequestHandler:

server_version

This will be "SimpleHTTP/" + __version__, where __version__ is defined at the module level.

extensions_map

A dictionary mapping suffixes into MIME types. The default is signified by an empty string, and is considered to be application/octet-stream. The mapping is used case-insensitively, and so should contain only lower-cased keys.

The SimpleHTTPRequestHandler class defines the following methods:

do_HEAD()

This method serves the 'HEAD' request type: it sends the headers it would send for the equivalent GET request. See the do_GET() method for a more complete explanation of the possible headers.

do_GET()

The request is mapped to a local file by interpreting the request as a path relative to the current working directory.

If the request was mapped to a directory, the directory is checked for a file named index.html or index.htm (in that order). If found, the file’s contents are returned; otherwise a directory listing is generated by calling the list_directory() method. This method uses os.listdir() to scan the directory, and returns a 404 error response if the listdir() fails.

If the request was mapped to a file, it is opened and the contents are returned. Any OSError exception in opening the requested file is mapped to a 404, 'File not found' error. Otherwise, the content type is guessed by calling the guess_type() method, which in turn uses the extensions_map variable.

A 'Content-type:' header with the guessed content type is output, followed by a 'Content-Length:' header with the file’s size and a 'Last-Modified:' header with the file’s modification time.

Then follows a blank line signifying the end of the headers, and then the contents of the file are output. If the file’s MIME type starts with text/ the file is opened in text mode; otherwise binary mode is used.

For example usage, see the implementation of the test() function invocation in the http.server module.

The SimpleHTTPRequestHandler class can be used in the following manner in order to create a very basic webserver serving files relative to the current directory:

import http.server
import socketserver

PORT = 8000

Handler = http.server.SimpleHTTPRequestHandler

with socketserver.TCPServer(("", PORT), Handler) as httpd:
    print("serving at port", PORT)
    httpd.serve_forever()

http.server can also be invoked directly using the -m switch of the interpreter with a port number argument. Similar to the previous example, this serves files relative to the current directory:

python -m http.server 8000

By default, server binds itself to all interfaces. The option -b/--bind specifies a specific address to which it should bind. For example, the following command causes the server to bind to localhost only:

python -m http.server 8000 --bind 127.0.0.1

Nouveau dans la version 3.4: --bind argument was introduced.

class http.server.CGIHTTPRequestHandler(request, client_address, server)

This class is used to serve either files or output of CGI scripts from the current directory and below. Note that mapping HTTP hierarchic structure to local directory structure is exactly as in SimpleHTTPRequestHandler.

Note

CGI scripts run by the CGIHTTPRequestHandler class cannot execute redirects (HTTP code 302), because code 200 (script output follows) is sent prior to execution of the CGI script. This pre-empts the status code.

The class will however, run the CGI script, instead of serving it as a file, if it guesses it to be a CGI script. Only directory-based CGI are used — the other common server configuration is to treat special extensions as denoting CGI scripts.

The do_GET() and do_HEAD() functions are modified to run CGI scripts and serve the output, instead of serving files, if the request leads to somewhere below the cgi_directories path.

The CGIHTTPRequestHandler defines the following data member:

cgi_directories

This defaults to ['/cgi-bin', '/htbin'] and describes directories to treat as containing CGI scripts.

The CGIHTTPRequestHandler defines the following method:

do_POST()

This method serves the 'POST' request type, only allowed for CGI scripts. Error 501, « Can only POST to CGI scripts », is output when trying to POST to a non-CGI url.

Note that CGI scripts will be run with UID of user nobody, for security reasons. Problems with the CGI script will be translated to error 403.

CGIHTTPRequestHandler can be enabled in the command line by passing the --cgi option:

python -m http.server --cgi 8000

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21.23. http.cookies — gestion d’état pour HTTP

Code source : Lib/http/cookies.py [https://github.com/python/cpython/tree/3.6/Lib/http/cookies.py]

Le module http.cookies définit des classes abstrayant le concept de témoin web (cookie), un mécanisme de gestion d’état pour HTTP. Il fournit une abstraction gérant des données textuelles et tout type de données sérialisable comme valeur de témoin.

Auparavant, le module appliquait strictement les règles d’analyse décrites dans les spécifications RFC 2109 [https://tools.ietf.org/html/rfc2109.html] et RFC 2068 [https://tools.ietf.org/html/rfc2068.html]. Entre temps, il a été découvert que Internet Explorer 3.0 ne suit pas les règles liées aux caractères précisées dans ces spécifications. De plus, plusieurs navigateurs et serveurs dans leur versions récentes ont assoupli les règles d’analyse quant à la gestion des témoins. En conséquence, les règles d’analyse utilisées sont un peu moins strictes que les spécifications initiales.

Les jeux de caractères string.ascii_letters, string.digits et !#$%&'*+-.^_`|~: définissent l’ensemble des caractères autorisés par ce module pour le nom du témoin (comme key).

Modifié dans la version 3.3: Ajouté « : » comme caractère autorisé pour les noms de témoin.

Note

Quand un témoin invalide est rencontré, l’exception CookieError est levée. Si les données du témoin proviennent d’un navigateur il faut impérativement gérer les données invalides en attrapant CookieError.

exception http.cookies.CookieError

Exception levée pour cause d’incompatibilité avec la RFC 2109 [https://tools.ietf.org/html/rfc2109.html]. Exemples : attributs incorrects, en-tête Set-Cookie incorrect, etc.

class http.cookies.BaseCookie([input])

Cette classe définit un dictionnaire dont les clés sont des chaines de caractères et dont les valeurs sont des instances de Morsel. Notez qu’à l’assignation d’une valeur à une clé, la valeur est transformée en Morsel contenant la clé et la valeur.

Si l’argument input est donné, il est passé à la méthode load().

class http.cookies.SimpleCookie([input])

This class derives from BaseCookie and overrides value_decode() and value_encode() to be the identity and str() respectively.

Voir aussi

Module http.cookiejar

Gestion de témoins HTTP pour clients web. Les modules http.cookiejar et http.cookies ne dépendent pas l’un de l’autre.

RFC 2109 [https://tools.ietf.org/html/rfc2109.html] - HTTP State Management Mechanism

Spécification de gestion d’états implantée par ce module.

21.23.1. Objets Cookie

BaseCookie.value_decode(val)

Return a decoded value from a string representation. Return value can be any type. This method does nothing in BaseCookie — it exists so it can be overridden.

BaseCookie.value_encode(val)

Return an encoded value. val can be any type, but return value must be a string. This method does nothing in BaseCookie — it exists so it can be overridden.

Généralement, les méthodes value_encode() et value_decode() doivent être inverses l’une de l’autre, c’est-à-dire qu’en envoyant la sortie de l’un dans l’entrée de l’autre la valeur finale doit être égale à la valeur initiale.

BaseCookie.output(attrs=None, header='Set-Cookie:', sep='\r\n')

Renvoie une représentation textuelle compatible avec les en-têtes HTTP. attrs et *header sont envoyés à la méthode output() de chaque classe Morsel. sep est le séparateur à utiliser pour joindre les valeurs d’en-têtes. Sa valeur par défaut est '\r\n' (CRLF).

BaseCookie.js_output(attrs=None)

Renvoie un extrait de code JavaScript qui, lorsque exécuté par un navigateur qui supporte le JavaScript, va fonctionner de la même manière que si les en-têtes HTTP avaient été envoyés.

attrs a la même signification que dans la méthode output().

BaseCookie.load(rawdata)

Si rawdata est une chaine de caractères, l’analyser comme étant un HTTP_COOKIE et ajouter les valeurs trouvées en tant que Morsels. S’il s’agit d’un dictionnaire, cela est équivalent à :

for k, v in rawdata.items():
    cookie[k] = v

21.23.2. Objets Morsel

class http.cookies.Morsel

Abstraction de paire clé / valeur, accompagnée d’attributs provenant de la spécification RFC 2109 [https://tools.ietf.org/html/rfc2109.html].

Les objets Morsel sont des objets compatibles dictionnaire, dont l’ensemble des clés est fixe et égal aux attributs RFC 2109 [https://tools.ietf.org/html/rfc2109.html] valides, qui sont

expires

path

comment

domain

max-age

secure

version

httponly

L’attribut httponly spécifie que le témoin transféré dans les requêtes HTTP n’est pas accessible par le biais de JavaScript. Il s’agit d’une contremesure à certaines attaques de scripts inter-sites (XSS).

Les clés ne sont pas sensibles à la casse, leur valeur par défaut est ''.

Modifié dans la version 3.5: Dorénavant, __eq__() prend en compte key et value.

Morsel.value

La valeur du témoin.

Obsolète depuis la version 3.5: assigning to value; use set() instead.

Morsel.coded_value

La valeur codée du témoin. C’est celle qui doit être transférée.

Obsolète depuis la version 3.5: assigning to coded_value; use set() instead.

Morsel.key

Le nom du témoin.

Obsolète depuis la version 3.5: assigning to key; use set() instead.

Morsel.set(key, value, coded_value)

Assigne les attributs key, value et coded_value.

Obsolète depuis la version 3.5: The undocumented LegalChars parameter is ignored and will be removed in a future version.

Morsel.isReservedKey(K)

Renvoie si K est membre des clés d’un Morsel.

Morsel.output(attrs=None, header='Set-Cookie:')

Renvoie une représentation textuelle du Morsel compatible avec les en-têtes HTTP. Par défaut, tous les attributs sont inclus, à moins que attrs ne soit renseigné. Dans ce cas la valeur doit être une liste d’attributs à utiliser. Par défaut, header a la valeur "Set-Cookie:".

Morsel.js_output(attrs=None)

Renvoie un extrait de code JavaScript qui, lorsque exécuté par un navigateur qui supporte le JavaScript, va fonctionner de la même manière que si les en-têtes HTTP avaient été envoyés.

attrs a la même signification que dans la méthode output().

Morsel.OutputString(attrs=None)

Renvoie une chaine de caractères représentant le Morsel, nettoyé de son contexte HTTP ou JavaScript.

attrs a la même signification que dans la méthode output().

Morsel.update(values)

Met à jour les valeurs du dictionnaire du Morsel avec les valeurs provenant du dictionnaire values. Lève une erreur si une des clés n’est pas un attribut RFC 2109 [https://tools.ietf.org/html/rfc2109.html] valide.

Modifié dans la version 3.5: une erreur est levée pour les clés invalides.

Morsel.copy(value)

Renvoie une copie superficielle de l’objet Morsel.

Modifié dans la version 3.5: renvoie un objet Morsel au lieu d’un dict.

Morsel.setdefault(key, value=None)

Lève une erreur si la clé n’est pas un attribut RFC 2109 [https://tools.ietf.org/html/rfc2109.html] valide, sinon fonctionne de la même manière que dict.setdefault().

21.23.3. Exemple

L’exemple suivant montre comment utiliser le module http.cookies.

>>> from http import cookies
>>> C = cookies.SimpleCookie()
>>> C["fig"] = "newton"
>>> C["sugar"] = "wafer"
>>> print(C) # generate HTTP headers
Set-Cookie: fig=newton
Set-Cookie: sugar=wafer
>>> print(C.output()) # same thing
Set-Cookie: fig=newton
Set-Cookie: sugar=wafer
>>> C = cookies.SimpleCookie()
>>> C["rocky"] = "road"
>>> C["rocky"]["path"] = "/cookie"
>>> print(C.output(header="Cookie:"))
Cookie: rocky=road; Path=/cookie
>>> print(C.output(attrs=[], header="Cookie:"))
Cookie: rocky=road
>>> C = cookies.SimpleCookie()
>>> C.load("chips=ahoy; vienna=finger") # load from a string (HTTP header)
>>> print(C)
Set-Cookie: chips=ahoy
Set-Cookie: vienna=finger
>>> C = cookies.SimpleCookie()
>>> C.load('keebler="E=everybody; L=\\"Loves\\"; fudge=\\012;";')
>>> print(C)
Set-Cookie: keebler="E=everybody; L=\"Loves\"; fudge=\012;"
>>> C = cookies.SimpleCookie()
>>> C["oreo"] = "doublestuff"
>>> C["oreo"]["path"] = "/"
>>> print(C)
Set-Cookie: oreo=doublestuff; Path=/
>>> C = cookies.SimpleCookie()
>>> C["twix"] = "none for you"
>>> C["twix"].value
'none for you'
>>> C = cookies.SimpleCookie()
>>> C["number"] = 7 # equivalent to C["number"] = str(7)
>>> C["string"] = "seven"
>>> C["number"].value
'7'
>>> C["string"].value
'seven'
>>> print(C)
Set-Cookie: number=7
Set-Cookie: string=seven

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21.24. http.cookiejar — Cookie handling for HTTP clients

Source code: Lib/http/cookiejar.py [https://github.com/python/cpython/tree/3.6/Lib/http/cookiejar.py]

The http.cookiejar module defines classes for automatic handling of HTTP cookies. It is useful for accessing web sites that require small pieces of data – cookies – to be set on the client machine by an HTTP response from a web server, and then returned to the server in later HTTP requests.

Both the regular Netscape cookie protocol and the protocol defined by RFC 2965 [https://tools.ietf.org/html/rfc2965.html] are handled. RFC 2965 handling is switched off by default. RFC 2109 [https://tools.ietf.org/html/rfc2109.html] cookies are parsed as Netscape cookies and subsequently treated either as Netscape or RFC 2965 cookies according to the “policy” in effect. Note that the great majority of cookies on the Internet are Netscape cookies. http.cookiejar attempts to follow the de-facto Netscape cookie protocol (which differs substantially from that set out in the original Netscape specification), including taking note of the max-age and port cookie-attributes introduced with RFC 2965.

Note

The various named parameters found in Set-Cookie and Set-Cookie2 headers (eg. domain and expires) are conventionally referred to as attributes. To distinguish them from Python attributes, the documentation for this module uses the term cookie-attribute instead.

The module defines the following exception:

exception http.cookiejar.LoadError

Instances of FileCookieJar raise this exception on failure to load cookies from a file. LoadError is a subclass of OSError.

Modifié dans la version 3.3: LoadError was made a subclass of OSError instead of IOError.

The following classes are provided:

class http.cookiejar.CookieJar(policy=None)

policy is an object implementing the CookiePolicy interface.

The CookieJar class stores HTTP cookies. It extracts cookies from HTTP requests, and returns them in HTTP responses. CookieJar instances automatically expire contained cookies when necessary. Subclasses are also responsible for storing and retrieving cookies from a file or database.

class http.cookiejar.FileCookieJar(filename, delayload=None, policy=None)

policy is an object implementing the CookiePolicy interface. For the other arguments, see the documentation for the corresponding attributes.

A CookieJar which can load cookies from, and perhaps save cookies to, a file on disk. Cookies are NOT loaded from the named file until either the load() or revert() method is called. Subclasses of this class are documented in section FileCookieJar subclasses and co-operation with web browsers.

class http.cookiejar.CookiePolicy

This class is responsible for deciding whether each cookie should be accepted from / returned to the server.

class http.cookiejar.DefaultCookiePolicy(blocked_domains=None, allowed_domains=None, netscape=True, rfc2965=False, rfc2109_as_netscape=None, hide_cookie2=False, strict_domain=False, strict_rfc2965_unverifiable=True, strict_ns_unverifiable=False, strict_ns_domain=DefaultCookiePolicy.DomainLiberal, strict_ns_set_initial_dollar=False, strict_ns_set_path=False)

Constructor arguments should be passed as keyword arguments only. blocked_domains is a sequence of domain names that we never accept cookies from, nor return cookies to. allowed_domains if not None, this is a sequence of the only domains for which we accept and return cookies. For all other arguments, see the documentation for CookiePolicy and DefaultCookiePolicy objects.

DefaultCookiePolicy implements the standard accept / reject rules for Netscape and RFC 2965 [https://tools.ietf.org/html/rfc2965.html] cookies. By default, RFC 2109 [https://tools.ietf.org/html/rfc2109.html] cookies (ie. cookies received in a Set-Cookie header with a version cookie-attribute of 1) are treated according to the RFC 2965 rules. However, if RFC 2965 handling is turned off or rfc2109_as_netscape is True, RFC 2109 cookies are “downgraded” by the CookieJar instance to Netscape cookies, by setting the version attribute of the Cookie instance to 0. DefaultCookiePolicy also provides some parameters to allow some fine-tuning of policy.

class http.cookiejar.Cookie

This class represents Netscape, RFC 2109 [https://tools.ietf.org/html/rfc2109.html] and RFC 2965 [https://tools.ietf.org/html/rfc2965.html] cookies. It is not expected that users of http.cookiejar construct their own Cookie instances. Instead, if necessary, call make_cookies() on a CookieJar instance.

Voir aussi

Module urllib.request

URL opening with automatic cookie handling.

Module http.cookies

HTTP cookie classes, principally useful for server-side code. The http.cookiejar and http.cookies modules do not depend on each other.

https://curl.haxx.se/rfc/cookie_spec.html

The specification of the original Netscape cookie protocol. Though this is still the dominant protocol, the “Netscape cookie protocol” implemented by all the major browsers (and http.cookiejar) only bears a passing resemblance to the one sketched out in cookie_spec.html.

RFC 2109 [https://tools.ietf.org/html/rfc2109.html] - HTTP State Management Mechanism

Obsoleted by RFC 2965 [https://tools.ietf.org/html/rfc2965.html]. Uses Set-Cookie with version=1.

RFC 2965 [https://tools.ietf.org/html/rfc2965.html] - HTTP State Management Mechanism

The Netscape protocol with the bugs fixed. Uses Set-Cookie2 in place of Set-Cookie. Not widely used.

http://kristol.org/cookie/errata.html

Unfinished errata to RFC 2965 [https://tools.ietf.org/html/rfc2965.html].

RFC 2964 [https://tools.ietf.org/html/rfc2964.html] - Use of HTTP State Management

21.24.1. CookieJar and FileCookieJar Objects

CookieJar objects support the iterator protocol for iterating over contained Cookie objects.

CookieJar has the following methods:

CookieJar.add_cookie_header(request)

Add correct Cookie header to request.

If policy allows (ie. the rfc2965 and hide_cookie2 attributes of the CookieJar’s CookiePolicy instance are true and false respectively), the Cookie2 header is also added when appropriate.

The request object (usually a urllib.request..Request instance) must support the methods get_full_url(), get_host(), get_type(), unverifiable(), has_header(), get_header(), header_items(), add_unredirected_header() and origin_req_host attribute as documented by urllib.request.

Modifié dans la version 3.3: request object needs origin_req_host attribute. Dependency on a deprecated method get_origin_req_host() has been removed.

CookieJar.extract_cookies(response, request)

Extract cookies from HTTP response and store them in the CookieJar, where allowed by policy.

The CookieJar will look for allowable Set-Cookie and Set-Cookie2 headers in the response argument, and store cookies as appropriate (subject to the CookiePolicy.set_ok() method’s approval).

The response object (usually the result of a call to urllib.request.urlopen(), or similar) should support an info() method, which returns an email.message.Message instance.

The request object (usually a urllib.request.Request instance) must support the methods get_full_url(), get_host(), unverifiable(), and origin_req_host attribute, as documented by urllib.request. The request is used to set default values for cookie-attributes as well as for checking that the cookie is allowed to be set.

Modifié dans la version 3.3: request object needs origin_req_host attribute. Dependency on a deprecated method get_origin_req_host() has been removed.

CookieJar.set_policy(policy)

Set the CookiePolicy instance to be used.

CookieJar.make_cookies(response, request)

Return sequence of Cookie objects extracted from response object.

See the documentation for extract_cookies() for the interfaces required of the response and request arguments.

CookieJar.set_cookie_if_ok(cookie, request)

Set a Cookie if policy says it’s OK to do so.

CookieJar.set_cookie(cookie)

Set a Cookie, without checking with policy to see whether or not it should be set.

CookieJar.clear([domain[, path[, name]]])

Clear some cookies.

If invoked without arguments, clear all cookies. If given a single argument, only cookies belonging to that domain will be removed. If given two arguments, cookies belonging to the specified domain and URL path are removed. If given three arguments, then the cookie with the specified domain, path and name is removed.

Raises KeyError if no matching cookie exists.

CookieJar.clear_session_cookies()

Discard all session cookies.

Discards all contained cookies that have a true discard attribute (usually because they had either no max-age or expires cookie-attribute, or an explicit discard cookie-attribute). For interactive browsers, the end of a session usually corresponds to closing the browser window.

Note that the save() method won’t save session cookies anyway, unless you ask otherwise by passing a true ignore_discard argument.

FileCookieJar implements the following additional methods:

FileCookieJar.save(filename=None, ignore_discard=False, ignore_expires=False)

Save cookies to a file.

This base class raises NotImplementedError. Subclasses may leave this method unimplemented.

filename is the name of file in which to save cookies. If filename is not specified, self.filename is used (whose default is the value passed to the constructor, if any); if self.filename is None, ValueError is raised.

ignore_discard: save even cookies set to be discarded. ignore_expires: save even cookies that have expired

The file is overwritten if it already exists, thus wiping all the cookies it contains. Saved cookies can be restored later using the load() or revert() methods.

FileCookieJar.load(filename=None, ignore_discard=False, ignore_expires=False)

Load cookies from a file.

Old cookies are kept unless overwritten by newly loaded ones.

Arguments are as for save().

The named file must be in the format understood by the class, or LoadError will be raised. Also, OSError may be raised, for example if the file does not exist.

Modifié dans la version 3.3: IOError était normalement levée, elle est maintenant un alias de OSError.

FileCookieJar.revert(filename=None, ignore_discard=False, ignore_expires=False)

Clear all cookies and reload cookies from a saved file.

revert() can raise the same exceptions as load(). If there is a failure, the object’s state will not be altered.

FileCookieJar instances have the following public attributes:

FileCookieJar.filename

Filename of default file in which to keep cookies. This attribute may be assigned to.

FileCookieJar.delayload

If true, load cookies lazily from disk. This attribute should not be assigned to. This is only a hint, since this only affects performance, not behaviour (unless the cookies on disk are changing). A CookieJar object may ignore it. None of the FileCookieJar classes included in the standard library lazily loads cookies.

21.24.2. FileCookieJar subclasses and co-operation with web browsers

The following CookieJar subclasses are provided for reading and writing.

class http.cookiejar.MozillaCookieJar(filename, delayload=None, policy=None)

A FileCookieJar that can load from and save cookies to disk in the Mozilla cookies.txt file format (which is also used by the Lynx and Netscape browsers).

Note

This loses information about RFC 2965 [https://tools.ietf.org/html/rfc2965.html] cookies, and also about newer or non-standard cookie-attributes such as port.

Avertissement

Back up your cookies before saving if you have cookies whose loss / corruption would be inconvenient (there are some subtleties which may lead to slight changes in the file over a load / save round-trip).

Also note that cookies saved while Mozilla is running will get clobbered by Mozilla.

class http.cookiejar.LWPCookieJar(filename, delayload=None, policy=None)

A FileCookieJar that can load from and save cookies to disk in format compatible with the libwww-perl library’s Set-Cookie3 file format. This is convenient if you want to store cookies in a human-readable file.

21.24.3. CookiePolicy Objects

Objects implementing the CookiePolicy interface have the following methods:

CookiePolicy.set_ok(cookie, request)

Return boolean value indicating whether cookie should be accepted from server.

cookie is a Cookie instance. request is an object implementing the interface defined by the documentation for CookieJar.extract_cookies().

CookiePolicy.return_ok(cookie, request)

Return boolean value indicating whether cookie should be returned to server.

cookie is a Cookie instance. request is an object implementing the interface defined by the documentation for CookieJar.add_cookie_header().

CookiePolicy.domain_return_ok(domain, request)

Return false if cookies should not be returned, given cookie domain.

This method is an optimization. It removes the need for checking every cookie with a particular domain (which might involve reading many files). Returning true from domain_return_ok() and path_return_ok() leaves all the work to return_ok().

If domain_return_ok() returns true for the cookie domain, path_return_ok() is called for the cookie path. Otherwise, path_return_ok() and return_ok() are never called for that cookie domain. If path_return_ok() returns true, return_ok() is called with the Cookie object itself for a full check. Otherwise, return_ok() is never called for that cookie path.

Note that domain_return_ok() is called for every cookie domain, not just for the request domain. For example, the function might be called with both ".example.com" and "www.example.com" if the request domain is "www.example.com". The same goes for path_return_ok().

The request argument is as documented for return_ok().

CookiePolicy.path_return_ok(path, request)

Return false if cookies should not be returned, given cookie path.

See the documentation for domain_return_ok().

In addition to implementing the methods above, implementations of the CookiePolicy interface must also supply the following attributes, indicating which protocols should be used, and how. All of these attributes may be assigned to.

CookiePolicy.netscape

Implement Netscape protocol.

CookiePolicy.rfc2965

Implement RFC 2965 [https://tools.ietf.org/html/rfc2965.html] protocol.

CookiePolicy.hide_cookie2

Don’t add Cookie2 header to requests (the presence of this header indicates to the server that we understand RFC 2965 [https://tools.ietf.org/html/rfc2965.html] cookies).

The most useful way to define a CookiePolicy class is by subclassing from DefaultCookiePolicy and overriding some or all of the methods above. CookiePolicy itself may be used as a “null policy” to allow setting and receiving any and all cookies (this is unlikely to be useful).

21.24.4. DefaultCookiePolicy Objects

Implements the standard rules for accepting and returning cookies.

Both RFC 2965 [https://tools.ietf.org/html/rfc2965.html] and Netscape cookies are covered. RFC 2965 handling is switched off by default.

The easiest way to provide your own policy is to override this class and call its methods in your overridden implementations before adding your own additional checks:

import http.cookiejar
class MyCookiePolicy(http.cookiejar.DefaultCookiePolicy):
    def set_ok(self, cookie, request):
        if not http.cookiejar.DefaultCookiePolicy.set_ok(self, cookie, request):
            return False
        if i_dont_want_to_store_this_cookie(cookie):
            return False
        return True

In addition to the features required to implement the CookiePolicy interface, this class allows you to block and allow domains from setting and receiving cookies. There are also some strictness switches that allow you to tighten up the rather loose Netscape protocol rules a little bit (at the cost of blocking some benign cookies).

A domain blacklist and whitelist is provided (both off by default). Only domains not in the blacklist and present in the whitelist (if the whitelist is active) participate in cookie setting and returning. Use the blocked_domains constructor argument, and blocked_domains() and set_blocked_domains() methods (and the corresponding argument and methods for allowed_domains). If you set a whitelist, you can turn it off again by setting it to None.

Domains in block or allow lists that do not start with a dot must equal the cookie domain to be matched. For example, "example.com" matches a blacklist entry of "example.com", but "www.example.com" does not. Domains that do start with a dot are matched by more specific domains too. For example, both "www.example.com" and "www.coyote.example.com" match ".example.com" (but "example.com" itself does not). IP addresses are an exception, and must match exactly. For example, if blocked_domains contains "192.168.1.2" and ".168.1.2", 192.168.1.2 is blocked, but 193.168.1.2 is not.

DefaultCookiePolicy implements the following additional methods:

DefaultCookiePolicy.blocked_domains()

Return the sequence of blocked domains (as a tuple).

DefaultCookiePolicy.set_blocked_domains(blocked_domains)

Set the sequence of blocked domains.

DefaultCookiePolicy.is_blocked(domain)

Return whether domain is on the blacklist for setting or receiving cookies.

DefaultCookiePolicy.allowed_domains()

Return None, or the sequence of allowed domains (as a tuple).

DefaultCookiePolicy.set_allowed_domains(allowed_domains)

Set the sequence of allowed domains, or None.

DefaultCookiePolicy.is_not_allowed(domain)

Return whether domain is not on the whitelist for setting or receiving cookies.

DefaultCookiePolicy instances have the following attributes, which are all initialised from the constructor arguments of the same name, and which may all be assigned to.

DefaultCookiePolicy.rfc2109_as_netscape

If true, request that the CookieJar instance downgrade RFC 2109 [https://tools.ietf.org/html/rfc2109.html] cookies (ie. cookies received in a Set-Cookie header with a version cookie-attribute of 1) to Netscape cookies by setting the version attribute of the Cookie instance to 0. The default value is None, in which case RFC 2109 cookies are downgraded if and only if RFC 2965 [https://tools.ietf.org/html/rfc2965.html] handling is turned off. Therefore, RFC 2109 cookies are downgraded by default.

General strictness switches:

DefaultCookiePolicy.strict_domain

Don’t allow sites to set two-component domains with country-code top-level domains like .co.uk, .gov.uk, .co.nz.etc. This is far from perfect and isn’t guaranteed to work!

RFC 2965 [https://tools.ietf.org/html/rfc2965.html] protocol strictness switches:

DefaultCookiePolicy.strict_rfc2965_unverifiable

Follow RFC 2965 [https://tools.ietf.org/html/rfc2965.html] rules on unverifiable transactions (usually, an unverifiable transaction is one resulting from a redirect or a request for an image hosted on another site). If this is false, cookies are never blocked on the basis of verifiability

Netscape protocol strictness switches:

DefaultCookiePolicy.strict_ns_unverifiable

Apply RFC 2965 [https://tools.ietf.org/html/rfc2965.html] rules on unverifiable transactions even to Netscape cookies.

DefaultCookiePolicy.strict_ns_domain

Flags indicating how strict to be with domain-matching rules for Netscape cookies. See below for acceptable values.

DefaultCookiePolicy.strict_ns_set_initial_dollar

Ignore cookies in Set-Cookie: headers that have names starting with '$'.

DefaultCookiePolicy.strict_ns_set_path

Don’t allow setting cookies whose path doesn’t path-match request URI.

strict_ns_domain is a collection of flags. Its value is constructed by or-ing together (for example, DomainStrictNoDots|DomainStrictNonDomain means both flags are set).

DefaultCookiePolicy.DomainStrictNoDots

When setting cookies, the “host prefix” must not contain a dot (eg. www.foo.bar.com can’t set a cookie for .bar.com, because www.foo contains a dot).

DefaultCookiePolicy.DomainStrictNonDomain

Cookies that did not explicitly specify a domain cookie-attribute can only be returned to a domain equal to the domain that set the cookie (eg. spam.example.com won’t be returned cookies from example.com that had no domain cookie-attribute).

DefaultCookiePolicy.DomainRFC2965Match

When setting cookies, require a full RFC 2965 [https://tools.ietf.org/html/rfc2965.html] domain-match.

The following attributes are provided for convenience, and are the most useful combinations of the above flags:

DefaultCookiePolicy.DomainLiberal

Equivalent to 0 (ie. all of the above Netscape domain strictness flags switched off).

DefaultCookiePolicy.DomainStrict

Equivalent to DomainStrictNoDots|DomainStrictNonDomain.

21.24.5. Objets Cookie

Cookie instances have Python attributes roughly corresponding to the standard cookie-attributes specified in the various cookie standards. The correspondence is not one-to-one, because there are complicated rules for assigning default values, because the max-age and expires cookie-attributes contain equivalent information, and because RFC 2109 [https://tools.ietf.org/html/rfc2109.html] cookies may be “downgraded” by http.cookiejar from version 1 to version 0 (Netscape) cookies.

Assignment to these attributes should not be necessary other than in rare circumstances in a CookiePolicy method. The class does not enforce internal consistency, so you should know what you’re doing if you do that.

Cookie.version

Integer or None. Netscape cookies have version 0. RFC 2965 [https://tools.ietf.org/html/rfc2965.html] and RFC 2109 [https://tools.ietf.org/html/rfc2109.html] cookies have a version cookie-attribute of 1. However, note that http.cookiejar may “downgrade” RFC 2109 cookies to Netscape cookies, in which case version is 0.

Cookie.name

Cookie name (a string).

Cookie.value

Cookie value (a string), or None.

Cookie.port

String representing a port or a set of ports (eg. “80”, or “80,8080”), or None.

Cookie.path

Cookie path (a string, eg. '/acme/rocket_launchers').

Cookie.secure

True if cookie should only be returned over a secure connection.

Cookie.expires

Integer expiry date in seconds since epoch, or None. See also the is_expired() method.

Cookie.discard

True if this is a session cookie.

Cookie.comment

String comment from the server explaining the function of this cookie, or None.

Cookie.comment_url

URL linking to a comment from the server explaining the function of this cookie, or None.

Cookie.rfc2109

True if this cookie was received as an RFC 2109 [https://tools.ietf.org/html/rfc2109.html] cookie (ie. the cookie arrived in a Set-Cookie header, and the value of the Version cookie-attribute in that header was 1). This attribute is provided because http.cookiejar may “downgrade” RFC 2109 cookies to Netscape cookies, in which case version is 0.

Cookie.port_specified

True if a port or set of ports was explicitly specified by the server (in the Set-Cookie / Set-Cookie2 header).

Cookie.domain_specified

True if a domain was explicitly specified by the server.

Cookie.domain_initial_dot

True if the domain explicitly specified by the server began with a dot ('.').

Cookies may have additional non-standard cookie-attributes. These may be accessed using the following methods:

Cookie.has_nonstandard_attr(name)

Return true if cookie has the named cookie-attribute.

Cookie.get_nonstandard_attr(name, default=None)

If cookie has the named cookie-attribute, return its value. Otherwise, return default.

Cookie.set_nonstandard_attr(name, value)

Set the value of the named cookie-attribute.

The Cookie class also defines the following method:

Cookie.is_expired(now=None)

True if cookie has passed the time at which the server requested it should expire. If now is given (in seconds since the epoch), return whether the cookie has expired at the specified time.

21.24.6. Exemples

The first example shows the most common usage of http.cookiejar:

import http.cookiejar, urllib.request
cj = http.cookiejar.CookieJar()
opener = urllib.request.build_opener(urllib.request.HTTPCookieProcessor(cj))
r = opener.open("http://example.com/")

This example illustrates how to open a URL using your Netscape, Mozilla, or Lynx cookies (assumes Unix/Netscape convention for location of the cookies file):

import os, http.cookiejar, urllib.request
cj = http.cookiejar.MozillaCookieJar()
cj.load(os.path.join(os.path.expanduser("~"), ".netscape", "cookies.txt"))
opener = urllib.request.build_opener(urllib.request.HTTPCookieProcessor(cj))
r = opener.open("http://example.com/")

The next example illustrates the use of DefaultCookiePolicy. Turn on RFC 2965 [https://tools.ietf.org/html/rfc2965.html] cookies, be more strict about domains when setting and returning Netscape cookies, and block some domains from setting cookies or having them returned:

import urllib.request
from http.cookiejar import CookieJar, DefaultCookiePolicy
policy = DefaultCookiePolicy(
    rfc2965=True, strict_ns_domain=Policy.DomainStrict,
    blocked_domains=["ads.net", ".ads.net"])
cj = CookieJar(policy)
opener = urllib.request.build_opener(urllib.request.HTTPCookieProcessor(cj))
r = opener.open("http://example.com/")

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21.25. xmlrpc — Modules Serveur et Client XMLRPC

XML-RPC est une méthode pour appeler des procédures distantes utilisant XML via HTTP. XML-RPC permet à un client d’appeler des fonctions avec leurs arguments sur un serveur distant (désigné par une URI), et recevoir en retour des données structurées.

xmlrpc est un paquet rassemblant un client et un serveur XML-RPC. Ces modules sont :

xmlrpc.client

xmlrpc.server

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21.26. xmlrpc.client — XML-RPC client access

Source code: Lib/xmlrpc/client.py [https://github.com/python/cpython/tree/3.6/Lib/xmlrpc/client.py]

XML-RPC is a Remote Procedure Call method that uses XML passed via HTTP(S) as a transport. With it, a client can call methods with parameters on a remote server (the server is named by a URI) and get back structured data. This module supports writing XML-RPC client code; it handles all the details of translating between conformable Python objects and XML on the wire.

Avertissement

The xmlrpc.client module is not secure against maliciously constructed data. If you need to parse untrusted or unauthenticated data see Vulnérabilités XML.

Modifié dans la version 3.5: For HTTPS URIs, xmlrpc.client now performs all the necessary certificate and hostname checks by default.

class xmlrpc.client.ServerProxy(uri, transport=None, encoding=None, verbose=False, allow_none=False, use_datetime=False, use_builtin_types=False, *, context=None)

Modifié dans la version 3.3: The use_builtin_types flag was added.

A ServerProxy instance is an object that manages communication with a remote XML-RPC server. The required first argument is a URI (Uniform Resource Indicator), and will normally be the URL of the server. The optional second argument is a transport factory instance; by default it is an internal SafeTransport instance for https: URLs and an internal HTTP Transport instance otherwise. The optional third argument is an encoding, by default UTF-8. The optional fourth argument is a debugging flag.

The following parameters govern the use of the returned proxy instance. If allow_none is true, the Python constant None will be translated into XML; the default behaviour is for None to raise a TypeError. This is a commonly-used extension to the XML-RPC specification, but isn’t supported by all clients and servers; see http://ontosys.com/xml-rpc/extensions.php [https://web.archive.org/web/20130120074804/http://ontosys.com/xml-rpc/extensions.php] for a description. The use_builtin_types flag can be used to cause date/time values to be presented as datetime.datetime objects and binary data to be presented as bytes objects; this flag is false by default. datetime.datetime, bytes and bytearray objects may be passed to calls. The obsolete use_datetime flag is similar to use_builtin_types but it applies only to date/time values.

Both the HTTP and HTTPS transports support the URL syntax extension for HTTP Basic Authentication: http://user:pass@host:port/path. The user:pass portion will be base64-encoded as an HTTP “Authorization” header, and sent to the remote server as part of the connection process when invoking an XML-RPC method. You only need to use this if the remote server requires a Basic Authentication user and password. If an HTTPS URL is provided, context may be ssl.SSLContext and configures the SSL settings of the underlying HTTPS connection.

The returned instance is a proxy object with methods that can be used to invoke corresponding RPC calls on the remote server. If the remote server supports the introspection API, the proxy can also be used to query the remote server for the methods it supports (service discovery) and fetch other server-associated metadata.

Types that are conformable (e.g. that can be marshalled through XML), include the following (and except where noted, they are unmarshalled as the same Python type):

XML-RPC type

Type Python

boolean

bool

int, i1, i2, i4, i8 or biginteger

int in range from -2147483648 to 2147483647. Values get the <int> tag.

double or float

float. Values get the <double> tag.

string

str

array

list or tuple containing conformable elements. Arrays are returned as lists.

struct

dict. Keys must be strings, values may be any conformable type. Objects of user-defined classes can be passed in; only their __dict__ attribute is transmitted.

dateTime.iso8601

DateTime or datetime.datetime. Returned type depends on values of use_builtin_types and use_datetime flags.

base64

Binary, bytes or bytearray. Returned type depends on the value of the use_builtin_types flag.

nil

The None constant. Passing is allowed only if allow_none is true.

bigdecimal

decimal.Decimal. Returned type only.

This is the full set of data types supported by XML-RPC. Method calls may also raise a special Fault instance, used to signal XML-RPC server errors, or ProtocolError used to signal an error in the HTTP/HTTPS transport layer. Both Fault and ProtocolError derive from a base class called Error. Note that the xmlrpc client module currently does not marshal instances of subclasses of built-in types.

When passing strings, characters special to XML such as <, >, and & will be automatically escaped. However, it’s the caller’s responsibility to ensure that the string is free of characters that aren’t allowed in XML, such as the control characters with ASCII values between 0 and 31 (except, of course, tab, newline and carriage return); failing to do this will result in an XML-RPC request that isn’t well-formed XML. If you have to pass arbitrary bytes via XML-RPC, use bytes or bytearray classes or the Binary wrapper class described below.

Server is retained as an alias for ServerProxy for backwards compatibility. New code should use ServerProxy.

Modifié dans la version 3.5: Added the context argument.

Modifié dans la version 3.6: Added support of type tags with prefixes (e.g. ex:nil). Added support of unmarshalling additional types used by Apache XML-RPC implementation for numerics: i1, i2, i8, biginteger, float and bigdecimal. See http://ws.apache.org/xmlrpc/types.html for a description.

Voir aussi

XML-RPC HOWTO [http://www.tldp.org/HOWTO/XML-RPC-HOWTO/index.html]

A good description of XML-RPC operation and client software in several languages. Contains pretty much everything an XML-RPC client developer needs to know.

XML-RPC Introspection [http://xmlrpc-c.sourceforge.net/introspection.html]

Describes the XML-RPC protocol extension for introspection.

XML-RPC Specification [http://xmlrpc.scripting.com/spec.html]

The official specification.

Unofficial XML-RPC Errata [http://effbot.org/zone/xmlrpc-errata.htm]

Fredrik Lundh’s « unofficial errata, intended to clarify certain details in the XML-RPC specification, as well as hint at “best practices” to use when designing your own XML-RPC implementations. »

21.26.1. ServerProxy Objects

A ServerProxy instance has a method corresponding to each remote procedure call accepted by the XML-RPC server. Calling the method performs an RPC, dispatched by both name and argument signature (e.g. the same method name can be overloaded with multiple argument signatures). The RPC finishes by returning a value, which may be either returned data in a conformant type or a Fault or ProtocolError object indicating an error.

Servers that support the XML introspection API support some common methods grouped under the reserved system attribute:

ServerProxy.system.listMethods()

This method returns a list of strings, one for each (non-system) method supported by the XML-RPC server.

ServerProxy.system.methodSignature(name)

This method takes one parameter, the name of a method implemented by the XML-RPC server. It returns an array of possible signatures for this method. A signature is an array of types. The first of these types is the return type of the method, the rest are parameters.

Because multiple signatures (ie. overloading) is permitted, this method returns a list of signatures rather than a singleton.

Signatures themselves are restricted to the top level parameters expected by a method. For instance if a method expects one array of structs as a parameter, and it returns a string, its signature is simply « string, array ». If it expects three integers and returns a string, its signature is « string, int, int, int ».

If no signature is defined for the method, a non-array value is returned. In Python this means that the type of the returned value will be something other than list.

ServerProxy.system.methodHelp(name)

This method takes one parameter, the name of a method implemented by the XML-RPC server. It returns a documentation string describing the use of that method. If no such string is available, an empty string is returned. The documentation string may contain HTML markup.

Modifié dans la version 3.5: Instances of ServerProxy support the context manager protocol for closing the underlying transport.

A working example follows. The server code:

from xmlrpc.server import SimpleXMLRPCServer

def is_even(n):
    return n % 2 == 0

server = SimpleXMLRPCServer(("localhost", 8000))
print("Listening on port 8000...")
server.register_function(is_even, "is_even")
server.serve_forever()

The client code for the preceding server:

import xmlrpc.client

with xmlrpc.client.ServerProxy("http://localhost:8000/") as proxy:
    print("3 is even: %s" % str(proxy.is_even(3)))
    print("100 is even: %s" % str(proxy.is_even(100)))

21.26.2. Objets DateTime

class xmlrpc.client.DateTime

This class may be initialized with seconds since the epoch, a time tuple, an ISO 8601 time/date string, or a datetime.datetime instance. It has the following methods, supported mainly for internal use by the marshalling/unmarshalling code:

decode(string)

Accept a string as the instance’s new time value.

encode(out)

Write the XML-RPC encoding of this DateTime item to the out stream object.

It also supports certain of Python’s built-in operators through rich comparison and __repr__() methods.

A working example follows. The server code:

import datetime
from xmlrpc.server import SimpleXMLRPCServer
import xmlrpc.client

def today():
    today = datetime.datetime.today()
    return xmlrpc.client.DateTime(today)

server = SimpleXMLRPCServer(("localhost", 8000))
print("Listening on port 8000...")
server.register_function(today, "today")
server.serve_forever()

The client code for the preceding server:

import xmlrpc.client
import datetime

proxy = xmlrpc.client.ServerProxy("http://localhost:8000/")

today = proxy.today()
# convert the ISO8601 string to a datetime object
converted = datetime.datetime.strptime(today.value, "%Y%m%dT%H:%M:%S")
print("Today: %s" % converted.strftime("%d.%m.%Y, %H:%M"))

21.26.3. Binary Objects

class xmlrpc.client.Binary

This class may be initialized from bytes data (which may include NULs). The primary access to the content of a Binary object is provided by an attribute:

data

The binary data encapsulated by the Binary instance. The data is provided as a bytes object.

Binary objects have the following methods, supported mainly for internal use by the marshalling/unmarshalling code:

decode(bytes)

Accept a base64 bytes object and decode it as the instance’s new data.

encode(out)

Write the XML-RPC base 64 encoding of this binary item to the out stream object.

The encoded data will have newlines every 76 characters as per RFC 2045 section 6.8 [https://tools.ietf.org/html/rfc2045.html#section-6.8], which was the de facto standard base64 specification when the XML-RPC spec was written.

It also supports certain of Python’s built-in operators through __eq__() and __ne__() methods.

Example usage of the binary objects. We’re going to transfer an image over XMLRPC:

from xmlrpc.server import SimpleXMLRPCServer
import xmlrpc.client

def python_logo():
    with open("python_logo.jpg", "rb") as handle:
        return xmlrpc.client.Binary(handle.read())

server = SimpleXMLRPCServer(("localhost", 8000))
print("Listening on port 8000...")
server.register_function(python_logo, 'python_logo')

server.serve_forever()

The client gets the image and saves it to a file:

import xmlrpc.client

proxy = xmlrpc.client.ServerProxy("http://localhost:8000/")
with open("fetched_python_logo.jpg", "wb") as handle:
    handle.write(proxy.python_logo().data)

21.26.4. Fault Objects

class xmlrpc.client.Fault

A Fault object encapsulates the content of an XML-RPC fault tag. Fault objects have the following attributes:

faultCode

A string indicating the fault type.

faultString

A string containing a diagnostic message associated with the fault.

In the following example we’re going to intentionally cause a Fault by returning a complex type object. The server code:

from xmlrpc.server import SimpleXMLRPCServer

# A marshalling error is going to occur because we're returning a
# complex number
def add(x, y):
    return x+y+0j

server = SimpleXMLRPCServer(("localhost", 8000))
print("Listening on port 8000...")
server.register_function(add, 'add')

server.serve_forever()

The client code for the preceding server:

import xmlrpc.client

proxy = xmlrpc.client.ServerProxy("http://localhost:8000/")
try:
    proxy.add(2, 5)
except xmlrpc.client.Fault as err:
    print("A fault occurred")
    print("Fault code: %d" % err.faultCode)
    print("Fault string: %s" % err.faultString)

21.26.5. ProtocolError Objects

class xmlrpc.client.ProtocolError

A ProtocolError object describes a protocol error in the underlying transport layer (such as a 404 “not found” error if the server named by the URI does not exist). It has the following attributes:

url

The URI or URL that triggered the error.

errcode

The error code.

errmsg

The error message or diagnostic string.

headers

A dict containing the headers of the HTTP/HTTPS request that triggered the error.

In the following example we’re going to intentionally cause a ProtocolError by providing an invalid URI:

import xmlrpc.client

# create a ServerProxy with a URI that doesn't respond to XMLRPC requests
proxy = xmlrpc.client.ServerProxy("http://google.com/")

try:
    proxy.some_method()
except xmlrpc.client.ProtocolError as err:
    print("A protocol error occurred")
    print("URL: %s" % err.url)
    print("HTTP/HTTPS headers: %s" % err.headers)
    print("Error code: %d" % err.errcode)
    print("Error message: %s" % err.errmsg)

21.26.6. MultiCall Objects

The MultiCall object provides a way to encapsulate multiple calls to a remote server into a single request 1.

class xmlrpc.client.MultiCall(server)

Create an object used to boxcar method calls. server is the eventual target of the call. Calls can be made to the result object, but they will immediately return None, and only store the call name and parameters in the MultiCall object. Calling the object itself causes all stored calls to be transmitted as a single system.multicall request. The result of this call is a generator; iterating over this generator yields the individual results.

A usage example of this class follows. The server code:

from xmlrpc.server import SimpleXMLRPCServer

def add(x, y):
    return x + y

def subtract(x, y):
    return x - y

def multiply(x, y):
    return x * y

def divide(x, y):
    return x // y

# A simple server with simple arithmetic functions
server = SimpleXMLRPCServer(("localhost", 8000))
print("Listening on port 8000...")
server.register_multicall_functions()
server.register_function(add, 'add')
server.register_function(subtract, 'subtract')
server.register_function(multiply, 'multiply')
server.register_function(divide, 'divide')
server.serve_forever()

The client code for the preceding server:

import xmlrpc.client

proxy = xmlrpc.client.ServerProxy("http://localhost:8000/")
multicall = xmlrpc.client.MultiCall(proxy)
multicall.add(7, 3)
multicall.subtract(7, 3)
multicall.multiply(7, 3)
multicall.divide(7, 3)
result = multicall()

print("7+3=%d, 7-3=%d, 7*3=%d, 7//3=%d" % tuple(result))

21.26.7. Convenience Functions

xmlrpc.client.dumps(params, methodname=None, methodresponse=None, encoding=None, allow_none=False)

Convert params into an XML-RPC request. or into a response if methodresponse is true. params can be either a tuple of arguments or an instance of the Fault exception class. If methodresponse is true, only a single value can be returned, meaning that params must be of length 1. encoding, if supplied, is the encoding to use in the generated XML; the default is UTF-8. Python’s None value cannot be used in standard XML-RPC; to allow using it via an extension, provide a true value for allow_none.

xmlrpc.client.loads(data, use_datetime=False, use_builtin_types=False)

Convert an XML-RPC request or response into Python objects, a (params, methodname). params is a tuple of argument; methodname is a string, or None if no method name is present in the packet. If the XML-RPC packet represents a fault condition, this function will raise a Fault exception. The use_builtin_types flag can be used to cause date/time values to be presented as datetime.datetime objects and binary data to be presented as bytes objects; this flag is false by default.

The obsolete use_datetime flag is similar to use_builtin_types but it applies only to date/time values.

Modifié dans la version 3.3: The use_builtin_types flag was added.

21.26.8. Example of Client Usage

# simple test program (from the XML-RPC specification)
from xmlrpc.client import ServerProxy, Error

# server = ServerProxy("http://localhost:8000") # local server
with ServerProxy("http://betty.userland.com") as proxy:

    print(proxy)

    try:
        print(proxy.examples.getStateName(41))
    except Error as v:
        print("ERROR", v)

To access an XML-RPC server through a HTTP proxy, you need to define a custom transport. The following example shows how:

import http.client
import xmlrpc.client

class ProxiedTransport(xmlrpc.client.Transport):

    def set_proxy(self, host, port=None, headers=None):
        self.proxy = host, port
        self.proxy_headers = headers

    def make_connection(self, host):
        connection = http.client.HTTPConnection(*self.proxy)
        connection.set_tunnel(host, headers=self.proxy_headers)
        self._connection = host, connection
        return connection

transport = ProxiedTransport()
transport.set_proxy('proxy-server', 8080)
server = xmlrpc.client.ServerProxy('http://betty.userland.com', transport=transport)
print(server.examples.getStateName(41))

21.26.9. Example of Client and Server Usage

See SimpleXMLRPCServer Example.

Notes

1

This approach has been first presented in a discussion on xmlrpc.com [https://web.archive.org/web/20060624230303/http://www.xmlrpc.com/discuss/msgReader$1208?mode=topic].

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21.27. xmlrpc.server — Basic XML-RPC servers

Source code: Lib/xmlrpc/server.py [https://github.com/python/cpython/tree/3.6/Lib/xmlrpc/server.py]

The xmlrpc.server module provides a basic server framework for XML-RPC servers written in Python. Servers can either be free standing, using SimpleXMLRPCServer, or embedded in a CGI environment, using CGIXMLRPCRequestHandler.

Avertissement

The xmlrpc.server module is not secure against maliciously constructed data. If you need to parse untrusted or unauthenticated data see Vulnérabilités XML.

class xmlrpc.server.SimpleXMLRPCServer(addr, requestHandler=SimpleXMLRPCRequestHandler, logRequests=True, allow_none=False, encoding=None, bind_and_activate=True, use_builtin_types=False)

Create a new server instance. This class provides methods for registration of functions that can be called by the XML-RPC protocol. The requestHandler parameter should be a factory for request handler instances; it defaults to SimpleXMLRPCRequestHandler. The addr and requestHandler parameters are passed to the socketserver.TCPServer constructor. If logRequests is true (the default), requests will be logged; setting this parameter to false will turn off logging. The allow_none and encoding parameters are passed on to xmlrpc.client and control the XML-RPC responses that will be returned from the server. The bind_and_activate parameter controls whether server_bind() and server_activate() are called immediately by the constructor; it defaults to true. Setting it to false allows code to manipulate the allow_reuse_address class variable before the address is bound. The use_builtin_types parameter is passed to the loads() function and controls which types are processed when date/times values or binary data are received; it defaults to false.

Modifié dans la version 3.3: The use_builtin_types flag was added.

class xmlrpc.server.CGIXMLRPCRequestHandler(allow_none=False, encoding=None, use_builtin_types=False)

Create a new instance to handle XML-RPC requests in a CGI environment. The allow_none and encoding parameters are passed on to xmlrpc.client and control the XML-RPC responses that will be returned from the server. The use_builtin_types parameter is passed to the loads() function and controls which types are processed when date/times values or binary data are received; it defaults to false.

Modifié dans la version 3.3: The use_builtin_types flag was added.

class xmlrpc.server.SimpleXMLRPCRequestHandler

Create a new request handler instance. This request handler supports POST requests and modifies logging so that the logRequests parameter to the SimpleXMLRPCServer constructor parameter is honored.

21.27.1. SimpleXMLRPCServer Objects

The SimpleXMLRPCServer class is based on socketserver.TCPServer and provides a means of creating simple, stand alone XML-RPC servers.

SimpleXMLRPCServer.register_function(function, name=None)

Register a function that can respond to XML-RPC requests. If name is given, it will be the method name associated with function, otherwise function.__name__ will be used. name can be either a normal or Unicode string, and may contain characters not legal in Python identifiers, including the period character.

SimpleXMLRPCServer.register_instance(instance, allow_dotted_names=False)

Register an object which is used to expose method names which have not been registered using register_function(). If instance contains a _dispatch() method, it is called with the requested method name and the parameters from the request. Its API is def _dispatch(self, method, params) (note that params does not represent a variable argument list). If it calls an underlying function to perform its task, that function is called as func(*params), expanding the parameter list. The return value from _dispatch() is returned to the client as the result. If instance does not have a _dispatch() method, it is searched for an attribute matching the name of the requested method.

If the optional allow_dotted_names argument is true and the instance does not have a _dispatch() method, then if the requested method name contains periods, each component of the method name is searched for individually, with the effect that a simple hierarchical search is performed. The value found from this search is then called with the parameters from the request, and the return value is passed back to the client.

Avertissement

Enabling the allow_dotted_names option allows intruders to access your module’s global variables and may allow intruders to execute arbitrary code on your machine. Only use this option on a secure, closed network.

SimpleXMLRPCServer.register_introspection_functions()

Registers the XML-RPC introspection functions system.listMethods, system.methodHelp and system.methodSignature.

SimpleXMLRPCServer.register_multicall_functions()

Registers the XML-RPC multicall function system.multicall.

SimpleXMLRPCRequestHandler.rpc_paths

An attribute value that must be a tuple listing valid path portions of the URL for receiving XML-RPC requests. Requests posted to other paths will result in a 404 « no such page » HTTP error. If this tuple is empty, all paths will be considered valid. The default value is ('/', '/RPC2').

21.27.1.1. SimpleXMLRPCServer Example

Server code:

from xmlrpc.server import SimpleXMLRPCServer
from xmlrpc.server import SimpleXMLRPCRequestHandler

# Restrict to a particular path.
class RequestHandler(SimpleXMLRPCRequestHandler):
    rpc_paths = ('/RPC2',)

# Create server
with SimpleXMLRPCServer(("localhost", 8000),
                        requestHandler=RequestHandler) as server:
    server.register_introspection_functions()

    # Register pow() function; this will use the value of
    # pow.__name__ as the name, which is just 'pow'.
    server.register_function(pow)

    # Register a function under a different name
    def adder_function(x,y):
        return x + y
    server.register_function(adder_function, 'add')

    # Register an instance; all the methods of the instance are
    # published as XML-RPC methods (in this case, just 'mul').
    class MyFuncs:
        def mul(self, x, y):
            return x * y

    server.register_instance(MyFuncs())

    # Run the server's main loop
    server.serve_forever()

The following client code will call the methods made available by the preceding server:

import xmlrpc.client

s = xmlrpc.client.ServerProxy('http://localhost:8000')
print(s.pow(2,3))  # Returns 2**3 = 8
print(s.add(2,3))  # Returns 5
print(s.mul(5,2))  # Returns 5*2 = 10

# Print list of available methods
print(s.system.listMethods())

The following example included in the Lib/xmlrpc/server.py module shows a server allowing dotted names and registering a multicall function.

Avertissement

Enabling the allow_dotted_names option allows intruders to access your module’s global variables and may allow intruders to execute arbitrary code on your machine. Only use this example only within a secure, closed network.

import datetime

class ExampleService:
    def getData(self):
        return '42'

    class currentTime:
        @staticmethod
        def getCurrentTime():
            return datetime.datetime.now()

with SimpleXMLRPCServer(("localhost", 8000)) as server:
    server.register_function(pow)
    server.register_function(lambda x,y: x+y, 'add')
    server.register_instance(ExampleService(), allow_dotted_names=True)
    server.register_multicall_functions()
    print('Serving XML-RPC on localhost port 8000')
    try:
        server.serve_forever()
    except KeyboardInterrupt:
        print("\nKeyboard interrupt received, exiting.")
        sys.exit(0)

This ExampleService demo can be invoked from the command line:

python -m xmlrpc.server

The client that interacts with the above server is included in Lib/xmlrpc/client.py:

server = ServerProxy("http://localhost:8000")

try:
    print(server.currentTime.getCurrentTime())
except Error as v:
    print("ERROR", v)

multi = MultiCall(server)
multi.getData()
multi.pow(2,9)
multi.add(1,2)
try:
    for response in multi():
        print(response)
except Error as v:
    print("ERROR", v)

This client which interacts with the demo XMLRPC server can be invoked as:

python -m xmlrpc.client

21.27.2. CGIXMLRPCRequestHandler

The CGIXMLRPCRequestHandler class can be used to handle XML-RPC requests sent to Python CGI scripts.

CGIXMLRPCRequestHandler.register_function(function, name=None)

Register a function that can respond to XML-RPC requests. If name is given, it will be the method name associated with function, otherwise function.__name__ will be used. name can be either a normal or Unicode string, and may contain characters not legal in Python identifiers, including the period character.

CGIXMLRPCRequestHandler.register_instance(instance)

Register an object which is used to expose method names which have not been registered using register_function(). If instance contains a _dispatch() method, it is called with the requested method name and the parameters from the request; the return value is returned to the client as the result. If instance does not have a _dispatch() method, it is searched for an attribute matching the name of the requested method; if the requested method name contains periods, each component of the method name is searched for individually, with the effect that a simple hierarchical search is performed. The value found from this search is then called with the parameters from the request, and the return value is passed back to the client.

CGIXMLRPCRequestHandler.register_introspection_functions()

Register the XML-RPC introspection functions system.listMethods, system.methodHelp and system.methodSignature.

CGIXMLRPCRequestHandler.register_multicall_functions()

Register the XML-RPC multicall function system.multicall.

CGIXMLRPCRequestHandler.handle_request(request_text=None)

Handle an XML-RPC request. If request_text is given, it should be the POST data provided by the HTTP server, otherwise the contents of stdin will be used.

Exemple :

class MyFuncs:
    def mul(self, x, y):
        return x * y

handler = CGIXMLRPCRequestHandler()
handler.register_function(pow)
handler.register_function(lambda x,y: x+y, 'add')
handler.register_introspection_functions()
handler.register_instance(MyFuncs())
handler.handle_request()

21.27.3. Documenting XMLRPC server

These classes extend the above classes to serve HTML documentation in response to HTTP GET requests. Servers can either be free standing, using DocXMLRPCServer, or embedded in a CGI environment, using DocCGIXMLRPCRequestHandler.

class xmlrpc.server.DocXMLRPCServer(addr, requestHandler=DocXMLRPCRequestHandler, logRequests=True, allow_none=False, encoding=None, bind_and_activate=True, use_builtin_types=True)

Create a new server instance. All parameters have the same meaning as for SimpleXMLRPCServer; requestHandler defaults to DocXMLRPCRequestHandler.

Modifié dans la version 3.3: The use_builtin_types flag was added.

class xmlrpc.server.DocCGIXMLRPCRequestHandler

Create a new instance to handle XML-RPC requests in a CGI environment.

class xmlrpc.server.DocXMLRPCRequestHandler

Create a new request handler instance. This request handler supports XML-RPC POST requests, documentation GET requests, and modifies logging so that the logRequests parameter to the DocXMLRPCServer constructor parameter is honored.

21.27.4. DocXMLRPCServer Objects

The DocXMLRPCServer class is derived from SimpleXMLRPCServer and provides a means of creating self-documenting, stand alone XML-RPC servers. HTTP POST requests are handled as XML-RPC method calls. HTTP GET requests are handled by generating pydoc-style HTML documentation. This allows a server to provide its own web-based documentation.

DocXMLRPCServer.set_server_title(server_title)

Set the title used in the generated HTML documentation. This title will be used inside the HTML « title » element.

DocXMLRPCServer.set_server_name(server_name)

Set the name used in the generated HTML documentation. This name will appear at the top of the generated documentation inside a « h1 » element.

DocXMLRPCServer.set_server_documentation(server_documentation)

Set the description used in the generated HTML documentation. This description will appear as a paragraph, below the server name, in the documentation.

21.27.5. DocCGIXMLRPCRequestHandler

The DocCGIXMLRPCRequestHandler class is derived from CGIXMLRPCRequestHandler and provides a means of creating self-documenting, XML-RPC CGI scripts. HTTP POST requests are handled as XML-RPC method calls. HTTP GET requests are handled by generating pydoc-style HTML documentation. This allows a server to provide its own web-based documentation.

DocCGIXMLRPCRequestHandler.set_server_title(server_title)

Set the title used in the generated HTML documentation. This title will be used inside the HTML « title » element.

DocCGIXMLRPCRequestHandler.set_server_name(server_name)

Set the name used in the generated HTML documentation. This name will appear at the top of the generated documentation inside a « h1 » element.

DocCGIXMLRPCRequestHandler.set_server_documentation(server_documentation)

Set the description used in the generated HTML documentation. This description will appear as a paragraph, below the server name, in the documentation.

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21.28. ipaddress — IPv4/IPv6 manipulation library

Source code: Lib/ipaddress.py [https://github.com/python/cpython/tree/3.6/Lib/ipaddress.py]

ipaddress provides the capabilities to create, manipulate and operate on IPv4 and IPv6 addresses and networks.

The functions and classes in this module make it straightforward to handle various tasks related to IP addresses, including checking whether or not two hosts are on the same subnet, iterating over all hosts in a particular subnet, checking whether or not a string represents a valid IP address or network definition, and so on.

This is the full module API reference—for an overview and introduction, see Introduction au module ipaddress.

Nouveau dans la version 3.3.

21.28.1. Convenience factory functions

The ipaddress module provides factory functions to conveniently create IP addresses, networks and interfaces:

ipaddress.ip_address(address)

Return an IPv4Address or IPv6Address object depending on the IP address passed as argument. Either IPv4 or IPv6 addresses may be supplied; integers less than 2**32 will be considered to be IPv4 by default. A ValueError is raised if address does not represent a valid IPv4 or IPv6 address.

>>> ipaddress.ip_address('192.168.0.1')
IPv4Address('192.168.0.1')
>>> ipaddress.ip_address('2001:db8::')
IPv6Address('2001:db8::')

ipaddress.ip_network(address, strict=True)

Return an IPv4Network or IPv6Network object depending on the IP address passed as argument. address is a string or integer representing the IP network. Either IPv4 or IPv6 networks may be supplied; integers less than 2**32 will be considered to be IPv4 by default. strict is passed to IPv4Network or IPv6Network constructor. A ValueError is raised if address does not represent a valid IPv4 or IPv6 address, or if the network has host bits set.

>>> ipaddress.ip_network('192.168.0.0/28')
IPv4Network('192.168.0.0/28')

ipaddress.ip_interface(address)

Return an IPv4Interface or IPv6Interface object depending on the IP address passed as argument. address is a string or integer representing the IP address. Either IPv4 or IPv6 addresses may be supplied; integers less than 2**32 will be considered to be IPv4 by default. A ValueError is raised if address does not represent a valid IPv4 or IPv6 address.

One downside of these convenience functions is that the need to handle both IPv4 and IPv6 formats means that error messages provide minimal information on the precise error, as the functions don’t know whether the IPv4 or IPv6 format was intended. More detailed error reporting can be obtained by calling the appropriate version specific class constructors directly.

21.28.2. IP Addresses

21.28.2.1. Address objects

The IPv4Address and IPv6Address objects share a lot of common attributes. Some attributes that are only meaningful for IPv6 addresses are also implemented by IPv4Address objects, in order to make it easier to write code that handles both IP versions correctly. Address objects are hashable, so they can be used as keys in dictionaries.

class ipaddress.IPv4Address(address)

Construct an IPv4 address. An AddressValueError is raised if address is not a valid IPv4 address.

The following constitutes a valid IPv4 address:

A string in decimal-dot notation, consisting of four decimal integers in the inclusive range 0–255, separated by dots (e.g. 192.168.0.1). Each integer represents an octet (byte) in the address. Leading zeroes are tolerated only for values less than 8 (as there is no ambiguity between the decimal and octal interpretations of such strings).

An integer that fits into 32 bits.

An integer packed into a bytes object of length 4 (most significant octet first).

>>> ipaddress.IPv4Address('192.168.0.1')
IPv4Address('192.168.0.1')
>>> ipaddress.IPv4Address(3232235521)
IPv4Address('192.168.0.1')
>>> ipaddress.IPv4Address(b'\xC0\xA8\x00\x01')
IPv4Address('192.168.0.1')

version

The appropriate version number: 4 for IPv4, 6 for IPv6.

max_prefixlen

The total number of bits in the address representation for this version: 32 for IPv4, 128 for IPv6.

The prefix defines the number of leading bits in an address that are compared to determine whether or not an address is part of a network.

compressed

exploded

The string representation in dotted decimal notation. Leading zeroes are never included in the representation.

As IPv4 does not define a shorthand notation for addresses with octets set to zero, these two attributes are always the same as str(addr) for IPv4 addresses. Exposing these attributes makes it easier to write display code that can handle both IPv4 and IPv6 addresses.

packed

The binary representation of this address - a bytes object of the appropriate length (most significant octet first). This is 4 bytes for IPv4 and 16 bytes for IPv6.

reverse_pointer

The name of the reverse DNS PTR record for the IP address, e.g.:

>>> ipaddress.ip_address("127.0.0.1").reverse_pointer
'1.0.0.127.in-addr.arpa'
>>> ipaddress.ip_address("2001:db8::1").reverse_pointer
'1.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.8.b.d.0.1.0.0.2.ip6.arpa'

This is the name that could be used for performing a PTR lookup, not the resolved hostname itself.

Nouveau dans la version 3.5.

is_multicast

True if the address is reserved for multicast use. See RFC 3171 [https://tools.ietf.org/html/rfc3171.html] (for IPv4) or RFC 2373 [https://tools.ietf.org/html/rfc2373.html] (for IPv6).

is_private

True if the address is allocated for private networks. See iana-ipv4-special-registry [https://www.iana.org/assignments/iana-ipv4-special-registry/iana-ipv4-special-registry.xhtml] (for IPv4) or iana-ipv6-special-registry [https://www.iana.org/assignments/iana-ipv6-special-registry/iana-ipv6-special-registry.xhtml] (for IPv6).

is_global

True if the address is allocated for public networks. See iana-ipv4-special-registry [https://www.iana.org/assignments/iana-ipv4-special-registry/iana-ipv4-special-registry.xhtml] (for IPv4) or iana-ipv6-special-registry [https://www.iana.org/assignments/iana-ipv6-special-registry/iana-ipv6-special-registry.xhtml] (for IPv6).

Nouveau dans la version 3.4.

is_unspecified

True if the address is unspecified. See RFC 5735 [https://tools.ietf.org/html/rfc5735.html] (for IPv4) or RFC 2373 [https://tools.ietf.org/html/rfc2373.html] (for IPv6).

is_reserved

True if the address is otherwise IETF reserved.

is_loopback

True if this is a loopback address. See RFC 3330 [https://tools.ietf.org/html/rfc3330.html] (for IPv4) or RFC 2373 [https://tools.ietf.org/html/rfc2373.html] (for IPv6).

is_link_local

True if the address is reserved for link-local usage. See RFC 3927 [https://tools.ietf.org/html/rfc3927.html].

class ipaddress.IPv6Address(address)

Construct an IPv6 address. An AddressValueError is raised if address is not a valid IPv6 address.

The following constitutes a valid IPv6 address:

A string consisting of eight groups of four hexadecimal digits, each group representing 16 bits. The groups are separated by colons. This describes an exploded (longhand) notation. The string can also be compressed (shorthand notation) by various means. See RFC 4291 [https://tools.ietf.org/html/rfc4291.html] for details. For example, "0000:0000:0000:0000:0000:0abc:0007:0def" can be compressed to "::abc:7:def".

An integer that fits into 128 bits.

An integer packed into a bytes object of length 16, big-endian.

>>> ipaddress.IPv6Address('2001:db8::1000')
IPv6Address('2001:db8::1000')

compressed

The short form of the address representation, with leading zeroes in groups omitted and the longest sequence of groups consisting entirely of zeroes collapsed to a single empty group.

This is also the value returned by str(addr) for IPv6 addresses.

exploded

The long form of the address representation, with all leading zeroes and groups consisting entirely of zeroes included.

For the following attributes, see the corresponding documentation of the IPv4Address class:

packed

reverse_pointer

version

max_prefixlen

is_multicast

is_private

is_global

is_unspecified

is_reserved

is_loopback

is_link_local

Nouveau dans la version 3.4: is_global

is_site_local

True if the address is reserved for site-local usage. Note that the site-local address space has been deprecated by RFC 3879 [https://tools.ietf.org/html/rfc3879.html]. Use is_private to test if this address is in the space of unique local addresses as defined by RFC 4193 [https://tools.ietf.org/html/rfc4193.html].

ipv4_mapped

For addresses that appear to be IPv4 mapped addresses (starting with ::FFFF/96), this property will report the embedded IPv4 address. For any other address, this property will be None.

sixtofour

For addresses that appear to be 6to4 addresses (starting with 2002::/16) as defined by RFC 3056 [https://tools.ietf.org/html/rfc3056.html], this property will report the embedded IPv4 address. For any other address, this property will be None.

teredo

For addresses that appear to be Teredo addresses (starting with 2001::/32) as defined by RFC 4380 [https://tools.ietf.org/html/rfc4380.html], this property will report the embedded (server, client) IP address pair. For any other address, this property will be None.

21.28.2.2. Conversion to Strings and Integers

To interoperate with networking interfaces such as the socket module, addresses must be converted to strings or integers. This is handled using the str() and int() builtin functions:

>>> str(ipaddress.IPv4Address('192.168.0.1'))
'192.168.0.1'
>>> int(ipaddress.IPv4Address('192.168.0.1'))
3232235521
>>> str(ipaddress.IPv6Address('::1'))
'::1'
>>> int(ipaddress.IPv6Address('::1'))
1

21.28.2.3. Opérateurs

Address objects support some operators. Unless stated otherwise, operators can only be applied between compatible objects (i.e. IPv4 with IPv4, IPv6 with IPv6).

21.28.2.3.1. Comparison operators

Address objects can be compared with the usual set of comparison operators. Some examples:

>>> IPv4Address('127.0.0.2') > IPv4Address('127.0.0.1')
True
>>> IPv4Address('127.0.0.2') == IPv4Address('127.0.0.1')
False
>>> IPv4Address('127.0.0.2') != IPv4Address('127.0.0.1')
True

21.28.2.3.2. Arithmetic operators

Integers can be added to or subtracted from address objects. Some examples:

>>> IPv4Address('127.0.0.2') + 3
IPv4Address('127.0.0.5')
>>> IPv4Address('127.0.0.2') - 3
IPv4Address('126.255.255.255')
>>> IPv4Address('255.255.255.255') + 1
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
ipaddress.AddressValueError: 4294967296 (>= 2**32) is not permitted as an IPv4 address

21.28.3. IP Network definitions

The IPv4Network and IPv6Network objects provide a mechanism for defining and inspecting IP network definitions. A network definition consists of a mask and a network address, and as such defines a range of IP addresses that equal the network address when masked (binary AND) with the mask. For example, a network definition with the mask 255.255.255.0 and the network address 192.168.1.0 consists of IP addresses in the inclusive range 192.168.1.0 to 192.168.1.255.

21.28.3.1. Prefix, net mask and host mask

There are several equivalent ways to specify IP network masks. A prefix /<nbits> is a notation that denotes how many high-order bits are set in the network mask. A net mask is an IP address with some number of high-order bits set. Thus the prefix /24 is equivalent to the net mask 255.255.255.0 in IPv4, or ffff:ff00:: in IPv6. In addition, a host mask is the logical inverse of a net mask, and is sometimes used (for example in Cisco access control lists) to denote a network mask. The host mask equivalent to /24 in IPv4 is 0.0.0.255.

21.28.3.2. Network objects

All attributes implemented by address objects are implemented by network objects as well. In addition, network objects implement additional attributes. All of these are common between IPv4Network and IPv6Network, so to avoid duplication they are only documented for IPv4Network. Network objects are hashable, so they can be used as keys in dictionaries.

class ipaddress.IPv4Network(address, strict=True)

Construct an IPv4 network definition. address can be one of the following:

A string consisting of an IP address and an optional mask, separated by a slash (/). The IP address is the network address, and the mask can be either a single number, which means it’s a prefix, or a string representation of an IPv4 address. If it’s the latter, the mask is interpreted as a net mask if it starts with a non-zero field, or as a host mask if it starts with a zero field, with the single exception of an all-zero mask which is treated as a net mask. If no mask is provided, it’s considered to be /32.

For example, the following address specifications are equivalent: 192.168.1.0/24, 192.168.1.0/255.255.255.0 and 192.168.1.0/0.0.0.255.

An integer that fits into 32 bits. This is equivalent to a single-address network, with the network address being address and the mask being /32.

An integer packed into a bytes object of length 4, big-endian. The interpretation is similar to an integer address.

A two-tuple of an address description and a netmask, where the address description is either a string, a 32-bits integer, a 4-bytes packed integer, or an existing IPv4Address object; and the netmask is either an integer representing the prefix length (e.g. 24) or a string representing the prefix mask (e.g. 255.255.255.0).

An AddressValueError is raised if address is not a valid IPv4 address. A NetmaskValueError is raised if the mask is not valid for an IPv4 address.

If strict is True and host bits are set in the supplied address, then ValueError is raised. Otherwise, the host bits are masked out to determine the appropriate network address.

Unless stated otherwise, all network methods accepting other network/address objects will raise TypeError if the argument’s IP version is incompatible to self.

Modifié dans la version 3.5: Added the two-tuple form for the address constructor parameter.

version

max_prefixlen

Refer to the corresponding attribute documentation in IPv4Address.

is_multicast

is_private

is_unspecified

is_reserved

is_loopback

is_link_local

These attributes are true for the network as a whole if they are true for both the network address and the broadcast address.

network_address

The network address for the network. The network address and the prefix length together uniquely define a network.

broadcast_address

The broadcast address for the network. Packets sent to the broadcast address should be received by every host on the network.

hostmask

The host mask, as an IPv4Address object.

netmask

The net mask, as an IPv4Address object.

with_prefixlen

compressed

exploded

A string representation of the network, with the mask in prefix notation.

with_prefixlen and compressed are always the same as str(network). exploded uses the exploded form the network address.

with_netmask

A string representation of the network, with the mask in net mask notation.

with_hostmask

A string representation of the network, with the mask in host mask notation.

num_addresses

The total number of addresses in the network.

prefixlen

Length of the network prefix, in bits.

hosts()

Returns an iterator over the usable hosts in the network. The usable hosts are all the IP addresses that belong to the network, except the network address itself and the network broadcast address. For networks with a mask length of 31, the network address and network broadcast address are also included in the result.

>>> list(ip_network('192.0.2.0/29').hosts())
[IPv4Address('192.0.2.1'), IPv4Address('192.0.2.2'),
 IPv4Address('192.0.2.3'), IPv4Address('192.0.2.4'),
 IPv4Address('192.0.2.5'), IPv4Address('192.0.2.6')]
>>> list(ip_network('192.0.2.0/31').hosts())
[IPv4Address('192.0.2.0'), IPv4Address('192.0.2.1')]

overlaps(other)

True if this network is partly or wholly contained in other or other is wholly contained in this network.

address_exclude(network)

Computes the network definitions resulting from removing the given network from this one. Returns an iterator of network objects. Raises ValueError if network is not completely contained in this network.

>>> n1 = ip_network('192.0.2.0/28')
>>> n2 = ip_network('192.0.2.1/32')
>>> list(n1.address_exclude(n2))
[IPv4Network('192.0.2.8/29'), IPv4Network('192.0.2.4/30'),
 IPv4Network('192.0.2.2/31'), IPv4Network('192.0.2.0/32')]

subnets(prefixlen_diff=1, new_prefix=None)

The subnets that join to make the current network definition, depending on the argument values. prefixlen_diff is the amount our prefix length should be increased by. new_prefix is the desired new prefix of the subnets; it must be larger than our prefix. One and only one of prefixlen_diff and new_prefix must be set. Returns an iterator of network objects.

>>> list(ip_network('192.0.2.0/24').subnets())
[IPv4Network('192.0.2.0/25'), IPv4Network('192.0.2.128/25')]
>>> list(ip_network('192.0.2.0/24').subnets(prefixlen_diff=2))
[IPv4Network('192.0.2.0/26'), IPv4Network('192.0.2.64/26'),
 IPv4Network('192.0.2.128/26'), IPv4Network('192.0.2.192/26')]
>>> list(ip_network('192.0.2.0/24').subnets(new_prefix=26))
[IPv4Network('192.0.2.0/26'), IPv4Network('192.0.2.64/26'),
 IPv4Network('192.0.2.128/26'), IPv4Network('192.0.2.192/26')]
>>> list(ip_network('192.0.2.0/24').subnets(new_prefix=23))
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
    raise ValueError('new prefix must be longer')
ValueError: new prefix must be longer
>>> list(ip_network('192.0.2.0/24').subnets(new_prefix=25))
[IPv4Network('192.0.2.0/25'), IPv4Network('192.0.2.128/25')]

supernet(prefixlen_diff=1, new_prefix=None)

The supernet containing this network definition, depending on the argument values. prefixlen_diff is the amount our prefix length should be decreased by. new_prefix is the desired new prefix of the supernet; it must be smaller than our prefix. One and only one of prefixlen_diff and new_prefix must be set. Returns a single network object.

>>> ip_network('192.0.2.0/24').supernet()
IPv4Network('192.0.2.0/23')
>>> ip_network('192.0.2.0/24').supernet(prefixlen_diff=2)
IPv4Network('192.0.0.0/22')
>>> ip_network('192.0.2.0/24').supernet(new_prefix=20)
IPv4Network('192.0.0.0/20')

compare_networks(other)

Compare this network to other. In this comparison only the network addresses are considered; host bits aren’t. Returns either -1, 0 or 1.

>>> ip_network('192.0.2.1/32').compare_networks(ip_network('192.0.2.2/32'))
-1
>>> ip_network('192.0.2.1/32').compare_networks(ip_network('192.0.2.0/32'))
1
>>> ip_network('192.0.2.1/32').compare_networks(ip_network('192.0.2.1/32'))
0

class ipaddress.IPv6Network(address, strict=True)

Construct an IPv6 network definition. address can be one of the following:

A string consisting of an IP address and an optional prefix length, separated by a slash (/). The IP address is the network address, and the prefix length must be a single number, the prefix. If no prefix length is provided, it’s considered to be /128.

Note that currently expanded netmasks are not supported. That means 2001:db00::0/24 is a valid argument while 2001:db00::0/ffff:ff00:: not.

An integer that fits into 128 bits. This is equivalent to a single-address network, with the network address being address and the mask being /128.

An integer packed into a bytes object of length 16, big-endian. The interpretation is similar to an integer address.

A two-tuple of an address description and a netmask, where the address description is either a string, a 128-bits integer, a 16-bytes packed integer, or an existing IPv6Address object; and the netmask is an integer representing the prefix length.

An AddressValueError is raised if address is not a valid IPv6 address. A NetmaskValueError is raised if the mask is not valid for an IPv6 address.

If strict is True and host bits are set in the supplied address, then ValueError is raised. Otherwise, the host bits are masked out to determine the appropriate network address.

Modifié dans la version 3.5: Added the two-tuple form for the address constructor parameter.

version

max_prefixlen

is_multicast

is_private

is_unspecified

is_reserved

is_loopback

is_link_local

network_address

broadcast_address

hostmask

netmask

with_prefixlen

compressed

exploded

with_netmask

with_hostmask

num_addresses

prefixlen

hosts()

Returns an iterator over the usable hosts in the network. The usable hosts are all the IP addresses that belong to the network, except the Subnet-Router anycast address. For networks with a mask length of 127, the Subnet-Router anycast address is also included in the result.

overlaps(other)

address_exclude(network)

subnets(prefixlen_diff=1, new_prefix=None)

supernet(prefixlen_diff=1, new_prefix=None)

compare_networks(other)

Refer to the corresponding attribute documentation in IPv4Network.

is_site_local

These attribute is true for the network as a whole if it is true for both the network address and the broadcast address.

21.28.3.3. Opérateurs

Network objects support some operators. Unless stated otherwise, operators can only be applied between compatible objects (i.e. IPv4 with IPv4, IPv6 with IPv6).

21.28.3.3.1. Logical operators

Network objects can be compared with the usual set of logical operators. Network objects are ordered first by network address, then by net mask.

21.28.3.3.2. Itération

Network objects can be iterated to list all the addresses belonging to the network. For iteration, all hosts are returned, including unusable hosts (for usable hosts, use the hosts() method). An example:

>>> for addr in IPv4Network('192.0.2.0/28'):
...     addr
...
IPv4Address('192.0.2.0')
IPv4Address('192.0.2.1')
IPv4Address('192.0.2.2')
IPv4Address('192.0.2.3')
IPv4Address('192.0.2.4')
IPv4Address('192.0.2.5')
IPv4Address('192.0.2.6')
IPv4Address('192.0.2.7')
IPv4Address('192.0.2.8')
IPv4Address('192.0.2.9')
IPv4Address('192.0.2.10')
IPv4Address('192.0.2.11')
IPv4Address('192.0.2.12')
IPv4Address('192.0.2.13')
IPv4Address('192.0.2.14')
IPv4Address('192.0.2.15')

21.28.3.3.3. Networks as containers of addresses

Network objects can act as containers of addresses. Some examples:

>>> IPv4Network('192.0.2.0/28')[0]
IPv4Address('192.0.2.0')
>>> IPv4Network('192.0.2.0/28')[15]
IPv4Address('192.0.2.15')
>>> IPv4Address('192.0.2.6') in IPv4Network('192.0.2.0/28')
True
>>> IPv4Address('192.0.3.6') in IPv4Network('192.0.2.0/28')
False

21.28.4. Interface objects

Interface objects are hashable, so they can be used as keys in dictionaries.

class ipaddress.IPv4Interface(address)

Construct an IPv4 interface. The meaning of address is as in the constructor of IPv4Network, except that arbitrary host addresses are always accepted.

IPv4Interface is a subclass of IPv4Address, so it inherits all the attributes from that class. In addition, the following attributes are available:

ip

The address (IPv4Address) without network information.

>>> interface = IPv4Interface('192.0.2.5/24')
>>> interface.ip
IPv4Address('192.0.2.5')

network

The network (IPv4Network) this interface belongs to.

>>> interface = IPv4Interface('192.0.2.5/24')
>>> interface.network
IPv4Network('192.0.2.0/24')

with_prefixlen

A string representation of the interface with the mask in prefix notation.

>>> interface = IPv4Interface('192.0.2.5/24')
>>> interface.with_prefixlen
'192.0.2.5/24'

with_netmask

A string representation of the interface with the network as a net mask.

>>> interface = IPv4Interface('192.0.2.5/24')
>>> interface.with_netmask
'192.0.2.5/255.255.255.0'

with_hostmask

A string representation of the interface with the network as a host mask.

>>> interface = IPv4Interface('192.0.2.5/24')
>>> interface.with_hostmask
'192.0.2.5/0.0.0.255'

class ipaddress.IPv6Interface(address)

Construct an IPv6 interface. The meaning of address is as in the constructor of IPv6Network, except that arbitrary host addresses are always accepted.

IPv6Interface is a subclass of IPv6Address, so it inherits all the attributes from that class. In addition, the following attributes are available:

ip

network

with_prefixlen

with_netmask

with_hostmask

Refer to the corresponding attribute documentation in IPv4Interface.

21.28.4.1. Opérateurs

Interface objects support some operators. Unless stated otherwise, operators can only be applied between compatible objects (i.e. IPv4 with IPv4, IPv6 with IPv6).

21.28.4.1.1. Logical operators

Interface objects can be compared with the usual set of logical operators.

For equality comparison (== and !=), both the IP address and network must be the same for the objects to be equal. An interface will not compare equal to any address or network object.

For ordering (<, >, etc) the rules are different. Interface and address objects with the same IP version can be compared, and the address objects will always sort before the interface objects. Two interface objects are first compared by their networks and, if those are the same, then by their IP addresses.

21.28.5. Other Module Level Functions

The module also provides the following module level functions:

ipaddress.v4_int_to_packed(address)

Represent an address as 4 packed bytes in network (big-endian) order. address is an integer representation of an IPv4 IP address. A ValueError is raised if the integer is negative or too large to be an IPv4 IP address.

>>> ipaddress.ip_address(3221225985)
IPv4Address('192.0.2.1')
>>> ipaddress.v4_int_to_packed(3221225985)
b'\xc0\x00\x02\x01'

ipaddress.v6_int_to_packed(address)

Represent an address as 16 packed bytes in network (big-endian) order. address is an integer representation of an IPv6 IP address. A ValueError is raised if the integer is negative or too large to be an IPv6 IP address.

ipaddress.summarize_address_range(first, last)

Return an iterator of the summarized network range given the first and last IP addresses. first is the first IPv4Address or IPv6Address in the range and last is the last IPv4Address or IPv6Address in the range. A TypeError is raised if first or last are not IP addresses or are not of the same version. A ValueError is raised if last is not greater than first or if first address version is not 4 or 6.

>>> [ipaddr for ipaddr in ipaddress.summarize_address_range(
...    ipaddress.IPv4Address('192.0.2.0'),
...    ipaddress.IPv4Address('192.0.2.130'))]
[IPv4Network('192.0.2.0/25'), IPv4Network('192.0.2.128/31'), IPv4Network('192.0.2.130/32')]

ipaddress.collapse_addresses(addresses)

Return an iterator of the collapsed IPv4Network or IPv6Network objects. addresses is an iterator of IPv4Network or IPv6Network objects. A TypeError is raised if addresses contains mixed version objects.

>>> [ipaddr for ipaddr in
... ipaddress.collapse_addresses([ipaddress.IPv4Network('192.0.2.0/25'),
... ipaddress.IPv4Network('192.0.2.128/25')])]
[IPv4Network('192.0.2.0/24')]

ipaddress.get_mixed_type_key(obj)

Return a key suitable for sorting between networks and addresses. Address and Network objects are not sortable by default; they’re fundamentally different, so the expression:

IPv4Address('192.0.2.0') <= IPv4Network('192.0.2.0/24')

doesn’t make sense. There are some times however, where you may wish to have ipaddress sort these anyway. If you need to do this, you can use this function as the key argument to sorted().

obj is either a network or address object.

21.28.6. Custom Exceptions

To support more specific error reporting from class constructors, the module defines the following exceptions:

exception ipaddress.AddressValueError(ValueError)

Any value error related to the address.

exception ipaddress.NetmaskValueError(ValueError)

Any value error related to the net mask.

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22. Services multimédia

Les modules documentés dans ce chapitre implémentent divers algorithmes ou interfaces principalement utiles pour les applications multimédia. Ils peuvent ne pas être disponibles sur votre installation. En voici un aperçu :

22.1. audioloop — Manipulation de données audio brutes

22.2. aifc — Lis et écrit dans les fichiers AIFF et AIFC

22.3. sunau — Read and write Sun AU files

22.3.1. AU_read Objects

22.3.2. AU_write Objects

22.4. wave — Lecture et écriture des fichiers WAV

22.4.1. Objets Wave_read

22.4.2. Objets Wave_write

22.5. chunk — Read IFF chunked data

22.6. colorsys — Conversions entre les systèmes de couleurs

22.7. imghdr — Determine the type of an image

22.8. sndhdr — Détermine le type d’un fichier audio

22.9. ossaudiodev — Access to OSS-compatible audio devices

22.9.1. Audio Device Objects

22.9.2. Mixer Device Objects

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22.1. audioloop — Manipulation de données audio brutes

The audioop module contains some useful operations on sound fragments. It operates on sound fragments consisting of signed integer samples 8, 16, 24 or 32 bits wide, stored in bytes-like objects. All scalar items are integers, unless specified otherwise.

Modifié dans la version 3.4: Support for 24-bit samples was added. All functions now accept any bytes-like object. String input now results in an immediate error.

This module provides support for a-LAW, u-LAW and Intel/DVI ADPCM encodings.

A few of the more complicated operations only take 16-bit samples, otherwise the sample size (in bytes) is always a parameter of the operation.

The module defines the following variables and functions:

exception audioop.error

This exception is raised on all errors, such as unknown number of bytes per sample, etc.

audioop.add(fragment1, fragment2, width)

Return a fragment which is the addition of the two samples passed as parameters. width is the sample width in bytes, either 1, 2, 3 or 4. Both fragments should have the same length. Samples are truncated in case of overflow.

audioop.adpcm2lin(adpcmfragment, width, state)

Decode an Intel/DVI ADPCM coded fragment to a linear fragment. See the description of lin2adpcm() for details on ADPCM coding. Return a tuple (sample, newstate) where the sample has the width specified in width.

audioop.alaw2lin(fragment, width)

Convert sound fragments in a-LAW encoding to linearly encoded sound fragments. a-LAW encoding always uses 8 bits samples, so width refers only to the sample width of the output fragment here.

audioop.avg(fragment, width)

Return the average over all samples in the fragment.

audioop.avgpp(fragment, width)

Return the average peak-peak value over all samples in the fragment. No filtering is done, so the usefulness of this routine is questionable.

audioop.bias(fragment, width, bias)

Return a fragment that is the original fragment with a bias added to each sample. Samples wrap around in case of overflow.

audioop.byteswap(fragment, width)

« Byteswap » all samples in a fragment and returns the modified fragment. Converts big-endian samples to little-endian and vice versa.

Nouveau dans la version 3.4.

audioop.cross(fragment, width)

Return the number of zero crossings in the fragment passed as an argument.

audioop.findfactor(fragment, reference)

Return a factor F such that rms(add(fragment, mul(reference, -F))) is minimal, i.e., return the factor with which you should multiply reference to make it match as well as possible to fragment. The fragments should both contain 2-byte samples.

The time taken by this routine is proportional to len(fragment).

audioop.findfit(fragment, reference)

Try to match reference as well as possible to a portion of fragment (which should be the longer fragment). This is (conceptually) done by taking slices out of fragment, using findfactor() to compute the best match, and minimizing the result. The fragments should both contain 2-byte samples. Return a tuple (offset, factor) where offset is the (integer) offset into fragment where the optimal match started and factor is the (floating-point) factor as per findfactor().

audioop.findmax(fragment, length)

Search fragment for a slice of length length samples (not bytes!) with maximum energy, i.e., return i for which rms(fragment[i*2:(i+length)*2]) is maximal. The fragments should both contain 2-byte samples.

The routine takes time proportional to len(fragment).

audioop.getsample(fragment, width, index)

Return the value of sample index from the fragment.

audioop.lin2adpcm(fragment, width, state)

Convert samples to 4 bit Intel/DVI ADPCM encoding. ADPCM coding is an adaptive coding scheme, whereby each 4 bit number is the difference between one sample and the next, divided by a (varying) step. The Intel/DVI ADPCM algorithm has been selected for use by the IMA, so it may well become a standard.

state is a tuple containing the state of the coder. The coder returns a tuple (adpcmfrag, newstate), and the newstate should be passed to the next call of lin2adpcm(). In the initial call, None can be passed as the state. adpcmfrag is the ADPCM coded fragment packed 2 4-bit values per byte.

audioop.lin2alaw(fragment, width)

Convert samples in the audio fragment to a-LAW encoding and return this as a bytes object. a-LAW is an audio encoding format whereby you get a dynamic range of about 13 bits using only 8 bit samples. It is used by the Sun audio hardware, among others.

audioop.lin2lin(fragment, width, newwidth)

Convert samples between 1-, 2-, 3- and 4-byte formats.

Note

In some audio formats, such as .WAV files, 16, 24 and 32 bit samples are signed, but 8 bit samples are unsigned. So when converting to 8 bit wide samples for these formats, you need to also add 128 to the result:

new_frames = audioop.lin2lin(frames, old_width, 1)
new_frames = audioop.bias(new_frames, 1, 128)

The same, in reverse, has to be applied when converting from 8 to 16, 24 or 32 bit width samples.

audioop.lin2ulaw(fragment, width)

Convert samples in the audio fragment to u-LAW encoding and return this as a bytes object. u-LAW is an audio encoding format whereby you get a dynamic range of about 14 bits using only 8 bit samples. It is used by the Sun audio hardware, among others.

audioop.max(fragment, width)

Return the maximum of the absolute value of all samples in a fragment.

audioop.maxpp(fragment, width)

Return the maximum peak-peak value in the sound fragment.

audioop.minmax(fragment, width)

Return a tuple consisting of the minimum and maximum values of all samples in the sound fragment.

audioop.mul(fragment, width, factor)

Return a fragment that has all samples in the original fragment multiplied by the floating-point value factor. Samples are truncated in case of overflow.

audioop.ratecv(fragment, width, nchannels, inrate, outrate, state[, weightA[, weightB]])

Convert the frame rate of the input fragment.

state is a tuple containing the state of the converter. The converter returns a tuple (newfragment, newstate), and newstate should be passed to the next call of ratecv(). The initial call should pass None as the state.

The weightA and weightB arguments are parameters for a simple digital filter and default to 1 and 0 respectively.

audioop.reverse(fragment, width)

Reverse the samples in a fragment and returns the modified fragment.

audioop.rms(fragment, width)

Return the root-mean-square of the fragment, i.e. sqrt(sum(S_i^2)/n).

C’est une mesure de la puissance dans un signal audio.

audioop.tomono(fragment, width, lfactor, rfactor)

Convert a stereo fragment to a mono fragment. The left channel is multiplied by lfactor and the right channel by rfactor before adding the two channels to give a mono signal.

audioop.tostereo(fragment, width, lfactor, rfactor)

Generate a stereo fragment from a mono fragment. Each pair of samples in the stereo fragment are computed from the mono sample, whereby left channel samples are multiplied by lfactor and right channel samples by rfactor.

audioop.ulaw2lin(fragment, width)

Convert sound fragments in u-LAW encoding to linearly encoded sound fragments. u-LAW encoding always uses 8 bits samples, so width refers only to the sample width of the output fragment here.

Note that operations such as mul() or max() make no distinction between mono and stereo fragments, i.e. all samples are treated equal. If this is a problem the stereo fragment should be split into two mono fragments first and recombined later. Here is an example of how to do that:

def mul_stereo(sample, width, lfactor, rfactor):
    lsample = audioop.tomono(sample, width, 1, 0)
    rsample = audioop.tomono(sample, width, 0, 1)
    lsample = audioop.mul(lsample, width, lfactor)
    rsample = audioop.mul(rsample, width, rfactor)
    lsample = audioop.tostereo(lsample, width, 1, 0)
    rsample = audioop.tostereo(rsample, width, 0, 1)
    return audioop.add(lsample, rsample, width)

If you use the ADPCM coder to build network packets and you want your protocol to be stateless (i.e. to be able to tolerate packet loss) you should not only transmit the data but also the state. Note that you should send the initial state (the one you passed to lin2adpcm()) along to the decoder, not the final state (as returned by the coder). If you want to use struct.Struct to store the state in binary you can code the first element (the predicted value) in 16 bits and the second (the delta index) in 8.

The ADPCM coders have never been tried against other ADPCM coders, only against themselves. It could well be that I misinterpreted the standards in which case they will not be interoperable with the respective standards.

The find*() routines might look a bit funny at first sight. They are primarily meant to do echo cancellation. A reasonably fast way to do this is to pick the most energetic piece of the output sample, locate that in the input sample and subtract the whole output sample from the input sample:

def echocancel(outputdata, inputdata):
    pos = audioop.findmax(outputdata, 800)    # one tenth second
    out_test = outputdata[pos*2:]
    in_test = inputdata[pos*2:]
    ipos, factor = audioop.findfit(in_test, out_test)
    # Optional (for better cancellation):
    # factor = audioop.findfactor(in_test[ipos*2:ipos*2+len(out_test)],
    #              out_test)
    prefill = '\0'*(pos+ipos)*2
    postfill = '\0'*(len(inputdata)-len(prefill)-len(outputdata))
    outputdata = prefill + audioop.mul(outputdata, 2, -factor) + postfill
    return audioop.add(inputdata, outputdata, 2)

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22.2. aifc — Lis et écrit dans les fichiers AIFF et AIFC

Code source: Lib/aifc.py [https://github.com/python/cpython/tree/3.6/Lib/aifc.py]

This module provides support for reading and writing AIFF and AIFF-C files. AIFF is Audio Interchange File Format, a format for storing digital audio samples in a file. AIFF-C is a newer version of the format that includes the ability to compress the audio data.

Audio files have a number of parameters that describe the audio data. The sampling rate or frame rate is the number of times per second the sound is sampled. The number of channels indicate if the audio is mono, stereo, or quadro. Each frame consists of one sample per channel. The sample size is the size in bytes of each sample. Thus a frame consists of nchannels * samplesize bytes, and a second’s worth of audio consists of nchannels * samplesize * framerate bytes.

For example, CD quality audio has a sample size of two bytes (16 bits), uses two channels (stereo) and has a frame rate of 44,100 frames/second. This gives a frame size of 4 bytes (2*2), and a second’s worth occupies 2*2*44100 bytes (176,400 bytes).

Le module aifc définit les fonctions suivantes :

aifc.open(file, mode=None)

Open an AIFF or AIFF-C file and return an object instance with methods that are described below. The argument file is either a string naming a file or a file object. mode must be 'r' or 'rb' when the file must be opened for reading, or 'w' or 'wb' when the file must be opened for writing. If omitted, file.mode is used if it exists, otherwise 'rb' is used. When used for writing, the file object should be seekable, unless you know ahead of time how many samples you are going to write in total and use writeframesraw() and setnframes(). The open() function may be used in a with statement. When the with block completes, the close() method is called.

Modifié dans la version 3.4: La prise en charge de l’instruction with a été ajoutée.

Objects returned by open() when a file is opened for reading have the following methods:

aifc.getnchannels()

Return the number of audio channels (1 for mono, 2 for stereo).

aifc.getsampwidth()

Donne la taille en octets des échantillons, individuellement.

aifc.getframerate()

Return the sampling rate (number of audio frames per second).

aifc.getnframes()

Donne le nombre de trames (frames) audio du fichier.

aifc.getcomptype()

Return a bytes array of length 4 describing the type of compression used in the audio file. For AIFF files, the returned value is b'NONE'.

aifc.getcompname()

Return a bytes array convertible to a human-readable description of the type of compression used in the audio file. For AIFF files, the returned value is b'not compressed'.

aifc.getparams()

Renvoie une namedtuple() (nchannels, sampwidth, framerate, nframes, comptype, compname), équivalent à la sortie des méthodes get*().

aifc.getmarkers()

Return a list of markers in the audio file. A marker consists of a tuple of three elements. The first is the mark ID (an integer), the second is the mark position in frames from the beginning of the data (an integer), the third is the name of the mark (a string).

aifc.getmark(id)

Return the tuple as described in getmarkers() for the mark with the given id.

aifc.readframes(nframes)

Read and return the next nframes frames from the audio file. The returned data is a string containing for each frame the uncompressed samples of all channels.

aifc.rewind()

Rewind the read pointer. The next readframes() will start from the beginning.

aifc.setpos(pos)

Va à la trame de numéro donné.

aifc.tell()

Donne le numéro de la trame courante.

aifc.close()

Close the AIFF file. After calling this method, the object can no longer be used.

Objects returned by open() when a file is opened for writing have all the above methods, except for readframes() and setpos(). In addition the following methods exist. The get*() methods can only be called after the corresponding set*() methods have been called. Before the first writeframes() or writeframesraw(), all parameters except for the number of frames must be filled in.

aifc.aiff()

Create an AIFF file. The default is that an AIFF-C file is created, unless the name of the file ends in '.aiff' in which case the default is an AIFF file.

aifc.aifc()

Create an AIFF-C file. The default is that an AIFF-C file is created, unless the name of the file ends in '.aiff' in which case the default is an AIFF file.

aifc.setnchannels(nchannels)

Définit le nombre de canaux du fichier audio.

aifc.setsampwidth(width)

Définit la taille en octets des échantillons audio.

aifc.setframerate(rate)

Specify the sampling frequency in frames per second.

aifc.setnframes(nframes)

Specify the number of frames that are to be written to the audio file. If this parameter is not set, or not set correctly, the file needs to support seeking.

aifc.setcomptype(type, name)

Specify the compression type. If not specified, the audio data will not be compressed. In AIFF files, compression is not possible. The name parameter should be a human-readable description of the compression type as a bytes array, the type parameter should be a bytes array of length 4. Currently the following compression types are supported: b'NONE', b'ULAW', b'ALAW', b'G722'.

aifc.setparams(nchannels, sampwidth, framerate, comptype, compname)

Set all the above parameters at once. The argument is a tuple consisting of the various parameters. This means that it is possible to use the result of a getparams() call as argument to setparams().

aifc.setmark(id, pos, name)

Add a mark with the given id (larger than 0), and the given name at the given position. This method can be called at any time before close().

aifc.tell()

Return the current write position in the output file. Useful in combination with setmark().

aifc.writeframes(data)

Write data to the output file. This method can only be called after the audio file parameters have been set.

Modifié dans la version 3.4: N’importe quel bytes-like object est maintenant accepté.

aifc.writeframesraw(data)

Like writeframes(), except that the header of the audio file is not updated.

Modifié dans la version 3.4: N’importe quel bytes-like object est maintenant accepté.

aifc.close()

Close the AIFF file. The header of the file is updated to reflect the actual size of the audio data. After calling this method, the object can no longer be used.

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22.3. sunau — Read and write Sun AU files

Code source : Lib/sunau.py [https://github.com/python/cpython/tree/3.6/Lib/sunau.py]

The sunau module provides a convenient interface to the Sun AU sound format. Note that this module is interface-compatible with the modules aifc and wave.

An audio file consists of a header followed by the data. The fields of the header are:

Field

Sommaire

magic word

The four bytes .snd.

header size

Size of the header, including info, in bytes.

data size

Physical size of the data, in bytes.

encoding

Indicates how the audio samples are encoded.

sample rate

The sampling rate.

# of channels

The number of channels in the samples.

info

ASCII string giving a description of the audio file (padded with null bytes).

Apart from the info field, all header fields are 4 bytes in size. They are all 32-bit unsigned integers encoded in big-endian byte order.

The sunau module defines the following functions:

sunau.open(file, mode)

If file is a string, open the file by that name, otherwise treat it as a seekable file-like object. mode can be any of

'r'

Mode lecture seule.

'w'

Mode écriture seule.

Note that it does not allow read/write files.

A mode of 'r' returns an AU_read object, while a mode of 'w' or 'wb' returns an AU_write object.

sunau.openfp(file, mode)

Un synonyme de open(), maintenu pour la rétrocompatibilité.

The sunau module defines the following exception:

exception sunau.Error

An error raised when something is impossible because of Sun AU specs or implementation deficiency.

The sunau module defines the following data items:

sunau.AUDIO_FILE_MAGIC

An integer every valid Sun AU file begins with, stored in big-endian form. This is the string .snd interpreted as an integer.

sunau.AUDIO_FILE_ENCODING_MULAW_8

sunau.AUDIO_FILE_ENCODING_LINEAR_8

sunau.AUDIO_FILE_ENCODING_LINEAR_16

sunau.AUDIO_FILE_ENCODING_LINEAR_24

sunau.AUDIO_FILE_ENCODING_LINEAR_32

sunau.AUDIO_FILE_ENCODING_ALAW_8

Values of the encoding field from the AU header which are supported by this module.

sunau.AUDIO_FILE_ENCODING_FLOAT

sunau.AUDIO_FILE_ENCODING_DOUBLE

sunau.AUDIO_FILE_ENCODING_ADPCM_G721

sunau.AUDIO_FILE_ENCODING_ADPCM_G722

sunau.AUDIO_FILE_ENCODING_ADPCM_G723_3

sunau.AUDIO_FILE_ENCODING_ADPCM_G723_5

Additional known values of the encoding field from the AU header, but which are not supported by this module.

22.3.1. AU_read Objects

AU_read objects, as returned by open() above, have the following methods:

AU_read.close()

Close the stream, and make the instance unusable. (This is called automatically on deletion.)

AU_read.getnchannels()

Returns number of audio channels (1 for mono, 2 for stereo).

AU_read.getsampwidth()

Renvoie la largeur de l’échantillon en octets.

AU_read.getframerate()

Renvoie la fréquence d’échantillonnage.

AU_read.getnframes()

Renvoie le nombre de trames audio.

AU_read.getcomptype()

Returns compression type. Supported compression types are 'ULAW', 'ALAW' and 'NONE'.

AU_read.getcompname()

Human-readable version of getcomptype(). The supported types have the respective names 'CCITT G.711 u-law', 'CCITT G.711 A-law' and 'not compressed'.

AU_read.getparams()

Renvoie une namedtuple() (nchannels, sampwidth, framerate, nframes, comptype, compname), équivalent à la sortie des méthodes get*().

AU_read.readframes(n)

Reads and returns at most n frames of audio, as a bytes object. The data will be returned in linear format. If the original data is in u-LAW format, it will be converted.

AU_read.rewind()

Remet le pointeur de fichier au début du flux audio.

Les deux fonctions suivantes utilisent le vocabulaire « position ». Ces positions sont compatible entre elles, la « position » de l’un est compatible avec la « position » de l’autre. Cette position est dépendante de l’implémentation.

AU_read.setpos(pos)

Set the file pointer to the specified position. Only values returned from tell() should be used for pos.

AU_read.tell()

Return current file pointer position. Note that the returned value has nothing to do with the actual position in the file.

The following two functions are defined for compatibility with the aifc, and don’t do anything interesting.

AU_read.getmarkers()

Renvoie None.

AU_read.getmark(id)

Lève une erreur.

22.3.2. AU_write Objects

AU_write objects, as returned by open() above, have the following methods:

AU_write.setnchannels(n)

Définit le nombre de canaux.

AU_write.setsampwidth(n)

Set the sample width (in bytes.)

Modifié dans la version 3.4: Added support for 24-bit samples.

AU_write.setframerate(n)

Set the frame rate.

AU_write.setnframes(n)

Set the number of frames. This can be later changed, when and if more frames are written.

AU_write.setcomptype(type, name)

Set the compression type and description. Only 'NONE' and 'ULAW' are supported on output.

AU_write.setparams(tuple)

The tuple should be (nchannels, sampwidth, framerate, nframes, comptype, compname), with values valid for the set*() methods. Set all parameters.

AU_write.tell()

Return current position in the file, with the same disclaimer for the AU_read.tell() and AU_read.setpos() methods.

AU_write.writeframesraw(data)

Écrit les trames audio sans corriger nframes.

Modifié dans la version 3.4: N’importe quel bytes-like object est maintenant accepté.

AU_write.writeframes(data)

Write audio frames and make sure nframes is correct.

Modifié dans la version 3.4: N’importe quel bytes-like object est maintenant accepté.

AU_write.close()

Make sure nframes is correct, and close the file.

This method is called upon deletion.

Note that it is invalid to set any parameters after calling writeframes() or writeframesraw().

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22.4. wave — Lecture et écriture des fichiers WAV

Code source : Lib/wave.py [https://github.com/python/cpython/tree/3.6/Lib/wave.py]

Le module wave fournit une interface pratique pour le format de son WAV. Il ne gère pas la compression ni la décompression, mais gère le mono et le stéréo.

Le module wave définit la fonction et l’exception suivante :

wave.open(file, mode=None)

Si file est une chaîne de caractères, ouvre le fichier sous ce nom, sinon, il est traité comme un objet de type fichier. mode peut être :

'rb'

Mode lecture seule.

'wb'

Mode écriture seule.

Notez que ce module ne permet pas de manipuler des fichiers WAV en lecture/écriture.

Un mode 'rb' renvoie un objet Wave_read, alors qu’un mode 'wb' renvoie un objet Wave_write. Si mode est omis et qu’un objet de type fichier est donné au paramètre file, file.mode est utilisé comme valeur par défaut pour mode.

Si vous donnez un objet de type fichier, l’objet wave ne le ferme pas lorsque sa méthode close() est appelée car c’est l’appelant qui est responsable de la fermeture.

The open() function may be used in a with statement. When the with block completes, the Wave_read.close() or Wave_write.close() method is called.

Modifié dans la version 3.4: Ajout de la gestion des fichiers non navigables.

wave.openfp(file, mode)

Un synonyme de open(), maintenu pour la rétrocompatibilité.

exception wave.Error

Une erreur est levée lorsque quelque chose est impossible car elle enfreint la spécification WAV ou rencontre un problème d’implémentation.

22.4.1. Objets Wave_read

Les objets Wave_read, tels qu’ils sont renvoyés par open(), ont les méthodes suivantes :

Wave_read.close()

Ferme le flux s’il a été ouvert par wave et rend l’instance inutilisable. Ceci est appelé automatiquement lorsque l’objet est détruit .

Wave_read.getnchannels()

Renvoie le nombre de canaux audio (1 pour mono, 2 pour stéréo).

Wave_read.getsampwidth()

Renvoie la largeur de l’échantillon en octets.

Wave_read.getframerate()

Renvoie la fréquence d’échantillonnage.

Wave_read.getnframes()

Renvoie le nombre de trames audio.

Wave_read.getcomptype()

Renvoie le type de compression ('NONE' est le seul type géré).

Wave_read.getcompname()

Version compréhensible de getcomptype(). Généralement, 'not compressed' équivaut à 'NONE'.

Wave_read.getparams()

Renvoie une namedtuple() (nchannels, sampwidth, framerate, nframes, comptype, compname), équivalent à la sortie des méthodes get*().

Wave_read.readframes(n)

Lit et renvoie au plus n trames audio, sous forme d’objet bytes.

Wave_read.rewind()

Remet le pointeur de fichier au début du flux audio.

Les deux méthodes suivantes sont définies pour la compatibilité avec le module aifc ; elles ne font rien d’intéressant.

Wave_read.getmarkers()

Renvoie None.

Wave_read.getmark(id)

Lève une erreur.

Les deux fonctions suivantes utilisent le vocabulaire « position ». Ces positions sont compatible entre elles, la « position » de l’un est compatible avec la « position » de l’autre. Cette position est dépendante de l’implémentation.

Wave_read.setpos(pos)

Place le pointeur du fichier sur la position spécifiée.

Wave_read.tell()

Renvoie la position actuelle du pointeur du fichier.

22.4.2. Objets Wave_write

Pour les flux de sortie navigables, l’en-tête wave est automatiquement mis à jour pour refléter le nombre de trames réellement écrites. Pour les flux non indexables, la valeur nframes doit être précise lorsque la première trame est écrite. Une valeur précise de nframes peut être obtenue en appelant les méthodes setnframes() ou setparams() en passant en paramètre le nombre de trames qui seront écrites avant que close() soit appelé puis en utilisant la méthode writeframesraw() pour écrire les trames audio, ou en appelant la méthode writeframes() avec toutes les trames audio. Dans ce dernier cas, la méthode writeframes() calcule le nombre de trames dans le flux audio et définit nframes en conséquence avant d’écrire les données des trames.

Les objets Wave_write, tels qu’ils sont renvoyés par open(), ont les méthodes suivantes :

Modifié dans la version 3.4: Ajout de la gestion des fichiers non navigables.

Wave_write.close()

Assurez-vous que nframes soit correct et fermez le fichier s’il a été ouvert par wave. Cette méthode est appelée à la destruction de l’objet. Il lève une erreur si le flux de sortie n’est pas navigable et si nframes ne correspond pas au nombre de trames réellement écrites.

Wave_write.setnchannels(n)

Définit le nombre de canaux.

Wave_write.setsampwidth(n)

Définit la largeur de l’échantillon à n octets.

Wave_write.setframerate(n)

Définit la fréquence des trames à n.

Modifié dans la version 3.2: Un paramètre non-entier passé à cette méthode est arrondi à l’entier le plus proche.

Wave_write.setnframes(n)

Définit le nombre de trames à n. Cela sera modifié ultérieurement si le nombre de trames réellement écrites est différent (la tentative de mise à jour générera une erreur si le flux de sortie n’est pas indexable).

Wave_write.setcomptype(type, name)

Définit le type de compression et la description. Pour le moment, seul le type de compression NONE est géré, c’est-à-dire aucune compression.

Wave_write.setparams(tuple)

Le tuple doit être (nchannels, sampwidth, framerate, nframes, comptype, compname), avec des valeurs valides pour les méthodes set*(). Tous les paramètres sont obligatoires et doivent être définis.

Wave_write.tell()

Renvoie la position actuelle dans le fichier, avec les mêmes réserves que pour les méthodes Wave_read.tell() et Wave_read.setpos().

Wave_write.writeframesraw(data)

Écrit les trames audio sans corriger nframes.

Modifié dans la version 3.4: N’importe quel bytes-like object est maintenant accepté.

Wave_write.writeframes(data)

Écrit des trames audio et s’assure que nframes est correct. Une erreur est levée si le flux de sortie est non-navigable et si le nombre total de trames écrites après que data soit écrit ne correspond pas à la valeur précédemment définie pour nframes.

Modifié dans la version 3.4: N’importe quel bytes-like object est maintenant accepté.

Notez qu’il est impossible de définir des paramètres après avoir appelé writeframes() ou writeframesraw(), et toute tentative en ce sens lève une wave.Error.

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22.5. chunk — Read IFF chunked data

Source code: Lib/chunk.py [https://github.com/python/cpython/tree/3.6/Lib/chunk.py]

This module provides an interface for reading files that use EA IFF 85 chunks. 1 This format is used in at least the Audio Interchange File Format (AIFF/AIFF-C) and the Real Media File Format (RMFF). The WAVE audio file format is closely related and can also be read using this module.

A chunk has the following structure:

Offset

Length

Sommaire

0

4

Chunk ID

4

4

Size of chunk in big-endian byte order, not including the header

8

n

Data bytes, where n is the size given in the preceding field

8 + n

0 or 1

Pad byte needed if n is odd and chunk alignment is used

The ID is a 4-byte string which identifies the type of chunk.

The size field (a 32-bit value, encoded using big-endian byte order) gives the size of the chunk data, not including the 8-byte header.

Usually an IFF-type file consists of one or more chunks. The proposed usage of the Chunk class defined here is to instantiate an instance at the start of each chunk and read from the instance until it reaches the end, after which a new instance can be instantiated. At the end of the file, creating a new instance will fail with an EOFError exception.

class chunk.Chunk(file, align=True, bigendian=True, inclheader=False)

Class which represents a chunk. The file argument is expected to be a file-like object. An instance of this class is specifically allowed. The only method that is needed is read(). If the methods seek() and tell() are present and don’t raise an exception, they are also used. If these methods are present and raise an exception, they are expected to not have altered the object. If the optional argument align is true, chunks are assumed to be aligned on 2-byte boundaries. If align is false, no alignment is assumed. The default value is true. If the optional argument bigendian is false, the chunk size is assumed to be in little-endian order. This is needed for WAVE audio files. The default value is true. If the optional argument inclheader is true, the size given in the chunk header includes the size of the header. The default value is false.

A Chunk object supports the following methods:

getname()

Returns the name (ID) of the chunk. This is the first 4 bytes of the chunk.

getsize()

Returns the size of the chunk.

close()

Close and skip to the end of the chunk. This does not close the underlying file.

The remaining methods will raise OSError if called after the close() method has been called. Before Python 3.3, they used to raise IOError, now an alias of OSError.

isatty()

Returns False.

seek(pos, whence=0)

Set the chunk’s current position. The whence argument is optional and defaults to 0 (absolute file positioning); other values are 1 (seek relative to the current position) and 2 (seek relative to the file’s end). There is no return value. If the underlying file does not allow seek, only forward seeks are allowed.

tell()

Return the current position into the chunk.

read(size=-1)

Read at most size bytes from the chunk (less if the read hits the end of the chunk before obtaining size bytes). If the size argument is negative or omitted, read all data until the end of the chunk. An empty bytes object is returned when the end of the chunk is encountered immediately.

skip()

Skip to the end of the chunk. All further calls to read() for the chunk will return b''. If you are not interested in the contents of the chunk, this method should be called so that the file points to the start of the next chunk.

Notes

1

« EA IFF 85 » Standard for Interchange Format Files, Jerry Morrison, Electronic Arts, January 1985.

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22.6. colorsys — Conversions entre les systèmes de couleurs

Code source : Lib/colorsys.py [https://github.com/python/cpython/tree/3.6/Lib/colorsys.py]

Le module colorsys définit les conversions bidirectionnelles des valeurs de couleur entre les couleurs exprimées dans l’espace colorimétrique RVB (Rouge Vert Bleu) utilisé par les écrans d’ordinateur et trois autres systèmes de coordonnées : YIQ, HLS (Hue Lightness Saturation) et HSV (Hue Saturation Value). Les coordonnées dans tous ces espaces colorimétriques sont des valeurs en virgule flottante. Dans l’espace YIQ, la coordonnée Y est comprise entre 0 et 1, mais les coordonnées I et Q peuvent être positives ou négatives. Dans tous les autres espaces, les coordonnées sont toutes comprises entre 0 et 1.

Voir aussi

Consultez http://www.poynton.com/ColorFAQ.html et https://www.cambridgeincolour.com/tutorials/color-spaces.htm pour plus d’informations concernant les espaces colorimétrique.

Le module colorsys définit les fonctions suivantes :

colorsys.rgb_to_yiq(r, g, b)

Convertit la couleur des coordonnées RGB (RVB) vers les coordonnées YIQ.

colorsys.yiq_to_rgb(y, i, q)

Convertit la couleur des coordonnées YIQ vers les coordonnées RGB (RVB).

colorsys.rgb_to_hls(r, g, b)

Convertit la couleur des coordonnées RGB (RVB) vers les coordonnées HLS (TSV).

colorsys.hls_to_rgb(h, l, s)

Convertit la couleur des coordonnées HLS (TSV) vers les coordonnées RGB (RVB).

colorsys.rgb_to_hsv(r, g, b)

Convertit la couleur des coordonnées RGB (RVB) vers les coordonnées HSV (TSV).

colorsys.hsv_to_rgb(h, s, v)

Convertit la couleur des coordonnées HSV (TSV) vers les coordonnées RGB (RVB).

Exemple :

>>> import colorsys
>>> colorsys.rgb_to_hsv(0.2, 0.4, 0.4)
(0.5, 0.5, 0.4)
>>> colorsys.hsv_to_rgb(0.5, 0.5, 0.4)
(0.2, 0.4, 0.4)

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22.7. imghdr — Determine the type of an image

Code source : Lib/imghdr.py [https://github.com/python/cpython/tree/3.6/Lib/imghdr.py]

The imghdr module determines the type of image contained in a file or byte stream.

The imghdr module defines the following function:

imghdr.what(filename, h=None)

Tests the image data contained in the file named by filename, and returns a string describing the image type. If optional h is provided, the filename is ignored and h is assumed to contain the byte stream to test.

Modifié dans la version 3.6: Accepte un path-like object.

The following image types are recognized, as listed below with the return value from what():

Valeur

Image format

'rgb'

SGI ImgLib Files

'gif'

GIF 87a and 89a Files

'pbm'

Portable Bitmap Files

'pgm'

Portable Graymap Files

'ppm'

Portable Pixmap Files

'tiff'

TIFF Files

'rast'

Sun Raster Files

'xbm'

X Bitmap Files

'jpeg'

JPEG data in JFIF or Exif formats

'bmp'

BMP files

'png'

Portable Network Graphics

'webp'

WebP files

'exr'

OpenEXR Files

Nouveau dans la version 3.5: The exr and webp formats were added.

You can extend the list of file types imghdr can recognize by appending to this variable:

imghdr.tests

A list of functions performing the individual tests. Each function takes two arguments: the byte-stream and an open file-like object. When what() is called with a byte-stream, the file-like object will be None.

The test function should return a string describing the image type if the test succeeded, or None if it failed.

Exemple :

>>> import imghdr
>>> imghdr.what('bass.gif')
'gif'

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22.8. sndhdr — Détermine le type d’un fichier audio

Code source : Lib/sndhdr.py [https://github.com/python/cpython/tree/3.6/Lib/sndhdr.py]

Le module sndhdr fournit des fonctions permettant d’essayer de déterminer le type de données audio contenues dans un fichier. Lorsque ces fonctions parviennent à déterminer le format de données, elles renvoient un namedtuple(), contenant cinq attributs : (filetype, framerate, nchannels, nframes, sampwidth). La valeur de type indique le format de données parmi 'aifc', 'aiff', 'au', 'hcom', 'sndr', 'sndt', 'voc', 'wav', '8svx', 'sb', 'ub', et 'ul'. La valeur de sampling_rate sera soit la vraie valeur, soit, si elle est inconnue ou compliquée à obtenir, 0. De même, channels vaut soit le nombre de canaux soit 0 s’il ne peut pas être déterminé ou si la valeur est compliquée à décoder. La valeur de frames sera soit le nombre de frames soit -1. Le dernier élément du tuple, bits_per_sample sera soit la taille d’un échantillon en bits, soit 'A' pour A-LAW ou 'U' pour u-LAW.

sndhdr.what(filename)

Détermine le type de données audio stockée dans le fichier filename en utilisant whathdr(). Si elle y parvient, le namedtuple décrit plus haut est renvoyé, sinon, None.

Modifié dans la version 3.5: Le type renvoyé passe d’un tuple à un namedtuple.

sndhdr.whathdr(filename)

Détermine le type de données audio contenue dans un fichier, en se basant sur ses entêtes. Le nom du fichier est donné par filename. Cette fonction renvoie un namedtuple tel que décrit plus haut, si elle y parvient, sinon None.

Modifié dans la version 3.5: Le type renvoyé passe d’un tuple à un namedtuple.

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22.9. ossaudiodev — Access to OSS-compatible audio devices

This module allows you to access the OSS (Open Sound System) audio interface. OSS is available for a wide range of open-source and commercial Unices, and is the standard audio interface for Linux and recent versions of FreeBSD.

Modifié dans la version 3.3: Operations in this module now raise OSError where IOError was raised.

Voir aussi

Open Sound System Programmer’s Guide [http://www.opensound.com/pguide/oss.pdf]

the official documentation for the OSS C API

The module defines a large number of constants supplied by the OSS device driver; see <sys/soundcard.h> on either Linux or FreeBSD for a listing.

ossaudiodev defines the following variables and functions:

exception ossaudiodev.OSSAudioError

This exception is raised on certain errors. The argument is a string describing what went wrong.

(If ossaudiodev receives an error from a system call such as open(), write(), or ioctl(), it raises OSError. Errors detected directly by ossaudiodev result in OSSAudioError.)

(For backwards compatibility, the exception class is also available as ossaudiodev.error.)

ossaudiodev.open(mode)

ossaudiodev.open(device, mode)

Open an audio device and return an OSS audio device object. This object supports many file-like methods, such as read(), write(), and fileno() (although there are subtle differences between conventional Unix read/write semantics and those of OSS audio devices). It also supports a number of audio-specific methods; see below for the complete list of methods.

device is the audio device filename to use. If it is not specified, this module first looks in the environment variable AUDIODEV for a device to use. If not found, it falls back to /dev/dsp.

mode is one of 'r' for read-only (record) access, 'w' for write-only (playback) access and 'rw' for both. Since many sound cards only allow one process to have the recorder or player open at a time, it is a good idea to open the device only for the activity needed. Further, some sound cards are half-duplex: they can be opened for reading or writing, but not both at once.

Note the unusual calling syntax: the first argument is optional, and the second is required. This is a historical artifact for compatibility with the older linuxaudiodev module which ossaudiodev supersedes.

ossaudiodev.openmixer([device])

Open a mixer device and return an OSS mixer device object. device is the mixer device filename to use. If it is not specified, this module first looks in the environment variable MIXERDEV for a device to use. If not found, it falls back to /dev/mixer.

22.9.1. Audio Device Objects

Before you can write to or read from an audio device, you must call three methods in the correct order:

setfmt() to set the output format

channels() to set the number of channels

speed() to set the sample rate

Alternately, you can use the setparameters() method to set all three audio parameters at once. This is more convenient, but may not be as flexible in all cases.

The audio device objects returned by open() define the following methods and (read-only) attributes:

oss_audio_device.close()

Explicitly close the audio device. When you are done writing to or reading from an audio device, you should explicitly close it. A closed device cannot be used again.

oss_audio_device.fileno()

Return the file descriptor associated with the device.

oss_audio_device.read(size)

Read size bytes from the audio input and return them as a Python string. Unlike most Unix device drivers, OSS audio devices in blocking mode (the default) will block read() until the entire requested amount of data is available.

oss_audio_device.write(data)

Write a bytes-like object data to the audio device and return the number of bytes written. If the audio device is in blocking mode (the default), the entire data is always written (again, this is different from usual Unix device semantics). If the device is in non-blocking mode, some data may not be written—see writeall().

Modifié dans la version 3.5: N’importe quel bytes-like object est maintenant accepté.

oss_audio_device.writeall(data)

Write a bytes-like object data to the audio device: waits until the audio device is able to accept data, writes as much data as it will accept, and repeats until data has been completely written. If the device is in blocking mode (the default), this has the same effect as write(); writeall() is only useful in non-blocking mode. Has no return value, since the amount of data written is always equal to the amount of data supplied.

Modifié dans la version 3.5: N’importe quel bytes-like object est maintenant accepté.

Modifié dans la version 3.2: Audio device objects also support the context management protocol, i.e. they can be used in a with statement.

The following methods each map to exactly one ioctl() system call. The correspondence is obvious: for example, setfmt() corresponds to the SNDCTL_DSP_SETFMT ioctl, and sync() to SNDCTL_DSP_SYNC (this can be useful when consulting the OSS documentation). If the underlying ioctl() fails, they all raise OSError.

oss_audio_device.nonblock()

Put the device into non-blocking mode. Once in non-blocking mode, there is no way to return it to blocking mode.

oss_audio_device.getfmts()

Return a bitmask of the audio output formats supported by the soundcard. Some of the formats supported by OSS are:

Format

Description

AFMT_MU_LAW

a logarithmic encoding (used by Sun .au files and /dev/audio)

AFMT_A_LAW

a logarithmic encoding

AFMT_IMA_ADPCM

a 4:1 compressed format defined by the Interactive Multimedia Association

AFMT_U8

Unsigned, 8-bit audio

AFMT_S16_LE

Signed, 16-bit audio, little-endian byte order (as used by Intel processors)

AFMT_S16_BE

Signed, 16-bit audio, big-endian byte order (as used by 68k, PowerPC, Sparc)

AFMT_S8

Signed, 8 bit audio

AFMT_U16_LE

Unsigned, 16-bit little-endian audio

AFMT_U16_BE

Unsigned, 16-bit big-endian audio

Consult the OSS documentation for a full list of audio formats, and note that most devices support only a subset of these formats. Some older devices only support AFMT_U8; the most common format used today is AFMT_S16_LE.

oss_audio_device.setfmt(format)

Try to set the current audio format to format—see getfmts() for a list. Returns the audio format that the device was set to, which may not be the requested format. May also be used to return the current audio format—do this by passing an « audio format » of AFMT_QUERY.

oss_audio_device.channels(nchannels)

Set the number of output channels to nchannels. A value of 1 indicates monophonic sound, 2 stereophonic. Some devices may have more than 2 channels, and some high-end devices may not support mono. Returns the number of channels the device was set to.

oss_audio_device.speed(samplerate)

Try to set the audio sampling rate to samplerate samples per second. Returns the rate actually set. Most sound devices don’t support arbitrary sampling rates. Common rates are:

Rate

Description

8000

default rate for /dev/audio

11025

speech recording

22050

44100

CD quality audio (at 16 bits/sample and 2 channels)

96000

DVD quality audio (at 24 bits/sample)

oss_audio_device.sync()

Wait until the sound device has played every byte in its buffer. (This happens implicitly when the device is closed.) The OSS documentation recommends closing and re-opening the device rather than using sync().

oss_audio_device.reset()

Immediately stop playing or recording and return the device to a state where it can accept commands. The OSS documentation recommends closing and re-opening the device after calling reset().

oss_audio_device.post()

Tell the driver that there is likely to be a pause in the output, making it possible for the device to handle the pause more intelligently. You might use this after playing a spot sound effect, before waiting for user input, or before doing disk I/O.

The following convenience methods combine several ioctls, or one ioctl and some simple calculations.

oss_audio_device.setparameters(format, nchannels, samplerate[, strict=False])

Set the key audio sampling parameters—sample format, number of channels, and sampling rate—in one method call. format, nchannels, and samplerate should be as specified in the setfmt(), channels(), and speed() methods. If strict is true, setparameters() checks to see if each parameter was actually set to the requested value, and raises OSSAudioError if not. Returns a tuple (format, nchannels, samplerate) indicating the parameter values that were actually set by the device driver (i.e., the same as the return values of setfmt(), channels(), and speed()).

For example,

(fmt, channels, rate) = dsp.setparameters(fmt, channels, rate)

is equivalent to

fmt = dsp.setfmt(fmt)
channels = dsp.channels(channels)
rate = dsp.rate(rate)

oss_audio_device.bufsize()

Returns the size of the hardware buffer, in samples.

oss_audio_device.obufcount()

Returns the number of samples that are in the hardware buffer yet to be played.

oss_audio_device.obuffree()

Returns the number of samples that could be queued into the hardware buffer to be played without blocking.

Audio device objects also support several read-only attributes:

oss_audio_device.closed

Boolean indicating whether the device has been closed.

oss_audio_device.name

String containing the name of the device file.

oss_audio_device.mode

The I/O mode for the file, either "r", "rw", or "w".

22.9.2. Mixer Device Objects

The mixer object provides two file-like methods:

oss_mixer_device.close()

This method closes the open mixer device file. Any further attempts to use the mixer after this file is closed will raise an OSError.

oss_mixer_device.fileno()

Returns the file handle number of the open mixer device file.

Modifié dans la version 3.2: Mixer objects also support the context management protocol.

The remaining methods are specific to audio mixing:

oss_mixer_device.controls()

This method returns a bitmask specifying the available mixer controls (« Control » being a specific mixable « channel », such as SOUND_MIXER_PCM or SOUND_MIXER_SYNTH). This bitmask indicates a subset of all available mixer controls—the SOUND_MIXER_* constants defined at module level. To determine if, for example, the current mixer object supports a PCM mixer, use the following Python code:

mixer=ossaudiodev.openmixer()
if mixer.controls() & (1 << ossaudiodev.SOUND_MIXER_PCM):
    # PCM is supported
    ... code ...

For most purposes, the SOUND_MIXER_VOLUME (master volume) and SOUND_MIXER_PCM controls should suffice—but code that uses the mixer should be flexible when it comes to choosing mixer controls. On the Gravis Ultrasound, for example, SOUND_MIXER_VOLUME does not exist.

oss_mixer_device.stereocontrols()

Returns a bitmask indicating stereo mixer controls. If a bit is set, the corresponding control is stereo; if it is unset, the control is either monophonic or not supported by the mixer (use in combination with controls() to determine which).

See the code example for the controls() function for an example of getting data from a bitmask.

oss_mixer_device.reccontrols()

Returns a bitmask specifying the mixer controls that may be used to record. See the code example for controls() for an example of reading from a bitmask.

oss_mixer_device.get(control)

Returns the volume of a given mixer control. The returned volume is a 2-tuple (left_volume,right_volume). Volumes are specified as numbers from 0 (silent) to 100 (full volume). If the control is monophonic, a 2-tuple is still returned, but both volumes are the same.

Raises OSSAudioError if an invalid control is specified, or OSError if an unsupported control is specified.

oss_mixer_device.set(control, (left, right))

Sets the volume for a given mixer control to (left,right). left and right must be ints and between 0 (silent) and 100 (full volume). On success, the new volume is returned as a 2-tuple. Note that this may not be exactly the same as the volume specified, because of the limited resolution of some soundcard’s mixers.

Raises OSSAudioError if an invalid mixer control was specified, or if the specified volumes were out-of-range.

oss_mixer_device.get_recsrc()

This method returns a bitmask indicating which control(s) are currently being used as a recording source.

oss_mixer_device.set_recsrc(bitmask)

Call this function to specify a recording source. Returns a bitmask indicating the new recording source (or sources) if successful; raises OSError if an invalid source was specified. To set the current recording source to the microphone input:

mixer.setrecsrc (1 << ossaudiodev.SOUND_MIXER_MIC)

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23. Internationalisation

Les modules décrits dans ce chapitre vous aident à rédiger des programmes indépendants des langues et des cultures en fournissant des mécanismes pour sélectionner une langue à utiliser dans les messages, ou en adaptant la sortie aux conventions culturelles.

La liste des modules documentés dans ce chapitre est :

23.1. gettext — Services d’internationalisation multilingue

23.1.1. API GNU gettext

23.1.2. API basée sur les classes

23.1.2.1. La classe NullTranslations

23.1.2.2. La classe GNUTranslations

23.1.2.3. Support du catalogue de message de Solaris

23.1.2.4. Le constructeur Catalog

23.1.3. Internationaliser vos programmes et modules

23.1.3.1. Localiser votre module

23.1.3.2. Localiser votre application

23.1.3.3. Changer de langue à la volée

23.1.3.4. Traductions différées

23.1.4. Remerciements

23.2. locale — Services d’internationalisation

23.2.1. Contexte, détails, conseils, astuces et mises en garde

23.2.2. Pour les auteurs d’extensions et les programmes qui intègrent Python

23.2.3. Accéder aux catalogues de messages

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23.1. gettext — Services d’internationalisation multilingue

Code source : Lib/gettext.py [https://github.com/python/cpython/tree/3.6/Lib/gettext.py]

Le module gettext fournit un service d’internationalisation (I18N) et de localisation linguistique (L10N) pour vos modules et applications Python. Il est compatible avec l’API du catalogue de messages GNU gettext et à un plus haut niveau, avec l’API basée sur les classes qui serait peut-être plus adaptée aux fichiers Python. L’interface décrite ci-dessous vous permet d’écrire les textes de vos modules et applications dans une langue naturelle, puis de fournir un catalogue de traductions pour les lancer ensuite dans d’autres langues naturelles.

Quelques astuces sur la localisation de vos modules et applications Python sont également données.

23.1.1. API GNU gettext

Le module gettext définit l’API suivante, qui est très proche de l’API de GNU gettext. Si vous utilisez cette API, cela affectera la traduction de toute votre application. C’est souvent le comportement attendu si votre application est monolingue, avec le choix de la langue qui dépend des paramètres linguistiques de l’utilisateur. Si vous localisez un module Python ou si votre application a besoin de changer de langue à la volée, il est plus judicieux d’utiliser l’API basée sur des classes.

gettext.bindtextdomain(domain, localedir=None)

Lie domain au répertoire localedir des localisations. Plus spécifiquement, gettext va chercher les fichiers binaires .mo pour un domaine donné, en utilisant le chemin suivant (sous Unix) : localedir/language/LC_MESSAGES/domain.mo, où language est contenu respectivement dans l’une des variables d’environnement suivantes : LANGUAGE, LC_ALL, LC_MESSAGES et LANG.

Si localedir n’est pas renseigné ou vaut None, alors le lien actuel de domain est renvoyé. 1

gettext.bind_textdomain_codeset(domain, codeset=None)

Lie domain à codeset, en changeant l’encodage des chaînes d’octets retournées par les fonctions lgettext(), ldgettext(), lngettext() et ldngettext(). Si codeset n’est pas renseigné, alors le lien actuel est renvoyé.

gettext.textdomain(domain=None)

Change ou interroge le domaine global actuel. Si domain vaut None, alors le domaine global actuel est renvoyé. Sinon, le domaine global est positionné à domain, puis renvoyé.

gettext.gettext(message)

Renvoie la traduction localisée de message, en se basant sur le domaine global actuel, la langue et le répertoire des localisations. Cette fonction est typiquement renommée _() dans le namespace courant (voir les exemples ci-dessous).

gettext.dgettext(domain, message)

Comme gettext(), mais cherche le message dans le domaine spécifié.

gettext.ngettext(singular, plural, n)

Comme gettext(), mais prend en compte les formes au pluriel. Si une traduction a été trouvée, utilise la formule pour trouver le pluriel à n et renvoie le message généré (quelques langues ont plus de deux formes au pluriel). Si aucune traduction n’a été trouvée, renvoie singular si n vaut 1, plural sinon.

La formule pour trouver le pluriel est récupérée dans l’entête du catalogue. C’est une expression en C ou en Python qui a une variable libre n et qui évalue l’index du pluriel dans le catalogue. Voir la documentation de GNU gettext [https://www.gnu.org/software/gettext/manual/gettext.html] pour la syntaxe précise à utiliser dans les fichiers .po et pour les formules dans différents langues.

gettext.dngettext(domain, singular, plural, n)

Comme ngettext(), mais cherche le message dans le domaine spécifié.

gettext.lgettext(message)

gettext.ldgettext(domain, message)

gettext.lngettext(singular, plural, n)

gettext.ldngettext(domain, singular, plural, n)

Équivalent aux fonctions correspondantes non préfixées par l (gettext(), dgettext(), ngettext() et dngettext()), mais la traduction est retournée en tant que chaîne d’octets, encodée avec l’encodage du système si aucun autre n’a été explicitement défini avec bind_textdomain_codeset().

Avertissement

Ces fonctions sont à éviter en Python 3 car elles renvoient des octets encodés. Il est préférable d’utiliser des alternatives qui renvoient de l’Unicode, puisque beaucoup d’applications Python voudront manipuler du texte lisible par des humains plutôt que des octets. En outre, il est possible que vous obteniez des exceptions non prévues liées à Unicode s’il y a des soucis d’encodage avec les chaînes de caractères traduites. Il est d’ailleurs probable que les fonctions l*() deviennent obsolètes dans les versions futures de Python à cause de leurs problèmes et limitations inhérents.

Notez que GNU gettext a aussi une méthode dcgettext(), mais elle a été considérée comme inutile et donc actuellement marquée comme non implémentée.

Voici un exemple classique d’utilisation de cette API :

import gettext
gettext.bindtextdomain('myapplication', '/path/to/my/language/directory')
gettext.textdomain('myapplication')
_ = gettext.gettext
# ...
print(_('This is a translatable string.'))

23.1.2. API basée sur les classes

L’API du module gettext basée sur les classes vous donne plus de flexibilité et est plus pratique que l’API de GNU gettext. Son utilisation est recommandée pour localiser vos applications et modules Python. gettext définit une classe « translations » qui analyse syntaxiquement les fichiers au format GNU .mo, et qui possède des méthodes pour renvoyer des chaînes de caractères. Les instances de cette classe « translations » peuvent également s’installer dans l’espace de noms natif en tant que fonction _().

gettext.find(domain, localedir=None, languages=None, all=False)

Cette fonction implémente l’algorithme standard de recherche de fichier mo. Il prend en entrée un domain, tout comme la fonction textdomain(). Le paramètre optionnel localedir est le même que celui de bindtextdomain(). Le paramètre optionnel langages est une liste de chaînes de caractères correspondants au code d’une langue.

Si localedir n’est pas renseigné, alors le répertoire de la locale par défaut du système est utilisé. 2 Si languages n’est pas renseigné, alors les variables d’environnement suivantes sont utilisées : LANGUAGE, LC_ALL, LC_MESSAGES et LANG. La première à renvoyer une valeur non vide est alors utilisée pour languages. Ces variables d’environnement doivent contenir une liste de langues, séparées par des deux-points, qui sera utilisée pour générer la liste des codes de langues attendue.

Recherche avec find(), découvre et normalise les langues, puis itère sur la liste obtenue afin de trouver un fichier de traduction existant et correspondant :

localedir/language/LC_MESSAGES/domain.mo

Le premier nom de fichier trouvé est renvoyé par find(). Si aucun fichier n’a été trouvé, alors None est renvoyé. Si all est vrai, est renvoyée la liste de tous les noms de fichiers, dans l’ordre dans lequel ils apparaissent dans languages ou dans les variables d’environnement.

gettext.translation(domain, localedir=None, languages=None, class_=None, fallback=False, codeset=None)

Renvoie une instance de la classe Translations en se basant sur domain, localedir et languages, qui sont d’abord passés en argument de find() afin d’obtenir une liste de chemin des fichiers .mo associés. Les instances avec des noms de fichiers .mo identiques sont mises en cache. La classe réellement instanciée est soit class_ si renseigné, soit une classe GNUTranslations. Le constructeur de cette classe doit prendre en argument un seul file object. Si renseigné, codeset modifiera le jeu de caractères utilisé pour encoder les chaînes de caractères traduites, dans les méthodes lgettext() et lngettext().

Si plusieurs fichiers ont été trouvés, les derniers sont utilisés comme substitut des premiers. Pour rendre possible cette substitution, copy.copy() est utilisé pour copier chaque objet traduit depuis le cache ; les vraies données de l’instance étant toujours recopiées dans le cache.

Si aucun fichier .mo n’a été trouvé, soit fallback vaut False (valeur par défaut) et une exception OSError est levée, soit fallback vaut True et une instance NullTranslations est renvoyée.

Modifié dans la version 3.3: Avant, c’était l’exception IOError qui était levée, au lieu de OSError.

gettext.install(domain, localedir=None, codeset=None, names=None)

Positionne la fonction _() dans l’espace de nommage natif de Python, en se basant sur domain, localedir et codeset, qui sont passés en argument de la fonction translation().

Concernant le paramètre names, se référer à la description de la méthode install().

Habituellement, la fonction _() est appliquée aux chaînes de caractères qui doivent être traduites comme suit :

print(_('This string will be translated.'))

Pour plus de confort, il vaut mieux positionner la fonction _() dans l’espace de nommage natif de Python pour la rendre plus accessible dans tous les modules de votre application.

23.1.2.1. La classe NullTranslations

Les classes de traduction implémentent le fait de passer d’une chaîne de caractères du fichier original à traduire à la traduction de celle-ci. La classe de base utilisée est NullTranslations. C’est l’interface de base à utiliser lorsque vous souhaitez écrire vos propres classes spécifiques à la traduction. Voici les méthodes de NullTranslations :

class gettext.NullTranslations(fp=None)

Prend un paramètre optionnel un file object fp, qui est ignoré par la classe de base. Initialise les variables d’instance « protégées » _info et _chardet, définies par des classes dérivées, tout comme _fallback qui est définie au travers de add_fallback(). Puis appelle self._parse(fp) si fp ne vaut pas None.

_parse(fp)

Cette méthode, non exécutée dans la classe de base, prend en paramètre un objet fichier fp et lit les données de ce dernier. Si vous avez un catalogue de messages dont le format n’est pas pris en charge, vous devriez surcharger cette méthode pour analyser votre format.

add_fallback(fallback)

Ajoute fallback comme objet de substitution pour l’objet de traduction courant. Un objet de traduction devrait interroger cet objet de substitution s’il ne peut fournir une traduction pour un message donné.

gettext(message)

Si un objet de substitution a été défini, transmet gettext() à celui-ci. Sinon, renvoie message. Surchargé dans les classes dérivées.

ngettext(singular, plural, n)

Si un objet de substitution a été défini, transmet ngettext() à celui-ci. Sinon, renvoie singular si n vaut 1, plural sinon. Surchargé dans les classes dérivées.

lgettext(message)

lngettext(singular, plural, n)

Équivalent de gettext() et ngettext(), mais la traduction est renvoyée sous la forme d’une chaîne d’octets, encodée avec l’encodage du système si aucun autre n’a été défini avec set_output_charset(). Surchargé dans les classes dérivées.

Avertissement

L’utilisation de ces méthodes doivent être évitée en Python 3. Voir l’avertissement de la fonction lgettext().

info()

Renvoie la variable « protégée » _info.

charset()

Renvoie l’encodage du fichier du catalogue de messages.

output_charset()

Renvoie l’encodage utilisé par lgettext() et lngettext() pour la traduction des messages.

set_output_charset(charset)

Modifie l’encodage utilisé pour la traduction des messages.

install(names=None)

Cette méthode positionne gettext() dans l’espace de nommage natif, en le liant à _.

Si le paramètre names est renseigné, celui-ci doit être une séquence contenant les noms des fonctions que vous souhaitez positionner dans l’espace de nommage natif, en plus de _(). Les noms pris en charge sont 'gettext', 'ngettext', 'lgettext' et 'lngettext'.

Notez que ce n’est là qu’un moyen parmi d’autres, quoique le plus pratique, pour rendre la fonction _() accessible à votre application. Puisque cela affecte toute l’application, et plus particulièrement l’espace de nommage natif, les modules localisés ne devraient jamais y positionner _(). Au lieu de cela, ces derniers doivent plutôt utiliser le code suivant pour rendre _() accessible par leurs modules :

import gettext
t = gettext.translation('mymodule', ...)
_ = t.gettext

Cela met _() dans l’espace de nommage global du module uniquement et donc n’affectera ses appels que dans ce module.

23.1.2.2. La classe GNUTranslations

Le module gettext fournit une classe supplémentaire qui hérite de NullTranslations : GNUTranslations. Cette classe surcharge _parse() pour permettre de lire les fichiers GNU gettext .mo au format petit et gros-boutiste.

GNUTranslations analyse les métadonnées optionnelles du catalogue de traduction. Il est d’usage avec GNU gettext d’utiliser une métadonnée pour traduire la chaîne vide. Cette métadonnée est un ensemble de paires de la forme clef: valeur comme définie par la RFC 822 [https://tools.ietf.org/html/rfc822.html], et doit contenir la clef Project-Id-Version. Si la clef Content-Type est trouvée dans une métadonnée, alors la propriété charset (jeu de caractères) est utilisée pour initialiser la variable d’instance « protégée » _charset, sinon cette dernière est positionnée à None. Si l’encodage du jeu de caractères est spécifié, tous les messages (identifiants et chaînes de caractères) lus depuis le catalogue sont convertis en chaînes Unicode via cet encodage, ou via l’encodage ASCII si non renseigné.

Et puisque les identifiants des messages sont également lus comme des chaînes Unicode, toutes les méthodes *gettext() les considéreront ainsi, et pas comme des chaînes d’octets.

La totalité des paires clef / valeur est insérée dans un dictionnaire et représente la variable d’instance « protégée » _info.

Si le nombre magique du fichier .mo est invalide, le numéro de la version majeure inattendu, ou si d’autres problèmes apparaissent durant la lecture du fichier, instancier une classe GNUTranslations peut lever une exception OSError.

class gettext.GNUTranslations

Les méthodes suivantes, provenant de l’implémentation de la classe de base, ont été surchargée :

gettext(message)

Recherche l’identifiant de message dans le catalogue et renvoie le message de la chaîne de caractères correspondante comme une chaîne Unicode. Si aucun identifiant n’a été trouvé pour message et qu’un substitut a été défini, la recherche est transmise à la méthode gettext() du substitut. Sinon, l’identifiant de message est renvoyé.

ngettext(singular, plural, n)

Effectue une recherche sur les formes plurielles de l’identifiant d’un message. singular est utilisé pour la recherche de l’identifiant dans le catalogue, alors que n permet de savoir quelle forme plurielle utiliser. La chaîne de caractère du message renvoyée est une chaîne Unicode.

Si l’identifiant du message n’est pas trouvé dans le catalogue et qu’un substitut a été spécifié, la requête est transmise à la méthode ngettext() du substitut. Sinon, est renvoyé singular lorsque n vaut 1, plural dans tous les autres cas.

Voici un exemple :

n = len(os.listdir('.'))
cat = GNUTranslations(somefile)
message = cat.ngettext(
    'There is %(num)d file in this directory',
    'There are %(num)d files in this directory',
    n) % {'num': n}

lgettext(message)

lngettext(singular, plural, n)

Équivalent de gettext() et ngettext(), mais la traduction est renvoyée sous la forme d’une chaîne d’octets, encodée avec l’encodage du système si aucun autre n’a été défini avec set_output_charset().

Avertissement

L’utilisation de ces méthodes doivent être évitée en Python 3. Voir l’avertissement de la fonction lgettext().

23.1.2.3. Support du catalogue de message de Solaris

Le système d’exploitation Solaris possède son propre format de fichier binaire .mo, mais pour l’heure, puisqu’on ne peut trouver de documentation sur ce format, il n’est pas géré.

23.1.2.4. Le constructeur Catalog

GNOME utilise une version du module gettext de James Henstridge, mais qui a une API légèrement différente. D’après la documentation, elle s’utilise ainsi :

import gettext
cat = gettext.Catalog(domain, localedir)
_ = cat.gettext
print(_('hello world'))

Pour des raisons de compatibilité avec cet ancien module, la fonction Catalog() est un alias de la fonction translation() décrite ci-dessous.

Une différence entre ce module et celui de Henstridge : les objets de son catalogue étaient accessibles depuis un schéma de l’API, mais cela semblait ne pas être utilisé et donc n’est pas pris en charge.

23.1.3. Internationaliser vos programmes et modules

L’internationalisation (I18N) consiste à permettre à un programme de recevoir des traductions dans plusieurs langues. La localisation (L10N) consiste à adapter un programme à la langue et aux habitudes culturelles locales, une fois celui-ci internationalisé. Afin de fournir du texte multilingue à votre programme Python, les étapes suivantes sont nécessaires :

préparer votre programme ou module en marquant spécifiquement les chaînes à traduire

lancer une suite d’outils sur les fichiers contenant des chaînes à traduire pour générer des catalogues de messages brut

créer les traductions spécifiques à une langue des catalogues de messages

utiliser le module gettext pour que les chaînes de caractères soient bien traduites

Afin de préparer votre code à être traduit (I18N), vous devrez rechercher toutes les chaînes de caractères de vos fichiers. À chaque chaîne de caractères à traduire doit être appliqué le marqueur _('...') — c’est-à-dire en appelant la fonction _(). Par exemple :

filename = 'mylog.txt'
message = _('writing a log message')
fp = open(filename, 'w')
fp.write(message)
fp.close()

Dans cet exemple, la chaîne 'writing a log message' est maquée comme traduite, contrairement aux chaînes 'mylog.txt' et 'w'.

Il existe quelques outils pour extraire les chaînes de caractères destinées à la traduction. Le programme d’origine GNU gettext ne prenait en charge que les codes sources en C ou C++, mais sa version étendue xgettext peut lire du code écrit dans de nombreux langages, dont le Python, afin de trouver les chaînes notées comme traduisibles. Babel [http://babel.pocoo.org/] est une bibliothèque en Python d’internationalisation, qui inclut un script pybabel permettant d’extraire et de compiler des catalogues de messages. Le programme de François Pinard, nommé xpot, fait de même et est disponible dans son paquet po-utils [https://github.com/pinard/po-utils].

(Python inclut également des versions en Python de ces programmes, pygettext.py et msgfmt.py, que certaines distributions Python installeront pour vous. pygettext.py est similaire à xgettext, mais ne comprend que le code source écrit en Python et ne peut prendre en charge d’autres langages de programmation tels que le C ou C++. pygettext.py possède une interface en ligne de commande similaire à celle de xgettext — pour plus de détails sur son utilisation, exécuter pygettext.py --help. msgfmt.py est compatible avec GNU msgfmt. Avec ces deux programmes, vous ne devriez pas avoir besoin du paquet GNU gettext pour internationaliser vos applications en Python.)

xgettext, pygettext et d’autres outils similaires génèrent des fichiers .po représentant les catalogues de messages. Il s’agit de fichiers structurés et lisibles par un être humain, qui contiennent toutes les chaînes du code source marquées comme traduisible, ainsi que leur traduction à utiliser.

Les copies de ces fichiers .po sont ensuite remises à des êtres humains qui traduisent le contenu pour chaque langue naturelle prise en charge. Pour chacune des langues, ces derniers renvoient la version complétée sous la forme d’un fichier <code-langue>.po qui a été compilé dans un fichier binaire .mo représentant le catalogue lisible par une machine à l’aide du programme msgfmt. Les fichiers .mo sont utilisés par le module gettext pour la traduction lors de l’exécution.

La façon dont vous utilisez le module gettext dans votre code dépend de si vous internationalisez un seul module ou l’ensemble de votre application. Les deux sections suivantes traitent chacune des cas.

23.1.3.1. Localiser votre module

Si vous localisez votre module, veillez à ne pas faire de changements globaux, e.g. dans l’espace de nom natif. Vous ne devriez pas utiliser l’API GNU gettext mais plutôt celle basée sur les classes.

Disons que votre module s’appelle « spam » et que les fichiers .mo de traduction dans les différentes langues naturelles soient dans /usr/share/locale au format GNU gettext. Voici ce que vous pouvez alors mettre en haut de votre module :

import gettext
t = gettext.translation('spam', '/usr/share/locale')
_ = t.gettext

23.1.3.2. Localiser votre application

Si vous localisez votre application, vous pouvez positionner la fonction _() de manière globale dans l’espace de nommage natif, généralement dans le fichier principal de votre application. Cela permettra à tous les fichiers de votre application de n’utiliser que _('...') sans devoir le redéfinir explicitement dans chaque fichier.

Dans ce cas, vous n’aurez à ajouter que le bout de code suivant au fichier principal de votre application :

import gettext
gettext.install('myapplication')

Si vous avez besoin de définir le dossier des localisations, vous pouvez le mettre en argument de la fonction install() :

import gettext
gettext.install('myapplication', '/usr/share/locale')

23.1.3.3. Changer de langue à la volée

Si votre programme a besoin de prendre en charge plusieurs langues en même temps, vous pouvez créer plusieurs instances de traduction, puis basculer entre elles de façon explicite, comme ceci :

import gettext

lang1 = gettext.translation('myapplication', languages=['en'])
lang2 = gettext.translation('myapplication', languages=['fr'])
lang3 = gettext.translation('myapplication', languages=['de'])

# start by using language1
lang1.install()

# ... time goes by, user selects language 2
lang2.install()

# ... more time goes by, user selects language 3
lang3.install()

23.1.3.4. Traductions différées

Dans la plupart des cas, en programmation, les chaînes de caractères sont traduites à l’endroit où on les écrit. Cependant, il peut arriver que vous ayez besoin de traduire une chaîne de caractères un peu plus loin. Un exemple classique est :

animals = ['mollusk',
           'albatross',
           'rat',
           'penguin',
           'python', ]
# ...
for a in animals:
    print(a)

Ici, vous voulez marquer les chaînes de caractères de la liste animals comme étant traduisibles, mais ne les traduire qu’au moment de les afficher.

Voici un moyen de gérer ce cas :

def _(message): return message

animals = [_('mollusk'),
           _('albatross'),
           _('rat'),
           _('penguin'),
           _('python'), ]

del _

# ...
for a in animals:
    print(_(a))

Cela fonctionne car la définition factice de _() renvoie simplement la chaîne de caractères passée en entrée. Et cette définition factice va temporairement outrepasser toute autre définition de _() dans l’espace de nommage natif (jusqu’à l’utilisation de la commande del). Attention toutefois si vous avez déjà une autre définition de _() dans l’espace de nommage local.

À noter qu’à la deuxième utilisation de _(), « a » ne sera pas vue comme traduisible par le programme gettext car ce n’est pas un chaîne au sens propre.

Voici une autre solution :

def N_(message): return message

animals = [N_('mollusk'),
           N_('albatross'),
           N_('rat'),
           N_('penguin'),
           N_('python'), ]

# ...
for a in animals:
    print(_(a))

Dans ce cas, les chaînes à traduire sont identifiées avec la fonction N_(), qui n’entre pas en conflit avec définition de _(). Cependant, il faudra apprendre à votre programme d’extraction de messages à rechercher les chaînes de caractères à traduire parmi celles ayant le marqueur N_(). xgettext, pygettext, pybabel extract et xpot prennent tous en charge cela grâce à l’option en ligne de commande -k. Le choix du nom N_() ici est totalement arbitraire et aurait très bien pu être MarqueurDeTraduction().

23.1.4. Remerciements

Les personnes suivantes ont contribué au code, ont fait des retours, ont participé aux suggestions de conception et aux implémentations précédentes, et ont partagé leur expérience précieuse pour la création de ce module :

Peter Funk

James Henstridge

Juan David Ibáñez Palomar

Marc-André Lemburg

Martin von Löwis

François Pinard

Barry Warsaw

Gustavo Niemeyer

Notes

1

Le dossier par défaut pour les localisations dépend du système : par exemple, sur RedHat c’est /usr/share/locale, mais sur Solaris c’est /usr/lib/locale. Le module gettext n’essaie pas de prendre en charge ce paramètre système, mais utilise le dossier sys.prefix/share/locale. C’est pour cette raison qu’il est toujours préférable d’appeler bindtextdomain() en donnant explicitement un chemin absolu au début de votre application.

2

Voir la note de bindtextdomain() ci-dessus.

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23.2. locale — Services d’internationalisation

Code source : Lib/locale.py [https://github.com/python/cpython/tree/3.6/Lib/locale.py]

Le module locale donne accès à la base de données et aux fonctionnalités des paramètres linguistiques définis par POSIX. Le mécanisme des paramètres linguistiques de POSIX permet aux développeurs de faire face à certaines problématiques culturelles dans une application, sans avoir à connaître toutes les spécificités de chaque pays où le logiciel est exécuté.

Le module locale est implémenté au-dessus du module _locale, qui lui-même utilise l’implémentation du paramètre régional ANSI C si disponible.

Le module locale définit l’exception et les fonctions suivantes :

exception locale.Error

Exception levée lorsque le paramètre régional passé en paramètre de setlocale() n’est pas reconnu.

locale.setlocale(category, locale=None)

Si locale ne vaut pas None, setlocale() modifie le paramètre régional pour la catégorie category. Les catégories disponibles sont listées dans la description des données ci-dessous. locale peut être une chaîne de caractères ou un itérable de deux chaînes de caractères (code de la langue et encodage). Si c’est un itérable, il est converti en un nom de paramètre régional à l’aide du moteur d’aliasing fait pour. Si c’est une chaîne vide, les paramètres par défaut de l’utilisateur sont utilisés. Si la modification du paramètre régional échoue, l’exception Error est levée. Si elle fonctionne, le nouveau paramètre est renvoyé.

Si locale est omis ou vaut None, le paramètre actuel de category est renvoyé.

setlocale() n’est pas thread-safe sur la plupart des systèmes. Les applications commencent généralement par un appel de :

import locale
locale.setlocale(locale.LC_ALL, '')

Cela définit les paramètres régionaux dans toutes les catégories sur ceux par défaut de l’utilisateur (habituellement spécifiés dans la variable d’environnement LANG). Si les paramètres régionaux ne sont pas modifiés par la suite, l’utilisation de fils d’exécution ne devrait pas poser de problèmes.

locale.localeconv()

Renvoie la base de données des conventions locales sous forme de dictionnaire. Ce dictionnaire a les chaînes de caractères suivantes comme clés :

Catégorie

Clé

Signification

LC_NUMERIC

'decimal_point'

Caractère du séparateur décimal (entre la partie entière et la partie décimale).

'grouping'

Séquence de nombres spécifiant les positions relatives attendues pour 'thousands_sep' (séparateur de milliers). Si la séquence se termine par CHAR_MAX, aucun autre regroupement n’est effectué. Si la séquence se termine par un 0, la dernière taille du groupe est utilisée à plusieurs reprises.

'thousands_sep'

Caractère utilisé entre les groupes (séparateur de milliers).

LC_MONETARY

'int_curr_symbol'

Symbole monétaire international.

'currency_symbol'

Symbole monétaire local.

'p_cs_precedes/n_cs_precedes'

Si le symbole monétaire précède ou non la valeur (pour les valeurs positives, resp. négatives).

'p_sep_by_space/n_sep_by_space'

Si le symbole monétaire est séparé de la valeur par une espace ou non (pour les valeurs positives, resp. négatives).

'mon_decimal_point'

Séparateur décimal (entre la partie entière et la partie décimale) utilisé pour les valeurs monétaires.

'frac_digits'

Nombre de décimales utilisées dans le format local des valeurs monétaires.

'int_frac_digits'

Nombre de décimales utilisées dans le format international des valeurs monétaires.

'mon_thousands_sep'

Séparateur de groupe utilisé pour les valeurs monétaires.

'mon_grouping'

Équivalent de 'grouping', utilisé pour les valeurs monétaires.

'positive_sign'

Symbole utilisé pour indiquer qu’une valeur monétaire est positive.

'negative_sign'

Symbole utilisé pour indiquer qu’une valeur monétaire est négative.

'p_sign_posn/n_sign_posn'

Position du signe (pour les valeurs positives, resp. négatives), voir ci-dessous.

Toutes les valeurs numériques peuvent être définies à CHAR_MAX pour indiquer qu’il n’y a pas de valeur spécifiée pour ces paramètres régionaux.

Les valeurs possibles pour 'p_sign_posn' et 'n_sign_posn' sont données ci-dessous.

Valeur

Explication

0

Le symbole monétaire et la valeur sont entourés de parenthèses.

1

Le signe doit précéder la valeur et le symbole monétaire.

2

Le signe doit suivre la valeur et le symbole monétaire.

3

Le signe doit précéder immédiatement la valeur.

4

Le signe doit suivre immédiatement la valeur.

CHAR_MAX

Rien n’est spécifié dans ces paramètres régionaux.

The function sets temporarily the LC_CTYPE locale to the LC_NUMERIC locale or the LC_MONETARY locale if locales are different and numeric or monetary strings are non-ASCII. This temporary change affects other threads.

Modifié dans la version 3.6.5: La fonction définit maintenant la valeur du paramètre LC_CTYPE à celle du paramètre LC_NUMERIC temporairement dans certains cas.

locale.nl_langinfo(option)

Renvoie quelques informations spécifiques aux paramètres régionaux sous forme de chaîne. Cette fonction n’est pas disponible sur tous les systèmes et l’ensemble des options possibles peut également varier d’une plateforme à l’autre. Les valeurs possibles pour les arguments sont des nombres, pour lesquels des constantes symboliques sont disponibles dans le module locale.

La fonction nl_langinfo() accepte l’une des clés suivantes. La plupart des descriptions sont extraites des descriptions correspondantes dans la bibliothèque GNU C.

locale.CODESET

Récupère une chaîne avec le nom de l’encodage des caractères utilisé par le paramètre régional sélectionné.

locale.D_T_FMT

Récupère une chaîne qui peut être utilisée comme une chaîne de format par time.strftime() afin de représenter la date et l’heure pour un paramètre régional spécifique.

locale.D_FMT

Récupère une chaîne qui peut être utilisée comme une chaîne de format par time.strftime() afin de représenter une date pour un paramètre régional spécifique.

locale.T_FMT

Récupère une chaîne qui peut être utilisée comme une chaîne de format par time.strftime() afin de représenter une heure pour un paramètre régional spécifique.

locale.T_FMT_AMPM

Récupère une chaîne de format pour time.strftime() afin de représenter l’heure au format am / pm.

DAY_1 ... DAY_7

Récupère le nom du n-ième jour de la semaine.

Note

Cela suit la convention américaine qui définit DAY_1 comme étant dimanche, et non la convention internationale (ISO 8601) où lundi est le premier jour de la semaine.

ABDAY_1 ... ABDAY_7

Récupère l’abréviation du n-ième jour de la semaine.

MON_1 ... MON_12

Récupère le nom du n-ième mois.

ABMON_1 ... ABMON_12

Récupère l’abréviation du n-ième mois.

locale.RADIXCHAR

Récupère le caractère de séparation radix (point décimal, virgule décimale, etc.).

locale.THOUSEP

Récupère le caractère de séparation des milliers (groupes de 3 chiffres).

locale.YESEXPR

Récupère une expression régulière qui peut être utilisée par la fonction regex pour reconnaître une réponse positive à une question fermée (oui / non).

Note

L’expression est dans une syntaxe adaptée à la fonction regex() de la bibliothèque C, qui peut différer de la syntaxe utilisée par re.

locale.NOEXPR

Récupère une expression régulière qui peut être utilisée par la fonction regex(3) pour reconnaître une réponse négative à une question fermée (oui / non).

locale.CRNCYSTR

Récupère le symbole monétaire, précédé de « - » si le symbole doit apparaître avant la valeur, « + » s’il doit apparaître après la valeur, ou « . » s’il doit remplacer le caractère de séparation radix.

locale.ERA

Récupère une chaîne qui représente l’ère utilisée pour le paramètre régional actuel.

La plupart des paramètres régionaux ne définissent pas cette valeur. Un exemple de région qui définit bien cette valeur est le japonais. Au Japon, la représentation traditionnelle des dates comprend le nom de l’ère correspondant au règne de l’empereur de l’époque.

Normalement, il ne devrait pas être nécessaire d’utiliser cette valeur directement. Spécifier le modificateur E dans leurs chaînes de format provoque l’utilisation de cette information par la fonction time.strftime(). Le format de la chaîne renvoyée n’est pas spécifié, et vous ne devez donc pas supposer en avoir connaissance sur des systèmes différents.

locale.ERA_D_T_FMT

Récupère la chaîne de format pour time.strftime() afin de représenter la date et l’heure pour un paramètre régional spécifique basée sur une ère.

locale.ERA_D_FMT

Récupère la chaîne de format pour time.strftime() afin de représenter une date pour un paramètre régional spécifique basée sur une ère.

locale.ERA_T_FMT

Récupère la chaîne de format pour time.strftime() afin de représenter une heure pour un paramètre régional spécifique basée sur une ère.

locale.ALT_DIGITS

Récupère une représentation de 100 valeurs maximum utilisées pour représenter les valeurs de 0 à 99.

locale.getdefaultlocale([envvars])

Tente de déterminer les paramètres régionaux par défaut, puis les renvoie sous la forme d’un n-uplet (code de la langue, encodage).

D’après POSIX, un programme qui n’a pas appelé setlocale(LC_ALL, '') fonctionne en utilisant le paramètre régional portable 'C'. Appeler setlocale(LC_ALL, '') lui permet d’utiliser les paramètres régionaux par défaut définis par la variable LANG. Comme nous ne voulons pas interférer avec les paramètres régionaux actuels, nous émulons donc le comportement décrit ci-dessus.

Afin de maintenir la compatibilité avec d’autres plateformes, non seulement la variable LANG est testée, mais c’est aussi le cas pour toute une liste de variables passés en paramètre via envvars. La première variable à être défini sera utilisée. envvars utilise par défaut le chemin de recherche utilisé dans GNU gettext ; il doit toujours contenir le nom de variable 'LANG'. Le chemin de recherche de GNU gettext contient 'LC_ALL', 'LC_CTYPE', 'LANG' et 'LANGUAGE', dans cet ordre.

À l’exception du code 'C', le code d’une langue correspond à la RFC 1766 [https://tools.ietf.org/html/rfc1766.html]. Le code de la langue et l”encodage peuvent valoir None si leur valeur ne peut être déterminée.

locale.getlocale(category=LC_CTYPE)

Renvoie les réglages actuels pour la catégorie de paramètres régionaux donnée, sous la forme d’une séquence contenant le code de la langue et l”encodage. La catégorie category peut être l’une des valeurs LC_* à l’exception de LC_ALL. La valeur par défaut est LC_CTYPE.

À l’exception du code 'C', le code d’une langue correspond à la RFC 1766 [https://tools.ietf.org/html/rfc1766.html]. Le code de la langue et l”encodage peuvent valoir None si leur valeur ne peut être déterminée.

locale.getpreferredencoding(do_setlocale=True)

Renvoie le codage utilisé pour les données textuelles, selon les préférences de l’utilisateur. Les préférences de l’utilisateur sont exprimées différemment selon les systèmes et peuvent ne pas être disponibles via les interfaces de programmation sur certains systèmes. Cette fonction ne renvoie donc qu’une supposition.

Sur certains systèmes, il est nécessaire d’invoquer setlocale() pour obtenir les préférences de l’utilisateur, cette fonction n’est donc pas utilisable sans protection dans les programmes à fils d’exécutions multiples. Si l’appel de setlocale n’est pas nécessaire ou souhaité, do_setlocale doit être réglé à False.

locale.normalize(localename)

Renvoie un code normalisé pour le nom du paramètre régional fourni. Ce code renvoyé est structuré de façon à être utilisé avec setlocale(). Si la normalisation échoue, le nom d’origine est renvoyé inchangé.

Si l’encodage donné n’est pas connu, la fonction utilise l’encodage par défaut pour le code du paramètre régional, tout comme setlocale().

locale.resetlocale(category=LC_ALL)

Définit le paramètre régional de la catégorie category au réglage par défaut.

Le réglage par défaut est déterminé en appelant getdefaultlocale(). La catégorie category vaut par défaut LC_ALL.

locale.strcoll(string1, string2)

Compare deux chaînes en se basant sur le paramètre LC_COLLATE actuel. Comme toute autre fonction de comparaison, renvoie une valeur négative, positive, ou 0, selon si string1 est lexicographiquement inférieure, supérieure, ou égale à string2.

locale.strxfrm(string)

Transforme une chaîne de caractères en une chaîne qui peut être utilisée dans les comparaisons sensibles aux paramètres régionaux. Par exemple, strxfrm(s1) < strxfrm(s2) est équivalent à strcoll(s1, s2) < 0. Cette fonction peut être utilisée lorsque la même chaîne est comparée de façon répétitive, par exemple lors de l’assemblage d’une séquence de chaînes.

locale.format(format, val, grouping=False, monetary=False)

Structure un nombre val en fonction du paramètre LC_NUMERIC actuel. Le format suit les conventions de l’opérateur %. Pour les valeurs à virgule flottante, le point décimal est modifié si nécessaire. Si grouping est vrai, le regroupement est également pris en compte.

Si monetary est vrai, la conversion utilise un séparateur des milliers monétaire et des chaînes de regroupement.

À noter que cette fonction ne fonctionnera que pour un seul marqueur %char. Pour les chaînes structurées entières, utiliser format_string().

locale.format_string(format, val, grouping=False)

Traite les marqueurs de structure en format % val, mais en prenant en compte les paramètres régionaux actuels.

locale.currency(val, symbol=True, grouping=False, international=False)

Structure un nombre val en fonction du paramètre LC_MONETARY actuel.

La chaîne renvoyée inclut le symbole monétaire si symbol est vrai, ce qui est le cas par défaut. Si grouping est vrai (ce qui n’est pas le cas par défaut), un regroupement est effectué avec la valeur. Si international est vrai (ce qui n’est pas le cas par défaut), le symbole de la devise internationale est utilisé.

Notez que cette fonction ne fonctionnera pas avec le paramètre régional “C”, vous devez donc d’abord en définir un via setlocale().

locale.str(float)

Structure un nombre flottant en utilisant le même format que la fonction native str(float), mais en prenant en compte le point décimal.

locale.delocalize(string)

Convertit une chaîne de caractères en une chaîne de nombres normalisés, en suivant les réglages LC_NUMERIC.

Nouveau dans la version 3.5.

locale.atof(string)

Convertit une chaîne de caractères en nombre à virgule flottante, en suivant les réglages LC_NUMERIC.

locale.atoi(string)

Convertit une chaîne de caractères en un entier, en suivant les réglages LC_NUMERIC.

locale.LC_CTYPE

Catégorie de paramètre régional pour les fonctions de type caractère. Suivant les réglages de la catégorie, les fonctions du module string gérant la casse peuvent changer leur comportement.

locale.LC_COLLATE

Catégorie de paramètre régional pour les tris de chaînes de caractères. Les fonctions strcoll() et strxfrm() du module locale sont concernées.

locale.LC_TIME

Catégorie de paramètre régional pour la mise en forme de la date et de l’heure. La fonction time.strftime() suit ces conventions.

locale.LC_MONETARY

Catégorie de paramètre régional pour la mise en forme des valeurs monétaires. Les options disponibles sont accessibles à partir de la fonction localeconv().

locale.LC_MESSAGES

Catégorie de paramètre régional pour l’affichage de messages. Actuellement, Python ne gère pas les messages spécifiques aux applications qui sont sensibles aux paramètres régionaux. Les messages affichés par le système d’exploitation, comme ceux renvoyés par os.strerror() peuvent être affectés par cette catégorie.

locale.LC_NUMERIC

Catégorie de paramètre régional pour la mise en forme des nombres. Les fonctions format(), atoi(), atof() et str() du module locale sont affectées par cette catégorie. Toutes les autres opérations de mise en forme des nombres ne sont pas affectées.

locale.LC_ALL

Combinaison de tous les paramètres régionaux. Si cette option est utilisée lors du changement de paramètres régionaux, la définition de ces paramètres pour toutes les catégories est tentée. Si cela échoue pour n’importe quelle catégorie, aucune d’entre elles n’est modifiée. Lorsque les paramètres régionaux sont récupérés à l’aide de cette option, une chaîne de caractères indiquant le réglage pour toutes les catégories est renvoyée. Cette chaîne peut alors être utilisée plus tard pour restaurer les paramètres d’origine.

locale.CHAR_MAX

Ceci est une constante symbolique utilisée pour différentes valeurs renvoyées par localeconv().

Exemple :

>>> import locale
>>> loc = locale.getlocale()  # get current locale
# use German locale; name might vary with platform
>>> locale.setlocale(locale.LC_ALL, 'de_DE')
>>> locale.strcoll('f\xe4n', 'foo')  # compare a string containing an umlaut
>>> locale.setlocale(locale.LC_ALL, '')   # use user's preferred locale
>>> locale.setlocale(locale.LC_ALL, 'C')  # use default (C) locale
>>> locale.setlocale(locale.LC_ALL, loc)  # restore saved locale

23.2.1. Contexte, détails, conseils, astuces et mises en garde

La norme C définie les paramètres régionaux comme une propriété à l’échelle d’un programme, qui peut être relativement coûteuse à changer. En plus de cela, certaines implémentations ne fonctionnent pas car des changements fréquents de paramètres régionaux peuvent causer des core dumps. Cela rend l’utilisation correcte de ces paramètres quelque peu pénible.

Initialement, lorsqu’un programme est démarré, les paramètres régionaux C sont utilisés, peu importe les réglages de l’utilisateur. Il y a toutefois une exception : la catégorie LC_CTYPE est modifiée au démarrage pour définir l’encodage des paramètres régionaux actuels comme celui défini par l’utilisateur. Le programme doit explicitement dire qu’il veut utiliser les réglages de l’utilisateur pour les autres catégories, en appelant setlocale(LC_ALL, '').

C’est généralement une mauvaise idée d’appeler setlocale() dans une routine de bibliothèque car cela a pour effet secondaire d’affecter le programme entier. Sauvegarder et restaurer les paramètres est presque aussi mauvais : c’est coûteux et cela affecte d’autres fils d’exécutions qui s’exécutent avant que les paramètres n’aient été restaurés.

Si, lors du développement d’un module à usage général, vous avez besoin d’une version indépendante des paramètres régionaux pour une opération y étant sensible (comme c’est le cas pour certains formats utilisés avec time.strftime()), vous devez trouver un moyen de le faire sans utiliser la routine de la bibliothèque standard. Le mieux est encore de se convaincre que l’usage des paramètres régionaux est une bonne chose. Ce n’est qu’en dernier recours que vous devez documenter que votre module n’est pas compatible avec les réglages du paramètre régional C.

La seule façon d’effectuer des opérations numériques conformément aux paramètres régionaux est d’utiliser les fonctions spéciales définies par ce module : atof(), atoi(), format(), str().

Il n’y a aucun moyen d’effectuer des conversions de casse et des classifications de caractères en fonction des paramètres régionaux. Pour les chaînes de caractères (Unicode), celles-ci se font uniquement en fonction de la valeur du caractère, tandis que pour les chaînes d’octets, les conversions et les classifications se font en fonction de la valeur ASCII de l’octet, et les octets dont le bit de poids fort est à 1 (c’est-à-dire les octets non ASCII) ne sont jamais convertis ou considérés comme faisant partie d’une classe de caractères comme une lettre ou une espace.

23.2.2. Pour les auteurs d’extensions et les programmes qui intègrent Python

Les modules d’extensions ne devraient jamais appeler setlocale(), sauf pour connaître le paramètre régional actuel. Mais comme la valeur renvoyée ne peut être utilisée que pour le restaurer, ce n’est pas très utile (sauf peut-être pour savoir si le paramètre régional est défini à C ou non).

Lorsque le code Python utilise le module locale pour changer le paramètre régional, cela affecte également l’application intégrée. Si l’application intégrée ne souhaite pas que cela se produise, elle doit supprimer le module d’extension _locale (qui fait tout le travail) de la table des modules natifs se trouvant dans le fichier config.c, et s’assurer que le module _locale n’est pas accessible en tant que bibliothèque partagée.

23.2.3. Accéder aux catalogues de messages

locale.gettext(msg)

locale.dgettext(domain, msg)

locale.dcgettext(domain, msg, category)

locale.textdomain(domain)

locale.bindtextdomain(domain, dir)

Le module locale expose l’interface gettext de la bibliothèque C sur les systèmes qui fournissent cette interface. Il se compose des fonctions gettext(), dgettext(), dcgettext(), textdomain(), bindtextdomain() et bind_textdomain_codeset(). Elles sont similaires aux fonctions du module gettext, mais utilisent le format binaire de la bibliothèque C pour les catalogues de messages.

Les applications Python ne devraient normalement pas avoir besoin de faire appel à ces fonctions, mais devraient plutôt utiliser gettext. Une exception connue pour cette règle concerne les applications qui sont liées avec des bibliothèques C supplémentaires faisant appel à c:func:gettext ou dcgettext(). Pour ces applications, il peut être nécessaire de lier le domaine du texte, afin que les bibliothèques puissent régionaliser correctement leurs catalogues de messages.

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24. Frameworks d’applications

Les modules décrits dans ce chapitre sont des frameworks qui encadreront la structure de vos programmes. Actuellement tous les modules décrits ici sont destinés à écrire des interfaces en ligne de commande.

La liste complète des modules décrits dans ce chapitre est :

24.1. turtle — Tortue graphique

24.1.1. Introduction

24.1.2. Résumé des méthodes de Turtle et Screen

24.1.2.1. Les méthodes du module Turtle

24.1.2.2. Methods of TurtleScreen/Screen

24.1.3. Methods of RawTurtle/Turtle and corresponding functions

24.1.3.1. Les mouvements dans le module Turtle

24.1.3.2. Tell Turtle’s state

24.1.3.3. Settings for measurement

24.1.3.4. Pen control

24.1.3.4.1. Drawing state

24.1.3.4.2. Color control

24.1.3.4.3. Filling

24.1.3.4.4. More drawing control

24.1.3.5. Turtle state

24.1.3.5.1. Visibility

24.1.3.5.2. Appearance

24.1.3.6. Using events

24.1.3.7. Special Turtle methods

24.1.3.8. Compound shapes

24.1.4. Methods of TurtleScreen/Screen and corresponding functions

24.1.4.1. Window control

24.1.4.2. Animation control

24.1.4.3. Using screen events

24.1.4.4. Input methods

24.1.4.5. Settings and special methods

24.1.4.6. Methods specific to Screen, not inherited from TurtleScreen

24.1.5. Public classes

24.1.6. Help and configuration

24.1.6.1. How to use help

24.1.6.2. Translation of docstrings into different languages

24.1.6.3. How to configure Screen and Turtles

24.1.7. turtledemo — Demo scripts

24.1.8. Changes since Python 2.6

24.1.9. Changes since Python 3.0

24.2. cmd — Interpréteurs en ligne de commande.

24.2.1. Objets Cmd

24.2.2. Exemple

24.3. shlex — Simple lexical analysis

24.3.1. shlex Objects

24.3.2. Parsing Rules

24.3.3. Improved Compatibility with Shells

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24.1. turtle — Tortue graphique

Code Source : Lib/turtle.py [https://github.com/python/cpython/tree/3.6/Lib/turtle.py]

24.1.1. Introduction

Une façon populaire pour initier les enfants au monde du développement est le module Tortue graphique. Ce dernier faisait partie du langage de programmation Logo créé par Wally Feurzig et Seymout Papert en 1966.

Imaginez un robot sous forme de tortue partant au centre (0, 0) d’un plan cartésien x-y. Après un import turtle, exécutez la commande turtle.forward(15) et la tortue se déplace (sur l’écran) de 15 pixels en face d’elle, en dessinant une ligne.

Turtle star

La tortue permet de dessiner des formes complexes en utilisant un programme qui répète des actions élémentaires.

from turtle import *
color('red', 'yellow')
begin_fill()
while True:
    forward(200)
    left(170)
    if abs(pos()) < 1:
        break
end_fill()
done()

On peut donc facilement construire des formes et images à partir de commandes simples.

Le module turtle est une version étendue du module homonyme appartenant à la distribution standard de Python jusqu’à la version 2.5.

Cette bibliothèque essaye de garder les avantages de l’ancien module et d’être (presque) 100% compatible avec celui-ci. Cela permet à l’apprenti développeur d’utiliser toutes les commandes, classes et méthodes de façon interactive pendant qu’il utilise le module depuis IDLE lancé avec l’option -n.

Turtle permet d’utiliser des primitives graphiques en utilisant un style de programmation orienté objet ou procédural. Du fait qu’il utilise la bibliothèque graphique tkinter, Turtle a besoin d’une version de python implémentant Tk.

L’interface orientée objet utilise essentiellement deux + deux classes :

La classe TurtleScreen définit une fenêtre graphique utilisé comme un terrain de jeu pour les dessins de la tortue. Le constructeur de cette classe a besoin d’un tkinter.Canvas ou ScrolledCanvas comme argument. Cette classe doit être utilisée seulement si turtle fait partie intégrante d’une autre application.

La fonction Screen() renvoie un singleton d’une sous-classe de TurtleScreen. Elle doit être utilisée quand le module turtle est utilisé de façon autonome pour dessiner. Le singleton renvoyé ne peut hériter de sa classe.

Toutes les méthodes de TurtleScreen/Screen existent également sous la forme de fonctions, c’est-à-dire que ces dernières peuvent être utilisées dans un style procédural.

La classe RawTurtle (alias RawPen) définit des objets Turtle qui peuvent dessiner sur la classe TurtleScreen. Son constructeur prend en paramètre un Canvas, un ScrolledCanvas ou un TurtleScreen permettant à l’objet RawTurtle de savoir où écrire.

La sous-classe Turtle (alias: Pen), dérivée de RawTurtle, dessine sur l’instance Screen qui est créée automatiquement si elle n’est pas déjà présente.

Toutes les méthodes de RawTurtle/Turtle existent également sous la forme de fonctions, c’est-à-dire que ces dernières pourront être utilisées en style procédural.

L’interface procédurale met à disposition des fonctions équivalentes à celles des méthodes des classes Screen et Turtle. Le nom d’une fonction est le même que la méthode équivalente. Un objet Screen est créé automatiquement dès qu’une fonction dérivée d’une méthode Screen est appelée. Un objet Turtle (sans nom) est créé automatiquement dès qu’une fonction dérivée d’une méthode Turtle est appelée.

Afin de pouvoir utiliser plusieurs tortues simultanément sur l’écran, vous devez utiliser l’interface orientée-objet.

Note

La liste des paramètres des fonctions est donnée dans cette documentation. Les méthodes ont, évidemment, le paramètre self comme premier argument, mais ce dernier n’est pas indiqué ici.

24.1.2. Résumé des méthodes de Turtle et Screen

24.1.2.1. Les méthodes du module Turtle

Les mouvements dans le module Turtle

Bouger et dessiner

forward() | fd()

backward() | bk() | back()

right() | rt()

left() | lt()

goto() | setpos() | setposition()

setx()

sety()

setheading() | seth()

home()

circle()

dot()

stamp()

clearstamp()

clearstamps()

undo()

speed()

Tell Turtle’s state

position() | pos()

towards()

xcor()

ycor()

heading()

distance()

Setting and measurement

degrees()

radians()

Pen control

Drawing state

pendown() | pd() | down()

penup() | pu() | up()

pensize() | width()

pen()

isdown()

Color control

color()

pencolor()

fillcolor()

Filling

filling()

begin_fill()

end_fill()

More drawing control

reset()

clear()

write()

Turtle state

Visibility

showturtle() | st()

hideturtle() | ht()

isvisible()

Appearance

shape()

resizemode()

shapesize() | turtlesize()

shearfactor()

settiltangle()

tiltangle()

tilt()

shapetransform()

get_shapepoly()

Using events

onclick()

onrelease()

ondrag()

Special Turtle methods

begin_poly()

end_poly()

get_poly()

clone()

getturtle() | getpen()

getscreen()

setundobuffer()

undobufferentries()

24.1.2.2. Methods of TurtleScreen/Screen

Window control

bgcolor()

bgpic()

clear() | clearscreen()

reset() | resetscreen()

screensize()

setworldcoordinates()

Animation control

delay()

tracer()

update()

Using screen events

listen()

onkey() | onkeyrelease()

onkeypress()

onclick() | onscreenclick()

ontimer()

mainloop() | done()

Settings and special methods

mode()

colormode()

getcanvas()

getshapes()

register_shape() | addshape()

turtles()

window_height()

window_width()

Input methods

textinput()

numinput()

Methods specific to Screen

bye()

exitonclick()

setup()

title()

24.1.3. Methods of RawTurtle/Turtle and corresponding functions

Most of the examples in this section refer to a Turtle instance called turtle.

24.1.3.1. Les mouvements dans le module Turtle

turtle.forward(distance)

turtle.fd(distance)

Paramètres

distance – a number (integer or float)

Move the turtle forward by the specified distance, in the direction the turtle is headed.

>>> turtle.position()
(0.00,0.00)
>>> turtle.forward(25)
>>> turtle.position()
(25.00,0.00)
>>> turtle.forward(-75)
>>> turtle.position()
(-50.00,0.00)

turtle.back(distance)

turtle.bk(distance)

turtle.backward(distance)

Paramètres

distance – a number

Move the turtle backward by distance, opposite to the direction the turtle is headed. Do not change the turtle’s heading.

>>> turtle.position()
(0.00,0.00)
>>> turtle.backward(30)
>>> turtle.position()
(-30.00,0.00)

turtle.right(angle)

turtle.rt(angle)

Paramètres

angle – a number (integer or float)

Turn turtle right by angle units. (Units are by default degrees, but can be set via the degrees() and radians() functions.) Angle orientation depends on the turtle mode, see mode().

>>> turtle.heading()
22.0
>>> turtle.right(45)
>>> turtle.heading()
337.0

turtle.left(angle)

turtle.lt(angle)

Paramètres

angle – a number (integer or float)

Turn turtle left by angle units. (Units are by default degrees, but can be set via the degrees() and radians() functions.) Angle orientation depends on the turtle mode, see mode().

>>> turtle.heading()
22.0
>>> turtle.left(45)
>>> turtle.heading()
67.0

turtle.goto(x, y=None)

turtle.setpos(x, y=None)

turtle.setposition(x, y=None)

Paramètres

x – a number or a pair/vector of numbers

y – a number or None

If y is None, x must be a pair of coordinates or a Vec2D (e.g. as returned by pos()).

Move turtle to an absolute position. If the pen is down, draw line. Do not change the turtle’s orientation.

>>> tp = turtle.pos()
>>> tp
(0.00,0.00)
>>> turtle.setpos(60,30)
>>> turtle.pos()
(60.00,30.00)
>>> turtle.setpos((20,80))
>>> turtle.pos()
(20.00,80.00)
>>> turtle.setpos(tp)
>>> turtle.pos()
(0.00,0.00)

turtle.setx(x)

Paramètres

x – a number (integer or float)

Set the turtle’s first coordinate to x, leave second coordinate unchanged.

>>> turtle.position()
(0.00,240.00)
>>> turtle.setx(10)
>>> turtle.position()
(10.00,240.00)

turtle.sety(y)

Paramètres

y – a number (integer or float)

Set the turtle’s second coordinate to y, leave first coordinate unchanged.

>>> turtle.position()
(0.00,40.00)
>>> turtle.sety(-10)
>>> turtle.position()
(0.00,-10.00)

turtle.setheading(to_angle)

turtle.seth(to_angle)

Paramètres

to_angle – a number (integer or float)

Set the orientation of the turtle to to_angle. Here are some common directions in degrees:

standard mode

logo mode

0 - east

0 - north

90 - north

90 - east

180 - west

180 - south

270 - south

270 - west

>>> turtle.setheading(90)
>>> turtle.heading()
90.0

turtle.home()

Move turtle to the origin – coordinates (0,0) – and set its heading to its start-orientation (which depends on the mode, see mode()).

>>> turtle.heading()
90.0
>>> turtle.position()
(0.00,-10.00)
>>> turtle.home()
>>> turtle.position()
(0.00,0.00)
>>> turtle.heading()
0.0

turtle.circle(radius, extent=None, steps=None)

Paramètres

radius – a number

extent – a number (or None)

steps – an integer (or None)

Draw a circle with given radius. The center is radius units left of the turtle; extent – an angle – determines which part of the circle is drawn. If extent is not given, draw the entire circle. If extent is not a full circle, one endpoint of the arc is the current pen position. Draw the arc in counterclockwise direction if radius is positive, otherwise in clockwise direction. Finally the direction of the turtle is changed by the amount of extent.

As the circle is approximated by an inscribed regular polygon, steps determines the number of steps to use. If not given, it will be calculated automatically. May be used to draw regular polygons.

>>> turtle.home()
>>> turtle.position()
(0.00,0.00)
>>> turtle.heading()
0.0
>>> turtle.circle(50)
>>> turtle.position()
(-0.00,0.00)
>>> turtle.heading()
0.0
>>> turtle.circle(120, 180)  # draw a semicircle
>>> turtle.position()
(0.00,240.00)
>>> turtle.heading()
180.0

turtle.dot(size=None, *color)

Paramètres

size – an integer >= 1 (if given)

color – a colorstring or a numeric color tuple

Draw a circular dot with diameter size, using color. If size is not given, the maximum of pensize+4 and 2*pensize is used.

>>> turtle.home()
>>> turtle.dot()
>>> turtle.fd(50); turtle.dot(20, "blue"); turtle.fd(50)
>>> turtle.position()
(100.00,-0.00)
>>> turtle.heading()
0.0

turtle.stamp()

Stamp a copy of the turtle shape onto the canvas at the current turtle position. Return a stamp_id for that stamp, which can be used to delete it by calling clearstamp(stamp_id).

>>> turtle.color("blue")
>>> turtle.stamp()
11
>>> turtle.fd(50)

turtle.clearstamp(stampid)

Paramètres

stampid – an integer, must be return value of previous stamp() call

Delete stamp with given stampid.

>>> turtle.position()
(150.00,-0.00)
>>> turtle.color("blue")
>>> astamp = turtle.stamp()
>>> turtle.fd(50)
>>> turtle.position()
(200.00,-0.00)
>>> turtle.clearstamp(astamp)
>>> turtle.position()
(200.00,-0.00)

turtle.clearstamps(n=None)

Paramètres

n – an integer (or None)

Delete all or first/last n of turtle’s stamps. If n is None, delete all stamps, if n > 0 delete first n stamps, else if n < 0 delete last n stamps.

>>> for i in range(8):
...     turtle.stamp(); turtle.fd(30)
13
14
15
16
17
18
19
20
>>> turtle.clearstamps(2)
>>> turtle.clearstamps(-2)
>>> turtle.clearstamps()

turtle.undo()

Undo (repeatedly) the last turtle action(s). Number of available undo actions is determined by the size of the undobuffer.

>>> for i in range(4):
...     turtle.fd(50); turtle.lt(80)
...
>>> for i in range(8):
...     turtle.undo()

turtle.speed(speed=None)

Paramètres

speed – an integer in the range 0..10 or a speedstring (see below)

Set the turtle’s speed to an integer value in the range 0..10. If no argument is given, return current speed.

If input is a number greater than 10 or smaller than 0.5, speed is set to 0. Speedstrings are mapped to speedvalues as follows:

« fastest »: 0

« fast »: 10

« normal »: 6

« slow »: 3

« slowest »: 1

Speeds from 1 to 10 enforce increasingly faster animation of line drawing and turtle turning.

Attention: speed = 0 means that no animation takes place. forward/back makes turtle jump and likewise left/right make the turtle turn instantly.

>>> turtle.speed()
3
>>> turtle.speed('normal')
>>> turtle.speed()
6
>>> turtle.speed(9)
>>> turtle.speed()
9

24.1.3.2. Tell Turtle’s state

turtle.position()

turtle.pos()

Return the turtle’s current location (x,y) (as a Vec2D vector).

>>> turtle.pos()
(440.00,-0.00)

turtle.towards(x, y=None)

Paramètres

x – a number or a pair/vector of numbers or a turtle instance

y – a number if x is a number, else None

Return the angle between the line from turtle position to position specified by (x,y), the vector or the other turtle. This depends on the turtle’s start orientation which depends on the mode - « standard »/ »world » or « logo »).

>>> turtle.goto(10, 10)
>>> turtle.towards(0,0)
225.0

turtle.xcor()

Return the turtle’s x coordinate.

>>> turtle.home()
>>> turtle.left(50)
>>> turtle.forward(100)
>>> turtle.pos()
(64.28,76.60)
>>> print(round(turtle.xcor(), 5))
64.27876

turtle.ycor()

Return the turtle’s y coordinate.

>>> turtle.home()
>>> turtle.left(60)
>>> turtle.forward(100)
>>> print(turtle.pos())
(50.00,86.60)
>>> print(round(turtle.ycor(), 5))
86.60254

turtle.heading()

Return the turtle’s current heading (value depends on the turtle mode, see mode()).

>>> turtle.home()
>>> turtle.left(67)
>>> turtle.heading()
67.0

turtle.distance(x, y=None)

Paramètres

x – a number or a pair/vector of numbers or a turtle instance

y – a number if x is a number, else None

Return the distance from the turtle to (x,y), the given vector, or the given other turtle, in turtle step units.

>>> turtle.home()
>>> turtle.distance(30,40)
50.0
>>> turtle.distance((30,40))
50.0
>>> joe = Turtle()
>>> joe.forward(77)
>>> turtle.distance(joe)
77.0

24.1.3.3. Settings for measurement

turtle.degrees(fullcircle=360.0)

Paramètres

fullcircle – a number

Set angle measurement units, i.e. set number of « degrees » for a full circle. Default value is 360 degrees.

>>> turtle.home()
>>> turtle.left(90)
>>> turtle.heading()
90.0

Change angle measurement unit to grad (also known as gon,
grade, or gradian and equals 1/100-th of the right angle.)
>>> turtle.degrees(400.0)
>>> turtle.heading()
100.0
>>> turtle.degrees(360)
>>> turtle.heading()
90.0

turtle.radians()

Set the angle measurement units to radians. Equivalent to degrees(2*math.pi).

>>> turtle.home()
>>> turtle.left(90)
>>> turtle.heading()
90.0
>>> turtle.radians()
>>> turtle.heading()
1.5707963267948966

24.1.3.4. Pen control

24.1.3.4.1. Drawing state

turtle.pendown()

turtle.pd()

turtle.down()

Pull the pen down – drawing when moving.

turtle.penup()

turtle.pu()

turtle.up()

Pull the pen up – no drawing when moving.

turtle.pensize(width=None)

turtle.width(width=None)

Paramètres

width – a positive number

Set the line thickness to width or return it. If resizemode is set to « auto » and turtleshape is a polygon, that polygon is drawn with the same line thickness. If no argument is given, the current pensize is returned.

>>> turtle.pensize()
1
>>> turtle.pensize(10)   # from here on lines of width 10 are drawn

turtle.pen(pen=None, **pendict)

Paramètres

pen – a dictionary with some or all of the below listed keys

pendict – one or more keyword-arguments with the below listed keys as keywords

Return or set the pen’s attributes in a « pen-dictionary » with the following key/value pairs:

« shown »: True/False

« pendown »: True/False

« pencolor »: color-string or color-tuple

« fillcolor »: color-string or color-tuple

« pensize »: positive number

« speed »: number in range 0..10

« resizemode »: « auto » or « user » or « noresize »

« stretchfactor »: (positive number, positive number)

« outline »: positive number

« tilt »: number

This dictionary can be used as argument for a subsequent call to pen() to restore the former pen-state. Moreover one or more of these attributes can be provided as keyword-arguments. This can be used to set several pen attributes in one statement.

>>> turtle.pen(fillcolor="black", pencolor="red", pensize=10)
>>> sorted(turtle.pen().items())
[('fillcolor', 'black'), ('outline', 1), ('pencolor', 'red'),
 ('pendown', True), ('pensize', 10), ('resizemode', 'noresize'),
 ('shearfactor', 0.0), ('shown', True), ('speed', 9),
 ('stretchfactor', (1.0, 1.0)), ('tilt', 0.0)]
>>> penstate=turtle.pen()
>>> turtle.color("yellow", "")
>>> turtle.penup()
>>> sorted(turtle.pen().items())[:3]
[('fillcolor', ''), ('outline', 1), ('pencolor', 'yellow')]
>>> turtle.pen(penstate, fillcolor="green")
>>> sorted(turtle.pen().items())[:3]
[('fillcolor', 'green'), ('outline', 1), ('pencolor', 'red')]

turtle.isdown()

Return True if pen is down, False if it’s up.

>>> turtle.penup()
>>> turtle.isdown()
False
>>> turtle.pendown()
>>> turtle.isdown()
True

24.1.3.4.2. Color control

turtle.pencolor(*args)

Return or set the pencolor.

Four input formats are allowed:

pencolor()

Return the current pencolor as color specification string or as a tuple (see example). May be used as input to another color/pencolor/fillcolor call.

pencolor(colorstring)

Set pencolor to colorstring, which is a Tk color specification string, such as "red", "yellow", or "#33cc8c".

pencolor((r, g, b))

Set pencolor to the RGB color represented by the tuple of r, g, and b. Each of r, g, and b must be in the range 0..colormode, where colormode is either 1.0 or 255 (see colormode()).

pencolor(r, g, b)

Set pencolor to the RGB color represented by r, g, and b. Each of r, g, and b must be in the range 0..colormode.

If turtleshape is a polygon, the outline of that polygon is drawn with the newly set pencolor.

>>> colormode()
1.0
>>> turtle.pencolor()
'red'
>>> turtle.pencolor("brown")
>>> turtle.pencolor()
'brown'
>>> tup = (0.2, 0.8, 0.55)
>>> turtle.pencolor(tup)
>>> turtle.pencolor()
(0.2, 0.8, 0.5490196078431373)
>>> colormode(255)
>>> turtle.pencolor()
(51.0, 204.0, 140.0)
>>> turtle.pencolor('#32c18f')
>>> turtle.pencolor()
(50.0, 193.0, 143.0)

turtle.fillcolor(*args)

Return or set the fillcolor.

Four input formats are allowed:

fillcolor()

Return the current fillcolor as color specification string, possibly in tuple format (see example). May be used as input to another color/pencolor/fillcolor call.

fillcolor(colorstring)

Set fillcolor to colorstring, which is a Tk color specification string, such as "red", "yellow", or "#33cc8c".

fillcolor((r, g, b))

Set fillcolor to the RGB color represented by the tuple of r, g, and b. Each of r, g, and b must be in the range 0..colormode, where colormode is either 1.0 or 255 (see colormode()).

fillcolor(r, g, b)

Set fillcolor to the RGB color represented by r, g, and b. Each of r, g, and b must be in the range 0..colormode.

If turtleshape is a polygon, the interior of that polygon is drawn with the newly set fillcolor.

>>> turtle.fillcolor("violet")
>>> turtle.fillcolor()
'violet'
>>> col = turtle.pencolor()
>>> col
(50.0, 193.0, 143.0)
>>> turtle.fillcolor(col)
>>> turtle.fillcolor()
(50.0, 193.0, 143.0)
>>> turtle.fillcolor('#ffffff')
>>> turtle.fillcolor()
(255.0, 255.0, 255.0)

turtle.color(*args)

Return or set pencolor and fillcolor.

Several input formats are allowed. They use 0 to 3 arguments as follows:

color()

Return the current pencolor and the current fillcolor as a pair of color specification strings or tuples as returned by pencolor() and fillcolor().

color(colorstring), color((r,g,b)), color(r,g,b)

Inputs as in pencolor(), set both, fillcolor and pencolor, to the given value.

color(colorstring1, colorstring2), color((r1,g1,b1), (r2,g2,b2))

Equivalent to pencolor(colorstring1) and fillcolor(colorstring2) and analogously if the other input format is used.

If turtleshape is a polygon, outline and interior of that polygon is drawn with the newly set colors.

>>> turtle.color("red", "green")
>>> turtle.color()
('red', 'green')
>>> color("#285078", "#a0c8f0")
>>> color()
((40.0, 80.0, 120.0), (160.0, 200.0, 240.0))

See also: Screen method colormode().

24.1.3.4.3. Filling

turtle.filling()

Return fillstate (True if filling, False else).

>>> turtle.begin_fill()
>>> if turtle.filling():
...    turtle.pensize(5)
... else:
...    turtle.pensize(3)

turtle.begin_fill()

To be called just before drawing a shape to be filled.

turtle.end_fill()

Fill the shape drawn after the last call to begin_fill().

>>> turtle.color("black", "red")
>>> turtle.begin_fill()
>>> turtle.circle(80)
>>> turtle.end_fill()

24.1.3.4.4. More drawing control

turtle.reset()

Delete the turtle’s drawings from the screen, re-center the turtle and set variables to the default values.

>>> turtle.goto(0,-22)
>>> turtle.left(100)
>>> turtle.position()
(0.00,-22.00)
>>> turtle.heading()
100.0
>>> turtle.reset()
>>> turtle.position()
(0.00,0.00)
>>> turtle.heading()
0.0

turtle.clear()

Delete the turtle’s drawings from the screen. Do not move turtle. State and position of the turtle as well as drawings of other turtles are not affected.

turtle.write(arg, move=False, align="left", font=("Arial", 8, "normal"))

Paramètres

arg – object to be written to the TurtleScreen

move – True/False

align – one of the strings « left », « center » or right »

font – a triple (fontname, fontsize, fonttype)

Write text - the string representation of arg - at the current turtle position according to align (« left », « center » or right ») and with the given font. If move is true, the pen is moved to the bottom-right corner of the text. By default, move is False.

>>> turtle.write("Home = ", True, align="center")
>>> turtle.write((0,0), True)

24.1.3.5. Turtle state

24.1.3.5.1. Visibility

turtle.hideturtle()

turtle.ht()

Make the turtle invisible. It’s a good idea to do this while you’re in the middle of doing some complex drawing, because hiding the turtle speeds up the drawing observably.

>>> turtle.hideturtle()

turtle.showturtle()

turtle.st()

Make the turtle visible.

>>> turtle.showturtle()

turtle.isvisible()

Return True if the Turtle is shown, False if it’s hidden.

>>> turtle.hideturtle()
>>> turtle.isvisible()
False
>>> turtle.showturtle()
>>> turtle.isvisible()
True

24.1.3.5.2. Appearance

turtle.shape(name=None)

Paramètres

name – a string which is a valid shapename

Set turtle shape to shape with given name or, if name is not given, return name of current shape. Shape with name must exist in the TurtleScreen’s shape dictionary. Initially there are the following polygon shapes: « arrow », « turtle », « circle », « square », « triangle », « classic ». To learn about how to deal with shapes see Screen method register_shape().

>>> turtle.shape()
'classic'
>>> turtle.shape("turtle")
>>> turtle.shape()
'turtle'

turtle.resizemode(rmode=None)

Paramètres

rmode – one of the strings « auto », « user », « noresize »

Set resizemode to one of the values: « auto », « user », « noresize ». If rmode is not given, return current resizemode. Different resizemodes have the following effects:

« auto »: adapts the appearance of the turtle corresponding to the value of pensize.

« user »: adapts the appearance of the turtle according to the values of stretchfactor and outlinewidth (outline), which are set by shapesize().

« noresize »: no adaption of the turtle’s appearance takes place.

resizemode(« user ») is called by shapesize() when used with arguments.

>>> turtle.resizemode()
'noresize'
>>> turtle.resizemode("auto")
>>> turtle.resizemode()
'auto'

turtle.shapesize(stretch_wid=None, stretch_len=None, outline=None)

turtle.turtlesize(stretch_wid=None, stretch_len=None, outline=None)

Paramètres

stretch_wid – positive number

stretch_len – positive number

outline – positive number

Return or set the pen’s attributes x/y-stretchfactors and/or outline. Set resizemode to « user ». If and only if resizemode is set to « user », the turtle will be displayed stretched according to its stretchfactors: stretch_wid is stretchfactor perpendicular to its orientation, stretch_len is stretchfactor in direction of its orientation, outline determines the width of the shapes’s outline.

>>> turtle.shapesize()
(1.0, 1.0, 1)
>>> turtle.resizemode("user")
>>> turtle.shapesize(5, 5, 12)
>>> turtle.shapesize()
(5, 5, 12)
>>> turtle.shapesize(outline=8)
>>> turtle.shapesize()
(5, 5, 8)

turtle.shearfactor(shear=None)

Paramètres

shear – number (optional)

Set or return the current shearfactor. Shear the turtleshape according to the given shearfactor shear, which is the tangent of the shear angle. Do not change the turtle’s heading (direction of movement). If shear is not given: return the current shearfactor, i. e. the tangent of the shear angle, by which lines parallel to the heading of the turtle are sheared.

>>> turtle.shape("circle")
>>> turtle.shapesize(5,2)
>>> turtle.shearfactor(0.5)
>>> turtle.shearfactor()
0.5

turtle.tilt(angle)

Paramètres

angle – a number

Rotate the turtleshape by angle from its current tilt-angle, but do not change the turtle’s heading (direction of movement).

>>> turtle.reset()
>>> turtle.shape("circle")
>>> turtle.shapesize(5,2)
>>> turtle.tilt(30)
>>> turtle.fd(50)
>>> turtle.tilt(30)
>>> turtle.fd(50)

turtle.settiltangle(angle)

Paramètres

angle – a number

Rotate the turtleshape to point in the direction specified by angle, regardless of its current tilt-angle. Do not change the turtle’s heading (direction of movement).

>>> turtle.reset()
>>> turtle.shape("circle")
>>> turtle.shapesize(5,2)
>>> turtle.settiltangle(45)
>>> turtle.fd(50)
>>> turtle.settiltangle(-45)
>>> turtle.fd(50)

Obsolète depuis la version 3.1.

turtle.tiltangle(angle=None)

Paramètres

angle – a number (optional)

Set or return the current tilt-angle. If angle is given, rotate the turtleshape to point in the direction specified by angle, regardless of its current tilt-angle. Do not change the turtle’s heading (direction of movement). If angle is not given: return the current tilt-angle, i. e. the angle between the orientation of the turtleshape and the heading of the turtle (its direction of movement).

>>> turtle.reset()
>>> turtle.shape("circle")
>>> turtle.shapesize(5,2)
>>> turtle.tilt(45)
>>> turtle.tiltangle()
45.0

turtle.shapetransform(t11=None, t12=None, t21=None, t22=None)

Paramètres

t11 – a number (optional)

t12 – a number (optional)

t21 – a number (optional)

t12 – a number (optional)

Set or return the current transformation matrix of the turtle shape.

If none of the matrix elements are given, return the transformation matrix as a tuple of 4 elements. Otherwise set the given elements and transform the turtleshape according to the matrix consisting of first row t11, t12 and second row t21, 22. The determinant t11 * t22 - t12 * t21 must not be zero, otherwise an error is raised. Modify stretchfactor, shearfactor and tiltangle according to the given matrix.

>>> turtle = Turtle()
>>> turtle.shape("square")
>>> turtle.shapesize(4,2)
>>> turtle.shearfactor(-0.5)
>>> turtle.shapetransform()
(4.0, -1.0, -0.0, 2.0)

turtle.get_shapepoly()

Return the current shape polygon as tuple of coordinate pairs. This can be used to define a new shape or components of a compound shape.

>>> turtle.shape("square")
>>> turtle.shapetransform(4, -1, 0, 2)
>>> turtle.get_shapepoly()
((50, -20), (30, 20), (-50, 20), (-30, -20))

24.1.3.6. Using events

turtle.onclick(fun, btn=1, add=None)

Paramètres

fun – a function with two arguments which will be called with the coordinates of the clicked point on the canvas

btn – number of the mouse-button, defaults to 1 (left mouse button)

add – True or False – if True, a new binding will be added, otherwise it will replace a former binding

Bind fun to mouse-click events on this turtle. If fun is None, existing bindings are removed. Example for the anonymous turtle, i.e. the procedural way:

>>> def turn(x, y):
...     left(180)
...
>>> onclick(turn)  # Now clicking into the turtle will turn it.
>>> onclick(None)  # event-binding will be removed

turtle.onrelease(fun, btn=1, add=None)

Paramètres

fun – a function with two arguments which will be called with the coordinates of the clicked point on the canvas

btn – number of the mouse-button, defaults to 1 (left mouse button)

add – True or False – if True, a new binding will be added, otherwise it will replace a former binding

Bind fun to mouse-button-release events on this turtle. If fun is None, existing bindings are removed.

>>> class MyTurtle(Turtle):
...     def glow(self,x,y):
...         self.fillcolor("red")
...     def unglow(self,x,y):
...         self.fillcolor("")
...
>>> turtle = MyTurtle()
>>> turtle.onclick(turtle.glow)     # clicking on turtle turns fillcolor red,
>>> turtle.onrelease(turtle.unglow) # releasing turns it to transparent.

turtle.ondrag(fun, btn=1, add=None)

Paramètres

fun – a function with two arguments which will be called with the coordinates of the clicked point on the canvas

btn – number of the mouse-button, defaults to 1 (left mouse button)

add – True or False – if True, a new binding will be added, otherwise it will replace a former binding

Bind fun to mouse-move events on this turtle. If fun is None, existing bindings are removed.

Remark: Every sequence of mouse-move-events on a turtle is preceded by a mouse-click event on that turtle.

>>> turtle.ondrag(turtle.goto)

Subsequently, clicking and dragging the Turtle will move it across the screen thereby producing handdrawings (if pen is down).

24.1.3.7. Special Turtle methods

turtle.begin_poly()

Start recording the vertices of a polygon. Current turtle position is first vertex of polygon.

turtle.end_poly()

Stop recording the vertices of a polygon. Current turtle position is last vertex of polygon. This will be connected with the first vertex.

turtle.get_poly()

Return the last recorded polygon.

>>> turtle.home()
>>> turtle.begin_poly()
>>> turtle.fd(100)
>>> turtle.left(20)
>>> turtle.fd(30)
>>> turtle.left(60)
>>> turtle.fd(50)
>>> turtle.end_poly()
>>> p = turtle.get_poly()
>>> register_shape("myFavouriteShape", p)

turtle.clone()

Create and return a clone of the turtle with same position, heading and turtle properties.

>>> mick = Turtle()
>>> joe = mick.clone()

turtle.getturtle()

turtle.getpen()

Return the Turtle object itself. Only reasonable use: as a function to return the « anonymous turtle »:

>>> pet = getturtle()
>>> pet.fd(50)
>>> pet
<turtle.Turtle object at 0x...>

turtle.getscreen()

Return the TurtleScreen object the turtle is drawing on. TurtleScreen methods can then be called for that object.

>>> ts = turtle.getscreen()
>>> ts
<turtle._Screen object at 0x...>
>>> ts.bgcolor("pink")

turtle.setundobuffer(size)

Paramètres

size – an integer or None

Set or disable undobuffer. If size is an integer an empty undobuffer of given size is installed. size gives the maximum number of turtle actions that can be undone by the undo() method/function. If size is None, the undobuffer is disabled.

>>> turtle.setundobuffer(42)

turtle.undobufferentries()

Return number of entries in the undobuffer.

>>> while undobufferentries():
...     undo()

24.1.3.8. Compound shapes

To use compound turtle shapes, which consist of several polygons of different color, you must use the helper class Shape explicitly as described below:

Create an empty Shape object of type « compound ».

Add as many components to this object as desired, using the addcomponent() method.

Par exemple :

>>> s = Shape("compound")
>>> poly1 = ((0,0),(10,-5),(0,10),(-10,-5))
>>> s.addcomponent(poly1, "red", "blue")
>>> poly2 = ((0,0),(10,-5),(-10,-5))
>>> s.addcomponent(poly2, "blue", "red")

Now add the Shape to the Screen’s shapelist and use it:

>>> register_shape("myshape", s)
>>> shape("myshape")

Note

The Shape class is used internally by the register_shape() method in different ways. The application programmer has to deal with the Shape class only when using compound shapes like shown above!

24.1.4. Methods of TurtleScreen/Screen and corresponding functions

Most of the examples in this section refer to a TurtleScreen instance called screen.

24.1.4.1. Window control

turtle.bgcolor(*args)

Paramètres

args – a color string or three numbers in the range 0..colormode or a 3-tuple of such numbers

Set or return background color of the TurtleScreen.

>>> screen.bgcolor("orange")
>>> screen.bgcolor()
'orange'
>>> screen.bgcolor("#800080")
>>> screen.bgcolor()
(128.0, 0.0, 128.0)

turtle.bgpic(picname=None)

Paramètres

picname – a string, name of a gif-file or "nopic", or None

Set background image or return name of current backgroundimage. If picname is a filename, set the corresponding image as background. If picname is "nopic", delete background image, if present. If picname is None, return the filename of the current backgroundimage.

>>> screen.bgpic()
'nopic'
>>> screen.bgpic("landscape.gif")
>>> screen.bgpic()
"landscape.gif"

turtle.clear()

turtle.clearscreen()

Delete all drawings and all turtles from the TurtleScreen. Reset the now empty TurtleScreen to its initial state: white background, no background image, no event bindings and tracing on.

Note

This TurtleScreen method is available as a global function only under the name clearscreen. The global function clear is a different one derived from the Turtle method clear.

turtle.reset()

turtle.resetscreen()

Reset all Turtles on the Screen to their initial state.

Note

This TurtleScreen method is available as a global function only under the name resetscreen. The global function reset is another one derived from the Turtle method reset.

turtle.screensize(canvwidth=None, canvheight=None, bg=None)

Paramètres

canvwidth – positive integer, new width of canvas in pixels

canvheight – positive integer, new height of canvas in pixels

bg – colorstring or color-tuple, new background color

If no arguments are given, return current (canvaswidth, canvasheight). Else resize the canvas the turtles are drawing on. Do not alter the drawing window. To observe hidden parts of the canvas, use the scrollbars. With this method, one can make visible those parts of a drawing which were outside the canvas before.

>>> screen.screensize()
(400, 300)
>>> screen.screensize(2000,1500)
>>> screen.screensize()
(2000, 1500)

e.g. to search for an erroneously escaped turtle ;-)

turtle.setworldcoordinates(llx, lly, urx, ury)

Paramètres

llx – a number, x-coordinate of lower left corner of canvas

lly – a number, y-coordinate of lower left corner of canvas

urx – a number, x-coordinate of upper right corner of canvas

ury – a number, y-coordinate of upper right corner of canvas

Set up user-defined coordinate system and switch to mode « world » if necessary. This performs a screen.reset(). If mode « world » is already active, all drawings are redrawn according to the new coordinates.

ATTENTION: in user-defined coordinate systems angles may appear distorted.

>>> screen.reset()
>>> screen.setworldcoordinates(-50,-7.5,50,7.5)
>>> for _ in range(72):
...     left(10)
...
>>> for _ in range(8):
...     left(45); fd(2)   # a regular octagon

24.1.4.2. Animation control

turtle.delay(delay=None)

Paramètres

delay – positive integer

Set or return the drawing delay in milliseconds. (This is approximately the time interval between two consecutive canvas updates.) The longer the drawing delay, the slower the animation.

Optional argument:

>>> screen.delay()
10
>>> screen.delay(5)
>>> screen.delay()
5

turtle.tracer(n=None, delay=None)

Paramètres

n – nonnegative integer

delay – nonnegative integer

Turn turtle animation on/off and set delay for update drawings. If n is given, only each n-th regular screen update is really performed. (Can be used to accelerate the drawing of complex graphics.) When called without arguments, returns the currently stored value of n. Second argument sets delay value (see delay()).

>>> screen.tracer(8, 25)
>>> dist = 2
>>> for i in range(200):
...     fd(dist)
...     rt(90)
...     dist += 2

turtle.update()

Perform a TurtleScreen update. To be used when tracer is turned off.

See also the RawTurtle/Turtle method speed().

24.1.4.3. Using screen events

turtle.listen(xdummy=None, ydummy=None)

Set focus on TurtleScreen (in order to collect key-events). Dummy arguments are provided in order to be able to pass listen() to the onclick method.

turtle.onkey(fun, key)

turtle.onkeyrelease(fun, key)

Paramètres

fun – a function with no arguments or None

key – a string: key (e.g. « a ») or key-symbol (e.g. « space »)

Bind fun to key-release event of key. If fun is None, event bindings are removed. Remark: in order to be able to register key-events, TurtleScreen must have the focus. (See method listen().)

>>> def f():
...     fd(50)
...     lt(60)
...
>>> screen.onkey(f, "Up")
>>> screen.listen()

turtle.onkeypress(fun, key=None)

Paramètres

fun – a function with no arguments or None

key – a string: key (e.g. « a ») or key-symbol (e.g. « space »)

Bind fun to key-press event of key if key is given, or to any key-press-event if no key is given. Remark: in order to be able to register key-events, TurtleScreen must have focus. (See method listen().)

>>> def f():
...     fd(50)
...
>>> screen.onkey(f, "Up")
>>> screen.listen()

turtle.onclick(fun, btn=1, add=None)

turtle.onscreenclick(fun, btn=1, add=None)

Paramètres

fun – a function with two arguments which will be called with the coordinates of the clicked point on the canvas

btn – number of the mouse-button, defaults to 1 (left mouse button)

add – True or False – if True, a new binding will be added, otherwise it will replace a former binding

Bind fun to mouse-click events on this screen. If fun is None, existing bindings are removed.

Example for a TurtleScreen instance named screen and a Turtle instance named turtle:

>>> screen.onclick(turtle.goto) # Subsequently clicking into the TurtleScreen will
>>>                             # make the turtle move to the clicked point.
>>> screen.onclick(None)        # remove event binding again

Note

This TurtleScreen method is available as a global function only under the name onscreenclick. The global function onclick is another one derived from the Turtle method onclick.

turtle.ontimer(fun, t=0)

Paramètres

fun – a function with no arguments

t – a number >= 0

Install a timer that calls fun after t milliseconds.

>>> running = True
>>> def f():
...     if running:
...         fd(50)
...         lt(60)
...         screen.ontimer(f, 250)
>>> f()   ### makes the turtle march around
>>> running = False

turtle.mainloop()

turtle.done()

Starts event loop - calling Tkinter’s mainloop function. Must be the last statement in a turtle graphics program. Must not be used if a script is run from within IDLE in -n mode (No subprocess) - for interactive use of turtle graphics.

>>> screen.mainloop()

24.1.4.4. Input methods

turtle.textinput(title, prompt)

Paramètres

title – string

prompt – string

Pop up a dialog window for input of a string. Parameter title is the title of the dialog window, prompt is a text mostly describing what information to input. Return the string input. If the dialog is canceled, return None.

>>> screen.textinput("NIM", "Name of first player:")

turtle.numinput(title, prompt, default=None, minval=None, maxval=None)

Paramètres

title – string

prompt – string

default – number (optional)

minval – number (optional)

maxval – number (optional)

Pop up a dialog window for input of a number. title is the title of the dialog window, prompt is a text mostly describing what numerical information to input. default: default value, minval: minimum value for input, maxval: maximum value for input The number input must be in the range minval .. maxval if these are given. If not, a hint is issued and the dialog remains open for correction. Return the number input. If the dialog is canceled, return None.

>>> screen.numinput("Poker", "Your stakes:", 1000, minval=10, maxval=10000)

24.1.4.5. Settings and special methods

turtle.mode(mode=None)

Paramètres

mode – one of the strings « standard », « logo » or « world »

Set turtle mode (« standard », « logo » or « world ») and perform reset. If mode is not given, current mode is returned.

Mode « standard » is compatible with old turtle. Mode « logo » is compatible with most Logo turtle graphics. Mode « world » uses user-defined « world coordinates ». Attention: in this mode angles appear distorted if x/y unit-ratio doesn’t equal 1.

Mode

Initial turtle heading

positive angles

« standard »

to the right (east)

counterclockwise

« logo »

upward (north)

clockwise

>>> mode("logo")   # resets turtle heading to north
>>> mode()
'logo'

turtle.colormode(cmode=None)

Paramètres

cmode – one of the values 1.0 or 255

Return the colormode or set it to 1.0 or 255. Subsequently r, g, b values of color triples have to be in the range 0..cmode.

>>> screen.colormode(1)
>>> turtle.pencolor(240, 160, 80)
Traceback (most recent call last):
     ...
TurtleGraphicsError: bad color sequence: (240, 160, 80)
>>> screen.colormode()
1.0
>>> screen.colormode(255)
>>> screen.colormode()
255
>>> turtle.pencolor(240,160,80)

turtle.getcanvas()

Return the Canvas of this TurtleScreen. Useful for insiders who know what to do with a Tkinter Canvas.

>>> cv = screen.getcanvas()
>>> cv
<turtle.ScrolledCanvas object ...>

turtle.getshapes()

Return a list of names of all currently available turtle shapes.

>>> screen.getshapes()
['arrow', 'blank', 'circle', ..., 'turtle']

turtle.register_shape(name, shape=None)

turtle.addshape(name, shape=None)

There are three different ways to call this function:

name is the name of a gif-file and shape is None: Install the corresponding image shape.

>>> screen.register_shape("turtle.gif")

Note

Image shapes do not rotate when turning the turtle, so they do not display the heading of the turtle!

name is an arbitrary string and shape is a tuple of pairs of coordinates: Install the corresponding polygon shape.

>>> screen.register_shape("triangle", ((5,-3), (0,5), (-5,-3)))

name is an arbitrary string and shape is a (compound) Shape object: Install the corresponding compound shape.

Add a turtle shape to TurtleScreen’s shapelist. Only thusly registered shapes can be used by issuing the command shape(shapename).

turtle.turtles()

Return the list of turtles on the screen.

>>> for turtle in screen.turtles():
...     turtle.color("red")

turtle.window_height()

Return the height of the turtle window.

>>> screen.window_height()
480

turtle.window_width()

Return the width of the turtle window.

>>> screen.window_width()
640

24.1.4.6. Methods specific to Screen, not inherited from TurtleScreen

turtle.bye()

Shut the turtlegraphics window.

turtle.exitonclick()

Bind bye() method to mouse clicks on the Screen.

If the value « using_IDLE » in the configuration dictionary is False (default value), also enter mainloop. Remark: If IDLE with the -n switch (no subprocess) is used, this value should be set to True in turtle.cfg. In this case IDLE’s own mainloop is active also for the client script.

turtle.setup(width=_CFG["width"], height=_CFG["height"], startx=_CFG["leftright"], starty=_CFG["topbottom"])

Set the size and position of the main window. Default values of arguments are stored in the configuration dictionary and can be changed via a turtle.cfg file.

Paramètres

width – if an integer, a size in pixels, if a float, a fraction of the screen; default is 50% of screen

height – if an integer, the height in pixels, if a float, a fraction of the screen; default is 75% of screen

startx – if positive, starting position in pixels from the left edge of the screen, if negative from the right edge, if None, center window horizontally

starty – if positive, starting position in pixels from the top edge of the screen, if negative from the bottom edge, if None, center window vertically

>>> screen.setup (width=200, height=200, startx=0, starty=0)
>>>              # sets window to 200x200 pixels, in upper left of screen
>>> screen.setup(width=.75, height=0.5, startx=None, starty=None)
>>>              # sets window to 75% of screen by 50% of screen and centers

turtle.title(titlestring)

Paramètres

titlestring – a string that is shown in the titlebar of the turtle graphics window

Set title of turtle window to titlestring.

>>> screen.title("Welcome to the turtle zoo!")

24.1.5. Public classes

class turtle.RawTurtle(canvas)

class turtle.RawPen(canvas)

Paramètres

canvas – a tkinter.Canvas, a ScrolledCanvas or a TurtleScreen

Create a turtle. The turtle has all methods described above as « methods of Turtle/RawTurtle ».

class turtle.Turtle

Subclass of RawTurtle, has the same interface but draws on a default Screen object created automatically when needed for the first time.

class turtle.TurtleScreen(cv)

Paramètres

cv – a tkinter.Canvas

Provides screen oriented methods like setbg() etc. that are described above.

class turtle.Screen

Subclass of TurtleScreen, with four methods added.

class turtle.ScrolledCanvas(master)

Paramètres

master – some Tkinter widget to contain the ScrolledCanvas, i.e. a Tkinter-canvas with scrollbars added

Used by class Screen, which thus automatically provides a ScrolledCanvas as playground for the turtles.

class turtle.Shape(type_, data)

Paramètres

type_ – one of the strings « polygon », « image », « compound »

Data structure modeling shapes. The pair (type_, data) must follow this specification:

type_

data

« polygon »

a polygon-tuple, i.e. a tuple of pairs of coordinates

« image »

an image (in this form only used internally!)

« compound »

None (a compound shape has to be constructed using the addcomponent() method)

addcomponent(poly, fill, outline=None)

Paramètres

poly – a polygon, i.e. a tuple of pairs of numbers

fill – a color the poly will be filled with

outline – a color for the poly’s outline (if given)

Exemple :

>>> poly = ((0,0),(10,-5),(0,10),(-10,-5))
>>> s = Shape("compound")
>>> s.addcomponent(poly, "red", "blue")
>>> # ... add more components and then use register_shape()

See Compound shapes.

class turtle.Vec2D(x, y)

A two-dimensional vector class, used as a helper class for implementing turtle graphics. May be useful for turtle graphics programs too. Derived from tuple, so a vector is a tuple!

Provides (for a, b vectors, k number):

a + b vector addition

a - b vector subtraction

a * b inner product

k * a and a * k multiplication with scalar

abs(a) absolute value of a

a.rotate(angle) rotation

24.1.6. Help and configuration

24.1.6.1. How to use help

The public methods of the Screen and Turtle classes are documented extensively via docstrings. So these can be used as online-help via the Python help facilities:

When using IDLE, tooltips show the signatures and first lines of the docstrings of typed in function-/method calls.

Calling help() on methods or functions displays the docstrings:

>>> help(Screen.bgcolor)
Help on method bgcolor in module turtle:

bgcolor(self, *args) unbound turtle.Screen method
    Set or return backgroundcolor of the TurtleScreen.

    Arguments (if given): a color string or three numbers
    in the range 0..colormode or a 3-tuple of such numbers.

      >>> screen.bgcolor("orange")
      >>> screen.bgcolor()
      "orange"
      >>> screen.bgcolor(0.5,0,0.5)
      >>> screen.bgcolor()
      "#800080"

>>> help(Turtle.penup)
Help on method penup in module turtle:

penup(self) unbound turtle.Turtle method
    Pull the pen up -- no drawing when moving.

    Aliases: penup | pu | up

    No argument

    >>> turtle.penup()

The docstrings of the functions which are derived from methods have a modified form:

>>> help(bgcolor)
Help on function bgcolor in module turtle:

bgcolor(*args)
    Set or return backgroundcolor of the TurtleScreen.

    Arguments (if given): a color string or three numbers
    in the range 0..colormode or a 3-tuple of such numbers.

    Example::

      >>> bgcolor("orange")
      >>> bgcolor()
      "orange"
      >>> bgcolor(0.5,0,0.5)
      >>> bgcolor()
      "#800080"

>>> help(penup)
Help on function penup in module turtle:

penup()
    Pull the pen up -- no drawing when moving.

    Aliases: penup | pu | up

    No argument

    Example:
    >>> penup()

These modified docstrings are created automatically together with the function definitions that are derived from the methods at import time.

24.1.6.2. Translation of docstrings into different languages

There is a utility to create a dictionary the keys of which are the method names and the values of which are the docstrings of the public methods of the classes Screen and Turtle.

turtle.write_docstringdict(filename="turtle_docstringdict")

Paramètres

filename – a string, used as filename

Create and write docstring-dictionary to a Python script with the given filename. This function has to be called explicitly (it is not used by the turtle graphics classes). The docstring dictionary will be written to the Python script filename.py. It is intended to serve as a template for translation of the docstrings into different languages.

If you (or your students) want to use turtle with online help in your native language, you have to translate the docstrings and save the resulting file as e.g. turtle_docstringdict_german.py.

If you have an appropriate entry in your turtle.cfg file this dictionary will be read in at import time and will replace the original English docstrings.

At the time of this writing there are docstring dictionaries in German and in Italian. (Requests please to glingl@aon.at.)

24.1.6.3. How to configure Screen and Turtles

The built-in default configuration mimics the appearance and behaviour of the old turtle module in order to retain best possible compatibility with it.

If you want to use a different configuration which better reflects the features of this module or which better fits to your needs, e.g. for use in a classroom, you can prepare a configuration file turtle.cfg which will be read at import time and modify the configuration according to its settings.

The built in configuration would correspond to the following turtle.cfg:

width = 0.5
height = 0.75
leftright = None
topbottom = None
canvwidth = 400
canvheight = 300
mode = standard
colormode = 1.0
delay = 10
undobuffersize = 1000
shape = classic
pencolor = black
fillcolor = black
resizemode = noresize
visible = True
language = english
exampleturtle = turtle
examplescreen = screen
title = Python Turtle Graphics
using_IDLE = False

Short explanation of selected entries:

The first four lines correspond to the arguments of the Screen.setup() method.

Line 5 and 6 correspond to the arguments of the method Screen.screensize().

shape can be any of the built-in shapes, e.g: arrow, turtle, etc. For more info try help(shape).

If you want to use no fillcolor (i.e. make the turtle transparent), you have to write fillcolor = "" (but all nonempty strings must not have quotes in the cfg-file).

If you want to reflect the turtle its state, you have to use resizemode = auto.

If you set e.g. language = italian the docstringdict turtle_docstringdict_italian.py will be loaded at import time (if present on the import path, e.g. in the same directory as turtle.

The entries exampleturtle and examplescreen define the names of these objects as they occur in the docstrings. The transformation of method-docstrings to function-docstrings will delete these names from the docstrings.

using_IDLE: Set this to True if you regularly work with IDLE and its -n switch (« no subprocess »). This will prevent exitonclick() to enter the mainloop.

There can be a turtle.cfg file in the directory where turtle is stored and an additional one in the current working directory. The latter will override the settings of the first one.

The Lib/turtledemo directory contains a turtle.cfg file. You can study it as an example and see its effects when running the demos (preferably not from within the demo-viewer).

24.1.7. turtledemo — Demo scripts

The turtledemo package includes a set of demo scripts. These scripts can be run and viewed using the supplied demo viewer as follows:

python -m turtledemo

Alternatively, you can run the demo scripts individually. For example,

python -m turtledemo.bytedesign

The turtledemo package directory contains:

A demo viewer __main__.py which can be used to view the sourcecode of the scripts and run them at the same time.

Multiple scripts demonstrating different features of the turtle module. Examples can be accessed via the Examples menu. They can also be run standalone.

A turtle.cfg file which serves as an example of how to write and use such files.

The demo scripts are:

Nom

Description

Features

bytedesign

complex classical turtle graphics pattern

tracer(), delay, update()

chaos

graphs Verhulst dynamics, shows that computer’s computations can generate results sometimes against the common sense expectations

world coordinates

clock

analog clock showing time of your computer

turtles as clock’s hands, ontimer

colormixer

experiment with r, g, b

ondrag()

forest

3 breadth-first trees

randomization

fractalcurves

Hilbert & Koch curves

recursion

lindenmayer

ethnomathematics (indian kolams)

L-System

minimal_hanoi

Towers of Hanoi

Rectangular Turtles as Hanoi discs (shape, shapesize)

nim

play the classical nim game with three heaps of sticks against the computer.

turtles as nimsticks, event driven (mouse, keyboard)

paint

super minimalistic drawing program

onclick()

peace

elementary

turtle: appearance and animation

penrose

aperiodic tiling with kites and darts

stamp()

planet_and_moon

simulation of gravitational system

compound shapes, Vec2D

round_dance

dancing turtles rotating pairwise in opposite direction

compound shapes, clone shapesize, tilt, get_shapepoly, update

sorting_animate

visual demonstration of different sorting methods

simple alignment, randomization

tree

a (graphical) breadth first tree (using generators)

clone()

two_canvases

simple design

turtles on two canvases

wikipedia

a pattern from the wikipedia article on turtle graphics

clone(), undo()

yinyang

another elementary example

circle()

Have fun!

24.1.8. Changes since Python 2.6

The methods Turtle.tracer(), Turtle.window_width() and Turtle.window_height() have been eliminated. Methods with these names and functionality are now available only as methods of Screen. The functions derived from these remain available. (In fact already in Python 2.6 these methods were merely duplications of the corresponding TurtleScreen/Screen-methods.)

The method Turtle.fill() has been eliminated. The behaviour of begin_fill() and end_fill() have changed slightly: now every filling-process must be completed with an end_fill() call.

A method Turtle.filling() has been added. It returns a boolean value: True if a filling process is under way, False otherwise. This behaviour corresponds to a fill() call without arguments in Python 2.6.

24.1.9. Changes since Python 3.0

The methods Turtle.shearfactor(), Turtle.shapetransform() and Turtle.get_shapepoly() have been added. Thus the full range of regular linear transforms is now available for transforming turtle shapes. Turtle.tiltangle() has been enhanced in functionality: it now can be used to get or set the tiltangle. Turtle.settiltangle() has been deprecated.

The method Screen.onkeypress() has been added as a complement to Screen.onkey() which in fact binds actions to the keyrelease event. Accordingly the latter has got an alias: Screen.onkeyrelease().

The method Screen.mainloop() has been added. So when working only with Screen and Turtle objects one must not additionally import mainloop() anymore.

Two input methods has been added Screen.textinput() and Screen.numinput(). These popup input dialogs and return strings and numbers respectively.

Two example scripts tdemo_nim.py and tdemo_round_dance.py have been added to the Lib/turtledemo directory.

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24.2. cmd — Interpréteurs en ligne de commande.

Code source: Lib/cmd.py [https://github.com/python/cpython/tree/3.6/Lib/cmd.py]

La Cmd fournit une base simple permettant d’écrire des interpréteurs en ligne de commande. Ceux-ci sont souvent utiles pour piloter des tests, pour des outils administratifs, et pour des prototypes destinés à être intégrés à une interface plus sophistiquée.

class cmd.Cmd(completekey='tab', stdin=None, stdout=None)

Une instance de Cmd ou d’une classe en héritant est un framework orienté ligne de commande. Il n’y a pas de bonne raison d’instancier Cmd directement. Elle est plutôt utile en tant que classe mère d’une classe-interprète que vous définirez afin d’hériter des méthodes de Cmd et d’encapsuler les opérations.

L’argument facultatif completekey est le nom readline d’une touche de complétion. Si completekey ne vaut pas None et que readline est disponible, la complétion de commandes est faite automatiquement.

Les arguments facultatifs stdin et stdout spécifient les objets-fichiers de lecture et d’écriture que l’instance de Cmd ou d’une classe fille utilisera comme entrée et sortie. Si ces arguments ne sont pas spécifiés, ils prendront comme valeur par défaut sys.stdin et sys.stdout.

Si vous souhaitez qu’un stdin donné soit utilisé, assurez-vous que l’attribut use_rawinput de l’instance vaille False, faute de quoi stdin sera ignoré.

24.2.1. Objets Cmd

Une instance de Cmd possède les méthodes suivantes :

Cmd.cmdloop(intro=None)

Affiche une invite de commande de manière répétée, accepte une entrée, soustrait un préfixe initial de l’entrée reçue et envoie aux méthodes d’opération la partie restante de l’entrée reçue.

L’argument facultatif est une bannière ou chaîne de caractères d’introduction à afficher avant la première invite de commande (il redéfinit l’attribut de classe intro).

Si le module readline est chargé, l’entrée héritera automatiquement d’une édition d’historique similaire à bash (Par exemple, Control-P reviendra à la dernière commande, Control-N avancera à la suivante, Control-F déplace le curseur vers la droite, Control-B déplace le curseur vers la gauche, etc…).

Une caractère de fin de fichier est transmis via la chaîne de caractères 'EOF'.

Une instance d’un interpréteur reconnaîtra un nom de commande foo si et seulement si celle-ci possède une méthode do_foo(). Les lignes commençant par le caractère '?' sont un cas particulier: elles sont envoyées à la méthode do_help(). Les lignes commençant par le caractère '!' sont également un cas particulier: elles sont envoyées à la méthode do_shell() (si une telle méthode est définie).

Cette méthode ne s’arrêtera que lorsque postcmd() renverra une valeur vraie. L’argument stop de postcmd() est la valeur de retour de la méthode do_*() correspondant à la commande.

Si la complétion est activée, la complétion de commandes sera faite automatiquement; et la complétion d’arguments sera faite en appelant complete_foo() avec les arguments text, line, begidx, et endidx. text est le préfixe que nous cherchons à faire coïncider: toutes les valeurs renvoyées doivent commencer par ce préfixe. line est la ligne d’entrée actuelle sans les espaces blancs de début. begidx et endidx sont les index de début et de fin du préfixe, ils pourraient être utilisés pour fournir différentes complétions en fonction de la position de l’argument.

Toutes les classes filles de Cmd héritent d’une méthode do_help() prédéfinie. Cette méthode appellera la méthode help_bar() lorsqu’elle est appelée avec un argument 'bar'. Si celle-ci n’est pas définie, elle affichera la docstring de do_bar(), (si elle a une docstring). Sans argument, do_help() listera tous les sujets d’aide (c’est à dire, toutes les commandes avec une méthode help_\*() correspondante ou commande ayant une docstring, elle lisera aussi les commandes non documentées.

Cmd.onecmd(str)

Interprète l’argument comme si il avait été entré en réponse à l’invite de commande. Cette méthode peut être surchargée, mais ne devrait normalement pas avoir besoin de l’être; voir les méthodes precmd() et postcmd() pour altérer l’exécution d’une commande. La valeur de retour est un flag indiquant si l’interprétation de commandes par l’interpréteur devrait arrêter. S’il existe une méthode do_*() pour la commande str, la valeur de retour de cette méthode est renvoyée. Dans le cas contraire, la valeur de retour de la méthode default() est renvoyée.

Cmd.emptyline()

Méthode appelée quand une ligne vide est entrée en réponse à l’invite de commande. Si cette méthode n’est pas surchargée, elle répète la dernière commande non-vide entrée.

Cmd.default(line)

Méthode appelée lorsque le préfixe de commande d’une ligne entrée n’est pas reconnu. Si cette méthode n’est pas surchargée, elle affiche un message d’erreur et s’arrête.

Cmd.completedefault(text, line, begidx, endidx)

Méthode appelée pour compléter une ligne entrée quand aucune méthode complete_*() spécifique à la commande n’est disponible. Par défaut, elle renvoie une liste vide.

Cmd.precmd(line)

Méthode de rappel exécutée juste avant que la ligne de commande line ne soit interprétée, mais après que l’invite de commande ait été généré et affiché. Cette méthode existe afin d’être surchargée par des classes filles de Cmd. La valeur de retour est utilisée comme la commande qui sera exécutée par la méthode onecmd(). L’implémentation de precmd() peut réécrire la commande ou simplement renvoyer line sans modification.

Cmd.postcmd(stop, line)

Méthode de rappel exécutée juste après qu’une commande ait été exécutée. Cette méthode existe afin d’être surchargée par des classes filles de Cmd. line est la ligne de commande ayant été exécutée et *stop est un flag indiquant si l’exécution sera terminée après un appel à postcmd(). stop sera la valeur de retour de onecmd(). La valeur de retour de cette méthode sera utilisée comme nouvelle valeur pour le flag interne correspondant à stop. Renvoyer False permettra à l’interprétation de continuer.

Cmd.preloop()

Méthode de rappel exécutée une fois lorsque cmdloop() est appelée. Cette méthode existe afin d’être surchargée par des classes filles de Cmd.

Cmd.postloop()

Méthode de rappel exécutée une fois lorsque cmdloop() va s’arrêter. Cette méthode existe afin d’être surchargée par des classes filles de Cmd.

Les instances de classes filles de Cmd possèdent des variables d’instance publiques:

Cmd.prompt

L’invite de commande affiché pour solliciter une entrée.

Cmd.identchars

La chaîne de caractères acceptée en tant que préfixe de commande.

Cmd.lastcmd

Le dernier préfixe de commande non-vide vu.

Cmd.cmdqueue

Une liste de lignes entrées en file. La liste cmdqueue est vérifiée dans cmdloop() lorsqu’une nouvelle entrée est nécessitée; si elle n’est pas vide, ses éléments seront traités dans l’ordre, comme si ils avaient entrés dans l’invite de commande.

Cmd.intro

Une chaîne de caractères à afficher en introduction ou bannière. Peut être surchargée en passant un argument à la méthode cmdloop().

Cmd.doc_header

L’en-tête à afficher si la sortie de l’aide possède une section pour les commandes documentées.

Cmd.misc_header

L’en-tête à afficher si la sortie de l’aide possède une section pour divers sujets (c’est-à-dire qu’il existe des méthodes help_*() sans méthodes do_*() correspondantes).

Cmd.undoc_header

L’en-tête à afficher si la sortie de l’aide possède une section pour les commandes non documentées (c’est-à-dire qu’il existe des méthodes dop_*() sans méthodes help_*() correspondantes).

Cmd.ruler

Le caractère utilisé pour afficher des lignes de séparation sous les en-têtes de messages d’aide. Si il est vide, aucune ligne de séparation n’est affichée. Par défaut, ce caractère vaut '='.

Cmd.use_rawinput

Un flag, valant True par défaut. Si ce flag est vrai, cmdloop() utilise input() pour afficher une invite de commande et lire la prochaine commande; si il est faux, sys.stdout.write() et sys.stdin.readline() sont utilisées. (Cela signifie qu’en important readline sur les systèmes qui le supportent, l’interpréteur va automatiquement supporter une édition de ligne similaire à Emacs ainsi que des touches d’historique de commande).

24.2.2. Exemple

Le module cmd est utile pour produire des invites de commande permettant à l’utilisateur de travailler avec un programme de manière interactive.

Cette section présente un exemple simple de comment produire une invite de commande autour de quelques commandes du module turtle.

Des commandes turtle basiques telles que forward() sont ajoutées à une classe fille de Cmd avec la méthode appelée do_forward(). L’argument est converti en nombre et envoyé au module turtle. La docstring est utilisée dans l’utilitaire d’aide fourni par l’invite de commande.

L’exemple inclut également un utilitaire d’enregistrement et de playback implémenté avec la méthode precmd(), qui est responsable du passage de l’entrée en minuscules ainsi que d’écrire les commandes dans un fichier. La méthode do_playback() lit le fichier et ajoute les commandes enregistrées à cmdqueue pour être rejouées immédiatement :

import cmd, sys
from turtle import *

class TurtleShell(cmd.Cmd):
    intro = 'Welcome to the turtle shell.   Type help or ? to list commands.\n'
    prompt = '(turtle) '
    file = None

    # ----- basic turtle commands -----
    def do_forward(self, arg):
        'Move the turtle forward by the specified distance:  FORWARD 10'
        forward(*parse(arg))
    def do_right(self, arg):
        'Turn turtle right by given number of degrees:  RIGHT 20'
        right(*parse(arg))
    def do_left(self, arg):
        'Turn turtle left by given number of degrees:  LEFT 90'
        left(*parse(arg))
    def do_goto(self, arg):
        'Move turtle to an absolute position with changing orientation.  GOTO 100 200'
        goto(*parse(arg))
    def do_home(self, arg):
        'Return turtle to the home position:  HOME'
        home()
    def do_circle(self, arg):
        'Draw circle with given radius an options extent and steps:  CIRCLE 50'
        circle(*parse(arg))
    def do_position(self, arg):
        'Print the current turtle position:  POSITION'
        print('Current position is %d %d\n' % position())
    def do_heading(self, arg):
        'Print the current turtle heading in degrees:  HEADING'
        print('Current heading is %d\n' % (heading(),))
    def do_color(self, arg):
        'Set the color:  COLOR BLUE'
        color(arg.lower())
    def do_undo(self, arg):
        'Undo (repeatedly) the last turtle action(s):  UNDO'
    def do_reset(self, arg):
        'Clear the screen and return turtle to center:  RESET'
        reset()
    def do_bye(self, arg):
        'Stop recording, close the turtle window, and exit:  BYE'
        print('Thank you for using Turtle')
        self.close()
        bye()
        return True

    # ----- record and playback -----
    def do_record(self, arg):
        'Save future commands to filename:  RECORD rose.cmd'
        self.file = open(arg, 'w')
    def do_playback(self, arg):
        'Playback commands from a file:  PLAYBACK rose.cmd'
        self.close()
        with open(arg) as f:
            self.cmdqueue.extend(f.read().splitlines())
    def precmd(self, line):
        line = line.lower()
        if self.file and 'playback' not in line:
            print(line, file=self.file)
        return line
    def close(self):
        if self.file:
            self.file.close()
            self.file = None

def parse(arg):
    'Convert a series of zero or more numbers to an argument tuple'
    return tuple(map(int, arg.split()))

if __name__ == '__main__':
    TurtleShell().cmdloop()

Voici une session d’exemple avec l’invite de commande turtle. Elle montre les fonctions d’aide, utilise les lignes vides pour répéter des commandes et montre l’utilitaire de playback:

Welcome to the turtle shell.   Type help or ? to list commands.

(turtle) ?

Documented commands (type help <topic>):
========================================
bye     color    goto     home  playback  record  right
circle  forward  heading  left  position  reset   undo

(turtle) help forward
Move the turtle forward by the specified distance:  FORWARD 10
(turtle) record spiral.cmd
(turtle) position
Current position is 0 0

(turtle) heading
Current heading is 0

(turtle) reset
(turtle) circle 20
(turtle) right 30
(turtle) circle 40
(turtle) right 30
(turtle) circle 60
(turtle) right 30
(turtle) circle 80
(turtle) right 30
(turtle) circle 100
(turtle) right 30
(turtle) circle 120
(turtle) right 30
(turtle) circle 120
(turtle) heading
Current heading is 180

(turtle) forward 100
(turtle)
(turtle) right 90
(turtle) forward 100
(turtle)
(turtle) right 90
(turtle) forward 400
(turtle) right 90
(turtle) forward 500
(turtle) right 90
(turtle) forward 400
(turtle) right 90
(turtle) forward 300
(turtle) playback spiral.cmd
Current position is 0 0

Current heading is 0

Current heading is 180

(turtle) bye
Thank you for using Turtle

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24.3. shlex — Simple lexical analysis

Code source : Lib/shlex.py [https://github.com/python/cpython/tree/3.6/Lib/shlex.py]

The shlex class makes it easy to write lexical analyzers for simple syntaxes resembling that of the Unix shell. This will often be useful for writing minilanguages, (for example, in run control files for Python applications) or for parsing quoted strings.

The shlex module defines the following functions:

shlex.split(s, comments=False, posix=True)

Split the string s using shell-like syntax. If comments is False (the default), the parsing of comments in the given string will be disabled (setting the commenters attribute of the shlex instance to the empty string). This function operates in POSIX mode by default, but uses non-POSIX mode if the posix argument is false.

Note

Since the split() function instantiates a shlex instance, passing None for s will read the string to split from standard input.

shlex.quote(s)

Return a shell-escaped version of the string s. The returned value is a string that can safely be used as one token in a shell command line, for cases where you cannot use a list.

This idiom would be unsafe:

>>> filename = 'somefile; rm -rf ~'
>>> command = 'ls -l {}'.format(filename)
>>> print(command)  # executed by a shell: boom!
ls -l somefile; rm -rf ~

quote() lets you plug the security hole:

>>> command = 'ls -l {}'.format(quote(filename))
>>> print(command)
ls -l 'somefile; rm -rf ~'
>>> remote_command = 'ssh home {}'.format(quote(command))
>>> print(remote_command)
ssh home 'ls -l '"'"'somefile; rm -rf ~'"'"''

The quoting is compatible with UNIX shells and with split():

>>> remote_command = split(remote_command)
>>> remote_command
['ssh', 'home', "ls -l 'somefile; rm -rf ~'"]
>>> command = split(remote_command[-1])
>>> command
['ls', '-l', 'somefile; rm -rf ~']

Nouveau dans la version 3.3.

The shlex module defines the following class:

class shlex.shlex(instream=None, infile=None, posix=False, punctuation_chars=False)

A shlex instance or subclass instance is a lexical analyzer object. The initialization argument, if present, specifies where to read characters from. It must be a file-/stream-like object with read() and readline() methods, or a string. If no argument is given, input will be taken from sys.stdin. The second optional argument is a filename string, which sets the initial value of the infile attribute. If the instream argument is omitted or equal to sys.stdin, this second argument defaults to « stdin ». The posix argument defines the operational mode: when posix is not true (default), the shlex instance will operate in compatibility mode. When operating in POSIX mode, shlex will try to be as close as possible to the POSIX shell parsing rules. The punctuation_chars argument provides a way to make the behaviour even closer to how real shells parse. This can take a number of values: the default value, False, preserves the behaviour seen under Python 3.5 and earlier. If set to True, then parsing of the characters ();<>|& is changed: any run of these characters (considered punctuation characters) is returned as a single token. If set to a non-empty string of characters, those characters will be used as the punctuation characters. Any characters in the wordchars attribute that appear in punctuation_chars will be removed from wordchars. See Improved Compatibility with Shells for more information.

Modifié dans la version 3.6: The punctuation_chars parameter was added.

Voir aussi

Module configparser

Parser for configuration files similar to the Windows .ini files.

24.3.1. shlex Objects

A shlex instance has the following methods:

shlex.get_token()

Return a token. If tokens have been stacked using push_token(), pop a token off the stack. Otherwise, read one from the input stream. If reading encounters an immediate end-of-file, eof is returned (the empty string ('') in non-POSIX mode, and None in POSIX mode).

shlex.push_token(str)

Push the argument onto the token stack.

shlex.read_token()

Read a raw token. Ignore the pushback stack, and do not interpret source requests. (This is not ordinarily a useful entry point, and is documented here only for the sake of completeness.)

shlex.sourcehook(filename)

When shlex detects a source request (see source below) this method is given the following token as argument, and expected to return a tuple consisting of a filename and an open file-like object.

Normally, this method first strips any quotes off the argument. If the result is an absolute pathname, or there was no previous source request in effect, or the previous source was a stream (such as sys.stdin), the result is left alone. Otherwise, if the result is a relative pathname, the directory part of the name of the file immediately before it on the source inclusion stack is prepended (this behavior is like the way the C preprocessor handles #include "file.h").

The result of the manipulations is treated as a filename, and returned as the first component of the tuple, with open() called on it to yield the second component. (Note: this is the reverse of the order of arguments in instance initialization!)

This hook is exposed so that you can use it to implement directory search paths, addition of file extensions, and other namespace hacks. There is no corresponding “close” hook, but a shlex instance will call the close() method of the sourced input stream when it returns EOF.

For more explicit control of source stacking, use the push_source() and pop_source() methods.

shlex.push_source(newstream, newfile=None)

Push an input source stream onto the input stack. If the filename argument is specified it will later be available for use in error messages. This is the same method used internally by the sourcehook() method.

shlex.pop_source()

Pop the last-pushed input source from the input stack. This is the same method used internally when the lexer reaches EOF on a stacked input stream.

shlex.error_leader(infile=None, lineno=None)

This method generates an error message leader in the format of a Unix C compiler error label; the format is '"%s", line %d: ', where the %s is replaced with the name of the current source file and the %d with the current input line number (the optional arguments can be used to override these).

This convenience is provided to encourage shlex users to generate error messages in the standard, parseable format understood by Emacs and other Unix tools.

Instances of shlex subclasses have some public instance variables which either control lexical analysis or can be used for debugging:

shlex.commenters

The string of characters that are recognized as comment beginners. All characters from the comment beginner to end of line are ignored. Includes just '#' by default.

shlex.wordchars

The string of characters that will accumulate into multi-character tokens. By default, includes all ASCII alphanumerics and underscore. In POSIX mode, the accented characters in the Latin-1 set are also included. If punctuation_chars is not empty, the characters ~-./*?=, which can appear in filename specifications and command line parameters, will also be included in this attribute, and any characters which appear in punctuation_chars will be removed from wordchars if they are present there.

shlex.whitespace

Characters that will be considered whitespace and skipped. Whitespace bounds tokens. By default, includes space, tab, linefeed and carriage-return.

shlex.escape

Characters that will be considered as escape. This will be only used in POSIX mode, and includes just '\' by default.

shlex.quotes

Characters that will be considered string quotes. The token accumulates until the same quote is encountered again (thus, different quote types protect each other as in the shell.) By default, includes ASCII single and double quotes.

shlex.escapedquotes

Characters in quotes that will interpret escape characters defined in escape. This is only used in POSIX mode, and includes just '"' by default.

shlex.whitespace_split

If True, tokens will only be split in whitespaces. This is useful, for example, for parsing command lines with shlex, getting tokens in a similar way to shell arguments. If this attribute is True, punctuation_chars will have no effect, and splitting will happen only on whitespaces. When using punctuation_chars, which is intended to provide parsing closer to that implemented by shells, it is advisable to leave whitespace_split as False (the default value).

shlex.infile

The name of the current input file, as initially set at class instantiation time or stacked by later source requests. It may be useful to examine this when constructing error messages.

shlex.instream

The input stream from which this shlex instance is reading characters.

shlex.source

This attribute is None by default. If you assign a string to it, that string will be recognized as a lexical-level inclusion request similar to the source keyword in various shells. That is, the immediately following token will be opened as a filename and input will be taken from that stream until EOF, at which point the close() method of that stream will be called and the input source will again become the original input stream. Source requests may be stacked any number of levels deep.

shlex.debug

If this attribute is numeric and 1 or more, a shlex instance will print verbose progress output on its behavior. If you need to use this, you can read the module source code to learn the details.

shlex.lineno

Source line number (count of newlines seen so far plus one).

shlex.token

The token buffer. It may be useful to examine this when catching exceptions.

shlex.eof

Token used to determine end of file. This will be set to the empty string (''), in non-POSIX mode, and to None in POSIX mode.

shlex.punctuation_chars

Characters that will be considered punctuation. Runs of punctuation characters will be returned as a single token. However, note that no semantic validity checking will be performed: for example, “>>>” could be returned as a token, even though it may not be recognised as such by shells.

Nouveau dans la version 3.6.

24.3.2. Parsing Rules

When operating in non-POSIX mode, shlex will try to obey to the following rules.

Quote characters are not recognized within words (Do"Not"Separate is parsed as the single word Do"Not"Separate);

Escape characters are not recognized;

Enclosing characters in quotes preserve the literal value of all characters within the quotes;

Closing quotes separate words ("Do"Separate is parsed as "Do" and Separate);

If whitespace_split is False, any character not declared to be a word character, whitespace, or a quote will be returned as a single-character token. If it is True, shlex will only split words in whitespaces;

EOF is signaled with an empty string ('');

It’s not possible to parse empty strings, even if quoted.

When operating in POSIX mode, shlex will try to obey to the following parsing rules.

Quotes are stripped out, and do not separate words ("Do"Not"Separate" is parsed as the single word DoNotSeparate);

Non-quoted escape characters (e.g. '\') preserve the literal value of the next character that follows;

Enclosing characters in quotes which are not part of escapedquotes (e.g. "'") preserve the literal value of all characters within the quotes;

Enclosing characters in quotes which are part of escapedquotes (e.g. '"') preserves the literal value of all characters within the quotes, with the exception of the characters mentioned in escape. The escape characters retain its special meaning only when followed by the quote in use, or the escape character itself. Otherwise the escape character will be considered a normal character.

EOF is signaled with a None value;

Quoted empty strings ('') are allowed.

24.3.3. Improved Compatibility with Shells

Nouveau dans la version 3.6.

The shlex class provides compatibility with the parsing performed by common Unix shells like bash, dash, and sh. To take advantage of this compatibility, specify the punctuation_chars argument in the constructor. This defaults to False, which preserves pre-3.6 behaviour. However, if it is set to True, then parsing of the characters ();<>|& is changed: any run of these characters is returned as a single token. While this is short of a full parser for shells (which would be out of scope for the standard library, given the multiplicity of shells out there), it does allow you to perform processing of command lines more easily than you could otherwise. To illustrate, you can see the difference in the following snippet:

 >>> import shlex
 >>> text = "a && b; c && d || e; f >'abc'; (def \"ghi\")"
 >>> list(shlex.shlex(text))
 ['a', '&', '&', 'b', ';', 'c', '&', '&', 'd', '|', '|', 'e', ';', 'f', '>',
 "'abc'", ';', '(', 'def', '"ghi"', ')']
 >>> list(shlex.shlex(text, punctuation_chars=True))
 ['a', '&&', 'b', ';', 'c', '&&', 'd', '||', 'e', ';', 'f', '>', "'abc'",
 ';', '(', 'def', '"ghi"', ')']

Of course, tokens will be returned which are not valid for shells, and you’ll need to implement your own error checks on the returned tokens.

Instead of passing True as the value for the punctuation_chars parameter, you can pass a string with specific characters, which will be used to determine which characters constitute punctuation. For example:

>>> import shlex
>>> s = shlex.shlex("a && b || c", punctuation_chars="|")
>>> list(s)
['a', '&', '&', 'b', '||', 'c']

Note

When punctuation_chars is specified, the wordchars attribute is augmented with the characters ~-./*?=. That is because these characters can appear in file names (including wildcards) and command-line arguments (e.g. --color=auto). Hence:

>>> import shlex
>>> s = shlex.shlex('~/a && b-c --color=auto || d *.py?',
...                 punctuation_chars=True)
>>> list(s)
['~/a', '&&', 'b-c', '--color=auto', '||', 'd', '*.py?']

For best effect, punctuation_chars should be set in conjunction with posix=True. (Note that posix=False is the default for shlex.)

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25. Interfaces Utilisateur Graphiques avec Tk

Tk/Tcl fait depuis longtemps partie intégrante de Python. Il fournit un jeu d’outils robustes et indépendants de la plateforme pour gérer des fenêtres. Disponible aux développeurs via le paquet tkinter et ses extensions, les modules tkinter.tix et tkinter.ttk.

Le paquet tkinter est une fine couche orientée objet au dessus de Tcl/Tk. Pour utiliser le module tkinter, vous n’avez pas à écrire de code Tcl, mais vous devrez consulter la documentation de Tk, et parfois la documentation de Tcl. Le module tkinter est un ensemble de surcouches implémentant les widgets Tk en classes Python. De plus, le module interne _tkinter fournit un mécanisme robuste permettant à des fils d’exécution Python et Tcl d’interagir.

Les avantages de tkinter sont sa rapidité, et qu’il est généralement fourni nativement avec Python. Bien que sa documentation soit mauvaise, d’autres ressources existent : des références, tutoriels, livres, … Le module tkinter est aussi célèbre pour son aspect vieillot, cependant il à été grandement amélioré depuis Tk 8.5. Néanmoins, il existe bien d’autres bibliothèques d’interfaces graphiques qui pourraient vous intéresser. Pour plus d’informations sur les alternatives, consultez le chapitre Autres paquets d’interface graphique utilisateur.

25.1. tkinter — Interface Python pour Tcl/Tk

25.1.1. Modules Tkinter

25.1.2. Guide de survie Tkinter

25.1.2.1. Mode d’emploi

25.1.2.2. Un simple programme Hello World

25.1.3. Un (très) rapide aperçu de Tcl/Tk

25.1.4. Correspondance entre Basic Tk et Tkinter

25.1.5. Relations entre Tk et Tkinter

25.1.6. Guide pratique

25.1.6.1. Définition des options

25.1.6.2. L’empaqueteur

25.1.6.3. Options de l’empaqueteur

25.1.6.4. Association des variables de l’objet graphique

25.1.6.5. Le gestionnaire de fenêtres

25.1.6.6. Types de données des options Tk

25.1.6.7. Liaisons et événements

25.1.6.8. Le paramètre index

25.1.6.9. Images

25.1.7. Gestionnaires de fichiers

25.2. tkinter.ttk — Tk themed widgets

25.2.1. Using Ttk

25.2.2. Ttk Widgets

25.2.3. Widget

25.2.3.1. Standard Options

25.2.3.2. Scrollable Widget Options

25.2.3.3. Label Options

25.2.3.4. Compatibility Options

25.2.3.5. Widget States

25.2.3.6. ttk.Widget

25.2.4. Combobox

25.2.4.1. Options

25.2.4.2. Virtual events

25.2.4.3. ttk.Combobox

25.2.5. Notebook

25.2.5.1. Options

25.2.5.2. Tab Options

25.2.5.3. Tab Identifiers

25.2.5.4. Virtual Events

25.2.5.5. ttk.Notebook

25.2.6. Progressbar

25.2.6.1. Options

25.2.6.2. ttk.Progressbar

25.2.7. Separator

25.2.7.1. Options

25.2.8. Sizegrip

25.2.8.1. Platform-specific notes

25.2.8.2. Bugs

25.2.9. Treeview

25.2.9.1. Options

25.2.9.2. Item Options

25.2.9.3. Tag Options

25.2.9.4. Column Identifiers

25.2.9.5. Virtual Events

25.2.9.6. ttk.Treeview

25.2.10. Ttk Styling

25.2.10.1. Layouts

25.3. tkinter.tix — Extension widgets for Tk

25.3.1. Using Tix

25.3.2. Tix Widgets

25.3.2.1. Basic Widgets

25.3.2.2. File Selectors

25.3.2.3. Hierarchical ListBox

25.3.2.4. Tabular ListBox

25.3.2.5. Manager Widgets

25.3.2.6. Image Types

25.3.2.7. Miscellaneous Widgets

25.3.2.8. Form Geometry Manager

25.3.3. Tix Commands

25.4. tkinter.scrolledtext — Gadget texte avec barre de défilement

25.5. IDLE

25.5.1. Menus

25.5.1.1. Menu File (Console et Éditeur)

25.5.1.2. Menu Edit (console et éditeur)

25.5.1.3. Menu Format (fenêtre d’édition uniquement)

25.5.1.4. Menu Run (fenêtre d’édition uniquement)

25.5.1.5. Menu Shell (fenêtre de console uniquement)

25.5.1.6. Menu Debug (fenêtre de console uniquement)

25.5.1.7. Menu Options (console et éditeur)

25.5.1.8. Menu Windows (console et éditeur)

25.5.1.9. Menu Help (console et éditeur)

25.5.1.10. Menus Contextuels

25.5.2. Édition et navigation

25.5.2.1. Editor windows

25.5.2.2. Key bindings

25.5.2.3. Indentation automatique

25.5.2.4. Complétions

25.5.2.5. Info-bulles

25.5.2.6. Fenêtre de console Python

25.5.2.7. Coloration du texte

25.5.3. Démarrage et exécution du code

25.5.3.1. Utilisation de la ligne de commande

25.5.3.2. Échec au démarrage

25.5.3.3. Running user code

25.5.3.4. User output in Shell

25.5.3.5. Développer des applications tkinter

25.5.3.6. Exécution sans sous-processus

25.5.4. Aide et préférences

25.5.4.1. Help sources

25.5.4.2. Modifier les préférences

25.5.4.3. IDLE on macOS

25.5.4.4. Extensions

25.6. Autres paquets d’interface graphique utilisateur

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25.1. tkinter — Interface Python pour Tcl/Tk

Code source : Lib/tkinter/__init__.py [https://github.com/python/cpython/tree/3.6/Lib/tkinter/__init__.py]

Le paquet tkinter (« interface Tk ») est l’interface Python standard de la boîte à outils d’IUG Tk. Tk et tkinter sont disponibles sur la plupart des plates-formes Unix, ainsi que sur les systèmes Windows (Tk lui-même ne fait pas partie de Python ; il est maintenu par ActiveState).

Exécuter python -m tkinter depuis la ligne de commande ouvre une fenêtre de démonstration d’une interface Tk simple, vous indiquant que tkinter est correctement installé sur votre système et indiquant également quelle version de Tcl/Tk est installée ; vous pouvez donc lire la documentation Tcl/Tk spécifique à cette version.

Voir aussi

Documentation de Tkinter :

Python Tkinter Resources [https://wiki.python.org/moin/TkInter]

Le Python Tkinter Topic Guide fournit beaucoup d’informations sur l’utilisation de Tk à partir de Python et des liens vers d’autres sources d’information sur Tk.

TKDocs [http://www.tkdocs.com/]

Tutoriel complet plus convivial pour certains des objets graphiques.

Tkinter 8.5 reference: a GUI for Python [https://web.archive.org/web/20190524140835/https://infohost.nmt.edu/tcc/help/pubs/tkinter/web/index.html]

Documents de référence en ligne.

Documents Tkinter sur effbot [http://effbot.org/tkinterbook/]

Référence en ligne pour tkinter réalisée par effbot.org.

Programming Python [http://learning-python.com/about-pp4e.html]

Livre de Mark Lutz, qui couvre excellemment bien Tkinter.

Modern Tkinter for Busy Python Developers [https://www.amazon.com/Modern-Tkinter-Python-Developers-ebook/dp/B0071QDNLO/]

Book by Mark Roseman about building attractive and modern graphical user interfaces with Python and Tkinter.

Python and Tkinter Programming [https://www.manning.com/books/python-and-tkinter-programming]

Livre de John Grayson (ISBN 1-884777-81-3).

Documentation de Tcl/Tk :

Commandes Tk [https://www.tcl.tk/man/tcl8.6/TkCmd/contents.htm]

La plupart des commandes sont disponibles sous forme de classes tkinter ou tkinter.ttk. Modifiez “8.6” pour correspondre à votre version installée de Tcl/Tk.

Pages de manuel récentes de Tcl/Tk [https://www.tcl.tk/doc/]

Manuels récents de Tcl/Tk sur www.tcl.tk.

ActiveState Tcl Home Page [http://tcl.activestate.com/]

Le développement de Tk/Tcl se déroule en grande partie au sein d’ActiveState.

Tcl and the Tk Toolkit [https://www.amazon.com/exec/obidos/ASIN/020163337X]

Livre de John Ousterhout, l’inventeur de Tcl.

Practical Programming in Tcl and Tk [http://www.beedub.com/book/]

Le livre encyclopédique de Brent Welch.

25.1.1. Modules Tkinter

La plupart du temps, tkinter est tout ce dont vous avez vraiment besoin mais un certain nombre de modules supplémentaires sont également disponibles. L’interface Tk est située dans un module binaire nommé _tkinter. Ce module contient l’interface de bas niveau vers Tk et ne doit jamais être utilisé directement par les développeurs. Il s’agit généralement d’une bibliothèque partagée (ou DLL) mais elle peut, dans certains cas, être liée statiquement à l’interpréteur Python.

En plus du module d’interface Tk, tkinter inclut un certain nombre de modules Python, tkinter.constants étant l’un des plus importants. Importer tkinter charge automatiquement tkinter.constants donc, habituellement, pour utiliser Tkinter, tout ce dont vous avez besoin est une simple commande d’importation :

import tkinter

Ou, plus souvent :

from tkinter import *

class tkinter.Tk(screenName=None, baseName=None, className='Tk', useTk=1)

La classe Tk est instanciée sans argument. Cela crée un widget de haut niveau de Tk qui est généralement la fenêtre principale d’une application. Chaque instance a son propre interpréteur Tcl associé.

tkinter.Tcl(screenName=None, baseName=None, className='Tk', useTk=0)

La fonction Tcl() est une fonction fabrique qui crée un objet similaire à celui créé par la classe Tk, sauf qu’elle n’initialise pas le sous-système Tk. Ceci est le plus souvent utile lorsque vous pilotez l’interpréteur Tcl dans un environnement où vous ne voulez pas créer des fenêtres de haut niveau supplémentaires, ou alors si c’est impossible (comme les systèmes Unix/Linux sans un serveur X). Un objet créé par Tcl() peut avoir une fenêtre de haut niveau créée (et le sous-système Tk initialisé) en appelant sa méthode loadtk().

Parmi les modules qui savent gérer Tk, nous pouvons citer :

tkinter.scrolledtext

Outil d’affichage de texte avec une barre de défilement verticale intégrée.

tkinter.colorchooser

Boîte de dialogue permettant à l’utilisateur de choisir une couleur.

tkinter.commondialog

Classe de base pour les boîtes de dialogue définies dans les autres modules listés ici.

tkinter.filedialog

Boîtes de dialogue standard permettant à l’utilisateur de spécifier un fichier à ouvrir ou à enregistrer.

tkinter.font

Utilitaires pour gérer les polices de caractères.

tkinter.messagebox

Accès aux boîtes de dialogue Tk standard.

tkinter.simpledialog

Boîtes de dialogue simples et fonctions utilitaires.

tkinter.dnd

Support du glisser-déposer pour tkinter. Il s’agit d’une méthode expérimentale qui ne sera plus maintenue lorsqu’elle sera remplacée par Tk DND.

turtle

Tortue graphique dans une fenêtre Tk.

25.1.2. Guide de survie Tkinter

Cette section n’est pas conçue pour être un tutoriel exhaustif de Tk ou Tkinter. Il s’agit plutôt d’un guide d’introduction au système.

Crédits :

Tk a été écrit par John Ousterhout de Berkeley.

Tkinter a été écrit par Steen Lumholt et Guido van Rossum.

Ce guide de survie a été écrit par Matt Conway de l’Université de Virginie.

Le rendu HTML, avec quelques modifications, a été réalisé à partir d’une version FrameMaker par Ken Manheimer.

Fredrik Lundh a élaboré et mis à jour les descriptions de l’interface des classes, en cohérence avec Tk 4.2.

Mike Clarkson a converti la documentation en LaTeX et a compilé le chapitre Interface utilisateur du manuel de référence.

25.1.2.1. Mode d’emploi

Cette section est divisée en deux parties : la première moitié (à peu près) couvre la partie théorique, tandis que la seconde moitié peut être utilisée comme guide pratique.

Lorsque l’on essaie de répondre à des questions sur la manière de faire « ceci ou cela », il est souvent préférable de trouver comment le faire en Tk, puis de le convertir en fonction correspondante tkinter. Les programmeurs Python peuvent souvent deviner la commande Python correcte en consultant la documentation Tk. Cela signifie que pour utiliser Tkinter, vous devez en savoir un peu plus sur Tk. Ce document ne peut pas remplir ce rôle, alors le mieux que nous puissions faire est de vous indiquer la meilleure documentation qui existe. Voici quelques conseils :

Les auteurs conseillent fortement d’obtenir une copie des pages de manuel de Tk. En particulier, les pages de manuel dans le répertoire manN sont les plus utiles. Les pages de manuel man3 décrivent l’interface C de la bibliothèque Tk et ne sont donc pas particulièrement utiles aux développeurs de scripts.

Addison-Wesley a publié un livre intitulé Tcl and the Tk Toolkit de John Ousterhout (ISBN 0-201-63337-X) qui est une bonne introduction à Tcl et Tk pour débutants. Le livre n’est pas exhaustif et, pour beaucoup de détails, il renvoie aux pages du manuel.

tkinter/__init__.py est souvent un dernier recours, mais peut être un bon endroit où aller quand rien d’autre ne fait sens.

25.1.2.2. Un simple programme Hello World

import tkinter as tk

class Application(tk.Frame):
    def __init__(self, master=None):
        super().__init__(master)
        self.master = master
        self.pack()
        self.create_widgets()

    def create_widgets(self):
        self.hi_there = tk.Button(self)
        self.hi_there["text"] = "Hello World\n(click me)"
        self.hi_there["command"] = self.say_hi
        self.hi_there.pack(side="top")

        self.quit = tk.Button(self, text="QUIT", fg="red",
                              command=self.master.destroy)
        self.quit.pack(side="bottom")

    def say_hi(self):
        print("hi there, everyone!")

root = tk.Tk()
app = Application(master=root)
app.mainloop()

25.1.3. Un (très) rapide aperçu de Tcl/Tk

La hiérarchie de classes semble compliquée mais, dans la pratique, les développeurs d’applications se réfèrent presque toujours aux classes situées tout en bas de la hiérarchie.

Notes :

Ces classes sont fournies dans le but d’organiser certaines fonctions sous un seul espace de nommage. Elles n’ont pas vocation à être instanciées indépendamment.

La classe Tk est destinée à être instanciée une seule fois dans une application. Les développeurs d’applications n’ont pas besoin d’en instancier une explicitement, Le système en crée une au besoin quand une des autres classes est instanciée.

La classe Widget n’est pas destinée à être instanciée, elle est destinée uniquement au sous-classement pour faire de « vrais » objets graphiques (en C++, on appelle cela une « classe abstraite »).

Pour comprendre cette documentation, il y aura des moments où vous aurez besoin de savoir comment lire de courts passages de Tk et comment identifier les différentes parties d’une commande Tk. (Voir la section Correspondance entre Basic Tk et Tkinter pour les équivalents tkinter de ce qui suit).

Les scripts Tk sont des programmes Tcl. Comme tous les programmes Tcl, les scripts Tk ne sont que des listes de commandes séparées par des espaces. Un objet graphique Tk n’est constitué que de sa classe, des options qui l’aident à se configurer et des actions qui lui font faire des choses utiles.

Pour créer un objet graphique en Tk, la commande est toujours de la forme :

classCommand newPathname options

classCommand

indique le type d’objet graphique à réaliser (un bouton, une étiquette, un menu…)

newPathname

est le nouveau nom pour cet objet graphique. Tous les noms dans Tk doivent être uniques. Pour vous aider à respecter cette règle, les objets graphiques dans Tk sont nommés avec des noms d’accès, tout comme les fichiers dans le système de fichiers. L’objet graphique de niveau supérieur, la racine (root en anglais), s’appelle . (point) et les enfants sont délimités par plusieurs points. Par exemple, .myApp.controlPanel.okButton pourrait être le nom d’un objet graphique.

options

configure l’apparence de l’objet graphique et, dans certains cas, son comportement. Les options se présentent sous la forme d’une liste de paramètres et de valeurs. Les paramètres sont précédés d’un « - », comme les paramètres d’une ligne de commande du shell Unix, et les valeurs sont mises entre guillemets si elles font plus d’un mot.

Par exemple :

button   .fred   -fg red -text "hi there"
   ^       ^     \______________________/
   |       |                |
 class    new            options
command  widget  (-opt val -opt val ...)

Une fois créé, le chemin d’accès à l’objet graphique devient une nouvelle commande. Cette nouvelle commande d’objet graphique est l’interface du programmeur pour que le nouvel objet graphique effectue une action. En C, cela prend la forme someAction(fred, someOptions), en C++, cela prend la forme fred.someAction(someOptions) et, en Tk, vous dites :

.fred someAction someOptions

Notez que le nom de l’objet, .fred, commence par un point.

Comme vous pouvez vous y attendre, les valeurs autorisées pour someAction dépendent de la classe de l’objet graphique : .fred disable fonctionne si fred est un bouton (fred devient grisé), mais ne fonctionne pas si fred est une étiquette (la désactivation des étiquettes n’existe pas dans Tk).

Les valeurs possibles de someOptions dépendent de l’action. Certaines actions, comme disable, ne nécessitent aucun argument ; d’autres, comme la commande delete d’une zone de saisie, nécessitent des arguments pour spécifier l’étendue du texte à supprimer.

25.1.4. Correspondance entre Basic Tk et Tkinter

Les commandes de classes dans Tk correspondent aux constructeurs de classes dans Tkinter.

button .fred                =====>  fred = Button()

Le constructeur d’un objet est implicite dans le nouveau nom qui lui est donné lors de la création. Dans Tkinter, les constructeurs sont spécifiés explicitement.

button .panel.fred          =====>  fred = Button(panel)

Les options de configuration dans Tk sont données dans des listes de paramètres séparés par des traits d’union suivies de leurs valeurs. Dans Tkinter, les options sont spécifiées sous forme d’arguments par mots-clés dans le constructeur d’instance, et d’arguments par mots-clés pour configurer les appels ou sous forme d’une entrée, dans le style dictionnaire, d’instance pour les instances établies. Voir la section Définition des options pour la façon de définir les options.

button .fred -fg red        =====>  fred = Button(panel, fg="red")
.fred configure -fg red     =====>  fred["fg"] = red
                            OR ==>  fred.config(fg="red")

Dans Tk, pour effectuer une action sur un objet graphique, utilisez le nom de l’objet graphique comme une commande et faites-le suivre d’un nom d’action, éventuellement avec des arguments (options). Dans Tkinter, vous appelez des méthodes sur l’instance de classe pour invoquer des actions sur l’objet graphique. Les actions (méthodes) qu’un objet graphique donné peut effectuer sont listées dans tkinter/__init__.py.

.fred invoke                =====>  fred.invoke()

Pour donner un objet graphique à l’empaqueteur (ce qui gère la disposition à l’écran), appelez pack avec des arguments optionnels. Dans Tkinter, la classe Pack contient toutes ces fonctionnalités et les différentes formes de la commande pack sont implémentées comme méthodes. Tous les objets graphiques de tkinter sont sous-classés depuis l’empaqueteur et donc héritent de toutes les méthodes d’empaquetage. Voir la documentation du module tkinter.tix pour plus d’informations sur le gestionnaire de disposition des formulaires.

pack .fred -side left       =====>  fred.pack(side="left")

25.1.5. Relations entre Tk et Tkinter

De haut en bas :

Votre application (Python)

Une application Python fait un appel tkinter.

tkinter (paquet Python)

Cet appel (par exemple, la création d’un objet graphique de type bouton) est implémenté dans le paquet tkinter, qui est écrit en Python. Cette fonction Python analyse les commandes et les arguments et les convertit en une forme qui les fait ressembler à un script Tk au lieu d’un script Python.

_tkinter (C)

Ces commandes et leurs arguments sont passés à une fonction C dans le module d’extension _tkinter — notez le tiret bas.

Objets graphiques Tk (C et Tcl)

Cette fonction C est capable d’effectuer des appels vers d’autres modules C, y compris les fonctions C qui composent la bibliothèque Tk. Tk est implémenté en C et un peu en Tcl. La partie Tcl des objets graphiques Tk est utilisée pour lier certains comportements par défaut aux objets graphiques, et est exécutée une fois au moment où le paquet Python tkinter est importé (cette étape est transparente pour l’utilisateur).

Tk (C)

La partie Tk des objets graphiques Tk implémente la correspondance finale avec …

Xlib (C)

la bibliothèque Xlib pour dessiner des éléments graphiques à l’écran.

25.1.6. Guide pratique

25.1.6.1. Définition des options

Les options contrôlent des paramètres tels que la couleur et la largeur de la bordure d’un objet graphique. Les options peuvent être réglées de trois façons :

Lors de la création de l’objet, à l’aide d’arguments par mots-clés

fred = Button(self, fg="red", bg="blue")

Après la création de l’objet, en manipulant le nom de l’option comme une entrée de dictionnaire

fred["fg"] = "red"
fred["bg"] = "blue"

Utilisez la méthode config() pour mettre à jour plusieurs attributs après la création de l’objet

fred.config(fg="red", bg="blue")

Pour l’explication complète d’une option donnée et de son comportement, voir les pages de manuel Tk de l’objet graphique en question.

Notez que les pages de manuel listent « OPTIONS STANDARD » et « OPTIONS SPÉCIFIQUES D’OBJETS GRAPHIQUES » pour chaque objet graphique. La première est une liste d’options communes à de nombreux objets graphiques, la seconde est une liste d’options propres à cet objet graphique particulier. Les options standard sont documentées sur la page de manuel options(3).

Aucune distinction n’est faite dans ce document entre les options standard et les options spécifiques à un objet graphique. Certaines options ne s’appliquent pas à certains types d’objets graphiques. La réaction d’un objet graphique donné à une option particulière dépend de la classe de l’objet graphique ; les boutons possèdent une option command, pas les étiquettes.

Les options gérées par un objet graphique donné sont listées dans la page de manuel de cet objet graphique, ou peuvent être interrogées à l’exécution en appelant la méthode config() sans argument, ou en appelant la méthode keys() sur cet objet graphique. La valeur de retour de ces appels est un dictionnaire dont la clé est le nom de l’option sous forme de chaîne (par exemple, 'relief') et dont les valeurs sont des 5-uplets.

Certaines options, comme bg, sont des synonymes d’options communes qui ont des noms longs (bg est une abréviation pour background « arrière-plan »). Passer le nom abrégé d’une option à la méthode config() renvoie un couple, pas un quintuplet. Le couple renvoyé contient le nom abrégé et le nom réel de l’option, par exemple ('bg','background').

Index

Signification

Exemple

0

nom des options

'relief'

1

nom de l’option pour la recherche dans la base de données

'relief'

2

classe de l’option pour la recherche dans la base de données

'Relief'

3

valeur par défaut

'raised'

4

valeur actuelle

'groove'

Exemple :

>>> print(fred.config())
{'relief': ('relief', 'relief', 'Relief', 'raised', 'groove')}

Bien sûr, le dictionnaire affiché contient toutes les options disponibles et leurs valeurs. Ceci n’est donné qu’à titre d’exemple.

25.1.6.2. L’empaqueteur

L’empaqueteur est l’un des mécanismes de Tk pour la gestion de la disposition des éléments sur l’écran. Les gestionnaires de géométrie sont utilisés pour spécifier le positionnement relatif du positionnement des objets graphiques dans leur conteneur — leur constructeur mutuel. Contrairement au plus encombrant placeur (qui est utilisé moins souvent, et nous n’en parlons pas ici), l’empaqueteur prend les spécifications qualitatives de relation — above, to the left of, filling, etc — et calcule tout pour déterminer les coordonnées exactes du placement pour vous.

La taille d’un objet graphique constructeur est déterminée par la taille des « objets graphiques hérités » à l’intérieur. L’empaqueteur est utilisé pour contrôler l’endroit où les objets graphiques hérités apparaissent à l’intérieur du constructeur dans lequel ils sont empaquetés. Vous pouvez regrouper des objets graphiques dans des cadres, et des cadres dans d’autres cadres, afin d’obtenir le type de mise en page souhaité. De plus, l’arrangement est ajusté dynamiquement pour s’adapter aux changements incrémentiels de la configuration, une fois qu’elle est empaquetées.

Notez que les objets graphiques n’apparaissent pas tant que leur disposition n’a pas été spécifiée avec un gestionnaire de géométrie. C’est une erreur de débutant courante de ne pas tenir compte de la spécification de la géométrie, puis d’être surpris lorsque l’objet graphique est créé mais que rien n’apparaît. Un objet graphique n’apparaît qu’après que, par exemple, la méthode pack() de l’empaqueteur lui ait été appliquée.

La méthode pack() peut être appelée avec des paires mot-clé-option/valeur qui contrôlent où l’objet graphique doit apparaître dans son conteneur et comment il doit se comporter lorsque la fenêtre principale de l’application est redimensionnée. En voici quelques exemples :

fred.pack()                     # defaults to side = "top"
fred.pack(side="left")
fred.pack(expand=1)

25.1.6.3. Options de l’empaqueteur

Pour de plus amples informations sur l’empaqueteur et les options qu’il peut prendre, voir les pages de manuel et la page 183 du livre de John Ousterhout.

anchor

Type d’ancrage. Indique l’endroit où l’empaqueteur doit placer chaque enfant dans son espace.

expand

Booléen, 0 ou 1.

fill

Valeurs acceptées : 'x', 'y', 'both', 'none'.

ipadx et ipady

Une distance — désignant l’écart interne de chaque côté de l’objet graphique hérité.

padx et pady

Une distance — désignant l’écart externe de chaque côté de l’objet graphique hérité.

side

Valeurs acceptées : 'left', 'right', 'top', 'bottom'.

25.1.6.4. Association des variables de l’objet graphique

L’assignation d’une valeur à certains objets graphiques (comme les objets graphique de saisie de texte) peut être liée directement aux variables de votre application à l’aide d’options spéciales. Ces options sont variable, textvariable, onvalue, offvalue et value. Ce lien fonctionne dans les deux sens : si la variable change pour une raison ou pour une autre, l’objet graphique auquel elle est connectée est mis à jour pour refléter la nouvelle valeur.

Malheureusement, dans l’implémentation actuelle de tkinter il n’est pas possible de passer une variable Python arbitraire à un objet graphique via une option variable ou textvariable. Les seuls types de variables pour lesquels cela fonctionne sont les variables qui sont sous-classées à partir d’une classe appelée Variable, définie dans tkinter.

Il existe de nombreuses sous-classes utiles de Variable déjà définies : StringVar, IntVar, DoubleVar et BooleanVar. Pour lire la valeur courante d’une telle variable, appelez la méthode get() dessus et, pour changer sa valeur, appelez la méthode set(). Si vous suivez ce protocole, l’objet graphique suivra toujours la valeur de la variable, sans autre intervention de votre part.

Par exemple :

class App(Frame):
    def __init__(self, master=None):
        super().__init__(master)
        self.pack()

        self.entrythingy = Entry()
        self.entrythingy.pack()

        # here is the application variable
        self.contents = StringVar()
        # set it to some value
        self.contents.set("this is a variable")
        # tell the entry widget to watch this variable
        self.entrythingy["textvariable"] = self.contents

        # and here we get a callback when the user hits return.
        # we will have the program print out the value of the
        # application variable when the user hits return
        self.entrythingy.bind('<Key-Return>',
                              self.print_contents)

    def print_contents(self, event):
        print("hi. contents of entry is now ---->",
              self.contents.get())

25.1.6.5. Le gestionnaire de fenêtres

Dans Tk, il y a une commande pratique, wm, pour interagir avec le gestionnaire de fenêtres. Les options de la commande wm vous permettent de contrôler les titres, le placement, les icônes en mode bitmap et encore d’autres choses du même genre. Dans tkinter, ces commandes ont été implémentées en tant que méthodes sur la classe Wm. Les objets graphiques de haut niveau sont sous-classés à partir de la classe Wm, ils peuvent donc appeler directement les méthodes de Wm.

Pour accéder à la fenêtre du plus haut niveau qui contient un objet graphique donné, vous pouvez souvent simplement vous référer au parent de cet objet graphique. Bien sûr, si l’objet graphique a été empaqueté à l’intérieur d’un cadre, le parent ne représentera pas la fenêtre de plus haut niveau. Pour accéder à la fenêtre du plus haut niveau qui contient un objet graphique arbitraire, vous pouvez appeler la méthode _root(). Cette méthode commence par un soulignement pour indiquer que cette fonction fait partie de l’implémentation, et non d’une interface avec la fonctionnalité Tk.

Voici quelques exemples d’utilisation courante :

import tkinter as tk

class App(tk.Frame):
    def __init__(self, master=None):
        super().__init__(master)
        self.pack()

# create the application
myapp = App()

#
# here are method calls to the window manager class
#
myapp.master.title("My Do-Nothing Application")
myapp.master.maxsize(1000, 400)

# start the program
myapp.mainloop()

25.1.6.6. Types de données des options Tk

anchor

Les valeurs acceptées sont des points cardinaux : « n », « ne », « e », « se », « s », « sw », « w », « nw » et « center ».

bitmap

Il y a huit bitmaps intégrés nommés : « error », « gray25 », « gray50 », « hourglass », « info », « questhead », « question », « warning »'. Pour spécifier un nom de fichier bitmap X, indiquez le chemin complet du fichier, précédé de @, comme dans "@/usr/contrib/bitmap/gumby.bit".

boolean

Vous pouvez lui donner les entiers 0 ou 1 ou les chaînes de caractères "yes" ou "no".

callback

N’importe quelle fonction Python qui ne prend pas d’argument. Par exemple :

def print_it():
    print("hi there")
fred["command"] = print_it

color

Les couleurs peuvent être données sous forme de noms de couleurs Xorg dans le fichier rgb.txt, ou sous forme de chaînes représentant les valeurs RVB en 4 bits : « #RGB », 8 bits : « #RRVVBB », 12 bits``« #RRRVVVBBB », ou 16 bits ``« #RRRRVVVVBBBB », où R,V,B représente ici tout chiffre hexadécimal valide. Voir page 160 du livre d’Ousterhout pour plus de détails.

cursor

Les noms de curseurs Xorg standard que l’on trouve dans cursorfont.h peuvent être utilisés, sans le préfixe XC_. Par exemple pour obtenir un curseur en forme de main (XC_hand2), utilisez la chaîne « hand2 ». Vous pouvez également spécifier votre propre bitmap et fichier masque. Voir page 179 du livre d’Ousterhout.

distance

Les distances à l’écran peuvent être spécifiées en pixels ou en distances absolues. Les pixels sont donnés sous forme de nombres et les distances absolues sous forme de chaînes de caractères, le dernier caractère indiquant les unités : c pour les centimètres, i pour les pouces (inches en anglais), m pour les millimètres, p pour les points d’impression. Par exemple, 3,5 pouces est noté « 3.5i ».

font

Tk utilise un format de nom de police sous forme de liste, tel que {courier 10 bold}. Les tailles de polices avec des nombres positifs sont mesurées en points ; les tailles avec des nombres négatifs sont mesurées en pixels.

geometry

Il s’agit d’une chaîne de caractères de la forme largeurxhauteur, où la largeur et la hauteur sont mesurées en pixels pour la plupart des objets graphiques (en caractères pour les objets graphiques affichant du texte). Par exemple : fred["geometry"] = "200x100".

justify

Les valeurs acceptées sont les chaînes de caractères : « left »`, « center », « right » et « fill ».

region

c’est une chaîne de caractères avec quatre éléments séparés par des espaces, chacun d’eux étant une distance valide (voir ci-dessus). Par exemple : "2 3 4 5"``et ``" 3i 2i 4.5i 2i"``et ``"3c 2c 4c 10.43c" sont toutes des régions valides.

relief

Détermine le style de bordure d’un objet graphique. Les valeurs valides sont : "raised", "sunken", "flat", "groove", et "ridge".

scrollcommand

C’est presque toujours la méthode set() d’un objet graphique de défilement, mais peut être n’importe quelle méthode d’objet graphique qui prend un seul argument.

wrap

Doit être l’un d’eux : "none", "char", ou "word".

25.1.6.7. Liaisons et événements

La méthode bind de la commande d’objet graphique vous permet de surveiller certains événements et d’avoir un déclencheur de fonction de rappel lorsque ce type d’événement se produit. La forme de la méthode de liaison est la suivante :

def bind(self, sequence, func, add=''):

où :

sequence

est une chaîne de caractères qui indique le type d’événement cible. (Voir la page du manuel de bind et la page 201 du livre de John Ousterhout pour plus de détails).

func

est une fonction Python, prenant un argument, à invoquer lorsque l’événement se produit. Une instance d’évènement sera passée en argument. (Les fonctions déployées de cette façon sont communément appelées callbacks ou « fonctions de rappel » en français).

add

est facultative, soit '' ou '+'. L’envoi d’une chaîne de caractères vide indique que cette liaison doit remplacer toute autre liaison à laquelle cet événement est associé. L’envoi de``«+»`` signifie que cette fonction doit être ajoutée à la liste des fonctions liées à ce type d’événement.

Par exemple :

def turn_red(self, event):
    event.widget["activeforeground"] = "red"

self.button.bind("<Enter>", self.turn_red)

Remarquez comment on accède au champ objet graphique de l’événement dans la fonction de rappel turn_red(). Ce champ contient l’objet graphique qui a capturé l’événement Xorg. Le tableau suivant répertorie les autres champs d’événements auxquels vous pouvez accéder, et comment ils sont nommés dans Tk, ce qui peut être utile lorsque vous vous référez aux pages de manuel Tk.

Tk

Champ évènement de Tkinter

Tk

Champ évènement de Tkinter

%f

focus

%A

char

%h

hauteur

%E

send_event

%k

keycode

%K

keysym

%s

state

%N

keysym_num

%t

time

%T

type

%w

width

%W

widget

%x

x

%X

x_root

%y

y

%Y

y_root

25.1.6.8. Le paramètre index

Un certain nombre d’objets graphiques nécessitent le passage de paramètres « indicés ». Ils sont utilisés pour pointer vers un endroit spécifique dans un objet graphique de type Texte, ou vers des caractères particuliers dans un objet graphique de type Entrée, ou vers des éléments de menu particuliers dans un objet graphique de type Menu.

Index des objets graphique de type Entrée (index, view index, etc.)

Les objets graphiques de type Entrée ont des options qui se réfèrent à la position des caractères dans le texte affiché. Vous pouvez utiliser ces fonctions tkinter pour accéder à ces points spéciaux dans les objets graphiques texte :

Index des objets graphiques texte

La notation de l’index des objets graphiques de type Texte est très riche et mieux décrite dans les pages du manuel Tk.

Index menu (menu.invoke(), menu.entryconfig(), etc.)

Certaines options et méthodes pour manipuler les menus nécessitent des éléments de spécifiques. Chaque fois qu’un index de menu est nécessaire pour une option ou un paramètre, vous pouvez utiliser :

un entier qui fait référence à la position numérique de l’entrée dans l’objet graphique, comptée à partir du haut, en commençant par 0 ;

la chaîne de caractères "active", qui fait référence à la position du menu qui se trouve actuellement sous le curseur ;

la chaîne de caractères "last" qui fait référence au dernier élément du menu ;

un entier précédé de @, comme dans @6, où l’entier est interprété comme une coordonnée y de pixels dans le système de coordonnées du menu ;

la chaîne de caractères "none", qui n’indique aucune entrée du menu, le plus souvent utilisée avec menu.activate() pour désactiver toutes les entrées, et enfin,

une chaîne de texte dont le motif correspond à l’étiquette de l’entrée de menu, telle qu’elle est balayée du haut vers le bas du menu. Notez que ce type d’index est considéré après tous les autres, ce qui signifie que les correspondances pour les éléments de menu étiquetés last, active ou none peuvent être interprétés comme les littéraux ci-dessus, plutôt.

25.1.6.9. Images

Des images de différents formats peuvent être créées à travers la sous-classe correspondante de tkinter.Image :

BitmapImage pour les images au format XBM.

PhotoImage pour les images aux formats PGM, PPM, GIF et PNG. Ce dernier est géré à partir de Tk 8.6.

L’un ou l’autre type d’image est créé par l’option file ou data (d’autres options sont également disponibles).

L’objet image peut alors être utilisé partout où un objet graphique sait gérer une option image (par ex. étiquettes, boutons, menus). Dans ces cas, Tk ne conserve pas de référence à l’image. Lorsque la dernière référence Python à l’objet image est supprimée, les données de l’image sont également supprimées, et Tk affiche une boite vide à l’endroit où l’image était utilisée.

Voir aussi

Le paquet Pillow [http://python-pillow.org/] ajoute la prise en charge de formats tels que BMP, JPEG, TIFF et WebP, entre autres.

25.1.7. Gestionnaires de fichiers

Tk vous permet d’enregistrer et de désenregistrer une fonction de rappel qui est appelée depuis la boucle principale de Tk lorsque des entrées-sorties sont possibles sur un descripteur de fichier. Un seul gestionnaire peut être enregistré par descripteur de fichier. Exemple de code :

import tkinter
widget = tkinter.Tk()
mask = tkinter.READABLE | tkinter.WRITABLE
widget.tk.createfilehandler(file, mask, callback)
...
widget.tk.deletefilehandler(file)

Cette fonction n’est pas disponible sous Windows.

Dans la mesure où vous ne savez pas combien d’octets sont disponibles en lecture, il ne faut pas utiliser les méthodes BufferedIOBase ou TextIOBase read() ou readline(), car elles requièrent d’indiquer le nombre de bytes à lire. Pour les connecteurs, les méthodes recv() ou recvfrom() fonctionnent bien ; pour les autres fichiers, utilisez des lectures brutes ou os.read(file.fileno(), maxbytecount).

Widget.tk.createfilehandler(file, mask, func)

Enregistre la fonction de rappel du gestionnaire de fichiers func. L’argument file peut être soit un objet avec une méthode fileno() (comme un objet fichier ou connecteur), soit un descripteur de fichier de type entier. L’argument mask est une combinaison OU de l’une des trois constantes ci-dessous. La fonction de rappel s’utilise comme suit :

callback(file, mask)

Widget.tk.deletefilehandler(file)

Désenregistre un gestionnaire de fichiers.

tkinter.READABLE

tkinter.WRITABLE

tkinter.EXCEPTION

Constantes utilisées dans les arguments mask.

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25.2. tkinter.ttk — Tk themed widgets

Source code: Lib/tkinter/ttk.py [https://github.com/python/cpython/tree/3.6/Lib/tkinter/ttk.py]

The tkinter.ttk module provides access to the Tk themed widget set, introduced in Tk 8.5. If Python has not been compiled against Tk 8.5, this module can still be accessed if Tile has been installed. The former method using Tk 8.5 provides additional benefits including anti-aliased font rendering under X11 and window transparency (requiring a composition window manager on X11).

The basic idea for tkinter.ttk is to separate, to the extent possible, the code implementing a widget’s behavior from the code implementing its appearance.

Voir aussi

Tk Widget Styling Support [https://www.tcl.tk/cgi-bin/tct/tip/48]

A document introducing theming support for Tk

25.2.1. Using Ttk

To start using Ttk, import its module:

from tkinter import ttk

To override the basic Tk widgets, the import should follow the Tk import:

from tkinter import *
from tkinter.ttk import *

That code causes several tkinter.ttk widgets (Button, Checkbutton, Entry, Frame, Label, LabelFrame, Menubutton, PanedWindow, Radiobutton, Scale and Scrollbar) to automatically replace the Tk widgets.

This has the direct benefit of using the new widgets which gives a better look and feel across platforms; however, the replacement widgets are not completely compatible. The main difference is that widget options such as « fg », « bg » and others related to widget styling are no longer present in Ttk widgets. Instead, use the ttk.Style class for improved styling effects.

Voir aussi

Converting existing applications to use Tile widgets [http://tktable.sourceforge.net/tile/doc/converting.txt]

A monograph (using Tcl terminology) about differences typically encountered when moving applications to use the new widgets.

25.2.2. Ttk Widgets

Ttk comes with 17 widgets, eleven of which already existed in tkinter: Button, Checkbutton, Entry, Frame, Label, LabelFrame, Menubutton, PanedWindow, Radiobutton, Scale and Scrollbar. The other six are new: Combobox, Notebook, Progressbar, Separator, Sizegrip and Treeview. And all them are subclasses of Widget.

Using the Ttk widgets gives the application an improved look and feel. As discussed above, there are differences in how the styling is coded.

Tk code:

l1 = tkinter.Label(text="Test", fg="black", bg="white")
l2 = tkinter.Label(text="Test", fg="black", bg="white")

Ttk code:

style = ttk.Style()
style.configure("BW.TLabel", foreground="black", background="white")

l1 = ttk.Label(text="Test", style="BW.TLabel")
l2 = ttk.Label(text="Test", style="BW.TLabel")

For more information about TtkStyling, see the Style class documentation.

25.2.3. Widget

ttk.Widget defines standard options and methods supported by Tk themed widgets and is not supposed to be directly instantiated.

25.2.3.1. Standard Options

All the ttk Widgets accepts the following options:

Option

Description

classe

Specifies the window class. The class is used when querying the option database for the window’s other options, to determine the default bindtags for the window, and to select the widget’s default layout and style. This option is read-only, and may only be specified when the window is created.

cursor

Specifies the mouse cursor to be used for the widget. If set to the empty string (the default), the cursor is inherited for the parent widget.

takefocus

Determines whether the window accepts the focus during keyboard traversal. 0, 1 or an empty string is returned. If 0 is returned, it means that the window should be skipped entirely during keyboard traversal. If 1, it means that the window should receive the input focus as long as it is viewable. And an empty string means that the traversal scripts make the decision about whether or not to focus on the window.

style

May be used to specify a custom widget style.

25.2.3.2. Scrollable Widget Options

The following options are supported by widgets that are controlled by a scrollbar.

Option

Description

xscrollcommand

Used to communicate with horizontal scrollbars.

When the view in the widget’s window change, the widget will generate a Tcl command based on the scrollcommand.

Usually this option consists of the method Scrollbar.set() of some scrollbar. This will cause the scrollbar to be updated whenever the view in the window changes.

yscrollcommand

Used to communicate with vertical scrollbars. For some more information, see above.

25.2.3.3. Label Options

The following options are supported by labels, buttons and other button-like widgets.

Option

Description

text

Specifies a text string to be displayed inside the widget.

textvariable

Specifies a name whose value will be used in place of the text option resource.

underline

If set, specifies the index (0-based) of a character to underline in the text string. The underline character is used for mnemonic activation.

image

Specifies an image to display. This is a list of 1 or more elements. The first element is the default image name. The rest of the list if a sequence of statespec/value pairs as defined by Style.map(), specifying different images to use when the widget is in a particular state or a combination of states. All images in the list should have the same size.

compound

Specifies how to display the image relative to the text, in the case both text and images options are present. Valid values are:

text: display text only

image: display image only

top, bottom, left, right: display image above, below, left of, or right of the text, respectively.

none: the default. display the image if present, otherwise the text.

width

If greater than zero, specifies how much space, in character widths, to allocate for the text label, if less than zero, specifies a minimum width. If zero or unspecified, the natural width of the text label is used.

25.2.3.4. Compatibility Options

Option

Description

state

May be set to « normal » or « disabled » to control the « disabled » state bit. This is a write-only option: setting it changes the widget state, but the Widget.state() method does not affect this option.

25.2.3.5. Widget States

The widget state is a bitmap of independent state flags.

Option

Description

active

The mouse cursor is over the widget and pressing a mouse button will cause some action to occur

disabled

Widget is disabled under program control

focus

Widget has keyboard focus

pressed

Widget is being pressed

selected

« On », « true », or « current » for things like Checkbuttons and radiobuttons

background

Windows and Mac have a notion of an « active » or foreground window. The background state is set for widgets in a background window, and cleared for those in the foreground window

readonly

Widget should not allow user modification

alternate

A widget-specific alternate display format

invalid

The widget’s value is invalid

A state specification is a sequence of state names, optionally prefixed with an exclamation point indicating that the bit is off.

25.2.3.6. ttk.Widget

Besides the methods described below, the ttk.Widget supports the methods tkinter.Widget.cget() and tkinter.Widget.configure().

class tkinter.ttk.Widget

identify(x, y)

Returns the name of the element at position x y, or the empty string if the point does not lie within any element.

x and y are pixel coordinates relative to the widget.

instate(statespec, callback=None, *args, **kw)

Test the widget’s state. If a callback is not specified, returns True if the widget state matches statespec and False otherwise. If callback is specified then it is called with args if widget state matches statespec.

state(statespec=None)

Modify or inquire widget state. If statespec is specified, sets the widget state according to it and return a new statespec indicating which flags were changed. If statespec is not specified, returns the currently-enabled state flags.

statespec will usually be a list or a tuple.

25.2.4. Combobox

The ttk.Combobox widget combines a text field with a pop-down list of values. This widget is a subclass of Entry.

Besides the methods inherited from Widget: Widget.cget(), Widget.configure(), Widget.identify(), Widget.instate() and Widget.state(), and the following inherited from Entry: Entry.bbox(), Entry.delete(), Entry.icursor(), Entry.index(), Entry.insert(), Entry.selection(), Entry.xview(), it has some other methods, described at ttk.Combobox.

25.2.4.1. Options

This widget accepts the following specific options:

Option

Description

exportselection

Boolean value. If set, the widget selection is linked to the Window Manager selection (which can be returned by invoking Misc.selection_get, for example).

justify

Specifies how the text is aligned within the widget. One of « left », « center », or « right ».

height

Specifies the height of the pop-down listbox, in rows.

postcommand

A script (possibly registered with Misc.register) that is called immediately before displaying the values. It may specify which values to display.

state

One of « normal », « readonly », or « disabled ». In the « readonly » state, the value may not be edited directly, and the user can only selection of the values from the dropdown list. In the « normal » state, the text field is directly editable. In the « disabled » state, no interaction is possible.

textvariable

Specifies a name whose value is linked to the widget value. Whenever the value associated with that name changes, the widget value is updated, and vice versa. See tkinter.StringVar.

valeurs

Specifies the list of values to display in the drop-down listbox.

width

Specifies an integer value indicating the desired width of the entry window, in average-size characters of the widget’s font.

25.2.4.2. Virtual events

The combobox widgets generates a <<ComboboxSelected>> virtual event when the user selects an element from the list of values.

25.2.4.3. ttk.Combobox

class tkinter.ttk.Combobox

current(newindex=None)

If newindex is specified, sets the combobox value to the element position newindex. Otherwise, returns the index of the current value or -1 if the current value is not in the values list.

get()

Returns the current value of the combobox.

set(value)

Sets the value of the combobox to value.

25.2.5. Notebook

Ttk Notebook widget manages a collection of windows and displays a single one at a time. Each child window is associated with a tab, which the user may select to change the currently-displayed window.

25.2.5.1. Options

This widget accepts the following specific options:

Option

Description

height

If present and greater than zero, specifies the desired height of the pane area (not including internal padding or tabs). Otherwise, the maximum height of all panes is used.

padding

Specifies the amount of extra space to add around the outside of the notebook. The padding is a list up to four length specifications left top right bottom. If fewer than four elements are specified, bottom defaults to top, right defaults to left, and top defaults to left.

width

If present and greater than zero, specified the desired width of the pane area (not including internal padding). Otherwise, the maximum width of all panes is used.

25.2.5.2. Tab Options

There are also specific options for tabs:

Option

Description

state

Either « normal », « disabled » or « hidden ». If « disabled », then the tab is not selectable. If « hidden », then the tab is not shown.

sticky

Specifies how the child window is positioned within the pane area. Value is a string containing zero or more of the characters « n », « s », « e » or « w ». Each letter refers to a side (north, south, east or west) that the child window will stick to, as per the grid() geometry manager.

padding

Specifies the amount of extra space to add between the notebook and this pane. Syntax is the same as for the option padding used by this widget.

text

Specifies a text to be displayed in the tab.

image

Specifies an image to display in the tab. See the option image described in Widget.

compound

Specifies how to display the image relative to the text, in the case both options text and image are present. See Label Options for legal values.

underline

Specifies the index (0-based) of a character to underline in the text string. The underlined character is used for mnemonic activation if Notebook.enable_traversal() is called.

25.2.5.3. Tab Identifiers

The tab_id present in several methods of ttk.Notebook may take any of the following forms:

An integer between zero and the number of tabs

The name of a child window

A positional specification of the form « @x,y », which identifies the tab

The literal string « current », which identifies the currently-selected tab

The literal string « end », which returns the number of tabs (only valid for Notebook.index())

25.2.5.4. Virtual Events

This widget generates a <<NotebookTabChanged>> virtual event after a new tab is selected.

25.2.5.5. ttk.Notebook

class tkinter.ttk.Notebook

add(child, **kw)

Adds a new tab to the notebook.

If window is currently managed by the notebook but hidden, it is restored to its previous position.

See Tab Options for the list of available options.

forget(tab_id)

Removes the tab specified by tab_id, unmaps and unmanages the associated window.

hide(tab_id)

Hides the tab specified by tab_id.

The tab will not be displayed, but the associated window remains managed by the notebook and its configuration remembered. Hidden tabs may be restored with the add() command.

identify(x, y)

Returns the name of the tab element at position x, y, or the empty string if none.

index(tab_id)

Returns the numeric index of the tab specified by tab_id, or the total number of tabs if tab_id is the string « end ».

insert(pos, child, **kw)

Inserts a pane at the specified position.

pos is either the string « end », an integer index, or the name of a managed child. If child is already managed by the notebook, moves it to the specified position.

See Tab Options for the list of available options.

select(tab_id=None)

Selects the specified tab_id.

The associated child window will be displayed, and the previously-selected window (if different) is unmapped. If tab_id is omitted, returns the widget name of the currently selected pane.

tab(tab_id, option=None, **kw)

Query or modify the options of the specific tab_id.

If kw is not given, returns a dictionary of the tab option values. If option is specified, returns the value of that option. Otherwise, sets the options to the corresponding values.

tabs()

Returns a list of windows managed by the notebook.

enable_traversal()

Enable keyboard traversal for a toplevel window containing this notebook.

This will extend the bindings for the toplevel window containing the notebook as follows:

Control-Tab: selects the tab following the currently selected one.

Shift-Control-Tab: selects the tab preceding the currently selected one.

Alt-K: where K is the mnemonic (underlined) character of any tab, will select that tab.

Multiple notebooks in a single toplevel may be enabled for traversal, including nested notebooks. However, notebook traversal only works properly if all panes have the notebook they are in as master.

25.2.6. Progressbar

The ttk.Progressbar widget shows the status of a long-running operation. It can operate in two modes: 1) the determinate mode which shows the amount completed relative to the total amount of work to be done and 2) the indeterminate mode which provides an animated display to let the user know that work is progressing.

25.2.6.1. Options

This widget accepts the following specific options:

Option

Description

orient

One of « horizontal » or « vertical ». Specifies the orientation of the progress bar.

length

Specifies the length of the long axis of the progress bar (width if horizontal, height if vertical).

mode

One of « determinate » or « indeterminate ».

maximum

A number specifying the maximum value. Defaults to 100.

valeur

The current value of the progress bar. In « determinate » mode, this represents the amount of work completed. In « indeterminate » mode, it is interpreted as modulo maximum; that is, the progress bar completes one « cycle » when its value increases by maximum.

variable

A name which is linked to the option value. If specified, the value of the progress bar is automatically set to the value of this name whenever the latter is modified.

phase

Read-only option. The widget periodically increments the value of this option whenever its value is greater than 0 and, in determinate mode, less than maximum. This option may be used by the current theme to provide additional animation effects.

25.2.6.2. ttk.Progressbar

class tkinter.ttk.Progressbar

start(interval=None)

Begin autoincrement mode: schedules a recurring timer event that calls Progressbar.step() every interval milliseconds. If omitted, interval defaults to 50 milliseconds.

step(amount=None)

Increments the progress bar’s value by amount.

amount defaults to 1.0 if omitted.

stop()

Stop autoincrement mode: cancels any recurring timer event initiated by Progressbar.start() for this progress bar.

25.2.7. Separator

The ttk.Separator widget displays a horizontal or vertical separator bar.

It has no other methods besides the ones inherited from ttk.Widget.

25.2.7.1. Options

This widget accepts the following specific option:

Option

Description

orient

One of « horizontal » or « vertical ». Specifies the orientation of the separator.

25.2.8. Sizegrip

The ttk.Sizegrip widget (also known as a grow box) allows the user to resize the containing toplevel window by pressing and dragging the grip.

This widget has neither specific options nor specific methods, besides the ones inherited from ttk.Widget.

25.2.8.1. Platform-specific notes

On MacOS X, toplevel windows automatically include a built-in size grip by default. Adding a Sizegrip is harmless, since the built-in grip will just mask the widget.

25.2.8.2. Bugs

If the containing toplevel’s position was specified relative to the right or bottom of the screen (e.g. ….), the Sizegrip widget will not resize the window.

This widget supports only « southeast » resizing.

25.2.9. Treeview

The ttk.Treeview widget displays a hierarchical collection of items. Each item has a textual label, an optional image, and an optional list of data values. The data values are displayed in successive columns after the tree label.

The order in which data values are displayed may be controlled by setting the widget option displaycolumns. The tree widget can also display column headings. Columns may be accessed by number or symbolic names listed in the widget option columns. See Column Identifiers.

Each item is identified by a unique name. The widget will generate item IDs if they are not supplied by the caller. There is a distinguished root item, named {}. The root item itself is not displayed; its children appear at the top level of the hierarchy.

Each item also has a list of tags, which can be used to associate event bindings with individual items and control the appearance of the item.

The Treeview widget supports horizontal and vertical scrolling, according to the options described in Scrollable Widget Options and the methods Treeview.xview() and Treeview.yview().

25.2.9.1. Options

This widget accepts the following specific options:

Option

Description

columns

A list of column identifiers, specifying the number of columns and their names.

displaycolumns

A list of column identifiers (either symbolic or integer indices) specifying which data columns are displayed and the order in which they appear, or the string « #all ».

height

Specifies the number of rows which should be visible. Note: the requested width is determined from the sum of the column widths.

padding

Specifies the internal padding for the widget. The padding is a list of up to four length specifications.

selectmode

Controls how the built-in class bindings manage the selection. One of « extended », « browse » or « none ». If set to « extended » (the default), multiple items may be selected. If « browse », only a single item will be selected at a time. If « none », the selection will not be changed.

Note that the application code and tag bindings can set the selection however they wish, regardless of the value of this option.

show

A list containing zero or more of the following values, specifying which elements of the tree to display.

tree: display tree labels in column #0.

headings: display the heading row.

The default is « tree headings », i.e., show all elements.

Note: Column #0 always refers to the tree column, even if show= »tree » is not specified.

25.2.9.2. Item Options

The following item options may be specified for items in the insert and item widget commands.

Option

Description

text

The textual label to display for the item.

image

A Tk Image, displayed to the left of the label.

valeurs

The list of values associated with the item.

Each item should have the same number of values as the widget option columns. If there are fewer values than columns, the remaining values are assumed empty. If there are more values than columns, the extra values are ignored.

open

True/False value indicating whether the item’s children should be displayed or hidden.

tags

A list of tags associated with this item.

25.2.9.3. Tag Options

The following options may be specified on tags:

Option

Description

foreground

Specifies the text foreground color.

background

Specifies the cell or item background color.

font

Specifies the font to use when drawing text.

image

Specifies the item image, in case the item’s image option is empty.

25.2.9.4. Column Identifiers

Column identifiers take any of the following forms:

A symbolic name from the list of columns option.

An integer n, specifying the nth data column.

A string of the form #n, where n is an integer, specifying the nth display column.

Notes :

Item’s option values may be displayed in a different order than the order in which they are stored.

Column #0 always refers to the tree column, even if show= »tree » is not specified.

A data column number is an index into an item’s option values list; a display column number is the column number in the tree where the values are displayed. Tree labels are displayed in column #0. If option displaycolumns is not set, then data column n is displayed in column #n+1. Again, column #0 always refers to the tree column.

25.2.9.5. Virtual Events

The Treeview widget generates the following virtual events.

Event

Description

<<TreeviewSelect>>

Generated whenever the selection changes.

<<TreeviewOpen>>

Generated just before settings the focus item to open=True.

<<TreeviewClose>>

Generated just after setting the focus item to open=False.

The Treeview.focus() and Treeview.selection() methods can be used to determine the affected item or items.

25.2.9.6. ttk.Treeview

class tkinter.ttk.Treeview

bbox(item, column=None)

Returns the bounding box (relative to the treeview widget’s window) of the specified item in the form (x, y, width, height).

If column is specified, returns the bounding box of that cell. If the item is not visible (i.e., if it is a descendant of a closed item or is scrolled offscreen), returns an empty string.

get_children(item=None)

Returns the list of children belonging to item.

If item is not specified, returns root children.

set_children(item, *newchildren)

Replaces item’s child with newchildren.

Children present in item that are not present in newchildren are detached from the tree. No items in newchildren may be an ancestor of item. Note that not specifying newchildren results in detaching item’s children.

column(column, option=None, **kw)

Query or modify the options for the specified column.

If kw is not given, returns a dict of the column option values. If option is specified then the value for that option is returned. Otherwise, sets the options to the corresponding values.

The valid options/values are:

id

Returns the column name. This is a read-only option.

anchor: One of the standard Tk anchor values.

Specifies how the text in this column should be aligned with respect to the cell.

minwidth: width

The minimum width of the column in pixels. The treeview widget will not make the column any smaller than specified by this option when the widget is resized or the user drags a column.

stretch: True/False

Specifies whether the column’s width should be adjusted when the widget is resized.

width: width

The width of the column in pixels.

To configure the tree column, call this with column = « #0 »

delete(*items)

Delete all specified items and all their descendants.

The root item may not be deleted.

detach(*items)

Unlinks all of the specified items from the tree.

The items and all of their descendants are still present, and may be reinserted at another point in the tree, but will not be displayed.

The root item may not be detached.

exists(item)

Returns True if the specified item is present in the tree.

focus(item=None)

If item is specified, sets the focus item to item. Otherwise, returns the current focus item, or “” if there is none.

heading(column, option=None, **kw)

Query or modify the heading options for the specified column.

If kw is not given, returns a dict of the heading option values. If option is specified then the value for that option is returned. Otherwise, sets the options to the corresponding values.

The valid options/values are:

text: text

The text to display in the column heading.

image: imageName

Specifies an image to display to the right of the column heading.

anchor: anchor

Specifies how the heading text should be aligned. One of the standard Tk anchor values.

command: callback

A callback to be invoked when the heading label is pressed.

To configure the tree column heading, call this with column = « #0 ».

identify(component, x, y)

Returns a description of the specified component under the point given by x and y, or the empty string if no such component is present at that position.

identify_row(y)

Returns the item ID of the item at position y.

identify_column(x)

Returns the data column identifier of the cell at position x.

The tree column has ID #0.

identify_region(x, y)

Returns one of:

region

meaning

heading

Tree heading area.

separator

Space between two columns headings.

tree

The tree area.

cell

A data cell.

Availability: Tk 8.6.

identify_element(x, y)

Returns the element at position x, y.

Availability: Tk 8.6.

index(item)

Returns the integer index of item within its parent’s list of children.

insert(parent, index, iid=None, **kw)

Creates a new item and returns the item identifier of the newly created item.

parent is the item ID of the parent item, or the empty string to create a new top-level item. index is an integer, or the value « end », specifying where in the list of parent’s children to insert the new item. If index is less than or equal to zero, the new node is inserted at the beginning; if index is greater than or equal to the current number of children, it is inserted at the end. If iid is specified, it is used as the item identifier; iid must not already exist in the tree. Otherwise, a new unique identifier is generated.

See Item Options for the list of available points.

item(item, option=None, **kw)

Query or modify the options for the specified item.

If no options are given, a dict with options/values for the item is returned. If option is specified then the value for that option is returned. Otherwise, sets the options to the corresponding values as given by kw.

move(item, parent, index)

Moves item to position index in parent’s list of children.

It is illegal to move an item under one of its descendants. If index is less than or equal to zero, item is moved to the beginning; if greater than or equal to the number of children, it is moved to the end. If item was detached it is reattached.

next(item)

Returns the identifier of item’s next sibling, or “” if item is the last child of its parent.

parent(item)

Returns the ID of the parent of item, or “” if item is at the top level of the hierarchy.

prev(item)

Returns the identifier of item’s previous sibling, or “” if item is the first child of its parent.

reattach(item, parent, index)

An alias for Treeview.move().

see(item)

Ensure that item is visible.

Sets all of item’s ancestors open option to True, and scrolls the widget if necessary so that item is within the visible portion of the tree.

selection(selop=None, items=None)

If selop is not specified, returns selected items. Otherwise, it will act according to the following selection methods.

Deprecated since version 3.6, will be removed in version 3.8: Using selection() for changing the selection state is deprecated. Use the following selection methods instead.

selection_set(*items)

items becomes the new selection.

Modifié dans la version 3.6: items can be passed as separate arguments, not just as a single tuple.

selection_add(*items)

Add items to the selection.

Modifié dans la version 3.6: items can be passed as separate arguments, not just as a single tuple.

selection_remove(*items)

Remove items from the selection.

Modifié dans la version 3.6: items can be passed as separate arguments, not just as a single tuple.

selection_toggle(*items)

Toggle the selection state of each item in items.

Modifié dans la version 3.6: items can be passed as separate arguments, not just as a single tuple.

set(item, column=None, value=None)

With one argument, returns a dictionary of column/value pairs for the specified item. With two arguments, returns the current value of the specified column. With three arguments, sets the value of given column in given item to the specified value.

tag_bind(tagname, sequence=None, callback=None)

Bind a callback for the given event sequence to the tag tagname. When an event is delivered to an item, the callbacks for each of the item’s tags option are called.

tag_configure(tagname, option=None, **kw)

Query or modify the options for the specified tagname.

If kw is not given, returns a dict of the option settings for tagname. If option is specified, returns the value for that option for the specified tagname. Otherwise, sets the options to the corresponding values for the given tagname.

tag_has(tagname, item=None)

If item is specified, returns 1 or 0 depending on whether the specified item has the given tagname. Otherwise, returns a list of all items that have the specified tag.

Availability: Tk 8.6

xview(*args)

Query or modify horizontal position of the treeview.

yview(*args)

Query or modify vertical position of the treeview.

25.2.10. Ttk Styling

Each widget in ttk is assigned a style, which specifies the set of elements making up the widget and how they are arranged, along with dynamic and default settings for element options. By default the style name is the same as the widget’s class name, but it may be overridden by the widget’s style option. If you don’t know the class name of a widget, use the method Misc.winfo_class() (somewidget.winfo_class()).

Voir aussi

Tcl’2004 conference presentation [http://tktable.sourceforge.net/tile/tile-tcl2004.pdf]

This document explains how the theme engine works

class tkinter.ttk.Style

This class is used to manipulate the style database.

configure(style, query_opt=None, **kw)

Query or set the default value of the specified option(s) in style.

Each key in kw is an option and each value is a string identifying the value for that option.

For example, to change every default button to be a flat button with some padding and a different background color:

from tkinter import ttk
import tkinter

root = tkinter.Tk()

ttk.Style().configure("TButton", padding=6, relief="flat",
   background="#ccc")

btn = ttk.Button(text="Sample")
btn.pack()

root.mainloop()

map(style, query_opt=None, **kw)

Query or sets dynamic values of the specified option(s) in style.

Each key in kw is an option and each value should be a list or a tuple (usually) containing statespecs grouped in tuples, lists, or some other preference. A statespec is a compound of one or more states and then a value.

An example may make it more understandable:

import tkinter
from tkinter import ttk

root = tkinter.Tk()

style = ttk.Style()
style.map("C.TButton",
    foreground=[('pressed', 'red'), ('active', 'blue')],
    background=[('pressed', '!disabled', 'black'), ('active', 'white')]
    )

colored_btn = ttk.Button(text="Test", style="C.TButton").pack()

root.mainloop()

Note that the order of the (states, value) sequences for an option does matter, if the order is changed to [('active', 'blue'), ('pressed', 'red')] in the foreground option, for example, the result would be a blue foreground when the widget were in active or pressed states.

lookup(style, option, state=None, default=None)

Returns the value specified for option in style.

If state is specified, it is expected to be a sequence of one or more states. If the default argument is set, it is used as a fallback value in case no specification for option is found.

To check what font a Button uses by default:

from tkinter import ttk

print(ttk.Style().lookup("TButton", "font"))

layout(style, layoutspec=None)

Define the widget layout for given style. If layoutspec is omitted, return the layout specification for given style.

layoutspec, if specified, is expected to be a list or some other sequence type (excluding strings), where each item should be a tuple and the first item is the layout name and the second item should have the format described in Layouts.

To understand the format, see the following example (it is not intended to do anything useful):

from tkinter import ttk
import tkinter

root = tkinter.Tk()

style = ttk.Style()
style.layout("TMenubutton", [
   ("Menubutton.background", None),
   ("Menubutton.button", {"children":
       [("Menubutton.focus", {"children":
           [("Menubutton.padding", {"children":
               [("Menubutton.label", {"side": "left", "expand": 1})]
           })]
       })]
   }),
])

mbtn = ttk.Menubutton(text='Text')
mbtn.pack()
root.mainloop()

element_create(elementname, etype, *args, **kw)

Create a new element in the current theme, of the given etype which is expected to be either « image », « from » or « vsapi ». The latter is only available in Tk 8.6a for Windows XP and Vista and is not described here.

If « image » is used, args should contain the default image name followed by statespec/value pairs (this is the imagespec), and kw may have the following options:

border=padding

padding is a list of up to four integers, specifying the left, top, right, and bottom borders, respectively.

height=height

Specifies a minimum height for the element. If less than zero, the base image’s height is used as a default.

padding=padding

Specifies the element’s interior padding. Defaults to border’s value if not specified.

sticky=spec

Specifies how the image is placed within the final parcel. spec contains zero or more characters « n », « s », « w », or « e ».

width=width

Specifies a minimum width for the element. If less than zero, the base image’s width is used as a default.

If « from » is used as the value of etype, element_create() will clone an existing element. args is expected to contain a themename, from which the element will be cloned, and optionally an element to clone from. If this element to clone from is not specified, an empty element will be used. kw is discarded.

element_names()

Returns the list of elements defined in the current theme.

element_options(elementname)

Returns the list of elementname’s options.

theme_create(themename, parent=None, settings=None)

Create a new theme.

It is an error if themename already exists. If parent is specified, the new theme will inherit styles, elements and layouts from the parent theme. If settings are present they are expected to have the same syntax used for theme_settings().

theme_settings(themename, settings)

Temporarily sets the current theme to themename, apply specified settings and then restore the previous theme.

Each key in settings is a style and each value may contain the keys “configure”, “map”, “layout” and “element create” and they are expected to have the same format as specified by the methods Style.configure(), Style.map(), Style.layout() and Style.element_create() respectively.

As an example, let’s change the Combobox for the default theme a bit:

from tkinter import ttk
import tkinter

root = tkinter.Tk()

style = ttk.Style()
style.theme_settings("default", {
   "TCombobox": {
       "configure": {"padding": 5},
       "map": {
           "background": [("active", "green2"),
                          ("!disabled", "green4")],
           "fieldbackground": [("!disabled", "green3")],
           "foreground": [("focus", "OliveDrab1"),
                          ("!disabled", "OliveDrab2")]
       }
   }
})

combo = ttk.Combobox().pack()

root.mainloop()

theme_names()

Returns a list of all known themes.

theme_use(themename=None)

If themename is not given, returns the theme in use. Otherwise, sets the current theme to themename, refreshes all widgets and emits a <<ThemeChanged>> event.

25.2.10.1. Layouts

A layout can be just None, if it takes no options, or a dict of options specifying how to arrange the element. The layout mechanism uses a simplified version of the pack geometry manager: given an initial cavity, each element is allocated a parcel. Valid options/values are:

side: whichside

Specifies which side of the cavity to place the element; one of top, right, bottom or left. If omitted, the element occupies the entire cavity.

sticky: nswe

Specifies where the element is placed inside its allocated parcel.

unit: 0 or 1

If set to 1, causes the element and all of its descendants to be treated as a single element for the purposes of Widget.identify() et al. It’s used for things like scrollbar thumbs with grips.

children: [sublayout… ]

Specifies a list of elements to place inside the element. Each element is a tuple (or other sequence type) where the first item is the layout name, and the other is a Layout.

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25.3. tkinter.tix — Extension widgets for Tk

Source code: Lib/tkinter/tix.py [https://github.com/python/cpython/tree/3.6/Lib/tkinter/tix.py]

Obsolète depuis la version 3.6: This Tk extension is unmaintained and should not be used in new code. Use tkinter.ttk instead.

The tkinter.tix (Tk Interface Extension) module provides an additional rich set of widgets. Although the standard Tk library has many useful widgets, they are far from complete. The tkinter.tix library provides most of the commonly needed widgets that are missing from standard Tk: HList, ComboBox, Control (a.k.a. SpinBox) and an assortment of scrollable widgets. tkinter.tix also includes many more widgets that are generally useful in a wide range of applications: NoteBook, FileEntry, PanedWindow, etc; there are more than 40 of them.

With all these new widgets, you can introduce new interaction techniques into applications, creating more useful and more intuitive user interfaces. You can design your application by choosing the most appropriate widgets to match the special needs of your application and users.

Voir aussi

Tix Homepage [http://tix.sourceforge.net/]

The home page for Tix. This includes links to additional documentation and downloads.

Tix Man Pages [http://tix.sourceforge.net/dist/current/man/]

On-line version of the man pages and reference material.

Tix Programming Guide [http://tix.sourceforge.net/dist/current/docs/tix-book/tix.book.html]

On-line version of the programmer’s reference material.

Tix Development Applications [http://tix.sourceforge.net/Tixapps/src/Tide.html]

Tix applications for development of Tix and Tkinter programs. Tide applications work under Tk or Tkinter, and include TixInspect, an inspector to remotely modify and debug Tix/Tk/Tkinter applications.

25.3.1. Using Tix

class tkinter.tix.Tk(screenName=None, baseName=None, className='Tix')

Toplevel widget of Tix which represents mostly the main window of an application. It has an associated Tcl interpreter.

Classes in the tkinter.tix module subclasses the classes in the tkinter. The former imports the latter, so to use tkinter.tix with Tkinter, all you need to do is to import one module. In general, you can just import tkinter.tix, and replace the toplevel call to tkinter.Tk with tix.Tk:

from tkinter import tix
from tkinter.constants import *
root = tix.Tk()

To use tkinter.tix, you must have the Tix widgets installed, usually alongside your installation of the Tk widgets. To test your installation, try the following:

from tkinter import tix
root = tix.Tk()
root.tk.eval('package require Tix')

If this fails, you have a Tk installation problem which must be resolved before proceeding. Use the environment variable TIX_LIBRARY to point to the installed Tix library directory, and make sure you have the dynamic object library (tix8183.dll or libtix8183.so) in the same directory that contains your Tk dynamic object library (tk8183.dll or libtk8183.so). The directory with the dynamic object library should also have a file called pkgIndex.tcl (case sensitive), which contains the line:

package ifneeded Tix 8.1 [list load "[file join $dir tix8183.dll]" Tix]

25.3.2. Tix Widgets

Tix [http://tix.sourceforge.net/dist/current/man/html/TixCmd/TixIntro.htm] introduces over 40 widget classes to the tkinter repertoire.

25.3.2.1. Basic Widgets

class tkinter.tix.Balloon

A Balloon [http://tix.sourceforge.net/dist/current/man/html/TixCmd/tixBalloon.htm] that pops up over a widget to provide help. When the user moves the cursor inside a widget to which a Balloon widget has been bound, a small pop-up window with a descriptive message will be shown on the screen.

class tkinter.tix.ButtonBox

The ButtonBox [http://tix.sourceforge.net/dist/current/man/html/TixCmd/tixButtonBox.htm] widget creates a box of buttons, such as is commonly used for Ok Cancel.

class tkinter.tix.ComboBox

The ComboBox [http://tix.sourceforge.net/dist/current/man/html/TixCmd/tixComboBox.htm] widget is similar to the combo box control in MS Windows. The user can select a choice by either typing in the entry subwidget or selecting from the listbox subwidget.

class tkinter.tix.Control

The Control [http://tix.sourceforge.net/dist/current/man/html/TixCmd/tixControl.htm] widget is also known as the SpinBox widget. The user can adjust the value by pressing the two arrow buttons or by entering the value directly into the entry. The new value will be checked against the user-defined upper and lower limits.

class tkinter.tix.LabelEntry

The LabelEntry [http://tix.sourceforge.net/dist/current/man/html/TixCmd/tixLabelEntry.htm] widget packages an entry widget and a label into one mega widget. It can be used to simplify the creation of « entry-form » type of interface.

class tkinter.tix.LabelFrame

The LabelFrame [http://tix.sourceforge.net/dist/current/man/html/TixCmd/tixLabelFrame.htm] widget packages a frame widget and a label into one mega widget. To create widgets inside a LabelFrame widget, one creates the new widgets relative to the frame subwidget and manage them inside the frame subwidget.

class tkinter.tix.Meter

The Meter [http://tix.sourceforge.net/dist/current/man/html/TixCmd/tixMeter.htm] widget can be used to show the progress of a background job which may take a long time to execute.

class tkinter.tix.OptionMenu

The OptionMenu [http://tix.sourceforge.net/dist/current/man/html/TixCmd/tixOptionMenu.htm] creates a menu button of options.

class tkinter.tix.PopupMenu

The PopupMenu [http://tix.sourceforge.net/dist/current/man/html/TixCmd/tixPopupMenu.htm] widget can be used as a replacement of the tk_popup command. The advantage of the Tix PopupMenu widget is it requires less application code to manipulate.

class tkinter.tix.Select

The Select [http://tix.sourceforge.net/dist/current/man/html/TixCmd/tixSelect.htm] widget is a container of button subwidgets. It can be used to provide radio-box or check-box style of selection options for the user.

class tkinter.tix.StdButtonBox

The StdButtonBox [http://tix.sourceforge.net/dist/current/man/html/TixCmd/tixStdButtonBox.htm] widget is a group of standard buttons for Motif-like dialog boxes.

25.3.2.2. File Selectors

class tkinter.tix.DirList

The DirList [http://tix.sourceforge.net/dist/current/man/html/TixCmd/tixDirList.htm] widget displays a list view of a directory, its previous directories and its sub-directories. The user can choose one of the directories displayed in the list or change to another directory.

class tkinter.tix.DirTree

The DirTree [http://tix.sourceforge.net/dist/current/man/html/TixCmd/tixDirTree.htm] widget displays a tree view of a directory, its previous directories and its sub-directories. The user can choose one of the directories displayed in the list or change to another directory.

class tkinter.tix.DirSelectDialog

The DirSelectDialog [http://tix.sourceforge.net/dist/current/man/html/TixCmd/tixDirSelectDialog.htm] widget presents the directories in the file system in a dialog window. The user can use this dialog window to navigate through the file system to select the desired directory.

class tkinter.tix.DirSelectBox

The DirSelectBox is similar to the standard Motif(TM) directory-selection box. It is generally used for the user to choose a directory. DirSelectBox stores the directories mostly recently selected into a ComboBox widget so that they can be quickly selected again.

class tkinter.tix.ExFileSelectBox

The ExFileSelectBox [http://tix.sourceforge.net/dist/current/man/html/TixCmd/tixExFileSelectBox.htm] widget is usually embedded in a tixExFileSelectDialog widget. It provides a convenient method for the user to select files. The style of the ExFileSelectBox widget is very similar to the standard file dialog on MS Windows 3.1.

class tkinter.tix.FileSelectBox

The FileSelectBox [http://tix.sourceforge.net/dist/current/man/html/TixCmd/tixFileSelectBox.htm] is similar to the standard Motif(TM) file-selection box. It is generally used for the user to choose a file. FileSelectBox stores the files mostly recently selected into a ComboBox widget so that they can be quickly selected again.

class tkinter.tix.FileEntry

The FileEntry [http://tix.sourceforge.net/dist/current/man/html/TixCmd/tixFileEntry.htm] widget can be used to input a filename. The user can type in the filename manually. Alternatively, the user can press the button widget that sits next to the entry, which will bring up a file selection dialog.

25.3.2.3. Hierarchical ListBox

class tkinter.tix.HList

The HList [http://tix.sourceforge.net/dist/current/man/html/TixCmd/tixHList.htm] widget can be used to display any data that have a hierarchical structure, for example, file system directory trees. The list entries are indented and connected by branch lines according to their places in the hierarchy.

class tkinter.tix.CheckList

The CheckList [http://tix.sourceforge.net/dist/current/man/html/TixCmd/tixCheckList.htm] widget displays a list of items to be selected by the user. CheckList acts similarly to the Tk checkbutton or radiobutton widgets, except it is capable of handling many more items than checkbuttons or radiobuttons.

class tkinter.tix.Tree

The Tree [http://tix.sourceforge.net/dist/current/man/html/TixCmd/tixTree.htm] widget can be used to display hierarchical data in a tree form. The user can adjust the view of the tree by opening or closing parts of the tree.

25.3.2.4. Tabular ListBox

class tkinter.tix.TList

The TList [http://tix.sourceforge.net/dist/current/man/html/TixCmd/tixTList.htm] widget can be used to display data in a tabular format. The list entries of a TList widget are similar to the entries in the Tk listbox widget. The main differences are (1) the TList widget can display the list entries in a two dimensional format and (2) you can use graphical images as well as multiple colors and fonts for the list entries.

25.3.2.5. Manager Widgets

class tkinter.tix.PanedWindow

The PanedWindow [http://tix.sourceforge.net/dist/current/man/html/TixCmd/tixPanedWindow.htm] widget allows the user to interactively manipulate the sizes of several panes. The panes can be arranged either vertically or horizontally. The user changes the sizes of the panes by dragging the resize handle between two panes.

class tkinter.tix.ListNoteBook

The ListNoteBook [http://tix.sourceforge.net/dist/current/man/html/TixCmd/tixListNoteBook.htm] widget is very similar to the TixNoteBook widget: it can be used to display many windows in a limited space using a notebook metaphor. The notebook is divided into a stack of pages (windows). At one time only one of these pages can be shown. The user can navigate through these pages by choosing the name of the desired page in the hlist subwidget.

class tkinter.tix.NoteBook

The NoteBook [http://tix.sourceforge.net/dist/current/man/html/TixCmd/tixNoteBook.htm] widget can be used to display many windows in a limited space using a notebook metaphor. The notebook is divided into a stack of pages. At one time only one of these pages can be shown. The user can navigate through these pages by choosing the visual « tabs » at the top of the NoteBook widget.

25.3.2.6. Image Types

The tkinter.tix module adds:

pixmap [http://tix.sourceforge.net/dist/current/man/html/TixCmd/pixmap.htm] capabilities to all tkinter.tix and tkinter widgets to create color images from XPM files.

Compound [http://tix.sourceforge.net/dist/current/man/html/TixCmd/compound.htm] image types can be used to create images that consists of multiple horizontal lines; each line is composed of a series of items (texts, bitmaps, images or spaces) arranged from left to right. For example, a compound image can be used to display a bitmap and a text string simultaneously in a Tk Button widget.

25.3.2.7. Miscellaneous Widgets

class tkinter.tix.InputOnly

The InputOnly [http://tix.sourceforge.net/dist/current/man/html/TixCmd/tixInputOnly.htm] widgets are to accept inputs from the user, which can be done with the bind command (Unix only).

25.3.2.8. Form Geometry Manager

In addition, tkinter.tix augments tkinter by providing:

class tkinter.tix.Form

The Form [http://tix.sourceforge.net/dist/current/man/html/TixCmd/tixForm.htm] geometry manager based on attachment rules for all Tk widgets.

25.3.3. Tix Commands

class tkinter.tix.tixCommand

The tix commands [http://tix.sourceforge.net/dist/current/man/html/TixCmd/tix.htm] provide access to miscellaneous elements of Tix’s internal state and the Tix application context. Most of the information manipulated by these methods pertains to the application as a whole, or to a screen or display, rather than to a particular window.

To view the current settings, the common usage is:

from tkinter import tix
root = tix.Tk()
print(root.tix_configure())

tixCommand.tix_configure(cnf=None, **kw)

Query or modify the configuration options of the Tix application context. If no option is specified, returns a dictionary all of the available options. If option is specified with no value, then the method returns a list describing the one named option (this list will be identical to the corresponding sublist of the value returned if no option is specified). If one or more option-value pairs are specified, then the method modifies the given option(s) to have the given value(s); in this case the method returns an empty string. Option may be any of the configuration options.

tixCommand.tix_cget(option)

Returns the current value of the configuration option given by option. Option may be any of the configuration options.

tixCommand.tix_getbitmap(name)

Locates a bitmap file of the name name.xpm or name in one of the bitmap directories (see the tix_addbitmapdir() method). By using tix_getbitmap(), you can avoid hard coding the pathnames of the bitmap files in your application. When successful, it returns the complete pathname of the bitmap file, prefixed with the character @. The returned value can be used to configure the bitmap option of the Tk and Tix widgets.

tixCommand.tix_addbitmapdir(directory)

Tix maintains a list of directories under which the tix_getimage() and tix_getbitmap() methods will search for image files. The standard bitmap directory is $TIX_LIBRARY/bitmaps. The tix_addbitmapdir() method adds directory into this list. By using this method, the image files of an applications can also be located using the tix_getimage() or tix_getbitmap() method.

tixCommand.tix_filedialog([dlgclass])

Returns the file selection dialog that may be shared among different calls from this application. This method will create a file selection dialog widget when it is called the first time. This dialog will be returned by all subsequent calls to tix_filedialog(). An optional dlgclass parameter can be passed as a string to specified what type of file selection dialog widget is desired. Possible options are tix, FileSelectDialog or tixExFileSelectDialog.

tixCommand.tix_getimage(self, name)

Locates an image file of the name name.xpm, name.xbm or name.ppm in one of the bitmap directories (see the tix_addbitmapdir() method above). If more than one file with the same name (but different extensions) exist, then the image type is chosen according to the depth of the X display: xbm images are chosen on monochrome displays and color images are chosen on color displays. By using tix_getimage(), you can avoid hard coding the pathnames of the image files in your application. When successful, this method returns the name of the newly created image, which can be used to configure the image option of the Tk and Tix widgets.

tixCommand.tix_option_get(name)

Gets the options maintained by the Tix scheme mechanism.

tixCommand.tix_resetoptions(newScheme, newFontSet[, newScmPrio])

Resets the scheme and fontset of the Tix application to newScheme and newFontSet, respectively. This affects only those widgets created after this call. Therefore, it is best to call the resetoptions method before the creation of any widgets in a Tix application.

The optional parameter newScmPrio can be given to reset the priority level of the Tk options set by the Tix schemes.

Because of the way Tk handles the X option database, after Tix has been has imported and inited, it is not possible to reset the color schemes and font sets using the tix_config() method. Instead, the tix_resetoptions() method must be used.

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25.4. tkinter.scrolledtext — Gadget texte avec barre de défilement

Code source : Lib/tkinter/scrolledtext.py [https://github.com/python/cpython/tree/3.6/Lib/tkinter/scrolledtext.py]

Le module tkinter.scrolledtext fournit une classe, de même nom, implémentant un simple gadget texte avec une barre de défilement verticale, configuré « pour faire ce qu’on attend de lui ». Utiliser ScrolledText est beaucoup plus simple que configurer un gadget texte et une barre de défilement. Le constructeur est le même que celui de la classe tkinter.Text.

Le gadget texte et la barre de défilement sont regroupés dans une Frame, et les méthodes gestionnaires de géométrie Grid et Pack sont récupérées de l’objet Frame. L’objet ScrolledText a donc tous les attributs classiques pour la gestion de la géométrie.

Si un contrôle plus fin est nécessaire, les attributs suivants sont disponibles :

ScrolledText.frame

Le cadre (objet Frame) qui englobe le gadget texte et le gadget de la barre de défilement.

ScrolledText.vbar

Le gadget de la barre de défilement.

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25.5. IDLE

Code source : Lib/idlelib/ [https://github.com/python/cpython/tree/3.6/Lib/idlelib/]

IDLE est l’environnement de développement et d’apprentissage intégré de Python (Integrated Development and Learning Environment).

IDLE a les fonctionnalités suivantes :

codé à 100% en pur Python, en utilisant l’outil d’interfaçage graphique tkinter

cross-platform: works mostly the same on Windows, Unix, and macOS

Console Python (interpréteur interactif) avec coloration du code entré, des sorties et des messages d’erreur

éditeur de texte multi-fenêtres avec annulations multiples, coloration Python, indentation automatique, aide pour les appels de fonction, autocomplétion, parmi d’autres fonctionnalités

recherche dans n’importe quelle fenêtre, remplacement dans une fenêtre d’édition et recherche dans des fichiers multiples (grep)

débogueur avec points d’arrêt persistants, pas-à-pas et visualisation des espaces de nommage locaux et globaux

configuration, navigateur et d’autres fenêtres de dialogue

25.5.1. Menus

IDLE has two main window types, the Shell window and the Editor window. It is possible to have multiple editor windows simultaneously. On Windows and Linux, each has its own top menu. Each menu documented below indicates which window type it is associated with.

Output windows, such as used for Edit => Find in Files, are a subtype of editor window. They currently have the same top menu but a different default title and context menu.

On macOS, there is one application menu. It dynamically changes according to the window currently selected. It has an IDLE menu, and some entries described below are moved around to conform to Apple guidlines.

25.5.1.1. Menu File (Console et Éditeur)

New File

Crée une nouvelle fenêtre d’édition.

Open…

Ouvre un fichier existant avec une fenêtre de dialogue pour l’ouverture.

Recent Files

Ouvre une liste des fichiers récents. Cliquez sur l’un d’eux pour l’ouvrir.

Open Module…

Ouvre un module existant (cherche dans sys.path).

Class Browser

Montre les fonctions, classes et méthodes dans une arborescence pour le fichier en cours d’édition. Dans la console, ouvre d’abord un module.

Path Browser

Affiche les dossiers de sys.path, les modules, fonctions, classes et méthodes dans une arborescence.

Save

Enregistre la fenêtre active sous le fichier associé, s’il existe. Les fenêtres qui ont été modifiées depuis leur ouverture ou leur dernier enregistrement ont un * avant et après le titre de la fenêtre. S’il n’y a aucun fichier associé, exécute Save As à la place.

Save As…

Enregistre la fenêtre active avec une fenêtre de dialogue d’enregistrement. Le fichier enregistré devient le nouveau fichier associé pour cette fenêtre.

Save Copy As…

Enregistre la fenêtre active sous un fichier différent sans changer le fichier associé.

Print Window

Imprime la fenêtre active avec l’imprimante par défaut.

Close

Ferme la fenêtre active (demande à enregistrer si besoin).

Exit

Ferme toutes les fenêtres et quitte IDLE (demande à enregistrer les fenêtres non sauvegardées).

25.5.1.2. Menu Edit (console et éditeur)

Undo

Annule le dernier changement dans la fenêtre active. Un maximum de 1000 changements peut être annulé.

Redo

Ré-applique le dernier changement annulé dans la fenêtre active.

Cut

Copie la sélection dans le presse-papier global ; puis supprime la sélection.

Copy

Copie la sélection dans le presse-papier global.

Paste

Insère le contenu du presse-papier global dans la fenêtre active.

Les fonctions du presse-papier sont aussi disponibles dans les menus contextuels.

Select All

Sélectionne la totalité du contenu de la fenêtre active.

Find…

Ouvre une fenêtre de recherche avec de nombreuses options

Find Again

Répète la dernière recherche, s’il y en a une.

Find Selection

Cherche la chaîne sélectionnée, s’il y en a une.

Find in Files…

Ouvre une fenêtre de recherche de fichiers. Présente les résultats dans une nouvelle fenêtre d’affichage.

Replace…

Ouvre une fenêtre de recherche et remplacement.

Go to Line

Déplace le curseur sur la ligne de numéro demandé et rend cette ligne visible.

Show Completions

Open a scrollable list allowing selection of keywords and attributes. See Completions in the Tips sections below.

Expand Word

Complète un préfixe que vous avez saisi pour correspondre à un mot complet de la même fenêtre ; recommencez pour obtenir un autre complément.

Show call tip

After an unclosed parenthesis for a function, open a small window with function parameter hints.

Show surrounding parens

Surligne les parenthèses encadrantes.

25.5.1.3. Menu Format (fenêtre d’édition uniquement)

Indent Region

Décale les lignes sélectionnées vers la droite d’un niveau d’indentation (4 espaces par défaut).

Dedent Region

Décale les lignes sélectionnées vers la gauche d’un niveau d’indentation (4 espaces par défaut).

Comment Out Region

Insère ## devant les lignes sélectionnées.

Uncomment Region

Enlève les # ou ## au début des lignes sélectionnées.

Tabify Region

Transforme les blocs d’espaces au début des lignes en tabulations. (Note : Nous recommandons d’utiliser des blocs de 4 espaces pour indenter du code Python.)

Untabify Region

Transforme toutes les tabulations en le bon nombre d’espaces.

Toggle Tabs

Ouvre une boîte de dialogue permettant de passer des espaces aux tabulations (et inversement) pour l’indentation.

New Indent Width

Ouvre une boîte de dialogue pour changer la taille de l’indentation. La valeur par défaut acceptée par la communauté Python est de 4 espaces.

Format Paragraph

Reformate le paragraphe actif, délimité par des lignes vides, en un bloc de commentaires, ou la chaîne de caractères multi-lignes ou ligne sélectionnée en chaîne de caractères. Toutes les lignes du paragraphe seront formatées à moins de N colonnes, avec N valant 72 par défaut.

Strip trailing whitespace

Enlève les espaces et autres caractères blancs après le dernier caractère non blanc d’une ligne en appliquant str.rstrip à chaque ligne, y compris les lignes avec des chaînes de caractère multi-lignes.

25.5.1.4. Menu Run (fenêtre d’édition uniquement)

Console Python

Ouvre ou active la fenêtre de console Python.

Check Module

Vérifie la syntaxe du module actuellement ouvert dans la fenêtre d’édition. Si le module n’a pas été enregistré, IDLE va soit demander à enregistrer à l’utilisateur, soit enregistrer automatiquement, selon l’option sélectionnée dans l’onglet General de la fenêtre de configuration d”IDLE. S’il y a une erreur de syntaxe, l’emplacement approximatif est indiqué dans la fenêtre d’édition.

Run Module

Do Check Module (above). If no error, restart the shell to clean the environment, then execute the module. Output is displayed in the Shell window. Note that output requires use of print or write. When execution is complete, the Shell retains focus and displays a prompt. At this point, one may interactively explore the result of execution. This is similar to executing a file with python -i file at a command line.

25.5.1.5. Menu Shell (fenêtre de console uniquement)

View Last Restart

Fait défiler la fenêtre de console jusqu’au dernier redémarrage de la console.

Restart Shell

Redémarre la console pour nettoyer l’environnement.

Interrupt Execution

Arrête un programme en cours d’exécution.

25.5.1.6. Menu Debug (fenêtre de console uniquement)

Go to File/Line

Cherche, sur la ligne active et la ligne en-dessous, un nom de fichier et un numéro de ligne. Le cas échéant, ouvre le fichier s’il n’est pas encore ouvert et montre la ligne. Utilisez ceci pour visualiser les lignes de code source référencées dans un traceback d’exception et les lignes trouvées par Find in Files. Également disponible dans le menu contextuel des fenêtres de console et d’affichage.

Debugger ([dés]activer)

Quand cette fonctionnalité est activée, le code saisi dans la console ou exécuté depuis un Éditeur s’exécutera avec le débogueur. Dans l’Éditeur, des points d’arrêt peuvent être placés avec le menu contextuel. Cette fonctionnalité est encore incomplète et plus ou moins expérimentale.

Stack Viewer

Montre l’état de la pile au moment de la dernière erreur dans une arborescence, avec accès aux variables locales et globales.

Auto-open Stack Viewer

Active ou désactive l’ouverture automatique de l’afficheur de pile après une erreur non gérée.

25.5.1.7. Menu Options (console et éditeur)

Configure IDLE

Open a configuration dialog and change preferences for the following: fonts, indentation, keybindings, text color themes, startup windows and size, additional help sources, and extensions (see below). On macOS, open the configuration dialog by selecting Preferences in the application menu. To use a new built-in color theme (IDLE Dark) with older IDLEs, save it as a new custom theme.

Non-default user settings are saved in a .idlerc directory in the user’s home directory. Problems caused by bad user configuration files are solved by editing or deleting one or more of the files in .idlerc.

Code Context (toggle)(Editor Window only)

Open a pane at the top of the edit window which shows the block context of the code which has scrolled above the top of the window. Clicking a line in this pane exposes that line at the top of the editor.

25.5.1.8. Menu Windows (console et éditeur)

Zoom Height

Toggles the window between normal size and maximum height. The initial size defaults to 40 lines by 80 chars unless changed on the General tab of the Configure IDLE dialog.

The rest of this menu lists the names of all open windows; select one to bring it to the foreground (deiconifying it if necessary).

25.5.1.9. Menu Help (console et éditeur)

About IDLE

Affiche la version, les copyrights, la licence, les crédits, entre autres.

IDLE Help

Display this IDLE document, detailing the menu options, basic editing and navigation, and other tips.

Python Docs

Accède à la documentation Python locale, si installée, ou ouvre docs.python.org dans un navigateur pour afficher la documentation Python la plus récente.

Turtle Demo

Run the turtledemo module with example python code and turtle drawings.

Additional help sources may be added here with the Configure IDLE dialog under the General tab. See the « Help sources » subsection below for more on Help menu choices.

25.5.1.10. Menus Contextuels

Open a context menu by right-clicking in a window (Control-click on macOS). Context menus have the standard clipboard functions also on the Edit menu.

Cut

Copie la sélection dans le presse-papier global ; puis supprime la sélection.

Copy

Copie la sélection dans le presse-papier global.

Paste

Insère le contenu du presse-papier global dans la fenêtre active.

Les fenêtres d’édition ont aussi des fonctions de points d’arrêt. Les lignes avec un point d’arrêt activé sont marquées. Les points d’arrêt n’ont d’effet que lorsque l’exécution se déroule sous débogueur. Les points d’arrêt pour un fichier sont enregistrés dans le dossier .idlerc de l’utilisateur.

Set Breakpoint

Place un point d’arrêt sur la ligne active.

Clear Breakpoint

Enlève le point d’arrêt sur cette ligne.

Shell and Output windows also have the following.

Go to file/line

Même effet que dans le menu Debug.

The Shell window also has an output squeezing facility explained in the the Python Shell window subsection below.

Squeeze

If the cursor is over an output line, squeeze all the output between the code above and the prompt below down to a “Squeezed text” label.

25.5.2. Édition et navigation

25.5.2.1. Editor windows

IDLE may open editor windows when it starts, depending on settings and how you start IDLE. Thereafter, use the File menu. There can be only one open editor window for a given file.

The title bar contains the name of the file, the full path, and the version of Python and IDLE running the window. The status bar contains the line number (“Ln”) and column number (“Col”). Line numbers start with 1; column numbers with 0.

IDLE assumes that files with a known .py* extension contain Python code and that other files do not. Run Python code with the Run menu.

25.5.2.2. Key bindings

In this section, “C” refers to the Control key on Windows and Unix and the Command key on macOS.

Retour arrière supprime à gauche ; Suppr supprime à droite

C-Retour arrière supprime le mot à gauche ; C-Suppr supprime le mot à droite

Utilisez les touches flèche et Page Haut / Page Bas pour vous déplacer

C-Flèche Gauche et C-Flèche Droite déplacent de mot en mot

Début/Fin vont au début / à la fin de la ligne

C-Début / C-Fin vont au début / à la fin du fichier

Quelques raccourcis Emacs utiles sont hérités de Tcl/Tk :

C-a début de ligne

C-e fin de ligne

C-k supprime la ligne (mais ne la met pas dans le presse-papier)

C-l centre la fenêtre autour du point d’insertion

C-b recule d’un caractère sans le supprimer (habituellement vous pouvez également utiliser les touches flèches pour faire cela)

C-f avance d’un caractère sans le supprimer (habituellement vous pouvez également utiliser les touches flèches pour faire cela)

C-p remonte d’une ligne (habituellement vous pouvez également utiliser les touches flèches pour faire cela)

C-d supprime le caractère suivant

Les raccourcis clavier standards (comme C-c pour copier et C-v pour coller) peuvent fonctionner. Les raccourcis clavier sont sélectionnés dans la fenêtre de configuration d”IDLE.

25.5.2.3. Indentation automatique

Après une structure d’ouverture de bloc, la prochaine ligne est indentée de 4 espaces (dans la console Python d’une tabulation). Après certains mots-clefs (break, return etc) la ligne suivante est dédentée. Dans une indentation au début de la ligne, Retour arrière supprime jusqu’à 4 espaces s’il y en a. Tab insère des espaces (dans la console, une tabulation), en nombre dépendant de la configuration. Les tabulations sont actuellement restreintes à quatre espaces à cause de limitations de Tcl/Tk.

See also the indent/dedent region commands in the edit menu.

25.5.2.4. Complétions

Les complétions sont fournies pour les fonctions, classes et attributs de classes incluses par défaut et celles définies par l’utilisateur. Les complétions sont aussi fournies pour les noms de fichiers.

La fenêtre d’auto-complétion (ACW, AutoCompleteWindow) s’ouvre après un délai prédéfini (deux secondes par défaut) après qu’un « . »** ou (dans une chaîne) un os.sep est saisi. Si, après un de ces caractères (éventuellement suivi d’autres caractères), une tabulation est saisie, l”ACW s’ouvre immédiatement si une complétion compatible est trouvée.

S’il n’y a qu’une seule complétion possible pour le caractère saisi, un Tab fournit cette complétion sans ouvrir l”ACW.

« Show Completions » force l’ouverture d’une fenêtre de complétion, par défaut C-espace ouvre une fenêtre de complétion. Dans une chaîne vide, cette fenêtre contient les fichiers du dossier actif. Sur une ligne vide, elle contient les fonctions et classes intégrées par défaut et définies par l’utilisateur de l’espace de nommage actif, plus tous les modules importés. Si des caractères ont été saisis, l”ACW essaie d’être plus spécifique.

Si une chaîne de caractère est saisie, la sélection de l”ACW va à l’entrée la plus proche de ces caractères. Saisir un Tab saisit la plus longue correspondance non ambiguë dans la console ou l’éditeur. Deux Tab à la suite fournissent la sélection de l”ACW, de la même manière que la touche « Entrée » ou un double-clic. Les touches flèches, Page Haut/Bas, la sélection à la souris et la molette de la souris fonctionnent tous sur l”ACW.

Les attributs « cachés » peuvent être atteints en saisissant le début d’un nom caché après un « . », e.g. »**_ ». Ceci permet l’accès aux modules utilisant __all__ ou aux attributs privés des classes.

Les complétions et la fonctionnalité « *Expand Word »* peuvent vous faire économiser beaucoup de temps !

Les complétions sont actuellement limitées à ce qui est présent dans les espaces de nommage. Les noms dans une fenêtre d’édition qui ne viennent pas de __main__ et sys.modules ne sont pas trouvés. Exécutez votre module avec vos importations pour corriger cette situation. Notez qu”IDLE lui-même place quelques modules dans sys.modules, qui peuvent être donc accédés par défaut, comme le module re.

Si vous n’aimez pas que l”ACW s’affiche spontanément, vous pouvez simplement augmenter le délai ou désactiver l’extension.

25.5.2.5. Info-bulles

Une info-bulle est affichée quand vous saisissez ( après le nom d’une fonction accessible. Une expression de nom peut inclure des points et des tirets bas.L’info-bulle reste affichée jusqu’à ce que vous cliquiez dessus, que le curseur se déplace hors de la zone des arguments, ou que ) soit saisi. Quand le curseur est dans la partie « arguments » de la définition, le menu ou raccourci affiche une info-bulle.

Une info-bulle contient la signature de la fonction et la première ligne de la docstring. Pour les fonctions incluses par défaut sans signature accessible, l’info-bulle contient toutes les lignes jusqu’à la cinquième ligne ou la première ligne vide. Ces détails sont sujets à changement.

L’ensemble des fonctions accessibles dépend des modules qui ont été importés dans le processus utilisateur, y compris ceux importés par IDLE lui-même et quelles définitions ont été exécutées, le tout depuis le dernier redémarrage.

Par exemple, redémarrez la console et saisissez itertools.count(. Une info-bulle s’affiche parce que IDLE importe itertools dans le processus utilisateur pour son propre usage (ceci pourrait changer). Saisissez turtle.write( et rien ne s’affiche. IDLE n’importe pas turtle. Le menu ou le raccourci ne font rien non plus. Saisir import *turtle puis turtle.write( fonctionnera.

Dans l’éditeur, les commandes d’importation n’ont pas d’effet jusqu’à ce que le fichier soit exécuté. Vous pouvez exécuter un fichier après avoir écrit les commandes d’importation au début, ou immédiatement exécuter un fichier existant avant de l’éditer.

25.5.2.6. Fenêtre de console Python

With IDLE’s Shell, one enters, edits, and recalls complete statements. Most consoles and terminals only work with a single physical line at a time.

When one pastes code into Shell, it is not compiled and possibly executed until one hits Return. One may edit pasted code first. If one pastes more that one statement into Shell, the result will be a SyntaxError when multiple statements are compiled as if they were one.

The editing features described in previous subsections work when entering code interactively. IDLE’s Shell window also responds to the following keys.

C-c interrompt l’exécution de la commande

C-d envoie fin-de-fichier (EOF) ; cela ferme la fenêtre s’il est saisi à une invite >>>

Alt-/ (Compléter le mot) est également utile pour réduire la quantité de texte saisie

Historique des commandes

Alt-p retrieves previous command matching what you have typed. On macOS use C-p.

Alt-n retrieves next. On macOS use C-n.

Entrée sur une des commandes précédentes récupère cette commande

25.5.2.7. Coloration du texte

IDLE affiche par défaut le texte en noir sur blanc mais colore le texte qui possède une signification spéciale. Pour la console, ceci concerne les sorties de la console et de l’utilisateur ainsi que les erreurs de l’utilisateur. Pour le code Python, dans l’invite de commande de la console ou sur un éditeur, ce sont les mots-clefs, noms de fonctions et de classes incluses par défaut, les noms suivant class et def, les chaînes de caractères et les commentaires. Pour n’importe quelle fenêtre de texte, ce sont le curseur (si présent), le texte trouvé (s’il y en a) et le texte sélectionné.

La coloration du texte est faite en arrière-plan, donc du texte non coloré est parfois visible. Pour changer les couleurs, utilisez l’onglet Highlighting de la fenêtre de configuration d”IDLE. Le marquage des points d’arrêt du débogueur dans l’éditeur et du texte dans les dialogues n’est pas configurable.

25.5.3. Démarrage et exécution du code

Quand il est démarré avec l’option -s, IDLE exécutera le fichier référencé par la variable d’environnement IDLE*STARTUP ou PYTHONSTARTUP. IDLE cherche d’abord IDLESTARTUP ; si IDLESTARTUP est présent, le fichier référencé est exécuté. Si IDLESTARTUP n’est pas présent, alors IDLE cherche PYTHONSTARTUP. Les fichiers référencés par ces variables d’environnement sont de bons endroits pour stocker des fonctions qui sont utilisées fréquemment depuis la console d”IDLE ou pour exécuter des commandes d’importation des modules communs.

De plus, Tk charge lui aussi un fichier de démarrage s’il est présent. Notez que le fichier de Tk est chargé sans condition. Ce fichier additionnel est .Idle.py et est recherché dans le dossier personnel de l’utilisateur. Les commandes dans ce fichier sont exécutées dans l’espace de nommage de Tk, donc ce fichier n’est pas utile pour importer des fonctions à utiliser depuis la console Python d”IDLE.

25.5.3.1. Utilisation de la ligne de commande

idle.py [-c command] [-d] [-e] [-h] [-i] [-r file] [-s] [-t title] [-] [arg] ...

-c command  run command in the shell window
-d          enable debugger and open shell window
-e          open editor window
-h          print help message with legal combinations and exit
-i          open shell window
-r file     run file in shell window
-s          run $IDLESTARTUP or $PYTHONSTARTUP first, in shell window
-t title    set title of shell window
-           run stdin in shell (- must be last option before args)

S’il y a des arguments :

Si -, -c ou -r sont utilisés, tous les arguments sont placés dans sys.argv[1:...] et sys.argv[0] est assigné à “”`, '-c', ou '-r'. Aucune fenêtre d’édition n’est ouverte, même si c’est le comportement par défaut fixé dans la fenêtre d’options.

Sinon, les arguments sont des fichiers ouverts pour édition et sys.argv reflète les arguments passés à IDLE lui-même.

25.5.3.2. Échec au démarrage

IDLE utilise un connecteur (socket en anglais) pour communiquer entre le processus d’interface graphique d”IDLE et le processus d’exécution de code de l’utilisateur. Une connexion doit être établie quand la console démarre ou redémarre (le redémarrage est indiqué par une ligne de division avec « RESTART »). Si le processus utilisateur échoue à établir une connexion avec le processus graphique, il affiche une fenêtre d’erreur Tk avec un message « connexion impossible » qui redirige l’utilisateur ici. Ensuite, il s’arrête.

Une cause d’échec courant est un fichier écrit par l’utilisateur avec le même nom qu’un module de la bibliothèque standard, comme random.py et tkinter.py. Quand un fichier de ce genre est enregistré dans le même répertoire qu’un fichier à exécuter, IDLE ne peut pas importer le fichier standard. La solution actuelle consiste à renommer le fichier de l’utilisateur.

Même si c’est plus rare qu’avant, un antivirus ou un pare-feu peuvent interrompre la connexion. Si le programme ne peut pas être paramétré pour autoriser la connexion, alors il doit être éteint pour qu”IDLE puisse fonctionner. Cette connexion interne est sûre car aucune donnée n’est visible depuis un port extérieur. Un problème similaire est une mauvaise configuration du réseau qui bloque les connexions.

Des problèmes d’installation de Python stoppent parfois IDLE : il peut y avoir un conflit de versions ou bien l’installation peut nécessiter des privilèges administrateurs. Si on corrige le conflit , ou qu’on ne peut ou ne veut pas accorder de privilège, il peut être plus facile de désinstaller complètement Python et de recommencer.

Un processus pythonw.exe zombie peut être un problème. Sous Windows, utilisez le Gestionnaire des Tâches pour en détecter puis en arrêter un. Parfois, un redémarrage causé par un plantage ou une interruption clavier (Ctrl-C) peut ne pas réussir à se connecter. Fermer la fenêtre d’erreur ou redémarrer la console dans le menu Shell peut résoudre un problème temporaire.

Quand IDLE démarre pour la première fois, il essaie de lire la configuration de l’utilisateur dans les fichiers de ~/.idlerc (~ est le répertoire personnel de l’utilisateur). S’il y a un problème, un message d’erreur devrait être affiché. Mis à part les erreurs aléatoires du disque dur, ceci peut être évité en n’éditant jamais les fichiers directement, mais en utilisant la fenêtre de configuration, dans Options. Quand cela arrive, la solution peut être de supprimer un ou plusieurs des fichiers de configuration.

Si IDLE se ferme sans message et qu’il n’a pas été démarré depuis une console, essayez de le démarrer depuis une console (python -m idlelib) et regardez si un message apparaît.

25.5.3.3. Running user code

With rare exceptions, the result of executing Python code with IDLE is intended to be the same as executing the same code by the default method, directly with Python in a text-mode system console or terminal window. However, the different interface and operation occasionally affect visible results. For instance, sys.modules starts with more entries, and threading.activeCount() returns 2 instead of 1.

By default, IDLE runs user code in a separate OS process rather than in the user interface process that runs the shell and editor. In the execution process, it replaces sys.stdin, sys.stdout, and sys.stderr with objects that get input from and send output to the Shell window. The original values stored in sys.__stdin__, sys.__stdout__, and sys.__stderr__ are not touched, but may be None.

When Shell has the focus, it controls the keyboard and screen. This is normally transparent, but functions that directly access the keyboard and screen will not work. These include system-specific functions that determine whether a key has been pressed and if so, which.

IDLE’s standard stream replacements are not inherited by subprocesses created in the execution process, whether directly by user code or by modules such as multiprocessing. If such subprocess use input from sys.stdin or print or write to sys.stdout or sys.stderr, IDLE should be started in a command line window. The secondary subprocess will then be attached to that window for input and output.

If sys is reset by user code, such as with importlib.reload(sys), IDLE’s changes are lost and input from the keyboard and output to the screen will not work correctly.

25.5.3.4. User output in Shell

When a program outputs text, the result is determined by the corresponding output device. When IDLE executes user code, sys.stdout and sys.stderr are connected to the display area of IDLE’s Shell. Some of its features are inherited from the underlying Tk Text widget. Others are programmed additions. Where it matters, Shell is designed for development rather than production runs.

For instance, Shell never throws away output. A program that sends unlimited output to Shell will eventually fill memory, resulting in a memory error. In contrast, some system text windows only keep the last n lines of output. A Windows console, for instance, keeps a user-settable 1 to 9999 lines, with 300 the default.

Text widgets display a subset of Unicode, the Basic Multilingual Plane (BMP). Which characters get a proper glyph instead of a replacement box depends on the operating system and installed fonts. Newline characters cause following text to appear on a new line, but other control characters are either replaced with a box or deleted. However, repr(), which is used for interactive echo of expression values, replaces control characters, some BMP codepoints, and all non-BMP characters with escape codes before they are output.

Normal and error output are generally kept separate (on separate lines) from code input and each other. They each get different highlight colors.

For SyntaxError tracebacks, the normal “^” marking where the error was detected is replaced by coloring the text with an error highlight. When code run from a file causes other exceptions, one may right click on a traceback line to jump to the corresponding line in an IDLE editor. The file will be opened if necessary.

Shell has a special facility for squeezing output lines down to a “Squeezed text” label. This is done automatically for output over N lines (N = 50 by default). N can be changed in the PyShell section of the General page of the Settings dialog. Output with fewer lines can be squeezed by right clicking on the output. This can be useful lines long enough to slow down scrolling.

Squeezed output is expanded in place by double-clicking the label. It can also be sent to the clipboard or a separate view window by right-clicking the label.

25.5.3.5. Développer des applications tkinter

IDLE is intentionally different from standard Python in order to facilitate development of tkinter programs. Enter import tkinter as tk; root = tk.Tk() in standard Python and nothing appears. Enter the same in IDLE and a tk window appears. In standard Python, one must also enter root.update() to see the window. IDLE does the equivalent in the background, about 20 times a second, which is about every 50 milleseconds. Next enter b = tk.Button(root, text='button'); b.pack(). Again, nothing visibly changes in standard Python until one enters root.update().

La plupart des programmes tkinter exécutent root.mainloop(), qui d’habitude ne renvoie pas jusqu’à ce que l’application tk soit détruite. Si le programme est exécuté avec python -i``ou depuis un éditeur *IDLE*, une invite de commande ``>>> n’apparaît pas tant que mainloop() ne termine pas, c’est-à-dire quand il ne reste plus rien avec lequel interagir.

Avec un programme tkinter exécuté depuis un éditeur IDLE, vous pouvez immédiatement commenter l’appel à mainloop. On a alors accès à une invite de commande et on peut interagir en direct avec l’application. Il faut juste se rappeler de réactiver l’appel à mainloop lors de l’exécution en Python standard.

25.5.3.6. Exécution sans sous-processus

Par défaut IDLE exécute le code de l’utilisateur dans un sous-processus séparé via un connecteur sur l’interface de la boucle locale. Cette connexion n’est pas visible de l’extérieur et rien n’est envoyé ou reçu d’Internet. Si un pare-feu s’en plaint quand même, vous pouvez l’ignorer.

Si la tentative de connexion par le socket échoue, IDLE vous le notifie. Ce genre d’échec est parfois temporaire, mais s’il persiste, le problème peut soit venir d’un pare-feu qui bloque la connexion ou d’une mauvaise configuration dans un système particulier. Jusqu’à ce que le problème soit résolu, vous pouvez exécuter IDLE avec l’option -n de la ligne de commande.

Si IDLE est démarré avec l’option -n de la ligne de commande, il s’exécute dans un seul processus et ne crée pas de sous-processus pour exécuter le serveur RPC d’exécution de Python. Ceci peut être utile si Python ne peut pas créer de sous-processus ou de connecteur RPC sur votre plateforme. Cependant, dans ce mode, le code de l’utilisateur n’est pas isolé de IDLE lui-même. De plus, l’environnement n’est pas réinitialisé quand Run/Run Module (F5) est sélectionné. Si votre code a été modifié, vous devez reload*() les modules affectés et ré-importer tous les éléments spécifiques (e.g. *from foo import baz) pour que les changements prennent effet. Pour toutes ces raisons, il est préférable d’exécuter IDLE avec le sous-processus par défaut si c’est possible.

Obsolète depuis la version 3.4.

25.5.4. Aide et préférences

25.5.4.1. Help sources

Help menu entry « IDLE Help » displays a formatted html version of the IDLE chapter of the Library Reference. The result, in a read-only tkinter text window, is close to what one sees in a web browser. Navigate through the text with a mousewheel, the scrollbar, or up and down arrow keys held down. Or click the TOC (Table of Contents) button and select a section header in the opened box.

Help menu entry « Python Docs » opens the extensive sources of help, including tutorials, available at docs.python.org/x.y, where “x.y” is the currently running Python version. If your system has an off-line copy of the docs (this may be an installation option), that will be opened instead.

Selected URLs can be added or removed from the help menu at any time using the General tab of the Configure IDLE dialog .

25.5.4.2. Modifier les préférences

The font preferences, highlighting, keys, and general preferences can be changed via Configure IDLE on the Option menu. Keys can be user defined; IDLE ships with four built-in key sets. In addition, a user can create a custom key set in the Configure IDLE dialog under the keys tab.

25.5.4.3. IDLE on macOS

Under System Preferences: Dock, one can set « Prefer tabs when opening documents » to « Always ». This setting is not compatible with the tk/tkinter GUI framework used by IDLE, and it breaks a few IDLE features.

25.5.4.4. Extensions

IDLE inclut un outil d’extensions. Les préférences pour les extensions peuvent être changées avec l’onglet Extensions de la fenêtre de préférences. Lisez le début de config-extensions.def dans le dossier idlelib pour plus d’informations. La seule extension actuellement utilisée par défaut est zzdummy, un exemple également utilisé pour les tests.

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25.6. Autres paquets d’interface graphique utilisateur

Des boîtes à outils multiplateformes (Windows, Mac OS X ou Unix et assimilé) majeures sont disponibles pour Python :

Voir aussi

PyGObject [https://wiki.gnome.org/Projects/PyGObject]

PyGObject provides introspection bindings for C libraries using GObject [https://developer.gnome.org/gobject/stable/]. One of these libraries is the GTK+ 3 [http://www.gtk.org/] widget set. GTK+ comes with many more widgets than Tkinter provides. An online Python GTK+ 3 Tutorial [https://python-gtk-3-tutorial.readthedocs.org/en/latest/] is available.

PyGTK [http://www.pygtk.org/]

PyGTK fournit une surcouche pour une version plus ancienne de la bibliothèque, GTK+ 2. Cette dernière fournit une interface orientée objet qui est légèrement plus haut niveau que son équivalent C. Il y a également une surcouche pour GNOME [https://www.gnome.org/]. Un tutoriel [http://www.pygtk.org/pygtk2tutorial/index.html] en ligne est disponible.

PyQt [https://riverbankcomputing.com/software/pyqt/intro]

PyQt est une surcouche de la boite à outils Qt basée sur sip. Qt est un framework complet de développement d’interface graphique en C++ , disponible pour Unix, Windows et Mac OS X. sip est un outil pour générer une surcouche de classes Python au dessus de bibliothèques C++, et est spécifiquement conçu pour Python.

PySide [https://wiki.qt.io/PySide]

PySide est une nouvelle surcouche de la boîte à outils Qt, fournie par Nokia. Comparée à PyQT, son système de licence est plus accommodant pour les application non open source.

wxPython [http://www.wxpython.org]

wxPython est une boîte à outils d’interface graphique multiplateforme pour Python qui est construite autour de la populaire boîte à outils wxWidgets [https://www.wxwidgets.org/] (anciennement wxWindows). En plus d’un ensemble de composants graphiques complet, wxPython fournit des classes pour de la documentation en ligne, de l’aide contextuelle, de l’impression, de la consultation de HTML, du rendu graphique bas niveau, du glisser-déposer, l’accès au système de presse-papier, un DSL de description de ressources en XML et même plus, y compris une collection de modules contribués par la communauté qui grandit sans cesse. Elle fournit un aspect et une expérience native pour les applications sur Windows, Mac OS X et systèmes Unix en utilisant les composants natifs de chaque plateforme quand cela est possible (GTK+ sur les systèmes Unix et assimilés).

PyGTK, PyQt, et wxPython fournissent tous un aspect et une expérience moderne ainsi que plus de composants graphiques que Tkinter. De plus, il y a de nombreuses autres boîtes à outils pour Python, que ce soit multiplateformes ou spécifiques à une plateforme. Consultez la page sur la programmation d’interface graphique [https://wiki.python.org/moin/GuiProgramming] du Wiki Python pour une liste bien plus complète, ainsi que des liens vers des documents où les différentes boîtes à outils graphiques sont comparées.

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26. Outils de développement

Les modules décrits dans ce chapitre vous aident à écrire des logiciels. Par exemple, le module pydoc prend un module et génère de la documentation basée sur son contenu. Les modules doctest et unittest contiennent des cades applicatifs pour écrire des tests unitaires qui permettent de valider automatiquement le code en vérifiant que chaque résultat attendu est produit. Le programme 2to3 peut traduire du code Python 2.x en Python 3.x.

La liste des modules documentés dans ce chapitre est :

26.1. typing — Support for type hints

26.1.1. Type aliases

26.1.2. NewType

26.1.3. Callable

26.1.4. Generics

26.1.5. User-defined generic types

26.1.6. The Any type

26.1.7. Classes, functions, and decorators

26.2. pydoc — Générateur de documentation et système d’aide en ligne

26.3. doctest — Test interactive Python examples

26.3.1. Simple Usage: Checking Examples in Docstrings

26.3.2. Simple Usage: Checking Examples in a Text File

26.3.3. How It Works

26.3.3.1. Which Docstrings Are Examined?

26.3.3.2. How are Docstring Examples Recognized?

26.3.3.3. What’s the Execution Context?

26.3.3.4. What About Exceptions?

26.3.3.5. Option Flags

26.3.3.6. Directives

26.3.3.7. Avertissements

26.3.4. Basic API

26.3.5. Unittest API

26.3.6. Advanced API

26.3.6.1. DocTest Objects

26.3.6.2. Example Objects

26.3.6.3. DocTestFinder objects

26.3.6.4. DocTestParser objects

26.3.6.5. DocTestRunner objects

26.3.6.6. OutputChecker objects

26.3.7. Debugging

26.3.8. Soapbox

26.4. unittest — Framework de tests unitaires

26.4.1. Exemple basique

26.4.2. Interface en ligne de commande

26.4.2.1. Options de la ligne de commande

26.4.3. Découverte des tests

26.4.4. Organiser le code de test

26.4.5. Réutilisation d’ancien code de test

26.4.6. Ignorer des tests et des erreurs prévisibles

26.4.7. Distinguer les itérations de test à l’aide de sous-tests

26.4.8. Classes et fonctions

26.4.8.1. Scénarios de tests

26.4.8.1.1. Alias obsolètes

26.4.8.2. Regroupement des tests

26.4.8.3. Chargement et exécution des tests

26.4.8.3.1. Protocole de chargement des tests (load_tests Protocol)

26.4.9. Classes et modules d’aménagements des tests

26.4.9.1. Classes de mise en place (setUpClass) et de démantèlement des tests (tearDownClass)

26.4.9.2. Module de mise en place (setUpModule) et de démantèlement des tests (tearDownModule)

26.4.10. Traitement des signaux

26.5. unittest.mock — Bibliothèque d’objets simulacres

26.5.1. Guide rapide

26.5.2. La classe Mock

26.5.2.1. Calling

26.5.2.2. Deleting Attributes

26.5.2.3. Mock names and the name attribute

26.5.2.4. Attaching Mocks as Attributes

26.5.3. The patchers

26.5.3.1. patch

26.5.3.2. patch.object

26.5.3.3. patch.dict

26.5.3.4. patch.multiple

26.5.3.5. patch methods: start and stop

26.5.3.6. patch builtins

26.5.3.7. TEST_PREFIX

26.5.3.8. Nesting Patch Decorators

26.5.3.9. Where to patch

26.5.3.10. Patching Descriptors and Proxy Objects

26.5.4. MagicMock and magic method support

26.5.4.1. Mocking Magic Methods

26.5.4.2. Magic Mock

26.5.5. Helpers

26.5.5.1. sentinel

26.5.5.2. DEFAULT

26.5.5.3. call

26.5.5.4. create_autospec

26.5.5.5. ANY

26.5.5.6. FILTER_DIR

26.5.5.7. mock_open

26.5.5.8. Autospeccing

26.6. unittest.mock — getting started

26.6.1. Utilisation de Mock ou l’art de singer

26.6.1.1. Simulation des méthodes

26.6.1.2. S’assurer de la bonne utilisation d’un objet

26.6.1.3. Simulation des classes

26.6.1.4. Naming your mocks

26.6.1.5. Tracking all Calls

26.6.1.6. Setting Return Values and Attributes

26.6.1.7. Raising exceptions with mocks

26.6.1.8. Side effect functions and iterables

26.6.1.9. Creating a Mock from an Existing Object

26.6.2. Patch Decorators

26.6.3. Further Examples

26.6.3.1. Mocking chained calls

26.6.3.2. Partial mocking

26.6.3.3. Mocking a Generator Method

26.6.3.4. Applying the same patch to every test method

26.6.3.5. Mocking Unbound Methods

26.6.3.6. Checking multiple calls with mock

26.6.3.7. Coping with mutable arguments

26.6.3.8. Nesting Patches

26.6.3.9. Mocking a dictionary with MagicMock

26.6.3.10. Mock subclasses and their attributes

26.6.3.11. Mocking imports with patch.dict

26.6.3.12. Tracking order of calls and less verbose call assertions

26.6.3.13. More complex argument matching

26.7. 2to3 — Traduction automatique de code en Python 2 vers Python 3

26.7.1. Utilisation de 2to3

26.7.2. Correcteurs

26.7.3. lib2to3 — la bibliothèque de 2to3

26.8. test — Regression tests package for Python

26.8.1. Writing Unit Tests for the test package

26.8.2. Running tests using the command-line interface

26.9. test.support — Utilities for the Python test suite

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26.1. typing — Support for type hints

Nouveau dans la version 3.5.

Code source : Lib/typing.py [https://github.com/python/cpython/tree/3.6/Lib/typing.py]

Note

The typing module has been included in the standard library on a provisional basis. New features might be added and API may change even between minor releases if deemed necessary by the core developers.

This module supports type hints as specified by PEP 484 [https://www.python.org/dev/peps/pep-0484] and PEP 526 [https://www.python.org/dev/peps/pep-0526]. The most fundamental support consists of the types Any, Union, Tuple, Callable, TypeVar, and Generic. For full specification please see PEP 484 [https://www.python.org/dev/peps/pep-0484]. For a simplified introduction to type hints see PEP 483 [https://www.python.org/dev/peps/pep-0483].

The function below takes and returns a string and is annotated as follows:

def greeting(name: str) -> str:
    return 'Hello ' + name

In the function greeting, the argument name is expected to be of type str and the return type str. Subtypes are accepted as arguments.

26.1.1. Type aliases

A type alias is defined by assigning the type to the alias. In this example, Vector and List[float] will be treated as interchangeable synonyms:

from typing import List
Vector = List[float]

def scale(scalar: float, vector: Vector) -> Vector:
    return [scalar * num for num in vector]

# typechecks; a list of floats qualifies as a Vector.
new_vector = scale(2.0, [1.0, -4.2, 5.4])

Type aliases are useful for simplifying complex type signatures. For example:

from typing import Dict, Tuple, List

ConnectionOptions = Dict[str, str]
Address = Tuple[str, int]
Server = Tuple[Address, ConnectionOptions]

def broadcast_message(message: str, servers: List[Server]) -> None:
    ...

# The static type checker will treat the previous type signature as
# being exactly equivalent to this one.
def broadcast_message(
        message: str,
        servers: List[Tuple[Tuple[str, int], Dict[str, str]]]) -> None:
    ...

Note that None as a type hint is a special case and is replaced by type(None).

26.1.2. NewType

Use the NewType() helper function to create distinct types:

from typing import NewType

UserId = NewType('UserId', int)
some_id = UserId(524313)

The static type checker will treat the new type as if it were a subclass of the original type. This is useful in helping catch logical errors:

def get_user_name(user_id: UserId) -> str:
    ...

# typechecks
user_a = get_user_name(UserId(42351))

# does not typecheck; an int is not a UserId
user_b = get_user_name(-1)

You may still perform all int operations on a variable of type UserId, but the result will always be of type int. This lets you pass in a UserId wherever an int might be expected, but will prevent you from accidentally creating a UserId in an invalid way:

# 'output' is of type 'int', not 'UserId'
output = UserId(23413) + UserId(54341)

Note that these checks are enforced only by the static type checker. At runtime the statement Derived = NewType('Derived', Base) will make Derived a function that immediately returns whatever parameter you pass it. That means the expression Derived(some_value) does not create a new class or introduce any overhead beyond that of a regular function call.

More precisely, the expression some_value is Derived(some_value) is always true at runtime.

This also means that it is not possible to create a subtype of Derived since it is an identity function at runtime, not an actual type:

from typing import NewType

UserId = NewType('UserId', int)

# Fails at runtime and does not typecheck
class AdminUserId(UserId): pass

However, it is possible to create a NewType() based on a “derived” NewType:

from typing import NewType

UserId = NewType('UserId', int)

ProUserId = NewType('ProUserId', UserId)

and typechecking for ProUserId will work as expected.

See PEP 484 [https://www.python.org/dev/peps/pep-0484] for more details.

Note

Recall that the use of a type alias declares two types to be equivalent to one another. Doing Alias = Original will make the static type checker treat Alias as being exactly equivalent to Original in all cases. This is useful when you want to simplify complex type signatures.

In contrast, NewType declares one type to be a subtype of another. Doing Derived = NewType('Derived', Original) will make the static type checker treat Derived as a subclass of Original, which means a value of type Original cannot be used in places where a value of type Derived is expected. This is useful when you want to prevent logic errors with minimal runtime cost.

Nouveau dans la version 3.5.2.

26.1.3. Callable

Frameworks expecting callback functions of specific signatures might be type hinted using Callable[[Arg1Type, Arg2Type], ReturnType].

Par exemple :

from typing import Callable

def feeder(get_next_item: Callable[[], str]) -> None:
    # Body

def async_query(on_success: Callable[[int], None],
                on_error: Callable[[int, Exception], None]) -> None:
    # Body

It is possible to declare the return type of a callable without specifying the call signature by substituting a literal ellipsis for the list of arguments in the type hint: Callable[..., ReturnType].

26.1.4. Generics

Since type information about objects kept in containers cannot be statically inferred in a generic way, abstract base classes have been extended to support subscription to denote expected types for container elements.

from typing import Mapping, Sequence

def notify_by_email(employees: Sequence[Employee],
                    overrides: Mapping[str, str]) -> None: ...

Generics can be parameterized by using a new factory available in typing called TypeVar.

from typing import Sequence, TypeVar

T = TypeVar('T')      # Declare type variable

def first(l: Sequence[T]) -> T:   # Generic function
    return l[0]

26.1.5. User-defined generic types

A user-defined class can be defined as a generic class.

from typing import TypeVar, Generic
from logging import Logger

T = TypeVar('T')

class LoggedVar(Generic[T]):
    def __init__(self, value: T, name: str, logger: Logger) -> None:
        self.name = name
        self.logger = logger
        self.value = value

    def set(self, new: T) -> None:
        self.log('Set ' + repr(self.value))
        self.value = new

    def get(self) -> T:
        self.log('Get ' + repr(self.value))
        return self.value

    def log(self, message: str) -> None:
        self.logger.info('%s: %s', self.name, message)

Generic[T] as a base class defines that the class LoggedVar takes a single type parameter T . This also makes T valid as a type within the class body.

The Generic base class uses a metaclass that defines __getitem__() so that LoggedVar[t] is valid as a type:

from typing import Iterable

def zero_all_vars(vars: Iterable[LoggedVar[int]]) -> None:
    for var in vars:
        var.set(0)

A generic type can have any number of type variables, and type variables may be constrained:

from typing import TypeVar, Generic
...

T = TypeVar('T')
S = TypeVar('S', int, str)

class StrangePair(Generic[T, S]):
    ...

Each type variable argument to Generic must be distinct. This is thus invalid:

from typing import TypeVar, Generic
...

T = TypeVar('T')

class Pair(Generic[T, T]):   # INVALID
    ...

You can use multiple inheritance with Generic:

from typing import TypeVar, Generic, Sized

T = TypeVar('T')

class LinkedList(Sized, Generic[T]):
    ...

When inheriting from generic classes, some type variables could be fixed:

from typing import TypeVar, Mapping

T = TypeVar('T')

class MyDict(Mapping[str, T]):
    ...

In this case MyDict has a single parameter, T.

Using a generic class without specifying type parameters assumes Any for each position. In the following example, MyIterable is not generic but implicitly inherits from Iterable[Any]:

from typing import Iterable

class MyIterable(Iterable): # Same as Iterable[Any]

User defined generic type aliases are also supported. Examples:

from typing import TypeVar, Iterable, Tuple, Union
S = TypeVar('S')
Response = Union[Iterable[S], int]

# Return type here is same as Union[Iterable[str], int]
def response(query: str) -> Response[str]:
    ...

T = TypeVar('T', int, float, complex)
Vec = Iterable[Tuple[T, T]]

def inproduct(v: Vec[T]) -> T: # Same as Iterable[Tuple[T, T]]
    return sum(x*y for x, y in v)

The metaclass used by Generic is a subclass of abc.ABCMeta. A generic class can be an ABC by including abstract methods or properties, and generic classes can also have ABCs as base classes without a metaclass conflict. Generic metaclasses are not supported. The outcome of parameterizing generics is cached, and most types in the typing module are hashable and comparable for equality.

26.1.6. The Any type

A special kind of type is Any. A static type checker will treat every type as being compatible with Any and Any as being compatible with every type.

This means that it is possible to perform any operation or method call on a value of type on Any and assign it to any variable:

from typing import Any

a = None    # type: Any
a = []      # OK
a = 2       # OK

s = ''      # type: str
s = a       # OK

def foo(item: Any) -> int:
    # Typechecks; 'item' could be any type,
    # and that type might have a 'bar' method
    item.bar()
    ...

Notice that no typechecking is performed when assigning a value of type Any to a more precise type. For example, the static type checker did not report an error when assigning a to s even though s was declared to be of type str and receives an int value at runtime!

Furthermore, all functions without a return type or parameter types will implicitly default to using Any:

def legacy_parser(text):
    ...
    return data

# A static type checker will treat the above
# as having the same signature as:
def legacy_parser(text: Any) -> Any:
    ...
    return data

This behavior allows Any to be used as an escape hatch when you need to mix dynamically and statically typed code.

Contrast the behavior of Any with the behavior of object. Similar to Any, every type is a subtype of object. However, unlike Any, the reverse is not true: object is not a subtype of every other type.

That means when the type of a value is object, a type checker will reject almost all operations on it, and assigning it to a variable (or using it as a return value) of a more specialized type is a type error. For example:

def hash_a(item: object) -> int:
    # Fails; an object does not have a 'magic' method.
    item.magic()
    ...

def hash_b(item: Any) -> int:
    # Typechecks
    item.magic()
    ...

# Typechecks, since ints and strs are subclasses of object
hash_a(42)
hash_a("foo")

# Typechecks, since Any is compatible with all types
hash_b(42)
hash_b("foo")

Use object to indicate that a value could be any type in a typesafe manner. Use Any to indicate that a value is dynamically typed.

26.1.7. Classes, functions, and decorators

The module defines the following classes, functions and decorators:

class typing.TypeVar

Type variable.

Utilisation :

T = TypeVar('T')  # Can be anything
A = TypeVar('A', str, bytes)  # Must be str or bytes

Type variables exist primarily for the benefit of static type checkers. They serve as the parameters for generic types as well as for generic function definitions. See class Generic for more information on generic types. Generic functions work as follows:

def repeat(x: T, n: int) -> Sequence[T]:
    """Return a list containing n references to x."""
    return [x]*n

def longest(x: A, y: A) -> A:
    """Return the longest of two strings."""
    return x if len(x) >= len(y) else y

The latter example’s signature is essentially the overloading of (str, str) -> str and (bytes, bytes) -> bytes. Also note that if the arguments are instances of some subclass of str, the return type is still plain str.

At runtime, isinstance(x, T) will raise TypeError. In general, isinstance() and issubclass() should not be used with types.

Type variables may be marked covariant or contravariant by passing covariant=True or contravariant=True. See PEP 484 [https://www.python.org/dev/peps/pep-0484] for more details. By default type variables are invariant. Alternatively, a type variable may specify an upper bound using bound=<type>. This means that an actual type substituted (explicitly or implicitly) for the type variable must be a subclass of the boundary type, see PEP 484 [https://www.python.org/dev/peps/pep-0484].

class typing.Generic

Abstract base class for generic types.

A generic type is typically declared by inheriting from an instantiation of this class with one or more type variables. For example, a generic mapping type might be defined as:

class Mapping(Generic[KT, VT]):
    def __getitem__(self, key: KT) -> VT:
        ...
        # Etc.

This class can then be used as follows:

X = TypeVar('X')
Y = TypeVar('Y')

def lookup_name(mapping: Mapping[X, Y], key: X, default: Y) -> Y:
    try:
        return mapping[key]
    except KeyError:
        return default

class typing.Type(Generic[CT_co])

A variable annotated with C may accept a value of type C. In contrast, a variable annotated with Type[C] may accept values that are classes themselves – specifically, it will accept the class object of C. For example:

a = 3         # Has type 'int'
b = int       # Has type 'Type[int]'
c = type(a)   # Also has type 'Type[int]'

Note that Type[C] is covariant:

class User: ...
class BasicUser(User): ...
class ProUser(User): ...
class TeamUser(User): ...

# Accepts User, BasicUser, ProUser, TeamUser, ...
def make_new_user(user_class: Type[User]) -> User:
    # ...
    return user_class()

The fact that Type[C] is covariant implies that all subclasses of C should implement the same constructor signature and class method signatures as C. The type checker should flag violations of this, but should also allow constructor calls in subclasses that match the constructor calls in the indicated base class. How the type checker is required to handle this particular case may change in future revisions of PEP 484 [https://www.python.org/dev/peps/pep-0484].

The only legal parameters for Type are classes, Any, type variables, and unions of any of these types. For example:

def new_non_team_user(user_class: Type[Union[BaseUser, ProUser]]): ...

Type[Any] is equivalent to Type which in turn is equivalent to type, which is the root of Python’s metaclass hierarchy.

Nouveau dans la version 3.5.2.

class typing.Iterable(Generic[T_co])

A generic version of collections.abc.Iterable.

class typing.Iterator(Iterable[T_co])

A generic version of collections.abc.Iterator.

class typing.Reversible(Iterable[T_co])

A generic version of collections.abc.Reversible.

class typing.SupportsInt

An ABC with one abstract method __int__.

class typing.SupportsFloat

An ABC with one abstract method __float__.

class typing.SupportsComplex

An ABC with one abstract method __complex__.

class typing.SupportsBytes

An ABC with one abstract method __bytes__.

class typing.SupportsAbs

An ABC with one abstract method __abs__ that is covariant in its return type.

class typing.SupportsRound

An ABC with one abstract method __round__ that is covariant in its return type.

class typing.Container(Generic[T_co])

A generic version of collections.abc.Container.

class typing.Hashable

An alias to collections.abc.Hashable

class typing.Sized

An alias to collections.abc.Sized

class typing.Collection(Sized, Iterable[T_co], Container[T_co])

A generic version of collections.abc.Collection

Nouveau dans la version 3.6.

class typing.AbstractSet(Sized, Collection[T_co])

A generic version of collections.abc.Set.

class typing.MutableSet(AbstractSet[T])

A generic version of collections.abc.MutableSet.

class typing.Mapping(Sized, Collection[KT], Generic[VT_co])

A generic version of collections.abc.Mapping.

class typing.MutableMapping(Mapping[KT, VT])

A generic version of collections.abc.MutableMapping.

class typing.Sequence(Reversible[T_co], Collection[T_co])

A generic version of collections.abc.Sequence.

class typing.MutableSequence(Sequence[T])

A generic version of collections.abc.MutableSequence.

class typing.ByteString(Sequence[int])

A generic version of collections.abc.ByteString.

This type represents the types bytes, bytearray, and memoryview.

As a shorthand for this type, bytes can be used to annotate arguments of any of the types mentioned above.

class typing.Deque(deque, MutableSequence[T])

A generic version of collections.deque.

Nouveau dans la version 3.6.1.

class typing.List(list, MutableSequence[T])

Generic version of list. Useful for annotating return types. To annotate arguments it is preferred to use abstract collection types such as Mapping, Sequence, or AbstractSet.

This type may be used as follows:

T = TypeVar('T', int, float)

def vec2(x: T, y: T) -> List[T]:
    return [x, y]

def keep_positives(vector: Sequence[T]) -> List[T]:
    return [item for item in vector if item > 0]

class typing.Set(set, MutableSet[T])

A generic version of builtins.set.

class typing.FrozenSet(frozenset, AbstractSet[T_co])

A generic version of builtins.frozenset.

class typing.MappingView(Sized, Iterable[T_co])

A generic version of collections.abc.MappingView.

class typing.KeysView(MappingView[KT_co], AbstractSet[KT_co])

A generic version of collections.abc.KeysView.

class typing.ItemsView(MappingView, Generic[KT_co, VT_co])

A generic version of collections.abc.ItemsView.

class typing.ValuesView(MappingView[VT_co])

A generic version of collections.abc.ValuesView.

class typing.Awaitable(Generic[T_co])

A generic version of collections.abc.Awaitable.

class typing.Coroutine(Awaitable[V_co], Generic[T_co T_contra, V_co])

A generic version of collections.abc.Coroutine. The variance and order of type variables correspond to those of Generator, for example:

from typing import List, Coroutine
c = None # type: Coroutine[List[str], str, int]
...
x = c.send('hi') # type: List[str]
async def bar() -> None:
    x = await c # type: int

class typing.AsyncIterable(Generic[T_co])

A generic version of collections.abc.AsyncIterable.

class typing.AsyncIterator(AsyncIterable[T_co])

A generic version of collections.abc.AsyncIterator.

class typing.ContextManager(Generic[T_co])

A generic version of contextlib.AbstractContextManager.

Nouveau dans la version 3.6.

class typing.AsyncContextManager(Generic[T_co])

An ABC with async abstract __aenter__() and __aexit__() methods.

Nouveau dans la version 3.6.

class typing.Dict(dict, MutableMapping[KT, VT])

A generic version of dict. The usage of this type is as follows:

def get_position_in_index(word_list: Dict[str, int], word: str) -> int:
    return word_list[word]

class typing.DefaultDict(collections.defaultdict, MutableMapping[KT, VT])

A generic version of collections.defaultdict.

Nouveau dans la version 3.5.2.

class typing.Counter(collections.Counter, Dict[T, int])

A generic version of collections.Counter.

Nouveau dans la version 3.6.1.

class typing.ChainMap(collections.ChainMap, MutableMapping[KT, VT])

A generic version of collections.ChainMap.

Nouveau dans la version 3.6.1.

class typing.Generator(Iterator[T_co], Generic[T_co, T_contra, V_co])

A generator can be annotated by the generic type Generator[YieldType, SendType, ReturnType]. For example:

def echo_round() -> Generator[int, float, str]:
    sent = yield 0
    while sent >= 0:
        sent = yield round(sent)
    return 'Done'

Note that unlike many other generics in the typing module, the SendType of Generator behaves contravariantly, not covariantly or invariantly.

If your generator will only yield values, set the SendType and ReturnType to None:

def infinite_stream(start: int) -> Generator[int, None, None]:
    while True:
        yield start
        start += 1

Alternatively, annotate your generator as having a return type of either Iterable[YieldType] or Iterator[YieldType]:

def infinite_stream(start: int) -> Iterator[int]:
    while True:
        yield start
        start += 1

class typing.AsyncGenerator(AsyncIterator[T_co], Generic[T_co, T_contra])

An async generator can be annotated by the generic type AsyncGenerator[YieldType, SendType]. For example:

async def echo_round() -> AsyncGenerator[int, float]:
    sent = yield 0
    while sent >= 0.0:
        rounded = await round(sent)
        sent = yield rounded

Unlike normal generators, async generators cannot return a value, so there is no ReturnType type parameter. As with Generator, the SendType behaves contravariantly.

If your generator will only yield values, set the SendType to None:

async def infinite_stream(start: int) -> AsyncGenerator[int, None]:
    while True:
        yield start
        start = await increment(start)

Alternatively, annotate your generator as having a return type of either AsyncIterable[YieldType] or AsyncIterator[YieldType]:

async def infinite_stream(start: int) -> AsyncIterator[int]:
    while True:
        yield start
        start = await increment(start)

Nouveau dans la version 3.5.4.

class typing.Text

Text is an alias for str. It is provided to supply a forward compatible path for Python 2 code: in Python 2, Text is an alias for unicode.

Use Text to indicate that a value must contain a unicode string in a manner that is compatible with both Python 2 and Python 3:

def add_unicode_checkmark(text: Text) -> Text:
    return text + u' \u2713'

Nouveau dans la version 3.5.2.

class typing.IO

class typing.TextIO

class typing.BinaryIO

Generic type IO[AnyStr] and its subclasses TextIO(IO[str]) and BinaryIO(IO[bytes]) represent the types of I/O streams such as returned by open().

class typing.Pattern

class typing.Match

These type aliases correspond to the return types from re.compile() and re.match(). These types (and the corresponding functions) are generic in AnyStr and can be made specific by writing Pattern[str], Pattern[bytes], Match[str], or Match[bytes].

class typing.NamedTuple

Typed version of namedtuple.

Utilisation :

class Employee(NamedTuple):
    name: str
    id: int

C’est équivalent à :

Employee = collections.namedtuple('Employee', ['name', 'id'])

To give a field a default value, you can assign to it in the class body:

class Employee(NamedTuple):
    name: str
    id: int = 3

employee = Employee('Guido')
assert employee.id == 3

Fields with a default value must come after any fields without a default.

The resulting class has two extra attributes: _field_types, giving a dict mapping field names to types, and _field_defaults, a dict mapping field names to default values. (The field names are in the _fields attribute, which is part of the namedtuple API.)

NamedTuple subclasses can also have docstrings and methods:

class Employee(NamedTuple):
    """Represents an employee."""
    name: str
    id: int = 3

    def __repr__(self) -> str:
        return f'<Employee {self.name}, id={self.id}>'

Backward-compatible usage:

Employee = NamedTuple('Employee', [('name', str), ('id', int)])

Modifié dans la version 3.6: Added support for PEP 526 [https://www.python.org/dev/peps/pep-0526] variable annotation syntax.

Modifié dans la version 3.6.1: Added support for default values, methods, and docstrings.

typing.NewType(typ)

A helper function to indicate a distinct types to a typechecker, see NewType. At runtime it returns a function that returns its argument. Usage:

UserId = NewType('UserId', int)
first_user = UserId(1)

Nouveau dans la version 3.5.2.

typing.cast(typ, val)

Cast a value to a type.

This returns the value unchanged. To the type checker this signals that the return value has the designated type, but at runtime we intentionally don’t check anything (we want this to be as fast as possible).

typing.get_type_hints(obj[, globals[, locals]])

Return a dictionary containing type hints for a function, method, module or class object.

This is often the same as obj.__annotations__. In addition, forward references encoded as string literals are handled by evaluating them in globals and locals namespaces. If necessary, Optional[t] is added for function and method annotations if a default value equal to None is set. For a class C, return a dictionary constructed by merging all the __annotations__ along C.__mro__ in reverse order.

@typing.overload

The @overload decorator allows describing functions and methods that support multiple different combinations of argument types. A series of @overload-decorated definitions must be followed by exactly one non-@overload-decorated definition (for the same function/method). The @overload-decorated definitions are for the benefit of the type checker only, since they will be overwritten by the non-@overload-decorated definition, while the latter is used at runtime but should be ignored by a type checker. At runtime, calling a @overload-decorated function directly will raise NotImplementedError. An example of overload that gives a more precise type than can be expressed using a union or a type variable:

@overload
def process(response: None) -> None:
    ...
@overload
def process(response: int) -> Tuple[int, str]:
    ...
@overload
def process(response: bytes) -> str:
    ...
def process(response):
    <actual implementation>

See PEP 484 [https://www.python.org/dev/peps/pep-0484] for details and comparison with other typing semantics.

@typing.no_type_check

Decorator to indicate that annotations are not type hints.

This works as class or function decorator. With a class, it applies recursively to all methods defined in that class (but not to methods defined in its superclasses or subclasses).

This mutates the function(s) in place.

@typing.no_type_check_decorator

Decorator to give another decorator the no_type_check() effect.

This wraps the decorator with something that wraps the decorated function in no_type_check().

typing.Any

Special type indicating an unconstrained type.

Every type is compatible with Any.

Any is compatible with every type.

typing.NoReturn

Special type indicating that a function never returns. For example:

from typing import NoReturn

def stop() -> NoReturn:
    raise RuntimeError('no way')

Nouveau dans la version 3.6.5.

typing.Union

Union type; Union[X, Y] means either X or Y.

To define a union, use e.g. Union[int, str]. Details:

The arguments must be types and there must be at least one.

Unions of unions are flattened, e.g.:

Union[Union[int, str], float] == Union[int, str, float]

Unions of a single argument vanish, e.g.:

Union[int] == int  # The constructor actually returns int

Redundant arguments are skipped, e.g.:

Union[int, str, int] == Union[int, str]

When comparing unions, the argument order is ignored, e.g.:

Union[int, str] == Union[str, int]

When a class and its subclass are present, the latter is skipped, e.g.:

Union[int, object] == object

You cannot subclass or instantiate a union.

You cannot write Union[X][Y].

You can use Optional[X] as a shorthand for Union[X, None].

typing.Optional

Optional type.

Optional[X] is equivalent to Union[X, None].

Note that this is not the same concept as an optional argument, which is one that has a default. An optional argument with a default does not require the Optional qualifier on its type annotation just because it is optional. For example:

def foo(arg: int = 0) -> None:
    ...

On the other hand, if an explicit value of None is allowed, the use of Optional is appropriate, whether the argument is optional or not. For example:

def foo(arg: Optional[int] = None) -> None:
    ...

typing.Tuple

Tuple type; Tuple[X, Y] is the type of a tuple of two items with the first item of type X and the second of type Y.

Example: Tuple[T1, T2] is a tuple of two elements corresponding to type variables T1 and T2. Tuple[int, float, str] is a tuple of an int, a float and a string.

To specify a variable-length tuple of homogeneous type, use literal ellipsis, e.g. Tuple[int, ...]. A plain Tuple is equivalent to Tuple[Any, ...], and in turn to tuple.

typing.Callable

Callable type; Callable[[int], str] is a function of (int) -> str.

The subscription syntax must always be used with exactly two values: the argument list and the return type. The argument list must be a list of types or an ellipsis; the return type must be a single type.

There is no syntax to indicate optional or keyword arguments; such function types are rarely used as callback types. Callable[..., ReturnType] (literal ellipsis) can be used to type hint a callable taking any number of arguments and returning ReturnType. A plain Callable is equivalent to Callable[..., Any], and in turn to collections.abc.Callable.

typing.ClassVar

Special type construct to mark class variables.

As introduced in PEP 526 [https://www.python.org/dev/peps/pep-0526], a variable annotation wrapped in ClassVar indicates that a given attribute is intended to be used as a class variable and should not be set on instances of that class. Usage:

class Starship:
    stats: ClassVar[Dict[str, int]] = {} # class variable
    damage: int = 10                     # instance variable

ClassVar accepts only types and cannot be further subscribed.

ClassVar is not a class itself, and should not be used with isinstance() or issubclass(). ClassVar does not change Python runtime behavior, but it can be used by third-party type checkers. For example, a type checker might flag the following code as an error:

enterprise_d = Starship(3000)
enterprise_d.stats = {} # Error, setting class variable on instance
Starship.stats = {}     # This is OK

Nouveau dans la version 3.5.3.

typing.AnyStr

AnyStr is a type variable defined as AnyStr = TypeVar('AnyStr', str, bytes).

It is meant to be used for functions that may accept any kind of string without allowing different kinds of strings to mix. For example:

def concat(a: AnyStr, b: AnyStr) -> AnyStr:
    return a + b

concat(u"foo", u"bar")  # Ok, output has type 'unicode'
concat(b"foo", b"bar")  # Ok, output has type 'bytes'
concat(u"foo", b"bar")  # Error, cannot mix unicode and bytes

typing.TYPE_CHECKING

A special constant that is assumed to be True by 3rd party static type checkers. It is False at runtime. Usage:

if TYPE_CHECKING:
    import expensive_mod

def fun(arg: 'expensive_mod.SomeType') -> None:
    local_var: expensive_mod.AnotherType = other_fun()

Note that the first type annotation must be enclosed in quotes, making it a « forward reference », to hide the expensive_mod reference from the interpreter runtime. Type annotations for local variables are not evaluated, so the second annotation does not need to be enclosed in quotes.

Nouveau dans la version 3.5.2.

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26.2. pydoc — Générateur de documentation et système d’aide en ligne

Code source : Lib/pydoc.py [https://github.com/python/cpython/tree/3.6/Lib/pydoc.py]

Le module pydoc génère automatiquement de la documentation à partir de modules Python. La documentation peut se présenter sous forme de pages de texte dans la console, rendue dans un navigateur web, ou sauvegardée dans des fichiers HTML.

Pour les modules, classes, fonctions et méthodes, la documentation affichée est tirée de la docstring (c.à.d de l’attribut __doc__) de l’objet et ce, de manière récursive pour les membres qui peuvent être documentés. S’il n’y a pas de docstring, pydoc essaie d’obtenir une description à partir du bloc de commentaires juste au-dessus de la définition de la classe, fonction ou méthode du fichier source, ou en haut du module (voir inspect.getcomments()).

La fonction native help() appelle le système d’aide en ligne dans l’interpréteur Python qui utilise pydoc pour générer sa documentation sous forme textuelle dans la console. Cette même documentation peut aussi être consultée à l’extérieur de l’interpréteur Python en lançant pydoc dans le terminal du système d’exploitation. Par exemple en lançant

pydoc sys

dans un terminal, cela affiche la documentation du module sys dans un style similaire à la commande Unix man. On peut passer comme argument à pydoc le nom d’une fonction, d’un module, d’un paquet, ou une référence pointant vers une classe, une méthode, ou une fonction dans un module ou dans un paquet. Si l’argument passé à pydoc est un chemin (c.à.d qu’il contient des séparateurs de chemin tels que la barre oblique / dans Unix), et fait référence à un fichier source Python existant, alors la documentation est générée pour ce fichier.

Note

Afin de trouver des objets et leur documentation, pydoc importe le ou les modules à documenter. Par conséquent tout code au niveau du module sera exécuté à cette occasion. Utiliser if __name__ == ‘__main__’: évite d’exécuter du code lorsqu’un fichier est appelé directement et non pas importé.

Lorsque l’on affiche une sortie sur la console, pydoc essaye de créer une pagination pour faciliter la lecture. Si la variable d’environnement PAGER est configurée, pydoc utilise sa valeur comme programme de pagination.

Ajouter une option -w avant l’argument entraine l’enregistrement de la documentation HTML générée dans un fichier du répertoire courant au lieu de l’afficher dans la console.

Ajouter une option -w avant l’argument cherche les lignes de résumé de tous les modules disponibles pour le mot clé donné comme argument, ceci à la manière de la commande Unix man. Les lignes de résumé d’un module sont les premières lignes de sa docstring.

Vous pouvez aussi utiliser pydoc pour lancer un serveur HTTP sur votre machine locale qui rendra la documentation consultable sur votre navigateur Web. pydoc -p 1234 lancera un serveur HTTP sur le port 1234, permettant de consulter la documentation à l’adresse http://localhost:1234/ dans votre navigateur web préféré. En précisant 0 comme numéro de port, un port non utilisé sera aléatoirement alloué.

pydoc -b démarre le serveur et ouvrira en plus un navigateur web vers une page d’index de module. Chaque page affichée a une barre de navigation en haut où vous pouvez Obtenir de l’aide sur un élément individuel, Rechercher tous les modules avec un mot-clé dans leur ligne de résumé, et aller dans les pages Index des modules, Thèmes et Mots clés.

Quand pydoc génère de la documentation, il utilise l’environnement et le chemin courant pour localiser les modules. Ainsi, en invoquant les documents pydoc spam en précisant la version du module, vous obtenez le même résultat qu’en lançant l’interpréteur Python et en tapant la commande import spam.

La documentation des modules principaux est supposée être hébergée sur https://docs.python.org/X.Y/library/ et https://docs.python.org/fr/X.Y/library pour la version française, où X et Y sont les versions respectivement majeures et mineures de l’interpréteur Python. Ces valeurs peuvent être redéfinies en configurant la variable d’environnement PYTHONDOCS sur une URL différente ou un répertoire local contenant les pages du manuel de la bibliothèque de référence.

Modifié dans la version 3.2: Ajout de l’option -b.

Modifié dans la version 3.3: Suppression de l’option -g.

Modifié dans la version 3.4: pydoc utilise à présent inspect.signature() plutôt que inspect.getfullargspec() pour extraire les informations de signatures des callables.

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26.3. doctest — Test interactive Python examples

Source code: Lib/doctest.py [https://github.com/python/cpython/tree/3.6/Lib/doctest.py]

The doctest module searches for pieces of text that look like interactive Python sessions, and then executes those sessions to verify that they work exactly as shown. There are several common ways to use doctest:

To check that a module’s docstrings are up-to-date by verifying that all interactive examples still work as documented.

To perform regression testing by verifying that interactive examples from a test file or a test object work as expected.

To write tutorial documentation for a package, liberally illustrated with input-output examples. Depending on whether the examples or the expository text are emphasized, this has the flavor of « literate testing » or « executable documentation ».

Here’s a complete but small example module:

"""
This is the "example" module.

The example module supplies one function, factorial().  For example,

>>> factorial(5)
120
"""

def factorial(n):
    """Return the factorial of n, an exact integer >= 0.

    >>> [factorial(n) for n in range(6)]
    [1, 1, 2, 6, 24, 120]
    >>> factorial(30)
    265252859812191058636308480000000
    >>> factorial(-1)
    Traceback (most recent call last):
        ...
    ValueError: n must be >= 0

    Factorials of floats are OK, but the float must be an exact integer:
    >>> factorial(30.1)
    Traceback (most recent call last):
        ...
    ValueError: n must be exact integer
    >>> factorial(30.0)
    265252859812191058636308480000000

    It must also not be ridiculously large:
    >>> factorial(1e100)
    Traceback (most recent call last):
        ...
    OverflowError: n too large
    """

    import math
    if not n >= 0:
        raise ValueError("n must be >= 0")
    if math.floor(n) != n:
        raise ValueError("n must be exact integer")
    if n+1 == n:  # catch a value like 1e300
        raise OverflowError("n too large")
    result = 1
    factor = 2
    while factor <= n:
        result *= factor
        factor += 1
    return result

if __name__ == "__main__":
    import doctest
    doctest.testmod()

If you run example.py directly from the command line, doctest works its magic:

$ python example.py
$

There’s no output! That’s normal, and it means all the examples worked. Pass -v to the script, and doctest prints a detailed log of what it’s trying, and prints a summary at the end:

$ python example.py -v
Trying:
    factorial(5)
Expecting:
    120
ok
Trying:
    [factorial(n) for n in range(6)]
Expecting:
    [1, 1, 2, 6, 24, 120]
ok

And so on, eventually ending with:

Trying:
    factorial(1e100)
Expecting:
    Traceback (most recent call last):
        ...
    OverflowError: n too large
ok
2 items passed all tests:
   1 tests in __main__
   8 tests in __main__.factorial
9 tests in 2 items.
9 passed and 0 failed.
Test passed.
$

That’s all you need to know to start making productive use of doctest! Jump in. The following sections provide full details. Note that there are many examples of doctests in the standard Python test suite and libraries. Especially useful examples can be found in the standard test file Lib/test/test_doctest.py.

26.3.1. Simple Usage: Checking Examples in Docstrings

The simplest way to start using doctest (but not necessarily the way you’ll continue to do it) is to end each module M with:

if __name__ == "__main__":
    import doctest
    doctest.testmod()

doctest then examines docstrings in module M.

Running the module as a script causes the examples in the docstrings to get executed and verified:

python M.py

This won’t display anything unless an example fails, in which case the failing example(s) and the cause(s) of the failure(s) are printed to stdout, and the final line of output is ***Test Failed*** N failures., where N is the number of examples that failed.

Run it with the -v switch instead:

python M.py -v

and a detailed report of all examples tried is printed to standard output, along with assorted summaries at the end.

You can force verbose mode by passing verbose=True to testmod(), or prohibit it by passing verbose=False. In either of those cases, sys.argv is not examined by testmod() (so passing -v or not has no effect).

There is also a command line shortcut for running testmod(). You can instruct the Python interpreter to run the doctest module directly from the standard library and pass the module name(s) on the command line:

python -m doctest -v example.py

This will import example.py as a standalone module and run testmod() on it. Note that this may not work correctly if the file is part of a package and imports other submodules from that package.

For more information on testmod(), see section Basic API.

26.3.2. Simple Usage: Checking Examples in a Text File

Another simple application of doctest is testing interactive examples in a text file. This can be done with the testfile() function:

import doctest
doctest.testfile("example.txt")

That short script executes and verifies any interactive Python examples contained in the file example.txt. The file content is treated as if it were a single giant docstring; the file doesn’t need to contain a Python program! For example, perhaps example.txt contains this:

The ``example`` module
======================

Using ``factorial``
-------------------

This is an example text file in reStructuredText format.  First import
``factorial`` from the ``example`` module:

    >>> from example import factorial

Now use it:

    >>> factorial(6)
    120

Running doctest.testfile("example.txt") then finds the error in this documentation:

File "./example.txt", line 14, in example.txt
Failed example:
    factorial(6)
Expected:
    120
Got:
    720

As with testmod(), testfile() won’t display anything unless an example fails. If an example does fail, then the failing example(s) and the cause(s) of the failure(s) are printed to stdout, using the same format as testmod().

By default, testfile() looks for files in the calling module’s directory. See section Basic API for a description of the optional arguments that can be used to tell it to look for files in other locations.

Like testmod(), testfile()”s verbosity can be set with the -v command-line switch or with the optional keyword argument verbose.

There is also a command line shortcut for running testfile(). You can instruct the Python interpreter to run the doctest module directly from the standard library and pass the file name(s) on the command line:

python -m doctest -v example.txt

Because the file name does not end with .py, doctest infers that it must be run with testfile(), not testmod().

For more information on testfile(), see section Basic API.

26.3.3. How It Works

This section examines in detail how doctest works: which docstrings it looks at, how it finds interactive examples, what execution context it uses, how it handles exceptions, and how option flags can be used to control its behavior. This is the information that you need to know to write doctest examples; for information about actually running doctest on these examples, see the following sections.

26.3.3.1. Which Docstrings Are Examined?

The module docstring, and all function, class and method docstrings are searched. Objects imported into the module are not searched.

In addition, if M.__test__ exists and « is true », it must be a dict, and each entry maps a (string) name to a function object, class object, or string. Function and class object docstrings found from M.__test__ are searched, and strings are treated as if they were docstrings. In output, a key K in M.__test__ appears with name

<name of M>.__test__.K

Any classes found are recursively searched similarly, to test docstrings in their contained methods and nested classes.

CPython implementation detail: Prior to version 3.4, extension modules written in C were not fully searched by doctest.

26.3.3.2. How are Docstring Examples Recognized?

In most cases a copy-and-paste of an interactive console session works fine, but doctest isn’t trying to do an exact emulation of any specific Python shell.

>>> # comments are ignored
>>> x = 12
>>> x
12
>>> if x == 13:
...     print("yes")
... else:
...     print("no")
...     print("NO")
...     print("NO!!!")
...
no
NO
NO!!!
>>>

Any expected output must immediately follow the final '>>> ' or '... ' line containing the code, and the expected output (if any) extends to the next '>>> ' or all-whitespace line.

The fine print:

Expected output cannot contain an all-whitespace line, since such a line is taken to signal the end of expected output. If expected output does contain a blank line, put <BLANKLINE> in your doctest example each place a blank line is expected.

All hard tab characters are expanded to spaces, using 8-column tab stops. Tabs in output generated by the tested code are not modified. Because any hard tabs in the sample output are expanded, this means that if the code output includes hard tabs, the only way the doctest can pass is if the NORMALIZE_WHITESPACE option or directive is in effect. Alternatively, the test can be rewritten to capture the output and compare it to an expected value as part of the test. This handling of tabs in the source was arrived at through trial and error, and has proven to be the least error prone way of handling them. It is possible to use a different algorithm for handling tabs by writing a custom DocTestParser class.

Output to stdout is captured, but not output to stderr (exception tracebacks are captured via a different means).

If you continue a line via backslashing in an interactive session, or for any other reason use a backslash, you should use a raw docstring, which will preserve your backslashes exactly as you type them:

>>> def f(x):
...     r'''Backslashes in a raw docstring: m\n'''
>>> print(f.__doc__)
Backslashes in a raw docstring: m\n

Otherwise, the backslash will be interpreted as part of the string. For example, the \n above would be interpreted as a newline character. Alternatively, you can double each backslash in the doctest version (and not use a raw string):

>>> def f(x):
...     '''Backslashes in a raw docstring: m\\n'''
>>> print(f.__doc__)
Backslashes in a raw docstring: m\n

The starting column doesn’t matter:

>>> assert "Easy!"
      >>> import math
          >>> math.floor(1.9)
          1

and as many leading whitespace characters are stripped from the expected output as appeared in the initial '>>> ' line that started the example.

26.3.3.3. What’s the Execution Context?

By default, each time doctest finds a docstring to test, it uses a shallow copy of M’s globals, so that running tests doesn’t change the module’s real globals, and so that one test in M can’t leave behind crumbs that accidentally allow another test to work. This means examples can freely use any names defined at top-level in M, and names defined earlier in the docstring being run. Examples cannot see names defined in other docstrings.

You can force use of your own dict as the execution context by passing globs=your_dict to testmod() or testfile() instead.

26.3.3.4. What About Exceptions?

No problem, provided that the traceback is the only output produced by the example: just paste in the traceback. 1 Since tracebacks contain details that are likely to change rapidly (for example, exact file paths and line numbers), this is one case where doctest works hard to be flexible in what it accepts.

Simple example:

>>> [1, 2, 3].remove(42)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
ValueError: list.remove(x): x not in list

That doctest succeeds if ValueError is raised, with the list.remove(x): x not in list detail as shown.

The expected output for an exception must start with a traceback header, which may be either of the following two lines, indented the same as the first line of the example:

Traceback (most recent call last):
Traceback (innermost last):

The traceback header is followed by an optional traceback stack, whose contents are ignored by doctest. The traceback stack is typically omitted, or copied verbatim from an interactive session.

The traceback stack is followed by the most interesting part: the line(s) containing the exception type and detail. This is usually the last line of a traceback, but can extend across multiple lines if the exception has a multi-line detail:

>>> raise ValueError('multi\n    line\ndetail')
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
ValueError: multi
    line
detail

The last three lines (starting with ValueError) are compared against the exception’s type and detail, and the rest are ignored.

Best practice is to omit the traceback stack, unless it adds significant documentation value to the example. So the last example is probably better as:

>>> raise ValueError('multi\n    line\ndetail')
Traceback (most recent call last):
    ...
ValueError: multi
    line
detail

Note that tracebacks are treated very specially. In particular, in the rewritten example, the use of ... is independent of doctest’s ELLIPSIS option. The ellipsis in that example could be left out, or could just as well be three (or three hundred) commas or digits, or an indented transcript of a Monty Python skit.

Some details you should read once, but won’t need to remember:

Doctest can’t guess whether your expected output came from an exception traceback or from ordinary printing. So, e.g., an example that expects ValueError: 42 is prime will pass whether ValueError is actually raised or if the example merely prints that traceback text. In practice, ordinary output rarely begins with a traceback header line, so this doesn’t create real problems.

Each line of the traceback stack (if present) must be indented further than the first line of the example, or start with a non-alphanumeric character. The first line following the traceback header indented the same and starting with an alphanumeric is taken to be the start of the exception detail. Of course this does the right thing for genuine tracebacks.

When the IGNORE_EXCEPTION_DETAIL doctest option is specified, everything following the leftmost colon and any module information in the exception name is ignored.

The interactive shell omits the traceback header line for some SyntaxErrors. But doctest uses the traceback header line to distinguish exceptions from non-exceptions. So in the rare case where you need to test a SyntaxError that omits the traceback header, you will need to manually add the traceback header line to your test example.

For some SyntaxErrors, Python displays the character position of the syntax error, using a ^ marker:

>>> 1 1
  File "<stdin>", line 1
    1 1
      ^
SyntaxError: invalid syntax

Since the lines showing the position of the error come before the exception type and detail, they are not checked by doctest. For example, the following test would pass, even though it puts the ^ marker in the wrong location:

>>> 1 1
  File "<stdin>", line 1
    1 1
    ^
SyntaxError: invalid syntax

26.3.3.5. Option Flags

A number of option flags control various aspects of doctest’s behavior. Symbolic names for the flags are supplied as module constants, which can be bitwise ORed together and passed to various functions. The names can also be used in doctest directives, and may be passed to the doctest command line interface via the -o option.

Nouveau dans la version 3.4: The -o command line option.

The first group of options define test semantics, controlling aspects of how doctest decides whether actual output matches an example’s expected output:

doctest.DONT_ACCEPT_TRUE_FOR_1

By default, if an expected output block contains just 1, an actual output block containing just 1 or just True is considered to be a match, and similarly for 0 versus False. When DONT_ACCEPT_TRUE_FOR_1 is specified, neither substitution is allowed. The default behavior caters to that Python changed the return type of many functions from integer to boolean; doctests expecting « little integer » output still work in these cases. This option will probably go away, but not for several years.

doctest.DONT_ACCEPT_BLANKLINE

By default, if an expected output block contains a line containing only the string <BLANKLINE>, then that line will match a blank line in the actual output. Because a genuinely blank line delimits the expected output, this is the only way to communicate that a blank line is expected. When DONT_ACCEPT_BLANKLINE is specified, this substitution is not allowed.

doctest.NORMALIZE_WHITESPACE

When specified, all sequences of whitespace (blanks and newlines) are treated as equal. Any sequence of whitespace within the expected output will match any sequence of whitespace within the actual output. By default, whitespace must match exactly. NORMALIZE_WHITESPACE is especially useful when a line of expected output is very long, and you want to wrap it across multiple lines in your source.

doctest.ELLIPSIS

When specified, an ellipsis marker (...) in the expected output can match any substring in the actual output. This includes substrings that span line boundaries, and empty substrings, so it’s best to keep usage of this simple. Complicated uses can lead to the same kinds of « oops, it matched too much! » surprises that .* is prone to in regular expressions.

doctest.IGNORE_EXCEPTION_DETAIL

When specified, an example that expects an exception passes if an exception of the expected type is raised, even if the exception detail does not match. For example, an example expecting ValueError: 42 will pass if the actual exception raised is ValueError: 3*14, but will fail, e.g., if TypeError is raised.

It will also ignore the module name used in Python 3 doctest reports. Hence both of these variations will work with the flag specified, regardless of whether the test is run under Python 2.7 or Python 3.2 (or later versions):

>>> raise CustomError('message')
Traceback (most recent call last):
CustomError: message

>>> raise CustomError('message')
Traceback (most recent call last):
my_module.CustomError: message

Note that ELLIPSIS can also be used to ignore the details of the exception message, but such a test may still fail based on whether or not the module details are printed as part of the exception name. Using IGNORE_EXCEPTION_DETAIL and the details from Python 2.3 is also the only clear way to write a doctest that doesn’t care about the exception detail yet continues to pass under Python 2.3 or earlier (those releases do not support doctest directives and ignore them as irrelevant comments). For example:

>>> (1, 2)[3] = 'moo'
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: object doesn't support item assignment

passes under Python 2.3 and later Python versions with the flag specified, even though the detail changed in Python 2.4 to say « does not » instead of « doesn’t ».

Modifié dans la version 3.2: IGNORE_EXCEPTION_DETAIL now also ignores any information relating to the module containing the exception under test.

doctest.SKIP

When specified, do not run the example at all. This can be useful in contexts where doctest examples serve as both documentation and test cases, and an example should be included for documentation purposes, but should not be checked. E.g., the example’s output might be random; or the example might depend on resources which would be unavailable to the test driver.

The SKIP flag can also be used for temporarily « commenting out » examples.

doctest.COMPARISON_FLAGS

A bitmask or’ing together all the comparison flags above.

The second group of options controls how test failures are reported:

doctest.REPORT_UDIFF

When specified, failures that involve multi-line expected and actual outputs are displayed using a unified diff.

doctest.REPORT_CDIFF

When specified, failures that involve multi-line expected and actual outputs will be displayed using a context diff.

doctest.REPORT_NDIFF

When specified, differences are computed by difflib.Differ, using the same algorithm as the popular ndiff.py utility. This is the only method that marks differences within lines as well as across lines. For example, if a line of expected output contains digit 1 where actual output contains letter l, a line is inserted with a caret marking the mismatching column positions.

doctest.REPORT_ONLY_FIRST_FAILURE

When specified, display the first failing example in each doctest, but suppress output for all remaining examples. This will prevent doctest from reporting correct examples that break because of earlier failures; but it might also hide incorrect examples that fail independently of the first failure. When REPORT_ONLY_FIRST_FAILURE is specified, the remaining examples are still run, and still count towards the total number of failures reported; only the output is suppressed.

doctest.FAIL_FAST

When specified, exit after the first failing example and don’t attempt to run the remaining examples. Thus, the number of failures reported will be at most 1. This flag may be useful during debugging, since examples after the first failure won’t even produce debugging output.

The doctest command line accepts the option -f as a shorthand for -o FAIL_FAST.

Nouveau dans la version 3.4.

doctest.REPORTING_FLAGS

A bitmask or’ing together all the reporting flags above.

There is also a way to register new option flag names, though this isn’t useful unless you intend to extend doctest internals via subclassing:

doctest.register_optionflag(name)

Create a new option flag with a given name, and return the new flag’s integer value. register_optionflag() can be used when subclassing OutputChecker or DocTestRunner to create new options that are supported by your subclasses. register_optionflag() should always be called using the following idiom:

MY_FLAG = register_optionflag('MY_FLAG')

26.3.3.6. Directives

Doctest directives may be used to modify the option flags for an individual example. Doctest directives are special Python comments following an example’s source code:

directive             ::=  "#" "doctest:" directive_options
directive_options     ::=  directive_option ("," directive_option)\*
directive_option      ::=  on_or_off directive_option_name
on_or_off             ::=  "+" \| "-"
directive_option_name ::=  "DONT_ACCEPT_BLANKLINE" \| "NORMALIZE_WHITESPACE" \| ...

Whitespace is not allowed between the + or - and the directive option name. The directive option name can be any of the option flag names explained above.

An example’s doctest directives modify doctest’s behavior for that single example. Use + to enable the named behavior, or - to disable it.

For example, this test passes:

>>> print(list(range(20)))
[0,   1,  2,  3,  4,  5,  6,  7,  8,  9,
10,  11, 12, 13, 14, 15, 16, 17, 18, 19]

Without the directive it would fail, both because the actual output doesn’t have two blanks before the single-digit list elements, and because the actual output is on a single line. This test also passes, and also requires a directive to do so:

>>> print(list(range(20)))
[0, 1, ..., 18, 19]

Multiple directives can be used on a single physical line, separated by commas:

>>> print(list(range(20)))
[0,    1, ...,   18,    19]

If multiple directive comments are used for a single example, then they are combined:

>>> print(list(range(20)))
...
[0,    1, ...,   18,    19]

As the previous example shows, you can add ... lines to your example containing only directives. This can be useful when an example is too long for a directive to comfortably fit on the same line:

>>> print(list(range(5)) + list(range(10, 20)) + list(range(30, 40)))
...
[0, ..., 4, 10, ..., 19, 30, ..., 39]

Note that since all options are disabled by default, and directives apply only to the example they appear in, enabling options (via + in a directive) is usually the only meaningful choice. However, option flags can also be passed to functions that run doctests, establishing different defaults. In such cases, disabling an option via - in a directive can be useful.

26.3.3.7. Avertissements

doctest is serious about requiring exact matches in expected output. If even a single character doesn’t match, the test fails. This will probably surprise you a few times, as you learn exactly what Python does and doesn’t guarantee about output. For example, when printing a dict, Python doesn’t guarantee that the key-value pairs will be printed in any particular order, so a test like

>>> foo()
{"Hermione": "hippogryph", "Harry": "broomstick"}

is vulnerable! One workaround is to do

>>> foo() == {"Hermione": "hippogryph", "Harry": "broomstick"}
True

instead. Another is to do

>>> d = sorted(foo().items())
>>> d
[('Harry', 'broomstick'), ('Hermione', 'hippogryph')]

There are others, but you get the idea.

Another bad idea is to print things that embed an object address, like

>>> id(1.0) # certain to fail some of the time
7948648
>>> class C: pass
>>> C()   # the default repr() for instances embeds an address
<__main__.C instance at 0x00AC18F0>

The ELLIPSIS directive gives a nice approach for the last example:

>>> C()
<__main__.C instance at 0x...>

Floating-point numbers are also subject to small output variations across platforms, because Python defers to the platform C library for float formatting, and C libraries vary widely in quality here.

>>> 1./7  # risky
0.14285714285714285
>>> print(1./7) # safer
0.142857142857
>>> print(round(1./7, 6)) # much safer
0.142857

Numbers of the form I/2.**J are safe across all platforms, and I often contrive doctest examples to produce numbers of that form:

>>> 3./4  # utterly safe
0.75

Simple fractions are also easier for people to understand, and that makes for better documentation.

26.3.4. Basic API

The functions testmod() and testfile() provide a simple interface to doctest that should be sufficient for most basic uses. For a less formal introduction to these two functions, see sections Simple Usage: Checking Examples in Docstrings and Simple Usage: Checking Examples in a Text File.

doctest.testfile(filename, module_relative=True, name=None, package=None, globs=None, verbose=None, report=True, optionflags=0, extraglobs=None, raise_on_error=False, parser=DocTestParser(), encoding=None)

All arguments except filename are optional, and should be specified in keyword form.

Test examples in the file named filename. Return (failure_count, test_count).

Optional argument module_relative specifies how the filename should be interpreted:

If module_relative is True (the default), then filename specifies an OS-independent module-relative path. By default, this path is relative to the calling module’s directory; but if the package argument is specified, then it is relative to that package. To ensure OS-independence, filename should use / characters to separate path segments, and may not be an absolute path (i.e., it may not begin with /).

If module_relative is False, then filename specifies an OS-specific path. The path may be absolute or relative; relative paths are resolved with respect to the current working directory.

Optional argument name gives the name of the test; by default, or if None, os.path.basename(filename) is used.

Optional argument package is a Python package or the name of a Python package whose directory should be used as the base directory for a module-relative filename. If no package is specified, then the calling module’s directory is used as the base directory for module-relative filenames. It is an error to specify package if module_relative is False.

Optional argument globs gives a dict to be used as the globals when executing examples. A new shallow copy of this dict is created for the doctest, so its examples start with a clean slate. By default, or if None, a new empty dict is used.

Optional argument extraglobs gives a dict merged into the globals used to execute examples. This works like dict.update(): if globs and extraglobs have a common key, the associated value in extraglobs appears in the combined dict. By default, or if None, no extra globals are used. This is an advanced feature that allows parameterization of doctests. For example, a doctest can be written for a base class, using a generic name for the class, then reused to test any number of subclasses by passing an extraglobs dict mapping the generic name to the subclass to be tested.

Optional argument verbose prints lots of stuff if true, and prints only failures if false; by default, or if None, it’s true if and only if '-v' is in sys.argv.

Optional argument report prints a summary at the end when true, else prints nothing at the end. In verbose mode, the summary is detailed, else the summary is very brief (in fact, empty if all tests passed).

Optional argument optionflags (default value 0) takes the bitwise OR of option flags. See section Option Flags.

Optional argument raise_on_error defaults to false. If true, an exception is raised upon the first failure or unexpected exception in an example. This allows failures to be post-mortem debugged. Default behavior is to continue running examples.

Optional argument parser specifies a DocTestParser (or subclass) that should be used to extract tests from the files. It defaults to a normal parser (i.e., DocTestParser()).

Optional argument encoding specifies an encoding that should be used to convert the file to unicode.

doctest.testmod(m=None, name=None, globs=None, verbose=None, report=True, optionflags=0, extraglobs=None, raise_on_error=False, exclude_empty=False)

All arguments are optional, and all except for m should be specified in keyword form.

Test examples in docstrings in functions and classes reachable from module m (or module __main__ if m is not supplied or is None), starting with m.__doc__.

Also test examples reachable from dict m.__test__, if it exists and is not None. m.__test__ maps names (strings) to functions, classes and strings; function and class docstrings are searched for examples; strings are searched directly, as if they were docstrings.

Only docstrings attached to objects belonging to module m are searched.

Return (failure_count, test_count).

Optional argument name gives the name of the module; by default, or if None, m.__name__ is used.

Optional argument exclude_empty defaults to false. If true, objects for which no doctests are found are excluded from consideration. The default is a backward compatibility hack, so that code still using doctest.master.summarize() in conjunction with testmod() continues to get output for objects with no tests. The exclude_empty argument to the newer DocTestFinder constructor defaults to true.

Optional arguments extraglobs, verbose, report, optionflags, raise_on_error, and globs are the same as for function testfile() above, except that globs defaults to m.__dict__.

doctest.run_docstring_examples(f, globs, verbose=False, name="NoName", compileflags=None, optionflags=0)

Test examples associated with object f; for example, f may be a string, a module, a function, or a class object.

A shallow copy of dictionary argument globs is used for the execution context.

Optional argument name is used in failure messages, and defaults to "NoName".

If optional argument verbose is true, output is generated even if there are no failures. By default, output is generated only in case of an example failure.

Optional argument compileflags gives the set of flags that should be used by the Python compiler when running the examples. By default, or if None, flags are deduced corresponding to the set of future features found in globs.

Optional argument optionflags works as for function testfile() above.

26.3.5. Unittest API

As your collection of doctest’ed modules grows, you’ll want a way to run all their doctests systematically. doctest provides two functions that can be used to create unittest test suites from modules and text files containing doctests. To integrate with unittest test discovery, include a load_tests() function in your test module:

import unittest
import doctest
import my_module_with_doctests

def load_tests(loader, tests, ignore):
    tests.addTests(doctest.DocTestSuite(my_module_with_doctests))
    return tests

There are two main functions for creating unittest.TestSuite instances from text files and modules with doctests:

doctest.DocFileSuite(*paths, module_relative=True, package=None, setUp=None, tearDown=None, globs=None, optionflags=0, parser=DocTestParser(), encoding=None)

Convert doctest tests from one or more text files to a unittest.TestSuite.

The returned unittest.TestSuite is to be run by the unittest framework and runs the interactive examples in each file. If an example in any file fails, then the synthesized unit test fails, and a failureException exception is raised showing the name of the file containing the test and a (sometimes approximate) line number.

Pass one or more paths (as strings) to text files to be examined.

Options may be provided as keyword arguments:

Optional argument module_relative specifies how the filenames in paths should be interpreted:

If module_relative is True (the default), then each filename in paths specifies an OS-independent module-relative path. By default, this path is relative to the calling module’s directory; but if the package argument is specified, then it is relative to that package. To ensure OS-independence, each filename should use / characters to separate path segments, and may not be an absolute path (i.e., it may not begin with /).

If module_relative is False, then each filename in paths specifies an OS-specific path. The path may be absolute or relative; relative paths are resolved with respect to the current working directory.

Optional argument package is a Python package or the name of a Python package whose directory should be used as the base directory for module-relative filenames in paths. If no package is specified, then the calling module’s directory is used as the base directory for module-relative filenames. It is an error to specify package if module_relative is False.

Optional argument setUp specifies a set-up function for the test suite. This is called before running the tests in each file. The setUp function will be passed a DocTest object. The setUp function can access the test globals as the globs attribute of the test passed.

Optional argument tearDown specifies a tear-down function for the test suite. This is called after running the tests in each file. The tearDown function will be passed a DocTest object. The setUp function can access the test globals as the globs attribute of the test passed.

Optional argument globs is a dictionary containing the initial global variables for the tests. A new copy of this dictionary is created for each test. By default, globs is a new empty dictionary.

Optional argument optionflags specifies the default doctest options for the tests, created by or-ing together individual option flags. See section Option Flags. See function set_unittest_reportflags() below for a better way to set reporting options.

Optional argument parser specifies a DocTestParser (or subclass) that should be used to extract tests from the files. It defaults to a normal parser (i.e., DocTestParser()).

Optional argument encoding specifies an encoding that should be used to convert the file to unicode.

The global __file__ is added to the globals provided to doctests loaded from a text file using DocFileSuite().

doctest.DocTestSuite(module=None, globs=None, extraglobs=None, test_finder=None, setUp=None, tearDown=None, checker=None)

Convert doctest tests for a module to a unittest.TestSuite.

The returned unittest.TestSuite is to be run by the unittest framework and runs each doctest in the module. If any of the doctests fail, then the synthesized unit test fails, and a failureException exception is raised showing the name of the file containing the test and a (sometimes approximate) line number.

Optional argument module provides the module to be tested. It can be a module object or a (possibly dotted) module name. If not specified, the module calling this function is used.

Optional argument globs is a dictionary containing the initial global variables for the tests. A new copy of this dictionary is created for each test. By default, globs is a new empty dictionary.

Optional argument extraglobs specifies an extra set of global variables, which is merged into globs. By default, no extra globals are used.

Optional argument test_finder is the DocTestFinder object (or a drop-in replacement) that is used to extract doctests from the module.

Optional arguments setUp, tearDown, and optionflags are the same as for function DocFileSuite() above.

This function uses the same search technique as testmod().

Modifié dans la version 3.5: DocTestSuite() returns an empty unittest.TestSuite if module contains no docstrings instead of raising ValueError.

Under the covers, DocTestSuite() creates a unittest.TestSuite out of doctest.DocTestCase instances, and DocTestCase is a subclass of unittest.TestCase. DocTestCase isn’t documented here (it’s an internal detail), but studying its code can answer questions about the exact details of unittest integration.

Similarly, DocFileSuite() creates a unittest.TestSuite out of doctest.DocFileCase instances, and DocFileCase is a subclass of DocTestCase.

So both ways of creating a unittest.TestSuite run instances of DocTestCase. This is important for a subtle reason: when you run doctest functions yourself, you can control the doctest options in use directly, by passing option flags to doctest functions. However, if you’re writing a unittest framework, unittest ultimately controls when and how tests get run. The framework author typically wants to control doctest reporting options (perhaps, e.g., specified by command line options), but there’s no way to pass options through unittest to doctest test runners.

For this reason, doctest also supports a notion of doctest reporting flags specific to unittest support, via this function:

doctest.set_unittest_reportflags(flags)

Set the doctest reporting flags to use.

Argument flags takes the bitwise OR of option flags. See section Option Flags. Only « reporting flags » can be used.

This is a module-global setting, and affects all future doctests run by module unittest: the runTest() method of DocTestCase looks at the option flags specified for the test case when the DocTestCase instance was constructed. If no reporting flags were specified (which is the typical and expected case), doctest’s unittest reporting flags are bitwise ORed into the option flags, and the option flags so augmented are passed to the DocTestRunner instance created to run the doctest. If any reporting flags were specified when the DocTestCase instance was constructed, doctest’s unittest reporting flags are ignored.

The value of the unittest reporting flags in effect before the function was called is returned by the function.

26.3.6. Advanced API

The basic API is a simple wrapper that’s intended to make doctest easy to use. It is fairly flexible, and should meet most users” needs; however, if you require more fine-grained control over testing, or wish to extend doctest’s capabilities, then you should use the advanced API.

The advanced API revolves around two container classes, which are used to store the interactive examples extracted from doctest cases:

Example: A single Python statement, paired with its expected output.

DocTest: A collection of Examples, typically extracted from a single docstring or text file.

Additional processing classes are defined to find, parse, and run, and check doctest examples:

DocTestFinder: Finds all docstrings in a given module, and uses a DocTestParser to create a DocTest from every docstring that contains interactive examples.

DocTestParser: Creates a DocTest object from a string (such as an object’s docstring).

DocTestRunner: Executes the examples in a DocTest, and uses an OutputChecker to verify their output.

OutputChecker: Compares the actual output from a doctest example with the expected output, and decides whether they match.

The relationships among these processing classes are summarized in the following diagram:

                            list of:
+------+                   +---------+
|module| --DocTestFinder-> | DocTest | --DocTestRunner-> results
+------+    |        ^     +---------+     |       ^    (printed)
            |        |     | Example |     |       |
            v        |     |   ...   |     v       |
           DocTestParser   | Example |   OutputChecker
                           +---------+

26.3.6.1. DocTest Objects

class doctest.DocTest(examples, globs, name, filename, lineno, docstring)

A collection of doctest examples that should be run in a single namespace. The constructor arguments are used to initialize the attributes of the same names.

DocTest defines the following attributes. They are initialized by the constructor, and should not be modified directly.

examples

A list of Example objects encoding the individual interactive Python examples that should be run by this test.

globs

The namespace (aka globals) that the examples should be run in. This is a dictionary mapping names to values. Any changes to the namespace made by the examples (such as binding new variables) will be reflected in globs after the test is run.

name

A string name identifying the DocTest. Typically, this is the name of the object or file that the test was extracted from.

filename

The name of the file that this DocTest was extracted from; or None if the filename is unknown, or if the DocTest was not extracted from a file.

lineno

The line number within filename where this DocTest begins, or None if the line number is unavailable. This line number is zero-based with respect to the beginning of the file.

docstring

The string that the test was extracted from, or None if the string is unavailable, or if the test was not extracted from a string.

26.3.6.2. Example Objects

class doctest.Example(source, want, exc_msg=None, lineno=0, indent=0, options=None)

A single interactive example, consisting of a Python statement and its expected output. The constructor arguments are used to initialize the attributes of the same names.

Example defines the following attributes. They are initialized by the constructor, and should not be modified directly.

source

A string containing the example’s source code. This source code consists of a single Python statement, and always ends with a newline; the constructor adds a newline when necessary.

want

The expected output from running the example’s source code (either from stdout, or a traceback in case of exception). want ends with a newline unless no output is expected, in which case it’s an empty string. The constructor adds a newline when necessary.

exc_msg

The exception message generated by the example, if the example is expected to generate an exception; or None if it is not expected to generate an exception. This exception message is compared against the return value of traceback.format_exception_only(). exc_msg ends with a newline unless it’s None. The constructor adds a newline if needed.

lineno

The line number within the string containing this example where the example begins. This line number is zero-based with respect to the beginning of the containing string.

indent

The example’s indentation in the containing string, i.e., the number of space characters that precede the example’s first prompt.

options

A dictionary mapping from option flags to True or False, which is used to override default options for this example. Any option flags not contained in this dictionary are left at their default value (as specified by the DocTestRunner’s optionflags). By default, no options are set.

26.3.6.3. DocTestFinder objects

class doctest.DocTestFinder(verbose=False, parser=DocTestParser(), recurse=True, exclude_empty=True)

A processing class used to extract the DocTests that are relevant to a given object, from its docstring and the docstrings of its contained objects. DocTests can be extracted from modules, classes, functions, methods, staticmethods, classmethods, and properties.

The optional argument verbose can be used to display the objects searched by the finder. It defaults to False (no output).

The optional argument parser specifies the DocTestParser object (or a drop-in replacement) that is used to extract doctests from docstrings.

If the optional argument recurse is false, then DocTestFinder.find() will only examine the given object, and not any contained objects.

If the optional argument exclude_empty is false, then DocTestFinder.find() will include tests for objects with empty docstrings.

DocTestFinder defines the following method:

find(obj[, name][, module][, globs][, extraglobs])

Return a list of the DocTests that are defined by obj’s docstring, or by any of its contained objects” docstrings.

The optional argument name specifies the object’s name; this name will be used to construct names for the returned DocTests. If name is not specified, then obj.__name__ is used.

The optional parameter module is the module that contains the given object. If the module is not specified or is None, then the test finder will attempt to automatically determine the correct module. The object’s module is used:

As a default namespace, if globs is not specified.

To prevent the DocTestFinder from extracting DocTests from objects that are imported from other modules. (Contained objects with modules other than module are ignored.)

To find the name of the file containing the object.

To help find the line number of the object within its file.

If module is False, no attempt to find the module will be made. This is obscure, of use mostly in testing doctest itself: if module is False, or is None but cannot be found automatically, then all objects are considered to belong to the (non-existent) module, so all contained objects will (recursively) be searched for doctests.

The globals for each DocTest is formed by combining globs and extraglobs (bindings in extraglobs override bindings in globs). A new shallow copy of the globals dictionary is created for each DocTest. If globs is not specified, then it defaults to the module’s __dict__, if specified, or {} otherwise. If extraglobs is not specified, then it defaults to {}.

26.3.6.4. DocTestParser objects

class doctest.DocTestParser

A processing class used to extract interactive examples from a string, and use them to create a DocTest object.

DocTestParser defines the following methods:

get_doctest(string, globs, name, filename, lineno)

Extract all doctest examples from the given string, and collect them into a DocTest object.

globs, name, filename, and lineno are attributes for the new DocTest object. See the documentation for DocTest for more information.

get_examples(string, name='<string>')

Extract all doctest examples from the given string, and return them as a list of Example objects. Line numbers are 0-based. The optional argument name is a name identifying this string, and is only used for error messages.

parse(string, name='<string>')

Divide the given string into examples and intervening text, and return them as a list of alternating Examples and strings. Line numbers for the Examples are 0-based. The optional argument name is a name identifying this string, and is only used for error messages.

26.3.6.5. DocTestRunner objects

class doctest.DocTestRunner(checker=None, verbose=None, optionflags=0)

A processing class used to execute and verify the interactive examples in a DocTest.

The comparison between expected outputs and actual outputs is done by an OutputChecker. This comparison may be customized with a number of option flags; see section Option Flags for more information. If the option flags are insufficient, then the comparison may also be customized by passing a subclass of OutputChecker to the constructor.

The test runner’s display output can be controlled in two ways. First, an output function can be passed to TestRunner.run(); this function will be called with strings that should be displayed. It defaults to sys.stdout.write. If capturing the output is not sufficient, then the display output can be also customized by subclassing DocTestRunner, and overriding the methods report_start(), report_success(), report_unexpected_exception(), and report_failure().

The optional keyword argument checker specifies the OutputChecker object (or drop-in replacement) that should be used to compare the expected outputs to the actual outputs of doctest examples.

The optional keyword argument verbose controls the DocTestRunner’s verbosity. If verbose is True, then information is printed about each example, as it is run. If verbose is False, then only failures are printed. If verbose is unspecified, or None, then verbose output is used iff the command-line switch -v is used.

The optional keyword argument optionflags can be used to control how the test runner compares expected output to actual output, and how it displays failures. For more information, see section Option Flags.

DocTestParser defines the following methods:

report_start(out, test, example)

Report that the test runner is about to process the given example. This method is provided to allow subclasses of DocTestRunner to customize their output; it should not be called directly.

example is the example about to be processed. test is the test containing example. out is the output function that was passed to DocTestRunner.run().

report_success(out, test, example, got)

Report that the given example ran successfully. This method is provided to allow subclasses of DocTestRunner to customize their output; it should not be called directly.

example is the example about to be processed. got is the actual output from the example. test is the test containing example. out is the output function that was passed to DocTestRunner.run().

report_failure(out, test, example, got)

Report that the given example failed. This method is provided to allow subclasses of DocTestRunner to customize their output; it should not be called directly.

example is the example about to be processed. got is the actual output from the example. test is the test containing example. out is the output function that was passed to DocTestRunner.run().

report_unexpected_exception(out, test, example, exc_info)

Report that the given example raised an unexpected exception. This method is provided to allow subclasses of DocTestRunner to customize their output; it should not be called directly.

example is the example about to be processed. exc_info is a tuple containing information about the unexpected exception (as returned by sys.exc_info()). test is the test containing example. out is the output function that was passed to DocTestRunner.run().

run(test, compileflags=None, out=None, clear_globs=True)

Run the examples in test (a DocTest object), and display the results using the writer function out.

The examples are run in the namespace test.globs. If clear_globs is true (the default), then this namespace will be cleared after the test runs, to help with garbage collection. If you would like to examine the namespace after the test completes, then use clear_globs=False.

compileflags gives the set of flags that should be used by the Python compiler when running the examples. If not specified, then it will default to the set of future-import flags that apply to globs.

The output of each example is checked using the DocTestRunner’s output checker, and the results are formatted by the DocTestRunner.report_*() methods.

summarize(verbose=None)

Print a summary of all the test cases that have been run by this DocTestRunner, and return a named tuple TestResults(failed, attempted).

The optional verbose argument controls how detailed the summary is. If the verbosity is not specified, then the DocTestRunner’s verbosity is used.

26.3.6.6. OutputChecker objects

class doctest.OutputChecker

A class used to check the whether the actual output from a doctest example matches the expected output. OutputChecker defines two methods: check_output(), which compares a given pair of outputs, and returns true if they match; and output_difference(), which returns a string describing the differences between two outputs.

OutputChecker defines the following methods:

check_output(want, got, optionflags)

Return True iff the actual output from an example (got) matches the expected output (want). These strings are always considered to match if they are identical; but depending on what option flags the test runner is using, several non-exact match types are also possible. See section Option Flags for more information about option flags.

output_difference(example, got, optionflags)

Return a string describing the differences between the expected output for a given example (example) and the actual output (got). optionflags is the set of option flags used to compare want and got.

26.3.7. Debugging

Doctest provides several mechanisms for debugging doctest examples:

Several functions convert doctests to executable Python programs, which can be run under the Python debugger, pdb.

The DebugRunner class is a subclass of DocTestRunner that raises an exception for the first failing example, containing information about that example. This information can be used to perform post-mortem debugging on the example.

The unittest cases generated by DocTestSuite() support the debug() method defined by unittest.TestCase.

You can add a call to pdb.set_trace() in a doctest example, and you’ll drop into the Python debugger when that line is executed. Then you can inspect current values of variables, and so on. For example, suppose a.py contains just this module docstring:

"""
>>> def f(x):
...     g(x*2)
>>> def g(x):
...     print(x+3)
...     import pdb; pdb.set_trace()
>>> f(3)
9
"""

Then an interactive Python session may look like this:

>>> import a, doctest
>>> doctest.testmod(a)
--Return--
> <doctest a[1]>(3)g()->None
-> import pdb; pdb.set_trace()
(Pdb) list
  1     def g(x):
  2         print(x+3)
  3  ->     import pdb; pdb.set_trace()
[EOF]
(Pdb) p x
6
(Pdb) step
--Return--
> <doctest a[0]>(2)f()->None
-> g(x*2)
(Pdb) list
  1     def f(x):
  2  ->     g(x*2)
[EOF]
(Pdb) p x
3
(Pdb) step
--Return--
> <doctest a[2]>(1)?()->None
-> f(3)
(Pdb) cont
(0, 3)
>>>

Functions that convert doctests to Python code, and possibly run the synthesized code under the debugger:

doctest.script_from_examples(s)

Convert text with examples to a script.

Argument s is a string containing doctest examples. The string is converted to a Python script, where doctest examples in s are converted to regular code, and everything else is converted to Python comments. The generated script is returned as a string. For example,

import doctest
print(doctest.script_from_examples(r"""
    Set x and y to 1 and 2.
    >>> x, y = 1, 2

    Print their sum:
    >>> print(x+y)
    3
"""))

displays:

# Set x and y to 1 and 2.
x, y = 1, 2
#
# Print their sum:
print(x+y)
# Expected:
## 3

This function is used internally by other functions (see below), but can also be useful when you want to transform an interactive Python session into a Python script.

doctest.testsource(module, name)

Convert the doctest for an object to a script.

Argument module is a module object, or dotted name of a module, containing the object whose doctests are of interest. Argument name is the name (within the module) of the object with the doctests of interest. The result is a string, containing the object’s docstring converted to a Python script, as described for script_from_examples() above. For example, if module a.py contains a top-level function f(), then

import a, doctest
print(doctest.testsource(a, "a.f"))

prints a script version of function f()”s docstring, with doctests converted to code, and the rest placed in comments.

doctest.debug(module, name, pm=False)

Debug the doctests for an object.

The module and name arguments are the same as for function testsource() above. The synthesized Python script for the named object’s docstring is written to a temporary file, and then that file is run under the control of the Python debugger, pdb.

A shallow copy of module.__dict__ is used for both local and global execution context.

Optional argument pm controls whether post-mortem debugging is used. If pm has a true value, the script file is run directly, and the debugger gets involved only if the script terminates via raising an unhandled exception. If it does, then post-mortem debugging is invoked, via pdb.post_mortem(), passing the traceback object from the unhandled exception. If pm is not specified, or is false, the script is run under the debugger from the start, via passing an appropriate exec() call to pdb.run().

doctest.debug_src(src, pm=False, globs=None)

Debug the doctests in a string.

This is like function debug() above, except that a string containing doctest examples is specified directly, via the src argument.

Optional argument pm has the same meaning as in function debug() above.

Optional argument globs gives a dictionary to use as both local and global execution context. If not specified, or None, an empty dictionary is used. If specified, a shallow copy of the dictionary is used.

The DebugRunner class, and the special exceptions it may raise, are of most interest to testing framework authors, and will only be sketched here. See the source code, and especially DebugRunner’s docstring (which is a doctest!) for more details:

class doctest.DebugRunner(checker=None, verbose=None, optionflags=0)

A subclass of DocTestRunner that raises an exception as soon as a failure is encountered. If an unexpected exception occurs, an UnexpectedException exception is raised, containing the test, the example, and the original exception. If the output doesn’t match, then a DocTestFailure exception is raised, containing the test, the example, and the actual output.

For information about the constructor parameters and methods, see the documentation for DocTestRunner in section Advanced API.

There are two exceptions that may be raised by DebugRunner instances:

exception doctest.DocTestFailure(test, example, got)

An exception raised by DocTestRunner to signal that a doctest example’s actual output did not match its expected output. The constructor arguments are used to initialize the attributes of the same names.

DocTestFailure defines the following attributes:

DocTestFailure.test

The DocTest object that was being run when the example failed.

DocTestFailure.example

The Example that failed.

DocTestFailure.got

The example’s actual output.

exception doctest.UnexpectedException(test, example, exc_info)

An exception raised by DocTestRunner to signal that a doctest example raised an unexpected exception. The constructor arguments are used to initialize the attributes of the same names.

UnexpectedException defines the following attributes:

UnexpectedException.test

The DocTest object that was being run when the example failed.

UnexpectedException.example

The Example that failed.

UnexpectedException.exc_info

A tuple containing information about the unexpected exception, as returned by sys.exc_info().

26.3.8. Soapbox

As mentioned in the introduction, doctest has grown to have three primary uses:

Checking examples in docstrings.

Regression testing.

Executable documentation / literate testing.

These uses have different requirements, and it is important to distinguish them. In particular, filling your docstrings with obscure test cases makes for bad documentation.

When writing a docstring, choose docstring examples with care. There’s an art to this that needs to be learned—it may not be natural at first. Examples should add genuine value to the documentation. A good example can often be worth many words. If done with care, the examples will be invaluable for your users, and will pay back the time it takes to collect them many times over as the years go by and things change. I’m still amazed at how often one of my doctest examples stops working after a « harmless » change.

Doctest also makes an excellent tool for regression testing, especially if you don’t skimp on explanatory text. By interleaving prose and examples, it becomes much easier to keep track of what’s actually being tested, and why. When a test fails, good prose can make it much easier to figure out what the problem is, and how it should be fixed. It’s true that you could write extensive comments in code-based testing, but few programmers do. Many have found that using doctest approaches instead leads to much clearer tests. Perhaps this is simply because doctest makes writing prose a little easier than writing code, while writing comments in code is a little harder. I think it goes deeper than just that: the natural attitude when writing a doctest-based test is that you want to explain the fine points of your software, and illustrate them with examples. This in turn naturally leads to test files that start with the simplest features, and logically progress to complications and edge cases. A coherent narrative is the result, instead of a collection of isolated functions that test isolated bits of functionality seemingly at random. It’s a different attitude, and produces different results, blurring the distinction between testing and explaining.

Regression testing is best confined to dedicated objects or files. There are several options for organizing tests:

Write text files containing test cases as interactive examples, and test the files using testfile() or DocFileSuite(). This is recommended, although is easiest to do for new projects, designed from the start to use doctest.

Define functions named _regrtest_topic that consist of single docstrings, containing test cases for the named topics. These functions can be included in the same file as the module, or separated out into a separate test file.

Define a __test__ dictionary mapping from regression test topics to docstrings containing test cases.

When you have placed your tests in a module, the module can itself be the test runner. When a test fails, you can arrange for your test runner to re-run only the failing doctest while you debug the problem. Here is a minimal example of such a test runner:

if __name__ == '__main__':
    import doctest
    flags = doctest.REPORT_NDIFF|doctest.FAIL_FAST
    if len(sys.argv) > 1:
        name = sys.argv[1]
        if name in globals():
            obj = globals()[name]
        else:
            obj = __test__[name]
        doctest.run_docstring_examples(obj, globals(), name=name,
                                       optionflags=flags)
    else:
        fail, total = doctest.testmod(optionflags=flags)
        print("{} failures out of {} tests".format(fail, total))

Notes

1

Examples containing both expected output and an exception are not supported. Trying to guess where one ends and the other begins is too error-prone, and that also makes for a confusing test.

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26.4. unittest — Framework de tests unitaires

Code source : Lib/unittest/__init__.py [https://github.com/python/cpython/tree/3.6/Lib/unittest/__init__.py]

(Si vous êtes déjà familier des concepts de base concernant les tests, vous pouvez souhaiter passer à la liste des méthodes.)

Le cadre applicatif de tests unitaires unittest était au départ inspiré par JUnit et ressemble aux principaux frameworks de tests unitaires des autres langages. Il gère l’automatisation des tests, le partage de code pour la mise en place et la finalisation des tests, l’agrégation de tests en collections, et l’indépendance des tests par rapport au framework utilisé.

Pour y parvenir, unittest gère quelques concepts importants avec une approche orientée objet :

aménagement de test (fixture)

Un aménagement de test (*fixture*) désigne la préparation nécessaire au déroulement d’un ou plusieurs tests, et toutes les actions de nettoyage associées. Cela peut concerner, par exemple, la création de bases de données temporaires ou mandataires, de répertoires, ou le démarrage d’un processus serveur.

scénario de test

Un scénario de test est l’élément de base des tests. Il attend une réponse spécifique pour un ensemble particulier d’entrées. unittest fournit une classe de base, TestCase, qui peut être utilisée pour créer de nouveaux scénarios de test.

suite de tests

Une suite de tests est une collection de scénarios de test, de suites de tests ou les deux. Cela sert à regrouper les tests qui devraient être exécutés ensemble.

lanceur de tests

Un lanceur de tests est un composant qui orchestre l’exécution des tests et fournit le résultat pour l’utilisateur. Le lanceur peut utiliser une interface graphique, une interface textuelle, ou renvoie une valeur spéciale pour indiquer les résultats de l’exécution des tests.

Voir aussi

Module doctest

Un autre module de test adoptant une approche très différente.

Simple Smalltalk Testing: With Patterns [https://web.archive.org/web/20150315073817/http://www.xprogramming.com/testfram.htm]

Le papier originel de Kent Beck sur les frameworks de test utilisant le modèle sur lequel s’appuie unittest.

Nose [https://nose.readthedocs.io/] and pytest [https://docs.pytest.org/]

Des frameworks tierces de tests unitaires avec une syntaxe allégée pour l’écriture des tests. Par exemple, assert func(10) == 42.

The Python Testing Tools Taxonomy [https://wiki.python.org/moin/PythonTestingToolsTaxonomy]

Une liste étendue des outils de test pour Python comprenant des frameworks de tests fonctionnels et des bibliothèques d’objets simulés (mocks).

Testing in Python Mailing List [http://lists.idyll.org/listinfo/testing-in-python]

Un groupe de discussion dédié aux tests, et outils de test, en Python.

Le script Tools/unittestgui/unittestgui.py dans la distribution source de Python est un outil avec une interface graphique pour découvrir et exécuter des tests. Il est principalement conçu pour être facile d’emploi pour les débutants en matière de tests unitaires. Pour les environnements de production il est recommandé que les tests soient pilotés par un système d’intégration continue comme Buildbot [https://buildbot.net/], Jenkins [https://jenkins.io/] ou Hudson [http://hudson-ci.org/].

26.4.1. Exemple basique

Le module unittest fournit un riche ensemble d’outils pour construire et lancer des tests. Cette section montre qu’une petite partie des outils suffit pour satisfaire les besoins de la plupart des utilisateurs.

Voici un court script pour tester trois méthodes de string :

import unittest

class TestStringMethods(unittest.TestCase):

    def test_upper(self):
        self.assertEqual('foo'.upper(), 'FOO')

    def test_isupper(self):
        self.assertTrue('FOO'.isupper())
        self.assertFalse('Foo'.isupper())

    def test_split(self):
        s = 'hello world'
        self.assertEqual(s.split(), ['hello', 'world'])
        # check that s.split fails when the separator is not a string
        with self.assertRaises(TypeError):
            s.split(2)

if __name__ == '__main__':
    unittest.main()

Un scénario de test est créé comme classe-fille de unittest.TestCase. Les trois tests individuels sont définis par des méthodes dont les noms commencent par les lettres test. Cette convention de nommage signale au lanceur de tests quelles méthodes sont des tests.

Le cœur de chaque test est un appel à assertEqual() pour vérifier un résultat attendu ; assertTrue() ou assertFalse() pour vérifier une condition ; ou assertRaises() pour vérifier qu’une exception particulière est levée. Ces méthodes sont utilisées à la place du mot-clé assert pour que le lanceur de tests puisse récupérer les résultats de tous les tests et produire un rapport.

Les méthodes setUp() et tearDown() vous autorisent à définir des instructions qui seront exécutées avant et après chaque méthode test. Elles sont davantage détaillées dans la section Organiser le code de test.

Le bloc final montre une manière simple de lancer les tests. unittest.main() fournit une interface en ligne de commande pour le script de test. Lorsqu’il est lancé en ligne de commande, le script ci-dessus produit une sortie qui ressemble à ceci :

...
----------------------------------------------------------------------
Ran 3 tests in 0.000s

OK

Passer l’option -v à votre script de test informera unittest.main() qu’il doit fournir un niveau plus important de détails, et produit la sortie suivante :

test_isupper (__main__.TestStringMethods) ... ok
test_split (__main__.TestStringMethods) ... ok
test_upper (__main__.TestStringMethods) ... ok

----------------------------------------------------------------------
Ran 3 tests in 0.001s

OK

Les exemples ci-dessus montrent les fonctionnalités d”unittest les plus communément utilisées et qui sont suffisantes pour couvrir les besoins courants en matière de test. Le reste de la documentation explore l’ensemble complet des fonctionnalités depuis les premiers principes.

26.4.2. Interface en ligne de commande

Le module unittest est utilisable depuis la ligne de commande pour exécuter des tests à partir de modules, de classes ou même de méthodes de test individuelles :

python -m unittest test_module1 test_module2
python -m unittest test_module.TestClass
python -m unittest test_module.TestClass.test_method

La commande accepte en argument une liste de n’importe quelle combinaison de noms de modules et de noms de classes ou de méthodes entièrement qualifiés.

Les modules de test peuvent également être spécifiés par un chemin de fichier :

python -m unittest tests/test_something.py

Cette fonctionnalité permet d’utiliser la complétion de l’interpréteur de commandes système (le shell) pour spécifier le module de test. Le chemin est converti en nom de module en supprimant le .py et en convertissant les séparateurs de chemin en “.”. Si vous voulez exécuter un fichier test qui n’est pas importable en tant que module, exécutez directement le fichier.

Pour obtenir plus de détails lors de l’exécution utilisez l’option -v (plus de verbosité) :

python -m unittest -v test_module

Quand la commande est exécutée sans arguments Découverte des tests est lancée :

python -m unittest

Pour afficher la liste de toutes les options de la commande utilisez l’option -h :

python -m unittest -h

Modifié dans la version 3.2: Dans les versions antérieures, il était seulement possible d’exécuter des méthodes de test individuelles et non des modules ou des classes.

26.4.2.1. Options de la ligne de commande

Le programme : unittest gère ces options de la ligne de commande :

-b, --buffer

Les flux de sortie et d’erreur standards sont mis en mémoire tampon pendant l’exécution des tests. L’affichage produit par un test réussi n’est pas pris en compte. Les sorties d’affichages d’un test en échec ou en erreur sont conservés et ajoutés aux messages d’erreur.

-c, --catch

Utiliser Control-C pendant l’exécution des tests attend que le test en cours se termine, puis affiche tous les résultats obtenus jusqu’ici. Une seconde utilisation de Control-C provoque l’exception normale KeyboardInterrupt.

Voir Signal Handling pour les fonctions qui utilisent cette fonctionnalité.

-f, --failfast

Arrête l’exécution des tests lors du premier cas d’erreur ou d’échec.

--locals

Affiche les variables locales dans les traces d’appels.

Nouveau dans la version 3.2: Les options de ligne de commande -b, -c et -f ont été ajoutées.

Nouveau dans la version 3.5: Ajout de l’option de ligne de commande --locals.

La ligne de commande peut également être utilisée pour découvrir les tests, pour exécuter tous les tests dans un projet ou juste un sous-ensemble.

26.4.3. Découverte des tests

Nouveau dans la version 3.2.

Unittest prend en charge une découverte simple des tests. Afin d’être compatible avec le système de découverte de tests, tous les fichiers de test doivent être des modules ou des paquets (incluant des paquets-espaces de nommage) importables du répertoire du projet (cela signifie que leurs noms doivent être des identifiants valables).

La découverte de tests est implémentée dans TestLoader.discover(), mais peut également être utilisée depuis la ligne de commande. Par exemple :

cd project_directory
python -m unittest discover

Note

Comme raccourci, python -m unittest est l’équivalent de python -m unittest discover. Pour passer des arguments au système de découverte des tests, la sous-commande discover doit être utilisée explicitement.

La sous-commande discover a les options suivantes  :

-v, --verbose

Affichage plus détaillé

-s, --start-directory directory

Répertoire racine pour démarrer la découverte (. par défaut).

-p, --pattern pattern

Motif de détection des fichiers de test (test*.py par défaut)

-t, --top-level-directory directory

Dossier du premier niveau du projet (Par défaut le dossier de départ)

Les options -s, -p et -t peuvent être passées en arguments positionnels dans cet ordre. Les deux lignes de commande suivantes sont équivalentes :

python -m unittest discover -s project_directory -p "*_test.py"
python -m unittest discover project_directory "*_test.py"

Il est aussi possible de passer un nom de paquet plutôt qu’un chemin, par exemple monprojet.souspaquet.test, comme répertoire racine. Le nom du paquet fourni est alors importé et son emplacement sur le système de fichiers est utilisé comme répertoire racine.

Prudence

Le mécanisme de découverte charge les tests en les important. Une fois que le système a trouvé tous les fichiers de tests du répertoire de démarrage spécifié, il transforme les chemins en noms de paquets à importer. Par exemple truc/bidule/machin.py est importé sous truc.bidule.machin.

Si un paquet est installé globalement et que le mécanisme de découverte de tests est effectué sur une copie différente du paquet, l’importation peut se produire à partir du mauvais endroit. Si cela arrive, le système émet un avertissement et se termine.

Si vous donnez le répertoire racine sous la forme d’un nom de paquet plutôt que d’un chemin d’accès à un répertoire, alors Python suppose que l’emplacement à partir duquel il importe est l’emplacement que vous voulez, vous ne verrez donc pas l’avertissement.

Les modules de test et les paquets peuvent adapter le chargement et la découverte des tests en utilisant le protocole load_tests protocol.

Modifié dans la version 3.4: La découverte de tests prend en charge les paquets-espaces de nommage.

26.4.4. Organiser le code de test

Les éléments de base des tests unitaires sont les scénarios de tests (test cases en anglais) — Des scénarios uniques qui sont mis en place et exécutés pour vérifier qu’ils sont corrects. Dans unittest, les scénarios de test sont représentés par des instances de unittest.TestCase. Pour créer vos propres scénarios de test, vous devez écrire des sous-classes de TestCase ou utiliser FunctionTestCase.

Le code de test d’une instance de TestCase doit être entièrement autonome, de sorte qu’il puisse être exécuté soit de manière isolée, soit en combinaison arbitraire avec un nombre quelconque d’autres scénarios de test.

La sous-classe TestCase la plus simple va tout simplement implémenter une méthode de test (c’est-à-dire une méthode dont le nom commence par test) afin d’exécuter un code de test spécifique :

import unittest

class DefaultWidgetSizeTestCase(unittest.TestCase):
    def test_default_widget_size(self):
        widget = Widget('The widget')
        self.assertEqual(widget.size(), (50, 50))

Notez que pour tester quelque chose, on utilise l’une des méthodes assert*() fournies par la classe de base TestCase. Si le test échoue, une exception est levée avec un message explicatif, et unittest identifie ce scénario de test comme un échec. Toute autre exception est traitée comme une erreur.

Les tests peuvent être nombreux et leur mise en place peut être répétitive. Heureusement, on peut factoriser le code de mise en place en implémentant une méthode appelée setUp(), que le système de test appelle automatiquement pour chaque test exécuté :

import unittest

class WidgetTestCase(unittest.TestCase):
    def setUp(self):
        self.widget = Widget('The widget')

    def test_default_widget_size(self):
        self.assertEqual(self.widget.size(), (50,50),
                         'incorrect default size')

    def test_widget_resize(self):
        self.widget.resize(100,150)
        self.assertEqual(self.widget.size(), (100,150),
                         'wrong size after resize')

Note

L’ordre dans lequel les différents tests sont exécutés est déterminé en classant les noms des méthodes de test en fonction de la relation d’ordre des chaines de caractères .

Si la méthode setUp() lève une exception pendant l’exécution du test, le système considère que le test a subi une erreur, et la méthode test n’est pas exécutée.

De même, on peut fournir une méthode tearDown() qui nettoie après l’exécution de la méthode de test :

import unittest

class WidgetTestCase(unittest.TestCase):
    def setUp(self):
        self.widget = Widget('The widget')

    def tearDown(self):
        self.widget.dispose()

Si setUp() a réussi, tearDown() est exécutée, que la méthode de test ait réussi ou non.

Such a working environment for the testing code is called a test fixture. A new TestCase instance is created as a unique test fixture used to execute each individual test method. Thus setUp(), tearDown(), and __init__() will be called once per test.

Il est recommandé d’utiliser TestCase pour regrouper les tests en fonction des fonctionnalités qu’ils testent. unittest fournit un mécanisme pour cela : la suite de tests, représentée par TestSuite du module unittest. Dans la plupart des cas, appeler unittest.main() fait correctement les choses et trouve tous les scénarios de test du module pour vous et les exécute.

Cependant, si vous voulez personnaliser la construction de votre suite de tests, vous pouvez le faire vous-même :

def suite():
    suite = unittest.TestSuite()
    suite.addTest(WidgetTestCase('test_default_widget_size'))
    suite.addTest(WidgetTestCase('test_widget_resize'))
    return suite

if __name__ == '__main__':
    runner = unittest.TextTestRunner()
    runner.run(suite())

Vous pouvez placer les définitions des scénarios de test et des suites de test dans le même module que le code à tester (tel que composant.py), mais il y a plusieurs avantages à placer le code de test dans un module séparé, tel que test_composant.py :

Le module de test peut être exécuté indépendamment depuis la ligne de commande.

Le code de test est plus facilement séparable du code livré.

La tentation est moins grande de changer le code de test pour l’adapter au code qu’il teste sans avoir une bonne raison.

Le code de test doit être modifié beaucoup moins souvent que le code qu’il teste.

Le code testé peut être réusiné plus facilement.

Les tests pour les modules écrits en C doivent de toute façon être dans des modules séparés, alors pourquoi ne pas être cohérent ?

Si la stratégie de test change, il n’est pas nécessaire de changer le code source.

26.4.5. Réutilisation d’ancien code de test

Certains utilisateurs constatent qu’ils ont du code de test existant qu’ils souhaitent exécuter à partir de unittest, sans convertir chaque ancienne fonction de test en une sous-classe de TestCase.

Pour cette raison, unittest fournit une classe FunctionTestCase. Cette sous-classe de TestCase peut être utilisée pour encapsuler une fonction de test existante. Des fonctions de mise en place (setUp) et de démantèlement (tearDown) peuvent également être fournies.

Étant donnée la fonction de test suivante :

def testSomething():
    something = makeSomething()
    assert something.name is not None
    # ...

on peut créer une instance de scénario de test équivalente, avec des méthodes optionnelles de mise en place et de démantèlement :

testcase = unittest.FunctionTestCase(testSomething,
                                     setUp=makeSomethingDB,
                                     tearDown=deleteSomethingDB)

Note

Même si la classe FunctionTestCase peut être utilisée pour convertir rapidement une base de test existante vers un système basé sur unittest, cette approche n’est pas recommandée. Prendre le temps de bien configurer les sous-classes de TestCase simplifiera considérablement les futurs réusinages des tests.

Dans certains cas, les tests déjà existants ont pu être écrits avec le module doctest. Dans ce cas, doctest fournit une classe DocTestSuite qui peut construire automatiquement des instances de la classe unittest.TestSuite depuis des tests basés sur le module doctest.

26.4.6. Ignorer des tests et des erreurs prévisibles

Nouveau dans la version 3.1.

Unittest permet d’ignorer des méthodes de test individuelles et même des classes entières de tests. De plus, il prend en charge le marquage d’un test comme étant une « erreur prévue ». Un test qui est cassé et qui échoue, mais qui ne doit pas être considéré comme un échec dans la classe TestResult.

Ignorer un test consiste à utiliser le décorateur skip() ou une de ses variantes conditionnelles.

Un exemple de tests à ignorer :

class MyTestCase(unittest.TestCase):

    @unittest.skip("demonstrating skipping")
    def test_nothing(self):
        self.fail("shouldn't happen")

    @unittest.skipIf(mylib.__version__ < (1, 3),
                     "not supported in this library version")
    def test_format(self):
        # Tests that work for only a certain version of the library.
        pass

    @unittest.skipUnless(sys.platform.startswith("win"), "requires Windows")
    def test_windows_support(self):
        # windows specific testing code
        pass

Ceci est le résultat de l’exécution de l’exemple ci-dessus en mode verbeux :

test_format (__main__.MyTestCase) ... skipped 'not supported in this library version'
test_nothing (__main__.MyTestCase) ... skipped 'demonstrating skipping'
test_windows_support (__main__.MyTestCase) ... skipped 'requires Windows'

----------------------------------------------------------------------
Ran 3 tests in 0.005s

OK (skipped=3)

Les classes peuvent être ignorées tout comme les méthodes :

@unittest.skip("showing class skipping")
class MySkippedTestCase(unittest.TestCase):
    def test_not_run(self):
        pass

La méthode TestCase.setUp() permet également d’ignorer le test. Ceci est utile lorsqu’une ressource qui doit être configurée n’est pas disponible.

Les erreurs prévisibles utilisent le décorateur expectedFailure()

class ExpectedFailureTestCase(unittest.TestCase):
    @unittest.expectedFailure
    def test_fail(self):
        self.assertEqual(1, 0, "broken")

Il est facile de faire ses propres décorateurs en créant un décorateur qui appelle skip() sur le test que vous voulez ignorer. Par exemple, ce décorateur ignore le test à moins que l’objet passé ne possède un certain attribut :

def skipUnlessHasattr(obj, attr):
    if hasattr(obj, attr):
        return lambda func: func
    return unittest.skip("{!r} doesn't have {!r}".format(obj, attr))

Les décorateurs suivants implémentent le système d’omission des tests et les erreurs prévisibles  :

@unittest.skip(reason)

Ignore sans condition le test décoré. La raison doit décrire la raison pour laquelle le test est omis.

@unittest.skipIf(condition, reason)

Ignore le test décoré si la condition est vraie.

@unittest.skipUnless(condition, reason)

Ignore le test décoré sauf si la condition est vraie.

@unittest.expectedFailure

Mark the test as an expected failure. If the test fails when run, the test is not counted as a failure.

exception unittest.SkipTest(reason)

Cette exception est levée pour ignorer un test.

Habituellement, on utilise TestCase.skipTest() ou l’un des décorateurs d’omission au lieu de le lever une exception directement.

Les tests ignorés ne lancent ni setUp() ni tearDown(). Les classes ignorées ne lancent ni setUpClass() ni tearDownClass(). Les modules sautés n’ont pas setUpModule() ou tearDownModule() d’exécutés.

26.4.7. Distinguer les itérations de test à l’aide de sous-tests

Nouveau dans la version 3.4.

When there are very small differences among your tests, for instance some parameters, unittest allows you to distinguish them inside the body of a test method using the subTest() context manager.

Par exemple, le test suivant :

class NumbersTest(unittest.TestCase):

    def test_even(self):
        """
        Test that numbers between 0 and 5 are all even.
        """
        for i in range(0, 6):
            with self.subTest(i=i):
                self.assertEqual(i % 2, 0)

produit le résultat suivant :

======================================================================
FAIL: test_even (__main__.NumbersTest) (i=1)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "subtests.py", line 32, in test_even
    self.assertEqual(i % 2, 0)
AssertionError: 1 != 0

======================================================================
FAIL: test_even (__main__.NumbersTest) (i=3)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "subtests.py", line 32, in test_even
    self.assertEqual(i % 2, 0)
AssertionError: 1 != 0

======================================================================
FAIL: test_even (__main__.NumbersTest) (i=5)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "subtests.py", line 32, in test_even
    self.assertEqual(i % 2, 0)
AssertionError: 1 != 0

Sans l’utilisation d’un sous-test, l’exécution se termine après le premier échec, et l’erreur est moins facile à diagnostiquer car la valeur de i ne s’affiche pas :

======================================================================
FAIL: test_even (__main__.NumbersTest)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "subtests.py", line 32, in test_even
    self.assertEqual(i % 2, 0)
AssertionError: 1 != 0

26.4.8. Classes et fonctions

Cette section décrit en détail l’API de unittest.

26.4.8.1. Scénarios de tests

class unittest.TestCase(methodName='runTest')

Les instances de la classe TestCase représentent des tests logiques unitaires dans l’univers unittest. Cette classe est conçue pour être utilisée comme classe de base. Les scénarios de tests sont à implémenter en héritant de cette classe. La classe implémente l’interface nécessaire au lanceur de tests pour lui permettre de les exécuter ainsi que les méthodes que le code de test peut utiliser pour vérifier et signaler les différents types d’erreurs.

Chaque instance de la classe TestCase n’exécute qu’une seule méthode de base : la méthode nommée methodName . Dans la plupart des utilisations de la classe TestCase, vous n’avez pas à changer le nom de la méthode, ni à réimplémenter la méthode runTest().

Modifié dans la version 3.2: La classe TestCase peut désormais être utilisée sans passer de paramètre methodName. Cela facilite l’usage de TestCase dans l’interpréteur interactif.

Les instances de la classe TestCase fournissent trois groupes de méthodes : un groupe utilisé pour exécuter le test, un autre utilisé par l’implémentation du test pour vérifier les conditions et signaler les échecs, et quelques méthodes de recherche permettant de recueillir des informations sur le test lui-même.

Les méthodes du premier groupe (exécution du test) sont :

setUp()

Méthode appelée pour réaliser la mise en place du test. Elle est exécutée immédiatement avant l’appel de la méthode de test ; à l’exception de AssertionError ou SkipTest, toute exception levée par cette méthode est considérée comme une erreur et non pas comme un échec du test. L’implémentation par défaut ne fait rien.

tearDown()

Méthode appelée immédiatement après l’appel de la méthode de test et l’enregistrement du résultat. Elle est appelée même si la méthode de test a levé une exception. De fait, l’implémentation d’un sous-classes doit être fait avec précaution si vous vérifiez l’état interne de la classe. Toute exception, autre que AssertionError ou SkipTest, levée par cette méthode est considérée comme une erreur supplémentaire plutôt que comme un échec du test (augmentant ainsi le nombre total des erreurs signalées). Cette méthode est appelée uniquement si l’exécution de setUp() est réussie quel que soit le résultat de la méthode de test. L’implémentation par défaut ne fait rien.

setUpClass()

A class method called before tests in an individual class are run. setUpClass is called with the class as the only argument and must be decorated as a classmethod():

@classmethod
def setUpClass(cls):
    ...

Voir Class and Module Fixtures pour plus de détails.

Nouveau dans la version 3.2.

tearDownClass()

Méthode de classe appelée après l’exécution des tests de la classe en question. tearDownClass est appelée avec la classe comme seul argument et doit être décorée comme une classmethod() :

@classmethod
def tearDownClass(cls):
    ...

Voir Class and Module Fixtures pour plus de détails.

Nouveau dans la version 3.2.

run(result=None)

Exécute le test, en collectant le résultat dans l’objet TestResult passé comme result. Si result est omis ou vaut None, un objet temporaire de résultat est créé (en appelant la méthode defaultTestResult()) et utilisé. L’objet résultat est renvoyé à l’appelant de run().

Le même effet peut être obtenu en appelant simplement l’instance TestCase.

Modifié dans la version 3.3: Les versions précédentes de run ne renvoyaient pas le résultat. Pas plus que l’appel d’une instance.

skipTest(reason)

Appeler cette fonction pendant l’exécution d’une méthode de test ou de setUp() permet d’ignorer le test en cours. Voir Ignorer des tests et des erreurs prévisibles pour plus d’informations.

Nouveau dans la version 3.1.

subTest(msg=None, **params)

Renvoie un gestionnaire de contexte qui exécute le bloc de code du contexte comme un sous-test. msg et params sont des valeurs optionnelles et arbitraires qui sont affichées chaque fois qu’un sous-test échoue, permettant de les identifier clairement.

Un scénario de test peut contenir un nombre quelconque de déclarations de sous-test, et elles peuvent être imbriquées librement.

Voir Distinguer les itérations de test à l’aide de sous-tests pour plus d’informations.

Nouveau dans la version 3.4.

debug()

Lance le test sans collecter le résultat. Ceci permet aux exceptions levées par le test d’être propagées à l’appelant, et donc peut être utilisé pour exécuter des tests sous un débogueur.

La classe TestCase fournit plusieurs méthodes d’assertion pour vérifier et signaler les échecs. Le tableau suivant énumère les méthodes les plus couramment utilisées (voir les tableaux ci-dessous pour plus de méthodes d’assertion) :

Méthode

Vérifie que

Disponible en

assertEqual(a, b)

a == b

assertNotEqual(a, b)

a != b

assertTrue(x)

bool(x) is True

assertFalse(x)

bool(x) is False

assertIs(a, b)

a is b

3.1

assertIsNot(a, b)

a is not b

3.1

assertIsNone(x)

x is None

3.1

assertIsNotNone(x)

x is not None

3.1

assertIn(a, b)

a in b

3.1

assertNotIn(a, b)

a not in b

3.1

assertIsInstance(a, b)

isinstance(a, b)

3.2

assertNotIsInstance(a, b)

not isinstance(a, b)

3.2

Toutes les méthodes assert prennent en charge un argument msg qui, s’il est spécifié, est utilisé comme message d’erreur en cas d’échec (voir aussi longMessage). Notez que l’argument mot-clé msg peut être passé à assertRaises(), assertRaisesRegex(), assertWarns(), assertWarnsRegex(), seulement quand elles sont utilisées comme gestionnaire de contexte.

assertEqual(first, second, msg=None)

Vérifie que first et second sont égaux. Si les valeurs ne sont pas égales, le test échouera.

En outre, si first et second ont exactement le même type et sont de type liste, tuple, dict, set, frozenset ou str ou tout autre type de sous classe enregistrée dans addTypeEqualityFunc(). La fonction égalité spécifique au type sera appelée pour générer une erreur plus utile (voir aussi liste des méthodes spécifiques de type).

Modifié dans la version 3.1: Ajout de l’appel automatique de la fonction d’égalité spécifique au type.

Modifié dans la version 3.2: Ajout de assertMultiLineEqual() comme fonction d’égalité de type par défaut pour comparer les chaînes.

assertNotEqual(first, second, msg=None)

Vérifie que first et second ne sont pas égaux. Si les valeurs sont égales, le test échouera.

assertTrue(expr, msg=None)

assertFalse(expr, msg=None)

Vérifie que expr est vraie (ou fausse).

Notez que cela revient à utiliser bool(expr) is True et non à expr is True (utilisez assertIs(expr, True) pour cette dernière). Cette méthode doit également être évitée lorsque des méthodes plus spécifiques sont disponibles (par exemple assertEqual(a, b) au lieu de assertTrue(a == b)), car elles fournissent un meilleur message d’erreur en cas d” échec.

assertIs(first, second, msg=None)

assertIsNot(first, second, msg=None)

Vérifie que first et second évaluent (ou n’évaluent pas) le même objet.

Nouveau dans la version 3.1.

assertIsNone(expr, msg=None)

assertIsNotNone(expr, msg=None)

Vérifie que expr est (ou n’est pas) la valeur None.

Nouveau dans la version 3.1.

assertIn(first, second, msg=None)

assertNotIn(first, second, msg=None)

Vérifie que first est (ou n’est pas) dans second.

Nouveau dans la version 3.1.

assertIsInstance(obj, cls, msg=None)

assertNotIsInstance(obj, cls, msg=None)

Vérifie que obj est (ou n’est pas) une instance de cls (Ce qui peut être une classe ou un tuple de classes, comme utilisée par isinstance()). Pour vérifier le type exact, utilisez assertIs(type(obj), cls).

Nouveau dans la version 3.2.

Il est également possible de vérifier la production des exceptions, des avertissements et des messages de journaux à l’aide des méthodes suivantes :

Méthode

Vérifie que

Disponible en

assertRaises(exc, fun, *args, **kwds)

fun(*args, **kwds) lève bien l’exception exc

assertRaisesRegex(exc, r, fun, *args, **kwds)

fun(*args, **kwds) lève bien l’exception exc et que le message correspond au motif de l’expression régulière r

3.1

assertWarns(warn, fun, *args, **kwds)

fun(*args, **kwds) lève bien l’avertissement warn

3.2

assertWarnsRegex(warn, r, fun, *args, **kwds)

fun(*args, **kwds) lève bien l’avertissement warn et que le message correspond au motif de l’expression régulière r

3.2

assertLogs(logger, level)

Le bloc with écrit dans le logger avec un niveau minimum égal à level

3.4

assertRaises(exception, callable, *args, **kwds)

assertRaises(exception, *, msg=None)

Vérifie qu’une exception est levée lorsque callable est appelé avec n’importe quel argument positionnel ou mot-clé qui est également passé à assertRaises(). Le test réussit si exception est levée, est en erreur si une autre exception est levée, ou en échec si aucune exception n’est levée. Pour capturer une exception d’un groupe d’exceptions, un couple contenant les classes d’exceptions peut être passé à exception.

Si seuls les arguments exception et éventuellement msg sont donnés, renvoie un gestionnaire de contexte pour que le code sous test puisse être écrit en ligne plutôt que comme une fonction :

with self.assertRaises(SomeException):
    do_something()

Lorsqu’il est utilisé comme gestionnaire de contexte, assertRaises() accepte l’argument de mot-clé supplémentaire msg.

Le gestionnaire de contexte enregistre l’exception capturée dans son attribut exception. Ceci est particulièrement utile si l’intention est d’effectuer des contrôles supplémentaires sur l’exception levée :

with self.assertRaises(SomeException) as cm:
    do_something()

the_exception = cm.exception
self.assertEqual(the_exception.error_code, 3)

Modifié dans la version 3.1: Ajout de la possibilité d’utiliser assertRaises() comme gestionnaire de contexte.

Modifié dans la version 3.2: Ajout de l’attribut exception.

Modifié dans la version 3.3: Ajout de l’argument msg comme mot-clé lorsqu’il est utilisé comme gestionnaire de contexte.

assertRaisesRegex(exception, regex, callable, *args, **kwds)

assertRaisesRegex(exception, regex, *, msg=None)

Comme assertRaises() mais vérifie aussi que regex correspond à la représentation de la chaîne de caractères de l’exception levée. regex peut être un objet d’expression rationnelle ou une chaîne contenant une expression rationnelle appropriée pour être utilisée par re.search(). Exemples :

self.assertRaisesRegex(ValueError, "invalid literal for.*XYZ'$",
                       int, 'XYZ')

ou :

with self.assertRaisesRegex(ValueError, 'literal'):
   int('XYZ')

Nouveau dans la version 3.1: under the name assertRaisesRegexp.

Modifié dans la version 3.2: Renommé en assertRaisesRegex().

Modifié dans la version 3.3: Ajout de l’argument msg comme mot-clé lorsqu’il est utilisé comme gestionnaire de contexte.

assertWarns(warning, callable, *args, **kwds)

assertWarns(warning, *, msg=None)

Test qu’un avertissement est déclenché lorsque callable est appelé avec n’importe quel argument positionnel ou mot-clé qui est également passé à assertWarns(). Le test passe si warning est déclenché et échoue s’il ne l’est pas. Toute exception est une erreur. Pour capturer un avertissement dans un ensemble d’avertissements, un couple contenant les classes d’avertissement peut être passé à warnings.

Si seuls les arguments * warning* et éventuellement msg sont donnés, renvoie un gestionnaire de contexte pour que le code testé puisse être écrit en ligne plutôt que comme une fonction :

with self.assertWarns(SomeWarning):
    do_something()

Lorsqu’il est utilisé comme gestionnaire de contexte, assertWarns() accepte l’argument de mot-clé supplémentaire msg.

Le gestionnaire de contexte stocke l’avertissement capturé dans son attribut warning, et la ligne source qui a déclenché les avertissements dans les attributs filename et lineno. Cette fonction peut être utile si l’intention est d’effectuer des contrôles supplémentaires sur l’avertissement capturé :

with self.assertWarns(SomeWarning) as cm:
    do_something()

self.assertIn('myfile.py', cm.filename)
self.assertEqual(320, cm.lineno)

Cette méthode fonctionne indépendamment des filtres d’avertissement en place lorsqu’elle est appelée.

Nouveau dans la version 3.2.

Modifié dans la version 3.3: Ajout de l’argument msg comme mot-clé lorsqu’il est utilisé comme gestionnaire de contexte.

assertWarnsRegex(warning, regex, callable, *args, **kwds)

assertWarnsRegex(warning, regex, *, msg=None)

Comme assertWarns() mais vérifie aussi qu’une regex corresponde au message de l’avertissement. regex peut être un objet d’expression régulière ou une chaîne contenant une expression régulière appropriée pour être utilisée par re.search(). Exemple :

self.assertWarnsRegex(DeprecationWarning,
                      r'legacy_function\(\) is deprecated',
                      legacy_function, 'XYZ')

ou :

with self.assertWarnsRegex(RuntimeWarning, 'unsafe frobnicating'):
    frobnicate('/etc/passwd')

Nouveau dans la version 3.2.

Modifié dans la version 3.3: Ajout de l’argument msg comme mot-clé lorsqu’il est utilisé comme gestionnaire de contexte.

assertLogs(logger=None, level=None)

Un gestionnaire de contexte pour tester qu’au moins un message est enregistré sur le logger ou un de ses enfants, avec au moins le niveau donné.

Si donné, logger doit être une classe logging.logger objet ou une classe str donnant le nom d’un journal. La valeur par défaut est le journal racine root, qui capture tous les messages.

S’il est donné, level doit être soit un entier, soit son équivalent sous forme de chaîne (par exemple "ERROR" ou logging.ERROR). La valeur par défaut est logging.INFO.

Le test passe si au moins un message émis à l’intérieur du bloc with correspond aux conditions logger et level, sinon il échoue.

L’objet retourné par le gestionnaire de contexte est une aide à l’enregistrement qui garde la trace des messages de journal correspondants. Il a deux attributs  :

records

Une liste d’objets logging.LogRecord de messages de log correspondants.

output

Une liste d’objets str avec la sortie formatée des messages correspondants.

Exemple :

with self.assertLogs('foo', level='INFO') as cm:
   logging.getLogger('foo').info('first message')
   logging.getLogger('foo.bar').error('second message')
self.assertEqual(cm.output, ['INFO:foo:first message',
                             'ERROR:foo.bar:second message'])

Nouveau dans la version 3.4.

Il existe également d’autres méthodes utilisées pour effectuer des contrôles plus spécifiques, telles que  :

Méthode

Vérifie que

Disponible en

assertAlmostEqual(a, b)

round(a-b, 7) == 0

assertNotAlmostEqual(a, b)

round(a-b, 7) != 0

assertGreater(a, b)

a > b

3.1

assertGreaterEqual(a, b)

a >= b

3.1

assertLess(a, b)

a < b

3.1

assertLessEqual(a, b)

a <= b

3.1

assertRegex(s, r)

r.search(s)

3.1

assertNotRegex(s, r)

not r.search(s)

3.2

assertCountEqual(a, b)

a and b have the same elements in the same number, regardless of their order

3.2

assertAlmostEqual(first, second, places=7, msg=None, delta=None)

assertNotAlmostEqual(first, second, places=7, msg=None, delta=None)

Vérifie que first et second sont approximativement (ou pas approximativement) égaux en calculant la différence, en arrondissant au nombre donné de décimales places (par défaut 7), et en comparant à zéro. Notez que ces méthodes arrondissent les valeurs au nombre donné de décimales (par exemple comme la fonction round()) et non aux chiffres significatifs.

Si delta est fourni au lieu de places, la différence entre first et second doit être inférieure ou égale (ou supérieure) à delta.

Supplying both delta and places raises a TypeError.

Modifié dans la version 3.2: assertAlmostEqual() considère automatiquement des objets presque égaux qui se comparent égaux. assertNotNotAlmostEqual() échoue automatiquement si les objets qui se comparent sont égaux. Ajout de l’argument mot-clé delta.

assertGreater(first, second, msg=None)

assertGreaterEqual(first, second, msg=None)

assertLess(first, second, msg=None)

assertLessEqual(first, second, msg=None)

Vérifie que first est respectivement >, >=, >=, < ou <= à second selon le nom de la méthode. Sinon, le test échouera :

>>> self.assertGreaterEqual(3, 4)
AssertionError: "3" unexpectedly not greater than or equal to "4"

Nouveau dans la version 3.1.

assertRegex(text, regex, msg=None)

assertNotRegex(text, regex, msg=None)

Vérifie qu’une recherche par motif regex correspond (ou ne correspond pas) à text. En cas d’échec, le message d’erreur inclura le motif et le texte (ou le motif et la partie du texte qui correspond de manière inattendue). regex peut être un objet d’expression régulière ou une chaîne contenant une expression régulière appropriée pour être utilisée par re.search().

Nouveau dans la version 3.1: under the name assertRegexpMatches.

Modifié dans la version 3.2: La méthode assertRegexpMatches() a été renommé en assertRegex().

Nouveau dans la version 3.2: assertNotRegex().

Nouveau dans la version 3.5: Le nom assertNotRegexpMatches` est un alias obsolète pour assertNotRegex().

assertCountEqual(first, second, msg=None)

Vérifie que la séquence first contient les mêmes éléments que second, quel que soit leur ordre. Si ce n’est pas le cas, un message d’erreur indiquant les différences entre les séquences est généré.

Les éléments en double ne sont pas ignorés lors de la comparaison entre first et second. Il vérifie si chaque élément a le même nombre dans les deux séquences. Équivalent à : assertEqual(Counter(list(first))), Counter(list(second))) mais fonctionne aussi avec des séquences d’objets non hachables.

Nouveau dans la version 3.2.

La méthode assertEqual() envoie le contrôle d’égalité pour les objets du même type à différentes méthodes spécifiques au type. Ces méthodes sont déjà implémentées pour la plupart des types intégrés, mais il est également possible d’enregistrer de nouvelles méthodes en utilisant addTypeEqualityFunc()  :

addTypeEqualityFunc(typeobj, function)

Enregistre une méthode spécifique appelée par assertEqual() pour vérifier si deux objets exactement du même typeobj (et non leurs sous-classes) sont égaux. function doit prendre deux arguments positionnels et un troisième argument mot-clé msg=None tout comme assertEqual() le fait. Il doit lever self.failureException(msg) lorsqu’une inégalité entre les deux premiers paramètres est détectée en fournissant éventuellement des informations utiles et expliquant l’inégalité en détail dans le message d’erreur.

Nouveau dans la version 3.1.

La liste des méthodes spécifiques utilisées automatiquement par assertEqual() est résumée dans le tableau suivant. Notez qu’il n’est généralement pas nécessaire d’invoquer ces méthodes directement.

Méthode

Utilisé pour comparer

Disponible en

assertMultiLineEqual(a, b)

chaînes

3.1

assertSequenceEqual(a, b)

séquences

3.1

assertListEqual(a, b)

listes

3.1

assertTupleEqual(a, b)

n-uplets

3.1

assertSetEqual(a, b)

sets ou frozensets

3.1

assertDictEqual(a, b)

dictionnaires

3.1

assertMultiLineEqual(first, second, msg=None)

Vérifie que la chaîne sur plusieurs lignes first est égale à la chaîne second. Si les deux chaînes de caractères ne sont pas égales, un diff mettant en évidence les différences est inclus dans le message d’erreur. Cette méthode est utilisée par défaut pour comparer les chaînes avec assertEqual().

Nouveau dans la version 3.1.

assertSequenceEqual(first, second, msg=None, seq_type=None)

Vérifie que deux séquences sont égales. Si un seq_type est fourni, first et second doivent tous deux être des instances de seq_type ou un échec est levé. Si les séquences sont différentes, un message d’erreur indiquant la différence entre les deux est généré.

Cette méthode n’est pas appelée directement par assertEqual(), mais sert à implémenter assertListEqual() et assertTupleEqual().

Nouveau dans la version 3.1.

assertListEqual(first, second, msg=None)

assertTupleEqual(first, second, msg=None)

Vérifie que deux listes ou deux n-uplets sont égaux. Si ce n’est pas le cas, un message d’erreur qui ne montre que les différences entre les deux est généré. Une erreur est également signalée si l’un ou l’autre des paramètres n’est pas du bon type. Ces méthodes sont utilisées par défaut pour comparer des listes ou des couples avec assertEqual().

Nouveau dans la version 3.1.

assertSetEqual(first, second, msg=None)

Vérifie que deux ensembles sont égaux. Si ce n’est pas le cas, un message d’erreur s’affiche et indique les différences entre les sets. Cette méthode est utilisée par défaut lors de la comparaison de sets ou de frozensets avec assertEqual().

Échoue si l’un des objets first ou second n’a pas de méthode set.difference().

Nouveau dans la version 3.1.

assertDictEqual(first, second, msg=None)

Vérifie que deux dictionnaires sont égaux. Si ce n’est pas le cas, un message d’erreur qui montre les différences dans les dictionnaires est généré. Cette méthode est utilisée par défaut pour comparer les dictionnaires dans les appels à assertEqual().

Nouveau dans la version 3.1.

Enfin, la classe TestCase fournit les méthodes et attributs suivants :

fail(msg=None)

Indique un échec du test sans condition, avec msg ou None pour le message d’erreur.

failureException

Cet attribut de classe donne l’exception levée par la méthode de test. Si un framework de tests doit utiliser une exception spécialisée, probablement pour enrichir l’exception d’informations additionnels., il doit hériter de cette classe d’exception pour bien fonctionner avec le framework. La valeur initiale de cet attribut est AssertionError.

longMessage

Cet attribut de classe détermine ce qui se passe lorsqu’un message d’échec personnalisé est passé en argument au paramètre msg à un appel assertXYYY qui échoue. True est la valeur par défaut. Dans ce cas, le message personnalisé est ajouté à la fin du message d’erreur standard. Lorsqu’il est réglé sur False, le message personnalisé remplace le message standard.

Le paramétrage de la classe peut être écrasé dans les méthodes de test individuelles en assignant un attribut d’instance, self.longMessage, à True ou False avant d’appeler les méthodes d’assertion.

Le réglage de la classe est réinitialisé avant chaque appel de test.

Nouveau dans la version 3.1.

maxDiff

Cet attribut contrôle la longueur maximale des diffs en sortie des méthodes qui génèrent des diffs en cas d’échec. La valeur par défaut est 80*8 caractères. Les méthodes d’assertions affectées par cet attribut sont assertSequenceEqual() (y compris toutes les méthodes de comparaison de séquences qui lui sont déléguées), assertDictEqual() et assertMultiLineEqual().

Régler maxDiff sur None` signifie qu’il n’y a pas de longueur maximale pour les diffs.

Nouveau dans la version 3.2.

Les frameworks de test peuvent utiliser les méthodes suivantes pour recueillir des informations sur le test :

countTestCases()

Renvoie le nombre de tests représentés par cet objet test. Pour les instances de TestCase, c’est toujours 1.

defaultTestResult()

Retourne une instance de la classe de résultat de test qui doit être utilisée pour cette classe de cas de test (si aucune autre instance de résultat n’est fournie à la méthode run()).

Pour les instances de TestCase, c’est toujours une instance de TestResult ; les sous-classes de TestCase peuvent la remplacer au besoin.

id()

Retourne une chaîne identifiant le cas de test spécifique. Il s’agit généralement du nom complet de la méthode de test, y compris le nom du module et de la classe.

shortDescription()

Renvoie une description du test, ou None si aucune description n’a été fournie. L’implémentation par défaut de cette méthode renvoie la première ligne de la docstring de la méthode de test, si disponible, ou None.

Modifié dans la version 3.1: En 3.1, ceci a été modifié pour ajouter le nom du test à la description courte, même en présence d’une docstring. Cela a causé des problèmes de compatibilité avec les extensions unittest et l’ajout du nom du test a été déplacé dans la classe TextTestResult dans Python 3.2.

addCleanup(function, *args, **kwargs)

Ajout d’une fonction à appeler après tearDown() pour nettoyer les ressources utilisées pendant le test. Les fonctions seront appelées dans l’ordre inverse de l’ordre dans lequel elles ont été ajoutées (LIFO). Elles sont appelées avec tous les arguments et arguments de mots-clés passés à addCleanup() quand elles sont ajoutées.

Si setUp() échoue, cela signifie que tearDown() n’est pas appelé, alors que les fonctions de nettoyage ajoutées seront toujours appelées.

Nouveau dans la version 3.1.

doCleanups()

Cette méthode est appelée sans conditions après tearDown(), ou après setUp() si setUp() lève une exception.

Cette méthode est chargée d’appeler toutes les fonctions de nettoyage ajoutées par addCleanup(). Si vous avez besoin de fonctions de nettoyage à appeler avant l’appel à tearDown() alors vous pouvez appeler doCleanups() vous-même.

doCleanups() extrait les méthodes de la pile des fonctions de nettoyage une à la fois, de sorte qu’elles peuvent être appelées à tout moment.

Nouveau dans la version 3.1.

class unittest.FunctionTestCase(testFunc, setUp=None, tearDown=None, description=None)

Cette classe implémente la partie de l’interface TestCase qui permet au lanceur de test de piloter le scénario de test, mais ne fournit pas les méthodes que le code test peut utiliser pour vérifier et signaler les erreurs. Ceci est utilisé pour créer des scénario de test utilisant du code de test existant afin de faciliter l’intégration dans un framework de test basé sur unittest.

26.4.8.1.1. Alias obsolètes

Pour des raisons historiques, certaines méthodes de la classe TestCase avaient un ou plusieurs alias qui sont maintenant obsolètes. Le tableau suivant énumère les noms corrects ainsi que leurs alias obsolètes  :

Nom de méthode

Alias obsolètes

Alias obsolètes

assertEqual()

failUnlessEqual

assertEquals

assertNotEqual()

failIfEqual

assertNotEquals

assertTrue()

failUnless

assert_

assertFalse()

failIf

assertRaises()

failUnlessRaises

assertAlmostEqual()

failUnlessAlmostEqual

assertAlmostEquals

assertNotAlmostEqual()

failIfAlmostEqual

assertNotAlmostEquals

assertRegex()

assertRegexpMatches

assertNotRegex()

assertNotRegexpMatches

assertRaisesRegex()

assertRaisesRegexp

Obsolète depuis la version 3.1: the fail* aliases listed in the second column.

Obsolète depuis la version 3.2: the assert* aliases listed in the third column.

Obsolète depuis la version 3.2: Les expressions assertRegexpMatches et assertRaisesRegexp ont été renommées en assertRegex() et assertRaisesRegex().

Obsolète depuis la version 3.5: assertNotRegexpMatches en faveur de assertNotRegex().

26.4.8.2. Regroupement des tests

class unittest.TestSuite(tests=())

Cette classe représente une agrégation de cas de test individuels et de suites de tests. La classe présente l’interface requise par le lanceur de test pour être exécutée comme tout autre cas de test. L’exécution d’une instance de TestSuite est identique à l’itération sur la suite, en exécutant chaque test indépendamment.

Si tests est fourni, il doit s’agir d’un itérable de cas de test individuels ou d’autres suites de test qui seront utilisés pour construire la suite initial. Des méthodes supplémentaires sont fournies pour ajouter ultérieurement des cas de test et des suites à la collection.

Les objets TestSuite se comportent comme les objets TestCase, sauf qu’ils n’implémentent pas réellement un test. Au lieu de cela, ils sont utilisés pour regrouper les tests en groupes de tests qui doivent être exécutés ensemble. Des méthodes supplémentaires sont disponibles pour ajouter des tests aux instances de TestSuite :

addTest(test)

Ajouter un objet TestCase ou TestSuite à la suite de tests.

addTests(tests)

Ajouter tous les tests d’un itérable d’instances de TestCase et de TestSuite à cette suite de tests.

C’est l’équivalent d’une itération sur tests, appelant addTest() pour chaque élément.

TestSuite partage les méthodes suivantes avec TestCase :

run(result)

Exécute les tests associés à cette suite, en collectant le résultat dans l’objet de résultat de test passé par result. Remarquer que contrairement à TestCase.run(), TestSuite.run() nécessite que l’objet résultat soit passé.

debug()

Exécute les tests associés à cette suite sans collecter le résultat. Ceci permet aux exceptions levées par le test d’être propagées à l’appelant et peut être utilisé pour exécuter des tests sous un débogueur.

countTestCases()

Renvoie le nombre de tests représentés par cet objet de test, y compris tous les tests individuels et les sous-suites.

__iter__()

Les tests groupés par une classe TestSuite sont toujours accessibles par itération. Les sous-classes peuvent fournir paresseusement des tests en surchargeant __iter__(). Notez que cette méthode peut être appelée plusieurs fois sur une même suite (par exemple lors du comptage des tests ou de la comparaison pour l’égalité) et que les tests retournés par itérations répétées avant TestSuite.run() doivent être les mêmes pour chaque itération. Après TestSuite.run(), les appelants ne devraient pas se fier aux tests retournés par cette méthode à moins qu’ils n’utilisent une sous-classe qui remplace TestSuite._removeTestAtIndex() pour préserver les références des tests.

Modifié dans la version 3.2: Dans les versions précédentes, la classe TestSuite accédait aux tests directement plutôt que par itération, donc surcharger la méthode __iter__() n’était pas suffisante pour fournir les tests.

Modifié dans la version 3.4: Dans les versions précédentes, la classe TestSuite contenait des références à chaque TestCase après l’appel à TestSuite.run(). Les sous-classes peuvent restaurer ce comportement en surchargeant TestSuite._removeTestAtIndex().

Dans l’utilisation typique de l’objet TestSuite, la méthode run() est invoquée par une classe TestRunner plutôt que par le système de test de l’utilisateur.

26.4.8.3. Chargement et exécution des tests

class unittest.TestLoader

La classe TestLoader est utilisée pour créer des suites de tests à partir de classes et de modules. Normalement, il n’est pas nécessaire de créer une instance de cette classe ; le module unittest fournit une instance qui peut être partagée comme unittest.defaultTestLoader. L’utilisation d’une sous-classe ou d’une instance permet cependant de personnaliser certaines propriétés configurables.

Les objets de la classe TestLoader ont les attributs suivants :

errors

Une liste des erreurs non fatales rencontrées lors du chargement des tests. Il est impossible de faire une remise à zéro pendant le chargement. Les erreurs fatales sont signalées par la méthode correspondante qui lève une exception à l’appelant. Les erreurs non fatales sont également indiquées par un test synthétique qui lève l’erreur initiale lors de l’exécution.

Nouveau dans la version 3.5.

Les objets de la classe TestLoader ont les attributs suivants :

loadTestsFromTestCase(testCaseClass)

Renvoie une suite de tous les cas de test contenus dans la classe TestCaseClassdérivée de testCase.

Une instance de cas de test est créée pour chaque méthode nommée par getTestCaseNames(). Par défaut, ce sont les noms des méthodes commençant par « test ». Si getTestTestCaseNames() ne renvoie aucune méthode, mais que la méthode runTest() est implémentée, un seul cas de test est créé pour cette méthode à la place.

loadTestsFromModule(module, pattern=None)

Renvoie une suite de tous les cas de test contenus dans le module donné. Cette méthode recherche module pour les classes dérivées de TestCase et crée une instance de la classe pour chaque méthode de test définie pour cette classe.

Note

Bien que l’utilisation d’une hiérarchie de classes TestCase (les classes dérivées de TestCase) peut être un moyen pratique de partager des fixtures et des fonctions utilitaires, définir une méthode de test pour des classes de base non destinées à être directement instanciée ne marche pas bien avec cette méthode. Cela peut toutefois s’avérer utile lorsque les fixtures sont différentes et définies dans des sous-classes.

Si un module fournit une fonction load_tests, il est appelé pour charger les tests. Cela permet aux modules de personnaliser le chargement des tests. C’est le protocole load_tests protocol. L’argument pattern est passé comme troisième argument à load_tests.

Modifié dans la version 3.2: Ajout de la prise en charge de load_tests.

Modifié dans la version 3.5: L’argument par défaut non documenté et non officiel use_load_tests est déprécié et ignoré, bien qu’il soit toujours accepté pour la compatibilité descendante. La méthode accepte aussi maintenant un argument pattern qui est passé à load_tests comme troisième argument.

loadTestsFromName(name, module=None)

Renvoie une suite de tous les cas de test en fonction d’un spécificateur de chaîne de caractères.

Le spécificateur name est un « nom pointillé » qui peut être résolu soit par un module, une classe de cas de test, une méthode de test dans une classe de cas de test, une instance de TestSuite, ou un objet appelable qui retourne une instance de classe TestCase ou de classe TestSuite. Ces contrôles sont appliqués dans l’ordre indiqué ici, c’est-à-dire qu’une méthode sur une classe de cas de test possible sera choisie comme « méthode de test dans une classe de cas de test », plutôt que comme « un objet appelable ».

Par exemple, si vous avez un module SampleTests contenant une classe TestCase (classe dérivée de la classe SampleTestCase) avec trois méthodes de test (test_one(), test_two() et test_three()), l’élément spécificateur SampleTests.sampleTestCase renvoie une suite qui va exécuter les trois méthodes de tests. L’utilisation du spécificateur SampleTests.SampleTestCase.test_two permettrait de retourner une suite de tests qui ne lancerait que la méthode test test_two(). Le spécificateur peut se référer à des modules et packages qui n’ont pas été importés. Ils seront importés par un effet de bord.

La méthode résout facultativement name relatif au module donné.

Modifié dans la version 3.5: Si une ImportError ou AttributeError se produit pendant la traversée de name, un test synthétique qui enrichie l’erreur produite lors de l’exécution est renvoyé. Ces erreurs sont incluses dans les erreurs accumulées par self.errors.

loadTestsFromNames(names, module=None)

Similaire à loadTestsFromName(), mais prend une séquence de noms plutôt qu’un seul nom. La valeur renvoyée est une suite de tests qui gère tous les tests définis pour chaque nom.

getTestCaseNames(testCaseClass)

Renvoie une séquence triée de noms de méthodes trouvés dans testCaseClass ; ceci doit être une sous-classe de TestCase.

discover(start_dir, pattern='test*.py', top_level_dir=None)

Trouve tous les modules de test en parcourant les sous-répertoires du répertoire de démarrage spécifié, et renvoie un objet TestSuite qui les contient. Seuls les fichiers de test qui correspondent à pattern sont chargés. Seuls les noms de modules qui sont importables (c’est-à-dire qui sont des identifiants Python valides) sont chargés.

Tous les modules de test doivent être importables depuis la racine du projet. Si le répertoire de démarrage n’est pas la racine, le répertoire racine doit être spécifié séparément.

Si l’importation d’un module échoue, par exemple en raison d’une erreur de syntaxe, celle-ci est alors enregistrée comme une erreur unique et la découverte se poursuit. Si l’échec de l’importation est dû au fait que SkipTest est levé, il est enregistré comme un saut plutôt que comme un message d’erreur.

Si un paquet (un répertoire contenant un fichier nommé __init__.py) est trouvé, le paquet est alors vérifié pour une fonction load_tests. Si elle existe, elle s’appellera package.load_tests(loader, tests, pattern). Le mécanisme de découverte de test prend soin de s’assurer qu’un paquet n’est vérifié qu’une seule fois au cours d’une invocation, même si la fonction load_tests appelle elle-même loader.discover.

Si load_tests existe alors la découverte ne poursuit pas la récursion dans le paquet, load_tests a la responsabilité de charger tous les tests dans le paquet.

Le motif n’est délibérément pas stocké en tant qu’attribut du chargeur afin que les paquets puissent continuer à être découverts eux-mêmes. top_level_dir est stocké de sorte que load_tests n’a pas besoin de passer cet argument a loader. discover().

start_dir peut être un nom de module ainsi qu’un répertoire.

Nouveau dans la version 3.2.

Modifié dans la version 3.4: Les modules qui lèvent SkipTest lors de l’importation sont enregistrés comme des sauts et non des erreurs. Le mécanisme de découverte fonctionne pour les paquets-espaces de nommage. Les chemins sont triés avant d’être importés pour que l’ordre d’exécution soit le même, même si l’ordre du système de fichiers sous-jacent ne dépend pas du nom du fichier.

Modifié dans la version 3.5: Les paquets trouvés sont maintenant vérifiés pour load_tests indépendamment du fait que leur chemin d’accès corresponde ou non à pattern, car il est impossible pour un nom de paquet de correspondre au motif par défaut.

Les attributs suivants d’une classe TestLoader peuvent être configurés soit par héritage, soit par affectation sur une instance  :

testMethodPrefix

Chaîne donnant le préfixe des noms de méthodes qui seront interprétés comme méthodes de test. La valeur par défaut est 'test'.

Ceci affecte les méthodes getTestCaseNames() et toutes les méthodes loadTestsFrom*().

sortTestMethodsUsing

Fonction à utiliser pour comparer les noms de méthodes lors de leur tri dans les méthodes getTestCaseNames() et toutes les méthodes loadTestsFrom*().

suiteClass

Objet appelable qui construit une suite de tests à partir d’une liste de tests. Aucune méthode sur l’objet résultant n’est nécessaire. La valeur par défaut est la classe TestSuite.

Cela affecte toutes les méthodes loadTestsFrom*().

class unittest.TestResult

Cette classe est utilisée pour compiler des informations sur les tests qui ont réussi et ceux qui ont échoué.

Un objet TestResult stocke les résultats d’un ensemble de tests. Les classes TestCase et TestSuite s’assurent que les résultats sont correctement enregistrés. Les auteurs du test n’ont pas à se soucier de l’enregistrement des résultats des tests.

Les cadriciels de test construits sur unittest peuvent nécessiter l’accès à l’objet TestResult généré en exécutant un ensemble de tests à des fins de génération de comptes-rendu. Une instance de TestResult est alors renvoyée par la méthode TestRunner.run() à cette fin.

Les instance de TestResult ont les attributs suivants qui sont intéressant pour l’inspection des résultats de l’exécution d’un ensemble de tests  :

errors

Une liste contenant un couple d’instances de TestCase et une chaînes de caractères contenant des traces formatées. Chaque couple représente un test qui a levé une exception inattendue.

failures

Une liste contenant un couple d’instances de TestCase et une chaînes de caractères contenant des traces formatées. Chaque tuple représente un test où un échec a été explicitement signalé en utilisant les méthodes TestCase.assert*().

skipped

Une liste contenant un couple d’instances de TestCase et une chaînes de caractères contenant la raison de l’omission du test.

Nouveau dans la version 3.1.

expectedFailures

Une liste contenant un couple d’instance TestCase et une chaînes de caractères contenant des traces formatées. Chaque coulpe représente un échec attendu du scénario de test.

unexpectedSuccesses

Une liste contenant les instances TestCase qui ont été marquées comme des échecs attendus, mais qui ont réussi.

shouldStop

A positionner sur True quand l’exécution des tests doit être arrêter par stop().

testsRun

Le nombre total de tests effectués jusqu’à présent.

buffer

S’il est défini sur true, sys.stdout et sys.stderr sont mis dans un tampon entre les appels de startTest() et stopTest(). La sortie collectée est répercutée sur les sorties sys.stdout et sys.stderr réels uniquement en cas d’échec ou d’erreur du test. Toute sortie est également attachée au message d’erreur.

Nouveau dans la version 3.2.

failfast

Si la valeur est true stop() est appelée lors de la première défaillance ou erreur, ce qui interrompt le test en cours d’exécution.

Nouveau dans la version 3.2.

tb_locals

Si la valeur est true, les variables locales sont affichées dans les traces d’appels.

Nouveau dans la version 3.5.

wasSuccessful()

Renvoie True si tous les tests effectués jusqu’à présent ont réussi, sinon renvoie False.

Modifié dans la version 3.4: Renvoie False s’il y a eu des unexpectedSuccesses dans les tests annotés avec le décorateur expectedFailure().

stop()

Cette méthode peut être appelée pour signaler que l’ensemble des tests en cours d’exécution doit être annulé en définissant l’attribut shouldStop sur True. Les instances de TestRunner doivent respecter ce signal et se terminer sans exécuter de tests supplémentaires.

Par exemple, cette fonctionnalité est utilisée par la classe TextTestRunner pour arrêter le cadriciel de test lorsque l’utilisateur lance une interruption clavier. Les outils interactifs qui fournissent des implémentations de TestRunner peuvent l’utiliser de la même manière.

Les méthodes suivantes de la classe TestResult sont utilisées pour maintenir les structures de données internes, et peuvent être étendues dans des sous-classes pour gérer des exigences supplémentaires en termes de compte-rendu. Cette fonction est particulièrement utile pour créer des outils qui prennent en charge la génération de rapports interactifs pendant l’exécution des tests.

startTest(test)

Appelé lorsque le scénario de test test est sur le point d’être exécuté.

stopTest(test)

Appelé après l’exécution du cas de test test, quel qu’en soit le résultat.

startTestRun()

Appelé une fois avant l’exécution des tests.

Nouveau dans la version 3.1.

stopTestRun()

Appelé une fois après l’exécution des tests.

Nouveau dans la version 3.1.

addError(test, err)

Appelé lorsque le cas de test test soulève une exception inattendue. err est un couple du formulaire renvoyé par sys.exc_info() : (type, valeur, traceback).

L’implémentation par défaut ajoute un couple (test, formatted_err) à l’attribut errors de l’instance, où formatted_err est une trace formatée à partir de err.

addFailure(test, err)

Appelé lorsque le cas de test test soulève une exception inattendue. err est un triplet de la même forme que celui renvoyé par sys.exc_info() : (type, valeur, traceback).

L’implémentation par défaut ajoute un couple (test, formatted_err) à l’attribut errors de l’instance, où formatted_err est une trace formatée à partir de err.

addSuccess(test)

Appelé lorsque le scénario de test test réussit.

L’implémentation par défaut ne fait rien.

addSkip(test, reason)

Appelé lorsque le scénario de test test est ignoré. raison est la raison pour laquelle le test donné à été ignoré.

L’implémentation par défaut ajoute un couple (test, raison) à l’attribut skipped de l’instance.

addExpectedFailure(test, err)

Appelé lorsque le scénario de test test échoue, mais qui a été marqué avec le décorateur expectedFailure().

L’implémentation par défaut ajoute un couple (test, formatted_err) à l’attribut errors de l’instance, où formatted_err est une trace formatée à partir de err.

addUnexpectedSuccess(test)

Appelé lorsque le scénario de test test réussit, mais que ce scénario a été marqué avec le décorateur expectedFailure().

L’implémentation par défaut ajoute le test à l’attribut unexpectedSuccesses de l’instance.

addSubTest(test, subtest, outcome)

Appelé à la fin d’un sous-test. test est le cas de test correspondant à la méthode de test. subtest est une instance dérivée de TestCase décrivant le sous-test.

Si outcome est None, le sous-test a réussi. Sinon, il a échoué avec une exception où outcome est un triplet du formulaire renvoyé par sys.exc_info() : (type, valeur, traceback).

L’implémentation par défaut ne fait rien lorsque le résultat est un succès, et enregistre les échecs de sous-test comme des échecs normaux.

Nouveau dans la version 3.4.

class unittest.TextTestResult(stream, descriptions, verbosity)

Une implémentation concrète de TestResult utilisé par la classe TextTestRunner.

Nouveau dans la version 3.2: Cette classe s’appelait auparavant _TextTestResult. L’ancien nom existe toujours en tant qu’alias, mais il est obsolète.

unittest.defaultTestLoader

Instance de la classe TestLoader destinée à être partagée. Si aucune personnalisation de la classe TestLoader n’est nécessaire, cette instance peut être utilisée au lieu de créer plusieurs fois de nouvelles instances.

class unittest.TextTestRunner(stream=None, descriptions=True, verbosity=1, failfast=False, buffer=False, resultclass=None, warnings=None, *, tb_locals=False)

Une implémentation de base d’un lanceur de test qui fournit les résultats dans un flux. Si stream est None, par défaut, sys.stderr est utilisé comme flux de sortie. Cette classe a quelques paramètres configurables, mais est essentiellement très simple. Les applications graphiques qui exécutent des suites de tests doivent fournir des implémentations alternatives. De telles implémentations doivent accepter **kwargs car l’interface pour construire les lanceurs change lorsque des fonctionnalités sont ajoutées à unittest.

Par défaut, ce lanceur affiche DeprecationWarning, PendingDeprecationWarning, ResourceWarning et ImportWarning même si elles sont ignorées par défaut. Les avertissements causés par des méthodes *unittest* dépréciées sont également spéciaux et, lorsque les filtres d’avertissement sont default ou always, ils n’apparaissent qu’une fois par module, afin d’éviter trop de messages d’alerte. Ce comportement peut être annulé en utilisant les options -Wd ou -Wa de Python (voir Gestion des avertissements) et en laissant warnings à None.

Modifié dans la version 3.2: Ajout du paramètre warnings.

Modifié dans la version 3.2: Le flux par défaut est défini sur sys.stderr au moment de l’instanciation plutôt qu’à l’importation.

Modifié dans la version 3.5: Ajout du paramètre tb_locals.

_makeResult()

Cette méthode renvoie l’instance de TestResult utilisée par run(). Il n’est pas destiné à être appelé directement, mais peut être surchargée dans des sous-classes pour fournir un TestResult personnalisé.

_makeResult() instancie la classe ou l’appelable passé dans le constructeur TextTestRunner comme argument resultclass. Il vaut par défaut TextTestResult si aucune resultclass n’est fournie. La classe de résultat est instanciée avec les arguments suivants :

stream, descriptions, verbosity

run(test)

This method is the main public interface to the TextTestRunner. This method takes a TestSuite or TestCase instance. A TestResult is created by calling _makeResult() and the test(s) are run and the results printed to stdout.

unittest.main(module='__main__', defaultTest=None, argv=None, testRunner=None, testLoader=unittest.defaultTestLoader, exit=True, verbosity=1, failfast=None, catchbreak=None, buffer=None, warnings=None)

Un programme en ligne de commande qui charge un ensemble de tests à partir du module et les exécute. L’utilisation principale est de rendre les modules de test facilement exécutables. L’utilisation la plus simple pour cette fonction est d’inclure la ligne suivante à la fin d’un script de test :

if __name__ == '__main__':
    unittest.main()

Vous pouvez exécuter des tests avec des informations plus détaillées en utilisant l’option de verbosité :

if __name__ == '__main__':
    unittest.main(verbosity=2)

L’argument defaultTest est soit le nom d’un seul test, soit un itérable de noms de test à exécuter si aucun nom de test n’est spécifié via argv. Si aucun nom de test n’est fourni via argv, tous les tests trouvés dans module sont exécutés.

L’argument argv peut être une liste d’options passées au programme, le premier élément étant le nom du programme. S’il n’est pas spécifié ou vaut None, les valeurs de sys.argv sont utilisées.

L’argument testRunner peut être soit une classe de lanceur de test, soit une instance déjà créée de celle-ci. Par défaut, main appelle sys.exit() avec un code de sortie indiquant le succès ou l’échec des tests exécutés.

L’argument testLoader doit être une instance de TestLoader, et par défaut de defaultTestLoader.

Les main sont utilisés à partir de l’interpréteur interactif en passant dans l’argument exit=False. Ceci affiche le résultat sur la sortie standard sans appeler sys.exit() :

>>> from unittest import main
>>> main(module='test_module', exit=False)

Les paramètres failfast, catchbreak et buffer ont le même effet que la même option en ligne de commande command-line options.

L’argument warnings spécifie l’argument filtre d’avertissement qui doit être utilisé lors de l’exécution des tests. Si elle n’est pas spécifiée, elle reste réglée sur None si une option -W' est passée à python (voir Utilisation des avertissements), sinon elle sera réglée sur 'default'.

L’appel de main renvoie en fait une instance de la classe TestProgram. Le résultat des tests effectués est enregistré sous l’attribut result.

Modifié dans la version 3.1: Ajout du paramètre exit.

Modifié dans la version 3.2: Ajout des paramètres verbosity, failfast, catchbreak, buffer et warnings.

Modifié dans la version 3.4: Le paramètre defaultTest a été modifié pour accepter également un itérable de noms de test.

26.4.8.3.1. Protocole de chargement des tests (load_tests Protocol)

Nouveau dans la version 3.2.

Les modules ou paquets peuvent personnaliser la façon dont les tests sont chargés à partir de ceux-ci pendant l’exécution des tests ou pendant la découverte de tests en implémentant une fonction appelée load_tests.

Si un module de test définit load_tests il est appelé par TestLoader.loadTestsFromModule() avec les arguments suivants :

load_tests(loader, standard_tests, pattern)

où pattern est passé directement depuis loadTestsFromModule. La valeur par défaut est None.

Elle doit renvoyer une classe TestSuite.

loader est l’instance de TestLoader qui effectue le chargement. standard_tests sont les tests qui sont chargés par défaut depuis le module. Il est courant que les modules de test veuillent seulement ajouter ou supprimer des tests de l’ensemble standard de tests. Le troisième argument est utilisé lors du chargement de paquets dans le cadre de la découverte de tests.

Une fonction typique de load_tests qui charge les tests d’un ensemble spécifique de classes TestCase peut ressembler à :

test_cases = (TestCase1, TestCase2, TestCase3)

def load_tests(loader, tests, pattern):
    suite = TestSuite()
    for test_class in test_cases:
        tests = loader.loadTestsFromTestCase(test_class)
        suite.addTests(tests)
    return suite

Si la découverte est lancée dans un répertoire contenant un paquet, soit à partir de la ligne de commande, soit en appelant TestLoader.discover(), alors le système recherche dans le fichier du paquet __init__.py la fonction load_tests. Si cette fonction n’existe pas, la découverte se poursuit dans le paquet comme si c’était juste un autre répertoire. Sinon, la découverte des tests du paquet est effectuée par load_tests qui est appelé avec les arguments suivants :

load_tests(loader, standard_tests, pattern)

Doit renvoyer une classe TestSuite représentant tous les tests du paquet. (standard_tests ne contient que les tests collectés dans le fichier __init__.py).

Comme le motif est passé à load_tests, le paquet est libre de continuer (et potentiellement de modifier) la découverte des tests. Une fonction « ne rien faire » load_tests pour un paquet de test ressemblerait à :

def load_tests(loader, standard_tests, pattern):
    # top level directory cached on loader instance
    this_dir = os.path.dirname(__file__)
    package_tests = loader.discover(start_dir=this_dir, pattern=pattern)
    standard_tests.addTests(package_tests)
    return standard_tests

Modifié dans la version 3.5: La découverte de test ne vérifie plus que les noms de paquets correspondent à pattern en raison de l’impossibilité de trouver des noms de paquets correspondant au motif par défaut.

26.4.9. Classes et modules d’aménagements des tests

Les classes et modules d’aménagements des tests sont implémentés dans TestSuite. Lorsque la suite de tests rencontre un test d’une nouvelle classe, alors tearDownClass() de la classe précédente (s’il y en a une) est appelé, suivi de setUpClass() de la nouvelle classe.

De même, si un test provient d’un module différent du test précédent, alors tearDownModule du module précédent est exécuté, suivi par setUpModule du nouveau module.

Après que tous les tests ont été exécutés, les tearDownClass et tearDownModule finaux sont exécutés.

Notez que les aménagements de tests partagés ne fonctionnent pas bien avec de « potentielles » fonctions comme la parallélisation de test et qu’ils brisent l’isolation des tests. Ils doivent être utilisés avec parcimonie.

L’ordre par défaut des tests créés par les chargeurs de tests unitaires est de regrouper tous les tests des mêmes modules et classes. Cela à pour conséquence que setUpClass / setUpModule (etc) sont appelé exactement une fois par classe et module. Si vous rendez l’ordre aléatoire, de sorte que les tests de différents modules et classes soient adjacents les uns aux autres, alors ces fonctions d’aménagements partagées peuvent être appelées plusieurs fois dans un même test.

Les aménagements de tests partagés ne sont pas conçus pour fonctionner avec des suites dont la commande n’est pas standard. Une BaseTestSuite existe toujours pour les cadriciels qui ne veulent pas gérer les aménagements de tests partagés.

S’il y a des exceptions levées pendant l’une des fonctions d’aménagement de tests partagés, le test est signalé comme étant en erreur. Parce qu’il n’y a pas d’instance de test correspondante, un objet _ErrorHolder (qui a la même interface qu’une classe TestCase) est créé pour représenter l’erreur. Si vous n’utilisez que le lanceur de test unitaire standard, ce détail n’a pas d’importance, mais si vous êtes un auteur de cadriciel de test, il peut être pertinent.

26.4.9.1. Classes de mise en place (setUpClass) et de démantèlement des tests (tearDownClass)

Elles doivent être implémentées en tant que méthodes de classe :

import unittest

class Test(unittest.TestCase):
    @classmethod
    def setUpClass(cls):
        cls._connection = createExpensiveConnectionObject()

    @classmethod
    def tearDownClass(cls):
        cls._connection.destroy()

Si vous voulez que les classes de base setUpClass et tearDownClass soient appelées, vous devez les appeler vous-même. Les implémentations dans TestCase sont vides.

Si une exception est levée pendant l’exécution de setUpClass alors les tests dans la classe ne sont pas exécutés et la classe tearDownClass n’est pas exécutée. Les classes ignorées n’auront pas d’exécution de setUpClass ou tearDownClass. Si l’exception est une exception SkipTest alors la classe est signalée comme ayant été ignorée au lieu d’être en échec.

26.4.9.2. Module de mise en place (setUpModule) et de démantèlement des tests (tearDownModule)

Elles doivent être implémentées en tant que fonctions :

def setUpModule():
    createConnection()

def tearDownModule():
    closeConnection()

Si une exception est levée pendant l’exécution de la fonction setUpModule alors aucun des tests du module ne sera exécuté et la fonction tearDownModule ne sera pas exécutée. Si l’exception est une exception SkipTest alors le module est signalé comme ayant été ignoré au lieu d’être en échec.

26.4.10. Traitement des signaux

Nouveau dans la version 3.2.

L’option -c/--catch en ligne de commande pour unittest, ainsi que le paramètre catchbreak vers unittest.main(), permettent une utilisation simplifiée du contrôle-C pendant un test. Avec l’activation de catchbreak, l’utilisation du contrôle-C permet de terminer le test en cours d’exécution, et le test se termine et rapporte tous les résultats obtenus jusqu’à présent. Un deuxième contrôle-C lève une exception classique KeyboardInterrupt.

Le gestionnaire du signal contrôle-C tente de rester compatible avec le code ou les tests qui installent leur propre gestionnaire signal.SIGINT. Si le gestionnaire unittest est appelé mais n’est pas le gestionnaire installé signal.SIGINT, c’est-à-dire qu’il a été remplacé par le système sous test et délégué, alors il appelle le gestionnaire par défaut. C’est normalement le comportement attendu par un code qui remplace un gestionnaire installé et lui délègue. Pour les tests individuels qui ont besoin que le signal contrôle-C « unittest » soit désactivée, le décorateur removeHandler() peut être utilisé.

Il existe quelques fonctions de support pour les auteurs de cadriciel afin d’activer la fonctionnalité de gestion des contrôle-C dans les cadriciels de test.

unittest.installHandler()

Installe le gestionnaire contrôle-c. Quand un signal.SIGINT est reçu (généralement en réponse à l’utilisateur appuyant sur contrôle-c) tous les résultats enregistrés vont appeler la méthode stop().

unittest.registerResult(result)

Enregistre un objet TestResult pour la gestion du contrôle-C. L’enregistrement d’un résultat stocke une référence faible sur celui-ci, de sorte qu’il n’empêche pas que le résultat soit collecté par le ramasse-miette.

L’enregistrement d’un objet TestResult n’a pas d’effets de bord si la gestion du contrôle-c n’est pas activée, donc les cadriciels de test peuvent enregistrer sans condition tous les résultats qu’ils créent indépendamment du fait que la gestion soit activée ou non.

unittest.removeResult(result)

Supprime un résultat enregistré. Une fois qu’un résultat a été supprimé, stop() n’est plus appelé sur cet objet résultat en réponse à un contrôle-c.

unittest.removeHandler(function=None)

Lorsqu’elle est appelée sans arguments, cette fonction supprime le gestionnaire contrôle-c s’il a été installé. Cette fonction peut également être utilisée comme décorateur de test pour supprimer temporairement le gestionnaire pendant l’exécution du test :

@unittest.removeHandler
def test_signal_handling(self):
    ...

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26.5. unittest.mock — Bibliothèque d’objets simulacres

Nouveau dans la version 3.3.

Code source : Lib/unittest/mock.py [https://github.com/python/cpython/tree/3.6/Lib/unittest/mock.py]

unittest.mock est une bibliothèque pour tester en Python. Elle permet de remplacer des parties du système sous tests par des objets simulacres et faire des assertions sur la façon dont ces objets ont été utilisés.

unittest.mock fournit une classe Mock pour ne pas avoir besoin de créer manuellement des objets factices dans la suite de tests. Après avoir effectué une action, on peut faire des assertions sur les méthodes / attributs utilisés et les arguments avec lesquels ils ont été appelés. On peut également spécifier des valeurs renvoyées et définir les attributs nécessaires aux tests.

De plus, mock fournit un décorateur patch() qui est capable de patcher les modules et les classes dans la portée d’un test, ainsi que sentinel pour créer des objets uniques. Voir le guide rapide quick guide pour quelques exemples d’utilisation de Mock, MagicMock et patch().

Mock est très facile à utiliser et est conçu pour être utilisé avec unittest. Mock est basé sur le modèle action -> assertion au lieu de enregistrement -> rejouer utilisé par de nombreux cadriciels d’objets simulacres.

Il y a un portage de unittest.mock pour les versions antérieures de Python, disponible sur PyPI [https://pypi.org/project/mock].

26.5.1. Guide rapide

Les classes Mock et MagicMock créent tous les attributs et méthodes au fur et à mesure des accès et stockent les détails de la façon dont ils ont été utilisés. On peut les configurer, pour spécifier des valeurs de renvoi ou limiter les attributs utilisables, puis faire des assertions sur la façon dont ils ont été utilisés :

>>> from unittest.mock import MagicMock
>>> thing = ProductionClass()
>>> thing.method = MagicMock(return_value=3)
>>> thing.method(3, 4, 5, key='value')
3
>>> thing.method.assert_called_with(3, 4, 5, key='value')

L’attribut side_effect permet de spécifier des effets de bords, y compris la levée d’une exception lorsqu’un objet simulacre est appelé :

>>> mock = Mock(side_effect=KeyError('foo'))
>>> mock()
Traceback (most recent call last):
 ...
KeyError: 'foo'

>>> values = {'a': 1, 'b': 2, 'c': 3}
>>> def side_effect(arg):
...     return values[arg]
...
>>> mock.side_effect = side_effect
>>> mock('a'), mock('b'), mock('c')
(1, 2, 3)
>>> mock.side_effect = [5, 4, 3, 2, 1]
>>> mock(), mock(), mock()
(5, 4, 3)

Il existe beaucoup d’autres façons de configurer et de contrôler le comportement de Mock. Par exemple, l’argument spec configure le mock pour qu’il utilise les spécifications d’un autre objet. Tenter d’accéder à des attributs ou méthodes sur le mock qui n’existent pas sur l’objet spec lève une AttributeError.

Le décorateur / gestionnaire de contexte patch() permet de simuler facilement des classes ou des objets dans un module sous tests. L’objet spécifié est remplacé par un objet simulacre (ou autre) pendant le test et est restauré à la fin du test :

>>> from unittest.mock import patch
>>> @patch('module.ClassName2')
... @patch('module.ClassName1')
... def test(MockClass1, MockClass2):
...     module.ClassName1()
...     module.ClassName2()
...     assert MockClass1 is module.ClassName1
...     assert MockClass2 is module.ClassName2
...     assert MockClass1.called
...     assert MockClass2.called
...
>>> test()

Note

When you nest patch decorators the mocks are passed in to the decorated function in the same order they applied (the normal python order that decorators are applied). This means from the bottom up, so in the example above the mock for module.ClassName1 is passed in first.

Avec patch(), il est important de patcher les objets dans l’espace de nommage où ils sont recherchés. C’est ce qui se fait normalement, mais pour un guide rapide, lisez où patcher.

Comme tout décorateur, patch() peut être utilisé comme gestionnaire de contexte avec une instruction with :

>>> with patch.object(ProductionClass, 'method', return_value=None) as mock_method:
...     thing = ProductionClass()
...     thing.method(1, 2, 3)
...
>>> mock_method.assert_called_once_with(1, 2, 3)

Il existe également patch.dict() pour définir des valeurs d’un dictionnaire au sein d’une portée et restaurer ce dictionnaire à son état d’origine lorsque le test se termine :

>>> foo = {'key': 'value'}
>>> original = foo.copy()
>>> with patch.dict(foo, {'newkey': 'newvalue'}, clear=True):
...     assert foo == {'newkey': 'newvalue'}
...
>>> assert foo == original

Mock gère le remplacement des méthodes magiques de Python. La façon la plus simple d’utiliser les méthodes magiques est la classe MagicMock. Elle permet de faire des choses comme :

>>> mock = MagicMock()
>>> mock.__str__.return_value = 'foobarbaz'
>>> str(mock)
'foobarbaz'
>>> mock.__str__.assert_called_with()

Mock permet d’assigner des fonctions (ou d’autres instances Mock) à des méthodes magiques et elles seront appelées correctement. La classe MagicMock est juste une variante de Mock qui a toutes les méthodes magiques pré-créées (enfin, toutes les méthodes utiles).

L’exemple suivant est un exemple de création de méthodes magiques avec la classe Mock ordinaire :

>>> mock = Mock()
>>> mock.__str__ = Mock(return_value='wheeeeee')
>>> str(mock)
'wheeeeee'

Pour être sûr que les objets simulacres dans vos tests ont la même API que les objets qu’ils remplacent, utilisez l’auto-spécification. L’auto-spécification peut se faire via l’argument autospec de patch ou par la fonction create_autospec(). L’auto-spécification crée des objets simulacres qui ont les mêmes attributs et méthodes que les objets qu’ils remplacent, et toutes les fonctions et méthodes (y compris les constructeurs) ont les mêmes signatures d’appel que l’objet réel.

Ceci garantit que vos objets simulacres échouent de la même manière que votre code de production s’ils ne sont pas utilisés correctement :

>>> from unittest.mock import create_autospec
>>> def function(a, b, c):
...     pass
...
>>> mock_function = create_autospec(function, return_value='fishy')
>>> mock_function(1, 2, 3)
'fishy'
>>> mock_function.assert_called_once_with(1, 2, 3)
>>> mock_function('wrong arguments')
Traceback (most recent call last):
 ...
TypeError: <lambda>() takes exactly 3 arguments (1 given)

La fonction create_autospec() peut aussi être utilisée sur les classes, où elle copie la signature de la méthode __init__, et sur les objets appelables où elle copie la signature de la méthode __call__.

26.5.2. La classe Mock

La classe Mock est un objet simulacre flexible destiné à remplacer l’utilisation d’objets bouchons et factices dans votre code. Les Mocks sont appelables et créent des attributs comme de nouveaux Mocks lorsque l’on y accède 1. L’accès au même attribut renvoie toujours le même mock. Les simulacres enregistrent la façon dont ils sont utilisés, ce qui permet de faire des assertions sur ce que le code leur a fait.

La classe MagicMock est une sous-classe de Mock avec toutes les méthodes magiques pré-créées et prête à l’emploi. Il existe également des variantes non appelables, utiles lorsque l’on simule des objets qui ne sont pas appelables : NonCallableMock et NonCallableMagicMock

Le décorateur patch() facilite le remplacement temporaire de classes d’un module avec un objet Mock. Par défaut patch() crée un MagicMock. On peut spécifier une classe alternative de Mock en utilisant le paramètre new_callable de patch().

class unittest.mock.Mock(spec=None, side_effect=None, return_value=DEFAULT, wraps=None, name=None, spec_set=None, unsafe=False, **kwargs)

Crée un nouvel objet Mock. Mock prend plusieurs arguments optionnels qui spécifient le comportement de l’objet Mock :

spec : une liste de chaînes de caractères ou un objet existant (une classe ou une instance) qui sert de spécification pour l’objet simulacre. Si on passe un objet, alors une liste de chaînes de caractères est formée en appelant la fonction dir sur l’objet (à l’exclusion des attributs et méthodes magiques non pris en charge). L’accès à un attribut qui n’est pas dans cette liste entraîne la levée d’une exception AttributeError.

Si spec est un objet (plutôt qu’une liste de chaînes de caractères) alors __class__ renvoie la classe de l’objet spécifié. Ceci permet aux mocks de passer les tests isinstance().

spec_set : variante plus stricte de spec. S’il est utilisé, essayer d’utiliser la fonction set ou tenter d’accéder à un attribut sur le mock qui n’est pas sur l’objet passé comme spec_set lève une exception AttributeError.

side_effect : fonction à appeler à chaque fois que le Mock est appelé. Voir l’attribut side_effect. Utile pour lever des exceptions ou modifier dynamiquement les valeurs de retour. La fonction est appelée avec les mêmes arguments que la fonction simulée et, à moins qu’elle ne renvoie DEFAULT, la valeur de retour de cette fonction devient la valeur de retour de la fonction simulée.

side_effect peut être soit une classe, soit une instance d’exception. Dans ce cas, l’exception est levée lors de l’appel de l’objet simulacre.

Si side_effect est un itérable alors chaque appel au mock renvoie la valeur suivante de l’itérable.

Utilisez None pour remettre à zéro un side_effect.

return_value : valeur renvoyée lors de l’appel de l’objet simulacre. Par défaut, il s’agit d’un nouveau Mock (créé lors du premier accès). Voir l’attribut return_value.

unsafe : par défaut, si un attribut commence par assert ou assret, une exception AttributeError est levée. Le fait de passer unsafe=True permet d’accéder à ces attributs.

Nouveau dans la version 3.5.

wraps : élément que le simulacre doit simuler. Si wraps n’est pas None alors appeler Mock passe l’appel à l’objet simulé (renvoyant le résultat réel). L’accès à un attribut sur le mock renvoie un objet Mock qui simule l’attribut correspondant de l’objet simulé (donc essayer d’accéder à un attribut qui n’existe pas lève une exception AttributeError).

Si l’objet simulacre a un ensemble explicite de return_value alors les appels ne sont pas passés à l’objet simulé et c’est return_value qui est renvoyée à la place.

name : Si le mock a un nom, il est alors utilisé par la fonction repr du mock. C’est utile pour le débogage. Le nom est propagé aux enfants de l’objet mock.

Les mocks peuvent aussi être appelés avec des arguments par mots-clés arbitraires. Ceux-ci sont utilisés pour définir les attributs sur le mock après sa création. Voir la méthode configure_mock() pour plus de détails.

assert_called(*args, **kwargs)

Asserter que le mock a été appelé au moins une fois.

>>> mock = Mock()
>>> mock.method()
<Mock name='mock.method()' id='...'>
>>> mock.method.assert_called()

Nouveau dans la version 3.6.

assert_called_once(*args, **kwargs)

Asserter que le mock a été appelé exactement une fois.

>>> mock = Mock()
>>> mock.method()
<Mock name='mock.method()' id='...'>
>>> mock.method.assert_called_once()
>>> mock.method()
<Mock name='mock.method()' id='...'>
>>> mock.method.assert_called_once()
Traceback (most recent call last):
...
AssertionError: Expected 'method' to have been called once. Called 2 times.

Nouveau dans la version 3.6.

assert_called_with(*args, **kwargs)

Cette méthode est un moyen pratique d’asserter que les appels sont effectués d’une manière particulière :

>>> mock = Mock()
>>> mock.method(1, 2, 3, test='wow')
<Mock name='mock.method()' id='...'>
>>> mock.method.assert_called_with(1, 2, 3, test='wow')

assert_called_once_with(*args, **kwargs)

Asserter que le simulacre a été appelé exactement une fois et que cet appel était avec les arguments spécifiés.

>>> mock = Mock(return_value=None)
>>> mock('foo', bar='baz')
>>> mock.assert_called_once_with('foo', bar='baz')
>>> mock('other', bar='values')
>>> mock.assert_called_once_with('other', bar='values')
Traceback (most recent call last):
  ...
AssertionError: Expected 'mock' to be called once. Called 2 times.

assert_any_call(*args, **kwargs)

Asserter que le simulacre a été appelé avec les arguments spécifiés.

Asserter que le simulacre a bien été appelé avec les arguments au cours de la vie du simulacre. Contrairement à assert_called_with() et assert_called_once_with() qui passent seulement si l’appel demandé correspond bien au dernier appel, et dans le cas de assert_called_once_with() l’appel au simulacre doit être unique.

>>> mock = Mock(return_value=None)
>>> mock(1, 2, arg='thing')
>>> mock('some', 'thing', 'else')
>>> mock.assert_any_call(1, 2, arg='thing')

assert_has_calls(calls, any_order=False)

Asserter que le simulacre a été appelé avec les appels spécifiés. L’attribut mock_calls est comparé à la liste des appels.

Si any_order est faux (la valeur par défaut) alors les appels doivent être séquentiels. Il peut y avoir des appels supplémentaires avant ou après les appels spécifiés.

Si any_order est vrai alors les appels peuvent être dans n’importe quel ordre, mais ils doivent tous apparaître dans mock_calls.

>>> mock = Mock(return_value=None)
>>> mock(1)
>>> mock(2)
>>> mock(3)
>>> mock(4)
>>> calls = [call(2), call(3)]
>>> mock.assert_has_calls(calls)
>>> calls = [call(4), call(2), call(3)]
>>> mock.assert_has_calls(calls, any_order=True)

assert_not_called()

Asserter que le simulacre n’a jamais été appelé.

>>> m = Mock()
>>> m.hello.assert_not_called()
>>> obj = m.hello()
>>> m.hello.assert_not_called()
Traceback (most recent call last):
  ...
AssertionError: Expected 'hello' to not have been called. Called 1 times.

Nouveau dans la version 3.5.

reset_mock(*, return_value=False, side_effect=False)

La méthode reset_mock réinitialise tous les attributs d’appel sur un simulacre :

>>> mock = Mock(return_value=None)
>>> mock('hello')
>>> mock.called
True
>>> mock.reset_mock()
>>> mock.called
False

Modifié dans la version 3.6: Ajout de deux arguments nommés à la fonction reset_mock.

Utile pour faire une série d’assertions qui réutilisent le même objet. Attention reset_mock() ne réinitialise pas la valeur de retour, les side_effect ou tout attribut enfant que vous avez défini en utilisant l’affectation normale par défaut. Pour réinitialiser return_value ou side_effect, utiliser les paramètres correspondants avec la valeur True. Les simulacres enfants et le simulacre de valeur de retour (le cas échéant) seront également réinitialisés.

Note

return_value, et side_effect sont utilisable uniquement par arguments nommés.

mock_add_spec(spec, spec_set=False)

Ajoute une spécification à un simulacre. spec peut être un objet ou une liste de chaînes de caractères. Seuls les attributs de la spécification spec peuvent être récupérés en tant qu’attributs du simulacre.

Si spec_set est vrai, seuls les attributs de la spécification peuvent être définis.

attach_mock(mock, attribute)

Attache un simulacre comme attribut de l’instance courante, en remplaçant son nom et son parent. Les appels au simulacre attaché sont enregistrés dans les attributs method_calls et mock_calls de l’instance courante.

configure_mock(**kwargs)

Définir les attributs sur le simulacre à l’aide d’arguments nommés.

Les attributs, les valeurs de retour et les effets de bords peuvent être définis sur des simulacres enfants en utilisant la notation par points standard et en dépaquetant un dictionnaire dans l’appel de méthode :

>>> mock = Mock()
>>> attrs = {'method.return_value': 3, 'other.side_effect': KeyError}
>>> mock.configure_mock(**attrs)
>>> mock.method()
3
>>> mock.other()
Traceback (most recent call last):
  ...
KeyError

La même chose peut être réalisée en utilisant le constructeur des simulacres :

>>> attrs = {'method.return_value': 3, 'other.side_effect': KeyError}
>>> mock = Mock(some_attribute='eggs', **attrs)
>>> mock.some_attribute
'eggs'
>>> mock.method()
3
>>> mock.other()
Traceback (most recent call last):
  ...
KeyError

configure_mock() existe pour faciliter la configuration après la création du simulacre.

__dir__()

Les objets Mock limitent les résultats de dir(un_mock) à des résultats utiles. Pour les simulacres avec une spécification spec, cela inclut tous les attributs autorisés du simulacre.

Voir FILTER_DIR pour savoir ce que fait ce filtrage, et comment le désactiver.

_get_child_mock(**kw)

Crée les simulacres enfants pour les attributs et la valeur de retour. Par défaut, les objets simulacre enfants sont du même type que le parent. Les sous-classes de Mock peuvent surcharger cette méthode pour personnaliser la façon dont les simulacres enfants sont créés.

Pour les simulacres non appelables, la variante appelable est utilisée (plutôt qu’une sous-classe personnalisée).

called

Un booléen représentant si le simulacre a bien été appelé ou non :

>>> mock = Mock(return_value=None)
>>> mock.called
False
>>> mock()
>>> mock.called
True

call_count

Un entier indiquant combien de fois le simulacre a été appelé :

>>> mock = Mock(return_value=None)
>>> mock.call_count
0
>>> mock()
>>> mock()
>>> mock.call_count
2

return_value

Définir cette option pour configurer la valeur renvoyé par appel du simulacre :

>>> mock = Mock()
>>> mock.return_value = 'fish'
>>> mock()
'fish'

La valeur de revoie par défaut est un simulacre configurable normalement :

>>> mock = Mock()
>>> mock.return_value.attribute = sentinel.Attribute
>>> mock.return_value()
<Mock name='mock()()' id='...'>
>>> mock.return_value.assert_called_with()

L’attribut return_value peut également être défini dans le constructeur :

>>> mock = Mock(return_value=3)
>>> mock.return_value
3
>>> mock()
3

side_effect

C’est soit une fonction à appeler lors de l’appel du simulacre, soit une exception (classe ou instance) à lever.

Si vous passez une fonction, elle est appelée avec les mêmes arguments que la fonction simulée et à moins que la fonction ne renvoie le singleton DEFAULT l’appel le la fonction simulée renvoie ce que la fonction renvoie. Si la fonction renvoie DEFAULT alors le simulacre renvoie sa valeur normale (celle de return_value).

Si vous passez un itérable, il est utilisé pour récupérer un itérateur qui doit renvoyer une valeur à chaque appel. Cette valeur peut être soit une instance d’exception à lever, soit une valeur à renvoyer à l’appel au simulacre (le traitement DEFAULT est identique au renvoie de la fonction simulée).

Un exemple d’un simulacre qui lève une exception (pour tester la gestion des exceptions d’une API) :

>>> mock = Mock()
>>> mock.side_effect = Exception('Boom!')
>>> mock()
Traceback (most recent call last):
  ...
Exception: Boom!

Utiliser side_effect pour renvoyer une séquence de valeurs :

>>> mock = Mock()
>>> mock.side_effect = [3, 2, 1]
>>> mock(), mock(), mock()
(3, 2, 1)

Utilisation d’un objet appelable :

>>> mock = Mock(return_value=3)
>>> def side_effect(*args, **kwargs):
...     return DEFAULT
...
>>> mock.side_effect = side_effect
>>> mock()
3

Un attribut side_effect peut être défini dans le constructeur. Voici un exemple qui ajoute un à la valeur du simulacre appelé et qui le renvoie :

>>> side_effect = lambda value: value + 1
>>> mock = Mock(side_effect=side_effect)
>>> mock(3)
4
>>> mock(-8)
-7

Positionner side_effect sur None l’efface :

>>> m = Mock(side_effect=KeyError, return_value=3)
>>> m()
Traceback (most recent call last):
 ...
KeyError
>>> m.side_effect = None
>>> m()
3

call_args

C’est soit None (si le simulacre n’a pas été appelé), soit les arguments avec lesquels le simulacre a été appelé en dernier. Le retour est sous la forme d’un tuple : le premier élément est l’ensemble des arguments ordonnés avec lequel le simulacre a été appelé (ou un tuple vide) et le second élément est l’ensemble des arguments nommés (ou un dictionnaire vide).

>>> mock = Mock(return_value=None)
>>> print(mock.call_args)
None
>>> mock()
>>> mock.call_args
call()
>>> mock.call_args == ()
True
>>> mock(3, 4)
>>> mock.call_args
call(3, 4)
>>> mock.call_args == ((3, 4),)
True
>>> mock(3, 4, 5, key='fish', next='w00t!')
>>> mock.call_args
call(3, 4, 5, key='fish', next='w00t!')

L’attribut call_args, ainsi que les éléments des listes call_args_list, method_calls et mock_calls sont des objets call. Ce sont des tuples, que l’on peut dépaqueter afin de faire des affirmations plus complexes sur chacun des arguments. Voir appels comme tuples.

call_args_list

This is a list of all the calls made to the mock object in sequence (so the length of the list is the number of times it has been called). Before any calls have been made it is an empty list. The call object can be used for conveniently constructing lists of calls to compare with call_args_list.

>>> mock = Mock(return_value=None)
>>> mock()
>>> mock(3, 4)
>>> mock(key='fish', next='w00t!')
>>> mock.call_args_list
[call(), call(3, 4), call(key='fish', next='w00t!')]
>>> expected = [(), ((3, 4),), ({'key': 'fish', 'next': 'w00t!'},)]
>>> mock.call_args_list == expected
True

Members of call_args_list are call objects. These can be unpacked as tuples to get at the individual arguments. See calls as tuples.

method_calls

As well as tracking calls to themselves, mocks also track calls to methods and attributes, and their methods and attributes:

>>> mock = Mock()
>>> mock.method()
<Mock name='mock.method()' id='...'>
>>> mock.property.method.attribute()
<Mock name='mock.property.method.attribute()' id='...'>
>>> mock.method_calls
[call.method(), call.property.method.attribute()]

Members of method_calls are call objects. These can be unpacked as tuples to get at the individual arguments. See calls as tuples.

mock_calls

mock_calls records all calls to the mock object, its methods, magic methods and return value mocks.

>>> mock = MagicMock()
>>> result = mock(1, 2, 3)
>>> mock.first(a=3)
<MagicMock name='mock.first()' id='...'>
>>> mock.second()
<MagicMock name='mock.second()' id='...'>
>>> int(mock)
1
>>> result(1)
<MagicMock name='mock()()' id='...'>
>>> expected = [call(1, 2, 3), call.first(a=3), call.second(),
... call.__int__(), call()(1)]
>>> mock.mock_calls == expected
True

Members of mock_calls are call objects. These can be unpacked as tuples to get at the individual arguments. See calls as tuples.

Note

The way mock_calls are recorded means that where nested calls are made, the parameters of ancestor calls are not recorded and so will always compare equal:

>>> mock = MagicMock()
>>> mock.top(a=3).bottom()
<MagicMock name='mock.top().bottom()' id='...'>
>>> mock.mock_calls
[call.top(a=3), call.top().bottom()]
>>> mock.mock_calls[-1] == call.top(a=-1).bottom()
True

__class__

Normally the __class__ attribute of an object will return its type. For a mock object with a spec, __class__ returns the spec class instead. This allows mock objects to pass isinstance() tests for the object they are replacing / masquerading as:

>>> mock = Mock(spec=3)
>>> isinstance(mock, int)
True

__class__ is assignable to, this allows a mock to pass an isinstance() check without forcing you to use a spec:

>>> mock = Mock()
>>> mock.__class__ = dict
>>> isinstance(mock, dict)
True

class unittest.mock.NonCallableMock(spec=None, wraps=None, name=None, spec_set=None, **kwargs)

A non-callable version of Mock. The constructor parameters have the same meaning of Mock, with the exception of return_value and side_effect which have no meaning on a non-callable mock.

Mock objects that use a class or an instance as a spec or spec_set are able to pass isinstance() tests:

>>> mock = Mock(spec=SomeClass)
>>> isinstance(mock, SomeClass)
True
>>> mock = Mock(spec_set=SomeClass())
>>> isinstance(mock, SomeClass)
True

The Mock classes have support for mocking magic methods. See magic methods for the full details.

The mock classes and the patch() decorators all take arbitrary keyword arguments for configuration. For the patch() decorators the keywords are passed to the constructor of the mock being created. The keyword arguments are for configuring attributes of the mock:

>>> m = MagicMock(attribute=3, other='fish')
>>> m.attribute
3
>>> m.other
'fish'

The return value and side effect of child mocks can be set in the same way, using dotted notation. As you can’t use dotted names directly in a call you have to create a dictionary and unpack it using **:

>>> attrs = {'method.return_value': 3, 'other.side_effect': KeyError}
>>> mock = Mock(some_attribute='eggs', **attrs)
>>> mock.some_attribute
'eggs'
>>> mock.method()
3
>>> mock.other()
Traceback (most recent call last):
  ...
KeyError

A callable mock which was created with a spec (or a spec_set) will introspect the specification object’s signature when matching calls to the mock. Therefore, it can match the actual call’s arguments regardless of whether they were passed positionally or by name:

>>> def f(a, b, c): pass
...
>>> mock = Mock(spec=f)
>>> mock(1, 2, c=3)
<Mock name='mock()' id='140161580456576'>
>>> mock.assert_called_with(1, 2, 3)
>>> mock.assert_called_with(a=1, b=2, c=3)

This applies to assert_called_with(), assert_called_once_with(), assert_has_calls() and assert_any_call(). When Autospeccing, it will also apply to method calls on the mock object.

Modifié dans la version 3.4: Added signature introspection on specced and autospecced mock objects.

class unittest.mock.PropertyMock(*args, **kwargs)

A mock intended to be used as a property, or other descriptor, on a class. PropertyMock provides __get__() and __set__() methods so you can specify a return value when it is fetched.

Fetching a PropertyMock instance from an object calls the mock, with no args. Setting it calls the mock with the value being set.

>>> class Foo:
...     @property
...     def foo(self):
...         return 'something'
...     @foo.setter
...     def foo(self, value):
...         pass
...
>>> with patch('__main__.Foo.foo', new_callable=PropertyMock) as mock_foo:
...     mock_foo.return_value = 'mockity-mock'
...     this_foo = Foo()
...     print(this_foo.foo)
...     this_foo.foo = 6
...
mockity-mock
>>> mock_foo.mock_calls
[call(), call(6)]

Because of the way mock attributes are stored you can’t directly attach a PropertyMock to a mock object. Instead you can attach it to the mock type object:

>>> m = MagicMock()
>>> p = PropertyMock(return_value=3)
>>> type(m).foo = p
>>> m.foo
3
>>> p.assert_called_once_with()

26.5.2.1. Calling

Mock objects are callable. The call will return the value set as the return_value attribute. The default return value is a new Mock object; it is created the first time the return value is accessed (either explicitly or by calling the Mock) - but it is stored and the same one returned each time.

Calls made to the object will be recorded in the attributes like call_args and call_args_list.

If side_effect is set then it will be called after the call has been recorded, so if side_effect raises an exception the call is still recorded.

The simplest way to make a mock raise an exception when called is to make side_effect an exception class or instance:

>>> m = MagicMock(side_effect=IndexError)
>>> m(1, 2, 3)
Traceback (most recent call last):
  ...
IndexError
>>> m.mock_calls
[call(1, 2, 3)]
>>> m.side_effect = KeyError('Bang!')
>>> m('two', 'three', 'four')
Traceback (most recent call last):
  ...
KeyError: 'Bang!'
>>> m.mock_calls
[call(1, 2, 3), call('two', 'three', 'four')]

If side_effect is a function then whatever that function returns is what calls to the mock return. The side_effect function is called with the same arguments as the mock. This allows you to vary the return value of the call dynamically, based on the input:

>>> def side_effect(value):
...     return value + 1
...
>>> m = MagicMock(side_effect=side_effect)
>>> m(1)
2
>>> m(2)
3
>>> m.mock_calls
[call(1), call(2)]

If you want the mock to still return the default return value (a new mock), or any set return value, then there are two ways of doing this. Either return mock.return_value from inside side_effect, or return DEFAULT:

>>> m = MagicMock()
>>> def side_effect(*args, **kwargs):
...     return m.return_value
...
>>> m.side_effect = side_effect
>>> m.return_value = 3
>>> m()
3
>>> def side_effect(*args, **kwargs):
...     return DEFAULT
...
>>> m.side_effect = side_effect
>>> m()
3

To remove a side_effect, and return to the default behaviour, set the side_effect to None:

>>> m = MagicMock(return_value=6)
>>> def side_effect(*args, **kwargs):
...     return 3
...
>>> m.side_effect = side_effect
>>> m()
3
>>> m.side_effect = None
>>> m()
6

The side_effect can also be any iterable object. Repeated calls to the mock will return values from the iterable (until the iterable is exhausted and a StopIteration is raised):

>>> m = MagicMock(side_effect=[1, 2, 3])
>>> m()
1
>>> m()
2
>>> m()
3
>>> m()
Traceback (most recent call last):
  ...
StopIteration

If any members of the iterable are exceptions they will be raised instead of returned:

>>> iterable = (33, ValueError, 66)
>>> m = MagicMock(side_effect=iterable)
>>> m()
33
>>> m()
Traceback (most recent call last):
 ...
ValueError
>>> m()
66

26.5.2.2. Deleting Attributes

Mock objects create attributes on demand. This allows them to pretend to be objects of any type.

You may want a mock object to return False to a hasattr() call, or raise an AttributeError when an attribute is fetched. You can do this by providing an object as a spec for a mock, but that isn’t always convenient.

You « block » attributes by deleting them. Once deleted, accessing an attribute will raise an AttributeError.

>>> mock = MagicMock()
>>> hasattr(mock, 'm')
True
>>> del mock.m
>>> hasattr(mock, 'm')
False
>>> del mock.f
>>> mock.f
Traceback (most recent call last):
    ...
AttributeError: f

26.5.2.3. Mock names and the name attribute

Since « name » is an argument to the Mock constructor, if you want your mock object to have a « name » attribute you can’t just pass it in at creation time. There are two alternatives. One option is to use configure_mock():

>>> mock = MagicMock()
>>> mock.configure_mock(name='my_name')
>>> mock.name
'my_name'

A simpler option is to simply set the « name » attribute after mock creation:

>>> mock = MagicMock()
>>> mock.name = "foo"

26.5.2.4. Attaching Mocks as Attributes

When you attach a mock as an attribute of another mock (or as the return value) it becomes a « child » of that mock. Calls to the child are recorded in the method_calls and mock_calls attributes of the parent. This is useful for configuring child mocks and then attaching them to the parent, or for attaching mocks to a parent that records all calls to the children and allows you to make assertions about the order of calls between mocks:

>>> parent = MagicMock()
>>> child1 = MagicMock(return_value=None)
>>> child2 = MagicMock(return_value=None)
>>> parent.child1 = child1
>>> parent.child2 = child2
>>> child1(1)
>>> child2(2)
>>> parent.mock_calls
[call.child1(1), call.child2(2)]

The exception to this is if the mock has a name. This allows you to prevent the « parenting » if for some reason you don’t want it to happen.

>>> mock = MagicMock()
>>> not_a_child = MagicMock(name='not-a-child')
>>> mock.attribute = not_a_child
>>> mock.attribute()
<MagicMock name='not-a-child()' id='...'>
>>> mock.mock_calls
[]

Mocks created for you by patch() are automatically given names. To attach mocks that have names to a parent you use the attach_mock() method:

>>> thing1 = object()
>>> thing2 = object()
>>> parent = MagicMock()
>>> with patch('__main__.thing1', return_value=None) as child1:
...     with patch('__main__.thing2', return_value=None) as child2:
...         parent.attach_mock(child1, 'child1')
...         parent.attach_mock(child2, 'child2')
...         child1('one')
...         child2('two')
...
>>> parent.mock_calls
[call.child1('one'), call.child2('two')]

1

The only exceptions are magic methods and attributes (those that have leading and trailing double underscores). Mock doesn’t create these but instead raises an AttributeError. This is because the interpreter will often implicitly request these methods, and gets very confused to get a new Mock object when it expects a magic method. If you need magic method support see magic methods.

26.5.3. The patchers

The patch decorators are used for patching objects only within the scope of the function they decorate. They automatically handle the unpatching for you, even if exceptions are raised. All of these functions can also be used in with statements or as class decorators.

26.5.3.1. patch

Note

patch() is straightforward to use. The key is to do the patching in the right namespace. See the section where to patch.

unittest.mock.patch(target, new=DEFAULT, spec=None, create=False, spec_set=None, autospec=None, new_callable=None, **kwargs)

patch() acts as a function decorator, class decorator or a context manager. Inside the body of the function or with statement, the target is patched with a new object. When the function/with statement exits the patch is undone.

If new is omitted, then the target is replaced with a MagicMock. If patch() is used as a decorator and new is omitted, the created mock is passed in as an extra argument to the decorated function. If patch() is used as a context manager the created mock is returned by the context manager.

target should be a string in the form 'package.module.ClassName'. The target is imported and the specified object replaced with the new object, so the target must be importable from the environment you are calling patch() from. The target is imported when the decorated function is executed, not at decoration time.

The spec and spec_set keyword arguments are passed to the MagicMock if patch is creating one for you.

In addition you can pass spec=True or spec_set=True, which causes patch to pass in the object being mocked as the spec/spec_set object.

new_callable allows you to specify a different class, or callable object, that will be called to create the new object. By default MagicMock is used.

A more powerful form of spec is autospec. If you set autospec=True then the mock will be created with a spec from the object being replaced. All attributes of the mock will also have the spec of the corresponding attribute of the object being replaced. Methods and functions being mocked will have their arguments checked and will raise a TypeError if they are called with the wrong signature. For mocks replacing a class, their return value (the “instance”) will have the same spec as the class. See the create_autospec() function and Autospeccing.

Instead of autospec=True you can pass autospec=some_object to use an arbitrary object as the spec instead of the one being replaced.

By default patch() will fail to replace attributes that don’t exist. If you pass in create=True, and the attribute doesn’t exist, patch will create the attribute for you when the patched function is called, and delete it again afterwards. This is useful for writing tests against attributes that your production code creates at runtime. It is off by default because it can be dangerous. With it switched on you can write passing tests against APIs that don’t actually exist!

Note

Modifié dans la version 3.5: If you are patching builtins in a module then you don’t need to pass create=True, it will be added by default.

Patch can be used as a TestCase class decorator. It works by decorating each test method in the class. This reduces the boilerplate code when your test methods share a common patchings set. patch() finds tests by looking for method names that start with patch.TEST_PREFIX. By default this is 'test', which matches the way unittest finds tests. You can specify an alternative prefix by setting patch.TEST_PREFIX.

Patch can be used as a context manager, with the with statement. Here the patching applies to the indented block after the with statement. If you use « as » then the patched object will be bound to the name after the « as »; very useful if patch() is creating a mock object for you.

patch() takes arbitrary keyword arguments. These will be passed to the Mock (or new_callable) on construction.

patch.dict(...), patch.multiple(...) and patch.object(...) are available for alternate use-cases.

patch() as function decorator, creating the mock for you and passing it into the decorated function:

>>> @patch('__main__.SomeClass')
... def function(normal_argument, mock_class):
...     print(mock_class is SomeClass)
...
>>> function(None)
True

Patching a class replaces the class with a MagicMock instance. If the class is instantiated in the code under test then it will be the return_value of the mock that will be used.

If the class is instantiated multiple times you could use side_effect to return a new mock each time. Alternatively you can set the return_value to be anything you want.

To configure return values on methods of instances on the patched class you must do this on the return_value. For example:

>>> class Class:
...     def method(self):
...         pass
...
>>> with patch('__main__.Class') as MockClass:
...     instance = MockClass.return_value
...     instance.method.return_value = 'foo'
...     assert Class() is instance
...     assert Class().method() == 'foo'
...

If you use spec or spec_set and patch() is replacing a class, then the return value of the created mock will have the same spec.

>>> Original = Class
>>> patcher = patch('__main__.Class', spec=True)
>>> MockClass = patcher.start()
>>> instance = MockClass()
>>> assert isinstance(instance, Original)
>>> patcher.stop()

The new_callable argument is useful where you want to use an alternative class to the default MagicMock for the created mock. For example, if you wanted a NonCallableMock to be used:

>>> thing = object()
>>> with patch('__main__.thing', new_callable=NonCallableMock) as mock_thing:
...     assert thing is mock_thing
...     thing()
...
Traceback (most recent call last):
  ...
TypeError: 'NonCallableMock' object is not callable

Another use case might be to replace an object with an io.StringIO instance:

>>> from io import StringIO
>>> def foo():
...     print('Something')
...
>>> @patch('sys.stdout', new_callable=StringIO)
... def test(mock_stdout):
...     foo()
...     assert mock_stdout.getvalue() == 'Something\n'
...
>>> test()

When patch() is creating a mock for you, it is common that the first thing you need to do is to configure the mock. Some of that configuration can be done in the call to patch. Any arbitrary keywords you pass into the call will be used to set attributes on the created mock:

>>> patcher = patch('__main__.thing', first='one', second='two')
>>> mock_thing = patcher.start()
>>> mock_thing.first
'one'
>>> mock_thing.second
'two'

As well as attributes on the created mock attributes, like the return_value and side_effect, of child mocks can also be configured. These aren’t syntactically valid to pass in directly as keyword arguments, but a dictionary with these as keys can still be expanded into a patch() call using **:

>>> config = {'method.return_value': 3, 'other.side_effect': KeyError}
>>> patcher = patch('__main__.thing', **config)
>>> mock_thing = patcher.start()
>>> mock_thing.method()
3
>>> mock_thing.other()
Traceback (most recent call last):
  ...
KeyError

26.5.3.2. patch.object

patch.object(target, attribute, new=DEFAULT, spec=None, create=False, spec_set=None, autospec=None, new_callable=None, **kwargs)

patch the named member (attribute) on an object (target) with a mock object.

patch.object() can be used as a decorator, class decorator or a context manager. Arguments new, spec, create, spec_set, autospec and new_callable have the same meaning as for patch(). Like patch(), patch.object() takes arbitrary keyword arguments for configuring the mock object it creates.

When used as a class decorator patch.object() honours patch.TEST_PREFIX for choosing which methods to wrap.

You can either call patch.object() with three arguments or two arguments. The three argument form takes the object to be patched, the attribute name and the object to replace the attribute with.

When calling with the two argument form you omit the replacement object, and a mock is created for you and passed in as an extra argument to the decorated function:

>>> @patch.object(SomeClass, 'class_method')
... def test(mock_method):
...     SomeClass.class_method(3)
...     mock_method.assert_called_with(3)
...
>>> test()

spec, create and the other arguments to patch.object() have the same meaning as they do for patch().

26.5.3.3. patch.dict

patch.dict(in_dict, values=(), clear=False, **kwargs)

Patch a dictionary, or dictionary like object, and restore the dictionary to its original state after the test.

in_dict can be a dictionary or a mapping like container. If it is a mapping then it must at least support getting, setting and deleting items plus iterating over keys.

in_dict can also be a string specifying the name of the dictionary, which will then be fetched by importing it.

values can be a dictionary of values to set in the dictionary. values can also be an iterable of (key, value) pairs.

If clear is true then the dictionary will be cleared before the new values are set.

patch.dict() can also be called with arbitrary keyword arguments to set values in the dictionary.

patch.dict() can be used as a context manager, decorator or class decorator. When used as a class decorator patch.dict() honours patch.TEST_PREFIX for choosing which methods to wrap.

patch.dict() can be used to add members to a dictionary, or simply let a test change a dictionary, and ensure the dictionary is restored when the test ends.

>>> foo = {}
>>> with patch.dict(foo, {'newkey': 'newvalue'}):
...     assert foo == {'newkey': 'newvalue'}
...
>>> assert foo == {}

>>> import os
>>> with patch.dict('os.environ', {'newkey': 'newvalue'}):
...     print(os.environ['newkey'])
...
newvalue
>>> assert 'newkey' not in os.environ

Keywords can be used in the patch.dict() call to set values in the dictionary:

>>> mymodule = MagicMock()
>>> mymodule.function.return_value = 'fish'
>>> with patch.dict('sys.modules', mymodule=mymodule):
...     import mymodule
...     mymodule.function('some', 'args')
...
'fish'

patch.dict() can be used with dictionary like objects that aren’t actually dictionaries. At the very minimum they must support item getting, setting, deleting and either iteration or membership test. This corresponds to the magic methods __getitem__(), __setitem__(), __delitem__() and either __iter__() or __contains__().

>>> class Container:
...     def __init__(self):
...         self.values = {}
...     def __getitem__(self, name):
...         return self.values[name]
...     def __setitem__(self, name, value):
...         self.values[name] = value
...     def __delitem__(self, name):
...         del self.values[name]
...     def __iter__(self):
...         return iter(self.values)
...
>>> thing = Container()
>>> thing['one'] = 1
>>> with patch.dict(thing, one=2, two=3):
...     assert thing['one'] == 2
...     assert thing['two'] == 3
...
>>> assert thing['one'] == 1
>>> assert list(thing) == ['one']

26.5.3.4. patch.multiple

patch.multiple(target, spec=None, create=False, spec_set=None, autospec=None, new_callable=None, **kwargs)

Perform multiple patches in a single call. It takes the object to be patched (either as an object or a string to fetch the object by importing) and keyword arguments for the patches:

with patch.multiple(settings, FIRST_PATCH='one', SECOND_PATCH='two'):
    ...

Use DEFAULT as the value if you want patch.multiple() to create mocks for you. In this case the created mocks are passed into a decorated function by keyword, and a dictionary is returned when patch.multiple() is used as a context manager.

patch.multiple() can be used as a decorator, class decorator or a context manager. The arguments spec, spec_set, create, autospec and new_callable have the same meaning as for patch(). These arguments will be applied to all patches done by patch.multiple().

When used as a class decorator patch.multiple() honours patch.TEST_PREFIX for choosing which methods to wrap.

If you want patch.multiple() to create mocks for you, then you can use DEFAULT as the value. If you use patch.multiple() as a decorator then the created mocks are passed into the decorated function by keyword.

>>> thing = object()
>>> other = object()

>>> @patch.multiple('__main__', thing=DEFAULT, other=DEFAULT)
... def test_function(thing, other):
...     assert isinstance(thing, MagicMock)
...     assert isinstance(other, MagicMock)
...
>>> test_function()

patch.multiple() can be nested with other patch decorators, but put arguments passed by keyword after any of the standard arguments created by patch():

>>> @patch('sys.exit')
... @patch.multiple('__main__', thing=DEFAULT, other=DEFAULT)
... def test_function(mock_exit, other, thing):
...     assert 'other' in repr(other)
...     assert 'thing' in repr(thing)
...     assert 'exit' in repr(mock_exit)
...
>>> test_function()

If patch.multiple() is used as a context manager, the value returned by the context manger is a dictionary where created mocks are keyed by name:

>>> with patch.multiple('__main__', thing=DEFAULT, other=DEFAULT) as values:
...     assert 'other' in repr(values['other'])
...     assert 'thing' in repr(values['thing'])
...     assert values['thing'] is thing
...     assert values['other'] is other
...

26.5.3.5. patch methods: start and stop

All the patchers have start() and stop() methods. These make it simpler to do patching in setUp methods or where you want to do multiple patches without nesting decorators or with statements.

To use them call patch(), patch.object() or patch.dict() as normal and keep a reference to the returned patcher object. You can then call start() to put the patch in place and stop() to undo it.

If you are using patch() to create a mock for you then it will be returned by the call to patcher.start.

>>> patcher = patch('package.module.ClassName')
>>> from package import module
>>> original = module.ClassName
>>> new_mock = patcher.start()
>>> assert module.ClassName is not original
>>> assert module.ClassName is new_mock
>>> patcher.stop()
>>> assert module.ClassName is original
>>> assert module.ClassName is not new_mock

A typical use case for this might be for doing multiple patches in the setUp method of a TestCase:

>>> class MyTest(TestCase):
...     def setUp(self):
...         self.patcher1 = patch('package.module.Class1')
...         self.patcher2 = patch('package.module.Class2')
...         self.MockClass1 = self.patcher1.start()
...         self.MockClass2 = self.patcher2.start()
...
...     def tearDown(self):
...         self.patcher1.stop()
...         self.patcher2.stop()
...
...     def test_something(self):
...         assert package.module.Class1 is self.MockClass1
...         assert package.module.Class2 is self.MockClass2
...
>>> MyTest('test_something').run()

Prudence

If you use this technique you must ensure that the patching is « undone » by calling stop. This can be fiddlier than you might think, because if an exception is raised in the setUp then tearDown is not called. unittest.TestCase.addCleanup() makes this easier:

>>> class MyTest(TestCase):
...     def setUp(self):
...         patcher = patch('package.module.Class')
...         self.MockClass = patcher.start()
...         self.addCleanup(patcher.stop)
...
...     def test_something(self):
...         assert package.module.Class is self.MockClass
...

As an added bonus you no longer need to keep a reference to the patcher object.

It is also possible to stop all patches which have been started by using patch.stopall().

patch.stopall()

Stop all active patches. Only stops patches started with start.

26.5.3.6. patch builtins

You can patch any builtins within a module. The following example patches builtin ord():

>>> @patch('__main__.ord')
... def test(mock_ord):
...     mock_ord.return_value = 101
...     print(ord('c'))
...
>>> test()
101

26.5.3.7. TEST_PREFIX

All of the patchers can be used as class decorators. When used in this way they wrap every test method on the class. The patchers recognise methods that start with 'test' as being test methods. This is the same way that the unittest.TestLoader finds test methods by default.

It is possible that you want to use a different prefix for your tests. You can inform the patchers of the different prefix by setting patch.TEST_PREFIX:

>>> patch.TEST_PREFIX = 'foo'
>>> value = 3
>>>
>>> @patch('__main__.value', 'not three')
... class Thing:
...     def foo_one(self):
...         print(value)
...     def foo_two(self):
...         print(value)
...
>>>
>>> Thing().foo_one()
not three
>>> Thing().foo_two()
not three
>>> value
3

26.5.3.8. Nesting Patch Decorators

If you want to perform multiple patches then you can simply stack up the decorators.

You can stack up multiple patch decorators using this pattern:

>>> @patch.object(SomeClass, 'class_method')
... @patch.object(SomeClass, 'static_method')
... def test(mock1, mock2):
...     assert SomeClass.static_method is mock1
...     assert SomeClass.class_method is mock2
...     SomeClass.static_method('foo')
...     SomeClass.class_method('bar')
...     return mock1, mock2
...
>>> mock1, mock2 = test()
>>> mock1.assert_called_once_with('foo')
>>> mock2.assert_called_once_with('bar')

Note that the decorators are applied from the bottom upwards. This is the standard way that Python applies decorators. The order of the created mocks passed into your test function matches this order.

26.5.3.9. Where to patch

patch() works by (temporarily) changing the object that a name points to with another one. There can be many names pointing to any individual object, so for patching to work you must ensure that you patch the name used by the system under test.

The basic principle is that you patch where an object is looked up, which is not necessarily the same place as where it is defined. A couple of examples will help to clarify this.

Imagine we have a project that we want to test with the following structure:

a.py
    -> Defines SomeClass

b.py
    -> from a import SomeClass
    -> some_function instantiates SomeClass

Now we want to test some_function but we want to mock out SomeClass using patch(). The problem is that when we import module b, which we will have to do then it imports SomeClass from module a. If we use patch() to mock out a.SomeClass then it will have no effect on our test; module b already has a reference to the real SomeClass and it looks like our patching had no effect.

The key is to patch out SomeClass where it is used (or where it is looked up ). In this case some_function will actually look up SomeClass in module b, where we have imported it. The patching should look like:

@patch('b.SomeClass')

However, consider the alternative scenario where instead of from a import SomeClass module b does import a and some_function uses a.SomeClass. Both of these import forms are common. In this case the class we want to patch is being looked up in the module and so we have to patch a.SomeClass instead:

@patch('a.SomeClass')

26.5.3.10. Patching Descriptors and Proxy Objects

Both patch and patch.object correctly patch and restore descriptors: class methods, static methods and properties. You should patch these on the class rather than an instance. They also work with some objects that proxy attribute access, like the django settings object [http://www.voidspace.org.uk/python/weblog/arch_d7_2010_12_04.shtml#e1198].

26.5.4. MagicMock and magic method support

26.5.4.1. Mocking Magic Methods

Mock supports mocking the Python protocol methods, also known as « magic methods ». This allows mock objects to replace containers or other objects that implement Python protocols.

Because magic methods are looked up differently from normal methods 2, this support has been specially implemented. This means that only specific magic methods are supported. The supported list includes almost all of them. If there are any missing that you need please let us know.

You mock magic methods by setting the method you are interested in to a function or a mock instance. If you are using a function then it must take self as the first argument 3.

>>> def __str__(self):
...     return 'fooble'
...
>>> mock = Mock()
>>> mock.__str__ = __str__
>>> str(mock)
'fooble'

>>> mock = Mock()
>>> mock.__str__ = Mock()
>>> mock.__str__.return_value = 'fooble'
>>> str(mock)
'fooble'

>>> mock = Mock()
>>> mock.__iter__ = Mock(return_value=iter([]))
>>> list(mock)
[]

One use case for this is for mocking objects used as context managers in a with statement:

>>> mock = Mock()
>>> mock.__enter__ = Mock(return_value='foo')
>>> mock.__exit__ = Mock(return_value=False)
>>> with mock as m:
...     assert m == 'foo'
...
>>> mock.__enter__.assert_called_with()
>>> mock.__exit__.assert_called_with(None, None, None)

Calls to magic methods do not appear in method_calls, but they are recorded in mock_calls.

Note

If you use the spec keyword argument to create a mock then attempting to set a magic method that isn’t in the spec will raise an AttributeError.

The full list of supported magic methods is:

__hash__, __sizeof__, __repr__ and __str__

__dir__, __format__ et __subclasses__

__floor__, __trunc__ et __ceil__

Comparisons: __lt__, __gt__, __le__, __ge__, __eq__ and __ne__

Container methods: __getitem__, __setitem__, __delitem__, __contains__, __len__, __iter__, __reversed__ and __missing__

Context manager: __enter__ and __exit__

Unary numeric methods: __neg__, __pos__ and __invert__

The numeric methods (including right hand and in-place variants): __add__, __sub__, __mul__, __matmul__, __div__, __truediv__, __floordiv__, __mod__, __divmod__, __lshift__, __rshift__, __and__, __xor__, __or__, and __pow__

Numeric conversion methods: __complex__, __int__, __float__ and __index__

Descriptor methods: __get__, __set__ and __delete__

Pickling: __reduce__, __reduce_ex__, __getinitargs__, __getnewargs__, __getstate__ and __setstate__

The following methods exist but are not supported as they are either in use by mock, can’t be set dynamically, or can cause problems:

__getattr__, __setattr__, __init__ and __new__

__prepare__, __instancecheck__, __subclasscheck__, __del__

26.5.4.2. Magic Mock

There are two MagicMock variants: MagicMock and NonCallableMagicMock.

class unittest.mock.MagicMock(*args, **kw)

MagicMock is a subclass of Mock with default implementations of most of the magic methods. You can use MagicMock without having to configure the magic methods yourself.

The constructor parameters have the same meaning as for Mock.

If you use the spec or spec_set arguments then only magic methods that exist in the spec will be created.

class unittest.mock.NonCallableMagicMock(*args, **kw)

A non-callable version of MagicMock.

The constructor parameters have the same meaning as for MagicMock, with the exception of return_value and side_effect which have no meaning on a non-callable mock.

The magic methods are setup with MagicMock objects, so you can configure them and use them in the usual way:

>>> mock = MagicMock()
>>> mock[3] = 'fish'
>>> mock.__setitem__.assert_called_with(3, 'fish')
>>> mock.__getitem__.return_value = 'result'
>>> mock[2]
'result'

By default many of the protocol methods are required to return objects of a specific type. These methods are preconfigured with a default return value, so that they can be used without you having to do anything if you aren’t interested in the return value. You can still set the return value manually if you want to change the default.

Methods and their defaults:

__lt__: NotImplemented

__gt__: NotImplemented

__le__: NotImplemented

__ge__: NotImplemented

__int__: 1

__contains__: False

__len__: 0

__iter__: iter([])

__exit__: False

__complex__: 1j

__float__: 1.0

__bool__: True

__index__: 1

__hash__: default hash for the mock

__str__: default str for the mock

__sizeof__: default sizeof for the mock

Par exemple :

>>> mock = MagicMock()
>>> int(mock)
1
>>> len(mock)
0
>>> list(mock)
[]
>>> object() in mock
False

The two equality methods, __eq__() and __ne__(), are special. They do the default equality comparison on identity, using the side_effect attribute, unless you change their return value to return something else:

>>> MagicMock() == 3
False
>>> MagicMock() != 3
True
>>> mock = MagicMock()
>>> mock.__eq__.return_value = True
>>> mock == 3
True

The return value of MagicMock.__iter__() can be any iterable object and isn’t required to be an iterator:

>>> mock = MagicMock()
>>> mock.__iter__.return_value = ['a', 'b', 'c']
>>> list(mock)
['a', 'b', 'c']
>>> list(mock)
['a', 'b', 'c']

If the return value is an iterator, then iterating over it once will consume it and subsequent iterations will result in an empty list:

>>> mock.__iter__.return_value = iter(['a', 'b', 'c'])
>>> list(mock)
['a', 'b', 'c']
>>> list(mock)
[]

MagicMock has all of the supported magic methods configured except for some of the obscure and obsolete ones. You can still set these up if you want.

Magic methods that are supported but not setup by default in MagicMock are:

__subclasses__

__dir__

__format__

__get__, __set__ et __delete__

__reversed__ et __missing__

__reduce__, __reduce_ex__, __getinitargs__, __getnewargs__, __getstate__ and __setstate__

__getformat__ et __setformat__

2

Magic methods should be looked up on the class rather than the instance. Different versions of Python are inconsistent about applying this rule. The supported protocol methods should work with all supported versions of Python.

3

The function is basically hooked up to the class, but each Mock instance is kept isolated from the others.

26.5.5. Helpers

26.5.5.1. sentinel

unittest.mock.sentinel

The sentinel object provides a convenient way of providing unique objects for your tests.

Attributes are created on demand when you access them by name. Accessing the same attribute will always return the same object. The objects returned have a sensible repr so that test failure messages are readable.

The sentinel attributes don’t preserve their identity when they are copied or pickled.

Sometimes when testing you need to test that a specific object is passed as an argument to another method, or returned. It can be common to create named sentinel objects to test this. sentinel provides a convenient way of creating and testing the identity of objects like this.

In this example we monkey patch method to return sentinel.some_object:

>>> real = ProductionClass()
>>> real.method = Mock(name="method")
>>> real.method.return_value = sentinel.some_object
>>> result = real.method()
>>> assert result is sentinel.some_object
>>> sentinel.some_object
sentinel.some_object

26.5.5.2. DEFAULT

unittest.mock.DEFAULT

The DEFAULT object is a pre-created sentinel (actually sentinel.DEFAULT). It can be used by side_effect functions to indicate that the normal return value should be used.

26.5.5.3. call

unittest.mock.call(*args, **kwargs)

call() is a helper object for making simpler assertions, for comparing with call_args, call_args_list, mock_calls and method_calls. call() can also be used with assert_has_calls().

>>> m = MagicMock(return_value=None)
>>> m(1, 2, a='foo', b='bar')
>>> m()
>>> m.call_args_list == [call(1, 2, a='foo', b='bar'), call()]
True

call.call_list()

For a call object that represents multiple calls, call_list() returns a list of all the intermediate calls as well as the final call.

call_list is particularly useful for making assertions on « chained calls ». A chained call is multiple calls on a single line of code. This results in multiple entries in mock_calls on a mock. Manually constructing the sequence of calls can be tedious.

call_list() can construct the sequence of calls from the same chained call:

>>> m = MagicMock()
>>> m(1).method(arg='foo').other('bar')(2.0)
<MagicMock name='mock().method().other()()' id='...'>
>>> kall = call(1).method(arg='foo').other('bar')(2.0)
>>> kall.call_list()
[call(1),
 call().method(arg='foo'),
 call().method().other('bar'),
 call().method().other()(2.0)]
>>> m.mock_calls == kall.call_list()
True

A call object is either a tuple of (positional args, keyword args) or (name, positional args, keyword args) depending on how it was constructed. When you construct them yourself this isn’t particularly interesting, but the call objects that are in the Mock.call_args, Mock.call_args_list and Mock.mock_calls attributes can be introspected to get at the individual arguments they contain.

The call objects in Mock.call_args and Mock.call_args_list are two-tuples of (positional args, keyword args) whereas the call objects in Mock.mock_calls, along with ones you construct yourself, are three-tuples of (name, positional args, keyword args).

You can use their « tupleness » to pull out the individual arguments for more complex introspection and assertions. The positional arguments are a tuple (an empty tuple if there are no positional arguments) and the keyword arguments are a dictionary:

>>> m = MagicMock(return_value=None)
>>> m(1, 2, 3, arg='one', arg2='two')
>>> kall = m.call_args
>>> args, kwargs = kall
>>> args
(1, 2, 3)
>>> kwargs
{'arg2': 'two', 'arg': 'one'}
>>> args is kall[0]
True
>>> kwargs is kall[1]
True

>>> m = MagicMock()
>>> m.foo(4, 5, 6, arg='two', arg2='three')
<MagicMock name='mock.foo()' id='...'>
>>> kall = m.mock_calls[0]
>>> name, args, kwargs = kall
>>> name
'foo'
>>> args
(4, 5, 6)
>>> kwargs
{'arg2': 'three', 'arg': 'two'}
>>> name is m.mock_calls[0][0]
True

26.5.5.4. create_autospec

unittest.mock.create_autospec(spec, spec_set=False, instance=False, **kwargs)

Create a mock object using another object as a spec. Attributes on the mock will use the corresponding attribute on the spec object as their spec.

Functions or methods being mocked will have their arguments checked to ensure that they are called with the correct signature.

If spec_set is True then attempting to set attributes that don’t exist on the spec object will raise an AttributeError.

If a class is used as a spec then the return value of the mock (the instance of the class) will have the same spec. You can use a class as the spec for an instance object by passing instance=True. The returned mock will only be callable if instances of the mock are callable.

create_autospec() also takes arbitrary keyword arguments that are passed to the constructor of the created mock.

See Autospeccing for examples of how to use auto-speccing with create_autospec() and the autospec argument to patch().

26.5.5.5. ANY

unittest.mock.ANY

Sometimes you may need to make assertions about some of the arguments in a call to mock, but either not care about some of the arguments or want to pull them individually out of call_args and make more complex assertions on them.

To ignore certain arguments you can pass in objects that compare equal to everything. Calls to assert_called_with() and assert_called_once_with() will then succeed no matter what was passed in.

>>> mock = Mock(return_value=None)
>>> mock('foo', bar=object())
>>> mock.assert_called_once_with('foo', bar=ANY)

ANY can also be used in comparisons with call lists like mock_calls:

>>> m = MagicMock(return_value=None)
>>> m(1)
>>> m(1, 2)
>>> m(object())
>>> m.mock_calls == [call(1), call(1, 2), ANY]
True

26.5.5.6. FILTER_DIR

unittest.mock.FILTER_DIR

FILTER_DIR is a module level variable that controls the way mock objects respond to dir() (only for Python 2.6 or more recent). The default is True, which uses the filtering described below, to only show useful members. If you dislike this filtering, or need to switch it off for diagnostic purposes, then set mock.FILTER_DIR = False.

With filtering on, dir(some_mock) shows only useful attributes and will include any dynamically created attributes that wouldn’t normally be shown. If the mock was created with a spec (or autospec of course) then all the attributes from the original are shown, even if they haven’t been accessed yet:

>>> dir(Mock())
['assert_any_call',
 'assert_called_once_with',
 'assert_called_with',
 'assert_has_calls',
 'attach_mock',
 ...
>>> from urllib import request
>>> dir(Mock(spec=request))
['AbstractBasicAuthHandler',
 'AbstractDigestAuthHandler',
 'AbstractHTTPHandler',
 'BaseHandler',
 ...

Many of the not-very-useful (private to Mock rather than the thing being mocked) underscore and double underscore prefixed attributes have been filtered from the result of calling dir() on a Mock. If you dislike this behaviour you can switch it off by setting the module level switch FILTER_DIR:

>>> from unittest import mock
>>> mock.FILTER_DIR = False
>>> dir(mock.Mock())
['_NonCallableMock__get_return_value',
 '_NonCallableMock__get_side_effect',
 '_NonCallableMock__return_value_doc',
 '_NonCallableMock__set_return_value',
 '_NonCallableMock__set_side_effect',
 '__call__',
 '__class__',
 ...

Alternatively you can just use vars(my_mock) (instance members) and dir(type(my_mock)) (type members) to bypass the filtering irrespective of mock.FILTER_DIR.

26.5.5.7. mock_open

unittest.mock.mock_open(mock=None, read_data=None)

A helper function to create a mock to replace the use of open(). It works for open() called directly or used as a context manager.

The mock argument is the mock object to configure. If None (the default) then a MagicMock will be created for you, with the API limited to methods or attributes available on standard file handles.

read_data is a string for the read(), readline(), and readlines() methods of the file handle to return. Calls to those methods will take data from read_data until it is depleted. The mock of these methods is pretty simplistic: every time the mock is called, the read_data is rewound to the start. If you need more control over the data that you are feeding to the tested code you will need to customize this mock for yourself. When that is insufficient, one of the in-memory filesystem packages on PyPI [https://pypi.org] can offer a realistic filesystem for testing.

Modifié dans la version 3.4: Added readline() and readlines() support. The mock of read() changed to consume read_data rather than returning it on each call.

Modifié dans la version 3.5: read_data is now reset on each call to the mock.

Using open() as a context manager is a great way to ensure your file handles are closed properly and is becoming common:

with open('/some/path', 'w') as f:
    f.write('something')

The issue is that even if you mock out the call to open() it is the returned object that is used as a context manager (and has __enter__() and __exit__() called).

Mocking context managers with a MagicMock is common enough and fiddly enough that a helper function is useful.

>>> m = mock_open()
>>> with patch('__main__.open', m):
...     with open('foo', 'w') as h:
...         h.write('some stuff')
...
>>> m.mock_calls
[call('foo', 'w'),
 call().__enter__(),
 call().write('some stuff'),
 call().__exit__(None, None, None)]
>>> m.assert_called_once_with('foo', 'w')
>>> handle = m()
>>> handle.write.assert_called_once_with('some stuff')

And for reading files:

>>> with patch('__main__.open', mock_open(read_data='bibble')) as m:
...     with open('foo') as h:
...         result = h.read()
...
>>> m.assert_called_once_with('foo')
>>> assert result == 'bibble'

26.5.5.8. Autospeccing

Autospeccing is based on the existing spec feature of mock. It limits the api of mocks to the api of an original object (the spec), but it is recursive (implemented lazily) so that attributes of mocks only have the same api as the attributes of the spec. In addition mocked functions / methods have the same call signature as the original so they raise a TypeError if they are called incorrectly.

Before I explain how auto-speccing works, here’s why it is needed.

Mock is a very powerful and flexible object, but it suffers from two flaws when used to mock out objects from a system under test. One of these flaws is specific to the Mock api and the other is a more general problem with using mock objects.

First the problem specific to Mock. Mock has two assert methods that are extremely handy: assert_called_with() and assert_called_once_with().

>>> mock = Mock(name='Thing', return_value=None)
>>> mock(1, 2, 3)
>>> mock.assert_called_once_with(1, 2, 3)
>>> mock(1, 2, 3)
>>> mock.assert_called_once_with(1, 2, 3)
Traceback (most recent call last):
 ...
AssertionError: Expected 'mock' to be called once. Called 2 times.

Because mocks auto-create attributes on demand, and allow you to call them with arbitrary arguments, if you misspell one of these assert methods then your assertion is gone:

>>> mock = Mock(name='Thing', return_value=None)
>>> mock(1, 2, 3)
>>> mock.assret_called_once_with(4, 5, 6)

Your tests can pass silently and incorrectly because of the typo.

The second issue is more general to mocking. If you refactor some of your code, rename members and so on, any tests for code that is still using the old api but uses mocks instead of the real objects will still pass. This means your tests can all pass even though your code is broken.

Note that this is another reason why you need integration tests as well as unit tests. Testing everything in isolation is all fine and dandy, but if you don’t test how your units are « wired together » there is still lots of room for bugs that tests might have caught.

mock already provides a feature to help with this, called speccing. If you use a class or instance as the spec for a mock then you can only access attributes on the mock that exist on the real class:

>>> from urllib import request
>>> mock = Mock(spec=request.Request)
>>> mock.assret_called_with
Traceback (most recent call last):
 ...
AttributeError: Mock object has no attribute 'assret_called_with'

The spec only applies to the mock itself, so we still have the same issue with any methods on the mock:

>>> mock.has_data()
<mock.Mock object at 0x...>
>>> mock.has_data.assret_called_with()

Auto-speccing solves this problem. You can either pass autospec=True to patch() / patch.object() or use the create_autospec() function to create a mock with a spec. If you use the autospec=True argument to patch() then the object that is being replaced will be used as the spec object. Because the speccing is done « lazily » (the spec is created as attributes on the mock are accessed) you can use it with very complex or deeply nested objects (like modules that import modules that import modules) without a big performance hit.

Here’s an example of it in use:

>>> from urllib import request
>>> patcher = patch('__main__.request', autospec=True)
>>> mock_request = patcher.start()
>>> request is mock_request
True
>>> mock_request.Request
<MagicMock name='request.Request' spec='Request' id='...'>

You can see that request.Request has a spec. request.Request takes two arguments in the constructor (one of which is self). Here’s what happens if we try to call it incorrectly:

>>> req = request.Request()
Traceback (most recent call last):
 ...
TypeError: <lambda>() takes at least 2 arguments (1 given)

The spec also applies to instantiated classes (i.e. the return value of specced mocks):

>>> req = request.Request('foo')
>>> req
<NonCallableMagicMock name='request.Request()' spec='Request' id='...'>

Request objects are not callable, so the return value of instantiating our mocked out request.Request is a non-callable mock. With the spec in place any typos in our asserts will raise the correct error:

>>> req.add_header('spam', 'eggs')
<MagicMock name='request.Request().add_header()' id='...'>
>>> req.add_header.assret_called_with
Traceback (most recent call last):
 ...
AttributeError: Mock object has no attribute 'assret_called_with'
>>> req.add_header.assert_called_with('spam', 'eggs')

In many cases you will just be able to add autospec=True to your existing patch() calls and then be protected against bugs due to typos and api changes.

As well as using autospec through patch() there is a create_autospec() for creating autospecced mocks directly:

>>> from urllib import request
>>> mock_request = create_autospec(request)
>>> mock_request.Request('foo', 'bar')
<NonCallableMagicMock name='mock.Request()' spec='Request' id='...'>

This isn’t without caveats and limitations however, which is why it is not the default behaviour. In order to know what attributes are available on the spec object, autospec has to introspect (access attributes) the spec. As you traverse attributes on the mock a corresponding traversal of the original object is happening under the hood. If any of your specced objects have properties or descriptors that can trigger code execution then you may not be able to use autospec. On the other hand it is much better to design your objects so that introspection is safe 4.

A more serious problem is that it is common for instance attributes to be created in the __init__() method and not to exist on the class at all. autospec can’t know about any dynamically created attributes and restricts the api to visible attributes.

>>> class Something:
...   def __init__(self):
...     self.a = 33
...
>>> with patch('__main__.Something', autospec=True):
...   thing = Something()
...   thing.a
...
Traceback (most recent call last):
  ...
AttributeError: Mock object has no attribute 'a'

There are a few different ways of resolving this problem. The easiest, but not necessarily the least annoying, way is to simply set the required attributes on the mock after creation. Just because autospec doesn’t allow you to fetch attributes that don’t exist on the spec it doesn’t prevent you setting them:

>>> with patch('__main__.Something', autospec=True):
...   thing = Something()
...   thing.a = 33
...

There is a more aggressive version of both spec and autospec that does prevent you setting non-existent attributes. This is useful if you want to ensure your code only sets valid attributes too, but obviously it prevents this particular scenario:

>>> with patch('__main__.Something', autospec=True, spec_set=True):
...   thing = Something()
...   thing.a = 33
...
Traceback (most recent call last):
 ...
AttributeError: Mock object has no attribute 'a'

Probably the best way of solving the problem is to add class attributes as default values for instance members initialised in __init__(). Note that if you are only setting default attributes in __init__() then providing them via class attributes (shared between instances of course) is faster too. e.g.

class Something:
    a = 33

This brings up another issue. It is relatively common to provide a default value of None for members that will later be an object of a different type. None would be useless as a spec because it wouldn’t let you access any attributes or methods on it. As None is never going to be useful as a spec, and probably indicates a member that will normally of some other type, autospec doesn’t use a spec for members that are set to None. These will just be ordinary mocks (well - MagicMocks):

>>> class Something:
...     member = None
...
>>> mock = create_autospec(Something)
>>> mock.member.foo.bar.baz()
<MagicMock name='mock.member.foo.bar.baz()' id='...'>

If modifying your production classes to add defaults isn’t to your liking then there are more options. One of these is simply to use an instance as the spec rather than the class. The other is to create a subclass of the production class and add the defaults to the subclass without affecting the production class. Both of these require you to use an alternative object as the spec. Thankfully patch() supports this - you can simply pass the alternative object as the autospec argument:

>>> class Something:
...   def __init__(self):
...     self.a = 33
...
>>> class SomethingForTest(Something):
...   a = 33
...
>>> p = patch('__main__.Something', autospec=SomethingForTest)
>>> mock = p.start()
>>> mock.a
<NonCallableMagicMock name='Something.a' spec='int' id='...'>

4

This only applies to classes or already instantiated objects. Calling a mocked class to create a mock instance does not create a real instance. It is only attribute lookups - along with calls to dir() - that are done.

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26.6. unittest.mock — getting started

Nouveau dans la version 3.3.

26.6.1. Utilisation de Mock ou l’art de singer

26.6.1.1. Simulation des méthodes

Usages courant de Mock :

Substitution des méthodes

Enregistrement des appels faits sur les objets

On peut remplacer une méthode sur un objet pour contrôler qu’elle est bien appelée avec le nombre correct d’arguments :

>>> real = SomeClass()
>>> real.method = MagicMock(name='method')
>>> real.method(3, 4, 5, key='value')
<MagicMock name='method()' id='...'>

Une fois notre objet simulacre appelé (via real.method dans notre exemple), il fournit des méthodes et attributs permettant de valider comment il a été appelé.

Note

Dans la majeure partie des exemples donnés ici, les classes Mock et MagicMock sont interchangeables. Étant donné que MagicMock est la classe la plus puissante des deux, cela fait sens de l’utiliser par défaut.

Une fois l’objet Mock appelé, son attribut called est défini à True. Qui plus est, nous pouvons utiliser les méthodes assert_called_with() ou assert_called_once_with() pour contrôler qu’il a été appelé avec les bons arguments.

Cet exemple teste que l’appel de la méthode ProductionClass().method implique bien celui de la méthode something :

>>> class ProductionClass:
...     def method(self):
...         self.something(1, 2, 3)
...     def something(self, a, b, c):
...         pass
...
>>> real = ProductionClass()
>>> real.something = MagicMock()
>>> real.method()
>>> real.something.assert_called_once_with(1, 2, 3)

26.6.1.2. S’assurer de la bonne utilisation d’un objet

Dans l’exemple précédent, nous avons directement remplacé une méthode par un objet (afin de valider que l’appel était correct). Une autre façon de faire est de passer un objet Mock en argument d’une méthode (ou de tout autre partie du code à tester) et ensuite de contrôler que notre objet a été utilisé de la façon attendue.

Ci-dessous, ProductionClass dispose d’une méthode closer. Si on l’appelle avec un objet, alors elle appelle la méthode close dessus.

>>> class ProductionClass:
...     def closer(self, something):
...         something.close()
...

Ainsi, pour tester cette classe, nous devons lui passer un objet ayant une méthode close, puis vérifier qu’elle a bien été appelée.

>>> real = ProductionClass()
>>> mock = Mock()
>>> real.closer(mock)
>>> mock.close.assert_called_with()

En fait, nous n’avons pas à nous soucier de fournir la méthode close dans notre objet « simulé ». Le simple fait d’accéder à la méthode close l’a crée. Si par contre la méthode close n’a pas été appelée alors, bien que le test la créée en y accédant, assert_called_with() lèvera une exception.

26.6.1.3. Simulation des classes

Un cas d’utilisation courant consiste à émuler les classes instanciées par le code que nous testons. Quand on patch une classe, alors cette classe est remplacée par un objet mock. Les instances de la classe étant créées en appelant la classe, on accède à « l’instance mock » via la valeur de retour de la classe émulée.

In the example below we have a function some_function that instantiates Foo and calls a method on it. The call to patch() replaces the class Foo with a mock. The Foo instance is the result of calling the mock, so it is configured by modifying the mock return_value.

>>> def some_function():
...     instance = module.Foo()
...     return instance.method()
...
>>> with patch('module.Foo') as mock:
...     instance = mock.return_value
...     instance.method.return_value = 'the result'
...     result = some_function()
...     assert result == 'the result'

26.6.1.4. Naming your mocks

It can be useful to give your mocks a name. The name is shown in the repr of the mock and can be helpful when the mock appears in test failure messages. The name is also propagated to attributes or methods of the mock:

>>> mock = MagicMock(name='foo')
>>> mock
<MagicMock name='foo' id='...'>
>>> mock.method
<MagicMock name='foo.method' id='...'>

26.6.1.5. Tracking all Calls

Often you want to track more than a single call to a method. The mock_calls attribute records all calls to child attributes of the mock - and also to their children.

>>> mock = MagicMock()
>>> mock.method()
<MagicMock name='mock.method()' id='...'>
>>> mock.attribute.method(10, x=53)
<MagicMock name='mock.attribute.method()' id='...'>
>>> mock.mock_calls
[call.method(), call.attribute.method(10, x=53)]

If you make an assertion about mock_calls and any unexpected methods have been called, then the assertion will fail. This is useful because as well as asserting that the calls you expected have been made, you are also checking that they were made in the right order and with no additional calls:

You use the call object to construct lists for comparing with mock_calls:

>>> expected = [call.method(), call.attribute.method(10, x=53)]
>>> mock.mock_calls == expected
True

However, parameters to calls that return mocks are not recorded, which means it is not possible to track nested calls where the parameters used to create ancestors are important:

>>> m = Mock()
>>> m.factory(important=True).deliver()
<Mock name='mock.factory().deliver()' id='...'>
>>> m.mock_calls[-1] == call.factory(important=False).deliver()
True

26.6.1.6. Setting Return Values and Attributes

Setting the return values on a mock object is trivially easy:

>>> mock = Mock()
>>> mock.return_value = 3
>>> mock()
3

Of course you can do the same for methods on the mock:

>>> mock = Mock()
>>> mock.method.return_value = 3
>>> mock.method()
3

The return value can also be set in the constructor:

>>> mock = Mock(return_value=3)
>>> mock()
3

If you need an attribute setting on your mock, just do it:

>>> mock = Mock()
>>> mock.x = 3
>>> mock.x
3

Sometimes you want to mock up a more complex situation, like for example mock.connection.cursor().execute("SELECT 1"). If we wanted this call to return a list, then we have to configure the result of the nested call.

We can use call to construct the set of calls in a « chained call » like this for easy assertion afterwards:

>>> mock = Mock()
>>> cursor = mock.connection.cursor.return_value
>>> cursor.execute.return_value = ['foo']
>>> mock.connection.cursor().execute("SELECT 1")
['foo']
>>> expected = call.connection.cursor().execute("SELECT 1").call_list()
>>> mock.mock_calls
[call.connection.cursor(), call.connection.cursor().execute('SELECT 1')]
>>> mock.mock_calls == expected
True

It is the call to .call_list() that turns our call object into a list of calls representing the chained calls.

26.6.1.7. Raising exceptions with mocks

A useful attribute is side_effect. If you set this to an exception class or instance then the exception will be raised when the mock is called.

>>> mock = Mock(side_effect=Exception('Boom!'))
>>> mock()
Traceback (most recent call last):
  ...
Exception: Boom!

26.6.1.8. Side effect functions and iterables

side_effect can also be set to a function or an iterable. The use case for side_effect as an iterable is where your mock is going to be called several times, and you want each call to return a different value. When you set side_effect to an iterable every call to the mock returns the next value from the iterable:

>>> mock = MagicMock(side_effect=[4, 5, 6])
>>> mock()
4
>>> mock()
5
>>> mock()
6

For more advanced use cases, like dynamically varying the return values depending on what the mock is called with, side_effect can be a function. The function will be called with the same arguments as the mock. Whatever the function returns is what the call returns:

>>> vals = {(1, 2): 1, (2, 3): 2}
>>> def side_effect(*args):
...     return vals[args]
...
>>> mock = MagicMock(side_effect=side_effect)
>>> mock(1, 2)
1
>>> mock(2, 3)
2

26.6.1.9. Creating a Mock from an Existing Object

One problem with over use of mocking is that it couples your tests to the implementation of your mocks rather than your real code. Suppose you have a class that implements some_method. In a test for another class, you provide a mock of this object that also provides some_method. If later you refactor the first class, so that it no longer has some_method - then your tests will continue to pass even though your code is now broken!

Mock allows you to provide an object as a specification for the mock, using the spec keyword argument. Accessing methods / attributes on the mock that don’t exist on your specification object will immediately raise an attribute error. If you change the implementation of your specification, then tests that use that class will start failing immediately without you having to instantiate the class in those tests.

>>> mock = Mock(spec=SomeClass)
>>> mock.old_method()
Traceback (most recent call last):
   ...
AttributeError: object has no attribute 'old_method'

Using a specification also enables a smarter matching of calls made to the mock, regardless of whether some parameters were passed as positional or named arguments:

>>> def f(a, b, c): pass
...
>>> mock = Mock(spec=f)
>>> mock(1, 2, 3)
<Mock name='mock()' id='140161580456576'>
>>> mock.assert_called_with(a=1, b=2, c=3)

If you want this smarter matching to also work with method calls on the mock, you can use auto-speccing.

If you want a stronger form of specification that prevents the setting of arbitrary attributes as well as the getting of them then you can use spec_set instead of spec.

26.6.2. Patch Decorators

Note

Avec patch(), il est important de patcher les objets dans l’espace de nommage où ils sont recherchés. C’est ce qui se fait normalement, mais pour un guide rapide, lisez où patcher.

A common need in tests is to patch a class attribute or a module attribute, for example patching a builtin or patching a class in a module to test that it is instantiated. Modules and classes are effectively global, so patching on them has to be undone after the test or the patch will persist into other tests and cause hard to diagnose problems.

mock provides three convenient decorators for this: patch(), patch.object() and patch.dict(). patch takes a single string, of the form package.module.Class.attribute to specify the attribute you are patching. It also optionally takes a value that you want the attribute (or class or whatever) to be replaced with. “patch.object” takes an object and the name of the attribute you would like patched, plus optionally the value to patch it with.

patch.object:

>>> original = SomeClass.attribute
>>> @patch.object(SomeClass, 'attribute', sentinel.attribute)
... def test():
...     assert SomeClass.attribute == sentinel.attribute
...
>>> test()
>>> assert SomeClass.attribute == original

>>> @patch('package.module.attribute', sentinel.attribute)
... def test():
...     from package.module import attribute
...     assert attribute is sentinel.attribute
...
>>> test()

If you are patching a module (including builtins) then use patch() instead of patch.object():

>>> mock = MagicMock(return_value=sentinel.file_handle)
>>> with patch('builtins.open', mock):
...     handle = open('filename', 'r')
...
>>> mock.assert_called_with('filename', 'r')
>>> assert handle == sentinel.file_handle, "incorrect file handle returned"

The module name can be “dotted”, in the form package.module if needed:

>>> @patch('package.module.ClassName.attribute', sentinel.attribute)
... def test():
...     from package.module import ClassName
...     assert ClassName.attribute == sentinel.attribute
...
>>> test()

A nice pattern is to actually decorate test methods themselves:

>>> class MyTest(unittest.TestCase):
...     @patch.object(SomeClass, 'attribute', sentinel.attribute)
...     def test_something(self):
...         self.assertEqual(SomeClass.attribute, sentinel.attribute)
...
>>> original = SomeClass.attribute
>>> MyTest('test_something').test_something()
>>> assert SomeClass.attribute == original

If you want to patch with a Mock, you can use patch() with only one argument (or patch.object() with two arguments). The mock will be created for you and passed into the test function / method:

>>> class MyTest(unittest.TestCase):
...     @patch.object(SomeClass, 'static_method')
...     def test_something(self, mock_method):
...         SomeClass.static_method()
...         mock_method.assert_called_with()
...
>>> MyTest('test_something').test_something()

You can stack up multiple patch decorators using this pattern:

>>> class MyTest(unittest.TestCase):
...     @patch('package.module.ClassName1')
...     @patch('package.module.ClassName2')
...     def test_something(self, MockClass2, MockClass1):
...         self.assertIs(package.module.ClassName1, MockClass1)
...         self.assertIs(package.module.ClassName2, MockClass2)
...
>>> MyTest('test_something').test_something()

When you nest patch decorators the mocks are passed in to the decorated function in the same order they applied (the normal python order that decorators are applied). This means from the bottom up, so in the example above the mock for test_module.ClassName2 is passed in first.

Il existe également patch.dict() pour définir des valeurs d’un dictionnaire au sein d’une portée et restaurer ce dictionnaire à son état d’origine lorsque le test se termine :

>>> foo = {'key': 'value'}
>>> original = foo.copy()
>>> with patch.dict(foo, {'newkey': 'newvalue'}, clear=True):
...     assert foo == {'newkey': 'newvalue'}
...
>>> assert foo == original

patch, patch.object and patch.dict can all be used as context managers.

Where you use patch() to create a mock for you, you can get a reference to the mock using the « as » form of the with statement:

>>> class ProductionClass:
...     def method(self):
...         pass
...
>>> with patch.object(ProductionClass, 'method') as mock_method:
...     mock_method.return_value = None
...     real = ProductionClass()
...     real.method(1, 2, 3)
...
>>> mock_method.assert_called_with(1, 2, 3)

As an alternative patch, patch.object and patch.dict can be used as class decorators. When used in this way it is the same as applying the decorator individually to every method whose name starts with « test ».

26.6.3. Further Examples

Here are some more examples for some slightly more advanced scenarios.

26.6.3.1. Mocking chained calls

Mocking chained calls is actually straightforward with mock once you understand the return_value attribute. When a mock is called for the first time, or you fetch its return_value before it has been called, a new Mock is created.

This means that you can see how the object returned from a call to a mocked object has been used by interrogating the return_value mock:

>>> mock = Mock()
>>> mock().foo(a=2, b=3)
<Mock name='mock().foo()' id='...'>
>>> mock.return_value.foo.assert_called_with(a=2, b=3)

From here it is a simple step to configure and then make assertions about chained calls. Of course another alternative is writing your code in a more testable way in the first place…

So, suppose we have some code that looks a little bit like this:

>>> class Something:
...     def __init__(self):
...         self.backend = BackendProvider()
...     def method(self):
...         response = self.backend.get_endpoint('foobar').create_call('spam', 'eggs').start_call()
...         # more code

Assuming that BackendProvider is already well tested, how do we test method()? Specifically, we want to test that the code section # more code uses the response object in the correct way.

As this chain of calls is made from an instance attribute we can monkey patch the backend attribute on a Something instance. In this particular case we are only interested in the return value from the final call to start_call so we don’t have much configuration to do. Let’s assume the object it returns is “file-like”, so we’ll ensure that our response object uses the builtin open() as its spec.

To do this we create a mock instance as our mock backend and create a mock response object for it. To set the response as the return value for that final start_call we could do this:

mock_backend.get_endpoint.return_value.create_call.return_value.start_call.return_value = mock_response

We can do that in a slightly nicer way using the configure_mock() method to directly set the return value for us:

>>> something = Something()
>>> mock_response = Mock(spec=open)
>>> mock_backend = Mock()
>>> config = {'get_endpoint.return_value.create_call.return_value.start_call.return_value': mock_response}
>>> mock_backend.configure_mock(**config)

With these we monkey patch the « mock backend » in place and can make the real call:

>>> something.backend = mock_backend
>>> something.method()

Using mock_calls we can check the chained call with a single assert. A chained call is several calls in one line of code, so there will be several entries in mock_calls. We can use call.call_list() to create this list of calls for us:

>>> chained = call.get_endpoint('foobar').create_call('spam', 'eggs').start_call()
>>> call_list = chained.call_list()
>>> assert mock_backend.mock_calls == call_list

26.6.3.2. Partial mocking

In some tests I wanted to mock out a call to datetime.date.today() to return a known date, but I didn’t want to prevent the code under test from creating new date objects. Unfortunately datetime.date is written in C, and so I couldn’t just monkey-patch out the static date.today() method.

I found a simple way of doing this that involved effectively wrapping the date class with a mock, but passing through calls to the constructor to the real class (and returning real instances).

The patch decorator is used here to mock out the date class in the module under test. The side_effect attribute on the mock date class is then set to a lambda function that returns a real date. When the mock date class is called a real date will be constructed and returned by side_effect.

>>> from datetime import date
>>> with patch('mymodule.date') as mock_date:
...     mock_date.today.return_value = date(2010, 10, 8)
...     mock_date.side_effect = lambda *args, **kw: date(*args, **kw)
...
...     assert mymodule.date.today() == date(2010, 10, 8)
...     assert mymodule.date(2009, 6, 8) == date(2009, 6, 8)
...

Note that we don’t patch datetime.date globally, we patch date in the module that uses it. See where to patch.

When date.today() is called a known date is returned, but calls to the date(...) constructor still return normal dates. Without this you can find yourself having to calculate an expected result using exactly the same algorithm as the code under test, which is a classic testing anti-pattern.

Calls to the date constructor are recorded in the mock_date attributes (call_count and friends) which may also be useful for your tests.

An alternative way of dealing with mocking dates, or other builtin classes, is discussed in this blog entry [https://williambert.online/2011/07/how-to-unit-testing-in-django-with-mocking-and-patching/].

26.6.3.3. Mocking a Generator Method

A Python generator is a function or method that uses the yield statement to return a series of values when iterated over 1.

A generator method / function is called to return the generator object. It is the generator object that is then iterated over. The protocol method for iteration is __iter__(), so we can mock this using a MagicMock.

Here’s an example class with an « iter » method implemented as a generator:

>>> class Foo:
...     def iter(self):
...         for i in [1, 2, 3]:
...             yield i
...
>>> foo = Foo()
>>> list(foo.iter())
[1, 2, 3]

How would we mock this class, and in particular its « iter » method?

To configure the values returned from the iteration (implicit in the call to list), we need to configure the object returned by the call to foo.iter().

>>> mock_foo = MagicMock()
>>> mock_foo.iter.return_value = iter([1, 2, 3])
>>> list(mock_foo.iter())
[1, 2, 3]

1

There are also generator expressions and more advanced uses [http://www.dabeaz.com/coroutines/index.html] of generators, but we aren’t concerned about them here. A very good introduction to generators and how powerful they are is: Generator Tricks for Systems Programmers [http://www.dabeaz.com/generators/].

26.6.3.4. Applying the same patch to every test method

If you want several patches in place for multiple test methods the obvious way is to apply the patch decorators to every method. This can feel like unnecessary repetition. For Python 2.6 or more recent you can use patch() (in all its various forms) as a class decorator. This applies the patches to all test methods on the class. A test method is identified by methods whose names start with test:

>>> @patch('mymodule.SomeClass')
... class MyTest(TestCase):
...
...     def test_one(self, MockSomeClass):
...         self.assertIs(mymodule.SomeClass, MockSomeClass)
...
...     def test_two(self, MockSomeClass):
...         self.assertIs(mymodule.SomeClass, MockSomeClass)
...
...     def not_a_test(self):
...         return 'something'
...
>>> MyTest('test_one').test_one()
>>> MyTest('test_two').test_two()
>>> MyTest('test_two').not_a_test()
'something'

An alternative way of managing patches is to use the patch methods: start and stop. These allow you to move the patching into your setUp and tearDown methods.

>>> class MyTest(TestCase):
...     def setUp(self):
...         self.patcher = patch('mymodule.foo')
...         self.mock_foo = self.patcher.start()
...
...     def test_foo(self):
...         self.assertIs(mymodule.foo, self.mock_foo)
...
...     def tearDown(self):
...         self.patcher.stop()
...
>>> MyTest('test_foo').run()

If you use this technique you must ensure that the patching is « undone » by calling stop. This can be fiddlier than you might think, because if an exception is raised in the setUp then tearDown is not called. unittest.TestCase.addCleanup() makes this easier:

>>> class MyTest(TestCase):
...     def setUp(self):
...         patcher = patch('mymodule.foo')
...         self.addCleanup(patcher.stop)
...         self.mock_foo = patcher.start()
...
...     def test_foo(self):
...         self.assertIs(mymodule.foo, self.mock_foo)
...
>>> MyTest('test_foo').run()

26.6.3.5. Mocking Unbound Methods

Whilst writing tests today I needed to patch an unbound method (patching the method on the class rather than on the instance). I needed self to be passed in as the first argument because I want to make asserts about which objects were calling this particular method. The issue is that you can’t patch with a mock for this, because if you replace an unbound method with a mock it doesn’t become a bound method when fetched from the instance, and so it doesn’t get self passed in. The workaround is to patch the unbound method with a real function instead. The patch() decorator makes it so simple to patch out methods with a mock that having to create a real function becomes a nuisance.

If you pass autospec=True to patch then it does the patching with a real function object. This function object has the same signature as the one it is replacing, but delegates to a mock under the hood. You still get your mock auto-created in exactly the same way as before. What it means though, is that if you use it to patch out an unbound method on a class the mocked function will be turned into a bound method if it is fetched from an instance. It will have self passed in as the first argument, which is exactly what I wanted:

>>> class Foo:
...   def foo(self):
...     pass
...
>>> with patch.object(Foo, 'foo', autospec=True) as mock_foo:
...   mock_foo.return_value = 'foo'
...   foo = Foo()
...   foo.foo()
...
'foo'
>>> mock_foo.assert_called_once_with(foo)

If we don’t use autospec=True then the unbound method is patched out with a Mock instance instead, and isn’t called with self.

26.6.3.6. Checking multiple calls with mock

mock has a nice API for making assertions about how your mock objects are used.

>>> mock = Mock()
>>> mock.foo_bar.return_value = None
>>> mock.foo_bar('baz', spam='eggs')
>>> mock.foo_bar.assert_called_with('baz', spam='eggs')

If your mock is only being called once you can use the assert_called_once_with() method that also asserts that the call_count is one.

>>> mock.foo_bar.assert_called_once_with('baz', spam='eggs')
>>> mock.foo_bar()
>>> mock.foo_bar.assert_called_once_with('baz', spam='eggs')
Traceback (most recent call last):
    ...
AssertionError: Expected to be called once. Called 2 times.

Both assert_called_with and assert_called_once_with make assertions about the most recent call. If your mock is going to be called several times, and you want to make assertions about all those calls you can use call_args_list:

>>> mock = Mock(return_value=None)
>>> mock(1, 2, 3)
>>> mock(4, 5, 6)
>>> mock()
>>> mock.call_args_list
[call(1, 2, 3), call(4, 5, 6), call()]

The call helper makes it easy to make assertions about these calls. You can build up a list of expected calls and compare it to call_args_list. This looks remarkably similar to the repr of the call_args_list:

>>> expected = [call(1, 2, 3), call(4, 5, 6), call()]
>>> mock.call_args_list == expected
True

26.6.3.7. Coping with mutable arguments

Another situation is rare, but can bite you, is when your mock is called with mutable arguments. call_args and call_args_list store references to the arguments. If the arguments are mutated by the code under test then you can no longer make assertions about what the values were when the mock was called.

Here’s some example code that shows the problem. Imagine the following functions defined in “mymodule”:

def frob(val):
    pass

def grob(val):
    "First frob and then clear val"
    frob(val)
    val.clear()

When we try to test that grob calls frob with the correct argument look what happens:

>>> with patch('mymodule.frob') as mock_frob:
...     val = {6}
...     mymodule.grob(val)
...
>>> val
set()
>>> mock_frob.assert_called_with({6})
Traceback (most recent call last):
    ...
AssertionError: Expected: (({6},), {})
Called with: ((set(),), {})

One possibility would be for mock to copy the arguments you pass in. This could then cause problems if you do assertions that rely on object identity for equality.

Here’s one solution that uses the side_effect functionality. If you provide a side_effect function for a mock then side_effect will be called with the same args as the mock. This gives us an opportunity to copy the arguments and store them for later assertions. In this example I’m using another mock to store the arguments so that I can use the mock methods for doing the assertion. Again a helper function sets this up for me.

>>> from copy import deepcopy
>>> from unittest.mock import Mock, patch, DEFAULT
>>> def copy_call_args(mock):
...     new_mock = Mock()
...     def side_effect(*args, **kwargs):
...         args = deepcopy(args)
...         kwargs = deepcopy(kwargs)
...         new_mock(*args, **kwargs)
...         return DEFAULT
...     mock.side_effect = side_effect
...     return new_mock
...
>>> with patch('mymodule.frob') as mock_frob:
...     new_mock = copy_call_args(mock_frob)
...     val = {6}
...     mymodule.grob(val)
...
>>> new_mock.assert_called_with({6})
>>> new_mock.call_args
call({6})

copy_call_args is called with the mock that will be called. It returns a new mock that we do the assertion on. The side_effect function makes a copy of the args and calls our new_mock with the copy.

Note

If your mock is only going to be used once there is an easier way of checking arguments at the point they are called. You can simply do the checking inside a side_effect function.

>>> def side_effect(arg):
...     assert arg == {6}
...
>>> mock = Mock(side_effect=side_effect)
>>> mock({6})
>>> mock(set())
Traceback (most recent call last):
    ...
AssertionError

An alternative approach is to create a subclass of Mock or MagicMock that copies (using copy.deepcopy()) the arguments. Here’s an example implementation:

>>> from copy import deepcopy
>>> class CopyingMock(MagicMock):
...     def __call__(self, *args, **kwargs):
...         args = deepcopy(args)
...         kwargs = deepcopy(kwargs)
...         return super(CopyingMock, self).__call__(*args, **kwargs)
...
>>> c = CopyingMock(return_value=None)
>>> arg = set()
>>> c(arg)
>>> arg.add(1)
>>> c.assert_called_with(set())
>>> c.assert_called_with(arg)
Traceback (most recent call last):
    ...
AssertionError: Expected call: mock({1})
Actual call: mock(set())
>>> c.foo
<CopyingMock name='mock.foo' id='...'>

When you subclass Mock or MagicMock all dynamically created attributes, and the return_value will use your subclass automatically. That means all children of a CopyingMock will also have the type CopyingMock.

26.6.3.8. Nesting Patches

Using patch as a context manager is nice, but if you do multiple patches you can end up with nested with statements indenting further and further to the right:

>>> class MyTest(TestCase):
...
...     def test_foo(self):
...         with patch('mymodule.Foo') as mock_foo:
...             with patch('mymodule.Bar') as mock_bar:
...                 with patch('mymodule.Spam') as mock_spam:
...                     assert mymodule.Foo is mock_foo
...                     assert mymodule.Bar is mock_bar
...                     assert mymodule.Spam is mock_spam
...
>>> original = mymodule.Foo
>>> MyTest('test_foo').test_foo()
>>> assert mymodule.Foo is original

With unittest cleanup functions and the patch methods: start and stop we can achieve the same effect without the nested indentation. A simple helper method, create_patch, puts the patch in place and returns the created mock for us:

>>> class MyTest(TestCase):
...
...     def create_patch(self, name):
...         patcher = patch(name)
...         thing = patcher.start()
...         self.addCleanup(patcher.stop)
...         return thing
...
...     def test_foo(self):
...         mock_foo = self.create_patch('mymodule.Foo')
...         mock_bar = self.create_patch('mymodule.Bar')
...         mock_spam = self.create_patch('mymodule.Spam')
...
...         assert mymodule.Foo is mock_foo
...         assert mymodule.Bar is mock_bar
...         assert mymodule.Spam is mock_spam
...
>>> original = mymodule.Foo
>>> MyTest('test_foo').run()
>>> assert mymodule.Foo is original

26.6.3.9. Mocking a dictionary with MagicMock

You may want to mock a dictionary, or other container object, recording all access to it whilst having it still behave like a dictionary.

We can do this with MagicMock, which will behave like a dictionary, and using side_effect to delegate dictionary access to a real underlying dictionary that is under our control.

When the __getitem__() and __setitem__() methods of our MagicMock are called (normal dictionary access) then side_effect is called with the key (and in the case of __setitem__ the value too). We can also control what is returned.

After the MagicMock has been used we can use attributes like call_args_list to assert about how the dictionary was used:

>>> my_dict = {'a': 1, 'b': 2, 'c': 3}
>>> def getitem(name):
...      return my_dict[name]
...
>>> def setitem(name, val):
...     my_dict[name] = val
...
>>> mock = MagicMock()
>>> mock.__getitem__.side_effect = getitem
>>> mock.__setitem__.side_effect = setitem

Note

An alternative to using MagicMock is to use Mock and only provide the magic methods you specifically want:

>>> mock = Mock()
>>> mock.__getitem__ = Mock(side_effect=getitem)
>>> mock.__setitem__ = Mock(side_effect=setitem)

A third option is to use MagicMock but passing in dict as the spec (or spec_set) argument so that the MagicMock created only has dictionary magic methods available:

>>> mock = MagicMock(spec_set=dict)
>>> mock.__getitem__.side_effect = getitem
>>> mock.__setitem__.side_effect = setitem

With these side effect functions in place, the mock will behave like a normal dictionary but recording the access. It even raises a KeyError if you try to access a key that doesn’t exist.

>>> mock['a']
1
>>> mock['c']
3
>>> mock['d']
Traceback (most recent call last):
    ...
KeyError: 'd'
>>> mock['b'] = 'fish'
>>> mock['d'] = 'eggs'
>>> mock['b']
'fish'
>>> mock['d']
'eggs'

After it has been used you can make assertions about the access using the normal mock methods and attributes:

>>> mock.__getitem__.call_args_list
[call('a'), call('c'), call('d'), call('b'), call('d')]
>>> mock.__setitem__.call_args_list
[call('b', 'fish'), call('d', 'eggs')]
>>> my_dict
{'a': 1, 'c': 3, 'b': 'fish', 'd': 'eggs'}

26.6.3.10. Mock subclasses and their attributes

There are various reasons why you might want to subclass Mock. One reason might be to add helper methods. Here’s a silly example:

>>> class MyMock(MagicMock):
...     def has_been_called(self):
...         return self.called
...
>>> mymock = MyMock(return_value=None)
>>> mymock
<MyMock id='...'>
>>> mymock.has_been_called()
False
>>> mymock()
>>> mymock.has_been_called()
True

The standard behaviour for Mock instances is that attributes and the return value mocks are of the same type as the mock they are accessed on. This ensures that Mock attributes are Mocks and MagicMock attributes are MagicMocks 2. So if you’re subclassing to add helper methods then they’ll also be available on the attributes and return value mock of instances of your subclass.

>>> mymock.foo
<MyMock name='mock.foo' id='...'>
>>> mymock.foo.has_been_called()
False
>>> mymock.foo()
<MyMock name='mock.foo()' id='...'>
>>> mymock.foo.has_been_called()
True

Sometimes this is inconvenient. For example, one user [https://code.google.com/p/mock/issues/detail?id=105] is subclassing mock to created a Twisted adaptor [https://twistedmatrix.com/documents/11.0.0/api/twisted.python.components.html]. Having this applied to attributes too actually causes errors.

Mock (in all its flavours) uses a method called _get_child_mock to create these « sub-mocks » for attributes and return values. You can prevent your subclass being used for attributes by overriding this method. The signature is that it takes arbitrary keyword arguments (**kwargs) which are then passed onto the mock constructor:

>>> class Subclass(MagicMock):
...     def _get_child_mock(self, **kwargs):
...         return MagicMock(**kwargs)
...
>>> mymock = Subclass()
>>> mymock.foo
<MagicMock name='mock.foo' id='...'>
>>> assert isinstance(mymock, Subclass)
>>> assert not isinstance(mymock.foo, Subclass)
>>> assert not isinstance(mymock(), Subclass)

2

An exception to this rule are the non-callable mocks. Attributes use the callable variant because otherwise non-callable mocks couldn’t have callable methods.

26.6.3.11. Mocking imports with patch.dict

One situation where mocking can be hard is where you have a local import inside a function. These are harder to mock because they aren’t using an object from the module namespace that we can patch out.

Generally local imports are to be avoided. They are sometimes done to prevent circular dependencies, for which there is usually a much better way to solve the problem (refactor the code) or to prevent « up front costs » by delaying the import. This can also be solved in better ways than an unconditional local import (store the module as a class or module attribute and only do the import on first use).

That aside there is a way to use mock to affect the results of an import. Importing fetches an object from the sys.modules dictionary. Note that it fetches an object, which need not be a module. Importing a module for the first time results in a module object being put in sys.modules, so usually when you import something you get a module back. This need not be the case however.

This means you can use patch.dict() to temporarily put a mock in place in sys.modules. Any imports whilst this patch is active will fetch the mock. When the patch is complete (the decorated function exits, the with statement body is complete or patcher.stop() is called) then whatever was there previously will be restored safely.

Here’s an example that mocks out the “fooble” module.

>>> mock = Mock()
>>> with patch.dict('sys.modules', {'fooble': mock}):
...    import fooble
...    fooble.blob()
...
<Mock name='mock.blob()' id='...'>
>>> assert 'fooble' not in sys.modules
>>> mock.blob.assert_called_once_with()

As you can see the import fooble succeeds, but on exit there is no “fooble” left in sys.modules.

This also works for the from module import name form:

>>> mock = Mock()
>>> with patch.dict('sys.modules', {'fooble': mock}):
...    from fooble import blob
...    blob.blip()
...
<Mock name='mock.blob.blip()' id='...'>
>>> mock.blob.blip.assert_called_once_with()

With slightly more work you can also mock package imports:

>>> mock = Mock()
>>> modules = {'package': mock, 'package.module': mock.module}
>>> with patch.dict('sys.modules', modules):
...    from package.module import fooble
...    fooble()
...
<Mock name='mock.module.fooble()' id='...'>
>>> mock.module.fooble.assert_called_once_with()

26.6.3.12. Tracking order of calls and less verbose call assertions

The Mock class allows you to track the order of method calls on your mock objects through the method_calls attribute. This doesn’t allow you to track the order of calls between separate mock objects, however we can use mock_calls to achieve the same effect.

Because mocks track calls to child mocks in mock_calls, and accessing an arbitrary attribute of a mock creates a child mock, we can create our separate mocks from a parent one. Calls to those child mock will then all be recorded, in order, in the mock_calls of the parent:

>>> manager = Mock()
>>> mock_foo = manager.foo
>>> mock_bar = manager.bar

>>> mock_foo.something()
<Mock name='mock.foo.something()' id='...'>
>>> mock_bar.other.thing()
<Mock name='mock.bar.other.thing()' id='...'>

>>> manager.mock_calls
[call.foo.something(), call.bar.other.thing()]

We can then assert about the calls, including the order, by comparing with the mock_calls attribute on the manager mock:

>>> expected_calls = [call.foo.something(), call.bar.other.thing()]
>>> manager.mock_calls == expected_calls
True

If patch is creating, and putting in place, your mocks then you can attach them to a manager mock using the attach_mock() method. After attaching calls will be recorded in mock_calls of the manager.

>>> manager = MagicMock()
>>> with patch('mymodule.Class1') as MockClass1:
...     with patch('mymodule.Class2') as MockClass2:
...         manager.attach_mock(MockClass1, 'MockClass1')
...         manager.attach_mock(MockClass2, 'MockClass2')
...         MockClass1().foo()
...         MockClass2().bar()
...
<MagicMock name='mock.MockClass1().foo()' id='...'>
<MagicMock name='mock.MockClass2().bar()' id='...'>
>>> manager.mock_calls
[call.MockClass1(),
 call.MockClass1().foo(),
 call.MockClass2(),
 call.MockClass2().bar()]

If many calls have been made, but you’re only interested in a particular sequence of them then an alternative is to use the assert_has_calls() method. This takes a list of calls (constructed with the call object). If that sequence of calls are in mock_calls then the assert succeeds.

>>> m = MagicMock()
>>> m().foo().bar().baz()
<MagicMock name='mock().foo().bar().baz()' id='...'>
>>> m.one().two().three()
<MagicMock name='mock.one().two().three()' id='...'>
>>> calls = call.one().two().three().call_list()
>>> m.assert_has_calls(calls)

Even though the chained call m.one().two().three() aren’t the only calls that have been made to the mock, the assert still succeeds.

Sometimes a mock may have several calls made to it, and you are only interested in asserting about some of those calls. You may not even care about the order. In this case you can pass any_order=True to assert_has_calls:

>>> m = MagicMock()
>>> m(1), m.two(2, 3), m.seven(7), m.fifty('50')
(...)
>>> calls = [call.fifty('50'), call(1), call.seven(7)]
>>> m.assert_has_calls(calls, any_order=True)

26.6.3.13. More complex argument matching

Using the same basic concept as ANY we can implement matchers to do more complex assertions on objects used as arguments to mocks.

Suppose we expect some object to be passed to a mock that by default compares equal based on object identity (which is the Python default for user defined classes). To use assert_called_with() we would need to pass in the exact same object. If we are only interested in some of the attributes of this object then we can create a matcher that will check these attributes for us.

You can see in this example how a “standard” call to assert_called_with isn’t sufficient:

>>> class Foo:
...     def __init__(self, a, b):
...         self.a, self.b = a, b
...
>>> mock = Mock(return_value=None)
>>> mock(Foo(1, 2))
>>> mock.assert_called_with(Foo(1, 2))
Traceback (most recent call last):
    ...
AssertionError: Expected: call(<__main__.Foo object at 0x...>)
Actual call: call(<__main__.Foo object at 0x...>)

A comparison function for our Foo class might look something like this:

>>> def compare(self, other):
...     if not type(self) == type(other):
...         return False
...     if self.a != other.a:
...         return False
...     if self.b != other.b:
...         return False
...     return True
...

And a matcher object that can use comparison functions like this for its equality operation would look something like this:

>>> class Matcher:
...     def __init__(self, compare, some_obj):
...         self.compare = compare
...         self.some_obj = some_obj
...     def __eq__(self, other):
...         return self.compare(self.some_obj, other)
...

Putting all this together:

>>> match_foo = Matcher(compare, Foo(1, 2))
>>> mock.assert_called_with(match_foo)

The Matcher is instantiated with our compare function and the Foo object we want to compare against. In assert_called_with the Matcher equality method will be called, which compares the object the mock was called with against the one we created our matcher with. If they match then assert_called_with passes, and if they don’t an AssertionError is raised:

>>> match_wrong = Matcher(compare, Foo(3, 4))
>>> mock.assert_called_with(match_wrong)
Traceback (most recent call last):
    ...
AssertionError: Expected: ((<Matcher object at 0x...>,), {})
Called with: ((<Foo object at 0x...>,), {})

With a bit of tweaking you could have the comparison function raise the AssertionError directly and provide a more useful failure message.

As of version 1.5, the Python testing library PyHamcrest [https://pyhamcrest.readthedocs.org/] provides similar functionality, that may be useful here, in the form of its equality matcher (hamcrest.library.integration.match_equality [https://pyhamcrest.readthedocs.org/en/release-1.8/integration/#module-hamcrest.library.integration.match_equality]).

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26.7. 2to3 — Traduction automatique de code en Python 2 vers Python 3

2to3 est un programme Python qui lit du code source en Python 2.x et applique une suite de correcteurs pour le transformer en code Python 3.x valide. La bibliothèque standard contient un ensemble riche de correcteurs qui gèreront quasiment tout le code. La bibliothèque lib2to3 utilisée par 2to3 est cependant une bibliothèque flexible et générique, il est donc possible d’écrire vos propres correcteurs pour 2to3. lib2to3 pourrait aussi être adaptée à des applications personnalisées dans lesquelles le code Python doit être édité automatiquement.

26.7.1. Utilisation de 2to3

2to3 sera généralement installé avec l’interpréteur Python en tant que script. Il est également situé dans le dossier Tools/scripts à racine de Python.

Les arguments de base de 2to3 sont une liste de fichiers et de répertoires à transformer. Les répertoires sont parcourus récursivement pour trouver les sources Python.

Voici un exemple de fichier source Python 2.x, example.py :

def greet(name):
    print "Hello, {0}!".format(name)
print "What's your name?"
name = raw_input()
greet(name)

Il peut être converti en code Python 3.x par 2to3 en ligne de commande :

$ 2to3 example.py

Une comparaison avec le fichier source original est affichée. 2to3 peut aussi écrire les modifications nécessaires directement dans le fichier source. (Une sauvegarde du fichier d’origine est effectuée à moins que l’option -n soit également donnée.) L’écriture des modifications est activée avec l’option -w :

$ 2to3 -w example.py

Après transformation, example.py ressemble à :

def greet(name):
    print("Hello, {0}!".format(name))
print("What's your name?")
name = input()
greet(name)

Les commentaires et les retraits sont préservés tout au long du processus de traduction.

Par défaut, 2to3 exécute un ensemble de correcteurs prédéfinis. L’option -l énumère tous les correcteurs disponibles. Un ensemble explicite de correcteurs à exécuter peut être donné avec -f. De même, -x désactive explicitement un correcteur. L’exemple suivant exécute uniquement les import et les correcteurs has_key :

$ 2to3 -f imports -f has_key example.py

Cette commande exécute tous les correcteurs, sauf le correcteurs apply :

$ 2to3 -x apply example.py

Certains correcteurs sont explicites, ce qui signifie qu’ils ne sont pas exécutés par défaut et doivent être énumérés sur la ligne de commande à exécuter. Ici, en plus des correcteurs par défaut, le correcteur idioms est exécuté :

$ 2to3 -f all -f idioms example.py

Notez que passer all active tous les correcteurs par défaut.

Parfois, 2to3 trouvera un endroit dans votre code source qui doit être changé, mais qu’il ne peut pas résoudre automatiquement. Dans ce cas, 2to3 affiche un avertissement sous la comparaison d’un fichier. Vous devez traiter l’avertissement afin d’avoir un code conforme à Python 3.x.

2to3 peut également réusiner les doctests. Pour activer ce mode, utilisez -d. Notez que seul les doctests seront réusinés. Cela ne nécessite pas que le module soit du Python valide. Par exemple, des doctests tels que des exemples dans un document reST peuvent également être réusinés avec cette option.

L’option -v augmente la quantité de messages générés par le processus de traduction.

Puisque certaines instructions d’affichage peuvent être analysées comme des appels ou des instructions de fonction, 2to3 ne peut pas toujours lire les fichiers contenant la fonction d’affichage. Lorsque 2to3 détecte la présence de la directive compilateur from __future__ import print_function, il modifie sa grammaire interne pour interpréter print() comme une fonction. Cette modification peut également être activée manuellement avec l’option -p. Utilisez -p pour exécuter des correcteurs sur du code dont les instructions d’affichage ont déjà été converties.

L’option -o ou --output-dir permet de donner autre répertoire pour les fichiers de sortie en écriture. L’option -n est requise quand on les utilise comme fichiers de sauvegarde qui n’ont pas de sens si les fichiers d’entrée ne sont pas écrasés.

Nouveau dans la version 3.2.3: L’option -o a été ajoutée.

L’option -W ou —write-unchanged-files indique à 2to3 de toujours écrire des fichiers de sortie même si aucun changement du fichier n’était nécessaire. Ceci est très utile avec !-o pour qu’un arbre des sources Python entier soit copié avec la traduction d’un répertoire à l’autre. Cette option implique -w sans quoi elle n’aurait pas de sens.

Nouveau dans la version 3.2.3: L’option -W a été ajoutée.

L’option --add-suffix spécifie une chaîne à ajouter à tous les noms de fichiers de sortie. L’option -n est nécessaire dans ce cas, puisque sauvegarder n’est pas nécessaire en écrivant dans des fichiers différents. Exemple:

$ 2to3 -n -W --add-suffix=3 example.py

Écrit un fichier converti nommé example.py3.

Nouveau dans la version 3.2.3: L’option --add-suffix est ajoutée.

Pour traduire un projet entier d’une arborescence de répertoires à une autre, utilisez :

$ 2to3 --output-dir=python3-version/mycode -W -n python2-version/mycode

26.7.2. Correcteurs

Chaque étape de la transformation du code est encapsulée dans un correcteur. La commande 2to3 -l les énumère. Comme documenté ci-dessus, chacun peut être activé ou désactivé individuellement. Ils sont décrits plus en détails ici.

apply

Supprime l’usage d”apply(). Par exemple, apply(function, *args, **kwargs) est converti en function(*args, **kwargs).

asserts

Remplace les noms de méthodes obsolètes du module unittest par les bons.

De

À

failUnlessEqual(a, b)

assertEqual(a, b)

assertEquals(a, b)

assertEqual(a, b)

failIfEqual(a, b)

assertNotEqual(a, b)

assertNotEquals(a, b)

assertNotEqual(a, b)

failUnless(a)

assertTrue(a)

assert_(a)

assertTrue(a)

failIf(a)

assertFalse(a)

failUnlessRaises(exc, cal)

assertRaises(exc, cal)

failUnlessAlmostEqual(a, b)

assertAlmostEqual(a, b)

assertAlmostEquals(a, b)

assertAlmostEqual(a, b)

failIfAlmostEqual(a, b)

assertNotAlmostEqual(a, b)

assertNotAlmostEquals(a, b)

assertNotAlmostEqual(a, b)

basestring

Convertit une basestring en str.

buffer

Convertit un buffer en memoryview. Ce correcteur est optionnel car l’API memoryview est similaire mais pas exactement pareil que celle de buffer.

dict

Fixe les méthodes d’itération sur les dictionnaires. dict.iteritems() est converti en dict.items(), dict.iterkeys() en dict.keys() et dict.itervalues() en dict.values(). De la même façon, dict.viewitems(), dict.viewkeys() et dict.viewvalues() sont convertis respectivement en dict.items(), dict.keys() et dict.values(). Il encapsule également les usages existants de dict.items(), dict.keys() et dict.values() dans un appel à list.

except

Convertit except X, T en except X as T.

exec

Convertit l’instruction exec en fonction exec().

execfile

Supprime l’usage de execfile(). L’argument de execfile() est encapsulé dans des appels à open(), compile() et exec().

exitfunc

Change l’affectation de sys.exitfunc pour utiliser le module atexit.

filter

Encapsule l’usage de filter() dans un appel à list.

funcattrs

Fixe les attributs de fonction ayant été renommés. Par exemple, my_function.func_closure est converti en my_function.__closure__.

future

Supprime les instructions from __future__ import new_feature.

getcwdu

Renomme os.getcwdu() en os.getcwd().

has_key

Change dict.has_key(key) en key in dict.

idioms

Ce correcteur optionnel effectue plusieurs transformations rendant le code Python plus idiomatique. Les comparaisons de types telles que type(x) is SomeClass et type(x) == SomeClass sont converties en isinstance(x, SomeClass). while 1 devient while True. Ce correcteur essaye aussi d’utiliser sorted() aux endroits appropriés. Par exemple, ce bloc

L = list(some_iterable)
L.sort()

est transformé en

L = sorted(some_iterable)

import

Détecte les importations voisines et les convertit en importations relatives.

imports

Gère les renommages de modules dans la bibliothèque standard.

imports2

Gères d’autres renommages de modules dans la bibliothèque standard. Il est distinct de imports seulement en raison de limitations techniques.

input

Convertit input(prompt) en eval(input(prompt)).

intern

Convertit intern() en sys.intern().

isinstance

Fixe les types dupliqués dans le second argument de isinstance(). Par exemple, isinstance(x, (int, int)) est converti en isinstance(x, int) et isinstance(x, (int, float, int)) est converti en isinstance(x, (int, float)).

itertools_imports

Supprime les importations de itertools.ifilter(), itertools.izip() et itertools.imap(). Les importations de itertools.ifilterfalse() sont aussi changées en itertools.filterfalse().

itertools

Change l’usage de itertools.ifilter(), itertools.izip() et itertools.imap() en leurs équivalents intégrés. itertools.ifilterfalse() est changé en itertools.filterfalse().

long

Renomme long en int.

map

Encapsule map() dans un appel à list. Change aussi map(None, x) en list(x). L’usage de from future_builtins import map désactive ce correcteur.

metaclass

Convertit l’ancienne syntaxe de métaclasse (__metaclass__ = Meta dans le corps de la classe) à la nouvelle (class X(metaclasse=Meta)).

methodattrs

Fixe les anciens noms d’attributs de méthodes. Par exemple, meth.im_func est converti en meth.__func__.

ne

Convertit l’ancienne syntaxe d’inégalité, <>, en !=.

next

Convertit l’usage des méthodes next() de l” itérateur en next(). Renomme également les méthodes next() en __next__().

nonzero

Renomme __nonzero__() en __bool__().

numliterals

Convertit les nombres écrits littéralement en octal dans leur nouvelle syntaxe.

operator

Converts calls to various functions in the operator module to other, but equivalent, function calls. When needed, the appropriate import statements are added, e.g. import collections. The following mapping are made:

De

À

operator.isCallable(obj)

hasattr(obj, '__call__')

operator.sequenceIncludes(obj)

operator.contains(obj)

operator.isSequenceType(obj)

isinstance(obj, collections.Sequence)

operator.isMappingType(obj)

isinstance(obj, collections.Mapping)

operator.isNumberType(obj)

isinstance(obj, numbers.Number)

operator.repeat(obj, n)

operator.mul(obj, n)

operator.irepeat(obj, n)

operator.imul(obj, n)

paren

Ajoute des parenthèses supplémentaires lorsqu’elles sont nécessaires dans les listes en compréhension. Par exemple, [x for x in 1, 2] devient [x for x in (1, 2)].

print

Convertit l’instruction print en fonction print().

raise

Convertit raise E, V en raise E(V) et raise E, V, T en raise E(V).with_traceback(T). Si E est un tuple, la conversion sera incorrecte puisque la substitution de tuples aux exceptions a été supprimée en 3.0.

raw_input

Convertit raw_input() en input().

reduce

Gère le déplacement de reduce() à functools.reduce().

reload

Convertit les appels à reload() en appels à imp.reload().

renames

Change sys.maxint en sys.maxsize.

repr

Remplace les accents graves utilisés comme repr par des appels à repr().

set_literal

Remplace l’usage du constructeur de set par les ensembles littéraux. Ce correcteur est optionnel.

standarderror

Renomme StandardError en Exception.

sys_exc

Change les sys.exc_value, sys.exc_type, sys.exc_traceback dépréciés en sys.exc_info().

throw

Fixe le changement de l’API dans la méthode throw() du générateur.

tuple_params

Supprime la décompression implicite des paramètres d’un tuple. Ce correcteur ajoute des variables temporaires.

types

Fixe le code cassé par la suppression de certains membres du module types.

unicode

Renomme unicode en str.

urllib

Gère le renommage des paquets urllib et urllib2 en urllib.

ws_comma

Supprime l’espace excédentaire des éléments séparés par des virgules. Ce correcteur est optionnel.

xrange

Renomme la fonction xrange() en range() et encapsule les appels à la fonction range() avec des appels à list.

xreadlines

Change for x in file.xreadlines() en for x in file.

zip

Encapsule l’usage de zip() dans un appel à list. Ceci est désactivé lorsque from future_builtins import zip apparaît.

26.7.3. lib2to3 — la bibliothèque de 2to3

Code source: Lib/lib2to3/ [https://github.com/python/cpython/tree/3.6/Lib/lib2to3/]

Note

L’API de lib2to3 devrait être considérée instable et peut changer drastiquement dans le futur.

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26.8. test — Regression tests package for Python

Note

The test package is meant for internal use by Python only. It is documented for the benefit of the core developers of Python. Any use of this package outside of Python’s standard library is discouraged as code mentioned here can change or be removed without notice between releases of Python.

The test package contains all regression tests for Python as well as the modules test.support and test.regrtest. test.support is used to enhance your tests while test.regrtest drives the testing suite.

Each module in the test package whose name starts with test_ is a testing suite for a specific module or feature. All new tests should be written using the unittest or doctest module. Some older tests are written using a « traditional » testing style that compares output printed to sys.stdout; this style of test is considered deprecated.

Voir aussi

Module unittest

Writing PyUnit regression tests.

Module doctest

Tests embedded in documentation strings.

26.8.1. Writing Unit Tests for the test package

It is preferred that tests that use the unittest module follow a few guidelines. One is to name the test module by starting it with test_ and end it with the name of the module being tested. The test methods in the test module should start with test_ and end with a description of what the method is testing. This is needed so that the methods are recognized by the test driver as test methods. Also, no documentation string for the method should be included. A comment (such as # Tests function returns only True or False) should be used to provide documentation for test methods. This is done because documentation strings get printed out if they exist and thus what test is being run is not stated.

A basic boilerplate is often used:

import unittest
from test import support

class MyTestCase1(unittest.TestCase):

    # Only use setUp() and tearDown() if necessary

    def setUp(self):
        ... code to execute in preparation for tests ...

    def tearDown(self):
        ... code to execute to clean up after tests ...

    def test_feature_one(self):
        # Test feature one.
        ... testing code ...

    def test_feature_two(self):
        # Test feature two.
        ... testing code ...

    ... more test methods ...

class MyTestCase2(unittest.TestCase):
    ... same structure as MyTestCase1 ...

... more test classes ...

if __name__ == '__main__':
    unittest.main()

This code pattern allows the testing suite to be run by test.regrtest, on its own as a script that supports the unittest CLI, or via the python -m unittest CLI.

The goal for regression testing is to try to break code. This leads to a few guidelines to be followed:

The testing suite should exercise all classes, functions, and constants. This includes not just the external API that is to be presented to the outside world but also « private » code.

Whitebox testing (examining the code being tested when the tests are being written) is preferred. Blackbox testing (testing only the published user interface) is not complete enough to make sure all boundary and edge cases are tested.

Make sure all possible values are tested including invalid ones. This makes sure that not only all valid values are acceptable but also that improper values are handled correctly.

Exhaust as many code paths as possible. Test where branching occurs and thus tailor input to make sure as many different paths through the code are taken.

Add an explicit test for any bugs discovered for the tested code. This will make sure that the error does not crop up again if the code is changed in the future.

Make sure to clean up after your tests (such as close and remove all temporary files).

If a test is dependent on a specific condition of the operating system then verify the condition already exists before attempting the test.

Import as few modules as possible and do it as soon as possible. This minimizes external dependencies of tests and also minimizes possible anomalous behavior from side-effects of importing a module.

Try to maximize code reuse. On occasion, tests will vary by something as small as what type of input is used. Minimize code duplication by subclassing a basic test class with a class that specifies the input:

class TestFuncAcceptsSequencesMixin:

    func = mySuperWhammyFunction

    def test_func(self):
        self.func(self.arg)

class AcceptLists(TestFuncAcceptsSequencesMixin, unittest.TestCase):
    arg = [1, 2, 3]

class AcceptStrings(TestFuncAcceptsSequencesMixin, unittest.TestCase):
    arg = 'abc'

class AcceptTuples(TestFuncAcceptsSequencesMixin, unittest.TestCase):
    arg = (1, 2, 3)

When using this pattern, remember that all classes that inherit from unittest.TestCase are run as tests. The Mixin class in the example above does not have any data and so can’t be run by itself, thus it does not inherit from unittest.TestCase.

Voir aussi

Test Driven Development

A book by Kent Beck on writing tests before code.

26.8.2. Running tests using the command-line interface

The test package can be run as a script to drive Python’s regression test suite, thanks to the -m option: python -m test. Under the hood, it uses test.regrtest; the call python -m test.regrtest used in previous Python versions still works. Running the script by itself automatically starts running all regression tests in the test package. It does this by finding all modules in the package whose name starts with test_, importing them, and executing the function test_main() if present or loading the tests via unittest.TestLoader.loadTestsFromModule if test_main does not exist. The names of tests to execute may also be passed to the script. Specifying a single regression test (python -m test test_spam) will minimize output and only print whether the test passed or failed.

Running test directly allows what resources are available for tests to use to be set. You do this by using the -u command-line option. Specifying all as the value for the -u option enables all possible resources: python -m test -uall. If all but one resource is desired (a more common case), a comma-separated list of resources that are not desired may be listed after all. The command python -m test -uall,-audio,-largefile will run test with all resources except the audio and largefile resources. For a list of all resources and more command-line options, run python -m test -h.

Some other ways to execute the regression tests depend on what platform the tests are being executed on. On Unix, you can run make test at the top-level directory where Python was built. On Windows, executing rt.bat from your PCBuild directory will run all regression tests.

26.9. test.support — Utilities for the Python test suite

The test.support module provides support for Python’s regression test suite.

Note

test.support is not a public module. It is documented here to help Python developers write tests. The API of this module is subject to change without backwards compatibility concerns between releases.

This module defines the following exceptions:

exception test.support.TestFailed

Exception to be raised when a test fails. This is deprecated in favor of unittest-based tests and unittest.TestCase’s assertion methods.

exception test.support.ResourceDenied

Subclass of unittest.SkipTest. Raised when a resource (such as a network connection) is not available. Raised by the requires() function.

The test.support module defines the following constants:

test.support.verbose

True when verbose output is enabled. Should be checked when more detailed information is desired about a running test. verbose is set by test.regrtest.

test.support.is_jython

True if the running interpreter is Jython.

test.support.TESTFN

Set to a name that is safe to use as the name of a temporary file. Any temporary file that is created should be closed and unlinked (removed).

The test.support module defines the following functions:

test.support.forget(module_name)

Remove the module named module_name from sys.modules and delete any byte-compiled files of the module.

test.support.is_resource_enabled(resource)

Return True if resource is enabled and available. The list of available resources is only set when test.regrtest is executing the tests.

test.support.requires(resource, msg=None)

Raise ResourceDenied if resource is not available. msg is the argument to ResourceDenied if it is raised. Always returns True if called by a function whose __name__ is '__main__'. Used when tests are executed by test.regrtest.

test.support.findfile(filename, subdir=None)

Return the path to the file named filename. If no match is found filename is returned. This does not equal a failure since it could be the path to the file.

Setting subdir indicates a relative path to use to find the file rather than looking directly in the path directories.

test.support.run_unittest(*classes)

Execute unittest.TestCase subclasses passed to the function. The function scans the classes for methods starting with the prefix test_ and executes the tests individually.

It is also legal to pass strings as parameters; these should be keys in sys.modules. Each associated module will be scanned by unittest.TestLoader.loadTestsFromModule(). This is usually seen in the following test_main() function:

def test_main():
    support.run_unittest(__name__)

This will run all tests defined in the named module.

test.support.run_doctest(module, verbosity=None)

Run doctest.testmod() on the given module. Return (failure_count, test_count).

If verbosity is None, doctest.testmod() is run with verbosity set to verbose. Otherwise, it is run with verbosity set to None.

test.support.check_warnings(*filters, quiet=True)

A convenience wrapper for warnings.catch_warnings() that makes it easier to test that a warning was correctly raised. It is approximately equivalent to calling warnings.catch_warnings(record=True) with warnings.simplefilter() set to always and with the option to automatically validate the results that are recorded.

check_warnings accepts 2-tuples of the form ("message regexp", WarningCategory) as positional arguments. If one or more filters are provided, or if the optional keyword argument quiet is False, it checks to make sure the warnings are as expected: each specified filter must match at least one of the warnings raised by the enclosed code or the test fails, and if any warnings are raised that do not match any of the specified filters the test fails. To disable the first of these checks, set quiet to True.

If no arguments are specified, it defaults to:

check_warnings(("", Warning), quiet=True)

In this case all warnings are caught and no errors are raised.

On entry to the context manager, a WarningRecorder instance is returned. The underlying warnings list from catch_warnings() is available via the recorder object’s warnings attribute. As a convenience, the attributes of the object representing the most recent warning can also be accessed directly through the recorder object (see example below). If no warning has been raised, then any of the attributes that would otherwise be expected on an object representing a warning will return None.

The recorder object also has a reset() method, which clears the warnings list.

The context manager is designed to be used like this:

with check_warnings(("assertion is always true", SyntaxWarning),
                    ("", UserWarning)):
    exec('assert(False, "Hey!")')
    warnings.warn(UserWarning("Hide me!"))

In this case if either warning was not raised, or some other warning was raised, check_warnings() would raise an error.

When a test needs to look more deeply into the warnings, rather than just checking whether or not they occurred, code like this can be used:

with check_warnings(quiet=True) as w:
    warnings.warn("foo")
    assert str(w.args[0]) == "foo"
    warnings.warn("bar")
    assert str(w.args[0]) == "bar"
    assert str(w.warnings[0].args[0]) == "foo"
    assert str(w.warnings[1].args[0]) == "bar"
    w.reset()
    assert len(w.warnings) == 0

Here all warnings will be caught, and the test code tests the captured warnings directly.

Modifié dans la version 3.2: New optional arguments filters and quiet.

test.support.captured_stdin()

test.support.captured_stdout()

test.support.captured_stderr()

A context managers that temporarily replaces the named stream with io.StringIO object.

Example use with output streams:

with captured_stdout() as stdout, captured_stderr() as stderr:
    print("hello")
    print("error", file=sys.stderr)
assert stdout.getvalue() == "hello\n"
assert stderr.getvalue() == "error\n"

Example use with input stream:

with captured_stdin() as stdin:
    stdin.write('hello\n')
    stdin.seek(0)
    # call test code that consumes from sys.stdin
    captured = input()
self.assertEqual(captured, "hello")

test.support.temp_dir(path=None, quiet=False)

A context manager that creates a temporary directory at path and yields the directory.

If path is None, the temporary directory is created using tempfile.mkdtemp(). If quiet is False, the context manager raises an exception on error. Otherwise, if path is specified and cannot be created, only a warning is issued.

test.support.change_cwd(path, quiet=False)

A context manager that temporarily changes the current working directory to path and yields the directory.

If quiet is False, the context manager raises an exception on error. Otherwise, it issues only a warning and keeps the current working directory the same.

test.support.temp_cwd(name='tempcwd', quiet=False)

A context manager that temporarily creates a new directory and changes the current working directory (CWD).

The context manager creates a temporary directory in the current directory with name name before temporarily changing the current working directory. If name is None, the temporary directory is created using tempfile.mkdtemp().

If quiet is False and it is not possible to create or change the CWD, an error is raised. Otherwise, only a warning is raised and the original CWD is used.

test.support.temp_umask(umask)

A context manager that temporarily sets the process umask.

test.support.can_symlink()

Return True if the OS supports symbolic links, False otherwise.

@test.support.skip_unless_symlink

A decorator for running tests that require support for symbolic links.

@test.support.anticipate_failure(condition)

A decorator to conditionally mark tests with unittest.expectedFailure(). Any use of this decorator should have an associated comment identifying the relevant tracker issue.

@test.support.run_with_locale(catstr, *locales)

A decorator for running a function in a different locale, correctly resetting it after it has finished. catstr is the locale category as a string (for example "LC_ALL"). The locales passed will be tried sequentially, and the first valid locale will be used.

test.support.make_bad_fd()

Create an invalid file descriptor by opening and closing a temporary file, and returning its descriptor.

test.support.import_module(name, deprecated=False)

This function imports and returns the named module. Unlike a normal import, this function raises unittest.SkipTest if the module cannot be imported.

Module and package deprecation messages are suppressed during this import if deprecated is True.

Nouveau dans la version 3.1.

test.support.import_fresh_module(name, fresh=(), blocked=(), deprecated=False)

This function imports and returns a fresh copy of the named Python module by removing the named module from sys.modules before doing the import. Note that unlike reload(), the original module is not affected by this operation.

fresh is an iterable of additional module names that are also removed from the sys.modules cache before doing the import.

blocked is an iterable of module names that are replaced with None in the module cache during the import to ensure that attempts to import them raise ImportError.

The named module and any modules named in the fresh and blocked parameters are saved before starting the import and then reinserted into sys.modules when the fresh import is complete.

Module and package deprecation messages are suppressed during this import if deprecated is True.

This function will raise ImportError if the named module cannot be imported.

Example use:

# Get copies of the warnings module for testing without affecting the
# version being used by the rest of the test suite. One copy uses the
# C implementation, the other is forced to use the pure Python fallback
# implementation
py_warnings = import_fresh_module('warnings', blocked=['_warnings'])
c_warnings = import_fresh_module('warnings', fresh=['_warnings'])

Nouveau dans la version 3.1.

test.support.bind_port(sock, host=HOST)

Bind the socket to a free port and return the port number. Relies on ephemeral ports in order to ensure we are using an unbound port. This is important as many tests may be running simultaneously, especially in a buildbot environment. This method raises an exception if the sock.family is AF_INET and sock.type is SOCK_STREAM, and the socket has SO_REUSEADDR or SO_REUSEPORT set on it. Tests should never set these socket options for TCP/IP sockets. The only case for setting these options is testing multicasting via multiple UDP sockets.

Additionally, if the SO_EXCLUSIVEADDRUSE socket option is available (i.e. on Windows), it will be set on the socket. This will prevent anyone else from binding to our host/port for the duration of the test.

test.support.find_unused_port(family=socket.AF_INET, socktype=socket.SOCK_STREAM)

Returns an unused port that should be suitable for binding. This is achieved by creating a temporary socket with the same family and type as the sock parameter (default is AF_INET, SOCK_STREAM), and binding it to the specified host address (defaults to 0.0.0.0) with the port set to 0, eliciting an unused ephemeral port from the OS. The temporary socket is then closed and deleted, and the ephemeral port is returned.

Either this method or bind_port() should be used for any tests where a server socket needs to be bound to a particular port for the duration of the test. Which one to use depends on whether the calling code is creating a python socket, or if an unused port needs to be provided in a constructor or passed to an external program (i.e. the -accept argument to openssl’s s_server mode). Always prefer bind_port() over find_unused_port() where possible. Using a hard coded port is discouraged since it can make multiple instances of the test impossible to run simultaneously, which is a problem for buildbots.

test.support.load_package_tests(pkg_dir, loader, standard_tests, pattern)

Generic implementation of the unittest load_tests protocol for use in test packages. pkg_dir is the root directory of the package; loader, standard_tests, and pattern are the arguments expected by load_tests. In simple cases, the test package’s __init__.py can be the following:

import os
from test.support import load_package_tests

def load_tests(*args):
    return load_package_tests(os.path.dirname(__file__), *args)

test.support.detect_api_mismatch(ref_api, other_api, *, ignore=())

Returns the set of attributes, functions or methods of ref_api not found on other_api, except for a defined list of items to be ignored in this check specified in ignore.

By default this skips private attributes beginning with “_” but includes all magic methods, i.e. those starting and ending in “__”.

Nouveau dans la version 3.5.

test.support.check__all__(test_case, module, name_of_module=None, extra=(), blacklist=())

Assert that the __all__ variable of module contains all public names.

The module’s public names (its API) are detected automatically based on whether they match the public name convention and were defined in module.

The name_of_module argument can specify (as a string or tuple thereof) what module(s) an API could be defined in in order to be detected as a public API. One case for this is when module imports part of its public API from other modules, possibly a C backend (like csv and its _csv).

The extra argument can be a set of names that wouldn’t otherwise be automatically detected as « public », like objects without a proper __module__ attribute. If provided, it will be added to the automatically detected ones.

The blacklist argument can be a set of names that must not be treated as part of the public API even though their names indicate otherwise.

Example use:

import bar
import foo
import unittest
from test import support

class MiscTestCase(unittest.TestCase):
    def test__all__(self):
        support.check__all__(self, foo)

class OtherTestCase(unittest.TestCase):
    def test__all__(self):
        extra = {'BAR_CONST', 'FOO_CONST'}
        blacklist = {'baz'}  # Undocumented name.
        # bar imports part of its API from _bar.
        support.check__all__(self, bar, ('bar', '_bar'),
                             extra=extra, blacklist=blacklist)

Nouveau dans la version 3.6.

The test.support module defines the following classes:

class test.support.TransientResource(exc, **kwargs)

Instances are a context manager that raises ResourceDenied if the specified exception type is raised. Any keyword arguments are treated as attribute/value pairs to be compared against any exception raised within the with statement. Only if all pairs match properly against attributes on the exception is ResourceDenied raised.

class test.support.EnvironmentVarGuard

Class used to temporarily set or unset environment variables. Instances can be used as a context manager and have a complete dictionary interface for querying/modifying the underlying os.environ. After exit from the context manager all changes to environment variables done through this instance will be rolled back.

Modifié dans la version 3.1: Added dictionary interface.

EnvironmentVarGuard.set(envvar, value)

Temporarily set the environment variable envvar to the value of value.

EnvironmentVarGuard.unset(envvar)

Temporarily unset the environment variable envvar.

class test.support.SuppressCrashReport

A context manager used to try to prevent crash dialog popups on tests that are expected to crash a subprocess.

On Windows, it disables Windows Error Reporting dialogs using SetErrorMode [https://msdn.microsoft.com/en-us/library/windows/desktop/ms680621.aspx].

On UNIX, resource.setrlimit() is used to set resource.RLIMIT_CORE’s soft limit to 0 to prevent coredump file creation.

On both platforms, the old value is restored by __exit__().

class test.support.WarningsRecorder

Class used to record warnings for unit tests. See documentation of check_warnings() above for more details.

class test.support.FakePath(path)

Simple path-like object. It implements the __fspath__() method which just returns the path argument. If path is an exception, it will be raised in __fspath__().

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27. Débogueur et instrumentation

Ces bibliothèques sont là pour vous aider lors du développement en Python : Le débogueur vous permet d’avancer pas à pas dans le code, d’analyser la pile d’appel, de placer des points d’arrêts, … Les outils d’instrumentation exécutent du code et vous donnent un rapport détaillé du temps d’exécution, vous permettant d’identifier les goulots d’étranglement dans vos programmes.

27.1. bdb — Framework de débogage

27.2. faulthandler — Dump the Python traceback

27.2.1. Dumping the traceback

27.2.2. Fault handler state

27.2.3. Dumping the tracebacks after a timeout

27.2.4. Dumping the traceback on a user signal

27.2.5. Issue with file descriptors

27.2.6. Exemple

27.3. pdb — Le débogueur Python

27.3.1. Commande du débogueur

27.4. The Python Profilers

27.4.1. Introduction to the profilers

27.4.2. Instant User’s Manual

27.4.3. profile and cProfile Module Reference

27.4.4. The Stats Class

27.4.5. What Is Deterministic Profiling?

27.4.6. Limitations

27.4.7. Calibration

27.4.8. Using a custom timer

27.5. timeit — Mesurer le temps d’exécution de fragments de code

27.5.1. Exemples simples

27.5.2. Interface Python

27.5.3. Interface en ligne de commande

27.5.4. Exemples

27.6. trace — Trace or track Python statement execution

27.6.1. Utilisation en ligne de commande.

27.6.1.1. Main options

27.6.1.2. Modifiers

27.6.1.3. Filters

27.6.2. Programmatic Interface

27.7. tracemalloc — Trace memory allocations

27.7.1. Exemples

27.7.1.1. Display the top 10

27.7.1.2. Compute differences

27.7.1.3. Get the traceback of a memory block

27.7.1.4. Pretty top

27.7.2. API

27.7.2.1. Fonctions

27.7.2.2. DomainFilter

27.7.2.3. Filter

27.7.2.4. Frame

27.7.2.5. Snapshot

27.7.2.6. Statistic

27.7.2.7. StatisticDiff

27.7.2.8. Trace

27.7.2.9. Traceback

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27.1. bdb — Framework de débogage

Code source : Lib/bdb.py [https://github.com/python/cpython/tree/3.6/Lib/bdb.py]

The bdb module handles basic debugger functions, like setting breakpoints or managing execution via the debugger.

L’exception suivante est définie :

exception bdb.BdbQuit

Exception raised by the Bdb class for quitting the debugger.

Le module bdb définis deux classes :

class bdb.Breakpoint(self, file, line, temporary=0, cond=None, funcname=None)

This class implements temporary breakpoints, ignore counts, disabling and (re-)enabling, and conditionals.

Breakpoints are indexed by number through a list called bpbynumber and by (file, line) pairs through bplist. The former points to a single instance of class Breakpoint. The latter points to a list of such instances since there may be more than one breakpoint per line.

When creating a breakpoint, its associated filename should be in canonical form. If a funcname is defined, a breakpoint hit will be counted when the first line of that function is executed. A conditional breakpoint always counts a hit.

Breakpoint instances have the following methods:

deleteMe()

Delete the breakpoint from the list associated to a file/line. If it is the last breakpoint in that position, it also deletes the entry for the file/line.

enable()

Active le point d’arrêt.

disable()

Désactive le point d’arrêt.

bpformat()

Return a string with all the information about the breakpoint, nicely formatted:

Le numéro du point d’arrêt.

S’il est temporaire ou non.

Its file,line position.

The condition that causes a break.

If it must be ignored the next N times.

The breakpoint hit count.

Nouveau dans la version 3.2.

bpprint(out=None)

Print the output of bpformat() to the file out, or if it is None, to standard output.

class bdb.Bdb(skip=None)

The Bdb class acts as a generic Python debugger base class.

This class takes care of the details of the trace facility; a derived class should implement user interaction. The standard debugger class (pdb.Pdb) is an example.

The skip argument, if given, must be an iterable of glob-style module name patterns. The debugger will not step into frames that originate in a module that matches one of these patterns. Whether a frame is considered to originate in a certain module is determined by the __name__ in the frame globals.

Nouveau dans la version 3.1: L’argument skip.

The following methods of Bdb normally don’t need to be overridden.

canonic(filename)

Auxiliary method for getting a filename in a canonical form, that is, as a case-normalized (on case-insensitive filesystems) absolute path, stripped of surrounding angle brackets.

reset()

Set the botframe, stopframe, returnframe and quitting attributes with values ready to start debugging.

trace_dispatch(frame, event, arg)

This function is installed as the trace function of debugged frames. Its return value is the new trace function (in most cases, that is, itself).

The default implementation decides how to dispatch a frame, depending on the type of event (passed as a string) that is about to be executed. event can be one of the following:

"line": A new line of code is going to be executed.

"call": A function is about to be called, or another code block entered.

"return": A function or other code block is about to return.

"exception" : Une exception est survenue.

"c_call" : Une fonction C est sur le point d’être appelée.

"c_return" : Une fonction C s’est terminée.

"c_exception": A C function has raised an exception.

For the Python events, specialized functions (see below) are called. For the C events, no action is taken.

Le paramètre arg dépend de l’événement précédent.

See the documentation for sys.settrace() for more information on the trace function. For more information on code and frame objects, refer to Hiérarchie des types standards.

dispatch_line(frame)

If the debugger should stop on the current line, invoke the user_line() method (which should be overridden in subclasses). Raise a BdbQuit exception if the Bdb.quitting flag is set (which can be set from user_line()). Return a reference to the trace_dispatch() method for further tracing in that scope.

dispatch_call(frame, arg)

If the debugger should stop on this function call, invoke the user_call() method (which should be overridden in subclasses). Raise a BdbQuit exception if the Bdb.quitting flag is set (which can be set from user_call()). Return a reference to the trace_dispatch() method for further tracing in that scope.

dispatch_return(frame, arg)

If the debugger should stop on this function return, invoke the user_return() method (which should be overridden in subclasses). Raise a BdbQuit exception if the Bdb.quitting flag is set (which can be set from user_return()). Return a reference to the trace_dispatch() method for further tracing in that scope.

dispatch_exception(frame, arg)

If the debugger should stop at this exception, invokes the user_exception() method (which should be overridden in subclasses). Raise a BdbQuit exception if the Bdb.quitting flag is set (which can be set from user_exception()). Return a reference to the trace_dispatch() method for further tracing in that scope.

Normally derived classes don’t override the following methods, but they may if they want to redefine the definition of stopping and breakpoints.

stop_here(frame)

This method checks if the frame is somewhere below botframe in the call stack. botframe is the frame in which debugging started.

break_here(frame)

This method checks if there is a breakpoint in the filename and line belonging to frame or, at least, in the current function. If the breakpoint is a temporary one, this method deletes it.

break_anywhere(frame)

This method checks if there is a breakpoint in the filename of the current frame.

Derived classes should override these methods to gain control over debugger operation.

user_call(frame, argument_list)

This method is called from dispatch_call() when there is the possibility that a break might be necessary anywhere inside the called function.

user_line(frame)

This method is called from dispatch_line() when either stop_here() or break_here() yields True.

user_return(frame, return_value)

This method is called from dispatch_return() when stop_here() yields True.

user_exception(frame, exc_info)

This method is called from dispatch_exception() when stop_here() yields True.

do_clear(arg)

Handle how a breakpoint must be removed when it is a temporary one.

This method must be implemented by derived classes.

Derived classes and clients can call the following methods to affect the stepping state.

set_step()

Arrête après une ligne de code.

set_next(frame)

Stop on the next line in or below the given frame.

set_return(frame)

Stop when returning from the given frame.

set_until(frame)

Stop when the line with the line no greater than the current one is reached or when returning from current frame.

set_trace([frame])

Start debugging from frame. If frame is not specified, debugging starts from caller’s frame.

set_continue()

Stop only at breakpoints or when finished. If there are no breakpoints, set the system trace function to None.

set_quit()

Set the quitting attribute to True. This raises BdbQuit in the next call to one of the dispatch_*() methods.

Derived classes and clients can call the following methods to manipulate breakpoints. These methods return a string containing an error message if something went wrong, or None if all is well.

set_break(filename, lineno, temporary=0, cond, funcname)

Set a new breakpoint. If the lineno line doesn’t exist for the filename passed as argument, return an error message. The filename should be in canonical form, as described in the canonic() method.

clear_break(filename, lineno)

Delete the breakpoints in filename and lineno. If none were set, an error message is returned.

clear_bpbynumber(arg)

Delete the breakpoint which has the index arg in the Breakpoint.bpbynumber. If arg is not numeric or out of range, return an error message.

clear_all_file_breaks(filename)

Delete all breakpoints in filename. If none were set, an error message is returned.

clear_all_breaks()

Supprime tous les points d’arrêt définis.

get_bpbynumber(arg)

Return a breakpoint specified by the given number. If arg is a string, it will be converted to a number. If arg is a non-numeric string, if the given breakpoint never existed or has been deleted, a ValueError is raised.

Nouveau dans la version 3.2.

get_break(filename, lineno)

Check if there is a breakpoint for lineno of filename.

get_breaks(filename, lineno)

Return all breakpoints for lineno in filename, or an empty list if none are set.

get_file_breaks(filename)

Return all breakpoints in filename, or an empty list if none are set.

get_all_breaks()

Donne tous les points d’arrêt définis.

Derived classes and clients can call the following methods to get a data structure representing a stack trace.

get_stack(f, t)

Get a list of records for a frame and all higher (calling) and lower frames, and the size of the higher part.

format_stack_entry(frame_lineno, lprefix=': ')

Return a string with information about a stack entry, identified by a (frame, lineno) tuple:

The canonical form of the filename which contains the frame.

Le nom de la fonction, ou "<lambda>".

Les arguments donnés.

Le résultat.

La ligne de code (si elle existe).

The following two methods can be called by clients to use a debugger to debug a statement, given as a string.

run(cmd, globals=None, locals=None)

Debug a statement executed via the exec() function. globals defaults to __main__.__dict__, locals defaults to globals.

runeval(expr, globals=None, locals=None)

Debug an expression executed via the eval() function. globals and locals have the same meaning as in run().

runctx(cmd, globals, locals)

For backwards compatibility. Calls the run() method.

runcall(func, *args, **kwds)

Debug a single function call, and return its result.

Finally, the module defines the following functions:

bdb.checkfuncname(b, frame)

Check whether we should break here, depending on the way the breakpoint b was set.

If it was set via line number, it checks if b.line is the same as the one in the frame also passed as argument. If the breakpoint was set via function name, we have to check we are in the right frame (the right function) and if we are in its first executable line.

bdb.effective(file, line, frame)

Determine if there is an effective (active) breakpoint at this line of code. Return a tuple of the breakpoint and a boolean that indicates if it is ok to delete a temporary breakpoint. Return (None, None) if there is no matching breakpoint.

bdb.set_trace()

Start debugging with a Bdb instance from caller’s frame.

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27.2. faulthandler — Dump the Python traceback

Nouveau dans la version 3.3.

This module contains functions to dump Python tracebacks explicitly, on a fault, after a timeout, or on a user signal. Call faulthandler.enable() to install fault handlers for the SIGSEGV, SIGFPE, SIGABRT, SIGBUS, and SIGILL signals. You can also enable them at startup by setting the PYTHONFAULTHANDLER environment variable or by using the -X faulthandler command line option.

The fault handler is compatible with system fault handlers like Apport or the Windows fault handler. The module uses an alternative stack for signal handlers if the sigaltstack() function is available. This allows it to dump the traceback even on a stack overflow.

The fault handler is called on catastrophic cases and therefore can only use signal-safe functions (e.g. it cannot allocate memory on the heap). Because of this limitation traceback dumping is minimal compared to normal Python tracebacks:

Only ASCII is supported. The backslashreplace error handler is used on encoding.

Each string is limited to 500 characters.

Only the filename, the function name and the line number are displayed. (no source code)

It is limited to 100 frames and 100 threads.

The order is reversed: the most recent call is shown first.

By default, the Python traceback is written to sys.stderr. To see tracebacks, applications must be run in the terminal. A log file can alternatively be passed to faulthandler.enable().

The module is implemented in C, so tracebacks can be dumped on a crash or when Python is deadlocked.

27.2.1. Dumping the traceback

faulthandler.dump_traceback(file=sys.stderr, all_threads=True)

Dump the tracebacks of all threads into file. If all_threads is False, dump only the current thread.

Modifié dans la version 3.5: Added support for passing file descriptor to this function.

27.2.2. Fault handler state

faulthandler.enable(file=sys.stderr, all_threads=True)

Enable the fault handler: install handlers for the SIGSEGV, SIGFPE, SIGABRT, SIGBUS and SIGILL signals to dump the Python traceback. If all_threads is True, produce tracebacks for every running thread. Otherwise, dump only the current thread.

The file must be kept open until the fault handler is disabled: see issue with file descriptors.

Modifié dans la version 3.5: Added support for passing file descriptor to this function.

Modifié dans la version 3.6: On Windows, a handler for Windows exception is also installed.

faulthandler.disable()

Disable the fault handler: uninstall the signal handlers installed by enable().

faulthandler.is_enabled()

Check if the fault handler is enabled.

27.2.3. Dumping the tracebacks after a timeout

faulthandler.dump_traceback_later(timeout, repeat=False, file=sys.stderr, exit=False)

Dump the tracebacks of all threads, after a timeout of timeout seconds, or every timeout seconds if repeat is True. If exit is True, call _exit() with status=1 after dumping the tracebacks. (Note _exit() exits the process immediately, which means it doesn’t do any cleanup like flushing file buffers.) If the function is called twice, the new call replaces previous parameters and resets the timeout. The timer has a sub-second resolution.

The file must be kept open until the traceback is dumped or cancel_dump_traceback_later() is called: see issue with file descriptors.

This function is implemented using a watchdog thread and therefore is not available if Python is compiled with threads disabled.

Modifié dans la version 3.5: Added support for passing file descriptor to this function.

faulthandler.cancel_dump_traceback_later()

Cancel the last call to dump_traceback_later().

27.2.4. Dumping the traceback on a user signal

faulthandler.register(signum, file=sys.stderr, all_threads=True, chain=False)

Register a user signal: install a handler for the signum signal to dump the traceback of all threads, or of the current thread if all_threads is False, into file. Call the previous handler if chain is True.

The file must be kept open until the signal is unregistered by unregister(): see issue with file descriptors.

Not available on Windows.

Modifié dans la version 3.5: Added support for passing file descriptor to this function.

faulthandler.unregister(signum)

Unregister a user signal: uninstall the handler of the signum signal installed by register(). Return True if the signal was registered, False otherwise.

Not available on Windows.

27.2.5. Issue with file descriptors

enable(), dump_traceback_later() and register() keep the file descriptor of their file argument. If the file is closed and its file descriptor is reused by a new file, or if os.dup2() is used to replace the file descriptor, the traceback will be written into a different file. Call these functions again each time that the file is replaced.

27.2.6. Exemple

Example of a segmentation fault on Linux with and without enabling the fault handler:

$ python3 -c "import ctypes; ctypes.string_at(0)"
Segmentation fault

$ python3 -q -X faulthandler
>>> import ctypes
>>> ctypes.string_at(0)
Fatal Python error: Segmentation fault

Current thread 0x00007fb899f39700 (most recent call first):
  File "/home/python/cpython/Lib/ctypes/__init__.py", line 486 in string_at
  File "<stdin>", line 1 in <module>
Segmentation fault

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27.3. pdb — Le débogueur Python

Code source : Lib/pdb.py [https://github.com/python/cpython/tree/3.6/Lib/pdb.py]

Le module pdb définit un débogueur de code source interactif pour les programmes Python. Il supporte le paramétrage (conditionnel) de points d’arrêt et l’exécution du code source ligne par ligne, l’inspection des frames de la pile, la liste du code source, et l’évaluation arbitraire de code Python dans le contexte de n’importe quelle frame de la pile. Il supporte aussi le débogage post-mortem et peut être contrôlé depuis un programme.

Le débogueur est extensible – Il est en réalité défini comme la classe Pdb. C’est actuellement non-documenté mais facilement compréhensible en lisant le code source. L’interface d’extension utilise les modules bdb et cmd.

L’invite du débogueur est (Pdb). L’usage typique pour exécuter un programme sous le contrôle du débogueur est :

>>> import pdb
>>> import mymodule
>>> pdb.run('mymodule.test()')
> <string>(0)?()
(Pdb) continue
> <string>(1)?()
(Pdb) continue
NameError: 'spam'
> <string>(1)?()
(Pdb)

Modifié dans la version 3.3: La complétion via le module readline' est disponible pour les commandes et les arguments de commande, par exemple les noms *global* et *local* sont proposés comme arguments de la commande ``p`.

Le fichier pdb.py peut aussi être invoqué comme un script pour déboguer d’autres scripts. Par exemple :

python3 -m pdb myscript.py

Si le programme débogué se termine anormalement, pdb entrera en débogage post-mortem. Après le débogage post-mortem (ou après une sortie normale du programme), pdb redémarrera le programme. Le redémarrage automatique préserve l’état de pdb (tels que les points d’arrêt) et dans la plupart des cas est plus utile que de quitter le débogueur à la sortie du programme.

Nouveau dans la version 3.2: Le fichier pdb.py accepte maintenant une option -c qui exécute les commandes comme si elles provenaient d’un fichier .pdbrc, voir Commande du débogueur.

L’usage typique pour forcer le débogueur depuis un programme s’exécutant est d’insérer

import pdb; pdb.set_trace()

à l’endroit où vous voulez pénétrer dans le débogueur. Vous pouvez alors parcourir le code suivant cette instruction, et continuer à exécuter sans le débogueur en utilisant la commande continue.

L’usage typique pour inspecter un programme planté :

>>> import pdb
>>> import mymodule
>>> mymodule.test()
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "./mymodule.py", line 4, in test
    test2()
  File "./mymodule.py", line 3, in test2
    print(spam)
NameError: spam
>>> pdb.pm()
> ./mymodule.py(3)test2()
-> print(spam)
(Pdb)

Le module définit les fonctions suivantes; chacune entre dans le débogueur d’une manière légèrement différente:

pdb.run(statement, globals=None, locals=None)

Exécute la déclaration (donnée sous forme de chaîne de caractères ou d’objet code) sous le contrôle du débogueur. L’invite de débogage apparaît avant l’exécution de tout code; vous pouvez définir des points d’arrêt et taper continue, ou vous pouvez passer à travers l’instruction en utilisant step ou next (toutes ces commandes sont expliquées ci-dessous). Les arguments globals et locals optionnels spécifient l’environnement dans lequel le code est exécuté; par défaut le dictionnaire du module __main__ est utilisé. (Voir l’explication des fonctions natives exec() ou eval().)

pdb.runeval(expression, globals=None, locals=None)

Évalue l”expression (donné comme une chaine de caractères ou un code objet) sous le contrôle du débogueur. Quand la fonction runeval() retourne, elle renvoie la valeur de l’expression. Autrement cette fonction est similaire à la fonction run().

pdb.runcall(function, *args, **kwds)

Appelle la function (une fonction ou une méthode, pas une chaine de caractères) avec les arguments donnés. Quand runcall() revient, il retourne ce que l’appel de fonctionne a renvoyé. L’invite de débogage apparaît dès que la fonction est entrée.

pdb.set_trace()

Entre le débogueur dans la frame de la pile d’appel. Ceci est utile pour coder en dur un point d’arrêt dans un programme, même si le code n’est pas autrement débogué (par exemple, quand une assertion échoue).

pdb.post_mortem(traceback=None)

Entre le débogage post-mortem de l’objet traceback donné. Si aucun traceback n’est donné, il utilise celui de l’exception en cours de traitement (une exception doit être gérée si la valeur par défaut doit être utilisée).

pdb.pm()

Entre le débogage post-mortem de la trace trouvé dans sys. last_traceback.

Les fonctions run* et set_trace() sont des alias pour instancier la classe Pdb et appeler la méthode du même nom. Si vous souhaitez accéder à d’autres fonctionnalités, vous devez le faire vous-même :

class pdb.Pdb(completekey='tab', stdin=None, stdout=None, skip=None, nosigint=False, readrc=True)

Le classe du débogueur est la classe Pdb.

Les arguments completekey, stdin et stdout sont transmis à la classe sous-jacente cmd.Cmd; voir la description ici.

L’argument skip, s’il est donné, doit être un itérable des noms de modules de style glob. Le débogueur n’entrera pas dans les frames qui proviennent d’un module qui correspond à l’un de ces motifs. 1

Par défaut, Pdb définit un gestionnaire pour le signal SIGINT (qui est envoyé lorsque l’utilisateur appuie sur Ctrl-C sur la console) lorsque vous donnez une commande continue. Ceci vous permet de pénétrer à nouveau dans le débogueur en appuyant sur Ctrl-C. Si vous voulez que Pdb ne touche pas le gestionnaire SIGINT, assignez nosigint à True.

L’argument readrc vaut True par défaut et contrôle si Pdb chargera les fichiers .pdbrc depuis le système de fichiers.

Exemple d’appel pour activer le traçage avec skip :

import pdb; pdb.Pdb(skip=['django.*']).set_trace()

Nouveau dans la version 3.1: L’argument skip.

Nouveau dans la version 3.2: L’argument nosigint. Auparavant, un gestionnaire SIGINT n’était jamais configuré par Pdb.

Modifié dans la version 3.6: L’argument readrc.

run(statement, globals=None, locals=None)

runeval(expression, globals=None, locals=None)

runcall(function, *args, **kwds)

set_trace()

Voir la documentation pour les fonctions expliquées ci-dessus.

27.3.1. Commande du débogueur

Les commandes reconnues par le débogueur sont listées. La plupart des commandes peuvent être abrégées à une ou deux lettres comme indiquées; par exemple. h(elp) signifie que soit h ou help peut être utilisée pour entrer la commande help (mais pas he or hel, ni H ou HELP). Les arguments des commandes doivent être séparées par des espaces (espaces ou tabulations). Les arguments optionnels sont entourés dans des crochets ([]) dans la syntaxe de la commande; les crochets ne doivent pas être insérés. Les alternatives dans la syntaxe de la commande sont séparés par une barre verticale (|).

Entrer une ligne vide répète la dernière commande entrée. Exception: si la dernière commande était la commande list, les 11 prochaines lignes sont affichées.

Les commandes que le débogueur ne reconnaît pas sont supposées être des instructions Python et sont exécutées dans le contexte du programme en cours de débogage. Les instructions Python peuvent également être préfixées avec un point d’exclamation (!). C’est une façon puissante d’inspecter le programme en cours de débogage; il est même possible de changer une variable ou d’appeler une fonction. Lorsqu’une exception se produit dans une telle instruction, le nom de l’exception est affiché mais l’état du débogueur n’est pas modifié.

Le débogueur supporte aliases. Les alias peuvent avoir des paramètres qui permettent un certain niveau d’adaptabilité au contexte étudié.

Plusieurs commandes peuvent être saisies sur une seule ligne, séparées par ;;. (Un seul ; n’est pas utilisé car il est le séparateur de plusieurs commandes dans une ligne qui est passée à l’analyseur Python. Aucune intelligence n’est appliquée pour séparer les commandes; l’entrée est divisée à la première paire de ;; paire, même si il est au milieu d’une chaîne de caractères.

Si un fichier .pdbrc existe dans le répertoire d’accueil de l’utilisateur ou dans le répertoire courant, il est lu et exécuté comme si il avait été écrit dans l’invite du débogueur. C’est particulièrement utile pour les alias. Si les deux fichiers existent, celui dans le répertoire d’accueil de l’utilisateur est lu en premier et les alias définis dedans peuvent être surchargés par le fichier local.

Modifié dans la version 3.2: Le fichier .pdbrc peut maintenant contenir des commandes qui continue le débogage, comme continue ou next. Précédemment, ces commandes n’avaient aucun effet.

h(elp) [command]

Sans argument, affiche la liste des commandes disponibles. Avec une commande comme argument, affiche l’aide de cette commande. help pdb affiche la documentation complète (la docstring du module pdb). Puisque l’argument command doit être un identificateur, help exec doit être entré pour obtenir de l’aide sur la commande !.

w(here)

Affiche une trace de pile, avec la frame le plus récent en bas. Une flèche indique le frame courant, qui détermine le contexte de la plupart des commandes.

d(own) [count]

Déplace le niveau de la frame courante count (par défaut un) vers le bas dans la trace de pile (vers une frame plus récente).

u(p) [count]

Déplace le niveau de la frame courante count (par défaut un) vers le haut dans la trace de pile (vers une frame plus ancienne).

b(reak) [([filename:]lineno | function) [, condition]]

Avec un argument lineno, définit une pause dans le fichier courant. Avec un argument function, définit une pause à la première instruction exécutable dans cette fonction. Le numéro de ligne peut être préfixé d’un nom de fichier et d’un deux-points, pour spécifier un point d’arrêt dans un autre fichier (probablement celui qui n’a pas encore été chargé). Le fichier est recherché sur sys.path. Notez que chaque point d’arrêt reçoit un numéro auquel se réfèrent toutes les autres commandes de point d’arrêt.

Si un second argument est présent, c’est une expression qui doit évaluer à True avant que le point d’arrêt ne soit honoré.

Sans argument, liste tous les arrêts, incluant pour chaque point d’arrêt, le nombre de fois qu’un point d’arrêt a été atteint, le nombre de ignore, et la condition associée le cas échéant.

tbreak [([filename:]lineno | function) [, condition]]

Point d’arrêt temporaire, qui est enlevé automatiquement au premier passage. Les arguments sont les mêmes que pour break.

cl(ear) [filename:lineno | bpnumber [bpnumber ...]]

Avec un argument filename:lineno, efface tous les points d’arrêt sur cette ligne. Avec une liste de numéros de points d’arrêt séparés par un espace, efface ces points d’arrêt. Sans argument, efface tous les points d’arrêt (mais demande d’abord confirmation).

disable [bpnumber [bpnumber ...]]

Désactive les points d’arrêt indiqués sous la forme d’une liste de numéros de points d’arrêt séparés par un espace. Désactiver un point d’arrêt signifie qu’il ne peut pas interrompre l’exécution du programme, mais à la différence d’effacer un point d’arrêt, il reste dans la liste des points d’arrêt et peut être (ré)activé.

enable [bpnumber [bpnumber ...]]

Active les points d’arrêt spécifiés.

ignore bpnumber [count]

Définit le nombre de fois où le point d’arrêt donné sera passé. Si le compte est omis, le compte est mis à 0. Un point d’arrêt devient actif lorsque le compte est nul. Lorsqu’il n’est pas nul, le comptage est diminué à chaque fois que le point d’arrêt est atteint et que le point d’arrêt n’est pas désactivé et que toute condition associée est évaluée comme vraie.

condition bpnumber [condition]

Définit une nouvelle condition pour le point d’arrêt, une expression qui doit évaluer à True avant que le point d’arrêt ne soit honoré. Si condition est absente, toute condition existante est supprimée, c’est-à-dire que le point d’arrêt est rendu inconditionnel.

commands [bpnumber]

Spécifie une liste de commandes pour le numéro du point d’arrêt bpnumber. Les commandes elles-mêmes apparaissent sur les lignes suivantes. Tapez une ligne contenant juste end pour terminer les commandes. Un exemple :

(Pdb) commands 1
(com) p some_variable
(com) end
(Pdb)

Pour supprimer toutes les commandes depuis un point d’arrêt, écrivez commands suivi immédiatement avec end; ceci supprime les commandes.

Sans argument bpnumber, les commandes se réfèrent au dernier point d’arrêt défini.

Vous pouvez utiliser les commandes de point d’arrêt pour redémarrer votre programme. Utilisez simplement la commande continue, ou step, ou toute autre commande qui reprend l’exécution.

Spécifie toute commande reprenant l’exécution (actuellement continue, step, next, return, jump, quit et leurs abréviations) termine la liste des commandes (comme si cette commande était immédiatement suivie de la fin). C’est parce que chaque fois que vous reprenez l’exécution (même avec un simple next ou step), vous pouvez rencontrer un autre point d’arrêt – qui pourrait avoir sa propre liste de commandes, conduisant à des ambiguïtés sur la liste à exécuter.

Si vous utilisez la commande “silence” dans la liste des commandes, le message habituel concernant l’arrêt à un point d’arrêt n’est pas affiché. Ceci peut être souhaitable pour les points d’arrêt qui doivent afficher un message spécifique et ensuite continuer. Si aucune des autres commandes n’affiche quoi que ce soit, vous ne voyez aucun signe indiquant que le point de rupture a été atteint.

s(tep)

Exécute la ligne en cours, s’arrête à la première occasion possible (soit dans une fonction qui est appelée, soit sur la ligne suivante de la fonction courante).

n(ext)

Continue l’exécution jusqu’à ce que la ligne suivante de la fonction en cours soit atteinte ou qu’elle revienne. (La différence entre next et step est que step s’arrête dans une fonction appelée, tandis que next exécute les fonctions appelées à (presque) pleine vitesse, ne s’arrêtant qu’à la ligne suivante dans la fonction courante.)

unt(il) [lineno]

Sans argument, continue l’exécution jusqu’à ce que la ligne avec un nombre supérieur au nombre actuel soit atteinte.

Avec un numéro de ligne, continue l’exécution jusqu’à ce qu’une ligne avec un numéro supérieur ou égal à celui-ci soit atteinte. Dans les deux cas, arrête également lorsque la frame courante revient.

Modifié dans la version 3.2: Permet de donner un numéro de ligne explicite.

r(eturn)

Continue l’exécution jusqu’au retour de la fonction courante.

c(ont(inue))

Continue l’exécution, seulement s’arrête quand un point d’arrêt est rencontré.

j(ump) lineno

Définit la prochaine ligne qui sera exécutée. Uniquement disponible dans la frame inférieur. Cela vous permet de revenir en arrière et d’exécuter à nouveau le code, ou de passer en avant pour sauter le code que vous ne voulez pas exécuter.

Il est à noter que tous les sauts ne sont pas autorisés – par exemple, il n’est pas possible de sauter au milieu d’une boucle for ou en dehors d’une clause finally.

l(ist) [first[, last]]

Liste le code source du fichier courant. Sans arguments, liste 11 lignes autour de la ligne courante ou continue le listing précédant. Avec l’argument ., liste 11 lignes autour de la ligne courante. Avec un argument, liste les 11 lignes autour de cette ligne. Avec deux arguments, liste la plage donnée; si le second argument est inférieur au premier, il est interprété comme un compte.

La ligne en cours dans l’image courante est indiquée par ->. Si une exception est en cours de débogage, la ligne où l’exception a été initialement levée ou propagée est indiquée par >>, si elle diffère de la ligne courante.

Nouveau dans la version 3.2: Le marqueur >>.

ll | longlist

Liste le code source de la fonction ou du bloc courant. Les lignes intéressantes sont marquées comme pour list.

Nouveau dans la version 3.2.

a(rgs)

Affiche la liste d’arguments de la fonction courante.

p expression

Évalue l”expression dans le contexte courant et affiche sa valeur.

Note

print() peut aussi être utilisée, mais n’est pas une commande du débogueur — il exécute la fonction Python print().

pp expression

Comme la commande p, sauf que la valeur de l’expression est joliment affiché en utilisant le module pprint.

whatis expression

Affiche le type de l”expression.

source expression

Essaie d’obtenir le code source pour l’objet donné et l’affiche.

Nouveau dans la version 3.2.

display [expression]

Affiche la valeur de l’expression si elle a changée, chaque fois que l’exécution s’arrête dans la frame courante.

Sans expression, liste toutes les expressions pour la frame courante.

Nouveau dans la version 3.2.

undisplay [expression]

N’affiche plus l’expression dans la frame courante. Sans expression, efface toutes les expressions d’affichage de la frame courante.

Nouveau dans la version 3.2.

interact

Démarre un interpréteur interactif (en utilisant le module code) dont l’espace de nommage global contient tous les noms (global et local) trouvés dans la portée courante.

Nouveau dans la version 3.2.

alias [name [command]]

Créez un alias appelé name qui exécute command. La commande ne doit pas être entourée de guillemets. Les paramètres remplaçables peuvent être indiqués par %1, %2 et ainsi de suite, tandis que %* est remplacé par tous les paramètres. Si aucune commande n’est donnée, l’alias courant pour name est affiché. Si aucun argument n’est donné, tous les alias sont listés.

Les alias peuvent être imbriqués et peuvent contenir tout ce qui peut être légalement tapé à l’invite pdb. Notez que les commandes pdb internes peuvent être remplacées par des alias. Une telle commande est alors masquée jusqu’à ce que l’alias soit supprimé. L”aliasing est appliqué récursivement au premier mot de la ligne de commande; tous les autres mots de la ligne sont laissés seuls.

Comme un exemple, voici deux alias utiles (spécialement quand il est placé dans le fichier .pdbrc) :

# Print instance variables (usage "pi classInst")
alias pi for k in %1.__dict__.keys(): print("%1.",k,"=",%1.__dict__[k])
# Print instance variables in self
alias ps pi self

unalias name

Supprime l’alias spécifié.

! statement

Exécute l’instruction statement (une ligne) dans le contexte de la frame de la pile courante. Le point d’exclamation peut être omis à moins que le premier mot de l’instruction ne ressemble à une commande de débogueur. Pour définir une variable globale, vous pouvez préfixer la commande d’assignation avec une instruction global sur la même ligne, par exemple :

(Pdb) global list_options; list_options = ['-l']
(Pdb)

run [args ...]

restart [args ...]

Redémarre le programme Python débogué. Si un argument est fourni, il est splitté avec shlex et le résultat es utilisé comme le nouveau sys.argv. L’historique, les points d’arrêt, les actions et les options du débogueur sont préservés. restart est un alias pour run.

q(uit)

Quitte le débogueur. Le programme exécuté est arrêté.

Notes

1

La question de savoir si une frame est considérée comme provenant d’un certain module est déterminée par le __name__ dans les globales de la frame.

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27.4. The Python Profilers

Source code: Lib/profile.py [https://github.com/python/cpython/tree/3.6/Lib/profile.py] and Lib/pstats.py [https://github.com/python/cpython/tree/3.6/Lib/pstats.py]

27.4.1. Introduction to the profilers

cProfile and profile provide deterministic profiling of Python programs. A profile is a set of statistics that describes how often and for how long various parts of the program executed. These statistics can be formatted into reports via the pstats module.

The Python standard library provides two different implementations of the same profiling interface:

cProfile is recommended for most users; it’s a C extension with reasonable overhead that makes it suitable for profiling long-running programs. Based on lsprof, contributed by Brett Rosen and Ted Czotter.

profile, a pure Python module whose interface is imitated by cProfile, but which adds significant overhead to profiled programs. If you’re trying to extend the profiler in some way, the task might be easier with this module. Originally designed and written by Jim Roskind.

Note

The profiler modules are designed to provide an execution profile for a given program, not for benchmarking purposes (for that, there is timeit for reasonably accurate results). This particularly applies to benchmarking Python code against C code: the profilers introduce overhead for Python code, but not for C-level functions, and so the C code would seem faster than any Python one.

27.4.2. Instant User’s Manual

This section is provided for users that « don’t want to read the manual. » It provides a very brief overview, and allows a user to rapidly perform profiling on an existing application.

To profile a function that takes a single argument, you can do:

import cProfile
import re
cProfile.run('re.compile("foo|bar")')

(Use profile instead of cProfile if the latter is not available on your system.)

The above action would run re.compile() and print profile results like the following:

      197 function calls (192 primitive calls) in 0.002 seconds

Ordered by: standard name

ncalls  tottime  percall  cumtime  percall filename:lineno(function)
     1    0.000    0.000    0.001    0.001 <string>:1(<module>)
     1    0.000    0.000    0.001    0.001 re.py:212(compile)
     1    0.000    0.000    0.001    0.001 re.py:268(_compile)
     1    0.000    0.000    0.000    0.000 sre_compile.py:172(_compile_charset)
     1    0.000    0.000    0.000    0.000 sre_compile.py:201(_optimize_charset)
     4    0.000    0.000    0.000    0.000 sre_compile.py:25(_identityfunction)
   3/1    0.000    0.000    0.000    0.000 sre_compile.py:33(_compile)

The first line indicates that 197 calls were monitored. Of those calls, 192 were primitive, meaning that the call was not induced via recursion. The next line: Ordered by: standard name, indicates that the text string in the far right column was used to sort the output. The column headings include:

ncalls

for the number of calls.

tottime

for the total time spent in the given function (and excluding time made in calls to sub-functions)

percall

is the quotient of tottime divided by ncalls

cumtime

is the cumulative time spent in this and all subfunctions (from invocation till exit). This figure is accurate even for recursive functions.

percall

is the quotient of cumtime divided by primitive calls

filename:lineno(function)

provides the respective data of each function

When there are two numbers in the first column (for example 3/1), it means that the function recursed. The second value is the number of primitive calls and the former is the total number of calls. Note that when the function does not recurse, these two values are the same, and only the single figure is printed.

Instead of printing the output at the end of the profile run, you can save the results to a file by specifying a filename to the run() function:

import cProfile
import re
cProfile.run('re.compile("foo|bar")', 'restats')

The pstats.Stats class reads profile results from a file and formats them in various ways.

The file cProfile can also be invoked as a script to profile another script. For example:

python -m cProfile [-o output_file] [-s sort_order] myscript.py

-o writes the profile results to a file instead of to stdout

-s specifies one of the sort_stats() sort values to sort the output by. This only applies when -o is not supplied.

The pstats module’s Stats class has a variety of methods for manipulating and printing the data saved into a profile results file:

import pstats
p = pstats.Stats('restats')
p.strip_dirs().sort_stats(-1).print_stats()

The strip_dirs() method removed the extraneous path from all the module names. The sort_stats() method sorted all the entries according to the standard module/line/name string that is printed. The print_stats() method printed out all the statistics. You might try the following sort calls:

p.sort_stats('name')
p.print_stats()

The first call will actually sort the list by function name, and the second call will print out the statistics. The following are some interesting calls to experiment with:

p.sort_stats('cumulative').print_stats(10)

This sorts the profile by cumulative time in a function, and then only prints the ten most significant lines. If you want to understand what algorithms are taking time, the above line is what you would use.

If you were looking to see what functions were looping a lot, and taking a lot of time, you would do:

p.sort_stats('time').print_stats(10)

to sort according to time spent within each function, and then print the statistics for the top ten functions.

You might also try:

p.sort_stats('file').print_stats('__init__')

This will sort all the statistics by file name, and then print out statistics for only the class init methods (since they are spelled with __init__ in them). As one final example, you could try:

p.sort_stats('time', 'cumulative').print_stats(.5, 'init')

This line sorts statistics with a primary key of time, and a secondary key of cumulative time, and then prints out some of the statistics. To be specific, the list is first culled down to 50% (re: .5) of its original size, then only lines containing init are maintained, and that sub-sub-list is printed.

If you wondered what functions called the above functions, you could now (p is still sorted according to the last criteria) do:

p.print_callers(.5, 'init')

and you would get a list of callers for each of the listed functions.

If you want more functionality, you’re going to have to read the manual, or guess what the following functions do:

p.print_callees()
p.add('restats')

Invoked as a script, the pstats module is a statistics browser for reading and examining profile dumps. It has a simple line-oriented interface (implemented using cmd) and interactive help.

27.4.3. profile and cProfile Module Reference

Both the profile and cProfile modules provide the following functions:

profile.run(command, filename=None, sort=-1)

This function takes a single argument that can be passed to the exec() function, and an optional file name. In all cases this routine executes:

exec(command, __main__.__dict__, __main__.__dict__)

and gathers profiling statistics from the execution. If no file name is present, then this function automatically creates a Stats instance and prints a simple profiling report. If the sort value is specified, it is passed to this Stats instance to control how the results are sorted.

profile.runctx(command, globals, locals, filename=None, sort=-1)

This function is similar to run(), with added arguments to supply the globals and locals dictionaries for the command string. This routine executes:

exec(command, globals, locals)

and gathers profiling statistics as in the run() function above.

class profile.Profile(timer=None, timeunit=0.0, subcalls=True, builtins=True)

This class is normally only used if more precise control over profiling is needed than what the cProfile.run() function provides.

A custom timer can be supplied for measuring how long code takes to run via the timer argument. This must be a function that returns a single number representing the current time. If the number is an integer, the timeunit specifies a multiplier that specifies the duration of each unit of time. For example, if the timer returns times measured in thousands of seconds, the time unit would be .001.

Directly using the Profile class allows formatting profile results without writing the profile data to a file:

import cProfile, pstats, io
pr = cProfile.Profile()
pr.enable()
# ... do something ...
pr.disable()
s = io.StringIO()
sortby = 'cumulative'
ps = pstats.Stats(pr, stream=s).sort_stats(sortby)
ps.print_stats()
print(s.getvalue())

enable()

Start collecting profiling data.

disable()

Stop collecting profiling data.

create_stats()

Stop collecting profiling data and record the results internally as the current profile.

print_stats(sort=-1)

Create a Stats object based on the current profile and print the results to stdout.

dump_stats(filename)

Write the results of the current profile to filename.

run(cmd)

Profile the cmd via exec().

runctx(cmd, globals, locals)

Profile the cmd via exec() with the specified global and local environment.

runcall(func, *args, **kwargs)

Profile func(*args, **kwargs)

Note that profiling will only work if the called command/function actually returns. If the interpreter is terminated (e.g. via a sys.exit() call during the called command/function execution) no profiling results will be printed.

27.4.4. The Stats Class

Analysis of the profiler data is done using the Stats class.

class pstats.Stats(*filenames or profile, stream=sys.stdout)

This class constructor creates an instance of a « statistics object » from a filename (or list of filenames) or from a Profile instance. Output will be printed to the stream specified by stream.

The file selected by the above constructor must have been created by the corresponding version of profile or cProfile. To be specific, there is no file compatibility guaranteed with future versions of this profiler, and there is no compatibility with files produced by other profilers, or the same profiler run on a different operating system. If several files are provided, all the statistics for identical functions will be coalesced, so that an overall view of several processes can be considered in a single report. If additional files need to be combined with data in an existing Stats object, the add() method can be used.

Instead of reading the profile data from a file, a cProfile.Profile or profile.Profile object can be used as the profile data source.

Stats objects have the following methods:

strip_dirs()

This method for the Stats class removes all leading path information from file names. It is very useful in reducing the size of the printout to fit within (close to) 80 columns. This method modifies the object, and the stripped information is lost. After performing a strip operation, the object is considered to have its entries in a « random » order, as it was just after object initialization and loading. If strip_dirs() causes two function names to be indistinguishable (they are on the same line of the same filename, and have the same function name), then the statistics for these two entries are accumulated into a single entry.

add(*filenames)

This method of the Stats class accumulates additional profiling information into the current profiling object. Its arguments should refer to filenames created by the corresponding version of profile.run() or cProfile.run(). Statistics for identically named (re: file, line, name) functions are automatically accumulated into single function statistics.

dump_stats(filename)

Save the data loaded into the Stats object to a file named filename. The file is created if it does not exist, and is overwritten if it already exists. This is equivalent to the method of the same name on the profile.Profile and cProfile.Profile classes.

sort_stats(*keys)

This method modifies the Stats object by sorting it according to the supplied criteria. The argument is typically a string identifying the basis of a sort (example: 'time' or 'name').

When more than one key is provided, then additional keys are used as secondary criteria when there is equality in all keys selected before them. For example, sort_stats('name', 'file') will sort all the entries according to their function name, and resolve all ties (identical function names) by sorting by file name.

Abbreviations can be used for any key names, as long as the abbreviation is unambiguous. The following are the keys currently defined:

Valid Arg

Signification

'calls'

call count

'cumulative'

cumulative time

'cumtime'

cumulative time

'file'

file name

'filename'

file name

'module'

file name

'ncalls'

call count

'pcalls'

primitive call count

'line'

line number

'name'

function name

'nfl'

name/file/line

'stdname'

standard name

'time'

internal time

'tottime'

internal time

Note that all sorts on statistics are in descending order (placing most time consuming items first), where as name, file, and line number searches are in ascending order (alphabetical). The subtle distinction between 'nfl' and 'stdname' is that the standard name is a sort of the name as printed, which means that the embedded line numbers get compared in an odd way. For example, lines 3, 20, and 40 would (if the file names were the same) appear in the string order 20, 3 and 40. In contrast, 'nfl' does a numeric compare of the line numbers. In fact, sort_stats('nfl') is the same as sort_stats('name', 'file', 'line').

For backward-compatibility reasons, the numeric arguments -1, 0, 1, and 2 are permitted. They are interpreted as 'stdname', 'calls', 'time', and 'cumulative' respectively. If this old style format (numeric) is used, only one sort key (the numeric key) will be used, and additional arguments will be silently ignored.

reverse_order()

This method for the Stats class reverses the ordering of the basic list within the object. Note that by default ascending vs descending order is properly selected based on the sort key of choice.

print_stats(*restrictions)

This method for the Stats class prints out a report as described in the profile.run() definition.

The order of the printing is based on the last sort_stats() operation done on the object (subject to caveats in add() and strip_dirs()).

The arguments provided (if any) can be used to limit the list down to the significant entries. Initially, the list is taken to be the complete set of profiled functions. Each restriction is either an integer (to select a count of lines), or a decimal fraction between 0.0 and 1.0 inclusive (to select a percentage of lines), or a string that will interpreted as a regular expression (to pattern match the standard name that is printed). If several restrictions are provided, then they are applied sequentially. For example:

print_stats(.1, 'foo:')

would first limit the printing to first 10% of list, and then only print functions that were part of filename .*foo:. In contrast, the command:

print_stats('foo:', .1)

would limit the list to all functions having file names .*foo:, and then proceed to only print the first 10% of them.

print_callers(*restrictions)

This method for the Stats class prints a list of all functions that called each function in the profiled database. The ordering is identical to that provided by print_stats(), and the definition of the restricting argument is also identical. Each caller is reported on its own line. The format differs slightly depending on the profiler that produced the stats:

With profile, a number is shown in parentheses after each caller to show how many times this specific call was made. For convenience, a second non-parenthesized number repeats the cumulative time spent in the function at the right.

With cProfile, each caller is preceded by three numbers: the number of times this specific call was made, and the total and cumulative times spent in the current function while it was invoked by this specific caller.

print_callees(*restrictions)

This method for the Stats class prints a list of all function that were called by the indicated function. Aside from this reversal of direction of calls (re: called vs was called by), the arguments and ordering are identical to the print_callers() method.

27.4.5. What Is Deterministic Profiling?

Deterministic profiling is meant to reflect the fact that all function call, function return, and exception events are monitored, and precise timings are made for the intervals between these events (during which time the user’s code is executing). In contrast, statistical profiling (which is not done by this module) randomly samples the effective instruction pointer, and deduces where time is being spent. The latter technique traditionally involves less overhead (as the code does not need to be instrumented), but provides only relative indications of where time is being spent.

In Python, since there is an interpreter active during execution, the presence of instrumented code is not required to do deterministic profiling. Python automatically provides a hook (optional callback) for each event. In addition, the interpreted nature of Python tends to add so much overhead to execution, that deterministic profiling tends to only add small processing overhead in typical applications. The result is that deterministic profiling is not that expensive, yet provides extensive run time statistics about the execution of a Python program.

Call count statistics can be used to identify bugs in code (surprising counts), and to identify possible inline-expansion points (high call counts). Internal time statistics can be used to identify « hot loops » that should be carefully optimized. Cumulative time statistics should be used to identify high level errors in the selection of algorithms. Note that the unusual handling of cumulative times in this profiler allows statistics for recursive implementations of algorithms to be directly compared to iterative implementations.

27.4.6. Limitations

One limitation has to do with accuracy of timing information. There is a fundamental problem with deterministic profilers involving accuracy. The most obvious restriction is that the underlying « clock » is only ticking at a rate (typically) of about .001 seconds. Hence no measurements will be more accurate than the underlying clock. If enough measurements are taken, then the « error » will tend to average out. Unfortunately, removing this first error induces a second source of error.

The second problem is that it « takes a while » from when an event is dispatched until the profiler’s call to get the time actually gets the state of the clock. Similarly, there is a certain lag when exiting the profiler event handler from the time that the clock’s value was obtained (and then squirreled away), until the user’s code is once again executing. As a result, functions that are called many times, or call many functions, will typically accumulate this error. The error that accumulates in this fashion is typically less than the accuracy of the clock (less than one clock tick), but it can accumulate and become very significant.

The problem is more important with profile than with the lower-overhead cProfile. For this reason, profile provides a means of calibrating itself for a given platform so that this error can be probabilistically (on the average) removed. After the profiler is calibrated, it will be more accurate (in a least square sense), but it will sometimes produce negative numbers (when call counts are exceptionally low, and the gods of probability work against you :-). ) Do not be alarmed by negative numbers in the profile. They should only appear if you have calibrated your profiler, and the results are actually better than without calibration.

27.4.7. Calibration

The profiler of the profile module subtracts a constant from each event handling time to compensate for the overhead of calling the time function, and socking away the results. By default, the constant is 0. The following procedure can be used to obtain a better constant for a given platform (see Limitations).

import profile
pr = profile.Profile()
for i in range(5):
    print(pr.calibrate(10000))

The method executes the number of Python calls given by the argument, directly and again under the profiler, measuring the time for both. It then computes the hidden overhead per profiler event, and returns that as a float. For example, on a 1.8Ghz Intel Core i5 running Mac OS X, and using Python’s time.clock() as the timer, the magical number is about 4.04e-6.

The object of this exercise is to get a fairly consistent result. If your computer is very fast, or your timer function has poor resolution, you might have to pass 100000, or even 1000000, to get consistent results.

When you have a consistent answer, there are three ways you can use it:

import profile

# 1. Apply computed bias to all Profile instances created hereafter.
profile.Profile.bias = your_computed_bias

# 2. Apply computed bias to a specific Profile instance.
pr = profile.Profile()
pr.bias = your_computed_bias

# 3. Specify computed bias in instance constructor.
pr = profile.Profile(bias=your_computed_bias)

If you have a choice, you are better off choosing a smaller constant, and then your results will « less often » show up as negative in profile statistics.

27.4.8. Using a custom timer

If you want to change how current time is determined (for example, to force use of wall-clock time or elapsed process time), pass the timing function you want to the Profile class constructor:

pr = profile.Profile(your_time_func)

The resulting profiler will then call your_time_func. Depending on whether you are using profile.Profile or cProfile.Profile, your_time_func’s return value will be interpreted differently:

profile.Profile

your_time_func should return a single number, or a list of numbers whose sum is the current time (like what os.times() returns). If the function returns a single time number, or the list of returned numbers has length 2, then you will get an especially fast version of the dispatch routine.

Be warned that you should calibrate the profiler class for the timer function that you choose (see Calibration). For most machines, a timer that returns a lone integer value will provide the best results in terms of low overhead during profiling. (os.times() is pretty bad, as it returns a tuple of floating point values). If you want to substitute a better timer in the cleanest fashion, derive a class and hardwire a replacement dispatch method that best handles your timer call, along with the appropriate calibration constant.

cProfile.Profile

your_time_func should return a single number. If it returns integers, you can also invoke the class constructor with a second argument specifying the real duration of one unit of time. For example, if your_integer_time_func returns times measured in thousands of seconds, you would construct the Profile instance as follows:

pr = cProfile.Profile(your_integer_time_func, 0.001)

As the cProfile.Profile class cannot be calibrated, custom timer functions should be used with care and should be as fast as possible. For the best results with a custom timer, it might be necessary to hard-code it in the C source of the internal _lsprof module.

Python 3.3 adds several new functions in time that can be used to make precise measurements of process or wall-clock time. For example, see time.perf_counter().

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27.5. timeit — Mesurer le temps d’exécution de fragments de code

Code source : Lib/timeit.py [https://github.com/python/cpython/tree/3.6/Lib/timeit.py]

Ce module fournit une façon simple de mesurer le temps d’exécution de fragments de code Python. Il expose une Interface en ligne de commande ainsi qu’une interface Python. Ce module permet d’éviter un certain nombre de problèmes classiques liés à la mesure des temps d’exécution. Voir par exemple à ce sujet l’introduction par Tim Peters du chapitre « Algorithmes » dans le livre Python Cookbook, aux éditions O’Reilly.

27.5.1. Exemples simples

L’exemple suivant illustre l’utilisation de l”Interface en ligne de commande afin de comparer trois expressions différentes :

$ python3 -m timeit '"-".join(str(n) for n in range(100))'
10000 loops, best of 3: 30.2 usec per loop
$ python3 -m timeit '"-".join([str(n) for n in range(100)])'
10000 loops, best of 3: 27.5 usec per loop
$ python3 -m timeit '"-".join(map(str, range(100)))'
10000 loops, best of 3: 23.2 usec per loop

L”Interface Python peut être utilisée aux mêmes fins avec :

>>> import timeit
>>> timeit.timeit('"-".join(str(n) for n in range(100))', number=10000)
0.3018611848820001
>>> timeit.timeit('"-".join([str(n) for n in range(100)])', number=10000)
0.2727368790656328
>>> timeit.timeit('"-".join(map(str, range(100)))', number=10000)
0.23702679807320237

Note however that timeit will automatically determine the number of repetitions only when the command-line interface is used. In the Exemples section you can find more advanced examples.

27.5.2. Interface Python

Ce module définit une classe publique ainsi que trois fonctions destinées à simplifier son usage :

timeit.timeit(stmt='pass', setup='pass', timer=<default timer>, number=1000000, globals=None)

Crée une instance d’objet Timer à partir de l’instruction donnée, du code setup et de la fonction timer, puis exécute sa méthode timeit() à number reprises. L’argument optionnel globals spécifie un espace de nommage dans lequel exécuter le code.

Modifié dans la version 3.5: Le paramètre optionnel globals a été ajouté.

timeit.repeat(stmt='pass', setup='pass', timer=<default timer>, repeat=3, number=1000000, globals=None)

Crée une instance d’objet Timer à partir de l’instruction donnée, du code setup et de la fonction timer, puis exécute sa méthode repeat() à number reprises, repeat fois. L’argument optionnel globals spécifie un espace de nommage dans lequel exécuter le code.

Modifié dans la version 3.5: Le paramètre optionnel globals a été ajouté.

timeit.default_timer()

Le minuteur par défaut, qui est toujours time.perf_counter().

Modifié dans la version 3.3: time.perf_counter() est désormais le minuteur par défaut.

class timeit.Timer(stmt='pass', setup='pass', timer=<timer function>, globals=None)

Classe permettant de mesurer le temps d’exécution de fragments de code.

Ce constructeur prend en argument une instruction dont le temps d’exécution doit être mesuré, une instruction additionnelle de mise en place et une fonction de chronométrage. Les deux instructions valent 'pass' par défaut; la fonction de chronométrage dépend de la plateforme d’exécution (se référer au doc string du module). stmt et setup peuvent contenir plusieurs instructions séparées par des ; ou des sauts de lignes tant qu’ils ne comportent pas de littéraux sur plusieurs lignes. L’instruction est exécutée dans l’espace de nommage de timeit par défaut ; ce comportement peut être modifié en passant un espace de nommage au paramètre globals.

Pour mesurer le temps d’exécution de la première instruction, utilisez la méthode timeit(). Les méthodes repeat() et autorange() sont des méthodes d’agrément permettant d’appeler timeit() à plusieurs reprises.

Le temps d’exécution de setup n’est pas pris en compte dans le temps global d’exécution.

Les paramètres stmt et setup peuvent également recevoir des objets appelables sans argument. Ceci transforme alors les appels à ces objets en fonction de chronométrage qui seront exécutées par timeit(). Notez que le surcoût lié à la mesure du temps d’exécution dans ce cas est légèrement supérieur en raisons des appels de fonction supplémentaires.

Modifié dans la version 3.5: Le paramètre optionnel globals a été ajouté.

timeit(number=1000000)

Mesure le temps number exécution de l’instruction principale. Ceci exécute l’instruction de mise en place une seule fois puis renvoie un flottant correspondant au temps nécessaire à l’exécution de l’instruction principale à plusieurs reprises, mesuré en secondes. L’argument correspond au nombre d’itérations dans la boucle, par défaut un million. L’instruction principale, l’instruction de mise en place et la fonction de chronométrage utilisée sont passées au constructeur.

Note

By default, timeit() temporarily turns off garbage collection during the timing. The advantage of this approach is that it makes independent timings more comparable. This disadvantage is that GC may be an important component of the performance of the function being measured. If so, GC can be re-enabled as the first statement in the setup string. For example:

timeit.Timer('for i in range(10): oct(i)', 'gc.enable()').timeit()

autorange(callback=None)

Détermine automatiquement combien de fois appeler timeit().

This is a convenience function that calls timeit() repeatedly so that the total time >= 0.2 second, returning the eventual (number of loops, time taken for that number of loops). It calls timeit() with number set to successive powers of ten (10, 100, 1000, …) up to a maximum of one billion, until the time taken is at least 0.2 second, or the maximum is reached.

Si callback est spécifié et n’est pas None, elle est appelée après chaque itération avec deux arguments (numéro de l’itération et temps écoulé) : callback(number, time_taken).

Nouveau dans la version 3.6.

repeat(repeat=3, number=1000000)

Appelle timeit() plusieurs fois.

Cette fonction d’agrément appelle timeit() à plusieurs reprises et renvoie une liste de résultats. Le premier argument spécifie le nombre d’appels à timeit(). Le second argument spécifie l’argument number de timeit().

Note

Il est tentant de vouloir calculer la moyenne et l’écart-type des résultats et notifier ces valeurs. Ce n’est cependant pas très utile. En pratique, la valeur la plus basse donne une estimation basse de la vitesse maximale à laquelle votre machine peut exécuter le fragment de code spécifié ; les valeurs hautes de la liste sont typiquement provoquées non pas par une variabilité de la vitesse d’exécution de Python, mais par d’autres processus interférant avec la précision du chronométrage. Le min() du résultat est probablement la seule valeur à laquelle vous devriez vous intéresser. Pour aller plus loin, vous devriez regarder l’intégralité des résultats et utiliser le bon sens plutôt que les statistiques.

print_exc(file=None)

Outil permettant d’afficher la trace du code chronométré.

Usage typique :

t = Timer(...)       # outside the try/except
try:
    t.timeit(...)    # or t.repeat(...)
except Exception:
    t.print_exc()

L’avantage par rapport à la trace standard est que les lignes sources du code compilé sont affichées. Le paramètre optionnel file définit l’endroit où la trace est envoyée, par défaut sys.stderr.

27.5.3. Interface en ligne de commande

Lorsque le module est appelé comme un programme en ligne de commande, la syntaxe suivante est utilisée :

python -m timeit [-n N] [-r N] [-u U] [-s S] [-t] [-c] [-h] [statement ...]

Les options suivantes sont gérées :

-n N, --number=N

nombre d’exécutions de l’instruction statement

-r N, --repeat=N

how many times to repeat the timer (default 3)

-s S, --setup=S

instruction exécutée une seule fois à l’initialisation (pass par défaut)

-p, --process

mesure le temps au niveau du processus et non au niveau du système, en utilisant time.process_time() plutôt que time.perf_counter() qui est utilisée par défaut

Nouveau dans la version 3.3.

-t, --time

use time.time() (deprecated)

-u, --unit=U

specify a time unit for timer output; can select usec, msec, or sec

Nouveau dans la version 3.5.

-c, --clock

use time.clock() (deprecated)

-v, --verbose

affiche les temps d’exécutions bruts, répéter pour plus de précision

-h, --help

affiche un court message d’aide puis quitte

Une instruction sur plusieurs lignes peut être donnée en entrée en spécifiant chaque ligne comme un argument séparé. Indenter une ligne est possible en encadrant l’argument de guillemets et en le préfixant par des espaces. Plusieurs -s sont gérées de la même façon.

Si -n n’est pas donnée, le nombre de boucles adapté est déterminé automatiquement en essayant les puissances de 10 successives jusqu’à ce que le temps total d’exécution dépasse 0,2 secondes.

default_timer() measurements can be affected by other programs running on the same machine, so the best thing to do when accurate timing is necessary is to repeat the timing a few times and use the best time. The -r option is good for this; the default of 3 repetitions is probably enough in most cases. You can use time.process_time() to measure CPU time.

Note

Il existe un surcoût minimal associé à l’exécution de l’instruction pass. Le code présenté ici ne tente pas de le masquer, mais vous devez être conscient de son existence. Ce surcoût minimal peut être mesuré en invoquant le programme sans argument ; il peut différer en fonction des versions de Python.

27.5.4. Exemples

Il est possible de fournir une instruction de mise en place exécutée une seule fois au début du chronométrage :

$ python -m timeit -s 'text = "sample string"; char = "g"'  'char in text'
10000000 loops, best of 3: 0.0877 usec per loop
$ python -m timeit -s 'text = "sample string"; char = "g"'  'text.find(char)'
1000000 loops, best of 3: 0.342 usec per loop

>>> import timeit
>>> timeit.timeit('char in text', setup='text = "sample string"; char = "g"')
0.41440500499993504
>>> timeit.timeit('text.find(char)', setup='text = "sample string"; char = "g"')
1.7246671520006203

La même chose peut être réalisée en utilisant la classe Timer et ses méthodes :

>>> import timeit
>>> t = timeit.Timer('char in text', setup='text = "sample string"; char = "g"')
>>> t.timeit()
0.3955516149999312
>>> t.repeat()
[0.40193588800002544, 0.3960157959998014, 0.39594301399984033]

Les exemples qui suivent montrent comment chronométrer des expressions sur plusieurs lignes. Nous comparons ici le coût d’utilisation de hasattr() par rapport à try/except pour tester la présence ou l’absence d’attributs d’un objet :

$ python -m timeit 'try:' '  str.__bool__' 'except AttributeError:' '  pass'
100000 loops, best of 3: 15.7 usec per loop
$ python -m timeit 'if hasattr(str, "__bool__"): pass'
100000 loops, best of 3: 4.26 usec per loop

$ python -m timeit 'try:' '  int.__bool__' 'except AttributeError:' '  pass'
1000000 loops, best of 3: 1.43 usec per loop
$ python -m timeit 'if hasattr(int, "__bool__"): pass'
100000 loops, best of 3: 2.23 usec per loop

>>> import timeit
>>> # attribute is missing
>>> s = """\
... try:
...     str.__bool__
... except AttributeError:
...     pass
... """
>>> timeit.timeit(stmt=s, number=100000)
0.9138244460009446
>>> s = "if hasattr(str, '__bool__'): pass"
>>> timeit.timeit(stmt=s, number=100000)
0.5829014980008651
>>>
>>> # attribute is present
>>> s = """\
... try:
...     int.__bool__
... except AttributeError:
...     pass
... """
>>> timeit.timeit(stmt=s, number=100000)
0.04215312199994514
>>> s = "if hasattr(int, '__bool__'): pass"
>>> timeit.timeit(stmt=s, number=100000)
0.08588060699912603

Afin de permettre à timeit d’accéder aux fonctions que vous avez définies, vous pouvez passer au paramètre setup une instruction d’importation :

def test():
    """Stupid test function"""
    L = [i for i in range(100)]

if __name__ == '__main__':
    import timeit
    print(timeit.timeit("test()", setup="from __main__ import test"))

Une autre possibilité est de passer globals() au paramètre globals, ceci qui exécutera le code dans l’espace de nommage global courant. Cela peut être plus pratique que de spécifier manuellement des importations :

def f(x):
    return x**2
def g(x):
    return x**4
def h(x):
    return x**8

import timeit
print(timeit.timeit('[func(42) for func in (f,g,h)]', globals=globals()))

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27.6. trace — Trace or track Python statement execution

Code source : Lib/abc.py [https://github.com/python/cpython/tree/3.6/Lib/abc.py]

The trace module allows you to trace program execution, generate annotated statement coverage listings, print caller/callee relationships and list functions executed during a program run. It can be used in another program or from the command line.

Voir aussi

Coverage.py [https://coverage.readthedocs.io/]

A popular third-party coverage tool that provides HTML output along with advanced features such as branch coverage.

27.6.1. Utilisation en ligne de commande.

The trace module can be invoked from the command line. It can be as simple as

python -m trace --count -C . somefile.py ...

The above will execute somefile.py and generate annotated listings of all Python modules imported during the execution into the current directory.

--help

Display usage and exit.

--version

Display the version of the module and exit.

27.6.1.1. Main options

At least one of the following options must be specified when invoking trace. The --listfuncs option is mutually exclusive with the --trace and --count options. When --listfuncs is provided, neither --count nor --trace are accepted, and vice versa.

-c, --count

Produce a set of annotated listing files upon program completion that shows how many times each statement was executed. See also --coverdir, --file and --no-report below.

-t, --trace

Display lines as they are executed.

-l, --listfuncs

Display the functions executed by running the program.

-r, --report

Produce an annotated list from an earlier program run that used the --count and --file option. This does not execute any code.

-T, --trackcalls

Display the calling relationships exposed by running the program.

27.6.1.2. Modifiers

-f, --file=<file>

Name of a file to accumulate counts over several tracing runs. Should be used with the --count option.

-C, --coverdir=<dir>

Directory where the report files go. The coverage report for package.module is written to file dir/package/module.cover.

-m, --missing

When generating annotated listings, mark lines which were not executed with >>>>>>.

-s, --summary

When using --count or --report, write a brief summary to stdout for each file processed.

-R, --no-report

Do not generate annotated listings. This is useful if you intend to make several runs with --count, and then produce a single set of annotated listings at the end.

-g, --timing

Prefix each line with the time since the program started. Only used while tracing.

27.6.1.3. Filters

These options may be repeated multiple times.

--ignore-module=<mod>

Ignore each of the given module names and its submodules (if it is a package). The argument can be a list of names separated by a comma.

--ignore-dir=<dir>

Ignore all modules and packages in the named directory and subdirectories. The argument can be a list of directories separated by os.pathsep.

27.6.2. Programmatic Interface

class trace.Trace(count=1, trace=1, countfuncs=0, countcallers=0, ignoremods=(), ignoredirs=(), infile=None, outfile=None, timing=False)

Create an object to trace execution of a single statement or expression. All parameters are optional. count enables counting of line numbers. trace enables line execution tracing. countfuncs enables listing of the functions called during the run. countcallers enables call relationship tracking. ignoremods is a list of modules or packages to ignore. ignoredirs is a list of directories whose modules or packages should be ignored. infile is the name of the file from which to read stored count information. outfile is the name of the file in which to write updated count information. timing enables a timestamp relative to when tracing was started to be displayed.

run(cmd)

Execute the command and gather statistics from the execution with the current tracing parameters. cmd must be a string or code object, suitable for passing into exec().

runctx(cmd, globals=None, locals=None)

Execute the command and gather statistics from the execution with the current tracing parameters, in the defined global and local environments. If not defined, globals and locals default to empty dictionaries.

runfunc(func, *args, **kwds)

Call func with the given arguments under control of the Trace object with the current tracing parameters.

results()

Return a CoverageResults object that contains the cumulative results of all previous calls to run, runctx and runfunc for the given Trace instance. Does not reset the accumulated trace results.

class trace.CoverageResults

A container for coverage results, created by Trace.results(). Should not be created directly by the user.

update(other)

Merge in data from another CoverageResults object.

write_results(show_missing=True, summary=False, coverdir=None)

Write coverage results. Set show_missing to show lines that had no hits. Set summary to include in the output the coverage summary per module. coverdir specifies the directory into which the coverage result files will be output. If None, the results for each source file are placed in its directory.

A simple example demonstrating the use of the programmatic interface:

import sys
import trace

# create a Trace object, telling it what to ignore, and whether to
# do tracing or line-counting or both.
tracer = trace.Trace(
    ignoredirs=[sys.prefix, sys.exec_prefix],
    trace=0,
    count=1)

# run the new command using the given tracer
tracer.run('main()')

# make a report, placing output in the current directory
r = tracer.results()
r.write_results(show_missing=True, coverdir=".")

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27.7. tracemalloc — Trace memory allocations

Nouveau dans la version 3.4.

Source code: Lib/tracemalloc.py [https://github.com/python/cpython/tree/3.6/Lib/tracemalloc.py]

The tracemalloc module is a debug tool to trace memory blocks allocated by Python. It provides the following information:

Traceback where an object was allocated

Statistics on allocated memory blocks per filename and per line number: total size, number and average size of allocated memory blocks

Compute the differences between two snapshots to detect memory leaks

To trace most memory blocks allocated by Python, the module should be started as early as possible by setting the PYTHONTRACEMALLOC environment variable to 1, or by using -X tracemalloc command line option. The tracemalloc.start() function can be called at runtime to start tracing Python memory allocations.

By default, a trace of an allocated memory block only stores the most recent frame (1 frame). To store 25 frames at startup: set the PYTHONTRACEMALLOC environment variable to 25, or use the -X tracemalloc=25 command line option.

27.7.1. Exemples

27.7.1.1. Display the top 10

Display the 10 files allocating the most memory:

import tracemalloc

tracemalloc.start()

# ... run your application ...

snapshot = tracemalloc.take_snapshot()
top_stats = snapshot.statistics('lineno')

print("[ Top 10 ]")
for stat in top_stats[:10]:
    print(stat)

Example of output of the Python test suite:

[ Top 10 ]
<frozen importlib._bootstrap>:716: size=4855 KiB, count=39328, average=126 B
<frozen importlib._bootstrap>:284: size=521 KiB, count=3199, average=167 B
/usr/lib/python3.4/collections/__init__.py:368: size=244 KiB, count=2315, average=108 B
/usr/lib/python3.4/unittest/case.py:381: size=185 KiB, count=779, average=243 B
/usr/lib/python3.4/unittest/case.py:402: size=154 KiB, count=378, average=416 B
/usr/lib/python3.4/abc.py:133: size=88.7 KiB, count=347, average=262 B
<frozen importlib._bootstrap>:1446: size=70.4 KiB, count=911, average=79 B
<frozen importlib._bootstrap>:1454: size=52.0 KiB, count=25, average=2131 B
<string>:5: size=49.7 KiB, count=148, average=344 B
/usr/lib/python3.4/sysconfig.py:411: size=48.0 KiB, count=1, average=48.0 KiB

We can see that Python loaded 4855 KiB data (bytecode and constants) from modules and that the collections module allocated 244 KiB to build namedtuple types.

See Snapshot.statistics() for more options.

27.7.1.2. Compute differences

Take two snapshots and display the differences:

import tracemalloc
tracemalloc.start()
# ... start your application ...

snapshot1 = tracemalloc.take_snapshot()
# ... call the function leaking memory ...
snapshot2 = tracemalloc.take_snapshot()

top_stats = snapshot2.compare_to(snapshot1, 'lineno')

print("[ Top 10 differences ]")
for stat in top_stats[:10]:
    print(stat)

Example of output before/after running some tests of the Python test suite:

[ Top 10 differences ]
<frozen importlib._bootstrap>:716: size=8173 KiB (+4428 KiB), count=71332 (+39369), average=117 B
/usr/lib/python3.4/linecache.py:127: size=940 KiB (+940 KiB), count=8106 (+8106), average=119 B
/usr/lib/python3.4/unittest/case.py:571: size=298 KiB (+298 KiB), count=589 (+589), average=519 B
<frozen importlib._bootstrap>:284: size=1005 KiB (+166 KiB), count=7423 (+1526), average=139 B
/usr/lib/python3.4/mimetypes.py:217: size=112 KiB (+112 KiB), count=1334 (+1334), average=86 B
/usr/lib/python3.4/http/server.py:848: size=96.0 KiB (+96.0 KiB), count=1 (+1), average=96.0 KiB
/usr/lib/python3.4/inspect.py:1465: size=83.5 KiB (+83.5 KiB), count=109 (+109), average=784 B
/usr/lib/python3.4/unittest/mock.py:491: size=77.7 KiB (+77.7 KiB), count=143 (+143), average=557 B
/usr/lib/python3.4/urllib/parse.py:476: size=71.8 KiB (+71.8 KiB), count=969 (+969), average=76 B
/usr/lib/python3.4/contextlib.py:38: size=67.2 KiB (+67.2 KiB), count=126 (+126), average=546 B

We can see that Python has loaded 8173 KiB of module data (bytecode and constants), and that this is 4428 KiB more than had been loaded before the tests, when the previous snapshot was taken. Similarly, the linecache module has cached 940 KiB of Python source code to format tracebacks, all of it since the previous snapshot.

If the system has little free memory, snapshots can be written on disk using the Snapshot.dump() method to analyze the snapshot offline. Then use the Snapshot.load() method reload the snapshot.

27.7.1.3. Get the traceback of a memory block

Code to display the traceback of the biggest memory block:

import tracemalloc

# Store 25 frames
tracemalloc.start(25)

# ... run your application ...

snapshot = tracemalloc.take_snapshot()
top_stats = snapshot.statistics('traceback')

# pick the biggest memory block
stat = top_stats[0]
print("%s memory blocks: %.1f KiB" % (stat.count, stat.size / 1024))
for line in stat.traceback.format():
    print(line)

Example of output of the Python test suite (traceback limited to 25 frames):

903 memory blocks: 870.1 KiB
  File "<frozen importlib._bootstrap>", line 716
  File "<frozen importlib._bootstrap>", line 1036
  File "<frozen importlib._bootstrap>", line 934
  File "<frozen importlib._bootstrap>", line 1068
  File "<frozen importlib._bootstrap>", line 619
  File "<frozen importlib._bootstrap>", line 1581
  File "<frozen importlib._bootstrap>", line 1614
  File "/usr/lib/python3.4/doctest.py", line 101
    import pdb
  File "<frozen importlib._bootstrap>", line 284
  File "<frozen importlib._bootstrap>", line 938
  File "<frozen importlib._bootstrap>", line 1068
  File "<frozen importlib._bootstrap>", line 619
  File "<frozen importlib._bootstrap>", line 1581
  File "<frozen importlib._bootstrap>", line 1614
  File "/usr/lib/python3.4/test/support/__init__.py", line 1728
    import doctest
  File "/usr/lib/python3.4/test/test_pickletools.py", line 21
    support.run_doctest(pickletools)
  File "/usr/lib/python3.4/test/regrtest.py", line 1276
    test_runner()
  File "/usr/lib/python3.4/test/regrtest.py", line 976
    display_failure=not verbose)
  File "/usr/lib/python3.4/test/regrtest.py", line 761
    match_tests=ns.match_tests)
  File "/usr/lib/python3.4/test/regrtest.py", line 1563
    main()
  File "/usr/lib/python3.4/test/__main__.py", line 3
    regrtest.main_in_temp_cwd()
  File "/usr/lib/python3.4/runpy.py", line 73
    exec(code, run_globals)
  File "/usr/lib/python3.4/runpy.py", line 160
    "__main__", fname, loader, pkg_name)

We can see that the most memory was allocated in the importlib module to load data (bytecode and constants) from modules: 870.1 KiB. The traceback is where the importlib loaded data most recently: on the import pdb line of the doctest module. The traceback may change if a new module is loaded.

27.7.1.4. Pretty top

Code to display the 10 lines allocating the most memory with a pretty output, ignoring <frozen importlib._bootstrap> and <unknown> files:

import linecache
import os
import tracemalloc

def display_top(snapshot, key_type='lineno', limit=10):
    snapshot = snapshot.filter_traces((
        tracemalloc.Filter(False, "<frozen importlib._bootstrap>"),
        tracemalloc.Filter(False, "<unknown>"),
    ))
    top_stats = snapshot.statistics(key_type)

    print("Top %s lines" % limit)
    for index, stat in enumerate(top_stats[:limit], 1):
        frame = stat.traceback[0]
        # replace "/path/to/module/file.py" with "module/file.py"
        filename = os.sep.join(frame.filename.split(os.sep)[-2:])
        print("#%s: %s:%s: %.1f KiB"
              % (index, filename, frame.lineno, stat.size / 1024))
        line = linecache.getline(frame.filename, frame.lineno).strip()
        if line:
            print('    %s' % line)

    other = top_stats[limit:]
    if other:
        size = sum(stat.size for stat in other)
        print("%s other: %.1f KiB" % (len(other), size / 1024))
    total = sum(stat.size for stat in top_stats)
    print("Total allocated size: %.1f KiB" % (total / 1024))

tracemalloc.start()

# ... run your application ...

snapshot = tracemalloc.take_snapshot()
display_top(snapshot)

Example of output of the Python test suite:

Top 10 lines
#1: Lib/base64.py:414: 419.8 KiB
    _b85chars2 = [(a + b) for a in _b85chars for b in _b85chars]
#2: Lib/base64.py:306: 419.8 KiB
    _a85chars2 = [(a + b) for a in _a85chars for b in _a85chars]
#3: collections/__init__.py:368: 293.6 KiB
    exec(class_definition, namespace)
#4: Lib/abc.py:133: 115.2 KiB
    cls = super().__new__(mcls, name, bases, namespace)
#5: unittest/case.py:574: 103.1 KiB
    testMethod()
#6: Lib/linecache.py:127: 95.4 KiB
    lines = fp.readlines()
#7: urllib/parse.py:476: 71.8 KiB
    for a in _hexdig for b in _hexdig}
#8: <string>:5: 62.0 KiB
#9: Lib/_weakrefset.py:37: 60.0 KiB
    self.data = set()
#10: Lib/base64.py:142: 59.8 KiB
    _b32tab2 = [a + b for a in _b32tab for b in _b32tab]
6220 other: 3602.8 KiB
Total allocated size: 5303.1 KiB

See Snapshot.statistics() for more options.

27.7.2. API

27.7.2.1. Fonctions

tracemalloc.clear_traces()

Clear traces of memory blocks allocated by Python.

See also stop().

tracemalloc.get_object_traceback(obj)

Get the traceback where the Python object obj was allocated. Return a Traceback instance, or None if the tracemalloc module is not tracing memory allocations or did not trace the allocation of the object.

See also gc.get_referrers() and sys.getsizeof() functions.

tracemalloc.get_traceback_limit()

Get the maximum number of frames stored in the traceback of a trace.

The tracemalloc module must be tracing memory allocations to get the limit, otherwise an exception is raised.

The limit is set by the start() function.

tracemalloc.get_traced_memory()

Get the current size and peak size of memory blocks traced by the tracemalloc module as a tuple: (current: int, peak: int).

tracemalloc.get_tracemalloc_memory()

Get the memory usage in bytes of the tracemalloc module used to store traces of memory blocks. Return an int.

tracemalloc.is_tracing()

True if the tracemalloc module is tracing Python memory allocations, False otherwise.

See also start() and stop() functions.

tracemalloc.start(nframe: int=1)

Start tracing Python memory allocations: install hooks on Python memory allocators. Collected tracebacks of traces will be limited to nframe frames. By default, a trace of a memory block only stores the most recent frame: the limit is 1. nframe must be greater or equal to 1.

Storing more than 1 frame is only useful to compute statistics grouped by 'traceback' or to compute cumulative statistics: see the Snapshot.compare_to() and Snapshot.statistics() methods.

Storing more frames increases the memory and CPU overhead of the tracemalloc module. Use the get_tracemalloc_memory() function to measure how much memory is used by the tracemalloc module.

The PYTHONTRACEMALLOC environment variable (PYTHONTRACEMALLOC=NFRAME) and the -X tracemalloc=NFRAME command line option can be used to start tracing at startup.

See also stop(), is_tracing() and get_traceback_limit() functions.

tracemalloc.stop()

Stop tracing Python memory allocations: uninstall hooks on Python memory allocators. Also clears all previously collected traces of memory blocks allocated by Python.

Call take_snapshot() function to take a snapshot of traces before clearing them.

See also start(), is_tracing() and clear_traces() functions.

tracemalloc.take_snapshot()

Take a snapshot of traces of memory blocks allocated by Python. Return a new Snapshot instance.

The snapshot does not include memory blocks allocated before the tracemalloc module started to trace memory allocations.

Tracebacks of traces are limited to get_traceback_limit() frames. Use the nframe parameter of the start() function to store more frames.

The tracemalloc module must be tracing memory allocations to take a snapshot, see the start() function.

See also the get_object_traceback() function.

27.7.2.2. DomainFilter

class tracemalloc.DomainFilter(inclusive: bool, domain: int)

Filter traces of memory blocks by their address space (domain).

Nouveau dans la version 3.6.

inclusive

If inclusive is True (include), match memory blocks allocated in the address space domain.

If inclusive is False (exclude), match memory blocks not allocated in the address space domain.

domain

Address space of a memory block (int). Read-only property.

27.7.2.3. Filter

class tracemalloc.Filter(inclusive: bool, filename_pattern: str, lineno: int=None, all_frames: bool=False, domain: int=None)

Filter on traces of memory blocks.

See the fnmatch.fnmatch() function for the syntax of filename_pattern. The '.pyc' file extension is replaced with '.py'.

Exemples :

Filter(True, subprocess.__file__) only includes traces of the subprocess module

Filter(False, tracemalloc.__file__) excludes traces of the tracemalloc module

Filter(False, "<unknown>") excludes empty tracebacks

Modifié dans la version 3.5: The '.pyo' file extension is no longer replaced with '.py'.

Modifié dans la version 3.6: Added the domain attribute.

domain

Address space of a memory block (int or None).

inclusive

If inclusive is True (include), only match memory blocks allocated in a file with a name matching filename_pattern at line number lineno.

If inclusive is False (exclude), ignore memory blocks allocated in a file with a name matching filename_pattern at line number lineno.

lineno

Line number (int) of the filter. If lineno is None, the filter matches any line number.

filename_pattern

Filename pattern of the filter (str). Read-only property.

all_frames

If all_frames is True, all frames of the traceback are checked. If all_frames is False, only the most recent frame is checked.

This attribute has no effect if the traceback limit is 1. See the get_traceback_limit() function and Snapshot.traceback_limit attribute.

27.7.2.4. Frame

class tracemalloc.Frame

Frame of a traceback.

The Traceback class is a sequence of Frame instances.

filename

Filename (str).

lineno

Line number (int).

27.7.2.5. Snapshot

class tracemalloc.Snapshot

Snapshot of traces of memory blocks allocated by Python.

The take_snapshot() function creates a snapshot instance.

compare_to(old_snapshot: Snapshot, key_type: str, cumulative: bool=False)

Compute the differences with an old snapshot. Get statistics as a sorted list of StatisticDiff instances grouped by key_type.

See the Snapshot.statistics() method for key_type and cumulative parameters.

The result is sorted from the biggest to the smallest by: absolute value of StatisticDiff.size_diff, StatisticDiff.size, absolute value of StatisticDiff.count_diff, Statistic.count and then by StatisticDiff.traceback.

dump(filename)

Write the snapshot into a file.

Use load() to reload the snapshot.

filter_traces(filters)

Create a new Snapshot instance with a filtered traces sequence, filters is a list of DomainFilter and Filter instances. If filters is an empty list, return a new Snapshot instance with a copy of the traces.

All inclusive filters are applied at once, a trace is ignored if no inclusive filters match it. A trace is ignored if at least one exclusive filter matches it.

Modifié dans la version 3.6: DomainFilter instances are now also accepted in filters.

classmethod load(filename)

Load a snapshot from a file.

See also dump().

statistics(key_type: str, cumulative: bool=False)

Get statistics as a sorted list of Statistic instances grouped by key_type:

key_type

description

'filename'

filename

'lineno'

filename and line number

'traceback'

traceback

If cumulative is True, cumulate size and count of memory blocks of all frames of the traceback of a trace, not only the most recent frame. The cumulative mode can only be used with key_type equals to 'filename' and 'lineno'.

The result is sorted from the biggest to the smallest by: Statistic.size, Statistic.count and then by Statistic.traceback.

traceback_limit

Maximum number of frames stored in the traceback of traces: result of the get_traceback_limit() when the snapshot was taken.

traces

Traces of all memory blocks allocated by Python: sequence of Trace instances.

The sequence has an undefined order. Use the Snapshot.statistics() method to get a sorted list of statistics.

27.7.2.6. Statistic

class tracemalloc.Statistic

Statistic on memory allocations.

Snapshot.statistics() returns a list of Statistic instances.

See also the StatisticDiff class.

count

Number of memory blocks (int).

size

Total size of memory blocks in bytes (int).

traceback

Traceback where the memory block was allocated, Traceback instance.

27.7.2.7. StatisticDiff

class tracemalloc.StatisticDiff

Statistic difference on memory allocations between an old and a new Snapshot instance.

Snapshot.compare_to() returns a list of StatisticDiff instances. See also the Statistic class.

count

Number of memory blocks in the new snapshot (int): 0 if the memory blocks have been released in the new snapshot.

count_diff

Difference of number of memory blocks between the old and the new snapshots (int): 0 if the memory blocks have been allocated in the new snapshot.

size

Total size of memory blocks in bytes in the new snapshot (int): 0 if the memory blocks have been released in the new snapshot.

size_diff

Difference of total size of memory blocks in bytes between the old and the new snapshots (int): 0 if the memory blocks have been allocated in the new snapshot.

traceback

Traceback where the memory blocks were allocated, Traceback instance.

27.7.2.8. Trace

class tracemalloc.Trace

Trace of a memory block.

The Snapshot.traces attribute is a sequence of Trace instances.

size

Size of the memory block in bytes (int).

traceback

Traceback where the memory block was allocated, Traceback instance.

27.7.2.9. Traceback

class tracemalloc.Traceback

Sequence of Frame instances sorted from the most recent frame to the oldest frame.

A traceback contains at least 1 frame. If the tracemalloc module failed to get a frame, the filename "<unknown>" at line number 0 is used.

When a snapshot is taken, tracebacks of traces are limited to get_traceback_limit() frames. See the take_snapshot() function.

The Trace.traceback attribute is an instance of Traceback instance.

format(limit=None)

Format the traceback as a list of lines with newlines. Use the linecache module to retrieve lines from the source code. If limit is set, only format the limit most recent frames.

Similar to the traceback.format_tb() function, except that format() does not include newlines.

Exemple :

print("Traceback (most recent call first):")
for line in traceback:
    print(line)

Sortie :

Traceback (most recent call first):
  File "test.py", line 9
    obj = Object()
  File "test.py", line 12
    tb = tracemalloc.get_object_traceback(f())

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28. Paquets et distribution de paquets logiciels

Ces bibliothèques vous aident lors de la publication et l’installation de logiciels Python. Bien que ces modules sont conçus pour fonctionner avec le Python Package Index [https://pypi.org], ils peuvent aussi être utilisés avec un serveur local, ou sans serveur.

28.1. distutils — Création et installation des modules Python

28.2. ensurepip — Bootstrapping the pip installer

28.2.1. Command line interface

28.2.2. Module API

28.3. venv — Création d’environnements virtuels

28.3.1. Création d’environnements virtuels

28.3.2. API

28.3.3. Un exemple d’extension de EnvBuilder

28.4. zipapp — Manage executable python zip archives

28.4.1. Exemple de base

28.4.2. Interface en ligne de commande

28.4.3. API Python

28.4.4. Exemples

28.4.5. Spécification de l’interprète

28.4.6. Création d’applications autonomes avec zipapp

28.4.6.1. Création d’un exécutable Windows

28.4.6.2. Mises en garde

28.4.7. Le format d’archive d’application Zip Python

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28.1. distutils — Création et installation des modules Python

Le package distutils fournit le support pour la création et l’installation de modules supplémentaires dans une installation Python. Les nouveaux modules peuvent être soit en Python pur à 100%, soit des modules d’extension écrits en C, soit des collections de paquets Python qui incluent des modules codés en C et en Python.

La plupart des utilisateurs de Python ne voudront pas utiliser ce module directement, mais plutôt les outils cross-version maintenus par la Python Packaging Authority. En particulier, setuptools [https://setuptools.readthedocs.io/en/latest/] est une alternative améliorée à distutils qui fournit :

support pour la déclaration des dépendances de projets

mécanismes supplémentaires pour configurer quels fichiers inclure dans les distributions source (y compris les extensions pour l’intégration avec les systèmes de contrôle de version)

la possibilité de déclarer les « points d’entrée » du projet, qui peuvent être utilisés comme base pour les systèmes d’extensions

la possibilité de générer automatiquement des exécutables en ligne de commande Windows au moment de l’installation plutôt que de devoir les pré-construire

comportement cohérent entre toutes les versions Python supportées

Le programme d’installation recommandé pip [https://pip.pypa.io/] exécute tous les scripts setup. py avec setuptools, même si le script lui-même n’importe que distutils. Pour plus d’informations, reportez-vous au Python Packaging User Guide [https://packaging.python.org].

À destination des auteurs et utilisateurs d’outils d’empaquetage cherchant une compréhension plus approfondie des détails du système actuel de création de paquets et de leur distribution, la documentation utilisateur historique de distutils la référence de son API restent disponibles :

Installation des modules python (Version historique)

Distribuer des modules Python (Version historique)

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28.2. ensurepip — Bootstrapping the pip installer

Nouveau dans la version 3.4.

The ensurepip package provides support for bootstrapping the pip installer into an existing Python installation or virtual environment. This bootstrapping approach reflects the fact that pip is an independent project with its own release cycle, and the latest available stable version is bundled with maintenance and feature releases of the CPython reference interpreter.

In most cases, end users of Python shouldn’t need to invoke this module directly (as pip should be bootstrapped by default), but it may be needed if installing pip was skipped when installing Python (or when creating a virtual environment) or after explicitly uninstalling pip.

Note

This module does not access the internet. All of the components needed to bootstrap pip are included as internal parts of the package.

Voir aussi

Installation de modules Python

The end user guide for installing Python packages

PEP 453 [https://www.python.org/dev/peps/pep-0453]: Explicit bootstrapping of pip in Python installations

The original rationale and specification for this module.

28.2.1. Command line interface

The command line interface is invoked using the interpreter’s -m switch.

The simplest possible invocation is:

python -m ensurepip

This invocation will install pip if it is not already installed, but otherwise does nothing. To ensure the installed version of pip is at least as recent as the one bundled with ensurepip, pass the --upgrade option:

python -m ensurepip --upgrade

By default, pip is installed into the current virtual environment (if one is active) or into the system site packages (if there is no active virtual environment). The installation location can be controlled through two additional command line options:

--root <dir>: Installs pip relative to the given root directory rather than the root of the currently active virtual environment (if any) or the default root for the current Python installation.

--user: Installs pip into the user site packages directory rather than globally for the current Python installation (this option is not permitted inside an active virtual environment).

By default, the scripts pipX and pipX.Y will be installed (where X.Y stands for the version of Python used to invoke ensurepip). The scripts installed can be controlled through two additional command line options:

--altinstall: if an alternate installation is requested, the pipX script will not be installed.

--default-pip: if a « default pip » installation is requested, the

pip script will be installed in addition to the two regular scripts.

Providing both of the script selection options will trigger an exception.

Modifié dans la version 3.6.3: The exit status is non-zero if the command fails.

28.2.2. Module API

ensurepip exposes two functions for programmatic use:

ensurepip.version()

Returns a string specifying the bundled version of pip that will be installed when bootstrapping an environment.

ensurepip.bootstrap(root=None, upgrade=False, user=False, altinstall=False, default_pip=False, verbosity=0)

Bootstraps pip into the current or designated environment.

root specifies an alternative root directory to install relative to. If root is None, then installation uses the default install location for the current environment.

upgrade indicates whether or not to upgrade an existing installation of an earlier version of pip to the bundled version.

user indicates whether to use the user scheme rather than installing globally.

By default, the scripts pipX and pipX.Y will be installed (where X.Y stands for the current version of Python).

If altinstall is set, then pipX will not be installed.

If default_pip is set, then pip will be installed in addition to the two regular scripts.

Setting both altinstall and default_pip will trigger ValueError.

verbosity controls the level of output to sys.stdout from the bootstrapping operation.

Note

The bootstrapping process has side effects on both sys.path and os.environ. Invoking the command line interface in a subprocess instead allows these side effects to be avoided.

Note

The bootstrapping process may install additional modules required by pip, but other software should not assume those dependencies will always be present by default (as the dependencies may be removed in a future version of pip).

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28.3. venv — Création d’environnements virtuels

Nouveau dans la version 3.3.

Code source : Lib/venv/ [https://github.com/python/cpython/tree/3.6/Lib/venv/]

The venv module provides support for creating lightweight « virtual environments » with their own site directories, optionally isolated from system site directories. Each virtual environment has its own Python binary (allowing creation of environments with various Python versions) and can have its own independent set of installed Python packages in its site directories.

Voir la PEP 405 [https://www.python.org/dev/peps/pep-0405] pour plus d’informations à propos des environnements virtuels Python.

Note

Le script pyenv est obsolète depuis Python 3.6 et a été remplacé par python3 -m venv.

28.3.1. Création d’environnements virtuels

La création d”environnements virtuels est faite en exécutant la commande venv :

python3 -m venv /path/to/new/virtual/environment

Running this command creates the target directory (creating any parent directories that don’t exist already) and places a pyvenv.cfg file in it with a home key pointing to the Python installation from which the command was run. It also creates a bin (or Scripts on Windows) subdirectory containing a copy/symlink of the Python binary/binaries (as appropriate for the platform or arguments used at environment creation time). It also creates an (initially empty) lib/pythonX.Y/site-packages subdirectory (on Windows, this is Lib\site-packages). If an existing directory is specified, it will be re-used.

Obsolète depuis la version 3.6: pyvenv était l’outil recommandé pour créer des environnements sous Python 3.3 et 3.4, et est obsolète depuis Python 3.6 [https://docs.python.org/dev/whatsnew/3.6.html#deprecated-features].

Modifié dans la version 3.5: L’utilisation de venv est maintenant recommandée pour créer vos environnements virtuels.

Voir aussi

Guide Utilisateur de l’Empaquetage Python : Créer et utiliser des environnements virtuels [https://packaging.python.org/installing/#creating-virtual-environments]

Sur Windows, appelez la commande venv comme suit :

c:\>c:\Python35\python -m venv c:\path\to\myenv

Alternativement, si vous avez configuré les variables PATH et PATHEXT pour votre installation Python :

c:\>python -m venv c:\path\to\myenv

La commande, si lancée avec -h, montrera les options disponibles :

usage: venv [-h] [--system-site-packages] [--symlinks | --copies] [--clear]
            [--upgrade] [--without-pip]
            ENV_DIR [ENV_DIR ...]

Creates virtual Python environments in one or more target directories.

positional arguments:
  ENV_DIR               A directory to create the environment in.

optional arguments:
  -h, --help            show this help message and exit
  --system-site-packages
                        Give the virtual environment access to the system
                        site-packages dir.
  --symlinks            Try to use symlinks rather than copies, when symlinks
                        are not the default for the platform.
  --copies              Try to use copies rather than symlinks, even when
                        symlinks are the default for the platform.
  --clear               Delete the contents of the environment directory if it
                        already exists, before environment creation.
  --upgrade             Upgrade the environment directory to use this version
                        of Python, assuming Python has been upgraded in-place.
  --without-pip         Skips installing or upgrading pip in the virtual
                        environment (pip is bootstrapped by default)

Once an environment has been created, you may wish to activate it, e.g. by
sourcing an activate script in its bin directory.

Modifié dans la version 3.4: Installe pip par défaut, ajout des options --without-pip et --copies

Modifié dans la version 3.4: Dans les versions précédentes, si le dossier de destination existait déjà, une erreur était levée, sauf si l’option --clear ou --upgrade était incluse.

Le fichier crée pyenv.cfg inclus aussi la clé include-system-site-packages, dont la valeur est true si venv est lancé avec l’option --system-site-packages, sinon sa valeur est false.

Sauf si l’option --without-pip est incluse, ensurepip sera invoqué pour amorcer pip dans l’environnement virtuel.

Plusieurs chemins peuvent être donnés à venv, et dans ce cas un environnement virtuel sera créé, en fonction des options incluses, à chaque chemin donné.

Once a virtual environment has been created, it can be « activated » using a script in the virtual environment’s binary directory. The invocation of the script is platform-specific (<venv> must be replaced by the path of the directory containing the virtual environment):

Plateforme

Invite de commande

Commande pour activer l’environnement virtuel

Posix

bash/zsh

$ source <venv>/bin/activate

fish

$ . <venv>/bin/activate.fish

csh/tcsh

$ source <venv>/bin/activate.csh

Windows

cmd.exe

C:\\{venv}\\Scripts\\activate.bat

PowerShell

PS C:\\> <venv>\\Scripts\\Activate.ps1

Vous ne devez pas spécialement activer un environnement ; l’activation ajoute juste le chemin du dossier de binaires de votre environnement virtuel à votre PATH, pour que « python » invoque l’interpréteur Python de l’environnement virtuel et que vous puissiez lancer des scripts installés sans avoir à utiliser leur chemin complet. Cependant, tous les scripts installés dans un environnement virtuel devraient être exécutables sans l’activer, et se lancer avec l’environnement virtuel Python automatiquement.

Vous pouvez désactiver un environnement virtuel en écrivant « deactivate » dans votre shell. Le mécanisme est spécifique à chaque plateforme : Par exemple, le script d’activation pour Bash défini une fonction « deactivate », alors que sur Windows il y a des scripts séparés appelés deactivate.bat et Deactivate.ps1 qui sont installés quand l’environnement virtuel est créé.

Nouveau dans la version 3.4: Les scripts d’activation pour fish et csh.

Note

Un environnement virtuel est un environnement Python tel que l’interpréteur Python, les bibliothèques et les scripts installés sont isolés de ceux installés dans d’autres environnements virtuels, et (par défaut) de toutes autres bibliothèques installées dans un Python « système », par exemple celui qui est installé avec votre système d’exploitation.

Un environnement virtuel est une arborescence de dossiers qui contiens les fichiers exécutables Python et autres fichiers qui indiquent que c’est un environnement virtuel.

Les outils d’installations communs comme Setuptools et pip fonctionnent comme prévu avec des environnements virtuels. En d’autres termes, quand un environnement virtuel est actif, ils installent les paquets Python dans l’environnement virtuel sans avoir besoin de leur préciser explicitement.

Quand un environnement virtuel est actif (Par exemple quand l’interpréteur Python de l’environnement virtuel est lancé), les attributs sys.prefix et sys.exec_prefix pointent vers le dossier racine de l’environnement virtuel, alors que sys.base_prefix et sys.base_exec_prefix pointent vers l’installation de Python qui n’est pas celle de l’environnement virtuel et qui a été utilisée pour créer l’environnement virtuel. Si un environnement virtuel n’est pas actif, alors sys.prefix est égal à sys.base_prefix et sys.exec_prefix est égal à sys.base_exec_prefix (ils pointent tous sur une installation Python qui n’est pas un environnement virtuel).

Quand un environnement virtuel est actif, toute option qui change le chemin d’installation sera ignoré de tous les fichiers de configuration distutils pour éviter que des projets soient accidentellement installés en dehors de l’environnement virtuel.

Quand vous travaillez dans une invite de commande shell, les utilisateurs peuvent activer un environnement virtuel en lançant un script activate situé dans le dossier des exécutables de l’environnement virtuel (le nom de fichier précis dépends du shell utilisé), ce qui ajoute le dossier des exécutables de l’environnement virtuel dans la variable d’environnement PATH. Il ne devrait jamais y avoir besoin dans d’autre circonstances d’activer un environnement virtuel. Des scripts installés dans un environnement virtuel ont un shebang qui pointe vers l’interpréteur Python de l’environnement virtuel. Cela veux dire que le script sera lancé avec cet interpréteur peut importe la valeur de PATH. Sur Windows, le shebang est interprété si vous avez le Lanceur Python pour Windows installé (Cela a été ajouté à Python 3.3 – Voir PEP 397 [https://www.python.org/dev/peps/pep-0397] pour plus de détails). De ce fait, double cliquer un script installé dans une fenêtre de l’Explorateur Windows devrai lancer le script avec le bon interpréteur sans avoir besoin de référencer son environnement virtuel dans PATH.

28.3.2. API

La méthode haut niveau décrite au dessus utilise une API simple qui permet à des créateurs d’environnements virtuels externes de personnaliser la création d’environnements virtuels basés sur leurs besoins, la classe EnvBuilder.

class venv.EnvBuilder(system_site_packages=False, clear=False, symlinks=False, upgrade=False, with_pip=False, prompt=None)

La classe EnvBuilder accepte les arguments suivants lors de l’instanciation :

system_site_packages – Une valeur booléenne qui indique que les site-packages du système Python devraient être disponibles dans l’environnement virtuel (par défaut à False).

clear – Une valeur booléenne qui, si vraie, supprimera le contenu de n’importe quel dossier existant cible, avant de créer l’environnement.

symlinks – a Boolean value indicating whether to attempt to symlink the Python binary (and any necessary DLLs or other binaries, e.g. pythonw.exe), rather than copying.

upgrade – Une valeur booléenne qui, si vraie, mettra à jour un environnement existant avec le Python lancé – utilisé quand Python à été mis a jour sur place (par défaut à False).

with_pip – Une valeur booléenne qui, si vraie, assure que pip est installé dans l’environnement virtuel. Cela utilise ensurepip avec l’option --default-pip.

prompt – Une chaine utilisée après que l’environnement virtuel est activé (par défaut à None ce qui veux dire qu’il utilisera le nom du dossier de l’environnement).

Modifié dans la version 3.4: Ajout du paramètre with_pip

Nouveau dans la version 3.6: Ajout du paramètre prompt

Les créateurs des outils de création d’environnement virtuel externes seront libres d’utiliser la classe EnvBuilder en tant que classe de base.

Le env-builder retourné est un objet qui a une méthode, create :

create(env_dir)

Cette méthode prends en argument obligatoire le chemin (absolu ou relatif par rapport au dossier courant) du dossier cible qui doit contenir l’environnement virtuel. La méthode create doit soit créer un environnement dans le dossier spécifié, soit lever une exception.

La méthode create de la classe EnvBuilder illustre les points d’entrées disponibles pour la personnalisation de sous-classes :

def create(self, env_dir):
    """
    Create a virtualized Python environment in a directory.
    env_dir is the target directory to create an environment in.
    """
    env_dir = os.path.abspath(env_dir)
    context = self.ensure_directories(env_dir)
    self.create_configuration(context)
    self.setup_python(context)
    self.setup_scripts(context)
    self.post_setup(context)

Chacune des méthodes ensure_directories(), create_configuration(), setup_python(), setup_scripts() et post_setup() peuvent être écrasés.

ensure_directories(env_dir)

Crée un dossier d’environnement et tous les dossiers nécessaires, et retourne un objet contexte. C’est juste un conteneur pour des attributs (comme des chemins), qui sera utilisé par d’autres méthodes. Ces dossiers peuvent déjà exister. tant que clear ou upgrade ont été spécifiés pour permettre de telles opérations dans un dossier d’environnement existant.

create_configuration(context)

Crée le fichier de configuration pyenv.cfg dans l’environnement.

setup_python(context)

Creates a copy of the Python executable (and, under Windows, DLLs) in the environment. On a POSIX system, if a specific executable python3.x was used, symlinks to python and python3 will be created pointing to that executable, unless files with those names already exist.

setup_scripts(context)

Installe les scripts d’activation appropriés à la plateforme dans l’environnement virtuel.

post_setup(context)

Une méthode qui n’est la que pour se faire surcharger dans des implémentation externes pour pré installer des paquets dans l’environnement virtuel ou pour exécuter des étapes post-création.

De plus, EnvBuilder propose cette méthode utilitaire qui peut être appelée de setup_scripts() ou post_setup() dans des sous classes pour assister dans l’installation de scripts customs dans l’environnement virtuel.

install_scripts(context, path)

path corresponds au chemin vers le dossier qui contiens les sous dossiers « common », « posix », « nt », chacun contenant des scripts destinés pour le dossier « bin » dans l’environnement. Le contenu du dossier « common » et le dossier correspondant à os.name sont copiés après quelque remplacement de texte temporaires :

__VENV_DIR__ est remplacé avec le chemin absolu du dossier de l’environnement.

__VENV_NAME__ est remplacé avec le nom de l’environnement (le dernier segment du chemin vers le dossier de l’environnement).

__VENV_PROMPT__ est remplacé par le prompt (nom de l’environnement entouré de parenthèses et avec un espace le suivant).

__VENV_BIN_NAME__ est remplacé par le nom du dossier bin (soit bin soit Scripts).

__VENV_PYTHON__ est remplacé avec le chemin absolu de l’exécutable de l’environnement.

Les dossiers peuvent exister (pour quand un environnement existant est mis à jour).

Il y a aussi une fonction pratique au niveau du module :

venv.create(env_dir, system_site_packages=False, clear=False, symlinks=False, with_pip=False)

Crée une EnvBuilder avec les arguments donnés, et appelle sa méthode create() avec l’argument env_dir.

Modifié dans la version 3.4: Ajout du paramètre with_pip

28.3.3. Un exemple d’extension de EnvBuilder

Le script qui suis montre comment étendre EnvBuilder en implémentant une sous-classe qui installe setuptools et pip dans un environnement créé :

import os
import os.path
from subprocess import Popen, PIPE
import sys
from threading import Thread
from urllib.parse import urlparse
from urllib.request import urlretrieve
import venv

class ExtendedEnvBuilder(venv.EnvBuilder):
    """
    This builder installs setuptools and pip so that you can pip or
    easy_install other packages into the created virtual environment.

    :param nodist: If True, setuptools and pip are not installed into the
                   created virtual environment.
    :param nopip: If True, pip is not installed into the created
                  virtual environment.
    :param progress: If setuptools or pip are installed, the progress of the
                     installation can be monitored by passing a progress
                     callable. If specified, it is called with two
                     arguments: a string indicating some progress, and a
                     context indicating where the string is coming from.
                     The context argument can have one of three values:
                     'main', indicating that it is called from virtualize()
                     itself, and 'stdout' and 'stderr', which are obtained
                     by reading lines from the output streams of a subprocess
                     which is used to install the app.

                     If a callable is not specified, default progress
                     information is output to sys.stderr.
    """

    def __init__(self, *args, **kwargs):
        self.nodist = kwargs.pop('nodist', False)
        self.nopip = kwargs.pop('nopip', False)
        self.progress = kwargs.pop('progress', None)
        self.verbose = kwargs.pop('verbose', False)
        super().__init__(*args, **kwargs)

    def post_setup(self, context):
        """
        Set up any packages which need to be pre-installed into the
        virtual environment being created.

        :param context: The information for the virtual environment
                        creation request being processed.
        """
        os.environ['VIRTUAL_ENV'] = context.env_dir
        if not self.nodist:
            self.install_setuptools(context)
        # Can't install pip without setuptools
        if not self.nopip and not self.nodist:
            self.install_pip(context)

    def reader(self, stream, context):
        """
        Read lines from a subprocess' output stream and either pass to a progress
        callable (if specified) or write progress information to sys.stderr.
        """
        progress = self.progress
        while True:
            s = stream.readline()
            if not s:
                break
            if progress is not None:
                progress(s, context)
            else:
                if not self.verbose:
                    sys.stderr.write('.')
                else:
                    sys.stderr.write(s.decode('utf-8'))
                sys.stderr.flush()
        stream.close()

    def install_script(self, context, name, url):
        _, _, path, _, _, _ = urlparse(url)
        fn = os.path.split(path)[-1]
        binpath = context.bin_path
        distpath = os.path.join(binpath, fn)
        # Download script into the virtual environment's binaries folder
        urlretrieve(url, distpath)
        progress = self.progress
        if self.verbose:
            term = '\n'
        else:
            term = ''
        if progress is not None:
            progress('Installing %s ...%s' % (name, term), 'main')
        else:
            sys.stderr.write('Installing %s ...%s' % (name, term))
            sys.stderr.flush()
        # Install in the virtual environment
        args = [context.env_exe, fn]
        p = Popen(args, stdout=PIPE, stderr=PIPE, cwd=binpath)
        t1 = Thread(target=self.reader, args=(p.stdout, 'stdout'))
        t1.start()
        t2 = Thread(target=self.reader, args=(p.stderr, 'stderr'))
        t2.start()
        p.wait()
        t1.join()
        t2.join()
        if progress is not None:
            progress('done.', 'main')
        else:
            sys.stderr.write('done.\n')
        # Clean up - no longer needed
        os.unlink(distpath)

    def install_setuptools(self, context):
        """
        Install setuptools in the virtual environment.

        :param context: The information for the virtual environment
                        creation request being processed.
        """
        url = 'https://bitbucket.org/pypa/setuptools/downloads/ez_setup.py'
        self.install_script(context, 'setuptools', url)
        # clear up the setuptools archive which gets downloaded
        pred = lambda o: o.startswith('setuptools-') and o.endswith('.tar.gz')
        files = filter(pred, os.listdir(context.bin_path))
        for f in files:
            f = os.path.join(context.bin_path, f)
            os.unlink(f)

    def install_pip(self, context):
        """
        Install pip in the virtual environment.

        :param context: The information for the virtual environment
                        creation request being processed.
        """
        url = 'https://raw.github.com/pypa/pip/master/contrib/get-pip.py'
        self.install_script(context, 'pip', url)

def main(args=None):
    compatible = True
    if sys.version_info < (3, 3):
        compatible = False
    elif not hasattr(sys, 'base_prefix'):
        compatible = False
    if not compatible:
        raise ValueError('This script is only for use with '
                         'Python 3.3 or later')
    else:
        import argparse

        parser = argparse.ArgumentParser(prog=__name__,
                                         description='Creates virtual Python '
                                                     'environments in one or '
                                                     'more target '
                                                     'directories.')
        parser.add_argument('dirs', metavar='ENV_DIR', nargs='+',
                            help='A directory in which to create the
                                 'virtual environment.')
        parser.add_argument('--no-setuptools', default=False,
                            action='store_true', dest='nodist',
                            help="Don't install setuptools or pip in the "
                                 "virtual environment.")
        parser.add_argument('--no-pip', default=False,
                            action='store_true', dest='nopip',
                            help="Don't install pip in the virtual "
                                 "environment.")
        parser.add_argument('--system-site-packages', default=False,
                            action='store_true', dest='system_site',
                            help='Give the virtual environment access to the '
                                 'system site-packages dir.')
        if os.name == 'nt':
            use_symlinks = False
        else:
            use_symlinks = True
        parser.add_argument('--symlinks', default=use_symlinks,
                            action='store_true', dest='symlinks',
                            help='Try to use symlinks rather than copies, '
                                 'when symlinks are not the default for '
                                 'the platform.')
        parser.add_argument('--clear', default=False, action='store_true',
                            dest='clear', help='Delete the contents of the '
                                               'virtual environment '
                                               'directory if it already '
                                               'exists, before virtual '
                                               'environment creation.')
        parser.add_argument('--upgrade', default=False, action='store_true',
                            dest='upgrade', help='Upgrade the virtual '
                                                 'environment directory to '
                                                 'use this version of '
                                                 'Python, assuming Python '
                                                 'has been upgraded '
                                                 'in-place.')
        parser.add_argument('--verbose', default=False, action='store_true',
                            dest='verbose', help='Display the output '
                                               'from the scripts which '
                                               'install setuptools and pip.')
        options = parser.parse_args(args)
        if options.upgrade and options.clear:
            raise ValueError('you cannot supply --upgrade and --clear together.')
        builder = ExtendedEnvBuilder(system_site_packages=options.system_site,
                                       clear=options.clear,
                                       symlinks=options.symlinks,
                                       upgrade=options.upgrade,
                                       nodist=options.nodist,
                                       nopip=options.nopip,
                                       verbose=options.verbose)
        for d in options.dirs:
            builder.create(d)

if __name__ == '__main__':
    rc = 1
    try:
        main()
        rc = 0
    except Exception as e:
        print('Error: %s' % e, file=sys.stderr)
    sys.exit(rc)

This script is also available for download online [https://gist.github.com/4673395].

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28.4. zipapp — Manage executable python zip archives

Nouveau dans la version 3.5.

Code source : Lib/zipapp.py [https://github.com/python/cpython/tree/3.6/Lib/zipapp.py]

Ce module fournit des outils pour gérer la création de fichiers zip contenant du code Python, qui peuvent être exécutés directement par l’interpréteur Python. Le module fournit à la fois une interface de ligne de commande Interface en ligne de commande et une interface API Python.

28.4.1. Exemple de base

L’exemple suivant montre comment l’interface de ligne de commande Interface en ligne de commande peut être utilisée pour créer une archive exécutable depuis un répertoire contenant du code Python. Lors de l’exécution, l’archive exécutera la fonction main du module myapp dans l’archive.

$ python -m zipapp myapp -m "myapp:main"
$ python myapp.pyz
<output from myapp>

28.4.2. Interface en ligne de commande

Lorsqu’il est appelé en tant que programme à partir de la ligne de commande, la syntaxe suivante est utilisée :

$ python -m zipapp source [options]

Si source est un répertoire, une archive est créée à partir du contenu de source. Si source est un fichier, ce doit être une archive et il est copié dans l’archive cible (ou le contenu de sa ligne shebang est affiché si l’option --info est indiquée).

Les options suivantes sont disponibles :

-o <output>, --output=<output>

Écrit la sortie dans un fichier nommé output. Si cette option n’est pas spécifiée, le nom du fichier de sortie sera le même que celui de l’entrée source, avec l’extension .pyz. Si un nom de fichier explicite est donné, il est utilisé tel quel (une extension .pyz doit donc être incluse si nécessaire).

Un nom de fichier de sortie doit être spécifié si la source est une archive (et, dans ce cas, la sortie ne doit pas être la même que la source).

-p <interpreter>, --python=<interpreter>

Ajoute une ligne #! à l’archive en spécifiant interpreter comme commande à exécuter. Aussi, sur un système POSIX, cela rend l’archive exécutable. Le comportement par défaut est de ne pas écrire la ligne #! et de ne pas rendre le fichier exécutable.

-m <mainfn>, --main=<mainfn>

Écrit un fichier __main__.py dans l’archive qui exécute mainfn. L’argument mainfn est de la forme « pkg.mod:fn », où « pkg.mod » est un paquet/module dans l’archive, et « fn » est un appelable dans le module donné. Le fichier __main__.py réalise cet appel.

--main ne peut pas être spécifié lors de la copie d’une archive.

--info

Affiche l’interpréteur intégré dans l’archive, à des fins de diagnostic. Dans ce cas, toutes les autres options sont ignorées et SOURCE doit être une archive et non un répertoire.

-h, --help

Affiche un court message d’aide et quitte.

28.4.3. API Python

Ce module définit deux fonctions utilitaires :

zipapp.create_archive(source, target=None, interpreter=None, main=None)

Crée une archive d’application à partir de source. La source peut être de natures suivantes :

The name of a directory, or a pathlib.Path object referring to a directory, in which case a new application archive will be created from the content of that directory.

The name of an existing application archive file, or a pathlib.Path object referring to such a file, in which case the file is copied to the target (modifying it to reflect the value given for the interpreter argument). The file name should include the .pyz extension, if required.

Un objet fichier ouvert pour la lecture en mode binaire. Le contenu du fichier doit être une archive d’application et Python suppose que l’objet fichier est positionné au début de l’archive.

L’argument target détermine où l’archive résultante sera écrite :

If it is the name of a file, or a pathlb.Path object, the archive will be written to that file.

S’il s’agit d’un objet fichier ouvert, l’archive sera écrite dans cet objet fichier, qui doit être ouvert pour l’écriture en mode octets.

Si la cible est omise (ou None), la source doit être un répertoire et la cible sera un fichier portant le même nom que la source, avec une extension .pyz ajoutée.

L’argument interpreter spécifie le nom de l’interpréteur Python avec lequel l’archive sera exécutée. Il est écrit dans une ligne shebang au début de l’archive. Sur un système POSIX, cela est interprété par le système d’exploitation et, sur Windows, il sera géré par le lanceur Python. L’omission de l”interpreter n’entraîne pas l’écriture d’une ligne shebang. Si un interpréteur est spécifié et que la cible est un nom de fichier, le bit exécutable du fichier cible sera mis à 1.

L’argument main spécifie le nom d’un appelable, utilisé comme programme principal pour l’archive. Il ne peut être spécifié que si la source est un répertoire et si la source ne contient pas déjà un fichier __main__.py. L’argument main doit prendre la forme pkg.module:callable et l’archive sera exécutée en important pkg.module et en exécutant l’appelable donné sans argument. Omettre main est une erreur si la source est un répertoire et ne contient pas un fichier __main__.py car, dans ce cas, l’archive résultante ne serait pas exécutable.

Si un objet fichier est spécifié pour source ou target, il est de la responsabilité de l’appelant de le fermer après avoir appelé create_archive.

Lors de la copie d’une archive existante, les objets fichier fournis n’ont besoin que des méthodes read et readline ou write. Lors de la création d’une archive à partir d’un répertoire, si la cible est un objet fichier, elle sera passée à la classe zipfile.ZipFile et devra fournir les méthodes nécessaires à cette classe.

zipapp.get_interpreter(archive)

Renvoie l’interpréteur spécifié dans la ligne #! au début de l’archive. S’il n’y a pas de ligne #!, renvoie None. L’argument archive peut être un nom de fichier ou un objet de type fichier ouvert à la lecture en mode binaire. Python suppose qu’il est au début de l’archive.

28.4.4. Exemples

Regroupe le contenu d’un répertoire dans une archive, puis l’exécute.

$ python -m zipapp myapp
$ python myapp.pyz
<output from myapp>

The same can be done using the create_archive() functon:

>>> import zipapp
>>> zipapp.create_archive('myapp.pyz', 'myapp')

Pour rendre l’application directement exécutable sur un système POSIX, spécifiez un interpréteur à utiliser.

$ python -m zipapp myapp -p "/usr/bin/env python"
$ ./myapp.pyz
<output from myapp>

Pour remplacer la ligne shebang sur une archive existante, créez une archive modifiée en utilisant la fonction create_archive() :

>>> import zipapp
>>> zipapp.create_archive('old_archive.pyz', 'new_archive.pyz', '/usr/bin/python3')

Pour mettre à jour le fichier sans créer de copie locale, effectuez le remplacement en mémoire à l’aide d’un objet BytesIO, puis écrasez la source par la suite. Notez qu’il y a un risque lors de l’écrasement d’un fichier local qu’une erreur entraîne la perte du fichier original. Ce code ne protège pas contre de telles erreurs, assurez-vous de prendre les mesures nécessaires en production. De plus, cette méthode ne fonctionnera que si l’archive tient en mémoire :

>>> import zipapp
>>> import io
>>> temp = io.BytesIO()
>>> zipapp.create_archive('myapp.pyz', temp, '/usr/bin/python2')
>>> with open('myapp.pyz', 'wb') as f:
>>>     f.write(temp.getvalue())

28.4.5. Spécification de l’interprète

Notez que si vous spécifiez un interpréteur et que vous distribuez ensuite votre archive d’application, vous devez vous assurer que l’interpréteur utilisé est portable. Le lanceur Python pour Windows gère la plupart des formes courantes de la ligne POSIX #!, mais il y a d’autres problèmes à considérer :

Si vous utilisez /usr/bin/env python (ou d’autres formes de la commande python, comme /usr/bin/python), vous devez considérer que vos utilisateurs peuvent avoir Python 2 ou Python 3 par défaut, et écrire votre code pour fonctionner dans les deux versions.

Si vous utilisez une version explicite, par exemple /usr/bin/env python3 votre application ne fonctionnera pas pour les utilisateurs qui n’ont pas cette version. (C’est peut-être ce que vous voulez si vous n’avez pas rendu votre code compatible Python 2).

Il n’y a aucun moyen de dire « python X.Y ou supérieur » donc faites attention si vous utilisez une version exacte comme /usr/bin/env python3.4 car vous devrez changer votre ligne shebang pour les utilisateurs de Python 3.5, par exemple.

Normalement, vous devriez utiliser un /usr/bin/env python2 ou /usr/bin/env python3, selon que votre code soit écrit pour Python 2 ou 3.

28.4.6. Création d’applications autonomes avec zipapp

En utilisant le module zipapp, il est possible de créer des programmes Python qui peuvent être distribués à des utilisateurs finaux dont le seul pré-requis est d’avoir la bonne version de Python installée sur leur ordinateur. Pour y arriver, la clé est de regrouper toutes les dépendances de l’application dans l’archive avec le code source de l’application.

Les étapes pour créer une archive autonome sont les suivantes :

Créez votre application dans un répertoire comme d’habitude, de manière à avoir un répertoire myapp contenant un fichier __main__.py et tout le code de l’application correspondante.

Installez toutes les dépendances de votre application dans le répertoire myapp en utilisant pip :

$ python -m pip install -r requirements.txt --target myapp

(ceci suppose que vous ayez vos dépendances de projet dans un fichier requirements.txt — sinon vous pouvez simplement lister les dépendances manuellement sur la ligne de commande pip).

Si nécessaire, supprimez les répertoires .dist-info créés par pip dans le répertoire myapp. Ceux-ci contiennent des métadonnées pour pip afin de gérer les paquets et, comme vous n’utiliserez plus pip, ils ne sont pas nécessaires (c’est sans conséquence si vous les laissez).

Regroupez le tout à l’aide de :

$ python -m zipapp -p "interpreter" myapp

Cela produira un exécutable autonome qui peut être exécuté sur n’importe quelle machine avec l’interpréteur approprié disponible. Voir Spécification de l’interprète pour plus de détails. Il peut être envoyé aux utilisateurs sous la forme d’un seul fichier.

Sous Unix, le fichier myapp.pyz est exécutable tel quel. Vous pouvez renommer le fichier pour supprimer l’extension .pyz si vous préférez un nom de commande « simple ». Sous Windows, le fichier myapp.pyz[w] est exécutable en vertu du fait que l’interpréteur Python est associé aux extensions de fichier .pyz et .pyzw une fois installé.

28.4.6.1. Création d’un exécutable Windows

Sous Windows, l’association de Python à l’extension .pyz est facultative et, de plus, il y a certains mécanismes qui ne reconnaissent pas les extensions enregistrées de manière « transparente » (l’exemple le plus simple est que subprocess.run(['myapp']) ne trouvera pas votre application — vous devez explicitement spécifier l’extension).

Sous Windows, il est donc souvent préférable de créer un exécutable à partir du zipapp. C’est relativement facile bien que cela nécessite un compilateur C. L’astuce repose sur le fait que les fichiers zip peuvent avoir des données arbitraires au début et les fichiers exe de Windows peuvent avoir des données arbitraires à la fin. Ainsi, en créant un lanceur approprié et en rajoutant le fichier .pyz à sa fin, vous obtenez un fichier unique qui exécute votre application.

Un lanceur approprié peut être aussi simple que ce qui suit :

#define Py_LIMITED_API 1
#include "Python.h"

#define WIN32_LEAN_AND_MEAN
#include <windows.h>

#ifdef WINDOWS
int WINAPI wWinMain(
    HINSTANCE hInstance,      /* handle to current instance */
    HINSTANCE hPrevInstance,  /* handle to previous instance */
    LPWSTR lpCmdLine,         /* pointer to command line */
    int nCmdShow              /* show state of window */
)
#else
int wmain()
#endif
{
    wchar_t **myargv = _alloca((__argc + 1) * sizeof(wchar_t*));
    myargv[0] = __wargv[0];
    memcpy(myargv + 1, __wargv, __argc * sizeof(wchar_t *));
    return Py_Main(__argc+1, myargv);
}

Si vous définissez le symbole du préprocesseur WINDOWS cela va générer un exécutable IUG, et sans lui, un exécutable console.

Pour compiler l’exécutable, vous pouvez soit simplement utiliser les outils standards en ligne de commande MSVC, soit profiter du fait que distutils sait comment compiler les sources Python :

>>> from distutils.ccompiler import new_compiler
>>> import distutils.sysconfig
>>> import sys
>>> import os
>>> from pathlib import Path

>>> def compile(src):
>>>     src = Path(src)
>>>     cc = new_compiler()
>>>     exe = src.stem
>>>     cc.add_include_dir(distutils.sysconfig.get_python_inc())
>>>     cc.add_library_dir(os.path.join(sys.base_exec_prefix, 'libs'))
>>>     # First the CLI executable
>>>     objs = cc.compile([str(src)])
>>>     cc.link_executable(objs, exe)
>>>     # Now the GUI executable
>>>     cc.define_macro('WINDOWS')
>>>     objs = cc.compile([str(src)])
>>>     cc.link_executable(objs, exe + 'w')

>>> if __name__ == "__main__":
>>>     compile("zastub.c")

Le lanceur résultant utilise le « Limited ABI » donc il fonctionnera sans changement avec n’importe quelle version de Python 3.x. Tout ce dont il a besoin est que Python (python3.dll) soit sur le PATH de l’utilisateur.

Pour une distribution entièrement autonome vous pouvez distribuer le lanceur avec votre application en fin de fichier, empaqueté avec la distribution embedded Python. Ceci fonctionnera sur n’importe quel ordinateur avec l’architecture appropriée (32 bits ou 64 bits).

28.4.6.2. Mises en garde

Il y a certaines limites à l’empaquetage de votre application dans un seul fichier. Dans la plupart des cas, si ce n’est tous, elles peuvent être traitées sans qu’il soit nécessaire d’apporter de modifications majeures à votre application.

Si votre application dépend d’un paquet qui inclut une extension C, ce paquet ne peut pas être exécuté à partir d’un fichier zip (c’est une limitation du système d’exploitation, car le code exécutable doit être présent dans le système de fichiers pour que le lanceur de l’OS puisse le charger). Dans ce cas, vous pouvez exclure cette dépendance du fichier zip et, soit demander à vos utilisateurs de l’installer, soit la fournir avec votre fichier zip et ajouter du code à votre fichier __main__.py pour inclure le répertoire contenant le module décompressé dans sys.path. Dans ce cas, vous devrez vous assurer d’envoyer les binaires appropriés pour votre ou vos architecture(s) cible(s) (et éventuellement choisir la bonne version à ajouter à sys.path au moment de l’exécution, basée sur la machine de l’utilisateur).

Si vous livrez un exécutable Windows comme décrit ci-dessus, vous devez vous assurer que vos utilisateurs ont python3.dll sur leur PATH (ce qui n’est pas le comportement par défaut de l’installateur) ou vous devez inclure la distribution intégrée dans votre application.

Le lanceur suggéré ci-dessus utilise l’API d’intégration Python. Cela signifie que dans votre application sys.executable sera votre application et pas un interpréteur Python classique. Votre code et ses dépendances doivent être préparés à cette possibilité. Par exemple, si votre application utilise le module multiprocessing, elle devra appeler multiprocessing.set_executable() pour que le module sache où trouver l’interpréteur Python standard.

28.4.7. Le format d’archive d’application Zip Python

Python est capable d’exécuter des fichiers zip qui contiennent un fichier __main__.py depuis la version 2.6. Pour être exécutée par Python, une archive d’application doit simplement être un fichier zip standard contenant un fichier __main__.py qui sera exécuté comme point d’entrée de l’application. Comme d’habitude pour tout script Python, le parent du script (dans ce cas le fichier zip) sera placé sur sys.path et ainsi d’autres modules pourront être importés depuis le fichier zip.

Le format de fichier zip permet d’ajouter des données arbitraires à un fichier zip. Le format de l’application zip utilise cette possibilité pour préfixer une ligne shebang POSIX standard dans le fichier (#!/path/to/interpreter).

Formellement, le format d’application zip de Python est donc :

Une ligne shebang facultative, contenant les caractères b'#! suivis d’un nom d’interpréteur, puis un caractère fin de ligne (b'\n'). Le nom de l’interpréteur peut être n’importe quoi acceptable pour le traitement shebang de l’OS, ou le lanceur Python sous Windows. L’interpréteur doit être encodé en UTF-8 sous Windows, et en sys.getfilesystemencoding() sur POSIX.

Des données zipfile standards, telles que générées par le module zipfile. Le contenu du fichier zip doit inclure un fichier appelé __main__.py (qui doit se trouver à la racine du fichier zip — c’est-à-dire qu’il ne peut se trouver dans un sous-répertoire). Les données du fichier zip peuvent être compressées ou non.

Si une archive d’application a une ligne shebang, elle peut avoir le bit exécutable activé sur les systèmes POSIX, pour lui permettre d’être exécutée directement.

Vous pouvez créer des archives d’applications sans utiliser les outils de ce module — le module existe pour faciliter les choses, mais les archives, créées par n’importe quel moyen tout en respectant le format ci-dessus, sont valides pour Python.

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Créé via Sphinx 2.3.1.

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29. Environnement d’exécution Python

Les modules décrits dans ce chapitre fournissent une large collection de services relatifs à l’interpréteur Python et son interaction avec son environnement. En voici un survol :

29.1. sys — Paramètres et fonctions propres à des systèmes

29.2. sysconfig — Provide access to Python’s configuration information

29.2.1. Configuration variables

29.2.2. Installation paths

29.2.3. Autres fonctions

29.2.4. Using sysconfig as a script

29.3. builtins — Objets natifs

29.4. __main__ — Point d’entrée des scripts

29.5. warnings — Contrôle des alertes

29.5.1. Catégories d’avertissement

29.5.2. Le filtre des avertissements

29.5.2.1. Default Warning Filters

29.5.3. Suppression temporaire des avertissements

29.5.4. Tester les avertissements

29.5.5. Updating Code For New Versions of Python

29.5.6. Fonctions disponibles

29.5.7. Gestionnaires de contexte disponibles

29.6. contextlib — Utilities for with-statement contexts

29.6.1. Utilitaires

29.6.2. Exemples et Recettes

29.6.2.1. Gérer un nombre variable de gestionnaires de contexte

29.6.2.2. Simplifying support for single optional context managers

29.6.2.3. Attraper des exceptions depuis les méthodes __enter__

29.6.2.4. Nettoyer dans une méthode __enter__

29.6.2.5. Remplacer un try-finally avec une option variable

29.6.2.6. Utiliser un gestionnaire de contexte en tant que décorateur de fonction

29.6.3. Gestionnaires de contexte à usage unique, réutilisables et réentrants

29.6.3.1. Gestionnaires de contexte réentrants

29.6.3.2. Gestionnaires de contexte réutilisables

29.7. abc — Classes de Base Abstraites

29.8. atexit — Gestionnaire de fin de programme

29.8.1. Exemple avec atexit

29.9. traceback — Print or retrieve a stack traceback

29.9.1. TracebackException Objects

29.9.2. StackSummary Objects

29.9.3. FrameSummary Objects

29.9.4. Traceback Examples

29.10. __future__ — Définitions des futurs

29.11. gc — Garbage Collector interface

29.12. inspect — Inspect live objects

29.12.1. Types and members

29.12.2. Retrieving source code

29.12.3. Introspecting callables with the Signature object

29.12.4. Classes et fonctions

29.12.5. The interpreter stack

29.12.6. Fetching attributes statically

29.12.7. Current State of Generators and Coroutines

29.12.8. Code Objects Bit Flags

29.12.9. Interface en ligne de commande

29.13. site — Site-specific configuration hook

29.13.1. Readline configuration

29.13.2. Module contents

29.14. fpectl — Floating point exception control

29.14.1. Exemple

29.14.2. Limitations and other considerations

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29.1. sys — Paramètres et fonctions propres à des systèmes

Ce module fournit un accès à certaines variables utilisées et maintenues par l’interpréteur, et à des fonctions interagissant fortement avec ce dernier. Ce module est toujours disponible.

sys.abiflags

Contient, sur les systèmes POSIX où Python a été compilé avec le script configure, les ABI flags tels que définis par la PEP 3149 [https://www.python.org/dev/peps/pep-3149].

Nouveau dans la version 3.2.

sys.argv

La liste des arguments de la ligne de commande passés à un script Python. argv[0] est le nom du script (chemin complet, ou non, en fonction du système d’exploitation). Si la commande a été exécutée avec l’option -c de l’interpréteur, argv[0] vaut la chaîne '-c'. Si aucun nom de script n’a été donné à l’interpréteur Python, argv[0] sera une chaîne vide.

Pour boucler sur l’entrée standard, ou la liste des fichiers donnés sur la ligne de commande, utilisez le module fileinput.

sys.base_exec_prefix

Défini au démarrage de Python, avant que site.py ne soit évalué, à la même valeur que exec_prefix. Hors d’un environnement virtuel, les valeurs restent les mêmes ; si site.py détecte qu’un environnement virtuel est utilisé, les valeurs de prefix et exec_prefix sont modifiées pour pointer vers l’environnement virtuel, alors que base_prefix et base_exec_prefix pointent toujours à la racine de l’installation de Python (celui utilisé pour créer l’environnement virtuel).

Nouveau dans la version 3.3.

sys.base_prefix

Défini au démarrage de Python, avant que site.py ne soit évalué, à la même valeur que prefix. Hors d’un environnement virtuel, les valeurs restent les mêmes ; si site.py détecte qu’un environnement virtuel est utilisé, les valeurs de prefix et exec_prefix sont modifiées pour pointer vers l’environnement virtuel, alors que base_prefix et base_exec_prefix pointent toujours à la racine de l’installation de Python (celui utilisé pour créer l’environnement virtuel).

Nouveau dans la version 3.3.

sys.byteorder

Un indicateur de l’ordre natif des octets. Vaudra 'big' sur les plateformes gros-boutistes (octet le plus significatif en premier), et 'little' sur les plateformes petit-boutiste (octet le moins significatif en premier).

sys.builtin_module_names

Un tuple de chaînes de caractères donnant les noms de tous les modules compilés dans l’interpréteur Python. (Cette information n’est pas disponible autrement — `modules.keys() liste seulement les modules importés.)

sys.call_tracing(func, args)

Appelle func(*args), avec le traçage activé. L’état du traçage est sauvegardé et restauré après l’appel. Ceci est destiné à être appelé depuis un débogueur à partir d’un point de contrôle, pour déboguer récursivement un autre code.

sys.copyright

Une chaîne contenant le copyright relatif à l’interpréteur Python.

sys._clear_type_cache()

Vide le cache interne de types. Le cache de types est utilisé pour accélérer les recherches d’attributs et de méthodes. N’utilisez cette fonction que pour libérer des références inutiles durant le débogage de fuite de référence.

Cette fonction ne devrait être utilisée que pour un usage interne et spécialisé.

sys._current_frames()

Renvoie un dictionnaire faisant correspondre chaque identifiant de fil d’exécution à la stack frame actuellement active pour ces fils d’exécution au moment où la fonction est appelée. Notez que les fonctions du module traceback peuvent construire une call stack à partir d’une telle frame.

N’ayant pas besoin de la coopération des fils d’exécution bloqués, cette fonction est très utile pour déboguer un deadlock. Aussi, les call stack de ces fils d’exécution ne changeront pas tant qu’ils seront bloqués. La frame renvoyée pour un fil d’exécution non bloqué peut ne plus être liée à l’activité courante du fil d’exécution au moment où le code appelant examine la frame.

Cette fonction ne devrait être utilisée que pour un usage interne et spécialisé.

sys._debugmallocstats()

Affiche des informations bas-niveau sur la sortie d’erreur à propos de l’état de l’allocateur de mémoire de CPython.

Si Python est configuré avec l’option –with-pydebug, il effectuera aussi quelques coûteuses vérifications de cohérence interne.

Nouveau dans la version 3.3.

CPython implementation detail: Cette fonction est spécifique à CPython. Le format de sa sortie n’est pas définit ici et pourrait changer.

sys.dllhandle

Nombre entier spécifiant le descripteur de la DLL Python. Disponibilité : Windows.

sys.displayhook(value)

Si value n’est pas None, cette fonction écrit repr(value) sur sys.stdout, et sauvegarde value dans builtins._. Si repr(value) ne peut pas être encodé avec sys.stdout.encoding en utilisant le gestionnaire d’erreur sys.stdout.errors (qui est probablement 'strict'), elle sera encodée avec sys.stdout.encoding en utilisant le gestionnaire d’erreur 'backslashreplace'.

sys.displayhook est appelé avec le résultat de l’évaluation d’une expression entrée dans une session Python interactive. L’affichage de ces valeurs peut être personnalisé en assignant une autre fonction d’un argument à sys.displayhook.

Pseudo-code :

def displayhook(value):
    if value is None:
        return
    # Set '_' to None to avoid recursion
    builtins._ = None
    text = repr(value)
    try:
        sys.stdout.write(text)
    except UnicodeEncodeError:
        bytes = text.encode(sys.stdout.encoding, 'backslashreplace')
        if hasattr(sys.stdout, 'buffer'):
            sys.stdout.buffer.write(bytes)
        else:
            text = bytes.decode(sys.stdout.encoding, 'strict')
            sys.stdout.write(text)
    sys.stdout.write("\n")
    builtins._ = value

Modifié dans la version 3.2: Utiliser le gestionnaire d’erreur 'backslashreplace' en cas d”UnicodeEncodeError.

sys.dont_write_bytecode

Si vrai, Python n’essaiera pas d’écrire de fichiers .pyc à l’importation de modules source. Cette valeur est initialement définie à True ou False en fonction de l’option de la ligne de commande -B et de la variable d’environnement PYTHONDONDONTWRITEBYTECODE, mais vous pouvez aussi la modifier vous-même pour contrôler la génération des fichiers de bytecode.

sys.excepthook(type, value, traceback)

Cette fonction affiche la traceback et l’exception donnée sur sys.stderr.

Lorsqu’une exception est levée et n’est pas attrapée, l’interpréteur appelle sys.excepthook avec trois arguments, la classe de l’exception, l’instance de l’exception, et un objet traceback. Dans une session interactive, cela se produit juste avant que le que l’invite soit rendue. Dans un programme Python, cela se produit juste avant que le programme quitte. La gestion de ces exceptions peut être personnalisé en affectant une autre fonction de trois arguments à sys.excepthook.

sys.__displayhook__

sys.__excepthook__

Ces objets contiennent les valeurs originales de displayhook et excepthook au début du programme. Elles sont sauvegardées de façon à ce que displayhook et excepthook puisse être restaurées au cas où elles seraient remplacées par des objets cassés.

sys.exc_info()

Cette fonction renvoie un tuple de trois valeurs qui donnent des informations sur l’exception actuellement traitée. L’information renvoyée est spécifique à la fois au fil d’exécution courant et à la stack frame courante. Si la stack frame actuelle ne traite pas d’exception, l’information est extraite de la stack frame parente, puis celle appelante, et ainsi de suite jusqu’à trouver une stack frame traitant une exception. Ici, « traiter une exception » signifie « exécute une clause except ». Pour chaque stack frame, seule l’information à propos d’une exception actuellement traitée est accessible.

Si aucune exception n’est actuellement traitée de toute la pile, un tuple contenant trois None sera renvoyé. Autrement, les valeurs renvoyées sont (type, value, traceback). Respectivement type reçoit le type de l’exception traitée (une classe fille de BaseException), value reçoit l’instance de l’exception (une instance du type de l’exception), et traceback reçoit un objet traceback (voir le Manuel de Référence) qui encapsule la pile d’appels au point où l’exception s’est produite à l’origine.

sys.exec_prefix

Une chaîne donnant le préfixe de dossier spécifique au site où les fichiers dépendant de la plateforme sont installés. Par défaut, c’est '/usr/local'. C’est configurable à la compilation avec l’option --exec-prefix du script configure. Tous les fichiers de configurations (tel que pyconfig,h) sont installés dans le dossier exec_prefix/lib/pythonX.Y/config, et les modules sous forme de bibliothèques partagées sont installés dans exec_prefix/lib/pythonX.Y/lib-dynload, où X.Y est le numéro de version de Python, par exemple 3.2.

Note

Si un environment virtuel est actif, cette valeur sera modifiée par site.py pour pointer vers l’environnement virtuel. La valeur d’origine sera toujours disponible via base_exec_prefix.

sys.executable

Une chaîne donnant le chemin absolu vers l’interpréteur Python, un fichier binaire exécutable, sur les système sur lesquels ça à du sens. Si Python n’est pas capable de récupérer le chemin réel de son exécutable, sys.executable sera une chaîne vide ou None.

sys.exit([arg])

Quitte Python. C’est implémente en levant l’exception SystemExit, afin que toutes les actions de nettoyage spécifiées par des clauses finally des instructions try soient correctement exécutées. Il est aussi possible d’intercepter la tentative de sortie à un niveau au dessus.

L’argument optionnel arg peut être un nombre entier donnant l’état de sortie (zéro par défaut), ou un autre type d’objet. Pour les shells (et autres), si c’est un entier, zéro signifie « terminé avec succès », et toutes les autres valeurs signifient « terminé anormalement ». La plupart des systèmes imposent qu’il se situe dans la plage 0–127, et leur comportement n’est pas défini pour les autres cas. Certains systèmes peu communs ont pour convention d’assigner un sens particulier à des valeur spécifiques. Les programmes Unix utilisent généralement 2 pour les erreurs de syntaxe dans les arguments de la ligne de commande, et 1 pour toutes les autres erreurs. Si un autre type est passé, None est équivalent à zéro, et tout autre objet est écrit sur stderr et donne un code de sortie 1. Typiquement, sys.exit("some error message") est un moyen rapide de quitter un programme en cas d’erreur.

Puisque la fonction exit() ne fait « que » lever une exception, elle ne fera quitter le processus que si elle est appelée depuis le fil d’exécution principal, et que l’exception n’est pas interceptée.

Modifié dans la version 3.6: Si une erreur survient lors du nettoyage après que l’interpréteur Python ai intercepté un SystemExit (typiquement une erreur en vidant les tampons des sorties standard), le code de sortie est changé à 120.

sys.flags

La struct sequence flags expose l’état des options de ligne de commande. Ces attributs sont en lecture seule.

attribut

option

debug

-d

inspect

-i

interactive

-i

isolated

-I

optimize

-O or -OO

dont_write_bytecode

-B

no_user_site

-s

no_site

-S

ignore_environment

-E

verbose

-v

bytes_warning

-b

quiet

-q

hash_randomization

-R

Modifié dans la version 3.2: Ajout de l’attribut quiet pour la nouvelle option -q.

Nouveau dans la version 3.2.3: L’attribut hash_randomization.

Modifié dans la version 3.3: Suppression de l’attribut obsolète division_warning.

Modifié dans la version 3.4: Added isolated attribute for -I isolated flag.

sys.float_info

Un struct sequence contenant des informations à propos du type float. Il contient des informations de bas niveau à propos de la précision et de la représentation interne. Les valeurs correspondent aux différentes constantes à propos des nombres à virgule flottantes définies dans le fichier d’entête float.h. Voir la section 5.2.4.2.2 de 1999 ISO/IEC C standard [C99], Characteristics of floating types, pour plus de détails.

attribut

macro float.h

explication

epsilon

DBL_EPSILON

différence entre 1 et la plus petite valeur plus grande que 1 représentable en float

dig

DBL_DIG

nombre maximum de décimales pouvant être représentées fidèlement dans un float (voir ci-dessous)

mant_dig

DBL_MANT_DIG

précision : nombre de base-radix chiffres dans la mantisse du float

max

DBL_MAX

plus grand float fini représentable

max_exp

DBL_MAX_EXP

plus grand nombre entier e tel que radix**(e-1) soit représentable sous forme de float finit

max_10_exp

DBL_MAX_10_EXP

plus grand nombre entier e tel que 10**e est dans l’intervalle des nombre flottants finis

min

DBL_MIN

plus petit nombre à virgule flottante positif normalisé

min_exp

DBL_MIN_EXP

plus petit entier e tel que radix**(e-1) est un float normalisé

min_10_exp

DBL_MIN_10_EXP

plus petit nombre entier e tel que 10**e est un nombre à virgule flottante normalisé

radix

FLT_RADIX

base de la représentation de l’exposant

rounds

FLT_ROUNDS

constante, nombre entier représentant le mode d’arrondi utilisé pour les opérations arithmétiques. Elle reflète la valeur de la macro système FLT_ROUNDS au moment du démarrage de l’interpréteur. Voir section 5.2.4.4.2.2 de la norme C99 pour une explication des valeurs possibles et de leurs significations.

L’attribut sys.float_info.dig nécessite plus d’explications : Si s est une chaîne représentant un nombre décimal avec au plus sys.float_info.dig chiffres significatifs, alors, convertir s en un nombre à virgule flottante puis à nouveau en chaîne redonnera la même valeur :

>>> import sys
>>> sys.float_info.dig
15
>>> s = '3.14159265358979'    # decimal string with 15 significant digits
>>> format(float(s), '.15g')  # convert to float and back -> same value
'3.14159265358979'

Cependant, pour les chaînes avec plus de sys.float_info.dig chiffres significatifs, ce n’est pas toujours vrai :

>>> s = '9876543211234567'    # 16 significant digits is too many!
>>> format(float(s), '.16g')  # conversion changes value
'9876543211234568'

sys.float_repr_style

Une chaîne indiquant comment la fonction repr() se comporte avec les nombres à virgule flottante. Si la chaîne a la valeur 'short', alors pour un float finit x, repr(x) essaye de donner une courte chaîne tel que float(repr(x)) == x. C’est le comportement typique à partir de Python 3.1. Autrement, float_repr_style a la valeur 'legacy' et repr(x) se comporte comme les versions antérieures à 3.1.

Nouveau dans la version 3.1.

sys.getallocatedblocks()

Renvoie le nombre de blocs mémoire actuellement alloués par l’interpréteur, peu importe leur taille. Cette fonction est principalement utile pour pister les fuites de mémoire. À cause des caches internes de l’interpréteur, le résultat peut varier d’un appel à l’autre. Appeler _clear_type_cache() et gc.collect() peut permettre d’obtenir des résultats plus prévisibles.

Si Python n’arrive pas a calculer raisonnablement cette information, getallocatedblocks() est autorisé à renvoyer 0 à la place.

Nouveau dans la version 3.4.

sys.getcheckinterval()

Renvoie le check interval de l’interpréteur, voir setcheckinterval().

Obsolète depuis la version 3.2: Utilisez plutôt getswitchinterval().

sys.getdefaultencoding()

Renvoie le nom du codage par défaut actuellement utilisé par l’implémentation Unicode pour coder les chaînes.

sys.getdlopenflags()

Renvoie la valeur actuelle des flags utilisés par les appels de dlopen(). Les noms symboliques valeurs peuvent être trouvées dans le module os. (Ce sont les constantes RTLD_xxx e.g. os.RTLD_LAZY). Disponibilité: Unix.

sys.getfilesystemencoding()

Donne le nom de l’encodage utilisé pour les conversions entre les noms de fichiers Unicode et les noms de fichiers en octets. Pour une compatibilité optimale, les noms de fichiers devraient toujours être représentés sous forme de chaînes de caractères, cependant les représenter sous forme d’objet bytes est aussi accepté. Les fonctions acceptant ou renvoyant des noms de fichiers devraient supporter les deux (str ou bytes), et convertir en interne dans la représentation du système.

Cet encodage est toujours compatible avec ASCII.

Les fonctions os.fsencode() et os.fsdecode() devraient être utilisées pour s’assurer qu’un encodage et un gestionnaire d’erreurs correct sont utilisés.

Sur Mac OS X, l’encodage est 'utf-8'.

Sur Unix, l’encodage est celui des paramètres régionaux.

Sur Windows, l’encodage peut être 'utf-8' ou 'mbcs', en fonction des paramètres de l’utilisateur.

Modifié dans la version 3.2: getfilesystemencoding() ne peut plus renvoyer None.

Modifié dans la version 3.6: Sur Windows, on est plus assurés d’obtenir 'mbcs'. Voir la PEP 529 [https://www.python.org/dev/peps/pep-0529] et _enablelegacywindowsfsencoding() pour plus d’informations.

sys.getfilesystemencodeerrors()

Donne le nom du mode de gestion d’erreur utilisé lors de la conversion des noms de fichiers entre Unicode et octets. Le nom de l’encodage est renvoyé par getfilesystemencoding().

Les fonctions os.fsencode() et os.fsdecode() devraient être utilisées pour s’assurer qu’un encodage et un gestionnaire d’erreurs correct sont utilisés.

Nouveau dans la version 3.6.

sys.getrefcount(object)

Donne le nombre de référence de l’objet object. Le nombre renvoyé est généralement d’une référence de plus qu’attendu, puisqu’il compte la référence (temporaire) de l’argument à getrefcount().

sys.getrecursionlimit()

Donne la limite actuelle de la limite de récursion, la profondeur maximum de la pile de l’interpréteur. Cette limite empêche Python de planter lors d’une récursion infinie à cause d’un débordement de la pile. Elle peut être modifiée par setrecursionlimit().

sys.getsizeof(object[, default])

Donne la taille d’un objet en octets. L’objet peut être de n’importe quel type. Le résultat sera correct pour tous les objets natifs, mais le résultat peut ne pas être toujours vrai pour les extensions, la valeur étant dépendante de l’implémentation.

Seule la mémoire directement attribuée à l’objet est prise en compte, pas la mémoire consommée par les objets vers lesquels il a des références.

S’il est fourni, default sera renvoyé si l’objet ne fournit aucun moyen de récupérer sa taille. Sinon, une exception TypeError sera levée.

getsizeof() appelle la méthode __sizeof__ de l’objet, et s’il est géré par lui, ajoute le surcoût du ramasse-miettes.

Voir la recursive sizeof recipe [https://code.activestate.com/recipes/577504] pour un exemple d’utilisation récursive de getsizeof() pour trouver la taille d’un contenant et de son contenu.

sys.getswitchinterval()

Renvoie la valeur du thread switch interval de l’interpréteur, voir setswitchinterval().

Nouveau dans la version 3.2.

sys._getframe([depth])

Renvoie une frame de la pile d’appels. Si le nombre entier optionnel depth est donné, la frame donnée sera de depth appels depuis le haut de la pile. Si c’est plus profond que la hauteur de la pile, une exception ValueError est levée. La profondeur par défaut est zéro, donnant ainsi la frame du dessus de la pile.

CPython implementation detail: Cette fonction ne devrait être utilisée que pour une utilisation interne et spécifique. Il n’est pas garanti qu’elle existe dans toutes les implémentations de Python.

sys.getprofile()

Renvoie la fonction de profilage tel que défini par setprofile().

sys.gettrace()

Renvoie la fonction de traçage tel que définie par settrace().

CPython implementation detail: La fonction gettrace() ne sert que pour implémenter des débogueurs, des profilers, outils d’analyse de couverture, etc…. Son comportement dépend de l’implémentation et non du langage, elle n’est donc pas forcément disponible dans toutes les implémentations de Python.

sys.getwindowsversion()

Renvoie un tuple nommé décrivant la version de Windows en cours d’exécution. Les attributs nommés sont major, minor, build, platform, service_pack, service_pack_minor, service_pack_major, suite_mask, product_type et platform_version. service_pack contient une string, platform_version un tuple de trois valeurs, et tous les autres sont des nombres entiers. Ces attributs sont également accessibles par leur nom, donc sys.getwindowsversion()[0] est équivalent à sys.getwindowsversion().major. Pour des raisons de compatibilité avec les versions antérieures, seuls les 5 premiers éléments sont accessibles par leur indice.

platform sera 2 (VER_PLATFORM_WIN32_NT).

product_type peut être une des valeurs suivantes :

Constante

Signification

1 (VER_NT_WORKSTATION)

Le système une station de travail.

2 (VER_NT_DOMAIN_CONTROLLER)

Le système est un contrôleur de domaine.

3 (VER_NT_SERVER)

Le système est un serveur, mais pas un contrôleur de domaine.

Cette fonction enveloppe la fonction Win32 GetVersionEx(). Voir la documentation de Microsoft sur OSVERSIONINFOEX() pour plus d’informations sur ces champs.

platform_version donne précisément la version majeure, mineure, et numéro de compilation du système d’exploitation sous-jacent, plutôt que la version émulée pour ce processus. Il est destiné à être utilisé pour de la journalisation plutôt que pour la détection de fonctionnalités.

Disponibilité : Windows.

Modifié dans la version 3.2: Changé en un tuple nommé, et ajout de service_pack_minor, service_pack_major, suite_mask, et product_type.

Modifié dans la version 3.6: Ajout de platform_version

sys.get_asyncgen_hooks()

Renvoie un objet asyncgen_hooks, qui est semblable à un namedtuple de la forme (firstiter, finalizer), où firstiter et finalizer sont soit None ou des fonctions qui prennent un asynchronous generator iterator comme argument, et sont utilisées pour planifier la finalisation d’un générateur asynchrone par un event loop.

Nouveau dans la version 3.6: Voir la PEP 525 [https://www.python.org/dev/peps/pep-0525] pour plus d’informations.

Note

Cette fonction à été ajoutée à titre provisoire (voir la PEP 411 [https://www.python.org/dev/peps/pep-0411] pour plus d’informations.)

sys.get_coroutine_wrapper()

Renvoie None, ou un wrapper donné via set_coroutine_wrapper().

Nouveau dans la version 3.5: Voir la PEP 492 [https://www.python.org/dev/peps/pep-0492] pour plus d’informations.

Note

Cette fonction à été ajoutée à titre provisoire (Voir la PEP 411 [https://www.python.org/dev/peps/pep-0411] pour plus d’informations.) Utilisez la uniquement à des fins de débogage.

sys.hash_info

Une struct sequence donnant les paramètres de l’implémentation de la fonction de hachage de nombres. Pour plus d’informations sur le hachage des types numériques, consultez Hachage des types numériques.

attribut

explication

width

Nombre de bits des valeurs de hash

modulus

contient le premier P utilisé dans le modulo pour les hash numériques

inf

valeur du hash pour un infini positif

nan

valeur du hash pour un nan

imag

multiplicateur utilisé pour la partie imaginaire d’un nombre complexe

algorithm

nom de l’algorithme pour le hachage des str, bytes, et memoryview

hash_bits

taille de la sortie interne de l’algorithme de hachage

seed_bits

taille de la seed key utilisée par l’algorithme de hachage

Nouveau dans la version 3.2.

Modifié dans la version 3.4: Ajout de algorithm, hash_bits et seed_bits

sys.hexversion

Le numéro de version codé sous forme d’un seul nombre entier. Ce numéro augmente avec chaque version, y compris pour les versions hors production. Par exemple, pour vérifier que l’interpréteur Python est au moins la version 1.5, utilisez :

if sys.hexversion >= 0x010502F0:
    # use some advanced feature
    ...
else:
    # use an alternative implementation or warn the user
    ...

Cet attribut s’appelle hexversion dans le sens où il ne semble avoir du sens que s’il est regardé après avoir été passé à la fonction native hex(). La struct sequence sys.version_info représente la même information d’une manière plus humaine.

Consultez Version des API et ABI pour plus d’informations sur hexversion.

sys.implementation

Un objet contenant des informations sur l’implémentation de la version actuelle de l’interpréteur Python. Les attributs suivants existent obligatoirement sur toutes les implémentations Python.

name est l’identifiant de l’implémentation, e.g. 'cpython'. Cette chaîne est définie par l’implémentation de Python, mais sera toujours en minuscule.

version est un named tuple, du même format que sys.version_info. Il représente la version de l”implementation de Python. C’est une information différente de la version du langage auquel l’interpréteur actuel se conforme (donnée par sys.version_info). Par exemple, pour PyPy 1.8 sys.implementation.version peut valoir sys.version_info(1, 8, 0, 'final', 0), alors que sys.version_info peut valoir sys.version_info(2, 7, 2, 'final', 0). Pour CPython ces deux valeurs sont identiques puisque c’est l’implémentation de référence.

hexversion est la version de l’implémentation sous forme hexadécimale, comme sys.hexversion.

cache_tag est la balise utilisée par le mécanisme d’importation dans les noms de fichiers des modules mis en cache. Par convention, il devrait se composer du nom et de la version de l’implémentation, comme `cpython-33'`.  Cependant, une implémentation Python peut utiliser une autre valeur si nécessaire.  ``cache_tag à None signifie que la mise en cache des modules doit être désactivée.

sys.implementation peut contenir d’autres attributs spécifiques à l’implémentation de Python. Ces attributs spécifiques doivent commencer par un underscore, et ne sont pas documentés ici. Indépendamment de son contenu, sys.implementation ne change jamais durant l’exécution de l’interpréteur, ni entre les versions d’une même implémentation. (Il peut cependant changer entre les versions du langage Python.) Voir la PEP 421 [https://www.python.org/dev/peps/pep-0421] pour plus d’informations.

Nouveau dans la version 3.3.

sys.int_info

Un struct sequence qui contient des informations sur la représentation interne des entiers de Python. Les attributs sont en lecture seule.

Attribut

Explication

bits_per_digit

nombre de bits utilisés pour chaque chiffre. Les entiers Python sont stockés en interne en base 2**int_info.bits_per_digit

sizeof_digit

taille en octets du type C utilisé pour représenter un chiffre

Nouveau dans la version 3.1.

sys.__interactivehook__

Lorsque cet attribut existe, sa valeur est automatiquement appelée (sans argument) par l’interpréteur lors de son démarrage en mode interactif. L’appel se fait après que le fichier PYTHONSTARTUP soit lu, afin que vous puissiez y configurer votre fonction. Configuré par le module site.

Nouveau dans la version 3.4.

sys.intern(string)

Ajoute string dans le tableau des chaînes « internées » et renvoie la chaîne internée – qui peut être string elle-même ou une copie. Interner une chaîne de caractères permet de gagner un peu de performance lors de l’accès aux dictionnaires – si les clés du dictionnaire et la clé recherchée sont internées, les comparaisons de clés (après le hachage) pourront se faire en comparant les pointeurs plutôt que caractère par caractère. Normalement, les noms utilisés dans les programmes Python sont automatiquement internés, et les dictionnaires utilisés pour stocker les attributs de modules, de classes, ou d’instances ont aussi leurs clés internées.

Les chaînes internées ne sont pas immortelles ; vous devez garder une référence à la valeur renvoyée par intern() pour en bénéficier.

sys.is_finalizing()

Donne True si l’interpréteur Python est en train de s’arrêter, et False dans le cas contraire.

Nouveau dans la version 3.5.

sys.last_type

sys.last_value

sys.last_traceback

Ces trois variables ne sont pas toujours définies. Elles sont définies lorsqu’une exception n’est pas gérée et que l’interpréteur affiche un message d’erreur et une stacktrace. Elles sont là pour permettre à un utilisateur, en mode interactif, d’importer un module de débogage et de faire son débogage post-mortem sans avoir à ré-exécuter la commande qui a causé l’erreur. (L’utilisation typique pour entrer dans le débogueur post-mortem est import pdb; pdb.pm(), voir pdb pour plus d’informations.).

La signification de ces variables est la même que celle des valeurs renvoyées par exc_info() ci-dessus.

sys.maxsize

Un entier donnant à la valeur maximale qu’une variable de type Py_ssize_t peut prendre. C’est typiquement 2**31 - 1 sur une plateforme 32 bits et 2**63 - 1` sur une plateforme 64 bits.

sys.maxunicode

Un entier donnant la valeur du plus grand point de code Unicode, c’est-à-dire 1114111 (`0x10FFFF en hexadécimal).

Modifié dans la version 3.3: Avant la PEP 393 [https://www.python.org/dev/peps/pep-0393], sys.maxunicode valait soit 0xFFFF soit 0x10FFFF, en fonction l’option de configuration qui spécifiait si les caractères Unicode étaient stockés en UCS-2 ou UCS-4.

sys.meta_path

Une liste d’objets meta path finder qui ont leur méthode find_spec() appelée pour voir si un des objets peut trouver le module à importer. La méthode find_spec() est appelée avec au moins le nom absolu du module importé. Si le module à importer est contenu dans un paquet, l’attribut __path__ du paquet parent est donné en deuxième argument. La méthode renvoie un module spec, ou None si le module ne peut être trouvé.

Voir aussi

importlib.abc.MetaPathFinder

La classe de base abstraite définissant l’interface des objets finder de meta_path.

importlib.machinery.ModuleSpec

La classe concrète dont find_spec() devrait renvoyer des instances.

Modifié dans la version 3.4: Les Module specs ont été introduits en Python 3.4, par la PEP 451 [https://www.python.org/dev/peps/pep-0451]. Les versions antérieures de Python cherchaient une méthode appelée find_module(). Celle-ci est toujours appelée en dernier recours, dans le cas où une meta_path n’a pas de méthode find_spec().

sys.modules

Un dictionnaire faisant correspondre des noms de modules à des modules déjà chargés. Il peut être manipulé, entre autre, pour forcer un module à être rechargé. Cependant, le remplacer ne fonctionnera pas forcément comme prévu et en supprimer des éléments essentiels peut planter Python.

sys.path

Une liste de chaînes de caractères spécifiant les chemins de recherche des modules, initialisée à partir de la variable d’environnement PYTHONPATH et d’une valeur par défaut dépendante de l’installation.

Puisqu’il est initialisé au démarrage du programme, le premier élément de cette liste, path[0], est le dossier contenant le script qui a été utilisé pour invoquer l’interpréteur Python. Si le dossier du script n’est pas disponible (typiquement, si l’interpréteur est invoqué interactivement ou si le script est lu à partir d’une entrée standard), path[0] sera une chaîne vide, qui indiquera à Python de chercher des modules dans le dossier actuel. Notez que le dossier du script est inséré avant les dossiers de PYTHONPATH.

Un programme est libre de modifier cette liste pour ses propres besoins. Seuls des str ou des bytes ne devraient être ajoutés à sys.path, tous les autres types de données étant ignorés durant l’importation.

Voir aussi

Le module site décrit comment utiliser les fichiers .pth pour étendre sys.path.

sys.path_hooks

Une liste d’appelables d’un argument, path, pour essayer de créer un finder pour ce chemin. Si un finder peut être créé, il doit être renvoyé par l’appelable, sinon une ImportError doit être levée.

Précisé à l’origine dans la PEP 302 [https://www.python.org/dev/peps/pep-0302].

sys.path_importer_cache

Un dictionnaire faisant office de cache pour les objets finder. Les clés sont les chemins qui ont été passés à sys.path_hooks et les valeurs sont les finders trouvés. Si un chemin est valide selon le système de fichiers mais qu’aucun finder n’est trouvé dans sys.path_hooks, None est stocké.

Précisé à l’origine dans la PEP 302 [https://www.python.org/dev/peps/pep-0302].

Modifié dans la version 3.3: None est stocké à la place de imp.NullImporter si aucun localisateur n’est trouvé.

sys.platform

Cette chaîne contient un identificateur de plateforme qui peut être typiquement utilisé pour ajouter des composants spécifiques à sys.path.

Pour les systèmes Unix, sauf sur Linux, c’est le nom de l’OS en minuscules comme renvoyé par uname -s suivi de la première partie de la version comme renvoyée par uname -r, e.g. 'sunos5' ou 'freebsd8', au moment où Python a été compilé. A moins que vous ne souhaitiez tester pour une version spécifique du système, vous pouvez faire comme suit :

if sys.platform.startswith('freebsd'):
    # FreeBSD-specific code here...
elif sys.platform.startswith('linux'):
    # Linux-specific code here...

Pour les autres systèmes, les valeurs sont :

Le système une station de travail.

Valeur pour plateforme

Linux

'linux'

Windows

'win32'

Windows/Cygwin

'cygwin'

Mac OS X

'darwin'

Modifié dans la version 3.3: Sur Linux, sys.platform ne contient plus la version majeure, c’est toujours 'linux', au lieu de 'linux2' ou 'linux3'. Comme les anciennes versions de Python incluent le numéro de version, il est recommandé de toujours utiliser startswith, tel qu’utilisé ci-dessus.

Voir aussi

os.name a une granularité plus grossière. os.uname() donne des informations sur la version dépendantes du système.

Le module platform fournit des vérifications détaillées pour l’identité du système.

sys.prefix

Une chaîne donnant le préfixe de répertoire spécifique au site dans lequel les fichiers Python indépendants de la plate-forme sont installés. Par défaut, c’est '/usr/local'. Ceci peut être défini à la compilation en passant l’argument --prefix au script configure. La collection principale des modules de la bibliothèque Python est installée dans le dossier prefix/lib/pythonX.Y et les entêtes indépendantes de la plateforme (toutes sauf pyconfig.h) sont stockées dans prefix/include/pythonX.Y, où X.Y est le numéro de version de Python, par exemple 3.2.

Note

Si a environnement virtuel est activé, cette valeur sera changée par site py pour pointer vers l’environnement virtuel. La valeur donnée au moment de la compilation de Python sera toujours disponible, dans base_prefix.

sys.ps1

sys.ps2

Chaînes spécifiant l’invite primaire et secondaire de l’interpréteur. Celles-ci ne sont définies que si l’interpréteur est en mode interactif. Dans ce cas, leurs valeurs initiales sont '>>>' et '...'. Si un objet qui n’est pas une chaîne est assigné à l’une ou l’autre variable, sa méthode str() sera appelée à chaque fois que l’interpréteur se prépare à lire une nouvelle commande interactive, c’est donc utilisable pour implémenter une invite dynamique.

sys.setcheckinterval(interval)

Défini l“« intervalle de vérification » de l’interpréteur. Ce nombre entier détermine la fréquence à laquelle l’interpréteur effectue des tâches périodiques tels que la commutation de fil d’exécution et la gestion de signaux. La valeur par défaut est 100, ce qui signifie que le contrôle est effectué toutes les 100 instructions virtuelles Python. L’augmenter peut améliorer les performances des programmes utilisant des fils d’exécution. Le paramétrer à une valeur inférieure ou égale à zéro permet d’effectuer ces tâches à chaque instruction virtuelle, maximisant ainsi la réactivité mais aussi son surcoût.

Obsolète depuis la version 3.2: Cette fonction n’a plus aucun effet : La logique interne de commutation de fils d’exécution et de gestion des tâches asynchrones ayant été réécrite. Utilisez setswitchinterval() à la place.

sys.setdlopenflags(n)

Définit les options utilisées par l’interpréteur lors des appels à dlopen(), typiquement utilisé par l’interpréteur pour charger des modules d’extension. Permet entre autre de résoudre tardivement les symboles lors des importations de modules (si appelé sys.setdlopenflags(0)). Pour partager les symboles entre modules, appelez sys.setdlopenflags(os.RTLD_GLOBAL). Les noms pour les valeurs de ces options peuvent être trouvés dans le module os (ce sont les constantes RTLD_xxx, comme os.RTLD_LAZY).

Disponibilité : Unix.

sys.setprofile(profilefunc)

Définit la fonction de profilage du système, qui vous permet d’implémenter un profileur de code source Python en Python. Voir le chapitre The Python Profilers pour plus d’informations sur le profileur Python. La fonction de profilage du système est appelée de la même façon que la fonction trace du (voir settrace()), mais elle est appelée pour des évènements différents, par exemple elle n’est pas appelée à chaque ligne de code exécutée (seulement sur appel et retours, mais l’événement pour les retours est appelé même en cas d’exception). Cette fonction est locale au fil d’exécution, et il n’existe aucun moyen, du point de vue du profileur, de prendre conscience des changements de contextes entre fils d’exécution, ça n’a donc aucun sens d’utiliser cette fonction dans un contexte multithread. Sa valeur de retour n’est pas utilisée, elle peut simplement renvoyer None.

Les fonctions de traçage doivent avoir trois arguments : frame, event, et arg. frame est la stack frame actuelle. event est une chaîne de caractères pouvant valoir : 'call', 'return', 'c_call', 'c_return' ou 'c_exception'. arg dépend du type de l’évènement.

Les événements ont la signification suivante :

'call'

Une fonction est appelée (ou Python entre dans un autre bloc de code). La fonction de traçage est appelée, arg est None.

'return'

La fonction (ou un autre type de bloc) est sur le point de se terminer. La fonction de traçage est appelée, arg est la valeur qui sera renvoyée, ou None si l’événement est causé par la levée d’une exception.

'c_call'

Une fonction C est sur le point d’être appelée. C’est soit une fonction d’extension ou une fonction native. arg représente la fonction C.

'c_return'

Une fonction C a renvoyé une valeur. arg représente la fonction C.

'c_exception'

Une fonction C a levé une exception. arg représente la fonction C.

sys.setrecursionlimit(limit)

Définit la profondeur maximale de la pile de l’interpréteur Python à limit. Cette limite empêche une récursion infinie de provoquer un débordement de la pile C et ainsi un crash de Python.

La limite haute dépend de la plate-forme. Un utilisateur pourrait avoir besoin de remonter la limite, lorsque son programme nécessite une récursion profonde, si sa plate-forme le permet. Cela doit être fait avec précaution, car une limite trop élevée peut conduire à un crash.

Si la nouvelle limite est plus basse que la profondeur actuelle, une RecursionError est levée.

Modifié dans la version 3.5.1: Une RecursionError est maintenant levée si la nouvelle limite est plus basse que la profondeur de récursion actuelle.

sys.setswitchinterval(interval)

Configure l’intervalle de bascule des fils d’exécution de l’interpréteur (en secondes). Ce nombre à virgule flottante détermine la durée idéale allouée aux fils d’exécution en cour d’exécution (durée appelée timeslices). Notez que la durée observée peut être plus grande, typiquement si des fonctions ou méthodes prenant beaucoup de temps sont utilisées. Aussi, le choix du fil d’exécution prenant la main à la fin de l’intervalle revient au système d’exploitation. L’interpréteur n’a pas son propre ordonnanceur.

Nouveau dans la version 3.2.

sys.settrace(tracefunc)

Définit la fonction de traçage du système, qui vous permet d’implémenter un débogueur de code source Python en Python. Cette fonction est locale au fil d’exécution courant. Pour qu’un débogueur puisse gérer plusieurs fils d’exécution, il doit enregistrer sa fonction en appelant settrace() pour chaque fil d’exécution qu’il souhaite surveiller.

Les fonctions de traçage doivent avoir trois arguments: frame, event, et arg. frame est la stack frame actuelle. event est une chaîne de caractères pouvant valoir : 'call', 'line', 'return', 'exception'. arg dépend du type de l’évènement.

La fonction de traçage est appelée (avec event à 'call') à chaque fois que l’interpréteur entre dans un nouveau scope. Elle doit renvoyer une référence à une fonction de traçage locale à utiliser pour ce scope, ou None si le Scope ne doit pas être tracé.

La fonction de traçage doit renvoyer une référence à elle-même (ou à une autre fonction de traçage pour un traçage ultérieur dans cette portée), ou None pour désactiver le traçage dans cette portée.

Les événements ont la signification suivante :

'call'

Une fonction est appelée (un un bloc de code). La fonction de traçage globale est appelée, arg est None, la valeur renvoyée donne la fonction de traçage locale.

'line'

L’interpréteur est sur le point d’exécuter une nouvelle ligne de code ou de ré-exécuter la condition d’une boucle. La fonction de traçage locale est appelée, arg vaut None, et la valeur de retour donne la nouvelle fonction de traçage locale. Voir Objects/lnotab_notes.txt pour une explication détaillée de ce mécanisme.

'return'

La fonction (ou un autre type de bloc) est sur le point de se terminer. La fonction de traçage locale est appelée, arg est la valeur qui sera renvoyée, ou None si l’événement est causé par la levée d’une exception. La valeur renvoyée par la fonction de traçage est ignorée.

'exception'

Une exception est survenue. La fonction de traçage locale est appelée, arg est le tuple (exception, valeur, traceback), la valeur renvoyée spécifie la nouvelle fonction de traçage locale.

Remarquez que, comme une exception se propage au travers de toute chaîne d’appelants, un événement 'exception' est généré à chaque niveau.

Pour plus d’informations sur les objets code et objets représentant une frame de la pile, consultez Hiérarchie des types standards.

CPython implementation detail: La fonction settrace() est destinée uniquement à l’implémentation de débogueurs, de profileurs, d’outils d’analyse de couverture et d’autres outils similaires. Son comportement fait partie de l’implémentation, plutôt que de la définition du langage, et peut donc ne pas être disponible dans toutes les implémentations de Python.

sys.set_asyncgen_hooks(firstiter, finalizer)

Accepte deux arguments optionnels nommés, qui sont appelables qui acceptent un asynchronous generator iterator comme argument. L’appelable firsttiter sera appelé lorsqu’un générateur asynchrone sera itéré pour la première fois, et l’appelable finalizer sera appelé lorsqu’un générateur asynchrone est sur le point d’être détruit.

Nouveau dans la version 3.6: Voir la PEP 525 [https://www.python.org/dev/peps/pep-0525] pour plus de détails. Pour un exemple de finalizer, voir l’implémentation de asyncio.Loop.shutdown_asyncgens dans Lib/asyncio/base_events.py [https://github.com/python/cpython/tree/3.6/Lib/asyncio/base_events.py]

Note

Cette fonction à été ajoutée à titre provisoire (voir la PEP 411 [https://www.python.org/dev/peps/pep-0411] pour plus d’informations.)

sys.set_coroutine_wrapper(wrapper)

Permet d’intercepter la création de coroutine (uniquement celles créés via async def, les générateurs décorés par types.coroutine() ou asyncio.coroutine() ne seront pas interceptés).

L’argument wrapper doit être soit :

un appelable qui accepte un argument (une coroutine);

None, pour réinitialiser le wrapper.

S’il est appelé deux fois, le nouveau wrapper remplace le précédent.

L’appelable wrapper ne peut pas définir de nouvelles coroutines, ni directement, ni indirectement :

def wrapper(coro):
    async def wrap(coro):
        return await coro
    return wrap(coro)
sys.set_coroutine_wrapper(wrapper)

async def foo():
    pass

# The following line will fail with a RuntimeError, because
# ``wrapper`` creates a ``wrap(coro)`` coroutine:
foo()

Voir aussi get_coroutine_wrapper().

Nouveau dans la version 3.5: Voir la PEP 492 [https://www.python.org/dev/peps/pep-0492] pour plus d’informations.

Note

Cette fonction à été ajoutée à titre provisoire (Voir la PEP 411 [https://www.python.org/dev/peps/pep-0411] pour plus d’informations.) Utilisez la uniquement à des fins de débogage.

sys._enablelegacywindowsfsencoding()

Change l’encodage et le mode de gestion d’erreur par défaut du système de fichiers à mbcs et replace respectivement, par cohérence avec les versions de Python antérieures à la 3.6.

Équivaut à définir la variable d’environnement PYTHONLEGACYWINDOWSFSENCODING avant de lancer Python.

Disponibilité : Windows

Nouveau dans la version 3.6: Voir la PEP 529 [https://www.python.org/dev/peps/pep-0529] pour plus d’informations.

sys.stdin

sys.stdout

sys.stderr

objets fichiers utilisés par l’interpréteur pour l’entrée standard, la sortie standard et la sortie d’erreurs :

stdin est utilisé pour toutes les entrées interactives (y compris les appels à input())

stdout est utilisé pour la sortie de print(), des expression et pour les invites de input() ;

Les invites de l’interpréteur et ses messages d’erreur sont écrits sur stderr.

Ces flux sont de classiques fichiers texte comme ceux renvoyés par la fonction open(). Leurs paramètres sont choisis comme suit :

L’encodage des caractères dépend de la plate-forme. Sous Windows, si le flux est interactif (c’est-à-dire si sa méthode isatty() donne True), l’encodage de la console est utilisée, sinon un encodage Windows. Sous d’autres plateformes, l’encodage local est utilisé (voir locale.getpreferredencoding()).

Sous toutes les plates-formes cependant, vous pouvez remplacer cette valeur en définissant la variable d’environnement PYTHONIOENCODING avant de démarrer Python.

En mode interactif, les entrées et sorties standards passent par un tampon d’une ligne. Autrement, elles passent par blocs dans un tampon, comme les fichiers textes classiques. Vous pouvez. Vous pouvez remplacer cette valeur avec l’option -u en ligne de commande.

Note

Pour écrire ou lire des données binaires depuis ou vers les flux standards, utilisez l’objet sous-jacent buffer. Par exemple, pour écrire des octets sur stdout, utilisez sys.stdout.buffer.write(b'abc').

Cependant, si vous écrivez une bibliothèque (ou ne contrôlez pas dans quel contexte son code sera exécuté), sachez que les flux standards peuvent être remplacés par des objets de type fichier tel un io.StringIO qui n’ont pas l’attribut buffer.

sys.__stdin__

sys.__stdout__

sys.__stderr__

Ces objets contiennent les valeurs d’origine de stdin, stderr et stdout tel que présentes au début du programme. Ils sont utilisés pendant la finalisation, et peuvent être utiles pour écrire dans le vrai flux standard, peu importe si l’objet sys.std* a été redirigé.

Ils peuvent également être utilisés pour restaurer les entrées / sorties d’origine, au cas où ils auraient été écrasés par des objets cassé, cependant la bonne façon de faire serait de sauvegarder explicitement les flux avant de les remplacer et ainsi pouvoir les restaurer.

Note

Dans certaines cas, stdin, stdout et stderr ainsi que les valeurs initiales __stdin__, __stdout__ et __stderr__ peuvent être None. C’est typiquement le cas pour les applications graphiques sur Windows qui ne sont pas connectées à une console, ou les applications Python démarrées avec pythonw.

sys.thread_info

Une struct sequence contenant des informations sur l’implémentation des fils d’exécution.

Attribut

Explication

name

Nom de l’implémentation des fils d’exécution :

'nt' : Fils d’exécution Windows

'pthread' : Fils d’exécution POSIX

'solaris' : Fils d’exécution Solaris

lock

Nom de l’implémentation du système de verrou :

'semaphore' : Verrou utilisant une sémaphore

'mutex+cond' : Un verrou utilisant un mutex et une condition variable

None si cette information n’est pas connue

version

Nom et version de l’implémentation des fils d’exécution, c’est une chaîne, ou None si ces informations sont inconnues.

Nouveau dans la version 3.3.

sys.tracebacklimit

Lorsque cette variable contient un nombre entier, elle détermine la profondeur maximum de la pile d’appels affichée lorsqu’une exception non gérée se produit. La valeur par défaut est 1000, lorsque cette valeur est égale ou inférieure à 0, la pile d’appels n’est pas affichée, seul seuls le type et la valeur de l’exception sont le sont.

sys.version

Une chaîne contenant le numéro de version de l’interpréteur Python, ainsi que d’autres informations comme le numéro de compilation et le compilateur utilisé. Cette chaîne est affichée lorsque l’interpréteur est démarré en mode interactif. N’essayez pas d’en extraire des informations de version, utilisez plutôt version_info et les fonctions fournies par le module platform.

sys.api_version

La version de l’API C pour cet interpréteur. Les développeurs peuvent trouver cette information utile en déboguant des conflits de versions entre Python et des modules d’extension.

sys.version_info

Un tuple contenant les cinq composants du numéro de version : major, minor, micro, releaselevel et serial. Toutes les valeurs sauf releaselevel sont des nombres entiers. releaselevel peut valoir 'alpha', 'beta', 'candidate', ou 'final'. La valeur de version_info pour Python 2.0 est (2, 0, 0, 'final', 0). Ces attributs sont aussi accessibles par leur nom, ainsi sys.version_info[0] est équivalent à sys.version_info.major, et ainsi de suite.

Modifié dans la version 3.1: Ajout des attributs nommés.

sys.warnoptions

C’est une spécificité de l’implémentation de la gestion des avertissements. Ne modifiez pas cette valeur. Reportez-vous au module warnings pour plus d’informations sur le gestionnaire d’avertissements.

sys.winver

Le numéro de version utilisé pour construire les clefs de registre sous Windows. Elle est stockée en tant que string resource 1000 dans la DLL Python. Cette valeur équivaut typiquement aux trois premiers caractères de version. Elle est fournie par le module sys à titre d’information, et la modifier n’a aucun effet sur les clés de registre utilisées par Python. Disponibilité: Windows.

sys._xoptions

Un dictionnaire des différentes options spécifiques à l’implémentation passés en ligne de commande via l’option -X. Aux noms des options correspondent soit leur valeur, si elle est donnée explicitement, soit à True. Exemple :

$ ./python -Xa=b -Xc
Python 3.2a3+ (py3k, Oct 16 2010, 20:14:50)
[GCC 4.4.3] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> import sys
>>> sys._xoptions
{'a': 'b', 'c': True}

CPython implementation detail: C’est un moyen spécifique à CPython pour accéder aux options passées via l’option -X. D’autres implémentations pourraient les exposer par d’autres moyens, ou pas du tout.

Nouveau dans la version 3.2.

Citations

C99

ISO/IEC 9899:1999. « Langages de programmation – C. » Un texte public de ce standard est disponible à http://www.open-std.org/jtc1/sc22/wg14/www/docs/n1256.pdf.

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29.2. sysconfig — Provide access to Python’s configuration information

Nouveau dans la version 3.2.

Source code: Lib/sysconfig.py [https://github.com/python/cpython/tree/3.6/Lib/sysconfig.py]

The sysconfig module provides access to Python’s configuration information like the list of installation paths and the configuration variables relevant for the current platform.

29.2.1. Configuration variables

A Python distribution contains a Makefile and a pyconfig.h header file that are necessary to build both the Python binary itself and third-party C extensions compiled using distutils.

sysconfig puts all variables found in these files in a dictionary that can be accessed using get_config_vars() or get_config_var().

Notice that on Windows, it’s a much smaller set.

sysconfig.get_config_vars(*args)

With no arguments, return a dictionary of all configuration variables relevant for the current platform.

With arguments, return a list of values that result from looking up each argument in the configuration variable dictionary.

For each argument, if the value is not found, return None.

sysconfig.get_config_var(name)

Return the value of a single variable name. Equivalent to get_config_vars().get(name).

If name is not found, return None.

Example of usage:

>>> import sysconfig
>>> sysconfig.get_config_var('Py_ENABLE_SHARED')
0
>>> sysconfig.get_config_var('LIBDIR')
'/usr/local/lib'
>>> sysconfig.get_config_vars('AR', 'CXX')
['ar', 'g++']

29.2.2. Installation paths

Python uses an installation scheme that differs depending on the platform and on the installation options. These schemes are stored in sysconfig under unique identifiers based on the value returned by os.name.

Every new component that is installed using distutils or a Distutils-based system will follow the same scheme to copy its file in the right places.

Python currently supports seven schemes:

posix_prefix: scheme for Posix platforms like Linux or Mac OS X. This is the default scheme used when Python or a component is installed.

posix_home: scheme for Posix platforms used when a home option is used upon installation. This scheme is used when a component is installed through Distutils with a specific home prefix.

posix_user: scheme for Posix platforms used when a component is installed through Distutils and the user option is used. This scheme defines paths located under the user home directory.

nt: scheme for NT platforms like Windows.

nt_user: scheme for NT platforms, when the user option is used.

Each scheme is itself composed of a series of paths and each path has a unique identifier. Python currently uses eight paths:

stdlib: directory containing the standard Python library files that are not platform-specific.

platstdlib: directory containing the standard Python library files that are platform-specific.

platlib: directory for site-specific, platform-specific files.

purelib: directory for site-specific, non-platform-specific files.

include: directory for non-platform-specific header files.

platinclude: directory for platform-specific header files.

scripts: directory for script files.

data: directory for data files.

sysconfig provides some functions to determine these paths.

sysconfig.get_scheme_names()

Return a tuple containing all schemes currently supported in sysconfig.

sysconfig.get_path_names()

Return a tuple containing all path names currently supported in sysconfig.

sysconfig.get_path(name[, scheme[, vars[, expand]]])

Return an installation path corresponding to the path name, from the install scheme named scheme.

name has to be a value from the list returned by get_path_names().

sysconfig stores installation paths corresponding to each path name, for each platform, with variables to be expanded. For instance the stdlib path for the nt scheme is: {base}/Lib.

get_path() will use the variables returned by get_config_vars() to expand the path. All variables have default values for each platform so one may call this function and get the default value.

If scheme is provided, it must be a value from the list returned by get_scheme_names(). Otherwise, the default scheme for the current platform is used.

If vars is provided, it must be a dictionary of variables that will update the dictionary return by get_config_vars().

If expand is set to False, the path will not be expanded using the variables.

If name is not found, return None.

sysconfig.get_paths([scheme[, vars[, expand]]])

Return a dictionary containing all installation paths corresponding to an installation scheme. See get_path() for more information.

If scheme is not provided, will use the default scheme for the current platform.

If vars is provided, it must be a dictionary of variables that will update the dictionary used to expand the paths.

If expand is set to false, the paths will not be expanded.

If scheme is not an existing scheme, get_paths() will raise a KeyError.

29.2.3. Autres fonctions

sysconfig.get_python_version()

Return the MAJOR.MINOR Python version number as a string. Similar to '%d.%d' % sys.version_info[:2].

sysconfig.get_platform()

Return a string that identifies the current platform.

This is used mainly to distinguish platform-specific build directories and platform-specific built distributions. Typically includes the OS name and version and the architecture (as supplied by os.uname()), although the exact information included depends on the OS; e.g. for IRIX the architecture isn’t particularly important (IRIX only runs on SGI hardware), but for Linux the kernel version isn’t particularly important.

Exemples de valeurs renvoyées :

linux-i586

linux-alpha (?)

solaris-2.6-sun4u

irix-5.3

irix64-6.2

Windows will return one of:

win-amd64 (64bit Windows on AMD64, aka x86_64, Intel64, and EM64T)

win-ia64 (64bit Windows on Itanium)

win32 (all others - specifically, sys.platform is returned)

Mac OS X can return:

macosx-10.6-ppc

macosx-10.4-ppc64

macosx-10.3-i386

macosx-10.4-fat

For other non-POSIX platforms, currently just returns sys.platform.

sysconfig.is_python_build()

Return True if the running Python interpreter was built from source and is being run from its built location, and not from a location resulting from e.g. running make install or installing via a binary installer.

sysconfig.parse_config_h(fp[, vars])

Parse a config.h-style file.

fp is a file-like object pointing to the config.h-like file.

A dictionary containing name/value pairs is returned. If an optional dictionary is passed in as the second argument, it is used instead of a new dictionary, and updated with the values read in the file.

sysconfig.get_config_h_filename()

Return the path of pyconfig.h.

sysconfig.get_makefile_filename()

Return the path of Makefile.

29.2.4. Using sysconfig as a script

You can use sysconfig as a script with Python’s -m option:

$ python -m sysconfig
Platform: "macosx-10.4-i386"
Python version: "3.2"
Current installation scheme: "posix_prefix"

Paths:
        data = "/usr/local"
        include = "/Users/tarek/Dev/svn.python.org/py3k/Include"
        platinclude = "."
        platlib = "/usr/local/lib/python3.2/site-packages"
        platstdlib = "/usr/local/lib/python3.2"
        purelib = "/usr/local/lib/python3.2/site-packages"
        scripts = "/usr/local/bin"
        stdlib = "/usr/local/lib/python3.2"

Variables:
        AC_APPLE_UNIVERSAL_BUILD = "0"
        AIX_GENUINE_CPLUSPLUS = "0"
        AR = "ar"
        ARFLAGS = "rc"
        ...

This call will print in the standard output the information returned by get_platform(), get_python_version(), get_path() and get_config_vars().

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29.3. builtins — Objets natifs

Ce module fournit un accès direct aux identifiants “natifs” de Python; par exemple, builtins.open est le nom complet pour la fonction native open(). Voir Fonctions natives et Constantes natives pour plus de documentation.

Ce module n’est normalement pas accédé explicitement par la plupart des applications, mais peut être utile dans des modules qui exposent des objets de même nom qu’une valeur native, mais pour qui le natif de même nom est aussi nécessaire. Par exemple, dans un module qui voudrait implémenter une fonction open() autour de la fonction native open(), ce module peut être utilisé directement :

import builtins

def open(path):
    f = builtins.open(path, 'r')
    return UpperCaser(f)

class UpperCaser:
    '''Wrapper around a file that converts output to upper-case.'''

    def __init__(self, f):
        self._f = f

    def read(self, count=-1):
        return self._f.read(count).upper()

    # ...

Spécificité de l’implémentation: La plupart des modules ont __builtins__ dans leurs globales. La valeur de __builtins__ est classiquement soit ce module, soit la valeur de l’attribut __dict__ du module. Puisque c’est une spécificité de CPython, ce n’est peut-être pas utilisé par toutes les autres implémentations.

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29.4. __main__ — Point d’entrée des scripts

'__main__' est le nom du scope dans lequel le code s’exécute en premier. Le nom d’un module (son __name__) vaut '__main__' lorsqu’il est lu de l’entrée standard, lorsque c’est un script, ou une invite interactive.

Un module peut découvrir s’il est exécuté dans le scope principal en vérifiant son __name__, ce qui permet typiquement d’exécuter du code lorsque le module est exécuté avec python -m mais pas lorsqu’il est importé :

if __name__ == "__main__":
    # execute only if run as a script
    main()

Pour un paquet, le même effet peut être obtenu en utilisant un module __main__.py, son contenu sera exécuté si le paquet est lancé via -m.

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29.5. warnings — Contrôle des alertes

Code source: Lib/warnings.py [https://github.com/python/cpython/tree/3.6/Lib/warnings.py]

Les messages d’avertissement sont généralement émis dans les situations où il est utile d’alerter l’utilisateur d’un problème dans un programme, mais qu’il n’est pas justifié de lever une exception et de le terminer. Par exemple, on peut vouloir émettre un avertissement lorsqu’un programme utilise un module obsolète.

Les développeurs Python émettent des avertissements en appelant la fonction warn() définie dans ce module. (Les développeurs C utilisent PyErr_WarnEx() ; voir Gestion des exceptions pour plus d’informations).

Les messages d’avertissement sont normalement écrits sur sys.stderr, mais leurs effets peuvent être modifiés, il est possible d’ignorer tous les avertissements ou au contraire les transformer en exceptions. L’effet des avertissements peut varier en fonction de la catégorie d’avertissement (voir ci-dessous), de son texte et d’où il est émis. Les répétitions d’un même avertissement d’une même source sont généralement ignorés.

La gestion des avertissements se fait en deux étapes : premièrement, chaque fois qu’un avertissement est émis, le module détermine si un message doit être émis ou non ; ensuite, si un message doit être émis, il est formaté et affiché en utilisant une fonction qui peut être définie par l’utilisateur.

Un filtre (une séquence de règles) est utilisé pour décider si un message d’avertissement doit être émis ou non. Des règles peuvent être ajoutées au filtre en appelant filterwarnings() et remises à leur état par défaut en appelant resetwarnings().

L’affichage des messages d’avertissement se fait en appelant la fonction showwarning(), qui peut être redéfinie ; l’implémentation par défaut formate le message en appelant formatwarning(), qui peut également être réutilisée par une implémentation personnalisée.

Voir aussi

logging.captureWarnings() vous permet de gérer tous les avertissements avec l’infrastructure de journalisation standard.

29.5.1. Catégories d’avertissement

There are a number of built-in exceptions that represent warning categories. This categorization is useful to be able to filter out groups of warnings. The following warnings category classes are currently defined:

Classe

Description

Warning

Il s’agit de la classe de base de toutes les classes de catégories d’avertissement. C’est une sous-classe de Exception.

UserWarning

Catégorie par défaut pour warn().

DeprecationWarning

Base category for warnings about deprecated features (ignored by default).

SyntaxWarning

Catégorie de base pour les avertissements concernant les syntaxes douteuses.

RuntimeWarning

Catégorie de base pour les avertissements concernant les fonctionnalités douteuses à l’exécution.

FutureWarning

Base category for warnings about constructs that will change semantically in the future.

PendingDeprecationWarning

Catégorie de base pour les avertissements concernant les fonctionnalités qui seront obsolètes dans le futur (ignorée par défaut).

ImportWarning

Catégorie de base pour les avertissements déclenchés lors de l’importation d’un module (ignoré par défaut).

UnicodeWarning

Catégorie de base pour les avertissements relatifs à Unicode.

BytesWarning

Catégorie de base pour les avertissements relatifs à bytes et bytearray.

ResourceWarning

Catégorie de base pour les avertissements relatifs à l’utilisation des ressources.

While these are technically built-in exceptions, they are documented here, because conceptually they belong to the warnings mechanism.

Le code utilisateur peut définir des catégories d’avertissement supplémentaires en héritant l’une des catégories d’avertissement standard. Une catégorie d’avertissement doit toujours hériter de la classe Warning.

29.5.2. Le filtre des avertissements

Le filtre des avertissements contrôle si les avertissements sont ignorés, affichés ou transformés en erreurs (ce qui lève une exception).

Conceptually, the warnings filter maintains an ordered list of filter specifications; any specific warning is matched against each filter specification in the list in turn until a match is found; the match determines the disposition of the match. Each entry is a tuple of the form (action, message, category, module, lineno), where:

action est l’une des chaînes de caractères suivantes :

Valeur

Action

"error"

transforme les avertissements correspondants en exceptions

"ignore"

ignore les avertissements correspondants

"always"

affiche toujours les avertissements correspondants

"default"

print the first occurrence of matching warnings for each location where the warning is issued

"module"

print the first occurrence of matching warnings for each module where the warning is issued

"once"

n’affiche que la première occurrence des avertissements correspondants, quel que soit l’endroit où ils se trouvent

message est une chaîne de caractères contenant une expression régulière avec laquelle le début du message d’avertissement doit correspondre. L’expression est compilée pour être toujours insensible à la casse.

category est une classe (une sous-classe de Warning) dont la catégorie d’avertissement doit être une sous-classe afin de correspondre.

module est une chaîne de caractères contenant une expression régulière avec laquelle le nom du module doit correspondre. L’expression est compilée pour être sensible à la casse.

lineno est le numéro de ligne d’où l’avertissement doit provenir, ou 0 pour correspondre à tous les numéros de ligne.

Puisque que la classe Warning hérite de la classe Exception, pour transformer un avertissement en erreur, il suffit de lever category(message).

The warnings filter is initialized by -W options passed to the Python interpreter command line. The interpreter saves the arguments for all -W options without interpretation in sys.warnoptions; the warnings module parses these when it is first imported (invalid options are ignored, after printing a message to sys.stderr).

29.5.2.1. Default Warning Filters

By default, Python installs several warning filters, which can be overridden by the command-line options passed to -W and calls to filterwarnings().

DeprecationWarning and PendingDeprecationWarning, and ImportWarning are ignored.

BytesWarning is ignored unless the -b option is given once or twice; in this case this warning is either printed (-b) or turned into an exception (-bb).

ResourceWarning is ignored unless Python was built in debug mode.

Modifié dans la version 3.2: DeprecationWarning est maintenant ignoré par défaut en plus de PendingDeprecationWarning.

29.5.3. Suppression temporaire des avertissements

If you are using code that you know will raise a warning, such as a deprecated function, but do not want to see the warning, then it is possible to suppress the warning using the catch_warnings context manager:

import warnings

def fxn():
    warnings.warn("deprecated", DeprecationWarning)

with warnings.catch_warnings():
    warnings.simplefilter("ignore")
    fxn()

Dans le gestionnaire de contexte, tous les avertissements sont simplement ignorés. Ceci vous permet d’utiliser du code déclaré obsolète sans voir l’avertissement tout en ne supprimant pas l’avertissement pour un autre code qui pourrait ne pas être conscient de son utilisation de code déprécié. Remarque : ceci ne peut être garanti que dans une application utilisant un seul fil d’exécution. Si deux ou plusieurs threads utilisent le gestionnaire de contexte catch_warnings en même temps, le comportement est indéfini.

29.5.4. Tester les avertissements

Pour tester les avertissements générés par le code, utilisez le gestionnaire de contexte catch_warnings. Avec lui, vous pouvez temporairement modifier le filtre d’avertissements pour faciliter votre test. Par exemple, procédez comme suit pour capturer tous les avertissements levés à vérifier :

import warnings

def fxn():
    warnings.warn("deprecated", DeprecationWarning)

with warnings.catch_warnings(record=True) as w:
    # Cause all warnings to always be triggered.
    warnings.simplefilter("always")
    # Trigger a warning.
    fxn()
    # Verify some things
    assert len(w) == 1
    assert issubclass(w[-1].category, DeprecationWarning)
    assert "deprecated" in str(w[-1].message)

Vous pouvez aussi faire en sorte que tous les avertissements soient des exceptions en utilisant error au lieu de always. Il faut savoir que si un avertissement a déjà été émis à cause d’une règle once ou default, quel que soit le filtre activé, l’avertissement ne sera pas revu à moins que le registre des avertissements lié à l’avertissement ait été vidé.

A sa sortie, le gestionnaire de contexte restaure le filtre des avertissements dans l’état où il était au démarrage du contexte. Cela empêche les tests de changer le filtre d’avertissements de manière inattendue entre les tests et d’aboutir à des résultats de test indéterminés. La fonction showwarning() du module est également restaurée à sa valeur originale. Remarque : ceci ne peut être garanti que dans une application mono-threadées. Si deux ou plusieurs fils d’exécution utilisent le gestionnaire de contexte catch_warnings en même temps, le comportement est indéfini.

Lorsque vous testez plusieurs opérations qui provoquent le même type d’avertissement, il est important de les tester d’une manière qui confirme que chaque opération provoque un nouvel avertissement (par exemple, définissez les avertissements comme exceptions et vérifiez que les opérations provoquent des exceptions, vérifiez que la longueur de la liste des avertissements continue à augmenter après chaque opération, ou bien supprimez les entrées précédentes de la liste des avertissements avant chaque nouvelle opération).

29.5.5. Updating Code For New Versions of Python

Warnings that are only of interest to the developer are ignored by default. As such you should make sure to test your code with typically ignored warnings made visible. You can do this from the command-line by passing -Wd to the interpreter (this is shorthand for -W default). This enables default handling for all warnings, including those that are ignored by default. To change what action is taken for encountered warnings you simply change what argument is passed to -W, e.g. -W error. See the -W flag for more details on what is possible.

To programmatically do the same as -Wd, use:

warnings.simplefilter('default')

Make sure to execute this code as soon as possible. This prevents the registering of what warnings have been raised from unexpectedly influencing how future warnings are treated.

Having certain warnings ignored by default is done to prevent a user from seeing warnings that are only of interest to the developer. As you do not necessarily have control over what interpreter a user uses to run their code, it is possible that a new version of Python will be released between your release cycles. The new interpreter release could trigger new warnings in your code that were not there in an older interpreter, e.g. DeprecationWarning for a module that you are using. While you as a developer want to be notified that your code is using a deprecated module, to a user this information is essentially noise and provides no benefit to them.

The unittest module has been also updated to use the 'default' filter while running tests.

29.5.6. Fonctions disponibles

warnings.warn(message, category=None, stacklevel=1, source=None)

Émet, ignore, ou transforme en exception un avertissement. L’argument category, s’il est donné, doit être une classe de catégorie d’avertissement (voir ci-dessus) ; et vaut par défaut UserWarning. Aussi message peut être une instance de Warning', auquel cas *category* sera ignoré et ``message.__class__` sera utilisé. Dans ce cas, le texte du message sera str(message). Cette fonction lève une exception si cet avertissement particulier émis est transformé en erreur par le filtre des avertissements, voir ci-dessus. L’argument stacklevel peut être utilisé par les fonctions wrapper écrites en Python, comme ceci :

def deprecation(message):
    warnings.warn(message, DeprecationWarning, stacklevel=2)

Fait en sorte que l’avertissement se réfère à l’appelant de deprecation() plutôt qu’à la source de deprecation() elle-même (puisque celle-ci irait à l’encontre du but du message d’avertissement).

source, s’il est fourni, est l’objet détruit qui a émis un ResourceWarning.

Modifié dans la version 3.6: Ajout du paramètre source.

warnings.warn_explicit(message, category, filename, lineno, module=None, registry=None, module_globals=None, source=None)

Il s’agit d’une interface de bas niveau pour la fonctionnalité de warn(), en passant explicitement le message, la catégorie, le nom de fichier et le numéro de ligne, et éventuellement le nom du module et le registre (qui devrait être le dictionnaire __warningregistry__ du module). Le nom de module par défaut est le nom de fichier sans .py ; si aucun registre n’est passé, l’avertissement n’est jamais supprimé. message doit être une chaîne de caractères et category une sous-classe de Warning ou message peut être une instance de Warning, auquel cas category sera ignoré.

module_globals, s’il est fourni, doit être l’espace de nommage global utilisé par le code pour lequel l’avertissement est émis. (Cet argument est utilisé pour afficher les sources des modules trouvés dans les fichiers zip ou d’autres sources d’importation hors du système de fichiers).

source, s’il est fourni, est l’objet détruit qui a émis un ResourceWarning.

Modifié dans la version 3.6: Ajout du paramètre source.

warnings.showwarning(message, category, filename, lineno, file=None, line=None)

Écrit un avertissement dans un fichier. L’implémentation par défaut appelle format warning(message, category, filename, lineno, line)``et écrit la chaîne résultante dans *file*, qui par défaut est ``sys.stderr. Vous pouvez remplacer cette fonction par n’importe quel appelable en l’affectant à warnings.showwarning. line est une ligne de code source à inclure dans le message d’avertissement ; si line n’est pas fourni, show warning() essaiera de lire la ligne spécifiée par filename et lineno.

warnings.formatwarning(message, category, filename, lineno, line=None)

Formate un avertissement de la manière standard. Ceci renvoie une chaîne pouvant contenir des retours à la ligne se termine par un retour à la ligne. line est une ligne de code source à inclure dans le message d’avertissement ; si line n’est pas fourni, formatwarning() essaiera de lire la ligne spécifiée par filename et lineno.

warnings.filterwarnings(action, message='', category=Warning, module='', lineno=0, append=False)

Insère une entrée dans la liste de warning filter specifications. L’entrée est insérée à l’avant par défaut ; si append est vrai, elle est insérée à la fin. Il vérifie le type des arguments, compile les expressions régulières message et module, et les insère sous forme de tuple dans la liste des filtres d’avertissements. Les entrées plus proches du début de la liste ont priorité sur les entrées plus loin dans la liste. Les arguments omis ont par défaut une valeur qui correspond à tout.

warnings.simplefilter(action, category=Warning, lineno=0, append=False)

Insère une entrée simple dans la liste de spécifications du filtre d’avertissements. La signification des paramètres de fonction est la même que pour filterwarnings(), mais les expressions régulières ne sont pas nécessaires car le filtre inséré correspond toujours à n’importe quel message dans n’importe quel module tant que la catégorie et le numéro de ligne correspondent.

warnings.resetwarnings()

Réinitialise le filtre des avertissements. Ceci supprime l’effet de tous les appels précédents à filterwarnings(), y compris celui de l’option -W des options de ligne de commande et des appels à simplefilter().

29.5.7. Gestionnaires de contexte disponibles

class warnings.catch_warnings(*, record=False, module=None)

Un gestionnaire de contexte qui copie et, à la sortie, restaure le filtre des avertissements et la fonction showwarning(). Si l’argument record est False (par défaut), le gestionnaire de contexte retourne None en entrant. Si record est True, une liste est renvoyée qui est progressivement remplie d’objets comme vus par une fonction custom showwarning' (qui supprime également la sortie vers ``sys.stdout`()). Chaque objet de la liste a des attributs avec les mêmes noms que les arguments de showwarning().

L’argument module prend un module qui sera utilisé à la place du module renvoyé lors de l’importation warnings dont le filtre sera protégé. Cet argument existe principalement pour tester le module warnings lui-même.

Note

Le gestionnaire catch_warnings fonctionne en remplaçant puis en restaurant plus tard la fonction showwarning() du module et la liste interne des spécifications du filtre. Cela signifie que le gestionnaire de contexte modifie l’état global et n’est donc pas prévisible avec plusieurs fils d’exécution.

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29.6. contextlib — Utilities for with-statement contexts

Code source : Lib/contextlib.py [https://github.com/python/cpython/tree/3.6/Lib/contextlib.py]

Ce module fournit des utilitaires pour les tâches impliquant le mot-clé with. Pour plus d’informations voir aussi Le type gestionnaire de contexte et Gestionnaire de contexte With.

29.6.1. Utilitaires

Fonctions et classes fournies :

class contextlib.AbstractContextManager

Classe mère abstraite pour les classes qui implémentent les méthodes object.__enter__() et object.__exit__(). Une implémentation par défaut de object.__enter__() est fournie, qui renvoie self, et object.__exit__() est une méthode abstraite qui renvoie None par défaut. Voir aussi la définition de Le type gestionnaire de contexte.

Nouveau dans la version 3.6.

@contextlib.contextmanager

Cette fonction est un decorator qui peut être utilisé pour définir une fonction fabriquant des gestionnaires de contexte à utiliser avec with, sans nécessiter de créer une classe ou des méthodes __enter__() et __exit__() séparées.

While many objects natively support use in with statements, sometimes a resource needs to be managed that isn’t a context manager in its own right, and doesn’t implement a close() method for use with contextlib.closing

An abstract example would be the following to ensure correct resource management:

from contextlib import contextmanager

@contextmanager
def managed_resource(*args, **kwds):
    # Code to acquire resource, e.g.:
    resource = acquire_resource(*args, **kwds)
    try:
        yield resource
    finally:
        # Code to release resource, e.g.:
        release_resource(resource)

>>> with managed_resource(timeout=3600) as resource:
...     # Resource is released at the end of this block,
...     # even if code in the block raises an exception

The function being decorated must return a generator-iterator when called. This iterator must yield exactly one value, which will be bound to the targets in the with statement’s as clause, if any.

At the point where the generator yields, the block nested in the with statement is executed. The generator is then resumed after the block is exited. If an unhandled exception occurs in the block, it is reraised inside the generator at the point where the yield occurred. Thus, you can use a try…except…finally statement to trap the error (if any), or ensure that some cleanup takes place. If an exception is trapped merely in order to log it or to perform some action (rather than to suppress it entirely), the generator must reraise that exception. Otherwise the generator context manager will indicate to the with statement that the exception has been handled, and execution will resume with the statement immediately following the with statement.

Le décorateur contextmanager() utilise la classe ContextDecorator afin que les gestionnaires de contexte qu’il crée puissent être utilisés aussi bien en tant que décorateurs qu’avec des instructions with. Quand vous l’utilisez comme décorateur, une nouvelle instance du générateur est créée à chaque appel de la fonction (cela permet aux gestionnaires de contexte à usage unique créés par contextmanager() de remplir la condition de pouvoir être invoqués plusieurs fois afin d’être utilisés comme décorateurs).

Modifié dans la version 3.2: Utilisation de la classe ContextDecorator.

contextlib.closing(thing)

Renvoie un gestionnaire de contexte qui ferme thing à la fin du bloc. C’est essentiellement équivalent à :

from contextlib import contextmanager

@contextmanager
def closing(thing):
    try:
        yield thing
    finally:
        thing.close()

Et cela vous permet d’écrire du code tel que :

from contextlib import closing
from urllib.request import urlopen

with closing(urlopen('http://www.python.org')) as page:
    for line in page:
        print(line)

sans besoin de fermer explicitement page. Même si une erreur survient, page.close() est appelée à la fermeture du bloc with.

contextlib.suppress(*exceptions)

Renvoie un gestionnaire de contexte qui supprime toutes les exceptions spécifiées si elles surviennent dans le corps du bloc with, et reprend l’exécution sur la première instruction qui suit la fin du bloc with.

Comme pour tous les mécanismes qui suppriment complètement les exceptions, ce gestionnaire de contexte doit seulement être utilisé pour couvrir des cas très spécifiques d’erreurs où il est certain que continuer silencieusement l’exécution du programme est la bonne chose à faire.

Par exemple :

from contextlib import suppress

with suppress(FileNotFoundError):
    os.remove('somefile.tmp')

with suppress(FileNotFoundError):
    os.remove('someotherfile.tmp')

Ce code est équivalent à :

try:
    os.remove('somefile.tmp')
except FileNotFoundError:
    pass

try:
    os.remove('someotherfile.tmp')
except FileNotFoundError:
    pass

Ce gestionnaire de contexte est réentrant.

Nouveau dans la version 3.4.

contextlib.redirect_stdout(new_target)

Gestionnaire de contexte servant à rediriger temporairement sys.stdout vers un autre fichier ou objet fichier-compatible.

Cet outil ajoute une certaine flexibilité aux fonctions ou classes existantes dont la sortie est envoyée vers la sortie standard.

Par exemple, la sortie de help() est normalement envoyée vers sys.stdout. Vous pouvez capturer cette sortie dans une chaîne de caractères en la redirigeant vers un objet io.StringIO :

f = io.StringIO()
with redirect_stdout(f):
    help(pow)
s = f.getvalue()

Pour envoyer la sortie de help() vers un fichier sur le disque, redirigez-la sur un fichier normal :

with open('help.txt', 'w') as f:
    with redirect_stdout(f):
        help(pow)

Pour envoyer la sortie de help() sur sys.stderr :

with redirect_stdout(sys.stderr):
    help(pow)

Notez que l’effet de bord global sur sys.stdout signifie que ce gestionnaire de contexte n’est pas adapté à une utilisation dans le code d’une bibliothèque ni dans la plupart des applications à plusieurs fils d’exécution. Aussi, cela n’a pas d’effet sur la sortie des sous-processus. Cependant, cela reste une approche utile pour beaucoup de scripts utilitaires.

Ce gestionnaire de contexte est réentrant.

Nouveau dans la version 3.4.

contextlib.redirect_stderr(new_target)

Similaire à redirect_stdout() mais redirige sys.stderr vers un autre fichier ou objet fichier-compatible.

Ce gestionnaire de contexte est réentrant.

Nouveau dans la version 3.5.

class contextlib.ContextDecorator

Une classe mère qui permet à un gestionnaire de contexte d’être aussi utilisé comme décorateur.

Les gestionnaires de contexte héritant de ContextDecorator doivent implémenter __enter__ et __exit__ comme habituellement. __exit__ conserve sa gestion optionnelle des exceptions même lors de l’utilisation en décorateur.

ContextDecorator est utilisé par contextmanager(), donc vous bénéficiez automatiquement de cette fonctionnalité.

Exemple de ContextDecorator :

from contextlib import ContextDecorator

class mycontext(ContextDecorator):
    def __enter__(self):
        print('Starting')
        return self

    def __exit__(self, *exc):
        print('Finishing')
        return False

>>> @mycontext()
... def function():
...     print('The bit in the middle')
...
>>> function()
Starting
The bit in the middle
Finishing

>>> with mycontext():
...     print('The bit in the middle')
...
Starting
The bit in the middle
Finishing

Ce changement est simplement un sucre syntaxique pour les constructions de la forme suivante :

def f():
    with cm():
        # Do stuff

ContextDecorator vous permet d’écrire à la place :

@cm()
def f():
    # Do stuff

Cela éclaircit le fait que cm s’applique à la fonction entière, et pas seulement à un morceau en particulier (et gagner un niveau d’indentation est toujours appréciable).

Les gestionnaires de contexte existants qui ont déjà une classe mère peuvent être étendus en utilisant ContextDecorator comme une mixin :

from contextlib import ContextDecorator

class mycontext(ContextBaseClass, ContextDecorator):
    def __enter__(self):
        return self

    def __exit__(self, *exc):
        return False

Note

As the decorated function must be able to be called multiple times, the underlying context manager must support use in multiple with statements. If this is not the case, then the original construct with the explicit with statement inside the function should be used.

Nouveau dans la version 3.2.

class contextlib.ExitStack

Gestionnaire de contexte conçu pour simplifier le fait de combiner programmatiquement d’autres gestionnaires de contexte et fonctions de nettoyage, spécifiquement ceux qui sont optionnels ou pilotés par des données d’entrée.

Par exemple, un ensemble de fichiers peut facilement être géré dans une unique instruction with comme suit :

with ExitStack() as stack:
    files = [stack.enter_context(open(fname)) for fname in filenames]
    # All opened files will automatically be closed at the end of
    # the with statement, even if attempts to open files later
    # in the list raise an exception

Chaque instance maintient une pile de fonctions de rappels (callbacks) enregistrées qui sont appelées en ordre inverse quand l’instance est fermée (explicitement ou implicitement à la fin d’un bloc with). Notez que ces fonctions ne sont pas invoquées implicitement quand l’instance de la pile de contextes est collectée par le ramasse-miettes.

Ce modèle de pile est utilisé afin que les gestionnaires de contexte qui acquièrent leurs ressources dans leur méthode __init__ (tels que les objets-fichiers) puissent être gérés correctement.

Comme les fonctions de rappel enregistrées sont invoquées dans l’ordre inverse d’enregistrement, cela revient au même que si de multiples blocs with imbriqués avaient été utilisés avec l’ensemble de fonctions enregistrées. Cela s’étend aussi à la gestion d’exceptions — si une fonction de rappel intérieure supprime ou remplace une exception, alors les fonctions extérieures reçoivent des arguments basés sur ce nouvel état.

C’est une API relativement bas-niveau qui s’occupe de dérouler correctement la pile des appels de sortie. Elle fournit une base adaptée pour des gestionnaires de contexte de plus haut niveau qui manipulent la pile de sortie de manière spécifique à l’application.

Nouveau dans la version 3.3.

enter_context(cm)

Entre dans un nouveau gestionnaire de contexte et ajoute sa méthode __exit__() à la pile d’appels. La valeur de retour est le résultat de la méthode __enter__() du gestionnaire de contexte donné.

Ces gestionnaires de contexte peuvent supprimer des exceptions comme ils le feraient normalement s’ils étaient utilisés directement derrière une instruction with.

push(exit)

Ajoute la méthode __exit__() d’un gestionnaire de contexte à la pile d’appels.

Comme __enter__ n’est pas invoquée, cette méthode peut être utilisée pour couvrir une partie de l’implémentation de __enter__() avec la propre méthode __exit__() d’un gestionnaire de contexte.

Si l’argument passé n’est pas un gestionnaire de contexte, la méthode assume qu’il s’agit d’une fonction de rappel avec la même signature que la méthode __exit__() des gestionnaires de contexte pour l’ajouter directement à la pile d’appels.

En retournant des valeurs vraies, ces fonctions peuvent supprimer des exceptions de la même manière que le peuvent les méthodes __exit__() des gestionnaires de contexte.

L’objet passé en paramètre est renvoyé par la fonction, ce qui permet à la méthode d’être utilisée comme décorateur de fonction.

callback(callback, *args, **kwds)

Accepte une fonction arbitraire et ses arguments et les ajoute à la pile des fonctions de rappel.

À la différence des autres méthodes, les fonctions de rappel ajoutées de cette manière ne peuvent pas supprimer les exceptions (puisqu’elles ne reçoivent jamais les détails de l’exception).

La fonction passée en paramètre est renvoyée par la méthode, ce qui permet à la méthode d’être utilisée comme décorateur de fonction.

pop_all()

Transfère la pile d’appels à une nouvelle instance de ExitStack et la renvoie. Aucune fonction de rappel n’est invoquée par cette opération — à la place, elles sont dorénavant invoquées quand la nouvelle pile sera close (soit explicitement soit implicitement à la fin d’un bloc with).

Par exemple, un groupe de fichiers peut être ouvert comme une opération « tout ou rien » comme suit :

with ExitStack() as stack:
    files = [stack.enter_context(open(fname)) for fname in filenames]
    # Hold onto the close method, but don't call it yet.
    close_files = stack.pop_all().close
    # If opening any file fails, all previously opened files will be
    # closed automatically. If all files are opened successfully,
    # they will remain open even after the with statement ends.
    # close_files() can then be invoked explicitly to close them all.

close()

Déroule immédiatement la pile d’appels, invoquant les fonctions de rappel dans l’ordre inverse d’enregistrement. Pour chaque gestionnaire de contexte et fonction de sortie enregistré, les arguments passés indiqueront qu’aucune exception n’est survenue.

29.6.2. Exemples et Recettes

Cette section décrit quelques exemples et recettes pour décrire une utilisation réelle des outils fournis par contextlib.

29.6.2.1. Gérer un nombre variable de gestionnaires de contexte

Le cas d’utilisation primaire de ExitStack est celui décrit dans la documentation de la classe : gérer un nombre variable de gestionnaires de contexte et d’autres opérations de nettoyage en une unique instruction with. La variabilité peut venir du nombre de gestionnaires de contexte voulus découlant d’une entrée de l’utilisateur (comme ouvrir une collection spécifique de fichiers de l’utilisateur), ou de certains gestionnaires de contexte qui peuvent être optionnels :

with ExitStack() as stack:
    for resource in resources:
        stack.enter_context(resource)
    if need_special_resource():
        special = acquire_special_resource()
        stack.callback(release_special_resource, special)
    # Perform operations that use the acquired resources

Comme montré, ExitStack rend aussi assez facile d’utiliser les instructions with pour gérer des ressources arbitraires qui ne gèrent pas nativement le protocole des gestionnaires de contexte.

29.6.2.2. Simplifying support for single optional context managers

In the specific case of a single optional context manager, ExitStack instances can be used as a « do nothing » context manager, allowing a context manager to easily be omitted without affecting the overall structure of the source code:

def debug_trace(details):
    if __debug__:
        return TraceContext(details)
    # Don't do anything special with the context in release mode
    return ExitStack()

with debug_trace():
    # Suite is traced in debug mode, but runs normally otherwise

29.6.2.3. Attraper des exceptions depuis les méthodes __enter__

Il est occasionnellement souhaitable d’attraper les exceptions depuis l’implémentation d’une méthode __enter__, sans attraper par inadvertance les exceptions du corps de l’instruction with ou de la méthode __exit__ des gestionnaires de contexte. En utilisant ExitStack, les étapes du protocole des gestionnaires de contexte peuvent être légèrement séparées pour permettre le code suivant :

stack = ExitStack()
try:
    x = stack.enter_context(cm)
except Exception:
    # handle __enter__ exception
else:
    with stack:
        # Handle normal case

Avoir à faire cela est en fait surtout utile pour indiquer que l”API sous-jacente devrait fournir une interface directe de gestion des ressources à utiliser avec les instructions try/except/finally, mais que toutes les API ne sont pas bien conçues dans cet objectif. Quand un gestionnaire de contexte est la seule API de gestion des ressources fournie, alors ExitStack peut rendre plus facile la gestion de plusieurs situations qui ne peuvent pas être traitées directement dans une instruction with.

29.6.2.4. Nettoyer dans une méthode __enter__

Comme indiqué dans la documentation de ExitStack.push(), cette méthode peut être utile pour nettoyer une ressource déjà allouée si les dernières étapes de l’implémentation de __enter__() échouent.

Voici un exemple de gestionnaire de contexte qui reçoit des fonctions d’acquisition de ressources et de libération, avec une méthode de validation optionnelle, et qui les adapte au protocole des gestionnaires de contexte :

from contextlib import contextmanager, AbstractContextManager, ExitStack

class ResourceManager(AbstractContextManager):

    def __init__(self, acquire_resource, release_resource, check_resource_ok=None):
        self.acquire_resource = acquire_resource
        self.release_resource = release_resource
        if check_resource_ok is None:
            def check_resource_ok(resource):
                return True
        self.check_resource_ok = check_resource_ok

    @contextmanager
    def _cleanup_on_error(self):
        with ExitStack() as stack:
            stack.push(self)
            yield
            # The validation check passed and didn't raise an exception
            # Accordingly, we want to keep the resource, and pass it
            # back to our caller
            stack.pop_all()

    def __enter__(self):
        resource = self.acquire_resource()
        with self._cleanup_on_error():
            if not self.check_resource_ok(resource):
                msg = "Failed validation for {!r}"
                raise RuntimeError(msg.format(resource))
        return resource

    def __exit__(self, *exc_details):
        # We don't need to duplicate any of our resource release logic
        self.release_resource()

29.6.2.5. Remplacer un try-finally avec une option variable

Un modèle que vous rencontrerez parfois est un bloc try-finally avec une option pour indiquer si le corps de la clause finally doit être exécuté ou non. Dans sa forme la plus simple (qui ne peut pas déjà être gérée avec juste une clause except), cela ressemble à :

cleanup_needed = True
try:
    result = perform_operation()
    if result:
        cleanup_needed = False
finally:
    if cleanup_needed:
        cleanup_resources()

Comme avec n’importe quel code basé sur une instruction try, cela peut poser problème pour le développement et la revue, parce que beaucoup de codes d’installation et de nettoyage peuvent finir par être séparés par des sections de code arbitrairement longues.

ExitStack rend possible de plutôt enregistrer une fonction de rappel pour être exécutée à la fin d’une instruction with, et décider ensuite de passer l’exécution de cet appel :

from contextlib import ExitStack

with ExitStack() as stack:
    stack.callback(cleanup_resources)
    result = perform_operation()
    if result:
        stack.pop_all()

Cela permet de rendre explicite dès le départ le comportement de nettoyage attendu, plutôt que de nécessiter une option séparée.

Si une application particulière utilise beaucoup ce modèle, cela peut-être simplifié encore plus au moyen d’une petite classe d’aide :

from contextlib import ExitStack

class Callback(ExitStack):
    def __init__(self, callback, *args, **kwds):
        super(Callback, self).__init__()
        self.callback(callback, *args, **kwds)

    def cancel(self):
        self.pop_all()

with Callback(cleanup_resources) as cb:
    result = perform_operation()
    if result:
        cb.cancel()

Si le nettoyage de la ressource n’est pas déjà soigneusement embarqué dans une fonction autonome, il est possible d’utiliser le décorateur ExitStack.callback() pour déclarer la fonction de nettoyage de ressource en avance :

from contextlib import ExitStack

with ExitStack() as stack:
    @stack.callback
    def cleanup_resources():
        ...
    result = perform_operation()
    if result:
        stack.pop_all()

Dû au fonctionnement du protocole des décorateurs, une fonction déclarée ainsi ne peut prendre aucun paramètre. À la place, les ressources à libérer doivent être récupérées depuis l’extérieur comme des variables de fermeture (closure).

29.6.2.6. Utiliser un gestionnaire de contexte en tant que décorateur de fonction

ContextDecorator rend possible l’utilisation d’un gestionnaire de contexte à la fois ordinairement avec une instruction with ou comme un décorateur de fonction.

Par exemple, il est parfois utile d’emballer les fonctions ou blocs d’instructions avec un journaliseur qui pourrait suivre le temps d’exécution entre l’entrée et la sortie. Plutôt qu’écrire à la fois un décorateur et un gestionnaire de contexte pour la même tâche, hériter de ContextDecorator fournit les deux fonctionnalités en une seule définition :

from contextlib import ContextDecorator
import logging

logging.basicConfig(level=logging.INFO)

class track_entry_and_exit(ContextDecorator):
    def __init__(self, name):
        self.name = name

    def __enter__(self):
        logging.info('Entering: %s', self.name)

    def __exit__(self, exc_type, exc, exc_tb):
        logging.info('Exiting: %s', self.name)

Les instances de cette classe peuvent être utilisées comme gestionnaires de contexte :

with track_entry_and_exit('widget loader'):
    print('Some time consuming activity goes here')
    load_widget()

Et comme décorateurs de fonctions :

@track_entry_and_exit('widget loader')
def activity():
    print('Some time consuming activity goes here')
    load_widget()

Notez qu’il y a une autre limitation en utilisant les gestionnaires de contexte comme décorateurs : il n’y a aucune manière d’accéder à la valeur de retour de __enter__(). Si cette valeur est nécessaire, il faut utiliser explicitement une instruction with.

Voir aussi

PEP 343 [https://www.python.org/dev/peps/pep-0343] - The « with » statement

La spécification, les motivations et des exemples de l’instruction with en Python.

29.6.3. Gestionnaires de contexte à usage unique, réutilisables et réentrants

La plupart des gestionnaires de contexte sont écrits d’une manière qui ne leur permet que d’être utilisés une fois avec une instruction with. Ces gestionnaires de contexte à usage unique doivent être recréés chaque fois qu’ils sont utilisés — tenter de les utiliser une seconde fois lève une exception ou ne fonctionne pas correctement.

Cette limitation commune signifie qu’il est généralement conseillé de créer les gestionnaires de contexte directement dans l’en-tête du bloc with où ils sont utilisés (comme montré dans tous les exemples d’utilisation au-dessus).

Les fichiers sont un exemple de gestionnaires de contexte étant effectivement à usage unique, puisque la première instruction with ferme le fichier, empêchant d’autres opérations d’entrée/sortie d’être exécutées sur ce fichier.

Les gestionnaires de contexte créés avec contextmanager() sont aussi à usage unique, et se plaindront du fait que le générateur sous-jacent ne produise plus de valeur si vous essayez de les utiliser une seconde fois :

>>> from contextlib import contextmanager
>>> @contextmanager
... def singleuse():
...     print("Before")
...     yield
...     print("After")
...
>>> cm = singleuse()
>>> with cm:
...     pass
...
Before
After
>>> with cm:
...     pass
...
Traceback (most recent call last):
    ...
RuntimeError: generator didn't yield

29.6.3.1. Gestionnaires de contexte réentrants

More sophisticated context managers may be « reentrant ». These context managers can not only be used in multiple with statements, but may also be used inside a with statement that is already using the same context manager.

threading.RLock est un exemple de gestionnaire de contexte réentrant, comme le sont aussi suppress() et redirect_stdout(). Voici un très simple exemple d’utilisation réentrante :

>>> from contextlib import redirect_stdout
>>> from io import StringIO
>>> stream = StringIO()
>>> write_to_stream = redirect_stdout(stream)
>>> with write_to_stream:
...     print("This is written to the stream rather than stdout")
...     with write_to_stream:
...         print("This is also written to the stream")
...
>>> print("This is written directly to stdout")
This is written directly to stdout
>>> print(stream.getvalue())
This is written to the stream rather than stdout
This is also written to the stream

Les exemples plus réels de réentrance sont susceptibles d’invoquer plusieurs fonctions s’entre-appelant, et donc être bien plus compliqués que cet exemple.

Notez aussi qu’être réentrant ne signifie pas être thread safe. redirect_stdout(), par exemple, n’est définitivement pas thread safe, puisqu’il effectue des changements globaux sur l’état du système en branchant sys.stdout sur différents flux.

29.6.3.2. Gestionnaires de contexte réutilisables

D’autres gestionnaires de contexte que ceux à usage unique et les réentrants sont les gestionnaires de contexte « réutilisables » (ou, pour être plus explicite, « réutilisables mais pas réentrants », puisque les gestionnaires de contexte réentrants sont aussi réutilisables). Ces gestionnaires de contexte sont conçus afin d’être utilisés plusieurs fois, mais échoueront (ou ne fonctionnent pas correctement) si l’instance de gestionnaire de contexte référencée a déjà été utilisée dans une instruction with englobante.

threading.Lock est un exemple de gestionnaire de contexte réutilisable mais pas réentrant (pour un verrou réentrant, il faut à la place utiliser threading.RLock).

Un autre exemple de gestionnaire de contexte réutilisable mais pas réentrant est ExitStack, puisqu’il invoque toutes les fonctions de rappel actuellement enregistrées en quittant l’instruction with, sans regarder où ces fonctions ont été ajoutées :

>>> from contextlib import ExitStack
>>> stack = ExitStack()
>>> with stack:
...     stack.callback(print, "Callback: from first context")
...     print("Leaving first context")
...
Leaving first context
Callback: from first context
>>> with stack:
...     stack.callback(print, "Callback: from second context")
...     print("Leaving second context")
...
Leaving second context
Callback: from second context
>>> with stack:
...     stack.callback(print, "Callback: from outer context")
...     with stack:
...         stack.callback(print, "Callback: from inner context")
...         print("Leaving inner context")
...     print("Leaving outer context")
...
Leaving inner context
Callback: from inner context
Callback: from outer context
Leaving outer context

Comme le montre la sortie de l’exemple, réutiliser une simple pile entre plusieurs instructions with fonctionne correctement, mais essayer de les imbriquer fait que la pile est vidée à la fin du with le plus imbriqué, ce qui n’est probablement pas le comportement voulu.

Pour éviter ce problème, utilisez des instances différentes de ExitStack plutôt qu’une seule instance :

>>> from contextlib import ExitStack
>>> with ExitStack() as outer_stack:
...     outer_stack.callback(print, "Callback: from outer context")
...     with ExitStack() as inner_stack:
...         inner_stack.callback(print, "Callback: from inner context")
...         print("Leaving inner context")
...     print("Leaving outer context")
...
Leaving inner context
Callback: from inner context
Leaving outer context
Callback: from outer context

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29.7. abc — Classes de Base Abstraites

Code source: Lib/abc.py [https://github.com/python/cpython/tree/3.6/Lib/abc.py]

Le module fournit l’infrastructure pour définir les classes de bases abstraites (Abstract Base Class ou ABC en anglais) en Python, tel qu’indiqué dans la PEP 3119 [https://www.python.org/dev/peps/pep-3119]; voir la PEP pour la raison de son ajout à Python. (Voir également la PEP 3141 [https://www.python.org/dev/peps/pep-3141] et le module numbers pour ce qui concerne la hiérarchie de types pour les nombres basés sur les classes de base abstraites). Par la suite nous utiliserons l’abréviation ABC (Abstract Base Class) pour désigner une classe de base abstraite.

The collections module has some concrete classes that derive from ABCs; these can, of course, be further derived. In addition, the collections.abc submodule has some ABCs that can be used to test whether a class or instance provides a particular interface, for example, if it is hashable or if it is a mapping.

Ce module fournit la métaclasse ABCMeta pour définir les ABC ainsi que la classe d’aide ABC, cette dernière permettant de définir des ABC en utilisant l’héritage :

class abc.ABC

Classe d’aide qui a ABCMeta pour métaclasse. Avec cette classe, une ABC peut être créée simplement en héritant de ABC , ce qui permet d’éviter l’utilisation parfois déroutante de métaclasse, par exemple :

from abc import ABC

class MyABC(ABC):
    pass

Il est à noter que le type de ABC reste ABCMeta. En conséquence, hériter de ABC nécessite les précautions habituelles concernant l’utilisation de métaclasses : l’utilisation d’héritage multiple peut entrainer des conflits de métaclasses. Il est également possible de définir une ABC en passant l’argument nommé metaclass et en utilisant ABCMeta directement, par exemple :

from abc import ABCMeta

class MyABC(metaclass=ABCMeta):
    pass

Nouveau dans la version 3.4.

class abc.ABCMeta

Métaclasse pour définir des classes de base abstraites (ABC).

Utilisez cette métaclasse pour créer une ABC. Il est possible d’hériter d’une ABC directement, cette classe de base abstraite fonctionne alors comme une classe mixin. Vous pouvez également enregistrer une classe concrète sans lien (même une classe native) et des ABC comme « sous-classes virtuelles » – celles-ci et leur descendantes seront considérées comme des sous-classes de la classe de base abstraite par la fonction native issubclass(), mais les ABC enregistrées n’apparaitront pas dans leur ordre de résolution des méthodes (MRO pour Method Resolution Order en anglais). Les implémentations de méthodes définies par l’ABC ne seront pas appelable (pas même via super()). 1

Les classes dont la métaclasse est ABCMeta possèdent les méthodes suivantes :

register(subclass)

Enregistrer subclass en tant que sous-classe virtuelle de cette ABC. Par exemple :

from abc import ABC

class MyABC(ABC):
    pass

MyABC.register(tuple)

assert issubclass(tuple, MyABC)
assert isinstance((), MyABC)

Modifié dans la version 3.3: Renvoie la sous-classe enregistrée pour permettre l’utilisation en tant que décorateur de classe.

Modifié dans la version 3.4: Pour détecter les appels à register(), vous pouvez utiliser la fonction get_cache_token().

Vous pouvez également redéfinir cette méthode dans une ABC :

__subclasshook__(subclass)

(Doit être définie en tant que méthode de classe.)

Vérifie si subclass est considérée comme une sous-classe de cette ABC. Cela signifie que vous pouvez personnaliser le comportement de issubclass sans nécessiter d’appeler register() pour chacune des classes que vous souhaitez considérer comme sous-classe de l’ABC. (Cette méthode de classe est appelée par la méthode __subclasscheck__() de la classe de base abstraite).

Cette méthode doit renvoyer True, False ou NotImplemented. Si elle renvoie True, subclass est considérée comme sous-classe de cette ABC. Si elle renvoie False, la subclass n’est pas considérée une sous-classe de cette ABC même si elle l’aurait été en temps normal. Si elle renvoie NotImplemented, la vérification d’appartenance à la sous-classe continue via le mécanisme habituel.

Pour une illustration de ces concepts, voir cet exemple de définition de ABC :

class Foo:
    def __getitem__(self, index):
        ...
    def __len__(self):
        ...
    def get_iterator(self):
        return iter(self)

class MyIterable(ABC):

    @abstractmethod
    def __iter__(self):
        while False:
            yield None

    def get_iterator(self):
        return self.__iter__()

    @classmethod
    def __subclasshook__(cls, C):
        if cls is MyIterable:
            if any("__iter__" in B.__dict__ for B in C.__mro__):
                return True
        return NotImplemented

MyIterable.register(Foo)

L’ABC MyIterable définit la méthode d’itération __iter__() comme méthode abstraite. L’implémentation qui lui est donnée ici peut être appelée depuis les sous-classes. La méthode get_iterator() fait également partie de la classe de base abstraite MyIterable, mais elle n’a pas à être redéfinie dans les classes dérivées non-abstraites.

La méthode de classe __subclasshook__() définie ici dit que toute classe qui possède la méthode __iter__() dans son __dict__ (ou dans une de ses classes de base, accédée via la liste __mro__) est considérée également comme un MyIterable.

Enfin, la dernière ligne fait de Foo une sous-classe virtuelle de MyIterable, même si cette classe ne définit pas de méthode __iter__() (elle utilise l’ancien protocole d’itération qui se définit en termes de __len__() et __getitem__()). A noter que cela ne rendra pas le get_iterator de MyIterable disponible comme une méthode de Foo, get_iterator est donc implémenté séparément.

Le module abc fournit aussi le décorateur :

@abc.abstractmethod

Un décorateur marquant les méthodes comme abstraites.

Utiliser ce décorateur nécessite que la métaclasse de la classe soit ABCMeta ou soit dérivée de celle-ci. Une classe qui possède une méta-classe dérivée de ABCMeta ne peut pas être instanciée à moins que toutes ses méthodes et propriétés abstraites soient redéfinies. Les méthodes abstraites peuvent être appelées en utilisant n’importe quel des mécanismes d’appel à “super”. abstractmethod() peut être utilisée pour déclarer des méthodes abstraites pour les propriétés et descripteurs.

Python ne gère pas l’ajout dynamique de méthodes abstraites à une classe, il n’est pas non plus possible de modifier l’état d’abstraction d’une méthode ou d’une classe une fois celle-ci créée. abstractmethod() n’affecte que les sous-classes dérivées utilisant l’héritage classique. Les « sous-classes virtuelles » enregistrées avec la méthode register() de l’ABC ne sont pas affectées.

Quand le décorateur abstractmethod() est utilisé en même temps que d’autres descripteurs de méthodes, il doit être appliqué en tant que décorateur le plus interne. Voir les exemples d’utilisation suivants :

class C(ABC):
    @abstractmethod
    def my_abstract_method(self, ...):
        ...
    @classmethod
    @abstractmethod
    def my_abstract_classmethod(cls, ...):
        ...
    @staticmethod
    @abstractmethod
    def my_abstract_staticmethod(...):
        ...

    @property
    @abstractmethod
    def my_abstract_property(self):
        ...
    @my_abstract_property.setter
    @abstractmethod
    def my_abstract_property(self, val):
        ...

    @abstractmethod
    def _get_x(self):
        ...
    @abstractmethod
    def _set_x(self, val):
        ...
    x = property(_get_x, _set_x)

In order to correctly interoperate with the abstract base class machinery, the descriptor must identify itself as abstract using __isabstractmethod__. In general, this attribute should be True if any of the methods used to compose the descriptor are abstract. For example, Python’s built-in property does the equivalent of:

class Descriptor:
    ...
    @property
    def __isabstractmethod__(self):
        return any(getattr(f, '__isabstractmethod__', False) for
                   f in (self._fget, self._fset, self._fdel))

Note

Contrairement aux méthodes abstraites Java, ces méthodes abstraites peuvent être implémentées. Cette implémentation peut être appelée via le mécanisme super() depuis la classe qui la redéfinit. C’est typiquement utile pour y appeler super et ainsi coopérer correctement dans un environnement utilisant de l’héritage multiple.

Le module abc gère également les décorateurs historiques suivants :

@abc.abstractclassmethod

Nouveau dans la version 3.2.

Obsolète depuis la version 3.3: Il est désormais possible d’utiliser classmethod avec abstractmethod(), cela rend ce décorateur redondant.

Sous-classe du décorateur natif classmethod() qui indique une méthode de classe ( classmethod ) abstraite. En dehors de cela, est similaire à abstractmethod().

Ce cas spécial est obsolète car le décorateur classmethod() est désormais correctement identifié comme abstrait quand il est appliqué à une méthode abstraite :

class C(ABC):
    @classmethod
    @abstractmethod
    def my_abstract_classmethod(cls, ...):
        ...

@abc.abstractstaticmethod

Nouveau dans la version 3.2.

Obsolète depuis la version 3.3: Il est désormais possible d’utiliser staticmethod avec abstractmethod(), cela rend ce décorateur redondant.

Sous-classe du décorateur natif classmethod() qui indique une méthode statique ( staticmethod ) abstraite. En dehors de cela, est similaire à abstractmethod().

Ce cas spécial est obsolète car le décorateur staticmethod() est désormais correctement identifié comme abstrait quand appliqué à une méthode abstraite :

class C(ABC):
    @staticmethod
    @abstractmethod
    def my_abstract_staticmethod(...):
        ...

@abc.abstractproperty

Obsolète depuis la version 3.3: Il est désormais possible d’utiliser property, property.getter(), property.setter() et property.deleter() avec abstractmethod(), ce qui rend ce décorateur redondant.

Sous-classe de property(), qui indique une propriété abstraite.

Ce cas spécial est obsolète car le décorateur property() est désormais correctement identifié comme abstrait quand appliqué à une méthode abstraite :

class C(ABC):
    @property
    @abstractmethod
    def my_abstract_property(self):
        ...

L’exemple ci-dessus définit une propriété en lecture seule. Vous pouvez également définir une propriété en lecture-écriture abstraite en indiquant une ou plusieurs des méthodes sous-jacentes comme abstraite :

class C(ABC):
    @property
    def x(self):
        ...

    @x.setter
    @abstractmethod
    def x(self, val):
        ...

Si seuls certains composants sont abstraits, seuls ces composants abstraits nécessitent d’être mis à jour pour créer une propriété concrète dans une sous-classe :

class D(C):
    @C.x.setter
    def x(self, val):
        ...

Le module abc fournit également la fonction suivante :

abc.get_cache_token()

Renvoie le jeton de cache ( cache token) de l’ABC.

Le jeton est un objet opaque (qui implémente le test d’égalité) qui identifie la version actuelle du cache de l’ABC pour les sous-classes virtuelles. Le jeton change avec chaque appel à ABCMeta.register() sur n’importe quelle ABC.

Nouveau dans la version 3.4.

Notes

1

Les développeurs C++ noteront que le concept Python de classe de base virtuelle ( virtual base class ) n’est pas le même que celui de C++.

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29.8. atexit — Gestionnaire de fin de programme

Le module atexit définit des fonctions pour inscrire et désinscrire des fonctions de nettoyage. Les fonctions ainsi inscrites sont automatiquement exécutées au moment de l’arrêt normal de l’interpréteur. atexit exécute ces fonctions dans l’ordre inverse dans lequel elles ont été inscrites ; si vous inscrivez A, B, et C, au moment de l’arrêt de l’interpréteur elles seront exécutées dans l’ordre C, B, A.

Note: Les fonctions inscrites via ce module ne sont pas appelées quand le programme est tué par un signal non géré par Python, quand une erreur fatale interne de Python est détectée, ou quand os._exit() est appelé.

atexit.register(func, *args, **kwargs)

Inscrit func comme une fonction à exécuter au moment de l’arrêt de l’interpréteur. Tout argument optionnel qui doit être passé à func doit être passé comme argument à register(). Il est possible d’inscrire les mêmes fonctions et arguments plus d’une fois.

Lors d’un arrêt normal du programme (par exemple, si sys.exit() est appelée ou l’exécution du module principal se termine), toutes les fonctions inscrites sont appelées, dans l’ordre de la dernière arrivée, première servie. La supposition est que les modules les plus bas niveau vont normalement être importés avant les modules haut niveau et ainsi être nettoyés en dernier.

Si une exception est levée durant l’exécution du gestionnaire de fin de programme, une trace d’appels est affichée (à moins que SystemExit ait été levée) et les informations de l’exception sont sauvegardées. Une fois que tous les gestionnaires de fin de programme ont eu une chance de s’exécuter, la dernière exception à avoir été levée l’est de nouveau.

Cette fonction renvoie func, ce qui rend possible de l’utiliser en tant que décorateur.

atexit.unregister(func)

Retire func de la liste des fonctions à exécuter à l’arrêt de l’interpréteur. Après avoir appelé unregister(), func est garantie de ne pas être appelée à l’arrêt de l’interpréteur, même si elle a été inscrite plus d’une fois. unregister() ne fait rien et reste muette dans le cas où func n’a pas été inscrite précédemment.

Voir aussi

Module readline

Un exemple utile de l’usage de atexit pour lire et écrire des fichiers d’historique readline.

29.8.1. Exemple avec atexit

Le simple exemple suivant démontre comment un module peut initialiser un compteur depuis un fichier quand il est importé, et sauver le valeur mise à jour du compteur automatiquement quand le programme se termine, sans avoir besoin que l’application fasse un appel explicite dans ce module au moment de l’arrêt de l’interpréteur.

try:
    with open("counterfile") as infile:
        _count = int(infile.read())
except FileNotFoundError:
    _count = 0

def incrcounter(n):
    global _count
    _count = _count + n

def savecounter():
    with open("counterfile", "w") as outfile:
        outfile.write("%d" % _count)

import atexit
atexit.register(savecounter)

Les arguments positionnels et par mot-clé peuvent aussi être passés à register() afin d’être repassés à la fonction inscrite lors de son appel :

def goodbye(name, adjective):
    print('Goodbye, %s, it was %s to meet you.' % (name, adjective))

import atexit
atexit.register(goodbye, 'Donny', 'nice')

# or:
atexit.register(goodbye, adjective='nice', name='Donny')

Utilisation en tant que décorateur :

import atexit

@atexit.register
def goodbye():
    print("You are now leaving the Python sector.")

Ceci fonctionne uniquement avec des fonctions qui peuvent être appelées sans argument.

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29.9. traceback — Print or retrieve a stack traceback

Source code: Lib/traceback.py [https://github.com/python/cpython/tree/3.6/Lib/traceback.py]

This module provides a standard interface to extract, format and print stack traces of Python programs. It exactly mimics the behavior of the Python interpreter when it prints a stack trace. This is useful when you want to print stack traces under program control, such as in a « wrapper » around the interpreter.

The module uses traceback objects — this is the object type that is stored in the sys.last_traceback variable and returned as the third item from sys.exc_info().

Le module définit les fonctions suivantes :

traceback.print_tb(tb, limit=None, file=None)

Print up to limit stack trace entries from traceback object tb (starting from the caller’s frame) if limit is positive. Otherwise, print the last abs(limit) entries. If limit is omitted or None, all entries are printed. If file is omitted or None, the output goes to sys.stderr; otherwise it should be an open file or file-like object to receive the output.

Modifié dans la version 3.5: Added negative limit support.

traceback.print_exception(etype, value, tb, limit=None, file=None, chain=True)

Print exception information and stack trace entries from traceback object tb to file. This differs from print_tb() in the following ways:

if tb is not None, it prints a header Traceback (most recent call last):

it prints the exception etype and value after the stack trace

if type(value) is SyntaxError and value has the appropriate format, it prints the line where the syntax error occurred with a caret indicating the approximate position of the error.

The optional limit argument has the same meaning as for print_tb(). If chain is true (the default), then chained exceptions (the __cause__ or __context__ attributes of the exception) will be printed as well, like the interpreter itself does when printing an unhandled exception.

Modifié dans la version 3.5: The etype argument is ignored and inferred from the type of value.

traceback.print_exc(limit=None, file=None, chain=True)

This is a shorthand for print_exception(*sys.exc_info(), limit, file, chain).

traceback.print_last(limit=None, file=None, chain=True)

This is a shorthand for print_exception(sys.last_type, sys.last_value, sys.last_traceback, limit, file, chain). In general it will work only after an exception has reached an interactive prompt (see sys.last_type).

traceback.print_stack(f=None, limit=None, file=None)

Print up to limit stack trace entries (starting from the invocation point) if limit is positive. Otherwise, print the last abs(limit) entries. If limit is omitted or None, all entries are printed. The optional f argument can be used to specify an alternate stack frame to start. The optional file argument has the same meaning as for print_tb().

Modifié dans la version 3.5: Added negative limit support.

traceback.extract_tb(tb, limit=None)

Return a StackSummary object representing a list of « pre-processed » stack trace entries extracted from the traceback object tb. It is useful for alternate formatting of stack traces. The optional limit argument has the same meaning as for print_tb(). A « pre-processed » stack trace entry is a FrameSummary object containing attributes filename, lineno, name, and line representing the information that is usually printed for a stack trace. The line is a string with leading and trailing whitespace stripped; if the source is not available it is None.

traceback.extract_stack(f=None, limit=None)

Extract the raw traceback from the current stack frame. The return value has the same format as for extract_tb(). The optional f and limit arguments have the same meaning as for print_stack().

traceback.format_list(extracted_list)

Given a list of tuples or FrameSummary objects as returned by extract_tb() or extract_stack(), return a list of strings ready for printing. Each string in the resulting list corresponds to the item with the same index in the argument list. Each string ends in a newline; the strings may contain internal newlines as well, for those items whose source text line is not None.

traceback.format_exception_only(etype, value)

Format the exception part of a traceback. The arguments are the exception type and value such as given by sys.last_type and sys.last_value. The return value is a list of strings, each ending in a newline. Normally, the list contains a single string; however, for SyntaxError exceptions, it contains several lines that (when printed) display detailed information about where the syntax error occurred. The message indicating which exception occurred is the always last string in the list.

traceback.format_exception(etype, value, tb, limit=None, chain=True)

Format a stack trace and the exception information. The arguments have the same meaning as the corresponding arguments to print_exception(). The return value is a list of strings, each ending in a newline and some containing internal newlines. When these lines are concatenated and printed, exactly the same text is printed as does print_exception().

Modifié dans la version 3.5: The etype argument is ignored and inferred from the type of value.

traceback.format_exc(limit=None, chain=True)

This is like print_exc(limit) but returns a string instead of printing to a file.

traceback.format_tb(tb, limit=None)

A shorthand for format_list(extract_tb(tb, limit)).

traceback.format_stack(f=None, limit=None)

A shorthand for format_list(extract_stack(f, limit)).

traceback.clear_frames(tb)

Clears the local variables of all the stack frames in a traceback tb by calling the clear() method of each frame object.

Nouveau dans la version 3.4.

traceback.walk_stack(f)

Walk a stack following f.f_back from the given frame, yielding the frame and line number for each frame. If f is None, the current stack is used. This helper is used with StackSummary.extract().

Nouveau dans la version 3.5.

traceback.walk_tb(tb)

Walk a traceback following tb_next yielding the frame and line number for each frame. This helper is used with StackSummary.extract().

Nouveau dans la version 3.5.

The module also defines the following classes:

29.9.1. TracebackException Objects

Nouveau dans la version 3.5.

TracebackException objects are created from actual exceptions to capture data for later printing in a lightweight fashion.

class traceback.TracebackException(exc_type, exc_value, exc_traceback, *, limit=None, lookup_lines=True, capture_locals=False)

Capture an exception for later rendering. limit, lookup_lines and capture_locals are as for the StackSummary class.

Note that when locals are captured, they are also shown in the traceback.

__cause__

A TracebackException of the original __cause__.

__context__

A TracebackException of the original __context__.

__suppress_context__

The __suppress_context__ value from the original exception.

stack

A StackSummary representing the traceback.

exc_type

The class of the original traceback.

filename

For syntax errors - the file name where the error occurred.

lineno

For syntax errors - the line number where the error occurred.

text

For syntax errors - the text where the error occurred.

offset

For syntax errors - the offset into the text where the error occurred.

msg

For syntax errors - the compiler error message.

classmethod from_exception(exc, *, limit=None, lookup_lines=True, capture_locals=False)

Capture an exception for later rendering. limit, lookup_lines and capture_locals are as for the StackSummary class.

Note that when locals are captured, they are also shown in the traceback.

format(*, chain=True)

Format the exception.

If chain is not True, __cause__ and __context__ will not be formatted.

The return value is a generator of strings, each ending in a newline and some containing internal newlines. print_exception() is a wrapper around this method which just prints the lines to a file.

The message indicating which exception occurred is always the last string in the output.

format_exception_only()

Format the exception part of the traceback.

The return value is a generator of strings, each ending in a newline.

Normally, the generator emits a single string; however, for SyntaxError exceptions, it emits several lines that (when printed) display detailed information about where the syntax error occurred.

The message indicating which exception occurred is always the last string in the output.

29.9.2. StackSummary Objects

Nouveau dans la version 3.5.

StackSummary objects represent a call stack ready for formatting.

class traceback.StackSummary

classmethod extract(frame_gen, *, limit=None, lookup_lines=True, capture_locals=False)

Construct a StackSummary object from a frame generator (such as is returned by walk_stack() or walk_tb()).

If limit is supplied, only this many frames are taken from frame_gen. If lookup_lines is False, the returned FrameSummary objects will not have read their lines in yet, making the cost of creating the StackSummary cheaper (which may be valuable if it may not actually get formatted). If capture_locals is True the local variables in each FrameSummary are captured as object representations.

classmethod from_list(a_list)

Construct a StackSummary object from a supplied list of FrameSummary objects or old-style list of tuples. Each tuple should be a 4-tuple with filename, lineno, name, line as the elements.

format()

Returns a list of strings ready for printing. Each string in the resulting list corresponds to a single frame from the stack. Each string ends in a newline; the strings may contain internal newlines as well, for those items with source text lines.

For long sequences of the same frame and line, the first few repetitions are shown, followed by a summary line stating the exact number of further repetitions.

Modifié dans la version 3.6: Long sequences of repeated frames are now abbreviated.

29.9.3. FrameSummary Objects

Nouveau dans la version 3.5.

FrameSummary objects represent a single frame in a traceback.

class traceback.FrameSummary(filename, lineno, name, lookup_line=True, locals=None, line=None)

Represent a single frame in the traceback or stack that is being formatted or printed. It may optionally have a stringified version of the frames locals included in it. If lookup_line is False, the source code is not looked up until the FrameSummary has the line attribute accessed (which also happens when casting it to a tuple). line may be directly provided, and will prevent line lookups happening at all. locals is an optional local variable dictionary, and if supplied the variable representations are stored in the summary for later display.

29.9.4. Traceback Examples

This simple example implements a basic read-eval-print loop, similar to (but less useful than) the standard Python interactive interpreter loop. For a more complete implementation of the interpreter loop, refer to the code module.

import sys, traceback

def run_user_code(envdir):
    source = input(">>> ")
    try:
        exec(source, envdir)
    except Exception:
        print("Exception in user code:")
        print("-"*60)
        traceback.print_exc(file=sys.stdout)
        print("-"*60)

envdir = {}
while True:
    run_user_code(envdir)

The following example demonstrates the different ways to print and format the exception and traceback:

import sys, traceback

def lumberjack():
    bright_side_of_death()

def bright_side_of_death():
    return tuple()[0]

try:
    lumberjack()
except IndexError:
    exc_type, exc_value, exc_traceback = sys.exc_info()
    print("*** print_tb:")
    traceback.print_tb(exc_traceback, limit=1, file=sys.stdout)
    print("*** print_exception:")
    # exc_type below is ignored on 3.5 and later
    traceback.print_exception(exc_type, exc_value, exc_traceback,
                              limit=2, file=sys.stdout)
    print("*** print_exc:")
    traceback.print_exc(limit=2, file=sys.stdout)
    print("*** format_exc, first and last line:")
    formatted_lines = traceback.format_exc().splitlines()
    print(formatted_lines[0])
    print(formatted_lines[-1])
    print("*** format_exception:")
    # exc_type below is ignored on 3.5 and later
    print(repr(traceback.format_exception(exc_type, exc_value,
                                          exc_traceback)))
    print("*** extract_tb:")
    print(repr(traceback.extract_tb(exc_traceback)))
    print("*** format_tb:")
    print(repr(traceback.format_tb(exc_traceback)))
    print("*** tb_lineno:", exc_traceback.tb_lineno)

The output for the example would look similar to this:

*** print_tb:
  File "<doctest...>", line 10, in <module>
    lumberjack()
*** print_exception:
Traceback (most recent call last):
  File "<doctest...>", line 10, in <module>
    lumberjack()
  File "<doctest...>", line 4, in lumberjack
    bright_side_of_death()
IndexError: tuple index out of range
*** print_exc:
Traceback (most recent call last):
  File "<doctest...>", line 10, in <module>
    lumberjack()
  File "<doctest...>", line 4, in lumberjack
    bright_side_of_death()
IndexError: tuple index out of range
*** format_exc, first and last line:
Traceback (most recent call last):
IndexError: tuple index out of range
*** format_exception:
['Traceback (most recent call last):\n',
 '  File "<doctest...>", line 10, in <module>\n    lumberjack()\n',
 '  File "<doctest...>", line 4, in lumberjack\n    bright_side_of_death()\n',
 '  File "<doctest...>", line 7, in bright_side_of_death\n    return tuple()[0]\n',
 'IndexError: tuple index out of range\n']
*** extract_tb:
[<FrameSummary file <doctest...>, line 10 in <module>>,
 <FrameSummary file <doctest...>, line 4 in lumberjack>,
 <FrameSummary file <doctest...>, line 7 in bright_side_of_death>]
*** format_tb:
['  File "<doctest...>", line 10, in <module>\n    lumberjack()\n',
 '  File "<doctest...>", line 4, in lumberjack\n    bright_side_of_death()\n',
 '  File "<doctest...>", line 7, in bright_side_of_death\n    return tuple()[0]\n']
*** tb_lineno: 10

The following example shows the different ways to print and format the stack:

>>> import traceback
>>> def another_function():
...     lumberstack()
...
>>> def lumberstack():
...     traceback.print_stack()
...     print(repr(traceback.extract_stack()))
...     print(repr(traceback.format_stack()))
...
>>> another_function()
  File "<doctest>", line 10, in <module>
    another_function()
  File "<doctest>", line 3, in another_function
    lumberstack()
  File "<doctest>", line 6, in lumberstack
    traceback.print_stack()
[('<doctest>', 10, '<module>', 'another_function()'),
 ('<doctest>', 3, 'another_function', 'lumberstack()'),
 ('<doctest>', 7, 'lumberstack', 'print(repr(traceback.extract_stack()))')]
['  File "<doctest>", line 10, in <module>\n    another_function()\n',
 '  File "<doctest>", line 3, in another_function\n    lumberstack()\n',
 '  File "<doctest>", line 8, in lumberstack\n    print(repr(traceback.format_stack()))\n']

This last example demonstrates the final few formatting functions:

>>> import traceback
>>> traceback.format_list([('spam.py', 3, '<module>', 'spam.eggs()'),
...                        ('eggs.py', 42, 'eggs', 'return "bacon"')])
['  File "spam.py", line 3, in <module>\n    spam.eggs()\n',
 '  File "eggs.py", line 42, in eggs\n    return "bacon"\n']
>>> an_error = IndexError('tuple index out of range')
>>> traceback.format_exception_only(type(an_error), an_error)
['IndexError: tuple index out of range\n']

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29.10. __future__ — Définitions des futurs

Source code: Lib/_future_.py [https://github.com/python/cpython/tree/3.6/Lib/_future_.py]

Le module __future__ est un vrai module, et il a trois objectifs :

éviter de dérouter les outils existants qui analysent les instructions d’importation et s’attendent à trouver les modules qu’ils importent ;

s’assurer que les instructions *future* lancées sous les versions antérieures à 2.1 lèvent au moins des exceptions à l’exécution (l’importation du module __future__ échoue, car il n’y avait pas de module de ce nom avant 2.1) ;

Pour documenter le phasage de changements entraînant des incompatibilités : introduction, utilisation obligatoire. Il s’agit d’une forme de documentation exécutable, qui peut être inspectée par un programme en important __future__ et en examinant son contenu.

Chaque instruction dans __future__.py est de la forme :

FeatureName = _Feature(OptionalRelease, MandatoryRelease,
                       CompilerFlag)

où, normalement, OptionalRelease est inférieur à MandatoryRelease, et les deux sont des quintuplets de la même forme que sys.version_info :

(PY_MAJOR_VERSION, # the 2 in 2.1.0a3; an int
 PY_MINOR_VERSION, # the 1; an int
 PY_MICRO_VERSION, # the 0; an int
 PY_RELEASE_LEVEL, # "alpha", "beta", "candidate" or "final"; string
 PY_RELEASE_SERIAL # the 3; an int
)

OptionalRelease enregistre la première version dans laquelle la fonctionnalité a été acceptée.

Dans le cas d’un MandatoryRelease qui n’a pas encore eu lieu, MandatoryRelease prédit la release dans laquelle la fonctionnalité deviendra un élément du langage.

Sinon MandatoryRelease enregistre lorsque la fonctionnalité est devenue une partie du langage ; dans cette version ou les suivantes, les modules n’ont plus besoin d’une déclaration future pour utiliser la fonctionnalité en question, mais ils peuvent continuer à utiliser ces importations.

MandatoryRelease peut également être None, ce qui signifie qu’une fonction planifiée a été abandonnée.

Les instances de classe _Feature ont deux méthodes correspondantes, getOptionalRelease() et getMandatoryRelease().

CompilerFlag est un drapeau (chaque bit représente un champ) qui doit être passé en tant que quatrième argument à la fonction native compile() pour activer la fonctionnalité dans le code compilé dynamiquement. Cet indicateur est stocké dans l’attribut compiler_flag dans les instances de _Feature.

Aucune fonctionnalité ne sera jamais supprimée de __future__. Depuis son introduction dans Python 2.1, les fonctionnalités suivantes ont trouvé leur places dans le langage utilisant ce mécanisme :

fonctionnalité

optionnel dans

obligatoire dans

effet

nested_scopes

2.1.0b1

2.2

PEP 227 [https://www.python.org/dev/peps/pep-0227] : Portées imbriquées

générateurs

2.2.0a1

2.3

PEP 255 [https://www.python.org/dev/peps/pep-0255] : Générateurs simples

division

2.2.0a2

3.0

PEP 238 [https://www.python.org/dev/peps/pep-0238] : Changement de l’opérateur de division

absolute_import

2.5.0a1

3.0

PEP 328 [https://www.python.org/dev/peps/pep-0328] : Importations : multilignes et absolues/relatives (ressource en anglais)

with_statement

2.5.0a1

2.6

PEP 343 [https://www.python.org/dev/peps/pep-0343] : L’instruction « with »

print_function

2.6.0a2

3.0

PEP 3105 [https://www.python.org/dev/peps/pep-3105] : Transformation de print en fonction

unicode_literals

2.6.0a2

3.0

PEP 3112 [https://www.python.org/dev/peps/pep-3112] : Chaînes d’octets littéraux en Python 3000

generator_stop

3.5.0b1

3.7

PEP 479 [https://www.python.org/dev/peps/pep-0479] : Gestion de *StopIteration à l’intérieur des générateurs*

Voir aussi

L’instruction future

Comment le compilateur gère les importations « futures ».

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29.11. gc — Garbage Collector interface

This module provides an interface to the optional garbage collector. It provides the ability to disable the collector, tune the collection frequency, and set debugging options. It also provides access to unreachable objects that the collector found but cannot free. Since the collector supplements the reference counting already used in Python, you can disable the collector if you are sure your program does not create reference cycles. Automatic collection can be disabled by calling gc.disable(). To debug a leaking program call gc.set_debug(gc.DEBUG_LEAK). Notice that this includes gc.DEBUG_SAVEALL, causing garbage-collected objects to be saved in gc.garbage for inspection.

The gc module provides the following functions:

gc.enable()

Enable automatic garbage collection.

gc.disable()

Disable automatic garbage collection.

gc.isenabled()

Returns true if automatic collection is enabled.

gc.collect(generation=2)

With no arguments, run a full collection. The optional argument generation may be an integer specifying which generation to collect (from 0 to 2). A ValueError is raised if the generation number is invalid. The number of unreachable objects found is returned.

The free lists maintained for a number of built-in types are cleared whenever a full collection or collection of the highest generation (2) is run. Not all items in some free lists may be freed due to the particular implementation, in particular float.

gc.set_debug(flags)

Set the garbage collection debugging flags. Debugging information will be written to sys.stderr. See below for a list of debugging flags which can be combined using bit operations to control debugging.

gc.get_debug()

Return the debugging flags currently set.

gc.get_objects()

Returns a list of all objects tracked by the collector, excluding the list returned.

gc.get_stats()

Return a list of three per-generation dictionaries containing collection statistics since interpreter start. The number of keys may change in the future, but currently each dictionary will contain the following items:

collections is the number of times this generation was collected;

collected is the total number of objects collected inside this generation;

uncollectable is the total number of objects which were found to be uncollectable (and were therefore moved to the garbage list) inside this generation.

Nouveau dans la version 3.4.

gc.set_threshold(threshold0[, threshold1[, threshold2]])

Set the garbage collection thresholds (the collection frequency). Setting threshold0 to zero disables collection.

The GC classifies objects into three generations depending on how many collection sweeps they have survived. New objects are placed in the youngest generation (generation 0). If an object survives a collection it is moved into the next older generation. Since generation 2 is the oldest generation, objects in that generation remain there after a collection. In order to decide when to run, the collector keeps track of the number object allocations and deallocations since the last collection. When the number of allocations minus the number of deallocations exceeds threshold0, collection starts. Initially only generation 0 is examined. If generation 0 has been examined more than threshold1 times since generation 1 has been examined, then generation 1 is examined as well. Similarly, threshold2 controls the number of collections of generation 1 before collecting generation 2.

gc.get_count()

Return the current collection counts as a tuple of (count0, count1, count2).

gc.get_threshold()

Return the current collection thresholds as a tuple of (threshold0, threshold1, threshold2).

gc.get_referrers(*objs)

Return the list of objects that directly refer to any of objs. This function will only locate those containers which support garbage collection; extension types which do refer to other objects but do not support garbage collection will not be found.

Note that objects which have already been dereferenced, but which live in cycles and have not yet been collected by the garbage collector can be listed among the resulting referrers. To get only currently live objects, call collect() before calling get_referrers().

Care must be taken when using objects returned by get_referrers() because some of them could still be under construction and hence in a temporarily invalid state. Avoid using get_referrers() for any purpose other than debugging.

gc.get_referents(*objs)

Return a list of objects directly referred to by any of the arguments. The referents returned are those objects visited by the arguments” C-level tp_traverse methods (if any), and may not be all objects actually directly reachable. tp_traverse methods are supported only by objects that support garbage collection, and are only required to visit objects that may be involved in a cycle. So, for example, if an integer is directly reachable from an argument, that integer object may or may not appear in the result list.

gc.is_tracked(obj)

Returns True if the object is currently tracked by the garbage collector, False otherwise. As a general rule, instances of atomic types aren’t tracked and instances of non-atomic types (containers, user-defined objects…) are. However, some type-specific optimizations can be present in order to suppress the garbage collector footprint of simple instances (e.g. dicts containing only atomic keys and values):

>>> gc.is_tracked(0)
False
>>> gc.is_tracked("a")
False
>>> gc.is_tracked([])
True
>>> gc.is_tracked({})
False
>>> gc.is_tracked({"a": 1})
False
>>> gc.is_tracked({"a": []})
True

Nouveau dans la version 3.1.

The following variables are provided for read-only access (you can mutate the values but should not rebind them):

gc.garbage

A list of objects which the collector found to be unreachable but could not be freed (uncollectable objects). Starting with Python 3.4, this list should be empty most of the time, except when using instances of C extension types with a non-NULL tp_del slot.

If DEBUG_SAVEALL is set, then all unreachable objects will be added to this list rather than freed.

Modifié dans la version 3.2: If this list is non-empty at interpreter shutdown, a ResourceWarning is emitted, which is silent by default. If DEBUG_UNCOLLECTABLE is set, in addition all uncollectable objects are printed.

Modifié dans la version 3.4: Following PEP 442 [https://www.python.org/dev/peps/pep-0442], objects with a __del__() method don’t end up in gc.garbage anymore.

gc.callbacks

A list of callbacks that will be invoked by the garbage collector before and after collection. The callbacks will be called with two arguments, phase and info.

phase can be one of two values:

« start »: The garbage collection is about to start.

« stop »: The garbage collection has finished.

info is a dict providing more information for the callback. The following keys are currently defined:

« generation »: The oldest generation being collected.

« collected »: When phase is « stop », the number of objects successfully collected.

« uncollectable »: When phase is « stop », the number of objects that could not be collected and were put in garbage.

Applications can add their own callbacks to this list. The primary use cases are:

Gathering statistics about garbage collection, such as how often various generations are collected, and how long the collection takes.

Allowing applications to identify and clear their own uncollectable types when they appear in garbage.

Nouveau dans la version 3.3.

The following constants are provided for use with set_debug():

gc.DEBUG_STATS

Print statistics during collection. This information can be useful when tuning the collection frequency.

gc.DEBUG_COLLECTABLE

Print information on collectable objects found.

gc.DEBUG_UNCOLLECTABLE

Print information of uncollectable objects found (objects which are not reachable but cannot be freed by the collector). These objects will be added to the garbage list.

Modifié dans la version 3.2: Also print the contents of the garbage list at interpreter shutdown, if it isn’t empty.

gc.DEBUG_SAVEALL

When set, all unreachable objects found will be appended to garbage rather than being freed. This can be useful for debugging a leaking program.

gc.DEBUG_LEAK

The debugging flags necessary for the collector to print information about a leaking program (equal to DEBUG_COLLECTABLE | DEBUG_UNCOLLECTABLE | DEBUG_SAVEALL).

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29.12. inspect — Inspect live objects

Code source : Lib/inspect.py [https://github.com/python/cpython/tree/3.6/Lib/inspect.py]

The inspect module provides several useful functions to help get information about live objects such as modules, classes, methods, functions, tracebacks, frame objects, and code objects. For example, it can help you examine the contents of a class, retrieve the source code of a method, extract and format the argument list for a function, or get all the information you need to display a detailed traceback.

There are four main kinds of services provided by this module: type checking, getting source code, inspecting classes and functions, and examining the interpreter stack.

29.12.1. Types and members

The getmembers() function retrieves the members of an object such as a class or module. The functions whose names begin with « is » are mainly provided as convenient choices for the second argument to getmembers(). They also help you determine when you can expect to find the following special attributes:

Type

Attribut

Description

module

__doc__

documentation string

__file__

filename (missing for built-in modules)

classe

__doc__

documentation string

__name__

name with which this class was defined

__qualname__

nom qualifié

__module__

name of module in which this class was defined

méthode

__doc__

documentation string

__name__

name with which this method was defined

__qualname__

nom qualifié

__func__

function object containing implementation of method

__self__

instance to which this method is bound, or None

fonction

__doc__

documentation string

__name__

name with which this function was defined

__qualname__

nom qualifié

__code__

code object containing compiled function bytecode

__defaults__

tuple of any default values for positional or keyword parameters

__kwdefaults__

mapping of any default values for keyword-only parameters

__globals__

global namespace in which this function was defined

__annotations__

mapping of parameters names to annotations; "return" key is reserved for return annotations.

traceback

tb_frame

frame object at this level

tb_lasti

index of last attempted instruction in bytecode

tb_lineno

current line number in Python source code

tb_next

next inner traceback object (called by this level)

frame

f_back

next outer frame object (this frame’s caller)

f_builtins

builtins namespace seen by this frame

f_code

code object being executed in this frame

f_globals

global namespace seen by this frame

f_lasti

index of last attempted instruction in bytecode

f_lineno

current line number in Python source code

f_locals

local namespace seen by this frame

f_trace

tracing function for this frame, or None

code

co_argcount

number of arguments (not including keyword only arguments, * or ** args)

co_code

string of raw compiled bytecode

co_cellvars

tuple of names of cell variables (referenced by containing scopes)

co_consts

tuple of constants used in the bytecode

co_filename

name of file in which this code object was created

co_firstlineno

number of first line in Python source code

co_flags

bitmap of CO_* flags, read more here

co_lnotab

encoded mapping of line numbers to bytecode indices

co_freevars

tuple of names of free variables (referenced via a function’s closure)

co_kwonlyargcount

number of keyword only arguments (not including ** arg)

co_name

name with which this code object was defined

co_names

tuple of names of local variables

co_nlocals

number of local variables

co_stacksize

virtual machine stack space required

co_varnames

tuple of names of arguments and local variables

générateur

__name__

name

__qualname__

nom qualifié

gi_frame

frame

gi_running

is the generator running?

gi_code

code

gi_yieldfrom

object being iterated by yield from, or None

coroutine

__name__

name

__qualname__

nom qualifié

cr_await

object being awaited on, or None

cr_frame

frame

cr_running

is the coroutine running?

cr_code

code

builtin

__doc__

documentation string

__name__

original name of this function or method

__qualname__

nom qualifié

__self__

instance to which a method is bound, or None

Modifié dans la version 3.5: Add __qualname__ and gi_yieldfrom attributes to generators.

The __name__ attribute of generators is now set from the function name, instead of the code name, and it can now be modified.

inspect.getmembers(object[, predicate])

Return all the members of an object in a list of (name, value) pairs sorted by name. If the optional predicate argument is supplied, only members for which the predicate returns a true value are included.

Note

getmembers() will only return class attributes defined in the metaclass when the argument is a class and those attributes have been listed in the metaclass” custom __dir__().

inspect.getmodulename(path)

Return the name of the module named by the file path, without including the names of enclosing packages. The file extension is checked against all of the entries in importlib.machinery.all_suffixes(). If it matches, the final path component is returned with the extension removed. Otherwise, None is returned.

Note that this function only returns a meaningful name for actual Python modules - paths that potentially refer to Python packages will still return None.

Modifié dans la version 3.3: The function is based directly on importlib.

inspect.ismodule(object)

Return true if the object is a module.

inspect.isclass(object)

Return true if the object is a class, whether built-in or created in Python code.

inspect.ismethod(object)

Return true if the object is a bound method written in Python.

inspect.isfunction(object)

Return true if the object is a Python function, which includes functions created by a lambda expression.

inspect.isgeneratorfunction(object)

Return true if the object is a Python generator function.

inspect.isgenerator(object)

Return true if the object is a generator.

inspect.iscoroutinefunction(object)

Return true if the object is a coroutine function (a function defined with an async def syntax).

Nouveau dans la version 3.5.

inspect.iscoroutine(object)

Return true if the object is a coroutine created by an async def function.

Nouveau dans la version 3.5.

inspect.isawaitable(object)

Return true if the object can be used in await expression.

Can also be used to distinguish generator-based coroutines from regular generators:

def gen():
    yield
@types.coroutine
def gen_coro():
    yield

assert not isawaitable(gen())
assert isawaitable(gen_coro())

Nouveau dans la version 3.5.

inspect.isasyncgenfunction(object)

Return true if the object is an asynchronous generator function, for example:

>>> async def agen():
...     yield 1
...
>>> inspect.isasyncgenfunction(agen)
True

Nouveau dans la version 3.6.

inspect.isasyncgen(object)

Return true if the object is an asynchronous generator iterator created by an asynchronous generator function.

Nouveau dans la version 3.6.

inspect.istraceback(object)

Return true if the object is a traceback.

inspect.isframe(object)

Return true if the object is a frame.

inspect.iscode(object)

Return true if the object is a code.

inspect.isbuiltin(object)

Return true if the object is a built-in function or a bound built-in method.

inspect.isroutine(object)

Return true if the object is a user-defined or built-in function or method.

inspect.isabstract(object)

Return true if the object is an abstract base class.

inspect.ismethoddescriptor(object)

Return true if the object is a method descriptor, but not if ismethod(), isclass(), isfunction() or isbuiltin() are true.

This, for example, is true of int.__add__. An object passing this test has a __get__() method but not a __set__() method, but beyond that the set of attributes varies. A __name__ attribute is usually sensible, and __doc__ often is.

Methods implemented via descriptors that also pass one of the other tests return false from the ismethoddescriptor() test, simply because the other tests promise more – you can, e.g., count on having the __func__ attribute (etc) when an object passes ismethod().

inspect.isdatadescriptor(object)

Return true if the object is a data descriptor.

Data descriptors have both a __get__ and a __set__ method. Examples are properties (defined in Python), getsets, and members. The latter two are defined in C and there are more specific tests available for those types, which is robust across Python implementations. Typically, data descriptors will also have __name__ and __doc__ attributes (properties, getsets, and members have both of these attributes), but this is not guaranteed.

inspect.isgetsetdescriptor(object)

Return true if the object is a getset descriptor.

CPython implementation detail: getsets are attributes defined in extension modules via PyGetSetDef structures. For Python implementations without such types, this method will always return False.

inspect.ismemberdescriptor(object)

Return true if the object is a member descriptor.

CPython implementation detail: Member descriptors are attributes defined in extension modules via PyMemberDef structures. For Python implementations without such types, this method will always return False.

29.12.2. Retrieving source code

inspect.getdoc(object)

Get the documentation string for an object, cleaned up with cleandoc(). If the documentation string for an object is not provided and the object is a class, a method, a property or a descriptor, retrieve the documentation string from the inheritance hierarchy.

Modifié dans la version 3.5: Documentation strings are now inherited if not overridden.

inspect.getcomments(object)

Return in a single string any lines of comments immediately preceding the object’s source code (for a class, function, or method), or at the top of the Python source file (if the object is a module). If the object’s source code is unavailable, return None. This could happen if the object has been defined in C or the interactive shell.

inspect.getfile(object)

Return the name of the (text or binary) file in which an object was defined. This will fail with a TypeError if the object is a built-in module, class, or function.

inspect.getmodule(object)

Try to guess which module an object was defined in.

inspect.getsourcefile(object)

Return the name of the Python source file in which an object was defined. This will fail with a TypeError if the object is a built-in module, class, or function.

inspect.getsourcelines(object)

Return a list of source lines and starting line number for an object. The argument may be a module, class, method, function, traceback, frame, or code object. The source code is returned as a list of the lines corresponding to the object and the line number indicates where in the original source file the first line of code was found. An OSError is raised if the source code cannot be retrieved.

Modifié dans la version 3.3: OSError is raised instead of IOError, now an alias of the former.

inspect.getsource(object)

Return the text of the source code for an object. The argument may be a module, class, method, function, traceback, frame, or code object. The source code is returned as a single string. An OSError is raised if the source code cannot be retrieved.

Modifié dans la version 3.3: OSError is raised instead of IOError, now an alias of the former.

inspect.cleandoc(doc)

Clean up indentation from docstrings that are indented to line up with blocks of code.

All leading whitespace is removed from the first line. Any leading whitespace that can be uniformly removed from the second line onwards is removed. Empty lines at the beginning and end are subsequently removed. Also, all tabs are expanded to spaces.

29.12.3. Introspecting callables with the Signature object

Nouveau dans la version 3.3.

The Signature object represents the call signature of a callable object and its return annotation. To retrieve a Signature object, use the signature() function.

inspect.signature(callable, *, follow_wrapped=True)

Return a Signature object for the given callable:

>>> from inspect import signature
>>> def foo(a, *, b:int, **kwargs):
...     pass

>>> sig = signature(foo)

>>> str(sig)
'(a, *, b:int, **kwargs)'

>>> str(sig.parameters['b'])
'b:int'

>>> sig.parameters['b'].annotation
<class 'int'>

Accepts a wide range of python callables, from plain functions and classes to functools.partial() objects.

Raises ValueError if no signature can be provided, and TypeError if that type of object is not supported.

Nouveau dans la version 3.5: follow_wrapped parameter. Pass False to get a signature of callable specifically (callable.__wrapped__ will not be used to unwrap decorated callables.)

Note

Some callables may not be introspectable in certain implementations of Python. For example, in CPython, some built-in functions defined in C provide no metadata about their arguments.

class inspect.Signature(parameters=None, *, return_annotation=Signature.empty)

A Signature object represents the call signature of a function and its return annotation. For each parameter accepted by the function it stores a Parameter object in its parameters collection.

The optional parameters argument is a sequence of Parameter objects, which is validated to check that there are no parameters with duplicate names, and that the parameters are in the right order, i.e. positional-only first, then positional-or-keyword, and that parameters with defaults follow parameters without defaults.

The optional return_annotation argument, can be an arbitrary Python object, is the « return » annotation of the callable.

Signature objects are immutable. Use Signature.replace() to make a modified copy.

Modifié dans la version 3.5: Signature objects are picklable and hashable.

empty

A special class-level marker to specify absence of a return annotation.

parameters

An ordered mapping of parameters” names to the corresponding Parameter objects.

return_annotation

The « return » annotation for the callable. If the callable has no « return » annotation, this attribute is set to Signature.empty.

bind(*args, **kwargs)

Create a mapping from positional and keyword arguments to parameters. Returns BoundArguments if *args and **kwargs match the signature, or raises a TypeError.

bind_partial(*args, **kwargs)

Works the same way as Signature.bind(), but allows the omission of some required arguments (mimics functools.partial() behavior.) Returns BoundArguments, or raises a TypeError if the passed arguments do not match the signature.

replace(*[, parameters][, return_annotation])

Create a new Signature instance based on the instance replace was invoked on. It is possible to pass different parameters and/or return_annotation to override the corresponding properties of the base signature. To remove return_annotation from the copied Signature, pass in Signature.empty.

>>> def test(a, b):
...     pass
>>> sig = signature(test)
>>> new_sig = sig.replace(return_annotation="new return anno")
>>> str(new_sig)
"(a, b) -> 'new return anno'"

classmethod from_callable(obj, *, follow_wrapped=True)

Return a Signature (or its subclass) object for a given callable obj. Pass follow_wrapped=False to get a signature of obj without unwrapping its __wrapped__ chain.

This method simplifies subclassing of Signature:

class MySignature(Signature):
    pass
sig = MySignature.from_callable(min)
assert isinstance(sig, MySignature)

Nouveau dans la version 3.5.

class inspect.Parameter(name, kind, *, default=Parameter.empty, annotation=Parameter.empty)

Parameter objects are immutable. Instead of modifying a Parameter object, you can use Parameter.replace() to create a modified copy.

Modifié dans la version 3.5: Parameter objects are picklable and hashable.

empty

A special class-level marker to specify absence of default values and annotations.

name

The name of the parameter as a string. The name must be a valid Python identifier.

CPython implementation detail: CPython generates implicit parameter names of the form .0 on the code objects used to implement comprehensions and generator expressions.

Modifié dans la version 3.6: These parameter names are exposed by this module as names like implicit0.

default

The default value for the parameter. If the parameter has no default value, this attribute is set to Parameter.empty.

annotation

The annotation for the parameter. If the parameter has no annotation, this attribute is set to Parameter.empty.

kind

Describes how argument values are bound to the parameter. Possible values (accessible via Parameter, like Parameter.KEYWORD_ONLY):

Nom

Signification

POSITIONAL_ONLY

Value must be supplied as a positional argument.

Python has no explicit syntax for defining positional-only parameters, but many built-in and extension module functions (especially those that accept only one or two parameters) accept them.

POSITIONAL_OR_KEYWORD

Value may be supplied as either a keyword or positional argument (this is the standard binding behaviour for functions implemented in Python.)

VAR_POSITIONAL

A tuple of positional arguments that aren’t bound to any other parameter. This corresponds to a *args parameter in a Python function definition.

KEYWORD_ONLY

Value must be supplied as a keyword argument. Keyword only parameters are those which appear after a * or *args entry in a Python function definition.

VAR_KEYWORD

A dict of keyword arguments that aren’t bound to any other parameter. This corresponds to a **kwargs parameter in a Python function definition.

Example: print all keyword-only arguments without default values:

>>> def foo(a, b, *, c, d=10):
...     pass

>>> sig = signature(foo)
>>> for param in sig.parameters.values():
...     if (param.kind == param.KEYWORD_ONLY and
...                        param.default is param.empty):
...         print('Parameter:', param)
Parameter: c

replace(*[, name][, kind][, default][, annotation])

Create a new Parameter instance based on the instance replaced was invoked on. To override a Parameter attribute, pass the corresponding argument. To remove a default value or/and an annotation from a Parameter, pass Parameter.empty.

>>> from inspect import Parameter
>>> param = Parameter('foo', Parameter.KEYWORD_ONLY, default=42)
>>> str(param)
'foo=42'

>>> str(param.replace()) # Will create a shallow copy of 'param'
'foo=42'

>>> str(param.replace(default=Parameter.empty, annotation='spam'))
"foo:'spam'"

Modifié dans la version 3.4: In Python 3.3 Parameter objects were allowed to have name set to None if their kind was set to POSITIONAL_ONLY. This is no longer permitted.

class inspect.BoundArguments

Result of a Signature.bind() or Signature.bind_partial() call. Holds the mapping of arguments to the function’s parameters.

arguments

An ordered, mutable mapping (collections.OrderedDict) of parameters” names to arguments” values. Contains only explicitly bound arguments. Changes in arguments will reflect in args and kwargs.

Should be used in conjunction with Signature.parameters for any argument processing purposes.

Note

Arguments for which Signature.bind() or Signature.bind_partial() relied on a default value are skipped. However, if needed, use BoundArguments.apply_defaults() to add them.

args

A tuple of positional arguments values. Dynamically computed from the arguments attribute.

kwargs

A dict of keyword arguments values. Dynamically computed from the arguments attribute.

signature

A reference to the parent Signature object.

apply_defaults()

Set default values for missing arguments.

For variable-positional arguments (*args) the default is an empty tuple.

For variable-keyword arguments (**kwargs) the default is an empty dict.

>>> def foo(a, b='ham', *args): pass
>>> ba = inspect.signature(foo).bind('spam')
>>> ba.apply_defaults()
>>> ba.arguments
OrderedDict([('a', 'spam'), ('b', 'ham'), ('args', ())])

Nouveau dans la version 3.5.

The args and kwargs properties can be used to invoke functions:

def test(a, *, b):
    ...

sig = signature(test)
ba = sig.bind(10, b=20)
test(*ba.args, **ba.kwargs)

Voir aussi

PEP 362 [https://www.python.org/dev/peps/pep-0362] - Function Signature Object.

The detailed specification, implementation details and examples.

29.12.4. Classes et fonctions

inspect.getclasstree(classes, unique=False)

Arrange the given list of classes into a hierarchy of nested lists. Where a nested list appears, it contains classes derived from the class whose entry immediately precedes the list. Each entry is a 2-tuple containing a class and a tuple of its base classes. If the unique argument is true, exactly one entry appears in the returned structure for each class in the given list. Otherwise, classes using multiple inheritance and their descendants will appear multiple times.

inspect.getargspec(func)

Get the names and default values of a Python function’s parameters. A named tuple ArgSpec(args, varargs, keywords, defaults) is returned. args is a list of the parameter names. varargs and keywords are the names of the * and ** parameters or None. defaults is a tuple of default argument values or None if there are no default arguments; if this tuple has n elements, they correspond to the last n elements listed in args.

Obsolète depuis la version 3.0: Use getfullargspec() for an updated API that is usually a drop-in replacement, but also correctly handles function annotations and keyword-only parameters.

Alternatively, use signature() and Signature Object, which provide a more structured introspection API for callables.

inspect.getfullargspec(func)

Get the names and default values of a Python function’s parameters. A named tuple is returned:

FullArgSpec(args, varargs, varkw, defaults, kwonlyargs, kwonlydefaults, annotations)

args is a list of the positional parameter names. varargs is the name of the * parameter or None if arbitrary positional arguments are not accepted. varkw is the name of the ** parameter or None if arbitrary keyword arguments are not accepted. defaults is an n-tuple of default argument values corresponding to the last n positional parameters, or None if there are no such defaults defined. kwonlyargs is a list of keyword-only parameter names. kwonlydefaults is a dictionary mapping parameter names from kwonlyargs to the default values used if no argument is supplied. annotations is a dictionary mapping parameter names to annotations. The special key "return" is used to report the function return value annotation (if any).

Note that signature() and Signature Object provide the recommended API for callable introspection, and support additional behaviours (like positional-only arguments) that are sometimes encountered in extension module APIs. This function is retained primarily for use in code that needs to maintain compatibility with the Python 2 inspect module API.

Modifié dans la version 3.4: This function is now based on signature(), but still ignores __wrapped__ attributes and includes the already bound first parameter in the signature output for bound methods.

Modifié dans la version 3.6: This method was previously documented as deprecated in favour of signature() in Python 3.5, but that decision has been reversed in order to restore a clearly supported standard interface for single-source Python 2/3 code migrating away from the legacy getargspec() API.

inspect.getargvalues(frame)

Get information about arguments passed into a particular frame. A named tuple ArgInfo(args, varargs, keywords, locals) is returned. args is a list of the argument names. varargs and keywords are the names of the * and ** arguments or None. locals is the locals dictionary of the given frame.

Note

This function was inadvertently marked as deprecated in Python 3.5.

inspect.formatargspec(args[, varargs, varkw, defaults, kwonlyargs, kwonlydefaults, annotations[, formatarg, formatvarargs, formatvarkw, formatvalue, formatreturns, formatannotations]])

Format a pretty argument spec from the values returned by getfullargspec().

The first seven arguments are (args, varargs, varkw, defaults, kwonlyargs, kwonlydefaults, annotations).

The other six arguments are functions that are called to turn argument names, * argument name, ** argument name, default values, return annotation and individual annotations into strings, respectively.

Par exemple :

>>> from inspect import formatargspec, getfullargspec
>>> def f(a: int, b: float):
...     pass
...
>>> formatargspec(*getfullargspec(f))
'(a: int, b: float)'

Obsolète depuis la version 3.5: Use signature() and Signature Object, which provide a better introspecting API for callables.

inspect.formatargvalues(args[, varargs, varkw, locals, formatarg, formatvarargs, formatvarkw, formatvalue])

Format a pretty argument spec from the four values returned by getargvalues(). The format* arguments are the corresponding optional formatting functions that are called to turn names and values into strings.

Note

This function was inadvertently marked as deprecated in Python 3.5.

inspect.getmro(cls)

Return a tuple of class cls’s base classes, including cls, in method resolution order. No class appears more than once in this tuple. Note that the method resolution order depends on cls’s type. Unless a very peculiar user-defined metatype is in use, cls will be the first element of the tuple.

inspect.getcallargs(func, *args, **kwds)

Bind the args and kwds to the argument names of the Python function or method func, as if it was called with them. For bound methods, bind also the first argument (typically named self) to the associated instance. A dict is returned, mapping the argument names (including the names of the * and ** arguments, if any) to their values from args and kwds. In case of invoking func incorrectly, i.e. whenever func(*args, **kwds) would raise an exception because of incompatible signature, an exception of the same type and the same or similar message is raised. For example:

>>> from inspect import getcallargs
>>> def f(a, b=1, *pos, **named):
...     pass
>>> getcallargs(f, 1, 2, 3) == {'a': 1, 'named': {}, 'b': 2, 'pos': (3,)}
True
>>> getcallargs(f, a=2, x=4) == {'a': 2, 'named': {'x': 4}, 'b': 1, 'pos': ()}
True
>>> getcallargs(f)
Traceback (most recent call last):
...
TypeError: f() missing 1 required positional argument: 'a'

Nouveau dans la version 3.2.

Obsolète depuis la version 3.5: Use Signature.bind() and Signature.bind_partial() instead.

inspect.getclosurevars(func)

Get the mapping of external name references in a Python function or method func to their current values. A named tuple ClosureVars(nonlocals, globals, builtins, unbound) is returned. nonlocals maps referenced names to lexical closure variables, globals to the function’s module globals and builtins to the builtins visible from the function body. unbound is the set of names referenced in the function that could not be resolved at all given the current module globals and builtins.

TypeError is raised if func is not a Python function or method.

Nouveau dans la version 3.3.

inspect.unwrap(func, *, stop=None)

Get the object wrapped by func. It follows the chain of __wrapped__ attributes returning the last object in the chain.

stop is an optional callback accepting an object in the wrapper chain as its sole argument that allows the unwrapping to be terminated early if the callback returns a true value. If the callback never returns a true value, the last object in the chain is returned as usual. For example, signature() uses this to stop unwrapping if any object in the chain has a __signature__ attribute defined.

ValueError is raised if a cycle is encountered.

Nouveau dans la version 3.4.

29.12.5. The interpreter stack

When the following functions return « frame records, » each record is a named tuple FrameInfo(frame, filename, lineno, function, code_context, index). The tuple contains the frame object, the filename, the line number of the current line, the function name, a list of lines of context from the source code, and the index of the current line within that list.

Modifié dans la version 3.5: Return a named tuple instead of a tuple.

Note

Keeping references to frame objects, as found in the first element of the frame records these functions return, can cause your program to create reference cycles. Once a reference cycle has been created, the lifespan of all objects which can be accessed from the objects which form the cycle can become much longer even if Python’s optional cycle detector is enabled. If such cycles must be created, it is important to ensure they are explicitly broken to avoid the delayed destruction of objects and increased memory consumption which occurs.

Though the cycle detector will catch these, destruction of the frames (and local variables) can be made deterministic by removing the cycle in a finally clause. This is also important if the cycle detector was disabled when Python was compiled or using gc.disable(). For example:

def handle_stackframe_without_leak():
    frame = inspect.currentframe()
    try:
        # do something with the frame
    finally:
        del frame

If you want to keep the frame around (for example to print a traceback later), you can also break reference cycles by using the frame.clear() method.

The optional context argument supported by most of these functions specifies the number of lines of context to return, which are centered around the current line.

inspect.getframeinfo(frame, context=1)

Get information about a frame or traceback object. A named tuple Traceback(filename, lineno, function, code_context, index) is returned.

inspect.getouterframes(frame, context=1)

Get a list of frame records for a frame and all outer frames. These frames represent the calls that lead to the creation of frame. The first entry in the returned list represents frame; the last entry represents the outermost call on frame’s stack.

Modifié dans la version 3.5: A list of named tuples FrameInfo(frame, filename, lineno, function, code_context, index) is returned.

inspect.getinnerframes(traceback, context=1)

Get a list of frame records for a traceback’s frame and all inner frames. These frames represent calls made as a consequence of frame. The first entry in the list represents traceback; the last entry represents where the exception was raised.

Modifié dans la version 3.5: A list of named tuples FrameInfo(frame, filename, lineno, function, code_context, index) is returned.

inspect.currentframe()

Return the frame object for the caller’s stack frame.

CPython implementation detail: This function relies on Python stack frame support in the interpreter, which isn’t guaranteed to exist in all implementations of Python. If running in an implementation without Python stack frame support this function returns None.

inspect.stack(context=1)

Return a list of frame records for the caller’s stack. The first entry in the returned list represents the caller; the last entry represents the outermost call on the stack.

Modifié dans la version 3.5: A list of named tuples FrameInfo(frame, filename, lineno, function, code_context, index) is returned.

inspect.trace(context=1)

Return a list of frame records for the stack between the current frame and the frame in which an exception currently being handled was raised in. The first entry in the list represents the caller; the last entry represents where the exception was raised.

Modifié dans la version 3.5: A list of named tuples FrameInfo(frame, filename, lineno, function, code_context, index) is returned.

29.12.6. Fetching attributes statically

Both getattr() and hasattr() can trigger code execution when fetching or checking for the existence of attributes. Descriptors, like properties, will be invoked and __getattr__() and __getattribute__() may be called.

For cases where you want passive introspection, like documentation tools, this can be inconvenient. getattr_static() has the same signature as getattr() but avoids executing code when it fetches attributes.

inspect.getattr_static(obj, attr, default=None)

Retrieve attributes without triggering dynamic lookup via the descriptor protocol, __getattr__() or __getattribute__().

Note: this function may not be able to retrieve all attributes that getattr can fetch (like dynamically created attributes) and may find attributes that getattr can’t (like descriptors that raise AttributeError). It can also return descriptors objects instead of instance members.

If the instance __dict__ is shadowed by another member (for example a property) then this function will be unable to find instance members.

Nouveau dans la version 3.2.

getattr_static() does not resolve descriptors, for example slot descriptors or getset descriptors on objects implemented in C. The descriptor object is returned instead of the underlying attribute.

You can handle these with code like the following. Note that for arbitrary getset descriptors invoking these may trigger code execution:

# example code for resolving the builtin descriptor types
class _foo:
    __slots__ = ['foo']

slot_descriptor = type(_foo.foo)
getset_descriptor = type(type(open(__file__)).name)
wrapper_descriptor = type(str.__dict__['__add__'])
descriptor_types = (slot_descriptor, getset_descriptor, wrapper_descriptor)

result = getattr_static(some_object, 'foo')
if type(result) in descriptor_types:
    try:
        result = result.__get__()
    except AttributeError:
        # descriptors can raise AttributeError to
        # indicate there is no underlying value
        # in which case the descriptor itself will
        # have to do
        pass

29.12.7. Current State of Generators and Coroutines

When implementing coroutine schedulers and for other advanced uses of generators, it is useful to determine whether a generator is currently executing, is waiting to start or resume or execution, or has already terminated. getgeneratorstate() allows the current state of a generator to be determined easily.

inspect.getgeneratorstate(generator)

Get current state of a generator-iterator.

Possible states are:

GEN_CREATED: Waiting to start execution.

GEN_RUNNING: Currently being executed by the interpreter.

GEN_SUSPENDED: Currently suspended at a yield expression.

GEN_CLOSED: Execution has completed.

Nouveau dans la version 3.2.

inspect.getcoroutinestate(coroutine)

Get current state of a coroutine object. The function is intended to be used with coroutine objects created by async def functions, but will accept any coroutine-like object that has cr_running and cr_frame attributes.

Possible states are:

CORO_CREATED: Waiting to start execution.

CORO_RUNNING: Currently being executed by the interpreter.

CORO_SUSPENDED: Currently suspended at an await expression.

CORO_CLOSED: Execution has completed.

Nouveau dans la version 3.5.

The current internal state of the generator can also be queried. This is mostly useful for testing purposes, to ensure that internal state is being updated as expected:

inspect.getgeneratorlocals(generator)

Get the mapping of live local variables in generator to their current values. A dictionary is returned that maps from variable names to values. This is the equivalent of calling locals() in the body of the generator, and all the same caveats apply.

If generator is a generator with no currently associated frame, then an empty dictionary is returned. TypeError is raised if generator is not a Python generator object.

CPython implementation detail: This function relies on the generator exposing a Python stack frame for introspection, which isn’t guaranteed to be the case in all implementations of Python. In such cases, this function will always return an empty dictionary.

Nouveau dans la version 3.3.

inspect.getcoroutinelocals(coroutine)

This function is analogous to getgeneratorlocals(), but works for coroutine objects created by async def functions.

Nouveau dans la version 3.5.

29.12.8. Code Objects Bit Flags

Python code objects have a co_flags attribute, which is a bitmap of the following flags:

inspect.CO_OPTIMIZED

The code object is optimized, using fast locals.

inspect.CO_NEWLOCALS

If set, a new dict will be created for the frame’s f_locals when the code object is executed.

inspect.CO_VARARGS

The code object has a variable positional parameter (*args-like).

inspect.CO_VARKEYWORDS

The code object has a variable keyword parameter (**kwargs-like).

inspect.CO_NESTED

The flag is set when the code object is a nested function.

inspect.CO_GENERATOR

The flag is set when the code object is a generator function, i.e. a generator object is returned when the code object is executed.

inspect.CO_NOFREE

The flag is set if there are no free or cell variables.

inspect.CO_COROUTINE

The flag is set when the code object is a coroutine function. When the code object is executed it returns a coroutine object. See PEP 492 [https://www.python.org/dev/peps/pep-0492] for more details.

Nouveau dans la version 3.5.

inspect.CO_ITERABLE_COROUTINE

The flag is used to transform generators into generator-based coroutines. Generator objects with this flag can be used in await expression, and can yield from coroutine objects. See PEP 492 [https://www.python.org/dev/peps/pep-0492] for more details.

Nouveau dans la version 3.5.

inspect.CO_ASYNC_GENERATOR

The flag is set when the code object is an asynchronous generator function. When the code object is executed it returns an asynchronous generator object. See PEP 525 [https://www.python.org/dev/peps/pep-0525] for more details.

Nouveau dans la version 3.6.

Note

The flags are specific to CPython, and may not be defined in other Python implementations. Furthermore, the flags are an implementation detail, and can be removed or deprecated in future Python releases. It’s recommended to use public APIs from the inspect module for any introspection needs.

29.12.9. Interface en ligne de commande

The inspect module also provides a basic introspection capability from the command line.

By default, accepts the name of a module and prints the source of that module. A class or function within the module can be printed instead by appended a colon and the qualified name of the target object.

--details

Print information about the specified object rather than the source code

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29.13. site — Site-specific configuration hook

Code source : Lib/site.py [https://github.com/python/cpython/tree/3.6/Lib/site.py]

This module is automatically imported during initialization. The automatic import can be suppressed using the interpreter’s -S option.

Importing this module will append site-specific paths to the module search path and add a few builtins, unless -S was used. In that case, this module can be safely imported with no automatic modifications to the module search path or additions to the builtins. To explicitly trigger the usual site-specific additions, call the site.main() function.

Modifié dans la version 3.3: Importing the module used to trigger paths manipulation even when using -S.

It starts by constructing up to four directories from a head and a tail part. For the head part, it uses sys.prefix and sys.exec_prefix; empty heads are skipped. For the tail part, it uses the empty string and then lib/site-packages (on Windows) or lib/pythonX.Y/site-packages (on Unix and Macintosh). For each of the distinct head-tail combinations, it sees if it refers to an existing directory, and if so, adds it to sys.path and also inspects the newly added path for configuration files.

Modifié dans la version 3.5: Support for the « site-python » directory has been removed.

If a file named « pyvenv.cfg » exists one directory above sys.executable, sys.prefix and sys.exec_prefix are set to that directory and it is also checked for site-packages (sys.base_prefix and sys.base_exec_prefix will always be the « real » prefixes of the Python installation). If « pyvenv.cfg » (a bootstrap configuration file) contains the key « include-system-site-packages » set to anything other than « false » (case-insensitive), the system-level prefixes will still also be searched for site-packages; otherwise they won’t.

A path configuration file is a file whose name has the form name.pth and exists in one of the four directories mentioned above; its contents are additional items (one per line) to be added to sys.path. Non-existing items are never added to sys.path, and no check is made that the item refers to a directory rather than a file. No item is added to sys.path more than once. Blank lines and lines beginning with # are skipped. Lines starting with import (followed by space or tab) are executed.

For example, suppose sys.prefix and sys.exec_prefix are set to /usr/local. The Python X.Y library is then installed in /usr/local/lib/pythonX.Y. Suppose this has a subdirectory /usr/local/lib/pythonX.Y/site-packages with three subsubdirectories, foo, bar and spam, and two path configuration files, foo.pth and bar.pth. Assume foo.pth contains the following:

# foo package configuration

foo
bar
bletch

and bar.pth contains:

# bar package configuration

bar

Then the following version-specific directories are added to sys.path, in this order:

/usr/local/lib/pythonX.Y/site-packages/bar
/usr/local/lib/pythonX.Y/site-packages/foo

Note that bletch is omitted because it doesn’t exist; the bar directory precedes the foo directory because bar.pth comes alphabetically before foo.pth; and spam is omitted because it is not mentioned in either path configuration file.

After these path manipulations, an attempt is made to import a module named sitecustomize, which can perform arbitrary site-specific customizations. It is typically created by a system administrator in the site-packages directory. If this import fails with an ImportError exception, it is silently ignored. If Python is started without output streams available, as with pythonw.exe on Windows (which is used by default to start IDLE), attempted output from sitecustomize is ignored. Any exception other than ImportError causes a silent and perhaps mysterious failure of the process.

After this, an attempt is made to import a module named usercustomize, which can perform arbitrary user-specific customizations, if ENABLE_USER_SITE is true. This file is intended to be created in the user site-packages directory (see below), which is part of sys.path unless disabled by -s. An ImportError will be silently ignored.

Note that for some non-Unix systems, sys.prefix and sys.exec_prefix are empty, and the path manipulations are skipped; however the import of sitecustomize and usercustomize is still attempted.

29.13.1. Readline configuration

On systems that support readline, this module will also import and configure the rlcompleter module, if Python is started in interactive mode and without the -S option. The default behavior is enable tab-completion and to use ~/.python_history as the history save file. To disable it, delete (or override) the sys.__interactivehook__ attribute in your sitecustomize or usercustomize module or your PYTHONSTARTUP file.

Modifié dans la version 3.4: Activation of rlcompleter and history was made automatic.

29.13.2. Module contents

site.PREFIXES

A list of prefixes for site-packages directories.

site.ENABLE_USER_SITE

Flag showing the status of the user site-packages directory. True means that it is enabled and was added to sys.path. False means that it was disabled by user request (with -s or PYTHONNOUSERSITE). None means it was disabled for security reasons (mismatch between user or group id and effective id) or by an administrator.

site.USER_SITE

Path to the user site-packages for the running Python. Can be None if getusersitepackages() hasn’t been called yet. Default value is ~/.local/lib/pythonX.Y/site-packages for UNIX and non-framework Mac OS X builds, ~/Library/Python/X.Y/lib/python/site-packages for Mac framework builds, and %APPDATA%\Python\PythonXY\site-packages on Windows. This directory is a site directory, which means that .pth files in it will be processed.

site.USER_BASE

Path to the base directory for the user site-packages. Can be None if getuserbase() hasn’t been called yet. Default value is ~/.local for UNIX and Mac OS X non-framework builds, ~/Library/Python/X.Y for Mac framework builds, and %APPDATA%\Python for Windows. This value is used by Distutils to compute the installation directories for scripts, data files, Python modules, etc. for the user installation scheme. See also PYTHONUSERBASE.

site.main()

Adds all the standard site-specific directories to the module search path. This function is called automatically when this module is imported, unless the Python interpreter was started with the -S flag.

Modifié dans la version 3.3: This function used to be called unconditionally.

site.addsitedir(sitedir, known_paths=None)

Add a directory to sys.path and process its .pth files. Typically used in sitecustomize or usercustomize (see above).

site.getsitepackages()

Return a list containing all global site-packages directories.

Nouveau dans la version 3.2.

site.getuserbase()

Return the path of the user base directory, USER_BASE. If it is not initialized yet, this function will also set it, respecting PYTHONUSERBASE.

Nouveau dans la version 3.2.

site.getusersitepackages()

Return the path of the user-specific site-packages directory, USER_SITE. If it is not initialized yet, this function will also set it, respecting PYTHONNOUSERSITE and USER_BASE.

Nouveau dans la version 3.2.

The site module also provides a way to get the user directories from the command line:

$ python3 -m site --user-site
/home/user/.local/lib/python3.3/site-packages

If it is called without arguments, it will print the contents of sys.path on the standard output, followed by the value of USER_BASE and whether the directory exists, then the same thing for USER_SITE, and finally the value of ENABLE_USER_SITE.

--user-base

Print the path to the user base directory.

--user-site

Print the path to the user site-packages directory.

If both options are given, user base and user site will be printed (always in this order), separated by os.pathsep.

If any option is given, the script will exit with one of these values: 0 if the user site-packages directory is enabled, 1 if it was disabled by the user, 2 if it is disabled for security reasons or by an administrator, and a value greater than 2 if there is an error.

Voir aussi

PEP 370 [https://www.python.org/dev/peps/pep-0370] – Répertoire site-packages propre à l’utilisateur.

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29.14. fpectl — Floating point exception control

Note

The fpectl module is not built by default, and its usage is discouraged and may be dangerous except in the hands of experts. See also the section Limitations and other considerations on limitations for more details.

Most computers carry out floating point operations in conformance with the so-called IEEE-754 standard. On any real computer, some floating point operations produce results that cannot be expressed as a normal floating point value. For example, try

>>> import math
>>> math.exp(1000)
inf
>>> math.exp(1000) / math.exp(1000)
nan

(The example above will work on many platforms. DEC Alpha may be one exception.) « Inf » is a special, non-numeric value in IEEE-754 that stands for « infinity », and « nan » means « not a number. » Note that, other than the non-numeric results, nothing special happened when you asked Python to carry out those calculations. That is in fact the default behaviour prescribed in the IEEE-754 standard, and if it works for you, stop reading now.

In some circumstances, it would be better to raise an exception and stop processing at the point where the faulty operation was attempted. The fpectl module is for use in that situation. It provides control over floating point units from several hardware manufacturers, allowing the user to turn on the generation of SIGFPE whenever any of the IEEE-754 exceptions Division by Zero, Overflow, or Invalid Operation occurs. In tandem with a pair of wrapper macros that are inserted into the C code comprising your python system, SIGFPE is trapped and converted into the Python FloatingPointError exception.

The fpectl module defines the following functions and may raise the given exception:

fpectl.turnon_sigfpe()

Turn on the generation of SIGFPE, and set up an appropriate signal handler.

fpectl.turnoff_sigfpe()

Reset default handling of floating point exceptions.

exception fpectl.FloatingPointError

After turnon_sigfpe() has been executed, a floating point operation that raises one of the IEEE-754 exceptions Division by Zero, Overflow, or Invalid operation will in turn raise this standard Python exception.

29.14.1. Exemple

The following example demonstrates how to start up and test operation of the fpectl module.

>>> import fpectl
>>> import fpetest
>>> fpectl.turnon_sigfpe()
>>> fpetest.test()
overflow        PASS
FloatingPointError: Overflow

div by 0        PASS
FloatingPointError: Division by zero
  [ more output from test elided ]
>>> import math
>>> math.exp(1000)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
FloatingPointError: in math_1

29.14.2. Limitations and other considerations

Setting up a given processor to trap IEEE-754 floating point errors currently requires custom code on a per-architecture basis. You may have to modify fpectl to control your particular hardware.

Conversion of an IEEE-754 exception to a Python exception requires that the wrapper macros PyFPE_START_PROTECT and PyFPE_END_PROTECT be inserted into your code in an appropriate fashion. Python itself has been modified to support the fpectl module, but many other codes of interest to numerical analysts have not.

The fpectl module is not thread-safe.

Voir aussi

Some files in the source distribution may be interesting in learning more about how this module operates. The include file Include/pyfpe.h discusses the implementation of this module at some length. Modules/fpetestmodule.c gives several examples of use. Many additional examples can be found in Objects/floatobject.c.

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30. Interpréteurs Python personnalisés

Les modules décrits dans ce chapitre permettent d’écrire des interfaces similaires à l’interpréteur interactif de Python. Si vous voulez un interpréteur Python qui gère quelques fonctionnalités supplémentaires, vous devriez regarder le module code. (Le module codeop est un module de plus bas niveau permettant de compiler des morceaux, pas forcément complets, de Python.)

La liste complète des modules décrits dans ce chapitre est :

30.1. code — Interpreter base classes

30.1.1. Interactive Interpreter Objects

30.1.2. Interactive Console Objects

30.2. codeop — Compilation de code Python

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30.1. code — Interpreter base classes

Code source : Lib/code.py [https://github.com/python/cpython/tree/3.6/Lib/code.py]

The code module provides facilities to implement read-eval-print loops in Python. Two classes and convenience functions are included which can be used to build applications which provide an interactive interpreter prompt.

class code.InteractiveInterpreter(locals=None)

This class deals with parsing and interpreter state (the user’s namespace); it does not deal with input buffering or prompting or input file naming (the filename is always passed in explicitly). The optional locals argument specifies the dictionary in which code will be executed; it defaults to a newly created dictionary with key '__name__' set to '__console__' and key '__doc__' set to None.

class code.InteractiveConsole(locals=None, filename="<console>")

Closely emulate the behavior of the interactive Python interpreter. This class builds on InteractiveInterpreter and adds prompting using the familiar sys.ps1 and sys.ps2, and input buffering.

code.interact(banner=None, readfunc=None, local=None, exitmsg=None)

Convenience function to run a read-eval-print loop. This creates a new instance of InteractiveConsole and sets readfunc to be used as the InteractiveConsole.raw_input() method, if provided. If local is provided, it is passed to the InteractiveConsole constructor for use as the default namespace for the interpreter loop. The interact() method of the instance is then run with banner and exitmsg passed as the banner and exit message to use, if provided. The console object is discarded after use.

Modifié dans la version 3.6: Added exitmsg parameter.

code.compile_command(source, filename="<input>", symbol="single")

This function is useful for programs that want to emulate Python’s interpreter main loop (a.k.a. the read-eval-print loop). The tricky part is to determine when the user has entered an incomplete command that can be completed by entering more text (as opposed to a complete command or a syntax error). This function almost always makes the same decision as the real interpreter main loop.

source is the source string; filename is the optional filename from which source was read, defaulting to '<input>'; and symbol is the optional grammar start symbol, which should be either 'single' (the default) or 'eval'.

Returns a code object (the same as compile(source, filename, symbol)) if the command is complete and valid; None if the command is incomplete; raises SyntaxError if the command is complete and contains a syntax error, or raises OverflowError or ValueError if the command contains an invalid literal.

30.1.1. Interactive Interpreter Objects

InteractiveInterpreter.runsource(source, filename="<input>", symbol="single")

Compile and run some source in the interpreter. Arguments are the same as for compile_command(); the default for filename is '<input>', and for symbol is 'single'. One several things can happen:

The input is incorrect; compile_command() raised an exception (SyntaxError or OverflowError). A syntax traceback will be printed by calling the showsyntaxerror() method. runsource() returns False.

The input is incomplete, and more input is required; compile_command() returned None. runsource() returns True.

The input is complete; compile_command() returned a code object. The code is executed by calling the runcode() (which also handles run-time exceptions, except for SystemExit). runsource() returns False.

The return value can be used to decide whether to use sys.ps1 or sys.ps2 to prompt the next line.

InteractiveInterpreter.runcode(code)

Execute a code object. When an exception occurs, showtraceback() is called to display a traceback. All exceptions are caught except SystemExit, which is allowed to propagate.

A note about KeyboardInterrupt: this exception may occur elsewhere in this code, and may not always be caught. The caller should be prepared to deal with it.

InteractiveInterpreter.showsyntaxerror(filename=None)

Display the syntax error that just occurred. This does not display a stack trace because there isn’t one for syntax errors. If filename is given, it is stuffed into the exception instead of the default filename provided by Python’s parser, because it always uses '<string>' when reading from a string. The output is written by the write() method.

InteractiveInterpreter.showtraceback()

Display the exception that just occurred. We remove the first stack item because it is within the interpreter object implementation. The output is written by the write() method.

Modifié dans la version 3.5: The full chained traceback is displayed instead of just the primary traceback.

InteractiveInterpreter.write(data)

Write a string to the standard error stream (sys.stderr). Derived classes should override this to provide the appropriate output handling as needed.

30.1.2. Interactive Console Objects

The InteractiveConsole class is a subclass of InteractiveInterpreter, and so offers all the methods of the interpreter objects as well as the following additions.

InteractiveConsole.interact(banner=None, exitmsg=None)

Closely emulate the interactive Python console. The optional banner argument specify the banner to print before the first interaction; by default it prints a banner similar to the one printed by the standard Python interpreter, followed by the class name of the console object in parentheses (so as not to confuse this with the real interpreter – since it’s so close!).

The optional exitmsg argument specifies an exit message printed when exiting. Pass the empty string to suppress the exit message. If exitmsg is not given or None, a default message is printed.

Modifié dans la version 3.4: To suppress printing any banner, pass an empty string.

Modifié dans la version 3.6: Print an exit message when exiting.

InteractiveConsole.push(line)

Push a line of source text to the interpreter. The line should not have a trailing newline; it may have internal newlines. The line is appended to a buffer and the interpreter’s runsource() method is called with the concatenated contents of the buffer as source. If this indicates that the command was executed or invalid, the buffer is reset; otherwise, the command is incomplete, and the buffer is left as it was after the line was appended. The return value is True if more input is required, False if the line was dealt with in some way (this is the same as runsource()).

InteractiveConsole.resetbuffer()

Remove any unhandled source text from the input buffer.

InteractiveConsole.raw_input(prompt="")

Write a prompt and read a line. The returned line does not include the trailing newline. When the user enters the EOF key sequence, EOFError is raised. The base implementation reads from sys.stdin; a subclass may replace this with a different implementation.

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30.2. codeop — Compilation de code Python

Code source : Lib/codeop.py [https://github.com/python/cpython/tree/3.6/Lib/codeop.py]

Le module codeop fournit des outils permettant d’émuler une boucle de lecture-évaluation-affichage (en anglais read-eval-print-loop ou REPL), comme dans le module code. Par conséquent, ce module n’est pas destiné à être utilisé directement ; pour inclure un REPL dans un programme, il est préférable d’utiliser le module code.

Cette tâche se divise en deux parties :

Pouvoir affirmer qu’une ligne d’entrée est une instruction complète, ou achève une instruction : en bref, savoir s’il faut afficher « >>> » ou « ... » à sa suite.

Conserver les instructions déjà entrées par l’utilisateur, afin que les entrées suivantes puissent êtres compilées avec elles.

Le module codeop fournit un moyen d’effectuer ces deux parties, individuellement ou simultanément.

Pour ne faire que la première partie :

codeop.compile_command(source, filename="<input>", symbol="single")

Essaye de compiler source, qui doit être une chaîne de caractères représentant du code Python valide et renvoie un objet code le cas échéant. Dans ce cas, l’attribut de nom de fichier de l’objet code renvoyé sera filename ('<input>' par défaut). Renvoie None si source n’est pas du code Python valide, mais un début de code Python valide.

En cas de problème avec source, une exception est levée ; SyntaxError si la syntaxe Python est incorrecte, et OverflowError ou ValueError si un littéral invalide est rencontré.

L’argument symbol détermine si source est compilée comme une instruction ('single', par défaut) ou comme une expression ('eval'). Toute autre valeur lèvera ValueError.

Note

Il est possible (quoique improbable) que l’analyseur s’arrête avant d’atteindre la fin du code source ; dans ce cas, les symboles venant après peuvent être ignorés au lieu de provoquer une erreur. Par exemple, une barre oblique inverse suivie de deux retours à la ligne peut être suivie par de la mémoire non-initialisée. Ceci sera corrigé quand l’interface de l’analyseur aura été améliorée.

class codeop.Compile

Les instances de cette classe ont des méthodes __call__() de signature identique à la fonction native compile(), à la différence près que si l’instance compile du code source contenant une instruction __future__, l’instance s’en « souviendra » et compilera tous les codes sources suivants avec cette instruction activée.

class codeop.CommandCompiler

Les instances de cette classe ont des méthodes __call__() de signature identique à la fonction compile_command(), à la différence près que si l’instance compile du code source contenant une instruction __future__, l’instance s’en « souviendra » et compilera tous les codes sources suivants avec cette instruction activée.

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31. Importer des modules

Les modules décrits dans ce chapitre fournissent de nouveaux moyens d’importer d’autres modules Python, et des hooks pour personnaliser le processus d’importation.

La liste complète des modules décrits dans ce chapitre est :

31.1. zipimport — Importer des modules à partir d’archives Zip

31.1.1. Objets zimporter

31.1.2. Exemples

31.2. pkgutil — Package extension utility

31.3. modulefinder — Identifie les modules utilisés par un script

31.3.1. Exemples d’utilisation de la classe ModuleFinder

31.4. runpy — Locating and executing Python modules

31.5. importlib — The implementation of import

31.5.1. Introduction

31.5.2. Fonctions

31.5.3. importlib.abc – Abstract base classes related to import

31.5.4. importlib.machinery – Importers and path hooks

31.5.5. importlib.util – Utility code for importers

31.5.6. Exemples

31.5.6.1. Importing programmatically

31.5.6.2. Checking if a module can be imported

31.5.6.3. Importing a source file directly

31.5.6.4. Setting up an importer

31.5.6.5. Approximating importlib.import_module()

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31.1. zipimport — Importer des modules à partir d’archives Zip

Ce module ajoute la possibilité d’importer des modules Python (*.py, *.pyc) et des paquets depuis des archives au format ZIP. Il n’est généralement pas nécessaire d’utiliser explicitement le module zipimport ; il est automatiquement utilisé par le mécanisme intégré de import pour les éléments sys.path qui sont des chemins vers les archives ZIP.

Typiquement, sys.path est une liste de noms de répertoires sous forme de chaînes. Ce module permet également à un élément de sys.path d’être une chaîne nommant une archive de fichier ZIP. L’archive ZIP peut contenir une structure de sous-répertoire pour prendre en charge les importations de paquets, et un chemin dans l’archive peut être spécifié pour importer uniquement à partir d’un sous-répertoire. Par exemple, le chemin d’accès example.zip/lib/ importerait uniquement depuis le sous-répertoire lib/ dans l’archive.

Tous les fichiers peuvent être présents dans l’archive ZIP, mais seuls les fichiers .py et .pyc sont disponibles pour importation. L’importation ZIP des modules dynamiques (.pyd, .so) est interdite. Notez que si une archive ne contient que des fichiers .py , Python n’essaiera pas de modifier l’archive en ajoutant le fichier correspondant .pyc, ce qui signifie que si une archive ZIP ne contient pas de fichier: .pyc, l’importation peut être assez lente.

Les archives ZIP avec un commentaire ne sont actuellement pas prises en charge.

Voir aussi

PKZIP Application Note [https://pkware.cachefly.net/webdocs/casestudies/APPNOTE.TXT]

Documentation sur le format de fichier ZIP par Phil Katz, créateur du format et des algorithmes utilisés.

PEP 273 [https://www.python.org/dev/peps/pep-0273] - Import Modules from Zip Archives

Écrit par James C. Ahlstrom, qui a également fourni une mise en œuvre. Python 2.3 suit les spécifications de PEP 273, mais utilise une implémentation écrite par Just van Rossum qui utilise les crochets d’importation décrits dans PEP 302.

PEP 302 [https://www.python.org/dev/peps/pep-0302] — Nouveaux crochets d’importation

Le PEP pour ajouter les crochets d’importation qui aident ce module à fonctionner.

Ce module définit une exception :

exception zipimport.ZipImportError

Exception levée par les objets zipimporter. C’est une sous-classe de ImportError, donc il peut être pris comme ImportError, aussi.

31.1.1. Objets zimporter

zipimporter est la classe pour importer des fichiers ZIP.

class zipimport.zipimporter(archivepath)

Créez une nouvelle instance de zipimporter. archivepath doit être un chemin vers un fichier ZIP, ou vers un chemin spécifique dans un fichier ZIP. Par exemple, un archivepath de foo/bar.zip/lib cherchera les modules dans le répertoire lib du fichier ZIP foo/bar.zip (si celui-ci existe).

ZipImportError est levée si archivepath ne pointe pas vers une archive ZIP valide.

find_module(fullname[, path])

Rechercher un module spécifié par fullname. fullname doit être le nom du module entièrement qualifié (dotted). Elle retourne l’instance zipimporter elle-même si le module a été trouvé, ou None si ce n’est pas le cas. L’argument optionnel path est ignoré — il est là pour la compatibilité avec le protocole de l’importateur.

get_code(fullname)

Retourne l’objet de code pour le module spécifié. Lève ZipImportError si le module n’a pas pu être trouvé.

get_data(pathname)

Renvoie les données associées à pathname. Lève OSError si le fichier n’a pas été trouvé.

Modifié dans la version 3.3: Précédemment, c’était l’exception IOError qui était levée, au lieu de OSError.

get_filename(fullname)

Renvoie la valeur __file____ qui serait définie si le module spécifié était importé. Lève ZipImportError si le module n’a pas pu être trouvé.

Nouveau dans la version 3.1.

get_source(fullname)

Renvoie le code source du module spécifié. Lève ZipImportError si le module n’a pas pu être trouvé, renvoie None si l’archive contient le module, mais n’en a pas la source.

is_package(fullname)

Renvoie True si le module spécifié par fullname est un paquet. Lève ZipImportError si le module n’a pas pu être trouvé.

load_module(fullname)

Charge le module spécifié par fullname. fullname doit être le nom du module entièrement qualifié (dotted). Il renvoie le module importé, ou augmente ZipImportError s’il n’a pas été trouvé.

archive

Le nom de fichier de l’archive ZIP associé à l’importateur, sans sous-chemin possible.

prefix

Le sous-chemin du fichier ZIP où les modules sont recherchés. C’est la chaîne vide pour les objets zipimporter qui pointent vers la racine du fichier ZIP.

Les attributs archive et prefix, lorsqu’ils sont combinés avec une barre oblique, égalent l’argument original archivepath donné au constructeur zipimporter.

31.1.2. Exemples

Voici un exemple qui importe un module d’une archive ZIP — notez que le module zipimport n’est pas explicitement utilisé.

$ unzip -l example.zip
Archive:  example.zip
  Length     Date   Time    Name
 --------    ----   ----    ----
     8467  11-26-02 22:30   jwzthreading.py
 --------                   -------
     8467                   1 file
$ ./python
Python 2.3 (#1, Aug 1 2003, 19:54:32)
>>> import sys
>>> sys.path.insert(0, 'example.zip')  # Add .zip file to front of path
>>> import jwzthreading
>>> jwzthreading.__file__
'example.zip/jwzthreading.py'

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31.2. pkgutil — Package extension utility

Code source : Lib/pkgutil.py [https://github.com/python/cpython/tree/3.6/Lib/pkgutil.py]

This module provides utilities for the import system, in particular package support.

class pkgutil.ModuleInfo(module_finder, name, ispkg)

A namedtuple that holds a brief summary of a module’s info.

Nouveau dans la version 3.6.

pkgutil.extend_path(path, name)

Extend the search path for the modules which comprise a package. Intended use is to place the following code in a package’s __init__.py:

from pkgutil import extend_path
__path__ = extend_path(__path__, __name__)

This will add to the package’s __path__ all subdirectories of directories on sys.path named after the package. This is useful if one wants to distribute different parts of a single logical package as multiple directories.

It also looks for *.pkg files beginning where * matches the name argument. This feature is similar to *.pth files (see the site module for more information), except that it doesn’t special-case lines starting with import. A *.pkg file is trusted at face value: apart from checking for duplicates, all entries found in a *.pkg file are added to the path, regardless of whether they exist on the filesystem. (This is a feature.)

If the input path is not a list (as is the case for frozen packages) it is returned unchanged. The input path is not modified; an extended copy is returned. Items are only appended to the copy at the end.

It is assumed that sys.path is a sequence. Items of sys.path that are not strings referring to existing directories are ignored. Unicode items on sys.path that cause errors when used as filenames may cause this function to raise an exception (in line with os.path.isdir() behavior).

class pkgutil.ImpImporter(dirname=None)

PEP 302 [https://www.python.org/dev/peps/pep-0302] Finder that wraps Python’s « classic » import algorithm.

If dirname is a string, a PEP 302 [https://www.python.org/dev/peps/pep-0302] finder is created that searches that directory. If dirname is None, a PEP 302 [https://www.python.org/dev/peps/pep-0302] finder is created that searches the current sys.path, plus any modules that are frozen or built-in.

Note that ImpImporter does not currently support being used by placement on sys.meta_path.

Obsolète depuis la version 3.3: This emulation is no longer needed, as the standard import mechanism is now fully PEP 302 compliant and available in importlib.

class pkgutil.ImpLoader(fullname, file, filename, etc)

Loader that wraps Python’s « classic » import algorithm.

Obsolète depuis la version 3.3: This emulation is no longer needed, as the standard import mechanism is now fully PEP 302 compliant and available in importlib.

pkgutil.find_loader(fullname)

Retrieve a module loader for the given fullname.

This is a backwards compatibility wrapper around importlib.util.find_spec() that converts most failures to ImportError and only returns the loader rather than the full ModuleSpec.

Modifié dans la version 3.3: Updated to be based directly on importlib rather than relying on the package internal PEP 302 import emulation.

Modifié dans la version 3.4: Updated to be based on PEP 451 [https://www.python.org/dev/peps/pep-0451]

pkgutil.get_importer(path_item)

Retrieve a finder for the given path_item.

The returned finder is cached in sys.path_importer_cache if it was newly created by a path hook.

The cache (or part of it) can be cleared manually if a rescan of sys.path_hooks is necessary.

Modifié dans la version 3.3: Updated to be based directly on importlib rather than relying on the package internal PEP 302 import emulation.

pkgutil.get_loader(module_or_name)

Get a loader object for module_or_name.

If the module or package is accessible via the normal import mechanism, a wrapper around the relevant part of that machinery is returned. Returns None if the module cannot be found or imported. If the named module is not already imported, its containing package (if any) is imported, in order to establish the package __path__.

Modifié dans la version 3.3: Updated to be based directly on importlib rather than relying on the package internal PEP 302 import emulation.

Modifié dans la version 3.4: Updated to be based on PEP 451 [https://www.python.org/dev/peps/pep-0451]

pkgutil.iter_importers(fullname='')

Yield finder objects for the given module name.

If fullname contains a “.”, the finders will be for the package containing fullname, otherwise they will be all registered top level finders (i.e. those on both sys.meta_path and sys.path_hooks).

If the named module is in a package, that package is imported as a side effect of invoking this function.

If no module name is specified, all top level finders are produced.

Modifié dans la version 3.3: Updated to be based directly on importlib rather than relying on the package internal PEP 302 import emulation.

pkgutil.iter_modules(path=None, prefix='')

Yields ModuleInfo for all submodules on path, or, if path is None, all top-level modules on sys.path.

path should be either None or a list of paths to look for modules in.

prefix is a string to output on the front of every module name on output.

Note

Only works for a finder which defines an iter_modules() method. This interface is non-standard, so the module also provides implementations for importlib.machinery.FileFinder and zipimport.zipimporter.

Modifié dans la version 3.3: Updated to be based directly on importlib rather than relying on the package internal PEP 302 import emulation.

pkgutil.walk_packages(path=None, prefix='', onerror=None)

Yields ModuleInfo for all modules recursively on path, or, if path is None, all accessible modules.

path should be either None or a list of paths to look for modules in.

prefix is a string to output on the front of every module name on output.

Note that this function must import all packages (not all modules!) on the given path, in order to access the __path__ attribute to find submodules.

onerror is a function which gets called with one argument (the name of the package which was being imported) if any exception occurs while trying to import a package. If no onerror function is supplied, ImportErrors are caught and ignored, while all other exceptions are propagated, terminating the search.

Exemples :

# list all modules python can access
walk_packages()

# list all submodules of ctypes
walk_packages(ctypes.__path__, ctypes.__name__ + '.')

Note

Only works for a finder which defines an iter_modules() method. This interface is non-standard, so the module also provides implementations for importlib.machinery.FileFinder and zipimport.zipimporter.

Modifié dans la version 3.3: Updated to be based directly on importlib rather than relying on the package internal PEP 302 import emulation.

pkgutil.get_data(package, resource)

Get a resource from a package.

This is a wrapper for the loader get_data API. The package argument should be the name of a package, in standard module format (foo.bar). The resource argument should be in the form of a relative filename, using / as the path separator. The parent directory name .. is not allowed, and nor is a rooted name (starting with a /).

The function returns a binary string that is the contents of the specified resource.

For packages located in the filesystem, which have already been imported, this is the rough equivalent of:

d = os.path.dirname(sys.modules[package].__file__)
data = open(os.path.join(d, resource), 'rb').read()

If the package cannot be located or loaded, or it uses a loader which does not support get_data, then None is returned. In particular, the loader for namespace packages does not support get_data.

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31.3. modulefinder — Identifie les modules utilisés par un script

Code source : Lib/modulefinder.py [https://github.com/python/cpython/tree/3.6/Lib/modulefinder.py]

Ce module fournit une classe ModuleFinder qui peut être utilisée pour déterminer la liste des modules importés par un script. modulefinder.py peut aussi être utilisé en tant que script, en passant le nom du fichier Python en argument, ce qui affichera un rapport sur les modules importés.

modulefinder.AddPackagePath(pkg_name, path)

Enregistre que le paquet pkg_name peut être trouvé au chemin path spécifié.

modulefinder.ReplacePackage(oldname, newname)

Permet de spécifier que le module nommé oldname est en réalité le paquet nommé newname.

class modulefinder.ModuleFinder(path=None, debug=0, excludes=[], replace_paths=[])

Cette classe fournit les méthodes run_script() et report() pour déterminer l’ensemble des modules importés par un script. path peut être une liste de dossiers dans lesquels chercher les modules ; si non spécifié, sys.path est utilisé. debug définit le niveau de débogage ; des valeurs plus élevées produisent plus de détails sur ce que fait la classe. excludes est une liste de noms de modules à exclure de l’analyse. replace_paths est une liste de tuples (oldpath, newpath) qui seront remplacés dans les chemins des modules.

report()

Affiche un rapport sur la sortie standard qui liste les modules importés par le script et leurs chemins, ainsi que les modules manquants ou qui n’ont pas été trouvés.

run_script(pathname)

Analyse le contenu du fichier pathname, qui doit contenir du code Python.

modules

Un dictionnaire de correspondance entre nom de modules et modules. Voir Exemples d’utilisation de la classe ModuleFinder.

31.3.1. Exemples d’utilisation de la classe ModuleFinder

Le script qui sera analysé (bacon.py) :

import re, itertools

try:
    import baconhameggs
except ImportError:
    pass

try:
    import guido.python.ham
except ImportError:
    pass

Le script qui va afficher le rapport de bacon.py :

from modulefinder import ModuleFinder

finder = ModuleFinder()
finder.run_script('bacon.py')

print('Loaded modules:')
for name, mod in finder.modules.items():
    print('%s: ' % name, end='')
    print(','.join(list(mod.globalnames.keys())[:3]))

print('-'*50)
print('Modules not imported:')
print('\n'.join(finder.badmodules.keys()))

Exemple de sortie (peut varier en fonction de l’architecture) :

Loaded modules:
_types:
copyreg:  _inverted_registry,_slotnames,__all__
sre_compile:  isstring,_sre,_optimize_unicode
_sre:
sre_constants:  REPEAT_ONE,makedict,AT_END_LINE
sys:
re:  __module__,finditer,_expand
itertools:
__main__:  re,itertools,baconhameggs
sre_parse:  _PATTERNENDERS,SRE_FLAG_UNICODE
array:
types:  __module__,IntType,TypeType
---------------------------------------------------
Modules not imported:
guido.python.ham
baconhameggs

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31.4. runpy — Locating and executing Python modules

Code source : Lib/runpy.py [https://github.com/python/cpython/tree/3.6/Lib/runpy.py]

The runpy module is used to locate and run Python modules without importing them first. Its main use is to implement the -m command line switch that allows scripts to be located using the Python module namespace rather than the filesystem.

Note that this is not a sandbox module - all code is executed in the current process, and any side effects (such as cached imports of other modules) will remain in place after the functions have returned.

Furthermore, any functions and classes defined by the executed code are not guaranteed to work correctly after a runpy function has returned. If that limitation is not acceptable for a given use case, importlib is likely to be a more suitable choice than this module.

The runpy module provides two functions:

runpy.run_module(mod_name, init_globals=None, run_name=None, alter_sys=False)

Execute the code of the specified module and return the resulting module globals dictionary. The module’s code is first located using the standard import mechanism (refer to PEP 302 [https://www.python.org/dev/peps/pep-0302] for details) and then executed in a fresh module namespace.

The mod_name argument should be an absolute module name. If the module name refers to a package rather than a normal module, then that package is imported and the __main__ submodule within that package is then executed and the resulting module globals dictionary returned.

The optional dictionary argument init_globals may be used to pre-populate the module’s globals dictionary before the code is executed. The supplied dictionary will not be modified. If any of the special global variables below are defined in the supplied dictionary, those definitions are overridden by run_module().

The special global variables __name__, __spec__, __file__, __cached__, __loader__ and __package__ are set in the globals dictionary before the module code is executed (Note that this is a minimal set of variables - other variables may be set implicitly as an interpreter implementation detail).

__name__ is set to run_name if this optional argument is not None, to mod_name + '.__main__' if the named module is a package and to the mod_name argument otherwise.

__spec__ will be set appropriately for the actually imported module (that is, __spec__.name will always be mod_name or mod_name + '.__main__, never run_name).

__file__, __cached__, __loader__ and __package__ are set as normal based on the module spec.

If the argument alter_sys is supplied and evaluates to True, then sys.argv[0] is updated with the value of __file__ and sys.modules[__name__] is updated with a temporary module object for the module being executed. Both sys.argv[0] and sys.modules[__name__] are restored to their original values before the function returns.

Note that this manipulation of sys is not thread-safe. Other threads may see the partially initialised module, as well as the altered list of arguments. It is recommended that the sys module be left alone when invoking this function from threaded code.

Voir aussi

The -m option offering equivalent functionality from the command line.

Modifié dans la version 3.1: Added ability to execute packages by looking for a __main__ submodule.

Modifié dans la version 3.2: Added __cached__ global variable (see PEP 3147 [https://www.python.org/dev/peps/pep-3147]).

Modifié dans la version 3.4: Updated to take advantage of the module spec feature added by PEP 451 [https://www.python.org/dev/peps/pep-0451]. This allows __cached__ to be set correctly for modules run this way, as well as ensuring the real module name is always accessible as __spec__.name.

runpy.run_path(file_path, init_globals=None, run_name=None)

Execute the code at the named filesystem location and return the resulting module globals dictionary. As with a script name supplied to the CPython command line, the supplied path may refer to a Python source file, a compiled bytecode file or a valid sys.path entry containing a __main__ module (e.g. a zipfile containing a top-level __main__.py file).

For a simple script, the specified code is simply executed in a fresh module namespace. For a valid sys.path entry (typically a zipfile or directory), the entry is first added to the beginning of sys.path. The function then looks for and executes a __main__ module using the updated path. Note that there is no special protection against invoking an existing __main__ entry located elsewhere on sys.path if there is no such module at the specified location.

The optional dictionary argument init_globals may be used to pre-populate the module’s globals dictionary before the code is executed. The supplied dictionary will not be modified. If any of the special global variables below are defined in the supplied dictionary, those definitions are overridden by run_path().

The special global variables __name__, __spec__, __file__, __cached__, __loader__ and __package__ are set in the globals dictionary before the module code is executed (Note that this is a minimal set of variables - other variables may be set implicitly as an interpreter implementation detail).

__name__ is set to run_name if this optional argument is not None and to '<run_path>' otherwise.

If the supplied path directly references a script file (whether as source or as precompiled byte code), then __file__ will be set to the supplied path, and __spec__, __cached__, __loader__ and __package__ will all be set to None.

If the supplied path is a reference to a valid sys.path entry, then __spec__ will be set appropriately for the imported __main__ module (that is, __spec__.name will always be __main__). __file__, __cached__, __loader__ and __package__ will be set as normal based on the module spec.

A number of alterations are also made to the sys module. Firstly, sys.path may be altered as described above. sys.argv[0] is updated with the value of file_path and sys.modules[__name__] is updated with a temporary module object for the module being executed. All modifications to items in sys are reverted before the function returns.

Note that, unlike run_module(), the alterations made to sys are not optional in this function as these adjustments are essential to allowing the execution of sys.path entries. As the thread-safety limitations still apply, use of this function in threaded code should be either serialised with the import lock or delegated to a separate process.

Voir aussi

Options de l’interface for equivalent functionality on the command line (python path/to/script).

Nouveau dans la version 3.2.

Modifié dans la version 3.4: Updated to take advantage of the module spec feature added by PEP 451 [https://www.python.org/dev/peps/pep-0451]. This allows __cached__ to be set correctly in the case where __main__ is imported from a valid sys.path entry rather than being executed directly.

Voir aussi

PEP 338 [https://www.python.org/dev/peps/pep-0338] – Exécuter des modules en tant que scripts

PEP written and implemented by Nick Coghlan.

PEP 366 [https://www.python.org/dev/peps/pep-0366] – Main module explicit relative imports

PEP written and implemented by Nick Coghlan.

PEP 451 [https://www.python.org/dev/peps/pep-0451] – A ModuleSpec Type for the Import System

PEP written and implemented by Eric Snow

Ligne de commande et environnement - CPython command line details

The importlib.import_module() function

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31.5. importlib — The implementation of import

Nouveau dans la version 3.1.

Source code: Lib/importlib/__init__.py [https://github.com/python/cpython/tree/3.6/Lib/importlib/__init__.py]

31.5.1. Introduction

The purpose of the importlib package is two-fold. One is to provide the implementation of the import statement (and thus, by extension, the __import__() function) in Python source code. This provides an implementation of import which is portable to any Python interpreter. This also provides an implementation which is easier to comprehend than one implemented in a programming language other than Python.

Two, the components to implement import are exposed in this package, making it easier for users to create their own custom objects (known generically as an importer) to participate in the import process.

Voir aussi

L’instruction import

The language reference for the import statement.

Packages specification [https://www.python.org/doc/essays/packages/]

Original specification of packages. Some semantics have changed since the writing of this document (e.g. redirecting based on None in sys.modules).

La fonction __import__()

The import statement is syntactic sugar for this function.

PEP 235 [https://www.python.org/dev/peps/pep-0235]

Import on Case-Insensitive Platforms

PEP 263 [https://www.python.org/dev/peps/pep-0263]

Defining Python Source Code Encodings

PEP 302 [https://www.python.org/dev/peps/pep-0302]

New Import Hooks

PEP 328 [https://www.python.org/dev/peps/pep-0328]

Imports: Multi-Line and Absolute/Relative

PEP 366 [https://www.python.org/dev/peps/pep-0366]

Main module explicit relative imports

PEP 420 [https://www.python.org/dev/peps/pep-0420]

Implicit namespace packages

PEP 451 [https://www.python.org/dev/peps/pep-0451]

A ModuleSpec Type for the Import System

PEP 488 [https://www.python.org/dev/peps/pep-0488]

Elimination of PYO files

PEP 489 [https://www.python.org/dev/peps/pep-0489]

Multi-phase extension module initialization

PEP 3120 [https://www.python.org/dev/peps/pep-3120]

Using UTF-8 as the Default Source Encoding

PEP 3147 [https://www.python.org/dev/peps/pep-3147]

PYC Repository Directories

31.5.2. Fonctions

importlib.__import__(name, globals=None, locals=None, fromlist=(), level=0)

An implementation of the built-in __import__() function.

Note

Programmatic importing of modules should use import_module() instead of this function.

importlib.import_module(name, package=None)

Import a module. The name argument specifies what module to import in absolute or relative terms (e.g. either pkg.mod or ..mod). If the name is specified in relative terms, then the package argument must be set to the name of the package which is to act as the anchor for resolving the package name (e.g. import_module('..mod', 'pkg.subpkg') will import pkg.mod).

The import_module() function acts as a simplifying wrapper around importlib.__import__(). This means all semantics of the function are derived from importlib.__import__(). The most important difference between these two functions is that import_module() returns the specified package or module (e.g. pkg.mod), while __import__() returns the top-level package or module (e.g. pkg).

If you are dynamically importing a module that was created since the interpreter began execution (e.g., created a Python source file), you may need to call invalidate_caches() in order for the new module to be noticed by the import system.

Modifié dans la version 3.3: Parent packages are automatically imported.

importlib.find_loader(name, path=None)

Find the loader for a module, optionally within the specified path. If the module is in sys.modules, then sys.modules[name].__loader__ is returned (unless the loader would be None or is not set, in which case ValueError is raised). Otherwise a search using sys.meta_path is done. None is returned if no loader is found.

A dotted name does not have its parents implicitly imported as that requires loading them and that may not be desired. To properly import a submodule you will need to import all parent packages of the submodule and use the correct argument to path.

Nouveau dans la version 3.3.

Modifié dans la version 3.4: If __loader__ is not set, raise ValueError, just like when the attribute is set to None.

Obsolète depuis la version 3.4: Use importlib.util.find_spec() instead.

importlib.invalidate_caches()

Invalidate the internal caches of finders stored at sys.meta_path. If a finder implements invalidate_caches() then it will be called to perform the invalidation. This function should be called if any modules are created/installed while your program is running to guarantee all finders will notice the new module’s existence.

Nouveau dans la version 3.3.

importlib.reload(module)

Reload a previously imported module. The argument must be a module object, so it must have been successfully imported before. This is useful if you have edited the module source file using an external editor and want to try out the new version without leaving the Python interpreter. The return value is the module object (which can be different if re-importing causes a different object to be placed in sys.modules).

When reload() is executed:

Python module’s code is recompiled and the module-level code re-executed, defining a new set of objects which are bound to names in the module’s dictionary by reusing the loader which originally loaded the module. The init function of extension modules is not called a second time.

As with all other objects in Python the old objects are only reclaimed after their reference counts drop to zero.

The names in the module namespace are updated to point to any new or changed objects.

Other references to the old objects (such as names external to the module) are not rebound to refer to the new objects and must be updated in each namespace where they occur if that is desired.

There are a number of other caveats:

When a module is reloaded, its dictionary (containing the module’s global variables) is retained. Redefinitions of names will override the old definitions, so this is generally not a problem. If the new version of a module does not define a name that was defined by the old version, the old definition remains. This feature can be used to the module’s advantage if it maintains a global table or cache of objects — with a try statement it can test for the table’s presence and skip its initialization if desired:

try:
    cache
except NameError:
    cache = {}

It is generally not very useful to reload built-in or dynamically loaded modules. Reloading sys, __main__, builtins and other key modules is not recommended. In many cases extension modules are not designed to be initialized more than once, and may fail in arbitrary ways when reloaded.

If a module imports objects from another module using from … import …, calling reload() for the other module does not redefine the objects imported from it — one way around this is to re-execute the from statement, another is to use import and qualified names (module.name) instead.

If a module instantiates instances of a class, reloading the module that defines the class does not affect the method definitions of the instances — they continue to use the old class definition. The same is true for derived classes.

Nouveau dans la version 3.4.

31.5.3. importlib.abc – Abstract base classes related to import

Source code: Lib/importlib/abc.py [https://github.com/python/cpython/tree/3.6/Lib/importlib/abc.py]

The importlib.abc module contains all of the core abstract base classes used by import. Some subclasses of the core abstract base classes are also provided to help in implementing the core ABCs.

ABC hierarchy:

object
 +-- Finder (deprecated)
 |    +-- MetaPathFinder
 |    +-- PathEntryFinder
 +-- Loader
      +-- ResourceLoader --------+
      +-- InspectLoader          |
           +-- ExecutionLoader --+
                                 +-- FileLoader
                                 +-- SourceLoader

class importlib.abc.Finder

An abstract base class representing a finder.

Obsolète depuis la version 3.3: Use MetaPathFinder or PathEntryFinder instead.

abstractmethod find_module(fullname, path=None)

An abstract method for finding a loader for the specified module. Originally specified in PEP 302 [https://www.python.org/dev/peps/pep-0302], this method was meant for use in sys.meta_path and in the path-based import subsystem.

Modifié dans la version 3.4: Returns None when called instead of raising NotImplementedError.

class importlib.abc.MetaPathFinder

An abstract base class representing a meta path finder. For compatibility, this is a subclass of Finder.

Nouveau dans la version 3.3.

find_spec(fullname, path, target=None)

An abstract method for finding a spec for the specified module. If this is a top-level import, path will be None. Otherwise, this is a search for a subpackage or module and path will be the value of __path__ from the parent package. If a spec cannot be found, None is returned. When passed in, target is a module object that the finder may use to make a more educated guess about what spec to return.

Nouveau dans la version 3.4.

find_module(fullname, path)

A legacy method for finding a loader for the specified module. If this is a top-level import, path will be None. Otherwise, this is a search for a subpackage or module and path will be the value of __path__ from the parent package. If a loader cannot be found, None is returned.

If find_spec() is defined, backwards-compatible functionality is provided.

Modifié dans la version 3.4: Returns None when called instead of raising NotImplementedError. Can use find_spec() to provide functionality.

Obsolète depuis la version 3.4: Use find_spec() instead.

invalidate_caches()

An optional method which, when called, should invalidate any internal cache used by the finder. Used by importlib.invalidate_caches() when invalidating the caches of all finders on sys.meta_path.

Modifié dans la version 3.4: Returns None when called instead of NotImplemented.

class importlib.abc.PathEntryFinder

An abstract base class representing a path entry finder. Though it bears some similarities to MetaPathFinder, PathEntryFinder is meant for use only within the path-based import subsystem provided by PathFinder. This ABC is a subclass of Finder for compatibility reasons only.

Nouveau dans la version 3.3.

find_spec(fullname, target=None)

An abstract method for finding a spec for the specified module. The finder will search for the module only within the path entry to which it is assigned. If a spec cannot be found, None is returned. When passed in, target is a module object that the finder may use to make a more educated guess about what spec to return.

Nouveau dans la version 3.4.

find_loader(fullname)

A legacy method for finding a loader for the specified module. Returns a 2-tuple of (loader, portion) where portion is a sequence of file system locations contributing to part of a namespace package. The loader may be None while specifying portion to signify the contribution of the file system locations to a namespace package. An empty list can be used for portion to signify the loader is not part of a namespace package. If loader is None and portion is the empty list then no loader or location for a namespace package were found (i.e. failure to find anything for the module).

If find_spec() is defined then backwards-compatible functionality is provided.

Modifié dans la version 3.4: Returns (None, []) instead of raising NotImplementedError. Uses find_spec() when available to provide functionality.

Obsolète depuis la version 3.4: Use find_spec() instead.

find_module(fullname)

A concrete implementation of Finder.find_module() which is equivalent to self.find_loader(fullname)[0].

Obsolète depuis la version 3.4: Use find_spec() instead.

invalidate_caches()

An optional method which, when called, should invalidate any internal cache used by the finder. Used by PathFinder.invalidate_caches() when invalidating the caches of all cached finders.

class importlib.abc.Loader

An abstract base class for a loader. See PEP 302 [https://www.python.org/dev/peps/pep-0302] for the exact definition for a loader.

create_module(spec)

A method that returns the module object to use when importing a module. This method may return None, indicating that default module creation semantics should take place.

Nouveau dans la version 3.4.

Modifié dans la version 3.5: Starting in Python 3.6, this method will not be optional when exec_module() is defined.

exec_module(module)

An abstract method that executes the module in its own namespace when a module is imported or reloaded. The module should already be initialized when exec_module() is called. When this method exists, create_module() must be defined.

Nouveau dans la version 3.4.

Modifié dans la version 3.6: create_module() must also be defined.

load_module(fullname)

A legacy method for loading a module. If the module cannot be loaded, ImportError is raised, otherwise the loaded module is returned.

If the requested module already exists in sys.modules, that module should be used and reloaded. Otherwise the loader should create a new module and insert it into sys.modules before any loading begins, to prevent recursion from the import. If the loader inserted a module and the load fails, it must be removed by the loader from sys.modules; modules already in sys.modules before the loader began execution should be left alone (see importlib.util.module_for_loader()).

The loader should set several attributes on the module. (Note that some of these attributes can change when a module is reloaded):

__name__

The name of the module.

__file__

The path to where the module data is stored (not set for built-in modules).

__cached__

The path to where a compiled version of the module is/should be stored (not set when the attribute would be inappropriate).

__path__

A list of strings specifying the search path within a package. This attribute is not set on modules.

__package__

The parent package for the module/package. If the module is top-level then it has a value of the empty string. The importlib.util.module_for_loader() decorator can handle the details for __package__.

__loader__

The loader used to load the module. The importlib.util.module_for_loader() decorator can handle the details for __package__.

When exec_module() is available then backwards-compatible functionality is provided.

Modifié dans la version 3.4: Raise ImportError when called instead of NotImplementedError. Functionality provided when exec_module() is available.

Obsolète depuis la version 3.4: The recommended API for loading a module is exec_module() (and create_module()). Loaders should implement it instead of load_module(). The import machinery takes care of all the other responsibilities of load_module() when exec_module() is implemented.

module_repr(module)

A legacy method which when implemented calculates and returns the given module’s repr, as a string. The module type’s default repr() will use the result of this method as appropriate.

Nouveau dans la version 3.3.

Modifié dans la version 3.4: Made optional instead of an abstractmethod.

Obsolète depuis la version 3.4: The import machinery now takes care of this automatically.

class importlib.abc.ResourceLoader

An abstract base class for a loader which implements the optional PEP 302 [https://www.python.org/dev/peps/pep-0302] protocol for loading arbitrary resources from the storage back-end.

abstractmethod get_data(path)

An abstract method to return the bytes for the data located at path. Loaders that have a file-like storage back-end that allows storing arbitrary data can implement this abstract method to give direct access to the data stored. OSError is to be raised if the path cannot be found. The path is expected to be constructed using a module’s __file__ attribute or an item from a package’s __path__.

Modifié dans la version 3.4: Raises OSError instead of NotImplementedError.

class importlib.abc.InspectLoader

An abstract base class for a loader which implements the optional PEP 302 [https://www.python.org/dev/peps/pep-0302] protocol for loaders that inspect modules.

get_code(fullname)

Return the code object for a module, or None if the module does not have a code object (as would be the case, for example, for a built-in module). Raise an ImportError if loader cannot find the requested module.

Note

While the method has a default implementation, it is suggested that it be overridden if possible for performance.

Modifié dans la version 3.4: No longer abstract and a concrete implementation is provided.

abstractmethod get_source(fullname)

An abstract method to return the source of a module. It is returned as a text string using universal newlines, translating all recognized line separators into '\n' characters. Returns None if no source is available (e.g. a built-in module). Raises ImportError if the loader cannot find the module specified.

Modifié dans la version 3.4: Raises ImportError instead of NotImplementedError.

is_package(fullname)

An abstract method to return a true value if the module is a package, a false value otherwise. ImportError is raised if the loader cannot find the module.

Modifié dans la version 3.4: Raises ImportError instead of NotImplementedError.

static source_to_code(data, path='<string>')

Create a code object from Python source.

The data argument can be whatever the compile() function supports (i.e. string or bytes). The path argument should be the « path » to where the source code originated from, which can be an abstract concept (e.g. location in a zip file).

With the subsequent code object one can execute it in a module by running exec(code, module.__dict__).

Nouveau dans la version 3.4.

Modifié dans la version 3.5: Made the method static.

exec_module(module)

Implementation of Loader.exec_module().

Nouveau dans la version 3.4.

load_module(fullname)

Implementation of Loader.load_module().

Obsolète depuis la version 3.4: use exec_module() instead.

class importlib.abc.ExecutionLoader

An abstract base class which inherits from InspectLoader that, when implemented, helps a module to be executed as a script. The ABC represents an optional PEP 302 [https://www.python.org/dev/peps/pep-0302] protocol.

abstractmethod get_filename(fullname)

An abstract method that is to return the value of __file__ for the specified module. If no path is available, ImportError is raised.

If source code is available, then the method should return the path to the source file, regardless of whether a bytecode was used to load the module.

Modifié dans la version 3.4: Raises ImportError instead of NotImplementedError.

class importlib.abc.FileLoader(fullname, path)

An abstract base class which inherits from ResourceLoader and ExecutionLoader, providing concrete implementations of ResourceLoader.get_data() and ExecutionLoader.get_filename().

The fullname argument is a fully resolved name of the module the loader is to handle. The path argument is the path to the file for the module.

Nouveau dans la version 3.3.

name

The name of the module the loader can handle.

path

Path to the file of the module.

load_module(fullname)

Calls super’s load_module().

Obsolète depuis la version 3.4: Use Loader.exec_module() instead.

abstractmethod get_filename(fullname)

Returns path.

abstractmethod get_data(path)

Reads path as a binary file and returns the bytes from it.

class importlib.abc.SourceLoader

An abstract base class for implementing source (and optionally bytecode) file loading. The class inherits from both ResourceLoader and ExecutionLoader, requiring the implementation of:

ResourceLoader.get_data()

ExecutionLoader.get_filename()

Should only return the path to the source file; sourceless loading is not supported.

The abstract methods defined by this class are to add optional bytecode file support. Not implementing these optional methods (or causing them to raise NotImplementedError) causes the loader to only work with source code. Implementing the methods allows the loader to work with source and bytecode files; it does not allow for sourceless loading where only bytecode is provided. Bytecode files are an optimization to speed up loading by removing the parsing step of Python’s compiler, and so no bytecode-specific API is exposed.

path_stats(path)

Optional abstract method which returns a dict containing metadata about the specified path. Supported dictionary keys are:

'mtime' (mandatory): an integer or floating-point number representing the modification time of the source code;

'size' (optional): the size in bytes of the source code.

Any other keys in the dictionary are ignored, to allow for future extensions. If the path cannot be handled, OSError is raised.

Nouveau dans la version 3.3.

Modifié dans la version 3.4: Raise OSError instead of NotImplementedError.

path_mtime(path)

Optional abstract method which returns the modification time for the specified path.

Obsolète depuis la version 3.3: This method is deprecated in favour of path_stats(). You don’t have to implement it, but it is still available for compatibility purposes. Raise OSError if the path cannot be handled.

Modifié dans la version 3.4: Raise OSError instead of NotImplementedError.

set_data(path, data)

Optional abstract method which writes the specified bytes to a file path. Any intermediate directories which do not exist are to be created automatically.

When writing to the path fails because the path is read-only (errno.EACCES/PermissionError), do not propagate the exception.

Modifié dans la version 3.4: No longer raises NotImplementedError when called.

get_code(fullname)

Concrete implementation of InspectLoader.get_code().

exec_module(module)

Concrete implementation of Loader.exec_module().

Nouveau dans la version 3.4.

load_module(fullname)

Concrete implementation of Loader.load_module().

Obsolète depuis la version 3.4: Use exec_module() instead.

get_source(fullname)

Concrete implementation of InspectLoader.get_source().

is_package(fullname)

Concrete implementation of InspectLoader.is_package(). A module is determined to be a package if its file path (as provided by ExecutionLoader.get_filename()) is a file named __init__ when the file extension is removed and the module name itself does not end in __init__.

31.5.4. importlib.machinery – Importers and path hooks

Source code: Lib/importlib/machinery.py [https://github.com/python/cpython/tree/3.6/Lib/importlib/machinery.py]

This module contains the various objects that help import find and load modules.

importlib.machinery.SOURCE_SUFFIXES

A list of strings representing the recognized file suffixes for source modules.

Nouveau dans la version 3.3.

importlib.machinery.DEBUG_BYTECODE_SUFFIXES

A list of strings representing the file suffixes for non-optimized bytecode modules.

Nouveau dans la version 3.3.

Obsolète depuis la version 3.5: Use BYTECODE_SUFFIXES instead.

importlib.machinery.OPTIMIZED_BYTECODE_SUFFIXES

A list of strings representing the file suffixes for optimized bytecode modules.

Nouveau dans la version 3.3.

Obsolète depuis la version 3.5: Use BYTECODE_SUFFIXES instead.

importlib.machinery.BYTECODE_SUFFIXES

A list of strings representing the recognized file suffixes for bytecode modules (including the leading dot).

Nouveau dans la version 3.3.

Modifié dans la version 3.5: The value is no longer dependent on __debug__.

importlib.machinery.EXTENSION_SUFFIXES

A list of strings representing the recognized file suffixes for extension modules.

Nouveau dans la version 3.3.

importlib.machinery.all_suffixes()

Returns a combined list of strings representing all file suffixes for modules recognized by the standard import machinery. This is a helper for code which simply needs to know if a filesystem path potentially refers to a module without needing any details on the kind of module (for example, inspect.getmodulename()).

Nouveau dans la version 3.3.

class importlib.machinery.BuiltinImporter

An importer for built-in modules. All known built-in modules are listed in sys.builtin_module_names. This class implements the importlib.abc.MetaPathFinder and importlib.abc.InspectLoader ABCs.

Only class methods are defined by this class to alleviate the need for instantiation.

Modifié dans la version 3.5: As part of PEP 489 [https://www.python.org/dev/peps/pep-0489], the builtin importer now implements Loader.create_module() and Loader.exec_module()

class importlib.machinery.FrozenImporter

An importer for frozen modules. This class implements the importlib.abc.MetaPathFinder and importlib.abc.InspectLoader ABCs.

Only class methods are defined by this class to alleviate the need for instantiation.

class importlib.machinery.WindowsRegistryFinder

Finder for modules declared in the Windows registry. This class implements the importlib.abc.MetaPathFinder ABC.

Only class methods are defined by this class to alleviate the need for instantiation.

Nouveau dans la version 3.3.

Obsolète depuis la version 3.6: Use site configuration instead. Future versions of Python may not enable this finder by default.

class importlib.machinery.PathFinder

A Finder for sys.path and package __path__ attributes. This class implements the importlib.abc.MetaPathFinder ABC.

Only class methods are defined by this class to alleviate the need for instantiation.

classmethod find_spec(fullname, path=None, target=None)

Class method that attempts to find a spec for the module specified by fullname on sys.path or, if defined, on path. For each path entry that is searched, sys.path_importer_cache is checked. If a non-false object is found then it is used as the path entry finder to look for the module being searched for. If no entry is found in sys.path_importer_cache, then sys.path_hooks is searched for a finder for the path entry and, if found, is stored in sys.path_importer_cache along with being queried about the module. If no finder is ever found then None is both stored in the cache and returned.

Nouveau dans la version 3.4.

Modifié dans la version 3.5: If the current working directory – represented by an empty string – is no longer valid then None is returned but no value is cached in sys.path_importer_cache.

classmethod find_module(fullname, path=None)

A legacy wrapper around find_spec().

Obsolète depuis la version 3.4: Use find_spec() instead.

classmethod invalidate_caches()

Calls importlib.abc.PathEntryFinder.invalidate_caches() on all finders stored in sys.path_importer_cache.

Modifié dans la version 3.4: Calls objects in sys.path_hooks with the current working directory for '' (i.e. the empty string).

class importlib.machinery.FileFinder(path, *loader_details)

A concrete implementation of importlib.abc.PathEntryFinder which caches results from the file system.

The path argument is the directory for which the finder is in charge of searching.

The loader_details argument is a variable number of 2-item tuples each containing a loader and a sequence of file suffixes the loader recognizes. The loaders are expected to be callables which accept two arguments of the module’s name and the path to the file found.

The finder will cache the directory contents as necessary, making stat calls for each module search to verify the cache is not outdated. Because cache staleness relies upon the granularity of the operating system’s state information of the file system, there is a potential race condition of searching for a module, creating a new file, and then searching for the module the new file represents. If the operations happen fast enough to fit within the granularity of stat calls, then the module search will fail. To prevent this from happening, when you create a module dynamically, make sure to call importlib.invalidate_caches().

Nouveau dans la version 3.3.

path

The path the finder will search in.

find_spec(fullname, target=None)

Attempt to find the spec to handle fullname within path.

Nouveau dans la version 3.4.

find_loader(fullname)

Attempt to find the loader to handle fullname within path.

invalidate_caches()

Clear out the internal cache.

classmethod path_hook(*loader_details)

A class method which returns a closure for use on sys.path_hooks. An instance of FileFinder is returned by the closure using the path argument given to the closure directly and loader_details indirectly.

If the argument to the closure is not an existing directory, ImportError is raised.

class importlib.machinery.SourceFileLoader(fullname, path)

A concrete implementation of importlib.abc.SourceLoader by subclassing importlib.abc.FileLoader and providing some concrete implementations of other methods.

Nouveau dans la version 3.3.

name

The name of the module that this loader will handle.

path

The path to the source file.

is_package(fullname)

Return true if path appears to be for a package.

path_stats(path)

Concrete implementation of importlib.abc.SourceLoader.path_stats().

set_data(path, data)

Concrete implementation of importlib.abc.SourceLoader.set_data().

load_module(name=None)

Concrete implementation of importlib.abc.Loader.load_module() where specifying the name of the module to load is optional.

Obsolète depuis la version 3.6: Use importlib.abc.Loader.exec_module() instead.

class importlib.machinery.SourcelessFileLoader(fullname, path)

A concrete implementation of importlib.abc.FileLoader which can import bytecode files (i.e. no source code files exist).

Please note that direct use of bytecode files (and thus not source code files) inhibits your modules from being usable by all Python implementations or new versions of Python which change the bytecode format.

Nouveau dans la version 3.3.

name

The name of the module the loader will handle.

path

The path to the bytecode file.

is_package(fullname)

Determines if the module is a package based on path.

get_code(fullname)

Returns the code object for name created from path.

get_source(fullname)

Returns None as bytecode files have no source when this loader is used.

load_module(name=None)

Concrete implementation of importlib.abc.Loader.load_module() where specifying the name of the module to load is optional.

Obsolète depuis la version 3.6: Use importlib.abc.Loader.exec_module() instead.

class importlib.machinery.ExtensionFileLoader(fullname, path)

A concrete implementation of importlib.abc.ExecutionLoader for extension modules.

The fullname argument specifies the name of the module the loader is to support. The path argument is the path to the extension module’s file.

Nouveau dans la version 3.3.

name

Name of the module the loader supports.

path

Path to the extension module.

create_module(spec)

Creates the module object from the given specification in accordance with PEP 489 [https://www.python.org/dev/peps/pep-0489].

Nouveau dans la version 3.5.

exec_module(module)

Initializes the given module object in accordance with PEP 489 [https://www.python.org/dev/peps/pep-0489].

Nouveau dans la version 3.5.

is_package(fullname)

Returns True if the file path points to a package’s __init__ module based on EXTENSION_SUFFIXES.

get_code(fullname)

Returns None as extension modules lack a code object.

get_source(fullname)

Returns None as extension modules do not have source code.

get_filename(fullname)

Returns path.

Nouveau dans la version 3.4.

class importlib.machinery.ModuleSpec(name, loader, *, origin=None, loader_state=None, is_package=None)

A specification for a module’s import-system-related state. This is typically exposed as the module’s __spec__ attribute. In the descriptions below, the names in parentheses give the corresponding attribute available directly on the module object. E.g. module.__spec__.origin == module.__file__. Note however that while the values are usually equivalent, they can differ since there is no synchronization between the two objects. Thus it is possible to update the module’s __path__ at runtime, and this will not be automatically reflected in __spec__.submodule_search_locations.

Nouveau dans la version 3.4.

name

(__name__)

A string for the fully-qualified name of the module.

loader

(__loader__)

The loader to use for loading. For namespace packages this should be set to None.

origin

(__file__)

Name of the place from which the module is loaded, e.g. « builtin » for built-in modules and the filename for modules loaded from source. Normally « origin » should be set, but it may be None (the default) which indicates it is unspecified.

submodule_search_locations

(__path__)

List of strings for where to find submodules, if a package (None otherwise).

loader_state

Container of extra module-specific data for use during loading (or None).

cached

(__cached__)

String for where the compiled module should be stored (or None).

parent

(__package__)

(Read-only) Fully-qualified name of the package to which the module belongs as a submodule (or None).

has_location

Boolean indicating whether or not the module’s « origin » attribute refers to a loadable location.

31.5.5. importlib.util – Utility code for importers

Source code: Lib/importlib/util.py [https://github.com/python/cpython/tree/3.6/Lib/importlib/util.py]

This module contains the various objects that help in the construction of an importer.

importlib.util.MAGIC_NUMBER

The bytes which represent the bytecode version number. If you need help with loading/writing bytecode then consider importlib.abc.SourceLoader.

Nouveau dans la version 3.4.

importlib.util.cache_from_source(path, debug_override=None, *, optimization=None)

Return the PEP 3147 [https://www.python.org/dev/peps/pep-3147]/PEP 488 [https://www.python.org/dev/peps/pep-0488] path to the byte-compiled file associated with the source path. For example, if path is /foo/bar/baz.py the return value would be /foo/bar/__pycache__/baz.cpython-32.pyc for Python 3.2. The cpython-32 string comes from the current magic tag (see get_tag(); if sys.implementation.cache_tag is not defined then NotImplementedError will be raised).

The optimization parameter is used to specify the optimization level of the bytecode file. An empty string represents no optimization, so /foo/bar/baz.py with an optimization of '' will result in a bytecode path of /foo/bar/__pycache__/baz.cpython-32.pyc. None causes the interpter’s optimization level to be used. Any other value’s string representation being used, so /foo/bar/baz.py with an optimization of 2 will lead to the bytecode path of /foo/bar/__pycache__/baz.cpython-32.opt-2.pyc. The string representation of optimization can only be alphanumeric, else ValueError is raised.

The debug_override parameter is deprecated and can be used to override the system’s value for __debug__. A True value is the equivalent of setting optimization to the empty string. A False value is the same as setting optimization to 1. If both debug_override an optimization are not None then TypeError is raised.

Nouveau dans la version 3.4.

Modifié dans la version 3.5: The optimization parameter was added and the debug_override parameter was deprecated.

Modifié dans la version 3.6: Accepte un path-like object.

importlib.util.source_from_cache(path)

Given the path to a PEP 3147 [https://www.python.org/dev/peps/pep-3147] file name, return the associated source code file path. For example, if path is /foo/bar/__pycache__/baz.cpython-32.pyc the returned path would be /foo/bar/baz.py. path need not exist, however if it does not conform to PEP 3147 [https://www.python.org/dev/peps/pep-3147] or PEP 488 [https://www.python.org/dev/peps/pep-0488] format, a ValueError is raised. If sys.implementation.cache_tag is not defined, NotImplementedError is raised.

Nouveau dans la version 3.4.

Modifié dans la version 3.6: Accepte un path-like object.

importlib.util.decode_source(source_bytes)

Decode the given bytes representing source code and return it as a string with universal newlines (as required by importlib.abc.InspectLoader.get_source()).

Nouveau dans la version 3.4.

importlib.util.resolve_name(name, package)

Resolve a relative module name to an absolute one.

If name has no leading dots, then name is simply returned. This allows for usage such as importlib.util.resolve_name('sys', __package__) without doing a check to see if the package argument is needed.

ValueError is raised if name is a relative module name but package is a false value (e.g. None or the empty string). ValueError is also raised a relative name would escape its containing package (e.g. requesting ..bacon from within the spam package).

Nouveau dans la version 3.3.

importlib.util.find_spec(name, package=None)

Find the spec for a module, optionally relative to the specified package name. If the module is in sys.modules, then sys.modules[name].__spec__ is returned (unless the spec would be None or is not set, in which case ValueError is raised). Otherwise a search using sys.meta_path is done. None is returned if no spec is found.

If name is for a submodule (contains a dot), the parent module is automatically imported.

name and package work the same as for import_module().

Nouveau dans la version 3.4.

importlib.util.module_from_spec(spec)

Create a new module based on spec and spec.loader.create_module.

If spec.loader.create_module does not return None, then any pre-existing attributes will not be reset. Also, no AttributeError will be raised if triggered while accessing spec or setting an attribute on the module.

This function is preferred over using types.ModuleType to create a new module as spec is used to set as many import-controlled attributes on the module as possible.

Nouveau dans la version 3.5.

@importlib.util.module_for_loader

A decorator for importlib.abc.Loader.load_module() to handle selecting the proper module object to load with. The decorated method is expected to have a call signature taking two positional arguments (e.g. load_module(self, module)) for which the second argument will be the module object to be used by the loader. Note that the decorator will not work on static methods because of the assumption of two arguments.

The decorated method will take in the name of the module to be loaded as expected for a loader. If the module is not found in sys.modules then a new one is constructed. Regardless of where the module came from, __loader__ set to self and __package__ is set based on what importlib.abc.InspectLoader.is_package() returns (if available). These attributes are set unconditionally to support reloading.

If an exception is raised by the decorated method and a module was added to sys.modules, then the module will be removed to prevent a partially initialized module from being in left in sys.modules. If the module was already in sys.modules then it is left alone.

Modifié dans la version 3.3: __loader__ and __package__ are automatically set (when possible).

Modifié dans la version 3.4: Set __name__, __loader__ __package__ unconditionally to support reloading.

Obsolète depuis la version 3.4: The import machinery now directly performs all the functionality provided by this function.

@importlib.util.set_loader

A decorator for importlib.abc.Loader.load_module() to set the __loader__ attribute on the returned module. If the attribute is already set the decorator does nothing. It is assumed that the first positional argument to the wrapped method (i.e. self) is what __loader__ should be set to.

Modifié dans la version 3.4: Set __loader__ if set to None, as if the attribute does not exist.

Obsolète depuis la version 3.4: The import machinery takes care of this automatically.

@importlib.util.set_package

A decorator for importlib.abc.Loader.load_module() to set the __package__ attribute on the returned module. If __package__ is set and has a value other than None it will not be changed.

Obsolète depuis la version 3.4: The import machinery takes care of this automatically.

importlib.util.spec_from_loader(name, loader, *, origin=None, is_package=None)

A factory function for creating a ModuleSpec instance based on a loader. The parameters have the same meaning as they do for ModuleSpec. The function uses available loader APIs, such as InspectLoader.is_package(), to fill in any missing information on the spec.

Nouveau dans la version 3.4.

importlib.util.spec_from_file_location(name, location, *, loader=None, submodule_search_locations=None)

A factory function for creating a ModuleSpec instance based on the path to a file. Missing information will be filled in on the spec by making use of loader APIs and by the implication that the module will be file-based.

Nouveau dans la version 3.4.

Modifié dans la version 3.6: Accepte un path-like object.

class importlib.util.LazyLoader(loader)

A class which postpones the execution of the loader of a module until the module has an attribute accessed.

This class only works with loaders that define exec_module() as control over what module type is used for the module is required. For those same reasons, the loader’s create_module() method must return None or a type for which its __class__ attribute can be mutated along with not using slots. Finally, modules which substitute the object placed into sys.modules will not work as there is no way to properly replace the module references throughout the interpreter safely; ValueError is raised if such a substitution is detected.

Note

For projects where startup time is critical, this class allows for potentially minimizing the cost of loading a module if it is never used. For projects where startup time is not essential then use of this class is heavily discouraged due to error messages created during loading being postponed and thus occurring out of context.

Nouveau dans la version 3.5.

Modifié dans la version 3.6: Began calling create_module(), removing the compatibility warning for importlib.machinery.BuiltinImporter and importlib.machinery.ExtensionFileLoader.

classmethod factory(loader)

A static method which returns a callable that creates a lazy loader. This is meant to be used in situations where the loader is passed by class instead of by instance.

suffixes = importlib.machinery.SOURCE_SUFFIXES
loader = importlib.machinery.SourceFileLoader
lazy_loader = importlib.util.LazyLoader.factory(loader)
finder = importlib.machinery.FileFinder(path, (lazy_loader, suffixes))

31.5.6. Exemples

31.5.6.1. Importing programmatically

To programmatically import a module, use importlib.import_module().

import importlib

itertools = importlib.import_module('itertools')

31.5.6.2. Checking if a module can be imported

If you need to find out if a module can be imported without actually doing the import, then you should use importlib.util.find_spec().

import importlib.util
import sys

# For illustrative purposes.
name = 'itertools'

spec = importlib.util.find_spec(name)
if spec is None:
    print("can't find the itertools module")
else:
    # If you chose to perform the actual import ...
    module = importlib.util.module_from_spec(spec)
    spec.loader.exec_module(module)
    # Adding the module to sys.modules is optional.
    sys.modules[name] = module

31.5.6.3. Importing a source file directly

To import a Python source file directly, use the following recipe (Python 3.5 and newer only):

import importlib.util
import sys

# For illustrative purposes.
import tokenize
file_path = tokenize.__file__
module_name = tokenize.__name__

spec = importlib.util.spec_from_file_location(module_name, file_path)
module = importlib.util.module_from_spec(spec)
spec.loader.exec_module(module)
# Optional; only necessary if you want to be able to import the module
# by name later.
sys.modules[module_name] = module

31.5.6.4. Setting up an importer

For deep customizations of import, you typically want to implement an importer. This means managing both the finder and loader side of things. For finders there are two flavours to choose from depending on your needs: a meta path finder or a path entry finder. The former is what you would put on sys.meta_path while the latter is what you create using a path entry hook on sys.path_hooks which works with sys.path entries to potentially create a finder. This example will show you how to register your own importers so that import will use them (for creating an importer for yourself, read the documentation for the appropriate classes defined within this package):

import importlib.machinery
import sys

# For illustrative purposes only.
SpamMetaPathFinder = importlib.machinery.PathFinder
SpamPathEntryFinder = importlib.machinery.FileFinder
loader_details = (importlib.machinery.SourceFileLoader,
                  importlib.machinery.SOURCE_SUFFIXES)

# Setting up a meta path finder.
# Make sure to put the finder in the proper location in the list in terms of
# priority.
sys.meta_path.append(SpamMetaPathFinder)

# Setting up a path entry finder.
# Make sure to put the path hook in the proper location in the list in terms
# of priority.
sys.path_hooks.append(SpamPathEntryFinder.path_hook(loader_details))

31.5.6.5. Approximating importlib.import_module()

Import itself is implemented in Python code, making it possible to expose most of the import machinery through importlib. The following helps illustrate the various APIs that importlib exposes by providing an approximate implementation of importlib.import_module() (Python 3.4 and newer for the importlib usage, Python 3.6 and newer for other parts of the code).

import importlib.util
import sys

def import_module(name, package=None):
    """An approximate implementation of import."""
    absolute_name = importlib.util.resolve_name(name, package)
    try:
        return sys.modules[absolute_name]
    except KeyError:
        pass

    path = None
    if '.' in absolute_name:
        parent_name, _, child_name = absolute_name.rpartition('.')
        parent_module = import_module(parent_name)
        path = parent_module.__spec__.submodule_search_locations
    for finder in sys.meta_path:
        spec = finder.find_spec(absolute_name, path)
        if spec is not None:
            break
    else:
        msg = f'No module named {absolute_name!r}'
        raise ModuleNotFoundError(msg, name=absolute_name)
    module = importlib.util.module_from_spec(spec)
    spec.loader.exec_module(module)
    sys.modules[absolute_name] = module
    if path is not None:
        setattr(parent_module, child_name, module)
    return module

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32. Services du Langage Python

Python fournit quelques modules pour vous aider à travailler avec le langage Python lui-même. Ces modules gèrent entre autres l’analyse lexicale, l’analyse syntaxique, et le désassemblage de bytecode.

Ces modules sont :

32.1. parser — Accès aux arbres syntaxiques

32.1.1. Creating ST Objects

32.1.2. Converting ST Objects

32.1.3. Queries on ST Objects

32.1.4. Exceptions and Error Handling

32.1.5. ST Objects

32.1.6. Example: Emulation of compile()

32.2. ast — Arbres Syntaxiques Abstraits

32.2.1. Les classes nœud

32.2.2. Grammaire abstraite

32.2.3. Outils du module ast

32.3. symtable — Access to the compiler’s symbol tables

32.3.1. Generating Symbol Tables

32.3.2. Examining Symbol Tables

32.4. symbol — Constantes utilisées dans les Arbres Syntaxiques

32.5. token — Constantes utilisées avec les arbres d’analyse Python (parse trees)

32.6. keyword — Tester si des chaînes sont des mot-clés Python

32.7. tokenize — Analyseur lexical de Python

32.7.1. Analyse Lexicale

32.7.2. Utilisation en ligne de commande.

32.7.3. Exemples

32.8. tabnanny — Détection d’indentation ambiguë

32.9. pyclbr — Python class browser support

32.9.1. Objets classes

32.9.2. Objets fonctions

32.10. py_compile — Compile Python source files

32.11. compileall — Byte-compile Python libraries

32.11.1. Command-line use

32.11.2. Public functions

32.12. dis – Désassembleur pour le code intermédiaire de Python

32.12.1. Analyse du code intermédiaire

32.12.2. Analyse de fonctions

32.12.3. Les instructions du code intermédiaire en Python

32.12.4. Opcode collections

32.13. pickletools — Tools for pickle developers

32.13.1. Utilisation de la ligne de commande

32.13.1.1. Options de la ligne de commande

32.13.2. Programmatic Interface

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32.1. parser — Accès aux arbres syntaxiques

Le module parser expose une interface à l’analyseur et au compilateur de byte-code internes de Python. Son objectif principal est de permettre à du code Python de modifier l’arbre syntaxique d’une expression Python puis de la rendre exécutable. Cette approche est plus fiable que celle consistant à manipuler des chaines de caractères, puisque l’analyse est faite avec le même analyseur que celui utilisé pour le code de l’application. C’est aussi plus rapide.

Note

À partir de Python 2.5, il est plus pratique de faire ces manipulations entre la génération de l’AST (Abstract Syntax Tree) et la compilation, en utilisant le module ast.

Certaines particularités de ce module sont importantes à retenir pour en faire un bon usage. Ce n’est pas un tutoriel sur la modification d’arbres syntaxiques Python, mais certains exemples d’utilisation du module parser sont présentés.

Le prérequis le plus important est une bonne compréhension de la grammaire Python utilisée par l’analyseur interne dont la syntaxe est documentée exhaustivement dans La référence du langage Python. L’analyseur lui-même est généré à partir d’une grammaire spécifiée dans le fichier Grammar/Grammar dans la distribution standard de Python. Les arbres syntaxiques stockés dans les objets ST créés par les fonctions expr() ou suite() de ce module sont directement le résultat de l’analyseur interne, alors que les objets ST créés par sequence2st() simulent ces structures. N’oubliez pas qu’une séquence considérée « correcte » dans une version de Python peut ne pas l’être dans une autre, la grammaire de Python pouvant évoluer. Cependant, déplacer du code source d’une version de Python à une autre sous forme textuelle donnera toujours des arbres syntaxique corrects, à l’exception qu’une version plus ancienne de l’interpréteur ne pourra pas analyser les constructions récentes du langage. Les arbres syntaxiques quant à eux ne sont généralement pas compatibles d’une version à l’autre, alors que le code source a toujours conservé la compatibilité ascendante.

Each element of the sequences returned by st2list() or st2tuple() has a simple form. Sequences representing non-terminal elements in the grammar always have a length greater than one. The first element is an integer which identifies a production in the grammar. These integers are given symbolic names in the C header file Include/graminit.h and the Python module symbol. Each additional element of the sequence represents a component of the production as recognized in the input string: these are always sequences which have the same form as the parent. An important aspect of this structure which should be noted is that keywords used to identify the parent node type, such as the keyword if in an if_stmt, are included in the node tree without any special treatment. For example, the if keyword is represented by the tuple (1, 'if'), where 1 is the numeric value associated with all NAME tokens, including variable and function names defined by the user. In an alternate form returned when line number information is requested, the same token might be represented as (1, 'if', 12), where the 12 represents the line number at which the terminal symbol was found.

Terminal elements are represented in much the same way, but without any child elements and the addition of the source text which was identified. The example of the if keyword above is representative. The various types of terminal symbols are defined in the C header file Include/token.h and the Python module token.

The ST objects are not required to support the functionality of this module, but are provided for three purposes: to allow an application to amortize the cost of processing complex parse trees, to provide a parse tree representation which conserves memory space when compared to the Python list or tuple representation, and to ease the creation of additional modules in C which manipulate parse trees. A simple « wrapper » class may be created in Python to hide the use of ST objects.

The parser module defines functions for a few distinct purposes. The most important purposes are to create ST objects and to convert ST objects to other representations such as parse trees and compiled code objects, but there are also functions which serve to query the type of parse tree represented by an ST object.

Voir aussi

Module symbol

Useful constants representing internal nodes of the parse tree.

Module token

Useful constants representing leaf nodes of the parse tree and functions for testing node values.

32.1.1. Creating ST Objects

ST objects may be created from source code or from a parse tree. When creating an ST object from source, different functions are used to create the 'eval' and 'exec' forms.

parser.expr(source)

The expr() function parses the parameter source as if it were an input to compile(source, 'file.py', 'eval'). If the parse succeeds, an ST object is created to hold the internal parse tree representation, otherwise an appropriate exception is raised.

parser.suite(source)

The suite() function parses the parameter source as if it were an input to compile(source, 'file.py', 'exec'). If the parse succeeds, an ST object is created to hold the internal parse tree representation, otherwise an appropriate exception is raised.

parser.sequence2st(sequence)

This function accepts a parse tree represented as a sequence and builds an internal representation if possible. If it can validate that the tree conforms to the Python grammar and all nodes are valid node types in the host version of Python, an ST object is created from the internal representation and returned to the called. If there is a problem creating the internal representation, or if the tree cannot be validated, a ParserError exception is raised. An ST object created this way should not be assumed to compile correctly; normal exceptions raised by compilation may still be initiated when the ST object is passed to compilest(). This may indicate problems not related to syntax (such as a MemoryError exception), but may also be due to constructs such as the result of parsing del f(0), which escapes the Python parser but is checked by the bytecode compiler.

Sequences representing terminal tokens may be represented as either two-element lists of the form (1, 'name') or as three-element lists of the form (1, 'name', 56). If the third element is present, it is assumed to be a valid line number. The line number may be specified for any subset of the terminal symbols in the input tree.

parser.tuple2st(sequence)

This is the same function as sequence2st(). This entry point is maintained for backward compatibility.

32.1.2. Converting ST Objects

ST objects, regardless of the input used to create them, may be converted to parse trees represented as list- or tuple- trees, or may be compiled into executable code objects. Parse trees may be extracted with or without line numbering information.

parser.st2list(st, line_info=False, col_info=False)

This function accepts an ST object from the caller in st and returns a Python list representing the equivalent parse tree. The resulting list representation can be used for inspection or the creation of a new parse tree in list form. This function does not fail so long as memory is available to build the list representation. If the parse tree will only be used for inspection, st2tuple() should be used instead to reduce memory consumption and fragmentation. When the list representation is required, this function is significantly faster than retrieving a tuple representation and converting that to nested lists.

If line_info is true, line number information will be included for all terminal tokens as a third element of the list representing the token. Note that the line number provided specifies the line on which the token ends. This information is omitted if the flag is false or omitted.

parser.st2tuple(st, line_info=False, col_info=False)

This function accepts an ST object from the caller in st and returns a Python tuple representing the equivalent parse tree. Other than returning a tuple instead of a list, this function is identical to st2list().

If line_info is true, line number information will be included for all terminal tokens as a third element of the list representing the token. This information is omitted if the flag is false or omitted.

parser.compilest(st, filename='<syntax-tree>')

The Python byte compiler can be invoked on an ST object to produce code objects which can be used as part of a call to the built-in exec() or eval() functions. This function provides the interface to the compiler, passing the internal parse tree from st to the parser, using the source file name specified by the filename parameter. The default value supplied for filename indicates that the source was an ST object.

Compiling an ST object may result in exceptions related to compilation; an example would be a SyntaxError caused by the parse tree for del f(0): this statement is considered legal within the formal grammar for Python but is not a legal language construct. The SyntaxError raised for this condition is actually generated by the Python byte-compiler normally, which is why it can be raised at this point by the parser module. Most causes of compilation failure can be diagnosed programmatically by inspection of the parse tree.

32.1.3. Queries on ST Objects

Two functions are provided which allow an application to determine if an ST was created as an expression or a suite. Neither of these functions can be used to determine if an ST was created from source code via expr() or suite() or from a parse tree via sequence2st().

parser.isexpr(st)

When st represents an 'eval' form, this function returns true, otherwise it returns false. This is useful, since code objects normally cannot be queried for this information using existing built-in functions. Note that the code objects created by compilest() cannot be queried like this either, and are identical to those created by the built-in compile() function.

parser.issuite(st)

This function mirrors isexpr() in that it reports whether an ST object represents an 'exec' form, commonly known as a « suite. » It is not safe to assume that this function is equivalent to not isexpr(st), as additional syntactic fragments may be supported in the future.

32.1.4. Exceptions and Error Handling

The parser module defines a single exception, but may also pass other built-in exceptions from other portions of the Python runtime environment. See each function for information about the exceptions it can raise.

exception parser.ParserError

Exception raised when a failure occurs within the parser module. This is generally produced for validation failures rather than the built-in SyntaxError raised during normal parsing. The exception argument is either a string describing the reason of the failure or a tuple containing a sequence causing the failure from a parse tree passed to sequence2st() and an explanatory string. Calls to sequence2st() need to be able to handle either type of exception, while calls to other functions in the module will only need to be aware of the simple string values.

Note that the functions compilest(), expr(), and suite() may raise exceptions which are normally raised by the parsing and compilation process. These include the built in exceptions MemoryError, OverflowError, SyntaxError, and SystemError. In these cases, these exceptions carry all the meaning normally associated with them. Refer to the descriptions of each function for detailed information.

32.1.5. ST Objects

Ordered and equality comparisons are supported between ST objects. Pickling of ST objects (using the pickle module) is also supported.

parser.STType

The type of the objects returned by expr(), suite() and sequence2st().

ST objects have the following methods:

ST.compile(filename='<syntax-tree>')

Same as compilest(st, filename).

ST.isexpr()

Same as isexpr(st).

ST.issuite()

Same as issuite(st).

ST.tolist(line_info=False, col_info=False)

Same as st2list(st, line_info, col_info).

ST.totuple(line_info=False, col_info=False)

Same as st2tuple(st, line_info, col_info).

32.1.6. Example: Emulation of compile()

While many useful operations may take place between parsing and bytecode generation, the simplest operation is to do nothing. For this purpose, using the parser module to produce an intermediate data structure is equivalent to the code

>>> code = compile('a + 5', 'file.py', 'eval')
>>> a = 5
>>> eval(code)
10

The equivalent operation using the parser module is somewhat longer, and allows the intermediate internal parse tree to be retained as an ST object:

>>> import parser
>>> st = parser.expr('a + 5')
>>> code = st.compile('file.py')
>>> a = 5
>>> eval(code)
10

An application which needs both ST and code objects can package this code into readily available functions:

import parser

def load_suite(source_string):
    st = parser.suite(source_string)
    return st, st.compile()

def load_expression(source_string):
    st = parser.expr(source_string)
    return st, st.compile()

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32.2. ast — Arbres Syntaxiques Abstraits

Code source : Lib/ast.py [https://github.com/python/cpython/tree/3.6/Lib/ast.py]

Le module ast permet aux applications Python de traiter la grammaire abstraite de l’arbre syntaxique Python. La grammaire abstraite Python elle-même est susceptible d’être modifiée à chaque nouvelle version de Python; ce module permet de trouver à quoi la grammaire actuelle ressemble.

Un arbre syntaxique abstrait peut être généré en passant l’option ast.PyCF_ONLY_AST à la fonction native compile(), ou en utilisant la fonction de facilité parse() fournie par le module. Le résultat est un arbre composé d’objets dont les classes héritent toutes de ast.AST. Un arbre syntaxique abstrait peut être compilé en code objet Python en utilisant la fonction native compile().

32.2.1. Les classes nœud

class ast.AST

C’est la classe de base de toute classe nœud de l’AST. Les classes nœud courantes sont dérivées du fichier Parser/Python.asdl, qui est reproduit ci-dessous. Ils sont définis dans le module C _ast et ré-exportés dans le module ast.

Il y a une classe définie pour chacun des symboles présents à gauche dans la grammaire abstraite (par exemple, ast.stmt ou ast.expr). En plus de cela, il y a une classe définie pour chacun des constructeurs présentés à droite; ces classes héritent des classes situées à gauche dans l’arbre. Par exemple, la classe ast.BinOp hérite de la classe ast.expr. Pour les règles de réécriture avec alternatives (comme sums), la partie gauche est abstraite : seules les instances des constructeurs spécifiques aux nœuds sont créés.

_fields

Chaque classe concrète possède un attribut _fields donnant les noms de tous les nœuds enfants.

Chaque instance d’une classe concrète possède un attribut pour chaque nœud enfant, du type défini par la grammaire. Par exemple, les instances ast.BinOp possèdent un attribut left de type ast.expr.

Si ces attributs sont marqués comme optionnels dans la grammaire (en utilisant un point d’interrogation ?), la valeur peut être None. Si les attributs peuvent avoir zéro ou plus valeurs (marqués avec un astérisque *), les valeurs sont représentées par des listes Python. Tous les attributs possibles doivent être présents et avoir une valeur valide pour compiler un AST avec compile().

lineno

col_offset

Les instances des sous-classes ast.expr et ast.stmt possèdent les attributs lineno et col_offset. L’attribut lineno est le numéro de ligne dans le code source (indexé à partir de 1 tel que la première ligne est la ligne 1) et l’attribut col_offset qui représente le décalage UTF-8 en byte du premier jeton qui a généré le nœud. Le décalage UTF-8 est enregistré parce que l’analyseur syntaxique utilise l’UTF-8 en interne.

Le constructeur d’une classe ast.T analyse ses arguments comme suit :

S’il y a des arguments positionnels, il doit y avoir autant de termes dans T._fields; ils sont assignés comme attributs portant ces noms.

S’il y a des arguments nommés, ils définissent les attributs de mêmes noms avec les valeurs données.

Par exemple, pour créer et peupler un nœud ast.UnaryOp, on peut utiliser

node = ast.UnaryOp()
node.op = ast.USub()
node.operand = ast.Num()
node.operand.n = 5
node.operand.lineno = 0
node.operand.col_offset = 0
node.lineno = 0
node.col_offset = 0

ou, plus compact

node = ast.UnaryOp(ast.USub(), ast.Num(5, lineno=0, col_offset=0),
                   lineno=0, col_offset=0)

32.2.2. Grammaire abstraite

La grammaire abstraite est actuellement définie comme suit :

-- ASDL's 7 builtin types are:
-- identifier, int, string, bytes, object, singleton, constant
--
-- singleton: None, True or False
-- constant can be None, whereas None means "no value" for object.

module Python
{
    mod = Module(stmt* body)
        | Interactive(stmt* body)
        | Expression(expr body)

        -- not really an actual node but useful in Jython's typesystem.
        | Suite(stmt* body)

    stmt = FunctionDef(identifier name, arguments args,
                       stmt* body, expr* decorator_list, expr? returns)
          | AsyncFunctionDef(identifier name, arguments args,
                             stmt* body, expr* decorator_list, expr? returns)

          | ClassDef(identifier name,
             expr* bases,
             keyword* keywords,
             stmt* body,
             expr* decorator_list)
          | Return(expr? value)

          | Delete(expr* targets)
          | Assign(expr* targets, expr value)
          | AugAssign(expr target, operator op, expr value)
          -- 'simple' indicates that we annotate simple name without parens
          | AnnAssign(expr target, expr annotation, expr? value, int simple)

          -- use 'orelse' because else is a keyword in target languages
          | For(expr target, expr iter, stmt* body, stmt* orelse)
          | AsyncFor(expr target, expr iter, stmt* body, stmt* orelse)
          | While(expr test, stmt* body, stmt* orelse)
          | If(expr test, stmt* body, stmt* orelse)
          | With(withitem* items, stmt* body)
          | AsyncWith(withitem* items, stmt* body)

          | Raise(expr? exc, expr? cause)
          | Try(stmt* body, excepthandler* handlers, stmt* orelse, stmt* finalbody)
          | Assert(expr test, expr? msg)

          | Import(alias* names)
          | ImportFrom(identifier? module, alias* names, int? level)

          | Global(identifier* names)
          | Nonlocal(identifier* names)
          | Expr(expr value)
          | Pass | Break | Continue

          -- XXX Jython will be different
          -- col_offset is the byte offset in the utf8 string the parser uses
          attributes (int lineno, int col_offset)

          -- BoolOp() can use left & right?
    expr = BoolOp(boolop op, expr* values)
         | BinOp(expr left, operator op, expr right)
         | UnaryOp(unaryop op, expr operand)
         | Lambda(arguments args, expr body)
         | IfExp(expr test, expr body, expr orelse)
         | Dict(expr* keys, expr* values)
         | Set(expr* elts)
         | ListComp(expr elt, comprehension* generators)
         | SetComp(expr elt, comprehension* generators)
         | DictComp(expr key, expr value, comprehension* generators)
         | GeneratorExp(expr elt, comprehension* generators)
         -- the grammar constrains where yield expressions can occur
         | Await(expr value)
         | Yield(expr? value)
         | YieldFrom(expr value)
         -- need sequences for compare to distinguish between
         -- x < 4 < 3 and (x < 4) < 3
         | Compare(expr left, cmpop* ops, expr* comparators)
         | Call(expr func, expr* args, keyword* keywords)
         | Num(object n) -- a number as a PyObject.
         | Str(string s) -- need to specify raw, unicode, etc?
         | FormattedValue(expr value, int? conversion, expr? format_spec)
         | JoinedStr(expr* values)
         | Bytes(bytes s)
         | NameConstant(singleton value)
         | Ellipsis
         | Constant(constant value)

         -- the following expression can appear in assignment context
         | Attribute(expr value, identifier attr, expr_context ctx)
         | Subscript(expr value, slice slice, expr_context ctx)
         | Starred(expr value, expr_context ctx)
         | Name(identifier id, expr_context ctx)
         | List(expr* elts, expr_context ctx)
         | Tuple(expr* elts, expr_context ctx)

          -- col_offset is the byte offset in the utf8 string the parser uses
          attributes (int lineno, int col_offset)

    expr_context = Load | Store | Del | AugLoad | AugStore | Param

    slice = Slice(expr? lower, expr? upper, expr? step)
          | ExtSlice(slice* dims)
          | Index(expr value)

    boolop = And | Or

    operator = Add | Sub | Mult | MatMult | Div | Mod | Pow | LShift
                 | RShift | BitOr | BitXor | BitAnd | FloorDiv

    unaryop = Invert | Not | UAdd | USub

    cmpop = Eq | NotEq | Lt | LtE | Gt | GtE | Is | IsNot | In | NotIn

    comprehension = (expr target, expr iter, expr* ifs, int is_async)

    excepthandler = ExceptHandler(expr? type, identifier? name, stmt* body)
                    attributes (int lineno, int col_offset)

    arguments = (arg* args, arg? vararg, arg* kwonlyargs, expr* kw_defaults,
                 arg? kwarg, expr* defaults)

    arg = (identifier arg, expr? annotation)
           attributes (int lineno, int col_offset)

    -- keyword arguments supplied to call (NULL identifier for **kwargs)
    keyword = (identifier? arg, expr value)

    -- import name with optional 'as' alias.
    alias = (identifier name, identifier? asname)

    withitem = (expr context_expr, expr? optional_vars)
}

32.2.3. Outils du module ast

À part la classe nœud, le module ast définit ces fonctions et classes utilitaires pour traverser les arbres syntaxiques abstraits :

ast.parse(source, filename='<unknown>', mode='exec')

Analyse le code source en un nœud AST. Équivalent à compile(source, filename, mode, ast.PyCF_ONLY_AST).

Avertissement

Il est possible de faire planter l’interpréteur Python avec des chaînes suffisamment grandes ou complexes lors de la compilation d’un objet AST dû à la limitation de la profondeur de la pile d’appels.

ast.literal_eval(node_or_string)

Évalue de manière sûre un nœud expression ou une chaîne de caractères contenant une expression littérale Python ou un conteneur. La chaîne de caractères ou le nœud fourni peut seulement faire partie des littéraux Python suivants : chaînes de caractères, bytes, nombres, n-uplets, listes, dictionnaires, ensembles, booléens, et None.

Cela peut être utilisé pour évaluer de manière sûre la chaîne de caractères contenant des valeurs Python de sources non fiable sans avoir besoin d’analyser les valeurs elles-mêmes. Cette fonction n’est pas capable d’évaluer des expressions complexes arbitraires, par exemple impliquant des opérateurs ou de l’indexation.

Avertissement

Il est possible de faire planter l’interpréteur Python avec des chaînes suffisamment grandes ou complexes lors de la compilation d’un objet AST dû à la limitation de la profondeur de la pile d’appels.

Modifié dans la version 3.2: Accepte maintenant les littéraux suivants bytes et sets.

ast.get_docstring(node, clean=True)

Return the docstring of the given node (which must be a FunctionDef, ClassDef or Module node), or None if it has no docstring. If clean is true, clean up the docstring’s indentation with inspect.cleandoc().

ast.fix_missing_locations(node)

Lorsque l’on compile un arbre avec compile(), le compilateur attend les attributs lineno et col_offset pour tous les nœuds qui les supportent. Il est fastidieux de les remplir pour les nœuds générés, cette fonction utilitaire ajoute ces attributs de manière récursive là où ils ne sont pas déjà définis, en les définissant comme les valeurs du nœud parent. Elle fonctionne récursivement en démarrant de node.

ast.increment_lineno(node, n=1)

Incrémente de n le numéro de ligne de chaque nœud dans l’arbre en commençant par le nœud node. C’est utile pour « déplacer du code » à un endroit différent dans un fichier.

ast.copy_location(new_node, old_node)

Copie le code source (lineno et col_offset) de l’ancien nœud old_node vers le nouveau nœud new_node si possible, et renvoie new_node.

ast.iter_fields(node)

Produit un n-uplet de (fieldname, value) pour chaque champ de node._fields qui est présent dans node.

ast.iter_child_nodes(node)

Produit tous les nœuds enfants directs de node, c’est à dire, tous les champs qui sont des nœuds et tous les éléments des champs qui sont des listes de nœuds.

ast.walk(node)

Produit récursivement tous les nœuds enfants dans l’arbre en commençant par node (node lui-même est inclus), sans ordre spécifique. C’est utile lorsque l’on souhaite modifier les nœuds sur place sans prêter attention au contexte.

class ast.NodeVisitor

Classe de base pour un visiteur de nœud, qui parcourt l’arbre syntaxique abstrait et appelle une fonction de visite pour chacun des nœuds trouvés. Cette fonction peut renvoyer une valeur qui est transmise par la méthode visit().

Cette classe est faite pour être dérivée, en ajoutant des méthodes de visite à la sous-classe.

visit(node)

Visite un nœud. L’implémentation par défaut appelle la méthode self.visit_classname où classname représente le nom de la classe du nœud, ou generic_visit() si cette méthode n’existe pas.

generic_visit(node)

Le visiteur appelle la méthode visit() de tous les enfants du nœud.

Notons que les nœuds enfants qui possèdent une méthode de visite spéciale ne seront pas visités à moins que le visiteur n’appelle la méthode generic_visit() ou ne les visite lui-même.

N’utilisez pas NodeVisitor si vous souhaitez appliquer des changements sur les nœuds lors du parcours. Pour cela, un visiteur spécial existe (NodeTransformer) qui permet les modifications.

class ast.NodeTransformer

Une sous-classe NodeVisitor qui traverse l’arbre syntaxique abstrait et permet les modifications des nœuds.

Le NodeTransformer traverse l’AST et utilise la valeur renvoyée par les méthodes du visiteur pour remplacer ou supprimer l’ancien nœud. Si la valeur renvoyée par la méthode du visiteur est None, le nœud est supprimé de sa position, sinon il est remplacé par la valeur de retour. La valeur de retour peut être le nœud original et dans ce cas, il n’y a pas de remplacement.

Voici un exemple du transformer qui réécrit les occurrences du dictionnaire (foo) en data['foo'] :

class RewriteName(NodeTransformer):

    def visit_Name(self, node):
        return copy_location(Subscript(
            value=Name(id='data', ctx=Load()),
            slice=Index(value=Str(s=node.id)),
            ctx=node.ctx
        ), node)

Gardez en tête que si un nœud sur lequel vous travaillez a des nœuds enfants, vous devez transformer également ces nœuds enfant vous-même ou appeler d’abord la méthode generic_visit() sur le nœud.

Pour les nœuds qui font partie d’une collection d’instructions (cela s’applique à tous les nœuds instruction), le visiteur peut aussi renvoyer la liste des nœuds plutôt qu’un seul nœud.

Utilisation typique du transformer :

node = YourTransformer().visit(node)

ast.dump(node, annotate_fields=True, include_attributes=False)

Renvoie un dump formaté de l’arbre dans node. C’est principalement utile à des fins de débogage. La chaîne de caractères renvoyée présente les noms et valeurs des champs. Cela rend le code impossible à évaluer, si l’on souhaite évaluer ce code, l’option annotate_fields doit être définie comme False. Les attributs comme les numéros de ligne et les décalages de colonne ne sont pas récupérés par défaut. Si l’on souhaite les récupérer, l’option include_attributes peut être définie comme True.

Voir aussi

Green Tree Snakes [https://greentreesnakes.readthedocs.org/], an external documentation resource, has good details on working with Python ASTs.

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32.3. symtable — Access to the compiler’s symbol tables

Code source : Lib/symtable.py [https://github.com/python/cpython/tree/3.6/Lib/symtable.py]

Symbol tables are generated by the compiler from AST just before bytecode is generated. The symbol table is responsible for calculating the scope of every identifier in the code. symtable provides an interface to examine these tables.

32.3.1. Generating Symbol Tables

symtable.symtable(code, filename, compile_type)

Return the toplevel SymbolTable for the Python source code. filename is the name of the file containing the code. compile_type is like the mode argument to compile().

32.3.2. Examining Symbol Tables

class symtable.SymbolTable

A namespace table for a block. The constructor is not public.

get_type()

Return the type of the symbol table. Possible values are 'class', 'module', and 'function'.

get_id()

Return the table’s identifier.

get_name()

Return the table’s name. This is the name of the class if the table is for a class, the name of the function if the table is for a function, or 'top' if the table is global (get_type() returns 'module').

get_lineno()

Return the number of the first line in the block this table represents.

is_optimized()

Return True if the locals in this table can be optimized.

is_nested()

Return True if the block is a nested class or function.

has_children()

Return True if the block has nested namespaces within it. These can be obtained with get_children().

has_exec()

Return True if the block uses exec.

get_identifiers()

Return a list of names of symbols in this table.

lookup(name)

Lookup name in the table and return a Symbol instance.

get_symbols()

Return a list of Symbol instances for names in the table.

get_children()

Return a list of the nested symbol tables.

class symtable.Function

A namespace for a function or method. This class inherits SymbolTable.

get_parameters()

Return a tuple containing names of parameters to this function.

get_locals()

Return a tuple containing names of locals in this function.

get_globals()

Return a tuple containing names of globals in this function.

get_frees()

Return a tuple containing names of free variables in this function.

class symtable.Class

A namespace of a class. This class inherits SymbolTable.

get_methods()

Return a tuple containing the names of methods declared in the class.

class symtable.Symbol

An entry in a SymbolTable corresponding to an identifier in the source. The constructor is not public.

get_name()

Return the symbol’s name.

is_referenced()

Return True if the symbol is used in its block.

is_imported()

Return True if the symbol is created from an import statement.

is_parameter()

Return True if the symbol is a parameter.

is_global()

Return True if the symbol is global.

is_declared_global()

Return True if the symbol is declared global with a global statement.

is_local()

Return True if the symbol is local to its block.

is_free()

Return True if the symbol is referenced in its block, but not assigned to.

is_assigned()

Return True if the symbol is assigned to in its block.

is_namespace()

Return True if name binding introduces new namespace.

If the name is used as the target of a function or class statement, this will be true.

Par exemple :

>>> table = symtable.symtable("def some_func(): pass", "string", "exec")
>>> table.lookup("some_func").is_namespace()
True

Note that a single name can be bound to multiple objects. If the result is True, the name may also be bound to other objects, like an int or list, that does not introduce a new namespace.

get_namespaces()

Return a list of namespaces bound to this name.

get_namespace()

Return the namespace bound to this name. If more than one namespace is bound, ValueError is raised.

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32.4. symbol — Constantes utilisées dans les Arbres Syntaxiques

Code source : Lib/symbol.py [https://github.com/python/cpython/tree/3.6/Lib/symbol.py]

Ce module fournit des constantes représentant les valeurs numériques des nœuds internes de l’analyseur. Contrairement à la plupart des constantes en Python, celles-ci utilisent des noms en minuscules. Référez-vous au fichier Grammar/Grammar dans la distribution de Python pour les définitions de ces noms dans le contexte de la grammaire du langage. La valeur numérique correspondant au nom peut changer d’une version de Python à l’autre.

Ce module fournit aussi ces objets :

symbol.sym_name

Dictionnaire faisant correspondre les valeurs numériques des constantes définies dans ce module à leurs noms, permettant de générer une représentation plus humaine des arbres syntaxiques.

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32.5. token — Constantes utilisées avec les arbres d’analyse Python (parse trees)

Code source : Lib/token.py [https://github.com/python/cpython/tree/3.6/Lib/token.py]

Ce module fournit des constantes qui représentent les valeurs numériques des nœuds enfants du parse tree (les jetons « terminaux »). Voir le fichier Grammar/Grammar dans la distribution Python pour la définitions des noms dans le contexte de la grammaire. Les valeurs numériques correspondant aux noms sont susceptibles de changer entre deux versions de Python.

Le module fournit également une correspondance entre les codes numériques et les noms et certaines fonctions. Les fonctions reflètent les définitions des fichiers d’en-tête C de Python.

token.tok_name

Dictionnaire faisant correspondre les valeurs numériques des constantes définies dans ce module à leurs noms, permettant de générer une représentation plus humaine des arbres syntaxiques.

token.ISTERMINAL(x)

Renvoie True pour les valeurs des jetons terminaux.

token.ISNONTERMINAL(x)

Renvoie True pour les valeurs des jetons non terminaux.

token.ISEOF(x)

Renvoie True si x est le marqueur indiquant la fin de de la source.

Les constantes associées aux jetons sont :

token.ENDMARKER

token.NAME

token.NUMBER

token.STRING

token.NEWLINE

token.INDENT

token.DEDENT

token.LPAR

token.RPAR

token.LSQB

token.RSQB

token.COLON

token.COMMA

token.SEMI

token.PLUS

token.MINUS

token.STAR

token.SLASH

token.VBAR

token.AMPER

token.LESS

token.GREATER

token.EQUAL

token.DOT

token.PERCENT

token.LBRACE

token.RBRACE

token.EQEQUAL

token.NOTEQUAL

token.LESSEQUAL

token.GREATEREQUAL

token.TILDE

token.CIRCUMFLEX

token.LEFTSHIFT

token.RIGHTSHIFT

token.DOUBLESTAR

token.PLUSEQUAL

token.MINEQUAL

token.STAREQUAL

token.SLASHEQUAL

token.PERCENTEQUAL

token.AMPEREQUAL

token.VBAREQUAL

token.CIRCUMFLEXEQUAL

token.LEFTSHIFTEQUAL

token.RIGHTSHIFTEQUAL

token.DOUBLESTAREQUAL

token.DOUBLESLASH

token.DOUBLESLASHEQUAL

token.AT

token.ATEQUAL

token.RARROW

token.ELLIPSIS

token.OP

token.AWAIT

token.ASYNC

token.ERRORTOKEN

token.N_TOKENS

token.NT_OFFSET

Modifié dans la version 3.5: Added AWAIT and ASYNC tokens. Starting with Python 3.7, « async » and « await » will be tokenized as NAME tokens, and AWAIT and ASYNC will be removed.

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32.6. keyword — Tester si des chaînes sont des mot-clés Python

Code source : Lib/keyword.py [https://github.com/python/cpython/tree/3.6/Lib/keyword.py]

Ce module permet à un programme Python de déterminer si une chaîne représente un mot-clé.

keyword.iskeyword(s)

Renvoie vrai si s est un mot-clé Python.

keyword.kwlist

Séquence contenant tous les mots-clés définis par l’interpréteur. Si certains mots-clés sont définis pour être actifs seulement si des instructions __future__ particulières sont effectives, ils seront tout de même inclus.

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32.7. tokenize — Analyseur lexical de Python

Code source : Lib/tokenize.py [https://github.com/python/cpython/tree/3.6/Lib/tokenize.py]

Le module tokenize fournit un analyseur lexical pour Python, implémenté en Python. L’analyseur de ce module renvoie les commentaire sous forme de token, se qui le rend intéressant pour implémenter des pretty-printers, typiquement pour faire de la coloration syntaxique.

Pour simplifier la gestion de flux de tokens, tous les tokens operator et delimiter, ainsi que les Ellipsis* sont renvoyés en utilisant le token générique OP. Le type exact peut être déterminé en vérifiant la propriété exact_type du named tuple renvoyé par tokenize.tokenize().

32.7.1. Analyse Lexicale

Le point d’entrée principal est un générateur :

tokenize.tokenize(readline)

Le générateur tokenize() prend un argument readline qui doit être un objet appelable exposant la même interface que la méthode io.IOBase.readline() des objets fichiers. Chaque appel a la fonction doit renvoyer une ligne sous forme de bytes.

Le générateur fournit des quintuplet contenants : le type du token, sa chaîne, un couple d’entiers (srow, scol) indiquant la ligne et la colonne où le token commence, un couple d’entiers (erow, ecol) indiquant la ligne et la colonne où il se termine, puis la ligne dans laquelle il a été trouvé. La ligne donnée (le dernier élément du tuple) est la ligne « logique », les continuation lines étant incluses. Le tuple est renvoyé sous forme de named tuple dont les noms sont : type string start end line.

The returned named tuple has an additional property named exact_type that contains the exact operator type for token.OP tokens. For all other token types exact_type equals the named tuple type field.

Modifié dans la version 3.1: Soutien ajouté pour tuples nommé.

Modifié dans la version 3.3: Soutien ajouté pour exact_type.

tokenize() détermine le codage source du fichier en recherchant une nomenclature UTF-8 ou un cookie d’encodage, selon la PEP 263 [https://www.python.org/dev/peps/pep-0263].

All constants from the token module are also exported from tokenize, as are three additional token type values:

tokenize.COMMENT

Valeur du jeton utilisée pour indiquer un commentaire.

tokenize.NL

Token value used to indicate a non-terminating newline. The NEWLINE token indicates the end of a logical line of Python code; NL tokens are generated when a logical line of code is continued over multiple physical lines.

tokenize.ENCODING

Token value that indicates the encoding used to decode the source bytes into text. The first token returned by tokenize() will always be an ENCODING token.

Une autre fonction est fournie pour inverser le processus de tokenisation. Ceci est utile pour créer des outils permettant de codifier un script, de modifier le flux de jetons et de réécrire le script modifié.

tokenize.untokenize(iterable)

Convertit les jetons en code source Python. L”iterable doit renvoyer des séquences avec au moins deux éléments, le type de jeton et la chaîne de caractères associée. Tout élément de séquence supplémentaire est ignoré.

Le script reconstruit est renvoyé sous la forme d’une chaîne unique. Le résultat est garanti pour que le jeton corresponde à l’entrée afin que la conversion soit sans perte et que les allers et retours soient assurés. La garantie ne s’applique qu’au type de jeton et à la chaîne de jetons car l’espacement entre les jetons (positions des colonnes) peut changer.

It returns bytes, encoded using the ENCODING token, which is the first token sequence output by tokenize().

tokenize() a besoin de détecter le codage des fichiers sources qu’il code. La fonction utilisée pour cela est disponible :

tokenize.detect_encoding(readline)

La fonction detect_encoding() est utilisée pour détecter l’encodage à utiliser pour décoder un fichier source Python. Il nécessite un seul argument, readline, de la même manière que le générateur tokenize().

Il appelle readline au maximum deux fois et renvoie le codage utilisé (sous forme de chaîne) et une liste de toutes les lignes (non décodées à partir des octets) dans lesquelles il a été lu.

It detects the encoding from the presence of a UTF-8 BOM or an encoding cookie as specified in PEP 263 [https://www.python.org/dev/peps/pep-0263]. If both a BOM and a cookie are present, but disagree, a SyntaxError will be raised. Note that if the BOM is found, 'utf-8-sig' will be returned as an encoding.

Si aucun codage n’est spécifié, la valeur par défaut, 'utf-8', sera renvoyée.

Utilisez open() pour ouvrir les fichiers source Python : ça utilise detect_encoding() pour détecter le codage du fichier.

tokenize.open(filename)

Ouvre un fichier en mode lecture seule en utilisant l’encodage détecté par dectect_encoding().

Nouveau dans la version 3.2.

exception tokenize.TokenError

Déclenché lorsque soit une docstring soit une expression qui pourrait être divisée sur plusieurs lignes n’est pas complété dans le fichier, par exemple :

"""Beginning of
docstring

ou :

[1,
 2,
 3

Note that unclosed single-quoted strings do not cause an error to be raised. They are tokenized as ERRORTOKEN, followed by the tokenization of their contents.

32.7.2. Utilisation en ligne de commande.

Nouveau dans la version 3.3.

Le module tokenize peut être exécuté en tant que script à partir de la ligne de commande. C’est aussi simple que :

python -m tokenize [-e] [filename.py]

Les options suivantes sont acceptées :

-h, --help

Montre ce message d’aide et quitte

-e, --exact

Affiche les noms de jetons en utilisant le même type.

Si filename.py est spécifié, son contenu est tokenisé vers stdout. Sinon, la tokenisation est effectuée sur ce qui est fourni sur stdin.

32.7.3. Exemples

Exemple d’un script qui transforme les littéraux de type float en type Decimal :

from tokenize import tokenize, untokenize, NUMBER, STRING, NAME, OP
from io import BytesIO

def decistmt(s):
    """Substitute Decimals for floats in a string of statements.

    >>> from decimal import Decimal
    >>> s = 'print(+21.3e-5*-.1234/81.7)'
    >>> decistmt(s)
    "print (+Decimal ('21.3e-5')*-Decimal ('.1234')/Decimal ('81.7'))"

    The format of the exponent is inherited from the platform C library.
    Known cases are "e-007" (Windows) and "e-07" (not Windows).  Since
    we're only showing 12 digits, and the 13th isn't close to 5, the
    rest of the output should be platform-independent.

    >>> exec(s)  #doctest: +ELLIPSIS
    -3.21716034272e-0...7

    Output from calculations with Decimal should be identical across all
    platforms.

    >>> exec(decistmt(s))
    -3.217160342717258261933904529E-7
    """
    result = []
    g = tokenize(BytesIO(s.encode('utf-8')).readline)  # tokenize the string
    for toknum, tokval, _, _, _ in g:
        if toknum == NUMBER and '.' in tokval:  # replace NUMBER tokens
            result.extend([
                (NAME, 'Decimal'),
                (OP, '('),
                (STRING, repr(tokval)),
                (OP, ')')
            ])
        else:
            result.append((toknum, tokval))
    return untokenize(result).decode('utf-8')

Exemple de tokenisation à partir de la ligne de commande. Le script :

def say_hello():
    print("Hello, World!")

say_hello()

sera tokenisé à la sortie suivante où la première colonne est la plage des coordonnées de la ligne/colonne où se trouve le jeton, la deuxième colonne est le nom du jeton, et la dernière colonne est la valeur du jeton (le cas échéant)

$ python -m tokenize hello.py
0,0-0,0:            ENCODING       'utf-8'
1,0-1,3:            NAME           'def'
1,4-1,13:           NAME           'say_hello'
1,13-1,14:          OP             '('
1,14-1,15:          OP             ')'
1,15-1,16:          OP             ':'
1,16-1,17:          NEWLINE        '\n'
2,0-2,4:            INDENT         '    '
2,4-2,9:            NAME           'print'
2,9-2,10:           OP             '('
2,10-2,25:          STRING         '"Hello, World!"'
2,25-2,26:          OP             ')'
2,26-2,27:          NEWLINE        '\n'
3,0-3,1:            NL             '\n'
4,0-4,0:            DEDENT         ''
4,0-4,9:            NAME           'say_hello'
4,9-4,10:           OP             '('
4,10-4,11:          OP             ')'
4,11-4,12:          NEWLINE        '\n'
5,0-5,0:            ENDMARKER      ''

The exact token type names can be displayed using the -e option:

$ python -m tokenize -e hello.py
0,0-0,0:            ENCODING       'utf-8'
1,0-1,3:            NAME           'def'
1,4-1,13:           NAME           'say_hello'
1,13-1,14:          LPAR           '('
1,14-1,15:          RPAR           ')'
1,15-1,16:          COLON          ':'
1,16-1,17:          NEWLINE        '\n'
2,0-2,4:            INDENT         '    '
2,4-2,9:            NAME           'print'
2,9-2,10:           LPAR           '('
2,10-2,25:          STRING         '"Hello, World!"'
2,25-2,26:          RPAR           ')'
2,26-2,27:          NEWLINE        '\n'
3,0-3,1:            NL             '\n'
4,0-4,0:            DEDENT         ''
4,0-4,9:            NAME           'say_hello'
4,9-4,10:           LPAR           '('
4,10-4,11:          RPAR           ')'
4,11-4,12:          NEWLINE        '\n'
5,0-5,0:            ENDMARKER      ''

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32.8. tabnanny — Détection d’indentation ambiguë

Code source : Lib/tabnanny.py [https://github.com/python/cpython/tree/3.6/Lib/tabnanny.py]

Pour l’instant ce module est destiné à être appelé comme un script. Toutefois, il est possible de l’importer dans un IDE et d’utiliser la fonction check() décrite ci-dessous.

Note

L’API fournie par ce module est susceptible de changer dans les versions futures ; ces modifications peuvent ne pas être rétro-compatibles.

tabnanny.check(file_or_dir)

Si file_or_dir est un répertoire et non un lien symbolique, alors descend récursivement l’arborescence de répertoire nommé par file_or_dir, en vérifiant tous les fichiers .py en chemin. Si file_or_dir est un fichier source Python ordinaire, il est vérifié pour les problèmes liés aux espaces blancs. Les messages de diagnostic sont écrits sur la sortie standard à l’aide de la fonction print().

tabnanny.verbose

Option indiquant s’il faut afficher des messages détaillés. Cela est incrémenté par l’option -v s’il est appelé comme un script.

tabnanny.filename_only

Option indiquant s’il faut afficher uniquement les noms de fichiers contenant des problèmes liés aux espaces blancs. Est défini à True par l’option -q s’il est appelé comme un script.

exception tabnanny.NannyNag

Déclenché par process_tokens() si une indentation ambiguë est détectée. Capturé et géré dans check().

tabnanny.process_tokens(tokens)

Cette fonction est utilisée par check() pour traiter les jetons générés par le module tokenize.

Voir aussi

Module tokenize

Analyseur lexical pour le code source Python.

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32.9. pyclbr — Python class browser support

Code source : Lib/pyclbr.py [https://github.com/python/cpython/tree/3.6/Lib/pyclbr.py]

The pyclbr module can be used to determine some limited information about the classes, methods and top-level functions defined in a module. The information provided is sufficient to implement a traditional three-pane class browser. The information is extracted from the source code rather than by importing the module, so this module is safe to use with untrusted code. This restriction makes it impossible to use this module with modules not implemented in Python, including all standard and optional extension modules.

pyclbr.readmodule(module, path=None)

Read a module and return a dictionary mapping class names to class descriptor objects. The parameter module should be the name of a module as a string; it may be the name of a module within a package. The path parameter should be a sequence, and is used to augment the value of sys.path, which is used to locate module source code.

pyclbr.readmodule_ex(module, path=None)

Like readmodule(), but the returned dictionary, in addition to mapping class names to class descriptor objects, also maps top-level function names to function descriptor objects. Moreover, if the module being read is a package, the key '__path__' in the returned dictionary has as its value a list which contains the package search path.

32.9.1. Objets classes

The Class objects used as values in the dictionary returned by readmodule() and readmodule_ex() provide the following data attributes:

Class.module

The name of the module defining the class described by the class descriptor.

Class.name

The name of the class.

Class.super

A list of Class objects which describe the immediate base classes of the class being described. Classes which are named as superclasses but which are not discoverable by readmodule() are listed as a string with the class name instead of as Class objects.

Class.methods

A dictionary mapping method names to line numbers.

Class.file

Name of the file containing the class statement defining the class.

Class.lineno

The line number of the class statement within the file named by file.

32.9.2. Objets fonctions

The Function objects used as values in the dictionary returned by readmodule_ex() provide the following attributes:

Function.module

The name of the module defining the function described by the function descriptor.

Function.name

The name of the function.

Function.file

Name of the file containing the def statement defining the function.

Function.lineno

The line number of the def statement within the file named by file.

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32.10. py_compile — Compile Python source files

Code source : Lib/py_compile.py [https://github.com/python/cpython/tree/3.6/Lib/py_compile.py]

The py_compile module provides a function to generate a byte-code file from a source file, and another function used when the module source file is invoked as a script.

Though not often needed, this function can be useful when installing modules for shared use, especially if some of the users may not have permission to write the byte-code cache files in the directory containing the source code.

exception py_compile.PyCompileError

Exception raised when an error occurs while attempting to compile the file.

py_compile.compile(file, cfile=None, dfile=None, doraise=False, optimize=-1)

Compile a source file to byte-code and write out the byte-code cache file. The source code is loaded from the file named file. The byte-code is written to cfile, which defaults to the PEP 3147 [https://www.python.org/dev/peps/pep-3147]/PEP 488 [https://www.python.org/dev/peps/pep-0488] path, ending in .pyc. For example, if file is /foo/bar/baz.py cfile will default to /foo/bar/__pycache__/baz.cpython-32.pyc for Python 3.2. If dfile is specified, it is used as the name of the source file in error messages when instead of file. If doraise is true, a PyCompileError is raised when an error is encountered while compiling file. If doraise is false (the default), an error string is written to sys.stderr, but no exception is raised. This function returns the path to byte-compiled file, i.e. whatever cfile value was used.

If the path that cfile becomes (either explicitly specified or computed) is a symlink or non-regular file, FileExistsError will be raised. This is to act as a warning that import will turn those paths into regular files if it is allowed to write byte-compiled files to those paths. This is a side-effect of import using file renaming to place the final byte-compiled file into place to prevent concurrent file writing issues.

optimize controls the optimization level and is passed to the built-in compile() function. The default of -1 selects the optimization level of the current interpreter.

Modifié dans la version 3.2: Changed default value of cfile to be PEP 3147 [https://www.python.org/dev/peps/pep-3147]-compliant. Previous default was file + 'c' ('o' if optimization was enabled). Also added the optimize parameter.

Modifié dans la version 3.4: Changed code to use importlib for the byte-code cache file writing. This means file creation/writing semantics now match what importlib does, e.g. permissions, write-and-move semantics, etc. Also added the caveat that FileExistsError is raised if cfile is a symlink or non-regular file.

py_compile.main(args=None)

Compile several source files. The files named in args (or on the command line, if args is None) are compiled and the resulting byte-code is cached in the normal manner. This function does not search a directory structure to locate source files; it only compiles files named explicitly. If '-' is the only parameter in args, the list of files is taken from standard input.

Modifié dans la version 3.2: Added support for '-'.

When this module is run as a script, the main() is used to compile all the files named on the command line. The exit status is nonzero if one of the files could not be compiled.

Voir aussi

Module compileall

Utilities to compile all Python source files in a directory tree.

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32.11. compileall — Byte-compile Python libraries

Code source : Lib/compileall.py [https://github.com/python/cpython/tree/3.6/Lib/compileall.py]

This module provides some utility functions to support installing Python libraries. These functions compile Python source files in a directory tree. This module can be used to create the cached byte-code files at library installation time, which makes them available for use even by users who don’t have write permission to the library directories.

32.11.1. Command-line use

This module can work as a script (using python -m compileall) to compile Python sources.

directory ...

file ...

Positional arguments are files to compile or directories that contain source files, traversed recursively. If no argument is given, behave as if the command line was -l <directories from sys.path>.

-l

Do not recurse into subdirectories, only compile source code files directly contained in the named or implied directories.

-f

Force rebuild even if timestamps are up-to-date.

-q

Do not print the list of files compiled. If passed once, error messages will still be printed. If passed twice (-qq), all output is suppressed.

-d destdir

Directory prepended to the path to each file being compiled. This will appear in compilation time tracebacks, and is also compiled in to the byte-code file, where it will be used in tracebacks and other messages in cases where the source file does not exist at the time the byte-code file is executed.

-x regex

regex is used to search the full path to each file considered for compilation, and if the regex produces a match, the file is skipped.

-i list

Read the file list and add each line that it contains to the list of files and directories to compile. If list is -, read lines from stdin.

-b

Write the byte-code files to their legacy locations and names, which may overwrite byte-code files created by another version of Python. The default is to write files to their PEP 3147 [https://www.python.org/dev/peps/pep-3147] locations and names, which allows byte-code files from multiple versions of Python to coexist.

-r

Control the maximum recursion level for subdirectories. If this is given, then -l option will not be taken into account. python -m compileall <directory> -r 0 is equivalent to python -m compileall <directory> -l.

-j N

Use N workers to compile the files within the given directory. If 0 is used, then the result of os.cpu_count() will be used.

Modifié dans la version 3.2: Added the -i, -b and -h options.

Modifié dans la version 3.5: Added the -j, -r, and -qq options. -q option was changed to a multilevel value. -b will always produce a byte-code file ending in .pyc, never .pyo.

There is no command-line option to control the optimization level used by the compile() function, because the Python interpreter itself already provides the option: python -O -m compileall.

32.11.2. Public functions

compileall.compile_dir(dir, maxlevels=10, ddir=None, force=False, rx=None, quiet=0, legacy=False, optimize=-1, workers=1)

Recursively descend the directory tree named by dir, compiling all .py files along the way. Return a true value if all the files compiled successfully, and a false value otherwise.

The maxlevels parameter is used to limit the depth of the recursion; it defaults to 10.

If ddir is given, it is prepended to the path to each file being compiled for use in compilation time tracebacks, and is also compiled in to the byte-code file, where it will be used in tracebacks and other messages in cases where the source file does not exist at the time the byte-code file is executed.

If force is true, modules are re-compiled even if the timestamps are up to date.

If rx is given, its search method is called on the complete path to each file considered for compilation, and if it returns a true value, the file is skipped.

If quiet is False or 0 (the default), the filenames and other information are printed to standard out. Set to 1, only errors are printed. Set to 2, all output is suppressed.

If legacy is true, byte-code files are written to their legacy locations and names, which may overwrite byte-code files created by another version of Python. The default is to write files to their PEP 3147 [https://www.python.org/dev/peps/pep-3147] locations and names, which allows byte-code files from multiple versions of Python to coexist.

optimize specifies the optimization level for the compiler. It is passed to the built-in compile() function.

The argument workers specifies how many workers are used to compile files in parallel. The default is to not use multiple workers. If the platform can’t use multiple workers and workers argument is given, then sequential compilation will be used as a fallback. If workers is lower than 0, a ValueError will be raised.

Modifié dans la version 3.2: Added the legacy and optimize parameter.

Modifié dans la version 3.5: Added the workers parameter.

Modifié dans la version 3.5: quiet parameter was changed to a multilevel value.

Modifié dans la version 3.5: The legacy parameter only writes out .pyc files, not .pyo files no matter what the value of optimize is.

Modifié dans la version 3.6: Accepte un path-like object.

compileall.compile_file(fullname, ddir=None, force=False, rx=None, quiet=0, legacy=False, optimize=-1)

Compile the file with path fullname. Return a true value if the file compiled successfully, and a false value otherwise.

If ddir is given, it is prepended to the path to the file being compiled for use in compilation time tracebacks, and is also compiled in to the byte-code file, where it will be used in tracebacks and other messages in cases where the source file does not exist at the time the byte-code file is executed.

If rx is given, its search method is passed the full path name to the file being compiled, and if it returns a true value, the file is not compiled and True is returned.

If quiet is False or 0 (the default), the filenames and other information are printed to standard out. Set to 1, only errors are printed. Set to 2, all output is suppressed.

If legacy is true, byte-code files are written to their legacy locations and names, which may overwrite byte-code files created by another version of Python. The default is to write files to their PEP 3147 [https://www.python.org/dev/peps/pep-3147] locations and names, which allows byte-code files from multiple versions of Python to coexist.

optimize specifies the optimization level for the compiler. It is passed to the built-in compile() function.

Nouveau dans la version 3.2.

Modifié dans la version 3.5: quiet parameter was changed to a multilevel value.

Modifié dans la version 3.5: The legacy parameter only writes out .pyc files, not .pyo files no matter what the value of optimize is.

compileall.compile_path(skip_curdir=True, maxlevels=0, force=False, quiet=0, legacy=False, optimize=-1)

Byte-compile all the .py files found along sys.path. Return a true value if all the files compiled successfully, and a false value otherwise.

If skip_curdir is true (the default), the current directory is not included in the search. All other parameters are passed to the compile_dir() function. Note that unlike the other compile functions, maxlevels defaults to 0.

Modifié dans la version 3.2: Added the legacy and optimize parameter.

Modifié dans la version 3.5: quiet parameter was changed to a multilevel value.

Modifié dans la version 3.5: The legacy parameter only writes out .pyc files, not .pyo files no matter what the value of optimize is.

To force a recompile of all the .py files in the Lib/ subdirectory and all its subdirectories:

import compileall

compileall.compile_dir('Lib/', force=True)

# Perform same compilation, excluding files in .svn directories.
import re
compileall.compile_dir('Lib/', rx=re.compile(r'[/\\][.]svn'), force=True)

# pathlib.Path objects can also be used.
import pathlib
compileall.compile_dir(pathlib.Path('Lib/'), force=True)

Voir aussi

Module py_compile

Byte-compile a single source file.

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32.12. dis – Désassembleur pour le code intermédiaire de Python

Code source : Lib/dis.py [https://github.com/python/cpython/tree/3.6/Lib/dis.py]

La bibliothèque dis supporte l’analyse du bytecode CPython en le désassemblant. Le code intermédiaire CPython, que cette bibliothèque prend en paramètre, est défini dans le fichier Include/opcode.h et est utilisé par le compilateur et l’interpréteur.

CPython implementation detail: Le code intermédiaire est un détail d’implémentation de l’interpréteur CPython. Il n’y a pas de garantie que le code intermédiaire sera ajouté, retiré, ou modifié dans les différentes versions de Python. L’utilisation de cette bibliothèque ne fonctionne pas nécessairement sur les machines virtuelles Python ni les différentes versions de Python.

Modifié dans la version 3.6: Utilisez 2 bits pour chaque instruction. Avant, le nombre de bits variait par instruction.

Exemple : Etant donné la fonction myfunc() :

def myfunc(alist):
    return len(alist)

la commande suivante peut-être utilisé pour afficher le désassemblage de myfunc() :

>>> dis.dis(myfunc)
  2           0 LOAD_GLOBAL              0 (len)
              2 LOAD_FAST                0 (alist)
              4 CALL_FUNCTION            1
              6 RETURN_VALUE

(Le « 2 » est un numéro de ligne).

32.12.1. Analyse du code intermédiaire

Nouveau dans la version 3.4.

L’analyse de l”API code intermédiaire permet de rassembler des blocs de code en Python dans une classe Bytecode, qui permet un accès facile aux détails du code compilé.

class dis.Bytecode(x, *, first_line=None, current_offset=None)

Analyse the bytecode corresponding to a function, generator, method, string of source code, or a code object (as returned by compile()).

Ceci est wrapper sur plusieurs fonctions de la liste ci-dessous, notamment get_instructions(), étant donné qu’une itération sur une instance de la classe Bytecode rend les opérations du code intermédiaire des instances de Instruction.

Si first_line ne vaut pas None, elle indique le nombre de la ligne qui doit être considérée comme première ligne source dans le code désassemblé. Autrement, les informations sur la ligne source sont prises directement à partir de la classe du code désassemblé.

Si la valeur de current_offset est différente de None, c’est une référence à un offset d’une instruction dans le code désassemblé. Cela veut dire que dis() va générer un marqueur de  » l’instruction en cours » contre le code d’opération donné.

classmethod from_traceback(tb)

Construisez une instance Bytecode à partir de la trace d’appel, en mettant current_offet à l’instruction responsable de l’exception.

codeobj

Le code compilé objet.

first_line

La première ligne source du code objet (si disponible)

dis()

Retourne une vue formatée des opérations du code intermédiaire (la même que celle envoyée par dis.dis(), mais comme une chaîne de caractères de plusieurs lignes ).

info()

Retourne une chaîne de caractères de plusieurs lignes formatée avec des informations détaillées sur l’objet code comme code_info().

Exemple :

>>> bytecode = dis.Bytecode(myfunc)
>>> for instr in bytecode:
...     print(instr.opname)
...
LOAD_GLOBAL
LOAD_FAST
CALL_FUNCTION
RETURN_VALUE

32.12.2. Analyse de fonctions

La bibliothèque dis comprend également l’analyse des fonctions suivantes, qui envoient l’entrée directement à la sortie souhaitée. Elles peuvent être utiles si il n’y a qu’une seule opération à effectuer, la représentation intermédiaire objet n’étant donc pas utile dans ce cas:

dis.code_info(x)

Return a formatted multi-line string with detailed code object information for the supplied function, generator, method, source code string or code object.

Il est à noter que le contenu exact des chaînes de caractères figurant dans les informations du code dépendent fortement sur l’implémentation, et peuvent changer arbitrairement sous machines virtuelles Python ou les versions de Python.

Nouveau dans la version 3.2.

dis.show_code(x, *, file=None)

Affiche des informations détaillées sur le code de la fonction fournie, la méthode, la chaîne de caractère du code source ou du code objet à file (ou bien sys.stdout si file n’est pas spécifié).

Ceci est un raccourci convenable de print(code_info(x), file=file), principalement fait pour l’exploration interactive sur l’invite de l’interpréteur.

Nouveau dans la version 3.2.

Modifié dans la version 3.4: Ajout du paramètre file.

dis.dis(x=None, *, file=None)

Disassemble the x object. x can denote either a module, a class, a method, a function, a generator, a code object, a string of source code or a byte sequence of raw bytecode. For a module, it disassembles all functions. For a class, it disassembles all methods (including class and static methods). For a code object or sequence of raw bytecode, it prints one line per bytecode instruction. Strings are first compiled to code objects with the compile() built-in function before being disassembled. If no object is provided, this function disassembles the last traceback.

Le désassemblage est envoyé sous forme de texte à l’argument du fichier file si il est fourni, et à sys.stdout sinon.

Modifié dans la version 3.4: Ajout du paramètre file.

dis.distb(tb=None, *, file=None)

Désassemble la fonction du haut de la pile des traces d’appels, en utilisant la dernière trace d’appels si rien n’a été envoyé. L’instruction à l’origine de l’exception est indiquée.

Le désassemblage est envoyé sous forme de texte à l’argument du fichier file si il est fourni, et à sys.stdout sinon.

Modifié dans la version 3.4: Ajout du paramètre file.

dis.disassemble(code, lasti=-1, *, file=None)

dis.disco(code, lasti=-1, *, file=None)

Désassemble un code objet, en indiquant la dernière instruction si lasti est fournie. La sortie est répartie sur les colonnes suivantes :

le numéro de ligne, pour la première instruction de chaque ligne

l’instruction en cours, indiquée par -->,

une instruction libellée, indiquée par > >,

l’adresse de l’instruction,

le nom de le code d’opération,

paramètres de l’opération, et

interprétation des paramètres entre parenthèses.

L’interprétation du paramètre reconnaît les noms des variables locales et globales, des valeurs constantes, des branchements cibles, et des opérateurs de comparaison.

Le désassemblage est envoyé sous forme de texte à l’argument du fichier file si il est fourni, et à sys.stdout sinon.

Modifié dans la version 3.4: Ajout du paramètre file.

dis.get_instructions(x, *, first_line=None)

Retourne un itérateur sur les instructions dans la fonction fournie, la méthode, les chaînes de caractères du code source ou objet.

Cet itérateur génère une série de n-uplets de Instruction qui donnent les détails de chacune des opérations dans le code fourni.

Si first_line ne vaut pas None, elle indique le nombre de la ligne qui doit être considérée comme première ligne source dans le code désassemblé. Autrement, les informations sur la ligne source sont prises directement à partir de la classe du code désassemblé.

Nouveau dans la version 3.4.

dis.findlinestarts(code)

This generator function uses the co_firstlineno and co_lnotab attributes of the code object code to find the offsets which are starts of lines in the source code. They are generated as (offset, lineno) pairs. See Objects/lnotab_notes.txt [https://github.com/python/cpython/tree/3.6/Objects/lnotab_notes.txt] for the co_lnotab format and how to decode it.

Modifié dans la version 3.6: Les numéros de lignes peuvent être décroissants. Avant, ils étaient toujours croissants.

dis.findlabels(code)

Detect all offsets in the code object code which are jump targets, and return a list of these offsets.

dis.stack_effect(opcode[, oparg])

Compute the stack effect of opcode with argument oparg.

Nouveau dans la version 3.4.

32.12.3. Les instructions du code intermédiaire en Python

La fonction get_instructions() et la méthode Bytecode fournit des détails sur le code intermédiaire des instructions comme Instruction instances:

class dis.Instruction

Détails sur le code intermédiaire de l’opération

opcode

code numérique pour l’opération, correspondant aux valeurs de l”opcode ci-dessous et les valeurs du code intermédiaire dans la Opcode collections.

opname

nom lisible/compréhensible de l’opération

arg

le cas échéant, argument numérique de l’opération sinon None

argval

resolved arg value (if known), otherwise same as arg

argrepr

human readable description of operation argument

offset

start index of operation within bytecode sequence

starts_line

line started by this opcode (if any), otherwise None

is_jump_target

True if other code jumps to here, otherwise False

Nouveau dans la version 3.4.

The Python compiler currently generates the following bytecode instructions.

General instructions

NOP

Do nothing code. Used as a placeholder by the bytecode optimizer.

POP_TOP

Removes the top-of-stack (TOS) item.

ROT_TWO

Swaps the two top-most stack items.

ROT_THREE

Lifts second and third stack item one position up, moves top down to position three.

DUP_TOP

Duplicates the reference on top of the stack.

Nouveau dans la version 3.2.

DUP_TOP_TWO

Duplicates the two references on top of the stack, leaving them in the same order.

Nouveau dans la version 3.2.

Unary operations

Unary operations take the top of the stack, apply the operation, and push the result back on the stack.

UNARY_POSITIVE

Implements TOS = +TOS.

UNARY_NEGATIVE

Implements TOS = -TOS.

UNARY_NOT

Implements TOS = not TOS.

UNARY_INVERT

Implements TOS = ~TOS.

GET_ITER

Implements TOS = iter(TOS).

GET_YIELD_FROM_ITER

If TOS is a generator iterator or coroutine object it is left as is. Otherwise, implements TOS = iter(TOS).

Nouveau dans la version 3.5.

Binary operations

Binary operations remove the top of the stack (TOS) and the second top-most stack item (TOS1) from the stack. They perform the operation, and put the result back on the stack.

BINARY_POWER

Implements TOS = TOS1 ** TOS.

BINARY_MULTIPLY

Implements TOS = TOS1 * TOS.

BINARY_MATRIX_MULTIPLY

Implements TOS = TOS1 @ TOS.

Nouveau dans la version 3.5.

BINARY_FLOOR_DIVIDE

Implements TOS = TOS1 // TOS.

BINARY_TRUE_DIVIDE

Implements TOS = TOS1 / TOS.

BINARY_MODULO

Implements TOS = TOS1 % TOS.

BINARY_ADD

Implements TOS = TOS1 + TOS.

BINARY_SUBTRACT

Implements TOS = TOS1 - TOS.

BINARY_SUBSCR

Implements TOS = TOS1[TOS].

BINARY_LSHIFT

Implements TOS = TOS1 << TOS.

BINARY_RSHIFT

Implements TOS = TOS1 >> TOS.

BINARY_AND

Implements TOS = TOS1 & TOS.

BINARY_XOR

Implements TOS = TOS1 ^ TOS.

BINARY_OR

Implements TOS = TOS1 | TOS.

In-place operations

In-place operations are like binary operations, in that they remove TOS and TOS1, and push the result back on the stack, but the operation is done in-place when TOS1 supports it, and the resulting TOS may be (but does not have to be) the original TOS1.

INPLACE_POWER

Implements in-place TOS = TOS1 ** TOS.

INPLACE_MULTIPLY

Implements in-place TOS = TOS1 * TOS.

INPLACE_MATRIX_MULTIPLY

Implements in-place TOS = TOS1 @ TOS.

Nouveau dans la version 3.5.

INPLACE_FLOOR_DIVIDE

Implements in-place TOS = TOS1 // TOS.

INPLACE_TRUE_DIVIDE

Implements in-place TOS = TOS1 / TOS.

INPLACE_MODULO

Implements in-place TOS = TOS1 % TOS.

INPLACE_ADD

Implements in-place TOS = TOS1 + TOS.

INPLACE_SUBTRACT

Implements in-place TOS = TOS1 - TOS.

INPLACE_LSHIFT

Implements in-place TOS = TOS1 << TOS.

INPLACE_RSHIFT

Implements in-place TOS = TOS1 >> TOS.

INPLACE_AND

Implements in-place TOS = TOS1 & TOS.

INPLACE_XOR

Implements in-place TOS = TOS1 ^ TOS.

INPLACE_OR

Implements in-place TOS = TOS1 | TOS.

STORE_SUBSCR

Implements TOS1[TOS] = TOS2.

DELETE_SUBSCR

Implements del TOS1[TOS].

Coroutine opcodes

GET_AWAITABLE

Implements TOS = get_awaitable(TOS), where get_awaitable(o) returns o if o is a coroutine object or a generator object with the CO_ITERABLE_COROUTINE flag, or resolves o.__await__.

Nouveau dans la version 3.5.

GET_AITER

Implements TOS = get_awaitable(TOS.__aiter__()). See GET_AWAITABLE for details about get_awaitable

Nouveau dans la version 3.5.

GET_ANEXT

Implements PUSH(get_awaitable(TOS.__anext__())). See GET_AWAITABLE for details about get_awaitable

Nouveau dans la version 3.5.

BEFORE_ASYNC_WITH

Resolves __aenter__ and __aexit__ from the object on top of the stack. Pushes __aexit__ and result of __aenter__() to the stack.

Nouveau dans la version 3.5.

SETUP_ASYNC_WITH

Creates a new frame object.

Nouveau dans la version 3.5.

Miscellaneous opcodes

PRINT_EXPR

Implements the expression statement for the interactive mode. TOS is removed from the stack and printed. In non-interactive mode, an expression statement is terminated with POP_TOP.

BREAK_LOOP

Terminates a loop due to a break statement.

CONTINUE_LOOP(target)

Continues a loop due to a continue statement. target is the address to jump to (which should be a FOR_ITER instruction).

SET_ADD(i)

Calls set.add(TOS1[-i], TOS). Used to implement set comprehensions.

LIST_APPEND(i)

Calls list.append(TOS[-i], TOS). Used to implement list comprehensions.

MAP_ADD(i)

Calls dict.setitem(TOS1[-i], TOS, TOS1). Used to implement dict comprehensions.

Nouveau dans la version 3.1.

For all of the SET_ADD, LIST_APPEND and MAP_ADD instructions, while the added value or key/value pair is popped off, the container object remains on the stack so that it is available for further iterations of the loop.

RETURN_VALUE

Returns with TOS to the caller of the function.

YIELD_VALUE

Pops TOS and yields it from a generator.

YIELD_FROM

Pops TOS and delegates to it as a subiterator from a generator.

Nouveau dans la version 3.3.

SETUP_ANNOTATIONS

Checks whether __annotations__ is defined in locals(), if not it is set up to an empty dict. This opcode is only emitted if a class or module body contains variable annotations statically.

Nouveau dans la version 3.6.

IMPORT_STAR

Loads all symbols not starting with '_' directly from the module TOS to the local namespace. The module is popped after loading all names. This opcode implements from module import *.

POP_BLOCK

Removes one block from the block stack. Per frame, there is a stack of blocks, denoting nested loops, try statements, and such.

POP_EXCEPT

Removes one block from the block stack. The popped block must be an exception handler block, as implicitly created when entering an except handler. In addition to popping extraneous values from the frame stack, the last three popped values are used to restore the exception state.

END_FINALLY

Terminates a finally clause. The interpreter recalls whether the exception has to be re-raised, or whether the function returns, and continues with the outer-next block.

LOAD_BUILD_CLASS

Pushes builtins.__build_class__() onto the stack. It is later called by CALL_FUNCTION to construct a class.

SETUP_WITH(delta)

This opcode performs several operations before a with block starts. First, it loads __exit__() from the context manager and pushes it onto the stack for later use by WITH_CLEANUP. Then, __enter__() is called, and a finally block pointing to delta is pushed. Finally, the result of calling the enter method is pushed onto the stack. The next opcode will either ignore it (POP_TOP), or store it in (a) variable(s) (STORE_FAST, STORE_NAME, or UNPACK_SEQUENCE).

Nouveau dans la version 3.2.

WITH_CLEANUP_START

Cleans up the stack when a with statement block exits. TOS is the context manager’s __exit__() bound method. Below TOS are 1–3 values indicating how/why the finally clause was entered:

SECOND = None

(SECOND, THIRD) = (WHY_{RETURN,CONTINUE}), retval

SECOND = WHY_*; no retval below it

(SECOND, THIRD, FOURTH) = exc_info()

In the last case, TOS(SECOND, THIRD, FOURTH) is called, otherwise TOS(None, None, None). Pushes SECOND and result of the call to the stack.

WITH_CLEANUP_FINISH

Pops exception type and result of “exit” function call from the stack.

If the stack represents an exception, and the function call returns a “true” value, this information is « zapped » and replaced with a single WHY_SILENCED to prevent END_FINALLY from re-raising the exception. (But non-local gotos will still be resumed.)

All of the following opcodes use their arguments.

STORE_NAME(namei)

Implements name = TOS. namei is the index of name in the attribute co_names of the code object. The compiler tries to use STORE_FAST or STORE_GLOBAL if possible.

DELETE_NAME(namei)

Implements del name, where namei is the index into co_names attribute of the code object.

UNPACK_SEQUENCE(count)

Unpacks TOS into count individual values, which are put onto the stack right-to-left.

UNPACK_EX(counts)

Implements assignment with a starred target: Unpacks an iterable in TOS into individual values, where the total number of values can be smaller than the number of items in the iterable: one of the new values will be a list of all leftover items.

The low byte of counts is the number of values before the list value, the high byte of counts the number of values after it. The resulting values are put onto the stack right-to-left.

STORE_ATTR(namei)

Implements TOS.name = TOS1, where namei is the index of name in co_names.

DELETE_ATTR(namei)

Implements del TOS.name, using namei as index into co_names.

STORE_GLOBAL(namei)

Works as STORE_NAME, but stores the name as a global.

DELETE_GLOBAL(namei)

Works as DELETE_NAME, but deletes a global name.

LOAD_CONST(consti)

Pushes co_consts[consti] onto the stack.

LOAD_NAME(namei)

Pushes the value associated with co_names[namei] onto the stack.

BUILD_TUPLE(count)

Creates a tuple consuming count items from the stack, and pushes the resulting tuple onto the stack.

BUILD_LIST(count)

Works as BUILD_TUPLE, but creates a list.

BUILD_SET(count)

Works as BUILD_TUPLE, but creates a set.

BUILD_MAP(count)

Pushes a new dictionary object onto the stack. Pops 2 * count items so that the dictionary holds count entries: {..., TOS3: TOS2, TOS1: TOS}.

Modifié dans la version 3.5: The dictionary is created from stack items instead of creating an empty dictionary pre-sized to hold count items.

BUILD_CONST_KEY_MAP(count)

The version of BUILD_MAP specialized for constant keys. count values are consumed from the stack. The top element on the stack contains a tuple of keys.

Nouveau dans la version 3.6.

BUILD_STRING(count)

Concatenates count strings from the stack and pushes the resulting string onto the stack.

Nouveau dans la version 3.6.

BUILD_TUPLE_UNPACK(count)

Pops count iterables from the stack, joins them in a single tuple, and pushes the result. Implements iterable unpacking in tuple displays (*x, *y, *z).

Nouveau dans la version 3.5.

BUILD_TUPLE_UNPACK_WITH_CALL(count)

This is similar to BUILD_TUPLE_UNPACK, but is used for f(*x, *y, *z) call syntax. The stack item at position count + 1 should be the corresponding callable f.

Nouveau dans la version 3.6.

BUILD_LIST_UNPACK(count)

This is similar to BUILD_TUPLE_UNPACK, but pushes a list instead of tuple. Implements iterable unpacking in list displays [*x, *y, *z].

Nouveau dans la version 3.5.

BUILD_SET_UNPACK(count)

This is similar to BUILD_TUPLE_UNPACK, but pushes a set instead of tuple. Implements iterable unpacking in set displays {*x, *y, *z}.

Nouveau dans la version 3.5.

BUILD_MAP_UNPACK(count)

Pops count mappings from the stack, merges them into a single dictionary, and pushes the result. Implements dictionary unpacking in dictionary displays {**x, **y, **z}.

Nouveau dans la version 3.5.

BUILD_MAP_UNPACK_WITH_CALL(count)

This is similar to BUILD_MAP_UNPACK, but is used for f(**x, **y, **z) call syntax. The stack item at position count + 2 should be the corresponding callable f.

Nouveau dans la version 3.5.

Modifié dans la version 3.6: The position of the callable is determined by adding 2 to the opcode argument instead of encoding it in the second byte of the argument.

LOAD_ATTR(namei)

Replaces TOS with getattr(TOS, co_names[namei]).

COMPARE_OP(opname)

Performs a Boolean operation. The operation name can be found in cmp_op[opname].

IMPORT_NAME(namei)

Imports the module co_names[namei]. TOS and TOS1 are popped and provide the fromlist and level arguments of __import__(). The module object is pushed onto the stack. The current namespace is not affected: for a proper import statement, a subsequent STORE_FAST instruction modifies the namespace.

IMPORT_FROM(namei)

Loads the attribute co_names[namei] from the module found in TOS. The resulting object is pushed onto the stack, to be subsequently stored by a STORE_FAST instruction.

JUMP_FORWARD(delta)

Increments bytecode counter by delta.

POP_JUMP_IF_TRUE(target)

If TOS is true, sets the bytecode counter to target. TOS is popped.

Nouveau dans la version 3.1.

POP_JUMP_IF_FALSE(target)

If TOS is false, sets the bytecode counter to target. TOS is popped.

Nouveau dans la version 3.1.

JUMP_IF_TRUE_OR_POP(target)

If TOS is true, sets the bytecode counter to target and leaves TOS on the stack. Otherwise (TOS is false), TOS is popped.

Nouveau dans la version 3.1.

JUMP_IF_FALSE_OR_POP(target)

If TOS is false, sets the bytecode counter to target and leaves TOS on the stack. Otherwise (TOS is true), TOS is popped.

Nouveau dans la version 3.1.

JUMP_ABSOLUTE(target)

Set bytecode counter to target.

FOR_ITER(delta)

TOS is an iterator. Call its __next__() method. If this yields a new value, push it on the stack (leaving the iterator below it). If the iterator indicates it is exhausted TOS is popped, and the byte code counter is incremented by delta.

LOAD_GLOBAL(namei)

Loads the global named co_names[namei] onto the stack.

SETUP_LOOP(delta)

Pushes a block for a loop onto the block stack. The block spans from the current instruction with a size of delta bytes.

SETUP_EXCEPT(delta)

Pushes a try block from a try-except clause onto the block stack. delta points to the first except block.

SETUP_FINALLY(delta)

Pushes a try block from a try-except clause onto the block stack. delta points to the finally block.

LOAD_FAST(var_num)

Pushes a reference to the local co_varnames[var_num] onto the stack.

STORE_FAST(var_num)

Stores TOS into the local co_varnames[var_num].

DELETE_FAST(var_num)

Deletes local co_varnames[var_num].

STORE_ANNOTATION(namei)

Stores TOS as locals()['__annotations__'][co_names[namei]] = TOS.

Nouveau dans la version 3.6.

LOAD_CLOSURE(i)

Pushes a reference to the cell contained in slot i of the cell and free variable storage. The name of the variable is co_cellvars[i] if i is less than the length of co_cellvars. Otherwise it is co_freevars[i - len(co_cellvars)].

LOAD_DEREF(i)

Loads the cell contained in slot i of the cell and free variable storage. Pushes a reference to the object the cell contains on the stack.

LOAD_CLASSDEREF(i)

Much like LOAD_DEREF but first checks the locals dictionary before consulting the cell. This is used for loading free variables in class bodies.

Nouveau dans la version 3.4.

STORE_DEREF(i)

Stores TOS into the cell contained in slot i of the cell and free variable storage.

DELETE_DEREF(i)

Empties the cell contained in slot i of the cell and free variable storage. Used by the del statement.

Nouveau dans la version 3.2.

RAISE_VARARGS(argc)

Raises an exception. argc indicates the number of arguments to the raise statement, ranging from 0 to 3. The handler will find the traceback as TOS2, the parameter as TOS1, and the exception as TOS.

CALL_FUNCTION(argc)

Calls a callable object with positional arguments. argc indicates the number of positional arguments. The top of the stack contains positional arguments, with the right-most argument on top. Below the arguments is a callable object to call. CALL_FUNCTION pops all arguments and the callable object off the stack, calls the callable object with those arguments, and pushes the return value returned by the callable object.

Modifié dans la version 3.6: This opcode is used only for calls with positional arguments.

CALL_FUNCTION_KW(argc)

Calls a callable object with positional (if any) and keyword arguments. argc indicates the total number of positional and keyword arguments. The top element on the stack contains a tuple of keyword argument names. Below that are keyword arguments in the order corresponding to the tuple. Below that are positional arguments, with the right-most parameter on top. Below the arguments is a callable object to call. CALL_FUNCTION_KW pops all arguments and the callable object off the stack, calls the callable object with those arguments, and pushes the return value returned by the callable object.

Modifié dans la version 3.6: Keyword arguments are packed in a tuple instead of a dictionary, argc indicates the total number of arguments.

CALL_FUNCTION_EX(flags)

Calls a callable object with variable set of positional and keyword arguments. If the lowest bit of flags is set, the top of the stack contains a mapping object containing additional keyword arguments. Below that is an iterable object containing positional arguments and a callable object to call. BUILD_MAP_UNPACK_WITH_CALL and BUILD_TUPLE_UNPACK_WITH_CALL can be used for merging multiple mapping objects and iterables containing arguments. Before the callable is called, the mapping object and iterable object are each « unpacked » and their contents passed in as keyword and positional arguments respectively. CALL_FUNCTION_EX pops all arguments and the callable object off the stack, calls the callable object with those arguments, and pushes the return value returned by the callable object.

Nouveau dans la version 3.6.

MAKE_FUNCTION(argc)

Pushes a new function object on the stack. From bottom to top, the consumed stack must consist of values if the argument carries a specified flag value

0x01 a tuple of default values for positional-only and positional-or-keyword parameters in positional order

0x02 a dictionary of keyword-only parameters” default values

0x04 an annotation dictionary

0x08 a tuple containing cells for free variables, making a closure

the code associated with the function (at TOS1)

the qualified name of the function (at TOS)

BUILD_SLICE(argc)

Pushes a slice object on the stack. argc must be 2 or 3. If it is 2, slice(TOS1, TOS) is pushed; if it is 3, slice(TOS2, TOS1, TOS) is pushed. See the slice() built-in function for more information.

EXTENDED_ARG(ext)

Prefixes any opcode which has an argument too big to fit into the default two bytes. ext holds two additional bytes which, taken together with the subsequent opcode’s argument, comprise a four-byte argument, ext being the two most-significant bytes.

FORMAT_VALUE(flags)

Used for implementing formatted literal strings (f-strings). Pops an optional fmt_spec from the stack, then a required value. flags is interpreted as follows:

(flags & 0x03) == 0x00: value is formatted as-is.

(flags & 0x03) == 0x01: call str() on value before formatting it.

(flags & 0x03) == 0x02: call repr() on value before formatting it.

(flags & 0x03) == 0x03: call ascii() on value before formatting it.

(flags & 0x04) == 0x04: pop fmt_spec from the stack and use it, else use an empty fmt_spec.

Formatting is performed using PyObject_Format(). The result is pushed on the stack.

Nouveau dans la version 3.6.

HAVE_ARGUMENT

This is not really an opcode. It identifies the dividing line between opcodes which don’t use their argument and those that do (< HAVE_ARGUMENT and >= HAVE_ARGUMENT, respectively).

Modifié dans la version 3.6: Now every instruction has an argument, but opcodes < HAVE_ARGUMENT ignore it. Before, only opcodes >= HAVE_ARGUMENT had an argument.

32.12.4. Opcode collections

These collections are provided for automatic introspection of bytecode instructions:

dis.opname

Sequence of operation names, indexable using the bytecode.

dis.opmap

Dictionary mapping operation names to bytecodes.

dis.cmp_op

Sequence of all compare operation names.

dis.hasconst

Sequence of bytecodes that access a constant.

dis.hasfree

Sequence of bytecodes that access a free variable (note that “free” in this context refers to names in the current scope that are referenced by inner scopes or names in outer scopes that are referenced from this scope. It does not include references to global or builtin scopes).

dis.hasname

Sequence of bytecodes that access an attribute by name.

dis.hasjrel

Sequence of bytecodes that have a relative jump target.

dis.hasjabs

Sequence of bytecodes that have an absolute jump target.

dis.haslocal

Sequence of bytecodes that access a local variable.

dis.hascompare

Sequence of bytecodes of Boolean operations.

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32.13. pickletools — Tools for pickle developers

Source code: Lib/pickletools.py [https://github.com/python/cpython/tree/3.6/Lib/pickletools.py]

This module contains various constants relating to the intimate details of the pickle module, some lengthy comments about the implementation, and a few useful functions for analyzing pickled data. The contents of this module are useful for Python core developers who are working on the pickle; ordinary users of the pickle module probably won’t find the pickletools module relevant.

32.13.1. Utilisation de la ligne de commande

Nouveau dans la version 3.2.

When invoked from the command line, python -m pickletools will disassemble the contents of one or more pickle files. Note that if you want to see the Python object stored in the pickle rather than the details of pickle format, you may want to use -m pickle instead. However, when the pickle file that you want to examine comes from an untrusted source, -m pickletools is a safer option because it does not execute pickle bytecode.

For example, with a tuple (1, 2) pickled in file x.pickle:

$ python -m pickle x.pickle
(1, 2)

$ python -m pickletools x.pickle
    0: \x80 PROTO      3
    2: K    BININT1    1
    4: K    BININT1    2
    6: \x86 TUPLE2
    7: q    BINPUT     0
    9: .    STOP
highest protocol among opcodes = 2

32.13.1.1. Options de la ligne de commande

-a, --annotate

Annotate each line with a short opcode description.

-o, --output=<file>

Name of a file where the output should be written.

-l, --indentlevel=<num>

The number of blanks by which to indent a new MARK level.

-m, --memo

When multiple objects are disassembled, preserve memo between disassemblies.

-p, --preamble=<preamble>

When more than one pickle file are specified, print given preamble before each disassembly.

32.13.2. Programmatic Interface

pickletools.dis(pickle, out=None, memo=None, indentlevel=4, annotate=0)

Outputs a symbolic disassembly of the pickle to the file-like object out, defaulting to sys.stdout. pickle can be a string or a file-like object. memo can be a Python dictionary that will be used as the pickle’s memo; it can be used to perform disassemblies across multiple pickles created by the same pickler. Successive levels, indicated by MARK opcodes in the stream, are indented by indentlevel spaces. If a nonzero value is given to annotate, each opcode in the output is annotated with a short description. The value of annotate is used as a hint for the column where annotation should start.

Nouveau dans la version 3.2: The annotate argument.

pickletools.genops(pickle)

Provides an iterator over all of the opcodes in a pickle, returning a sequence of (opcode, arg, pos) triples. opcode is an instance of an OpcodeInfo class; arg is the decoded value, as a Python object, of the opcode’s argument; pos is the position at which this opcode is located. pickle can be a string or a file-like object.

pickletools.optimize(picklestring)

Returns a new equivalent pickle string after eliminating unused PUT opcodes. The optimized pickle is shorter, takes less transmission time, requires less storage space, and unpickles more efficiently.

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33. Services divers

Les modules documentés dans ce chapitre fournissent différents services disponibles dans toutes les version de Python. En voici un aperçu :

33.1. formatter — Generic output formatting

33.1.1. The Formatter Interface

33.1.2. Formatter Implementations

33.1.3. The Writer Interface

33.1.4. Writer Implementations

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33.1. formatter — Generic output formatting

Obsolète depuis la version 3.4: Due to lack of usage, the formatter module has been deprecated.

This module supports two interface definitions, each with multiple implementations: The formatter interface, and the writer interface which is required by the formatter interface.

Formatter objects transform an abstract flow of formatting events into specific output events on writer objects. Formatters manage several stack structures to allow various properties of a writer object to be changed and restored; writers need not be able to handle relative changes nor any sort of « change back » operation. Specific writer properties which may be controlled via formatter objects are horizontal alignment, font, and left margin indentations. A mechanism is provided which supports providing arbitrary, non-exclusive style settings to a writer as well. Additional interfaces facilitate formatting events which are not reversible, such as paragraph separation.

Writer objects encapsulate device interfaces. Abstract devices, such as file formats, are supported as well as physical devices. The provided implementations all work with abstract devices. The interface makes available mechanisms for setting the properties which formatter objects manage and inserting data into the output.

33.1.1. The Formatter Interface

Interfaces to create formatters are dependent on the specific formatter class being instantiated. The interfaces described below are the required interfaces which all formatters must support once initialized.

One data element is defined at the module level:

formatter.AS_IS

Value which can be used in the font specification passed to the push_font() method described below, or as the new value to any other push_property() method. Pushing the AS_IS value allows the corresponding pop_property() method to be called without having to track whether the property was changed.

The following attributes are defined for formatter instance objects:

formatter.writer

The writer instance with which the formatter interacts.

formatter.end_paragraph(blanklines)

Close any open paragraphs and insert at least blanklines before the next paragraph.

formatter.add_line_break()

Add a hard line break if one does not already exist. This does not break the logical paragraph.

formatter.add_hor_rule(*args, **kw)

Insert a horizontal rule in the output. A hard break is inserted if there is data in the current paragraph, but the logical paragraph is not broken. The arguments and keywords are passed on to the writer’s send_line_break() method.

formatter.add_flowing_data(data)

Provide data which should be formatted with collapsed whitespace. Whitespace from preceding and successive calls to add_flowing_data() is considered as well when the whitespace collapse is performed. The data which is passed to this method is expected to be word-wrapped by the output device. Note that any word-wrapping still must be performed by the writer object due to the need to rely on device and font information.

formatter.add_literal_data(data)

Provide data which should be passed to the writer unchanged. Whitespace, including newline and tab characters, are considered legal in the value of data.

formatter.add_label_data(format, counter)

Insert a label which should be placed to the left of the current left margin. This should be used for constructing bulleted or numbered lists. If the format value is a string, it is interpreted as a format specification for counter, which should be an integer. The result of this formatting becomes the value of the label; if format is not a string it is used as the label value directly. The label value is passed as the only argument to the writer’s send_label_data() method. Interpretation of non-string label values is dependent on the associated writer.

Format specifications are strings which, in combination with a counter value, are used to compute label values. Each character in the format string is copied to the label value, with some characters recognized to indicate a transform on the counter value. Specifically, the character '1' represents the counter value formatter as an Arabic number, the characters 'A' and 'a' represent alphabetic representations of the counter value in upper and lower case, respectively, and 'I' and 'i' represent the counter value in Roman numerals, in upper and lower case. Note that the alphabetic and roman transforms require that the counter value be greater than zero.

formatter.flush_softspace()

Send any pending whitespace buffered from a previous call to add_flowing_data() to the associated writer object. This should be called before any direct manipulation of the writer object.

formatter.push_alignment(align)

Push a new alignment setting onto the alignment stack. This may be AS_IS if no change is desired. If the alignment value is changed from the previous setting, the writer’s new_alignment() method is called with the align value.

formatter.pop_alignment()

Restore the previous alignment.

formatter.push_font((size, italic, bold, teletype))

Change some or all font properties of the writer object. Properties which are not set to AS_IS are set to the values passed in while others are maintained at their current settings. The writer’s new_font() method is called with the fully resolved font specification.

formatter.pop_font()

Restore the previous font.

formatter.push_margin(margin)

Increase the number of left margin indentations by one, associating the logical tag margin with the new indentation. The initial margin level is 0. Changed values of the logical tag must be true values; false values other than AS_IS are not sufficient to change the margin.

formatter.pop_margin()

Restore the previous margin.

formatter.push_style(*styles)

Push any number of arbitrary style specifications. All styles are pushed onto the styles stack in order. A tuple representing the entire stack, including AS_IS values, is passed to the writer’s new_styles() method.

formatter.pop_style(n=1)

Pop the last n style specifications passed to push_style(). A tuple representing the revised stack, including AS_IS values, is passed to the writer’s new_styles() method.

formatter.set_spacing(spacing)

Set the spacing style for the writer.

formatter.assert_line_data(flag=1)

Inform the formatter that data has been added to the current paragraph out-of-band. This should be used when the writer has been manipulated directly. The optional flag argument can be set to false if the writer manipulations produced a hard line break at the end of the output.

33.1.2. Formatter Implementations

Two implementations of formatter objects are provided by this module. Most applications may use one of these classes without modification or subclassing.

class formatter.NullFormatter(writer=None)

A formatter which does nothing. If writer is omitted, a NullWriter instance is created. No methods of the writer are called by NullFormatter instances. Implementations should inherit from this class if implementing a writer interface but don’t need to inherit any implementation.

class formatter.AbstractFormatter(writer)

The standard formatter. This implementation has demonstrated wide applicability to many writers, and may be used directly in most circumstances. It has been used to implement a full-featured World Wide Web browser.

33.1.3. The Writer Interface

Interfaces to create writers are dependent on the specific writer class being instantiated. The interfaces described below are the required interfaces which all writers must support once initialized. Note that while most applications can use the AbstractFormatter class as a formatter, the writer must typically be provided by the application.

writer.flush()

Flush any buffered output or device control events.

writer.new_alignment(align)

Set the alignment style. The align value can be any object, but by convention is a string or None, where None indicates that the writer’s « preferred » alignment should be used. Conventional align values are 'left', 'center', 'right', and 'justify'.

writer.new_font(font)

Set the font style. The value of font will be None, indicating that the device’s default font should be used, or a tuple of the form (size, italic, bold, teletype). Size will be a string indicating the size of font that should be used; specific strings and their interpretation must be defined by the application. The italic, bold, and teletype values are Boolean values specifying which of those font attributes should be used.

writer.new_margin(margin, level)

Set the margin level to the integer level and the logical tag to margin. Interpretation of the logical tag is at the writer’s discretion; the only restriction on the value of the logical tag is that it not be a false value for non-zero values of level.

writer.new_spacing(spacing)

Set the spacing style to spacing.

writer.new_styles(styles)

Set additional styles. The styles value is a tuple of arbitrary values; the value AS_IS should be ignored. The styles tuple may be interpreted either as a set or as a stack depending on the requirements of the application and writer implementation.

writer.send_line_break()

Break the current line.

writer.send_paragraph(blankline)

Produce a paragraph separation of at least blankline blank lines, or the equivalent. The blankline value will be an integer. Note that the implementation will receive a call to send_line_break() before this call if a line break is needed; this method should not include ending the last line of the paragraph. It is only responsible for vertical spacing between paragraphs.

writer.send_hor_rule(*args, **kw)

Display a horizontal rule on the output device. The arguments to this method are entirely application- and writer-specific, and should be interpreted with care. The method implementation may assume that a line break has already been issued via send_line_break().

writer.send_flowing_data(data)

Output character data which may be word-wrapped and re-flowed as needed. Within any sequence of calls to this method, the writer may assume that spans of multiple whitespace characters have been collapsed to single space characters.

writer.send_literal_data(data)

Output character data which has already been formatted for display. Generally, this should be interpreted to mean that line breaks indicated by newline characters should be preserved and no new line breaks should be introduced. The data may contain embedded newline and tab characters, unlike data provided to the send_formatted_data() interface.

writer.send_label_data(data)

Set data to the left of the current left margin, if possible. The value of data is not restricted; treatment of non-string values is entirely application- and writer-dependent. This method will only be called at the beginning of a line.

33.1.4. Writer Implementations

Three implementations of the writer object interface are provided as examples by this module. Most applications will need to derive new writer classes from the NullWriter class.

class formatter.NullWriter

A writer which only provides the interface definition; no actions are taken on any methods. This should be the base class for all writers which do not need to inherit any implementation methods.

class formatter.AbstractWriter

A writer which can be used in debugging formatters, but not much else. Each method simply announces itself by printing its name and arguments on standard output.

class formatter.DumbWriter(file=None, maxcol=72)

Simple writer class which writes output on the file object passed in as file or, if file is omitted, on standard output. The output is simply word-wrapped to the number of columns specified by maxcol. This class is suitable for reflowing a sequence of paragraphs.

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34. Services spécifiques à MS Windows

Ce chapitre documente les modules qui ne sont disponibles que sous MS Windows.

34.1. msilib — Read and write Microsoft Installer files

34.1.1. Database Objects

34.1.2. View Objects

34.1.3. Summary Information Objects

34.1.4. Record Objects

34.1.5. Errors

34.1.6. CAB Objects

34.1.7. Directory Objects

34.1.8. Features

34.1.9. GUI classes

34.1.10. Precomputed tables

34.2. msvcrt — Useful routines from the MS VC++ runtime

34.2.1. File Operations

34.2.2. Console I/O

34.2.3. Other Functions

34.3. winreg — Windows registry access

34.3.1. Fonctions

34.3.2. Constantes

34.3.2.1. HKEY_* Constants

34.3.2.2. Access Rights

34.3.2.2.1. 64-bit Specific

34.3.2.3. Value Types

34.3.3. Registry Handle Objects

34.4. winsound — Sound-playing interface for Windows

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34.1. msilib — Read and write Microsoft Installer files

Source code: Lib/msilib/__init__.py [https://github.com/python/cpython/tree/3.6/Lib/msilib/__init__.py]

The msilib supports the creation of Microsoft Installer (.msi) files. Because these files often contain an embedded « cabinet » file (.cab), it also exposes an API to create CAB files. Support for reading .cab files is currently not implemented; read support for the .msi database is possible.

This package aims to provide complete access to all tables in an .msi file, therefore, it is a fairly low-level API. Two primary applications of this package are the distutils command bdist_msi, and the creation of Python installer package itself (although that currently uses a different version of msilib).

The package contents can be roughly split into four parts: low-level CAB routines, low-level MSI routines, higher-level MSI routines, and standard table structures.

msilib.FCICreate(cabname, files)

Create a new CAB file named cabname. files must be a list of tuples, each containing the name of the file on disk, and the name of the file inside the CAB file.

The files are added to the CAB file in the order they appear in the list. All files are added into a single CAB file, using the MSZIP compression algorithm.

Callbacks to Python for the various steps of MSI creation are currently not exposed.

msilib.UuidCreate()

Return the string representation of a new unique identifier. This wraps the Windows API functions UuidCreate() and UuidToString().

msilib.OpenDatabase(path, persist)

Return a new database object by calling MsiOpenDatabase. path is the file name of the MSI file; persist can be one of the constants MSIDBOPEN_CREATEDIRECT, MSIDBOPEN_CREATE, MSIDBOPEN_DIRECT, MSIDBOPEN_READONLY, or MSIDBOPEN_TRANSACT, and may include the flag MSIDBOPEN_PATCHFILE. See the Microsoft documentation for the meaning of these flags; depending on the flags, an existing database is opened, or a new one created.

msilib.CreateRecord(count)

Return a new record object by calling MSICreateRecord(). count is the number of fields of the record.

msilib.init_database(name, schema, ProductName, ProductCode, ProductVersion, Manufacturer)

Create and return a new database name, initialize it with schema, and set the properties ProductName, ProductCode, ProductVersion, and Manufacturer.

schema must be a module object containing tables and _Validation_records attributes; typically, msilib.schema should be used.

The database will contain just the schema and the validation records when this function returns.

msilib.add_data(database, table, records)

Add all records to the table named table in database.

The table argument must be one of the predefined tables in the MSI schema, e.g. 'Feature', 'File', 'Component', 'Dialog', 'Control', etc.

records should be a list of tuples, each one containing all fields of a record according to the schema of the table. For optional fields, None can be passed.

Field values can be ints, strings, or instances of the Binary class.

class msilib.Binary(filename)

Represents entries in the Binary table; inserting such an object using add_data() reads the file named filename into the table.

msilib.add_tables(database, module)

Add all table content from module to database. module must contain an attribute tables listing all tables for which content should be added, and one attribute per table that has the actual content.

This is typically used to install the sequence tables.

msilib.add_stream(database, name, path)

Add the file path into the _Stream table of database, with the stream name name.

msilib.gen_uuid()

Return a new UUID, in the format that MSI typically requires (i.e. in curly braces, and with all hexdigits in upper-case).

Voir aussi

FCICreate [https://msdn.microsoft.com/en-us/library/bb432265.aspx] UuidCreate [https://msdn.microsoft.com/en-us/library/windows/desktop/aa379205.aspx] UuidToString [https://msdn.microsoft.com/en-us/library/windows/desktop/aa379352.aspx]

34.1.1. Database Objects

Database.OpenView(sql)

Return a view object, by calling MSIDatabaseOpenView(). sql is the SQL statement to execute.

Database.Commit()

Commit the changes pending in the current transaction, by calling MSIDatabaseCommit().

Database.GetSummaryInformation(count)

Return a new summary information object, by calling MsiGetSummaryInformation(). count is the maximum number of updated values.

Voir aussi

MSIDatabaseOpenView [https://msdn.microsoft.com/en-us/library/windows/desktop/aa370082.aspx] MSIDatabaseCommit [https://msdn.microsoft.com/en-us/library/windows/desktop/aa370075.aspx] MSIGetSummaryInformation [https://msdn.microsoft.com/en-us/library/windows/desktop/aa370301.aspx]

34.1.2. View Objects

View.Execute(params)

Execute the SQL query of the view, through MSIViewExecute(). If params is not None, it is a record describing actual values of the parameter tokens in the query.

View.GetColumnInfo(kind)

Return a record describing the columns of the view, through calling MsiViewGetColumnInfo(). kind can be either MSICOLINFO_NAMES or MSICOLINFO_TYPES.

View.Fetch()

Return a result record of the query, through calling MsiViewFetch().

View.Modify(kind, data)

Modify the view, by calling MsiViewModify(). kind can be one of MSIMODIFY_SEEK, MSIMODIFY_REFRESH, MSIMODIFY_INSERT, MSIMODIFY_UPDATE, MSIMODIFY_ASSIGN, MSIMODIFY_REPLACE, MSIMODIFY_MERGE, MSIMODIFY_DELETE, MSIMODIFY_INSERT_TEMPORARY, MSIMODIFY_VALIDATE, MSIMODIFY_VALIDATE_NEW, MSIMODIFY_VALIDATE_FIELD, or MSIMODIFY_VALIDATE_DELETE.

data must be a record describing the new data.

View.Close()

Close the view, through MsiViewClose().

Voir aussi

MsiViewExecute [https://msdn.microsoft.com/en-us/library/windows/desktop/aa370513.aspx] MSIViewGetColumnInfo [https://msdn.microsoft.com/en-us/library/windows/desktop/aa370516.aspx] MsiViewFetch [https://msdn.microsoft.com/en-us/library/windows/desktop/aa370514.aspx] MsiViewModify [https://msdn.microsoft.com/en-us/library/windows/desktop/aa370519.aspx] MsiViewClose [https://msdn.microsoft.com/en-us/library/windows/desktop/aa370510.aspx]

34.1.3. Summary Information Objects

SummaryInformation.GetProperty(field)

Return a property of the summary, through MsiSummaryInfoGetProperty(). field is the name of the property, and can be one of the constants PID_CODEPAGE, PID_TITLE, PID_SUBJECT, PID_AUTHOR, PID_KEYWORDS, PID_COMMENTS, PID_TEMPLATE, PID_LASTAUTHOR, PID_REVNUMBER, PID_LASTPRINTED, PID_CREATE_DTM, PID_LASTSAVE_DTM, PID_PAGECOUNT, PID_WORDCOUNT, PID_CHARCOUNT, PID_APPNAME, or PID_SECURITY.

SummaryInformation.GetPropertyCount()

Return the number of summary properties, through MsiSummaryInfoGetPropertyCount().

SummaryInformation.SetProperty(field, value)

Set a property through MsiSummaryInfoSetProperty(). field can have the same values as in GetProperty(), value is the new value of the property. Possible value types are integer and string.

SummaryInformation.Persist()

Write the modified properties to the summary information stream, using MsiSummaryInfoPersist().

Voir aussi

MsiSummaryInfoGetProperty [https://msdn.microsoft.com/en-us/library/windows/desktop/aa370409.aspx] MsiSummaryInfoGetPropertyCount [https://msdn.microsoft.com/en-us/library/windows/desktop/aa370488.aspx] MsiSummaryInfoSetProperty [https://msdn.microsoft.com/en-us/library/windows/desktop/aa370491.aspx] MsiSummaryInfoPersist [https://msdn.microsoft.com/en-us/library/windows/desktop/aa370490.aspx]

34.1.4. Record Objects

Record.GetFieldCount()

Return the number of fields of the record, through MsiRecordGetFieldCount().

Record.GetInteger(field)

Return the value of field as an integer where possible. field must be an integer.

Record.GetString(field)

Return the value of field as a string where possible. field must be an integer.

Record.SetString(field, value)

Set field to value through MsiRecordSetString(). field must be an integer; value a string.

Record.SetStream(field, value)

Set field to the contents of the file named value, through MsiRecordSetStream(). field must be an integer; value a string.

Record.SetInteger(field, value)

Set field to value through MsiRecordSetInteger(). Both field and value must be an integer.

Record.ClearData()

Set all fields of the record to 0, through MsiRecordClearData().

Voir aussi

MsiRecordGetFieldCount [https://msdn.microsoft.com/en-us/library/windows/desktop/aa370366.aspx] MsiRecordSetString [https://msdn.microsoft.com/en-us/library/windows/desktop/aa370373.aspx] MsiRecordSetStream [https://msdn.microsoft.com/en-us/library/windows/desktop/aa370372.aspx] MsiRecordSetInteger [https://msdn.microsoft.com/en-us/library/windows/desktop/aa370371.aspx] MsiRecordClearData [https://msdn.microsoft.com/en-us/library/windows/desktop/aa370364.aspx]

34.1.5. Errors

All wrappers around MSI functions raise MSIError; the string inside the exception will contain more detail.

34.1.6. CAB Objects

class msilib.CAB(name)

The class CAB represents a CAB file. During MSI construction, files will be added simultaneously to the Files table, and to a CAB file. Then, when all files have been added, the CAB file can be written, then added to the MSI file.

name is the name of the CAB file in the MSI file.

append(full, file, logical)

Add the file with the pathname full to the CAB file, under the name logical. If there is already a file named logical, a new file name is created.

Return the index of the file in the CAB file, and the new name of the file inside the CAB file.

commit(database)

Generate a CAB file, add it as a stream to the MSI file, put it into the Media table, and remove the generated file from the disk.

34.1.7. Directory Objects

class msilib.Directory(database, cab, basedir, physical, logical, default[, componentflags])

Create a new directory in the Directory table. There is a current component at each point in time for the directory, which is either explicitly created through start_component(), or implicitly when files are added for the first time. Files are added into the current component, and into the cab file. To create a directory, a base directory object needs to be specified (can be None), the path to the physical directory, and a logical directory name. default specifies the DefaultDir slot in the directory table. componentflags specifies the default flags that new components get.

start_component(component=None, feature=None, flags=None, keyfile=None, uuid=None)

Add an entry to the Component table, and make this component the current component for this directory. If no component name is given, the directory name is used. If no feature is given, the current feature is used. If no flags are given, the directory’s default flags are used. If no keyfile is given, the KeyPath is left null in the Component table.

add_file(file, src=None, version=None, language=None)

Add a file to the current component of the directory, starting a new one if there is no current component. By default, the file name in the source and the file table will be identical. If the src file is specified, it is interpreted relative to the current directory. Optionally, a version and a language can be specified for the entry in the File table.

glob(pattern, exclude=None)

Add a list of files to the current component as specified in the glob pattern. Individual files can be excluded in the exclude list.

remove_pyc()

Remove .pyc files on uninstall.

Voir aussi

Directory Table [https://msdn.microsoft.com/en-us/library/windows/desktop/aa368295.aspx] File Table [https://msdn.microsoft.com/en-us/library/windows/desktop/aa368596.aspx] Component Table [https://msdn.microsoft.com/en-us/library/windows/desktop/aa368007.aspx] FeatureComponents Table [https://msdn.microsoft.com/en-us/library/windows/desktop/aa368579.aspx]

34.1.8. Features

class msilib.Feature(db, id, title, desc, display, level=1, parent=None, directory=None, attributes=0)

Add a new record to the Feature table, using the values id, parent.id, title, desc, display, level, directory, and attributes. The resulting feature object can be passed to the start_component() method of Directory.

set_current()

Make this feature the current feature of msilib. New components are automatically added to the default feature, unless a feature is explicitly specified.

Voir aussi

Feature Table [https://msdn.microsoft.com/en-us/library/windows/desktop/aa368585.aspx]

34.1.9. GUI classes

msilib provides several classes that wrap the GUI tables in an MSI database. However, no standard user interface is provided; use bdist_msi to create MSI files with a user-interface for installing Python packages.

class msilib.Control(dlg, name)

Base class of the dialog controls. dlg is the dialog object the control belongs to, and name is the control’s name.

event(event, argument, condition=1, ordering=None)

Make an entry into the ControlEvent table for this control.

mapping(event, attribute)

Make an entry into the EventMapping table for this control.

condition(action, condition)

Make an entry into the ControlCondition table for this control.

class msilib.RadioButtonGroup(dlg, name, property)

Create a radio button control named name. property is the installer property that gets set when a radio button is selected.

add(name, x, y, width, height, text, value=None)

Add a radio button named name to the group, at the coordinates x, y, width, height, and with the label text. If value is None, it defaults to name.

class msilib.Dialog(db, name, x, y, w, h, attr, title, first, default, cancel)

Return a new Dialog object. An entry in the Dialog table is made, with the specified coordinates, dialog attributes, title, name of the first, default, and cancel controls.

control(name, type, x, y, width, height, attributes, property, text, control_next, help)

Return a new Control object. An entry in the Control table is made with the specified parameters.

This is a generic method; for specific types, specialized methods are provided.

text(name, x, y, width, height, attributes, text)

Add and return a Text control.

bitmap(name, x, y, width, height, text)

Add and return a Bitmap control.

line(name, x, y, width, height)

Add and return a Line control.

pushbutton(name, x, y, width, height, attributes, text, next_control)

Add and return a PushButton control.

radiogroup(name, x, y, width, height, attributes, property, text, next_control)

Add and return a RadioButtonGroup control.

checkbox(name, x, y, width, height, attributes, property, text, next_control)

Add and return a CheckBox control.

Voir aussi

Dialog Table [https://msdn.microsoft.com/en-us/library/windows/desktop/aa368286.aspx] Control Table [https://msdn.microsoft.com/en-us/library/windows/desktop/aa368044.aspx] Control Types [https://msdn.microsoft.com/en-us/library/windows/desktop/aa368039.aspx] ControlCondition Table [https://msdn.microsoft.com/en-us/library/windows/desktop/aa368035.aspx] ControlEvent Table [https://msdn.microsoft.com/en-us/library/windows/desktop/aa368037.aspx] EventMapping Table [https://msdn.microsoft.com/en-us/library/windows/desktop/aa368559.aspx] RadioButton Table [https://msdn.microsoft.com/en-us/library/windows/desktop/aa370962.aspx]

34.1.10. Precomputed tables

msilib provides a few subpackages that contain only schema and table definitions. Currently, these definitions are based on MSI version 2.0.

msilib.schema

This is the standard MSI schema for MSI 2.0, with the tables variable providing a list of table definitions, and _Validation_records providing the data for MSI validation.

msilib.sequence

This module contains table contents for the standard sequence tables: AdminExecuteSequence, AdminUISequence, AdvtExecuteSequence, InstallExecuteSequence, and InstallUISequence.

msilib.text

This module contains definitions for the UIText and ActionText tables, for the standard installer actions.

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34.2. msvcrt — Useful routines from the MS VC++ runtime

These functions provide access to some useful capabilities on Windows platforms. Some higher-level modules use these functions to build the Windows implementations of their services. For example, the getpass module uses this in the implementation of the getpass() function.

Further documentation on these functions can be found in the Platform API documentation.

The module implements both the normal and wide char variants of the console I/O api. The normal API deals only with ASCII characters and is of limited use for internationalized applications. The wide char API should be used where ever possible.

Modifié dans la version 3.3: Operations in this module now raise OSError where IOError was raised.

34.2.1. File Operations

msvcrt.locking(fd, mode, nbytes)

Lock part of a file based on file descriptor fd from the C runtime. Raises OSError on failure. The locked region of the file extends from the current file position for nbytes bytes, and may continue beyond the end of the file. mode must be one of the LK_* constants listed below. Multiple regions in a file may be locked at the same time, but may not overlap. Adjacent regions are not merged; they must be unlocked individually.

msvcrt.LK_LOCK

msvcrt.LK_RLCK

Locks the specified bytes. If the bytes cannot be locked, the program immediately tries again after 1 second. If, after 10 attempts, the bytes cannot be locked, OSError is raised.

msvcrt.LK_NBLCK

msvcrt.LK_NBRLCK

Locks the specified bytes. If the bytes cannot be locked, OSError is raised.

msvcrt.LK_UNLCK

Unlocks the specified bytes, which must have been previously locked.

msvcrt.setmode(fd, flags)

Set the line-end translation mode for the file descriptor fd. To set it to text mode, flags should be os.O_TEXT; for binary, it should be os.O_BINARY.

msvcrt.open_osfhandle(handle, flags)

Create a C runtime file descriptor from the file handle handle. The flags parameter should be a bitwise OR of os.O_APPEND, os.O_RDONLY, and os.O_TEXT. The returned file descriptor may be used as a parameter to os.fdopen() to create a file object.

msvcrt.get_osfhandle(fd)

Return the file handle for the file descriptor fd. Raises OSError if fd is not recognized.

34.2.2. Console I/O

msvcrt.kbhit()

Return true if a keypress is waiting to be read.

msvcrt.getch()

Read a keypress and return the resulting character as a byte string. Nothing is echoed to the console. This call will block if a keypress is not already available, but will not wait for Enter to be pressed. If the pressed key was a special function key, this will return '\000' or '\xe0'; the next call will return the keycode. The Control-C keypress cannot be read with this function.

msvcrt.getwch()

Wide char variant of getch(), returning a Unicode value.

msvcrt.getche()

Similar to getch(), but the keypress will be echoed if it represents a printable character.

msvcrt.getwche()

Wide char variant of getche(), returning a Unicode value.

msvcrt.putch(char)

Print the byte string char to the console without buffering.

msvcrt.putwch(unicode_char)

Wide char variant of putch(), accepting a Unicode value.

msvcrt.ungetch(char)

Cause the byte string char to be « pushed back » into the console buffer; it will be the next character read by getch() or getche().

msvcrt.ungetwch(unicode_char)

Wide char variant of ungetch(), accepting a Unicode value.

34.2.3. Other Functions

msvcrt.heapmin()

Force the malloc() heap to clean itself up and return unused blocks to the operating system. On failure, this raises OSError.

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34.3. winreg — Windows registry access

These functions expose the Windows registry API to Python. Instead of using an integer as the registry handle, a handle object is used to ensure that the handles are closed correctly, even if the programmer neglects to explicitly close them.

Modifié dans la version 3.3: Several functions in this module used to raise a WindowsError, which is now an alias of OSError.

34.3.1. Fonctions

This module offers the following functions:

winreg.CloseKey(hkey)

Closes a previously opened registry key. The hkey argument specifies a previously opened key.

Note

If hkey is not closed using this method (or via hkey.Close()), it is closed when the hkey object is destroyed by Python.

winreg.ConnectRegistry(computer_name, key)

Establishes a connection to a predefined registry handle on another computer, and returns a handle object.

computer_name is the name of the remote computer, of the form r"\\computername". If None, the local computer is used.

key is the predefined handle to connect to.

The return value is the handle of the opened key. If the function fails, an OSError exception is raised.

Modifié dans la version 3.3: See above.

winreg.CreateKey(key, sub_key)

Creates or opens the specified key, returning a handle object.

key is an already open key, or one of the predefined HKEY_* constants.

sub_key is a string that names the key this method opens or creates.

If key is one of the predefined keys, sub_key may be None. In that case, the handle returned is the same key handle passed in to the function.

If the key already exists, this function opens the existing key.

The return value is the handle of the opened key. If the function fails, an OSError exception is raised.

Modifié dans la version 3.3: See above.

winreg.CreateKeyEx(key, sub_key, reserved=0, access=KEY_WRITE)

Creates or opens the specified key, returning a handle object.

key is an already open key, or one of the predefined HKEY_* constants.

sub_key is a string that names the key this method opens or creates.

reserved is a reserved integer, and must be zero. The default is zero.

access is an integer that specifies an access mask that describes the desired security access for the key. Default is KEY_WRITE. See Access Rights for other allowed values.

If key is one of the predefined keys, sub_key may be None. In that case, the handle returned is the same key handle passed in to the function.

If the key already exists, this function opens the existing key.

The return value is the handle of the opened key. If the function fails, an OSError exception is raised.

Nouveau dans la version 3.2.

Modifié dans la version 3.3: See above.

winreg.DeleteKey(key, sub_key)

Deletes the specified key.

key is an already open key, or one of the predefined HKEY_* constants.

sub_key is a string that must be a subkey of the key identified by the key parameter. This value must not be None, and the key may not have subkeys.

This method can not delete keys with subkeys.

If the method succeeds, the entire key, including all of its values, is removed. If the method fails, an OSError exception is raised.

Modifié dans la version 3.3: See above.

winreg.DeleteKeyEx(key, sub_key, access=KEY_WOW64_64KEY, reserved=0)

Deletes the specified key.

Note

The DeleteKeyEx() function is implemented with the RegDeleteKeyEx Windows API function, which is specific to 64-bit versions of Windows. See the RegDeleteKeyEx documentation [https://msdn.microsoft.com/en-us/library/ms724847%28VS.85%29.aspx].

key is an already open key, or one of the predefined HKEY_* constants.

sub_key is a string that must be a subkey of the key identified by the key parameter. This value must not be None, and the key may not have subkeys.

reserved is a reserved integer, and must be zero. The default is zero.

access is an integer that specifies an access mask that describes the desired security access for the key. Default is KEY_WOW64_64KEY. See Access Rights for other allowed values.

This method can not delete keys with subkeys.

If the method succeeds, the entire key, including all of its values, is removed. If the method fails, an OSError exception is raised.

On unsupported Windows versions, NotImplementedError is raised.

Nouveau dans la version 3.2.

Modifié dans la version 3.3: See above.

winreg.DeleteValue(key, value)

Removes a named value from a registry key.

key is an already open key, or one of the predefined HKEY_* constants.

value is a string that identifies the value to remove.

winreg.EnumKey(key, index)

Enumerates subkeys of an open registry key, returning a string.

key is an already open key, or one of the predefined HKEY_* constants.

index is an integer that identifies the index of the key to retrieve.

The function retrieves the name of one subkey each time it is called. It is typically called repeatedly until an OSError exception is raised, indicating, no more values are available.

Modifié dans la version 3.3: See above.

winreg.EnumValue(key, index)

Enumerates values of an open registry key, returning a tuple.

key is an already open key, or one of the predefined HKEY_* constants.

index is an integer that identifies the index of the value to retrieve.

The function retrieves the name of one subkey each time it is called. It is typically called repeatedly, until an OSError exception is raised, indicating no more values.

The result is a tuple of 3 items:

Index

Signification

0

A string that identifies the value name

1

An object that holds the value data, and whose type depends on the underlying registry type

2

An integer that identifies the type of the value data (see table in docs for SetValueEx())

Modifié dans la version 3.3: See above.

winreg.ExpandEnvironmentStrings(str)

Expands environment variable placeholders %NAME% in strings like REG_EXPAND_SZ:

>>> ExpandEnvironmentStrings('%windir%')
'C:\\Windows'

winreg.FlushKey(key)

Writes all the attributes of a key to the registry.

key is an already open key, or one of the predefined HKEY_* constants.

It is not necessary to call FlushKey() to change a key. Registry changes are flushed to disk by the registry using its lazy flusher. Registry changes are also flushed to disk at system shutdown. Unlike CloseKey(), the FlushKey() method returns only when all the data has been written to the registry. An application should only call FlushKey() if it requires absolute certainty that registry changes are on disk.

Note

If you don’t know whether a FlushKey() call is required, it probably isn’t.

winreg.LoadKey(key, sub_key, file_name)

Creates a subkey under the specified key and stores registration information from a specified file into that subkey.

key is a handle returned by ConnectRegistry() or one of the constants HKEY_USERS or HKEY_LOCAL_MACHINE.

sub_key is a string that identifies the subkey to load.

file_name is the name of the file to load registry data from. This file must have been created with the SaveKey() function. Under the file allocation table (FAT) file system, the filename may not have an extension.

A call to LoadKey() fails if the calling process does not have the SE_RESTORE_PRIVILEGE privilege. Note that privileges are different from permissions – see the RegLoadKey documentation [https://msdn.microsoft.com/en-us/library/ms724889%28v=VS.85%29.aspx] for more details.

If key is a handle returned by ConnectRegistry(), then the path specified in file_name is relative to the remote computer.

winreg.OpenKey(key, sub_key, reserved=0, access=KEY_READ)

winreg.OpenKeyEx(key, sub_key, reserved=0, access=KEY_READ)

Opens the specified key, returning a handle object.

key is an already open key, or one of the predefined HKEY_* constants.

sub_key is a string that identifies the sub_key to open.

reserved is a reserved integer, and must be zero. The default is zero.

access is an integer that specifies an access mask that describes the desired security access for the key. Default is KEY_READ. See Access Rights for other allowed values.

The result is a new handle to the specified key.

If the function fails, OSError is raised.

Modifié dans la version 3.2: Allow the use of named arguments.

Modifié dans la version 3.3: See above.

winreg.QueryInfoKey(key)

Returns information about a key, as a tuple.

key is an already open key, or one of the predefined HKEY_* constants.

The result is a tuple of 3 items:

Index

Signification

0

An integer giving the number of sub keys this key has.

1

An integer giving the number of values this key has.

2

An integer giving when the key was last modified (if available) as 100’s of nanoseconds since Jan 1, 1601.

winreg.QueryValue(key, sub_key)

Retrieves the unnamed value for a key, as a string.

key is an already open key, or one of the predefined HKEY_* constants.

sub_key is a string that holds the name of the subkey with which the value is associated. If this parameter is None or empty, the function retrieves the value set by the SetValue() method for the key identified by key.

Values in the registry have name, type, and data components. This method retrieves the data for a key’s first value that has a NULL name. But the underlying API call doesn’t return the type, so always use QueryValueEx() if possible.

winreg.QueryValueEx(key, value_name)

Retrieves the type and data for a specified value name associated with an open registry key.

key is an already open key, or one of the predefined HKEY_* constants.

value_name is a string indicating the value to query.

The result is a tuple of 2 items:

Index

Signification

0

The value of the registry item.

1

An integer giving the registry type for this value (see table in docs for SetValueEx())

winreg.SaveKey(key, file_name)

Saves the specified key, and all its subkeys to the specified file.

key is an already open key, or one of the predefined HKEY_* constants.

file_name is the name of the file to save registry data to. This file cannot already exist. If this filename includes an extension, it cannot be used on file allocation table (FAT) file systems by the LoadKey() method.

If key represents a key on a remote computer, the path described by file_name is relative to the remote computer. The caller of this method must possess the SeBackupPrivilege security privilege. Note that privileges are different than permissions – see the Conflicts Between User Rights and Permissions documentation [https://msdn.microsoft.com/en-us/library/ms724878%28v=VS.85%29.aspx] for more details.

This function passes NULL for security_attributes to the API.

winreg.SetValue(key, sub_key, type, value)

Associates a value with a specified key.

key is an already open key, or one of the predefined HKEY_* constants.

sub_key is a string that names the subkey with which the value is associated.

type is an integer that specifies the type of the data. Currently this must be REG_SZ, meaning only strings are supported. Use the SetValueEx() function for support for other data types.

value is a string that specifies the new value.

If the key specified by the sub_key parameter does not exist, the SetValue function creates it.

Value lengths are limited by available memory. Long values (more than 2048 bytes) should be stored as files with the filenames stored in the configuration registry. This helps the registry perform efficiently.

The key identified by the key parameter must have been opened with KEY_SET_VALUE access.

winreg.SetValueEx(key, value_name, reserved, type, value)

Stores data in the value field of an open registry key.

key is an already open key, or one of the predefined HKEY_* constants.

value_name is a string that names the subkey with which the value is associated.

reserved can be anything – zero is always passed to the API.

type is an integer that specifies the type of the data. See Value Types for the available types.

value is a string that specifies the new value.

This method can also set additional value and type information for the specified key. The key identified by the key parameter must have been opened with KEY_SET_VALUE access.

To open the key, use the CreateKey() or OpenKey() methods.

Value lengths are limited by available memory. Long values (more than 2048 bytes) should be stored as files with the filenames stored in the configuration registry. This helps the registry perform efficiently.

winreg.DisableReflectionKey(key)

Disables registry reflection for 32-bit processes running on a 64-bit operating system.

key is an already open key, or one of the predefined HKEY_* constants.

Will generally raise NotImplemented if executed on a 32-bit operating system.

If the key is not on the reflection list, the function succeeds but has no effect. Disabling reflection for a key does not affect reflection of any subkeys.

winreg.EnableReflectionKey(key)

Restores registry reflection for the specified disabled key.

key is an already open key, or one of the predefined HKEY_* constants.

Will generally raise NotImplemented if executed on a 32-bit operating system.

Restoring reflection for a key does not affect reflection of any subkeys.

winreg.QueryReflectionKey(key)

Determines the reflection state for the specified key.

key is an already open key, or one of the predefined HKEY_* constants.

Returns True if reflection is disabled.

Will generally raise NotImplemented if executed on a 32-bit operating system.

34.3.2. Constantes

The following constants are defined for use in many _winreg functions.

34.3.2.1. HKEY_* Constants

winreg.HKEY_CLASSES_ROOT

Registry entries subordinate to this key define types (or classes) of documents and the properties associated with those types. Shell and COM applications use the information stored under this key.

winreg.HKEY_CURRENT_USER

Registry entries subordinate to this key define the preferences of the current user. These preferences include the settings of environment variables, data about program groups, colors, printers, network connections, and application preferences.

winreg.HKEY_LOCAL_MACHINE

Registry entries subordinate to this key define the physical state of the computer, including data about the bus type, system memory, and installed hardware and software.

winreg.HKEY_USERS

Registry entries subordinate to this key define the default user configuration for new users on the local computer and the user configuration for the current user.

winreg.HKEY_PERFORMANCE_DATA

Registry entries subordinate to this key allow you to access performance data. The data is not actually stored in the registry; the registry functions cause the system to collect the data from its source.

winreg.HKEY_CURRENT_CONFIG

Contains information about the current hardware profile of the local computer system.

winreg.HKEY_DYN_DATA

This key is not used in versions of Windows after 98.

34.3.2.2. Access Rights

For more information, see Registry Key Security and Access [https://msdn.microsoft.com/en-us/library/ms724878%28v=VS.85%29.aspx].

winreg.KEY_ALL_ACCESS

Combines the STANDARD_RIGHTS_REQUIRED, KEY_QUERY_VALUE, KEY_SET_VALUE, KEY_CREATE_SUB_KEY, KEY_ENUMERATE_SUB_KEYS, KEY_NOTIFY, and KEY_CREATE_LINK access rights.

winreg.KEY_WRITE

Combines the STANDARD_RIGHTS_WRITE, KEY_SET_VALUE, and KEY_CREATE_SUB_KEY access rights.

winreg.KEY_READ

Combines the STANDARD_RIGHTS_READ, KEY_QUERY_VALUE, KEY_ENUMERATE_SUB_KEYS, and KEY_NOTIFY values.

winreg.KEY_EXECUTE

Equivalent to KEY_READ.

winreg.KEY_QUERY_VALUE

Required to query the values of a registry key.

winreg.KEY_SET_VALUE

Required to create, delete, or set a registry value.

winreg.KEY_CREATE_SUB_KEY

Required to create a subkey of a registry key.

winreg.KEY_ENUMERATE_SUB_KEYS

Required to enumerate the subkeys of a registry key.

winreg.KEY_NOTIFY

Required to request change notifications for a registry key or for subkeys of a registry key.

winreg.KEY_CREATE_LINK

Reserved for system use.

34.3.2.2.1. 64-bit Specific

For more information, see Accessing an Alternate Registry View [https://msdn.microsoft.com/en-us/library/aa384129(v=VS.85).aspx].

winreg.KEY_WOW64_64KEY

Indicates that an application on 64-bit Windows should operate on the 64-bit registry view.

winreg.KEY_WOW64_32KEY

Indicates that an application on 64-bit Windows should operate on the 32-bit registry view.

34.3.2.3. Value Types

For more information, see Registry Value Types [https://msdn.microsoft.com/en-us/library/ms724884%28v=VS.85%29.aspx].

winreg.REG_BINARY

Binary data in any form.

winreg.REG_DWORD

32-bit number.

winreg.REG_DWORD_LITTLE_ENDIAN

A 32-bit number in little-endian format. Equivalent to REG_DWORD.

winreg.REG_DWORD_BIG_ENDIAN

A 32-bit number in big-endian format.

winreg.REG_EXPAND_SZ

Null-terminated string containing references to environment variables (%PATH%).

winreg.REG_LINK

A Unicode symbolic link.

winreg.REG_MULTI_SZ

A sequence of null-terminated strings, terminated by two null characters. (Python handles this termination automatically.)

winreg.REG_NONE

No defined value type.

winreg.REG_QWORD

A 64-bit number.

Nouveau dans la version 3.6.

winreg.REG_QWORD_LITTLE_ENDIAN

A 64-bit number in little-endian format. Equivalent to REG_QWORD.

Nouveau dans la version 3.6.

winreg.REG_RESOURCE_LIST

A device-driver resource list.

winreg.REG_FULL_RESOURCE_DESCRIPTOR

A hardware setting.

winreg.REG_RESOURCE_REQUIREMENTS_LIST

A hardware resource list.

winreg.REG_SZ

A null-terminated string.

34.3.3. Registry Handle Objects

This object wraps a Windows HKEY object, automatically closing it when the object is destroyed. To guarantee cleanup, you can call either the Close() method on the object, or the CloseKey() function.

All registry functions in this module return one of these objects.

All registry functions in this module which accept a handle object also accept an integer, however, use of the handle object is encouraged.

Handle objects provide semantics for __bool__() – thus

if handle:
    print("Yes")

will print Yes if the handle is currently valid (has not been closed or detached).

The object also support comparison semantics, so handle objects will compare true if they both reference the same underlying Windows handle value.

Handle objects can be converted to an integer (e.g., using the built-in int() function), in which case the underlying Windows handle value is returned. You can also use the Detach() method to return the integer handle, and also disconnect the Windows handle from the handle object.

PyHKEY.Close()

Closes the underlying Windows handle.

If the handle is already closed, no error is raised.

PyHKEY.Detach()

Detaches the Windows handle from the handle object.

The result is an integer that holds the value of the handle before it is detached. If the handle is already detached or closed, this will return zero.

After calling this function, the handle is effectively invalidated, but the handle is not closed. You would call this function when you need the underlying Win32 handle to exist beyond the lifetime of the handle object.

PyHKEY.__enter__()

PyHKEY.__exit__(*exc_info)

The HKEY object implements __enter__() and __exit__() and thus supports the context protocol for the with statement:

with OpenKey(HKEY_LOCAL_MACHINE, "foo") as key:
    ...  # work with key

will automatically close key when control leaves the with block.

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34.4. winsound — Sound-playing interface for Windows

The winsound module provides access to the basic sound-playing machinery provided by Windows platforms. It includes functions and several constants.

winsound.Beep(frequency, duration)

Beep the PC’s speaker. The frequency parameter specifies frequency, in hertz, of the sound, and must be in the range 37 through 32,767. The duration parameter specifies the number of milliseconds the sound should last. If the system is not able to beep the speaker, RuntimeError is raised.

winsound.PlaySound(sound, flags)

Call the underlying PlaySound() function from the Platform API. The sound parameter may be a filename, a system sound alias, audio data as a bytes-like object, or None. Its interpretation depends on the value of flags, which can be a bitwise ORed combination of the constants described below. If the sound parameter is None, any currently playing waveform sound is stopped. If the system indicates an error, RuntimeError is raised.

winsound.MessageBeep(type=MB_OK)

Call the underlying MessageBeep() function from the Platform API. This plays a sound as specified in the registry. The type argument specifies which sound to play; possible values are -1, MB_ICONASTERISK, MB_ICONEXCLAMATION, MB_ICONHAND, MB_ICONQUESTION, and MB_OK, all described below. The value -1 produces a « simple beep »; this is the final fallback if a sound cannot be played otherwise. If the system indicates an error, RuntimeError is raised.

winsound.SND_FILENAME

The sound parameter is the name of a WAV file. Do not use with SND_ALIAS.

winsound.SND_ALIAS

The sound parameter is a sound association name from the registry. If the registry contains no such name, play the system default sound unless SND_NODEFAULT is also specified. If no default sound is registered, raise RuntimeError. Do not use with SND_FILENAME.

All Win32 systems support at least the following; most systems support many more:

PlaySound() name

Corresponding Control Panel Sound name

'SystemAsterisk'

Asterisk

'SystemExclamation'

Exclamation

'SystemExit'

Exit Windows

'SystemHand'

Critical Stop

'SystemQuestion'

Question

Par exemple :

import winsound
# Play Windows exit sound.
winsound.PlaySound("SystemExit", winsound.SND_ALIAS)

# Probably play Windows default sound, if any is registered (because
# "*" probably isn't the registered name of any sound).
winsound.PlaySound("*", winsound.SND_ALIAS)

winsound.SND_LOOP

Play the sound repeatedly. The SND_ASYNC flag must also be used to avoid blocking. Cannot be used with SND_MEMORY.

winsound.SND_MEMORY

The sound parameter to PlaySound() is a memory image of a WAV file, as a bytes-like object.

Note

This module does not support playing from a memory image asynchronously, so a combination of this flag and SND_ASYNC will raise RuntimeError.

winsound.SND_PURGE

Stop playing all instances of the specified sound.

Note

This flag is not supported on modern Windows platforms.

winsound.SND_ASYNC

Return immediately, allowing sounds to play asynchronously.

winsound.SND_NODEFAULT

If the specified sound cannot be found, do not play the system default sound.

winsound.SND_NOSTOP

Do not interrupt sounds currently playing.

winsound.SND_NOWAIT

Return immediately if the sound driver is busy.

Note

This flag is not supported on modern Windows platforms.

winsound.MB_ICONASTERISK

Play the SystemDefault sound.

winsound.MB_ICONEXCLAMATION

Play the SystemExclamation sound.

winsound.MB_ICONHAND

Play the SystemHand sound.

winsound.MB_ICONQUESTION

Play the SystemQuestion sound.

winsound.MB_OK

Play the SystemDefault sound.

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35. Services spécifiques à Unix

Les modules décrits dans ce chapitre fournissent des interfaces aux fonctionnalités propres au système d’exploitation Unix ou, dans certains cas, à certaines de ses variantes, en voici un aperçu :

35.1. posix — Les appels système POSIX les plus courants

35.1.1. Prise en charge de gros fichiers

35.1.2. Contenu du Module

35.2. pwd — The password database

35.3. spwd — La base de données de mots de passe shadow

35.4. grp — The group database

35.5. crypt — Function to check Unix passwords

35.5.1. Hashing Methods

35.5.2. Module Attributes

35.5.3. Module Functions

35.5.4. Exemples

35.6. termios — Le style POSIX le contrôle TTY

35.6.1. Exemple

35.7. tty — Fonctions de gestion du terminal

35.8. pty — Outils de manipulation de pseudo-terminaux

35.8.1. Exemple

35.9. fcntl — The fcntl and ioctl system calls

35.10. pipes — Interface au pipelines shell

35.10.1. L’Objet Template

35.11. resource — Resource usage information

35.11.1. Resource Limits

35.11.2. Resource Usage

35.12. nis — Interface à Sun’s NIS (pages jaunes)

35.13. syslog — Unix syslog library routines

35.13.1. Exemples

35.13.1.1. Simple example

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35.1. posix — Les appels système POSIX les plus courants

Ce module permet d’accéder aux fonctionnalités du système d’exploitation normalisés par le Standard C et le Standard POSIX (une interface Unix habilement déguisée).

Ne pas importer ce module directement. À la place, importer le module os, qui fournit une version portable de cette interface. Sous Unix, le module os fournit un sur-ensemble de l’interface posix. Sous les systèmes d’exploitation non Unix le module posix n’est pas disponible, mais un sous ensemble est toujours disponible via l’interface os. Une fois que os est importé, il n’y a aucune perte de performance à l’utiliser à la place de posix. De plus, os fournit des fonctionnalités supplémentaires, telles que l’appel automatique de putenv() lorsqu’une entrée dans os.environ est modifiée.

Les erreurs sont signalées comme des exceptions; les exceptions habituelles sont données pour les erreurs de type, tandis que les erreurs signalées par les appels système lèvent une erreur OSError.

35.1.1. Prise en charge de gros fichiers

De nombreux systèmes d’exploitation (y compris AIX, HP-UX, Irix et Solaris) prennent en charge les fichiers d’une taille supérieure à 2 Go malgré que le compilateur C utilise des types int et long d’une longueur de 32 bit. Ceci est généralement accompli en définissant un nouveau type de 64 bit. Ces fichiers sont parfois appelés fichiers volumineux.

La prise en charge des fichiers volumineux dans Python est activée lorsque la taille de off_t est supérieure à long et que le type long long est disponible et est au moins aussi grand que off_t. Il peut-être nécessaire de configurer et compiler Python avec certaines options pour activer ce mode. Par exemple, il est activé par défaut avec les versions récentes d’Irix, mais avec Solaris 2.6 et 2.7 vous avez besoin de faire quelque chose comme:

CFLAGS="`getconf LFS_CFLAGS`" OPT="-g -O2 $CFLAGS" \
        ./configure

Sur les systèmes Linux capable de supporter les fichiers volumineux, cela pourrait fonctionner :

CFLAGS='-D_LARGEFILE64_SOURCE -D_FILE_OFFSET_BITS=64' OPT="-g -O2 $CFLAGS" \
        ./configure

35.1.2. Contenu du Module

En plus des nombreuses fonctions décrites dans la documentation du module os, posix possède les éléments suivants:

posix.environ

Un dictionnaire représentant les variables d’environnement au moment où l’interpréteur à été lancé. Les clés et les valeurs sont des bytes sous Unix et des str sous Windows. Par exemple, environ[b'HOME'] (environ['HOME'] dans Windows) est le chemin de votre dossier d’accueil, équivalent à getenv("HOME") en C.

Modifier ce dictionnaire n’affecte pas les variables d’environnements fournis par execv(), popen() ou system(); Si vous avez besoin de changer l’environnement, passer le paramètre environ à execve() ou ajouter les assignations de variables et les export à la commande à exécuter via system() ou popen().

Modifié dans la version 3.2: Sous Unix, les clés et les valeurs sont des octets.

Note

Le module os fournit une implémentation alternative à environ qui met à jour l’environnement en cas de modification. Notez également que la mise à jour de os.environ rendra ce dictionnaire obsolète. Il est recommandé d’utiliser le module os au lieu du module posix dans ce cas-ci.

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35.2. pwd — The password database

This module provides access to the Unix user account and password database. It is available on all Unix versions.

Password database entries are reported as a tuple-like object, whose attributes correspond to the members of the passwd structure (Attribute field below, see <pwd.h>):

Index

Attribut

Signification

0

pw_name

Nom d’utilisateur

1

pw_passwd

Optional encrypted password

2

pw_uid

Numerical user ID

3

pw_gid

Numerical group ID

4

pw_gecos

User name or comment field

5

pw_dir

Répertoire d’accueil de l’utilisateur

6

pw_shell

User command interpreter

The uid and gid items are integers, all others are strings. KeyError is raised if the entry asked for cannot be found.

Note

In traditional Unix the field pw_passwd usually contains a password encrypted with a DES derived algorithm (see module crypt). However most modern unices use a so-called shadow password system. On those unices the pw_passwd field only contains an asterisk ('*') or the letter 'x' where the encrypted password is stored in a file /etc/shadow which is not world readable. Whether the pw_passwd field contains anything useful is system-dependent. If available, the spwd module should be used where access to the encrypted password is required.

It defines the following items:

pwd.getpwuid(uid)

Return the password database entry for the given numeric user ID.

pwd.getpwnam(name)

Return the password database entry for the given user name.

pwd.getpwall()

Return a list of all available password database entries, in arbitrary order.

Voir aussi

Module grp

Interface pour la base de données des groupes, similaire à celle-ci.

Module spwd

An interface to the shadow password database, similar to this.

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35.3. spwd — La base de données de mots de passe shadow

Ce module permet d’accéder à la base de données UNIX de mots de passe shadow. Elle est disponible sur différentes versions d’UNIX.

Vous devez disposer des droits suffisants pour accéder à la base de données de mots de passe shadow (cela signifie généralement que vous devez être root).

Les entrées de la base de données de mots de passe shadow sont renvoyées comme un objet semblable à un tuple, dont les attributs correspondent aux membres de la structure spwd (champ attribut ci-dessous, voir <shadow.h>) :

Index

Attribut

Signification

0

sp_namp

Nom d’utilisateur

1

sp_pwdp

Mot de passe haché

2

sp_lstchg

Date du dernier changement

3

sp_min

Nombre minimal de jours entre les modifications

4

sp_max

Nombre maximal de jours entre les modifications

5

sp_warn

Nombre de jours avant l’expiration du mot de passe pendant lequel l’utilisateur doit être prévenu

6

sp_inact

Nombre de jours avant la désactivation du compte, suite à l’expiration du mot de passe

7

sp_expire

Date à laquelle le compte expire, en nombre de jours depuis le 1er janvier 1970

8

sp_flag

Réservé

Les champs sp_namp et sp_pwdp sont des chaines de caractères, tous les autres sont des entiers. KeyError est levée si l’entrée demandée est introuvable.

Les fonctions suivantes sont définies :

spwd.getspnam(name)

Renvoie l’entrée de base de données de mot de passe shadow pour le nom d’utilisateur donné.

Modifié dans la version 3.6: Lève une PermissionError au lieu d’une KeyError si l’utilisateur n’a pas les droits suffisants.

spwd.getspall()

Renvoie une liste de toutes les entrées de la base de données de mots de passe shadow, dans un ordre arbitraire.

Voir aussi

Module grp

Interface pour la base de données des groupes, similaire à celle-ci.

Module pwd

Interface pour la base de données (normale) des mots de passe, semblable à ceci.

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35.4. grp — The group database

This module provides access to the Unix group database. It is available on all Unix versions.

Group database entries are reported as a tuple-like object, whose attributes correspond to the members of the group structure (Attribute field below, see <pwd.h>):

Index

Attribut

Signification

0

gr_name

the name of the group

1

gr_passwd

the (encrypted) group password; often empty

2

gr_gid

the numerical group ID

3

gr_mem

all the group member’s user names

The gid is an integer, name and password are strings, and the member list is a list of strings. (Note that most users are not explicitly listed as members of the group they are in according to the password database. Check both databases to get complete membership information. Also note that a gr_name that starts with a + or - is likely to be a YP/NIS reference and may not be accessible via getgrnam() or getgrgid().)

It defines the following items:

grp.getgrgid(gid)

Return the group database entry for the given numeric group ID. KeyError is raised if the entry asked for cannot be found.

Obsolète depuis la version 3.6: Since Python 3.6 the support of non-integer arguments like floats or strings in getgrgid() is deprecated.

grp.getgrnam(name)

Return the group database entry for the given group name. KeyError is raised if the entry asked for cannot be found.

grp.getgrall()

Return a list of all available group entries, in arbitrary order.

Voir aussi

Module pwd

An interface to the user database, similar to this.

Module spwd

An interface to the shadow password database, similar to this.

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35.5. crypt — Function to check Unix passwords

Source code: Lib/crypt.py [https://github.com/python/cpython/tree/3.6/Lib/crypt.py]

This module implements an interface to the crypt(3) routine, which is a one-way hash function based upon a modified DES algorithm; see the Unix man page for further details. Possible uses include storing hashed passwords so you can check passwords without storing the actual password, or attempting to crack Unix passwords with a dictionary.

Notice that the behavior of this module depends on the actual implementation of the crypt(3) routine in the running system. Therefore, any extensions available on the current implementation will also be available on this module.

35.5.1. Hashing Methods

Nouveau dans la version 3.3.

The crypt module defines the list of hashing methods (not all methods are available on all platforms):

crypt.METHOD_SHA512

A Modular Crypt Format method with 16 character salt and 86 character hash. This is the strongest method.

crypt.METHOD_SHA256

Another Modular Crypt Format method with 16 character salt and 43 character hash.

crypt.METHOD_MD5

Another Modular Crypt Format method with 8 character salt and 22 character hash.

crypt.METHOD_CRYPT

The traditional method with a 2 character salt and 13 characters of hash. This is the weakest method.

35.5.2. Module Attributes

Nouveau dans la version 3.3.

crypt.methods

A list of available password hashing algorithms, as crypt.METHOD_* objects. This list is sorted from strongest to weakest.

35.5.3. Module Functions

The crypt module defines the following functions:

crypt.crypt(word, salt=None)

word will usually be a user’s password as typed at a prompt or in a graphical interface. The optional salt is either a string as returned from mksalt(), one of the crypt.METHOD_* values (though not all may be available on all platforms), or a full encrypted password including salt, as returned by this function. If salt is not provided, the strongest method will be used (as returned by methods()).

Checking a password is usually done by passing the plain-text password as word and the full results of a previous crypt() call, which should be the same as the results of this call.

salt (either a random 2 or 16 character string, possibly prefixed with $digit$ to indicate the method) which will be used to perturb the encryption algorithm. The characters in salt must be in the set [./a-zA-Z0-9], with the exception of Modular Crypt Format which prefixes a $digit$.

Returns the hashed password as a string, which will be composed of characters from the same alphabet as the salt.

Since a few crypt(3) extensions allow different values, with different sizes in the salt, it is recommended to use the full crypted password as salt when checking for a password.

Modifié dans la version 3.3: Accept crypt.METHOD_* values in addition to strings for salt.

crypt.mksalt(method=None)

Return a randomly generated salt of the specified method. If no method is given, the strongest method available as returned by methods() is used.

The return value is a string either of 2 characters in length for crypt.METHOD_CRYPT, or 19 characters starting with $digit$ and 16 random characters from the set [./a-zA-Z0-9], suitable for passing as the salt argument to crypt().

Nouveau dans la version 3.3.

35.5.4. Exemples

A simple example illustrating typical use (a constant-time comparison operation is needed to limit exposure to timing attacks. hmac.compare_digest() is suitable for this purpose):

import pwd
import crypt
import getpass
from hmac import compare_digest as compare_hash

def login():
    username = input('Python login: ')
    cryptedpasswd = pwd.getpwnam(username)[1]
    if cryptedpasswd:
        if cryptedpasswd == 'x' or cryptedpasswd == '*':
            raise ValueError('no support for shadow passwords')
        cleartext = getpass.getpass()
        return compare_hash(crypt.crypt(cleartext, cryptedpasswd), cryptedpasswd)
    else:
        return True

To generate a hash of a password using the strongest available method and check it against the original:

import crypt
from hmac import compare_digest as compare_hash

hashed = crypt.crypt(plaintext)
if not compare_hash(hashed, crypt.crypt(plaintext, hashed)):
    raise ValueError("hashed version doesn't validate against original")

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35.6. termios — Le style POSIX le contrôle TTY

Ce module fournit une interface aux appels POSIX pour le contrôle des E/S TTY. Pour une description complète de ces appels, voir la page du manuel UNIX termios(3). C’est disponible uniquement pour les versions Unix qui supportent le style POSIX termios et les contrôles d’entrées/sorties TTY configurés à l’installation.

Toutes les fonctions de ce module prennent un descripteur de fichier fd comme premier argument. Ça peut être un descripteur de fichiers entier, tel que le retourne sys.stdin.fileno(), ou un file object, tel que sys.stdin.

Ce module définit aussi toutes les constantes nécessaires pour travailler avec les fonctions fournies ici; elles ont les mêmes noms que leurs équivalents en C. Pour plus d’informations sur l’utilisation de ces terminaux, veuillez vous référer à votre documentation système.

Le module définit les fonctions suivantes :

termios.tcgetattr(fd)

Retourne une liste contenant les attributs TTY pour le descripteur de fichier fd, tel que: [iflag, oflag, cflag, lflag, ispeed, ospeed, cc] où cc est une liste de caractères spéciaux TTY (chacun est une chaine de caractère de longueur 1, à l’exception des éléments ayant les indices VMIN et VTIME, ceux-ci sont alors des entiers quand ces champs sont définis). L’interprétation des options (flags en anglais) et des vitesses ainsi que l’indexation dans le tableau cc doit être fait en utilisant les constantes symboliques définies dans le module termios.

termios.tcsetattr(fd, when, attributes)

Définit les attributs TTY pour le descripteur de fichiers fd à partir des attributs, qui est une liste comme celle retournée par tcgetattr(). L’argument when détermine quand les attributs sont changés: TCSANOW pour un changement immédiat, TCSADRAIN pour un changement après la transmission de toute sortie en file d’attente, ou TCSAFLUSH pour un changement après avoir transmis toute sortie en file d’attente et rejeté toutes entrée en file d’attente.

termios.tcsendbreak(fd, duration)

Send a break on file descriptor fd. A zero duration sends a break for 0.25–0.5 seconds; a nonzero duration has a system dependent meaning.

termios.tcdrain(fd)

Attends que toutes les sorties écrites dans le descripteur de fichier fd soient transmises.

termios.tcflush(fd, queue)

Vide la queue de données du descripteur de fichier fd. Le sélecteur queue précise la queue: TCIFLUSH pour la queue des entrées, TCOFLUSH pour la queue des sorties, ou TCIOFLUSH pour les deux queues.

termios.tcflow(fd, action)

Suspends ou reprends l’entrée ou la sortie du descripteur de fichier fd. L’argument action peut être TCOOFF pour suspendre la sortie, TCOON pour relancer la sortie, TCIOFF pour suspendre l’entrée, ou TCION pour relancer l’entrée.

Voir aussi

Le module tty

Fonctions utiles pour les opérations de contrôle communes dans le terminal.

35.6.1. Exemple

Voici une fonction qui demande à l’utilisateur d’entrer un mot de passe sans l’afficher. Remarquez la technique qui consiste à séparer un appel à tcgetattr() et une instruction try… finally pour s’assurer que les anciens attributs tty soient restaurés tels quels quoi qu’il arrive :

def getpass(prompt="Password: "):
    import termios, sys
    fd = sys.stdin.fileno()
    old = termios.tcgetattr(fd)
    new = termios.tcgetattr(fd)
    new[3] = new[3] & ~termios.ECHO          # lflags
    try:
        termios.tcsetattr(fd, termios.TCSADRAIN, new)
        passwd = input(prompt)
    finally:
        termios.tcsetattr(fd, termios.TCSADRAIN, old)
    return passwd

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35.7. tty — Fonctions de gestion du terminal

Code source : Lib/tty.py [https://github.com/python/cpython/tree/3.6/Lib/tty.py]

Le module tty expose des fonctions permettant de mettre le tty en mode cbreak ou raw.

Puisqu’il a besoin du module termios, il ne fonctionnera que sur Unix.

Le module tty définit les fonctions suivantes :

tty.setraw(fd, when=termios.TCSAFLUSH)

Définit le mode du descripteur de fichier fd à row. Par défaut, when vaut termios.TCSAFLUSH, et est passé à termios.tcsetattr().

tty.setcbreak(fd, when=termios.TCSAFLUSH)

Définit le mode du descripteur de fichier fd à cbreak. when vaut termios.TCSAFLUSH par défaut, et est passé à termios.tcsetattr().

Voir aussi

Module termios

Interface bas niveau de gestion du terminal.

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35.8. pty — Outils de manipulation de pseudo-terminaux

Code source : Lib/pty.py [https://github.com/python/cpython/tree/3.6/Lib/pty.py]

Le module pty expose des fonctions de manipulation de pseudo-terminaux, il permet d’écrire un programme capable de démarrer un autre processus, d’écrire et de lire depuis son terminal.

La gestion de pseudo-terminaux étant très dépendante de la plateforme, ce code ne gère que Linux. (Code supposé fonctionner sur d’autres plateformes, mais sans avoir été testé).

Le module pty expose les fonctions suivantes :

pty.fork()

Fork. Connecte le terminal contrôlé par le fils à un pseudo-terminal. La valeur renvoyée est (pid, fd). Notez que le fils obtient 0 comme pid et un fd non valide. Le parent obtient le pid du fils, et fd un descripteur de fichier connecté à un terminal contrôlé par le fils (et donc à l’entrée et la sortie standard du fils).

pty.openpty()

Ouvre une nouvelle paire de pseudo-terminaux, en utilisant si possible os.openpty(), ou du code émulant la fonctionnalité pour des systèmes Unix génériques. Renvoie une paire de descripteurs de fichier (master, slave), pour le maître et pour l’esclave respectivement.

pty.spawn(argv[, master_read[, stdin_read]])

Crée un nouveau processus et connecte son terminal aux entrées/sorties standard du processus courant. C’est typiquement utilisé pour duper les programmes insistant sur le fait de lire depuis leur terminal.

Les fonctions master_read et stdin_read doivent être des fonctions lisant sur un descripteur de fichier. Par défaut elles lisent 1024 octets à chaque fois qu’elles sont appelées.

Modifié dans la version 3.4: spawn() renvoie maintenant la valeur renvoyée par os.waitpid() sur le processus fils.

35.8.1. Exemple

Le programme suivant se comporte comme la commande Unix script(1), utilisant un pseudo-terminal pour enregistrer toutes les entrées et sorties d’une session dans un fichier typescript.

import argparse
import os
import pty
import sys
import time

parser = argparse.ArgumentParser()
parser.add_argument('-a', dest='append', action='store_true')
parser.add_argument('-p', dest='use_python', action='store_true')
parser.add_argument('filename', nargs='?', default='typescript')
options = parser.parse_args()

shell = sys.executable if options.use_python else os.environ.get('SHELL', 'sh')
filename = options.filename
mode = 'ab' if options.append else 'wb'

with open(filename, mode) as script:
    def read(fd):
        data = os.read(fd, 1024)
        script.write(data)
        return data

    print('Script started, file is', filename)
    script.write(('Script started on %s\n' % time.asctime()).encode())

    pty.spawn(shell, read)

    script.write(('Script done on %s\n' % time.asctime()).encode())
    print('Script done, file is', filename)

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35.9. fcntl — The fcntl and ioctl system calls

This module performs file control and I/O control on file descriptors. It is an interface to the fcntl() and ioctl() Unix routines. For a complete description of these calls, see fcntl(2) and ioctl(2) Unix manual pages.

All functions in this module take a file descriptor fd as their first argument. This can be an integer file descriptor, such as returned by sys.stdin.fileno(), or an io.IOBase object, such as sys.stdin itself, which provides a fileno() that returns a genuine file descriptor.

Modifié dans la version 3.3: Operations in this module used to raise an IOError where they now raise an OSError.

Le module définit les fonctions suivantes :

fcntl.fcntl(fd, cmd, arg=0)

Perform the operation cmd on file descriptor fd (file objects providing a fileno() method are accepted as well). The values used for cmd are operating system dependent, and are available as constants in the fcntl module, using the same names as used in the relevant C header files. The argument arg can either be an integer value, or a bytes object. With an integer value, the return value of this function is the integer return value of the C fcntl() call. When the argument is bytes it represents a binary structure, e.g. created by struct.pack(). The binary data is copied to a buffer whose address is passed to the C fcntl() call. The return value after a successful call is the contents of the buffer, converted to a bytes object. The length of the returned object will be the same as the length of the arg argument. This is limited to 1024 bytes. If the information returned in the buffer by the operating system is larger than 1024 bytes, this is most likely to result in a segmentation violation or a more subtle data corruption.

If the fcntl() fails, an OSError is raised.

fcntl.ioctl(fd, request, arg=0, mutate_flag=True)

This function is identical to the fcntl() function, except that the argument handling is even more complicated.

The request parameter is limited to values that can fit in 32-bits. Additional constants of interest for use as the request argument can be found in the termios module, under the same names as used in the relevant C header files.

The parameter arg can be one of an integer, an object supporting the read-only buffer interface (like bytes) or an object supporting the read-write buffer interface (like bytearray).

In all but the last case, behaviour is as for the fcntl() function.

If a mutable buffer is passed, then the behaviour is determined by the value of the mutate_flag parameter.

If it is false, the buffer’s mutability is ignored and behaviour is as for a read-only buffer, except that the 1024 byte limit mentioned above is avoided – so long as the buffer you pass is at least as long as what the operating system wants to put there, things should work.

If mutate_flag is true (the default), then the buffer is (in effect) passed to the underlying ioctl() system call, the latter’s return code is passed back to the calling Python, and the buffer’s new contents reflect the action of the ioctl(). This is a slight simplification, because if the supplied buffer is less than 1024 bytes long it is first copied into a static buffer 1024 bytes long which is then passed to ioctl() and copied back into the supplied buffer.

If the ioctl() fails, an OSError exception is raised.

Un exemple :

>>> import array, fcntl, struct, termios, os
>>> os.getpgrp()
13341
>>> struct.unpack('h', fcntl.ioctl(0, termios.TIOCGPGRP, "  "))[0]
13341
>>> buf = array.array('h', [0])
>>> fcntl.ioctl(0, termios.TIOCGPGRP, buf, 1)
0
>>> buf
array('h', [13341])

fcntl.flock(fd, operation)

Perform the lock operation operation on file descriptor fd (file objects providing a fileno() method are accepted as well). See the Unix manual flock(2) for details. (On some systems, this function is emulated using fcntl().)

If the flock() fails, an OSError exception is raised.

fcntl.lockf(fd, cmd, len=0, start=0, whence=0)

This is essentially a wrapper around the fcntl() locking calls. fd is the file descriptor of the file to lock or unlock, and cmd is one of the following values:

LOCK_UN – unlock

LOCK_SH – acquire a shared lock

LOCK_EX – acquire an exclusive lock

When cmd is LOCK_SH or LOCK_EX, it can also be bitwise ORed with LOCK_NB to avoid blocking on lock acquisition. If LOCK_NB is used and the lock cannot be acquired, an OSError will be raised and the exception will have an errno attribute set to EACCES or EAGAIN (depending on the operating system; for portability, check for both values). On at least some systems, LOCK_EX can only be used if the file descriptor refers to a file opened for writing.

len is the number of bytes to lock, start is the byte offset at which the lock starts, relative to whence, and whence is as with io.IOBase.seek(), specifically:

0 – relative to the start of the file (os.SEEK_SET)

1 – relative to the current buffer position (os.SEEK_CUR)

2 – relative to the end of the file (os.SEEK_END)

The default for start is 0, which means to start at the beginning of the file. The default for len is 0 which means to lock to the end of the file. The default for whence is also 0.

Examples (all on a SVR4 compliant system):

import struct, fcntl, os

f = open(...)
rv = fcntl.fcntl(f, fcntl.F_SETFL, os.O_NDELAY)

lockdata = struct.pack('hhllhh', fcntl.F_WRLCK, 0, 0, 0, 0, 0)
rv = fcntl.fcntl(f, fcntl.F_SETLKW, lockdata)

Note that in the first example the return value variable rv will hold an integer value; in the second example it will hold a bytes object. The structure lay-out for the lockdata variable is system dependent — therefore using the flock() call may be better.

Voir aussi

Module os

If the locking flags O_SHLOCK and O_EXLOCK are present in the os module (on BSD only), the os.open() function provides an alternative to the lockf() and flock() functions.

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35.10. pipes — Interface au pipelines shell

Code source : Lib/pipes.py [https://github.com/python/cpython/tree/3.6/Lib/pipes.py]

Le module pipes définit une classe permettant d’abstraire le concept de pipeline — une séquence de convertisseurs d’un fichier vers un autre.

Du fait que le module utilise les lignes de commandes /bin/sh, un shell POSIX ou compatible est requis pour os.system() et os.popen().

Le module pipes définit la classe suivante :

class pipes.Template

Une abstraction d’un pipeline.

Exemple :

>>> import pipes
>>> t = pipes.Template()
>>> t.append('tr a-z A-Z', '--')
>>> f = t.open('pipefile', 'w')
>>> f.write('hello world')
>>> f.close()
>>> open('pipefile').read()
'HELLO WORLD'

35.10.1. L’Objet Template

Les méthodes de l’objet Template :

Template.reset()

Réinitialise un modèle de pipeline à son état initial.

Template.clone()

Renvoie un nouveau modèle de pipeline, équivalent.

Template.debug(flag)

Si flag est vrai, active le débogage. Sinon, le désactive. Quand le débogage est actif, les commandes à exécuter seront affichée et le shell est pourvu de la commande set -x afin d’être plus verbeux.

Template.append(cmd, kind)

Ajoute une nouvelle action à la fin. La variable cmd doit être une commande bourne shell valide. La variable kind est composée de deux lettres.

La première lettre peut soit être '-' (qui signifie que la commande lit sa sortie standard), soit 'f' (qui signifie que la commande lit un fichier donné par la ligne de commande), soit '.' (qui signifie que la commande ne lit pas d’entrée, et donc doit être la première.)

De même, la seconde lettre peut soit être '-' (qui signifie que la commande écrit sur la sortie standard), soit 'f' (qui signifie que la commande écrit sur un fichier donné par la ligne de commande), soit '.' (qui signifie que la commande n’écrit rien, et donc doit être la dernière.)

Template.prepend(cmd, kind)

Ajoute une nouvelle action au début. Voir append() pour plus d’explications sur les arguments.

Template.open(file, mode)

Renvoie un objet file-like, ouvert à file, mais permettant d’écrire vers le pipeline ou de lire depuis celui-ci. À noter que seulement un des deux (“r” ou “w”) peut être donné.

Template.copy(infile, outfile)

Copie infile vers outfile au travers du pipe.

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35.11. resource — Resource usage information

This module provides basic mechanisms for measuring and controlling system resources utilized by a program.

Symbolic constants are used to specify particular system resources and to request usage information about either the current process or its children.

An OSError is raised on syscall failure.

exception resource.error

A deprecated alias of OSError.

Modifié dans la version 3.3: Following PEP 3151 [https://www.python.org/dev/peps/pep-3151], this class was made an alias of OSError.

35.11.1. Resource Limits

Resources usage can be limited using the setrlimit() function described below. Each resource is controlled by a pair of limits: a soft limit and a hard limit. The soft limit is the current limit, and may be lowered or raised by a process over time. The soft limit can never exceed the hard limit. The hard limit can be lowered to any value greater than the soft limit, but not raised. (Only processes with the effective UID of the super-user can raise a hard limit.)

The specific resources that can be limited are system dependent. They are described in the getrlimit(2) man page. The resources listed below are supported when the underlying operating system supports them; resources which cannot be checked or controlled by the operating system are not defined in this module for those platforms.

resource.RLIM_INFINITY

Constant used to represent the limit for an unlimited resource.

resource.getrlimit(resource)

Returns a tuple (soft, hard) with the current soft and hard limits of resource. Raises ValueError if an invalid resource is specified, or error if the underlying system call fails unexpectedly.

resource.setrlimit(resource, limits)

Sets new limits of consumption of resource. The limits argument must be a tuple (soft, hard) of two integers describing the new limits. A value of RLIM_INFINITY can be used to request a limit that is unlimited.

Raises ValueError if an invalid resource is specified, if the new soft limit exceeds the hard limit, or if a process tries to raise its hard limit. Specifying a limit of RLIM_INFINITY when the hard or system limit for that resource is not unlimited will result in a ValueError. A process with the effective UID of super-user can request any valid limit value, including unlimited, but ValueError will still be raised if the requested limit exceeds the system imposed limit.

setrlimit may also raise error if the underlying system call fails.

resource.prlimit(pid, resource[, limits])

Combines setrlimit() and getrlimit() in one function and supports to get and set the resources limits of an arbitrary process. If pid is 0, then the call applies to the current process. resource and limits have the same meaning as in setrlimit(), except that limits is optional.

When limits is not given the function returns the resource limit of the process pid. When limits is given the resource limit of the process is set and the former resource limit is returned.

Raises ProcessLookupError when pid can’t be found and PermissionError when the user doesn’t have CAP_SYS_RESOURCE for the process.

Availability: Linux 2.6.36 or later with glibc 2.13 or later

Nouveau dans la version 3.4.

These symbols define resources whose consumption can be controlled using the setrlimit() and getrlimit() functions described below. The values of these symbols are exactly the constants used by C programs.

The Unix man page for getrlimit(2) lists the available resources. Note that not all systems use the same symbol or same value to denote the same resource. This module does not attempt to mask platform differences — symbols not defined for a platform will not be available from this module on that platform.

resource.RLIMIT_CORE

The maximum size (in bytes) of a core file that the current process can create. This may result in the creation of a partial core file if a larger core would be required to contain the entire process image.

resource.RLIMIT_CPU

The maximum amount of processor time (in seconds) that a process can use. If this limit is exceeded, a SIGXCPU signal is sent to the process. (See the signal module documentation for information about how to catch this signal and do something useful, e.g. flush open files to disk.)

resource.RLIMIT_FSIZE

The maximum size of a file which the process may create.

resource.RLIMIT_DATA

The maximum size (in bytes) of the process’s heap.

resource.RLIMIT_STACK

The maximum size (in bytes) of the call stack for the current process. This only affects the stack of the main thread in a multi-threaded process.

resource.RLIMIT_RSS

The maximum resident set size that should be made available to the process.

resource.RLIMIT_NPROC

The maximum number of processes the current process may create.

resource.RLIMIT_NOFILE

The maximum number of open file descriptors for the current process.

resource.RLIMIT_OFILE

The BSD name for RLIMIT_NOFILE.

resource.RLIMIT_MEMLOCK

The maximum address space which may be locked in memory.

resource.RLIMIT_VMEM

The largest area of mapped memory which the process may occupy.

resource.RLIMIT_AS

The maximum area (in bytes) of address space which may be taken by the process.

resource.RLIMIT_MSGQUEUE

The number of bytes that can be allocated for POSIX message queues.

Availability: Linux 2.6.8 or later.

Nouveau dans la version 3.4.

resource.RLIMIT_NICE

The ceiling for the process’s nice level (calculated as 20 - rlim_cur).

Availability: Linux 2.6.12 or later.

Nouveau dans la version 3.4.

resource.RLIMIT_RTPRIO

The ceiling of the real-time priority.

Availability: Linux 2.6.12 or later.

Nouveau dans la version 3.4.

resource.RLIMIT_RTTIME

The time limit (in microseconds) on CPU time that a process can spend under real-time scheduling without making a blocking syscall.

Availability: Linux 2.6.25 or later.

Nouveau dans la version 3.4.

resource.RLIMIT_SIGPENDING

The number of signals which the process may queue.

Availability: Linux 2.6.8 or later.

Nouveau dans la version 3.4.

resource.RLIMIT_SBSIZE

The maximum size (in bytes) of socket buffer usage for this user. This limits the amount of network memory, and hence the amount of mbufs, that this user may hold at any time.

Availability: FreeBSD 9 or later.

Nouveau dans la version 3.4.

resource.RLIMIT_SWAP

The maximum size (in bytes) of the swap space that may be reserved or used by all of this user id’s processes. This limit is enforced only if bit 1 of the vm.overcommit sysctl is set. Please see tuning(7) for a complete description of this sysctl.

Availability: FreeBSD 9 or later.

Nouveau dans la version 3.4.

resource.RLIMIT_NPTS

The maximum number of pseudo-terminals created by this user id.

Availability: FreeBSD 9 or later.

Nouveau dans la version 3.4.

35.11.2. Resource Usage

These functions are used to retrieve resource usage information:

resource.getrusage(who)

This function returns an object that describes the resources consumed by either the current process or its children, as specified by the who parameter. The who parameter should be specified using one of the RUSAGE_* constants described below.

The fields of the return value each describe how a particular system resource has been used, e.g. amount of time spent running is user mode or number of times the process was swapped out of main memory. Some values are dependent on the clock tick internal, e.g. the amount of memory the process is using.

For backward compatibility, the return value is also accessible as a tuple of 16 elements.

The fields ru_utime and ru_stime of the return value are floating point values representing the amount of time spent executing in user mode and the amount of time spent executing in system mode, respectively. The remaining values are integers. Consult the getrusage(2) man page for detailed information about these values. A brief summary is presented here:

Index

Field

Resource

0

ru_utime

time in user mode (float)

1

ru_stime

time in system mode (float)

2

ru_maxrss

maximum resident set size

3

ru_ixrss

shared memory size

4

ru_idrss

unshared memory size

5

ru_isrss

unshared stack size

6

ru_minflt

page faults not requiring I/O

7

ru_majflt

page faults requiring I/O

8

ru_nswap

number of swap outs

9

ru_inblock

block input operations

10

ru_oublock

block output operations

11

ru_msgsnd

messages sent

12

ru_msgrcv

messages received

13

ru_nsignals

signals received

14

ru_nvcsw

voluntary context switches

15

ru_nivcsw

involuntary context switches

This function will raise a ValueError if an invalid who parameter is specified. It may also raise error exception in unusual circumstances.

resource.getpagesize()

Returns the number of bytes in a system page. (This need not be the same as the hardware page size.)

The following RUSAGE_* symbols are passed to the getrusage() function to specify which processes information should be provided for.

resource.RUSAGE_SELF

Pass to getrusage() to request resources consumed by the calling process, which is the sum of resources used by all threads in the process.

resource.RUSAGE_CHILDREN

Pass to getrusage() to request resources consumed by child processes of the calling process which have been terminated and waited for.

resource.RUSAGE_BOTH

Pass to getrusage() to request resources consumed by both the current process and child processes. May not be available on all systems.

resource.RUSAGE_THREAD

Pass to getrusage() to request resources consumed by the current thread. May not be available on all systems.

Nouveau dans la version 3.2.

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35.12. nis — Interface à Sun’s NIS (pages jaunes)

Le module nis est une simple abstraction de la librairie NIS, utile pour l’administration centralisée de plusieurs hôtes.

Du fait que NIS existe seulement sur les systèmes Unix, ce module est seulement disponible pour Unix.

Le module nis définit les instructions suivantes :

nis.match(key, mapname, domain=default_domain)

Renvoie la valeur correspondante à key dans carte mapname, ou lève une erreur (nis.error) s’il n’y en a pas. Toutes les deux doivent être des chaînes, key doit être une chaîne ASCII. La valeur renvoyée est un dictionnaire arbitraire d’octets (pourrait contenir NULL et autres joyeusetés).

Notez que mapname est vérifié la première fois si c’est un alias d’un autre nom.

L’argument domain permet de passer outre le domaine NIS utilisé pour les recherches. Lorsqu’il n’est pas spécifié, recherche est dans le domaine NIS défaut.

nis.cat(mapname, domain=default_domain)

Renvoie un dictionnaire qui associe key à value tel que match(key, mapname)==value. Notez que les clés comme les valeurs peuvent contenir des séquences arbitraires d’octets.

Notez que mapname est vérifié la première fois si c’est un alias d’un autre nom.

L’argument domain permet de passer outre le domaine NIS utilisé pour les recherches. Lorsqu’il n’est pas spécifié, recherche est dans le domaine NIS défaut.

nis.maps(domain=default_domain)

Renvoie la liste de toutes les correspondances valides.

L’argument domain permet de passer outre le domaine NIS utilisé pour les recherches. Lorsqu’il n’est pas spécifié, recherche est dans le domaine NIS défaut.

nis.get_default_domain()

Renvoie le domaine NIS par défaut du système.

Le module nis définit les exceptions suivantes :

exception nis.error

Une erreur apparaît quand une fonction NIS renvoie un code d’erreur.

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35.13. syslog — Unix syslog library routines

This module provides an interface to the Unix syslog library routines. Refer to the Unix manual pages for a detailed description of the syslog facility.

This module wraps the system syslog family of routines. A pure Python library that can speak to a syslog server is available in the logging.handlers module as SysLogHandler.

Le module définit les fonctions suivantes :

syslog.syslog(message)

syslog.syslog(priority, message)

Send the string message to the system logger. A trailing newline is added if necessary. Each message is tagged with a priority composed of a facility and a level. The optional priority argument, which defaults to LOG_INFO, determines the message priority. If the facility is not encoded in priority using logical-or (LOG_INFO | LOG_USER), the value given in the openlog() call is used.

If openlog() has not been called prior to the call to syslog(), openlog() will be called with no arguments.

syslog.openlog([ident[, logoption[, facility]]])

Logging options of subsequent syslog() calls can be set by calling openlog(). syslog() will call openlog() with no arguments if the log is not currently open.

The optional ident keyword argument is a string which is prepended to every message, and defaults to sys.argv[0] with leading path components stripped. The optional logoption keyword argument (default is 0) is a bit field – see below for possible values to combine. The optional facility keyword argument (default is LOG_USER) sets the default facility for messages which do not have a facility explicitly encoded.

Modifié dans la version 3.2: In previous versions, keyword arguments were not allowed, and ident was required. The default for ident was dependent on the system libraries, and often was python instead of the name of the python program file.

syslog.closelog()

Reset the syslog module values and call the system library closelog().

This causes the module to behave as it does when initially imported. For example, openlog() will be called on the first syslog() call (if openlog() hasn’t already been called), and ident and other openlog() parameters are reset to defaults.

syslog.setlogmask(maskpri)

Set the priority mask to maskpri and return the previous mask value. Calls to syslog() with a priority level not set in maskpri are ignored. The default is to log all priorities. The function LOG_MASK(pri) calculates the mask for the individual priority pri. The function LOG_UPTO(pri) calculates the mask for all priorities up to and including pri.

The module defines the following constants:

Priority levels (high to low):

LOG_EMERG, LOG_ALERT, LOG_CRIT, LOG_ERR, LOG_WARNING, LOG_NOTICE, LOG_INFO, LOG_DEBUG.

Facilities:

LOG_KERN, LOG_USER, LOG_MAIL, LOG_DAEMON, LOG_AUTH, LOG_LPR, LOG_NEWS, LOG_UUCP, LOG_CRON, LOG_SYSLOG, LOG_LOCAL0 to LOG_LOCAL7, and, if defined in <syslog.h>, LOG_AUTHPRIV.

Log options:

LOG_PID, LOG_CONS, LOG_NDELAY, and, if defined in <syslog.h>, LOG_ODELAY, LOG_NOWAIT, and LOG_PERROR.

35.13.1. Exemples

35.13.1.1. Simple example

A simple set of examples:

import syslog

syslog.syslog('Processing started')
if error:
    syslog.syslog(syslog.LOG_ERR, 'Processing started')

An example of setting some log options, these would include the process ID in logged messages, and write the messages to the destination facility used for mail logging:

syslog.openlog(logoption=syslog.LOG_PID, facility=syslog.LOG_MAIL)
syslog.syslog('E-mail processing initiated...')

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36. Modules remplacés

Les modules documentés ici sont obsolètes et ne sont gardés que pour la rétro-compatibilité. Ils ont été remplacés par d’autres modules.

36.1. optparse — Parser for command line options

36.1.1. Background

36.1.1.1. Terminology

36.1.1.2. What are options for?

36.1.1.3. What are positional arguments for?

36.1.2. Tutoriel

36.1.2.1. Understanding option actions

36.1.2.2. The store action

36.1.2.3. Handling boolean (flag) options

36.1.2.4. Other actions

36.1.2.5. Valeurs par défaut

36.1.2.6. Generating help

36.1.2.6.1. Grouping Options

36.1.2.7. Printing a version string

36.1.2.8. How optparse handles errors

36.1.2.9. Putting it all together

36.1.3. Reference Guide

36.1.3.1. Creating the parser

36.1.3.2. Populating the parser

36.1.3.3. Defining options

36.1.3.4. Option attributes

36.1.3.5. Standard option actions

36.1.3.6. Standard option types

36.1.3.7. Analyse des arguments

36.1.3.8. Querying and manipulating your option parser

36.1.3.9. Conflicts between options

36.1.3.10. Nettoyage

36.1.3.11. Other methods

36.1.4. Option Callbacks

36.1.4.1. Defining a callback option

36.1.4.2. How callbacks are called

36.1.4.3. Raising errors in a callback

36.1.4.4. Callback example 1: trivial callback

36.1.4.5. Callback example 2: check option order

36.1.4.6. Callback example 3: check option order (generalized)

36.1.4.7. Callback example 4: check arbitrary condition

36.1.4.8. Callback example 5: fixed arguments

36.1.4.9. Callback example 6: variable arguments

36.1.5. Extending optparse

36.1.5.1. Adding new types

36.1.5.2. Adding new actions

36.2. imp — Access the import internals

36.2.1. Exemples

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36.1. optparse — Parser for command line options

Code source : Lib/optparse.py [https://github.com/python/cpython/tree/3.6/Lib/optparse.py]

Obsolète depuis la version 3.2: The optparse module is deprecated and will not be developed further; development will continue with the argparse module.

optparse is a more convenient, flexible, and powerful library for parsing command-line options than the old getopt module. optparse uses a more declarative style of command-line parsing: you create an instance of OptionParser, populate it with options, and parse the command line. optparse allows users to specify options in the conventional GNU/POSIX syntax, and additionally generates usage and help messages for you.

Here’s an example of using optparse in a simple script:

from optparse import OptionParser
...
parser = OptionParser()
parser.add_option("-f", "--file", dest="filename",
                  help="write report to FILE", metavar="FILE")
parser.add_option("-q", "--quiet",
                  action="store_false", dest="verbose", default=True,
                  help="don't print status messages to stdout")

(options, args) = parser.parse_args()

With these few lines of code, users of your script can now do the « usual thing » on the command-line, for example:

<yourscript> --file=outfile -q

As it parses the command line, optparse sets attributes of the options object returned by parse_args() based on user-supplied command-line values. When parse_args() returns from parsing this command line, options.filename will be "outfile" and options.verbose will be False. optparse supports both long and short options, allows short options to be merged together, and allows options to be associated with their arguments in a variety of ways. Thus, the following command lines are all equivalent to the above example:

<yourscript> -f outfile --quiet
<yourscript> --quiet --file outfile
<yourscript> -q -foutfile
<yourscript> -qfoutfile

Additionally, users can run one of

<yourscript> -h
<yourscript> --help

and optparse will print out a brief summary of your script’s options:

Usage: <yourscript> [options]

Options:
  -h, --help            show this help message and exit
  -f FILE, --file=FILE  write report to FILE
  -q, --quiet           don't print status messages to stdout

where the value of yourscript is determined at runtime (normally from sys.argv[0]).

36.1.1. Background

optparse was explicitly designed to encourage the creation of programs with straightforward, conventional command-line interfaces. To that end, it supports only the most common command-line syntax and semantics conventionally used under Unix. If you are unfamiliar with these conventions, read this section to acquaint yourself with them.

36.1.1.1. Terminology

argument

a string entered on the command-line, and passed by the shell to execl() or execv(). In Python, arguments are elements of sys.argv[1:] (sys.argv[0] is the name of the program being executed). Unix shells also use the term « word ».

It is occasionally desirable to substitute an argument list other than sys.argv[1:], so you should read « argument » as « an element of sys.argv[1:], or of some other list provided as a substitute for sys.argv[1:] ».

option

an argument used to supply extra information to guide or customize the execution of a program. There are many different syntaxes for options; the traditional Unix syntax is a hyphen (« -« ) followed by a single letter, e.g. -x or -F. Also, traditional Unix syntax allows multiple options to be merged into a single argument, e.g. -x -F is equivalent to -xF. The GNU project introduced -- followed by a series of hyphen-separated words, e.g. --file or --dry-run. These are the only two option syntaxes provided by optparse.

Some other option syntaxes that the world has seen include:

a hyphen followed by a few letters, e.g. -pf (this is not the same as multiple options merged into a single argument)

a hyphen followed by a whole word, e.g. -file (this is technically equivalent to the previous syntax, but they aren’t usually seen in the same program)

a plus sign followed by a single letter, or a few letters, or a word, e.g. +f, +rgb

a slash followed by a letter, or a few letters, or a word, e.g. /f, /file

These option syntaxes are not supported by optparse, and they never will be. This is deliberate: the first three are non-standard on any environment, and the last only makes sense if you’re exclusively targeting VMS, MS-DOS, and/or Windows.

option argument

an argument that follows an option, is closely associated with that option, and is consumed from the argument list when that option is. With optparse, option arguments may either be in a separate argument from their option:

-f foo
--file foo

or included in the same argument:

-ffoo
--file=foo

Typically, a given option either takes an argument or it doesn’t. Lots of people want an « optional option arguments » feature, meaning that some options will take an argument if they see it, and won’t if they don’t. This is somewhat controversial, because it makes parsing ambiguous: if -a takes an optional argument and -b is another option entirely, how do we interpret -ab? Because of this ambiguity, optparse does not support this feature.

argument positionnel

something leftover in the argument list after options have been parsed, i.e. after options and their arguments have been parsed and removed from the argument list.

required option

an option that must be supplied on the command-line; note that the phrase « required option » is self-contradictory in English. optparse doesn’t prevent you from implementing required options, but doesn’t give you much help at it either.

For example, consider this hypothetical command-line:

prog -v --report report.txt foo bar

-v and --report are both options. Assuming that --report takes one argument, report.txt is an option argument. foo and bar are positional arguments.

36.1.1.2. What are options for?

Options are used to provide extra information to tune or customize the execution of a program. In case it wasn’t clear, options are usually optional. A program should be able to run just fine with no options whatsoever. (Pick a random program from the Unix or GNU toolsets. Can it run without any options at all and still make sense? The main exceptions are find, tar, and dd—all of which are mutant oddballs that have been rightly criticized for their non-standard syntax and confusing interfaces.)

Lots of people want their programs to have « required options ». Think about it. If it’s required, then it’s not optional! If there is a piece of information that your program absolutely requires in order to run successfully, that’s what positional arguments are for.

As an example of good command-line interface design, consider the humble cp utility, for copying files. It doesn’t make much sense to try to copy files without supplying a destination and at least one source. Hence, cp fails if you run it with no arguments. However, it has a flexible, useful syntax that does not require any options at all:

cp SOURCE DEST
cp SOURCE ... DEST-DIR

You can get pretty far with just that. Most cp implementations provide a bunch of options to tweak exactly how the files are copied: you can preserve mode and modification time, avoid following symlinks, ask before clobbering existing files, etc. But none of this distracts from the core mission of cp, which is to copy either one file to another, or several files to another directory.

36.1.1.3. What are positional arguments for?

Positional arguments are for those pieces of information that your program absolutely, positively requires to run.

A good user interface should have as few absolute requirements as possible. If your program requires 17 distinct pieces of information in order to run successfully, it doesn’t much matter how you get that information from the user—most people will give up and walk away before they successfully run the program. This applies whether the user interface is a command-line, a configuration file, or a GUI: if you make that many demands on your users, most of them will simply give up.

In short, try to minimize the amount of information that users are absolutely required to supply—use sensible defaults whenever possible. Of course, you also want to make your programs reasonably flexible. That’s what options are for. Again, it doesn’t matter if they are entries in a config file, widgets in the « Preferences » dialog of a GUI, or command-line options—the more options you implement, the more flexible your program is, and the more complicated its implementation becomes. Too much flexibility has drawbacks as well, of course; too many options can overwhelm users and make your code much harder to maintain.

36.1.2. Tutoriel

While optparse is quite flexible and powerful, it’s also straightforward to use in most cases. This section covers the code patterns that are common to any optparse-based program.

First, you need to import the OptionParser class; then, early in the main program, create an OptionParser instance:

from optparse import OptionParser
...
parser = OptionParser()

Then you can start defining options. The basic syntax is:

parser.add_option(opt_str, ...,
                  attr=value, ...)

Each option has one or more option strings, such as -f or --file, and several option attributes that tell optparse what to expect and what to do when it encounters that option on the command line.

Typically, each option will have one short option string and one long option string, e.g.:

parser.add_option("-f", "--file", ...)

You’re free to define as many short option strings and as many long option strings as you like (including zero), as long as there is at least one option string overall.

The option strings passed to OptionParser.add_option() are effectively labels for the option defined by that call. For brevity, we will frequently refer to encountering an option on the command line; in reality, optparse encounters option strings and looks up options from them.

Once all of your options are defined, instruct optparse to parse your program’s command line:

(options, args) = parser.parse_args()

(If you like, you can pass a custom argument list to parse_args(), but that’s rarely necessary: by default it uses sys.argv[1:].)

parse_args() returns two values:

options, an object containing values for all of your options—e.g. if --file takes a single string argument, then options.file will be the filename supplied by the user, or None if the user did not supply that option

args, the list of positional arguments leftover after parsing options

This tutorial section only covers the four most important option attributes: action, type, dest (destination), and help. Of these, action is the most fundamental.

36.1.2.1. Understanding option actions

Actions tell optparse what to do when it encounters an option on the command line. There is a fixed set of actions hard-coded into optparse; adding new actions is an advanced topic covered in section Extending optparse. Most actions tell optparse to store a value in some variable—for example, take a string from the command line and store it in an attribute of options.

If you don’t specify an option action, optparse defaults to store.

36.1.2.2. The store action

The most common option action is store, which tells optparse to take the next argument (or the remainder of the current argument), ensure that it is of the correct type, and store it to your chosen destination.

Par exemple :

parser.add_option("-f", "--file",
                  action="store", type="string", dest="filename")

Now let’s make up a fake command line and ask optparse to parse it:

args = ["-f", "foo.txt"]
(options, args) = parser.parse_args(args)

When optparse sees the option string -f, it consumes the next argument, foo.txt, and stores it in options.filename. So, after this call to parse_args(), options.filename is "foo.txt".

Some other option types supported by optparse are int and float. Here’s an option that expects an integer argument:

parser.add_option("-n", type="int", dest="num")

Note that this option has no long option string, which is perfectly acceptable. Also, there’s no explicit action, since the default is store.

Let’s parse another fake command-line. This time, we’ll jam the option argument right up against the option: since -n42 (one argument) is equivalent to -n 42 (two arguments), the code

(options, args) = parser.parse_args(["-n42"])
print(options.num)

affichera 42.

If you don’t specify a type, optparse assumes string. Combined with the fact that the default action is store, that means our first example can be a lot shorter:

parser.add_option("-f", "--file", dest="filename")

If you don’t supply a destination, optparse figures out a sensible default from the option strings: if the first long option string is --foo-bar, then the default destination is foo_bar. If there are no long option strings, optparse looks at the first short option string: the default destination for -f is f.

optparse also includes the built-in complex type. Adding types is covered in section Extending optparse.

36.1.2.3. Handling boolean (flag) options

Flag options—set a variable to true or false when a particular option is seen—are quite common. optparse supports them with two separate actions, store_true and store_false. For example, you might have a verbose flag that is turned on with -v and off with -q:

parser.add_option("-v", action="store_true", dest="verbose")
parser.add_option("-q", action="store_false", dest="verbose")

Here we have two different options with the same destination, which is perfectly OK. (It just means you have to be a bit careful when setting default values—see below.)

When optparse encounters -v on the command line, it sets options.verbose to True; when it encounters -q, options.verbose is set to False.

36.1.2.4. Other actions

Some other actions supported by optparse are:

"store_const"

store a constant value

"append"

append this option’s argument to a list

"count"

increment a counter by one

"callback"

call a specified function

These are covered in section Reference Guide, Reference Guide and section Option Callbacks.

36.1.2.5. Valeurs par défaut

All of the above examples involve setting some variable (the « destination ») when certain command-line options are seen. What happens if those options are never seen? Since we didn’t supply any defaults, they are all set to None. This is usually fine, but sometimes you want more control. optparse lets you supply a default value for each destination, which is assigned before the command line is parsed.

First, consider the verbose/quiet example. If we want optparse to set verbose to True unless -q is seen, then we can do this:

parser.add_option("-v", action="store_true", dest="verbose", default=True)
parser.add_option("-q", action="store_false", dest="verbose")

Since default values apply to the destination rather than to any particular option, and these two options happen to have the same destination, this is exactly equivalent:

parser.add_option("-v", action="store_true", dest="verbose")
parser.add_option("-q", action="store_false", dest="verbose", default=True)

Consider this:

parser.add_option("-v", action="store_true", dest="verbose", default=False)
parser.add_option("-q", action="store_false", dest="verbose", default=True)

Again, the default value for verbose will be True: the last default value supplied for any particular destination is the one that counts.

A clearer way to specify default values is the set_defaults() method of OptionParser, which you can call at any time before calling parse_args():

parser.set_defaults(verbose=True)
parser.add_option(...)
(options, args) = parser.parse_args()

As before, the last value specified for a given option destination is the one that counts. For clarity, try to use one method or the other of setting default values, not both.

36.1.2.6. Generating help

optparse’s ability to generate help and usage text automatically is useful for creating user-friendly command-line interfaces. All you have to do is supply a help value for each option, and optionally a short usage message for your whole program. Here’s an OptionParser populated with user-friendly (documented) options:

usage = "usage: %prog [options] arg1 arg2"
parser = OptionParser(usage=usage)
parser.add_option("-v", "--verbose",
                  action="store_true", dest="verbose", default=True,
                  help="make lots of noise [default]")
parser.add_option("-q", "--quiet",
                  action="store_false", dest="verbose",
                  help="be vewwy quiet (I'm hunting wabbits)")
parser.add_option("-f", "--filename",
                  metavar="FILE", help="write output to FILE")
parser.add_option("-m", "--mode",
                  default="intermediate",
                  help="interaction mode: novice, intermediate, "
                       "or expert [default: %default]")

If optparse encounters either -h or --help on the command-line, or if you just call parser.print_help(), it prints the following to standard output:

Usage: <yourscript> [options] arg1 arg2

Options:
  -h, --help            show this help message and exit
  -v, --verbose         make lots of noise [default]
  -q, --quiet           be vewwy quiet (I'm hunting wabbits)
  -f FILE, --filename=FILE
                        write output to FILE
  -m MODE, --mode=MODE  interaction mode: novice, intermediate, or
                        expert [default: intermediate]

(If the help output is triggered by a help option, optparse exits after printing the help text.)

There’s a lot going on here to help optparse generate the best possible help message:

the script defines its own usage message:

usage = "usage: %prog [options] arg1 arg2"

optparse expands %prog in the usage string to the name of the current program, i.e. os.path.basename(sys.argv[0]). The expanded string is then printed before the detailed option help.

If you don’t supply a usage string, optparse uses a bland but sensible default: "Usage: %prog [options]", which is fine if your script doesn’t take any positional arguments.

every option defines a help string, and doesn’t worry about line-wrapping—optparse takes care of wrapping lines and making the help output look good.

options that take a value indicate this fact in their automatically-generated help message, e.g. for the « mode » option:

-m MODE, --mode=MODE

Here, « MODE » is called the meta-variable: it stands for the argument that the user is expected to supply to -m/--mode. By default, optparse converts the destination variable name to uppercase and uses that for the meta-variable. Sometimes, that’s not what you want—for example, the --filename option explicitly sets metavar="FILE", resulting in this automatically-generated option description:

-f FILE, --filename=FILE

This is important for more than just saving space, though: the manually written help text uses the meta-variable FILE to clue the user in that there’s a connection between the semi-formal syntax -f FILE and the informal semantic description « write output to FILE ». This is a simple but effective way to make your help text a lot clearer and more useful for end users.

options that have a default value can include %default in the help string—optparse will replace it with str() of the option’s default value. If an option has no default value (or the default value is None), %default expands to none.

36.1.2.6.1. Grouping Options

When dealing with many options, it is convenient to group these options for better help output. An OptionParser can contain several option groups, each of which can contain several options.

An option group is obtained using the class OptionGroup:

class optparse.OptionGroup(parser, title, description=None)

where

parser is the OptionParser instance the group will be inserted in to

title is the group title

description, optional, is a long description of the group

OptionGroup inherits from OptionContainer (like OptionParser) and so the add_option() method can be used to add an option to the group.

Once all the options are declared, using the OptionParser method add_option_group() the group is added to the previously defined parser.

Continuing with the parser defined in the previous section, adding an OptionGroup to a parser is easy:

group = OptionGroup(parser, "Dangerous Options",
                    "Caution: use these options at your own risk.  "
                    "It is believed that some of them bite.")
group.add_option("-g", action="store_true", help="Group option.")
parser.add_option_group(group)

This would result in the following help output:

Usage: <yourscript> [options] arg1 arg2

Options:
  -h, --help            show this help message and exit
  -v, --verbose         make lots of noise [default]
  -q, --quiet           be vewwy quiet (I'm hunting wabbits)
  -f FILE, --filename=FILE
                        write output to FILE
  -m MODE, --mode=MODE  interaction mode: novice, intermediate, or
                        expert [default: intermediate]

  Dangerous Options:
    Caution: use these options at your own risk.  It is believed that some
    of them bite.

    -g                  Group option.

A bit more complete example might involve using more than one group: still extending the previous example:

group = OptionGroup(parser, "Dangerous Options",
                    "Caution: use these options at your own risk.  "
                    "It is believed that some of them bite.")
group.add_option("-g", action="store_true", help="Group option.")
parser.add_option_group(group)

group = OptionGroup(parser, "Debug Options")
group.add_option("-d", "--debug", action="store_true",
                 help="Print debug information")
group.add_option("-s", "--sql", action="store_true",
                 help="Print all SQL statements executed")
group.add_option("-e", action="store_true", help="Print every action done")
parser.add_option_group(group)

that results in the following output:

Usage: <yourscript> [options] arg1 arg2

Options:
  -h, --help            show this help message and exit
  -v, --verbose         make lots of noise [default]
  -q, --quiet           be vewwy quiet (I'm hunting wabbits)
  -f FILE, --filename=FILE
                        write output to FILE
  -m MODE, --mode=MODE  interaction mode: novice, intermediate, or expert
                        [default: intermediate]

  Dangerous Options:
    Caution: use these options at your own risk.  It is believed that some
    of them bite.

    -g                  Group option.

  Debug Options:
    -d, --debug         Print debug information
    -s, --sql           Print all SQL statements executed
    -e                  Print every action done

Another interesting method, in particular when working programmatically with option groups is:

OptionParser.get_option_group(opt_str)

Return the OptionGroup to which the short or long option string opt_str (e.g. '-o' or '--option') belongs. If there’s no such OptionGroup, return None.

36.1.2.7. Printing a version string

Similar to the brief usage string, optparse can also print a version string for your program. You have to supply the string as the version argument to OptionParser:

parser = OptionParser(usage="%prog [-f] [-q]", version="%prog 1.0")

%prog is expanded just like it is in usage. Apart from that, version can contain anything you like. When you supply it, optparse automatically adds a --version option to your parser. If it encounters this option on the command line, it expands your version string (by replacing %prog), prints it to stdout, and exits.

For example, if your script is called /usr/bin/foo:

$ /usr/bin/foo --version
foo 1.0

The following two methods can be used to print and get the version string:

OptionParser.print_version(file=None)

Print the version message for the current program (self.version) to file (default stdout). As with print_usage(), any occurrence of %prog in self.version is replaced with the name of the current program. Does nothing if self.version is empty or undefined.

OptionParser.get_version()

Same as print_version() but returns the version string instead of printing it.

36.1.2.8. How optparse handles errors

There are two broad classes of errors that optparse has to worry about: programmer errors and user errors. Programmer errors are usually erroneous calls to OptionParser.add_option(), e.g. invalid option strings, unknown option attributes, missing option attributes, etc. These are dealt with in the usual way: raise an exception (either optparse.OptionError or TypeError) and let the program crash.

Handling user errors is much more important, since they are guaranteed to happen no matter how stable your code is. optparse can automatically detect some user errors, such as bad option arguments (passing -n 4x where -n takes an integer argument), missing arguments (-n at the end of the command line, where -n takes an argument of any type). Also, you can call OptionParser.error() to signal an application-defined error condition:

(options, args) = parser.parse_args()
...
if options.a and options.b:
    parser.error("options -a and -b are mutually exclusive")

In either case, optparse handles the error the same way: it prints the program’s usage message and an error message to standard error and exits with error status 2.

Consider the first example above, where the user passes 4x to an option that takes an integer:

$ /usr/bin/foo -n 4x
Usage: foo [options]

foo: error: option -n: invalid integer value: '4x'

Or, where the user fails to pass a value at all:

$ /usr/bin/foo -n
Usage: foo [options]

foo: error: -n option requires an argument

optparse-generated error messages take care always to mention the option involved in the error; be sure to do the same when calling OptionParser.error() from your application code.

If optparse’s default error-handling behaviour does not suit your needs, you’ll need to subclass OptionParser and override its exit() and/or error() methods.

36.1.2.9. Putting it all together

Here’s what optparse-based scripts usually look like:

from optparse import OptionParser
...
def main():
    usage = "usage: %prog [options] arg"
    parser = OptionParser(usage)
    parser.add_option("-f", "--file", dest="filename",
                      help="read data from FILENAME")
    parser.add_option("-v", "--verbose",
                      action="store_true", dest="verbose")
    parser.add_option("-q", "--quiet",
                      action="store_false", dest="verbose")
    ...
    (options, args) = parser.parse_args()
    if len(args) != 1:
        parser.error("incorrect number of arguments")
    if options.verbose:
        print("reading %s..." % options.filename)
    ...

if __name__ == "__main__":
    main()

36.1.3. Reference Guide

36.1.3.1. Creating the parser

The first step in using optparse is to create an OptionParser instance.

class optparse.OptionParser(...)

The OptionParser constructor has no required arguments, but a number of optional keyword arguments. You should always pass them as keyword arguments, i.e. do not rely on the order in which the arguments are declared.

usage (default: "%prog [options]")

The usage summary to print when your program is run incorrectly or with a help option. When optparse prints the usage string, it expands %prog to os.path.basename(sys.argv[0]) (or to prog if you passed that keyword argument). To suppress a usage message, pass the special value optparse.SUPPRESS_USAGE.

option_list (default: [])

A list of Option objects to populate the parser with. The options in option_list are added after any options in standard_option_list (a class attribute that may be set by OptionParser subclasses), but before any version or help options. Deprecated; use add_option() after creating the parser instead.

option_class (default: optparse.Option)

Class to use when adding options to the parser in add_option().

version (default: None)

A version string to print when the user supplies a version option. If you supply a true value for version, optparse automatically adds a version option with the single option string --version. The substring %prog is expanded the same as for usage.

conflict_handler (default: "error")

Specifies what to do when options with conflicting option strings are added to the parser; see section Conflicts between options.

description (default: None)

A paragraph of text giving a brief overview of your program. optparse reformats this paragraph to fit the current terminal width and prints it when the user requests help (after usage, but before the list of options).

formatter (default: a new IndentedHelpFormatter)

An instance of optparse.HelpFormatter that will be used for printing help text. optparse provides two concrete classes for this purpose: IndentedHelpFormatter and TitledHelpFormatter.

add_help_option (default: True)

If true, optparse will add a help option (with option strings -h and --help) to the parser.

prog

The string to use when expanding %prog in usage and version instead of os.path.basename(sys.argv[0]).

epilog (default: None)

A paragraph of help text to print after the option help.

36.1.3.2. Populating the parser

There are several ways to populate the parser with options. The preferred way is by using OptionParser.add_option(), as shown in section Tutoriel. add_option() can be called in one of two ways:

pass it an Option instance (as returned by make_option())

pass it any combination of positional and keyword arguments that are acceptable to make_option() (i.e., to the Option constructor), and it will create the Option instance for you

The other alternative is to pass a list of pre-constructed Option instances to the OptionParser constructor, as in:

option_list = [
    make_option("-f", "--filename",
                action="store", type="string", dest="filename"),
    make_option("-q", "--quiet",
                action="store_false", dest="verbose"),
    ]
parser = OptionParser(option_list=option_list)

(make_option() is a factory function for creating Option instances; currently it is an alias for the Option constructor. A future version of optparse may split Option into several classes, and make_option() will pick the right class to instantiate. Do not instantiate Option directly.)

36.1.3.3. Defining options

Each Option instance represents a set of synonymous command-line option strings, e.g. -f and --file. You can specify any number of short or long option strings, but you must specify at least one overall option string.

The canonical way to create an Option instance is with the add_option() method of OptionParser.

OptionParser.add_option(option)

OptionParser.add_option(*opt_str, attr=value, ...)

To define an option with only a short option string:

parser.add_option("-f", attr=value, ...)

And to define an option with only a long option string:

parser.add_option("--foo", attr=value, ...)

The keyword arguments define attributes of the new Option object. The most important option attribute is action, and it largely determines which other attributes are relevant or required. If you pass irrelevant option attributes, or fail to pass required ones, optparse raises an OptionError exception explaining your mistake.

An option’s action determines what optparse does when it encounters this option on the command-line. The standard option actions hard-coded into optparse are:

"store"

store this option’s argument (default)

"store_const"

store a constant value

"store_true"

store a true value

"store_false"

store a false value

"append"

append this option’s argument to a list

"append_const"

append a constant value to a list

"count"

increment a counter by one

"callback"

call a specified function

"help"

print a usage message including all options and the documentation for them

(If you don’t supply an action, the default is "store". For this action, you may also supply type and dest option attributes; see Standard option actions.)

As you can see, most actions involve storing or updating a value somewhere. optparse always creates a special object for this, conventionally called options (it happens to be an instance of optparse.Values). Option arguments (and various other values) are stored as attributes of this object, according to the dest (destination) option attribute.

For example, when you call

parser.parse_args()

one of the first things optparse does is create the options object:

options = Values()

If one of the options in this parser is defined with

parser.add_option("-f", "--file", action="store", type="string", dest="filename")

and the command-line being parsed includes any of the following:

-ffoo
-f foo
--file=foo
--file foo

then optparse, on seeing this option, will do the equivalent of

options.filename = "foo"

The type and dest option attributes are almost as important as action, but action is the only one that makes sense for all options.

36.1.3.4. Option attributes

The following option attributes may be passed as keyword arguments to OptionParser.add_option(). If you pass an option attribute that is not relevant to a particular option, or fail to pass a required option attribute, optparse raises OptionError.

Option.action

(default: "store")

Determines optparse’s behaviour when this option is seen on the command line; the available options are documented here.

Option.type

(default: "string")

The argument type expected by this option (e.g., "string" or "int"); the available option types are documented here.

Option.dest

(default: derived from option strings)

If the option’s action implies writing or modifying a value somewhere, this tells optparse where to write it: dest names an attribute of the options object that optparse builds as it parses the command line.

Option.default

The value to use for this option’s destination if the option is not seen on the command line. See also OptionParser.set_defaults().

Option.nargs

(default: 1)

How many arguments of type type should be consumed when this option is seen. If > 1, optparse will store a tuple of values to dest.

Option.const

For actions that store a constant value, the constant value to store.

Option.choices

For options of type "choice", the list of strings the user may choose from.

Option.callback

For options with action "callback", the callable to call when this option is seen. See section Option Callbacks for detail on the arguments passed to the callable.

Option.callback_args

Option.callback_kwargs

Additional positional and keyword arguments to pass to callback after the four standard callback arguments.

Option.help

Help text to print for this option when listing all available options after the user supplies a help option (such as --help). If no help text is supplied, the option will be listed without help text. To hide this option, use the special value optparse.SUPPRESS_HELP.

Option.metavar

(default: derived from option strings)

Stand-in for the option argument(s) to use when printing help text. See section Tutoriel for an example.

36.1.3.5. Standard option actions

The various option actions all have slightly different requirements and effects. Most actions have several relevant option attributes which you may specify to guide optparse’s behaviour; a few have required attributes, which you must specify for any option using that action.

"store" [relevant: type, dest, nargs, choices]

The option must be followed by an argument, which is converted to a value according to type and stored in dest. If nargs > 1, multiple arguments will be consumed from the command line; all will be converted according to type and stored to dest as a tuple. See the Standard option types section.

If choices is supplied (a list or tuple of strings), the type defaults to "choice".

If type is not supplied, it defaults to "string".

If dest is not supplied, optparse derives a destination from the first long option string (e.g., --foo-bar implies foo_bar). If there are no long option strings, optparse derives a destination from the first short option string (e.g., -f implies f).

Exemple :

parser.add_option("-f")
parser.add_option("-p", type="float", nargs=3, dest="point")

As it parses the command line

-f foo.txt -p 1 -3.5 4 -fbar.txt

optparse will set

options.f = "foo.txt"
options.point = (1.0, -3.5, 4.0)
options.f = "bar.txt"

"store_const" [required: const; relevant: dest]

The value const is stored in dest.

Exemple :

parser.add_option("-q", "--quiet",
                  action="store_const", const=0, dest="verbose")
parser.add_option("-v", "--verbose",
                  action="store_const", const=1, dest="verbose")
parser.add_option("--noisy",
                  action="store_const", const=2, dest="verbose")

If --noisy is seen, optparse will set

options.verbose = 2

"store_true" [relevant: dest]

A special case of "store_const" that stores a true value to dest.

"store_false" [relevant: dest]

Like "store_true", but stores a false value.

Exemple :

parser.add_option("--clobber", action="store_true", dest="clobber")
parser.add_option("--no-clobber", action="store_false", dest="clobber")

"append" [relevant: type, dest, nargs, choices]

The option must be followed by an argument, which is appended to the list in dest. If no default value for dest is supplied, an empty list is automatically created when optparse first encounters this option on the command-line. If nargs > 1, multiple arguments are consumed, and a tuple of length nargs is appended to dest.

The defaults for type and dest are the same as for the "store" action.

Exemple :

parser.add_option("-t", "--tracks", action="append", type="int")

If -t3 is seen on the command-line, optparse does the equivalent of:

options.tracks = []
options.tracks.append(int("3"))

If, a little later on, --tracks=4 is seen, it does:

options.tracks.append(int("4"))

The append action calls the append method on the current value of the option. This means that any default value specified must have an append method. It also means that if the default value is non-empty, the default elements will be present in the parsed value for the option, with any values from the command line appended after those default values:

>>> parser.add_option("--files", action="append", default=['~/.mypkg/defaults'])
>>> opts, args = parser.parse_args(['--files', 'overrides.mypkg'])
>>> opts.files
['~/.mypkg/defaults', 'overrides.mypkg']

"append_const" [required: const; relevant: dest]

Like "store_const", but the value const is appended to dest; as with "append", dest defaults to None, and an empty list is automatically created the first time the option is encountered.

"count" [relevant: dest]

Increment the integer stored at dest. If no default value is supplied, dest is set to zero before being incremented the first time.

Exemple :

parser.add_option("-v", action="count", dest="verbosity")

The first time -v is seen on the command line, optparse does the equivalent of:

options.verbosity = 0
options.verbosity += 1

Every subsequent occurrence of -v results in

options.verbosity += 1

"callback" [required: callback; relevant: type, nargs, callback_args, callback_kwargs]

Call the function specified by callback, which is called as

func(option, opt_str, value, parser, *args, **kwargs)

See section Option Callbacks for more detail.

"help"

Prints a complete help message for all the options in the current option parser. The help message is constructed from the usage string passed to OptionParser’s constructor and the help string passed to every option.

If no help string is supplied for an option, it will still be listed in the help message. To omit an option entirely, use the special value optparse.SUPPRESS_HELP.

optparse automatically adds a help option to all OptionParsers, so you do not normally need to create one.

Exemple :

from optparse import OptionParser, SUPPRESS_HELP

# usually, a help option is added automatically, but that can
# be suppressed using the add_help_option argument
parser = OptionParser(add_help_option=False)

parser.add_option("-h", "--help", action="help")
parser.add_option("-v", action="store_true", dest="verbose",
                  help="Be moderately verbose")
parser.add_option("--file", dest="filename",
                  help="Input file to read data from")
parser.add_option("--secret", help=SUPPRESS_HELP)

If optparse sees either -h or --help on the command line, it will print something like the following help message to stdout (assuming sys.argv[0] is "foo.py"):

Usage: foo.py [options]

Options:
  -h, --help        Show this help message and exit
  -v                Be moderately verbose
  --file=FILENAME   Input file to read data from

After printing the help message, optparse terminates your process with sys.exit(0).

"version"

Prints the version number supplied to the OptionParser to stdout and exits. The version number is actually formatted and printed by the print_version() method of OptionParser. Generally only relevant if the version argument is supplied to the OptionParser constructor. As with help options, you will rarely create version options, since optparse automatically adds them when needed.

36.1.3.6. Standard option types

optparse has five built-in option types: "string", "int", "choice", "float" and "complex". If you need to add new option types, see section Extending optparse.

Arguments to string options are not checked or converted in any way: the text on the command line is stored in the destination (or passed to the callback) as-is.

Integer arguments (type "int") are parsed as follows:

if the number starts with 0x, it is parsed as a hexadecimal number

if the number starts with 0, it is parsed as an octal number

if the number starts with 0b, it is parsed as a binary number

otherwise, the number is parsed as a decimal number

The conversion is done by calling int() with the appropriate base (2, 8, 10, or 16). If this fails, so will optparse, although with a more useful error message.

"float" and "complex" option arguments are converted directly with float() and complex(), with similar error-handling.

"choice" options are a subtype of "string" options. The choices option attribute (a sequence of strings) defines the set of allowed option arguments. optparse.check_choice() compares user-supplied option arguments against this master list and raises OptionValueError if an invalid string is given.

36.1.3.7. Analyse des arguments

The whole point of creating and populating an OptionParser is to call its parse_args() method:

(options, args) = parser.parse_args(args=None, values=None)

where the input parameters are

args

the list of arguments to process (default: sys.argv[1:])

values

an optparse.Values object to store option arguments in (default: a new instance of Values) – if you give an existing object, the option defaults will not be initialized on it

and the return values are

options

the same object that was passed in as values, or the optparse.Values instance created by optparse

args

the leftover positional arguments after all options have been processed

The most common usage is to supply neither keyword argument. If you supply values, it will be modified with repeated setattr() calls (roughly one for every option argument stored to an option destination) and returned by parse_args().

If parse_args() encounters any errors in the argument list, it calls the OptionParser’s error() method with an appropriate end-user error message. This ultimately terminates your process with an exit status of 2 (the traditional Unix exit status for command-line errors).

36.1.3.8. Querying and manipulating your option parser

The default behavior of the option parser can be customized slightly, and you can also poke around your option parser and see what’s there. OptionParser provides several methods to help you out:

OptionParser.disable_interspersed_args()

Set parsing to stop on the first non-option. For example, if -a and -b are both simple options that take no arguments, optparse normally accepts this syntax:

prog -a arg1 -b arg2

and treats it as equivalent to

prog -a -b arg1 arg2

To disable this feature, call disable_interspersed_args(). This restores traditional Unix syntax, where option parsing stops with the first non-option argument.

Use this if you have a command processor which runs another command which has options of its own and you want to make sure these options don’t get confused. For example, each command might have a different set of options.

OptionParser.enable_interspersed_args()

Set parsing to not stop on the first non-option, allowing interspersing switches with command arguments. This is the default behavior.

OptionParser.get_option(opt_str)

Returns the Option instance with the option string opt_str, or None if no options have that option string.

OptionParser.has_option(opt_str)

Return true if the OptionParser has an option with option string opt_str (e.g., -q or --verbose).

OptionParser.remove_option(opt_str)

If the OptionParser has an option corresponding to opt_str, that option is removed. If that option provided any other option strings, all of those option strings become invalid. If opt_str does not occur in any option belonging to this OptionParser, raises ValueError.

36.1.3.9. Conflicts between options

If you’re not careful, it’s easy to define options with conflicting option strings:

parser.add_option("-n", "--dry-run", ...)
...
parser.add_option("-n", "--noisy", ...)

(This is particularly true if you’ve defined your own OptionParser subclass with some standard options.)

Every time you add an option, optparse checks for conflicts with existing options. If it finds any, it invokes the current conflict-handling mechanism. You can set the conflict-handling mechanism either in the constructor:

parser = OptionParser(..., conflict_handler=handler)

or with a separate call:

parser.set_conflict_handler(handler)

The available conflict handlers are:

"error" (default)

assume option conflicts are a programming error and raise OptionConflictError

"resolve"

resolve option conflicts intelligently (see below)

As an example, let’s define an OptionParser that resolves conflicts intelligently and add conflicting options to it:

parser = OptionParser(conflict_handler="resolve")
parser.add_option("-n", "--dry-run", ..., help="do no harm")
parser.add_option("-n", "--noisy", ..., help="be noisy")

At this point, optparse detects that a previously-added option is already using the -n option string. Since conflict_handler is "resolve", it resolves the situation by removing -n from the earlier option’s list of option strings. Now --dry-run is the only way for the user to activate that option. If the user asks for help, the help message will reflect that:

Options:
  --dry-run     do no harm
  ...
  -n, --noisy   be noisy

It’s possible to whittle away the option strings for a previously-added option until there are none left, and the user has no way of invoking that option from the command-line. In that case, optparse removes that option completely, so it doesn’t show up in help text or anywhere else. Carrying on with our existing OptionParser:

parser.add_option("--dry-run", ..., help="new dry-run option")

At this point, the original -n/--dry-run option is no longer accessible, so optparse removes it, leaving this help text:

Options:
  ...
  -n, --noisy   be noisy
  --dry-run     new dry-run option

36.1.3.10. Nettoyage

OptionParser instances have several cyclic references. This should not be a problem for Python’s garbage collector, but you may wish to break the cyclic references explicitly by calling destroy() on your OptionParser once you are done with it. This is particularly useful in long-running applications where large object graphs are reachable from your OptionParser.

36.1.3.11. Other methods

OptionParser supports several other public methods:

OptionParser.set_usage(usage)

Set the usage string according to the rules described above for the usage constructor keyword argument. Passing None sets the default usage string; use optparse.SUPPRESS_USAGE to suppress a usage message.

OptionParser.print_usage(file=None)

Print the usage message for the current program (self.usage) to file (default stdout). Any occurrence of the string %prog in self.usage is replaced with the name of the current program. Does nothing if self.usage is empty or not defined.

OptionParser.get_usage()

Same as print_usage() but returns the usage string instead of printing it.

OptionParser.set_defaults(dest=value, ...)

Set default values for several option destinations at once. Using set_defaults() is the preferred way to set default values for options, since multiple options can share the same destination. For example, if several « mode » options all set the same destination, any one of them can set the default, and the last one wins:

parser.add_option("--advanced", action="store_const",
                  dest="mode", const="advanced",
                  default="novice")    # overridden below
parser.add_option("--novice", action="store_const",
                  dest="mode", const="novice",
                  default="advanced")  # overrides above setting

To avoid this confusion, use set_defaults():

parser.set_defaults(mode="advanced")
parser.add_option("--advanced", action="store_const",
                  dest="mode", const="advanced")
parser.add_option("--novice", action="store_const",
                  dest="mode", const="novice")

36.1.4. Option Callbacks

When optparse’s built-in actions and types aren’t quite enough for your needs, you have two choices: extend optparse or define a callback option. Extending optparse is more general, but overkill for a lot of simple cases. Quite often a simple callback is all you need.

There are two steps to defining a callback option:

define the option itself using the "callback" action

write the callback; this is a function (or method) that takes at least four arguments, as described below

36.1.4.1. Defining a callback option

As always, the easiest way to define a callback option is by using the OptionParser.add_option() method. Apart from action, the only option attribute you must specify is callback, the function to call:

parser.add_option("-c", action="callback", callback=my_callback)

callback is a function (or other callable object), so you must have already defined my_callback() when you create this callback option. In this simple case, optparse doesn’t even know if -c takes any arguments, which usually means that the option takes no arguments—the mere presence of -c on the command-line is all it needs to know. In some circumstances, though, you might want your callback to consume an arbitrary number of command-line arguments. This is where writing callbacks gets tricky; it’s covered later in this section.

optparse always passes four particular arguments to your callback, and it will only pass additional arguments if you specify them via callback_args and callback_kwargs. Thus, the minimal callback function signature is:

def my_callback(option, opt, value, parser):

The four arguments to a callback are described below.

There are several other option attributes that you can supply when you define a callback option:

type

has its usual meaning: as with the "store" or "append" actions, it instructs optparse to consume one argument and convert it to type. Rather than storing the converted value(s) anywhere, though, optparse passes it to your callback function.

nargs

also has its usual meaning: if it is supplied and > 1, optparse will consume nargs arguments, each of which must be convertible to type. It then passes a tuple of converted values to your callback.

callback_args

a tuple of extra positional arguments to pass to the callback

callback_kwargs

a dictionary of extra keyword arguments to pass to the callback

36.1.4.2. How callbacks are called

All callbacks are called as follows:

func(option, opt_str, value, parser, *args, **kwargs)

where

option

is the Option instance that’s calling the callback

opt_str

is the option string seen on the command-line that’s triggering the callback. (If an abbreviated long option was used, opt_str will be the full, canonical option string—e.g. if the user puts --foo on the command-line as an abbreviation for --foobar, then opt_str will be "--foobar".)

value

is the argument to this option seen on the command-line. optparse will only expect an argument if type is set; the type of value will be the type implied by the option’s type. If type for this option is None (no argument expected), then value will be None. If nargs > 1, value will be a tuple of values of the appropriate type.

parser

is the OptionParser instance driving the whole thing, mainly useful because you can access some other interesting data through its instance attributes:

parser.largs

the current list of leftover arguments, ie. arguments that have been consumed but are neither options nor option arguments. Feel free to modify parser.largs, e.g. by adding more arguments to it. (This list will become args, the second return value of parse_args().)

parser.rargs

the current list of remaining arguments, ie. with opt_str and value (if applicable) removed, and only the arguments following them still there. Feel free to modify parser.rargs, e.g. by consuming more arguments.

parser.values

the object where option values are by default stored (an instance of optparse.OptionValues). This lets callbacks use the same mechanism as the rest of optparse for storing option values; you don’t need to mess around with globals or closures. You can also access or modify the value(s) of any options already encountered on the command-line.

args

is a tuple of arbitrary positional arguments supplied via the callback_args option attribute.

kwargs

is a dictionary of arbitrary keyword arguments supplied via callback_kwargs.

36.1.4.3. Raising errors in a callback

The callback function should raise OptionValueError if there are any problems with the option or its argument(s). optparse catches this and terminates the program, printing the error message you supply to stderr. Your message should be clear, concise, accurate, and mention the option at fault. Otherwise, the user will have a hard time figuring out what they did wrong.

36.1.4.4. Callback example 1: trivial callback

Here’s an example of a callback option that takes no arguments, and simply records that the option was seen:

def record_foo_seen(option, opt_str, value, parser):
    parser.values.saw_foo = True

parser.add_option("--foo", action="callback", callback=record_foo_seen)

Of course, you could do that with the "store_true" action.

36.1.4.5. Callback example 2: check option order

Here’s a slightly more interesting example: record the fact that -a is seen, but blow up if it comes after -b in the command-line.

def check_order(option, opt_str, value, parser):
    if parser.values.b:
        raise OptionValueError("can't use -a after -b")
    parser.values.a = 1
...
parser.add_option("-a", action="callback", callback=check_order)
parser.add_option("-b", action="store_true", dest="b")

36.1.4.6. Callback example 3: check option order (generalized)

If you want to re-use this callback for several similar options (set a flag, but blow up if -b has already been seen), it needs a bit of work: the error message and the flag that it sets must be generalized.

def check_order(option, opt_str, value, parser):
    if parser.values.b:
        raise OptionValueError("can't use %s after -b" % opt_str)
    setattr(parser.values, option.dest, 1)
...
parser.add_option("-a", action="callback", callback=check_order, dest='a')
parser.add_option("-b", action="store_true", dest="b")
parser.add_option("-c", action="callback", callback=check_order, dest='c')

36.1.4.7. Callback example 4: check arbitrary condition

Of course, you could put any condition in there—you’re not limited to checking the values of already-defined options. For example, if you have options that should not be called when the moon is full, all you have to do is this:

def check_moon(option, opt_str, value, parser):
    if is_moon_full():
        raise OptionValueError("%s option invalid when moon is full"
                               % opt_str)
    setattr(parser.values, option.dest, 1)
...
parser.add_option("--foo",
                  action="callback", callback=check_moon, dest="foo")

(The definition of is_moon_full() is left as an exercise for the reader.)

36.1.4.8. Callback example 5: fixed arguments

Things get slightly more interesting when you define callback options that take a fixed number of arguments. Specifying that a callback option takes arguments is similar to defining a "store" or "append" option: if you define type, then the option takes one argument that must be convertible to that type; if you further define nargs, then the option takes nargs arguments.

Here’s an example that just emulates the standard "store" action:

def store_value(option, opt_str, value, parser):
    setattr(parser.values, option.dest, value)
...
parser.add_option("--foo",
                  action="callback", callback=store_value,
                  type="int", nargs=3, dest="foo")

Note that optparse takes care of consuming 3 arguments and converting them to integers for you; all you have to do is store them. (Or whatever; obviously you don’t need a callback for this example.)

36.1.4.9. Callback example 6: variable arguments

Things get hairy when you want an option to take a variable number of arguments. For this case, you must write a callback, as optparse doesn’t provide any built-in capabilities for it. And you have to deal with certain intricacies of conventional Unix command-line parsing that optparse normally handles for you. In particular, callbacks should implement the conventional rules for bare -- and - arguments:

either -- or - can be option arguments

bare -- (if not the argument to some option): halt command-line processing and discard the --

bare - (if not the argument to some option): halt command-line processing but keep the - (append it to parser.largs)

If you want an option that takes a variable number of arguments, there are several subtle, tricky issues to worry about. The exact implementation you choose will be based on which trade-offs you’re willing to make for your application (which is why optparse doesn’t support this sort of thing directly).

Nevertheless, here’s a stab at a callback for an option with variable arguments:

def vararg_callback(option, opt_str, value, parser):
    assert value is None
    value = []

    def floatable(str):
        try:
            float(str)
            return True
        except ValueError:
            return False

    for arg in parser.rargs:
        # stop on --foo like options
        if arg[:2] == "--" and len(arg) > 2:
            break
        # stop on -a, but not on -3 or -3.0
        if arg[:1] == "-" and len(arg) > 1 and not floatable(arg):
            break
        value.append(arg)

    del parser.rargs[:len(value)]
    setattr(parser.values, option.dest, value)

...
parser.add_option("-c", "--callback", dest="vararg_attr",
                  action="callback", callback=vararg_callback)

36.1.5. Extending optparse

Since the two major controlling factors in how optparse interprets command-line options are the action and type of each option, the most likely direction of extension is to add new actions and new types.

36.1.5.1. Adding new types

To add new types, you need to define your own subclass of optparse’s Option class. This class has a couple of attributes that define optparse’s types: TYPES and TYPE_CHECKER.

Option.TYPES

A tuple of type names; in your subclass, simply define a new tuple TYPES that builds on the standard one.

Option.TYPE_CHECKER

A dictionary mapping type names to type-checking functions. A type-checking function has the following signature:

def check_mytype(option, opt, value)

where option is an Option instance, opt is an option string (e.g., -f), and value is the string from the command line that must be checked and converted to your desired type. check_mytype() should return an object of the hypothetical type mytype. The value returned by a type-checking function will wind up in the OptionValues instance returned by OptionParser.parse_args(), or be passed to a callback as the value parameter.

Your type-checking function should raise OptionValueError if it encounters any problems. OptionValueError takes a single string argument, which is passed as-is to OptionParser’s error() method, which in turn prepends the program name and the string "error:" and prints everything to stderr before terminating the process.

Here’s a silly example that demonstrates adding a "complex" option type to parse Python-style complex numbers on the command line. (This is even sillier than it used to be, because optparse 1.3 added built-in support for complex numbers, but never mind.)

First, the necessary imports:

from copy import copy
from optparse import Option, OptionValueError

You need to define your type-checker first, since it’s referred to later (in the TYPE_CHECKER class attribute of your Option subclass):

def check_complex(option, opt, value):
    try:
        return complex(value)
    except ValueError:
        raise OptionValueError(
            "option %s: invalid complex value: %r" % (opt, value))

Finally, the Option subclass:

class MyOption (Option):
    TYPES = Option.TYPES + ("complex",)
    TYPE_CHECKER = copy(Option.TYPE_CHECKER)
    TYPE_CHECKER["complex"] = check_complex

(If we didn’t make a copy() of Option.TYPE_CHECKER, we would end up modifying the TYPE_CHECKER attribute of optparse’s Option class. This being Python, nothing stops you from doing that except good manners and common sense.)

That’s it! Now you can write a script that uses the new option type just like any other optparse-based script, except you have to instruct your OptionParser to use MyOption instead of Option:

parser = OptionParser(option_class=MyOption)
parser.add_option("-c", type="complex")

Alternately, you can build your own option list and pass it to OptionParser; if you don’t use add_option() in the above way, you don’t need to tell OptionParser which option class to use:

option_list = [MyOption("-c", action="store", type="complex", dest="c")]
parser = OptionParser(option_list=option_list)

36.1.5.2. Adding new actions

Adding new actions is a bit trickier, because you have to understand that optparse has a couple of classifications for actions:

« store » actions

actions that result in optparse storing a value to an attribute of the current OptionValues instance; these options require a dest attribute to be supplied to the Option constructor.

« typed » actions

actions that take a value from the command line and expect it to be of a certain type; or rather, a string that can be converted to a certain type. These options require a type attribute to the Option constructor.

These are overlapping sets: some default « store » actions are "store", "store_const", "append", and "count", while the default « typed » actions are "store", "append", and "callback".

When you add an action, you need to categorize it by listing it in at least one of the following class attributes of Option (all are lists of strings):

Option.ACTIONS

All actions must be listed in ACTIONS.

Option.STORE_ACTIONS

« store » actions are additionally listed here.

Option.TYPED_ACTIONS

« typed » actions are additionally listed here.

Option.ALWAYS_TYPED_ACTIONS

Actions that always take a type (i.e. whose options always take a value) are additionally listed here. The only effect of this is that optparse assigns the default type, "string", to options with no explicit type whose action is listed in ALWAYS_TYPED_ACTIONS.

In order to actually implement your new action, you must override Option’s take_action() method and add a case that recognizes your action.

For example, let’s add an "extend" action. This is similar to the standard "append" action, but instead of taking a single value from the command-line and appending it to an existing list, "extend" will take multiple values in a single comma-delimited string, and extend an existing list with them. That is, if --names is an "extend" option of type "string", the command line

--names=foo,bar --names blah --names ding,dong

would result in a list

["foo", "bar", "blah", "ding", "dong"]

Again we define a subclass of Option:

class MyOption(Option):

    ACTIONS = Option.ACTIONS + ("extend",)
    STORE_ACTIONS = Option.STORE_ACTIONS + ("extend",)
    TYPED_ACTIONS = Option.TYPED_ACTIONS + ("extend",)
    ALWAYS_TYPED_ACTIONS = Option.ALWAYS_TYPED_ACTIONS + ("extend",)

    def take_action(self, action, dest, opt, value, values, parser):
        if action == "extend":
            lvalue = value.split(",")
            values.ensure_value(dest, []).extend(lvalue)
        else:
            Option.take_action(
                self, action, dest, opt, value, values, parser)

Features of note:

"extend" both expects a value on the command-line and stores that value somewhere, so it goes in both STORE_ACTIONS and TYPED_ACTIONS.

to ensure that optparse assigns the default type of "string" to "extend" actions, we put the "extend" action in ALWAYS_TYPED_ACTIONS as well.

MyOption.take_action() implements just this one new action, and passes control back to Option.take_action() for the standard optparse actions.

values is an instance of the optparse_parser.Values class, which provides the very useful ensure_value() method. ensure_value() is essentially getattr() with a safety valve; it is called as

values.ensure_value(attr, value)

If the attr attribute of values doesn’t exist or is None, then ensure_value() first sets it to value, and then returns “value. This is very handy for actions like "extend", "append", and "count", all of which accumulate data in a variable and expect that variable to be of a certain type (a list for the first two, an integer for the latter). Using ensure_value() means that scripts using your action don’t have to worry about setting a default value for the option destinations in question; they can just leave the default as None and ensure_value() will take care of getting it right when it’s needed.

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36.2. imp — Access the import internals

Source code: Lib/imp.py [https://github.com/python/cpython/tree/3.6/Lib/imp.py]

Obsolète depuis la version 3.4: The imp package is pending deprecation in favor of importlib.

This module provides an interface to the mechanisms used to implement the import statement. It defines the following constants and functions:

imp.get_magic()

Return the magic string value used to recognize byte-compiled code files (.pyc files). (This value may be different for each Python version.)

Obsolète depuis la version 3.4: Use importlib.util.MAGIC_NUMBER instead.

imp.get_suffixes()

Return a list of 3-element tuples, each describing a particular type of module. Each triple has the form (suffix, mode, type), where suffix is a string to be appended to the module name to form the filename to search for, mode is the mode string to pass to the built-in open() function to open the file (this can be 'r' for text files or 'rb' for binary files), and type is the file type, which has one of the values PY_SOURCE, PY_COMPILED, or C_EXTENSION, described below.

Obsolète depuis la version 3.3: Use the constants defined on importlib.machinery instead.

imp.find_module(name[, path])

Try to find the module name. If path is omitted or None, the list of directory names given by sys.path is searched, but first a few special places are searched: the function tries to find a built-in module with the given name (C_BUILTIN), then a frozen module (PY_FROZEN), and on some systems some other places are looked in as well (on Windows, it looks in the registry which may point to a specific file).

Otherwise, path must be a list of directory names; each directory is searched for files with any of the suffixes returned by get_suffixes() above. Invalid names in the list are silently ignored (but all list items must be strings).

If search is successful, the return value is a 3-element tuple (file, pathname, description):

file is an open file object positioned at the beginning, pathname is the pathname of the file found, and description is a 3-element tuple as contained in the list returned by get_suffixes() describing the kind of module found.

If the module does not live in a file, the returned file is None, pathname is the empty string, and the description tuple contains empty strings for its suffix and mode; the module type is indicated as given in parentheses above. If the search is unsuccessful, ImportError is raised. Other exceptions indicate problems with the arguments or environment.

If the module is a package, file is None, pathname is the package path and the last item in the description tuple is PKG_DIRECTORY.

This function does not handle hierarchical module names (names containing dots). In order to find P.M, that is, submodule M of package P, use find_module() and load_module() to find and load package P, and then use find_module() with the path argument set to P.__path__. When P itself has a dotted name, apply this recipe recursively.

Obsolète depuis la version 3.3: Use importlib.util.find_spec() instead unless Python 3.3 compatibility is required, in which case use importlib.find_loader(). For example usage of the former case, see the Exemples section of the importlib documentation.

imp.load_module(name, file, pathname, description)

Load a module that was previously found by find_module() (or by an otherwise conducted search yielding compatible results). This function does more than importing the module: if the module was already imported, it will reload the module! The name argument indicates the full module name (including the package name, if this is a submodule of a package). The file argument is an open file, and pathname is the corresponding file name; these can be None and '', respectively, when the module is a package or not being loaded from a file. The description argument is a tuple, as would be returned by get_suffixes(), describing what kind of module must be loaded.

If the load is successful, the return value is the module object; otherwise, an exception (usually ImportError) is raised.

Important: the caller is responsible for closing the file argument, if it was not None, even when an exception is raised. This is best done using a try … finally statement.

Obsolète depuis la version 3.3: If previously used in conjunction with imp.find_module() then consider using importlib.import_module(), otherwise use the loader returned by the replacement you chose for imp.find_module(). If you called imp.load_module() and related functions directly with file path arguments then use a combination of importlib.util.spec_from_file_location() and importlib.util.module_from_spec(). See the Exemples section of the importlib documentation for details of the various approaches.

imp.new_module(name)

Return a new empty module object called name. This object is not inserted in sys.modules.

Obsolète depuis la version 3.4: Use importlib.util.module_from_spec() instead.

imp.reload(module)

Reload a previously imported module. The argument must be a module object, so it must have been successfully imported before. This is useful if you have edited the module source file using an external editor and want to try out the new version without leaving the Python interpreter. The return value is the module object (the same as the module argument).

When reload(module) is executed:

Python modules” code is recompiled and the module-level code reexecuted, defining a new set of objects which are bound to names in the module’s dictionary. The init function of extension modules is not called a second time.

As with all other objects in Python the old objects are only reclaimed after their reference counts drop to zero.

The names in the module namespace are updated to point to any new or changed objects.

Other references to the old objects (such as names external to the module) are not rebound to refer to the new objects and must be updated in each namespace where they occur if that is desired.

There are a number of other caveats:

When a module is reloaded, its dictionary (containing the module’s global variables) is retained. Redefinitions of names will override the old definitions, so this is generally not a problem. If the new version of a module does not define a name that was defined by the old version, the old definition remains. This feature can be used to the module’s advantage if it maintains a global table or cache of objects — with a try statement it can test for the table’s presence and skip its initialization if desired:

try:
    cache
except NameError:
    cache = {}

It is legal though generally not very useful to reload built-in or dynamically loaded modules, except for sys, __main__ and builtins. In many cases, however, extension modules are not designed to be initialized more than once, and may fail in arbitrary ways when reloaded.

If a module imports objects from another module using from … import …, calling reload() for the other module does not redefine the objects imported from it — one way around this is to re-execute the from statement, another is to use import and qualified names (module.*name*) instead.

If a module instantiates instances of a class, reloading the module that defines the class does not affect the method definitions of the instances — they continue to use the old class definition. The same is true for derived classes.

Modifié dans la version 3.3: Relies on both __name__ and __loader__ being defined on the module being reloaded instead of just __name__.

Obsolète depuis la version 3.4: Use importlib.reload() instead.

The following functions are conveniences for handling PEP 3147 [https://www.python.org/dev/peps/pep-3147] byte-compiled file paths.

Nouveau dans la version 3.2.

imp.cache_from_source(path, debug_override=None)

Return the PEP 3147 [https://www.python.org/dev/peps/pep-3147] path to the byte-compiled file associated with the source path. For example, if path is /foo/bar/baz.py the return value would be /foo/bar/__pycache__/baz.cpython-32.pyc for Python 3.2. The cpython-32 string comes from the current magic tag (see get_tag(); if sys.implementation.cache_tag is not defined then NotImplementedError will be raised). By passing in True or False for debug_override you can override the system’s value for __debug__, leading to optimized bytecode.

path need not exist.

Modifié dans la version 3.3: If sys.implementation.cache_tag is None, then NotImplementedError is raised.

Obsolète depuis la version 3.4: Use importlib.util.cache_from_source() instead.

Modifié dans la version 3.5: The debug_override parameter no longer creates a .pyo file.

imp.source_from_cache(path)

Given the path to a PEP 3147 [https://www.python.org/dev/peps/pep-3147] file name, return the associated source code file path. For example, if path is /foo/bar/__pycache__/baz.cpython-32.pyc the returned path would be /foo/bar/baz.py. path need not exist, however if it does not conform to PEP 3147 [https://www.python.org/dev/peps/pep-3147] format, a ValueError is raised. If sys.implementation.cache_tag is not defined, NotImplementedError is raised.

Modifié dans la version 3.3: Raise NotImplementedError when sys.implementation.cache_tag is not defined.

Obsolète depuis la version 3.4: Use importlib.util.source_from_cache() instead.

imp.get_tag()

Return the PEP 3147 [https://www.python.org/dev/peps/pep-3147] magic tag string matching this version of Python’s magic number, as returned by get_magic().

Obsolète depuis la version 3.4: Use sys.implementation.cache_tag directly starting in Python 3.3.

The following functions help interact with the import system’s internal locking mechanism. Locking semantics of imports are an implementation detail which may vary from release to release. However, Python ensures that circular imports work without any deadlocks.

imp.lock_held()

Return True if the global import lock is currently held, else False. On platforms without threads, always return False.

On platforms with threads, a thread executing an import first holds a global import lock, then sets up a per-module lock for the rest of the import. This blocks other threads from importing the same module until the original import completes, preventing other threads from seeing incomplete module objects constructed by the original thread. An exception is made for circular imports, which by construction have to expose an incomplete module object at some point.

Modifié dans la version 3.3: The locking scheme has changed to per-module locks for the most part. A global import lock is kept for some critical tasks, such as initializing the per-module locks.

Obsolète depuis la version 3.4.

imp.acquire_lock()

Acquire the interpreter’s global import lock for the current thread. This lock should be used by import hooks to ensure thread-safety when importing modules.

Once a thread has acquired the import lock, the same thread may acquire it again without blocking; the thread must release it once for each time it has acquired it.

On platforms without threads, this function does nothing.

Modifié dans la version 3.3: The locking scheme has changed to per-module locks for the most part. A global import lock is kept for some critical tasks, such as initializing the per-module locks.

Obsolète depuis la version 3.4.

imp.release_lock()

Release the interpreter’s global import lock. On platforms without threads, this function does nothing.

Modifié dans la version 3.3: The locking scheme has changed to per-module locks for the most part. A global import lock is kept for some critical tasks, such as initializing the per-module locks.

Obsolète depuis la version 3.4.

The following constants with integer values, defined in this module, are used to indicate the search result of find_module().

imp.PY_SOURCE

The module was found as a source file.

Obsolète depuis la version 3.3.

imp.PY_COMPILED

The module was found as a compiled code object file.

Obsolète depuis la version 3.3.

imp.C_EXTENSION

The module was found as dynamically loadable shared library.

Obsolète depuis la version 3.3.

imp.PKG_DIRECTORY

The module was found as a package directory.

Obsolète depuis la version 3.3.

imp.C_BUILTIN

The module was found as a built-in module.

Obsolète depuis la version 3.3.

imp.PY_FROZEN

The module was found as a frozen module.

Obsolète depuis la version 3.3.

class imp.NullImporter(path_string)

The NullImporter type is a PEP 302 [https://www.python.org/dev/peps/pep-0302] import hook that handles non-directory path strings by failing to find any modules. Calling this type with an existing directory or empty string raises ImportError. Otherwise, a NullImporter instance is returned.

Instances have only one method:

find_module(fullname[, path])

This method always returns None, indicating that the requested module could not be found.

Modifié dans la version 3.3: None is inserted into sys.path_importer_cache instead of an instance of NullImporter.

Obsolète depuis la version 3.4: Insert None into sys.path_importer_cache instead.

36.2.1. Exemples

The following function emulates what was the standard import statement up to Python 1.4 (no hierarchical module names). (This implementation wouldn’t work in that version, since find_module() has been extended and load_module() has been added in 1.4.)

import imp
import sys

def __import__(name, globals=None, locals=None, fromlist=None):
    # Fast path: see if the module has already been imported.
    try:
        return sys.modules[name]
    except KeyError:
        pass

    # If any of the following calls raises an exception,
    # there's a problem we can't handle -- let the caller handle it.

    fp, pathname, description = imp.find_module(name)

    try:
        return imp.load_module(name, fp, pathname, description)
    finally:
        # Since we may exit via an exception, close fp explicitly.
        if fp:
            fp.close()

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37. Modules non Documentés

Voici un rapide survol des modules actuellement non documentés, mais qui devraient l’être. N’hésitez pas à contribuer à leur documentation ! (En anglais, par mail, à docs@python.org.)

L’idée de lister les modules à documenter vient d’un message de Fredrik Lundh. Depuis, le contenu de ce chapitre à pu être mis à jour.

37.1. Modules spécifiques à une plateforme

Ces modules sont utilisés pour implémenter le module os.path, et n’ont pas plus de documentation. Le besoin de les documenter ne se fait pas réellement sentir.

ntpath

— Implémentation de os.path pour les plateformes Win32 et Win64.

posixpath

— Implementation du module os.path pour les systèmes POSIX.

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Extension et intégration de l’interpréteur Python

Ce document décrit comment écrire des modules en C ou C++ pour étendre l’interpréteur Python à de nouveaux modules. En plus de définir de nouvelles fonctions, ces modules peuvent définir de nouveaux types d’objets ainsi que leur méthodes. Ce document explique aussi comment intégrer l’interpréteur Python dans une autre application, pour être utilisé comme langage d’extension. Enfin, ce document montre comment compiler et lier les modules d’extension pour qu’ils puissent être chargés dynamiquement (à l’exécution) dans l’interpréteur, si le système d’exploitation sous-jacent supporte cette fonctionnalité.

Ce document présuppose que vous avez des connaissances de base sur Python. Pour une introduction informelle du langage, voyez Le tutoriel Python. La référence du langage Python donne une définition plus formelle du langage. La bibliothèque standard documente les objets types, fonctions et modules existants (tous intégrés et écrits en Python) qui donnent au langage sa large gamme d’applications.

Pour une description dans sa totalité de l’API Python/C, voir Manuel de référence de l’API Python/C.

Les outils tiers recommandés

Ce guide ne couvre que les outils basiques permettant de créer des extensions fournies dans cette version de CPython. Les outils tiers tels que Cython [http://cython.org/], cffi [https://cffi.readthedocs.io], SWIG [http://www.swig.org] et Numba [https://numba.pydata.org/] offrent des approches plus simples et plus élaborées pour créer des extensions C et C++ pour Python.

Voir aussi

Guide d’utilisation de l’empaquetage Python : Extensions binaires [https://packaging.python.org/en/latest/extensions/]

Le guide d’utilisation de l’empaquetage Python ne couvre pas uniquement quelques outils disponibles qui simplifient la création d’extensions binaires, mais aborde aussi les différentes raisons pour lesquelles créer un module d’extension peut être souhaitable d’entrée.

Création d’extensions sans outils tiers

Cette section du guide couvre la création d’extensions C et C++ sans l’utilisation d’outils tiers. Cette section est destinée aux créateurs de ces outils, plus que d’être une méthode recommandée pour créer votre propre extension C.

1. Étendre Python en C ou C++

1.1. Un exemple simple

1.2. Intermezzo: Les erreurs et exceptions

1.3. Retour vers l’exemple

1.4. La fonction d’initialisation et le tableau des méthodes du module

1.5. Compilation and Linkage

1.6. Calling Python Functions from C

1.7. Extracting Parameters in Extension Functions

1.8. Keyword Parameters for Extension Functions

1.9. Building Arbitrary Values

1.10. Reference Counts

1.11. Writing Extensions in C++

1.12. Providing a C API for an Extension Module

2. Defining Extension Types: Tutorial

2.1. The Basics

2.2. Adding data and methods to the Basic example

2.3. Providing finer control over data attributes

2.4. Supporting cyclic garbage collection

2.5. Subclassing other types

3. Defining Extension Types: Assorted Topics

3.1. Finalization and De-allocation

3.2. Object Presentation

3.3. Attribute Management

3.4. Object Comparison

3.5. Abstract Protocol Support

3.6. Weak Reference Support

3.7. More Suggestions

4. Construire des extensions C et C++

4.1. Construire les extensions C et C++ avec distutils

4.2. Distribuer vos modules d’extension

5. Construire des extensions C et C++ sur Windows

5.1. Une approche « recette de cuisine »

5.2. Différences entre Unix et Windows

5.3. Utiliser les DLL en pratique

Intégrer l’interpréteur CPython dans une plus grande application

Parfois, plutôt que de créer une extension qui s’exécute dans l’interpréteur Python comme application principale, il est préférable d’intégrer l’interpréteur Python dans une application plus large. Cette section donne quelques informations nécessaires au succès de cette opération.

1. Intégrer Python dans une autre application

1.1. Intégration de très haut niveau

1.2. Au-delà de l’intégration de haut niveau : survol

1.3. Intégration pure

1.4. Étendre un Python intégré

1.5. Intégrer Python dans du C++

1.6. Compiler et Lier en environnement Unix ou similaire

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1. Étendre Python en C ou C++

Il est relativement facile d’ajouter de nouveaux modules à Python, si vous savez programmer en C. Ces <modules d’extension> extension modules permettent deux choses qui ne sont pas possible directement en Python: Elles peuvent définir de nouveaux types natifs, et peuvent appeler des fonctions de bibliothèques C ou appels systèmes.

Pour gérer les extensions, l’API Python (Application Programmer Interface) définit un ensemble de fonctions, macros et variables qui donnent accès à la plupart des aspects du système d’exécution de Python. L’API Python est incorporée dans un fichier source C en incluant l’en-tête "Python.h".

La compilation d’un module d’extension dépend de l’usage prévu et de la configuration du système, plus de détails peuvent être trouvés dans les chapitres suivants.

Note

L’interface d’extension C est spécifique à CPython, et les modules d’extension ne fonctionne pas sur les autres implémentations de Python. Dans de nombreux cas, il est possible d’éviter la rédaction des extensions en C et ainsi préserver la portabilité vers d’autres implémentations. Par exemple, si vous devez appeler une fonction de la bibliothèque C ou faire un appel système, vous devriez envisager d’utiliser le module ctypes ou d’utiliser la bibliothèque cffi [https://cffi.readthedocs.org] plutôt que d’écrire du code C sur mesure. Ces modules vous permettent d’écrire du code Python s’interfaçant avec le code C et sont plus portables entre les implémentations de Python que l’écriture et la compilation d’une d’extension C.

1.1. Un exemple simple

Créons un module d’extension appelé spam (la nourriture préférée de fans des Monty Python …) et disons que nous voulons créer une interface Python à la fonction de la bibliothèque C system() 1. Cette fonction prend une chaîne de caractères terminée par NULL comme argument et renvoie un entier. Nous voulons que cette fonction soit appelable à partir de Python comme suit :

>>> import spam
>>> status = spam.system("ls -l")

Commencez par créer un fichier spammodule.c. (Historiquement, si un module se nomme spam, le fichier C contenant son implémentation est appelé spammodule.c. Si le nom du module est très long, comme spammify, le nom du module peut être juste spammify.c.)

La première ligne de notre fichier peut être :

#include <Python.h>

qui récupère l’API Python (vous pouvez ajouter un commentaire décrivant le but du module et un avis de droit d’auteur si vous le souhaitez).

Note

Python pouvant définir certaines définitions pré-processeur qui affectent les têtes standard sur certains systèmes, vous devez inclure Python.h avant les en-têtes standards.

Tous les symboles exposés par Python.h sont préfixés de Py ou PY, sauf ceux qui sont définis dans les en-têtes standard. Pour le confort, et comme ils sont largement utilisés par l’interpréteur Python, "Python.h" inclut lui même quelques d’en-têtes standard : <stdio.h>, <string.h>, <errno.h> et <stdlib.h>. Si ce dernier n’existe pas sur votre système, il déclare les fonctions malloc(), free() et realloc() directement.

La prochaine chose que nous ajoutons à notre fichier de module est la fonction C qui sera appelée lorsque l’expression Python spam.system(chaîne) sera évaluée (nous verrons bientôt comment elle finit par être appelée) :

static PyObject *
spam_system(PyObject *self, PyObject *args)
{
    const char *command;
    int sts;

    if (!PyArg_ParseTuple(args, "s", &command))
        return NULL;
    sts = system(command);
    return PyLong_FromLong(sts);
}

Il y a une correspondance directe de la liste des arguments en Python (par exemple, l’expression "ls -l") aux arguments passés à la fonction C. La fonction C a toujours deux arguments, appelés par convention self et args.

Pour les fonctions au niveau du module, l’argument self pointe sur l’objet module, pour une méthode, il pointe sur l’instance de l’objet.

L’argument args sera un pointeur vers un tuple Python contenant les arguments. Chaque élément du tuple correspond à un argument dans la liste des arguments de l’appel. Les arguments sont des objets Python — afin d’en faire quelque chose dans notre fonction C, nous devons les convertir en valeurs C. La fonction PyArg_ParseTuple() de l’API Python vérifie les types des arguments et les convertit en valeurs C. Elle utilise un modèle sous forme de chaîne pour déterminer les types requis des arguments ainsi que les types de variables C dans lequel stocker les valeurs converties. Nous en verront plus, plus tard.

PyArg_ParseTuple() renvoie vrai (pas zéro) si tous les arguments ont le bon type et que ses composants ont été stockés dans les variables dont les adresses données. Il renvoie faux (zéro) si une liste d’arguments invalide a été passée. Dans ce dernier cas, elle lève également une exception appropriée de sorte que la fonction d’appel puisse renvoyer NULL immédiatement (comme nous l’avons vu dans l’exemple).

1.2. Intermezzo: Les erreurs et exceptions

Une convention primordiale imprégnant tout l’interpréteur Python est: quand une fonction échoue, elle devrait laisser une exception et renvoyer une valeur d’erreur (typiquement un pointeur NULL). Dans l’interpréteur, les exceptions sont stockés dans une variable globale statique, si cette variable est NULL, aucune exception n’a eu lieu. Une seconde variable globale stocke la « valeur associée » à l’exception (le deuxième argument de raise). Une troisième variable contient la trace de la pile dans le cas où l’erreur soit survenue dans du code Python. Ces trois variables sont les équivalents C du résultat de sys.exc_info() en Python (voir la section sur le module sys dans The Python Library Reference). Il est important de les connaître pour comprendre comment les erreurs sont propagées.

L’API Python définit un certain nombre de fonctions pour créer différents types d’exceptions.

La plus courante est PyErr_SetString(). Ses arguments sont un objet exception et une chaîne C. L’objet exception est généralement un objet prédéfini comme PyExc_ZeroDivisionError. La chaîne C indique la cause de l’erreur et est convertie en une chaîne Python puis stockée en tant que « valeur associée » à l’exception.

Une autre fonction utile est PyErr_SetFromErrno(), qui construit une exception à partir de la valeur de la variable globale errno. La fonction la plus générale est PyErr_SetObject(), qui prend deux arguments: l’exception et sa valeur associée. Vous ne devez pas appliquer Py_INCREF() aux objets transmis à ces fonctions.

Vous pouvez tester de manière non destructive si une exception a été levée avec PyErr_Occurred(). Cela renvoie l’objet exception actuel, ou NULL si aucune exception n’a eu lieu. Cependant, vous ne devriez pas avoir besoin d’appeler PyErr_Occurred() pour voir si une erreur est survenue durant l’appel d’une fonction, puisque vous devriez être en mesure de le déterminer à partir de la valeur de retour.

Lorsqu’une fonction f ayant appelé une autre fonction g détecte que cette dernière a échoué, f devrait donner une valeur d’erreur à son tour (habituellement NULL ou -1). f ne devrait pas appeler l’une des fonctions PyErr_*(), l’une d’elles ayant déjà été appelée par g. La fonction appelant f est alors censée renvoyer aussi un code d’erreur à celle qui l’a appelée, toujours sans utiliser PyErr_*(), et ainsi de suite. La cause la plus détaillée de l’erreur a déjà été signalée par la fonction l’ayant détectée en premier. Une fois l’erreur remontée à la boucle principale de l’interpréteur Python, il interrompt le code en cours d’exécution et essaie de trouver un gestionnaire d’exception spécifié par le développeur Python.

(Il y a des situations où un module peut effectivement donner un message d’erreur plus détaillé en appelant une autre fonction PyErr_*(), dans de tels cas, il est tout à fait possible de le faire. Cependant, ce n’est généralement pas nécessaire, et peut amener à perdre des informations sur la cause de l’erreur: la plupart des opérations peuvent échouer pour tout un tas de raisons).

Pour ignorer une exception qui aurait été émise lors d’un appel de fonction qui aurait échoué, l’exception doit être retirée explicitement en appelant PyErr_Clear(). Le seul cas pour lequel du code C devrait appeler PyErr_Clear() est lorsqu’il ne veut pas passer l’erreur à l’interpréteur, mais souhaite la gérer lui-même (peut-être en essayant quelque chose d’autre, ou en prétendant que rien n’a mal tourné).

Chaque échec de malloc() doit être transformé en une exception — l’appelant direct de malloc() (ou realloc()) doit appeler PyErr_NoMemory() et prendre l’initiative de renvoyer une valeur d’erreur. Toutes les fonctions construisant des objets (tels que PyLong_FromLong()) le font déjà, donc cette note ne concerne que ceux qui appellent malloc() directement.

Notez également que, à l’exception notable de PyArg_ParseTuple() et compagnie, les fonctions qui renvoient leur statut sous forme d’entier donnent généralement une valeur positive ou zéro en cas de succès et -1 en cas d’échec, comme les appels du système Unix.

Enfin, lorsque vous renvoyez un code d’erreur, n’oubliez pas faire un brin de nettoyage (en appelant Py_XDECREF() ou Py_DECREF() avec les objets que vous auriez déjà créés) !

Le choix de l’exception à lever vous incombe. Il existe des objets C correspondant à chaque exception Python, tel que PyExc_ZeroDivisionError, que vous pouvez utiliser directement. Choisissez judicieusement vos exceptions, typiquement n’utilisez pas PyExc_TypeError pour indiquer qu’un fichier n’a pas pu être ouvert (qui devrait probablement être PyExc_IOError). Si quelque chose ne va pas avec la liste des arguments, la fonction PyArg_ParseTuple() lève habituellement une exception PyExc_TypeError. Mais si vous avez un argument dont la valeur doit être dans un intervalle particulier ou qui doit satisfaire d’autres conditions, PyExc_ValueError sera plus appropriée.

Vous pouvez également créer une exception spécifique à votre module. Pour cela, déclarez simplement une variable statique au début de votre fichier :

static PyObject *SpamError;

et initialisez-la dans la fonction d’initialisation de votre module (PyInit_spam()) avec un objet exception (Passons, pour le moment, la vérification des codes d’erreur) :

PyMODINIT_FUNC
PyInit_spam(void)
{
    PyObject *m;

    m = PyModule_Create(&spammodule);
    if (m == NULL)
        return NULL;

    SpamError = PyErr_NewException("spam.error", NULL, NULL);
    Py_INCREF(SpamError);
    PyModule_AddObject(m, "error", SpamError);
    return m;
}

Notez que le nom de exception, côté Python, est spam.error. La fonction PyErr_NewException() peut créer une classe héritant de Exception (à moins qu’une autre classe ne lui soit fournie à la place de NULL), voir Exceptions natives.

Notez également que la variable SpamError contient une référence à la nouvelle classe créée; ceci est intentionnel! Comme l’exception peut être retirée du module par un code externe, une référence à la classe est nécessaire pour assurer qu’il ne sera pas rejeté, causant SpamError à devenir un pointeur défaillant. S’il devenait un pointeur défaillant, le C code qui lève l’exception peut engendrer un rejet central ou des effets secondaires inattendus.

Nous traiterons de l’utilisation de PyMODINIT_FUNC comme un type de retour de fonction plus tard dans cette section.

L’exception spam.error peut être levée dans votre module d’extension en appelant PyErr_SetString() comme montré ci-dessous :

static PyObject *
spam_system(PyObject *self, PyObject *args)
{
    const char *command;
    int sts;

    if (!PyArg_ParseTuple(args, "s", &command))
        return NULL;
    sts = system(command);
    if (sts < 0) {
        PyErr_SetString(SpamError, "System command failed");
        return NULL;
    }
    return PyLong_FromLong(sts);
}

1.3. Retour vers l’exemple

En revenant vers notre fonction exemple, vous devriez maintenant être capable de comprendre cette affirmation :

if (!PyArg_ParseTuple(args, "s", &command))
    return NULL;

Elle renvoie NULL (l’indicateur d’erreur pour les fonctions renvoyant des pointeurs d’objet) si une erreur est détectée dans la liste des arguments,se fiant à l’exception définie par PyArg_ParseTuple(). Autrement,la valeur chaîne de l’argument a été copiée dans la variable locale command. Il s’agit d’une attribution de pointeur et vous n’êtes pas supposés modifier la chaîne qui vers laquelle il pointe (donc en C Standard, la variable command doit être clairement déclarée comme const char *command).

La prochaine instruction est un appel à la fonction Unix system(), en lui passant la chaîne que nous venons d’obtenir à partir de PyArg_ParseTuple() :

sts = system(command);

Notre fonction spam.system() doit renvoyer la valeur de sts comme un objet Python. Cela est effectué par l’utilisation de la fonction PyLong_FromLong().

return PyLong_FromLong(sts);

Dans ce cas, elle renverra un objet entier. (Oui, même les entiers sont des objets dans le tas en Python!)

Si vous avez une fonction C qui ne renvoie aucun argument utile (une fonction renvoyant void), la fonction Python correspondante doit renvoyer None. Vous aurez besoin de cette locution pour cela (qui est implémentée par la macro Py_RETURN_NONE) :

Py_INCREF(Py_None);
return Py_None;

Py_None est le nom C pour l’objet spécial Python None. C’est un authentique objet Python plutôt qu’un pointeur NULL, qui signifie qu’une erreur est survenue, dans la plupart des situations, comme nous l’avons vu.

1.4. La fonction d’initialisation et le tableau des méthodes du module

Nous avons promis de montrer comment spam_system() est appelée depuis les programmes Python. D’abord, nous avons besoin d’avoir son nom et son adresse dans un « tableau des méthodes » :

static PyMethodDef SpamMethods[] = {
    ...
    {"system",  spam_system, METH_VARARGS,
     "Execute a shell command."},
    ...
    {NULL, NULL, 0, NULL}        /* Sentinel */
};

Notez la troisième entrée (METH_VARARGS). C’est un indicateur du type de convention à utiliser pour la fonction C, à destination de l’interpréteur. Il doit valoir normalement METH_VARARGS ou METH_VARARGS | METH_KEYWORDS ; la valeur 0 indique qu’une variante obsolète de PyArg_ParseTuple() est utilisée.

Si seulement METH_VARARGS est utilisé, la fonction s’attend à ce que les paramètres Python soient passés comme un n-uplet que l’on peut analyser via PyArg_ParseTuple() ; des informations supplémentaires sont fournies plus bas.

Le bit METH_KEYWORDS peut être mis à un dans le troisième champ si des arguments par mot-clés doivent être passés à la fonction. Dans ce cas, la fonction C doit accepter un troisième paramètre PyObject * qui est un dictionnaire des mots-clés. Utilisez PyArg_ParseTupleAndKeywords() pour analyser les arguments d’une telle fonction.

Le tableau des méthodes doit être référencé dans la structure de définition du module :

static struct PyModuleDef spammodule = {
    PyModuleDef_HEAD_INIT,
    "spam",   /* name of module */
    spam_doc, /* module documentation, may be NULL */
    -1,       /* size of per-interpreter state of the module,
                 or -1 if the module keeps state in global variables. */
    SpamMethods
};

This structure, in turn, must be passed to the interpreter in the module’s initialization function. The initialization function must be named PyInit_name(), where name is the name of the module, and should be the only non-static item defined in the module file:

PyMODINIT_FUNC
PyInit_spam(void)
{
    return PyModule_Create(&spammodule);
}

Note that PyMODINIT_FUNC declares the function as PyObject * return type, declares any special linkage declarations required by the platform, and for C++ declares the function as extern "C".

When the Python program imports module spam for the first time, PyInit_spam() is called. (See below for comments about embedding Python.) It calls PyModule_Create(), which returns a module object, and inserts built-in function objects into the newly created module based upon the table (an array of PyMethodDef structures) found in the module definition. PyModule_Create() returns a pointer to the module object that it creates. It may abort with a fatal error for certain errors, or return NULL if the module could not be initialized satisfactorily. The init function must return the module object to its caller, so that it then gets inserted into sys.modules.

When embedding Python, the PyInit_spam() function is not called automatically unless there’s an entry in the PyImport_Inittab table. To add the module to the initialization table, use PyImport_AppendInittab(), optionally followed by an import of the module:

int
main(int argc, char *argv[])
{
    wchar_t *program = Py_DecodeLocale(argv[0], NULL);
    if (program == NULL) {
        fprintf(stderr, "Fatal error: cannot decode argv[0]\n");
        exit(1);
    }

    /* Add a built-in module, before Py_Initialize */
    PyImport_AppendInittab("spam", PyInit_spam);

    /* Pass argv[0] to the Python interpreter */
    Py_SetProgramName(program);

    /* Initialize the Python interpreter.  Required. */
    Py_Initialize();

    /* Optionally import the module; alternatively,
       import can be deferred until the embedded script
       imports it. */
    PyImport_ImportModule("spam");

    ...

    PyMem_RawFree(program);
    return 0;
}

Note

Removing entries from sys.modules or importing compiled modules into multiple interpreters within a process (or following a fork() without an intervening exec()) can create problems for some extension modules. Extension module authors should exercise caution when initializing internal data structures.

A more substantial example module is included in the Python source distribution as Modules/xxmodule.c. This file may be used as a template or simply read as an example.

Note

Unlike our spam example, xxmodule uses multi-phase initialization (new in Python 3.5), where a PyModuleDef structure is returned from PyInit_spam, and creation of the module is left to the import machinery. For details on multi-phase initialization, see PEP 489 [https://www.python.org/dev/peps/pep-0489].

1.5. Compilation and Linkage

There are two more things to do before you can use your new extension: compiling and linking it with the Python system. If you use dynamic loading, the details may depend on the style of dynamic loading your system uses; see the chapters about building extension modules (chapter Construire des extensions C et C++) and additional information that pertains only to building on Windows (chapter Construire des extensions C et C++ sur Windows) for more information about this.

If you can’t use dynamic loading, or if you want to make your module a permanent part of the Python interpreter, you will have to change the configuration setup and rebuild the interpreter. Luckily, this is very simple on Unix: just place your file (spammodule.c for example) in the Modules/ directory of an unpacked source distribution, add a line to the file Modules/Setup.local describing your file:

spam spammodule.o

and rebuild the interpreter by running make in the toplevel directory. You can also run make in the Modules/ subdirectory, but then you must first rebuild Makefile there by running “make Makefile”. (This is necessary each time you change the Setup file.)

If your module requires additional libraries to link with, these can be listed on the line in the configuration file as well, for instance:

spam spammodule.o -lX11

1.6. Calling Python Functions from C

So far we have concentrated on making C functions callable from Python. The reverse is also useful: calling Python functions from C. This is especially the case for libraries that support so-called « callback » functions. If a C interface makes use of callbacks, the equivalent Python often needs to provide a callback mechanism to the Python programmer; the implementation will require calling the Python callback functions from a C callback. Other uses are also imaginable.

Fortunately, the Python interpreter is easily called recursively, and there is a standard interface to call a Python function. (I won’t dwell on how to call the Python parser with a particular string as input — if you’re interested, have a look at the implementation of the -c command line option in Modules/main.c from the Python source code.)

Calling a Python function is easy. First, the Python program must somehow pass you the Python function object. You should provide a function (or some other interface) to do this. When this function is called, save a pointer to the Python function object (be careful to Py_INCREF() it!) in a global variable — or wherever you see fit. For example, the following function might be part of a module definition:

static PyObject *my_callback = NULL;

static PyObject *
my_set_callback(PyObject *dummy, PyObject *args)
{
    PyObject *result = NULL;
    PyObject *temp;

    if (PyArg_ParseTuple(args, "O:set_callback", &temp)) {
        if (!PyCallable_Check(temp)) {
            PyErr_SetString(PyExc_TypeError, "parameter must be callable");
            return NULL;
        }
        Py_XINCREF(temp);         /* Add a reference to new callback */
        Py_XDECREF(my_callback);  /* Dispose of previous callback */
        my_callback = temp;       /* Remember new callback */
        /* Boilerplate to return "None" */
        Py_INCREF(Py_None);
        result = Py_None;
    }
    return result;
}

This function must be registered with the interpreter using the METH_VARARGS flag; this is described in section La fonction d’initialisation et le tableau des méthodes du module. The PyArg_ParseTuple() function and its arguments are documented in section Extracting Parameters in Extension Functions.

The macros Py_XINCREF() and Py_XDECREF() increment/decrement the reference count of an object and are safe in the presence of NULL pointers (but note that temp will not be NULL in this context). More info on them in section Reference Counts.

Later, when it is time to call the function, you call the C function PyObject_CallObject(). This function has two arguments, both pointers to arbitrary Python objects: the Python function, and the argument list. The argument list must always be a tuple object, whose length is the number of arguments. To call the Python function with no arguments, pass in NULL, or an empty tuple; to call it with one argument, pass a singleton tuple. Py_BuildValue() returns a tuple when its format string consists of zero or more format codes between parentheses. For example:

int arg;
PyObject *arglist;
PyObject *result;
...
arg = 123;
...
/* Time to call the callback */
arglist = Py_BuildValue("(i)", arg);
result = PyObject_CallObject(my_callback, arglist);
Py_DECREF(arglist);

PyObject_CallObject() returns a Python object pointer: this is the return value of the Python function. PyObject_CallObject() is « reference-count-neutral » with respect to its arguments. In the example a new tuple was created to serve as the argument list, which is Py_DECREF()-ed immediately after the PyObject_CallObject() call.

The return value of PyObject_CallObject() is « new »: either it is a brand new object, or it is an existing object whose reference count has been incremented. So, unless you want to save it in a global variable, you should somehow Py_DECREF() the result, even (especially!) if you are not interested in its value.

Before you do this, however, it is important to check that the return value isn’t NULL. If it is, the Python function terminated by raising an exception. If the C code that called PyObject_CallObject() is called from Python, it should now return an error indication to its Python caller, so the interpreter can print a stack trace, or the calling Python code can handle the exception. If this is not possible or desirable, the exception should be cleared by calling PyErr_Clear(). For example:

if (result == NULL)
    return NULL; /* Pass error back */
...use result...
Py_DECREF(result);

Depending on the desired interface to the Python callback function, you may also have to provide an argument list to PyObject_CallObject(). In some cases the argument list is also provided by the Python program, through the same interface that specified the callback function. It can then be saved and used in the same manner as the function object. In other cases, you may have to construct a new tuple to pass as the argument list. The simplest way to do this is to call Py_BuildValue(). For example, if you want to pass an integral event code, you might use the following code:

PyObject *arglist;
...
arglist = Py_BuildValue("(l)", eventcode);
result = PyObject_CallObject(my_callback, arglist);
Py_DECREF(arglist);
if (result == NULL)
    return NULL; /* Pass error back */
/* Here maybe use the result */
Py_DECREF(result);

Note the placement of Py_DECREF(arglist) immediately after the call, before the error check! Also note that strictly speaking this code is not complete: Py_BuildValue() may run out of memory, and this should be checked.

You may also call a function with keyword arguments by using PyObject_Call(), which supports arguments and keyword arguments. As in the above example, we use Py_BuildValue() to construct the dictionary.

PyObject *dict;
...
dict = Py_BuildValue("{s:i}", "name", val);
result = PyObject_Call(my_callback, NULL, dict);
Py_DECREF(dict);
if (result == NULL)
    return NULL; /* Pass error back */
/* Here maybe use the result */
Py_DECREF(result);

1.7. Extracting Parameters in Extension Functions

The PyArg_ParseTuple() function is declared as follows:

int PyArg_ParseTuple(PyObject *arg, const char *format, ...);

The arg argument must be a tuple object containing an argument list passed from Python to a C function. The format argument must be a format string, whose syntax is explained in Analyse des arguments et construction des valeurs in the Python/C API Reference Manual. The remaining arguments must be addresses of variables whose type is determined by the format string.

Note that while PyArg_ParseTuple() checks that the Python arguments have the required types, it cannot check the validity of the addresses of C variables passed to the call: if you make mistakes there, your code will probably crash or at least overwrite random bits in memory. So be careful!

Notez que n’importe quelles références sur un objet Python qui sont données à l’appelant sont des références empruntées ; ne décrémentez pas leur compteur de références !

Some example calls:

#define PY_SSIZE_T_CLEAN  /* Make "s#" use Py_ssize_t rather than int. */
#include <Python.h>

int ok;
int i, j;
long k, l;
const char *s;
Py_ssize_t size;

ok = PyArg_ParseTuple(args, ""); /* No arguments */
    /* Python call: f() */

ok = PyArg_ParseTuple(args, "s", &s); /* A string */
    /* Possible Python call: f('whoops!') */

ok = PyArg_ParseTuple(args, "lls", &k, &l, &s); /* Two longs and a string */
    /* Possible Python call: f(1, 2, 'three') */

ok = PyArg_ParseTuple(args, "(ii)s#", &i, &j, &s, &size);
    /* A pair of ints and a string, whose size is also returned */
    /* Possible Python call: f((1, 2), 'three') */

{
    const char *file;
    const char *mode = "r";
    int bufsize = 0;
    ok = PyArg_ParseTuple(args, "s|si", &file, &mode, &bufsize);
    /* A string, and optionally another string and an integer */
    /* Possible Python calls:
       f('spam')
       f('spam', 'w')
       f('spam', 'wb', 100000) */
}

{
    int left, top, right, bottom, h, v;
    ok = PyArg_ParseTuple(args, "((ii)(ii))(ii)",
             &left, &top, &right, &bottom, &h, &v);
    /* A rectangle and a point */
    /* Possible Python call:
       f(((0, 0), (400, 300)), (10, 10)) */
}

{
    Py_complex c;
    ok = PyArg_ParseTuple(args, "D:myfunction", &c);
    /* a complex, also providing a function name for errors */
    /* Possible Python call: myfunction(1+2j) */
}

1.8. Keyword Parameters for Extension Functions

The PyArg_ParseTupleAndKeywords() function is declared as follows:

int PyArg_ParseTupleAndKeywords(PyObject *arg, PyObject *kwdict,
                                const char *format, char *kwlist[], ...);

The arg and format parameters are identical to those of the PyArg_ParseTuple() function. The kwdict parameter is the dictionary of keywords received as the third parameter from the Python runtime. The kwlist parameter is a NULL-terminated list of strings which identify the parameters; the names are matched with the type information from format from left to right. On success, PyArg_ParseTupleAndKeywords() returns true, otherwise it returns false and raises an appropriate exception.

Note

Nested tuples cannot be parsed when using keyword arguments! Keyword parameters passed in which are not present in the kwlist will cause TypeError to be raised.

Here is an example module which uses keywords, based on an example by Geoff Philbrick (philbrick@hks.com):

#include "Python.h"

static PyObject *
keywdarg_parrot(PyObject *self, PyObject *args, PyObject *keywds)
{
    int voltage;
    char *state = "a stiff";
    char *action = "voom";
    char *type = "Norwegian Blue";

    static char *kwlist[] = {"voltage", "state", "action", "type", NULL};

    if (!PyArg_ParseTupleAndKeywords(args, keywds, "i|sss", kwlist,
                                     &voltage, &state, &action, &type))
        return NULL;

    printf("-- This parrot wouldn't %s if you put %i Volts through it.\n",
           action, voltage);
    printf("-- Lovely plumage, the %s -- It's %s!\n", type, state);

    Py_RETURN_NONE;
}

static PyMethodDef keywdarg_methods[] = {
    /* The cast of the function is necessary since PyCFunction values
     * only take two PyObject* parameters, and keywdarg_parrot() takes
     * three.
     */
    {"parrot", (PyCFunction)keywdarg_parrot, METH_VARARGS | METH_KEYWORDS,
     "Print a lovely skit to standard output."},
    {NULL, NULL, 0, NULL}   /* sentinel */
};

static struct PyModuleDef keywdargmodule = {
    PyModuleDef_HEAD_INIT,
    "keywdarg",
    NULL,
    -1,
    keywdarg_methods
};

PyMODINIT_FUNC
PyInit_keywdarg(void)
{
    return PyModule_Create(&keywdargmodule);
}

1.9. Building Arbitrary Values

This function is the counterpart to PyArg_ParseTuple(). It is declared as follows:

PyObject *Py_BuildValue(const char *format, ...);

It recognizes a set of format units similar to the ones recognized by PyArg_ParseTuple(), but the arguments (which are input to the function, not output) must not be pointers, just values. It returns a new Python object, suitable for returning from a C function called from Python.

One difference with PyArg_ParseTuple(): while the latter requires its first argument to be a tuple (since Python argument lists are always represented as tuples internally), Py_BuildValue() does not always build a tuple. It builds a tuple only if its format string contains two or more format units. If the format string is empty, it returns None; if it contains exactly one format unit, it returns whatever object is described by that format unit. To force it to return a tuple of size 0 or one, parenthesize the format string.

Examples (to the left the call, to the right the resulting Python value):

Py_BuildValue("")                        None
Py_BuildValue("i", 123)                  123
Py_BuildValue("iii", 123, 456, 789)      (123, 456, 789)
Py_BuildValue("s", "hello")              'hello'
Py_BuildValue("y", "hello")              b'hello'
Py_BuildValue("ss", "hello", "world")    ('hello', 'world')
Py_BuildValue("s#", "hello", 4)          'hell'
Py_BuildValue("y#", "hello", 4)          b'hell'
Py_BuildValue("()")                      ()
Py_BuildValue("(i)", 123)                (123,)
Py_BuildValue("(ii)", 123, 456)          (123, 456)
Py_BuildValue("(i,i)", 123, 456)         (123, 456)
Py_BuildValue("[i,i]", 123, 456)         [123, 456]
Py_BuildValue("{s:i,s:i}",
              "abc", 123, "def", 456)    {'abc': 123, 'def': 456}
Py_BuildValue("((ii)(ii)) (ii)",
              1, 2, 3, 4, 5, 6)          (((1, 2), (3, 4)), (5, 6))

1.10. Reference Counts

In languages like C or C++, the programmer is responsible for dynamic allocation and deallocation of memory on the heap. In C, this is done using the functions malloc() and free(). In C++, the operators new and delete are used with essentially the same meaning and we’ll restrict the following discussion to the C case.

Every block of memory allocated with malloc() should eventually be returned to the pool of available memory by exactly one call to free(). It is important to call free() at the right time. If a block’s address is forgotten but free() is not called for it, the memory it occupies cannot be reused until the program terminates. This is called a memory leak. On the other hand, if a program calls free() for a block and then continues to use the block, it creates a conflict with re-use of the block through another malloc() call. This is called using freed memory. It has the same bad consequences as referencing uninitialized data — core dumps, wrong results, mysterious crashes.

Common causes of memory leaks are unusual paths through the code. For instance, a function may allocate a block of memory, do some calculation, and then free the block again. Now a change in the requirements for the function may add a test to the calculation that detects an error condition and can return prematurely from the function. It’s easy to forget to free the allocated memory block when taking this premature exit, especially when it is added later to the code. Such leaks, once introduced, often go undetected for a long time: the error exit is taken only in a small fraction of all calls, and most modern machines have plenty of virtual memory, so the leak only becomes apparent in a long-running process that uses the leaking function frequently. Therefore, it’s important to prevent leaks from happening by having a coding convention or strategy that minimizes this kind of errors.

Since Python makes heavy use of malloc() and free(), it needs a strategy to avoid memory leaks as well as the use of freed memory. The chosen method is called reference counting. The principle is simple: every object contains a counter, which is incremented when a reference to the object is stored somewhere, and which is decremented when a reference to it is deleted. When the counter reaches zero, the last reference to the object has been deleted and the object is freed.

An alternative strategy is called automatic garbage collection. (Sometimes, reference counting is also referred to as a garbage collection strategy, hence my use of « automatic » to distinguish the two.) The big advantage of automatic garbage collection is that the user doesn’t need to call free() explicitly. (Another claimed advantage is an improvement in speed or memory usage — this is no hard fact however.) The disadvantage is that for C, there is no truly portable automatic garbage collector, while reference counting can be implemented portably (as long as the functions malloc() and free() are available — which the C Standard guarantees). Maybe some day a sufficiently portable automatic garbage collector will be available for C. Until then, we’ll have to live with reference counts.

While Python uses the traditional reference counting implementation, it also offers a cycle detector that works to detect reference cycles. This allows applications to not worry about creating direct or indirect circular references; these are the weakness of garbage collection implemented using only reference counting. Reference cycles consist of objects which contain (possibly indirect) references to themselves, so that each object in the cycle has a reference count which is non-zero. Typical reference counting implementations are not able to reclaim the memory belonging to any objects in a reference cycle, or referenced from the objects in the cycle, even though there are no further references to the cycle itself.

The cycle detector is able to detect garbage cycles and can reclaim them. The gc module exposes a way to run the detector (the collect() function), as well as configuration interfaces and the ability to disable the detector at runtime. The cycle detector is considered an optional component; though it is included by default, it can be disabled at build time using the --without-cycle-gc option to the configure script on Unix platforms (including Mac OS X). If the cycle detector is disabled in this way, the gc module will not be available.

1.10.1. Reference Counting in Python

There are two macros, Py_INCREF(x) and Py_DECREF(x), which handle the incrementing and decrementing of the reference count. Py_DECREF() also frees the object when the count reaches zero. For flexibility, it doesn’t call free() directly — rather, it makes a call through a function pointer in the object’s type object. For this purpose (and others), every object also contains a pointer to its type object.

The big question now remains: when to use Py_INCREF(x) and Py_DECREF(x)? Let’s first introduce some terms. Nobody « owns » an object; however, you can own a reference to an object. An object’s reference count is now defined as the number of owned references to it. The owner of a reference is responsible for calling Py_DECREF() when the reference is no longer needed. Ownership of a reference can be transferred. There are three ways to dispose of an owned reference: pass it on, store it, or call Py_DECREF(). Forgetting to dispose of an owned reference creates a memory leak.

It is also possible to borrow 2 a reference to an object. The borrower of a reference should not call Py_DECREF(). The borrower must not hold on to the object longer than the owner from which it was borrowed. Using a borrowed reference after the owner has disposed of it risks using freed memory and should be avoided completely 3.

The advantage of borrowing over owning a reference is that you don’t need to take care of disposing of the reference on all possible paths through the code — in other words, with a borrowed reference you don’t run the risk of leaking when a premature exit is taken. The disadvantage of borrowing over owning is that there are some subtle situations where in seemingly correct code a borrowed reference can be used after the owner from which it was borrowed has in fact disposed of it.

A borrowed reference can be changed into an owned reference by calling Py_INCREF(). This does not affect the status of the owner from which the reference was borrowed — it creates a new owned reference, and gives full owner responsibilities (the new owner must dispose of the reference properly, as well as the previous owner).

1.10.2. Ownership Rules

Whenever an object reference is passed into or out of a function, it is part of the function’s interface specification whether ownership is transferred with the reference or not.

Most functions that return a reference to an object pass on ownership with the reference. In particular, all functions whose function it is to create a new object, such as PyLong_FromLong() and Py_BuildValue(), pass ownership to the receiver. Even if the object is not actually new, you still receive ownership of a new reference to that object. For instance, PyLong_FromLong() maintains a cache of popular values and can return a reference to a cached item.

Many functions that extract objects from other objects also transfer ownership with the reference, for instance PyObject_GetAttrString(). The picture is less clear, here, however, since a few common routines are exceptions: PyTuple_GetItem(), PyList_GetItem(), PyDict_GetItem(), and PyDict_GetItemString() all return references that you borrow from the tuple, list or dictionary.

The function PyImport_AddModule() also returns a borrowed reference, even though it may actually create the object it returns: this is possible because an owned reference to the object is stored in sys.modules.

When you pass an object reference into another function, in general, the function borrows the reference from you — if it needs to store it, it will use Py_INCREF() to become an independent owner. There are exactly two important exceptions to this rule: PyTuple_SetItem() and PyList_SetItem(). These functions take over ownership of the item passed to them — even if they fail! (Note that PyDict_SetItem() and friends don’t take over ownership — they are « normal. »)

When a C function is called from Python, it borrows references to its arguments from the caller. The caller owns a reference to the object, so the borrowed reference’s lifetime is guaranteed until the function returns. Only when such a borrowed reference must be stored or passed on, it must be turned into an owned reference by calling Py_INCREF().

The object reference returned from a C function that is called from Python must be an owned reference — ownership is transferred from the function to its caller.

1.10.3. Thin Ice

There are a few situations where seemingly harmless use of a borrowed reference can lead to problems. These all have to do with implicit invocations of the interpreter, which can cause the owner of a reference to dispose of it.

The first and most important case to know about is using Py_DECREF() on an unrelated object while borrowing a reference to a list item. For instance:

void
bug(PyObject *list)
{
    PyObject *item = PyList_GetItem(list, 0);

    PyList_SetItem(list, 1, PyLong_FromLong(0L));
    PyObject_Print(item, stdout, 0); /* BUG! */
}

This function first borrows a reference to list[0], then replaces list[1] with the value 0, and finally prints the borrowed reference. Looks harmless, right? But it’s not!

Let’s follow the control flow into PyList_SetItem(). The list owns references to all its items, so when item 1 is replaced, it has to dispose of the original item 1. Now let’s suppose the original item 1 was an instance of a user-defined class, and let’s further suppose that the class defined a __del__() method. If this class instance has a reference count of 1, disposing of it will call its __del__() method.

Since it is written in Python, the __del__() method can execute arbitrary Python code. Could it perhaps do something to invalidate the reference to item in bug()? You bet! Assuming that the list passed into bug() is accessible to the __del__() method, it could execute a statement to the effect of del list[0], and assuming this was the last reference to that object, it would free the memory associated with it, thereby invalidating item.

The solution, once you know the source of the problem, is easy: temporarily increment the reference count. The correct version of the function reads:

void
no_bug(PyObject *list)
{
    PyObject *item = PyList_GetItem(list, 0);

    Py_INCREF(item);
    PyList_SetItem(list, 1, PyLong_FromLong(0L));
    PyObject_Print(item, stdout, 0);
    Py_DECREF(item);
}

This is a true story. An older version of Python contained variants of this bug and someone spent a considerable amount of time in a C debugger to figure out why his __del__() methods would fail…

The second case of problems with a borrowed reference is a variant involving threads. Normally, multiple threads in the Python interpreter can’t get in each other’s way, because there is a global lock protecting Python’s entire object space. However, it is possible to temporarily release this lock using the macro Py_BEGIN_ALLOW_THREADS, and to re-acquire it using Py_END_ALLOW_THREADS. This is common around blocking I/O calls, to let other threads use the processor while waiting for the I/O to complete. Obviously, the following function has the same problem as the previous one:

void
bug(PyObject *list)
{
    PyObject *item = PyList_GetItem(list, 0);
    Py_BEGIN_ALLOW_THREADS
    ...some blocking I/O call...
    Py_END_ALLOW_THREADS
    PyObject_Print(item, stdout, 0); /* BUG! */
}

1.10.4. NULL Pointers

In general, functions that take object references as arguments do not expect you to pass them NULL pointers, and will dump core (or cause later core dumps) if you do so. Functions that return object references generally return NULL only to indicate that an exception occurred. The reason for not testing for NULL arguments is that functions often pass the objects they receive on to other function — if each function were to test for NULL, there would be a lot of redundant tests and the code would run more slowly.

It is better to test for NULL only at the « source: » when a pointer that may be NULL is received, for example, from malloc() or from a function that may raise an exception.

The macros Py_INCREF() and Py_DECREF() do not check for NULL pointers — however, their variants Py_XINCREF() and Py_XDECREF() do.

The macros for checking for a particular object type (Pytype_Check()) don’t check for NULL pointers — again, there is much code that calls several of these in a row to test an object against various different expected types, and this would generate redundant tests. There are no variants with NULL checking.

The C function calling mechanism guarantees that the argument list passed to C functions (args in the examples) is never NULL — in fact it guarantees that it is always a tuple 4.

It is a severe error to ever let a NULL pointer « escape » to the Python user.

1.11. Writing Extensions in C++

It is possible to write extension modules in C++. Some restrictions apply. If the main program (the Python interpreter) is compiled and linked by the C compiler, global or static objects with constructors cannot be used. This is not a problem if the main program is linked by the C++ compiler. Functions that will be called by the Python interpreter (in particular, module initialization functions) have to be declared using extern "C". It is unnecessary to enclose the Python header files in extern "C" {...} — they use this form already if the symbol __cplusplus is defined (all recent C++ compilers define this symbol).

1.12. Providing a C API for an Extension Module

Many extension modules just provide new functions and types to be used from Python, but sometimes the code in an extension module can be useful for other extension modules. For example, an extension module could implement a type « collection » which works like lists without order. Just like the standard Python list type has a C API which permits extension modules to create and manipulate lists, this new collection type should have a set of C functions for direct manipulation from other extension modules.

At first sight this seems easy: just write the functions (without declaring them static, of course), provide an appropriate header file, and document the C API. And in fact this would work if all extension modules were always linked statically with the Python interpreter. When modules are used as shared libraries, however, the symbols defined in one module may not be visible to another module. The details of visibility depend on the operating system; some systems use one global namespace for the Python interpreter and all extension modules (Windows, for example), whereas others require an explicit list of imported symbols at module link time (AIX is one example), or offer a choice of different strategies (most Unices). And even if symbols are globally visible, the module whose functions one wishes to call might not have been loaded yet!

Portability therefore requires not to make any assumptions about symbol visibility. This means that all symbols in extension modules should be declared static, except for the module’s initialization function, in order to avoid name clashes with other extension modules (as discussed in section La fonction d’initialisation et le tableau des méthodes du module). And it means that symbols that should be accessible from other extension modules must be exported in a different way.

Python provides a special mechanism to pass C-level information (pointers) from one extension module to another one: Capsules. A Capsule is a Python data type which stores a pointer (void *). Capsules can only be created and accessed via their C API, but they can be passed around like any other Python object. In particular, they can be assigned to a name in an extension module’s namespace. Other extension modules can then import this module, retrieve the value of this name, and then retrieve the pointer from the Capsule.

There are many ways in which Capsules can be used to export the C API of an extension module. Each function could get its own Capsule, or all C API pointers could be stored in an array whose address is published in a Capsule. And the various tasks of storing and retrieving the pointers can be distributed in different ways between the module providing the code and the client modules.

Whichever method you choose, it’s important to name your Capsules properly. The function PyCapsule_New() takes a name parameter (const char *); you’re permitted to pass in a NULL name, but we strongly encourage you to specify a name. Properly named Capsules provide a degree of runtime type-safety; there is no feasible way to tell one unnamed Capsule from another.

In particular, Capsules used to expose C APIs should be given a name following this convention:

modulename.attributename

The convenience function PyCapsule_Import() makes it easy to load a C API provided via a Capsule, but only if the Capsule’s name matches this convention. This behavior gives C API users a high degree of certainty that the Capsule they load contains the correct C API.

The following example demonstrates an approach that puts most of the burden on the writer of the exporting module, which is appropriate for commonly used library modules. It stores all C API pointers (just one in the example!) in an array of void pointers which becomes the value of a Capsule. The header file corresponding to the module provides a macro that takes care of importing the module and retrieving its C API pointers; client modules only have to call this macro before accessing the C API.

The exporting module is a modification of the spam module from section Un exemple simple. The function spam.system() does not call the C library function system() directly, but a function PySpam_System(), which would of course do something more complicated in reality (such as adding « spam » to every command). This function PySpam_System() is also exported to other extension modules.

The function PySpam_System() is a plain C function, declared static like everything else:

static int
PySpam_System(const char *command)
{
    return system(command);
}

The function spam_system() is modified in a trivial way:

static PyObject *
spam_system(PyObject *self, PyObject *args)
{
    const char *command;
    int sts;

    if (!PyArg_ParseTuple(args, "s", &command))
        return NULL;
    sts = PySpam_System(command);
    return PyLong_FromLong(sts);
}

In the beginning of the module, right after the line

#include "Python.h"

two more lines must be added:

#define SPAM_MODULE
#include "spammodule.h"

The #define is used to tell the header file that it is being included in the exporting module, not a client module. Finally, the module’s initialization function must take care of initializing the C API pointer array:

PyMODINIT_FUNC
PyInit_spam(void)
{
    PyObject *m;
    static void *PySpam_API[PySpam_API_pointers];
    PyObject *c_api_object;

    m = PyModule_Create(&spammodule);
    if (m == NULL)
        return NULL;

    /* Initialize the C API pointer array */
    PySpam_API[PySpam_System_NUM] = (void *)PySpam_System;

    /* Create a Capsule containing the API pointer array's address */
    c_api_object = PyCapsule_New((void *)PySpam_API, "spam._C_API", NULL);

    if (c_api_object != NULL)
        PyModule_AddObject(m, "_C_API", c_api_object);
    return m;
}

Note that PySpam_API is declared static; otherwise the pointer array would disappear when PyInit_spam() terminates!

The bulk of the work is in the header file spammodule.h, which looks like this:

#ifndef Py_SPAMMODULE_H
#define Py_SPAMMODULE_H
#ifdef __cplusplus
extern "C" {
#endif

/* Header file for spammodule */

/* C API functions */
#define PySpam_System_NUM 0
#define PySpam_System_RETURN int
#define PySpam_System_PROTO (const char *command)

/* Total number of C API pointers */
#define PySpam_API_pointers 1

#ifdef SPAM_MODULE
/* This section is used when compiling spammodule.c */

static PySpam_System_RETURN PySpam_System PySpam_System_PROTO;

#else
/* This section is used in modules that use spammodule's API */

static void **PySpam_API;

#define PySpam_System \
 (*(PySpam_System_RETURN (*)PySpam_System_PROTO) PySpam_API[PySpam_System_NUM])

/* Return -1 on error, 0 on success.
 * PyCapsule_Import will set an exception if there's an error.
 */
static int
import_spam(void)
{
    PySpam_API = (void **)PyCapsule_Import("spam._C_API", 0);
    return (PySpam_API != NULL) ? 0 : -1;
}

#endif

#ifdef __cplusplus
}
#endif

#endif /* !defined(Py_SPAMMODULE_H) */

All that a client module must do in order to have access to the function PySpam_System() is to call the function (or rather macro) import_spam() in its initialization function:

PyMODINIT_FUNC
PyInit_client(void)
{
    PyObject *m;

    m = PyModule_Create(&clientmodule);
    if (m == NULL)
        return NULL;
    if (import_spam() < 0)
        return NULL;
    /* additional initialization can happen here */
    return m;
}

The main disadvantage of this approach is that the file spammodule.h is rather complicated. However, the basic structure is the same for each function that is exported, so it has to be learned only once.

Finally it should be mentioned that Capsules offer additional functionality, which is especially useful for memory allocation and deallocation of the pointer stored in a Capsule. The details are described in the Python/C API Reference Manual in the section Capsules and in the implementation of Capsules (files Include/pycapsule.h and Objects/pycapsule.c in the Python source code distribution).

Notes

1

An interface for this function already exists in the standard module os — it was chosen as a simple and straightforward example.

2

The metaphor of « borrowing » a reference is not completely correct: the owner still has a copy of the reference.

3

Checking that the reference count is at least 1 does not work — the reference count itself could be in freed memory and may thus be reused for another object!

4

These guarantees don’t hold when you use the « old » style calling convention — this is still found in much existing code.

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2. Defining Extension Types: Tutorial

Python allows the writer of a C extension module to define new types that can be manipulated from Python code, much like the built-in str and list types. The code for all extension types follows a pattern, but there are some details that you need to understand before you can get started. This document is a gentle introduction to the topic.

2.1. The Basics

The CPython runtime sees all Python objects as variables of type PyObject*, which serves as a « base type » for all Python objects. The PyObject structure itself only contains the object’s reference count and a pointer to the object’s « type object ». This is where the action is; the type object determines which (C) functions get called by the interpreter when, for instance, an attribute gets looked up on an object, a method called, or it is multiplied by another object. These C functions are called « type methods ».

So, if you want to define a new extension type, you need to create a new type object.

This sort of thing can only be explained by example, so here’s a minimal, but complete, module that defines a new type named Custom inside a C extension module custom:

Note

What we’re showing here is the traditional way of defining static extension types. It should be adequate for most uses. The C API also allows defining heap-allocated extension types using the PyType_FromSpec() function, which isn’t covered in this tutorial.

#include <Python.h>

typedef struct {
    PyObject_HEAD
    /* Type-specific fields go here. */
} CustomObject;

static PyTypeObject CustomType = {
    PyVarObject_HEAD_INIT(NULL, 0)
    .tp_name = "custom.Custom",
    .tp_doc = "Custom objects",
    .tp_basicsize = sizeof(CustomObject),
    .tp_itemsize = 0,
    .tp_flags = Py_TPFLAGS_DEFAULT,
    .tp_new = PyType_GenericNew,
};

static PyModuleDef custommodule = {
    PyModuleDef_HEAD_INIT,
    .m_name = "custom",
    .m_doc = "Example module that creates an extension type.",
    .m_size = -1,
};

PyMODINIT_FUNC
PyInit_custom(void)
{
    PyObject *m;
    if (PyType_Ready(&CustomType) < 0)
        return NULL;

    m = PyModule_Create(&custommodule);
    if (m == NULL)
        return NULL;

    Py_INCREF(&CustomType);
    PyModule_AddObject(m, "Custom", (PyObject *) &CustomType);
    return m;
}

Now that’s quite a bit to take in at once, but hopefully bits will seem familiar from the previous chapter. This file defines three things:

What a Custom object contains: this is the CustomObject struct, which is allocated once for each Custom instance.

How the Custom type behaves: this is the CustomType struct, which defines a set of flags and function pointers that the interpreter inspects when specific operations are requested.

How to initialize the custom module: this is the PyInit_custom function and the associated custommodule struct.

The first bit is:

typedef struct {
    PyObject_HEAD
} CustomObject;

This is what a Custom object will contain. PyObject_HEAD is mandatory at the start of each object struct and defines a field called ob_base of type PyObject, containing a pointer to a type object and a reference count (these can be accessed using the macros Py_REFCNT and Py_TYPE respectively). The reason for the macro is to abstract away the layout and to enable additional fields in debug builds.

Note

There is no semicolon above after the PyObject_HEAD macro. Be wary of adding one by accident: some compilers will complain.

Of course, objects generally store additional data besides the standard PyObject_HEAD boilerplate; for example, here is the definition for standard Python floats:

typedef struct {
    PyObject_HEAD
    double ob_fval;
} PyFloatObject;

The second bit is the definition of the type object.

static PyTypeObject CustomType = {
    PyVarObject_HEAD_INIT(NULL, 0)
    .tp_name = "custom.Custom",
    .tp_doc = "Custom objects",
    .tp_basicsize = sizeof(CustomObject),
    .tp_itemsize = 0,
    .tp_new = PyType_GenericNew,
};

Note

We recommend using C99-style designated initializers as above, to avoid listing all the PyTypeObject fields that you don’t care about and also to avoid caring about the fields” declaration order.

The actual definition of PyTypeObject in object.h has many more fields than the definition above. The remaining fields will be filled with zeros by the C compiler, and it’s common practice to not specify them explicitly unless you need them.

We’re going to pick it apart, one field at a time:

PyVarObject_HEAD_INIT(NULL, 0)

This line is mandatory boilerplate to initialize the ob_base field mentioned above.

.tp_name = "custom.Custom",

The name of our type. This will appear in the default textual representation of our objects and in some error messages, for example:

>>> "" + custom.Custom()
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: can only concatenate str (not "custom.Custom") to str

Note that the name is a dotted name that includes both the module name and the name of the type within the module. The module in this case is custom and the type is Custom, so we set the type name to custom.Custom. Using the real dotted import path is important to make your type compatible with the pydoc and pickle modules.

.tp_basicsize = sizeof(CustomObject),
.tp_itemsize = 0,

This is so that Python knows how much memory to allocate when creating new Custom instances. tp_itemsize is only used for variable-sized objects and should otherwise be zero.

Note

If you want your type to be subclassable from Python, and your type has the same tp_basicsize as its base type, you may have problems with multiple inheritance. A Python subclass of your type will have to list your type first in its __bases__, or else it will not be able to call your type’s __new__() method without getting an error. You can avoid this problem by ensuring that your type has a larger value for tp_basicsize than its base type does. Most of the time, this will be true anyway, because either your base type will be object, or else you will be adding data members to your base type, and therefore increasing its size.

We set the class flags to Py_TPFLAGS_DEFAULT.

.tp_flags = Py_TPFLAGS_DEFAULT,

All types should include this constant in their flags. It enables all of the members defined until at least Python 3.3. If you need further members, you will need to OR the corresponding flags.

We provide a doc string for the type in tp_doc.

.tp_doc = "Custom objects",

To enable object creation, we have to provide a tp_new handler. This is the equivalent of the Python method __new__(), but has to be specified explicitly. In this case, we can just use the default implementation provided by the API function PyType_GenericNew().

.tp_new = PyType_GenericNew,

Everything else in the file should be familiar, except for some code in PyInit_custom():

if (PyType_Ready(&CustomType) < 0)
    return;

This initializes the Custom type, filling in a number of members to the appropriate default values, including ob_type that we initially set to NULL.

PyModule_AddObject(m, "Custom", (PyObject *) &CustomType);

This adds the type to the module dictionary. This allows us to create Custom instances by calling the Custom class:

>>> import custom
>>> mycustom = custom.Custom()

That’s it! All that remains is to build it; put the above code in a file called custom.c and:

from distutils.core import setup, Extension
setup(name="custom", version="1.0",
      ext_modules=[Extension("custom", ["custom.c"])])

in a file called setup.py; then typing

$ python setup.py build

at a shell should produce a file custom.so in a subdirectory; move to that directory and fire up Python — you should be able to import custom and play around with Custom objects.

That wasn’t so hard, was it?

Of course, the current Custom type is pretty uninteresting. It has no data and doesn’t do anything. It can’t even be subclassed.

Note

While this documentation showcases the standard distutils module for building C extensions, it is recommended in real-world use cases to use the newer and better-maintained setuptools library. Documentation on how to do this is out of scope for this document and can be found in the Python Packaging User’s Guide [https://packaging.python.org/tutorials/distributing-packages/].

2.2. Adding data and methods to the Basic example

Let’s extend the basic example to add some data and methods. Let’s also make the type usable as a base class. We’ll create a new module, custom2 that adds these capabilities:

#include <Python.h>
#include "structmember.h"

typedef struct {
    PyObject_HEAD
    PyObject *first; /* first name */
    PyObject *last;  /* last name */
    int number;
} CustomObject;

static void
Custom_dealloc(CustomObject *self)
{
    Py_XDECREF(self->first);
    Py_XDECREF(self->last);
    Py_TYPE(self)->tp_free((PyObject *) self);
}

static PyObject *
Custom_new(PyTypeObject *type, PyObject *args, PyObject *kwds)
{
    CustomObject *self;
    self = (CustomObject *) type->tp_alloc(type, 0);
    if (self != NULL) {
        self->first = PyUnicode_FromString("");
        if (self->first == NULL) {
            Py_DECREF(self);
            return NULL;
        }
        self->last = PyUnicode_FromString("");
        if (self->last == NULL) {
            Py_DECREF(self);
            return NULL;
        }
        self->number = 0;
    }
    return (PyObject *) self;
}

static int
Custom_init(CustomObject *self, PyObject *args, PyObject *kwds)
{
    static char *kwlist[] = {"first", "last", "number", NULL};
    PyObject *first = NULL, *last = NULL, *tmp;

    if (!PyArg_ParseTupleAndKeywords(args, kwds, "|OOi", kwlist,
                                     &first, &last,
                                     &self->number))
        return -1;

    if (first) {
        tmp = self->first;
        Py_INCREF(first);
        self->first = first;
        Py_XDECREF(tmp);
    }
    if (last) {
        tmp = self->last;
        Py_INCREF(last);
        self->last = last;
        Py_XDECREF(tmp);
    }
    return 0;
}

static PyMemberDef Custom_members[] = {
    {"first", T_OBJECT_EX, offsetof(CustomObject, first), 0,
     "first name"},
    {"last", T_OBJECT_EX, offsetof(CustomObject, last), 0,
     "last name"},
    {"number", T_INT, offsetof(CustomObject, number), 0,
     "custom number"},
    {NULL}  /* Sentinel */
};

static PyObject *
Custom_name(CustomObject *self, PyObject *Py_UNUSED(ignored))
{
    if (self->first == NULL) {
        PyErr_SetString(PyExc_AttributeError, "first");
        return NULL;
    }
    if (self->last == NULL) {
        PyErr_SetString(PyExc_AttributeError, "last");
        return NULL;
    }
    return PyUnicode_FromFormat("%S %S", self->first, self->last);
}

static PyMethodDef Custom_methods[] = {
    {"name", (PyCFunction) Custom_name, METH_NOARGS,
     "Return the name, combining the first and last name"
    },
    {NULL}  /* Sentinel */
};

static PyTypeObject CustomType = {
    PyVarObject_HEAD_INIT(NULL, 0)
    .tp_name = "custom2.Custom",
    .tp_doc = "Custom objects",
    .tp_basicsize = sizeof(CustomObject),
    .tp_itemsize = 0,
    .tp_flags = Py_TPFLAGS_DEFAULT | Py_TPFLAGS_BASETYPE,
    .tp_new = Custom_new,
    .tp_init = (initproc) Custom_init,
    .tp_dealloc = (destructor) Custom_dealloc,
    .tp_members = Custom_members,
    .tp_methods = Custom_methods,
};

static PyModuleDef custommodule = {
    PyModuleDef_HEAD_INIT,
    .m_name = "custom2",
    .m_doc = "Example module that creates an extension type.",
    .m_size = -1,
};

PyMODINIT_FUNC
PyInit_custom2(void)
{
    PyObject *m;
    if (PyType_Ready(&CustomType) < 0)
        return NULL;

    m = PyModule_Create(&custommodule);
    if (m == NULL)
        return NULL;

    Py_INCREF(&CustomType);
    PyModule_AddObject(m, "Custom", (PyObject *) &CustomType);
    return m;
}

This version of the module has a number of changes.

We’ve added an extra include:

#include <structmember.h>

This include provides declarations that we use to handle attributes, as described a bit later.

The Custom type now has three data attributes in its C struct, first, last, and number. The first and last variables are Python strings containing first and last names. The number attribute is a C integer.

The object structure is updated accordingly:

typedef struct {
    PyObject_HEAD
    PyObject *first; /* first name */
    PyObject *last;  /* last name */
    int number;
} CustomObject;

Because we now have data to manage, we have to be more careful about object allocation and deallocation. At a minimum, we need a deallocation method:

static void
Custom_dealloc(CustomObject *self)
{
    Py_XDECREF(self->first);
    Py_XDECREF(self->last);
    Py_TYPE(self)->tp_free((PyObject *) self);
}

which is assigned to the tp_dealloc member:

.tp_dealloc = (destructor) Custom_dealloc,

This method first clears the reference counts of the two Python attributes. Py_XDECREF() correctly handles the case where its argument is NULL (which might happen here if tp_new failed midway). It then calls the tp_free member of the object’s type (computed by Py_TYPE(self)) to free the object’s memory. Note that the object’s type might not be CustomType, because the object may be an instance of a subclass.

Note

The explicit cast to destructor above is needed because we defined Custom_dealloc to take a CustomObject * argument, but the tp_dealloc function pointer expects to receive a PyObject * argument. Otherwise, the compiler will emit a warning. This is object-oriented polymorphism, in C!

We want to make sure that the first and last names are initialized to empty strings, so we provide a tp_new implementation:

static PyObject *
Custom_new(PyTypeObject *type, PyObject *args, PyObject *kwds)
{
    CustomObject *self;
    self = (CustomObject *) type->tp_alloc(type, 0);
    if (self != NULL) {
        self->first = PyUnicode_FromString("");
        if (self->first == NULL) {
            Py_DECREF(self);
            return NULL;
        }
        self->last = PyUnicode_FromString("");
        if (self->last == NULL) {
            Py_DECREF(self);
            return NULL;
        }
        self->number = 0;
    }
    return (PyObject *) self;
}

and install it in the tp_new member:

.tp_new = Custom_new,

The tp_new handler is responsible for creating (as opposed to initializing) objects of the type. It is exposed in Python as the __new__() method. It is not required to define a tp_new member, and indeed many extension types will simply reuse PyType_GenericNew() as done in the first version of the Custom type above. In this case, we use the tp_new handler to initialize the first and last attributes to non-NULL default values.

tp_new is passed the type being instantiated (not necessarily CustomType, if a subclass is instantiated) and any arguments passed when the type was called, and is expected to return the instance created. tp_new handlers always accept positional and keyword arguments, but they often ignore the arguments, leaving the argument handling to initializer (a.k.a. tp_init in C or __init__ in Python) methods.

Note

tp_new shouldn’t call tp_init explicitly, as the interpreter will do it itself.

The tp_new implementation calls the tp_alloc slot to allocate memory:

self = (CustomObject *) type->tp_alloc(type, 0);

Since memory allocation may fail, we must check the tp_alloc result against NULL before proceeding.

Note

We didn’t fill the tp_alloc slot ourselves. Rather PyType_Ready() fills it for us by inheriting it from our base class, which is object by default. Most types use the default allocation strategy.

Note

If you are creating a co-operative tp_new (one that calls a base type’s tp_new or __new__()), you must not try to determine what method to call using method resolution order at runtime. Always statically determine what type you are going to call, and call its tp_new directly, or via type->tp_base->tp_new. If you do not do this, Python subclasses of your type that also inherit from other Python-defined classes may not work correctly. (Specifically, you may not be able to create instances of such subclasses without getting a TypeError.)

We also define an initialization function which accepts arguments to provide initial values for our instance:

static int
Custom_init(CustomObject *self, PyObject *args, PyObject *kwds)
{
    static char *kwlist[] = {"first", "last", "number", NULL};
    PyObject *first = NULL, *last = NULL, *tmp;

    if (!PyArg_ParseTupleAndKeywords(args, kwds, "|OOi", kwlist,
                                     &first, &last,
                                     &self->number))
        return -1;

    if (first) {
        tmp = self->first;
        Py_INCREF(first);
        self->first = first;
        Py_XDECREF(tmp);
    }
    if (last) {
        tmp = self->last;
        Py_INCREF(last);
        self->last = last;
        Py_XDECREF(tmp);
    }
    return 0;
}

by filling the tp_init slot.

.tp_init = (initproc) Custom_init,

The tp_init slot is exposed in Python as the __init__() method. It is used to initialize an object after it’s created. Initializers always accept positional and keyword arguments, and they should return either 0 on success or -1 on error.

Unlike the tp_new handler, there is no guarantee that tp_init is called at all (for example, the pickle module by default doesn’t call __init__() on unpickled instances). It can also be called multiple times. Anyone can call the __init__() method on our objects. For this reason, we have to be extra careful when assigning the new attribute values. We might be tempted, for example to assign the first member like this:

if (first) {
    Py_XDECREF(self->first);
    Py_INCREF(first);
    self->first = first;
}

But this would be risky. Our type doesn’t restrict the type of the first member, so it could be any kind of object. It could have a destructor that causes code to be executed that tries to access the first member; or that destructor could release the Global interpreter Lock and let arbitrary code run in other threads that accesses and modifies our object.

To be paranoid and protect ourselves against this possibility, we almost always reassign members before decrementing their reference counts. When don’t we have to do this?

when we absolutely know that the reference count is greater than 1;

when we know that deallocation of the object 1 will neither release the GIL nor cause any calls back into our type’s code;

when decrementing a reference count in a tp_dealloc handler on a type which doesn’t support cyclic garbage collection 2.

We want to expose our instance variables as attributes. There are a number of ways to do that. The simplest way is to define member definitions:

static PyMemberDef Custom_members[] = {
    {"first", T_OBJECT_EX, offsetof(CustomObject, first), 0,
     "first name"},
    {"last", T_OBJECT_EX, offsetof(CustomObject, last), 0,
     "last name"},
    {"number", T_INT, offsetof(CustomObject, number), 0,
     "custom number"},
    {NULL}  /* Sentinel */
};

and put the definitions in the tp_members slot:

.tp_members = Custom_members,

Each member definition has a member name, type, offset, access flags and documentation string. See the Generic Attribute Management section below for details.

A disadvantage of this approach is that it doesn’t provide a way to restrict the types of objects that can be assigned to the Python attributes. We expect the first and last names to be strings, but any Python objects can be assigned. Further, the attributes can be deleted, setting the C pointers to NULL. Even though we can make sure the members are initialized to non-NULL values, the members can be set to NULL if the attributes are deleted.

We define a single method, Custom.name(), that outputs the objects name as the concatenation of the first and last names.

static PyObject *
Custom_name(CustomObject *self)
{
    if (self->first == NULL) {
        PyErr_SetString(PyExc_AttributeError, "first");
        return NULL;
    }
    if (self->last == NULL) {
        PyErr_SetString(PyExc_AttributeError, "last");
        return NULL;
    }
    return PyUnicode_FromFormat("%S %S", self->first, self->last);
}

The method is implemented as a C function that takes a Custom (or Custom subclass) instance as the first argument. Methods always take an instance as the first argument. Methods often take positional and keyword arguments as well, but in this case we don’t take any and don’t need to accept a positional argument tuple or keyword argument dictionary. This method is equivalent to the Python method:

def name(self):
    return "%s %s" % (self.first, self.last)

Note that we have to check for the possibility that our first and last members are NULL. This is because they can be deleted, in which case they are set to NULL. It would be better to prevent deletion of these attributes and to restrict the attribute values to be strings. We’ll see how to do that in the next section.

Now that we’ve defined the method, we need to create an array of method definitions:

static PyMethodDef Custom_methods[] = {
    {"name", (PyCFunction) Custom_name, METH_NOARGS,
     "Return the name, combining the first and last name"
    },
    {NULL}  /* Sentinel */
};

(note that we used the METH_NOARGS flag to indicate that the method is expecting no arguments other than self)

and assign it to the tp_methods slot:

.tp_methods = Custom_methods,

Finally, we’ll make our type usable as a base class for subclassing. We’ve written our methods carefully so far so that they don’t make any assumptions about the type of the object being created or used, so all we need to do is to add the Py_TPFLAGS_BASETYPE to our class flag definition:

.tp_flags = Py_TPFLAGS_DEFAULT | Py_TPFLAGS_BASETYPE,

We rename PyInit_custom() to PyInit_custom2(), update the module name in the PyModuleDef struct, and update the full class name in the PyTypeObject struct.

Finally, we update our setup.py file to build the new module:

from distutils.core import setup, Extension
setup(name="custom", version="1.0",
      ext_modules=[
         Extension("custom", ["custom.c"]),
         Extension("custom2", ["custom2.c"]),
         ])

2.3. Providing finer control over data attributes

In this section, we’ll provide finer control over how the first and last attributes are set in the Custom example. In the previous version of our module, the instance variables first and last could be set to non-string values or even deleted. We want to make sure that these attributes always contain strings.

#include <Python.h>
#include "structmember.h"

typedef struct {
    PyObject_HEAD
    PyObject *first; /* first name */
    PyObject *last;  /* last name */
    int number;
} CustomObject;

static void
Custom_dealloc(CustomObject *self)
{
    Py_XDECREF(self->first);
    Py_XDECREF(self->last);
    Py_TYPE(self)->tp_free((PyObject *) self);
}

static PyObject *
Custom_new(PyTypeObject *type, PyObject *args, PyObject *kwds)
{
    CustomObject *self;
    self = (CustomObject *) type->tp_alloc(type, 0);
    if (self != NULL) {
        self->first = PyUnicode_FromString("");
        if (self->first == NULL) {
            Py_DECREF(self);
            return NULL;
        }
        self->last = PyUnicode_FromString("");
        if (self->last == NULL) {
            Py_DECREF(self);
            return NULL;
        }
        self->number = 0;
    }
    return (PyObject *) self;
}

static int
Custom_init(CustomObject *self, PyObject *args, PyObject *kwds)
{
    static char *kwlist[] = {"first", "last", "number", NULL};
    PyObject *first = NULL, *last = NULL, *tmp;

    if (!PyArg_ParseTupleAndKeywords(args, kwds, "|UUi", kwlist,
                                     &first, &last,
                                     &self->number))
        return -1;

    if (first) {
        tmp = self->first;
        Py_INCREF(first);
        self->first = first;
        Py_DECREF(tmp);
    }
    if (last) {
        tmp = self->last;
        Py_INCREF(last);
        self->last = last;
        Py_DECREF(tmp);
    }
    return 0;
}

static PyMemberDef Custom_members[] = {
    {"number", T_INT, offsetof(CustomObject, number), 0,
     "custom number"},
    {NULL}  /* Sentinel */
};

static PyObject *
Custom_getfirst(CustomObject *self, void *closure)
{
    Py_INCREF(self->first);
    return self->first;
}

static int
Custom_setfirst(CustomObject *self, PyObject *value, void *closure)
{
    PyObject *tmp;
    if (value == NULL) {
        PyErr_SetString(PyExc_TypeError, "Cannot delete the first attribute");
        return -1;
    }
    if (!PyUnicode_Check(value)) {
        PyErr_SetString(PyExc_TypeError,
                        "The first attribute value must be a string");
        return -1;
    }
    tmp = self->first;
    Py_INCREF(value);
    self->first = value;
    Py_DECREF(tmp);
    return 0;
}

static PyObject *
Custom_getlast(CustomObject *self, void *closure)
{
    Py_INCREF(self->last);
    return self->last;
}

static int
Custom_setlast(CustomObject *self, PyObject *value, void *closure)
{
    PyObject *tmp;
    if (value == NULL) {
        PyErr_SetString(PyExc_TypeError, "Cannot delete the last attribute");
        return -1;
    }
    if (!PyUnicode_Check(value)) {
        PyErr_SetString(PyExc_TypeError,
                        "The last attribute value must be a string");
        return -1;
    }
    tmp = self->last;
    Py_INCREF(value);
    self->last = value;
    Py_DECREF(tmp);
    return 0;
}

static PyGetSetDef Custom_getsetters[] = {
    {"first", (getter) Custom_getfirst, (setter) Custom_setfirst,
     "first name", NULL},
    {"last", (getter) Custom_getlast, (setter) Custom_setlast,
     "last name", NULL},
    {NULL}  /* Sentinel */
};

static PyObject *
Custom_name(CustomObject *self, PyObject *Py_UNUSED(ignored))
{
    return PyUnicode_FromFormat("%S %S", self->first, self->last);
}

static PyMethodDef Custom_methods[] = {
    {"name", (PyCFunction) Custom_name, METH_NOARGS,
     "Return the name, combining the first and last name"
    },
    {NULL}  /* Sentinel */
};

static PyTypeObject CustomType = {
    PyVarObject_HEAD_INIT(NULL, 0)
    .tp_name = "custom3.Custom",
    .tp_doc = "Custom objects",
    .tp_basicsize = sizeof(CustomObject),
    .tp_itemsize = 0,
    .tp_flags = Py_TPFLAGS_DEFAULT | Py_TPFLAGS_BASETYPE,
    .tp_new = Custom_new,
    .tp_init = (initproc) Custom_init,
    .tp_dealloc = (destructor) Custom_dealloc,
    .tp_members = Custom_members,
    .tp_methods = Custom_methods,
    .tp_getset = Custom_getsetters,
};

static PyModuleDef custommodule = {
    PyModuleDef_HEAD_INIT,
    .m_name = "custom3",
    .m_doc = "Example module that creates an extension type.",
    .m_size = -1,
};

PyMODINIT_FUNC
PyInit_custom3(void)
{
    PyObject *m;
    if (PyType_Ready(&CustomType) < 0)
        return NULL;

    m = PyModule_Create(&custommodule);
    if (m == NULL)
        return NULL;

    Py_INCREF(&CustomType);
    PyModule_AddObject(m, "Custom", (PyObject *) &CustomType);
    return m;
}

To provide greater control, over the first and last attributes, we’ll use custom getter and setter functions. Here are the functions for getting and setting the first attribute:

static PyObject *
Custom_getfirst(CustomObject *self, void *closure)
{
    Py_INCREF(self->first);
    return self->first;
}

static int
Custom_setfirst(CustomObject *self, PyObject *value, void *closure)
{
    PyObject *tmp;
    if (value == NULL) {
        PyErr_SetString(PyExc_TypeError, "Cannot delete the first attribute");
        return -1;
    }
    if (!PyUnicode_Check(value)) {
        PyErr_SetString(PyExc_TypeError,
                        "The first attribute value must be a string");
        return -1;
    }
    tmp = self->first;
    Py_INCREF(value);
    self->first = value;
    Py_DECREF(tmp);
    return 0;
}

The getter function is passed a Custom object and a « closure », which is a void pointer. In this case, the closure is ignored. (The closure supports an advanced usage in which definition data is passed to the getter and setter. This could, for example, be used to allow a single set of getter and setter functions that decide the attribute to get or set based on data in the closure.)

The setter function is passed the Custom object, the new value, and the closure. The new value may be NULL, in which case the attribute is being deleted. In our setter, we raise an error if the attribute is deleted or if its new value is not a string.

We create an array of PyGetSetDef structures:

static PyGetSetDef Custom_getsetters[] = {
    {"first", (getter) Custom_getfirst, (setter) Custom_setfirst,
     "first name", NULL},
    {"last", (getter) Custom_getlast, (setter) Custom_setlast,
     "last name", NULL},
    {NULL}  /* Sentinel */
};

and register it in the tp_getset slot:

.tp_getset = Custom_getsetters,

The last item in a PyGetSetDef structure is the « closure » mentioned above. In this case, we aren’t using a closure, so we just pass NULL.

We also remove the member definitions for these attributes:

static PyMemberDef Custom_members[] = {
    {"number", T_INT, offsetof(CustomObject, number), 0,
     "custom number"},
    {NULL}  /* Sentinel */
};

We also need to update the tp_init handler to only allow strings 3 to be passed:

static int
Custom_init(CustomObject *self, PyObject *args, PyObject *kwds)
{
    static char *kwlist[] = {"first", "last", "number", NULL};
    PyObject *first = NULL, *last = NULL, *tmp;

    if (!PyArg_ParseTupleAndKeywords(args, kwds, "|UUi", kwlist,
                                     &first, &last,
                                     &self->number))
        return -1;

    if (first) {
        tmp = self->first;
        Py_INCREF(first);
        self->first = first;
        Py_DECREF(tmp);
    }
    if (last) {
        tmp = self->last;
        Py_INCREF(last);
        self->last = last;
        Py_DECREF(tmp);
    }
    return 0;
}

With these changes, we can assure that the first and last members are never NULL so we can remove checks for NULL values in almost all cases. This means that most of the Py_XDECREF() calls can be converted to Py_DECREF() calls. The only place we can’t change these calls is in the tp_dealloc implementation, where there is the possibility that the initialization of these members failed in tp_new.

We also rename the module initialization function and module name in the initialization function, as we did before, and we add an extra definition to the setup.py file.

2.4. Supporting cyclic garbage collection

Python has a cyclic garbage collector (GC) that can identify unneeded objects even when their reference counts are not zero. This can happen when objects are involved in cycles. For example, consider:

>>> l = []
>>> l.append(l)
>>> del l

In this example, we create a list that contains itself. When we delete it, it still has a reference from itself. Its reference count doesn’t drop to zero. Fortunately, Python’s cyclic garbage collector will eventually figure out that the list is garbage and free it.

In the second version of the Custom example, we allowed any kind of object to be stored in the first or last attributes 4. Besides, in the second and third versions, we allowed subclassing Custom, and subclasses may add arbitrary attributes. For any of those two reasons, Custom objects can participate in cycles:

>>> import custom3
>>> class Derived(custom3.Custom): pass
...
>>> n = Derived()
>>> n.some_attribute = n

To allow a Custom instance participating in a reference cycle to be properly detected and collected by the cyclic GC, our Custom type needs to fill two additional slots and to enable a flag that enables these slots:

#include <Python.h>
#include "structmember.h"

typedef struct {
    PyObject_HEAD
    PyObject *first; /* first name */
    PyObject *last;  /* last name */
    int number;
} CustomObject;

static int
Custom_traverse(CustomObject *self, visitproc visit, void *arg)
{
    Py_VISIT(self->first);
    Py_VISIT(self->last);
    return 0;
}

static int
Custom_clear(CustomObject *self)
{
    Py_CLEAR(self->first);
    Py_CLEAR(self->last);
    return 0;
}

static void
Custom_dealloc(CustomObject *self)
{
    PyObject_GC_UnTrack(self);
    Custom_clear(self);
    Py_TYPE(self)->tp_free((PyObject *) self);
}

static PyObject *
Custom_new(PyTypeObject *type, PyObject *args, PyObject *kwds)
{
    CustomObject *self;
    self = (CustomObject *) type->tp_alloc(type, 0);
    if (self != NULL) {
        self->first = PyUnicode_FromString("");
        if (self->first == NULL) {
            Py_DECREF(self);
            return NULL;
        }
        self->last = PyUnicode_FromString("");
        if (self->last == NULL) {
            Py_DECREF(self);
            return NULL;
        }
        self->number = 0;
    }
    return (PyObject *) self;
}

static int
Custom_init(CustomObject *self, PyObject *args, PyObject *kwds)
{
    static char *kwlist[] = {"first", "last", "number", NULL};
    PyObject *first = NULL, *last = NULL, *tmp;

    if (!PyArg_ParseTupleAndKeywords(args, kwds, "|UUi", kwlist,
                                     &first, &last,
                                     &self->number))
        return -1;

    if (first) {
        tmp = self->first;
        Py_INCREF(first);
        self->first = first;
        Py_DECREF(tmp);
    }
    if (last) {
        tmp = self->last;
        Py_INCREF(last);
        self->last = last;
        Py_DECREF(tmp);
    }
    return 0;
}

static PyMemberDef Custom_members[] = {
    {"number", T_INT, offsetof(CustomObject, number), 0,
     "custom number"},
    {NULL}  /* Sentinel */
};

static PyObject *
Custom_getfirst(CustomObject *self, void *closure)
{
    Py_INCREF(self->first);
    return self->first;
}

static int
Custom_setfirst(CustomObject *self, PyObject *value, void *closure)
{
    if (value == NULL) {
        PyErr_SetString(PyExc_TypeError, "Cannot delete the first attribute");
        return -1;
    }
    if (!PyUnicode_Check(value)) {
        PyErr_SetString(PyExc_TypeError,
                        "The first attribute value must be a string");
        return -1;
    }
    Py_INCREF(value);
    Py_CLEAR(self->first);
    self->first = value;
    return 0;
}

static PyObject *
Custom_getlast(CustomObject *self, void *closure)
{
    Py_INCREF(self->last);
    return self->last;
}

static int
Custom_setlast(CustomObject *self, PyObject *value, void *closure)
{
    if (value == NULL) {
        PyErr_SetString(PyExc_TypeError, "Cannot delete the last attribute");
        return -1;
    }
    if (!PyUnicode_Check(value)) {
        PyErr_SetString(PyExc_TypeError,
                        "The last attribute value must be a string");
        return -1;
    }
    Py_INCREF(value);
    Py_CLEAR(self->last);
    self->last = value;
    return 0;
}

static PyGetSetDef Custom_getsetters[] = {
    {"first", (getter) Custom_getfirst, (setter) Custom_setfirst,
     "first name", NULL},
    {"last", (getter) Custom_getlast, (setter) Custom_setlast,
     "last name", NULL},
    {NULL}  /* Sentinel */
};

static PyObject *
Custom_name(CustomObject *self, PyObject *Py_UNUSED(ignored))
{
    return PyUnicode_FromFormat("%S %S", self->first, self->last);
}

static PyMethodDef Custom_methods[] = {
    {"name", (PyCFunction) Custom_name, METH_NOARGS,
     "Return the name, combining the first and last name"
    },
    {NULL}  /* Sentinel */
};

static PyTypeObject CustomType = {
    PyVarObject_HEAD_INIT(NULL, 0)
    .tp_name = "custom4.Custom",
    .tp_doc = "Custom objects",
    .tp_basicsize = sizeof(CustomObject),
    .tp_itemsize = 0,
    .tp_flags = Py_TPFLAGS_DEFAULT | Py_TPFLAGS_BASETYPE | Py_TPFLAGS_HAVE_GC,
    .tp_new = Custom_new,
    .tp_init = (initproc) Custom_init,
    .tp_dealloc = (destructor) Custom_dealloc,
    .tp_traverse = (traverseproc) Custom_traverse,
    .tp_clear = (inquiry) Custom_clear,
    .tp_members = Custom_members,
    .tp_methods = Custom_methods,
    .tp_getset = Custom_getsetters,
};

static PyModuleDef custommodule = {
    PyModuleDef_HEAD_INIT,
    .m_name = "custom4",
    .m_doc = "Example module that creates an extension type.",
    .m_size = -1,
};

PyMODINIT_FUNC
PyInit_custom4(void)
{
    PyObject *m;
    if (PyType_Ready(&CustomType) < 0)
        return NULL;

    m = PyModule_Create(&custommodule);
    if (m == NULL)
        return NULL;

    Py_INCREF(&CustomType);
    PyModule_AddObject(m, "Custom", (PyObject *) &CustomType);
    return m;
}

First, the traversal method lets the cyclic GC know about subobjects that could participate in cycles:

static int
Custom_traverse(CustomObject *self, visitproc visit, void *arg)
{
    int vret;
    if (self->first) {
        vret = visit(self->first, arg);
        if (vret != 0)
            return vret;
    }
    if (self->last) {
        vret = visit(self->last, arg);
        if (vret != 0)
            return vret;
    }
    return 0;
}

For each subobject that can participate in cycles, we need to call the visit() function, which is passed to the traversal method. The visit() function takes as arguments the subobject and the extra argument arg passed to the traversal method. It returns an integer value that must be returned if it is non-zero.

Python provides a Py_VISIT() macro that automates calling visit functions. With Py_VISIT(), we can minimize the amount of boilerplate in Custom_traverse:

static int
Custom_traverse(CustomObject *self, visitproc visit, void *arg)
{
    Py_VISIT(self->first);
    Py_VISIT(self->last);
    return 0;
}

Note

The tp_traverse implementation must name its arguments exactly visit and arg in order to use Py_VISIT().

Second, we need to provide a method for clearing any subobjects that can participate in cycles:

static int
Custom_clear(CustomObject *self)
{
    Py_CLEAR(self->first);
    Py_CLEAR(self->last);
    return 0;
}

Notice the use of the Py_CLEAR() macro. It is the recommended and safe way to clear data attributes of arbitrary types while decrementing their reference counts. If you were to call Py_XDECREF() instead on the attribute before setting it to NULL, there is a possibility that the attribute’s destructor would call back into code that reads the attribute again (especially if there is a reference cycle).

Note

You could emulate Py_CLEAR() by writing:

PyObject *tmp;
tmp = self->first;
self->first = NULL;
Py_XDECREF(tmp);

Nevertheless, it is much easier and less error-prone to always use Py_CLEAR() when deleting an attribute. Don’t try to micro-optimize at the expense of robustness!

The deallocator Custom_dealloc may call arbitrary code when clearing attributes. It means the circular GC can be triggered inside the function. Since the GC assumes reference count is not zero, we need to untrack the object from the GC by calling PyObject_GC_UnTrack() before clearing members. Here is our reimplemented deallocator using PyObject_GC_UnTrack() and Custom_clear:

static void
Custom_dealloc(CustomObject *self)
{
    PyObject_GC_UnTrack(self);
    Custom_clear(self);
    Py_TYPE(self)->tp_free((PyObject *) self);
}

Finally, we add the Py_TPFLAGS_HAVE_GC flag to the class flags:

.tp_flags = Py_TPFLAGS_DEFAULT | Py_TPFLAGS_BASETYPE | Py_TPFLAGS_HAVE_GC,

That’s pretty much it. If we had written custom tp_alloc or tp_free handlers, we’d need to modify them for cyclic garbage collection. Most extensions will use the versions automatically provided.

2.5. Subclassing other types

It is possible to create new extension types that are derived from existing types. It is easiest to inherit from the built in types, since an extension can easily use the PyTypeObject it needs. It can be difficult to share these PyTypeObject structures between extension modules.

In this example we will create a SubList type that inherits from the built-in list type. The new type will be completely compatible with regular lists, but will have an additional increment() method that increases an internal counter:

>>> import sublist
>>> s = sublist.SubList(range(3))
>>> s.extend(s)
>>> print(len(s))
6
>>> print(s.increment())
1
>>> print(s.increment())
2

#include <Python.h>

typedef struct {
    PyListObject list;
    int state;
} SubListObject;

static PyObject *
SubList_increment(SubListObject *self, PyObject *unused)
{
    self->state++;
    return PyLong_FromLong(self->state);
}

static PyMethodDef SubList_methods[] = {
    {"increment", (PyCFunction) SubList_increment, METH_NOARGS,
     PyDoc_STR("increment state counter")},
    {NULL},
};

static int
SubList_init(SubListObject *self, PyObject *args, PyObject *kwds)
{
    if (PyList_Type.tp_init((PyObject *) self, args, kwds) < 0)
        return -1;
    self->state = 0;
    return 0;
}

static PyTypeObject SubListType = {
    PyVarObject_HEAD_INIT(NULL, 0)
    .tp_name = "sublist.SubList",
    .tp_doc = "SubList objects",
    .tp_basicsize = sizeof(SubListObject),
    .tp_itemsize = 0,
    .tp_flags = Py_TPFLAGS_DEFAULT | Py_TPFLAGS_BASETYPE,
    .tp_init = (initproc) SubList_init,
    .tp_methods = SubList_methods,
};

static PyModuleDef sublistmodule = {
    PyModuleDef_HEAD_INIT,
    .m_name = "sublist",
    .m_doc = "Example module that creates an extension type.",
    .m_size = -1,
};

PyMODINIT_FUNC
PyInit_sublist(void)
{
    PyObject *m;
    SubListType.tp_base = &PyList_Type;
    if (PyType_Ready(&SubListType) < 0)
        return NULL;

    m = PyModule_Create(&sublistmodule);
    if (m == NULL)
        return NULL;

    Py_INCREF(&SubListType);
    PyModule_AddObject(m, "SubList", (PyObject *) &SubListType);
    return m;
}

As you can see, the source code closely resembles the Custom examples in previous sections. We will break down the main differences between them.

typedef struct {
    PyListObject list;
    int state;
} SubListObject;

The primary difference for derived type objects is that the base type’s object structure must be the first value. The base type will already include the PyObject_HEAD() at the beginning of its structure.

When a Python object is a SubList instance, its PyObject * pointer can be safely cast to both PyListObject * and SubListObject *:

static int
SubList_init(SubListObject *self, PyObject *args, PyObject *kwds)
{
    if (PyList_Type.tp_init((PyObject *) self, args, kwds) < 0)
        return -1;
    self->state = 0;
    return 0;
}

We see above how to call through to the __init__ method of the base type.

This pattern is important when writing a type with custom tp_new and tp_dealloc members. The tp_new handler should not actually create the memory for the object with its tp_alloc, but let the base class handle it by calling its own tp_new.

The PyTypeObject struct supports a tp_base specifying the type’s concrete base class. Due to cross-platform compiler issues, you can’t fill that field directly with a reference to PyList_Type; it should be done later in the module initialization function:

PyMODINIT_FUNC
PyInit_sublist(void)
{
    PyObject* m;
    SubListType.tp_base = &PyList_Type;
    if (PyType_Ready(&SubListType) < 0)
        return NULL;

    m = PyModule_Create(&sublistmodule);
    if (m == NULL)
        return NULL;

    Py_INCREF(&SubListType);
    PyModule_AddObject(m, "SubList", (PyObject *) &SubListType);
    return m;
}

Before calling PyType_Ready(), the type structure must have the tp_base slot filled in. When we are deriving an existing type, it is not necessary to fill out the tp_alloc slot with PyType_GenericNew() – the allocation function from the base type will be inherited.

After that, calling PyType_Ready() and adding the type object to the module is the same as with the basic Custom examples.

Notes

1

This is true when we know that the object is a basic type, like a string or a float.

2

We relied on this in the tp_dealloc handler in this example, because our type doesn’t support garbage collection.

3

We now know that the first and last members are strings, so perhaps we could be less careful about decrementing their reference counts, however, we accept instances of string subclasses. Even though deallocating normal strings won’t call back into our objects, we can’t guarantee that deallocating an instance of a string subclass won’t call back into our objects.

4

Also, even with our attributes restricted to strings instances, the user could pass arbitrary str subclasses and therefore still create reference cycles.

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3. Defining Extension Types: Assorted Topics

This section aims to give a quick fly-by on the various type methods you can implement and what they do.

Here is the definition of PyTypeObject, with some fields only used in debug builds omitted:

typedef struct _typeobject {
    PyObject_VAR_HEAD
    const char *tp_name; /* For printing, in format "<module>.<name>" */
    Py_ssize_t tp_basicsize, tp_itemsize; /* For allocation */

    /* Methods to implement standard operations */

    destructor tp_dealloc;
    printfunc tp_print;
    getattrfunc tp_getattr;
    setattrfunc tp_setattr;
    PyAsyncMethods *tp_as_async; /* formerly known as tp_compare (Python 2)
                                    or tp_reserved (Python 3) */
    reprfunc tp_repr;

    /* Method suites for standard classes */

    PyNumberMethods *tp_as_number;
    PySequenceMethods *tp_as_sequence;
    PyMappingMethods *tp_as_mapping;

    /* More standard operations (here for binary compatibility) */

    hashfunc tp_hash;
    ternaryfunc tp_call;
    reprfunc tp_str;
    getattrofunc tp_getattro;
    setattrofunc tp_setattro;

    /* Functions to access object as input/output buffer */
    PyBufferProcs *tp_as_buffer;

    /* Flags to define presence of optional/expanded features */
    unsigned long tp_flags;

    const char *tp_doc; /* Documentation string */

    /* call function for all accessible objects */
    traverseproc tp_traverse;

    /* delete references to contained objects */
    inquiry tp_clear;

    /* rich comparisons */
    richcmpfunc tp_richcompare;

    /* weak reference enabler */
    Py_ssize_t tp_weaklistoffset;

    /* Iterators */
    getiterfunc tp_iter;
    iternextfunc tp_iternext;

    /* Attribute descriptor and subclassing stuff */
    struct PyMethodDef *tp_methods;
    struct PyMemberDef *tp_members;
    struct PyGetSetDef *tp_getset;
    struct _typeobject *tp_base;
    PyObject *tp_dict;
    descrgetfunc tp_descr_get;
    descrsetfunc tp_descr_set;
    Py_ssize_t tp_dictoffset;
    initproc tp_init;
    allocfunc tp_alloc;
    newfunc tp_new;
    freefunc tp_free; /* Low-level free-memory routine */
    inquiry tp_is_gc; /* For PyObject_IS_GC */
    PyObject *tp_bases;
    PyObject *tp_mro; /* method resolution order */
    PyObject *tp_cache;
    PyObject *tp_subclasses;
    PyObject *tp_weaklist;
    destructor tp_del;

    /* Type attribute cache version tag. Added in version 2.6 */
    unsigned int tp_version_tag;

    destructor tp_finalize;

} PyTypeObject;

Now that’s a lot of methods. Don’t worry too much though – if you have a type you want to define, the chances are very good that you will only implement a handful of these.

As you probably expect by now, we’re going to go over this and give more information about the various handlers. We won’t go in the order they are defined in the structure, because there is a lot of historical baggage that impacts the ordering of the fields. It’s often easiest to find an example that includes the fields you need and then change the values to suit your new type.

const char *tp_name; /* For printing */

The name of the type – as mentioned in the previous chapter, this will appear in various places, almost entirely for diagnostic purposes. Try to choose something that will be helpful in such a situation!

Py_ssize_t tp_basicsize, tp_itemsize; /* For allocation */

These fields tell the runtime how much memory to allocate when new objects of this type are created. Python has some built-in support for variable length structures (think: strings, tuples) which is where the tp_itemsize field comes in. This will be dealt with later.

const char *tp_doc;

Here you can put a string (or its address) that you want returned when the Python script references obj.__doc__ to retrieve the doc string.

Now we come to the basic type methods – the ones most extension types will implement.

3.1. Finalization and De-allocation

destructor tp_dealloc;

This function is called when the reference count of the instance of your type is reduced to zero and the Python interpreter wants to reclaim it. If your type has memory to free or other clean-up to perform, you can put it here. The object itself needs to be freed here as well. Here is an example of this function:

static void
newdatatype_dealloc(newdatatypeobject *obj)
{
    free(obj->obj_UnderlyingDatatypePtr);
    Py_TYPE(obj)->tp_free(obj);
}

One important requirement of the deallocator function is that it leaves any pending exceptions alone. This is important since deallocators are frequently called as the interpreter unwinds the Python stack; when the stack is unwound due to an exception (rather than normal returns), nothing is done to protect the deallocators from seeing that an exception has already been set. Any actions which a deallocator performs which may cause additional Python code to be executed may detect that an exception has been set. This can lead to misleading errors from the interpreter. The proper way to protect against this is to save a pending exception before performing the unsafe action, and restoring it when done. This can be done using the PyErr_Fetch() and PyErr_Restore() functions:

static void
my_dealloc(PyObject *obj)
{
    MyObject *self = (MyObject *) obj;
    PyObject *cbresult;

    if (self->my_callback != NULL) {
        PyObject *err_type, *err_value, *err_traceback;

        /* This saves the current exception state */
        PyErr_Fetch(&err_type, &err_value, &err_traceback);

        cbresult = PyObject_CallObject(self->my_callback, NULL);
        if (cbresult == NULL)
            PyErr_WriteUnraisable(self->my_callback);
        else
            Py_DECREF(cbresult);

        /* This restores the saved exception state */
        PyErr_Restore(err_type, err_value, err_traceback);

        Py_DECREF(self->my_callback);
    }
    Py_TYPE(obj)->tp_free((PyObject*)self);
}

Note

There are limitations to what you can safely do in a deallocator function. First, if your type supports garbage collection (using tp_traverse and/or tp_clear), some of the object’s members can have been cleared or finalized by the time tp_dealloc is called. Second, in tp_dealloc, your object is in an unstable state: its reference count is equal to zero. Any call to a non-trivial object or API (as in the example above) might end up calling tp_dealloc again, causing a double free and a crash.

Starting with Python 3.4, it is recommended not to put any complex finalization code in tp_dealloc, and instead use the new tp_finalize type method.

Voir aussi

PEP 442 [https://www.python.org/dev/peps/pep-0442] explains the new finalization scheme.

3.2. Object Presentation

In Python, there are two ways to generate a textual representation of an object: the repr() function, and the str() function. (The print() function just calls str().) These handlers are both optional.

reprfunc tp_repr;
reprfunc tp_str;

The tp_repr handler should return a string object containing a representation of the instance for which it is called. Here is a simple example:

static PyObject *
newdatatype_repr(newdatatypeobject * obj)
{
    return PyUnicode_FromFormat("Repr-ified_newdatatype{{size:%d}}",
                                obj->obj_UnderlyingDatatypePtr->size);
}

If no tp_repr handler is specified, the interpreter will supply a representation that uses the type’s tp_name and a uniquely-identifying value for the object.

The tp_str handler is to str() what the tp_repr handler described above is to repr(); that is, it is called when Python code calls str() on an instance of your object. Its implementation is very similar to the tp_repr function, but the resulting string is intended for human consumption. If tp_str is not specified, the tp_repr handler is used instead.

Here is a simple example:

static PyObject *
newdatatype_str(newdatatypeobject * obj)
{
    return PyUnicode_FromFormat("Stringified_newdatatype{{size:%d}}",
                                obj->obj_UnderlyingDatatypePtr->size);
}

3.3. Attribute Management

For every object which can support attributes, the corresponding type must provide the functions that control how the attributes are resolved. There needs to be a function which can retrieve attributes (if any are defined), and another to set attributes (if setting attributes is allowed). Removing an attribute is a special case, for which the new value passed to the handler is NULL.

Python supports two pairs of attribute handlers; a type that supports attributes only needs to implement the functions for one pair. The difference is that one pair takes the name of the attribute as a char*, while the other accepts a PyObject*. Each type can use whichever pair makes more sense for the implementation’s convenience.

getattrfunc  tp_getattr;        /* char * version */
setattrfunc  tp_setattr;
/* ... */
getattrofunc tp_getattro;       /* PyObject * version */
setattrofunc tp_setattro;

If accessing attributes of an object is always a simple operation (this will be explained shortly), there are generic implementations which can be used to provide the PyObject* version of the attribute management functions. The actual need for type-specific attribute handlers almost completely disappeared starting with Python 2.2, though there are many examples which have not been updated to use some of the new generic mechanism that is available.

3.3.1. Generic Attribute Management

Most extension types only use simple attributes. So, what makes the attributes simple? There are only a couple of conditions that must be met:

The name of the attributes must be known when PyType_Ready() is called.

No special processing is needed to record that an attribute was looked up or set, nor do actions need to be taken based on the value.

Note that this list does not place any restrictions on the values of the attributes, when the values are computed, or how relevant data is stored.

When PyType_Ready() is called, it uses three tables referenced by the type object to create descriptors which are placed in the dictionary of the type object. Each descriptor controls access to one attribute of the instance object. Each of the tables is optional; if all three are NULL, instances of the type will only have attributes that are inherited from their base type, and should leave the tp_getattro and tp_setattro fields NULL as well, allowing the base type to handle attributes.

The tables are declared as three fields of the type object:

struct PyMethodDef *tp_methods;
struct PyMemberDef *tp_members;
struct PyGetSetDef *tp_getset;

If tp_methods is not NULL, it must refer to an array of PyMethodDef structures. Each entry in the table is an instance of this structure:

typedef struct PyMethodDef {
    const char  *ml_name;       /* method name */
    PyCFunction  ml_meth;       /* implementation function */
    int          ml_flags;      /* flags */
    const char  *ml_doc;        /* docstring */
} PyMethodDef;

One entry should be defined for each method provided by the type; no entries are needed for methods inherited from a base type. One additional entry is needed at the end; it is a sentinel that marks the end of the array. The ml_name field of the sentinel must be NULL.

The second table is used to define attributes which map directly to data stored in the instance. A variety of primitive C types are supported, and access may be read-only or read-write. The structures in the table are defined as:

typedef struct PyMemberDef {
    char *name;
    int   type;
    int   offset;
    int   flags;
    char *doc;
} PyMemberDef;

For each entry in the table, a descriptor will be constructed and added to the type which will be able to extract a value from the instance structure. The type field should contain one of the type codes defined in the structmember.h header; the value will be used to determine how to convert Python values to and from C values. The flags field is used to store flags which control how the attribute can be accessed.

The following flag constants are defined in structmember.h; they may be combined using bitwise-OR.

Constante

Signification

READONLY

Never writable.

READ_RESTRICTED

Not readable in restricted mode.

WRITE_RESTRICTED

Not writable in restricted mode.

RESTRICTED

Not readable or writable in restricted mode.

An interesting advantage of using the tp_members table to build descriptors that are used at runtime is that any attribute defined this way can have an associated doc string simply by providing the text in the table. An application can use the introspection API to retrieve the descriptor from the class object, and get the doc string using its __doc__ attribute.

As with the tp_methods table, a sentinel entry with a name value of NULL is required.

3.3.2. Type-specific Attribute Management

For simplicity, only the char* version will be demonstrated here; the type of the name parameter is the only difference between the char* and PyObject* flavors of the interface. This example effectively does the same thing as the generic example above, but does not use the generic support added in Python 2.2. It explains how the handler functions are called, so that if you do need to extend their functionality, you’ll understand what needs to be done.

The tp_getattr handler is called when the object requires an attribute look-up. It is called in the same situations where the __getattr__() method of a class would be called.

Voici un exemple :

static PyObject *
newdatatype_getattr(newdatatypeobject *obj, char *name)
{
    if (strcmp(name, "data") == 0)
    {
        return PyLong_FromLong(obj->data);
    }

    PyErr_Format(PyExc_AttributeError,
                 "'%.50s' object has no attribute '%.400s'",
                 tp->tp_name, name);
    return NULL;
}

The tp_setattr handler is called when the __setattr__() or __delattr__() method of a class instance would be called. When an attribute should be deleted, the third parameter will be NULL. Here is an example that simply raises an exception; if this were really all you wanted, the tp_setattr handler should be set to NULL.

static int
newdatatype_setattr(newdatatypeobject *obj, char *name, PyObject *v)
{
    PyErr_Format(PyExc_RuntimeError, "Read-only attribute: %s", name);
    return -1;
}

3.4. Object Comparison

richcmpfunc tp_richcompare;

The tp_richcompare handler is called when comparisons are needed. It is analogous to the rich comparison methods, like __lt__(), and also called by PyObject_RichCompare() and PyObject_RichCompareBool().

This function is called with two Python objects and the operator as arguments, where the operator is one of Py_EQ, Py_NE, Py_LE, Py_GT, Py_LT or Py_GT. It should compare the two objects with respect to the specified operator and return Py_True or Py_False if the comparison is successful, Py_NotImplemented to indicate that comparison is not implemented and the other object’s comparison method should be tried, or NULL if an exception was set.

Here is a sample implementation, for a datatype that is considered equal if the size of an internal pointer is equal:

static PyObject *
newdatatype_richcmp(PyObject *obj1, PyObject *obj2, int op)
{
    PyObject *result;
    int c, size1, size2;

    /* code to make sure that both arguments are of type
       newdatatype omitted */

    size1 = obj1->obj_UnderlyingDatatypePtr->size;
    size2 = obj2->obj_UnderlyingDatatypePtr->size;

    switch (op) {
    case Py_LT: c = size1 <  size2; break;
    case Py_LE: c = size1 <= size2; break;
    case Py_EQ: c = size1 == size2; break;
    case Py_NE: c = size1 != size2; break;
    case Py_GT: c = size1 >  size2; break;
    case Py_GE: c = size1 >= size2; break;
    }
    result = c ? Py_True : Py_False;
    Py_INCREF(result);
    return result;
 }

3.5. Abstract Protocol Support

Python supports a variety of abstract “protocols;” the specific interfaces provided to use these interfaces are documented in Couche d’abstraction des objets.

A number of these abstract interfaces were defined early in the development of the Python implementation. In particular, the number, mapping, and sequence protocols have been part of Python since the beginning. Other protocols have been added over time. For protocols which depend on several handler routines from the type implementation, the older protocols have been defined as optional blocks of handlers referenced by the type object. For newer protocols there are additional slots in the main type object, with a flag bit being set to indicate that the slots are present and should be checked by the interpreter. (The flag bit does not indicate that the slot values are non-NULL. The flag may be set to indicate the presence of a slot, but a slot may still be unfilled.)

PyNumberMethods   *tp_as_number;
PySequenceMethods *tp_as_sequence;
PyMappingMethods  *tp_as_mapping;

If you wish your object to be able to act like a number, a sequence, or a mapping object, then you place the address of a structure that implements the C type PyNumberMethods, PySequenceMethods, or PyMappingMethods, respectively. It is up to you to fill in this structure with appropriate values. You can find examples of the use of each of these in the Objects directory of the Python source distribution.

hashfunc tp_hash;

This function, if you choose to provide it, should return a hash number for an instance of your data type. Here is a simple example:

static Py_hash_t
newdatatype_hash(newdatatypeobject *obj)
{
    Py_hash_t result;
    result = obj->some_size + 32767 * obj->some_number;
    if (result == -1)
       result = -2;
    return result;
}

Py_hash_t is a signed integer type with a platform-varying width. Returning -1 from tp_hash indicates an error, which is why you should be careful to avoid returning it when hash computation is successful, as seen above.

ternaryfunc tp_call;

This function is called when an instance of your data type is « called », for example, if obj1 is an instance of your data type and the Python script contains obj1('hello'), the tp_call handler is invoked.

This function takes three arguments:

self is the instance of the data type which is the subject of the call. If the call is obj1('hello'), then self is obj1.

args is a tuple containing the arguments to the call. You can use PyArg_ParseTuple() to extract the arguments.

kwds is a dictionary of keyword arguments that were passed. If this is non-NULL and you support keyword arguments, use PyArg_ParseTupleAndKeywords() to extract the arguments. If you do not want to support keyword arguments and this is non-NULL, raise a TypeError with a message saying that keyword arguments are not supported.

Here is a toy tp_call implementation:

static PyObject *
newdatatype_call(newdatatypeobject *self, PyObject *args, PyObject *kwds)
{
    PyObject *result;
    char *arg1;
    char *arg2;
    char *arg3;

    if (!PyArg_ParseTuple(args, "sss:call", &arg1, &arg2, &arg3)) {
        return NULL;
    }
    result = PyUnicode_FromFormat(
        "Returning -- value: [%d] arg1: [%s] arg2: [%s] arg3: [%s]\n",
        obj->obj_UnderlyingDatatypePtr->size,
        arg1, arg2, arg3);
    return result;
}

/* Iterators */
getiterfunc tp_iter;
iternextfunc tp_iternext;

These functions provide support for the iterator protocol. Both handlers take exactly one parameter, the instance for which they are being called, and return a new reference. In the case of an error, they should set an exception and return NULL. tp_iter corresponds to the Python __iter__() method, while tp_iternext corresponds to the Python __next__() method.

Any iterable object must implement the tp_iter handler, which must return an iterator object. Here the same guidelines apply as for Python classes:

For collections (such as lists and tuples) which can support multiple independent iterators, a new iterator should be created and returned by each call to tp_iter.

Objects which can only be iterated over once (usually due to side effects of iteration, such as file objects) can implement tp_iter by returning a new reference to themselves – and should also therefore implement the tp_iternext handler.

Any iterator object should implement both tp_iter and tp_iternext. An iterator’s tp_iter handler should return a new reference to the iterator. Its tp_iternext handler should return a new reference to the next object in the iteration, if there is one. If the iteration has reached the end, tp_iternext may return NULL without setting an exception, or it may set StopIteration in addition to returning NULL; avoiding the exception can yield slightly better performance. If an actual error occurs, tp_iternext should always set an exception and return NULL.

3.6. Weak Reference Support

One of the goals of Python’s weak reference implementation is to allow any type to participate in the weak reference mechanism without incurring the overhead on performance-critical objects (such as numbers).

Voir aussi

Documentation for the weakref module.

For an object to be weakly referencable, the extension type must do two things:

Include a PyObject* field in the C object structure dedicated to the weak reference mechanism. The object’s constructor should leave it NULL (which is automatic when using the default tp_alloc).

Set the tp_weaklistoffset type member to the offset of the aforementioned field in the C object structure, so that the interpreter knows how to access and modify that field.

Concretely, here is how a trivial object structure would be augmented with the required field:

typedef struct {
    PyObject_HEAD
    PyObject *weakreflist;  /* List of weak references */
} TrivialObject;

And the corresponding member in the statically-declared type object:

static PyTypeObject TrivialType = {
    PyVarObject_HEAD_INIT(NULL, 0)
    /* ... other members omitted for brevity ... */
    .tp_weaklistoffset = offsetof(TrivialObject, weakreflist),
};

The only further addition is that tp_dealloc needs to clear any weak references (by calling PyObject_ClearWeakRefs()) if the field is non-NULL:

static void
Trivial_dealloc(TrivialObject *self)
{
    /* Clear weakrefs first before calling any destructors */
    if (self->weakreflist != NULL)
        PyObject_ClearWeakRefs((PyObject *) self);
    /* ... remainder of destruction code omitted for brevity ... */
    Py_TYPE(self)->tp_free((PyObject *) self);
}

3.7. More Suggestions

In order to learn how to implement any specific method for your new data type, get the CPython source code. Go to the Objects directory, then search the C source files for tp_ plus the function you want (for example, tp_richcompare). You will find examples of the function you want to implement.

When you need to verify that an object is a concrete instance of the type you are implementing, use the PyObject_TypeCheck() function. A sample of its use might be something like the following:

if (!PyObject_TypeCheck(some_object, &MyType)) {
    PyErr_SetString(PyExc_TypeError, "arg #1 not a mything");
    return NULL;
}

Voir aussi

Download CPython source releases.

https://www.python.org/downloads/source/

The CPython project on GitHub, where the CPython source code is developed.

https://github.com/python/cpython

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4. Construire des extensions C et C++

Une extension C pour CPython est une bibliothèque partagée (Un .so sur Linux, un .pyd sur Windows), qui expose une fonction d’initialisation.

Pour pouvoir être importée, la bibliothèque partagée doit pourvoir être trouvée dans PYTHONPATH, et doit porter le nom du module, avec l’extension appropriée. En utilisant distutils, le nom est généré automatiquement.

La fonction d’initialisation doit avoir le prototype :

PyObject* PyInit_modulename(void)

Elle doit donner soit un module entièrement initialisé, soit une instance de PyModuleDef. Voir Initializing C modules pour plus de détails.

Pour les modules dont les noms sont entièrement en ASCII, la fonction doit être nommée PyInit_<modulename>, dont <modulename> est remplacé par le nom du module. En utilisant Multi-phase initialization, il est possible d’utiliser des noms de modules comptant des caractères non ASCII. Dans ce cas, le nom de la fonction d’initialisation est PyInitU_<modulename>, où modulename est encodé avec l’encodage punyencode de Python, dont les tirets sont remplacés par des tirets-bas. En Python ça donne :

def initfunc_name(name):
    try:
        suffix = b'_' + name.encode('ascii')
    except UnicodeEncodeError:
        suffix = b'U_' + name.encode('punycode').replace(b'-', b'_')
    return b'PyInit' + suffix

Il est possible d’exporter plusieurs modules depuis une seule bibliothèque partagée en définissant plusieurs fonctions d’initialisation. Cependant pour les importer, un lien symbolique doit être créé pour chacun, ou un importer personnalisé, puisque par défaut seule la fonction correspondant au nom du fichier est cherchée. Voir le chapitre « Multiple modules in one library » dans la PEP 489 [https://www.python.org/dev/peps/pep-0489] pour plus d’informations.

4.1. Construire les extensions C et C++ avec distutils

Des modules d’extension peuvent être construits avec distutils, qui est inclus dans Python. Puisque distutils gère aussi la création de paquets binaires, les utilisateurs n’auront pas nécessairement besoin ni d’un compilateur ni de distutils pour installer l’extension.

Un paquet distutils contient un script setup.py. C’est un simple fichier Python, ressemblant dans la plupart des cas à :

from distutils.core import setup, Extension

module1 = Extension('demo',
                    sources = ['demo.c'])

setup (name = 'PackageName',
       version = '1.0',
       description = 'This is a demo package',
       ext_modules = [module1])

Avec ce setup.py et un fichier demo.c, lancer

python setup.py build

compilera demo.c, et produira un module d’extension nommé demo dans le dossier build. En fonction du système, le fichier du module peut se retrouver dans build/lib.system, et son nom peut être demo.py ou demo.pyd.

Dans le fichier setup.py, tout est exécuté en appelant la fonction setup. Elle prend un nombre variable d’arguments nommés, dont l’exemple précédent n’utilise qu’une partie. L’exemple précise des méta-informations pour construire les paquets, et définir le contenu du paquet. Normalement un paquet contient des modules additionnels, comme des modules sources, documentation, sous paquets, etc. Referez-vous à la documentation de distutils dans Distribuer des modules Python (Version historique) pour en apprendre plus sur les fonctionnalités de distutils. Cette section n’explique que la construction de modules d’extension.

Il est classique de pré-calculer les arguments à la fonction setup(), pour plus de lisibilité. Dans l’exemple ci-dessus, l’argument ext_modules à setup() est une liste de modules d’extension, chacun est une instance de la classe Extension. Dans l’exemple, l’instance définit une extension nommée demo construite par la compilation d’un seul fichier source demo.c.

Dans la plupart des cas, construire une extension est plus complexe à cause des bibliothèques et définitions de préprocesseurs dont la compilation pourrait dépendre. C’est ce qu’on remarque dans l’exemple plus bas.

from distutils.core import setup, Extension

module1 = Extension('demo',
                    define_macros = [('MAJOR_VERSION', '1'),
                                     ('MINOR_VERSION', '0')],
                    include_dirs = ['/usr/local/include'],
                    libraries = ['tcl83'],
                    library_dirs = ['/usr/local/lib'],
                    sources = ['demo.c'])

setup (name = 'PackageName',
       version = '1.0',
       description = 'This is a demo package',
       author = 'Martin v. Loewis',
       author_email = 'martin@v.loewis.de',
       url = 'https://docs.python.org/extending/building',
       long_description = '''
This is really just a demo package.
''',
       ext_modules = [module1])

Dans cet exemple, la fonction setup() est appelée avec quelques autres méta-informations, ce qui est recommandé pour distribuer des paquets. En ce qui concerne l’extension, sont définis quelques macros préprocesseur, dossiers pour les en-têtes et bibliothèques. En fonction du compilateur, distutils peut donner ces informations de manière différente. Par exemple, sur Unix, ça peut ressembler aux commandes

gcc -DNDEBUG -g -O3 -Wall -Wstrict-prototypes -fPIC -DMAJOR_VERSION=1 -DMINOR_VERSION=0 -I/usr/local/include -I/usr/local/include/python2.2 -c demo.c -o build/temp.linux-i686-2.2/demo.o

gcc -shared build/temp.linux-i686-2.2/demo.o -L/usr/local/lib -ltcl83 -o build/lib.linux-i686-2.2/demo.so

Ces lignes ne sont qu’à titre d’exemple, les utilisateurs de distutils doivent avoir confiance en distutils qui fera les appels correctement.

4.2. Distribuer vos modules d’extension

Lorsqu’une extension a été construite avec succès, il existe trois moyens de l’utiliser.

Typiquement, les utilisateurs vont vouloir installer le module, ils le font en exécutant

python setup.py install

Les mainteneurs de modules voudront produire des paquets source, pour ce faire ils exécuteront

python setup.py sdist

Dans certains cas, des fichiers supplémentaires doivent être inclus dans une distribution source : c’est possible via un fichier MANIFEST.in, c.f. Spécifier les fichiers à distribuer.

Si la distribution source a été construite avec succès, les mainteneurs peuvent créer une distribution binaire. En fonction de la plateforme, une des commandes suivantes peut être utilisée.

python setup.py bdist_wininst
python setup.py bdist_rpm
python setup.py bdist_dumb

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5. Construire des extensions C et C++ sur Windows

Cette page explique rapidement comment créer un module d’extension Windows pour Python en utilisant Microsoft Visual C++, et donne plus d’informations contextuelles sur son fonctionnement. Le texte explicatif est utile tant pour le développeur Windows qui apprend à construire des extensions Python que pour le développeur Unix souhaitant produire des logiciels pouvant être construits sur Unix et Windows.

Les auteurs de modules sont invités à utiliser l’approche distutils pour construire des modules d’extension, au lieu de celle décrite dans cette section. Vous aurez toujours besoin du compilateur C utilisé pour construire Python ; typiquement Microsoft Visual C++.

Note

Cette page mentionne plusieurs noms de fichiers comprenant un numéro de version Python encodé. Ces noms de fichiers sont construits sous le format de version XY ; en pratique, 'X' représente le numéro de version majeure et 'Y' représente le numéro de version mineure de la version Python avec laquelle vous travaillez. Par exemple, si vous utilisez Python 2.2.1, XY correspond à 22.

5.1. Une approche « recette de cuisine »

Il y a deux approches lorsque l’on construit des modules d’extension sur Windows, tout comme sur Unix : utiliser le paquet distutils pour contrôler le processus de construction, ou faire les choses manuellement. L’approche distutils fonctionne bien pour la plupart des extensions ; la documentation pour utiliser distutils pour construire et empaqueter les modules d’extension est disponible dans Distribuer des modules Python (Version historique). Si vous considérez que vous avez réellement besoin de faire les choses manuellement, il pourrait être enrichissant d’étudier le fichier de projet winsound [https://github.com/python/cpython/tree/3.6/PCbuild/winsound.vcxproj] pour le module de la bibliothèque standard.

5.2. Différences entre Unix et Windows

Unix et Windows utilisent des paradigmes complètement différents pour le chargement du code pendant l’exécution. Avant d’essayer de construire un module qui puisse être chargé dynamiquement, soyez conscient du mode de fonctionnement du système.

Sur Unix, un fichier objet partagé (.so) contient du code servant au programme, ainsi que les noms des fonctions et les données que l’on s’attend à trouver dans le programme. Quand le fichier est attaché au programme, toutes les références à ces fonctions et données dans le code du fichier sont modifiées pour pointer vers les localisations actuelles dans le programme où sont désormais placées les fonctions et données dans la mémoire. C’est tout simplement une opération de liaison.

Sur Windows, un fichier bibliothèque de liens dynamiques (.dll) n’a pas de références paresseuses. A la place, un accès aux fonctions ou données passe par une table de conversion. Cela est fait pour que le code DLL ne doive pas être réarrangé à l’exécution pour renvoyer à la mémoire du programme ; à la place, le code utilise déjà la table de conversion DLL, et cette table est modifiée à l’exécution pour pointer vers les fonctions et données.

Sur Unix, il n’y a qu’un type de bibliothèque de fichier (.a) qui contient du code venant de plusieurs fichiers objets (.o). Durant l’étape de liaison pour créer un fichier objet partagé (.so), le lieur peut informer qu’il ne sait pas où un identificateur est défini. Le lieur le cherchera dans les fichiers objet dans les bibliothèques ; s’il le trouve, il inclura tout le code provenant de ce fichier objet.

Sur Windows, il y a deux types de bibliothèques, une bibliothèque statique et une bibliothèque d’importation (toutes deux appelées .lib). Une bibliothèque statique est comme un fichier Unix .a ; elle contient du code pouvant être inclus si nécessaire. Une bibliothèque d’importation est uniquement utilisée pour rassurer le lieur qu’un certain identificateur est légal, et sera présent dans le programme quand la DLL est chargée. Comme ça le lieur utilise les informations provenant de la bibliothèque d’importation pour construire la table de conversion pour utiliser les identificateurs qui ne sont pas inclus dans la DLL. Quand une application ou une DLL est liée, une bibliothèque d’importation peut être générée, qui devra être utilisée pour toutes les futures DLL dépendantes aux symboles provenant de l’application ou de la DLL.

Supposons que vous construisez deux modules de chargement dynamiques, B et C, qui ne devraient pas partager un autre bloc de code avec A. Sur Unix, vous ne transmettrez pas A.a au lieur pour B.so et C.so ; cela le ferait être inclus deux fois, pour que B et C aient chacun leur propre copie. Sur Windows, construire A.dll construira aussi A.lib. Vous transmettez A.lib au lieur pour B et C. A.lib ne contient pas de code ; il contient uniquement des informations qui seront utilisées lors de l’exécution pour accéder au code de A.

Sur Windows, utiliser une bibliothèque d’importation est comme utiliser import spam; cela vous donne accès aux noms des spams, mais ne crée par de copie séparée. Sur Unix, se lier à une bibliothèque est plus comme from spam import * ; cela crée une copie séparée.

5.3. Utiliser les DLL en pratique

Le Python de Windows est construit en Microsoft Visual C++ ; utiliser d’autres compilateurs pourrait fonctionner, ou pas (cependant Borland a l’air de fonctionner). Le reste de cette section est spécifique à MSVC++.

Lorsque vous créez des DLL sur Windows, vous devez transmettre pythonXY.lib au lieur. Pour construire deux DLL, spam et ni (qui utilisent des fonctions C trouvées dans spam), vous pouvez utiliser ces commandes :

cl /LD /I/python/include spam.c ../libs/pythonXY.lib
cl /LD /I/python/include ni.c spam.lib ../libs/pythonXY.lib

La première commande a créé trois fichiers : spam.obj, spam.dll et spam.lib. Spam.dll ne contient pas de fonctions Python (telles que PyArg_ParseTuple()), mais il sait comment trouver le code Python grâce à pythonXY.lib.

La seconde commande a créé ni.dll (et .obj et .lib), qui sait comment trouver les fonctions nécessaires dans spam, ainsi qu’à partir de l’exécutable Python.

Chaque identificateur n’est pas exporté vers la table de conversion. Si vous voulez que tout autre module (y compris Python) soit capable de voir vos identificateurs, vous devez préciser _declspec(dllexport), comme dans void _declspec(dllexport) initspam(void) ou PyObject _declspec(dllexport) *NiGetSpamData(void).

Developer Studio apportera beaucoup de bibliothèques d’importation dont vous n’avez pas vraiment besoin, augmentant d’environ 100ko votre exécutable. Pour s’en débarrasser, allez dans les Paramètres du Projet, onglet Lien, pour préciser ignorer les bibliothèques par défaut. Et la msvcrtxx.lib correcte à la liste des bibliothèques.

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1. Intégrer Python dans une autre application

Les chapitres précédents couvraient l’extension de Python, c’est-à-dire, comment enrichir une fonctionnalité de Python en y attachant une bibliothèque de fonctions C. C’est aussi possible dans l’autre sens : enrichir vos applications C/C++ en y intégrant Python. Intégrer Python vous permet d’implémenter certaines fonctionnalités de vos applications en Python plutôt qu’en C ou C++. C’est utile dans de nombreux cas, un exemple serait de permettre aux utilisateurs d’adapter une application à leurs besoins en y écrivant des scripts Python. Vous pouvez aussi l’utiliser vous même si certaines fonctionnalités peuvent être rédigées plus facilement en Python.

Intégrer et étendre Python sont des tâches presque identiques. La différence est qu’en étendant Python, le programme principal reste l’interpréteur Python, alors qu’en intégrant Python le programme principal peut ne rien à voir avec Python. C’est simplement quelques parties du programme qui appellent l’interpréteur Python pour exécuter un peu de code Python.

En intégrant Python, vous fournissez le programme principal. L’une de ses tâches sera d’initialiser l’interpréteur. Au minimum vous devrez appeler Py_Initialize(). Il est possible, avec quelques appels supplémentaires, de passer des options à Python. Ensuite vous pourrez appeler l’interpréteur depuis n’importe quelle partie de votre programme.

Il existe différents moyens d’appeler l’interpréteur : vous pouvez donner une chaîne contenant des instructions Python à PyRun_SimpleString(), ou vous pouvez donner un pointeur de fichier stdio et un nom de fichier (juste pour nommer les messages d’erreur) à PyRunSimpleFile(). Vous pouvez aussi appeler les API de bas niveau décrites dans les chapitres précédents pour construire et utiliser des objets Python.

Voir aussi

Manuel de référence de l’API Python/C

Les détails sur l’interface entre Python et le C sont donnés dans ce manuel. Pléthore informations s’y trouvent.

1.1. Intégration de très haut niveau

La manière la plus simple d’intégrer Python est d’utiliser une interface de très haut niveau. Cette interface a pour but d’exécuter un script Python sans avoir à interagir avec directement. C’est utile, par exemple, pour effectuer une opération sur un fichier.

#include <Python.h>

int
main(int argc, char *argv[])
{
    wchar_t *program = Py_DecodeLocale(argv[0], NULL);
    if (program == NULL) {
        fprintf(stderr, "Fatal error: cannot decode argv[0]\n");
        exit(1);
    }
    Py_SetProgramName(program);  /* optional but recommended */
    Py_Initialize();
    PyRun_SimpleString("from time import time,ctime\n"
                       "print('Today is', ctime(time()))\n");
    if (Py_FinalizeEx() < 0) {
        exit(120);
    }
    PyMem_RawFree(program);
    return 0;
}

C’est la fonction Py_SetProgramName() qui devrait être appelée en premier, avant Py_Initialize(), afin d’informer l’interpréteur des chemins vers ses bibliothèques. Ensuite l’interpréteur est initialisé par Py_Initialize(), suivi de l’exécution de Python codé en dur affichant la date et l’heure, puis, l’appel à Py_FinalizeEx() éteint l’interpréteur, engendrant ainsi la fin du programme. Dans un vrai programme, vous pourriez vouloir lire le script Python depuis une autre source, peut être depuis un éditeur de texte, un fichier, ou une base de donnée. Récupérer du code Python depuis un fichier se fait via PyRun_SimplFile(), qui vous économise le travail d’allouer de la mémoire et de charger le contenu du fichier.

1.2. Au-delà de l’intégration de haut niveau : survol

L’interface de haut niveau vous permet d’exécuter n’importe quel morceau de code Python depuis votre application, mais échanger des données est quelque peu alambiqué. Si c’est ce dont vous avez besoin, vous devez utiliser des appels de niveau plus bas. Il vous en coûtera plus de lignes de C à écrire, mais vous pourrez presque tout faire.

Il est à souligner qu’étendre ou intégrer Python revient à la louche au même, en dépit de la différence d’intention. La plupart des sujets parcourus dans les chapitres précédents sont toujours valides. Pour le prouver, regardez ce qu’un code d’extension de Python vers C fait réellement :

Convertir des valeurs de Python vers le C,

Appeler une fonction C en utilisant les valeurs converties, et

Convertir les résultats de l’appel à la fonction C pour Python.

Lors de l’intégration de Python, le code de l’interface fait :

Convertir les valeurs depuis le C vers Python,

Effectuer un appel de fonction de l’interface Python en utilisant les valeurs converties, et

Convertir les valeurs de l’appel Python pour le C.

Tel que vous le voyez, les conversions sont simplement inversées pour s’adapter aux différentes directions de transfert inter-langage. La seule différence est la fonction que vous appelez entre les deux conversions de données. Lors de l’extension, vous appelez une fonction C, lors de l’intégration vous appelez une fonction Python.

Ce chapitre ne couvrira pas la conversion des données de Python vers le C ni l’inverse. Aussi, un usage correct des références, ainsi que savoir gérer les erreurs sont considérés acquis. Ces aspects étant identiques à l’extension de l’interpréteur, vous pouvez vous référer aux chapitres précédents.

1.3. Intégration pure

L’objectif du premier programme est d’exécuter une fonction dans un script Python. Comme dans la section à propos des interfaces de haut niveau, l’interpréteur n’interagit pas directement avec l’application (mais le fera dans la section suivante).

Le code pour appeler une fonction définie dans un script Python est :

#include <Python.h>

int
main(int argc, char *argv[])
{
    PyObject *pName, *pModule, *pFunc;
    PyObject *pArgs, *pValue;
    int i;

    if (argc < 3) {
        fprintf(stderr,"Usage: call pythonfile funcname [args]\n");
        return 1;
    }

    Py_Initialize();
    pName = PyUnicode_DecodeFSDefault(argv[1]);
    /* Error checking of pName left out */

    pModule = PyImport_Import(pName);
    Py_DECREF(pName);

    if (pModule != NULL) {
        pFunc = PyObject_GetAttrString(pModule, argv[2]);
        /* pFunc is a new reference */

        if (pFunc && PyCallable_Check(pFunc)) {
            pArgs = PyTuple_New(argc - 3);
            for (i = 0; i < argc - 3; ++i) {
                pValue = PyLong_FromLong(atoi(argv[i + 3]));
                if (!pValue) {
                    Py_DECREF(pArgs);
                    Py_DECREF(pModule);
                    fprintf(stderr, "Cannot convert argument\n");
                    return 1;
                }
                /* pValue reference stolen here: */
                PyTuple_SetItem(pArgs, i, pValue);
            }
            pValue = PyObject_CallObject(pFunc, pArgs);
            Py_DECREF(pArgs);
            if (pValue != NULL) {
                printf("Result of call: %ld\n", PyLong_AsLong(pValue));
                Py_DECREF(pValue);
            }
            else {
                Py_DECREF(pFunc);
                Py_DECREF(pModule);
                PyErr_Print();
                fprintf(stderr,"Call failed\n");
                return 1;
            }
        }
        else {
            if (PyErr_Occurred())
                PyErr_Print();
            fprintf(stderr, "Cannot find function \"%s\"\n", argv[2]);
        }
        Py_XDECREF(pFunc);
        Py_DECREF(pModule);
    }
    else {
        PyErr_Print();
        fprintf(stderr, "Failed to load \"%s\"\n", argv[1]);
        return 1;
    }
    if (Py_FinalizeEx() < 0) {
        return 120;
    }
    return 0;
}

Ce code charge un script Python en utilisant argv[1], et appelle une fonction dont le nom est dans argv[2]. Ses arguments entiers sont les autres valeurs de argv. Si vous compilez et liez ce programme (appelons l’exécutable call), et l’appelez pour exécuter un script Python, tel que :

def multiply(a,b):
    print("Will compute", a, "times", b)
    c = 0
    for i in range(0, a):
        c = c + b
    return c

alors, le résultat sera :

$ call multiply multiply 3 2
Will compute 3 times 2
Result of call: 6

Bien que le programme soit plutôt gros pour ses fonctionnalités, la plupart du code n’est que conversion de données entre Python et C, aussi que pour rapporter les erreurs. La partie intéressante, qui concerne l’intégration de Python débute par

Py_Initialize();
pName = PyUnicode_DecodeFSDefault(argv[1]);
/* Error checking of pName left out */
pModule = PyImport_Import(pName);

Après avoir initialisé l’interpréteur, le script est chargé en utilisant PyImport_Import(). Cette fonction prend une chaîne Python pour argument, elle-même construite en utilisant la fonction de conversion PyUnicode_FromString().

pFunc = PyObject_GetAttrString(pModule, argv[2]);
/* pFunc is a new reference */

if (pFunc && PyCallable_Check(pFunc)) {
    ...
}
Py_XDECREF(pFunc);

Une fois le script chargé, le nom recherché est obtenu en utilisant PyObject_GetAttrString(). Si le nom existe, et que l’objet récupéré peut être appelé, vous pouvez présumer sans risque que c’est une fonction. Le programme continue, classiquement, par la construction de n-uplet d’arguments. L’appel à la fonction Python est alors effectué avec :

pValue = PyObject_CallObject(pFunc, pArgs);

Après l’exécution de la fonction, pValue est soit NULL, soit une référence sur la valeur donnée par la fonction. Assurez-vous de libérer la référence après avoir utilisé la valeur.

1.4. Étendre un Python intégré

Jusqu’à présent, l’interpréteur Python intégré n’avait pas accès aux fonctionnalités de l’application elle-même. L’API Python le permet en étendant l’interpréteur intégré. Autrement dit, l’interpréteur intégré est étendu avec des fonctions fournies par l’application. Bien que cela puisse sembler complexe, ce n’est pas si dur. Il suffit d’oublier que l’application démarre l’interpréteur Python, au lieu de cela, voyez l’application comme un ensemble de fonctions, et rédigez un peu de code pour exposer ces fonctions à Python, tout comme vous écririez une extension Python normale. Par exemple :

static int numargs=0;

/* Return the number of arguments of the application command line */
static PyObject*
emb_numargs(PyObject *self, PyObject *args)
{
    if(!PyArg_ParseTuple(args, ":numargs"))
        return NULL;
    return PyLong_FromLong(numargs);
}

static PyMethodDef EmbMethods[] = {
    {"numargs", emb_numargs, METH_VARARGS,
     "Return the number of arguments received by the process."},
    {NULL, NULL, 0, NULL}
};

static PyModuleDef EmbModule = {
    PyModuleDef_HEAD_INIT, "emb", NULL, -1, EmbMethods,
    NULL, NULL, NULL, NULL
};

static PyObject*
PyInit_emb(void)
{
    return PyModule_Create(&EmbModule);
}

Insérez le code ci-dessus juste avant la fonction main(). Ajoutez aussi les deux instructions suivantes avant l’appel à Py_Initialize() :

numargs = argc;
PyImport_AppendInittab("emb", &PyInit_emb);

Ces deux lignes initialisent la variable numarg, et rend la fonction emb.numargs() accessible à l’interpréteur intégré. Avec ces ajouts, le script Python petit maintenant faire des choses comme

import emb
print("Number of arguments", emb.numargs())

Dans un cas réel, les méthodes exposeraient une API de l’application à Python.

1.5. Intégrer Python dans du C++

Il est aussi possible d’intégrer Python dans un programme en C++, la manière exacte dont cela se fait dépend de détails du système C++ utilisé. En général vous écrirez le programme principal en C++, utiliserez un compilateur C++ pour compiler et lier votre programme. Il n’y a pas besoin de recompiler Python en utilisant C++.

1.6. Compiler et Lier en environnement Unix ou similaire

Ce n’est pas évident de trouver les bonnes options à passer au compilateur (et linker) pour intégrer l’interpréteur Python dans une application, Python ayant besoin de charger des extensions sous forme de bibliothèques dynamiques en C (des .so) pour se lier avec.

Pour trouver les bonnes options de compilateur et linker, vous pouvez exécuter le script python(X.Y)-config généré durant l’installation (un script python3-config peut aussi être disponible). Ce script a quelques options, celles-ci vous seront utiles :

pythonX.Y-config --cflags vous donnera les options recommandées pour compiler :

$ /opt/bin/python3.4-config --cflags
-I/opt/include/python3.4m -I/opt/include/python3.4m -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes

pythonX.Y-config --ldflags vous donnera les drapeaux recommandés lors de l’édition de lien :

$ /opt/bin/python3.4-config --ldflags
-L/opt/lib/python3.4/config-3.4m -lpthread -ldl -lutil -lm -lpython3.4m -Xlinker -export-dynamic

Note

Pour éviter la confusion entre différentes installations de Python, (et plus spécialement entre celle de votre système et votre version compilée), il est recommandé d’utiliser un chemin absolu vers pythonX.Y-config, comme dans l’exemple précédent.

Si cette procédure ne fonctionne pas pour vous (il n’est pas garanti qu’elle fonctionne pour toutes les plateformes Unix, mais nous traiteront volontiers les rapports de bugs), vous devrez lire la documentation de votre système sur la liaison dynamique (dynamic linking) et / ou examiner le Makefile de Python (utilisez sysconfig.get_makefile_filename() pour trouver son emplacement) et les options de compilation. Dans ce cas, le module sysconfig est un outil utile pour extraire automatiquement les valeurs de configuration que vous voudrez combiner ensemble. Par exemple :

>>> import sysconfig
>>> sysconfig.get_config_var('LIBS')
'-lpthread -ldl  -lutil'
>>> sysconfig.get_config_var('LINKFORSHARED')
'-Xlinker -export-dynamic'

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Manuel de référence de l’API Python/C

C’est la documentation de l’API utilisée par les développeurs C et C++ écrivant des modules d’extension ou intégrant Python. Elle va de pair avec Extension et intégration de l’interpréteur Python, qui décrit les principes généraux de l’écriture d’extensions, mais ne rentre pas dans les détails de chaque fonction de l’API.

Introduction

Include Files

Objects, Types and Reference Counts

Exceptions

Embarquer Python

Debugging Builds

ABI Stable

The Very High Level Layer

Reference Counting

Gestion des exceptions

Printing and clearing

Lever des exceptions

Issuing warnings

Querying the error indicator

Traitement des signaux

Exception Classes

Objets exception

Objets exception Unicode

Contrôle de la récursion

Exceptions standards

Standard Warning Categories

Utilitaires

Operating System Utilities

System Functions

Process Control

Importer des modules

Data marshalling support

Analyse des arguments et construction des valeurs

Conversion et formatage de chaînes

Réflexion

Codec registry and support functions

Couche d’abstraction des objets

Protocole Objet

Number Protocol

Sequence Protocol

Mapping Protocol

Protocole d’itération

Protocole tampon

Ancien Buffer Protocol

Couche des objets concrets

Objets fondamentaux

Objets numériques

Objets séquences

Objets conteneurs

Objets fonctions

Autres objets

Initialization, Finalization, and Threads

Initializing and finalizing the interpreter

Process-wide parameters

Thread State and the Global Interpreter Lock

Sub-interpreter support

Asynchronous Notifications

Profiling and Tracing

Support avancé du débogueur

Memory Management

Aperçu

Raw Memory Interface

Memory Interface

Object allocators

Customize Memory Allocators

The pymalloc allocator

Exemples

Implémentation d’objets

Allouer des objets dans le tas

Common Object Structures

Objets type

Number Object Structures

Mapping Object Structures

Sequence Object Structures

Buffer Object Structures

Async Object Structures

Supporting Cyclic Garbage Collection

Version des API et ABI

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Introduction

The Application Programmer’s Interface to Python gives C and C++ programmers access to the Python interpreter at a variety of levels. The API is equally usable from C++, but for brevity it is generally referred to as the Python/C API. There are two fundamentally different reasons for using the Python/C API. The first reason is to write extension modules for specific purposes; these are C modules that extend the Python interpreter. This is probably the most common use. The second reason is to use Python as a component in a larger application; this technique is generally referred to as embedding Python in an application.

Writing an extension module is a relatively well-understood process, where a « cookbook » approach works well. There are several tools that automate the process to some extent. While people have embedded Python in other applications since its early existence, the process of embedding Python is less straightforward than writing an extension.

Many API functions are useful independent of whether you’re embedding or extending Python; moreover, most applications that embed Python will need to provide a custom extension as well, so it’s probably a good idea to become familiar with writing an extension before attempting to embed Python in a real application.

Include Files

All function, type and macro definitions needed to use the Python/C API are included in your code by the following line:

#include "Python.h"

This implies inclusion of the following standard headers: <stdio.h>, <string.h>, <errno.h>, <limits.h>, <assert.h> and <stdlib.h> (if available).

Note

Python pouvant définir certaines définitions pré-processeur qui affectent les têtes standard sur certains systèmes, vous devez inclure Python.h avant les en-têtes standards.

All user visible names defined by Python.h (except those defined by the included standard headers) have one of the prefixes Py or _Py. Names beginning with _Py are for internal use by the Python implementation and should not be used by extension writers. Structure member names do not have a reserved prefix.

Important: user code should never define names that begin with Py or _Py. This confuses the reader, and jeopardizes the portability of the user code to future Python versions, which may define additional names beginning with one of these prefixes.

The header files are typically installed with Python. On Unix, these are located in the directories prefix/include/pythonversion/ and exec_prefix/include/pythonversion/, where prefix and exec_prefix are defined by the corresponding parameters to Python’s configure script and version is '%d.%d' % sys.version_info[:2]. On Windows, the headers are installed in prefix/include, where prefix is the installation directory specified to the installer.

To include the headers, place both directories (if different) on your compiler’s search path for includes. Do not place the parent directories on the search path and then use #include <pythonX.Y/Python.h>; this will break on multi-platform builds since the platform independent headers under prefix include the platform specific headers from exec_prefix.

C++ users should note that though the API is defined entirely using C, the header files do properly declare the entry points to be extern "C", so there is no need to do anything special to use the API from C++.

Objects, Types and Reference Counts

Most Python/C API functions have one or more arguments as well as a return value of type PyObject*. This type is a pointer to an opaque data type representing an arbitrary Python object. Since all Python object types are treated the same way by the Python language in most situations (e.g., assignments, scope rules, and argument passing), it is only fitting that they should be represented by a single C type. Almost all Python objects live on the heap: you never declare an automatic or static variable of type PyObject, only pointer variables of type PyObject* can be declared. The sole exception are the type objects; since these must never be deallocated, they are typically static PyTypeObject objects.

All Python objects (even Python integers) have a type and a reference count. An object’s type determines what kind of object it is (e.g., an integer, a list, or a user-defined function; there are many more as explained in Hiérarchie des types standards). For each of the well-known types there is a macro to check whether an object is of that type; for instance, PyList_Check(a) is true if (and only if) the object pointed to by a is a Python list.

Reference Counts

The reference count is important because today’s computers have a finite (and often severely limited) memory size; it counts how many different places there are that have a reference to an object. Such a place could be another object, or a global (or static) C variable, or a local variable in some C function. When an object’s reference count becomes zero, the object is deallocated. If it contains references to other objects, their reference count is decremented. Those other objects may be deallocated in turn, if this decrement makes their reference count become zero, and so on. (There’s an obvious problem with objects that reference each other here; for now, the solution is « don’t do that. »)

Reference counts are always manipulated explicitly. The normal way is to use the macro Py_INCREF() to increment an object’s reference count by one, and Py_DECREF() to decrement it by one. The Py_DECREF() macro is considerably more complex than the incref one, since it must check whether the reference count becomes zero and then cause the object’s deallocator to be called. The deallocator is a function pointer contained in the object’s type structure. The type-specific deallocator takes care of decrementing the reference counts for other objects contained in the object if this is a compound object type, such as a list, as well as performing any additional finalization that’s needed. There’s no chance that the reference count can overflow; at least as many bits are used to hold the reference count as there are distinct memory locations in virtual memory (assuming sizeof(Py_ssize_t) >= sizeof(void*)). Thus, the reference count increment is a simple operation.

It is not necessary to increment an object’s reference count for every local variable that contains a pointer to an object. In theory, the object’s reference count goes up by one when the variable is made to point to it and it goes down by one when the variable goes out of scope. However, these two cancel each other out, so at the end the reference count hasn’t changed. The only real reason to use the reference count is to prevent the object from being deallocated as long as our variable is pointing to it. If we know that there is at least one other reference to the object that lives at least as long as our variable, there is no need to increment the reference count temporarily. An important situation where this arises is in objects that are passed as arguments to C functions in an extension module that are called from Python; the call mechanism guarantees to hold a reference to every argument for the duration of the call.

However, a common pitfall is to extract an object from a list and hold on to it for a while without incrementing its reference count. Some other operation might conceivably remove the object from the list, decrementing its reference count and possible deallocating it. The real danger is that innocent-looking operations may invoke arbitrary Python code which could do this; there is a code path which allows control to flow back to the user from a Py_DECREF(), so almost any operation is potentially dangerous.

A safe approach is to always use the generic operations (functions whose name begins with PyObject_, PyNumber_, PySequence_ or PyMapping_). These operations always increment the reference count of the object they return. This leaves the caller with the responsibility to call Py_DECREF() when they are done with the result; this soon becomes second nature.

Reference Count Details

The reference count behavior of functions in the Python/C API is best explained in terms of ownership of references. Ownership pertains to references, never to objects (objects are not owned: they are always shared). « Owning a reference » means being responsible for calling Py_DECREF on it when the reference is no longer needed. Ownership can also be transferred, meaning that the code that receives ownership of the reference then becomes responsible for eventually decref’ing it by calling Py_DECREF() or Py_XDECREF() when it’s no longer needed—or passing on this responsibility (usually to its caller). When a function passes ownership of a reference on to its caller, the caller is said to receive a new reference. When no ownership is transferred, the caller is said to borrow the reference. Nothing needs to be done for a borrowed reference.

Conversely, when a calling function passes in a reference to an object, there are two possibilities: the function steals a reference to the object, or it does not. Stealing a reference means that when you pass a reference to a function, that function assumes that it now owns that reference, and you are not responsible for it any longer.

Few functions steal references; the two notable exceptions are PyList_SetItem() and PyTuple_SetItem(), which steal a reference to the item (but not to the tuple or list into which the item is put!). These functions were designed to steal a reference because of a common idiom for populating a tuple or list with newly created objects; for example, the code to create the tuple (1, 2, "three") could look like this (forgetting about error handling for the moment; a better way to code this is shown below):

PyObject *t;

t = PyTuple_New(3);
PyTuple_SetItem(t, 0, PyLong_FromLong(1L));
PyTuple_SetItem(t, 1, PyLong_FromLong(2L));
PyTuple_SetItem(t, 2, PyUnicode_FromString("three"));

Here, PyLong_FromLong() returns a new reference which is immediately stolen by PyTuple_SetItem(). When you want to keep using an object although the reference to it will be stolen, use Py_INCREF() to grab another reference before calling the reference-stealing function.

Incidentally, PyTuple_SetItem() is the only way to set tuple items; PySequence_SetItem() and PyObject_SetItem() refuse to do this since tuples are an immutable data type. You should only use PyTuple_SetItem() for tuples that you are creating yourself.

Equivalent code for populating a list can be written using PyList_New() and PyList_SetItem().

However, in practice, you will rarely use these ways of creating and populating a tuple or list. There’s a generic function, Py_BuildValue(), that can create most common objects from C values, directed by a format string. For example, the above two blocks of code could be replaced by the following (which also takes care of the error checking):

PyObject *tuple, *list;

tuple = Py_BuildValue("(iis)", 1, 2, "three");
list = Py_BuildValue("[iis]", 1, 2, "three");

It is much more common to use PyObject_SetItem() and friends with items whose references you are only borrowing, like arguments that were passed in to the function you are writing. In that case, their behaviour regarding reference counts is much saner, since you don’t have to increment a reference count so you can give a reference away (« have it be stolen »). For example, this function sets all items of a list (actually, any mutable sequence) to a given item:

int
set_all(PyObject *target, PyObject *item)
{
    Py_ssize_t i, n;

    n = PyObject_Length(target);
    if (n < 0)
        return -1;
    for (i = 0; i < n; i++) {
        PyObject *index = PyLong_FromSsize_t(i);
        if (!index)
            return -1;
        if (PyObject_SetItem(target, index, item) < 0) {
            Py_DECREF(index);
            return -1;
        }
        Py_DECREF(index);
    }
    return 0;
}

The situation is slightly different for function return values. While passing a reference to most functions does not change your ownership responsibilities for that reference, many functions that return a reference to an object give you ownership of the reference. The reason is simple: in many cases, the returned object is created on the fly, and the reference you get is the only reference to the object. Therefore, the generic functions that return object references, like PyObject_GetItem() and PySequence_GetItem(), always return a new reference (the caller becomes the owner of the reference).

It is important to realize that whether you own a reference returned by a function depends on which function you call only — the plumage (the type of the object passed as an argument to the function) doesn’t enter into it! Thus, if you extract an item from a list using PyList_GetItem(), you don’t own the reference — but if you obtain the same item from the same list using PySequence_GetItem() (which happens to take exactly the same arguments), you do own a reference to the returned object.

Here is an example of how you could write a function that computes the sum of the items in a list of integers; once using PyList_GetItem(), and once using PySequence_GetItem().

long
sum_list(PyObject *list)
{
    Py_ssize_t i, n;
    long total = 0, value;
    PyObject *item;

    n = PyList_Size(list);
    if (n < 0)
        return -1; /* Not a list */
    for (i = 0; i < n; i++) {
        item = PyList_GetItem(list, i); /* Can't fail */
        if (!PyLong_Check(item)) continue; /* Skip non-integers */
        value = PyLong_AsLong(item);
        if (value == -1 && PyErr_Occurred())
            /* Integer too big to fit in a C long, bail out */
            return -1;
        total += value;
    }
    return total;
}

long
sum_sequence(PyObject *sequence)
{
    Py_ssize_t i, n;
    long total = 0, value;
    PyObject *item;
    n = PySequence_Length(sequence);
    if (n < 0)
        return -1; /* Has no length */
    for (i = 0; i < n; i++) {
        item = PySequence_GetItem(sequence, i);
        if (item == NULL)
            return -1; /* Not a sequence, or other failure */
        if (PyLong_Check(item)) {
            value = PyLong_AsLong(item);
            Py_DECREF(item);
            if (value == -1 && PyErr_Occurred())
                /* Integer too big to fit in a C long, bail out */
                return -1;
            total += value;
        }
        else {
            Py_DECREF(item); /* Discard reference ownership */
        }
    }
    return total;
}

Types

There are few other data types that play a significant role in the Python/C API; most are simple C types such as int, long, double and char*. A few structure types are used to describe static tables used to list the functions exported by a module or the data attributes of a new object type, and another is used to describe the value of a complex number. These will be discussed together with the functions that use them.

Exceptions

The Python programmer only needs to deal with exceptions if specific error handling is required; unhandled exceptions are automatically propagated to the caller, then to the caller’s caller, and so on, until they reach the top-level interpreter, where they are reported to the user accompanied by a stack traceback.

For C programmers, however, error checking always has to be explicit. All functions in the Python/C API can raise exceptions, unless an explicit claim is made otherwise in a function’s documentation. In general, when a function encounters an error, it sets an exception, discards any object references that it owns, and returns an error indicator. If not documented otherwise, this indicator is either NULL or -1, depending on the function’s return type. A few functions return a Boolean true/false result, with false indicating an error. Very few functions return no explicit error indicator or have an ambiguous return value, and require explicit testing for errors with PyErr_Occurred(). These exceptions are always explicitly documented.

Exception state is maintained in per-thread storage (this is equivalent to using global storage in an unthreaded application). A thread can be in one of two states: an exception has occurred, or not. The function PyErr_Occurred() can be used to check for this: it returns a borrowed reference to the exception type object when an exception has occurred, and NULL otherwise. There are a number of functions to set the exception state: PyErr_SetString() is the most common (though not the most general) function to set the exception state, and PyErr_Clear() clears the exception state.

The full exception state consists of three objects (all of which can be NULL): the exception type, the corresponding exception value, and the traceback. These have the same meanings as the Python result of sys.exc_info(); however, they are not the same: the Python objects represent the last exception being handled by a Python try … except statement, while the C level exception state only exists while an exception is being passed on between C functions until it reaches the Python bytecode interpreter’s main loop, which takes care of transferring it to sys.exc_info() and friends.

Note that starting with Python 1.5, the preferred, thread-safe way to access the exception state from Python code is to call the function sys.exc_info(), which returns the per-thread exception state for Python code. Also, the semantics of both ways to access the exception state have changed so that a function which catches an exception will save and restore its thread’s exception state so as to preserve the exception state of its caller. This prevents common bugs in exception handling code caused by an innocent-looking function overwriting the exception being handled; it also reduces the often unwanted lifetime extension for objects that are referenced by the stack frames in the traceback.

As a general principle, a function that calls another function to perform some task should check whether the called function raised an exception, and if so, pass the exception state on to its caller. It should discard any object references that it owns, and return an error indicator, but it should not set another exception — that would overwrite the exception that was just raised, and lose important information about the exact cause of the error.

A simple example of detecting exceptions and passing them on is shown in the sum_sequence() example above. It so happens that this example doesn’t need to clean up any owned references when it detects an error. The following example function shows some error cleanup. First, to remind you why you like Python, we show the equivalent Python code:

def incr_item(dict, key):
    try:
        item = dict[key]
    except KeyError:
        item = 0
    dict[key] = item + 1

Here is the corresponding C code, in all its glory:

int
incr_item(PyObject *dict, PyObject *key)
{
    /* Objects all initialized to NULL for Py_XDECREF */
    PyObject *item = NULL, *const_one = NULL, *incremented_item = NULL;
    int rv = -1; /* Return value initialized to -1 (failure) */

    item = PyObject_GetItem(dict, key);
    if (item == NULL) {
        /* Handle KeyError only: */
        if (!PyErr_ExceptionMatches(PyExc_KeyError))
            goto error;

        /* Clear the error and use zero: */
        PyErr_Clear();
        item = PyLong_FromLong(0L);
        if (item == NULL)
            goto error;
    }
    const_one = PyLong_FromLong(1L);
    if (const_one == NULL)
        goto error;

    incremented_item = PyNumber_Add(item, const_one);
    if (incremented_item == NULL)
        goto error;

    if (PyObject_SetItem(dict, key, incremented_item) < 0)
        goto error;
    rv = 0; /* Success */
    /* Continue with cleanup code */

 error:
    /* Cleanup code, shared by success and failure path */

    /* Use Py_XDECREF() to ignore NULL references */
    Py_XDECREF(item);
    Py_XDECREF(const_one);
    Py_XDECREF(incremented_item);

    return rv; /* -1 for error, 0 for success */
}

This example represents an endorsed use of the goto statement in C! It illustrates the use of PyErr_ExceptionMatches() and PyErr_Clear() to handle specific exceptions, and the use of Py_XDECREF() to dispose of owned references that may be NULL (note the 'X' in the name; Py_DECREF() would crash when confronted with a NULL reference). It is important that the variables used to hold owned references are initialized to NULL for this to work; likewise, the proposed return value is initialized to -1 (failure) and only set to success after the final call made is successful.

Embarquer Python

The one important task that only embedders (as opposed to extension writers) of the Python interpreter have to worry about is the initialization, and possibly the finalization, of the Python interpreter. Most functionality of the interpreter can only be used after the interpreter has been initialized.

The basic initialization function is Py_Initialize(). This initializes the table of loaded modules, and creates the fundamental modules builtins, __main__, and sys. It also initializes the module search path (sys.path).

Py_Initialize() does not set the « script argument list » (sys.argv). If this variable is needed by Python code that will be executed later, it must be set explicitly with a call to PySys_SetArgvEx(argc, argv, updatepath) after the call to Py_Initialize().

On most systems (in particular, on Unix and Windows, although the details are slightly different), Py_Initialize() calculates the module search path based upon its best guess for the location of the standard Python interpreter executable, assuming that the Python library is found in a fixed location relative to the Python interpreter executable. In particular, it looks for a directory named lib/pythonX.Y relative to the parent directory where the executable named python is found on the shell command search path (the environment variable PATH).

For instance, if the Python executable is found in /usr/local/bin/python, it will assume that the libraries are in /usr/local/lib/pythonX.Y. (In fact, this particular path is also the « fallback » location, used when no executable file named python is found along PATH.) The user can override this behavior by setting the environment variable PYTHONHOME, or insert additional directories in front of the standard path by setting PYTHONPATH.

The embedding application can steer the search by calling Py_SetProgramName(file) before calling Py_Initialize(). Note that PYTHONHOME still overrides this and PYTHONPATH is still inserted in front of the standard path. An application that requires total control has to provide its own implementation of Py_GetPath(), Py_GetPrefix(), Py_GetExecPrefix(), and Py_GetProgramFullPath() (all defined in Modules/getpath.c).

Sometimes, it is desirable to « uninitialize » Python. For instance, the application may want to start over (make another call to Py_Initialize()) or the application is simply done with its use of Python and wants to free memory allocated by Python. This can be accomplished by calling Py_FinalizeEx(). The function Py_IsInitialized() returns true if Python is currently in the initialized state. More information about these functions is given in a later chapter. Notice that Py_FinalizeEx() does not free all memory allocated by the Python interpreter, e.g. memory allocated by extension modules currently cannot be released.

Debugging Builds

Python can be built with several macros to enable extra checks of the interpreter and extension modules. These checks tend to add a large amount of overhead to the runtime so they are not enabled by default.

A full list of the various types of debugging builds is in the file Misc/SpecialBuilds.txt in the Python source distribution. Builds are available that support tracing of reference counts, debugging the memory allocator, or low-level profiling of the main interpreter loop. Only the most frequently-used builds will be described in the remainder of this section.

Compiling the interpreter with the Py_DEBUG macro defined produces what is generally meant by « a debug build » of Python. Py_DEBUG is enabled in the Unix build by adding --with-pydebug to the ./configure command. It is also implied by the presence of the not-Python-specific _DEBUG macro. When Py_DEBUG is enabled in the Unix build, compiler optimization is disabled.

In addition to the reference count debugging described below, the following extra checks are performed:

Extra checks are added to the object allocator.

Extra checks are added to the parser and compiler.

Downcasts from wide types to narrow types are checked for loss of information.

A number of assertions are added to the dictionary and set implementations. In addition, the set object acquires a test_c_api() method.

Sanity checks of the input arguments are added to frame creation.

The storage for ints is initialized with a known invalid pattern to catch reference to uninitialized digits.

Low-level tracing and extra exception checking are added to the runtime virtual machine.

Extra checks are added to the memory arena implementation.

Extra debugging is added to the thread module.

There may be additional checks not mentioned here.

Defining Py_TRACE_REFS enables reference tracing. When defined, a circular doubly linked list of active objects is maintained by adding two extra fields to every PyObject. Total allocations are tracked as well. Upon exit, all existing references are printed. (In interactive mode this happens after every statement run by the interpreter.) Implied by Py_DEBUG.

Please refer to Misc/SpecialBuilds.txt in the Python source distribution for more detailed information.

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ABI Stable

L’API C de Python change à chaque version. La majorité de ces changement n’affecte cependant pas la compatibilité du code source. Typiquement, des API sont ajoutées, mais ni modifiées ni supprimées (bien que certaines interfaces puissent être supprimées, après avoir d’abord été dépréciées).

Malheureusement, la compatibilité de l’API ne s’étend pas à une compatibilité binaire (l’ABI). L’évolution des structures en est la raison principale : l’ajout de nouveaux attributs, ou le changement du type d’un attribut peut ne pas casser l’API mais casser l’ABI. Par conséquent, les modules d’extension doivent être recompilés à chaque nouvelle version de Python (ce n’est exceptionnellement pas nécessaire sur Unix, si aucune des interfaces modifiées n’est utilisée). De plus, sous Windows, les modules d’extension sont liés à un pythonXY.dll spécifique, ils est donc nécessaire de les recompiler pour les lier au nouveau DLL.

Depuis Python 3.2 il est garanti qu’une certaine partie de l’API gardera une ABI stable. Les modules d’extension souhaitant utiliser cette API (Appellée « API limitée ») doivent définir Py_LIMITED_API. Des spécificités de l’interpréteur sont alors cachées au module, en contrepartie le module devient compatible avec toutes les versions de Python 3.x (x>=2) sans recompilation.

Dans certains cas, il est nécessaire d’étendre l’ABI stable avec de nouvelles fonctions. Les modules d’extension souhaitant utiliser ces nouvelles APIs doivent configurer Py_LIMITED_API à la valeur Py_VERSION_HEX correspondant à la plus ancienne version de Python qu’ils souhaitent supporter (voir Version des API et ABI, par exemple 0x03030000 pour Python 3.3). De tels modules fonctionneront dans toutes les versions ultérieures de Python, mais ne pourront pas se charger (dû à des symboles manquants) sur les versions plus anciennes.

Depuis Python 3.2, l’ensemble des fonctions exposées par l’API limitée est documentée dans la PEP 384 [https://www.python.org/dev/peps/pep-0384]. Dans la documentation de l’API C, les éléments ne faisant pas partie de l’API limitée sont notés « Ne faisant pas partie de l’API limitée » (« Not part of the limited API »).

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The Very High Level Layer

The functions in this chapter will let you execute Python source code given in a file or a buffer, but they will not let you interact in a more detailed way with the interpreter.

Several of these functions accept a start symbol from the grammar as a parameter. The available start symbols are Py_eval_input, Py_file_input, and Py_single_input. These are described following the functions which accept them as parameters.

Note also that several of these functions take FILE* parameters. One particular issue which needs to be handled carefully is that the FILE structure for different C libraries can be different and incompatible. Under Windows (at least), it is possible for dynamically linked extensions to actually use different libraries, so care should be taken that FILE* parameters are only passed to these functions if it is certain that they were created by the same library that the Python runtime is using.

int Py_Main(int argc, wchar_t **argv)

The main program for the standard interpreter. This is made available for programs which embed Python. The argc and argv parameters should be prepared exactly as those which are passed to a C program’s main() function (converted to wchar_t according to the user’s locale). It is important to note that the argument list may be modified (but the contents of the strings pointed to by the argument list are not). The return value will be 0 if the interpreter exits normally (i.e., without an exception), 1 if the interpreter exits due to an exception, or 2 if the parameter list does not represent a valid Python command line.

Note that if an otherwise unhandled SystemExit is raised, this function will not return 1, but exit the process, as long as Py_InspectFlag is not set.

int PyRun_AnyFile(FILE *fp, const char *filename)

This is a simplified interface to PyRun_AnyFileExFlags() below, leaving closeit set to 0 and flags set to NULL.

int PyRun_AnyFileFlags(FILE *fp, const char *filename, PyCompilerFlags *flags)

This is a simplified interface to PyRun_AnyFileExFlags() below, leaving the closeit argument set to 0.

int PyRun_AnyFileEx(FILE *fp, const char *filename, int closeit)

This is a simplified interface to PyRun_AnyFileExFlags() below, leaving the flags argument set to NULL.

int PyRun_AnyFileExFlags(FILE *fp, const char *filename, int closeit, PyCompilerFlags *flags)

If fp refers to a file associated with an interactive device (console or terminal input or Unix pseudo-terminal), return the value of PyRun_InteractiveLoop(), otherwise return the result of PyRun_SimpleFile(). filename is decoded from the filesystem encoding (sys.getfilesystemencoding()). If filename is NULL, this function uses "???" as the filename.

int PyRun_SimpleString(const char *command)

This is a simplified interface to PyRun_SimpleStringFlags() below, leaving the PyCompilerFlags* argument set to NULL.

int PyRun_SimpleStringFlags(const char *command, PyCompilerFlags *flags)

Executes the Python source code from command in the __main__ module according to the flags argument. If __main__ does not already exist, it is created. Returns 0 on success or -1 if an exception was raised. If there was an error, there is no way to get the exception information. For the meaning of flags, see below.

Note that if an otherwise unhandled SystemExit is raised, this function will not return -1, but exit the process, as long as Py_InspectFlag is not set.

int PyRun_SimpleFile(FILE *fp, const char *filename)

This is a simplified interface to PyRun_SimpleFileExFlags() below, leaving closeit set to 0 and flags set to NULL.

int PyRun_SimpleFileEx(FILE *fp, const char *filename, int closeit)

This is a simplified interface to PyRun_SimpleFileExFlags() below, leaving flags set to NULL.

int PyRun_SimpleFileExFlags(FILE *fp, const char *filename, int closeit, PyCompilerFlags *flags)

Similar to PyRun_SimpleStringFlags(), but the Python source code is read from fp instead of an in-memory string. filename should be the name of the file, it is decoded from the filesystem encoding (sys.getfilesystemencoding()). If closeit is true, the file is closed before PyRun_SimpleFileExFlags returns.

int PyRun_InteractiveOne(FILE *fp, const char *filename)

This is a simplified interface to PyRun_InteractiveOneFlags() below, leaving flags set to NULL.

int PyRun_InteractiveOneFlags(FILE *fp, const char *filename, PyCompilerFlags *flags)

Read and execute a single statement from a file associated with an interactive device according to the flags argument. The user will be prompted using sys.ps1 and sys.ps2. filename is decoded from the filesystem encoding (sys.getfilesystemencoding()).

Returns 0 when the input was executed successfully, -1 if there was an exception, or an error code from the errcode.h include file distributed as part of Python if there was a parse error. (Note that errcode.h is not included by Python.h, so must be included specifically if needed.)

int PyRun_InteractiveLoop(FILE *fp, const char *filename)

This is a simplified interface to PyRun_InteractiveLoopFlags() below, leaving flags set to NULL.

int PyRun_InteractiveLoopFlags(FILE *fp, const char *filename, PyCompilerFlags *flags)

Read and execute statements from a file associated with an interactive device until EOF is reached. The user will be prompted using sys.ps1 and sys.ps2. filename is decoded from the filesystem encoding (sys.getfilesystemencoding()). Returns 0 at EOF or a negative number upon failure.

int (*PyOS_InputHook)(void)

Can be set to point to a function with the prototype int func(void). The function will be called when Python’s interpreter prompt is about to become idle and wait for user input from the terminal. The return value is ignored. Overriding this hook can be used to integrate the interpreter’s prompt with other event loops, as done in the Modules/_tkinter.c in the Python source code.

char* (*PyOS_ReadlineFunctionPointer)(FILE *, FILE *, const char *)

Can be set to point to a function with the prototype char *func(FILE *stdin, FILE *stdout, char *prompt), overriding the default function used to read a single line of input at the interpreter’s prompt. The function is expected to output the string prompt if it’s not NULL, and then read a line of input from the provided standard input file, returning the resulting string. For example, The readline module sets this hook to provide line-editing and tab-completion features.

The result must be a string allocated by PyMem_RawMalloc() or PyMem_RawRealloc(), or NULL if an error occurred.

Modifié dans la version 3.4: The result must be allocated by PyMem_RawMalloc() or PyMem_RawRealloc(), instead of being allocated by PyMem_Malloc() or PyMem_Realloc().

struct _node* PyParser_SimpleParseString(const char *str, int start)

This is a simplified interface to PyParser_SimpleParseStringFlagsFilename() below, leaving filename set to NULL and flags set to 0.

struct _node* PyParser_SimpleParseStringFlags(const char *str, int start, int flags)

This is a simplified interface to PyParser_SimpleParseStringFlagsFilename() below, leaving filename set to NULL.

struct _node* PyParser_SimpleParseStringFlagsFilename(const char *str, const char *filename, int start, int flags)

Parse Python source code from str using the start token start according to the flags argument. The result can be used to create a code object which can be evaluated efficiently. This is useful if a code fragment must be evaluated many times. filename is decoded from the filesystem encoding (sys.getfilesystemencoding()).

struct _node* PyParser_SimpleParseFile(FILE *fp, const char *filename, int start)

This is a simplified interface to PyParser_SimpleParseFileFlags() below, leaving flags set to 0.

struct _node* PyParser_SimpleParseFileFlags(FILE *fp, const char *filename, int start, int flags)

Similar to PyParser_SimpleParseStringFlagsFilename(), but the Python source code is read from fp instead of an in-memory string.

PyObject* PyRun_String(const char *str, int start, PyObject *globals, PyObject *locals)

Return value: New reference.

This is a simplified interface to PyRun_StringFlags() below, leaving flags set to NULL.

PyObject* PyRun_StringFlags(const char *str, int start, PyObject *globals, PyObject *locals, PyCompilerFlags *flags)

Return value: New reference.

Execute Python source code from str in the context specified by the objects globals and locals with the compiler flags specified by flags. globals must be a dictionary; locals can be any object that implements the mapping protocol. The parameter start specifies the start token that should be used to parse the source code.

Returns the result of executing the code as a Python object, or NULL if an exception was raised.

PyObject* PyRun_File(FILE *fp, const char *filename, int start, PyObject *globals, PyObject *locals)

Return value: New reference.

This is a simplified interface to PyRun_FileExFlags() below, leaving closeit set to 0 and flags set to NULL.

PyObject* PyRun_FileEx(FILE *fp, const char *filename, int start, PyObject *globals, PyObject *locals, int closeit)

Return value: New reference.

This is a simplified interface to PyRun_FileExFlags() below, leaving flags set to NULL.

PyObject* PyRun_FileFlags(FILE *fp, const char *filename, int start, PyObject *globals, PyObject *locals, PyCompilerFlags *flags)

Return value: New reference.

This is a simplified interface to PyRun_FileExFlags() below, leaving closeit set to 0.

PyObject* PyRun_FileExFlags(FILE *fp, const char *filename, int start, PyObject *globals, PyObject *locals, int closeit, PyCompilerFlags *flags)

Return value: New reference.

Similar to PyRun_StringFlags(), but the Python source code is read from fp instead of an in-memory string. filename should be the name of the file, it is decoded from the filesystem encoding (sys.getfilesystemencoding()). If closeit is true, the file is closed before PyRun_FileExFlags() returns.

PyObject* Py_CompileString(const char *str, const char *filename, int start)

Return value: New reference.

This is a simplified interface to Py_CompileStringFlags() below, leaving flags set to NULL.

PyObject* Py_CompileStringFlags(const char *str, const char *filename, int start, PyCompilerFlags *flags)

Return value: New reference.

This is a simplified interface to Py_CompileStringExFlags() below, with optimize set to -1.

PyObject* Py_CompileStringObject(const char *str, PyObject *filename, int start, PyCompilerFlags *flags, int optimize)

Parse and compile the Python source code in str, returning the resulting code object. The start token is given by start; this can be used to constrain the code which can be compiled and should be Py_eval_input, Py_file_input, or Py_single_input. The filename specified by filename is used to construct the code object and may appear in tracebacks or SyntaxError exception messages. This returns NULL if the code cannot be parsed or compiled.

The integer optimize specifies the optimization level of the compiler; a value of -1 selects the optimization level of the interpreter as given by -O options. Explicit levels are 0 (no optimization; __debug__ is true), 1 (asserts are removed, __debug__ is false) or 2 (docstrings are removed too).

Nouveau dans la version 3.4.

PyObject* Py_CompileStringExFlags(const char *str, const char *filename, int start, PyCompilerFlags *flags, int optimize)

Like Py_CompileStringObject(), but filename is a byte string decoded from the filesystem encoding (os.fsdecode()).

Nouveau dans la version 3.2.

PyObject* PyEval_EvalCode(PyObject *co, PyObject *globals, PyObject *locals)

Return value: New reference.

This is a simplified interface to PyEval_EvalCodeEx(), with just the code object, and global and local variables. The other arguments are set to NULL.

PyObject* PyEval_EvalCodeEx(PyObject *co, PyObject *globals, PyObject *locals, PyObject **args, int argcount, PyObject **kws, int kwcount, PyObject **defs, int defcount, PyObject *kwdefs, PyObject *closure)

Evaluate a precompiled code object, given a particular environment for its evaluation. This environment consists of a dictionary of global variables, a mapping object of local variables, arrays of arguments, keywords and defaults, a dictionary of default values for keyword-only arguments and a closure tuple of cells.

PyFrameObject

The C structure of the objects used to describe frame objects. The fields of this type are subject to change at any time.

PyObject* PyEval_EvalFrame(PyFrameObject *f)

Evaluate an execution frame. This is a simplified interface to PyEval_EvalFrameEx(), for backward compatibility.

PyObject* PyEval_EvalFrameEx(PyFrameObject *f, int throwflag)

This is the main, unvarnished function of Python interpretation. It is literally 2000 lines long. The code object associated with the execution frame f is executed, interpreting bytecode and executing calls as needed. The additional throwflag parameter can mostly be ignored - if true, then it causes an exception to immediately be thrown; this is used for the throw() methods of generator objects.

Modifié dans la version 3.4: Cette fonction inclut maintenant une assertion de débogage afin d’assurer qu’elle ne passe pas sous silence une exception active.

int PyEval_MergeCompilerFlags(PyCompilerFlags *cf)

This function changes the flags of the current evaluation frame, and returns true on success, false on failure.

int Py_eval_input

The start symbol from the Python grammar for isolated expressions; for use with Py_CompileString().

int Py_file_input

The start symbol from the Python grammar for sequences of statements as read from a file or other source; for use with Py_CompileString(). This is the symbol to use when compiling arbitrarily long Python source code.

int Py_single_input

The start symbol from the Python grammar for a single statement; for use with Py_CompileString(). This is the symbol used for the interactive interpreter loop.

struct PyCompilerFlags

This is the structure used to hold compiler flags. In cases where code is only being compiled, it is passed as int flags, and in cases where code is being executed, it is passed as PyCompilerFlags *flags. In this case, from __future__ import can modify flags.

Whenever PyCompilerFlags *flags is NULL, cf_flags is treated as equal to 0, and any modification due to from __future__ import is discarded.

struct PyCompilerFlags {
    int cf_flags;
}

int CO_FUTURE_DIVISION

This bit can be set in flags to cause division operator / to be interpreted as « true division » according to PEP 238 [https://www.python.org/dev/peps/pep-0238].

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Reference Counting

The macros in this section are used for managing reference counts of Python objects.

void Py_INCREF(PyObject *o)

Increment the reference count for object o. The object must not be NULL; if you aren’t sure that it isn’t NULL, use Py_XINCREF().

void Py_XINCREF(PyObject *o)

Increment the reference count for object o. The object may be NULL, in which case the macro has no effect.

void Py_DECREF(PyObject *o)

Decrement the reference count for object o. The object must not be NULL; if you aren’t sure that it isn’t NULL, use Py_XDECREF(). If the reference count reaches zero, the object’s type’s deallocation function (which must not be NULL) is invoked.

Avertissement

The deallocation function can cause arbitrary Python code to be invoked (e.g. when a class instance with a __del__() method is deallocated). While exceptions in such code are not propagated, the executed code has free access to all Python global variables. This means that any object that is reachable from a global variable should be in a consistent state before Py_DECREF() is invoked. For example, code to delete an object from a list should copy a reference to the deleted object in a temporary variable, update the list data structure, and then call Py_DECREF() for the temporary variable.

void Py_XDECREF(PyObject *o)

Decrement the reference count for object o. The object may be NULL, in which case the macro has no effect; otherwise the effect is the same as for Py_DECREF(), and the same warning applies.

void Py_CLEAR(PyObject *o)

Decrement the reference count for object o. The object may be NULL, in which case the macro has no effect; otherwise the effect is the same as for Py_DECREF(), except that the argument is also set to NULL. The warning for Py_DECREF() does not apply with respect to the object passed because the macro carefully uses a temporary variable and sets the argument to NULL before decrementing its reference count.

It is a good idea to use this macro whenever decrementing the value of a variable that might be traversed during garbage collection.

The following functions are for runtime dynamic embedding of Python: Py_IncRef(PyObject *o), Py_DecRef(PyObject *o). They are simply exported function versions of Py_XINCREF() and Py_XDECREF(), respectively.

The following functions or macros are only for use within the interpreter core: _Py_Dealloc(), _Py_ForgetReference(), _Py_NewReference(), as well as the global variable _Py_RefTotal.

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Gestion des exceptions

The functions described in this chapter will let you handle and raise Python exceptions. It is important to understand some of the basics of Python exception handling. It works somewhat like the POSIX errno variable: there is a global indicator (per thread) of the last error that occurred. Most C API functions don’t clear this on success, but will set it to indicate the cause of the error on failure. Most C API functions also return an error indicator, usually NULL if they are supposed to return a pointer, or -1 if they return an integer (exception: the PyArg_*() functions return 1 for success and 0 for failure).

Concretely, the error indicator consists of three object pointers: the exception’s type, the exception’s value, and the traceback object. Any of those pointers can be NULL if non-set (although some combinations are forbidden, for example you can’t have a non-NULL traceback if the exception type is NULL).

When a function must fail because some function it called failed, it generally doesn’t set the error indicator; the function it called already set it. It is responsible for either handling the error and clearing the exception or returning after cleaning up any resources it holds (such as object references or memory allocations); it should not continue normally if it is not prepared to handle the error. If returning due to an error, it is important to indicate to the caller that an error has been set. If the error is not handled or carefully propagated, additional calls into the Python/C API may not behave as intended and may fail in mysterious ways.

Note

The error indicator is not the result of sys.exc_info(). The former corresponds to an exception that is not yet caught (and is therefore still propagating), while the latter returns an exception after it is caught (and has therefore stopped propagating).

Printing and clearing

void PyErr_Clear()

Clear the error indicator. If the error indicator is not set, there is no effect.

void PyErr_PrintEx(int set_sys_last_vars)

Print a standard traceback to sys.stderr and clear the error indicator. Unless the error is a SystemExit. In that case the no traceback is printed and Python process will exit with the error code specified by the SystemExit instance.

Call this function only when the error indicator is set. Otherwise it will cause a fatal error!

If set_sys_last_vars is nonzero, the variables sys.last_type, sys.last_value and sys.last_traceback will be set to the type, value and traceback of the printed exception, respectively.

void PyErr_Print()

Alias for PyErr_PrintEx(1).

void PyErr_WriteUnraisable(PyObject *obj)

This utility function prints a warning message to sys.stderr when an exception has been set but it is impossible for the interpreter to actually raise the exception. It is used, for example, when an exception occurs in an __del__() method.

The function is called with a single argument obj that identifies the context in which the unraisable exception occurred. If possible, the repr of obj will be printed in the warning message.

Lever des exceptions

These functions help you set the current thread’s error indicator. For convenience, some of these functions will always return a NULL pointer for use in a return statement.

void PyErr_SetString(PyObject *type, const char *message)

This is the most common way to set the error indicator. The first argument specifies the exception type; it is normally one of the standard exceptions, e.g. PyExc_RuntimeError. You need not increment its reference count. The second argument is an error message; it is decoded from 'utf-8”.

void PyErr_SetObject(PyObject *type, PyObject *value)

This function is similar to PyErr_SetString() but lets you specify an arbitrary Python object for the « value » of the exception.

PyObject* PyErr_Format(PyObject *exception, const char *format, ...)

Return value: Always NULL.

This function sets the error indicator and returns NULL. exception should be a Python exception class. The format and subsequent parameters help format the error message; they have the same meaning and values as in PyUnicode_FromFormat(). format is an ASCII-encoded string.

PyObject* PyErr_FormatV(PyObject *exception, const char *format, va_list vargs)

Return value: Always NULL.

Same as PyErr_Format(), but taking a va_list argument rather than a variable number of arguments.

Nouveau dans la version 3.5.

void PyErr_SetNone(PyObject *type)

This is a shorthand for PyErr_SetObject(type, Py_None).

int PyErr_BadArgument()

This is a shorthand for PyErr_SetString(PyExc_TypeError, message), where message indicates that a built-in operation was invoked with an illegal argument. It is mostly for internal use.

PyObject* PyErr_NoMemory()

Return value: Always NULL.

This is a shorthand for PyErr_SetNone(PyExc_MemoryError); it returns NULL so an object allocation function can write return PyErr_NoMemory(); when it runs out of memory.

PyObject* PyErr_SetFromErrno(PyObject *type)

Return value: Always NULL.

This is a convenience function to raise an exception when a C library function has returned an error and set the C variable errno. It constructs a tuple object whose first item is the integer errno value and whose second item is the corresponding error message (gotten from strerror()), and then calls PyErr_SetObject(type, object). On Unix, when the errno value is EINTR, indicating an interrupted system call, this calls PyErr_CheckSignals(), and if that set the error indicator, leaves it set to that. The function always returns NULL, so a wrapper function around a system call can write return PyErr_SetFromErrno(type); when the system call returns an error.

PyObject* PyErr_SetFromErrnoWithFilenameObject(PyObject *type, PyObject *filenameObject)

Similar to PyErr_SetFromErrno(), with the additional behavior that if filenameObject is not NULL, it is passed to the constructor of type as a third parameter. In the case of OSError exception, this is used to define the filename attribute of the exception instance.

PyObject* PyErr_SetFromErrnoWithFilenameObjects(PyObject *type, PyObject *filenameObject, PyObject *filenameObject2)

Similar to PyErr_SetFromErrnoWithFilenameObject(), but takes a second filename object, for raising errors when a function that takes two filenames fails.

Nouveau dans la version 3.4.

PyObject* PyErr_SetFromErrnoWithFilename(PyObject *type, const char *filename)

Return value: Always NULL.

Similar to PyErr_SetFromErrnoWithFilenameObject(), but the filename is given as a C string. filename is decoded from the filesystem encoding (os.fsdecode()).

PyObject* PyErr_SetFromWindowsErr(int ierr)

Return value: Always NULL.

This is a convenience function to raise WindowsError. If called with ierr of 0, the error code returned by a call to GetLastError() is used instead. It calls the Win32 function FormatMessage() to retrieve the Windows description of error code given by ierr or GetLastError(), then it constructs a tuple object whose first item is the ierr value and whose second item is the corresponding error message (gotten from FormatMessage()), and then calls PyErr_SetObject(PyExc_WindowsError, object). This function always returns NULL. Availability: Windows.

PyObject* PyErr_SetExcFromWindowsErr(PyObject *type, int ierr)

Return value: Always NULL.

Similar to PyErr_SetFromWindowsErr(), with an additional parameter specifying the exception type to be raised. Availability: Windows.

PyObject* PyErr_SetFromWindowsErrWithFilename(int ierr, const char *filename)

Return value: Always NULL.

Similar to PyErr_SetFromWindowsErrWithFilenameObject(), but the filename is given as a C string. filename is decoded from the filesystem encoding (os.fsdecode()). Availability: Windows.

PyObject* PyErr_SetExcFromWindowsErrWithFilenameObject(PyObject *type, int ierr, PyObject *filename)

Similar to PyErr_SetFromWindowsErrWithFilenameObject(), with an additional parameter specifying the exception type to be raised. Availability: Windows.

PyObject* PyErr_SetExcFromWindowsErrWithFilenameObjects(PyObject *type, int ierr, PyObject *filename, PyObject *filename2)

Similar to PyErr_SetExcFromWindowsErrWithFilenameObject(), but accepts a second filename object. Availability: Windows.

Nouveau dans la version 3.4.

PyObject* PyErr_SetExcFromWindowsErrWithFilename(PyObject *type, int ierr, const char *filename)

Return value: Always NULL.

Similar to PyErr_SetFromWindowsErrWithFilename(), with an additional parameter specifying the exception type to be raised. Availability: Windows.

PyObject* PyErr_SetImportError(PyObject *msg, PyObject *name, PyObject *path)

This is a convenience function to raise ImportError. msg will be set as the exception’s message string. name and path, both of which can be NULL, will be set as the ImportError’s respective name and path attributes.

Nouveau dans la version 3.3.

void PyErr_SyntaxLocationObject(PyObject *filename, int lineno, int col_offset)

Set file, line, and offset information for the current exception. If the current exception is not a SyntaxError, then it sets additional attributes, which make the exception printing subsystem think the exception is a SyntaxError.

Nouveau dans la version 3.4.

void PyErr_SyntaxLocationEx(const char *filename, int lineno, int col_offset)

Like PyErr_SyntaxLocationObject(), but filename is a byte string decoded from the filesystem encoding (os.fsdecode()).

Nouveau dans la version 3.2.

void PyErr_SyntaxLocation(const char *filename, int lineno)

Like PyErr_SyntaxLocationEx(), but the col_offset parameter is omitted.

void PyErr_BadInternalCall()

This is a shorthand for PyErr_SetString(PyExc_SystemError, message), where message indicates that an internal operation (e.g. a Python/C API function) was invoked with an illegal argument. It is mostly for internal use.

Issuing warnings

Use these functions to issue warnings from C code. They mirror similar functions exported by the Python warnings module. They normally print a warning message to sys.stderr; however, it is also possible that the user has specified that warnings are to be turned into errors, and in that case they will raise an exception. It is also possible that the functions raise an exception because of a problem with the warning machinery. The return value is 0 if no exception is raised, or -1 if an exception is raised. (It is not possible to determine whether a warning message is actually printed, nor what the reason is for the exception; this is intentional.) If an exception is raised, the caller should do its normal exception handling (for example, Py_DECREF() owned references and return an error value).

int PyErr_WarnEx(PyObject *category, const char *message, Py_ssize_t stack_level)

Issue a warning message. The category argument is a warning category (see below) or NULL; the message argument is a UTF-8 encoded string. stack_level is a positive number giving a number of stack frames; the warning will be issued from the currently executing line of code in that stack frame. A stack_level of 1 is the function calling PyErr_WarnEx(), 2 is the function above that, and so forth.

Warning categories must be subclasses of PyExc_Warning; PyExc_Warning is a subclass of PyExc_Exception; the default warning category is PyExc_RuntimeWarning. The standard Python warning categories are available as global variables whose names are enumerated at Standard Warning Categories.

For information about warning control, see the documentation for the warnings module and the -W option in the command line documentation. There is no C API for warning control.

PyObject* PyErr_SetImportErrorSubclass(PyObject *msg, PyObject *name, PyObject *path)

Much like PyErr_SetImportError() but this function allows for specifying a subclass of ImportError to raise.

Nouveau dans la version 3.6.

int PyErr_WarnExplicitObject(PyObject *category, PyObject *message, PyObject *filename, int lineno, PyObject *module, PyObject *registry)

Issue a warning message with explicit control over all warning attributes. This is a straightforward wrapper around the Python function warnings.warn_explicit(), see there for more information. The module and registry arguments may be set to NULL to get the default effect described there.

Nouveau dans la version 3.4.

int PyErr_WarnExplicit(PyObject *category, const char *message, const char *filename, int lineno, const char *module, PyObject *registry)

Similar to PyErr_WarnExplicitObject() except that message and module are UTF-8 encoded strings, and filename is decoded from the filesystem encoding (os.fsdecode()).

int PyErr_WarnFormat(PyObject *category, Py_ssize_t stack_level, const char *format, ...)

Function similar to PyErr_WarnEx(), but use PyUnicode_FromFormat() to format the warning message. format is an ASCII-encoded string.

Nouveau dans la version 3.2.

int PyErr_ResourceWarning(PyObject *source, Py_ssize_t stack_level, const char *format, ...)

Function similar to PyErr_WarnFormat(), but category is ResourceWarning and pass source to warnings.WarningMessage().

Nouveau dans la version 3.6.

Querying the error indicator

PyObject* PyErr_Occurred()

Return value: Borrowed reference.

Test whether the error indicator is set. If set, return the exception type (the first argument to the last call to one of the PyErr_Set*() functions or to PyErr_Restore()). If not set, return NULL. You do not own a reference to the return value, so you do not need to Py_DECREF() it.

Note

Do not compare the return value to a specific exception; use PyErr_ExceptionMatches() instead, shown below. (The comparison could easily fail since the exception may be an instance instead of a class, in the case of a class exception, or it may be a subclass of the expected exception.)

int PyErr_ExceptionMatches(PyObject *exc)

Equivalent to PyErr_GivenExceptionMatches(PyErr_Occurred(), exc). This should only be called when an exception is actually set; a memory access violation will occur if no exception has been raised.

int PyErr_GivenExceptionMatches(PyObject *given, PyObject *exc)

Return true if the given exception matches the exception type in exc. If exc is a class object, this also returns true when given is an instance of a subclass. If exc is a tuple, all exception types in the tuple (and recursively in subtuples) are searched for a match.

void PyErr_Fetch(PyObject **ptype, PyObject **pvalue, PyObject **ptraceback)

Retrieve the error indicator into three variables whose addresses are passed. If the error indicator is not set, set all three variables to NULL. If it is set, it will be cleared and you own a reference to each object retrieved. The value and traceback object may be NULL even when the type object is not.

Note

This function is normally only used by code that needs to catch exceptions or by code that needs to save and restore the error indicator temporarily, e.g.:

{
   PyObject *type, *value, *traceback;
   PyErr_Fetch(&type, &value, &traceback);

   /* ... code that might produce other errors ... */

   PyErr_Restore(type, value, traceback);
}

void PyErr_Restore(PyObject *type, PyObject *value, PyObject *traceback)

Set the error indicator from the three objects. If the error indicator is already set, it is cleared first. If the objects are NULL, the error indicator is cleared. Do not pass a NULL type and non-NULL value or traceback. The exception type should be a class. Do not pass an invalid exception type or value. (Violating these rules will cause subtle problems later.) This call takes away a reference to each object: you must own a reference to each object before the call and after the call you no longer own these references. (If you don’t understand this, don’t use this function. I warned you.)

Note

This function is normally only used by code that needs to save and restore the error indicator temporarily. Use PyErr_Fetch() to save the current error indicator.

void PyErr_NormalizeException(PyObject**exc, PyObject**val, PyObject**tb)

Under certain circumstances, the values returned by PyErr_Fetch() below can be « unnormalized », meaning that *exc is a class object but *val is not an instance of the same class. This function can be used to instantiate the class in that case. If the values are already normalized, nothing happens. The delayed normalization is implemented to improve performance.

Note

This function does not implicitly set the __traceback__ attribute on the exception value. If setting the traceback appropriately is desired, the following additional snippet is needed:

if (tb != NULL) {
  PyException_SetTraceback(val, tb);
}

void PyErr_GetExcInfo(PyObject **ptype, PyObject **pvalue, PyObject **ptraceback)

Retrieve the exception info, as known from sys.exc_info(). This refers to an exception that was already caught, not to an exception that was freshly raised. Returns new references for the three objects, any of which may be NULL. Does not modify the exception info state.

Note

This function is not normally used by code that wants to handle exceptions. Rather, it can be used when code needs to save and restore the exception state temporarily. Use PyErr_SetExcInfo() to restore or clear the exception state.

Nouveau dans la version 3.3.

void PyErr_SetExcInfo(PyObject *type, PyObject *value, PyObject *traceback)

Set the exception info, as known from sys.exc_info(). This refers to an exception that was already caught, not to an exception that was freshly raised. This function steals the references of the arguments. To clear the exception state, pass NULL for all three arguments. For general rules about the three arguments, see PyErr_Restore().

Note

This function is not normally used by code that wants to handle exceptions. Rather, it can be used when code needs to save and restore the exception state temporarily. Use PyErr_GetExcInfo() to read the exception state.

Nouveau dans la version 3.3.

Traitement des signaux

int PyErr_CheckSignals()

This function interacts with Python’s signal handling. It checks whether a signal has been sent to the processes and if so, invokes the corresponding signal handler. If the signal module is supported, this can invoke a signal handler written in Python. In all cases, the default effect for SIGINT is to raise the KeyboardInterrupt exception. If an exception is raised the error indicator is set and the function returns -1; otherwise the function returns 0. The error indicator may or may not be cleared if it was previously set.

void PyErr_SetInterrupt()

This function simulates the effect of a SIGINT signal arriving — the next time PyErr_CheckSignals() is called, KeyboardInterrupt will be raised. It may be called without holding the interpreter lock.

int PySignal_SetWakeupFd(int fd)

This utility function specifies a file descriptor to which the signal number is written as a single byte whenever a signal is received. fd must be non-blocking. It returns the previous such file descriptor.

The value -1 disables the feature; this is the initial state. This is equivalent to signal.set_wakeup_fd() in Python, but without any error checking. fd should be a valid file descriptor. The function should only be called from the main thread.

Modifié dans la version 3.5: On Windows, the function now also supports socket handles.

Exception Classes

PyObject* PyErr_NewException(const char *name, PyObject *base, PyObject *dict)

Return value: New reference.

This utility function creates and returns a new exception class. The name argument must be the name of the new exception, a C string of the form module.classname. The base and dict arguments are normally NULL. This creates a class object derived from Exception (accessible in C as PyExc_Exception).

The __module__ attribute of the new class is set to the first part (up to the last dot) of the name argument, and the class name is set to the last part (after the last dot). The base argument can be used to specify alternate base classes; it can either be only one class or a tuple of classes. The dict argument can be used to specify a dictionary of class variables and methods.

PyObject* PyErr_NewExceptionWithDoc(const char *name, const char *doc, PyObject *base, PyObject *dict)

Return value: New reference.

Same as PyErr_NewException(), except that the new exception class can easily be given a docstring: If doc is non-NULL, it will be used as the docstring for the exception class.

Nouveau dans la version 3.2.

Objets exception

PyObject* PyException_GetTraceback(PyObject *ex)

Return value: New reference.

Return the traceback associated with the exception as a new reference, as accessible from Python through __traceback__. If there is no traceback associated, this returns NULL.

int PyException_SetTraceback(PyObject *ex, PyObject *tb)

Set the traceback associated with the exception to tb. Use Py_None to clear it.

PyObject* PyException_GetContext(PyObject *ex)

Return the context (another exception instance during whose handling ex was raised) associated with the exception as a new reference, as accessible from Python through __context__. If there is no context associated, this returns NULL.

void PyException_SetContext(PyObject *ex, PyObject *ctx)

Set the context associated with the exception to ctx. Use NULL to clear it. There is no type check to make sure that ctx is an exception instance. This steals a reference to ctx.

PyObject* PyException_GetCause(PyObject *ex)

Return the cause (either an exception instance, or None, set by raise ... from ...) associated with the exception as a new reference, as accessible from Python through __cause__.

void PyException_SetCause(PyObject *ex, PyObject *cause)

Set the cause associated with the exception to cause. Use NULL to clear it. There is no type check to make sure that cause is either an exception instance or None. This steals a reference to cause.

__suppress_context__ is implicitly set to True by this function.

Objets exception Unicode

The following functions are used to create and modify Unicode exceptions from C.

PyObject* PyUnicodeDecodeError_Create(const char *encoding, const char *object, Py_ssize_t length, Py_ssize_t start, Py_ssize_t end, const char *reason)

Create a UnicodeDecodeError object with the attributes encoding, object, length, start, end and reason. encoding and reason are UTF-8 encoded strings.

PyObject* PyUnicodeEncodeError_Create(const char *encoding, const Py_UNICODE *object, Py_ssize_t length, Py_ssize_t start, Py_ssize_t end, const char *reason)

Create a UnicodeEncodeError object with the attributes encoding, object, length, start, end and reason. encoding and reason are UTF-8 encoded strings.

PyObject* PyUnicodeTranslateError_Create(const Py_UNICODE *object, Py_ssize_t length, Py_ssize_t start, Py_ssize_t end, const char *reason)

Create a UnicodeTranslateError object with the attributes object, length, start, end and reason. reason is a UTF-8 encoded string.

PyObject* PyUnicodeDecodeError_GetEncoding(PyObject *exc)

PyObject* PyUnicodeEncodeError_GetEncoding(PyObject *exc)

Return the encoding attribute of the given exception object.

PyObject* PyUnicodeDecodeError_GetObject(PyObject *exc)

PyObject* PyUnicodeEncodeError_GetObject(PyObject *exc)

PyObject* PyUnicodeTranslateError_GetObject(PyObject *exc)

Return the object attribute of the given exception object.

int PyUnicodeDecodeError_GetStart(PyObject *exc, Py_ssize_t *start)

int PyUnicodeEncodeError_GetStart(PyObject *exc, Py_ssize_t *start)

int PyUnicodeTranslateError_GetStart(PyObject *exc, Py_ssize_t *start)

Get the start attribute of the given exception object and place it into *start. start must not be NULL. Return 0 on success, -1 on failure.

int PyUnicodeDecodeError_SetStart(PyObject *exc, Py_ssize_t start)

int PyUnicodeEncodeError_SetStart(PyObject *exc, Py_ssize_t start)

int PyUnicodeTranslateError_SetStart(PyObject *exc, Py_ssize_t start)

Set the start attribute of the given exception object to start. Return 0 on success, -1 on failure.

int PyUnicodeDecodeError_GetEnd(PyObject *exc, Py_ssize_t *end)

int PyUnicodeEncodeError_GetEnd(PyObject *exc, Py_ssize_t *end)

int PyUnicodeTranslateError_GetEnd(PyObject *exc, Py_ssize_t *end)

Get the end attribute of the given exception object and place it into *end. end must not be NULL. Return 0 on success, -1 on failure.

int PyUnicodeDecodeError_SetEnd(PyObject *exc, Py_ssize_t end)

int PyUnicodeEncodeError_SetEnd(PyObject *exc, Py_ssize_t end)

int PyUnicodeTranslateError_SetEnd(PyObject *exc, Py_ssize_t end)

Set the end attribute of the given exception object to end. Return 0 on success, -1 on failure.

PyObject* PyUnicodeDecodeError_GetReason(PyObject *exc)

PyObject* PyUnicodeEncodeError_GetReason(PyObject *exc)

PyObject* PyUnicodeTranslateError_GetReason(PyObject *exc)

Return the reason attribute of the given exception object.

int PyUnicodeDecodeError_SetReason(PyObject *exc, const char *reason)

int PyUnicodeEncodeError_SetReason(PyObject *exc, const char *reason)

int PyUnicodeTranslateError_SetReason(PyObject *exc, const char *reason)

Set the reason attribute of the given exception object to reason. Return 0 on success, -1 on failure.

Contrôle de la récursion

These two functions provide a way to perform safe recursive calls at the C level, both in the core and in extension modules. They are needed if the recursive code does not necessarily invoke Python code (which tracks its recursion depth automatically).

int Py_EnterRecursiveCall(const char *where)

Marks a point where a recursive C-level call is about to be performed.

If USE_STACKCHECK is defined, this function checks if the OS stack overflowed using PyOS_CheckStack(). In this is the case, it sets a MemoryError and returns a nonzero value.

The function then checks if the recursion limit is reached. If this is the case, a RecursionError is set and a nonzero value is returned. Otherwise, zero is returned.

where should be a string such as " in instance check" to be concatenated to the RecursionError message caused by the recursion depth limit.

void Py_LeaveRecursiveCall()

Ends a Py_EnterRecursiveCall(). Must be called once for each successful invocation of Py_EnterRecursiveCall().

Properly implementing tp_repr for container types requires special recursion handling. In addition to protecting the stack, tp_repr also needs to track objects to prevent cycles. The following two functions facilitate this functionality. Effectively, these are the C equivalent to reprlib.recursive_repr().

int Py_ReprEnter(PyObject *object)

Called at the beginning of the tp_repr implementation to detect cycles.

If the object has already been processed, the function returns a positive integer. In that case the tp_repr implementation should return a string object indicating a cycle. As examples, dict objects return {...} and list objects return [...].

The function will return a negative integer if the recursion limit is reached. In that case the tp_repr implementation should typically return NULL.

Otherwise, the function returns zero and the tp_repr implementation can continue normally.

void Py_ReprLeave(PyObject *object)

Ends a Py_ReprEnter(). Must be called once for each invocation of Py_ReprEnter() that returns zero.

Exceptions standards

All standard Python exceptions are available as global variables whose names are PyExc_ followed by the Python exception name. These have the type PyObject*; they are all class objects. For completeness, here are all the variables:

Nom C

Nom Python

Notes

PyExc_BaseException

BaseException

(1)

PyExc_Exception

Exception

(1)

PyExc_ArithmeticError

ArithmeticError

(1)

PyExc_AssertionError

AssertionError

PyExc_AttributeError

AttributeError

PyExc_BlockingIOError

BlockingIOError

PyExc_BrokenPipeError

BrokenPipeError

PyExc_BufferError

BufferError

PyExc_ChildProcessError

ChildProcessError

PyExc_ConnectionAbortedError

ConnectionAbortedError

PyExc_ConnectionError

ConnectionError

PyExc_ConnectionRefusedError

ConnectionRefusedError

PyExc_ConnectionResetError

ConnectionResetError

PyExc_EOFError

EOFError

PyExc_FileExistsError

FileExistsError

PyExc_FloatingPointError

FileNotFoundError

PyExc_FloatingPointError

FloatingPointError

PyExc_GeneratorExit

GeneratorExit

PyExc_ImportError

ImportError

PyExc_IndentationError

IndentationError

PyExc_IndexError

IndexError

PyExc_InterruptedError

InterruptedError

PyExc_IsADirectoryError

IsADirectoryError

PyExc_KeyError

KeyError

PyExc_KeyboardInterrupt

KeyboardInterrupt

PyExc_LookupError

LookupError

(1)

PyExc_MemoryError

MemoryError

PyExc_ModuleNotFoundError

ModuleNotFoundError

PyExc_NameError

NameError

PyExc_NotADirectoryError

NotADirectoryError

PyExc_NotImplementedError

NotImplementedError

PyExc_OSError

OSError

(1)

PyExc_OverflowError

OverflowError

PyExc_PermissionError

PermissionError

PyExc_ProcessLookupError

ProcessLookupError

PyExc_ReferenceError

RecursionError

PyExc_ReferenceError

ReferenceError

(2)

PyExc_RuntimeError

RuntimeError

PyExc_StopAsyncIteration

StopAsyncIteration

PyExc_StopIteration

StopIteration

PyExc_SyntaxError

SyntaxError

PyExc_SystemError

SystemError

PyExc_SystemExit

SystemExit

PyExc_TabError

TabError

PyExc_ImportError

TimeoutError

PyExc_TypeError

TypeError

PyExc_UnboundLocalError

UnboundLocalError

PyExc_UnicodeDecodeError

UnicodeDecodeError

PyExc_UnicodeEncodeError

UnicodeEncodeError

PyExc_UnicodeError

UnicodeError

PyExc_UnicodeTranslateError

UnicodeTranslateError

PyExc_ValueError

ValueError

PyExc_ZeroDivisionError

ZeroDivisionError

Nouveau dans la version 3.3: PyExc_BlockingIOError, PyExc_BrokenPipeError, PyExc_ChildProcessError, PyExc_ConnectionError, PyExc_ConnectionAbortedError, PyExc_ConnectionRefusedError, PyExc_ConnectionResetError, PyExc_FileExistsError, PyExc_FileNotFoundError, PyExc_InterruptedError, PyExc_IsADirectoryError, PyExc_NotADirectoryError, PyExc_PermissionError, PyExc_ProcessLookupError and PyExc_TimeoutError were introduced following PEP 3151 [https://www.python.org/dev/peps/pep-3151].

Nouveau dans la version 3.5: PyExc_StopAsyncIteration et PyExc_RecursionError.

Nouveau dans la version 3.6: PyExc_ModuleNotFoundError.

These are compatibility aliases to PyExc_OSError:

Nom C

Notes

PyExc_EnvironmentError

PyExc_IOError

PyExc_WindowsError

(3)

Modifié dans la version 3.3: These aliases used to be separate exception types.

Notes :

C’est la classe de base pour les autres exceptions standards.

Identique à weakref.ReferenceError.

Only defined on Windows; protect code that uses this by testing that the preprocessor macro MS_WINDOWS is defined.

Standard Warning Categories

All standard Python warning categories are available as global variables whose names are PyExc_ followed by the Python exception name. These have the type PyObject*; they are all class objects. For completeness, here are all the variables:

Nom C

Nom Python

Notes

PyExc_Warning

Warning

(1)

PyExc_BytesWarning

BytesWarning

PyExc_DeprecationWarning

DeprecationWarning

PyExc_FutureWarning

FutureWarning

PyExc_ImportWarning

ImportWarning

PyExc_PendingDeprecationWarning

PendingDeprecationWarning

PyExc_ResourceWarning

ResourceWarning

PyExc_RuntimeWarning

RuntimeWarning

PyExc_SyntaxWarning

SyntaxWarning

PyExc_UnicodeWarning

UnicodeWarning

PyExc_UserWarning

UserWarning

Nouveau dans la version 3.2: PyExc_ResourceWarning.

Notes :

C’est la classe de base pour les autres catégories de warning.

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Utilitaires

Les fonctions de ce chapitre sont utilitaires, certaines aident à rendre le code en C plus portable, d’autres à utiliser des modules Python depuis du C, analyser des arguments de fonctions, ou encore construire des valeurs Python à partir de valeurs C.

Operating System Utilities

System Functions

Process Control

Importer des modules

Data marshalling support

Analyse des arguments et construction des valeurs

Analyse des arguments

Chaînes et tampons

Les nombres

Autres objets

Fonction de l’API

Construction des valeurs

Conversion et formatage de chaînes

Réflexion

Codec registry and support functions

Codec lookup API

Registry API for Unicode encoding error handlers

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Operating System Utilities

PyObject* PyOS_FSPath(PyObject *path)

Return value: New reference.

Return the file system representation for path. If the object is a str or bytes object, then its reference count is incremented. If the object implements the os.PathLike interface, then __fspath__() is returned as long as it is a str or bytes object. Otherwise TypeError is raised and NULL is returned.

Nouveau dans la version 3.6.

int Py_FdIsInteractive(FILE *fp, const char *filename)

Return true (nonzero) if the standard I/O file fp with name filename is deemed interactive. This is the case for files for which isatty(fileno(fp)) is true. If the global flag Py_InteractiveFlag is true, this function also returns true if the filename pointer is NULL or if the name is equal to one of the strings '<stdin>' or '???'.

void PyOS_AfterFork()

Function to update some internal state after a process fork; this should be called in the new process if the Python interpreter will continue to be used. If a new executable is loaded into the new process, this function does not need to be called.

int PyOS_CheckStack()

Return true when the interpreter runs out of stack space. This is a reliable check, but is only available when USE_STACKCHECK is defined (currently on Windows using the Microsoft Visual C++ compiler). USE_STACKCHECK will be defined automatically; you should never change the definition in your own code.

PyOS_sighandler_t PyOS_getsig(int i)

Return the current signal handler for signal i. This is a thin wrapper around either sigaction() or signal(). Do not call those functions directly! PyOS_sighandler_t is a typedef alias for void (*)(int).

PyOS_sighandler_t PyOS_setsig(int i, PyOS_sighandler_t h)

Set the signal handler for signal i to be h; return the old signal handler. This is a thin wrapper around either sigaction() or signal(). Do not call those functions directly! PyOS_sighandler_t is a typedef alias for void (*)(int).

wchar_t* Py_DecodeLocale(const char* arg, size_t *size)

Decode a byte string from the locale encoding with the surrogateescape error handler: undecodable bytes are decoded as characters in range U+DC80..U+DCFF. If a byte sequence can be decoded as a surrogate character, escape the bytes using the surrogateescape error handler instead of decoding them.

Encoding, highest priority to lowest priority:

UTF-8 on macOS and Android;

ASCII if the LC_CTYPE locale is "C", nl_langinfo(CODESET) returns the ASCII encoding (or an alias), and mbstowcs() and wcstombs() functions use the ISO-8859-1 encoding.

the current locale encoding (LC_CTYPE locale).

Return a pointer to a newly allocated wide character string, use PyMem_RawFree() to free the memory. If size is not NULL, write the number of wide characters excluding the null character into *size.

Return NULL on decoding error or memory allocation error. If size is not NULL, *size is set to (size_t)-1 on memory error or set to (size_t)-2 on decoding error.

Decoding errors should never happen, unless there is a bug in the C library.

Use the Py_EncodeLocale() function to encode the character string back to a byte string.

Voir aussi

The PyUnicode_DecodeFSDefaultAndSize() and PyUnicode_DecodeLocaleAndSize() functions.

Nouveau dans la version 3.5.

char* Py_EncodeLocale(const wchar_t *text, size_t *error_pos)

Encode a wide character string to the locale encoding with the surrogateescape error handler: surrogate characters in the range U+DC80..U+DCFF are converted to bytes 0x80..0xFF.

Encoding, highest priority to lowest priority:

UTF-8 on macOS and Android;

ASCII if the LC_CTYPE locale is "C", nl_langinfo(CODESET) returns the ASCII encoding (or an alias), and mbstowcs() and wcstombs() functions uses the ISO-8859-1 encoding.

the current locale encoding.

Return a pointer to a newly allocated byte string, use PyMem_Free() to free the memory. Return NULL on encoding error or memory allocation error

If error_pos is not NULL, *error_pos is set to the index of the invalid character on encoding error, or set to (size_t)-1 otherwise.

Use the Py_DecodeLocale() function to decode the bytes string back to a wide character string.

Voir aussi

The PyUnicode_EncodeFSDefault() and PyUnicode_EncodeLocale() functions.

Nouveau dans la version 3.5.

System Functions

These are utility functions that make functionality from the sys module accessible to C code. They all work with the current interpreter thread’s sys module’s dict, which is contained in the internal thread state structure.

PyObject *PySys_GetObject(const char *name)

Return value: Borrowed reference.

Return the object name from the sys module or NULL if it does not exist, without setting an exception.

int PySys_SetObject(const char *name, PyObject *v)

Set name in the sys module to v unless v is NULL, in which case name is deleted from the sys module. Returns 0 on success, -1 on error.

void PySys_ResetWarnOptions()

Reset sys.warnoptions to an empty list.

void PySys_AddWarnOption(wchar_t *s)

Append s to sys.warnoptions.

void PySys_AddWarnOptionUnicode(PyObject *unicode)

Append unicode to sys.warnoptions.

void PySys_SetPath(wchar_t *path)

Set sys.path to a list object of paths found in path which should be a list of paths separated with the platform’s search path delimiter (: on Unix, ; on Windows).

void PySys_WriteStdout(const char *format, ...)

Write the output string described by format to sys.stdout. No exceptions are raised, even if truncation occurs (see below).

format should limit the total size of the formatted output string to 1000 bytes or less – after 1000 bytes, the output string is truncated. In particular, this means that no unrestricted « %s » formats should occur; these should be limited using « %.<N>s » where <N> is a decimal number calculated so that <N> plus the maximum size of other formatted text does not exceed 1000 bytes. Also watch out for « %f », which can print hundreds of digits for very large numbers.

If a problem occurs, or sys.stdout is unset, the formatted message is written to the real (C level) stdout.

void PySys_WriteStderr(const char *format, ...)

As PySys_WriteStdout(), but write to sys.stderr or stderr instead.

void PySys_FormatStdout(const char *format, ...)

Function similar to PySys_WriteStdout() but format the message using PyUnicode_FromFormatV() and don’t truncate the message to an arbitrary length.

Nouveau dans la version 3.2.

void PySys_FormatStderr(const char *format, ...)

As PySys_FormatStdout(), but write to sys.stderr or stderr instead.

Nouveau dans la version 3.2.

void PySys_AddXOption(const wchar_t *s)

Parse s as a set of -X options and add them to the current options mapping as returned by PySys_GetXOptions().

Nouveau dans la version 3.2.

PyObject *PySys_GetXOptions()

Return value: Borrowed reference.

Return the current dictionary of -X options, similarly to sys._xoptions. On error, NULL is returned and an exception is set.

Nouveau dans la version 3.2.

Process Control

void Py_FatalError(const char *message)

Print a fatal error message and kill the process. No cleanup is performed. This function should only be invoked when a condition is detected that would make it dangerous to continue using the Python interpreter; e.g., when the object administration appears to be corrupted. On Unix, the standard C library function abort() is called which will attempt to produce a core file.

void Py_Exit(int status)

Exit the current process. This calls Py_FinalizeEx() and then calls the standard C library function exit(status). If Py_FinalizeEx() indicates an error, the exit status is set to 120.

Modifié dans la version 3.6: Errors from finalization no longer ignored.

int Py_AtExit(void (*func)())

Register a cleanup function to be called by Py_FinalizeEx(). The cleanup function will be called with no arguments and should return no value. At most 32 cleanup functions can be registered. When the registration is successful, Py_AtExit() returns 0; on failure, it returns -1. The cleanup function registered last is called first. Each cleanup function will be called at most once. Since Python’s internal finalization will have completed before the cleanup function, no Python APIs should be called by func.

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Importer des modules

PyObject* PyImport_ImportModule(const char *name)

Return value: New reference.

This is a simplified interface to PyImport_ImportModuleEx() below, leaving the globals and locals arguments set to NULL and level set to 0. When the name argument contains a dot (when it specifies a submodule of a package), the fromlist argument is set to the list ['*'] so that the return value is the named module rather than the top-level package containing it as would otherwise be the case. (Unfortunately, this has an additional side effect when name in fact specifies a subpackage instead of a submodule: the submodules specified in the package’s __all__ variable are loaded.) Return a new reference to the imported module, or NULL with an exception set on failure. A failing import of a module doesn’t leave the module in sys.modules.

This function always uses absolute imports.

PyObject* PyImport_ImportModuleNoBlock(const char *name)

This function is a deprecated alias of PyImport_ImportModule().

Modifié dans la version 3.3: This function used to fail immediately when the import lock was held by another thread. In Python 3.3 though, the locking scheme switched to per-module locks for most purposes, so this function’s special behaviour isn’t needed anymore.

PyObject* PyImport_ImportModuleEx(const char *name, PyObject *globals, PyObject *locals, PyObject *fromlist)

Return value: New reference.

Import a module. This is best described by referring to the built-in Python function __import__().

The return value is a new reference to the imported module or top-level package, or NULL with an exception set on failure. Like for __import__(), the return value when a submodule of a package was requested is normally the top-level package, unless a non-empty fromlist was given.

Failing imports remove incomplete module objects, like with PyImport_ImportModule().

PyObject* PyImport_ImportModuleLevelObject(PyObject *name, PyObject *globals, PyObject *locals, PyObject *fromlist, int level)

Return value: New reference.

Import a module. This is best described by referring to the built-in Python function __import__(), as the standard __import__() function calls this function directly.

The return value is a new reference to the imported module or top-level package, or NULL with an exception set on failure. Like for __import__(), the return value when a submodule of a package was requested is normally the top-level package, unless a non-empty fromlist was given.

Nouveau dans la version 3.3.

PyObject* PyImport_ImportModuleLevel(const char *name, PyObject *globals, PyObject *locals, PyObject *fromlist, int level)

Return value: New reference.

Similar to PyImport_ImportModuleLevelObject(), but the name is a UTF-8 encoded string instead of a Unicode object.

Modifié dans la version 3.3: Negative values for level are no longer accepted.

PyObject* PyImport_Import(PyObject *name)

Return value: New reference.

This is a higher-level interface that calls the current « import hook function » (with an explicit level of 0, meaning absolute import). It invokes the __import__() function from the __builtins__ of the current globals. This means that the import is done using whatever import hooks are installed in the current environment.

This function always uses absolute imports.

PyObject* PyImport_ReloadModule(PyObject *m)

Return value: New reference.

Reload a module. Return a new reference to the reloaded module, or NULL with an exception set on failure (the module still exists in this case).

PyObject* PyImport_AddModuleObject(PyObject *name)

Return value: Borrowed reference.

Return the module object corresponding to a module name. The name argument may be of the form package.module. First check the modules dictionary if there’s one there, and if not, create a new one and insert it in the modules dictionary. Return NULL with an exception set on failure.

Note

This function does not load or import the module; if the module wasn’t already loaded, you will get an empty module object. Use PyImport_ImportModule() or one of its variants to import a module. Package structures implied by a dotted name for name are not created if not already present.

Nouveau dans la version 3.3.

PyObject* PyImport_AddModule(const char *name)

Return value: Borrowed reference.

Similar to PyImport_AddModuleObject(), but the name is a UTF-8 encoded string instead of a Unicode object.

PyObject* PyImport_ExecCodeModule(const char *name, PyObject *co)

Return value: New reference.

Given a module name (possibly of the form package.module) and a code object read from a Python bytecode file or obtained from the built-in function compile(), load the module. Return a new reference to the module object, or NULL with an exception set if an error occurred. name is removed from sys.modules in error cases, even if name was already in sys.modules on entry to PyImport_ExecCodeModule(). Leaving incompletely initialized modules in sys.modules is dangerous, as imports of such modules have no way to know that the module object is an unknown (and probably damaged with respect to the module author’s intents) state.

The module’s __spec__ and __loader__ will be set, if not set already, with the appropriate values. The spec’s loader will be set to the module’s __loader__ (if set) and to an instance of SourceFileLoader otherwise.

The module’s __file__ attribute will be set to the code object’s co_filename. If applicable, __cached__ will also be set.

This function will reload the module if it was already imported. See PyImport_ReloadModule() for the intended way to reload a module.

If name points to a dotted name of the form package.module, any package structures not already created will still not be created.

See also PyImport_ExecCodeModuleEx() and PyImport_ExecCodeModuleWithPathnames().

PyObject* PyImport_ExecCodeModuleEx(const char *name, PyObject *co, const char *pathname)

Return value: New reference.

Like PyImport_ExecCodeModule(), but the __file__ attribute of the module object is set to pathname if it is non-NULL.

See also PyImport_ExecCodeModuleWithPathnames().

PyObject* PyImport_ExecCodeModuleObject(PyObject *name, PyObject *co, PyObject *pathname, PyObject *cpathname)

Return value: New reference.

Like PyImport_ExecCodeModuleEx(), but the __cached__ attribute of the module object is set to cpathname if it is non-NULL. Of the three functions, this is the preferred one to use.

Nouveau dans la version 3.3.

PyObject* PyImport_ExecCodeModuleWithPathnames(const char *name, PyObject *co, const char *pathname, const char *cpathname)

Return value: New reference.

Like PyImport_ExecCodeModuleObject(), but name, pathname and cpathname are UTF-8 encoded strings. Attempts are also made to figure out what the value for pathname should be from cpathname if the former is set to NULL.

Nouveau dans la version 3.2.

Modifié dans la version 3.3: Uses imp.source_from_cache() in calculating the source path if only the bytecode path is provided.

long PyImport_GetMagicNumber()

Return the magic number for Python bytecode files (a.k.a. .pyc file). The magic number should be present in the first four bytes of the bytecode file, in little-endian byte order. Returns -1 on error.

Modifié dans la version 3.3: Return value of -1 upon failure.

const char * PyImport_GetMagicTag()

Return the magic tag string for PEP 3147 [https://www.python.org/dev/peps/pep-3147] format Python bytecode file names. Keep in mind that the value at sys.implementation.cache_tag is authoritative and should be used instead of this function.

Nouveau dans la version 3.2.

PyObject* PyImport_GetModuleDict()

Return value: Borrowed reference.

Return the dictionary used for the module administration (a.k.a. sys.modules). Note that this is a per-interpreter variable.

PyObject* PyImport_GetImporter(PyObject *path)

Return value: New reference.

Return a finder object for a sys.path/pkg.__path__ item path, possibly by fetching it from the sys.path_importer_cache dict. If it wasn’t yet cached, traverse sys.path_hooks until a hook is found that can handle the path item. Return None if no hook could; this tells our caller that the path based finder could not find a finder for this path item. Cache the result in sys.path_importer_cache. Return a new reference to the finder object.

void _PyImport_Init()

Initialize the import mechanism. For internal use only.

void PyImport_Cleanup()

Empty the module table. For internal use only.

void _PyImport_Fini()

Finalize the import mechanism. For internal use only.

PyObject* _PyImport_FindExtension(char *, char *)

For internal use only.

int PyImport_ImportFrozenModuleObject(PyObject *name)

Return value: New reference.

Load a frozen module named name. Return 1 for success, 0 if the module is not found, and -1 with an exception set if the initialization failed. To access the imported module on a successful load, use PyImport_ImportModule(). (Note the misnomer — this function would reload the module if it was already imported.)

Nouveau dans la version 3.3.

Modifié dans la version 3.4: The __file__ attribute is no longer set on the module.

int PyImport_ImportFrozenModule(const char *name)

Similar to PyImport_ImportFrozenModuleObject(), but the name is a UTF-8 encoded string instead of a Unicode object.

struct _frozen

This is the structure type definition for frozen module descriptors, as generated by the freeze utility (see Tools/freeze/ in the Python source distribution). Its definition, found in Include/import.h, is:

struct _frozen {
    char *name;
    unsigned char *code;
    int size;
};

const struct _frozen* PyImport_FrozenModules

This pointer is initialized to point to an array of struct _frozen records, terminated by one whose members are all NULL or zero. When a frozen module is imported, it is searched in this table. Third-party code could play tricks with this to provide a dynamically created collection of frozen modules.

int PyImport_AppendInittab(const char *name, PyObject* (*initfunc)(void))

Add a single module to the existing table of built-in modules. This is a convenience wrapper around PyImport_ExtendInittab(), returning -1 if the table could not be extended. The new module can be imported by the name name, and uses the function initfunc as the initialization function called on the first attempted import. This should be called before Py_Initialize().

struct _inittab

Structure describing a single entry in the list of built-in modules. Each of these structures gives the name and initialization function for a module built into the interpreter. The name is an ASCII encoded string. Programs which embed Python may use an array of these structures in conjunction with PyImport_ExtendInittab() to provide additional built-in modules. The structure is defined in Include/import.h as:

struct _inittab {
    char *name;                 /* ASCII encoded string */
    PyObject* (*initfunc)(void);
};

int PyImport_ExtendInittab(struct _inittab *newtab)

Add a collection of modules to the table of built-in modules. The newtab array must end with a sentinel entry which contains NULL for the name field; failure to provide the sentinel value can result in a memory fault. Returns 0 on success or -1 if insufficient memory could be allocated to extend the internal table. In the event of failure, no modules are added to the internal table. This should be called before Py_Initialize().

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Data marshalling support

These routines allow C code to work with serialized objects using the same data format as the marshal module. There are functions to write data into the serialization format, and additional functions that can be used to read the data back. Files used to store marshalled data must be opened in binary mode.

Numeric values are stored with the least significant byte first.

The module supports two versions of the data format: version 0 is the historical version, version 1 shares interned strings in the file, and upon unmarshalling. Version 2 uses a binary format for floating point numbers. Py_MARSHAL_VERSION indicates the current file format (currently 2).

void PyMarshal_WriteLongToFile(long value, FILE *file, int version)

Marshal a long integer, value, to file. This will only write the least-significant 32 bits of value; regardless of the size of the native long type. version indicates the file format.

void PyMarshal_WriteObjectToFile(PyObject *value, FILE *file, int version)

Marshal a Python object, value, to file. version indicates the file format.

PyObject* PyMarshal_WriteObjectToString(PyObject *value, int version)

Return value: New reference.

Return a bytes object containing the marshalled representation of value. version indicates the file format.

The following functions allow marshalled values to be read back in.

long PyMarshal_ReadLongFromFile(FILE *file)

Return a C long from the data stream in a FILE* opened for reading. Only a 32-bit value can be read in using this function, regardless of the native size of long.

On error, sets the appropriate exception (EOFError) and returns -1.

int PyMarshal_ReadShortFromFile(FILE *file)

Return a C short from the data stream in a FILE* opened for reading. Only a 16-bit value can be read in using this function, regardless of the native size of short.

On error, sets the appropriate exception (EOFError) and returns -1.

PyObject* PyMarshal_ReadObjectFromFile(FILE *file)

Return value: New reference.

Return a Python object from the data stream in a FILE* opened for reading.

On error, sets the appropriate exception (EOFError, ValueError or TypeError) and returns NULL.

PyObject* PyMarshal_ReadLastObjectFromFile(FILE *file)

Return value: New reference.

Return a Python object from the data stream in a FILE* opened for reading. Unlike PyMarshal_ReadObjectFromFile(), this function assumes that no further objects will be read from the file, allowing it to aggressively load file data into memory so that the de-serialization can operate from data in memory rather than reading a byte at a time from the file. Only use these variant if you are certain that you won’t be reading anything else from the file.

On error, sets the appropriate exception (EOFError, ValueError or TypeError) and returns NULL.

PyObject* PyMarshal_ReadObjectFromString(const char *data, Py_ssize_t len)

Return value: New reference.

Return a Python object from the data stream in a byte buffer containing len bytes pointed to by data.

On error, sets the appropriate exception (EOFError, ValueError or TypeError) and returns NULL.

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Analyse des arguments et construction des valeurs

Ces fonctions sont utiles pour créer vos propres fonctions et méthodes d’extensions. Des informations supplémentaires et des exemples sont disponibles ici: Extension et intégration de l’interpréteur Python.

Dans Les trois premières de ces fonctions décrites, PyArg_ParseTuple(), PyArg_ParseTupleAndKeywords(), et PyArg_Parse(), toutes utilisent des chaînes de format qui sont utilisées pour indiquer à la fonction les arguments attendus. Les chaînes de format utilise la même syntaxe pour chacune de ces fonctions.

Analyse des arguments

Une chaîne de format se compose de zéro ou plusieurs « unités de format ». Une unité de format décrit un objet Python, elle est généralement composée d’un seul caractère ou d’une séquence d’unités de format entre parenthèses. À quelques exceptions près, une unité de format qui n’est pas une séquence entre parenthèses correspond normalement à un argument d’une seule adresse pour ces fonctions. Dans la description qui suit, la forme entre guillemets est l’unité de format, l’entrée entre parenthèses est le type d’objet Python qui correspond à l’unité de format, et l’entrée entre crochets est le type de la variable C (ou des variables) dont l’adresse doit être donnée.

Chaînes et tampons

Ces formats permettent d’accéder à un objet sous forme d’un fragment de mémoire contigüe. Il n’est pas nécessaire d’allouer la mémoire pour l”unicode ou le bytes renvoyé.

In general, when a format sets a pointer to a buffer, the buffer is managed by the corresponding Python object, and the buffer shares the lifetime of this object. You won’t have to release any memory yourself. The only exceptions are es, es#, et and et#.

Néanmoins, quand une structure Py_buffer est en cours de remplissage, le tampon sous-jacent est verrouillé pour permettre à l’appelant d’utiliser le tampon par la suite, même à l’intérieur d’un bloc Py_BEGIN_ALLOW_THREADS, sans risques de voir des données muables se faire redimensionner ou supprimer. En conséquence, il vous appartient d’appeler PyBuffer_Release() après avoir terminé de traiter les données (ou après une interruption prématurée du traitement de ces données).

Sauf indication contraire, les tampons ne se terminent pas par NUL.

Some formats require a read-only bytes-like object, and set a pointer instead of a buffer structure. They work by checking that the object’s PyBufferProcs.bf_releasebuffer field is NULL, which disallows mutable objects such as bytearray.

Note

Pour toutes les variantes du marqueur # (s#, y#, etc), le type de l’argument length (int ou Py_ssize_t) est contrôlé en définissant la macro PY_SSIZE_T_CLEAN avant d’inclure le fichier Python.h. Si la macro est définie, la longueur est de type Py_ssize_t au lieu d’être de type int. Ce comportement changera dans une future version de Python, qui supportera seulement Py_ssize_t a la place de int. Il est préférable de toujours définir PY_SSIZE_T_CLEAN.

s (str) [const char *]

Convert a Unicode object to a C pointer to a character string. A pointer to an existing string is stored in the character pointer variable whose address you pass. The C string is NUL-terminated. The Python string must not contain embedded null code points; if it does, a ValueError exception is raised. Unicode objects are converted to C strings using 'utf-8' encoding. If this conversion fails, a UnicodeError is raised.

Note

This format does not accept bytes-like objects. If you want to accept filesystem paths and convert them to C character strings, it is preferable to use the O& format with PyUnicode_FSConverter() as converter.

Modifié dans la version 3.5: Previously, TypeError was raised when embedded null code points were encountered in the Python string.

s* (str ou bytes-like object) [Py_buffer]

This format accepts Unicode objects as well as bytes-like objects. It fills a Py_buffer structure provided by the caller. In this case the resulting C string may contain embedded NUL bytes. Unicode objects are converted to C strings using 'utf-8' encoding.

s# (str, read-only bytes-like object) [const char *, int or Py_ssize_t]

Like s*, except that it doesn’t accept mutable objects. The result is stored into two C variables, the first one a pointer to a C string, the second one its length. The string may contain embedded null bytes. Unicode objects are converted to C strings using 'utf-8' encoding.

z (str ou None) [const char *]

Comme s, mais l’objet Python peut aussi être None, auquel cas le pointeur C devient NULL.

z* (str, bytes-like object ou None) [Py_buffer]

Like s*, but the Python object may also be None, in which case the buf member of the Py_buffer structure is set to NULL.

z# (str, read-only bytes-like object or None) [const char *, int]

Comme s#, mais l’objet Python peut également être None, dans ce cas le pointeur C est définie à NULL.

y (read-only bytes-like object) [const char *]

This format converts a bytes-like object to a C pointer to a character string; it does not accept Unicode objects. The bytes buffer must not contain embedded null bytes; if it does, a ValueError exception is raised.

Modifié dans la version 3.5: Previously, TypeError was raised when embedded null bytes were encountered in the bytes buffer.

y* (bytes-like object) [Py_buffer]

This variant on s* doesn’t accept Unicode objects, only bytes-like objects. This is the recommended way to accept binary data.

y# (read-only bytes-like object) [const char *, int]

Cette variante de s# n’accepte pas les objets Unicode, uniquement des objets assimilés à des octets.

S (bytes) [PyBytesObject *]

Requires that the Python object is a bytes object, without attempting any conversion. Raises TypeError if the object is not a bytes object. The C variable may also be declared as PyObject*.

Y (bytearray) [PyByteArrayObject *]

Requires that the Python object is a bytearray object, without attempting any conversion. Raises TypeError if the object is not a bytearray object. The C variable may also be declared as PyObject*.

u (str) [Py_UNICODE *]

Convert a Python Unicode object to a C pointer to a NUL-terminated buffer of Unicode characters. You must pass the address of a Py_UNICODE pointer variable, which will be filled with the pointer to an existing Unicode buffer. Please note that the width of a Py_UNICODE character depends on compilation options (it is either 16 or 32 bits). The Python string must not contain embedded null code points; if it does, a ValueError exception is raised.

Modifié dans la version 3.5: Previously, TypeError was raised when embedded null code points were encountered in the Python string.

Deprecated since version 3.3, will be removed in version 4.0: Part of the old-style Py_UNICODE API; please migrate to using PyUnicode_AsWideCharString().

u# (str) [Py_UNICODE *, int]

This variant on u stores into two C variables, the first one a pointer to a Unicode data buffer, the second one its length. This variant allows null code points.

Deprecated since version 3.3, will be removed in version 4.0: Part of the old-style Py_UNICODE API; please migrate to using PyUnicode_AsWideCharString().

Z (str ou None) [Py_UNICODE *]

Comme u, mais l’objet Python peut aussi être None, auquel cas le pointeur Py_UNICODE vaut NULL.

Deprecated since version 3.3, will be removed in version 4.0: Part of the old-style Py_UNICODE API; please migrate to using PyUnicode_AsWideCharString().

Z# (str ou None) [Py_UNICODE *, int]

Comme u#, mais l’objet Python peut également être None, auquel cas le pointeur Py_UNICODE vaut NULL.

Deprecated since version 3.3, will be removed in version 4.0: Part of the old-style Py_UNICODE API; please migrate to using PyUnicode_AsWideCharString().

U (str) [PyObject *]

Requires that the Python object is a Unicode object, without attempting any conversion. Raises TypeError if the object is not a Unicode object. The C variable may also be declared as PyObject*.

w* (lecture-écriture bytes-like object) [Py_buffer]

This format accepts any object which implements the read-write buffer interface. It fills a Py_buffer structure provided by the caller. The buffer may contain embedded null bytes. The caller have to call PyBuffer_Release() when it is done with the buffer.

es (str) [const char *encoding, char **buffer]

This variant on s is used for encoding Unicode into a character buffer. It only works for encoded data without embedded NUL bytes.

This format requires two arguments. The first is only used as input, and must be a const char* which points to the name of an encoding as a NUL-terminated string, or NULL, in which case 'utf-8' encoding is used. An exception is raised if the named encoding is not known to Python. The second argument must be a char**; the value of the pointer it references will be set to a buffer with the contents of the argument text. The text will be encoded in the encoding specified by the first argument.

PyArg_ParseTuple() will allocate a buffer of the needed size, copy the encoded data into this buffer and adjust *buffer to reference the newly allocated storage. The caller is responsible for calling PyMem_Free() to free the allocated buffer after use.

et (str, bytes or bytearray) [const char *encoding, char **buffer]

Same as es except that byte string objects are passed through without recoding them. Instead, the implementation assumes that the byte string object uses the encoding passed in as parameter.

es# (str) [const char *encoding, char **buffer, int *buffer_length]

This variant on s# is used for encoding Unicode into a character buffer. Unlike the es format, this variant allows input data which contains NUL characters.

It requires three arguments. The first is only used as input, and must be a const char* which points to the name of an encoding as a NUL-terminated string, or NULL, in which case 'utf-8' encoding is used. An exception is raised if the named encoding is not known to Python. The second argument must be a char**; the value of the pointer it references will be set to a buffer with the contents of the argument text. The text will be encoded in the encoding specified by the first argument. The third argument must be a pointer to an integer; the referenced integer will be set to the number of bytes in the output buffer.

Il existe deux modes de fonctionnement :

If *buffer points a NULL pointer, the function will allocate a buffer of the needed size, copy the encoded data into this buffer and set *buffer to reference the newly allocated storage. The caller is responsible for calling PyMem_Free() to free the allocated buffer after usage.

If *buffer points to a non-NULL pointer (an already allocated buffer), PyArg_ParseTuple() will use this location as the buffer and interpret the initial value of *buffer_length as the buffer size. It will then copy the encoded data into the buffer and NUL-terminate it. If the buffer is not large enough, a ValueError will be set.

Dans les deux cas, *buffer_length est la longueur des données encodées, sans l’octet NUL de fin.

et# (str, bytes or bytearray) [const char *encoding, char **buffer, int *buffer_length]

Same as es# except that byte string objects are passed through without recoding them. Instead, the implementation assumes that the byte string object uses the encoding passed in as parameter.

Les nombres

b (int) [unsigned char]

Convertit un entier Python positif ou nul en un unsigned tiny int, stocké dans un unsigned char C.

B (int) [unsigned char]

Convertit un entier Python en un tiny int sans vérifier le débordement, stocké dans un unsigned char C.

h (int) [short int]

Convertit un entier Python en un short int C.

H (int) [unsigned short int]

Convertit un entier Python en un unsigned short int C, sans contrôle de débordement.

i (int) [int]

Convertit un entier Python en un int C.

I (int) [unsigned int]

Convertit un entier Python en un unsigned int C, sans contrôle de le débordement.

l (int) [long int]

Convertit un entier Python en un long int.

k (int) [unsigned long]

Convertit un entier Python en un unsigned long C sans en vérifier le débordement.

L (int) [long long]

Convert a Python integer to a C long long.

K (int) [unsigned long long]

Convert a Python integer to a C unsigned long long without overflow checking.

n (int) [Py_ssize_t]

Convertit un entier Python en un short int C.

c (bytes ou bytearray de longueur 1) [char]

Convertit un byte Python, représenté comme un objet bytes ou bytearray de longueur 1, en un char C.

Modifié dans la version 3.3: Allow bytearray objects.

C (str de longueur 1) [int]

Convertit un caractère Python, représenté comme un objet str de longueur 1, en un int C.

f (float) [float]

Convertit un nombre flottant Python vers un float.

d (float) [double]

Convertit un nombre flottant Python vers un double C.

D (complex) [Py_complex]

Convertit un nombre complexe Python vers une structure Py_complex C.

Autres objets

O (objet) [PyObject *]

Stocke un objet Python (sans aucune conversion) en un pointeur sur un objet C. Ainsi, Le programme C reçoit l’objet réel qui a été passé. Le compteur de référence sur l’objet n’est pas incrémenté. Le pointeur stocké n’est pas NULL.

O! (objet) [typeobject, PyObject *]

Store a Python object in a C object pointer. This is similar to O, but takes two C arguments: the first is the address of a Python type object, the second is the address of the C variable (of type PyObject*) into which the object pointer is stored. If the Python object does not have the required type, TypeError is raised.

O& (objet) [converter, anything]

Convert a Python object to a C variable through a converter function. This takes two arguments: the first is a function, the second is the address of a C variable (of arbitrary type), converted to void *. The converter function in turn is called as follows:

status = converter(object, address);

where object is the Python object to be converted and address is the void* argument that was passed to the PyArg_Parse*() function. The returned status should be 1 for a successful conversion and 0 if the conversion has failed. When the conversion fails, the converter function should raise an exception and leave the content of address unmodified.

If the converter returns Py_CLEANUP_SUPPORTED, it may get called a second time if the argument parsing eventually fails, giving the converter a chance to release any memory that it had already allocated. In this second call, the object parameter will be NULL; address will have the same value as in the original call.

Modifié dans la version 3.1: Py_CLEANUP_SUPPORTED à été ajouté.

p (bool) [int]

Tests the value passed in for truth (a boolean predicate) and converts the result to its equivalent C true/false integer value. Sets the int to 1 if the expression was true and 0 if it was false. This accepts any valid Python value. See Valeurs booléennes for more information about how Python tests values for truth.

Nouveau dans la version 3.3.

(items) (tuple) [matching-items]

L’objet doit être une séquence Python dont la longueur est le nombre d’unités de formats dans articles. Les arguments C doivent correspondre à chaque unité de format particulière dans articles. Les unités de formats pour les séquences peuvent être imbriquées.

It is possible to pass « long » integers (integers whose value exceeds the platform’s LONG_MAX) however no proper range checking is done — the most significant bits are silently truncated when the receiving field is too small to receive the value (actually, the semantics are inherited from downcasts in C — your mileage may vary).

Quelques autres caractères ont un sens dans une chaîne de format. On ne doit pas les trouvées dans des parenthèses imbriquées. Ce sont :

|

Indicates that the remaining arguments in the Python argument list are optional. The C variables corresponding to optional arguments should be initialized to their default value — when an optional argument is not specified, PyArg_ParseTuple() does not touch the contents of the corresponding C variable(s).

$

PyArg_ParseTupleAndKeywords() only: Indicates that the remaining arguments in the Python argument list are keyword-only. Currently, all keyword-only arguments must also be optional arguments, so | must always be specified before $ in the format string.

Nouveau dans la version 3.3.

:

The list of format units ends here; the string after the colon is used as the function name in error messages (the « associated value » of the exception that PyArg_ParseTuple() raises).

;

La liste des unités de format s’arrête ici ; la chaîne après le point-virgule est utilise comme message d’erreur au lieu du message d’erreur par défaut. : et ; sont mutuellement exclusifs.

Notez que n’importe quelles références sur un objet Python qui sont données à l’appelant sont des références empruntées ; ne décrémentez pas leur compteur de références !

Les arguments additionnels qui sont donnés à ces fonctions doivent être des adresses de variables dont le type est déterminé par la chaîne de format. Elles sont utilisées pour stocker les valeurs du n-uplet d’entrée. Il y a quelques cas, comme décrit précédemment dans le liste des unités de formats, où ces paramètres sont utilisés comme valeurs d’entrée. Dans ce cas, ils devraient correspondre à ce qui est spécifié pour l’unité de format correspondante.

For the conversion to succeed, the arg object must match the format and the format must be exhausted. On success, the PyArg_Parse*() functions return true, otherwise they return false and raise an appropriate exception. When the PyArg_Parse*() functions fail due to conversion failure in one of the format units, the variables at the addresses corresponding to that and the following format units are left untouched.

Fonction de l’API

int PyArg_ParseTuple(PyObject *args, const char *format, ...)

Parse the parameters of a function that takes only positional parameters into local variables. Returns true on success; on failure, it returns false and raises the appropriate exception.

int PyArg_VaParse(PyObject *args, const char *format, va_list vargs)

Identical to PyArg_ParseTuple(), except that it accepts a va_list rather than a variable number of arguments.

int PyArg_ParseTupleAndKeywords(PyObject *args, PyObject *kw, const char *format, char *keywords[], ...)

Parse the parameters of a function that takes both positional and keyword parameters into local variables. The keywords argument is a NULL-terminated array of keyword parameter names. Empty names denote positional-only parameters. Returns true on success; on failure, it returns false and raises the appropriate exception.

Modifié dans la version 3.6: Added support for positional-only parameters.

int PyArg_VaParseTupleAndKeywords(PyObject *args, PyObject *kw, const char *format, char *keywords[], va_list vargs)

Identical to PyArg_ParseTupleAndKeywords(), except that it accepts a va_list rather than a variable number of arguments.

int PyArg_ValidateKeywordArguments(PyObject *)

Ensure that the keys in the keywords argument dictionary are strings. This is only needed if PyArg_ParseTupleAndKeywords() is not used, since the latter already does this check.

Nouveau dans la version 3.2.

int PyArg_Parse(PyObject *args, const char *format, ...)

Function used to deconstruct the argument lists of « old-style » functions — these are functions which use the METH_OLDARGS parameter parsing method, which has been removed in Python 3. This is not recommended for use in parameter parsing in new code, and most code in the standard interpreter has been modified to no longer use this for that purpose. It does remain a convenient way to decompose other tuples, however, and may continue to be used for that purpose.

int PyArg_UnpackTuple(PyObject *args, const char *name, Py_ssize_t min, Py_ssize_t max, ...)

A simpler form of parameter retrieval which does not use a format string to specify the types of the arguments. Functions which use this method to retrieve their parameters should be declared as METH_VARARGS in function or method tables. The tuple containing the actual parameters should be passed as args; it must actually be a tuple. The length of the tuple must be at least min and no more than max; min and max may be equal. Additional arguments must be passed to the function, each of which should be a pointer to a PyObject* variable; these will be filled in with the values from args; they will contain borrowed references. The variables which correspond to optional parameters not given by args will not be filled in; these should be initialized by the caller. This function returns true on success and false if args is not a tuple or contains the wrong number of elements; an exception will be set if there was a failure.

This is an example of the use of this function, taken from the sources for the _weakref helper module for weak references:

static PyObject *
weakref_ref(PyObject *self, PyObject *args)
{
    PyObject *object;
    PyObject *callback = NULL;
    PyObject *result = NULL;

    if (PyArg_UnpackTuple(args, "ref", 1, 2, &object, &callback)) {
        result = PyWeakref_NewRef(object, callback);
    }
    return result;
}

The call to PyArg_UnpackTuple() in this example is entirely equivalent to this call to PyArg_ParseTuple():

PyArg_ParseTuple(args, "O|O:ref", &object, &callback)

Construction des valeurs

PyObject* Py_BuildValue(const char *format, ...)

Return value: New reference.

Create a new value based on a format string similar to those accepted by the PyArg_Parse*() family of functions and a sequence of values. Returns the value or NULL in the case of an error; an exception will be raised if NULL is returned.

Py_BuildValue() does not always build a tuple. It builds a tuple only if its format string contains two or more format units. If the format string is empty, it returns None; if it contains exactly one format unit, it returns whatever object is described by that format unit. To force it to return a tuple of size 0 or one, parenthesize the format string.

When memory buffers are passed as parameters to supply data to build objects, as for the s and s# formats, the required data is copied. Buffers provided by the caller are never referenced by the objects created by Py_BuildValue(). In other words, if your code invokes malloc() and passes the allocated memory to Py_BuildValue(), your code is responsible for calling free() for that memory once Py_BuildValue() returns.

In the following description, the quoted form is the format unit; the entry in (round) parentheses is the Python object type that the format unit will return; and the entry in [square] brackets is the type of the C value(s) to be passed.

The characters space, tab, colon and comma are ignored in format strings (but not within format units such as s#). This can be used to make long format strings a tad more readable.

s (str ou None) [char *]

Convert a null-terminated C string to a Python str object using 'utf-8' encoding. If the C string pointer is NULL, None is used.

s# (str ou None) [char *, int]

Convert a C string and its length to a Python str object using 'utf-8' encoding. If the C string pointer is NULL, the length is ignored and None is returned.

y (bytes) [char *]

This converts a C string to a Python bytes object. If the C string pointer is NULL, None is returned.

y# (bytes) [char *, int]

This converts a C string and its lengths to a Python object. If the C string pointer is NULL, None is returned.

z (str ou None) [char *]

Same as s.

z# (str ou None) [char *, int]

Same as s#.

u (str) [wchar_t *]

Convert a null-terminated wchar_t buffer of Unicode (UTF-16 or UCS-4) data to a Python Unicode object. If the Unicode buffer pointer is NULL, None is returned.

u# (str) [wchar_t *, int]

Convert a Unicode (UTF-16 or UCS-4) data buffer and its length to a Python Unicode object. If the Unicode buffer pointer is NULL, the length is ignored and None is returned.

U (str ou None) [char *]

Same as s.

U# (str ou None) [char *, int]

Same as s#.

i (int) [int]

Convert a plain C int to a Python integer object.

b (int) [char]

Convert a plain C char to a Python integer object.

h (int) [short int]

Convert a plain C short int to a Python integer object.

l (int) [long int]

Convertit un long int en un int Python.

B (int) [unsigned char]

Convert a C unsigned char to a Python integer object.

H (int) [unsigned short int]

Convert a C unsigned short int to a Python integer object.

I (int) [unsigned int]

Convert a C unsigned int to a Python integer object.

k (int) [unsigned long]

Convert a C unsigned long to a Python integer object.

L (int) [long long]

Convert a C long long to a Python integer object.

K (int) [unsigned long long]

Convert a C unsigned long long to a Python integer object.

n (int) [Py_ssize_t]

Convert a C Py_ssize_t to a Python integer.

c (bytes de taille 1) [char]

Convert a C int representing a byte to a Python bytes object of length 1.

C (str de longueur 1) [int]

Convert a C int representing a character to Python str object of length 1.

d (float) [double]

Convert a C double to a Python floating point number.

f (float) [float]

Convert a C float to a Python floating point number.

D (complex) [Py_complex *]

Convert a C Py_complex structure to a Python complex number.

O (objet) [PyObject *]

Pass a Python object untouched (except for its reference count, which is incremented by one). If the object passed in is a NULL pointer, it is assumed that this was caused because the call producing the argument found an error and set an exception. Therefore, Py_BuildValue() will return NULL but won’t raise an exception. If no exception has been raised yet, SystemError is set.

S (objet) [PyObject *]

Same as O.

N (objet) [PyObject *]

Same as O, except it doesn’t increment the reference count on the object. Useful when the object is created by a call to an object constructor in the argument list.

O& (objet) [converter, anything]

Convert anything to a Python object through a converter function. The function is called with anything (which should be compatible with void *) as its argument and should return a « new » Python object, or NULL if an error occurred.

(items) (tuple) [matching-items]

Convert a sequence of C values to a Python tuple with the same number of items.

[items] (list) [matching-items]

Convert a sequence of C values to a Python list with the same number of items.

{items} (dict) [matching-items]

Convert a sequence of C values to a Python dictionary. Each pair of consecutive C values adds one item to the dictionary, serving as key and value, respectively.

If there is an error in the format string, the SystemError exception is set and NULL returned.

PyObject* Py_VaBuildValue(const char *format, va_list vargs)

Identical to Py_BuildValue(), except that it accepts a va_list rather than a variable number of arguments.

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Conversion et formatage de chaînes

Fonctions de conversion pour les nombres et pour la sortie des chaînes formatées.

int PyOS_snprintf(char *str, size_t size, const char *format, ...)

Output not more than size bytes to str according to the format string format and the extra arguments. See the Unix man page snprintf(2).

int PyOS_vsnprintf(char *str, size_t size, const char *format, va_list va)

Output not more than size bytes to str according to the format string format and the variable argument list va. Unix man page vsnprintf(2).

PyOS_snprintf() and PyOS_vsnprintf() wrap the Standard C library functions snprintf() and vsnprintf(). Their purpose is to guarantee consistent behavior in corner cases, which the Standard C functions do not.

The wrappers ensure that str*[*size-1] is always '\0' upon return. They never write more than size bytes (including the trailing '\0') into str. Both functions require that str != NULL, size > 0 and format != NULL.

If the platform doesn’t have vsnprintf() and the buffer size needed to avoid truncation exceeds size by more than 512 bytes, Python aborts with a Py_FatalError.

The return value (rv) for these functions should be interpreted as follows:

When 0 <= rv < size, the output conversion was successful and rv characters were written to str (excluding the trailing '\0' byte at str*[*rv]).

When rv >= size, the output conversion was truncated and a buffer with rv + 1 bytes would have been needed to succeed. str*[*size-1] is '\0' in this case.

When rv < 0, « something bad happened. » str*[*size-1] is '\0' in this case too, but the rest of str is undefined. The exact cause of the error depends on the underlying platform.

The following functions provide locale-independent string to number conversions.

double PyOS_string_to_double(const char *s, char **endptr, PyObject *overflow_exception)

Convert a string s to a double, raising a Python exception on failure. The set of accepted strings corresponds to the set of strings accepted by Python’s float() constructor, except that s must not have leading or trailing whitespace. The conversion is independent of the current locale.

If endptr is NULL, convert the whole string. Raise ValueError and return -1.0 if the string is not a valid representation of a floating-point number.

If endptr is not NULL, convert as much of the string as possible and set *endptr to point to the first unconverted character. If no initial segment of the string is the valid representation of a floating-point number, set *endptr to point to the beginning of the string, raise ValueError, and return -1.0.

If s represents a value that is too large to store in a float (for example, "1e500" is such a string on many platforms) then if overflow_exception is NULL return Py_HUGE_VAL (with an appropriate sign) and don’t set any exception. Otherwise, overflow_exception must point to a Python exception object; raise that exception and return -1.0. In both cases, set *endptr to point to the first character after the converted value.

If any other error occurs during the conversion (for example an out-of-memory error), set the appropriate Python exception and return -1.0.

Nouveau dans la version 3.1.

char* PyOS_double_to_string(double val, char format_code, int precision, int flags, int *ptype)

Convert a double val to a string using supplied format_code, precision, and flags.

format_code must be one of 'e', 'E', 'f', 'F', 'g', 'G' or 'r'. For 'r', the supplied precision must be 0 and is ignored. The 'r' format code specifies the standard repr() format.

flags can be zero or more of the values Py_DTSF_SIGN, Py_DTSF_ADD_DOT_0, or Py_DTSF_ALT, or-ed together:

Py_DTSF_SIGN means to always precede the returned string with a sign character, even if val is non-negative.

Py_DTSF_ADD_DOT_0 means to ensure that the returned string will not look like an integer.

Py_DTSF_ALT means to apply « alternate » formatting rules. See the documentation for the PyOS_snprintf() '#' specifier for details.

If ptype is non-NULL, then the value it points to will be set to one of Py_DTST_FINITE, Py_DTST_INFINITE, or Py_DTST_NAN, signifying that val is a finite number, an infinite number, or not a number, respectively.

The return value is a pointer to buffer with the converted string or NULL if the conversion failed. The caller is responsible for freeing the returned string by calling PyMem_Free().

Nouveau dans la version 3.1.

int PyOS_stricmp(const char *s1, const char *s2)

Case insensitive comparison of strings. The function works almost identically to strcmp() except that it ignores the case.

int PyOS_strnicmp(const char *s1, const char *s2, Py_ssize_t  size)

Case insensitive comparison of strings. The function works almost identically to strncmp() except that it ignores the case.

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Réflexion

PyObject* PyEval_GetBuiltins()

Return value: Borrowed reference.

Renvoie un dictionnaire des fonctions natives de la frame en cours d’exécution, ou si aucune frame n’est exécutée, les fonctions natives du thread indiqué par le thread state.

PyObject* PyEval_GetLocals()

Return value: Borrowed reference.

Renvoie un dictionnaire des variables locales de la frame en cours d’exécution, ou NULL si aucune frame n’est en cours d’exécution.

PyObject* PyEval_GetGlobals()

Return value: Borrowed reference.

Renvoie un dictionnaire des variables globales de la frame en cours d’exécution ou NULL si aucune frame n’est en cours d’exécution.

PyFrameObject* PyEval_GetFrame()

Return value: Borrowed reference.

Renvoie la frame actuelle selon le thread state, qui est NULL si aucune frame n’est en cours d’exécution.

int PyFrame_GetLineNumber(PyFrameObject *frame)

Renvoie le numéro de ligne que frame est en train d’exécuter

const char* PyEval_GetFuncName(PyObject *func)

Renvoie le nom de func s’il s’agit d’une fonction, d’une classe ou d’un objet d’instance, sinon le nom du type de func

const char* PyEval_GetFuncDesc(PyObject *func)

Renvoie une description en chaîne de caractères, en fonction du type de func. Les valeurs renvoyées peuvent être "()" pour les fonction et les méthodes, \" constructor\", \" instance\", \" object\". Concaténé avec le résultat de PyEval_GetFuncName(), le résultat sera une description de func

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Codec registry and support functions

int PyCodec_Register(PyObject *search_function)

Register a new codec search function.

As side effect, this tries to load the encodings package, if not yet done, to make sure that it is always first in the list of search functions.

int PyCodec_KnownEncoding(const char *encoding)

Return 1 or 0 depending on whether there is a registered codec for the given encoding. This function always succeeds.

PyObject* PyCodec_Encode(PyObject *object, const char *encoding, const char *errors)

Generic codec based encoding API.

object is passed through the encoder function found for the given encoding using the error handling method defined by errors. errors may be NULL to use the default method defined for the codec. Raises a LookupError if no encoder can be found.

PyObject* PyCodec_Decode(PyObject *object, const char *encoding, const char *errors)

Generic codec based decoding API.

object is passed through the decoder function found for the given encoding using the error handling method defined by errors. errors may be NULL to use the default method defined for the codec. Raises a LookupError if no encoder can be found.

Codec lookup API

In the following functions, the encoding string is looked up converted to all lower-case characters, which makes encodings looked up through this mechanism effectively case-insensitive. If no codec is found, a KeyError is set and NULL returned.

PyObject* PyCodec_Encoder(const char *encoding)

Get an encoder function for the given encoding.

PyObject* PyCodec_Decoder(const char *encoding)

Get a decoder function for the given encoding.

PyObject* PyCodec_IncrementalEncoder(const char *encoding, const char *errors)

Get an IncrementalEncoder object for the given encoding.

PyObject* PyCodec_IncrementalDecoder(const char *encoding, const char *errors)

Get an IncrementalDecoder object for the given encoding.

PyObject* PyCodec_StreamReader(const char *encoding, PyObject *stream, const char *errors)

Get a StreamReader factory function for the given encoding.

PyObject* PyCodec_StreamWriter(const char *encoding, PyObject *stream, const char *errors)

Get a StreamWriter factory function for the given encoding.

Registry API for Unicode encoding error handlers

int PyCodec_RegisterError(const char *name, PyObject *error)

Register the error handling callback function error under the given name. This callback function will be called by a codec when it encounters unencodable characters/undecodable bytes and name is specified as the error parameter in the call to the encode/decode function.

The callback gets a single argument, an instance of UnicodeEncodeError, UnicodeDecodeError or UnicodeTranslateError that holds information about the problematic sequence of characters or bytes and their offset in the original string (see Objets exception Unicode for functions to extract this information). The callback must either raise the given exception, or return a two-item tuple containing the replacement for the problematic sequence, and an integer giving the offset in the original string at which encoding/decoding should be resumed.

Return 0 on success, -1 on error.

PyObject* PyCodec_LookupError(const char *name)

Lookup the error handling callback function registered under name. As a special case NULL can be passed, in which case the error handling callback for « strict » will be returned.

PyObject* PyCodec_StrictErrors(PyObject *exc)

Raise exc as an exception.

PyObject* PyCodec_IgnoreErrors(PyObject *exc)

Ignore the unicode error, skipping the faulty input.

PyObject* PyCodec_ReplaceErrors(PyObject *exc)

Replace the unicode encode error with ? or U+FFFD.

PyObject* PyCodec_XMLCharRefReplaceErrors(PyObject *exc)

Replace the unicode encode error with XML character references.

PyObject* PyCodec_BackslashReplaceErrors(PyObject *exc)

Replace the unicode encode error with backslash escapes (\x, \u and \U).

PyObject* PyCodec_NameReplaceErrors(PyObject *exc)

Replace the unicode encode error with \N{...} escapes.

Nouveau dans la version 3.5.

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Couche d’abstraction des objets

Dans ce chapitre, les fonctions s’appliquent à des objets Python sans tenir compte de leur type, ou des classes d’objets au sens large (par exemple, tous les types numériques, ou tous les types de séquence). Quand ils sont utilisés sur des types d’objets qui ne correspondent pas, ils lèveront une exception Python.

Il n’est pas possible d’utiliser ces fonctions sur des objets qui n’ont pas été correctement initialisés, comme un objet liste qui a été créé avec PyList_New() mais dont les éléments n’ont pas encore été mis à une valeur non-NULL.

Protocole Objet

Number Protocol

Sequence Protocol

Mapping Protocol

Protocole d’itération

Protocole tampon

La structure buffer

Buffer request types

request-independent fields

readonly, format

shape, strides, suboffsets

contiguity requests

compound requests

Complex arrays

NumPy-style: shape and strides

PIL-style: shape, strides and suboffsets

Fonctions relatives aux tampons

Ancien Buffer Protocol

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Protocole Objet

PyObject* Py_NotImplemented

Le singleton NotImplemented, utilisé pour signaler qu’une opération n’est pas implémentée pour la combinaison de types en question.

Py_RETURN_NOTIMPLEMENTED

Traite proprement le renvoi de Py_NotImplemented depuis l’intérieur d’une fonction C (c’est-à-dire, incrémente le compteur de référence de NotImplemented et le renvoie).

int PyObject_Print(PyObject *o, FILE *fp, int flags)

Écrit un objet o, dans le fichier fp. Renvoie -1 en cas d’erreur. L’argument flags est utilisé pour permettre certaines options de rendu. La seule option actuellement gérée est Py_PRINT_RAW ; si cet argument est fourni, le str() de l’objet est utilisé pour le rendu à la place de repr().

int PyObject_HasAttr(PyObject *o, PyObject *attr_name)

Renvoie 1 si o a l’attribut attr_name, et 0 sinon. Ceci est équivalent à l’expression Python hasattr(o, attr_name). Cette fonction réussit toujours.

Note that exceptions which occur while calling __getattr__() and __getattribute__() methods will get suppressed. To get error reporting use PyObject_GetAttr() instead.

int PyObject_HasAttrString(PyObject *o, const char *attr_name)

Renvoie 1 si o a l’attribut attr_name, et 0 sinon. Ceci est équivalent à l’expression Python hasattr(o, attr_name). Cette fonction réussit toujours.

Note that exceptions which occur while calling __getattr__() and __getattribute__() methods and creating a temporary string object will get suppressed. To get error reporting use PyObject_GetAttrString() instead.

PyObject* PyObject_GetAttr(PyObject *o, PyObject *attr_name)

Return value: New reference.

Récupère l’attribut nommé attr_name de l’objet o. Renvoie la valeur de l’attribut en cas de succès, ou NULL en cas d’échec. Ceci est équivalent à l’expression Python o.attr_name.

PyObject* PyObject_GetAttrString(PyObject *o, const char *attr_name)

Return value: New reference.

Récupère un attribut nommé attr_name de l’objet o. Renvoie la valeur de l’attribut en cas de succès, ou NULL en cas d’échec. Ceci est équivalent à l’expression Python o.attr_name.

PyObject* PyObject_GenericGetAttr(PyObject *o, PyObject *name)

Accesseur d’attribut générique destiné à être mis dans le slot tp_getattro d’un objet type. Recherche un descripteur dans le dictionnaire de classes du MRO de l’objet ainsi qu’un attribut dans le __dict__ de l’objet (si présent). Comme défini dans Implémentation de descripteurs, les descripteurs de données sont prioritaires sur les attributs d’instance, contrairement aux autres descripteurs. Sinon, une AttributeError est levée.

int PyObject_SetAttr(PyObject *o, PyObject *attr_name, PyObject *v)

Définit la valeur de l’attribut nommé attr_name, pour l’objet o, à la valeur v. Lève une exception et renvoie -1 en cas d’échec ; renvoie 0 en cas de succès. Ceci est équivalent à l’instruction Python o.attr_name = v.

Si v est NULL, l’attribut est supprimé. Cette fonctionnalité est obsolète,nous vous conseillons d’utiliser PyObject_DelAttr().

int PyObject_SetAttrString(PyObject *o, const char *attr_name, PyObject *v)

Définit la valeur de l’attribut nommé attr_name, pour l’objet o, à la valeur v. Lève une exception et renvoie -1 en cas d’échec ; renvoie 0 en cas de succès. Ceci est équivalent à l’instruction Python o.attr_name = v.

Si v est NULL, l’attribut est supprimé. Cette fonctionnalité est obsolète, nous vous conseillons d’utiliser PyObject_DelAttr().

int PyObject_GenericSetAttr(PyObject *o, PyObject *name, PyObject *value)

Accesseur et suppresseur générique d’attributs qui est fait pour être mis dans le tp_setattro d’un objet type. Il cherche un descripteur de données dans le dictionnaire de classes dans le MRO de l’objet et, si ce descripteur est trouvé, c’est lui qui est utilisé de préférence pour la suppression et la définition de l’attribut dans le dictionnaire d’instance. Sinon, l’attribut est défini ou supprimé dans le __dict__ de l’objet (si présent). En cas de succès, 0 est renvoyé, sinon une AttributeError est levée et -1 est renvoyé.

int PyObject_DelAttr(PyObject *o, PyObject *attr_name)

Supprime l’attribut nommé attr_name, pour l’objet o. Renvoie -1 en cas d’échec. Ceci est l’équivalent de l’expression Python del o.attr_name.

int PyObject_DelAttrString(PyObject *o, const char *attr_name)

Supprime l’attribut nommé attr_name, pour l’objet o. Renvoie -1 en cas d’échec. Ceci est l’équivalent de l’expression Python del o.attr_name.

PyObject* PyObject_GenericGetDict(PyObject *o, void *context)

Une implémentation générique de l’accesseur d’un descripteur d’un __dict__. Crée le dictionnaire si nécessaire.

Nouveau dans la version 3.3.

int PyObject_GenericSetDict(PyObject *o, void *context)

Une implémentation générique du mutateur d’un descripteur de __dict__. Cette implémentation n’autorise pas la suppression du dictionnaire.

Nouveau dans la version 3.3.

PyObject* PyObject_RichCompare(PyObject *o1, PyObject *o2, int opid)

Return value: New reference.

Compare les valeurs de o1 et o2 en utilisant l’opération spécifiée par opid, qui doit être Py_LT, Py_LE, Py_EQ, Py_NE, Py_GT, ou Py_GE, correspondant à <, <=, ==, !=, >, ou >= respectivement. Ceci est l’équivalent de l’expression Python o1 op o2, où op est l’opérateur correspondant à opid. Renvoie la valeur de la comparaison en cas de succès, ou NULL en cas d’échec.

int PyObject_RichCompareBool(PyObject *o1, PyObject *o2, int opid)

Compare les valeurs de o1 et o2 en utilisant l’opération spécifiée par opid, qui doit être Py_LT, Py_LE, Py_EQ, Py_NE, Py_GT, ou Py_GE, correspondant à <, <=, ==, !=, >, ou >= respectivement. Renvoie -1 en cas d’erreur, 0 si le résultat est faux, et 1 sinon. Ceci est l’équivalent de l’expression Python o1 op o2, où op est l’opérateur correspondant à opid.

Note

Si o1 et o2 sont le même objet, PyObject_RichCompareBool() renvoie toujours 1 pour Py_EQ et 0 pour Py_NE.

PyObject* PyObject_Repr(PyObject *o)

Return value: New reference.

Calcule une représentation en chaîne de caractères de l’objet o. Renvoie la représentation en chaîne de caractères en cas de succès, NULL en cas d’échec. Ceci est l’équivalent de l’expression Python repr(o). Appelé par la fonction intégrée repr().

Modifié dans la version 3.4: Cette fonction inclut maintenant une assertion de débogage afin d’assurer qu’elle ne passe pas sous silence une exception active.

PyObject* PyObject_ASCII(PyObject *o)

Comme PyObject_Repr(), calcule une représentation en chaîne de caractères de l’objet o, mais échappe les caractères non ASCII dans la chaîne de caractères renvoyée par PyObject_Repr() avec” \x, \u ou \U. Cela génère une chaîne de caractères similaire à celle renvoyée par PyObject_Repr() en Python 2. Appelée par la fonction native ascii().

PyObject* PyObject_Str(PyObject *o)

Return value: New reference.

Calcule une représentation en chaîne de caractères de l’objet o. Renvoie la représentation en chaîne de caractères en cas de succès, NULL en cas d’échec. Ceci est l’équivalent de l’expression Python str(o). Appelée par la fonction native str(), et, par conséquent, par la fonction print().

Modifié dans la version 3.4: Cette fonction inclut maintenant une assertion de débogage afin d’assurer qu’elle ne passe pas sous silence une exception active.

PyObject* PyObject_Bytes(PyObject *o)

Calcule une représentation en octets de l’objet o. NULL est renvoyé en cas d’échec, un objet séquence d’octets est renvoyé en cas de succès. Ceci est l’équivalent de l’expression Python bytes(o), quand o n’est pas un entier. Contrairement à bytes(o), une exception TypeError est levée lorsque o est un entier au lieu d’un objet octet initialisé avec des zéros.

int PyObject_IsSubclass(PyObject *derived, PyObject *cls)

Renvoie 1 si la classe derived est identique à ou dérivée de la classe cls, renvoie 0 sinon. En cas d’erreur, renvoie -1.

Si cls est un tuple, la vérification est menée sur chaque entrée de cls. Le résultat sera 1 quand au moins une des vérifications renvoie 1, sinon ce sera 0.

Si cls a une méthode __subclasscheck__(), elle est appelée pour déterminer le statut de la sous-classe comme décrit dans PEP 3119 [https://www.python.org/dev/peps/pep-3119]. Sinon, derived est une sous-classe de cls si c’est une sous-classe directe ou indirecte, c’est-à-dire contenue dans cls.__mro__.

Normalement seulement les classes objets, c’est-à-dire les instances de type ou d’une classe dérivée, sont considérées classes. Cependant, les objets peuvent surcharger cela en ayant un attribut __bases__ (qui doit être un tuple de classes de bases).

int PyObject_IsInstance(PyObject *inst, PyObject *cls)

Renvoie 1 si inst est une instance de la classe cls ou une sous-classe de cls, ou 0 sinon. En cas d’erreur, renvoie -1 et initialise une exception.

Si cls est un tuple, la vérification est menée sur chaque entrée de cls. Le résultat sera 1 quand au moins une des vérifications renvoie 1, sinon ce sera 0.

Si cls a une méthode __subclasscheck__(), elle sera appelée pour déterminer le statut de la sous-classe comme décrit dans PEP 3119 [https://www.python.org/dev/peps/pep-3119]. Sinon, inst est une instance cls si sa classe est une sous-classe de cls.

Une instance inst peut surcharger ce qui est considéré comme sa classe en ayant un attribut __class__.

Un objet cls peut surcharger s’il est considéré comme une classe, et ce que ses classes de bases sont, en ayant un attribut __bases__ (qui doit être un tuple des classes de base).

int PyCallable_Check(PyObject *o)

Détermine si l’objet o est appelable. Renvoie 1 si c’est le cas, et 0 sinon. Cette fonction réussit toujours.

PyObject* PyObject_Call(PyObject *callable_object, PyObject *args, PyObject *kw)

Return value: New reference.

Call a callable Python object callable_object, with arguments given by the tuple args, and named arguments given by the dictionary kw. If no named arguments are needed, kw may be NULL. args must not be NULL, use an empty tuple if no arguments are needed. Returns the result of the call on success, or NULL on failure. This is the equivalent of the Python expression callable_object(*args, **kw).

PyObject* PyObject_CallObject(PyObject *callable_object, PyObject *args)

Return value: New reference.

Call a callable Python object callable_object, with arguments given by the tuple args. If no arguments are needed, then args may be NULL. Returns the result of the call on success, or NULL on failure. This is the equivalent of the Python expression callable_object(*args).

PyObject* PyObject_CallFunction(PyObject *callable, const char *format, ...)

Return value: New reference.

Call a callable Python object callable, with a variable number of C arguments. The C arguments are described using a Py_BuildValue() style format string. The format may be NULL, indicating that no arguments are provided. Returns the result of the call on success, or NULL on failure. This is the equivalent of the Python expression callable(*args). Note that if you only pass PyObject * args, PyObject_CallFunctionObjArgs() is a faster alternative.

Modifié dans la version 3.4: The type of format was changed from char *.

PyObject* PyObject_CallMethod(PyObject *o, const char *method, const char *format, ...)

Return value: New reference.

Call the method named method of object o with a variable number of C arguments. The C arguments are described by a Py_BuildValue() format string that should produce a tuple. The format may be NULL, indicating that no arguments are provided. Returns the result of the call on success, or NULL on failure. This is the equivalent of the Python expression o.method(args). Note that if you only pass PyObject * args, PyObject_CallMethodObjArgs() is a faster alternative.

Modifié dans la version 3.4: The types of method and format were changed from char *.

PyObject* PyObject_CallFunctionObjArgs(PyObject *callable, ..., NULL)

Return value: New reference.

Call a callable Python object callable, with a variable number of PyObject* arguments. The arguments are provided as a variable number of parameters followed by NULL. Returns the result of the call on success, or NULL on failure.

PyObject* PyObject_CallMethodObjArgs(PyObject *o, PyObject *name, ..., NULL)

Return value: New reference.

Calls a method of the object o, where the name of the method is given as a Python string object in name. It is called with a variable number of PyObject* arguments. The arguments are provided as a variable number of parameters followed by NULL. Returns the result of the call on success, or NULL on failure.

Py_hash_t PyObject_Hash(PyObject *o)

Compute and return the hash value of an object o. On failure, return -1. This is the equivalent of the Python expression hash(o).

Modifié dans la version 3.2: The return type is now Py_hash_t. This is a signed integer the same size as Py_ssize_t.

Py_hash_t PyObject_HashNotImplemented(PyObject *o)

Set a TypeError indicating that type(o) is not hashable and return -1. This function receives special treatment when stored in a tp_hash slot, allowing a type to explicitly indicate to the interpreter that it is not hashable.

int PyObject_IsTrue(PyObject *o)

Returns 1 if the object o is considered to be true, and 0 otherwise. This is equivalent to the Python expression not not o. On failure, return -1.

int PyObject_Not(PyObject *o)

Returns 0 if the object o is considered to be true, and 1 otherwise. This is equivalent to the Python expression not o. On failure, return -1.

PyObject* PyObject_Type(PyObject *o)

Return value: New reference.

When o is non-NULL, returns a type object corresponding to the object type of object o. On failure, raises SystemError and returns NULL. This is equivalent to the Python expression type(o). This function increments the reference count of the return value. There’s really no reason to use this function instead of the common expression o->ob_type, which returns a pointer of type PyTypeObject*, except when the incremented reference count is needed.

int PyObject_TypeCheck(PyObject *o, PyTypeObject *type)

Return true if the object o is of type type or a subtype of type. Both parameters must be non-NULL.

Py_ssize_t PyObject_Size(PyObject *o)

Py_ssize_t PyObject_Length(PyObject *o)

Return the length of object o. If the object o provides either the sequence and mapping protocols, the sequence length is returned. On error, -1 is returned. This is the equivalent to the Python expression len(o).

Py_ssize_t PyObject_LengthHint(PyObject *o, Py_ssize_t default)

Return an estimated length for the object o. First try to return its actual length, then an estimate using __length_hint__(), and finally return the default value. On error return -1. This is the equivalent to the Python expression operator.length_hint(o, default).

Nouveau dans la version 3.4.

PyObject* PyObject_GetItem(PyObject *o, PyObject *key)

Return value: New reference.

Return element of o corresponding to the object key or NULL on failure. This is the equivalent of the Python expression o[key].

int PyObject_SetItem(PyObject *o, PyObject *key, PyObject *v)

Map the object key to the value v. Raise an exception and return -1 on failure; return 0 on success. This is the equivalent of the Python statement o[key] = v.

int PyObject_DelItem(PyObject *o, PyObject *key)

Remove the mapping for the object key from the object o. Return -1 on failure. This is equivalent to the Python statement del o[key].

PyObject* PyObject_Dir(PyObject *o)

Return value: New reference.

This is equivalent to the Python expression dir(o), returning a (possibly empty) list of strings appropriate for the object argument, or NULL if there was an error. If the argument is NULL, this is like the Python dir(), returning the names of the current locals; in this case, if no execution frame is active then NULL is returned but PyErr_Occurred() will return false.

PyObject* PyObject_GetIter(PyObject *o)

Return value: New reference.

This is equivalent to the Python expression iter(o). It returns a new iterator for the object argument, or the object itself if the object is already an iterator. Raises TypeError and returns NULL if the object cannot be iterated.

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Number Protocol

int PyNumber_Check(PyObject *o)

Returns 1 if the object o provides numeric protocols, and false otherwise. This function always succeeds.

PyObject* PyNumber_Add(PyObject *o1, PyObject *o2)

Return value: New reference.

Returns the result of adding o1 and o2, or NULL on failure. This is the equivalent of the Python expression o1 + o2.

PyObject* PyNumber_Subtract(PyObject *o1, PyObject *o2)

Return value: New reference.

Returns the result of subtracting o2 from o1, or NULL on failure. This is the equivalent of the Python expression o1 - o2.

PyObject* PyNumber_Multiply(PyObject *o1, PyObject *o2)

Return value: New reference.

Returns the result of multiplying o1 and o2, or NULL on failure. This is the equivalent of the Python expression o1 * o2.

PyObject* PyNumber_MatrixMultiply(PyObject *o1, PyObject *o2)

Returns the result of matrix multiplication on o1 and o2, or NULL on failure. This is the equivalent of the Python expression o1 @ o2.

Nouveau dans la version 3.5.

PyObject* PyNumber_FloorDivide(PyObject *o1, PyObject *o2)

Return value: New reference.

Return the floor of o1 divided by o2, or NULL on failure. This is equivalent to the « classic » division of integers.

PyObject* PyNumber_TrueDivide(PyObject *o1, PyObject *o2)

Return value: New reference.

Return a reasonable approximation for the mathematical value of o1 divided by o2, or NULL on failure. The return value is « approximate » because binary floating point numbers are approximate; it is not possible to represent all real numbers in base two. This function can return a floating point value when passed two integers.

PyObject* PyNumber_Remainder(PyObject *o1, PyObject *o2)

Return value: New reference.

Returns the remainder of dividing o1 by o2, or NULL on failure. This is the equivalent of the Python expression o1 % o2.

PyObject* PyNumber_Divmod(PyObject *o1, PyObject *o2)

Return value: New reference.

See the built-in function divmod(). Returns NULL on failure. This is the equivalent of the Python expression divmod(o1, o2).

PyObject* PyNumber_Power(PyObject *o1, PyObject *o2, PyObject *o3)

Return value: New reference.

See the built-in function pow(). Returns NULL on failure. This is the equivalent of the Python expression pow(o1, o2, o3), where o3 is optional. If o3 is to be ignored, pass Py_None in its place (passing NULL for o3 would cause an illegal memory access).

PyObject* PyNumber_Negative(PyObject *o)

Return value: New reference.

Returns the negation of o on success, or NULL on failure. This is the equivalent of the Python expression -o.

PyObject* PyNumber_Positive(PyObject *o)

Return value: New reference.

Returns o on success, or NULL on failure. This is the equivalent of the Python expression +o.

PyObject* PyNumber_Absolute(PyObject *o)

Return value: New reference.

Returns the absolute value of o, or NULL on failure. This is the equivalent of the Python expression abs(o).

PyObject* PyNumber_Invert(PyObject *o)

Return value: New reference.

Returns the bitwise negation of o on success, or NULL on failure. This is the equivalent of the Python expression ~o.

PyObject* PyNumber_Lshift(PyObject *o1, PyObject *o2)

Return value: New reference.

Returns the result of left shifting o1 by o2 on success, or NULL on failure. This is the equivalent of the Python expression o1 << o2.

PyObject* PyNumber_Rshift(PyObject *o1, PyObject *o2)

Return value: New reference.

Returns the result of right shifting o1 by o2 on success, or NULL on failure. This is the equivalent of the Python expression o1 >> o2.

PyObject* PyNumber_And(PyObject *o1, PyObject *o2)

Return value: New reference.

Returns the « bitwise and » of o1 and o2 on success and NULL on failure. This is the equivalent of the Python expression o1 & o2.

PyObject* PyNumber_Xor(PyObject *o1, PyObject *o2)

Return value: New reference.

Returns the « bitwise exclusive or » of o1 by o2 on success, or NULL on failure. This is the equivalent of the Python expression o1 ^ o2.

PyObject* PyNumber_Or(PyObject *o1, PyObject *o2)

Return value: New reference.

Returns the « bitwise or » of o1 and o2 on success, or NULL on failure. This is the equivalent of the Python expression o1 | o2.

PyObject* PyNumber_InPlaceAdd(PyObject *o1, PyObject *o2)

Return value: New reference.

Returns the result of adding o1 and o2, or NULL on failure. The operation is done in-place when o1 supports it. This is the equivalent of the Python statement o1 += o2.

PyObject* PyNumber_InPlaceSubtract(PyObject *o1, PyObject *o2)

Return value: New reference.

Returns the result of subtracting o2 from o1, or NULL on failure. The operation is done in-place when o1 supports it. This is the equivalent of the Python statement o1 -= o2.

PyObject* PyNumber_InPlaceMultiply(PyObject *o1, PyObject *o2)

Return value: New reference.

Returns the result of multiplying o1 and o2, or NULL on failure. The operation is done in-place when o1 supports it. This is the equivalent of the Python statement o1 *= o2.

PyObject* PyNumber_InPlaceMatrixMultiply(PyObject *o1, PyObject *o2)

Returns the result of matrix multiplication on o1 and o2, or NULL on failure. The operation is done in-place when o1 supports it. This is the equivalent of the Python statement o1 @= o2.

Nouveau dans la version 3.5.

PyObject* PyNumber_InPlaceFloorDivide(PyObject *o1, PyObject *o2)

Return value: New reference.

Returns the mathematical floor of dividing o1 by o2, or NULL on failure. The operation is done in-place when o1 supports it. This is the equivalent of the Python statement o1 //= o2.

PyObject* PyNumber_InPlaceTrueDivide(PyObject *o1, PyObject *o2)

Return value: New reference.

Return a reasonable approximation for the mathematical value of o1 divided by o2, or NULL on failure. The return value is « approximate » because binary floating point numbers are approximate; it is not possible to represent all real numbers in base two. This function can return a floating point value when passed two integers. The operation is done in-place when o1 supports it.

PyObject* PyNumber_InPlaceRemainder(PyObject *o1, PyObject *o2)

Return value: New reference.

Returns the remainder of dividing o1 by o2, or NULL on failure. The operation is done in-place when o1 supports it. This is the equivalent of the Python statement o1 %= o2.

PyObject* PyNumber_InPlacePower(PyObject *o1, PyObject *o2, PyObject *o3)

Return value: New reference.

See the built-in function pow(). Returns NULL on failure. The operation is done in-place when o1 supports it. This is the equivalent of the Python statement o1 **= o2 when o3 is Py_None, or an in-place variant of pow(o1, o2, o3) otherwise. If o3 is to be ignored, pass Py_None in its place (passing NULL for o3 would cause an illegal memory access).

PyObject* PyNumber_InPlaceLshift(PyObject *o1, PyObject *o2)

Return value: New reference.

Returns the result of left shifting o1 by o2 on success, or NULL on failure. The operation is done in-place when o1 supports it. This is the equivalent of the Python statement o1 <<= o2.

PyObject* PyNumber_InPlaceRshift(PyObject *o1, PyObject *o2)

Return value: New reference.

Returns the result of right shifting o1 by o2 on success, or NULL on failure. The operation is done in-place when o1 supports it. This is the equivalent of the Python statement o1 >>= o2.

PyObject* PyNumber_InPlaceAnd(PyObject *o1, PyObject *o2)

Return value: New reference.

Returns the « bitwise and » of o1 and o2 on success and NULL on failure. The operation is done in-place when o1 supports it. This is the equivalent of the Python statement o1 &= o2.

PyObject* PyNumber_InPlaceXor(PyObject *o1, PyObject *o2)

Return value: New reference.

Returns the « bitwise exclusive or » of o1 by o2 on success, or NULL on failure. The operation is done in-place when o1 supports it. This is the equivalent of the Python statement o1 ^= o2.

PyObject* PyNumber_InPlaceOr(PyObject *o1, PyObject *o2)

Return value: New reference.

Returns the « bitwise or » of o1 and o2 on success, or NULL on failure. The operation is done in-place when o1 supports it. This is the equivalent of the Python statement o1 |= o2.

PyObject* PyNumber_Long(PyObject *o)

Return value: New reference.

Returns the o converted to an integer object on success, or NULL on failure. This is the equivalent of the Python expression int(o).

PyObject* PyNumber_Float(PyObject *o)

Return value: New reference.

Returns the o converted to a float object on success, or NULL on failure. This is the equivalent of the Python expression float(o).

PyObject* PyNumber_Index(PyObject *o)

Returns the o converted to a Python int on success or NULL with a TypeError exception raised on failure.

PyObject* PyNumber_ToBase(PyObject *n, int base)

Returns the integer n converted to base base as a string. The base argument must be one of 2, 8, 10, or 16. For base 2, 8, or 16, the returned string is prefixed with a base marker of '0b', '0o', or '0x', respectively. If n is not a Python int, it is converted with PyNumber_Index() first.

Py_ssize_t PyNumber_AsSsize_t(PyObject *o, PyObject *exc)

Returns o converted to a Py_ssize_t value if o can be interpreted as an integer. If the call fails, an exception is raised and -1 is returned.

If o can be converted to a Python int but the attempt to convert to a Py_ssize_t value would raise an OverflowError, then the exc argument is the type of exception that will be raised (usually IndexError or OverflowError). If exc is NULL, then the exception is cleared and the value is clipped to PY_SSIZE_T_MIN for a negative integer or PY_SSIZE_T_MAX for a positive integer.

int PyIndex_Check(PyObject *o)

Returns 1 if o is an index integer (has the nb_index slot of the tp_as_number structure filled in), and 0 otherwise. This function always succeeds.

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Sequence Protocol

int PySequence_Check(PyObject *o)

Return 1 if the object provides sequence protocol, and 0 otherwise. Note that it returns 1 for Python classes with a __getitem__() method unless they are dict subclasses since in general case it is impossible to determine what the type of keys it supports. This function always succeeds.

Py_ssize_t PySequence_Size(PyObject *o)

Py_ssize_t PySequence_Length(PyObject *o)

Returns the number of objects in sequence o on success, and -1 on failure. This is equivalent to the Python expression len(o).

PyObject* PySequence_Concat(PyObject *o1, PyObject *o2)

Return value: New reference.

Return the concatenation of o1 and o2 on success, and NULL on failure. This is the equivalent of the Python expression o1 + o2.

PyObject* PySequence_Repeat(PyObject *o, Py_ssize_t count)

Return value: New reference.

Return the result of repeating sequence object o count times, or NULL on failure. This is the equivalent of the Python expression o * count.

PyObject* PySequence_InPlaceConcat(PyObject *o1, PyObject *o2)

Return value: New reference.

Return the concatenation of o1 and o2 on success, and NULL on failure. The operation is done in-place when o1 supports it. This is the equivalent of the Python expression o1 += o2.

PyObject* PySequence_InPlaceRepeat(PyObject *o, Py_ssize_t count)

Return value: New reference.

Return the result of repeating sequence object o count times, or NULL on failure. The operation is done in-place when o supports it. This is the equivalent of the Python expression o *= count.

PyObject* PySequence_GetItem(PyObject *o, Py_ssize_t i)

Return value: New reference.

Return the ith element of o, or NULL on failure. This is the equivalent of the Python expression o[i].

PyObject* PySequence_GetSlice(PyObject *o, Py_ssize_t i1, Py_ssize_t i2)

Return value: New reference.

Return the slice of sequence object o between i1 and i2, or NULL on failure. This is the equivalent of the Python expression o[i1:i2].

int PySequence_SetItem(PyObject *o, Py_ssize_t i, PyObject *v)

Assign object v to the ith element of o. Raise an exception and return -1 on failure; return 0 on success. This is the equivalent of the Python statement o[i] = v. This function does not steal a reference to v.

If v is NULL, the element is deleted, however this feature is deprecated in favour of using PySequence_DelItem().

int PySequence_DelItem(PyObject *o, Py_ssize_t i)

Delete the ith element of object o. Returns -1 on failure. This is the equivalent of the Python statement del o[i].

int PySequence_SetSlice(PyObject *o, Py_ssize_t i1, Py_ssize_t i2, PyObject *v)

Assign the sequence object v to the slice in sequence object o from i1 to i2. This is the equivalent of the Python statement o[i1:i2] = v.

int PySequence_DelSlice(PyObject *o, Py_ssize_t i1, Py_ssize_t i2)

Delete the slice in sequence object o from i1 to i2. Returns -1 on failure. This is the equivalent of the Python statement del o[i1:i2].

Py_ssize_t PySequence_Count(PyObject *o, PyObject *value)

Return the number of occurrences of value in o, that is, return the number of keys for which o[key] == value. On failure, return -1. This is equivalent to the Python expression o.count(value).

int PySequence_Contains(PyObject *o, PyObject *value)

Determine if o contains value. If an item in o is equal to value, return 1, otherwise return 0. On error, return -1. This is equivalent to the Python expression value in o.

Py_ssize_t PySequence_Index(PyObject *o, PyObject *value)

Return the first index i for which o[i] == value. On error, return -1. This is equivalent to the Python expression o.index(value).

PyObject* PySequence_List(PyObject *o)

Return value: New reference.

Return a list object with the same contents as the sequence or iterable o, or NULL on failure. The returned list is guaranteed to be new. This is equivalent to the Python expression list(o).

PyObject* PySequence_Tuple(PyObject *o)

Return value: New reference.

Return a tuple object with the same contents as the sequence or iterable o, or NULL on failure. If o is a tuple, a new reference will be returned, otherwise a tuple will be constructed with the appropriate contents. This is equivalent to the Python expression tuple(o).

PyObject* PySequence_Fast(PyObject *o, const char *m)

Return value: New reference.

Return the sequence or iterable o as a list, unless it is already a tuple or list, in which case o is returned. Use PySequence_Fast_GET_ITEM() to access the members of the result. Returns NULL on failure. If the object is not a sequence or iterable, raises TypeError with m as the message text.

Py_ssize_t PySequence_Fast_GET_SIZE(PyObject *o)

Returns the length of o, assuming that o was returned by PySequence_Fast() and that o is not NULL. The size can also be gotten by calling PySequence_Size() on o, but PySequence_Fast_GET_SIZE() is faster because it can assume o is a list or tuple.

PyObject* PySequence_Fast_GET_ITEM(PyObject *o, Py_ssize_t i)

Return value: Borrowed reference.

Return the ith element of o, assuming that o was returned by PySequence_Fast(), o is not NULL, and that i is within bounds.

PyObject** PySequence_Fast_ITEMS(PyObject *o)

Return the underlying array of PyObject pointers. Assumes that o was returned by PySequence_Fast() and o is not NULL.

Note, if a list gets resized, the reallocation may relocate the items array. So, only use the underlying array pointer in contexts where the sequence cannot change.

PyObject* PySequence_ITEM(PyObject *o, Py_ssize_t i)

Return value: New reference.

Return the ith element of o or NULL on failure. Macro form of PySequence_GetItem() but without checking that PySequence_Check() on o is true and without adjustment for negative indices.

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Mapping Protocol

See also PyObject_GetItem(), PyObject_SetItem() and PyObject_DelItem().

int PyMapping_Check(PyObject *o)

Return 1 if the object provides mapping protocol or supports slicing, and 0 otherwise. Note that it returns 1 for Python classes with a __getitem__() method since in general case it is impossible to determine what the type of keys it supports. This function always succeeds.

Py_ssize_t PyMapping_Size(PyObject *o)

Py_ssize_t PyMapping_Length(PyObject *o)

Returns the number of keys in object o on success, and -1 on failure. This is equivalent to the Python expression len(o).

PyObject* PyMapping_GetItemString(PyObject *o, const char *key)

Return value: New reference.

Return element of o corresponding to the string key or NULL on failure. This is the equivalent of the Python expression o[key]. See also PyObject_GetItem().

int PyMapping_SetItemString(PyObject *o, const char *key, PyObject *v)

Map the string key to the value v in object o. Returns -1 on failure. This is the equivalent of the Python statement o[key] = v. See also PyObject_SetItem().

int PyMapping_DelItem(PyObject *o, PyObject *key)

Remove the mapping for the object key from the object o. Return -1 on failure. This is equivalent to the Python statement del o[key]. This is an alias of PyObject_DelItem().

int PyMapping_DelItemString(PyObject *o, const char *key)

Remove the mapping for the string key from the object o. Return -1 on failure. This is equivalent to the Python statement del o[key].

int PyMapping_HasKey(PyObject *o, PyObject *key)

Return 1 if the mapping object has the key key and 0 otherwise. This is equivalent to the Python expression key in o. This function always succeeds.

Note that exceptions which occur while calling the __getitem__() method will get suppressed. To get error reporting use PyObject_GetItem() instead.

int PyMapping_HasKeyString(PyObject *o, const char *key)

Return 1 if the mapping object has the key key and 0 otherwise. This is equivalent to the Python expression key in o. This function always succeeds.

Note that exceptions which occur while calling the __getitem__() method and creating a temporary string object will get suppressed. To get error reporting use PyMapping_GetItemString() instead.

PyObject* PyMapping_Keys(PyObject *o)

Return value: New reference.

On success, return a list or tuple of the keys in object o. On failure, return NULL.

PyObject* PyMapping_Values(PyObject *o)

Return value: New reference.

On success, return a list or tuple of the values in object o. On failure, return NULL.

PyObject* PyMapping_Items(PyObject *o)

Return value: New reference.

On success, return a list or tuple of the items in object o, where each item is a tuple containing a key-value pair. On failure, return NULL.

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Protocole d’itération

Il existe deux fonctions dédiées à l’interaction avec les itérateurs.

int PyIter_Check(PyObject *o)

Renvoie vrai si l’objet o supporte le protocole d’itération.

PyObject* PyIter_Next(PyObject *o)

Return value: New reference.

Renvoie la valeur suivante d’une itération de o. L’objet doit être un itérateur (c’est à l’appelant de faire cette vérification). Renvoie NULL s’il n’y a plus de valeurs, sans déclarer d’exception. Renvoie NULL en déclarant une exception si une erreur survient lors de la récupération d’un élément.

Pour écrire une boucle itérant un itérateur, le code C devrait ressembler à :

PyObject *iterator = PyObject_GetIter(obj);
PyObject *item;

if (iterator == NULL) {
    /* propagate error */
}

while (item = PyIter_Next(iterator)) {
    /* do something with item */
    ...
    /* release reference when done */
    Py_DECREF(item);
}

Py_DECREF(iterator);

if (PyErr_Occurred()) {
    /* propagate error */
}
else {
    /* continue doing useful work */
}

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Protocole tampon

Certains objets Python enveloppent l’accès à un tableau de mémoire sous-jacente (nommée zone tampon ou simplement tampon, buffer en anglais). Les objets natifs bytes et bytearray en sont des exemples, ainsi que quelques types d’extension comme array.array. Les bibliothèques tierces peuvent définir leurs propres types à des fins spéciales, telles que le traitement d’image ou l’analyse numérique.

Alors que chacun de ces types a sa propre sémantique, ils partagent la caractéristique commune d’être soutenus par un tampon de mémoire important. Il est donc souhaitable, dans certains cas, d’accéder à cette mémoire directement sans l’étape intermédiaire de copie.

Python fournit une telle facilité au niveau du C sous la forme de protocole tampon. Ce protocole comporte deux aspects :

du côté producteur, un type peut exporter une « interface tampon » qui permet aux objets de ce type d’exposer des informations concernant leur tampon sous-jacent. Cette interface est décrite dans la section Buffer Object Structures ;

du côté consommateur, plusieurs moyens sont disponibles pour obtenir un pointeur vers les données sous-jacentes brutes d’un objet (par exemple un paramètre de méthode).

Des objets simples tels que bytes et bytearray exposent leur tampon sous-jacent dans un format orienté octet. D’autres formes sont possibles ; par exemple, les éléments exposés par un array.array peuvent être des valeurs multi-octets.

Un exemple de consommateur de l’interface tampon est la méthode write() des objets fichiers : tout objet qui peut exporter une série d’octets à travers l’interface tampon peut être écrit dans un fichier. Alors que write() n’a besoin que d’un accès lecture au contenu interne de l’objet qui lui est passé, d’autres méthodes telles que readinto() nécessitent un accès écriture au contenu de leur argument. L’interface buffer permet aux objets d’autoriser ou de rejeter sélectivement l’exportation de tampons en mode lecture-écriture et en mode lecture seule.

Un consommateur de l’interface tampon peut acquérir un tampon sur un objet cible de deux manières :

appelez PyObject_GetBuffer() avec les paramètres appropriés ;

appelez PyArg_ParseTuple() (ou l’un de ses fonctions sœurs) avec l’un des y*, w* ou s* format codes.

Dans les deux cas, PyBuffer_Release() doit être appelée quand le tampon n’est plus nécessaire. Ne pas le faire peut conduire à divers problèmes tels que des fuites de ressources.

La structure buffer

Les structures tampons (ou simplement les « tampons », buffers en anglais) sont utiles pour exposer les données binaires d’un autre objet au programmeur Python. Elles peuvent également être utilisées comme un mécanisme de découpage sans copie. En utilisant leur capacité à référencer un bloc de mémoire, il est possible d’exposer toutes les données au programmeur Python assez facilement. La mémoire peut être un grand tableau constant dans une extension C, il peut s’agir d’un bloc brut de mémoire à manipuler avant de passer à une bibliothèque de système d’exploitation ou être utilisé pour transmettre des données structurées dans son format natif en mémoire.

Contrairement à la plupart des types de données exposés par l’interpréteur Python, les tampons ne sont pas de simples pointeurs vers PyObject mais plutôt des structures C simples. Cela leur permet d’être créés et copiés très simplement. lorsque vous avez besoin d’une enveloppe générique (wrapper en anglais) pour un tampon, un objet memoryview peut être créé.

For short instructions how to write an exporting object, see Buffer Object Structures. For obtaining a buffer, see PyObject_GetBuffer().

Py_buffer

void *buf

A pointer to the start of the logical structure described by the buffer fields. This can be any location within the underlying physical memory block of the exporter. For example, with negative strides the value may point to the end of the memory block.

For contiguous arrays, the value points to the beginning of the memory block.

void *obj

A new reference to the exporting object. The reference is owned by the consumer and automatically decremented and set to NULL by PyBuffer_Release(). The field is the equivalent of the return value of any standard C-API function.

As a special case, for temporary buffers that are wrapped by PyMemoryView_FromBuffer() or PyBuffer_FillInfo() this field is NULL. In general, exporting objects MUST NOT use this scheme.

Py_ssize_t len

product(shape) * itemsize. For contiguous arrays, this is the length of the underlying memory block. For non-contiguous arrays, it is the length that the logical structure would have if it were copied to a contiguous representation.

Accessing ((char *)buf)[0] up to ((char *)buf)[len-1] is only valid if the buffer has been obtained by a request that guarantees contiguity. In most cases such a request will be PyBUF_SIMPLE or PyBUF_WRITABLE.

int readonly

An indicator of whether the buffer is read-only. This field is controlled by the PyBUF_WRITABLE flag.

Py_ssize_t itemsize

Item size in bytes of a single element. Same as the value of struct.calcsize() called on non-NULL format values.

Important exception: If a consumer requests a buffer without the PyBUF_FORMAT flag, format will be set to NULL, but itemsize still has the value for the original format.

If shape is present, the equality product(shape) * itemsize == len still holds and the consumer can use itemsize to navigate the buffer.

If shape is NULL as a result of a PyBUF_SIMPLE or a PyBUF_WRITABLE request, the consumer must disregard itemsize and assume itemsize == 1.

const char *format

A NUL terminated string in struct module style syntax describing the contents of a single item. If this is NULL, "B" (unsigned bytes) is assumed.

This field is controlled by the PyBUF_FORMAT flag.

int ndim

The number of dimensions the memory represents as an n-dimensional array. If it is 0, buf points to a single item representing a scalar. In this case, shape, strides and suboffsets MUST be NULL.

The macro PyBUF_MAX_NDIM limits the maximum number of dimensions to 64. Exporters MUST respect this limit, consumers of multi-dimensional buffers SHOULD be able to handle up to PyBUF_MAX_NDIM dimensions.

Py_ssize_t *shape

An array of Py_ssize_t of length ndim indicating the shape of the memory as an n-dimensional array. Note that shape[0] * ... * shape[ndim-1] * itemsize MUST be equal to len.

Shape values are restricted to shape[n] >= 0. The case shape[n] == 0 requires special attention. See complex arrays for further information.

The shape array is read-only for the consumer.

Py_ssize_t *strides

An array of Py_ssize_t of length ndim giving the number of bytes to skip to get to a new element in each dimension.

Stride values can be any integer. For regular arrays, strides are usually positive, but a consumer MUST be able to handle the case strides[n] <= 0. See complex arrays for further information.

The strides array is read-only for the consumer.

Py_ssize_t *suboffsets

An array of Py_ssize_t of length ndim. If suboffsets[n] >= 0, the values stored along the nth dimension are pointers and the suboffset value dictates how many bytes to add to each pointer after de-referencing. A suboffset value that is negative indicates that no de-referencing should occur (striding in a contiguous memory block).

If all suboffsets are negative (i.e. no de-referencing is needed), then this field must be NULL (the default value).

This type of array representation is used by the Python Imaging Library (PIL). See complex arrays for further information how to access elements of such an array.

The suboffsets array is read-only for the consumer.

void *internal

This is for use internally by the exporting object. For example, this might be re-cast as an integer by the exporter and used to store flags about whether or not the shape, strides, and suboffsets arrays must be freed when the buffer is released. The consumer MUST NOT alter this value.

Buffer request types

Buffers are usually obtained by sending a buffer request to an exporting object via PyObject_GetBuffer(). Since the complexity of the logical structure of the memory can vary drastically, the consumer uses the flags argument to specify the exact buffer type it can handle.

All Py_buffer fields are unambiguously defined by the request type.

request-independent fields

The following fields are not influenced by flags and must always be filled in with the correct values: obj, buf, len, itemsize, ndim.

readonly, format

PyBUF_WRITABLE

Controls the readonly field. If set, the exporter MUST provide a writable buffer or else report failure. Otherwise, the exporter MAY provide either a read-only or writable buffer, but the choice MUST be consistent for all consumers.

PyBUF_FORMAT

Controls the format field. If set, this field MUST be filled in correctly. Otherwise, this field MUST be NULL.

PyBUF_WRITABLE can be |”d to any of the flags in the next section. Since PyBUF_SIMPLE is defined as 0, PyBUF_WRITABLE can be used as a stand-alone flag to request a simple writable buffer.

PyBUF_FORMAT can be |”d to any of the flags except PyBUF_SIMPLE. The latter already implies format B (unsigned bytes).

shape, strides, suboffsets

The flags that control the logical structure of the memory are listed in decreasing order of complexity. Note that each flag contains all bits of the flags below it.

Request

shape

strides

suboffsets

PyBUF_INDIRECT

oui

oui

if needed

PyBUF_STRIDES

oui

oui

NULL

PyBUF_ND

oui

NULL

NULL

PyBUF_SIMPLE

NULL

NULL

NULL

contiguity requests

C or Fortran contiguity can be explicitly requested, with and without stride information. Without stride information, the buffer must be C-contiguous.

Request

shape

strides

suboffsets

contig

PyBUF_C_CONTIGUOUS

oui

oui

NULL

C

PyBUF_F_CONTIGUOUS

oui

oui

NULL

F

PyBUF_ANY_CONTIGUOUS

oui

oui

NULL

C or F

PyBUF_ND

oui

NULL

NULL

C

compound requests

All possible requests are fully defined by some combination of the flags in the previous section. For convenience, the buffer protocol provides frequently used combinations as single flags.

In the following table U stands for undefined contiguity. The consumer would have to call PyBuffer_IsContiguous() to determine contiguity.

Request

shape

strides

suboffsets

contig

readonly

format

PyBUF_FULL

oui

oui

if needed

U

0

oui

PyBUF_FULL_RO

oui

oui

if needed

U

1 or 0

oui

PyBUF_RECORDS

oui

oui

NULL

U

0

oui

PyBUF_RECORDS_RO

oui

oui

NULL

U

1 or 0

oui

PyBUF_STRIDED

oui

oui

NULL

U

0

NULL

PyBUF_STRIDED_RO

oui

oui

NULL

U

1 or 0

NULL

PyBUF_CONTIG

oui

NULL

NULL

C

0

NULL

PyBUF_CONTIG_RO

oui

NULL

NULL

C

1 or 0

NULL

Complex arrays

NumPy-style: shape and strides

The logical structure of NumPy-style arrays is defined by itemsize, ndim, shape and strides.

If ndim == 0, the memory location pointed to by buf is interpreted as a scalar of size itemsize. In that case, both shape and strides are NULL.

If strides is NULL, the array is interpreted as a standard n-dimensional C-array. Otherwise, the consumer must access an n-dimensional array as follows:

ptr = (char *)buf + indices[0] * strides[0] + ... + indices[n-1] * strides[n-1] item = *((typeof(item) *)ptr);

As noted above, buf can point to any location within the actual memory block. An exporter can check the validity of a buffer with this function:

def verify_structure(memlen, itemsize, ndim, shape, strides, offset):
    """Verify that the parameters represent a valid array within
       the bounds of the allocated memory:
           char *mem: start of the physical memory block
           memlen: length of the physical memory block
           offset: (char *)buf - mem
    """
    if offset % itemsize:
        return False
    if offset < 0 or offset+itemsize > memlen:
        return False
    if any(v % itemsize for v in strides):
        return False

    if ndim <= 0:
        return ndim == 0 and not shape and not strides
    if 0 in shape:
        return True

    imin = sum(strides[j]*(shape[j]-1) for j in range(ndim)
               if strides[j] <= 0)
    imax = sum(strides[j]*(shape[j]-1) for j in range(ndim)
               if strides[j] > 0)

    return 0 <= offset+imin and offset+imax+itemsize <= memlen

PIL-style: shape, strides and suboffsets

In addition to the regular items, PIL-style arrays can contain pointers that must be followed in order to get to the next element in a dimension. For example, the regular three-dimensional C-array char v[2][2][3] can also be viewed as an array of 2 pointers to 2 two-dimensional arrays: char (*v[2])[2][3]. In suboffsets representation, those two pointers can be embedded at the start of buf, pointing to two char x[2][3] arrays that can be located anywhere in memory.

Here is a function that returns a pointer to the element in an N-D array pointed to by an N-dimensional index when there are both non-NULL strides and suboffsets:

void *get_item_pointer(int ndim, void *buf, Py_ssize_t *strides,
                       Py_ssize_t *suboffsets, Py_ssize_t *indices) {
    char *pointer = (char*)buf;
    int i;
    for (i = 0; i < ndim; i++) {
        pointer += strides[i] * indices[i];
        if (suboffsets[i] >=0 ) {
            pointer = *((char**)pointer) + suboffsets[i];
        }
    }
    return (void*)pointer;
}

Fonctions relatives aux tampons

int PyObject_CheckBuffer(PyObject *obj)

Return 1 if obj supports the buffer interface otherwise 0. When 1 is returned, it doesn’t guarantee that PyObject_GetBuffer() will succeed. This function always succeeds.

int PyObject_GetBuffer(PyObject *exporter, Py_buffer *view, int flags)

Send a request to exporter to fill in view as specified by flags. If the exporter cannot provide a buffer of the exact type, it MUST raise PyExc_BufferError, set view->obj to NULL and return -1.

On success, fill in view, set view->obj to a new reference to exporter and return 0. In the case of chained buffer providers that redirect requests to a single object, view->obj MAY refer to this object instead of exporter (See Buffer Object Structures).

Successful calls to PyObject_GetBuffer() must be paired with calls to PyBuffer_Release(), similar to malloc() and free(). Thus, after the consumer is done with the buffer, PyBuffer_Release() must be called exactly once.

void PyBuffer_Release(Py_buffer *view)

Release the buffer view and decrement the reference count for view->obj. This function MUST be called when the buffer is no longer being used, otherwise reference leaks may occur.

It is an error to call this function on a buffer that was not obtained via PyObject_GetBuffer().

Py_ssize_t PyBuffer_SizeFromFormat(const char *)

Return the implied itemsize from format. This function is not yet implemented.

int PyBuffer_IsContiguous(Py_buffer *view, char order)

Return 1 if the memory defined by the view is C-style (order is 'C') or Fortran-style (order is 'F') contiguous or either one (order is 'A'). Return 0 otherwise. This function always succeeds.

int PyBuffer_ToContiguous(void *buf, Py_buffer *src, Py_ssize_t len, char order)

Copy len bytes from src to its contiguous representation in buf. order can be 'C' or 'F' (for C-style or Fortran-style ordering). 0 is returned on success, -1 on error.

This function fails if len != src->len.

void PyBuffer_FillContiguousStrides(int ndims, Py_ssize_t *shape, Py_ssize_t *strides, int itemsize, char order)

Fill the strides array with byte-strides of a contiguous (C-style if order is 'C' or Fortran-style if order is 'F') array of the given shape with the given number of bytes per element.

int PyBuffer_FillInfo(Py_buffer *view, PyObject *exporter, void *buf, Py_ssize_t len, int readonly, int flags)

Handle buffer requests for an exporter that wants to expose buf of size len with writability set according to readonly. buf is interpreted as a sequence of unsigned bytes.

The flags argument indicates the request type. This function always fills in view as specified by flags, unless buf has been designated as read-only and PyBUF_WRITABLE is set in flags.

On success, set view->obj to a new reference to exporter and return 0. Otherwise, raise PyExc_BufferError, set view->obj to NULL and return -1;

If this function is used as part of a getbufferproc, exporter MUST be set to the exporting object and flags must be passed unmodified. Otherwise, exporter MUST be NULL.

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Ancien Buffer Protocol

Obsolète depuis la version 3.0.

Ces fonctions faisaient partie de l’API de l’ancien protocole de tampons dans Python 2. Dans Python 3, ce protocole n’existe plus, mais les fonctions sont toujours exposées pour simplifier le portage de code Python 2.x. Elles se comportent comme une abstraction de compatibilité du nouveau protocole de tampons, mais sans vous donner de contrôle sur la durée de vie des ressources acquises lorsqu’un tampon est exporté.

Il est donc recommandé d’appeler PyObject_GetBuffer() (ou les codes y* ou w* à la famille de fonctions PyArg_ParseTuple()) pour obtenir une vue d’un tampon sur un objet, et PyBuffer_Release() lorsque la vue peut être libérée.

int PyObject_AsCharBuffer(PyObject *obj, const char **buffer, Py_ssize_t *buffer_len)

Retourne un pointeur vers un emplacement de mémoire en lecture seule utilisable en tant qu’entrée basée sur des caractères. L’argument obj doit prendre en charge l’interface de tampon de caractère à segment unique. En cas de succès, retourne 0, définit buffer à l’emplacement de la mémoire et buffer_len à la longueur de la mémoire tampon. Retourne -1 et affecte une exception TypeError en cas d’erreur.

int PyObject_AsReadBuffer(PyObject *obj, const void **buffer, Py_ssize_t *buffer_len)

Retourne un pointeur vers un emplacement de mémoire en lecture seule contenant des données arbitraires. L’argument obj doit prendre en charge l’interface de tampon lisible à segment unique. En cas de succès, retourne 0, définit buffer à l’emplacement de la mémoire et buffer_len à la longueur de la mémoire tampon. Renvoie -1 et affecte l’exception TypeError en cas d’erreur.

int PyObject_CheckReadBuffer(PyObject *o)

Returns 1 if o supports the single-segment readable buffer interface. Otherwise returns 0. This function always succeeds.

Note that this function tries to get and release a buffer, and exceptions which occur while calling correspoding functions will get suppressed. To get error reporting use PyObject_GetBuffer() instead.

int PyObject_AsWriteBuffer(PyObject *obj, void **buffer, Py_ssize_t *buffer_len)

Renvoie un pointeur vers un espace mémoire dans lequel il est possible décrire. L’argument obj doit gérer l’interface single-segment, character buffer. Si tout s’est bien passé, 0 est renvoyé, buffer pointe vers l’espace mémoire, et buffer_len vaudra la taille du tampon. Renvoie -1 et met l’exception TypeError en cas d’erreur.

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Couche des objets concrets

Les fonctions de ce chapitre sont spécifiques à certains types d’objets Python. Leur donner un objet du mauvais type n’est pas une bonne idée, si vous recevez un objet d’un programme Python, et que vous n’êtes pas sûr qu’il soit du bon type, vous devez vérifier son type en premier. Par exemple, pour vérifier qu’un objet est un dictionnaire, utilisez PyDict_Check(). Ce chapitre est organisé comme un arbre généalogique de types d’objets Python.

Avertissement

Tandis que les fonctions décrites dans ce chapitre vérifient avec soin le type des objets qui leur sont passés, beaucoup d’entre elles ne vérifient pas que NULL est passé au lieu d’un objet valide. Autoriser NULL à être passé peut provoquer des violations d’accès à la mémoire et ainsi terminer immédiatement l’interpréteur.

Objets fondamentaux

Cette section décrit les objets de type Python et l’objet singleton None.

Objets type

L’objet None

Objets numériques

Objets Integer

Les objets booléens

Objets représentant les nombres à virgule flottante

Objets nombres complexes

Nombres complexes en tant que structures C

Nombres complexes en tant qu’objets Python

Objets séquences

Les opérations génériques sur les objets séquences ont été discutées dans le chapitre précédent. Cette section traite des genres spécifiques d’objets séquences qui sont intrinsèques au langage Python.

Objets bytes

Objets tableau d’octets

Macros de vérification de type

Fonctions directes sur l’API

Macros

Unicode Objects and Codecs

Unicode Objects

Unicode Type

Unicode Character Properties

Creating and accessing Unicode strings

Deprecated Py_UNICODE APIs

Locale Encoding

File System Encoding

wchar_t Support

Built-in Codecs

Generic Codecs

UTF-8 Codecs

UTF-32 Codecs

UTF-16 Codecs

UTF-7 Codecs

Unicode-Escape Codecs

Raw-Unicode-Escape Codecs

Latin-1 Codecs

ASCII Codecs

Character Map Codecs

MBCS codecs for Windows

Methods & Slots

Methods and Slot Functions

Tuple Objects

Struct Sequence Objects

List Objects

Objets conteneurs

Objets dictionnaires

Set Objects

Objets fonctions

Objets fonctions

Instance Method Objects

Objets méthode

Objets Cellules

Objets code

Autres objets

Objets fichiers

Module Objects

Initializing C modules

Single-phase initialization

Multi-phase initialization

Low-level module creation functions

Support functions

Module lookup

Itérateurs

Les descripteurs

Slice Objects

Ellipsis Object

Objets de type MemoryView

Objets à références faibles

Capsules

Objets générateur

Objets coroutines

Objets DateTime

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Objets type

PyTypeObject

The C structure of the objects used to describe built-in types.

PyObject* PyType_Type

This is the type object for type objects; it is the same object as type in the Python layer.

int PyType_Check(PyObject *o)

Return true if the object o is a type object, including instances of types derived from the standard type object. Return false in all other cases.

int PyType_CheckExact(PyObject *o)

Return true if the object o is a type object, but not a subtype of the standard type object. Return false in all other cases.

unsigned int PyType_ClearCache()

Clear the internal lookup cache. Return the current version tag.

unsigned long PyType_GetFlags(PyTypeObject* type)

Return the tp_flags member of type. This function is primarily meant for use with Py_LIMITED_API; the individual flag bits are guaranteed to be stable across Python releases, but access to tp_flags itself is not part of the limited API.

Nouveau dans la version 3.2.

Modifié dans la version 3.4: The return type is now unsigned long rather than long.

void PyType_Modified(PyTypeObject *type)

Invalidate the internal lookup cache for the type and all of its subtypes. This function must be called after any manual modification of the attributes or base classes of the type.

int PyType_HasFeature(PyTypeObject *o, int feature)

Return true if the type object o sets the feature feature. Type features are denoted by single bit flags.

int PyType_IS_GC(PyTypeObject *o)

Return true if the type object includes support for the cycle detector; this tests the type flag Py_TPFLAGS_HAVE_GC.

int PyType_IsSubtype(PyTypeObject *a, PyTypeObject *b)

Return true if a is a subtype of b.

This function only checks for actual subtypes, which means that __subclasscheck__() is not called on b. Call PyObject_IsSubclass() to do the same check that issubclass() would do.

PyObject* PyType_GenericAlloc(PyTypeObject *type, Py_ssize_t nitems)

Return value: New reference.

Generic handler for the tp_alloc slot of a type object. Use Python’s default memory allocation mechanism to allocate a new instance and initialize all its contents to NULL.

PyObject* PyType_GenericNew(PyTypeObject *type, PyObject *args, PyObject *kwds)

Return value: New reference.

Generic handler for the tp_new slot of a type object. Create a new instance using the type’s tp_alloc slot.

int PyType_Ready(PyTypeObject *type)

Finalize a type object. This should be called on all type objects to finish their initialization. This function is responsible for adding inherited slots from a type’s base class. Return 0 on success, or return -1 and sets an exception on error.

PyObject* PyType_FromSpec(PyType_Spec *spec)

Creates and returns a heap type object from the spec passed to the function.

PyObject* PyType_FromSpecWithBases(PyType_Spec *spec, PyObject *bases)

Creates and returns a heap type object from the spec. In addition to that, the created heap type contains all types contained by the bases tuple as base types. This allows the caller to reference other heap types as base types.

Nouveau dans la version 3.3.

void* PyType_GetSlot(PyTypeObject *type, int slot)

Return the function pointer stored in the given slot. If the result is NULL, this indicates that either the slot is NULL, or that the function was called with invalid parameters. Callers will typically cast the result pointer into the appropriate function type.

Nouveau dans la version 3.4.

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L’objet None

Notez que le PyTypeObject de None n’est pas directement exposé via l’API Python/C. Puisque None est un singleton, tester son identité (en utilisant == en C) est suffisant. Il n’existe pas de fonction PyNone_Check() pour la même raison.

PyObject* Py_None

L’objet Python None, exprimant l’absence de valeur. Cet objet n’a aucune méthode. Il doit être traité exactement comme les autres objets en terme de comptage de références.

Py_RETURN_NONE

Renvoie, de la bonne manière, Py_None depuis une fonction C (c’est à dire en incrémentant les références à None avant de le donner).

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Objets Integer

All integers are implemented as « long » integer objects of arbitrary size.

On error, most PyLong_As* APIs return (return type)-1 which cannot be distinguished from a number. Use PyErr_Occurred() to disambiguate.

PyLongObject

This subtype of PyObject represents a Python integer object.

PyTypeObject PyLong_Type

This instance of PyTypeObject represents the Python integer type. This is the same object as int in the Python layer.

int PyLong_Check(PyObject *p)

Return true if its argument is a PyLongObject or a subtype of PyLongObject.

int PyLong_CheckExact(PyObject *p)

Return true if its argument is a PyLongObject, but not a subtype of PyLongObject.

PyObject* PyLong_FromLong(long v)

Return value: New reference.

Return a new PyLongObject object from v, or NULL on failure.

The current implementation keeps an array of integer objects for all integers between -5 and 256, when you create an int in that range you actually just get back a reference to the existing object. So it should be possible to change the value of 1. I suspect the behaviour of Python in this case is undefined. :-)

PyObject* PyLong_FromUnsignedLong(unsigned long v)

Return value: New reference.

Return a new PyLongObject object from a C unsigned long, or NULL on failure.

PyObject* PyLong_FromSsize_t(Py_ssize_t v)

Return a new PyLongObject object from a C Py_ssize_t, or NULL on failure.

PyObject* PyLong_FromSize_t(size_t v)

Return a new PyLongObject object from a C size_t, or NULL on failure.

PyObject* PyLong_FromLongLong(long long v)

Return value: New reference.

Return a new PyLongObject object from a C long long, or NULL on failure.

PyObject* PyLong_FromUnsignedLongLong(unsigned long long v)

Return value: New reference.

Return a new PyLongObject object from a C unsigned long long, or NULL on failure.

PyObject* PyLong_FromDouble(double v)

Return value: New reference.

Return a new PyLongObject object from the integer part of v, or NULL on failure.

PyObject* PyLong_FromString(const char *str, char **pend, int base)

Return value: New reference.

Return a new PyLongObject based on the string value in str, which is interpreted according to the radix in base. If pend is non-NULL, *pend will point to the first character in str which follows the representation of the number. If base is 0, str is interpreted using the Entiers littéraux definition; in this case, leading zeros in a non-zero decimal number raises a ValueError. If base is not 0, it must be between 2 and 36, inclusive. Leading spaces and single underscores after a base specifier and between digits are ignored. If there are no digits, ValueError will be raised.

PyObject* PyLong_FromUnicode(Py_UNICODE *u, Py_ssize_t length, int base)

Return value: New reference.

Convert a sequence of Unicode digits to a Python integer value. The Unicode string is first encoded to a byte string using PyUnicode_EncodeDecimal() and then converted using PyLong_FromString().

Deprecated since version 3.3, will be removed in version 4.0: Part of the old-style Py_UNICODE API; please migrate to using PyLong_FromUnicodeObject().

PyObject* PyLong_FromUnicodeObject(PyObject *u, int base)

Convert a sequence of Unicode digits in the string u to a Python integer value. The Unicode string is first encoded to a byte string using PyUnicode_EncodeDecimal() and then converted using PyLong_FromString().

Nouveau dans la version 3.3.

PyObject* PyLong_FromVoidPtr(void *p)

Return value: New reference.

Create a Python integer from the pointer p. The pointer value can be retrieved from the resulting value using PyLong_AsVoidPtr().

long PyLong_AsLong(PyObject *obj)

Return a C long representation of obj. If obj is not an instance of PyLongObject, first call its __int__() method (if present) to convert it to a PyLongObject.

Raise OverflowError if the value of obj is out of range for a long.

Returns -1 on error. Use PyErr_Occurred() to disambiguate.

long PyLong_AsLongAndOverflow(PyObject *obj, int *overflow)

Return a C long representation of obj. If obj is not an instance of PyLongObject, first call its __int__() method (if present) to convert it to a PyLongObject.

If the value of obj is greater than LONG_MAX or less than LONG_MIN, set *overflow to 1 or -1, respectively, and return -1; otherwise, set *overflow to 0. If any other exception occurs set *overflow to 0 and return -1 as usual.

Returns -1 on error. Use PyErr_Occurred() to disambiguate.

long long PyLong_AsLongLong(PyObject *obj)

Return a C long long representation of obj. If obj is not an instance of PyLongObject, first call its __int__() method (if present) to convert it to a PyLongObject.

Raise OverflowError if the value of obj is out of range for a long.

Returns -1 on error. Use PyErr_Occurred() to disambiguate.

long long PyLong_AsLongLongAndOverflow(PyObject *obj, int *overflow)

Return a C long long representation of obj. If obj is not an instance of PyLongObject, first call its __int__() method (if present) to convert it to a PyLongObject.

If the value of obj is greater than PY_LLONG_MAX or less than PY_LLONG_MIN, set *overflow to 1 or -1, respectively, and return -1; otherwise, set *overflow to 0. If any other exception occurs set *overflow to 0 and return -1 as usual.

Returns -1 on error. Use PyErr_Occurred() to disambiguate.

Nouveau dans la version 3.2.

Py_ssize_t PyLong_AsSsize_t(PyObject *pylong)

Return a C Py_ssize_t representation of pylong. pylong must be an instance of PyLongObject.

Raise OverflowError if the value of pylong is out of range for a Py_ssize_t.

Returns -1 on error. Use PyErr_Occurred() to disambiguate.

unsigned long PyLong_AsUnsignedLong(PyObject *pylong)

Return a C unsigned long representation of pylong. pylong must be an instance of PyLongObject.

Raise OverflowError if the value of pylong is out of range for a unsigned long.

Returns (unsigned long)-1 on error. Use PyErr_Occurred() to disambiguate.

size_t PyLong_AsSize_t(PyObject *pylong)

Return a C size_t representation of pylong. pylong must be an instance of PyLongObject.

Raise OverflowError if the value of pylong is out of range for a size_t.

Returns (size_t)-1 on error. Use PyErr_Occurred() to disambiguate.

unsigned long long PyLong_AsUnsignedLongLong(PyObject *pylong)

Return a C unsigned long long representation of pylong. pylong must be an instance of PyLongObject.

Raise OverflowError if the value of pylong is out of range for an unsigned long long.

Returns (unsigned long long)-1 on error. Use PyErr_Occurred() to disambiguate.

Modifié dans la version 3.1: A negative pylong now raises OverflowError, not TypeError.

unsigned long PyLong_AsUnsignedLongMask(PyObject *obj)

Return a C unsigned long representation of obj. If obj is not an instance of PyLongObject, first call its __int__() method (if present) to convert it to a PyLongObject.

If the value of obj is out of range for an unsigned long, return the reduction of that value modulo ULONG_MAX + 1.

Returns -1 on error. Use PyErr_Occurred() to disambiguate.

unsigned long long PyLong_AsUnsignedLongLongMask(PyObject *obj)

Return a C unsigned long long representation of obj. If obj is not an instance of PyLongObject, first call its __int__() method (if present) to convert it to a PyLongObject.

If the value of obj is out of range for an unsigned long long, return the reduction of that value modulo PY_ULLONG_MAX + 1.

Returns -1 on error. Use PyErr_Occurred() to disambiguate.

double PyLong_AsDouble(PyObject *pylong)

Return a C double representation of pylong. pylong must be an instance of PyLongObject.

Raise OverflowError if the value of pylong is out of range for a double.

Returns -1.0 on error. Use PyErr_Occurred() to disambiguate.

void* PyLong_AsVoidPtr(PyObject *pylong)

Convert a Python integer pylong to a C void pointer. If pylong cannot be converted, an OverflowError will be raised. This is only assured to produce a usable void pointer for values created with PyLong_FromVoidPtr().

Returns NULL on error. Use PyErr_Occurred() to disambiguate.

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Les objets booléens

Les booléens en Python sont implémentés comme une classe dérivée des entiers. Il y a seulement deux booléens, Py_False et Py_True. Comme tel, les fonctions de création de suppression ne s’appliquent pas aux booléens. Toutefois, les macros suivantes sont disponibles.

int PyBool_Check(PyObject *o)

Renvoie vrai si o est de type PyBook_Type.

PyObject* Py_False

L’objet Python False. Cet objet n’a pas de méthodes. En ce qui concerne le comptage de référence, il doit être traité comme n’importe quel autre objet.

PyObject* Py_True

L’objet Python True. Cet objet n’a pas de méthodes. En ce qui concerne le comptage de références, il doit être traité comme n’importe quel autre objet.

Py_RETURN_FALSE

Renvoie Py_False depuis une fonction tout en incrémentant son nombre de références.

Py_RETURN_TRUE

Renvoie Py_True depuis une fonction, en incrémentant son nombre de références.

PyObject* PyBool_FromLong(long v)

Return value: New reference.

Renvoie une nouvelle référence de Py_True ou Py_False en fonction de la valeur de v.

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Objets représentant les nombres à virgule flottante

PyFloatObject

Ce sous-type de l’objet PyObject représente un nombre à virgule flottante en Python.

PyTypeObject PyFloat_Type

Cette instance de l’objet PyTypeObject représente le type nombre à virgule flottante en Python. C’est le même objet que la classe float de la couche Python.

int PyFloat_Check(PyObject *p)

Renvoie vrai si l’argument est de type PyFloatObject ou un sous-type de PyFloatObject.

int PyFloat_CheckExact(PyObject *p)

Renvoie vrai si l’argument est de type PyFloatObject, mais pas un sous-type de PyFloatObject.

PyObject* PyFloat_FromString(PyObject *str)

Return value: New reference.

Crée un objet PyFloatObject à partir de la valeur de la chaîne de caractères str, ou NULL en cas d’échec.

PyObject* PyFloat_FromDouble(double v)

Return value: New reference.

Crée un objet PyFloatObject à partir de v, ou NULL en cas d’échec.

double PyFloat_AsDouble(PyObject *pyfloat)

Renvoie une représentation du contenu d’un pyfloat sous la forme d’un double en C. Si le pyfloat n’est pas un nombre à virgule flottante mais contient une méthode __float__(), elle est d’abord appelée pour convertir le pyfloat en nombre à virgule flottante. Cette méthode renvoie -1.0 en cas d’échec, il faut appeler PyErr_Occurred() pour vérifier les erreurs.

double PyFloat_AS_DOUBLE(PyObject *pyfloat)

Renvoie une représentation du contenu d’un pyfloat sous la forme d’un double en C, sans vérifier les erreurs.

PyObject* PyFloat_GetInfo(void)

Renvoie une instance structseq qui contient les informations sur la précision et les valeurs minimales et maximales pour un nombre à virgule flottante. C’est une enveloppe autour du fichier d’entête float.h.

double PyFloat_GetMax()

Renvoie le nombre à virgule flottante fini maximal DBL_MAX sous la forme d’un double en C.

double PyFloat_GetMin()

Renvoie le nombre à virgule flottante minimal normalisé DBL_MIN sous la forme double en C.

int PyFloat_ClearFreeList()

Libère la mémoire de la free list des nombres à virgule flottante. Renvoie le nombre d’éléments qui n’ont pas pu être libérés.

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Objets nombres complexes

Les objets Python nombres complexes sont implémentés comme deux types distincts, lorsqu’ils sont vus de l’API C : l’un est l’objet Python tel qu’il est vu par les programmes Python, et l’autre est une structure C qui représente la valeur complexe courante. L’API fournit des fonctions pour travailler avec ces deux représentations.

Nombres complexes en tant que structures C

Remarquez que les fonctions qui acceptent ces structures comme paramètres et les renvoient comme résultats le font par valeur au lieur de les dé-référencer en utilisant des pointeurs. Cela est constant dans toute l’API.

Py_complex

Structure C représentant la valeur d’un nombre complexe Python. La majorité des fonctions qui traitent des nombres complexes utilisent cette structure en entrée ou en sortie, selon le cas. Elle est définie par :

typedef struct {
   double real;
   double imag;
} Py_complex;

Py_complex _Py_c_sum(Py_complex left, Py_complex right)

Renvoie la somme de deux nombres complexes, sous la forme d’un Py_complex en C.

Py_complex _Py_c_diff(Py_complex left, Py_complex right)

Renvoie la différence de deux nombres complexes, sous la forme d’un Py_complex en C.

Py_complex _Py_c_neg(Py_complex complex)

Renvoie l’opposé du nombre complexe complex, sous la forme d’un Py_complex en C.

Py_complex _Py_c_prod(Py_complex left, Py_complex right)

Renvoie le produit de deux nombres complexes, sous la forme d’un Py_complex en C.

Py_complex _Py_c_quot(Py_complex dividend, Py_complex divisor)

Renvoie le quotient de deux nombres complexes, sous la forme d’un Py_complex en C.

Si divisor est nul, cette méthode renvoie zéro et assigne EDOM à errno.

Py_complex _Py_c_pow(Py_complex num, Py_complex exp)

Renvoie num à la puissance exp, sous la forme d’un Py_complex en C.

Si num est nul et exp n’est pas un nombre réel positif, cette méthode renvoie zéro et assigne EDOM à errno.

Nombres complexes en tant qu’objets Python

PyComplexObject

Ce sous-type de l’objet PyObject représente un nombre complexe en Python.

PyTypeObject PyComplex_Type

Cette instance de PyTypeObject représente le type nombre complexe Python. C’est le même objet que la classe complex de la couche Python.

int PyComplex_Check(PyObject *p)

Renvoie vrai si l’argument est de type PyComplexObject ou un sous-type de PyComplexObject.

int PyComplex_CheckExact(PyObject *p)

Renvoie vrai si l’argument est de type PyComplexObject, mais pas un sous-type de PyComplexObject.

PyObject* PyComplex_FromCComplex(Py_complex v)

Return value: New reference.

Crée un nouveau nombre complexe à partir de la valeur d’un Py_complex en C.

PyObject* PyComplex_FromDoubles(double real, double imag)

Return value: New reference.

Renvoie un nouveau PyComplexObject à partir de real et de imag.

double PyComplex_RealAsDouble(PyObject *op)

Renvoie la partie réelle du nombre complexe op sous la forme d’un double en C.

double PyComplex_ImagAsDouble(PyObject *op)

Renvoie la partie imaginaire du nombre complexe op sous la forme d’un double en C.

Py_complex PyComplex_AsCComplex(PyObject *op)

Renvoie la valeur du nombre complexe op sous la forme d’un Py_complex en C.

Si op n’est pas un nombre complexe Python mais a une méthode __complex__(), cette méthode est d’abord appelée pour convertir op en nombre complexe Python. En cas d’échec, cette méthode renvoie -1.0 en tant que nombre réel.

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Objets bytes

These functions raise TypeError when expecting a bytes parameter and are called with a non-bytes parameter.

PyBytesObject

This subtype of PyObject represents a Python bytes object.

PyTypeObject PyBytes_Type

This instance of PyTypeObject represents the Python bytes type; it is the same object as bytes in the Python layer.

int PyBytes_Check(PyObject *o)

Return true if the object o is a bytes object or an instance of a subtype of the bytes type.

int PyBytes_CheckExact(PyObject *o)

Return true if the object o is a bytes object, but not an instance of a subtype of the bytes type.

PyObject* PyBytes_FromString(const char *v)

Return a new bytes object with a copy of the string v as value on success, and NULL on failure. The parameter v must not be NULL; it will not be checked.

PyObject* PyBytes_FromStringAndSize(const char *v, Py_ssize_t len)

Return a new bytes object with a copy of the string v as value and length len on success, and NULL on failure. If v is NULL, the contents of the bytes object are uninitialized.

PyObject* PyBytes_FromFormat(const char *format, ...)

Take a C printf()-style format string and a variable number of arguments, calculate the size of the resulting Python bytes object and return a bytes object with the values formatted into it. The variable arguments must be C types and must correspond exactly to the format characters in the format string. The following format characters are allowed:

Format Characters

Type

Comment

%%

n/a

The literal % character.

%c

int

A single byte, represented as a C int.

%d

int

Exactly equivalent to printf("%d").

%u

unsigned int

Exactly equivalent to printf("%u").

%ld

long

Exactly equivalent to printf("%ld").

%lu

unsigned long

Exactly equivalent to printf("%lu").

%zd

Py_ssize_t

Exactly equivalent to printf("%zd").

%zu

size_t

Exactly equivalent to printf("%zu").

%i

int

Exactly equivalent to printf("%i").

%x

int

Exactly equivalent to printf("%x").

%s

char*

A null-terminated C character array.

%p

void*

The hex representation of a C pointer. Mostly equivalent to printf("%p") except that it is guaranteed to start with the literal 0x regardless of what the platform’s printf yields.

An unrecognized format character causes all the rest of the format string to be copied as-is to the result object, and any extra arguments discarded.

PyObject* PyBytes_FromFormatV(const char *format, va_list vargs)

Identical to PyBytes_FromFormat() except that it takes exactly two arguments.

PyObject* PyBytes_FromObject(PyObject *o)

Return the bytes representation of object o that implements the buffer protocol.

Py_ssize_t PyBytes_Size(PyObject *o)

Return the length of the bytes in bytes object o.

Py_ssize_t PyBytes_GET_SIZE(PyObject *o)

Macro form of PyBytes_Size() but without error checking.

char* PyBytes_AsString(PyObject *o)

Return a pointer to the contents of o. The pointer refers to the internal buffer of o, which consists of len(o) + 1 bytes. The last byte in the buffer is always null, regardless of whether there are any other null bytes. The data must not be modified in any way, unless the object was just created using PyBytes_FromStringAndSize(NULL, size). It must not be deallocated. If o is not a bytes object at all, PyBytes_AsString() returns NULL and raises TypeError.

char* PyBytes_AS_STRING(PyObject *string)

Macro form of PyBytes_AsString() but without error checking.

int PyBytes_AsStringAndSize(PyObject *obj, char **buffer, Py_ssize_t *length)

Return the null-terminated contents of the object obj through the output variables buffer and length.

If length is NULL, the bytes object may not contain embedded null bytes; if it does, the function returns -1 and a ValueError is raised.

The buffer refers to an internal buffer of obj, which includes an additional null byte at the end (not counted in length). The data must not be modified in any way, unless the object was just created using PyBytes_FromStringAndSize(NULL, size). It must not be deallocated. If obj is not a bytes object at all, PyBytes_AsStringAndSize() returns -1 and raises TypeError.

Modifié dans la version 3.5: Previously, TypeError was raised when embedded null bytes were encountered in the bytes object.

void PyBytes_Concat(PyObject **bytes, PyObject *newpart)

Create a new bytes object in *bytes containing the contents of newpart appended to bytes; the caller will own the new reference. The reference to the old value of bytes will be stolen. If the new object cannot be created, the old reference to bytes will still be discarded and the value of *bytes will be set to NULL; the appropriate exception will be set.

void PyBytes_ConcatAndDel(PyObject **bytes, PyObject *newpart)

Create a new bytes object in *bytes containing the contents of newpart appended to bytes. This version decrements the reference count of newpart.

int _PyBytes_Resize(PyObject **bytes, Py_ssize_t newsize)

A way to resize a bytes object even though it is « immutable ». Only use this to build up a brand new bytes object; don’t use this if the bytes may already be known in other parts of the code. It is an error to call this function if the refcount on the input bytes object is not one. Pass the address of an existing bytes object as an lvalue (it may be written into), and the new size desired. On success, *bytes holds the resized bytes object and 0 is returned; the address in *bytes may differ from its input value. If the reallocation fails, the original bytes object at *bytes is deallocated, *bytes is set to NULL, MemoryError is set, and -1 is returned.

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Objets tableau d’octets

PyByteArrayObject

Ce sous-type de PyObject représente un objet bytearray Python.

PyTypeObject PyByteArray_Type

Cette instance de PyTypeObject représente le type Python bytearray, c’est le même que bytearray côté Python.

Macros de vérification de type

int PyByteArray_Check(PyObject *o)

Renvoie vrai si l’objet o est un bytearray ou une instance d’un sous-type du type bytearray.

int PyByteArray_CheckExact(PyObject *o)

Renvoie vrai si l’objet o est un bytearray, mais pas une instance d’un sous-type du type bytearray.

Fonctions directes sur l’API

PyObject* PyByteArray_FromObject(PyObject *o)

Renvoie un nouvel objet bytearray depuis n’importe quel objet, o, qui implémente le protocole buffer.

PyObject* PyByteArray_FromStringAndSize(const char *string, Py_ssize_t len)

Crée un nouvel objet bytearray à partir d’un objet string et de sa longueur, len. En cas d’échec, NULL est renvoyé.

PyObject* PyByteArray_Concat(PyObject *a, PyObject *b)

Concatène les bytearrays a et b et renvoie un nouveau bytearray avec le résultat.

Py_ssize_t PyByteArray_Size(PyObject *bytearray)

Renvoie la taille de bytearray après vérification de la présence d’un pointeur NULL.

char* PyByteArray_AsString(PyObject *bytearray)

Renvoie le contenu de bytearray sous forme d’un tableau de caractères, en vérifiant que ce n’est pas un pointeur NULL. Le tableau renvoyé se termine toujours par un octet null.

int PyByteArray_Resize(PyObject *bytearray, Py_ssize_t len)

Redimensionne le tampon interne de bytearray à la taille len.

Macros

Ces macros sont taillées pour la vitesse d’exécution et ne vérifient pas les pointeurs.

char* PyByteArray_AS_STRING(PyObject *bytearray)

Version macro de PyByteArray_AsString().

Py_ssize_t PyByteArray_GET_SIZE(PyObject *bytearray)

Version macro de PyByteArray_Size().

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Unicode Objects and Codecs

Unicode Objects

Since the implementation of PEP 393 [https://www.python.org/dev/peps/pep-0393] in Python 3.3, Unicode objects internally use a variety of representations, in order to allow handling the complete range of Unicode characters while staying memory efficient. There are special cases for strings where all code points are below 128, 256, or 65536; otherwise, code points must be below 1114112 (which is the full Unicode range).

Py_UNICODE* and UTF-8 representations are created on demand and cached in the Unicode object. The Py_UNICODE* representation is deprecated and inefficient; it should be avoided in performance- or memory-sensitive situations.

Due to the transition between the old APIs and the new APIs, unicode objects can internally be in two states depending on how they were created:

« canonical » unicode objects are all objects created by a non-deprecated unicode API. They use the most efficient representation allowed by the implementation.

« legacy » unicode objects have been created through one of the deprecated APIs (typically PyUnicode_FromUnicode()) and only bear the Py_UNICODE* representation; you will have to call PyUnicode_READY() on them before calling any other API.

Unicode Type

These are the basic Unicode object types used for the Unicode implementation in Python:

Py_UCS4

Py_UCS2

Py_UCS1

These types are typedefs for unsigned integer types wide enough to contain characters of 32 bits, 16 bits and 8 bits, respectively. When dealing with single Unicode characters, use Py_UCS4.

Nouveau dans la version 3.3.

Py_UNICODE

This is a typedef of wchar_t, which is a 16-bit type or 32-bit type depending on the platform.

Modifié dans la version 3.3: In previous versions, this was a 16-bit type or a 32-bit type depending on whether you selected a « narrow » or « wide » Unicode version of Python at build time.

PyASCIIObject

PyCompactUnicodeObject

PyUnicodeObject

These subtypes of PyObject represent a Python Unicode object. In almost all cases, they shouldn’t be used directly, since all API functions that deal with Unicode objects take and return PyObject pointers.

Nouveau dans la version 3.3.

PyTypeObject PyUnicode_Type

This instance of PyTypeObject represents the Python Unicode type. It is exposed to Python code as str.

The following APIs are really C macros and can be used to do fast checks and to access internal read-only data of Unicode objects:

int PyUnicode_Check(PyObject *o)

Return true if the object o is a Unicode object or an instance of a Unicode subtype.

int PyUnicode_CheckExact(PyObject *o)

Return true if the object o is a Unicode object, but not an instance of a subtype.

int PyUnicode_READY(PyObject *o)

Ensure the string object o is in the « canonical » representation. This is required before using any of the access macros described below.

Returns 0 on success and -1 with an exception set on failure, which in particular happens if memory allocation fails.

Nouveau dans la version 3.3.

Py_ssize_t PyUnicode_GET_LENGTH(PyObject *o)

Return the length of the Unicode string, in code points. o has to be a Unicode object in the « canonical » representation (not checked).

Nouveau dans la version 3.3.

Py_UCS1* PyUnicode_1BYTE_DATA(PyObject *o)

Py_UCS2* PyUnicode_2BYTE_DATA(PyObject *o)

Py_UCS4* PyUnicode_4BYTE_DATA(PyObject *o)

Return a pointer to the canonical representation cast to UCS1, UCS2 or UCS4 integer types for direct character access. No checks are performed if the canonical representation has the correct character size; use PyUnicode_KIND() to select the right macro. Make sure PyUnicode_READY() has been called before accessing this.

Nouveau dans la version 3.3.

PyUnicode_WCHAR_KIND

PyUnicode_1BYTE_KIND

PyUnicode_2BYTE_KIND

PyUnicode_4BYTE_KIND

Return values of the PyUnicode_KIND() macro.

Nouveau dans la version 3.3.

int PyUnicode_KIND(PyObject *o)

Return one of the PyUnicode kind constants (see above) that indicate how many bytes per character this Unicode object uses to store its data. o has to be a Unicode object in the « canonical » representation (not checked).

Nouveau dans la version 3.3.

void* PyUnicode_DATA(PyObject *o)

Return a void pointer to the raw unicode buffer. o has to be a Unicode object in the « canonical » representation (not checked).

Nouveau dans la version 3.3.

void PyUnicode_WRITE(int kind, void *data, Py_ssize_t index, Py_UCS4 value)

Write into a canonical representation data (as obtained with PyUnicode_DATA()). This macro does not do any sanity checks and is intended for usage in loops. The caller should cache the kind value and data pointer as obtained from other macro calls. index is the index in the string (starts at 0) and value is the new code point value which should be written to that location.

Nouveau dans la version 3.3.

Py_UCS4 PyUnicode_READ(int kind, void *data, Py_ssize_t index)

Read a code point from a canonical representation data (as obtained with PyUnicode_DATA()). No checks or ready calls are performed.

Nouveau dans la version 3.3.

Py_UCS4 PyUnicode_READ_CHAR(PyObject *o, Py_ssize_t index)

Read a character from a Unicode object o, which must be in the « canonical » representation. This is less efficient than PyUnicode_READ() if you do multiple consecutive reads.

Nouveau dans la version 3.3.

PyUnicode_MAX_CHAR_VALUE(PyObject *o)

Return the maximum code point that is suitable for creating another string based on o, which must be in the « canonical » representation. This is always an approximation but more efficient than iterating over the string.

Nouveau dans la version 3.3.

int PyUnicode_ClearFreeList()

Clear the free list. Return the total number of freed items.

Py_ssize_t PyUnicode_GET_SIZE(PyObject *o)

Return the size of the deprecated Py_UNICODE representation, in code units (this includes surrogate pairs as 2 units). o has to be a Unicode object (not checked).

Deprecated since version 3.3, will be removed in version 4.0: Part of the old-style Unicode API, please migrate to using PyUnicode_GET_LENGTH().

Py_ssize_t PyUnicode_GET_DATA_SIZE(PyObject *o)

Return the size of the deprecated Py_UNICODE representation in bytes. o has to be a Unicode object (not checked).

Deprecated since version 3.3, will be removed in version 4.0: Part of the old-style Unicode API, please migrate to using PyUnicode_GET_LENGTH().

Py_UNICODE* PyUnicode_AS_UNICODE(PyObject *o)

const char* PyUnicode_AS_DATA(PyObject *o)

Return a pointer to a Py_UNICODE representation of the object. The returned buffer is always terminated with an extra null code point. It may also contain embedded null code points, which would cause the string to be truncated when used in most C functions. The AS_DATA form casts the pointer to const char *. The o argument has to be a Unicode object (not checked).

Modifié dans la version 3.3: This macro is now inefficient – because in many cases the Py_UNICODE representation does not exist and needs to be created – and can fail (return NULL with an exception set). Try to port the code to use the new PyUnicode_nBYTE_DATA() macros or use PyUnicode_WRITE() or PyUnicode_READ().

Deprecated since version 3.3, will be removed in version 4.0: Part of the old-style Unicode API, please migrate to using the PyUnicode_nBYTE_DATA() family of macros.

Unicode Character Properties

Unicode provides many different character properties. The most often needed ones are available through these macros which are mapped to C functions depending on the Python configuration.

int Py_UNICODE_ISSPACE(Py_UNICODE ch)

Return 1 or 0 depending on whether ch is a whitespace character.

int Py_UNICODE_ISLOWER(Py_UNICODE ch)

Return 1 or 0 depending on whether ch is a lowercase character.

int Py_UNICODE_ISUPPER(Py_UNICODE ch)

Return 1 or 0 depending on whether ch is an uppercase character.

int Py_UNICODE_ISTITLE(Py_UNICODE ch)

Return 1 or 0 depending on whether ch is a titlecase character.

int Py_UNICODE_ISLINEBREAK(Py_UNICODE ch)

Return 1 or 0 depending on whether ch is a linebreak character.

int Py_UNICODE_ISDECIMAL(Py_UNICODE ch)

Return 1 or 0 depending on whether ch is a decimal character.

int Py_UNICODE_ISDIGIT(Py_UNICODE ch)

Return 1 or 0 depending on whether ch is a digit character.

int Py_UNICODE_ISNUMERIC(Py_UNICODE ch)

Return 1 or 0 depending on whether ch is a numeric character.

int Py_UNICODE_ISALPHA(Py_UNICODE ch)

Return 1 or 0 depending on whether ch is an alphabetic character.

int Py_UNICODE_ISALNUM(Py_UNICODE ch)

Return 1 or 0 depending on whether ch is an alphanumeric character.

int Py_UNICODE_ISPRINTABLE(Py_UNICODE ch)

Return 1 or 0 depending on whether ch is a printable character. Nonprintable characters are those characters defined in the Unicode character database as « Other » or « Separator », excepting the ASCII space (0x20) which is considered printable. (Note that printable characters in this context are those which should not be escaped when repr() is invoked on a string. It has no bearing on the handling of strings written to sys.stdout or sys.stderr.)

These APIs can be used for fast direct character conversions:

Py_UNICODE Py_UNICODE_TOLOWER(Py_UNICODE ch)

Return the character ch converted to lower case.

Obsolète depuis la version 3.3: This function uses simple case mappings.

Py_UNICODE Py_UNICODE_TOUPPER(Py_UNICODE ch)

Return the character ch converted to upper case.

Obsolète depuis la version 3.3: This function uses simple case mappings.

Py_UNICODE Py_UNICODE_TOTITLE(Py_UNICODE ch)

Return the character ch converted to title case.

Obsolète depuis la version 3.3: This function uses simple case mappings.

int Py_UNICODE_TODECIMAL(Py_UNICODE ch)

Return the character ch converted to a decimal positive integer. Return -1 if this is not possible. This macro does not raise exceptions.

int Py_UNICODE_TODIGIT(Py_UNICODE ch)

Return the character ch converted to a single digit integer. Return -1 if this is not possible. This macro does not raise exceptions.

double Py_UNICODE_TONUMERIC(Py_UNICODE ch)

Return the character ch converted to a double. Return -1.0 if this is not possible. This macro does not raise exceptions.

These APIs can be used to work with surrogates:

Py_UNICODE_IS_SURROGATE(ch)

Check if ch is a surrogate (0xD800 <= ch <= 0xDFFF).

Py_UNICODE_IS_HIGH_SURROGATE(ch)

Check if ch is a high surrogate (0xD800 <= ch <= 0xDBFF).

Py_UNICODE_IS_LOW_SURROGATE(ch)

Check if ch is a low surrogate (0xDC00 <= ch <= 0xDFFF).

Py_UNICODE_JOIN_SURROGATES(high, low)

Join two surrogate characters and return a single Py_UCS4 value. high and low are respectively the leading and trailing surrogates in a surrogate pair.

Creating and accessing Unicode strings

To create Unicode objects and access their basic sequence properties, use these APIs:

PyObject* PyUnicode_New(Py_ssize_t size, Py_UCS4 maxchar)

Create a new Unicode object. maxchar should be the true maximum code point to be placed in the string. As an approximation, it can be rounded up to the nearest value in the sequence 127, 255, 65535, 1114111.

This is the recommended way to allocate a new Unicode object. Objects created using this function are not resizable.

Nouveau dans la version 3.3.

PyObject* PyUnicode_FromKindAndData(int kind, const void *buffer, Py_ssize_t size)

Create a new Unicode object with the given kind (possible values are PyUnicode_1BYTE_KIND etc., as returned by PyUnicode_KIND()). The buffer must point to an array of size units of 1, 2 or 4 bytes per character, as given by the kind.

Nouveau dans la version 3.3.

PyObject* PyUnicode_FromStringAndSize(const char *u, Py_ssize_t size)

Create a Unicode object from the char buffer u. The bytes will be interpreted as being UTF-8 encoded. The buffer is copied into the new object. If the buffer is not NULL, the return value might be a shared object, i.e. modification of the data is not allowed.

If u is NULL, this function behaves like PyUnicode_FromUnicode() with the buffer set to NULL. This usage is deprecated in favor of PyUnicode_New().

PyObject *PyUnicode_FromString(const char *u)

Create a Unicode object from a UTF-8 encoded null-terminated char buffer u.

PyObject* PyUnicode_FromFormat(const char *format, ...)

Take a C printf()-style format string and a variable number of arguments, calculate the size of the resulting Python unicode string and return a string with the values formatted into it. The variable arguments must be C types and must correspond exactly to the format characters in the format ASCII-encoded string. The following format characters are allowed:

Format Characters

Type

Comment

%%

n/a

The literal % character.

%c

int

A single character, represented as a C int.

%d

int

Exactly equivalent to printf("%d").

%u

unsigned int

Exactly equivalent to printf("%u").

%ld

long

Exactly equivalent to printf("%ld").

%li

long

Exactly equivalent to printf("%li").

%lu

unsigned long

Exactly equivalent to printf("%lu").

%lld

long long

Exactly equivalent to printf("%lld").

%lli

long long

Exactly equivalent to printf("%lli").

%llu

unsigned long long

Exactly equivalent to printf("%llu").

%zd

Py_ssize_t

Exactly equivalent to printf("%zd").

%zi

Py_ssize_t

Exactly equivalent to printf("%zi").

%zu

size_t

Exactly equivalent to printf("%zu").

%i

int

Exactly equivalent to printf("%i").

%x

int

Exactly equivalent to printf("%x").

%s

char*

A null-terminated C character array.

%p

void*

The hex representation of a C pointer. Mostly equivalent to printf("%p") except that it is guaranteed to start with the literal 0x regardless of what the platform’s printf yields.

%A

PyObject*

The result of calling ascii().

%U

PyObject*

Un objet Unicode.

%V

PyObject*, char *

A unicode object (which may be NULL) and a null-terminated C character array as a second parameter (which will be used, if the first parameter is NULL).

%S

PyObject*

The result of calling PyObject_Str().

%R

PyObject*

The result of calling PyObject_Repr().

An unrecognized format character causes all the rest of the format string to be copied as-is to the result string, and any extra arguments discarded.

Note

The width formatter unit is number of characters rather than bytes. The precision formatter unit is number of bytes for "%s" and "%V" (if the PyObject* argument is NULL), and a number of characters for "%A", "%U", "%S", "%R" and "%V" (if the PyObject* argument is not NULL).

Modifié dans la version 3.2: Support for "%lld" and "%llu" added.

Modifié dans la version 3.3: Support for "%li", "%lli" and "%zi" added.

Modifié dans la version 3.4: Support width and precision formatter for "%s", "%A", "%U", "%V", "%S", "%R" added.

PyObject* PyUnicode_FromFormatV(const char *format, va_list vargs)

Identical to PyUnicode_FromFormat() except that it takes exactly two arguments.

PyObject* PyUnicode_FromEncodedObject(PyObject *obj, const char *encoding, const char *errors)

Return value: New reference.

Decode an encoded object obj to a Unicode object.

bytes, bytearray and other bytes-like objects are decoded according to the given encoding and using the error handling defined by errors. Both can be NULL to have the interface use the default values (see Built-in Codecs for details).

All other objects, including Unicode objects, cause a TypeError to be set.

The API returns NULL if there was an error. The caller is responsible for decref’ing the returned objects.

Py_ssize_t PyUnicode_GetLength(PyObject *unicode)

Return the length of the Unicode object, in code points.

Nouveau dans la version 3.3.

Py_ssize_t PyUnicode_CopyCharacters(PyObject *to, Py_ssize_t to_start, PyObject *from, Py_ssize_t from_start, Py_ssize_t how_many)

Copy characters from one Unicode object into another. This function performs character conversion when necessary and falls back to memcpy() if possible. Returns -1 and sets an exception on error, otherwise returns the number of copied characters.

Nouveau dans la version 3.3.

Py_ssize_t PyUnicode_Fill(PyObject *unicode, Py_ssize_t start, Py_ssize_t length, Py_UCS4 fill_char)

Fill a string with a character: write fill_char into unicode[start:start+length].

Fail if fill_char is bigger than the string maximum character, or if the string has more than 1 reference.

Return the number of written character, or return -1 and raise an exception on error.

Nouveau dans la version 3.3.

int PyUnicode_WriteChar(PyObject *unicode, Py_ssize_t index, Py_UCS4 character)

Write a character to a string. The string must have been created through PyUnicode_New(). Since Unicode strings are supposed to be immutable, the string must not be shared, or have been hashed yet.

This function checks that unicode is a Unicode object, that the index is not out of bounds, and that the object can be modified safely (i.e. that it its reference count is one).

Nouveau dans la version 3.3.

Py_UCS4 PyUnicode_ReadChar(PyObject *unicode, Py_ssize_t index)

Read a character from a string. This function checks that unicode is a Unicode object and the index is not out of bounds, in contrast to the macro version PyUnicode_READ_CHAR().

Nouveau dans la version 3.3.

PyObject* PyUnicode_Substring(PyObject *str, Py_ssize_t start, Py_ssize_t end)

Return a substring of str, from character index start (included) to character index end (excluded). Negative indices are not supported.

Nouveau dans la version 3.3.

Py_UCS4* PyUnicode_AsUCS4(PyObject *u, Py_UCS4 *buffer, Py_ssize_t buflen, int copy_null)

Copy the string u into a UCS4 buffer, including a null character, if copy_null is set. Returns NULL and sets an exception on error (in particular, a SystemError if buflen is smaller than the length of u). buffer is returned on success.

Nouveau dans la version 3.3.

Py_UCS4* PyUnicode_AsUCS4Copy(PyObject *u)

Copy the string u into a new UCS4 buffer that is allocated using PyMem_Malloc(). If this fails, NULL is returned with a MemoryError set. The returned buffer always has an extra null code point appended.

Nouveau dans la version 3.3.

Deprecated Py_UNICODE APIs

Deprecated since version 3.3, will be removed in version 4.0.

These API functions are deprecated with the implementation of PEP 393 [https://www.python.org/dev/peps/pep-0393]. Extension modules can continue using them, as they will not be removed in Python 3.x, but need to be aware that their use can now cause performance and memory hits.

PyObject* PyUnicode_FromUnicode(const Py_UNICODE *u, Py_ssize_t size)

Return value: New reference.

Create a Unicode object from the Py_UNICODE buffer u of the given size. u may be NULL which causes the contents to be undefined. It is the user’s responsibility to fill in the needed data. The buffer is copied into the new object.

If the buffer is not NULL, the return value might be a shared object. Therefore, modification of the resulting Unicode object is only allowed when u is NULL.

If the buffer is NULL, PyUnicode_READY() must be called once the string content has been filled before using any of the access macros such as PyUnicode_KIND().

Please migrate to using PyUnicode_FromKindAndData(), PyUnicode_FromWideChar() or PyUnicode_New().

Py_UNICODE* PyUnicode_AsUnicode(PyObject *unicode)

Return a read-only pointer to the Unicode object’s internal Py_UNICODE buffer, or NULL on error. This will create the Py_UNICODE* representation of the object if it is not yet available. The buffer is always terminated with an extra null code point. Note that the resulting Py_UNICODE string may also contain embedded null code points, which would cause the string to be truncated when used in most C functions.

Please migrate to using PyUnicode_AsUCS4(), PyUnicode_AsWideChar(), PyUnicode_ReadChar() or similar new APIs.

PyObject* PyUnicode_TransformDecimalToASCII(Py_UNICODE *s, Py_ssize_t size)

Create a Unicode object by replacing all decimal digits in Py_UNICODE buffer of the given size by ASCII digits 0–9 according to their decimal value. Return NULL if an exception occurs.

Py_UNICODE* PyUnicode_AsUnicodeAndSize(PyObject *unicode, Py_ssize_t *size)

Like PyUnicode_AsUnicode(), but also saves the Py_UNICODE() array length (excluding the extra null terminator) in size. Note that the resulting Py_UNICODE* string may contain embedded null code points, which would cause the string to be truncated when used in most C functions.

Nouveau dans la version 3.3.

Py_UNICODE* PyUnicode_AsUnicodeCopy(PyObject *unicode)

Create a copy of a Unicode string ending with a null code point. Return NULL and raise a MemoryError exception on memory allocation failure, otherwise return a new allocated buffer (use PyMem_Free() to free the buffer). Note that the resulting Py_UNICODE* string may contain embedded null code points, which would cause the string to be truncated when used in most C functions.

Nouveau dans la version 3.2.

Please migrate to using PyUnicode_AsUCS4Copy() or similar new APIs.

Py_ssize_t PyUnicode_GetSize(PyObject *unicode)

Return the size of the deprecated Py_UNICODE representation, in code units (this includes surrogate pairs as 2 units).

Please migrate to using PyUnicode_GetLength().

PyObject* PyUnicode_FromObject(PyObject *obj)

Return value: New reference.

Copy an instance of a Unicode subtype to a new true Unicode object if necessary. If obj is already a true Unicode object (not a subtype), return the reference with incremented refcount.

Objects other than Unicode or its subtypes will cause a TypeError.

Locale Encoding

The current locale encoding can be used to decode text from the operating system.

PyObject* PyUnicode_DecodeLocaleAndSize(const char *str, Py_ssize_t len, const char *errors)

Decode a string from the current locale encoding. The supported error handlers are "strict" and "surrogateescape" (PEP 383 [https://www.python.org/dev/peps/pep-0383]). The decoder uses "strict" error handler if errors is NULL. str must end with a null character but cannot contain embedded null characters.

Use PyUnicode_DecodeFSDefaultAndSize() to decode a string from Py_FileSystemDefaultEncoding (the locale encoding read at Python startup).

Voir aussi

The Py_DecodeLocale() function.

Nouveau dans la version 3.3.

Modifié dans la version 3.6.5: The function now also uses the current locale encoding for the surrogateescape error handler. Previously, Py_DecodeLocale() was used for the surrogateescape, and the current locale encoding was used for strict.

PyObject* PyUnicode_DecodeLocale(const char *str, const char *errors)

Similar to PyUnicode_DecodeLocaleAndSize(), but compute the string length using strlen().

Nouveau dans la version 3.3.

PyObject* PyUnicode_EncodeLocale(PyObject *unicode, const char *errors)

Encode a Unicode object to the current locale encoding. The supported error handlers are "strict" and "surrogateescape" (PEP 383 [https://www.python.org/dev/peps/pep-0383]). The encoder uses "strict" error handler if errors is NULL. Return a bytes object. unicode cannot contain embedded null characters.

Use PyUnicode_EncodeFSDefault() to encode a string to Py_FileSystemDefaultEncoding (the locale encoding read at Python startup).

Voir aussi

The Py_EncodeLocale() function.

Nouveau dans la version 3.3.

Modifié dans la version 3.6.5: The function now also uses the current locale encoding for the surrogateescape error handler. Previously, Py_EncodeLocale() was used for the surrogateescape, and the current locale encoding was used for strict.

File System Encoding

To encode and decode file names and other environment strings, Py_FileSystemDefaultEncoding should be used as the encoding, and Py_FileSystemDefaultEncodeErrors should be used as the error handler (PEP 383 [https://www.python.org/dev/peps/pep-0383] and PEP 529 [https://www.python.org/dev/peps/pep-0529]). To encode file names to bytes during argument parsing, the "O&" converter should be used, passing PyUnicode_FSConverter() as the conversion function:

int PyUnicode_FSConverter(PyObject* obj, void* result)

ParseTuple converter: encode str objects – obtained directly or through the os.PathLike interface – to bytes using PyUnicode_EncodeFSDefault(); bytes objects are output as-is. result must be a PyBytesObject* which must be released when it is no longer used.

Nouveau dans la version 3.1.

Modifié dans la version 3.6: Accepte un path-like object.

To decode file names to str during argument parsing, the "O&" converter should be used, passing PyUnicode_FSDecoder() as the conversion function:

int PyUnicode_FSDecoder(PyObject* obj, void* result)

ParseTuple converter: decode bytes objects – obtained either directly or indirectly through the os.PathLike interface – to str using PyUnicode_DecodeFSDefaultAndSize(); str objects are output as-is. result must be a PyUnicodeObject* which must be released when it is no longer used.

Nouveau dans la version 3.2.

Modifié dans la version 3.6: Accepte un path-like object.

PyObject* PyUnicode_DecodeFSDefaultAndSize(const char *s, Py_ssize_t size)

Decode a string using Py_FileSystemDefaultEncoding and the Py_FileSystemDefaultEncodeErrors error handler.

If Py_FileSystemDefaultEncoding is not set, fall back to the locale encoding.

Py_FileSystemDefaultEncoding is initialized at startup from the locale encoding and cannot be modified later. If you need to decode a string from the current locale encoding, use PyUnicode_DecodeLocaleAndSize().

Voir aussi

The Py_DecodeLocale() function.

Modifié dans la version 3.6: Use Py_FileSystemDefaultEncodeErrors error handler.

PyObject* PyUnicode_DecodeFSDefault(const char *s)

Decode a null-terminated string using Py_FileSystemDefaultEncoding and the Py_FileSystemDefaultEncodeErrors error handler.

If Py_FileSystemDefaultEncoding is not set, fall back to the locale encoding.

Use PyUnicode_DecodeFSDefaultAndSize() if you know the string length.

Modifié dans la version 3.6: Use Py_FileSystemDefaultEncodeErrors error handler.

PyObject* PyUnicode_EncodeFSDefault(PyObject *unicode)

Encode a Unicode object to Py_FileSystemDefaultEncoding with the Py_FileSystemDefaultEncodeErrors error handler, and return bytes. Note that the resulting bytes object may contain null bytes.

If Py_FileSystemDefaultEncoding is not set, fall back to the locale encoding.

Py_FileSystemDefaultEncoding is initialized at startup from the locale encoding and cannot be modified later. If you need to encode a string to the current locale encoding, use PyUnicode_EncodeLocale().

Voir aussi

The Py_EncodeLocale() function.

Nouveau dans la version 3.2.

Modifié dans la version 3.6: Use Py_FileSystemDefaultEncodeErrors error handler.

wchar_t Support

wchar_t support for platforms which support it:

PyObject* PyUnicode_FromWideChar(const wchar_t *w, Py_ssize_t size)

Return value: New reference.

Create a Unicode object from the wchar_t buffer w of the given size. Passing -1 as the size indicates that the function must itself compute the length, using wcslen. Return NULL on failure.

Py_ssize_t PyUnicode_AsWideChar(PyObject *unicode, wchar_t *w, Py_ssize_t size)

Copy the Unicode object contents into the wchar_t buffer w. At most size wchar_t characters are copied (excluding a possibly trailing null termination character). Return the number of wchar_t characters copied or -1 in case of an error. Note that the resulting wchar_t* string may or may not be null-terminated. It is the responsibility of the caller to make sure that the wchar_t* string is null-terminated in case this is required by the application. Also, note that the wchar_t* string might contain null characters, which would cause the string to be truncated when used with most C functions.

wchar_t* PyUnicode_AsWideCharString(PyObject *unicode, Py_ssize_t *size)

Convert the Unicode object to a wide character string. The output string always ends with a null character. If size is not NULL, write the number of wide characters (excluding the trailing null termination character) into *size.

Returns a buffer allocated by PyMem_Alloc() (use PyMem_Free() to free it) on success. On error, returns NULL, *size is undefined and raises a MemoryError. Note that the resulting wchar_t string might contain null characters, which would cause the string to be truncated when used with most C functions.

Nouveau dans la version 3.2.

Built-in Codecs

Python provides a set of built-in codecs which are written in C for speed. All of these codecs are directly usable via the following functions.

Many of the following APIs take two arguments encoding and errors, and they have the same semantics as the ones of the built-in str() string object constructor.

Setting encoding to NULL causes the default encoding to be used which is ASCII. The file system calls should use PyUnicode_FSConverter() for encoding file names. This uses the variable Py_FileSystemDefaultEncoding internally. This variable should be treated as read-only: on some systems, it will be a pointer to a static string, on others, it will change at run-time (such as when the application invokes setlocale).

Error handling is set by errors which may also be set to NULL meaning to use the default handling defined for the codec. Default error handling for all built-in codecs is « strict » (ValueError is raised).

The codecs all use a similar interface. Only deviation from the following generic ones are documented for simplicity.

Generic Codecs

These are the generic codec APIs:

PyObject* PyUnicode_Decode(const char *s, Py_ssize_t size, const char *encoding, const char *errors)

Return value: New reference.

Create a Unicode object by decoding size bytes of the encoded string s. encoding and errors have the same meaning as the parameters of the same name in the str() built-in function. The codec to be used is looked up using the Python codec registry. Return NULL if an exception was raised by the codec.

PyObject* PyUnicode_AsEncodedString(PyObject *unicode, const char *encoding, const char *errors)

Return value: New reference.

Encode a Unicode object and return the result as Python bytes object. encoding and errors have the same meaning as the parameters of the same name in the Unicode encode() method. The codec to be used is looked up using the Python codec registry. Return NULL if an exception was raised by the codec.

PyObject* PyUnicode_Encode(const Py_UNICODE *s, Py_ssize_t size, const char *encoding, const char *errors)

Return value: New reference.

Encode the Py_UNICODE buffer s of the given size and return a Python bytes object. encoding and errors have the same meaning as the parameters of the same name in the Unicode encode() method. The codec to be used is looked up using the Python codec registry. Return NULL if an exception was raised by the codec.

Deprecated since version 3.3, will be removed in version 4.0: Part of the old-style Py_UNICODE API; please migrate to using PyUnicode_AsEncodedString().

UTF-8 Codecs

These are the UTF-8 codec APIs:

PyObject* PyUnicode_DecodeUTF8(const char *s, Py_ssize_t size, const char *errors)

Return value: New reference.

Create a Unicode object by decoding size bytes of the UTF-8 encoded string s. Return NULL if an exception was raised by the codec.

PyObject* PyUnicode_DecodeUTF8Stateful(const char *s, Py_ssize_t size, const char *errors, Py_ssize_t *consumed)

Return value: New reference.

If consumed is NULL, behave like PyUnicode_DecodeUTF8(). If consumed is not NULL, trailing incomplete UTF-8 byte sequences will not be treated as an error. Those bytes will not be decoded and the number of bytes that have been decoded will be stored in consumed.

PyObject* PyUnicode_AsUTF8String(PyObject *unicode)

Return value: New reference.

Encode a Unicode object using UTF-8 and return the result as Python bytes object. Error handling is « strict ». Return NULL if an exception was raised by the codec.

char* PyUnicode_AsUTF8AndSize(PyObject *unicode, Py_ssize_t *size)

Return a pointer to the UTF-8 encoding of the Unicode object, and store the size of the encoded representation (in bytes) in size. The size argument can be NULL; in this case no size will be stored. The returned buffer always has an extra null byte appended (not included in size), regardless of whether there are any other null code points.

In the case of an error, NULL is returned with an exception set and no size is stored.

This caches the UTF-8 representation of the string in the Unicode object, and subsequent calls will return a pointer to the same buffer. The caller is not responsible for deallocating the buffer.

Nouveau dans la version 3.3.

char* PyUnicode_AsUTF8(PyObject *unicode)

As PyUnicode_AsUTF8AndSize(), but does not store the size.

Nouveau dans la version 3.3.

PyObject* PyUnicode_EncodeUTF8(const Py_UNICODE *s, Py_ssize_t size, const char *errors)

Return value: New reference.

Encode the Py_UNICODE buffer s of the given size using UTF-8 and return a Python bytes object. Return NULL if an exception was raised by the codec.

Deprecated since version 3.3, will be removed in version 4.0: Part of the old-style Py_UNICODE API; please migrate to using PyUnicode_AsUTF8String(), PyUnicode_AsUTF8AndSize() or PyUnicode_AsEncodedString().

UTF-32 Codecs

These are the UTF-32 codec APIs:

PyObject* PyUnicode_DecodeUTF32(const char *s, Py_ssize_t size, const char *errors, int *byteorder)

Decode size bytes from a UTF-32 encoded buffer string and return the corresponding Unicode object. errors (if non-NULL) defines the error handling. It defaults to « strict ».

If byteorder is non-NULL, the decoder starts decoding using the given byte order:

*byteorder == -1: little endian
*byteorder == 0:  native order
*byteorder == 1:  big endian

If *byteorder is zero, and the first four bytes of the input data are a byte order mark (BOM), the decoder switches to this byte order and the BOM is not copied into the resulting Unicode string. If *byteorder is -1 or 1, any byte order mark is copied to the output.

After completion, *byteorder is set to the current byte order at the end of input data.

If byteorder is NULL, the codec starts in native order mode.

Return NULL if an exception was raised by the codec.

PyObject* PyUnicode_DecodeUTF32Stateful(const char *s, Py_ssize_t size, const char *errors, int *byteorder, Py_ssize_t *consumed)

If consumed is NULL, behave like PyUnicode_DecodeUTF32(). If consumed is not NULL, PyUnicode_DecodeUTF32Stateful() will not treat trailing incomplete UTF-32 byte sequences (such as a number of bytes not divisible by four) as an error. Those bytes will not be decoded and the number of bytes that have been decoded will be stored in consumed.

PyObject* PyUnicode_AsUTF32String(PyObject *unicode)

Return a Python byte string using the UTF-32 encoding in native byte order. The string always starts with a BOM mark. Error handling is « strict ». Return NULL if an exception was raised by the codec.

PyObject* PyUnicode_EncodeUTF32(const Py_UNICODE *s, Py_ssize_t size, const char *errors, int byteorder)

Return a Python bytes object holding the UTF-32 encoded value of the Unicode data in s. Output is written according to the following byte order:

byteorder == -1: little endian
byteorder == 0:  native byte order (writes a BOM mark)
byteorder == 1:  big endian

If byteorder is 0, the output string will always start with the Unicode BOM mark (U+FEFF). In the other two modes, no BOM mark is prepended.

If Py_UNICODE_WIDE is not defined, surrogate pairs will be output as a single code point.

Return NULL if an exception was raised by the codec.

Deprecated since version 3.3, will be removed in version 4.0: Part of the old-style Py_UNICODE API; please migrate to using PyUnicode_AsUTF32String() or PyUnicode_AsEncodedString().

UTF-16 Codecs

These are the UTF-16 codec APIs:

PyObject* PyUnicode_DecodeUTF16(const char *s, Py_ssize_t size, const char *errors, int *byteorder)

Return value: New reference.

Decode size bytes from a UTF-16 encoded buffer string and return the corresponding Unicode object. errors (if non-NULL) defines the error handling. It defaults to « strict ».

If byteorder is non-NULL, the decoder starts decoding using the given byte order:

*byteorder == -1: little endian
*byteorder == 0:  native order
*byteorder == 1:  big endian

If *byteorder is zero, and the first two bytes of the input data are a byte order mark (BOM), the decoder switches to this byte order and the BOM is not copied into the resulting Unicode string. If *byteorder is -1 or 1, any byte order mark is copied to the output (where it will result in either a \ufeff or a \ufffe character).

After completion, *byteorder is set to the current byte order at the end of input data.

If byteorder is NULL, the codec starts in native order mode.

Return NULL if an exception was raised by the codec.

PyObject* PyUnicode_DecodeUTF16Stateful(const char *s, Py_ssize_t size, const char *errors, int *byteorder, Py_ssize_t *consumed)

Return value: New reference.

If consumed is NULL, behave like PyUnicode_DecodeUTF16(). If consumed is not NULL, PyUnicode_DecodeUTF16Stateful() will not treat trailing incomplete UTF-16 byte sequences (such as an odd number of bytes or a split surrogate pair) as an error. Those bytes will not be decoded and the number of bytes that have been decoded will be stored in consumed.

PyObject* PyUnicode_AsUTF16String(PyObject *unicode)

Return value: New reference.

Return a Python byte string using the UTF-16 encoding in native byte order. The string always starts with a BOM mark. Error handling is « strict ». Return NULL if an exception was raised by the codec.

PyObject* PyUnicode_EncodeUTF16(const Py_UNICODE *s, Py_ssize_t size, const char *errors, int byteorder)

Return value: New reference.

Return a Python bytes object holding the UTF-16 encoded value of the Unicode data in s. Output is written according to the following byte order:

byteorder == -1: little endian
byteorder == 0:  native byte order (writes a BOM mark)
byteorder == 1:  big endian

If byteorder is 0, the output string will always start with the Unicode BOM mark (U+FEFF). In the other two modes, no BOM mark is prepended.

If Py_UNICODE_WIDE is defined, a single Py_UNICODE value may get represented as a surrogate pair. If it is not defined, each Py_UNICODE values is interpreted as a UCS-2 character.

Return NULL if an exception was raised by the codec.

Deprecated since version 3.3, will be removed in version 4.0: Part of the old-style Py_UNICODE API; please migrate to using PyUnicode_AsUTF16String() or PyUnicode_AsEncodedString().

UTF-7 Codecs

These are the UTF-7 codec APIs:

PyObject* PyUnicode_DecodeUTF7(const char *s, Py_ssize_t size, const char *errors)

Create a Unicode object by decoding size bytes of the UTF-7 encoded string s. Return NULL if an exception was raised by the codec.

PyObject* PyUnicode_DecodeUTF7Stateful(const char *s, Py_ssize_t size, const char *errors, Py_ssize_t *consumed)

If consumed is NULL, behave like PyUnicode_DecodeUTF7(). If consumed is not NULL, trailing incomplete UTF-7 base-64 sections will not be treated as an error. Those bytes will not be decoded and the number of bytes that have been decoded will be stored in consumed.

PyObject* PyUnicode_EncodeUTF7(const Py_UNICODE *s, Py_ssize_t size, int base64SetO, int base64WhiteSpace, const char *errors)

Encode the Py_UNICODE buffer of the given size using UTF-7 and return a Python bytes object. Return NULL if an exception was raised by the codec.

If base64SetO is nonzero, « Set O » (punctuation that has no otherwise special meaning) will be encoded in base-64. If base64WhiteSpace is nonzero, whitespace will be encoded in base-64. Both are set to zero for the Python « utf-7 » codec.

Deprecated since version 3.3, will be removed in version 4.0: Part of the old-style Py_UNICODE API; please migrate to using PyUnicode_AsEncodedString().

Unicode-Escape Codecs

These are the « Unicode Escape » codec APIs:

PyObject* PyUnicode_DecodeUnicodeEscape(const char *s, Py_ssize_t size, const char *errors)

Return value: New reference.

Create a Unicode object by decoding size bytes of the Unicode-Escape encoded string s. Return NULL if an exception was raised by the codec.

PyObject* PyUnicode_AsUnicodeEscapeString(PyObject *unicode)

Return value: New reference.

Encode a Unicode object using Unicode-Escape and return the result as a bytes object. Error handling is « strict ». Return NULL if an exception was raised by the codec.

PyObject* PyUnicode_EncodeUnicodeEscape(const Py_UNICODE *s, Py_ssize_t size)

Return value: New reference.

Encode the Py_UNICODE buffer of the given size using Unicode-Escape and return a bytes object. Return NULL if an exception was raised by the codec.

Deprecated since version 3.3, will be removed in version 4.0: Part of the old-style Py_UNICODE API; please migrate to using PyUnicode_AsUnicodeEscapeString().

Raw-Unicode-Escape Codecs

These are the « Raw Unicode Escape » codec APIs:

PyObject* PyUnicode_DecodeRawUnicodeEscape(const char *s, Py_ssize_t size, const char *errors)

Return value: New reference.

Create a Unicode object by decoding size bytes of the Raw-Unicode-Escape encoded string s. Return NULL if an exception was raised by the codec.

PyObject* PyUnicode_AsRawUnicodeEscapeString(PyObject *unicode)

Return value: New reference.

Encode a Unicode object using Raw-Unicode-Escape and return the result as a bytes object. Error handling is « strict ». Return NULL if an exception was raised by the codec.

PyObject* PyUnicode_EncodeRawUnicodeEscape(const Py_UNICODE *s, Py_ssize_t size)

Return value: New reference.

Encode the Py_UNICODE buffer of the given size using Raw-Unicode-Escape and return a bytes object. Return NULL if an exception was raised by the codec.

Deprecated since version 3.3, will be removed in version 4.0: Part of the old-style Py_UNICODE API; please migrate to using PyUnicode_AsRawUnicodeEscapeString() or PyUnicode_AsEncodedString().

Latin-1 Codecs

These are the Latin-1 codec APIs: Latin-1 corresponds to the first 256 Unicode ordinals and only these are accepted by the codecs during encoding.

PyObject* PyUnicode_DecodeLatin1(const char *s, Py_ssize_t size, const char *errors)

Return value: New reference.

Create a Unicode object by decoding size bytes of the Latin-1 encoded string s. Return NULL if an exception was raised by the codec.

PyObject* PyUnicode_AsLatin1String(PyObject *unicode)

Return value: New reference.

Encode a Unicode object using Latin-1 and return the result as Python bytes object. Error handling is « strict ». Return NULL if an exception was raised by the codec.

PyObject* PyUnicode_EncodeLatin1(const Py_UNICODE *s, Py_ssize_t size, const char *errors)

Return value: New reference.

Encode the Py_UNICODE buffer of the given size using Latin-1 and return a Python bytes object. Return NULL if an exception was raised by the codec.

Deprecated since version 3.3, will be removed in version 4.0: Part of the old-style Py_UNICODE API; please migrate to using PyUnicode_AsLatin1String() or PyUnicode_AsEncodedString().

ASCII Codecs

These are the ASCII codec APIs. Only 7-bit ASCII data is accepted. All other codes generate errors.

PyObject* PyUnicode_DecodeASCII(const char *s, Py_ssize_t size, const char *errors)

Return value: New reference.

Create a Unicode object by decoding size bytes of the ASCII encoded string s. Return NULL if an exception was raised by the codec.

PyObject* PyUnicode_AsASCIIString(PyObject *unicode)

Return value: New reference.

Encode a Unicode object using ASCII and return the result as Python bytes object. Error handling is « strict ». Return NULL if an exception was raised by the codec.

PyObject* PyUnicode_EncodeASCII(const Py_UNICODE *s, Py_ssize_t size, const char *errors)

Return value: New reference.

Encode the Py_UNICODE buffer of the given size using ASCII and return a Python bytes object. Return NULL if an exception was raised by the codec.

Deprecated since version 3.3, will be removed in version 4.0: Part of the old-style Py_UNICODE API; please migrate to using PyUnicode_AsASCIIString() or PyUnicode_AsEncodedString().

Character Map Codecs

This codec is special in that it can be used to implement many different codecs (and this is in fact what was done to obtain most of the standard codecs included in the encodings package). The codec uses mapping to encode and decode characters. The mapping objects provided must support the __getitem__() mapping interface; dictionaries and sequences work well.

These are the mapping codec APIs:

PyObject* PyUnicode_DecodeCharmap(const char *data, Py_ssize_t size, PyObject *mapping, const char *errors)

Return value: New reference.

Create a Unicode object by decoding size bytes of the encoded string s using the given mapping object. Return NULL if an exception was raised by the codec.

If mapping is NULL, Latin-1 decoding will be applied. Else mapping must map bytes ordinals (integers in the range from 0 to 255) to Unicode strings, integers (which are then interpreted as Unicode ordinals) or None. Unmapped data bytes – ones which cause a LookupError, as well as ones which get mapped to None, 0xFFFE or '\ufffe', are treated as undefined mappings and cause an error.

PyObject* PyUnicode_AsCharmapString(PyObject *unicode, PyObject *mapping)

Return value: New reference.

Encode a Unicode object using the given mapping object and return the result as a bytes object. Error handling is « strict ». Return NULL if an exception was raised by the codec.

The mapping object must map Unicode ordinal integers to bytes objects, integers in the range from 0 to 255 or None. Unmapped character ordinals (ones which cause a LookupError) as well as mapped to None are treated as « undefined mapping » and cause an error.

PyObject* PyUnicode_EncodeCharmap(const Py_UNICODE *s, Py_ssize_t size, PyObject *mapping, const char *errors)

Return value: New reference.

Encode the Py_UNICODE buffer of the given size using the given mapping object and return the result as a bytes object. Return NULL if an exception was raised by the codec.

Deprecated since version 3.3, will be removed in version 4.0: Part of the old-style Py_UNICODE API; please migrate to using PyUnicode_AsCharmapString() or PyUnicode_AsEncodedString().

The following codec API is special in that maps Unicode to Unicode.

PyObject* PyUnicode_Translate(PyObject *unicode, PyObject *mapping, const char *errors)

Return value: New reference.

Translate a Unicode object using the given mapping object and return the resulting Unicode object. Return NULL if an exception was raised by the codec.

The mapping object must map Unicode ordinal integers to Unicode strings, integers (which are then interpreted as Unicode ordinals) or None (causing deletion of the character). Unmapped character ordinals (ones which cause a LookupError) are left untouched and are copied as-is.

PyObject* PyUnicode_TranslateCharmap(const Py_UNICODE *s, Py_ssize_t size, PyObject *mapping, const char *errors)

Return value: New reference.

Translate a Py_UNICODE buffer of the given size by applying a character mapping table to it and return the resulting Unicode object. Return NULL when an exception was raised by the codec.

Deprecated since version 3.3, will be removed in version 4.0: Part of the old-style Py_UNICODE API; please migrate to using PyUnicode_Translate(). or generic codec based API

MBCS codecs for Windows

These are the MBCS codec APIs. They are currently only available on Windows and use the Win32 MBCS converters to implement the conversions. Note that MBCS (or DBCS) is a class of encodings, not just one. The target encoding is defined by the user settings on the machine running the codec.

PyObject* PyUnicode_DecodeMBCS(const char *s, Py_ssize_t size, const char *errors)

Return value: New reference.

Create a Unicode object by decoding size bytes of the MBCS encoded string s. Return NULL if an exception was raised by the codec.

PyObject* PyUnicode_DecodeMBCSStateful(const char *s, Py_ssize_t size, const char *errors, Py_ssize_t *consumed)

If consumed is NULL, behave like PyUnicode_DecodeMBCS(). If consumed is not NULL, PyUnicode_DecodeMBCSStateful() will not decode trailing lead byte and the number of bytes that have been decoded will be stored in consumed.

PyObject* PyUnicode_AsMBCSString(PyObject *unicode)

Return value: New reference.

Encode a Unicode object using MBCS and return the result as Python bytes object. Error handling is « strict ». Return NULL if an exception was raised by the codec.

PyObject* PyUnicode_EncodeCodePage(int code_page, PyObject *unicode, const char *errors)

Encode the Unicode object using the specified code page and return a Python bytes object. Return NULL if an exception was raised by the codec. Use CP_ACP code page to get the MBCS encoder.

Nouveau dans la version 3.3.

PyObject* PyUnicode_EncodeMBCS(const Py_UNICODE *s, Py_ssize_t size, const char *errors)

Return value: New reference.

Encode the Py_UNICODE buffer of the given size using MBCS and return a Python bytes object. Return NULL if an exception was raised by the codec.

Deprecated since version 3.3, will be removed in version 4.0: Part of the old-style Py_UNICODE API; please migrate to using PyUnicode_AsMBCSString(), PyUnicode_EncodeCodePage() or PyUnicode_AsEncodedString().

Methods & Slots

Methods and Slot Functions

The following APIs are capable of handling Unicode objects and strings on input (we refer to them as strings in the descriptions) and return Unicode objects or integers as appropriate.

They all return NULL or -1 if an exception occurs.

PyObject* PyUnicode_Concat(PyObject *left, PyObject *right)

Return value: New reference.

Concat two strings giving a new Unicode string.

PyObject* PyUnicode_Split(PyObject *s, PyObject *sep, Py_ssize_t maxsplit)

Return value: New reference.

Split a string giving a list of Unicode strings. If sep is NULL, splitting will be done at all whitespace substrings. Otherwise, splits occur at the given separator. At most maxsplit splits will be done. If negative, no limit is set. Separators are not included in the resulting list.

PyObject* PyUnicode_Splitlines(PyObject *s, int keepend)

Return value: New reference.

Split a Unicode string at line breaks, returning a list of Unicode strings. CRLF is considered to be one line break. If keepend is 0, the Line break characters are not included in the resulting strings.

PyObject* PyUnicode_Translate(PyObject *str, PyObject *table, const char *errors)

Translate a string by applying a character mapping table to it and return the resulting Unicode object.

The mapping table must map Unicode ordinal integers to Unicode ordinal integers or None (causing deletion of the character).

Mapping tables need only provide the __getitem__() interface; dictionaries and sequences work well. Unmapped character ordinals (ones which cause a LookupError) are left untouched and are copied as-is.

errors has the usual meaning for codecs. It may be NULL which indicates to use the default error handling.

PyObject* PyUnicode_Join(PyObject *separator, PyObject *seq)

Return value: New reference.

Join a sequence of strings using the given separator and return the resulting Unicode string.

Py_ssize_t PyUnicode_Tailmatch(PyObject *str, PyObject *substr, Py_ssize_t start, Py_ssize_t end, int direction)

Return 1 if substr matches str[start:end] at the given tail end (direction == -1 means to do a prefix match, direction == 1 a suffix match), 0 otherwise. Return -1 if an error occurred.

Py_ssize_t PyUnicode_Find(PyObject *str, PyObject *substr, Py_ssize_t start, Py_ssize_t end, int direction)

Return the first position of substr in str[start:end] using the given direction (direction == 1 means to do a forward search, direction == -1 a backward search). The return value is the index of the first match; a value of -1 indicates that no match was found, and -2 indicates that an error occurred and an exception has been set.

Py_ssize_t PyUnicode_FindChar(PyObject *str, Py_UCS4 ch, Py_ssize_t start, Py_ssize_t end, int direction)

Return the first position of the character ch in str[start:end] using the given direction (direction == 1 means to do a forward search, direction == -1 a backward search). The return value is the index of the first match; a value of -1 indicates that no match was found, and -2 indicates that an error occurred and an exception has been set.

Nouveau dans la version 3.3.

Py_ssize_t PyUnicode_Count(PyObject *str, PyObject *substr, Py_ssize_t start, Py_ssize_t end)

Return the number of non-overlapping occurrences of substr in str[start:end]. Return -1 if an error occurred.

PyObject* PyUnicode_Replace(PyObject *str, PyObject *substr, PyObject *replstr, Py_ssize_t maxcount)

Return value: New reference.

Replace at most maxcount occurrences of substr in str with replstr and return the resulting Unicode object. maxcount == -1 means replace all occurrences.

int PyUnicode_Compare(PyObject *left, PyObject *right)

Compare two strings and return -1, 0, 1 for less than, equal, and greater than, respectively.

This function returns -1 upon failure, so one should call PyErr_Occurred() to check for errors.

int PyUnicode_CompareWithASCIIString(PyObject *uni, const char *string)

Compare a unicode object, uni, with string and return -1, 0, 1 for less than, equal, and greater than, respectively. It is best to pass only ASCII-encoded strings, but the function interprets the input string as ISO-8859-1 if it contains non-ASCII characters.

This function does not raise exceptions.

PyObject* PyUnicode_RichCompare(PyObject *left, PyObject *right, int op)

Rich compare two unicode strings and return one of the following:

NULL in case an exception was raised

Py_True or Py_False for successful comparisons

Py_NotImplemented in case the type combination is unknown

Possible values for op are Py_GT, Py_GE, Py_EQ, Py_NE, Py_LT, and Py_LE.

PyObject* PyUnicode_Format(PyObject *format, PyObject *args)

Return value: New reference.

Return a new string object from format and args; this is analogous to format % args.

int PyUnicode_Contains(PyObject *container, PyObject *element)

Check whether element is contained in container and return true or false accordingly.

element has to coerce to a one element Unicode string. -1 is returned if there was an error.

void PyUnicode_InternInPlace(PyObject **string)

Intern the argument *string in place. The argument must be the address of a pointer variable pointing to a Python unicode string object. If there is an existing interned string that is the same as *string, it sets *string to it (decrementing the reference count of the old string object and incrementing the reference count of the interned string object), otherwise it leaves *string alone and interns it (incrementing its reference count). (Clarification: even though there is a lot of talk about reference counts, think of this function as reference-count-neutral; you own the object after the call if and only if you owned it before the call.)

PyObject* PyUnicode_InternFromString(const char *v)

A combination of PyUnicode_FromString() and PyUnicode_InternInPlace(), returning either a new unicode string object that has been interned, or a new (« owned ») reference to an earlier interned string object with the same value.

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Tuple Objects

PyTupleObject

This subtype of PyObject represents a Python tuple object.

PyTypeObject PyTuple_Type

This instance of PyTypeObject represents the Python tuple type; it is the same object as tuple in the Python layer.

int PyTuple_Check(PyObject *p)

Return true if p is a tuple object or an instance of a subtype of the tuple type.

int PyTuple_CheckExact(PyObject *p)

Return true if p is a tuple object, but not an instance of a subtype of the tuple type.

PyObject* PyTuple_New(Py_ssize_t len)

Return value: New reference.

Return a new tuple object of size len, or NULL on failure.

PyObject* PyTuple_Pack(Py_ssize_t n, ...)

Return value: New reference.

Return a new tuple object of size n, or NULL on failure. The tuple values are initialized to the subsequent n C arguments pointing to Python objects. PyTuple_Pack(2, a, b) is equivalent to Py_BuildValue("(OO)", a, b).

Py_ssize_t PyTuple_Size(PyObject *p)

Take a pointer to a tuple object, and return the size of that tuple.

Py_ssize_t PyTuple_GET_SIZE(PyObject *p)

Return the size of the tuple p, which must be non-NULL and point to a tuple; no error checking is performed.

PyObject* PyTuple_GetItem(PyObject *p, Py_ssize_t pos)

Return value: Borrowed reference.

Return the object at position pos in the tuple pointed to by p. If pos is out of bounds, return NULL and sets an IndexError exception.

PyObject* PyTuple_GET_ITEM(PyObject *p, Py_ssize_t pos)

Return value: Borrowed reference.

Like PyTuple_GetItem(), but does no checking of its arguments.

PyObject* PyTuple_GetSlice(PyObject *p, Py_ssize_t low, Py_ssize_t high)

Return value: New reference.

Take a slice of the tuple pointed to by p from low to high and return it as a new tuple.

int PyTuple_SetItem(PyObject *p, Py_ssize_t pos, PyObject *o)

Insert a reference to object o at position pos of the tuple pointed to by p. Return 0 on success.

Note

This function « steals » a reference to o.

void PyTuple_SET_ITEM(PyObject *p, Py_ssize_t pos, PyObject *o)

Like PyTuple_SetItem(), but does no error checking, and should only be used to fill in brand new tuples.

Note

This function « steals » a reference to o.

int _PyTuple_Resize(PyObject **p, Py_ssize_t newsize)

Can be used to resize a tuple. newsize will be the new length of the tuple. Because tuples are supposed to be immutable, this should only be used if there is only one reference to the object. Do not use this if the tuple may already be known to some other part of the code. The tuple will always grow or shrink at the end. Think of this as destroying the old tuple and creating a new one, only more efficiently. Returns 0 on success. Client code should never assume that the resulting value of *p will be the same as before calling this function. If the object referenced by *p is replaced, the original *p is destroyed. On failure, returns -1 and sets *p to NULL, and raises MemoryError or SystemError.

int PyTuple_ClearFreeList()

Clear the free list. Return the total number of freed items.

Struct Sequence Objects

Struct sequence objects are the C equivalent of namedtuple() objects, i.e. a sequence whose items can also be accessed through attributes. To create a struct sequence, you first have to create a specific struct sequence type.

PyTypeObject* PyStructSequence_NewType(PyStructSequence_Desc *desc)

Create a new struct sequence type from the data in desc, described below. Instances of the resulting type can be created with PyStructSequence_New().

void PyStructSequence_InitType(PyTypeObject *type, PyStructSequence_Desc *desc)

Initializes a struct sequence type type from desc in place.

int PyStructSequence_InitType2(PyTypeObject *type, PyStructSequence_Desc *desc)

The same as PyStructSequence_InitType, but returns 0 on success and -1 on failure.

Nouveau dans la version 3.4.

PyStructSequence_Desc

Contains the meta information of a struct sequence type to create.

Field

Type C

Signification

name

char *

name of the struct sequence type

doc

char *

pointer to docstring for the type or NULL to omit

fields

PyStructSequence_Field *

pointer to NULL-terminated array with field names of the new type

n_in_sequence

int

number of fields visible to the Python side (if used as tuple)

PyStructSequence_Field

Describes a field of a struct sequence. As a struct sequence is modeled as a tuple, all fields are typed as PyObject*. The index in the fields array of the PyStructSequence_Desc determines which field of the struct sequence is described.

Field

Type C

Signification

name

char *

name for the field or NULL to end the list of named fields, set to PyStructSequence_UnnamedField to leave unnamed

doc

char *

field docstring or NULL to omit

char* PyStructSequence_UnnamedField

Special value for a field name to leave it unnamed.

PyObject* PyStructSequence_New(PyTypeObject *type)

Creates an instance of type, which must have been created with PyStructSequence_NewType().

PyObject* PyStructSequence_GetItem(PyObject *p, Py_ssize_t pos)

Return the object at position pos in the struct sequence pointed to by p. No bounds checking is performed.

PyObject* PyStructSequence_GET_ITEM(PyObject *p, Py_ssize_t pos)

Macro equivalent of PyStructSequence_GetItem().

void PyStructSequence_SetItem(PyObject *p, Py_ssize_t pos, PyObject *o)

Sets the field at index pos of the struct sequence p to value o. Like PyTuple_SET_ITEM(), this should only be used to fill in brand new instances.

Note

This function « steals » a reference to o.

void PyStructSequence_SET_ITEM(PyObject *p, Py_ssize_t *pos, PyObject *o)

Macro equivalent of PyStructSequence_SetItem().

Note

This function « steals » a reference to o.

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List Objects

PyListObject

This subtype of PyObject represents a Python list object.

PyTypeObject PyList_Type

This instance of PyTypeObject represents the Python list type. This is the same object as list in the Python layer.

int PyList_Check(PyObject *p)

Return true if p is a list object or an instance of a subtype of the list type.

int PyList_CheckExact(PyObject *p)

Return true if p is a list object, but not an instance of a subtype of the list type.

PyObject* PyList_New(Py_ssize_t len)

Return value: New reference.

Return a new list of length len on success, or NULL on failure.

Note

If len is greater than zero, the returned list object’s items are set to NULL. Thus you cannot use abstract API functions such as PySequence_SetItem() or expose the object to Python code before setting all items to a real object with PyList_SetItem().

Py_ssize_t PyList_Size(PyObject *list)

Return the length of the list object in list; this is equivalent to len(list) on a list object.

Py_ssize_t PyList_GET_SIZE(PyObject *list)

Macro form of PyList_Size() without error checking.

PyObject* PyList_GetItem(PyObject *list, Py_ssize_t index)

Return value: Borrowed reference.

Return the object at position index in the list pointed to by list. The position must be positive, indexing from the end of the list is not supported. If index is out of bounds, return NULL and set an IndexError exception.

PyObject* PyList_GET_ITEM(PyObject *list, Py_ssize_t i)

Return value: Borrowed reference.

Macro form of PyList_GetItem() without error checking.

int PyList_SetItem(PyObject *list, Py_ssize_t index, PyObject *item)

Set the item at index index in list to item. Return 0 on success or -1 on failure.

Note

This function « steals » a reference to item and discards a reference to an item already in the list at the affected position.

void PyList_SET_ITEM(PyObject *list, Py_ssize_t i, PyObject *o)

Macro form of PyList_SetItem() without error checking. This is normally only used to fill in new lists where there is no previous content.

Note

This macro « steals » a reference to item, and, unlike PyList_SetItem(), does not discard a reference to any item that is being replaced; any reference in list at position i will be leaked.

int PyList_Insert(PyObject *list, Py_ssize_t index, PyObject *item)

Insert the item item into list list in front of index index. Return 0 if successful; return -1 and set an exception if unsuccessful. Analogous to list.insert(index, item).

int PyList_Append(PyObject *list, PyObject *item)

Append the object item at the end of list list. Return 0 if successful; return -1 and set an exception if unsuccessful. Analogous to list.append(item).

PyObject* PyList_GetSlice(PyObject *list, Py_ssize_t low, Py_ssize_t high)

Return value: New reference.

Return a list of the objects in list containing the objects between low and high. Return NULL and set an exception if unsuccessful. Analogous to list[low:high]. Negative indices, as when slicing from Python, are not supported.

int PyList_SetSlice(PyObject *list, Py_ssize_t low, Py_ssize_t high, PyObject *itemlist)

Set the slice of list between low and high to the contents of itemlist. Analogous to list[low:high] = itemlist. The itemlist may be NULL, indicating the assignment of an empty list (slice deletion). Return 0 on success, -1 on failure. Negative indices, as when slicing from Python, are not supported.

int PyList_Sort(PyObject *list)

Sort the items of list in place. Return 0 on success, -1 on failure. This is equivalent to list.sort().

int PyList_Reverse(PyObject *list)

Reverse the items of list in place. Return 0 on success, -1 on failure. This is the equivalent of list.reverse().

PyObject* PyList_AsTuple(PyObject *list)

Return value: New reference.

Return a new tuple object containing the contents of list; equivalent to tuple(list).

int PyList_ClearFreeList()

Clear the free list. Return the total number of freed items.

Nouveau dans la version 3.3.

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Objets dictionnaires

PyDictObject

This subtype of PyObject represents a Python dictionary object.

PyTypeObject PyDict_Type

This instance of PyTypeObject represents the Python dictionary type. This is the same object as dict in the Python layer.

int PyDict_Check(PyObject *p)

Return true if p is a dict object or an instance of a subtype of the dict type.

int PyDict_CheckExact(PyObject *p)

Return true if p is a dict object, but not an instance of a subtype of the dict type.

PyObject* PyDict_New()

Return value: New reference.

Return a new empty dictionary, or NULL on failure.

PyObject* PyDictProxy_New(PyObject *mapping)

Return value: New reference.

Return a types.MappingProxyType object for a mapping which enforces read-only behavior. This is normally used to create a view to prevent modification of the dictionary for non-dynamic class types.

void PyDict_Clear(PyObject *p)

Empty an existing dictionary of all key-value pairs.

int PyDict_Contains(PyObject *p, PyObject *key)

Determine if dictionary p contains key. If an item in p is matches key, return 1, otherwise return 0. On error, return -1. This is equivalent to the Python expression key in p.

PyObject* PyDict_Copy(PyObject *p)

Return value: New reference.

Return a new dictionary that contains the same key-value pairs as p.

int PyDict_SetItem(PyObject *p, PyObject *key, PyObject *val)

Insert value into the dictionary p with a key of key. key must be hashable; if it isn’t, TypeError will be raised. Return 0 on success or -1 on failure.

int PyDict_SetItemString(PyObject *p, const char *key, PyObject *val)

Insert value into the dictionary p using key as a key. key should be a char*. The key object is created using PyUnicode_FromString(key). Return 0 on success or -1 on failure.

int PyDict_DelItem(PyObject *p, PyObject *key)

Remove the entry in dictionary p with key key. key must be hashable; if it isn’t, TypeError is raised. Return 0 on success or -1 on failure.

int PyDict_DelItemString(PyObject *p, const char *key)

Remove the entry in dictionary p which has a key specified by the string key. Return 0 on success or -1 on failure.

PyObject* PyDict_GetItem(PyObject *p, PyObject *key)

Return value: Borrowed reference.

Return the object from dictionary p which has a key key. Return NULL if the key key is not present, but without setting an exception.

Note that exceptions which occur while calling __hash__() and __eq__() methods will get suppressed. To get error reporting use PyDict_GetItemWithError() instead.

PyObject* PyDict_GetItemWithError(PyObject *p, PyObject *key)

Variant of PyDict_GetItem() that does not suppress exceptions. Return NULL with an exception set if an exception occurred. Return NULL without an exception set if the key wasn’t present.

PyObject* PyDict_GetItemString(PyObject *p, const char *key)

Return value: Borrowed reference.

This is the same as PyDict_GetItem(), but key is specified as a char*, rather than a PyObject*.

Note that exceptions which occur while calling __hash__() and __eq__() methods and creating a temporary string object will get suppressed. To get error reporting use PyDict_GetItemWithError() instead.

PyObject* PyDict_SetDefault(PyObject *p, PyObject *key, PyObject *default)

Return value: Borrowed reference.

This is the same as the Python-level dict.setdefault(). If present, it returns the value corresponding to key from the dictionary p. If the key is not in the dict, it is inserted with value defaultobj and defaultobj is returned. This function evaluates the hash function of key only once, instead of evaluating it independently for the lookup and the insertion.

Nouveau dans la version 3.4.

PyObject* PyDict_Items(PyObject *p)

Return value: New reference.

Return a PyListObject containing all the items from the dictionary.

PyObject* PyDict_Keys(PyObject *p)

Return value: New reference.

Return a PyListObject containing all the keys from the dictionary.

PyObject* PyDict_Values(PyObject *p)

Return value: New reference.

Return a PyListObject containing all the values from the dictionary p.

Py_ssize_t PyDict_Size(PyObject *p)

Return the number of items in the dictionary. This is equivalent to len(p) on a dictionary.

int PyDict_Next(PyObject *p, Py_ssize_t *ppos, PyObject **pkey, PyObject **pvalue)

Iterate over all key-value pairs in the dictionary p. The Py_ssize_t referred to by ppos must be initialized to 0 prior to the first call to this function to start the iteration; the function returns true for each pair in the dictionary, and false once all pairs have been reported. The parameters pkey and pvalue should either point to PyObject* variables that will be filled in with each key and value, respectively, or may be NULL. Any references returned through them are borrowed. ppos should not be altered during iteration. Its value represents offsets within the internal dictionary structure, and since the structure is sparse, the offsets are not consecutive.

Par exemple :

PyObject *key, *value;
Py_ssize_t pos = 0;

while (PyDict_Next(self->dict, &pos, &key, &value)) {
    /* do something interesting with the values... */
    ...
}

The dictionary p should not be mutated during iteration. It is safe to modify the values of the keys as you iterate over the dictionary, but only so long as the set of keys does not change. For example:

PyObject *key, *value;
Py_ssize_t pos = 0;

while (PyDict_Next(self->dict, &pos, &key, &value)) {
    long i = PyLong_AsLong(value);
    if (i == -1 && PyErr_Occurred()) {
        return -1;
    }
    PyObject *o = PyLong_FromLong(i + 1);
    if (o == NULL)
        return -1;
    if (PyDict_SetItem(self->dict, key, o) < 0) {
        Py_DECREF(o);
        return -1;
    }
    Py_DECREF(o);
}

int PyDict_Merge(PyObject *a, PyObject *b, int override)

Iterate over mapping object b adding key-value pairs to dictionary a. b may be a dictionary, or any object supporting PyMapping_Keys() and PyObject_GetItem(). If override is true, existing pairs in a will be replaced if a matching key is found in b, otherwise pairs will only be added if there is not a matching key in a. Return 0 on success or -1 if an exception was raised.

int PyDict_Update(PyObject *a, PyObject *b)

This is the same as PyDict_Merge(a, b, 1) in C, and is similar to a.update(b) in Python except that PyDict_Update() doesn’t fall back to the iterating over a sequence of key value pairs if the second argument has no « keys » attribute. Return 0 on success or -1 if an exception was raised.

int PyDict_MergeFromSeq2(PyObject *a, PyObject *seq2, int override)

Update or merge into dictionary a, from the key-value pairs in seq2. seq2 must be an iterable object producing iterable objects of length 2, viewed as key-value pairs. In case of duplicate keys, the last wins if override is true, else the first wins. Return 0 on success or -1 if an exception was raised. Equivalent Python (except for the return value):

def PyDict_MergeFromSeq2(a, seq2, override):
    for key, value in seq2:
        if override or key not in a:
            a[key] = value

int PyDict_ClearFreeList()

Clear the free list. Return the total number of freed items.

Nouveau dans la version 3.3.

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Set Objects

This section details the public API for set and frozenset objects. Any functionality not listed below is best accessed using the either the abstract object protocol (including PyObject_CallMethod(), PyObject_RichCompareBool(), PyObject_Hash(), PyObject_Repr(), PyObject_IsTrue(), PyObject_Print(), and PyObject_GetIter()) or the abstract number protocol (including PyNumber_And(), PyNumber_Subtract(), PyNumber_Or(), PyNumber_Xor(), PyNumber_InPlaceAnd(), PyNumber_InPlaceSubtract(), PyNumber_InPlaceOr(), and PyNumber_InPlaceXor()).

PySetObject

This subtype of PyObject is used to hold the internal data for both set and frozenset objects. It is like a PyDictObject in that it is a fixed size for small sets (much like tuple storage) and will point to a separate, variable sized block of memory for medium and large sized sets (much like list storage). None of the fields of this structure should be considered public and are subject to change. All access should be done through the documented API rather than by manipulating the values in the structure.

PyTypeObject PySet_Type

This is an instance of PyTypeObject representing the Python set type.

PyTypeObject PyFrozenSet_Type

This is an instance of PyTypeObject representing the Python frozenset type.

The following type check macros work on pointers to any Python object. Likewise, the constructor functions work with any iterable Python object.

int PySet_Check(PyObject *p)

Return true if p is a set object or an instance of a subtype.

int PyFrozenSet_Check(PyObject *p)

Return true if p is a frozenset object or an instance of a subtype.

int PyAnySet_Check(PyObject *p)

Return true if p is a set object, a frozenset object, or an instance of a subtype.

int PyAnySet_CheckExact(PyObject *p)

Return true if p is a set object or a frozenset object but not an instance of a subtype.

int PyFrozenSet_CheckExact(PyObject *p)

Return true if p is a frozenset object but not an instance of a subtype.

PyObject* PySet_New(PyObject *iterable)

Return value: New reference.

Return a new set containing objects returned by the iterable. The iterable may be NULL to create a new empty set. Return the new set on success or NULL on failure. Raise TypeError if iterable is not actually iterable. The constructor is also useful for copying a set (c=set(s)).

PyObject* PyFrozenSet_New(PyObject *iterable)

Return value: New reference.

Return a new frozenset containing objects returned by the iterable. The iterable may be NULL to create a new empty frozenset. Return the new set on success or NULL on failure. Raise TypeError if iterable is not actually iterable.

The following functions and macros are available for instances of set or frozenset or instances of their subtypes.

Py_ssize_t PySet_Size(PyObject *anyset)

Return the length of a set or frozenset object. Equivalent to len(anyset). Raises a PyExc_SystemError if anyset is not a set, frozenset, or an instance of a subtype.

Py_ssize_t PySet_GET_SIZE(PyObject *anyset)

Macro form of PySet_Size() without error checking.

int PySet_Contains(PyObject *anyset, PyObject *key)

Return 1 if found, 0 if not found, and -1 if an error is encountered. Unlike the Python __contains__() method, this function does not automatically convert unhashable sets into temporary frozensets. Raise a TypeError if the key is unhashable. Raise PyExc_SystemError if anyset is not a set, frozenset, or an instance of a subtype.

int PySet_Add(PyObject *set, PyObject *key)

Add key to a set instance. Also works with frozenset instances (like PyTuple_SetItem() it can be used to fill-in the values of brand new frozensets before they are exposed to other code). Return 0 on success or -1 on failure. Raise a TypeError if the key is unhashable. Raise a MemoryError if there is no room to grow. Raise a SystemError if set is not an instance of set or its subtype.

The following functions are available for instances of set or its subtypes but not for instances of frozenset or its subtypes.

int PySet_Discard(PyObject *set, PyObject *key)

Return 1 if found and removed, 0 if not found (no action taken), and -1 if an error is encountered. Does not raise KeyError for missing keys. Raise a TypeError if the key is unhashable. Unlike the Python discard() method, this function does not automatically convert unhashable sets into temporary frozensets. Raise PyExc_SystemError if set is not an instance of set or its subtype.

PyObject* PySet_Pop(PyObject *set)

Return value: New reference.

Return a new reference to an arbitrary object in the set, and removes the object from the set. Return NULL on failure. Raise KeyError if the set is empty. Raise a SystemError if set is not an instance of set or its subtype.

int PySet_Clear(PyObject *set)

Empty an existing set of all elements.

int PySet_ClearFreeList()

Clear the free list. Return the total number of freed items.

Nouveau dans la version 3.3.

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Objets fonctions

There are a few functions specific to Python functions.

PyFunctionObject

The C structure used for functions.

PyTypeObject PyFunction_Type

This is an instance of PyTypeObject and represents the Python function type. It is exposed to Python programmers as types.FunctionType.

int PyFunction_Check(PyObject *o)

Return true if o is a function object (has type PyFunction_Type). The parameter must not be NULL.

PyObject* PyFunction_New(PyObject *code, PyObject *globals)

Return value: New reference.

Return a new function object associated with the code object code. globals must be a dictionary with the global variables accessible to the function.

The function’s docstring and name are retrieved from the code object. __module__ is retrieved from globals. The argument defaults, annotations and closure are set to NULL. __qualname__ is set to the same value as the function’s name.

PyObject* PyFunction_NewWithQualName(PyObject *code, PyObject *globals, PyObject *qualname)

Return value: New reference.

As PyFunction_New(), but also allows setting the function object’s __qualname__ attribute. qualname should be a unicode object or NULL; if NULL, the __qualname__ attribute is set to the same value as its __name__ attribute.

Nouveau dans la version 3.3.

PyObject* PyFunction_GetCode(PyObject *op)

Return value: Borrowed reference.

Return the code object associated with the function object op.

PyObject* PyFunction_GetGlobals(PyObject *op)

Return value: Borrowed reference.

Return the globals dictionary associated with the function object op.

PyObject* PyFunction_GetModule(PyObject *op)

Return value: Borrowed reference.

Return the __module__ attribute of the function object op. This is normally a string containing the module name, but can be set to any other object by Python code.

PyObject* PyFunction_GetDefaults(PyObject *op)

Return value: Borrowed reference.

Return the argument default values of the function object op. This can be a tuple of arguments or NULL.

int PyFunction_SetDefaults(PyObject *op, PyObject *defaults)

Set the argument default values for the function object op. defaults must be Py_None or a tuple.

Raises SystemError and returns -1 on failure.

PyObject* PyFunction_GetClosure(PyObject *op)

Return value: Borrowed reference.

Return the closure associated with the function object op. This can be NULL or a tuple of cell objects.

int PyFunction_SetClosure(PyObject *op, PyObject *closure)

Set the closure associated with the function object op. closure must be Py_None or a tuple of cell objects.

Raises SystemError and returns -1 on failure.

PyObject *PyFunction_GetAnnotations(PyObject *op)

Return the annotations of the function object op. This can be a mutable dictionary or NULL.

int PyFunction_SetAnnotations(PyObject *op, PyObject *annotations)

Set the annotations for the function object op. annotations must be a dictionary or Py_None.

Raises SystemError and returns -1 on failure.

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Instance Method Objects

An instance method is a wrapper for a PyCFunction and the new way to bind a PyCFunction to a class object. It replaces the former call PyMethod_New(func, NULL, class).

PyTypeObject PyInstanceMethod_Type

This instance of PyTypeObject represents the Python instance method type. It is not exposed to Python programs.

int PyInstanceMethod_Check(PyObject *o)

Return true if o is an instance method object (has type PyInstanceMethod_Type). The parameter must not be NULL.

PyObject* PyInstanceMethod_New(PyObject *func)

Return a new instance method object, with func being any callable object func is the function that will be called when the instance method is called.

PyObject* PyInstanceMethod_Function(PyObject *im)

Return the function object associated with the instance method im.

PyObject* PyInstanceMethod_GET_FUNCTION(PyObject *im)

Macro version of PyInstanceMethod_Function() which avoids error checking.

Objets méthode

Methods are bound function objects. Methods are always bound to an instance of a user-defined class. Unbound methods (methods bound to a class object) are no longer available.

PyTypeObject PyMethod_Type

This instance of PyTypeObject represents the Python method type. This is exposed to Python programs as types.MethodType.

int PyMethod_Check(PyObject *o)

Return true if o is a method object (has type PyMethod_Type). The parameter must not be NULL.

PyObject* PyMethod_New(PyObject *func, PyObject *self)

Return value: New reference.

Return a new method object, with func being any callable object and self the instance the method should be bound. func is the function that will be called when the method is called. self must not be NULL.

PyObject* PyMethod_Function(PyObject *meth)

Return value: Borrowed reference.

Return the function object associated with the method meth.

PyObject* PyMethod_GET_FUNCTION(PyObject *meth)

Return value: Borrowed reference.

Macro version of PyMethod_Function() which avoids error checking.

PyObject* PyMethod_Self(PyObject *meth)

Return value: Borrowed reference.

Return the instance associated with the method meth.

PyObject* PyMethod_GET_SELF(PyObject *meth)

Return value: Borrowed reference.

Macro version of PyMethod_Self() which avoids error checking.

int PyMethod_ClearFreeList()

Clear the free list. Return the total number of freed items.

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Objets Cellules

Les objets « Cellules » (cell en anglais) sont utilisés pour implémenter des variables référencées dans de multiples environnements. Pour chacune de ces variables, un objet cellule est créé pour stocker sa valeur ; les variables locales de chaque pile d’exécution qui référence cette valeur contiennent une référence sur les cellules des autres environnements qui utilisent aussi cette variable. Quand la valeur est accédée, la valeur de la cellule est utilisée, au lei de celle de l’objet cellule proprement dit. Ce dé-référencement de l’objet cellule requiert l’intervention du bytecode généré ; il n’est pas automatiquement dé-référencé quand il est accédé. Il est plausible que les objets cellules ne soit utilisés ailleurs.

PyCellObject

Structure C utilisée pour les objets cellules.

PyTypeObject PyCell_Type

Type objet correspondant aux objets cellules.

int PyCell_Check(ob)

Renvoie True si ob est un objet cellule ; ob ne doit pas être à NULL.

PyObject* PyCell_New(PyObject *ob)

Return value: New reference.

Crée et retourne un nouvel objet cellule contenant la valeur ob. Le paramètre peut être mis à NULL.

PyObject* PyCell_Get(PyObject *cell)

Return value: New reference.

Renvoie le contenu de la cellule cell.

PyObject* PyCell_GET(PyObject *cell)

Return value: Borrowed reference.

Renvoie le contenu de la cellule cell, mais sans vérifier si cell est non NULL et sans vérifier si c’est un objet cellule.

int PyCell_Set(PyObject *cell, PyObject *value)

Définit le contenu de l’objet cellule à value. Cela libère la référence à toute valeur de la cellule. value peut être fixé à NULL. cell ne doit pas être NULL ; si ce n’est pas un objet cellule, -1 est renvoyé. Si c’est un objet cellule, renvoie 0.

void PyCell_SET(PyObject *cell, PyObject *value)

Définit la valeur de l’objet cellule à value. Pas de comptage de références n’est ajusté et il n’y” a pas de contrôle effectué pour vérifier la sûreté ; cell doit être à non NULL et doit être un objet cellule.

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Objets code

Les objets Code sont spécifiques à l’implémentation bas niveau de CPython. Chacun d’eux représente une partie de code exécutable, qui n’a pas encore été lié dans une fonction.

PyCodeObject

La structure C utilisée pour décrire les objets Code. Les attributs de cette structure sont sujets à changer à tout moment.

PyTypeObject PyCode_Type

C’est une instance de PyTypeObject représentant le type Python code.

int PyCode_Check(PyObject *co)

Renvoie vrai si co est un objet code.

int PyCode_GetNumFree(PyCodeObject *co)

Renvoie le nombre de variables libres dans co.

PyCodeObject* PyCode_New(int argcount, int kwonlyargcount, int nlocals, int stacksize, int flags, PyObject *code, PyObject *consts, PyObject *names, PyObject *varnames, PyObject *freevars, PyObject *cellvars, PyObject *filename, PyObject *name, int firstlineno, PyObject *lnotab)

Renvoie un nouvel objet code. Si vous avez besoin d’un objet code factice pour créer une frame, utilisez plutôt PyCode_NewEmpty(). Appeler PyCode_New() peut vous lier directement à une version spécifique de Python, le bytecode étant sujet à modifications.

PyCodeObject* PyCode_NewEmpty(const char *filename, const char *funcname, int firstlineno)

Renvoie un nouvel objet code avec le nom de fichier, le nom de fonction, et le numéro de première ligne donnés. Il n’est pas permis d’utiliser exec() ou eval() sur l’objet renvoyé.

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Objets fichiers

Ces API sont une émulation minimale de l’API C Python 2 pour les objets fichier natifs, qui reposaient sur la gestion des entrées-sorties avec tampon (FILE*) de la bibliothèque standard C. En Python 3, les fichiers et les flux utilisent le nouveau module io, qui définit plusieurs couches au dessus des entrées/sorties bas niveau sans tampon du système d’exploitation. Les fonctions définies ci-dessous, écrites en C, encapsulent ces nouvelles APi pour les rendre plus faciles d’utilisation et sont majoritairement pensées pour signaler des erreurs internes dans l’interpréteur ; il est conseillé au code tiers d’utiliser les API de io à la place.

PyFile_FromFd(int fd, const char *name, const char *mode, int buffering, const char *encoding, const char *errors, const char *newline, int closefd)

Crée un objet fichier Python à partir du descripteur d’un fichier déjà ouvert fd. Les arguments name, encoding, errors et newline peuvent être NULL pour utiliser ceux par défaut ; buffering peut être -1 pour utiliser celui par défaut ; name est ignoré et gardé pour la rétro-compatibilité. Renvoie NULL en cas d’échec. Pour une description plus détaillée des arguments, merci de vous référer à la documentation de fonction io.open().

Avertissement

Étant donné que les flux de données Python possèdent leur propre couche de tampon, les mélanger avec des descripteurs de fichiers du niveau du système d’exploitation peut produire des erreurs (comme par exemple un ordre des données inattendu).

Modifié dans la version 3.2: ignore l’attribut name

int PyObject_AsFileDescriptor(PyObject *p)

Renvoie un descripteur de fichier associé avec p comme un int. Si l’objet est un entier, sa valeur est renvoyée. Sinon, la méthode fileno() de l’objet est appelée si elle existe; la méthode doit renvoyer un entier, qui est renvoyé en tant que valeur du descripteur. Affecte une exception et renvoie -1 lors d’un échec.

PyObject* PyFile_GetLine(PyObject *p, int n)

Return value: New reference.

Cette fonction, équivalente à p.readline([n]), lit une ligne de l’objet p. p peut être un objet fichier ou n’importe quel objet qui possède une méthode readline(). Si n vaut 0, une seule ligne est lue, indépendamment de la taille de la ligne. Si n est plus grand que 0, un maximum de n octets seront lus en provenance du fichier ; une ligne partielle peut être renvoyée. Dans les deux cas, une chaîne de caractères vide est renvoyée si la fin du fichier est atteinte immédiatement. Cependant, si n est plus petit que 0, une ligne est lue indépendamment de sa taille, mais EOFError est levée si la fin du fichier est atteinte immédiatement.

int PyFile_WriteObject(PyObject *obj, PyObject *p, int flags)

Écrit l’objet obj dans l’objet fichier p. La seule option gérée pour flags est Py_PRINT_RAW ; si défini, l’attribut str() de l’objet est écrit à la place de l’attribut repr(). Retourne 0 en cas de succès ou -1 en cas échec ; l’exception appropriée sera levée.

int PyFile_WriteString(const char *s, PyObject *p)

Écrit la chaîne de caractères s dans l’objet fichier p. Retourne 0 en cas de succès ou -1 en cas d’échec ; l’exception appropriée sera mise en place.

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Module Objects

PyTypeObject PyModule_Type

This instance of PyTypeObject represents the Python module type. This is exposed to Python programs as types.ModuleType.

int PyModule_Check(PyObject *p)

Return true if p is a module object, or a subtype of a module object.

int PyModule_CheckExact(PyObject *p)

Return true if p is a module object, but not a subtype of PyModule_Type.

PyObject* PyModule_NewObject(PyObject *name)

Return a new module object with the __name__ attribute set to name. The module’s __name__, __doc__, __package__, and __loader__ attributes are filled in (all but __name__ are set to None); the caller is responsible for providing a __file__ attribute.

Nouveau dans la version 3.3.

Modifié dans la version 3.4: __package__ and __loader__ are set to None.

PyObject* PyModule_New(const char *name)

Return value: New reference.

Similar to PyModule_NewObject(), but the name is a UTF-8 encoded string instead of a Unicode object.

PyObject* PyModule_GetDict(PyObject *module)

Return value: Borrowed reference.

Return the dictionary object that implements module’s namespace; this object is the same as the __dict__ attribute of the module object. If module is not a module object (or a subtype of a module object), SystemError is raised and NULL is returned.

It is recommended extensions use other PyModule_*() and PyObject_*() functions rather than directly manipulate a module’s __dict__.

PyObject* PyModule_GetNameObject(PyObject *module)

Return module’s __name__ value. If the module does not provide one, or if it is not a string, SystemError is raised and NULL is returned.

Nouveau dans la version 3.3.

char* PyModule_GetName(PyObject *module)

Similar to PyModule_GetNameObject() but return the name encoded to 'utf-8'.

void* PyModule_GetState(PyObject *module)

Return the « state » of the module, that is, a pointer to the block of memory allocated at module creation time, or NULL. See PyModuleDef.m_size.

PyModuleDef* PyModule_GetDef(PyObject *module)

Return a pointer to the PyModuleDef struct from which the module was created, or NULL if the module wasn’t created from a definition.

PyObject* PyModule_GetFilenameObject(PyObject *module)

Return the name of the file from which module was loaded using module’s __file__ attribute. If this is not defined, or if it is not a unicode string, raise SystemError and return NULL; otherwise return a reference to a Unicode object.

Nouveau dans la version 3.2.

char* PyModule_GetFilename(PyObject *module)

Similar to PyModule_GetFilenameObject() but return the filename encoded to “utf-8”.

Obsolète depuis la version 3.2: PyModule_GetFilename() raises UnicodeEncodeError on unencodable filenames, use PyModule_GetFilenameObject() instead.

Initializing C modules

Modules objects are usually created from extension modules (shared libraries which export an initialization function), or compiled-in modules (where the initialization function is added using PyImport_AppendInittab()). See Construire des extensions C et C++ or Étendre un Python intégré for details.

The initialization function can either pass a module definition instance to PyModule_Create(), and return the resulting module object, or request « multi-phase initialization » by returning the definition struct itself.

PyModuleDef

The module definition struct, which holds all information needed to create a module object. There is usually only one statically initialized variable of this type for each module.

PyModuleDef_Base m_base

Always initialize this member to PyModuleDef_HEAD_INIT.

char* m_name

Name for the new module.

char* m_doc

Docstring for the module; usually a docstring variable created with PyDoc_STRVAR() is used.

Py_ssize_t m_size

Module state may be kept in a per-module memory area that can be retrieved with PyModule_GetState(), rather than in static globals. This makes modules safe for use in multiple sub-interpreters.

This memory area is allocated based on m_size on module creation, and freed when the module object is deallocated, after the m_free function has been called, if present.

Setting m_size to -1 means that the module does not support sub-interpreters, because it has global state.

Setting it to a non-negative value means that the module can be re-initialized and specifies the additional amount of memory it requires for its state. Non-negative m_size is required for multi-phase initialization.

See PEP 3121 [https://www.python.org/dev/peps/pep-3121] for more details.

PyMethodDef* m_methods

A pointer to a table of module-level functions, described by PyMethodDef values. Can be NULL if no functions are present.

PyModuleDef_Slot* m_slots

An array of slot definitions for multi-phase initialization, terminated by a {0, NULL} entry. When using single-phase initialization, m_slots must be NULL.

Modifié dans la version 3.5: Prior to version 3.5, this member was always set to NULL, and was defined as:

inquiry m_reload

traverseproc m_traverse

A traversal function to call during GC traversal of the module object, or NULL if not needed. This function may be called before module state is allocated (PyModule_GetState() may return NULL), and before the Py_mod_exec function is executed.

inquiry m_clear

A clear function to call during GC clearing of the module object, or NULL if not needed. This function may be called before module state is allocated (PyModule_GetState() may return NULL), and before the Py_mod_exec function is executed.

freefunc m_free

A function to call during deallocation of the module object, or NULL if not needed. This function may be called before module state is allocated (PyModule_GetState() may return NULL), and before the Py_mod_exec function is executed.

Single-phase initialization

The module initialization function may create and return the module object directly. This is referred to as « single-phase initialization », and uses one of the following two module creation functions:

PyObject* PyModule_Create(PyModuleDef *def)

Create a new module object, given the definition in def. This behaves like PyModule_Create2() with module_api_version set to PYTHON_API_VERSION.

PyObject* PyModule_Create2(PyModuleDef *def, int module_api_version)

Create a new module object, given the definition in def, assuming the API version module_api_version. If that version does not match the version of the running interpreter, a RuntimeWarning is emitted.

Note

Most uses of this function should be using PyModule_Create() instead; only use this if you are sure you need it.

Before it is returned from in the initialization function, the resulting module object is typically populated using functions like PyModule_AddObject().

Multi-phase initialization

An alternate way to specify extensions is to request « multi-phase initialization ». Extension modules created this way behave more like Python modules: the initialization is split between the creation phase, when the module object is created, and the execution phase, when it is populated. The distinction is similar to the __new__() and __init__() methods of classes.

Unlike modules created using single-phase initialization, these modules are not singletons: if the sys.modules entry is removed and the module is re-imported, a new module object is created, and the old module is subject to normal garbage collection – as with Python modules. By default, multiple modules created from the same definition should be independent: changes to one should not affect the others. This means that all state should be specific to the module object (using e.g. using PyModule_GetState()), or its contents (such as the module’s __dict__ or individual classes created with PyType_FromSpec()).

All modules created using multi-phase initialization are expected to support sub-interpreters. Making sure multiple modules are independent is typically enough to achieve this.

To request multi-phase initialization, the initialization function (PyInit_modulename) returns a PyModuleDef instance with non-empty m_slots. Before it is returned, the PyModuleDef instance must be initialized with the following function:

PyObject* PyModuleDef_Init(PyModuleDef *def)

Ensures a module definition is a properly initialized Python object that correctly reports its type and reference count.

Returns def cast to PyObject*, or NULL if an error occurred.

Nouveau dans la version 3.5.

The m_slots member of the module definition must point to an array of PyModuleDef_Slot structures:

PyModuleDef_Slot

int slot

A slot ID, chosen from the available values explained below.

void* value

Value of the slot, whose meaning depends on the slot ID.

Nouveau dans la version 3.5.

The m_slots array must be terminated by a slot with id 0.

The available slot types are:

Py_mod_create

Specifies a function that is called to create the module object itself. The value pointer of this slot must point to a function of the signature:

PyObject* create_module(PyObject *spec, PyModuleDef *def)

The function receives a ModuleSpec instance, as defined in PEP 451 [https://www.python.org/dev/peps/pep-0451], and the module definition. It should return a new module object, or set an error and return NULL.

This function should be kept minimal. In particular, it should not call arbitrary Python code, as trying to import the same module again may result in an infinite loop.

Multiple Py_mod_create slots may not be specified in one module definition.

If Py_mod_create is not specified, the import machinery will create a normal module object using PyModule_New(). The name is taken from spec, not the definition, to allow extension modules to dynamically adjust to their place in the module hierarchy and be imported under different names through symlinks, all while sharing a single module definition.

There is no requirement for the returned object to be an instance of PyModule_Type. Any type can be used, as long as it supports setting and getting import-related attributes. However, only PyModule_Type instances may be returned if the PyModuleDef has non-NULL m_traverse, m_clear, m_free; non-zero m_size; or slots other than Py_mod_create.

Py_mod_exec

Specifies a function that is called to execute the module. This is equivalent to executing the code of a Python module: typically, this function adds classes and constants to the module. The signature of the function is:

int exec_module(PyObject* module)

If multiple Py_mod_exec slots are specified, they are processed in the order they appear in the m_slots array.

See PEP 489 [https://www.python.org/dev/peps/pep-0489] for more details on multi-phase initialization.

Low-level module creation functions

The following functions are called under the hood when using multi-phase initialization. They can be used directly, for example when creating module objects dynamically. Note that both PyModule_FromDefAndSpec and PyModule_ExecDef must be called to fully initialize a module.

PyObject * PyModule_FromDefAndSpec(PyModuleDef *def, PyObject *spec)

Create a new module object, given the definition in module and the ModuleSpec spec. This behaves like PyModule_FromDefAndSpec2() with module_api_version set to PYTHON_API_VERSION.

Nouveau dans la version 3.5.

PyObject * PyModule_FromDefAndSpec2(PyModuleDef *def, PyObject *spec, int module_api_version)

Create a new module object, given the definition in module and the ModuleSpec spec, assuming the API version module_api_version. If that version does not match the version of the running interpreter, a RuntimeWarning is emitted.

Note

Most uses of this function should be using PyModule_FromDefAndSpec() instead; only use this if you are sure you need it.

Nouveau dans la version 3.5.

int PyModule_ExecDef(PyObject *module, PyModuleDef *def)

Process any execution slots (Py_mod_exec) given in def.

Nouveau dans la version 3.5.

int PyModule_SetDocString(PyObject *module, const char *docstring)

Set the docstring for module to docstring. This function is called automatically when creating a module from PyModuleDef, using either PyModule_Create or PyModule_FromDefAndSpec.

Nouveau dans la version 3.5.

int PyModule_AddFunctions(PyObject *module, PyMethodDef *functions)

Add the functions from the NULL terminated functions array to module. Refer to the PyMethodDef documentation for details on individual entries (due to the lack of a shared module namespace, module level « functions » implemented in C typically receive the module as their first parameter, making them similar to instance methods on Python classes). This function is called automatically when creating a module from PyModuleDef, using either PyModule_Create or PyModule_FromDefAndSpec.

Nouveau dans la version 3.5.

Support functions

The module initialization function (if using single phase initialization) or a function called from a module execution slot (if using multi-phase initialization), can use the following functions to help initialize the module state:

int PyModule_AddObject(PyObject *module, const char *name, PyObject *value)

Add an object to module as name. This is a convenience function which can be used from the module’s initialization function. This steals a reference to value. Return -1 on error, 0 on success.

int PyModule_AddIntConstant(PyObject *module, const char *name, long value)

Add an integer constant to module as name. This convenience function can be used from the module’s initialization function. Return -1 on error, 0 on success.

int PyModule_AddStringConstant(PyObject *module, const char *name, const char *value)

Add a string constant to module as name. This convenience function can be used from the module’s initialization function. The string value must be NULL-terminated. Return -1 on error, 0 on success.

int PyModule_AddIntMacro(PyObject *module, macro)

Add an int constant to module. The name and the value are taken from macro. For example PyModule_AddIntMacro(module, AF_INET) adds the int constant AF_INET with the value of AF_INET to module. Return -1 on error, 0 on success.

int PyModule_AddStringMacro(PyObject *module, macro)

Add a string constant to module.

Module lookup

Single-phase initialization creates singleton modules that can be looked up in the context of the current interpreter. This allows the module object to be retrieved later with only a reference to the module definition.

These functions will not work on modules created using multi-phase initialization, since multiple such modules can be created from a single definition.

PyObject* PyState_FindModule(PyModuleDef *def)

Returns the module object that was created from def for the current interpreter. This method requires that the module object has been attached to the interpreter state with PyState_AddModule() beforehand. In case the corresponding module object is not found or has not been attached to the interpreter state yet, it returns NULL.

int PyState_AddModule(PyObject *module, PyModuleDef *def)

Attaches the module object passed to the function to the interpreter state. This allows the module object to be accessible via PyState_FindModule().

Only effective on modules created using single-phase initialization.

Nouveau dans la version 3.3.

int PyState_RemoveModule(PyModuleDef *def)

Removes the module object created from def from the interpreter state.

Nouveau dans la version 3.3.

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Itérateurs

Python fournit deux itérateurs génériques. Le premier est un itérateur de séquence, il fonctionne avec n’importe quelle séquence gérant la méthode __getitem__(). Le second fonctionne avec un objet appelable et une valeur sentinelle, il appelle l’appelable pour obtenir chaque élément de la séquence, et l’itération se termine lorsque la sentinelle est reçue.

PyTypeObject PySeqIter_Type

Type des itérateurs renvoyés par les fonctions PySeqIter_New() et la forme à un argument de la fonction native iter() pour les séquences natives.

int PySeqIter_Check(op)

Renvoie vrai si op est de type PySeqIter_Type.

PyObject* PySeqIter_New(PyObject *seq)

Return value: New reference.

Renvoie un itérateur sur la séquence seq. L’itération prend fin lorsque la séquence lève IndexError lors d’une tentative d’accès.

PyTypeObject PyCallIter_Type

Type de l’itérateur renvoyé par les fonctions PyCallIter_New() et iter() à deux arguments.

int PyCallIter_Check(op)

Renvoie vrai si op est de type PyCallIter_Type.

PyObject* PyCallIter_New(PyObject *callable, PyObject *sentinel)

Return value: New reference.

Renvoie un nouvel itérateur. Le premier paramètre, callable, peut être n’importe quel objet Python appelable sans aucun paramètre ; chaque appel doit renvoyer l’élément suivant de l’itération. Lorsque callable renvoie une valeur égale à sentinel, l’itération prend fin.

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Les descripteurs

Les « Descripteurs » sont des objets décrivant des attributs pour un objet. Ils se trouvent dans le dictionnaire du type de l’objet.

PyTypeObject PyProperty_Type

L’objet type des descripteurs natifs.

PyObject* PyDescr_NewGetSet(PyTypeObject *type, struct PyGetSetDef *getset)

Return value: New reference.

PyObject* PyDescr_NewMember(PyTypeObject *type, struct PyMemberDef *meth)

Return value: New reference.

PyObject* PyDescr_NewMethod(PyTypeObject *type, struct PyMethodDef *meth)

Return value: New reference.

PyObject* PyDescr_NewWrapper(PyTypeObject *type, struct wrapperbase *wrapper, void *wrapped)

Return value: New reference.

PyObject* PyDescr_NewClassMethod(PyTypeObject *type, PyMethodDef *method)

Return value: New reference.

int PyDescr_IsData(PyObject *descr)

Renvoie vrai si le descripteur descr décrit un attribut de donnée, ou faux s’il décrit une méthode. descr doit être un objet descripteur. Il n’y a pas de vérification d’erreur.

PyObject* PyWrapper_New(PyObject *, PyObject *)

Return value: New reference.

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Slice Objects

PyTypeObject PySlice_Type

The type object for slice objects. This is the same as slice in the Python layer.

int PySlice_Check(PyObject *ob)

Return true if ob is a slice object; ob must not be NULL.

PyObject* PySlice_New(PyObject *start, PyObject *stop, PyObject *step)

Return value: New reference.

Return a new slice object with the given values. The start, stop, and step parameters are used as the values of the slice object attributes of the same names. Any of the values may be NULL, in which case the None will be used for the corresponding attribute. Return NULL if the new object could not be allocated.

int PySlice_GetIndices(PyObject *slice, Py_ssize_t length, Py_ssize_t *start, Py_ssize_t *stop, Py_ssize_t *step)

Retrieve the start, stop and step indices from the slice object slice, assuming a sequence of length length. Treats indices greater than length as errors.

Returns 0 on success and -1 on error with no exception set (unless one of the indices was not None and failed to be converted to an integer, in which case -1 is returned with an exception set).

You probably do not want to use this function.

Modifié dans la version 3.2: The parameter type for the slice parameter was PySliceObject* before.

int PySlice_GetIndicesEx(PyObject *slice, Py_ssize_t length, Py_ssize_t *start, Py_ssize_t *stop, Py_ssize_t *step, Py_ssize_t *slicelength)

Usable replacement for PySlice_GetIndices(). Retrieve the start, stop, and step indices from the slice object slice assuming a sequence of length length, and store the length of the slice in slicelength. Out of bounds indices are clipped in a manner consistent with the handling of normal slices.

Returns 0 on success and -1 on error with exception set.

Modifié dans la version 3.2: The parameter type for the slice parameter was PySliceObject* before.

Ellipsis Object

PyObject *Py_Ellipsis

The Python Ellipsis object. This object has no methods. It needs to be treated just like any other object with respect to reference counts. Like Py_None it is a singleton object.

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Objets de type MemoryView

A memoryview object exposes the C level buffer interface as a Python object which can then be passed around like any other object.

PyObject *PyMemoryView_FromObject(PyObject *obj)

Create a memoryview object from an object that provides the buffer interface. If obj supports writable buffer exports, the memoryview object will be read/write, otherwise it may be either read-only or read/write at the discretion of the exporter.

PyObject *PyMemoryView_FromMemory(char *mem, Py_ssize_t size, int flags)

Create a memoryview object using mem as the underlying buffer. flags can be one of PyBUF_READ or PyBUF_WRITE.

Nouveau dans la version 3.3.

PyObject *PyMemoryView_FromBuffer(Py_buffer *view)

Create a memoryview object wrapping the given buffer structure view. For simple byte buffers, PyMemoryView_FromMemory() is the preferred function.

PyObject *PyMemoryView_GetContiguous(PyObject *obj, int buffertype, char order)

Create a memoryview object to a contiguous chunk of memory (in either “C” or “F’ortran order) from an object that defines the buffer interface. If memory is contiguous, the memoryview object points to the original memory. Otherwise, a copy is made and the memoryview points to a new bytes object.

int PyMemoryView_Check(PyObject *obj)

Return true if the object obj is a memoryview object. It is not currently allowed to create subclasses of memoryview.

Py_buffer *PyMemoryView_GET_BUFFER(PyObject *mview)

Return a pointer to the memoryview’s private copy of the exporter’s buffer. mview must be a memoryview instance; this macro doesn’t check its type, you must do it yourself or you will risk crashes.

Py_buffer *PyMemoryView_GET_BASE(PyObject *mview)

Return either a pointer to the exporting object that the memoryview is based on or NULL if the memoryview has been created by one of the functions PyMemoryView_FromMemory() or PyMemoryView_FromBuffer(). mview must be a memoryview instance.

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Objets à références faibles

Python gère les références faibles comme des objets de première classe. Il existe deux types d’objets spécifiques qui implémentent directement les références faibles. Le premier est un objet de référence simple, et le second agit autant que possible comme un mandataire vers l’objet original.

int PyWeakref_Check(ob)

Renvoie vrai si ob est soit une référence, soit un objet proxy.

int PyWeakref_CheckRef(ob)

Retourne vrai si ob est un objet référence.

int PyWeakref_CheckProxy(ob)

Retourne vrai si ob est un objet proxy

PyObject* PyWeakref_NewRef(PyObject *ob, PyObject *callback)

Return value: New reference.

Retourne un objet de référence faible pour l’objet ob. Elle renvoie toujours une nouvelle référence, mais cela ne signifie pas qu’un nouvel objet est créé ; un objet référence existant peut être renvoyé. Le second paramètre, callback, peut être un objet appelable qui reçoit une notification lorsque ob est collecté par le ramasse-miette (garbage collected en anglais) ; il doit accepter un paramètre unique, qui est l’objet référence faible lui-même. callback peut aussi être positionné à None ou à NULL. Si ob n’est pas un objet faiblement référençable, ou si callback n’est pas appelable, None` ou NULL, ceci retourne NULL et lève une TypeError.

PyObject* PyWeakref_NewProxy(PyObject *ob, PyObject *callback)

Return value: New reference.

Retourne un objet mandataire à référence faible pour l’objet ob. Ceci renvoie toujours une nouvelle référence, mais ne garantit pas la création d’un nouvel objet ; un objet proxy existant peut être retourné. Le second paramètre, callback, peut être un objet appelable qui reçoit une notification lorsque ob est collecté ; il doit accepter un seul paramètre, qui sera l’objet de référence faible lui-même. callback peut aussi être None ou NULLL. Si ob n’est pas un objet faiblement référençable, ou si callback n’est pas appelable, None` ou NULL, ceci renvoie NULL et lève une TypeError.

PyObject* PyWeakref_GetObject(PyObject *ref)

Return value: Borrowed reference.

Retourne l’objet référencé à partir d’une référence faible, ref. Si le référence n’existe plus, alors l’objet renvoie Py_None.

Note

Cette fonction renvoie une référence empruntée à l’objet référencé. Cela signifie que vous devez toujours appeler Py_INCREF() sur l’objet sauf si vous savez qu’il ne peut pas être détruit tant que vous l’utilisez encore.

PyObject* PyWeakref_GET_OBJECT(PyObject *ref)

Return value: Borrowed reference.

Similaire à PyWeakref_GetObject(), mais implémenté comme une macro qui ne vérifie pas les erreurs.

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Capsules

Reportez-vous à Providing a C API for an Extension Module pour plus d’informations sur l’utilisation de ces objets.

Nouveau dans la version 3.1.

PyCapsule

This subtype of PyObject represents an opaque value, useful for C extension modules who need to pass an opaque value (as a void* pointer) through Python code to other C code. It is often used to make a C function pointer defined in one module available to other modules, so the regular import mechanism can be used to access C APIs defined in dynamically loaded modules.

PyCapsule_Destructor

The type of a destructor callback for a capsule. Defined as:

typedef void (*PyCapsule_Destructor)(PyObject *);

See PyCapsule_New() for the semantics of PyCapsule_Destructor callbacks.

int PyCapsule_CheckExact(PyObject *p)

Return true if its argument is a PyCapsule.

PyObject* PyCapsule_New(void *pointer, const char *name, PyCapsule_Destructor destructor)

Return value: New reference.

Create a PyCapsule encapsulating the pointer. The pointer argument may not be NULL.

On failure, set an exception and return NULL.

The name string may either be NULL or a pointer to a valid C string. If non-NULL, this string must outlive the capsule. (Though it is permitted to free it inside the destructor.)

If the destructor argument is not NULL, it will be called with the capsule as its argument when it is destroyed.

If this capsule will be stored as an attribute of a module, the name should be specified as modulename.attributename. This will enable other modules to import the capsule using PyCapsule_Import().

void* PyCapsule_GetPointer(PyObject *capsule, const char *name)

Retrieve the pointer stored in the capsule. On failure, set an exception and return NULL.

The name parameter must compare exactly to the name stored in the capsule. If the name stored in the capsule is NULL, the name passed in must also be NULL. Python uses the C function strcmp() to compare capsule names.

PyCapsule_Destructor PyCapsule_GetDestructor(PyObject *capsule)

Return the current destructor stored in the capsule. On failure, set an exception and return NULL.

It is legal for a capsule to have a NULL destructor. This makes a NULL return code somewhat ambiguous; use PyCapsule_IsValid() or PyErr_Occurred() to disambiguate.

void* PyCapsule_GetContext(PyObject *capsule)

Return the current context stored in the capsule. On failure, set an exception and return NULL.

It is legal for a capsule to have a NULL context. This makes a NULL return code somewhat ambiguous; use PyCapsule_IsValid() or PyErr_Occurred() to disambiguate.

const char* PyCapsule_GetName(PyObject *capsule)

Return the current name stored in the capsule. On failure, set an exception and return NULL.

It is legal for a capsule to have a NULL name. This makes a NULL return code somewhat ambiguous; use PyCapsule_IsValid() or PyErr_Occurred() to disambiguate.

void* PyCapsule_Import(const char *name, int no_block)

Import a pointer to a C object from a capsule attribute in a module. The name parameter should specify the full name to the attribute, as in module.attribute. The name stored in the capsule must match this string exactly. If no_block is true, import the module without blocking (using PyImport_ImportModuleNoBlock()). If no_block is false, import the module conventionally (using PyImport_ImportModule()).

Return the capsule’s internal pointer on success. On failure, set an exception and return NULL.

int PyCapsule_IsValid(PyObject *capsule, const char *name)

Determines whether or not capsule is a valid capsule. A valid capsule is non-NULL, passes PyCapsule_CheckExact(), has a non-NULL pointer stored in it, and its internal name matches the name parameter. (See PyCapsule_GetPointer() for information on how capsule names are compared.)

In other words, if PyCapsule_IsValid() returns a true value, calls to any of the accessors (any function starting with PyCapsule_Get()) are guaranteed to succeed.

Return a nonzero value if the object is valid and matches the name passed in. Return 0 otherwise. This function will not fail.

int PyCapsule_SetContext(PyObject *capsule, void *context)

Set the context pointer inside capsule to context.

Return 0 on success. Return nonzero and set an exception on failure.

int PyCapsule_SetDestructor(PyObject *capsule, PyCapsule_Destructor destructor)

Set the destructor inside capsule to destructor.

Return 0 on success. Return nonzero and set an exception on failure.

int PyCapsule_SetName(PyObject *capsule, const char *name)

Set the name inside capsule to name. If non-NULL, the name must outlive the capsule. If the previous name stored in the capsule was not NULL, no attempt is made to free it.

Return 0 on success. Return nonzero and set an exception on failure.

int PyCapsule_SetPointer(PyObject *capsule, void *pointer)

Set the void pointer inside capsule to pointer. The pointer may not be NULL.

Return 0 on success. Return nonzero and set an exception on failure.

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Objets générateur

Python utilise des objets générateurs pour implémenter les itérations de générateurs. Ils sont normalement crées en itérant sur une fonction donnant des valeurs via yield, au lieu d’appeler explicitement PyGen_New() ou PyGen_NewWithQualName().

PyGenObject

La structure C utilisée pour les objets générateurs.

PyTypeObject PyGen_Type

Le type objet correspondant aux objets générateurs.

int PyGen_Check(PyObject *ob)

Renvoie True si ob est un objet générateur. ob ne doit pas être NULL.

int PyGen_CheckExact(PyObject *ob)

Renvoie True si le type de ob est PyGen_Type. ob ne doit pas être NULL.

PyObject* PyGen_New(PyFrameObject *frame)

Return value: New reference.

Crée et renvoie un nouvel objet générateur basé sur l’objet frame. Une référence à frame est volée par cette fonction. L’argument ne doit pas être NULL.

PyObject* PyGen_NewWithQualName(PyFrameObject *frame, PyObject *name, PyObject *qualname)

Return value: New reference.

Crée et renvoie un nouvel objet générateur basé sur l’objet frame, avec __name__ et __qualname__ valant name et qualname. Une référence à frame est volée par cette fonction. L’argument frame ne doit pas être NULL.

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Objets coroutines

Nouveau dans la version 3.5.

Les objets coroutines sont les objets renvoyés par les fonctions déclarées avec le mot clef async.

PyCoroObject

La structure C utilisée pour les objets coroutine.

PyTypeObject PyCoro_Type

L’objet type correspondant aux objets coroutines.

int PyCoro_CheckExact(PyObject *ob)

Renvoie vrai si ob est de type PyCoro_Type. ob ne doit pas être NULL.

PyObject* PyCoro_New(PyFrameObject *frame, PyObject *name, PyObject *qualname)

Return value: New reference.

Crée et renvoie un nouvel objet coroutine basé sur l’objet frame, avec __name__ et __qualname__ respectivement assignés de name et qualname. Une référence à frame est empruntée par cette fonction. L’argument frame ne doit pas être NULL.

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Objets DateTime

De nombreux objets date et time sont exposés par le module DateTime. Avant d’utiliser une de ces fonctions, le fichier d’en-tête datetime.h doit être inclus dans vos sources (veuillez noter qu’il n’est pas inclus par le fichier Python.h) et la macro PyDateTime_IMPORT doit-être invoquée, généralement lors de la fonction d’initialisation du module. La macro crée un pointeur vers une structure C et place celui-ci dans une variable statique, PyDateTimeAPI, qui est utilisée par les macros suivantes.

Macros pour vérifier les types :

int PyDate_Check(PyObject *ob)

Renvoie vrai si ob est de type PyDateTime_DateType ou un sous-type de PyDateTime_DateType. ob ne doit pas être NULL.

int PyDate_CheckExact(PyObject *ob)

Renvoie vrai si ob est de type PyDateTime_DateType. ob ne doit pas être NULL.

int PyDateTime_Check(PyObject *ob)

Renvoie vrai si ob est de type PyDateTime_DateTimeType ou un sous-type de PyDateTime_DateTimeType. ob ne doit pas être NULL.

int PyDateTime_CheckExact(PyObject *ob)

Renvoie vrai si ob est de type PyDateTime_DateTimeType. ob ne doit pas être NULL.

int PyTime_Check(PyObject *ob)

Renvoie vrai si ob est de type PyDateTime_TimeType ou un sous-type de PyDateTime_TimeType. ob ne doit pas être NULL.

int PyTime_CheckExact(PyObject *ob)

Renvoie vrai si ob est de type PyDateTime_TimeType. ob ne doit pas être NULL.

int PyDelta_Check(PyObject *ob)

Renvoie vrai si ob est de type PyDateTime_DeltaType ou un sous-type de PyDateTime_DeltaType. ob ne doit pas être NULL.

int PyDelta_CheckExact(PyObject *ob)

Renvoie vrai si ob est de type PyDateTime_DeltaType. ob ne doit pas être NULL.

int PyTZInfo_Check(PyObject *ob)

Renvoie vrai si ob est de type PyDateTime_TZInfoType ou un sous-type de PyDateTime_TZInfoType. ob ne doit pas être NULL.

int PyTZInfo_CheckExact(PyObject *ob)

Renvoie vrai si ob est de type PyDateTime_TZInfoType. ob ne doit pas être NULL.

Macros pour créer des objets :

PyObject* PyDate_FromDate(int year, int month, int day)

Return value: New reference.

Return a datetime.date object with the specified year, month and day.

PyObject* PyDateTime_FromDateAndTime(int year, int month, int day, int hour, int minute, int second, int usecond)

Return value: New reference.

Return a datetime.datetime object with the specified year, month, day, hour, minute, second and microsecond.

PyObject* PyTime_FromTime(int hour, int minute, int second, int usecond)

Return value: New reference.

Return a datetime.time object with the specified hour, minute, second and microsecond.

PyObject* PyDelta_FromDSU(int days, int seconds, int useconds)

Return value: New reference.

Return a datetime.timedelta object representing the given number of days, seconds and microseconds. Normalization is performed so that the resulting number of microseconds and seconds lie in the ranges documented for datetime.timedelta objects.

Macros pour extraire les champs des objets date. L’argument doit être une instance de PyDateTime_Date, ou une sous-classe (telle que PyDateTime_DateTime). L’argument ne doit pas être NULL, et le type n’est pas vérifié :

int PyDateTime_GET_YEAR(PyDateTime_Date *o)

Renvoie l’année, sous forme d’entier positif.

int PyDateTime_GET_MONTH(PyDateTime_Date *o)

Renvoie le mois, sous forme d’entier allant de 1 à 12.

int PyDateTime_GET_DAY(PyDateTime_Date *o)

Renvoie le jour, sous forme d’entier allant de 1 à 31.

Macros pour extraire les champs des objets datetime. L’argument doit être une instance de PyDateTime_DateTime ou une sous-classe de celle-ci. L’argument ne doit pas être NULL, et le type n’est pas vérifié :

int PyDateTime_DATE_GET_HOUR(PyDateTime_DateTime *o)

Renvoie l’heure, sous forme d’entier allant de 0 à 23.

int PyDateTime_DATE_GET_MINUTE(PyDateTime_DateTime *o)

Renvoie la minute, sous forme d’entier allant de 0 à 59.

int PyDateTime_DATE_GET_SECOND(PyDateTime_DateTime *o)

Renvoie la seconde, sous forme d’entier allant de 0 à 59.

int PyDateTime_DATE_GET_MICROSECOND(PyDateTime_DateTime *o)

Renvoie la microseconde, sous forme d’entier allant de 0 à 999999.

Macros pour extraire les champs des objets time. L’argument doit être une instance de PyDateTime_Time ou une sous-classe de celle-ci. L’argument ne doit pas être NULL, et le type n’est pas vérifié :

int PyDateTime_TIME_GET_HOUR(PyDateTime_Time *o)

Renvoie l’heure, sous forme d’entier allant de 0 à 23.

int PyDateTime_TIME_GET_MINUTE(PyDateTime_Time *o)

Renvoie la minute, sous forme d’entier allant de 0 à 59.

int PyDateTime_TIME_GET_SECOND(PyDateTime_Time *o)

Renvoie la seconde, sous forme d’entier allant de 0 à 59.

int PyDateTime_TIME_GET_MICROSECOND(PyDateTime_Time *o)

Renvoie la microseconde, sous forme d’entier allant de 0 à 999999.

Macros pour extraire les champs des objets time delta. L’argument doit être une instance de PyDateTime_Delta ou une sous-classe de celle-ci. L’argument ne doit pas être NULL, et le type n’est pas vérifié :

int PyDateTime_DELTA_GET_DAYS(PyDateTime_Delta *o)

Renvoie le nombre de jours, sous forme d’entier allant de -999999999 à 999999999.

Nouveau dans la version 3.3.

int PyDateTime_DELTA_GET_SECONDS(PyDateTime_Delta *o)

Renvoie le nombre de secondes sous forme d’entier allant de 0 à 86399.

Nouveau dans la version 3.3.

int PyDateTime_DELTA_GET_MICROSECONDS(PyDateTime_Delta *o)

Renvoie le nombre de microsecondes, sous forme d’entier allant de 0 à 999999.

Nouveau dans la version 3.3.

Macros de confort pour les modules implémentant l’API DB :

PyObject* PyDateTime_FromTimestamp(PyObject *args)

Return value: New reference.

Create and return a new datetime.datetime object given an argument tuple suitable for passing to datetime.datetime.fromtimestamp().

PyObject* PyDate_FromTimestamp(PyObject *args)

Return value: New reference.

Create and return a new datetime.date object given an argument tuple suitable for passing to datetime.date.fromtimestamp().

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Initialization, Finalization, and Threads

Initializing and finalizing the interpreter

void Py_Initialize()

Initialize the Python interpreter. In an application embedding Python, this should be called before using any other Python/C API functions; with the exception of Py_SetProgramName(), Py_SetPythonHome() and Py_SetPath(). This initializes the table of loaded modules (sys.modules), and creates the fundamental modules builtins, __main__ and sys. It also initializes the module search path (sys.path). It does not set sys.argv; use PySys_SetArgvEx() for that. This is a no-op when called for a second time (without calling Py_FinalizeEx() first). There is no return value; it is a fatal error if the initialization fails.

Note

On Windows, changes the console mode from O_TEXT to O_BINARY, which will also affect non-Python uses of the console using the C Runtime.

void Py_InitializeEx(int initsigs)

This function works like Py_Initialize() if initsigs is 1. If initsigs is 0, it skips initialization registration of signal handlers, which might be useful when Python is embedded.

int Py_IsInitialized()

Return true (nonzero) when the Python interpreter has been initialized, false (zero) if not. After Py_FinalizeEx() is called, this returns false until Py_Initialize() is called again.

int Py_FinalizeEx()

Undo all initializations made by Py_Initialize() and subsequent use of Python/C API functions, and destroy all sub-interpreters (see Py_NewInterpreter() below) that were created and not yet destroyed since the last call to Py_Initialize(). Ideally, this frees all memory allocated by the Python interpreter. This is a no-op when called for a second time (without calling Py_Initialize() again first). Normally the return value is 0. If there were errors during finalization (flushing buffered data), -1 is returned.

This function is provided for a number of reasons. An embedding application might want to restart Python without having to restart the application itself. An application that has loaded the Python interpreter from a dynamically loadable library (or DLL) might want to free all memory allocated by Python before unloading the DLL. During a hunt for memory leaks in an application a developer might want to free all memory allocated by Python before exiting from the application.

Bugs and caveats: The destruction of modules and objects in modules is done in random order; this may cause destructors (__del__() methods) to fail when they depend on other objects (even functions) or modules. Dynamically loaded extension modules loaded by Python are not unloaded. Small amounts of memory allocated by the Python interpreter may not be freed (if you find a leak, please report it). Memory tied up in circular references between objects is not freed. Some memory allocated by extension modules may not be freed. Some extensions may not work properly if their initialization routine is called more than once; this can happen if an application calls Py_Initialize() and Py_FinalizeEx() more than once.

Nouveau dans la version 3.6.

void Py_Finalize()

This is a backwards-compatible version of Py_FinalizeEx() that disregards the return value.

Process-wide parameters

int Py_SetStandardStreamEncoding(const char *encoding, const char *errors)

This function should be called before Py_Initialize(), if it is called at all. It specifies which encoding and error handling to use with standard IO, with the same meanings as in str.encode().

It overrides PYTHONIOENCODING values, and allows embedding code to control IO encoding when the environment variable does not work.

encoding and/or errors may be NULL to use PYTHONIOENCODING and/or default values (depending on other settings).

Note that sys.stderr always uses the « backslashreplace » error handler, regardless of this (or any other) setting.

If Py_FinalizeEx() is called, this function will need to be called again in order to affect subsequent calls to Py_Initialize().

Returns 0 if successful, a nonzero value on error (e.g. calling after the interpreter has already been initialized).

Nouveau dans la version 3.4.

void Py_SetProgramName(wchar_t *name)

This function should be called before Py_Initialize() is called for the first time, if it is called at all. It tells the interpreter the value of the argv[0] argument to the main() function of the program (converted to wide characters). This is used by Py_GetPath() and some other functions below to find the Python run-time libraries relative to the interpreter executable. The default value is 'python'. The argument should point to a zero-terminated wide character string in static storage whose contents will not change for the duration of the program’s execution. No code in the Python interpreter will change the contents of this storage.

Use Py_DecodeLocale() to decode a bytes string to get a wchar_* string.

wchar* Py_GetProgramName()

Return the program name set with Py_SetProgramName(), or the default. The returned string points into static storage; the caller should not modify its value.

wchar_t* Py_GetPrefix()

Return the prefix for installed platform-independent files. This is derived through a number of complicated rules from the program name set with Py_SetProgramName() and some environment variables; for example, if the program name is '/usr/local/bin/python', the prefix is '/usr/local'. The returned string points into static storage; the caller should not modify its value. This corresponds to the prefix variable in the top-level Makefile and the --prefix argument to the configure script at build time. The value is available to Python code as sys.prefix. It is only useful on Unix. See also the next function.

wchar_t* Py_GetExecPrefix()

Return the exec-prefix for installed platform-dependent files. This is derived through a number of complicated rules from the program name set with Py_SetProgramName() and some environment variables; for example, if the program name is '/usr/local/bin/python', the exec-prefix is '/usr/local'. The returned string points into static storage; the caller should not modify its value. This corresponds to the exec_prefix variable in the top-level Makefile and the --exec-prefix argument to the configure script at build time. The value is available to Python code as sys.exec_prefix. It is only useful on Unix.

Background: The exec-prefix differs from the prefix when platform dependent files (such as executables and shared libraries) are installed in a different directory tree. In a typical installation, platform dependent files may be installed in the /usr/local/plat subtree while platform independent may be installed in /usr/local.

Generally speaking, a platform is a combination of hardware and software families, e.g. Sparc machines running the Solaris 2.x operating system are considered the same platform, but Intel machines running Solaris 2.x are another platform, and Intel machines running Linux are yet another platform. Different major revisions of the same operating system generally also form different platforms. Non-Unix operating systems are a different story; the installation strategies on those systems are so different that the prefix and exec-prefix are meaningless, and set to the empty string. Note that compiled Python bytecode files are platform independent (but not independent from the Python version by which they were compiled!).

System administrators will know how to configure the mount or automount programs to share /usr/local between platforms while having /usr/local/plat be a different filesystem for each platform.

wchar_t* Py_GetProgramFullPath()

Return the full program name of the Python executable; this is computed as a side-effect of deriving the default module search path from the program name (set by Py_SetProgramName() above). The returned string points into static storage; the caller should not modify its value. The value is available to Python code as sys.executable.

wchar_t* Py_GetPath()

Return the default module search path; this is computed from the program name (set by Py_SetProgramName() above) and some environment variables. The returned string consists of a series of directory names separated by a platform dependent delimiter character. The delimiter character is ':' on Unix and Mac OS X, ';' on Windows. The returned string points into static storage; the caller should not modify its value. The list sys.path is initialized with this value on interpreter startup; it can be (and usually is) modified later to change the search path for loading modules.

void Py_SetPath(const wchar_t *)

Set the default module search path. If this function is called before Py_Initialize(), then Py_GetPath() won’t attempt to compute a default search path but uses the one provided instead. This is useful if Python is embedded by an application that has full knowledge of the location of all modules. The path components should be separated by the platform dependent delimiter character, which is ':' on Unix and Mac OS X, ';' on Windows.

This also causes sys.executable to be set only to the raw program name (see Py_SetProgramName()) and for sys.prefix and sys.exec_prefix to be empty. It is up to the caller to modify these if required after calling Py_Initialize().

Use Py_DecodeLocale() to decode a bytes string to get a wchar_* string.

The path argument is copied internally, so the caller may free it after the call completes.

const char* Py_GetVersion()

Return the version of this Python interpreter. This is a string that looks something like

"3.0a5+ (py3k:63103M, May 12 2008, 00:53:55) \n[GCC 4.2.3]"

The first word (up to the first space character) is the current Python version; the first three characters are the major and minor version separated by a period. The returned string points into static storage; the caller should not modify its value. The value is available to Python code as sys.version.

const char* Py_GetPlatform()

Return the platform identifier for the current platform. On Unix, this is formed from the « official » name of the operating system, converted to lower case, followed by the major revision number; e.g., for Solaris 2.x, which is also known as SunOS 5.x, the value is 'sunos5'. On Mac OS X, it is 'darwin'. On Windows, it is 'win'. The returned string points into static storage; the caller should not modify its value. The value is available to Python code as sys.platform.

const char* Py_GetCopyright()

Return the official copyright string for the current Python version, for example

'Copyright 1991-1995 Stichting Mathematisch Centrum, Amsterdam'

The returned string points into static storage; the caller should not modify its value. The value is available to Python code as sys.copyright.

const char* Py_GetCompiler()

Return an indication of the compiler used to build the current Python version, in square brackets, for example:

"[GCC 2.7.2.2]"

The returned string points into static storage; the caller should not modify its value. The value is available to Python code as part of the variable sys.version.

const char* Py_GetBuildInfo()

Return information about the sequence number and build date and time of the current Python interpreter instance, for example

"#67, Aug  1 1997, 22:34:28"

The returned string points into static storage; the caller should not modify its value. The value is available to Python code as part of the variable sys.version.

void PySys_SetArgvEx(int argc, wchar_t **argv, int updatepath)

Set sys.argv based on argc and argv. These parameters are similar to those passed to the program’s main() function with the difference that the first entry should refer to the script file to be executed rather than the executable hosting the Python interpreter. If there isn’t a script that will be run, the first entry in argv can be an empty string. If this function fails to initialize sys.argv, a fatal condition is signalled using Py_FatalError().

If updatepath is zero, this is all the function does. If updatepath is non-zero, the function also modifies sys.path according to the following algorithm:

If the name of an existing script is passed in argv[0], the absolute path of the directory where the script is located is prepended to sys.path.

Otherwise (that is, if argc is 0 or argv[0] doesn’t point to an existing file name), an empty string is prepended to sys.path, which is the same as prepending the current working directory (".").

Use Py_DecodeLocale() to decode a bytes string to get a wchar_* string.

Note

It is recommended that applications embedding the Python interpreter for purposes other than executing a single script pass 0 as updatepath, and update sys.path themselves if desired. See CVE-2008-5983 [https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2008-5983].

On versions before 3.1.3, you can achieve the same effect by manually popping the first sys.path element after having called PySys_SetArgv(), for example using:

PyRun_SimpleString("import sys; sys.path.pop(0)\n");

Nouveau dans la version 3.1.3.

void PySys_SetArgv(int argc, wchar_t **argv)

This function works like PySys_SetArgvEx() with updatepath set to 1 unless the python interpreter was started with the -I.

Use Py_DecodeLocale() to decode a bytes string to get a wchar_* string.

Modifié dans la version 3.4: The updatepath value depends on -I.

void Py_SetPythonHome(wchar_t *home)

Set the default « home » directory, that is, the location of the standard Python libraries. See PYTHONHOME for the meaning of the argument string.

The argument should point to a zero-terminated character string in static storage whose contents will not change for the duration of the program’s execution. No code in the Python interpreter will change the contents of this storage.

Use Py_DecodeLocale() to decode a bytes string to get a wchar_* string.

w_char* Py_GetPythonHome()

Return the default « home », that is, the value set by a previous call to Py_SetPythonHome(), or the value of the PYTHONHOME environment variable if it is set.

Thread State and the Global Interpreter Lock

The Python interpreter is not fully thread-safe. In order to support multi-threaded Python programs, there’s a global lock, called the global interpreter lock or GIL, that must be held by the current thread before it can safely access Python objects. Without the lock, even the simplest operations could cause problems in a multi-threaded program: for example, when two threads simultaneously increment the reference count of the same object, the reference count could end up being incremented only once instead of twice.

Therefore, the rule exists that only the thread that has acquired the GIL may operate on Python objects or call Python/C API functions. In order to emulate concurrency of execution, the interpreter regularly tries to switch threads (see sys.setswitchinterval()). The lock is also released around potentially blocking I/O operations like reading or writing a file, so that other Python threads can run in the meantime.

The Python interpreter keeps some thread-specific bookkeeping information inside a data structure called PyThreadState. There’s also one global variable pointing to the current PyThreadState: it can be retrieved using PyThreadState_Get().

Releasing the GIL from extension code

Most extension code manipulating the GIL has the following simple structure:

Save the thread state in a local variable.
Release the global interpreter lock.
... Do some blocking I/O operation ...
Reacquire the global interpreter lock.
Restore the thread state from the local variable.

This is so common that a pair of macros exists to simplify it:

Py_BEGIN_ALLOW_THREADS
... Do some blocking I/O operation ...
Py_END_ALLOW_THREADS

The Py_BEGIN_ALLOW_THREADS macro opens a new block and declares a hidden local variable; the Py_END_ALLOW_THREADS macro closes the block. These two macros are still available when Python is compiled without thread support (they simply have an empty expansion).

When thread support is enabled, the block above expands to the following code:

PyThreadState *_save;

_save = PyEval_SaveThread();
...Do some blocking I/O operation...
PyEval_RestoreThread(_save);

Here is how these functions work: the global interpreter lock is used to protect the pointer to the current thread state. When releasing the lock and saving the thread state, the current thread state pointer must be retrieved before the lock is released (since another thread could immediately acquire the lock and store its own thread state in the global variable). Conversely, when acquiring the lock and restoring the thread state, the lock must be acquired before storing the thread state pointer.

Note

Calling system I/O functions is the most common use case for releasing the GIL, but it can also be useful before calling long-running computations which don’t need access to Python objects, such as compression or cryptographic functions operating over memory buffers. For example, the standard zlib and hashlib modules release the GIL when compressing or hashing data.

Non-Python created threads

When threads are created using the dedicated Python APIs (such as the threading module), a thread state is automatically associated to them and the code showed above is therefore correct. However, when threads are created from C (for example by a third-party library with its own thread management), they don’t hold the GIL, nor is there a thread state structure for them.

If you need to call Python code from these threads (often this will be part of a callback API provided by the aforementioned third-party library), you must first register these threads with the interpreter by creating a thread state data structure, then acquiring the GIL, and finally storing their thread state pointer, before you can start using the Python/C API. When you are done, you should reset the thread state pointer, release the GIL, and finally free the thread state data structure.

The PyGILState_Ensure() and PyGILState_Release() functions do all of the above automatically. The typical idiom for calling into Python from a C thread is:

PyGILState_STATE gstate;
gstate = PyGILState_Ensure();

/* Perform Python actions here. */
result = CallSomeFunction();
/* evaluate result or handle exception */

/* Release the thread. No Python API allowed beyond this point. */
PyGILState_Release(gstate);

Note that the PyGILState_*() functions assume there is only one global interpreter (created automatically by Py_Initialize()). Python supports the creation of additional interpreters (using Py_NewInterpreter()), but mixing multiple interpreters and the PyGILState_*() API is unsupported.

Another important thing to note about threads is their behaviour in the face of the C fork() call. On most systems with fork(), after a process forks only the thread that issued the fork will exist. That also means any locks held by other threads will never be released. Python solves this for os.fork() by acquiring the locks it uses internally before the fork, and releasing them afterwards. In addition, it resets any Verrous in the child. When extending or embedding Python, there is no way to inform Python of additional (non-Python) locks that need to be acquired before or reset after a fork. OS facilities such as pthread_atfork() would need to be used to accomplish the same thing. Additionally, when extending or embedding Python, calling fork() directly rather than through os.fork() (and returning to or calling into Python) may result in a deadlock by one of Python’s internal locks being held by a thread that is defunct after the fork. PyOS_AfterFork() tries to reset the necessary locks, but is not always able to.

High-level API

These are the most commonly used types and functions when writing C extension code, or when embedding the Python interpreter:

PyInterpreterState

This data structure represents the state shared by a number of cooperating threads. Threads belonging to the same interpreter share their module administration and a few other internal items. There are no public members in this structure.

Threads belonging to different interpreters initially share nothing, except process state like available memory, open file descriptors and such. The global interpreter lock is also shared by all threads, regardless of to which interpreter they belong.

PyThreadState

This data structure represents the state of a single thread. The only public data member is PyInterpreterState *interp, which points to this thread’s interpreter state.

void PyEval_InitThreads()

Initialize and acquire the global interpreter lock. It should be called in the main thread before creating a second thread or engaging in any other thread operations such as PyEval_ReleaseThread(tstate). It is not needed before calling PyEval_SaveThread() or PyEval_RestoreThread().

This is a no-op when called for a second time.

Modifié dans la version 3.2: This function cannot be called before Py_Initialize() anymore.

Note

When only the main thread exists, no GIL operations are needed. This is a common situation (most Python programs do not use threads), and the lock operations slow the interpreter down a bit. Therefore, the lock is not created initially. This situation is equivalent to having acquired the lock: when there is only a single thread, all object accesses are safe. Therefore, when this function initializes the global interpreter lock, it also acquires it. Before the Python _thread module creates a new thread, knowing that either it has the lock or the lock hasn’t been created yet, it calls PyEval_InitThreads(). When this call returns, it is guaranteed that the lock has been created and that the calling thread has acquired it.

It is not safe to call this function when it is unknown which thread (if any) currently has the global interpreter lock.

This function is not available when thread support is disabled at compile time.

int PyEval_ThreadsInitialized()

Returns a non-zero value if PyEval_InitThreads() has been called. This function can be called without holding the GIL, and therefore can be used to avoid calls to the locking API when running single-threaded. This function is not available when thread support is disabled at compile time.

PyThreadState* PyEval_SaveThread()

Release the global interpreter lock (if it has been created and thread support is enabled) and reset the thread state to NULL, returning the previous thread state (which is not NULL). If the lock has been created, the current thread must have acquired it. (This function is available even when thread support is disabled at compile time.)

void PyEval_RestoreThread(PyThreadState *tstate)

Acquire the global interpreter lock (if it has been created and thread support is enabled) and set the thread state to tstate, which must not be NULL. If the lock has been created, the current thread must not have acquired it, otherwise deadlock ensues. (This function is available even when thread support is disabled at compile time.)

PyThreadState* PyThreadState_Get()

Return the current thread state. The global interpreter lock must be held. When the current thread state is NULL, this issues a fatal error (so that the caller needn’t check for NULL).

PyThreadState* PyThreadState_Swap(PyThreadState *tstate)

Swap the current thread state with the thread state given by the argument tstate, which may be NULL. The global interpreter lock must be held and is not released.

void PyEval_ReInitThreads()

This function is called from PyOS_AfterFork() to ensure that newly created child processes don’t hold locks referring to threads which are not running in the child process.

The following functions use thread-local storage, and are not compatible with sub-interpreters:

PyGILState_STATE PyGILState_Ensure()

Ensure that the current thread is ready to call the Python C API regardless of the current state of Python, or of the global interpreter lock. This may be called as many times as desired by a thread as long as each call is matched with a call to PyGILState_Release(). In general, other thread-related APIs may be used between PyGILState_Ensure() and PyGILState_Release() calls as long as the thread state is restored to its previous state before the Release(). For example, normal usage of the Py_BEGIN_ALLOW_THREADS and Py_END_ALLOW_THREADS macros is acceptable.

The return value is an opaque « handle » to the thread state when PyGILState_Ensure() was called, and must be passed to PyGILState_Release() to ensure Python is left in the same state. Even though recursive calls are allowed, these handles cannot be shared - each unique call to PyGILState_Ensure() must save the handle for its call to PyGILState_Release().

When the function returns, the current thread will hold the GIL and be able to call arbitrary Python code. Failure is a fatal error.

void PyGILState_Release(PyGILState_STATE)

Release any resources previously acquired. After this call, Python’s state will be the same as it was prior to the corresponding PyGILState_Ensure() call (but generally this state will be unknown to the caller, hence the use of the GILState API).

Every call to PyGILState_Ensure() must be matched by a call to PyGILState_Release() on the same thread.

PyThreadState* PyGILState_GetThisThreadState()

Get the current thread state for this thread. May return NULL if no GILState API has been used on the current thread. Note that the main thread always has such a thread-state, even if no auto-thread-state call has been made on the main thread. This is mainly a helper/diagnostic function.

int PyGILState_Check()

Return 1 if the current thread is holding the GIL and 0 otherwise. This function can be called from any thread at any time. Only if it has had its Python thread state initialized and currently is holding the GIL will it return 1. This is mainly a helper/diagnostic function. It can be useful for example in callback contexts or memory allocation functions when knowing that the GIL is locked can allow the caller to perform sensitive actions or otherwise behave differently.

Nouveau dans la version 3.4.

The following macros are normally used without a trailing semicolon; look for example usage in the Python source distribution.

Py_BEGIN_ALLOW_THREADS

This macro expands to { PyThreadState *_save; _save = PyEval_SaveThread();. Note that it contains an opening brace; it must be matched with a following Py_END_ALLOW_THREADS macro. See above for further discussion of this macro. It is a no-op when thread support is disabled at compile time.

Py_END_ALLOW_THREADS

This macro expands to PyEval_RestoreThread(_save); }. Note that it contains a closing brace; it must be matched with an earlier Py_BEGIN_ALLOW_THREADS macro. See above for further discussion of this macro. It is a no-op when thread support is disabled at compile time.

Py_BLOCK_THREADS

This macro expands to PyEval_RestoreThread(_save);: it is equivalent to Py_END_ALLOW_THREADS without the closing brace. It is a no-op when thread support is disabled at compile time.

Py_UNBLOCK_THREADS

This macro expands to _save = PyEval_SaveThread();: it is equivalent to Py_BEGIN_ALLOW_THREADS without the opening brace and variable declaration. It is a no-op when thread support is disabled at compile time.

Low-level API

All of the following functions are only available when thread support is enabled at compile time, and must be called only when the global interpreter lock has been created.

PyInterpreterState* PyInterpreterState_New()

Create a new interpreter state object. The global interpreter lock need not be held, but may be held if it is necessary to serialize calls to this function.

void PyInterpreterState_Clear(PyInterpreterState *interp)

Reset all information in an interpreter state object. The global interpreter lock must be held.

void PyInterpreterState_Delete(PyInterpreterState *interp)

Destroy an interpreter state object. The global interpreter lock need not be held. The interpreter state must have been reset with a previous call to PyInterpreterState_Clear().

PyThreadState* PyThreadState_New(PyInterpreterState *interp)

Create a new thread state object belonging to the given interpreter object. The global interpreter lock need not be held, but may be held if it is necessary to serialize calls to this function.

void PyThreadState_Clear(PyThreadState *tstate)

Reset all information in a thread state object. The global interpreter lock must be held.

void PyThreadState_Delete(PyThreadState *tstate)

Destroy a thread state object. The global interpreter lock need not be held. The thread state must have been reset with a previous call to PyThreadState_Clear().

PyObject* PyThreadState_GetDict()

Return value: Borrowed reference.

Return a dictionary in which extensions can store thread-specific state information. Each extension should use a unique key to use to store state in the dictionary. It is okay to call this function when no current thread state is available. If this function returns NULL, no exception has been raised and the caller should assume no current thread state is available.

int PyThreadState_SetAsyncExc(long id, PyObject *exc)

Asynchronously raise an exception in a thread. The id argument is the thread id of the target thread; exc is the exception object to be raised. This function does not steal any references to exc. To prevent naive misuse, you must write your own C extension to call this. Must be called with the GIL held. Returns the number of thread states modified; this is normally one, but will be zero if the thread id isn’t found. If exc is NULL, the pending exception (if any) for the thread is cleared. This raises no exceptions.

void PyEval_AcquireThread(PyThreadState *tstate)

Acquire the global interpreter lock and set the current thread state to tstate, which should not be NULL. The lock must have been created earlier. If this thread already has the lock, deadlock ensues.

PyEval_RestoreThread() is a higher-level function which is always available (even when thread support isn’t enabled or when threads have not been initialized).

void PyEval_ReleaseThread(PyThreadState *tstate)

Reset the current thread state to NULL and release the global interpreter lock. The lock must have been created earlier and must be held by the current thread. The tstate argument, which must not be NULL, is only used to check that it represents the current thread state — if it isn’t, a fatal error is reported.

PyEval_SaveThread() is a higher-level function which is always available (even when thread support isn’t enabled or when threads have not been initialized).

void PyEval_AcquireLock()

Acquire the global interpreter lock. The lock must have been created earlier. If this thread already has the lock, a deadlock ensues.

Obsolète depuis la version 3.2: This function does not update the current thread state. Please use PyEval_RestoreThread() or PyEval_AcquireThread() instead.

void PyEval_ReleaseLock()

Release the global interpreter lock. The lock must have been created earlier.

Obsolète depuis la version 3.2: This function does not update the current thread state. Please use PyEval_SaveThread() or PyEval_ReleaseThread() instead.

Sub-interpreter support

While in most uses, you will only embed a single Python interpreter, there are cases where you need to create several independent interpreters in the same process and perhaps even in the same thread. Sub-interpreters allow you to do that. You can switch between sub-interpreters using the PyThreadState_Swap() function. You can create and destroy them using the following functions:

PyThreadState* Py_NewInterpreter()

Create a new sub-interpreter. This is an (almost) totally separate environment for the execution of Python code. In particular, the new interpreter has separate, independent versions of all imported modules, including the fundamental modules builtins, __main__ and sys. The table of loaded modules (sys.modules) and the module search path (sys.path) are also separate. The new environment has no sys.argv variable. It has new standard I/O stream file objects sys.stdin, sys.stdout and sys.stderr (however these refer to the same underlying file descriptors).

The return value points to the first thread state created in the new sub-interpreter. This thread state is made in the current thread state. Note that no actual thread is created; see the discussion of thread states below. If creation of the new interpreter is unsuccessful, NULL is returned; no exception is set since the exception state is stored in the current thread state and there may not be a current thread state. (Like all other Python/C API functions, the global interpreter lock must be held before calling this function and is still held when it returns; however, unlike most other Python/C API functions, there needn’t be a current thread state on entry.)

Extension modules are shared between (sub-)interpreters as follows: the first time a particular extension is imported, it is initialized normally, and a (shallow) copy of its module’s dictionary is squirreled away. When the same extension is imported by another (sub-)interpreter, a new module is initialized and filled with the contents of this copy; the extension’s init function is not called. Note that this is different from what happens when an extension is imported after the interpreter has been completely re-initialized by calling Py_FinalizeEx() and Py_Initialize(); in that case, the extension’s initmodule function is called again.

void Py_EndInterpreter(PyThreadState *tstate)

Destroy the (sub-)interpreter represented by the given thread state. The given thread state must be the current thread state. See the discussion of thread states below. When the call returns, the current thread state is NULL. All thread states associated with this interpreter are destroyed. (The global interpreter lock must be held before calling this function and is still held when it returns.) Py_FinalizeEx() will destroy all sub-interpreters that haven’t been explicitly destroyed at that point.

Bugs and caveats

Because sub-interpreters (and the main interpreter) are part of the same process, the insulation between them isn’t perfect — for example, using low-level file operations like os.close() they can (accidentally or maliciously) affect each other’s open files. Because of the way extensions are shared between (sub-)interpreters, some extensions may not work properly; this is especially likely when the extension makes use of (static) global variables, or when the extension manipulates its module’s dictionary after its initialization. It is possible to insert objects created in one sub-interpreter into a namespace of another sub-interpreter; this should be done with great care to avoid sharing user-defined functions, methods, instances or classes between sub-interpreters, since import operations executed by such objects may affect the wrong (sub-)interpreter’s dictionary of loaded modules.

Also note that combining this functionality with PyGILState_*() APIs is delicate, because these APIs assume a bijection between Python thread states and OS-level threads, an assumption broken by the presence of sub-interpreters. It is highly recommended that you don’t switch sub-interpreters between a pair of matching PyGILState_Ensure() and PyGILState_Release() calls. Furthermore, extensions (such as ctypes) using these APIs to allow calling of Python code from non-Python created threads will probably be broken when using sub-interpreters.

Asynchronous Notifications

A mechanism is provided to make asynchronous notifications to the main interpreter thread. These notifications take the form of a function pointer and a void pointer argument.

int Py_AddPendingCall(int (*func)(void *), void *arg)

Schedule a function to be called from the main interpreter thread. On success, 0 is returned and func is queued for being called in the main thread. On failure, -1 is returned without setting any exception.

When successfully queued, func will be eventually called from the main interpreter thread with the argument arg. It will be called asynchronously with respect to normally running Python code, but with both these conditions met:

on a bytecode boundary;

with the main thread holding the global interpreter lock (func can therefore use the full C API).

func must return 0 on success, or -1 on failure with an exception set. func won’t be interrupted to perform another asynchronous notification recursively, but it can still be interrupted to switch threads if the global interpreter lock is released.

This function doesn’t need a current thread state to run, and it doesn’t need the global interpreter lock.

Avertissement

This is a low-level function, only useful for very special cases. There is no guarantee that func will be called as quick as possible. If the main thread is busy executing a system call, func won’t be called before the system call returns. This function is generally not suitable for calling Python code from arbitrary C threads. Instead, use the PyGILState API.

Nouveau dans la version 3.1.

Profiling and Tracing

The Python interpreter provides some low-level support for attaching profiling and execution tracing facilities. These are used for profiling, debugging, and coverage analysis tools.

This C interface allows the profiling or tracing code to avoid the overhead of calling through Python-level callable objects, making a direct C function call instead. The essential attributes of the facility have not changed; the interface allows trace functions to be installed per-thread, and the basic events reported to the trace function are the same as had been reported to the Python-level trace functions in previous versions.

int (*Py_tracefunc)(PyObject *obj, PyFrameObject *frame, int what, PyObject *arg)

The type of the trace function registered using PyEval_SetProfile() and PyEval_SetTrace(). The first parameter is the object passed to the registration function as obj, frame is the frame object to which the event pertains, what is one of the constants PyTrace_CALL, PyTrace_EXCEPTION, PyTrace_LINE, PyTrace_RETURN, PyTrace_C_CALL, PyTrace_C_EXCEPTION, or PyTrace_C_RETURN, and arg depends on the value of what:

Value of what

Meaning of arg

PyTrace_CALL

Always Py_None.

PyTrace_EXCEPTION

Exception information as returned by sys.exc_info().

PyTrace_LINE

Always Py_None.

PyTrace_RETURN

Value being returned to the caller, or NULL if caused by an exception.

PyTrace_C_CALL

Function object being called.

PyTrace_C_EXCEPTION

Function object being called.

PyTrace_C_RETURN

Function object being called.

int PyTrace_CALL

The value of the what parameter to a Py_tracefunc function when a new call to a function or method is being reported, or a new entry into a generator. Note that the creation of the iterator for a generator function is not reported as there is no control transfer to the Python bytecode in the corresponding frame.

int PyTrace_EXCEPTION

The value of the what parameter to a Py_tracefunc function when an exception has been raised. The callback function is called with this value for what when after any bytecode is processed after which the exception becomes set within the frame being executed. The effect of this is that as exception propagation causes the Python stack to unwind, the callback is called upon return to each frame as the exception propagates. Only trace functions receives these events; they are not needed by the profiler.

int PyTrace_LINE

The value passed as the what parameter to a trace function (but not a profiling function) when a line-number event is being reported.

int PyTrace_RETURN

The value for the what parameter to Py_tracefunc functions when a call is about to return.

int PyTrace_C_CALL

The value for the what parameter to Py_tracefunc functions when a C function is about to be called.

int PyTrace_C_EXCEPTION

The value for the what parameter to Py_tracefunc functions when a C function has raised an exception.

int PyTrace_C_RETURN

The value for the what parameter to Py_tracefunc functions when a C function has returned.

void PyEval_SetProfile(Py_tracefunc func, PyObject *obj)

Set the profiler function to func. The obj parameter is passed to the function as its first parameter, and may be any Python object, or NULL. If the profile function needs to maintain state, using a different value for obj for each thread provides a convenient and thread-safe place to store it. The profile function is called for all monitored events except PyTrace_LINE and PyTrace_EXCEPTION.

void PyEval_SetTrace(Py_tracefunc func, PyObject *obj)

Set the tracing function to func. This is similar to PyEval_SetProfile(), except the tracing function does receive line-number events and does not receive any event related to C function objects being called. Any trace function registered using PyEval_SetTrace() will not receive PyTrace_C_CALL, PyTrace_C_EXCEPTION or PyTrace_C_RETURN as a value for the what parameter.

PyObject* PyEval_GetCallStats(PyObject *self)

Return a tuple of function call counts. There are constants defined for the positions within the tuple:

Nom

Valeur

PCALL_ALL

0

PCALL_FUNCTION

1

PCALL_FAST_FUNCTION

2

PCALL_FASTER_FUNCTION

3

PCALL_METHOD

4

PCALL_BOUND_METHOD

5

PCALL_CFUNCTION

6

PCALL_TYPE

7

PCALL_GENERATOR

8

PCALL_OTHER

9

PCALL_POP

10

PCALL_FAST_FUNCTION means no argument tuple needs to be created. PCALL_FASTER_FUNCTION means that the fast-path frame setup code is used.

If there is a method call where the call can be optimized by changing the argument tuple and calling the function directly, it gets recorded twice.

This function is only present if Python is compiled with CALL_PROFILE defined.

Support avancé du débogueur

These functions are only intended to be used by advanced debugging tools.

PyInterpreterState* PyInterpreterState_Head()

Return the interpreter state object at the head of the list of all such objects.

PyInterpreterState* PyInterpreterState_Next(PyInterpreterState *interp)

Return the next interpreter state object after interp from the list of all such objects.

PyThreadState * PyInterpreterState_ThreadHead(PyInterpreterState *interp)

Return the pointer to the first PyThreadState object in the list of threads associated with the interpreter interp.

PyThreadState* PyThreadState_Next(PyThreadState *tstate)

Return the next thread state object after tstate from the list of all such objects belonging to the same PyInterpreterState object.

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Memory Management

Aperçu

Memory management in Python involves a private heap containing all Python objects and data structures. The management of this private heap is ensured internally by the Python memory manager. The Python memory manager has different components which deal with various dynamic storage management aspects, like sharing, segmentation, preallocation or caching.

At the lowest level, a raw memory allocator ensures that there is enough room in the private heap for storing all Python-related data by interacting with the memory manager of the operating system. On top of the raw memory allocator, several object-specific allocators operate on the same heap and implement distinct memory management policies adapted to the peculiarities of every object type. For example, integer objects are managed differently within the heap than strings, tuples or dictionaries because integers imply different storage requirements and speed/space tradeoffs. The Python memory manager thus delegates some of the work to the object-specific allocators, but ensures that the latter operate within the bounds of the private heap.

It is important to understand that the management of the Python heap is performed by the interpreter itself and that the user has no control over it, even if they regularly manipulate object pointers to memory blocks inside that heap. The allocation of heap space for Python objects and other internal buffers is performed on demand by the Python memory manager through the Python/C API functions listed in this document.

To avoid memory corruption, extension writers should never try to operate on Python objects with the functions exported by the C library: malloc(), calloc(), realloc() and free(). This will result in mixed calls between the C allocator and the Python memory manager with fatal consequences, because they implement different algorithms and operate on different heaps. However, one may safely allocate and release memory blocks with the C library allocator for individual purposes, as shown in the following example:

PyObject *res;
char *buf = (char *) malloc(BUFSIZ); /* for I/O */

if (buf == NULL)
    return PyErr_NoMemory();
...Do some I/O operation involving buf...
res = PyBytes_FromString(buf);
free(buf); /* malloc'ed */
return res;

In this example, the memory request for the I/O buffer is handled by the C library allocator. The Python memory manager is involved only in the allocation of the string object returned as a result.

In most situations, however, it is recommended to allocate memory from the Python heap specifically because the latter is under control of the Python memory manager. For example, this is required when the interpreter is extended with new object types written in C. Another reason for using the Python heap is the desire to inform the Python memory manager about the memory needs of the extension module. Even when the requested memory is used exclusively for internal, highly-specific purposes, delegating all memory requests to the Python memory manager causes the interpreter to have a more accurate image of its memory footprint as a whole. Consequently, under certain circumstances, the Python memory manager may or may not trigger appropriate actions, like garbage collection, memory compaction or other preventive procedures. Note that by using the C library allocator as shown in the previous example, the allocated memory for the I/O buffer escapes completely the Python memory manager.

Voir aussi

The PYTHONMALLOC environment variable can be used to configure the memory allocators used by Python.

The PYTHONMALLOCSTATS environment variable can be used to print statistics of the pymalloc memory allocator every time a new pymalloc object arena is created, and on shutdown.

Raw Memory Interface

The following function sets are wrappers to the system allocator. These functions are thread-safe, the GIL does not need to be held.

The default raw memory block allocator uses the following functions: malloc(), calloc(), realloc() and free(); call malloc(1) (or calloc(1, 1)) when requesting zero bytes.

Nouveau dans la version 3.4.

void* PyMem_RawMalloc(size_t n)

Allocates n bytes and returns a pointer of type void* to the allocated memory, or NULL if the request fails.

Requesting zero bytes returns a distinct non-NULL pointer if possible, as if PyMem_RawMalloc(1) had been called instead. The memory will not have been initialized in any way.

void* PyMem_RawCalloc(size_t nelem, size_t elsize)

Allocates nelem elements each whose size in bytes is elsize and returns a pointer of type void* to the allocated memory, or NULL if the request fails. The memory is initialized to zeros.

Requesting zero elements or elements of size zero bytes returns a distinct non-NULL pointer if possible, as if PyMem_RawCalloc(1, 1) had been called instead.

Nouveau dans la version 3.5.

void* PyMem_RawRealloc(void *p, size_t n)

Resizes the memory block pointed to by p to n bytes. The contents will be unchanged to the minimum of the old and the new sizes.

If p is NULL, the call is equivalent to PyMem_RawMalloc(n); else if n is equal to zero, the memory block is resized but is not freed, and the returned pointer is non-NULL.

Unless p is NULL, it must have been returned by a previous call to PyMem_RawMalloc(), PyMem_RawRealloc() or PyMem_RawCalloc().

If the request fails, PyMem_RawRealloc() returns NULL and p remains a valid pointer to the previous memory area.

void PyMem_RawFree(void *p)

Frees the memory block pointed to by p, which must have been returned by a previous call to PyMem_RawMalloc(), PyMem_RawRealloc() or PyMem_RawCalloc(). Otherwise, or if PyMem_RawFree(p) has been called before, undefined behavior occurs.

If p is NULL, no operation is performed.

Memory Interface

The following function sets, modeled after the ANSI C standard, but specifying behavior when requesting zero bytes, are available for allocating and releasing memory from the Python heap.

By default, these functions use pymalloc memory allocator.

Avertissement

The GIL must be held when using these functions.

Modifié dans la version 3.6: The default allocator is now pymalloc instead of system malloc().

void* PyMem_Malloc(size_t n)

Allocates n bytes and returns a pointer of type void* to the allocated memory, or NULL if the request fails.

Requesting zero bytes returns a distinct non-NULL pointer if possible, as if PyMem_Malloc(1) had been called instead. The memory will not have been initialized in any way.

void* PyMem_Calloc(size_t nelem, size_t elsize)

Allocates nelem elements each whose size in bytes is elsize and returns a pointer of type void* to the allocated memory, or NULL if the request fails. The memory is initialized to zeros.

Requesting zero elements or elements of size zero bytes returns a distinct non-NULL pointer if possible, as if PyMem_Calloc(1, 1) had been called instead.

Nouveau dans la version 3.5.

void* PyMem_Realloc(void *p, size_t n)

Resizes the memory block pointed to by p to n bytes. The contents will be unchanged to the minimum of the old and the new sizes.

If p is NULL, the call is equivalent to PyMem_Malloc(n); else if n is equal to zero, the memory block is resized but is not freed, and the returned pointer is non-NULL.

Unless p is NULL, it must have been returned by a previous call to PyMem_Malloc(), PyMem_Realloc() or PyMem_Calloc().

If the request fails, PyMem_Realloc() returns NULL and p remains a valid pointer to the previous memory area.

void PyMem_Free(void *p)

Frees the memory block pointed to by p, which must have been returned by a previous call to PyMem_Malloc(), PyMem_Realloc() or PyMem_Calloc(). Otherwise, or if PyMem_Free(p) has been called before, undefined behavior occurs.

If p is NULL, no operation is performed.

The following type-oriented macros are provided for convenience. Note that TYPE refers to any C type.

TYPE* PyMem_New(TYPE, size_t n)

Same as PyMem_Malloc(), but allocates (n * sizeof(TYPE)) bytes of memory. Returns a pointer cast to TYPE*. The memory will not have been initialized in any way.

TYPE* PyMem_Resize(void *p, TYPE, size_t n)

Same as PyMem_Realloc(), but the memory block is resized to (n * sizeof(TYPE)) bytes. Returns a pointer cast to TYPE*. On return, p will be a pointer to the new memory area, or NULL in the event of failure.

This is a C preprocessor macro; p is always reassigned. Save the original value of p to avoid losing memory when handling errors.

void PyMem_Del(void *p)

Same as PyMem_Free().

In addition, the following macro sets are provided for calling the Python memory allocator directly, without involving the C API functions listed above. However, note that their use does not preserve binary compatibility across Python versions and is therefore deprecated in extension modules.

PyMem_MALLOC(size)

PyMem_NEW(type, size)

PyMem_REALLOC(ptr, size)

PyMem_RESIZE(ptr, type, size)

PyMem_FREE(ptr)

PyMem_DEL(ptr)

Object allocators

The following function sets, modeled after the ANSI C standard, but specifying behavior when requesting zero bytes, are available for allocating and releasing memory from the Python heap.

By default, these functions use pymalloc memory allocator.

Avertissement

The GIL must be held when using these functions.

void* PyObject_Malloc(size_t n)

Allocates n bytes and returns a pointer of type void* to the allocated memory, or NULL if the request fails.

Requesting zero bytes returns a distinct non-NULL pointer if possible, as if PyObject_Malloc(1) had been called instead. The memory will not have been initialized in any way.

void* PyObject_Calloc(size_t nelem, size_t elsize)

Allocates nelem elements each whose size in bytes is elsize and returns a pointer of type void* to the allocated memory, or NULL if the request fails. The memory is initialized to zeros.

Requesting zero elements or elements of size zero bytes returns a distinct non-NULL pointer if possible, as if PyObject_Calloc(1, 1) had been called instead.

Nouveau dans la version 3.5.

void* PyObject_Realloc(void *p, size_t n)

Resizes the memory block pointed to by p to n bytes. The contents will be unchanged to the minimum of the old and the new sizes.

If p is NULL, the call is equivalent to PyObject_Malloc(n); else if n is equal to zero, the memory block is resized but is not freed, and the returned pointer is non-NULL.

Unless p is NULL, it must have been returned by a previous call to PyObject_Malloc(), PyObject_Realloc() or PyObject_Calloc().

If the request fails, PyObject_Realloc() returns NULL and p remains a valid pointer to the previous memory area.

void PyObject_Free(void *p)

Frees the memory block pointed to by p, which must have been returned by a previous call to PyObject_Malloc(), PyObject_Realloc() or PyObject_Calloc(). Otherwise, or if PyObject_Free(p) has been called before, undefined behavior occurs.

If p is NULL, no operation is performed.

Customize Memory Allocators

Nouveau dans la version 3.4.

PyMemAllocatorEx

Structure used to describe a memory block allocator. The structure has four fields:

Field

Signification

void *ctx

user context passed as first argument

void* malloc(void *ctx, size_t size)

allocate a memory block

void* calloc(void *ctx, size_t nelem, size_t elsize)

allocate a memory block initialized with zeros

void* realloc(void *ctx, void *ptr, size_t new_size)

allocate or resize a memory block

void free(void *ctx, void *ptr)

free a memory block

Modifié dans la version 3.5: The PyMemAllocator structure was renamed to PyMemAllocatorEx and a new calloc field was added.

PyMemAllocatorDomain

Enum used to identify an allocator domain. Domains:

PYMEM_DOMAIN_RAW

Functions:

PyMem_RawMalloc()

PyMem_RawRealloc()

PyMem_RawCalloc()

PyMem_RawFree()

PYMEM_DOMAIN_MEM

Functions:

PyMem_Malloc(),

PyMem_Realloc()

PyMem_Calloc()

PyMem_Free()

PYMEM_DOMAIN_OBJ

Functions:

PyObject_Malloc()

PyObject_Realloc()

PyObject_Calloc()

PyObject_Free()

void PyMem_GetAllocator(PyMemAllocatorDomain domain, PyMemAllocatorEx *allocator)

Get the memory block allocator of the specified domain.

void PyMem_SetAllocator(PyMemAllocatorDomain domain, PyMemAllocatorEx *allocator)

Set the memory block allocator of the specified domain.

The new allocator must return a distinct non-NULL pointer when requesting zero bytes.

For the PYMEM_DOMAIN_RAW domain, the allocator must be thread-safe: the GIL is not held when the allocator is called.

If the new allocator is not a hook (does not call the previous allocator), the PyMem_SetupDebugHooks() function must be called to reinstall the debug hooks on top on the new allocator.

void PyMem_SetupDebugHooks(void)

Setup hooks to detect bugs in the Python memory allocator functions.

Newly allocated memory is filled with the byte 0xCB, freed memory is filled with the byte 0xDB.

Runtime checks:

Detect API violations, ex: PyObject_Free() called on a buffer allocated by PyMem_Malloc()

Detect write before the start of the buffer (buffer underflow)

Detect write after the end of the buffer (buffer overflow)

Check that the GIL is held when allocator functions of PYMEM_DOMAIN_OBJ (ex: PyObject_Malloc()) and PYMEM_DOMAIN_MEM (ex: PyMem_Malloc()) domains are called

On error, the debug hooks use the tracemalloc module to get the traceback where a memory block was allocated. The traceback is only displayed if tracemalloc is tracing Python memory allocations and the memory block was traced.

These hooks are installed by default if Python is compiled in debug mode. The PYTHONMALLOC environment variable can be used to install debug hooks on a Python compiled in release mode.

Modifié dans la version 3.6: This function now also works on Python compiled in release mode. On error, the debug hooks now use tracemalloc to get the traceback where a memory block was allocated. The debug hooks now also check if the GIL is held when functions of PYMEM_DOMAIN_OBJ and PYMEM_DOMAIN_MEM domains are called.

The pymalloc allocator

Python has a pymalloc allocator optimized for small objects (smaller or equal to 512 bytes) with a short lifetime. It uses memory mappings called « arenas » with a fixed size of 256 KB. It falls back to PyMem_RawMalloc() and PyMem_RawRealloc() for allocations larger than 512 bytes.

pymalloc is the default allocator of the PYMEM_DOMAIN_MEM (ex: PyMem_Malloc()) and PYMEM_DOMAIN_OBJ (ex: PyObject_Malloc()) domains.

The arena allocator uses the following functions:

VirtualAlloc() and VirtualFree() on Windows,

mmap() and munmap() if available,

malloc() and free() otherwise.

Customize pymalloc Arena Allocator

Nouveau dans la version 3.4.

PyObjectArenaAllocator

Structure used to describe an arena allocator. The structure has three fields:

Field

Signification

void *ctx

user context passed as first argument

void* alloc(void *ctx, size_t size)

allocate an arena of size bytes

void free(void *ctx, size_t size, void *ptr)

free an arena

PyObject_GetArenaAllocator(PyObjectArenaAllocator *allocator)

Get the arena allocator.

PyObject_SetArenaAllocator(PyObjectArenaAllocator *allocator)

Set the arena allocator.

Exemples

Here is the example from section Aperçu, rewritten so that the I/O buffer is allocated from the Python heap by using the first function set:

PyObject *res;
char *buf = (char *) PyMem_Malloc(BUFSIZ); /* for I/O */

if (buf == NULL)
    return PyErr_NoMemory();
/* ...Do some I/O operation involving buf... */
res = PyBytes_FromString(buf);
PyMem_Free(buf); /* allocated with PyMem_Malloc */
return res;

The same code using the type-oriented function set:

PyObject *res;
char *buf = PyMem_New(char, BUFSIZ); /* for I/O */

if (buf == NULL)
    return PyErr_NoMemory();
/* ...Do some I/O operation involving buf... */
res = PyBytes_FromString(buf);
PyMem_Del(buf); /* allocated with PyMem_New */
return res;

Note that in the two examples above, the buffer is always manipulated via functions belonging to the same set. Indeed, it is required to use the same memory API family for a given memory block, so that the risk of mixing different allocators is reduced to a minimum. The following code sequence contains two errors, one of which is labeled as fatal because it mixes two different allocators operating on different heaps.

char *buf1 = PyMem_New(char, BUFSIZ);
char *buf2 = (char *) malloc(BUFSIZ);
char *buf3 = (char *) PyMem_Malloc(BUFSIZ);
...
PyMem_Del(buf3);  /* Wrong -- should be PyMem_Free() */
free(buf2);       /* Right -- allocated via malloc() */
free(buf1);       /* Fatal -- should be PyMem_Del()  */

In addition to the functions aimed at handling raw memory blocks from the Python heap, objects in Python are allocated and released with PyObject_New(), PyObject_NewVar() and PyObject_Del().

These will be explained in the next chapter on defining and implementing new object types in C.

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Implémentation d’objets

Ce chapitre décrit les fonctions, types, et macros utilisées pour définir de nouveaux types d’objets.

Allouer des objets dans le tas

Common Object Structures

Objets type

Number Object Structures

Mapping Object Structures

Sequence Object Structures

Buffer Object Structures

Async Object Structures

Supporting Cyclic Garbage Collection

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Allouer des objets dans le tas

PyObject* _PyObject_New(PyTypeObject *type)

Return value: New reference.

PyVarObject* _PyObject_NewVar(PyTypeObject *type, Py_ssize_t size)

Return value: New reference.

PyObject* PyObject_Init(PyObject *op, PyTypeObject *type)

Return value: Borrowed reference.

Permet d’initialiser un objet op nouvellement alloué ainsi que son type et sa référence initiale. Renvoie l’objet initialisé. La présence de type indique que l’objet doit être traité par le détecteur d’ordures cycliques, il est de ce fait ajouté à l’ensemble du détecteur d’objets observés. Les autres champs de l’objet ne sont pas affectés.

PyVarObject* PyObject_InitVar(PyVarObject *op, PyTypeObject *type, Py_ssize_t size)

Return value: Borrowed reference.

Ça fait tout ce que PyObject_Init() fait, et il initialise également l’information de la longueur pour un objet de taille variable.

TYPE* PyObject_New(TYPE, PyTypeObject *type)

Return value: New reference.

Alloue un nouvel objet Python en utilisant le type de structure C TYPE et l’objet de type python type. Les champs non définis par l’en-tête de l’objet Python ne sont pas initialisés; le compteur de la référence objet sera un. La taille de l’allocation de la mémoire est déterminé par le champs de l’objet type tp_basicsize.

TYPE* PyObject_NewVar(TYPE, PyTypeObject *type, Py_ssize_t size)

Return value: New reference.

Alloue un nouvel objet Python en utilisant le type de structure C TYPE et l’objet de type Python type. Les champs non définis par l’en-tête de l’objet Python ne sont pas initialisés. La mémoire allouée est suffisante pour pour la structure TYPE plus size champs de la taille donnée par le champ de type tp_itemsize. C’est utile pour l’implémentation d’objets comme les tuples, qui sont capables de déterminer leur taille à la construction. Allouer les champs en même temps que l’objet diminue le nombre d’allocations, améliorant ainsi les performances.

void PyObject_Del(PyObject *op)

Libère la mémoire allouée à un objet utilisant PyObject_New() ou PyObject_NewVar(). C’est normalement appelé par le gestionnaire tp_dealloc spécifié dans le type d’objet. Le champ de l’objet ne devrait pas être accessible après cet appel puisque la mémoire n’est plus un objet Python valide.

PyObject _Py_NoneStruct

Objet qui est visible en tant que None dans Python. Ne devrait être accessible uniquement en utilisant la macro Py_None, qui évalue cet objet à un pointeur.

Voir aussi

PyModule_Create()

Allouer et créer des modules d’extension.

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Common Object Structures

There are a large number of structures which are used in the definition of object types for Python. This section describes these structures and how they are used.

All Python objects ultimately share a small number of fields at the beginning of the object’s representation in memory. These are represented by the PyObject and PyVarObject types, which are defined, in turn, by the expansions of some macros also used, whether directly or indirectly, in the definition of all other Python objects.

PyObject

All object types are extensions of this type. This is a type which contains the information Python needs to treat a pointer to an object as an object. In a normal « release » build, it contains only the object’s reference count and a pointer to the corresponding type object. Nothing is actually declared to be a PyObject, but every pointer to a Python object can be cast to a PyObject*. Access to the members must be done by using the macros Py_REFCNT and Py_TYPE.

PyVarObject

This is an extension of PyObject that adds the ob_size field. This is only used for objects that have some notion of length. This type does not often appear in the Python/C API. Access to the members must be done by using the macros Py_REFCNT, Py_TYPE, and Py_SIZE.

PyObject_HEAD

This is a macro used when declaring new types which represent objects without a varying length. The PyObject_HEAD macro expands to:

PyObject ob_base;

See documentation of PyObject above.

PyObject_VAR_HEAD

This is a macro used when declaring new types which represent objects with a length that varies from instance to instance. The PyObject_VAR_HEAD macro expands to:

PyVarObject ob_base;

See documentation of PyVarObject above.

Py_TYPE(o)

This macro is used to access the ob_type member of a Python object. It expands to:

(((PyObject*)(o))->ob_type)

Py_REFCNT(o)

This macro is used to access the ob_refcnt member of a Python object. It expands to:

(((PyObject*)(o))->ob_refcnt)

Py_SIZE(o)

This macro is used to access the ob_size member of a Python object. It expands to:

(((PyVarObject*)(o))->ob_size)

PyObject_HEAD_INIT(type)

This is a macro which expands to initialization values for a new PyObject type. This macro expands to:

_PyObject_EXTRA_INIT
1, type,

PyVarObject_HEAD_INIT(type, size)

This is a macro which expands to initialization values for a new PyVarObject type, including the ob_size field. This macro expands to:

_PyObject_EXTRA_INIT
1, type, size,

PyCFunction

Type of the functions used to implement most Python callables in C. Functions of this type take two PyObject* parameters and return one such value. If the return value is NULL, an exception shall have been set. If not NULL, the return value is interpreted as the return value of the function as exposed in Python. The function must return a new reference.

PyCFunctionWithKeywords

Type of the functions used to implement Python callables in C that take keyword arguments: they take three PyObject* parameters and return one such value. See PyCFunction above for the meaning of the return value.

PyMethodDef

Structure used to describe a method of an extension type. This structure has four fields:

Field

Type C

Signification

ml_name

char *

name of the method

ml_meth

PyCFunction

pointer to the C implementation

ml_flags

int

flag bits indicating how the call should be constructed

ml_doc

char *

points to the contents of the docstring

The ml_meth is a C function pointer. The functions may be of different types, but they always return PyObject*. If the function is not of the PyCFunction, the compiler will require a cast in the method table. Even though PyCFunction defines the first parameter as PyObject*, it is common that the method implementation uses the specific C type of the self object.

The ml_flags field is a bitfield which can include the following flags. The individual flags indicate either a calling convention or a binding convention. Of the calling convention flags, only METH_VARARGS and METH_KEYWORDS can be combined. Any of the calling convention flags can be combined with a binding flag.

METH_VARARGS

This is the typical calling convention, where the methods have the type PyCFunction. The function expects two PyObject* values. The first one is the self object for methods; for module functions, it is the module object. The second parameter (often called args) is a tuple object representing all arguments. This parameter is typically processed using PyArg_ParseTuple() or PyArg_UnpackTuple().

METH_KEYWORDS

Methods with these flags must be of type PyCFunctionWithKeywords. The function expects three parameters: self, args, and a dictionary of all the keyword arguments. The flag must be combined with METH_VARARGS, and the parameters are typically processed using PyArg_ParseTupleAndKeywords().

METH_NOARGS

Methods without parameters don’t need to check whether arguments are given if they are listed with the METH_NOARGS flag. They need to be of type PyCFunction. The first parameter is typically named self and will hold a reference to the module or object instance. In all cases the second parameter will be NULL.

METH_O

Methods with a single object argument can be listed with the METH_O flag, instead of invoking PyArg_ParseTuple() with a "O" argument. They have the type PyCFunction, with the self parameter, and a PyObject* parameter representing the single argument.

These two constants are not used to indicate the calling convention but the binding when use with methods of classes. These may not be used for functions defined for modules. At most one of these flags may be set for any given method.

METH_CLASS

The method will be passed the type object as the first parameter rather than an instance of the type. This is used to create class methods, similar to what is created when using the classmethod() built-in function.

METH_STATIC

The method will be passed NULL as the first parameter rather than an instance of the type. This is used to create static methods, similar to what is created when using the staticmethod() built-in function.

One other constant controls whether a method is loaded in place of another definition with the same method name.

METH_COEXIST

The method will be loaded in place of existing definitions. Without METH_COEXIST, the default is to skip repeated definitions. Since slot wrappers are loaded before the method table, the existence of a sq_contains slot, for example, would generate a wrapped method named __contains__() and preclude the loading of a corresponding PyCFunction with the same name. With the flag defined, the PyCFunction will be loaded in place of the wrapper object and will co-exist with the slot. This is helpful because calls to PyCFunctions are optimized more than wrapper object calls.

PyMemberDef

Structure which describes an attribute of a type which corresponds to a C struct member. Its fields are:

Field

Type C

Signification

name

char *

name of the member

type

int

the type of the member in the C struct

offset

Py_ssize_t

the offset in bytes that the member is located on the type’s object struct

flags

int

flag bits indicating if the field should be read-only or writable

doc

char *

points to the contents of the docstring

type can be one of many T_ macros corresponding to various C types. When the member is accessed in Python, it will be converted to the equivalent Python type.

Macro name

Type C

T_SHORT

short

T_INT

int

T_LONG

long

T_FLOAT

float

T_DOUBLE

double

T_STRING

char *

T_OBJECT

PyObject *

T_OBJECT_EX

PyObject *

T_CHAR

char

T_BYTE

char

T_UBYTE

unsigned char

T_UINT

unsigned int

T_USHORT

unsigned short

T_ULONG

unsigned long

T_BOOL

char

T_LONGLONG

long long

T_ULONGLONG

unsigned long long

T_PYSSIZET

Py_ssize_t

T_OBJECT and T_OBJECT_EX differ in that T_OBJECT returns None if the member is NULL and T_OBJECT_EX raises an AttributeError. Try to use T_OBJECT_EX over T_OBJECT because T_OBJECT_EX handles use of the del statement on that attribute more correctly than T_OBJECT.

flags can be 0 for write and read access or READONLY for read-only access. Using T_STRING for type implies READONLY. T_STRING data is interpreted as UTF-8. Only T_OBJECT and T_OBJECT_EX members can be deleted. (They are set to NULL).

PyGetSetDef

Structure to define property-like access for a type. See also description of the PyTypeObject.tp_getset slot.

Field

Type C

Signification

name

char *

attribute name

get

getter

C Function to get the attribute

set

setter

optional C function to set or delete the attribute, if omitted the attribute is readonly

doc

char *

optional docstring

closure

void *

optional function pointer, providing additional data for getter and setter

The get function takes one PyObject* parameter (the instance) and a function pointer (the associated closure):

typedef PyObject *(*getter)(PyObject *, void *);

It should return a new reference on success or NULL with a set exception on failure.

set functions take two PyObject* parameters (the instance and the value to be set) and a function pointer (the associated closure):

typedef int (*setter)(PyObject *, PyObject *, void *);

In case the attribute should be deleted the second parameter is NULL. Should return 0 on success or -1 with a set exception on failure.

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Objets type

Perhaps one of the most important structures of the Python object system is the structure that defines a new type: the PyTypeObject structure. Type objects can be handled using any of the PyObject_*() or PyType_*() functions, but do not offer much that’s interesting to most Python applications. These objects are fundamental to how objects behave, so they are very important to the interpreter itself and to any extension module that implements new types.

Type objects are fairly large compared to most of the standard types. The reason for the size is that each type object stores a large number of values, mostly C function pointers, each of which implements a small part of the type’s functionality. The fields of the type object are examined in detail in this section. The fields will be described in the order in which they occur in the structure.

Typedefs: unaryfunc, binaryfunc, ternaryfunc, inquiry, intargfunc, intintargfunc, intobjargproc, intintobjargproc, objobjargproc, destructor, freefunc, printfunc, getattrfunc, getattrofunc, setattrfunc, setattrofunc, reprfunc, hashfunc

The structure definition for PyTypeObject can be found in Include/object.h. For convenience of reference, this repeats the definition found there:

typedef struct _typeobject {
    PyObject_VAR_HEAD
    const char *tp_name; /* For printing, in format "<module>.<name>" */
    Py_ssize_t tp_basicsize, tp_itemsize; /* For allocation */

    /* Methods to implement standard operations */

    destructor tp_dealloc;
    printfunc tp_print;
    getattrfunc tp_getattr;
    setattrfunc tp_setattr;
    PyAsyncMethods *tp_as_async; /* formerly known as tp_compare (Python 2)
                                    or tp_reserved (Python 3) */
    reprfunc tp_repr;

    /* Method suites for standard classes */

    PyNumberMethods *tp_as_number;
    PySequenceMethods *tp_as_sequence;
    PyMappingMethods *tp_as_mapping;

    /* More standard operations (here for binary compatibility) */

    hashfunc tp_hash;
    ternaryfunc tp_call;
    reprfunc tp_str;
    getattrofunc tp_getattro;
    setattrofunc tp_setattro;

    /* Functions to access object as input/output buffer */
    PyBufferProcs *tp_as_buffer;

    /* Flags to define presence of optional/expanded features */
    unsigned long tp_flags;

    const char *tp_doc; /* Documentation string */

    /* call function for all accessible objects */
    traverseproc tp_traverse;

    /* delete references to contained objects */
    inquiry tp_clear;

    /* rich comparisons */
    richcmpfunc tp_richcompare;

    /* weak reference enabler */
    Py_ssize_t tp_weaklistoffset;

    /* Iterators */
    getiterfunc tp_iter;
    iternextfunc tp_iternext;

    /* Attribute descriptor and subclassing stuff */
    struct PyMethodDef *tp_methods;
    struct PyMemberDef *tp_members;
    struct PyGetSetDef *tp_getset;
    struct _typeobject *tp_base;
    PyObject *tp_dict;
    descrgetfunc tp_descr_get;
    descrsetfunc tp_descr_set;
    Py_ssize_t tp_dictoffset;
    initproc tp_init;
    allocfunc tp_alloc;
    newfunc tp_new;
    freefunc tp_free; /* Low-level free-memory routine */
    inquiry tp_is_gc; /* For PyObject_IS_GC */
    PyObject *tp_bases;
    PyObject *tp_mro; /* method resolution order */
    PyObject *tp_cache;
    PyObject *tp_subclasses;
    PyObject *tp_weaklist;
    destructor tp_del;

    /* Type attribute cache version tag. Added in version 2.6 */
    unsigned int tp_version_tag;

    destructor tp_finalize;

} PyTypeObject;

The type object structure extends the PyVarObject structure. The ob_size field is used for dynamic types (created by type_new(), usually called from a class statement). Note that PyType_Type (the metatype) initializes tp_itemsize, which means that its instances (i.e. type objects) must have the ob_size field.

PyObject* PyObject._ob_next

PyObject* PyObject._ob_prev

These fields are only present when the macro Py_TRACE_REFS is defined. Their initialization to NULL is taken care of by the PyObject_HEAD_INIT macro. For statically allocated objects, these fields always remain NULL. For dynamically allocated objects, these two fields are used to link the object into a doubly-linked list of all live objects on the heap. This could be used for various debugging purposes; currently the only use is to print the objects that are still alive at the end of a run when the environment variable PYTHONDUMPREFS is set.

These fields are not inherited by subtypes.

Py_ssize_t PyObject.ob_refcnt

This is the type object’s reference count, initialized to 1 by the PyObject_HEAD_INIT macro. Note that for statically allocated type objects, the type’s instances (objects whose ob_type points back to the type) do not count as references. But for dynamically allocated type objects, the instances do count as references.

This field is not inherited by subtypes.

PyTypeObject* PyObject.ob_type

This is the type’s type, in other words its metatype. It is initialized by the argument to the PyObject_HEAD_INIT macro, and its value should normally be &PyType_Type. However, for dynamically loadable extension modules that must be usable on Windows (at least), the compiler complains that this is not a valid initializer. Therefore, the convention is to pass NULL to the PyObject_HEAD_INIT macro and to initialize this field explicitly at the start of the module’s initialization function, before doing anything else. This is typically done like this:

Foo_Type.ob_type = &PyType_Type;

This should be done before any instances of the type are created. PyType_Ready() checks if ob_type is NULL, and if so, initializes it to the ob_type field of the base class. PyType_Ready() will not change this field if it is non-zero.

This field is inherited by subtypes.

Py_ssize_t PyVarObject.ob_size

For statically allocated type objects, this should be initialized to zero. For dynamically allocated type objects, this field has a special internal meaning.

This field is not inherited by subtypes.

const char* PyTypeObject.tp_name

Pointer to a NUL-terminated string containing the name of the type. For types that are accessible as module globals, the string should be the full module name, followed by a dot, followed by the type name; for built-in types, it should be just the type name. If the module is a submodule of a package, the full package name is part of the full module name. For example, a type named T defined in module M in subpackage Q in package P should have the tp_name initializer "P.Q.M.T".

For dynamically allocated type objects, this should just be the type name, and the module name explicitly stored in the type dict as the value for key '__module__'.

For statically allocated type objects, the tp_name field should contain a dot. Everything before the last dot is made accessible as the __module__ attribute, and everything after the last dot is made accessible as the __name__ attribute.

If no dot is present, the entire tp_name field is made accessible as the __name__ attribute, and the __module__ attribute is undefined (unless explicitly set in the dictionary, as explained above). This means your type will be impossible to pickle. Additionally, it will not be listed in module documentations created with pydoc.

This field is not inherited by subtypes.

Py_ssize_t PyTypeObject.tp_basicsize

Py_ssize_t PyTypeObject.tp_itemsize

These fields allow calculating the size in bytes of instances of the type.

There are two kinds of types: types with fixed-length instances have a zero tp_itemsize field, types with variable-length instances have a non-zero tp_itemsize field. For a type with fixed-length instances, all instances have the same size, given in tp_basicsize.

For a type with variable-length instances, the instances must have an ob_size field, and the instance size is tp_basicsize plus N times tp_itemsize, where N is the « length » of the object. The value of N is typically stored in the instance’s ob_size field. There are exceptions: for example, ints use a negative ob_size to indicate a negative number, and N is abs(ob_size) there. Also, the presence of an ob_size field in the instance layout doesn’t mean that the instance structure is variable-length (for example, the structure for the list type has fixed-length instances, yet those instances have a meaningful ob_size field).

The basic size includes the fields in the instance declared by the macro PyObject_HEAD or PyObject_VAR_HEAD (whichever is used to declare the instance struct) and this in turn includes the _ob_prev and _ob_next fields if they are present. This means that the only correct way to get an initializer for the tp_basicsize is to use the sizeof operator on the struct used to declare the instance layout. The basic size does not include the GC header size.

These fields are inherited separately by subtypes. If the base type has a non-zero tp_itemsize, it is generally not safe to set tp_itemsize to a different non-zero value in a subtype (though this depends on the implementation of the base type).

A note about alignment: if the variable items require a particular alignment, this should be taken care of by the value of tp_basicsize. Example: suppose a type implements an array of double. tp_itemsize is sizeof(double). It is the programmer’s responsibility that tp_basicsize is a multiple of sizeof(double) (assuming this is the alignment requirement for double).

destructor PyTypeObject.tp_dealloc

A pointer to the instance destructor function. This function must be defined unless the type guarantees that its instances will never be deallocated (as is the case for the singletons None and Ellipsis).

The destructor function is called by the Py_DECREF() and Py_XDECREF() macros when the new reference count is zero. At this point, the instance is still in existence, but there are no references to it. The destructor function should free all references which the instance owns, free all memory buffers owned by the instance (using the freeing function corresponding to the allocation function used to allocate the buffer), and finally (as its last action) call the type’s tp_free function. If the type is not subtypable (doesn’t have the Py_TPFLAGS_BASETYPE flag bit set), it is permissible to call the object deallocator directly instead of via tp_free. The object deallocator should be the one used to allocate the instance; this is normally PyObject_Del() if the instance was allocated using PyObject_New() or PyObject_VarNew(), or PyObject_GC_Del() if the instance was allocated using PyObject_GC_New() or PyObject_GC_NewVar().

This field is inherited by subtypes.

printfunc PyTypeObject.tp_print

Reserved slot, formerly used for print formatting in Python 2.x.

getattrfunc PyTypeObject.tp_getattr

An optional pointer to the get-attribute-string function.

This field is deprecated. When it is defined, it should point to a function that acts the same as the tp_getattro function, but taking a C string instead of a Python string object to give the attribute name. The signature is

PyObject * tp_getattr(PyObject *o, char *attr_name);

This field is inherited by subtypes together with tp_getattro: a subtype inherits both tp_getattr and tp_getattro from its base type when the subtype’s tp_getattr and tp_getattro are both NULL.

setattrfunc PyTypeObject.tp_setattr

An optional pointer to the function for setting and deleting attributes.

This field is deprecated. When it is defined, it should point to a function that acts the same as the tp_setattro function, but taking a C string instead of a Python string object to give the attribute name. The signature is

PyObject * tp_setattr(PyObject *o, char *attr_name, PyObject *v);

The v argument is set to NULL to delete the attribute. This field is inherited by subtypes together with tp_setattro: a subtype inherits both tp_setattr and tp_setattro from its base type when the subtype’s tp_setattr and tp_setattro are both NULL.

PyAsyncMethods* tp_as_async

Pointer to an additional structure that contains fields relevant only to objects which implement awaitable and asynchronous iterator protocols at the C-level. See Async Object Structures for details.

Nouveau dans la version 3.5: Formerly known as tp_compare and tp_reserved.

reprfunc PyTypeObject.tp_repr

An optional pointer to a function that implements the built-in function repr().

The signature is the same as for PyObject_Repr(); it must return a string or a Unicode object. Ideally, this function should return a string that, when passed to eval(), given a suitable environment, returns an object with the same value. If this is not feasible, it should return a string starting with '<' and ending with '>' from which both the type and the value of the object can be deduced.

When this field is not set, a string of the form <%s object at %p> is returned, where %s is replaced by the type name, and %p by the object’s memory address.

This field is inherited by subtypes.

PyNumberMethods* tp_as_number

Pointer to an additional structure that contains fields relevant only to objects which implement the number protocol. These fields are documented in Number Object Structures.

The tp_as_number field is not inherited, but the contained fields are inherited individually.

PySequenceMethods* tp_as_sequence

Pointer to an additional structure that contains fields relevant only to objects which implement the sequence protocol. These fields are documented in Sequence Object Structures.

The tp_as_sequence field is not inherited, but the contained fields are inherited individually.

PyMappingMethods* tp_as_mapping

Pointer to an additional structure that contains fields relevant only to objects which implement the mapping protocol. These fields are documented in Mapping Object Structures.

The tp_as_mapping field is not inherited, but the contained fields are inherited individually.

hashfunc PyTypeObject.tp_hash

An optional pointer to a function that implements the built-in function hash().

The signature is the same as for PyObject_Hash(); it must return a value of the type Py_hash_t. The value -1 should not be returned as a normal return value; when an error occurs during the computation of the hash value, the function should set an exception and return -1.

This field can be set explicitly to PyObject_HashNotImplemented() to block inheritance of the hash method from a parent type. This is interpreted as the equivalent of __hash__ = None at the Python level, causing isinstance(o, collections.Hashable) to correctly return False. Note that the converse is also true - setting __hash__ = None on a class at the Python level will result in the tp_hash slot being set to PyObject_HashNotImplemented().

When this field is not set, an attempt to take the hash of the object raises TypeError.

This field is inherited by subtypes together with tp_richcompare: a subtype inherits both of tp_richcompare and tp_hash, when the subtype’s tp_richcompare and tp_hash are both NULL.

ternaryfunc PyTypeObject.tp_call

An optional pointer to a function that implements calling the object. This should be NULL if the object is not callable. The signature is the same as for PyObject_Call().

This field is inherited by subtypes.

reprfunc PyTypeObject.tp_str

An optional pointer to a function that implements the built-in operation str(). (Note that str is a type now, and str() calls the constructor for that type. This constructor calls PyObject_Str() to do the actual work, and PyObject_Str() will call this handler.)

The signature is the same as for PyObject_Str(); it must return a string or a Unicode object. This function should return a « friendly » string representation of the object, as this is the representation that will be used, among other things, by the print() function.

When this field is not set, PyObject_Repr() is called to return a string representation.

This field is inherited by subtypes.

getattrofunc PyTypeObject.tp_getattro

An optional pointer to the get-attribute function.

The signature is the same as for PyObject_GetAttr(). It is usually convenient to set this field to PyObject_GenericGetAttr(), which implements the normal way of looking for object attributes.

This field is inherited by subtypes together with tp_getattr: a subtype inherits both tp_getattr and tp_getattro from its base type when the subtype’s tp_getattr and tp_getattro are both NULL.

setattrofunc PyTypeObject.tp_setattro

An optional pointer to the function for setting and deleting attributes.

The signature is the same as for PyObject_SetAttr(), but setting v to NULL to delete an attribute must be supported. It is usually convenient to set this field to PyObject_GenericSetAttr(), which implements the normal way of setting object attributes.

This field is inherited by subtypes together with tp_setattr: a subtype inherits both tp_setattr and tp_setattro from its base type when the subtype’s tp_setattr and tp_setattro are both NULL.

PyBufferProcs* PyTypeObject.tp_as_buffer

Pointer to an additional structure that contains fields relevant only to objects which implement the buffer interface. These fields are documented in Buffer Object Structures.

The tp_as_buffer field is not inherited, but the contained fields are inherited individually.

unsigned long PyTypeObject.tp_flags

This field is a bit mask of various flags. Some flags indicate variant semantics for certain situations; others are used to indicate that certain fields in the type object (or in the extension structures referenced via tp_as_number, tp_as_sequence, tp_as_mapping, and tp_as_buffer) that were historically not always present are valid; if such a flag bit is clear, the type fields it guards must not be accessed and must be considered to have a zero or NULL value instead.

Inheritance of this field is complicated. Most flag bits are inherited individually, i.e. if the base type has a flag bit set, the subtype inherits this flag bit. The flag bits that pertain to extension structures are strictly inherited if the extension structure is inherited, i.e. the base type’s value of the flag bit is copied into the subtype together with a pointer to the extension structure. The Py_TPFLAGS_HAVE_GC flag bit is inherited together with the tp_traverse and tp_clear fields, i.e. if the Py_TPFLAGS_HAVE_GC flag bit is clear in the subtype and the tp_traverse and tp_clear fields in the subtype exist and have NULL values.

The following bit masks are currently defined; these can be ORed together using the | operator to form the value of the tp_flags field. The macro PyType_HasFeature() takes a type and a flags value, tp and f, and checks whether tp->tp_flags & f is non-zero.

Py_TPFLAGS_HEAPTYPE

This bit is set when the type object itself is allocated on the heap. In this case, the ob_type field of its instances is considered a reference to the type, and the type object is INCREF’ed when a new instance is created, and DECREF’ed when an instance is destroyed (this does not apply to instances of subtypes; only the type referenced by the instance’s ob_type gets INCREF’ed or DECREF’ed).

Py_TPFLAGS_BASETYPE

This bit is set when the type can be used as the base type of another type. If this bit is clear, the type cannot be subtyped (similar to a « final » class in Java).

Py_TPFLAGS_READY

This bit is set when the type object has been fully initialized by PyType_Ready().

Py_TPFLAGS_READYING

This bit is set while PyType_Ready() is in the process of initializing the type object.

Py_TPFLAGS_HAVE_GC

This bit is set when the object supports garbage collection. If this bit is set, instances must be created using PyObject_GC_New() and destroyed using PyObject_GC_Del(). More information in section Supporting Cyclic Garbage Collection. This bit also implies that the GC-related fields tp_traverse and tp_clear are present in the type object.

Py_TPFLAGS_DEFAULT

This is a bitmask of all the bits that pertain to the existence of certain fields in the type object and its extension structures. Currently, it includes the following bits: Py_TPFLAGS_HAVE_STACKLESS_EXTENSION, Py_TPFLAGS_HAVE_VERSION_TAG.

Py_TPFLAGS_LONG_SUBCLASS

Py_TPFLAGS_LIST_SUBCLASS

Py_TPFLAGS_TUPLE_SUBCLASS

Py_TPFLAGS_BYTES_SUBCLASS

Py_TPFLAGS_UNICODE_SUBCLASS

Py_TPFLAGS_DICT_SUBCLASS

Py_TPFLAGS_BASE_EXC_SUBCLASS

Py_TPFLAGS_TYPE_SUBCLASS

These flags are used by functions such as PyLong_Check() to quickly determine if a type is a subclass of a built-in type; such specific checks are faster than a generic check, like PyObject_IsInstance(). Custom types that inherit from built-ins should have their tp_flags set appropriately, or the code that interacts with such types will behave differently depending on what kind of check is used.

Py_TPFLAGS_HAVE_FINALIZE

This bit is set when the tp_finalize slot is present in the type structure.

Nouveau dans la version 3.4.

const char* PyTypeObject.tp_doc

An optional pointer to a NUL-terminated C string giving the docstring for this type object. This is exposed as the __doc__ attribute on the type and instances of the type.

This field is not inherited by subtypes.

traverseproc PyTypeObject.tp_traverse

An optional pointer to a traversal function for the garbage collector. This is only used if the Py_TPFLAGS_HAVE_GC flag bit is set. More information about Python’s garbage collection scheme can be found in section Supporting Cyclic Garbage Collection.

The tp_traverse pointer is used by the garbage collector to detect reference cycles. A typical implementation of a tp_traverse function simply calls Py_VISIT() on each of the instance’s members that are Python objects. For example, this is function local_traverse() from the _thread extension module:

static int
local_traverse(localobject *self, visitproc visit, void *arg)
{
    Py_VISIT(self->args);
    Py_VISIT(self->kw);
    Py_VISIT(self->dict);
    return 0;
}

Note that Py_VISIT() is called only on those members that can participate in reference cycles. Although there is also a self->key member, it can only be NULL or a Python string and therefore cannot be part of a reference cycle.

On the other hand, even if you know a member can never be part of a cycle, as a debugging aid you may want to visit it anyway just so the gc module’s get_referents() function will include it.

Note that Py_VISIT() requires the visit and arg parameters to local_traverse() to have these specific names; don’t name them just anything.

This field is inherited by subtypes together with tp_clear and the Py_TPFLAGS_HAVE_GC flag bit: the flag bit, tp_traverse, and tp_clear are all inherited from the base type if they are all zero in the subtype.

inquiry PyTypeObject.tp_clear

An optional pointer to a clear function for the garbage collector. This is only used if the Py_TPFLAGS_HAVE_GC flag bit is set.

The tp_clear member function is used to break reference cycles in cyclic garbage detected by the garbage collector. Taken together, all tp_clear functions in the system must combine to break all reference cycles. This is subtle, and if in any doubt supply a tp_clear function. For example, the tuple type does not implement a tp_clear function, because it’s possible to prove that no reference cycle can be composed entirely of tuples. Therefore the tp_clear functions of other types must be sufficient to break any cycle containing a tuple. This isn’t immediately obvious, and there’s rarely a good reason to avoid implementing tp_clear.

Implementations of tp_clear should drop the instance’s references to those of its members that may be Python objects, and set its pointers to those members to NULL, as in the following example:

static int
local_clear(localobject *self)
{
    Py_CLEAR(self->key);
    Py_CLEAR(self->args);
    Py_CLEAR(self->kw);
    Py_CLEAR(self->dict);
    return 0;
}

The Py_CLEAR() macro should be used, because clearing references is delicate: the reference to the contained object must not be decremented until after the pointer to the contained object is set to NULL. This is because decrementing the reference count may cause the contained object to become trash, triggering a chain of reclamation activity that may include invoking arbitrary Python code (due to finalizers, or weakref callbacks, associated with the contained object). If it’s possible for such code to reference self again, it’s important that the pointer to the contained object be NULL at that time, so that self knows the contained object can no longer be used. The Py_CLEAR() macro performs the operations in a safe order.

Because the goal of tp_clear functions is to break reference cycles, it’s not necessary to clear contained objects like Python strings or Python integers, which can’t participate in reference cycles. On the other hand, it may be convenient to clear all contained Python objects, and write the type’s tp_dealloc function to invoke tp_clear.

More information about Python’s garbage collection scheme can be found in section Supporting Cyclic Garbage Collection.

This field is inherited by subtypes together with tp_traverse and the Py_TPFLAGS_HAVE_GC flag bit: the flag bit, tp_traverse, and tp_clear are all inherited from the base type if they are all zero in the subtype.

richcmpfunc PyTypeObject.tp_richcompare

An optional pointer to the rich comparison function, whose signature is PyObject *tp_richcompare(PyObject *a, PyObject *b, int op). The first parameter is guaranteed to be an instance of the type that is defined by PyTypeObject.

The function should return the result of the comparison (usually Py_True or Py_False). If the comparison is undefined, it must return Py_NotImplemented, if another error occurred it must return NULL and set an exception condition.

Note

If you want to implement a type for which only a limited set of comparisons makes sense (e.g. == and !=, but not < and friends), directly raise TypeError in the rich comparison function.

This field is inherited by subtypes together with tp_hash: a subtype inherits tp_richcompare and tp_hash when the subtype’s tp_richcompare and tp_hash are both NULL.

The following constants are defined to be used as the third argument for tp_richcompare and for PyObject_RichCompare():

Constante

Comparaison

Py_LT

<

Py_LE

<=

Py_EQ

==

Py_NE

!=

Py_GT

>

Py_GE

>=

Py_ssize_t PyTypeObject.tp_weaklistoffset

If the instances of this type are weakly referenceable, this field is greater than zero and contains the offset in the instance structure of the weak reference list head (ignoring the GC header, if present); this offset is used by PyObject_ClearWeakRefs() and the PyWeakref_*() functions. The instance structure needs to include a field of type PyObject* which is initialized to NULL.

Do not confuse this field with tp_weaklist; that is the list head for weak references to the type object itself.

This field is inherited by subtypes, but see the rules listed below. A subtype may override this offset; this means that the subtype uses a different weak reference list head than the base type. Since the list head is always found via tp_weaklistoffset, this should not be a problem.

When a type defined by a class statement has no __slots__ declaration, and none of its base types are weakly referenceable, the type is made weakly referenceable by adding a weak reference list head slot to the instance layout and setting the tp_weaklistoffset of that slot’s offset.

When a type’s __slots__ declaration contains a slot named __weakref__, that slot becomes the weak reference list head for instances of the type, and the slot’s offset is stored in the type’s tp_weaklistoffset.

When a type’s __slots__ declaration does not contain a slot named __weakref__, the type inherits its tp_weaklistoffset from its base type.

getiterfunc PyTypeObject.tp_iter

An optional pointer to a function that returns an iterator for the object. Its presence normally signals that the instances of this type are iterable (although sequences may be iterable without this function).

This function has the same signature as PyObject_GetIter().

This field is inherited by subtypes.

iternextfunc PyTypeObject.tp_iternext

An optional pointer to a function that returns the next item in an iterator. When the iterator is exhausted, it must return NULL; a StopIteration exception may or may not be set. When another error occurs, it must return NULL too. Its presence signals that the instances of this type are iterators.

Iterator types should also define the tp_iter function, and that function should return the iterator instance itself (not a new iterator instance).

This function has the same signature as PyIter_Next().

This field is inherited by subtypes.

struct PyMethodDef* PyTypeObject.tp_methods

An optional pointer to a static NULL-terminated array of PyMethodDef structures, declaring regular methods of this type.

For each entry in the array, an entry is added to the type’s dictionary (see tp_dict below) containing a method descriptor.

This field is not inherited by subtypes (methods are inherited through a different mechanism).

struct PyMemberDef* PyTypeObject.tp_members

An optional pointer to a static NULL-terminated array of PyMemberDef structures, declaring regular data members (fields or slots) of instances of this type.

For each entry in the array, an entry is added to the type’s dictionary (see tp_dict below) containing a member descriptor.

This field is not inherited by subtypes (members are inherited through a different mechanism).

struct PyGetSetDef* PyTypeObject.tp_getset

An optional pointer to a static NULL-terminated array of PyGetSetDef structures, declaring computed attributes of instances of this type.

For each entry in the array, an entry is added to the type’s dictionary (see tp_dict below) containing a getset descriptor.

This field is not inherited by subtypes (computed attributes are inherited through a different mechanism).

PyTypeObject* PyTypeObject.tp_base

An optional pointer to a base type from which type properties are inherited. At this level, only single inheritance is supported; multiple inheritance require dynamically creating a type object by calling the metatype.

This field is not inherited by subtypes (obviously), but it defaults to &PyBaseObject_Type (which to Python programmers is known as the type object).

PyObject* PyTypeObject.tp_dict

The type’s dictionary is stored here by PyType_Ready().

This field should normally be initialized to NULL before PyType_Ready is called; it may also be initialized to a dictionary containing initial attributes for the type. Once PyType_Ready() has initialized the type, extra attributes for the type may be added to this dictionary only if they don’t correspond to overloaded operations (like __add__()).

This field is not inherited by subtypes (though the attributes defined in here are inherited through a different mechanism).

Avertissement

It is not safe to use PyDict_SetItem() on or otherwise modify tp_dict with the dictionary C-API.

descrgetfunc PyTypeObject.tp_descr_get

An optional pointer to a « descriptor get » function.

The function signature is

PyObject * tp_descr_get(PyObject *self, PyObject *obj, PyObject *type);

This field is inherited by subtypes.

descrsetfunc PyTypeObject.tp_descr_set

An optional pointer to a function for setting and deleting a descriptor’s value.

The function signature is

int tp_descr_set(PyObject *self, PyObject *obj, PyObject *value);

The value argument is set to NULL to delete the value. This field is inherited by subtypes.

Py_ssize_t PyTypeObject.tp_dictoffset

If the instances of this type have a dictionary containing instance variables, this field is non-zero and contains the offset in the instances of the type of the instance variable dictionary; this offset is used by PyObject_GenericGetAttr().

Do not confuse this field with tp_dict; that is the dictionary for attributes of the type object itself.

If the value of this field is greater than zero, it specifies the offset from the start of the instance structure. If the value is less than zero, it specifies the offset from the end of the instance structure. A negative offset is more expensive to use, and should only be used when the instance structure contains a variable-length part. This is used for example to add an instance variable dictionary to subtypes of str or tuple. Note that the tp_basicsize field should account for the dictionary added to the end in that case, even though the dictionary is not included in the basic object layout. On a system with a pointer size of 4 bytes, tp_dictoffset should be set to -4 to indicate that the dictionary is at the very end of the structure.

The real dictionary offset in an instance can be computed from a negative tp_dictoffset as follows:

dictoffset = tp_basicsize + abs(ob_size)*tp_itemsize + tp_dictoffset
if dictoffset is not aligned on sizeof(void*):
    round up to sizeof(void*)

where tp_basicsize, tp_itemsize and tp_dictoffset are taken from the type object, and ob_size is taken from the instance. The absolute value is taken because ints use the sign of ob_size to store the sign of the number. (There’s never a need to do this calculation yourself; it is done for you by _PyObject_GetDictPtr().)

This field is inherited by subtypes, but see the rules listed below. A subtype may override this offset; this means that the subtype instances store the dictionary at a difference offset than the base type. Since the dictionary is always found via tp_dictoffset, this should not be a problem.

When a type defined by a class statement has no __slots__ declaration, and none of its base types has an instance variable dictionary, a dictionary slot is added to the instance layout and the tp_dictoffset is set to that slot’s offset.

When a type defined by a class statement has a __slots__ declaration, the type inherits its tp_dictoffset from its base type.

(Adding a slot named __dict__ to the __slots__ declaration does not have the expected effect, it just causes confusion. Maybe this should be added as a feature just like __weakref__ though.)

initproc PyTypeObject.tp_init

An optional pointer to an instance initialization function.

This function corresponds to the __init__() method of classes. Like __init__(), it is possible to create an instance without calling __init__(), and it is possible to reinitialize an instance by calling its __init__() method again.

The function signature is

int tp_init(PyObject *self, PyObject *args, PyObject *kwds)

The self argument is the instance to be initialized; the args and kwds arguments represent positional and keyword arguments of the call to __init__().

The tp_init function, if not NULL, is called when an instance is created normally by calling its type, after the type’s tp_new function has returned an instance of the type. If the tp_new function returns an instance of some other type that is not a subtype of the original type, no tp_init function is called; if tp_new returns an instance of a subtype of the original type, the subtype’s tp_init is called.

This field is inherited by subtypes.

allocfunc PyTypeObject.tp_alloc

An optional pointer to an instance allocation function.

The function signature is

PyObject *tp_alloc(PyTypeObject *self, Py_ssize_t nitems)

The purpose of this function is to separate memory allocation from memory initialization. It should return a pointer to a block of memory of adequate length for the instance, suitably aligned, and initialized to zeros, but with ob_refcnt set to 1 and ob_type set to the type argument. If the type’s tp_itemsize is non-zero, the object’s ob_size field should be initialized to nitems and the length of the allocated memory block should be tp_basicsize + nitems*tp_itemsize, rounded up to a multiple of sizeof(void*); otherwise, nitems is not used and the length of the block should be tp_basicsize.

Do not use this function to do any other instance initialization, not even to allocate additional memory; that should be done by tp_new.

This field is inherited by static subtypes, but not by dynamic subtypes (subtypes created by a class statement); in the latter, this field is always set to PyType_GenericAlloc(), to force a standard heap allocation strategy. That is also the recommended value for statically defined types.

newfunc PyTypeObject.tp_new

An optional pointer to an instance creation function.

If this function is NULL for a particular type, that type cannot be called to create new instances; presumably there is some other way to create instances, like a factory function.

The function signature is

PyObject *tp_new(PyTypeObject *subtype, PyObject *args, PyObject *kwds)

The subtype argument is the type of the object being created; the args and kwds arguments represent positional and keyword arguments of the call to the type. Note that subtype doesn’t have to equal the type whose tp_new function is called; it may be a subtype of that type (but not an unrelated type).

The tp_new function should call subtype->tp_alloc(subtype, nitems) to allocate space for the object, and then do only as much further initialization as is absolutely necessary. Initialization that can safely be ignored or repeated should be placed in the tp_init handler. A good rule of thumb is that for immutable types, all initialization should take place in tp_new, while for mutable types, most initialization should be deferred to tp_init.

This field is inherited by subtypes, except it is not inherited by static types whose tp_base is NULL or &PyBaseObject_Type.

destructor PyTypeObject.tp_free

An optional pointer to an instance deallocation function. Its signature is freefunc:

void tp_free(void *)

An initializer that is compatible with this signature is PyObject_Free().

This field is inherited by static subtypes, but not by dynamic subtypes (subtypes created by a class statement); in the latter, this field is set to a deallocator suitable to match PyType_GenericAlloc() and the value of the Py_TPFLAGS_HAVE_GC flag bit.

inquiry PyTypeObject.tp_is_gc

An optional pointer to a function called by the garbage collector.

The garbage collector needs to know whether a particular object is collectible or not. Normally, it is sufficient to look at the object’s type’s tp_flags field, and check the Py_TPFLAGS_HAVE_GC flag bit. But some types have a mixture of statically and dynamically allocated instances, and the statically allocated instances are not collectible. Such types should define this function; it should return 1 for a collectible instance, and 0 for a non-collectible instance. The signature is

int tp_is_gc(PyObject *self)

(The only example of this are types themselves. The metatype, PyType_Type, defines this function to distinguish between statically and dynamically allocated types.)

This field is inherited by subtypes.

PyObject* PyTypeObject.tp_bases

Tuple of base types.

This is set for types created by a class statement. It should be NULL for statically defined types.

This field is not inherited.

PyObject* PyTypeObject.tp_mro

Tuple containing the expanded set of base types, starting with the type itself and ending with object, in Method Resolution Order.

This field is not inherited; it is calculated fresh by PyType_Ready().

destructor PyTypeObject.tp_finalize

An optional pointer to an instance finalization function. Its signature is destructor:

void tp_finalize(PyObject *)

If tp_finalize is set, the interpreter calls it once when finalizing an instance. It is called either from the garbage collector (if the instance is part of an isolated reference cycle) or just before the object is deallocated. Either way, it is guaranteed to be called before attempting to break reference cycles, ensuring that it finds the object in a sane state.

tp_finalize should not mutate the current exception status; therefore, a recommended way to write a non-trivial finalizer is:

static void
local_finalize(PyObject *self)
{
    PyObject *error_type, *error_value, *error_traceback;

    /* Save the current exception, if any. */
    PyErr_Fetch(&error_type, &error_value, &error_traceback);

    /* ... */

    /* Restore the saved exception. */
    PyErr_Restore(error_type, error_value, error_traceback);
}

For this field to be taken into account (even through inheritance), you must also set the Py_TPFLAGS_HAVE_FINALIZE flags bit.

This field is inherited by subtypes.

Nouveau dans la version 3.4.

Voir aussi

« Safe object finalization » (PEP 442 [https://www.python.org/dev/peps/pep-0442])

PyObject* PyTypeObject.tp_cache

Unused. Not inherited. Internal use only.

PyObject* PyTypeObject.tp_subclasses

List of weak references to subclasses. Not inherited. Internal use only.

PyObject* PyTypeObject.tp_weaklist

Weak reference list head, for weak references to this type object. Not inherited. Internal use only.

The remaining fields are only defined if the feature test macro COUNT_ALLOCS is defined, and are for internal use only. They are documented here for completeness. None of these fields are inherited by subtypes.

Py_ssize_t PyTypeObject.tp_allocs

Number of allocations.

Py_ssize_t PyTypeObject.tp_frees

Number of frees.

Py_ssize_t PyTypeObject.tp_maxalloc

Maximum simultaneously allocated objects.

PyTypeObject* PyTypeObject.tp_next

Pointer to the next type object with a non-zero tp_allocs field.

Also, note that, in a garbage collected Python, tp_dealloc may be called from any Python thread, not just the thread which created the object (if the object becomes part of a refcount cycle, that cycle might be collected by a garbage collection on any thread). This is not a problem for Python API calls, since the thread on which tp_dealloc is called will own the Global Interpreter Lock (GIL). However, if the object being destroyed in turn destroys objects from some other C or C++ library, care should be taken to ensure that destroying those objects on the thread which called tp_dealloc will not violate any assumptions of the library.

Number Object Structures

PyNumberMethods

This structure holds pointers to the functions which an object uses to implement the number protocol. Each function is used by the function of similar name documented in the Number Protocol section.

Here is the structure definition:

typedef struct {
     binaryfunc nb_add;
     binaryfunc nb_subtract;
     binaryfunc nb_multiply;
     binaryfunc nb_remainder;
     binaryfunc nb_divmod;
     ternaryfunc nb_power;
     unaryfunc nb_negative;
     unaryfunc nb_positive;
     unaryfunc nb_absolute;
     inquiry nb_bool;
     unaryfunc nb_invert;
     binaryfunc nb_lshift;
     binaryfunc nb_rshift;
     binaryfunc nb_and;
     binaryfunc nb_xor;
     binaryfunc nb_or;
     unaryfunc nb_int;
     void *nb_reserved;
     unaryfunc nb_float;

     binaryfunc nb_inplace_add;
     binaryfunc nb_inplace_subtract;
     binaryfunc nb_inplace_multiply;
     binaryfunc nb_inplace_remainder;
     ternaryfunc nb_inplace_power;
     binaryfunc nb_inplace_lshift;
     binaryfunc nb_inplace_rshift;
     binaryfunc nb_inplace_and;
     binaryfunc nb_inplace_xor;
     binaryfunc nb_inplace_or;

     binaryfunc nb_floor_divide;
     binaryfunc nb_true_divide;
     binaryfunc nb_inplace_floor_divide;
     binaryfunc nb_inplace_true_divide;

     unaryfunc nb_index;

     binaryfunc nb_matrix_multiply;
     binaryfunc nb_inplace_matrix_multiply;
} PyNumberMethods;

Note

Binary and ternary functions must check the type of all their operands, and implement the necessary conversions (at least one of the operands is an instance of the defined type). If the operation is not defined for the given operands, binary and ternary functions must return Py_NotImplemented, if another error occurred they must return NULL and set an exception.

Note

The nb_reserved field should always be NULL. It was previously called nb_long, and was renamed in Python 3.0.1.

Mapping Object Structures

PyMappingMethods

This structure holds pointers to the functions which an object uses to implement the mapping protocol. It has three members:

lenfunc PyMappingMethods.mp_length

This function is used by PyMapping_Size() and PyObject_Size(), and has the same signature. This slot may be set to NULL if the object has no defined length.

binaryfunc PyMappingMethods.mp_subscript

This function is used by PyObject_GetItem() and PySequence_GetSlice(), and has the same signature as PyObject_GetItem(). This slot must be filled for the PyMapping_Check() function to return 1, it can be NULL otherwise.

objobjargproc PyMappingMethods.mp_ass_subscript

This function is used by PyObject_SetItem(), PyObject_DelItem(), PyObject_SetSlice() and PyObject_DelSlice(). It has the same signature as PyObject_SetItem(), but v can also be set to NULL to delete an item. If this slot is NULL, the object does not support item assignment and deletion.

Sequence Object Structures

PySequenceMethods

This structure holds pointers to the functions which an object uses to implement the sequence protocol.

lenfunc PySequenceMethods.sq_length

This function is used by PySequence_Size() and PyObject_Size(), and has the same signature. It is also used for handling negative indices via the sq_item and the sq_ass_item slots.

binaryfunc PySequenceMethods.sq_concat

This function is used by PySequence_Concat() and has the same signature. It is also used by the + operator, after trying the numeric addition via the nb_add slot.

ssizeargfunc PySequenceMethods.sq_repeat

This function is used by PySequence_Repeat() and has the same signature. It is also used by the * operator, after trying numeric multiplication via the nb_multiply slot.

ssizeargfunc PySequenceMethods.sq_item

This function is used by PySequence_GetItem() and has the same signature. It is also used by PyObject_GetItem(), after trying the subscription via the mp_subscript slot. This slot must be filled for the PySequence_Check() function to return 1, it can be NULL otherwise.

Negative indexes are handled as follows: if the sq_length slot is filled, it is called and the sequence length is used to compute a positive index which is passed to sq_item. If sq_length is NULL, the index is passed as is to the function.

ssizeobjargproc PySequenceMethods.sq_ass_item

This function is used by PySequence_SetItem() and has the same signature. It is also used by PyObject_SetItem() and PyObject_DelItem(), after trying the item assignment and deletion via the mp_ass_subscript slot. This slot may be left to NULL if the object does not support item assignment and deletion.

objobjproc PySequenceMethods.sq_contains

This function may be used by PySequence_Contains() and has the same signature. This slot may be left to NULL, in this case PySequence_Contains() simply traverses the sequence until it finds a match.

binaryfunc PySequenceMethods.sq_inplace_concat

This function is used by PySequence_InPlaceConcat() and has the same signature. It should modify its first operand, and return it. This slot may be left to NULL, in this case PySequence_InPlaceConcat() will fall back to PySequence_Concat(). It is also used by the augmented assignment +=, after trying numeric inplace addition via the nb_inplace_add slot.

ssizeargfunc PySequenceMethods.sq_inplace_repeat

This function is used by PySequence_InPlaceRepeat() and has the same signature. It should modify its first operand, and return it. This slot may be left to NULL, in this case PySequence_InPlaceRepeat() will fall back to PySequence_Repeat(). It is also used by the augmented assignment *=, after trying numeric inplace multiplication via the nb_inplace_multiply slot.

Buffer Object Structures

PyBufferProcs

This structure holds pointers to the functions required by the Buffer protocol. The protocol defines how an exporter object can expose its internal data to consumer objects.

getbufferproc PyBufferProcs.bf_getbuffer

The signature of this function is:

int (PyObject *exporter, Py_buffer *view, int flags);

Handle a request to exporter to fill in view as specified by flags. Except for point (3), an implementation of this function MUST take these steps:

Check if the request can be met. If not, raise PyExc_BufferError, set view->obj to NULL and return -1.

Fill in the requested fields.

Increment an internal counter for the number of exports.

Set view->obj to exporter and increment view->obj.

Return 0.

If exporter is part of a chain or tree of buffer providers, two main schemes can be used:

Re-export: Each member of the tree acts as the exporting object and sets view->obj to a new reference to itself.

Redirect: The buffer request is redirected to the root object of the tree. Here, view->obj will be a new reference to the root object.

The individual fields of view are described in section Buffer structure, the rules how an exporter must react to specific requests are in section Buffer request types.

All memory pointed to in the Py_buffer structure belongs to the exporter and must remain valid until there are no consumers left. format, shape, strides, suboffsets and internal are read-only for the consumer.

PyBuffer_FillInfo() provides an easy way of exposing a simple bytes buffer while dealing correctly with all request types.

PyObject_GetBuffer() is the interface for the consumer that wraps this function.

releasebufferproc PyBufferProcs.bf_releasebuffer

The signature of this function is:

void (PyObject *exporter, Py_buffer *view);

Handle a request to release the resources of the buffer. If no resources need to be released, PyBufferProcs.bf_releasebuffer may be NULL. Otherwise, a standard implementation of this function will take these optional steps:

Decrement an internal counter for the number of exports.

If the counter is 0, free all memory associated with view.

The exporter MUST use the internal field to keep track of buffer-specific resources. This field is guaranteed to remain constant, while a consumer MAY pass a copy of the original buffer as the view argument.

This function MUST NOT decrement view->obj, since that is done automatically in PyBuffer_Release() (this scheme is useful for breaking reference cycles).

PyBuffer_Release() is the interface for the consumer that wraps this function.

Async Object Structures

Nouveau dans la version 3.5.

PyAsyncMethods

This structure holds pointers to the functions required to implement awaitable and asynchronous iterator objects.

Here is the structure definition:

typedef struct {
    unaryfunc am_await;
    unaryfunc am_aiter;
    unaryfunc am_anext;
} PyAsyncMethods;

unaryfunc PyAsyncMethods.am_await

The signature of this function is:

PyObject *am_await(PyObject *self)

The returned object must be an iterator, i.e. PyIter_Check() must return 1 for it.

This slot may be set to NULL if an object is not an awaitable.

unaryfunc PyAsyncMethods.am_aiter

The signature of this function is:

PyObject *am_aiter(PyObject *self)

Must return an awaitable object. See __anext__() for details.

This slot may be set to NULL if an object does not implement asynchronous iteration protocol.

unaryfunc PyAsyncMethods.am_anext

The signature of this function is:

PyObject *am_anext(PyObject *self)

Must return an awaitable object. See __anext__() for details. This slot may be set to NULL.

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Supporting Cyclic Garbage Collection

Python’s support for detecting and collecting garbage which involves circular references requires support from object types which are « containers » for other objects which may also be containers. Types which do not store references to other objects, or which only store references to atomic types (such as numbers or strings), do not need to provide any explicit support for garbage collection.

To create a container type, the tp_flags field of the type object must include the Py_TPFLAGS_HAVE_GC and provide an implementation of the tp_traverse handler. If instances of the type are mutable, a tp_clear implementation must also be provided.

Py_TPFLAGS_HAVE_GC

Objects with a type with this flag set must conform with the rules documented here. For convenience these objects will be referred to as container objects.

Constructors for container types must conform to two rules:

The memory for the object must be allocated using PyObject_GC_New() or PyObject_GC_NewVar().

Once all the fields which may contain references to other containers are initialized, it must call PyObject_GC_Track().

TYPE* PyObject_GC_New(TYPE, PyTypeObject *type)

Analogous to PyObject_New() but for container objects with the Py_TPFLAGS_HAVE_GC flag set.

TYPE* PyObject_GC_NewVar(TYPE, PyTypeObject *type, Py_ssize_t size)

Analogous to PyObject_NewVar() but for container objects with the Py_TPFLAGS_HAVE_GC flag set.

TYPE* PyObject_GC_Resize(TYPE, PyVarObject *op, Py_ssize_t newsize)

Resize an object allocated by PyObject_NewVar(). Returns the resized object or NULL on failure. op must not be tracked by the collector yet.

void PyObject_GC_Track(PyObject *op)

Adds the object op to the set of container objects tracked by the collector. The collector can run at unexpected times so objects must be valid while being tracked. This should be called once all the fields followed by the tp_traverse handler become valid, usually near the end of the constructor.

void _PyObject_GC_TRACK(PyObject *op)

A macro version of PyObject_GC_Track(). It should not be used for extension modules.

Obsolète depuis la version 3.6: This macro is removed from Python 3.8.

Similarly, the deallocator for the object must conform to a similar pair of rules:

Before fields which refer to other containers are invalidated, PyObject_GC_UnTrack() must be called.

The object’s memory must be deallocated using PyObject_GC_Del().

void PyObject_GC_Del(void *op)

Releases memory allocated to an object using PyObject_GC_New() or PyObject_GC_NewVar().

void PyObject_GC_UnTrack(void *op)

Remove the object op from the set of container objects tracked by the collector. Note that PyObject_GC_Track() can be called again on this object to add it back to the set of tracked objects. The deallocator (tp_dealloc handler) should call this for the object before any of the fields used by the tp_traverse handler become invalid.

void _PyObject_GC_UNTRACK(PyObject *op)

A macro version of PyObject_GC_UnTrack(). It should not be used for extension modules.

Obsolète depuis la version 3.6: This macro is removed from Python 3.8.

The tp_traverse handler accepts a function parameter of this type:

int (*visitproc)(PyObject *object, void *arg)

Type of the visitor function passed to the tp_traverse handler. The function should be called with an object to traverse as object and the third parameter to the tp_traverse handler as arg. The Python core uses several visitor functions to implement cyclic garbage detection; it’s not expected that users will need to write their own visitor functions.

The tp_traverse handler must have the following type:

int (*traverseproc)(PyObject *self, visitproc visit, void *arg)

Traversal function for a container object. Implementations must call the visit function for each object directly contained by self, with the parameters to visit being the contained object and the arg value passed to the handler. The visit function must not be called with a NULL object argument. If visit returns a non-zero value that value should be returned immediately.

To simplify writing tp_traverse handlers, a Py_VISIT() macro is provided. In order to use this macro, the tp_traverse implementation must name its arguments exactly visit and arg:

void Py_VISIT(PyObject *o)

If o is not NULL, call the visit callback, with arguments o and arg. If visit returns a non-zero value, then return it. Using this macro, tp_traverse handlers look like:

static int
my_traverse(Noddy *self, visitproc visit, void *arg)
{
    Py_VISIT(self->foo);
    Py_VISIT(self->bar);
    return 0;
}

The tp_clear handler must be of the inquiry type, or NULL if the object is immutable.

int (*inquiry)(PyObject *self)

Drop references that may have created reference cycles. Immutable objects do not have to define this method since they can never directly create reference cycles. Note that the object must still be valid after calling this method (don’t just call Py_DECREF() on a reference). The collector will call this method if it detects that this object is involved in a reference cycle.

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Version des API et ABI

PY_VERSION_HEX est le numéro de version de Python encodé en un seul entier.

Par exemple si le PY_VERSION_HEX` est défini à  ``0x030401a2, la version d’information sous-jacente peut être trouvée en la traitant comme un nombre sous 32 bits de la manière suivante:

Bytes

Bits (ordre gros-boutiste)

Signification

1

1-8

PY_MAJOR_VERSION (le 3 dans 3.4.1a2)

2

9-16

PY_MINOR_VERSION (le 4 dans 3.4.1a2)

3

17-24

PY_MICRO_VERSION (le 1 dans 3.4.1a2)

4

25-28

PY_RELEASE_LEVEL (0xA pour alpha, 0xB pour bêta, 0xC pour une version candidate et 0xF pour final), dans ce cas c’est alpha.

29-32

PY_RELEASE_SERIAL (le 2 au 3.4.1a2, zéro pour des versions finales)

Ainsi 3.4.1a2 est une hexane-version 0x030401a2.

Toutes les macros données sont définies dans Include/patchlevel.h [https://github.com/python/cpython/tree/3.6/Include/patchlevel.h].

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Distribuer des modules Python

Email

distutils-sig@python.org

En tant que logiciel libre populaire, Python bénéficie d’une communauté active de contributeurs et d’utilisateurs qui rendent à leur tour leurs logiciels disponibles, sous licence libre, pour les autres développeurs Python.

Cela permet aux utilisateurs de Python de partager et de collaborer efficacement, bénéficiant des solutions que les autres ont déjà crées pour résoudre les problèmes communs (ou même, parfois, rares !), aussi que de partager leurs propres solutions à tous.

Ce guide couvre la partie distribution du processus. Pour un guide sur l’installation d’autres projets Python, voir installation guide.

Note

Pour les entreprises et autres institutions, gardez en tête que certaines organisations ont leurs propres règles sur l’utilisation et la contribution au logiciel libre. Prenez ces règles en compte lorsque vous utilisez les outils de distribution et d’installation fournis par Python.

Vocabulaire

le Python Packaging Index [https://pypi.org/pypi] est un dépôt public de paquets sous licence libre rendus disponibles par d’autres utilisateurs Python

le Python Packaging Authority [https://www.pypa.io] est le groupe de développeurs et d’auteurs de documentation responsables de la maintenance et de l’évolution des outils standards de création de paquets, des métadonnées, et des formats de fichiers standards. Ils maintiennent quelques outils, documentation, et gestionnaires de ticket, aussi bien sur GitHub [https://github.com/pypa] que sur BitBucket [https://bitbucket.org/pypa/].

distutils est le premier système de construction et de distribution ajouté à la bibliothèque standard en 1998. Bien que l’utilisation directe de distutils est progressivement supprimée, elle reste le fondement de l’infrastructure actuelle de construction de paquet et de distribution. Au delà de rester dans la bibliothèque standard, son nom vit aussi sous d’autres formes, tel que la liste de diffusion utilisée pour coordonner le développement et les standards de la création de paquet.

setuptools [https://setuptools.readthedocs.io/en/latest/], d’abord publié en 2004, est (en grande partie) le remplaçant de distutils. La nouveauté la plus notable, au delà des outils non modifiés de distutils est la possibilité de déclarer des dépendances à d’autres paquets. C’est l’alternative actuellement recommandée car plus régulièrement mise à jour que distutils et gère mieux les standards de création de paquets actuels, pour un large choix de version de Python.

wheel [https://wheel.readthedocs.org] (dans ce contexte) est un projet qui ajoute la commande bdist_wheel à distutils/setuptools [https://setuptools.readthedocs.io/en/latest/]. Cela produit un paquet binaire multiplateforme (nommé « wheels » ou « wheel files » et définis dans la PEP 427 [https://www.python.org/dev/peps/pep-0427]) qui permet aux bibliothèques Python, même celles incluant des extensions binaires, d’être installées sur un système sans avoir à les compiler localement.

Licence libre et collaboration

Dans la plupart des pays du monde, le logiciel est automatiquement couvert par les droits d’auteur. Cela signifie que les autres développeurs ont besoin d’une autorisation explicite pour copier, utiliser, modifier, et redistribuer le logiciel.

Les licences libres sont un moyen d’autoriser explicitement ces permissions par un moyen relativement cohérent, autorisant les développeurs à partager et collaborer efficacement en rendant des solutions communes à divers problèmes librement disponibles. Cela laisse beaucoup de développeurs libres de dépenser plus de temps concentrés sur des problèmes relativement uniques à leur cas spécifiques.

Les outils de distribution fournis avec Python sont conçus pour rendre la vie des développeurs relativement simple lorsqu’ils souhaitent contribuer, s’il le désirent, à ces ressources communes.

Ces mêmes outils de distribution peuvent aussi être utilisés pour distribuer du logiciel à l’intérieur d’une organisation, que ce soit du logiciel libre ou non.

Installer les outils

La bibliothèque standard n’inclut pas d’outils capable de créer des paquets selon les standards modernes, car l’équipe fondamentale de développement à trouvé qu’il était plus important d’avoir des outils standards qui fonctionnent de manière cohérente, même avec de plus vieilles versions de Python.

Les outils de construction de paquets et de distribution actuellement recommandées peuvent être installées en invoquant le module pip dans une invite de commande :

python -m pip install setuptools wheel twine

Note

Pour les utilisateurs d’environnements POSIX (incluant Mac OS X et les utilisateurs de Linux), ces instructions supposent l’utilisation d’un environnement virtuel.

Pour les utilisateurs de Windows, ces instructions supposent que l’option proposant de modifier la variable d’environnement PATH à été cochée lors de l’installation de Python.

Le Python Packaging User Guide contient plus de détails sur les (en) outils actuellement recommandés [https://packaging.python.org/en/latest/current/#packaging-tool-recommendations].

Lire le manuel

Le Python Packaging User Guide couvre les différentes étapes et les éléments clés de la création d’un projet :

(en) Structure d’un projet

(en) Construire et empaqueter le projet

(en) Téléverser le projet sur le Python Packaging Index

Comment puis-je …?

Ce sont des réponses rapides ou des liens pour certaines tâches courantes.

… choisir un nom pour mon projet ?

Ce n’est pas un sujet facile, mais voici quelques conseils :

vérifiez dans le Python Packaging Index si le nom est déjà utilisé

vérifiez sur quelques sites d’hébergement populaires tels que GitHub, BitBucket, etc pour voir s’il y existe déjà un projet avec ce nom

vérifiez ce qui sort en recherchant sur le web le nom que vous envisagez

évitez les mots trop communs, plus particulièrement ceux ayant plusieurs significations, car pour vos utilisateurs, cela complique la recherche de votre logiciel

… créer et distribuer des extensions binaires ?

C’est un sujet particulièrement compliqué, avec pléthore alternatives disponibles dont le choix dépend de votre objectif exact. Voir le Python Packaging User Guide pour plus d’informations et de recommandations.

Voir aussi

Python Packaging User Guide: Binary Extensions [https://packaging.python.org/en/latest/extensions]

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Installation de modules Python

Email

distutils-sig@python.org

En tant que logiciel libre populaire, Python bénéficie d’une communauté active de contributeurs et d’utilisateurs qui rendent à leur tour leurs logiciels disponibles, sous licence libre, pour les autres développeurs Python.

Cela permet aux utilisateurs de Python de partager et de collaborer efficacement, bénéficiant des solutions que les autres ont déjà crées pour résoudre les problèmes communs (ou même, parfois, rares !), aussi que de partager leurs propres solutions à tous.

Ce guide couvre la partie installation. Pour un guide sur la création et le partage de vos propres projets Python, voyez le guide de distribution.

Note

Pour les entreprises et autres institutions, gardez en tête que certaines organisations ont leurs propres règles sur l’utilisation et la contribution au logiciel libre. Prenez ces règles en compte lorsque vous utilisez les outils de distribution et d’installation fournis par Python.

Vocabulaire

pip est l’outil d’installation de prédilection. À partir de Python 3.4, il est inclus par défaut avec l’installateur de Python.

Un environnement virtuel est un environnement Python semi-isolé qui autorise les paquets à être installés pour une application particulière, plutôt que d’être installés au niveau du système.

venv est l’outil standard pour créer des environnements virtuels, et est intégré à Python depuis la version 3.3. Depuis Python 3.4, il installe aussi pip dans tous les environnements virtuels créés.

virtualenv est une alternative tierce à venv (et son prédécesseur). Elle permet la création d’environnements virtuels pour les versions de Python antérieures à 3.4, qui ne fournissent pas de venv, ou ne sont pas capables d’installer automatiquement pip dans les environnements créés.

L”Index des Paquets Python [https://pypi.org] est un dépôt public des paquets sous licence ouverte disponibles pour tous les utilisateurs Python.

l”Autorité des Paquets Python [https://www.pypa.io/en/latest/] est le groupe de développeurs et d’auteurs de documentation responsable de la maintenance et l’évolution des outils d’empaquetage standards et des métadonnées associées, ainsi que des standards sur les formats de fichiers. Ils maintiennent une multitude d’outils, documentations, et des systèmes de tickets sur GitHub [https://github.com/pypa] et BitBucket [https://bitbucket.org/pypa/].

distutils est le premier système de construction et de distribution ajouté à la bibliothèque standard en 1998. Bien que l’utilisation directe de distutils soit progressivement supprimée, elle reste le fondement de l’infrastructure actuelle de construction de paquet et de distribution. Au-delà de rester dans la bibliothèque standard, son nom vit aussi sous d’autres formes, tel que la liste de diffusion utilisée pour coordonner le développement et les standards de la création de paquet.

Obsolète depuis la version 3.6: pyvenv était l’outil recommandé pour créer des environnements sous Python 3.3 et 3.4, et est obsolète depuis Python 3.6 [https://docs.python.org/dev/whatsnew/3.6.html#deprecated-features].

Modifié dans la version 3.5: L’utilisation de venv est maintenant recommandée pour créer vos environnements virtuels.

Voir aussi

Guide Utilisateur de l’Empaquetage Python : Créer et utiliser des environnements virtuels [https://packaging.python.org/installing/#creating-virtual-environments]

Utilisation de base

Les outils standards de création de paquets sont tous conçus pour être utilisés à partir de la ligne de commande.

La commande suivante va installer la dernière version d’un module et ses dépendances depuis le Python Package Index :

python -m pip install SomePackage

Note

Pour les utilisateurs POSIX (y compris Mac OS X et Linux), les exemples de ce guide supposent l’utilisation d’un environnement virtuel.

Pour les utilisateurs de Windows, les exemples de ce guide supposent que l’option proposant de modifier la variable d’environnement PATH à été cochée lors de l’installation de Python.

Il est aussi possible de préciser une version minimum exacte directement depuis la ligne de commande. Utiliser des caractères de comparaison tel que >, < ou d’autres caractères spéciaux qui sont interprétés par le shell, le nom du paquet et la version doivent être mis entre guillemets :

python -m pip install SomePackage==1.0.4    # specific version
python -m pip install "SomePackage>=1.0.4"  # minimum version

Normalement, si un module approprié est déjà installé, l’installer à nouveau n’aura aucun effet. La mise à jour de modules existants doit être demandée explicitement :

python -m pip install --upgrade SomePackage

Plus d’informations et de ressources concernant pip et ses capacités peuvent être trouvées dans le Python Packaging User Guide [https://packaging.python.org].

La création d’environnements virtuels est réalisée grâce au module venv. Installer des paquets au sein de l’environnement virtuel courant utilise les commandes montrées précédemment.

Voir aussi

Guide Utilisateur de l’Empaquetage Python : Installer les paquets de la distribution Python [https://packaging.python.org/installing/]

Comment puis-je … ?

Ce sont des réponses rapides ou des liens pour certaines tâches courantes.

… Installer pip avec une version de Python antérieures à la 3.4 ?

Python n’a commencé à fournir pip depuis Python 3.4. Pour les versions précédentes, pip a besoin d’être « amorcé » tel que décrit dans le Python Packaging User Guide.

Voir aussi

Guide Utilisateur de l’Empaquetage Python : Pré-requis pour installer des paquets [https://packaging.python.org/installing/#requirements-for-installing-packages]

… Installer des paquets juste pour l’utilisateur actuel ?

Donner l’option --user à python -m pip install lui fera installer un paquet juste pour l’utilisateur en cours, plutôt que pour tous les utilisateurs du système.

… Installer des paquets Python scientifiques ?

Un certain nombre de paquets scientifiques Python ont des dépendances binaires complexes, et ne sont pas actuellement faciles à installer directement avec pip. Pour le moment, il est souvent plus simple pour les utilisateurs d’installer ces paquets par d’autres moyens [https://packaging.python.org/science/] plutôt que d’essayer de les installer avec pip.

Voir aussi

Guide Utilisateur de l’Empaquetage Python : Installer des paquets scientifiques [https://packaging.python.org/science/]

… Travailler avec plusieurs versions de Python installés en parallèle ?

Sous Linux, Max OS X et autres systèmes POSIX, utiliser les commandes Python de la version souhaitée en combinaison avec l’option -m permet de lancer la version appropriée de pip :

python2   -m pip install SomePackage  # default Python 2
python2.7 -m pip install SomePackage  # specifically Python 2.7
python3   -m pip install SomePackage  # default Python 3
python3.4 -m pip install SomePackage  # specifically Python 3.4

Les versions appropriées des commandes pip peuvent aussi être disponibles.

Sous Windows, utilisez le lanceur Python py en combinaison avec l’option -m :

py -2   -m pip install SomePackage  # default Python 2
py -2.7 -m pip install SomePackage  # specifically Python 2.7
py -3   -m pip install SomePackage  # default Python 3
py -3.4 -m pip install SomePackage  # specifically Python 3.4

Les problèmes d’installation typiques

Installer dans le Python du système sur Linux

Sur les systèmes Linux, une installation de Python sera généralement incluse dans le cadre de la distribution. Installer dans cette installation de Python nécessite un accès root sur le système, et peut interférer avec le fonctionnement du gestionnaire de paquets du système et d’autres composants du système si un composant est mis à jour de façon inattendue en utilisant pip.

Sur de tels systèmes, il est souvent préférable d’utiliser un environnement virtuel ou une installation par l’utilisateur lors de l’installation des paquets avec pip.

Pip n’est pas installé

Il est possible que pip ne soit pas installé par défaut. Une solution est :

python -m ensurepip --default-pip

Voir aussi installing pip. [https://packaging.python.org/tutorials/installing-packages/#install-pip-setuptools-and-wheel]

Installation d’extensions binaires

Python a généralement beaucoup misé sur une distribution basée sur les sources, avec laquelle les utilisateurs finaux devaient compiler, lors de l’installation, les modules d’extension à partir des sources.

Avec l’introduction du format binaire wheel, et la possibilité de publier des wheels, pour, au moins Windows et Mac OS X, via le Python Package Index, ce problème devrait diminuer au fil du temps, car les utilisateurs sont plus régulièrement en mesure d’installer des extensions pré-compilées plutôt que de devoir les compiler eux-mêmes.

Certaines solutions pour installer des paquets scientifiques [https://packaging.python.org/science/] qui ne sont pas encore disponibles comme wheel pré-construites peuvent aussi aider à obtenir d’autres extensions binaires sans devoir les construire localement.

Voir aussi

Guide Utilisateur de l’Empaquetage Python : Extensions binaires [https://packaging.python.org/extensions/]

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Les HOWTOs de Python

les Guides Pratique Python sont des documents couvrant chacun un sujet unique et spécifique de la manière la plus complète possible. Créés à partir de la suite Documentation Project’s HOWTO Linux, cette suite essaie de promouvoir les documentations plus détaillées que la Python Library Reference.

Actuellement, les HOWTOs sont :

Portage de code Python 2 vers Python 3

Portage des modules d’extension vers Python 3

Curses Programming with Python

Guide pour l’utilisation des descripteurs

Guide pratique : programmation fonctionnelle

Tutoriel sur la journalisation

Logging Cookbook

Guide des expressions régulières

Socket Programming HOWTO

Guide pour le tri

Guide Unicode

HOWTO Fetch Internet Resources Using The urllib Package

Tutoriel argparse

Introduction au module ipaddress

Argument Clinic How-To

Instrumenter CPython avec DTrace et SystemTap

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Portage de code Python 2 vers Python 3

auteur

Brett Cannon

Résumé

Python 3 étant le futur de Python tandis que Python 2 est encore activement utilisé, il est préférable de faire en sorte que votre projet soit disponible pour les deux versions majeures de Python. Ce guide est destiné à vous aider à comprendre comment gérer simultanément Python 2 & 3.

Si vous cherchez à porter un module d’extension plutôt que du pur Python, veuillez consulter Portage des modules d’extension vers Python 3.

Si vous souhaitez lire l’avis d’un développeur principal de Python sur ce qui a motivé la création de Python 3, vous pouvez lire le Python 3 Q & A [https://ncoghlan-devs-python-notes.readthedocs.org/en/latest/python3/questions_and_answers.html] de Nick Coghlan ou bien Why Python 3 exists [http://www.snarky.ca/why-python-3-exists] de Brett Cannon.

Vous pouvez solliciter par courriel l’aide de la liste de diffusion python-porting [https://mail.python.org/mailman/listinfo/python-porting] pour vos questions liées au portage.

La version courte

Afin de rendre votre projet compatible Python 2/3 avec le même code source, les étapes de base sont :

Ne se préoccuper que du support de Python 2.7

S’assurer d’une bonne couverture des tests (coverage.py [https://pypi.org/project/coverage] peut aider ; pip install coverage)

Apprendre les différences entre Python 2 et 3

Utiliser Futurize [http://python-future.org/automatic_conversion.html] (ou Modernize [https://python-modernize.readthedocs.org/en/latest/]) pour mettre à jour votre code (par exemple pip install future)

Utilisez Pylint [https://pypi.org/project/pylint] pour vous assurer que vous ne régressez pas sur votre prise en charge de Python 3 (pip install pylint)

Utiliser caniusepython3 [https://pypi.org/project/caniusepython3] pour déterminer quelles sont, parmi les dépendances que vous utilisez, celles qui bloquent votre utilisation de Python 3 (pip install caniusepython3)

Une fois que vos dépendances ne sont plus un obstacle, utiliser l’intégration continue pour s’assurer que votre code demeure compatible Python 2 & 3 (tox [https://pypi.org/project/tox] peut aider à tester la comptabilité de sources avec plusieurs versions de Python; pip install tox)

Envisager l’utilisation d’un vérifieur de type statique afin de vous assurer que votre façon d’utiliser les types est compatible avec Python 2 et 3 (par exemple en utilisant mypy [http://mypy-lang.org/] pour vérifier votre typage sous Python 2 et 3).

Détails

Un point clé du support simultané de Python 2 et 3 est qu’il vous est possible de commencer dès aujourd’hui ! Même si vos dépendances ne sont pas encore compatibles Python 3, vous pouvez moderniser votre code dès maintenant pour gérer Python 3. La plupart des modifications nécessaires à la compatibilité Python 3 donnent un code plus propre utilisant une syntaxe plus récente, même dans du code Python 2.

Un autre point important est que la modernisation de votre code Python 2 pour le rendre compatible Python 3 est pratiquement automatique. Bien qu’il soit possible d’avoir à effectuer des changements d’API compte-tenu de la clarification de la gestion des données textuelles et binaires dans Python 3, le travail de bas niveau est en grande partie fait pour vous et vous pouvez ainsi bénéficiez de ces modifications automatiques immédiatement.

Gardez ces points-clés en tête pendant que vous lisez les détails ci-dessous concernant le portage de votre code vers une compatibilité simultanée Python 2 et 3.

Abandon de la compatibilité Python 2.6 et antérieures

Bien qu’il soit possible de rendre Python 2.5 compatible avec Python 3, il est beaucoup plus simple de n’avoir qu’à travailler avec Python 2.7. Si abandonner Python 2.5 n’est pas une option, alors le projet six [https://pypi.org/project/six] peut vous aider à gérer simultanément Python 2.5 et 3 (pip install six). Néanmoins, soyez conscient que la quasi-totalité des projets listés dans ce guide pratique ne seront pas applicables à votre situation.

Si vous pouvez ignorer Python 2.5 et antérieur, les changements nécessaires à appliquer à votre code devraient encore ressembler à vos yeux à du code Python idiomatique. Dans le pire cas, vous devrez utiliser une fonction plutôt qu’une méthode dans certains cas, ou bien vous devrez importer une fonction plutôt qu’utiliser une fonction native, mais le reste du temps le code transformé devrait vous rester familier.

Mais nous vous conseillons de viser seulement un support de Python 2.7. Python 2.6 n’est plus supporté gratuitement et par conséquent ne reçoit plus aucun correctif. Cela signifie que vous devrez trouver des solutions de contournement aux problèmes que vous rencontrez avec Python 2.6. Il existe en outre des outils mentionnés dans ce guide pratique qui ne supportent pas Python 2.6 (par exemple Pylint [https://pypi.org/project/pylint]), ce qui sera de plus en plus courant au fil du temps. Il est simplement plus facile pour vous de n’assurer une compatibilité qu’avec les versions de Python que vous avez l’obligation de gérer.

Assurez vous de spécifier la bonne version supportée dans le fichier setup.py

Votre fichier setup.py devrait contenir le bon trove classifier [https://pypi.org/classifiers] spécifiant les versions de Python avec lesquelles vous êtes compatible. Comme votre projet ne supporte pas encore Python 3, vous devriez au moins spécifier Programming Language :: Python :: 2 :: Only. Dans l’idéal vous devriez indiquer chaque version majeure/mineure de Python que vous gérez, par exemple Programming Language :: Python :: 2.7.

Obtenir une bonne couverture de code

Une fois que votre code est compatible avec la plus ancienne version de Python 2 que vous souhaitez, vous devez vous assurer que votre suite de test a une couverture suffisante. Une bonne règle empirique consiste à avoir suffisamment confiance en la suite de test pour qu’une erreur apparaissant après la réécriture du code par les outils automatiques résulte de bogues de ces derniers et non de votre code. Si vous souhaitez une valeur cible, essayez de dépasser les 80 % de couverture (et ne vous sentez pas coupable si vous trouvez difficile de faire mieux que 90 % de couverture). Si vous ne disposez pas encore d’un outil pour mesurer la couverture de code, coverage.py [https://pypi.org/project/coverage] est recommandé.

Apprendre les différences entre Python 2 et 3

Une fois que votre code est bien testé, vous êtes prêt à démarrer votre portage vers Python 3 ! Mais afin de comprendre comment votre code va changer et à quoi s’intéresser spécifiquement pendant que vous codez, vous aurez sûrement envie de découvrir quels sont les changements introduits par Python 3 par rapport à Python 2. Pour atteindre cet objectif, les deux meilleurs moyens sont de lire le document « What’s New » [https://docs.python.org/3/whatsnew/index.html] de chaque version de Python 3 et le livre Porting to Python 3 [http://python3porting.com/] (gratuit en ligne). Il y a également une cheat sheet [http://python-future.org/compatible_idioms.html] très pratique du projet Python-Future.

Mettre à jour votre code

Une fois que vous pensez en savoir suffisamment sur les différences entre Python 3 et Python 2, il est temps de mettre à jour votre code ! Vous avez le choix entre deux outils pour porter votre code automatiquement : Futurize [http://python-future.org/automatic_conversion.html] et Modernize [https://python-modernize.readthedocs.org/en/latest/]. Le choix de l’outil dépend de la dose de Python 3 que vous souhaitez introduire dans votre code. Futurize [http://python-future.org/automatic_conversion.html] s’efforce d’introduire les idiomes et pratiques de Python 3 dans Python 2, par exemple en réintroduisant le type bytes de Python 3 de telle sorte que la sémantique soit identique entre les deux versions majeures de Python. En revanche, Modernize [https://python-modernize.readthedocs.org/en/latest/] est plus conservateur et vise un sous-ensemble d’instructions Python 2/3, en s’appuyant directement sur six [https://pypi.org/project/six] pour la compatibilité. Python 3 étant le futur de Python, il pourrait être préférable d’utiliser Futurize afin de commencer à s’ajuster aux nouvelles pratiques introduites par Python 3 avec lesquelles vous n’êtes pas encore habitué.

Indépendamment de l’outil sur lequel se porte votre choix, celui-ci mettra à jour votre code afin qu’il puisse être exécuté par Python 3 tout en maintenant sa compatibilité avec la version de Python 2 dont vous êtes parti. En fonction du niveau de prudence que vous visez, vous pouvez exécuter l’outil sur votre suite de test d’abord puis inspecter visuellement la différence afin de vous assurer que la transformation est exacte. Après avoir transformé votre suite de test et vérifié que tous les tests s’exécutent comme attendu, vous pouvez transformer le code de votre application avec l’assurance que chaque test qui échoue correspond à un échec de traduction.

Malheureusement les outils ne peuvent pas automatiser tous les changements requis pour permettre à votre code de s’exécuter sous Python 3 et il y a donc quelques points sur lesquels vous devrez travailler manuellement afin d’atteindre la compatibilité totale Python 3 (les étapes nécessaires peuvent varier en fonction de l’outil utilisé). Lisez la documentation de l’outil que vous avez choisi afin d’identifier ce qu’il corrige par défaut et ce qui peut être appliqué de façon optionnelle afin de savoir ce qui sera (ou non) corrigé pour vous ou ce que vous devrez modifier vous-même (par exemple, le remplacement io.open() plutôt que la fonction native open() est inactif par défaut dans Modernize). Heureusement, il n’y a que quelques points à surveiller qui peuvent réellement être considérés comme des problèmes difficiles à déboguer si vous n’y prêtez pas attention.

Division

Dans Python 3, 5 / 2 == 2.5 et non 2; toutes les divisions entre des valeurs int renvoient un float. Ce changement était en réalité planifié depuis Python 2.2, publié en 2002. Depuis cette date, les utilisateurs ont été encouragés à ajouter from __future__ import division à tous les fichiers utilisant les opérateurs / et // ou à exécuter l’interpréteur avec l’option -Q. Si vous n’avez pas suivi cette recommandation, vous devrez manuellement modifier votre code et effectuer deux changements :

Ajouter from __future__ import division à vos fichiers

Remplacer tous les opérateurs de division par // pour la division entière, le cas échant, ou utiliser / et vous attendre à un résultat flottant

La raison pour laquelle / n’est pas simplement remplacé par // automatiquement est que si un objet définit une méthode __truediv__ mais pas de méthode __floordiv__, alors votre code pourrait produire une erreur (par exemple, une classe définie par l’utilisateur qui utilise / pour définir une opération quelconque mais pour laquelle // n’a pas du tout la même signification, voire n’est pas utilisé du tout).

Texte et données binaires

Dans Python 2, il était possible d’utiliser le type str pour du texte et pour des données binaires. Malheureusement cet amalgame entre deux concepts différents peut conduire à du code fragile pouvant parfois fonctionner pour les deux types de données et parfois non. Cela a également conduit à des API confuses si les auteurs ne déclaraient pas explicitement que quelque chose qui acceptait str était compatible avec du texte ou des données binaires et pas un seul des deux types. Cela a compliqué la situation pour les personnes devant gérer plusieurs langages avec des API qui ne se préoccupaient pas de la gestion de unicode lorsqu’elles affirmaient être compatibles avec des données au format texte.

Afin de rendre la distinction entre texte et données binaires claire et prononcée, Python 3 a suivi la voie pavée par la plupart des langages créés à l’ère d’Internet et a séparé les types texte et données binaires de telle sorte qu’il ne soit plus possible de les confondre (Python est antérieur à la démocratisation de l’accès à Internet). Cette séparation ne pose pas de problème pour du code ne gérant soit que du texte, soit que des données binaires. Cependant un code source devant gérer les deux doit désormais se préoccuper du type des données manipulées, ce qui explique que ce processus ne peut pas être entièrement automatisé.

Pour commencer, vous devrez choisir quelles API travaillent sur du texte et lesquelles travaillent avec des données binaires (il est fortement recommandé de ne pas concevoir d’API qui gèrent les deux types compte-tenu de la difficulté supplémentaire que cela induit). Dans Python 2, cela signifie s’assurer que les API recevant du texte en entrée peuvent gérer unicode et celles qui reçoivent des données binaires fonctionnent avec le type bytes de Python 3 (qui est un sous-ensemble de str dans Python 2 et opère comme un alias du type bytes de Python 2). En général, le principal problème consiste à inventorier quelles méthodes existent et opèrent sur quel type dans Python & 3 simultanément (pour le texte, il s’agit de unicode dans Python 2 et str dans Python 3, pour le binaire il s’agit de str/bytes dans Python 2 et bytes dans Python 3). Le tableau ci-dessous liste les méthodes spécifiques à chaque type de données dans Python 2 et 3 (par exemple, la méthode decode() peut être utilisée sur des données binaires équivalentes en Python 2 et 3, mais ne peut pas être utilisée de la même façon sur le type texte en Python 2 et 3 car le type str de Python 3 ne possède pas de telle méthode). Notez que depuis Python 3.5, la méthode __mod__ a été ajoutée au type bytes.

Format texte

Format binaire

decode

encode

format

isdecimal

isnumeric

Vous pouvez rendre le problème plus simple à gérer en réalisant les opérations d’encodage et de décodage entre données binaires et texte aux extrémités de votre code. Cela signifie que lorsque vous recevez du texte dans un format binaire, vous devez immédiatement le décoder. À l’inverse si votre code doit transmettre du texte sous forme binaire, encodez-le le plus tard possible. Cela vous permet de ne manipuler que du texte à l’intérieur de votre code et permet de ne pas se préoccuper du type des données sur lesquelles vous travaillez.

Le point suivant est de s’assurer que vous savez quelles chaînes de caractères littérales de votre code correspondent à du texte ou à du binaire. Vous devez préfixer par b tous les littéraux qui représentent des données binaires et par u les littéraux qui représentent du texte (il existe une importation du module __future__ permettant de forcer l’encodage de toutes les chaînes de caractères littérales non spécifiées en Unicode, mais cette pratique s’est avérée moins efficace que l’ajout explicite des préfixe b et u).

Une conséquence de cette dichotomie est que vous devez être prudents lors de l’ouverture d’un fichier. À moins que vous travailliez sous Windows, il y a des chances pour que vous ne vous soyez jamais préoccupé de spécifier le mode b lorsque vous ouvrez des fichiers binaires (par exemple rb pour lire un fichier binaire). Sous Python 3, les fichiers binaire et texte sont distincts et mutuellement incompatibles ; se référer au module io pour plus de détails. Ainsi vous devez décider lorsque vous ouvrez un fichier si vous y accéderez en mode binaire (ce qui permet de lire et écrire des données binaires) ou en mode texte (ce qui permet de lire et écrire du texte). Vous devez également utiliser io.open() pour ouvrir des fichiers plutôt que la fonction native open() étant donné que le module io est cohérent de Python 2 à 3, ce qui n’est pas vrai pour la fonction open() (en Python 3, il s’agit en réalité de io.open()). Ne cherchez pas à appliquer l’ancienne pratique consistant à utiliser codecs.open() qui n’est nécessaire que pour préserver une compatibilité avec Python 2.5.

Les constructeurs des types str et bytes possèdent une sémantique différente pour les mêmes arguments sous Python 2 et 3. Passer un entier à bytes sous Python 2 produit une représentation de cet entier en chaîne de caractères : bytes(3) == '3'. Mais sous Python 3, fournir un argument entier à bytes produit un objet bytes de la longueur de l’entier spécifié, rempli par des octets nuls : bytes(3) == b'\x00\x00\x00'. La même prudence est nécessaire lorsque vous passez un objet bytes à str. En Python 2, vous récupérez simplement l’objet bytes initial : str(b'3') == b'3'. Mais en Python 3, vous récupérez la représentation en chaîne de caractères de l’objet bytes : str(b'3') == "b'3'".

Enfin, l’indiçage des données binaires exige une manipulation prudente (bien que le découpage, ou slicing en anglais, ne nécessite pas d’attention particulière). En Python 2, b'123'[1] == b'2' tandis qu’en Python 3 b'123'[1] == 50. Puisque les données binaires ne sont simplement qu’une collection de nombres en binaire, Python 3 renvoie la valeur entière de l’octet indicé. Mais en Python 2, étant donné que bytes == str, l’indiçage renvoie une tranche de longueur 1 de bytes. Le projet six [https://pypi.org/project/six] dispose d’une fonction appelée six.indexbytes() qui renvoie un entier comme en Python 3 : six.indexbytes(b'123', 1).

Pour résumer :

Décidez lesquelles de vos API travaillent sur du texte et lesquelles travaillent sur des données binaires

Assurez vous que votre code travaillant sur du texte fonctionne aussi avec le type unicode et que le code travaillant sur du binaire fonctionne avec le type bytes en Python 2 (voir le tableau ci-dessus pour la liste des méthodes utilisables par chaque type)

Préfixez tous vos littéraux binaires par b et toutes vos chaînes de caractères littérales par u

Décodez les données binaires en texte dès que possible, encodez votre texte au format binaire le plus tard possible

Ouvrez les fichiers avec la fonction io.open() et assurez-vous de spécifier le mode b le cas échéant

Utilisez avec prudence l’indiçage sur des données binaires

Utilisez la détection de fonctionnalités plutôt que la détection de version

Vous rencontrerez inévitablement du code devant décider quoi faire en fonction de la version de Python qui s’exécute. La meilleure façon de gérer ce cas est de détecter si les fonctionnalités dont vous avez besoin sont gérées par la version de Python sous laquelle le code s’exécute. Si pour certaines raisons cela ne fonctionne pas, alors vous devez tester si votre version est Python 2 et non Python 3. Afin de clarifier cette pratique, voici un exemple.

Supposons que vous avez besoin d’accéder à une fonctionnalité de importlib [https://docs.python.org/3/library/importlib.html#module-importlib] qui n’est disponible dans la bibliothèque standard de Python que depuis la version 3.3 et est disponible pour Python 2 via le module importlib2 [https://pypi.org/project/importlib2] sur PyPI. Vous pourriez être tenté d’écrire un code qui accède, par exemple, au module importlib.abc avec l’approche suivante :

import sys

if sys.version_info[0] == 3:
    from importlib import abc
else:
    from importlib2 import abc

Le problème est le suivant : que se passe-t-il lorsque Python 4 est publié ? Il serait préférable de traiter le cas Python 2 comme l’exception plutôt que Python 3 et de supposer que les versions futures de Python 2 seront plus compatibles avec Python 3 qu’avec Python 2 :

import sys

if sys.version_info[0] > 2:
    from importlib import abc
else:
    from importlib2 import abc

Néanmoins la meilleure solution est de ne pas chercher à déterminer la version de Python mais plutôt à détecter les fonctionnalités disponibles. Cela évite les problèmes potentiels liés aux erreurs de détection de version et facilite la compatibilité future :

try:
    from importlib import abc
except ImportError:
    from importlib2 import abc

Prévenir les régressions de compatibilité

Une fois votre code traduit pour être compatible avec Python 3, vous devez vous assurer que votre code n’a pas régressé ou qu’il ne fonctionne pas sous Python 3. Ceci est particulièrement important si une de vos dépendances vous empêche de réellement exécuter le code sous Python 3 pour le moment.

Afin de vous aider à maintenir la compatibilité, nous préconisons que tous les nouveaux modules que vous créez aient au moins le bloc de code suivant en en-tête :

from __future__ import absolute_import
from __future__ import division
from __future__ import print_function

Vous pouvez également lancer Python 2 avec le paramètre -3 afin d’être alerté en cas de divers problèmes de compatibilité que votre code déclenche durant son exécution. Si vous transformez les avertissements en erreur avec -Werror, vous pouvez être certain que ne passez pas accidentellement à côté d’un avertissement.

Vous pouvez également utiliser le projet Pylint [https://pypi.org/project/pylint] et son option --py3k afin de modifier votre code pour recevoir des avertissements lorsque celui-ci dévie de la compatibilité Python 3. Cela vous évite par ailleurs d’appliquer Modernize [https://python-modernize.readthedocs.org/en/latest/] ou Futurize [http://python-future.org/automatic_conversion.html] sur votre code régulièrement pour détecter des régressions liées à la compatibilité. Cependant cela nécessite de votre part le support de Python 2.7 et Python 3.4 ou ultérieur étant donné qu’il s’agit de la version minimale gérée par Pylint.

Vérifier quelles dépendances empêchent la migration

Après avoir rendu votre code compatible avec Python 3, vous devez commencer à vous intéresser au portage de vos dépendances. Le projet caniusepython3 [https://pypi.org/project/caniusepython3] a été créé afin de vous aider à déterminer quels projets sont bloquants dans votre support de Python 3, directement ou indirectement. Il existe un outil en ligne de commande ainsi qu’une interface web : https://caniusepython3.com.

Le projet fournit également du code intégrable dans votre suite de test qui déclenchera un échec de test lorsque plus aucune de vos dépendances n’est bloquante pour l’utilisation de Python 3. Cela vous permet de ne pas avoir à vérifier manuellement vos dépendances et d’être notifié rapidement quand vous pouvez exécuter votre application avec Python 3.

Mettre à jour votre fichier setup.py pour spécifier la compatibilité avec Python 3

Une fois que votre code fonctionne sous Python 3, vous devez mettre à jour vos classeurs dans votre setup.py pour inclure Programming Language :: Python :: 3 et non seulement le support de Python 2. Cela signifiera à quiconque utilise votre code que vous gérez Python 2 et 3. Dans l’idéal vous devrez aussi ajouter une mention pour chaque version majeure/mineure de Python que vous supportez désormais.

Utiliser l’intégration continue pour maintenir la compatibilité

Une fois que vous êtes en mesure d’exécuter votre code sous Python 3, vous devrez vous assurer que celui-ci fonctionne toujours pour Python 2 & 3. tox [https://pypi.org/project/tox] est vraisemblablement le meilleur outil pour exécuter vos tests avec plusieurs interpréteurs Python. Vous pouvez alors intégrer tox à votre système d’intégration continue afin de ne jamais accidentellement casser votre gestion de Python 2 ou 3.

Vous pouvez également utiliser l’option -bb de l’interpréteur Python 3 afin de déclencher une exception lorsque vous comparez des bytes à des chaînes de caractères ou à un entier (cette deuxième possibilité est disponible à partir de Python 3.5). Par défaut, des comparaisons entre types différents renvoient simplement False mais si vous avez fait une erreur dans votre séparation de la gestion texte/données binaires ou votre indiçage des bytes, vous ne trouverez pas facilement le bogue. Ce drapeau lève une exception lorsque ce genre de comparaison apparaît, facilitant ainsi son identification et sa localisation.

Et c’est à peu près tout ! Une fois ceci fait, votre code source est compatible avec Python 2 et 3 simultanément. Votre suite de test est également en place de telle sorte que vous ne cassiez pas la compatibilité Python 2 ou 3 indépendamment de la version que vous utilisez pendant le développement.

Envisager l’utilisation d’un vérificateur de type statique optionnel

Une autre façon de faciliter le portage de votre code est d’utiliser un vérificateur de type statique comme mypy [http://mypy-lang.org/] ou pytype [https://github.com/google/pytype]. Ces outils peuvent être utilisés pour analyser votre code comme s’il était exécuté sous Python 2, puis une seconde fois comme s’il était exécuté sous Python 3. L’utilisation double d’un vérificateur de type statique de cette façon permet de détecter si, par exemple, vous faites une utilisation inappropriée des types de données binaires dans une version de Python par rapport à l’autre. Si vous ajoutez les indices optionnels de typage à votre code, vous pouvez alors explicitement déclarer que vos API attendent des données binaires ou du texte, ce qui facilite alors la vérification du comportement de votre code dans les deux versions de Python.

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Portage des modules d’extension vers Python 3

auteur

Benjamin Peterson

Résumé

Changer l’API C n’était pas l’un des objectifs de Python 3, cependant les nombreux changements au niveau Python ont rendu impossible de garder l’API de Python 2 comme elle était. Certains changements tels que l’unification de int() et long() sont plus apparents au niveau C. Ce document s’efforce de documenter les incompatibilités et la façon dont elles peuvent être contournées.

Compilation conditionnelle

La façon la plus simple de compiler seulement une section de code pour Python 3 est de vérifier si PY_MAJOR_VERSION est supérieur ou égal à 3. :

#if PY_MAJOR_VERSION >= 3
#define IS_PY3K
#endif

Les fonctions manquantes dans l’API peuvent être remplacées par des alias à leurs équivalents dans des blocs conditionnels.

Modifications apportées aux API des objets

Python 3 a fusionné certains types avec des fonctions identiques tout en séparant de façon propre, d’autres.

Unification de str et unicode

Le type str() de Python 3 est l’équivalent de unicode() sous Python 2 ; Les fonctions C sont appelées PyUnicode_* pour les deux versions. L’ancien type de chaîne de caractères de 8 bits est devenue bytes(), avec des fonctions C nommées PyBytes_*. Python 2.6 et toutes les versions supérieures fournissent un en-tête de compatibilité, bytesobject.h, faisant correspondre les noms PyBytes aux PyString. Pour une meilleure compatibilité avec Python 3, PyUnicode doit être utilisé seulement pour des données textuelles et PyBytes pour des données binaires. Il est important de noter que PyBytes et PyUnicode en Python 3 ne sont pas remplaçables contrairement à PyString et PyUnicode dans Python 2. L’exemple suivant montre l’utilisation optimale de PyUnicode, PyString, et PyBytes.

#include "stdlib.h"
#include "Python.h"
#include "bytesobject.h"

/* text example */
static PyObject *
say_hello(PyObject *self, PyObject *args) {
    PyObject *name, *result;

    if (!PyArg_ParseTuple(args, "U:say_hello", &name))
        return NULL;

    result = PyUnicode_FromFormat("Hello, %S!", name);
    return result;
}

/* just a forward */
static char * do_encode(PyObject *);

/* bytes example */
static PyObject *
encode_object(PyObject *self, PyObject *args) {
    char *encoded;
    PyObject *result, *myobj;

    if (!PyArg_ParseTuple(args, "O:encode_object", &myobj))
        return NULL;

    encoded = do_encode(myobj);
    if (encoded == NULL)
        return NULL;
    result = PyBytes_FromString(encoded);
    free(encoded);
    return result;
}

Unification de long et int

Python 3 n’a qu’un type d’entier, int(). Mais il correspond au type long() de Python 2 — le type int() utilisé dans Python 2 a été supprimé. Dans l’API C, les fonctions PyInt_* sont remplacées par leurs équivalents PyLong_*.

Initialisation et état du module

Python 3 a remanié son système d’initialisation des modules d’extension (Voir PEP 3121 [https://www.python.org/dev/peps/pep-3121].). Au lieu de stocker les états de module dans les variables globales, les états doivent être stockés dans une structure spécifique à l’interpréteur. Créer des modules qui ont un fonctionnement correct en Python 2 et Python 3 est délicat. L’exemple suivant montre comment.

#include "Python.h"

struct module_state {
    PyObject *error;
};

#if PY_MAJOR_VERSION >= 3
#define GETSTATE(m) ((struct module_state*)PyModule_GetState(m))
#else
#define GETSTATE(m) (&_state)
static struct module_state _state;
#endif

static PyObject *
error_out(PyObject *m) {
    struct module_state *st = GETSTATE(m);
    PyErr_SetString(st->error, "something bad happened");
    return NULL;
}

static PyMethodDef myextension_methods[] = {
    {"error_out", (PyCFunction)error_out, METH_NOARGS, NULL},
    {NULL, NULL}
};

#if PY_MAJOR_VERSION >= 3

static int myextension_traverse(PyObject *m, visitproc visit, void *arg) {
    Py_VISIT(GETSTATE(m)->error);
    return 0;
}

static int myextension_clear(PyObject *m) {
    Py_CLEAR(GETSTATE(m)->error);
    return 0;
}

static struct PyModuleDef moduledef = {
        PyModuleDef_HEAD_INIT,
        "myextension",
        NULL,
        sizeof(struct module_state),
        myextension_methods,
        NULL,
        myextension_traverse,
        myextension_clear,
        NULL
};

#define INITERROR return NULL

PyMODINIT_FUNC
PyInit_myextension(void)

#else
#define INITERROR return

void
initmyextension(void)
#endif
{
#if PY_MAJOR_VERSION >= 3
    PyObject *module = PyModule_Create(&moduledef);
#else
    PyObject *module = Py_InitModule("myextension", myextension_methods);
#endif

    if (module == NULL)
        INITERROR;
    struct module_state *st = GETSTATE(module);

    st->error = PyErr_NewException("myextension.Error", NULL, NULL);
    if (st->error == NULL) {
        Py_DECREF(module);
        INITERROR;
    }

#if PY_MAJOR_VERSION >= 3
    return module;
#endif
}

CObject remplacé par Capsule

L’objet Capsule a été introduit dans Python 3.1 et 2.7 pour remplacer CObject. Le type CObject était utile, mais son API posait des soucis : elle ne permettait pas la distinction entre les objets C valides, ce qui permettait aux objets C assortis incorrectement de planter l’interpréteur, et certaines des API s’appuyaient sur un comportement indéfini en C. (Pour plus de détails sur la logique de Capsules, veuillez consulter bpo-5630 [https://bugs.python.org/issue5630]).

Si vous utilisez actuellement CObjects et que vous voulez migrer vers la version 3.1 ou plus récente, vous devrez passer à Capsules. CObject est déprécié dans 3.1 et 2.7 et est supprimé dans Python 3.2. Si vous ne gérez que les versions 2.7, ou 3.1 et supérieures, vous pouvez simplement passer à Capsule. Si vous avez besoin de gérer Python 3.0, ou des versions de Python antérieures à 2.7, vous devez gérer CObjects et Capsules. (Notez que Python 3.0 n’est plus maintenu, et qu’il n’est pas recommandé pour une utilisation en production).

L’exemple suivant d’en-tête de fichier capsulethunk.h peut résoudre le problème. Il suffit d’écrire votre code dans l’API Capsule et d’inclure ce fichier d’en-tête après Python.h. Votre code utilisera automatiquement Capsules dans les versions de Python avec Capsules, et passera à CObjects lorsque les Capsules ne sont pas disponibles.

capsulethunk.h reproduit le fonctionnement de Capsules en utilisant CObjects. Cependant, CObject ne permet pas de stocker le « nom » de la capsule. Les objets simulés Capsule créés par capsulethunk.h se comportent légèrement différemment des véritables Capsules. Ainsi :

Le paramètre name passé à PyCapsule_New() est ignoré.

Le paramètre name passé à PyCapsule_IsValid() et PyCapsule_GetPointer() est ignoré et il n’y a pas de vérification d’erreur du nom.

PyCapsule_GetName() renvoie toujours un NULL.

PyCapsule_SetName() lève toujours une exception et renvoie un échec. Note : Puisqu’il n’y a aucun moyen de stocker un nom dans un CObject, l’échec verbeux de PyCapsule_SetName() a été jugé préférable à un échec non-verbeux dans ce cas. Si cela ne vous convenait pas, vous pouvez modifier votre copie locale selon vos besoins.

Vous pouvez trouver capsulethunk.h dans la distribution source de Python comme Doc/includes/capsulethunk.h [https://github.com/python/cpython/tree/3.6/Doc/includes/capsulethunk.h]. Nous l’incluons ici pour votre confort :

#ifndef __CAPSULETHUNK_H
#define __CAPSULETHUNK_H

#if (    (PY_VERSION_HEX <  0x02070000) \
     || ((PY_VERSION_HEX >= 0x03000000) \
      && (PY_VERSION_HEX <  0x03010000)) )

#define __PyCapsule_GetField(capsule, field, default_value) \
    ( PyCapsule_CheckExact(capsule) \
        ? (((PyCObject *)capsule)->field) \
        : (default_value) \
    ) \

#define __PyCapsule_SetField(capsule, field, value) \
    ( PyCapsule_CheckExact(capsule) \
        ? (((PyCObject *)capsule)->field = value), 1 \
        : 0 \
    ) \

#define PyCapsule_Type PyCObject_Type

#define PyCapsule_CheckExact(capsule) (PyCObject_Check(capsule))
#define PyCapsule_IsValid(capsule, name) (PyCObject_Check(capsule))

#define PyCapsule_New(pointer, name, destructor) \
    (PyCObject_FromVoidPtr(pointer, destructor))

#define PyCapsule_GetPointer(capsule, name) \
    (PyCObject_AsVoidPtr(capsule))

/* Don't call PyCObject_SetPointer here, it fails if there's a destructor */
#define PyCapsule_SetPointer(capsule, pointer) \
    __PyCapsule_SetField(capsule, cobject, pointer)

#define PyCapsule_GetDestructor(capsule) \
    __PyCapsule_GetField(capsule, destructor)

#define PyCapsule_SetDestructor(capsule, dtor) \
    __PyCapsule_SetField(capsule, destructor, dtor)

/*
 * Sorry, there's simply no place
 * to store a Capsule "name" in a CObject.
 */
#define PyCapsule_GetName(capsule) NULL

static int
PyCapsule_SetName(PyObject *capsule, const char *unused)
{
    unused = unused;
    PyErr_SetString(PyExc_NotImplementedError,
        "can't use PyCapsule_SetName with CObjects");
    return 1;
}

#define PyCapsule_GetContext(capsule) \
    __PyCapsule_GetField(capsule, descr)

#define PyCapsule_SetContext(capsule, context) \
    __PyCapsule_SetField(capsule, descr, context)

static void *
PyCapsule_Import(const char *name, int no_block)
{
    PyObject *object = NULL;
    void *return_value = NULL;
    char *trace;
    size_t name_length = (strlen(name) + 1) * sizeof(char);
    char *name_dup = (char *)PyMem_MALLOC(name_length);

    if (!name_dup) {
        return NULL;
    }

    memcpy(name_dup, name, name_length);

    trace = name_dup;
    while (trace) {
        char *dot = strchr(trace, '.');
        if (dot) {
            *dot++ = '\0';
        }

        if (object == NULL) {
            if (no_block) {
                object = PyImport_ImportModuleNoBlock(trace);
            } else {
                object = PyImport_ImportModule(trace);
                if (!object) {
                    PyErr_Format(PyExc_ImportError,
                        "PyCapsule_Import could not "
                        "import module \"%s\"", trace);
                }
            }
        } else {
            PyObject *object2 = PyObject_GetAttrString(object, trace);
            Py_DECREF(object);
            object = object2;
        }
        if (!object) {
            goto EXIT;
        }

        trace = dot;
    }

    if (PyCObject_Check(object)) {
        PyCObject *cobject = (PyCObject *)object;
        return_value = cobject->cobject;
    } else {
        PyErr_Format(PyExc_AttributeError,
            "PyCapsule_Import \"%s\" is not valid",
            name);
    }

EXIT:
    Py_XDECREF(object);
    if (name_dup) {
        PyMem_FREE(name_dup);
    }
    return return_value;
}

#endif /* #if PY_VERSION_HEX < 0x02070000 */

#endif /* __CAPSULETHUNK_H */

Autres options

Si vous écrivez un nouveau module d’extension, vous pouvez envisager d’utiliser Cython [http://cython.org/]. Il traduit un langage de type Python en C. Les modules d’extension qu’il crée sont compatibles avec Python 3 et Python 2.

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Curses Programming with Python

Auteur

A.M. Kuchling, Eric S. Raymond

Version

2.04

Résumé

This document describes how to use the curses extension module to control text-mode displays.

What is curses?

The curses library supplies a terminal-independent screen-painting and keyboard-handling facility for text-based terminals; such terminals include VT100s, the Linux console, and the simulated terminal provided by various programs. Display terminals support various control codes to perform common operations such as moving the cursor, scrolling the screen, and erasing areas. Different terminals use widely differing codes, and often have their own minor quirks.

In a world of graphical displays, one might ask « why bother »? It’s true that character-cell display terminals are an obsolete technology, but there are niches in which being able to do fancy things with them are still valuable. One niche is on small-footprint or embedded Unixes that don’t run an X server. Another is tools such as OS installers and kernel configurators that may have to run before any graphical support is available.

The curses library provides fairly basic functionality, providing the programmer with an abstraction of a display containing multiple non-overlapping windows of text. The contents of a window can be changed in various ways—adding text, erasing it, changing its appearance—and the curses library will figure out what control codes need to be sent to the terminal to produce the right output. curses doesn’t provide many user-interface concepts such as buttons, checkboxes, or dialogs; if you need such features, consider a user interface library such as Urwid [https://pypi.org/project/urwid/].

The curses library was originally written for BSD Unix; the later System V versions of Unix from AT&T added many enhancements and new functions. BSD curses is no longer maintained, having been replaced by ncurses, which is an open-source implementation of the AT&T interface. If you’re using an open-source Unix such as Linux or FreeBSD, your system almost certainly uses ncurses. Since most current commercial Unix versions are based on System V code, all the functions described here will probably be available. The older versions of curses carried by some proprietary Unixes may not support everything, though.

The Windows version of Python doesn’t include the curses module. A ported version called UniCurses [https://pypi.org/project/UniCurses] is available. You could also try the Console module [http://effbot.org/zone/console-index.htm] written by Fredrik Lundh, which doesn’t use the same API as curses but provides cursor-addressable text output and full support for mouse and keyboard input.

The Python curses module

The Python module is a fairly simple wrapper over the C functions provided by curses; if you’re already familiar with curses programming in C, it’s really easy to transfer that knowledge to Python. The biggest difference is that the Python interface makes things simpler by merging different C functions such as addstr(), mvaddstr(), and mvwaddstr() into a single addstr() method. You’ll see this covered in more detail later.

This HOWTO is an introduction to writing text-mode programs with curses and Python. It doesn’t attempt to be a complete guide to the curses API; for that, see the Python library guide’s section on ncurses, and the C manual pages for ncurses. It will, however, give you the basic ideas.

Starting and ending a curses application

Before doing anything, curses must be initialized. This is done by calling the initscr() function, which will determine the terminal type, send any required setup codes to the terminal, and create various internal data structures. If successful, initscr() returns a window object representing the entire screen; this is usually called stdscr after the name of the corresponding C variable.

import curses
stdscr = curses.initscr()

Usually curses applications turn off automatic echoing of keys to the screen, in order to be able to read keys and only display them under certain circumstances. This requires calling the noecho() function.

curses.noecho()

Applications will also commonly need to react to keys instantly, without requiring the Enter key to be pressed; this is called cbreak mode, as opposed to the usual buffered input mode.

curses.cbreak()

Terminals usually return special keys, such as the cursor keys or navigation keys such as Page Up and Home, as a multibyte escape sequence. While you could write your application to expect such sequences and process them accordingly, curses can do it for you, returning a special value such as curses.KEY_LEFT. To get curses to do the job, you’ll have to enable keypad mode.

stdscr.keypad(True)

Terminating a curses application is much easier than starting one. You’ll need to call:

curses.nocbreak()
stdscr.keypad(False)
curses.echo()

to reverse the curses-friendly terminal settings. Then call the endwin() function to restore the terminal to its original operating mode.

curses.endwin()

A common problem when debugging a curses application is to get your terminal messed up when the application dies without restoring the terminal to its previous state. In Python this commonly happens when your code is buggy and raises an uncaught exception. Keys are no longer echoed to the screen when you type them, for example, which makes using the shell difficult.

In Python you can avoid these complications and make debugging much easier by importing the curses.wrapper() function and using it like this:

from curses import wrapper

def main(stdscr):
    # Clear screen
    stdscr.clear()

    # This raises ZeroDivisionError when i == 10.
    for i in range(0, 11):
        v = i-10
        stdscr.addstr(i, 0, '10 divided by {} is {}'.format(v, 10/v))

    stdscr.refresh()
    stdscr.getkey()

wrapper(main)

The wrapper() function takes a callable object and does the initializations described above, also initializing colors if color support is present. wrapper() then runs your provided callable. Once the callable returns, wrapper() will restore the original state of the terminal. The callable is called inside a try…except that catches exceptions, restores the state of the terminal, and then re-raises the exception. Therefore your terminal won’t be left in a funny state on exception and you’ll be able to read the exception’s message and traceback.

Windows and Pads

Windows are the basic abstraction in curses. A window object represents a rectangular area of the screen, and supports methods to display text, erase it, allow the user to input strings, and so forth.

The stdscr object returned by the initscr() function is a window object that covers the entire screen. Many programs may need only this single window, but you might wish to divide the screen into smaller windows, in order to redraw or clear them separately. The newwin() function creates a new window of a given size, returning the new window object.

begin_x = 20; begin_y = 7
height = 5; width = 40
win = curses.newwin(height, width, begin_y, begin_x)

Note that the coordinate system used in curses is unusual. Coordinates are always passed in the order y,x, and the top-left corner of a window is coordinate (0,0). This breaks the normal convention for handling coordinates where the x coordinate comes first. This is an unfortunate difference from most other computer applications, but it’s been part of curses since it was first written, and it’s too late to change things now.

Your application can determine the size of the screen by using the curses.LINES and curses.COLS variables to obtain the y and x sizes. Legal coordinates will then extend from (0,0) to (curses.LINES - 1, curses.COLS - 1).

When you call a method to display or erase text, the effect doesn’t immediately show up on the display. Instead you must call the refresh() method of window objects to update the screen.

This is because curses was originally written with slow 300-baud terminal connections in mind; with these terminals, minimizing the time required to redraw the screen was very important. Instead curses accumulates changes to the screen and displays them in the most efficient manner when you call refresh(). For example, if your program displays some text in a window and then clears the window, there’s no need to send the original text because they’re never visible.

In practice, explicitly telling curses to redraw a window doesn’t really complicate programming with curses much. Most programs go into a flurry of activity, and then pause waiting for a keypress or some other action on the part of the user. All you have to do is to be sure that the screen has been redrawn before pausing to wait for user input, by first calling stdscr.refresh() or the refresh() method of some other relevant window.

A pad is a special case of a window; it can be larger than the actual display screen, and only a portion of the pad displayed at a time. Creating a pad requires the pad’s height and width, while refreshing a pad requires giving the coordinates of the on-screen area where a subsection of the pad will be displayed.

pad = curses.newpad(100, 100)
# These loops fill the pad with letters; addch() is
# explained in the next section
for y in range(0, 99):
    for x in range(0, 99):
        pad.addch(y,x, ord('a') + (x*x+y*y) % 26)

# Displays a section of the pad in the middle of the screen.
# (0,0) : coordinate of upper-left corner of pad area to display.
# (5,5) : coordinate of upper-left corner of window area to be filled
#         with pad content.
# (20, 75) : coordinate of lower-right corner of window area to be
#          : filled with pad content.
pad.refresh( 0,0, 5,5, 20,75)

The refresh() call displays a section of the pad in the rectangle extending from coordinate (5,5) to coordinate (20,75) on the screen; the upper left corner of the displayed section is coordinate (0,0) on the pad. Beyond that difference, pads are exactly like ordinary windows and support the same methods.

If you have multiple windows and pads on screen there is a more efficient way to update the screen and prevent annoying screen flicker as each part of the screen gets updated. refresh() actually does two things:

Calls the noutrefresh() method of each window to update an underlying data structure representing the desired state of the screen.

Calls the function doupdate() function to change the physical screen to match the desired state recorded in the data structure.

Instead you can call noutrefresh() on a number of windows to update the data structure, and then call doupdate() to update the screen.

Displaying Text

From a C programmer’s point of view, curses may sometimes look like a twisty maze of functions, all subtly different. For example, addstr() displays a string at the current cursor location in the stdscr window, while mvaddstr() moves to a given y,x coordinate first before displaying the string. waddstr() is just like addstr(), but allows specifying a window to use instead of using stdscr by default. mvwaddstr() allows specifying both a window and a coordinate.

Fortunately the Python interface hides all these details. stdscr is a window object like any other, and methods such as addstr() accept multiple argument forms. Usually there are four different forms.

Form

Description

str or ch

Display the string str or character ch at the current position

str or ch, attr

Display the string str or character ch, using attribute attr at the current position

y, x, str or ch

Move to position y,x within the window, and display str or ch

y, x, str or ch, attr

Move to position y,x within the window, and display str or ch, using attribute attr

Attributes allow displaying text in highlighted forms such as boldface, underline, reverse code, or in color. They’ll be explained in more detail in the next subsection.

The addstr() method takes a Python string or bytestring as the value to be displayed. The contents of bytestrings are sent to the terminal as-is. Strings are encoded to bytes using the value of the window’s encoding attribute; this defaults to the default system encoding as returned by locale.getpreferredencoding().

The addch() methods take a character, which can be either a string of length 1, a bytestring of length 1, or an integer.

Constants are provided for extension characters; these constants are integers greater than 255. For example, ACS_PLMINUS is a +/- symbol, and ACS_ULCORNER is the upper left corner of a box (handy for drawing borders). You can also use the appropriate Unicode character.

Windows remember where the cursor was left after the last operation, so if you leave out the y,x coordinates, the string or character will be displayed wherever the last operation left off. You can also move the cursor with the move(y,x) method. Because some terminals always display a flashing cursor, you may want to ensure that the cursor is positioned in some location where it won’t be distracting; it can be confusing to have the cursor blinking at some apparently random location.

If your application doesn’t need a blinking cursor at all, you can call curs_set(False) to make it invisible. For compatibility with older curses versions, there’s a leaveok(bool) function that’s a synonym for curs_set(). When bool is true, the curses library will attempt to suppress the flashing cursor, and you won’t need to worry about leaving it in odd locations.

Attributes and Color

Characters can be displayed in different ways. Status lines in a text-based application are commonly shown in reverse video, or a text viewer may need to highlight certain words. curses supports this by allowing you to specify an attribute for each cell on the screen.

An attribute is an integer, each bit representing a different attribute. You can try to display text with multiple attribute bits set, but curses doesn’t guarantee that all the possible combinations are available, or that they’re all visually distinct. That depends on the ability of the terminal being used, so it’s safest to stick to the most commonly available attributes, listed here.

Attribut

Description

A_BLINK

Blinking text

A_BOLD

Extra bright or bold text

A_DIM

Half bright text

A_REVERSE

Reverse-video text

A_STANDOUT

The best highlighting mode available

A_UNDERLINE

Underlined text

So, to display a reverse-video status line on the top line of the screen, you could code:

stdscr.addstr(0, 0, "Current mode: Typing mode",
              curses.A_REVERSE)
stdscr.refresh()

The curses library also supports color on those terminals that provide it. The most common such terminal is probably the Linux console, followed by color xterms.

To use color, you must call the start_color() function soon after calling initscr(), to initialize the default color set (the curses.wrapper() function does this automatically). Once that’s done, the has_colors() function returns TRUE if the terminal in use can actually display color. (Note: curses uses the American spelling “color”, instead of the Canadian/British spelling “colour”. If you’re used to the British spelling, you’ll have to resign yourself to misspelling it for the sake of these functions.)

The curses library maintains a finite number of color pairs, containing a foreground (or text) color and a background color. You can get the attribute value corresponding to a color pair with the color_pair() function; this can be bitwise-OR’ed with other attributes such as A_REVERSE, but again, such combinations are not guaranteed to work on all terminals.

An example, which displays a line of text using color pair 1:

stdscr.addstr("Pretty text", curses.color_pair(1))
stdscr.refresh()

As I said before, a color pair consists of a foreground and background color. The init_pair(n, f, b) function changes the definition of color pair n, to foreground color f and background color b. Color pair 0 is hard-wired to white on black, and cannot be changed.

Colors are numbered, and start_color() initializes 8 basic colors when it activates color mode. They are: 0:black, 1:red, 2:green, 3:yellow, 4:blue, 5:magenta, 6:cyan, and 7:white. The curses module defines named constants for each of these colors: curses.COLOR_BLACK, curses.COLOR_RED, and so forth.

Let’s put all this together. To change color 1 to red text on a white background, you would call:

curses.init_pair(1, curses.COLOR_RED, curses.COLOR_WHITE)

When you change a color pair, any text already displayed using that color pair will change to the new colors. You can also display new text in this color with:

stdscr.addstr(0,0, "RED ALERT!", curses.color_pair(1))

Very fancy terminals can change the definitions of the actual colors to a given RGB value. This lets you change color 1, which is usually red, to purple or blue or any other color you like. Unfortunately, the Linux console doesn’t support this, so I’m unable to try it out, and can’t provide any examples. You can check if your terminal can do this by calling can_change_color(), which returns True if the capability is there. If you’re lucky enough to have such a talented terminal, consult your system’s man pages for more information.

User Input

The C curses library offers only very simple input mechanisms. Python’s curses module adds a basic text-input widget. (Other libraries such as Urwid [https://pypi.org/project/urwid/] have more extensive collections of widgets.)

There are two methods for getting input from a window:

getch() refreshes the screen and then waits for the user to hit a key, displaying the key if echo() has been called earlier. You can optionally specify a coordinate to which the cursor should be moved before pausing.

getkey() does the same thing but converts the integer to a string. Individual characters are returned as 1-character strings, and special keys such as function keys return longer strings containing a key name such as KEY_UP or ^G.

It’s possible to not wait for the user using the nodelay() window method. After nodelay(True), getch() and getkey() for the window become non-blocking. To signal that no input is ready, getch() returns curses.ERR (a value of -1) and getkey() raises an exception. There’s also a halfdelay() function, which can be used to (in effect) set a timer on each getch(); if no input becomes available within a specified delay (measured in tenths of a second), curses raises an exception.

The getch() method returns an integer; if it’s between 0 and 255, it represents the ASCII code of the key pressed. Values greater than 255 are special keys such as Page Up, Home, or the cursor keys. You can compare the value returned to constants such as curses.KEY_PPAGE, curses.KEY_HOME, or curses.KEY_LEFT. The main loop of your program may look something like this:

while True:
    c = stdscr.getch()
    if c == ord('p'):
        PrintDocument()
    elif c == ord('q'):
        break  # Exit the while loop
    elif c == curses.KEY_HOME:
        x = y = 0

The curses.ascii module supplies ASCII class membership functions that take either integer or 1-character string arguments; these may be useful in writing more readable tests for such loops. It also supplies conversion functions that take either integer or 1-character-string arguments and return the same type. For example, curses.ascii.ctrl() returns the control character corresponding to its argument.

There’s also a method to retrieve an entire string, getstr(). It isn’t used very often, because its functionality is quite limited; the only editing keys available are the backspace key and the Enter key, which terminates the string. It can optionally be limited to a fixed number of characters.

curses.echo()            # Enable echoing of characters

# Get a 15-character string, with the cursor on the top line
s = stdscr.getstr(0,0, 15)

The curses.textpad module supplies a text box that supports an Emacs-like set of keybindings. Various methods of the Textbox class support editing with input validation and gathering the edit results either with or without trailing spaces. Here’s an example:

import curses
from curses.textpad import Textbox, rectangle

def main(stdscr):
    stdscr.addstr(0, 0, "Enter IM message: (hit Ctrl-G to send)")

    editwin = curses.newwin(5,30, 2,1)
    rectangle(stdscr, 1,0, 1+5+1, 1+30+1)
    stdscr.refresh()

    box = Textbox(editwin)

    # Let the user edit until Ctrl-G is struck.
    box.edit()

    # Get resulting contents
    message = box.gather()

See the library documentation on curses.textpad for more details.

For More Information

This HOWTO doesn’t cover some advanced topics, such as reading the contents of the screen or capturing mouse events from an xterm instance, but the Python library page for the curses module is now reasonably complete. You should browse it next.

If you’re in doubt about the detailed behavior of the curses functions, consult the manual pages for your curses implementation, whether it’s ncurses or a proprietary Unix vendor’s. The manual pages will document any quirks, and provide complete lists of all the functions, attributes, and ACS_* characters available to you.

Because the curses API is so large, some functions aren’t supported in the Python interface. Often this isn’t because they’re difficult to implement, but because no one has needed them yet. Also, Python doesn’t yet support the menu library associated with ncurses. Patches adding support for these would be welcome; see the Python Developer’s Guide [https://devguide.python.org/] to learn more about submitting patches to Python.

Writing Programs with NCURSES [http://invisible-island.net/ncurses/ncurses-intro.html]: a lengthy tutorial for C programmers.

The ncurses man page [http://linux.die.net/man/3/ncurses]

The ncurses FAQ [http://invisible-island.net/ncurses/ncurses.faq.html]

« Use curses… don’t swear » [https://www.youtube.com/watch?v=eN1eZtjLEnU]: video of a PyCon 2013 talk on controlling terminals using curses or Urwid.

« Console Applications with Urwid » [http://www.pyvideo.org/video/1568/console-applications-with-urwid]: video of a PyCon CA 2012 talk demonstrating some applications written using Urwid.

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Guide pour l’utilisation des descripteurs

Auteur

Raymond Hettinger

Contact

<python at rcn dot com>

Sommaire

Guide pour l’utilisation des descripteurs

Résumé

Définition et introduction

Protocole descripteur

Invocation des descripteurs

Exemple de descripteur

Propriétés

Fonctions et méthodes

Méthodes statiques et méthodes de classe

Résumé

Defines descriptors, summarizes the protocol, and shows how descriptors are called. Examines a custom descriptor and several built-in python descriptors including functions, properties, static methods, and class methods. Shows how each works by giving a pure Python equivalent and a sample application.

L’apprentissage des descripteurs permet non seulement d’accéder à un ensemble d’outils plus vaste, mais aussi de mieux comprendre le fonctionnement de Python et d’apprécier l’élégance de sa conception.

Définition et introduction

En général, un descripteur est un attribut objet avec un « comportement contraignant », dont l’accès à l’attribut a été remplacé par des méthodes dans le protocole du descripteur. Ces méthodes sont : __get__(), __set__(), et __delete__(). Si l’une de ces méthodes est définie pour un objet, il s’agit d’un descripteur.

Le comportement par défaut pour l’accès aux attributs consiste à obtenir, définir ou supprimer l’attribut du dictionnaire d’un objet. Par exemple, a. x a une chaîne de recherche commençant par a. __dict__ ['x'], puis type (a). __dict__ ['x'], et continuant à travers les classes de base de type (a) À l’exclusion des sous-classes. Si la valeur recherchée est un objet définissant l’une des méthodes de descripteur, Python peut substituer le comportement par défaut et appeler à la place la méthode Descriptor. Lorsque cela se produit dans la chaîne de précédence dépend de quelles méthodes descripteur ont été définies.

Les descripteurs sont un protocole puissant et à usage général. Ils sont le mécanisme derrière les propriétés, les méthodes, les méthodes statiques, les méthodes de classes et super(). Ils sont utilisés dans tout Python lui-même pour implémenter les nouvelles classes de style introduites dans la version 2.2. Les descripteurs simplifient le code C sous-jacent et offrent un ensemble flexible de nouveaux outils pour les programmes Python quotidiens.

Protocole descripteur

descr.__get__(self, obj, type=None) --> value

descr.__set__(self, obj, value) --> None

descr.__delete__(self, obj) --> None

C’est tout ce qu’il y a à faire. Définissez n’importe laquelle de ces méthodes et un objet est considéré comme un descripteur et peut remplacer le comportement par défaut lorsqu’il est recherché comme un attribut.

Si un objet définit à la fois __get__() et __set__(), il est considéré comme un descripteur de données. Les descripteurs qui ne définissent que __get__() sont appelés descripteurs non-data (ils sont généralement utilisés pour des méthodes mais d’autres utilisations sont possibles).

Les descripteurs de données et les descripteurs non-data diffèrent dans la façon dont les dérogations sont calculées en ce qui concerne les entrées du dictionnaire d’une instance. Si le dictionnaire d’une instance comporte une entrée portant le même nom qu’un descripteur de données, le descripteur de données est prioritaire. Si le dictionnaire d’une instance comporte une entrée portant le même nom qu’un descripteur non-data, l’entrée du dictionnaire a la priorité.

Pour faire un descripteur de données en lecture seule, définissez à la fois __get__() et __set__() avec __set__() levant une erreur AttributeError quand il est appelé. Définir la méthode __set__set__() avec une exception élevant le caractère générique est suffisant pour en faire un descripteur de données.

Invocation des descripteurs

Un descripteur peut être appelé directement par son nom de méthode. Par exemple, d.__get__(obj).

Alternativement, il est plus courant qu’un descripteur soit invoqué automatiquement lors de l’accès aux attributs. Par exemple, obj.d recherche d dans le dictionnaire de obj.d. Si d définit la méthode __get__(), alors d.__get__(obj) est invoqué selon les règles de priorité énumérées ci-dessous.

Les détails de l’invocation dépendent du fait que obj est un objet ou une classe.

Pour les objets, la machinerie est en object.__getattribute__() qui transforme b.x en type(b).__dict__['x'].__get__(b, type(b)]. L’implémentation fonctionne à travers une chaîne de priorité qui donne la priorité aux descripteurs de données sur les variables d’instance, la priorité aux variables d’instance sur les descripteurs non-data, et attribue la priorité la plus faible à __getattr__() si fourni. L’implémentation complète de C peut être trouvée dans PyObject_GenericGetAttr() dans Objects/object.c [https://github.com/python/cpython/tree/3.6/Objects/object.c].

Pour les classes, la machinerie est dans type.__getattribute__() qui transforme B.x en B.__dict__['x'].__get__(None, B). En Python pur, il ressemble à :

def __getattribute__(self, key):
    "Emulate type_getattro() in Objects/typeobject.c"
    v = object.__getattribute__(self, key)
    if hasattr(v, '__get__'):
        return v.__get__(None, self)
    return v

Les points importants à retenir sont :

les descripteurs sont appelés par la méthode __getattribute__()

redéfinition __getattribute____() empêche les appels automatiques de descripteurs

objet.__getattribute__() et type.__getattribute__() font différents appels à __get__().

les descripteurs de données remplacent toujours les dictionnaires d’instances.

les descripteurs non-data peuvent être remplacés par des dictionnaires d’instance.

L’objet retourné par super() a aussi une méthode personnalisée __getattribute__() pour appeler les descripteurs. L’appel super(B, obj).m() recherche obj.__class__.__mro__ pour la classe de base A immédiatement après B et renvoie ensuite A.__dict__['m'].__get__(obj, B). Si ce n’est pas un descripteur, m est retourné inchangé. Si ce n’est pas dans le dictionnaire, m renvoie à une recherche avec object.__getattribute__().

Les détails d’implémentation sont dans super_getattro() dans Objects/typeobject.c [https://github.com/python/cpython/tree/3.6/Objects/typeobject.c] et un équivalent Python pur peut être trouvé dans Guido’s Tutorial [https://www.python.org/download/releases/2.2.3/descrintro/#cooperation].

Les détails ci-dessus montrent que le mécanisme des descripteurs est intégré dans les méthodes __getattribute__() pour object, type et super(). Les classes héritent de cette machinerie lorsqu’elles dérivent de object ou si elles ont une méta-classe fournissant des fonctionnalités similaires. De même, les classes peuvent désactiver l’appel de descripteurs en remplaçant __getattribute__().

Exemple de descripteur

Le code suivant crée une classe dont les objets sont des descripteurs de données qui affichent un message pour chaque lecture ou écriture. Redéfinir __getattribute__() est une approche alternative qui pourrait le faire pour chaque attribut. Cependant, ce descripteur n’est utile que pour le suivi de quelques attributs choisis :

class RevealAccess(object):
    """A data descriptor that sets and returns values
       normally and prints a message logging their access.
    """

    def __init__(self, initval=None, name='var'):
        self.val = initval
        self.name = name

    def __get__(self, obj, objtype):
        print('Retrieving', self.name)
        return self.val

    def __set__(self, obj, val):
        print('Updating', self.name)
        self.val = val

>>> class MyClass(object):
...     x = RevealAccess(10, 'var "x"')
...     y = 5
...
>>> m = MyClass()
>>> m.x
Retrieving var "x"
10
>>> m.x = 20
Updating var "x"
>>> m.x
Retrieving var "x"
20
>>> m.y
5

Le protocole est simple et offre des possibilités passionnantes. Plusieurs cas d’utilisation sont si courants qu’ils ont été regroupés en appels de fonction individuels. Les propriétés, les méthodes liées, les méthodes statiques et les méthodes de classe sont toutes basées sur le protocole du descripteur.

Propriétés

Appeler property() est une façon succincte de construire un descripteur de données qui déclenche des appels de fonction lors de l’accès à un attribut. Sa signature est :

property(fget=None, fset=None, fdel=None, doc=None) -> property attribute

La documentation montre une utilisation typique pour définir un attribut géré x :

class C(object):
    def getx(self): return self.__x
    def setx(self, value): self.__x = value
    def delx(self): del self.__x
    x = property(getx, setx, delx, "I'm the 'x' property.")

Pour voir comment property() est implémenté dans le protocole du descripteur, voici un un équivalent Python pur :

class Property(object):
    "Emulate PyProperty_Type() in Objects/descrobject.c"

    def __init__(self, fget=None, fset=None, fdel=None, doc=None):
        self.fget = fget
        self.fset = fset
        self.fdel = fdel
        if doc is None and fget is not None:
            doc = fget.__doc__
        self.__doc__ = doc

    def __get__(self, obj, objtype=None):
        if obj is None:
            return self
        if self.fget is None:
            raise AttributeError("unreadable attribute")
        return self.fget(obj)

    def __set__(self, obj, value):
        if self.fset is None:
            raise AttributeError("can't set attribute")
        self.fset(obj, value)

    def __delete__(self, obj):
        if self.fdel is None:
            raise AttributeError("can't delete attribute")
        self.fdel(obj)

    def getter(self, fget):
        return type(self)(fget, self.fset, self.fdel, self.__doc__)

    def setter(self, fset):
        return type(self)(self.fget, fset, self.fdel, self.__doc__)

    def deleter(self, fdel):
        return type(self)(self.fget, self.fset, fdel, self.__doc__)

La fonction native property() aide chaque fois qu’une interface utilisateur a accordé l’accès à un attribut et que des modifications ultérieures nécessitent l’intervention d’une méthode.

Par exemple, une classe de tableur peut donner accès à une valeur de cellule via Cell('b10').value. Les améliorations ultérieures du programme exigent que la cellule soit recalculée à chaque accès ; cependant, le programmeur ne veut pas affecter le code client existant accédant directement à l’attribut. La solution consiste à envelopper l’accès à l’attribut de valeur dans un descripteur de données de propriété :

class Cell(object):
    . . .
    def getvalue(self):
        "Recalculate the cell before returning value"
        self.recalc()
        return self._value
    value = property(getvalue)

Fonctions et méthodes

Les fonctionnalités orientées objet de Python sont construites sur un environnement basé sur des fonctions. À l’aide de descripteurs non-data, les deux sont fusionnés de façon transparente.

Les dictionnaires de classes stockent les méthodes sous forme de fonctions. Dans une définition de classe, les méthodes sont écrites en utilisant def ou lambda, les outils habituels pour créer des fonctions. Les méthodes ne diffèrent des fonctions régulières que par le fait que le premier argument est réservé à l’instance de l’objet. Par convention Python, la référence de l’instance est appelée self mais peut être appelée this ou tout autre nom de variable.

To support method calls, functions include the __get__() method for binding methods during attribute access. This means that all functions are non-data descriptors which return bound methods when they are invoked from an object. In pure python, it works like this:

class Function(object):
    . . .
    def __get__(self, obj, objtype=None):
        "Simulate func_descr_get() in Objects/funcobject.c"
        if obj is None:
            return self
        return types.MethodType(self, obj)

L’exécution de l’interpréteur montre comment le descripteur de fonction se comporte dans la pratique :

>>> class D(object):
...     def f(self, x):
...         return x
...
>>> d = D()

# Access through the class dictionary does not invoke __get__.
# It just returns the underlying function object.
>>> D.__dict__['f']
<function D.f at 0x00C45070>

# Dotted access from a class calls __get__() which just returns
# the underlying function unchanged.
>>> D.f
<function D.f at 0x00C45070>

# The function has a __qualname__ attribute to support introspection
>>> D.f.__qualname__
'D.f'

# Dotted access from an instance calls __get__() which returns the
# function wrapped in a bound method object
>>> d.f
<bound method D.f of <__main__.D object at 0x00B18C90>>

# Internally, the bound method stores the underlying function,
# the bound instance, and the class of the bound instance.
>>> d.f.__func__
<function D.f at 0x1012e5ae8>
>>> d.f.__self__
<__main__.D object at 0x1012e1f98>
>>> d.f.__class__
<class 'method'>

Méthodes statiques et méthodes de classe

Les descripteurs non-data fournissent un mécanisme simple pour les variations des patrons habituels des fonctions de liaison dans les méthodes.

Pour résumer, les fonctions ont une méthode __get__() pour qu’elles puissent être converties en méthode lorsqu’on y accède comme attributs. Le descripteur non-data transforme un appel obj.f(*args)``en ``f(obj, *args). Appeler klass.f(*args) devient f(*args).

Ce tableau résume le lien (binding) et ses deux variantes les plus utiles :

Transformation

Appelé depuis un Objet

Appelé depuis un Classe

fonction

f(obj, *args)

f(*args)

méthode statique

f(*args)

f(*args)

méthode de classe

f(type(obj), *args)

f(klass, *args)

Les méthodes statiques renvoient la fonction sous-jacente sans modifications. Appeler c.f ou C.f est l’équivalent d’une recherche directe dans objet.__getattribute__(c, "f") ou objet.__getattribute__(C, "f"). Par conséquent, la fonction devient accessible de manière identique à partir d’un objet ou d’une classe.

Les bonnes candidates pour être méthode statique sont des méthodes qui ne font pas référence à la variable self.

Par exemple, un paquet traitant de statistiques peut inclure une classe qui est un conteneur pour des données expérimentales. La classe fournit les méthodes normales pour calculer la moyenne, la moyenne, la médiane et d’autres statistiques descriptives qui dépendent des données. Cependant, il peut y avoir des fonctions utiles qui sont conceptuellement liées mais qui ne dépendent pas des données. Par exemple, erf(x) est une routine de conversion pratique qui apparaît dans le travail statistique mais qui ne dépend pas directement d’un ensemble de données particulier. Elle peut être appelée à partir d’un objet ou de la classe : s.erf(1.5) --> .9332` ou Sample.erf(1.5) --> .9332.

Depuis que les méthodes statiques renvoient la fonction sous-jacente sans changement, les exemples d’appels ne sont pas excitants :

>>> class E(object):
...     def f(x):
...         print(x)
...     f = staticmethod(f)
...
>>> print(E.f(3))
3
>>> print(E().f(3))
3

En utilisant le protocole de descripteur non-data, une version Python pure de staticmethod() ressemblerait à ceci :

class StaticMethod(object):
    "Emulate PyStaticMethod_Type() in Objects/funcobject.c"

    def __init__(self, f):
        self.f = f

    def __get__(self, obj, objtype=None):
        return self.f

Contrairement aux méthodes statiques, les méthodes de classe préchargent la référence de classe dans la liste d’arguments avant d’appeler la fonction. Ce format est le même que l’appelant soit un objet ou une classe :

>>> class E(object):
...     def f(klass, x):
...         return klass.__name__, x
...     f = classmethod(f)
...
>>> print(E.f(3))
('E', 3)
>>> print(E().f(3))
('E', 3)

Ce comportement est utile lorsque la fonction n’a besoin que d’une référence de classe et ne se soucie pas des données sous-jacentes. Une des utilisations des méthodes de classe est de créer d’autres constructeurs de classe. En Python 2.3, la méthode de classe dict.fromkeys() crée un nouveau dictionnaire à partir d’une liste de clés. L’équivalent Python pur est :

class Dict(object):
    . . .
    def fromkeys(klass, iterable, value=None):
        "Emulate dict_fromkeys() in Objects/dictobject.c"
        d = klass()
        for key in iterable:
            d[key] = value
        return d
    fromkeys = classmethod(fromkeys)

Maintenant un nouveau dictionnaire de clés uniques peut être construit comme ceci :

>>> Dict.fromkeys('abracadabra')
{'a': None, 'r': None, 'b': None, 'c': None, 'd': None}

En utilisant le protocole de descripteur non-data, une version Python pure de classmethod() ressemblerait à ceci :

class ClassMethod(object):
    "Emulate PyClassMethod_Type() in Objects/funcobject.c"

    def __init__(self, f):
        self.f = f

    def __get__(self, obj, klass=None):
        if klass is None:
            klass = type(obj)
        def newfunc(*args):
            return self.f(klass, *args)
        return newfunc

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Guide pratique : programmation fonctionnelle

Auteur

A. M. Kuchling

Version

0.32

Dans ce document, nous allons faire un tour des fonctionnalités de Python adaptées à la réalisation d’un programme dans un style fonctionnel. Après une introduction à la programmation fonctionnelle, nous aborderons des outils tels que les iterators et les generators ainsi que les modules itertools et functools.

Introduction

Cette section détaille les fondamentaux de la programmation fonctionnelle. Si seules les fonctionnalités de Python vous intéressent, vous pouvez sauter cette partie et lire la section suivante sur les Itérateurs.

Les langages de programmation permettent de traiter des problèmes selon différentes approches :

La plupart des langages de programmation suivent une logique procédurale : les programmes sont constitués de listes d’instructions qui détaillent les opérations que l’ordinateur doit appliquer aux entrées du programme. C, Pascal ou encore les interpréteurs de commandes Unix sont des langages procéduraux.

Les langages déclaratifs permettent d’écrire la spécification du problème et laissent l’implémentation du langage trouver une façon efficace de réaliser les calculs nécessaires à sa résolution. SQL est un langage déclaratif que vous êtes susceptible de connaître ; une requête SQL décrit le jeu de données que vous souhaitez récupérer et le moteur SQL choisit de parcourir les tables ou d’utiliser les index, l’ordre de résolution des sous-clauses, etc.

Les programmes orientés objet manipulent des ensembles d’objets. Ceux-ci possèdent un état interne et des méthodes qui interrogent ou modifient cet état d’une façon ou d’une autre. Smalltalk et Java sont deux langages orientés objet. C++ et Python gèrent la programmation orientée objet mais n’imposent pas l’utilisation de telles fonctionnalités.

La programmation fonctionnelle implique de décomposer un problème en un ensemble de fonctions. Dans l’idéal, les fonctions produisent des sorties à partir d’entrées et ne possède pas d’état interne qui soit susceptible de modifier la sortie pour une entrée donnée. Les langages fonctionnels les plus connus sont ceux de la famille ML (Standard ML, OCaml et autres) et Haskell.

Les personnes qui conçoivent des langages de programmation peuvent choisir de privilégier une approche par rapport à une autre. Cela complexifie l’écriture de programmes appliquant un paradigme différent de celui considéré. Certains langages sont multi-paradigmes et gère plusieurs approches différentes. Lisp, C++ et Python sont de tels langages ; vous pouvez écrire des programmes ou des bibliothèques dans un style procédural, orienté objet ou fonctionnel dans chacun d’entre eux. Différentes parties d’une application peuvent être écrites selon des approches différentes ; par exemple, l’interface graphique peut suivre le paradigme orienté objet tandis que la logique de traitement est procédurale ou fonctionnelle.

Dans un programme fonctionnel, l’entrée traverse un ensemble de fonctions. Chaque fonction opère sur son entrée et produit une sortie. Le style fonctionnel préconise de ne pas écrire de fonctions ayant des effets de bord, c’est-à-dire qui modifient un état interne ou réalisent d’autres changements qui ne sont pas visibles dans la valeur de sortie de la fonction. Les fonctions qui ne présentent aucun effet de bord sont dites purement fonctionnelles. L’interdiction des effets de bord signifie qu’aucune structure de données n’est mise à jour lors de l’exécution du programme ; chaque sortie d’une fonction ne dépend que de son entrée.

Certains langages sont très stricts en ce qui concerne la pureté des fonctions et ne laissent même pas la possibilité d’assigner des variables avec des expressions telles que a = 3 ou c = a + b, cependant il est difficile d’éviter tous les effets de bord. Afficher un message sur l’écran ou écrire un fichier sur le disque sont des effets de bord. Par exemple, un appel aux fonctions print() ou time.sleep() en Python ne renvoie aucune valeur utile ; ces fonctions ne sont appelées que pour leur effet de bord (afficher du texte sur l’écran et mettre en pause l’exécution du programme).

Les programmes Python écrits dans un style fonctionnel ne poussent généralement pas le curseur de la pureté à l’extrême en interdisant toute entrée/sortie ou les assignations ; ils exhibent une interface fonctionnelle en apparence mais utilisent des fonctionnalités impures en interne. Par exemple, l’implémentation d’une fonction peut assigner dans des variables locales mais ne modifiera pas de variable globale et n’aura pas d’autre effet de bord.

La programmation fonctionnelle peut être considérée comme l’opposé de la programmation orientée objet. Les objets encapsulent un état interne ainsi qu’une collection de méthodes qui permettent de modifier cet état. Les programmes consistent à appliquer les bons changements à ces états. La programmation fonctionnelle vous impose d’éviter au maximum ces changements d’états en travaillant sur des données qui traversent un flux de fonctions. En Python, vous pouvez combiner ces deux approches en écrivant des fonctions qui prennent en argument et renvoient des instances représentants des objets de votre application (courriers électroniques, transactions, etc.).

Programmer sous la contrainte du paradigme fonctionnel peut sembler étrange. Pourquoi vouloir éviter les objets et les effets de bord ? Il existe des avantages théoriques et pratiques au style fonctionnel :

Preuves formelles.

Modularité.

Composabilité.

Facilité de débogage et de test.

Preuves formelles

Un avantage théorique est qu’il plus facile de construire une preuve mathématique de l’exactitude d’un programme fonctionnel.

Les chercheurs ont longtemps souhaité trouver des façons de prouver mathématiquement qu’un programme est correct. Cela ne se borne pas à tester si la sortie d’un programme est correcte sur de nombreuses entrées ou lire le code source et en conclure que le celui-ci semble juste. L’objectif est d’établir une preuve rigoureuse que le programme produit le bon résultat pour toutes les entrées possibles.

La technique utilisée pour prouver l’exactitude d’un programme est d’écrire des invariants, c’est-à-dire des propriétés de l’entrée et des variables du programme qui sont toujours vérifiées. Pour chaque ligne de code, il suffit de montrer que si les invariants X et Y sont vrais avant l’exécution de cette ligne, les invariants légèrement modifiés X” et Y” sont vérifiés après son exécution. Ceci se répète jusqu’à atteindre la fin du programme. À ce stade, les invariants doivent alors correspondre aux propriétés que l’on souhaite que la sortie du programme vérifie.

L’aversion du style fonctionnel envers les assignations de variable est apparue car celles-ci sont difficiles à gérer avec cette méthode. Les assignations peuvent rompre des invariants qui étaient vrais auparavant sans pour autant produire de nouveaux invariants qui pourraient être propagés.

Malheureusement, prouver l’exactitude d’un programme est très peu commode et ne concerne que rarement des logiciels en Python. Même des programmes triviaux nécessitent souvent des preuves s’étalant sur plusieurs pages ; la preuve de l’exactitude d’un programme relativement gros serait gigantesque. Peu, voire aucun, des programmes que vous utilisez quotidiennement (l’interpréteur Python, votre analyseur syntaxique XML, votre navigateur web) ne peuvent être prouvés exacts. Même si vous écriviez ou généreriez une preuve, il faudrait encore vérifier celle-ci. Peut-être qu’elle contient une erreur et que vous pensez désormais, à tort, que vous avez prouvé que votre programme est correct.

Modularité

Un intérêt plus pratique de la programmation fonctionnelle est qu’elle impose de décomposer le problème en petits morceaux. Les programmes qui en résultent sont souvent plus modulaires. Il est plus simple de spécifier et d’écrire une petite fonction qui ne fait qu’une seule tâche plutôt qu’une grosse fonction qui réalise une transformation complexe. Les petites fonctions sont plus faciles à lire et à vérifier.

Facilité de débogage et de test

Tester et déboguer un programme fonctionnel est plus facile.

Déboguer est plus simple car les fonctions sont généralement petites et bien spécifiées. Lorsqu’un programme ne fonctionne pas, chaque fonction constitue une étape intermédiaire au niveau de laquelle vous pouvez vérifier que les valeurs sont justes. Vous pouvez observer les entrées intermédiaires et les sorties afin d’isoler rapidement la fonction qui est à l’origine du bogue.

Les tests sont plus faciles car chaque fonction est désormais un sujet potentiel pour un test unitaire. Les fonctions ne dépendent pas d’un état particulier du système qui devrait être répliqué avant d’exécuter un test ; à la place vous n’avez qu’à produire une entrée synthétique et vérifier que le résultat correspond à ce que vous attendez.

Composabilité

En travaillant sur un programme dans le style fonctionnel, vous écrivez un certain nombre de fonctions avec des entrées et des sorties variables. Certaines de ces fonctions sont inévitablement spécifiques à une application en particulier, mais d’autres peuvent s’appliquer à de nombreux cas d’usage. Par exemple, une fonction qui liste l’ensemble des fichiers XML d’un répertoire à partir du chemin de celui-ci ou une fonction qui renvoie le contenu d’un fichier à partir de son nom peuvent être utiles dans de nombreuses situations.

Au fur et à mesure, vous constituez ainsi une bibliothèque personnelle d’utilitaires. Souvent, vous pourrez construire de nouveaux programmes en agençant des fonctions existantes dans une nouvelle configuration et en écrivant quelques fonctions spécifiques à votre objectif en cours.

Itérateurs

Commençons par jeter un œil à une des fonctionnalités les plus importantes pour écrire en style fonctionnel avec Python : les itérateurs.

Un itérateur est un objet qui représente un flux de données ; cet objet renvoie les données un élément à la fois. Un itérateur Python doit posséder une méthode __next__() qui ne prend pas d’argument et renvoie toujours l’élément suivant du flux. S’il n’y plus d’élément dans le flux, __next__() doit lever une exception StopIteration. Toutefois, ce n’est pas indispensable ; il est envisageable d’écrire un itérateur qui produit un flux infini de données.

La fonction native iter() prend un objet arbitraire et tente de construire un itérateur qui renvoie le contenu de l’objet (ou ses éléments) en levant une exception TypeError si l’objet ne gère pas l’itération. Plusieurs types de données natifs à Python gèrent l’itération, notamment les listes et les dictionnaires. On appelle iterable un objet pour lequel il est possible de construire un itérateur.

Vous pouvez expérimenter avec l’interface d’itération manuellement :

>>> L = [1, 2, 3]
>>> it = iter(L)
>>> it
<...iterator object at ...>
>>> it.__next__()  # same as next(it)
1
>>> next(it)
2
>>> next(it)
3
>>> next(it)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
StopIteration
>>>

Python s’attend à travailler sur des objets itérables dans divers contextes et tout particulièrement dans une boucle for. Dans l’expression for X in Y, Y doit être un itérateur ou un objet pour lequel iter() peut générer un itérateur. Ces deux expressions sont équivalentes :

for i in iter(obj):
    print(i)

for i in obj:
    print(i)

Les itérateurs peuvent être transformés en listes ou en tuples en appelant les constructeurs respectifs list() et tuple() :

>>> L = [1, 2, 3]
>>> iterator = iter(L)
>>> t = tuple(iterator)
>>> t
(1, 2, 3)

Le dépaquetage de séquences fonctionne également sur les itérateurs : si vous savez qu’un itérateur renvoie N éléments, vous pouvez les dépaqueter dans un n-uplet :

>>> L = [1, 2, 3]
>>> iterator = iter(L)
>>> a, b, c = iterator
>>> a, b, c
(1, 2, 3)

Certaines fonctions natives telles que max() et min() prennent un itérateur en argument et en renvoie le plus grand ou le plus petit élément. Les opérateurs "in" et "not in" gèrent également les itérateurs : X in iterator est vrai si X a été trouvé dans le flux renvoyé par l’itérateur. Vous rencontrerez bien sûr des problèmes si l’itérateur est infini : max(), min() ne termineront jamais et, si l’élément X n’apparaît pas dans le flux, les opérateurs "in" et "not in" non plus.

Notez qu’il n’est possible de parcourir un itérateur que vers l’avant et qu’il est impossible de récupérer l’élément précédent, de réinitialiser l’itérateur ou d’en créer une copie. Des objets itérateurs peuvent offrir ces possibilités de façon facultative, mais le protocole d’itération ne spécifie que la méthode __next__(). Certaines fonctions peuvent ainsi consommer l’entièreté de la sortie d’un itérateur et, si vous devez utiliser le même flux pour autre chose, vous devrez en créer un nouveau.

Types de données itérables

Nous avons vu précédemment comment les listes et les tuples gèrent les itérateurs. En réalité, n’importe quel type de séquence en Python, par exemple les chaînes de caractères, sont itérables.

Appeler iter() sur un dictionnaire renvoie un itérateur qui parcourt l’ensemble de ses clés :

>>> m = {'Jan': 1, 'Feb': 2, 'Mar': 3, 'Apr': 4, 'May': 5, 'Jun': 6,
...      'Jul': 7, 'Aug': 8, 'Sep': 9, 'Oct': 10, 'Nov': 11, 'Dec': 12}
>>> for key in m:
...     print(key, m[key])
Mar 3
Feb 2
Aug 8
Sep 9
Apr 4
Jun 6
Jul 7
Jan 1
May 5
Nov 11
Dec 12
Oct 10

Note that the order is essentially random, because it’s based on the hash ordering of the objects in the dictionary.

Appliquer iter() sur un dictionnaire produit un itérateur sur ses clés mais il est possible d’obtenir d’autres itérateurs par d’autres méthodes. Si vous souhaitez itérer sur les valeurs ou les paires clé/valeur du dictionnaire, vous pouvez explicitement appeler les méthodes values() ou items() pour obtenir l’itérateur idoine.

Le constructeur dict() accepte de prendre un itérateur en argument qui renvoie un flux fini de pairs (clé, valeur) :

>>> L = [('Italy', 'Rome'), ('France', 'Paris'), ('US', 'Washington DC')]
>>> dict(iter(L))
{'Italy': 'Rome', 'US': 'Washington DC', 'France': 'Paris'}

Les fichiers gèrent aussi l’itération en appelant la méthode readline() jusqu’à ce qu’il n’y ait plus d’autre ligne dans le fichier. Cela signifie que vous pouvez lire l’intégralité d’un fichier de la façon suivante :

for line in file:
    # do something for each line
    ...

Les ensembles peuvent être créés à partir d’un itérable et autorisent l’itération sur les éléments de l’ensemble :

S = {2, 3, 5, 7, 11, 13}
for i in S:
    print(i)

Expressions génératrices et compréhension de listes

Deux opérations courantes réalisables sur la sortie d’un itérateur sont 1) effectuer une opération pour chaque élément, 2) extraire le sous-ensemble des éléments qui vérifient une certaine condition. Par exemple, pour une liste de chaînes de caractères, vous pouvez choisir de retirer tous les caractères blancs à la fin de chaque ligne ou extraire toutes les chaînes contenant une sous-chaîne précise.

Les compréhensions de listes et les expressions génératrices sont des façons concises d’exprimer de telles opérations, inspirées du langage de programmation fonctionnel Haskell (https://www.haskell.org/). Vous pouvez retirer tous les caractères blancs initiaux et finaux d’un flux de chaînes de caractères à l’aide du code suivant :

line_list = ['  line 1\n', 'line 2  \n', ...]

# Generator expression -- returns iterator
stripped_iter = (line.strip() for line in line_list)

# List comprehension -- returns list
stripped_list = [line.strip() for line in line_list]

Vous pouvez ne sélectionner que certains éléments en ajoutant une condition « if » :

stripped_list = [line.strip() for line in line_list
                 if line != ""]

La compréhension de liste renvoie une liste Python ; stripped_list est une liste contenant les lignes après transformation, pas un itérateur. Les expressions génératrices renvoient un itérateur qui calcule les valeurs au fur et à mesure sans toutes les matérialiser d’un seul coup. Cela signifie que les compréhensions de listes ne sont pas très utiles si vous travaillez sur des itérateurs infinis ou produisant une très grande quantité de données. Les expressions génératrices sont préférables dans ce cas.

Les expressions génératrices sont écrites entre parenthèses (« () ») et les compréhensions de listes entre crochets (« [] »). Les expressions génératrices sont de la forme :

( expression for expr in sequence1
             if condition1
             for expr2 in sequence2
             if condition2
             for expr3 in sequence3 ...
             if condition3
             for exprN in sequenceN
             if conditionN )

La compréhension de liste équivalente s’écrit de la même manière, utilisez juste des crochets à la place des parenthèses.

Les éléments de la sortie sont les valeurs successives de expression. La clause if est facultative ; si elle est présente, expression n’est évaluée et ajoutée au résultat que si condition est vérifiée.

Les expressions génératrices doivent toujours être écrites entre parenthèses, mais les parenthèses qui encadrent un appel de fonction comptent aussi. Si vous souhaitez créer un itérateur qui soit immédiatement passé à une fonction, vous pouvez écrire :

obj_total = sum(obj.count for obj in list_all_objects())

Les clauses for ... in indiquent les séquences sur lesquelles itérer. Celles-ci peuvent être de longueurs différentes car l’itération est réalisée de gauche à droite et non en parallèle. sequence2 est parcourue entièrement pour chaque élément de sequence1. sequence3 est ensuite parcourue dans son intégralité pour chaque paire d’éléments de sequence1 et sequence2.

Autrement dit, une compréhension de liste ou une expression génératrice est équivalente au code Python ci-dessous :

for expr1 in sequence1:
    if not (condition1):
        continue   # Skip this element
    for expr2 in sequence2:
        if not (condition2):
            continue   # Skip this element
        ...
        for exprN in sequenceN:
            if not (conditionN):
                continue   # Skip this element

            # Output the value of
            # the expression.

Ainsi lorsque plusieurs clauses for ... in sont présentes mais sans condition if, la longueur totale de la nouvelle séquence est égale au produit des longueurs des séquences itérées. Si vous travaillez sur deux listes de longueur 3, la sortie contiendra 9 éléments :

>>> seq1 = 'abc'
>>> seq2 = (1, 2, 3)
>>> [(x, y) for x in seq1 for y in seq2]
[('a', 1), ('a', 2), ('a', 3),
 ('b', 1), ('b', 2), ('b', 3),
 ('c', 1), ('c', 2), ('c', 3)]

Afin de ne pas créer une ambiguïté dans la grammaire de Python, expression doit être encadrée par des parenthèses si elle produit un n-uplet. La première compréhension de liste ci-dessous n’est pas valide syntaxiquement, tandis que la seconde l’est :

# Syntax error
[x, y for x in seq1 for y in seq2]
# Correct
[(x, y) for x in seq1 for y in seq2]

Générateurs

Les générateurs forment une classe spéciale de fonctions qui simplifie la création d’itérateurs. Les fonctions habituelles calculent une valeur et la renvoie, tandis que les générateurs renvoient un itérateur qui produit un flux de valeurs.

Vous connaissez sans doute le fonctionnement des appels de fonctions en Python ou en C. Lorsqu’une fonction est appelée, un espace de nommage privé lui est associé pour ses variables locales. Lorsque le programme atteint une instruction return, les variables locales sont détruites et la valeur est renvoyée à l’appelant. Les appels postérieurs à la même fonction créent un nouvel espace de nommage privé et de nouvelles variables locales. Cependant, que se passerait-il si les variables locales n’étaient pas détruites lors de la sortie d’une fonction ? Et s’il était possible de reprendre l’exécution de la fonction là où elle s’était arrêtée ? Les générateurs sont une réponse à ces questions ; vous pouvez considérer qu’il s’agit de fonctions qu’il est possible d’interrompre, puis de relancer sans perdre leur progression.

Voici un exemple simple de fonction génératrice :

>>> def generate_ints(N):
...    for i in range(N):
...        yield i

N’importe quelle fonction contenant le mot-clé yield est un générateur ; le compilateur bytecode de Python détecte ce mot-clé et prend en compte cette particularité de la fonction.

Lorsque vous appelez une fonction génératrice, celle-ci ne renvoie pas une unique valeur ; elle renvoie un objet générateur qui implémente le protocole d’itération. Lorsque l’expression yield est exécutée, le générateur renvoie la valeur de i, d’une façon similaire à un return. La différence principale entre yield et return est qu’en atteignant l’instruction yield, l’état du générateur est suspendu et les variables locales sont conservées. Lors de l’appel suivant à la méthode __next__() du générateur, la fonction reprend son exécution.

Voici un exemple d’utilisation du générateur generate_ints() :

>>> gen = generate_ints(3)
>>> gen
<generator object generate_ints at ...>
>>> next(gen)
0
>>> next(gen)
1
>>> next(gen)
2
>>> next(gen)
Traceback (most recent call last):
  File "stdin", line 1, in <module>
  File "stdin", line 2, in generate_ints
StopIteration

You could equally write for i in generate_ints(5), or a, b, c = generate_ints(3).

Dans une fonction génératrice, une instruction return value entraine la levée d’une exception StopIteration(value) dans la méthode __next__(). Lorsque cela se produit (ou que la fin de la fonction est atteinte), le flot de nouvelles valeurs s’arrête et le générateur ne peut plus rien produire.

Vous pouvez obtenir le même comportement que celui des générateurs en écrivant votre propre classe qui stocke les variables locales du générateur comme variables d’instance. Pour renvoyer une liste d’entiers, par exemple, vous pouvez initialiser self.count à 0 et écrire la méthode __next__() de telle sorte qu’elle incrémente self.count puis le renvoie. Cependant, cela devient beaucoup plus complexe pour des générateurs relativement sophistiqués.

Lib/test/test_generators.py [https://github.com/python/cpython/tree/3.6/Lib/test/test_generators.py], la suite de test de la bibliothèque Python, contient de nombreux exemples intéressants. Voici un générateur qui implémente le parcours d’un arbre dans l’ordre en utilisant des générateurs de façon récursive.

# A recursive generator that generates Tree leaves in in-order.
def inorder(t):
    if t:
        for x in inorder(t.left):
            yield x

        yield t.label

        for x in inorder(t.right):
            yield x

Deux autres exemples de test_generators.py permettent de résoudre le problème des N Reines (placer N reines sur un échiquier de dimensions NxN de telle sorte qu’aucune reine ne soit en position d’en prendre une autre) et le problème du cavalier (trouver un chemin permettant au cavalier de visiter toutes les cases d’un échiquier NxN sans jamais visiter la même case deux fois).

Transmettre des valeurs au générateur

Avant Python 2.5, les générateurs ne pouvaient que produire des sorties. Une fois le code du générateur exécuté pour créer un itérateur, il était impossible d’introduire de l’information nouvelle dans la fonction mise en pause. Une astuce consistait à obtenir cette fonctionnalité en autorisant le générateur à consulter des variables globales ou en lui passant des objets mutables modifiés hors du générateur, mais ces approches étaient compliquées.

À partir de Python 2.5, il existe une méthode simple pour transmettre des valeurs à un générateur. Le mot-clé yield est devenu une expression qui renvoie une valeur sur laquelle il est possible d’opérer et que vous pouvez assigner à une variable :

val = (yield i)

Comme dans l’exemple ci-dessus, nous vous recommandons de toujours encadrer les expressions yield par des parenthèses lorsque vous utilisez leur valeur de retour. Elles ne sont pas toujours indispensables mais mieux vaut prévenir que guérir : il est plus facile de les ajouter systématiquement que de prendre le risque de les oublier là où elles sont requises.

(Les règles exactes de parenthésage sont spécifies dans la PEP 342 [https://www.python.org/dev/peps/pep-0342] : une expression yield doit toujours être parenthésée sauf s’il s’agit de l’expression la plus externe du côté droit d’une assignation. Cela signifie que vous pouvez écrire val = yield i mais que les parenthèses sont requises s’il y a une opération, comme dans val = (yield i) + 12.)

Des valeurs peuvent être transmises à un générateur en appelant sa méthode send(value). Celle-ci reprend l’exécution du générateur et l’expression yield renvoie la valeur spécifiée. Si c’est la méthode __next__() habituelle qui est appelée, alors yield renvoie None.

Voici un exemple de compteur qui s’incrémente de 1 mais dont il est possible de modifier le compte interne.

def counter(maximum):
    i = 0
    while i < maximum:
        val = (yield i)
        # If value provided, change counter
        if val is not None:
            i = val
        else:
            i += 1

Et voici comment il est possible de modifier le compteur :

>>> it = counter(10)
>>> next(it)
0
>>> next(it)
1
>>> it.send(8)
8
>>> next(it)
9
>>> next(it)
Traceback (most recent call last):
  File "t.py", line 15, in <module>
    it.next()
StopIteration

Puisque yield renvoie souvent None, vous devez toujours vérifier si c’est le cas. N’utilisez pas la valeur de retour à moins d’être certain que seule la méthode send() sera utilisée pour reprendre l’exécution de la fonction génératrice.

En plus de send(), il existe deux autres méthodes s’appliquant aux générateurs :

throw(type, value=None, traceback=None) permet de lever une exception dans le générateur ; celle-ci est levée par l’expression yield à l’endroit où l’exécution a été mise en pause.

close() lève une exception GeneratorExit dans le générateur afin de terminer l’itération. Le code du générateur qui reçoit cette exception doit lever à son tour GeneratorExit ou StopIteration. Il est illégal d’attraper cette exception et de faire quoi que ce soit d’autre, ceci déclenche une erreur RuntimeError. Lorsque le ramasse-miette de Python collecte le générateur, il appelle sa méthode close().

Si vous devez exécuter du code pour faire le ménage lors d’une GeneratorExit, nous vous suggérons d’utiliser une structure try: ... finally plutôt que d’attraper GeneratorExit.

Ces changements cumulés transforment les générateurs de producteurs unidirectionnels d’information vers un statut hybride à la fois producteur et consommateur.

Les générateurs sont également devenus des coroutines, une forme généralisée de sous-routine. L’exécution des sous-routines démarre à un endroit et se termine à un autre (au début de la fonction et au niveau de l’instruction return), tandis qu’il est possible d’entrer, de sortir ou de reprendre une coroutine à différents endroits (les instructions yield).

Fonctions natives

Voyons un peu plus en détail les fonctions natives souvent utilisées de concert avec les itérateurs.

map() et filter() sont deux fonctions natives de Python qui clonent les propriétés des expressions génératrices :

map(f, iterA, iterB, ...) renvoie un itérateur sur une séquence

f(iterA[0], iterB[0]), f(iterA[1], iterB[1]), f(iterA[2], iterB[2]), ....

>>> def upper(s):
...     return s.upper()

>>> list(map(upper, ['sentence', 'fragment']))
['SENTENCE', 'FRAGMENT']
>>> [upper(s) for s in ['sentence', 'fragment']]
['SENTENCE', 'FRAGMENT']

Vous pouvez obtenir le même comportement à l’aide d’une compréhension de liste.

filter(predicate, iter) renvoie un itérateur sur l’ensemble des éléments de la séquence qui vérifient une certaine condition. Son comportement peut également être reproduit par une compréhension de liste. Un prédicat est une fonction qui renvoie vrai ou faux en fonction d’une certaine condition. Dans le cas de filter(), le prédicat ne doit prendre qu’un seul argument.

>>> def is_even(x):
...     return (x % 2) == 0

>>> list(filter(is_even, range(10)))
[0, 2, 4, 6, 8]

Cela peut se réécrire sous la forme d’une compréhension de liste :

>>> list(x for x in range(10) if is_even(x))
[0, 2, 4, 6, 8]

enumerate(iter, start=0) énumère les éléments de l’itérable en renvoyant des paires contenant le nombre d’éléments déjà listés (depuis le début) et l’élément en cours

>>> for item in enumerate(['subject', 'verb', 'object']):
...     print(item)
(0, 'subject')
(1, 'verb')
(2, 'object')

enumerate() est souvent utilisée lorsque l’on souhaite boucler sur une liste tout en listant les indices pour lesquels une certaine condition est vérifiée :

f = open('data.txt', 'r')
for i, line in enumerate(f):
    if line.strip() == '':
        print('Blank line at line #%i' % i)

sorted(iterable, key=None, reverse=False) rassemble tous les éléments de l’itérable dans une liste, les classe et renvoie le résultat classé. Les arguments key et reverse sont passés à la méthode sort() de la liste ainsi construite.

>>> import random
>>> # Generate 8 random numbers between [0, 10000)
>>> rand_list = random.sample(range(10000), 8)
>>> rand_list
[769, 7953, 9828, 6431, 8442, 9878, 6213, 2207]
>>> sorted(rand_list)
[769, 2207, 6213, 6431, 7953, 8442, 9828, 9878]
>>> sorted(rand_list, reverse=True)
[9878, 9828, 8442, 7953, 6431, 6213, 2207, 769]

(Pour plus de détails sur les algorithmes de tri, se référer à Guide pour le tri.)

Les fonctions natives any(iter) et all(iter) permettent d’observer les valeurs de vérité des éléments d’un itérable. any() renvoie True si au moins un élément de l’itérable s’évalue comme vrai et all() renvoie True si tous les éléments s’évaluent comme vrai :

>>> any([0, 1, 0])
True
>>> any([0, 0, 0])
False
>>> any([1, 1, 1])
True
>>> all([0, 1, 0])
False
>>> all([0, 0, 0])
False
>>> all([1, 1, 1])
True

zip(iterA, iterB, ...) rassemble un élément de chaque itérable dans un n-uplet :

zip(['a', 'b', 'c'], (1, 2, 3)) =>
  ('a', 1), ('b', 2), ('c', 3)

Cela ne construit pas de liste stockée en mémoire, ni ne vide les itérateurs d’entrée avant de renvoyer sa valeur ; en réalité les n-uplets sont construits et renvoyés au fur et à mesure (il s’agit techniquement parlant d’un comportement d”évaluation paresseuse [https://fr.wikipedia.org/wiki/%C3%89valuation_paresseuse]).

Cet itérateur suppose qu’il opère sur des itérables de même longueur. Si la longueur des itérables diffère, le flux résultant a la même longueur que le plus court des itérables.

zip(['a', 'b'], (1, 2, 3)) =>
  ('a', 1), ('b', 2)

Toutefois, vous devez éviter de dépendre de ce comportement. En effet un élément d’un des itérables les plus longs peut être retiré puis jeté (car l’autre itérable est trop court). Cela signifie que vous ne pouvez alors plus utiliser cet itérable car vous allez sauter l’élément qui vient d’être jeté.

Le module itertools

Le module itertools contient de nombreux itérateurs très utilisés, ainsi que des fonctions pour combiner différents itérateurs. Cette section présente le contenu du module au travers de quelques exemples.

Les fonctions du module se divisent en quelques grandes catégories :

Les fonctions qui transforment un itérateur existant en un nouvel itérateur.

Les fonctions qui traitent les éléments d’un itérateur comme les arguments d’une fonction.

Les fonctions qui permettent de sélectionner des portions de la sortie d’un itérateur.

Une fonction qui permet de grouper la sortie d’un itérateur.

Créer de nouveaux itérateurs

itertools.count(start, step) renvoie un flux infini de valeurs régulièrement espacées. Vous pouvez spécifier la valeur de départ (par défaut, 0) et l’intervalle entre les nombres (par défaut, 1) :

itertools.count() =>
  0, 1, 2, 3, 4, 5, 6, 7, 8, 9, ...
itertools.count(10) =>
  10, 11, 12, 13, 14, 15, 16, 17, 18, 19, ...
itertools.count(10, 5) =>
  10, 15, 20, 25, 30, 35, 40, 45, 50, 55, ...

itertools.cycle(iter) sauvegarde une copie du contenu de l’itérable passé en argument et renvoie un nouvel itérateur qui produit tous les éléments du premier au dernier et se répète indéfiniment.

itertools.cycle([1, 2, 3, 4, 5]) =>
  1, 2, 3, 4, 5, 1, 2, 3, 4, 5, ...

itertools.repeat(elem, [n]) renvoie l’élément passé en argument n fois ou répète l’élément à l’infini si n n’est pas spécifié.

itertools.repeat('abc') =>
  abc, abc, abc, abc, abc, abc, abc, abc, abc, abc, ...
itertools.repeat('abc', 5) =>
  abc, abc, abc, abc, abc

itertools.chain(iterA, iterB, ...) reçoit un nombre arbitraire d’itérables en entrée et les concatène, renvoyant tous les éléments du premier itérateur, puis tous ceux du second et ainsi de suite jusqu’à ce que tous les itérables aient été épuisés.

itertools.chain(['a', 'b', 'c'], (1, 2, 3)) =>
  a, b, c, 1, 2, 3

itertools.islice(iter, [start], stop, [step]) renvoie une portion de l’itérateur. En passant seulement l’argument stop, il renvoie les stop premiers éléments. En spécifiant un indice de début, vous récupérez stop - start éléments ; utilisez step pour spécifier une valeur de pas. Cependant vous ne pouvez pas utiliser de valeurs négatives pour start, stop ou step (contrairement aux listes et chaînes de caractères de Python).

itertools.islice(range(10), 8) =>
  0, 1, 2, 3, 4, 5, 6, 7
itertools.islice(range(10), 2, 8) =>
  2, 3, 4, 5, 6, 7
itertools.islice(range(10), 2, 8, 2) =>
  2, 4, 6

itertools.tee(iter, [n]) duplique un itérateur et renvoie n itérateurs indépendants, chacun copiant le contenu de l’itérateur source. La valeur par défaut pour n est 2. La réplication des itérateurs nécessite la sauvegarde d’une partie du contenu de l’itérateur source, ce qui peut consommer beaucoup de mémoire si l’itérateur est grand et que l’un des nouveaux itérateurs est plus consommé que les autres.

itertools.tee( itertools.count() ) =>
   iterA, iterB

where iterA ->
   0, 1, 2, 3, 4, 5, 6, 7, 8, 9, ...

and   iterB ->
   0, 1, 2, 3, 4, 5, 6, 7, 8, 9, ...

Appliquer des fonctions au contenu des itérateurs

Le module operator rassemble des fonctions équivalentes aux opérateurs Python. Par exemple, operator.add(a,b) additionne deux valeurs, operator.ne(a, b) est équivalent à a != b et operator.attrgetter('id') renvoie un objet appelable qui récupère l’attribut .id.

itertools.starmap(func, iter) suppose que l’itérable renvoie une séquence de n-uplets et appelle func en utilisant tous les n-uplets comme arguments :

itertools.starmap(os.path.join,
                  [('/bin', 'python'), ('/usr', 'bin', 'java'),
                   ('/usr', 'bin', 'perl'), ('/usr', 'bin', 'ruby')])
=>
  /bin/python, /usr/bin/java, /usr/bin/perl, /usr/bin/ruby

Sélectionner des éléments

Une autre catégorie de fonctions est celle permettant de sélectionner un sous-ensemble des éléments de l’itérateur selon un prédicat donné.

itertools.filterfalse(predicate, iter) est l’opposé de filter() et renvoie tous les éléments pour lesquels le prédicat est faux :

itertools.filterfalse(is_even, itertools.count()) =>
  1, 3, 5, 7, 9, 11, 13, 15, ...

itertools.takewhile(predicate, iter) renvoie les éléments de l’itérateur tant que ceux-ci vérifient le prédicat. Dès lors que le prédicat renvoie faux, l’itération s’arrête.

def less_than_10(x):
    return x < 10

itertools.takewhile(less_than_10, itertools.count()) =>
  0, 1, 2, 3, 4, 5, 6, 7, 8, 9

itertools.takewhile(is_even, itertools.count()) =>
  0

itertools.dropwhile(predicate, iter) supprime des éléments tant que le prédicat renvoie vrai puis renvoie le reste des éléments de l’itérable.

itertools.dropwhile(less_than_10, itertools.count()) =>
  10, 11, 12, 13, 14, 15, 16, 17, 18, 19, ...

itertools.dropwhile(is_even, itertools.count()) =>
  1, 2, 3, 4, 5, 6, 7, 8, 9, 10, ...

itertools.compress(data, selectors) prend un itérateur data et un itérateur selectors et renvoie les éléments de data pour lesquels l’élément correspondant de selectors est évalué à vrai. L’itération s’arrête lorsque l’un des deux itérateurs est épuisé :

itertools.compress([1, 2, 3, 4, 5], [True, True, False, False, True]) =>
   1, 2, 5

Fonctions combinatoires

itertools.combinations(iterable, r) renvoie un itérateur qui produit toutes les combinaisons possibles de r-uplets des éléments de iterable.

itertools.combinations([1, 2, 3, 4, 5], 2) =>
  (1, 2), (1, 3), (1, 4), (1, 5),
  (2, 3), (2, 4), (2, 5),
  (3, 4), (3, 5),
  (4, 5)

itertools.combinations([1, 2, 3, 4, 5], 3) =>
  (1, 2, 3), (1, 2, 4), (1, 2, 5), (1, 3, 4), (1, 3, 5), (1, 4, 5),
  (2, 3, 4), (2, 3, 5), (2, 4, 5),
  (3, 4, 5)

Les éléments de chaque tuple sont ordonnés dans le même ordre que leur apparition dans iterable. Ainsi, dans les exemples ci-dessus, le nombre 1 se trouve toujours avant 2, 3, 4 ou 5. La fonction itertools.permutations(iterable, r=None) supprime la contrainte sur l’ordre et renvoie tous les arrangements possibles de longueur r :

itertools.permutations([1, 2, 3, 4, 5], 2) =>
  (1, 2), (1, 3), (1, 4), (1, 5),
  (2, 1), (2, 3), (2, 4), (2, 5),
  (3, 1), (3, 2), (3, 4), (3, 5),
  (4, 1), (4, 2), (4, 3), (4, 5),
  (5, 1), (5, 2), (5, 3), (5, 4)

itertools.permutations([1, 2, 3, 4, 5]) =>
  (1, 2, 3, 4, 5), (1, 2, 3, 5, 4), (1, 2, 4, 3, 5),
  ...
  (5, 4, 3, 2, 1)

Si vous ne spécifiez pas de valeur pour r, la longueur de l’itérable est utilisée par défaut, c’est-à-dire que toutes les permutations de la séquence sont renvoyées.

Notez que ces fonctions génèrent toutes les combinaisons possibles en se basant sur la position des éléments et ne requièrent pas que les éléments de iterable soient uniques :

itertools.permutations('aba', 3) =>
  ('a', 'b', 'a'), ('a', 'a', 'b'), ('b', 'a', 'a'),
  ('b', 'a', 'a'), ('a', 'a', 'b'), ('a', 'b', 'a')

Le triplet ('a', 'a', 'b') apparaît deux fois mais les deux chaînes de caractères 'a' proviennent de deux positions différentes.

La fonction itertools.combinations_with_replacement(iterable, r) assouplit une autre contrainte : les éléments peuvent être répétés au sein du même n-uplet. Il s’agit d’un tirage avec remise : le premier élément sélectionné pour chaque n-uplet est replacé dans la séquence avant le tirage du deuxième.

itertools.combinations_with_replacement([1, 2, 3, 4, 5], 2) =>
  (1, 1), (1, 2), (1, 3), (1, 4), (1, 5),
  (2, 2), (2, 3), (2, 4), (2, 5),
  (3, 3), (3, 4), (3, 5),
  (4, 4), (4, 5),
  (5, 5)

Grouper les éléments

La dernière fonction que allons voir, itertools.groupby(iter, key_func=None) est la plus complexe. key_func(elem) est une fonction qui produit une clé pour chaque élément renvoyé par l’itérable. Si vous ne spécifiez pas de fonction key, alors celle-ci est l’identité par défaut (c’est-à-dire que la clé d’un élément est l’élément lui-même).

groupby() rassemble tous éléments consécutifs de l’itérable sous-jacent qui ont la même clé et renvoie un flux de paires contenant la clé et un itérateur produisant la liste des éléments pour cette clé.

city_list = [('Decatur', 'AL'), ('Huntsville', 'AL'), ('Selma', 'AL'),
             ('Anchorage', 'AK'), ('Nome', 'AK'),
             ('Flagstaff', 'AZ'), ('Phoenix', 'AZ'), ('Tucson', 'AZ'),
             ...
            ]

def get_state(city_state):
    return city_state[1]

itertools.groupby(city_list, get_state) =>
  ('AL', iterator-1),
  ('AK', iterator-2),
  ('AZ', iterator-3), ...

where
iterator-1 =>
  ('Decatur', 'AL'), ('Huntsville', 'AL'), ('Selma', 'AL')
iterator-2 =>
  ('Anchorage', 'AK'), ('Nome', 'AK')
iterator-3 =>
  ('Flagstaff', 'AZ'), ('Phoenix', 'AZ'), ('Tucson', 'AZ')

groupby() fait l’hypothèse que le contenu de l’itérable sous-jacent est d’ores et déjà ordonné en fonction de la clé. Notez que les itérateurs générés utilisent également l’itérable sous-jacent. Vous devez donc consommer l’intégralité des résultats du premier itérateur renvoyé (iterator-1 dans l’exemple ci-dessus) avant de récupérer le deuxième itérateur (iterator-2 dans l’exemple ci-dessus) et la clé à laquelle il est associé.

Le module functools

Le module functools introduit par Python 2.5 contient diverses fonctions d’ordre supérieur. Une fonction d’ordre supérieur prend une ou plusieurs fonctions en entrée et renvoie une fonction. L’outil le plus important de ce module est la fonction functools.partial().

En programmant dans un style fonctionnel, il est courant de vouloir construire des variantes de fonctions existantes dont certains paramètres sont prédéfinis. Par exemple, considérons une fonction Python f(a, b, c). Si vous voulez une nouvelle fonction g(b, c) équivalente à f(1, b, c), c’est-à-dire fixer le premier paramètre de f(). La fonction g() est une appelée « application partielle » de f().

Le constructeur de partial() prend en argument (fonction, arg1, arg2, ..., kwarg1=value1, kwarg2=value2, ...). Un appel à l’objet ainsi créé invoque la fonction fonction avec les arguments spécifiés.

Voici un exemple court mais réaliste :

import functools

def log(message, subsystem):
    """Write the contents of 'message' to the specified subsystem."""
    print('%s: %s' % (subsystem, message))
    ...

server_log = functools.partial(log, subsystem='server')
server_log('Unable to open socket')

functools.reduce(func, iter, [initial_value]) applique une opération cumulative à tous les éléments d’un itérable et ne peut donc être appliquée à des itérables infinis. func doit être une fonction qui prend deux éléments et renvoie une seule valeur. functools.reduce() prend les deux premiers éléments A et B renvoyés par l’itérateur et calcule func(A, B). Elle extrait ensuite le troisième élément C et calcule func(func(A, B), C) puis combine ce résultat avec le quatrième élément renvoyé etc. jusqu’à épuisement de l’itérable. Une exception TypeError est levée si l’itérable ne renvoie aucune valeur. La valeur initiale initial_value, si spécifiée, est utilisée comme point de départ et le premier calcul est alors func(inital_value, A).

>>> import operator, functools
>>> functools.reduce(operator.concat, ['A', 'BB', 'C'])
'ABBC'
>>> functools.reduce(operator.concat, [])
Traceback (most recent call last):
  ...
TypeError: reduce() of empty sequence with no initial value
>>> functools.reduce(operator.mul, [1, 2, 3], 1)
6
>>> functools.reduce(operator.mul, [], 1)
1

Si vous combinez operator.add() avec functools.reduce(), vous allez additionner tous les éléments de l’itérable. Ce cas est suffisamment courant pour qu’il existe une fonction native sum() qui lui est équivalent :

>>> import functools, operator
>>> functools.reduce(operator.add, [1, 2, 3, 4], 0)
10
>>> sum([1, 2, 3, 4])
10
>>> sum([])
0

Cependant, il peut être plus lisible dans de nombreuses situations impliquant functools.reduce() de simplement écrire la boucle for :

import functools
# Instead of:
product = functools.reduce(operator.mul, [1, 2, 3], 1)

# You can write:
product = 1
for i in [1, 2, 3]:
    product *= i

itertools.accumulate(iterable, func=operator.add) est une fonction similaire qui réalise le même calcul mais, plutôt que de renvoyer seulement le résultat final, accumulate() renvoie un itérateur qui génère la séquence de tous les résultats intermédiaires :

itertools.accumulate([1, 2, 3, 4, 5]) =>
  1, 3, 6, 10, 15

itertools.accumulate([1, 2, 3, 4, 5], operator.mul) =>
  1, 2, 6, 24, 120

Le module operator

Le module operator mentionné précédemment contient un ensemble de fonctions reproduisant les opérateurs de Python. Ces fonctions sont souvent utiles en programmation fonctionnelle car elles permettent de ne pas avoir à écrire des fonctions triviales qui ne réalisent qu’une seule opération.

Voici quelques fonctions de ce module :

Les opérations mathématiques : add(), sub(), mul(), floordiv(), abs(), …

Les opérations logiques : not_(), truth().

Les opérations bit à bit : and_(), or_(), invert().

Les comparaisons : eq(), ne(), lt(), le(), gt(), et ge().

L’identification des objets : is_(), is_not().

Veuillez vous référer à la documentation du module operator pour une liste complète.

Expressions lambda et fonctions courtes

Dans un style de programmation fonctionnel, il est courant d’avoir besoin de petites fonctions utilisées comme prédicats ou pour combiner des éléments d’une façon ou d’une autre.

S’il existe une fonction native Python ou une fonction d’un module qui convient, vous n’avez pas besoin de définir de nouvelle fonction :

stripped_lines = [line.strip() for line in lines]
existing_files = filter(os.path.exists, file_list)

If the function you need doesn’t exist, you need to write it. One way to write small functions is to use the lambda statement. lambda takes a number of parameters and an expression combining these parameters, and creates an anonymous function that returns the value of the expression:

adder = lambda x, y: x+y

print_assign = lambda name, value: name + '=' + str(value)

Une autre façon de faire est de simplement utiliser l’instruction def afin de définir une fonction de la manière habituelle :

def adder(x, y):
    return x + y

def print_assign(name, value):
    return name + '=' + str(value)

La méthode à préférer est une question de style, en général l’auteur évite l’utilisation de lambda.

Une des raisons est que lambda ne peut pas définir toutes les fonctions. Le résultat doit pouvoir se calculer en une seule expression, ce qui signifie qu’il est impossible d’avoir des comparaisons if ... elif ... else à plusieurs branches ou des structures try ... except. Si vous essayez de trop en faire dans une expression lambda, vous finirez avec une expression illisible. Par exemple, pouvez-vous dire du premier coup d’œil ce que fait le code ci-dessous ?

import functools
total = functools.reduce(lambda a, b: (0, a[1] + b[1]), items)[1]

Vous pouvez sûrement comprendre ce que fait ce code mais cela prend du temps de démêler l’expression pour y voir plus clair. Une clause def concise améliore la situation :

import functools
def combine(a, b):
    return 0, a[1] + b[1]

total = functools.reduce(combine, items)[1]

Toutefois l’idéal aurait été de simplement se contenter d’une boucle for :

total = 0
for a, b in items:
    total += b

ou de la fonction native sum() et d’une expression génératrice :

total = sum(b for a, b in items)

Les boucles for sont souvent plus lisibles que la fonction functools.reduce().

Frederik Lundh a suggéré quelques règles pour le réusinage de code impliquant les expressions lambda :

Écrire une fonction lambda.

Écrire un commentaire qui explique ce que fait cette satanée fonction lambda.

Scruter le commentaire pendant quelques temps et réfléchir à un nom qui synthétise son essence.

Réécrire la fonction lambda en une définition def en utilisant ce nom.

Effacer le commentaire.

J’aime beaucoup ces règles mais vous êtes libre de ne pas être d’accord et de ne pas préférer ce style sans lambda.

Historique des modifications et remerciements

L’auteur souhaiterait remercier les personnes suivantes pour leurs suggestions, leurs corrections et leur aide sur les premières versions de cet article : Ian Bicking, Nick Coghlan, Nick Efford, Raymond Hettinger, Jim Jewett, Mike Krell, Leandro Lameiro, Jussi Salmela, Collin Winter, Blake Winton.

Version 0.1 : publiée le 30 juin 2006.

Version 0.11 : publiée le 1er juillet 2006. Correction orthographique.

Version 0.2 : publiée le 10 juillet 2006. Fusion des sections genexp et listcomp. Correction orthographique.

Version 0.21 : ajout de plusieurs références suggérées sur la liste de diffusion tutor.

Version 0.30 : ajout d’une section sur le module functional écrite par Collin Winter ; ajout d’une courte section sur le module operator ; quelques autres modifications.

Références

Général

Structure and Interpretation of Computer Programs par Harold Abelson et Gerald Jay Sussman avec Julie Sussman. Disponible à l’adresse https://mitpress.mit.edu/sicp/. Ce livre est un classique en informatique. Les chapitres 2 et 3 présentent l’utilisation des séquences et des flux pour organiser le flot de données dans un programme. Les exemples du livre utilisent le langage Scheme mais la plupart des approches décrites dans ces chapitres s’appliquent au style fonctionnel de Python.

http://www.defmacro.org/ramblings/fp.html : une présentation générale à la programmation fonctionnelle avec une longue introduction historique et des exemples en Java.

https://fr.wikipedia.org/wiki/Programmation_fonctionnelle : l’entrée Wikipédia qui décrit la programmation fonctionnelle.

https://fr.wikipedia.org/wiki/Coroutine : l’entrée pour les coroutines.

https://fr.wikipedia.org/wiki/Curryfication : l’entrée pour le concept de curryfication (création d’applications partielles).

Spécifique à Python

http://gnosis.cx/TPiP/ : le premier chapitre du livre de David Mertz Text Processing in Python présente l’utilisation de la programmation fonctionnelle pour le traitement de texte dans la section « Utilisation des fonctions d’ordre supérieur pour le traitement de texte ».

Mertz a également écrit une série de 3 articles (en anglais) sur la programmation fonctionnelle pour le site de IBM DeveloperWorks, voir la partie 1 [https://www.ibm.com/developerworks/linux/library/l-prog/index.html], la partie 2 [https://www.ibm.com/developerworks/linux/library/l-prog2/index.html] et la partie 3 [https://www.ibm.com/developerworks/linux/library/l-prog3/index.html].

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Tutoriel sur la journalisation

Auteur

Vinay Sajip <vinay_sajip at red-dove dot com>

Les bases de l’utilisation du module logging

La journalisation (logging en anglais) est une façon de suivre les événements qui ont lieu durant le fonctionnement d’un logiciel. Le développeur du logiciel ajoute des appels à l’outil de journalisation dans son code pour indiquer que certains événements ont eu lieu. Un événement est décrit par un message descriptif, qui peut éventuellement contenir des données variables (c’est-à-dire qui peuvent être différentes pour chaque occurrence de l’événement). Un événement a aussi une importance que le développeur lui attribue ; cette importance peut aussi être appelée niveau ou sévérité.

Quand utiliser logging

Le module logging fournit un ensemble de fonctions de commodités pour une utilisation simple du module. Ce sont les fonctions debug(), info(), warning(), error() et critical(). Pour déterminer quand employer la journalisation, voyez la table ci-dessous, qui vous indique, pour chaque tâche parmi les plus communes, l’outil approprié.

Tâche que vous souhaitez mener

Le meilleur outil pour cette tâche

Affiche la sortie console d’un script en ligne de commande ou d’un programme lors de son utilisation ordinaire

print()

Rapporter des évènements qui ont lieu au cours du fonctionnement normal d’un programme (par exemple pour suivre un statut ou examiner des dysfonctionnements)

logging.info() (ou logging.debug() pour une sortie très détaillée à visée diagnostique)

Émettre un avertissement (warning en anglais) en relation avec un évènement particulier au cours du fonctionnement d’un programme

warnings.warn() dans le code de la bibliothèque si le problème est évitable et l’application cliente doit être modifiée pour éliminer cet avertissement

logging.warning() si l’application cliente ne peut rien faire pour corriger la situation mais l’évènement devrait quand même être noté

Rapporter une erreur lors d’un évènement particulier en cours d’exécution

Lever une exception

Rapporter la suppression d’une erreur sans lever d’exception (par exemple pour la gestion d’erreur d’un processus de long terme sur un serveur)

logging.error(), logging.exception() ou logging.critical(), au mieux, selon l’erreur spécifique et le domaine d’application

Les fonctions de journalisation sont nommées d’après le niveau ou la sévérité des évènements qu’elles suivent. Les niveaux standards et leurs applications sont décrits ci-dessous (par ordre croissant de sévérité) :

Niveau

Quand il est utilisé

DEBUG

Information détaillée, intéressante seulement lorsqu’on diagnostique un problème.

INFO

Confirmation que tout fonctionne comme prévu.

WARNING

L’indication que quelque chose d’inattendu a eu lieu, ou de la possibilité d’un problème dans un futur proche (par exemple « espace disque faible »). Le logiciel fonctionne encore normalement.

ERROR

Du fait d’un problème plus sérieux, le logiciel n’a pas été capable de réaliser une tâche.

CRITICAL

Une erreur sérieuse, indiquant que le programme lui-même pourrait être incapable de continuer à fonctionner.

Le niveau par défaut est WARNING, ce qui signifie que seuls les évènements de ce niveau et au-dessus sont suivis, sauf si le paquet logging est configuré pour faire autrement.

Les évènements suivis peuvent être gérés de différentes façons. La manière la plus simple est de les afficher dans la console. Une autre méthode commune est de les écrire dans un fichier.

Un exemple simple

Un exemple très simple est :

import logging
logging.warning('Watch out!')  # will print a message to the console
logging.info('I told you so')  # will not print anything

Si vous entrez ces lignes dans un script que vous exécutez, vous verrez :

WARNING:root:Watch out!

affiché dans la console. Le message INFO n’apparaît pas parce que le niveau par défaut est WARNING. Le message affiché inclut l’indication du niveau et la description de l’évènement fournie dans l’appel à logging, ici « Watch out! ». Ne vous préoccupez pas de la partie « root » pour le moment : nous détaillerons ce point plus bas. La sortie elle-même peut être formatée de multiples manières si besoin. Les options de formatage seront aussi expliquées plus bas.

Enregistrer les évènements dans un fichier

Il est très commun d’enregistrer les évènements dans un fichier, c’est donc ce que nous allons regarder maintenant. Il faut essayer ce qui suit avec un interpréteur Python nouvellement démarré, ne poursuivez pas la session commencée ci-dessus :

import logging
logging.basicConfig(filename='example.log',level=logging.DEBUG)
logging.debug('This message should go to the log file')
logging.info('So should this')
logging.warning('And this, too')

Maintenant, si nous ouvrons le fichier et lisons ce qui s’y trouve, on trouvera les messages de log :

DEBUG:root:This message should go to the log file
INFO:root:So should this
WARNING:root:And this, too

Cet exemple montre aussi comment on peut régler le niveau de journalisation qui sert de seuil pour le suivi. Dans ce cas, comme nous avons réglé le seuil à DEBUG, tous les messages ont été écrits.

Si vous souhaitez régler le niveau de journalisation à partir d’une option de la ligne de commande comme :

--log=INFO

et que vous passez ensuite la valeur du paramètre donné à l’option –log dans une variable loglevel, vous pouvez utiliser :

getattr(logging, loglevel.upper())

de manière à obtenir la valeur à passer à basicConfig() à travers l’argument level. Vous pouvez vérifier que l’utilisateur n’a fait aucune erreur pour la valeur de ce paramètre, comme dans l’exemple ci-dessous :

# assuming loglevel is bound to the string value obtained from the
# command line argument. Convert to upper case to allow the user to
# specify --log=DEBUG or --log=debug
numeric_level = getattr(logging, loglevel.upper(), None)
if not isinstance(numeric_level, int):
    raise ValueError('Invalid log level: %s' % loglevel)
logging.basicConfig(level=numeric_level, ...)

L’appel à basicConfig() doit être fait avant un appel à debug(), info(), etc. Comme l’objectif est d’avoir un outil de configuration simple et d’usage unique, seul le premier appel aura un effet, les appels suivants ne font rien.

Si vous exécutez le script plusieurs fois, les messages des exécutions successives sont ajoutés au fichier example.log. Si vous voulez que chaque exécution reprenne un fichier vierge, sans conserver les messages des exécutions précédentes, vous pouvez spécifier l’argument filemode, en changeant l’appel à l’exemple précédent par :

logging.basicConfig(filename='example.log', filemode='w', level=logging.DEBUG)

La sortie est identique à la précédente, mais le texte n’est plus ajouté au fichier de log, donc les messages des exécutions précédentes sont perdus.

Employer logging à partir de différents modules

Si votre programme est composé de plusieurs modules, voici une façon d’organiser l’outil de journalisation :

# myapp.py
import logging
import mylib

def main():
    logging.basicConfig(filename='myapp.log', level=logging.INFO)
    logging.info('Started')
    mylib.do_something()
    logging.info('Finished')

if __name__ == '__main__':
    main()

# mylib.py
import logging

def do_something():
    logging.info('Doing something')

Si vous exécutez myapp.py, vous verrez ceci dans myapp.log :

INFO:root:Started
INFO:root:Doing something
INFO:root:Finished

ce qui est normalement ce à quoi vous vous attendiez. Vous pouvez généraliser cela à plusieurs modules, en employant le motif de mylib.py. Remarquez qu’avec cette méthode simple, vous ne pourrez pas savoir, en lisant le fichier de log, d’où viennent les messages dans votre application, sauf dans la description de l’évènement. Si vous voulez suivre la localisation des messages, référerez-vous à la documentation avancée Usage avancé de Logging.

Journalisation de données variables

Pour enregistrer des données variables, utilisez une chaîne formatée dans le message de description de l’évènement et ajoutez les données variables comme argument. Par exemple :

import logging
logging.warning('%s before you %s', 'Look', 'leap!')

affichera :

WARNING:root:Look before you leap!

Comme vous pouvez le voir, l’inclusion des données variables dans le message de description de l’évènement emploie le vieux style de formatage avec %. C’est pour assurer la rétrocompatibilité : le module logging est antérieur aux nouvelles options de formatage comme str.format() ou string.Template. Ces nouvelles options de formatage sont gérées, mais leur exploration sort du cadre de ce tutoriel, voyez Using particular formatting styles throughout your application pour plus d’information.

Modifier le format du message affiché

Pour changer le format utilisé pour afficher le message, vous devez préciser le format que vous souhaitez employer :

import logging
logging.basicConfig(format='%(levelname)s:%(message)s', level=logging.DEBUG)
logging.debug('This message should appear on the console')
logging.info('So should this')
logging.warning('And this, too')

ce qui affiche :

DEBUG:This message should appear on the console
INFO:So should this
WARNING:And this, too

Notez que le root qui apparaissait dans les exemples précédents a disparu. Pour voir l’ensemble des éléments qui peuvent apparaître dans la chaîne de format, référez-vous à la documentation pour LogRecord attributes. Pour une utilisation simple, vous avez seulement besoin du levelname (la sévérité), du message (la description de l’évènement, avec les données variables) et peut-être du moment auquel l’évènement a eu lieu. Nous décrivons ces points dans la prochaine section.

Afficher l’horodatage dans les messages

Pour afficher la date ou le temps d’un évènement, ajoutez %(asctime) dans votre chaîne de formatage :

import logging
logging.basicConfig(format='%(asctime)s %(message)s')
logging.warning('is when this event was logged.')

ce qui affichera quelque chose comme :

2010-12-12 11:41:42,612 is when this event was logged.

Le format par défaut de l’horodatage (comme ci-dessus) est donné par la norme ISO8601 ou RFC 3339 [https://tools.ietf.org/html/rfc3339.html]. Pour plus de contrôle sur le formatage de l’horodatage, vous pouvez fournir à basicConfig un argument datefmt, comme dans l’exemple suivant :

import logging
logging.basicConfig(format='%(asctime)s %(message)s', datefmt='%m/%d/%Y %I:%M:%S %p')
logging.warning('is when this event was logged.')

ce qui affichera quelque chose comme :

12/12/2010 11:46:36 AM is when this event was logged.

Le format de datefmt est le même que celui de time.strftime().

Étapes suivantes

Nous concluons ainsi le tutoriel basique. Il devrait suffire à vous mettre le pied à l’étrier pour utiliser logging. Le module logging a beaucoup d’autre cordes à son arc, mais pour en profiter au maximum, vous devez prendre le temps de lire les sections suivantes. Si vous êtes prêt, servez-vous votre boisson préférée et poursuivons.

If your logging needs are simple, then use the above examples to incorporate logging into your own scripts, and if you run into problems or don’t understand something, please post a question on the comp.lang.python Usenet group (available at https://groups.google.com/group/comp.lang.python) and you should receive help before too long.

Vous êtes encore là ? Vous pouvez lire les prochaines sections, qui donnent un peu plus de détails que l’introduction ci-dessus. Après ça, vous pouvez jeter un œil à Logging Cookbook.

Usage avancé de Logging

La bibliothèque de journalisation adopte une approche modulaire et offre différentes catégories de composants : loggers, handlers, filters et formatters.

Les enregistreurs (loggers en anglais) exposent l’interface que le code de l’application utilise directement.

Les gestionnaires (handlers) envoient les entrées de journal (créés par les loggers) vers les destinations voulues.

Les filtres (filters) fournissent un moyen de choisir finement quelles entrées de journal doivent être sorties.

Les formateurs (formatters) spécifient la structure de l’entrée de journal dans la sortie finale.

L’information relative à un événement est passée entre loggers, handlers et formatters dans une instance de la classe LogRecord.

La journalisation est réalisée en appelant les méthodes d’instance de la classe Logger (que l’on appelle ci-dessous loggers). Chaque instance a un nom et les instances sont organisées conceptuellement comme des hiérarchies dans l’espace de nommage, en utilisant un point comme séparateur. Par exemple, un logger appelé scan est le parent des loggers scan.text, scan.html et scan.pdf. Les noms des loggers peuvent être ce que vous voulez et indiquent le sous-domaine d’une application depuis lequel le message enregistré a été émis.

Une bonne convention lorsqu’on nomme les loggers est d’utiliser un logger au niveau du module, dans chaque module qui emploie logging, nommé de la façon suivante :

logger = logging.getLogger(__name__)

Cela signifie que le nom d’un logger se rapporte à la hiérarchie du paquet et des modules, et il est évident de voir où un événement a été enregistré simplement en regardant le nom du logger.

La racine de la hiérarchie des loggers est appelée le root logger. C’est le logger utilisé par les fonctions debug(), info(), warning(), error() et critical(), qui appelle en fait les méthodes du même nom de l’objet root logger. Les fonctions et les méthodes ont la même signature. Le nom du root logger est affiché comme « root » dans la sortie.

Il est bien sûr possible d’enregistrer des messages pour des destinations différentes. Ce paquet permet d’écrire des entrées de journal dans des fichiers, des ressources HTTP GET/POST, par courriel via SMTP, des connecteurs (socket en anglais) génériques, des files d’attente, ou des mécanismes d’enregistrement spécifiques au système d’exploitation, comme syslog ou le journal d’événements de Windows NT. Les destinations sont servies par des classes handler. Vous pouvez créer votre propre classe de destination si vous avez des besoins spéciaux qui ne sont couverts par aucune classe handler prédéfinie.

Par défaut, aucune destination n’est prédéfinie pour les messages de journalisation. Vous pouvez définir une destination (comme la console ou un fichier) en utilisant basicConfig() comme dans les exemples donnés dans le tutoriel. Si vous appelez les fonctions debug(), info(), warning(), error() et critical(), celles-ci vérifient si une destination a été définie ; si ce n’est pas le cas, la destination est assignée à la console (sys.stderr) avec un format par défaut pour le message affiché, avant d’être déléguée au logger racine, qui sort le message.

Le format par défaut des messages est défini par basicConfig() comme suit :

severity:logger name:message

Vous pouvez modifier ce comportement en passant une chaîne de formatage à basicConfig() par l’argument nommé format. Consultez Formatter Objects pour toutes les options de construction de cette chaîne de formatage.

Flux du processus de journalisation

Le flux des informations associées à un évènement dans les loggers et les handlers est illustré dans le diagramme suivant.

Loggers

Les objets de classe Logger ont un rôle triple. Premièrement, ils exposent plusieurs méthodes au code de l’application, de manière à ce qu’elle puisse enregistrer des messages en cours d’exécution. Deuxièmement, les objets logger déterminent sur quel message agir selon leur sévérité (à partir des filtres par défaut) ou selon les objets filter associés. Troisièmement, les objets logger transmettent les messages pertinents à tous les handlers concernés.

Les méthodes des objets logger les plus utilisées appartiennent à deux catégories : la configuration et l’envoi de messages.

Voici les méthodes de configuration les plus communes :

Logger.setLevel() spécifie le plus bas niveau de sévérité qu’un logger traitera. Ainsi, debug est le niveau de sévérité défini par défaut le plus bas et critical est le plus haut. Par exemple, si le niveau de sévérité est INFO, le logger ne traite que les messages de niveau INFO, WARNING, ERROR et CRITICAL ; il ignore les messages de niveau DEBUG.

Logger.addHandler() et Logger.removeHandler() ajoutent ou enlèvent des objets handlers au logger. Les objets handlers sont expliqués plus en détail dans Handlers.

Logger.addFilter() et Logger.removeFilter() ajoutent ou enlèvent des objets filter au logger. Les objets filters sont expliqués plus en détail dans Filter Objects.

Comme nous l’expliquons aux deux derniers paragraphes de cette section, vous n’avez pas besoin de faire appel à ces méthodes à chaque fois que vous créez un logger.

Une fois que l’objet logger est correctement configuré, les méthodes suivantes permettent de créer un message :

Les méthodes Logger.debug(), Logger.info(), Logger.warning(), Logger.error() et Logger.critical() créent des entrées de journal avec un message et un niveau correspondant à leur nom. Le message est en fait une chaîne de caractères qui peut contenir la syntaxe standard de substitution de chaînes de caractères : %s, %d, %f, etc. L’argument suivant est une liste des objets correspondant aux champs à substituer dans le message. En ce qui concerne **kwargs, les méthodes de logging ne tiennent compte que du mot clef exc_info et l’utilisent pour déterminer s’il faut enregistrer les informations associées à une exception.

Logger.exception() crée un message similaire à Logger.error(). La différence est que Logger.exception() ajoute la trace de la pile d’exécution au message. On ne peut appeler cette méthode qu’à l’intérieur d’un bloc de gestion d’exception.

Logger.log() prend le niveau de sévérité comme argument explicite. C’est un peu plus verbeux pour enregistrer des messages que d’utiliser les méthodes plus pratiques décrites si dessus, mais c’est ce qui permet d’enregistrer des messages pour des niveaux de sévérité définis par l’utilisateur.

getLogger() renvoie une référence à un objet logger du nom spécifié si celui-ci est donné en argument. Dans le cas contraire, se sera le logger root. Ces noms sont des structures hiérarchiques séparées par des points. Des appels répétés à getLogger() avec le même nom renvoient une référence au même objet logger. Les loggers qui sont plus bas dans cette liste hiérarchique sont des enfants des loggers plus haut dans la liste. Par exemple, si un logger a le nom foo, les loggers avec les noms foo.bar, foo.bar.baz, et foo.bam sont tous des descendants de foo.

On associe aux loggers un concept de niveau effectif. Si aucun niveau n’est explicitement défini pour un logger, c’est le niveau du parent qui est utilisé comme niveau effectif. Si le parent n’a pas de niveau défini, c’est celui de son parent qui est considéré, et ainsi de suite ; on examine tous les ancêtres jusqu’à ce qu’un niveau explicite soit trouvé. Le logger root a toujours un niveau explicite (WARNING par défaut). Quand le logger traite un événement, c’est ce niveau effectif qui est utilisé pour déterminer si cet événement est transmis à ses handlers.

Les loggers fils font remonter leurs messages aux handlers associés à leurs loggers parents. De ce fait, il n’est pas nécessaire de définir et configurer des handlers pour tous les loggers employés par une application. Il suffit de configurer les handlers pour un logger de haut niveau et de créer des loggers fils quand c’est nécessaire (on peut cependant empêcher la propagation aux ancêtres des messages en donnant la valeur False à l’attribut propagate d’un logger).

Handlers

Les objets de type Handler sont responsables de la distribution des messages (selon leur niveau de sévérité) vers les destinations spécifiées pour ce handler. Les objets Logger peuvent ajouter des objets handler à eux-mêmes en appelant addHandler(). Pour donner un exemple, une application peut envoyer tous les messages dans un fichier journal, tous les messages de niveau error ou supérieur vers la sortie standard, et tous les messages de niveau critical vers une adresse de courriel. Dans ce scenario, nous avons besoin de trois handlers, responsable chacun d’envoyer des messages d’une sévérité donnée vers une destination donnée.

La bibliothèque standard inclut déjà un bon nombre de types de gestionnaires (voir Gestionnaires utiles) ; le tutoriel utilise surtout StreamHandler et FileHandler dans ses exemples.

Peu de méthodes des objets handlers sont intéressantes pour les développeurs. Les seules méthodes intéressantes lorsqu’on utilise les objets handlers natifs (c’est à dire si l’on ne crée pas d”handler personnalisé) sont les méthodes de configuration suivantes :

La méthode setLevel(), comme celle des objets logger permet de spécifier le plus bas niveau de sévérité qui sera distribué à la destination appropriée. Pourquoi y a-t-il deux méthodes setLevel() ? Le niveau défini dans le logger détermine quelle sévérité doit avoir un message pour être transmis à ses handlers. Le niveau mis pour chaque handler détermine quels messages seront envoyés aux destinations.

setFormatter() sélectionne l’objet Formatter utilisé par cet handler.

addFilter() et removeFilter() configurent et respectivement dé-configurent des objets filter sur les handlers.

Le code d’une application ne devrait ni instancier, ni utiliser d’instances de la classe Handler. La classe Handler est plutôt d’une classe de base qui définit l’interface que tous les gestionnaires doivent avoir et établit les comportements par défaut que les classes filles peuvent employer (ou redéfinir).

Formatters

Les objets formatter configurent l’ordre final, la structure et le contenu du message. Contrairement à la classe de base logging.Handler, le code d’une application peut instancier un objet de classe formatter, même si vous pouvez toujours sous-classer formatter si vous avez besoin d’un comportement spécial dans votre application. Le constructeur a trois arguments optionnels : une chaîne de formatage du message, un chaîne de formatage de la date et un indicateur de style.

logging.Formatter.__init__(fmt=None, datefmt=None, style='%')

S’il n’y a pas de chaîne de formatage, la chaîne brute est utilisée par défaut. S’il n’y a pas de chaîne de formatage de date, le format de date par défaut est :

%Y-%m-%d %H:%M:%S

avec les millisecondes en suffixe. Le style est %, { ou $. Si aucun n’est spécifié, % sera utilisé.

Si l’argument style est %, la chaîne de formatage utilise %(<clef de dictionnaire>)s comme style de substitution de chaîne de caractères ; les clefs possibles sont documentées dans LogRecord attributes. Si le style est {, le message de la chaîne de formatage est compatible avec str.format() (en employant des arguments à mots clefs). Enfin si le style est $ alors la chaîne de formatage du message doit être conforme à ce qui est attendu de string.Template.substitute().

Modifié dans la version 3.2: Ajout du paramètre style.

La chaîne de formatage de message suivante enregistrera le temps dans un format lisible par les humains, la sévérité du message et son contenu, dans cet ordre :

'%(asctime)s - %(levelname)s - %(message)s'

Les formatters emploient une fonction configurable par l’utilisateur pour convertir le temps de création d’une entrée de journal en un tuple. Par défaut, time.localtime() est employé ; pour changer cela pour une instance particulière de formatter, assignez une fonction avec la même signature que time.localtime() ou time.gmtime() à l’attribut converter de cette instance. Pour changer cela pour tous les formatters, par exemple si vous voulez que tous votre horodatage soit affiché en GMT, changez l’attribut converter de la classe Formatter en time.gmtime.

Configuration de Logging

On peut configurer logging de trois façons :

Créer des loggers, handlers et formatters explicitement en utilisant du code Python qui appelle les méthodes de configuration listées ci-dessus.

Créer un fichier de configuration de logging et le lire en employant la fonction fileConfig().

Créer un dictionnaire d’informations de configuration et le passer à la fonction dictConfig().

Pour la documentation de référence de ces deux dernières options, voyez Configuration functions. L’exemple suivant configure un logger très simple, un handler employant la console, et un formatter simple en utilisant du code Python :

import logging

# create logger
logger = logging.getLogger('simple_example')
logger.setLevel(logging.DEBUG)

# create console handler and set level to debug
ch = logging.StreamHandler()
ch.setLevel(logging.DEBUG)

# create formatter
formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')

# add formatter to ch
ch.setFormatter(formatter)

# add ch to logger
logger.addHandler(ch)

# 'application' code
logger.debug('debug message')
logger.info('info message')
logger.warn('warn message')
logger.error('error message')
logger.critical('critical message')

L’exécution de ce module via la ligne de commande produit la sortie suivante :

$ python simple_logging_module.py
2005-03-19 15:10:26,618 - simple_example - DEBUG - debug message
2005-03-19 15:10:26,620 - simple_example - INFO - info message
2005-03-19 15:10:26,695 - simple_example - WARNING - warn message
2005-03-19 15:10:26,697 - simple_example - ERROR - error message
2005-03-19 15:10:26,773 - simple_example - CRITICAL - critical message

Le module Python suivant crée un logger, un handler et un formatter identiques à ceux de l’exemple détaillé au-dessus, au nom des objets près :

import logging
import logging.config

logging.config.fileConfig('logging.conf')

# create logger
logger = logging.getLogger('simpleExample')

# 'application' code
logger.debug('debug message')
logger.info('info message')
logger.warn('warn message')
logger.error('error message')
logger.critical('critical message')

Voici le fichier logging.conf :

[loggers]
keys=root,simpleExample

[handlers]
keys=consoleHandler

[formatters]
keys=simpleFormatter

[logger_root]
level=DEBUG
handlers=consoleHandler

[logger_simpleExample]
level=DEBUG
handlers=consoleHandler
qualname=simpleExample
propagate=0

[handler_consoleHandler]
class=StreamHandler
level=DEBUG
formatter=simpleFormatter
args=(sys.stdout,)

[formatter_simpleFormatter]
format=%(asctime)s - %(name)s - %(levelname)s - %(message)s
datefmt=

La sortie est presque identique à celle de l’exemple qui n’est pas basé sur un fichier de configuration :

$ python simple_logging_config.py
2005-03-19 15:38:55,977 - simpleExample - DEBUG - debug message
2005-03-19 15:38:55,979 - simpleExample - INFO - info message
2005-03-19 15:38:56,054 - simpleExample - WARNING - warn message
2005-03-19 15:38:56,055 - simpleExample - ERROR - error message
2005-03-19 15:38:56,130 - simpleExample - CRITICAL - critical message

Vous pouvez constatez les avantages de l’approche par fichier de configuration par rapport à celle du code Python, principalement la séparation de la configuration et du code, et la possibilité pour une personne qui ne code pas de modifier facilement les propriétés de logging.

Avertissement

The fileConfig() function takes a default parameter, disable_existing_loggers, which defaults to True for reasons of backward compatibility. This may or may not be what you want, since it will cause any loggers existing before the fileConfig() call to be disabled unless they (or an ancestor) are explicitly named in the configuration. Please refer to the reference documentation for more information, and specify False for this parameter if you wish.

The dictionary passed to dictConfig() can also specify a Boolean value with key disable_existing_loggers, which if not specified explicitly in the dictionary also defaults to being interpreted as True. This leads to the logger-disabling behaviour described above, which may not be what you want - in which case, provide the key explicitly with a value of False.

Notez que les noms de classe référencés dans le fichier de configuration doivent être relatifs au module logging, ou des valeurs absolues qui peuvent être résolues à travers les mécanismes d’importation habituels. Ainsi, on peut soit utiliser WatchedFileHandler (relativement au module logging) ou mypackage.mymodule.MyHandler (pour une classe définie dans le paquet mypackage et le module mymodule, si mypackage est disponible dans les chemins d’importation de Python).

Dans Python 3.2, un nouveau moyen de configuration de la journalisation a été introduit, à l’aide de dictionnaires pour contenir les informations de configuration. Cela fournit un sur-ensemble de la fonctionnalité décrite ci-dessus basée sur un fichier de configuration et c’est la méthode recommandée pour les nouvelles applications et les déploiements. Étant donné qu’un dictionnaire Python est utilisé pour contenir des informations de configuration et que vous pouvez remplir ce dictionnaire à l’aide de différents moyens, vous avez plus d’options pour la configuration. Par exemple, vous pouvez utiliser un fichier de configuration au format JSON ou, si vous avez accès à la fonctionnalité de traitement YAML, un fichier au format YAML, pour remplir le dictionnaire de configuration. Ou bien sûr, vous pouvez construire le dictionnaire dans le code Python, le recevoir sous forme de pickle sur un connecteur, ou utiliser n’importe quelle approche suivant la logique de votre application.

Voici un exemple définissant la même configuration que ci-dessus, au format YAML pour le dictionnaire correspondant à cette nouvelle approche :

version: 1
formatters:
  simple:
    format: '%(asctime)s - %(name)s - %(levelname)s - %(message)s'
handlers:
  console:
    class: logging.StreamHandler
    level: DEBUG
    formatter: simple
    stream: ext://sys.stdout
loggers:
  simpleExample:
    level: DEBUG
    handlers: [console]
    propagate: no
root:
  level: DEBUG
  handlers: [console]

Pour plus d’informations sur la journalisation à l’aide d’un dictionnaire, consultez Configuration functions.

Comportement par défaut (si aucune configuration n’est fournie)

Si aucune configuration de journalisation n’est fournie, il est possible d’avoir une situation où un événement doit faire l’objet d’une journalisation, mais où aucun gestionnaire ne peut être trouvé pour tracer l’événement. Le comportement du paquet logging dans ces circonstances dépend de la version Python.

Pour les versions de Python antérieures à 3.2, le comportement est le suivant :

Si logging.raiseExceptions vaut False (mode production), l’événement est silencieusement abandonné.

Si logging.raiseExceptions vaut True (mode de développement), un message No handlers could be found for logger X.Y.Z est écrit sur la sortie standard une fois.

Dans Python 3.2 et ultérieur, le comportement est le suivant :

L’événement est sorti à l’aide d’un « gestionnaire de dernier recours », stocké dans logging.lastResort. Ce gestionnaire interne n’est associé à aucun enregistreur et agit comme un StreamHandler qui écrit le message de description de l’événement vers la valeur actuelle de sys.stderr (par conséquent, en respectant les redirections qui peuvent être en vigueur). Aucun formatage n’est fait sur le message – juste le message de description de l’événement nu est affiché. Le niveau du gestionnaire est défini sur WARNING, de sorte que tous les événements de cette sévérité et plus seront écrits.

Pour obtenir un comportement antérieur à 3.2, logging.lastResort peut être mis à None.

Configuration de la journalisation pour une bibliothèque

Lors du développement d’une bibliothèque qui utilise la journalisation, vous devez prendre soin de documenter la façon dont la bibliothèque utilise la journalisation (par exemple, les noms des enregistreurs utilisés). Consacrez aussi un peu de temps à la configuration de la journalisation. Si l’application utilisant votre bibliothèque n’utilise pas la journalisation et que le code de la bibliothèque effectue des appels de journalisation, alors (comme décrit dans la section précédente), les événements de gravité WARNING et au-dessus seront écrits sur sys.stderr. Cela est considéré comme le meilleur comportement par défaut.

If for some reason you don’t want these messages printed in the absence of any logging configuration, you can attach a do-nothing handler to the top-level logger for your library. This avoids the message being printed, since a handler will be always be found for the library’s events: it just doesn’t produce any output. If the library user configures logging for application use, presumably that configuration will add some handlers, and if levels are suitably configured then logging calls made in library code will send output to those handlers, as normal.

Un gestionnaire ne-fait-rien est inclus dans le paquet de journalisation : NullHandler (depuis Python 3.1). Une instance de ce gestionnaire peut être ajoutée à l’enregistreur de niveau supérieur de l’espace de nommage de journalisation utilisé par la bibliothèque (si vous souhaitez empêcher la copie de la journalisation de votre bibliothèque dans sys.stderr en l’absence de configuration de journalisation). Si toute la journalisation par une bibliothèque foo est effectuée en utilisant des enregistreurs avec des noms correspondant à foo.x, foo.x.y, etc., alors le code :

import logging
logging.getLogger('foo').addHandler(logging.NullHandler())

doit avoir l’effet désiré. Si une organisation produit un certain nombre de bibliothèques, le nom de l’enregistreur spécifié peut être orgname.foo plutôt que simplement foo.

Note

Il est vivement conseillé de ne pas ajouter de gestionnaires autres que NullHandler aux enregistreurs de votre bibliothèque. Cela est dû au fait que la configuration des gestionnaires est la prérogative du développeur d’applications qui utilise votre bibliothèque. Le développeur d’applications connaît le public cible et les gestionnaires les plus appropriés pour ses applications : si vous ajoutez des gestionnaires « sous le manteau », vous pourriez bien interférer avec les tests unitaires et la journalisation qui convient à ses exigences.

Niveaux de journalisation

Les valeurs numériques des niveaux de journalisation sont données dans le tableau suivant. Celles-ci n’ont d’intérêt que si vous voulez définir vos propres niveaux, avec des valeurs spécifiques par rapport aux niveaux prédéfinis. Si vous définissez un niveau avec la même valeur numérique, il écrase la valeur prédéfinie ; le nom prédéfini est perdu.

Niveau

Valeur numérique

CRITICAL

50

ERROR

40

WARNING

30

INFO

20

DEBUG

10

NOTSET

0

Les niveaux peuvent également être associés à des enregistreurs, étant définis soit par le développeur, soit par le chargement d’une configuration de journalisation enregistrée. Lorsqu’une méthode de journalisation est appelée sur un enregistreur, l’enregistreur compare son propre niveau avec le niveau associé à l’appel de méthode. Si le niveau de l’enregistreur est supérieur à l’appel de méthode, aucun message de journalisation n’est réellement généré. C’est le mécanisme de base contrôlant la verbosité de la sortie de journalisation.

Les messages de journalisation sont codés en tant qu’instances de LogRecord. Lorsqu’un enregistreur décide de réellement enregistrer un événement, une instance de LogRecord est créée à partir du message de journalisation.

Les messages de journalisation sont soumis à un mécanisme d’expédition via l’utilisation de handlers, qui sont des instances de sous-classes de la classe Handler. Les gestionnaires sont chargés de s’assurer qu’un message journalisé (sous la forme d’un LogRecord) atterrit dans un emplacement particulier (ou un ensemble d’emplacements) qui est utile pour le public cible pour ce message (tels que les utilisateurs finaux, le personnel chargé de l’assistance aux utilisateurs, les administrateurs système ou les développeurs). Des instances de LogRecord adaptées à leur destination finale sont passées aux gestionnaires destinées à des destinations particulières. Chaque enregistreur peut avoir zéro, un ou plusieurs gestionnaires associés à celui-ci (via la méthode addHandler() de Logger). En plus de tous les gestionnaires directement associés à un enregistreur, tous les gestionnaires associés à tous les ancêtres de l’enregistreur sont appelés pour envoyer le message (à moins que l’indicateur propager pour un enregistreur soit défini sur la valeur False, auquel cas le passage à l’ancêtre gestionnaires s’arrête).

Tout comme pour les enregistreurs, les gestionnaires peuvent avoir des niveaux associés. Le niveau d’un gestionnaire agit comme un filtre de la même manière que le niveau d’un enregistreur. Si un gestionnaire décide de réellement distribuer un événement, la méthode emit() est utilisée pour envoyer le message à sa destination. La plupart des sous-classes définies par l’utilisateur de Handler devront remplacer ce emit().

Niveaux personnalisés

La définition de vos propres niveaux est possible, mais ne devrait pas être nécessaire, car les niveaux existants ont été choisis par expérience. Cependant, si vous êtes convaincu que vous avez besoin de niveaux personnalisés, prenez grand soin à leur réalisation et il est pratiquement certain que c’est une très mauvaise idée de définir des niveaux personnalisés si vous développez une bibliothèque. Car si plusieurs auteurs de bibliothèque définissent tous leurs propres niveaux personnalisés, il y a une chance que la sortie de journalisation de ces multiples bibliothèques utilisées ensemble sera difficile pour le développeur à utiliser pour contrôler et/ou interpréter, car une valeur numérique donnée peut signifier des choses différentes pour différentes bibliothèques.

Gestionnaires utiles

En plus de la classe de base Handler, de nombreuses sous-classes utiles sont fournies :

Les instances StreamHandler envoient des messages aux flux (objets de type fichier).

Les instances FileHandler envoient des messages à des fichiers sur le disque.

BaseRotatingHandler est la classe de base pour les gestionnaires qui assurent la rotation des fichiers de journalisation à partir d’un certain point. Elle n’est pas destinée à être instanciée directement. Utilisez plutôt RotatingFileHandler ou TimedRotatingFileHandler.

Les instances RotatingFileHandler envoient des messages à des fichiers sur le disque, avec la prise en charge des tailles maximales de fichiers de journalisation et de la rotation des fichiers de journalisation.

Les instances de TimedRotatingFileHandler envoient des messages aux fichiers de disque, en permutant le fichier journal à intervalles réguliers.

Les instances de SocketHandler envoient des messages aux connecteurs TCP/IP. Depuis 3.4, les connecteurs UNIX sont également pris en charge.

Les instances de DatagramHandler envoient des messages aux connecteurs UDP. Depuis 3.4, les connecteurs UNIX sont également pris en charge.

Les instances de SMTPHandler envoient des messages à une adresse e-mail désignée.

Les instances de SysLogHandler envoient des messages à un daemon syslog UNIX, éventuellement sur un ordinateur distant.

Les instances de NTEventLogHandler envoient des messages à un journal des événements Windows NT/2000/XP.

Les instances de MemoryHandler envoient des messages à un tampon en mémoire, qui est vidé chaque fois que des critères spécifiques sont remplis.

Les instances de HTTPHandler envoient des messages à un serveur HTTP à l’aide de la sémantique GET ou POST.

Les instances de WatchedFileHandler surveillent le fichier sur lequel elles se connectent. Si le fichier change, il est fermé et rouvert à l’aide du nom de fichier. Ce gestionnaire n’est utile que sur les systèmes de type UNIX ; Windows ne prend pas en charge le mécanisme sous-jacent utilisé.

Les instances de QueueHandler envoient des messages à une file d’attente, telles que celles implémentées dans les modules queue ou multiprocessing.

Les instances NullHandler ne font rien avec les messages d’erreur. Ils sont utilisés par les développeurs de bibliothèques qui veulent utiliser la journalisation, mais qui veulent éviter les messages de type No handlers could be found for logger XXX, affiché si celui qui utilise la bibliothèque n’a pas configuré la journalisation. Voir Configuration de la journalisation pour une bibliothèque pour plus d’informations.

Nouveau dans la version 3.1: La classe NullHandler.

Nouveau dans la version 3.2: La classe QueueHandler.

The NullHandler, StreamHandler and FileHandler classes are defined in the core logging package. The other handlers are defined in a sub-module, logging.handlers. (There is also another sub-module, logging.config, for configuration functionality.)

Les messages journalisés sont mis en forme pour la présentation via des instances de la classe Formatter. Ils sont initialisés avec une chaîne de format appropriée pour une utilisation avec l’opérateur % et un dictionnaire.

Pour formater plusieurs messages dans un lot, des instances de BufferingFormatter peuvent être utilisées. En plus de la chaîne de format (qui est appliquée à chaque message dans le lot), il existe des dispositions pour les chaînes de format d’en-tête et de fin.

Lorsque le filtrage basé sur le niveau de l’enregistreur et/ou le niveau du gestionnaire ne suffit pas, les instances de Filter peuvent être ajoutées aux deux instances de Logger et Handler (par le biais de leur méthode addFilter()). Avant de décider de traiter un message plus loin, les enregistreurs et les gestionnaires consultent tous leurs filtres pour obtenir l’autorisation. Si un filtre renvoie une valeur False, le traitement du message est arrêté.

La fonctionnalité de base Filter permet de filtrer par nom de logger spécifique. Si cette fonctionnalité est utilisée, les messages envoyés à l’enregistreur nommé et à ses enfants sont autorisés via le filtre et tous les autres sont abandonnés.

Exceptions levées par la journalisation

Le paquet de journalisation est conçu pour ne pas faire apparaître les exceptions qui se produisent lors de la journalisation en production. Il s’agit de sorte que les erreurs qui se produisent lors de la gestion des événements de journalisation (telles qu’une mauvaise configuration de la journalisation, une erreur réseau ou d’autres erreurs similaires) ne provoquent pas l’arrêt de l’application utilisant la journalisation.

Les exceptions SystemExit et KeyboardInterrupt ne sont jamais passées sous silence. Les autres exceptions qui se produisent pendant la méthode emit() d’une sous classe Handler sont passées à sa méthode handleError().

L’implémentation par défaut de handleError() dans la classe Handler vérifie si une variable au niveau du module, raiseExceptions, est définie. Si cette valeur est définie, la trace de la pile d’appels est affichée sur sys.stderr. Si elle n’est pas définie, l’exception est passée sous silence.

Note

La valeur par défaut de raiseExceptions est True. C’est parce que pendant le développement, vous voulez généralement être notifié de toutes les exceptions qui se produisent. Il est conseillé de définir raiseExceptions à False pour une utilisation en production.

Utilisation d’objets arbitraires comme messages

Dans les sections et exemples précédents, il a été supposé que le message passé lors de la journalisation de l’événement est une chaîne. Cependant, ce n’est pas la seule possibilité. Vous pouvez passer un objet arbitraire en tant que message et sa méthode __str__() est appelée lorsque le système de journalisation doit le convertir en une représentation sous forme de chaîne. En fait, si vous le souhaitez, vous pouvez complètement éviter de calculer une représentation sous forme de chaîne. Par exemple, les gestionnaires SocketHandler émettent un événement en lui appliquant pickle et en l’envoyant sur le réseau.

Optimisation

La mise en forme des arguments de message est différée jusqu’à ce qu’elle ne puisse pas être évitée. Toutefois, le calcul des arguments passés à la méthode de journalisation peut également être coûteux et vous voudrez peut-être éviter de le faire si l’enregistreur va simplement jeter votre événement. Pour décider de ce qu’il faut faire, vous pouvez appeler la méthode isEnabledFor() qui prend en argument le niveau et renvoie True si un événement est créé par l’enregistreur pour ce niveau d’appel. Vous pouvez écrire un code qui ressemble à ça :

if logger.isEnabledFor(logging.DEBUG):
    logger.debug('Message with %s, %s', expensive_func1(),
                                        expensive_func2())

de sorte que si le seuil du journaliseur est défini au-dessus de DEBUG, les appels à expensive_func1() et expensive_func2() ne sont jamais faits.

Note

Dans certains cas, isEnabledFor() peut être plus coûteux que vous le souhaitez (par exemple pour les enregistreurs profondément imbriqués où un niveau explicite n’est défini que dans la hiérarchie des enregistreurs). Dans de tels cas (ou si vous souhaitez éviter d’appeler une méthode dans des boucles optimisées), vous pouvez mettre en cache le résultat d’un appel à isEnabledFor() dans une variable locale ou d’instance, et l’utiliser au lieu d’appeler la méthode à chaque fois. Une telle valeur mise en cache ne doit être recalculée que lorsque la configuration de journalisation change dynamiquement pendant l’exécution de l’application (ce qui est rarement le cas).

Il existe d’autres optimisations qui peuvent être faites pour des applications spécifiques qui nécessitent un contrôle plus précis sur les informations de journalisation collectées. Voici une liste de choses que vous pouvez faire pour éviter le traitement pendant la journalisation dont vous n’avez pas besoin :

Ce que vous ne voulez pas collecter

Comment éviter de le collecter

Informations sur l’endroit où les appels ont été faits.

Définissez logging._srcfile à None. Cela évite d’appeler sys._getframe(), qui peut aider à accélérer votre code dans des environnements comme PyPy (qui ne peut pas accélérer le code qui utilise sys._getframe()), si et quand PyPy prendra en charge Python 3.x.

Informations de threading.

Mettez logging.logThreads à 0.

Informations sur le processus.

Mettez logging.logProcesses à 0.

Notez également que le module de journalisation principale inclut uniquement les gestionnaires de base. Si vous n’importez pas logging.handlers et logging.config, ils ne prendront pas de mémoire.

Voir aussi

Module logging

Référence d’API pour le module de journalisation.

Module logging.config

API de configuration pour le module de journalisation.

Module logging.handlers

Gestionnaires utiles inclus avec le module de journalisation.

A logging cookbook

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Logging Cookbook

Auteur

Vinay Sajip <vinay_sajip at red-dove dot com>

This page contains a number of recipes related to logging, which have been found useful in the past.

Using logging in multiple modules

Multiple calls to logging.getLogger('someLogger') return a reference to the same logger object. This is true not only within the same module, but also across modules as long as it is in the same Python interpreter process. It is true for references to the same object; additionally, application code can define and configure a parent logger in one module and create (but not configure) a child logger in a separate module, and all logger calls to the child will pass up to the parent. Here is a main module:

import logging
import auxiliary_module

# create logger with 'spam_application'
logger = logging.getLogger('spam_application')
logger.setLevel(logging.DEBUG)
# create file handler which logs even debug messages
fh = logging.FileHandler('spam.log')
fh.setLevel(logging.DEBUG)
# create console handler with a higher log level
ch = logging.StreamHandler()
ch.setLevel(logging.ERROR)
# create formatter and add it to the handlers
formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
fh.setFormatter(formatter)
ch.setFormatter(formatter)
# add the handlers to the logger
logger.addHandler(fh)
logger.addHandler(ch)

logger.info('creating an instance of auxiliary_module.Auxiliary')
a = auxiliary_module.Auxiliary()
logger.info('created an instance of auxiliary_module.Auxiliary')
logger.info('calling auxiliary_module.Auxiliary.do_something')
a.do_something()
logger.info('finished auxiliary_module.Auxiliary.do_something')
logger.info('calling auxiliary_module.some_function()')
auxiliary_module.some_function()
logger.info('done with auxiliary_module.some_function()')

Here is the auxiliary module:

import logging

# create logger
module_logger = logging.getLogger('spam_application.auxiliary')

class Auxiliary:
    def __init__(self):
        self.logger = logging.getLogger('spam_application.auxiliary.Auxiliary')
        self.logger.info('creating an instance of Auxiliary')

    def do_something(self):
        self.logger.info('doing something')
        a = 1 + 1
        self.logger.info('done doing something')

def some_function():
    module_logger.info('received a call to "some_function"')

La sortie ressemble à ceci :

2005-03-23 23:47:11,663 - spam_application - INFO -
   creating an instance of auxiliary_module.Auxiliary
2005-03-23 23:47:11,665 - spam_application.auxiliary.Auxiliary - INFO -
   creating an instance of Auxiliary
2005-03-23 23:47:11,665 - spam_application - INFO -
   created an instance of auxiliary_module.Auxiliary
2005-03-23 23:47:11,668 - spam_application - INFO -
   calling auxiliary_module.Auxiliary.do_something
2005-03-23 23:47:11,668 - spam_application.auxiliary.Auxiliary - INFO -
   doing something
2005-03-23 23:47:11,669 - spam_application.auxiliary.Auxiliary - INFO -
   done doing something
2005-03-23 23:47:11,670 - spam_application - INFO -
   finished auxiliary_module.Auxiliary.do_something
2005-03-23 23:47:11,671 - spam_application - INFO -
   calling auxiliary_module.some_function()
2005-03-23 23:47:11,672 - spam_application.auxiliary - INFO -
   received a call to 'some_function'
2005-03-23 23:47:11,673 - spam_application - INFO -
   done with auxiliary_module.some_function()

Logging from multiple threads

Logging from multiple threads requires no special effort. The following example shows logging from the main (initial) thread and another thread:

import logging
import threading
import time

def worker(arg):
    while not arg['stop']:
        logging.debug('Hi from myfunc')
        time.sleep(0.5)

def main():
    logging.basicConfig(level=logging.DEBUG, format='%(relativeCreated)6d %(threadName)s %(message)s')
    info = {'stop': False}
    thread = threading.Thread(target=worker, args=(info,))
    thread.start()
    while True:
        try:
            logging.debug('Hello from main')
            time.sleep(0.75)
        except KeyboardInterrupt:
            info['stop'] = True
            break
    thread.join()

if __name__ == '__main__':
    main()

When run, the script should print something like the following:

   0 Thread-1 Hi from myfunc
   3 MainThread Hello from main
 505 Thread-1 Hi from myfunc
 755 MainThread Hello from main
1007 Thread-1 Hi from myfunc
1507 MainThread Hello from main
1508 Thread-1 Hi from myfunc
2010 Thread-1 Hi from myfunc
2258 MainThread Hello from main
2512 Thread-1 Hi from myfunc
3009 MainThread Hello from main
3013 Thread-1 Hi from myfunc
3515 Thread-1 Hi from myfunc
3761 MainThread Hello from main
4017 Thread-1 Hi from myfunc
4513 MainThread Hello from main
4518 Thread-1 Hi from myfunc

This shows the logging output interspersed as one might expect. This approach works for more threads than shown here, of course.

Multiple handlers and formatters

Loggers are plain Python objects. The addHandler() method has no minimum or maximum quota for the number of handlers you may add. Sometimes it will be beneficial for an application to log all messages of all severities to a text file while simultaneously logging errors or above to the console. To set this up, simply configure the appropriate handlers. The logging calls in the application code will remain unchanged. Here is a slight modification to the previous simple module-based configuration example:

import logging

logger = logging.getLogger('simple_example')
logger.setLevel(logging.DEBUG)
# create file handler which logs even debug messages
fh = logging.FileHandler('spam.log')
fh.setLevel(logging.DEBUG)
# create console handler with a higher log level
ch = logging.StreamHandler()
ch.setLevel(logging.ERROR)
# create formatter and add it to the handlers
formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
ch.setFormatter(formatter)
fh.setFormatter(formatter)
# add the handlers to logger
logger.addHandler(ch)
logger.addHandler(fh)

# 'application' code
logger.debug('debug message')
logger.info('info message')
logger.warn('warn message')
logger.error('error message')
logger.critical('critical message')

Notice that the “application” code does not care about multiple handlers. All that changed was the addition and configuration of a new handler named fh.

The ability to create new handlers with higher- or lower-severity filters can be very helpful when writing and testing an application. Instead of using many print statements for debugging, use logger.debug: Unlike the print statements, which you will have to delete or comment out later, the logger.debug statements can remain intact in the source code and remain dormant until you need them again. At that time, the only change that needs to happen is to modify the severity level of the logger and/or handler to debug.

Logging to multiple destinations

Let’s say you want to log to console and file with different message formats and in differing circumstances. Say you want to log messages with levels of DEBUG and higher to file, and those messages at level INFO and higher to the console. Let’s also assume that the file should contain timestamps, but the console messages should not. Here’s how you can achieve this:

import logging

# set up logging to file - see previous section for more details
logging.basicConfig(level=logging.DEBUG,
                    format='%(asctime)s %(name)-12s %(levelname)-8s %(message)s',
                    datefmt='%m-%d %H:%M',
                    filename='/temp/myapp.log',
                    filemode='w')
# define a Handler which writes INFO messages or higher to the sys.stderr
console = logging.StreamHandler()
console.setLevel(logging.INFO)
# set a format which is simpler for console use
formatter = logging.Formatter('%(name)-12s: %(levelname)-8s %(message)s')
# tell the handler to use this format
console.setFormatter(formatter)
# add the handler to the root logger
logging.getLogger('').addHandler(console)

# Now, we can log to the root logger, or any other logger. First the root...
logging.info('Jackdaws love my big sphinx of quartz.')

# Now, define a couple of other loggers which might represent areas in your
# application:

logger1 = logging.getLogger('myapp.area1')
logger2 = logging.getLogger('myapp.area2')

logger1.debug('Quick zephyrs blow, vexing daft Jim.')
logger1.info('How quickly daft jumping zebras vex.')
logger2.warning('Jail zesty vixen who grabbed pay from quack.')
logger2.error('The five boxing wizards jump quickly.')

When you run this, on the console you will see

root        : INFO     Jackdaws love my big sphinx of quartz.
myapp.area1 : INFO     How quickly daft jumping zebras vex.
myapp.area2 : WARNING  Jail zesty vixen who grabbed pay from quack.
myapp.area2 : ERROR    The five boxing wizards jump quickly.

and in the file you will see something like

10-22 22:19 root         INFO     Jackdaws love my big sphinx of quartz.
10-22 22:19 myapp.area1  DEBUG    Quick zephyrs blow, vexing daft Jim.
10-22 22:19 myapp.area1  INFO     How quickly daft jumping zebras vex.
10-22 22:19 myapp.area2  WARNING  Jail zesty vixen who grabbed pay from quack.
10-22 22:19 myapp.area2  ERROR    The five boxing wizards jump quickly.

As you can see, the DEBUG message only shows up in the file. The other messages are sent to both destinations.

This example uses console and file handlers, but you can use any number and combination of handlers you choose.

Configuration server example

Here is an example of a module using the logging configuration server:

import logging
import logging.config
import time
import os

# read initial config file
logging.config.fileConfig('logging.conf')

# create and start listener on port 9999
t = logging.config.listen(9999)
t.start()

logger = logging.getLogger('simpleExample')

try:
    # loop through logging calls to see the difference
    # new configurations make, until Ctrl+C is pressed
    while True:
        logger.debug('debug message')
        logger.info('info message')
        logger.warn('warn message')
        logger.error('error message')
        logger.critical('critical message')
        time.sleep(5)
except KeyboardInterrupt:
    # cleanup
    logging.config.stopListening()
    t.join()

And here is a script that takes a filename and sends that file to the server, properly preceded with the binary-encoded length, as the new logging configuration:

#!/usr/bin/env python
import socket, sys, struct

with open(sys.argv[1], 'rb') as f:
    data_to_send = f.read()

HOST = 'localhost'
PORT = 9999
s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
print('connecting...')
s.connect((HOST, PORT))
print('sending config...')
s.send(struct.pack('>L', len(data_to_send)))
s.send(data_to_send)
s.close()
print('complete')

Dealing with handlers that block

Sometimes you have to get your logging handlers to do their work without blocking the thread you’re logging from. This is common in Web applications, though of course it also occurs in other scenarios.

A common culprit which demonstrates sluggish behaviour is the SMTPHandler: sending emails can take a long time, for a number of reasons outside the developer’s control (for example, a poorly performing mail or network infrastructure). But almost any network-based handler can block: Even a SocketHandler operation may do a DNS query under the hood which is too slow (and this query can be deep in the socket library code, below the Python layer, and outside your control).

One solution is to use a two-part approach. For the first part, attach only a QueueHandler to those loggers which are accessed from performance-critical threads. They simply write to their queue, which can be sized to a large enough capacity or initialized with no upper bound to their size. The write to the queue will typically be accepted quickly, though you will probably need to catch the queue.Full exception as a precaution in your code. If you are a library developer who has performance-critical threads in their code, be sure to document this (together with a suggestion to attach only QueueHandlers to your loggers) for the benefit of other developers who will use your code.

The second part of the solution is QueueListener, which has been designed as the counterpart to QueueHandler. A QueueListener is very simple: it’s passed a queue and some handlers, and it fires up an internal thread which listens to its queue for LogRecords sent from QueueHandlers (or any other source of LogRecords, for that matter). The LogRecords are removed from the queue and passed to the handlers for processing.

The advantage of having a separate QueueListener class is that you can use the same instance to service multiple QueueHandlers. This is more resource-friendly than, say, having threaded versions of the existing handler classes, which would eat up one thread per handler for no particular benefit.

An example of using these two classes follows (imports omitted):

que = queue.Queue(-1)  # no limit on size
queue_handler = QueueHandler(que)
handler = logging.StreamHandler()
listener = QueueListener(que, handler)
root = logging.getLogger()
root.addHandler(queue_handler)
formatter = logging.Formatter('%(threadName)s: %(message)s')
handler.setFormatter(formatter)
listener.start()
# The log output will display the thread which generated
# the event (the main thread) rather than the internal
# thread which monitors the internal queue. This is what
# you want to happen.
root.warning('Look out!')
listener.stop()

which, when run, will produce:

MainThread: Look out!

Modifié dans la version 3.5: Prior to Python 3.5, the QueueListener always passed every message received from the queue to every handler it was initialized with. (This was because it was assumed that level filtering was all done on the other side, where the queue is filled.) From 3.5 onwards, this behaviour can be changed by passing a keyword argument respect_handler_level=True to the listener’s constructor. When this is done, the listener compares the level of each message with the handler’s level, and only passes a message to a handler if it’s appropriate to do so.

Sending and receiving logging events across a network

Let’s say you want to send logging events across a network, and handle them at the receiving end. A simple way of doing this is attaching a SocketHandler instance to the root logger at the sending end:

import logging, logging.handlers

rootLogger = logging.getLogger('')
rootLogger.setLevel(logging.DEBUG)
socketHandler = logging.handlers.SocketHandler('localhost',
                    logging.handlers.DEFAULT_TCP_LOGGING_PORT)
# don't bother with a formatter, since a socket handler sends the event as
# an unformatted pickle
rootLogger.addHandler(socketHandler)

# Now, we can log to the root logger, or any other logger. First the root...
logging.info('Jackdaws love my big sphinx of quartz.')

# Now, define a couple of other loggers which might represent areas in your
# application:

logger1 = logging.getLogger('myapp.area1')
logger2 = logging.getLogger('myapp.area2')

logger1.debug('Quick zephyrs blow, vexing daft Jim.')
logger1.info('How quickly daft jumping zebras vex.')
logger2.warning('Jail zesty vixen who grabbed pay from quack.')
logger2.error('The five boxing wizards jump quickly.')

At the receiving end, you can set up a receiver using the socketserver module. Here is a basic working example:

import pickle
import logging
import logging.handlers
import socketserver
import struct

class LogRecordStreamHandler(socketserver.StreamRequestHandler):
    """Handler for a streaming logging request.

    This basically logs the record using whatever logging policy is
    configured locally.
    """

    def handle(self):
        """
        Handle multiple requests - each expected to be a 4-byte length,
        followed by the LogRecord in pickle format. Logs the record
        according to whatever policy is configured locally.
        """
        while True:
            chunk = self.connection.recv(4)
            if len(chunk) < 4:
                break
            slen = struct.unpack('>L', chunk)[0]
            chunk = self.connection.recv(slen)
            while len(chunk) < slen:
                chunk = chunk + self.connection.recv(slen - len(chunk))
            obj = self.unPickle(chunk)
            record = logging.makeLogRecord(obj)
            self.handleLogRecord(record)

    def unPickle(self, data):
        return pickle.loads(data)

    def handleLogRecord(self, record):
        # if a name is specified, we use the named logger rather than the one
        # implied by the record.
        if self.server.logname is not None:
            name = self.server.logname
        else:
            name = record.name
        logger = logging.getLogger(name)
        # N.B. EVERY record gets logged. This is because Logger.handle
        # is normally called AFTER logger-level filtering. If you want
        # to do filtering, do it at the client end to save wasting
        # cycles and network bandwidth!
        logger.handle(record)

class LogRecordSocketReceiver(socketserver.ThreadingTCPServer):
    """
    Simple TCP socket-based logging receiver suitable for testing.
    """

    allow_reuse_address = True

    def __init__(self, host='localhost',
                 port=logging.handlers.DEFAULT_TCP_LOGGING_PORT,
                 handler=LogRecordStreamHandler):
        socketserver.ThreadingTCPServer.__init__(self, (host, port), handler)
        self.abort = 0
        self.timeout = 1
        self.logname = None

    def serve_until_stopped(self):
        import select
        abort = 0
        while not abort:
            rd, wr, ex = select.select([self.socket.fileno()],
                                       [], [],
                                       self.timeout)
            if rd:
                self.handle_request()
            abort = self.abort

def main():
    logging.basicConfig(
        format='%(relativeCreated)5d %(name)-15s %(levelname)-8s %(message)s')
    tcpserver = LogRecordSocketReceiver()
    print('About to start TCP server...')
    tcpserver.serve_until_stopped()

if __name__ == '__main__':
    main()

First run the server, and then the client. On the client side, nothing is printed on the console; on the server side, you should see something like:

About to start TCP server...
   59 root            INFO     Jackdaws love my big sphinx of quartz.
   59 myapp.area1     DEBUG    Quick zephyrs blow, vexing daft Jim.
   69 myapp.area1     INFO     How quickly daft jumping zebras vex.
   69 myapp.area2     WARNING  Jail zesty vixen who grabbed pay from quack.
   69 myapp.area2     ERROR    The five boxing wizards jump quickly.

Note that there are some security issues with pickle in some scenarios. If these affect you, you can use an alternative serialization scheme by overriding the makePickle() method and implementing your alternative there, as well as adapting the above script to use your alternative serialization.

Adding contextual information to your logging output

Sometimes you want logging output to contain contextual information in addition to the parameters passed to the logging call. For example, in a networked application, it may be desirable to log client-specific information in the log (e.g. remote client’s username, or IP address). Although you could use the extra parameter to achieve this, it’s not always convenient to pass the information in this way. While it might be tempting to create Logger instances on a per-connection basis, this is not a good idea because these instances are not garbage collected. While this is not a problem in practice, when the number of Logger instances is dependent on the level of granularity you want to use in logging an application, it could be hard to manage if the number of Logger instances becomes effectively unbounded.

Using LoggerAdapters to impart contextual information

An easy way in which you can pass contextual information to be output along with logging event information is to use the LoggerAdapter class. This class is designed to look like a Logger, so that you can call debug(), info(), warning(), error(), exception(), critical() and log(). These methods have the same signatures as their counterparts in Logger, so you can use the two types of instances interchangeably.

When you create an instance of LoggerAdapter, you pass it a Logger instance and a dict-like object which contains your contextual information. When you call one of the logging methods on an instance of LoggerAdapter, it delegates the call to the underlying instance of Logger passed to its constructor, and arranges to pass the contextual information in the delegated call. Here’s a snippet from the code of LoggerAdapter:

def debug(self, msg, *args, **kwargs):
    """
    Delegate a debug call to the underlying logger, after adding
    contextual information from this adapter instance.
    """
    msg, kwargs = self.process(msg, kwargs)
    self.logger.debug(msg, *args, **kwargs)

The process() method of LoggerAdapter is where the contextual information is added to the logging output. It’s passed the message and keyword arguments of the logging call, and it passes back (potentially) modified versions of these to use in the call to the underlying logger. The default implementation of this method leaves the message alone, but inserts an “extra” key in the keyword argument whose value is the dict-like object passed to the constructor. Of course, if you had passed an “extra” keyword argument in the call to the adapter, it will be silently overwritten.

The advantage of using “extra” is that the values in the dict-like object are merged into the LogRecord instance’s __dict__, allowing you to use customized strings with your Formatter instances which know about the keys of the dict-like object. If you need a different method, e.g. if you want to prepend or append the contextual information to the message string, you just need to subclass LoggerAdapter and override process() to do what you need. Here is a simple example:

class CustomAdapter(logging.LoggerAdapter):
    """
    This example adapter expects the passed in dict-like object to have a
    'connid' key, whose value in brackets is prepended to the log message.
    """
    def process(self, msg, kwargs):
        return '[%s] %s' % (self.extra['connid'], msg), kwargs

which you can use like this:

logger = logging.getLogger(__name__)
adapter = CustomAdapter(logger, {'connid': some_conn_id})

Then any events that you log to the adapter will have the value of some_conn_id prepended to the log messages.

Using objects other than dicts to pass contextual information

You don’t need to pass an actual dict to a LoggerAdapter - you could pass an instance of a class which implements __getitem__ and __iter__ so that it looks like a dict to logging. This would be useful if you want to generate values dynamically (whereas the values in a dict would be constant).

Using Filters to impart contextual information

You can also add contextual information to log output using a user-defined Filter. Filter instances are allowed to modify the LogRecords passed to them, including adding additional attributes which can then be output using a suitable format string, or if needed a custom Formatter.

For example in a web application, the request being processed (or at least, the interesting parts of it) can be stored in a threadlocal (threading.local) variable, and then accessed from a Filter to add, say, information from the request - say, the remote IP address and remote user’s username - to the LogRecord, using the attribute names “ip” and “user” as in the LoggerAdapter example above. In that case, the same format string can be used to get similar output to that shown above. Here’s an example script:

import logging
from random import choice

class ContextFilter(logging.Filter):
    """
    This is a filter which injects contextual information into the log.

    Rather than use actual contextual information, we just use random
    data in this demo.
    """

    USERS = ['jim', 'fred', 'sheila']
    IPS = ['123.231.231.123', '127.0.0.1', '192.168.0.1']

    def filter(self, record):

        record.ip = choice(ContextFilter.IPS)
        record.user = choice(ContextFilter.USERS)
        return True

if __name__ == '__main__':
    levels = (logging.DEBUG, logging.INFO, logging.WARNING, logging.ERROR, logging.CRITICAL)
    logging.basicConfig(level=logging.DEBUG,
                        format='%(asctime)-15s %(name)-5s %(levelname)-8s IP: %(ip)-15s User: %(user)-8s %(message)s')
    a1 = logging.getLogger('a.b.c')
    a2 = logging.getLogger('d.e.f')

    f = ContextFilter()
    a1.addFilter(f)
    a2.addFilter(f)
    a1.debug('A debug message')
    a1.info('An info message with %s', 'some parameters')
    for x in range(10):
        lvl = choice(levels)
        lvlname = logging.getLevelName(lvl)
        a2.log(lvl, 'A message at %s level with %d %s', lvlname, 2, 'parameters')

which, when run, produces something like:

2010-09-06 22:38:15,292 a.b.c DEBUG    IP: 123.231.231.123 User: fred     A debug message
2010-09-06 22:38:15,300 a.b.c INFO     IP: 192.168.0.1     User: sheila   An info message with some parameters
2010-09-06 22:38:15,300 d.e.f CRITICAL IP: 127.0.0.1       User: sheila   A message at CRITICAL level with 2 parameters
2010-09-06 22:38:15,300 d.e.f ERROR    IP: 127.0.0.1       User: jim      A message at ERROR level with 2 parameters
2010-09-06 22:38:15,300 d.e.f DEBUG    IP: 127.0.0.1       User: sheila   A message at DEBUG level with 2 parameters
2010-09-06 22:38:15,300 d.e.f ERROR    IP: 123.231.231.123 User: fred     A message at ERROR level with 2 parameters
2010-09-06 22:38:15,300 d.e.f CRITICAL IP: 192.168.0.1     User: jim      A message at CRITICAL level with 2 parameters
2010-09-06 22:38:15,300 d.e.f CRITICAL IP: 127.0.0.1       User: sheila   A message at CRITICAL level with 2 parameters
2010-09-06 22:38:15,300 d.e.f DEBUG    IP: 192.168.0.1     User: jim      A message at DEBUG level with 2 parameters
2010-09-06 22:38:15,301 d.e.f ERROR    IP: 127.0.0.1       User: sheila   A message at ERROR level with 2 parameters
2010-09-06 22:38:15,301 d.e.f DEBUG    IP: 123.231.231.123 User: fred     A message at DEBUG level with 2 parameters
2010-09-06 22:38:15,301 d.e.f INFO     IP: 123.231.231.123 User: fred     A message at INFO level with 2 parameters

Logging to a single file from multiple processes

Although logging is thread-safe, and logging to a single file from multiple threads in a single process is supported, logging to a single file from multiple processes is not supported, because there is no standard way to serialize access to a single file across multiple processes in Python. If you need to log to a single file from multiple processes, one way of doing this is to have all the processes log to a SocketHandler, and have a separate process which implements a socket server which reads from the socket and logs to file. (If you prefer, you can dedicate one thread in one of the existing processes to perform this function.) This section documents this approach in more detail and includes a working socket receiver which can be used as a starting point for you to adapt in your own applications.

If you are using a recent version of Python which includes the multiprocessing module, you could write your own handler which uses the Lock class from this module to serialize access to the file from your processes. The existing FileHandler and subclasses do not make use of multiprocessing at present, though they may do so in the future. Note that at present, the multiprocessing module does not provide working lock functionality on all platforms (see https://bugs.python.org/issue3770).

Alternatively, you can use a Queue and a QueueHandler to send all logging events to one of the processes in your multi-process application. The following example script demonstrates how you can do this; in the example a separate listener process listens for events sent by other processes and logs them according to its own logging configuration. Although the example only demonstrates one way of doing it (for example, you may want to use a listener thread rather than a separate listener process – the implementation would be analogous) it does allow for completely different logging configurations for the listener and the other processes in your application, and can be used as the basis for code meeting your own specific requirements:

# You'll need these imports in your own code
import logging
import logging.handlers
import multiprocessing

# Next two import lines for this demo only
from random import choice, random
import time

#
# Because you'll want to define the logging configurations for listener and workers, the
# listener and worker process functions take a configurer parameter which is a callable
# for configuring logging for that process. These functions are also passed the queue,
# which they use for communication.
#
# In practice, you can configure the listener however you want, but note that in this
# simple example, the listener does not apply level or filter logic to received records.
# In practice, you would probably want to do this logic in the worker processes, to avoid
# sending events which would be filtered out between processes.
#
# The size of the rotated files is made small so you can see the results easily.
def listener_configurer():
    root = logging.getLogger()
    h = logging.handlers.RotatingFileHandler('mptest.log', 'a', 300, 10)
    f = logging.Formatter('%(asctime)s %(processName)-10s %(name)s %(levelname)-8s %(message)s')
    h.setFormatter(f)
    root.addHandler(h)

# This is the listener process top-level loop: wait for logging events
# (LogRecords)on the queue and handle them, quit when you get a None for a
# LogRecord.
def listener_process(queue, configurer):
    configurer()
    while True:
        try:
            record = queue.get()
            if record is None:  # We send this as a sentinel to tell the listener to quit.
                break
            logger = logging.getLogger(record.name)
            logger.handle(record)  # No level or filter logic applied - just do it!
        except Exception:
            import sys, traceback
            print('Whoops! Problem:', file=sys.stderr)
            traceback.print_exc(file=sys.stderr)

# Arrays used for random selections in this demo

LEVELS = [logging.DEBUG, logging.INFO, logging.WARNING,
          logging.ERROR, logging.CRITICAL]

LOGGERS = ['a.b.c', 'd.e.f']

MESSAGES = [
    'Random message #1',
    'Random message #2',
    'Random message #3',
]

# The worker configuration is done at the start of the worker process run.
# Note that on Windows you can't rely on fork semantics, so each process
# will run the logging configuration code when it starts.
def worker_configurer(queue):
    h = logging.handlers.QueueHandler(queue)  # Just the one handler needed
    root = logging.getLogger()
    root.addHandler(h)
    # send all messages, for demo; no other level or filter logic applied.
    root.setLevel(logging.DEBUG)

# This is the worker process top-level loop, which just logs ten events with
# random intervening delays before terminating.
# The print messages are just so you know it's doing something!
def worker_process(queue, configurer):
    configurer(queue)
    name = multiprocessing.current_process().name
    print('Worker started: %s' % name)
    for i in range(10):
        time.sleep(random())
        logger = logging.getLogger(choice(LOGGERS))
        level = choice(LEVELS)
        message = choice(MESSAGES)
        logger.log(level, message)
    print('Worker finished: %s' % name)

# Here's where the demo gets orchestrated. Create the queue, create and start
# the listener, create ten workers and start them, wait for them to finish,
# then send a None to the queue to tell the listener to finish.
def main():
    queue = multiprocessing.Queue(-1)
    listener = multiprocessing.Process(target=listener_process,
                                       args=(queue, listener_configurer))
    listener.start()
    workers = []
    for i in range(10):
        worker = multiprocessing.Process(target=worker_process,
                                         args=(queue, worker_configurer))
        workers.append(worker)
        worker.start()
    for w in workers:
        w.join()
    queue.put_nowait(None)
    listener.join()

if __name__ == '__main__':
    main()

A variant of the above script keeps the logging in the main process, in a separate thread:

import logging
import logging.config
import logging.handlers
from multiprocessing import Process, Queue
import random
import threading
import time

def logger_thread(q):
    while True:
        record = q.get()
        if record is None:
            break
        logger = logging.getLogger(record.name)
        logger.handle(record)

def worker_process(q):
    qh = logging.handlers.QueueHandler(q)
    root = logging.getLogger()
    root.setLevel(logging.DEBUG)
    root.addHandler(qh)
    levels = [logging.DEBUG, logging.INFO, logging.WARNING, logging.ERROR,
              logging.CRITICAL]
    loggers = ['foo', 'foo.bar', 'foo.bar.baz',
               'spam', 'spam.ham', 'spam.ham.eggs']
    for i in range(100):
        lvl = random.choice(levels)
        logger = logging.getLogger(random.choice(loggers))
        logger.log(lvl, 'Message no. %d', i)

if __name__ == '__main__':
    q = Queue()
    d = {
        'version': 1,
        'formatters': {
            'detailed': {
                'class': 'logging.Formatter',
                'format': '%(asctime)s %(name)-15s %(levelname)-8s %(processName)-10s %(message)s'
            }
        },
        'handlers': {
            'console': {
                'class': 'logging.StreamHandler',
                'level': 'INFO',
            },
            'file': {
                'class': 'logging.FileHandler',
                'filename': 'mplog.log',
                'mode': 'w',
                'formatter': 'detailed',
            },
            'foofile': {
                'class': 'logging.FileHandler',
                'filename': 'mplog-foo.log',
                'mode': 'w',
                'formatter': 'detailed',
            },
            'errors': {
                'class': 'logging.FileHandler',
                'filename': 'mplog-errors.log',
                'mode': 'w',
                'level': 'ERROR',
                'formatter': 'detailed',
            },
        },
        'loggers': {
            'foo': {
                'handlers': ['foofile']
            }
        },
        'root': {
            'level': 'DEBUG',
            'handlers': ['console', 'file', 'errors']
        },
    }
    workers = []
    for i in range(5):
        wp = Process(target=worker_process, name='worker %d' % (i + 1), args=(q,))
        workers.append(wp)
        wp.start()
    logging.config.dictConfig(d)
    lp = threading.Thread(target=logger_thread, args=(q,))
    lp.start()
    # At this point, the main process could do some useful work of its own
    # Once it's done that, it can wait for the workers to terminate...
    for wp in workers:
        wp.join()
    # And now tell the logging thread to finish up, too
    q.put(None)
    lp.join()

This variant shows how you can e.g. apply configuration for particular loggers - e.g. the foo logger has a special handler which stores all events in the foo subsystem in a file mplog-foo.log. This will be used by the logging machinery in the main process (even though the logging events are generated in the worker processes) to direct the messages to the appropriate destinations.

Using file rotation

Sometimes you want to let a log file grow to a certain size, then open a new file and log to that. You may want to keep a certain number of these files, and when that many files have been created, rotate the files so that the number of files and the size of the files both remain bounded. For this usage pattern, the logging package provides a RotatingFileHandler:

import glob
import logging
import logging.handlers

LOG_FILENAME = 'logging_rotatingfile_example.out'

# Set up a specific logger with our desired output level
my_logger = logging.getLogger('MyLogger')
my_logger.setLevel(logging.DEBUG)

# Add the log message handler to the logger
handler = logging.handlers.RotatingFileHandler(
              LOG_FILENAME, maxBytes=20, backupCount=5)

my_logger.addHandler(handler)

# Log some messages
for i in range(20):
    my_logger.debug('i = %d' % i)

# See what files are created
logfiles = glob.glob('%s*' % LOG_FILENAME)

for filename in logfiles:
    print(filename)

The result should be 6 separate files, each with part of the log history for the application:

logging_rotatingfile_example.out
logging_rotatingfile_example.out.1
logging_rotatingfile_example.out.2
logging_rotatingfile_example.out.3
logging_rotatingfile_example.out.4
logging_rotatingfile_example.out.5

The most current file is always logging_rotatingfile_example.out, and each time it reaches the size limit it is renamed with the suffix .1. Each of the existing backup files is renamed to increment the suffix (.1 becomes .2, etc.) and the .6 file is erased.

Obviously this example sets the log length much too small as an extreme example. You would want to set maxBytes to an appropriate value.

Use of alternative formatting styles

When logging was added to the Python standard library, the only way of formatting messages with variable content was to use the %-formatting method. Since then, Python has gained two new formatting approaches: string.Template (added in Python 2.4) and str.format() (added in Python 2.6).

Logging (as of 3.2) provides improved support for these two additional formatting styles. The Formatter class been enhanced to take an additional, optional keyword parameter named style. This defaults to '%', but other possible values are '{' and '$', which correspond to the other two formatting styles. Backwards compatibility is maintained by default (as you would expect), but by explicitly specifying a style parameter, you get the ability to specify format strings which work with str.format() or string.Template. Here’s an example console session to show the possibilities:

>>> import logging
>>> root = logging.getLogger()
>>> root.setLevel(logging.DEBUG)
>>> handler = logging.StreamHandler()
>>> bf = logging.Formatter('{asctime} {name} {levelname:8s} {message}',
...                        style='{')
>>> handler.setFormatter(bf)
>>> root.addHandler(handler)
>>> logger = logging.getLogger('foo.bar')
>>> logger.debug('This is a DEBUG message')
2010-10-28 15:11:55,341 foo.bar DEBUG    This is a DEBUG message
>>> logger.critical('This is a CRITICAL message')
2010-10-28 15:12:11,526 foo.bar CRITICAL This is a CRITICAL message
>>> df = logging.Formatter('$asctime $name ${levelname} $message',
...                        style='$')
>>> handler.setFormatter(df)
>>> logger.debug('This is a DEBUG message')
2010-10-28 15:13:06,924 foo.bar DEBUG This is a DEBUG message
>>> logger.critical('This is a CRITICAL message')
2010-10-28 15:13:11,494 foo.bar CRITICAL This is a CRITICAL message
>>>

Note that the formatting of logging messages for final output to logs is completely independent of how an individual logging message is constructed. That can still use %-formatting, as shown here:

>>> logger.error('This is an%s %s %s', 'other,', 'ERROR,', 'message')
2010-10-28 15:19:29,833 foo.bar ERROR This is another, ERROR, message
>>>

Logging calls (logger.debug(), logger.info() etc.) only take positional parameters for the actual logging message itself, with keyword parameters used only for determining options for how to handle the actual logging call (e.g. the exc_info keyword parameter to indicate that traceback information should be logged, or the extra keyword parameter to indicate additional contextual information to be added to the log). So you cannot directly make logging calls using str.format() or string.Template syntax, because internally the logging package uses %-formatting to merge the format string and the variable arguments. There would no changing this while preserving backward compatibility, since all logging calls which are out there in existing code will be using %-format strings.

There is, however, a way that you can use {}- and $- formatting to construct your individual log messages. Recall that for a message you can use an arbitrary object as a message format string, and that the logging package will call str() on that object to get the actual format string. Consider the following two classes:

class BraceMessage:
    def __init__(self, fmt, *args, **kwargs):
        self.fmt = fmt
        self.args = args
        self.kwargs = kwargs

    def __str__(self):
        return self.fmt.format(*self.args, **self.kwargs)

class DollarMessage:
    def __init__(self, fmt, **kwargs):
        self.fmt = fmt
        self.kwargs = kwargs

    def __str__(self):
        from string import Template
        return Template(self.fmt).substitute(**self.kwargs)

Either of these can be used in place of a format string, to allow {}- or $-formatting to be used to build the actual « message » part which appears in the formatted log output in place of « %(message)s » or « {message} » or « $message ». It’s a little unwieldy to use the class names whenever you want to log something, but it’s quite palatable if you use an alias such as __ (double underscore — not to be confused with _, the single underscore used as a synonym/alias for gettext.gettext() or its brethren).

The above classes are not included in Python, though they’re easy enough to copy and paste into your own code. They can be used as follows (assuming that they’re declared in a module called wherever):

>>> from wherever import BraceMessage as __
>>> print(__('Message with {0} {name}', 2, name='placeholders'))
Message with 2 placeholders
>>> class Point: pass
...
>>> p = Point()
>>> p.x = 0.5
>>> p.y = 0.5
>>> print(__('Message with coordinates: ({point.x:.2f}, {point.y:.2f})',
...       point=p))
Message with coordinates: (0.50, 0.50)
>>> from wherever import DollarMessage as __
>>> print(__('Message with $num $what', num=2, what='placeholders'))
Message with 2 placeholders
>>>

While the above examples use print() to show how the formatting works, you would of course use logger.debug() or similar to actually log using this approach.

One thing to note is that you pay no significant performance penalty with this approach: the actual formatting happens not when you make the logging call, but when (and if) the logged message is actually about to be output to a log by a handler. So the only slightly unusual thing which might trip you up is that the parentheses go around the format string and the arguments, not just the format string. That’s because the __ notation is just syntax sugar for a constructor call to one of the XXXMessage classes.

If you prefer, you can use a LoggerAdapter to achieve a similar effect to the above, as in the following example:

import logging

class Message(object):
    def __init__(self, fmt, args):
        self.fmt = fmt
        self.args = args

    def __str__(self):
        return self.fmt.format(*self.args)

class StyleAdapter(logging.LoggerAdapter):
    def __init__(self, logger, extra=None):
        super(StyleAdapter, self).__init__(logger, extra or {})

    def log(self, level, msg, *args, **kwargs):
        if self.isEnabledFor(level):
            msg, kwargs = self.process(msg, kwargs)
            self.logger._log(level, Message(msg, args), (), **kwargs)

logger = StyleAdapter(logging.getLogger(__name__))

def main():
    logger.debug('Hello, {}', 'world!')

if __name__ == '__main__':
    logging.basicConfig(level=logging.DEBUG)
    main()

The above script should log the message Hello, world! when run with Python 3.2 or later.

Customizing LogRecord

Every logging event is represented by a LogRecord instance. When an event is logged and not filtered out by a logger’s level, a LogRecord is created, populated with information about the event and then passed to the handlers for that logger (and its ancestors, up to and including the logger where further propagation up the hierarchy is disabled). Before Python 3.2, there were only two places where this creation was done:

Logger.makeRecord(), which is called in the normal process of logging an event. This invoked LogRecord directly to create an instance.

makeLogRecord(), which is called with a dictionary containing attributes to be added to the LogRecord. This is typically invoked when a suitable dictionary has been received over the network (e.g. in pickle form via a SocketHandler, or in JSON form via an HTTPHandler).

This has usually meant that if you need to do anything special with a LogRecord, you’ve had to do one of the following.

Create your own Logger subclass, which overrides Logger.makeRecord(), and set it using setLoggerClass() before any loggers that you care about are instantiated.

Add a Filter to a logger or handler, which does the necessary special manipulation you need when its filter() method is called.

The first approach would be a little unwieldy in the scenario where (say) several different libraries wanted to do different things. Each would attempt to set its own Logger subclass, and the one which did this last would win.

The second approach works reasonably well for many cases, but does not allow you to e.g. use a specialized subclass of LogRecord. Library developers can set a suitable filter on their loggers, but they would have to remember to do this every time they introduced a new logger (which they would do simply by adding new packages or modules and doing

logger = logging.getLogger(__name__)

at module level). It’s probably one too many things to think about. Developers could also add the filter to a NullHandler attached to their top-level logger, but this would not be invoked if an application developer attached a handler to a lower-level library logger — so output from that handler would not reflect the intentions of the library developer.

In Python 3.2 and later, LogRecord creation is done through a factory, which you can specify. The factory is just a callable you can set with setLogRecordFactory(), and interrogate with getLogRecordFactory(). The factory is invoked with the same signature as the LogRecord constructor, as LogRecord is the default setting for the factory.

This approach allows a custom factory to control all aspects of LogRecord creation. For example, you could return a subclass, or just add some additional attributes to the record once created, using a pattern similar to this:

old_factory = logging.getLogRecordFactory()

def record_factory(*args, **kwargs):
    record = old_factory(*args, **kwargs)
    record.custom_attribute = 0xdecafbad
    return record

logging.setLogRecordFactory(record_factory)

This pattern allows different libraries to chain factories together, and as long as they don’t overwrite each other’s attributes or unintentionally overwrite the attributes provided as standard, there should be no surprises. However, it should be borne in mind that each link in the chain adds run-time overhead to all logging operations, and the technique should only be used when the use of a Filter does not provide the desired result.

Subclassing QueueHandler - a ZeroMQ example

You can use a QueueHandler subclass to send messages to other kinds of queues, for example a ZeroMQ “publish” socket. In the example below,the socket is created separately and passed to the handler (as its “queue”):

import zmq   # using pyzmq, the Python binding for ZeroMQ
import json  # for serializing records portably

ctx = zmq.Context()
sock = zmq.Socket(ctx, zmq.PUB)  # or zmq.PUSH, or other suitable value
sock.bind('tcp://*:5556')        # or wherever

class ZeroMQSocketHandler(QueueHandler):
    def enqueue(self, record):
        self.queue.send_json(record.__dict__)

handler = ZeroMQSocketHandler(sock)

Of course there are other ways of organizing this, for example passing in the data needed by the handler to create the socket:

class ZeroMQSocketHandler(QueueHandler):
    def __init__(self, uri, socktype=zmq.PUB, ctx=None):
        self.ctx = ctx or zmq.Context()
        socket = zmq.Socket(self.ctx, socktype)
        socket.bind(uri)
        super().__init__(socket)

    def enqueue(self, record):
        self.queue.send_json(record.__dict__)

    def close(self):
        self.queue.close()

Subclassing QueueListener - a ZeroMQ example

You can also subclass QueueListener to get messages from other kinds of queues, for example a ZeroMQ “subscribe” socket. Here’s an example:

class ZeroMQSocketListener(QueueListener):
    def __init__(self, uri, *handlers, **kwargs):
        self.ctx = kwargs.get('ctx') or zmq.Context()
        socket = zmq.Socket(self.ctx, zmq.SUB)
        socket.setsockopt_string(zmq.SUBSCRIBE, '')  # subscribe to everything
        socket.connect(uri)
        super().__init__(socket, *handlers, **kwargs)

    def dequeue(self):
        msg = self.queue.recv_json()
        return logging.makeLogRecord(msg)

Voir aussi

Module logging

Référence d’API pour le module de journalisation.

Module logging.config

API de configuration pour le module de journalisation.

Module logging.handlers

Gestionnaires utiles inclus avec le module de journalisation.

A basic logging tutorial

A more advanced logging tutorial

An example dictionary-based configuration

Below is an example of a logging configuration dictionary - it’s taken from the documentation on the Django project [https://docs.djangoproject.com/en/1.9/topics/logging/#configuring-logging]. This dictionary is passed to dictConfig() to put the configuration into effect:

LOGGING = {
    'version': 1,
    'disable_existing_loggers': True,
    'formatters': {
        'verbose': {
            'format': '%(levelname)s %(asctime)s %(module)s %(process)d %(thread)d %(message)s'
        },
        'simple': {
            'format': '%(levelname)s %(message)s'
        },
    },
    'filters': {
        'special': {
            '()': 'project.logging.SpecialFilter',
            'foo': 'bar',
        }
    },
    'handlers': {
        'null': {
            'level':'DEBUG',
            'class':'django.utils.log.NullHandler',
        },
        'console':{
            'level':'DEBUG',
            'class':'logging.StreamHandler',
            'formatter': 'simple'
        },
        'mail_admins': {
            'level': 'ERROR',
            'class': 'django.utils.log.AdminEmailHandler',
            'filters': ['special']
        }
    },
    'loggers': {
        'django': {
            'handlers':['null'],
            'propagate': True,
            'level':'INFO',
        },
        'django.request': {
            'handlers': ['mail_admins'],
            'level': 'ERROR',
            'propagate': False,
        },
        'myproject.custom': {
            'handlers': ['console', 'mail_admins'],
            'level': 'INFO',
            'filters': ['special']
        }
    }
}

For more information about this configuration, you can see the relevant section [https://docs.djangoproject.com/en/1.9/topics/logging/#configuring-logging] of the Django documentation.

Using a rotator and namer to customize log rotation processing

An example of how you can define a namer and rotator is given in the following snippet, which shows zlib-based compression of the log file:

def namer(name):
    return name + ".gz"

def rotator(source, dest):
    with open(source, "rb") as sf:
        data = sf.read()
        compressed = zlib.compress(data, 9)
        with open(dest, "wb") as df:
            df.write(compressed)
    os.remove(source)

rh = logging.handlers.RotatingFileHandler(...)
rh.rotator = rotator
rh.namer = namer

These are not « true » .gz files, as they are bare compressed data, with no « container » such as you’d find in an actual gzip file. This snippet is just for illustration purposes.

A more elaborate multiprocessing example

The following working example shows how logging can be used with multiprocessing using configuration files. The configurations are fairly simple, but serve to illustrate how more complex ones could be implemented in a real multiprocessing scenario.

In the example, the main process spawns a listener process and some worker processes. Each of the main process, the listener and the workers have three separate configurations (the workers all share the same configuration). We can see logging in the main process, how the workers log to a QueueHandler and how the listener implements a QueueListener and a more complex logging configuration, and arranges to dispatch events received via the queue to the handlers specified in the configuration. Note that these configurations are purely illustrative, but you should be able to adapt this example to your own scenario.

Here’s the script - the docstrings and the comments hopefully explain how it works:

import logging
import logging.config
import logging.handlers
from multiprocessing import Process, Queue, Event, current_process
import os
import random
import time

class MyHandler:
    """
    A simple handler for logging events. It runs in the listener process and
    dispatches events to loggers based on the name in the received record,
    which then get dispatched, by the logging system, to the handlers
    configured for those loggers.
    """
    def handle(self, record):
        logger = logging.getLogger(record.name)
        # The process name is transformed just to show that it's the listener
        # doing the logging to files and console
        record.processName = '%s (for %s)' % (current_process().name, record.processName)
        logger.handle(record)

def listener_process(q, stop_event, config):
    """
    This could be done in the main process, but is just done in a separate
    process for illustrative purposes.

    This initialises logging according to the specified configuration,
    starts the listener and waits for the main process to signal completion
    via the event. The listener is then stopped, and the process exits.
    """
    logging.config.dictConfig(config)
    listener = logging.handlers.QueueListener(q, MyHandler())
    listener.start()
    if os.name == 'posix':
        # On POSIX, the setup logger will have been configured in the
        # parent process, but should have been disabled following the
        # dictConfig call.
        # On Windows, since fork isn't used, the setup logger won't
        # exist in the child, so it would be created and the message
        # would appear - hence the "if posix" clause.
        logger = logging.getLogger('setup')
        logger.critical('Should not appear, because of disabled logger ...')
    stop_event.wait()
    listener.stop()

def worker_process(config):
    """
    A number of these are spawned for the purpose of illustration. In
    practice, they could be a heterogeneous bunch of processes rather than
    ones which are identical to each other.

    This initialises logging according to the specified configuration,
    and logs a hundred messages with random levels to randomly selected
    loggers.

    A small sleep is added to allow other processes a chance to run. This
    is not strictly needed, but it mixes the output from the different
    processes a bit more than if it's left out.
    """
    logging.config.dictConfig(config)
    levels = [logging.DEBUG, logging.INFO, logging.WARNING, logging.ERROR,
              logging.CRITICAL]
    loggers = ['foo', 'foo.bar', 'foo.bar.baz',
               'spam', 'spam.ham', 'spam.ham.eggs']
    if os.name == 'posix':
        # On POSIX, the setup logger will have been configured in the
        # parent process, but should have been disabled following the
        # dictConfig call.
        # On Windows, since fork isn't used, the setup logger won't
        # exist in the child, so it would be created and the message
        # would appear - hence the "if posix" clause.
        logger = logging.getLogger('setup')
        logger.critical('Should not appear, because of disabled logger ...')
    for i in range(100):
        lvl = random.choice(levels)
        logger = logging.getLogger(random.choice(loggers))
        logger.log(lvl, 'Message no. %d', i)
        time.sleep(0.01)

def main():
    q = Queue()
    # The main process gets a simple configuration which prints to the console.
    config_initial = {
        'version': 1,
        'formatters': {
            'detailed': {
                'class': 'logging.Formatter',
                'format': '%(asctime)s %(name)-15s %(levelname)-8s %(processName)-10s %(message)s'
            }
        },
        'handlers': {
            'console': {
                'class': 'logging.StreamHandler',
                'level': 'INFO',
            },
        },
        'root': {
            'level': 'DEBUG',
            'handlers': ['console']
        },
    }
    # The worker process configuration is just a QueueHandler attached to the
    # root logger, which allows all messages to be sent to the queue.
    # We disable existing loggers to disable the "setup" logger used in the
    # parent process. This is needed on POSIX because the logger will
    # be there in the child following a fork().
    config_worker = {
        'version': 1,
        'disable_existing_loggers': True,
        'handlers': {
            'queue': {
                'class': 'logging.handlers.QueueHandler',
                'queue': q,
            },
        },
        'root': {
            'level': 'DEBUG',
            'handlers': ['queue']
        },
    }
    # The listener process configuration shows that the full flexibility of
    # logging configuration is available to dispatch events to handlers however
    # you want.
    # We disable existing loggers to disable the "setup" logger used in the
    # parent process. This is needed on POSIX because the logger will
    # be there in the child following a fork().
    config_listener = {
        'version': 1,
        'disable_existing_loggers': True,
        'formatters': {
            'detailed': {
                'class': 'logging.Formatter',
                'format': '%(asctime)s %(name)-15s %(levelname)-8s %(processName)-10s %(message)s'
            },
            'simple': {
                'class': 'logging.Formatter',
                'format': '%(name)-15s %(levelname)-8s %(processName)-10s %(message)s'
            }
        },
        'handlers': {
            'console': {
                'class': 'logging.StreamHandler',
                'level': 'INFO',
                'formatter': 'simple',
            },
            'file': {
                'class': 'logging.FileHandler',
                'filename': 'mplog.log',
                'mode': 'w',
                'formatter': 'detailed',
            },
            'foofile': {
                'class': 'logging.FileHandler',
                'filename': 'mplog-foo.log',
                'mode': 'w',
                'formatter': 'detailed',
            },
            'errors': {
                'class': 'logging.FileHandler',
                'filename': 'mplog-errors.log',
                'mode': 'w',
                'level': 'ERROR',
                'formatter': 'detailed',
            },
        },
        'loggers': {
            'foo': {
                'handlers': ['foofile']
            }
        },
        'root': {
            'level': 'DEBUG',
            'handlers': ['console', 'file', 'errors']
        },
    }
    # Log some initial events, just to show that logging in the parent works
    # normally.
    logging.config.dictConfig(config_initial)
    logger = logging.getLogger('setup')
    logger.info('About to create workers ...')
    workers = []
    for i in range(5):
        wp = Process(target=worker_process, name='worker %d' % (i + 1),
                     args=(config_worker,))
        workers.append(wp)
        wp.start()
        logger.info('Started worker: %s', wp.name)
    logger.info('About to create listener ...')
    stop_event = Event()
    lp = Process(target=listener_process, name='listener',
                 args=(q, stop_event, config_listener))
    lp.start()
    logger.info('Started listener')
    # We now hang around for the workers to finish their work.
    for wp in workers:
        wp.join()
    # Workers all done, listening can now stop.
    # Logging in the parent still works normally.
    logger.info('Telling listener to stop ...')
    stop_event.set()
    lp.join()
    logger.info('All done.')

if __name__ == '__main__':
    main()

Inserting a BOM into messages sent to a SysLogHandler

RFC 5424 [https://tools.ietf.org/html/rfc5424.html] requires that a Unicode message be sent to a syslog daemon as a set of bytes which have the following structure: an optional pure-ASCII component, followed by a UTF-8 Byte Order Mark (BOM), followed by Unicode encoded using UTF-8. (See the relevant section of the specification [https://tools.ietf.org/html/rfc5424.html#section-6].)

In Python 3.1, code was added to SysLogHandler to insert a BOM into the message, but unfortunately, it was implemented incorrectly, with the BOM appearing at the beginning of the message and hence not allowing any pure-ASCII component to appear before it.

As this behaviour is broken, the incorrect BOM insertion code is being removed from Python 3.2.4 and later. However, it is not being replaced, and if you want to produce RFC 5424 [https://tools.ietf.org/html/rfc5424.html]-compliant messages which include a BOM, an optional pure-ASCII sequence before it and arbitrary Unicode after it, encoded using UTF-8, then you need to do the following:

Attach a Formatter instance to your SysLogHandler instance, with a format string such as:

'ASCII section\ufeffUnicode section'

The Unicode code point U+FEFF, when encoded using UTF-8, will be encoded as a UTF-8 BOM – the byte-string b'\xef\xbb\xbf'.

Replace the ASCII section with whatever placeholders you like, but make sure that the data that appears in there after substitution is always ASCII (that way, it will remain unchanged after UTF-8 encoding).

Replace the Unicode section with whatever placeholders you like; if the data which appears there after substitution contains characters outside the ASCII range, that’s fine – it will be encoded using UTF-8.

The formatted message will be encoded using UTF-8 encoding by SysLogHandler. If you follow the above rules, you should be able to produce RFC 5424 [https://tools.ietf.org/html/rfc5424.html]-compliant messages. If you don’t, logging may not complain, but your messages will not be RFC 5424-compliant, and your syslog daemon may complain.

Implementing structured logging

Although most logging messages are intended for reading by humans, and thus not readily machine-parseable, there might be circumstances where you want to output messages in a structured format which is capable of being parsed by a program (without needing complex regular expressions to parse the log message). This is straightforward to achieve using the logging package. There are a number of ways in which this could be achieved, but the following is a simple approach which uses JSON to serialise the event in a machine-parseable manner:

import json
import logging

class StructuredMessage(object):
    def __init__(self, message, **kwargs):
        self.message = message
        self.kwargs = kwargs

    def __str__(self):
        return '%s >>> %s' % (self.message, json.dumps(self.kwargs))

_ = StructuredMessage   # optional, to improve readability

logging.basicConfig(level=logging.INFO, format='%(message)s')
logging.info(_('message 1', foo='bar', bar='baz', num=123, fnum=123.456))

If the above script is run, it prints:

message 1 >>> {"fnum": 123.456, "num": 123, "bar": "baz", "foo": "bar"}

Note that the order of items might be different according to the version of Python used.

If you need more specialised processing, you can use a custom JSON encoder, as in the following complete example:

from __future__ import unicode_literals

import json
import logging

# This next bit is to ensure the script runs unchanged on 2.x and 3.x
try:
    unicode
except NameError:
    unicode = str

class Encoder(json.JSONEncoder):
    def default(self, o):
        if isinstance(o, set):
            return tuple(o)
        elif isinstance(o, unicode):
            return o.encode('unicode_escape').decode('ascii')
        return super(Encoder, self).default(o)

class StructuredMessage(object):
    def __init__(self, message, **kwargs):
        self.message = message
        self.kwargs = kwargs

    def __str__(self):
        s = Encoder().encode(self.kwargs)
        return '%s >>> %s' % (self.message, s)

_ = StructuredMessage   # optional, to improve readability

def main():
    logging.basicConfig(level=logging.INFO, format='%(message)s')
    logging.info(_('message 1', set_value={1, 2, 3}, snowman='\u2603'))

if __name__ == '__main__':
    main()

When the above script is run, it prints:

message 1 >>> {"snowman": "\u2603", "set_value": [1, 2, 3]}

Note that the order of items might be different according to the version of Python used.

Customizing handlers with dictConfig()

There are times when you want to customize logging handlers in particular ways, and if you use dictConfig() you may be able to do this without subclassing. As an example, consider that you may want to set the ownership of a log file. On POSIX, this is easily done using shutil.chown(), but the file handlers in the stdlib don’t offer built-in support. You can customize handler creation using a plain function such as:

def owned_file_handler(filename, mode='a', encoding=None, owner=None):
    if owner:
        if not os.path.exists(filename):
            open(filename, 'a').close()
        shutil.chown(filename, *owner)
    return logging.FileHandler(filename, mode, encoding)

You can then specify, in a logging configuration passed to dictConfig(), that a logging handler be created by calling this function:

LOGGING = {
    'version': 1,
    'disable_existing_loggers': False,
    'formatters': {
        'default': {
            'format': '%(asctime)s %(levelname)s %(name)s %(message)s'
        },
    },
    'handlers': {
        'file':{
            # The values below are popped from this dictionary and
            # used to create the handler, set the handler's level and
            # its formatter.
            '()': owned_file_handler,
            'level':'DEBUG',
            'formatter': 'default',
            # The values below are passed to the handler creator callable
            # as keyword arguments.
            'owner': ['pulse', 'pulse'],
            'filename': 'chowntest.log',
            'mode': 'w',
            'encoding': 'utf-8',
        },
    },
    'root': {
        'handlers': ['file'],
        'level': 'DEBUG',
    },
}

In this example I am setting the ownership using the pulse user and group, just for the purposes of illustration. Putting it together into a working script, chowntest.py:

import logging, logging.config, os, shutil

def owned_file_handler(filename, mode='a', encoding=None, owner=None):
    if owner:
        if not os.path.exists(filename):
            open(filename, 'a').close()
        shutil.chown(filename, *owner)
    return logging.FileHandler(filename, mode, encoding)

LOGGING = {
    'version': 1,
    'disable_existing_loggers': False,
    'formatters': {
        'default': {
            'format': '%(asctime)s %(levelname)s %(name)s %(message)s'
        },
    },
    'handlers': {
        'file':{
            # The values below are popped from this dictionary and
            # used to create the handler, set the handler's level and
            # its formatter.
            '()': owned_file_handler,
            'level':'DEBUG',
            'formatter': 'default',
            # The values below are passed to the handler creator callable
            # as keyword arguments.
            'owner': ['pulse', 'pulse'],
            'filename': 'chowntest.log',
            'mode': 'w',
            'encoding': 'utf-8',
        },
    },
    'root': {
        'handlers': ['file'],
        'level': 'DEBUG',
    },
}

logging.config.dictConfig(LOGGING)
logger = logging.getLogger('mylogger')
logger.debug('A debug message')

To run this, you will probably need to run as root:

$ sudo python3.3 chowntest.py
$ cat chowntest.log
2013-11-05 09:34:51,128 DEBUG mylogger A debug message
$ ls -l chowntest.log
-rw-r--r-- 1 pulse pulse 55 2013-11-05 09:34 chowntest.log

Note that this example uses Python 3.3 because that’s where shutil.chown() makes an appearance. This approach should work with any Python version that supports dictConfig() - namely, Python 2.7, 3.2 or later. With pre-3.3 versions, you would need to implement the actual ownership change using e.g. os.chown().

In practice, the handler-creating function may be in a utility module somewhere in your project. Instead of the line in the configuration:

'()': owned_file_handler,

you could use e.g.:

'()': 'ext://project.util.owned_file_handler',

where project.util can be replaced with the actual name of the package where the function resides. In the above working script, using 'ext://__main__.owned_file_handler' should work. Here, the actual callable is resolved by dictConfig() from the ext:// specification.

This example hopefully also points the way to how you could implement other types of file change - e.g. setting specific POSIX permission bits - in the same way, using os.chmod().

Of course, the approach could also be extended to types of handler other than a FileHandler - for example, one of the rotating file handlers, or a different type of handler altogether.

Using particular formatting styles throughout your application

In Python 3.2, the Formatter gained a style keyword parameter which, while defaulting to % for backward compatibility, allowed the specification of { or $ to support the formatting approaches supported by str.format() and string.Template. Note that this governs the formatting of logging messages for final output to logs, and is completely orthogonal to how an individual logging message is constructed.

Logging calls (debug(), info() etc.) only take positional parameters for the actual logging message itself, with keyword parameters used only for determining options for how to handle the logging call (e.g. the exc_info keyword parameter to indicate that traceback information should be logged, or the extra keyword parameter to indicate additional contextual information to be added to the log). So you cannot directly make logging calls using str.format() or string.Template syntax, because internally the logging package uses %-formatting to merge the format string and the variable arguments. There would no changing this while preserving backward compatibility, since all logging calls which are out there in existing code will be using %-format strings.

There have been suggestions to associate format styles with specific loggers, but that approach also runs into backward compatibility problems because any existing code could be using a given logger name and using %-formatting.

For logging to work interoperably between any third-party libraries and your code, decisions about formatting need to be made at the level of the individual logging call. This opens up a couple of ways in which alternative formatting styles can be accommodated.

Using LogRecord factories

In Python 3.2, along with the Formatter changes mentioned above, the logging package gained the ability to allow users to set their own LogRecord subclasses, using the setLogRecordFactory() function. You can use this to set your own subclass of LogRecord, which does the Right Thing by overriding the getMessage() method. The base class implementation of this method is where the msg % args formatting happens, and where you can substitute your alternate formatting; however, you should be careful to support all formatting styles and allow %-formatting as the default, to ensure interoperability with other code. Care should also be taken to call str(self.msg), just as the base implementation does.

Refer to the reference documentation on setLogRecordFactory() and LogRecord for more information.

Using custom message objects

There is another, perhaps simpler way that you can use {}- and $- formatting to construct your individual log messages. You may recall (from Utilisation d’objets arbitraires comme messages) that when logging you can use an arbitrary object as a message format string, and that the logging package will call str() on that object to get the actual format string. Consider the following two classes:

class BraceMessage(object):
    def __init__(self, fmt, *args, **kwargs):
        self.fmt = fmt
        self.args = args
        self.kwargs = kwargs

    def __str__(self):
        return self.fmt.format(*self.args, **self.kwargs)

class DollarMessage(object):
    def __init__(self, fmt, **kwargs):
        self.fmt = fmt
        self.kwargs = kwargs

    def __str__(self):
        from string import Template
        return Template(self.fmt).substitute(**self.kwargs)

Either of these can be used in place of a format string, to allow {}- or $-formatting to be used to build the actual « message » part which appears in the formatted log output in place of “%(message)s” or “{message}” or “$message”. If you find it a little unwieldy to use the class names whenever you want to log something, you can make it more palatable if you use an alias such as M or _ for the message (or perhaps __, if you are using _ for localization).

Examples of this approach are given below. Firstly, formatting with str.format():

>>> __ = BraceMessage
>>> print(__('Message with {0} {1}', 2, 'placeholders'))
Message with 2 placeholders
>>> class Point: pass
...
>>> p = Point()
>>> p.x = 0.5
>>> p.y = 0.5
>>> print(__('Message with coordinates: ({point.x:.2f}, {point.y:.2f})', point=p))
Message with coordinates: (0.50, 0.50)

Secondly, formatting with string.Template:

>>> __ = DollarMessage
>>> print(__('Message with $num $what', num=2, what='placeholders'))
Message with 2 placeholders
>>>

One thing to note is that you pay no significant performance penalty with this approach: the actual formatting happens not when you make the logging call, but when (and if) the logged message is actually about to be output to a log by a handler. So the only slightly unusual thing which might trip you up is that the parentheses go around the format string and the arguments, not just the format string. That’s because the __ notation is just syntax sugar for a constructor call to one of the XXXMessage classes shown above.

Configuring filters with dictConfig()

You can configure filters using dictConfig(), though it might not be obvious at first glance how to do it (hence this recipe). Since Filter is the only filter class included in the standard library, and it is unlikely to cater to many requirements (it’s only there as a base class), you will typically need to define your own Filter subclass with an overridden filter() method. To do this, specify the () key in the configuration dictionary for the filter, specifying a callable which will be used to create the filter (a class is the most obvious, but you can provide any callable which returns a Filter instance). Here is a complete example:

import logging
import logging.config
import sys

class MyFilter(logging.Filter):
    def __init__(self, param=None):
        self.param = param

    def filter(self, record):
        if self.param is None:
            allow = True
        else:
            allow = self.param not in record.msg
        if allow:
            record.msg = 'changed: ' + record.msg
        return allow

LOGGING = {
    'version': 1,
    'filters': {
        'myfilter': {
            '()': MyFilter,
            'param': 'noshow',
        }
    },
    'handlers': {
        'console': {
            'class': 'logging.StreamHandler',
            'filters': ['myfilter']
        }
    },
    'root': {
        'level': 'DEBUG',
        'handlers': ['console']
    },
}

if __name__ == '__main__':
    logging.config.dictConfig(LOGGING)
    logging.debug('hello')
    logging.debug('hello - noshow')

This example shows how you can pass configuration data to the callable which constructs the instance, in the form of keyword parameters. When run, the above script will print:

changed: hello

which shows that the filter is working as configured.

A couple of extra points to note:

If you can’t refer to the callable directly in the configuration (e.g. if it lives in a different module, and you can’t import it directly where the configuration dictionary is), you can use the form ext://... as described in Access to external objects. For example, you could have used the text 'ext://__main__.MyFilter' instead of MyFilter in the above example.

As well as for filters, this technique can also be used to configure custom handlers and formatters. See User-defined objects for more information on how logging supports using user-defined objects in its configuration, and see the other cookbook recipe Customizing handlers with dictConfig() above.

Customized exception formatting

There might be times when you want to do customized exception formatting - for argument’s sake, let’s say you want exactly one line per logged event, even when exception information is present. You can do this with a custom formatter class, as shown in the following example:

import logging

class OneLineExceptionFormatter(logging.Formatter):
    def formatException(self, exc_info):
        """
        Format an exception so that it prints on a single line.
        """
        result = super(OneLineExceptionFormatter, self).formatException(exc_info)
        return repr(result)  # or format into one line however you want to

    def format(self, record):
        s = super(OneLineExceptionFormatter, self).format(record)
        if record.exc_text:
            s = s.replace('\n', '') + '|'
        return s

def configure_logging():
    fh = logging.FileHandler('output.txt', 'w')
    f = OneLineExceptionFormatter('%(asctime)s|%(levelname)s|%(message)s|',
                                  '%d/%m/%Y %H:%M:%S')
    fh.setFormatter(f)
    root = logging.getLogger()
    root.setLevel(logging.DEBUG)
    root.addHandler(fh)

def main():
    configure_logging()
    logging.info('Sample message')
    try:
        x = 1 / 0
    except ZeroDivisionError as e:
        logging.exception('ZeroDivisionError: %s', e)

if __name__ == '__main__':
    main()

When run, this produces a file with exactly two lines:

28/01/2015 07:21:23|INFO|Sample message|
28/01/2015 07:21:23|ERROR|ZeroDivisionError: integer division or modulo by zero|'Traceback (most recent call last):\n  File "logtest7.py", line 30, in main\n    x = 1 / 0\nZeroDivisionError: integer division or modulo by zero'|

While the above treatment is simplistic, it points the way to how exception information can be formatted to your liking. The traceback module may be helpful for more specialized needs.

Speaking logging messages

There might be situations when it is desirable to have logging messages rendered in an audible rather than a visible format. This is easy to do if you have text-to-speech (TTS) functionality available in your system, even if it doesn’t have a Python binding. Most TTS systems have a command line program you can run, and this can be invoked from a handler using subprocess. It’s assumed here that TTS command line programs won’t expect to interact with users or take a long time to complete, and that the frequency of logged messages will be not so high as to swamp the user with messages, and that it’s acceptable to have the messages spoken one at a time rather than concurrently, The example implementation below waits for one message to be spoken before the next is processed, and this might cause other handlers to be kept waiting. Here is a short example showing the approach, which assumes that the espeak TTS package is available:

import logging
import subprocess
import sys

class TTSHandler(logging.Handler):
    def emit(self, record):
        msg = self.format(record)
        # Speak slowly in a female English voice
        cmd = ['espeak', '-s150', '-ven+f3', msg]
        p = subprocess.Popen(cmd, stdout=subprocess.PIPE,
                             stderr=subprocess.STDOUT)
        # wait for the program to finish
        p.communicate()

def configure_logging():
    h = TTSHandler()
    root = logging.getLogger()
    root.addHandler(h)
    # the default formatter just returns the message
    root.setLevel(logging.DEBUG)

def main():
    logging.info('Hello')
    logging.debug('Goodbye')

if __name__ == '__main__':
    configure_logging()
    sys.exit(main())

When run, this script should say « Hello » and then « Goodbye » in a female voice.

The above approach can, of course, be adapted to other TTS systems and even other systems altogether which can process messages via external programs run from a command line.

Buffering logging messages and outputting them conditionally

There might be situations where you want to log messages in a temporary area and only output them if a certain condition occurs. For example, you may want to start logging debug events in a function, and if the function completes without errors, you don’t want to clutter the log with the collected debug information, but if there is an error, you want all the debug information to be output as well as the error.

Here is an example which shows how you could do this using a decorator for your functions where you want logging to behave this way. It makes use of the logging.handlers.MemoryHandler, which allows buffering of logged events until some condition occurs, at which point the buffered events are flushed - passed to another handler (the target handler) for processing. By default, the MemoryHandler flushed when its buffer gets filled up or an event whose level is greater than or equal to a specified threshold is seen. You can use this recipe with a more specialised subclass of MemoryHandler if you want custom flushing behavior.

The example script has a simple function, foo, which just cycles through all the logging levels, writing to sys.stderr to say what level it’s about to log at, and then actually logging a message at that level. You can pass a parameter to foo which, if true, will log at ERROR and CRITICAL levels - otherwise, it only logs at DEBUG, INFO and WARNING levels.

The script just arranges to decorate foo with a decorator which will do the conditional logging that’s required. The decorator takes a logger as a parameter and attaches a memory handler for the duration of the call to the decorated function. The decorator can be additionally parameterised using a target handler, a level at which flushing should occur, and a capacity for the buffer. These default to a StreamHandler which writes to sys.stderr, logging.ERROR and 100 respectively.

Here’s the script:

import logging
from logging.handlers import MemoryHandler
import sys

logger = logging.getLogger(__name__)
logger.addHandler(logging.NullHandler())

def log_if_errors(logger, target_handler=None, flush_level=None, capacity=None):
    if target_handler is None:
        target_handler = logging.StreamHandler()
    if flush_level is None:
        flush_level = logging.ERROR
    if capacity is None:
        capacity = 100
    handler = MemoryHandler(capacity, flushLevel=flush_level, target=target_handler)

    def decorator(fn):
        def wrapper(*args, **kwargs):
            logger.addHandler(handler)
            try:
                return fn(*args, **kwargs)
            except Exception:
                logger.exception('call failed')
                raise
            finally:
                super(MemoryHandler, handler).flush()
                logger.removeHandler(handler)
        return wrapper

    return decorator

def write_line(s):
    sys.stderr.write('%s\n' % s)

def foo(fail=False):
    write_line('about to log at DEBUG ...')
    logger.debug('Actually logged at DEBUG')
    write_line('about to log at INFO ...')
    logger.info('Actually logged at INFO')
    write_line('about to log at WARNING ...')
    logger.warning('Actually logged at WARNING')
    if fail:
        write_line('about to log at ERROR ...')
        logger.error('Actually logged at ERROR')
        write_line('about to log at CRITICAL ...')
        logger.critical('Actually logged at CRITICAL')
    return fail

decorated_foo = log_if_errors(logger)(foo)

if __name__ == '__main__':
    logger.setLevel(logging.DEBUG)
    write_line('Calling undecorated foo with False')
    assert not foo(False)
    write_line('Calling undecorated foo with True')
    assert foo(True)
    write_line('Calling decorated foo with False')
    assert not decorated_foo(False)
    write_line('Calling decorated foo with True')
    assert decorated_foo(True)

When this script is run, the following output should be observed:

Calling undecorated foo with False
about to log at DEBUG ...
about to log at INFO ...
about to log at WARNING ...
Calling undecorated foo with True
about to log at DEBUG ...
about to log at INFO ...
about to log at WARNING ...
about to log at ERROR ...
about to log at CRITICAL ...
Calling decorated foo with False
about to log at DEBUG ...
about to log at INFO ...
about to log at WARNING ...
Calling decorated foo with True
about to log at DEBUG ...
about to log at INFO ...
about to log at WARNING ...
about to log at ERROR ...
Actually logged at DEBUG
Actually logged at INFO
Actually logged at WARNING
Actually logged at ERROR
about to log at CRITICAL ...
Actually logged at CRITICAL

As you can see, actual logging output only occurs when an event is logged whose severity is ERROR or greater, but in that case, any previous events at lower severities are also logged.

You can of course use the conventional means of decoration:

@log_if_errors(logger)
def foo(fail=False):
    ...

Formatting times using UTC (GMT) via configuration

Sometimes you want to format times using UTC, which can be done using a class such as UTCFormatter, shown below:

import logging
import time

class UTCFormatter(logging.Formatter):
    converter = time.gmtime

and you can then use the UTCFormatter in your code instead of Formatter. If you want to do that via configuration, you can use the dictConfig() API with an approach illustrated by the following complete example:

import logging
import logging.config
import time

class UTCFormatter(logging.Formatter):
    converter = time.gmtime

LOGGING = {
    'version': 1,
    'disable_existing_loggers': False,
    'formatters': {
        'utc': {
            '()': UTCFormatter,
            'format': '%(asctime)s %(message)s',
        },
        'local': {
            'format': '%(asctime)s %(message)s',
        }
    },
    'handlers': {
        'console1': {
            'class': 'logging.StreamHandler',
            'formatter': 'utc',
        },
        'console2': {
            'class': 'logging.StreamHandler',
            'formatter': 'local',
        },
    },
    'root': {
        'handlers': ['console1', 'console2'],
   }
}

if __name__ == '__main__':
    logging.config.dictConfig(LOGGING)
    logging.warning('The local time is %s', time.asctime())

When this script is run, it should print something like:

2015-10-17 12:53:29,501 The local time is Sat Oct 17 13:53:29 2015
2015-10-17 13:53:29,501 The local time is Sat Oct 17 13:53:29 2015

showing how the time is formatted both as local time and UTC, one for each handler.

Using a context manager for selective logging

There are times when it would be useful to temporarily change the logging configuration and revert it back after doing something. For this, a context manager is the most obvious way of saving and restoring the logging context. Here is a simple example of such a context manager, which allows you to optionally change the logging level and add a logging handler purely in the scope of the context manager:

import logging
import sys

class LoggingContext(object):
    def __init__(self, logger, level=None, handler=None, close=True):
        self.logger = logger
        self.level = level
        self.handler = handler
        self.close = close

    def __enter__(self):
        if self.level is not None:
            self.old_level = self.logger.level
            self.logger.setLevel(self.level)
        if self.handler:
            self.logger.addHandler(self.handler)

    def __exit__(self, et, ev, tb):
        if self.level is not None:
            self.logger.setLevel(self.old_level)
        if self.handler:
            self.logger.removeHandler(self.handler)
        if self.handler and self.close:
            self.handler.close()
        # implicit return of None => don't swallow exceptions

If you specify a level value, the logger’s level is set to that value in the scope of the with block covered by the context manager. If you specify a handler, it is added to the logger on entry to the block and removed on exit from the block. You can also ask the manager to close the handler for you on block exit - you could do this if you don’t need the handler any more.

To illustrate how it works, we can add the following block of code to the above:

if __name__ == '__main__':
    logger = logging.getLogger('foo')
    logger.addHandler(logging.StreamHandler())
    logger.setLevel(logging.INFO)
    logger.info('1. This should appear just once on stderr.')
    logger.debug('2. This should not appear.')
    with LoggingContext(logger, level=logging.DEBUG):
        logger.debug('3. This should appear once on stderr.')
    logger.debug('4. This should not appear.')
    h = logging.StreamHandler(sys.stdout)
    with LoggingContext(logger, level=logging.DEBUG, handler=h, close=True):
        logger.debug('5. This should appear twice - once on stderr and once on stdout.')
    logger.info('6. This should appear just once on stderr.')
    logger.debug('7. This should not appear.')

We initially set the logger’s level to INFO, so message #1 appears and message #2 doesn’t. We then change the level to DEBUG temporarily in the following with block, and so message #3 appears. After the block exits, the logger’s level is restored to INFO and so message #4 doesn’t appear. In the next with block, we set the level to DEBUG again but also add a handler writing to sys.stdout. Thus, message #5 appears twice on the console (once via stderr and once via stdout). After the with statement’s completion, the status is as it was before so message #6 appears (like message #1) whereas message #7 doesn’t (just like message #2).

If we run the resulting script, the result is as follows:

$ python logctx.py
1. This should appear just once on stderr.
3. This should appear once on stderr.
5. This should appear twice - once on stderr and once on stdout.
5. This should appear twice - once on stderr and once on stdout.
6. This should appear just once on stderr.

If we run it again, but pipe stderr to /dev/null, we see the following, which is the only message written to stdout:

$ python logctx.py 2>/dev/null
5. This should appear twice - once on stderr and once on stdout.

Once again, but piping stdout to /dev/null, we get:

$ python logctx.py >/dev/null
1. This should appear just once on stderr.
3. This should appear once on stderr.
5. This should appear twice - once on stderr and once on stdout.
6. This should appear just once on stderr.

In this case, the message #5 printed to stdout doesn’t appear, as expected.

Of course, the approach described here can be generalised, for example to attach logging filters temporarily. Note that the above code works in Python 2 as well as Python 3.

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Guide des expressions régulières

Auteur

A.M. Kuchling <amk@amk.ca>

Résumé

Ce document constitue un guide d’introduction à l’utilisation des expressions régulières en Python avec le module re. Il fournit une introduction plus abordable que la section correspondante dans le guide de référence de la bibliothèque.

Introduction

Les expressions régulières (notées RE ou motifs regex dans ce document) sont essentiellement un petit langage de programmation hautement spécialisé embarqué dans Python et dont la manipulation est rendue possible par l’utilisation du module re. En utilisant ce petit langage, vous définissez des règles pour spécifier une correspondance avec un ensemble souhaité de chaînes de caractères ; ces chaînes peuvent être des phrases, des adresses de courriel, des commandes TeX ou tout ce que vous voulez. Vous pouvez ensuite poser des questions telles que « Est-ce que cette chaîne de caractères correspond au motif ? » ou « Y a-t-il une correspondance pour ce motif à l’intérieur de la chaîne de caractères ? ». Vous pouvez aussi utiliser les RE pour modifier une chaîne de caractères ou la découper de différentes façons.

Un motif d’expression régulière est compilé en code intermédiaire (bytecode en anglais) qui est ensuite exécuté par un moteur de correspondance écrit en C. Pour une utilisation plus poussée, il peut s’avérer nécessaire de s’intéresser à la manière dont le moteur exécute la RE afin d’écrire une expression dont le code intermédiaire est plus rapide. L’optimisation n’est pas traitée dans ce document, parce qu’elle nécessite d’avoir une bonne compréhension des mécanismes internes du moteur de correspondance.

Le langage des expressions régulières est relativement petit et restreint, donc toutes les tâches de manipulation de chaînes de caractères ne peuvent pas être réalisées à l’aide d’expressions régulières. Il existe aussi des tâches qui peuvent être réalisées à l’aide d’expressions régulières mais qui ont tendance à produire des expressions régulières très compliquées. Dans ces cas, il est plus utile d’écrire du code Python pour réaliser le traitement ; même si le code Python est plus lent qu’une expression régulière élaborée, il sera probablement plus compréhensible.

Motifs simples

Nous commençons par étudier les expressions régulières les plus simples. Dans la mesure où les expressions régulières sont utilisées pour manipuler des chaînes de caractères, nous commençons par l’action la plus courante : la correspondance de caractères.

Pour une explication détaillée sur le concept informatique sous-jacent aux expressions régulières (automate à états déterministe ou non-déterministe), vous pouvez vous référer à n’importe quel manuel sur l’écriture de compilateurs.

Correspondance de caractères

La plupart des lettres ou caractères correspondent simplement à eux-mêmes. Par exemple, l’expression régulière test correspond à la chaîne de caractères test, précisément. Vous pouvez activer le mode non-sensible à la casse qui permet à cette RE de correspondre également à Test ou TEST (ce sujet est traité par la suite).

Il existe des exceptions à cette règle ; certains caractères sont des métacaractères spéciaux et ne correspondent pas à eux-mêmes. Au lieu de cela, ils signalent que certaines choses non ordinaires doivent correspondre, ou ils affectent d’autre portions de la RE en les répétant ou en changeant leur sens. Une grande partie de ce document est consacrée au fonctionnement de ces métacaractères.

Voici une liste complète des métacaractères ; leur sens est décrit dans la suite de ce guide.

. ^ $ * + ? { } [ ] \ | ( )

Les premiers métacaractères que nous étudions sont [ et ]. Ils sont utilisés pour spécifier une classe de caractères, qui forme un ensemble de caractères dont vous souhaitez trouver la correspondance. Les caractères peuvent être listés individuellement, ou une plage de caractères peut être indiquée en fournissant deux caractères séparés par un “-“`. Par exemple, [abc] correspond à n’importe quel caractère parmi a, b, ou c ; c’est équivalent à [a-c], qui utilise une plage pour exprimer le même ensemble de caractères. Si vous voulez trouver une chaîne qui ne contient que des lettres en minuscules, la RE est [a-z].

Les métacaractères ne sont pas actifs dans les classes. Par exemple, [akm$] correspond à n’importe quel caractère parmi 'a', 'k', 'm' ou '$' ; '$' est habituellement un métacaractère mais dans une classe de caractères, il est dépourvu de sa signification spéciale.

Vous pouvez trouver une correspondance avec les caractères non listés dans une classe en spécifiant le complément de l’ensemble. Ceci est indiqué en plaçant un '^' en tant que premier caractère de la classe ; '^' en dehors d’une classe de caractères correspond au caractère '^'. Par exemple, [^5] correspond à tous les caractères, sauf '5'.

Le métacaractère le plus important est probablement la barre oblique inverse ( backslash en anglais), \. Comme dans les chaînes de caractères en Python, la barre oblique inverse peut être suivie par différents caractères pour signaler différentes séquences spéciales. Elle est aussi utilisée pour échapper tous les métacaractères afin d’en trouver les correspondances dans les motifs ; par exemple, si vous devez trouver une correspondance pour [ ou \, vous pouvez les précéder avec une barre oblique inverse pour annuler leur signification spéciale : \[ ou \\.

Certaines séquences spéciales commençant par '\' représentent des ensembles de caractères prédéfinis qui sont souvent utiles, tels que l’ensemble des chiffres, l’ensemble des lettres ou l’ensemble des caractères qui ne sont pas des « blancs ».

Prenons un exemple : \w correspond à n’importe quel caractère alphanumérique. Si l’expression régulière est exprimée en bytes, c’est équivalent à la classe [a-zA-Z0-9_]. Si l’expression régulière est une chaîne de caractères, \w correspond à tous les caractères identifiés comme lettre dans la base de données Unicode fournie par le module unicodedata. Vous pouvez utiliser la définition plus restrictive de \w dans un motif exprimé en chaîne de caractères en spécifiant l’option re.ASCII lors de la compilation de l’expression régulière.

La liste de séquences spéciales suivante est incomplète. Pour une liste complète des séquences et définitions de classes étendues relatives aux motifs de chaînes de caractères Unicode, reportez-vous à la dernière partie de la référence Syntaxe d’Expressions Régulières de la bibliothèque standard. En général, les versions Unicode trouvent une correspondance avec n’importe quel caractère présent dans la catégorie appropriée de la base de données Unicode.

\d

Correspond à n’importe quel caractère numérique ; équivalent à la classe [0-9].

\D

Correspond à n’importe caractère non numérique ; équivalent à la classe [^0-9].

\s

Correspond à n’importe quel caractère « blanc » ; équivalent à la classe [ \t\n\r\f\v].

\S

Correspond à n’importe caractère autre que « blanc » ; équivalent à la classe [^ \t\n\r\f\v].

\w

Correspond à n’importe caractère alphanumérique ; équivalent à la classe [a-zA-Z0-9_].

\W

Correspond à n’importe caractère non-alphanumérique ; équivalent à la classe [^a-zA-Z0-9_].

Ces séquences peuvent être incluses dans une classe de caractères. Par exemple, [\s,.] est une classe de caractères qui correspond à tous les caractères « blancs » ou ',' ou '.'.

Le dernier métacaractère de cette section est .. Il correspond à tous les caractères, à l’exception du caractère de retour à la ligne ; il existe un mode alternatif (re.DOTALL) dans lequel il correspond également eu caractère de retour à la ligne. . est souvent utilisé lorsque l’on veut trouver une correspondance avec « n’importe quel caractère ».

Répétitions

Trouver des correspondances de divers ensembles de caractères est la première utilisation des expressions régulières, ce que l’on ne peut pas faire avec les méthodes des chaînes. Cependant, si c’était la seule possibilité des expressions régulières, le gain ne serait pas significatif. Une autre utilisation consiste à spécifier des portions d’une RE qui peuvent être répétées un certain nombre de fois.

Le premier métacaractère pour la répétition que nous abordons est *. * ne correspond pas au caractère littéral '*' ; à la place, il spécifie que le caractère précédent peut correspondre zéro, une ou plusieurs fois (au lieu d’une seule fois).

Par exemple, cha*t correspond à 'cht' (0 caractère 'a'), 'chat' (1 'a'), 'chaaat' (3 caractères 'a') et ainsi de suite.

Les répétitions telles que * sont gloutonnes ; quand vous répétez une RE, le moteur de correspondance essaie de trouver la correspondance la plus longue en répétant le motif tant qu’il le peut. Si la suite du motif ne correspond pas, le moteur de correspondance revient en arrière et essaie avec moins de répétitions.

Un exemple étape par étape mettra les choses au clair. Considérons l’expression a[bcd]*b. Elle correspond à la lettre 'a', suivi d’aucune ou plusieurs lettres de la classe [bcd]` et finit par un 'b'. Maintenant, supposons que nous cherchons une correspondance de cette RE avec la chaîne de caractères 'abcbd'.

Étape

Correspond

Explication

1

a

Le a correspond dans la RE.

2

abcbd

Le moteur de correspondance trouve [bcd]*, va aussi loin qu’il le peut, ce qui n’est pas la fin de la chaîne.

3

échec

Le moteur essaie de trouver une correspondance avec b mais la position courante est à la fin de la chaîne de caractères, donc il échoue.

4

abcb

Retour en arrière, de manière à ce que [bcd]* corresponde avec un caractère de moins.

5

échec

Essaie encore b, mais la position courante est le dernier caractère, qui est 'd'.

6

abc

Encore un retour en arrière, de manière à ce que [bcd]* ne corresponde qu’à bc.

6

abcb

Essaie b encore une fois. Cette fois, le caractère à la position courante est 'b', donc cela fonctionne.

La fin de la RE est maintenant atteinte et la correspondance trouvée est 'abcb'. Ceci démontre comment le moteur de correspondance essaie d’aller le plus loin possible en premier et, si la correspondance échoue, il revient progressivement en arrière et ré-essaie avec le reste de la RE encore et encore. Il revient en arrière jusqu’à qu’il n’y ait aucune correspondance pour [bcd]* et, si cela échoue toujours, le moteur conclut que la chaîne de caractères et la RE ne correspondent pas du tout.

Un autre métacaractère de répétition est +, qui fait correspondre une ou plusieurs fois. Faites bien attention à la différence entre * et + ; * fait correspondre zéro fois ou plus, ainsi ce qui doit être répété peut ne pas être présent du tout, alors que + requiert au moins une occurrence. Pour continuer avec le même exemple, cha+t correspond avec 'chat' (1 'a'), 'chaaat' (3 'a') mais ne correspond pas avec 'ct'.

Il existe deux autres quantificateurs pour les répétitions. Le point d’interrogation, ?, fait correspondre zéro ou une fois ; vous pouvez vous le représenter comme indiquant une option. Par exemple, méta-?caractère fait correspondre soit métacaractère, soit méta-caractère.

Le plus compliqué des quantificateurs est {m,n} où m et n sont des entiers décimaux. Ce quantificateur indique qu’il faut au moins m répétitions et au plus n. Par exemple, a/{1,3}b fait correspondre 'a/b', 'a//b' et 'a///b'. Elle ne fait pas correspondre 'ab' (pas de barre oblique) ni 'a////b' (quatre barres obliques).

Vous pouvez omettre soit m, soit n ; dans ce cas, une valeur raisonnable est prise pour la valeur manquante. Omettre m considère que la borne basse est 0 alors qu’omettre n signifie qu’il n’y a pas de borne supérieure.

Le lecteur attentif aura noté que les trois premiers quantificateurs peuvent être exprimés en utilisant cette notation. {0,} est la même chose que *, {1,} est équivalent à + et {0,1} se comporte comme ?. Il est préférable d’utiliser *, + ou ? quand vous le pouvez, simplement parce qu’ils sont plus courts et plus faciles à lire.

Utilisation des expressions régulières

Maintenant que nous avons vu quelques expressions régulières simples, utilisons-les concrètement. Le module re fournit une interface pour le moteur de correspondance, ce qui permet de compiler les RE en objets et d’effectuer des correspondances avec.

Compilation des expressions régulières

Les expressions régulières sont compilées en objets motifs, qui possèdent des méthodes pour diverses opérations telles que la recherche de correspondances ou les substitutions dans les chaînes.

>>> import re
>>> p = re.compile('ab*')
>>> p
re.compile('ab*')

re.compile() accepte aussi une option flags, utilisée pour activer des fonctionnalités particulières et des variations de syntaxe. Nous étudierons la définition des variables plus tard et, pour l’instant, un seul exemple suffit :

>>> p = re.compile('ab*', re.IGNORECASE)

La RE passée à re.compile() est une chaîne. Les RE sont des chaînes car les expressions régulières ne font pas partie intrinsèque du langage Python et aucune syntaxe particulière n’a été créée pour les exprimer (il existe des applications qui ne nécessitent aucune RE et il n’a donc aucune raison de grossir les spécifications du langage en incluant les RE). Ainsi, le module re est simplement un module d’extension en C inclus dans Python, tout comme les modules socket ou zlib.

Exprimer les RE comme des chaînes de caractères garde le langage Python plus simple mais introduit un inconvénient qui fait l’objet de la section suivante.

La maudite barre oblique inverse

Comme indiqué précédemment, les expressions régulières utilisent la barre oblique inverse (backslash en anglais) pour indiquer des constructions particulières ou pour autoriser des caractères spéciaux sans que leur signification spéciale ne soit invoquée. C’est en contradiction avec l’usage de Python qui est qu’un caractère doit avoir la même signification dans les littéraux de chaînes de caractères.

Considérons que vous voulez écrire une RE qui fait correspondre la chaîne de caractères \section (on en trouve dans un fichier LaTeX). Pour savoir ce qu’il faut coder dans votre programme, commençons par la chaîne de caractères cherchée. Ensuite, nous devons échapper chaque barre oblique inverse et tout autre métacaractère en les précédant d’une barre oblique inverse, ce qui donne la chaîne de caractères \\section. La chaîne résultante qui doit être passée à re.compile() est donc \\section. Comme nous devons l’exprimer sous la forme d’une chaîne littérale Python, nous devons échapper les deux barres obliques inverses encore une fois.

Caractères

Niveau

\section

Chaîne de caractère à chercher

\\section

Barre oblique inverse échappée pour re.compile()

"\\\\section"

Barres obliques inverses échappées pour un littéral de chaîne de caractères

Pour faire court, si vous cherchez une correspondance pour une barre oblique inverse littérale, écrivez '\\\\' dans votre chaîne RE, car l’expression régulière doit être \\ et que chaque barre oblique inverse doit être exprimée comme \\ dans un littéral chaîne de caractères Python. Dans les RE qui comportent plusieurs barres obliques inverses, cela conduit à beaucoup de barres obliques inverses et rend la chaîne résultante difficile à comprendre.

La solution consiste à utiliser les chaînes brutes Python pour les expressions régulières ; les barres obliques inverses ne sont pas gérées d’une manière particulière dans les chaînes littérales préfixées avec 'r'. Ainsi, r"\n" est la chaîne de deux caractères contenant '\' et 'n' alors que "\n" est la chaîne contenant uniquement le caractère retour à la ligne. Les expressions régulières sont souvent écrites dans le code Python en utilisant la notation « chaînes brutes ».

En complément, les séquences d’échappement valides dans les expressions régulières, mais non valides dans les littéraux chaînes classiques, produisent dorénavant un DeprecationWarning et, possiblement, deviendront une SyntaxError, ce qui signifie que les séquences seront invalides si la notation « chaîne brute » ou l’échappement des barres obliques inverses ne sont pas utilisés.

Chaîne normale

Chaîne de caractères brute

"ab*"

r"ab*"

"\\\\section"

r"\\section"

"\\w+\\s+\\1"

r"\w+\s+\1"

Recherche de correspondances

Une fois que nous avons un objet représentant une expression régulière compilée, qu’en faisons-nous ? Les objets motifs ont plusieurs méthodes et attributs. Seuls les plus significatifs seront couverts ici ; consultez la documentation re pour la liste complète.

Méthode/Attribut

Objectif

match()

Détermine si la RE fait correspond dès le début de la chaîne.

search()

Analyse la chaîne à la recherche d’une position où la RE correspond.

findall()

Trouve toutes les sous-chaînes qui correspondent à la RE et les renvoie sous la forme d’une liste.

finditer()

Trouve toutes les sous-chaînes qui correspondent à la RE et les renvoie sous la forme d’un itérateur.

match() and search() return None if no match can be found. If they’re successful, a match object instance is returned, containing information about the match: where it starts and ends, the substring it matched, and more.

Vous pouvez apprendre leur fonctionnement en expérimentant de manière interactive avec le module re. Si vous disposez de tkinter, vous pouvez aussi regarder les sources de Tools/demo/redemo.py [https://github.com/python/cpython/tree/3.6/Tools/demo/redemo.py], un programme de démonstration inclus dans la distribution Python. Ce programme vous permet de rentrer des RE et des chaînes, affichant si la RE correspond ou pas. redemo.py peut s’avérer particulièrement utile quand vous devez déboguer une RE compliquée.

Ce guide utilise l’interpréteur standard de Python pour ses exemples. Commencez par lancer l’interpréteur Python, importez le module re et compilez une RE :

>>> import re
>>> p = re.compile('[a-z]+')
>>> p
re.compile('[a-z]+')

Now, you can try matching various strings against the RE [a-z]+. An empty string shouldn’t match at all, since + means “one or more repetitions”. match() should return None in this case, which will cause the interpreter to print no output. You can explicitly print the result of match() to make this clear.

>>> p.match("")
>>> print(p.match(""))
None

Now, let’s try it on a string that it should match, such as tempo. In this case, match() will return a match object, so you should store the result in a variable for later use.

>>> m = p.match('tempo')
>>> m
<_sre.SRE_Match object; span=(0, 5), match='tempo'>

Maintenant, vous pouvez interroger l’objet correspondance pour obtenir des informations sur la chaîne qui correspond. Les instances d’objets correspondances possèdent plusieurs méthodes et attributs ; les plus importants sont :

Méthode/Attribut

Objectif

group()

Renvoie la chaîne de caractères correspondant à la RE

start()

Renvoie la position de début de la correspondance

end()

Renvoie la position de fin de la correspondance

span()

Renvoie un tuple contenant les positions (début, fin) de la correspondance

Essayons ces méthodes pour clarifier leur signification :

>>> m.group()
'tempo'
>>> m.start(), m.end()
(0, 5)
>>> m.span()
(0, 5)

group() returns the substring that was matched by the RE. start() and end() return the starting and ending index of the match. span() returns both start and end indexes in a single tuple. Since the match() method only checks if the RE matches at the start of a string, start() will always be zero. However, the search() method of patterns scans through the string, so the match may not start at zero in that case.

>>> print(p.match('::: message'))
None
>>> m = p.search('::: message'); print(m)
<_sre.SRE_Match object; span=(4, 11), match='message'>
>>> m.group()
'message'
>>> m.span()
(4, 11)

Dans les programmes réels, la façon de faire la plus courante consiste à stocker l’objet correspondance dans une variable, puis à vérifier s’il vaut None. Généralement, cela ressemble à ceci :

p = re.compile( ... )
m = p.match( 'string goes here' )
if m:
    print('Match found: ', m.group())
else:
    print('No match')

Two pattern methods return all of the matches for a pattern. findall() returns a list of matching strings:

>>> p = re.compile(r'\d+')
>>> p.findall('12 drummers drumming, 11 pipers piping, 10 lords a-leaping')
['12', '11', '10']

Le préfixe r, qui indique une chaîne brute littérale, est nécessaire dans cet exemple car les séquences d’échappement dans une chaîne littérale qui ne sont pas reconnues par Python, alors qu’elles le sont par les expressions régulières, induisent maintenant un DeprecationWarning et deviendront possiblement des SyntaxError. Reportez-vous à La maudite barre oblique inverse.

findall() doit créer la liste entière avant d’être renvoyé comme résultat. La méthode finditer() renvoie une séquence d’instances d’objets correspondances en tant qu’itérateur :

>>> iterator = p.finditer('12 drummers drumming, 11 ... 10 ...')
>>> iterator
<callable_iterator object at 0x...>
>>> for match in iterator:
...     print(match.span())
...
(0, 2)
(22, 24)
(29, 31)

Fonctions de niveau module

Vous n’avez pas besoin de créer un objet motif et d’appeler ses méthodes ; le module re fournit des fonctions à son niveau, ce sont match(), search(), findall(), sub() et ainsi de suite. Ces fonctions prennent les mêmes arguments que les méthodes correspondantes des objets motifs, avec la chaîne RE ajoutée en tant que premier argument. Elles renvoient toujours None ou une instance d’objet correspondance.

>>> print(re.match(r'From\s+', 'Fromage amk'))
None
>>> re.match(r'From\s+', 'From amk Thu May 14 19:12:10 1998')
<_sre.SRE_Match object; span=(0, 5), match='From '>

En interne, ces fonctions créent simplement un objet motif pour vous et appellent la méthode appropriée de cet objet. Elles stockent également l’objet compilé dans un cache afin que les appels suivants qui utilisent la même RE n’aient pas besoin d’analyser le motif une nouvelle fois.

Devez-vous utiliser ces fonctions au niveau des modules ou devez-vous calculer le motif et appeler vous-même ses méthodes ? Si vous utilisez l’expression régulière à l’intérieur d’une boucle, la pré-compilation permet d’économiser quelques appels de fonctions. En dehors des boucles, il n’y a pas beaucoup de différence grâce au cache interne.

Options de compilation

Les options de compilation vous permettent de modifier le comportement des expressions régulières. Ces options sont accessibles dans le module re par deux noms, un long du type IGNORECASE et un court (une seule lettre) tel que I (si vous êtes habitués aux modificateurs de motifs Perl, la version courte utilise les mêmes lettres que Perl, par exemple la version courte de re.VERBOSE est re.X). Plusieurs options peuvent être spécifiées en appliquant l’opérateur bit-à-bit OR ; par exemple, re.I | re.M active à la fois les options I et M.

Vous trouvez ci-dessous le tableau des options disponibles, suivies d’explications détaillées.

Option

Signification

ASCII, A

Transforme plusieurs échappements tels que \w, \b, \s et \d de manière à ce qu’ils ne correspondent qu’à des caractères ASCII ayant la propriété demandée.

DOTALL, S

Fait en sorte que . corresponde à n’importe quel caractère, caractère de retour à la ligne inclus.

IGNORECASE, I

Recherche une correspondance sans tenir compte de la casse.

LOCALE, L

Recherche une correspondance en tenant compte de la configuration de la région.

MULTILINE, M

Correspondance multi-lignes, affecte ^ et $.

VERBOSE, X (pour extended, c-à-d étendu en anglais)

Active les RE verbeuses, qui peuvent être organisées de manière plus propre et compréhensible.

I

IGNORECASE

Effectue une correspondance insensible à la casse ; les classes de caractères et les littéraux de chaînes de caractères ignorent la casse pour la correspondance. Par exemple, [A-Z] correspond aussi aux lettres minuscules. La correspondance Unicode complète fonctionne également, sauf si l’option ASCII est utilisée pour désactiver les correspondances non ASCII. Lorsque les motifs Unicode [a-z] ou [A-Z] sont utilisés en combinaison avec l’option IGNORECASE, ils correspondent avec les 52 lettres ASCII et 4 lettres non ASCII supplémentaires : “İ” (U+0130, lettre I en majuscule latine avec un point au-dessus), “ı” (U+0131, lettre minuscule latine i sans point au-dessus), “ſ” (U+017F, lettre minuscule latine longue s) et “K” (U+212A, signe du Kelvin). Spam correspond ainsi à 'Spam', 'spam', 'spAM' ou 'ſpam' (ce dernier ne correspond qu’en mode Unicode). Le passage en minuscules ne prend pas en compte la configuration de région courante ; elle le fait si vous mettez aussi l’option LOCALE.

L

LOCALE

Rend \w, \W, \b, \B et les correspondances non sensibles à la casse dépendants de la configuration de la région courante au lieu de la base de données Unicode.

Les locales sont une caractéristique de la bibliothèque C destinées à favoriser une programmation qui tient compte des différences linguistiques (NdT : nous utilisons configuration de région dans cette page pour désigner ce concept de la bibliothèque C). Par exemple, si vous traitez du texte français, vous souhaitez pouvoir écrire \w+ pour faire correspondre les mots, mais \w ne correspond qu’à la classe de caractères [A-Za-za-z] en octets ; cette classe ne correspond pas avec les octets codant é ou ç. Si votre système est configuré correctement et que la configuration de région est définie sur “français”, certaines fonctions C diront à votre programme que l’octet codant é doit être considéré comme une lettre. Définir l’option LOCALE lors de la compilation d’une expression régulière fait que l’objet compilé résultant utilise ces fonctions C pour \w ; c’est plus lent mais cela permet à \w+ de correspondre avec les mots français tel qu’attendu. L’utilisation de cette option est déconseillée en Python 3 car le mécanisme de locale est très peu fiable, il ne gère qu’une seule « culture » à la fois et il ne fonctionne qu’avec des locales 8 bits. La correspondance Unicode est déjà activée par défaut dans Python 3 pour les motifs Unicode (type str) et elle est capable de gérer différentes configurations de régions.

M

MULTILINE

Nota : ^ et $ n’ont pas encore été expliqués ; ils sont introduits dans la section Plus de métacaractères.

Normalement, ^ correspond uniquement au début de la chaîne, et $ correspond uniquement à la fin de la chaîne et immédiatement avant la nouvelle ligne (s’il y en a une) à la fin de la chaîne. Lorsque cette option est spécifiée, ^ correspond au début de la chaîne de caractères et au début de chaque ligne de la chaîne de caractères, immédiatement après le début de la nouvelle ligne. De même, le métacaractère $ correspond à la fin de la chaîne de caractères ou à la fin de chaque ligne (précédant immédiatement chaque nouvelle ligne).

S

DOTALL

Fait que le caractère spécial '.' corresponde avec n’importe quel caractère, y compris le retour à la ligne ; sans cette option, '.' correspond avec tout, sauf le retour à la ligne.

A

ASCII

Fait que \w, \W, \b, \B, \s et \S ne correspondent qu’avec des caractères ASCII au lieu de l’ensemble des caractères Unicode. Cette option n’a de sens que pour des motifs Unicode, elle est ignorée pour les motifs bytes.

X

VERBOSE

Cette option vous permet d’écrire des expressions régulières plus lisibles en vous permettant plus de flexibilité pour le formatage. Lorsque cette option est activée, les « blancs » dans la chaîne RE sont ignorés, sauf lorsque le « blanc » se trouve dans une classe de caractères ou est précédé d’une barre oblique inverse ; ceci vous permet d’organiser et d’indenter vos RE plus clairement. Cette option vous permet également de placer des commentaires dans une RE, ils seront ignorés par le moteur ; les commentaires commencent par un '#' qui n’est ni dans une classe de caractères, ni précédé d’une barre oblique inverse.

Par exemple, voici une RE qui utilise re.VERBOSE ; vous pouvez constater qu’elle est beaucoup plus facile à lire

charref = re.compile(r"""
 &[#]                # Start of a numeric entity reference
 (
     0[0-7]+         # Octal form
   | [0-9]+          # Decimal form
   | x[0-9a-fA-F]+   # Hexadecimal form
 )
 ;                   # Trailing semicolon
""", re.VERBOSE)

Sans l’option verbeuse, cette RE ressemble à ceci :

charref = re.compile("&#(0[0-7]+"
                     "|[0-9]+"
                     "|x[0-9a-fA-F]+);")

Dans l’exemple ci-dessus, Python concatène automatiquement les littéraux chaînes de caractères qui ont été utilisés pour séparer la RE en petits morceaux, mais la RE reste plus difficile à comprendre que sa version utilisant re.VERBOSE.

Des motifs plus puissants

Jusqu’à présent nous avons seulement couvert une partie des fonctionnalités des expressions régulières. Dans cette section, nous couvrirons quelques nouveaux métacaractères et l’utilisation des groupes pour récupérer des portions de textes correspondantes.

Plus de métacaractères

Nous n’avons pas encore couvert tous les métacaractères. Cette section traite de la plupart de ceux que nous n’avons pas abordés.

Certains métacaractères restants sont des assertions de largeur zéro (zero-width assertions en anglais). Ils ne font pas avancer le moteur dans la chaîne de caractères ; ils ne consomment aucun caractère et ils réussissent ou échouent tout simplement. Par exemple, \b est une assertion selon laquelle la position actuelle est située à la limite d’un mot ; la position n’est pas modifiée par le  » b  ». Cela signifie que les assertions de largeur zéro ne doivent pas être répétées car, si elles correspondent à un endroit donné, elles correspondent automatiquement un nombre infini de fois.

|

Union ensembliste ou opérateur « ou ». Si A et B sont des expressions régulières, A|B correspond à toute chaine qui correspond à A ou à B. La priorité de | est très faible afin de pouvoir effectuer simplement des unions de chaînes de plusieurs caractères. Crow|Servo correspond avec 'Crow' ou 'Servo', mais pas avec 'Cro', un 'w' ou un 'S', ou encore 'ervo'.

Pour correspondre avec un '|' littéral, utilisez \| ou placez-le dans une classe de caractères, comme ceci [|].

^

Correspond à un début de ligne. À moins que l’option MULTILINE ne soit activée, cela ne fait correspondre que le début de la chaîne. Dans le mode MULTILINE, cela fait aussi correspondre immédiatement après chaque nouvelle ligne à l’intérieur de la chaîne.

Par exemple, si vous voulez trouver le mot From uniquement quand il est en début de ligne, la RE à utiliser est ^From.

>>> print(re.search('^From', 'From Here to Eternity'))
<_sre.SRE_Match object; span=(0, 4), match='From'>
>>> print(re.search('^From', 'Reciting From Memory'))
None

Pour trouver un '^' littéral, utilisez \^.

$

Correspond à une fin de ligne, ce qui veut dire soit la fin de la chaîne, soit tout emplacement qui est suivi du caractère de nouvelle ligne.

>>> print(re.search('}$', '{block}'))
<_sre.SRE_Match object; span=(6, 7), match='}'>
>>> print(re.search('}$', '{block} '))
None
>>> print(re.search('}$', '{block}\n'))
<_sre.SRE_Match object; span=(6, 7), match='}'>

Pour trouver un '$' littéral, utilisez \$ ou placez-le à l’intérieur d’une classe de caractères, comme ceci [$].

\A

Correspond au début de la chaîne de caractère, uniquement. Si l’option MULTILINE n’est pas activée, \A et ^ sont équivalents. Dans le mode MULTILINE, ils sont différents : \A ne correspond toujours qu’au début de la chaîne alors que ^ correspond aussi aux emplacements situés immédiatement après une nouvelle ligne à l’intérieur de la chaîne.

\Z

Correspond uniquement à la fin d’une chaîne de caractères.

\b

Limite de mot. C’est une assertion de largeur zéro qui correspond uniquement aux positions de début et de fin de mot. Un mot est défini comme une séquence de caractères alphanumériques ; ainsi, la fin d’un mot est indiquée par un « blanc » ou un caractère non-alphanumérique.

L’exemple suivant fait correspondre class seulement si c’est un mot complet ; il n’y a pas de correspondance quand il est à l’intérieur d’un autre mot.

>>> p = re.compile(r'\bclass\b')
>>> print(p.search('no class at all'))
<_sre.SRE_Match object; span=(3, 8), match='class'>
>>> print(p.search('the declassified algorithm'))
None
>>> print(p.search('one subclass is'))
None

Quand vous utilisez cette séquence spéciale, gardez deux choses à l’esprit. Tout d’abord, c’est la pire collision entre les littéraux des chaînes Python et les séquences d’expressions régulières. Dans les littéraux de chaîne de caractères Python, \b` est le caractère de retour-arrière (backspace en anglais), dont la valeur ASCII est 8. Si vous n’utilisez pas les chaînes de caractères brutes, alors Python convertit le \b en retour-arrière, et votre RE ne correspond pas à ce que vous attendez. L’exemple suivant ressemble à notre RE précédente, mais nous avons omis le `'r' devant la chaîne RE.

>>> p = re.compile('\bclass\b')
>>> print(p.search('no class at all'))
None
>>> print(p.search('\b' + 'class' + '\b'))
<_sre.SRE_Match object; span=(0, 7), match='\x08class\x08'>

Ensuite, dans une classe de caractères, où cette assertion n’a pas lieu d’être, \b représente le caractère retour-arrière, afin d’être compatible avec les littéraux de chaînes de caractères.

\B

Encore une assertion de largeur zéro, qui est l’opposée de \b, c’est-à-dire qu’elle fait correspondre uniquement les emplacements qui ne sont pas à la limite d’un mot.

Regroupement

Frequently you need to obtain more information than just whether the RE matched or not. Regular expressions are often used to dissect strings by writing a RE divided into several subgroups which match different components of interest. For example, an RFC-822 header line is divided into a header name and a value, separated by a ':', like this:

From: author@example.com
User-Agent: Thunderbird 1.5.0.9 (X11/20061227)
MIME-Version: 1.0
To: editor@example.com

Vous pouvez alors écrire une expression régulière qui fait correspondre une ligne d’en-tête entière et qui comporte un groupe correspondant au nom de l’en-tête, et un autre groupe correspondant à la valeur de l’en-tête.

Les groupes sont délimités par les métacaractères marqueurs '('``et ``')'. '(' et ')' ont à peu près le même sens que dans les expressions mathématiques ; ils forment un groupe à partir des expressions qu’ils encadrent ; vous pouvez répéter le contenu d’un groupe à l’aide d’un quantificateur, comme *, +, ? ou {m,n}. Par exemple, (ab)* correspond à zéro, une ou plusieurs fois ab.

>>> p = re.compile('(ab)*')
>>> print(p.match('ababababab').span())
(0, 10)

Groups indicated with '(', ')' also capture the starting and ending index of the text that they match; this can be retrieved by passing an argument to group(), start(), end(), and span(). Groups are numbered starting with 0. Group 0 is always present; it’s the whole RE, so match object methods all have group 0 as their default argument. Later we’ll see how to express groups that don’t capture the span of text that they match.

>>> p = re.compile('(a)b')
>>> m = p.match('ab')
>>> m.group()
'ab'
>>> m.group(0)
'ab'

Les sous-groupes sont numérotés de la gauche vers la droite, à partir de 1. Les groupes peuvent être imbriqués ; pour déterminer le numéro, il vous suffit de compter le nombre de parenthèses ouvrantes de la gauche vers la droite.

>>> p = re.compile('(a(b)c)d')
>>> m = p.match('abcd')
>>> m.group(0)
'abcd'
>>> m.group(1)
'abc'
>>> m.group(2)
'b'

group() can be passed multiple group numbers at a time, in which case it will return a tuple containing the corresponding values for those groups.

>>> m.group(2,1,2)
('b', 'abc', 'b')

The groups() method returns a tuple containing the strings for all the subgroups, from 1 up to however many there are.

>>> m.groups()
('abc', 'b')

Les renvois dans un motif vous permettent de spécifier que le contenu d’un groupe précédent doit aussi être trouvé à l’emplacement actuel dans la chaîne. Par exemple, \1 réussit si le contenu du premier groupe se trouve aussi à la position courante, sinon il échoue. Rappelez-vous que les littéraux de chaînes Python utilisent aussi la barre oblique inverse suivie d’un nombre pour insérer des caractères arbitraires dans une chaîne ; soyez sûr d’utiliser une chaîne brute quand vous faites des renvois dans une RE.

Par exemple, la RE suivante détecte les mots doublés dans une chaîne.

>>> p = re.compile(r'\b(\w+)\s+\1\b')
>>> p.search('Paris in the the spring').group()
'the the'

Les renvois tels que celui-ci ne sont pas très utiles pour effectuer une simple recherche dans une chaîne — il n’y a que peu de formats de textes qui répètent des données ainsi — mais vous verrez bientôt qu’ils sont très utiles pour effectuer des substitutions dans les chaînes.

Groupes non de capture et groupes nommés

Les RE élaborées peuvent utiliser de nombreux groupes, à la fois pour capturer des sous-chaînes intéressantes ainsi que pour regrouper et structurer la RE elle-même. Dans les RE complexes, il devient difficile de garder la trace des numéros de groupes. Deux caractéristiques aident à résoudre ce problème, toutes deux utilisant la même syntaxe d’extension des expressions régulières. Nous allons donc commencer en examinant cette syntaxe.

Les puissantes extensions des expressions régulières de Perl 5 sont réputées. Pour les mettre en œuvre, les développeurs Perl ne pouvaient pas utiliser de nouveaux métacaractères simples ou de nouvelles séquences commençant par \ sans que les RE Perl ne deviennent trop différentes des RE standards au point de créer de la confusion. S’ils avaient choisi & comme nouveau métacaractère, par exemple, les expressions déjà écrites auraient considéré que & était un caractère standard et ne l’aurait pas échappé en écrivant \& ou [&].

La solution adoptée par les développeurs Perl a été d’utiliser (?...) comme syntaxe d’extension. Placer ? immédiatement après une parenthèse était une erreur de syntaxe, parce que le ? n’a alors rien à répéter. Ainsi, cela n’a pas introduit de problème de compatibilité. Les caractères qui suivent immédiatement le ? indiquent quelle extension est utilisée, donc (?=truc) est une chose (une assertion positive anticipée) et (?:truc) est une autre chose (la sous-expression truc que l’on groupe).

Python gère plusieurs des extensions Perl et rajoute une extension à la syntaxe des extensions Perl. Si le premier caractère après le point d’interrogation est P, cela signifie que c’est une extension spécifique à Python.

Après avoir vu la syntaxe générale d’extension des RE, nous pouvons revenir aux fonctionnalités qui simplifient le travail avec les groupes dans des RE complexes.

Parfois, vous souhaitez utiliser un groupe pour marquer une partie de l’expression régulière mais le contenu de ce groupe ne vous intéresse pas vraiment. Vous pouvez l’indiquer explicitement en utilisant la syntaxe de groupe, mais sans indiquer que vous voulez en capturer le contenu : (?:...), où vous remplacez les ... par n’importe quelle expression régulière.

>>> m = re.match("([abc])+", "abc")
>>> m.groups()
('c',)
>>> m = re.match("(?:[abc])+", "abc")
>>> m.groups()
()

À part le fait que vous n’avez pas accès au contenu du groupe, un groupe se comporte exactement de la même manière qu’un groupe de capture ; vous pouvez placer n’importe quoi dedans, spécifier une répétition avec un métacaractère tel que * et l’imbriquer dans un autre groupe (de capture ou pas). (?:...) est particulièrement utile quand vous modifiez des motifs existants, puisque vous pouvez ajouter de nouveaux groupes sans changer la façon dont les autres groupes sont numérotés. Nous devons mentionner ici qu’il n’y a aucune différence de performance dans la recherche de groupes, de capture ou non ; les deux formes travaillent à la même vitesse.

Une fonctionnalité plus importante est le nommage des groupes : au lieu d’y faire référence par des nombres, vous pouvez référencer des groupes par leur nom.

La syntaxe pour nommer les groupes est l’une des extensions spécifiques à Python : (?P<nom>....)`. nom est, vous vous en doutez, le nom du groupe. Les groupes nommés se comportent exactement comme des groupes de capture, sauf qu’ils associent en plus un nom à un groupe. Les méthodes des objets correspondances qui gèrent les groupes de capture acceptent soit des entiers qui font référence aux numéros des groupes, soit des chaînes de caractères qui désignent les noms des groupes désirés. Les groupes nommés se voient toujours attribuer un numéro, vous pouvez ainsi récupérer les informations d’un groupe de deux façons :

>>> p = re.compile(r'(?P<word>\b\w+\b)')
>>> m = p.search( '(((( Lots of punctuation )))' )
>>> m.group('word')
'Lots'
>>> m.group(1)
'Lots'

Les groupes nommés sont pratiques car il est plus facile de se rappeler un nom qu’un numéro. Voici un exemple de RE tirée du module imaplib :

InternalDate = re.compile(r'INTERNALDATE "'
        r'(?P<day>[ 123][0-9])-(?P<mon>[A-Z][a-z][a-z])-'
        r'(?P<year>[0-9][0-9][0-9][0-9])'
        r' (?P<hour>[0-9][0-9]):(?P<min>[0-9][0-9]):(?P<sec>[0-9][0-9])'
        r' (?P<zonen>[-+])(?P<zoneh>[0-9][0-9])(?P<zonem>[0-9][0-9])'
        r'"')

Il est évidemment plus facile de récupérer m.group('zonem') que de se rappeler de récupérer le groupe 9.

La syntaxe des renvois dans une expression telle que (....)\1 fait référence au numéro du groupe. Il y a naturellement une variante qui utilise le nom du groupe au lieu du numéro. C’est une autre extension Python : (?P=nom) indique que le contenu du groupe appelé nom doit correspondre à nouveau avec l’emplacement courant. L’expression régulière pour trouver des mots doublés, \b(\w+)\s+\1\b peut ainsi être ré-écrite en \b(?P<mot>\w+)\s+(?P=mot)\b :

>>> p = re.compile(r'\b(?P<word>\w+)\s+(?P=word)\b')
>>> p.search('Paris in the the spring').group()
'the the'

Assertions prédictives

Une autre assertion de largeur zéro est l’assertion prédictive. Une assertion prédictive peut s’exprimer sous deux formes, la positive et la négative, comme ceci :

(?=...)

Assertion prédictive positive. Elle réussit si l’expression régulière contenue, représentée ici par ..., correspond effectivement à l’emplacement courant ; dans le cas contraire, elle échoue. Mais, une fois que l’expression contenue a été essayée, le moteur de correspondance n’avance pas ; le reste du motif est testé à l’endroit même où l’assertion a commencé.

(?!...)

Assertion prédictive négative. C’est l’opposée de l’assertion positive ; elle réussit si l’expression régulière contenue ne correspond pas à l’emplacement courant dans la chaine.

Pour rendre ceci plus concret, regardons le cas où une prédiction est utile. Considérons un motif simple qui doit faire correspondre un nom de fichier et le diviser en un nom de base et une extension, séparés par un .. Par exemple, dans news.rc, news est le nom de base et rc est l’extension du nom de fichier.

Le motif de correspondance est plutôt simple :

.*[.].*$

Notez que le . doit être traité spécialement car c’est un métacaractère, nous le plaçons donc à l’intérieur d’une classe de caractères pour ne faire correspondre que ce caractère spécifique. Notez également le $ en fin ; nous l’avons ajouté pour nous assurer que tout le reste de la chaîne est bien inclus dans l’extension. Cette expression régulière fait correspondre truc.bar, autoexec.bat, sendmail.cf et printers.conf.

Maintenant, compliquons un peu le problème ; si nous voulons faire correspondre les noms de fichiers dont l’extension n’est pas bat ? voici quelques tentatives incorrectes :

.*[.][^b].*$ Le premier essai ci-dessus tente d’exclure bat en spécifiant que le premier caractère de l’extension ne doit pas être b. Cela ne fonctionne pas, car le motif n’accepte pas truc.bar.

.*[.]([^b]..|.[^a].|..[^t])$

L’expression devient plus confuse si nous essayons de réparer la première solution en spécifiant l’un des cas suivants : le premier caractère de l’extension n’est pas b ; le deuxième caractère n’est pas a ; ou le troisième caractère n’est pas t`. Ce motif accepte truc.bar et rejette autoexec.bat, mais elle nécessite une extension de trois lettres et n’accepte pas un nom de fichier avec une extension de deux lettres comme sendmail.cf. Compliquons encore une fois le motif pour essayer de le réparer.

.*[.]([^b].?.?|.[^a]?.?|..?[^t]?)$

Pour cette troisième tentative, les deuxième et troisième lettres sont devenues facultatives afin de permettre la correspondance avec des extensions plus courtes que trois caractères, comme sendmail.cf.

Le motif devient vraiment compliqué maintenant, ce qui le rend difficile à lire et à comprendre. Pire, si le problème change et que vous voulez exclure à la fois bat et exe en tant qu’extensions, le modèle deviendra encore plus compliqué et confus.

Une assertion prédictive négative supprime toute cette confusion :

.*[.](?!bat$)[^.]*$ Cette assertion prédictive négative signifie : si l’expression bat ne correspond pas à cet emplacement, essaie le reste du motif ; si bat$ correspond, tout le motif échoue. Le $ est nécessaire pour s’assurer que quelque chose comme sample.batch, où c’est seulement le début de l’extension qui vaut bat, est autorisé. Le [^...]* s’assure que le motif fonctionne lorsqu’il y a plusieurs points dans le nom de fichier.

Exclure une autre extension de nom de fichier est maintenant facile ; il suffit de l’ajouter comme alternative à l’intérieur de l’assertion. Le motif suivant exclut les noms de fichiers qui se terminent par bat ou exe :

.*[.](?!bat$|exe$)[^.]*$

Modification de chaînes

Jusqu’à présent, nous avons simplement effectué des recherches dans une chaîne statique. Les expressions régulières sont aussi couramment utilisées pour modifier les chaînes de caractères de diverses manières, en utilisant les méthodes suivantes des motifs :

Méthode/Attribut

Objectif

split()

Découpe la chaîne de caractère en liste, la découpant partout où la RE correspond

sub()

Recherche toutes les sous-chaînes de caractères où la RE correspond et les substitue par une chaîne de caractères différente

subn()

Fait la même chose que sub(), mais renvoie la nouvelle chaîne et le nombre de remplacements effectués

Découpage de chaînes

The split() method of a pattern splits a string apart wherever the RE matches, returning a list of the pieces. It’s similar to the split() method of strings but provides much more generality in the delimiters that you can split by; string split() only supports splitting by whitespace or by a fixed string. As you’d expect, there’s a module-level re.split() function, too.

.split(string[, maxsplit=0])

Découpe string en suivant les correspondances de l’expression régulière. Si des parenthèses de capture sont utilisées dans la RE, leur contenu est également renvoyé dans la liste résultante. Si maxsplit n’est pas nul, au plus maxsplit découpages sont effectués.

Vous pouvez limiter le nombre de découpages effectués en passant une valeur pour maxsplit. Quand maxsplit n’est pas nul, au plus maxsplit découpages sont effectués et le reste de la chaîne est renvoyé comme dernier élément de la liste. Dans l’exemple suivant, le délimiteur est toute séquence de caractères non alphanumériques.

>>> p = re.compile(r'\W+')
>>> p.split('This is a test, short and sweet, of split().')
['This', 'is', 'a', 'test', 'short', 'and', 'sweet', 'of', 'split', '']
>>> p.split('This is a test, short and sweet, of split().', 3)
['This', 'is', 'a', 'test, short and sweet, of split().']

Parfois, vous voulez récupérer le texte entre les délimiteurs mais aussi quel était le délimiteur. Si des parenthèses de capture sont utilisées dans la RE, leurs valeurs sont également renvoyées dans la liste. Comparons les appels suivants :

>>> p = re.compile(r'\W+')
>>> p2 = re.compile(r'(\W+)')
>>> p.split('This... is a test.')
['This', 'is', 'a', 'test', '']
>>> p2.split('This... is a test.')
['This', '... ', 'is', ' ', 'a', ' ', 'test', '.', '']

La fonction de niveau module re.split() ajoute la RE à utiliser comme premier argument, mais est par ailleurs identique.

>>> re.split(r'[\W]+', 'Words, words, words.')
['Words', 'words', 'words', '']
>>> re.split(r'([\W]+)', 'Words, words, words.')
['Words', ', ', 'words', ', ', 'words', '.', '']
>>> re.split(r'[\W]+', 'Words, words, words.', 1)
['Words', 'words, words.']

Recherche et substitution

Another common task is to find all the matches for a pattern, and replace them with a different string. The sub() method takes a replacement value, which can be either a string or a function, and the string to be processed.

.sub(replacement, string[, count=0])

Renvoie la chaîne obtenue en remplaçant les occurrences sans chevauchement les plus à gauche de la RE dans string par la substitution replacement. Si le motif n’est pas trouvé, string est renvoyée inchangée.

L’argument optionnel count est le nombre maximum d’occurrences du motif à remplacer ; count doit être un entier positif ou nul. La valeur par défaut de 0 signifie qu’il faut remplacer toutes les occurrences.

Here’s a simple example of using the sub() method. It replaces colour names with the word colour:

>>> p = re.compile('(blue|white|red)')
>>> p.sub('colour', 'blue socks and red shoes')
'colour socks and colour shoes'
>>> p.sub('colour', 'blue socks and red shoes', count=1)
'colour socks and red shoes'

The subn() method does the same work, but returns a 2-tuple containing the new string value and the number of replacements that were performed:

>>> p = re.compile('(blue|white|red)')
>>> p.subn('colour', 'blue socks and red shoes')
('colour socks and colour shoes', 2)
>>> p.subn('colour', 'no colours at all')
('no colours at all', 0)

Empty matches are replaced only when they’re not adjacent to a previous match.

>>> p = re.compile('x*')
>>> p.sub('-', 'abxd')
'-a-b-d-'

Si replacement est une chaîne de caractères, toute barre oblique inverse d’échappement est traitée. C’est-à-dire que `\n est converti en caractère de nouvelle ligne, \r est converti en retour chariot, et ainsi de suite. Les échappements inconnus comme \& sont laissés tels quels. Les renvois, tels que \6, sont remplacés par la sous-chaîne correspondante au groupe dans le RE. Ceci vous permet d’incorporer des parties du texte original dans la chaîne de remplacement résultante.

Cet exemple fait correspondre le mot section suivi par une chaîne encadrée par { et }, et modifie section en subsection :

>>> p = re.compile('section{ ( [^}]* ) }', re.VERBOSE)
>>> p.sub(r'subsection{\1}','section{First} section{second}')
'subsection{First} subsection{second}'

Il existe aussi une syntaxe pour faire référence aux groupes nommés définis par la syntaxe (?P<nom>....). \g<nom> utilise la sous-chaîne correspondante au groupe nommé nom et \g<numéro> utilise le numéro de groupe correspondant. \g<2> est donc l’équivalent de \2, mais n’est pas ambigu dans une chaîne de substitution telle que \g<2>0 (\20 serait interprété comme une référence au groupe 20 et non comme une référence au groupe 2 suivie du caractère littéral '0'). Les substitutions suivantes sont toutes équivalentes mais utilisent les trois variantes de la chaîne de remplacement.

>>> p = re.compile('section{ (?P<name> [^}]* ) }', re.VERBOSE)
>>> p.sub(r'subsection{\1}','section{First}')
'subsection{First}'
>>> p.sub(r'subsection{\g<1>}','section{First}')
'subsection{First}'
>>> p.sub(r'subsection{\g<name>}','section{First}')
'subsection{First}'

replacement peut aussi être une fonction, ce qui vous donne encore plus de contrôle. Si replacement est une fonction, la fonction est appelée pour chaque occurrence non chevauchante de pattern. À chaque appel, un argument objet correspondance est passé à la fonction, qui peut utiliser cette information pour calculer la chaîne de remplacement désirée et la renvoyer.

Dans l’exemple suivant, la fonction de substitution convertit un nombre décimal en hexadécimal :

>>> def hexrepl(match):
...     "Return the hex string for a decimal number"
...     value = int(match.group())
...     return hex(value)
...
>>> p = re.compile(r'\d+')
>>> p.sub(hexrepl, 'Call 65490 for printing, 49152 for user code.')
'Call 0xffd2 for printing, 0xc000 for user code.'

Quand vous utilisez la fonction de niveau module re.sub(), le motif est passé comme premier argument. Vous pouvez fournir le motif sous forme d’objet ou de chaîne de caractères ; si vous avez besoin de spécifier des options pour l’expression régulière, vous devez soit utiliser un objet motif comme premier paramètre, soit utiliser des modificateurs intégrés dans la chaîne de caractères, par exemple sub("(?i)b+", "x", "bbbb BBBBB")```renvoie ``'x x'.

Problèmes classiques

Les expressions régulières constituent un outil puissant pour certaines applications mais, à certains égards, leur comportement n’est pas intuitif et, parfois, elles ne se comportent pas comme vous pouvez vous y attendre. Cette section met en évidence certains des pièges les plus courants.

Utilisez les méthodes du type string

Parfois, il ne faut pas utiliser le module re. Si vous faites correspondre une chaîne fixe, ou une classe à un seul caractère, et que vous n’utilisez pas les fonctionnalités de re telles que l’option IGNORECASE, alors la puissance des expressions régulières n’est pas nécessaire. Les chaînes de caractères ont plusieurs méthodes pour opérer sur des chaînes fixes et elles sont généralement beaucoup plus rapides, parce que l’implémentation est une seule petite boucle C qui a été optimisée, au lieu du gros moteur d’expressions régulières plus généraliste.

Nous pouvons prendre l’exemple du remplacement d’une seule chaîne fixe par une autre ; vous souhaitez remplacer mot par acte. re.sub() semble être faite pour cela, mais regardons la méthode replace(). Notons que replace() remplace aussi mot à l’intérieur des mots, transformant moteur en acteeur, mais la RE naïve mot aurait aussi fait cela (pour éviter d’effectuer la substitution sur des parties de mots, le motif doit être \bmot\b, qui exige que mot soit en limite de mot d’un côté et de l’autre ; c’est au-delà des capacités de la méthode replace()).

Une autre tâche classique est de supprimer chaque occurrence d’un seul caractère d’une chaîne de caractères ou de le remplacer par un autre caractère unique. Vous pouvez le faire avec quelque chose comme re.sub('\n', ' ', S), mais translate() en est capable et est plus rapide que n’importe quelle opération d’expression régulière.

Bref, avant de passer au module re, évaluez d’abord si votre problème peut être résolu avec une méthode de chaîne plus rapide et plus simple.

match() contre search()

La fonction match() vérifie seulement si la RE correspond au début de la chaîne de caractères tandis que search() parcourt la chaîne de caractères pour trouver une correspondance. Il est important de garder cette distinction à l’esprit. Rappelez-vous, match() ne trouve qu’une correspondance qui commence à 0 ; si la correspondance commence plus loin, match() ne la trouve pas.

>>> print(re.match('super', 'superstition').span())
(0, 5)
>>> print(re.match('super', 'insuperable'))
None

D’un autre côté, search() balaie la chaîne de caractères, rapportant la première correspondance qu’elle trouve.

>>> print(re.search('super', 'superstition').span())
(0, 5)
>>> print(re.search('super', 'insuperable').span())
(2, 7)

Vous pouvez être tenté d’utiliser re.match() en ajoutant simplement .* au début de votre RE. Ce n’est pas une bonne idée, utilisez plutôt re.search(). Le compilateur d’expressions régulières analyse les REs pour optimiser le processus de recherche d’une correspondance. Cette analyse permet de déterminer ce que doit être le premier caractère d’une correspondance ; par exemple, un motif commençant par Corbeau doit faire correspondre un 'C' en tête. L’analyse permet au moteur de parcourir rapidement la chaîne de caractères à la recherche du caractère de départ, n’essayant la correspondance complète que si un « C » a déjà été trouvé.

Ajouter .* annihile cette optimisation, nécessitant un balayage jusqu’à la fin de la chaîne de caractères, puis un retour en arrière pour trouver une correspondance pour le reste de la RE. Préférez l’utilisation re.search().

Glouton contre non-glouton

Si vous répétez un motif dans une expression régulière, comme a*, l’action résultante est de consommer autant de motifs que possible. C’est un problème lorsque vous essayez de faire correspondre une paire de délimiteurs, comme des chevrons encadrant une balise HTML. Le motif naïf pour faire correspondre une seule balise HTML ne fonctionne pas en raison de la nature gloutonne de .*.

>>> s = '<html><head><title>Title</title>'
>>> len(s)
32
>>> print(re.match('<.*>', s).span())
(0, 32)
>>> print(re.match('<.*>', s).group())
<html><head><title>Title</title>

La RE correspond au '<' de '<html>' et le .*` consomme le reste de la chaîne. Mais, comme il reste des éléments du motif dans la RE et que le > ne peut pas correspondre à la fin de la chaîne de caractères, le moteur d’expression régulière doit faire marche arrière caractère par caractère jusqu’à ce qu’il trouve une correspondance pour le >. La correspondance finale s’étend du '<' de '<html>' au '>' de '</title>', ce qui n’est pas ce que vous voulez.

Dans ce cas, la solution consiste à utiliser des quantificateurs non gloutons tels que *?, +?, ?? ou {m,n}?, qui effectuent une correspondance aussi petite que possible. Dans l’exemple ci-dessus, le '>' est essayé immédiatement après que le '<' corresponde et, s’il échoue, le moteur avance caractère par caractère, ré-essayant '>' à chaque pas. Nous obtenons alors le bon résultat :

>>> print(re.match('<.*?>', s).group())
<html>

Note : l’analyse du HTML ou du XML avec des expressions régulières est tout sauf une sinécure. Les motifs écrits à la va-vite traiteront les cas communs, mais HTML et XML ont des cas spéciaux qui font planter l’expression régulière évidente ; quand vous aurez écrit une expression régulière qui traite tous les cas possibles, les motifs seront très compliqués. Utilisez un module d’analyse HTML ou XML pour de telles tâches.

Utilisez re.VERBOSE

À présent, vous vous êtes rendu compte que les expressions régulières sont une notation très compacte, mais qu’elles ne sont pas très lisibles. Une RE modérément complexe peut rapidement devenir une longue collection de barres obliques inverses, de parenthèses et de métacaractères, ce qui la rend difficile à lire et à comprendre.

Pour de telles RE, activer l’option re.VERBOSE à la compilation de l’expression régulière peut être utile ; cela vous permet de formater l’expression régulière de manière plus claire.

L’option re.VERBOSE a plusieurs effets. Les espaces dans l’expression régulière qui ne sont pas à l’intérieur d’une classe de caractères sont ignorées. Cela signifie qu’une expression comme chien | chat est équivalente à chien|chat qui est moins lisible, mais [a b] correspond toujours aux caractères 'a', 'b' ou à une espace. En outre, vous avez la possibilité de mettre des commentaires à l’intérieur d’une RE ; les commentaires s’étendent du caractère # à la nouvelle ligne suivante. Lorsque vous l’utilisez avec des chaînes à triple guillemets, cela permet aux RE d’être formatées plus proprement :

pat = re.compile(r"""
 \s*                 # Skip leading whitespace
 (?P<header>[^:]+)   # Header name
 \s* :               # Whitespace, and a colon
 (?P<value>.*?)      # The header's value -- *? used to
                     # lose the following trailing whitespace
 \s*$                # Trailing whitespace to end-of-line
""", re.VERBOSE)

Ceci est beaucoup plus lisible que :

pat = re.compile(r"\s*(?P<header>[^:]+)\s*:(?P<value>.*?)\s*$")

Vos commentaires

Les expressions régulières sont un sujet compliqué. Est-ce que ce document vous a aidé à les comprendre ? Des parties ne sont pas claires, ou des problèmes que vous avez rencontrés ne sont pas traités ici ? Si tel est le cas, merci d’envoyer vos suggestions d’améliorations à l’auteur.

Le livre le plus complet sur les expressions régulières est certainement Mastering Regular Expressions de Jeffrey Friedl, publié par O’Reilly. Malheureusement, il se concentre sur les déclinaisons Perl et Java des expressions régulières et ne contient aucun contenu pour Python ; il n’est donc pas utile d’en faire référence pour la programmation Python. (La première édition traitait du module Python regex, maintenant supprimé, ce qui ne vous aidera pas beaucoup.) Pensez à le retirer de votre bibliothèque.

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Socket Programming HOWTO

Auteur

Gordon McMillan

Résumé

Sockets are used nearly everywhere, but are one of the most severely misunderstood technologies around. This is a 10,000 foot overview of sockets. It’s not really a tutorial - you’ll still have work to do in getting things operational. It doesn’t cover the fine points (and there are a lot of them), but I hope it will give you enough background to begin using them decently.

Interfaces de connexion (sockets)

Je ne vais aborder que les connecteurs INET (i.e. IPv4), mais ils représentent au moins 99% des connecteurs (socket en anglais) utilisés. Et je n’aborderai que les connecteurs STREAM (i.e. TCP) — à moins que vous ne sachiez vraiment ce que vous faites (auquel cas ce HOWTO n’est pas pour vous !), vous obtiendrez un meilleur comportement et de meilleures performances avec un connecteur STREAM que tout autre. Je vais essayer d’éclaircir le mystère de ce qu’est un connecteur, ainsi que quelques conseils sur la façon de travailler avec des connecteurs bloquants et non bloquants. Mais je vais commencer par aborder les connecteurs bloquants. Nous avons besoin de savoir comment ils fonctionnent avant de traiter les connecteurs non bloquants.

Part of the trouble with understanding these things is that « socket » can mean a number of subtly different things, depending on context. So first, let’s make a distinction between a « client » socket - an endpoint of a conversation, and a « server » socket, which is more like a switchboard operator. The client application (your browser, for example) uses « client » sockets exclusively; the web server it’s talking to uses both « server » sockets and « client » sockets.

Historique

Of the various forms of IPC, sockets are by far the most popular. On any given platform, there are likely to be other forms of IPC that are faster, but for cross-platform communication, sockets are about the only game in town.

They were invented in Berkeley as part of the BSD flavor of Unix. They spread like wildfire with the Internet. With good reason — the combination of sockets with INET makes talking to arbitrary machines around the world unbelievably easy (at least compared to other schemes).

Créer un connecteur

Roughly speaking, when you clicked on the link that brought you to this page, your browser did something like the following:

# create an INET, STREAMing socket
s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
# now connect to the web server on port 80 - the normal http port
s.connect(("www.python.org", 80))

When the connect completes, the socket s can be used to send in a request for the text of the page. The same socket will read the reply, and then be destroyed. That’s right, destroyed. Client sockets are normally only used for one exchange (or a small set of sequential exchanges).

What happens in the web server is a bit more complex. First, the web server creates a « server socket »:

# create an INET, STREAMing socket
serversocket = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
# bind the socket to a public host, and a well-known port
serversocket.bind((socket.gethostname(), 80))
# become a server socket
serversocket.listen(5)

Quelques remarques : nous avons utilisé socket.gethostname() pour que le connecteur soit visible par le monde extérieur. Si nous avions utilisé s.bind((('localhost', 80)) ou s.bind((('127.0.0.0.1', 80)) nous aurions encore un connecteur « serveur », mais qui ne serait visible que sur la machine même. s.bind('', 80)] spécifie que le socket est accessible par toute adresse que la machine possède.

Une deuxième chose à noter : les ports dont le numéro est petit sont généralement réservés aux services « bien connus » (HTTP, SNMP, etc.). Si vous expérimentez, utilisez un nombre suffisamment élevé (4 chiffres).

Enfin, l’argument listen indique à la bibliothèque de connecteurs que nous voulons qu’elle mette en file d’attente jusqu’à 5 requêtes de connexion (le maximum normal) avant de refuser les connexions externes. Si le reste du code est écrit correctement, cela devrait suffire.

Now that we have a « server » socket, listening on port 80, we can enter the mainloop of the web server:

while True:
    # accept connections from outside
    (clientsocket, address) = serversocket.accept()
    # now do something with the clientsocket
    # in this case, we'll pretend this is a threaded server
    ct = client_thread(clientsocket)
    ct.run()

There’s actually 3 general ways in which this loop could work - dispatching a thread to handle clientsocket, create a new process to handle clientsocket, or restructure this app to use non-blocking sockets, and multiplex between our « server » socket and any active clientsockets using select. More about that later. The important thing to understand now is this: this is all a « server » socket does. It doesn’t send any data. It doesn’t receive any data. It just produces « client » sockets. Each clientsocket is created in response to some other « client » socket doing a connect() to the host and port we’re bound to. As soon as we’ve created that clientsocket, we go back to listening for more connections. The two « clients » are free to chat it up - they are using some dynamically allocated port which will be recycled when the conversation ends.

Communication Entre Processus

Si vous avez besoin d’une communication rapide entre deux processus sur une même machine, vous devriez regarder comment utiliser les pipes ou la mémoire partagée. Si vous décidez d’utiliser les connecteurs AF_INET, liez le connecteur « serveur » à 'localhost'. Sur la plupart des plates-formes, cela court-circuite quelques couches réseau et est un peu plus rapide.

Voir aussi

The multiprocessing integrates cross-platform IPC into a higher-level API.

Using a Socket

The first thing to note, is that the web browser’s « client » socket and the web server’s « client » socket are identical beasts. That is, this is a « peer to peer » conversation. Or to put it another way, as the designer, you will have to decide what the rules of etiquette are for a conversation. Normally, the connecting socket starts the conversation, by sending in a request, or perhaps a signon. But that’s a design decision - it’s not a rule of sockets.

Now there are two sets of verbs to use for communication. You can use send and recv, or you can transform your client socket into a file-like beast and use read and write. The latter is the way Java presents its sockets. I’m not going to talk about it here, except to warn you that you need to use flush on sockets. These are buffered « files », and a common mistake is to write something, and then read for a reply. Without a flush in there, you may wait forever for the reply, because the request may still be in your output buffer.

Now we come to the major stumbling block of sockets - send and recv operate on the network buffers. They do not necessarily handle all the bytes you hand them (or expect from them), because their major focus is handling the network buffers. In general, they return when the associated network buffers have been filled (send) or emptied (recv). They then tell you how many bytes they handled. It is your responsibility to call them again until your message has been completely dealt with.

When a recv returns 0 bytes, it means the other side has closed (or is in the process of closing) the connection. You will not receive any more data on this connection. Ever. You may be able to send data successfully; I’ll talk more about this later.

Un protocole comme HTTP utilise un connecteur pour un seul transfert. Le client envoie une demande, puis lit une réponse. C’est tout. Le connecteur est mis au rebut. Cela signifie qu’un client peut détecter la fin de la réponse en recevant 0 octet.

Mais si vous prévoyez de réutiliser votre connecteur pour d’autres transferts, vous devez réaliser que il n’y a pas d”EOT sur un connecteur. Je répète : si un connecteur send ou recv retourne après avoir manipulé 0 octets, la connexion a été interrompue. Si la connexion n’a pas été interrompue, vous pouvez attendre sur un recv pour toujours, car le connecteur ne vous dira pas qu’il n’y a plus rien à lire (pour le moment). Maintenant, si vous y réfléchissez un peu, vous allez vous rendre compte d’une vérité fondamentale sur les connecteurs : les messages doivent être de longueur fixe (beurk), ou être délimités (haussement d’épaules), ou indiquer de quelle longueur ils sont (beaucoup mieux), ou terminer en coupant la connexion. Le choix est entièrement de votre côté, (mais certaines façons sont plus justes que d’autres).

En supposant que vous ne vouliez pas terminer la connexion, la solution la plus simple est un message de longueur fixe :

class MySocket:
    """demonstration class only
      - coded for clarity, not efficiency
    """

    def __init__(self, sock=None):
        if sock is None:
            self.sock = socket.socket(
                            socket.AF_INET, socket.SOCK_STREAM)
        else:
            self.sock = sock

    def connect(self, host, port):
        self.sock.connect((host, port))

    def mysend(self, msg):
        totalsent = 0
        while totalsent < MSGLEN:
            sent = self.sock.send(msg[totalsent:])
            if sent == 0:
                raise RuntimeError("socket connection broken")
            totalsent = totalsent + sent

    def myreceive(self):
        chunks = []
        bytes_recd = 0
        while bytes_recd < MSGLEN:
            chunk = self.sock.recv(min(MSGLEN - bytes_recd, 2048))
            if chunk == b'':
                raise RuntimeError("socket connection broken")
            chunks.append(chunk)
            bytes_recd = bytes_recd + len(chunk)
        return b''.join(chunks)

The sending code here is usable for almost any messaging scheme - in Python you send strings, and you can use len() to determine its length (even if it has embedded \0 characters). It’s mostly the receiving code that gets more complex. (And in C, it’s not much worse, except you can’t use strlen if the message has embedded \0s.)

The easiest enhancement is to make the first character of the message an indicator of message type, and have the type determine the length. Now you have two recvs - the first to get (at least) that first character so you can look up the length, and the second in a loop to get the rest. If you decide to go the delimited route, you’ll be receiving in some arbitrary chunk size, (4096 or 8192 is frequently a good match for network buffer sizes), and scanning what you’ve received for a delimiter.

One complication to be aware of: if your conversational protocol allows multiple messages to be sent back to back (without some kind of reply), and you pass recv an arbitrary chunk size, you may end up reading the start of a following message. You’ll need to put that aside and hold onto it, until it’s needed.

Prefixing the message with its length (say, as 5 numeric characters) gets more complex, because (believe it or not), you may not get all 5 characters in one recv. In playing around, you’ll get away with it; but in high network loads, your code will very quickly break unless you use two recv loops - the first to determine the length, the second to get the data part of the message. Nasty. This is also when you’ll discover that send does not always manage to get rid of everything in one pass. And despite having read this, you will eventually get bit by it!

In the interests of space, building your character, (and preserving my competitive position), these enhancements are left as an exercise for the reader. Lets move on to cleaning up.

Données binaires

It is perfectly possible to send binary data over a socket. The major problem is that not all machines use the same formats for binary data. For example, a Motorola chip will represent a 16 bit integer with the value 1 as the two hex bytes 00 01. Intel and DEC, however, are byte-reversed - that same 1 is 01 00. Socket libraries have calls for converting 16 and 32 bit integers - ntohl, htonl, ntohs, htons where « n » means network and « h » means host, « s » means short and « l » means long. Where network order is host order, these do nothing, but where the machine is byte-reversed, these swap the bytes around appropriately.

In these days of 32 bit machines, the ascii representation of binary data is frequently smaller than the binary representation. That’s because a surprising amount of the time, all those longs have the value 0, or maybe 1. The string « 0 » would be two bytes, while binary is four. Of course, this doesn’t fit well with fixed-length messages. Decisions, decisions.

Déconnexion

Strictly speaking, you’re supposed to use shutdown on a socket before you close it. The shutdown is an advisory to the socket at the other end. Depending on the argument you pass it, it can mean « I’m not going to send anymore, but I’ll still listen », or « I’m not listening, good riddance! ». Most socket libraries, however, are so used to programmers neglecting to use this piece of etiquette that normally a close is the same as shutdown(); close(). So in most situations, an explicit shutdown is not needed.

One way to use shutdown effectively is in an HTTP-like exchange. The client sends a request and then does a shutdown(1). This tells the server « This client is done sending, but can still receive. » The server can detect « EOF » by a receive of 0 bytes. It can assume it has the complete request. The server sends a reply. If the send completes successfully then, indeed, the client was still receiving.

Python takes the automatic shutdown a step further, and says that when a socket is garbage collected, it will automatically do a close if it’s needed. But relying on this is a very bad habit. If your socket just disappears without doing a close, the socket at the other end may hang indefinitely, thinking you’re just being slow. Please close your sockets when you’re done.

When Sockets Die

Probably the worst thing about using blocking sockets is what happens when the other side comes down hard (without doing a close). Your socket is likely to hang. TCP is a reliable protocol, and it will wait a long, long time before giving up on a connection. If you’re using threads, the entire thread is essentially dead. There’s not much you can do about it. As long as you aren’t doing something dumb, like holding a lock while doing a blocking read, the thread isn’t really consuming much in the way of resources. Do not try to kill the thread - part of the reason that threads are more efficient than processes is that they avoid the overhead associated with the automatic recycling of resources. In other words, if you do manage to kill the thread, your whole process is likely to be screwed up.

Non-blocking Sockets

Si vous avez compris ce qui précède, vous savez déjà tout ce que vous devez savoir sur la mécanique de l’utilisation des connecteurs. Vous utiliserez toujours les mêmes appels, de la même façon. C’est juste que, si vous le faites bien, votre application sera presque dans la poche.

En Python, vous utilisez socket.setblocking(0) pour le rendre non-bloquant. En C, c’est plus complexe (pour commencer, vous devez choisir entre la version BSD O_NONBLOCK et la version Posix presque impossible à distinguer O_NDELAY, qui est complètement différente de TCP_NODELAY), mais c’est exactement la même idée. Vous le faites après avoir créé le connecteur mais avant de l’utiliser (en fait, si vous êtes fou, vous pouvez alterner).

The major mechanical difference is that send, recv, connect and accept can return without having done anything. You have (of course) a number of choices. You can check return code and error codes and generally drive yourself crazy. If you don’t believe me, try it sometime. Your app will grow large, buggy and suck CPU. So let’s skip the brain-dead solutions and do it right.

Utiliser select.

En C, implémenter select est assez complexe. En Python, c’est du gâteau, mais c’est assez proche de la version C ; aussi, si vous comprenez select en Python, vous aurez peu de problèmes avec lui en C :

ready_to_read, ready_to_write, in_error = \
               select.select(
                  potential_readers,
                  potential_writers,
                  potential_errs,
                  timeout)

You pass select three lists: the first contains all sockets that you might want to try reading; the second all the sockets you might want to try writing to, and the last (normally left empty) those that you want to check for errors. You should note that a socket can go into more than one list. The select call is blocking, but you can give it a timeout. This is generally a sensible thing to do - give it a nice long timeout (say a minute) unless you have good reason to do otherwise.

In return, you will get three lists. They contain the sockets that are actually readable, writable and in error. Each of these lists is a subset (possibly empty) of the corresponding list you passed in.

Si un connecteur se trouve dans la liste des sorties que vous pouvez lire, vous pouvez être pratiquement certain qu’un recv sur ce connecteur retournera quelque chose. Même chose pour la liste des sorties sur lesquelles vous pouvez écrire. Vous pourrez envoyer quelque chose. Peut-être pas tout ce que vous voudrez, mais quelque chose est mieux que rien. (En fait, n’importe quel connecteur raisonnablement sain retournera en écriture — cela signifie simplement que l’espace tampon réseau sortant est disponible).

Si vous avez un connecteur « serveur », mettez-le dans la liste des lecteurs potentiels. Si il apparaît dans la liste des sorties que vous pouvez lire, votre accept fonctionnera (presque certainement). Si vous avez créé un nouveau connecteur pour connect à quelqu’un d’autre, mettez-le dans la liste des éditeurs potentiels. Si il apparaît dans la liste des sorties sur lesquelles vous pouvez écrire, vous avez une bonne chance qu’il se soit connecté.

En fait, select peut être pratique même avec des connecteurs bloquants. C’est une façon de déterminer si vous allez bloquer — le connecteur redevient lisible lorsqu’il y a quelque chose dans les tampons. Cependant, cela n’aide pas encore à déterminer si l’autre extrémité a terminé, ou si elle est simplement occupée par autre chose.

Alerte de portabilité : Sous Unix, select fonctionne aussi bien avec les connecteurs qu’avec les fichiers. N’essayez pas cela sous Windows. Sous Windows, select ne fonctionne qu’avec les connecteurs. Notez également qu’en C, la plupart des options de connecteurs les plus avancées se font différemment sous Windows. En fait, sous Windows, j’utilise habituellement des fils d’exécution (qui fonctionnent très, très bien) avec mes connecteurs.

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Guide pour le tri

Auteur

Andrew Dalke et Raymond Hettinger

Version

0.1

Les listes Python ont une méthode native list.sort() qui modifie les listes elles-mêmes. Il y a également une fonction native sorted() qui construit une nouvelle liste triée depuis un itérable.

Dans ce document, nous explorons différentes techniques pour trier les données en Python.

Les bases du tri

Un tri ascendant simple est très facile : il suffit d’appeler la fonction sorted(). Elle renvoie une nouvelle liste triée :

>>> sorted([5, 2, 3, 1, 4])
[1, 2, 3, 4, 5]

Vous pouvez aussi utiliser la méthode list.sort(). Elle modifie la liste elle-même (et renvoie None pour éviter les confusions). Habituellement, cette méthode est moins pratique que la fonction sorted() – mais si vous n’avez pas besoin de la liste originale, cette technique est légèrement plus efficace.

>>> a = [5, 2, 3, 1, 4]
>>> a.sort()
>>> a
[1, 2, 3, 4, 5]

Une autre différence est que la méthode list.sort() est seulement définie pour les listes. Au contraire, la fonction sorted() accepte n’importe quel itérable.

>>> sorted({1: 'D', 2: 'B', 3: 'B', 4: 'E', 5: 'A'})
[1, 2, 3, 4, 5]

Fonctions clef

list.sort() et sorted() ont un paramètre nommé key afin de spécifier une fonction qui peut être appelée sur chaque élément de la liste afin d’effectuer des comparaisons.

Par exemple, voici une comparaison de texte insensible à la casse:

>>> sorted("This is a test string from Andrew".split(), key=str.lower)
['a', 'Andrew', 'from', 'is', 'string', 'test', 'This']

La valeur du paramètre key devrait être une fonction qui prend un seul argument et renvoie une clef à utiliser à des fins de tri. Cette technique est rapide car la fonction clef est appelée exactement une seule fois pour chaque enregistrement en entrée.

Un usage fréquent est de faire un tri sur des objets complexes en utilisant les indices des objets en tant que clef. Par exemple :

>>> student_tuples = [
...     ('john', 'A', 15),
...     ('jane', 'B', 12),
...     ('dave', 'B', 10),
... ]
>>> sorted(student_tuples, key=lambda student: student[2])   # sort by age
[('dave', 'B', 10), ('jane', 'B', 12), ('john', 'A', 15)]

La même technique marche pour des objets avec des attributs nommés. Par exemple :

>>> class Student:
...     def __init__(self, name, grade, age):
...         self.name = name
...         self.grade = grade
...         self.age = age
...     def __repr__(self):
...         return repr((self.name, self.grade, self.age))

>>> student_objects = [
...     Student('john', 'A', 15),
...     Student('jane', 'B', 12),
...     Student('dave', 'B', 10),
... ]
>>> sorted(student_objects, key=lambda student: student.age)   # sort by age
[('dave', 'B', 10), ('jane', 'B', 12), ('john', 'A', 15)]

Fonctions du module operator

Les fonctions clef utilisées ci-dessus sont courantes, donc Python fournit des fonctions permettant de rendre plus simple et plus rapide l’usage des fonctions d’accesseur. Le module operator contient les fonctions itemgetter(), attrgetter(), et methodcaller().

En utilisant ces fonctions, les exemples au dessus deviennent plus simples et plus rapides :

>>> from operator import itemgetter, attrgetter

>>> sorted(student_tuples, key=itemgetter(2))
[('dave', 'B', 10), ('jane', 'B', 12), ('john', 'A', 15)]

>>> sorted(student_objects, key=attrgetter('age'))
[('dave', 'B', 10), ('jane', 'B', 12), ('john', 'A', 15)]

Les fonctions du module operator permettent plusieurs niveaux de tri. Par exemple, pour trier par grade puis par age :

>>> sorted(student_tuples, key=itemgetter(1,2))
[('john', 'A', 15), ('dave', 'B', 10), ('jane', 'B', 12)]

>>> sorted(student_objects, key=attrgetter('grade', 'age'))
[('john', 'A', 15), ('dave', 'B', 10), ('jane', 'B', 12)]

Ascendant et descendant

list.sort() et sorted() acceptent un paramètre nommé reverse avec une valeur booléenne. C’est utilisé pour déterminer l’ordre descendant des tris. Par exemple, pour avoir les données des étudiants dans l’ordre inverse par age :

>>> sorted(student_tuples, key=itemgetter(2), reverse=True)
[('john', 'A', 15), ('jane', 'B', 12), ('dave', 'B', 10)]

>>> sorted(student_objects, key=attrgetter('age'), reverse=True)
[('john', 'A', 15), ('jane', 'B', 12), ('dave', 'B', 10)]

Stabilité des tris et tris complexes

Les tris sont garantis stables [https://fr.wikipedia.org/wiki/Algorithme_de_tri#Caract.C3.A8re_stable]. Cela signifie que lorsque plusieurs enregistrements on la même clef, leur ordre original est préservé.

>>> data = [('red', 1), ('blue', 1), ('red', 2), ('blue', 2)]
>>> sorted(data, key=itemgetter(0))
[('blue', 1), ('blue', 2), ('red', 1), ('red', 2)]

Notez comme les deux enregistrements pour blue gardent leur ordre original et que par conséquent il est garanti que ('blue', 1) précède ('blue', 2).

Cette propriété fantastique vous permet de construire des tris complexes dans des tris en plusieurs étapes. Par exemple, afin de sortir les données des étudiants en ordre descendant par grade puis en ordre ascendant par age, effectuez un tri par age en premier puis un second tri par grade :

>>> s = sorted(student_objects, key=attrgetter('age'))     # sort on secondary key
>>> sorted(s, key=attrgetter('grade'), reverse=True)       # now sort on primary key, descending
[('dave', 'B', 10), ('jane', 'B', 12), ('john', 'A', 15)]

L’algorithme Timsort [https://fr.wikipedia.org/wiki/Timsort] utilisé dans Python effectue de multiples tris efficacement parce qu’il peut tirer avantage de n’importe quel ordre de existant dans un jeu de données.

La méthode traditionnelle utilisant Decorate-Sort-Undecorate

Cette technique est appelée Decorate-Sort-Undecorate et se base sur trois étapes :

Premièrement, la liste de départ est décorée avec les nouvelles valeurs qui contrôlent l’ordre du tri.

En second lieu, la liste décorée est triée.

Enfin, la décoration est supprimée, créant ainsi une liste qui contient seulement la valeur initiale dans le nouvel ordre.

Par exemple, pour trier les données étudiant par grade en utilisant l’approche DSU :

>>> decorated = [(student.grade, i, student) for i, student in enumerate(student_objects)]
>>> decorated.sort()
>>> [student for grade, i, student in decorated]               # undecorate
[('john', 'A', 15), ('jane', 'B', 12), ('dave', 'B', 10)]

Cette technique marche parce que les tuples sont comparés par ordre lexicographique; les premiers objets sont comparés; si il y a des objets identiques, alors l’objet suivant est comparé, et ainsi de suite.

Il n’est pas strictement nécessaire dans tous les cas d’inclure l’indice i dans la liste décorée, mais l’inclure donne deux avantages :

Le tri est stable – si deux objets on la même clef, leur ordre sera préservé dans la liste triée.

Les objets d’origine ne sont pas nécessairement comparables car l’ordre des tuples décorés sera déterminé par au plus les deux premiers objets. Donc par exemple la liste originale pourrait contenir des nombres complexes qui pourraient ne pas être triés directement.

Un autre nom pour cette technique est Schwartzian transform [https://en.wikipedia.org/wiki/Schwartzian_transform], après que Randal L. Schwartz l’ait popularisé chez les développeurs Perl.

Maintenant que le tri Python fournit des fonctions-clef, cette technique n’est plus souvent utilisée.

La méthode traditionnelle d’utiliser le paramètre cmp

Plusieurs construction données dans ce guide se basent sur Python 2.4 ou plus. Avant cela, il n’y avait pas la fonction sorted() et la méthode list.sort() ne prenait pas d’arguments nommés. À la place, toutes les versions Python 2.x utilisaient un paramètre cmp pour prendre en charge les fonctions de comparaisons définies par les utilisateurs.

En Py3.0, le paramètre cmp à été supprimé complètement (dans le cadre d’un effort plus général pour simplifier et unifier le langage, en éliminant le conflit entre les comparaisons riches et la méthode magique __cmp__()).

En Python 2.x, le tri permettait en paramètre une fonction optionnelle qui peut être appelée pour faire des comparaisons. Cette fonction devrait prendre deux arguments à comparer pour renvoyer une valeur négative pour inférieur-à, renvoyer zéro si ils sont égaux, ou renvoyer une valeur positive pour supérieur-à. Par exemple, nous pouvons faire :

>>> def numeric_compare(x, y):
...     return x - y
>>> sorted([5, 2, 4, 1, 3], cmp=numeric_compare)
[1, 2, 3, 4, 5]

Ou nous pouvons inverser l’ordre de comparaison avec :

>>> def reverse_numeric(x, y):
...     return y - x
>>> sorted([5, 2, 4, 1, 3], cmp=reverse_numeric)
[5, 4, 3, 2, 1]

En portant du code depuis Python 2.X vers 3.x, des problèmes peuvent survenir quand des utilisateurs fournissent une fonction de comparaison et qu’il faut convertir cette fonction en une fonction-clef. La fonction d’encapsulation suivante rend cela plus facile à faire :

def cmp_to_key(mycmp):
    'Convert a cmp= function into a key= function'
    class K:
        def __init__(self, obj, *args):
            self.obj = obj
        def __lt__(self, other):
            return mycmp(self.obj, other.obj) < 0
        def __gt__(self, other):
            return mycmp(self.obj, other.obj) > 0
        def __eq__(self, other):
            return mycmp(self.obj, other.obj) == 0
        def __le__(self, other):
            return mycmp(self.obj, other.obj) <= 0
        def __ge__(self, other):
            return mycmp(self.obj, other.obj) >= 0
        def __ne__(self, other):
            return mycmp(self.obj, other.obj) != 0
    return K

Pour convertir une fonction clef, ils suffit d’encapsuler l’ancienne fonction de comparaison :

>>> sorted([5, 2, 4, 1, 3], key=cmp_to_key(reverse_numeric))
[5, 4, 3, 2, 1]

En Python 3.2, la fonction functools.cmp_to_key() à été ajoutée au module functools dans la librairie standard.

Curiosités et conclusion

Pour du tri de texte localisé, utilisez locale.strxfrm() en tant que fonction clef ou locale.strcoll() comme fonction de comparaison.

Le paramètre reverse maintient toujours un tri stable (de telle sorte que les enregistrements avec des clef égales gardent le même ordre). Notez que cet effet peut être simulé sans le paramètre en utilisant la fonction native reversed() deux fois :

>>> data = [('red', 1), ('blue', 1), ('red', 2), ('blue', 2)]
>>> standard_way = sorted(data, key=itemgetter(0), reverse=True)
>>> double_reversed = list(reversed(sorted(reversed(data), key=itemgetter(0))))
>>> assert standard_way == double_reversed
>>> standard_way
[('red', 1), ('red', 2), ('blue', 1), ('blue', 2)]

Il est garanti que les routines de tri utilisent les méthodes __lt__() lorsqu’elles effectuent des comparaisons entre deux objets. Donc il est facile d’ajouter un ordre de tri standard à une classe en définissant sa méthode __lt__() :

>>> Student.__lt__ = lambda self, other: self.age < other.age
>>> sorted(student_objects)
[('dave', 'B', 10), ('jane', 'B', 12), ('john', 'A', 15)]

Les fonctions clef n’ont pas besoin de dépendre directement des objets triés. Une fonction clef peut aussi accéder à des ressources externes. En l’occurrence, si les grades des étudiants sont stockés dans un dictionnaire, ils peuvent être utilisés pour trier une liste différentes de noms d’étudiants :

>>> students = ['dave', 'john', 'jane']
>>> newgrades = {'john': 'F', 'jane':'A', 'dave': 'C'}
>>> sorted(students, key=newgrades.__getitem__)
['jane', 'dave', 'john']

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Guide Unicode

Version

1.12

This HOWTO discusses Python support for Unicode, and explains various problems that people commonly encounter when trying to work with Unicode.

Introduction à Unicode

Histoire des codes de caractères

En 1968, l”American Standard Code for Information Interchange, mieux connu sous son acronyme ASCII, a été normalisé. L’ASCII définissait des codes numériques pour différents caractères, les valeurs numériques s’étendant de 0 à 127. Par exemple, la lettre minuscule « a » est assignée à 97 comme valeur de code.

ASCII était une norme développée par les États-Unis, elle ne définissait donc que des caractères non accentués. Il y avait « e », mais pas « é » ou « Í ». Cela signifiait que les langues qui nécessitaient des caractères accentués ne pouvaient pas être fidèlement représentées en ASCII. (En fait, les accents manquants importaient pour l’anglais aussi, qui contient des mots tels que « naïve » et « café », et certaines publications ont des styles propres qui exigent des orthographes tels que « coöperate ».)

Pendant un certain temps, les gens ont juste écrit des programmes qui n’affichaient pas d’accents. Au milieu des années 1980, un programme Apple II BASIC écrit par un français pouvait avoir des lignes comme celles-ci :

PRINT "MISE A JOUR TERMINEE"
PRINT "PARAMETRES ENREGISTRES"

Ces messages devraient contenir des accents (terminée, paramètre, enregistrés) et ils ont juste l’air anormaux à quelqu’un lisant le français.

Dans les années 1980, presque tous les ordinateurs personnels étaient à 8 bits, ce qui signifie que les octets pouvaient contenir des valeurs allant de 0 à 255. Les codes ASCII allaient seulement jusqu’à 127, alors certaines machines ont assigné les valeurs entre 128 et 255 à des caractères accentués. Différentes machines avaient des codes différents, cependant, ce qui a conduit à des problèmes d’échange de fichiers. Finalement, divers ensembles de valeurs couramment utilisés pour la gamme 128–255 ont émergé. Certains étaient de véritables normes, définies par l’Organisation internationale de normalisation, et certaines étaient des conventions de facto qui ont été inventées par une entreprise ou une autre et qui ont fini par se répandre.

255 caractères, ça n’est pas beaucoup. Par exemple, vous ne pouvez pas contenir à la fois les caractères accentués utilisés en Europe occidentale et l’alphabet cyrillique utilisé pour le russe dans la gamme 128–255, car il y a plus de 128 de tous ces caractères.

Vous pouviez écrire les fichiers avec des codes différents (tous vos fichiers russes dans un système de codage appelé KOI8, tous vos fichiers français dans un système de codage différent appelé Latin1), mais que faire si vous souhaitiez écrire un document français citant du texte russe ? Dans les années 80, les gens ont commencé à vouloir résoudre ce problème, et les efforts de standardisation Unicode ont commencé.

Unicode a commencé par utiliser des caractères 16 bits au lieu de 8 bits. 16 bits signifie que vous avez 2^16 = 65 536 valeurs distinctes disponibles, ce qui permet de représenter de nombreux caractères différents à partir de nombreux alphabets différents. Un des objectifs initiaux était de faire en sorte que Unicode contienne les alphabets de chaque langue humaine. Il s’avère que même 16 bits ne suffisent pas pour atteindre cet objectif, et la spécification Unicode moderne utilise une gamme de codes plus étendue, allant de 0 à 1 114 111 (0x10FFFF en base 16).

Il existe une norme ISO connexe, ISO 10646. Unicode et ISO 10646 étaient à l’origine des efforts séparés, mais les spécifications ont été fusionnées avec la révision 1.1 d’Unicode.

(Cette discussion sur l’historique d’Unicode est extrêmement simplifiée. Les détails historiques précis ne sont pas nécessaires pour comprendre comment utiliser efficacement Unicode, mais si vous êtes curieux, consultez le site du consortium Unicode indiqué dans les références ou la page Wikipédia pour Unicode [https://en.wikipedia.org/wiki/Unicode#History] (page en anglais) pour plus d’informations.)

Définitions

A character is the smallest possible component of a text. “A”, “B”, “C”, etc., are all different characters. So are “È” and “Í”. Characters are abstractions, and vary depending on the language or context you’re talking about. For example, the symbol for ohms (Ω) is usually drawn much like the capital letter omega (Ω) in the Greek alphabet (they may even be the same in some fonts), but these are two different characters that have different meanings.

The Unicode standard describes how characters are represented by code points. A code point is an integer value, usually denoted in base 16. In the standard, a code point is written using the notation U+12CA to mean the character with value 0x12ca (4,810 decimal). The Unicode standard contains a lot of tables listing characters and their corresponding code points:

0061    'a'; LATIN SMALL LETTER A
0062    'b'; LATIN SMALL LETTER B
0063    'c'; LATIN SMALL LETTER C
...
007B    '{'; LEFT CURLY BRACKET

Strictly, these definitions imply that it’s meaningless to say “this is character U+12CA”. U+12CA is a code point, which represents some particular character; in this case, it represents the character “ETHIOPIC SYLLABLE WI”. In informal contexts, this distinction between code points and characters will sometimes be forgotten.

Un caractère est représenté sur un écran ou sur papier par un ensemble d’éléments graphiques appelé glyphe. Le glyphe d’un A majuscule, par exemple, est deux traits diagonaux et un trait horizontal, bien que les détails exacts dépendent de la police utilisée. La plupart du code Python n’a pas besoin de s’inquiéter des glyphes ; trouver le bon glyphe à afficher est généralement le travail d’une boîte à outils GUI ou du moteur de rendu des polices d’un terminal.

Encodages

To summarize the previous section: a Unicode string is a sequence of code points, which are numbers from 0 through 0x10FFFF (1,114,111 decimal). This sequence needs to be represented as a set of bytes (meaning, values from 0 through 255) in memory. The rules for translating a Unicode string into a sequence of bytes are called an encoding.

The first encoding you might think of is an array of 32-bit integers. In this representation, the string « Python » would look like this:

   P           y           t           h           o           n
0x50 00 00 00 79 00 00 00 74 00 00 00 68 00 00 00 6f 00 00 00 6e 00 00 00
   0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Cette représentation est simple mais son utilisation pose un certain nombre de problèmes.

Elle n’est pas portable ; des processeurs différents ordonnent les octets différemment.

Elle gâche beaucoup d’espace. Dans la plupart des textes, la majorité des points de code sont inférieurs à 127, ou à 255, donc beaucoup d’espace est occupé par des octets 0x00. La chaîne ci-dessus occupe 24 octets, à comparer aux 6 octets nécessaires pour une représentation en ASCII. L’utilisation supplémentaire de RAM n’a pas trop d’importance (les ordinateurs de bureau ont des gigaoctets de RAM et les chaînes ne sont généralement pas si grandes que ça), mais l’accroissement de notre utilisation du disque et de la bande passante réseau par un facteur de 4 est intolérable.

Elle n’est pas compatible avec les fonctions C existantes telles que strlen(), il faudrait donc utiliser une nouvelle famille de fonctions, celle des chaînes larges (wide strings).

De nombreuses normes Internet sont définies en termes de données textuelles et ne peuvent pas gérer le contenu incorporant des octets zéro.

Généralement, les gens n’utilisent pas cet encodage, mais optent pour d’autres encodages plus efficaces et pratiques. UTF-8 est probablement l’encodage le plus couramment pris en charge ; celui-ci sera abordé ci-dessous.

Les encodages n’ont pas à gérer tous les caractères Unicode possibles, et les plupart ne le font pas. Les règles pour convertir une chaîne Unicode en codage ASCII, par exemple, sont simples. pour chaque point de code :

Si le point de code est < 128, chaque octet est identique à la valeur du point de code.

Si le point de code est égal à 128 ou plus, la chaîne Unicode ne peut pas être représentée dans ce codage (Python déclenche une exception UnicodeEncodeError dans ce cas).

Latin-1, également connu sous le nom de ISO-8859-1, est un encodage similaire. Les points de code Unicode 0–255 étant identiques aux valeurs de Latin-1, la conversion en cet encodage nécessite simplement la conversion des points de code en octets de même valeur ; si un point de code supérieur à 255 est rencontré, la chaîne ne peut pas être codée en latin-1.

Les encodages ne doivent pas nécessairement être de simples mappages un à un, comme Latin-1. Prenons l’exemple du code EBCDIC d’IBM, utilisé sur les ordinateurs centraux IBM. Les valeurs de lettre ne faisaient pas partie d’un bloc: les lettres « a » à « i » étaient comprises entre 129 et 137, mais les lettres « j » à « r » étaient comprises entre 145 et 153. Si vous vouliez utiliser EBCDIC comme encodage, vous auriez probablement utilisé une sorte de table de correspondance pour effectuer la conversion, mais il s’agit en surtout d’un détail d’implémentation.

UTF-8 is one of the most commonly used encodings. UTF stands for « Unicode Transformation Format », and the “8” means that 8-bit numbers are used in the encoding. (There are also a UTF-16 and UTF-32 encodings, but they are less frequently used than UTF-8.) UTF-8 uses the following rules:

Si le point de code est < 128, il est représenté par la valeur de l’octet correspondant.

Si le point de code est ≥ 128, il est transformé en une séquence de deux, trois ou quatre octets, où chaque octet de la séquence est compris entre 128 et 255.

UTF-8 a plusieurs propriétés intéressantes :

Il peut gérer n’importe quel point de code Unicode.

A Unicode string is turned into a sequence of bytes containing no embedded zero bytes. This avoids byte-ordering issues, and means UTF-8 strings can be processed by C functions such as strcpy() and sent through protocols that can’t handle zero bytes.

Une chaîne de texte ASCII est également un texte UTF-8 valide.

UTF-8 est assez compact. La majorité des caractères couramment utilisés peuvent être représentés avec un ou deux octets.

Si des octets sont corrompus ou perdus, il est possible de déterminer le début du prochain point de code encodé en UTF-8 et de se resynchroniser. Il est également improbable que des données 8-bits aléatoires ressemblent à du UTF-8 valide.

Références

Le site du Consortium Unicode [http://www.unicode.org], en anglais, a des diagrammes de caractères, un glossaire et des versions PDF de la spécification Unicode. Préparez-vous à une lecture difficile. Une chronologie [http://www.unicode.org/history/] de l’origine et du développement de l’Unicode est également disponible sur le site.

To help understand the standard, Jukka Korpela has written an introductory guide [https://www.cs.tut.fi/~jkorpela/unicode/guide.html] to reading the Unicode character tables.

Another good introductory article [http://www.joelonsoftware.com/articles/Unicode.html] was written by Joel Spolsky. If this introduction didn’t make things clear to you, you should try reading this alternate article before continuing.

Les pages Wikipédia sont souvent utiles ; voir les pages pour « Codage des caractères [https://fr.wikipedia.org/wiki/Codage_des_caract%C3%A8res] » et UTF-8 [https://fr.wikipedia.org/wiki/UTF-8], par exemple.

Prise en charge Unicode de Python

Maintenant que vous avez appris les rudiments de l’Unicode, nous pouvons regarder les fonctionnalités Unicode de Python.

Le type String

Since Python 3.0, the language features a str type that contain Unicode characters, meaning any string created using "unicode rocks!", 'unicode rocks!', or the triple-quoted string syntax is stored as Unicode.

L’encodage par défaut pour le code source Python est UTF-8, il est donc facile d’inclure des caractères Unicode dans une chaîne littérale :

try:
    with open('/tmp/input.txt', 'r') as f:
        ...
except OSError:
    # 'File not found' error message.
    print("Fichier non trouvé")

You can use a different encoding from UTF-8 by putting a specially-formatted comment as the first or second line of the source code:

# -*- coding: <encoding name> -*-

Note : Python 3 sait gérer les caractères Unicode dans les identifiants :

répertoire = "/tmp/records.log"
with open(répertoire, "w") as f:
    f.write("test\n")

Si vous ne pouvez pas entrer un caractère particulier dans votre éditeur ou si vous voulez garder le code source uniquement en ASCII pour une raison quelconque, vous pouvez également utiliser des séquences d’échappement dans les littéraux de chaîne (en fonction de votre système, il se peut que vous voyiez le glyphe réel du delta majuscule au lieu d’une séquence d’échappement \u...)

>>> "\N{GREEK CAPITAL LETTER DELTA}"  # Using the character name
'\u0394'
>>> "\u0394"                          # Using a 16-bit hex value
'\u0394'
>>> "\U00000394"                      # Using a 32-bit hex value
'\u0394'

De plus, une chaîne de caractères peut être créée en utilisant la méthode decode() de la classe bytes. Cette méthode prend un argument encoding, UTF-8 par exemple, et optionnellement un argument errors.

L’argument errors détermine la réponse lorsque la chaîne en entrée ne peut pas être convertie selon les règles de l’encodage. Les valeurs autorisées pour cet argument sont 'strict' (« strict » : lève une exception UnicodeDecodeError), 'replace' (« remplacer » : utilise U+FFFD, REPLACEMENT CARACTER), 'ignore' (« ignorer » : n’inclut pas le caractère dans le résultat Unicode) ou 'backslashreplace' (« remplacer avec antislash » : insère une séquence d’échappement \xNN). Les exemples suivants illustrent les différences :

>>> b'\x80abc'.decode("utf-8", "strict")
Traceback (most recent call last):
    ...
UnicodeDecodeError: 'utf-8' codec can't decode byte 0x80 in position 0:
  invalid start byte
>>> b'\x80abc'.decode("utf-8", "replace")
'\ufffdabc'
>>> b'\x80abc'.decode("utf-8", "backslashreplace")
'\\x80abc'
>>> b'\x80abc'.decode("utf-8", "ignore")
'abc'

Encodings are specified as strings containing the encoding’s name. Python 3.2 comes with roughly 100 different encodings; see the Python Library Reference at Standard Encodings for a list. Some encodings have multiple names; for example, 'latin-1', 'iso_8859_1' and '8859” are all synonyms for the same encoding.

Des chaînes Unicode à un caractère peuvent également être créées avec la fonction native chr(), qui prend des entiers et renvoie une chaîne Unicode de longueur 1 qui contient le point de code correspondant. L’opération inverse est la fonction native ord() qui prend une chaîne Unicode d’un caractère et renvoie la valeur du point de code :

>>> chr(57344)
'\ue000'
>>> ord('\ue000')
57344

Conversion en octets

La méthode inverse de bytes.decode() est str.encode(), qui renvoie une représentation bytes de la chaîne Unicode, codée dans l’encodage encoding demandé.

Le paramètre errors est le même que le paramètre de la méthode decode() mais possède quelques gestionnaires supplémentaires. En plus de 'strict', 'ignore' et 'remplace' (qui dans ce cas insère un point d’interrogation au lieu du caractère non codable), il y a aussi 'xmlcharrefreplace' (insère une référence XML), backslashreplace (insère une séquence \uNNNN) et namereplace (insère une séquence \N{...}).

L’exemple suivant montre les différents résultats :

>>> u = chr(40960) + 'abcd' + chr(1972)
>>> u.encode('utf-8')
b'\xea\x80\x80abcd\xde\xb4'
>>> u.encode('ascii')
Traceback (most recent call last):
    ...
UnicodeEncodeError: 'ascii' codec can't encode character '\ua000' in
  position 0: ordinal not in range(128)
>>> u.encode('ascii', 'ignore')
b'abcd'
>>> u.encode('ascii', 'replace')
b'?abcd?'
>>> u.encode('ascii', 'xmlcharrefreplace')
b'&#40960;abcd&#1972;'
>>> u.encode('ascii', 'backslashreplace')
b'\\ua000abcd\\u07b4'
>>> u.encode('ascii', 'namereplace')
b'\\N{YI SYLLABLE IT}abcd\\u07b4'

Les routines de bas niveau pour enregistrer et accéder aux encodages disponibles se trouvent dans le module codecs. L’implémentation de nouveaux encodages nécessite également de comprendre le module codecs. Cependant, les fonctions d’encodage et de décodage renvoyées par ce module sont généralement de bas-niveau pour être facilement utilisées et l’écriture de nouveaux encodages est une tâche très spécialisée, donc le module ne sera pas couvert dans ce guide.

Littéraux Unicode dans le code source Python

Dans le code source Python, des points de code Unicode spécifiques peuvent être écrits en utilisant la séquence d’échappement \u, suivie de quatre chiffres hexadécimaux donnant le point de code. La séquence d’échappement \U est similaire, mais attend huit chiffres hexadécimaux, pas quatre :

>>> s = "a\xac\u1234\u20ac\U00008000"
... #     ^^^^ two-digit hex escape
... #         ^^^^^^ four-digit Unicode escape
... #                     ^^^^^^^^^^ eight-digit Unicode escape
>>> [ord(c) for c in s]
[97, 172, 4660, 8364, 32768]

L’utilisation de séquences d’échappement pour des points de code supérieurs à 127 est acceptable à faible dose, mais devient gênante si vous utilisez beaucoup de caractères accentués, comme c’est le cas dans un programme avec des messages en français ou dans une autre langue utilisant des lettres accentuées. Vous pouvez également assembler des chaînes de caractères à l’aide de la fonction native chr(), mais c’est encore plus fastidieux.

Idéalement, vous devriez être capable d’écrire des littéraux dans l’encodage naturel de votre langue. Vous pourriez alors éditer le code source de Python avec votre éditeur favori qui affiche les caractères accentués naturellement, et a les bons caractères utilisés au moment de l’exécution.

Python considère que le code source est écrit en UTF-8 par défaut, mais vous pouvez utiliser presque n’importe quel encodage si vous déclarez l’encodage utilisé. Cela se fait en incluant un commentaire spécial sur la première ou la deuxième ligne du fichier source :

#!/usr/bin/env python
# -*- coding: latin-1 -*-

u = 'abcdé'
print(ord(u[-1]))

La syntaxe s’inspire de la notation d”Emacs pour spécifier les variables locales à un fichier. Emacs supporte de nombreuses variables différentes, mais Python ne gère que coding. Les symboles -*- indiquent à Emacs que le commentaire est spécial ; ils n’ont aucune signification pour Python mais sont une convention. Python cherche coding: name ou coding=name dans le commentaire.

Si vous n’incluez pas un tel commentaire, l’encodage par défaut est UTF-8 comme déjà mentionné. Voir aussi la PEP 263 [https://www.python.org/dev/peps/pep-0263] pour plus d’informations.

Propriétés Unicode

The Unicode specification includes a database of information about code points. For each defined code point, the information includes the character’s name, its category, the numeric value if applicable (Unicode has characters representing the Roman numerals and fractions such as one-third and four-fifths). There are also properties related to the code point’s use in bidirectional text and other display-related properties.

Le programme suivant affiche des informations sur plusieurs caractères et affiche la valeur numérique d’un caractère particulier :

import unicodedata

u = chr(233) + chr(0x0bf2) + chr(3972) + chr(6000) + chr(13231)

for i, c in enumerate(u):
    print(i, '%04x' % ord(c), unicodedata.category(c), end=" ")
    print(unicodedata.name(c))

# Get numeric value of second character
print(unicodedata.numeric(u[1]))

Si vous l’exécutez, cela affiche :

0 00e9 Ll LATIN SMALL LETTER E WITH ACUTE
1 0bf2 No TAMIL NUMBER ONE THOUSAND
2 0f84 Mn TIBETAN MARK HALANTA
3 1770 Lo TAGBANWA LETTER SA
4 33af So SQUARE RAD OVER S SQUARED
1000.0

Les codes de catégorie sont des abréviations décrivant la nature du caractère. Celles-ci sont regroupées en catégories telles que « Lettre », « Nombre », « Ponctuation » ou « Symbole », qui sont à leur tour divisées en sous-catégories. Pour prendre par exemple les codes de la sortie ci-dessus, 'Ll' signifie « Lettre, minuscules », 'No' signifie « Nombre, autre », 'Mn' est « Marque, non-espaçant », et 'So' est « Symbole, autre ». Voir la section Valeurs générales des catégories de la documentation de la base de données de caractères Unicode [http://www.unicode.org/reports/tr44/#General_Category_Values] (ressource en anglais) pour une liste de codes de catégories.

Expressions régulières Unicode

Les expressions régulières gérées par le module re peuvent être fournies sous forme de chaîne d’octets ou de texte. Certaines séquences de caractères spéciaux telles que \d et \w ont des significations différentes selon que le motif est fourni en octets ou en texte. Par exemple, \d correspond aux caractères [0-9] en octets mais dans les chaînes de caractères correspond à tout caractère de la catégorie 'Nd'.

Dans cet exemple, la chaîne contient le nombre 57 écrit en chiffres arabes et thaïlandais :

import re
p = re.compile(r'\d+')

s = "Over \u0e55\u0e57 57 flavours"
m = p.search(s)
print(repr(m.group()))

Une fois exécuté, \d+ correspond aux chiffres thaïlandais et les affiche. Si vous fournissez le drapeau re.ASCII à compile(), \d+ correspond cette fois à la chaîne « 57 ».

De même, \w correspond à une grande variété de caractères Unicode mais seulement [a-zA-Z0-9_] en octets (ou si re.ASCII est fourni) et \s correspond soit aux caractères blancs Unicode soit aux caractères [ \t\n\r\f\v].

Références

Quelques bonnes discussions alternatives sur la gestion d’Unicode par Python sont :

Processing Text Files in Python 3 [http://python-notes.curiousefficiency.org/en/latest/python3/text_file_processing.html], par Nick Coghlan.

Pragmatic Unicode [http://nedbatchelder.com/text/unipain.html], a PyCon 2012 presentation by Ned Batchelder.

Le type str est décrit dans la référence de la bibliothèque Python à Type Séquence de Texte — str.

La documentation du module unicodedata.

La documentation du module codecs.

Marc-André Lemburg a donné une présentation intitulée « Python et Unicode » (diapositives PDF) [https://downloads.egenix.com/python/Unicode-EPC2002-Talk.pdf] à EuroPython 2002. Les diapositives sont un excellent aperçu de la conception des fonctionnalités Unicode de Python 2 (où le type de chaîne Unicode est appelé unicode et les littéraux commencent par u).

Lecture et écriture de données Unicode

Une fois que vous avez écrit du code qui fonctionne avec des données Unicode, le problème suivant concerne les entrées/sorties. Comment obtenir des chaînes Unicode dans votre programme et comment convertir les chaînes Unicode dans une forme appropriée pour le stockage ou la transmission ?

Il est possible que vous n’ayez rien à faire en fonction de vos sources d’entrée et des destinations de vos données de sortie ; il convient de vérifier si les bibliothèques utilisées dans votre application gèrent l’Unicode nativement. Par exemple, les analyseurs XML renvoient souvent des données Unicode. De nombreuses bases de données relationnelles prennent également en charge les colonnes encodées en Unicode et peuvent renvoyer des valeurs Unicode à partir d’une requête SQL.

Les données Unicode sont généralement converties en un encodage particulier avant d’être écrites sur le disque ou envoyées sur un connecteur réseau. Il est possible de faire tout le travail vous-même : ouvrir un fichier, lire un élément 8-bits, puis convertir les octets avec bytes.decode(encoding). Cependant, l’approche manuelle n’est pas recommandée.

La nature multi-octets des encodages pose problème ; un caractère Unicode peut être représenté par plusieurs octets. Si vous voulez lire le fichier par morceaux de taille arbitraire (disons 1024 ou 4096 octets), vous devez écrire un code de gestion des erreurs pour détecter le cas où une partie seulement des octets codant un seul caractère Unicode est lue à la fin d’un morceau. Une solution serait de lire le fichier entier en mémoire et d’effectuer le décodage, mais cela vous empêche de travailler avec des fichiers extrêmement volumineux ; si vous avez besoin de lire un fichier de 2 Gio, vous avez besoin de 2 Gio de RAM (plus que ça, en fait, puisque pendant un moment, vous aurez besoin d’avoir à la fois la chaîne encodée et sa version Unicode en mémoire).

La solution serait d’utiliser l’interface de décodage de bas-niveau pour intercepter le cas des séquences d’encodage incomplètes. Ce travail d’implémentation a déjà été fait pour vous : la fonction native open() peut renvoyer un objet de type fichier qui suppose que le contenu du fichier est dans un encodage spécifié et accepte les paramètres Unicode pour des méthodes telles que read() et write(). Ceci fonctionne grâce aux paramètres encoding et errors de open() qui sont interprétés comme ceux de str.encode() et bytes.decode().

Lire de l’Unicode à partir d’un fichier est donc simple :

with open('unicode.txt', encoding='utf-8') as f:
    for line in f:
        print(repr(line))

Il est également possible d’ouvrir des fichiers en mode « mise à jour », permettant à la fois la lecture et l’écriture :

with open('test', encoding='utf-8', mode='w+') as f:
    f.write('\u4500 blah blah blah\n')
    f.seek(0)
    print(repr(f.readline()[:1]))

Le caractère Unicode U+FEFFF est utilisé comme marque pour indiquer le boutisme (c’est-à-dire l’ordre dans lequel les octets sont placés pour indiquer une valeur sur plusieurs octets, byte-order mark en anglais ou BOM), et est souvent écrit en tête (premier caractère) d’un fichier afin d’aider à l’auto-détection du boutisme du fichier. Certains encodages, comme UTF-16, s’attendent à ce qu’une BOM soit présente au début d’un fichier ; lorsqu’un tel encodage est utilisé, la BOM sera automatiquement écrite comme premier caractère et sera silencieusement retirée lorsque le fichier sera lu. Il existe des variantes de ces encodages, comme utf-16-le et utf-16-be pour les encodages petit-boutiste et gros-boutiste, qui spécifient un ordre d’octets donné et ne sautent pas la BOM.

In some areas, it is also convention to use a « BOM » at the start of UTF-8 encoded files; the name is misleading since UTF-8 is not byte-order dependent. The mark simply announces that the file is encoded in UTF-8. Use the “utf-8-sig” codec to automatically skip the mark if present for reading such files.

Noms de fichiers Unicode

Most of the operating systems in common use today support filenames that contain arbitrary Unicode characters. Usually this is implemented by converting the Unicode string into some encoding that varies depending on the system. For example, Mac OS X uses UTF-8 while Windows uses a configurable encoding; on Windows, Python uses the name « mbcs » to refer to whatever the currently configured encoding is. On Unix systems, there will only be a filesystem encoding if you’ve set the LANG or LC_CTYPE environment variables; if you haven’t, the default encoding is UTF-8.

La fonction sys.getfilesystemencoding() renvoie l’encodage à utiliser sur votre système actuel, au cas où vous voudriez faire l’encodage manuellement, mais il n’y a pas vraiment de raisons de s’embêter avec ça. Lors de l’ouverture d’un fichier pour la lecture ou l’écriture, vous pouvez généralement simplement fournir la chaîne Unicode comme nom de fichier et elle est automatiquement convertie à l’encodage qui convient :

filename = 'filename\u4500abc'
with open(filename, 'w') as f:
    f.write('blah\n')

Les fonctions du module os telles que os.stat() acceptent également les noms de fichiers Unicode.

The os.listdir() function returns filenames and raises an issue: should it return the Unicode version of filenames, or should it return bytes containing the encoded versions? os.listdir() will do both, depending on whether you provided the directory path as bytes or a Unicode string. If you pass a Unicode string as the path, filenames will be decoded using the filesystem’s encoding and a list of Unicode strings will be returned, while passing a byte path will return the filenames as bytes. For example, assuming the default filesystem encoding is UTF-8, running the following program:

fn = 'filename\u4500abc'
f = open(fn, 'w')
f.close()

import os
print(os.listdir(b'.'))
print(os.listdir('.'))

produit la sortie suivante :

amk:~$ python t.py
[b'filename\xe4\x94\x80abc', ...]
['filename\u4500abc', ...]

La première liste contient les noms de fichiers encodés en UTF-8 et la seconde contient les versions Unicode.

Note that on most occasions, the Unicode APIs should be used. The bytes APIs should only be used on systems where undecodable file names can be present, i.e. Unix systems.

Conseils pour écrire des programmes compatibles Unicode

Cette section fournit quelques suggestions sur l’écriture de logiciels qui traitent de l’Unicode.

Le conseil le plus important est :

Il convient que le logiciel ne traite que des chaînes Unicode en interne, décodant les données d’entrée dès que possible et encodant la sortie uniquement à la fin.

Si vous essayez d’écrire des fonctions de traitement qui acceptent à la fois les chaînes Unicode et les chaînes d’octets, les possibilités d’occurrences de bogues dans votre programme augmentent partout où vous combinez les deux différents types de chaînes. Il n’y a pas d’encodage ou de décodage automatique : si vous faites par exemple str + octets, une TypeError est levée.

Lors de l’utilisation de données provenant d’un navigateur Web ou d’une autre source non fiable, une technique courante consiste à vérifier la présence de caractères illégaux dans une chaîne de caractères avant de l’utiliser pour générer une ligne de commande ou de la stocker dans une base de données. Si vous le faites, vérifiez bien la chaîne décodée, pas les données d’octets codés ; certains encodages peuvent avoir des propriétés intéressantes, comme ne pas être bijectifs ou ne pas être entièrement compatibles avec l’ASCII. C’est particulièrement vrai si l’encodage est spécifié explicitement dans vos données d’entrée, car l’attaquant peut alors choisir un moyen intelligent de cacher du texte malveillant dans le flux de données encodé.

Conversion entre les encodages de fichiers

La classe StreamRecoder peut convertir de manière transparente entre les encodages : prenant un flux qui renvoie des données dans l’encodage #1, elle se comporte comme un flux qui renvoie des données dans l’encodage #2.

Par exemple, si vous avez un fichier d’entrée f qui est en Latin-1, vous pouvez l’encapsuler dans un StreamRecoder pour qu’il renvoie des octets encodés en UTF-8 :

new_f = codecs.StreamRecoder(f,
    # en/decoder: used by read() to encode its results and
    # by write() to decode its input.
    codecs.getencoder('utf-8'), codecs.getdecoder('utf-8'),

    # reader/writer: used to read and write to the stream.
    codecs.getreader('latin-1'), codecs.getwriter('latin-1') )

Fichiers dans un encodage inconnu

Vous avez besoin de modifier un fichier, mais vous ne connaissez pas son encodage ? Si vous savez que l’encodage est compatible ASCII et que vous voulez seulement examiner ou modifier les parties ASCII, vous pouvez ouvrir le fichier avec le gestionnaire d’erreurs surrogateescape :

with open(fname, 'r', encoding="ascii", errors="surrogateescape") as f:
    data = f.read()

# make changes to the string 'data'

with open(fname + '.new', 'w',
          encoding="ascii", errors="surrogateescape") as f:
    f.write(data)

The surrogateescape error handler will decode any non-ASCII bytes as code points in the Unicode Private Use Area ranging from U+DC80 to U+DCFF. These private code points will then be turned back into the same bytes when the surrogateescape error handler is used when encoding the data and writing it back out.

Références

Une partie de la conférence Mastering Python 3 Input/Output [http://pyvideo.org/video/289/pycon-2010--mastering-python-3-i-o] (ressource en anglais), donnée lors de PyCon 2010 de David Beazley, parle du traitement de texte et du traitement des données binaires.

Le PDF du diaporama de la présentation de Marc-André Lemburg « Writing Unicodeaware Applications in Python » [https://downloads.egenix.com/python/LSM2005-Developing-Unicode-aware-applications-in-Python.pdf] (ressource en anglais) traite des questions d’encodage de caractères ainsi que de l’internationalisation et de la localisation d’une application. Ces diapositives ne couvrent que Python 2.x.

The Guts of Unicode in Python [http://pyvideo.org/video/1768/the-guts-of-unicode-in-python] (ressource en anglais) est une conférence PyCon 2013 donnée par Benjamin Peterson qui traite de la représentation interne Unicode en Python 3.3.

Remerciements

La première ébauche de ce document a été rédigée par Andrew Kuchling. Il a depuis été révisé par Alexander Belopolsky, Georg Brandl, Andrew Kuchling et Ezio Melotti.

Thanks to the following people who have noted errors or offered suggestions on this article: Éric Araujo, Nicholas Bastin, Nick Coghlan, Marius Gedminas, Kent Johnson, Ken Krugler, Marc-André Lemburg, Martin von Löwis, Terry J. Reedy, Chad Whitacre.

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HOWTO Fetch Internet Resources Using The urllib Package

Auteur

Michael Foord [http://www.voidspace.org.uk/python/index.shtml]

Note

There is a French translation of an earlier revision of this HOWTO, available at urllib2 - Le Manuel manquant [http://www.voidspace.org.uk/python/articles/urllib2_francais.shtml].

Introduction

Related Articles

You may also find useful the following article on fetching web resources with Python:

Basic Authentication [http://www.voidspace.org.uk/python/articles/authentication.shtml]

A tutorial on Basic Authentication, with examples in Python.

urllib.request is a Python module for fetching URLs (Uniform Resource Locators). It offers a very simple interface, in the form of the urlopen function. This is capable of fetching URLs using a variety of different protocols. It also offers a slightly more complex interface for handling common situations - like basic authentication, cookies, proxies and so on. These are provided by objects called handlers and openers.

urllib.request supports fetching URLs for many « URL schemes » (identified by the string before the ":" in URL - for example "ftp" is the URL scheme of "ftp://python.org/") using their associated network protocols (e.g. FTP, HTTP). This tutorial focuses on the most common case, HTTP.

For straightforward situations urlopen is very easy to use. But as soon as you encounter errors or non-trivial cases when opening HTTP URLs, you will need some understanding of the HyperText Transfer Protocol. The most comprehensive and authoritative reference to HTTP is RFC 2616 [https://tools.ietf.org/html/rfc2616.html]. This is a technical document and not intended to be easy to read. This HOWTO aims to illustrate using urllib, with enough detail about HTTP to help you through. It is not intended to replace the urllib.request docs, but is supplementary to them.

Fetching URLs

The simplest way to use urllib.request is as follows:

import urllib.request
with urllib.request.urlopen('http://python.org/') as response:
   html = response.read()

If you wish to retrieve a resource via URL and store it in a temporary location, you can do so via the shutil.copyfileobj() and tempfile.NamedTemporaryFile() functions:

import shutil
import tempfile
import urllib.request

with urllib.request.urlopen('http://python.org/') as response:
    with tempfile.NamedTemporaryFile(delete=False) as tmp_file:
        shutil.copyfileobj(response, tmp_file)

with open(tmp_file.name) as html:
    pass

Many uses of urllib will be that simple (note that instead of an “http:” URL we could have used a URL starting with “ftp:”, “file:”, etc.). However, it’s the purpose of this tutorial to explain the more complicated cases, concentrating on HTTP.

HTTP is based on requests and responses - the client makes requests and servers send responses. urllib.request mirrors this with a Request object which represents the HTTP request you are making. In its simplest form you create a Request object that specifies the URL you want to fetch. Calling urlopen with this Request object returns a response object for the URL requested. This response is a file-like object, which means you can for example call .read() on the response:

import urllib.request

req = urllib.request.Request('http://www.voidspace.org.uk')
with urllib.request.urlopen(req) as response:
   the_page = response.read()

Note that urllib.request makes use of the same Request interface to handle all URL schemes. For example, you can make an FTP request like so:

req = urllib.request.Request('ftp://example.com/')

In the case of HTTP, there are two extra things that Request objects allow you to do: First, you can pass data to be sent to the server. Second, you can pass extra information (« metadata ») about the data or the about request itself, to the server - this information is sent as HTTP « headers ». Let’s look at each of these in turn.

Data

Sometimes you want to send data to a URL (often the URL will refer to a CGI (Common Gateway Interface) script or other web application). With HTTP, this is often done using what’s known as a POST request. This is often what your browser does when you submit a HTML form that you filled in on the web. Not all POSTs have to come from forms: you can use a POST to transmit arbitrary data to your own application. In the common case of HTML forms, the data needs to be encoded in a standard way, and then passed to the Request object as the data argument. The encoding is done using a function from the urllib.parse library.

import urllib.parse
import urllib.request

url = 'http://www.someserver.com/cgi-bin/register.cgi'
values = {'name' : 'Michael Foord',
          'location' : 'Northampton',
          'language' : 'Python' }

data = urllib.parse.urlencode(values)
data = data.encode('ascii') # data should be bytes
req = urllib.request.Request(url, data)
with urllib.request.urlopen(req) as response:
   the_page = response.read()

Note that other encodings are sometimes required (e.g. for file upload from HTML forms - see HTML Specification, Form Submission [https://www.w3.org/TR/REC-html40/interact/forms.html#h-17.13] for more details).

If you do not pass the data argument, urllib uses a GET request. One way in which GET and POST requests differ is that POST requests often have « side-effects »: they change the state of the system in some way (for example by placing an order with the website for a hundredweight of tinned spam to be delivered to your door). Though the HTTP standard makes it clear that POSTs are intended to always cause side-effects, and GET requests never to cause side-effects, nothing prevents a GET request from having side-effects, nor a POST requests from having no side-effects. Data can also be passed in an HTTP GET request by encoding it in the URL itself.

This is done as follows:

>>> import urllib.request
>>> import urllib.parse
>>> data = {}
>>> data['name'] = 'Somebody Here'
>>> data['location'] = 'Northampton'
>>> data['language'] = 'Python'
>>> url_values = urllib.parse.urlencode(data)
>>> print(url_values)  # The order may differ from below.
name=Somebody+Here&language=Python&location=Northampton
>>> url = 'http://www.example.com/example.cgi'
>>> full_url = url + '?' + url_values
>>> data = urllib.request.urlopen(full_url)

Notice that the full URL is created by adding a ? to the URL, followed by the encoded values.

Headers

We’ll discuss here one particular HTTP header, to illustrate how to add headers to your HTTP request.

Some websites 1 dislike being browsed by programs, or send different versions to different browsers 2. By default urllib identifies itself as Python-urllib/x.y (where x and y are the major and minor version numbers of the Python release, e.g. Python-urllib/2.5), which may confuse the site, or just plain not work. The way a browser identifies itself is through the User-Agent header 3. When you create a Request object you can pass a dictionary of headers in. The following example makes the same request as above, but identifies itself as a version of Internet Explorer 4.

import urllib.parse
import urllib.request

url = 'http://www.someserver.com/cgi-bin/register.cgi'
user_agent = 'Mozilla/5.0 (Windows NT 6.1; Win64; x64)'
values = {'name': 'Michael Foord',
          'location': 'Northampton',
          'language': 'Python' }
headers = {'User-Agent': user_agent}

data = urllib.parse.urlencode(values)
data = data.encode('ascii')
req = urllib.request.Request(url, data, headers)
with urllib.request.urlopen(req) as response:
   the_page = response.read()

The response also has two useful methods. See the section on info and geturl which comes after we have a look at what happens when things go wrong.

Gestion des exceptions

urlopen raises URLError when it cannot handle a response (though as usual with Python APIs, built-in exceptions such as ValueError, TypeError etc. may also be raised).

HTTPError is the subclass of URLError raised in the specific case of HTTP URLs.

The exception classes are exported from the urllib.error module.

URLError

Often, URLError is raised because there is no network connection (no route to the specified server), or the specified server doesn’t exist. In this case, the exception raised will have a “reason” attribute, which is a tuple containing an error code and a text error message.

e.g.

>>> req = urllib.request.Request('http://www.pretend_server.org')
>>> try: urllib.request.urlopen(req)
... except urllib.error.URLError as e:
...     print(e.reason)
...
(4, 'getaddrinfo failed')

HTTPError

Every HTTP response from the server contains a numeric « status code ». Sometimes the status code indicates that the server is unable to fulfil the request. The default handlers will handle some of these responses for you (for example, if the response is a « redirection » that requests the client fetch the document from a different URL, urllib will handle that for you). For those it can’t handle, urlopen will raise an HTTPError. Typical errors include “404” (page not found), “403” (request forbidden), and “401” (authentication required).

See section 10 of RFC 2616 [https://tools.ietf.org/html/rfc2616.html] for a reference on all the HTTP error codes.

The HTTPError instance raised will have an integer “code” attribute, which corresponds to the error sent by the server.

Error Codes

Because the default handlers handle redirects (codes in the 300 range), and codes in the 100–299 range indicate success, you will usually only see error codes in the 400–599 range.

http.server.BaseHTTPRequestHandler.responses is a useful dictionary of response codes in that shows all the response codes used by RFC 2616 [https://tools.ietf.org/html/rfc2616.html]. The dictionary is reproduced here for convenience

# Table mapping response codes to messages; entries have the
# form {code: (shortmessage, longmessage)}.
responses = {
    100: ('Continue', 'Request received, please continue'),
    101: ('Switching Protocols',
          'Switching to new protocol; obey Upgrade header'),

    200: ('OK', 'Request fulfilled, document follows'),
    201: ('Created', 'Document created, URL follows'),
    202: ('Accepted',
          'Request accepted, processing continues off-line'),
    203: ('Non-Authoritative Information', 'Request fulfilled from cache'),
    204: ('No Content', 'Request fulfilled, nothing follows'),
    205: ('Reset Content', 'Clear input form for further input.'),
    206: ('Partial Content', 'Partial content follows.'),

    300: ('Multiple Choices',
          'Object has several resources -- see URI list'),
    301: ('Moved Permanently', 'Object moved permanently -- see URI list'),
    302: ('Found', 'Object moved temporarily -- see URI list'),
    303: ('See Other', 'Object moved -- see Method and URL list'),
    304: ('Not Modified',
          'Document has not changed since given time'),
    305: ('Use Proxy',
          'You must use proxy specified in Location to access this '
          'resource.'),
    307: ('Temporary Redirect',
          'Object moved temporarily -- see URI list'),

    400: ('Bad Request',
          'Bad request syntax or unsupported method'),
    401: ('Unauthorized',
          'No permission -- see authorization schemes'),
    402: ('Payment Required',
          'No payment -- see charging schemes'),
    403: ('Forbidden',
          'Request forbidden -- authorization will not help'),
    404: ('Not Found', 'Nothing matches the given URI'),
    405: ('Method Not Allowed',
          'Specified method is invalid for this server.'),
    406: ('Not Acceptable', 'URI not available in preferred format.'),
    407: ('Proxy Authentication Required', 'You must authenticate with '
          'this proxy before proceeding.'),
    408: ('Request Timeout', 'Request timed out; try again later.'),
    409: ('Conflict', 'Request conflict.'),
    410: ('Gone',
          'URI no longer exists and has been permanently removed.'),
    411: ('Length Required', 'Client must specify Content-Length.'),
    412: ('Precondition Failed', 'Precondition in headers is false.'),
    413: ('Request Entity Too Large', 'Entity is too large.'),
    414: ('Request-URI Too Long', 'URI is too long.'),
    415: ('Unsupported Media Type', 'Entity body in unsupported format.'),
    416: ('Requested Range Not Satisfiable',
          'Cannot satisfy request range.'),
    417: ('Expectation Failed',
          'Expect condition could not be satisfied.'),

    500: ('Internal Server Error', 'Server got itself in trouble'),
    501: ('Not Implemented',
          'Server does not support this operation'),
    502: ('Bad Gateway', 'Invalid responses from another server/proxy.'),
    503: ('Service Unavailable',
          'The server cannot process the request due to a high load'),
    504: ('Gateway Timeout',
          'The gateway server did not receive a timely response'),
    505: ('HTTP Version Not Supported', 'Cannot fulfill request.'),
    }

When an error is raised the server responds by returning an HTTP error code and an error page. You can use the HTTPError instance as a response on the page returned. This means that as well as the code attribute, it also has read, geturl, and info, methods as returned by the urllib.response module:

>>> req = urllib.request.Request('http://www.python.org/fish.html')
>>> try:
...     urllib.request.urlopen(req)
... except urllib.error.HTTPError as e:
...     print(e.code)
...     print(e.read())
...
404
b'<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN"
  "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd">\n\n\n<html
  ...
  <title>Page Not Found</title>\n
  ...

Wrapping it Up

So if you want to be prepared for HTTPError or URLError there are two basic approaches. I prefer the second approach.

Number 1

from urllib.request import Request, urlopen
from urllib.error import URLError, HTTPError
req = Request(someurl)
try:
    response = urlopen(req)
except HTTPError as e:
    print('The server couldn\'t fulfill the request.')
    print('Error code: ', e.code)
except URLError as e:
    print('We failed to reach a server.')
    print('Reason: ', e.reason)
else:
    # everything is fine

Note

The except HTTPError must come first, otherwise except URLError will also catch an HTTPError.

Number 2

from urllib.request import Request, urlopen
from urllib.error import URLError
req = Request(someurl)
try:
    response = urlopen(req)
except URLError as e:
    if hasattr(e, 'reason'):
        print('We failed to reach a server.')
        print('Reason: ', e.reason)
    elif hasattr(e, 'code'):
        print('The server couldn\'t fulfill the request.')
        print('Error code: ', e.code)
else:
    # everything is fine

info and geturl

The response returned by urlopen (or the HTTPError instance) has two useful methods info() and geturl() and is defined in the module urllib.response..

geturl - this returns the real URL of the page fetched. This is useful because urlopen (or the opener object used) may have followed a redirect. The URL of the page fetched may not be the same as the URL requested.

info - this returns a dictionary-like object that describes the page fetched, particularly the headers sent by the server. It is currently an http.client.HTTPMessage instance.

Typical headers include “Content-length”, “Content-type”, and so on. See the Quick Reference to HTTP Headers [https://www.cs.tut.fi/~jkorpela/http.html] for a useful listing of HTTP headers with brief explanations of their meaning and use.

Openers and Handlers

When you fetch a URL you use an opener (an instance of the perhaps confusingly-named urllib.request.OpenerDirector). Normally we have been using the default opener - via urlopen - but you can create custom openers. Openers use handlers. All the « heavy lifting » is done by the handlers. Each handler knows how to open URLs for a particular URL scheme (http, ftp, etc.), or how to handle an aspect of URL opening, for example HTTP redirections or HTTP cookies.

You will want to create openers if you want to fetch URLs with specific handlers installed, for example to get an opener that handles cookies, or to get an opener that does not handle redirections.

To create an opener, instantiate an OpenerDirector, and then call .add_handler(some_handler_instance) repeatedly.

Alternatively, you can use build_opener, which is a convenience function for creating opener objects with a single function call. build_opener adds several handlers by default, but provides a quick way to add more and/or override the default handlers.

Other sorts of handlers you might want to can handle proxies, authentication, and other common but slightly specialised situations.

install_opener can be used to make an opener object the (global) default opener. This means that calls to urlopen will use the opener you have installed.

Opener objects have an open method, which can be called directly to fetch urls in the same way as the urlopen function: there’s no need to call install_opener, except as a convenience.

Basic Authentication

To illustrate creating and installing a handler we will use the HTTPBasicAuthHandler. For a more detailed discussion of this subject – including an explanation of how Basic Authentication works - see the Basic Authentication Tutorial [http://www.voidspace.org.uk/python/articles/authentication.shtml].

When authentication is required, the server sends a header (as well as the 401 error code) requesting authentication. This specifies the authentication scheme and a “realm”. The header looks like: WWW-Authenticate: SCHEME realm="REALM".

e.g.

WWW-Authenticate: Basic realm="cPanel Users"

The client should then retry the request with the appropriate name and password for the realm included as a header in the request. This is “basic authentication”. In order to simplify this process we can create an instance of HTTPBasicAuthHandler and an opener to use this handler.

The HTTPBasicAuthHandler uses an object called a password manager to handle the mapping of URLs and realms to passwords and usernames. If you know what the realm is (from the authentication header sent by the server), then you can use a HTTPPasswordMgr. Frequently one doesn’t care what the realm is. In that case, it is convenient to use HTTPPasswordMgrWithDefaultRealm. This allows you to specify a default username and password for a URL. This will be supplied in the absence of you providing an alternative combination for a specific realm. We indicate this by providing None as the realm argument to the add_password method.

The top-level URL is the first URL that requires authentication. URLs « deeper » than the URL you pass to .add_password() will also match.

# create a password manager
password_mgr = urllib.request.HTTPPasswordMgrWithDefaultRealm()

# Add the username and password.
# If we knew the realm, we could use it instead of None.
top_level_url = "http://example.com/foo/"
password_mgr.add_password(None, top_level_url, username, password)

handler = urllib.request.HTTPBasicAuthHandler(password_mgr)

# create "opener" (OpenerDirector instance)
opener = urllib.request.build_opener(handler)

# use the opener to fetch a URL
opener.open(a_url)

# Install the opener.
# Now all calls to urllib.request.urlopen use our opener.
urllib.request.install_opener(opener)

Note

In the above example we only supplied our HTTPBasicAuthHandler to build_opener. By default openers have the handlers for normal situations – ProxyHandler (if a proxy setting such as an http_proxy environment variable is set), UnknownHandler, HTTPHandler, HTTPDefaultErrorHandler, HTTPRedirectHandler, FTPHandler, FileHandler, DataHandler, HTTPErrorProcessor.

top_level_url is in fact either a full URL (including the “http:” scheme component and the hostname and optionally the port number) e.g. "http://example.com/" or an « authority » (i.e. the hostname, optionally including the port number) e.g. "example.com" or "example.com:8080" (the latter example includes a port number). The authority, if present, must NOT contain the « userinfo » component - for example "joe:password@example.com" is not correct.

Proxies

urllib will auto-detect your proxy settings and use those. This is through the ProxyHandler, which is part of the normal handler chain when a proxy setting is detected. Normally that’s a good thing, but there are occasions when it may not be helpful 5. One way to do this is to setup our own ProxyHandler, with no proxies defined. This is done using similar steps to setting up a Basic Authentication [http://www.voidspace.org.uk/python/articles/authentication.shtml] handler:

>>> proxy_support = urllib.request.ProxyHandler({})
>>> opener = urllib.request.build_opener(proxy_support)
>>> urllib.request.install_opener(opener)

Note

Currently urllib.request does not support fetching of https locations through a proxy. However, this can be enabled by extending urllib.request as shown in the recipe 6.

Note

HTTP_PROXY will be ignored if a variable REQUEST_METHOD is set; see the documentation on getproxies().

Sockets and Layers

The Python support for fetching resources from the web is layered. urllib uses the http.client library, which in turn uses the socket library.

As of Python 2.3 you can specify how long a socket should wait for a response before timing out. This can be useful in applications which have to fetch web pages. By default the socket module has no timeout and can hang. Currently, the socket timeout is not exposed at the http.client or urllib.request levels. However, you can set the default timeout globally for all sockets using

import socket
import urllib.request

# timeout in seconds
timeout = 10
socket.setdefaulttimeout(timeout)

# this call to urllib.request.urlopen now uses the default timeout
# we have set in the socket module
req = urllib.request.Request('http://www.voidspace.org.uk')
response = urllib.request.urlopen(req)

Notes

This document was reviewed and revised by John Lee.

1

Google for example.

2

Browser sniffing is a very bad practice for website design - building sites using web standards is much more sensible. Unfortunately a lot of sites still send different versions to different browsers.

3

The user agent for MSIE 6 is “Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; SV1; .NET CLR 1.1.4322)”

4

For details of more HTTP request headers, see Quick Reference to HTTP Headers [https://www.cs.tut.fi/~jkorpela/http.html].

5

In my case I have to use a proxy to access the internet at work. If you attempt to fetch localhost URLs through this proxy it blocks them. IE is set to use the proxy, which urllib picks up on. In order to test scripts with a localhost server, I have to prevent urllib from using the proxy.

6

urllib opener for SSL proxy (CONNECT method): ASPN Cookbook Recipe [https://code.activestate.com/recipes/456195/].

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Tutoriel argparse

auteur

Tshepang Lekhonkhobe

Ce tutoriel est destiné à être une introduction en douceur à argparse, le module d’analyse de ligne de commande recommandé dans la bibliothèque standard de Python.

Note

Il y a deux autres modules qui remplissent le même rôle : getopt (un équivalent de getopt() du langage C) et optparse qui est obsolète. Il faut noter que argparse est basé sur optparse et donc s’utilise de manière très similaire.

Concepts

Commençons par l’utilisation de la commande ls pour voir le type de fonctionnalité que nous allons étudier dans ce tutoriel d’introduction :

$ ls
cpython  devguide  prog.py  pypy  rm-unused-function.patch
$ ls pypy
ctypes_configure  demo  dotviewer  include  lib_pypy  lib-python ...
$ ls -l
total 20
drwxr-xr-x 19 wena wena 4096 Feb 18 18:51 cpython
drwxr-xr-x  4 wena wena 4096 Feb  8 12:04 devguide
-rwxr-xr-x  1 wena wena  535 Feb 19 00:05 prog.py
drwxr-xr-x 14 wena wena 4096 Feb  7 00:59 pypy
-rw-r--r--  1 wena wena  741 Feb 18 01:01 rm-unused-function.patch
$ ls --help
Usage: ls [OPTION]... [FILE]...
List information about the FILEs (the current directory by default).
Sort entries alphabetically if none of -cftuvSUX nor --sort is specified.
...

Quelques concepts que l’on peut apprendre avec les quatre commandes :

La commande ls est utile quand elle est exécutée sans aucun paramètre. Elle affiche par défaut le contenu du dossier courant.

Si l’on veut plus que ce qui est proposé par défaut, il faut l’indiquer. Dans le cas présent, on veut afficher un dossier différent : pypy. Ce que l’on a fait c’est spécifier un argument positionnel. C’est appelé ainsi car cela permet au programme de savoir quoi faire avec la valeur en se basant seulement sur sa position dans la ligne de commande. Ce concept est plus pertinent pour une commande comme cp dont l’usage de base est cp SRC DEST. Le premier argument est ce que vous voulez copier et le second est où vous voulez le copier.

Maintenant, supposons que l’on veuille changer la façon dont le programme agit. Dans notre exemple, on affiche plus d’information pour chaque ficher que simplement leur nom. Dans ce cas, -l est un argument facultatif.

C’est un fragment du texte d’aide. Cela peut être très utile quand on tombe sur un programme que l’on à jamais utilisé auparavant car on peut comprendre son fonctionnement simplement en lisant l’aide associée.

Les bases

Commençons par un exemple très simple qui ne fait (quasiment) rien :

import argparse
parser = argparse.ArgumentParser()
parser.parse_args()

Ce qui suit est le résultat de l’exécution du code :

$ python3 prog.py
$ python3 prog.py --help
usage: prog.py [-h]

optional arguments:
  -h, --help  show this help message and exit
$ python3 prog.py --verbose
usage: prog.py [-h]
prog.py: error: unrecognized arguments: --verbose
$ python3 prog.py foo
usage: prog.py [-h]
prog.py: error: unrecognized arguments: foo

Voilà ce qu’il se passe :

Exécuter le script sans aucun paramètre a pour effet de ne rien afficher sur la sortie d’erreur. Ce n’est pas très utile.

Le deuxième commence à montrer l’intérêt du module argparse. On n’a quasiment rien fait mais on a déjà un beau message d’aide.

L’option --help, que l’on peut aussi raccourcir en -h, est la seule option que l’on a gratuitement (pas besoin de la préciser). Préciser quoi que ce soit d’autre entraîne une erreur. Mais même dans ce cas, on reçoit aussi un message utile, toujours gratuitement.

Introduction aux arguments positionnels

Un exemple :

import argparse
parser = argparse.ArgumentParser()
parser.add_argument("echo")
args = parser.parse_args()
print(args.echo)

On exécute le code :

$ python3 prog.py
usage: prog.py [-h] echo
prog.py: error: the following arguments are required: echo
$ python3 prog.py --help
usage: prog.py [-h] echo

positional arguments:
  echo

optional arguments:
  -h, --help  show this help message and exit
$ python3 prog.py foo
foo

Voilà ce qu’il se passe :

On a ajouté la méthode add_argument() que l’on utilise pour préciser quels paramètre de lignes de commandes le programme peut accepter. Dans le cas présent, je l’ai appelé echo pour que cela corresponde à sa fonction.

Utiliser le programme nécessite maintenant que l’on précise un paramètre.

La méthode parse_args() renvoie en réalité certaines données des paramètres précisés, dans le cas présent : echo.

La variable est comme une forme de “magie” que argparse effectue gratuitement (c.-à-d. pas besoin de préciser dans quelle variable la valeur est stockée). Vous aurez aussi remarqué que le nom est le même que l’argument en chaîne de caractères donné à la méthode : echo.

Notez cependant que, même si l’affichage d’aide paraît bien , il n’est pas aussi utile qu’il pourrait l’être. Par exemple, on peut lire que echo est un argument positionnel mais on ne peut pas savoir ce que cela fait autrement qu’en le devinant ou en lisant le code source. Donc, rendons-le un peu plus utile :

import argparse
parser = argparse.ArgumentParser()
parser.add_argument("echo", help="echo the string you use here")
args = parser.parse_args()
print(args.echo)

Et on obtient :

$ python3 prog.py -h
usage: prog.py [-h] echo

positional arguments:
  echo        echo the string you use here

optional arguments:
  -h, --help  show this help message and exit

À présent, que diriez-vous de faire quelque chose d’encore plus utile :

import argparse
parser = argparse.ArgumentParser()
parser.add_argument("square", help="display a square of a given number")
args = parser.parse_args()
print(args.square**2)

Ce qui suit est le résultat de l’exécution du code :

$ python3 prog.py 4
Traceback (most recent call last):
  File "prog.py", line 5, in <module>
    print(args.square**2)
TypeError: unsupported operand type(s) for ** or pow(): 'str' and 'int'

Cela n’a pas très bien fonctionné. C’est parce que argparse traite les paramètres que l’on donne comme des chaînes de caractères à moins qu’on ne lui indique de faire autrement. Donc, disons à argparse de traiter cette entrée comme un entier :

import argparse
parser = argparse.ArgumentParser()
parser.add_argument("square", help="display a square of a given number",
                    type=int)
args = parser.parse_args()
print(args.square**2)

Ce qui suit est le résultat de l’exécution du code :

$ python3 prog.py 4
16
$ python3 prog.py four
usage: prog.py [-h] square
prog.py: error: argument square: invalid int value: 'four'

Cela a bien fonctionné. Maintenant le programme va même s’arrêter si l’entrée n’est pas légale avant de procéder à l’exécution.

Introduction aux arguments optionnels

Jusqu’à maintenant, on a joué avec les arguments positionnels. Regardons comment ajouter des paramètres optionnels :

import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--verbosity", help="increase output verbosity")
args = parser.parse_args()
if args.verbosity:
    print("verbosity turned on")

Et le résultat :

$ python3 prog.py --verbosity 1
verbosity turned on
$ python3 prog.py
$ python3 prog.py --help
usage: prog.py [-h] [--verbosity VERBOSITY]

optional arguments:
  -h, --help            show this help message and exit
  --verbosity VERBOSITY
                        increase output verbosity
$ python3 prog.py --verbosity
usage: prog.py [-h] [--verbosity VERBOSITY]
prog.py: error: argument --verbosity: expected one argument

Voilà ce qu’il se passe :

Le programme est écrit de sorte qu’il n’affiche rien sauf si l’option --verbosity est précisée.

Pour montrer que l’option est bien optionnelle il n’y aura pas d’erreur s’il on exécute le programme sans celle-ci. Notez que par défaut, si une option n’est pas utilisée, la variable associée, dans le cas présent : args.verbosity, prend la valeur None c’est pourquoi elle échoue le test de vérité de l’assertion if.

Le message d’aide est quelque peu différent.

Quand on utilise l’option --verbosity on doit aussi préciser une valeur, n’importe laquelle.

L’exemple ci-dessus accepte des valeurs entières arbitraires pour --verbosity mais pour notre programme simple seule deux valeurs sont réellement utiles : True et False. Modifions le code en accord avec cela :

import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--verbose", help="increase output verbosity",
                    action="store_true")
args = parser.parse_args()
if args.verbose:
    print("verbosity turned on")

Et le résultat :

$ python3 prog.py --verbose
verbosity turned on
$ python3 prog.py --verbose 1
usage: prog.py [-h] [--verbose]
prog.py: error: unrecognized arguments: 1
$ python3 prog.py --help
usage: prog.py [-h] [--verbose]

optional arguments:
  -h, --help  show this help message and exit
  --verbose   increase output verbosity

Voilà ce qu’il se passe :

Maintenant le paramètre est plus une option que quelque chose qui nécessite une valeur. On a même changé le nom du paramètre pour qu’il corresponde à cette idée. Notez que maintenant on précise une nouvelle action clavier et qu’on lui donne la valeur "store_true". Cela signifie que si l’option est précisée la valeur True est assignée à args.verbose. Ne rien préciser implique la valeur False.

Dans l’esprit de ce que sont vraiment les options, pas des paramètres, il se plaint quand vous tentez de préciser une valeur.

Notez que l’aide est différente.

Les paramètres raccourcis

Si vous êtes familier avec l’utilisation de la ligne de commande, vous avez dû remarquer que je n’ai pour l’instant rien dit au sujet des versions raccourcies des paramètres. C’est très simple :

import argparse
parser = argparse.ArgumentParser()
parser.add_argument("-v", "--verbose", help="increase output verbosity",
                    action="store_true")
args = parser.parse_args()
if args.verbose:
    print("verbosity turned on")

Et voilà :

$ python3 prog.py -v
verbosity turned on
$ python3 prog.py --help
usage: prog.py [-h] [-v]

optional arguments:
  -h, --help     show this help message and exit
  -v, --verbose  increase output verbosity

Notez que la nouvelle option est aussi indiquée dans l’aide.

Combinaison d’arguments positionnels et optionnels

Notre programme continue de croître en complexité :

import argparse
parser = argparse.ArgumentParser()
parser.add_argument("square", type=int,
                    help="display a square of a given number")
parser.add_argument("-v", "--verbose", action="store_true",
                    help="increase output verbosity")
args = parser.parse_args()
answer = args.square**2
if args.verbose:
    print("the square of {} equals {}".format(args.square, answer))
else:
    print(answer)

Et voilà le résultat :

$ python3 prog.py
usage: prog.py [-h] [-v] square
prog.py: error: the following arguments are required: square
$ python3 prog.py 4
16
$ python3 prog.py 4 --verbose
the square of 4 equals 16
$ python3 prog.py --verbose 4
the square of 4 equals 16

Nous avons ajouté un argument nommé, d’où le message d’erreur.

Notez que l’ordre importe peu.

Qu’en est-il si nous donnons à ce programme la possibilité d’avoir plusieurs niveaux de verbosité, et que celui-ci les prend en compte :

import argparse
parser = argparse.ArgumentParser()
parser.add_argument("square", type=int,
                    help="display a square of a given number")
parser.add_argument("-v", "--verbosity", type=int,
                    help="increase output verbosity")
args = parser.parse_args()
answer = args.square**2
if args.verbosity == 2:
    print("the square of {} equals {}".format(args.square, answer))
elif args.verbosity == 1:
    print("{}^2 == {}".format(args.square, answer))
else:
    print(answer)

Et le résultat :

$ python3 prog.py 4
16
$ python3 prog.py 4 -v
usage: prog.py [-h] [-v VERBOSITY] square
prog.py: error: argument -v/--verbosity: expected one argument
$ python3 prog.py 4 -v 1
4^2 == 16
$ python3 prog.py 4 -v 2
the square of 4 equals 16
$ python3 prog.py 4 -v 3
16

Tout semble bon sauf le dernier, qui montre que notre programme contient un bogue. Corrigeons cela en restreignant les valeurs que --verbosity accepte :

import argparse
parser = argparse.ArgumentParser()
parser.add_argument("square", type=int,
                    help="display a square of a given number")
parser.add_argument("-v", "--verbosity", type=int, choices=[0, 1, 2],
                    help="increase output verbosity")
args = parser.parse_args()
answer = args.square**2
if args.verbosity == 2:
    print("the square of {} equals {}".format(args.square, answer))
elif args.verbosity == 1:
    print("{}^2 == {}".format(args.square, answer))
else:
    print(answer)

Et le résultat :

$ python3 prog.py 4 -v 3
usage: prog.py [-h] [-v {0,1,2}] square
prog.py: error: argument -v/--verbosity: invalid choice: 3 (choose from 0, 1, 2)
$ python3 prog.py 4 -h
usage: prog.py [-h] [-v {0,1,2}] square

positional arguments:
  square                display a square of a given number

optional arguments:
  -h, --help            show this help message and exit
  -v {0,1,2}, --verbosity {0,1,2}
                        increase output verbosity

Notez que ce changement est pris en compte à la fois dans le message d’erreur et dans le texte d’aide.

Essayons maintenant une approche différente pour jouer sur la verbosité, ce qui arrive fréquemment. Cela correspond également à comment le programme CPython gère ses propres paramètres de verbosité (jetez un œil sur la sortie de la commande python --help) :

import argparse
parser = argparse.ArgumentParser()
parser.add_argument("square", type=int,
                    help="display the square of a given number")
parser.add_argument("-v", "--verbosity", action="count",
                    help="increase output verbosity")
args = parser.parse_args()
answer = args.square**2
if args.verbosity == 2:
    print("the square of {} equals {}".format(args.square, answer))
elif args.verbosity == 1:
    print("{}^2 == {}".format(args.square, answer))
else:
    print(answer)

Nous avons introduit une autre action, "count", pour compter le nombre d’occurrences d’une argument optionnel en particulier :

$ python3 prog.py 4
16
$ python3 prog.py 4 -v
4^2 == 16
$ python3 prog.py 4 -vv
the square of 4 equals 16
$ python3 prog.py 4 --verbosity --verbosity
the square of 4 equals 16
$ python3 prog.py 4 -v 1
usage: prog.py [-h] [-v] square
prog.py: error: unrecognized arguments: 1
$ python3 prog.py 4 -h
usage: prog.py [-h] [-v] square

positional arguments:
  square           display a square of a given number

optional arguments:
  -h, --help       show this help message and exit
  -v, --verbosity  increase output verbosity
$ python3 prog.py 4 -vvv
16

Oui, c’est maintenant d’avantage une option (similaire à action="store_true") de la version précédente de notre script. Cela devrait expliquer le message d’erreur.

Cela se comporte de la même manière que l’action "store_true".

Maintenant voici une démonstration de ce que l’action "count" fait. Vous avez sûrement vu ce genre d’utilisation auparavant.

Et si vous ne spécifiez pas l’option -v, cette option prendra la valeur None.

Comme on s’y attend, en spécifiant l’option dans sa forme longue, on devrait obtenir la même sortie.

Malheureusement, notre sortie d’aide n’est pas très informative à propos des nouvelles possibilités de notre programme, mais cela peut toujours être corrigé en améliorant sa documentation (en utilisant l’argument help).

La dernière sortie du programme montre que celui-ci contient un bogue.

Corrigeons :

import argparse
parser = argparse.ArgumentParser()
parser.add_argument("square", type=int,
                    help="display a square of a given number")
parser.add_argument("-v", "--verbosity", action="count",
                    help="increase output verbosity")
args = parser.parse_args()
answer = args.square**2

# bugfix: replace == with >=
if args.verbosity >= 2:
    print("the square of {} equals {}".format(args.square, answer))
elif args.verbosity >= 1:
    print("{}^2 == {}".format(args.square, answer))
else:
    print(answer)

Et c’est ce que ça donne :

$ python3 prog.py 4 -vvv
the square of 4 equals 16
$ python3 prog.py 4 -vvvv
the square of 4 equals 16
$ python3 prog.py 4
Traceback (most recent call last):
  File "prog.py", line 11, in <module>
    if args.verbosity >= 2:
TypeError: '>=' not supported between instances of 'NoneType' and 'int'

Les premières exécutions du programme sont correctes, et le bogue que nous avons eu est corrigé. Cela dit, nous voulons que n’importe quelle valeur >= 2 rende le programme aussi verbeux que possible.

La troisième sortie de programme n’est pas si bien que ça.

Corrigeons ce bogue :

import argparse
parser = argparse.ArgumentParser()
parser.add_argument("square", type=int,
                    help="display a square of a given number")
parser.add_argument("-v", "--verbosity", action="count", default=0,
                    help="increase output verbosity")
args = parser.parse_args()
answer = args.square**2
if args.verbosity >= 2:
    print("the square of {} equals {}".format(args.square, answer))
elif args.verbosity >= 1:
    print("{}^2 == {}".format(args.square, answer))
else:
    print(answer)

Nous venons juste d’introduire un nouveau mot clef, default. Nous l’avons définit à 0 pour le rendre comparable aux autres valeurs. Rappelez-vous que par défaut, si un argument optionnel n’est pas spécifié, il sera définit à None, et ne pourra pas être comparé à une valeur de type entier (une erreur TypeError serait alors levée).

Et :

$ python3 prog.py 4
16

Vous pouvez aller assez loin seulement avec ce que nous avons appris jusqu’à maintenant, et nous n’avons qu’aperçu la surface. Le module argparse est très puissant, et nous allons l’explorer un peu plus avant la fin de ce tutoriel.

Aller un peu plus loin

Qu’en est-il si nous souhaitons étendre notre mini programme pour le rendre capable de calculer d’autres puissances, et pas seulement des carrés :

import argparse
parser = argparse.ArgumentParser()
parser.add_argument("x", type=int, help="the base")
parser.add_argument("y", type=int, help="the exponent")
parser.add_argument("-v", "--verbosity", action="count", default=0)
args = parser.parse_args()
answer = args.x**args.y
if args.verbosity >= 2:
    print("{} to the power {} equals {}".format(args.x, args.y, answer))
elif args.verbosity >= 1:
    print("{}^{} == {}".format(args.x, args.y, answer))
else:
    print(answer)

Sortie :

$ python3 prog.py
usage: prog.py [-h] [-v] x y
prog.py: error: the following arguments are required: x, y
$ python3 prog.py -h
usage: prog.py [-h] [-v] x y

positional arguments:
  x                the base
  y                the exponent

optional arguments:
  -h, --help       show this help message and exit
  -v, --verbosity
$ python3 prog.py 4 2 -v
4^2 == 16

Il est à noter que jusqu’à présent nous avons utilisé le niveau de verbosité pour changer le texte qui est affiché. L’exemple suivant au contraire utilise le niveau de verbosité pour afficher plus de texte à la place :

import argparse
parser = argparse.ArgumentParser()
parser.add_argument("x", type=int, help="the base")
parser.add_argument("y", type=int, help="the exponent")
parser.add_argument("-v", "--verbosity", action="count", default=0)
args = parser.parse_args()
answer = args.x**args.y
if args.verbosity >= 2:
    print("Running '{}'".format(__file__))
if args.verbosity >= 1:
    print("{}^{} == ".format(args.x, args.y), end="")
print(answer)

Sortie :

$ python3 prog.py 4 2
16
$ python3 prog.py 4 2 -v
4^2 == 16
$ python3 prog.py 4 2 -vv
Running 'prog.py'
4^2 == 16

Paramètres en conflit

Jusque là, nous avons travaillé avec deux méthodes d’une instance de argparse.ArgumentParser. En voici une troisième, add_mutually_exclusive_group(). Elle nous permet de spécifier des paramètres qui sont en conflit entre eux. Changeons aussi le reste du programme de telle sorte que la nouvelle fonctionnalité fasse sens : nous allons introduire l’option --quiet, qui va avoir l’effet opposé de l’option --verbose :

import argparse

parser = argparse.ArgumentParser()
group = parser.add_mutually_exclusive_group()
group.add_argument("-v", "--verbose", action="store_true")
group.add_argument("-q", "--quiet", action="store_true")
parser.add_argument("x", type=int, help="the base")
parser.add_argument("y", type=int, help="the exponent")
args = parser.parse_args()
answer = args.x**args.y

if args.quiet:
    print(answer)
elif args.verbose:
    print("{} to the power {} equals {}".format(args.x, args.y, answer))
else:
    print("{}^{} == {}".format(args.x, args.y, answer))

Notre programme est maintenant plus simple, et nous avons perdu des fonctionnalités pour faire cette démonstration. Peu importe, voici la sortie du programme :

$ python3 prog.py 4 2
4^2 == 16
$ python3 prog.py 4 2 -q
16
$ python3 prog.py 4 2 -v
4 to the power 2 equals 16
$ python3 prog.py 4 2 -vq
usage: prog.py [-h] [-v | -q] x y
prog.py: error: argument -q/--quiet: not allowed with argument -v/--verbose
$ python3 prog.py 4 2 -v --quiet
usage: prog.py [-h] [-v | -q] x y
prog.py: error: argument -q/--quiet: not allowed with argument -v/--verbose

Cela devrait être facile à suivre. J’ai ajouté cette dernière sortie pour que vous puissiez voir le genre de flexibilité que vous pouvez avoir, par exemple pour faire un mélange entre des paramètres courts et longs.

Avant d’en finir, vous voudrez certainement dire à vos utilisateurs quel est le but principal de votre programme, juste dans le cas ou ils ne le sauraient pas :

import argparse

parser = argparse.ArgumentParser(description="calculate X to the power of Y")
group = parser.add_mutually_exclusive_group()
group.add_argument("-v", "--verbose", action="store_true")
group.add_argument("-q", "--quiet", action="store_true")
parser.add_argument("x", type=int, help="the base")
parser.add_argument("y", type=int, help="the exponent")
args = parser.parse_args()
answer = args.x**args.y

if args.quiet:
    print(answer)
elif args.verbose:
    print("{} to the power {} equals {}".format(args.x, args.y, answer))
else:
    print("{}^{} == {}".format(args.x, args.y, answer))

Notez cette nuance dans le texte d’utilisation. Les options [-v | -q]` nous disent que nous pouvons utiliser au choix -v ou -q, mais pas les deux ensemble :

$ python3 prog.py --help
usage: prog.py [-h] [-v | -q] x y

calculate X to the power of Y

positional arguments:
  x              the base
  y              the exponent

optional arguments:
  -h, --help     show this help message and exit
  -v, --verbose
  -q, --quiet

Conclusion

Le module argparse offre bien plus que ce qui est montré ici. Sa documentation est assez détaillée, complète et pleine d’exemples. En ayant accompli ce tutoriel, vous pourrez facilement comprendre cette documentation sans vous sentir dépassé.

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Introduction au module ipaddress

auteur

Peter Moody

auteur

Nick Coghlan

Aperçu

Ce document vise à fournir une introduction rapide au module ipaddress. Il est destiné aux utilisateurs qui ne sont pas familiers avec la terminologie des réseaux IP, mais il peut aussi être utile aux ingénieurs réseaux qui cherchent un aperçu de la représentation des concepts d’adressage IP avec le module ipaddress.

Créer un objet Adresse/Réseau/Interface

Vu que ipaddress est un module pour inspecter et manipuler des adresses IP, la première chose que vous voudrez faire est de créer quelques objets. Vous pouvez utiliser ipaddress pour créer des objets à partir de chaînes de caractères et d’entiers.

Note sur les versions d’IP

Pour les lecteurs qui ne sont pas particulièrement familiers avec l’adressage IP il est important de savoir que le protocole IP est actuellement en évolution de la version 4 du protocole vers la version 6. Cette transition est largement due au fait que la version 4 du protocole ne fournit pas assez d’adresses pour gérer les besoins du monde entier, particulièrement à cause de la croissance des périphériques directement connectés à Internet.

Expliquer les détails des différences entre les deux versions du protocole est au-delà du périmètre de cette introduction, mais les lecteurs doivent au moins être avertis de l’existence de ces deux versions et qu’il sera nécessaire de forcer l’utilisation d’une version ou de l’autre.

Adresses IP des hôtes

Les adresses, souvent dénommées « adresses hôtes » sont les unités les plus basiques quand on travaille avec l’adressage IP. Le moyen le plus simple de créer des adresses est d’utiliser la fonction de fabrication ipaddress.ip_address() qui va automatiquement déterminer quoi créer entre une adresse IPv4 ou une adresse IPv6 en fonction de la valeur qui est transmise :

>>> ipaddress.ip_address('192.0.2.1')
IPv4Address('192.0.2.1')
>>> ipaddress.ip_address('2001:DB8::1')
IPv6Address('2001:db8::1')

Les adresses peuvent être créées directement depuis des entiers. Les valeurs qui correspondent à des entiers 32 bits sont assimilées à des adresses IPv4 :

>>> ipaddress.ip_address(3221225985)
IPv4Address('192.0.2.1')
>>> ipaddress.ip_address(42540766411282592856903984951653826561)
IPv6Address('2001:db8::1')

Pour forcer l’utilisation d’IPv4 ou d’IPv6, la classe appropriée peut être invoquée directement. C’est particulièrement utile pour forcer la création d’adresse IPv6 pour de petits entiers :

>>> ipaddress.ip_address(1)
IPv4Address('0.0.0.1')
>>> ipaddress.IPv4Address(1)
IPv4Address('0.0.0.1')
>>> ipaddress.IPv6Address(1)
IPv6Address('::1')

Définir des réseaux

Les adresses hôtes sont souvent regroupées dans des réseaux IP, donc ipaddress fournit un moyen de créer, d’inspecter et de manipuler les définitions des réseaux. Les objets correspondants aux réseaux IP sont construits à partir de chaînes de caractères qui définissent le périmètre des adresses hôtes qui font partie de ce réseau. La forme la plus simple de cette information est un couple « adresse réseau/préfixe réseau » , où le préfixe définit le nombre de bits de tête qui sont comparés pour déterminer si l’adresse fait ou ne fait pas partie de ce réseau et l’adresse réseau définit la valeur attendue pour ces bits.

Tout comme pour les adresses, une fonction de fabrication est disponible et détermine automatiquement la version correcte d’IP :

>>> ipaddress.ip_network('192.0.2.0/24')
IPv4Network('192.0.2.0/24')
>>> ipaddress.ip_network('2001:db8::0/96')
IPv6Network('2001:db8::/96')

Il est interdit pour des objets réseaux d’avoir des bits affectés à leurs hôtes mis à 1. Ainsi la chaine de caractères 192.0.2.1/24 ne peut définir un réseau. Ces objets réseaux sont aussi appelés objets d’interfaces car la notation adresse ip / réseau est couramment utilisée pour décrire les interfaces réseau d’un ordinateur sur un réseau donné (nous les détaillons plus loin dans cette section).

Par défaut, tenter de créer un objet réseau avec des bits d’hôtes mis à 1 lève une ValueError. Pour demander que les bits supplémentaires soient plutôt forcés à zéro, l’attribut strict=False peut être passé au constructeur :

>>> ipaddress.ip_network('192.0.2.1/24')
Traceback (most recent call last):
   ...
ValueError: 192.0.2.1/24 has host bits set
>>> ipaddress.ip_network('192.0.2.1/24', strict=False)
IPv4Network('192.0.2.0/24')

Alors que la forme textuelle offre davantage de flexibilité les réseaux peuvent aussi être définis avec des entiers, tout comme les adresses hôtes. Dans ce cas le réseau est considéré comme contenant uniquement l’adresse identifiée par l’entier, donc le préfixe réseau inclut l’adresse du réseau complet :

>>> ipaddress.ip_network(3221225984)
IPv4Network('192.0.2.0/32')
>>> ipaddress.ip_network(42540766411282592856903984951653826560)
IPv6Network('2001:db8::/128')

Comme avec les adresses, la création d’un type de réseau particulier peut être forcée en appelant directement le constructeur de la classe plutôt que d’utiliser la fonction de fabrication.

Interfaces des hôtes

Comme mentionné ci-dessus, si vous avez besoin de décrire une adresse sur un réseau particulier, ni l’adresse ni les classes réseaux ne sont suffisantes. Les notations comme 192.0.2.1/24 sont généralement utilisées par les ingénieurs réseaux et les personnes qui écrivent des outils pour les pare-feu et les routeurs comme raccourci pour  » l’hôte 192.0.2.1 sur le réseau 192.0.2.0/24 », par conséquent, ipaddress fournit un ensemble de classes hybrides qui associent une adresse à un réseau particulier. L’interface pour la création est identique à celle pour la définition des objets réseaux, excepté que la partie adresse n’est pas contrainte d’être une adresse réseau.

>>> ipaddress.ip_interface('192.0.2.1/24')
IPv4Interface('192.0.2.1/24')
>>> ipaddress.ip_interface('2001:db8::1/96')
IPv6Interface('2001:db8::1/96')

Les entiers sont acceptés en entrée (comme avec les réseaux) et l’utilisation d’une version d’IP peut être forcée en appelant directement le constructeur adapté.

Inspecter les objets Address/Network/Interface

Vous vous êtes donné la peine de créer un objet (adresse|réseau|interface)IPv(4|6), donc vous voudrez probablement des informations sur celui-ci. ipaddress essaie de rendre ceci facile et intuitif.

Extraire la version du protocole IP :

>>> addr4 = ipaddress.ip_address('192.0.2.1')
>>> addr6 = ipaddress.ip_address('2001:db8::1')
>>> addr6.version
6
>>> addr4.version
4

Obtenir le réseau à partir de l’interface :

>>> host4 = ipaddress.ip_interface('192.0.2.1/24')
>>> host4.network
IPv4Network('192.0.2.0/24')
>>> host6 = ipaddress.ip_interface('2001:db8::1/96')
>>> host6.network
IPv6Network('2001:db8::/96')

Trouver combien d’adresses individuelles sont dans un réseau :

>>> net4 = ipaddress.ip_network('192.0.2.0/24')
>>> net4.num_addresses
256
>>> net6 = ipaddress.ip_network('2001:db8::0/96')
>>> net6.num_addresses
4294967296

Itération sur chacune des adresses « utilisables » d’un réseau :

>>> net4 = ipaddress.ip_network('192.0.2.0/24')
>>> for x in net4.hosts():
...     print(x)
192.0.2.1
192.0.2.2
192.0.2.3
192.0.2.4
...
192.0.2.252
192.0.2.253
192.0.2.254

Obtenir le masque réseau (définit les bits correspondant au préfixe du réseau) ou le masque de l’hôte (tous les bits qui ne sont pas dans le masque du réseau) :

>>> net4 = ipaddress.ip_network('192.0.2.0/24')
>>> net4.netmask
IPv4Address('255.255.255.0')
>>> net4.hostmask
IPv4Address('0.0.0.255')
>>> net6 = ipaddress.ip_network('2001:db8::0/96')
>>> net6.netmask
IPv6Address('ffff:ffff:ffff:ffff:ffff:ffff::')
>>> net6.hostmask
IPv6Address('::ffff:ffff')

Éclater ou compresser l’adresse :

>>> addr6.exploded
'2001:0db8:0000:0000:0000:0000:0000:0001'
>>> addr6.compressed
'2001:db8::1'
>>> net6.exploded
'2001:0db8:0000:0000:0000:0000:0000:0000/96'
>>> net6.compressed
'2001:db8::/96'

Alors que IPv4 ne gère pas l’éclatement ou la compression, les objets associés fournissent toujours les propriétés adaptées pour que du code, le plus neutre possible vis-à-vis de la version, puisse facilement s’assurer que la forme la plus concise ou la plus verbeuse utilisée pour des adresses IPv6 va aussi fonctionner pour gérer des adresses IPv4.

Réseaux en tant que listes d’adresses

Il est parfois utile de traiter les réseaux en tant que listes. Cela signifie qu’il est possible de les indexer comme ça :

>>> net4[1]
IPv4Address('192.0.2.1')
>>> net4[-1]
IPv4Address('192.0.2.255')
>>> net6[1]
IPv6Address('2001:db8::1')
>>> net6[-1]
IPv6Address('2001:db8::ffff:ffff')

Cela signifie aussi que les objets réseaux se prêtent bien à l’utilisation de la syntaxe suivante pour le test d’appartenance à la liste :

if address in network:
    # do something

En se basant sur le préfixe réseau on peut efficacement tester l’appartenance :

>>> addr4 = ipaddress.ip_address('192.0.2.1')
>>> addr4 in ipaddress.ip_network('192.0.2.0/24')
True
>>> addr4 in ipaddress.ip_network('192.0.3.0/24')
False

Comparaisons

ipaddress fournit des moyens simples et intuitifs (du moins nous l’espérons) pour comparer les objets, quand cela fait sens :

>>> ipaddress.ip_address('192.0.2.1') < ipaddress.ip_address('192.0.2.2')
True

Une exception TypeError est levée si vous tentez de comparer des objets de différentes versions ou de types différents.

Utiliser des adresse IP avec d’autre modules

Les autres modules qui utilisent des adresses IP (comme socket) n’acceptent généralement pas les objets de ce module directement. Au lieu de cela, ils doivent être convertis en entiers ou en chaînes de caractères que l’autre module va accepter :

>>> addr4 = ipaddress.ip_address('192.0.2.1')
>>> str(addr4)
'192.0.2.1'
>>> int(addr4)
3221225985

Obtenir plus de détails lors de l’échec de la création de l’instance

Lors de la création des objets Adresse/Réseau/Interface en utilisant les fonctions de fabrication agnostiques à la version, n’importe quelle erreur va être signalée en tant que ValueError avec un message d’erreur générique qui dit simplement que la valeur entrée n’a pas été reconnue en tant qu’objet de ce type. Pour fournir plus de détails sur la cause du rejet, il faudrait reconnaitre si la valeur est supposée être une adresse IPv4 ou IPv6.

Pour gérer les cas d’usage où il est utile d’avoir accès à ces détails, les constructeurs individuels des classes lèvent actuellement les sous-classes de ValueError, ipaddress.AddressValueError et ipaddress.NetmaskValueError pour indiquer précisément quelle partie de la définition n’a pas pu être correctement traitée.

Les messages d’erreur sont particulièrement plus détaillés lors de l’utilisation directe du constructeur. Par exemple :

>>> ipaddress.ip_address("192.168.0.256")
Traceback (most recent call last):
  ...
ValueError: '192.168.0.256' does not appear to be an IPv4 or IPv6 address
>>> ipaddress.IPv4Address("192.168.0.256")
Traceback (most recent call last):
  ...
ipaddress.AddressValueError: Octet 256 (> 255) not permitted in '192.168.0.256'

>>> ipaddress.ip_network("192.168.0.1/64")
Traceback (most recent call last):
  ...
ValueError: '192.168.0.1/64' does not appear to be an IPv4 or IPv6 network
>>> ipaddress.IPv4Network("192.168.0.1/64")
Traceback (most recent call last):
  ...
ipaddress.NetmaskValueError: '64' is not a valid netmask

Cependant, les exceptions spécifiques des deux modules ont ValueError comme classe parent ; donc si vous n’êtes pas intéressé par le type particulier d’erreur remontée, vous pouvez écrire votre code comme suit :

try:
    network = ipaddress.IPv4Network(address)
except ValueError:
    print('address/netmask is invalid for IPv4:', address)

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Argument Clinic How-To

auteur

Larry Hastings

Résumé

Argument Clinic est un préprocesseur pour les fichiers C de CPython. Il permet d’automatiser les tâches répétitives lors de la rédaction du code d’analyse d’arguments pour les modules natifs. Ce document vous montre comment convertir votre première fonction C de façon à ce qu’elle fonctionne avec Argument Clinic, avant d’introduire des usages plus avancés d’Argument Clinic.

Argument Clinic est pour le moment considéré comme un outil interne à CPython. Il n’est pas conçu pour gérer des fichiers à l’extérieur de CPython, et sa compatibilité ascendante n’est pas garantie pour les versions futures. En d’autres termes, si vous êtes mainteneur d’une extension C pour CPython, vous pouvez bien sûr expérimenter avec Argument Clinic sur votre propre code. Mais la version d’Argument Clinic livrée avec la prochaine version de CPython pourrait être totalement incompatible et casser tout votre code.

Les objectifs d’Argument Clinic

Le premier objectif d’Argument Clinic est de prendre en charge toute l’analyse d’arguments à l’intérieur de CPython. Cela signifie que si vous convertissez une fonction pour fonctionner avec Argument Clinic, cette fonction n’a plus du tout besoin d’analyser ses propres arguments. Le code généré par Argument Clinic doit être une « boîte noire » avec en entrée l’appel de CPython, et en sortie l’appel à votre code. Entre les deux, PyObject *args (et éventuellement PyObject *kwargs) sont convertis magiquement dans les variables et types C dont vous avez besoin.

Pour que le premier objectif d’Argument Clinic soit atteint, il faut qu’il soit facile à utiliser. Actuellement, travailler avec la bibliothèque d’analyse d’arguments de CPython est une corvée. Il faut maintenir une quantité surprenante d’informations redondantes. En utilisant Argument Clinic, il n’est plus nécessaire de se répéter.

Certainement, personne ne voudrait utiliser Argument Clinic s’il ne réglait pas leur problème – sans en créer de nouveaux. Il est donc de la première importance qu’Argument Clinic génère du code correct. Il est aussi souhaitable que le code soit aussi plus rapide. Au minimum, il ne doit pas introduire de régression significative sur la vitesse d’exécution. (Au bout du compte, Argument Clinic devrait permettre une accélération importante – on pourrait ré-écrire son générateur de code pour produire du code d’analyse d’argument adapté au mieux, plutôt que d’utiliser la bibliothèque d’analyse d’argument générique. On aurait ainsi l’analyse d’argument la plus rapide possible !)

De plus, Argument Clinic doit être suffisamment flexible pour s’accommoder d’approches différentes de l’analyse d’arguments. Il y a des fonctions dans Python dont le traitement des arguments est très étrange ; le but d’Argument Clinic est de les gérer toutes.

Finalement, la motivation première d’Argument Clinic était de fournir des « signatures » pour l’introspection des composants natifs de CPython. Précédemment, les fonctions d’introspection levaient une exception si vous passiez un composant natif. Grâce à Argument Clinic, ce comportement appartient au passé !

En travaillant avec Argument Clinic, il faut garder à l’esprit que plus vous lui donnez de détails, meilleur sera son boulot. Argument Clinic est bien sûr assez simple pour le moment. Mais à mesure qu’il évoluera et deviendra plus sophistiqué, il sera capable de faire beaucoup de choses intéressantes et intelligentes à partir de l’information que vous lui fournissez.

Concepts de base et utilisation

Argument Clinic est livré avec CPython; vous le trouverez dans Tools/clinic/clinic.py. Si vous exécutez ce script, en spécifiant un fichier C comme argument :

$ python3 Tools/clinic/clinic.py foo.c

Argument Clinic va parcourir le fichier en cherchant cette ligne :

/*[clinic input]

Lorsqu’il en trouve une, il lit tout ce qui suit, jusqu’à cette ligne :

[clinic start generated code]*/

Tout ce qui se trouve entre ces deux lignes est une entrée pour Argument Clinic. Toutes ces lignes, en incluant les commentaires de début et de fin, sont appelées collectivement un « bloc » d’Argument Clinic.

Lorsque Argument Clinic analyse l’un de ces blocs, il produit une sortie. Cette sortie est réécrite dans le fichier C immédiatement après le bloc, suivie par un commentaire contenant une somme de contrôle. Le bloc Argument Clinic ressemble maintenant à cela :

/*[clinic input]
... clinic input goes here ...
[clinic start generated code]*/
... clinic output goes here ...
/*[clinic end generated code: checksum=...]*/

Si vous exécutez de nouveau Argument Clinic sur ce même fichier, Argument Clinic supprime la vieille sortie, et écrit la nouvelle sortie avec une ligne de somme de contrôle mise à jour. Cependant, si l’entrée n’a pas changé, la sortie ne change pas non plus.

Vous ne devez jamais modifier la sortie d’un bloc Argument Clinic. Changez plutôt l’entrée jusqu’à obtenir la sortie souhaitée (c’est précisément le but de la somme de contrôle, détecter si la sortie a été changée. En effet, ces modifications seront perdues après que Argument Clinic a écrit une nouvelle sortie).

Par souci de clarté, voilà la terminologie que nous emploierons :

La première ligne du commentaire (/*[clinic input]) est la ligne de début.

La dernière ligne du commentaire initial ([clinic start generated code]*/) est la ligne de fin.

La dernière ligne (/*[clinic end generated code: checksum=...]*/) est la ligne de contrôle.

On appelle entrée ce qui se trouve entre la ligne de début et la ligne de fin.

Et on appelle sortie ce qui se trouve entre la ligne de fin et la ligne de contrôle.

L’ensemble du texte, depuis la ligne de début jusqu’à la ligne de contrôle incluse s’appelle le bloc. (Un bloc qui n’a pas encore été traité avec succès par Argument Clinic n’a pas encore de sortie ni de ligne de contrôle mais est quand même considéré comme un bloc)

Convertissez votre première fonction

La meilleure manière de comprendre le fonctionnement d’Argument Clinic est de convertir une fonction. Voici donc les étapes minimales que vous devez suivre pour convertir une fonction de manière à ce qu’elle fonctionne avec Argument Clinic. Remarquez que pour du code que vous comptez inclure dans CPython, vous devrez certainement pousser plus loin la conversion, en utilisant les concepts avancés que nous verrons plus loin dans ce document (comme return converters et self converters). Mais concentrons nous pour le moment sur les choses simples.

En route !

Assurez-vous que vous travaillez sur une copie récemment mise à jour du code de CPython.

Trouvez une fonction native de Python qui fait appel à PyArg_ParseTuple() ou PyArg_ParseTupleAndKeywords(), et n’a pas encore été convertie par Argument Clinic. Pour cet exemple, j’utilise _pickle.Pickler.dump().

Si l’appel à PyArg_Parse utilise l’un des formats suivants :

O&
O!
es
es#
et
et#

ou s’il y a de multiples appels à PyArg_ParseTuple(), choisissez une fonction différente. Argument Clinic gère tous ces scénarios, mais se sont des sujets trop avancés pour notre première fonction.

Par ailleurs, si la fonction a des appels multiples à PyArg_ParseTuple() ou PyArg_ParseTupleAndKeywords() dans lesquels elle permet différents types pour les mêmes arguments, il n’est probablement pas possible de la convertir pour Argument Clinic. Argument Clinic ne gère pas les fonctions génériques ou les paramètres polymorphes.

Ajoutez les lignes standard suivantes au-dessus de votre fonction pour créer notre bloc :

/*[clinic input]
[clinic start generated code]*/

Coupez la docstring et collez-la entre les lignes commençant par [clinic], en enlevant tout le bazar qui en fait une chaîne de caractères correcte en C. Une fois que c’est fait, vous devez avoir seulement le texte, aligné à gauche, sans ligne plus longue que 80 caractères (Argument Clinic préserve l’indentation à l’intérieur de la docstring).

Si l’ancienne docstring commençait par une ligne qui ressemble à une signature de fonction, supprimez cette ligne. (Elle n’est plus nécessaire pour la docstring. Dans le futur, quand vous utiliserez help() pour une fonction native, la première ligne sera construite automatiquement à partir de la signature de la fonction.)

Échantillon :

/*[clinic input]
Write a pickled representation of obj to the open file.
[clinic start generated code]*/

Si votre docstring ne contient pas de ligne « résumé », Argument Clinic va se plaindre. Assurons-nous donc qu’il y en a une. La ligne « résumé » doit être un paragraphe consistant en une seule ligne de 80 colonnes au début de la docstring.

Dans notre exemple, la docstring est seulement composée d’une ligne de résumé, donc le code ne change pas à cette étape.

Au dessus de la docstring, entrez le nom de la fonction, suivi d’une ligne vide. Ce doit être le nom de la fonction en Python et être le chemin complet jusqu’à la fonction. Il doit commencer par le nom du module, suivi de tous les sous-modules, puis, si la fonction est une méthode de classe, inclure aussi le nom de la classe.

Échantillon :

/*[clinic input]
_pickle.Pickler.dump

Write a pickled representation of obj to the open file.
[clinic start generated code]*/

Si c’est la première fois que ce module ou cette classe est utilisée avec Argument Clinic dans ce fichier C, vous devez déclarer votre module et/ou votre classe. Pour suivre de bonnes pratiques avec Argument Clinic, il vaut mieux faire ces déclaration quelque part en tête du fichier C, comme les fichiers inclus et les statiques (dans cet extrait, nous montrons les deux blocs à côté l’un de l’autre).

Le nom de la classe et du module doivent être les mêmes que ceux vus par Python. Selon le cas, référez-vous à PyModuleDef ou PyTypeObject

Quand vous déclarez une classe, vous devez aussi spécifier deux aspects de son type en C: la déclaration de type que vous utiliseriez pour un pointeur vers une instance de cette classe et un pointeur vers le PyTypeObject de cette classe.

Échantillon :

/*[clinic input]
module _pickle
class _pickle.Pickler "PicklerObject *" "&Pickler_Type"
[clinic start generated code]*/

/*[clinic input]
_pickle.Pickler.dump

Write a pickled representation of obj to the open file.
[clinic start generated code]*/

Déclarez chacun des paramètres de la fonction. Chaque paramètre doit être sur une ligne séparée. Tous les paramètres doivent être indentés par rapport au nom de la fonction et à la docstring.

La forme générale de ces paramètres est la suivante :

name_of_parameter: converter

Si le paramètre a une valeur par défaut, ajoutez ceci après le convertisseur :

name_of_parameter: converter = default_value

Argument Clinic peut traiter les « valeurs par défaut » de manière assez sophistiquée; voyez la section ci-dessous sur les valeurs par défaut pour plus de détails.

Ajoutez une ligne vide sous les paramètres.

Que fait le « convertisseur » ? Il établit à la fois le type de variable utilisé en C et la méthode pour convertir la valeur Python en valeur C lors de l’exécution. Pour le moment, vous allez utiliser ce qui s’appelle un « convertisseur hérité » – une syntaxe de convenance qui facilite le portage de vieux code dans Argument Clinic.

Pour chaque paramètre, copiez l”« unité de format » de ce paramètre à partir de l’argument de PyArg_Parse() et spécifiez ça comme convertisseur, entre guillemets. (l”« unité de format » est le nom formel pour la partie du paramètre format, de un à trois caractères, qui indique à la fonction d’analyse d’arguments quel est le type de la variable et comment la convertir. Pour plus d’information sur les unités de format, voyez Analyse des arguments et construction des valeurs.)

Pour des unités de format de plusieurs caractères, comme z#, utilisez l’ensemble des 2 ou 3 caractères de la chaîne.

Échantillon :

 /*[clinic input]
 module _pickle
 class _pickle.Pickler "PicklerObject *" "&Pickler_Type"
 [clinic start generated code]*/

 /*[clinic input]
 _pickle.Pickler.dump

    obj: 'O'

Write a pickled representation of obj to the open file.
[clinic start generated code]*/

Si votre fonction a le caractère | dans son format, parce que certains paramètres ont des valeurs par défaut, vous pouvez l’ignorer. Argument Clinic infère quels paramètres sont optionnels selon s’ils ont ou non une valeur par défaut.

Si votre fonction a le caractère $ dans son format, parce qu’elle n’accepte que des arguments nommés, spécifiez * sur une ligne à part, avant le premier argument nommé, avec la même indentation que les lignes de paramètres.

(_pickle.Pickler.dump n’a ni l’un ni l’autre, donc notre exemple est inchangé.)

Si la fonction C existante appelle PyArg_ParseTuple() (et pas PyArg_ParseTupleAndKeywords()), alors tous ses arguments sont uniquement positionnels.

Pour marquer tous les paramètres comme uniquement positionnels dans Argument Clinic, ajoutez / sur une ligne à part après le dernier paramètre, avec la même indentation que les lignes de paramètres.

Pour le moment, c’est tout ou rien ; soit tous les paramètres sont uniquement positionnels, ou aucun ne l’est. (Dans le futur, Argument Clinic supprimera peut être cette restriction.)

Échantillon :

/*[clinic input]
module _pickle
class _pickle.Pickler "PicklerObject *" "&Pickler_Type"
[clinic start generated code]*/

/*[clinic input]
_pickle.Pickler.dump

    obj: 'O'
    /

Write a pickled representation of obj to the open file.
[clinic start generated code]*/

Il est utile d’ajouter une docstring pour chaque paramètre, mais c’est optionnel; vous pouvez passer cette étape si vous préférez.

Voici comment ajouter la docstring d’un paramètre. La première ligne doit être plus indentée que la définition du paramètre. La marge gauche de cette première ligne établit la marge gauche pour l’ensemble de la docstring de ce paramètre; tout le texte que vous écrivez sera indenté de cette quantité. Vous pouvez écrire autant de texte que vous le souhaitez, sur plusieurs lignes.

Échantillon :

/*[clinic input]
module _pickle
class _pickle.Pickler "PicklerObject *" "&Pickler_Type"
[clinic start generated code]*/

/*[clinic input]
_pickle.Pickler.dump

    obj: 'O'
        The object to be pickled.
    /

Write a pickled representation of obj to the open file.
[clinic start generated code]*/

Enregistrez puis fermez le fichier, puis exécutez Tools/clinic/clinic.py dessus. Avec un peu de chance tout a fonctionné, votre bloc a maintenant une sortie, et un fichier .c.h a été généré ! Ré-ouvrez le fichier dans votre éditeur pour voir :

/*[clinic input]
_pickle.Pickler.dump

    obj: 'O'
        The object to be pickled.
    /

Write a pickled representation of obj to the open file.
[clinic start generated code]*/

static PyObject *
_pickle_Pickler_dump(PicklerObject *self, PyObject *obj)
/*[clinic end generated code: output=87ecad1261e02ac7 input=552eb1c0f52260d9]*/

Bien sûr, si Argument Clinic n’a pas produit de sortie, c’est qu’il a rencontré une erreur dans votre entrée. Corrigez vos erreurs et réessayez jusqu’à ce qu’Argument Clinic traite votre fichier sans problème.

Pour plus de visibilité, la plupart du code a été écrit dans un fichier .c.h. Vous devez l’inclure dans votre fichier .c original, typiquement juste après le bloc du module clinic :

#include "clinic/_pickle.c.h"

Vérifiez bien que le code d’analyse d’argument généré par Argument Clinic ressemble bien au code existant.

Assurez vous premièrement que les deux codes utilisent la même fonction pour analyser les arguments. Le code existant doit appeler soit PyArg_ParseTuple() soit PyArg_ParseTupleAndKeywords(); assurez vous que le code généré par Argument Clinic appelle exactement la même fonction.

Deuxièmement, la chaîne de caractère du format passée dans PyArg_ParseTuple() ou PyArg_ParseTupleAndKeywords() doit être exactement la même que celle écrite à la main, jusqu’aux deux points ou au point virgule.

(Argument Clinic génère toujours ses chaînes de format avec : suivi du nom de la fonction. Si la chaîne de format du code existant termine par ;, pour fournir une aide sur l’utilisation, ce changement n’a aucun effet, ne vous en souciez pas.)

Troisièmement, pour des paramètres dont l’unité de format nécessite deux arguments (comme une variable de longueur, ou une chaîne d’encodage, ou un pointeur vers une fonction de conversion), assurez vous que ce deuxième argument est exactement le même entre les deux invocations.

Quatrièmement, à l’intérieur de la section sortie du bloc, vous trouverez une macro pré-processeur qui définit les structures statiques PyMethodDef appropriées pour ce module natif :

#define __PICKLE_PICKLER_DUMP_METHODDEF    \
{"dump", (PyCFunction)__pickle_Pickler_dump, METH_O, __pickle_Pickler_dump__doc__},

Cette structure statique doit être exactement la même que la structure statique PyMethodDef existante pour ce module natif.

Si l’un de ces éléments diffère de quelque façon que se soit, ajustez la spécification de fonction d’Argument Clinic et exécutez de nouveau Tools/clinic/clinic.py jusqu’à ce qu’elles soient identiques.

Notez que la dernière ligne de cette sortie est la déclaration de votre fonction impl. C’est là que va l’implémentation de la fonction native. Supprimez le prototype de la fonction que vous modifiez, mais laissez l’accolade ouverte. Maintenant, supprimez tout le code d’analyse d’argument et les déclarations de toutes les variables auxquelles il assigne les arguments. Vous voyez que désormais, les arguments Python sont ceux de cette fonction impl; si l’implémentation utilise des noms différents pour ces variables, corrigez-les.

Comme c’est un peu bizarre, ça vaut la peine de répéter. Votre fonction doit ressembler à ça :

static return_type
your_function_impl(...)
/*[clinic end generated code: checksum=...]*/
{
...

Argument Clinic génère une ligne de contrôle et la fonction prototype juste au dessus. Vous devez écrire les accolades d’ouverture (et de fermeture) pour la fonction, et l’implémentation à l’intérieur.

Échantillon :

/*[clinic input]
module _pickle
class _pickle.Pickler "PicklerObject *" "&Pickler_Type"
[clinic start generated code]*/
/*[clinic end generated code: checksum=da39a3ee5e6b4b0d3255bfef95601890afd80709]*/

/*[clinic input]
_pickle.Pickler.dump

    obj: 'O'
        The object to be pickled.
    /

Write a pickled representation of obj to the open file.
[clinic start generated code]*/

PyDoc_STRVAR(__pickle_Pickler_dump__doc__,
"Write a pickled representation of obj to the open file.\n"
"\n"
...
static PyObject *
_pickle_Pickler_dump_impl(PicklerObject *self, PyObject *obj)
/*[clinic end generated code: checksum=3bd30745bf206a48f8b576a1da3d90f55a0a4187]*/
{
    /* Check whether the Pickler was initialized correctly (issue3664).
       Developers often forget to call __init__() in their subclasses, which
       would trigger a segfault without this check. */
    if (self->write == NULL) {
        PyErr_Format(PicklingError,
                     "Pickler.__init__() was not called by %s.__init__()",
                     Py_TYPE(self)->tp_name);
        return NULL;
    }

    if (_Pickler_ClearBuffer(self) < 0)
        return NULL;

    ...

Vous vous souvenez de la macro avec la structure PyMethodDef pour cette fonction ? Trouvez la structure PyMethodDef existante pour cette fonction et remplacez là par une référence à cette macro. (Si la fonction native est définie au niveau d’un module, vous le trouverez certainement vers la fin du fichier; s’il s’agît d’une méthode de classe, se sera sans doute plus bas, mais relativement près de l’implémentation.)

Notez que le corps de la macro contient une virgule finale. Donc, lorsque vous remplacez la structure statique PyMethodDef par la macro, n’ajoutez pas de virgule à la fin.

Échantillon :

static struct PyMethodDef Pickler_methods[] = {
    __PICKLE_PICKLER_DUMP_METHODDEF
    __PICKLE_PICKLER_CLEAR_MEMO_METHODDEF
    {NULL, NULL}                /* sentinel */
};

Compilez, puis faites tourner les portions idoines de la suite de tests de régressions. Ce changement ne doit introduire aucun nouveau message d’erreur ou avertissement à la compilation, et il ne devrait y avoir aucun changement visible de l’extérieur au comportement de Python.

Enfin, à part pour une différence : si vous exécutez inspect.signature() sur votre fonction, vous obtiendrez maintenant une signature valide !

Félicitations, vous avez adapté votre première fonction pour qu’elle utilise Argument Clinic !

Sujets avancés

Maintenant que vous avez un peu d’expérience avec Argument Clinic, c’est le moment pour des sujets avancés.

Valeurs par défaut

La valeur par défaut que vous fournissez pour un paramètre ne peut pas être n’importe quelle expression. Actuellement, ce qui est géré :

Constantes numériques (entier ou nombre flottant)

Chaînes constantes

True, False et None

Constantes symboliques simples comme sys.maxsize, qui doivent commencer par le nom du module

Si par curiosité vous voulez lire l’implémentation, c’est from_builtin() dans Lib/inspect.py.

(Dans le futur, il est possible que l’on ait besoin de l’améliorer, pour autoriser les expressions complètes comme CONSTANT - 1.)

Renaming the C functions and variables generated by Argument Clinic

Argument Clinic automatically names the functions it generates for you. Occasionally this may cause a problem, if the generated name collides with the name of an existing C function. There’s an easy solution: override the names used for the C functions. Just add the keyword "as" to your function declaration line, followed by the function name you wish to use. Argument Clinic will use that function name for the base (generated) function, then add "_impl" to the end and use that for the name of the impl function.

Par exemple, si nous voulons renommer les noms de fonction C générés pour pickle.Pickler.dump, ça ressemblerait à ça :

/*[clinic input]
pickle.Pickler.dump as pickler_dumper

...

La fonction de base sera maintenant nommée pickler_dumper(), et la fonction impl serait maintenant nommé pickler_dumper_impl().

De même, vous pouvez avoir un problème quand vous souhaiterez donner à un paramètre un nom spécifique à Python, mais ce nom peut être gênant en C. Argument Clinic vous permet de donner à un paramètre des noms différents en Python et en C :

/*[clinic input]
pickle.Pickler.dump

    obj: object
    file as file_obj: object
    protocol: object = NULL
    *
    fix_imports: bool = True

Here, the name used in Python (in the signature and the keywords array) would be file, but the C variable would be named file_obj.

Vous pouvez utiliser ceci pour renommer aussi le paramètre self

Conversion des fonctions en utilisant PyArg_UnpackTuple

To convert a function parsing its arguments with PyArg_UnpackTuple(), simply write out all the arguments, specifying each as an object. You may specify the type argument to cast the type as appropriate. All arguments should be marked positional-only (add a / on a line by itself after the last argument).

Actuellement, le code généré utilise PyArg_ParseTuple(), mais cela va bientôt changer.

Groupes optionnels

Some legacy functions have a tricky approach to parsing their arguments: they count the number of positional arguments, then use a switch statement to call one of several different PyArg_ParseTuple() calls depending on how many positional arguments there are. (These functions cannot accept keyword-only arguments.) This approach was used to simulate optional arguments back before PyArg_ParseTupleAndKeywords() was created.

While functions using this approach can often be converted to use PyArg_ParseTupleAndKeywords(), optional arguments, and default values, it’s not always possible. Some of these legacy functions have behaviors PyArg_ParseTupleAndKeywords() doesn’t directly support. The most obvious example is the builtin function range(), which has an optional argument on the left side of its required argument! Another example is curses.window.addch(), which has a group of two arguments that must always be specified together. (The arguments are called x and y; if you call the function passing in x, you must also pass in y—and if you don’t pass in x you may not pass in y either.)

In any case, the goal of Argument Clinic is to support argument parsing for all existing CPython builtins without changing their semantics. Therefore Argument Clinic supports this alternate approach to parsing, using what are called optional groups. Optional groups are groups of arguments that must all be passed in together. They can be to the left or the right of the required arguments. They can only be used with positional-only parameters.

Note

Optional groups are only intended for use when converting functions that make multiple calls to PyArg_ParseTuple()! Functions that use any other approach for parsing arguments should almost never be converted to Argument Clinic using optional groups. Functions using optional groups currently cannot have accurate signatures in Python, because Python just doesn’t understand the concept. Please avoid using optional groups wherever possible.

To specify an optional group, add a [ on a line by itself before the parameters you wish to group together, and a ] on a line by itself after these parameters. As an example, here’s how curses.window.addch uses optional groups to make the first two parameters and the last parameter optional:

/*[clinic input]

curses.window.addch

    [
    x: int
      X-coordinate.
    y: int
      Y-coordinate.
    ]

    ch: object
      Character to add.

    [
    attr: long
      Attributes for the character.
    ]
    /

...

Notes :

For every optional group, one additional parameter will be passed into the impl function representing the group. The parameter will be an int named group_{direction}_{number}, where {direction} is either right or left depending on whether the group is before or after the required parameters, and {number} is a monotonically increasing number (starting at 1) indicating how far away the group is from the required parameters. When the impl is called, this parameter will be set to zero if this group was unused, and set to non-zero if this group was used. (By used or unused, I mean whether or not the parameters received arguments in this invocation.)

S’il n’y a pas d’arguments requis, les groupes optionnels se comportent comme s’ils étaient à droite des arguments requis.

In the case of ambiguity, the argument parsing code favors parameters on the left (before the required parameters).

Optional groups can only contain positional-only parameters.

Les groupes optionnels sont seulement destinés au code hérité. Ne les utilisez pas dans du nouveau code.

Using real Argument Clinic converters, instead of « legacy converters »

To save time, and to minimize how much you need to learn to achieve your first port to Argument Clinic, the walkthrough above tells you to use « legacy converters ». « Legacy converters » are a convenience, designed explicitly to make porting existing code to Argument Clinic easier. And to be clear, their use is acceptable when porting code for Python 3.4.

However, in the long term we probably want all our blocks to use Argument Clinic’s real syntax for converters. Why? A couple reasons:

The proper converters are far easier to read and clearer in their intent.

There are some format units that are unsupported as « legacy converters », because they require arguments, and the legacy converter syntax doesn’t support specifying arguments.

In the future we may have a new argument parsing library that isn’t restricted to what PyArg_ParseTuple() supports; this flexibility won’t be available to parameters using legacy converters.

Therefore, if you don’t mind a little extra effort, please use the normal converters instead of legacy converters.

In a nutshell, the syntax for Argument Clinic (non-legacy) converters looks like a Python function call. However, if there are no explicit arguments to the function (all functions take their default values), you may omit the parentheses. Thus bool and bool() are exactly the same converters.

All arguments to Argument Clinic converters are keyword-only. All Argument Clinic converters accept the following arguments:

c_default

The default value for this parameter when defined in C. Specifically, this will be the initializer for the variable declared in the « parse function ». See the section on default values for how to use this. Specified as a string.

annotation

The annotation value for this parameter. Not currently supported, because PEP 8 mandates that the Python library may not use annotations.

In addition, some converters accept additional arguments. Here is a list of these arguments, along with their meanings:

accept

A set of Python types (and possibly pseudo-types); this restricts the allowable Python argument to values of these types. (This is not a general-purpose facility; as a rule it only supports specific lists of types as shown in the legacy converter table.)

To accept None, add NoneType to this set.

bitwise

Only supported for unsigned integers. The native integer value of this Python argument will be written to the parameter without any range checking, even for negative values.

converter

Only supported by the object converter. Specifies the name of a C « converter function » to use to convert this object to a native type.

encoding

Only supported for strings. Specifies the encoding to use when converting this string from a Python str (Unicode) value into a C char * value.

subclass_of

Only supported for the object converter. Requires that the Python value be a subclass of a Python type, as expressed in C.

type

Only supported for the object and self converters. Specifies the C type that will be used to declare the variable. Default value is "PyObject *".

zeroes

Only supported for strings. If true, embedded NUL bytes ('\\0') are permitted inside the value. The length of the string will be passed in to the impl function, just after the string parameter, as a parameter named <parameter_name>_length.

Please note, not every possible combination of arguments will work. Usually these arguments are implemented by specific PyArg_ParseTuple format units, with specific behavior. For example, currently you cannot call unsigned_short without also specifying bitwise=True. Although it’s perfectly reasonable to think this would work, these semantics don’t map to any existing format unit. So Argument Clinic doesn’t support it. (Or, at least, not yet.)

Below is a table showing the mapping of legacy converters into real Argument Clinic converters. On the left is the legacy converter, on the right is the text you’d replace it with.

'B'

unsigned_char(bitwise=True)

'b'

unsigned_char

'c'

char

'C'

int(accept={str})

'd'

double

'D'

Py_complex

'es'

str(encoding='name_of_encoding')

'es#'

str(encoding='name_of_encoding', zeroes=True)

'et'

str(encoding='name_of_encoding', accept={bytes, bytearray, str})

'et#'

str(encoding='name_of_encoding', accept={bytes, bytearray, str}, zeroes=True)

'f'

float

'h'

short

'H'

unsigned_short(bitwise=True)

'i'

int

'I'

unsigned_int(bitwise=True)

'k'

unsigned_long(bitwise=True)

'K'

unsigned_long_long(bitwise=True)

'l'

long

'L'

long long

'n'

Py_ssize_t

'O'

object

'O!'

object(subclass_of='&PySomething_Type')

'O&'

object(converter='name_of_c_function')

'p'

bool

'S'

PyBytesObject

's'

str

's#'

str(zeroes=True)

's*'

Py_buffer(accept={buffer, str})

'U'

unicode

'u'

Py_UNICODE

'u#'

Py_UNICODE(zeroes=True)

'w*'

Py_buffer(accept={rwbuffer})

'Y'

PyByteArrayObject

'y'

str(accept={bytes})

'y#'

str(accept={robuffer}, zeroes=True)

'y*'

Py_buffer

'Z'

Py_UNICODE(accept={str, NoneType})

'Z#'

Py_UNICODE(accept={str, NoneType}, zeroes=True)

'z'

str(accept={str, NoneType})

'z#'

str(accept={str, NoneType}, zeroes=True)

'z*'

Py_buffer(accept={buffer, str, NoneType})

As an example, here’s our sample pickle.Pickler.dump using the proper converter:

/*[clinic input]
pickle.Pickler.dump

    obj: object
        The object to be pickled.
    /

Write a pickled representation of obj to the open file.
[clinic start generated code]*/

Argument Clinic will show you all the converters it has available. For each converter it’ll show you all the parameters it accepts, along with the default value for each parameter. Just run Tools/clinic/clinic.py --converters to see the full list.

Py_buffer

When using the Py_buffer converter (or the 's*', 'w*', '*y', or 'z*' legacy converters), you must not call PyBuffer_Release() on the provided buffer. Argument Clinic generates code that does it for you (in the parsing function).

Advanced converters

Remember those format units you skipped for your first time because they were advanced? Here’s how to handle those too.

The trick is, all those format units take arguments—either conversion functions, or types, or strings specifying an encoding. (But « legacy converters » don’t support arguments. That’s why we skipped them for your first function.) The argument you specified to the format unit is now an argument to the converter; this argument is either converter (for O&), subclass_of (for O!), or encoding (for all the format units that start with e).

When using subclass_of, you may also want to use the other custom argument for object(): type, which lets you set the type actually used for the parameter. For example, if you want to ensure that the object is a subclass of PyUnicode_Type, you probably want to use the converter object(type='PyUnicodeObject *', subclass_of='&PyUnicode_Type').

One possible problem with using Argument Clinic: it takes away some possible flexibility for the format units starting with e. When writing a PyArg_Parse call by hand, you could theoretically decide at runtime what encoding string to pass in to PyArg_ParseTuple(). But now this string must be hard-coded at Argument-Clinic-preprocessing-time. This limitation is deliberate; it made supporting this format unit much easier, and may allow for future optimizations. This restriction doesn’t seem unreasonable; CPython itself always passes in static hard-coded encoding strings for parameters whose format units start with e.

Parameter default values

Default values for parameters can be any of a number of values. At their simplest, they can be string, int, or float literals:

foo: str = "abc"
bar: int = 123
bat: float = 45.6

They can also use any of Python’s built-in constants:

yep:  bool = True
nope: bool = False
nada: object = None

There’s also special support for a default value of NULL, and for simple expressions, documented in the following sections.

The NULL default value

For string and object parameters, you can set them to None to indicate that there’s no default. However, that means the C variable will be initialized to Py_None. For convenience’s sakes, there’s a special value called NULL for just this reason: from Python’s perspective it behaves like a default value of None, but the C variable is initialized with NULL.

Expressions specified as default values

The default value for a parameter can be more than just a literal value. It can be an entire expression, using math operators and looking up attributes on objects. However, this support isn’t exactly simple, because of some non-obvious semantics.

Consider the following example:

foo: Py_ssize_t = sys.maxsize - 1

sys.maxsize can have different values on different platforms. Therefore Argument Clinic can’t simply evaluate that expression locally and hard-code it in C. So it stores the default in such a way that it will get evaluated at runtime, when the user asks for the function’s signature.

What namespace is available when the expression is evaluated? It’s evaluated in the context of the module the builtin came from. So, if your module has an attribute called « max_widgets », you may simply use it:

foo: Py_ssize_t = max_widgets

If the symbol isn’t found in the current module, it fails over to looking in sys.modules. That’s how it can find sys.maxsize for example. (Since you don’t know in advance what modules the user will load into their interpreter, it’s best to restrict yourself to modules that are preloaded by Python itself.)

Evaluating default values only at runtime means Argument Clinic can’t compute the correct equivalent C default value. So you need to tell it explicitly. When you use an expression, you must also specify the equivalent expression in C, using the c_default parameter to the converter:

foo: Py_ssize_t(c_default="PY_SSIZE_T_MAX - 1") = sys.maxsize - 1

Another complication: Argument Clinic can’t know in advance whether or not the expression you supply is valid. It parses it to make sure it looks legal, but it can’t actually know. You must be very careful when using expressions to specify values that are guaranteed to be valid at runtime!

Finally, because expressions must be representable as static C values, there are many restrictions on legal expressions. Here’s a list of Python features you’re not permitted to use:

Function calls.

Inline if statements (3 if foo else 5).

Automatic sequence unpacking (*[1, 2, 3]).

List/set/dict comprehensions and generator expressions.

Tuple/list/set/dict literals.

Using a return converter

By default the impl function Argument Clinic generates for you returns PyObject *. But your C function often computes some C type, then converts it into the PyObject * at the last moment. Argument Clinic handles converting your inputs from Python types into native C types—why not have it convert your return value from a native C type into a Python type too?

That’s what a « return converter » does. It changes your impl function to return some C type, then adds code to the generated (non-impl) function to handle converting that value into the appropriate PyObject *.

The syntax for return converters is similar to that of parameter converters. You specify the return converter like it was a return annotation on the function itself. Return converters behave much the same as parameter converters; they take arguments, the arguments are all keyword-only, and if you’re not changing any of the default arguments you can omit the parentheses.

(If you use both "as" and a return converter for your function, the "as" should come before the return converter.)

There’s one additional complication when using return converters: how do you indicate an error has occurred? Normally, a function returns a valid (non-NULL) pointer for success, and NULL for failure. But if you use an integer return converter, all integers are valid. How can Argument Clinic detect an error? Its solution: each return converter implicitly looks for a special value that indicates an error. If you return that value, and an error has been set (PyErr_Occurred() returns a true value), then the generated code will propagate the error. Otherwise it will encode the value you return like normal.

Currently Argument Clinic supports only a few return converters:

bool
int
unsigned int
long
unsigned int
size_t
Py_ssize_t
float
double
DecodeFSDefault

None of these take parameters. For the first three, return -1 to indicate error. For DecodeFSDefault, the return type is char *; return a NULL pointer to indicate an error.

(There’s also an experimental NoneType converter, which lets you return Py_None on success or NULL on failure, without having to increment the reference count on Py_None. I’m not sure it adds enough clarity to be worth using.)

To see all the return converters Argument Clinic supports, along with their parameters (if any), just run Tools/clinic/clinic.py --converters for the full list.

Cloning existing functions

If you have a number of functions that look similar, you may be able to use Clinic’s « clone » feature. When you clone an existing function, you reuse:

its parameters, including

their names,

their converters, with all parameters,

their default values,

their per-parameter docstrings,

their kind (whether they’re positional only, positional or keyword, or keyword only), and

its return converter.

The only thing not copied from the original function is its docstring; the syntax allows you to specify a new docstring.

Here’s the syntax for cloning a function:

/*[clinic input]
module.class.new_function [as c_basename] = module.class.existing_function

Docstring for new_function goes here.
[clinic start generated code]*/

(The functions can be in different modules or classes. I wrote module.class in the sample just to illustrate that you must use the full path to both functions.)

Sorry, there’s no syntax for partially-cloning a function, or cloning a function then modifying it. Cloning is an all-or nothing proposition.

Also, the function you are cloning from must have been previously defined in the current file.

Calling Python code

The rest of the advanced topics require you to write Python code which lives inside your C file and modifies Argument Clinic’s runtime state. This is simple: you simply define a Python block.

A Python block uses different delimiter lines than an Argument Clinic function block. It looks like this:

/*[python input]
# python code goes here
[python start generated code]*/

All the code inside the Python block is executed at the time it’s parsed. All text written to stdout inside the block is redirected into the « output » after the block.

As an example, here’s a Python block that adds a static integer variable to the C code:

/*[python input]
print('static int __ignored_unused_variable__ = 0;')
[python start generated code]*/
static int __ignored_unused_variable__ = 0;
/*[python checksum:...]*/

Using a « self converter »

Argument Clinic automatically adds a « self » parameter for you using a default converter. It automatically sets the type of this parameter to the « pointer to an instance » you specified when you declared the type. However, you can override Argument Clinic’s converter and specify one yourself. Just add your own self parameter as the first parameter in a block, and ensure that its converter is an instance of self_converter or a subclass thereof.

What’s the point? This lets you override the type of self, or give it a different default name.

How do you specify the custom type you want to cast self to? If you only have one or two functions with the same type for self, you can directly use Argument Clinic’s existing self converter, passing in the type you want to use as the type parameter:

/*[clinic input]

_pickle.Pickler.dump

  self: self(type="PicklerObject *")
  obj: object
  /

Write a pickled representation of the given object to the open file.
[clinic start generated code]*/

On the other hand, if you have a lot of functions that will use the same type for self, it’s best to create your own converter, subclassing self_converter but overwriting the type member:

/*[python input]
class PicklerObject_converter(self_converter):
    type = "PicklerObject *"
[python start generated code]*/

/*[clinic input]

_pickle.Pickler.dump

  self: PicklerObject
  obj: object
  /

Write a pickled representation of the given object to the open file.
[clinic start generated code]*/

Writing a custom converter

As we hinted at in the previous section… you can write your own converters! A converter is simply a Python class that inherits from CConverter. The main purpose of a custom converter is if you have a parameter using the O& format unit—parsing this parameter means calling a PyArg_ParseTuple() « converter function ».

Your converter class should be named *something*_converter. If the name follows this convention, then your converter class will be automatically registered with Argument Clinic; its name will be the name of your class with the _converter suffix stripped off. (This is accomplished with a metaclass.)

You shouldn’t subclass CConverter.__init__. Instead, you should write a converter_init() function. converter_init() always accepts a self parameter; after that, all additional parameters must be keyword-only. Any arguments passed in to the converter in Argument Clinic will be passed along to your converter_init().

There are some additional members of CConverter you may wish to specify in your subclass. Here’s the current list:

type

The C type to use for this variable. type should be a Python string specifying the type, e.g. int. If this is a pointer type, the type string should end with ' *'.

default

The Python default value for this parameter, as a Python value. Or the magic value unspecified if there is no default.

py_default

default as it should appear in Python code, as a string. Or None if there is no default.

c_default

default as it should appear in C code, as a string. Or None if there is no default.

c_ignored_default

The default value used to initialize the C variable when there is no default, but not specifying a default may result in an « uninitialized variable » warning. This can easily happen when using option groups—although properly-written code will never actually use this value, the variable does get passed in to the impl, and the C compiler will complain about the « use » of the uninitialized value. This value should always be a non-empty string.

converter

The name of the C converter function, as a string.

impl_by_reference

A boolean value. If true, Argument Clinic will add a & in front of the name of the variable when passing it into the impl function.

parse_by_reference

A boolean value. If true, Argument Clinic will add a & in front of the name of the variable when passing it into PyArg_ParseTuple().

Here’s the simplest example of a custom converter, from Modules/zlibmodule.c:

/*[python input]

class ssize_t_converter(CConverter):
    type = 'Py_ssize_t'
    converter = 'ssize_t_converter'

[python start generated code]*/
/*[python end generated code: output=da39a3ee5e6b4b0d input=35521e4e733823c7]*/

This block adds a converter to Argument Clinic named ssize_t. Parameters declared as ssize_t will be declared as type Py_ssize_t, and will be parsed by the 'O&' format unit, which will call the ssize_t_converter converter function. ssize_t variables automatically support default values.

More sophisticated custom converters can insert custom C code to handle initialization and cleanup. You can see more examples of custom converters in the CPython source tree; grep the C files for the string CConverter.

Writing a custom return converter

Writing a custom return converter is much like writing a custom converter. Except it’s somewhat simpler, because return converters are themselves much simpler.

Return converters must subclass CReturnConverter. There are no examples yet of custom return converters, because they are not widely used yet. If you wish to write your own return converter, please read Tools/clinic/clinic.py, specifically the implementation of CReturnConverter and all its subclasses.

METH_O and METH_NOARGS

To convert a function using METH_O, make sure the function’s single argument is using the object converter, and mark the arguments as positional-only:

/*[clinic input]
meth_o_sample

     argument: object
     /
[clinic start generated code]*/

To convert a function using METH_NOARGS, just don’t specify any arguments.

You can still use a self converter, a return converter, and specify a type argument to the object converter for METH_O.

tp_new and tp_init functions

You can convert tp_new and tp_init functions. Just name them __new__ or __init__ as appropriate. Notes:

The function name generated for __new__ doesn’t end in __new__ like it would by default. It’s just the name of the class, converted into a valid C identifier.

No PyMethodDef #define is generated for these functions.

__init__ functions return int, not PyObject *.

Use the docstring as the class docstring.

Although __new__ and __init__ functions must always accept both the args and kwargs objects, when converting you may specify any signature for these functions that you like. (If your function doesn’t support keywords, the parsing function generated will throw an exception if it receives any.)

Changing and redirecting Clinic’s output

It can be inconvenient to have Clinic’s output interspersed with your conventional hand-edited C code. Luckily, Clinic is configurable: you can buffer up its output for printing later (or earlier!), or write its output to a separate file. You can also add a prefix or suffix to every line of Clinic’s generated output.

While changing Clinic’s output in this manner can be a boon to readability, it may result in Clinic code using types before they are defined, or your code attempting to use Clinic-generated code before it is defined. These problems can be easily solved by rearranging the declarations in your file, or moving where Clinic’s generated code goes. (This is why the default behavior of Clinic is to output everything into the current block; while many people consider this hampers readability, it will never require rearranging your code to fix definition-before-use problems.)

Let’s start with defining some terminology:

field

A field, in this context, is a subsection of Clinic’s output. For example, the #define for the PyMethodDef structure is a field, called methoddef_define. Clinic has seven different fields it can output per function definition:

docstring_prototype
docstring_definition
methoddef_define
impl_prototype
parser_prototype
parser_definition
impl_definition

All the names are of the form "<a>_<b>", where "<a>" is the semantic object represented (the parsing function, the impl function, the docstring, or the methoddef structure) and "<b>" represents what kind of statement the field is. Field names that end in "_prototype" represent forward declarations of that thing, without the actual body/data of the thing; field names that end in "_definition" represent the actual definition of the thing, with the body/data of the thing. ("methoddef" is special, it’s the only one that ends with "_define", representing that it’s a preprocessor #define.)

destination

A destination is a place Clinic can write output to. There are five built-in destinations:

block

The default destination: printed in the output section of the current Clinic block.

buffer

A text buffer where you can save text for later. Text sent here is appended to the end of any existing text. It’s an error to have any text left in the buffer when Clinic finishes processing a file.

file

A separate « clinic file » that will be created automatically by Clinic. The filename chosen for the file is {basename}.clinic{extension}, where basename and extension were assigned the output from os.path.splitext() run on the current file. (Example: the file destination for _pickle.c would be written to _pickle.clinic.c.)

Important: When using a file destination, you must check in the generated file!

two-pass

A buffer like buffer. However, a two-pass buffer can only be dumped once, and it prints out all text sent to it during all processing, even from Clinic blocks after the dumping point.

suppress

The text is suppressed—thrown away.

Clinic defines five new directives that let you reconfigure its output.

The first new directive is dump:

dump <destination>

This dumps the current contents of the named destination into the output of the current block, and empties it. This only works with buffer and two-pass destinations.

The second new directive is output. The most basic form of output is like this:

output <field> <destination>

This tells Clinic to output field to destination. output also supports a special meta-destination, called everything, which tells Clinic to output all fields to that destination.

output has a number of other functions:

output push
output pop
output preset <preset>

output push and output pop allow you to push and pop configurations on an internal configuration stack, so that you can temporarily modify the output configuration, then easily restore the previous configuration. Simply push before your change to save the current configuration, then pop when you wish to restore the previous configuration.

output preset sets Clinic’s output to one of several built-in preset configurations, as follows:

block

Clinic’s original starting configuration. Writes everything immediately after the input block.

Suppress the parser_prototype and docstring_prototype, write everything else to block.

file

Designed to write everything to the « clinic file » that it can. You then #include this file near the top of your file. You may need to rearrange your file to make this work, though usually this just means creating forward declarations for various typedef and PyTypeObject definitions.

Suppress the parser_prototype and docstring_prototype, write the impl_definition to block, and write everything else to file.

The default filename is "{dirname}/clinic/{basename}.h".

buffer

Save up most of the output from Clinic, to be written into your file near the end. For Python files implementing modules or builtin types, it’s recommended that you dump the buffer just above the static structures for your module or builtin type; these are normally very near the end. Using buffer may require even more editing than file, if your file has static PyMethodDef arrays defined in the middle of the file.

Suppress the parser_prototype, impl_prototype, and docstring_prototype, write the impl_definition to block, and write everything else to file.

two-pass

Similar to the buffer preset, but writes forward declarations to the two-pass buffer, and definitions to the buffer. This is similar to the buffer preset, but may require less editing than buffer. Dump the two-pass buffer near the top of your file, and dump the buffer near the end just like you would when using the buffer preset.

Suppresses the impl_prototype, write the impl_definition to block, write docstring_prototype, methoddef_define, and parser_prototype to two-pass, write everything else to buffer.

partial-buffer

Similar to the buffer preset, but writes more things to block, only writing the really big chunks of generated code to buffer. This avoids the definition-before-use problem of buffer completely, at the small cost of having slightly more stuff in the block’s output. Dump the buffer near the end, just like you would when using the buffer preset.

Suppresses the impl_prototype, write the docstring_definition and parser_definition to buffer, write everything else to block.

The third new directive is destination:

destination <name> <command> [...]

This performs an operation on the destination named name.

There are two defined subcommands: new and clear.

The new subcommand works like this:

destination <name> new <type>

This creates a new destination with name <name> and type <type>.

There are five destination types:

suppress

Throws the text away.

block

Writes the text to the current block. This is what Clinic originally did.

buffer

A simple text buffer, like the « buffer » builtin destination above.

file

A text file. The file destination takes an extra argument, a template to use for building the filename, like so:

destination <name> new <type> <file_template>

The template can use three strings internally that will be replaced by bits of the filename:

{path}

The full path to the file, including directory and full filename.

{dirname}

The name of the directory the file is in.

{basename}

Just the name of the file, not including the directory.

{basename_root}

Basename with the extension clipped off (everything up to but not including the last “.”).

{basename_extension}

The last “.” and everything after it. If the basename does not contain a period, this will be the empty string.

If there are no periods in the filename, {basename} and {filename} are the same, and {extension} is empty. « {basename}{extension} » is always exactly the same as « {filename} ». »

two-pass

A two-pass buffer, like the « two-pass » builtin destination above.

The clear subcommand works like this:

destination <name> clear

It removes all the accumulated text up to this point in the destination. (I don’t know what you’d need this for, but I thought maybe it’d be useful while someone’s experimenting.)

The fourth new directive is set:

set line_prefix "string"
set line_suffix "string"

set lets you set two internal variables in Clinic. line_prefix is a string that will be prepended to every line of Clinic’s output; line_suffix is a string that will be appended to every line of Clinic’s output.

Both of these support two format strings:

{block comment start}

Turns into the string /*, the start-comment text sequence for C files.

{block comment end}

Turns into the string */, the end-comment text sequence for C files.

The final new directive is one you shouldn’t need to use directly, called preserve:

preserve

This tells Clinic that the current contents of the output should be kept, unmodified. This is used internally by Clinic when dumping output into file files; wrapping it in a Clinic block lets Clinic use its existing checksum functionality to ensure the file was not modified by hand before it gets overwritten.

The #ifdef trick

If you’re converting a function that isn’t available on all platforms, there’s a trick you can use to make life a little easier. The existing code probably looks like this:

#ifdef HAVE_FUNCTIONNAME
static module_functionname(...)
{
...
}
#endif /* HAVE_FUNCTIONNAME */

And then in the PyMethodDef structure at the bottom the existing code will have:

#ifdef HAVE_FUNCTIONNAME
{'functionname', ... },
#endif /* HAVE_FUNCTIONNAME */

In this scenario, you should enclose the body of your impl function inside the #ifdef, like so:

#ifdef HAVE_FUNCTIONNAME
/*[clinic input]
module.functionname
...
[clinic start generated code]*/
static module_functionname(...)
{
...
}
#endif /* HAVE_FUNCTIONNAME */

Then, remove those three lines from the PyMethodDef structure, replacing them with the macro Argument Clinic generated:

MODULE_FUNCTIONNAME_METHODDEF

(You can find the real name for this macro inside the generated code. Or you can calculate it yourself: it’s the name of your function as defined on the first line of your block, but with periods changed to underscores, uppercased, and "_METHODDEF" added to the end.)

Perhaps you’re wondering: what if HAVE_FUNCTIONNAME isn’t defined? The MODULE_FUNCTIONNAME_METHODDEF macro won’t be defined either!

Here’s where Argument Clinic gets very clever. It actually detects that the Argument Clinic block might be deactivated by the #ifdef. When that happens, it generates a little extra code that looks like this:

#ifndef MODULE_FUNCTIONNAME_METHODDEF
    #define MODULE_FUNCTIONNAME_METHODDEF
#endif /* !defined(MODULE_FUNCTIONNAME_METHODDEF) */

That means the macro always works. If the function is defined, this turns into the correct structure, including the trailing comma. If the function is undefined, this turns into nothing.

However, this causes one ticklish problem: where should Argument Clinic put this extra code when using the « block » output preset? It can’t go in the output block, because that could be deactivated by the #ifdef. (That’s the whole point!)

In this situation, Argument Clinic writes the extra code to the « buffer » destination. This may mean that you get a complaint from Argument Clinic:

Warning in file "Modules/posixmodule.c" on line 12357:
Destination buffer 'buffer' not empty at end of file, emptying.

When this happens, just open your file, find the dump buffer block that Argument Clinic added to your file (it’ll be at the very bottom), then move it above the PyMethodDef structure where that macro is used.

Using Argument Clinic in Python files

It’s actually possible to use Argument Clinic to preprocess Python files. There’s no point to using Argument Clinic blocks, of course, as the output wouldn’t make any sense to the Python interpreter. But using Argument Clinic to run Python blocks lets you use Python as a Python preprocessor!

Since Python comments are different from C comments, Argument Clinic blocks embedded in Python files look slightly different. They look like this:

#/*[python input]
#print("def foo(): pass")
#[python start generated code]*/
def foo(): pass
#/*[python checksum:...]*/

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Instrumenter CPython avec DTrace et SystemTap

auteur

David Malcolm

auteur

Łukasz Langa

DTrace et SystemTap sont des outils de surveillance, chacun fournissant un moyen de d’inspecter ce que font les processus d’un système informatique. Ils utilisent tous les deux des langages dédiés permettant à un utilisateur d’écrire des scripts qui permettent de :

Filtrer les processus à observer.

Recueillir des données sur le processus choisi.

Générer des rapports sur les données.

À partir de Python 3.6, CPython peut être compilé avec des « marqueurs » intégrés, aussi appelés « sondes », qui peuvent être observés par un script DTrace ou SystemTap, ce qui facilite le suivi des processus CPython.

CPython implementation detail: Les marqueurs DTrace sont des détails d’implémentation de l’interpréteur CPython. Aucune garantie n’est donnée quant à la compatibilité des sondes entre les versions de CPython. Les scripts DTrace peuvent s’arrêter de fonctionner ou fonctionner incorrectement sans avertissement lors du changement de version de CPython.

Activer les marqueurs statiques

macOS est livré avec un support intégré pour DTrace. Sous Linux, pour construire CPython avec les marqueurs embarqués pour SystemTap, les outils de développement SystemTap doivent être installés.

Sur une machine Linux, cela se fait via :

$ yum install systemtap-sdt-devel

ou :

$ sudo apt-get install systemtap-sdt-dev

CPython doit être configuré avec l’option --with-dtrace :

checking for --with-dtrace... yes

Sous macOS, vous pouvez lister les sondes DTrace disponibles en exécutant un processus Python en arrière-plan et en listant toutes les sondes mises à disposition par le fournisseur Python :

$ python3.6 -q &
$ sudo dtrace -l -P python$!  # or: dtrace -l -m python3.6

   ID   PROVIDER            MODULE                          FUNCTION NAME
29564 python18035        python3.6          _PyEval_EvalFrameDefault function-entry
29565 python18035        python3.6             dtrace_function_entry function-entry
29566 python18035        python3.6          _PyEval_EvalFrameDefault function-return
29567 python18035        python3.6            dtrace_function_return function-return
29568 python18035        python3.6                           collect gc-done
29569 python18035        python3.6                           collect gc-start
29570 python18035        python3.6          _PyEval_EvalFrameDefault line
29571 python18035        python3.6                 maybe_dtrace_line line

Sous Linux, pour vérifier que les marqueurs statiques SystemTap sont présents dans le binaire compilé, il suffit de regarder s’il contient une section .note.stapsdt.

$ readelf -S ./python | grep .note.stapsdt
[30] .note.stapsdt        NOTE         0000000000000000 00308d78

Si vous avez compilé Python en tant que bibliothèque partagée (avec --enable-shared), vous devez plutôt regarder dans la bibliothèque partagée. Par exemple :

$ readelf -S libpython3.3dm.so.1.0 | grep .note.stapsdt
[29] .note.stapsdt        NOTE         0000000000000000 00365b68

Une version suffisamment moderne de readelf peut afficher les métadonnées :

$ readelf -n ./python

Displaying notes found at file offset 0x00000254 with length 0x00000020:
    Owner                 Data size          Description
    GNU                  0x00000010          NT_GNU_ABI_TAG (ABI version tag)
        OS: Linux, ABI: 2.6.32

Displaying notes found at file offset 0x00000274 with length 0x00000024:
    Owner                 Data size          Description
    GNU                  0x00000014          NT_GNU_BUILD_ID (unique build ID bitstring)
        Build ID: df924a2b08a7e89f6e11251d4602022977af2670

Displaying notes found at file offset 0x002d6c30 with length 0x00000144:
    Owner                 Data size          Description
    stapsdt              0x00000031          NT_STAPSDT (SystemTap probe descriptors)
        Provider: python
        Name: gc__start
        Location: 0x00000000004371c3, Base: 0x0000000000630ce2, Semaphore: 0x00000000008d6bf6
        Arguments: -4@%ebx
    stapsdt              0x00000030          NT_STAPSDT (SystemTap probe descriptors)
        Provider: python
        Name: gc__done
        Location: 0x00000000004374e1, Base: 0x0000000000630ce2, Semaphore: 0x00000000008d6bf8
        Arguments: -8@%rax
    stapsdt              0x00000045          NT_STAPSDT (SystemTap probe descriptors)
        Provider: python
        Name: function__entry
        Location: 0x000000000053db6c, Base: 0x0000000000630ce2, Semaphore: 0x00000000008d6be8
        Arguments: 8@%rbp 8@%r12 -4@%eax
    stapsdt              0x00000046          NT_STAPSDT (SystemTap probe descriptors)
        Provider: python
        Name: function__return
        Location: 0x000000000053dba8, Base: 0x0000000000630ce2, Semaphore: 0x00000000008d6bea
        Arguments: 8@%rbp 8@%r12 -4@%eax

Les métadonnées ci-dessus contiennent des informations pour SystemTap décrivant comment il peut mettre à jour des instructions de code machine stratégiquement placées pour activer les crochets de traçage utilisés par un script SystemTap.

Sondes DTrace statiques

L’exemple suivant de script DTrace montre la hiérarchie d’appel/retour d’un script Python, en ne traçant que l’invocation d’une fonction start. En d’autres termes, les appels de fonctions lors de la phase d’import ne seront pas répertoriées :

self int indent;

python$target:::function-entry
/copyinstr(arg1) == "start"/
{
        self->trace = 1;
}

python$target:::function-entry
/self->trace/
{
        printf("%d\t%*s:", timestamp, 15, probename);
        printf("%*s", self->indent, "");
        printf("%s:%s:%d\n", basename(copyinstr(arg0)), copyinstr(arg1), arg2);
        self->indent++;
}

python$target:::function-return
/self->trace/
{
        self->indent--;
        printf("%d\t%*s:", timestamp, 15, probename);
        printf("%*s", self->indent, "");
        printf("%s:%s:%d\n", basename(copyinstr(arg0)), copyinstr(arg1), arg2);
}

python$target:::function-return
/copyinstr(arg1) == "start"/
{
        self->trace = 0;
}

Il peut être utilisé de cette manière :

$ sudo dtrace -q -s call_stack.d -c "python3.6 script.py"

La sortie ressemble à ceci :

156641360502280  function-entry:call_stack.py:start:23
156641360518804  function-entry: call_stack.py:function_1:1
156641360532797  function-entry:  call_stack.py:function_3:9
156641360546807 function-return:  call_stack.py:function_3:10
156641360563367 function-return: call_stack.py:function_1:2
156641360578365  function-entry: call_stack.py:function_2:5
156641360591757  function-entry:  call_stack.py:function_1:1
156641360605556  function-entry:   call_stack.py:function_3:9
156641360617482 function-return:   call_stack.py:function_3:10
156641360629814 function-return:  call_stack.py:function_1:2
156641360642285 function-return: call_stack.py:function_2:6
156641360656770  function-entry: call_stack.py:function_3:9
156641360669707 function-return: call_stack.py:function_3:10
156641360687853  function-entry: call_stack.py:function_4:13
156641360700719 function-return: call_stack.py:function_4:14
156641360719640  function-entry: call_stack.py:function_5:18
156641360732567 function-return: call_stack.py:function_5:21
156641360747370 function-return:call_stack.py:start:28

Marqueurs statiques SystemTap

La façon la plus simple d’utiliser l’intégration SystemTap est d’utiliser directement les marqueurs statiques. Pour cela vous devez pointer explicitement le fichier binaire qui les contient.

Par exemple, ce script SystemTap peut être utilisé pour afficher la hiérarchie d’appel/retour d’un script Python :

probe process("python").mark("function__entry") {
     filename = user_string($arg1);
     funcname = user_string($arg2);
     lineno = $arg3;

     printf("%s => %s in %s:%d\\n",
            thread_indent(1), funcname, filename, lineno);
}

probe process("python").mark("function__return") {
    filename = user_string($arg1);
    funcname = user_string($arg2);
    lineno = $arg3;

    printf("%s <= %s in %s:%d\\n",
           thread_indent(-1), funcname, filename, lineno);
}

Il peut être utilisé de cette manière :

$ stap \
  show-call-hierarchy.stp \
  -c "./python test.py"

La sortie ressemble à ceci :

11408 python(8274):        => __contains__ in Lib/_abcoll.py:362
11414 python(8274):         => __getitem__ in Lib/os.py:425
11418 python(8274):          => encode in Lib/os.py:490
11424 python(8274):          <= encode in Lib/os.py:493
11428 python(8274):         <= __getitem__ in Lib/os.py:426
11433 python(8274):        <= __contains__ in Lib/_abcoll.py:366

où les colonnes sont :

temps en microsecondes depuis le début du script

nom de l’exécutable

PID du processus

et le reste indique la hiérarchie d’appel/retour lorsque le script s’exécute.

Pour une compilation –enable-shared de CPython, les marqueurs sont contenus dans la bibliothèque partagée libpython, et le chemin du module de la sonde doit le refléter. Par exemple, la ligne de l’exemple ci-dessus :

probe process("python").mark("function__entry") {

doit plutôt se lire comme :

probe process("python").library("libpython3.6dm.so.1.0").mark("function__entry") {

(en supposant une version compilée avec le débogage activé de CPython 3.6)

Marqueurs statiques disponibles

function__entry(str filename, str funcname, int lineno)

Ce marqueur indique que l’exécution d’une fonction Python a commencé. Il n’est déclenché que pour les fonctions en Python pur (code intermédiaire).

Le nom de fichier, le nom de la fonction et le numéro de ligne sont renvoyés au script de traçage sous forme d’arguments positionnels, auxquels il faut accéder en utilisant $arg1, $arg2, $arg3 :

$arg1 : (const char *) nom de fichier, accessible via user_string($arg1)

$arg2 : (const char *) nom de la fonction, accessible via user_string($arg2)

$arg3 : numéro de ligne int

function__return(str filename, str funcname, int lineno)

Ce marqueur est l’inverse de function__entry(), et indique que l’exécution d’une fonction Python est terminée (soit via return, soit via une exception). Il n’est déclenché que pour les fonctions en Python pur (code intermédiaire).

Les arguments sont les mêmes que pour function__entry()

line(str filename, str funcname, int lineno)

Ce marqueur indique qu’une ligne Python est sur le point d’être exécutée. C’est l’équivalent du traçage ligne par ligne avec un profileur Python. Il n’est pas déclenché dans les fonctions C.

Les arguments sont les mêmes que pour function__entry().

gc__start(int generation)

Fonction appelée lorsque l’interpréteur Python lance un cycle de collecte du ramasse-miettes. arg0 est la génération à scanner, comme gc.collect().

gc__done(long collected)

Fonction appelée lorsque l’interpréteur Python termine un cycle de collecte du ramasse-miettes. Arg0 est le nombre d’objets collectés.

Tapsets de SystemTap

La façon la plus simple d’utiliser l’intégration SystemTap est d’utiliser un « tapset ». L’équivalent pour SystemTap d’une bibliothèque, qui permet de masquer les détails de niveau inférieur des marqueurs statiques.

Voici un fichier tapset, basé sur une version non partagée compilée de CPython :

/*
   Provide a higher-level wrapping around the function__entry and
   function__return markers:
 \*/
probe python.function.entry = process("python").mark("function__entry")
{
    filename = user_string($arg1);
    funcname = user_string($arg2);
    lineno = $arg3;
    frameptr = $arg4
}
probe python.function.return = process("python").mark("function__return")
{
    filename = user_string($arg1);
    funcname = user_string($arg2);
    lineno = $arg3;
    frameptr = $arg4
}

Si ce fichier est installé dans le répertoire tapset de SystemTap (par exemple /usr/share/systemtap/tapset), alors ces sondes supplémentaires deviennent disponibles :

python.function.entry(str filename, str funcname, int lineno, frameptr)

This probe point indicates that execution of a Python function has begun. It is only triggered for pure-python (bytecode) functions.

python.function.return(str filename, str funcname, int lineno, frameptr)

This probe point is the converse of python.function.return(), and indicates that execution of a Python function has ended (either via return, or via an exception). It is only triggered for pure-python (bytecode) functions.

Exemples

Ce script SystemTap utilise le tapset ci-dessus pour implémenter plus proprement l’exemple précédent de traçage de la hiérarchie des appels de fonctions Python, sans avoir besoin de nommer directement les marqueurs statiques :

probe python.function.entry
{
  printf("%s => %s in %s:%d\n",
         thread_indent(1), funcname, filename, lineno);
}

probe python.function.return
{
  printf("%s <= %s in %s:%d\n",
         thread_indent(-1), funcname, filename, lineno);
}

Le script suivant utilise le tapset ci-dessus pour fournir une vue de l’ensemble du code CPython en cours d’exécution, montrant les 20 cadres de la pile d’appel (stack frames) les plus fréquemment utilisées du code intermédiaire, chaque seconde, sur l’ensemble du système :

global fn_calls;

probe python.function.entry
{
    fn_calls[pid(), filename, funcname, lineno] += 1;
}

probe timer.ms(1000) {
    printf("\033[2J\033[1;1H") /* clear screen \*/
    printf("%6s %80s %6s %30s %6s\n",
           "PID", "FILENAME", "LINE", "FUNCTION", "CALLS")
    foreach ([pid, filename, funcname, lineno] in fn_calls- limit 20) {
        printf("%6d %80s %6d %30s %6d\n",
            pid, filename, lineno, funcname,
            fn_calls[pid, filename, funcname, lineno]);
    }
    delete fn_calls;
}

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FAQ générale sur Python

Informations générales

Qu’est-ce que Python ?

Qu’est ce que la Python Software Foundation ?

Existe-il des restrictions liées à la propriété intellectuelle quant à l’utilisation de Python ?

Pourquoi Python a été créé ?

Pour quoi Python est-il fait ?

Comment fonctionne le numérotage des versions de Python ?

Comment obtenir une copie du code source de Python ?

Comment obtenir la documentation de Python ?

Je n’ai jamais programmé avant. Existe t-il un tutoriel Python ?

Y a-t-il un forum ou une liste de diffusion dédié à Python ?

Comment obtenir une version bêta test de Python ?

Comment soumettre un rapport de bogues ou un correctif pour Python ?

Existe-t-il des articles publiés au sujet de Python auxquels je peux me référer ?

Y a-t-il des livres au sujet de Python ?

Où www.python.org est-il localisé dans le monde ?

Pourquoi le nom Python ?

Dois-je aimer « Monty Python’s Flying Circus » ?

Python c’est le monde réel

Quel est le niveau de stabilité de Python ?

Combien de personnes utilisent Python ?

Y a-t-il un nombre de projets significatif réalisés en Python ?

Quelles sont les nouveautés en développement attendues pour Python ?

Est-il raisonnable de proposer des changements incompatibles dans Python ?

Existe-t-il un meilleur langage de programmation pour les programmeurs débutants ?

Informations générales

Qu’est-ce que Python ?

Python est un langage de programmation interprété, interactif, orienté objet. Il incorpore des modules, des exceptions, un typage dynamique et des classes. Python combine une puissance incroyable et une syntaxe très claire. Il dispose de liens avec de nombreuses interfaces de programmation pour systèmes d’exploitation et bibliothèques, ainsi que divers systèmes d’interfaces graphiques, et il peut être étendu grâce au C ou C++. Il est aussi utilisable comme langage d’extension (script) pour les logiciels qui nécessitent une interface de programmation. Enfin, Python est portable : il fonctionne sur multiples variantes Unix, sur Mac, ainsi que sur Windows 2000 et versions supérieures.

Pour en savoir plus, commencez par Le tutoriel Python. Le « Guide des Débutants pour Python [https://wiki.python.org/moin/BeginnersGuide] » renvoie vers d’autres tutoriels et ressources d’initiation pour apprendre Python.

Qu’est ce que la Python Software Foundation ?

La Python Software Foundation (PSF) est une organisation indépendante à but non lucratif qui détient les droits d’auteur sur les versions Python 2.1 et plus récentes. La mission de la PSF est de faire progresser les technologies ouvertes (open source) relatives au langage de programmation Python et de promouvoir son utilisation. Le page d’accueil de la PSF se trouve à l’adresse suivante : https://www.python.org/psf/.

Si vous utilisez Python et que vous le trouvez utile, merci de contribuer par le biais de la page de donation de la PSF [https://www.python.org/psf/donations/].

Existe-il des restrictions liées à la propriété intellectuelle quant à l’utilisation de Python ?

Vous pouvez faire ce que vous souhaitez avec la source, tant que vous respecterez la licence d’utilisation et que vous l’afficherez dans toute documentation que vous produirez au sujet de Python. Si vous respectez ces règles, vous pouvez utiliser Python dans un cadre commercial, vendre le code source ou la forme binaire (modifiée ou non), ou vendre des produits qui incorporent Python sous une forme quelconque. Bien entendu, nous souhaiterions avoir connaissance de tous les projets commerciaux utilisant Python.

Voir la page de licence d’utilisation de la PSF [https://www.python.org/psf/license/] pour trouver davantage d’informations et un lien vers la version intégrale de la licence d’utilisation.

Le logo de Python est une marque déposée, et dans certains cas une autorisation est nécessaire pour l’utiliser. Consultez la politique d’utilisation de la marque [https://www.python.org/psf/trademarks/] pour plus d’informations.

Pourquoi Python a été créé ?

Voici un très bref résumé de comment tout a commencé, écrit par Guido van Rossum (puis traduit en français) :

J’avais une expérience complète avec la mise en œuvre du langage interprété ABC au sein du CWI, et en travaillant dans ce groupe j’ai appris beaucoup à propos de la conception de langage. C’est l’origine de nombreuses fonctionnalités de Python, notamment l’utilisation de l’indentation pour le groupement et l’inclusion de types de très haut niveau (bien que dans les détails ils soient tous différents dans Python).

J’avais un certain nombre de différends avec le langage ABC, mais j’aimais aussi beaucoup de ses fonctionnalités. Il était impossible d’étendre le langage ABC (ou ses implémentations) pour remédier à mes réclamations – en vérité le manque d’extensibilité était l’un des plus gros problème. J’avais un peu d’expérience avec l’utilisation de Modula-2+ et j’en ai parlé avec les concepteurs de Modula-3 et j’ai lu le rapport sur Modula-3. Modula-3 est à l’origine de la syntaxe et de la sémantique utilisée pour les exceptions, et quelques autres fonctionnalités en Python.

Je travaillais sur un groupe de systèmes d’exploitation distribués Amoeba au CWI. Nous avions besoin d’un meilleur moyen pour gérer l’administration système qu’écrire un programme en C ou en script Bourne shell, puisque l’Amoeba avait sa propre interface d’appels système qui n’était pas facilement accessible depuis les scripts Bourne shell. Mon expérience avec le traitement des erreurs dans l’Amoeba m’a vraiment fait prendre conscience de l’importance des exceptions en tant que fonctionnalité d’un langage de programmation.

Il m’est venu à l’esprit qu’un langage de script avec une syntaxe comme ABC mais avec un accès aux appels systèmes d’Amoeba remplirait les besoins. J’ai réalisé que ce serait idiot d’écrire un langage spécifique à Amoeba, donc j’ai décidé que j’avais besoin d’un langage qui serait généralement extensible.

Pendant les vacances de Noël 1989, j’avais beaucoup de temps à disposition, donc j’ai décidé de faire un essai. Durant l’année suivante, j’ai encore beaucoup travaillé dessus sur mon propre temps. Python a été utilisé dans le projet Amoeba avec un succès croissant, et les retours de mes collègues m’ont permis d’ajouter beaucoup des premières améliorations.

En Février 1991, juste après un peu plus d’un an de développement, j’ai décidé de le poster sur USENET. Le reste se trouve dans le fichier « Misc/HISTORY ».

Pour quoi Python est-il fait ?

Python est un langage de programmation haut niveau généraliste qui peut être utilisé pour pallier à différents problèmes.

Le langage vient avec une bibliothèque standard importante qui couvre des domaines tels que le traitement des chaînes de caractères (expressions régulières, Unicode, calcul de différences entre les fichiers), les protocoles Internet (HTTP, FTP, SMTP, XML-RPC, POP, IMAP, script CGI), ingénierie logicielle (tests unitaires, enregistrement, analyse de code Python), et interfaces pour systèmes d’exploitation (appels système, système de fichiers, connecteurs TCP/IP). Regardez la table des matières La bibliothèque standard pour avoir une idée de ce qui est disponible. Une grande variété de greffons tiers existent aussi. Consultez le sommaire des paquets Python [https://pypi.org] pour trouver les paquets qui pourraient vous intéresser.

Comment fonctionne le numérotage des versions de Python ?

Les versions de Python sont numérotées A.B.C ou A.B. A est une version majeure – elle est augmentée seulement lorsqu’il y a des changements conséquents dans le langage. B est une version mineure, elle est augmentée lors de changements de moindre importance. C est un micro-niveau – elle est augmentée à chaque sortie de correctifs de bogue.

Toutes les sorties ne concernent pas la correction de bogues. A l’approche de la sortie d’une nouvelle version majeure, une série de versions de développement sont créées, dénommées alpha, beta, release candidate. Les alphas sont des versions primaires dans lesquelles les interfaces ne sont pas encore finalisées; ce n’est pas inattendu de voir des changements d’interface entre deux versions alpha. Les betas sont plus stables, préservent les interfaces existantes mais peuvent ajouter de nouveaux modules, les release candidate sont figées, elles ne font aucun changement à l’exception de ceux nécessaires pour corriger des bogues critiques.

Les versions alpha, beta et release candidate ont un suffixe supplémentaire. Le suffixe pour une version alpha est « aN » où N est un petit nombre, le suffixe pour une version beta est bN où N est un petit nombre, et le suffixe pour une release candidate est « cN » où N est un petit nombre. En d’autres mots, toutes les versions nommées 2.0.aN précèdent les versions 2.0.bN, qui elles-mêmes précèdent 2.0cN, et celles-ci précèdent la version 2.0.

Vous pouvez aussi trouver des versions avec un signe « + » en suffixe, par exemple « 2.2+». Ces versions sont non distribuées, construites directement depuis le dépôt de développement de CPython. En pratique, après la sortie finale d’une version mineure, la version est augmentée à la prochaine version mineure, qui devient la version a0, c’est-à-dire 2.4a0.

Voir aussi la documentation pour for sys.version, sys.hexversion, et sys.version_info.

Comment obtenir une copie du code source de Python ?

La dernière version du code source déployée est toujours disponible sur python.org, à https://www.python.org/downloads/. Le code source de la dernière version en développement peut être obtenue à https://github.com/python/cpython/.

Le code source est dans une archive gzippée au format tar, elle contient le code source C complet, la documentation formatée avec Sphinx, les libraires Python, des exemples de programmes, et plusieurs morceaux de code utiles distribuables librement. Le code source sera compilé et prêt à fonctionner immédiatement sur la plupart des plateformes UNIX.

Consultez la section Premiers pas du Guide des Développeurs Python [https://devguide.python.org/setup/] pour plus d’informations sur comment obtenir le code source et le compiler.

Comment obtenir la documentation de Python ?

La documentation standard pour la version stable actuelle est disponible à https://docs.python.org/3/. Des versions aux formats PDF, texte et HTML sont aussi disponibles à https://docs.python.org/3/download.html.

La documentation est écrite au format reStructuredText et traitée par l’outil de documentation Sphinx [http://sphinx-doc.org/]. La source du reStructuredText pour la documentation constitue une partie des sources de Python.

Je n’ai jamais programmé avant. Existe t-il un tutoriel Python ?

Il y a de nombreux tutoriels et livres disponibles. La documentation standard inclut Le tutoriel Python.

Consultez le Guide du Débutant [https://wiki.python.org/moin/BeginnersGuide] afin de trouver des informations pour les développeurs Python débutants, incluant une liste de tutoriels.

Y a-t-il un forum ou une liste de diffusion dédié à Python ?

Il y a un forum, comp.lang.python et une liste de diffusion, python-list [https://mail.python.org/mailman/listinfo/python-list]. Le forum et la liste de diffusion sont des passerelles l’un vers l’autre – si vous pouvez lire les news ce n’est pas inutile de souscrire à la liste de diffusion. comp.lang.python a beaucoup d’activité, il reçoit des centaines de messages chaque jour, et les lecteurs du réseau Usenet sont souvent plus capables de faire face à ce volume.

Les annonces pour les nouvelles versions et événements peuvent êtres trouvées dans comp.lang.python.announce, une liste diminuée peu active qui reçoit environ 5 messages par jour. C’est disponible à liste de diffusion des annonces Python [https://mail.python.org/mailman/listinfo/python-announce-list].

Plus d’informations à propos des autres listes de diffusion et forums peuvent être trouvées à https://www.python.org/community/lists/.

Comment obtenir une version bêta test de Python ?

Les versions alpha et bêta sont disponibles depuis https://www.python.org/downloads/. Toutes les versions sont annoncées sur les newsgroups comp.lang.python et comp.lang.python.announce ainsi que sur la page d’accueil de Python à https://www.python.org/; un flux RSS d’actualités y est aussi disponible.

Vous pouvez aussi accéder aux de Python en développement grâce à Git. Voir Le Guide du Développeur Python [https://devguide.python.org/] pour plus de détails.

Comment soumettre un rapport de bogues ou un correctif pour Python ?

Pour reporter un bogue ou soumettre un correctif, merci d’utiliser https://bugs.python.org/.

Vous devez avoir un compte Roundup pour reporter des bogues; cela nous permet de vous contacter si nous avons des questions complémentaires. Cela permettra aussi le suivi de traitement de votre bogue. Si vous avez auparavant utilisé SourceForge pour reporter des bogues sur Python, vous pouvez obtenir un mot de passe Roundup grâce à la procédure de réinitialisation de mot de passe de Roundup [https://bugs.python.org/user?@template=forgotten].

Pour davantage d’informations sur comment Python est développé, consultez le Guide du Développeur Python [https://devguide.python.org/].

Existe-t-il des articles publiés au sujet de Python auxquels je peux me référer ?

C’est probablement mieux de vous référer à votre livre favori à propos de Python.

Le tout premier article à propos de Python a été écrit en 1991 et est maintenant obsolète.

Guido van Rossum et Jelke de Boer, « Interactively Testing Remote Servers Using the Python Programming Language », CWI Quarterly, Volume 4, Issue 4 (December 1991), Amsterdam, pp 283–303.

Y a-t-il des livres au sujet de Python ?

Oui, il y en a beaucoup, et d’autres sont en cours de publication. Voir le wiki python à https://wiki.python.org/moin/PythonBooks pour avoir une liste.

Vous pouvez aussi chercher chez les revendeurs de livres en ligne avec le terme « Python » et éliminer les références concernant les Monty Python, ou peut-être faire une recherche avec les termes « langage » et « Python ».

Où www.python.org est-il localisé dans le monde ?

L’infrastructure du projet Python est localisé dans le monde entier. www.python.org [https://www.python.org] est gracieusement hébergé par Rackspace [https://www.rackspace.com], avec un cache CDN fourni par Fastly [https://www.fastly.com]. Upfront Systems [http://www.upfrontsystems.co.za/] héberge bugs.python.org [https://bugs.python.org].

Pourquoi le nom Python ?

Quand il a commencé à implémenter Python, Guido van Rossum a aussi lu le script publié par « Monty Python’s Flying Circus » [https://en.wikipedia.org/wiki/Monty_Python], une série comique des années 1970 diffusée par la BBC. Van Rossum a pensé qu’il avait besoin d’un nom court, unique, et un peu mystérieux, donc il a décidé de l’appeler le langage Python.

Dois-je aimer « Monty Python’s Flying Circus » ?

Non, mais ça peut aider. :)

Python c’est le monde réel

Quel est le niveau de stabilité de Python ?

Très stable. Les versions stables sont sorties environ tous les 6 à 18 mois depuis 1991, et il semble probable que ça continue. Actuellement il y a habituellement environ 18 mois entre deux sorties de version majeure.

The developers issue « bugfix » releases of older versions, so the stability of existing releases gradually improves. Bugfix releases, indicated by a third component of the version number (e.g. 3.5.3, 3.6.2), are managed for stability; only fixes for known problems are included in a bugfix release, and it’s guaranteed that interfaces will remain the same throughout a series of bugfix releases.

The latest stable releases can always be found on the Python download page [https://www.python.org/downloads/]. There are two production-ready version of Python: 2.x and 3.x, but the recommended one at this times is Python 3.x. Although Python 2.x is still widely used, it will not be maintained after January 1, 2020 [https://www.python.org/dev/peps/pep-0373/]. Python 2.x was known for having more third-party libraries available, however, by the time of this writing, most of the widely used libraries support Python 3.x, and some are even dropping the Python 2.x support.

Combien de personnes utilisent Python ?

Il y a probablement des dizaines de milliers d’utilisateurs, cependant c’est difficile d’obtenir un nombre exact.

Python est disponible en téléchargement gratuit, donc il n’y a pas de chiffres de ventes, il est disponible depuis de nombreux sites différents et il est inclus avec de beaucoup de distributions Linux, donc les statistiques de téléchargement ne donnent pas la totalité non plus.

Le forum comp.lang.python est très actif, mais tous les utilisateurs de Python ne laissent pas de messages dessus ou même ne le lisent pas.

Y a-t-il un nombre de projets significatif réalisés en Python ?

Voir https://www.python.org/about/success pour avoir une liste des projets qui utilisent Python. En consultant les comptes-rendu des conférences Python précédentes [https://www.python.org/community/workshops/] il s’avère que les contributions proviennent de nombreux organismes et entreprises divers.

Les projets Python à grande visibilité incluent Mailman mailing list manager [http://www.list.org] et l’application serveur Zope [http://www.zope.org]. Plusieurs distributions Linux, notamment Red Hat [https://www.redhat.com], qui a écrit tout ou partie de son installateur et de son logiciel d’administration système en Python. Les entreprises qui utilisent Python en interne comprennent Google, Yahoo, et Lucasfilm Ltd.

Quelles sont les nouveautés en développement attendues pour Python ?

Regardez les propositions d’amélioration de Python (« Python Enhancement Proposals », ou PEP) sur https://www.python.org/dev/peps/. Les PEP sont des documents techniques qui décrivent une nouvelle fonctionnalité qui a été suggérée pour Python, en fournissant une spécification technique concise et logique. Recherchez une PEP intitulée « Python X.Y Release Schedule », où X.Y est la version qui n’a pas encore été publiée.

Le nouveau développement est discuté sur la liste de diffusion python-dev [https://mail.python.org/mailman/listinfo/python-dev/].

Est-il raisonnable de proposer des changements incompatibles dans Python ?

En général, non. Il y a déjà des millions de lignes de code de Python tout autour du monde, donc n’importe quel changement dans le langage qui rend invalide ne serait-ce qu’une très petite fraction du code de programmes existants doit être désapprouvé. Même si vous pouvez fournir un programme de conversion, il y a toujours des problèmes de mise à jour dans toutes les documentations, beaucoup de livres ont été écrits au sujet de Python, et nous ne voulons pas les rendre invalides soudainement.

En fournissant un rythme de mise à jour progressif qui est obligatoire si une fonctionnalité doit être changée.

Existe-t-il un meilleur langage de programmation pour les programmeurs débutants ?

Oui.

Il reste commun pour les étudiants de commencer avec un langage procédural et à typage statique comme le Pascal, le C, ou un sous-ensemble du C++ ou Java. Les étudiants pourraient être mieux servis en apprenant Python comme premier langage. Python a une syntaxe très simple et cohérente ainsi qu’une vaste libraire standard, plus important encore, utiliser Python dans les cours d’initiation à la programmation permet aux étudiants de se concentrer sur les compétences de programmation les cruciales comme les problèmes de découpage et d’architecture. Avec Python, les étudiants peuvent rapidement aborder des concepts fondamentaux comme les boucles et les procédures. Ils peuvent même probablement travailler avec des objets définis dans leurs premiers cours.

Pour un étudiant qui n’a jamais programmé avant, utiliser un langage à typage statique peut sembler contre-nature. Cela représente une complexité additionnelle que l’étudiant doit maîtriser ce qui ralentit le cours. Les étudiants essaient d’apprendre à penser comme un ordinateur, décomposer les problèmes, établir une architecture propre, et résumer les données. Apprendre à utiliser un langage typé statiquement est important sur le long terme, ce n’est pas nécessairement la meilleure idée pour s’adresser aux étudiants durant leur tout premier cours.

De nombreux autres aspects de Python en font un bon premier langage. Comme Java, Python a une large bibliothèque standard donc les étudiants peuvent être assigner à la programmation de projets très tôt dans leur apprentissage qui fait quelque chose. Les missions ne sont pas restreintes aux quatre fonction standards. En utilisant la bibliothèque standard, les étudiants peuvent ressentir de la satisfaction en travaillant sur des applications réalistes alors qu’ils apprennent les fondamentaux de la programmation. Utiliser la bibliothèque standard apprend aussi aux étudiants la réutilisation de code. Les modules tiers tels que PyGame sont aussi très utiles pour étendre les compétences des étudiants.

L’interpréteur interactif de Python permet aux étudiants de tester les fonctionnalités du langage pendant qu’ils programment. Ils peuvent garder une fenêtre avec l’interpréteur en fonctionnement pendant qu’ils rentrent la source de leur programme dans une autre fenêtre. S’ils ne peuvent pas se souvenir des méthodes pour une liste, ils peuvent faire quelque chose comme ça :

>>> L = []
>>> dir(L)
['__add__', '__class__', '__contains__', '__delattr__', '__delitem__',
'__dir__', '__doc__', '__eq__', '__format__', '__ge__',
'__getattribute__', '__getitem__', '__gt__', '__hash__', '__iadd__',
'__imul__', '__init__', '__iter__', '__le__', '__len__', '__lt__',
'__mul__', '__ne__', '__new__', '__reduce__', '__reduce_ex__',
'__repr__', '__reversed__', '__rmul__', '__setattr__', '__setitem__',
'__sizeof__', '__str__', '__subclasshook__', 'append', 'clear',
'copy', 'count', 'extend', 'index', 'insert', 'pop', 'remove',
'reverse', 'sort']
>>> [d for d in dir(L) if '__' not in d]
['append', 'clear', 'copy', 'count', 'extend', 'index', 'insert', 'pop', 'remove', 'reverse', 'sort']

>>> help(L.append)
Help on built-in function append:

append(...)
    L.append(object) -> None -- append object to end

>>> L.append(1)
>>> L
[1]

Avec l’interpréteur, la documentation n’est jamais loin des étudiants quand ils travaillent.

Il y a aussi de bons environnements de développement intégrés (EDIs) pour Python. IDLE est un EDI multiplateforme pour Python qui est écrit en Python en utilisant Tkinter. PythonWin est un IDE spécifique à Windows. Les utilisateurs d’Emcs seront heureux d’apprendre qu’il y a un très bon mode Python pour Emacs. Tous ces environnements de développement intégrés fournissent la coloration syntaxique, l’auto-indentation, et l’accès à l’interpréteur interactif durant le codage. Consultez le wiki Python [https://wiki.python.org/moin/PythonEditors] pour une liste complète des environnements de développement intégrés.

Si vous voulez discuter de l’usage de Python dans l’éducation, vous devriez intéressé pour rejoindre la liste de diffusion pour l’enseignement [https://www.python.org/community/sigs/current/edu-sig].

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FAQ de programmation

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FAQ de programmation

Questions générales

Existe-t-il un débogueur de code source avec points d’arrêts, exécution pas-à-pas, etc. ?

Existe-t-il des outils pour aider à trouver des bogues ou faire de l’analyse statique de code ?

Comment créer un binaire autonome à partir d’un script Python ?

Existe-t-il des normes de développement ou un guide de style pour écrire des programmes Python ?

Fondamentaux

Pourquoi une UnboundLocalError est levée alors qu’une variable a une valeur ?

Quelles sont les règles pour les variables locales et globales en Python ?

Pourquoi des expressions lambda définies dans une boucle avec des valeurs différentes retournent-elles le même résultat ?

Comment partager des variables globales entre modules ?

Quelles sont les « bonnes pratiques » pour utiliser import dans un module ?

Pourquoi les arguments par défaut sont-ils partagés entre les objets ?

Comment passer des paramètres optionnels ou nommés d’une fonction à l’autre ?

Quelle est la différence entre les arguments et les paramètres ?

Pourquoi modifier la liste “y” modifie aussi la liste “x” ?

Comment écrire une fonction qui modifie ses paramètres ? (passage par référence)

Comment construire une fonction d’ordre supérieur en Python ?

Comment copier un objet en Python ?

Comment récupérer les méthodes ou les attributs d’un objet ?

Comment un code peut-il obtenir le nom d’un objet ?

Qu’en est-il de la précédence de l’opérateur virgule ?

Existe-t-il un équivalent à l’opérateur ternaire « ?: » du C ?

Est-il possible d’écrire des programmes obscurcis (obfuscated) d’une ligne en Python ?

Nombres et chaînes de caractères

Comment écrire des entiers hexadécimaux ou octaux ?

Pourquoi -22 // 10 donne-t-il -3 ?

Comment convertir une chaîne de caractères en nombre ?

Comment convertir un nombre en chaîne de caractères ?

Comment modifier une chaîne de caractères « sur place » ?

Comment utiliser des chaînes de caractères pour appeler des fonctions/méthodes ?

Existe-t-il un équivalent à la fonction chomp() de Perl, pour retirer les caractères de fin de ligne d’une chaîne de caractères ?

Existe-t-il un équivalent à scanf() ou sscanf() ?

Que signifient les erreurs UnicodeDecodeError ou UnicodeEncodeError ?

Performances

Mon programme est trop lent. Comment l’accélérer ?

Quelle est la manière la plus efficace de concaténer un grand nombre de chaînes de caractères ?

Séquences (n-uplets / listes)

Comment convertir les listes en n-uplets et inversement ?

Qu’est-ce qu’un index négatif ?

Comment itérer à rebours sur une séquence ?

Comment retirer les doublons d’une liste ?

Comment construire un tableau en Python ?

Comment créer une liste à plusieurs dimensions ?

Comment appliquer une méthode à une séquence d’objets ?

Pourquoi a_tuple[i] += ['item'] lève-t-il une exception alors que l’addition fonctionne ?

Dictionnaires

Comment puis-je faire stocker et afficher les clefs d’un dictionnaire dans un ordre cohérent ?

Je souhaite faire un classement compliqué : peut on faire une transformation de Schwartz en Python ?

Comment ordonner une liste en fonction des valeurs d’une autre liste ?

Objets

Qu’est-ce qu’une classe ?

Qu’est-ce qu’une méthode ?

Qu’est-ce que self ?

Comment vérifier si un objet est une instance d’une classe donnée ou d’une sous-classe de celle-ci ?

Qu’est-ce que la délégation ?

Comment appeler une méthode définie dans une classe de base depuis une classe dérivée qui la surcharge ?

Comment organiser un code pour permettre de changer la classe de base plus facilement ?

Comment créer des données statiques de classe et des méthodes statiques de classe ?

Comment surcharger les constructeurs (ou méthodes) en Python ?

J’essaie d’utiliser __spam et j’obtiens une erreur à propos de _SomeClassName__spam.

Ma classe définit __del__ mais elle n’est pas appelée lorsque je supprime l’objet.

Comment obtenir toutes les instances d’une classe ?

Pourquoi le résultat de id() peut-il être le même pour deux objets différents ?

Modules

Comment créer des fichiers .pyc ?

Comment obtenir le nom du module actuel ?

Comment avoir des modules qui s’importent mutuellement ?

__import__('x.y.z') renvoie <module 'x'> ; comment accéder à z ?

Quand j’édite un module et que je le réimporte, je ne vois pas les changements. Pourquoi ?

Questions générales

Existe-t-il un débogueur de code source avec points d’arrêts, exécution pas-à-pas, etc. ?

Oui.

Le module pdb est un débogueur console simple, mais parfaitement adapté à Python. Il fait partie de la bibliothèque standard de Python, sa documentation se trouve dans le manuel de référence. Vous pouvez vous inspirer du code de pdb pour écrire votre propre débogueur.

L’environnement de développement interactif IDLE, qui est fourni avec la distribution standard de Python (normalement disponible dans Tools/scripts/idle) contient un débogueur graphique.

PythonWin est un environnement de développement intégré (EDI) Python qui embarque un débogueur graphique basé sur pdb. Le débogueur PythonWin colore les points d’arrêts et possède quelques fonctionnalités sympathiques, comme la possibilité de déboguer des programmes développés sans PythonWin. PythonWin est disponible dans le projet Extensions Python pour Windows [https://sourceforge.net/projects/pywin32/] et fait partie de la distribution ActivePython (voir https://www.activestate.com/activepython).

Boa Constructor [http://boa-constructor.sourceforge.net/] est un EDI et un constructeur d’interface homme-machine basé sur wxWidgets. Il propose la création et la manipulation de fenêtres, un inspecteur d’objets, de nombreuses façons de visualiser des sources comme un navigateur d’objets, les hiérarchies d’héritage, la documentation html générée par les docstrings, un débogueur avancé, une aide intégrée et la prise en charge de Zope.

Eric [http://eric-ide.python-projects.org/] est un EDI basé sur PyQt et l’outil d’édition Scintilla.

Pydb est une version du débogueur standard Python pdb, modifié pour être utilisé avec DDD (Data Display Debugger), un célèbre débogueur graphique. Pydb est disponible sur http://bashdb.sourceforge.net/pydb/ et DDD est disponible sur https://www.gnu.org/software/ddd.

Il existe de nombreux EDI Python propriétaires qui embarquent un débogueur graphique. Notamment :

Wing IDE (https://wingware.com/)

Komodo IDE (https://komodoide.com/)

PyCharm (https://www.jetbrains.com/pycharm/)

Existe-t-il des outils pour aider à trouver des bogues ou faire de l’analyse statique de code ?

Oui.

PyChecker est un outil d’analyse statique qui trouve les bogues dans le code source Python et émet des avertissements relatifs à la complexité et au style du code. PyChecker est disponible sur http://pychecker.sourceforge.net/.

Pylint <https://www.pylint.org/>`_ est un autre outil qui vérifie si un module satisfait aux normes de développement, et qui permet en plus d’écrire des greffons pour ajouter des fonctionnalités personnalisées. En plus de la vérification des bogues effectuée par PyChecker, Pylint effectue quelques vérifications supplémentaires comme la longueur des lignes, les conventions de nommage des variables, que les interfaces déclarées sont implémentées en totalité, et plus encore. https://docs.pylint.org/ fournit la liste complète des fonctionnalités de Pylint.

Comment créer un binaire autonome à partir d’un script Python ?

Pour créer un programme autonome, c’est-à-dire un programme que n’importe qui peut télécharger et exécuter sans avoir à installer une distribution Python au préalable, il n’est pas nécessaire de compiler du code Python en code C. Il existe en effet plusieurs outils qui déterminent les modules requis par un programme et lient ces modules avec un binaire Python pour produire un seul exécutable.

Un de ces outils est freeze, qui se trouve dans Tools/freeze de l’arborescence des sources de Python. Il convertit le code intermédiaire (bytecode) Python en tableaux C ; un compilateur C permet d’intégrer tous vos modules dans un nouveau programme, qui est ensuite lié aux modules standards Python.

Il fonctionne en cherchant de manière récursive les instructions d’import (sous les deux formes) dans le code source et en recherchant ces modules dans le chemin Python standard ainsi que dans le répertoire source (pour les modules natifs). Il transforme ensuite le code intermédiaire des modules écrits en Python en code C (des tableaux pré-remplis qui peuvent être transformés en objets code à l’aide du module marshal) et crée un fichier de configuration personnalisé qui contient uniquement les modules natifs qui sont réellement utilisés dans le programme. Il compile ensuite le code C généré et le lie au reste de l’interpréteur Python pour former un binaire autonome qui fait exactement la même chose que le script.

Bien évidemment, freeze nécessite un compilateur C. Il existe d’autres outils qui peuvent s’en passer. Un de ceux-ci est py2exe de Thomas Heller (pour Windows uniquement) disponible sur

http://www.py2exe.org/

Another tool is Anthony Tuininga’s cx_Freeze [http://cx-freeze.sourceforge.net/].

Existe-t-il des normes de développement ou un guide de style pour écrire des programmes Python ?

Oui. Le style de développement que les modules de la bibliothèque standard doivent obligatoirement respecter est documenté dans la PEP 8 [https://www.python.org/dev/peps/pep-0008].

Fondamentaux

Pourquoi une UnboundLocalError est levée alors qu’une variable a une valeur ?

Il est parfois surprenant d’obtenir une UnboundLocalError dans du code jusqu’à présent correct, quand celui-ci est modifié en ajoutant une instruction d’affectation quelque part dans le corps d’une fonction.

Le code suivant :

>>> x = 10
>>> def bar():
...     print(x)
>>> bar()
10

fonctionne, mais le suivant :

>>> x = 10
>>> def foo():
...     print(x)
...     x += 1

lève une UnboundLocalError :

>>> foo()
Traceback (most recent call last):
  ...
UnboundLocalError: local variable 'x' referenced before assignment

Cela est dû au fait que, quand une variable est affectée dans un contexte, cette variable devient locale à ce contexte et remplace toute variable du même nom du contexte appelant. Vu que la dernière instruction dans foo affecte une nouvelle valeur à x, le compilateur la traite comme une nouvelle variable. Par conséquent, quand le print(x) essaye d’afficher la variable non initialisée, une erreur se produit.

Dans l’exemple ci-dessus, la variable du contexte appelant reste accessible en la déclarant globale :

>>> x = 10
>>> def foobar():
...     global x
...     print(x)
...     x += 1
>>> foobar()
10

Cette déclaration explicite est obligatoire pour se rappeler que (contrairement au cas à peu près similaire avec des variables de classe et d’instance), c’est la valeur de la variable du contexte appelant qui est modifiée :

>>> print(x)
11

Une alternative dans un contexte imbriqué consiste à utiliser le mot-clé nonlocal :

>>> def foo():
...    x = 10
...    def bar():
...        nonlocal x
...        print(x)
...        x += 1
...    bar()
...    print(x)
>>> foo()
10
11

Quelles sont les règles pour les variables locales et globales en Python ?

En Python, si une variable n’est pas modifiée dans une fonction mais seulement lue, elle est implicitement considérée comme globale. Si une valeur lui est affectée, elle est considérée locale (sauf si elle est explicitement déclarée globale).

Bien que surprenant au premier abord, ce choix s’explique facilement. D’une part, exiger global pour des variables affectées est une protection contre des effets de bord inattendus. D’autre part, si global était obligatoire pour toutes les références à des objets globaux, il faudrait mettre global partout, car il faudrait dans ce cas déclarer globale chaque référence à une fonction native ou à un composant d’un module importé. Le codé serait alors truffé de déclarations global, ce qui nuirait à leur raison d’être : identifier les effets de bords.

Pourquoi des expressions lambda définies dans une boucle avec des valeurs différentes retournent-elles le même résultat ?

Supposons que l’on utilise une boucle itérative pour définir des expressions lambda (voire même des fonctions) différentes, par exemple :

>>> squares = []
>>> for x in range(5):
...     squares.append(lambda: x**2)

Le code précédent crée une liste de 5 expressions lambda qui calculent chacune x**2. En les exécutant, on pourrait s’attendre à obtenir 0, 1, 4, 9 et 16. Elles renvoient en réalité toutes 16 :

>>> squares[2]()
16
>>> squares[4]()
16

Ceci s’explique par le fait que x n’est pas une variable locale aux expressions, mais est définie dans le contexte appelant. Elle est lue à l’appel de l’expression lambda – et non au moment où cette expression est définie. À la fin de la boucle, x vaut 4, donc toutes les fonctions renvoient 4*2, i.e. 16. Ceci se vérifie également en changeant la valeur de x et en constatant que les résultats sont modifiés :

>>> x = 8
>>> squares[2]()
64

Pour éviter ce phénomène, les valeurs doivent être stockées dans des variables locales aux expressions lambda pour que celles-ci ne se basent plus sur la variable globale x :

>>> squares = []
>>> for x in range(5):
...     squares.append(lambda n=x: n**2)

Dans ce code, n=x crée une nouvelle variable n, locale à l’expression. Cette variable est évaluée quand l’expression est définie donc n a la même valeur que x à ce moment. La valeur de n est donc 0 dans la première lambda, 1 dans la deuxième, 2 dans la troisième et ainsi de suite. Chaque expression lambda renvoie donc le résultat correct :

>>> squares[2]()
4
>>> squares[4]()
16

Ce comportement n’est pas propre aux expressions lambda, mais s’applique aussi aux fonctions normales.

Comment partager des variables globales entre modules ?

La manière standard de partager des informations entre modules d’un même programme est de créer un module spécial (souvent appelé config ou cfg) et de l’importer dans tous les modules de l’application ; le module devient accessible depuis l’espace de nommage global. Vu qu’il n’y a qu’une instance de chaque module, tout changement dans l’instance est propagé partout. Par exemple :

config.py :

x = 0   # Default value of the 'x' configuration setting

mod.py :

import config
config.x = 1

main.py :

import config
import mod
print(config.x)

Pour les mêmes raisons, l’utilisation d’un module est aussi à la base de l’implémentation du patron de conception singleton.

Quelles sont les « bonnes pratiques » pour utiliser import dans un module ?

De manière générale, il ne faut pas faire from modulename import *. Ceci encombre l’espace de nommage de l’importateur et rend la détection de noms non-définis beaucoup plus ardue pour les analyseurs de code.

Les modules doivent être importés au début d’un fichier. Ceci permet d’afficher clairement de quels modules le code à besoin et évite de se demander si le module est dans le contexte. Faire un seul import par ligne rend l’ajout et la suppression d’une importation de module plus aisé, mais importer plusieurs modules sur une même ligne prend moins d’espace.

Il est recommandé d’importer les modules dans l’ordre suivant :

les modules de la bibliothèque standard — e.g. sys, os, getopt, re

les modules externes (tout ce qui est installé dans le dossier site-packages de Python) — e.g. mx.DateTime, ZODB, PIL.Image, etc.

les modules développés en local

Il est parfois nécessaire de déplacer des importations dans une fonction ou une classe pour éviter les problèmes d’importations circulaires. Comme le souligne Gordon McMillan :

Il n’y a aucun souci à faire des importations circulaires tant que les deux modules utilisent la forme import <module>. Ça ne pose problème que si le second module cherche à récupérer un nom du premier module (« from module import name ») et que l’importation est dans l’espace de nommage du fichier. Les noms du premier module ne sont en effet pas encore disponibles car le premier module est occupé à importer le second.

Dans ce cas, si le second module n’est utilisé que dans une fonction, l’importation peut facilement être déplacée dans cette fonction. Au moment où l’importation sera appelée, le premier module aura fini de s’initialiser et le second pourra faire son importation.

Il peut parfois être nécessaire de déplacer des importations de modules hors de l’espace de plus haut niveau du code si certains de ces modules dépendent de la machine utilisée. Dans ce cas de figure, il est parfois impossible d’importer tous les modules au début du fichier. Dans ce cas, il est recommandé d’importer les modules adéquats dans le code spécifique à la machine.

Les imports ne devraient être déplacés dans un espace local, comme dans la définition d’une fonction, que si cela est nécessaire pour résoudre un problème comme éviter des dépendances circulaires ou réduire le temps d’initialisation d’un module. Cette technique est particulièrement utile si la majorité des imports est superflue selon le flux d’exécution du programme. Il est également pertinent de déplacer des importations dans une fonction si le module n’est utilisé qu’au sein de cette fonction. Le premier chargement d’un module peut être coûteux à cause du coût fixe d’initialisation d’un module, mais charger un module plusieurs fois est quasiment gratuit, cela ne coûte que quelques indirections dans un dictionnaire. Même si le nom du module est sorti du contexte courant, le module est probablement disponible dans sys.modules.

Pourquoi les arguments par défaut sont-ils partagés entre les objets ?

C’est un problème que rencontrent souvent les programmeurs débutants. Examinons la fonction suivante :

def foo(mydict={}):  # Danger: shared reference to one dict for all calls
    ... compute something ...
    mydict[key] = value
    return mydict

Au premier appel de cette fonction, mydict ne contient qu’un seul élément. Au second appel, mydict contient deux éléments car quand foo() commence son exécution, mydict contient déjà un élément.

On est souvent amené à croire qu’un appel de fonction créé des nouveaux objets pour les valeurs par défaut. Ce n’est pas le cas. Les valeurs par défaut ne sont créées qu’une et une seule fois, au moment où la fonction est définie. Si l’objet est modifié, comme le dictionnaire dans cet exemple, les appels suivants à cette fonction font référence à l’objet ainsi modifié.

Par définition, les objets immuables comme les nombres, les chaînes de caractères, les n-uplets et None ne sont pas modifiés. Les changements sur des objets muables comme les dictionnaires, les listes et les instances de classe peuvent porter à confusion.

En raison de cette fonctionnalité, il vaut mieux ne pas utiliser d’objets muables comme valeurs par défaut. Il vaut mieux utiliser None comme valeur par défaut et, à l’intérieur de la fonction, vérifier si le paramètre est à None et créer une nouvelle liste, dictionnaire ou autre, le cas échéant. Par exemple, il ne faut pas écrire :

def foo(mydict={}):
    ...

mais plutôt :

def foo(mydict=None):
    if mydict is None:
        mydict = {}  # create a new dict for local namespace

Cette fonctionnalité a une utilité. Il est courant de mettre en cache les paramètres et la valeur de retour de chacun des appels d’une fonction coûteuse à exécuter, et de renvoyer la valeur stockée en cache si le même appel est ré-effectué. C’est la technique dite de « mémoïsation », qui s’implémente de la manière suivante :

# Callers can only provide two parameters and optionally pass _cache by keyword
def expensive(arg1, arg2, *, _cache={}):
    if (arg1, arg2) in _cache:
        return _cache[(arg1, arg2)]

    # Calculate the value
    result = ... expensive computation ...
    _cache[(arg1, arg2)] = result           # Store result in the cache
    return result

Il est possible d’utiliser une variable globale contenant un dictionnaire à la place de la valeur par défaut ; ce n’est qu’une question de goût.

Comment passer des paramètres optionnels ou nommés d’une fonction à l’autre ?

Il faut récupérer les arguments en utilisant les sélecteurs * et ** dans la liste des paramètres de la fonction ; ceci donne les arguments positionnels sous la forme d’un n-uplet et les arguments nommés sous forme de dictionnaire. Ces arguments peuvent être passés à une autre fonction en utilisant * et ** :

def f(x, *args, **kwargs):
    ...
    kwargs['width'] = '14.3c'
    ...
    g(x, *args, **kwargs)

Quelle est la différence entre les arguments et les paramètres ?

Les paramètres sont les noms qui apparaissent dans une définition de fonction, alors que les arguments sont les valeurs qui sont réellement passées à une fonction lors de l’appel de celle-ci. Les paramètres définissent les types des arguments qu’une fonction accepte. Ainsi, avec la définition de fonction suivante :

def func(foo, bar=None, **kwargs):
    pass

foo, bar et kwargs sont des paramètres de func. Mais à l’appel de func avec, par exemple :

func(42, bar=314, extra=somevar)

les valeurs 42, 314, et somevar sont des arguments.

Pourquoi modifier la liste “y” modifie aussi la liste “x” ?

Si vous avez écrit du code comme :

>>> x = []
>>> y = x
>>> y.append(10)
>>> y
[10]
>>> x
[10]

vous vous demandez peut-être pourquoi l’ajout d’un élément à y a aussi changé x.

Il y a deux raisons qui conduisent à ce comportement :

Les variables ne sont que des noms qui font référence à des objets. La ligne y = x ne crée pas une copie de la liste — elle crée une nouvelle variable y qui pointe sur le même objet que x. Ceci signifie qu’il n’existe qu’un seul objet (la liste) auquel x et y font référence.

Les listes sont des muable, ce qui signifie que leur contenu peut être modifié.

Après l’appel de append(), le contenu de l’objet muable est passé de [] à [10]. Vu que les deux variables font référence au même objet, il est possible d’accéder à la valeur modifiée [10] avec chacun des noms.

Si au contraire, on affecte un objet immuable à x :

>>> x = 5  # ints are immutable
>>> y = x
>>> x = x + 1  # 5 can't be mutated, we are creating a new object here
>>> x
6
>>> y
5

on observe que x et y ne sont ici plus égales. Les entiers sont des immuables (immutable), et x = x + 1 ne change pas l’entier 5 en incrémentant sa valeur. Au contraire, un nouvel objet est créé (l’entier 6) et affecté à x (c’est à dire qu’on change l’objet auquel fait référence x). Après cette affectation on a deux objets (les entiers 6 et 5) et deux variables qui font référence à ces deux objets (x fait désormais référence à 6 mais y fait toujours référence à 5).

Certaines opérations (par exemple, y.append(10) et y.sort()) modifient l’objet, alors que des opérations identiques en apparence (par exemple y = y + [10] et sorted(y)) créent un nouvel objet. En général, en Python, une méthode qui modifie un objet renvoie None (c’est même systématique dans la bibliothèque standard) pour éviter la confusion entre les deux opérations. Donc écrire par erreur y.sort() en pensant obtenir une copie triée de y donne None, ce qui conduit très souvent le programme à générer une erreur facile à diagnostiquer.

Il existe cependant une classe d’opérations qui se comporte différemment selon le type : les opérateurs d’affectation incrémentaux. Par exemple, += modifie les listes mais pas les n-uplets ni les entiers (a_list += [1, 2, 3] équivaut à a_list.extend([1, 2, 3]) et modifie a_list, alors que some_tuple += (1, 2, 3) et some_int += 1 créent de nouveaux objets).

En d’autres termes :

Il est possible d’appliquer des opérations qui modifient un objet muable (list, dict, set, etc.) et toutes les variables qui y font référence verront le changement.

Toutes les variables qui font référence à un objet immuable (str, int, tuple, etc.) renvoient la même valeur, mais les opérations qui transforment cette valeur en une nouvelle valeur renvoient toujours un nouvel objet.

L’opérateur is ou la fonction native id() permettent de savoir si deux variables font référence au même objet.

Comment écrire une fonction qui modifie ses paramètres ? (passage par référence)

En Python, les arguments sont passés comme des affectations de variables. Vu qu’une affectation crée des références à des objets, il n’y a pas de lien entre un argument dans l’appel de la fonction et sa définition, et donc pas de passage par référence en soi. Il y a cependant plusieurs façons d’en émuler un.

En renvoyant un n-uplet de résultats :

def func2(a, b):
    a = 'new-value'        # a and b are local names
    b = b + 1              # assigned to new objects
    return a, b            # return new values

x, y = 'old-value', 99
x, y = func2(x, y)
print(x, y)                # output: new-value 100

C’est presque toujours la meilleure solution.

En utilisant des variables globales. Cette approche ne fonctionne pas dans des contextes à plusieurs fils d’exécution (elle n’est pas thread-safe), et n’est donc pas recommandée.

En passant un objet muable (modifiable sur place) :

def func1(a):
    a[0] = 'new-value'     # 'a' references a mutable list
    a[1] = a[1] + 1        # changes a shared object

args = ['old-value', 99]
func1(args)
print(args[0], args[1])    # output: new-value 100

En passant un dictionnaire, qui sera modifié :

def func3(args):
    args['a'] = 'new-value'     # args is a mutable dictionary
    args['b'] = args['b'] + 1   # change it in-place

args = {'a': 'old-value', 'b': 99}
func3(args)
print(args['a'], args['b'])

Ou regrouper les valeurs dans une instance de classe :

class callByRef:
    def __init__(self, **args):
        for (key, value) in args.items():
            setattr(self, key, value)

def func4(args):
    args.a = 'new-value'        # args is a mutable callByRef
    args.b = args.b + 1         # change object in-place

args = callByRef(a='old-value', b=99)
func4(args)
print(args.a, args.b)

Faire quelque chose d’aussi compliqué est rarement une bonne idée.

La meilleure option reste de renvoyer un n-uplet contenant les différents résultats.

Comment construire une fonction d’ordre supérieur en Python ?

Deux possibilités : on peut utiliser des portées imbriquées ou bien des objets appelables. Par exemple, supposons que l’on souhaite définir linear(a, b) qui renvoie une fonction f(x) qui calcule la valeur a*x+b. En utilisant les portées imbriquées :

def linear(a, b):
    def result(x):
        return a * x + b
    return result

Ou en utilisant un objet appelable :

class linear:

    def __init__(self, a, b):
        self.a, self.b = a, b

    def __call__(self, x):
        return self.a * x + self.b

Dans les deux cas

taxes = linear(0.3, 2)

donne un objet appelable où taxes(10e6) == 0.3 * 10e6 + 2.

L’approche par objet appelable a le désavantage d’être légèrement plus lente et de produire un code légèrement plus long. Cependant, il faut noter qu’une collection d’objet appelables peuvent partager leurs signatures par héritage :

class exponential(linear):
    # __init__ inherited
    def __call__(self, x):
        return self.a * (x ** self.b)

Les objets peuvent encapsuler un état pour plusieurs méthodes :

class counter:

    value = 0

    def set(self, x):
        self.value = x

    def up(self):
        self.value = self.value + 1

    def down(self):
        self.value = self.value - 1

count = counter()
inc, dec, reset = count.up, count.down, count.set

Ici inc(), dec() et reset() agissent comme des fonctions partageant une même variable compteur.

Comment copier un objet en Python ?

En général, essayez copy.copy() ou copy.deepcopy(). Tous les objets ne peuvent pas être copiés, mais la plupart le peuvent.

Certains objets peuvent être copiés plus facilement que d’autres. Les dictionnaires ont une méthode copy() :

newdict = olddict.copy()

Les séquences peuvent être copiées via la syntaxe des tranches :

new_l = l[:]

Comment récupérer les méthodes ou les attributs d’un objet ?

Pour une instance x d’une classe définie par un utilisateur, dir(x) renvoie une liste alphabétique des noms contenants les attributs de l’instance, et les attributs et méthodes définies par sa classe.

Comment un code peut-il obtenir le nom d’un objet ?

De façon générale, il ne peut pas, par ce que les objets n’ont pas réellement de noms. Essentiellement, l’assignation attache un nom à une valeur; C’est vrai aussi pour les instructions def et class, à la différence que dans ce cas la valeur est appelable. Par exemple, dans le code suivant :

>>> class A:
...     pass
...
>>> B = A
>>> a = B()
>>> b = a
>>> print(b)
<__main__.A object at 0x16D07CC>
>>> print(a)
<__main__.A object at 0x16D07CC>

Affirmer que la classe a un nom est discutable. Bien qu’elle soit liée à deux noms, et qu’elle soit appelée via le nom B, l’instance créée déclare tout de même être une instance de la classe A. De même, il est impossible de dire si le nom de l’instance est a ou b, les deux noms étant attachés à la même valeur.

De façon générale, une application ne devrait pas avoir besoin de « connaître le nom » d’une valeur particulière. À moins d’être délibérément en train d’écrire un programme introspectif, c’est souvent l’indication qu’un changement d’approche serait bénéfique.

Sur comp.lang.python, Fredrik Lundh a donné un jour une excellente analogie pour répondre à cette question :

C’est pareil que trouver le nom du chat qui traîne devant votre porte : le chat (objet) ne peut pas vous dire lui-même son nom, et il s’en moque un peu – alors le meilleur moyen de savoir comment il s’appelle est de demander à tous vos voisins (espaces de nommage) si c’est leur chat (objet)…

…et ne soyez pas surpris si vous découvrez qu’il est connu sous plusieurs noms, ou s’il n’a pas de nom du tout !

Qu’en est-il de la précédence de l’opérateur virgule ?

La virgule n’est pas un opérateur en Python. Observez le code suivant :

>>> "a" in "b", "a"
(False, 'a')

Comme la virgule n’est pas un opérateur, mais un séparateur entre deux expressions, l’expression ci-dessus est évaluée de la même façon que si vous aviez écrit :

("a" in "b"), "a"

et non :

"a" in ("b", "a")

Ceci est vrai pour tous les opérateurs d’affectation (=, += etc). Ce ne sont pas vraiment des opérateurs mais plutôt des délimiteurs syntaxiques dans les instructions d’affectation.

Existe-t-il un équivalent à l’opérateur ternaire « ?: » du C ?

Oui. Sa syntaxe est la suivante :

[on_true] if [expression] else [on_false]

x, y = 50, 25
small = x if x < y else y

Avant l’introduction de cette syntaxe dans Python 2.5, il était courant d’utiliser les opérateurs de logique :

[expression] and [on_true] or [on_false]

Cet idiome est dangereux, car il donne un résultat erroné quand on_true a la valeur booléenne fausse. Il faut donc toujours utiliser la forme ... if ... else ....

Est-il possible d’écrire des programmes obscurcis (obfuscated) d’une ligne en Python ?

Oui. Cela est généralement réalisé en imbriquant les lambda dans des lambda. Observez les trois exemples suivants de Ulf Bartelt :

from functools import reduce

# Primes < 1000
print(list(filter(None,map(lambda y:y*reduce(lambda x,y:x*y!=0,
map(lambda x,y=y:y%x,range(2,int(pow(y,0.5)+1))),1),range(2,1000)))))

# First 10 Fibonacci numbers
print(list(map(lambda x,f=lambda x,f:(f(x-1,f)+f(x-2,f)) if x>1 else 1:
f(x,f), range(10))))

# Mandelbrot set
print((lambda Ru,Ro,Iu,Io,IM,Sx,Sy:reduce(lambda x,y:x+y,map(lambda y,
Iu=Iu,Io=Io,Ru=Ru,Ro=Ro,Sy=Sy,L=lambda yc,Iu=Iu,Io=Io,Ru=Ru,Ro=Ro,i=IM,
Sx=Sx,Sy=Sy:reduce(lambda x,y:x+y,map(lambda x,xc=Ru,yc=yc,Ru=Ru,Ro=Ro,
i=i,Sx=Sx,F=lambda xc,yc,x,y,k,f=lambda xc,yc,x,y,k,f:(k<=0)or (x*x+y*y
>=4.0) or 1+f(xc,yc,x*x-y*y+xc,2.0*x*y+yc,k-1,f):f(xc,yc,x,y,k,f):chr(
64+F(Ru+x*(Ro-Ru)/Sx,yc,0,0,i)),range(Sx))):L(Iu+y*(Io-Iu)/Sy),range(Sy
))))(-2.1, 0.7, -1.2, 1.2, 30, 80, 24))
#    \___ ___/  \___ ___/  |   |   |__ lines on screen
#        V          V      |   |______ columns on screen
#        |          |      |__________ maximum of "iterations"
#        |          |_________________ range on y axis
#        |____________________________ range on x axis

Les enfants, ne faites pas ça chez vous !

Nombres et chaînes de caractères

Comment écrire des entiers hexadécimaux ou octaux ?

Pour écrire un entier octal, faites précéder la valeur octale par un zéro, puis un « o » majuscule ou minuscule. Par exemple pour affecter la valeur octale « 10 » (8 en décimal) à la variable « a », tapez :

>>> a = 0o10
>>> a
8

L’hexadécimal est tout aussi simple, faites précéder le nombre hexadécimal par un zéro, puis un « x » majuscule ou minuscule. Les nombres hexadécimaux peuvent être écrits en majuscules ou en minuscules. Par exemple, dans l’interpréteur Python :

>>> a = 0xa5
>>> a
165
>>> b = 0XB2
>>> b
178

Pourquoi -22 // 10 donne-t-il -3 ?

Cela est principalement dû à la volonté que i % j ait le même signe que j. Si vous voulez en plus que :

i == (i // j) * j + (i % j)

alors la division entière doit renvoyer l’entier inférieur. Le C impose également que cette égalité soit vérifiée, et donc les compilateurs qui tronquent i // j ont besoin que i % j ait le même signe que i.

Il y a peu de cas d’utilisation réels pour i % j quand j est négatif. Quand j est positif, il y en a beaucoup, et dans pratiquement tous, il est plus utile que i % j soit >=0. Si l’horloge affiche 10 h maintenant, qu’affichait-elle il y a 200 heures ? -190 % 12 == 2 est utile ; -190 % 12 == -10 est un bogue en puissance.

Comment convertir une chaîne de caractères en nombre ?

Pour les entiers, utilisez le constructeur natif de int(), par exemple int('144') == 144. De façon similaire, float() donne la valeur flottante, par exemple float('144') == 144.0.

Par défaut, ces fonctions interprètent les nombres comme des décimaux, de telle façon que int('0144') == 144 et int('0x144') lève une ValueError. Le second argument (optionnel) de int(string, base) est la base dans laquelle convertir, donc int('0x144', 16) == 324. Si la base donnée est 0, le nombre est interprété selon les règles Python : un préfixe 0o indique de l’octal et 0x indique de l’hexadécimal.

N’utilisez pas la fonction native eval() pour convertir des chaînes de caractères en nombres. eval() est beaucoup plus lente et pose des problèmes de sécurité : quelqu’un pourrait vous envoyer une expression Python pouvant avoir des effets de bord indésirables. Par exemple, quelqu’un pourrait passer __import__('os').system("rm -rf $HOME") ce qui effacerait votre répertoire personnel.

eval() a aussi pour effet d’interpréter les nombres comme des expressions Python. Ainsi eval('09') produit une erreur de syntaxe, parce que Python ne permet pas les “0” en tête d’un nombre décimal (à l’exception du nombre “0”).

Comment convertir un nombre en chaîne de caractères ?

Pour transformer, par exemple, le nombre 144 en la chaîne de caractères “144”, il faut utiliser la fonction native str(). Pour obtenir la représentation hexadécimale ou octale, il faut utiliser les fonctions natives hex() ou oct(). Pour des représentations non-conventionnelles, se référer aux sections Chaînes de caractères formatées littérales et Syntaxe de formatage de chaîne, e.g. "{:04d}".format(144) produit '0144' et "{:.3f}".format(1.0/3.0) produit '0.333'.

Comment modifier une chaîne de caractères « sur place » ?

C’est impossible car les chaînes de caractères sont immuables. Dans la plupart des cas, il faut tout simplement construire une nouvelle chaîne à partir des morceaux de l’ancienne. Si toutefois vous avez besoin d’un objet capable de modifier de la donnée Unicode « sur place », essayez d’utiliser un objet io.StringIO ou le module array :

>>> import io
>>> s = "Hello, world"
>>> sio = io.StringIO(s)
>>> sio.getvalue()
'Hello, world'
>>> sio.seek(7)
7
>>> sio.write("there!")
6
>>> sio.getvalue()
'Hello, there!'

>>> import array
>>> a = array.array('u', s)
>>> print(a)
array('u', 'Hello, world')
>>> a[0] = 'y'
>>> print(a)
array('u', 'yello, world')
>>> a.tounicode()
'yello, world'

Comment utiliser des chaînes de caractères pour appeler des fonctions/méthodes ?

Il y a plusieurs façons de faire.

La meilleure est d’utiliser un dictionnaire qui fait correspondre les chaînes de caractères à des fonctions. Le principal avantage de cette technique est que les chaînes n’ont pas besoin d’être égales aux noms de fonctions. C’est aussi la façon principale d’imiter la construction « case » :

def a():
    pass

def b():
    pass

dispatch = {'go': a, 'stop': b}  # Note lack of parens for funcs

dispatch[get_input()]()  # Note trailing parens to call function

Utiliser la fonction getattr() :

import foo
getattr(foo, 'bar')()

Notez que getattr() marche sur n’importe quel objet, ceci inclut les classes, les instances de classes, les modules et ainsi de suite.

Ceci est utilisé à plusieurs reprises dans la bibliothèque standard, de cette façon :

class Foo:
    def do_foo(self):
        ...

    def do_bar(self):
        ...

f = getattr(foo_instance, 'do_' + opname)
f()

Utilisez locals() ou eval() pour résoudre le nom de la fonction :

def myFunc():
    print("hello")

fname = "myFunc"

f = locals()[fname]
f()

f = eval(fname)
f()

Note : utiliser eval() est lent est dangereux. Si vous n’avez pas un contrôle absolu sur le contenu de la chaîne de caractères, quelqu’un pourrait passer une chaîne de caractères pouvant appeler n’importe quelle fonction.

Existe-t-il un équivalent à la fonction chomp() de Perl, pour retirer les caractères de fin de ligne d’une chaîne de caractères ?

Vous pouvez utiliser S.rstrip("\r\n") pour retirer toutes les occurrences de tout marqueur de fin de ligne à la fin d’une chaîne de caractère S, sans en enlever aucune espace. Si la chaîne S représente plus d’une ligne, avec plusieurs lignes vides, les marqueurs de fin de ligne de chaque ligne vide seront retirés :

>>> lines = ("line 1 \r\n"
...          "\r\n"
...          "\r\n")
>>> lines.rstrip("\n\r")
'line 1 '

Vu que cela ne sert presque qu’à lire un texte ligne à ligne, utiliser S.rstrip() de cette manière fonctionne correctement.

Existe-t-il un équivalent à scanf() ou sscanf() ?

Pas exactement.

Pour une simple analyse de chaîne, l’approche la plus simple est généralement de découper la ligne en mots délimités par des espaces, en utilisant la méthode split() des objets chaîne de caractères, et ensuite de convertir les chaînes de décimaux en valeurs numériques en utilisant la fonction int() ou float(). split() possède un paramètre optionnel « sep » qui est utile si la ligne utilise autre chose que des espaces comme séparateurs.

Pour des analyses plus compliquées, les expressions rationnelles sont plus puissantes que la fonction sscanf() de C et mieux adaptées à la tâche.

Que signifient les erreurs UnicodeDecodeError ou UnicodeEncodeError ?

Voir Guide Unicode.

Performances

Mon programme est trop lent. Comment l’accélérer ?

Question difficile en général. Il faut garder en tête les points suivants avant d’aller plus loin :

Les performances varient en fonction des implémentations de Python. Cette FAQ ne traite que de CPython.

Les comportements peuvent différer d’un système d’exploitation à l’autre, tout particulièrement quand il s’agit d’entrée/sortie ou de fils d’exécution multiples.

Il faut toujours essayer de trouver où sont les points de contention d’un programme avant d’essayer d’optimiser du code (voir le module profile).

Écrire des scripts d’évaluation de performances permet de progresser rapidement dans la recherche d’améliorations (voir le module timeit).

Il est très fortement recommandé d’avoir une bonne couverture de code (avec des tests unitaires ou autre) avant d’ajouter des erreurs dans des optimisations sophistiquées.

Ceci étant dit, il y a beaucoup d’astuces pour accélérer du code Python. Voici quelques principes généraux qui peuvent aider à atteindre des niveaux de performance satisfaisants :

Améliorer les algorithmes (ou en changer pour des plus performants) peut produire de bien meilleurs résultats que d’optimiser ça et là de petites portions du code.

Utiliser les structures de données adaptées. Se référer à la documentation des Types natifs et du module collections.

Quand la bibliothèque standard fournit une implémentation pour quelque chose, il y a de fortes chances (même si ce n’est pas systématique) que cette implémentation soit plus rapide que la votre. C’est d’autant plus vrai pour les routines écrites en C, comme les routines natives et certaines extensions de types. Par exemple, il faut utiliser la méthode native list.sort() ou la fonction sorted() similaire pour classer (et se référer à la section Guide pour le tri pour des exemples d’utilisation courante).

Les abstractions ont tendance à créer des indirections et obligent l’interpréteur à faire plus d’efforts. Si le niveau d’indirection dépasse la quantité de travail effectif, le programme sera ralenti. Il faut toujours éviter trop d’indirections, en particulier sous la forme de fonctions ou méthodes trop petites (qui nuisent aussi souvent à la clarté du code).

Si vous atteignez les limites de ce que du Python « pur » permet de faire, il y a des outils qui permettent d’aller plus loin. Par exemple, Cython [http://cython.org] peut compiler une version légèrement modifiée de code Python en une extension C et est disponible sur de nombreuses plate-formes. Cython peut bénéficier de la compilation (et de l’annotation, optionnelle, des types) pour rendre votre code beaucoup plus rapide que s’il était interprété. Si vous avez confiance en vos capacités de programmation en C, vous pouvez aussi écrire un module d’extension en C vous-même.

Voir aussi

La page wiki dédiée aux astuces de performance [https://wiki.python.org/moin/PythonSpeed/PerformanceTips].

Quelle est la manière la plus efficace de concaténer un grand nombre de chaînes de caractères ?

Les objets str et bytes sont immuables, par conséquent concaténer un grand nombre de chaînes de caractères entre elles n’est pas très efficace car chaque concaténation crée un nouvel objet. Dans le cas général, la complexité est quadratique par rapport à la taille totale de la chaîne.

Pour mettre bout-à-bout un grand nombre d’objets str, la technique recommandée consiste à toutes les mettre dans une liste et appeler la méthode str.join() à la fin :

chunks = []
for s in my_strings:
    chunks.append(s)
result = ''.join(chunks)

(une autre technique relativement efficace consiste à utiliser io.StringIO)

Pour concaténer un grand nombre d’objets bytes, la technique recommandée consiste à étendre un objet bytearray en utilisant la concaténation en-place (l’opérateur +=) :

result = bytearray()
for b in my_bytes_objects:
    result += b

Séquences (n-uplets / listes)

Comment convertir les listes en n-uplets et inversement ?

Le constructeur de type tuple(seq) convertit toute séquence (plus précisément, tout itérable) en un n-uplet avec les mêmes éléments dans le même ordre.

Par exemple tuple([1, 2, 3]) renvoie (1, 2, 3) et tuple('abc') renvoie ('a', 'b', 'c'). Si l’argument est un n-uplet, cela ne crée pas de copie, mais renvoie le même objet, ce qui fait de tuple() une fonction économique à appeler quand vous ne savez pas si votre objet est déjà un n-uplet.

Le constructeur de type list(seq) convertit toute séquence ou itérable en liste contenant les mêmes éléments dans le même ordre. Par exemple, list((1,2,3)) renvoie [1,2,3] et list('abc') renvoie ['a','b','c']. Si l’argument est une liste, il renvoie une copie, de la même façon que seq[:].

Qu’est-ce qu’un index négatif ?

Les séquences Python sont indexées avec des nombres positifs aussi bien que négatifs. Pour les nombres positifs, 0 est le premier indice, 1 est le deuxième, et ainsi de suite. Pour les indices négatifs, -1 est le dernier index, -2 est le pénultième (avant-dernier), et ainsi de suite. On peut aussi dire que seq[-n] est équivalent à seq[len(seq)-n].

Utiliser des indices négatifs peut être très pratique. Par exemple S[:-1] représente la chaîne tout entière à l’exception du dernier caractère, ce qui est pratique pour retirer un caractère de fin de ligne à la fin d’une chaîne.

Comment itérer à rebours sur une séquence ?

Utilisez la fonction native reversed(), qui a été introduite en Python 2.4 :

for x in reversed(sequence):
    ...  # do something with x ...

Cela ne modifie pas la séquence initiale, mais construit à la place une copie en ordre inverse pour itérer dessus.

Avec Python 2.3 vous pouvez utiliser la syntaxe étendue de tranches :

for x in sequence[::-1]:
    ...  # do something with x ...

Comment retirer les doublons d’une liste ?

Lisez le « livre de recettes » Python pour trouver une longue discussion sur les nombreuses approches possibles :

https://code.activestate.com/recipes/52560/

Si changer l’ordre de la liste ne vous dérange pas, commencez par ordonner celle-ci, puis parcourez-la d’un bout à l’autre, en supprimant les doublons trouvés en chemin :

if mylist:
    mylist.sort()
    last = mylist[-1]
    for i in range(len(mylist)-2, -1, -1):
        if last == mylist[i]:
            del mylist[i]
        else:
            last = mylist[i]

Si tous les éléments de la liste peuvent être utilisés comme des clés de dictionnaire (c’est à dire, qu’elles sont toutes hachables) ceci est souvent plus rapide

mylist = list(set(mylist))

Ceci convertit la liste en un ensemble, ce qui supprime automatiquement les doublons, puis la transforme à nouveau en liste.

Comment construire un tableau en Python ?

Utilisez une liste :

["this", 1, "is", "an", "array"]

Les listes ont un coût équivalent à celui des tableaux C ou Pascal ; la principale différence est qu’une liste Python peut contenir des objets de différents types.

Le module array fournit des méthodes pour créer des tableaux de types fixes dans une représentation compacte, mais ils sont plus lents à indexer que les listes. Notez aussi que l’extension Numeric (et d’autres) fournissent différentes structures de type tableaux, avec des caractéristiques différentes.

Pour obtenir des listes chaînées à la sauce Lisp, vous pouvez émuler les cons cells en utilisant des n-uplets :

lisp_list = ("like",  ("this",  ("example", None) ) )

Si vous voulez pouvoir modifier les éléments, utilisez une liste plutôt qu’un tuple. Ici la version équivalente du car de Lisp est lisp_list[0] et l’équivalent de cdr est lisp_list[1]. Ne faites ceci que si vous êtes réellement sûr d’en avoir besoin, cette méthode est en général bien plus lente que les listes Python.

Comment créer une liste à plusieurs dimensions ?

Vous avez probablement essayé de créer une liste à plusieurs dimensions de cette façon :

>>> A = [[None] * 2] * 3

Elle semble correcte si on l’affiche :

>>> A
[[None, None], [None, None], [None, None]]

Mais quand vous affectez une valeur, celle-ci apparaît à plusieurs endroits

>>> A[0][0] = 5
>>> A
[[5, None], [5, None], [5, None]]

Dupliquer une liste en utilisant * ne crée en réalité pas de copie mais seulement des références aux objets existants. Le *3 crée une liste contenant trois références à la même liste de longueur deux. Un changement dans une colonne apparaîtra donc dans toutes les colonnes, ce qui n’est très probablement pas ce que vous souhaitiez.

L’approche suggérée est d’abord de créer une liste de la longueur désirée, puis de remplir tous les éléments avec une nouvelle chaîne :

A = [None] * 3
for i in range(3):
    A[i] = [None] * 2

Cela génère une liste contenant elle-même trois listes distinctes, de longueur deux. Vous pouvez aussi utiliser la syntaxe des listes en compréhension :

w, h = 2, 3
A = [[None] * w for i in range(h)]

Vous pouvez aussi utiliser une extension qui fournit un type matriciel natif ; NumPy [http://www.numpy.org/] est la plus répandue.

Comment appliquer une méthode à une séquence d’objets ?

Utilisez une liste en compréhension :

result = [obj.method() for obj in mylist]

Pourquoi a_tuple[i] += ['item'] lève-t-il une exception alors que l’addition fonctionne ?

Ceci est dû à la combinaison de deux facteurs : le fait que les opérateurs d’affectation incrémentaux sont des opérateurs d”affectation et à la différence entre les objets muables et immuables en Python.

Cette discussion est valable, en général, quand des opérateurs d’affectation incrémentale sont appliqués aux éléments d’un n-uplet qui pointe sur des objets muables, mais on prendra list et += comme exemple.

Si vous écrivez :

>>> a_tuple = (1, 2)
>>> a_tuple[0] += 1
Traceback (most recent call last):
   ...
TypeError: 'tuple' object does not support item assignment

La cause de l’exception est claire : 1 est ajouté à l’objet a_tuple[0] qui pointe sur (1), ce qui produit l’objet résultant 2, mais, lorsque l’on tente d’affecter le résultat du calcul, 2, à l’élément 0 du n-uplet, on obtient une erreur car il est impossible de modifier la cible sur laquelle pointe un élément d’un n-uplet.

Sous le capot, une instruction d’affectation incrémentale fait à peu près ceci :

>>> result = a_tuple[0] + 1
>>> a_tuple[0] = result
Traceback (most recent call last):
  ...
TypeError: 'tuple' object does not support item assignment

C’est la partie de l’affectation de l’opération qui génère l’erreur, vu qu’un n-uplet est immuable.

Quand vous écrivez un code du style :

>>> a_tuple = (['foo'], 'bar')
>>> a_tuple[0] += ['item']
Traceback (most recent call last):
  ...
TypeError: 'tuple' object does not support item assignment

L’exception est un peu plus surprenante et, chose encore plus étrange, malgré l’erreur, l’ajout a fonctionné :

>>> a_tuple[0]
['foo', 'item']

Pour comprendre ce qui se passe, il faut savoir que, premièrement, si un objet implémente la méthode magique c, celle-ci est appelée quand l’affectation incrémentale += est exécutée et sa valeur de retour est utilisée dans l’instruction d’affectation ; et que, deuxièmement, pour les listes, __iadd__ équivaut à appeler extend sur la liste et à renvoyer celle-ci. C’est pour cette raison que l’on dit que pour les listes, += est un « raccourci » pour list.extend :

>>> a_list = []
>>> a_list += [1]
>>> a_list
[1]

C’est équivalent à :

>>> result = a_list.__iadd__([1])
>>> a_list = result

L’objet sur lequel pointe a_list a été modifié et le pointeur vers l’objet modifié est réaffecté à a_list. In fine, l’affectation ne change rien, puisque c’est un pointeur vers le même objet que sur lequel pointait a_list, mais l’affectation a tout de même lieu.

Donc, dans notre exemple avec un n-uplet, il se passe quelque chose équivalent à :

>>> result = a_tuple[0].__iadd__(['item'])
>>> a_tuple[0] = result
Traceback (most recent call last):
  ...
TypeError: 'tuple' object does not support item assignment

L’appel à __iadd__ réussit et la liste est étendue, mais bien que result pointe sur le même objet que a_tuple[0], l’affectation finale échoue car les n-uplets ne sont pas muables.

Dictionnaires

Comment puis-je faire stocker et afficher les clefs d’un dictionnaire dans un ordre cohérent ?

Use collections.OrderedDict.

Je souhaite faire un classement compliqué : peut on faire une transformation de Schwartz en Python ?

Cette technique, attribuée à Randal Schwartz de la communauté Perl, ordonne les éléments d’une liste à l’aide une transformation qui fait correspondre chaque élément à sa « valeur de tri ». En Python, ceci est géré par l’argument key de la méthode list.sort() :

Isorted = L[:]
Isorted.sort(key=lambda s: int(s[10:15]))

Comment ordonner une liste en fonction des valeurs d’une autre liste ?

Fusionnez-les dans un itérateur de n-uplets, ordonnez la liste obtenue, puis choisissez l’élément que vous voulez

>>> list1 = ["what", "I'm", "sorting", "by"]
>>> list2 = ["something", "else", "to", "sort"]
>>> pairs = zip(list1, list2)
>>> pairs = sorted(pairs)
>>> pairs
[("I'm", 'else'), ('by', 'sort'), ('sorting', 'to'), ('what', 'something')]
>>> result = [x[1] for x in pairs]
>>> result
['else', 'sort', 'to', 'something']

Vous pouvez remplacer la dernière étape par :

>>> result = []
>>> for p in pairs: result.append(p[1])

Si cela vous semble plus lisible, vous pouvez utiliser cette forme plutôt qu’une liste en compréhension. Toutefois, ce code est presque deux fois plus lent pour une liste de grande taille. Pourquoi ? Tout d’abord, parce que append() doit ré-allouer de la mémoire et, même si elle utilise quelques astuces pour éviter d’effectuer la ré-allocation à chaque appel, elle doit tout de même le faire de temps en temps, ce qui coûte assez cher. Deuxièmement, parce que l’expression result.append fait un accès supplémentaire à un attribut et, enfin, parce que tous ces appels de fonctions réduisent la vitesse d’exécution.

Objets

Qu’est-ce qu’une classe ?

Une classe est le type d’objet particulier créé par l’exécution d’une déclaration de classe. Les objets de classe sont utilisés comme modèles pour créer des objets, qui incarnent à la fois les données (attributs) et le code (méthodes) spécifiques à un type de données.

Une classe peut être fondée sur une ou plusieurs autres classes, appelée sa (ou ses) classe(s) de base. Elle hérite alors des attributs et des méthodes de ses classes de base. Cela permet à un modèle d’objet d’être successivement raffiné par héritage. Vous pourriez avoir une classe générique Mailbox, qui fournit des méthodes d’accès de base pour une boîte aux lettres, et des sous-classes telles que MboxMailbox, MaildirMailbox, OutlookMailbox qui gèrent les plusieurs formats spécifiques de boîtes aux lettres.

Qu’est-ce qu’une méthode ?

Une méthode est une fonction sur un objet x qu’on appelle de manière générale sous la forme x.name(arguments…). Les méthodes sont définies comme des fonctions à l’intérieur de la définition de classe :

class C:
    def meth(self, arg):
        return arg * 2 + self.attribute

Qu’est-ce que self ?

Par convention, le premier argument d’une méthode est appelé self. Une méthode meth(self, a, b, c) doit être appelée sous la forme x.meth(a, b, c) où x est une instance de la classe dans laquelle cette méthode est définie ; tout se passe comme si la méthode était appelée comme meth(x, a, b, c).

Voir aussi Pourquoi « self » doit-il être explicitement utilisé dans les définitions et les appels de méthode ?.

Comment vérifier si un objet est une instance d’une classe donnée ou d’une sous-classe de celle-ci ?

Utilisez la fonction native isinstance(obj, cls). Vous pouvez vérifier qu’un objet est une instance de plusieurs classes à la fois en fournissant un n-uplet à la place d’une seule classe, par exemple, isinstance(obj, (class1, class2, ...)). Vous pouvez également vérifier qu’un objet est l’un des types natifs de Python, par exemple isinstance(obj, str) ou isinstance(obj, (int, float, complex)).

Notez que la plupart des programmes n’utilisent que rarement isInstance() sur les classes définies par l’utilisateur. Si vous développez vous-même des classes, une approche plus orientée-objet consiste définir des méthodes sur les classes qui sont porteuses d’un comportement particulier, plutôt que de vérifier la classe de l’objet et de faire un traitement ad-hoc. Par exemple, si vous avez une fonction qui fait quelque chose :

def search(obj):
    if isinstance(obj, Mailbox):
        ...  # code to search a mailbox
    elif isinstance(obj, Document):
        ...  # code to search a document
    elif ...

Une meilleure approche est de définir une méthode search() dans toutes les classes et qu’il suffit d’appeler de la manière suivante :

class Mailbox:
    def search(self):
        ...  # code to search a mailbox

class Document:
    def search(self):
        ...  # code to search a document

obj.search()

Qu’est-ce que la délégation ?

La délégation est une technique orientée objet (aussi appelée « patron de conception). Prenons un objet x dont on souhaite modifier le comportement d’une seule de ses méthodes. On peut créer une nouvelle classe qui fournit une nouvelle implémentation de la méthode qui nous intéresse dans l’évolution et qui délègue toute autre méthode à la méthode correspondante de x.

Les programmeurs Python peuvent facilement mettre en œuvre la délégation. Par exemple, la classe suivante implémente une classe qui se comporte comme un fichier, mais convertit toutes les données écrites en majuscules :

class UpperOut:

    def __init__(self, outfile):
        self._outfile = outfile

    def write(self, s):
        self._outfile.write(s.upper())

    def __getattr__(self, name):
        return getattr(self._outfile, name)

Ici, la classe UpperOut redéfinit la méthode write() pour convertir la chaîne d’argument en majuscules avant d’appeler la méthode sous-jacentes self.__outfile.write(). Toutes les autres méthodes sont déléguées à l’objet sous-jacent self.__outfile. La délégation se fait par la méthode __getattr__, consulter the language reference pour plus d’informations sur le contrôle d’accès d’attribut.

Notez que pour une utilisation plus générale de la délégation, les choses peuvent se compliquer. Lorsque les attributs doivent être définis aussi bien que récupérés, la classe doit définir une méthode __setattr__() aussi, et il doit le faire avec soin. La mise en œuvre basique de la méthode __setattr__() est à peu près équivalent à ce qui suit :

class X:
    ...
    def __setattr__(self, name, value):
        self.__dict__[name] = value
    ...

La plupart des implémentations de __setattr__() doivent modifier self.__dict__ pour stocker l’état local de self sans provoquer une récursion infinie.

Comment appeler une méthode définie dans une classe de base depuis une classe dérivée qui la surcharge ?

Utilisez la fonction native super() :

class Derived(Base):
    def meth(self):
        super(Derived, self).meth()

Pour les versions antérieures à 3.0, vous pouvez utiliser des classes classiques : pour une définition de classe comme class Derived(Base): ... vous pouvez appeler la méthode meth() définie dans Base (ou l’une des classes de base de Base) en faisant Base.meth(self, arguments...). Ici, Base.meth est une méthode non liée, il faut donc fournir l’argument self.

Comment organiser un code pour permettre de changer la classe de base plus facilement ?

Vous pouvez définir un alias pour la classe de base, lui attribuer la classe de base réelle avant la définition de classe, et utiliser l’alias au long de votre classe. Ensuite, tout ce que vous devez changer est la valeur attribuée à l’alias. Accessoirement, cette astuce est également utile si vous voulez déterminer dynamiquement (par exemple en fonction de la disponibilité des ressources) la classe de base à utiliser. Exemple :

BaseAlias = <real base class>

class Derived(BaseAlias):
    def meth(self):
        BaseAlias.meth(self)
        ...

Comment créer des données statiques de classe et des méthodes statiques de classe ?

Les données statiques et les méthodes statiques (au sens C++ ou Java) sont prises en charge en Python.

Pour les données statiques, il suffit de définir un attribut de classe. Pour attribuer une nouvelle valeur à l’attribut, vous devez explicitement utiliser le nom de classe dans l’affectation :

class C:
    count = 0   # number of times C.__init__ called

    def __init__(self):
        C.count = C.count + 1

    def getcount(self):
        return C.count  # or return self.count

c.count se réfère également à C.count pour tout c tel que isInstance (c, C) est vrai, sauf remplacement par c lui-même ou par une classe sur le chemin de recherche de classe de base de c.__class__ jusqu’à C.

Attention : dans une méthode de C, une affectation comme self.count = 42 crée une nouvelle instance sans rapport avec le nom count dans le dictionnaire de données de self. La redéfinition d’une donnée statique de classe doit toujours spécifier la classe, que l’on soit à l’intérieur d’une méthode ou non :

C.count = 314

Il est possible d’utiliser des méthodes statiques :

class C:
    @staticmethod
    def static(arg1, arg2, arg3):
        # No 'self' parameter!
        ...

Cependant, d’une manière beaucoup plus simple pour obtenir l’effet d’une méthode statique se fait par une simple fonction au niveau du module :

def getcount():
    return C.count

Si votre code est structuré de manière à définir une classe (ou bien la hiérarchie des classes connexes) par module, ceci fournira l’encapsulation souhaitée.

Comment surcharger les constructeurs (ou méthodes) en Python ?

Cette réponse s’applique en fait à toutes les méthodes, mais la question se pose généralement dans le contexte des constructeurs.

En C++, on écrirait

class C {
    C() { cout << "No arguments\n"; }
    C(int i) { cout << "Argument is " << i << "\n"; }
}

En Python, vous devez écrire un constructeur unique qui considère tous les cas en utilisant des arguments par défaut. Par exemple :

class C:
    def __init__(self, i=None):
        if i is None:
            print("No arguments")
        else:
            print("Argument is", i)

Ce n’est pas tout à fait équivalent, mais suffisamment proche dans la pratique.

Vous pouvez aussi utiliser une liste d’arguments de longueur variable, par exemple

def __init__(self, *args):
    ...

La même approche fonctionne pour toutes les définitions de méthode.

J’essaie d’utiliser __spam et j’obtiens une erreur à propos de _SomeClassName__spam.

Les noms de variables commençant avec deux tirets bas sont « déformés », c’est un moyen simple mais efficace de définir des variables privées à une classe. Tout identifiant de la forme __spam (commençant par au moins deux tirets bas et se terminant par au plus un tiret bas) est textuellement remplacé par _classname__spam, où classname est le nom de la classe en cours sans les éventuels tirets bas du début.

Cela ne garantit aucune protection : un utilisateur extérieur peut encore délibérément accéder à l’attribut _classname__spam et les valeurs privées sont visibles dans l’objet __dict__. De nombreux programmeurs Python ne prennent jamais la peine d’utiliser des noms de variable privés.

Ma classe définit __del__ mais elle n’est pas appelée lorsque je supprime l’objet.

Il y a plusieurs explications possibles.

La commande del n’appelle pas forcément __del__() — elle décrémente simplement le compteur de références de l’objet et, si celui-ci arrive à zéro, __del__() est appelée.

Si la structure de données contient des références circulaires (e.g. un arbre dans lequel chaque fils référence son père, et chaque père garde une liste de ses fils), le compteur de références n’arrivera jamais à zéro. Python exécute périodiquement un algorithme pour détecter ce genre de cycles, mais il peut se passer un certain temps entre le moment où la structure est référencée pour la dernière fois et l’appel du ramasse-miettes, donc la méthode __del__() peut être appelée à un moment aléatoire et pas opportun. C’est gênant pour essayer reproduire un problème. Pire, l’ordre dans lequel les méthodes __del__() des objets sont appelées est arbitraire. Il est possible de forcer l’appel du ramasse-miettes avec la fonction gc.collect(), mais il existe certains cas où les objets ne seront jamais nettoyés.

Bien que le ramasse-miette de cycles existe, il est tout de même recommandé de définir une méthode close() explicite sur des objets, et de l’appeler quand leur cycle de vie s’achève. Cette méthode close() peut alors supprimer les attributs qui référencent des sous-objets. Il vaut mieux ne pas appeler la méthode __del__() directement, mais la méthode __del__() devrait appeler la méthode close() et close() doit pouvoir être appelée plusieurs fois sur le même objet.

Une alternative pour éviter les références cycliques consiste à utiliser le module weakref, qui permet de faire référence à des objets sans incrémenter leur compteur de références. Par exemple, les structures d’arbres devraient utiliser des références faibles entre pères et fils (si nécessaire !).

Enfin, si la méthode __del__() lève une exception, un message d’avertissement s’affiche dans sys.stderr.

Comment obtenir toutes les instances d’une classe ?

Python ne tient pas de registre de toutes les instances d’une classe (ni de n’importe quel type natif). Il est cependant possible de programmer le constructeur de la classe de façon à tenir un tel registre, en maintenant une liste de références faibles vers chaque instance.

Pourquoi le résultat de id() peut-il être le même pour deux objets différents ?

La fonction native id() renvoie un entier dont l’unicité est garantie durant toute la vie de l’objet. Vu qu’en CPython cet entier est en réalité l’adresse mémoire de l’objet, il est fréquent qu’un nouvel objet soit alloué à une adresse mémoire identique à celle d’un objet venant d’être supprimé. Comme l’illustre le code suivant :

>>> id(1000)
13901272
>>> id(2000)
13901272

Les deux identifiants appartiennent à des objets entiers créés juste avant l’appel à id() et détruits immédiatement après. Pour s’assurer que les objets dont on veut examiner les identifiants sont toujours en vie, créons une nouvelle référence à l’objet :

>>> a = 1000; b = 2000
>>> id(a)
13901272
>>> id(b)
13891296

Modules

Comment créer des fichiers .pyc ?

Quand un module est importé pour la première fois (ou si le fichier source a été modifié depuis la création du fichier compilé), un fichier .pyc contenant le code précompilé est créé dans un sous-dossier __pycache__ du dossier contentant le fichier .py. Le nom du fichier .pyc est identique au fichier .py et se termine par .pyc, avec une partie centrale qui dépend du binaire python qui l’a créé (voir la PEP 3147 [https://www.python.org/dev/peps/pep-3147] pour de plus amples précisions).

Une des raisons pour lesquelles un fichier .pyc peut ne pas être créé est un problème de droits sur le dossier qui contient le fichier source, ce qui veut dire qu’il est impossible de créer le sous-dossier __pycache__. Ceci peut arriver, par exemple, si vous développez en tant qu’un certain utilisateur, mais que le code est exécuté en tant qu’un autre utilisateur, par exemple pour tester un serveur Web.

La création du fichier .pyc est automatique durant l’import d’un module si Python est capable (en termes de droits, d’espace disque, etc) de créer un sous-dossier __pycache__ et d’écrire le module ainsi compilé dans ce sous-répertoire, à moins que la variable d’environnement PYTHONDONTWRITEBYTECODE soit définie.

Exécuter du Python dans un script de plus haut niveau n’est pas considéré comme un import et le fichier .pyc n’est pas créé. Par exemple, si un module de plus haut niveau foo.py importe un autre module xyz.py, alors à l’exécution de foo (en tapant python foo.py dans la console), un fichier .pyc est créé pour xyz mais pas pour foo car foo.py n’est pas importé.

Pour créer un fichier .pyc pour foo — c’est-à-dire créer un fichier .pyc pour un module qui n’est pas importé — il existe les modules py_compile et compileall.

Le module py_compile peut compiler n’importe quel module manuellement. Il est ainsi possible d’appeler la fonction compile() de manière interactive :

>>> import py_compile
>>> py_compile.compile('foo.py')

Ces lignes écrivent le .pyc dans un sous-dossier __pycache__ à côté de foo.py (le paramètre optionnel cfile permet de changer ce comportement).

Tous les fichiers d’un ou plusieurs dossiers peuvent aussi être compilés avec le module compileall. C’est possible depuis l’invite de commande en exécutant compileall.py avec le chemin du dossier contenant les fichiers Python à compiler :

python -m compileall .

Comment obtenir le nom du module actuel ?

Un module peut déterminer son propre nom en examinant la variable globale prédéfinie __name__. Si celle-ci vaut '__main__', c’est que le programme est exécuté comme un script. Beaucoup de modules qui doivent normalement être importés pour pouvoir être utilisés fournissent aussi une interface en ligne de commande ou un test automatique. Ils n’exécutent cette portion du code qu’après avoir vérifié la valeur de __name__ :

def main():
    print('Running test...')
    ...

if __name__ == '__main__':
    main()

Comment avoir des modules qui s’importent mutuellement ?

Considérons les modules suivants :

foo.py :

from bar import bar_var
foo_var = 1

bar.py :

from foo import foo_var
bar_var = 2

Le problème réside dans les étapes que l’interpréteur va réaliser :

main importe foo

Les variables globales (vides) de foo sont créées

foo est compilé et commence à s’exécuter

foo importe bar

Les variables globales (vides) de bar sont créées

bar est compilé et commence à s’exécuter

bar importe foo (en réalité, rien ne passe car il y a déjà un module appelé foo)

bar.foo_var = foo.foo_var

La dernière étape échoue car Python n’a pas fini d’interpréter foo et le dictionnaire global des symboles de foo est encore vide.

Le même phénomène arrive quand on utilise import foo, et qu’on essaye ensuite d’accéder à foo.foo_var dans le code global.

Il y a (au moins) trois façons de contourner ce problème.

Guido van Rossum déconseille d’utiliser from <module> import ... et de mettre tout le code dans des fonctions. L’initialisation des variables globales et des variables de classe ne doit utiliser que des constantes ou des fonctions natives. Ceci implique que tout ce qui est fourni par un module soit référencé par <module>.<nom>.

Jim Roskind recommande d’effectuer les étapes suivantes dans cet ordre dans chaque module :

les exportations (variables globales, fonctions et les classes qui ne nécessitent d’importer des classes de base)

les instructions import

le code (avec les variables globales qui sont initialisées à partir de valeurs importées).

van Rossum désapprouve cette approche car les importations se trouvent à un endroit bizarre, mais cela fonctionne.

Matthias Urlichs conseille de restructurer le code pour éviter les importations récursives.

Ces solutions peuvent être combinées.

__import__('x.y.z') renvoie <module 'x'> ; comment accéder à z ?

Utilisez plutôt la fonction import_module() de importlib :

z = importlib.import_module('x.y.z')

Quand j’édite un module et que je le réimporte, je ne vois pas les changements. Pourquoi ?

Pour des raisons de performance et de cohérence, Python ne lit le fichier d’un module que la première fois où celui-ci est importé. Si ce n’était pas le cas, dans un programme composé d’un très grand nombre de modules qui importent tous le même module de base, ce module de base serait analysé et ré-analysé un très grand nombre de fois. Pour forcer la relecture d’un module, il faut faire :

import importlib
import modname
importlib.reload(modname)

Attention, cette technique ne marche pas systématiquement. En particulier, les modules qui contiennent des instructions comme

from modname import some_objects

will continue to work with the old version of the imported objects. If the module contains class definitions, existing class instances will not be updated to use the new class definition. This can result in the following paradoxical behaviour:

>>> import importlib
>>> import cls
>>> c = cls.C()                # Create an instance of C
>>> importlib.reload(cls)
<module 'cls' from 'cls.py'>
>>> isinstance(c, cls.C)       # isinstance is false?!?
False

The nature of the problem is made clear if you print out the « identity » of the class objects:

>>> hex(id(c.__class__))
'0x7352a0'
>>> hex(id(cls.C))
'0x4198d0'

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FAQ histoire et design

Sommaire

FAQ histoire et design

Pourquoi Python utilise-t-il l’indentation pour grouper les instructions ?

Pourquoi ai-je d’étranges résultats suite à de simples opérations arithmétiques ?

Pourquoi les calculs à virgules flottantes sont si imprécis ?

Pourquoi les chaînes de caractères Python sont-elles immuables ?

Pourquoi « self » doit-il être explicitement utilisé dans les définitions et les appels de méthode ?

Pourquoi ne puis-je pas utiliser d’assignation dans une expression ?

Pourquoi Python utilise des méthodes pour certaines fonctionnalités (ex : list.index()) mais des fonctions pour d’autres (ex : len(list)) ?

Pourquoi join() est une méthode de chaîne plutôt qu’une de liste ou de tuple ?

À quel point les exceptions sont-elles rapides ?

Pourquoi n’y a-t-il pas une instruction switch ou une structure similaire à switch / case en Python ?

Est-il possible d’émuler des fils d’exécution dans l’interpréteur plutôt que se baser sur les implémentations spécifique aux OS ?

Pourquoi les expressions lambda ne peuvent pas contenir d’instructions ?

Python peut-il être compilé en code machine, en C ou dans un autre langage ?

Comment Python gère la mémoire ?

Pourquoi CPython n’utilise-il pas un ramasse-miette plus traditionnel ?

Pourquoi toute la mémoire n’est pas libérée lorsque CPython s’arrête ?

Pourquoi les tuples et les list sont deux types de données séparés ?

How are lists implemented in CPython?

How are dictionaries implemented in CPython?

Pourquoi les clés du dictionnaire sont immuables ?

Pourquoi list.sort() ne renvoie pas la liste triée ?

Comment spécifiez-vous et appliquez-vous une spécification d’interface en Python ?

Pourquoi n’y a-t-il pas de goto en Python ?

Pourquoi les chaînes de caractères brutes (r-strings) ne peuvent-elles pas se terminer par un backslash ?

Pourquoi la déclaration with pour les assignations d’attributs n’existe pas en Python ?

Pourquoi les deux-points sont-ils nécessaires pour les déclarations if/while/def/class ?

Pourquoi Python permet-il les virgules à la fin des listes et des tuples ?

Pourquoi Python utilise-t-il l’indentation pour grouper les instructions ?

Guido van Rossum considère que l’usage de l’indentation pour regrouper les blocs d’instruction est élégant et contribue énormément à la clarté globale du programme Python. La plupart des gens finissent par aimer cette particularité au bout d’un moment.

Comme il n’y a pas d’accolades de début/fin, il ne peut y avoir de différence entre le bloc perçu par l’analyseur syntaxique et le lecteur humain. Parfois les programmeurs C pourront trouver un morceau de code comme celui-ci :

if (x <= y)
        x++;
        y--;
z++;

Seule l’instruction x++ sera exécutée si la condition est vraie, mais l’indentation pourrait vous faire penser le contraire. Mêmes des développeurs C expérimentés resteront pendant un moment à se demander pourquoi y est décrémenté même si x > y.

Comme il n’y a pas d’accolades de début/fin, Python est moins sujet aux conflits de style de code. En C, on peut placer les accolades de nombreuses façons. Si vous êtes habitués à lire et écrire selon un style particulier, vous pourriez vous sentir perturbé en lisant (ou en devant écrire) avec un autre style.

Nombre de styles de programmation utilisent des accolades de début/fin sur une ligne à part. Cela rend les programmes beaucoup plus longs et fait perdre une bonne partie de l’espace visible sur l’écran, empêchant un peu d’avoir une vue globale du programme. Idéalement, une fonction doit être visible sur un écran (environ 20 ou 30 lignes). 20 lignes de Python peuvent faire beaucoup plus que 20 lignes de C. Ce n’est pas seulement dû à l’absence d’accolades de début/fin – l’absence de déclarations et la présence de types de haut-niveau en sont également responsables – mais la syntaxe basée sur l’indentation aide sûrement.

Pourquoi ai-je d’étranges résultats suite à de simples opérations arithmétiques ?

Voir la question suivante.

Pourquoi les calculs à virgules flottantes sont si imprécis ?

Les gens sont très souvent surpris par des résultats comme celui-ci :

>>> 1.2 - 1.0
0.19999999999999996

et pensent que c’est un bug dans Python. Ça ne l’est pas. Ceci n’a d’ailleurs que peu à voir avec Python, mais avec la manière dont la plateforme sous-jacente gère les nombres à virgule flottante.

La classe float dans CPython utilise le type double du langage C comme stockage. La valeur d’un objet float est stockée dans un format binaire à virgule flottante avec une précision fixe (généralement 53 bits). Python utilise des opérations qui proviennent du langage C qui à leur tour reposent sur l’implémentation au niveau du processeur afin d’effectuer des opérations en virgule flottante. Cela signifie que dans le cadre des opérations sur les nombres à virgule flottante, Python se comporte comme beaucoup de langages populaires dont C et Java.

Beaucoup de nombres pouvant être écrits facilement en notation décimale ne peuvent pas s’exprimer de manière exacte en binaire à virgule flottante. Par exemple, après :

>>> x = 1.2

la valeur stockée pour x est une (très bonne) approximation de la valeur décimale 1.2, mais cette valeur n’est pas exacte. Sur une machine typique, la valeur stockée est en fait :

1.0011001100110011001100110011001100110011001100110011 (binary)

qui est, exactement :

1.1999999999999999555910790149937383830547332763671875 (decimal)

La précision typique de 53 bits des floats Python permet une précision de 15–16 décimales.

Veuillez vous référer au chapitre sur floating point arithmetic du tutoriel python pour de plus amples informations.

Pourquoi les chaînes de caractères Python sont-elles immuables ?

Il y a plusieurs avantages.

La première concerne la performance : savoir qu’une chaîne de caractères est immuable signifie que l’allocation mémoire allouée lors de la création de cette chaîne est fixe et figée. C’est aussi l’une des raisons pour lesquelles on fait la distinction entre les tuples et les listes.

Un autre avantage est que les chaînes en Python sont considérées aussi « élémentaires » que les nombres. Aucun processus ne changera la valeur du nombre 8 en autre chose, et en Python, aucun processus changera la chaîne de caractère « huit » en autre chose.

Pourquoi « self » doit-il être explicitement utilisé dans les définitions et les appels de méthode ?

L’idée a été empruntée à Modula-3. Il s’avère être très utile, pour diverses raisons.

Tout d’abord, il est plus évident d’utiliser une méthode ou un attribut d’instance par exemple au lieu d’une variable locale. Lire self.x ou self.meth() est sans ambiguïté sur le fait que c’est une variable d’instance ou une méthode qui est utilisée, même si vous ne connaissez pas la définition de classe par cœur. En C++, vous pouvez les reconnaitre par l’absence d’une déclaration de variable locale (en supposant que les variables globales sont rares ou facilement reconnaissables) – mais en Python, il n’y a pas de déclarations de variables locales, de sorte que vous devez chercher la définition de classe pour être sûr. Certaines normes de programmation C++ et Java préfixent les attributs d’instance par m_. Cette syntaxe explicite est ainsi utile également pour ces langages.

Ensuite, ça veut dire qu’aucune syntaxe spéciale n’est nécessaire si vous souhaitez explicitement référencer ou appeler la méthode depuis une classe en particulier. En C++, si vous utilisez la méthode d’une classe de base elle-même surchargée par une classe dérivée, vous devez utiliser l’opérateur :: – en Python vous pouvez écrire baseclass.methodname(self, <argument list>). C’est particulièrement utile pour les méthodes __init__(), et de manière générale dans les cas où une classe dérivée veut étendre la méthode du même nom de la classe de base, devant ainsi appeler la méthode de la classe de base d’une certaine manière.

Enfin, pour des variables d’instance, ça résout un problème syntactique pour l’assignation : puisque les variables locales en Python sont (par définition !) ces variables auxquelles les valeurs sont assignées dans le corps d’une fonction (et n’étant pas déclarées explicitement globales), il doit y avoir un moyen de dire à l’interpréteur qu’une assignation est censée assigner une variable d’instance plutôt qu’une variable locale, et doit de préférence être syntactique (pour des raisons d’efficacité). C++ fait ça au travers de déclarations, mais Python n’a pas de déclarations et ça serait dommage d’avoir à les introduire juste pour cette raison. Utiliser explicitement self.var résout ça avec élégance. Pareillement, pour utiliser des variables d’instance, avoir à écrire self.var signifie que les références vers des noms non-qualifiés au sein d’une méthode n’ont pas à être cherchés dans l’annuaire d’instances. En d’autres termes, les variables locales et les variables d’instance vivent dans deux différents espaces de nommage, et vous devez dire à Python quel espace de nommage utiliser.

Pourquoi ne puis-je pas utiliser d’assignation dans une expression ?

De nombreuses personnes habituées à C ou Perl se plaignent de vouloir utiliser cet idiome C :

while (line = readline(f)) {
    // do something with line
}

où en Python vous êtes forcé à écrire ceci :

while True:
    line = f.readline()
    if not line:
        break
    ...  # do something with line

La raison pour ne pas autoriser l’assignation dans les expressions en Python est un bug fréquent, et difficile à trouver dans ces autres langages, causé par cette construction :

if (x = 0) {
    // error handling
}
else {
    // code that only works for nonzero x
}

Cette erreur est une simple coquille : x = 0, qui assigne 0 à la variable x, a été écrit alors que la comparaison x == 0 est certainement ce qui était souhaité.

De nombreuses alternatives ont été proposées. La plupart économisaient quelques touches mais utilisaient des mots clefs ou des syntaxes arbitraires ou cryptiques, et manquaient à la règle que toute proposition de changement de langage devrait respecter : elle doit intuitivement suggérer la bonne signification au lecteur qui n’a pas encore été introduit à cette syntaxe.

Un phénomène intéressant est que la plupart des programmeurs Python expérimentés reconnaissent l’idiome while True et ne semblent pas manquer l’assignation dans la construction de l’expression; seuls les nouveaux-venus expriment un fort désir d’ajouter ceci au langage.

Il y a une manière alternative de faire ça qui semble attrayante mais elle est généralement moins robuste que la solution while True :

line = f.readline()
while line:
    ...  # do something with line...
    line = f.readline()

Le problème avec ceci est que si vous changez d’avis sur la manière dont vous allez récupérer la prochaine ligne (ex : vous voulez changer en sys.stdin.readline()) vous devez vous souvenir de le changer à deux endroits dans votre programme – la deuxième occurrence est cachée en bas de la boucle.

La meilleur approche est d’utiliser les itérateurs, rendant possible de parcourir des objets en utilisant l’instruction for. Par exemple, les objets fichiers gèrent le protocole d’itération, donc vous pouvez simplement écrire :

for line in f:
    ...  # do something with line...

Pourquoi Python utilise des méthodes pour certaines fonctionnalités (ex : list.index()) mais des fonctions pour d’autres (ex : len(list)) ?

As Guido said:

(a) For some operations, prefix notation just reads better than postfix – prefix (and infix!) operations have a long tradition in mathematics which likes notations where the visuals help the mathematician thinking about a problem. Compare the easy with which we rewrite a formula like x*(a+b) into x*a + x*b to the clumsiness of doing the same thing using a raw OO notation.

(b) When I read code that says len(x) I know that it is asking for the length of something. This tells me two things: the result is an integer, and the argument is some kind of container. To the contrary, when I read x.len(), I have to already know that x is some kind of container implementing an interface or inheriting from a class that has a standard len(). Witness the confusion we occasionally have when a class that is not implementing a mapping has a get() or keys() method, or something that isn’t a file has a write() method.

—https://mail.python.org/pipermail/python-3000/2006-November/004643.html

Pourquoi join() est une méthode de chaîne plutôt qu’une de liste ou de tuple ?

Les chaînes sont devenues bien plus comme d’autres types standards à partir de Python 1.6, lorsque les méthodes ont été ajoutées fournissant ainsi les mêmes fonctionnalités que celles qui étaient déjà disponibles en utilisant les fonctions du module string. La plupart de ces nouvelles méthodes ont été largement acceptées, mais celle qui semble rendre certains programmeurs inconfortables est :

", ".join(['1', '2', '4', '8', '16'])

qui donne le résultat :

"1, 2, 4, 8, 16"

Il y a deux arguments fréquents contre cet usage.

Le premier se caractérise par les lignes suivantes : « C’est vraiment moche d’utiliser une méthode de chaîne littérale (chaîne constante) », à laquelle la réponse est qu’il se peut, mais une chaîne littérale est juste une valeur fixe. Si la méthode est autorisée sur des noms liés à des chaînes, il n’y a pas de raison logique à les rendre indisponibles sur des chaînes littérales.

La deuxième objection se réfère typiquement à : « Je suis réellement en train de dire à une séquence de joindre ses membres avec une constante de chaîne ». Malheureusement, vous ne l’êtes pas. Pour quelque raison, il semble être bien moins difficile d’avoir split() en tant que méthode de chaîne, puisque dans ce cas il est facile de voir que

"1, 2, 4, 8, 16".split(", ")

est une instruction à une chaîne littérale de renvoyer les sous-chaînes délimitées par le séparateur fournit (ou, par défaut, les espaces, ou groupes d’espaces).

join() est une méthode de chaîne parce qu’en l’utilisant vous dites au séparateur de chaîne d’itérer une séquence de chaînes et de s’insérer entre les éléments adjacents. Cette méthode peut être utilisée avec n’importe quel argument qui obéit aux règles d’objets séquence, incluant n’importe quelles nouvelles classes que vous pourriez définir vous-même. Des méthodes similaires existent pour des objets bytes et bytearray.

À quel point les exceptions sont-elles rapides ?

Un bloc try / except est extrêmement efficient tant qu’aucune exception ne sont levée. En effet, intercepter une exception s’avère coûteux. Dans les versions de précédant Python 2.0, il était courant d’utiliser cette pratique :

try:
    value = mydict[key]
except KeyError:
    mydict[key] = getvalue(key)
    value = mydict[key]

Cela n’a de sens que si vous vous attendez à ce que le dictionnaire ait la clé presque tout le temps. Si ce n’était pas le cas, vous l’auriez codé comme suit :

if key in mydict:
    value = mydict[key]
else:
    value = mydict[key] = getvalue(key)

Pour ce cas, vous pouvez également utiliser value = dict.setdefault(key, getvalue(key)), mais seulement si l’appel à getvalue() est suffisamment peu coûteux car il est évalué dans tous les cas.

Pourquoi n’y a-t-il pas une instruction switch ou une structure similaire à switch / case en Python ?

Vous pouvez le faire assez facilement avec une séquence de if... elif... elif... else. Il y a eu quelques propositions pour la syntaxe de l’instruction switch, mais il n’y a pas (encore) de consensus sur le cas des intervalles. Voir la PEP 275 [https://www.python.org/dev/peps/pep-0275] pour tous les détails et l’état actuel.

Dans les cas où vous devez choisir parmi un très grand nombre de possibilités, vous pouvez créer un dictionnaire faisant correspondre des valeurs à des fonctions à appeler. Par exemple :

def function_1(...):
    ...

functions = {'a': function_1,
             'b': function_2,
             'c': self.method_1, ...}

func = functions[value]
func()

Pour appeler les méthodes sur des objets, vous pouvez simplifier davantage en utilisant la fonction native getattr() pour récupérer les méthodes avec un nom donné :

def visit_a(self, ...):
    ...
...

def dispatch(self, value):
    method_name = 'visit_' + str(value)
    method = getattr(self, method_name)
    method()

Il est suggéré que vous utilisiez un préfixe pour les noms de méthodes, telles que visit_ dans cet exemple. Sans ce préfixe, si les valeurs proviennent d’une source non fiable, un attaquant serait en mesure d’appeler n’importe quelle méthode sur votre objet.

Est-il possible d’émuler des fils d’exécution dans l’interpréteur plutôt que se baser sur les implémentations spécifique aux OS ?

Réponse 1 : Malheureusement, l’interpréteur pousse au moins un bloc de pile C (stack frame) pour chaque bloc de pile de Python. Aussi, les extensions peuvent rappeler dans Python à presque n’importe quel moment. Par conséquent, une implémentation complète des fils d’exécution nécessiterai un support complet en C.

Réponse 2: Heureusement, il existe Stackless Python, qui à complètement ré-architecturé la boucle principale de l’interpréteur afin de ne pas utiliser la pile C.

Pourquoi les expressions lambda ne peuvent pas contenir d’instructions ?

Les expressions lambda de Python ne peuvent pas contenir d’instructions parce que le cadre syntaxique de Python ne peut pas gérer les instructions imbriquées à l’intérieur d’expressions. Cependant, en Python, ce n’est pas vraiment un problème. Contrairement aux formes lambda dans d’autres langages, où elles ajoutent des fonctionnalités, les expressions lambda de Python sont seulement une notation concise si vous êtes trop paresseux pour définir une fonction.

Les fonctions sont déjà des objets de première classe en Python et peuvent être déclarées dans une portée locale. L’unique avantage d’utiliser une fonction lambda au lieu d’une fonction définie localement est que vous n’avez nullement besoin d’un nom pour la fonction – Mais c’est juste une variable locale à laquelle est affecté l’objet fonction (qui est exactement le même type d’objet qui donne une expression lambda) !

Python peut-il être compilé en code machine, en C ou dans un autre langage ?

Cython [http://cython.org/] compile une version modifiée de Python avec des annotations optionnelles en extensions C. Nuitka [http://www.nuitka.net/] est un nouveau compilateur de Python vers C++, visant à supporter le langage Python entièrement. Pour compiler en Java, vous pouvez regarder VOC [https://voc.readthedocs.io].

Comment Python gère la mémoire ?

Les détails de la gestion de la mémoire en Python dépendent de l’implémentation. En effet, l’implémentation standard de Python, CPython, utilise des compteurs de références afin de détecter des objets inaccessibles et un autre mécanisme pour collecter les références circulaires, exécutant périodiquement un algorithme de détection de cycles qui recherche les cycles inaccessibles et supprime les objets impliqués. Le module gc fournit des fonctions pour lancer le ramasse-miettes, d’obtenir des statistiques de débogage et ajuster ses paramètres.

Cependant, d’autres implémentations (par exemple Jython [http://www.jython.org] ou PyPy [http://www.pypy.org]) peuvent compter sur un mécanisme différent comme un véritable ramasse-miette. Cette différence peut causer de subtils problèmes de portabilité si votre code Python dépend du comportement de l’implémentation du compteur de références.

Dans certaines implémentations de Python, le code suivant (qui marche parfaitement avec CPython) aurait probablement manqué de descripteurs de fichiers :

for file in very_long_list_of_files:
    f = open(file)
    c = f.read(1)

En effet, à l’aide du comptage de références et du destructeur d’objets de CPython, chaque nouvelle affectation à f ferme le fichier précédent. Cependant, avec un GC classique, ces objets seront seulement recueillies (et fermés) à intervalles variables et possiblement avec de longs intervalles.

Si vous souhaitez écrire du code qui fonctionne avec n’importe quelle implémentation de Python, vous devez explicitement fermer le fichier ou utiliser l’instruction with ; ceci fonctionnera indépendamment du système de gestion de la mémoire :

for file in very_long_list_of_files:
    with open(file) as f:
        c = f.read(1)

Pourquoi CPython n’utilise-il pas un ramasse-miette plus traditionnel ?

D’une part, ce n’est pas une caractéristique normalisé en C et par conséquent ce n’est pas portable. (Oui, nous connaissons la bibliothèque GC Boehm. Elle contient du code assembleur pour la plupart des plates-formes classiques, mais pas toutes, et bien qu’elle soit le plus souvent transparent, c’est loin d’être le cas, des correctifs sont nécessaires afin que Python fonctionne correctement avec.)

Le GC classique devient également un problème lorsque Python est incorporé dans d’autres applications. Bien que dans une application Python, il ne soit pas gênant de remplacer les fonctions malloc() et free()` avec les versions fournies par la bibliothèque *GC*, une application incluant Python peut vouloir avoir ses propres implémentations de ``malloc() et free() et peut ne pas vouloir celles de Python. À l’heure actuelle, CPython fonctionne avec n’importe quelle implémentation correcte de malloc() et free().

Pourquoi toute la mémoire n’est pas libérée lorsque CPython s’arrête ?

Les objets référencés depuis les espaces de nommage globaux des modules Python ne sont pas toujours désalloués lorsque Python s’arrête. Cela peut se produire s’il y a des références circulaires. Il y a aussi certaines parties de mémoire qui sont alloués par la bibliothèque C qui sont impossibles à libérer (par exemple un outil comme Purify s’en plaindra). Python est, cependant, agressif sur le nettoyage de la mémoire en quittant et cherche à détruire chaque objet.

Si vous voulez forcer Python à désallouer certains objets en quittant, utilisez le module texit pour exécuter une fonction qui va forcer ces destructions.

Pourquoi les tuples et les list sont deux types de données séparés ?

Les listes et les tuples, bien que semblable à bien des égards, sont généralement utilisés de façons fondamentalement différentes. Les tuples peuvent être considérés comme étant similaires aux dossiers en Pascal ou aux structures en C; Ce sont de petites collections de données associées qui peuvent être de différents types qui sont utilisées ensemble. Par exemple, un repère cartésien est correctement représenté comme un tuple de deux ou trois nombres.

Les listes, ressemblent davantage à des tableaux dans d’autres langues. Elles ont tendance à contenir un nombre variable d’objets de même type manipulés individuellement. Par exemple, os.listdir('.') renvoie une liste de chaînes représentant les fichiers dans le dossier courant. Les fonctions travaillant sur cette sortie accepteraient généralement sans aucun problème que vous ajoutiez un ou deux fichiers supplémentaire dans le dossier.

Les tuples sont immuables, ce qui signifie que lorsqu’un tuple a été créé, vous ne pouvez remplacer aucun de ses éléments par une nouvelle valeur. Les listes sont muables, ce qui signifie que vous pouvez toujours modifier les éléments d’une liste. Seuls des éléments immuables peuvent être utilisés comme clés de dictionnaires, et donc de tuple et list seul des tuples peuvent être utilisés comme clés.

How are lists implemented in CPython?

CPython’s lists are really variable-length arrays, not Lisp-style linked lists. The implementation uses a contiguous array of references to other objects, and keeps a pointer to this array and the array’s length in a list head structure.

Cela rend l’indexation d’une liste a[i] une opération dont le coût est indépendant de la taille de la liste ou de la valeur de l’indice.

Lorsque des éléments sont ajoutés ou insérés, le tableau de références est redimensionné. Un savoir-faire ingénieux permet l’amélioration des performances lors de l’ajout fréquent d’éléments ; Lorsque le tableau doit être étendu, un certain espace supplémentaire est alloué de sorte que pour la prochaine fois, ceci ne nécessite plus un redimensionnement effectif.

How are dictionaries implemented in CPython?

CPython’s dictionaries are implemented as resizable hash tables. Compared to B-trees, this gives better performance for lookup (the most common operation by far) under most circumstances, and the implementation is simpler.

Les dictionnaires fonctionnent en calculant un code de hachage pour chaque clé stockée dans le dictionnaire en utilisant la fonction hash(). Le code de hachage varie grandement selon la clé et du nombre de processus utilisés ; Par exemple, la chaine de caractère « Python » pourrait avoir comme code de hachage une valeur allant jusqu’à-539294296 tandis que la chaine « python »,qui se distingue de la première par un seul bit, pourrait avoir comme code de hachage une valeur allant jusqu’à 1142331976. Le code de hachage est ensuite utilisé pour calculer un emplacement dans un tableau interne où la valeur est stockée. Dans l’hypothèse où vous stockez les clés qui ont toutes des valeurs de hachage différentes, cela signifie que les dictionnaires parcourt le dictionnaire en un temps constant – O(1), en notation scientifique informatique - - pour récupérer une clé. Cela signifie également qu’aucun ordre de tri des clés n’est maintenu, et lors du parcours du tableau, les .keys() et .items() afficheront le contenu du dictionnaire dans un certain ordre arbitraire qui peut changer à chaque appel d’un programme.

Pourquoi les clés du dictionnaire sont immuables ?

L’implémentation de la table de hachage des dictionnaires utilise une valeur de hachage calculée à partir de la valeur de la clé pour trouver la clé elle-même. Si la clé était un objet muable, sa valeur peut changer, et donc son hachage pourrait également changer. Mais toute personne modifiant l’objet clé ne peut pas dire qu’elle a été utilisée comme une clé de dictionnaire. Il ne peut déplacer l’entrée dans le dictionnaire. Ainsi, lorsque vous essayez de rechercher le même objet dans le dictionnaire, il ne sera pas disponible parce que sa valeur de hachage est différente. Si vous essayez de chercher l’ancienne valeur, elle serait également introuvable car la valeur de l’objet trouvé dans cet emplacement de hachage serait différente.

Si vous voulez un dictionnaire indexé avec une liste, il faut simplement convertir la liste en un tuple ; la fonction tuple(L) crée un tuple avec les mêmes entrées que la liste L. Les tuples sont immuables et peuvent donc être utilisés comme clés du dictionnaire.

Certaines solutions insatisfaisantes qui ont été proposées :

Les listes de hachage par leur adresse (ID de l’objet). Cela ne fonctionne pas parce que si vous créez une nouvelle liste avec la même valeur, elle ne sera pas retrouvée; par exemple :

mydict = {[1, 2]: '12'}
print(mydict[[1, 2]])

cela lèverait une exception de type KeyError car l’ID de [1, 2] utilisé dans la deuxième ligne diffère de celle de la première ligne. En d’autres termes, les clés de dictionnaire doivent être comparées à l’aide du comparateur == et non à l’aide du mot clé is.

Faire une copie lors de l’utilisation d’une liste en tant que clé. Cela ne fonctionne pas puisque la liste, étant un objet muable, pourrait contenir une référence à elle-même ou avoir une boucle infinie au niveau du code copié.

Autoriser les listes en tant que clés, mais indiquer à l’utilisateur de ne pas les modifier. Cela permettrait un ensemble de bogues difficiles à suivre dans les programmes lorsque vous avez oublié ou modifié une liste par accident. Cela casse également un impératif important des dictionnaires : chaque valeur de d.keys() est utilisable comme clé du dictionnaire.

Marquer les listes comme étant en lecture seule une fois qu’elles sont utilisées comme clé de dictionnaire. Le problème est que ce n’est pas seulement l’objet de niveau supérieur qui pourrait changer sa valeur; vous pourriez utiliser un tuple contenant une liste comme clé. Utiliser n’importe quoi comme une clé dans un dictionnaire nécessiterait de marquer tous les objets accessibles à partir de là comme en lecture seule – et encore une fois, les objets se faisant référence pourraient provoquer une boucle infinie.

Il y a un truc pour contourner ceci si vous en avez besoin, mais utilisez-le à vos risques et périls. Vous pouvez encapsuler une structure mutable à l’intérieur d’une instance de classe qui a à la fois une méthode __eq__() et __hash__(). Vous devez ensuite vous assurer que la valeur de hachage pour tous ces objets wrapper qui résident dans un dictionnaire (ou une autre structure basée sur le hachage), restent fixes pendant que l’objet est dans le dictionnaire (ou une autre structure).

class ListWrapper:
    def __init__(self, the_list):
        self.the_list = the_list

    def __eq__(self, other):
        return self.the_list == other.the_list

    def __hash__(self):
        l = self.the_list
        result = 98767 - len(l)*555
        for i, el in enumerate(l):
            try:
                result = result + (hash(el) % 9999999) * 1001 + i
            except Exception:
                result = (result % 7777777) + i * 333
        return result

Notez que le calcul de hachage peut être compliqué car il est possible que certains membres de la liste peuvent être impossible à hacher et aussi par la possibilité de débordement arithmétique.

De plus, il faut toujours que, si o1 == o2 (par exemple o1.__eq__(o2) vaut True) alors hash(o1) == hash(o2) (par exemple, o1.__hash__() == o2.__hash__()), que l’objet se trouve dans un dictionnaire ou pas. Si vous ne remplissez pas ces conditions, les dictionnaires et autres structures basées sur le hachage se comporteront mal.

Dans le cas de ListWrapper, chaque fois que l’objet wrapper est dans un dictionnaire, la liste encapsulée ne doit pas changer pour éviter les anomalies. Ne faites pas cela à moins que vous n’ayez pensé aux potentielles conséquences de ne pas satisfaire entièrement ces conditions. Vous avez été prévenus.

Pourquoi list.sort() ne renvoie pas la liste triée ?

Dans les situations où la performance est importante, faire une copie de la liste juste pour la trier serait un gaspillage. Par conséquent, list.sort() trie la liste en place. Afin de vous le rappeler, il ne retourne pas la liste triée. De cette façon, vous ne serez pas dupés en écrasant accidentellement une liste lorsque vous avez besoin d’une copie triée, mais vous devrez également garder sous la main la version non triée.

Si vous souhaitez retourner une nouvelle liste, utilisez plutôt la fonction native sorted(). Cette fonction crée une nouvelle liste à partir d’un itérable fourni, la trie et la retourne. Par exemple, voici comment itérer sur les clefs d’un dictionnaire dans l’ordre trié :

for key in sorted(mydict):
    ...  # do whatever with mydict[key]...

Comment spécifiez-vous et appliquez-vous une spécification d’interface en Python ?

Une spécification d’interface pour un module fourni par des langages tels que C++ et Java décrit les prototypes pour les méthodes et les fonctions du module. Beaucoup estiment que la vérification au moment de la compilation des spécifications d’interface aide à la construction de grands programmes.

Python 2.6 ajoute un module abc qui vous permet de définir des classes de base abstraites (ABCs). Vous pouvez ensuite utiliser isinstance() et issubclass() pour vérifier si une instance ou une classe implémente une ABC particulière. Le module collections.abc définit un ensemble d’ABCs utiles telles que Iterable, Container et collections.abc.MutableMapping.

Pour Python, la plupart des avantages des spécifications d’interface peuvent être obtenus par une discipline de test appropriée pour les composants. Il existe aussi un outil, PyChecker, qui peut être utilisé pour trouver des problèmes d’héritage.

Une bonne suite de tests pour un module peut à la fois fournir un test de non régression et servir de spécification d’interface de module ainsi qu’un ensemble d’exemples. De nombreux modules Python peuvent être exécutés en tant que script pour fournir un simple « auto-test ». Même les modules qui utilisent des interfaces externes complexes peuvent souvent être testés isolément à l’aide d’émulations triviales embryonnaires de l’interface externe. Les modules doctest et UnitTest ou des frameworks de test tiers peuvent être utilisés pour construire des suites de tests exhaustives qui éprouvent chaque ligne de code dans un module.

Une discipline de test appropriée peut aider à construire des applications complexes de grande taille en Python aussi bien que le feraient des spécifications d’interface. En fait, c’est peut être même mieux parce qu’une spécification d’interface ne peut pas tester certaines propriétés d’un programme. Par exemple, la méthode Append() est censée ajouter de nouveaux éléments à la fin d’une liste « sur place » ; une spécification d’interface ne peut pas tester que votre implémentation de append() va réellement le faire correctement, mais il est trivial de vérifier cette propriété dans une suite de tests.

L’écriture des suites de tests est très utile, et vous voudrez peut-être concevoir votre code de manière à le rendre facilement testable. Une technique de plus en plus populaire, le développement dirigé par les tests, requiert d’écrire d’abord des éléments de la suite de tests, avant d’écrire le code réel. Bien sûr, Python vous permet d’être laxiste et de ne pas écrire de test du tout.

Pourquoi n’y a-t-il pas de goto en Python ?

Vous pouvez utiliser les exceptions afin de mettre en place un « goto structuré » qui fonctionne même avec les appels de fonctions. Beaucoup de personnes estiment que les exceptions peuvent émuler idéalement tout utilisation raisonnable des constructions go ou goto en C, en Fortran ou autres langages de programmation. Par exemple :

class label(Exception): pass  # declare a label

try:
    ...
    if condition: raise label()  # goto label
    ...
except label:  # where to goto
    pass
...

Cela ne vous permet pas de sauter au milieu d’une boucle. Néanmoins, dans tous les cas cela est généralement considéré comme un abus de goto. À Utiliser avec parcimonie.

Pourquoi les chaînes de caractères brutes (r-strings) ne peuvent-elles pas se terminer par un backslash ?

Plus précisément, elles ne peuvent pas se terminer par un nombre impair de backslashes : le backslash non appairé à la fin échappe le caractère de guillemet final, laissant une chaîne non terminée.

Les chaînes brutes ont été conçues pour faciliter la création de données pour les processeurs de texte (principalement les moteurs d’expressions régulières) qui veulent faire leur propre traitement d’échappement d”antislashes. Ces processeurs considèrent un antislash de fin non-appairé comme une erreur, alors les chaînes brutes ne le permettent pas. En retour, elles vous permettent de transmettre le caractère de citation de la chaîne en l’échappant avec un antislash. Ces règles fonctionnent bien lorsque les chaînes brutes sont utilisées pour leur but premier.

Si vous essayez de construire des chemins d’accès Windows, notez que tous les appels système Windows acceptent également les slashes « classiques » :

f = open("/mydir/file.txt")  # works fine!

Si vous essayez de construire un chemin d’accès pour une commande DOS, essayez par exemple l’un de ceux-là

dir = r"\this\is\my\dos\dir" "\\"
dir = r"\this\is\my\dos\dir\ "[:-1]
dir = "\\this\\is\\my\\dos\\dir\\"

Pourquoi la déclaration with pour les assignations d’attributs n’existe pas en Python ?

Python a une instruction with qui encapsule l’exécution d’un bloc, en appelant le code sur l’entrée et la sortie du bloc. Certains langages possèdent une construction qui ressemble à ceci :

with obj:
    a = 1               # equivalent to obj.a = 1
    total = total + 1   # obj.total = obj.total + 1

En Python, une telle construction serait ambiguë.

Les autres langages, tels que le Pascal, le Delphi et le C++ utilisent des types statiques, il est donc possible de savoir d’une manière claire et directe ce à quoi est attribué un membre. C’est le point principal du typage statique –le compilateur connaît toujours la portée de toutes les variables au moment de la compilation.

Python utilise le typage dynamique. Il est impossible de savoir à l’avance quel attribut est utilisé comme référence lors de l’exécution. Les attributs membres peuvent être ajoutés ou retirés des objets à la volée. Il est donc impossible de savoir, d’une simple lecture, quel attribut est référencé : s’il est local, global ou un attribut membre?

Prenons par exemple l’extrait incomplet suivant :

def foo(a):
    with a:
        print(x)

L’extrait suppose que « a » doit avoir un attribut membre appelé « x ». Néanmoins, il n’y a rien en Python qui en informe l’interpréteur. Que se passe-t-il si « a » est, disons, un entier ? Si une variable globale nommée « x » existe, sera-t-elle utilisée dans le bloc with ? Comme vous voyez, la nature dynamique du Python rend ces choix beaucoup plus difficiles.

L’avantage principal de with et des fonctionnalités de langage similaires (réduction du volume de code) peut, cependant, être facilement réalisé en Python par assignation. Au lieu de :

function(args).mydict[index][index].a = 21
function(args).mydict[index][index].b = 42
function(args).mydict[index][index].c = 63

écrivez ceci :

ref = function(args).mydict[index][index]
ref.a = 21
ref.b = 42
ref.c = 63

Cela a également pour effet secondaire d’augmenter la vitesse d’exécution car les liaisons de noms sont résolues au moment de l’exécution en Python, et la deuxième version n’a besoin d’exécuter la résolution qu’une seule fois.

Pourquoi les deux-points sont-ils nécessaires pour les déclarations if/while/def/class ?

Le deux-points est principalement nécessaires pour améliorer la lisibilité (l’un des résultats du langage expérimental ABC). Considérez ceci :

if a == b
    print(a)

versus

if a == b:
    print(a)

Remarquez comment le deuxième est un peu plus facile à lire. Remarquez aussi comment un deux-points introduit l’exemple dans cette réponse à la FAQ ; c’est un usage standard en anglais.

Une autre raison mineure est que les deux-points facilitent la tâche des éditeurs avec coloration syntaxique ; ils peuvent rechercher les deux-points pour décider quand l’indentation doit être augmentée au lieu d’avoir à faire une analyse plus élaborée du texte du programme.

Pourquoi Python permet-il les virgules à la fin des listes et des tuples ?

Python vous permet d’ajouter une virgule à la fin des listes, des tuples et des dictionnaires :

[1, 2, 3,]
('a', 'b', 'c',)
d = {
    "A": [1, 5],
    "B": [6, 7],  # last trailing comma is optional but good style
}

Il y a plusieurs raisons d’accepter cela.

Lorsque vous avez une valeur littérale pour une liste, un tuple ou un dictionnaire réparti sur plusieurs lignes, il est plus facile d’ajouter plus d’éléments parce que vous n’avez pas besoin de vous rappeler d’ajouter une virgule à la ligne précédente. Les lignes peuvent aussi être réorganisées sans créer une erreur de syntaxe.

L’omission accidentelle de la virgule peut entraîner des erreurs difficiles à diagnostiquer, par exemple :

x = [
  "fee",
  "fie"
  "foo",
  "fum"
]

Cette liste a l’air d’avoir quatre éléments, mais elle en contient en fait trois : « fee », « fiefoo » et « fum ». Toujours ajouter la virgule permet d’éviter cette source d’erreur.

Permettre la virgule de fin peut également faciliter la génération de code.

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FAQ sur la bibliothèque et les extensions

Sommaire

FAQ sur la bibliothèque et les extensions

Questions générales sur la bibliothèque

Comment trouver un module ou une application pour effectuer la tâche X ?

Où sont stockés les fichiers sources math.py, socket.py, regex.py, etc ?

Comment rendre un script Python exécutable sous Unix ?

Existe-t’il un module curse ou termcap en Python ?

Existe-t’il un équivalent à la fonction C onexit() en Python ?

Pourquoi mes gestionnaires de signaux ne fonctionnent-t’ils pas ?

Tâches fréquentes

Comment tester un programme ou un composant Python ?

Comment générer la documentation à partir des docstrings ?

Comment détecter qu’une touche est pressée ?

Fils d’exécution

Comment programmer avec des fils d’exécution ?

Aucun de mes fils ne semble s’exécuter : pourquoi ?

Comment découper et répartir une tâche au sein d’un ensemble de fils d’exécutions ?

Quels types de mutations sur des variables globales sont compatibles avec les programmes à fils d’exécution multiples ? sécurisé ?

Pourquoi ne pas se débarrasser du verrou global de l’interpréteur ?

Les entrées/sorties

Comment supprimer un fichier ? (et autres questions sur les fichiers…)

Comment copier un fichier ?

Comment lire (ou écrire) des données binaires ?

Il me semble impossible d’utiliser os.read() sur un tube créé avec os.popen() ; pourquoi ?

Comment accéder au port de transmission en série (RS-232) ?

Pourquoi fermer sys.stdout, sys.stdin, sys.stderr ne les ferme pas réellement ?

Programmation réseau et Internet

Quels sont les outils Python dédiés à la Toile ?

Comment reproduire un envoi de formulaire CGI (METHOD=POST) ?

Quel module utiliser pour générer du HTML ?

Comment envoyer un courriel avec un script Python ?

Comment éviter de bloquer dans la méthode connect() d’un connecteur réseau ?

Bases de données

Existe-t’il des modules Python pour s’interfacer avec des bases de données ?

Comment implémenter la persistance d’objets en Python ?

Mathématiques et calcul numérique

Comment générer des nombres aléatoires en Python ?

Questions générales sur la bibliothèque

Comment trouver un module ou une application pour effectuer la tâche X ?

Regardez si la bibliothèque standard contient un module approprié (avec l’expérience, vous connaitrez le contenu de la bibliothèque standard et pourrez sauter cette étape).

Pour des paquets tiers, regardez dans l’index des paquets Python [https://pypi.org] ou essayez Google [https://www.google.com] ou un autre moteur de recherche (NDT : comme le moteur français Qwant [https://www.qwant.com]). Rechercher « Python » accompagné d’un ou deux mots-clés se rapportant à ce qui vous intéresse donne souvent de bons résultats.

Où sont stockés les fichiers sources math.py, socket.py, regex.py, etc ?

Si vous ne parvenez pas à trouver le fichier source d’un module, c’est peut-être parce que celui-ci est un module natif ou bien un module implémenté en C, C++, ou autre langage compilé, qui est chargé dynamiquement. Dans ce cas, vous ne possédez peut-être pas le fichier source ou celui-ci est en réalité stocké quelque part dans un dossier de fichiers source C (qui ne sera pas dans le chemin Python), comme par exemple mathmodule.c.

Il y a (au moins) trois types de modules dans Python :

les modules écrits en Python (.py) ;

les modules écrits en C et chargés dynamiquement (.dll, .pyd, .so, .sl, etc.) ;

les modules écrits en C et liés à l’interpréteur ; pour obtenir leur liste, entrez :

import sys
print(sys.builtin_module_names)

Comment rendre un script Python exécutable sous Unix ?

Deux conditions doivent être remplies : les droits d’accès au fichier doivent permettre son exécution et la première ligne du script doit commencer par #! suivi du chemin vers l’interpréteur Python.

La première condition est remplie en exécutant chmod +x scriptfile ou chmod 755 scriptfile.

Il y a plusieurs façons de remplir la seconde. La plus simple consiste à écrire au tout début du fichier

#!/usr/local/bin/python

en utilisant le chemin de l’interpréteur Python sur votre machine.

Pour rendre ce script indépendant de la localisation de l’interpréteur Python, il faut utiliser le programme env. La ligne ci-dessous fonctionne sur la quasi-totalité des dérivés de Unix, à condition que l’interpréteur Python soit dans un dossier référencé dans la variable PATH de l’utilisateur :

#!/usr/bin/env python

Ne faites pas ceci pour des scripts CGI. La variable PATH des scripts CGI est souvent très succincte, il faut par conséquent préciser le chemin absolu réel de l’interpréteur.

Il peut arriver que l’environnement d’un utilisateur soit si chargé que le programme /usr/bin/env échoue ; ou que le programme env n’existe pas du tout. Dans ce cas, vous pouvez utiliser l’astuce suivante, élaborée par Alex Rezinsky :

#! /bin/sh
""":"
exec python $0 ${1+"$@"}
"""

Le léger inconvénient est que cela définit la variable __doc__ du script. Cependant, il est possible de corriger cela en ajoutant

__doc__ = """...Whatever..."""

Existe-t’il un module curse ou termcap en Python ?

Pour les dérivés d’Unix : la distribution standard de Python contient un module curses dans le sous-dossier Modules [https://github.com/python/cpython/tree/3.6/Modules], bien qu’il ne soit pas compilé par défaut. Il n’est pas disponible en Windows — le module curses n’existant pas en Windows.

Le module curses comprend les fonctionnalités de base de curses et beaucoup de fonctionnalités supplémentaires provenant de ncurses et de SYSV curses comme la couleur, la gestion des ensembles de caractères alternatifs, la prise en charge du pavé tactile et de la souris. Cela implique que le module n’est pas compatible avec des systèmes d’exploitation qui n’ont que le curses de BSD mais, de nos jours, de tels systèmes d’exploitation ne semblent plus exister ou être maintenus.

Pour Windows : utilisez le module consolelib [http://effbot.org/zone/console-index.htm].

Existe-t’il un équivalent à la fonction C onexit() en Python ?

Le module atexit fournit une fonction d’enregistrement similaire à la fonction C onexit().

Pourquoi mes gestionnaires de signaux ne fonctionnent-t’ils pas ?

Le problème le plus courant est d’appeler le gestionnaire de signaux avec les mauvais arguments. Un gestionnaire est appelé de la façon suivante

handler(signum, frame)

donc il doit être déclaré avec deux paramètres :

def handler(signum, frame):
    ...

Tâches fréquentes

Comment tester un programme ou un composant Python ?

Python fournit deux cadriciels de test. Le module doctest cherche des exemples dans les docstrings d’un module et les exécute. Il compare alors la sortie avec la sortie attendue, telle que définie dans la docstring.

Le module unittest est un cadriciel un peu plus élaboré basé sur les cadriciels de test de Java et de Smalltalk.

Pour rendre le test plus aisé, il est nécessaire de bien découper le code d’un programme. Votre programme doit avoir la quasi-totalité des fonctionnalités dans des fonctions ou des classes — et ceci a parfois l’avantage aussi plaisant qu’inattendu de rendre le programme plus rapide, les accès aux variables locales étant en effet plus rapides que les accès aux variables globales. De plus le programme doit éviter au maximum de manipuler des variables globales, car ceci rend le test beaucoup plus difficile.

La « logique générale » d’un programme devrait être aussi simple que

if __name__ == "__main__":
    main_logic()

à la fin du module principal du programme.

Une fois que la logique du programme est implémentée par un ensemble de fonctions et de comportements de classes, il faut écrire des fonctions de test qui vont éprouver cette logique. À chaque module, il est possible d’associer une suite de tests qui joue de manière automatique un ensemble de tests. Au premier abord, il semble qu’il faille fournir un effort conséquent, mais comme Python est un langage concis et flexible, c’est surprenamment aisé. Écrire simultanément le code « de production » et les fonctions de test associées rend le développement plus agréable et plus amusant, car ceci permet de trouver des bogues, voire des défauts de conception, plus facilement.

Les « modules auxiliaires » qui n’ont pas vocation à être le module principal du programme peuvent inclure un test pour se vérifier eux-mêmes.

if __name__ == "__main__":
    self_test()

Les programmes qui interagissent avec des interfaces externes complexes peuvent être testés même quand ces interfaces ne sont pas disponibles, en utilisant des interfaces « simulacres » implémentées en Python.

Comment générer la documentation à partir des docstrings ?

Le module pydoc peut générer du HTML à partir des docstrings du code source Python. Il est aussi possible de documenter une API uniquement à partir des docstrings à l’aide de epydoc [http://epydoc.sourceforge.net/]. Sphinx [http://sphinx-doc.org] peut également inclure du contenu provenant de docstrings.

Comment détecter qu’une touche est pressée ?

Pour les dérivés d’Unix, plusieurs solutions s’offrent à vous. C’est facile en utilisant le module curses, mais curses est un module assez conséquent à apprendre.

Fils d’exécution

Comment programmer avec des fils d’exécution ?

Veillez à bien utiliser le module threading et non le module _thread. Le module threading fournit une abstraction plus facile à manipuler que les primitives de bas-niveau du module _thread.

Un ensemble de diapositives issues du didacticiel de Aahz sur les fils d’exécution est disponible à http://www.pythoncraft.com/OSCON2001/.

Aucun de mes fils ne semble s’exécuter : pourquoi ?

Dès que le fil d’exécution principal se termine, tous les fils sont tués. Le fil principal s’exécute trop rapidement, sans laisser le temps aux autres fils de faire quoi que ce soit.

Une correction simple consiste à ajouter un temps d’attente suffisamment long à la fin du programme pour que tous les fils puissent se terminer :

import threading, time

def thread_task(name, n):
    for i in range(n):
        print(name, i)

for i in range(10):
    T = threading.Thread(target=thread_task, args=(str(i), i))
    T.start()

time.sleep(10)  # <---------------------------!

Mais à présent, sur beaucoup de plates-formes, les fils ne s’exécutent pas en parallèle, mais semblent s’exécuter de manière séquentielle, l’un après l’autre ! En réalité, l’ordonnanceur de fils du système d’exploitation ne démarre pas de nouveau fil avant que le précédent ne soit bloqué.

Une correction simple consiste à ajouter un petit temps d’attente au début de la fonction :

def thread_task(name, n):
    time.sleep(0.001)  # <--------------------!
    for i in range(n):
        print(name, i)

for i in range(10):
    T = threading.Thread(target=thread_task, args=(str(i), i))
    T.start()

time.sleep(10)

Au lieu d’essayer de trouver une bonne valeur d’attente pour la fonction time.sleep(), il vaut mieux utiliser un mécanisme basé sur les sémaphores. Une solution consiste à utiliser le module queue pour créer un objet file, faire en sorte que chaque fil ajoute un jeton à la file quand il se termine, et que le fil principal retire autant de jetons de la file qu’il y a de fils.

Comment découper et répartir une tâche au sein d’un ensemble de fils d’exécutions ?

La manière la plus simple est d’utiliser le nouveau module concurrent.futures, en particulier la classe ThreadPoolExecutor.

Ou bien, si vous désirez contrôler plus finement l’algorithme de distribution, vous pouvez écrire votre propre logique « à la main ». Utilisez le module queue pour créer une file de tâches ; la classe Queue gère une liste d’objets et a une méthode .put(objet) pour ajouter un élément à la file, et une méthode .get() pour les récupérer. La classe s’occupe de gérer les verrous pour que chaque tâche soit exécutée une et une seule fois.

Voici un exemple trivial :

import threading, queue, time

# The worker thread gets jobs off the queue.  When the queue is empty, it
# assumes there will be no more work and exits.
# (Realistically workers will run until terminated.)
def worker():
    print('Running worker')
    time.sleep(0.1)
    while True:
        try:
            arg = q.get(block=False)
        except queue.Empty:
            print('Worker', threading.currentThread(), end=' ')
            print('queue empty')
            break
        else:
            print('Worker', threading.currentThread(), end=' ')
            print('running with argument', arg)
            time.sleep(0.5)

# Create queue
q = queue.Queue()

# Start a pool of 5 workers
for i in range(5):
    t = threading.Thread(target=worker, name='worker %i' % (i+1))
    t.start()

# Begin adding work to the queue
for i in range(50):
    q.put(i)

# Give threads time to run
print('Main thread sleeping')
time.sleep(5)

Quand celui-ci est exécuté, il produit la sortie suivante :

Running worker
Running worker
Running worker
Running worker
Running worker
Main thread sleeping
Worker <Thread(worker 1, started 130283832797456)> running with argument 0
Worker <Thread(worker 2, started 130283824404752)> running with argument 1
Worker <Thread(worker 3, started 130283816012048)> running with argument 2
Worker <Thread(worker 4, started 130283807619344)> running with argument 3
Worker <Thread(worker 5, started 130283799226640)> running with argument 4
Worker <Thread(worker 1, started 130283832797456)> running with argument 5
...

Consultez la documentation du module pour plus de détails ; la classe Queue fournit une interface pleine de fonctionnalités.

Quels types de mutations sur des variables globales sont compatibles avec les programmes à fils d’exécution multiples ? sécurisé ?

Le verrou global de l’interpréteur (GIL pour global interpreter lock) est utilisé en interne pour s’assurer que la machine virtuelle Python (MVP) n’exécute qu’un seul fil à la fois. De manière générale, Python ne change de fil qu’entre les instructions du code intermédiaire ; sys.setswitchinterval() permet de contrôler la fréquence de bascule entre les fils. Chaque instruction du code intermédiaire, et, par conséquent, tout le code C appelé par cette instruction est donc atomique du point de vue d’un programme Python.

En théorie, cela veut dire qu’un décompte exact nécessite une connaissance parfaite de l’implémentation de la MVP. En pratique, cela veut dire que les opérations sur des variables partagées de type natif (les entier, les listes, les dictionnaires etc.) qui « semblent atomiques » le sont réellement.

Par exemple, les opérations suivantes sont toutes atomiques (L, L1 et L2 sont des listes, D, D1 et D2 sont des dictionnaires, x et y sont des objets, i et j des entiers) :

L.append(x)
L1.extend(L2)
x = L[i]
x = L.pop()
L1[i:j] = L2
L.sort()
x = y
x.field = y
D[x] = y
D1.update(D2)
D.keys()

Les suivantes ne le sont pas :

i = i+1
L.append(L[-1])
L[i] = L[j]
D[x] = D[x] + 1

Les opérations qui remplacent d’autres objets peuvent invoquer la méthode __del__() de ces objets quand leur compteur de référence passe à zéro, et cela peut avoir de l’impact. C’est tout particulièrement vrai pour les des changements massifs sur des dictionnaires ou des listes. En cas de doute, il vaut mieux utiliser un mutex.

Pourquoi ne pas se débarrasser du verrou global de l’interpréteur ?

Le verrou global de l’interpréteur (GIL) est souvent vu comme un obstacle au déploiement de code Python sur des serveurs puissants avec de nombreux processeurs, car un programme Python à fils d’exécutions multiples n’utilise en réalité qu’un seul processeur. Presque tout le code Python ne peut en effet être exécuté qu’avec le GIL acquis.

Back in the days of Python 1.5, Greg Stein actually implemented a comprehensive patch set (the « free threading » patches) that removed the GIL and replaced it with fine-grained locking. Adam Olsen recently did a similar experiment in his python-safethread [http://code.google.com/p/python-safethread/] project. Unfortunately, both experiments exhibited a sharp drop in single-thread performance (at least 30% slower), due to the amount of fine-grained locking necessary to compensate for the removal of the GIL.

Cela ne signifie pas qu’il est impossible de tirer profit de Python sur des machines à plusieurs cœurs ! Il faut seulement être malin et diviser le travail à faire entre plusieurs processus plutôt qu’entre plusieurs fils d’exécution. La classe ProcessPoolExecutor du nouveau module concurrent.futures permet de faire cela facilement ; le module multiprocessing fournit une API de plus bas-niveau pour un meilleur contrôle sur la distribution des tâches.

Des extensions C appropriées peuvent aussi aider ; en utilisant une extension C pour effectuer une tâche longue, l’extension peut relâcher le GIL pendant que le fil est en train d’exécuter ce code et laisser les autres fils travailler. Des modules de la bibliothèque standard comme zlib ou hashlib utilisent cette technique.

On a déjà proposé de restreindre le GIL par interpréteur, et non plus d’être complétement global ; les interpréteurs ne seraient plus en mesure de partager des objets. Malheureusement, cela n’a pas beaucoup de chance non plus d’arriver. Cela nécessiterait un travail considérable, car la façon dont beaucoup d’objets sont implémentés rend leur état global. Par exemple, les entiers et les chaînes de caractères courts sont mis en cache ; ces caches devraient être déplacés au niveau de l’interpréteur. D’autres objets ont leur propre liste de suppression, ces listes devraient être déplacées au niveau de l’interpréteur et ainsi de suite.

C’est une tâche sans fin, car les extensions tierces ont le même problème, et il est probable que les extensions tierces soient développées plus vite qu’il ne soit possible de les corriger pour les faire stocker leur état au niveau de l’interpréteur et non plus au niveau global.

Et enfin, quel intérêt y-a t’il à avoir plusieurs interpréteurs qui ne partagent pas d’état, par rapport à faire tourner chaque interpréteur dans un processus différent ?

Les entrées/sorties

Comment supprimer un fichier ? (et autres questions sur les fichiers…)

Utilisez os.remove(filename) ou os.unlink(filename) ; pour la documentation, référez-vous au module os. Ces deux fonctions sont identiques, unlink() n’est tout simplement que le nom de l’appel système à cette fonction sous Unix.

Utilisez os.rmdir() pour supprimer un dossier et os.mkdir() pour en créer un nouveau. os.makedirs(chemin) crée les dossiers intermédiaires de chemin qui n’existent pas et os.removedirs(chemin) supprime les dossiers intermédiaires si ceux-ci sont vides. Pour supprimer une arborescence et tout son contenu, utilisez shutil.rmtree().

os.rename(ancien_chemin, nouveau_chemin) permet de renommer un fichier.

Pour supprimer le contenu d’un fichier, ouvrez celui-ci avec f = open(nom_du_fichier, "rb+"), puis exécutez f.truncate(décalage) où décalage est par défaut la position actuelle de la tête de lecture. Il existe aussi os.ftruncate(df, décalage) pour les fichiers ouverts avec os.open(), où df est le descripteur de fichier (un entier court).

Le module shutil propose aussi un grand nombre de fonctions pour effectuer des opérations sur des fichiers comme copyfile(), copytree() et rmtree().

Comment copier un fichier ?

Le module shutil fournit la fonction copyfile(). Sous MacOS 9, celle-ci ne copie pas le clonage de ressources ni les informations du chercheur.

Comment lire (ou écrire) des données binaires ?

Pour lire ou écrire des formats de données complexes en binaire, il est recommandé d’utiliser le module struct. Celui-ci permet de convertir une chaîne de caractères qui contient des données binaires, souvent des nombres, en objets Python, et vice-versa.

Par exemple, le code suivant lit, depuis un fichier, deux entiers codés sur 2 octets et un entier codé sur 4 octets, en format gros-boutiste :

import struct

with open(filename, "rb") as f:
    s = f.read(8)
    x, y, z = struct.unpack(">hhl", s)

« > » dans la chaîne de formatage indique que la donnée doit être lue en mode gros-boutiste, la lettre « h » indique un entier court (2 octets) et la lettre « l » indique un entier long (4 octets).

Pour une donnée plus régulière (p. ex. une liste homogène d’entiers ou de nombres à virgule flottante), il est possible d’utiliser le module array.

Note

Pour lire et écrire de la donnée binaire, il est obligatoire d’ouvrir le fichier en mode binaire également (ici, en passant "rb" à open()). En utilisant "r" (valeur par défaut), le fichier est ouvert en mode textuel et f.read() renvoie des objets str au lieu d’objets bytes.

Il me semble impossible d’utiliser os.read() sur un tube créé avec os.popen() ; pourquoi ?

os.read() est une fonction de bas niveau qui prend en paramètre un descripteur de fichier — un entier court qui représente le fichier ouvert. os.popen() crée un objet fichier de haut niveau, du même type que celui renvoyé par la fonction native open(). Par conséquent, pour lire n octets d’un tube p créé avec os.popen(), il faut utiliser p.read(n).

Comment accéder au port de transmission en série (RS-232) ?

Pour Win32, POSIX (Linux, BSD, etc.) et Jython :

http://pyserial.sourceforge.net

Pour Unix, référez-vous à une publication sur Usenet de Mitch Chapman :

https://groups.google.com/groups?selm=34A04430.CF9@ohioee.com

Pourquoi fermer sys.stdout, sys.stdin, sys.stderr ne les ferme pas réellement ?

Les objets fichiers en Python sont des abstractions de haut niveau sur les descripteurs de fichier C de bas niveau.

Pour la plupart des objets fichiers créés en Python avec la fonction native open(), f.close() marque le fichier comme fermé du point de vue de Python et ferme aussi le descripteur C sous-jacent. Le même mécanisme est enclenché automatiquement dans le destructeur de f, lorsque f est recyclé.

Mais stdin, stdout et stderr ont droit à un traitement spécial en Python, car leur statut en C est lui-aussi spécial. Exécuter sys.stdout.close() marque l’objet fichier comme fermé du point de vue de Python, mais le descripteur de fichier C associé n’est pas fermé.

Pour fermer le descripteur de fichier sous-jacent C de l’une de ces trois sorties, demandez-vous avant tout si vous êtes sûr de vous (cela peut, par exemple, perturber le bon fonctionnement de modules qui font des opérations d’entrée-sortie). Si c’est le cas, utilisez os.close() :

os.close(stdin.fileno())
os.close(stdout.fileno())
os.close(stderr.fileno())

Il est aussi possible de fermer respectivement les constantes numériques 0, 1 ou 2.

Programmation réseau et Internet

Quels sont les outils Python dédiés à la Toile ?

Référez-vous aux chapitres intitulés Gestion des protocoles internet et Traitement des données provenant d’Internet dans le manuel de référence de la bibliothèque. Python a de nombreux modules pour construire des applications de Toile côté client comme côté serveur.

Un résumé des cadriciels disponibles est maintenu par Paul Boddie à l’adresse https://wiki.python.org/moin/WebProgramming.

Cameron Laird maintient un ensemble intéressant d’articles sur les technologies Python dédiées à la Toile à l’adresse http://phaseit.net/claird/comp.lang.python/web_python.

Comment reproduire un envoi de formulaire CGI (METHOD=POST) ?

J’aimerais récupérer la page de retour d’un envoi de formulaire sur la Toile. Existe-t’il déjà du code qui pourrait m’aider à le faire facilement ?

Oui. Voici un exemple simple d’utilisation de urllib.request :

#!/usr/local/bin/python

import urllib.request

# build the query string
qs = "First=Josephine&MI=Q&Last=Public"

# connect and send the server a path
req = urllib.request.urlopen('http://www.some-server.out-there'
                             '/cgi-bin/some-cgi-script', data=qs)
with req:
    msg, hdrs = req.read(), req.info()

Remarquez qu’en général, la chaîne de caractères d’une requête POST encodée avec des des signes « % » doit être mise entre guillemets à l’aide de urllib.parse.urlencode(). Par exemple pour envoyer name=Guy Steele, Jr. :

>>> import urllib.parse
>>> urllib.parse.urlencode({'name': 'Guy Steele, Jr.'})
'name=Guy+Steele%2C+Jr.'

Voir aussi

HOWTO Fetch Internet Resources Using The urllib Package pour des exemples complets.

Quel module utiliser pour générer du HTML ?

La page wiki de la programmation Toile [https://wiki.python.org/moin/WebProgramming] (en anglais) répertorie un ensemble de liens pertinents.

Comment envoyer un courriel avec un script Python ?

Utilisez le module smtplib de la bibliothèque standard.

Voici un exemple très simple d’un envoyeur de courriel qui l’utilise. Cette méthode fonctionne sur tous les serveurs qui implémentent SMTP.

import sys, smtplib

fromaddr = input("From: ")
toaddrs  = input("To: ").split(',')
print("Enter message, end with ^D:")
msg = ''
while True:
    line = sys.stdin.readline()
    if not line:
        break
    msg += line

# The actual mail send
server = smtplib.SMTP('localhost')
server.sendmail(fromaddr, toaddrs, msg)
server.quit()

Sous Unix, il est possible d’utiliser sendmail. La localisation de l’exécutable sendmail dépend du système ; cela peut-être /usr/lib/sendmail ou /usr/sbin/sendmail, la page de manuel de sendmail peut vous aider. Par exemple :

import os

SENDMAIL = "/usr/sbin/sendmail"  # sendmail location
p = os.popen("%s -t -i" % SENDMAIL, "w")
p.write("To: receiver@example.com\n")
p.write("Subject: test\n")
p.write("\n")  # blank line separating headers from body
p.write("Some text\n")
p.write("some more text\n")
sts = p.close()
if sts != 0:
    print("Sendmail exit status", sts)

Comment éviter de bloquer dans la méthode connect() d’un connecteur réseau ?

Le module select est fréquemment utilisé pour effectuer des entrées-sorties asynchrones sur des connecteurs réseaux.

Pour empêcher une connexion TCP de se bloquer, il est possible de mettre le connecteur en mode lecture seule. Avec cela, au moment du connect(), la connexion pourra être immédiate (peu probable) ou bien vous obtiendrez une exception qui contient le numéro d’erreur dans .errno. errno.EINPROGRESS indique que la connexion est en cours, mais qu’elle n’a pas encore aboutie. La valeur dépend du système d’exploitation, donc renseignez-vous sur la valeur utilisée par votre système.

connect_ex() permet d’éviter la création de l’exception, et de ne renvoyer que la valeur de errno. Pour vérifier l’état de la connexion, utilisez encore une fois connect_ex() — 0 ou errno.EISCONN indiquent que la connexion est active — ou passez le connecteur en argument de select() pour vérifier si le connecteur est prêt à recevoir des entrées.

Note

Le module asyncore propose une approche en cadriciel pour écrire du code réseau non-bloquant. La bibliothèque tierce Twisted [https://twistedmatrix.com/trac/] en est une alternative plébiscitée, avec un grand nombre de fonctionnalités.

Bases de données

Existe-t’il des modules Python pour s’interfacer avec des bases de données ?

Oui.

La distribution standard de Python fournit aussi des interfaces à des bases de données comme DBM ou GDBM. Il existe aussi le module sqlite3 qui implémente une base de données relationelle légère sur disque.

La gestion de la plupart des bases de données relationnelles est assurée. Voir la page wiki DatabaseProgramming [https://wiki.python.org/moin/DatabaseProgramming] pour plus de détails.

Comment implémenter la persistance d’objets en Python ?

Le module pickle répond à cela de manière large (bien qu’il ne soit pas possible de stocker des fichiers ouverts, des connecteurs ou des fenêtres par exemple), et le module shelve de la bibliothèque utilise pickle et (g)dbm pour créer des liens persistants vers des objets Python.

Mathématiques et calcul numérique

Comment générer des nombres aléatoires en Python ?

Le module random de la bibliothèque standard comprend un générateur de nombres aléatoires. Son utilisation est simple :

import random
random.random()

Le code précédent renvoie un nombre à virgule flottante aléatoire dans l’intervalle [0, 1[.

Ce module fournit beaucoup d’autres générateurs spécialisés comme :

randrange(a, b) génère un entier dans l’intervalle [a, b[.

uniform(a, b) génère un nombre à virgule flottante aléatoire dans l’intervalle [a, b[.

normalvariate(mean, sdev) simule la loi normale (Gaussienne).

Des fonctions de haut niveau opèrent directement sur des séquences comme :

choice(S) sélectionne au hasard un élément d’une séquence donnée

shuffle(L) mélange une liste en-place, c-à-d lui applique une permutation aléatoire

Il existe aussi une classe Random qu’il est possible d’instancier pour créer des générateurs aléatoires indépendants.

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FAQ extension/intégration

Sommaire

FAQ extension/intégration

Puis-je créer mes propres fonctions en C ?

Puis-je créer mes propres fonctions en C++ ?

Écrire directement en C est difficile ; existe-t-il des alternatives ?

Comment puis-je exécuter des instructions quelconques Python à partir de C ?

Comment puis-je évaluer une expression quelconque de Python à partir de C ?

Comment puis-je extraire des donnés en C d’un objet Python ?

Comment utiliser Py_BuildValue() pour créer un tuple de longueur définie ?

Comment puis-je appeler la méthode d’un objet à partir de C ?

Comment puis-je récupérer la sortie de PyErr_Print() (ou tout ce qui s’affiche sur stdout/stderr) ?

Comment accéder à un module écrit en Python à partir de C ?

Comment s’interfacer avec les objets C++ depuis Python ?

J’ai ajouté un module en utilisant le fichier Setup et la compilation échoue ; pourquoi ?

Comment déboguer une extension ?

Je veux compiler un module Python sur mon système Linux, mais il manque certains fichiers. Pourquoi ?

Comment distinguer une « entrée incomplète » (incomplete input) d’une « entrée invalide » (invalid input) ?

Comment puis-je trouver les symboles g++ indéfinis __builtin_new ou __pure_virtual ?

Puis-je créer une classe d’objets avec certaines méthodes implémentées en C et d’autres en Python (p. ex. en utilisant l’héritage) ?

Puis-je créer mes propres fonctions en C ?

Oui, vous pouvez créer des modules intégrés contenant des fonctions, des variables, des exceptions et même de nouveaux types en C. Ceci est expliqué dans le document Extension et intégration de l’interpréteur Python.

La plupart des livres Python intermédiaires ou avancés couvrent également ce sujet.

Puis-je créer mes propres fonctions en C++ ?

Oui, en utilisant les fonctionnalités de compatibilité C existantes en C++. Placez extern "C" { ... } autour des fichiers Python inclus et mettez extern "C" avant chaque fonction qui va être appelée par l’interpréteur Python. Les objets C++ globaux ou statiques avec les constructeurs ne sont probablement pas une bonne idée.

Écrire directement en C est difficile ; existe-t-il des alternatives ?

Il y a un certain nombre de solutions existantes qui vous permettent d’écrire vos propres extensions C, selon ce que vous essayez de faire.

Cython [http://cython.org] et son cousin Pyrex [https://www.cosc.canterbury.ac.nz/greg.ewing/python/Pyrex/] sont des compilateurs qui acceptent une forme légèrement modifiée de Python et produisent du code C correspondant. Cython et Pyrex permettent d’écrire une extension sans avoir à connaître l’API C de Python.

Si vous avez besoin d’accéder à l’interface d’une bibliothèque C ou C++ pour laquelle aucune extension Python n’existe à ce jour, vous pouvez essayer d’encapsuler les types de données et fonctions de la bibliothèque avec un outil tel que SWIG [http://www.swig.org]. SIP [https://riverbankcomputing.com/software/sip/intro], CXX [http://cxx.sourceforge.net/], Boost [http://www.boost.org/libs/python/doc/index.html] ou Weave [https://github.com/scipy/weave] sont également des alternatives pour encapsuler des bibliothèques C++.

Comment puis-je exécuter des instructions quelconques Python à partir de C ?

The highest-level function to do this is PyRun_SimpleString() which takes a single string argument to be executed in the context of the module __main__ and returns 0 for success and -1 when an exception occurred (including SyntaxError). If you want more control, use PyRun_String(); see the source for PyRun_SimpleString() in Python/pythonrun.c.

Comment puis-je évaluer une expression quelconque de Python à partir de C ?

Appelez la fonction PyRun_String() de la question précédente avec le symbole de départ Py_eval_input ; il analyse une expression, l’évalue et renvoie sa valeur.

Comment puis-je extraire des donnés en C d’un objet Python ?

Cela dépend du type d’objet. Si c’est un tuple, PyTuple_Size() renvoie sa longueur et PyTuple_GetItem() renvoie l’élément à l’index spécifié. Les listes ont des fonctions similaires, PyListSize() et PyList_GetItem().

Pour les bytes, PyBytes_Size() renvoie sa longueur et PyBytes_AsStringAndSize() fournit un pointeur vers sa valeur et sa longueur. Notez que les objets bytes en Python peuvent contenir des valeurs nulles, c’est pourquoi il ne faut pas utiliser la fonction C strlen().

To test the type of an object, first make sure it isn’t NULL, and then use PyBytes_Check(), PyTuple_Check(), PyList_Check(), etc.

Il y a aussi une API de haut niveau pour les objets Python qui est fournie par l’interface dite « abstraite » — voir Include/abstract.h pour plus de détails. Elle permet l’interfaçage avec tout type de séquence Python en utilisant des appels tels que PySequence_Length(), PySequence_GetItem(), etc. ainsi que de nombreux autres protocoles utiles tels que les nombres (PyNumber_Index() et autres) et les correspondances dans les APIs PyMapping.

Comment utiliser Py_BuildValue() pour créer un tuple de longueur définie ?

Vous ne pouvez pas. Utilisez PyTuple_Pack() à la place.

Comment puis-je appeler la méthode d’un objet à partir de C ?

La fonction PyObject_CallMethod() peut être utilisée pour appeler la méthode d’un objet. Les paramètres sont l’objet, le nom de la méthode à appeler, une chaîne de caractères comme celle utilisée pour Py_BuildValue() et les valeurs des arguments :

PyObject *
PyObject_CallMethod(PyObject *object, const char *method_name,
                    const char *arg_format, ...);

Cela fonctionne pour tous les objets qui ont des méthodes — qu’elles soient intégrées ou définies par l’utilisateur. Vous êtes responsable de « Py_DECREF()er » la valeur de retour à la fin.

Pour appeler, p. ex., la méthode seek d’un objet file avec les arguments 10, 0 (en supposant que le pointeur de l’objet fichier est f) :

res = PyObject_CallMethod(f, "seek", "(ii)", 10, 0);
if (res == NULL) {
        ... an exception occurred ...
}
else {
        Py_DECREF(res);
}

Notez que PyObject_CallObject() veut toujours un tuple comme liste d’arguments. Aussi, pour appeler une fonction sans arguments, utilisez « () » pour être conforme au type et, pour appeler une fonction avec un paramètre, entourez-le de parenthèses, p. ex. « (i) ».

Comment puis-je récupérer la sortie de PyErr_Print() (ou tout ce qui s’affiche sur stdout/stderr) ?

Dans le code Python, définissez un objet qui possède la méthode write(). Affectez cet objet à sys.stdout et sys.stderr. Appelez print_error ou faites simplement en sorte que le mécanisme standard de remontée des erreurs fonctionne. Ensuite, la sortie sera dirigée vers l’endroit où votre méthode write() écrit.

La façon la plus simple consiste à utiliser la classe io.StringIO :

>>> import io, sys
>>> sys.stdout = io.StringIO()
>>> print('foo')
>>> print('hello world!')
>>> sys.stderr.write(sys.stdout.getvalue())
foo
hello world!

Le code d’un objet à la fonctionnalité similaire ressemblerait à ceci :

>>> import io, sys
>>> class StdoutCatcher(io.TextIOBase):
...     def __init__(self):
...         self.data = []
...     def write(self, stuff):
...         self.data.append(stuff)
...
>>> import sys
>>> sys.stdout = StdoutCatcher()
>>> print('foo')
>>> print('hello world!')
>>> sys.stderr.write(''.join(sys.stdout.data))
foo
hello world!

Comment accéder à un module écrit en Python à partir de C ?

Vous pouvez obtenir un pointeur sur l’objet module comme suit :

module = PyImport_ImportModule("<modulename>");

Si le module n’a pas encore été importé (c.-à-d. qu’il n’est pas encore présent dans sys.modules), cela initialise le module ; sinon il renvoie simplement la valeur de sys.modules["<modulename>"]. Notez qu’il n’inscrit le module dans aucun espace de nommage — il s’assure seulement qu’il a été initialisé et qu’il est stocké dans sys.modules.

Vous pouvez alors accéder aux attributs du module (c.-à-d. à tout nom défini dans le module) comme suit :

attr = PyObject_GetAttrString(module, "<attrname>");

Appeler PyObject_SetAttrString() pour assigner des valeurs aux variables du module fonctionne également.

Comment s’interfacer avec les objets C++ depuis Python ?

Selon vos besoins, de nombreuses approches sont possibles. Pour le faire manuellement, commencez par lire le document « Extension et intégration ». Sachez que pour le système d’exécution Python, il n’y a pas beaucoup de différence entre C et C++ — donc la méthode pour construire un nouveau type Python à partir d’une structure C (pointeur) fonctionne également avec des objets en C++.

Pour les bibliothèques C++, voir Écrire directement en C est difficile ; existe-t-il des alternatives ?.

J’ai ajouté un module en utilisant le fichier Setup et la compilation échoue ; pourquoi ?

Le fichier Setup doit se terminer par une ligne vide, s’il n’y a pas de ligne vide, le processus de compilation échoue (ce problème peut se régler en bidouillant un script shell, et ce bogue est si mineur qu’il ne mérite pas qu’on s’y attarde).

Comment déboguer une extension ?

Lorsque vous utilisez GDB avec des extensions chargées dynamiquement, vous ne pouvez pas placer de point d’arrêt dans votre extension tant que celle-ci n’est pas chargée.

Dans votre fichier .gdbinit (ou manuellement), ajoutez la commande :

br _PyImport_LoadDynamicModule

Ensuite, lorsque vous exécutez GDB :

$ gdb /local/bin/python
gdb) run myscript.py
gdb) continue # repeat until your extension is loaded
gdb) finish   # so that your extension is loaded
gdb) br myfunction.c:50
gdb) continue

Je veux compiler un module Python sur mon système Linux, mais il manque certains fichiers. Pourquoi ?

La plupart des versions pré-compilées de Python n’incluent pas le répertoire /usr/lib/python2.x/config/, qui contient les différents fichiers nécessaires à la compilation des extensions Python.

Pour Red Hat, installez le RPM python-devel pour obtenir les fichiers nécessaires.

Pour Debian, exécutez apt-get install python-dev.

Comment distinguer une « entrée incomplète » (incomplete input) d’une « entrée invalide » (invalid input) ?

Parfois vous souhaitez émuler le comportement de l’interpréteur interactif Python, quand il vous donne une invite de continuation lorsque l’entrée est incomplète (par exemple, vous avez tapé le début d’une instruction « if » ou vous n’avez pas fermé vos parenthèses ou triple guillemets) mais il vous renvoie immédiatement une erreur syntaxique quand la saisie est incorrecte.

En Python, vous pouvez utiliser le module codeop, qui se rapproche assez du comportement de l’analyseur. Par exemple, IDLE l’utilise.

La façon la plus simple de le faire en C est d’appeler PyRun_InteractiveLoop() (peut-être dans un autre fil d’exécution) et laisser l’interpréteur Python gérer l’entrée pour vous. Vous pouvez également définir PyOS_ReadlineFunctionPointer() pour pointer vers votre fonction d’entrée personnalisée. Voir Modules/readline.c et Parser/myreadline.c pour plus de conseils.

However sometimes you have to run the embedded Python interpreter in the same thread as your rest application and you can’t allow the PyRun_InteractiveLoop() to stop while waiting for user input. The one solution then is to call PyParser_ParseString() and test for e.error equal to E_EOF, which means the input is incomplete. Here’s a sample code fragment, untested, inspired by code from Alex Farber:

#include <Python.h>
#include <node.h>
#include <errcode.h>
#include <grammar.h>
#include <parsetok.h>
#include <compile.h>

int testcomplete(char *code)
  /* code should end in \n */
  /* return -1 for error, 0 for incomplete, 1 for complete */
{
  node *n;
  perrdetail e;

  n = PyParser_ParseString(code, &_PyParser_Grammar,
                           Py_file_input, &e);
  if (n == NULL) {
    if (e.error == E_EOF)
      return 0;
    return -1;
  }

  PyNode_Free(n);
  return 1;
}

Une autre solution est d’essayer de compiler la chaîne reçue avec Py_CompileString(). Si cela se compile sans erreur, essayez d’exécuter l’objet code renvoyé en appelant PyEval_EvalCode(). Sinon, enregistrez l’entrée pour plus tard. Si la compilation échoue, vérifiez s’il s’agit d’une erreur ou s’il faut juste plus de données — en extrayant la chaîne de message du tuple d’exception et en la comparant à la chaîne « unexpected EOF while parsing ». Voici un exemple complet d’utilisation de la bibliothèque readline de GNU (il vous est possible d’ignorer SIGINT lors de l’appel à readline()) :

#include <stdio.h>
#include <readline.h>

#include <Python.h>
#include <object.h>
#include <compile.h>
#include <eval.h>

int main (int argc, char* argv[])
{
  int i, j, done = 0;                          /* lengths of line, code */
  char ps1[] = ">>> ";
  char ps2[] = "... ";
  char *prompt = ps1;
  char *msg, *line, *code = NULL;
  PyObject *src, *glb, *loc;
  PyObject *exc, *val, *trb, *obj, *dum;

  Py_Initialize ();
  loc = PyDict_New ();
  glb = PyDict_New ();
  PyDict_SetItemString (glb, "__builtins__", PyEval_GetBuiltins ());

  while (!done)
  {
    line = readline (prompt);

    if (NULL == line)                          /* Ctrl-D pressed */
    {
      done = 1;
    }
    else
    {
      i = strlen (line);

      if (i > 0)
        add_history (line);                    /* save non-empty lines */

      if (NULL == code)                        /* nothing in code yet */
        j = 0;
      else
        j = strlen (code);

      code = realloc (code, i + j + 2);
      if (NULL == code)                        /* out of memory */
        exit (1);

      if (0 == j)                              /* code was empty, so */
        code[0] = '\0';                        /* keep strncat happy */

      strncat (code, line, i);                 /* append line to code */
      code[i + j] = '\n';                      /* append '\n' to code */
      code[i + j + 1] = '\0';

      src = Py_CompileString (code, "<stdin>", Py_single_input);

      if (NULL != src)                         /* compiled just fine - */
      {
        if (ps1  == prompt ||                  /* ">>> " or */
            '\n' == code[i + j - 1])           /* "... " and double '\n' */
        {                                               /* so execute it */
          dum = PyEval_EvalCode (src, glb, loc);
          Py_XDECREF (dum);
          Py_XDECREF (src);
          free (code);
          code = NULL;
          if (PyErr_Occurred ())
            PyErr_Print ();
          prompt = ps1;
        }
      }                                        /* syntax error or E_EOF? */
      else if (PyErr_ExceptionMatches (PyExc_SyntaxError))
      {
        PyErr_Fetch (&exc, &val, &trb);        /* clears exception! */

        if (PyArg_ParseTuple (val, "sO", &msg, &obj) &&
            !strcmp (msg, "unexpected EOF while parsing")) /* E_EOF */
        {
          Py_XDECREF (exc);
          Py_XDECREF (val);
          Py_XDECREF (trb);
          prompt = ps2;
        }
        else                                   /* some other syntax error */
        {
          PyErr_Restore (exc, val, trb);
          PyErr_Print ();
          free (code);
          code = NULL;
          prompt = ps1;
        }
      }
      else                                     /* some non-syntax error */
      {
        PyErr_Print ();
        free (code);
        code = NULL;
        prompt = ps1;
      }

      free (line);
    }
  }

  Py_XDECREF(glb);
  Py_XDECREF(loc);
  Py_Finalize();
  exit(0);
}

Comment puis-je trouver les symboles g++ indéfinis __builtin_new ou __pure_virtual ?

Pour charger dynamiquement les modules d’extension g++, vous devez recompiler Python, effectuer l’édition de liens en utilisant g++ (modifiez LINKCC dans le Python Modules Makefile), et effectuer l’édition de liens de votre module d’extension avec g++ (par exemple, g++ -shared -o mymodule.so mymodule.o).

Puis-je créer une classe d’objets avec certaines méthodes implémentées en C et d’autres en Python (p. ex. en utilisant l’héritage) ?

Oui, vous pouvez hériter de classes intégrées telles que int, list, dict, etc.

La bibliothèque Boost Python Library (BPL, http://www.boost.org/libs/python/doc/index.html) fournit un moyen de le faire depuis C++ (c.-à-d. que vous pouvez hériter d’une classe d’extension écrite en C++ en utilisant BPL).

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FAQ : Python et Windows

Sommaire

FAQ : Python et Windows

Comment exécuter un programme Python sous Windows ?

Comment rendre des scripts Python exécutables ?

Pourquoi Python met-il du temps à démarrer ?

Comment construire un exécutable depuis un script Python ?

Est-ce qu’un fichier *.pyd est la même chose qu’une DLL ?

Comment puis-je intégrer Python dans une application Windows ?

Comment empêcher mon éditeur d’utiliser des tabulations dans mes fichiers Python ?

Comment puis-je vérifier de manière non bloquante qu’une touche a été pressée ?

Comment exécuter un programme Python sous Windows ?

Ce n’est pas forcément une question simple. Si vous êtes déjà familier avec le lancement de programmes depuis la ligne de commande de Windows alors tout semblera évident ; sinon, vous pourriez avoir besoin d’être un peu guidé.

Unless you use some sort of integrated development environment, you will end up typing Windows commands into what is variously referred to as a « DOS window » or « Command prompt window ». Usually you can create such a window from your search bar by searching for cmd. You should be able to recognize when you have started such a window because you will see a Windows « command prompt », which usually looks like this:

C:\>

La lettre peut être différente, et il peut y avoir d’autres choses à la suite, alors il se peut que ça ressemble également à ça :

D:\YourName\Projects\Python>

selon la configuration de votre ordinateur et ce que vous avez récemment fait avec. Une fois que vous avez ouvert cette fenêtre, vous êtes bien partis pour pouvoir lancer des programmes Python.

Retenez que vos scripts Python doivent être traités par un autre programme appelé « l’interpréteur » Python. L’interpréteur lit votre script, le compile en bytecode, et exécute le bytecode pour faire tourner votre programme. Alors, comment faire pour donner votre code Python à l’interpréteur ?

First, you need to make sure that your command window recognises the word « py » as an instruction to start the interpreter. If you have opened a command window, you should try entering the command py and hitting return:

C:\Users\YourName> py

Vous devez voir quelque chose comme ça :

Python 3.6.4 (v3.6.4:d48eceb, Dec 19 2017, 06:04:45) [MSC v.1900 32 bit (Intel)] on win32
Type "help", "copyright", "credits" or "license" for more information.
>>>

Vous avez lancé l’interpréteur dans son « mode interactif ». Cela signifie que vous pouvez entrer des instructions ou des expressions Python de manière interactive pour qu’elles soient exécutées. Il s’agit là d’une des plus puissantes fonctionnalités de Python. Vous pouvez le vérifier en entrant quelques commandes de votre choix et en regardant le résultat :

>>> print("Hello")
Hello
>>> "Hello" * 3
'HelloHelloHello'

Many people use the interactive mode as a convenient yet highly programmable calculator. When you want to end your interactive Python session, call the exit() function or hold the Ctrl key down while you enter a Z, then hit the « Enter » key to get back to your Windows command prompt.

You may also find that you have a Start-menu entry such as Start ‣ Programs ‣ Python 3.x ‣ Python (command line) that results in you seeing the >>> prompt in a new window. If so, the window will disappear after you call the exit() function or enter the Ctrl-Z character; Windows is running a single « python » command in the window, and closes it when you terminate the interpreter.

Now that we know the py command is recognized, you can give your Python script to it. You’ll have to give either an absolute or a relative path to the Python script. Let’s say your Python script is located in your desktop and is named hello.py, and your command prompt is nicely opened in your home directory so you’re seeing something similar to:

C:\Users\YourName>

So now you’ll ask the py command to give your script to Python by typing py followed by your script path:

C:\Users\YourName> py Desktop\hello.py
hello

Comment rendre des scripts Python exécutables ?

Sous Windows, l’installateur Python associe l’extension .py avec un type de fichier (Python.File) et une commande qui lance l’interpréteur (D:\Program Files\Python\python.exe "%1" %*). Cela suffit pour pouvoir exécuter les scripts Python depuis la ligne de commande en saisissant foo.py. Si vous souhaitez pouvoir exécuter les scripts en saisissant simplement foo sans l’extension, vous devez ajouter .py au paramètre d’environnement PATHEXT.

Pourquoi Python met-il du temps à démarrer ?

Normalement, sous Windows, Python se lance très rapidement, mais parfois des rapports d’erreurs indiquent que Python commence soudain à prendre beaucoup de temps pour démarrer. C’est d’autant plus intrigant que Python fonctionne correctement avec d’autres Windows configurés de façon similaire.

Le problème peut venir d’un antivirus mal configuré. Certains antivirus sont connus pour doubler le temps de démarrage lorsqu’ils sont configurés pour surveiller toutes les lectures du système de fichiers. Essayez de regarder si les antivirus des deux machines sont bien paramétrés à l’identique. McAfee est particulièrement problématique lorsqu’il est paramétré pour surveiller toutes les lectures du système de fichiers.

Comment construire un exécutable depuis un script Python ?

See http://cx-freeze.sourceforge.net/ for a distutils extension that allows you to create console and GUI executables from Python code. py2exe [http://www.py2exe.org/], the most popular extension for building Python 2.x-based executables, does not yet support Python 3 but a version that does is in development.

Est-ce qu’un fichier *.pyd est la même chose qu’une DLL ?

Oui, les fichiers .pyd sont des fichiers dll, mais il y a quelques différences. Si vous avez une DLL foo.pyd, celle-ci doit posséder une fonction PyInit_foo(). Vous pouvez alors écrire en Python « import foo » et Python recherchera le fichier foo.pyd (ainsi que foo.py et foo.pyc); s’il le trouve, il tentera d’appeler PyInit_foo() pour l’initialiser. Ne liez pas votre .exe avec foo.lib car dans ce cas Windows aura besoin de la DLL.

Notez que le chemin de recherche pour foo.pyd est PYTHONPATH, il est différent de celui qu’utilise Windows pour rechercher foo.dll. De plus, foo.pyd n’a pas besoin d’être présent pour que votre programme s’exécute alors que si vous avez lié votre programme avec une dll celle-ci est requise. Bien sûr foo.pyd est nécessaire si vous écrivez import foo. Dans une DLL le lien est déclaré dans le code source avec __declspec(dllexport). Dans un .pyd la liaison est définie dans une liste de fonctions disponibles.

Comment puis-je intégrer Python dans une application Windows ?

L’intégration de l’interpréteur Python dans une application Windows peut se résumer comme suit :

Ne compilez pas Python directement dans votre fichier .exe. Sous Windows, Python doit être une DLL pour pouvoir importer des modules qui sont eux-mêmes des DLL (ceci constitue une information de première importance non documentée). Au lieu de cela faites un lien vers pythonNN.dll qui est généralement placé dans C:\Windows\System. NN étant la version Python, par exemple « 33 » pour Python 3.3.

Vous pouvez créer un lien vers Python de deux manières différentes. Un lien au moment du chargement signifie pointer vers pythonNN.lib, tandis qu’un lien au moment de l’exécution signifie pointer vers pythonNN.dll. (Note générale : pythonNN.lib est le soi-disant « import lib » correspondant à pythonNN.dll. Il définit simplement des liens symboliques pour l’éditeur de liens.)

La liaison en temps réel simplifie grandement les options de liaison ; tout se passe au moment de l’exécution. Votre code doit charger pythonNN.dll en utilisant la routine Windows LoadLibraryEx(). Le code doit aussi utiliser des routines d’accès et des données dans pythonNN.dll (c’est-à-dire les API C de Python) en utilisant des pointeurs obtenus par la routine Windows GetProcAddress(). Les macros peuvent rendre l’utilisation de ces pointeurs transparente à tout code C qui appelle des routines dans l’API C de Python.

Note Borland : convertir pythonNN.lib au format OMF en utilisant Coff2Omf.exe en premier.

Si vous utilisez SWIG, il est facile de créer un « module d’extension » Python qui rendra les données et les méthodes de l’application disponibles pour Python. SWIG s’occupera de tous les détails ennuyeux pour vous. Le résultat est du code C que vous liez dans votre fichier.exe (!) Vous n’avez pas besoin de créer un fichier DLL, et cela simplifie également la liaison.

SWIG va créer une fonction d’initialisation (fonction en C) dont le nom dépend du nom du module d’extension. Par exemple, si le nom du module est leo, la fonction init sera appelée initleo(). Si vous utilisez des classes shadow SWIG, comme vous le devriez, la fonction init sera appelée initleoc(). Ceci initialise une classe auxiliaire invisible utilisée par la classe shadow.

La raison pour laquelle vous pouvez lier le code C à l’étape 2 dans votre fichier.exe est que l’appel de la fonction d’initialisation équivaut à importer le module dans Python ! (C’est le deuxième fait clé non documenté.)

En bref, vous pouvez utiliser le code suivant pour initialiser l’interpréteur Python avec votre module d’extension.

#include "python.h"
...
Py_Initialize();  // Initialize Python.
initmyAppc();  // Initialize (import) the helper class.
PyRun_SimpleString("import myApp");  // Import the shadow class.

Il y a deux problèmes avec l’API C de Python qui apparaîtront si vous utilisez un compilateur autre que MSVC, le compilateur utilisé pour construire pythonNN.dll.

Problème 1 : Les fonctions dites de « Très Haut Niveau » qui prennent les arguments FILE * ne fonctionneront pas dans un environnement multi-compilateur car chaque compilateur aura une notion différente de la structure de FILE. Du point de vue de l’implémentation, il s’agit de fonctions de très bas niveau.

Problème 2 : SWIG génère le code suivant lors de la génération d’encapsuleurs pour annuler les fonctions :

Py_INCREF(Py_None);
_resultobj = Py_None;
return _resultobj;

Hélas, Py_None est une macro qui se développe en référence à une structure de données complexe appelée _Py_NoneStruct dans pythonNN.dll. Encore une fois, ce code échouera dans un environnement multi-compilateur. Remplacez ce code par :

return Py_BuildValue("");

Il est possible d’utiliser la commande %typemap de SWIG pour effectuer le changement automatiquement, bien que je n’ai pas réussi à le faire fonctionner (je suis un débutant complet avec SWIG).

Utiliser un script shell Python pour créer une fenêtre d’interpréteur Python depuis votre application Windows n’est pas une bonne idée ; la fenêtre résultante sera indépendante du système de fenêtrage de votre application. Vous (ou la classe wxPythonWindow) devriez plutôt créer une fenêtre d’interpréteur « native ». Il est facile de connecter cette fenêtre à l’interpréteur Python. Vous pouvez rediriger l’entrée/sortie de Python vers n’importe quel objet qui supporte la lecture et l’écriture, donc tout ce dont vous avez besoin est un objet Python (défini dans votre module d’extension) qui contient les méthodes read() et write().

Comment empêcher mon éditeur d’utiliser des tabulations dans mes fichiers Python ?

La FAQ ne recommande pas l’utilisation des indentations et le guide stylistique de Python, la PEP 8 [https://www.python.org/dev/peps/pep-0008], recommande l’utilisation de 4 espaces dans les codes Python. C’est aussi le comportement par défaut d’Emacs avec Python.

Quel que soit votre éditeur, mélanger des tabulations et des espaces est une mauvaise idée. Visual C++, par exemple, peut être facilement configuré pour utiliser des espaces : allez dans Tools ‣ Options ‣ Tabs et pour le type de fichier par défaut, vous devez mettre Tab size et Indent size à 4, puis sélectionner Insert spaces.

Python va lever IndentationError ou TabError si un mélange de tabulation et d’indentation pose problème en début de ligne. Vous pouvez aussi utiliser le module tabnanny pour détecter ces erreurs.

Comment puis-je vérifier de manière non bloquante qu’une touche a été pressée ?

Utilisez le module msvcrt. C’est une extension standard spécifique à Windows, qui définit une fonction kbhit() qui vérifie si une pression de touche s’est produite, et getch() qui récupère le caractère sans l’afficher.

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FAQ interface graphique

Sommaire

FAQ interface graphique

Questions générales sur l’interface graphique

Quelles bibliothèques d’interfaces graphiques multi-plateformes existent en Python ?

Tkinter

wxWidgets

Qt

Gtk+

Kivy

FLTK

OpenGL

Quelles boîtes à outils IUG spécifiques à la plate-forme existent pour Python ?

Questions à propos de Tkinter

Comment puis-je geler (freezer) les applications Tkinter ?

Puis-je modifier des événements Tk pendant l’écoute des E/S ?

Je n’arrive pas à faire fonctionner les raccourcis clavier dans Tkinter : pourquoi ?

Questions générales sur l’interface graphique

Quelles bibliothèques d’interfaces graphiques multi-plateformes existent en Python ?

Selon les plateformes que vous comptez utiliser, il en existe plusieurs. Certaines ne sont cependant pas encore disponibles en Python 3. A minima, Tkinter et Qt sont connus pour être compatibles avec Python 3.

Tkinter

Les versions standards de Python incluent une interface orientée objet pour le jeu d’objets graphiques Tcl/Tk, appelée tkinter. C’est probablement la plus facile à installer (puisqu’elle est incluse avec la plupart des distributions binaires [https://www.python.org/downloads/] de Python) et à utiliser. Pour plus d’informations sur Tk, y compris les liens vers les sources, voir la page d’accueil Tcl/Tk [https://www.tcl.tk]. Tcl/Tk est entièrement portable sur les plates-formes Mac OS X, Windows et Unix.

wxWidgets

wxWidgets (https://www.wxwidgets.org) est une librairie de classe IUG portable et gratuite écrite en C++ qui fournit une apparence native sur un certain nombre de plates-formes, elle est notamment en version stable pour Windows, Mac OS X, GTK et X11. Des clients sont disponibles pour un certain nombre de langages, y compris Python, Perl, Ruby, etc.

wxPython (http://www.wxpython.org) est le portage Python de wxWidgets. Bien qu’il soit légèrement en retard sur les versions officielles de wxWidgets, il offre également des fonctionnalités propres à Python qui ne sont pas disponibles pour les autres langages. WxPython dispose de plus, d’une communauté d’utilisateurs et de développeurs active.

wxWidgets et wxPython sont tous deux des logiciels libres, open source, avec des licences permissives qui permettent leur utilisation dans des produits commerciaux ainsi que dans des logiciels gratuits ou contributifs (shareware).

Qt

Il existe des liens disponibles pour la boîte à outils Qt (en utilisant soit PyQt [https://riverbankcomputing.com/software/pyqt/intro] ou PySide [https://wiki.qt.io/PySide]) et pour KDE (PyKDE4 [https://techbase.kde.org/Languages/Python/Using_PyKDE_4]). PyQt est actuellement plus mûre que PySide, mais*PyQt* nécessite d’acheter une licence de Riverbank Computing [https://www.riverbankcomputing.com/commercial/license-faq] si vous voulez écrire des applications propriétaires. PySide est gratuit pour toutes les applications.

Qt >= 4.5 est sous licence LGPL ; de plus, des licences commerciales sont disponibles auprès de The Qt Company [https://www.qt.io/licensing/].

Gtk+

The GObject introspection bindings [https://wiki.gnome.org/Projects/PyGObject] for Python allow you to write GTK+ 3 applications. There is also a Python GTK+ 3 Tutorial [https://python-gtk-3-tutorial.readthedocs.org/en/latest/].

The older PyGtk bindings for the Gtk+ 2 toolkit [http://www.gtk.org] have been implemented by James Henstridge; see <http://www.pygtk.org>.

Kivy

*Kivy* [https://kivy.org/] est une bibliothèque GUI multi-plateformes disponible à la fois sur les systèmes d’exploitation de bureau (Windows, MacOS, Linux) et les appareils mobiles (Android, iOS). Elle est écrite en Python et Cython, et peut utiliser une série de fenêtres de backends.

Kivy est un logiciel libre et open source distribué sous licence MIT.

FLTK

Les liaisons Python pour the FLTK toolkit [http://www.fltk.org], un système de fenêtrage multi-plateformes simple mais puissant et mûr, sont disponibles auprès de the PyFLTK project [http://pyfltk.sourceforge.net].

OpenGL

Pour les clients OpenGL, voir PyOpenGL [http://pyopengl.sourceforge.net].

Quelles boîtes à outils IUG spécifiques à la plate-forme existent pour Python ?

By installing the PyObjc Objective-C bridge [https://pythonhosted.org/pyobjc/], Python programs can use Mac OS X’s Cocoa libraries.

Pythonwin de Mark Hammond inclut une interface vers les classes Microsoft Foundation Classes et un environnement de programmation Python qui est écrit principalement en Python utilisant les classes MFC.

Questions à propos de Tkinter

Comment puis-je geler (freezer) les applications Tkinter ?

Freeze est un outil pour créer des applications autonomes. Lors du freezage des applications Tkinter, les applications ne seront pas vraiment autonomes, car l’application aura toujours besoin des bibliothèques Tcl et Tk.

Une solution consiste à empaqueter les bibliothèques Tcl et Tk dans l’application et de les retrouver à l’exécution en utilisant les variables d’environnement TCL_LIBRARY et TK_LIBRARY.

Pour obtenir des applications vraiment autonomes, les scripts Tcl qui forment la bibliothèque doivent également être intégrés dans l’application. Un outil supportant cela est SAM (modules autonomes), qui fait partie de la distribution Tix (http://tix.sourceforge.net/).

Compilez Tix avec SAM activé, exécutez l’appel approprié à Tclsam_init(), etc. dans le fichier Modules/tkappinit.c de Python, et liez avec libtclsam et libtksam (il est également possible d’inclure les bibliothèques Tix).

Puis-je modifier des événements Tk pendant l’écoute des E/S ?

Sur d’autres plates-formes que Windows, oui, et vous n’avez même pas besoin de fils d’exécution multiples ! Mais vous devrez restructurer un peu votre code E/S. Tk possède l’équivalent de l’appel XtAddInput() de Xt, qui vous permet d’enregistrer une fonction de callback qui sera appelée par la boucle principale Tk lorsque des E/S sont disponibles sur un descripteur de fichier. Voir Gestionnaires de fichiers.

Je n’arrive pas à faire fonctionner les raccourcis clavier dans Tkinter : pourquoi ?

Une raison récurrente est que les gestionnaires d’évènements liés à des évènements avec la méthode bind() ne sont pas pris en charge même lorsque la touche appropriée est activée.

La cause la plus fréquente est que l’objet graphique auquel s’applique la liaison n’a pas de « focus clavier ». Consultez la documentation Tk pour la commande focus. Habituellement, un objet graphique reçoit le focus du clavier en cliquant dessus (mais pas pour les étiquettes ; voir l’option takefocus).

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FAQ « Pourquoi Python est installé sur mon ordinateur ? »

Qu’est-ce que Python ?

Python est un langage de programmation. Il est utilisé dans de nombreuses applications. Souvent utilisé dans les lycées et universités comme langage d’introduction à la programmation pour sa simplicité d’apprentissage, il est aussi utilisé par des développeurs professionnels appartenant à des grands groupes comme Google, la NASA, Lucasfilm etc.

Si vous voulez en apprendre plus sur Python, vous pouvez commencer par le Guide des Débutants pour Python [https://wiki.python.org/moin/BeginnersGuide].

Pourquoi Python est installé sur ma machine ?

Si Python est installé sur votre système mais que vous ne vous rappelez pas l’avoir installé, il y a plusieurs raisons possibles à sa présence.

Peut être qu’un autre utilisateur de l’ordinateur voulait apprendre la programmation et l’a installé, dans ce cas vous allez devoir trouver qui a utilisé votre machine et aurait pu l’installer.

Une application tierce installée sur votre machine écrite en Python installera Python. Il existe de nombreuses applications de ce type, allant de programme avec interface graphique, jusqu’aux scripts d’administration, en passant par les serveurs.

Certaines machines fonctionnant avec le système d’exploitation Windows possèdent une installation de Python. À ce jour, les ordinateurs des marques Hewlett-Packard et Compaq incluent nativement Python. Certains outils d’administration de ces marques sont écrits en Python.

Python est installé par défaut et à l’installation par de nombreux systèmes Unix, comme Mac OS X et certaines distributions Linux.

Puis-je supprimer Python ?

Cela dépend de l’origine de Python.

Si Python a été installé délibérément par une personne tierce ou vous même, vous pouvez le supprimer sans causer de dommage. Sous Windows, vous pouvez simplement utiliser l’icône d’Ajout / Suppression de programmes du Panneau de configuration.

Si Python a été installé par une application tierce, Python peut être désinstallé, l’application l’ayant installé cessera alors de fonctionner. Dans ce cas, désinstallez l’application en utilisant son outil de désinstallation est plus indiqué que supprimer Python.

Si Python a été installé avec votre système d’exploitation, le supprimer n’est pas recommandé. Si vous choisissez tout de même de le supprimer, tous les outils écrits en python cesseront alors de fonctionner, certains outils pouvant être importants. La réinstallation intégrale du système pourrait être nécessaire pour résoudre les problèmes suite à la désinstallation de Python.

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Glossaire

>>>

L’invite de commande utilisée par défaut dans l’interpréteur interactif. On la voit souvent dans des exemples de code qui peuvent être exécutés interactivement dans l’interpréteur.

...

L’invite de commande utilisée par défaut dans l’interpréteur interactif lorsqu’on entre un bloc de code indenté, dans des délimiteurs fonctionnant par paires (parenthèses, crochets, accolades, triple guillemets), ou après un décorateur.

2to3

Outil qui essaie de convertir du code pour Python 2.x en code pour Python 3.x en gérant la plupart des incompatibilités qui peuvent être détectées en analysant la source et parcourant son arbre syntaxique.

2to3 est disponible dans la bibliothèque standard sous le nom de lib2to3 ; un point d’entrée indépendant est fourni via Tools/scripts/2to3. Cf. 2to3 — Traduction automatique de code en Python 2 vers Python 3.

classe de base abstraite

Les classes de base abstraites (ABC, suivant l’abréviation anglaise Abstract Base Class) complètent le duck-typing en fournissant un moyen de définir des interfaces pour les cas où d’autres techniques comme hasattr() seraient inélégantes ou subtilement fausses (par exemple avec les méthodes magiques). Les ABC introduisent des sous-classes virtuelles qui n’héritent pas d’une classe mais qui sont quand même reconnues par isinstance() ou issubclass() (voir la documentation du module abc). Python contient de nombreuses ABC pour les structures de données (dans le module collections.abc), les nombres (dans le module numbers), les flux (dans le module io) et les chercheurs-chargeurs du système d’importation (dans le module importlib.abc). Vous pouvez créer vos propres ABC avec le module abc.

annotation

Étiquette associée à une variable, un attribut de classe, un paramètre de fonction ou une valeur de retour. Elle est utilisée par convention comme type hint.

Les annotations de variables locales ne sont pas accessibles au moment de l’exécution, mais les annotations de variables globales, d’attributs de classe et de fonctions sont stockées dans l’attribut spécial __annotations__ des modules, classes et fonctions, respectivement.

Voir variable annotation, function annotation, PEP 484 [https://www.python.org/dev/peps/pep-0484] et PEP 526 [https://www.python.org/dev/peps/pep-0526], qui décrivent cette fonctionnalité.

argument

Valeur, donnée à une fonction ou à une méthode lors de son appel. Il existe deux types d’arguments :

argument nommé : un argument précédé d’un identifiant (comme name=) ou un dictionnaire précédé de **, lors d’un appel de fonction. Par exemple, 3 et 5 sont tous les deux des arguments nommés dans l’appel à complex() ici :

complex(real=3, imag=5)
complex(**{'real': 3, 'imag': 5})

argument positionnel : un argument qui n’est pas nommé. Les arguments positionnels apparaissent au début de la liste des arguments, ou donnés sous forme d’un itérable précédé par *. Par exemple, 3 et 5 sont tous les deux des arguments positionnels dans les appels suivants :

complex(3, 5)
complex(*(3, 5))

Les arguments se retrouvent dans le corps de la fonction appelée parmi les variables locales. Voir la section Appels à propos des règles dictant cette affectation. Syntaxiquement, toute expression est acceptée comme argument, et c’est la valeur résultante de l’expression qui sera affectée à la variable locale.

Voir aussi parameter dans le glossaire, la question Différence entre argument et paramètre de la FAQ et la PEP 362 [https://www.python.org/dev/peps/pep-0362].

gestionnaire de contexte asynchrone

(asynchronous context manager en anglais) Objet contrôlant l’environnement à l’intérieur d’une instruction with en définissant les méthodes __aenter__() et __aexit__(). A été Introduit par la PEP 492 [https://www.python.org/dev/peps/pep-0492].

générateur asynchrone

Fonction qui renvoie un asynchronous generator iterator. Cela ressemble à une coroutine définie par async def, sauf qu’elle contient une ou des expressions yield produisant ainsi uns série de valeurs utilisables dans une boucle async for.

Usually refers to an asynchronous generator function, but may refer to an asynchronous generator iterator in some contexts. In cases where the intended meaning isn’t clear, using the full terms avoids ambiguity.

Un générateur asynchrone peut contenir des expressions await ainsi que des instructions async for, et async with.

itérateur de générateur asynchrone

Objet créé par une fonction asynchronous generator.

This is an asynchronous iterator which when called using the __anext__() method returns an awaitable object which will execute the body of the asynchronous generator function until the next yield expression.

Chaque yield suspend temporairement l’exécution, en gardant en mémoire l’endroit et l’état de l’exécution (ce qui inclut les variables locales et les try en cours). Lorsque l’exécution de l’itérateur de générateur asynchrone reprend avec un nouvel awaitable renvoyé par __anext__(), elle repart de là où elle s’était arrêtée. Voir la PEP 492 [https://www.python.org/dev/peps/pep-0492] et la PEP 525 [https://www.python.org/dev/peps/pep-0525].

itérable asynchrone

Objet qui peut être utilisé dans une instruction async for. Sa méthode __aiter__() doit renvoyer un asynchronous iterator. A été introduit par la PEP 492 [https://www.python.org/dev/peps/pep-0492].

itérateur asynchrone

An object that implements the __aiter__() and __anext__() methods. __anext__ must return an awaitable object. async for resolves the awaitables returned by an asynchronous iterator’s __anext__() method until it raises a StopAsyncIteration exception. Introduced by PEP 492 [https://www.python.org/dev/peps/pep-0492].

attribut

Valeur associée à un objet et désignée par son nom via une notation utilisant des points. Par exemple, si un objet o possède un attribut a, il sera référencé par o.a.

awaitable

Objet pouvant être utilisé dans une expression await. Ce peut être une coroutine ou un objet avec une méthode __await__(). Voir aussi la PEP 492 [https://www.python.org/dev/peps/pep-0492].

BDFL

Dictateur bienveillant à vie (Benevolent Dictator For Life en anglais). Pseudonyme de Guido van Rossum [https://www.python.org/~guido/], le créateur de Python.

fichier binaire

Un file object capable de lire et d’écrire des bytes-like objects. Des fichiers binaires sont, par exemple, les fichiers ouverts en mode binaire ('rb', 'wb', ou 'rb+'), sys.stdin.buffer, sys.stdout.buffer, les instances de io.BytesIO ou de gzip.GzipFile.

Consultez fichier texte, un objet fichier capable de lire et d’écrire des objets str.

objet octet-compatible

Un objet gérant les Protocole tampon et pouvant exporter un tampon (buffer en anglais) C-contiguous. Cela inclut les objets bytes, bytearray et array.array, ainsi que beaucoup d’objets memoryview. Les objets bytes-compatibles peuvent être utilisés pour diverses opérations sur des données binaires, comme la compression, la sauvegarde dans un fichier binaire ou l’envoi sur le réseau.

Certaines opérations nécessitent de travailler sur des données binaires variables. La documentation parle de ceux-ci comme des read-write bytes-like objects. Par exemple, bytearray ou une memoryview d’un bytearray en font partie. D’autres opérations nécessitent de travailler sur des données binaires stockées dans des objets immuables (« read-only bytes-like objects »), par exemples bytes ou memoryview d’un objet byte.

code intermédiaire (bytecode)

Le code source, en Python, est compilé en un code intermédiaire (bytecode en anglais), la représentation interne à CPython d’un programme Python. Le code intermédiaire est mis en cache dans un fichier .pyc de manière à ce qu’une seconde exécution soit plus rapide (la compilation en code intermédiaire a déjà été faite). On dit que ce langage intermédiaire est exécuté sur une virtual machine qui exécute des instructions machine pour chaque instruction du code intermédiaire. Notez que le code intermédiaire n’a pas vocation à fonctionner sur différentes machines virtuelles Python ou à être stable entre différentes versions de Python.

La documentation du module dis fournit une liste des instructions du code intermédiaire.

classe

Modèle pour créer des objets définis par l’utilisateur. Une définition de classe (class) contient normalement des définitions de méthodes qui agissent sur les instances de la classe.

variable de classe

Une variable définie dans une classe et destinée à être modifiée uniquement au niveau de la classe (c’est-à-dire, pas dans une instance de la classe).

coercition

Conversion implicite d’une instance d’un type vers un autre lors d’une opération dont les deux opérandes doivent être de même type. Par exemple int(3.15) convertit explicitement le nombre à virgule flottante en nombre entier 3. Mais dans l’opération 3 + 4.5, les deux opérandes sont d’un type différent, alors qu’elles doivent avoir le même type pour être additionnées (sinon une exception TypeError serait levée). Sans coercition, toutes les opérandes, même de types compatibles, devraient être converties (on parle aussi de cast) explicitement par le développeur, par exemple : float(3) + 4.5 au lieu du simple 3 + 4.5.

nombre complexe

Extension des nombres réels familiers, dans laquelle tous les nombres sont exprimés sous la forme d’une somme d’une partie réelle et d’une partie imaginaire. Les nombres imaginaires sont les nombres réels multipliés par l’unité imaginaire (la racine carrée de -1, souvent écrite i en mathématiques ou j par les ingénieurs). Python comprend nativement les nombres complexes, écrits avec cette dernière notation : la partie imaginaire est écrite avec un suffixe j, exemple, 3+1j. Pour utiliser les équivalents complexes de math, utilisez cmath. Les nombres complexes sont un concept assez avancé en mathématiques. Si vous ne connaissez pas ce concept, vous pouvez tranquillement les ignorer.

gestionnaire de contexte

Objet contrôlant l’environnement à l’intérieur d’un bloc with en définissant les méthodes __enter__() et __exit__(). Consultez la PEP 343 [https://www.python.org/dev/peps/pep-0343].

contigu

Un tampon (buffer en anglais) est considéré comme contigu s’il est soit C-contigu soit Fortran-contigu. Les tampons de dimension zéro sont C-contigus et Fortran-contigus. Pour un tableau à une dimension, ses éléments doivent être placés en mémoire l’un à côté de l’autre, dans l’ordre croissant de leur indice, en commençant à zéro. Pour qu’un tableau multidimensionnel soit C-contigu, le dernier indice doit être celui qui varie le plus rapidement lors du parcours de ses éléments dans l’ordre de leur adresse mémoire. À l’inverse, dans les tableaux Fortran-contigu, c’est le premier indice qui doit varier le plus rapidement.

coroutine

Les coroutines sont une forme généralisées des fonctions. On entre dans une fonction en un point et on en sort en un autre point. On peut entrer, sortir et reprendre l’exécution d’une coroutine en plusieurs points. Elles peuvent être implémentées en utilisant l’instruction async def. Voir aussi la PEP 492 [https://www.python.org/dev/peps/pep-0492].

fonction coroutine

Fonction qui renvoie un objet coroutine. Une fonction coroutine peut être définie par l’instruction async def et peut contenir les mots clés await, async for ainsi que async with. A été introduit par la PEP 492 [https://www.python.org/dev/peps/pep-0492].

CPython

L’implémentation canonique du langage de programmation Python, tel que distribué sur python.org [https://www.python.org]. Le terme « CPython » est utilisé dans certains contextes lorsqu’il est nécessaire de distinguer cette implémentation des autres comme Jython ou IronPython.

décorateur

Fonction dont la valeur de retour est une autre fonction. Un décorateur est habituellement utilisé pour transformer une fonction via la syntaxe @wrapper, dont les exemples typiques sont : classmethod() et staticmethod().

La syntaxe des décorateurs est simplement du sucre syntaxique, les définitions des deux fonctions suivantes sont sémantiquement équivalentes :

def f(...):
    ...
f = staticmethod(f)

@staticmethod
def f(...):
    ...

Quoique moins fréquemment utilisé, le même concept existe pour les classes. Consultez la documentation définitions de fonctions et définitions de classes pour en savoir plus sur les décorateurs.

descripteur

N’importe quel objet définissant les méthodes __get__(), __set__(), ou __delete__(). Lorsque l’attribut d’une classe est un descripteur, son comportement spécial est déclenché lors de la recherche des attributs. Normalement, lorsque vous écrivez a.b pour obtenir, affecter ou effacer un attribut, Python recherche l’objet nommé b dans le dictionnaire de la classe de a. Mais si b est un descripteur, c’est la méthode de ce descripteur qui est alors appelée. Comprendre les descripteurs est requis pour avoir une compréhension approfondie de Python, ils sont la base de nombre de ses caractéristiques notamment les fonctions, méthodes, propriétés, méthodes de classes, méthodes statiques et les références aux classes parentes.

Pour plus d’informations sur les méthodes des descripteurs, consultez Implémentation de descripteurs.

dictionnaire

Structure de donnée associant des clés à des valeurs. Les clés peuvent être n’importe quel objet possédant les méthodes __hash__() et __eq__(). En Perl, les dictionnaires sont appelés « hash ».

vue de dictionnaire

Objets retournés par les méthodes dict.keys(), dict.values() et dict.items(). Ils fournissent des vues dynamiques des entrées du dictionnaire, ce qui signifie que lorsque le dictionnaire change, la vue change. Pour transformer une vue en vraie liste, utilisez list(dictview). Voir Les vues de dictionnaires.

docstring (chaîne de documentation)

Première chaîne littérale qui apparaît dans l’expression d’une classe, fonction, ou module. Bien qu’ignorée à l’exécution, elle est reconnue par le compilateur et placée dans l’attribut __doc__ de la classe, de la fonction ou du module. Comme cette chaîne est disponible par introspection, c’est l’endroit idéal pour documenter l’objet.

duck-typing

Style de programmation qui ne prend pas en compte le type d’un objet pour déterminer s’il respecte une interface, mais qui appelle simplement la méthode ou l’attribut (Si ça a un bec et que ça cancane, ça doit être un canard, duck signifie canard en anglais). En se concentrant sur les interfaces plutôt que les types, du code bien construit améliore sa flexibilité en autorisant des substitutions polymorphiques. Le duck-typing évite de vérifier les types via type() ou isinstance(), Notez cependant que le duck-typing peut travailler de pair avec les classes de base abstraites. À la place, le duck-typing utilise plutôt hasattr() ou la programmation EAFP.

EAFP

Il est plus simple de demander pardon que demander la permission (Easier to Ask for Forgiveness than Permission en anglais). Ce style de développement Python fait l’hypothèse que le code est valide et traite les exceptions si cette hypothèse s’avère fausse. Ce style, propre et efficace, est caractérisé par la présence de beaucoup de mots clés try et except. Cette technique de programmation contraste avec le style LBYL utilisé couramment dans les langages tels que C.

expression

Suite logique de termes et chiffres conformes à la syntaxe Python dont l’évaluation fournit une valeur. En d’autres termes, une expression est une suite d’éléments tels que des noms, opérateurs, littéraux, accès d’attributs, méthodes ou fonctions qui aboutissent à une valeur. Contrairement à beaucoup d’autres langages, les différentes constructions du langage ne sont pas toutes des expressions. On trouve également des instructions qui ne peuvent pas être utilisées comme expressions, tel que if. Les affectations sont également des instructions et non des expressions.

module d’extension

Module écrit en C ou C++, utilisant l’API C de Python pour interagir avec Python et le code de l’utilisateur.

f-string

Chaîne littérale préfixée de 'f' ou 'F'. Les « f-strings » sont un raccourci pour formatted string literals. Voir la PEP 498 [https://www.python.org/dev/peps/pep-0498].

objet fichier

Objet exposant une ressource via une API orientée fichier (avec les méthodes read() ou write()). En fonction de la manière dont il a été créé, un objet fichier peut interfacer l’accès à un fichier sur le disque ou à un autre type de stockage ou de communication (typiquement l’entrée standard, la sortie standard, un tampon en mémoire, un connecteur réseau…). Les objets fichiers sont aussi appelés file-like-objects ou streams.

Il existe en réalité trois catégories de fichiers objets : les fichiers binaires bruts, les fichiers binaires avec tampon (buffer) et les fichiers textes. Leurs interfaces sont définies dans le module io. Le moyen le plus simple et direct de créer un objet fichier est d’utiliser la fonction open().

objet fichier-compatible

Synonyme de objet fichier.

chercheur

Objet qui essaie de trouver un chargeur pour le module en cours d’importation.

Depuis Python 3.3, il existe deux types de chercheurs : les chercheurs dans les méta-chemins à utiliser avec sys.meta_path ; les chercheurs d’entrée dans path à utiliser avec sys.path_hooks.

Voir les PEP 302 [https://www.python.org/dev/peps/pep-0302], PEP 420 [https://www.python.org/dev/peps/pep-0420] et PEP 451 [https://www.python.org/dev/peps/pep-0451] pour plus de détails.

division entière

Division mathématique arrondissant à l’entier inférieur. L’opérateur de la division entière est //. Par exemple l’expression 11 // 4 vaut 2, contrairement à 11 / 4 qui vaut 2.75. Notez que (-11) // 4 vaut -3 car l’arrondi se fait à l’entier inférieur. Voir la PEP 328 [https://www.python.org/dev/peps/pep-0328].

fonction

Suite d’instructions qui renvoie une valeur à son appelant. On peut lui passer des arguments qui pourront être utilisés dans le corps de la fonction. Voir aussi paramètre, méthode et Définition de fonctions.

annotation de fonction

annotation d’un paramètre de fonction ou valeur de retour.

Function annotations are usually used for type hints: for example, this function is expected to take two int arguments and is also expected to have an int return value:

def sum_two_numbers(a: int, b: int) -> int:
   return a + b

L’annotation syntaxique de la fonction est expliquée dans la section Définition de fonctions.

Voir variable annotation et PEP 484 [https://www.python.org/dev/peps/pep-0484], qui décrivent cette fonctionnalité.

__future__

Pseudo-module que les développeurs peuvent utiliser pour activer de nouvelles fonctionnalités du langage qui ne sont pas compatibles avec l’interpréteur utilisé.

En important le module __future__ et en affichant ses variables, vous pouvez voir à quel moment une nouvelle fonctionnalité a été rajoutée dans le langage et quand elle devient le comportement par défaut :

>>> import __future__
>>> __future__.division
_Feature((2, 2, 0, 'alpha', 2), (3, 0, 0, 'alpha', 0), 8192)

ramasse-miettes

(garbage collection en anglais) Mécanisme permettant de libérer de la mémoire lorsqu’elle n’est plus utilisée. Python utilise un ramasse-miettes par comptage de référence et un ramasse-miettes cyclique capable de détecter et casser les références circulaires. Le ramasse-miettes peut être contrôlé en utilisant le module gc.

générateur

Fonction qui renvoie un itérateur de générateur. Cela ressemble à une fonction normale, en dehors du fait qu’elle contient une ou des expressions yield produisant une série de valeurs utilisable dans une boucle for ou récupérées une à une via la fonction next().

Fait généralement référence à une fonction générateur mais peut faire référence à un itérateur de générateur dans certains contextes. Dans les cas où le sens voulu n’est pas clair, utiliser les termes complets lève l’ambigüité.

itérateur de générateur

Objet créé par une fonction générateur.

Chaque yield suspend temporairement l’exécution, en se rappelant l’endroit et l’état de l’exécution (y compris les variables locales et les try en cours). Lorsque l’itérateur de générateur reprend, il repart là où il en était (contrairement à une fonction qui prendrait un nouveau départ à chaque invocation).

expression génératrice

Expression qui donne un itérateur. Elle ressemble à une expression normale, suivie d’une expression for définissant une variable de boucle, un intervalle et une expression if optionnelle. Toute cette expression génère des valeurs pour la fonction qui l’entoure :

>>> sum(i*i for i in range(10))         # sum of squares 0, 1, 4, ... 81
285

fonction générique

Fonction composée de plusieurs fonctions implémentant les mêmes opérations pour différents types. L’implémentation à utiliser est déterminée lors de l’appel par l’algorithme de répartition.

Voir aussi single dispatch, le décorateur functools.singledispatch() et la PEP 443 [https://www.python.org/dev/peps/pep-0443].

GIL

Voir global interpreter lock.

verrou global de l’interpréteur

(global interpreter lock en anglais) Mécanisme utilisé par l’interpréteur CPython pour s’assurer qu’un seul fil d’exécution (thread en anglais) n’exécute le bytecode à la fois. Cela simplifie l’implémentation de CPython en rendant le modèle objet (incluant des parties critiques comme la classe native dict) implicitement protégé contre les accès concourants. Verrouiller l’interpréteur entier rend plus facile l’implémentation de multiples fils d’exécution (multi-thread en anglais), au détriment malheureusement de beaucoup du parallélisme possible sur les machines ayant plusieurs processeurs.

Cependant, certains modules d’extension, standards ou non, sont conçus de manière à libérer le GIL lorsqu’ils effectuent des tâches lourdes tel que la compression ou le hachage. De la même manière, le GIL est toujours libéré lors des entrées / sorties.

Les tentatives précédentes d’implémenter un interpréteur Python avec une granularité de verrouillage plus fine ont toutes échouées, à cause de leurs mauvaises performances dans le cas d’un processeur unique. Il est admis que corriger ce problème de performance induit mènerait à une implémentation beaucoup plus compliquée et donc plus coûteuse à maintenir.

hachable

Un objet est hachable s’il a une empreinte (hash) qui ne change jamais (il doit donc implémenter une méthode __hash__()) et s’il peut être comparé à d’autres objets (avec la méthode __eq__()). Les objets hachables dont la comparaison par __eq__ est vraie doivent avoir la même empreinte.

La hachabilité permet à un objet d’être utilisé comme clé de dictionnaire ou en tant que membre d’un ensemble (type set), car ces structures de données utilisent ce hash.

Tous les types immuables natifs de Python sont hachables, mais les conteneurs muables (comme les listes ou les dictionnaires) ne le sont pas. Toutes les instances de classes définies par les utilisateurs sont hachables par défaut. Elles sont toutes considérées différentes (sauf avec elles-mêmes) et leur valeur de hachage est calculée à partir de leur id().

IDLE

Environnement de développement intégré pour Python. IDLE est un éditeur basique et un interpréteur livré avec la distribution standard de Python.

immuable

Objet dont la valeur ne change pas. Les nombres, les chaînes et les n-uplets sont immuables. Ils ne peuvent être modifiés. Un nouvel objet doit être créé si une valeur différente doit être stockée. Ils jouent un rôle important quand une valeur de hash constante est requise, typiquement en clé de dictionnaire.

chemin des importations

Liste de entrées dans lesquelles le chercheur basé sur les chemins cherche les modules à importer. Typiquement, lors d’une importation, cette liste vient de sys.path ; pour les sous-paquets, elle peut aussi venir de l’attribut __path__ du paquet parent.

importer

Processus rendant le code Python d’un module disponible dans un autre.

importateur

Objet qui trouve et charge un module, en même temps un chercheur et un chargeur.

interactif

Python a un interpréteur interactif, ce qui signifie que vous pouvez écrire des expressions et des instructions à l’invite de l’interpréteur. L’interpréteur Python va les exécuter immédiatement et vous en présenter le résultat. Démarrez juste python (probablement depuis le menu principal de votre ordinateur). C’est un moyen puissant pour tester de nouvelles idées ou étudier de nouveaux modules (souvenez-vous de help(x)).

interprété

Python est un langage interprété, en opposition aux langages compilés, bien que la frontière soit floue en raison de la présence d’un compilateur en code intermédiaire. Cela signifie que les fichiers sources peuvent être exécutés directement, sans avoir à compiler un fichier exécutable intermédiaire. Les langages interprétés ont généralement un cycle de développement / débogage plus court que les langages compilés. Cependant, ils s’exécutent généralement plus lentement. Voir aussi interactif.

arrêt de l’interpréteur

Lorsqu’on lui demande de s’arrêter, l’interpréteur Python entre dans une phase spéciale où il libère graduellement les ressources allouées, comme les modules ou quelques structures de données internes. Il fait aussi quelques appels au ramasse-miettes. Cela peut déclencher l’exécution de code dans des destructeurs ou des fonctions de rappels de weakrefs. Le code exécuté lors de l’arrêt peut rencontrer des exceptions puisque les ressources auxquelles il fait appel sont susceptibles de ne plus fonctionner, (typiquement les modules des bibliothèques ou le mécanisme de warning).

La principale raison d’arrêt de l’interpréteur est que le module __main__ ou le script en cours d’exécution a terminé de s’exécuter.

itérable

Objet capable de renvoyer ses éléments un à un. Par exemple, tous les types séquence (comme list, str, et tuple), quelques autres types comme dict, objets fichiers ou tout objet d’une classe ayant une méthode __iter__() ou __getitem__() qui implémente la sémantique d’une Sequence.

Les itérables peuvent être utilisés dans des boucles for et à beaucoup d’autres endroits où une séquence est requise (zip(), map()…). Lorsqu’un itérable est passé comme argument à la fonction native iter(), celle-ci fournit en retour un itérateur sur cet itérable. Cet itérateur n’est valable que pour une seule passe sur le jeu de valeurs. Lors de l’utilisation d’itérables, il n’est habituellement pas nécessaire d’appeler iter() ou de s’occuper soi-même des objets itérateurs. L’instruction for le fait automatiquement pour vous, créant une variable temporaire anonyme pour garder l’itérateur durant la boucle. Voir aussi itérateur, séquence et générateur.

itérateur

Objet représentant un flux de donnée. Des appels successifs à la méthode __next__() de l’itérateur (ou le passer à la fonction native next()) donne successivement les objets du flux. Lorsque plus aucune donnée n’est disponible, une exception StopIteration est levée. À ce point, l’itérateur est épuisé et tous les appels suivants à sa méthode __next__() lèveront encore une exception StopIteration. Les itérateurs doivent avoir une méthode __iter__() qui renvoie l’objet itérateur lui-même, de façon à ce que chaque itérateur soit aussi itérable et puisse être utilisé dans la plupart des endroits où d’autres itérables sont attendus. Une exception notable est un code qui tente plusieurs itérations complètes. Un objet conteneur, (tel que list) produit un nouvel itérateur neuf à chaque fois qu’il est passé à la fonction iter() ou s’il est utilisé dans une boucle for. Faire ceci sur un itérateur donnerait simplement le même objet itérateur épuisé utilisé dans son itération précédente, le faisant ressembler à un conteneur vide.

Vous trouverez davantage d’informations dans Les types itérateurs.

fonction clé

Une fonction clé est un objet appelable qui renvoie une valeur à fins de tri ou de classement. Par exemple, la fonction locale.strxfrm() est utilisée pour générer une clé de classement prenant en compte les conventions de classement spécifiques aux paramètres régionaux courants.

Plusieurs outils dans Python acceptent des fonctions clés pour déterminer comment les éléments sont classés ou groupés. On peut citer les fonctions min(), max(), sorted(), list.sort(), heapq.merge(), heapq.nsmallest(), heapq.nlargest() et itertools.groupby().

Il existe plusieurs moyens de créer une fonction clé. Par exemple, la méthode str.lower() peut servir de fonction clé pour effectuer des recherches insensibles à la casse. Aussi, il est possible de créer des fonctions clés avec des expressions lambda, comme lambda r: (r[0], r[2]). Vous noterez que le module operator propose des constructeurs de fonctions clefs : attrgetter(), itemgetter() et methodcaller(). Voir Comment Trier pour des exemples de création et d’utilisation de fonctions clefs.

argument nommé

Voir argument.

lambda

Fonction anonyme sous la forme d’une expression et ne contenant qu’une seule expression, exécutée lorsque la fonction est appelée. La syntaxe pour créer des fonctions lambda est : lambda [parameters]: expression

LBYL

Regarde avant de sauter, (Look before you leap en anglais). Ce style de programmation consiste à vérifier des conditions avant d’effectuer des appels ou des accès. Ce style contraste avec le style EAFP et se caractérise par la présence de beaucoup d’instructions if.

Dans un environnement avec plusieurs fils d’exécution (multi-threaded en anglais), le style LBYL peut engendrer un séquencement critique (race condition en anglais) entre le « regarde » et le « sauter ». Par exemple, le code if key in mapping: return mapping[key] peut échouer si un autre fil d’exécution supprime la clé key du mapping après le test mais avant l’accès. Ce problème peut être résolu avec des verrous (locks) ou avec l’approche EAFP.

list

Un type natif de sequence dans Python. En dépit de son nom, une list ressemble plus à un tableau (array dans la plupart des langages) qu’à une liste chaînée puisque les accès se font en O(1).

liste en compréhension (ou liste en intension)

Écriture concise pour manipuler tout ou partie des éléments d’une séquence et renvoyer une liste contenant les résultats. result = ['{:#04x}'.format(x) for x in range(256) if x % 2 == 0] génère la liste composée des nombres pairs de 0 à 255 écrits sous formes de chaînes de caractères et en hexadécimal (0x…). La clause if est optionnelle. Si elle est omise, tous les éléments du range(256) seront utilisés.

chargeur

Objet qui charge un module. Il doit définir une méthode nommée load_module(). Un chargeur est typiquement donné par un chercheur. Voir la PEP 302 [https://www.python.org/dev/peps/pep-0302] pour plus de détails et importlib.ABC.Loader pour sa classe de base abstraite.

tableau de correspondances

(mapping en anglais) Conteneur permettant de rechercher des éléments à partir de clés et implémentant les méthodes spécifiées dans les classes de base abstraites collections.abc.Mapping ou collections.abc.MutableMapping. Les classes suivantes sont des exemples de tableaux de correspondances : dict, collections.defaultdict, collections.OrderedDict et collections.Counter.

chercheur dans les méta-chemins

Un chercheur renvoyé par une recherche dans sys.meta_path. Les chercheurs dans les méta-chemins ressemblent, mais sont différents des chercheurs d’entrée dans path.

Voir importlib.abc.MetaPathFinder pour les méthodes que les chercheurs dans les méta-chemins doivent implémenter.

métaclasse

Classe d’une classe. Les définitions de classe créent un nom pour la classe, un dictionnaire de classe et une liste de classes parentes. La métaclasse a pour rôle de réunir ces trois paramètres pour construire la classe. La plupart des langages orientés objet fournissent une implémentation par défaut. La particularité de Python est la possibilité de créer des métaclasses personnalisées. La plupart des utilisateurs n’auront jamais besoin de cet outil, mais lorsque le besoin survient, les métaclasses offrent des solutions élégantes et puissantes. Elles sont utilisées pour journaliser les accès à des propriétés, rendre sûrs les environnements multi-threads, suivre la création d’objets, implémenter des singletons et bien d’autres tâches.

Plus d’informations sont disponibles dans : Méta-classes.

méthode

Fonction définie à l’intérieur d’une classe. Lorsqu’elle est appelée comme un attribut d’une instance de cette classe, la méthode reçoit l’instance en premier argument (qui, par convention, est habituellement nommé self). Voir function et nested scope.

ordre de résolution des méthodes

L’ordre de résolution des méthodes (MRO pour Method Resolution Order en anglais) est, lors de la recherche d’un attribut dans les classes parentes, la façon dont l’interpréteur Python classe ces classes parentes. Voir The Python 2.3 Method Resolution Order [https://www.python.org/download/releases/2.3/mro/] pour plus de détails sur l’algorithme utilisé par l’interpréteur Python depuis la version 2.3.

module

Objet utilisé pour organiser une portion unitaire de code en Python. Les modules ont un espace de nommage et peuvent contenir n’importe quels objets Python. Charger des modules est appelé importer.

Voir aussi paquet.

spécificateur de module

Espace de nommage contenant les informations, relatives à l’importation, utilisées pour charger un module. C’est une instance de la classe importlib.machinery.ModuleSpec.

MRO

Voir ordre de résolution des méthodes.

muable

Un objet muable peut changer de valeur tout en gardant le même id(). Voir aussi immuable.

n-uplet nommé

(named-tuple en anglais) Classe qui, comme un n-uplet (tuple en anglais), a ses éléments accessibles par leur indice. Et en plus, les éléments sont accessibles par leur nom. Par exemple, time.localtime() donne un objet ressemblant à un n-uplet, dont year est accessible par son indice : t[0] ou par son nom : t.tm_year).

Un n-uplet nommé peut être un type natif tel que time.struct_time ou il peut être construit comme une simple classe. Un n-uplet nommé complet peut aussi être créé via la fonction collections.namedtuple(). Cette dernière approche fournit automatiquement des fonctionnalités supplémentaires, tel qu’une représentation lisible comme Employee(name='jones', title='programmer').

espace de nommage

L’endroit où une variable est stockée. Les espaces de nommage sont implémentés avec des dictionnaires. Il existe des espaces de nommage globaux, natifs ou imbriqués dans les objets (dans les méthodes). Les espaces de nommage favorisent la modularité car ils permettent d’éviter les conflits de noms. Par exemple, les fonctions builtins.open et os.open() sont différenciées par leurs espaces de nom. Les espaces de nommage aident aussi à la lisibilité et la maintenabilité en rendant clair quel module implémente une fonction. Par exemple, écrire random.seed() ou itertools.islice() affiche clairement que ces fonctions sont implémentées respectivement dans les modules random et itertools.

paquet-espace de nommage

Un paquet tel que défini dans la PEP 421 [https://www.python.org/dev/peps/pep-0421] qui ne sert qu’à contenir des sous-paquets. Les paquets-espace de nommage peuvent n’avoir aucune représentation physique et, plus spécifiquement, ne sont pas comme un paquet classique puisqu’ils n’ont pas de fichier __init__.py.

Voir aussi module.

portée imbriquée

Possibilité de faire référence à une variable déclarée dans une définition englobante. Typiquement, une fonction définie à l’intérieur d’une autre fonction a accès aux variables de cette dernière. Souvenez-vous cependant que cela ne fonctionne que pour accéder à des variables, pas pour les assigner. Les variables locales sont lues et assignées dans l’espace de nommage le plus proche. Tout comme les variables globales qui sont stockés dans l’espace de nommage global, le mot clef nonlocal permet d’écrire dans l’espace de nommage dans lequel est déclarée la variable.

nouvelle classe

Ancien nom pour l’implémentation actuelle des classes, pour tous les objets. Dans les anciennes versions de Python, seules les nouvelles classes pouvaient utiliser les nouvelles fonctionnalités telles que __slots__, les descripteurs, les propriétés, __getattribute__(), les méthodes de classe et les méthodes statiques.

objet

N’importe quelle donnée comportant des états (sous forme d’attributs ou d’une valeur) et un comportement (des méthodes). C’est aussi (object) l’ancêtre commun à absolument toutes les nouvelles classes.

paquet

module Python qui peut contenir des sous-modules ou des sous-paquets. Techniquement, un paquet est un module qui possède un attribut __path__.

Voir aussi paquet classique et namespace package.

paramètre

Entité nommée dans la définition d’une fonction (ou méthode), décrivant un argument (ou dans certains cas des arguments) que la fonction accepte. Il existe cinq sortes de paramètres :

positional-or-keyword : l’argument peut être passé soit par sa position, soit en tant que argument nommé. C’est le type de paramètre par défaut. Par exemple, foo et bar dans l’exemple suivant :

def func(foo, bar=None): ...

positional-only: l’argument ne peut être donné que par sa position. Python n’a pas de syntaxe pour déclarer de tels paramètres, cependant des fonctions natives, comme abs(), en utilisent.

keyword-only : l’argument ne peut être fourni que nommé. Les paramètres keyword-only peuvent être définis en utilisant un seul paramètre var-positional, ou en ajoutant une étoile (*) seule dans la liste des paramètres avant eux. Par exemple, kw_only1 et kw_only2 dans le code suivant :

def func(arg, *, kw_only1, kw_only2): ...

var-positional : une séquence d’arguments positionnels peut être fournie (en plus de tous les arguments positionnels déjà acceptés par d’autres paramètres). Un tel paramètre peut être défini en préfixant son nom par une *. Par exemple args ci-après :

def func(*args, **kwargs): ...

var-keyword : une quantité arbitraire d’arguments peut être passée, chacun étant nommé (en plus de tous les arguments nommés déjà acceptés par d’autres paramètres). Un tel paramètre est défini en préfixant le nom du paramètre par **. Par exemple, kwargs ci-dessus.

Les paramètres peuvent spécifier des arguments obligatoires ou optionnels, ainsi que des valeurs par défaut pour les arguments optionnels.

Voir aussi argument dans le glossaire, la question sur la différence entre les arguments et les paramètres dans la FAQ, la classe inspect.Parameter, la section Définition de fonctions et la PEP 362 [https://www.python.org/dev/peps/pep-0362].

entrée de chemin

Emplacement dans le chemin des importations (import path en anglais, d’où le path) que le chercheur basé sur les chemins consulte pour trouver des modules à importer.

chercheur de chemins

chercheur renvoyé par un appelable sur un sys.path_hooks (c’est-à-dire un point d’entrée pour la recherche dans path) qui sait où trouver des modules lorsqu’on lui donne une entrée de path.

Voir importlib.abc.PathEntryFinder pour les méthodes qu’un chercheur d’entrée dans path doit implémenter.

point d’entrée pour la recherche dans path

Appelable dans la liste sys.path_hook qui donne un chercheur d’entrée dans path s’il sait où trouver des modules pour une entrée dans path donnée.

chercheur basé sur les chemins

L’un des chercheurs dans les méta-chemins par défaut qui cherche des modules dans un chemin des importations.

objet simili-chemin

Objet représentant un chemin du système de fichiers. Un objet simili-chemin est un objet str ou un objet bytes représentant un chemin ou un objet implémentant le protocole os.PathLike. Un objet qui accepte le protocole os.PathLike peut être converti en un chemin str ou bytes du système de fichiers en appelant la fonction os.fspath(). os.fsdecode() et os.fsencode() peuvent être utilisées, respectivement, pour garantir un résultat de type str ou bytes à la place. A été Introduit par la PEP 519 [https://www.python.org/dev/peps/pep-0519].

PEP

Python Enhancement Proposal (Proposition d’amélioration Python). Un PEP est un document de conception fournissant des informations à la communauté Python ou décrivant une nouvelle fonctionnalité pour Python, ses processus ou son environnement. Les PEP doivent fournir une spécification technique concise et une justification des fonctionnalités proposées.

Les PEPs sont censés être les principaux mécanismes pour proposer de nouvelles fonctionnalités majeures, pour recueillir les commentaires de la communauté sur une question et pour documenter les décisions de conception qui sont intégrées en Python. L’auteur du PEP est responsable de l’établissement d’un consensus au sein de la communauté et de documenter les opinions contradictoires.

Voir PEP 1 [https://www.python.org/dev/peps/pep-0001].

portion

Jeu de fichiers dans un seul dossier (pouvant être stocké sous forme de fichier zip) qui contribue à l’espace de nommage d’un paquet, tel que défini dans la PEP 420 [https://www.python.org/dev/peps/pep-0420].

argument positionnel

Voir argument.

API provisoire

Une API provisoire est une API qui n’offre aucune garantie de rétrocompatibilité (la bibliothèque standard exige la rétrocompatibilité). Bien que des changements majeurs d’une telle interface ne soient pas attendus, tant qu’elle est étiquetée provisoire, des changements cassant la rétrocompatibilité (y compris sa suppression complète) peuvent survenir si les développeurs principaux le jugent nécessaire. Ces modifications ne surviendront que si de sérieux problèmes sont découverts et qu’ils n’avaient pas été identifiés avant l’ajout de l’API.

Même pour les API provisoires, les changements cassant la rétrocompatibilité sont considérés comme des « solutions de dernier recours ». Tout ce qui est possible sera fait pour tenter de résoudre les problèmes en conservant la rétrocompatibilité.

Ce processus permet à la bibliothèque standard de continuer à évoluer avec le temps, sans se bloquer longtemps sur des erreurs d’architecture. Voir la PEP 411 [https://www.python.org/dev/peps/pep-0411] pour plus de détails.

paquet provisoire

Voir provisional API.

Python 3000

Surnom donné à la série des Python 3.x (très vieux surnom donné à l’époque où Python 3 représentait un futur lointain). Aussi abrégé Py3k.

Pythonique

Idée, ou bout de code, qui colle aux idiomes de Python plutôt qu’aux concepts communs rencontrés dans d’autres langages. Par exemple, il est idiomatique en Python de parcourir les éléments d’un itérable en utilisant for. Beaucoup d’autres langages n’ont pas cette possibilité, donc les gens qui ne sont pas habitués à Python utilisent parfois un compteur numérique à la place :

for i in range(len(food)):
    print(food[i])

Plutôt qu’utiliser la méthode, plus propre et élégante, donc Pythonique :

for piece in food:
    print(piece)

nom qualifié

Nom, comprenant des points, montrant le « chemin » de l’espace de nommage global d’un module vers une classe, fonction ou méthode définie dans ce module, tel que défini dans la PEP 3155 [https://www.python.org/dev/peps/pep-3155]. Pour les fonctions et classes de premier niveau, le nom qualifié est le même que le nom de l’objet :

>>> class C:
...     class D:
...         def meth(self):
...             pass
...
>>> C.__qualname__
'C'
>>> C.D.__qualname__
'C.D'
>>> C.D.meth.__qualname__
'C.D.meth'

Lorsqu’il est utilisé pour nommer des modules, le nom qualifié complet (fully qualified name - FQN en anglais) signifie le chemin complet (séparé par des points) vers le module, incluant tous les paquets parents. Par exemple : email.mime.text :

>>> import email.mime.text
>>> email.mime.text.__name__
'email.mime.text'

nombre de références

Nombre de références à un objet. Lorsque le nombre de références à un objet descend à zéro, l’objet est désalloué. Le comptage de référence n’est généralement pas visible dans le code Python, mais c’est un élément clé de l’implémentation CPython. Le module sys définit une fonction getrefcount() que les développeurs peuvent utiliser pour obtenir le nombre de références à un objet donné.

paquet classique

paquet traditionnel, tel qu’un dossier contenant un fichier __init__.py.

Voir aussi paquet-espace de nommage.

__slots__

Déclaration dans une classe qui économise de la mémoire en pré-allouant de l’espace pour les attributs des instances et qui élimine le dictionnaire (des attributs) des instances. Bien que populaire, cette technique est difficile à maîtriser et devrait être réservée à de rares cas où un grand nombre d’instances dans une application devient un sujet critique pour la mémoire.

séquence

itérable qui offre un accès efficace à ses éléments par un indice sous forme de nombre entier via la méthode spéciale __getitem__() et qui définit une méthode __len__() donnant sa taille. Voici quelques séquences natives : list, str, tuple, et bytes. Notez que dict possède aussi une méthode __getitem__() et une méthode __len__(), mais il est considéré comme un mapping plutôt qu’une séquence, car ses accès se font par une clé arbitraire immuable plutôt qu’un nombre entier.

La classe abstraite de base collections.abc.Sequence définit une interface plus riche qui va au-delà des simples __getitem__() et __len__(), en ajoutant count(), index(), __contains__() et __reversed__(). Les types qui implémentent cette interface étendue peuvent s’enregistrer explicitement en utilisant register().

distribution simple

Forme de distribution, comme les fonction génériques, où l’implémentation est choisie en fonction du type d’un seul argument.

tranche

(slice en anglais), un objet contenant habituellement une portion de séquence. Une tranche est créée en utilisant la notation [] avec des : entre les nombres lorsque plusieurs sont fournis, comme dans variable_name[1:3:5]. Cette notation utilise des objets slice en interne.

méthode spéciale

(special method en anglais) Méthode appelée implicitement par Python pour exécuter une opération sur un type, comme une addition. De telles méthodes ont des noms commençant et terminant par des doubles tirets bas. Les méthodes spéciales sont documentées dans Méthodes spéciales.

instruction

Une instruction (statement en anglais) est un composant d’un « bloc » de code. Une instruction est soit une expression, soit une ou plusieurs constructions basées sur un mot-clé, comme if, while ou for.

struct sequence

A tuple with named elements. Struct sequences expose an interface similar to named tuple in that elements can be accessed either by index or as an attribute. However, they do not have any of the named tuple methods like _make() or _asdict(). Examples of struct sequences include sys.float_info and the return value of os.stat().

encodage de texte

Codec (codeur-décodeur) qui convertit des chaînes de caractères Unicode en octets (classe bytes).

fichier texte

file object capable de lire et d’écrire des objets str. Souvent, un fichier texte (text file en anglais) accède en fait à un flux de donnée en octets et gère l”text encoding automatiquement. Des exemples de fichiers textes sont les fichiers ouverts en mode texte ('r' ou 'w'), sys.stdin, sys.stdout et les instances de io.StringIO.

Voir aussi binary file pour un objet fichier capable de lire et d’écrire bytes-like objects.

chaîne entre triple guillemets

Chaîne qui est délimitée par trois guillemets simples (') ou trois guillemets doubles ("). Bien qu’elle ne fournisse aucune fonctionnalité qui ne soit pas disponible avec une chaîne entre guillemets, elle est utile pour de nombreuses raisons. Elle vous autorise à insérer des guillemets simples et doubles dans une chaîne sans avoir à les protéger et elle peut s’étendre sur plusieurs lignes sans avoir à terminer chaque ligne par un \. Elle est ainsi particulièrement utile pour les chaînes de documentation (docstrings).

type

Le type d’un objet Python détermine quel genre d’objet c’est. Tous les objets ont un type. Le type d’un objet peut être obtenu via son attribut __class__ ou via type(obj).

alias de type

Synonyme d’un type, créé en affectant le type à un identifiant.

Les alias de types sont utiles pour simplifier les indications de types. Par exemple :

from typing import List, Tuple

def remove_gray_shades(
        colors: List[Tuple[int, int, int]]) -> List[Tuple[int, int, int]]:
    pass

pourrait être rendu plus lisible comme ceci :

from typing import List, Tuple

Color = Tuple[int, int, int]

def remove_gray_shades(colors: List[Color]) -> List[Color]:
    pass

Voir typing et PEP 484 [https://www.python.org/dev/peps/pep-0484], qui décrivent cette fonctionnalité.

indication de type

Le annotation qui spécifie le type attendu pour une variable, un attribut de classe, un paramètre de fonction ou une valeur de retour.

Les indications de type sont facultatives et ne sont pas indispensables à l’interpréteur Python, mais elles sont utiles aux outils d’analyse de type statique et aident les IDE à compléter et à réusiner (code refactoring en anglais) le code.

Les indicateurs de type de variables globales, d’attributs de classe et de fonctions, mais pas de variables locales, peuvent être consultés en utilisant typing.get_type_hints().

Voir typing et PEP 484 [https://www.python.org/dev/peps/pep-0484], qui décrivent cette fonctionnalité.

retours à la ligne universels

Une manière d’interpréter des flux de texte dans lesquels sont reconnues toutes les fins de ligne suivantes : la convention Unix '\n', la convention Windows '\r\n' et l’ancienne convention Macintosh '\r'. Voir la PEP 278 [https://www.python.org/dev/peps/pep-0278] et la PEP 3116 [https://www.python.org/dev/peps/pep-3116], ainsi que la fonction bytes.splitlines() pour d’autres usages.

annotation de variable

annotation d’une variable ou d’un attribut de classe.

Lorsque vous annotez une variable ou un attribut de classe, l’affectation est facultative :

class C:
    field: 'annotation'

Les annotations de variables sont généralement utilisées pour des indications de types : par exemple, cette variable devrait prendre des valeurs de type int :

count: int = 0

La syntaxe d’annotation de la variable est expliquée dans la section Les assignations annotées.

Reportez-vous à function annotation, à la PEP 484 [https://www.python.org/dev/peps/pep-0484] et à la PEP 526 [https://www.python.org/dev/peps/pep-0526] qui décrivent cette fonctionnalité.

environnement virtuel

Environnement d’exécution isolé (en mode coopératif) qui permet aux utilisateurs de Python et aux applications d’installer et de mettre à jour des paquets sans interférer avec d’autres applications Python fonctionnant sur le même système.

Voir aussi venv.

machine virtuelle

Ordinateur défini entièrement par du logiciel. La machine virtuelle (virtual machine) de Python exécute le bytecode produit par le compilateur de bytecode.

Le zen de Python

Liste de principes et de préceptes utiles pour comprendre et utiliser le langage. Cette liste peut être obtenue en tapant « import this » dans une invite Python interactive.

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À propos de ces documents

Ces documents sont générés à partir de sources en reStructuredText [http://docutils.sourceforge.net/rst.html] par Sphinx [http://sphinx-doc.org/], un analyseur de documents spécialement conçu pour la documentation Python.

Le développement de la documentation et de ses outils est entièrement basé sur le volontariat, tout comme Python. Si vous voulez contribuer, allez voir la page S’attaquer aux bogues qui contient des informations pour vous y aider. Les nouveaux volontaires sont toujours les bienvenus !

Merci beaucoup à :

Fred L. Drake, Jr., créateur des outils originaux de la documentation Python et rédacteur de la plupart de son contenu ;

le projet Docutils [http://docutils.sourceforge.net/] pour avoir créé reStructuredText et la suite d’outils Docutils ;

Fredrik Lundh pour son projet Alternative Python Reference [http://effbot.org/zone/pyref.htm], dont Sphinx a pris beaucoup de bonnes idées.

Contributeurs de la documentation Python

De nombreuses personnes ont contribué au langage Python, à sa bibliothèque standard et à sa documentation. Consultez Misc/ACKS [https://github.com/python/cpython/tree/3.6/Misc/ACKS] dans les sources de la distribution Python pour avoir une liste partielle des contributeurs.

Ce n’est que grâce aux suggestions et contributions de la communauté Python que Python a une documentation si merveilleuse — Merci !

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S’attaquer aux bogues

Python est un langage de programmation robuste réputé pour sa stabilité. Afin de maintenir cette réputation, les développeurs souhaitent connaître tout problème que vous pourriez rencontrer dans Python.

Il est parfois plus rapide de réparer les bogues soi-même et d’en proposer les correctifs, ça simplifie le processus et implique moins de monde. Apprenez à contribuer.

Bogues de documentation

Si vous trouvez un bogue dans cette documentation ou si vous désirez proposer une amélioration, si cela concerne aussi la documentation en anglais, ouvrez un rapport sur le tracker décrivant en anglais le bogue et où vous l’avez trouvé. Si le problème ne touche que la traduction en français, ouvrez un ticket sur https://github.com/python/python-docs-fr/issues, ou venez nous en toucher un mot sur le canal #python-fr sur freenode (https://webchat.freenode.net/). Si vous avez une suggestion de correction, merci de l’inclure également.

Si vous êtes limité par le temps, vous pouvez aussi envoyer un courriel à docs@python.org (les bogues de comportement peuvent être envoyés à python-list@python.org). « docs@ » est une liste de diffusion gérée par des volontaires, votre requête sera vue, mais elle peut prendre un moment pour être traitée.

Voir aussi

Documentation bugs [https://bugs.python.org/issue?@filter=status&@filter=components&components=4&status=1&@columns=id,activity,title,status&@sort=-activity] sur le gestionnaire de ticket de Python

Utilisation du gestionnaire de tickets Python

Les rapports de bogues pour Python lui-même devraient être soumis via le Bug Tracker Python (http://bugs.python.org/). Le gestionnaire de tickets propose un formulaire Web permettant de saisir des informations pertinentes à soumettre aux développeurs.

La première étape pour remplir un rapport est de déterminer si le problème a déjà été rapporté. L’avantage de cette approche, en plus d’économiser du temps aux développeurs, est d’apprendre ce qui a été fait pour le résoudre ; il se peut que le problème soit déjà résolu dans la prochaine version, ou que des informations complémentaires soient attendues (auquel cas votre contribution est la bienvenue !). Pour ce faire, cherchez dans la base de données de bogues grâce à la boîte de recherche en haut de la page.

Si le problème que vous soumettez n’est pas déjà dans le bug tracker, revenez au Python Bug Tracker et connectez-vous. Si vous n’avez pas déjà un compte pour le tracker, cliquez sur le lien « S’enregistrer », ou, si vous utilisez OpenID, sur l’un des logos des fournisseurs OpenID dans la barre latérale. Il n’est pas possible de soumettre un rapport de bogue de manière anonyme.

Une fois identifié, pour pouvez rapporter un bogue. Sélectionnez le lien Create New dans la barre latérale pour ouvrir un nouveau formulaire de rapport de bogue.

Le formulaire de soumission a un certain nombre de champs. Pour le champ « Titre », saisissez une très courte description du problème ; moins de dix mots est approprié. Dans le champ « Type », sélectionnez le type de problème ; sélectionnez aussi « Composant » et « Versions » en rapport avec le bogue.

Dans le champ « Commentaire », décrivez le problème de manière détaillée, incluant ce à quoi vous vous attendiez et ce qui s’est vraiment produit. Assurez-vous d’y inclure les éventuels modules d’extensions impliqués et la plateforme matérielle et logicielle vous utilisiez (en incluant les informations de versions).

Chaque bogue sera attribué à un développeur qui déterminera ce qui est nécessaire d’entreprendre pour corriger le problème. Vous recevrez une notification à chaque action effectuée sur le bogue.

Voir aussi

Comment rédiger des bugs de manière efficiente [http://www.chiark.greenend.org.uk/~sgtatham/bugs.html]

Article qui entre dans les détails sur la manière de créer un rapport de bogue utile. Il décrit quel genre d’information est utile et pourquoi elle est utile.

Guide de la rédaction de bugs [https://developer.mozilla.org/en-US/docs/Mozilla/QA/Bug_writing_guidelines]

Conseils pour écrire un bon rapport de bogue. Certains sont spécifiques au projet Mozilla mais présentent des bonnes pratiques générales.

Commencer à contribuer à Python vous-même

Au-delà de simplement remonter les bogues que vous trouvez, il est aussi apprécié d’y attacher des correctifs. Vous pouvez trouver plus d’informations pour débuter la rédaction de correctifs dans le Python Developer’s Guide [https://devguide.python.org/]. Si vous avez des questions, le core-mentorship mailing list [https://mail.python.org/mailman/listinfo/core-mentorship/] est un endroit amical pour obtenir des réponses à toutes les questions à propos du processus de corrections de bugs dans Python.

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Copyright

Python et cette documentation sont :

Copyright © 2001-2020 Python Software Foundation. All rights reserved.

Copyright © 2000 BeOpen.com. Tous droits réservés.

Copyright © 1995-2000 Corporation for National Research Initiatives. Tous droits réservés.

Copyright © 1991-1995 Stichting Mathematisch Centrum. Tous droits réservés.

Voir Histoire et licence pour des informations complètes concernant la licence et les permissions.

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Histoire et licence

Histoire du logiciel

Python a été créé au début des années 1990 par Guido van Rossum, au Stichting Mathematisch Centrum (CWI, voir https://www.cwi.nl/) au Pays-Bas en tant que successeur d’un langage appelé ABC. Guido est l’auteur principal de Python, bien qu’il inclut de nombreuses contributions de la part d’autres personnes.

En 1995, Guido continua son travail sur Python au Corporation for National Research Initiatives (CNRI, voir https://www.cnri.reston.va.us/) de Reston, en Viriginie, d’où il diffusa plusieurs versions du logiciel.

In May 2000, Guido and the Python core development team moved to BeOpen.com to form the BeOpen PythonLabs team. In October of the same year, the PythonLabs team moved to Digital Creations (now Zope Corporation; see https://www.zope.org/). In 2001, the Python Software Foundation (PSF, see https://www.python.org/psf/) was formed, a non-profit organization created specifically to own Python-related Intellectual Property. Zope Corporation is a sponsoring member of the PSF.

Toutes les versions de Python sont Open Source (voir https://www.opensource.org/ pour la définition d’Open Source). Historiquement, la plupart, mais pas toutes, des versions de Python ont également été compatible avec la GPL, le tableau ci-dessous résume les différentes versions.

Version

Dérivé de

Année

Propriétaire

Compatible avec la GPL ?

0.9.0 à 1.2

n/a

1991-1995

CWI

oui

1.3 à 1.5.2

1.2

1995-1999

CNRI

oui

1.6

1.5.2

2000

CNRI

non

2.0

1.6

2000

BeOpen.com

non

1.6.1

1.6

2001

CNRI

non

2.1

2.0+1.6.1

2001

PSF

non

2.0.1

2.0+1.6.1

2001

PSF

oui

2.1.1

2.1+2.0.1

2001

PSF

oui

2.1.2

2.1.1

2002

PSF

oui

2.1.3

2.1.2

2002

PSF

oui

2.2 et ultérieure

2.1.1

2001-maintenant

PSF

oui

Note

Compatible GPL ne signifie pas que nous distribuons Python sous licence GPL. Toutes les licences Python, excepté la licence GPL, vous permettent la distribution d’une version modifiée sans rendre open source ces changements. La licence « compatible GPL » rend possible la diffusion de Python avec un autre logiciel qui est lui, diffusé sous la licence GPL ; les licences « non-compatibles GPL » ne le peuvent pas.

Merci aux nombreux bénévoles qui ont travaillé sous la direction de Guido pour rendre ces versions possibles.

Conditions générales pour accéder à, ou utiliser, Python

PSF LICENSE AGREEMENT FOR PYTHON 3.6.11

1. This LICENSE AGREEMENT is between the Python Software Foundation ("PSF"), and
   the Individual or Organization ("Licensee") accessing and otherwise using Python
   3.6.11 software in source or binary form and its associated documentation.

2. Subject to the terms and conditions of this License Agreement, PSF hereby
   grants Licensee a nonexclusive, royalty-free, world-wide license to reproduce,
   analyze, test, perform and/or display publicly, prepare derivative works,
   distribute, and otherwise use Python 3.6.11 alone or in any derivative
   version, provided, however, that PSF's License Agreement and PSF's notice of
   copyright, i.e., "Copyright © 2001-2020 Python Software Foundation; All Rights
   Reserved" are retained in Python 3.6.11 alone or in any derivative version
   prepared by Licensee.

3. In the event Licensee prepares a derivative work that is based on or
   incorporates Python 3.6.11 or any part thereof, and wants to make the
   derivative work available to others as provided herein, then Licensee hereby
   agrees to include in any such work a brief summary of the changes made to Python
   3.6.11.

4. PSF is making Python 3.6.11 available to Licensee on an "AS IS" basis.
   PSF MAKES NO REPRESENTATIONS OR WARRANTIES, EXPRESS OR IMPLIED.  BY WAY OF
   EXAMPLE, BUT NOT LIMITATION, PSF MAKES NO AND DISCLAIMS ANY REPRESENTATION OR
   WARRANTY OF MERCHANTABILITY OR FITNESS FOR ANY PARTICULAR PURPOSE OR THAT THE
   USE OF PYTHON 3.6.11 WILL NOT INFRINGE ANY THIRD PARTY RIGHTS.

5. PSF SHALL NOT BE LIABLE TO LICENSEE OR ANY OTHER USERS OF PYTHON 3.6.11
   FOR ANY INCIDENTAL, SPECIAL, OR CONSEQUENTIAL DAMAGES OR LOSS AS A RESULT OF
   MODIFYING, DISTRIBUTING, OR OTHERWISE USING PYTHON 3.6.11, OR ANY DERIVATIVE
   THEREOF, EVEN IF ADVISED OF THE POSSIBILITY THEREOF.

6. This License Agreement will automatically terminate upon a material breach of
   its terms and conditions.

7. Nothing in this License Agreement shall be deemed to create any relationship
   of agency, partnership, or joint venture between PSF and Licensee.  This License
   Agreement does not grant permission to use PSF trademarks or trade name in a
   trademark sense to endorse or promote products or services of Licensee, or any
   third party.

8. By copying, installing or otherwise using Python 3.6.11, Licensee agrees
   to be bound by the terms and conditions of this License Agreement.

LICENCE D’UTILISATION BEOPEN.COM POUR PYTHON 2.0

LICENCE D’UTILISATION LIBRE BEOPEN PYTHON VERSION 1

1. This LICENSE AGREEMENT is between BeOpen.com ("BeOpen"), having an office at
   160 Saratoga Avenue, Santa Clara, CA 95051, and the Individual or Organization
   ("Licensee") accessing and otherwise using this software in source or binary
   form and its associated documentation ("the Software").

2. Subject to the terms and conditions of this BeOpen Python License Agreement,
   BeOpen hereby grants Licensee a non-exclusive, royalty-free, world-wide license
   to reproduce, analyze, test, perform and/or display publicly, prepare derivative
   works, distribute, and otherwise use the Software alone or in any derivative
   version, provided, however, that the BeOpen Python License is retained in the
   Software, alone or in any derivative version prepared by Licensee.

3. BeOpen is making the Software available to Licensee on an "AS IS" basis.
   BEOPEN MAKES NO REPRESENTATIONS OR WARRANTIES, EXPRESS OR IMPLIED.  BY WAY OF
   EXAMPLE, BUT NOT LIMITATION, BEOPEN MAKES NO AND DISCLAIMS ANY REPRESENTATION OR
   WARRANTY OF MERCHANTABILITY OR FITNESS FOR ANY PARTICULAR PURPOSE OR THAT THE
   USE OF THE SOFTWARE WILL NOT INFRINGE ANY THIRD PARTY RIGHTS.

4. BEOPEN SHALL NOT BE LIABLE TO LICENSEE OR ANY OTHER USERS OF THE SOFTWARE FOR
   ANY INCIDENTAL, SPECIAL, OR CONSEQUENTIAL DAMAGES OR LOSS AS A RESULT OF USING,
   MODIFYING OR DISTRIBUTING THE SOFTWARE, OR ANY DERIVATIVE THEREOF, EVEN IF
   ADVISED OF THE POSSIBILITY THEREOF.

5. This License Agreement will automatically terminate upon a material breach of
   its terms and conditions.

6. This License Agreement shall be governed by and interpreted in all respects
   by the law of the State of California, excluding conflict of law provisions.
   Nothing in this License Agreement shall be deemed to create any relationship of
   agency, partnership, or joint venture between BeOpen and Licensee.  This License
   Agreement does not grant permission to use BeOpen trademarks or trade names in a
   trademark sense to endorse or promote products or services of Licensee, or any
   third party.  As an exception, the "BeOpen Python" logos available at
   http://www.pythonlabs.com/logos.html may be used according to the permissions
   granted on that web page.

7. By copying, installing or otherwise using the software, Licensee agrees to be
   bound by the terms and conditions of this License Agreement.

LICENCE D’UTILISATION CNRI POUR PYTHON 1.6.1

1. This LICENSE AGREEMENT is between the Corporation for National Research
   Initiatives, having an office at 1895 Preston White Drive, Reston, VA 20191
   ("CNRI"), and the Individual or Organization ("Licensee") accessing and
   otherwise using Python 1.6.1 software in source or binary form and its
   associated documentation.

2. Subject to the terms and conditions of this License Agreement, CNRI hereby
   grants Licensee a nonexclusive, royalty-free, world-wide license to reproduce,
   analyze, test, perform and/or display publicly, prepare derivative works,
   distribute, and otherwise use Python 1.6.1 alone or in any derivative version,
   provided, however, that CNRI's License Agreement and CNRI's notice of copyright,
   i.e., "Copyright © 1995-2001 Corporation for National Research Initiatives; All
   Rights Reserved" are retained in Python 1.6.1 alone or in any derivative version
   prepared by Licensee.  Alternately, in lieu of CNRI's License Agreement,
   Licensee may substitute the following text (omitting the quotes): "Python 1.6.1
   is made available subject to the terms and conditions in CNRI's License
   Agreement.  This Agreement together with Python 1.6.1 may be located on the
   Internet using the following unique, persistent identifier (known as a handle):
   1895.22/1013.  This Agreement may also be obtained from a proxy server on the
   Internet using the following URL: http://hdl.handle.net/1895.22/1013."

3. In the event Licensee prepares a derivative work that is based on or
   incorporates Python 1.6.1 or any part thereof, and wants to make the derivative
   work available to others as provided herein, then Licensee hereby agrees to
   include in any such work a brief summary of the changes made to Python 1.6.1.

4. CNRI is making Python 1.6.1 available to Licensee on an "AS IS" basis.  CNRI
   MAKES NO REPRESENTATIONS OR WARRANTIES, EXPRESS OR IMPLIED.  BY WAY OF EXAMPLE,
   BUT NOT LIMITATION, CNRI MAKES NO AND DISCLAIMS ANY REPRESENTATION OR WARRANTY
   OF MERCHANTABILITY OR FITNESS FOR ANY PARTICULAR PURPOSE OR THAT THE USE OF
   PYTHON 1.6.1 WILL NOT INFRINGE ANY THIRD PARTY RIGHTS.

5. CNRI SHALL NOT BE LIABLE TO LICENSEE OR ANY OTHER USERS OF PYTHON 1.6.1 FOR
   ANY INCIDENTAL, SPECIAL, OR CONSEQUENTIAL DAMAGES OR LOSS AS A RESULT OF
   MODIFYING, DISTRIBUTING, OR OTHERWISE USING PYTHON 1.6.1, OR ANY DERIVATIVE
   THEREOF, EVEN IF ADVISED OF THE POSSIBILITY THEREOF.

6. This License Agreement will automatically terminate upon a material breach of
   its terms and conditions.

7. This License Agreement shall be governed by the federal intellectual property
   law of the United States, including without limitation the federal copyright
   law, and, to the extent such U.S. federal law does not apply, by the law of the
   Commonwealth of Virginia, excluding Virginia's conflict of law provisions.
   Notwithstanding the foregoing, with regard to derivative works based on Python
   1.6.1 that incorporate non-separable material that was previously distributed
   under the GNU General Public License (GPL), the law of the Commonwealth of
   Virginia shall govern this License Agreement only as to issues arising under or
   with respect to Paragraphs 4, 5, and 7 of this License Agreement.  Nothing in
   this License Agreement shall be deemed to create any relationship of agency,
   partnership, or joint venture between CNRI and Licensee.  This License Agreement
   does not grant permission to use CNRI trademarks or trade name in a trademark
   sense to endorse or promote products or services of Licensee, or any third
   party.

8. By clicking on the "ACCEPT" button where indicated, or by copying, installing
   or otherwise using Python 1.6.1, Licensee agrees to be bound by the terms and
   conditions of this License Agreement.

LICENCE D’UTILISATION CWI POUR PYTHON 0.9.0 à 1.2

Copyright © 1991 - 1995, Stichting Mathematisch Centrum Amsterdam, The
Netherlands.  All rights reserved.

Permission to use, copy, modify, and distribute this software and its
documentation for any purpose and without fee is hereby granted, provided that
the above copyright notice appear in all copies and that both that copyright
notice and this permission notice appear in supporting documentation, and that
the name of Stichting Mathematisch Centrum or CWI not be used in advertising or
publicity pertaining to distribution of the software without specific, written
prior permission.

STICHTING MATHEMATISCH CENTRUM DISCLAIMS ALL WARRANTIES WITH REGARD TO THIS
SOFTWARE, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS, IN NO
EVENT SHALL STICHTING MATHEMATISCH CENTRUM BE LIABLE FOR ANY SPECIAL, INDIRECT
OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE,
DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS
SOFTWARE.

Licences et remerciements pour les logiciels tiers

Cette section est une liste incomplète mais grandissante de licences et remerciements pour les logiciels tiers incorporés dans la distribution de Python.

Mersenne twister

Le module _random inclut du code construit à partir d’un téléchargement depuis http://www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/MT2002/emt19937ar.html. Voici mot pour mot les commentaires du code original :

A C-program for MT19937, with initialization improved 2002/1/26.
Coded by Takuji Nishimura and Makoto Matsumoto.

Before using, initialize the state by using init_genrand(seed)
or init_by_array(init_key, key_length).

Copyright (C) 1997 - 2002, Makoto Matsumoto and Takuji Nishimura,
All rights reserved.

Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions
are met:

 1. Redistributions of source code must retain the above copyright
    notice, this list of conditions and the following disclaimer.

 2. Redistributions in binary form must reproduce the above copyright
    notice, this list of conditions and the following disclaimer in the
    documentation and/or other materials provided with the distribution.

 3. The names of its contributors may not be used to endorse or promote
    products derived from this software without specific prior written
    permission.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
A PARTICULAR PURPOSE ARE DISCLAIMED.  IN NO EVENT SHALL THE COPYRIGHT OWNER OR
CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

Any feedback is very welcome.
http://www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/emt.html
email: m-mat @ math.sci.hiroshima-u.ac.jp (remove space)

Interfaces de connexion (sockets)

Le module socket utilise les fonctions getaddrinfo() et getnameinfo() codées dans des fichiers source séparés et provenant du projet WIDE: http://www.wide.ad.jp/.

Copyright (C) 1995, 1996, 1997, and 1998 WIDE Project.
All rights reserved.

Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions
are met:
1. Redistributions of source code must retain the above copyright
   notice, this list of conditions and the following disclaimer.
2. Redistributions in binary form must reproduce the above copyright
   notice, this list of conditions and the following disclaimer in the
   documentation and/or other materials provided with the distribution.
3. Neither the name of the project nor the names of its contributors
   may be used to endorse or promote products derived from this software
   without specific prior written permission.

THIS SOFTWARE IS PROVIDED BY THE PROJECT AND CONTRIBUTORS ``AS IS'' AND
ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
ARE DISCLAIMED.  IN NO EVENT SHALL THE PROJECT OR CONTRIBUTORS BE LIABLE
FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS
OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION)
HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY
OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF
SUCH DAMAGE.

Virgule flottante et contrôle d’exception

Le code source pour le module fpectl inclut la note suivante :

  ---------------------------------------------------------------------
 /                       Copyright (c) 1996.                           \
|          The Regents of the University of California.                 |
|                        All rights reserved.                           |
|                                                                       |
|   Permission to use, copy, modify, and distribute this software for   |
|   any purpose without fee is hereby granted, provided that this en-   |
|   tire notice is included in all copies of any software which is or   |
|   includes  a  copy  or  modification  of  this software and in all   |
|   copies of the supporting documentation for such software.           |
|                                                                       |
|   This  work was produced at the University of California, Lawrence   |
|   Livermore National Laboratory under  contract  no.  W-7405-ENG-48   |
|   between  the  U.S.  Department  of  Energy and The Regents of the   |
|   University of California for the operation of UC LLNL.              |
|                                                                       |
|                              DISCLAIMER                               |
|                                                                       |
|   This  software was prepared as an account of work sponsored by an   |
|   agency of the United States Government. Neither the United States   |
|   Government  nor the University of California nor any of their em-   |
|   ployees, makes any warranty, express or implied, or  assumes  any   |
|   liability  or  responsibility  for the accuracy, completeness, or   |
|   usefulness of any information,  apparatus,  product,  or  process   |
|   disclosed,   or  represents  that  its  use  would  not  infringe   |
|   privately-owned rights. Reference herein to any specific  commer-   |
|   cial  products,  process,  or  service  by trade name, trademark,   |
|   manufacturer, or otherwise, does not  necessarily  constitute  or   |
|   imply  its endorsement, recommendation, or favoring by the United   |
|   States Government or the University of California. The views  and   |
|   opinions  of authors expressed herein do not necessarily state or   |
|   reflect those of the United States Government or  the  University   |
|   of  California,  and shall not be used for advertising or product   |
 \  endorsement purposes.                                              /
  ---------------------------------------------------------------------

Interfaces de connexion asynchrones

Les modules asynchat et asyncore contiennent la note suivante :

Copyright 1996 by Sam Rushing

                        All Rights Reserved

Permission to use, copy, modify, and distribute this software and
its documentation for any purpose and without fee is hereby
granted, provided that the above copyright notice appear in all
copies and that both that copyright notice and this permission
notice appear in supporting documentation, and that the name of Sam
Rushing not be used in advertising or publicity pertaining to
distribution of the software without specific, written prior
permission.

SAM RUSHING DISCLAIMS ALL WARRANTIES WITH REGARD TO THIS SOFTWARE,
INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS, IN
NO EVENT SHALL SAM RUSHING BE LIABLE FOR ANY SPECIAL, INDIRECT OR
CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS
OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT,
NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT OF OR IN
CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE.

Gestion de témoin (cookie)

Le module http.cookies contient la note suivante :

Copyright 2000 by Timothy O'Malley <timo@alum.mit.edu>

               All Rights Reserved

Permission to use, copy, modify, and distribute this software
and its documentation for any purpose and without fee is hereby
granted, provided that the above copyright notice appear in all
copies and that both that copyright notice and this permission
notice appear in supporting documentation, and that the name of
Timothy O'Malley  not be used in advertising or publicity
pertaining to distribution of the software without specific, written
prior permission.

Timothy O'Malley DISCLAIMS ALL WARRANTIES WITH REGARD TO THIS
SOFTWARE, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY
AND FITNESS, IN NO EVENT SHALL Timothy O'Malley BE LIABLE FOR
ANY SPECIAL, INDIRECT OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES
WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR
PERFORMANCE OF THIS SOFTWARE.

Traçage d’exécution

Le module trace contient la note suivante :

portions copyright 2001, Autonomous Zones Industries, Inc., all rights...
err...  reserved and offered to the public under the terms of the
Python 2.2 license.
Author: Zooko O'Whielacronx
http://zooko.com/
mailto:zooko@zooko.com

Copyright 2000, Mojam Media, Inc., all rights reserved.
Author: Skip Montanaro

Copyright 1999, Bioreason, Inc., all rights reserved.
Author: Andrew Dalke

Copyright 1995-1997, Automatrix, Inc., all rights reserved.
Author: Skip Montanaro

Copyright 1991-1995, Stichting Mathematisch Centrum, all rights reserved.

Permission to use, copy, modify, and distribute this Python software and
its associated documentation for any purpose without fee is hereby
granted, provided that the above copyright notice appears in all copies,
and that both that copyright notice and this permission notice appear in
supporting documentation, and that the name of neither Automatrix,
Bioreason or Mojam Media be used in advertising or publicity pertaining to
distribution of the software without specific, written prior permission.

Les fonctions UUencode et UUdecode

Le module uu contient la note suivante :

Copyright 1994 by Lance Ellinghouse
Cathedral City, California Republic, United States of America.
                       All Rights Reserved
Permission to use, copy, modify, and distribute this software and its
documentation for any purpose and without fee is hereby granted,
provided that the above copyright notice appear in all copies and that
both that copyright notice and this permission notice appear in
supporting documentation, and that the name of Lance Ellinghouse
not be used in advertising or publicity pertaining to distribution
of the software without specific, written prior permission.
LANCE ELLINGHOUSE DISCLAIMS ALL WARRANTIES WITH REGARD TO
THIS SOFTWARE, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND
FITNESS, IN NO EVENT SHALL LANCE ELLINGHOUSE CENTRUM BE LIABLE
FOR ANY SPECIAL, INDIRECT OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES
WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN
ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT
OF OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE.

Modified by Jack Jansen, CWI, July 1995:
- Use binascii module to do the actual line-by-line conversion
  between ascii and binary. This results in a 1000-fold speedup. The C
  version is still 5 times faster, though.
- Arguments more compliant with Python standard

Appel de procédures distantes en XML (RPC, pour Remote Procedure Call)

Le module xmlrpc.client contient la note suivante :

    The XML-RPC client interface is

Copyright (c) 1999-2002 by Secret Labs AB
Copyright (c) 1999-2002 by Fredrik Lundh

By obtaining, using, and/or copying this software and/or its
associated documentation, you agree that you have read, understood,
and will comply with the following terms and conditions:

Permission to use, copy, modify, and distribute this software and
its associated documentation for any purpose and without fee is
hereby granted, provided that the above copyright notice appears in
all copies, and that both that copyright notice and this permission
notice appear in supporting documentation, and that the name of
Secret Labs AB or the author not be used in advertising or publicity
pertaining to distribution of the software without specific, written
prior permission.

SECRET LABS AB AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH REGARD
TO THIS SOFTWARE, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANT-
ABILITY AND FITNESS.  IN NO EVENT SHALL SECRET LABS AB OR THE AUTHOR
BE LIABLE FOR ANY SPECIAL, INDIRECT OR CONSEQUENTIAL DAMAGES OR ANY
DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
OF THIS SOFTWARE.

test_epoll

Le module test_epoll contient la note suivante :

Copyright (c) 2001-2006 Twisted Matrix Laboratories.

Permission is hereby granted, free of charge, to any person obtaining
a copy of this software and associated documentation files (the
"Software"), to deal in the Software without restriction, including
without limitation the rights to use, copy, modify, merge, publish,
distribute, sublicense, and/or sell copies of the Software, and to
permit persons to whom the Software is furnished to do so, subject to
the following conditions:

The above copyright notice and this permission notice shall be
included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE
LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION
OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION
WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

Select kqueue

Le module select contient la note suivante pour l’interface kqueue :

Copyright (c) 2000 Doug White, 2006 James Knight, 2007 Christian Heimes
All rights reserved.

Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions
are met:
1. Redistributions of source code must retain the above copyright
   notice, this list of conditions and the following disclaimer.
2. Redistributions in binary form must reproduce the above copyright
   notice, this list of conditions and the following disclaimer in the
   documentation and/or other materials provided with the distribution.

THIS SOFTWARE IS PROVIDED BY THE AUTHOR AND CONTRIBUTORS ``AS IS'' AND
ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
ARE DISCLAIMED.  IN NO EVENT SHALL THE AUTHOR OR CONTRIBUTORS BE LIABLE
FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS
OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION)
HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY
OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF
SUCH DAMAGE.

SipHash24

Le fichier Python/pyhash.c contiens une implémentation par Marek Majkowski de l’algorithme SipHash24 de Dan Bernstein. Il contient la note suivante :

<MIT License>
Copyright (c) 2013  Marek Majkowski <marek@popcount.org>

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in
all copies or substantial portions of the Software.
</MIT License>

Original location:
   https://github.com/majek/csiphash/

Solution inspired by code from:
   Samuel Neves (supercop/crypto_auth/siphash24/little)
   djb (supercop/crypto_auth/siphash24/little2)
   Jean-Philippe Aumasson (https://131002.net/siphash/siphash24.c)

strtod et dtoa

Le fichier Python/dtoa.c, qui fournit les fonctions dtoa et strtod pour la conversion de doubles C vers et depuis les chaînes, est tiré d’un fichier du même nom par David M. Gay, actuellement disponible sur http://www.netlib.org/fp/. Le fichier original, tel que récupéré le 16 mars 2009, contient la licence suivante :

/****************************************************************
 *
 * The author of this software is David M. Gay.
 *
 * Copyright (c) 1991, 2000, 2001 by Lucent Technologies.
 *
 * Permission to use, copy, modify, and distribute this software for any
 * purpose without fee is hereby granted, provided that this entire notice
 * is included in all copies of any software which is or includes a copy
 * or modification of this software and in all copies of the supporting
 * documentation for such software.
 *
 * THIS SOFTWARE IS BEING PROVIDED "AS IS", WITHOUT ANY EXPRESS OR IMPLIED
 * WARRANTY.  IN PARTICULAR, NEITHER THE AUTHOR NOR LUCENT MAKES ANY
 * REPRESENTATION OR WARRANTY OF ANY KIND CONCERNING THE MERCHANTABILITY
 * OF THIS SOFTWARE OR ITS FITNESS FOR ANY PARTICULAR PURPOSE.
 *
 ***************************************************************/

OpenSSL

Les modules hashlib, posix, ssl, et crypt utilisent la bibliothèque OpenSSL pour améliorer les performances, si elle est disponible via le système d’exploitation. Aussi les outils d’installation sur Windows et Mac OS X peuvent inclure une copie des bibliothèques d’OpenSSL, donc on colle une copie de la licence d’OpenSSL ici :

 LICENSE ISSUES
 ==============

 The OpenSSL toolkit stays under a dual license, i.e. both the conditions of
 the OpenSSL License and the original SSLeay license apply to the toolkit.
 See below for the actual license texts. Actually both licenses are BSD-style
 Open Source licenses. In case of any license issues related to OpenSSL
 please contact openssl-core@openssl.org.

 OpenSSL License
 ---------------

   /* ====================================================================
    * Copyright (c) 1998-2008 The OpenSSL Project.  All rights reserved.
    *
    * Redistribution and use in source and binary forms, with or without
    * modification, are permitted provided that the following conditions
    * are met:
    *
    * 1. Redistributions of source code must retain the above copyright
    *    notice, this list of conditions and the following disclaimer.
    *
    * 2. Redistributions in binary form must reproduce the above copyright
    *    notice, this list of conditions and the following disclaimer in
    *    the documentation and/or other materials provided with the
    *    distribution.
    *
    * 3. All advertising materials mentioning features or use of this
    *    software must display the following acknowledgment:
    *    "This product includes software developed by the OpenSSL Project
    *    for use in the OpenSSL Toolkit. (http://www.openssl.org/)"
    *
    * 4. The names "OpenSSL Toolkit" and "OpenSSL Project" must not be used to
    *    endorse or promote products derived from this software without
    *    prior written permission. For written permission, please contact
    *    openssl-core@openssl.org.
    *
    * 5. Products derived from this software may not be called "OpenSSL"
    *    nor may "OpenSSL" appear in their names without prior written
    *    permission of the OpenSSL Project.
    *
    * 6. Redistributions of any form whatsoever must retain the following
    *    acknowledgment:
    *    "This product includes software developed by the OpenSSL Project
    *    for use in the OpenSSL Toolkit (http://www.openssl.org/)"
    *
    * THIS SOFTWARE IS PROVIDED BY THE OpenSSL PROJECT ``AS IS'' AND ANY
    * EXPRESSED OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
    * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
    * PURPOSE ARE DISCLAIMED.  IN NO EVENT SHALL THE OpenSSL PROJECT OR
    * ITS CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
    * SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT
    * NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
    * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION)
    * HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT,
    * STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
    * ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED
    * OF THE POSSIBILITY OF SUCH DAMAGE.
    * ====================================================================
    *
    * This product includes cryptographic software written by Eric Young
    * (eay@cryptsoft.com).  This product includes software written by Tim
    * Hudson (tjh@cryptsoft.com).
    *
    */

Original SSLeay License
-----------------------

   /* Copyright (C) 1995-1998 Eric Young (eay@cryptsoft.com)
    * All rights reserved.
    *
    * This package is an SSL implementation written
    * by Eric Young (eay@cryptsoft.com).
    * The implementation was written so as to conform with Netscapes SSL.
    *
    * This library is free for commercial and non-commercial use as long as
    * the following conditions are aheared to.  The following conditions
    * apply to all code found in this distribution, be it the RC4, RSA,
    * lhash, DES, etc., code; not just the SSL code.  The SSL documentation
    * included with this distribution is covered by the same copyright terms
    * except that the holder is Tim Hudson (tjh@cryptsoft.com).
    *
    * Copyright remains Eric Young's, and as such any Copyright notices in
    * the code are not to be removed.
    * If this package is used in a product, Eric Young should be given attribution
    * as the author of the parts of the library used.
    * This can be in the form of a textual message at program startup or
    * in documentation (online or textual) provided with the package.
    *
    * Redistribution and use in source and binary forms, with or without
    * modification, are permitted provided that the following conditions
    * are met:
    * 1. Redistributions of source code must retain the copyright
    *    notice, this list of conditions and the following disclaimer.
    * 2. Redistributions in binary form must reproduce the above copyright
    *    notice, this list of conditions and the following disclaimer in the
    *    documentation and/or other materials provided with the distribution.
    * 3. All advertising materials mentioning features or use of this software
    *    must display the following acknowledgement:
    *    "This product includes cryptographic software written by
    *     Eric Young (eay@cryptsoft.com)"
    *    The word 'cryptographic' can be left out if the rouines from the library
    *    being used are not cryptographic related :-).
    * 4. If you include any Windows specific code (or a derivative thereof) from
    *    the apps directory (application code) you must include an acknowledgement:
    *    "This product includes software written by Tim Hudson (tjh@cryptsoft.com)"
    *
    * THIS SOFTWARE IS PROVIDED BY ERIC YOUNG ``AS IS'' AND
    * ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
    * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
    * ARE DISCLAIMED.  IN NO EVENT SHALL THE AUTHOR OR CONTRIBUTORS BE LIABLE
    * FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
    * DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS
    * OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION)
    * HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
    * LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY
    * OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF
    * SUCH DAMAGE.
    *
    * The licence and distribution terms for any publically available version or
    * derivative of this code cannot be changed.  i.e. this code cannot simply be
    * copied and put under another distribution licence
    * [including the GNU Public Licence.]
    */

expat

Le module pyexpat est compilé avec une copie des sources d”expat, sauf si la compilation est configurée avec --with-system-expat :

Copyright (c) 1998, 1999, 2000 Thai Open Source Software Center Ltd
                               and Clark Cooper

Permission is hereby granted, free of charge, to any person obtaining
a copy of this software and associated documentation files (the
"Software"), to deal in the Software without restriction, including
without limitation the rights to use, copy, modify, merge, publish,
distribute, sublicense, and/or sell copies of the Software, and to
permit persons to whom the Software is furnished to do so, subject to
the following conditions:

The above copyright notice and this permission notice shall be included
in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY
CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,
TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE
SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

libffi

Le module _ctypes est compilé en utilisant une copie des sources de la libffi, sauf si la compilation est configurée avec --with-system-libffi :

Copyright (c) 1996-2008  Red Hat, Inc and others.

Permission is hereby granted, free of charge, to any person obtaining
a copy of this software and associated documentation files (the
``Software''), to deal in the Software without restriction, including
without limitation the rights to use, copy, modify, merge, publish,
distribute, sublicense, and/or sell copies of the Software, and to
permit persons to whom the Software is furnished to do so, subject to
the following conditions:

The above copyright notice and this permission notice shall be included
in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED ``AS IS'', WITHOUT WARRANTY OF ANY KIND,
EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
NONINFRINGEMENT.  IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
DEALINGS IN THE SOFTWARE.

zlib

Le module zlib est compilé en utilisant une copie du code source de zlib si la version de zlib trouvée sur le système est trop vieille pour être utilisée :

Copyright (C) 1995-2011 Jean-loup Gailly and Mark Adler

This software is provided 'as-is', without any express or implied
warranty.  In no event will the authors be held liable for any damages
arising from the use of this software.

Permission is granted to anyone to use this software for any purpose,
including commercial applications, and to alter it and redistribute it
freely, subject to the following restrictions:

1. The origin of this software must not be misrepresented; you must not
   claim that you wrote the original software. If you use this software
   in a product, an acknowledgment in the product documentation would be
   appreciated but is not required.

2. Altered source versions must be plainly marked as such, and must not be
   misrepresented as being the original software.

3. This notice may not be removed or altered from any source distribution.

Jean-loup Gailly        Mark Adler
jloup@gzip.org          madler@alumni.caltech.edu

cfuhash

L’implémentation des dictionnaires, utilisée par le module tracemalloc est basée sur le projet cfuhash :

Copyright (c) 2005 Don Owens
All rights reserved.

This code is released under the BSD license:

Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions
are met:

  * Redistributions of source code must retain the above copyright
    notice, this list of conditions and the following disclaimer.

  * Redistributions in binary form must reproduce the above
    copyright notice, this list of conditions and the following
    disclaimer in the documentation and/or other materials provided
    with the distribution.

  * Neither the name of the author nor the names of its
    contributors may be used to endorse or promote products derived
    from this software without specific prior written permission.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION)
HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT,
STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED
OF THE POSSIBILITY OF SUCH DAMAGE.

libmpdec

Le module _decimal est construit en incluant une copie de la bibliothèque libmpdec, sauf si elle est compilée avec --with-system-libmpdec :

Copyright (c) 2008-2016 Stefan Krah. All rights reserved.

Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions
are met:

1. Redistributions of source code must retain the above copyright
   notice, this list of conditions and the following disclaimer.

2. Redistributions in binary form must reproduce the above copyright
   notice, this list of conditions and the following disclaimer in the
   documentation and/or other materials provided with the distribution.

THIS SOFTWARE IS PROVIDED BY THE AUTHOR AND CONTRIBUTORS "AS IS" AND
ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
ARE DISCLAIMED.  IN NO EVENT SHALL THE AUTHOR OR CONTRIBUTORS BE LIABLE
FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS
OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION)
HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY
OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF
SUCH DAMAGE.

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Distribuer des modules Python (Version historique)

Auteurs

Greg Ward, Anthony Baxter

Email

distutils-sig@python.org

Voir aussi

Distribuer des modules Python

La documentation actuelle de distribution de modules

Ce document décrit les outils de distribution de Python (« Distutils ») du point de vue d’un développeur de modules. Il décrit comment utiliser Distutils pour rendre des modules et extensions Python disponible à une large audience, simplement, avec un faible surcoût sur les mécaniques de construction, déploiement et installation.

Note

Ce guide ne couvre que les outils de base, fournis avec cette version de Python, pour construire et distribuer des extensions. D’autres outils peuvent être plus sécurisés et plus simple à utiliser. Consultez quick recommendations section [https://packaging.python.org/en/latest/current/] dans le Python Packaging User Guide pour plus d’informations.

1. An Introduction to Distutils

1.1. Concepts et Terminologie

1.2. Un exemple simple

1.3. General Python terminology

1.4. Distutils-specific terminology

2. Writing the Setup Script

2.1. Listing whole packages

2.2. Listing individual modules

2.3. Describing extension modules

2.4. Relationships between Distributions and Packages

2.5. Installing Scripts

2.6. Installing Package Data

2.7. Installing Additional Files

2.8. Additional meta-data

2.9. Debugging the setup script

3. Writing the Setup Configuration File

4. Créer une distribution source

4.1. Spécifier les fichiers à distribuer

4.2. Options pour le manifeste

5. Créer une distribution compilée

5.1. Créer un paquet RPM

5.2. Créer un installateur Windows

5.3. Compiler pour toute les plateformes Windows

5.4. Contrôle d’accès utilisateur Vista (UAC)

6. L’index de paquets Python (Python Package Index : PyPI)

6.1. PyPI overview

6.2. Distutils commands

6.3. PyPI package display

7. Exemples

7.1. Pure Python distribution (by module)

7.2. Pure Python distribution (by package)

7.3. Single extension module

7.4. Checking a package

7.5. Reading the metadata

8. Extension de Distutils

8.1. Intégrer de nouvelles commandes

8.2. Ajout de nouveaux types de distribution

9. Référence des commandes

9.1. Installer des modules: la famille de commande install

9.2. Créer une distribution source: la commande sdist

10. Référence de l’API

10.1. distutils.core — Fonctionnalités principales du module Distutils

10.2. distutils.ccompiler — Classe de base CCompiler

10.3. distutils.unixccompiler — Compilateur C Unix

10.4. distutils.msvccompiler — Compilateur Microsoft

10.5. distutils.bcppcompiler — Compilateur Borland

10.6. distutils.cygwincompiler — Compilateur Cygwin

10.7. distutils.archive_util — Utilitaires d’archivage

10.8. distutils.dep_util — Vérification des dépendances

10.9. distutils.dir_util — Opérations sur l’arborescence des répertoires

10.10. distutils.file_util — Traitements mono-fichier

10.11. distutils.util — Autres fonctions de service

10.12. distutils.dist — La classe Distribution

10.13. distutils.extension — La classe Extension

10.14. distutils.debug — Mode de débogage du module Distutils

10.15. distutils.errors — Exceptions du module Distutils

10.16. distutils.fancy_getopt — Encapsulation du module getopt standard

10.17. distutils.filelist — La classe FileList liste des fichiers

10.18. distutils.log — Journalisation basée sur le style de la PEP 282

10.19. distutils.spawn — Crée un sous-processus

10.20. distutils.sysconfig — Informations de configuration du système

10.21. distutils.text_file — La classe TextFile

10.22. distutils.version — Classes de numéros de version

10.23. distutils.cmd — Classe de base abstraite pour les commandes Distutils

10.24. Créer une nouvelle commande Distutils

10.25. distutils.command — Commandes Distutils individuelles

10.26. distutils.command.bdist — Construit un installateur binaire

10.27. distutils.command.bdist_packager — Classe de base abstraite pour empaqueteurs

10.28. distutils.command.bdist_dumb — Construit un installateur passif (dumb)

10.29. distutils.command.bdist_msi — Construit un installateur Microsoft

10.30. distutils.command.bdist_rpm — Construit une distribution binaire au format Redhat RPM et SRPM

10.31. distutils.command.bdist_wininst — Construit un installateur Windows

10.32. distutils.command.sdist — Construit une distribution source

10.33. distutils.command.build — Construit tous les fichiers d’un paquet

10.34. distutils.command.build_clib — Construit toutes les bibliothèques C d’un paquet

10.35. distutils.command.build_ext — Construit toutes les extensions d’un paquet

10.36. distutils.command.build_py — Construit les fichiers .py/.pyc d’un paquet

10.37. distutils.command.build_scripts — Construit les scripts d’un paquet

10.38. distutils.command.clean — Nettoie un dossier de compilation d’un paquet

10.39. distutils.command.config — Effectue la configuration d’un paquet

10.40. distutils.command.install — Installe un paquet

10.41. distutils.command.install_data — Installe les fichiers de données d’un paquet

10.42. distutils.command.install_headers — Installe les fichiers d’en-tête C/C++ d’un paquet

10.43. distutils.command.install_lib — Installe les fichiers de bibliothèque à partir d’un paquet

10.44. distutils.command.install_scripts — Installe les fichiers de script d’un paquet

10.45. distutils.command.register — Enregistre un module dans l’Index des paquets Python (Python Package Index ou PyPI en anglais)

10.46. distutils.command.check — Vérifie les méta-données d’un paquet

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1. An Introduction to Distutils

This document covers using the Distutils to distribute your Python modules, concentrating on the role of developer/distributor: if you’re looking for information on installing Python modules, you should refer to the Installation des modules python (Version historique) chapter.

1.1. Concepts et Terminologie

Using the Distutils is quite simple, both for module developers and for users/administrators installing third-party modules. As a developer, your responsibilities (apart from writing solid, well-documented and well-tested code, of course!) are:

write a setup script (setup.py by convention)

(optional) write a setup configuration file

create a source distribution

(optional) create one or more built (binary) distributions

Each of these tasks is covered in this document.

Not all module developers have access to a multitude of platforms, so it’s not always feasible to expect them to create a multitude of built distributions. It is hoped that a class of intermediaries, called packagers, will arise to address this need. Packagers will take source distributions released by module developers, build them on one or more platforms, and release the resulting built distributions. Thus, users on the most popular platforms will be able to install most popular Python module distributions in the most natural way for their platform, without having to run a single setup script or compile a line of code.

1.2. Un exemple simple

The setup script is usually quite simple, although since it’s written in Python, there are no arbitrary limits to what you can do with it, though you should be careful about putting arbitrarily expensive operations in your setup script. Unlike, say, Autoconf-style configure scripts, the setup script may be run multiple times in the course of building and installing your module distribution.

If all you want to do is distribute a module called foo, contained in a file foo.py, then your setup script can be as simple as this:

from distutils.core import setup
setup(name='foo',
      version='1.0',
      py_modules=['foo'],
      )

Some observations:

most information that you supply to the Distutils is supplied as keyword arguments to the setup() function

those keyword arguments fall into two categories: package metadata (name, version number) and information about what’s in the package (a list of pure Python modules, in this case)

modules are specified by module name, not filename (the same will hold true for packages and extensions)

it’s recommended that you supply a little more metadata, in particular your name, email address and a URL for the project (see section Writing the Setup Script for an example)

To create a source distribution for this module, you would create a setup script, setup.py, containing the above code, and run this command from a terminal:

python setup.py sdist

For Windows, open a command prompt window (Start ‣ Accessories) and change the command to:

setup.py sdist

sdist will create an archive file (e.g., tarball on Unix, ZIP file on Windows) containing your setup script setup.py, and your module foo.py. The archive file will be named foo-1.0.tar.gz (or .zip), and will unpack into a directory foo-1.0.

If an end-user wishes to install your foo module, all they have to do is download foo-1.0.tar.gz (or .zip), unpack it, and—from the foo-1.0 directory—run

python setup.py install

which will ultimately copy foo.py to the appropriate directory for third-party modules in their Python installation.

This simple example demonstrates some fundamental concepts of the Distutils. First, both developers and installers have the same basic user interface, i.e. the setup script. The difference is which Distutils commands they use: the sdist command is almost exclusively for module developers, while install is more often for installers (although most developers will want to install their own code occasionally).

If you want to make things really easy for your users, you can create one or more built distributions for them. For instance, if you are running on a Windows machine, and want to make things easy for other Windows users, you can create an executable installer (the most appropriate type of built distribution for this platform) with the bdist_wininst command. For example:

python setup.py bdist_wininst

will create an executable installer, foo-1.0.win32.exe, in the current directory.

Other useful built distribution formats are RPM, implemented by the bdist_rpm command, Solaris pkgtool (bdist_pkgtool), and HP-UX swinstall (bdist_sdux). For example, the following command will create an RPM file called foo-1.0.noarch.rpm:

python setup.py bdist_rpm

(The bdist_rpm command uses the rpm executable, therefore this has to be run on an RPM-based system such as Red Hat Linux, SuSE Linux, or Mandrake Linux.)

You can find out what distribution formats are available at any time by running

python setup.py bdist --help-formats

1.3. General Python terminology

If you’re reading this document, you probably have a good idea of what modules, extensions, and so forth are. Nevertheless, just to be sure that everyone is operating from a common starting point, we offer the following glossary of common Python terms:

module

the basic unit of code reusability in Python: a block of code imported by some other code. Three types of modules concern us here: pure Python modules, extension modules, and packages.

pure Python module

a module written in Python and contained in a single .py file (and possibly associated .pyc files). Sometimes referred to as a « pure module. »

module d’extension

a module written in the low-level language of the Python implementation: C/C++ for Python, Java for Jython. Typically contained in a single dynamically loadable pre-compiled file, e.g. a shared object (.so) file for Python extensions on Unix, a DLL (given the .pyd extension) for Python extensions on Windows, or a Java class file for Jython extensions. (Note that currently, the Distutils only handles C/C++ extensions for Python.)

paquet

a module that contains other modules; typically contained in a directory in the filesystem and distinguished from other directories by the presence of a file __init__.py.

paquet racine

the root of the hierarchy of packages. (This isn’t really a package, since it doesn’t have an __init__.py file. But we have to call it something.) The vast majority of the standard library is in the root package, as are many small, standalone third-party modules that don’t belong to a larger module collection. Unlike regular packages, modules in the root package can be found in many directories: in fact, every directory listed in sys.path contributes modules to the root package.

1.4. Distutils-specific terminology

The following terms apply more specifically to the domain of distributing Python modules using the Distutils:

module distribution

a collection of Python modules distributed together as a single downloadable resource and meant to be installed en masse. Examples of some well-known module distributions are NumPy, SciPy, Pillow, or mxBase. (This would be called a package, except that term is already taken in the Python context: a single module distribution may contain zero, one, or many Python packages.)

pure module distribution

a module distribution that contains only pure Python modules and packages. Sometimes referred to as a « pure distribution. »

non-pure module distribution

a module distribution that contains at least one extension module. Sometimes referred to as a « non-pure distribution. »

distribution root

the top-level directory of your source tree (or source distribution); the directory where setup.py exists. Generally setup.py will be run from this directory.

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2. Writing the Setup Script

The setup script is the centre of all activity in building, distributing, and installing modules using the Distutils. The main purpose of the setup script is to describe your module distribution to the Distutils, so that the various commands that operate on your modules do the right thing. As we saw in section Un exemple simple above, the setup script consists mainly of a call to setup(), and most information supplied to the Distutils by the module developer is supplied as keyword arguments to setup().

Here’s a slightly more involved example, which we’ll follow for the next couple of sections: the Distutils” own setup script. (Keep in mind that although the Distutils are included with Python 1.6 and later, they also have an independent existence so that Python 1.5.2 users can use them to install other module distributions. The Distutils” own setup script, shown here, is used to install the package into Python 1.5.2.)

#!/usr/bin/env python

from distutils.core import setup

setup(name='Distutils',
      version='1.0',
      description='Python Distribution Utilities',
      author='Greg Ward',
      author_email='gward@python.net',
      url='https://www.python.org/sigs/distutils-sig/',
      packages=['distutils', 'distutils.command'],
     )

There are only two differences between this and the trivial one-file distribution presented in section Un exemple simple: more metadata, and the specification of pure Python modules by package, rather than by module. This is important since the Distutils consist of a couple of dozen modules split into (so far) two packages; an explicit list of every module would be tedious to generate and difficult to maintain. For more information on the additional meta-data, see section Additional meta-data.

Note that any pathnames (files or directories) supplied in the setup script should be written using the Unix convention, i.e. slash-separated. The Distutils will take care of converting this platform-neutral representation into whatever is appropriate on your current platform before actually using the pathname. This makes your setup script portable across operating systems, which of course is one of the major goals of the Distutils. In this spirit, all pathnames in this document are slash-separated.

This, of course, only applies to pathnames given to Distutils functions. If you, for example, use standard Python functions such as glob.glob() or os.listdir() to specify files, you should be careful to write portable code instead of hardcoding path separators:

glob.glob(os.path.join('mydir', 'subdir', '*.html'))
os.listdir(os.path.join('mydir', 'subdir'))

2.1. Listing whole packages

The packages option tells the Distutils to process (build, distribute, install, etc.) all pure Python modules found in each package mentioned in the packages list. In order to do this, of course, there has to be a correspondence between package names and directories in the filesystem. The default correspondence is the most obvious one, i.e. package distutils is found in the directory distutils relative to the distribution root. Thus, when you say packages = ['foo'] in your setup script, you are promising that the Distutils will find a file foo/__init__.py (which might be spelled differently on your system, but you get the idea) relative to the directory where your setup script lives. If you break this promise, the Distutils will issue a warning but still process the broken package anyway.

If you use a different convention to lay out your source directory, that’s no problem: you just have to supply the package_dir option to tell the Distutils about your convention. For example, say you keep all Python source under lib, so that modules in the « root package » (i.e., not in any package at all) are in lib, modules in the foo package are in lib/foo, and so forth. Then you would put

package_dir = {'': 'lib'}

in your setup script. The keys to this dictionary are package names, and an empty package name stands for the root package. The values are directory names relative to your distribution root. In this case, when you say packages = ['foo'], you are promising that the file lib/foo/__init__.py exists.

Another possible convention is to put the foo package right in lib, the foo.bar package in lib/bar, etc. This would be written in the setup script as

package_dir = {'foo': 'lib'}

A package: dir entry in the package_dir dictionary implicitly applies to all packages below package, so the foo.bar case is automatically handled here. In this example, having packages = ['foo', 'foo.bar'] tells the Distutils to look for lib/__init__.py and lib/bar/__init__.py. (Keep in mind that although package_dir applies recursively, you must explicitly list all packages in packages: the Distutils will not recursively scan your source tree looking for any directory with an __init__.py file.)

2.2. Listing individual modules

For a small module distribution, you might prefer to list all modules rather than listing packages—especially the case of a single module that goes in the « root package » (i.e., no package at all). This simplest case was shown in section Un exemple simple; here is a slightly more involved example:

py_modules = ['mod1', 'pkg.mod2']

This describes two modules, one of them in the « root » package, the other in the pkg package. Again, the default package/directory layout implies that these two modules can be found in mod1.py and pkg/mod2.py, and that pkg/__init__.py exists as well. And again, you can override the package/directory correspondence using the package_dir option.

2.3. Describing extension modules

Just as writing Python extension modules is a bit more complicated than writing pure Python modules, describing them to the Distutils is a bit more complicated. Unlike pure modules, it’s not enough just to list modules or packages and expect the Distutils to go out and find the right files; you have to specify the extension name, source file(s), and any compile/link requirements (include directories, libraries to link with, etc.).

All of this is done through another keyword argument to setup(), the ext_modules option. ext_modules is just a list of Extension instances, each of which describes a single extension module. Suppose your distribution includes a single extension, called foo and implemented by foo.c. If no additional instructions to the compiler/linker are needed, describing this extension is quite simple:

Extension('foo', ['foo.c'])

The Extension class can be imported from distutils.core along with setup(). Thus, the setup script for a module distribution that contains only this one extension and nothing else might be:

from distutils.core import setup, Extension
setup(name='foo',
      version='1.0',
      ext_modules=[Extension('foo', ['foo.c'])],
      )

The Extension class (actually, the underlying extension-building machinery implemented by the build_ext command) supports a great deal of flexibility in describing Python extensions, which is explained in the following sections.

2.3.1. Extension names and packages

The first argument to the Extension constructor is always the name of the extension, including any package names. For example,

Extension('foo', ['src/foo1.c', 'src/foo2.c'])

describes an extension that lives in the root package, while

Extension('pkg.foo', ['src/foo1.c', 'src/foo2.c'])

describes the same extension in the pkg package. The source files and resulting object code are identical in both cases; the only difference is where in the filesystem (and therefore where in Python’s namespace hierarchy) the resulting extension lives.

If you have a number of extensions all in the same package (or all under the same base package), use the ext_package keyword argument to setup(). For example,

setup(...,
      ext_package='pkg',
      ext_modules=[Extension('foo', ['foo.c']),
                   Extension('subpkg.bar', ['bar.c'])],
     )

will compile foo.c to the extension pkg.foo, and bar.c to pkg.subpkg.bar.

2.3.2. Extension source files

The second argument to the Extension constructor is a list of source files. Since the Distutils currently only support C, C++, and Objective-C extensions, these are normally C/C++/Objective-C source files. (Be sure to use appropriate extensions to distinguish C++ source files: .cc and .cpp seem to be recognized by both Unix and Windows compilers.)

However, you can also include SWIG interface (.i) files in the list; the build_ext command knows how to deal with SWIG extensions: it will run SWIG on the interface file and compile the resulting C/C++ file into your extension.

This warning notwithstanding, options to SWIG can be currently passed like this:

setup(...,
      ext_modules=[Extension('_foo', ['foo.i'],
                             swig_opts=['-modern', '-I../include'])],
      py_modules=['foo'],
     )

Or on the commandline like this:

> python setup.py build_ext --swig-opts="-modern -I../include"

On some platforms, you can include non-source files that are processed by the compiler and included in your extension. Currently, this just means Windows message text (.mc) files and resource definition (.rc) files for Visual C++. These will be compiled to binary resource (.res) files and linked into the executable.

2.3.3. Preprocessor options

Three optional arguments to Extension will help if you need to specify include directories to search or preprocessor macros to define/undefine: include_dirs, define_macros, and undef_macros.

For example, if your extension requires header files in the include directory under your distribution root, use the include_dirs option:

Extension('foo', ['foo.c'], include_dirs=['include'])

You can specify absolute directories there; if you know that your extension will only be built on Unix systems with X11R6 installed to /usr, you can get away with

Extension('foo', ['foo.c'], include_dirs=['/usr/include/X11'])

You should avoid this sort of non-portable usage if you plan to distribute your code: it’s probably better to write C code like

#include <X11/Xlib.h>

If you need to include header files from some other Python extension, you can take advantage of the fact that header files are installed in a consistent way by the Distutils install_headers command. For example, the Numerical Python header files are installed (on a standard Unix installation) to /usr/local/include/python1.5/Numerical. (The exact location will differ according to your platform and Python installation.) Since the Python include directory—/usr/local/include/python1.5 in this case—is always included in the search path when building Python extensions, the best approach is to write C code like

#include <Numerical/arrayobject.h>

If you must put the Numerical include directory right into your header search path, though, you can find that directory using the Distutils distutils.sysconfig module:

from distutils.sysconfig import get_python_inc
incdir = os.path.join(get_python_inc(plat_specific=1), 'Numerical')
setup(...,
      Extension(..., include_dirs=[incdir]),
      )

Even though this is quite portable—it will work on any Python installation, regardless of platform—it’s probably easier to just write your C code in the sensible way.

You can define and undefine pre-processor macros with the define_macros and undef_macros options. define_macros takes a list of (name, value) tuples, where name is the name of the macro to define (a string) and value is its value: either a string or None. (Defining a macro FOO to None is the equivalent of a bare #define FOO in your C source: with most compilers, this sets FOO to the string 1.) undef_macros is just a list of macros to undefine.

Par exemple :

Extension(...,
          define_macros=[('NDEBUG', '1'),
                         ('HAVE_STRFTIME', None)],
          undef_macros=['HAVE_FOO', 'HAVE_BAR'])

is the equivalent of having this at the top of every C source file:

#define NDEBUG 1
#define HAVE_STRFTIME
#undef HAVE_FOO
#undef HAVE_BAR

2.3.4. Library options

You can also specify the libraries to link against when building your extension, and the directories to search for those libraries. The libraries option is a list of libraries to link against, library_dirs is a list of directories to search for libraries at link-time, and runtime_library_dirs is a list of directories to search for shared (dynamically loaded) libraries at run-time.

For example, if you need to link against libraries known to be in the standard library search path on target systems

Extension(...,
          libraries=['gdbm', 'readline'])

If you need to link with libraries in a non-standard location, you’ll have to include the location in library_dirs:

Extension(...,
          library_dirs=['/usr/X11R6/lib'],
          libraries=['X11', 'Xt'])

(Again, this sort of non-portable construct should be avoided if you intend to distribute your code.)

2.3.5. Autres options

There are still some other options which can be used to handle special cases.

The optional option is a boolean; if it is true, a build failure in the extension will not abort the build process, but instead simply not install the failing extension.

The extra_objects option is a list of object files to be passed to the linker. These files must not have extensions, as the default extension for the compiler is used.

extra_compile_args and extra_link_args can be used to specify additional command line options for the respective compiler and linker command lines.

export_symbols is only useful on Windows. It can contain a list of symbols (functions or variables) to be exported. This option is not needed when building compiled extensions: Distutils will automatically add initmodule to the list of exported symbols.

The depends option is a list of files that the extension depends on (for example header files). The build command will call the compiler on the sources to rebuild extension if any on this files has been modified since the previous build.

2.4. Relationships between Distributions and Packages

A distribution may relate to packages in three specific ways:

It can require packages or modules.

It can provide packages or modules.

It can obsolete packages or modules.

These relationships can be specified using keyword arguments to the distutils.core.setup() function.

Dependencies on other Python modules and packages can be specified by supplying the requires keyword argument to setup(). The value must be a list of strings. Each string specifies a package that is required, and optionally what versions are sufficient.

To specify that any version of a module or package is required, the string should consist entirely of the module or package name. Examples include 'mymodule' and 'xml.parsers.expat'.

If specific versions are required, a sequence of qualifiers can be supplied in parentheses. Each qualifier may consist of a comparison operator and a version number. The accepted comparison operators are:

<    >    ==
<=   >=   !=

These can be combined by using multiple qualifiers separated by commas (and optional whitespace). In this case, all of the qualifiers must be matched; a logical AND is used to combine the evaluations.

Let’s look at a bunch of examples:

Requires Expression

Explication

==1.0

Only version 1.0 is compatible

>1.0, !=1.5.1, <2.0

Any version after 1.0 and before 2.0 is compatible, except 1.5.1

Now that we can specify dependencies, we also need to be able to specify what we provide that other distributions can require. This is done using the provides keyword argument to setup(). The value for this keyword is a list of strings, each of which names a Python module or package, and optionally identifies the version. If the version is not specified, it is assumed to match that of the distribution.

Quelques exemples :

Provides Expression

Explication

mypkg

Provide mypkg, using the distribution version

mypkg (1.1)

Provide mypkg version 1.1, regardless of the distribution version

A package can declare that it obsoletes other packages using the obsoletes keyword argument. The value for this is similar to that of the requires keyword: a list of strings giving module or package specifiers. Each specifier consists of a module or package name optionally followed by one or more version qualifiers. Version qualifiers are given in parentheses after the module or package name.

The versions identified by the qualifiers are those that are obsoleted by the distribution being described. If no qualifiers are given, all versions of the named module or package are understood to be obsoleted.

2.5. Installing Scripts

So far we have been dealing with pure and non-pure Python modules, which are usually not run by themselves but imported by scripts.

Scripts are files containing Python source code, intended to be started from the command line. Scripts don’t require Distutils to do anything very complicated. The only clever feature is that if the first line of the script starts with #! and contains the word « python », the Distutils will adjust the first line to refer to the current interpreter location. By default, it is replaced with the current interpreter location. The --executable (or -e) option will allow the interpreter path to be explicitly overridden.

The scripts option simply is a list of files to be handled in this way. From the PyXML setup script:

setup(...,
      scripts=['scripts/xmlproc_parse', 'scripts/xmlproc_val']
      )

Modifié dans la version 3.1: All the scripts will also be added to the MANIFEST file if no template is provided. See Spécifier les fichiers à distribuer.

2.6. Installing Package Data

Often, additional files need to be installed into a package. These files are often data that’s closely related to the package’s implementation, or text files containing documentation that might be of interest to programmers using the package. These files are called package data.

Package data can be added to packages using the package_data keyword argument to the setup() function. The value must be a mapping from package name to a list of relative path names that should be copied into the package. The paths are interpreted as relative to the directory containing the package (information from the package_dir mapping is used if appropriate); that is, the files are expected to be part of the package in the source directories. They may contain glob patterns as well.

The path names may contain directory portions; any necessary directories will be created in the installation.

For example, if a package should contain a subdirectory with several data files, the files can be arranged like this in the source tree:

setup.py
src/
    mypkg/
        __init__.py
        module.py
        data/
            tables.dat
            spoons.dat
            forks.dat

The corresponding call to setup() might be:

setup(...,
      packages=['mypkg'],
      package_dir={'mypkg': 'src/mypkg'},
      package_data={'mypkg': ['data/*.dat']},
      )

Modifié dans la version 3.1: All the files that match package_data will be added to the MANIFEST file if no template is provided. See Spécifier les fichiers à distribuer.

2.7. Installing Additional Files

The data_files option can be used to specify additional files needed by the module distribution: configuration files, message catalogs, data files, anything which doesn’t fit in the previous categories.

data_files specifies a sequence of (directory, files) pairs in the following way:

setup(...,
      data_files=[('bitmaps', ['bm/b1.gif', 'bm/b2.gif']),
                  ('config', ['cfg/data.cfg']),
                  ('/etc/init.d', ['init-script'])]
     )

Note that you can specify the directory names where the data files will be installed, but you cannot rename the data files themselves.

Each (directory, files) pair in the sequence specifies the installation directory and the files to install there. If directory is a relative path, it is interpreted relative to the installation prefix (Python’s sys.prefix for pure-Python packages, sys.exec_prefix for packages that contain extension modules). Each file name in files is interpreted relative to the setup.py script at the top of the package source distribution. No directory information from files is used to determine the final location of the installed file; only the name of the file is used.

You can specify the data_files options as a simple sequence of files without specifying a target directory, but this is not recommended, and the install command will print a warning in this case. To install data files directly in the target directory, an empty string should be given as the directory.

Modifié dans la version 3.1: All the files that match data_files will be added to the MANIFEST file if no template is provided. See Spécifier les fichiers à distribuer.

2.8. Additional meta-data

The setup script may include additional meta-data beyond the name and version. This information includes:

Meta-Data

Description

Valeur

Notes

name

name of the package

short string

(1)

version

version of this release

short string

(1)(2)

author

package author’s name

short string

(3)

author_email

email address of the package author

email address

(3)

maintainer

package maintainer’s name

short string

(3)

maintainer_email

email address of the package maintainer

email address

(3)

url

home page for the package

URL

(1)

description

short, summary description of the package

short string

long_description

longer description of the package

long string

(5)

download_url

location where the package may be downloaded

URL

(4)

classifiers

a list of classifiers

list of strings

(4)

platforms

a list of platforms

list of strings

license

license for the package

short string

(6)

Notes :

These fields are required.

It is recommended that versions take the form major.minor[.patch[.sub]].

Either the author or the maintainer must be identified. If maintainer is provided, distutils lists it as the author in PKG-INFO.

These fields should not be used if your package is to be compatible with Python versions prior to 2.2.3 or 2.3. The list is available from the PyPI website [https://pypi.org/].

The long_description field is used by PyPI when you are registering a package, to build its home page.

The license field is a text indicating the license covering the package where the license is not a selection from the « License » Trove classifiers. See the Classifier field. Notice that there’s a licence distribution option which is deprecated but still acts as an alias for license.

“chaîne courte”

A single line of text, not more than 200 characters.

“chaîne longue”

Multiple lines of plain text in reStructuredText format (see http://docutils.sourceforge.net/).

“liste de chaînes”

See below.

Encoding the version information is an art in itself. Python packages generally adhere to the version format major.minor[.patch][sub]. The major number is 0 for initial, experimental releases of software. It is incremented for releases that represent major milestones in a package. The minor number is incremented when important new features are added to the package. The patch number increments when bug-fix releases are made. Additional trailing version information is sometimes used to indicate sub-releases. These are « a1,a2,…,aN » (for alpha releases, where functionality and API may change), « b1,b2,…,bN » (for beta releases, which only fix bugs) and « pr1,pr2,…,prN » (for final pre-release release testing). Some examples:

0.1.0

the first, experimental release of a package

1.0.1a2

the second alpha release of the first patch version of 1.0

classifiers are specified in a Python list:

setup(...,
      classifiers=[
          'Development Status :: 4 - Beta',
          'Environment :: Console',
          'Environment :: Web Environment',
          'Intended Audience :: End Users/Desktop',
          'Intended Audience :: Developers',
          'Intended Audience :: System Administrators',
          'License :: OSI Approved :: Python Software Foundation License',
          'Operating System :: MacOS :: MacOS X',
          'Operating System :: Microsoft :: Windows',
          'Operating System :: POSIX',
          'Programming Language :: Python',
          'Topic :: Communications :: Email',
          'Topic :: Office/Business',
          'Topic :: Software Development :: Bug Tracking',
          ],
      )

2.9. Debugging the setup script

Sometimes things go wrong, and the setup script doesn’t do what the developer wants.

Distutils catches any exceptions when running the setup script, and print a simple error message before the script is terminated. The motivation for this behaviour is to not confuse administrators who don’t know much about Python and are trying to install a package. If they get a big long traceback from deep inside the guts of Distutils, they may think the package or the Python installation is broken because they don’t read all the way down to the bottom and see that it’s a permission problem.

On the other hand, this doesn’t help the developer to find the cause of the failure. For this purpose, the DISTUTILS_DEBUG environment variable can be set to anything except an empty string, and distutils will now print detailed information about what it is doing, dump the full traceback when an exception occurs, and print the whole command line when an external program (like a C compiler) fails.

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3. Writing the Setup Configuration File

Often, it’s not possible to write down everything needed to build a distribution a priori: you may need to get some information from the user, or from the user’s system, in order to proceed. As long as that information is fairly simple—a list of directories to search for C header files or libraries, for example—then providing a configuration file, setup.cfg, for users to edit is a cheap and easy way to solicit it. Configuration files also let you provide default values for any command option, which the installer can then override either on the command-line or by editing the config file.

The setup configuration file is a useful middle-ground between the setup script—which, ideally, would be opaque to installers 1—and the command-line to the setup script, which is outside of your control and entirely up to the installer. In fact, setup.cfg (and any other Distutils configuration files present on the target system) are processed after the contents of the setup script, but before the command-line. This has several useful consequences:

installers can override some of what you put in setup.py by editing setup.cfg

you can provide non-standard defaults for options that are not easily set in setup.py

installers can override anything in setup.cfg using the command-line options to setup.py

The basic syntax of the configuration file is simple:

[command]
option=value
...

where command is one of the Distutils commands (e.g. build_py, install), and option is one of the options that command supports. Any number of options can be supplied for each command, and any number of command sections can be included in the file. Blank lines are ignored, as are comments, which run from a '#' character until the end of the line. Long option values can be split across multiple lines simply by indenting the continuation lines.

You can find out the list of options supported by a particular command with the universal --help option, e.g.

$ python setup.py --help build_ext
[...]
Options for 'build_ext' command:
  --build-lib (-b)     directory for compiled extension modules
  --build-temp (-t)    directory for temporary files (build by-products)
  --inplace (-i)       ignore build-lib and put compiled extensions into the
                       source directory alongside your pure Python modules
  --include-dirs (-I)  list of directories to search for header files
  --define (-D)        C preprocessor macros to define
  --undef (-U)         C preprocessor macros to undefine
  --swig-opts          list of SWIG command line options
[...]

Note that an option spelled --foo-bar on the command-line is spelled foo_bar in configuration files.

For example, say you want your extensions to be built « in-place »—that is, you have an extension pkg.ext, and you want the compiled extension file (ext.so on Unix, say) to be put in the same source directory as your pure Python modules pkg.mod1 and pkg.mod2. You can always use the --inplace option on the command-line to ensure this:

python setup.py build_ext --inplace

But this requires that you always specify the build_ext command explicitly, and remember to provide --inplace. An easier way is to « set and forget » this option, by encoding it in setup.cfg, the configuration file for this distribution:

[build_ext]
inplace=1

This will affect all builds of this module distribution, whether or not you explicitly specify build_ext. If you include setup.cfg in your source distribution, it will also affect end-user builds—which is probably a bad idea for this option, since always building extensions in-place would break installation of the module distribution. In certain peculiar cases, though, modules are built right in their installation directory, so this is conceivably a useful ability. (Distributing extensions that expect to be built in their installation directory is almost always a bad idea, though.)

Another example: certain commands take a lot of options that don’t change from run to run; for example, bdist_rpm needs to know everything required to generate a « spec » file for creating an RPM distribution. Some of this information comes from the setup script, and some is automatically generated by the Distutils (such as the list of files installed). But some of it has to be supplied as options to bdist_rpm, which would be very tedious to do on the command-line for every run. Hence, here is a snippet from the Distutils” own setup.cfg:

[bdist_rpm]
release = 1
packager = Greg Ward <gward@python.net>
doc_files = CHANGES.txt
            README.txt
            USAGE.txt
            doc/
            examples/

Note that the doc_files option is simply a whitespace-separated string split across multiple lines for readability.

Voir aussi

Syntax of config files in « Installing Python Modules »

More information on the configuration files is available in the manual for system administrators.

Notes

1

This ideal probably won’t be achieved until auto-configuration is fully supported by the Distutils.

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4. Créer une distribution source

Comme montré dans le chapitre Un exemple simple, vous pouvez utiliser la commande sdist pour créer une distribution source. Dans le cas le plus simple,

python setup.py sdist

(en supposant que vous n’avez spécifié aucune option pour la commande sdist dans le script de préparation ou le fichier de configuration), sdist crée une archive au format par défaut pour la plateforme utilisée. Le format par défaut est un fichier tar compressé (.tar.gz) sur Unix et un fichier ZIP sur Windows.

Vous pouvez donner autant de formats que désiré via l’option --formats, par exemple :

python setup.py sdist --formats=gztar,zip

pour créer un fichier tarball compressé et un fichier ZIP. Les formats disponibles actuellement sont :

Format

Description

Notes

zip

Fichier zip (.zip)

(1), (3)

gztar

Fichier tar compressé par gzip (.tar.gz)

(2)

bztar

Fichier tar compressé par bzip2 (.tar.bz2)

xztar

Fichier tar compressé par xz (.tar.xz)

ztar

Fichier tar compressé par compress (.tar.Z)

(4)

tar

fichier tar (.tar)

Modifié dans la version 3.5: Ajout du support des fichiers xztar.

Notes :

Par défaut sur Windows

Par défaut sur Unix

nécessite soit un utilitaire zip extérieur ou le module zipfile (inclut dans la bibliothèque standard depuis Python 1.6)

nécessite le programme compress. Remarquez que ce format sera bientôt obsolète et sera enlevé des prochaines version de Python.

Lorsque vous utilisez n’importe quel format tar (gztar, bztar, xztar, ztar or tar), vous pouvez spécifier sous Unix le propriétaire et le groupe qui seront appliqué pour chaque fichier de l’archive.

Par exemple, si vous voulez que tous les fichiers de l’archive soient détenu par root :

python setup.py sdist --owner=root --group=root

4.1. Spécifier les fichiers à distribuer

Si vous ne fournissez pas une liste explicite de fichiers (ou les instructions pour la générer), la commande sdist en met par défaut le minimum dans la distribution source :

tous les fichiers source Python sous-entendus par les options py_modules et packages

tous les fichiers source C mentionnés dans les arguments ext_modules ou libraries

scripts identifiés par l’argument scripts. Voir Installing Scripts.

tout ce qui ressemble à un script de test test/test*.py (pour l’instant, Distutils ne fait rien avec ces scripts de test, si ce n’est les inclure dans les distributions sources, mais dans le futur un standard sera implémenté pour tester les distributions de module Python)

README.txt (ou README), setup.py (ou peut importe la manière dont vous avez appelé votre script d’installation) et setup.cfg

tous les fichiers associés aux méta-données package_data. Voir Installing Package Data.

tous les fichiers associés aux méta-données data_files. Voir Installing Additional Files.

Parfois ce fonctionnement suffit, mais généralement vous voudrez spécifier des fichiers supplémentaires à distribuer. La façon classique de le faire est d’écrire un manifeste modèle, appelé MANIFEST.in par défaut. Ce manifeste modèle est juste une liste d’instructions pour générer votre fichier manifeste final, MANIFEST, qui est la liste exacte des fichiers à inclure dans votre distribution source. La commande sdist traite ce modèle et génère un manifeste à partir de ces instructions et de ce qu’elle trouve dans le système de fichiers.

Si vous préférez créer votre propre fichier manifeste, le format est simple : un nom de fichier par ligne, uniquement des fichiers normaux (ou leur lien symbolique). Si vous fournissez votre propre MANIFEST, vous devez tout spécifier : les groupes de fichiers par défaut décrits au-dessus ne sont pas inclus automatiquement dans ce cas.

Modifié dans la version 3.1: Un MANIFEST existant généré automatiquement sera régénéré sans que sdist ne compare son heure de modification à MANIFEST.in ou setup.py.

Modifié dans la version 3.1.3: Les fichiers MANIFEST commencent par un commentaire indiquant qu’ils sont générés. Les fichiers sans ce commentaire ne sont pas réécrits ou supprimés.

Modifié dans la version 3.2.2: sdist lira un ficher MANIFEST s’il n’existe pas de MANIFEST.in , tel qu’il en avait l’habitude.

Le modèle de manifeste possède une commande par ligne, où chaque commande spécifie un ensemble de fichiers à inclure ou à exclure de la distribution source. Par exemple, regardons à nouveau le propre manifeste de Distutils :

include *.txt
recursive-include examples *.txt *.py
prune examples/sample?/build

La signification est assez claire : inclure tous les fichiers à la racine de la distribution correspondant à *.txt, tous les fichiers n’importe où dans le dossier examples correspondant à *.txt ou *.py, et exclure tous les dossiers correspondant à examples/sample?/build. Tout ceci est fait après l’ensemble d’inclusions standard, vous pouvez donc exclure des fichiers précédemment inclus en utilisant une instruction explicite dans le manifeste. (Vous pouvez aussi utiliser l’option --no-defaults pour désactiver complètement les inclusions standards). Il existe d’autres commandes dans le langage du fichier manifeste, consultez le chapitre Créer une distribution source: la commande sdist.

L’ordre des commandes dans le modèle manifeste compte : nous avons, à la base, la liste de fichiers par défaut telle que décrite plus haut. Ensuite, chaque commande du modèle ajoute ou supprime des fichiers de cette liste. Une fois que le traitement du manifeste modèle est fini, nous enlevons les fichiers qui ne doivent pas être inclus dans la distribution source :

tous les fichiers dans l’arborescence de build de Distutils (par défaut build/)

tous les fichiers dans les dossiers nommés RCS, CVS, .svn, .hg, .git, .bzr ou _darcs

Maintenant nous avons notre liste complète de fichiers ; elle est désormais écrite dans le manifeste pour une utilisation future et sera utilisée pour construire la ou les archive(s) de notre distribution source.

Vous pouvez désactiver l’ensemble des fichiers inclus par défaut en utilisant l’option --no-defaults, ainsi que désactiver les exclusions standards avec l’option --no-prune.

Voici le manifeste modèle de Distutils, suivons comment la commande sdist construit la liste des fichiers à inclure dans la distribution source de Distutils.

inclure tous les fichiers source Python dans les sous-dossiers distutils et distutils/command (parce que des paquets correspondant à ces deux dossiers ont été mentionnés dans l’argument packages du script d’installation — voir le chapitre Writing the Setup Script)

inclure README.txt, setup.py et setup.cfg (fichiers standards)

inclure test/test*.py (fichiers standard)

inclure *.txt à la racine de la distribution (ceci trouve README.txt une seconde fois, mais les redondances sont supprimées plus tard)

inclure tout fichier de la forme *.txt ou *.py dans la sous-arborescence de examples,

exclure tous les fichiers dans les sous-arborescences dont les dossiers racines sont de la forme examples/sample?/build— Ceci peut exclure des fichiers inclus dans les étapes précédentes, il est donc important que la commande prune dans le manifeste modèle vienne après la commande recursive-include

exclure l’arborescence de build ainsi que les dossiers RCS, CVS, .svn, .hg, .git, .bzr et _darcs

Comme dans le script de préparation, les chemins des fichiers et des dossiers dans le manifeste modèle doivent toujours être séparés par des barres obliques (slash en anglais) ; Distutils s’occupe de les convertir à la représentation standard de votre plateforme. De cette manière, le manifeste modèle est portable sur tout système d’exploitation.

4.2. Options pour le manifeste

L’ordre normal des opérations pour la commande sdist est le suivant :

si le fichier manifeste (MANIFEST par défaut) existe et que la première ligne n’a pas de commentaire indiquant qu’il a été généré par MANIFEST.in, alors il est utilisé tel quel, inchangé

si le manifeste n’existe pas ou s’il a été généré automatiquement, lire MANIFEST.in et créer le manifeste

s’il n’existe ni MANIFEST, ni MANIFEST.in, alors créer un manifeste contenant uniquement le groupe de fichiers par défaut

utiliser maintenant la liste de fichiers de MANIFEST (qu’il ait été généré ou lu) pour créer la ou les archive(s) de la distribution source

Il existe deux manières pour modifier ce comportement. D’abord utilisez les options --no-defaults et --no-prune pour désactiver les inclusions et exclusions standards.

Ensuite, si vous ne voulez que (ré)générer le manifeste, mais pas créer la distribution source :

python setup.py sdist --manifest-only

L’option -o est un raccourci pour l’option --manifest-only.

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5. Créer une distribution compilée

Une « distribution compilée » vous fait surement penser à un « paquet binaire » ou à un « installateur » (tout dépend de votre environnement). Ce n’est cependant pas forcément un binaire, il peut ne contenir que des sources Python et / ou du byte-code ; et nous n’appelons pas ça un package parce que ce mot est déjà utilisé dans Python (et « installateur » est un terme spécifique au monde des systèmes de bureau).

Une distribution compilée est une manière de rendre la vie plus facile à ceux qui installent votre module : pour les utilisateurs de système Linux basé sur RPM, ce sera des binaires RPM ; pour les utilisateurs de Windows, c’est un installateur exécutable ; pour les utilisateurs de Linux basés sur Debian, c’est un paquet Debian ; et ainsi de suite. Évidemment, personne n’est capable de créer une distribution compilée pour toutes les plateformes existantes, donc Distutils est fait pour permettre aux développeurs de se concentrer sur leurs spécialités — écrire du code et créer des distributions source — pendant que d’autres, appelés packagers s’occupent de transformer les sources en paquets pour chaque plateforme.

Of course, the module developer could be their own packager; or the packager could be a volunteer « out there » somewhere who has access to a platform which the original developer does not; or it could be software periodically grabbing new source distributions and turning them into built distributions for as many platforms as the software has access to. Regardless of who they are, a packager uses the setup script and the bdist command family to generate built distributions.

Pour prendre un exemple simple, si je lance la commande suivante dans les sources de Distutils :

python setup.py bdist

alors Distutils construit ma distribution du module (Distutils lui-même dans ce cas), fait une « fausse » installation (aussi dans le dossier build) et crée le type de distribution compilée par défaut pour ma plateforme. Le format par défaut est un « bête » fichier tar pour Unix et un simple installateur exécutable pour Windows (ce fichier tar est considéré comme « bête » car il doit être décompressé à un endroit précis pour fonctionner).

Par conséquent, la commande si dessus crée le fichier Distutils-1.0.plat.tar.gz sur les systèmes Unix ; décompresser cette archive tar au bon endroit installe Distutils exactement comme si vous aviez téléchargé la distribution source et lancé python setup.py install (le « bon endroit » est soit la racine du système de fichier, ou le dossier de Python prefix, tout dépend des options données à la commande bdist_dumb ; la valeur par défaut est de créer une distribution « bête » relative à prefix).

Évidemment, pour une distribution en Python pur, ce n’est pas aussi simple que de simplement lancer python setup.py install—mais pour une distribution non-pure qui inclut des extensions qui devraient être compilées, ça peut faire la différence entre quelqu’un qui sera capable d’utiliser votre extension, ou non. De plus créer une distribution compilée « intelligente » tel qu’un paquet RPM ou un installateur exécutable Windows, est bien plus pratique pour les utilisateurs, même si votre module n’inclut aucune extension.

La commande bdist a l’option --formats, similaire à la commande sdist, que vous pouvez utiliser pour sélectionner le type de distribution compilée à générer : par exemple,

python setup.py bdist --format=zip

serait, lors d’une exécution sur un système Unix, crée Distutils-1.0.plat.zip—à nouveau, cette archive devra être décompressé depuis la racine pour installer Distutils.

Les formats disponibles pour les distributions compilées sont :

Format

Description

Notes

gztar

fichier tar gzippé (.tar.gz)

(1)

bztar

fichier tar de type bzipped (.tar.bz2)

xztar

fichier tar de type xzipped (.tar.xz)

ztar

fichier tar compressé par compress (.tar.Z)

(3)

tar

fichier tar (.tar)

zip

fichier zip (.zip)

(2),(4)

rpm

RPM

(5)

pkgtool

Solaris pkgtool

sdux

HP-UX swinstall

wininst

fichier zip auto-extracteur Windows

(4)

msi

Installateur Microsoft.

Modifié dans la version 3.5: Ajout du support des fichiers xztar.

Notes :

par défaut sur Unix

par défaut sur Windows

nécessite un programme externe compress.

nécessite soit un utilitaire zip extérieur ou le module zipfile (inclut dans la bibliothèque standard depuis Python 1.6)

nécessite un programme externe rpm, version 3.0.4 ou mieux (utilisez rpm --version pour connaître quelle version vous avez)

Vous ne devez pas utiliser la commande bdist avec l’option --formats ; Vous pouvez également utiliser la commande qui implémente directement le format qui vous intéresse. Certaines de ces « sous-commandes » bdist génèrent plusieurs formats similaires ; par exemple, La commande bdist_dumb génère les archives aux formats « bêtes » (tar, gztar, bztar, xztar, ztar, et zip), et bdist_rpm génère les binaires RPM et ainsi que les sources. Les sous-commandes bdist, et les formats générés par chacun, sont :

Commande

Formats

bdist_dumb

tar, gztar, bztar, xztar, ztar, zip

bdist_rpm

rpm, srpm

bdist_wininst

wininst

bdist_msi

msi

Le chapitre suivant donne des détails individuel sur les commandes bdist_*.

5.1. Créer un paquet RPM

Le format RPM est utilisé par beaucoup de distributions Linux populaires, incluant Red Hat, SuSE et Mandrake. Si l’une d’entre elle (ou n’importe quelle autre distribution basé sur RPM) est votre environnement habituel, créer un paquet pour les autres utilisateur de ces distributions est trivial. Cela dépend de la complexité de votre module et des différences entre les distributions Linux, vous pourrez aussi créer des RPM qui fonctionneront sur des distributions RPM différentes.

La manière habituelle de créer un RPM de votre module est d’utiliser la commande bdist_rpm :

python setup.py bdist_rpm

ou la commande bdist avec l’option --format :

python setup.py bdist --formats=rpm

La première vous permet de spécifier des options spécifiques à RPM ; la dernière vous permet de spécifier plusieurs formats d’un seul coup. Si vous avez besoin d’utiliser les deux, vous pouvez explicitement spécifier plusieurs commandes bdist_* et leurs options :

python setup.py bdist_rpm --packager="John Doe <jdoe@example.org>" \
                bdist_wininst --target-version="2.0"

La création de Package RPM est configurée par un fichier .spec, un peu comme Distutils est configuré par script setup.py. Pour vous faciliter la tâche, la commande bdist_rpm crée normalement un fichier .spec basé sur les informations que vous fournissez dans setup.py, dans les options de la ligne de commande et dans la configuration de Distutils. Beaucoup d’options du fichier .spec sont dérivées des options du script de préparation suivant :

Option de fichier RPM .spec

Options du script de préparation Distutils

Nom

name

Summary (dans le préambule)

description

Version

version

Vendor

author et author_email, ou — & maintainer et maintainer_email

Copyright

license

Url

url

%description (section)

long_description

De plus, il y a beaucoup d’options dans le fichier .spec qui n’ont aucun équivalent dans le script de préparation. La plupart de celles ci sont gérées par les options de la commande bdist_rpm suivant :

Option de fichier RPM .spec

Option de bdist_rpm

valeur par défaut

Version

release

« 1 »

Group

group

« Développement/Bibliothèques »

Vendor

vendor

(voir au-dessus)

Packager

packager

(none)

Provides

provides

(none)

Requires

requires

(none)

Conflicts

conflicts

(none)

Obsoletes

obsoletes

(none)

Distribution

distribution_name

(none)

BuildRequires

build_requires

(none)

Icon

icon

(none)

Fournir ces options en ligne de commande est fastidieux et sujet à des erreurs, il est donc recommandé de les mettre dans un fichier de configuration. setup.cfg— voir la section Writing the Setup Configuration File. Si vous distribuez ou empaquetez beaucoup de modules de distribution Python, vous pourriez vouloir mettre les options qui s’appliquent à tous vos projets dans votre fichier de configuration personnel Distutils (~/.pydistutils.cfg). Si vous voulez temporairement désactiver ce fichier, vous pouvez passer l’option --no-user-cfg à setup.py.

La création de binaire RPM se fait en trois étapes, chacune gérée automatiquement par Distutils :

crée un fichier .spec qui décrit le paquet (comme le script de préparation Distutils, en réalité la plupart des informations du script de préparation se retrouve dans le fichier .spec)

crée un RPM source

crée le RPM « binaire » (qui peut ou non contenir des binaires, tout dépend de si votre module contiens des extensions)

Normalement, RPM réunit les deux dernières étapes ensemble ; quand vous utilisez Distutils, les trois étapes sont regroupées.

Si vous le souhaitez, vous pouvez séparer ces trois étapes. Vous pouvez utiliser l’option --spec-only pour faire en sorte que la commande bdist_rpm crée juste le fichier .spec et quitte ; dans ce cas, le fichier .spec sera écrit dans le dossier de distribution (« distribution directory ») — normalement dist/, mais personnalisable avec l’option --dist-dir. (Normalement, le fichier .spec se retrouve profondément enfoui dans l’arborescence, dans un dossier temporaire créé par la commande bdist_rpm.)

5.2. Créer un installateur Windows

Les installateurs exécutables sont le format naturel pour les distributions sur Windows. Ils affichent une jolie interface graphique, montrent quelques informations à propos du module qui va être installé, tiré des métadonnées dans le script de préparation, laisse l’utilisateur choisir quelques options et démarrer ou annuler l’installation.

Étant donné que les métadonnées sont tirées du script de préparation, créer un installateur Windows est généralement facile, il suffit de lancer :

python setup.py bdist_wininst

ou la commande bdist avec l’option --formats :

python setup.py bdist --formats=wininst

Si vous avez un module pur (contenant seulement des modules et des packages en Python pur), l’installateur final ne sera lié a aucune version de Python et aura un nom du type foo-1.0.win32.exe. Ces installateurs peuvent même être créés sur les plateformes Unix ou Mac OS X.

Si vous avez une distribution « non-pure », l’extension peut être créée uniquement pour les plateformes Windows et sera lié à une version de Python. Le nom de l’installateur reflétera ça et sera de format foo-1.0.win32-py2.0.exe. Vous devrez créer un installateur pour chaque version de Python que vous voulez supporter.

L’installeur essaiera de compiler les modules purs en bytecode après installation sur le système cible dans les modes normaux et optimisé. Si vous ne voulez pas que ce soit fait, vous pouvez lancer la commande bdist_wininst avec l’option --no-target-compile et/ou l’option --no-target-optimize.

Par défaut l’installateur affichera le super logo « Python Powered », mais vous pouvez aussi donnez votre propre bitmap de 152x261 qui doit être un fichier .bmp Windows avec l’option --bitmap.

L’installateur affichera aussi un grand titre en arrière plan de la fenêtre quand exécuté, qui est composé du nom de votre distribution et du numéro de version. Cela peut être changé avec un autre texte avec l’option --title.

Le fichier d’installation sera écrit dans le dossier de distribution (« distribution directory ») — normalement dist/, mais personnalisable avec l’option --dist-dir.

5.3. Compiler pour toute les plateformes Windows

Depuis Python 2.6, distutils est capable de compiler pour toutes les plateformes de Windows. En pratique, cela signifie qu’avec les bons outils installés, vous pouvez utiliser une version 32 bits de Windows pour créer une extension 64 bits et vice-versa.

To build for an alternate platform, specify the --plat-name option to the build command. Valid values are currently “win32”, “win-amd64” and “win-ia64”. For example, on a 32bit version of Windows, you could execute:

python setup.py build --plat-name=win-amd64

pour construire une version 64 bits de votre module. L’installateur Windows supporte aussi cette option, donc la commande :

python setup.py build --plat-name=win-amd64 bdist_wininst

créera un installateur exécutable 64 bits depuis votre version 32 bits de Windows.

Pour compiler pour toute les versions de Windows, vous devez télécharger le code source de Python et de le compiler pour la plateforme choisie - il est impossible de le faire depuis une installation de Python (vu que les fichiers .lib pour les autres plateformes ne sont pas inclut). En pratique, cela veut dire qu’un utilisateur de systeme 32 bits devra utiliser Visual Studio 2008 pour ouvrir la solution PCBuild/PCbuild.sln dans l’arborescence des sources de Python et construire la version « x64 » du projet « pythoncore » avant de pouvoir compiler son extension.

Remarquez que par défaut Visual Studio 2008 n’installe pas les outils et compilateur 64 bits. Vous devrez peut-être ré-exécuter le processus d’installation et sélectionner ces outils (utiliser le Panneau de Contrôle -> [Ajouter/Supprimer] est un bon moyen de vérifier ou modifier votre installation existante.)

5.3.1. Le script de post-installation

Depuis Python 2.3, un script post-installation peut être spécifié avec l’option --install-script. Le nom du script doit être spécifié et présent dans l’argument « scripts » de la fonction setup.

Ce script doit être lancé au moment de l’installation sur le système cible après que tous les fichiers ont été copiés, avec la valeur de argv[1] à -install, et une autre fois durant la désinstallation avant que les fichiers soient supprimés avec la valeur de argv[1] à -remove.

Le script d’installation s’exécute intégré à la fenêtre d’installation, chaque sortie (sys.stdout, sys.stderr) est redirigé dans le tampon et sera affiché dans le GUI après que les scripts soient finis.

Certaines fonctions spécialement utiles dans ce contexte sont disponibles comme fonctions natives additionnelles dans le script d’installation.

directory_created(path)

file_created(path)

Ces fonctions peuvent être appelées lorsqu’un répertoire ou un fichier est crée par le script de post installation au moment de l’installation. Cela va enregistrer le chemin avec le des-installateur, de sorte qu’il soit retiré lors de la des-installation de la distribution. pour être sûr, les répertoires sont uniquement retirés s’ils sont vides.

get_special_folder_path(csidl_string)

Cette fonction peut être utilisée pour extraire des localisations de fichiers spéciaux sous Windows comme un menu démarrer ou le Bureau. Cela renvoie le chemin complet pour le fichier. csidl_string doit être unes des chaines suivantes :

"CSIDL_APPDATA"

"CSIDL_COMMON_STARTMENU"
"CSIDL_STARTMENU"

"CSIDL_COMMON_DESKTOPDIRECTORY"
"CSIDL_DESKTOPDIRECTORY"

"CSIDL_COMMON_STARTUP"
"CSIDL_STARTUP"

"CSIDL_COMMON_PROGRAMS"
"CSIDL_PROGRAMS"

"CSIDL_FONTS"

Si le fichier ne peut être extrait, OSError est obtenu..

Quel dossier est disponible dépend de la version exacte de Windows, et probablement aussi de la configuration. pour des détails se référer à la documentation Microsoft de la fonction SHGetSpecialFolderPath().

create_shortcut(target, description, filename[, arguments[, workdir[, iconpath[, iconindex]]]])

Cette fonction crée un raccourci. cible est le chemin au programme auquel mène le raccourci. description est la description du raccourci. nomfichier est le titre du raccourci que verra l’utilisateur. arguments spécifie les arguments de la ligne de commande, si existant. cheminRep est le répertoire de travail pour le programme. cheminIcone est le fichier contenant l’icône pour le raccourci, et IndexIcone est l’index pour l’icône dans le fichier cheminIcone. Encore, pour les détails consulter la documentation Microsoft pour l’interface ILienShell.

5.4. Contrôle d’accès utilisateur Vista (UAC)

Depuis Python 2.6, bdist_wininst accepte une option --user-access-control. Sa valeur par défaut est “none” (Ce qui veut dire que aucun UAC est fait), et les autres valeurs valides sont “auto” (ce qui veut dire qu’il faut demander une élévation de privilèges UAC si Python a été installé pour tous les utilisateurs) et “force” (Toujours demander une élévation de privilèges).

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6. L’index de paquets Python (Python Package Index : PyPI)

The Python Package Index (PyPI) [https://pypi.org] stores meta-data describing distributions packaged with distutils, as well as package data like distribution files if a package author wishes.

Distutils provides the register and upload commands for pushing meta-data and distribution files to PyPI, respectively. See Distutils commands for information on these commands.

6.1. PyPI overview

PyPI lets you submit any number of versions of your distribution to the index. If you alter the meta-data for a particular version, you can submit it again and the index will be updated.

PyPI holds a record for each (name, version) combination submitted. The first user to submit information for a given name is designated the Owner of that name. Changes can be submitted through the register command or through the web interface. Owners can designate other users as Owners or Maintainers. Maintainers can edit the package information, but not designate new Owners or Maintainers.

By default PyPI displays only the newest version of a given package. The web interface lets one change this default behavior and manually select which versions to display and hide.

For each version, PyPI displays a home page. The home page is created from the long_description which can be submitted via the register command. See PyPI package display for more information.

6.2. Distutils commands

Distutils exposes two commands for submitting package data to PyPI: the register command for submitting meta-data to PyPI and the upload command for submitting distribution files. Both commands read configuration data from a special file called a .pypirc file.

6.2.1. The register command

The distutils command register is used to submit your distribution’s meta-data to an index server. It is invoked as follows:

python setup.py register

Distutils will respond with the following prompt:

running register
We need to know who you are, so please choose either:
    1. use your existing login,
    2. register as a new user,
    3. have the server generate a new password for you (and email it to you), or
    4. quit
Your selection [default 1]:

Note: if your username and password are saved locally, you will not see this menu. Also, refer to The .pypirc file for how to store your credentials in a .pypirc file.

If you have not registered with PyPI, then you will need to do so now. You should choose option 2, and enter your details as required. Soon after submitting your details, you will receive an email which will be used to confirm your registration.

Once you are registered, you may choose option 1 from the menu. You will be prompted for your PyPI username and password, and register will then submit your meta-data to the index.

See Additional command options for options to the register command.

6.2.2. The upload command

The distutils command upload pushes the distribution files to PyPI.

The command is invoked immediately after building one or more distribution files. For example, the command

python setup.py sdist bdist_wininst upload

will cause the source distribution and the Windows installer to be uploaded to PyPI. Note that these will be uploaded even if they are built using an earlier invocation of setup.py, but that only distributions named on the command line for the invocation including the upload command are uploaded.

If a register command was previously called in the same command, and if the password was entered in the prompt, upload will reuse the entered password. This is useful if you do not want to store a password in clear text in a .pypirc file.

You can use the --sign option to tell upload to sign each uploaded file using GPG (GNU Privacy Guard). The gpg program must be available for execution on the system PATH. You can also specify which key to use for signing using the --identity=name option.

See Additional command options for additional options to the upload command.

6.2.3. Additional command options

This section describes options common to both the register and upload commands.

The --repository or -r option lets you specify a PyPI server different from the default. For example:

python setup.py sdist bdist_wininst upload -r https://example.com/pypi

For convenience, a name can be used in place of the URL when the .pypirc file is configured to do so. For example:

python setup.py register -r other

See The .pypirc file for more information on defining alternate servers.

The --show-response option displays the full response text from the PyPI server, which is useful when debugging problems with registering and uploading.

6.2.4. The .pypirc file

The register and upload commands both check for the existence of a .pypirc file at the location $HOME/.pypirc. If this file exists, the command uses the username, password, and repository URL configured in the file. The format of a .pypirc file is as follows:

[distutils]
index-servers =
    pypi

[pypi]
repository: <repository-url>
username: <username>
password: <password>

The distutils section defines an index-servers variable that lists the name of all sections describing a repository.

Each section describing a repository defines three variables:

repository, that defines the url of the PyPI server. Defaults to

https://upload.pypi.org/legacy/.

username, which is the registered username on the PyPI server.

password, that will be used to authenticate. If omitted the user

will be prompt to type it when needed.

If you want to define another server a new section can be created and listed in the index-servers variable:

[distutils]
index-servers =
    pypi
    other

[pypi]
repository: <repository-url>
username: <username>
password: <password>

[other]
repository: https://example.com/pypi
username: <username>
password: <password>

This allows the register and upload commands to be called with the --repository option as described in Additional command options.

Specifically, you might want to add the PyPI Test Repository [https://wiki.python.org/moin/TestPyPI] to your .pypirc to facilitate testing before doing your first upload to PyPI itself.

6.3. PyPI package display

The long_description field plays a special role at PyPI. It is used by the server to display a home page for the registered package.

If you use the reStructuredText [http://docutils.sourceforge.net/rst.html] syntax for this field, PyPI will parse it and display an HTML output for the package home page.

The long_description field can be attached to a text file located in the package:

from distutils.core import setup

with open('README.txt') as file:
    long_description = file.read()

setup(name='Distutils',
      long_description=long_description)

In that case, README.txt is a regular reStructuredText text file located in the root of the package besides setup.py.

To prevent registering broken reStructuredText content, you can use the rst2html program that is provided by the docutils package and check the long_description from the command line:

$ python setup.py --long-description | rst2html.py > output.html

docutils will display a warning if there’s something wrong with your syntax. Because PyPI applies additional checks (e.g. by passing --no-raw to rst2html.py in the command above), being able to run the command above without warnings does not guarantee that PyPI will convert the content successfully.

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7. Exemples

This chapter provides a number of basic examples to help get started with distutils. Additional information about using distutils can be found in the Distutils Cookbook.

Voir aussi

Distutils Cookbook [https://wiki.python.org/moin/Distutils/Cookbook]

Collection of recipes showing how to achieve more control over distutils.

7.1. Pure Python distribution (by module)

If you’re just distributing a couple of modules, especially if they don’t live in a particular package, you can specify them individually using the py_modules option in the setup script.

In the simplest case, you’ll have two files to worry about: a setup script and the single module you’re distributing, foo.py in this example:

<root>/
        setup.py
        foo.py

(In all diagrams in this section, <root> will refer to the distribution root directory.) A minimal setup script to describe this situation would be:

from distutils.core import setup
setup(name='foo',
      version='1.0',
      py_modules=['foo'],
      )

Note that the name of the distribution is specified independently with the name option, and there’s no rule that says it has to be the same as the name of the sole module in the distribution (although that’s probably a good convention to follow). However, the distribution name is used to generate filenames, so you should stick to letters, digits, underscores, and hyphens.

Since py_modules is a list, you can of course specify multiple modules, eg. if you’re distributing modules foo and bar, your setup might look like this:

<root>/
        setup.py
        foo.py
        bar.py

and the setup script might be

from distutils.core import setup
setup(name='foobar',
      version='1.0',
      py_modules=['foo', 'bar'],
      )

You can put module source files into another directory, but if you have enough modules to do that, it’s probably easier to specify modules by package rather than listing them individually.

7.2. Pure Python distribution (by package)

If you have more than a couple of modules to distribute, especially if they are in multiple packages, it’s probably easier to specify whole packages rather than individual modules. This works even if your modules are not in a package; you can just tell the Distutils to process modules from the root package, and that works the same as any other package (except that you don’t have to have an __init__.py file).

The setup script from the last example could also be written as

from distutils.core import setup
setup(name='foobar',
      version='1.0',
      packages=[''],
      )

(The empty string stands for the root package.)

If those two files are moved into a subdirectory, but remain in the root package, e.g.:

<root>/
        setup.py
        src/      foo.py
                  bar.py

then you would still specify the root package, but you have to tell the Distutils where source files in the root package live:

from distutils.core import setup
setup(name='foobar',
      version='1.0',
      package_dir={'': 'src'},
      packages=[''],
      )

More typically, though, you will want to distribute multiple modules in the same package (or in sub-packages). For example, if the foo and bar modules belong in package foobar, one way to layout your source tree is

<root>/
        setup.py
        foobar/
                 __init__.py
                 foo.py
                 bar.py

This is in fact the default layout expected by the Distutils, and the one that requires the least work to describe in your setup script:

from distutils.core import setup
setup(name='foobar',
      version='1.0',
      packages=['foobar'],
      )

If you want to put modules in directories not named for their package, then you need to use the package_dir option again. For example, if the src directory holds modules in the foobar package:

<root>/
        setup.py
        src/
                 __init__.py
                 foo.py
                 bar.py

an appropriate setup script would be

from distutils.core import setup
setup(name='foobar',
      version='1.0',
      package_dir={'foobar': 'src'},
      packages=['foobar'],
      )

Or, you might put modules from your main package right in the distribution root:

<root>/
        setup.py
        __init__.py
        foo.py
        bar.py

in which case your setup script would be

from distutils.core import setup
setup(name='foobar',
      version='1.0',
      package_dir={'foobar': ''},
      packages=['foobar'],
      )

(The empty string also stands for the current directory.)

If you have sub-packages, they must be explicitly listed in packages, but any entries in package_dir automatically extend to sub-packages. (In other words, the Distutils does not scan your source tree, trying to figure out which directories correspond to Python packages by looking for __init__.py files.) Thus, if the default layout grows a sub-package:

<root>/
        setup.py
        foobar/
                 __init__.py
                 foo.py
                 bar.py
                 subfoo/
                           __init__.py
                           blah.py

then the corresponding setup script would be

from distutils.core import setup
setup(name='foobar',
      version='1.0',
      packages=['foobar', 'foobar.subfoo'],
      )

7.3. Single extension module

Extension modules are specified using the ext_modules option. package_dir has no effect on where extension source files are found; it only affects the source for pure Python modules. The simplest case, a single extension module in a single C source file, is:

<root>/
        setup.py
        foo.c

If the foo extension belongs in the root package, the setup script for this could be

from distutils.core import setup
from distutils.extension import Extension
setup(name='foobar',
      version='1.0',
      ext_modules=[Extension('foo', ['foo.c'])],
      )

If the extension actually belongs in a package, say foopkg, then

With exactly the same source tree layout, this extension can be put in the foopkg package simply by changing the name of the extension:

from distutils.core import setup
from distutils.extension import Extension
setup(name='foobar',
      version='1.0',
      ext_modules=[Extension('foopkg.foo', ['foo.c'])],
      )

7.4. Checking a package

The check command allows you to verify if your package meta-data meet the minimum requirements to build a distribution.

To run it, just call it using your setup.py script. If something is missing, check will display a warning.

Let’s take an example with a simple script:

from distutils.core import setup

setup(name='foobar')

Running the check command will display some warnings:

$ python setup.py check
running check
warning: check: missing required meta-data: version, url
warning: check: missing meta-data: either (author and author_email) or
         (maintainer and maintainer_email) must be supplied

If you use the reStructuredText syntax in the long_description field and docutils [http://docutils.sourceforge.net] is installed you can check if the syntax is fine with the check command, using the restructuredtext option.

For example, if the setup.py script is changed like this:

from distutils.core import setup

desc = """\
My description
==============

This is the description of the ``foobar`` package.
"""

setup(name='foobar', version='1', author='tarek',
    author_email='tarek@ziade.org',
    url='http://example.com', long_description=desc)

Where the long description is broken, check will be able to detect it by using the docutils parser:

$ python setup.py check --restructuredtext
running check
warning: check: Title underline too short. (line 2)
warning: check: Could not finish the parsing.

7.5. Reading the metadata

The distutils.core.setup() function provides a command-line interface that allows you to query the metadata fields of a project through the setup.py script of a given project:

$ python setup.py --name
distribute

This call reads the name metadata by running the distutils.core.setup() function. Although, when a source or binary distribution is created with Distutils, the metadata fields are written in a static file called PKG-INFO. When a Distutils-based project is installed in Python, the PKG-INFO file is copied alongside the modules and packages of the distribution under NAME-VERSION-pyX.X.egg-info, where NAME is the name of the project, VERSION its version as defined in the Metadata, and pyX.X the major and minor version of Python like 2.7 or 3.2.

You can read back this static file, by using the distutils.dist.DistributionMetadata class and its read_pkg_file() method:

>>> from distutils.dist import DistributionMetadata
>>> metadata = DistributionMetadata()
>>> metadata.read_pkg_file(open('distribute-0.6.8-py2.7.egg-info'))
>>> metadata.name
'distribute'
>>> metadata.version
'0.6.8'
>>> metadata.description
'Easily download, build, install, upgrade, and uninstall Python packages'

Notice that the class can also be instantiated with a metadata file path to loads its values:

>>> pkg_info_path = 'distribute-0.6.8-py2.7.egg-info'
>>> DistributionMetadata(pkg_info_path).name
'distribute'

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8. Extension de Distutils

Distutils peut être étendu de multiples façons. La plupart des extensions sont soit des nouvelles commandes soit des remplacements de commandes existantes. De nouvelles commandes pourraient par exemple servir à l’empaquetage pour des plateformes spécifiques tandis que des remplacements peuvent modifier certains aspects des commandes existantes.

La plupart des extensions de distutils sont faites dans le script setup.py. La plupart ajoutent simplement quelques extensions de fichiers qui devraient être copiés dans le paquet en plus des fichiers .py.

La plupart des implémentations des commandes distutils sont des sous-classes de distutils.cmd.Command. Les nouvelles commandes peuvent hériter directement de Command, alors que les remplacements dérivent souvent de Command indirectement, directement sous-classant la commande qu’ils remplacent. Les commandes doivent dériver de la classe Command.

8.1. Intégrer de nouvelles commandes

Il y a différentes façons d’intégrer de nouvelles implémentations de commandes dans distutils. La plus difficile est de faire pression pour inclure une nouvelle fonctionnalité dans distutils même, et d’attendre (et demander) une version de Python l’implémentant. C’est très difficile pour beaucoup de raisons.

La plus commune, et possiblement la plus raisonnable pour la plupart des cas, est d’inclure les nouvelles implémentations dans votre fichier setup.py, et de faire en sorte que la fonction distutils.core.setup() les utilise :

from distutils.command.build_py import build_py as _build_py
from distutils.core import setup

class build_py(_build_py):
    """Specialized Python source builder."""

    # implement whatever needs to be different...

setup(cmdclass={'build_py': build_py},
      ...)

Cette approche est la plus valable si les nouvelles implémentations doivent être utilisées pour utiliser un paquet particulier, vu que toutes les personnes intéressées par le paquet devront avoir ces nouvelles implémentations de commandes.

Depuis Python 2.4, une troisième option est disponible, prévue pour permettre d’ajouter de nouvelles commandes compatibles avec le script existant setup.py sans avoir besoin de modifier l’installation Python. C’est fait pour que les extensions tierces puissent rester compatibles avec d’autres systèmes d’empaquetage, mais les commandes peuvent être utilisées pour tout ce que les commandes de distutils peuvent faire. Une nouvelle option de configuration, command_packages (option shell --command-packages), peut être utilisée pour spécifier des recherches de paquets additionnels pour des modules qui implémentent des commandes. Comme toutes les options distutils, cela peut être spécifié en ligne de commande ou dans un fichier de configuration. Cette option peut être fixée dans la section [global] d’un fichier de configuration, ou avant n’importe quelle commande dans un shell. Si définie dans un fichier de configuration, elle peut être écrasée depuis la ligne de commande. Mettre une chaine de caractères vide en valeur de cette option forcera l’utilisation de la valeur par défaut. Cela ne devrait jamais être fixé dans un fichier de configuration donné avec un paquet.

Cette nouvelle option peut être utilisée pour ajouter n’importe quel nombre de paquet à la liste des paquets recherchés pour les implémentations de commandes ; plusieurs noms de paquets doivent être séparés par des virgules. Quand non spécifié, la recherche est seulement faite dans le paquet distutils.command. Cependant, lorsque setup.py est lancé avec l’option --command-packages distcmds,buildcmds, les paquets distutils.command, distcmds, et buildcmds seront cherchés dans cet ordre. Il est attendu des nouvelles commandes d’être implémentées en modules du même nom que la commande en utilisant des classes partageant le même nom. Comme dans l’exemple shell donné ci-dessus, la commande bdist_openpkg pourrait être implémentée avec la classe distcmds.bdist_openpkg.bdist_openpkg ou buildcmds.bdist_openpkg.bdist_openpkg.

8.2. Ajout de nouveaux types de distribution

Les commandes qui créent des distributions (fichiers dans le dossier dist/) doivent ajouter la paire (command, filename) à self.distribution.dist_files pour que upload puisse publier sur PyPI. Le nom de fichier (filename) dans la paire ne contiens pas de chemin, juste le nom du fichier lui-même. En mode dry-run, les paires doivent toujours être ajoutées pour représenter ce qui aurait été créé.

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9. Référence des commandes

9.1. Installer des modules: la famille de commande install

La commande d’installation s’assure que la commande de construction a bien été lancé puis lance les sous-commandes install_lib, install_data et install_scripts.

9.1.1. install_data

Cette commande installe tous les fichiers fournis avec la distribution.

9.1.2. install_scripts

Cette commande installe tout les scripts (Python) dans la distribution.

9.2. Créer une distribution source: la commande sdist

Les commandes du modèle manifeste sont :

Commande

Description

include pat1 pat2 ...

Inclut tous les fichiers ressemblant aux modèles listés

exclude pat1 pat2 ...

exclut tous les fichiers ressemblant aux modèles listés

recursive-include dir pat1 pat2 ...

inclut récursivement tous les fichiers sous dir ressemblant aux modèles listés

recursive-exclude dir pat1 pat2 ...

exclut tous les fichiers sous dir ressemblant aux modèles listés

global-include pat1 pat2 ...

Inclut tous les fichiers dans l’arborescence ressemblant aux modèles listés

global-exclude pat1 pat2 ...

exclut tous les fichiers dans l’arborescence ressemblant aux modèles listés

prune dir

exclut tous les fichiers dans dir

graft dir

inclut tous les fichiers dans dir

Les modèles sont de style Unix glob : * correspond à n’importe quelle chaîne de caractères d’un nom de fichier valide, ? correspond à un seul caractère d’un nom de fichier valide et [range] correspond à n’importe quel caractère dans la range (e.g., a-z, a-zA-Z, a-f0-9_.). La définition de « caractère de nom de fichier valide » est spécifique à chaque plateforme: sur Unix il s’agir de n’importe quel caractère à part le slash; sur Windows il s’agir de n’importe quel caractère a part l’anti-slash et les deux points.

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10. Référence de l’API

10.1. distutils.core — Fonctionnalités principales du module Distutils

Le module distutils.core est le seul module qui a besoin d’être installé pour utiliser Distutils. Il fournit le setup() (qui est appelé par le script setup.py). Il fournit indirectement les classes distutils.dist.Distribution et distutils.cmd.Command.

distutils.core.setup(arguments)

La fonction de base à tout faire qui fait presque tout ce dont vous pourriez attendre d’une méthode Distutils.

La fonction setup prend un grand nombre d’arguments. Ils sont présentés dans le tableau suivant.

nom de l’argument

valeur

type

name

Le nom du paquet

une chaîne de caractères

version

Le numéro de version du paquet, voir distutils.version

une chaîne de caractères

description

Une ligne unique décrivant le paquet

une chaîne de caractères

long_description

Une description plus longue du paquet

une chaîne de caractères

author

Le nom de l’auteur du paquet

une chaîne de caractères

author_email

L’adresse e-mail de l’auteur du paquet

une chaîne de caractères

maintainer

Le nom de l’actuel mainteneur, s’il est différent de l’auteur. Remarquez que si maintainer est fourni, distutils l’utilise à la place de author dans PKG-INFO.

une chaîne de caractères

maintainer_email

Le courriel de l’actuel mainteneur, si différent de l’auteur

une chaîne de caractères

url

Une URL pour le paquet (page d’accueil)

une chaîne de caractères

download_url

Une URL pour télécharger le paquet

une chaîne de caractères

packages

Une liste des paquets Python que distutils va manipuler

une liste de chaînes de caractères

py_modules

Une liste de modules Python que distutils va manipuler

une liste de chaînes de caractères

scripts

Une liste de scripts autonomes à construire et à installer

une liste de chaînes de caractères

ext_modules

Une liste des extensions Python à construire

une liste d’instances de distutils.core.Extension

classifiers

Une liste de catégories pour le paquet

une liste des chaînes de caractères, les classificateurs valides sont listés sur PyPI [https://pypi.org/pypi?:action=list_classifiers].

distclass

la classe Distribution à utiliser

une sous classe de distutils.core.Distribution

script_name

Le nom du script setup.py . Initialisé par sys.argv[0]

une chaîne de caractères

script_args

Arguments à fournir au script d’installation

une liste de chaînes de caractères

options

options par défaut pour le script d’installation

un dictionnaire

license

La licence pour le paquet

une chaîne de caractères

keywords

Méta-données descriptives, voir PEP 314 [https://www.python.org/dev/peps/pep-0314]

Une liste de chaînes de caractères ou une chaîne de caractère dont les éléments sont séparés par des virgules.

platforms

Une liste de chaînes de caractères ou une chaîne de caractère dont les éléments sont séparés par des virgules.

cmdclass

Un dictionnaire des noms de commandes et des sous-classes Command

un dictionnaire

data_files

Une liste de fichiers de données à installer

une liste

package_dir

Un dictionnaire des paquets et des noms de dossiers

un dictionnaire

distutils.core.run_setup(script_name[, script_args=None, stop_after='run'])

Exécute un script d’installation dans un environnement quelque peu contrôlé, et renvoie une instance distutils.dist.distribution qui contrôle l’exécution. Ceci est utile si vous avez besoin de connaître les méta-données de la distribution (passées sous forme d’arguments nommés de script à la fonction setup()), ou le contenu des fichiers de configuration ou de la ligne de commande.

script_name est un fichier qui sera lu et exécuté avec exec(). sys.argv[0] sera remplacé par script par la durée de l’appel. script_args est une liste de chaînes de caractères; si fourni, sys.argv[1:] sera remplacé par script_args pour la durée de l’appel.

stop_after dit à setup() quand s’arrêter; valeurs possibles:

valeur

description

init

S’arrête une fois que l’instance Distribution a été créée et renseignée avec les arguments-clés de setup()

config

S’arrête une fois que les fichiers de configuration ont été parcouru (et que leurs données ont été stockées dans l’instance Distribution)

commandline

S’arrête une fois que la ligne de commande (sys.argv[1:] ou script_args) a été parcouru (et les données stockées dans l’instance Distribution)

run

S’arrête une fois que toutes les commandes ont été exécutées (comme si setup() fût appelé de la manière habituelle). Ceci est la valeur par défaut.

De plus, le module distutils.core a exposé un nombre de classe qui existent ailleurs.

Extension du module distutils.extension

Command du module distutils.cmd

Distribution du module distutils.dist

Une courte description de chacune d’elle suit, mais consultez le module concerné pour une référence complète.

class distutils.core.Extension

La classe Extension décrit un seul module d’extension C ou C++ dans un script d’installation. Elle accepte dans son constructeur les arguments nommés suivants:

nom de l’argument

valeur

type

name

Le nom complet de l’extension, incluant n’importe quel paquet — c-à-d pas un nom de fichier ou de chemin mais un nom Python séparé par des points.

une chaîne de caractères

sources

list of source filenames, relative to the distribution root (where the setup script lives), in Unix form (slash-separated) for portability. Source files may be C, C++, SWIG (.i), platform-specific resource files, or whatever else is recognized by the build_ext command as source for a Python extension.

une liste de chaînes de caractères

include_dirs

liste des répertoires où chercher les fichiers d’entêtes C/C++ (en format Unix dans un souci de portabilité)

une liste de chaînes de caractères

define_macros

Liste de macros à définir ; chaque macro est définie à l’aide d’un couple (name, value), où value correspond soit à la chaîne sur laquelle la macro doit être définie, soit à None pour définir la macro sur aucune valeur particulière (équivalent à #define TRUC dans la source ou à -DTRUC dans la ligne de commande du compilateur C Unix.

une liste de tuples

undef_macros

Liste de macros à ignorer explicitement.

une liste de chaînes de caractères

library_dirs

Liste de répertoires à parcourir pour chercher les bibliothèques C/C++ lors de la phase d’édition de liens.

une liste de chaînes de caractères

libraries

Liste de noms de bibliothèques à lier à la compilation. Pas de noms de fichiers ou de chemin.

une liste de chaînes de caractères

runtime_library_dirs

Liste de répertoires à parcourir pour les bibliothèques C/C++ lors de la phase d’exécution. Pour les extensions partagées, c’est à ce moment que l’extension est chargée.

une liste de chaînes de caractères

extra_objects

Liste des fichiers supplémentaires à lier (par exemple les fichiers d’objets non explicités dans les “sources”, bibliothèque statique qui doit être explicitement spécifiée, fichiers de ressources binaires, etc. ).

une liste de chaînes de caractères

extra_compile_args

Toute information supplémentaire spécifique à la plate-forme et au compilateur à utiliser lors de la compilation des fichiers sources dans “sources”. Pour les plates-formes et les compilateurs où une ligne de commande a du sens, il s’agit généralement d’une liste d’arguments de ligne de commande, mais pour d’autres plates-formes, cela peut être n’importe quoi.

une liste de chaînes de caractères

extra_link_args

Toute information supplémentaire spécifique à la plate-forme et au compilateur à utiliser lors de la liaison de fichiers objets pour créer l’extension (ou pour créer un nouvel interpréteur Python statique). Interprétation similaire à celle de extra_compile_args.

une liste de chaînes de caractères

export_symbols

Liste des symboles à exporter à partir d’une extension partagée. N’est pas utilisé sur toutes les plates-formes et n’est généralement pas nécessaire pour les extensions Python, qui exportent généralement exactement un symbole : init + nom_de_l'extension.

une liste de chaînes de caractères

depends

Liste des fichiers dont dépend l’extension.

une liste de chaînes de caractères

language

Langage de l’extension (par exemple 'c', 'c++', 'objc'). Il sera détecté selon l’extension de la source s’il n’est pas précisé.

une chaîne de caractères

optional

Spécifie qu’un échec de compilation dans l’extension ne doit pas interrompre le processus de compilation, mais simplement ignorer l’extension.

un booléen

class distutils.core.Distribution

Une classe Distribution décrit comment compiler, installer et empaqueter un paquet logiciel Python.

Voir la fonction setup() pour une liste des arguments de mots-clés acceptés par le constructeur Distribution. setup() crée une instance de Distribution.

class distutils.core.Command

Une classe Command (ou plutôt une instance d’une de ses sous-classes) implémente une commande distutils unique.

10.2. distutils.ccompiler — Classe de base CCompiler

Ce module fournit la classe de base abstraite pour les classes CCompiler. Une instance de CCompiler peut être utilisée pour toutes les étapes de compilation et de liaison nécessaires à la compilation d’un projet unique. Des méthodes sont fournies pour définir des options pour le compilateur — définitions de macros, inclusion des répertoires, des chemins de liens, des bibliothèques, etc.

Ce module fournit les fonctions suivantes.

distutils.ccompiler.gen_lib_options(compiler, library_dirs, runtime_library_dirs, libraries)

Génère des options de liaison pour chercher dans les répertoires des bibliothèques et pour effectuer les liaisons avec des bibliothèques spécifiques. libraries et library_dirs sont, respectivement, des listes de noms de bibliothèques (pas de noms de fichiers !) et de répertoires à rechercher. Renvoie une liste d’options de ligne de commande utilisables avec certains compilateurs (en fonction des deux chaînes de format transmises).

distutils.ccompiler.gen_preprocess_options(macros, include_dirs)

Génère les options du préprocesseur C (-D, -U, -I) utilisées par au moins deux types de compilateurs : les compilateurs type Unix et Visual C++. macros est une liste de couples où (name,) est traité comme non définie (-U); (name, value) est traité comme définie (-D). include_dirs est la liste de noms de répertoires à ajouter au chemin de recherche du fichier d’en-tête (-I). Renvoie une liste d’options de ligne de commande pour les compilateurs Unix ou Visual C+++.

distutils.ccompiler.get_default_compiler(osname, platform)

Détermine le compilateur par défaut a utiliser par une plateforme donnée.

osname doit être l’un des noms d’OS Python standard (c’est-à-dire un des noms renvoyés par os.name) et platform la valeur commune renvoyés par sys.platform pour la plate-forme en question.

Les valeurs par défaut sont os.name et sys.platform si les paramètres ne sont pas fournis.

distutils.ccompiler.new_compiler(plat=None, compiler=None, verbose=0, dry_run=0, force=0)

Fonction de génération produisant une instance d’une sous-classe CCompiler pour la combinaison plateforme/compilateur fournie. Par défaut, plat est le os.name (par exemple 'posix', 'nt'), et compiler est le compilateur par défaut pour cette plate-forme. Actuellement, seuls 'posix' et 'nt' sont gérés, et les compilateurs par défaut sont ceux qui gèrent une « interface Unix traditionnelle » (UnixCCompiler) et Visual C++ (MSVCCompiler). Notez qu’il est tout à fait possible de demander un objet compilateur Unix sous Windows, et un objet compilateur Microsoft sous Unix. Si vous fournissez une valeur pour compiler, plat est ignoré.

distutils.ccompiler.show_compilers()

Affiche la liste des compilateurs disponibles (utilisés par l’option --help-compiler pour les commandes build, build_ext, build_clib).

class distutils.ccompiler.CCompiler([verbose=0, dry_run=0, force=0])

La classe de base abstraite CCompiler définit l’interface qui doit être implémentée par des classes de compilateur concrètes. La classe possède également quelques méthodes utilitaires utilisées par plusieurs classes de compilateurs.

L’idée de base derrière une classe abstraite de compilateur est que chaque instance peut être utilisée pour toutes les étapes de compilation/lien dans la construction d’un seul projet. Ainsi, les attributs communs à toutes ces étapes de compilation et de liaison (ce qui inclut les répertoires, les macros à définir, les bibliothèques à relier, etc.) sont des attributs de l’instance du compilateur. Pour tenir compte des variations dans la façon dont chaque fichier est traité, la plupart de ces attributs peuvent être modifiés en fonction de chaque compilation ou de chaque lien.

Le constructeur de chaque sous-classe crée une instance de l’objet Compiler. Les paramètres optionnels sont verbose (affiche plus d’information à l’exécution), dry_run (ne pas exécuter les étapes) et force (tout reconstruire, indépendamment des dépendances). Tous ces paramètres ont la valeur par défaut 0 (désactivé). Notez que vous ne voulez probablement pas instancier directement la classe CCompiler ou une de ses sous-classes. Utilisez plutôt la fonction génératrice distutils.CCompiler.new_compiler().

Les méthodes suivantes vous permettent de modifier manuellement les options du compilateur de l’instance de la classe Compiler.

add_include_dir(dir)

Ajoute dir à la liste des répertoires qui sont recherchés pour les fichiers d’en-tête. Le compilateur est chargé de rechercher les répertoires dans l’ordre dans lequel ils sont fournis par des appels successifs à add_include_dir().

set_include_dirs(dirs)

Affecte la liste des répertoires qui seront recherchés à la valeur de dirs (une liste de chaînes). Remplace tous les appels précédents de add_include_dir() ; les appels suivants de add_include_dir() s’ajoutent à la liste transmise par set_include_dirs(). Ceci n’affecte pas la liste des répertoires d’inclusion standard que le compilateur peut rechercher par défaut.

add_library(libname)

Ajoute libname à la liste des bibliothèques qui seront incluses dans tous les liens gérés par l’objet compilateur. Notez que libname ne doit pas être le nom d’un fichier contenant une bibliothèque, mais le nom de la bibliothèque elle-même : le nom du fichier sera déduit par l’éditeur de liens, le compilateur ou la classe de compilation (selon la plate-forme).

L’éditeur de liens est chargé de lier les bibliothèques dans l’ordre dans lequel elles sont fournies à add_library() et/ou set_libraries(). Il est parfaitement valide de dupliquer les noms de bibliothèques ; l’éditeur de liens est chargé de créer des liens avec les bibliothèques autant de fois que les noms sont mentionnées.

set_libraries(libnames)

Affecte la liste des bibliothèques à inclure dans tous les liens gérés par l’objet compilateur avec la valeur de libnames (une liste des chaînes de caractères). Ceci n’affecte pas les bibliothèques système standard que l’éditeur de liens peut inclure par défaut.

add_library_dir(dir)

Ajoute dir à la liste des répertoires qui seront recherchés pour les bibliothèques spécifiées dans add_library() et set_libraries(). L’éditeur de liens est chargé de rechercher les bibliothèques dans l’ordre dans lequel elles sont fournies à add_library_dir() et/ou set_library_dirs().

set_library_dirs(dirs)

Affecte la liste des répertoires de recherche de bibliothèque avec la valeur de dirs (une liste de chaînes de caractères). Cela n’affecte pas le chemin de recherche standard de la bibliothèque que l’éditeur de liens peut rechercher par défaut.

add_runtime_library_dir(dir)

Ajoute dir à la liste des répertoires qui seront recherchés par les bibliothèques partagées au moment de l’exécution.

set_runtime_library_dirs(dirs)

Affecte la liste des répertoires pour rechercher les bibliothèques partagées au moment de l’exécution à la valeur de dirs (une liste des chaînes de caractères). Ceci n’affecte aucun chemin de recherche standard que l’éditeur de liens d’exécution peut rechercher par défaut.

define_macro(name[, value=None])

Définit une macro de préprocesseur pour toutes les compilations gérées par cet objet compilateur. Le paramètre optionnel value doit être une chaîne de caractères ; s’il n’est pas fourni, alors la macro sera définie sans valeur explicite et le résultat exact dépendra du compilateur utilisé.

undefine_macro(name)

Désactive une macro de préprocesseur pour toutes les compilations gérées par cet objet compilateur. Si la même macro est définie par define_macro() et ensuite désactivée par un appel à undefine_macro(), le dernier appel est prioritaire (y compris en cas de redéfinitions multiples). Si la macro est redéfinie/désactivée par compilation (c’est-à-dire dans l’appel à compile()), alors cet appel prévaut.

add_link_object(object)

Ajoute objet à la liste des fichiers objets (ou analogues, tels que les fichiers de bibliothèque explicitement nommés ou la sortie des « compilateurs de ressources ») à inclure dans chaque lien qui est géré par ce compilateur d’objets.

set_link_objects(objects)

Définit la liste des fichiers objets (ou analogues) à inclure dans chaque lien à la valeur de objects. Ceci n’affecte pas les fichiers d’objets standard que l’éditeur de liens peut inclure par défaut (comme les bibliothèques système).

Les méthodes suivantes offre des services pour l’auto-détection des options du compilateur. Elles offrent des fonctionnalités similaires à celles du programme GNU autoconf.

detect_language(sources)

Détecte le langage d’un fichier donné, ou d’une liste de fichiers. Utilise les attributs d’instance language_map (un dictionnaire) et language_order (une liste) pour faire le travail.

find_library_file(dirs, lib[, debug=0])

Recherche dans la liste des répertoires spécifiés un fichier de bibliothèque statique ou partagée lib et renvoie le chemin complet vers ce fichier. Si debug est vrai, recherche une version de débogage (si cela a du sens sur la plate-forme actuelle). Renvoie None si lib n’a pas été trouvé dans l’un des répertoires spécifiés.

has_function(funcname[, includes=None, include_dirs=None, libraries=None, library_dirs=None])

Renvoie un booléen indiquant si funcname est pris en charge sur la plate-forme courante. Les arguments optionnels peuvent être utilisés pour enrichir l’environnement de compilation en fournissant des fichiers, des répertoires de fichiers, des bibliothèques, des répertoires de bibliothèques supplémentaires

library_dir_option(dir)

Renvoie l’option de compilation pour ajouter dir à la liste des répertoires recherchés pour les bibliothèques.

library_option(lib)

Renvoie l’option de compilation pour ajouter lib à la liste des bibliothèques liées à la bibliothèque partagée ou à l’exécutable.

runtime_library_dir_option(dir)

Renvoie l’option de compilation pour ajouter dir à la liste des répertoires recherchés par les bibliothèques d’exécution.

set_executables(**args)

Définit les exécutables (et leurs options) qui seront exécutés pour effectuer les différentes étapes de compilation. L’ensemble exact des exécutables qui peuvent être spécifiés ici dépend de la classe du compilateur (via l’attribut de classe executables), mais la plupart utilisent :

attribut

description

compiler

Le compilateur C/C++.

linker_so

L’éditeur de liens utilisé pour la création d’objets ou de bibliothèques partagées.

linker_exe

L’éditeur de lien utilisé pour créer des exécutables binaires.

archiver

Créateur de bibliothèque statique.

Sur les plates-formes disposant d’un outil de ligne de commande (Unix, DOS/Windows), chacun de ces éléments est une chaîne qui sera fractionnée en un nom exécutable et, éventuellement, une liste d’arguments. Le fractionnement de la chaîne est réalisée selon la même procédure que celle appliquée par les shells Unix : les mots sont délimités par des espaces, mais les guillemets et les antislashs permettent de les ignorer. Voir distutils.util.split_quoted().

Les méthodes suivantes permettent d’exécuter des étapes lors de processus de construction.

compile(sources[, output_dir=None, macros=None, include_dirs=None, debug=0, extra_preargs=None, extra_postargs=None, depends=None])

Compile un ou plusieurs fichiers source. Génère des fichiers objets (par exemple, transforme un fichier .c en fichier .o).

sources doit être une liste de noms de fichiers, généralement des fichiers C/C++, mais elle pourrait contenir n’importe quel fichier géré par un compilateur et une classe de compilateur (par exemple, MSVCCompiler peut gérer les fichiers de ressources dans sources). Renvoie une liste de noms de fichiers objet : un objet par nom de fichier dans sources. Selon les cas, tous les fichiers source ne seront pas forcément compilés, mais tous les noms de fichiers objet correspondants seront renvoyés.

Si output_dir est donné, les fichiers objets seront placés à l’intérieur, tout en conservant leurs chemins relatifs. Par exemple, le truc/machin.c compile normalement en truc/machin.o (pour une implémentation Unix) ; si output_dir a la valeur build, alors il compilera en build/truc/machin.o.

Le paramètre macros, s’il est donné, doit être une liste de définitions de macros. Une définition de macro est soit un couple (nom, valeur), ou un singleton (nom,). Le premier définit une macro ; si la valeur est None, la macro est définie sans valeur explicite. L’utilisation d’un singleton désactive la macro. Les définitions, redéfinitions ou désactivations ultérieures priment.

include_dirs doit être une liste de chaînes de caractères contenant les répertoires à ajouter au chemin de recherche par défaut pour cette compilation uniquement.

debug est un booléen ; si sa valeur est vraie, le compilateur est chargé d’afficher les symboles de débogage dans (ou à côté) du ou des fichiers objets.

extra_preargs et extra_postargs dépendent de l’implémentation. Sur les plates-formes qui ont une ligne de commande (par exemple Unix, DOS/Windows), il s’agit très probablement de listes de chaînes de caractères. Ce sont des arguments supplémentaires à ajouter avant (preargs) et après (postargs) la ligne de commande du compilateur. Sur d’autres plates-formes, consultez la documentation de la classe d’implémentation. Ces paramètres sont exposés pour permettre de sortir du cadre de la classe abstraite en cas de nécessité.

depends est une liste de noms de fichiers dont dépendent toutes les cibles. Si un fichier source est plus ancien qu’un fichier dans depends, alors le fichier source sera recompilé. Cela permet un suivi des dépendances à un niveau macro.

Lève CompileError en cas d’échec.

create_static_lib(objects, output_libname[, output_dir=None, debug=0, target_lang=None])

Relie un ensemble d’éléments pour créer un fichier de bibliothèque statique. L’ensemble d’éléments se compose de la liste des fichiers d’objets fournis comme objets, des fichiers d’objets supplémentaires fournis à add_link_object() et/ou set_link_objects(), des bibliothèques fournies à add_library() et/ou set_libraries() et les bibliothèques fournies à libraries (le cas échéant).

output_libname doit être un nom de bibliothèque et non un nom de fichier ; le nom de fichier sera déduit du nom de bibliothèque. output_dir est le répertoire dans lequel le fichier bibliothèque sera placé.

debug est un booléen ; si sa valeur est vraie, les informations de débogage seront incluses dans la bibliothèque (notez que sur la plupart des plateformes, c’est à l’étape de compilation que ce paramètre est pris en compte : le paramètre debug est inclus ici pour assurer une cohérence).

target_lang est le langage cible pour lequel les objets donnés sont compilés. Cela permet un traitement spécifique du temps de liaison dans certains langages.

Lève LibError en cas d’échec.

link(target_desc, objects, output_filename[, output_dir=None, libraries=None, library_dirs=None, runtime_library_dirs=None, export_symbols=None, debug=0, extra_preargs=None, extra_postargs=None, build_temp=None, target_lang=None])

Relie un ensemble d’éléments pour créer un fichier exécutable ou une bibliothèque partagée.

L’ensemble d’éléments se compose de la liste des fichiers objets fournis comme objets. output_filename devrait être un nom de fichier. Si output_dir est fourni, output_filename lui est relatif (c’est-à-dire que output_filename peut être un chemin vers un fichier ).

libraries est une liste de bibliothèques avec lesquelles il est possible d’établir des liens. Ce sont des noms de bibliothèques, pas des noms de fichiers, puisqu’ils sont traduits en noms de fichiers d’une manière spécifique à la plate-forme (par exemple truc devient libtruc.a sous Unix et truc.lib sous DOS/Windows). Cependant, ils peuvent inclure un chemin, ce qui signifie que l’éditeur de liens cherchera dans ce chemin spécifique plutôt que de rechercher tous les emplacements standard.

library_dirs, s’il est fourni, doit être une liste de répertoires à rechercher pour les bibliothèques qui ont été spécifiées comme des bibliothèques pures (c’est-à-dire sans aucun répertoire). Celles-ci s’ajoutent aux valeurs par défaut du système et à celles fournies à add_library_dir() et/ou set_library_dirs(). runtime_library_dirs est une liste de répertoires qui seront intégrés dans la bibliothèque partagée et utilisés pour rechercher d’autres bibliothèques partagées dont elle dépend à l’exécution. (Ceci est probablement valable uniquement sous UNIX.)

export_symbols est une liste de symboles que la bibliothèque partagée va exporter. (Ceci est probablement valable uniquement sous Window.)

debug s’utilise comme pour compile() et create_static_lib(), avec la nuance qu’elle a ici une importance sur la plupart des plateformes (par opposition à create_static_lib() qui inclut une option debug pour se conformer à l’interface).

extra_preargs et extra_postargs s’utilisent comme pour compile() (sauf bien sûr qu’ils fournissent des arguments à la ligne de commande pour l’éditeur de liens spécifique utilisé).

target_lang est le langage cible pour lequel les objets donnés sont compilés. Cela permet un traitement spécifique du temps de liaison dans certains langages.

Lève LinkError en cas d’échec.

link_executable(objects, output_progname[, output_dir=None, libraries=None, library_dirs=None, runtime_library_dirs=None, debug=0, extra_preargs=None, extra_postargs=None, target_lang=None])

Lie un exécutable. output_progname est le nom de l’exécutable du fichier, tandis que objects est une liste de noms de fichiers objets à lier. Les autres arguments sont les mêmes que pour la méthode link().

link_shared_lib(objects, output_libname[, output_dir=None, libraries=None, library_dirs=None, runtime_library_dirs=None, export_symbols=None, debug=0, extra_preargs=None, extra_postargs=None, build_temp=None, target_lang=None])

Lie une bibliothèque partagée. output_libname est le nom de la bibliothèque de sortie, tandis que objects est une liste de noms de fichiers d’objets à lier. Les autres arguments sont les mêmes que pour la méthode link().

link_shared_object(objects, output_filename[, output_dir=None, libraries=None, library_dirs=None, runtime_library_dirs=None, export_symbols=None, debug=0, extra_preargs=None, extra_postargs=None, build_temp=None, target_lang=None])

Lie un objet partagé. output_filename est le nom de l’objet partagé qui sera créé, tandis que objects est une liste de noms de fichiers d’objets à lier. Les autres arguments sont les mêmes que pour la méthode link().

preprocess(source[, output_file=None, macros=None, include_dirs=None, extra_preargs=None, extra_postargs=None])

Prétraitement d’un seul fichier source C/C++, désigné dans source. La sortie du traitement est écrite dans un fichier nommé output_file, ou dans stdout si output_file n’est pas fourni. macros est une liste de définitions de macros comme pour compile(), qui vont s’ajouter aux macros définies avec define_macro() et undefine_macro(). include_dirs est une liste de noms de répertoires qui seront ajoutés à la liste par défaut, de la même manière que add_include_dir().

Lève PreprocessError en cas d’échec.

Les méthodes utilitaires suivantes sont définies par la classe CCompiler, à l’usage des différentes sous-classes concrètes.

executable_filename(basename[, strip_dir=0, output_dir=''])

Renvoie le nom de fichier de l’exécutable pour un nom de base donné. Généralement, pour les plates-formes non Windows, c’est le même nom que le nom de base, tandis que sur Windows l’extension .exe sera ajouté.

library_filename(libname[, lib_type='static', strip_dir=0, output_dir=''])

Renvoie le nom de fichier pour le nom de bibliothèque donné sur la plate-forme actuelle. Sous Unix, une bibliothèque avec un lib_type de type static sera généralement de la forme liblibname.a, tandis qu’un lib_type de type dynamic sera de la forme liblibname.so.

object_filenames(source_filenames[, strip_dir=0, output_dir=''])

Renvoie le nom des fichiers objets pour les fichiers sources donnés. source_filenames doit être une liste de noms de fichiers.

shared_object_filename(basename[, strip_dir=0, output_dir=''])

Renvoie le nom d’un fichier objet partagé pour le nom de fichier basename.

execute(func, args[, msg=None, level=1])

Invoque distutils.util.execute(). Cette méthode invoque une fonction Python func avec les arguments args , après journalisation et prise en compte de l’option dry_run.

spawn(cmd)

Invoque distutils.util.spawn(). Invoque un processus externe pour exécuter la commande donnée.

mkpath(name[, mode=511])

Invoque distutils.dir_util.mkpath(). Crée un répertoire et tous les répertoires parents manquants.

move_file(src, dst)

Invoque distutils.file_util.move_file(). Renomme src en dst.

announce(msg[, level=1])

Écrit un message en utilisant distutils.log.debug().

warn(msg)

Écris un message d’avertissement msg dans la sortie d’erreur standard.

debug_print(msg)

Si l’option debug est activée pour cette instance de CCompiler, affiche msg sur la sortie standard, sinon rien ne s’affiche.

10.3. distutils.unixccompiler — Compilateur C Unix

Ce module fournit la classe UnixCCompiler, une sous-classe de la classe CCompiler qui gère les compilateurs C ayant une interface en ligne de commande conforme au standard Unix :

macros définies avec l’option -Dname[=value].

macros désaffectées avec -Uname.

inclut les répertoires de recherche spécifiés avec l’option -Idir.

bibliothèques spécifiées avec l’option -llib

répertoires de recherche des bibliothèques définis avec l’option -Ldir.

compilation gérée par cc (ou similaire) exécutable avec l’option -c compile .c vers .o.

édition de liens pour une bibliothèque statique gérée par le programme en ligne de commande ar (éventuellement avec le programme ranlib).

édition de liens pour une bibliothèque gérée par cc -shared.

10.4. distutils.msvccompiler — Compilateur Microsoft

This module provides MSVCCompiler, an implementation of the abstract CCompiler class for Microsoft Visual Studio. Typically, extension modules need to be compiled with the same compiler that was used to compile Python. For Python 2.3 and earlier, the compiler was Visual Studio 6. For Python 2.4 and 2.5, the compiler is Visual Studio .NET 2003. The AMD64 and Itanium binaries are created using the Platform SDK.

La classe MSVCCompiler sélectionnera normalement le bon compilateur, éditeur de liens, etc. Pour remplacer ces choix, les variables d’environnement DISTUTILS_USE_SDK et MSSdk doivent être toutes les deux définies. MSSdk indique que l’environnement courant a été configuré par le script SetEnv.Cmd du kit de développement logiciel (SDK), ou que les variables d’environnement ont été enregistrées lorsque le kit a été installé ; DISTUTILS_USE_SDK indique que l’utilisateur de distutils a choisi explicitement de remplacer le compilateur utilisé par MSVCCompiler.

10.5. distutils.bcppcompiler — Compilateur Borland

Ce module fournit BorlandCCompiler, une sous-classe de la classe abstraite CCompiler classe pour le compilateur Borland C++.

10.6. distutils.cygwincompiler — Compilateur Cygwin

Ce module fournit la classe CygwinCCompiler, une sous-classe de la classe UnixCCompiler qui gère Cygwin, le portage du compilateur GNU C sur Windows. Il contient également la classe Mingw32CCompiler qui gère le portage mingw32 de GCC (comme cygwin en mode no-cygwin).

10.7. distutils.archive_util — Utilitaires d’archivage

Ce module fournit quelques fonctions pour créer des fichiers d’archive, tels que des archives aux formats tarballs ou zipfiles.

distutils.archive_util.make_archive(base_name, format[, root_dir=None, base_dir=None, verbose=0, dry_run=0])

Crée un fichier d’archive (par exemple zip ou tar). base_name est le nom du fichier à créer, sans extension spécifique indiquant le format. format est le format d’archive : un parmi zip, tar, gztar, bztar, xztar, xztar, ou ztar. root_dir est un répertoire qui sera le répertoire racine de l’archive ; c’est-à-dire que le programme se positionne dans root_dir avant de créer l’archive. base_dir est le répertoire à partir duquel se lance l’archivage ; par exemple, base_dir est le préfixe commun à tous les fichiers et répertoires de l’archive. root_dir et base_dir sont tous deux par défaut dans le répertoire courant. Renvoie le nom du fichier archive.

Modifié dans la version 3.5: Ajout du support des fichiers xztar.

distutils.archive_util.make_tarball(base_name, base_dir[, compress='gzip', verbose=0, dry_run=0])

Crée une archive (compressée en option) sous forme de fichier au format tar à partir de tous les fichiers dans et sous base_dir. compress doit être 'gzip' (par défaut), 'bzip2', 'xz', 'compress' ou None. Pour la méthode 'compress' l’utilitaire de compression nommé par compress doit être sur le chemin de recherche par défaut, donc c’est sans doute spécifique à Unix. Le fichier tar de sortie sera nommé base_dir.tar, avec l’extension de compression appropriée (.gz, .bz2, .xz ou .Z). Renvoie le nom du fichier de sortie.

Modifié dans la version 3.5: Ajout du support de la compression xz.

distutils.archive_util.make_zipfile(base_name, base_dir[, verbose=0, dry_run=0])

Crée un fichier zip à partir de tous les fichiers dans et sous base_dir. Le fichier zip de sortie est nommé base_name + .zip. Utilise soit le module Python zipfile (si disponible) ou l’utilitaire InfoZIP zip (s’il est installé et trouvé sur le chemin de recherche par défaut). Si aucun des deux outils n’est disponible, lève DistutilsExecError. Renvoie le nom du fichier zip de sortie.

10.8. distutils.dep_util — Vérification des dépendances

Ce module fournit des fonctions permettant d’effectuer des tests de dépendance simples, basés sur les horodatages de fichiers et de groupes de fichiers, ainsi que des fonctionnalités entièrement basées sur ces analyses de dépendance par rapport aux horodatages.

distutils.dep_util.newer(source, target)

Renvoie la valeur true si source existe et a été modifiée plus récemment que target, ou si source existe et target n’existe pas. Renvoie la valeur false si les deux existent et que target est aussi ou plus récent que source. Lève DistutilsFileError si source n’existe pas.

distutils.dep_util.newer_pairwise(sources, targets)

Parcourt en parallèle deux listes de noms de fichiers, en vérifiant si chaque source est plus récente que sa cible correspondante. Renvoie une paire de listes (sources, cibles) où la source est plus récente que la cible, selon la sémantique de newer().

distutils.dep_util.newer_group(sources, target[, missing='error'])

Return true if target is out-of-date with respect to any file listed in sources. In other words, if target exists and is newer than every file in sources, return false; otherwise return true. missing controls what we do when a source file is missing; the default ('error') is to blow up with an OSError from inside os.stat(); if it is 'ignore', we silently drop any missing source files; if it is 'newer', any missing source files make us assume that target is out-of-date (this is handy in « dry-run » mode: it’ll make you pretend to carry out commands that wouldn’t work because inputs are missing, but that doesn’t matter because you’re not actually going to run the commands).

10.9. distutils.dir_util — Opérations sur l’arborescence des répertoires

Ce module fournit des fonctions pour travailler sur des répertoires et des arborescences de répertoires.

distutils.dir_util.mkpath(name[, mode=0o777, verbose=0, dry_run=0])

Crée un répertoire et tous les répertoires parents manquants. Si le répertoire existe déjà (ou si name est la chaîne vide, c’est-à-dire le répertoire courant, qui existe bien sûr), alors ne fait rien. Lève DistutilsFileError s’il n’est pas possible de créer un répertoire en cours de route (par exemple, un sous-chemin existe, mais est un fichier plutôt qu’un répertoire). Si verbose est vrai, affiche un résumé d’une ligne de chaque mkdir vers stdout. Renvoie la liste des répertoires réellement créés.

distutils.dir_util.create_tree(base_dir, files[, mode=0o777, verbose=0, dry_run=0])

Crée tous les répertoires vides sous base_dir nécessaires pour placer files. base_dir est le nom d’un répertoire qui n’existe pas encore nécessairement ; files est une liste de noms de fichiers relatifs à base_dir. base_dir + la partie répertoire de chaque fichier dans files est créée si elle n’existe pas déjà. Les options mode, verbose et dry_run sont les mêmes que pour mkpath().

distutils.dir_util.copy_tree(src, dst[, preserve_mode=1, preserve_times=1, preserve_symlinks=0, update=0, verbose=0, dry_run=0])

Copie une arborescence de répertoires entière src vers un nouvel emplacement dst. src et dst doivent tous deux être des noms de répertoire. Si src n’est pas un répertoire, lève DistutilsFileError. Si dst n’existe pas, il est créé avec mkpath(). Le résultat final de la copie est que chaque fichier dans src est copié dans dst, et les répertoires sous src sont récursivement copiés dans dst. Renvoie la liste des fichiers qui ont été copiés ou qui auraient pu l’être, en utilisant leur nom de sortie. La valeur renvoyée n’est pas affectée par update ou dry_run : c’est tout simplement la liste de tous les fichiers sous src, avec les noms modifiés pour être sous dst.

Les modes preserve_mode et preserve_times sont les mêmes que pour distutils.file_util.copy_file() ; il faut savoir que cela ne concerne que les fichiers réguliers, et non les dossiers. Si preserve_symlinks est vrai, les liens symboliques seront copiés en tant que liens symboliques (sur les plateformes qui les gèrent !); sinon (par défaut), la destination du lien sera copiée. update et verbose sont les mêmes que pour copy_file().

Les fichiers dans src qui commencent par .nfs sont ignorés (plus d’informations sur ces fichiers sont disponibles dans la réponse D2 de la page NFS FAQ page [http://nfs.sourceforge.net/#section_d]).

Modifié dans la version 3.3.1: Les fichiers NFS sont ignorés.

distutils.dir_util.remove_tree(directory[, verbose=0, dry_run=0])

Supprime récursivement directory et tous les fichiers et répertoires en dessous. Toutes les erreurs sont ignorées (sauf si verbose est vrai, elles sont affichées sur sys.stdout).

10.10. distutils.file_util — Traitements mono-fichier

Ce module contient quelques fonctions de service pour travailler sur des fichiers individuels.

distutils.file_util.copy_file(src, dst[, preserve_mode=1, preserve_times=1, update=0, link=None, verbose=0, dry_run=0])

Copie le fichier src dans dst. Si dst est un répertoire, alors src y est copié avec le même nom ; sinon, il faut que ce soit un nom de fichier. Si preserve_mode est vrai (par défaut), le mode du fichier (son type et ses bits de permission, ou ce qui est analogue sur la plate-forme actuelle) sont copiés. Si preserve_times est vrai (par défaut), les horodatages de la dernière modification et du dernier accès sont également copiés. Si update est vrai, src ne peut être copié que si dst n’existe pas, ou si dst existe mais est plus ancien que src.

link permets de créer des liens physiques (en utilisant os.link()) ou symboliques (en utilisant os.symlink()) au lieu de les copier : paramétrez la valeur a 'hard' ou 'sym' ; si elle vaut None (par défaut), les fichiers sont copiés. Ne définissez pas link sur les systèmes qui ne les gèrent pas : copy_file() ne vérifie pas si des liens symboliques ou physiques sont disponibles. La fonction _copy_file_contents() est utilisée pour copier le contenu des fichiers.

Renvoie un couple (dest_name, copied) : dest_name est le nom réel du fichier de sortie, et copied est vrai si le fichier a été copié (ou aurait été copié, si dry_run est vrai).

distutils.file_util.move_file(src, dst[, verbose, dry_run])

Déplace le fichier src vers dst. Si dst est un répertoire, le fichier y est déplacé avec le même nom ; sinon, src est simplement renommé dst. Renvoie le nouveau nom complet du fichier.

Avertissement

Gère les déplacements inter-périphériques sous Unix en utilisant copy_file(). Qu’en est-il sur les autres systèmes ?

distutils.file_util.write_file(filename, contents)

Crée un fichier appelé filename et y écrit contents (une séquence de chaînes sans terminaison de ligne).

10.11. distutils.util — Autres fonctions de service

Ce module contient d’autres éléments qui ne correspondent à aucun autre module de service.

distutils.util.get_platform()

Return a string that identifies the current platform. This is used mainly to distinguish platform-specific build directories and platform-specific built distributions. Typically includes the OS name and version and the architecture (as supplied by “os.uname()”), although the exact information included depends on the OS; eg. for IRIX the architecture isn’t particularly important (IRIX only runs on SGI hardware), but for Linux the kernel version isn’t particularly important.

Exemples de valeurs renvoyées :

linux-i586

linux-alpha

solaris-2.6-sun4u

irix-5.3

irix64-6.2

Pour les plates-formes qui ne sont pas POSIX, renvoie simplement sys.platform.

Pour les systèmes Mac OS X, la version du système d’exploitation correspond à la version minimale sur laquelle les binaires pourront être exécutés (c’est-à-dire la valeur de MACOSX_DEPLOYMENT_TARGET pendant la compilation de Python), et non la version du système actuel.

Pour les binaires universels construits sur Mac OS X, la valeur de l’architecture reflète l’état du binaire universel au lieu de celle de l’architecture du processeur en cours. Pour les binaires universels 32 bits, l’architecture est fat, pour les binaires universels 64 bits, l’architecture est fat64, et pour les binaires universels 4 voies, l’architecture est universelle. A partir de Python 2.7 et Python 3.2, l’architecture fat3 est utilisée pour une compilation universelle à 3 voies (ppc, i386, x86_64) et intel est utilisée pour une compilation universelle avec les architectures i386 et x86_64

Exemples de valeurs renvoyées sous Mac OS X :

macosx-10.3-ppc

macosx-10.3-fat

macosx-10.5-universal

macosx-10.6-intel

distutils.util.convert_path(pathname)

Renvoie un chemin pathname qui fonctionne sur le système de fichiers natif. Par exemple, il sépare le chemin sur / et le recompose en utilisant le séparateur de répertoires courant. Cela est nécessaire parce que les noms de fichiers dans les scripts d’installations sont toujours fournis dans le style Unix, et doivent être convertis dans la convention du système avant d’être utilisé par le système de fichiers. Lève ValueError sur les systèmes non UNIX si pathname commence ou se termine par une barre oblique (slash en anglais).

distutils.util.change_root(new_root, pathname)

Renvoie un chemin pathname préfixé avec new_root. Si pathname est relatif, c`est l’équivalent de os.path.join(new_root,pathname) Sinon, il faut rendre pathname relatif et joindre les deux, ce qui est dangereux sous DOS/Windows.

distutils.util.check_environ()

Vérifie que “os.environ” possède toutes les variables d’environnement utilisables dans les fichiers de configuration, les options en ligne de commande, etc. À l’heure actuelle, cela comprend :

HOME. Répertoire d’accueil de l’utilisateur (Unix uniquement)

PLAT. Description de la plate-forme actuelle, y compris le matériel et le l’OS (voir get_platform())

distutils.util.subst_vars(s, local_vars)

Exécute la substitution de variable de style shell/Perl sur s. Chaque occurrence de $ suivie d’un nom est considérée comme une variable, et la variable est remplacée par la valeur trouvée dans le dictionnaire local_vars, ou dans os.environ si elle ne se trouve pas dans local_vars. os.environ est d’abord vérifié/étendu pour garantir qu’elle contient certaines valeurs : voir check_environ(). Lève ValueError pour toute variable non trouvée dans local_vars ou os.environ.

Remarquez qu’il ne s’agit pas d’une fonction d’interpolation de chaîne à part entière. Une $variable valide ne peut être composée que de lettres majuscules et minuscules, de chiffres et d’un tiret bas. Aucune syntaxe de type {} ou () pour indiquer des variables n’est disponible.

distutils.util.split_quoted(s)

Sépare une chaîne de caractères selon les règles de type shell Unix pour les guillemets et les barres obliques inverses. En bref : les mots sont délimités par des espaces, tant que ces espaces ne sont pas échappées par une barre oblique inversée, ou à l’intérieur d’une chaîne guillemets. Les guillemets simples et doubles sont équivalents, et les caractères entre guillemets peuvent être échappés à l’aide d’une barre oblique inversée. La barre oblique inversée est supprimée de toute séquence d’échappement à deux caractères, ne laissant que le caractère échappé. Les caractères guillemets sont supprimés de toute chaîne de caractères entre guillemets. Renvoie une liste de mots.

distutils.util.execute(func, args[, msg=None, verbose=0, dry_run=0])

Exécute une action qui affecte le monde extérieur (par exemple, écrire dans le système de fichiers). De telles actions sont spéciales car elles sont désactivées par l’option dry_run. Cette méthode s’occupe de tout. Vous devez simplement fournir la fonction à appeler avec un couple d’argument lui correspondant et un message facultatif à afficher.

distutils.util.strtobool(val)

Convertit une chaîne de caractères représentant une valeur booléenne en 1 (si elle est évaluée comme vraie) ou 0 (si elle est évaluée comme fausse).

Les valeurs vraies sont , y, yes, t, true, on et 1. Les valeurs fausses sont n, no, f, false, off et 0. Lève ValueError si val est autre chose.

distutils.util.byte_compile(py_files[, optimize=0, force=0, prefix=None, base_dir=None, verbose=1, dry_run=0, direct=None])

Effectue une compilation vers du bytecode Python à partir d’un ensemble de fichiers sources Python dans un fichier .pyc dans un sous répertoire __pycache__ (voir PEP 3147 [https://www.python.org/dev/peps/pep-3147] et PEP 488 [https://www.python.org/dev/peps/pep-0488]). py_files est une liste de fichiers à compiler ; tous les fichiers qui ne se terminent pas par .py sont ignorés en silence. optimize doit être l’un des éléments suivants :

0: ne pas optimiser

1: optimisation normale (comme python -O)

2: optimisation supplémentaire (comme python -OO)

Si force est vrai, tous les fichiers sont recompilés indépendamment des horodatages.

Le nom du fichier source encodé dans chaque fichier bytecode est par défaut le nom présent dans la liste des noms de fichiers source py_files ; vous pouvez modifier dynamiquement ses noms avec prefix et basedir. prefix est une chaîne de caractères qui sera supprimée de chaque nom de fichier source, et base_dir est un nom de répertoire qui sera préfixé au nom (après que le prefixe soit supprimé). Vous pouvez choisir de fournir l’un ou l’autre (ou les deux) paramètres : prefixe et base_dir.

Si dry_run est vrai, ne fait rien qui puisse affecter le système de fichiers.

La compilation binaire se fait soit directement dans l’interpréteur courant avec le module standard py_compile, soit indirectement en écrivant un script temporaire et en l’exécutant. Normalement, vous devez laisser byte_compile() choisir d’utiliser la compilation directe ou non (voir le code-source pour les détails). Le paramètre direct est utilisé par le script généré en mode indirect ; à moins que vous ne sachiez ce que vous faites, laissez le paramètre à None (Aucun).

Modifié dans la version 3.2.3: Crée des fichiers .pyc avec un sous-répertoire import magic tag dans leur nom, dans le sous répertoire __pycache__ plutôt que dans le répertoire courant, sans tag.

Modifié dans la version 3.5: Crée des fichiers .pyc selon la PEP 488 [https://www.python.org/dev/peps/pep-0488].

distutils.util.rfc822_escape(header)

Renvoie une version de header traitée avec les échappements compatibles avec les en-têtes RFC 822 [https://tools.ietf.org/html/rfc822.html], en s’assurant qu’il y a 8 espaces après chaque nouvelle ligne. Notez qu’il ne fait aucune autre modification de la chaîne de caractères.

10.12. distutils.dist — La classe Distribution

Ce module fournit la classe Distribution, qui représente le module distribution en cours de construction/installation/distribution.

10.13. distutils.extension — La classe Extension

Ce module fournit la classe Extension, utilisée pour décrire les modules d’extension C/C++ dans les scripts de configuration.

10.14. distutils.debug — Mode de débogage du module Distutils

Ce module fournit l’option DEBUG.

10.15. distutils.errors — Exceptions du module Distutils

Fournit les exceptions utilisées par les modules de Distutils. Notez que les modules Distutils peuvent soulever des exceptions standard ; en particulier, SystemExit est généralement levée pour les erreurs qui sont manifestement de la responsabilité de l’utilisateur final (ex : mauvais argument en ligne de commande).

Ce module est utilisable avec la syntaxe from ... import * ; il n’exporte que des symboles dont le nom commence par Distutils et se termine par Error.

10.16. distutils.fancy_getopt — Encapsulation du module getopt standard

Ce module est une encapsulation du module standard getopt qui apporte les fonctionnalités supplémentaires suivantes :

Les options short et long sont liées entre elles.

Les options ont des pages d’aide, donc fancy_getopt() pourrait potentiellement créer un résumé d’utilisation complet

Les options définissent les attributs à partir d’un objet fourni.

Les options booléennes peuvent avoir des « alias négatifs » — par exemple l’option -quiet est l’alias négatif de --verbose, l’option -quiet sur la ligne de commande met verbose à faux.

distutils.fancy_getopt.fancy_getopt(options, negative_opt, object, args)

Encapsulation de la fonction getopt. options est une liste de triplets (long_option, short_option, help_string) comme décrit dans le constructeur de la classe FancyGetopt. negative_opt doit être un dictionnaire associant les noms des options aux noms des options, la clé et la valeur doivent être dans la liste options. object est un objet qui sera utilisé pour stocker des valeurs (voir la méthode getopt() de la classe FancyGetopt). args est la liste des arguments. Utilise sys.argv[1 :] si None est passé à args.

distutils.fancy_getopt.wrap_text(text, width)

Ajoute des retours à la ligne à texte de manière à ce que la largeur soit inférieure à largeur.

class distutils.fancy_getopt.FancyGetopt([option_table=None])

La liste option_table est constituée de triplets : (long_option, short_option, help_string*)

Si une option prend un argument, sa long_option doit se terminer par '='. short_option doit être un seul caractère, jamais ':'`'. *option_courte* doit être ``None si long_option n’a pas de short_option correspondante. Tous les triplets d’options doivent avoir des options longues.

La classe FancyGetopt fournit les méthodes suivantes :

FancyGetopt.getopt([args=None, object=None])

Analyse les options de ligne de commande des arguments. Les stocke en tant qu’attributs de objet.

Si args est None ou n’est pas définie, utilise sys.argv[1:]. Si object est None ou n’est pas définie, créer une nouvelle instance de la classe OptionDummy , stocke les valeurs d’options dans l’instance et renvoie un couple (args, object). Si objet est fourni, il est modifié sur place et getopt() renvoie simplement args; dans les deux cas, Les arguments args renvoyés sont une copie modifiée de la liste args transmise, qui est n’est pas modifiée.

FancyGetopt.get_option_order()

Renvoie la liste des couples (option, valeur) traités par l’exécution précédente de getopt(). Déclenche RuntimeError si getopt() n’a pas encore été appelée.

FancyGetopt.generate_help([header=None])

Génère un texte d’aide (une liste de chaînes, une par ligne de sortie suggérée) de la liste d’options pour l’objet de la classe FancyGetopt.

S’il est fourni, affiche l’en-tête header en haut de l’aide.

10.17. distutils.filelist — La classe FileList liste des fichiers

Ce module fournit la classe FileList, utilisée pour parcourir le système de fichiers et construire des listes de fichiers.

10.18. distutils.log — Journalisation basée sur le style de la PEP 282

10.19. distutils.spawn — Crée un sous-processus

Ce module offre la fonction spawn(), une interface avec diverses fonctions spécifiques à la plate-forme pour lancer un autre programme dans un sous-processus. Inclut également find_executable() pour rechercher le chemin d’accès pour un nom d’exécutable donné.

10.20. distutils.sysconfig — Informations de configuration du système

Le module distutils.sysconfig donne accès aux informations de configuration bas niveau de Python. Les variables de configuration spécifiques disponibles dépendent de la plate-forme et de la configuration. Les variables spécifiques dépendent du processus de compilation de la version spécifique de Python en cours d’exécution. Les variables sont celles qui se trouvent dans le fichier Makefile et dans les entêtes de configuration installés avec Python sur des systèmes Unix. Le fichier des entêtes de configuration s’appelle pyconfig.h pour les versions de Python commençant par 2.2, et config.h pour les versions antérieures de Python.

Quelques fonctions supplémentaires sont fournies pour effectuer des manipulations utiles pour d’autres parties du paquet distutils.

distutils.sysconfig.PREFIX

Le résultat de os.path.normpath(sys.prefix).

distutils.sysconfig.EXEC_PREFIX

Le résultat de os.path.normpath(sys.exec_prefix).

distutils.sysconfig.get_config_var(name)

Retourne la valeur d’une seule variable. C’est l’équivalent de get_config_vars().get(name).

distutils.sysconfig.get_config_vars(...)

Retourne un ensemble de définitions de variables. S’il n’y a pas d’arguments, cela renvoie un dictionnaire qui associe les noms des variables de configuration aux valeurs. Si des arguments sont spécifiés, ils doivent être des chaînes de caractères, et la valeur renvoyée sera une séquence donnant les valeurs correspondantes. Si un nom donné n’a pas de valeur correspondante, la valeur None sera utilisée pour cette variable.

distutils.sysconfig.get_config_h_filename()

Renvoie le nom complet du chemin d’accès de l’en-tête de configuration. Pour Unix, c’est l’en-tête généré par le script configure ; pour les autres plates-formes, l’en-tête provient directement de la distribution source Python. Le fichier est un fichier texte spécifique à la plate-forme.

distutils.sysconfig.get_makefile_filename()

Renvoie le nom complet du chemin d’accès du fichier Makefile utilisé pour construire Python. Pour Unix, c’est le fichier généré par le script configure. La définition pour les autres plateformes varie. S’il existe, il s’agit d’un fichier texte spécifique à la plate-forme. Cette fonction n’est utile que sur les plates-formes POSIX.

distutils.sysconfig.get_python_inc([plat_specific[, prefix]])

Renvoie le répertoire pour les fichiers d’inclusion C standards ou dépendants de la plate-forme. Si plat_specific est vrai, le répertoire include dépendant de la plate-forme est renvoyé ; si la valeur est faux ou None, le répertoire indépendant de la plate-forme est renvoyé. Si prefix est donné, il est utilisé soit comme préfixe au lieu de PREFIX, soit comme préfixe d’exécution au lieu de EXEC_PREFIX si plat_specific est vrai.

distutils.sysconfig.get_python_lib([plat_specific[, standard_lib[, prefix]]])

Renvoie le répertoire pour l’installation de la bibliothèque standard ou dépendante de la plate-forme. Si plat_specific est vrai, le répertoire include dépendant de la plate-forme est renvoyé ; si la valeur est faux ou None, le répertoire indépendant de la plate-forme est renvoyé. Si prefix est donné, il est utilisé soit comme préfixe au lieu de PREFIX, soit comme préfixe d’exécution au lieu de EXEC_PREFIX si plat_specific est vrai. Si standard_lib est vrai, le répertoire de la bibliothèque standard est renvoyé plutôt que le répertoire d’installation des extensions tierces.

La fonction suivante est uniquement destinée à être utilisée dans le paquet distutils.

distutils.sysconfig.customize_compiler(compiler)

Exécute toute personnalisation spécifique à la plate-forme d’une instance distutils.ccompiler.CCompiler.

Cette fonction n’est nécessaire que sous Unix pour le moment, mais doit être appelée de manière cohérente pour supporter la compatibilité ascendante. Elle insère des informations qui varient d’une version à l’autre d’Unix et qui sont stockées dans le fichier Python Makefile. Ces informations comprennent le compilateur, les options du compilateur et de l’éditeur de liens sélectionnés, ainsi que l’extension utilisée par l’éditeur de liens pour les objets partagés.

Cette fonction est encore plus spéciale, et ne devrait être utilisée que dans les procédures de compilation de Python.

distutils.sysconfig.set_python_build()

Informe le module distutils.sysconfig qu’il est utilisé dans le cadre du processus de compilation de Python. Cela change beaucoup d’emplacements relatifs pour les fichiers, ce qui les place dans la zone de compilation plutôt que dans un interpréteur Python installé.

10.21. distutils.text_file — La classe TextFile

Ce module fournit la classe TextFile, qui donne une interface aux fichiers texte qui s’occupe (optionnellement) de supprimer les commentaires, d’ignorer les lignes vides et de joindre les lignes avec des antislash.

class distutils.text_file.TextFile([filename=None, file=None, **options])

Cette classe fournit un objet de type fichier qui se charge de tout ce que vous voulez généralement faire lors du traitement d’un fichier texte ayant une syntaxe ligne par ligne : Suppression des commentaires (tant que # est votre caractère de commentaire), passer les lignes vides, joindre des lignes adjacentes en échappant la nouvelle ligne (les lignes se terminant par une antislash), supprime les espace blancs avant et après le texte etc. Toutes ces fonctions sont optionnelles et peuvent être commandées indépendamment.

La classe fournit une méthode warn() pour pouvoir générer des messages d’avertissement qui renvoie le numéro de ligne physique, même si la ligne logique en question couvre plusieurs lignes physiques. Fournit également unreadline() pour implémenter un système prospectif ligne par ligne.

Les instances de TextFile sont créées soit avec filename, soit avec file ou bien les deux. RuntimeError est levé si les deux valent None. filename doit être une chaîne de caractères, et file un objet fichier (ou quelque chose qui fournit les méthodes readline() et close()). Il est recommandé de fournir au moins filename, afin que TextFile puisse l’inclure dans les messages d’avertissement. Si file n’est pas fourni, TextFile crée son propre fichier en utilisant la fonction open().

Les options sont toutes booléennes et affectent les valeurs renvoyées par readline().

Nom des options

description

default

strip_comments

strip from '#' to end-of-line, as well as any whitespace leading up to the '#'—unless it is escaped by a backslash

true

lstrip_ws

Efface les espaces blancs en début de chaque ligne avant de la renvoyer.

false

rstrip_ws

Efface les espaces blancs de fin de ligne (y compris le terminateur de ligne !) de chaque ligne avant de la renvoyer.

true

skip_blanks

Ignore les lignes qui sont vides *après* la suppression des commentaires et des espaces. (Si lstrip_ws et rstrip_ws sont tous les deux faux, alors certaines lignes peuvent être composées uniquement d’espaces : elles ne seront pas ignorées, même si skip_blanks est vrai.

true

join_lines

Si sur la ligne, une antislash est le dernier caractère et que ce caractère n’est pas le caractère de nouvelle ligne. Joint la ligne suivante pour former une ligne logique. Si N lignes consécutives se terminent par une antislash, alors N+1 lignes physiques seront liées pour former une seul ligne logique.

false

collapse_join

Supprime les espaces blancs des lignes qui sont jointes à leur prédécesseur. n’est utile que que si (join_lines and not lstrip_ws).

false

Notez que puisque rstrip_ws peut effacer la fin de la ligne, la sémantique de readline() doit être différente de celle de la méthode standard readline() des objets fichier ! En particulier, readline() renvoie None pour indiquer la fin du fichier: une chaîne vide peut être juste une ligne blanche (ou une ligne entièrement blanche), si rstrip_ws est vrai mais pas si skip_blanks est faux.

open(filename)

Ouvre un nouveau fichier filename. Remplace tous les arguments du constructeur file ou filename.

close()

Ferme le fichier courant et oublie toutes les informations connues à son sujet (y compris le nom du fichier et le numéro de la ligne courante).

warn(msg[, line=None])

Affiche (vers stderr) un message d’avertissement lié à la ligne logique courante dans le fichier courant. Si la ligne logique courante dans le fichier s’étend sur plusieurs lignes physiques, l’avertissement se réfère à une plage de lignes physiques, telles que "lignes 3-5". Si line est fourni, il remplace le numéro de la ligne courante ; il peut s’agir d’une liste ou d’un couple pour indiquer une plage de lignes physiques, ou d’un entier pour une seule ligne physique.

readline()

Lit et renvoie une seule ligne logique à partir du fichier courant (ou à partir d’un tampon interne si les lignes ont déjà été marqué comme non lue avec unreadline()). Si l’option join_lines est vraie, cela peut impliquer la lecture de plusieurs lignes physiques concaténées en une seule chaîne. Met à jour le numéro de la ligne courante. Appeler warn() après readline() émet donc un avertissement sur la ou les lignes physiques qui viennent d’être lues. Renvoie None à la fin du fichier, puisque la chaîne vide peut se produire si rstrip_ws est vrai mais pas si strip_blanks est faux.

readlines()

Lit et renvoie la liste de toutes les lignes logiques restant dans le fichier courant. Met à jour le numéro de la ligne courante à la dernière ligne du fichier.

unreadline(line)

Insère la ligne line (une chaîne de caractères) dans un tampon interne qui sera vérifié par les futurs appels de readline(). Utile pour implémenter un analyseur prospectif ligne par ligne. Notez que les lignes qui sont « non lues » avec unreadline() ne sont ensuite pas traitées de nouveau (espace blancs, ou autre) quand elles sont lues avec readline(). Si plusieurs appels sont faits à unreadline() avant un appel à readline(), les lignes sont renvoyées dans l’ordre de la plus récente première à la plus ancienne.

10.22. distutils.version — Classes de numéros de version

10.23. distutils.cmd — Classe de base abstraite pour les commandes Distutils

Ce module fournit la classe de base abstraite Command.

class distutils.cmd.Command(dist)

Classe de base abstraite pour définir les classes de commandes, les « ouvrières » de Distutils. Une analogie utile pour les classes de commandes est de les considérer comme des sous-routines avec des variables locales appelées options. Les options sont déclarées dans initialiser_options() et définies (compte tenu de leur valeur finale) dans finalize_options(), qui doivent être définies pour chaque classe de commande. La distinction entre les deux est nécessaire parce que les valeurs des options peuvent venir de l’extérieur (ligne de commande, fichier de configuration, ….), et toutes les options dépendantes d’autres options doivent être calculées après que ces options externes aient été traitées — ce qui explique finalize_options(). Le corps de la sous-routine, où s’effectue tout le travail est basé sur les valeurs de ses options, est la méthode run(), qui doit être implémentée par chaque classe de commande.

Le constructeur prend un seul argument, dist, une instance de Distribution.

10.24. Créer une nouvelle commande Distutils

Cette section décrit les étapes pour créer une nouvelle commande Distutils.

Une nouvelle commande doit résider dans un module du package distutils.command. Il existe un exemple de modèle dans ce répertoire nommé command_template. Copiez ce fichier dans un nouveau module portant le même nom que la nouvelle commande que vous implémentez. Ce module doit implémenter une classe portant le même nom que le module (et la commande). Par exemple, pour créer la commande peel_banana (afin que les utilisateurs puissent exécuter setup.py peel_banana), vous devez copier le fichier commande_template dans distutils/command/peel_banana.py, puis l’éditer pour qu’il implémente la classe peel_banana, une sous-classe de la classe distutils.cmd.Command.

Les sous-classes de la classe Command doivent définir les méthodes suivantes.

Command.initialize_options()

Définit des valeurs par défaut pour toutes les options que cette commande gère. Notez que ces valeurs par défaut peuvent être remplacées par d’autres commandes, par le script d’installation, par des fichiers de configuration ou par la ligne de commande. Ce n’est donc pas l’endroit idéal pour introduire des dépendances entre les options. En règle générale, les méthodes suivantes initialize_options() ne font que des assignations de type self.truc = None.

Command.finalize_options()

Définit les valeurs finales pour toutes les options que cette commande gère. Cette méthode doit toujours être appelée le plus tard possible, c’est-à-dire après que toutes les affectations des options de la ligne de commande ou que d’autres commandes ont été faites. C’est donc l’endroit idéal pour introduire des dépendances d’options : si truc dépend de machin, alors il est sûr de mettre truc de machin aussi longtemps que truc a toujours la même valeur qui lui a été attribué par initialize_options().

Command.run()

La raison d’être d’une commande : exécuter l’action programmée en étant contrôlée par les options initialisées dans initialize_options(), personnalisées par d’autres commandes, par le script de configuration, par la ligne de commande et les fichiers de configuration, puis finalisée dans finalize_options(). Toutes les interactions avec le système de fichiers et la sortie du terminal doivent être effectuées par run().

Command.sub_commands

sub_commands formalise la notion de « famille » de commandes, par exemple. install est le parent des sous-commandes install_lib, install_headers, etc. Le parent d’une famille de commandes définit sub_commands en tant qu’attribut de classe ; c’est une liste de couples (command_name, predicate), avec command_name le nom de la commande et predicate une fonction, une chaîne ou None. predicate est une méthode de la commande parent qui détermine si la commande correspondante est applicable dans la situation actuelle. Par exemple : install_headers n’est applicable que s’il existe des fichiers d’en-tête C à installer. Si predicate est None, cette commande est toujours effectuée.

sub_commands est généralement défini à la fin d’une classe, car les prédicats peuvent être des méthodes de la classe, ils doivent donc déjà avoir été définis. L’exemple canonique est la commande install.

10.25. distutils.command — Commandes Distutils individuelles

10.26. distutils.command.bdist — Construit un installateur binaire

10.27. distutils.command.bdist_packager — Classe de base abstraite pour empaqueteurs

10.28. distutils.command.bdist_dumb — Construit un installateur passif (dumb)

10.29. distutils.command.bdist_msi — Construit un installateur Microsoft

class distutils.command.bdist_msi.bdist_msi

Construit un installateur Windows Installeur [https://msdn.microsoft.com/en-us/library/cc185688(VS.85).aspx] (.msi)

Dans la plupart des cas, l’installateur bdist_msi est un meilleur choix que l’installateur bdist_wininst, car il gère mieux les plates-formes Win64, et permet en plus aux administrateurs d’effectuer des installations non interactives ainsi que des installations via des stratégies de groupe.

10.30. distutils.command.bdist_rpm — Construit une distribution binaire au format Redhat RPM et SRPM

10.31. distutils.command.bdist_wininst — Construit un installateur Windows

10.32. distutils.command.sdist — Construit une distribution source

10.33. distutils.command.build — Construit tous les fichiers d’un paquet

10.34. distutils.command.build_clib — Construit toutes les bibliothèques C d’un paquet

10.35. distutils.command.build_ext — Construit toutes les extensions d’un paquet

10.36. distutils.command.build_py — Construit les fichiers .py/.pyc d’un paquet

class distutils.command.build_py.build_py

class distutils.command.build_py.build_py_2to3

Implémentation alternative de build_py qui exécute également la bibliothèque de conversion 2to3 sur chaque fichier .py qui va être installé. Pour l’utiliser dans un fichier setup.py pour une distribution conçue pour fonctionner avec Python 2.x et 3.x, ajouter :

try:
    from distutils.command.build_py import build_py_2to3 as build_py
except ImportError:
    from distutils.command.build_py import build_py

à votre setup.py et, plus tard :

cmdclass = {'build_py': build_py}

à l’appel de setup().

10.37. distutils.command.build_scripts — Construit les scripts d’un paquet

10.38. distutils.command.clean — Nettoie un dossier de compilation d’un paquet

Cette commande supprime les fichiers temporaires créés par la commande build et ses sous-commandes, comme les fichiers objets compilés intermédiaires. Avec l’option --all, le répertoire de compilation sera supprimé.

Les modules d’extension construits sur place ne seront pas effacés, car ils ne sont pas dans le répertoire build.

10.39. distutils.command.config — Effectue la configuration d’un paquet

10.40. distutils.command.install — Installe un paquet

10.41. distutils.command.install_data — Installe les fichiers de données d’un paquet

10.42. distutils.command.install_headers — Installe les fichiers d’en-tête C/C++ d’un paquet

10.43. distutils.command.install_lib — Installe les fichiers de bibliothèque à partir d’un paquet

10.44. distutils.command.install_scripts — Installe les fichiers de script d’un paquet

10.45. distutils.command.register — Enregistre un module dans l’Index des paquets Python (Python Package Index ou PyPI en anglais)

La commande register enregistre le paquet dans l’index des paquets Python. Plus de détails à ce sujet dans la PEP 301 [https://www.python.org/dev/peps/pep-0301].

10.46. distutils.command.check — Vérifie les méta-données d’un paquet

La commande check effectue des tests sur les méta-données d’un paquet. Par exemple, elle vérifie que toutes les méta-données requises sont fournies lorsque les arguments sont passés à la fonction setup().

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Installation des modules python (Version historique)

Auteur

Greg Ward

Voir aussi

Installation de modules Python

The up to date module installation documentations

Ce document décrit les utilitaires de distribution de Python (« Distutils ») du point de vue de l’utilisateur final, décrivant comment étendre les capacités d’une installation standard de python en construisant et installant des modules python tiers et des extensions.

Note

This guide only covers the basic tools for building and distributing extensions that are provided as part of this version of Python. Third party tools offer easier to use and more secure alternatives. Refer to the quick recommendations section [https://packaging.python.org/en/latest/current/] in the Python Packaging User Guide for more information.

Introduction

Bien que la vaste bibliothèque standard de Python comble beaucoup de besoins en programmation, il arrive souvent un moment où vous avez besoin d’ajouter de nouvelles fonctionnalités à votre installation de Python, via des modules tiers. Cela peut être nécessaire pour vous aider à écrire vos programmes ou pour prendre en charge une application écrite en Python que vous souhaitez utiliser.

Dans le passé, il y a eu peu de prise d’aide à l’ajout de modules tiers sur une installation existante de Python. Avec l’introduction des utilitaires de distribution de Python (Distutils pour faire plus court) dans Python 2.0, ceci a changé.

Ce document s’adresse principalement aux personnes qui ont besoin d’installer des modules tiers de Python : les utilisateurs finaux et les administrateurs système, qui ont juste besoin de faire fonctionner une application Python, et les programmeurs Python, qui veulent ajouter de nouvelles fonctionnalités à leur boîte à outils. Vous n’avez pas besoin de connaître Python pour lire ce document. Il y aura quelques brèves utilisations du mode interactif de Python pour explorer votre installation, mais c’est tout. Si vous cherchez des informations sur la façon de distribuer vos propres modules Python afin que d’autres puissent les utiliser, allez voir le manuel Distribuer des modules Python (Version historique). Debugging the setup script peut aussi être intéressant.

Le meilleur des cas : l’installation simple

Dans le meilleur des cas, quelqu’un aura préparé une version spéciale de la distribution du module que vous souhaitez installer qui est destiné spécifiquement à votre plateforme et elle va s’installer comme n’importe quel autre logiciel sur votre plateforme. Par exemple, le développeur du module pourrait faire un installeur exécutable disponible pour les utilisateurs Windows, un paquetage RPM pour les utilisateurs de systèmes Linux basés sur RPM (Red Hat, SuSE, Mandrake et bien d’autres), un paquet Debian pour les utilisateurs de Linux basé sur le système Debian et ainsi de suite.

Dans ce cas, vous devez télécharger le programme d’installation approprié à votre plateforme et faire d’elle ce qui vous semble évident : l’exécuter s’il s’agit d’un exécutable d’installation, rpm --install si c’est un RPM, etc. Vous n’avez même pas besoin d’exécuter Python ou un script d’installation, vous n’avez pas besoin de compiler quoi que ce soit – vous devriez même pas avoir besoin de lire toutes les instructions (même si c’est toujours une bonne idée de le faire).

Bien sûr, les choses ne seront pas toujours aussi simple que cela. Vous pourriez être intéressés par une distribution d’un module qui n’a pas de programme d’installation facile à utiliser pour votre plateforme. Dans ce cas, vous allez devoir repartir des fichiers sources publiés par l’auteur/mainteneur du module. L’installation à partir des sources n’est pas très difficile, du moment que les modules en question sont empaquetés de façon standard. Le cœur de ce document explique comment configurer et installer des modules à partir des sources.

Le nouveau standard: Distutils

Si vous téléchargez une distribution source du module, vous pouvez dire assez rapidement s’il a été empaqueté et distribué de la façon standard, c’est-à-dire en utilisant Distutils. Premièrement, le nom et le numéro de version de la distribution sont affichés en bonne place dans le nom de l’archive téléchargée, par exemple foo-1.0.tar.gz ou widget-0.9.7.zip. Ensuite, l’archive se décompresse dans un répertoire du même nom : foo-1.0 ou widget-0.9.7. En outre, la distribution contient un script d’installation setup.py et un fichier nommé README.txt ou éventuellement juste README, qui doit expliquer que la construction et l’installation de la distribution du module se fait simplement en exécutant ceci :

python setup.py install

Sous Windows, cette commande doit être lancée depuis une invite de commande (Démarrer ‣ Accessoires) :

setup.py install

Si toutes ces choses sont vérifiées, alors vous savez déjà comment construire et installer le module que vous venez de télécharger : en exécutant la commande ci-dessus. Sauf si vous avez besoin d’installer les choses d’une manière non standard ou de personnaliser le processus de construction, vous n’avez pas vraiment besoin de ce manuel. Ou plutôt, la commande ci-dessus est tout ce dont vous avez besoin de retenir de ce manuel.

Construction standard et installation

Comme décrit dans la section Le nouveau standard: Distutils, construire et installer une distribution de modules en utilisant les Distutils consiste généralement à exécuter une simple commande dans un terminal :

python setup.py install

Différences selon les plateformes

Vous devez toujours exécuter la commande setup à partir du répertoire racine de la distribution, à savoir le sous-répertoire de plus haut niveau dans l’arborescence où se sont décompressées les sources de la distribution du module. Par exemple, si vous venez de télécharger les sources d’une distribution du module foo-1.0.tar.gz sous un système UNIX, la méthode normale consiste à faire :

gunzip -c foo-1.0.tar.gz | tar xf -    # unpacks into directory foo-1.0
cd foo-1.0
python setup.py install

Sous Windows, vous avez probablement téléchargé foo-1.0.zip. Si vous avez téléchargé le fichier d’archive dans C:\Temp, il se décompressera alors dans C:\Temp\foo-1.0 ; vous pouvez utiliser soit un gestionnaire d’archives graphique (comme WinZip), soit un outil de ligne de commande (tels que unzip ou pkunzip) pour décompresser l’archive. Ensuite, ouvrez une fenêtre d’invite de commandes et exécutez :

cd c:\Temp\foo-1.0
python setup.py install

Fractionnement du travail

Exécuter setup.py install construit et installe tous les modules en un seul coup. Si vous préférez travailler progressivement — ce qui est particulièrement utile si vous souhaitez personnaliser le processus de construction ou si les choses vont mal — vous pouvez utiliser le script de configuration pour faire une chose à la fois. Cela est particulièrement utile lorsque la construction et l’installation doit être faite par différents utilisateurs — par exemple, vous pouvez vouloir construire une distribution d’un module et la transférer à un administrateur système pour l’installation (ou le faire vous-même, avec les privilèges de super-utilisateur).

Par exemple, vous pouvez construire tout en une seule étape et ensuite installer le tout dans une deuxième étape, en invoquant le script d’installation deux fois :

python setup.py build
python setup.py install

Si vous faites cela, vous remarquerez que l’exécution de la commande install lance d’abord la commande build, qui, dans ce cas, s’aperçoit vite qu’il n’a rien à faire, puisque tout dans le dossier build est à jour.

Il se peut que vous n’ayez pas souvent besoin de cette capacité à séparer les étapes si tout ce que vous faites est d’installer les modules téléchargés sur le Net, mais c’est très pratique pour des tâches plus avancées. Si vous en venez à distribuer vos propres modules et extensions Python, vous allez exécuter beaucoup de commandes individuelles de Distutils, indépendamment les unes des autres.

Comment fonctionne une construction

Comme sous-entendu ci-dessus, la commande build est chargée de mettre les fichiers à installer dans un répertoire de travail. Par défaut, c’est build à la racine de la distribution ; si vous êtes très préoccupés par la vitesse, ou si vous voulez conserver l’arborescence des sources d’origine, vous pouvez changer le répertoire de construction avec l’option --build-base. Par exemple :

python setup.py build --build-base=/path/to/pybuild/foo-1.0

(Ou vous pourriez le faire de façon permanente avec une directive dans votre système ou dans le fichier de configuration personnelle de Distutils ; voir la section Distutils Configuration Files.) Normalement, ce n’est pas nécessaire.

L’arborescence par défaut produite par la compilation se présente comme suit :

--- build/ --- lib/
or
--- build/ --- lib.<plat>/
               temp.<plat>/

où <plat> représente une brève description de l’actuel système d’exploitation / plateforme matérielle et la version Python. La première forme, avec juste un dossier lib est utilisée pour les « distributions de modules purs » — c’est-à-dire des distributions de module qui n’incorporent que des modules en Python. Si un module de la distribution contient au moins une extension (modules écrits en C/C++), alors il faut utiliser la deuxième forme, avec deux dossiers <plat>. Dans ce cas, le répertoire temp.plat contient les fichiers temporaires générés par le processus de compilation et de génération de liens (ils ne seront pas installés). Dans les deux cas, le dossier lib (ou lib.plat) contient tous les modules Python (Python pur et extensions) qui seront installés.

Dans l’avenir, d’autres répertoires seront ajoutés pour gérer les scripts Python, de la documentation, des exécutables binaires et tout ce qui est nécessaire pour gérer le travail de l’installation de modules et d’applications Python.

Comment fonctionne l’installation

Après l’exécution de la commande build (que vous l’ayez exécutée explicitement ou que la commande install l’ait fait pour vous), le travail de la commande install est relativement simple : tout ce qu’il a à faire est de copier tout ce qui est sous build/lib (ou build/lib.plat) dans le répertoire que vous avez choisi pour l’installation.

Si vous ne choisissez aucun répertoire d’installation — c’est-à-dire, si vous lancez simplement setup.py install — alors la commande install installe le module dans l’emplacement standard pour les modules tiers de Python. Cet emplacement varie selon la plateforme et selon la façon dont vous avez construit ou installé Python lui-même. Sous UNIX (et Mac OS X, qui est également basé sur Unix), cela dépend aussi du module de la distribution en cours d’installation, suivant qu’il est en pur Python ou s’il contient des extensions (« non-pur ») :

Plateforme

Emplacement standard de l’installation

Valeur par défaut

Notes

UNIX (pur)

prefix/lib/pythonX.Y/site-packages

/usr/local/lib/pythonX.Y/site-packages

(1)

UNIX (non-pur)

exec-prefix/lib/pythonX.Y/site-packages

/usr/local/lib/pythonX.Y/site-packages

(1)

Windows

prefix\Lib\site-packages

C:\PythonXY\Lib\site-packages

(2)

Notes :

La plupart des distributions Linux incluent Python comme un élément de base du système, donc prefix et exec-prefix sont généralement tous les deux /usr sous Linux. Si vous construisez vous-même Python sous Linux (ou tout autre système de type Unix), les valeurs par défaut de prefix et exec-prefix sont souvent /usr/local.

Sous Windows, le dossier d’installation par défaut était : C:\Program Files\Python sous Python 1.6a1, 1.5.2 et avant.

prefix et exec-prefix désignent les répertoires dans lesquels Python est installé et où il trouve ses bibliothèques lors de l’exécution. Ils sont toujours identiques sous Windows et très souvent les mêmes sous Unix et Mac OS X. Vous pouvez trouver ce que votre installation de Python utilise pour prefix et exec-prefix en exécutant Python en mode interactif et en tapant quelques commandes simples. Sous Unix, tapez simplement python à l’invite du shell. Sous Windows, sélectionnez Démarrer ‣ Programmes ‣ Python X.Y ‣ Python (ligne de commande). Une fois l’interpréteur démarré, vous tapez du code Python à l’invite de commande. Par exemple, sur mon système Linux, je tape les trois instructions ci-dessous et obtiens la sortie suivante pour trouver mes prefix et exec-prefix :

Python 2.4 (#26, Aug  7 2004, 17:19:02)
Type "help", "copyright", "credits" or "license" for more information.
>>> import sys
>>> sys.prefix
'/usr'
>>> sys.exec_prefix
'/usr'

Quelques autres remplacements utilisés dans ce document : X.Y représente la version de Python, par exemple 3.2 ; abiflags sera remplacé par la valeur de sys.abiflags ou la chaine vide pour les plateformes qui ne définissent pas d’indicateurs d’ABI ; distname sera remplacé par le nom de la distribution de modules en train d’être installée. Les points et la capitalisation sont importantes dans les chemins ; par exemple, une valeur qui utilise python3.2 sur Unix utilisera typiquement Python32 sur Windows.

Si vous ne voulez pas installer des modules à l’emplacement standard, ou si vous n’avez pas la permission d’écrire à cet endroit, alors lisez la section Installation alternative relative aux installations alternatives. Si vous souhaitez personnaliser encore plus vos répertoires d’installation, lisez la section Custom Installation sur les installations personnalisées.

Installation alternative

Il est souvent nécessaire ou désirable d’installer des modules à un emplacement autre que l’emplacement standard pour les modules Python tiers. Par exemple, sur un système Unix il est possible que vous n’ayez pas la permission d’écrire dans le dossier standard pour les modules tiers. Ou vous pouvez vouloir essayer un module avant d’en faire une partie standard de votre installation locale de Python. C’est surtout vrai lors d’une mise à jour d’une distribution déjà présente : vous voulez vous assurer que votre base de scripts fonctionne encore avec la nouvelle version avant de faire la mise à jour pour de bon.

La commande install de Distutils est conçue pour rendre l’installation de distributions de modules à un emplacement alternatif simple et sans douleur. L’idée de base est que vous lui fournissez un dossier de base pour l’installation, et la commande install choisit un ensemble de dossiers (appelé le schéma d’installation) dans lequel elle installe les fichiers. Les détails diffèrent d’une plateforme à une autre, donc lisez les sections ci-dessous qui s’appliquent à vous.

Notez que les différents schémas d’installation alternative sont mutuellement exclusifs : vous pouvez passer --user, ou --home, ou --prefix et --exc-prefix, ou --install-base et --install-platbase, mais vous ne pouvez pas mélanger ces groupes.

Installation alternative : le schéma user

Ce schéma est conçu pour être la solution la plus pratique pour les utilisateurs qui n’ont pas la permission d’écrire dans le dossier site-packages global, ou qui ne veulent pas y écrire. Il est activé avec une simple option :

python setup.py install --user

Les fichiers seront installés dans des sous-dossiers de site.USER_BASE (écrit userbase dans la suite). Ce schéma installe des modules Python purs et les modules d’extension au même endroit (aussi connu sous le nom de site.USER_SITE).Voici les valeurs pour UNIX, y compris Mac OS X :

Type de fichier

Dossier d’installation

modules

userbase/lib/pythonX.Y/site-packages

scripts

userbase/bin

données

userbase

en-têtes C

userbase/include/pythonX.Yabiflags/distname

Et voici les valeurs utilisées sur Windows :

Type de fichier

Dossier d’installation

modules

userbase\PythonXY\site-packages

scripts

userbase\PythonXY\Scripts

données

userbase

en-têtes C

userbase\PythonXY\Include{distname}

L’avantage d’utiliser ce schéma plutôt que les autres décrits plus bas est que le dossier site-package du schéma user est en temps normal toujours inclus dans sys.path (voir site pour plus d’informations), ce qui signifie qu’il n’y a rien d’autre à faire après avoir exécuté le script setup.py pour finaliser l’installation.

La commande build_ext possède aussi une option --user pour ajouter userbase/include dans les chemins où le compilateur recherche les fichiers d’en-têtes et userbase/lib dans les chemins où le compilateur recherche les bibliothèques ainsi que les bibliothèques C partagées chargeables à l’exécution (rpath).

Installation alternative : le schéma home

L’idée derrière le « schéma home » est que vous compilez et maintenez un espace personnel de modules Python. Le nom de ce schéma vient de l’idée du dossier « home » sur Unix, vu qu’il n’est pas rare pour un utilisateur UNIX d’agencer son dossier home avec la même disposition que /usr/ ou /usr/local/. Ce schéma peut être utilisé par n’importe qui, quel que soit le système d’exploitation.

Installer une nouvelle distribution de module est aussi simple que :

python setup.py install --home=<dir>

où vous pouvez fournir le dossier de votre choix à l’option --home. Sur Unix, les paresseux peuvent mettre un simple tilde (~) ; la commande install le remplacera par le chemin vers votre dossier personnel :

python setup.py install --home=~

Pour que Python puisse trouver les distributions installées avec ce schéma, vous devez modifier le chemin de recherche de Python ou modifier sitecustomize (voir site) pour appeler site.addsitedir() ou modifier sys.path.

L’option --home définit le dossier de base de l’installation. Les fichiers sont installés dans les dossiers suivants sous la base de l’installation de la façon suivante :

Type de fichier

Dossier d’installation

modules

home/lib/python

scripts

home/bin

données

home

en-têtes C

home/include/python/distname

(Remplacez mentalement les slashs avec des antislashs si vous êtes sur Windows.)

Installation alternative : Unix (le schéma de préfixe)

Le schéma de préfixe est utile quand vous voulez une installation de Python pour faire la compilation/l’installation (c-à-d exécuter le script setup), mais utiliser les modules tiers d’une installation Python différente (ou quelque chose qui ressemble à une installation Python différente). Si cela vous semble inhabituel, ça l’est — c’est pourquoi les schémas user et home viennent avant. Cependant, il y a au moins deux cas connus où le schéma prefix est utile.

Premièrement, considérez que beaucoup de distributions Linux mettent Python dans /usr, plutôt que le traditionnel /usr/local. C’est tout à fait approprié, puisque dans ces cas Python fait partie du « système » plutôt que d’une addition locale. Cependant, si vous installez des modules Python depuis leur source, vous voulez probablement qu’ils aillent dans /usr/local/lib/python2.X plutôt que dans /usr/lib/python2.X. Ça peut être fait avec :

/usr/bin/python setup.py install --prefix=/usr/local

Une autre possibilité est un système de fichiers réseau où le nom utilisé pour écrire dans un dossier distant est différent du nom utilisé pour le lire : par exemple, l’interpréteur Python auquel on accède par /usr/local/bin/python peut chercher les modules dans /usr/local/lib/python2.X, mais ces modules doivent être installés dans, par exemple, /mnt/@server/export/lib/python2.X. Ça peut être fait avec :

/usr/local/bin/python setup.py install --prefix=/mnt/@server/export

Dans les deux cas, l’option --prefix définit la base de l’installation et l’option --exec-prefix définit la base d’installation spécifique à la plateforme, qui est utilisée pour des fichiers spécifiques à la plateforme (actuellement, ça ne concerne que les distributions de modules non-purs, mais cela pourrait être étendu aux bibliothèques C, exécutables, etc.). Si l’option --exec-prefix n’est pas fournie, elle vaut par défaut --prefix. Les fichiers sont installés ainsi :

Type de fichier

Dossier d’installation

Modules Python

prefix/lib/pythonX.Y/site-packages

modules d’extension

exec-prefix/lib/pythonX.Y/site-packages

scripts

prefix/bin

données

prefix

en-têtes C

prefix/include/pythonX.Yabiflags/distname

Il n’est pas obligatoire que --prefix ou --exec-prefix pointent vers une installation alternative de Python. Si les dossiers listés ci-dessus n’existent pas, ils sont créés au moment de l’installation.

Accessoirement, la vraie raison pour laquelle le schéma prefix est important est simplement qu’une installation Unix standard utilise le schéma prefix, mais avec les options --prefix et --exec-prefix fournies par Python lui-même en tant que sys.prefix et sys.exec_prefix. Vous pouvez donc penser que vous n’utiliserez jamais le schéma prefix, mais à chaque fois que vous lancez python setup.py install sans autre option, vous l’utilisez.

Notez qu’installer des extensions à une installation Python alternative n’a aucun effet sur la façon dont ces extensions sont construites. En particulier, les fichiers en-têtes de Python (Python.h et ses amis) installés avec l’interpréteur Python utilisé pour exécuter le script setup seront utilisés pour compiler les extensions. Il est de votre responsabilité de vous assurer que l’interpréteur utilisé pour exécuter les extensions installées de cette façon est compatible avec celui utilisé pour les compiler. La meilleure façon pour cela est de s’assurer qu’ils sont exactement la même version de Python (possiblement des compilations différentes, ou différentes copies de la même). (Évidemment, si vos --prefix et --exec-prefix ne pointent pas vers une installation alternative de Python, cela n’a pas de sens.)

Installation alternative : Windows (le schéma de préfixe)

Windows has no concept of a user’s home directory, and since the standard Python installation under Windows is simpler than under Unix, the --prefix option has traditionally been used to install additional packages in separate locations on Windows.

python setup.py install --prefix="\Temp\Python"

to install modules to the \Temp\Python directory on the current drive.

The installation base is defined by the --prefix option; the --exec-prefix option is not supported under Windows, which means that pure Python modules and extension modules are installed into the same location. Files are installed as follows:

Type de fichier

Dossier d’installation

modules

prefix\Lib\site-packages

scripts

prefix\Scripts

données

prefix

en-têtes C

prefix\Include{distname}

Custom Installation

Sometimes, the alternate installation schemes described in section Installation alternative just don’t do what you want. You might want to tweak just one or two directories while keeping everything under the same base directory, or you might want to completely redefine the installation scheme. In either case, you’re creating a custom installation scheme.

To create a custom installation scheme, you start with one of the alternate schemes and override some of the installation directories used for the various types of files, using these options:

Type de fichier

Override option

Modules Python

--install-purelib

modules d’extension

--install-platlib

all modules

--install-lib

scripts

--install-scripts

données

--install-data

en-têtes C

--install-headers

These override options can be relative, absolute, or explicitly defined in terms of one of the installation base directories. (There are two installation base directories, and they are normally the same—they only differ when you use the Unix « prefix scheme » and supply different --prefix and --exec-prefix options; using --install-lib will override values computed or given for --install-purelib and --install-platlib, and is recommended for schemes that don’t make a difference between Python and extension modules.)

For example, say you’re installing a module distribution to your home directory under Unix—but you want scripts to go in ~/scripts rather than ~/bin. As you might expect, you can override this directory with the --install-scripts option; in this case, it makes most sense to supply a relative path, which will be interpreted relative to the installation base directory (your home directory, in this case):

python setup.py install --home=~ --install-scripts=scripts

Another Unix example: suppose your Python installation was built and installed with a prefix of /usr/local/python, so under a standard installation scripts will wind up in /usr/local/python/bin. If you want them in /usr/local/bin instead, you would supply this absolute directory for the --install-scripts option:

python setup.py install --install-scripts=/usr/local/bin

(This performs an installation using the « prefix scheme, » where the prefix is whatever your Python interpreter was installed with— /usr/local/python in this case.)

If you maintain Python on Windows, you might want third-party modules to live in a subdirectory of prefix, rather than right in prefix itself. This is almost as easy as customizing the script installation directory—you just have to remember that there are two types of modules to worry about, Python and extension modules, which can conveniently be both controlled by one option:

python setup.py install --install-lib=Site

The specified installation directory is relative to prefix. Of course, you also have to ensure that this directory is in Python’s module search path, such as by putting a .pth file in a site directory (see site). See section Modifying Python’s Search Path to find out how to modify Python’s search path.

If you want to define an entire installation scheme, you just have to supply all of the installation directory options. The recommended way to do this is to supply relative paths; for example, if you want to maintain all Python module-related files under python in your home directory, and you want a separate directory for each platform that you use your home directory from, you might define the following installation scheme:

python setup.py install --home=~ \
                        --install-purelib=python/lib \
                        --install-platlib=python/lib.$PLAT \
                        --install-scripts=python/scripts
                        --install-data=python/data

ou :

python setup.py install --home=~/python \
                        --install-purelib=lib \
                        --install-platlib='lib.$PLAT' \
                        --install-scripts=scripts
                        --install-data=data

$PLAT is not (necessarily) an environment variable—it will be expanded by the Distutils as it parses your command line options, just as it does when parsing your configuration file(s).

Obviously, specifying the entire installation scheme every time you install a new module distribution would be very tedious. Thus, you can put these options into your Distutils config file (see section Distutils Configuration Files):

[install]
install-base=$HOME
install-purelib=python/lib
install-platlib=python/lib.$PLAT
install-scripts=python/scripts
install-data=python/data

ou (équivalent),

[install]
install-base=$HOME/python
install-purelib=lib
install-platlib=lib.$PLAT
install-scripts=scripts
install-data=data

Note that these two are not equivalent if you supply a different installation base directory when you run the setup script. For example,

python setup.py install --install-base=/tmp

would install pure modules to /tmp/python/lib in the first case, and to /tmp/lib in the second case. (For the second case, you probably want to supply an installation base of /tmp/python.)

You probably noticed the use of $HOME and $PLAT in the sample configuration file input. These are Distutils configuration variables, which bear a strong resemblance to environment variables. In fact, you can use environment variables in config files on platforms that have such a notion but the Distutils additionally define a few extra variables that may not be in your environment, such as $PLAT. (And of course, on systems that don’t have environment variables, such as Mac OS 9, the configuration variables supplied by the Distutils are the only ones you can use.) See section Distutils Configuration Files for details.

Note

When a virtual environment is activated, any options that change the installation path will be ignored from all distutils configuration files to prevent inadvertently installing projects outside of the virtual environment.

Modifying Python’s Search Path

When the Python interpreter executes an import statement, it searches for both Python code and extension modules along a search path. A default value for the path is configured into the Python binary when the interpreter is built. You can determine the path by importing the sys module and printing the value of sys.path.

$ python
Python 2.2 (#11, Oct  3 2002, 13:31:27)
[GCC 2.96 20000731 (Red Hat Linux 7.3 2.96-112)] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> import sys
>>> sys.path
['', '/usr/local/lib/python2.3', '/usr/local/lib/python2.3/plat-linux2',
 '/usr/local/lib/python2.3/lib-tk', '/usr/local/lib/python2.3/lib-dynload',
 '/usr/local/lib/python2.3/site-packages']
>>>

The null string in sys.path represents the current working directory.

The expected convention for locally installed packages is to put them in the …/site-packages/ directory, but you may want to install Python modules into some arbitrary directory. For example, your site may have a convention of keeping all software related to the web server under /www. Add-on Python modules might then belong in /www/python, and in order to import them, this directory must be added to sys.path. There are several different ways to add the directory.

The most convenient way is to add a path configuration file to a directory that’s already on Python’s path, usually to the .../site-packages/ directory. Path configuration files have an extension of .pth, and each line must contain a single path that will be appended to sys.path. (Because the new paths are appended to sys.path, modules in the added directories will not override standard modules. This means you can’t use this mechanism for installing fixed versions of standard modules.)

Paths can be absolute or relative, in which case they’re relative to the directory containing the .pth file. See the documentation of the site module for more information.

A slightly less convenient way is to edit the site.py file in Python’s standard library, and modify sys.path. site.py is automatically imported when the Python interpreter is executed, unless the -S switch is supplied to suppress this behaviour. So you could simply edit site.py and add two lines to it:

import sys
sys.path.append('/www/python/')

However, if you reinstall the same major version of Python (perhaps when upgrading from 2.2 to 2.2.2, for example) site.py will be overwritten by the stock version. You’d have to remember that it was modified and save a copy before doing the installation.

There are two environment variables that can modify sys.path. PYTHONHOME sets an alternate value for the prefix of the Python installation. For example, if PYTHONHOME is set to /www/python, the search path will be set to ['', '/www/python/lib/pythonX.Y/', '/www/python/lib/pythonX.Y/plat-linux2', ...].

The PYTHONPATH variable can be set to a list of paths that will be added to the beginning of sys.path. For example, if PYTHONPATH is set to /www/python:/opt/py, the search path will begin with ['/www/python', '/opt/py']. (Note that directories must exist in order to be added to sys.path; the site module removes paths that don’t exist.)

Finally, sys.path is just a regular Python list, so any Python application can modify it by adding or removing entries.

Distutils Configuration Files

As mentioned above, you can use Distutils configuration files to record personal or site preferences for any Distutils options. That is, any option to any command can be stored in one of two or three (depending on your platform) configuration files, which will be consulted before the command-line is parsed. This means that configuration files will override default values, and the command-line will in turn override configuration files. Furthermore, if multiple configuration files apply, values from « earlier » files are overridden by « later » files.

Location and names of config files

The names and locations of the configuration files vary slightly across platforms. On Unix and Mac OS X, the three configuration files (in the order they are processed) are:

Type de fichier

Location and filename

Notes

system

prefix/lib/pythonver/distutils/distutils.cfg

(1)

personal

$HOME/.pydistutils.cfg

(2)

local

setup.cfg

(3)

And on Windows, the configuration files are:

Type de fichier

Location and filename

Notes

system

prefix\Lib\distutils\distutils.cfg

(4)

personal

%HOME%\pydistutils.cfg

(5)

local

setup.cfg

(3)

On all platforms, the « personal » file can be temporarily disabled by passing the –no-user-cfg option.

Notes :

Strictly speaking, the system-wide configuration file lives in the directory where the Distutils are installed; under Python 1.6 and later on Unix, this is as shown. For Python 1.5.2, the Distutils will normally be installed to prefix/lib/python1.5/site-packages/distutils, so the system configuration file should be put there under Python 1.5.2.

On Unix, if the HOME environment variable is not defined, the user’s home directory will be determined with the getpwuid() function from the standard pwd module. This is done by the os.path.expanduser() function used by Distutils.

I.e., in the current directory (usually the location of the setup script).

(See also note (1).) Under Python 1.6 and later, Python’s default « installation prefix » is C:\Python, so the system configuration file is normally C:\Python\Lib\distutils\distutils.cfg. Under Python 1.5.2, the default prefix was C:\Program Files\Python, and the Distutils were not part of the standard library—so the system configuration file would be C:\Program Files\Python\distutils\distutils.cfg in a standard Python 1.5.2 installation under Windows.

On Windows, if the HOME environment variable is not defined, USERPROFILE then HOMEDRIVE and HOMEPATH will be tried. This is done by the os.path.expanduser() function used by Distutils.

Syntax of config files

The Distutils configuration files all have the same syntax. The config files are grouped into sections. There is one section for each Distutils command, plus a global section for global options that affect every command. Each section consists of one option per line, specified as option=value.

For example, the following is a complete config file that just forces all commands to run quietly by default:

[global]
verbose=0

If this is installed as the system config file, it will affect all processing of any Python module distribution by any user on the current system. If it is installed as your personal config file (on systems that support them), it will affect only module distributions processed by you. And if it is used as the setup.cfg for a particular module distribution, it affects only that distribution.

You could override the default « build base » directory and make the build* commands always forcibly rebuild all files with the following:

[build]
build-base=blib
force=1

which corresponds to the command-line arguments

python setup.py build --build-base=blib --force

except that including the build command on the command-line means that command will be run. Including a particular command in config files has no such implication; it only means that if the command is run, the options in the config file will apply. (Or if other commands that derive values from it are run, they will use the values in the config file.)

You can find out the complete list of options for any command using the --help option, e.g.:

python setup.py build --help

and you can find out the complete list of global options by using --help without a command:

python setup.py --help

See also the « Reference » section of the « Distributing Python Modules » manual.

Building Extensions: Tips and Tricks

Whenever possible, the Distutils try to use the configuration information made available by the Python interpreter used to run the setup.py script. For example, the same compiler and linker flags used to compile Python will also be used for compiling extensions. Usually this will work well, but in complicated situations this might be inappropriate. This section discusses how to override the usual Distutils behaviour.

Tweaking compiler/linker flags

Compiling a Python extension written in C or C++ will sometimes require specifying custom flags for the compiler and linker in order to use a particular library or produce a special kind of object code. This is especially true if the extension hasn’t been tested on your platform, or if you’re trying to cross-compile Python.

In the most general case, the extension author might have foreseen that compiling the extensions would be complicated, and provided a Setup file for you to edit. This will likely only be done if the module distribution contains many separate extension modules, or if they often require elaborate sets of compiler flags in order to work.

A Setup file, if present, is parsed in order to get a list of extensions to build. Each line in a Setup describes a single module. Lines have the following structure:

module ... [sourcefile ...] [cpparg ...] [library ...]

Let’s examine each of the fields in turn.

module is the name of the extension module to be built, and should be a valid Python identifier. You can’t just change this in order to rename a module (edits to the source code would also be needed), so this should be left alone.

sourcefile is anything that’s likely to be a source code file, at least judging by the filename. Filenames ending in .c are assumed to be written in C, filenames ending in .C, .cc, and .c++ are assumed to be C++, and filenames ending in .m or .mm are assumed to be in Objective C.

cpparg is an argument for the C preprocessor, and is anything starting with -I, -D, -U or -C.

library is anything ending in .a or beginning with -l or -L.

If a particular platform requires a special library on your platform, you can add it by editing the Setup file and running python setup.py build. For example, if the module defined by the line

foo foomodule.c

must be linked with the math library libm.a on your platform, simply add -lm to the line:

foo foomodule.c -lm

Arbitrary switches intended for the compiler or the linker can be supplied with the -Xcompiler arg and -Xlinker arg options:

foo foomodule.c -Xcompiler -o32 -Xlinker -shared -lm

The next option after -Xcompiler and -Xlinker will be appended to the proper command line, so in the above example the compiler will be passed the -o32 option, and the linker will be passed -shared. If a compiler option requires an argument, you’ll have to supply multiple -Xcompiler options; for example, to pass -x c++ the Setup file would have to contain -Xcompiler -x -Xcompiler c++.

Compiler flags can also be supplied through setting the CFLAGS environment variable. If set, the contents of CFLAGS will be added to the compiler flags specified in the Setup file.

Using non-Microsoft compilers on Windows

Borland/CodeGear C++

This subsection describes the necessary steps to use Distutils with the Borland C++ compiler version 5.5. First you have to know that Borland’s object file format (OMF) is different from the format used by the Python version you can download from the Python or ActiveState Web site. (Python is built with Microsoft Visual C++, which uses COFF as the object file format.) For this reason you have to convert Python’s library python25.lib into the Borland format. You can do this as follows:

coff2omf python25.lib python25_bcpp.lib

The coff2omf program comes with the Borland compiler. The file python25.lib is in the Libs directory of your Python installation. If your extension uses other libraries (zlib, …) you have to convert them too.

The converted files have to reside in the same directories as the normal libraries.

How does Distutils manage to use these libraries with their changed names? If the extension needs a library (eg. foo) Distutils checks first if it finds a library with suffix _bcpp (eg. foo_bcpp.lib) and then uses this library. In the case it doesn’t find such a special library it uses the default name (foo.lib.) 1

To let Distutils compile your extension with Borland C++ you now have to type:

python setup.py build --compiler=bcpp

If you want to use the Borland C++ compiler as the default, you could specify this in your personal or system-wide configuration file for Distutils (see section Distutils Configuration Files.)

Voir aussi

C++Builder Compiler [https://www.embarcadero.com/products]

Information about the free C++ compiler from Borland, including links to the download pages.

Creating Python Extensions Using Borland’s Free Compiler [http://www.cyberus.ca/~g_will/pyExtenDL.shtml]

Document describing how to use Borland’s free command-line C++ compiler to build Python.

GNU C / Cygwin / MinGW

This section describes the necessary steps to use Distutils with the GNU C/C++ compilers in their Cygwin and MinGW distributions. 2 For a Python interpreter that was built with Cygwin, everything should work without any of these following steps.

Not all extensions can be built with MinGW or Cygwin, but many can. Extensions most likely to not work are those that use C++ or depend on Microsoft Visual C extensions.

To let Distutils compile your extension with Cygwin you have to type:

python setup.py build --compiler=cygwin

and for Cygwin in no-cygwin mode 3 or for MinGW type:

python setup.py build --compiler=mingw32

If you want to use any of these options/compilers as default, you should consider writing it in your personal or system-wide configuration file for Distutils (see section Distutils Configuration Files.)

Older Versions of Python and MinGW

The following instructions only apply if you’re using a version of Python inferior to 2.4.1 with a MinGW inferior to 3.0.0 (with binutils-2.13.90-20030111-1).

These compilers require some special libraries. This task is more complex than for Borland’s C++, because there is no program to convert the library. First you have to create a list of symbols which the Python DLL exports. (You can find a good program for this task at https://sourceforge.net/projects/mingw/files/MinGW/Extension/pexports/).

pexports python25.dll >python25.def

The location of an installed python25.dll will depend on the installation options and the version and language of Windows. In a « just for me » installation, it will appear in the root of the installation directory. In a shared installation, it will be located in the system directory.

Then you can create from these information an import library for gcc.

/cygwin/bin/dlltool --dllname python25.dll --def python25.def --output-lib libpython25.a

The resulting library has to be placed in the same directory as python25.lib. (Should be the libs directory under your Python installation directory.)

If your extension uses other libraries (zlib,…) you might have to convert them too. The converted files have to reside in the same directories as the normal libraries do.

Voir aussi

Building Python modules on MS Windows platform with MinGW [http://old.zope.org/Members/als/tips/win32_mingw_modules]

Information about building the required libraries for the MinGW environment.

Notes

1

This also means you could replace all existing COFF-libraries with OMF-libraries of the same name.

2

Check https://www.sourceware.org/cygwin/ and http://www.mingw.org/ for more information

3

Then you have no POSIX emulation available, but you also don’t need cygwin1.dll.

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Index des modules Python

_ | a | b | c | d | e | f | g | h | i | j | k | l | m | n | o | p | q | r | s | t | u | v | w | x | z

| _ |
| __future__ | Future statement definitions
| __main__ | The environment where the top-level script is run.
| _dummy_thread | Drop-in replacement for the _thread module.
| _thread | Low-level threading API.
| a |
| abc | Abstract base classes according to PEP 3119.
| aifc | Read and write audio files in AIFF or AIFC format.
| argparse | Command-line option and argument parsing library.
| array | Space efficient arrays of uniformly typed numeric values.
| ast | Abstract Syntax Tree classes and manipulation.
| asynchat | Support for asynchronous command/response protocols.
| asyncio | Asynchronous I/O, event loop, coroutines and tasks.
| asyncore | A base class for developing asynchronous socket handling services.
| atexit | Register and execute cleanup functions.
| audioop | Manipulate raw audio data.
| b |
| base64 | RFC 3548: Base16, Base32, Base64 Data Encodings; Base85 and Ascii85
| bdb | Debugger framework.
| binascii | Tools for converting between binary and various ASCII-encoded binary representations.
| binhex | Encode and decode files in binhex4 format.
| bisect | Array bisection algorithms for binary searching.
| builtins | The module that provides the built-in namespace.
| bz2 | Interfaces for bzip2 compression and decompression.
| c |
| calendar | Functions for working with calendars, including some emulation of the Unix cal program.
| cgi | Helpers for running Python scripts via the Common Gateway Interface.
| cgitb | Configurable traceback handler for CGI scripts.
| chunk | Module to read IFF chunks.
| cmath | Mathematical functions for complex numbers.
| cmd | Build line-oriented command interpreters.
| code | Facilities to implement read-eval-print loops.
| codecs | Encode and decode data and streams.
| codeop | Compile (possibly incomplete) Python code.
- | collections | Container datatypes
|     collections.abc | Abstract base classes for containers
| colorsys | Conversion functions between RGB and other color systems.
| compileall | Tools for byte-compiling all Python source files in a directory tree.
- | concurrent |
|     concurrent.futures | Execute computations concurrently using threads or processes.
| configparser | Configuration file parser.
| contextlib | Utilities for with-statement contexts.
| copy | Shallow and deep copy operations.
| copyreg | Register pickle support functions.
| cProfile |
| crypt (Unix) | The crypt() function used to check Unix passwords.
| csv | Write and read tabular data to and from delimited files.
| ctypes | A foreign function library for Python.
- | curses (Unix) | An interface to the curses library, providing portable terminal handling.
|     curses.ascii | Constants and set-membership functions for ASCII characters.
|     curses.panel | A panel stack extension that adds depth to curses windows.
|     curses.textpad | Emacs-like input editing in a curses window.
| d |
| datetime | Basic date and time types.
- | dbm | Interfaces to various Unix "database" formats.
|     dbm.dumb | Portable implementation of the simple DBM interface.
|     dbm.gnu (Unix) | GNU's reinterpretation of dbm.
|     dbm.ndbm (Unix) | The standard "database" interface, based on ndbm.
| decimal | Implementation of the General Decimal Arithmetic Specification.
| difflib | Helpers for computing differences between objects.
| dis | Disassembler for Python bytecode.
- | distutils | Support for building and installing Python modules into an existing Python installation.
|     distutils.archive_util | Utility functions for creating archive files (tarballs, zip files, ...)
|     distutils.bcppcompiler |
|     distutils.ccompiler | Abstract CCompiler class
|     distutils.cmd | This module provides the abstract base class Command. This class is subclassed by the modules in the distutils.command subpackage.
|     distutils.command | This subpackage contains one module for each standard Distutils command.
|     distutils.command.bdist | Build a binary installer for a package
|     distutils.command.bdist_dumb | Build a "dumb" installer - a simple archive of files
|     distutils.command.bdist_msi | Build a binary distribution as a Windows MSI file
|     distutils.command.bdist_packager | Abstract base class for packagers
|     distutils.command.bdist_rpm | Build a binary distribution as a Redhat RPM and SRPM
|     distutils.command.bdist_wininst | Build a Windows installer
|     distutils.command.build | Build all files of a package
|     distutils.command.build_clib | Build any C libraries in a package
|     distutils.command.build_ext | Build any extensions in a package
|     distutils.command.build_py | Build the .py/.pyc files of a package
|     distutils.command.build_scripts | Build the scripts of a package
|     distutils.command.check | Check the metadata of a package
|     distutils.command.clean | Clean a package build area
|     distutils.command.config | Perform package configuration
|     distutils.command.install | Install a package
|     distutils.command.install_data | Install data files from a package
|     distutils.command.install_headers | Install C/C++ header files from a package
|     distutils.command.install_lib | Install library files from a package
|     distutils.command.install_scripts | Install script files from a package
|     distutils.command.register | Register a module with the Python Package Index
|     distutils.command.sdist | Build a source distribution
|     distutils.core | The core Distutils functionality
|     distutils.cygwinccompiler |
|     distutils.debug | Provides the debug flag for distutils
|     distutils.dep_util | Utility functions for simple dependency checking
|     distutils.dir_util | Utility functions for operating on directories and directory trees
|     distutils.dist | Provides the Distribution class, which represents the module distribution being built/installed/distributed
|     distutils.errors | Provides standard distutils exceptions
|     distutils.extension | Provides the Extension class, used to describe C/C++ extension modules in setup scripts
|     distutils.fancy_getopt | Additional getopt functionality
|     distutils.file_util | Utility functions for operating on single files
|     distutils.filelist | The FileList class, used for poking about the file system and building lists of files.
|     distutils.log | A simple logging mechanism, 282-style
|     distutils.msvccompiler | Microsoft Compiler
|     distutils.spawn | Provides the spawn() function
|     distutils.sysconfig | Low-level access to configuration information of the Python interpreter.
|     distutils.text_file | provides the TextFile class, a simple interface to text files
|     distutils.unixccompiler | UNIX C Compiler
|     distutils.util | Miscellaneous other utility functions
|     distutils.version | implements classes that represent module version numbers.
| doctest | Test pieces of code within docstrings.
| dummy_threading | Drop-in replacement for the threading module.
| e |
- | email | Package supporting the parsing, manipulating, and generating email messages.
|     email.charset | Character Sets
|     email.contentmanager | Storing and Retrieving Content from MIME Parts
|     email.encoders | Encoders for email message payloads.
|     email.errors | The exception classes used by the email package.
|     email.generator | Generate flat text email messages from a message structure.
|     email.header | Representing non-ASCII headers
|     email.headerregistry | Automatic Parsing of headers based on the field name
|     email.iterators | Iterate over a message object tree.
|     email.message | The base class representing email messages.
|     email.mime | Build MIME messages.
|     email.parser | Parse flat text email messages to produce a message object structure.
|     email.policy | Controlling the parsing and generating of messages
|     email.utils | Miscellaneous email package utilities.
- | encodings |
|     encodings.idna | Internationalized Domain Names implementation
|     encodings.mbcs | Windows ANSI codepage
|     encodings.utf_8_sig | UTF-8 codec with BOM signature
| ensurepip | Bootstrapping the "pip" installer into an existing Python installation or virtual environment.
| enum | Implementation of an enumeration class.
| errno | Standard errno system symbols.
| f |
| faulthandler | Dump the Python traceback.
| fcntl (Unix) | The fcntl() and ioctl() system calls.
| filecmp | Compare files efficiently.
| fileinput | Loop over standard input or a list of files.
| fnmatch | Unix shell style filename pattern matching.
| formatter | Obsolète: Generic output formatter and device interface.
| fpectl (Unix) | Provide control for floating point exception handling.
| fractions | Rational numbers.
| ftplib | FTP protocol client (requires sockets).
| functools | Higher-order functions and operations on callable objects.
| g |
| gc | Interface to the cycle-detecting garbage collector.
| getopt | Portable parser for command line options; support both short and long option names.
| getpass | Portable reading of passwords and retrieval of the userid.
| gettext | Multilingual internationalization services.
| glob | Unix shell style pathname pattern expansion.
| grp (Unix) | The group database (getgrnam() and friends).
| gzip | Interfaces for gzip compression and decompression using file objects.
| h |
| hashlib | Secure hash and message digest algorithms.
| heapq | Heap queue algorithm (a.k.a. priority queue).
| hmac | Keyed-Hashing for Message Authentication (HMAC) implementation
- | html | Helpers for manipulating HTML.
|     html.entities | Definitions of HTML general entities.
|     html.parser | A simple parser that can handle HTML and XHTML.
- | http | HTTP status codes and messages
|     http.client | HTTP and HTTPS protocol client (requires sockets).
|     http.cookiejar | Classes for automatic handling of HTTP cookies.
|     http.cookies | Support for HTTP state management (cookies).
|     http.server | HTTP server and request handlers.
| i |
| imaplib | IMAP4 protocol client (requires sockets).
| imghdr | Determine the type of image contained in a file or byte stream.
| imp | Obsolète: Access the implementation of the import statement.
- | importlib | The implementation of the import machinery.
|     importlib.abc | Abstract base classes related to import
|     importlib.machinery | Importers and path hooks
|     importlib.util | Utility code for importers
| inspect | Extract information and source code from live objects.
| io | Core tools for working with streams.
| ipaddress | IPv4/IPv6 manipulation library.
| itertools | Functions creating iterators for efficient looping.
| j |
- | json | Encode and decode the JSON format.
|     json.tool | A command line to validate and pretty-print JSON.
| k |
| keyword | Test whether a string is a keyword in Python.
| l |
| lib2to3 | the 2to3 library
| linecache | This module provides random access to individual lines from text files.
| locale | Internationalization services.
- | logging | Flexible event logging system for applications.
|     logging.config | Configuration of the logging module.
|     logging.handlers | Handlers for the logging module.
| lzma | A Python wrapper for the liblzma compression library.
| m |
| macpath | Mac OS 9 path manipulation functions.
| mailbox | Manipulate mailboxes in various formats
| mailcap | Mailcap file handling.
| marshal | Convert Python objects to streams of bytes and back (with different constraints).
| math | Mathematical functions (sin() etc.).
| mimetypes | Mapping of filename extensions to MIME types.
| mmap | Interface to memory-mapped files for Unix and Windows.
| modulefinder | Find modules used by a script.
| msilib (Windows) | Creation of Microsoft Installer files, and CAB files.
| msvcrt (Windows) | Miscellaneous useful routines from the MS VC++ runtime.
- | multiprocessing | Process-based parallelism.
|     multiprocessing.connection | API for dealing with sockets.
|     multiprocessing.dummy | Dumb wrapper around threading.
|     multiprocessing.managers | Share data between process with shared objects.
|     multiprocessing.pool | Create pools of processes.
|     multiprocessing.sharedctypes | Allocate ctypes objects from shared memory.
| n |
| netrc | Loading of .netrc files.
| nis (Unix) | Interface to Sun's NIS (Yellow Pages) library.
| nntplib | NNTP protocol client (requires sockets).
| numbers | Numeric abstract base classes (Complex, Real, Integral, etc.).
| o |
| operator | Functions corresponding to the standard operators.
| optparse | Obsolète: Command-line option parsing library.
- | os | Miscellaneous operating system interfaces.
|     os.path | Operations on pathnames.
| ossaudiodev (Linux, FreeBSD) | Access to OSS-compatible audio devices.
| p |
| parser | Access parse trees for Python source code.
| pathlib | Object-oriented filesystem paths
| pdb | The Python debugger for interactive interpreters.
| pickle | Convert Python objects to streams of bytes and back.
| pickletools | Contains extensive comments about the pickle protocols and pickle-machine opcodes, as well as some useful functions.
| pipes (Unix) | A Python interface to Unix shell pipelines.
| pkgutil | Utilities for the import system.
| platform | Retrieves as much platform identifying data as possible.
| plistlib | Generate and parse Mac OS X plist files.
| poplib | POP3 protocol client (requires sockets).
| posix (Unix) | The most common POSIX system calls (normally used via module os).
| pprint | Data pretty printer.
| profile | Python source profiler.
| pstats | Statistics object for use with the profiler.
| pty (Linux) | Pseudo-Terminal Handling for Linux.
| pwd (Unix) | The password database (getpwnam() and friends).
| py_compile | Generate byte-code files from Python source files.
| pyclbr | Supports information extraction for a Python class browser.
| pydoc | Documentation generator and online help system.
| q |
| queue | A synchronized queue class.
| quopri | Encode and decode files using the MIME quoted-printable encoding.
| r |
| random | Generate pseudo-random numbers with various common distributions.
| re | Regular expression operations.
| readline (Unix) | GNU readline support for Python.
| reprlib | Alternate repr() implementation with size limits.
| resource (Unix) | An interface to provide resource usage information on the current process.
| rlcompleter | Python identifier completion, suitable for the GNU readline library.
| runpy | Locate and run Python modules without importing them first.
| s |
| sched | General purpose event scheduler.
| secrets | Generate secure random numbers for managing secrets.
| select | Wait for I/O completion on multiple streams.
| selectors | High-level I/O multiplexing.
| shelve | Python object persistence.
| shlex | Simple lexical analysis for Unix shell-like languages.
| shutil | High-level file operations, including copying.
| signal | Set handlers for asynchronous events.
| site | Module responsible for site-specific configuration.
| smtpd | A SMTP server implementation in Python.
| smtplib | SMTP protocol client (requires sockets).
| sndhdr | Determine type of a sound file.
| socket | Low-level networking interface.
| socketserver | A framework for network servers.
| spwd (Unix) | The shadow password database (getspnam() and friends).
| sqlite3 | A DB-API 2.0 implementation using SQLite 3.x.
| ssl | TLS/SSL wrapper for socket objects
| stat | Utilities for interpreting the results of os.stat(), os.lstat() and os.fstat().
| statistics | mathematical statistics functions
| string | Common string operations.
| stringprep | String preparation, as per RFC 3453
| struct | Interpret bytes as packed binary data.
| subprocess | Subprocess management.
| sunau | Provide an interface to the Sun AU sound format.
| symbol | Constants representing internal nodes of the parse tree.
| symtable | Interface to the compiler's internal symbol tables.
| sys | Access system-specific parameters and functions.
| sysconfig | Python's configuration information
| syslog (Unix) | An interface to the Unix syslog library routines.
| t |
| tabnanny | Tool for detecting white space related problems in Python source files in a directory tree.
| tarfile | Read and write tar-format archive files.
| telnetlib | Telnet client class.
| tempfile | Generate temporary files and directories.
| termios (Unix) | POSIX style tty control.
- | test | Regression tests package containing the testing suite for Python.
|     test.support | Support for Python's regression test suite.
| textwrap | Text wrapping and filling
| threading | Thread-based parallelism.
| time | Time access and conversions.
| timeit | Measure the execution time of small code snippets.
- | tkinter | Interface to Tcl/Tk for graphical user interfaces
|     tkinter.scrolledtext (Tk) | Text widget with a vertical scroll bar.
|     tkinter.tix | Tk Extension Widgets for Tkinter
|     tkinter.ttk | Tk themed widget set
| token | Constants representing terminal nodes of the parse tree.
| tokenize | Lexical scanner for Python source code.
| trace | Trace or track Python statement execution.
| traceback | Print or retrieve a stack traceback.
| tracemalloc | Trace memory allocations.
| tty (Unix) | Utility functions that perform common terminal control operations.
| turtle | An educational framework for simple graphics applications
| turtledemo | A viewer for example turtle scripts
| types | Names for built-in types.
| typing | Support for type hints (see PEP 484).
| u |
| unicodedata | Access the Unicode Database.
- | unittest | Unit testing framework for Python.
|     unittest.mock | Mock object library.
- | urllib |
|     urllib.error | Exception classes raised by urllib.request.
|     urllib.parse | Parse URLs into or assemble them from components.
|     urllib.request | Extensible library for opening URLs.
|     urllib.response | Response classes used by urllib.
|     urllib.robotparser | Load a robots.txt file and answer questions about fetchability of other URLs.
| uu | Encode and decode files in uuencode format.
| uuid | UUID objects (universally unique identifiers) according to RFC 4122
| v |
| venv | Creation of virtual environments.
| w |
| warnings | Issue warning messages and control their disposition.
| wave | Provide an interface to the WAV sound format.
| weakref | Support for weak references and weak dictionaries.
| webbrowser | Easy-to-use controller for Web browsers.
| winreg (Windows) | Routines and objects for manipulating the Windows registry.
| winsound (Windows) | Access to the sound-playing machinery for Windows.
- | wsgiref | WSGI Utilities and Reference Implementation.
|     wsgiref.handlers | WSGI server/gateway base classes.
|     wsgiref.headers | WSGI response header tools.
|     wsgiref.simple_server | A simple WSGI HTTP server.
|     wsgiref.util | WSGI environment utilities.
|     wsgiref.validate | WSGI conformance checker.
| x |
| xdrlib | Encoders and decoders for the External Data Representation (XDR).
- | xml | Package containing XML processing modules
|     xml.dom | Document Object Model API for Python.
|     xml.dom.minidom | Minimal Document Object Model (DOM) implementation.
|     xml.dom.pulldom | Support for building partial DOM trees from SAX events.
|     xml.etree.ElementTree | Implementation of the ElementTree API.
|     xml.parsers.expat | An interface to the Expat non-validating XML parser.
|     xml.parsers.expat.errors |
|     xml.parsers.expat.model |
|     xml.sax | Package containing SAX2 base classes and convenience functions.
|     xml.sax.handler | Base classes for SAX event handlers.
|     xml.sax.saxutils | Convenience functions and classes for use with SAX.
|     xml.sax.xmlreader | Interface which SAX-compliant XML parsers must implement.
- | xmlrpc |
|     xmlrpc.client | XML-RPC client access.
|     xmlrpc.server | Basic XML-RPC server implementations.
| z |
| zipapp | Manage executable python zip archives
| zipfile | Read and write ZIP-format archive files.
| zipimport | support for importing Python modules from ZIP archives.
| zlib | Low-level interface to compression and decompression routines compatible with gzip.

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Indexer les pages par lettre:

Symboles | _ | A | B | C | D | E | F | G | H | I | J | K | L | M | N | O | P | Q | R | S | T | U | V | W | X | Y | Z

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Download Python 3.6.11 Documentation

Last updated on: juin 29, 2020.

To download an archive containing all the documents for this version of Python in one of various formats, follow one of links in this table. The numbers in the table are the size of the download files in megabytes.

Format | Packed as .zip | Packed as .tar.bz2
PDF (US-Letter paper size) | Download (ca. 13 MB) | Download (ca. 13 MB)
PDF (A4 paper size) | Download (ca. 13 MB) | Download (ca. 13 MB)
HTML | Download (ca. 9 MB) | Download (ca. 6 MB)
Plain Text | Download (ca. 3 MB) | Download (ca. 2 MB)
EPUB | Download (ca. 5.5 MB) |

These archives contain all the content in the documentation.

HTML Help (.chm) files are made available in the "Windows" section on the Python download page.

Unpacking

Unix users should download the .tar.bz2 archives; these are bzipped tar archives and can be handled in the usual way using tar and the bzip2 program. The InfoZIP unzip program can be used to handle the ZIP archives if desired. The .tar.bz2 archives provide the best compression and fastest download times.

Windows users can use the ZIP archives since those are customary on that platform. These are created on Unix using the InfoZIP zip program.

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If you have comments or suggestions for the Python documentation, please send email to docs@python.org.

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Index – A

A (dans le module re)

A-LAW, [1]

a-LAW

a2b_base64() (dans le module binascii)

a2b_hex() (dans le module binascii)

a2b_hqx() (dans le module binascii)

a2b_qp() (dans le module binascii)

a2b_uu() (dans le module binascii)

a85decode() (dans le module base64)

a85encode() (dans le module base64)

ABC (classe dans abc)

abc (module)

ABCMeta (classe dans abc)

abiflags (dans le module sys)

abort()

(dans le module os)

(méthode asyncio.DatagramTransport)

(méthode asyncio.WriteTransport)

(méthode ftplib.FTP)

(méthode threading.Barrier)

above() (méthode curses.panel.Panel)

abs

fonction de base, [1]

abs() (dans le module operator)

(fonction de base)

(méthode decimal.Context)

abspath() (dans le module os.path)

AbstractBasicAuthHandler (classe dans urllib.request)

abstractclassmethod() (dans le module abc)

AbstractContextManager (classe dans contextlib)

AbstractDigestAuthHandler (classe dans urllib.request)

AbstractEventLoop (classe dans asyncio)

AbstractEventLoopPolicy (classe dans asyncio)

AbstractFormatter (classe dans formatter)

abstractmethod() (dans le module abc)

abstractproperty() (dans le module abc)

AbstractSet (classe dans typing)

abstractstaticmethod() (dans le module abc)

AbstractWriter (classe dans formatter)

accept() (méthode asyncore.dispatcher)

(méthode multiprocessing.connection.Listener)

(méthode socket.socket)

access() (dans le module os)

accumulate() (dans le module itertools)

aclose() (méthode agen)

acos() (dans le module cmath)

(dans le module math)

acosh() (dans le module cmath)

(dans le module math)

acquire() (méthode _thread.lock)

(méthode asyncio.Condition)

(méthode asyncio.Lock)

(méthode asyncio.Semaphore)

(méthode logging.Handler)

(méthode multiprocessing.Lock)

(méthode multiprocessing.RLock)

(méthode threading.Condition)

(méthode threading.Lock)

(méthode threading.RLock)

(méthode threading.Semaphore)

acquire_lock() (dans le module imp)

action (attribut optparse.Option)

Action (classe dans argparse)

ACTIONS (attribut optparse.Option)

active_children() (dans le module multiprocessing)

active_count() (dans le module threading)

add() (dans le module audioop)

(dans le module operator)

(méthode decimal.Context)

(méthode frozenset)

(méthode mailbox.Mailbox)

(méthode mailbox.Maildir)

(méthode msilib.RadioButtonGroup)

(méthode pstats.Stats)

(méthode tarfile.TarFile)

(méthode tkinter.ttk.Notebook)

add_alias() (dans le module email.charset)

add_alternative() (méthode email.message.EmailMessage)

add_argument() (méthode argparse.ArgumentParser)

add_argument_group() (méthode argparse.ArgumentParser)

add_attachment() (méthode email.message.EmailMessage)

add_cgi_vars() (méthode wsgiref.handlers.BaseHandler)

add_charset() (dans le module email.charset)

add_codec() (dans le module email.charset)

add_cookie_header() (méthode http.cookiejar.CookieJar)

add_data() (dans le module msilib)

add_done_callback() (méthode asyncio.Future)

(méthode concurrent.futures.Future)

add_fallback() (méthode gettext.NullTranslations)

add_file() (méthode msilib.Directory)

add_flag() (méthode mailbox.MaildirMessage)

(méthode mailbox.mboxMessage)

(méthode mailbox.MMDFMessage)

add_flowing_data() (méthode formatter.formatter)

add_folder() (méthode mailbox.Maildir)

(méthode mailbox.MH)

add_get_handler() (méthode email.contentmanager.ContentManager)

add_handler() (méthode urllib.request.OpenerDirector)

add_header() (méthode email.message.EmailMessage)

(méthode email.message.Message)

(méthode urllib.request.Request)

(méthode wsgiref.headers.Headers)

add_history() (dans le module readline)

add_hor_rule() (méthode formatter.formatter)

add_include_dir() (méthode distutils.ccompiler.CCompiler)

add_label() (méthode mailbox.BabylMessage)

add_label_data() (méthode formatter.formatter)

add_library() (méthode distutils.ccompiler.CCompiler)

add_library_dir() (méthode distutils.ccompiler.CCompiler)

add_line_break() (méthode formatter.formatter)

add_link_object() (méthode distutils.ccompiler.CCompiler)

add_literal_data() (méthode formatter.formatter)

add_mutually_exclusive_group() (méthode argparse.ArgumentParser)

add_option() (méthode optparse.OptionParser)

add_parent() (méthode urllib.request.BaseHandler)

add_password() (méthode urllib.request.HTTPPasswordMgr)

(méthode urllib.request.HTTPPasswordMgrWithPriorAuth)

add_reader() (méthode asyncio.AbstractEventLoop)

add_related() (méthode email.message.EmailMessage)

add_runtime_library_dir() (méthode distutils.ccompiler.CCompiler)

add_section() (méthode configparser.ConfigParser)

(méthode configparser.RawConfigParser)

add_sequence() (méthode mailbox.MHMessage)

add_set_handler() (méthode email.contentmanager.ContentManager)

add_signal_handler() (méthode asyncio.AbstractEventLoop)

add_stream() (dans le module msilib)

add_subparsers() (méthode argparse.ArgumentParser)

add_tables() (dans le module msilib)

add_type() (dans le module mimetypes)

add_unredirected_header() (méthode urllib.request.Request)

add_writer() (méthode asyncio.AbstractEventLoop)

addch() (méthode curses.window)

addCleanup() (méthode unittest.TestCase)

addcomponent() (méthode turtle.Shape)

addError() (méthode unittest.TestResult)

addExpectedFailure() (méthode unittest.TestResult)

addFailure() (méthode unittest.TestResult)

addfile() (méthode tarfile.TarFile)

addFilter() (méthode logging.Handler)

(méthode logging.Logger)

addHandler() (méthode logging.Logger)

addition

addLevelName() (dans le module logging)

addnstr() (méthode curses.window)

AddPackagePath() (dans le module modulefinder)

addr (attribut smtpd.SMTPChannel)

addr_spec (attribut email.headerregistry.Address)

address (attribut email.headerregistry.SingleAddressHeader)

(attribut multiprocessing.connection.Listener)

(attribut multiprocessing.managers.BaseManager)

Address (classe dans email.headerregistry)

address_exclude() (méthode ipaddress.IPv4Network)

(méthode ipaddress.IPv6Network)

address_family (attribut socketserver.BaseServer)

address_string() (méthode http.server.BaseHTTPRequestHandler)

addresses (attribut email.headerregistry.AddressHeader)

(attribut email.headerregistry.Group)

AddressHeader (classe dans email.headerregistry)

addressof() (dans le module ctypes)

AddressValueError

addshape() (dans le module turtle)

addsitedir() (dans le module site)

addSkip() (méthode unittest.TestResult)

addstr() (méthode curses.window)

addSubTest() (méthode unittest.TestResult)

addSuccess() (méthode unittest.TestResult)

addTest() (méthode unittest.TestSuite)

addTests() (méthode unittest.TestSuite)

addTypeEqualityFunc() (méthode unittest.TestCase)

addUnexpectedSuccess() (méthode unittest.TestResult)

adjusted() (méthode decimal.Decimal)

adler32() (dans le module zlib)

ADPCM, Intel/DVI

adpcm2lin() (dans le module audioop)

AF_ALG (dans le module socket)

AF_CAN (dans le module socket)

AF_INET (dans le module socket)

AF_INET6 (dans le module socket)

AF_LINK (dans le module socket)

AF_PACKET (dans le module socket)

AF_RDS (dans le module socket)

AF_UNIX (dans le module socket)

aifc (module)

aifc() (méthode aifc.aifc)

AIFF, [1]

aiff() (méthode aifc.aifc)

AIFF-C, [1]

alarm() (dans le module signal)

alaw2lin() (dans le module audioop)

ALERT_DESCRIPTION_HANDSHAKE_FAILURE (dans le module ssl)

ALERT_DESCRIPTION_INTERNAL_ERROR (dans le module ssl)

AlertDescription (classe dans ssl)

algorithms_available (dans le module hashlib)

algorithms_guaranteed (dans le module hashlib)

alias (pdb command)

alias de type

alignment() (dans le module ctypes)

alive (attribut weakref.finalize)

all() (fonction de base)

all_errors (dans le module ftplib)

all_features (dans le module xml.sax.handler)

all_frames (attribut tracemalloc.Filter)

all_properties (dans le module xml.sax.handler)

all_suffixes() (dans le module importlib.machinery)

all_tasks() (méthode de la classe asyncio.Task)

allocate_lock() (dans le module _thread)

allow_reuse_address (attribut socketserver.BaseServer)

allowed_domains() (méthode http.cookiejar.DefaultCookiePolicy)

alt() (dans le module curses.ascii)

ALT_DIGITS (dans le module locale)

altsep (dans le module os)

altzone (dans le module time)

ALWAYS_TYPED_ACTIONS (attribut optparse.Option)

AMPER (dans le module token)

AMPEREQUAL (dans le module token)

and

bitwise

opérateur, [1], [2]

and_() (dans le module operator)

annotated

assignment

annotation

(attribut inspect.Parameter)

annotation de fonction

annotation de variable

annotations

function, [1]

announce() (méthode distutils.ccompiler.CCompiler)

anonymous

function

answer_challenge() (dans le module multiprocessing.connection)

anticipate_failure() (dans le module test.support)

Any (dans le module typing)

ANY (dans le module unittest.mock)

any() (fonction de base)

AnyStr (dans le module typing)

API provisoire

api_version (dans le module sys)

apop() (méthode poplib.POP3)

APPDATA

append() (méthode array.array)

(méthode collections.deque)

(méthode email.header.Header)

(méthode imaplib.IMAP4)

(méthode msilib.CAB)

(méthode pipes.Template)

(méthode xml.etree.ElementTree.Element)

(sequence method)

append_history_file() (dans le module readline)

appendChild() (méthode xml.dom.Node)

appendleft() (méthode collections.deque)

application_uri() (dans le module wsgiref.util)

apply (2to3 fixer)

apply() (méthode multiprocessing.pool.Pool)

apply_async() (méthode multiprocessing.pool.Pool)

apply_defaults() (méthode inspect.BoundArguments)

architecture() (dans le module platform)

archive (attribut zipimport.zipimporter)

aRepr (dans le module reprlib)

argparse (module)

args (attribut BaseException)

(attribut functools.partial)

(attribut inspect.BoundArguments)

(attribut subprocess.CompletedProcess)

(attribut subprocess.Popen)

(pdb command)

argtypes (attribut ctypes._FuncPtr)

argument

call semantics

difference from parameter

function

function definition

argument nommé

argument positionnel

ArgumentDefaultsHelpFormatter (classe dans argparse)

ArgumentError

ArgumentParser (classe dans argparse)

arguments (attribut inspect.BoundArguments)

argv (dans le module sys)

(in module sys)

arithmetic

conversion

operation, binary

operation, unary

ArithmeticError

array

module, [1]

array (classe dans array)

Array (classe dans ctypes)

array (module)

Array() (dans le module multiprocessing)

(dans le module multiprocessing.sharedctypes)

(méthode multiprocessing.managers.SyncManager)

arrays

arraysize (attribut sqlite3.Cursor)

arrêt de l'interpréteur

article() (méthode nntplib.NNTP)

as

except clause

import statement

mot-clé, [1], [2]

with statement

as_bytes() (méthode email.message.EmailMessage)

(méthode email.message.Message)

as_completed() (dans le module asyncio)

(dans le module concurrent.futures)

as_integer_ratio() (méthode decimal.Decimal)

(méthode float)

AS_IS (dans le module formatter)

as_posix() (méthode pathlib.PurePath)

as_string() (méthode email.message.EmailMessage)

(méthode email.message.Message)

as_tuple() (méthode decimal.Decimal)

as_uri() (méthode pathlib.PurePath)

ASCII, [1]

ascii

(dans le module re)

fonction de base

ascii() (dans le module curses.ascii)

(fonction de base)

ascii_letters (dans le module string)

ascii_lowercase (dans le module string)

ascii_uppercase (dans le module string)

asctime() (dans le module time)

asend() (méthode agen)

asin() (dans le module cmath)

(dans le module math)

asinh() (dans le module cmath)

(dans le module math)

assert

état, [1]

assert_any_call() (méthode unittest.mock.Mock)

assert_called() (méthode unittest.mock.Mock)

assert_called_once() (méthode unittest.mock.Mock)

assert_called_once_with() (méthode unittest.mock.Mock)

assert_called_with() (méthode unittest.mock.Mock)

assert_has_calls() (méthode unittest.mock.Mock)

assert_line_data() (méthode formatter.formatter)

assert_not_called() (méthode unittest.mock.Mock)

assertAlmostEqual() (méthode unittest.TestCase)

assertCountEqual() (méthode unittest.TestCase)

assertDictEqual() (méthode unittest.TestCase)

assertEqual() (méthode unittest.TestCase)

assertFalse() (méthode unittest.TestCase)

assertGreater() (méthode unittest.TestCase)

assertGreaterEqual() (méthode unittest.TestCase)

assertIn() (méthode unittest.TestCase)

AssertionError

exception

assertions

debugging

assertIs() (méthode unittest.TestCase)

assertIsInstance() (méthode unittest.TestCase)

assertIsNone() (méthode unittest.TestCase)

assertIsNot() (méthode unittest.TestCase)

assertIsNotNone() (méthode unittest.TestCase)

assertLess() (méthode unittest.TestCase)

assertLessEqual() (méthode unittest.TestCase)

assertListEqual() (méthode unittest.TestCase)

assertLogs() (méthode unittest.TestCase)

assertMultiLineEqual() (méthode unittest.TestCase)

assertNotAlmostEqual() (méthode unittest.TestCase)

assertNotEqual() (méthode unittest.TestCase)

assertNotIn() (méthode unittest.TestCase)

assertNotIsInstance() (méthode unittest.TestCase)

assertNotRegex() (méthode unittest.TestCase)

assertRaises() (méthode unittest.TestCase)

assertRaisesRegex() (méthode unittest.TestCase)

assertRegex() (méthode unittest.TestCase)

asserts (2to3 fixer)

assertSequenceEqual() (méthode unittest.TestCase)

assertSetEqual() (méthode unittest.TestCase)

assertTrue() (méthode unittest.TestCase)

assertTupleEqual() (méthode unittest.TestCase)

assertWarns() (méthode unittest.TestCase)

assertWarnsRegex() (méthode unittest.TestCase)

assignment

annotated

attribute, [1]

augmented

class attribute

class instance attribute

slice

slicing

statement, [1]

subscript

subscription

target list

AST (classe dans ast)

ast (module)

astimezone() (méthode datetime.datetime)

async

mot-clé

ASYNC (dans le module token)

async def

état

async for

état

in comprehensions, [1]

async with

état

async() (dans le module asyncio)

async_chat (classe dans asynchat)

async_chat.ac_in_buffer_size (dans le module asynchat)

async_chat.ac_out_buffer_size (dans le module asynchat)

AsyncContextManager (classe dans typing)

AsyncGenerator (classe dans collections.abc)

(classe dans typing)

AsyncGeneratorType (dans le module types)

asynchat (module)

asynchronous generator

asynchronous iterator

function

asynchronous-generator

objet

asyncio (module)

asyncio.subprocess.DEVNULL (dans le module asyncio)

asyncio.subprocess.PIPE (dans le module asyncio)

asyncio.subprocess.Process (classe dans asyncio)

asyncio.subprocess.STDOUT (dans le module asyncio)

AsyncIterable (classe dans collections.abc)

(classe dans typing)

AsyncIterator (classe dans collections.abc)

(classe dans typing)

asyncore (module)

AsyncResult (classe dans multiprocessing.pool)

AT (dans le module token)

at_eof() (méthode asyncio.StreamReader)

atan() (dans le module cmath)

(dans le module math)

atan2() (dans le module math)

atanh() (dans le module cmath)

(dans le module math)

ATEQUAL (dans le module token)

atexit (attribut weakref.finalize)

(module)

athrow() (méthode agen)

atof() (dans le module locale)

atoi() (dans le module locale)

atom

attach() (méthode email.message.Message)

attach_mock() (méthode unittest.mock.Mock)

AttlistDeclHandler() (méthode xml.parsers.expat.xmlparser)

attrgetter() (dans le module operator)

attrib (attribut xml.etree.ElementTree.Element)

attribut

attribute

assignment, [1]

assignment, class

assignment, class instance

class

class instance

deletion

generic special

reference

special

AttributeError

exception

attributes (attribut xml.dom.Node)

AttributesImpl (classe dans xml.sax.xmlreader)

AttributesNSImpl (classe dans xml.sax.xmlreader)

attroff() (méthode curses.window)

attron() (méthode curses.window)

attrset() (méthode curses.window)

Audio Interchange File Format, [1]

AUDIO_FILE_ENCODING_ADPCM_G721 (dans le module sunau)

AUDIO_FILE_ENCODING_ADPCM_G722 (dans le module sunau)

AUDIO_FILE_ENCODING_ADPCM_G723_3 (dans le module sunau)

AUDIO_FILE_ENCODING_ADPCM_G723_5 (dans le module sunau)

AUDIO_FILE_ENCODING_ALAW_8 (dans le module sunau)

AUDIO_FILE_ENCODING_DOUBLE (dans le module sunau)

AUDIO_FILE_ENCODING_FLOAT (dans le module sunau)

AUDIO_FILE_ENCODING_LINEAR_16 (dans le module sunau)

AUDIO_FILE_ENCODING_LINEAR_24 (dans le module sunau)

AUDIO_FILE_ENCODING_LINEAR_32 (dans le module sunau)

AUDIO_FILE_ENCODING_LINEAR_8 (dans le module sunau)

AUDIO_FILE_ENCODING_MULAW_8 (dans le module sunau)

AUDIO_FILE_MAGIC (dans le module sunau)

AUDIODEV

audioop (module)

augmented

assignment

auth() (méthode ftplib.FTP_TLS)

(méthode smtplib.SMTP)

authenticate() (méthode imaplib.IMAP4)

AuthenticationError

authenticators() (méthode netrc.netrc)

authkey (attribut multiprocessing.Process)

auto (classe dans enum)

autorange() (méthode timeit.Timer)

avg() (dans le module audioop)

avgpp() (dans le module audioop)

avoids_symlink_attacks (attribut shutil.rmtree)

await

in comprehensions

mot-clé, [1], [2]

AWAIT (dans le module token)

awaitable

Awaitable (classe dans collections.abc)

(classe dans typing)

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Index – B

b"

bytes literal

b'

bytes literal

b16decode() (dans le module base64)

b16encode() (dans le module base64)

b2a_base64() (dans le module binascii)

b2a_hex() (dans le module binascii)

b2a_hqx() (dans le module binascii)

b2a_qp() (dans le module binascii)

b2a_uu() (dans le module binascii)

b32decode() (dans le module base64)

b32encode() (dans le module base64)

b64decode() (dans le module base64)

b64encode() (dans le module base64)

b85decode() (dans le module base64)

b85encode() (dans le module base64)

Babyl (classe dans mailbox)

BabylMessage (classe dans mailbox)

back() (dans le module turtle)

backslash character

backslashreplace_errors() (dans le module codecs)

backward() (dans le module turtle)

BadStatusLine

BadZipFile

BadZipfile

Balloon (classe dans tkinter.tix)

Barrier (classe dans multiprocessing)

(classe dans threading)

Barrier() (méthode multiprocessing.managers.SyncManager)

base64

encoding

module

base64 (module)

base_exec_prefix (dans le module sys)

base_prefix (dans le module sys)

BaseCGIHandler (classe dans wsgiref.handlers)

BaseCookie (classe dans http.cookies)

BaseEventLoop (classe dans asyncio)

BaseException

BaseHandler (classe dans urllib.request)

(classe dans wsgiref.handlers)

BaseHeader (classe dans email.headerregistry)

BaseHTTPRequestHandler (classe dans http.server)

BaseManager (classe dans multiprocessing.managers)

basename() (dans le module os.path)

BaseProxy (classe dans multiprocessing.managers)

BaseRequestHandler (classe dans socketserver)

BaseRotatingHandler (classe dans logging.handlers)

BaseSelector (classe dans selectors)

BaseServer (classe dans socketserver)

basestring (2to3 fixer)

BaseSubprocessTransport (classe dans asyncio)

BaseTransport (classe dans asyncio)

basicConfig() (dans le module logging)

BasicContext (classe dans decimal)

BasicInterpolation (classe dans configparser)

baudrate() (dans le module curses)

bbox() (méthode tkinter.ttk.Treeview)

BDADDR_ANY (dans le module socket)

BDADDR_LOCAL (dans le module socket)

bdb

module

Bdb (classe dans bdb)

bdb (module)

BdbQuit

BDFL

bdist_msi (classe dans distutils.command.bdist_msi)

beep() (dans le module curses)

Beep() (dans le module winsound)

BEFORE_ASYNC_WITH (opcode)

begin_fill() (dans le module turtle)

begin_poly() (dans le module turtle)

below() (méthode curses.panel.Panel)

Benchmarking

benchmarking

betavariate() (dans le module random)

bgcolor() (dans le module turtle)

bgpic() (dans le module turtle)

bias() (dans le module audioop)

bidirectional() (dans le module unicodedata)

BigEndianStructure (classe dans ctypes)

bin() (fonction de base)

binary

arithmetic operation

bitwise operation

data, packing

literals

Binary (classe dans msilib)

(classe dans xmlrpc.client)

binary literal

binary mode

binary semaphores

BINARY_ADD (opcode)

BINARY_AND (opcode)

BINARY_FLOOR_DIVIDE (opcode)

BINARY_LSHIFT (opcode)

BINARY_MATRIX_MULTIPLY (opcode)

BINARY_MODULO (opcode)

BINARY_MULTIPLY (opcode)

BINARY_OR (opcode)

BINARY_POWER (opcode)

BINARY_RSHIFT (opcode)

BINARY_SUBSCR (opcode)

BINARY_SUBTRACT (opcode)

BINARY_TRUE_DIVIDE (opcode)

BINARY_XOR (opcode)

BinaryIO (classe dans typing)

binascii (module)

bind (widgets)

bind() (méthode asyncore.dispatcher)

(méthode inspect.Signature)

(méthode socket.socket)

bind_partial() (méthode inspect.Signature)

bind_port() (dans le module test.support)

bind_textdomain_codeset() (dans le module gettext)

binding

global name

name, [1], [2], [3], [4], [5], [6]

bindtextdomain() (dans le module gettext)

(dans le module locale)

binhex

module

binhex (module)

binhex() (dans le module binhex)

bisect (module)

bisect() (dans le module bisect)

bisect_left() (dans le module bisect)

bisect_right() (dans le module bisect)

bit_length() (méthode int)

bitmap() (méthode msilib.Dialog)

bitwise

and

operation, binary

operation, unary

operations

or

xor

bk() (dans le module turtle)

bkgd() (méthode curses.window)

bkgdset() (méthode curses.window)

blake2b() (dans le module hashlib)

blake2b, blake2s

blake2b.MAX_DIGEST_SIZE (dans le module hashlib)

blake2b.MAX_KEY_SIZE (dans le module hashlib)

blake2b.PERSON_SIZE (dans le module hashlib)

blake2b.SALT_SIZE (dans le module hashlib)

blake2s() (dans le module hashlib)

blake2s.MAX_DIGEST_SIZE (dans le module hashlib)

blake2s.MAX_KEY_SIZE (dans le module hashlib)

blake2s.PERSON_SIZE (dans le module hashlib)

blake2s.SALT_SIZE (dans le module hashlib)

blank line

block

code

block_size (attribut hmac.HMAC)

blocked_domains() (méthode http.cookiejar.DefaultCookiePolicy)

BlockingIOError, [1]

BNF, [1]

body() (méthode nntplib.NNTP)

body_encode() (méthode email.charset.Charset)

body_encoding (attribut email.charset.Charset)

body_line_iterator() (dans le module email.iterators)

BOM (dans le module codecs)

BOM_BE (dans le module codecs)

BOM_LE (dans le module codecs)

BOM_UTF16 (dans le module codecs)

BOM_UTF16_BE (dans le module codecs)

BOM_UTF16_LE (dans le module codecs)

BOM_UTF32 (dans le module codecs)

BOM_UTF32_BE (dans le module codecs)

BOM_UTF32_LE (dans le module codecs)

BOM_UTF8 (dans le module codecs)

bool (classe de base)

Boolean

objet, [1]

operation

operations, [1]

type

values

BOOLEAN_STATES (attribut configparser.ConfigParser)

bootstrap() (dans le module ensurepip)

border() (méthode curses.window)

bottom() (méthode curses.panel.Panel)

bottom_panel() (dans le module curses.panel)

BoundArguments (classe dans inspect)

BoundaryError

BoundedSemaphore (classe dans asyncio)

(classe dans multiprocessing)

(classe dans threading)

BoundedSemaphore() (méthode multiprocessing.managers.SyncManager)

box() (méthode curses.window)

bpformat() (méthode bdb.Breakpoint)

bpprint() (méthode bdb.Breakpoint)

break

état, [1], [2], [3], [4]

break (pdb command)

break_anywhere() (méthode bdb.Bdb)

break_here() (méthode bdb.Bdb)

break_long_words (attribut textwrap.TextWrapper)

BREAK_LOOP (opcode)

break_on_hyphens (attribut textwrap.TextWrapper)

Breakpoint (classe dans bdb)

breakpoints

broadcast_address (attribut ipaddress.IPv4Network)

(attribut ipaddress.IPv6Network)

broken (attribut threading.Barrier)

BrokenBarrierError

BrokenPipeError

BrokenProcessPool

BROWSER, [1]

BsdDbShelf (classe dans shelve)

buffer (2to3 fixer)

(attribut io.TextIOBase)

(attribut unittest.TestResult)

buffer interface

(see buffer protocol)

buffer object

(see buffer protocol)

buffer protocol

binary sequence types

str (built-in class)

buffer size, I/O

buffer_info() (méthode array.array)

buffer_size (attribut xml.parsers.expat.xmlparser)

buffer_text (attribut xml.parsers.expat.xmlparser)

buffer_used (attribut xml.parsers.expat.xmlparser)

BufferedIOBase (classe dans io)

BufferedRandom (classe dans io)

BufferedReader (classe dans io)

BufferedRWPair (classe dans io)

BufferedWriter (classe dans io)

BufferError

BufferingHandler (classe dans logging.handlers)

BufferTooShort

bufsize() (méthode ossaudiodev.oss_audio_device)

BUILD_CONST_KEY_MAP (opcode)

BUILD_LIST (opcode)

BUILD_LIST_UNPACK (opcode)

BUILD_MAP (opcode)

BUILD_MAP_UNPACK (opcode)

BUILD_MAP_UNPACK_WITH_CALL (opcode)

build_opener() (dans le module urllib.request)

build_py (classe dans distutils.command.build_py)

build_py_2to3 (classe dans distutils.command.build_py)

BUILD_SET (opcode)

BUILD_SET_UNPACK (opcode)

BUILD_SLICE (opcode)

BUILD_STRING (opcode)

BUILD_TUPLE (opcode)

BUILD_TUPLE_UNPACK (opcode)

BUILD_TUPLE_UNPACK_WITH_CALL (opcode)

built-in

method

types

built-in function

call

objet, [1]

built-in method

call

objet, [1]

builtin_module_names (dans le module sys)

BuiltinFunctionType (dans le module types)

BuiltinImporter (classe dans importlib.machinery)

BuiltinMethodType (dans le module types)

builtins

module, [1], [2], [3], [4]

builtins (module)

ButtonBox (classe dans tkinter.tix)

bye() (dans le module turtle)

byref() (dans le module ctypes)

byte

byte-code

file, [1]

byte_compile() (dans le module distutils.util)

bytearray

formatting

interpolation

methods

objet, [1], [2], [3]

bytearray (classe de base)

bytecode

Bytecode (classe dans dis)

Bytecode.codeobj (dans le module dis)

Bytecode.first_line (dans le module dis)

BYTECODE_SUFFIXES (dans le module importlib.machinery)

byteorder (dans le module sys)

bytes

fonction de base, [1]

formatting

interpolation

methods

objet, [1], [2]

str (built-in class)

bytes (attribut uuid.UUID)

(classe de base)

bytes literal

bytes_le (attribut uuid.UUID)

BytesFeedParser (classe dans email.parser)

BytesGenerator (classe dans email.generator)

BytesHeaderParser (classe dans email.parser)

BytesIO (classe dans io)

BytesParser (classe dans email.parser)

ByteString (classe dans collections.abc)

(classe dans typing)

byteswap() (dans le module audioop)

(méthode array.array)

BytesWarning

bz2 (module)

BZ2Compressor (classe dans bz2)

BZ2Decompressor (classe dans bz2)

BZ2File (classe dans bz2)

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Index – C

C

language, [1], [2], [3], [4], [5]

structures

C-contiguous, [1]

c_bool (classe dans ctypes)

C_BUILTIN (dans le module imp)

c_byte (classe dans ctypes)

c_char (classe dans ctypes)

c_char_p (classe dans ctypes)

c_contiguous (attribut memoryview)

c_double (classe dans ctypes)

C_EXTENSION (dans le module imp)

c_float (classe dans ctypes)

c_int (classe dans ctypes)

c_int16 (classe dans ctypes)

c_int32 (classe dans ctypes)

c_int64 (classe dans ctypes)

c_int8 (classe dans ctypes)

c_long (classe dans ctypes)

c_longdouble (classe dans ctypes)

c_longlong (classe dans ctypes)

c_short (classe dans ctypes)

c_size_t (classe dans ctypes)

c_ssize_t (classe dans ctypes)

c_ubyte (classe dans ctypes)

c_uint (classe dans ctypes)

c_uint16 (classe dans ctypes)

c_uint32 (classe dans ctypes)

c_uint64 (classe dans ctypes)

c_uint8 (classe dans ctypes)

c_ulong (classe dans ctypes)

c_ulonglong (classe dans ctypes)

c_ushort (classe dans ctypes)

c_void_p (classe dans ctypes)

c_wchar (classe dans ctypes)

c_wchar_p (classe dans ctypes)

CAB (classe dans msilib)

cache_from_source() (dans le module imp)

(dans le module importlib.util)

cached (attribut importlib.machinery.ModuleSpec)

CacheFTPHandler (classe dans urllib.request)

calcsize() (dans le module struct)

Calendar (classe dans calendar)

calendar (module)

calendar() (dans le module calendar)

call

built-in function

built-in method

class instance

class object, [1], [2]

function, [1], [2]

instance, [1]

method

procedure

user-defined function

call() (dans le module subprocess)

(dans le module unittest.mock)

call_args (attribut unittest.mock.Mock)

call_args_list (attribut unittest.mock.Mock)

call_at() (méthode asyncio.AbstractEventLoop)

call_count (attribut unittest.mock.Mock)

call_exception_handler() (méthode asyncio.AbstractEventLoop)

CALL_FUNCTION (opcode)

CALL_FUNCTION_EX (opcode)

CALL_FUNCTION_KW (opcode)

call_later() (méthode asyncio.AbstractEventLoop)

call_list() (méthode unittest.mock.call)

call_soon() (méthode asyncio.AbstractEventLoop)

call_soon_threadsafe() (méthode asyncio.AbstractEventLoop)

call_tracing() (dans le module sys)

callable

objet, [1]

Callable (classe dans collections.abc)

(dans le module typing)

callable() (fonction de base)

CallableProxyType (dans le module weakref)

callback (attribut optparse.Option)

callback() (méthode contextlib.ExitStack)

callback_args (attribut optparse.Option)

callback_kwargs (attribut optparse.Option)

callbacks (dans le module gc)

called (attribut unittest.mock.Mock)

CalledProcessError

calloc()

CAN_BCM (dans le module socket)

can_change_color() (dans le module curses)

can_fetch() (méthode urllib.robotparser.RobotFileParser)

CAN_RAW_FD_FRAMES (dans le module socket)

can_symlink() (dans le module test.support)

can_write_eof() (méthode asyncio.StreamWriter)

(méthode asyncio.WriteTransport)

cancel() (méthode asyncio.Future)

(méthode asyncio.Handle)

(méthode asyncio.Task)

(méthode concurrent.futures.Future)

(méthode sched.scheduler)

(méthode threading.Timer)

cancel_dump_traceback_later() (dans le module faulthandler)

cancel_join_thread() (méthode multiprocessing.Queue)

cancelled() (méthode asyncio.Future)

(méthode concurrent.futures.Future)

CancelledError

CannotSendHeader

CannotSendRequest

canonic() (méthode bdb.Bdb)

canonical() (méthode decimal.Context)

(méthode decimal.Decimal)

capa() (méthode poplib.POP3)

capitalize() (méthode bytearray)

(méthode bytes)

(méthode str)

Capsule

objet

captured_stderr() (dans le module test.support)

captured_stdin() (dans le module test.support)

captured_stdout() (dans le module test.support)

captureWarnings() (dans le module logging)

capwords() (dans le module string)

casefold() (méthode str)

cast() (dans le module ctypes)

(dans le module typing)

(méthode memoryview)

cat() (dans le module nis)

catch_warnings (classe dans warnings)

category() (dans le module unicodedata)

cbreak() (dans le module curses)

CC

ccc() (méthode ftplib.FTP_TLS)

CCompiler (classe dans distutils.ccompiler)

CDLL (classe dans ctypes)

ceil() (dans le module math)

(in module math)

center() (méthode bytearray)

(méthode bytes)

(méthode str)

CERT_NONE (dans le module ssl)

CERT_OPTIONAL (dans le module ssl)

CERT_REQUIRED (dans le module ssl)

cert_store_stats() (méthode ssl.SSLContext)

cert_time_to_seconds() (dans le module ssl)

CertificateError

certificates

CFLAGS, [1], [2]

CFUNCTYPE() (dans le module ctypes)

CGI

debugging

exceptions

protocol

security

tracebacks

cgi (module)

cgi_directories (attribut http.server.CGIHTTPRequestHandler)

CGIHandler (classe dans wsgiref.handlers)

CGIHTTPRequestHandler (classe dans http.server)

cgitb (module)

CGIXMLRPCRequestHandler (classe dans xmlrpc.server)

chain() (dans le module itertools)

chaining

comparisons, [1]

exception

ChainMap (classe dans collections)

(classe dans typing)

chaîne entre triple guillemets

change_cwd() (dans le module test.support)

change_root() (dans le module distutils.util)

CHANNEL_BINDING_TYPES (dans le module ssl)

channel_class (attribut smtpd.SMTPServer)

channels() (méthode ossaudiodev.oss_audio_device)

CHAR_MAX (dans le module locale)

character, [1], [2]

CharacterDataHandler() (méthode xml.parsers.expat.xmlparser)

characters() (méthode xml.sax.handler.ContentHandler)

characters_written (attribut BlockingIOError)

chargeur

Charset (classe dans email.charset)

charset() (méthode gettext.NullTranslations)

chdir() (dans le module os)

check (attribut lzma.LZMADecompressor)

check() (dans le module tabnanny)

(méthode imaplib.IMAP4)

check__all__() (dans le module test.support)

check_call() (dans le module subprocess)

check_environ() (dans le module distutils.util)

check_hostname (attribut ssl.SSLContext)

check_output() (dans le module subprocess)

(méthode doctest.OutputChecker)

check_returncode() (méthode subprocess.CompletedProcess)

check_unused_args() (méthode string.Formatter)

check_warnings() (dans le module test.support)

checkbox() (méthode msilib.Dialog)

checkcache() (dans le module linecache)

checkfuncname() (dans le module bdb)

CheckList (classe dans tkinter.tix)

checksum

Cyclic Redundancy Check

chemin des importations

chercheur

chercheur basé sur les chemins

chercheur dans les méta-chemins

chercheur de chemins

chflags() (dans le module os)

chgat() (méthode curses.window)

childNodes (attribut xml.dom.Node)

ChildProcessError

chmod() (dans le module os)

(méthode pathlib.Path)

choice() (dans le module random)

(dans le module secrets)

choices (attribut optparse.Option)

choices() (dans le module random)

chown() (dans le module os)

(dans le module shutil)

chr

fonction de base

chr() (fonction de base)

chroot() (dans le module os)

Chunk (classe dans chunk)

chunk (module)

cipher

DES

cipher() (méthode ssl.SSLSocket)

circle() (dans le module turtle)

CIRCUMFLEX (dans le module token)

CIRCUMFLEXEQUAL (dans le module token)

Clamped (classe dans decimal)

class

attribute

attribute assignment

body

constructor

definition, [1]

état

instance

name

objet, [1], [2]

Class (classe dans symtable)

Class browser

class instance

attribute

attribute assignment

call

objet, [1], [2]

class object

call, [1], [2]

classe

classe de base abstraite

classmethod

fonction de base

classmethod() (fonction de base)

ClassVar (dans le module typing)

clause

CLD_CONTINUED (dans le module os)

CLD_DUMPED (dans le module os)

CLD_EXITED (dans le module os)

CLD_TRAPPED (dans le module os)

clean() (méthode mailbox.Maildir)

cleandoc() (dans le module inspect)

cleanup functions

clear (pdb command)

Clear Breakpoint

clear() (dans le module turtle), [1]

(méthode asyncio.Event)

(méthode collections.deque)

(méthode curses.window)

(méthode dict)

(méthode email.message.EmailMessage)

(méthode frame)

(méthode frozenset)

(méthode http.cookiejar.CookieJar)

(méthode mailbox.Mailbox)

(méthode threading.Event)

(méthode xml.etree.ElementTree.Element)

(sequence method)

clear_all_breaks() (méthode bdb.Bdb)

clear_all_file_breaks() (méthode bdb.Bdb)

clear_bpbynumber() (méthode bdb.Bdb)

clear_break() (méthode bdb.Bdb)

clear_cache() (dans le module filecmp)

clear_content() (méthode email.message.EmailMessage)

clear_flags() (méthode decimal.Context)

clear_frames() (dans le module traceback)

clear_history() (dans le module readline)

clear_session_cookies() (méthode http.cookiejar.CookieJar)

clear_traces() (dans le module tracemalloc)

clear_traps() (méthode decimal.Context)

clearcache() (dans le module linecache)

ClearData() (méthode msilib.Record)

clearok() (méthode curses.window)

clearscreen() (dans le module turtle)

clearstamp() (dans le module turtle)

clearstamps() (dans le module turtle)

Client() (dans le module multiprocessing.connection)

client_address (attribut http.server.BaseHTTPRequestHandler)

clock() (dans le module time)

clock_getres() (dans le module time)

clock_gettime() (dans le module time)

CLOCK_HIGHRES (dans le module time)

CLOCK_MONOTONIC (dans le module time)

CLOCK_MONOTONIC_RAW (dans le module time)

CLOCK_PROCESS_CPUTIME_ID (dans le module time)

CLOCK_REALTIME (dans le module time)

clock_settime() (dans le module time)

CLOCK_THREAD_CPUTIME_ID (dans le module time)

clone() (dans le module turtle)

(méthode email.generator.BytesGenerator)

(méthode email.generator.Generator)

(méthode email.policy.Policy)

(méthode pipes.Template)

cloneNode() (méthode xml.dom.Node)

close() (dans le module fileinput)

(dans le module os)

(in module os)

(méthode aifc.aifc), [1]

(méthode asyncio.AbstractEventLoop)

(méthode asyncio.BaseSubprocessTransport)

(méthode asyncio.BaseTransport)

(méthode asyncio.Server)

(méthode asyncio.StreamWriter)

(méthode asyncore.dispatcher)

(méthode chunk.Chunk)

(méthode contextlib.ExitStack)

(méthode coroutine)

(méthode dbm.dumb.dumbdbm)

(méthode dbm.gnu.gdbm)

(méthode dbm.ndbm.ndbm)

(méthode distutils.text_file.TextFile)

(méthode email.parser.BytesFeedParser)

(méthode ftplib.FTP)

(méthode generator)

(méthode html.parser.HTMLParser)

(méthode http.client.HTTPConnection)

(méthode imaplib.IMAP4)

(méthode io.IOBase)

(méthode logging.FileHandler)

(méthode logging.Handler)

(méthode logging.handlers.MemoryHandler)

(méthode logging.handlers.NTEventLogHandler)

(méthode logging.handlers.SocketHandler)

(méthode logging.handlers.SysLogHandler)

(méthode mailbox.Mailbox)

(méthode mailbox.Maildir)

(méthode mailbox.MH)

(méthode mmap.mmap)

Close() (méthode msilib.View)

close() (méthode multiprocessing.connection.Connection)

(méthode multiprocessing.connection.Listener)

(méthode multiprocessing.pool.Pool)

(méthode multiprocessing.Queue)

(méthode os.scandir)

(méthode ossaudiodev.oss_audio_device)

(méthode ossaudiodev.oss_mixer_device)

(méthode select.devpoll)

(méthode select.epoll)

(méthode select.kqueue)

(méthode selectors.BaseSelector)

(méthode shelve.Shelf)

(méthode socket.socket)

(méthode sqlite3.Connection)

(méthode sqlite3.Cursor)

(méthode sunau.AU_read)

(méthode sunau.AU_write)

(méthode tarfile.TarFile)

(méthode telnetlib.Telnet)

(méthode urllib.request.BaseHandler)

(méthode wave.Wave_read)

(méthode wave.Wave_write)

Close() (méthode winreg.PyHKEY)

close() (méthode xml.etree.ElementTree.TreeBuilder)

(méthode xml.etree.ElementTree.XMLParser)

(méthode xml.etree.ElementTree.XMLPullParser)

(méthode xml.sax.xmlreader.IncrementalParser)

(méthode zipfile.ZipFile)

close_connection (attribut http.server.BaseHTTPRequestHandler)

close_when_done() (méthode asynchat.async_chat)

closed (attribut http.client.HTTPResponse)

(attribut io.IOBase)

(attribut mmap.mmap)

(attribut ossaudiodev.oss_audio_device)

(attribut select.devpoll)

(attribut select.epoll)

(attribut select.kqueue)

CloseKey() (dans le module winreg)

closelog() (dans le module syslog)

closerange() (dans le module os)

closing() (dans le module contextlib)

clrtobot() (méthode curses.window)

clrtoeol() (méthode curses.window)

cmath (module)

cmd

module

cmd (attribut subprocess.CalledProcessError)

(attribut subprocess.TimeoutExpired)

Cmd (classe dans cmd)

cmd (module)

cmdloop() (méthode cmd.Cmd)

cmdqueue (attribut cmd.Cmd)

cmp() (dans le module filecmp)

cmp_op (dans le module dis)

cmp_to_key() (dans le module functools)

cmpfiles() (dans le module filecmp)

CMSG_LEN() (dans le module socket)

CMSG_SPACE() (dans le module socket)

co_argcount (code object attribute)

CO_ASYNC_GENERATOR (dans le module inspect)

co_cellvars (code object attribute)

co_code (code object attribute)

co_consts (code object attribute)

CO_COROUTINE (dans le module inspect)

co_filename (code object attribute)

co_firstlineno (code object attribute)

co_flags (code object attribute)

co_freevars (code object attribute)

CO_FUTURE_DIVISION (variable C)

CO_GENERATOR (dans le module inspect)

CO_ITERABLE_COROUTINE (dans le module inspect)

co_lnotab (code object attribute)

co_name (code object attribute)

co_names (code object attribute)

CO_NESTED (dans le module inspect)

CO_NEWLOCALS (dans le module inspect)

co_nlocals (code object attribute)

CO_NOFREE (dans le module inspect)

CO_OPTIMIZED (dans le module inspect)

co_stacksize (code object attribute)

CO_VARARGS (dans le module inspect)

CO_VARKEYWORDS (dans le module inspect)

co_varnames (code object attribute)

code

block

code (attribut SystemExit)

(attribut urllib.error.HTTPError)

(attribut xml.etree.ElementTree.ParseError)

(attribut xml.parsers.expat.ExpatError)

(module)

code intermédiaire (bytecode)

code object, [1], [2], [3]

code_info() (dans le module dis)

CodecInfo (classe dans codecs)

Codecs

decode

encode

codecs (module)

coded_value (attribut http.cookies.Morsel)

codeop (module)

codepoint2name (dans le module html.entities)

codes (dans le module xml.parsers.expat.errors)

CODESET (dans le module locale)

CodeType (dans le module types)

coding

style

coercition

col_offset (attribut ast.AST)

collapse_addresses() (dans le module ipaddress)

collapse_rfc2231_value() (dans le module email.utils)

collect() (dans le module gc)

collect_incoming_data() (méthode asynchat.async_chat)

Collection (classe dans collections.abc)

(classe dans typing)

collections (module)

collections.abc (module)

colno (attribut json.JSONDecodeError)

(attribut re.error)

COLON (dans le module token)

color() (dans le module turtle)

color_content() (dans le module curses)

color_pair() (dans le module curses)

colormode() (dans le module turtle)

colorsys (module)

COLS, [1]

column() (méthode tkinter.ttk.Treeview)

COLUMNS, [1]

columns (attribut os.terminal_size)

combinations() (dans le module itertools)

combinations_with_replacement() (dans le module itertools)

combine() (méthode de la classe datetime.datetime)

combining() (dans le module unicodedata)

ComboBox (classe dans tkinter.tix)

Combobox (classe dans tkinter.ttk)

comma

trailing

tuple display

COMMA (dans le module token)

command (attribut http.server.BaseHTTPRequestHandler)

Command (classe dans distutils.cmd)

(classe dans distutils.core)

command line

command line option

--help

--version

-?

-b

-B

-c <command>

-d

-E

-h

-i

-I

-J

-m <module-name>

-O

-OO

-q

-R

-s

-S

-u

-V

-v

-W arg

-x

-X

CommandCompiler (classe dans codeop)

commands (pdb command)

comment

(attribut http.cookiejar.Cookie)

(attribut zipfile.ZipFile)

(attribut zipfile.ZipInfo)

COMMENT (dans le module tokenize)

Comment() (dans le module xml.etree.ElementTree)

comment_url (attribut http.cookiejar.Cookie)

commenters (attribut shlex.shlex)

CommentHandler() (méthode xml.parsers.expat.xmlparser)

commit() (méthode msilib.CAB)

Commit() (méthode msilib.Database)

commit() (méthode sqlite3.Connection)

common (attribut filecmp.dircmp)

Common Gateway Interface

common_dirs (attribut filecmp.dircmp)

common_files (attribut filecmp.dircmp)

common_funny (attribut filecmp.dircmp)

common_types (dans le module mimetypes)

commonpath() (dans le module os.path)

commonprefix() (dans le module os.path)

communicate() (méthode asyncio.asyncio.subprocess.Process)

(méthode subprocess.Popen)

compare() (méthode decimal.Context)

(méthode decimal.Decimal)

(méthode difflib.Differ)

compare_digest() (dans le module hmac)

(dans le module secrets)

compare_networks() (méthode ipaddress.IPv4Network)

(méthode ipaddress.IPv6Network)

COMPARE_OP (opcode)

compare_signal() (méthode decimal.Context)

(méthode decimal.Decimal)

compare_to() (méthode tracemalloc.Snapshot)

compare_total() (méthode decimal.Context)

(méthode decimal.Decimal)

compare_total_mag() (méthode decimal.Context)

(méthode decimal.Decimal)

comparing

objects

comparison

operator

COMPARISON_FLAGS (dans le module doctest)

comparisons

chaining, [1]

Compat32 (classe dans email.policy)

compat32 (dans le module email.policy)

compile

fonction de base, [1], [2], [3], [4]

Compile (classe dans codeop)

compile() (dans le module py_compile)

(dans le module re)

(fonction de base)

(méthode distutils.ccompiler.CCompiler)

(méthode parser.ST)

compile_command() (dans le module code)

(dans le module codeop)

compile_dir() (dans le module compileall)

compile_file() (dans le module compileall)

compile_path() (dans le module compileall)

compileall (module)

compileall command line option

-b

-d destdir

-f

-i list

-j N

-l

-q

-r

-x regex

directory ...

file ...

compilest() (dans le module parser)

complete() (méthode rlcompleter.Completer)

complete_statement() (dans le module sqlite3)

completedefault() (méthode cmd.Cmd)

CompletedProcess (classe dans subprocess)

complex

fonction de base, [1]

number

objet

Complex (classe dans numbers)

complex (classe de base)

complex literal

complex number

literals

objet, [1]

compound

statement

comprehensions

list

compress() (dans le module bz2)

(dans le module gzip)

(dans le module itertools)

(dans le module lzma)

(dans le module zlib)

(méthode bz2.BZ2Compressor)

(méthode lzma.LZMACompressor)

(méthode zlib.Compress)

compress_size (attribut zipfile.ZipInfo)

compress_type (attribut zipfile.ZipInfo)

compressed (attribut ipaddress.IPv4Address)

(attribut ipaddress.IPv4Network)

(attribut ipaddress.IPv6Address)

(attribut ipaddress.IPv6Network)

compression() (méthode ssl.SSLSocket)

CompressionError

compressobj() (dans le module zlib)

COMSPEC, [1]

concat() (dans le module operator)

concatenation

operation

concurrent.futures (module)

Condition (classe dans asyncio)

(classe dans multiprocessing)

(classe dans threading)

condition (pdb command)

condition() (méthode msilib.Control)

Condition() (méthode multiprocessing.managers.SyncManager)

Conditional

expression

conditional

expression

ConfigParser (classe dans configparser)

configparser (module)

configuration

file

file, debugger

file, path

configuration information

configure() (méthode tkinter.ttk.Style)

configure_mock() (méthode unittest.mock.Mock)

confstr() (dans le module os)

confstr_names (dans le module os)

conjugate() (complex number method)

(méthode decimal.Decimal)

(méthode numbers.Complex)

conn (attribut smtpd.SMTPChannel)

connect() (dans le module sqlite3)

(méthode asyncore.dispatcher)

(méthode ftplib.FTP)

(méthode http.client.HTTPConnection)

(méthode multiprocessing.managers.BaseManager)

(méthode smtplib.SMTP)

(méthode socket.socket)

connect_accepted_socket() (méthode asyncio.BaseEventLoop)

connect_ex() (méthode socket.socket)

connect_read_pipe() (méthode asyncio.AbstractEventLoop)

connect_write_pipe() (méthode asyncio.AbstractEventLoop)

connection (attribut sqlite3.Cursor)

Connection (classe dans multiprocessing.connection)

(classe dans sqlite3)

connection_lost() (méthode asyncio.BaseProtocol)

connection_made() (méthode asyncio.BaseProtocol)

ConnectionAbortedError

ConnectionError

ConnectionRefusedError

ConnectionResetError

ConnectRegistry() (dans le module winreg)

const (attribut optparse.Option)

constant

constructor

class

constructor() (dans le module copyreg)

consumed (attribut asyncio.LimitOverrunError)

container, [1]

iteration over

Container (classe dans collections.abc)

(classe dans typing)

contains() (dans le module operator)

content type

MIME

content_manager (attribut email.policy.EmailPolicy)

content_type (attribut email.headerregistry.ContentTypeHeader)

ContentDispositionHeader (classe dans email.headerregistry)

ContentHandler (classe dans xml.sax.handler)

ContentManager (classe dans email.contentmanager)

contents (attribut ctypes._Pointer)

ContentTooShortError

ContentTransferEncoding (classe dans email.headerregistry)

ContentTypeHeader (classe dans email.headerregistry)

context (attribut ssl.SSLSocket)

Context (classe dans decimal)

context management protocol

context manager, [1]

context_diff() (dans le module difflib)

ContextDecorator (classe dans contextlib)

contextlib (module)

ContextManager (classe dans typing)

contextmanager() (dans le module contextlib)

contigu

contiguous

(attribut memoryview)

continue

état, [1], [2], [3], [4]

continue (pdb command)

CONTINUE_LOOP (opcode)

Control (classe dans msilib)

(classe dans tkinter.tix)

control() (méthode msilib.Dialog)

(méthode select.kqueue)

controlnames (dans le module curses.ascii)

controls() (méthode ossaudiodev.oss_mixer_device)

conversion

arithmetic

string, [1]

ConversionError

conversions

numeric

convert_arg_line_to_args() (méthode argparse.ArgumentParser)

convert_field() (méthode string.Formatter)

convert_path() (dans le module distutils.util)

Cookie (classe dans http.cookiejar)

CookieError

cookiejar (attribut urllib.request.HTTPCookieProcessor)

CookieJar (classe dans http.cookiejar)

CookiePolicy (classe dans http.cookiejar)

Coordinated Universal Time

Copy

copy

module

protocol

copy (module)

copy() (dans le module copy)

(dans le module multiprocessing.sharedctypes)

(dans le module shutil)

(méthode collections.deque)

(méthode decimal.Context)

(méthode dict)

(méthode frozenset)

(méthode hashlib.hash)

(méthode hmac.HMAC)

(méthode http.cookies.Morsel)

(méthode imaplib.IMAP4)

(méthode pipes.Template)

(méthode types.MappingProxyType)

(méthode zlib.Compress)

(méthode zlib.Decompress)

(sequence method)

copy2() (dans le module shutil)

copy_abs() (méthode decimal.Context)

(méthode decimal.Decimal)

copy_decimal() (méthode decimal.Context)

copy_file() (dans le module distutils.file_util)

copy_location() (dans le module ast)

copy_negate() (méthode decimal.Context)

(méthode decimal.Decimal)

copy_sign() (méthode decimal.Context)

(méthode decimal.Decimal)

copy_tree() (dans le module distutils.dir_util)

copyfile() (dans le module shutil)

copyfileobj() (dans le module shutil)

copying files

copymode() (dans le module shutil)

copyreg (module)

copyright (dans le module sys)

(in module sys)

(variable de base)

copysign() (dans le module math)

copystat() (dans le module shutil)

copytree() (dans le module shutil)

coroutine, [1], [2]

function

Coroutine (classe dans collections.abc)

(classe dans typing)

coroutine() (dans le module asyncio)

(dans le module types)

CoroutineType (dans le module types)

cos() (dans le module cmath)

(dans le module math)

cosh() (dans le module cmath)

(dans le module math)

count (attribut tracemalloc.Statistic)

(attribut tracemalloc.StatisticDiff)

count() (dans le module itertools)

(méthode array.array)

(méthode bytearray)

(méthode bytes)

(méthode collections.deque)

(méthode str)

(sequence method)

count_diff (attribut tracemalloc.StatisticDiff)

Counter (classe dans collections)

(classe dans typing)

countOf() (dans le module operator)

countTestCases() (méthode unittest.TestCase)

(méthode unittest.TestSuite)

CoverageResults (classe dans trace)

CPP

CPPFLAGS

cProfile (module)

CPU time

cpu_count() (dans le module multiprocessing)

(dans le module os)

CPython

crawl_delay() (méthode urllib.robotparser.RobotFileParser)

CRC (attribut zipfile.ZipInfo)

crc32() (dans le module binascii)

(dans le module zlib)

crc_hqx() (dans le module binascii)

create() (dans le module venv)

(méthode imaplib.IMAP4)

(méthode venv.EnvBuilder)

create_aggregate() (méthode sqlite3.Connection)

create_archive() (dans le module zipapp)

create_autospec() (dans le module unittest.mock)

create_collation() (méthode sqlite3.Connection)

create_configuration() (méthode venv.EnvBuilder)

create_connection() (dans le module socket)

(méthode asyncio.AbstractEventLoop)

create_datagram_endpoint() (méthode asyncio.AbstractEventLoop)

create_decimal() (méthode decimal.Context)

create_decimal_from_float() (méthode decimal.Context)

create_default_context() (dans le module ssl)

create_function() (méthode sqlite3.Connection)

create_future() (méthode asyncio.AbstractEventLoop)

create_module (fonction C)

create_module() (méthode importlib.abc.Loader)

(méthode importlib.machinery.ExtensionFileLoader)

CREATE_NEW_CONSOLE (dans le module subprocess)

CREATE_NEW_PROCESS_GROUP (dans le module subprocess)

create_server() (méthode asyncio.AbstractEventLoop)

create_shortcut() (fonction de base)

create_socket() (méthode asyncore.dispatcher)

create_static_lib() (méthode distutils.ccompiler.CCompiler)

create_stats() (méthode profile.Profile)

create_string_buffer() (dans le module ctypes)

create_subprocess_exec() (dans le module asyncio)

create_subprocess_shell() (dans le module asyncio)

create_system (attribut zipfile.ZipInfo)

create_task() (méthode asyncio.AbstractEventLoop)

create_tree() (dans le module distutils.dir_util)

create_unicode_buffer() (dans le module ctypes)

create_unix_connection() (méthode asyncio.AbstractEventLoop)

create_unix_server() (méthode asyncio.AbstractEventLoop)

create_version (attribut zipfile.ZipInfo)

createAttribute() (méthode xml.dom.Document)

createAttributeNS() (méthode xml.dom.Document)

createComment() (méthode xml.dom.Document)

createDocument() (méthode xml.dom.DOMImplementation)

createDocumentType() (méthode xml.dom.DOMImplementation)

createElement() (méthode xml.dom.Document)

createElementNS() (méthode xml.dom.Document)

createfilehandler() (méthode tkinter.Widget.tk)

CreateKey() (dans le module winreg)

CreateKeyEx() (dans le module winreg)

createLock() (méthode logging.Handler)

(méthode logging.NullHandler)

createProcessingInstruction() (méthode xml.dom.Document)

CreateRecord() (dans le module msilib)

createSocket() (méthode logging.handlers.SocketHandler)

createTextNode() (méthode xml.dom.Document)

credits (variable de base)

critical() (dans le module logging)

(méthode logging.Logger)

CRNCYSTR (dans le module locale)

cross() (dans le module audioop)

crypt

module

crypt (module)

crypt() (dans le module crypt)

crypt(3), [1], [2]

cryptography

csv

(module)

cte (attribut email.headerregistry.ContentTransferEncoding)

cte_type (attribut email.policy.Policy)

ctermid() (dans le module os)

ctime() (dans le module time)

(méthode datetime.date)

(méthode datetime.datetime)

ctrl() (dans le module curses.ascii)

CTRL_BREAK_EVENT (dans le module signal)

CTRL_C_EVENT (dans le module signal)

ctypes (module)

curdir (dans le module os)

currency() (dans le module locale)

current() (méthode tkinter.ttk.Combobox)

current_process() (dans le module multiprocessing)

current_task() (méthode de la classe asyncio.Task)

current_thread() (dans le module threading)

CurrentByteIndex (attribut xml.parsers.expat.xmlparser)

CurrentColumnNumber (attribut xml.parsers.expat.xmlparser)

currentframe() (dans le module inspect)

CurrentLineNumber (attribut xml.parsers.expat.xmlparser)

curs_set() (dans le module curses)

curses (module)

curses.ascii (module)

curses.panel (module)

curses.textpad (module)

Cursor (classe dans sqlite3)

cursor() (méthode sqlite3.Connection)

cursyncup() (méthode curses.window)

customize_compiler() (dans le module distutils.sysconfig)

Cut

cwd() (méthode de la classe pathlib.Path)

(méthode ftplib.FTP)

cycle() (dans le module itertools)

Cyclic Redundancy Check

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Index – D

D_FMT (dans le module locale)

D_T_FMT (dans le module locale)

daemon (attribut multiprocessing.Process)

(attribut threading.Thread)

dangling

else

data

packing binary

tabular

type

type, immutable

data (attribut collections.UserDict)

(attribut collections.UserList)

(attribut select.kevent)

(attribut selectors.SelectorKey)

(attribut urllib.request.Request)

(attribut xml.dom.Comment)

(attribut xml.dom.ProcessingInstruction)

(attribut xml.dom.Text)

(attribut xmlrpc.client.Binary)

Data (classe dans plistlib)

data() (méthode xml.etree.ElementTree.TreeBuilder)

data_open() (méthode urllib.request.DataHandler)

data_received() (méthode asyncio.Protocol)

database

Unicode

DatabaseError

databases

datagram_received() (méthode asyncio.DatagramProtocol)

DatagramHandler (classe dans logging.handlers)

DatagramProtocol (classe dans asyncio)

DatagramRequestHandler (classe dans socketserver)

DataHandler (classe dans urllib.request)

date (classe dans datetime)

date() (méthode datetime.datetime)

(méthode nntplib.NNTP)

date_time (attribut zipfile.ZipInfo)

date_time_string() (méthode http.server.BaseHTTPRequestHandler)

DateHeader (classe dans email.headerregistry)

datetime (attribut email.headerregistry.DateHeader)

(classe dans datetime)

DateTime (classe dans xmlrpc.client)

datetime (module)

datum

day (attribut datetime.date)

(attribut datetime.datetime)

day_abbr (dans le module calendar)

day_name (dans le module calendar)

daylight (dans le module time)

Daylight Saving Time

DbfilenameShelf (classe dans shelve)

dbm (module)

dbm.dumb (module)

dbm.gnu

module, [1]

dbm.gnu (module)

dbm.ndbm

module, [1]

dbm.ndbm (module)

dcgettext() (dans le module locale)

deallocation, object

debug (attribut imaplib.IMAP4)

(attribut shlex.shlex)

(attribut zipfile.ZipFile)

DEBUG (dans le module re)

debug() (dans le module doctest)

(dans le module logging)

(méthode logging.Logger)

(méthode pipes.Template)

(méthode unittest.TestCase)

(méthode unittest.TestSuite)

DEBUG_BYTECODE_SUFFIXES (dans le module importlib.machinery)

DEBUG_COLLECTABLE (dans le module gc)

DEBUG_LEAK (dans le module gc)

debug_print() (méthode distutils.ccompiler.CCompiler)

DEBUG_SAVEALL (dans le module gc)

debug_src() (dans le module doctest)

DEBUG_STATS (dans le module gc)

DEBUG_UNCOLLECTABLE (dans le module gc)

debugger, [1], [2]

configuration file

debugging

assertions

CGI

DebuggingServer (classe dans smtpd)

debuglevel (attribut http.client.HTTPResponse)

DebugRunner (classe dans doctest)

Decimal (classe dans decimal)

decimal (module)

decimal literal

decimal() (dans le module unicodedata)

DecimalException (classe dans decimal)

decode

Codecs

decode (attribut codecs.CodecInfo)

decode() (dans le module base64)

(dans le module codecs)

(dans le module quopri)

(dans le module uu)

(méthode bytearray)

(méthode bytes)

(méthode codecs.Codec)

(méthode codecs.IncrementalDecoder)

(méthode json.JSONDecoder)

(méthode xmlrpc.client.Binary)

(méthode xmlrpc.client.DateTime)

decode_header() (dans le module email.header)

(dans le module nntplib)

decode_params() (dans le module email.utils)

decode_rfc2231() (dans le module email.utils)

decode_source() (dans le module importlib.util)

decodebytes() (dans le module base64)

DecodedGenerator (classe dans email.generator)

decodestring() (dans le module base64)

(dans le module quopri)

decomposition() (dans le module unicodedata)

decompress() (dans le module bz2)

(dans le module gzip)

(dans le module lzma)

(dans le module zlib)

(méthode bz2.BZ2Decompressor)

(méthode lzma.LZMADecompressor)

(méthode zlib.Decompress)

decompressobj() (dans le module zlib)

DEDENT (dans le module token)

DEDENT token, [1]

dedent() (dans le module textwrap)

deepcopy() (dans le module copy)

def

état

def_prog_mode() (dans le module curses)

def_shell_mode() (dans le module curses)

default

parameter value

default (attribut inspect.Parameter)

(attribut optparse.Option)

(dans le module email.policy)

DEFAULT (dans le module unittest.mock)

default() (méthode cmd.Cmd)

(méthode json.JSONEncoder)

DEFAULT_BUFFER_SIZE (dans le module io)

default_bufsize (dans le module xml.dom.pulldom)

default_exception_handler() (méthode asyncio.AbstractEventLoop)

default_factory (attribut collections.defaultdict)

DEFAULT_FORMAT (dans le module tarfile)

DEFAULT_IGNORES (dans le module filecmp)

default_open() (méthode urllib.request.BaseHandler)

DEFAULT_PROTOCOL (dans le module pickle)

default_timer() (dans le module timeit)

DefaultContext (classe dans decimal)

DefaultCookiePolicy (classe dans http.cookiejar)

defaultdict (classe dans collections)

DefaultDict (classe dans typing)

DefaultHandler() (méthode xml.parsers.expat.xmlparser)

DefaultHandlerExpand() (méthode xml.parsers.expat.xmlparser)

defaults() (méthode configparser.ConfigParser)

DefaultSelector (classe dans selectors)

defaultTestLoader (dans le module unittest)

defaultTestResult() (méthode unittest.TestCase)

defects (attribut email.headerregistry.BaseHeader)

(attribut email.message.EmailMessage)

(attribut email.message.Message)

define_macro() (méthode distutils.ccompiler.CCompiler)

definition

class, [1]

function, [1]

defpath (dans le module os)

DefragResult (classe dans urllib.parse)

DefragResultBytes (classe dans urllib.parse)

degrees() (dans le module math)

(dans le module turtle)

del

état, [1], [2], [3]

del_param() (méthode email.message.EmailMessage)

(méthode email.message.Message)

delattr() (fonction de base)

delay() (dans le module turtle)

delay_output() (dans le module curses)

delayload (attribut http.cookiejar.FileCookieJar)

delch() (méthode curses.window)

dele() (méthode poplib.POP3)

delete() (méthode ftplib.FTP)

(méthode imaplib.IMAP4)

(méthode tkinter.ttk.Treeview)

DELETE_ATTR (opcode)

DELETE_DEREF (opcode)

DELETE_FAST (opcode)

DELETE_GLOBAL (opcode)

DELETE_NAME (opcode)

DELETE_SUBSCR (opcode)

deleteacl() (méthode imaplib.IMAP4)

deletefilehandler() (méthode tkinter.Widget.tk)

DeleteKey() (dans le module winreg)

DeleteKeyEx() (dans le module winreg)

deleteln() (méthode curses.window)

deleteMe() (méthode bdb.Breakpoint)

DeleteValue() (dans le module winreg)

deletion

attribute

target

target list

delimiter (attribut csv.Dialect)

delimiters

delitem() (dans le module operator)

deliver_challenge() (dans le module multiprocessing.connection)

delocalize() (dans le module locale)

demo_app() (dans le module wsgiref.simple_server)

denominator (attribut fractions.Fraction)

(attribut numbers.Rational)

DeprecationWarning

deque (classe dans collections)

Deque (classe dans typing)

dequeue() (méthode logging.handlers.QueueListener)

DER_cert_to_PEM_cert() (dans le module ssl)

derwin() (méthode curses.window)

DES

cipher

descripteur

description (attribut sqlite3.Cursor)

description() (méthode nntplib.NNTP)

descriptions() (méthode nntplib.NNTP)

dest (attribut optparse.Option)

destructor, [1]

detach() (méthode io.BufferedIOBase)

(méthode io.TextIOBase)

(méthode socket.socket)

(méthode tkinter.ttk.Treeview)

(méthode weakref.finalize)

Detach() (méthode winreg.PyHKEY)

detect_api_mismatch() (dans le module test.support)

detect_encoding() (dans le module tokenize)

detect_language() (méthode distutils.ccompiler.CCompiler)

deterministic profiling

device_encoding() (dans le module os)

devnull (dans le module os)

DEVNULL (dans le module subprocess)

devpoll() (dans le module select)

DevpollSelector (classe dans selectors)

décorateur

dgettext() (dans le module gettext)

(dans le module locale)

dialect (attribut csv.csvreader)

(attribut csv.csvwriter)

Dialect (classe dans csv)

Dialog (classe dans msilib)

dict (2to3 fixer)

Dict (classe dans typing)

dict (classe de base)

dict() (méthode multiprocessing.managers.SyncManager)

dictConfig() (dans le module logging.config)

dictionary

display

objet, [1], [2], [3], [4], [5], [6], [7]

type, operations on

dictionnaire

DictReader (classe dans csv)

DictWriter (classe dans csv)

diff_bytes() (dans le module difflib)

diff_files (attribut filecmp.dircmp)

Differ (classe dans difflib), [1]

difference() (méthode frozenset)

difference_update() (méthode frozenset)

difflib (module)

digest() (méthode hashlib.hash)

(méthode hashlib.shake)

(méthode hmac.HMAC)

digest_size (attribut hmac.HMAC)

digit() (dans le module unicodedata)

digits (dans le module string)

dir() (fonction de base)

(méthode ftplib.FTP)

dircmp (classe dans filecmp)

directory

changing

creating

deleting, [1]

site-packages

traversal, [1]

walking, [1]

Directory (classe dans msilib)

directory ...

compileall command line option

directory_created() (fonction de base)

DirEntry (classe dans os)

DirList (classe dans tkinter.tix)

dirname() (dans le module os.path)

DirSelectBox (classe dans tkinter.tix)

DirSelectDialog (classe dans tkinter.tix)

DirTree (classe dans tkinter.tix)

dis (module)

dis() (dans le module dis)

(dans le module pickletools)

(méthode dis.Bytecode)

disable (pdb command)

disable() (dans le module faulthandler)

(dans le module gc)

(dans le module logging)

(méthode bdb.Breakpoint)

(méthode profile.Profile)

disable_interspersed_args() (méthode optparse.OptionParser)

DisableReflectionKey() (dans le module winreg)

disassemble() (dans le module dis)

discard (attribut http.cookiejar.Cookie)

discard() (méthode frozenset)

(méthode mailbox.Mailbox)

(méthode mailbox.MH)

discard_buffers() (méthode asynchat.async_chat)

disco() (dans le module dis)

discover() (méthode unittest.TestLoader)

disk_usage() (dans le module shutil)

dispatch_call() (méthode bdb.Bdb)

dispatch_exception() (méthode bdb.Bdb)

dispatch_line() (méthode bdb.Bdb)

dispatch_return() (méthode bdb.Bdb)

dispatch_table (attribut pickle.Pickler)

dispatcher (classe dans asyncore)

dispatcher_with_send (classe dans asyncore)

display

dictionary

list

set

tuple

display (pdb command)

display_name (attribut email.headerregistry.Address)

(attribut email.headerregistry.Group)

displayhook() (dans le module sys)

dist() (dans le module platform)

distance() (dans le module turtle)

distb() (dans le module dis)

Distribution (classe dans distutils.core)

distribution simple

distutils (module)

distutils.archive_util (module)

distutils.bcppcompiler (module)

distutils.ccompiler (module)

distutils.cmd (module)

distutils.command (module)

distutils.command.bdist (module)

distutils.command.bdist_dumb (module)

distutils.command.bdist_msi (module)

distutils.command.bdist_packager (module)

distutils.command.bdist_rpm (module)

distutils.command.bdist_wininst (module)

distutils.command.build (module)

distutils.command.build_clib (module)

distutils.command.build_ext (module)

distutils.command.build_py (module)

distutils.command.build_scripts (module)

distutils.command.check (module)

distutils.command.clean (module)

distutils.command.config (module)

distutils.command.install (module)

distutils.command.install_data (module)

distutils.command.install_headers (module)

distutils.command.install_lib (module)

distutils.command.install_scripts (module)

distutils.command.register (module)

distutils.command.sdist (module)

distutils.core (module)

distutils.cygwinccompiler (module)

distutils.debug (module)

distutils.dep_util (module)

distutils.dir_util (module)

distutils.dist (module)

distutils.errors (module)

distutils.extension (module)

distutils.fancy_getopt (module)

distutils.file_util (module)

distutils.filelist (module)

distutils.log (module)

distutils.msvccompiler (module)

distutils.spawn (module)

distutils.sysconfig (module)

distutils.text_file (module)

distutils.unixccompiler (module)

distutils.util (module)

distutils.version (module)

DISTUTILS_DEBUG

divide() (méthode decimal.Context)

divide_int() (méthode decimal.Context)

division

division entière

DivisionByZero (classe dans decimal)

divmod

fonction de base, [1], [2]

divmod() (fonction de base)

(méthode decimal.Context)

DllCanUnloadNow() (dans le module ctypes)

DllGetClassObject() (dans le module ctypes)

dllhandle (dans le module sys)

dngettext() (dans le module gettext)

do_clear() (méthode bdb.Bdb)

do_command() (méthode curses.textpad.Textbox)

do_GET() (méthode http.server.SimpleHTTPRequestHandler)

do_handshake() (méthode ssl.SSLSocket)

do_HEAD() (méthode http.server.SimpleHTTPRequestHandler)

do_POST() (méthode http.server.CGIHTTPRequestHandler)

doc (attribut json.JSONDecodeError)

doc_header (attribut cmd.Cmd)

DocCGIXMLRPCRequestHandler (classe dans xmlrpc.server)

DocFileSuite() (dans le module doctest)

doCleanups() (méthode unittest.TestCase)

docmd() (méthode smtplib.SMTP)

docstring

(attribut doctest.DocTest)

(chaîne de documentation)

docstrings, [1]

DocTest (classe dans doctest)

doctest (module)

DocTestFailure

DocTestFinder (classe dans doctest)

DocTestParser (classe dans doctest)

DocTestRunner (classe dans doctest)

DocTestSuite() (dans le module doctest)

doctype() (méthode xml.etree.ElementTree.TreeBuilder)

(méthode xml.etree.ElementTree.XMLParser)

documentation

generation

online

documentation string

documentation strings, [1]

documentElement (attribut xml.dom.Document)

DocXMLRPCRequestHandler (classe dans xmlrpc.server)

DocXMLRPCServer (classe dans xmlrpc.server)

domain (attribut email.headerregistry.Address)

(attribut tracemalloc.DomainFilter)

(attribut tracemalloc.Filter)

domain_initial_dot (attribut http.cookiejar.Cookie)

domain_return_ok() (méthode http.cookiejar.CookiePolicy)

domain_specified (attribut http.cookiejar.Cookie)

DomainFilter (classe dans tracemalloc)

DomainLiberal (attribut http.cookiejar.DefaultCookiePolicy)

DomainRFC2965Match (attribut http.cookiejar.DefaultCookiePolicy)

DomainStrict (attribut http.cookiejar.DefaultCookiePolicy)

DomainStrictNoDots (attribut http.cookiejar.DefaultCookiePolicy)

DomainStrictNonDomain (attribut http.cookiejar.DefaultCookiePolicy)

DOMEventStream (classe dans xml.dom.pulldom)

DOMException

DomstringSizeErr

done() (dans le module turtle)

(méthode asyncio.Future)

(méthode concurrent.futures.Future)

(méthode xdrlib.Unpacker)

DONT_ACCEPT_BLANKLINE (dans le module doctest)

DONT_ACCEPT_TRUE_FOR_1 (dans le module doctest)

dont_write_bytecode (dans le module sys)

doRollover() (méthode logging.handlers.RotatingFileHandler)

(méthode logging.handlers.TimedRotatingFileHandler)

DOT (dans le module token)

dot() (dans le module turtle)

DOTALL (dans le module re)

doublequote (attribut csv.Dialect)

DOUBLESLASH (dans le module token)

DOUBLESLASHEQUAL (dans le module token)

DOUBLESTAR (dans le module token)

DOUBLESTAREQUAL (dans le module token)

doupdate() (dans le module curses)

down (pdb command)

down() (dans le module turtle)

drain() (méthode asyncio.StreamWriter)

drop_whitespace (attribut textwrap.TextWrapper)

dropwhile() (dans le module itertools)

dst() (méthode datetime.datetime)

(méthode datetime.time)

(méthode datetime.timezone)

(méthode datetime.tzinfo)

DTDHandler (classe dans xml.sax.handler)

duck-typing

DumbWriter (classe dans formatter)

dummy_threading (module)

dump() (dans le module ast)

(dans le module json)

(dans le module marshal)

(dans le module pickle)

(dans le module plistlib)

(dans le module xml.etree.ElementTree)

(méthode pickle.Pickler)

(méthode tracemalloc.Snapshot)

dump_stats() (méthode profile.Profile)

(méthode pstats.Stats)

dump_traceback() (dans le module faulthandler)

dump_traceback_later() (dans le module faulthandler)

dumps() (dans le module json)

(dans le module marshal)

(dans le module pickle)

(dans le module plistlib)

(dans le module xmlrpc.client)

dup() (dans le module os)

(méthode socket.socket)

dup2() (dans le module os)

DUP_TOP (opcode)

DUP_TOP_TWO (opcode)

DuplicateOptionError

DuplicateSectionError

dwFlags (attribut subprocess.STARTUPINFO)

DynamicClassAttribute() (dans le module types)

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Index – E

e

in numeric literal

e (dans le module cmath)

(dans le module math)

E2BIG (dans le module errno)

EACCES (dans le module errno)

EADDRINUSE (dans le module errno)

EADDRNOTAVAIL (dans le module errno)

EADV (dans le module errno)

EAFNOSUPPORT (dans le module errno)

EAFP

EAGAIN (dans le module errno)

EALREADY (dans le module errno)

east_asian_width() (dans le module unicodedata)

EBADE (dans le module errno)

EBADF (dans le module errno)

EBADFD (dans le module errno)

EBADMSG (dans le module errno)

EBADR (dans le module errno)

EBADRQC (dans le module errno)

EBADSLT (dans le module errno)

EBFONT (dans le module errno)

EBUSY (dans le module errno)

ECHILD (dans le module errno)

echo() (dans le module curses)

echochar() (méthode curses.window)

ECHRNG (dans le module errno)

ECOMM (dans le module errno)

ECONNABORTED (dans le module errno)

ECONNREFUSED (dans le module errno)

ECONNRESET (dans le module errno)

EDEADLK (dans le module errno)

EDEADLOCK (dans le module errno)

EDESTADDRREQ (dans le module errno)

edit() (méthode curses.textpad.Textbox)

EDOM (dans le module errno)

EDOTDOT (dans le module errno)

EDQUOT (dans le module errno)

EEXIST (dans le module errno)

EFAULT (dans le module errno)

EFBIG (dans le module errno)

effective() (dans le module bdb)

ehlo() (méthode smtplib.SMTP)

ehlo_or_helo_if_needed() (méthode smtplib.SMTP)

EHOSTDOWN (dans le module errno)

EHOSTUNREACH (dans le module errno)

EIDRM (dans le module errno)

EILSEQ (dans le module errno)

EINPROGRESS (dans le module errno)

EINTR (dans le module errno)

EINVAL (dans le module errno)

EIO (dans le module errno)

EISCONN (dans le module errno)

EISDIR (dans le module errno)

EISNAM (dans le module errno)

EL2HLT (dans le module errno)

EL2NSYNC (dans le module errno)

EL3HLT (dans le module errno)

EL3RST (dans le module errno)

Element (classe dans xml.etree.ElementTree)

element_create() (méthode tkinter.ttk.Style)

element_names() (méthode tkinter.ttk.Style)

element_options() (méthode tkinter.ttk.Style)

ElementDeclHandler() (méthode xml.parsers.expat.xmlparser)

elements() (méthode collections.Counter)

ElementTree (classe dans xml.etree.ElementTree)

ELIBACC (dans le module errno)

ELIBBAD (dans le module errno)

ELIBEXEC (dans le module errno)

ELIBMAX (dans le module errno)

ELIBSCN (dans le module errno)

elif

mot-clé

Ellinghouse, Lance

Ellipsis

objet

ELLIPSIS (dans le module doctest)

(dans le module token)

Ellipsis (variable de base)

ELNRNG (dans le module errno)

ELOOP (dans le module errno)

else

conditional expression

dangling

mot-clé, [1], [2], [3], [4], [5], [6], [7]

email (module)

email.charset (module)

email.contentmanager (module)

email.encoders (module)

email.errors (module)

email.generator (module)

email.header (module)

email.headerregistry (module)

email.iterators (module)

email.message (module)

email.mime (module)

email.parser (module)

email.policy (module)

email.utils (module)

EmailMessage (classe dans email.message)

EmailPolicy (classe dans email.policy)

EMFILE (dans le module errno)

emit() (méthode logging.FileHandler)

(méthode logging.Handler)

(méthode logging.handlers.BufferingHandler)

(méthode logging.handlers.DatagramHandler)

(méthode logging.handlers.HTTPHandler)

(méthode logging.handlers.NTEventLogHandler)

(méthode logging.handlers.QueueHandler)

(méthode logging.handlers.RotatingFileHandler)

(méthode logging.handlers.SMTPHandler)

(méthode logging.handlers.SocketHandler)

(méthode logging.handlers.SysLogHandler)

(méthode logging.handlers.TimedRotatingFileHandler)

(méthode logging.handlers.WatchedFileHandler)

(méthode logging.NullHandler)

(méthode logging.StreamHandler)

EMLINK (dans le module errno)

Empty

empty

list

tuple, [1]

empty (attribut inspect.Parameter)

(attribut inspect.Signature)

empty() (méthode asyncio.Queue)

(méthode multiprocessing.Queue)

(méthode multiprocessing.SimpleQueue)

(méthode queue.Queue)

(méthode sched.scheduler)

EMPTY_NAMESPACE (dans le module xml.dom)

emptyline() (méthode cmd.Cmd)

EMSGSIZE (dans le module errno)

EMULTIHOP (dans le module errno)

enable (pdb command)

enable() (dans le module cgitb)

(dans le module faulthandler)

(dans le module gc)

(méthode bdb.Breakpoint)

(méthode imaplib.IMAP4)

(méthode profile.Profile)

enable_callback_tracebacks() (dans le module sqlite3)

enable_interspersed_args() (méthode optparse.OptionParser)

enable_load_extension() (méthode sqlite3.Connection)

enable_traversal() (méthode tkinter.ttk.Notebook)

ENABLE_USER_SITE (dans le module site)

EnableReflectionKey() (dans le module winreg)

ENAMETOOLONG (dans le module errno)

ENAVAIL (dans le module errno)

enclose() (méthode curses.window)

encodage de texte

encode

Codecs

encode (attribut codecs.CodecInfo)

encode() (dans le module base64)

(dans le module codecs)

(dans le module quopri)

(dans le module uu)

(méthode codecs.Codec)

(méthode codecs.IncrementalEncoder)

(méthode email.header.Header)

(méthode json.JSONEncoder)

(méthode str)

(méthode xmlrpc.client.Binary)

(méthode xmlrpc.client.DateTime)

encode_7or8bit() (dans le module email.encoders)

encode_base64() (dans le module email.encoders)

encode_noop() (dans le module email.encoders)

encode_quopri() (dans le module email.encoders)

encode_rfc2231() (dans le module email.utils)

encodebytes() (dans le module base64)

EncodedFile() (dans le module codecs)

encodePriority() (méthode logging.handlers.SysLogHandler)

encodestring() (dans le module base64)

(dans le module quopri)

encoding

base64

quoted-printable

encoding (attribut curses.window)

(attribut io.TextIOBase)

(attribut UnicodeError)

ENCODING (dans le module tarfile)

(dans le module tokenize)

encoding declarations (source file)

encodings.idna (module)

encodings.mbcs (module)

encodings.utf_8_sig (module)

encodings_map (attribut mimetypes.MimeTypes)

(dans le module mimetypes)

end (attribut UnicodeError)

end() (méthode re.match)

(méthode xml.etree.ElementTree.TreeBuilder)

end_fill() (dans le module turtle)

END_FINALLY (opcode)

end_headers() (méthode http.server.BaseHTTPRequestHandler)

end_paragraph() (méthode formatter.formatter)

end_poly() (dans le module turtle)

EndCdataSectionHandler() (méthode xml.parsers.expat.xmlparser)

EndDoctypeDeclHandler() (méthode xml.parsers.expat.xmlparser)

endDocument() (méthode xml.sax.handler.ContentHandler)

endElement() (méthode xml.sax.handler.ContentHandler)

EndElementHandler() (méthode xml.parsers.expat.xmlparser)

endElementNS() (méthode xml.sax.handler.ContentHandler)

endheaders() (méthode http.client.HTTPConnection)

ENDMARKER (dans le module token)

EndNamespaceDeclHandler() (méthode xml.parsers.expat.xmlparser)

endpos (attribut re.match)

endPrefixMapping() (méthode xml.sax.handler.ContentHandler)

endswith() (méthode bytearray)

(méthode bytes)

(méthode str)

endwin() (dans le module curses)

ENETDOWN (dans le module errno)

ENETRESET (dans le module errno)

ENETUNREACH (dans le module errno)

ENFILE (dans le module errno)

ENOANO (dans le module errno)

ENOBUFS (dans le module errno)

ENOCSI (dans le module errno)

ENODATA (dans le module errno)

ENODEV (dans le module errno)

ENOENT (dans le module errno)

ENOEXEC (dans le module errno)

ENOLCK (dans le module errno)

ENOLINK (dans le module errno)

ENOMEM (dans le module errno)

ENOMSG (dans le module errno)

ENONET (dans le module errno)

ENOPKG (dans le module errno)

ENOPROTOOPT (dans le module errno)

ENOSPC (dans le module errno)

ENOSR (dans le module errno)

ENOSTR (dans le module errno)

ENOSYS (dans le module errno)

ENOTBLK (dans le module errno)

ENOTCONN (dans le module errno)

ENOTDIR (dans le module errno)

ENOTEMPTY (dans le module errno)

ENOTNAM (dans le module errno)

ENOTSOCK (dans le module errno)

ENOTTY (dans le module errno)

ENOTUNIQ (dans le module errno)

enqueue() (méthode logging.handlers.QueueHandler)

enqueue_sentinel() (méthode logging.handlers.QueueListener)

ensure_directories() (méthode venv.EnvBuilder)

ensure_future() (dans le module asyncio)

ensurepip (module)

enter() (méthode sched.scheduler)

enter_context() (méthode contextlib.ExitStack)

enterabs() (méthode sched.scheduler)

entities (attribut xml.dom.DocumentType)

EntityDeclHandler() (méthode xml.parsers.expat.xmlparser)

entitydefs (dans le module html.entities)

EntityResolver (classe dans xml.sax.handler)

entrée de chemin

Enum (classe dans enum)

enum (module)

enum_certificates() (dans le module ssl)

enum_crls() (dans le module ssl)

enumerate() (dans le module threading)

(fonction de base)

EnumKey() (dans le module winreg)

EnumValue() (dans le module winreg)

EnvBuilder (classe dans venv)

environ (dans le module os)

(dans le module posix)

environb (dans le module os)

environment

environment variables

deleting

setting

EnvironmentError

Environments

virtual

EnvironmentVarGuard (classe dans test.support)

environnement virtuel

ENXIO (dans le module errno)

eof (attribut bz2.BZ2Decompressor)

(attribut lzma.LZMADecompressor)

(attribut shlex.shlex)

(attribut ssl.MemoryBIO)

(attribut zlib.Decompress)

eof_received() (méthode asyncio.Protocol)

EOFError

(built-in exception)

EOPNOTSUPP (dans le module errno)

EOVERFLOW (dans le module errno)

EPERM (dans le module errno)

EPFNOSUPPORT (dans le module errno)

epilogue (attribut email.message.EmailMessage)

(attribut email.message.Message)

EPIPE (dans le module errno)

epoch

epoll() (dans le module select)

EpollSelector (classe dans selectors)

EPROTO (dans le module errno)

EPROTONOSUPPORT (dans le module errno)

EPROTOTYPE (dans le module errno)

eq() (dans le module operator)

EQEQUAL (dans le module token)

EQUAL (dans le module token)

ERA (dans le module locale)

ERA_D_FMT (dans le module locale)

ERA_D_T_FMT (dans le module locale)

ERA_T_FMT (dans le module locale)

ERANGE (dans le module errno)

erase() (méthode curses.window)

erasechar() (dans le module curses)

EREMCHG (dans le module errno)

EREMOTE (dans le module errno)

EREMOTEIO (dans le module errno)

ERESTART (dans le module errno)

erf() (dans le module math)

erfc() (dans le module math)

EROFS (dans le module errno)

ERR (dans le module curses)

errcheck (attribut ctypes._FuncPtr)

errcode (attribut xmlrpc.client.ProtocolError)

errmsg (attribut xmlrpc.client.ProtocolError)

errno

module

errno (attribut OSError)

(module)

Error, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12]

error, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17]

error handling

error() (dans le module logging)

(méthode argparse.ArgumentParser)

(méthode logging.Logger)

(méthode urllib.request.OpenerDirector)

(méthode xml.sax.handler.ErrorHandler)

error_body (attribut wsgiref.handlers.BaseHandler)

error_content_type (attribut http.server.BaseHTTPRequestHandler)

error_headers (attribut wsgiref.handlers.BaseHandler)

error_leader() (méthode shlex.shlex)

error_message_format (attribut http.server.BaseHTTPRequestHandler)

error_output() (méthode wsgiref.handlers.BaseHandler)

error_perm

error_proto, [1]

error_received() (méthode asyncio.DatagramProtocol)

error_reply

error_status (attribut wsgiref.handlers.BaseHandler)

error_temp

ErrorByteIndex (attribut xml.parsers.expat.xmlparser)

ErrorCode (attribut xml.parsers.expat.xmlparser)

errorcode (dans le module errno)

ErrorColumnNumber (attribut xml.parsers.expat.xmlparser)

ErrorHandler (classe dans xml.sax.handler)

ErrorLineNumber (attribut xml.parsers.expat.xmlparser)

Errors

logging

errors

(attribut io.TextIOBase)

(attribut unittest.TestLoader)

(attribut unittest.TestResult)

ErrorString() (dans le module xml.parsers.expat)

ERRORTOKEN (dans le module token)

escape (attribut shlex.shlex)

escape sequence

escape() (dans le module cgi)

(dans le module glob)

(dans le module html)

(dans le module re)

(dans le module xml.sax.saxutils)

escapechar (attribut csv.Dialect)

escapedquotes (attribut shlex.shlex)

ESHUTDOWN (dans le module errno)

ESOCKTNOSUPPORT (dans le module errno)

espace de nommage

ESPIPE (dans le module errno)

ESRCH (dans le module errno)

ESRMNT (dans le module errno)

ESTALE (dans le module errno)

ESTRPIPE (dans le module errno)

ETIME (dans le module errno)

ETIMEDOUT (dans le module errno)

Etiny() (méthode decimal.Context)

ETOOMANYREFS (dans le module errno)

Etop() (méthode decimal.Context)

ETXTBSY (dans le module errno)

EUCLEAN (dans le module errno)

EUNATCH (dans le module errno)

EUSERS (dans le module errno)

eval

fonction de base, [1], [2], [3], [4], [5]

eval() (fonction de base)

evaluation

order

Event (classe dans asyncio)

(classe dans multiprocessing)

(classe dans threading)

event scheduling

event() (méthode msilib.Control)

Event() (méthode multiprocessing.managers.SyncManager)

events (attribut selectors.SelectorKey)

(widgets)

EWOULDBLOCK (dans le module errno)

EX_CANTCREAT (dans le module os)

EX_CONFIG (dans le module os)

EX_DATAERR (dans le module os)

EX_IOERR (dans le module os)

EX_NOHOST (dans le module os)

EX_NOINPUT (dans le module os)

EX_NOPERM (dans le module os)

EX_NOTFOUND (dans le module os)

EX_NOUSER (dans le module os)

EX_OK (dans le module os)

EX_OSERR (dans le module os)

EX_OSFILE (dans le module os)

EX_PROTOCOL (dans le module os)

EX_SOFTWARE (dans le module os)

EX_TEMPFAIL (dans le module os)

EX_UNAVAILABLE (dans le module os)

EX_USAGE (dans le module os)

example (attribut doctest.DocTestFailure)

(attribut doctest.UnexpectedException)

Example (classe dans doctest)

examples (attribut doctest.DocTest)

exc_info (attribut doctest.UnexpectedException)

(in module sys)

exc_info() (dans le module sys)

(in module sys)

exc_msg (attribut doctest.Example)

exc_type (attribut traceback.TracebackException)

excel (classe dans csv)

excel_tab (classe dans csv)

except

état

mot-clé

except (2to3 fixer)

excepthook() (dans le module sys)

(in module sys)

Exception

exception, [1]

AssertionError

AttributeError

chaining

GeneratorExit, [1]

handler

ImportError

NameError

raising

StopAsyncIteration

StopIteration, [1]

TypeError

ValueError

ZeroDivisionError

EXCEPTION (dans le module tkinter)

exception handler

exception() (dans le module logging)

(méthode asyncio.Future)

(méthode asyncio.StreamReader)

(méthode concurrent.futures.Future)

(méthode logging.Logger)

exceptions

in CGI scripts

exclusive

or

EXDEV (dans le module errno)

exec

fonction de base, [1], [2], [3]

exec (2to3 fixer)

exec() (fonction de base)

exec_module (fonction C)

exec_module() (méthode importlib.abc.InspectLoader)

(méthode importlib.abc.Loader)

(méthode importlib.abc.SourceLoader)

(méthode importlib.machinery.ExtensionFileLoader)

exec_prefix, [1], [2]

EXEC_PREFIX (dans le module distutils.sysconfig)

exec_prefix (dans le module sys)

execfile (2to3 fixer)

execl() (dans le module os)

execle() (dans le module os)

execlp() (dans le module os)

execlpe() (dans le module os)

executable (dans le module sys)

(in module sys)

Executable Zip Files

executable_filename() (méthode distutils.ccompiler.CCompiler)

execute() (dans le module distutils.util)

(méthode distutils.ccompiler.CCompiler)

Execute() (méthode msilib.View)

execute() (méthode sqlite3.Connection)

(méthode sqlite3.Cursor)

executemany() (méthode sqlite3.Connection)

(méthode sqlite3.Cursor)

executescript() (méthode sqlite3.Connection)

(méthode sqlite3.Cursor)

execution

frame, [1]

restricted

stack

execution model

ExecutionLoader (classe dans importlib.abc)

Executor (classe dans concurrent.futures)

execv() (dans le module os)

execve() (dans le module os)

execvp() (dans le module os)

execvpe() (dans le module os)

ExFileSelectBox (classe dans tkinter.tix)

EXFULL (dans le module errno)

exists() (dans le module os.path)

(méthode pathlib.Path)

(méthode tkinter.ttk.Treeview)

exit (variable de base)

exit()

(dans le module _thread)

(dans le module sys)

(méthode argparse.ArgumentParser)

exitcode (attribut multiprocessing.Process)

exitfunc (2to3 fixer)

exitonclick() (dans le module turtle)

ExitStack (classe dans contextlib)

exp() (dans le module cmath)

(dans le module math)

(méthode decimal.Context)

(méthode decimal.Decimal)

expand() (méthode re.match)

expand_tabs (attribut textwrap.TextWrapper)

ExpandEnvironmentStrings() (dans le module winreg)

expandNode() (méthode xml.dom.pulldom.DOMEventStream)

expandtabs() (méthode bytearray)

(méthode bytes)

(méthode str)

expanduser() (dans le module os.path)

(méthode pathlib.Path)

expandvars() (dans le module os.path)

Expat

ExpatError

expect() (méthode telnetlib.Telnet)

expected (attribut asyncio.IncompleteReadError)

expectedFailure() (dans le module unittest)

expectedFailures (attribut unittest.TestResult)

expires (attribut http.cookiejar.Cookie)

exploded (attribut ipaddress.IPv4Address)

(attribut ipaddress.IPv4Network)

(attribut ipaddress.IPv6Address)

(attribut ipaddress.IPv6Network)

expm1() (dans le module math)

expovariate() (dans le module random)

expr() (dans le module parser)

expression, [1]

Conditional

conditional

generator

lambda, [1]

list, [1], [2]

statement

yield

expression génératrice

expunge() (méthode imaplib.IMAP4)

extend() (méthode array.array)

(méthode collections.deque)

(méthode xml.etree.ElementTree.Element)

(sequence method)

extend_path() (dans le module pkgutil)

EXTENDED_ARG (opcode)

ExtendedContext (classe dans decimal)

ExtendedInterpolation (classe dans configparser)

extendleft() (méthode collections.deque)

extension

module

Extension (classe dans distutils.core)

EXTENSION_SUFFIXES (dans le module importlib.machinery)

ExtensionFileLoader (classe dans importlib.machinery)

extensions_map (attribut http.server.SimpleHTTPRequestHandler)

External Data Representation, [1]

external_attr (attribut zipfile.ZipInfo)

ExternalClashError

ExternalEntityParserCreate() (méthode xml.parsers.expat.xmlparser)

ExternalEntityRefHandler() (méthode xml.parsers.expat.xmlparser)

extra (attribut zipfile.ZipInfo)

extract() (méthode de la classe traceback.StackSummary)

(méthode tarfile.TarFile)

(méthode zipfile.ZipFile)

extract_cookies() (méthode http.cookiejar.CookieJar)

extract_stack() (dans le module traceback)

extract_tb() (dans le module traceback)

extract_version (attribut zipfile.ZipInfo)

extractall() (méthode tarfile.TarFile)

(méthode zipfile.ZipFile)

ExtractError

extractfile() (méthode tarfile.TarFile)

extsep (dans le module os)

état

assert, [1]

async def

async for

async with

break, [1], [2], [3], [4]

class

continue, [1], [2], [3], [4]

def

del, [1], [2], [3]

except

for, [1], [2], [3]

global, [1]

if, [1]

import, [1], [2], [3], [4]

nonlocal

pass

raise, [1]

return, [1], [2]

try, [1], [2]

while, [1], [2], [3]

with, [1]

yield

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Index – F

f"

formatted string literal

f'

formatted string literal

f-string, [1]

f_back (frame attribute)

f_builtins (frame attribute)

f_code (frame attribute)

f_contiguous (attribut memoryview)

f_globals (frame attribute)

f_lasti (frame attribute)

f_lineno (frame attribute)

f_locals (frame attribute)

F_LOCK (dans le module os)

F_OK (dans le module os)

F_TEST (dans le module os)

F_TLOCK (dans le module os)

f_trace (frame attribute)

F_ULOCK (dans le module os)

fabs() (dans le module math)

factorial() (dans le module math)

factory() (méthode de la classe importlib.util.LazyLoader)

fail() (méthode unittest.TestCase)

FAIL_FAST (dans le module doctest)

failfast (attribut unittest.TestResult)

failureException (attribut unittest.TestCase)

failures (attribut unittest.TestResult)

FakePath (classe dans test.support)

False, [1], [2]

false

False (Built-in object)

(variable de base)

family (attribut socket.socket)

fancy_getopt() (dans le module distutils.fancy_getopt)

FancyGetopt (classe dans distutils.fancy_getopt)

FancyURLopener (classe dans urllib.request)

fast (attribut pickle.Pickler)

fatalError() (méthode xml.sax.handler.ErrorHandler)

Fault (classe dans xmlrpc.client)

faultCode (attribut xmlrpc.client.Fault)

faulthandler (module)

faultString (attribut xmlrpc.client.Fault)

fchdir() (dans le module os)

fchmod() (dans le module os)

fchown() (dans le module os)

FCICreate() (dans le module msilib)

fcntl (module)

fcntl() (dans le module fcntl)

fd (attribut selectors.SelectorKey)

fd() (dans le module turtle)

fdatasync() (dans le module os)

fdopen() (dans le module os)

Feature (classe dans msilib)

feature_external_ges (dans le module xml.sax.handler)

feature_external_pes (dans le module xml.sax.handler)

feature_namespace_prefixes (dans le module xml.sax.handler)

feature_namespaces (dans le module xml.sax.handler)

feature_string_interning (dans le module xml.sax.handler)

feature_validation (dans le module xml.sax.handler)

feed() (méthode email.parser.BytesFeedParser)

(méthode html.parser.HTMLParser)

(méthode xml.etree.ElementTree.XMLParser)

(méthode xml.etree.ElementTree.XMLPullParser)

(méthode xml.sax.xmlreader.IncrementalParser)

feed_data() (méthode asyncio.StreamReader)

feed_eof() (méthode asyncio.StreamReader)

FeedParser (classe dans email.parser)

fetch() (méthode imaplib.IMAP4)

Fetch() (méthode msilib.View)

fetchall() (méthode sqlite3.Cursor)

fetchmany() (méthode sqlite3.Cursor)

fetchone() (méthode sqlite3.Cursor)

fflags (attribut select.kevent)

fichier binaire

fichier texte

field_size_limit() (dans le module csv)

fieldnames (attribut csv.csvreader)

fields (attribut uuid.UUID)

file

.ini

.pdbrc

byte-code, [1]

configuration

copying

debugger configuration

large files

mime.types

modes

objet, [1]

path configuration

plist

temporary

file (attribut pyclbr.Class)

(attribut pyclbr.Function)

file ...

compileall command line option

file control

UNIX

file name

temporary

file object

io module

open() built-in function

FILE_ATTRIBUTE_ARCHIVE (dans le module stat)

FILE_ATTRIBUTE_COMPRESSED (dans le module stat)

FILE_ATTRIBUTE_DEVICE (dans le module stat)

FILE_ATTRIBUTE_DIRECTORY (dans le module stat)

FILE_ATTRIBUTE_ENCRYPTED (dans le module stat)

FILE_ATTRIBUTE_HIDDEN (dans le module stat)

FILE_ATTRIBUTE_INTEGRITY_STREAM (dans le module stat)

FILE_ATTRIBUTE_NO_SCRUB_DATA (dans le module stat)

FILE_ATTRIBUTE_NORMAL (dans le module stat)

FILE_ATTRIBUTE_NOT_CONTENT_INDEXED (dans le module stat)

FILE_ATTRIBUTE_OFFLINE (dans le module stat)

FILE_ATTRIBUTE_READONLY (dans le module stat)

FILE_ATTRIBUTE_REPARSE_POINT (dans le module stat)

FILE_ATTRIBUTE_SPARSE_FILE (dans le module stat)

FILE_ATTRIBUTE_SYSTEM (dans le module stat)

FILE_ATTRIBUTE_TEMPORARY (dans le module stat)

FILE_ATTRIBUTE_VIRTUAL (dans le module stat)

file_created() (fonction de base)

file_dispatcher (classe dans asyncore)

file_open() (méthode urllib.request.FileHandler)

file_size (attribut zipfile.ZipInfo)

file_wrapper (classe dans asyncore)

filecmp (module)

fileConfig() (dans le module logging.config)

FileCookieJar (classe dans http.cookiejar)

FileEntry (classe dans tkinter.tix)

FileExistsError

FileFinder (classe dans importlib.machinery)

FileHandler (classe dans logging)

(classe dans urllib.request)

FileInput (classe dans fileinput)

fileinput (module)

FileIO (classe dans io)

filelineno() (dans le module fileinput)

FileLoader (classe dans importlib.abc)

filemode() (dans le module stat)

filename (attribut doctest.DocTest)

(attribut http.cookiejar.FileCookieJar)

(attribut OSError)

(attribut traceback.TracebackException)

(attribut tracemalloc.Frame)

(attribut zipfile.ZipFile)

(attribut zipfile.ZipInfo)

filename() (dans le module fileinput)

filename2 (attribut OSError)

filename_only (dans le module tabnanny)

filename_pattern (attribut tracemalloc.Filter)

filenames

pathname expansion

wildcard expansion

fileno() (dans le module fileinput)

(méthode http.client.HTTPResponse)

(méthode io.IOBase)

(méthode multiprocessing.connection.Connection)

(méthode ossaudiodev.oss_audio_device)

(méthode ossaudiodev.oss_mixer_device)

(méthode select.devpoll)

(méthode select.epoll)

(méthode select.kqueue)

(méthode selectors.DevpollSelector)

(méthode selectors.EpollSelector)

(méthode selectors.KqueueSelector)

(méthode socket.socket)

(méthode socketserver.BaseServer)

(méthode telnetlib.Telnet)

FileNotFoundError

fileobj (attribut selectors.SelectorKey)

FileSelectBox (classe dans tkinter.tix)

FileType (classe dans argparse)

FileWrapper (classe dans wsgiref.util)

fill() (dans le module textwrap)

(méthode textwrap.TextWrapper)

fillcolor() (dans le module turtle)

filling() (dans le module turtle)

filter (2to3 fixer)

(attribut select.kevent)

Filter (classe dans logging)

(classe dans tracemalloc)

filter() (dans le module curses)

(dans le module fnmatch)

(fonction de base)

(méthode logging.Filter)

(méthode logging.Handler)

(méthode logging.Logger)

FILTER_DIR (dans le module unittest.mock)

filter_traces() (méthode tracemalloc.Snapshot)

filterfalse() (dans le module itertools)

filterwarnings() (dans le module warnings)

finalization, of objects

finalize (classe dans weakref)

finalize_options() (méthode distutils.cmd.Command)

finalizer

finally

mot-clé, [1], [2], [3], [4]

find() (dans le module gettext)

(méthode bytearray)

(méthode bytes)

(méthode doctest.DocTestFinder)

(méthode mmap.mmap)

(méthode str)

(méthode xml.etree.ElementTree.Element)

(méthode xml.etree.ElementTree.ElementTree)

find_class() (méthode pickle.Unpickler)

(pickle protocol)

find_library() (dans le module ctypes.util)

find_library_file() (méthode distutils.ccompiler.CCompiler)

find_loader() (dans le module importlib)

(dans le module pkgutil)

(méthode importlib.abc.PathEntryFinder)

(méthode importlib.machinery.FileFinder)

find_longest_match() (méthode difflib.SequenceMatcher)

find_module() (dans le module imp)

(méthode de la classe importlib.machinery.PathFinder)

(méthode imp.NullImporter)

(méthode importlib.abc.Finder)

(méthode importlib.abc.MetaPathFinder)

(méthode importlib.abc.PathEntryFinder)

(méthode zipimport.zipimporter)

find_msvcrt() (dans le module ctypes.util)

find_spec

finder

find_spec() (dans le module importlib.util)

(méthode de la classe importlib.machinery.PathFinder)

(méthode importlib.abc.MetaPathFinder)

(méthode importlib.abc.PathEntryFinder)

(méthode importlib.machinery.FileFinder)

find_unused_port() (dans le module test.support)

find_user_password() (méthode urllib.request.HTTPPasswordMgr), [1]

findall() (dans le module re)

(méthode re.regex)

(méthode xml.etree.ElementTree.Element)

(méthode xml.etree.ElementTree.ElementTree)

findCaller() (méthode logging.Logger)

finder

find_spec

Finder (classe dans importlib.abc)

findfactor() (dans le module audioop)

findfile() (dans le module test.support)

findfit() (dans le module audioop)

finditer() (dans le module re)

(méthode re.regex)

findlabels() (dans le module dis)

findlinestarts() (dans le module dis)

findmatch() (dans le module mailcap)

findmax() (dans le module audioop)

findtext() (méthode xml.etree.ElementTree.Element)

(méthode xml.etree.ElementTree.ElementTree)

finish() (méthode socketserver.BaseRequestHandler)

finish_request() (méthode socketserver.BaseServer)

firstChild (attribut xml.dom.Node)

firstkey() (méthode dbm.gnu.gdbm)

firstweekday() (dans le module calendar)

fix_missing_locations() (dans le module ast)

fix_sentence_endings (attribut textwrap.TextWrapper)

Flag (classe dans enum)

flag_bits (attribut zipfile.ZipInfo)

flags (attribut re.regex)

(attribut select.kevent)

(dans le module sys)

flash() (dans le module curses)

flatten() (méthode email.generator.BytesGenerator)

(méthode email.generator.Generator)

flattening

objects

float

fonction de base, [1], [2]

float (classe de base)

float_info (dans le module sys)

float_repr_style (dans le module sys)

floating point

literals

number

objet, [1], [2]

floating point literal

FloatingPointError, [1]

FloatOperation (classe dans decimal)

flock() (dans le module fcntl)

floor() (dans le module math)

(in module math)

floordiv() (dans le module operator)

flush() (méthode bz2.BZ2Compressor)

(méthode formatter.writer)

(méthode io.BufferedWriter)

(méthode io.IOBase)

(méthode logging.Handler)

(méthode logging.handlers.BufferingHandler)

(méthode logging.handlers.MemoryHandler)

(méthode logging.StreamHandler)

(méthode lzma.LZMACompressor)

(méthode mailbox.Mailbox)

(méthode mailbox.Maildir)

(méthode mailbox.MH)

(méthode mmap.mmap)

(méthode zlib.Compress)

(méthode zlib.Decompress)

flush_headers() (méthode http.server.BaseHTTPRequestHandler)

flush_softspace() (méthode formatter.formatter)

flushinp() (dans le module curses)

FlushKey() (dans le module winreg)

fma() (méthode decimal.Context)

(méthode decimal.Decimal)

fmod() (dans le module math)

FMT_BINARY (dans le module plistlib)

FMT_XML (dans le module plistlib)

fnmatch (module)

fnmatch() (dans le module fnmatch)

fnmatchcase() (dans le module fnmatch)

focus() (méthode tkinter.ttk.Treeview)

fold (attribut datetime.datetime)

(attribut datetime.time)

fold() (méthode email.headerregistry.BaseHeader)

(méthode email.policy.Compat32)

(méthode email.policy.EmailPolicy)

(méthode email.policy.Policy)

fold_binary() (méthode email.policy.Compat32)

(méthode email.policy.EmailPolicy)

(méthode email.policy.Policy)

fonction

fonction clé

fonction coroutine

fonction de base

__import__

abs, [1]

ascii

bytes, [1]

chr

classmethod

compile, [1], [2], [3], [4]

complex, [1]

divmod, [1], [2]

eval, [1], [2], [3], [4], [5]

exec, [1], [2], [3]

float, [1], [2]

hash, [1], [2], [3]

help

id

int, [1], [2]

len, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11]

max

min

open, [1]

ord

pow, [1], [2], [3], [4], [5]

print

range

repr, [1], [2], [3]

round

slice, [1]

staticmethod

tuple, [1]

type, [1], [2], [3]

fonction générique

for

état, [1], [2], [3]

in comprehensions

FOR_ITER (opcode)

forget() (dans le module test.support)

(méthode tkinter.ttk.Notebook)

fork() (dans le module os)

(dans le module pty)

ForkingMixIn (classe dans socketserver)

ForkingTCPServer (classe dans socketserver)

ForkingUDPServer (classe dans socketserver)

forkpty() (dans le module os)

form

lambda

Form (classe dans tkinter.tix)

format (attribut memoryview)

(attribut struct.Struct)

format() (built-in function)

__str__() (object method)

format() (dans le module locale)

(fonction de base)

(méthode logging.Formatter)

(méthode logging.Handler)

(méthode pprint.PrettyPrinter)

(méthode str)

(méthode string.Formatter)

(méthode traceback.StackSummary)

(méthode traceback.TracebackException)

(méthode tracemalloc.Traceback)

format_datetime() (dans le module email.utils)

format_exc() (dans le module traceback)

format_exception() (dans le module traceback)

format_exception_only() (dans le module traceback)

(méthode traceback.TracebackException)

format_field() (méthode string.Formatter)

format_help() (méthode argparse.ArgumentParser)

format_list() (dans le module traceback)

format_map() (méthode str)

format_stack() (dans le module traceback)

format_stack_entry() (méthode bdb.Bdb)

format_string() (dans le module locale)

format_tb() (dans le module traceback)

format_usage() (méthode argparse.ArgumentParser)

FORMAT_VALUE (opcode)

formataddr() (dans le module email.utils)

formatargspec() (dans le module inspect)

formatargvalues() (dans le module inspect)

formatdate() (dans le module email.utils)

FormatError

FormatError() (dans le module ctypes)

formatException() (méthode logging.Formatter)

formatmonth() (méthode calendar.HTMLCalendar)

(méthode calendar.TextCalendar)

formatStack() (méthode logging.Formatter)

formatted string literal

Formatter (classe dans logging)

(classe dans string)

formatter (module)

formatTime() (méthode logging.Formatter)

formatting

bytearray (%)

bytes (%)

formatting, string (%)

formatwarning() (dans le module warnings)

formatyear() (méthode calendar.HTMLCalendar)

(méthode calendar.TextCalendar)

formatyearpage() (méthode calendar.HTMLCalendar)

Fortran contiguous, [1]

forward() (dans le module turtle)

found_terminator() (méthode asynchat.async_chat)

fpathconf() (dans le module os)

fpectl (module)

fqdn (attribut smtpd.SMTPChannel)

Fraction (classe dans fractions)

fractions (module)

frame

execution, [1]

objet

frame (attribut tkinter.scrolledtext.ScrolledText)

Frame (classe dans tracemalloc)

FrameSummary (classe dans traceback)

FrameType (dans le module types)

free

variable

free()

freeze utility

freeze_support() (dans le module multiprocessing)

frexp() (dans le module math)

from

import statement, [1]

mot-clé, [1]

yield from expression

from_address() (méthode ctypes._CData)

from_buffer() (méthode ctypes._CData)

from_buffer_copy() (méthode ctypes._CData)

from_bytes() (méthode de la classe int)

from_callable() (méthode de la classe inspect.Signature)

from_decimal() (méthode fractions.Fraction)

from_exception() (méthode de la classe traceback.TracebackException)

from_file() (méthode de la classe zipfile.ZipInfo)

from_float() (méthode decimal.Decimal)

(méthode fractions.Fraction)

from_iterable() (méthode de la classe itertools.chain)

from_list() (méthode de la classe traceback.StackSummary)

from_param() (méthode ctypes._CData)

from_traceback() (méthode de la classe dis.Bytecode)

frombuf() (méthode de la classe tarfile.TarInfo)

frombytes() (méthode array.array)

fromfd() (dans le module socket)

(méthode select.epoll)

(méthode select.kqueue)

fromfile() (méthode array.array)

fromhex() (méthode de la classe bytearray)

(méthode de la classe bytes)

(méthode de la classe float)

fromkeys() (méthode collections.Counter)

(méthode de la classe dict)

fromlist() (méthode array.array)

fromordinal() (méthode de la classe datetime.date)

(méthode de la classe datetime.datetime)

fromshare() (dans le module socket)

fromstring() (dans le module xml.etree.ElementTree)

(méthode array.array)

fromstringlist() (dans le module xml.etree.ElementTree)

fromtarfile() (méthode de la classe tarfile.TarInfo)

fromtimestamp() (méthode de la classe datetime.date)

(méthode de la classe datetime.datetime)

fromunicode() (méthode array.array)

fromutc() (méthode datetime.timezone)

(méthode datetime.tzinfo)

FrozenImporter (classe dans importlib.machinery)

frozenset

objet, [1]

FrozenSet (classe dans typing)

frozenset (classe de base)

fsdecode() (dans le module os)

fsencode() (dans le module os)

fspath() (dans le module os)

fstat() (dans le module os)

fstatvfs() (dans le module os)

fsum() (dans le module math)

fsync() (dans le module os)

FTP

ftplib (standard module)

protocol, [1]

FTP (classe dans ftplib)

ftp_open() (méthode urllib.request.FTPHandler)

FTP_TLS (classe dans ftplib)

FTPHandler (classe dans urllib.request)

ftplib (module)

ftruncate() (dans le module os)

Full

full() (méthode asyncio.Queue)

(méthode multiprocessing.Queue)

(méthode queue.Queue)

full_url (attribut urllib.request.Request)

fullmatch() (dans le module re)

(méthode re.regex)

func (attribut functools.partial)

funcattrs (2to3 fixer)

function

annotations, [1]

anonymous

argument

call, [1], [2]

call, user-defined

definition, [1]

generator, [1]

name, [1]

objet, [1], [2], [3], [4], [5]

user-defined

Function (classe dans symtable)

function__entry (fonction C)

function__return (fonction C)

FunctionTestCase (classe dans unittest)

FunctionType (dans le module types)

functools (module)

funny_files (attribut filecmp.dircmp)

future

statement

future (2to3 fixer)

Future (classe dans asyncio)

(classe dans concurrent.futures)

FutureWarning

fwalk() (dans le module os)

Navigation

index

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3.6.11 Documentation »

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Index – G

G.722

gaierror

gamma() (dans le module math)

gammavariate() (dans le module random)

garbage (dans le module gc)

garbage collection

gather() (dans le module asyncio)

(méthode curses.textpad.Textbox)

gauss() (dans le module random)

gc (module)

gc__done (fonction C)

gc__start (fonction C)

gcd() (dans le module fractions)

(dans le module math)

ge() (dans le module operator)

gen_lib_options() (dans le module distutils.ccompiler)

gen_preprocess_options() (dans le module distutils.ccompiler)

gen_uuid() (dans le module msilib)

generate_help() (méthode distutils.fancy_getopt.FancyGetopt)

generator

expression

function, [1], [2]

iterator, [1]

objet, [1], [2]

Generator (classe dans collections.abc)

(classe dans email.generator)

(classe dans typing)

generator expression

GeneratorExit

exception, [1]

GeneratorType (dans le module types)

generic

special attribute

Generic (classe dans typing)

generic_visit() (méthode ast.NodeVisitor)

genops() (dans le module pickletools)

gestionnaire de contexte

gestionnaire de contexte asynchrone

get() (dans le module webbrowser)

(méthode asyncio.Queue)

(méthode configparser.ConfigParser)

(méthode dict)

(méthode email.message.EmailMessage)

(méthode email.message.Message)

(méthode mailbox.Mailbox)

(méthode multiprocessing.pool.AsyncResult)

(méthode multiprocessing.Queue)

(méthode multiprocessing.SimpleQueue)

(méthode ossaudiodev.oss_mixer_device)

(méthode queue.Queue)

(méthode tkinter.ttk.Combobox)

(méthode types.MappingProxyType)

(méthode xml.etree.ElementTree.Element)

GET_AITER (opcode)

get_all() (méthode email.message.EmailMessage)

(méthode email.message.Message)

(méthode wsgiref.headers.Headers)

get_all_breaks() (méthode bdb.Bdb)

get_all_start_methods() (dans le module multiprocessing)

GET_ANEXT (opcode)

get_app() (méthode wsgiref.simple_server.WSGIServer)

get_archive_formats() (dans le module shutil)

get_asyncgen_hooks() (dans le module sys)

GET_AWAITABLE (opcode)

get_begidx() (dans le module readline)

get_blocking() (dans le module os)

get_body() (méthode email.message.EmailMessage)

get_body_encoding() (méthode email.charset.Charset)

get_boundary() (méthode email.message.EmailMessage)

(méthode email.message.Message)

get_bpbynumber() (méthode bdb.Bdb)

get_break() (méthode bdb.Bdb)

get_breaks() (méthode bdb.Bdb)

get_buffer() (méthode xdrlib.Packer)

(méthode xdrlib.Unpacker)

get_bytes() (méthode mailbox.Mailbox)

get_ca_certs() (méthode ssl.SSLContext)

get_cache_token() (dans le module abc)

get_channel_binding() (méthode ssl.SSLSocket)

get_charset() (méthode email.message.Message)

get_charsets() (méthode email.message.EmailMessage)

(méthode email.message.Message)

get_children() (méthode symtable.SymbolTable)

(méthode tkinter.ttk.Treeview)

get_ciphers() (méthode ssl.SSLContext)

get_clock_info() (dans le module time)

get_close_matches() (dans le module difflib)

get_code() (méthode importlib.abc.InspectLoader)

(méthode importlib.abc.SourceLoader)

(méthode importlib.machinery.ExtensionFileLoader)

(méthode importlib.machinery.SourcelessFileLoader)

(méthode zipimport.zipimporter)

get_completer() (dans le module readline)

get_completer_delims() (dans le module readline)

get_completion_type() (dans le module readline)

get_config_h_filename() (dans le module distutils.sysconfig)

(dans le module sysconfig)

get_config_var() (dans le module distutils.sysconfig)

(dans le module sysconfig)

get_config_vars() (dans le module distutils.sysconfig)

(dans le module sysconfig)

get_content() (dans le module email.contentmanager)

(méthode email.contentmanager.ContentManager)

(méthode email.message.EmailMessage)

get_content_charset() (méthode email.message.EmailMessage)

(méthode email.message.Message)

get_content_disposition() (méthode email.message.EmailMessage)

(méthode email.message.Message)

get_content_maintype() (méthode email.message.EmailMessage)

(méthode email.message.Message)

get_content_subtype() (méthode email.message.EmailMessage)

(méthode email.message.Message)

get_content_type() (méthode email.message.EmailMessage)

(méthode email.message.Message)

get_context() (dans le module multiprocessing)

get_coroutine_wrapper() (dans le module sys)

get_count() (dans le module gc)

get_current_history_length() (dans le module readline)

get_data() (dans le module pkgutil)

(méthode importlib.abc.FileLoader)

(méthode importlib.abc.ResourceLoader)

(méthode zipimport.zipimporter)

get_date() (méthode mailbox.MaildirMessage)

get_debug() (dans le module gc)

(méthode asyncio.AbstractEventLoop)

get_default() (méthode argparse.ArgumentParser)

get_default_compiler() (dans le module distutils.ccompiler)

get_default_domain() (dans le module nis)

get_default_type() (méthode email.message.EmailMessage)

(méthode email.message.Message)

get_default_verify_paths() (dans le module ssl)

get_dialect() (dans le module csv)

get_docstring() (dans le module ast)

get_doctest() (méthode doctest.DocTestParser)

get_endidx() (dans le module readline)

get_environ() (méthode wsgiref.simple_server.WSGIRequestHandler)

get_errno() (dans le module ctypes)

get_event_loop() (dans le module asyncio)

(méthode asyncio.AbstractEventLoopPolicy)

get_event_loop_policy() (dans le module asyncio)

get_examples() (méthode doctest.DocTestParser)

get_exception_handler() (méthode asyncio.AbstractEventLoop)

get_exec_path() (dans le module os)

get_extra_info() (méthode asyncio.BaseTransport)

(méthode asyncio.StreamWriter)

get_field() (méthode string.Formatter)

get_file() (méthode mailbox.Babyl)

(méthode mailbox.Mailbox)

(méthode mailbox.Maildir)

(méthode mailbox.mbox)

(méthode mailbox.MH)

(méthode mailbox.MMDF)

get_file_breaks() (méthode bdb.Bdb)

get_filename() (méthode email.message.EmailMessage)

(méthode email.message.Message)

(méthode importlib.abc.ExecutionLoader)

(méthode importlib.abc.FileLoader)

(méthode importlib.machinery.ExtensionFileLoader)

(méthode zipimport.zipimporter)

get_flags() (méthode mailbox.MaildirMessage)

(méthode mailbox.mboxMessage)

(méthode mailbox.MMDFMessage)

get_folder() (méthode mailbox.Maildir)

(méthode mailbox.MH)

get_frees() (méthode symtable.Function)

get_from() (méthode mailbox.mboxMessage)

(méthode mailbox.MMDFMessage)

get_full_url() (méthode urllib.request.Request)

get_globals() (méthode symtable.Function)

get_grouped_opcodes() (méthode difflib.SequenceMatcher)

get_handle_inheritable() (dans le module os)

get_header() (méthode urllib.request.Request)

get_history_item() (dans le module readline)

get_history_length() (dans le module readline)

get_id() (méthode symtable.SymbolTable)

get_ident() (dans le module _thread)

(dans le module threading)

get_identifiers() (méthode symtable.SymbolTable)

get_importer() (dans le module pkgutil)

get_info() (méthode mailbox.MaildirMessage)

get_inheritable() (dans le module os)

(méthode socket.socket)

get_instructions() (dans le module dis)

get_interpreter() (dans le module zipapp)

GET_ITER (opcode)

get_key() (méthode selectors.BaseSelector)

get_labels() (méthode mailbox.Babyl)

(méthode mailbox.BabylMessage)

get_last_error() (dans le module ctypes)

get_line_buffer() (dans le module readline)

get_lineno() (méthode symtable.SymbolTable)

get_loader() (dans le module pkgutil)

get_locals() (méthode symtable.Function)

get_logger() (dans le module multiprocessing)

get_magic() (dans le module imp)

get_makefile_filename() (dans le module distutils.sysconfig)

(dans le module sysconfig)

get_map() (méthode selectors.BaseSelector)

get_matching_blocks() (méthode difflib.SequenceMatcher)

get_message() (méthode mailbox.Mailbox)

get_method() (méthode urllib.request.Request)

get_methods() (méthode symtable.Class)

get_mixed_type_key() (dans le module ipaddress)

get_name() (méthode symtable.Symbol)

(méthode symtable.SymbolTable)

get_namespace() (méthode symtable.Symbol)

get_namespaces() (méthode symtable.Symbol)

get_nonstandard_attr() (méthode http.cookiejar.Cookie)

get_nowait() (méthode asyncio.Queue)

(méthode multiprocessing.Queue)

(méthode queue.Queue)

get_object_traceback() (dans le module tracemalloc)

get_objects() (dans le module gc)

get_opcodes() (méthode difflib.SequenceMatcher)

get_option() (méthode optparse.OptionParser)

get_option_group() (méthode optparse.OptionParser)

get_option_order() (méthode distutils.fancy_getopt.FancyGetopt)

get_osfhandle() (dans le module msvcrt)

get_output_charset() (méthode email.charset.Charset)

get_param() (méthode email.message.Message)

get_parameters() (méthode symtable.Function)

get_params() (méthode email.message.Message)

get_path() (dans le module sysconfig)

get_path_names() (dans le module sysconfig)

get_paths() (dans le module sysconfig)

get_payload() (méthode email.message.Message)

get_pid() (méthode asyncio.BaseSubprocessTransport)

get_pipe_transport() (méthode asyncio.BaseSubprocessTransport)

get_platform() (dans le module distutils.util)

(dans le module sysconfig)

get_poly() (dans le module turtle)

get_position() (méthode xdrlib.Unpacker)

get_protocol() (méthode asyncio.BaseTransport)

get_python_inc() (dans le module distutils.sysconfig)

get_python_lib() (dans le module distutils.sysconfig)

get_python_version() (dans le module sysconfig)

get_recsrc() (méthode ossaudiodev.oss_mixer_device)

get_referents() (dans le module gc)

get_referrers() (dans le module gc)

get_request() (méthode socketserver.BaseServer)

get_returncode() (méthode asyncio.BaseSubprocessTransport)

get_scheme() (méthode wsgiref.handlers.BaseHandler)

get_scheme_names() (dans le module sysconfig)

get_sequences() (méthode mailbox.MH)

(méthode mailbox.MHMessage)

get_server() (méthode multiprocessing.managers.BaseManager)

get_server_certificate() (dans le module ssl)

get_shapepoly() (dans le module turtle)

get_socket() (méthode telnetlib.Telnet)

get_source() (méthode importlib.abc.InspectLoader)

(méthode importlib.abc.SourceLoader)

(méthode importlib.machinery.ExtensionFileLoader)

(méthode importlib.machinery.SourcelessFileLoader)

(méthode zipimport.zipimporter)

get_special_folder_path() (fonction de base)

get_stack() (méthode asyncio.Task)

(méthode bdb.Bdb)

get_start_method() (dans le module multiprocessing)

get_starttag_text() (méthode html.parser.HTMLParser)

get_stats() (dans le module gc)

get_stderr() (méthode wsgiref.handlers.BaseHandler)

(méthode wsgiref.simple_server.WSGIRequestHandler)

get_stdin() (méthode wsgiref.handlers.BaseHandler)

get_string() (méthode mailbox.Mailbox)

get_subdir() (méthode mailbox.MaildirMessage)

get_suffixes() (dans le module imp)

get_symbols() (méthode symtable.SymbolTable)

get_tag() (dans le module imp)

get_task_factory() (méthode asyncio.AbstractEventLoop)

get_terminal_size() (dans le module os)

(dans le module shutil)

get_terminator() (méthode asynchat.async_chat)

get_threshold() (dans le module gc)

get_token() (méthode shlex.shlex)

get_traceback_limit() (dans le module tracemalloc)

get_traced_memory() (dans le module tracemalloc)

get_tracemalloc_memory() (dans le module tracemalloc)

get_type() (méthode symtable.SymbolTable)

get_type_hints() (dans le module typing)

get_unixfrom() (méthode email.message.EmailMessage)

(méthode email.message.Message)

get_unpack_formats() (dans le module shutil)

get_usage() (méthode optparse.OptionParser)

get_value() (méthode string.Formatter)

get_version() (méthode optparse.OptionParser)

get_visible() (méthode mailbox.BabylMessage)

get_wch() (méthode curses.window)

get_write_buffer_limits() (méthode asyncio.WriteTransport)

get_write_buffer_size() (méthode asyncio.WriteTransport)

GET_YIELD_FROM_ITER (opcode)

getacl() (méthode imaplib.IMAP4)

getaddresses() (dans le module email.utils)

getaddrinfo() (dans le module socket)

(méthode asyncio.AbstractEventLoop)

getallocatedblocks() (dans le module sys)

getannotation() (méthode imaplib.IMAP4)

getargspec() (dans le module inspect)

getargvalues() (dans le module inspect)

getatime() (dans le module os.path)

getattr() (fonction de base)

getattr_static() (dans le module inspect)

getAttribute() (méthode xml.dom.Element)

getAttributeNode() (méthode xml.dom.Element)

getAttributeNodeNS() (méthode xml.dom.Element)

getAttributeNS() (méthode xml.dom.Element)

GetBase() (méthode xml.parsers.expat.xmlparser)

getbegyx() (méthode curses.window)

getbkgd() (méthode curses.window)

getboolean() (méthode configparser.ConfigParser)

getbuffer() (méthode io.BytesIO)

getByteStream() (méthode xml.sax.xmlreader.InputSource)

getcallargs() (dans le module inspect)

getcanvas() (dans le module turtle)

getcapabilities() (méthode nntplib.NNTP)

getcaps() (dans le module mailcap)

getch() (dans le module msvcrt)

(méthode curses.window)

getCharacterStream() (méthode xml.sax.xmlreader.InputSource)

getche() (dans le module msvcrt)

getcheckinterval() (dans le module sys)

getChild() (méthode logging.Logger)

getchildren() (méthode xml.etree.ElementTree.Element)

getclasstree() (dans le module inspect)

getclosurevars() (dans le module inspect)

GetColumnInfo() (méthode msilib.View)

getColumnNumber() (méthode xml.sax.xmlreader.Locator)

getcomments() (dans le module inspect)

getcompname() (méthode aifc.aifc)

(méthode sunau.AU_read)

(méthode wave.Wave_read)

getcomptype() (méthode aifc.aifc)

(méthode sunau.AU_read)

(méthode wave.Wave_read)

getContentHandler() (méthode xml.sax.xmlreader.XMLReader)

getcontext() (dans le module decimal)

getcoroutinelocals() (dans le module inspect)

getcoroutinestate() (dans le module inspect)

getctime() (dans le module os.path)

getcwd() (dans le module os)

getcwdb() (dans le module os)

getcwdu (2to3 fixer)

getdecoder() (dans le module codecs)

getdefaultencoding() (dans le module sys)

getdefaultlocale() (dans le module locale)

getdefaulttimeout() (dans le module socket)

getdlopenflags() (dans le module sys)

getdoc() (dans le module inspect)

getDOMImplementation() (dans le module xml.dom)

getDTDHandler() (méthode xml.sax.xmlreader.XMLReader)

getEffectiveLevel() (méthode logging.Logger)

getegid() (dans le module os)

getElementsByTagName() (méthode xml.dom.Document)

(méthode xml.dom.Element)

getElementsByTagNameNS() (méthode xml.dom.Document)

(méthode xml.dom.Element)

getencoder() (dans le module codecs)

getEncoding() (méthode xml.sax.xmlreader.InputSource)

getEntityResolver() (méthode xml.sax.xmlreader.XMLReader)

getenv() (dans le module os)

getenvb() (dans le module os)

getErrorHandler() (méthode xml.sax.xmlreader.XMLReader)

geteuid() (dans le module os)

getEvent() (méthode xml.dom.pulldom.DOMEventStream)

getEventCategory() (méthode logging.handlers.NTEventLogHandler)

getEventType() (méthode logging.handlers.NTEventLogHandler)

getException() (méthode xml.sax.SAXException)

getFeature() (méthode xml.sax.xmlreader.XMLReader)

GetFieldCount() (méthode msilib.Record)

getfile() (dans le module inspect)

getfilesystemencodeerrors() (dans le module sys)

getfilesystemencoding() (dans le module sys)

getfirst() (méthode cgi.FieldStorage)

getfloat() (méthode configparser.ConfigParser)

getfmts() (méthode ossaudiodev.oss_audio_device)

getfqdn() (dans le module socket)

getframeinfo() (dans le module inspect)

getframerate() (méthode aifc.aifc)

(méthode sunau.AU_read)

(méthode wave.Wave_read)

getfullargspec() (dans le module inspect)

getgeneratorlocals() (dans le module inspect)

getgeneratorstate() (dans le module inspect)

getgid() (dans le module os)

getgrall() (dans le module grp)

getgrgid() (dans le module grp)

getgrnam() (dans le module grp)

getgrouplist() (dans le module os)

getgroups() (dans le module os)

getheader() (méthode http.client.HTTPResponse)

getheaders() (méthode http.client.HTTPResponse)

gethostbyaddr() (dans le module socket)

(in module socket)

gethostbyname() (dans le module socket)

gethostbyname_ex() (dans le module socket)

gethostname() (dans le module socket)

(in module socket)

getincrementaldecoder() (dans le module codecs)

getincrementalencoder() (dans le module codecs)

getinfo() (méthode zipfile.ZipFile)

getinnerframes() (dans le module inspect)

GetInputContext() (méthode xml.parsers.expat.xmlparser)

getint() (méthode configparser.ConfigParser)

GetInteger() (méthode msilib.Record)

getitem() (dans le module operator)

getiterator() (méthode xml.etree.ElementTree.Element)

(méthode xml.etree.ElementTree.ElementTree)

getitimer() (dans le module signal)

getkey() (méthode curses.window)

GetLastError() (dans le module ctypes)

getLength() (méthode xml.sax.xmlreader.Attributes)

getLevelName() (dans le module logging)

getline() (dans le module linecache)

getLineNumber() (méthode xml.sax.xmlreader.Locator)

getlist() (méthode cgi.FieldStorage)

getloadavg() (dans le module os)

getlocale() (dans le module locale)

getLogger() (dans le module logging)

getLoggerClass() (dans le module logging)

getlogin() (dans le module os)

getLogRecordFactory() (dans le module logging)

getmark() (méthode aifc.aifc)

(méthode sunau.AU_read)

(méthode wave.Wave_read)

getmarkers() (méthode aifc.aifc)

(méthode sunau.AU_read)

(méthode wave.Wave_read)

getmaxyx() (méthode curses.window)

getmember() (méthode tarfile.TarFile)

getmembers() (dans le module inspect)

(méthode tarfile.TarFile)

getMessage() (méthode logging.LogRecord)

(méthode xml.sax.SAXException)

getMessageID() (méthode logging.handlers.NTEventLogHandler)

getmodule() (dans le module inspect)

getmodulename() (dans le module inspect)

getmouse() (dans le module curses)

getmro() (dans le module inspect)

getmtime() (dans le module os.path)

getname() (méthode chunk.Chunk)

getName() (méthode threading.Thread)

getNameByQName() (méthode xml.sax.xmlreader.AttributesNS)

getnameinfo() (dans le module socket)

(méthode asyncio.AbstractEventLoop)

getnames() (méthode tarfile.TarFile)

getNames() (méthode xml.sax.xmlreader.Attributes)

getnchannels() (méthode aifc.aifc)

(méthode sunau.AU_read)

(méthode wave.Wave_read)

getnframes() (méthode aifc.aifc)

(méthode sunau.AU_read)

(méthode wave.Wave_read)

getnode

getnode() (dans le module uuid)

getopt (module)

getopt() (dans le module getopt)

(méthode distutils.fancy_getopt.FancyGetopt)

GetoptError

getouterframes() (dans le module inspect)

getoutput() (dans le module subprocess)

getpagesize() (dans le module resource)

getparams() (méthode aifc.aifc)

(méthode sunau.AU_read)

(méthode wave.Wave_read)

getparyx() (méthode curses.window)

getpass (module)

getpass() (dans le module getpass)

GetPassWarning

getpeercert() (méthode ssl.SSLSocket)

getpeername() (méthode socket.socket)

getpen() (dans le module turtle)

getpgid() (dans le module os)

getpgrp() (dans le module os)

getpid() (dans le module os)

getpos() (méthode html.parser.HTMLParser)

getppid() (dans le module os)

getpreferredencoding() (dans le module locale)

getpriority() (dans le module os)

getprofile() (dans le module sys)

GetProperty() (méthode msilib.SummaryInformation)

getProperty() (méthode xml.sax.xmlreader.XMLReader)

GetPropertyCount() (méthode msilib.SummaryInformation)

getprotobyname() (dans le module socket)

getproxies() (dans le module urllib.request)

getPublicId() (méthode xml.sax.xmlreader.InputSource)

(méthode xml.sax.xmlreader.Locator)

getpwall() (dans le module pwd)

getpwnam() (dans le module pwd)

getpwuid() (dans le module pwd)

getQNameByName() (méthode xml.sax.xmlreader.AttributesNS)

getQNames() (méthode xml.sax.xmlreader.AttributesNS)

getquota() (méthode imaplib.IMAP4)

getquotaroot() (méthode imaplib.IMAP4)

getrandbits() (dans le module random)

getrandom() (dans le module os)

getreader() (dans le module codecs)

getrecursionlimit() (dans le module sys)

getrefcount() (dans le module sys)

getresgid() (dans le module os)

getresponse() (méthode http.client.HTTPConnection)

getresuid() (dans le module os)

getrlimit() (dans le module resource)

getroot() (méthode xml.etree.ElementTree.ElementTree)

getrusage() (dans le module resource)

getsample() (dans le module audioop)

getsampwidth() (méthode aifc.aifc)

(méthode sunau.AU_read)

(méthode wave.Wave_read)

getscreen() (dans le module turtle)

getservbyname() (dans le module socket)

getservbyport() (dans le module socket)

GetSetDescriptorType (dans le module types)

getshapes() (dans le module turtle)

getsid() (dans le module os)

getsignal() (dans le module signal)

getsitepackages() (dans le module site)

getsize() (dans le module os.path)

(méthode chunk.Chunk)

getsizeof() (dans le module sys)

getsockname() (méthode socket.socket)

getsockopt() (méthode socket.socket)

getsource() (dans le module inspect)

getsourcefile() (dans le module inspect)

getsourcelines() (dans le module inspect)

getspall() (dans le module spwd)

getspnam() (dans le module spwd)

getstate() (dans le module random)

(méthode codecs.IncrementalDecoder)

(méthode codecs.IncrementalEncoder)

getstatusoutput() (dans le module subprocess)

getstr() (méthode curses.window)

GetString() (méthode msilib.Record)

getSubject() (méthode logging.handlers.SMTPHandler)

GetSummaryInformation() (méthode msilib.Database)

getswitchinterval() (dans le module sys)

getSystemId() (méthode xml.sax.xmlreader.InputSource)

(méthode xml.sax.xmlreader.Locator)

getsyx() (dans le module curses)

gettarinfo() (méthode tarfile.TarFile)

gettempdir() (dans le module tempfile)

gettempdirb() (dans le module tempfile)

gettempprefix() (dans le module tempfile)

gettempprefixb() (dans le module tempfile)

getTestCaseNames() (méthode unittest.TestLoader)

gettext (module)

gettext() (dans le module gettext)

(dans le module locale)

(méthode gettext.GNUTranslations)

(méthode gettext.NullTranslations)

gettimeout() (méthode socket.socket)

gettrace() (dans le module sys)

getturtle() (dans le module turtle)

getType() (méthode xml.sax.xmlreader.Attributes)

getuid() (dans le module os)

geturl() (méthode urllib.parse.urllib.parse.SplitResult)

getuser() (dans le module getpass)

getuserbase() (dans le module site)

getusersitepackages() (dans le module site)

getvalue() (méthode io.BytesIO)

(méthode io.StringIO)

getValue() (méthode xml.sax.xmlreader.Attributes)

getValueByQName() (méthode xml.sax.xmlreader.AttributesNS)

getwch() (dans le module msvcrt)

getwche() (dans le module msvcrt)

getweakrefcount() (dans le module weakref)

getweakrefs() (dans le module weakref)

getwelcome() (méthode ftplib.FTP)

(méthode nntplib.NNTP)

(méthode poplib.POP3)

getwin() (dans le module curses)

getwindowsversion() (dans le module sys)

getwriter() (dans le module codecs)

getxattr() (dans le module os)

getyx() (méthode curses.window)

générateur

générateur asynchrone

gid (attribut tarfile.TarInfo)

GIL

glob

module

glob (module)

glob() (dans le module glob)

(méthode msilib.Directory)

(méthode pathlib.Path)

global

état, [1]

name binding

namespace

global interpreter lock

globals() (fonction de base)

globs (attribut doctest.DocTest)

gmtime() (dans le module time)

gname (attribut tarfile.TarInfo)

GNOME

GNU_FORMAT (dans le module tarfile)

gnu_getopt() (dans le module getopt)

GNUTranslations (classe dans gettext)

got (attribut doctest.DocTestFailure)

goto() (dans le module turtle)

grammar

Graphical User Interface

GREATER (dans le module token)

GREATEREQUAL (dans le module token)

Greenwich Mean Time

GRND_NONBLOCK (dans le module os)

GRND_RANDOM (dans le module os)

Group (classe dans email.headerregistry)

group() (méthode nntplib.NNTP)

(méthode pathlib.Path)

(méthode re.match)

groupby() (dans le module itertools)

groupdict() (méthode re.match)

groupindex (attribut re.regex)

grouping

groups (attribut email.headerregistry.AddressHeader)

(attribut re.regex)

groups() (méthode re.match)

grp (module)

gt() (dans le module operator)

guess_all_extensions() (dans le module mimetypes)

(méthode mimetypes.MimeTypes)

guess_extension() (dans le module mimetypes)

(méthode mimetypes.MimeTypes)

guess_scheme() (dans le module wsgiref.util)

guess_type() (dans le module mimetypes)

(méthode mimetypes.MimeTypes)

GUI

gzip (module)

GzipFile (classe dans gzip)

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Index – H

hachable

halfdelay() (dans le module curses)

Handle (classe dans asyncio)

handle an exception

handle() (méthode http.server.BaseHTTPRequestHandler)

(méthode logging.Handler)

(méthode logging.handlers.QueueListener)

(méthode logging.Logger)

(méthode logging.NullHandler)

(méthode socketserver.BaseRequestHandler)

(méthode wsgiref.simple_server.WSGIRequestHandler)

handle_accept() (méthode asyncore.dispatcher)

handle_accepted() (méthode asyncore.dispatcher)

handle_charref() (méthode html.parser.HTMLParser)

handle_close() (méthode asyncore.dispatcher)

handle_comment() (méthode html.parser.HTMLParser)

handle_connect() (méthode asyncore.dispatcher)

handle_data() (méthode html.parser.HTMLParser)

handle_decl() (méthode html.parser.HTMLParser)

handle_defect() (méthode email.policy.Policy)

handle_endtag() (méthode html.parser.HTMLParser)

handle_entityref() (méthode html.parser.HTMLParser)

handle_error() (méthode asyncore.dispatcher)

(méthode socketserver.BaseServer)

handle_expect_100() (méthode http.server.BaseHTTPRequestHandler)

handle_expt() (méthode asyncore.dispatcher)

handle_one_request() (méthode http.server.BaseHTTPRequestHandler)

handle_pi() (méthode html.parser.HTMLParser)

handle_read() (méthode asyncore.dispatcher)

handle_request() (méthode socketserver.BaseServer)

(méthode xmlrpc.server.CGIXMLRPCRequestHandler)

handle_startendtag() (méthode html.parser.HTMLParser)

handle_starttag() (méthode html.parser.HTMLParser)

handle_timeout() (méthode socketserver.BaseServer)

handle_write() (méthode asyncore.dispatcher)

handleError() (méthode logging.Handler)

(méthode logging.handlers.SocketHandler)

handler

exception

Handler (classe dans logging)

handler() (dans le module cgitb)

harmonic_mean() (dans le module statistics)

HAS_ALPN (dans le module ssl)

has_children() (méthode symtable.SymbolTable)

has_colors() (dans le module curses)

HAS_ECDH (dans le module ssl)

has_exec() (méthode symtable.SymbolTable)

has_extn() (méthode smtplib.SMTP)

has_function() (méthode distutils.ccompiler.CCompiler)

has_header() (méthode csv.Sniffer)

(méthode urllib.request.Request)

has_ic() (dans le module curses)

has_il() (dans le module curses)

has_ipv6 (dans le module socket)

has_key (2to3 fixer)

has_key() (dans le module curses)

has_location (attribut importlib.machinery.ModuleSpec)

has_nonstandard_attr() (méthode http.cookiejar.Cookie)

HAS_NPN (dans le module ssl)

has_option() (méthode configparser.ConfigParser)

(méthode optparse.OptionParser)

has_section() (méthode configparser.ConfigParser)

HAS_SNI (dans le module ssl)

has_ticket (attribut ssl.SSLSession)

HAS_TLSv1_3 (dans le module ssl)

hasattr() (fonction de base)

hasAttribute() (méthode xml.dom.Element)

hasAttributeNS() (méthode xml.dom.Element)

hasAttributes() (méthode xml.dom.Node)

hasChildNodes() (méthode xml.dom.Node)

hascompare (dans le module dis)

hasconst (dans le module dis)

hasFeature() (méthode xml.dom.DOMImplementation)

hasfree (dans le module dis)

hash

fonction de base, [1], [2], [3]

hash character

hash() (fonction de base)

hash.block_size (dans le module hashlib)

hash.digest_size (dans le module hashlib)

hash_info (dans le module sys)

hashable

Hashable (classe dans collections.abc)

(classe dans typing)

hasHandlers() (méthode logging.Logger)

hashlib (module)

hasjabs (dans le module dis)

hasjrel (dans le module dis)

haslocal (dans le module dis)

hasname (dans le module dis)

HAVE_ARGUMENT (opcode)

HAVE_THREADS (dans le module decimal)

HCI_DATA_DIR (dans le module socket)

HCI_FILTER (dans le module socket)

HCI_TIME_STAMP (dans le module socket)

head() (méthode nntplib.NNTP)

Header (classe dans email.header)

header_encode() (méthode email.charset.Charset)

header_encode_lines() (méthode email.charset.Charset)

header_encoding (attribut email.charset.Charset)

header_factory (attribut email.policy.EmailPolicy)

header_fetch_parse() (méthode email.policy.Compat32)

(méthode email.policy.EmailPolicy)

(méthode email.policy.Policy)

header_items() (méthode urllib.request.Request)

header_max_count() (méthode email.policy.EmailPolicy)

(méthode email.policy.Policy)

header_offset (attribut zipfile.ZipInfo)

header_source_parse() (méthode email.policy.Compat32)

(méthode email.policy.EmailPolicy)

(méthode email.policy.Policy)

header_store_parse() (méthode email.policy.Compat32)

(méthode email.policy.EmailPolicy)

(méthode email.policy.Policy)

HeaderError

HeaderParseError

HeaderParser (classe dans email.parser)

HeaderRegistry (classe dans email.headerregistry)

headers

MIME, [1]

headers (attribut http.server.BaseHTTPRequestHandler)

(attribut urllib.error.HTTPError)

(attribut xmlrpc.client.ProtocolError)

Headers (classe dans wsgiref.headers)

heading() (dans le module turtle)

(méthode tkinter.ttk.Treeview)

heapify() (dans le module heapq)

heapmin() (dans le module msvcrt)

heappop() (dans le module heapq)

heappush() (dans le module heapq)

heappushpop() (dans le module heapq)

heapq (module)

heapreplace() (dans le module heapq)

helo() (méthode smtplib.SMTP)

help

fonction de base

online

help (attribut optparse.Option)

(pdb command)

help() (fonction de base)

(méthode nntplib.NNTP)

herror

hex (attribut uuid.UUID)

hex() (fonction de base)

(méthode bytearray)

(méthode bytes)

(méthode float)

(méthode memoryview)

hexadecimal

literals

hexadecimal literal

hexbin() (dans le module binhex)

hexdigest() (méthode hashlib.hash)

(méthode hashlib.shake)

(méthode hmac.HMAC)

hexdigits (dans le module string)

hexlify() (dans le module binascii)

hexversion (dans le module sys)

hidden() (méthode curses.panel.Panel)

hide() (méthode curses.panel.Panel)

(méthode tkinter.ttk.Notebook)

hide_cookie2 (attribut http.cookiejar.CookiePolicy)

hideturtle() (dans le module turtle)

hierarchy

type

HierarchyRequestErr

HIGHEST_PROTOCOL (dans le module pickle)

HKEY_CLASSES_ROOT (dans le module winreg)

HKEY_CURRENT_CONFIG (dans le module winreg)

HKEY_CURRENT_USER (dans le module winreg)

HKEY_DYN_DATA (dans le module winreg)

HKEY_LOCAL_MACHINE (dans le module winreg)

HKEY_PERFORMANCE_DATA (dans le module winreg)

HKEY_USERS (dans le module winreg)

hline() (méthode curses.window)

HList (classe dans tkinter.tix)

hls_to_rgb() (dans le module colorsys)

hmac (module)

HOME, [1], [2], [3], [4]

home() (dans le module turtle)

(méthode de la classe pathlib.Path)

HOMEDRIVE, [1]

HOMEPATH, [1]

hook_compressed() (dans le module fileinput)

hook_encoded() (dans le module fileinput)

hooks

import

meta

path

host (attribut urllib.request.Request)

hostmask (attribut ipaddress.IPv4Network)

(attribut ipaddress.IPv6Network)

hosts (attribut netrc.netrc)

hosts() (méthode ipaddress.IPv4Network)

(méthode ipaddress.IPv6Network)

hour (attribut datetime.datetime)

(attribut datetime.time)

HRESULT (classe dans ctypes)

hStdError (attribut subprocess.STARTUPINFO)

hStdInput (attribut subprocess.STARTUPINFO)

hStdOutput (attribut subprocess.STARTUPINFO)

hsv_to_rgb() (dans le module colorsys)

ht() (dans le module turtle)

HTML, [1]

html (module)

html.entities (module)

html.parser (module)

html5 (dans le module html.entities)

HTMLCalendar (classe dans calendar)

HtmlDiff (classe dans difflib)

HTMLParser (classe dans html.parser)

htonl() (dans le module socket)

htons() (dans le module socket)

HTTP

http (standard module)

http.client (standard module)

protocol, [1], [2], [3], [4], [5]

HTTP (dans le module email.policy)

http (module)

http.client (module)

http.cookiejar (module)

http.cookies (module)

http.server (module)

http_error_301() (méthode urllib.request.HTTPRedirectHandler)

http_error_302() (méthode urllib.request.HTTPRedirectHandler)

http_error_303() (méthode urllib.request.HTTPRedirectHandler)

http_error_307() (méthode urllib.request.HTTPRedirectHandler)

http_error_401() (méthode urllib.request.HTTPBasicAuthHandler)

(méthode urllib.request.HTTPDigestAuthHandler)

http_error_407() (méthode urllib.request.ProxyBasicAuthHandler)

(méthode urllib.request.ProxyDigestAuthHandler)

http_error_auth_reqed() (méthode urllib.request.AbstractBasicAuthHandler)

(méthode urllib.request.AbstractDigestAuthHandler)

http_error_default() (méthode urllib.request.BaseHandler)

http_error_nnn() (méthode urllib.request.BaseHandler)

http_open() (méthode urllib.request.HTTPHandler)

HTTP_PORT (dans le module http.client)

http_proxy, [1], [2]

http_response() (méthode urllib.request.HTTPErrorProcessor)

http_version (attribut wsgiref.handlers.BaseHandler)

HTTPBasicAuthHandler (classe dans urllib.request)

HTTPConnection (classe dans http.client)

HTTPCookieProcessor (classe dans urllib.request)

httpd

HTTPDefaultErrorHandler (classe dans urllib.request)

HTTPDigestAuthHandler (classe dans urllib.request)

HTTPError

HTTPErrorProcessor (classe dans urllib.request)

HTTPException

HTTPHandler (classe dans logging.handlers)

(classe dans urllib.request)

HTTPPasswordMgr (classe dans urllib.request)

HTTPPasswordMgrWithDefaultRealm (classe dans urllib.request)

HTTPPasswordMgrWithPriorAuth (classe dans urllib.request)

HTTPRedirectHandler (classe dans urllib.request)

HTTPResponse (classe dans http.client)

https_open() (méthode urllib.request.HTTPSHandler)

HTTPS_PORT (dans le module http.client)

https_response() (méthode urllib.request.HTTPErrorProcessor)

HTTPSConnection (classe dans http.client)

HTTPServer (classe dans http.server)

HTTPSHandler (classe dans urllib.request)

HTTPStatus (classe dans http)

hypot() (dans le module math)

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Index – I

I (dans le module re)

I/O control

buffering, [1]

POSIX

tty

UNIX

iadd() (dans le module operator)

iand() (dans le module operator)

iconcat() (dans le module operator)

id

fonction de base

id (attribut ssl.SSLSession)

id() (fonction de base)

(méthode unittest.TestCase)

idcok() (méthode curses.window)

ident (attribut select.kevent)

(attribut threading.Thread)

identchars (attribut cmd.Cmd)

identifier, [1]

identify() (méthode tkinter.ttk.Notebook)

(méthode tkinter.ttk.Treeview)

(méthode tkinter.ttk.Widget)

identify_column() (méthode tkinter.ttk.Treeview)

identify_element() (méthode tkinter.ttk.Treeview)

identify_region() (méthode tkinter.ttk.Treeview)

identify_row() (méthode tkinter.ttk.Treeview)

identity

test

identity of an object

idioms (2to3 fixer)

IDLE, [1]

IDLE*STARTUP

IDLESTARTUP

idlok() (méthode curses.window)

IEEE-754

if

conditional expression

état, [1]

in comprehensions

if_indextoname() (dans le module socket)

if_nameindex() (dans le module socket)

if_nametoindex() (dans le module socket)

ifloordiv() (dans le module operator)

iglob() (dans le module glob)

ignorableWhitespace() (méthode xml.sax.handler.ContentHandler)

ignore (pdb command)

ignore_errors() (dans le module codecs)

IGNORE_EXCEPTION_DETAIL (dans le module doctest)

ignore_patterns() (dans le module shutil)

IGNORECASE (dans le module re)

ihave() (méthode nntplib.NNTP)

IISCGIHandler (classe dans wsgiref.handlers)

ilshift() (dans le module operator)

imag (attribut numbers.Complex)

imaginary literal

imap() (méthode multiprocessing.pool.Pool)

IMAP4

protocol

IMAP4 (classe dans imaplib)

IMAP4.abort

IMAP4.error

IMAP4.readonly

IMAP4_SSL

protocol

IMAP4_SSL (classe dans imaplib)

IMAP4_stream

protocol

IMAP4_stream (classe dans imaplib)

imap_unordered() (méthode multiprocessing.pool.Pool)

imaplib (module)

imatmul() (dans le module operator)

imghdr (module)

immedok() (méthode curses.window)

immuable

immutable

data type

object, [1]

objet

sequence types

immutable object

immutable sequence

objet

immutable types

subclassing

imod() (dans le module operator)

imp

module

imp (module)

ImpImporter (classe dans pkgutil)

implementation (dans le module sys)

ImpLoader (classe dans pkgutil)

import

état, [1], [2], [3], [4]

hooks

import (2to3 fixer)

import hooks

import machinery

import_fresh_module() (dans le module test.support)

IMPORT_FROM (opcode)

import_module() (dans le module importlib)

(dans le module test.support)

IMPORT_NAME (opcode)

IMPORT_STAR (opcode)

importateur

importer

ImportError

exception

importlib (module)

importlib.abc (module)

importlib.machinery (module)

importlib.util (module)

imports (2to3 fixer)

imports2 (2to3 fixer)

ImportWarning

ImproperConnectionState

imul() (dans le module operator)

in

mot-clé, [1]

opérateur, [1], [2]

in_dll() (méthode ctypes._CData)

in_table_a1() (dans le module stringprep)

in_table_b1() (dans le module stringprep)

in_table_c11() (dans le module stringprep)

in_table_c11_c12() (dans le module stringprep)

in_table_c12() (dans le module stringprep)

in_table_c21() (dans le module stringprep)

in_table_c21_c22() (dans le module stringprep)

in_table_c22() (dans le module stringprep)

in_table_c3() (dans le module stringprep)

in_table_c4() (dans le module stringprep)

in_table_c5() (dans le module stringprep)

in_table_c6() (dans le module stringprep)

in_table_c7() (dans le module stringprep)

in_table_c8() (dans le module stringprep)

in_table_c9() (dans le module stringprep)

in_table_d1() (dans le module stringprep)

in_table_d2() (dans le module stringprep)

in_transaction (attribut sqlite3.Connection)

inch() (méthode curses.window)

inclusive

or

inclusive (attribut tracemalloc.DomainFilter)

(attribut tracemalloc.Filter)

Incomplete

IncompleteRead

IncompleteReadError

incr_item(), [1]

increment_lineno() (dans le module ast)

incrementaldecoder (attribut codecs.CodecInfo)

IncrementalDecoder (classe dans codecs)

incrementalencoder (attribut codecs.CodecInfo)

IncrementalEncoder (classe dans codecs)

IncrementalNewlineDecoder (classe dans io)

IncrementalParser (classe dans xml.sax.xmlreader)

indent (attribut doctest.Example)

INDENT (dans le module token)

INDENT token

indent() (dans le module textwrap)

indentation

IndentationError

index operation

index() (dans le module operator)

(méthode array.array)

(méthode bytearray)

(méthode bytes)

(méthode collections.deque)

(méthode str)

(méthode tkinter.ttk.Notebook)

(méthode tkinter.ttk.Treeview)

(sequence method)

IndexError

indexOf() (dans le module operator)

IndexSizeErr

indication de type

indices() (méthode slice)

inet_aton() (dans le module socket)

inet_ntoa() (dans le module socket)

inet_ntop() (dans le module socket)

inet_pton() (dans le module socket)

Inexact (classe dans decimal)

inf (dans le module cmath)

(dans le module math)

infile

json.tool command line option

infile (attribut shlex.shlex)

Infinity

infj (dans le module cmath)

info() (dans le module logging)

(méthode dis.Bytecode)

(méthode gettext.NullTranslations)

(méthode logging.Logger)

infolist() (méthode zipfile.ZipFile)

inheritance

ini file

init() (dans le module mimetypes)

init_color() (dans le module curses)

init_database() (dans le module msilib)

init_pair() (dans le module curses)

inited (dans le module mimetypes)

initgroups() (dans le module os)

initial_indent (attribut textwrap.TextWrapper)

initialize_options() (méthode distutils.cmd.Command)

initscr() (dans le module curses)

inode() (méthode os.DirEntry)

INPLACE_ADD (opcode)

INPLACE_AND (opcode)

INPLACE_FLOOR_DIVIDE (opcode)

INPLACE_LSHIFT (opcode)

INPLACE_MATRIX_MULTIPLY (opcode)

INPLACE_MODULO (opcode)

INPLACE_MULTIPLY (opcode)

INPLACE_OR (opcode)

INPLACE_POWER (opcode)

INPLACE_RSHIFT (opcode)

INPLACE_SUBTRACT (opcode)

INPLACE_TRUE_DIVIDE (opcode)

INPLACE_XOR (opcode)

input

(2to3 fixer)

input() (dans le module fileinput)

(fonction de base)

input_charset (attribut email.charset.Charset)

input_codec (attribut email.charset.Charset)

InputOnly (classe dans tkinter.tix)

InputSource (classe dans xml.sax.xmlreader)

inquiry (type C)

insch() (méthode curses.window)

insdelln() (méthode curses.window)

insert() (méthode array.array)

(méthode collections.deque)

(méthode tkinter.ttk.Notebook)

(méthode tkinter.ttk.Treeview)

(méthode xml.etree.ElementTree.Element)

(sequence method)

insert_text() (dans le module readline)

insertBefore() (méthode xml.dom.Node)

insertln() (méthode curses.window)

insnstr() (méthode curses.window)

insort() (dans le module bisect)

insort_left() (dans le module bisect)

insort_right() (dans le module bisect)

inspect (module)

inspect command line option

--details

InspectLoader (classe dans importlib.abc)

insstr() (méthode curses.window)

install() (dans le module gettext)

(méthode gettext.NullTranslations)

install_opener() (dans le module urllib.request)

install_scripts() (méthode venv.EnvBuilder)

installHandler() (dans le module unittest)

instance

call, [1]

class

objet, [1], [2]

instancemethod

objet

instate() (méthode tkinter.ttk.Widget)

instr() (méthode curses.window)

instream (attribut shlex.shlex)

instruction

Instruction (classe dans dis)

Instruction.arg (dans le module dis)

Instruction.argrepr (dans le module dis)

Instruction.argval (dans le module dis)

Instruction.is_jump_target (dans le module dis)

Instruction.offset (dans le module dis)

Instruction.opcode (dans le module dis)

Instruction.opname (dans le module dis)

Instruction.starts_line (dans le module dis)

int

fonction de base, [1], [2]

int (attribut uuid.UUID)

(classe de base)

Int2AP() (dans le module imaplib)

int_info (dans le module sys)

integer

literals

objet, [1], [2]

representation

types, operations on

integer literal

Integral (classe dans numbers)

Integrated Development Environment

IntegrityError

Intel/DVI ADPCM

IntEnum (classe dans enum)

interact (pdb command)

interact() (dans le module code)

(méthode code.InteractiveConsole)

(méthode telnetlib.Telnet)

interactif

interactive mode

InteractiveConsole (classe dans code)

InteractiveInterpreter (classe dans code)

intern (2to3 fixer)

intern() (dans le module sys)

internal type

internal_attr (attribut zipfile.ZipInfo)

Internaldate2tuple() (dans le module imaplib)

internalSubset (attribut xml.dom.DocumentType)

Internet

interpolated string literal

interpolation

bytearray (%)

bytes (%)

interpolation, string (%)

InterpolationDepthError

InterpolationError

InterpolationMissingOptionError

InterpolationSyntaxError

interpreter

interpreter lock

interpreter prompts

interprété

interrupt() (méthode sqlite3.Connection)

interrupt_main() (dans le module _thread)

InterruptedError

intersection() (méthode frozenset)

intersection_update() (méthode frozenset)

IntFlag (classe dans enum)

intro (attribut cmd.Cmd)

InuseAttributeErr

inv() (dans le module operator)

InvalidAccessErr

invalidate_caches() (dans le module importlib)

(méthode de la classe importlib.machinery.PathFinder)

(méthode importlib.abc.MetaPathFinder)

(méthode importlib.abc.PathEntryFinder)

(méthode importlib.machinery.FileFinder)

InvalidCharacterErr

InvalidModificationErr

InvalidOperation (classe dans decimal)

InvalidStateErr

InvalidStateError

InvalidURL

inversion

invert() (dans le module operator)

invocation

io

module

IO (classe dans typing)

io (module)

io.StringIO

objet

IOBase (classe dans io)

ioctl() (dans le module fcntl)

(méthode socket.socket)

IOError

ior() (dans le module operator)

ip (attribut ipaddress.IPv4Interface)

(attribut ipaddress.IPv6Interface)

ip_address() (dans le module ipaddress)

ip_interface() (dans le module ipaddress)

ip_network() (dans le module ipaddress)

ipaddress (module)

ipow() (dans le module operator)

ipv4_mapped (attribut ipaddress.IPv6Address)

IPv4Address (classe dans ipaddress)

IPv4Interface (classe dans ipaddress)

IPv4Network (classe dans ipaddress)

IPv6Address (classe dans ipaddress)

IPv6Interface (classe dans ipaddress)

IPv6Network (classe dans ipaddress)

irshift() (dans le module operator)

is

opérateur, [1]

is not

opérateur, [1]

is_() (dans le module operator)

is_absolute() (méthode pathlib.PurePath)

is_alive() (méthode multiprocessing.Process)

(méthode threading.Thread)

is_assigned() (méthode symtable.Symbol)

is_attachment() (méthode email.message.EmailMessage)

is_authenticated() (méthode urllib.request.HTTPPasswordMgrWithPriorAuth)

is_block_device() (méthode pathlib.Path)

is_blocked() (méthode http.cookiejar.DefaultCookiePolicy)

is_canonical() (méthode decimal.Context)

(méthode decimal.Decimal)

is_char_device() (méthode pathlib.Path)

IS_CHARACTER_JUNK() (dans le module difflib)

is_check_supported() (dans le module lzma)

is_closed() (méthode asyncio.AbstractEventLoop)

is_closing() (méthode asyncio.BaseTransport)

is_declared_global() (méthode symtable.Symbol)

is_dir() (méthode os.DirEntry)

(méthode pathlib.Path)

(méthode zipfile.ZipInfo)

is_enabled() (dans le module faulthandler)

is_expired() (méthode http.cookiejar.Cookie)

is_fifo() (méthode pathlib.Path)

is_file() (méthode os.DirEntry)

(méthode pathlib.Path)

is_finalizing() (dans le module sys)

is_finite() (méthode decimal.Context)

(méthode decimal.Decimal)

is_free() (méthode symtable.Symbol)

is_global (attribut ipaddress.IPv4Address)

(attribut ipaddress.IPv6Address)

is_global() (méthode symtable.Symbol)

is_hop_by_hop() (dans le module wsgiref.util)

is_imported() (méthode symtable.Symbol)

is_infinite() (méthode decimal.Context)

(méthode decimal.Decimal)

is_integer() (méthode float)

is_jython (dans le module test.support)

IS_LINE_JUNK() (dans le module difflib)

is_linetouched() (méthode curses.window)

is_link_local (attribut ipaddress.IPv4Address)

(attribut ipaddress.IPv4Network)

(attribut ipaddress.IPv6Address)

(attribut ipaddress.IPv6Network)

is_local() (méthode symtable.Symbol)

is_loopback (attribut ipaddress.IPv4Address)

(attribut ipaddress.IPv4Network)

(attribut ipaddress.IPv6Address)

(attribut ipaddress.IPv6Network)

is_multicast (attribut ipaddress.IPv4Address)

(attribut ipaddress.IPv4Network)

(attribut ipaddress.IPv6Address)

(attribut ipaddress.IPv6Network)

is_multipart() (méthode email.message.EmailMessage)

(méthode email.message.Message)

is_namespace() (méthode symtable.Symbol)

is_nan() (méthode decimal.Context)

(méthode decimal.Decimal)

is_nested() (méthode symtable.SymbolTable)

is_normal() (méthode decimal.Context)

(méthode decimal.Decimal)

is_not() (dans le module operator)

is_not_allowed() (méthode http.cookiejar.DefaultCookiePolicy)

is_optimized() (méthode symtable.SymbolTable)

is_package() (méthode importlib.abc.InspectLoader)

(méthode importlib.abc.SourceLoader)

(méthode importlib.machinery.ExtensionFileLoader)

(méthode importlib.machinery.SourceFileLoader)

(méthode importlib.machinery.SourcelessFileLoader)

(méthode zipimport.zipimporter)

is_parameter() (méthode symtable.Symbol)

is_private (attribut ipaddress.IPv4Address)

(attribut ipaddress.IPv4Network)

(attribut ipaddress.IPv6Address)

(attribut ipaddress.IPv6Network)

is_python_build() (dans le module sysconfig)

is_qnan() (méthode decimal.Context)

(méthode decimal.Decimal)

is_referenced() (méthode symtable.Symbol)

is_reserved (attribut ipaddress.IPv4Address)

(attribut ipaddress.IPv4Network)

(attribut ipaddress.IPv6Address)

(attribut ipaddress.IPv6Network)

is_reserved() (méthode pathlib.PurePath)

is_resource_enabled() (dans le module test.support)

is_running() (méthode asyncio.AbstractEventLoop)

is_set() (méthode asyncio.Event)

(méthode threading.Event)

is_signed() (méthode decimal.Context)

(méthode decimal.Decimal)

is_site_local (attribut ipaddress.IPv6Address)

(attribut ipaddress.IPv6Network)

is_snan() (méthode decimal.Context)

(méthode decimal.Decimal)

is_socket() (méthode pathlib.Path)

is_subnormal() (méthode decimal.Context)

(méthode decimal.Decimal)

is_symlink() (méthode os.DirEntry)

(méthode pathlib.Path)

is_tarfile() (dans le module tarfile)

is_term_resized() (dans le module curses)

is_tracing() (dans le module tracemalloc)

is_tracked() (dans le module gc)

is_unspecified (attribut ipaddress.IPv4Address)

(attribut ipaddress.IPv4Network)

(attribut ipaddress.IPv6Address)

(attribut ipaddress.IPv6Network)

is_wintouched() (méthode curses.window)

is_zero() (méthode decimal.Context)

(méthode decimal.Decimal)

is_zipfile() (dans le module zipfile)

isabs() (dans le module os.path)

isabstract() (dans le module inspect)

IsADirectoryError

isalnum() (dans le module curses.ascii)

(méthode bytearray)

(méthode bytes)

(méthode str)

isalpha() (dans le module curses.ascii)

(méthode bytearray)

(méthode bytes)

(méthode str)

isascii() (dans le module curses.ascii)

isasyncgen() (dans le module inspect)

isasyncgenfunction() (dans le module inspect)

isatty() (dans le module os)

(méthode chunk.Chunk)

(méthode io.IOBase)

isawaitable() (dans le module inspect)

isblank() (dans le module curses.ascii)

isblk() (méthode tarfile.TarInfo)

isbuiltin() (dans le module inspect)

ischr() (méthode tarfile.TarInfo)

isclass() (dans le module inspect)

isclose() (dans le module cmath)

(dans le module math)

iscntrl() (dans le module curses.ascii)

iscode() (dans le module inspect)

iscoroutine() (dans le module asyncio)

(dans le module inspect)

iscoroutinefunction() (dans le module asyncio)

(dans le module inspect)

isctrl() (dans le module curses.ascii)

isDaemon() (méthode threading.Thread)

isdatadescriptor() (dans le module inspect)

isdecimal() (méthode str)

isdev() (méthode tarfile.TarInfo)

isdigit() (dans le module curses.ascii)

(méthode bytearray)

(méthode bytes)

(méthode str)

isdir() (dans le module os.path)

(méthode tarfile.TarInfo)

isdisjoint() (méthode frozenset)

isdown() (dans le module turtle)

iselement() (dans le module xml.etree.ElementTree)

isenabled() (dans le module gc)

isEnabledFor() (méthode logging.Logger)

isendwin() (dans le module curses)

ISEOF() (dans le module token)

isexpr() (dans le module parser)

(méthode parser.ST)

isfifo() (méthode tarfile.TarInfo)

isfile() (dans le module os.path)

(méthode tarfile.TarInfo)

isfinite() (dans le module cmath)

(dans le module math)

isfirstline() (dans le module fileinput)

isframe() (dans le module inspect)

isfunction() (dans le module inspect)

isgenerator() (dans le module inspect)

isgeneratorfunction() (dans le module inspect)

isgetsetdescriptor() (dans le module inspect)

isgraph() (dans le module curses.ascii)

isidentifier() (méthode str)

isinf() (dans le module cmath)

(dans le module math)

isinstance (2to3 fixer)

isinstance() (fonction de base)

iskeyword() (dans le module keyword)

isleap() (dans le module calendar)

islice() (dans le module itertools)

islink() (dans le module os.path)

islnk() (méthode tarfile.TarInfo)

islower() (dans le module curses.ascii)

(méthode bytearray)

(méthode bytes)

(méthode str)

ismemberdescriptor() (dans le module inspect)

ismeta() (dans le module curses.ascii)

ismethod() (dans le module inspect)

ismethoddescriptor() (dans le module inspect)

ismodule() (dans le module inspect)

ismount() (dans le module os.path)

isnan() (dans le module cmath)

(dans le module math)

ISNONTERMINAL() (dans le module token)

isnumeric() (méthode str)

isocalendar() (méthode datetime.date)

(méthode datetime.datetime)

isoformat() (méthode datetime.date)

(méthode datetime.datetime)

(méthode datetime.time)

isolation_level (attribut sqlite3.Connection)

isoweekday() (méthode datetime.date)

(méthode datetime.datetime)

isprint() (dans le module curses.ascii)

isprintable() (méthode str)

ispunct() (dans le module curses.ascii)

isreadable() (dans le module pprint)

(méthode pprint.PrettyPrinter)

isrecursive() (dans le module pprint)

(méthode pprint.PrettyPrinter)

isreg() (méthode tarfile.TarInfo)

isReservedKey() (méthode http.cookies.Morsel)

isroutine() (dans le module inspect)

isSameNode() (méthode xml.dom.Node)

isspace() (dans le module curses.ascii)

(méthode bytearray)

(méthode bytes)

(méthode str)

isstdin() (dans le module fileinput)

issubclass() (fonction de base)

issubset() (méthode frozenset)

issuite() (dans le module parser)

(méthode parser.ST)

issuperset() (méthode frozenset)

issym() (méthode tarfile.TarInfo)

ISTERMINAL() (dans le module token)

istitle() (méthode bytearray)

(méthode bytes)

(méthode str)

istraceback() (dans le module inspect)

isub() (dans le module operator)

isupper() (dans le module curses.ascii)

(méthode bytearray)

(méthode bytes)

(méthode str)

isvisible() (dans le module turtle)

isxdigit() (dans le module curses.ascii)

item

sequence

string

item selection

item() (méthode tkinter.ttk.Treeview)

(méthode xml.dom.NamedNodeMap)

(méthode xml.dom.NodeList)

itemgetter() (dans le module operator)

items() (méthode configparser.ConfigParser)

(méthode dict)

(méthode email.message.EmailMessage)

(méthode email.message.Message)

(méthode mailbox.Mailbox)

(méthode types.MappingProxyType)

(méthode xml.etree.ElementTree.Element)

itemsize (attribut array.array)

(attribut memoryview)

ItemsView (classe dans collections.abc)

(classe dans typing)

iter() (fonction de base)

(méthode xml.etree.ElementTree.Element)

(méthode xml.etree.ElementTree.ElementTree)

iter_attachments() (méthode email.message.EmailMessage)

iter_child_nodes() (dans le module ast)

iter_fields() (dans le module ast)

iter_importers() (dans le module pkgutil)

iter_modules() (dans le module pkgutil)

iter_parts() (méthode email.message.EmailMessage)

iter_unpack() (dans le module struct)

(méthode struct.Struct)

iterable

unpacking

Iterable (classe dans collections.abc)

(classe dans typing)

Iterator (classe dans collections.abc)

(classe dans typing)

iterator protocol

iterdecode() (dans le module codecs)

iterdir() (méthode pathlib.Path)

iterdump() (méthode sqlite3.Connection)

iterencode() (dans le module codecs)

(méthode json.JSONEncoder)

iterfind() (méthode xml.etree.ElementTree.Element)

(méthode xml.etree.ElementTree.ElementTree)

iteritems() (méthode mailbox.Mailbox)

iterkeys() (méthode mailbox.Mailbox)

itermonthdates() (méthode calendar.Calendar)

itermonthdays() (méthode calendar.Calendar)

itermonthdays2() (méthode calendar.Calendar)

iterparse() (dans le module xml.etree.ElementTree)

itertext() (méthode xml.etree.ElementTree.Element)

itertools (2to3 fixer)

(module)

itertools_imports (2to3 fixer)

itervalues() (méthode mailbox.Mailbox)

iterweekdays() (méthode calendar.Calendar)

itérable

itérable asynchrone

itérateur

itérateur asynchrone

itérateur de générateur

itérateur de générateur asynchrone

ITIMER_PROF (dans le module signal)

ITIMER_REAL (dans le module signal)

ITIMER_VIRTUAL (dans le module signal)

ItimerError

itruediv() (dans le module operator)

ixor() (dans le module operator)

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Index – J

j

in numeric literal

Jansen, Jack

Java

language

java_ver() (dans le module platform)

join() (dans le module os.path)

(méthode asyncio.Queue)

(méthode bytearray)

(méthode bytes)

(méthode multiprocessing.JoinableQueue)

(méthode multiprocessing.pool.Pool)

(méthode multiprocessing.Process)

(méthode queue.Queue)

(méthode str)

(méthode threading.Thread)

join_thread() (méthode multiprocessing.Queue)

JoinableQueue (classe dans multiprocessing)

joinpath() (méthode pathlib.PurePath)

js_output() (méthode http.cookies.BaseCookie)

(méthode http.cookies.Morsel)

json

module

json (module)

json.tool (module)

json.tool command line option

--help

--sort-keys

-h

infile

outfile

JSONDecodeError

JSONDecoder (classe dans json)

JSONEncoder (classe dans json)

jump (pdb command)

JUMP_ABSOLUTE (opcode)

JUMP_FORWARD (opcode)

JUMP_IF_FALSE_OR_POP (opcode)

JUMP_IF_TRUE_OR_POP (opcode)

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Index – K

kbhit() (dans le module msvcrt)

KDEDIR

kevent() (dans le module select)

key

(attribut http.cookies.Morsel)

key/datum pair

KEY_ALL_ACCESS (dans le module winreg)

KEY_CREATE_LINK (dans le module winreg)

KEY_CREATE_SUB_KEY (dans le module winreg)

KEY_ENUMERATE_SUB_KEYS (dans le module winreg)

KEY_EXECUTE (dans le module winreg)

KEY_NOTIFY (dans le module winreg)

KEY_QUERY_VALUE (dans le module winreg)

KEY_READ (dans le module winreg)

KEY_SET_VALUE (dans le module winreg)

KEY_WOW64_32KEY (dans le module winreg)

KEY_WOW64_64KEY (dans le module winreg)

KEY_WRITE (dans le module winreg)

KeyboardInterrupt

(built-in exception), [1]

KeyError

keyname() (dans le module curses)

keypad() (méthode curses.window)

keyrefs() (méthode weakref.WeakKeyDictionary)

keys() (méthode dict)

(méthode email.message.EmailMessage)

(méthode email.message.Message)

(méthode mailbox.Mailbox)

(méthode sqlite3.Row)

(méthode types.MappingProxyType)

(méthode xml.etree.ElementTree.Element)

KeysView (classe dans collections.abc)

(classe dans typing)

keyword

(module)

keywords (attribut functools.partial)

kill() (dans le module os)

(méthode asyncio.asyncio.subprocess.Process)

(méthode asyncio.BaseSubprocessTransport)

(méthode subprocess.Popen)

killchar() (dans le module curses)

killpg() (dans le module os)

kind (attribut inspect.Parameter)

knownfiles (dans le module mimetypes)

kqueue() (dans le module select)

KqueueSelector (classe dans selectors)

kwargs (attribut inspect.BoundArguments)

kwlist (dans le module keyword)

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Index – L

L (dans le module re)

LabelEntry (classe dans tkinter.tix)

LabelFrame (classe dans tkinter.tix)

lambda

expression, [1]

form

LambdaType (dans le module types)

LANG, [1], [2], [3], [4]

LANGUAGE, [1]

language

C, [1], [2], [3], [4], [5]

Java

large files

LargeZipFile

last() (méthode nntplib.NNTP)

last_accepted (attribut multiprocessing.connection.Listener)

last_traceback (dans le module sys)

(in module sys)

last_type (dans le module sys)

last_value (dans le module sys)

lastChild (attribut xml.dom.Node)

lastcmd (attribut cmd.Cmd)

lastgroup (attribut re.match)

lastindex (attribut re.match)

lastResort (dans le module logging)

lastrowid (attribut sqlite3.Cursor)

layout() (méthode tkinter.ttk.Style)

lazycache() (dans le module linecache)

LazyLoader (classe dans importlib.util)

LBRACE (dans le module token)

LBYL

LC_ALL, [1]

(dans le module locale)

LC_COLLATE (dans le module locale)

LC_CTYPE (dans le module locale)

LC_MESSAGES, [1]

(dans le module locale)

LC_MONETARY (dans le module locale)

LC_NUMERIC (dans le module locale)

LC_TIME (dans le module locale)

lchflags() (dans le module os)

lchmod() (dans le module os)

(méthode pathlib.Path)

lchown() (dans le module os)

LDCXXSHARED

ldexp() (dans le module math)

LDFLAGS

ldgettext() (dans le module gettext)

ldngettext() (dans le module gettext)

Le zen de Python

le() (dans le module operator)

leading whitespace

leapdays() (dans le module calendar)

leaveok() (méthode curses.window)

left (attribut filecmp.dircmp)

left() (dans le module turtle)

left_list (attribut filecmp.dircmp)

left_only (attribut filecmp.dircmp)

LEFTSHIFT (dans le module token)

LEFTSHIFTEQUAL (dans le module token)

len

fonction de base, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11]

len() (fonction de base)

length (attribut xml.dom.NamedNodeMap)

(attribut xml.dom.NodeList)

length_hint() (dans le module operator)

LESS (dans le module token)

LESSEQUAL (dans le module token)

lexical analysis

lexical definitions

lexists() (dans le module os.path)

lgamma() (dans le module math)

lgettext() (dans le module gettext)

(méthode gettext.GNUTranslations)

(méthode gettext.NullTranslations)

lib2to3 (module)

libc_ver() (dans le module platform)

library (attribut ssl.SSLError)

(dans le module dbm.ndbm)

library_dir_option() (méthode distutils.ccompiler.CCompiler)

library_filename() (méthode distutils.ccompiler.CCompiler)

library_option() (méthode distutils.ccompiler.CCompiler)

LibraryLoader (classe dans ctypes)

license (variable de base)

LifoQueue (classe dans asyncio)

(classe dans queue)

light-weight processes

limit_denominator() (méthode fractions.Fraction)

LimitOverrunError

lin2adpcm() (dans le module audioop)

lin2alaw() (dans le module audioop)

lin2lin() (dans le module audioop)

lin2ulaw() (dans le module audioop)

line (fonction C)

line continuation

line joining, [1]

line structure

line() (méthode msilib.Dialog)

line-buffered I/O

line_buffering (attribut io.TextIOWrapper)

line_num (attribut csv.csvreader)

linecache (module)

lineno (attribut ast.AST)

(attribut doctest.DocTest)

(attribut doctest.Example)

(attribut json.JSONDecodeError)

(attribut pyclbr.Class)

(attribut pyclbr.Function)

(attribut re.error)

(attribut shlex.shlex)

(attribut traceback.TracebackException)

(attribut tracemalloc.Filter)

(attribut tracemalloc.Frame)

(attribut xml.parsers.expat.ExpatError)

lineno() (dans le module fileinput)

LINES, [1], [2], [3], [4]

lines (attribut os.terminal_size)

linesep (attribut email.policy.Policy)

(dans le module os)

lineterminator (attribut csv.Dialect)

LineTooLong

link() (dans le module os)

(méthode distutils.ccompiler.CCompiler)

link_executable() (méthode distutils.ccompiler.CCompiler)

link_shared_lib() (méthode distutils.ccompiler.CCompiler)

link_shared_object() (méthode distutils.ccompiler.CCompiler)

linkname (attribut tarfile.TarInfo)

linux_distribution() (dans le module platform)

list

assignment, target

comprehensions

deletion target

display

empty

expression, [1], [2]

objet, [1], [2], [3], [4], [5], [6], [7], [8]

target, [1], [2]

type, operations on

List (classe dans typing)

list (classe de base)

(pdb command)

list() (méthode imaplib.IMAP4)

(méthode multiprocessing.managers.SyncManager)

(méthode nntplib.NNTP)

(méthode poplib.POP3)

(méthode tarfile.TarFile)

LIST_APPEND (opcode)

list_dialects() (dans le module csv)

list_folders() (méthode mailbox.Maildir)

(méthode mailbox.MH)

listdir() (dans le module os)

liste en compréhension (ou liste en intension)

listen() (dans le module logging.config)

(dans le module turtle)

(méthode asyncore.dispatcher)

(méthode socket.socket)

Listener (classe dans multiprocessing.connection)

listMethods() (méthode xmlrpc.client.ServerProxy.system)

ListNoteBook (classe dans tkinter.tix)

listxattr() (dans le module os)

literal, [1]

literal_eval() (dans le module ast)

literals

binary

complex number

floating point

hexadecimal

integer

numeric

octal

LittleEndianStructure (classe dans ctypes)

ljust() (méthode bytearray)

(méthode bytes)

(méthode str)

LK_LOCK (dans le module msvcrt)

LK_NBLCK (dans le module msvcrt)

LK_NBRLCK (dans le module msvcrt)

LK_RLCK (dans le module msvcrt)

LK_UNLCK (dans le module msvcrt)

ll (pdb command)

LMTP (classe dans smtplib)

ln() (méthode decimal.Context)

(méthode decimal.Decimal)

LNAME

lngettext() (dans le module gettext)

(méthode gettext.GNUTranslations)

(méthode gettext.NullTranslations)

load() (dans le module json)

(dans le module marshal)

(dans le module pickle)

(dans le module plistlib)

(méthode de la classe tracemalloc.Snapshot)

(méthode http.cookiejar.FileCookieJar)

(méthode http.cookies.BaseCookie)

(méthode pickle.Unpickler)

LOAD_ATTR (opcode)

LOAD_BUILD_CLASS (opcode)

load_cert_chain() (méthode ssl.SSLContext)

LOAD_CLASSDEREF (opcode)

LOAD_CLOSURE (opcode)

LOAD_CONST (opcode)

load_default_certs() (méthode ssl.SSLContext)

LOAD_DEREF (opcode)

load_dh_params() (méthode ssl.SSLContext)

load_extension() (méthode sqlite3.Connection)

LOAD_FAST (opcode)

LOAD_GLOBAL (opcode)

load_module() (dans le module imp)

(méthode importlib.abc.FileLoader)

(méthode importlib.abc.InspectLoader)

(méthode importlib.abc.Loader)

(méthode importlib.abc.SourceLoader)

(méthode importlib.machinery.SourceFileLoader)

(méthode importlib.machinery.SourcelessFileLoader)

(méthode zipimport.zipimporter)

LOAD_NAME (opcode)

load_package_tests() (dans le module test.support)

load_verify_locations() (méthode ssl.SSLContext)

loader

(attribut importlib.machinery.ModuleSpec)

Loader (classe dans importlib.abc)

loader_state (attribut importlib.machinery.ModuleSpec)

LoadError

LoadKey() (dans le module winreg)

LoadLibrary() (méthode ctypes.LibraryLoader)

loads() (dans le module json)

(dans le module marshal)

(dans le module pickle)

(dans le module plistlib)

(dans le module xmlrpc.client)

loadTestsFromModule() (méthode unittest.TestLoader)

loadTestsFromName() (méthode unittest.TestLoader)

loadTestsFromNames() (méthode unittest.TestLoader)

loadTestsFromTestCase() (méthode unittest.TestLoader)

local (classe dans threading)

localcontext() (dans le module decimal)

LOCALE (dans le module re)

locale (module)

localeconv() (dans le module locale)

LocaleHTMLCalendar (classe dans calendar)

LocaleTextCalendar (classe dans calendar)

localName (attribut xml.dom.Attr)

(attribut xml.dom.Node)

locals() (fonction de base)

localtime() (dans le module email.utils)

(dans le module time)

Locator (classe dans xml.sax.xmlreader)

Lock (classe dans asyncio)

(classe dans multiprocessing)

(classe dans threading)

lock() (méthode mailbox.Babyl)

(méthode mailbox.Mailbox)

(méthode mailbox.Maildir)

(méthode mailbox.mbox)

(méthode mailbox.MH)

(méthode mailbox.MMDF)

Lock() (méthode multiprocessing.managers.SyncManager)

lock, interpreter

lock_held() (dans le module imp)

locked() (méthode _thread.lock)

(méthode asyncio.Condition)

(méthode asyncio.Lock)

(méthode asyncio.Semaphore)

lockf() (dans le module fcntl)

(dans le module os)

locking() (dans le module msvcrt)

LockType (dans le module _thread)

log() (dans le module cmath)

(dans le module logging)

(dans le module math)

(méthode logging.Logger)

log10() (dans le module cmath)

(dans le module math)

(méthode decimal.Context)

(méthode decimal.Decimal)

log1p() (dans le module math)

log2() (dans le module math)

log_date_time_string() (méthode http.server.BaseHTTPRequestHandler)

log_error() (méthode http.server.BaseHTTPRequestHandler)

log_exception() (méthode wsgiref.handlers.BaseHandler)

log_message() (méthode http.server.BaseHTTPRequestHandler)

log_request() (méthode http.server.BaseHTTPRequestHandler)

log_to_stderr() (dans le module multiprocessing)

logb() (méthode decimal.Context)

(méthode decimal.Decimal)

Logger (classe dans logging)

LoggerAdapter (classe dans logging)

logging

Errors

logging (module)

logging.config (module)

logging.handlers (module)

logical line

logical_and() (méthode decimal.Context)

(méthode decimal.Decimal)

logical_invert() (méthode decimal.Context)

(méthode decimal.Decimal)

logical_or() (méthode decimal.Context)

(méthode decimal.Decimal)

logical_xor() (méthode decimal.Context)

(méthode decimal.Decimal)

login() (méthode ftplib.FTP)

(méthode imaplib.IMAP4)

(méthode nntplib.NNTP)

(méthode smtplib.SMTP)

login_cram_md5() (méthode imaplib.IMAP4)

LOGNAME, [1]

lognormvariate() (dans le module random)

logout() (méthode imaplib.IMAP4)

LogRecord (classe dans logging)

long (2to3 fixer)

long integer

objet

LONG_MAX

longMessage (attribut unittest.TestCase)

longname() (dans le module curses)

lookup() (dans le module codecs)

(dans le module unicodedata)

(méthode symtable.SymbolTable)

(méthode tkinter.ttk.Style)

lookup_error() (dans le module codecs)

LookupError

loop

over mutable sequence

statement, [1], [2], [3]

loop control

target

loop() (dans le module asyncore)

lower() (méthode bytearray)

(méthode bytes)

(méthode str)

LPAR (dans le module token)

lru_cache() (dans le module functools)

lseek() (dans le module os)

lshift() (dans le module operator)

LSQB (dans le module token)

lstat() (dans le module os)

(méthode pathlib.Path)

lstrip() (méthode bytearray)

(méthode bytes)

(méthode str)

lsub() (méthode imaplib.IMAP4)

lt() (dans le module operator)

(dans le module turtle)

LWPCookieJar (classe dans http.cookiejar)

lzma (module)

LZMACompressor (classe dans lzma)

LZMADecompressor (classe dans lzma)

LZMAError

LZMAFile (classe dans lzma)

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Index – M

M (dans le module re)

mac_ver() (dans le module platform)

machine virtuelle

machine() (dans le module platform)

macpath (module)

macros (attribut netrc.netrc)

MAGIC_NUMBER (dans le module importlib.util)

MagicMock (classe dans unittest.mock)

Mailbox (classe dans mailbox)

mailbox (module)

mailcap (module)

Maildir (classe dans mailbox)

MaildirMessage (classe dans mailbox)

mailfrom (attribut smtpd.SMTPChannel)

MailmanProxy (classe dans smtpd)

main(), [1], [2]

(dans le module py_compile)

(dans le module site)

(dans le module unittest)

main_thread() (dans le module threading)

mainloop() (dans le module turtle)

maintype (attribut email.headerregistry.ContentTypeHeader)

major (attribut email.headerregistry.MIMEVersionHeader)

major() (dans le module os)

make_alternative() (méthode email.message.EmailMessage)

make_archive() (dans le module distutils.archive_util)

(dans le module shutil)

make_bad_fd() (dans le module test.support)

make_cookies() (méthode http.cookiejar.CookieJar)

make_file() (méthode difflib.HtmlDiff)

MAKE_FUNCTION (opcode)

make_header() (dans le module email.header)

make_mixed() (méthode email.message.EmailMessage)

make_msgid() (dans le module email.utils)

make_parser() (dans le module xml.sax)

make_related() (méthode email.message.EmailMessage)

make_server() (dans le module wsgiref.simple_server)

make_table() (méthode difflib.HtmlDiff)

make_tarball() (dans le module distutils.archive_util)

make_zipfile() (dans le module distutils.archive_util)

makedev() (dans le module os)

makedirs() (dans le module os)

makeelement() (méthode xml.etree.ElementTree.Element)

makefile() (méthode socket.socket)

(socket method)

makeLogRecord() (dans le module logging)

makePickle() (méthode logging.handlers.SocketHandler)

makeRecord() (méthode logging.Logger)

makeSocket() (méthode logging.handlers.DatagramHandler)

(méthode logging.handlers.SocketHandler)

maketrans() (méthode statique bytearray)

(méthode statique bytes)

(méthode statique str)

malloc()

mangle_from_ (attribut email.policy.Compat32)

(attribut email.policy.Policy)

mangling

name, [1]

map (2to3 fixer)

map() (fonction de base)

(méthode concurrent.futures.Executor)

(méthode multiprocessing.pool.Pool)

(méthode tkinter.ttk.Style)

MAP_ADD (opcode)

map_async() (méthode multiprocessing.pool.Pool)

map_table_b2() (dans le module stringprep)

map_table_b3() (dans le module stringprep)

map_to_type() (méthode email.headerregistry.HeaderRegistry)

mapLogRecord() (méthode logging.handlers.HTTPHandler)

mapping

objet, [1], [2], [3], [4], [5]

types, operations on

Mapping (classe dans collections.abc)

(classe dans typing)

mapping() (méthode msilib.Control)

MappingProxyType (classe dans types)

MappingView (classe dans collections.abc)

(classe dans typing)

mapPriority() (méthode logging.handlers.SysLogHandler)

maps (attribut collections.ChainMap)

maps() (dans le module nis)

marshal (module)

marshalling

objects

masking

operations

Match (classe dans typing)

match() (dans le module nis)

(dans le module re)

(méthode pathlib.PurePath)

(méthode re.regex)

match_hostname() (dans le module ssl)

math

module, [1]

math (module)

matmul() (dans le module operator)

matrix multiplication

max

fonction de base

max (attribut datetime.date)

(attribut datetime.datetime)

(attribut datetime.time)

(attribut datetime.timedelta)

max() (dans le module audioop)

(fonction de base)

(méthode decimal.Context)

(méthode decimal.Decimal)

max_count (attribut email.headerregistry.BaseHeader)

MAX_EMAX (dans le module decimal)

MAX_INTERPOLATION_DEPTH (dans le module configparser)

max_line_length (attribut email.policy.Policy)

max_lines (attribut textwrap.TextWrapper)

max_mag() (méthode decimal.Context)

(méthode decimal.Decimal)

MAX_PREC (dans le module decimal)

max_prefixlen (attribut ipaddress.IPv4Address)

(attribut ipaddress.IPv4Network)

(attribut ipaddress.IPv6Address)

(attribut ipaddress.IPv6Network)

maxarray (attribut reprlib.Repr)

maxdeque (attribut reprlib.Repr)

maxdict (attribut reprlib.Repr)

maxDiff (attribut unittest.TestCase)

maxfrozenset (attribut reprlib.Repr)

maxlen (attribut collections.deque)

maxlevel (attribut reprlib.Repr)

maxlist (attribut reprlib.Repr)

maxlong (attribut reprlib.Repr)

maxother (attribut reprlib.Repr)

maxpp() (dans le module audioop)

maxset (attribut reprlib.Repr)

maxsize (attribut asyncio.Queue)

(dans le module sys)

maxstring (attribut reprlib.Repr)

maxtuple (attribut reprlib.Repr)

maxunicode (dans le module sys)

MAXYEAR (dans le module datetime)

MB_ICONASTERISK (dans le module winsound)

MB_ICONEXCLAMATION (dans le module winsound)

MB_ICONHAND (dans le module winsound)

MB_ICONQUESTION (dans le module winsound)

MB_OK (dans le module winsound)

mbox (classe dans mailbox)

mboxMessage (classe dans mailbox)

mean() (dans le module statistics)

median() (dans le module statistics)

median_grouped() (dans le module statistics)

median_high() (dans le module statistics)

median_low() (dans le module statistics)

MemberDescriptorType (dans le module types)

membership

test

memmove() (dans le module ctypes)

MemoryBIO (classe dans ssl)

MemoryError

MemoryHandler (classe dans logging.handlers)

memoryview

objet, [1]

memoryview (classe de base)

memset() (dans le module ctypes)

merge() (dans le module heapq)

Message (classe dans email.message)

(classe dans mailbox)

message digest, MD5

message_factory (attribut email.policy.Policy)

message_from_binary_file() (dans le module email)

message_from_bytes() (dans le module email)

message_from_file() (dans le module email)

message_from_string() (dans le module email)

MessageBeep() (dans le module winsound)

MessageClass (attribut http.server.BaseHTTPRequestHandler)

MessageError

MessageParseError

messages (dans le module xml.parsers.expat.errors)

meta

hooks

meta hooks

meta() (dans le module curses)

meta_path (dans le module sys)

metaclass

(2to3 fixer)

metaclass hint

MetaPathFinder (classe dans importlib.abc)

metavar (attribut optparse.Option)

MetavarTypeHelpFormatter (classe dans argparse)

Meter (classe dans tkinter.tix)

METH_CLASS (variable de base)

METH_COEXIST (variable de base)

METH_KEYWORDS (variable de base)

METH_NOARGS (variable de base)

METH_O (variable de base)

METH_STATIC (variable de base)

METH_VARARGS (variable de base)

method

built-in

call

objet, [1], [2], [3], [4], [5]

user-defined

method (attribut urllib.request.Request)

method_calls (attribut unittest.mock.Mock)

METHOD_CRYPT (dans le module crypt)

METHOD_MD5 (dans le module crypt)

METHOD_SHA256 (dans le module crypt)

METHOD_SHA512 (dans le module crypt)

methodattrs (2to3 fixer)

methodcaller() (dans le module operator)

methodHelp() (méthode xmlrpc.client.ServerProxy.system)

methods

bytearray

bytes

string

methods (attribut pyclbr.Class)

(dans le module crypt)

methodSignature() (méthode xmlrpc.client.ServerProxy.system)

MethodType (dans le module types)

(in module types), [1]

métaclasse

méthode

méthode spéciale

MH (classe dans mailbox)

MHMessage (classe dans mailbox)

microsecond (attribut datetime.datetime)

(attribut datetime.time)

MIME

base64 encoding

content type

headers, [1]

quoted-printable encoding

MIMEApplication (classe dans email.mime.application)

MIMEAudio (classe dans email.mime.audio)

MIMEBase (classe dans email.mime.base)

MIMEImage (classe dans email.mime.image)

MIMEMessage (classe dans email.mime.message)

MIMEMultipart (classe dans email.mime.multipart)

MIMENonMultipart (classe dans email.mime.nonmultipart)

MIMEPart (classe dans email.message)

MIMEText (classe dans email.mime.text)

MimeTypes (classe dans mimetypes)

mimetypes (module)

MIMEVersionHeader (classe dans email.headerregistry)

min

fonction de base

min (attribut datetime.date)

(attribut datetime.datetime)

(attribut datetime.time)

(attribut datetime.timedelta)

min() (fonction de base)

(méthode decimal.Context)

(méthode decimal.Decimal)

MIN_EMIN (dans le module decimal)

MIN_ETINY (dans le module decimal)

min_mag() (méthode decimal.Context)

(méthode decimal.Decimal)

MINEQUAL (dans le module token)

minmax() (dans le module audioop)

minor (attribut email.headerregistry.MIMEVersionHeader)

minor() (dans le module os)

minus

MINUS (dans le module token)

minus() (méthode decimal.Context)

minute (attribut datetime.datetime)

(attribut datetime.time)

MINYEAR (dans le module datetime)

mirrored() (dans le module unicodedata)

misc_header (attribut cmd.Cmd)

MissingSectionHeaderError

MIXERDEV

mkd() (méthode ftplib.FTP)

mkdir() (dans le module os)

(méthode pathlib.Path)

mkdtemp() (dans le module tempfile)

mkfifo() (dans le module os)

mknod() (dans le module os)

mkpath() (dans le module distutils.dir_util)

(méthode distutils.ccompiler.CCompiler)

mksalt() (dans le module crypt)

mkstemp() (dans le module tempfile)

mktemp() (dans le module tempfile)

mktime() (dans le module time)

mktime_tz() (dans le module email.utils)

mlsd() (méthode ftplib.FTP)

mmap (classe dans mmap)

(module)

MMDF (classe dans mailbox)

MMDFMessage (classe dans mailbox)

Mock (classe dans unittest.mock)

mock_add_spec() (méthode unittest.mock.Mock)

mock_calls (attribut unittest.mock.Mock)

mock_open() (dans le module unittest.mock)

mod() (dans le module operator)

mode (attribut io.FileIO)

(attribut ossaudiodev.oss_audio_device)

(attribut tarfile.TarInfo)

mode() (dans le module statistics)

(dans le module turtle)

modes

file

modf() (dans le module math)

modified() (méthode urllib.robotparser.RobotFileParser)

Modify() (méthode msilib.View)

modify() (méthode select.devpoll)

(méthode select.epoll)

(méthode select.poll)

(méthode selectors.BaseSelector)

module

__main__, [1], [2], [3], [4], [5], [6], [7]

_locale

_thread

array, [1]

base64

bdb

binhex

builtins, [1], [2], [3], [4]

cmd

copy

crypt

dbm.gnu, [1]

dbm.ndbm, [1]

errno

extension

glob

imp

importing

io

json

math, [1]

namespace

objet, [1], [2]

os

pickle, [1], [2], [3]

pty

pwd

pyexpat

re, [1]

search path, [1], [2], [3], [4], [5], [6], [7]

shelve

signal, [1]

sitecustomize

socket

stat

string

struct

sys, [1], [2], [3], [4], [5], [6]

types

urllib.request

usercustomize

uu

module (attribut pyclbr.Class)

(attribut pyclbr.Function)

module d'extension

module spec

module_for_loader() (dans le module importlib.util)

module_from_spec() (dans le module importlib.util)

module_repr() (méthode importlib.abc.Loader)

ModuleFinder (classe dans modulefinder)

modulefinder (module)

ModuleInfo (classe dans pkgutil)

ModuleNotFoundError

modules (attribut modulefinder.ModuleFinder)

(dans le module sys)

(in module sys), [1]

ModuleSpec (classe dans importlib.machinery)

ModuleType (classe dans types)

(in module types)

modulo

monotonic() (dans le module time)

month (attribut datetime.date)

(attribut datetime.datetime)

month() (dans le module calendar)

month_abbr (dans le module calendar)

month_name (dans le module calendar)

monthcalendar() (dans le module calendar)

monthdatescalendar() (méthode calendar.Calendar)

monthdays2calendar() (méthode calendar.Calendar)

monthdayscalendar() (méthode calendar.Calendar)

monthrange() (dans le module calendar)

Morsel (classe dans http.cookies)

most_common() (méthode collections.Counter)

mot-clé

as, [1], [2]

async

await, [1], [2]

elif

else, [1], [2], [3], [4], [5], [6], [7]

except

finally, [1], [2], [3], [4]

from, [1]

in, [1]

yield

mouseinterval() (dans le module curses)

mousemask() (dans le module curses)

move() (dans le module shutil)

(méthode curses.panel.Panel)

(méthode curses.window)

(méthode mmap.mmap)

(méthode tkinter.ttk.Treeview)

move_file() (dans le module distutils.file_util)

(méthode distutils.ccompiler.CCompiler)

move_to_end() (méthode collections.OrderedDict)

MozillaCookieJar (classe dans http.cookiejar)

MRO

mro() (méthode class)

msg (attribut http.client.HTTPResponse)

(attribut json.JSONDecodeError)

(attribut re.error)

(attribut traceback.TracebackException)

msg() (méthode telnetlib.Telnet)

msi

msilib (module)

msvcrt (module)

mt_interact() (méthode telnetlib.Telnet)

mtime (attribut gzip.GzipFile)

(attribut tarfile.TarInfo)

mtime() (méthode urllib.robotparser.RobotFileParser)

muable

mul() (dans le module audioop)

(dans le module operator)

MultiCall (classe dans xmlrpc.client)

MULTILINE (dans le module re)

MultipartConversionError

multiplication

multiply() (méthode decimal.Context)

multiprocessing (module)

multiprocessing.connection (module)

multiprocessing.dummy (module)

multiprocessing.Manager() (dans le module multiprocessing.sharedctypes)

multiprocessing.managers (module)

multiprocessing.pool (module)

multiprocessing.sharedctypes (module)

mutable

objet, [1], [2]

sequence types

mutable object

mutable sequence

loop over

objet

MutableMapping (classe dans collections.abc)

(classe dans typing)

MutableSequence (classe dans collections.abc)

(classe dans typing)

MutableSet (classe dans collections.abc)

(classe dans typing)

mvderwin() (méthode curses.window)

mvwin() (méthode curses.window)

myrights() (méthode imaplib.IMAP4)

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Index – N

n-uplet nommé

N_TOKENS (dans le module token)

n_waiting (attribut threading.Barrier)

name, [1], [2]

binding, [1], [2], [3], [4], [5], [6]

binding, global

class

function, [1]

mangling, [1]

rebinding

unbinding

name (attribut codecs.CodecInfo)

(attribut doctest.DocTest)

(attribut email.headerregistry.BaseHeader)

(attribut hashlib.hash)

(attribut hmac.HMAC)

(attribut http.cookiejar.Cookie)

(attribut importlib.abc.FileLoader)

(attribut importlib.machinery.ExtensionFileLoader)

(attribut importlib.machinery.ModuleSpec)

(attribut importlib.machinery.SourceFileLoader)

(attribut importlib.machinery.SourcelessFileLoader)

(attribut inspect.Parameter)

(attribut io.FileIO)

(attribut multiprocessing.Process)

(attribut os.DirEntry)

(attribut ossaudiodev.oss_audio_device)

(attribut pyclbr.Class)

(attribut pyclbr.Function)

(attribut tarfile.TarInfo)

(attribut threading.Thread)

(attribut xml.dom.Attr)

(attribut xml.dom.DocumentType)

(dans le module os)

NAME (dans le module token)

name() (dans le module unicodedata)

name2codepoint (dans le module html.entities)

NamedTemporaryFile() (dans le module tempfile)

NamedTuple (classe dans typing)

namedtuple() (dans le module collections)

NameError

exception

NameError (built-in exception)

namelist() (méthode zipfile.ZipFile)

nameprep() (dans le module encodings.idna)

namer (attribut logging.handlers.BaseRotatingHandler)

namereplace_errors() (dans le module codecs)

names

private

namespace

global

module

package

Namespace (classe dans argparse)

(classe dans multiprocessing.managers)

namespace() (méthode imaplib.IMAP4)

Namespace() (méthode multiprocessing.managers.SyncManager)

NAMESPACE_DNS (dans le module uuid)

NAMESPACE_OID (dans le module uuid)

NAMESPACE_URL (dans le module uuid)

NAMESPACE_X500 (dans le module uuid)

NamespaceErr

namespaceURI (attribut xml.dom.Node)

NaN

nan (dans le module cmath)

(dans le module math)

nanj (dans le module cmath)

NannyNag

napms() (dans le module curses)

nargs (attribut optparse.Option)

nbytes (attribut memoryview)

ndiff() (dans le module difflib)

ndim (attribut memoryview)

ne (2to3 fixer)

ne() (dans le module operator)

needs_input (attribut bz2.BZ2Decompressor)

(attribut lzma.LZMADecompressor)

neg() (dans le module operator)

negation

netmask (attribut ipaddress.IPv4Network)

(attribut ipaddress.IPv6Network)

NetmaskValueError

netrc (classe dans netrc)

(module)

NetrcParseError

netscape (attribut http.cookiejar.CookiePolicy)

network (attribut ipaddress.IPv4Interface)

(attribut ipaddress.IPv6Interface)

Network News Transfer Protocol

network_address (attribut ipaddress.IPv4Network)

(attribut ipaddress.IPv6Network)

new() (dans le module hashlib)

(dans le module hmac)

new_alignment() (méthode formatter.writer)

new_child() (méthode collections.ChainMap)

new_class() (dans le module types)

new_compiler() (dans le module distutils.ccompiler)

new_event_loop() (dans le module asyncio)

(méthode asyncio.AbstractEventLoopPolicy)

new_font() (méthode formatter.writer)

new_margin() (méthode formatter.writer)

new_module() (dans le module imp)

new_panel() (dans le module curses.panel)

new_spacing() (méthode formatter.writer)

new_styles() (méthode formatter.writer)

newer() (dans le module distutils.dep_util)

newer_group() (dans le module distutils.dep_util)

newer_pairwise() (dans le module distutils.dep_util)

newgroups() (méthode nntplib.NNTP)

NEWLINE (dans le module token)

NEWLINE token, [1]

newlines (attribut io.TextIOBase)

newnews() (méthode nntplib.NNTP)

newpad() (dans le module curses)

NewType() (dans le module typing)

newwin() (dans le module curses)

next (2to3 fixer)

(pdb command)

next() (fonction de base)

(méthode nntplib.NNTP)

(méthode tarfile.TarFile)

(méthode tkinter.ttk.Treeview)

next_minus() (méthode decimal.Context)

(méthode decimal.Decimal)

next_plus() (méthode decimal.Context)

(méthode decimal.Decimal)

next_toward() (méthode decimal.Context)

(méthode decimal.Decimal)

nextfile() (dans le module fileinput)

nextkey() (méthode dbm.gnu.gdbm)

nextSibling (attribut xml.dom.Node)

ngettext() (dans le module gettext)

(méthode gettext.GNUTranslations)

(méthode gettext.NullTranslations)

nice() (dans le module os)

nis (module)

NL (dans le module tokenize)

nl() (dans le module curses)

nl_langinfo() (dans le module locale)

nlargest() (dans le module heapq)

nlst() (méthode ftplib.FTP)

NNTP

protocol

NNTP (classe dans nntplib)

nntp_implementation (attribut nntplib.NNTP)

NNTP_SSL (classe dans nntplib)

nntp_version (attribut nntplib.NNTP)

NNTPDataError

NNTPError

nntplib (module)

NNTPPermanentError

NNTPProtocolError

NNTPReplyError

NNTPTemporaryError

no_proxy

no_type_check() (dans le module typing)

no_type_check_decorator() (dans le module typing)

nocbreak() (dans le module curses)

NoDataAllowedErr

node() (dans le module platform)

nodelay() (méthode curses.window)

nodeName (attribut xml.dom.Node)

NodeTransformer (classe dans ast)

nodeType (attribut xml.dom.Node)

nodeValue (attribut xml.dom.Node)

NodeVisitor (classe dans ast)

noecho() (dans le module curses)

NOEXPR (dans le module locale)

nom qualifié

nombre complexe

nombre de références

NoModificationAllowedErr

nonblock() (méthode ossaudiodev.oss_audio_device)

NonCallableMagicMock (classe dans unittest.mock)

NonCallableMock (classe dans unittest.mock)

None

objet, [1], [2]

None (Built-in object)

(variable de base)

nonl() (dans le module curses)

nonlocal

état

nonzero (2to3 fixer)

noop() (méthode imaplib.IMAP4)

(méthode poplib.POP3)

NoOptionError

NOP (opcode)

noqiflush() (dans le module curses)

noraw() (dans le module curses)

NoReturn (dans le module typing)

normalize() (dans le module locale)

(dans le module unicodedata)

(méthode decimal.Context)

(méthode decimal.Decimal)

(méthode xml.dom.Node)

NORMALIZE_WHITESPACE (dans le module doctest)

normalvariate() (dans le module random)

normcase() (dans le module os.path)

normpath() (dans le module os.path)

NoSectionError

NoSuchMailboxError

not

opérateur, [1]

not in

opérateur, [1], [2]

not_() (dans le module operator)

NotADirectoryError

notation

notationDecl() (méthode xml.sax.handler.DTDHandler)

NotationDeclHandler() (méthode xml.parsers.expat.xmlparser)

notations (attribut xml.dom.DocumentType)

NotConnected

NoteBook (classe dans tkinter.tix)

Notebook (classe dans tkinter.ttk)

NotEmptyError

NOTEQUAL (dans le module token)

NotFoundErr

notify() (méthode asyncio.Condition)

(méthode threading.Condition)

notify_all() (méthode asyncio.Condition)

(méthode threading.Condition)

notimeout() (méthode curses.window)

NotImplemented

objet

NotImplemented (variable de base)

NotImplementedError

NotStandaloneHandler() (méthode xml.parsers.expat.xmlparser)

NotSupportedErr

NotSupportedError

noutrefresh() (méthode curses.window)

nouvelle classe

now() (méthode de la classe datetime.datetime)

NSIG (dans le module signal)

nsmallest() (dans le module heapq)

NT_OFFSET (dans le module token)

NTEventLogHandler (classe dans logging.handlers)

ntohl() (dans le module socket)

ntohs() (dans le module socket)

ntransfercmd() (méthode ftplib.FTP)

null

operation, [1]

NullFormatter (classe dans formatter)

NullHandler (classe dans logging)

NullImporter (classe dans imp)

NullTranslations (classe dans gettext)

NullWriter (classe dans formatter)

num_addresses (attribut ipaddress.IPv4Network)

(attribut ipaddress.IPv6Network)

number

complex

floating point

Number (classe dans numbers)

NUMBER (dans le module token)

number_class() (méthode decimal.Context)

(méthode decimal.Decimal)

numbers (module)

numerator (attribut fractions.Fraction)

(attribut numbers.Rational)

numeric

conversions

literals

object

objet, [1], [2], [3]

types, operations on

numeric literal

numeric() (dans le module unicodedata)

Numerical Python

numinput() (dans le module turtle)

numliterals (2to3 fixer)

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Index – O

O_APPEND (dans le module os)

O_ASYNC (dans le module os)

O_BINARY (dans le module os)

O_CLOEXEC (dans le module os)

O_CREAT (dans le module os)

O_DIRECT (dans le module os)

O_DIRECTORY (dans le module os)

O_DSYNC (dans le module os)

O_EXCL (dans le module os)

O_EXLOCK (dans le module os)

O_NDELAY (dans le module os)

O_NOATIME (dans le module os)

O_NOCTTY (dans le module os)

O_NOFOLLOW (dans le module os)

O_NOINHERIT (dans le module os)

O_NONBLOCK (dans le module os)

O_PATH (dans le module os)

O_RANDOM (dans le module os)

O_RDONLY (dans le module os)

O_RDWR (dans le module os)

O_RSYNC (dans le module os)

O_SEQUENTIAL (dans le module os)

O_SHLOCK (dans le module os)

O_SHORT_LIVED (dans le module os)

O_SYNC (dans le module os)

O_TEMPORARY (dans le module os)

O_TEXT (dans le module os)

O_TMPFILE (dans le module os)

O_TRUNC (dans le module os)

O_WRONLY (dans le module os)

obj (attribut memoryview)

object

code, [1], [2], [3]

deallocation

finalization

immutable, [1]

numeric

object (attribut UnicodeError)

(classe de base)

object.__slots__ (variable de base)

object_filenames() (méthode distutils.ccompiler.CCompiler)

objects

comparing

flattening

marshalling

persistent

pickling

serializing

objet

asynchronous-generator

Boolean, [1]

built-in function, [1]

built-in method, [1]

bytearray, [1], [2], [3]

bytes, [1], [2]

callable, [1]

Capsule

class, [1], [2]

class instance, [1], [2]

complex

complex number, [1]

dictionary, [1], [2], [3], [4], [5], [6], [7]

Ellipsis

file, [1]

floating point, [1], [2]

frame

frozenset, [1]

function, [1], [2], [3], [4], [5]

generator, [1], [2]

immutable

immutable sequence

instance, [1], [2]

instancemethod

integer, [1], [2]

io.StringIO

list, [1], [2], [3], [4], [5], [6], [7], [8]

long integer

mapping, [1], [2], [3], [4], [5]

memoryview, [1]

method, [1], [2], [3], [4], [5]

module, [1], [2]

mutable, [1], [2]

mutable sequence

None, [1], [2]

NotImplemented

numeric, [1], [2], [3]

range

sequence, [1], [2], [3], [4], [5], [6], [7], [8]

set, [1], [2], [3]

set type

slice

socket

string, [1], [2]

traceback, [1], [2], [3], [4]

tuple, [1], [2], [3], [4], [5], [6]

type, [1], [2]

user-defined function, [1], [2]

user-defined method

objet fichier

objet fichier-compatible

objet octet-compatible

objet simili-chemin

obufcount() (méthode ossaudiodev.oss_audio_device)

obuffree() (méthode ossaudiodev.oss_audio_device)

oct() (fonction de base)

octal

literals

octal literal

octdigits (dans le module string)

offset (attribut traceback.TracebackException)

(attribut xml.parsers.expat.ExpatError)

OK (dans le module curses)

OleDLL (classe dans ctypes)

onclick() (dans le module turtle), [1]

ondrag() (dans le module turtle)

onecmd() (méthode cmd.Cmd)

onkey() (dans le module turtle)

onkeypress() (dans le module turtle)

onkeyrelease() (dans le module turtle)

onrelease() (dans le module turtle)

onscreenclick() (dans le module turtle)

ontimer() (dans le module turtle)

OP (dans le module token)

OP_ALL (dans le module ssl)

OP_CIPHER_SERVER_PREFERENCE (dans le module ssl)

OP_ENABLE_MIDDLEBOX_COMPAT (dans le module ssl)

OP_NO_COMPRESSION (dans le module ssl)

OP_NO_SSLv2 (dans le module ssl)

OP_NO_SSLv3 (dans le module ssl)

OP_NO_TICKET (dans le module ssl)

OP_NO_TLSv1 (dans le module ssl)

OP_NO_TLSv1_1 (dans le module ssl)

OP_NO_TLSv1_2 (dans le module ssl)

OP_NO_TLSv1_3 (dans le module ssl)

OP_SINGLE_DH_USE (dans le module ssl)

OP_SINGLE_ECDH_USE (dans le module ssl)

open

fonction de base, [1]

open() (dans le module aifc)

(dans le module bz2)

(dans le module codecs)

(dans le module dbm)

(dans le module dbm.dumb)

(dans le module dbm.gnu)

(dans le module dbm.ndbm)

(dans le module gzip)

(dans le module io)

(dans le module lzma)

(dans le module os)

(dans le module ossaudiodev)

(dans le module shelve)

(dans le module sunau)

(dans le module tarfile)

(dans le module tokenize)

(dans le module wave)

(dans le module webbrowser)

(fonction de base)

(méthode de la classe tarfile.TarFile)

(méthode distutils.text_file.TextFile)

(méthode imaplib.IMAP4)

(méthode pathlib.Path)

(méthode pipes.Template)

(méthode telnetlib.Telnet)

(méthode urllib.request.OpenerDirector)

(méthode urllib.request.URLopener)

(méthode webbrowser.controller)

(méthode zipfile.ZipFile)

open_connection() (dans le module asyncio)

open_new() (dans le module webbrowser)

(méthode webbrowser.controller)

open_new_tab() (dans le module webbrowser)

(méthode webbrowser.controller)

open_osfhandle() (dans le module msvcrt)

open_unix_connection() (dans le module asyncio)

open_unknown() (méthode urllib.request.URLopener)

OpenDatabase() (dans le module msilib)

OpenerDirector (classe dans urllib.request)

openfp() (dans le module sunau)

(dans le module wave)

OpenKey() (dans le module winreg)

OpenKeyEx() (dans le module winreg)

openlog() (dans le module syslog)

openmixer() (dans le module ossaudiodev)

openpty() (dans le module os)

(dans le module pty)

OpenSSL

(use in module hashlib)

(use in module ssl)

OPENSSL_VERSION (dans le module ssl)

OPENSSL_VERSION_INFO (dans le module ssl)

OPENSSL_VERSION_NUMBER (dans le module ssl)

OpenView() (méthode msilib.Database)

operation

binary arithmetic

binary bitwise

Boolean

concatenation

null, [1]

power

repetition

shifting

slice

subscript

unary arithmetic

unary bitwise

OperationalError

operations

bitwise

Boolean, [1]

masking

shifting

operations on

dictionary type

integer types

list type

mapping types

numeric types

sequence types, [1]

operator

+ (plus), [1], [2]

- (minus), [1], [2]

comparison

overloading

precedence

ternary

operator (2to3 fixer)

(module)

operators

opérateur

!=, [1]

% (percent), [1]

& (ampersand), [1]

* (asterisk), [1]

**, [1]

/ (slash), [1]

//, [1]

< (less), [1]

<<, [1]

<=, [1]

==, [1]

> (greater), [1]

>=, [1]

>>, [1]

@ (at)

^ (caret), [1]

| (vertical bar), [1]

~ (tilde), [1]

and, [1], [2]

in, [1], [2]

is, [1]

is not, [1]

not, [1]

not in, [1], [2]

or, [1], [2]

opmap (dans le module dis)

opname (dans le module dis)

optimize() (dans le module pickletools)

OPTIMIZED_BYTECODE_SUFFIXES (dans le module importlib.machinery)

Optional (dans le module typing)

OptionGroup (classe dans optparse)

OptionMenu (classe dans tkinter.tix)

OptionParser (classe dans optparse)

options (attribut doctest.Example)

(attribut ssl.SSLContext)

Options (classe dans ssl)

options() (méthode configparser.ConfigParser)

optionxform() (méthode configparser.ConfigParser), [1]

optparse (module)

or

bitwise

exclusive

inclusive

opérateur, [1], [2]

or_() (dans le module operator)

ord

fonction de base

ord() (fonction de base)

order

evaluation

ordered_attributes (attribut xml.parsers.expat.xmlparser)

OrderedDict (classe dans collections)

ordre de résolution des méthodes

origin (attribut importlib.machinery.ModuleSpec)

origin_req_host (attribut urllib.request.Request)

origin_server (attribut wsgiref.handlers.BaseHandler)

os

module

os (module)

os.path (module)

os_environ (attribut wsgiref.handlers.BaseHandler)

OSError

ossaudiodev (module)

OSSAudioError

outfile

json.tool command line option

output

standard

output (attribut subprocess.CalledProcessError)

(attribut subprocess.TimeoutExpired)

(attribut unittest.TestCase)

output() (méthode http.cookies.BaseCookie)

(méthode http.cookies.Morsel)

output_charset (attribut email.charset.Charset)

output_charset() (méthode gettext.NullTranslations)

output_codec (attribut email.charset.Charset)

output_difference() (méthode doctest.OutputChecker)

OutputChecker (classe dans doctest)

OutputString() (méthode http.cookies.Morsel)

over() (méthode nntplib.NNTP)

Overflow (classe dans decimal)

OverflowError

(built-in exception), [1], [2], [3], [4], [5]

overlaps() (méthode ipaddress.IPv4Network)

(méthode ipaddress.IPv6Network)

overlay() (méthode curses.window)

overload() (dans le module typing)

overloading

operator

overwrite() (méthode curses.window)

owner() (méthode pathlib.Path)

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Index – P

p (pdb command)

P_ALL (dans le module os)

P_DETACH (dans le module os)

P_NOWAIT (dans le module os)

P_NOWAITO (dans le module os)

P_OVERLAY (dans le module os)

P_PGID (dans le module os)

P_PID (dans le module os)

P_WAIT (dans le module os)

pack() (dans le module struct)

(méthode mailbox.MH)

(méthode struct.Struct)

pack_array() (méthode xdrlib.Packer)

pack_bytes() (méthode xdrlib.Packer)

pack_double() (méthode xdrlib.Packer)

pack_farray() (méthode xdrlib.Packer)

pack_float() (méthode xdrlib.Packer)

pack_fopaque() (méthode xdrlib.Packer)

pack_fstring() (méthode xdrlib.Packer)

pack_into() (dans le module struct)

(méthode struct.Struct)

pack_list() (méthode xdrlib.Packer)

pack_opaque() (méthode xdrlib.Packer)

pack_string() (méthode xdrlib.Packer)

package, [1]

namespace

portion

regular

package variable

__all__

packed (attribut ipaddress.IPv4Address)

(attribut ipaddress.IPv6Address)

Packer (classe dans xdrlib)

packing

binary data

packing (widgets)

PAGER

pair_content() (dans le module curses)

pair_number() (dans le module curses)

PanedWindow (classe dans tkinter.tix)

paquet

paquet classique

paquet provisoire

paquet-espace de nommage

parameter

call semantics

difference from argument

function definition

value, default

Parameter (classe dans inspect)

ParameterizedMIMEHeader (classe dans email.headerregistry)

parameters (attribut inspect.Signature)

paramètre

params (attribut email.headerregistry.ParameterizedMIMEHeader)

pardir (dans le module os)

paren (2to3 fixer)

parent (attribut importlib.machinery.ModuleSpec)

(attribut urllib.request.BaseHandler)

parent() (méthode tkinter.ttk.Treeview)

parenthesized form

parentNode (attribut xml.dom.Node)

parents (attribut collections.ChainMap)

paretovariate() (dans le module random)

parse() (dans le module ast)

(dans le module cgi)

(dans le module xml.dom.minidom)

(dans le module xml.dom.pulldom)

(dans le module xml.etree.ElementTree)

(dans le module xml.sax)

(méthode doctest.DocTestParser)

(méthode email.parser.BytesParser)

(méthode email.parser.Parser)

(méthode string.Formatter)

(méthode urllib.robotparser.RobotFileParser)

(méthode xml.etree.ElementTree.ElementTree)

Parse() (méthode xml.parsers.expat.xmlparser)

parse() (méthode xml.sax.xmlreader.XMLReader)

parse_and_bind() (dans le module readline)

parse_args() (méthode argparse.ArgumentParser)

PARSE_COLNAMES (dans le module sqlite3)

parse_config_h() (dans le module sysconfig)

PARSE_DECLTYPES (dans le module sqlite3)

parse_header() (dans le module cgi)

parse_known_args() (méthode argparse.ArgumentParser)

parse_multipart() (dans le module cgi)

parse_qs() (dans le module cgi)

(dans le module urllib.parse)

parse_qsl() (dans le module cgi)

(dans le module urllib.parse)

parseaddr() (dans le module email.utils)

parsebytes() (méthode email.parser.BytesParser)

parsedate() (dans le module email.utils)

parsedate_to_datetime() (dans le module email.utils)

parsedate_tz() (dans le module email.utils)

ParseError (classe dans xml.etree.ElementTree)

ParseFile() (méthode xml.parsers.expat.xmlparser)

ParseFlags() (dans le module imaplib)

parser

Parser (classe dans email.parser)

parser (module)

ParserCreate() (dans le module xml.parsers.expat)

ParserError

ParseResult (classe dans urllib.parse)

ParseResultBytes (classe dans urllib.parse)

parsestr() (méthode email.parser.Parser)

parseString() (dans le module xml.dom.minidom)

(dans le module xml.dom.pulldom)

(dans le module xml.sax)

parsing

Python source code

URL

ParsingError

partial (attribut asyncio.IncompleteReadError)

partial() (dans le module functools)

(méthode imaplib.IMAP4)

partialmethod (classe dans functools)

parties (attribut threading.Barrier)

partition() (méthode bytearray)

(méthode bytes)

(méthode str)

pass

état

pass_() (méthode poplib.POP3)

Paste

patch() (dans le module unittest.mock)

patch.dict() (dans le module unittest.mock)

patch.multiple() (dans le module unittest.mock)

patch.object() (dans le module unittest.mock)

patch.stopall() (dans le module unittest.mock)

PATH, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20], [21], [22], [23], [24], [25], [26], [27], [28], [29], [30], [31], [32], [33], [34]

path

configuration file

hooks

module search, [1], [2], [3], [4], [5], [6], [7]

operations, [1]

path (attribut http.cookiejar.Cookie)

(attribut http.server.BaseHTTPRequestHandler)

(attribut importlib.abc.FileLoader)

(attribut importlib.machinery.ExtensionFileLoader)

(attribut importlib.machinery.FileFinder)

(attribut importlib.machinery.SourceFileLoader)

(attribut importlib.machinery.SourcelessFileLoader)

(attribut os.DirEntry)

Path (classe dans pathlib)

path (dans le module sys)

(in module sys), [1], [2], [3]

path based finder

Path browser

path hooks

path_hook() (méthode de la classe importlib.machinery.FileFinder)

path_hooks (dans le module sys)

path_importer_cache (dans le module sys)

path_mtime() (méthode importlib.abc.SourceLoader)

path_return_ok() (méthode http.cookiejar.CookiePolicy)

path_stats() (méthode importlib.abc.SourceLoader)

(méthode importlib.machinery.SourceFileLoader)

pathconf() (dans le module os)

pathconf_names (dans le module os)

PathEntryFinder (classe dans importlib.abc)

PATHEXT, [1]

PathFinder (classe dans importlib.machinery)

pathlib (module)

PathLike (classe dans os)

pathname2url() (dans le module urllib.request)

pathsep (dans le module os)

pattern (attribut re.error)

(attribut re.regex)

Pattern (classe dans typing)

pause() (dans le module signal)

pause_reading() (méthode asyncio.ReadTransport)

pause_writing() (méthode asyncio.BaseProtocol)

PAX_FORMAT (dans le module tarfile)

pax_headers (attribut tarfile.TarFile)

(attribut tarfile.TarInfo)

pbkdf2_hmac() (dans le module hashlib)

pd() (dans le module turtle)

Pdb (class in pdb)

(classe dans pdb)

pdb (module)

peek() (méthode bz2.BZ2File)

(méthode gzip.GzipFile)

(méthode io.BufferedReader)

(méthode lzma.LZMAFile)

(méthode weakref.finalize)

peer (attribut smtpd.SMTPChannel)

PEM_cert_to_DER_cert() (dans le module ssl)

pen() (dans le module turtle)

pencolor() (dans le module turtle)

pending (attribut ssl.MemoryBIO)

pending() (méthode ssl.SSLSocket)

PendingDeprecationWarning

pendown() (dans le module turtle)

pensize() (dans le module turtle)

penup() (dans le module turtle)

PEP

PERCENT (dans le module token)

PERCENTEQUAL (dans le module token)

perf_counter() (dans le module time)

Performance

PermissionError

permutations() (dans le module itertools)

Persist() (méthode msilib.SummaryInformation)

persistence

persistent

objects

persistent_id (pickle protocol)

persistent_id() (méthode pickle.Pickler)

persistent_load (pickle protocol)

persistent_load() (méthode pickle.Unpickler)

PF_CAN (dans le module socket)

PF_PACKET (dans le module socket)

PF_RDS (dans le module socket)

pformat() (dans le module pprint)

(méthode pprint.PrettyPrinter)

phase() (dans le module cmath)

Philbrick, Geoff

physical line, [1], [2]

pi (dans le module cmath)

(dans le module math)

pickle

module, [1], [2], [3]

pickle (module)

pickle() (dans le module copyreg)

PickleError

Pickler (classe dans pickle)

pickletools (module)

pickletools command line option

--annotate

--indentlevel=<num>

--memo

--output=<file>

--preamble=<preamble>

-a

-l

-m

-o

-p

pickling

objects

PicklingError

pid (attribut asyncio.asyncio.subprocess.Process)

(attribut multiprocessing.Process)

(attribut subprocess.Popen)

PIPE (dans le module subprocess)

Pipe() (dans le module multiprocessing)

pipe() (dans le module os)

pipe2() (dans le module os)

PIPE_BUF (dans le module select)

pipe_connection_lost() (méthode asyncio.SubprocessProtocol)

pipe_data_received() (méthode asyncio.SubprocessProtocol)

pipes (module)

PKG_DIRECTORY (dans le module imp)

pkgutil (module)

placeholder (attribut textwrap.TextWrapper)

PLAT

platform (dans le module sys)

(in module sys)

(module)

platform() (dans le module platform)

PlaySound() (dans le module winsound)

plist

file

plistlib (module)

plock() (dans le module os)

plus

PLUS (dans le module token)

plus() (méthode decimal.Context)

PLUSEQUAL (dans le module token)

pm() (dans le module pdb)

point d'entrée pour la recherche dans path

POINTER() (dans le module ctypes)

pointer() (dans le module ctypes)

polar() (dans le module cmath)

Policy (classe dans email.policy)

poll() (dans le module select)

(méthode multiprocessing.connection.Connection)

(méthode select.devpoll)

(méthode select.epoll)

(méthode select.poll)

(méthode subprocess.Popen)

PollSelector (classe dans selectors)

Pool (classe dans multiprocessing.pool)

pop() (méthode array.array)

(méthode collections.deque)

(méthode dict)

(méthode frozenset)

(méthode mailbox.Mailbox)

(sequence method)

POP3

protocol

POP3 (classe dans poplib)

POP3_SSL (classe dans poplib)

pop_alignment() (méthode formatter.formatter)

pop_all() (méthode contextlib.ExitStack)

POP_BLOCK (opcode)

POP_EXCEPT (opcode)

pop_font() (méthode formatter.formatter)

POP_JUMP_IF_FALSE (opcode)

POP_JUMP_IF_TRUE (opcode)

pop_margin() (méthode formatter.formatter)

pop_source() (méthode shlex.shlex)

pop_style() (méthode formatter.formatter)

POP_TOP (opcode)

Popen (classe dans subprocess)

popen() (dans le module os)

(dans le module platform)

(in module os), [1]

popitem() (méthode collections.OrderedDict)

(méthode dict)

(méthode mailbox.Mailbox)

popleft() (méthode collections.deque)

poplib (module)

PopupMenu (classe dans tkinter.tix)

port (attribut http.cookiejar.Cookie)

port_specified (attribut http.cookiejar.Cookie)

portée imbriquée

portion

package

pos (attribut json.JSONDecodeError)

(attribut re.error)

(attribut re.match)

pos() (dans le module operator)

(dans le module turtle)

position (attribut xml.etree.ElementTree.ParseError)

position() (dans le module turtle)

POSIX

I/O control

threads

posix (module)

POSIX_FADV_DONTNEED (dans le module os)

POSIX_FADV_NOREUSE (dans le module os)

POSIX_FADV_NORMAL (dans le module os)

POSIX_FADV_RANDOM (dans le module os)

POSIX_FADV_SEQUENTIAL (dans le module os)

POSIX_FADV_WILLNEED (dans le module os)

posix_fadvise() (dans le module os)

posix_fallocate() (dans le module os)

POSIXLY_CORRECT

PosixPath (classe dans pathlib)

post() (méthode nntplib.NNTP)

(méthode ossaudiodev.oss_audio_device)

post_handshake_auth (attribut ssl.SSLContext)

post_mortem() (dans le module pdb)

post_setup() (méthode venv.EnvBuilder)

postcmd() (méthode cmd.Cmd)

postloop() (méthode cmd.Cmd)

pow

fonction de base, [1], [2], [3], [4], [5]

pow() (dans le module math)

(dans le module operator)

(fonction de base)

power

operation

power() (méthode decimal.Context)

pp (pdb command)

pprint (module)

pprint() (dans le module pprint)

(méthode pprint.PrettyPrinter)

prcal() (dans le module calendar)

pread() (dans le module os)

preamble (attribut email.message.EmailMessage)

(attribut email.message.Message)

precedence

operator

precmd() (méthode cmd.Cmd)

prefix, [1], [2], [3]

(attribut xml.dom.Attr)

(attribut xml.dom.Node)

(attribut zipimport.zipimporter)

PREFIX (dans le module distutils.sysconfig)

prefix (dans le module sys)

PREFIXES (dans le module site)

prefixlen (attribut ipaddress.IPv4Network)

(attribut ipaddress.IPv6Network)

preloop() (méthode cmd.Cmd)

prepare() (méthode logging.handlers.QueueHandler)

(méthode logging.handlers.QueueListener)

prepare_class() (dans le module types)

prepare_input_source() (dans le module xml.sax.saxutils)

prepend() (méthode pipes.Template)

preprocess() (méthode distutils.ccompiler.CCompiler)

PrettyPrinter (classe dans pprint)

prev() (méthode tkinter.ttk.Treeview)

previousSibling (attribut xml.dom.Node)

primary

print

fonction de base

print (2to3 fixer)

print() (built-in function)

__str__() (object method)

print() (fonction de base)

print_callees() (méthode pstats.Stats)

print_callers() (méthode pstats.Stats)

print_directory() (dans le module cgi)

print_environ() (dans le module cgi)

print_environ_usage() (dans le module cgi)

print_exc() (dans le module traceback)

(méthode timeit.Timer)

print_exception() (dans le module traceback)

PRINT_EXPR (opcode)

print_form() (dans le module cgi)

print_help() (méthode argparse.ArgumentParser)

print_last() (dans le module traceback)

print_stack() (dans le module traceback)

(méthode asyncio.Task)

print_stats() (méthode profile.Profile)

(méthode pstats.Stats)

print_tb() (dans le module traceback)

print_usage() (méthode argparse.ArgumentParser)

(méthode optparse.OptionParser)

print_version() (méthode optparse.OptionParser)

printable (dans le module string)

printdir() (méthode zipfile.ZipFile)

printf-style formatting, [1]

PRIO_PGRP (dans le module os)

PRIO_PROCESS (dans le module os)

PRIO_USER (dans le module os)

PriorityQueue (classe dans asyncio)

(classe dans queue)

private

names

prlimit() (dans le module resource)

prmonth() (dans le module calendar)

(méthode calendar.TextCalendar)

ProactorEventLoop (classe dans asyncio)

procedure

call

process

group, [1]

id

id of parent

killing, [1]

scheduling priority, [1]

signalling, [1]

Process (classe dans multiprocessing)

process() (méthode logging.LoggerAdapter)

process_exited() (méthode asyncio.SubprocessProtocol)

process_message() (méthode smtpd.SMTPServer)

process_request() (méthode socketserver.BaseServer)

process_time() (dans le module time)

process_tokens() (dans le module tabnanny)

ProcessError

processes, light-weight

ProcessingInstruction() (dans le module xml.etree.ElementTree)

processingInstruction() (méthode xml.sax.handler.ContentHandler)

ProcessingInstructionHandler() (méthode xml.parsers.expat.xmlparser)

ProcessLookupError

processor time

processor() (dans le module platform)

ProcessPoolExecutor (classe dans concurrent.futures)

product() (dans le module itertools)

Profile (classe dans profile)

profile (module)

profile function, [1], [2]

profiler, [1]

profiling, deterministic

program

ProgrammingError

Progressbar (classe dans tkinter.ttk)

prompt (attribut cmd.Cmd)

prompt_user_passwd() (méthode urllib.request.FancyURLopener)

prompts, interpreter

propagate (attribut logging.Logger)

property (classe de base)

property list

property_declaration_handler (dans le module xml.sax.handler)

property_dom_node (dans le module xml.sax.handler)

property_lexical_handler (dans le module xml.sax.handler)

property_xml_string (dans le module xml.sax.handler)

PropertyMock (classe dans unittest.mock)

prot_c() (méthode ftplib.FTP_TLS)

prot_p() (méthode ftplib.FTP_TLS)

proto (attribut socket.socket)

protocol

CGI

context management

copy

FTP, [1]

HTTP, [1], [2], [3], [4], [5]

IMAP4

IMAP4_SSL

IMAP4_stream

iterator

NNTP

POP3

SMTP

Telnet

protocol (attribut ssl.SSLContext)

Protocol (classe dans asyncio)

PROTOCOL_SSLv2 (dans le module ssl)

PROTOCOL_SSLv23 (dans le module ssl)

PROTOCOL_SSLv3 (dans le module ssl)

PROTOCOL_TLS (dans le module ssl)

PROTOCOL_TLS_CLIENT (dans le module ssl)

PROTOCOL_TLS_SERVER (dans le module ssl)

PROTOCOL_TLSv1 (dans le module ssl)

PROTOCOL_TLSv1_1 (dans le module ssl)

PROTOCOL_TLSv1_2 (dans le module ssl)

protocol_version (attribut http.server.BaseHTTPRequestHandler)

PROTOCOL_VERSION (attribut imaplib.IMAP4)

ProtocolError (classe dans xmlrpc.client)

proxy() (dans le module weakref)

proxyauth() (méthode imaplib.IMAP4)

ProxyBasicAuthHandler (classe dans urllib.request)

ProxyDigestAuthHandler (classe dans urllib.request)

ProxyHandler (classe dans urllib.request)

ProxyType (dans le module weakref)

ProxyTypes (dans le module weakref)

pryear() (méthode calendar.TextCalendar)

ps1 (dans le module sys)

ps2 (dans le module sys)

pstats (module)

pstdev() (dans le module statistics)

pthread_kill() (dans le module signal)

pthread_sigmask() (dans le module signal)

pthreads

pty

module

pty (module)

pu() (dans le module turtle)

publicId (attribut xml.dom.DocumentType)

PullDom (classe dans xml.dom.pulldom)

punctuation (dans le module string)

punctuation_chars (attribut shlex.shlex)

PurePath (classe dans pathlib)

PurePath.anchor (dans le module pathlib)

PurePath.drive (dans le module pathlib)

PurePath.name (dans le module pathlib)

PurePath.parent (dans le module pathlib)

PurePath.parents (dans le module pathlib)

PurePath.parts (dans le module pathlib)

PurePath.root (dans le module pathlib)

PurePath.stem (dans le module pathlib)

PurePath.suffix (dans le module pathlib)

PurePath.suffixes (dans le module pathlib)

PurePosixPath (classe dans pathlib)

PureProxy (classe dans smtpd)

PureWindowsPath (classe dans pathlib)

purge() (dans le module re)

Purpose.CLIENT_AUTH (dans le module ssl)

Purpose.SERVER_AUTH (dans le module ssl)

push() (méthode asynchat.async_chat)

(méthode code.InteractiveConsole)

(méthode contextlib.ExitStack)

push_alignment() (méthode formatter.formatter)

push_font() (méthode formatter.formatter)

push_margin() (méthode formatter.formatter)

push_source() (méthode shlex.shlex)

push_style() (méthode formatter.formatter)

push_token() (méthode shlex.shlex)

push_with_producer() (méthode asynchat.async_chat)

pushbutton() (méthode msilib.Dialog)

put() (méthode asyncio.Queue)

(méthode multiprocessing.Queue)

(méthode multiprocessing.SimpleQueue)

(méthode queue.Queue)

put_nowait() (méthode asyncio.Queue)

(méthode multiprocessing.Queue)

(méthode queue.Queue)

putch() (dans le module msvcrt)

putenv() (dans le module os)

putheader() (méthode http.client.HTTPConnection)

putp() (dans le module curses)

putrequest() (méthode http.client.HTTPConnection)

putwch() (dans le module msvcrt)

putwin() (méthode curses.window)

pvariance() (dans le module statistics)

pwd

module

pwd (module)

pwd() (méthode ftplib.FTP)

pwrite() (dans le module os)

Py_AddPendingCall (fonction C)

Py_AddPendingCall()

Py_AtExit (fonction C)

Py_BEGIN_ALLOW_THREADS

(macro C)

Py_BLOCK_THREADS (macro C)

Py_buffer (type C)

Py_buffer.buf (membre C)

Py_buffer.format (membre C)

Py_buffer.internal (membre C)

Py_buffer.itemsize (membre C)

Py_buffer.len (membre C)

Py_buffer.ndim (membre C)

Py_buffer.obj (membre C)

Py_buffer.readonly (membre C)

Py_buffer.shape (membre C)

Py_buffer.strides (membre C)

Py_buffer.suboffsets (membre C)

Py_BuildValue (fonction C)

Py_CLEAR (fonction C)

py_compile (module)

PY_COMPILED (dans le module imp)

Py_CompileString (fonction C)

Py_CompileString(), [1], [2]

Py_CompileStringExFlags (fonction C)

Py_CompileStringFlags (fonction C)

Py_CompileStringObject (fonction C)

Py_complex (type C)

Py_DecodeLocale (fonction C)

Py_DECREF (fonction C)

Py_DECREF()

Py_Ellipsis (variable C)

Py_EncodeLocale (fonction C)

Py_END_ALLOW_THREADS

(macro C)

Py_EndInterpreter (fonction C)

Py_EnterRecursiveCall (fonction C)

Py_eval_input (variable C)

Py_Exit (fonction C)

Py_False (variable C)

Py_FatalError (fonction C)

Py_FatalError()

Py_FdIsInteractive (fonction C)

Py_file_input (variable C)

Py_Finalize (fonction C)

Py_FinalizeEx (fonction C)

Py_FinalizeEx(), [1], [2], [3], [4]

PY_FROZEN (dans le module imp)

Py_GetBuildInfo (fonction C)

Py_GetCompiler (fonction C)

Py_GetCopyright (fonction C)

Py_GetExecPrefix (fonction C)

Py_GetExecPrefix()

Py_GetPath (fonction C)

Py_GetPath(), [1], [2]

Py_GetPlatform (fonction C)

Py_GetPrefix (fonction C)

Py_GetPrefix()

Py_GetProgramFullPath (fonction C)

Py_GetProgramFullPath()

Py_GetProgramName (fonction C)

Py_GetPythonHome (fonction C)

Py_GetVersion (fonction C)

Py_INCREF (fonction C)

Py_INCREF()

Py_Initialize (fonction C)

Py_Initialize(), [1], [2], [3]

Py_InitializeEx (fonction C)

Py_IsInitialized (fonction C)

Py_IsInitialized()

Py_LeaveRecursiveCall (fonction C)

Py_Main (fonction C)

Py_mod_create (variable C)

Py_mod_exec (variable C)

Py_NewInterpreter (fonction C)

Py_None (variable C)

Py_NotImplemented (variable C)

py_object (classe dans ctypes)

Py_PRINT_RAW

Py_REFCNT (macro C)

Py_ReprEnter (fonction C)

Py_ReprLeave (fonction C)

Py_RETURN_FALSE (macro C)

Py_RETURN_NONE (macro C)

Py_RETURN_NOTIMPLEMENTED (macro C)

Py_RETURN_TRUE (macro C)

Py_SetPath (fonction C)

Py_SetPath()

Py_SetProgramName (fonction C)

Py_SetProgramName(), [1], [2], [3]

Py_SetPythonHome (fonction C)

Py_SetStandardStreamEncoding (fonction C)

Py_single_input (variable C)

Py_SIZE (macro C)

PY_SOURCE (dans le module imp)

PY_SSIZE_T_MAX

Py_TPFLAGS_BASE_EXC_SUBCLASS (variable de base)

Py_TPFLAGS_BASETYPE (variable de base)

Py_TPFLAGS_BYTES_SUBCLASS (variable de base)

Py_TPFLAGS_DEFAULT (variable de base)

Py_TPFLAGS_DICT_SUBCLASS (variable de base)

Py_TPFLAGS_HAVE_FINALIZE (variable de base)

Py_TPFLAGS_HAVE_GC (variable de base)

Py_TPFLAGS_HEAPTYPE (variable de base)

Py_TPFLAGS_LIST_SUBCLASS (variable de base)

Py_TPFLAGS_LONG_SUBCLASS (variable de base)

Py_TPFLAGS_READY (variable de base)

Py_TPFLAGS_READYING (variable de base)

Py_TPFLAGS_TUPLE_SUBCLASS (variable de base)

Py_TPFLAGS_TYPE_SUBCLASS (variable de base)

Py_TPFLAGS_UNICODE_SUBCLASS (variable de base)

Py_tracefunc (type C)

Py_True (variable C)

Py_TYPE (macro C)

Py_UCS1 (type C)

Py_UCS2 (type C)

Py_UCS4 (type C)

Py_UNBLOCK_THREADS (macro C)

Py_UNICODE (type C)

Py_UNICODE_IS_HIGH_SURROGATE (macro C)

Py_UNICODE_IS_LOW_SURROGATE (macro C)

Py_UNICODE_IS_SURROGATE (macro C)

Py_UNICODE_ISALNUM (fonction C)

Py_UNICODE_ISALPHA (fonction C)

Py_UNICODE_ISDECIMAL (fonction C)

Py_UNICODE_ISDIGIT (fonction C)

Py_UNICODE_ISLINEBREAK (fonction C)

Py_UNICODE_ISLOWER (fonction C)

Py_UNICODE_ISNUMERIC (fonction C)

Py_UNICODE_ISPRINTABLE (fonction C)

Py_UNICODE_ISSPACE (fonction C)

Py_UNICODE_ISTITLE (fonction C)

Py_UNICODE_ISUPPER (fonction C)

Py_UNICODE_JOIN_SURROGATES (macro C)

Py_UNICODE_TODECIMAL (fonction C)

Py_UNICODE_TODIGIT (fonction C)

Py_UNICODE_TOLOWER (fonction C)

Py_UNICODE_TONUMERIC (fonction C)

Py_UNICODE_TOTITLE (fonction C)

Py_UNICODE_TOUPPER (fonction C)

Py_VaBuildValue (fonction C)

Py_VISIT (fonction C)

Py_XDECREF (fonction C)

Py_XDECREF()

Py_XINCREF (fonction C)

PyAnySet_Check (fonction C)

PyAnySet_CheckExact (fonction C)

PyArg_Parse (fonction C)

PyArg_ParseTuple (fonction C)

PyArg_ParseTuple()

PyArg_ParseTupleAndKeywords (fonction C)

PyArg_ParseTupleAndKeywords()

PyArg_UnpackTuple (fonction C)

PyArg_ValidateKeywordArguments (fonction C)

PyArg_VaParse (fonction C)

PyArg_VaParseTupleAndKeywords (fonction C)

PyASCIIObject (type C)

PyAsyncMethods (type C)

PyAsyncMethods.am_aiter (membre C)

PyAsyncMethods.am_anext (membre C)

PyAsyncMethods.am_await (membre C)

PyBool_Check (fonction C)

PyBool_FromLong (fonction C)

PyBUF_ANY_CONTIGUOUS (macro C)

PyBUF_C_CONTIGUOUS (macro C)

PyBUF_CONTIG (macro C)

PyBUF_CONTIG_RO (macro C)

PyBUF_F_CONTIGUOUS (macro C)

PyBUF_FORMAT (macro C)

PyBUF_FULL (macro C)

PyBUF_FULL_RO (macro C)

PyBUF_INDIRECT (macro C)

PyBUF_ND (macro C), [1]

PyBUF_RECORDS (macro C)

PyBUF_RECORDS_RO (macro C)

PyBUF_SIMPLE (macro C)

PyBUF_STRIDED (macro C)

PyBUF_STRIDED_RO (macro C)

PyBUF_STRIDES (macro C)

PyBUF_WRITABLE (macro C)

PyBuffer_FillContiguousStrides (fonction C)

PyBuffer_FillInfo (fonction C)

PyBuffer_IsContiguous (fonction C)

PyBuffer_Release (fonction C)

PyBuffer_SizeFromFormat (fonction C)

PyBuffer_ToContiguous (fonction C)

PyBufferProcs

(type C)

PyBufferProcs.bf_getbuffer (membre C)

PyBufferProcs.bf_releasebuffer (membre C)

PyByteArray_AS_STRING (fonction C)

PyByteArray_AsString (fonction C)

PyByteArray_Check (fonction C)

PyByteArray_CheckExact (fonction C)

PyByteArray_Concat (fonction C)

PyByteArray_FromObject (fonction C)

PyByteArray_FromStringAndSize (fonction C)

PyByteArray_GET_SIZE (fonction C)

PyByteArray_Resize (fonction C)

PyByteArray_Size (fonction C)

PyByteArray_Type (variable C)

PyByteArrayObject (type C)

PyBytes_AS_STRING (fonction C)

PyBytes_AsString (fonction C)

PyBytes_AsStringAndSize (fonction C)

PyBytes_Check (fonction C)

PyBytes_CheckExact (fonction C)

PyBytes_Concat (fonction C)

PyBytes_ConcatAndDel (fonction C)

PyBytes_FromFormat (fonction C)

PyBytes_FromFormatV (fonction C)

PyBytes_FromObject (fonction C)

PyBytes_FromString (fonction C)

PyBytes_FromStringAndSize (fonction C)

PyBytes_GET_SIZE (fonction C)

PyBytes_Size (fonction C)

PyBytes_Type (variable C)

PyBytesObject (type C)

PyCallable_Check (fonction C)

PyCallIter_Check (fonction C)

PyCallIter_New (fonction C)

PyCallIter_Type (variable C)

PyCapsule (type C)

PyCapsule_CheckExact (fonction C)

PyCapsule_Destructor (type C)

PyCapsule_GetContext (fonction C)

PyCapsule_GetDestructor (fonction C)

PyCapsule_GetName (fonction C)

PyCapsule_GetPointer (fonction C)

PyCapsule_Import (fonction C)

PyCapsule_IsValid (fonction C)

PyCapsule_New (fonction C)

PyCapsule_SetContext (fonction C)

PyCapsule_SetDestructor (fonction C)

PyCapsule_SetName (fonction C)

PyCapsule_SetPointer (fonction C)

PyCell_Check (fonction C)

PyCell_GET (fonction C)

PyCell_Get (fonction C)

PyCell_New (fonction C)

PyCell_SET (fonction C)

PyCell_Set (fonction C)

PyCell_Type (variable C)

PyCellObject (type C)

PyCFunction (type C)

PyCFunctionWithKeywords (type C)

pyclbr (module)

PyCode_Check (fonction C)

PyCode_GetNumFree (fonction C)

PyCode_New (fonction C)

PyCode_NewEmpty (fonction C)

PyCode_Type (variable C)

PyCodec_BackslashReplaceErrors (fonction C)

PyCodec_Decode (fonction C)

PyCodec_Decoder (fonction C)

PyCodec_Encode (fonction C)

PyCodec_Encoder (fonction C)

PyCodec_IgnoreErrors (fonction C)

PyCodec_IncrementalDecoder (fonction C)

PyCodec_IncrementalEncoder (fonction C)

PyCodec_KnownEncoding (fonction C)

PyCodec_LookupError (fonction C)

PyCodec_NameReplaceErrors (fonction C)

PyCodec_Register (fonction C)

PyCodec_RegisterError (fonction C)

PyCodec_ReplaceErrors (fonction C)

PyCodec_StreamReader (fonction C)

PyCodec_StreamWriter (fonction C)

PyCodec_StrictErrors (fonction C)

PyCodec_XMLCharRefReplaceErrors (fonction C)

PyCodeObject (type C)

PyCompactUnicodeObject (type C)

PyCompileError

PyCompilerFlags (type C)

PyComplex_AsCComplex (fonction C)

PyComplex_Check (fonction C)

PyComplex_CheckExact (fonction C)

PyComplex_FromCComplex (fonction C)

PyComplex_FromDoubles (fonction C)

PyComplex_ImagAsDouble (fonction C)

PyComplex_RealAsDouble (fonction C)

PyComplex_Type (variable C)

PyComplexObject (type C)

PyCoro_CheckExact (fonction C)

PyCoro_New (fonction C)

PyCoro_Type (variable C)

PyCoroObject (type C)

PyDate_Check (fonction C)

PyDate_CheckExact (fonction C)

PyDate_FromDate (fonction C)

PyDate_FromTimestamp (fonction C)

PyDateTime_Check (fonction C)

PyDateTime_CheckExact (fonction C)

PyDateTime_DATE_GET_HOUR (fonction C)

PyDateTime_DATE_GET_MICROSECOND (fonction C)

PyDateTime_DATE_GET_MINUTE (fonction C)

PyDateTime_DATE_GET_SECOND (fonction C)

PyDateTime_DELTA_GET_DAYS (fonction C)

PyDateTime_DELTA_GET_MICROSECONDS (fonction C)

PyDateTime_DELTA_GET_SECONDS (fonction C)

PyDateTime_FromDateAndTime (fonction C)

PyDateTime_FromTimestamp (fonction C)

PyDateTime_GET_DAY (fonction C)

PyDateTime_GET_MONTH (fonction C)

PyDateTime_GET_YEAR (fonction C)

PyDateTime_TIME_GET_HOUR (fonction C)

PyDateTime_TIME_GET_MICROSECOND (fonction C)

PyDateTime_TIME_GET_MINUTE (fonction C)

PyDateTime_TIME_GET_SECOND (fonction C)

PyDelta_Check (fonction C)

PyDelta_CheckExact (fonction C)

PyDelta_FromDSU (fonction C)

PyDescr_IsData (fonction C)

PyDescr_NewClassMethod (fonction C)

PyDescr_NewGetSet (fonction C)

PyDescr_NewMember (fonction C)

PyDescr_NewMethod (fonction C)

PyDescr_NewWrapper (fonction C)

PyDict_Check (fonction C)

PyDict_CheckExact (fonction C)

PyDict_Clear (fonction C)

PyDict_ClearFreeList (fonction C)

PyDict_Contains (fonction C)

PyDict_Copy (fonction C)

PyDict_DelItem (fonction C)

PyDict_DelItemString (fonction C)

PyDict_GetItem (fonction C)

PyDict_GetItemString (fonction C)

PyDict_GetItemWithError (fonction C)

PyDict_Items (fonction C)

PyDict_Keys (fonction C)

PyDict_Merge (fonction C)

PyDict_MergeFromSeq2 (fonction C)

PyDict_New (fonction C)

PyDict_Next (fonction C)

PyDict_SetDefault (fonction C)

PyDict_SetItem (fonction C)

PyDict_SetItemString (fonction C)

PyDict_Size (fonction C)

PyDict_Type (variable C)

PyDict_Update (fonction C)

PyDict_Values (fonction C)

PyDictObject (type C)

PyDictProxy_New (fonction C)

PyDLL (classe dans ctypes)

pydoc (module)

PyErr_BadArgument (fonction C)

PyErr_BadInternalCall (fonction C)

PyErr_CheckSignals (fonction C)

PyErr_Clear (fonction C)

PyErr_Clear(), [1]

PyErr_ExceptionMatches (fonction C)

PyErr_ExceptionMatches()

PyErr_Fetch (fonction C)

PyErr_Fetch()

PyErr_Format (fonction C)

PyErr_FormatV (fonction C)

PyErr_GetExcInfo (fonction C)

PyErr_GivenExceptionMatches (fonction C)

PyErr_NewException (fonction C)

PyErr_NewExceptionWithDoc (fonction C)

PyErr_NoMemory (fonction C)

PyErr_NormalizeException (fonction C)

PyErr_Occurred (fonction C)

PyErr_Occurred()

PyErr_Print (fonction C)

PyErr_PrintEx (fonction C)

PyErr_ResourceWarning (fonction C)

PyErr_Restore (fonction C)

PyErr_Restore()

PyErr_SetExcFromWindowsErr (fonction C)

PyErr_SetExcFromWindowsErrWithFilename (fonction C)

PyErr_SetExcFromWindowsErrWithFilenameObject (fonction C)

PyErr_SetExcFromWindowsErrWithFilenameObjects (fonction C)

PyErr_SetExcInfo (fonction C)

PyErr_SetFromErrno (fonction C)

PyErr_SetFromErrnoWithFilename (fonction C)

PyErr_SetFromErrnoWithFilenameObject (fonction C)

PyErr_SetFromErrnoWithFilenameObjects (fonction C)

PyErr_SetFromWindowsErr (fonction C)

PyErr_SetFromWindowsErrWithFilename (fonction C)

PyErr_SetImportError (fonction C)

PyErr_SetImportErrorSubclass (fonction C)

PyErr_SetInterrupt (fonction C)

PyErr_SetNone (fonction C)

PyErr_SetObject (fonction C)

PyErr_SetString (fonction C)

PyErr_SetString()

PyErr_SyntaxLocation (fonction C)

PyErr_SyntaxLocationEx (fonction C)

PyErr_SyntaxLocationObject (fonction C)

PyErr_WarnEx (fonction C)

PyErr_WarnExplicit (fonction C)

PyErr_WarnExplicitObject (fonction C)

PyErr_WarnFormat (fonction C)

PyErr_WriteUnraisable (fonction C)

PyEval_AcquireLock (fonction C)

PyEval_AcquireThread (fonction C)

PyEval_AcquireThread()

PyEval_EvalCode (fonction C)

PyEval_EvalCodeEx (fonction C)

PyEval_EvalFrame (fonction C)

PyEval_EvalFrameEx (fonction C)

PyEval_GetBuiltins (fonction C)

PyEval_GetCallStats (fonction C)

PyEval_GetFrame (fonction C)

PyEval_GetFuncDesc (fonction C)

PyEval_GetFuncName (fonction C)

PyEval_GetGlobals (fonction C)

PyEval_GetLocals (fonction C)

PyEval_InitThreads (fonction C)

PyEval_InitThreads()

PyEval_MergeCompilerFlags (fonction C)

PyEval_ReInitThreads (fonction C)

PyEval_ReleaseLock (fonction C)

PyEval_ReleaseThread (fonction C)

PyEval_ReleaseThread()

PyEval_RestoreThread (fonction C)

PyEval_RestoreThread(), [1]

PyEval_SaveThread (fonction C)

PyEval_SaveThread(), [1]

PyEval_SetProfile (fonction C)

PyEval_SetTrace (fonction C)

PyEval_ThreadsInitialized (fonction C)

PyExc_ArithmeticError

PyExc_AssertionError

PyExc_AttributeError

PyExc_BaseException

PyExc_BlockingIOError

PyExc_BrokenPipeError

PyExc_BufferError

PyExc_BytesWarning

PyExc_ChildProcessError

PyExc_ConnectionAbortedError

PyExc_ConnectionError

PyExc_ConnectionRefusedError

PyExc_ConnectionResetError

PyExc_DeprecationWarning

PyExc_EnvironmentError

PyExc_EOFError

PyExc_Exception

PyExc_FileExistsError

PyExc_FileNotFoundError

PyExc_FloatingPointError

PyExc_FutureWarning

PyExc_GeneratorExit

PyExc_ImportError

PyExc_ImportWarning

PyExc_IndentationError

PyExc_IndexError

PyExc_InterruptedError

PyExc_IOError

PyExc_IsADirectoryError

PyExc_KeyboardInterrupt

PyExc_KeyError

PyExc_LookupError

PyExc_MemoryError

PyExc_ModuleNotFoundError

PyExc_NameError

PyExc_NotADirectoryError

PyExc_NotImplementedError

PyExc_OSError

PyExc_OverflowError

PyExc_PendingDeprecationWarning

PyExc_PermissionError

PyExc_ProcessLookupError

PyExc_RecursionError

PyExc_ReferenceError

PyExc_ResourceWarning

PyExc_RuntimeError

PyExc_RuntimeWarning

PyExc_StopAsyncIteration

PyExc_StopIteration

PyExc_SyntaxError

PyExc_SyntaxWarning

PyExc_SystemError

PyExc_SystemExit

PyExc_TabError

PyExc_TimeoutError

PyExc_TypeError

PyExc_UnboundLocalError

PyExc_UnicodeDecodeError

PyExc_UnicodeEncodeError

PyExc_UnicodeError

PyExc_UnicodeTranslateError

PyExc_UnicodeWarning

PyExc_UserWarning

PyExc_ValueError

PyExc_Warning

PyExc_WindowsError

PyExc_ZeroDivisionError

PyException_GetCause (fonction C)

PyException_GetContext (fonction C)

PyException_GetTraceback (fonction C)

PyException_SetCause (fonction C)

PyException_SetContext (fonction C)

PyException_SetTraceback (fonction C)

pyexpat

module

PyFile_FromFd (fonction C)

PyFile_GetLine (fonction C)

PyFile_WriteObject (fonction C)

PyFile_WriteString (fonction C)

PyFloat_AS_DOUBLE (fonction C)

PyFloat_AsDouble (fonction C)

PyFloat_Check (fonction C)

PyFloat_CheckExact (fonction C)

PyFloat_ClearFreeList (fonction C)

PyFloat_FromDouble (fonction C)

PyFloat_FromString (fonction C)

PyFloat_GetInfo (fonction C)

PyFloat_GetMax (fonction C)

PyFloat_GetMin (fonction C)

PyFloat_Type (variable C)

PyFloatObject (type C)

PyFrame_GetLineNumber (fonction C)

PyFrameObject (type C)

PyFrozenSet_Check (fonction C)

PyFrozenSet_CheckExact (fonction C)

PyFrozenSet_New (fonction C)

PyFrozenSet_Type (variable C)

PyFunction_Check (fonction C)

PyFunction_GetAnnotations (fonction C)

PyFunction_GetClosure (fonction C)

PyFunction_GetCode (fonction C)

PyFunction_GetDefaults (fonction C)

PyFunction_GetGlobals (fonction C)

PyFunction_GetModule (fonction C)

PyFunction_New (fonction C)

PyFunction_NewWithQualName (fonction C)

PyFunction_SetAnnotations (fonction C)

PyFunction_SetClosure (fonction C)

PyFunction_SetDefaults (fonction C)

PyFunction_Type (variable C)

PyFunctionObject (type C)

PYFUNCTYPE() (dans le module ctypes)

PyGen_Check (fonction C)

PyGen_CheckExact (fonction C)

PyGen_New (fonction C)

PyGen_NewWithQualName (fonction C)

PyGen_Type (variable C)

PyGenObject (type C)

PyGetSetDef (type C)

PyGILState_Check (fonction C)

PyGILState_Ensure (fonction C)

PyGILState_GetThisThreadState (fonction C)

PyGILState_Release (fonction C)

PyImport_AddModule (fonction C)

PyImport_AddModuleObject (fonction C)

PyImport_AppendInittab (fonction C)

PyImport_Cleanup (fonction C)

PyImport_ExecCodeModule (fonction C)

PyImport_ExecCodeModuleEx (fonction C)

PyImport_ExecCodeModuleObject (fonction C)

PyImport_ExecCodeModuleWithPathnames (fonction C)

PyImport_ExtendInittab (fonction C)

PyImport_FrozenModules (variable C)

PyImport_GetImporter (fonction C)

PyImport_GetMagicNumber (fonction C)

PyImport_GetMagicTag (fonction C)

PyImport_GetModuleDict (fonction C)

PyImport_Import (fonction C)

PyImport_ImportFrozenModule (fonction C)

PyImport_ImportFrozenModuleObject (fonction C)

PyImport_ImportModule (fonction C)

PyImport_ImportModuleEx (fonction C)

PyImport_ImportModuleLevel (fonction C)

PyImport_ImportModuleLevelObject (fonction C)

PyImport_ImportModuleNoBlock (fonction C)

PyImport_ReloadModule (fonction C)

PyIndex_Check (fonction C)

PyInit_modulename (fonction C)

PyInstanceMethod_Check (fonction C)

PyInstanceMethod_Function (fonction C)

PyInstanceMethod_GET_FUNCTION (fonction C)

PyInstanceMethod_New (fonction C)

PyInstanceMethod_Type (variable C)

PyInterpreterState (type C)

PyInterpreterState_Clear (fonction C)

PyInterpreterState_Delete (fonction C)

PyInterpreterState_Head (fonction C)

PyInterpreterState_New (fonction C)

PyInterpreterState_Next (fonction C)

PyInterpreterState_ThreadHead (fonction C)

PyIter_Check (fonction C)

PyIter_Next (fonction C)

PyList_Append (fonction C)

PyList_AsTuple (fonction C)

PyList_Check (fonction C)

PyList_CheckExact (fonction C)

PyList_ClearFreeList (fonction C)

PyList_GET_ITEM (fonction C)

PyList_GET_SIZE (fonction C)

PyList_GetItem (fonction C)

PyList_GetItem()

PyList_GetSlice (fonction C)

PyList_Insert (fonction C)

PyList_New (fonction C)

PyList_Reverse (fonction C)

PyList_SET_ITEM (fonction C)

PyList_SetItem (fonction C)

PyList_SetItem()

PyList_SetSlice (fonction C)

PyList_Size (fonction C)

PyList_Sort (fonction C)

PyList_Type (variable C)

PyListObject (type C)

PyLong_AsDouble (fonction C)

PyLong_AsLong (fonction C)

PyLong_AsLongAndOverflow (fonction C)

PyLong_AsLongLong (fonction C)

PyLong_AsLongLongAndOverflow (fonction C)

PyLong_AsSize_t (fonction C)

PyLong_AsSsize_t (fonction C)

PyLong_AsUnsignedLong (fonction C)

PyLong_AsUnsignedLongLong (fonction C)

PyLong_AsUnsignedLongLongMask (fonction C)

PyLong_AsUnsignedLongMask (fonction C)

PyLong_AsVoidPtr (fonction C)

PyLong_Check (fonction C)

PyLong_CheckExact (fonction C)

PyLong_FromDouble (fonction C)

PyLong_FromLong (fonction C)

PyLong_FromLongLong (fonction C)

PyLong_FromSize_t (fonction C)

PyLong_FromSsize_t (fonction C)

PyLong_FromString (fonction C)

PyLong_FromUnicode (fonction C)

PyLong_FromUnicodeObject (fonction C)

PyLong_FromUnsignedLong (fonction C)

PyLong_FromUnsignedLongLong (fonction C)

PyLong_FromVoidPtr (fonction C)

PyLong_Type (variable C)

PyLongObject (type C)

PyMapping_Check (fonction C)

PyMapping_DelItem (fonction C)

PyMapping_DelItemString (fonction C)

PyMapping_GetItemString (fonction C)

PyMapping_HasKey (fonction C)

PyMapping_HasKeyString (fonction C)

PyMapping_Items (fonction C)

PyMapping_Keys (fonction C)

PyMapping_Length (fonction C)

PyMapping_SetItemString (fonction C)

PyMapping_Size (fonction C)

PyMapping_Values (fonction C)

PyMappingMethods (type C)

PyMappingMethods.mp_ass_subscript (membre C)

PyMappingMethods.mp_length (membre C)

PyMappingMethods.mp_subscript (membre C)

PyMarshal_ReadLastObjectFromFile (fonction C)

PyMarshal_ReadLongFromFile (fonction C)

PyMarshal_ReadObjectFromFile (fonction C)

PyMarshal_ReadObjectFromString (fonction C)

PyMarshal_ReadShortFromFile (fonction C)

PyMarshal_WriteLongToFile (fonction C)

PyMarshal_WriteObjectToFile (fonction C)

PyMarshal_WriteObjectToString (fonction C)

PyMem_Calloc (fonction C)

PyMem_Del (fonction C)

PYMEM_DOMAIN_MEM (variable C)

PYMEM_DOMAIN_OBJ (variable C)

PYMEM_DOMAIN_RAW (variable C)

PyMem_Free (fonction C)

PyMem_GetAllocator (fonction C)

PyMem_Malloc (fonction C)

PyMem_New (fonction C)

PyMem_RawCalloc (fonction C)

PyMem_RawFree (fonction C)

PyMem_RawMalloc (fonction C)

PyMem_RawRealloc (fonction C)

PyMem_Realloc (fonction C)

PyMem_Resize (fonction C)

PyMem_SetAllocator (fonction C)

PyMem_SetupDebugHooks (fonction C)

PyMemAllocatorDomain (type C)

PyMemAllocatorEx (type C)

PyMemberDef (type C)

PyMemoryView_Check (fonction C)

PyMemoryView_FromBuffer (fonction C)

PyMemoryView_FromMemory (fonction C)

PyMemoryView_FromObject (fonction C)

PyMemoryView_GET_BASE (fonction C)

PyMemoryView_GET_BUFFER (fonction C)

PyMemoryView_GetContiguous (fonction C)

PyMethod_Check (fonction C)

PyMethod_ClearFreeList (fonction C)

PyMethod_Function (fonction C)

PyMethod_GET_FUNCTION (fonction C)

PyMethod_GET_SELF (fonction C)

PyMethod_New (fonction C)

PyMethod_Self (fonction C)

PyMethod_Type (variable C)

PyMethodDef (type C)

PyModule_AddFunctions (fonction C)

PyModule_AddIntConstant (fonction C)

PyModule_AddIntMacro (fonction C)

PyModule_AddObject (fonction C)

PyModule_AddStringConstant (fonction C)

PyModule_AddStringMacro (fonction C)

PyModule_Check (fonction C)

PyModule_CheckExact (fonction C)

PyModule_Create (fonction C)

PyModule_Create2 (fonction C)

PyModule_ExecDef (fonction C)

PyModule_FromDefAndSpec (fonction C)

PyModule_FromDefAndSpec2 (fonction C)

PyModule_GetDef (fonction C)

PyModule_GetDict (fonction C)

PyModule_GetFilename (fonction C)

PyModule_GetFilenameObject (fonction C)

PyModule_GetName (fonction C)

PyModule_GetNameObject (fonction C)

PyModule_GetState (fonction C)

PyModule_New (fonction C)

PyModule_NewObject (fonction C)

PyModule_SetDocString (fonction C)

PyModule_Type (variable C)

PyModuleDef (type C)

PyModuleDef.m_base (membre C)

PyModuleDef.m_clear (membre C)

PyModuleDef.m_doc (membre C)

PyModuleDef.m_free (membre C)

PyModuleDef.m_methods (membre C)

PyModuleDef.m_name (membre C)

PyModuleDef.m_reload (membre C)

PyModuleDef.m_size (membre C)

PyModuleDef.m_slots (membre C)

PyModuleDef.m_traverse (membre C)

PyModuleDef_Init (fonction C)

PyModuleDef_Slot (type C)

PyModuleDef_Slot.slot (membre C)

PyModuleDef_Slot.value (membre C)

PyNumber_Absolute (fonction C)

PyNumber_Add (fonction C)

PyNumber_And (fonction C)

PyNumber_AsSsize_t (fonction C)

PyNumber_Check (fonction C)

PyNumber_Divmod (fonction C)

PyNumber_Float (fonction C)

PyNumber_FloorDivide (fonction C)

PyNumber_Index (fonction C)

PyNumber_InPlaceAdd (fonction C)

PyNumber_InPlaceAnd (fonction C)

PyNumber_InPlaceFloorDivide (fonction C)

PyNumber_InPlaceLshift (fonction C)

PyNumber_InPlaceMatrixMultiply (fonction C)

PyNumber_InPlaceMultiply (fonction C)

PyNumber_InPlaceOr (fonction C)

PyNumber_InPlacePower (fonction C)

PyNumber_InPlaceRemainder (fonction C)

PyNumber_InPlaceRshift (fonction C)

PyNumber_InPlaceSubtract (fonction C)

PyNumber_InPlaceTrueDivide (fonction C)

PyNumber_InPlaceXor (fonction C)

PyNumber_Invert (fonction C)

PyNumber_Long (fonction C)

PyNumber_Lshift (fonction C)

PyNumber_MatrixMultiply (fonction C)

PyNumber_Multiply (fonction C)

PyNumber_Negative (fonction C)

PyNumber_Or (fonction C)

PyNumber_Positive (fonction C)

PyNumber_Power (fonction C)

PyNumber_Remainder (fonction C)

PyNumber_Rshift (fonction C)

PyNumber_Subtract (fonction C)

PyNumber_ToBase (fonction C)

PyNumber_TrueDivide (fonction C)

PyNumber_Xor (fonction C)

PyNumberMethods (type C)

PyObject (type C)

PyObject._ob_next (membre C)

PyObject._ob_prev (membre C)

PyObject.ob_refcnt (membre C)

PyObject.ob_type (membre C)

PyObject_AsCharBuffer (fonction C)

PyObject_ASCII (fonction C)

PyObject_AsFileDescriptor (fonction C)

PyObject_AsReadBuffer (fonction C)

PyObject_AsWriteBuffer (fonction C)

PyObject_Bytes (fonction C)

PyObject_Call (fonction C)

PyObject_CallFunction (fonction C)

PyObject_CallFunctionObjArgs (fonction C)

PyObject_CallMethod (fonction C)

PyObject_CallMethodObjArgs (fonction C)

PyObject_CallObject (fonction C)

PyObject_CallObject()

PyObject_Calloc (fonction C)

PyObject_CheckBuffer (fonction C)

PyObject_CheckReadBuffer (fonction C)

PyObject_Del (fonction C)

PyObject_DelAttr (fonction C)

PyObject_DelAttrString (fonction C)

PyObject_DelItem (fonction C)

PyObject_Dir (fonction C)

PyObject_Free (fonction C)

PyObject_GC_Del (fonction C)

PyObject_GC_New (fonction C)

PyObject_GC_NewVar (fonction C)

PyObject_GC_Resize (fonction C)

PyObject_GC_Track (fonction C)

PyObject_GC_UnTrack (fonction C)

PyObject_GenericGetAttr (fonction C)

PyObject_GenericGetDict (fonction C)

PyObject_GenericSetAttr (fonction C)

PyObject_GenericSetDict (fonction C)

PyObject_GetArenaAllocator (fonction C)

PyObject_GetAttr (fonction C)

PyObject_GetAttrString (fonction C)

PyObject_GetBuffer (fonction C)

PyObject_GetItem (fonction C)

PyObject_GetIter (fonction C)

PyObject_HasAttr (fonction C)

PyObject_HasAttrString (fonction C)

PyObject_Hash (fonction C)

PyObject_HashNotImplemented (fonction C)

PyObject_HEAD (macro C)

PyObject_HEAD_INIT (macro C)

PyObject_Init (fonction C)

PyObject_InitVar (fonction C)

PyObject_IsInstance (fonction C)

PyObject_IsSubclass (fonction C)

PyObject_IsTrue (fonction C)

PyObject_Length (fonction C)

PyObject_LengthHint (fonction C)

PyObject_Malloc (fonction C)

PyObject_New (fonction C)

PyObject_NewVar (fonction C)

PyObject_Not (fonction C)

PyObject_Print (fonction C)

PyObject_Realloc (fonction C)

PyObject_Repr (fonction C)

PyObject_RichCompare (fonction C)

PyObject_RichCompareBool (fonction C)

PyObject_SetArenaAllocator (fonction C)

PyObject_SetAttr (fonction C)

PyObject_SetAttrString (fonction C)

PyObject_SetItem (fonction C)

PyObject_Size (fonction C)

PyObject_Str (fonction C)

PyObject_Type (fonction C)

PyObject_TypeCheck (fonction C)

PyObject_VAR_HEAD (macro C)

PyObjectArenaAllocator (type C)

PyOS_AfterFork (fonction C)

PyOS_CheckStack (fonction C)

PyOS_double_to_string (fonction C)

PyOS_FSPath (fonction C)

PyOS_getsig (fonction C)

PyOS_InputHook (variable C)

PyOS_ReadlineFunctionPointer (variable C)

PyOS_setsig (fonction C)

PyOS_snprintf (fonction C)

PyOS_stricmp (fonction C)

PyOS_string_to_double (fonction C)

PyOS_strnicmp (fonction C)

PyOS_vsnprintf (fonction C)

PyParser_SimpleParseFile (fonction C)

PyParser_SimpleParseFileFlags (fonction C)

PyParser_SimpleParseString (fonction C)

PyParser_SimpleParseStringFlags (fonction C)

PyParser_SimpleParseStringFlagsFilename (fonction C)

PyPI

(see Python Package Index (PyPI))

PyProperty_Type (variable C)

PyRun_AnyFile (fonction C)

PyRun_AnyFileEx (fonction C)

PyRun_AnyFileExFlags (fonction C)

PyRun_AnyFileFlags (fonction C)

PyRun_File (fonction C)

PyRun_FileEx (fonction C)

PyRun_FileExFlags (fonction C)

PyRun_FileFlags (fonction C)

PyRun_InteractiveLoop (fonction C)

PyRun_InteractiveLoopFlags (fonction C)

PyRun_InteractiveOne (fonction C)

PyRun_InteractiveOneFlags (fonction C)

PyRun_SimpleFile (fonction C)

PyRun_SimpleFileEx (fonction C)

PyRun_SimpleFileExFlags (fonction C)

PyRun_SimpleString (fonction C)

PyRun_SimpleStringFlags (fonction C)

PyRun_String (fonction C)

PyRun_StringFlags (fonction C)

PySeqIter_Check (fonction C)

PySeqIter_New (fonction C)

PySeqIter_Type (variable C)

PySequence_Check (fonction C)

PySequence_Concat (fonction C)

PySequence_Contains (fonction C)

PySequence_Count (fonction C)

PySequence_DelItem (fonction C)

PySequence_DelSlice (fonction C)

PySequence_Fast (fonction C)

PySequence_Fast_GET_ITEM (fonction C)

PySequence_Fast_GET_SIZE (fonction C)

PySequence_Fast_ITEMS (fonction C)

PySequence_GetItem (fonction C)

PySequence_GetItem()

PySequence_GetSlice (fonction C)

PySequence_Index (fonction C)

PySequence_InPlaceConcat (fonction C)

PySequence_InPlaceRepeat (fonction C)

PySequence_ITEM (fonction C)

PySequence_Length (fonction C)

PySequence_List (fonction C)

PySequence_Repeat (fonction C)

PySequence_SetItem (fonction C)

PySequence_SetSlice (fonction C)

PySequence_Size (fonction C)

PySequence_Tuple (fonction C)

PySequenceMethods (type C)

PySequenceMethods.sq_ass_item (membre C)

PySequenceMethods.sq_concat (membre C)

PySequenceMethods.sq_contains (membre C)

PySequenceMethods.sq_inplace_concat (membre C)

PySequenceMethods.sq_inplace_repeat (membre C)

PySequenceMethods.sq_item (membre C)

PySequenceMethods.sq_length (membre C)

PySequenceMethods.sq_repeat (membre C)

PySet_Add (fonction C)

PySet_Check (fonction C)

PySet_Clear (fonction C)

PySet_ClearFreeList (fonction C)

PySet_Contains (fonction C)

PySet_Discard (fonction C)

PySet_GET_SIZE (fonction C)

PySet_New (fonction C)

PySet_Pop (fonction C)

PySet_Size (fonction C)

PySet_Type (variable C)

PySetObject (type C)

PySignal_SetWakeupFd (fonction C)

PySlice_Check (fonction C)

PySlice_GetIndices (fonction C)

PySlice_GetIndicesEx (fonction C)

PySlice_New (fonction C)

PySlice_Type (variable C)

PyState_AddModule (fonction C)

PyState_FindModule (fonction C)

PyState_RemoveModule (fonction C)

PyStructSequence_Desc (type C)

PyStructSequence_Field (type C)

PyStructSequence_GET_ITEM (fonction C)

PyStructSequence_GetItem (fonction C)

PyStructSequence_InitType (fonction C)

PyStructSequence_InitType2 (fonction C)

PyStructSequence_New (fonction C)

PyStructSequence_NewType (fonction C)

PyStructSequence_SET_ITEM (fonction C)

PyStructSequence_SetItem (fonction C)

PyStructSequence_UnnamedField (variable C)

PySys_AddWarnOption (fonction C)

PySys_AddWarnOptionUnicode (fonction C)

PySys_AddXOption (fonction C)

PySys_FormatStderr (fonction C)

PySys_FormatStdout (fonction C)

PySys_GetObject (fonction C)

PySys_GetXOptions (fonction C)

PySys_ResetWarnOptions (fonction C)

PySys_SetArgv (fonction C)

PySys_SetArgv()

PySys_SetArgvEx (fonction C)

PySys_SetArgvEx(), [1]

PySys_SetObject (fonction C)

PySys_SetPath (fonction C)

PySys_WriteStderr (fonction C)

PySys_WriteStdout (fonction C)

Python 3000

Python Editor

Python Enhancement Proposals

PEP 1

PEP 100

PEP 11, [1], [2], [3]

PEP 205, [1]

PEP 207

PEP 208

PEP 217

PEP 218, [1], [2]

PEP 227, [1], [2]

PEP 229

PEP 230, [1]

PEP 232

PEP 234

PEP 235

PEP 236, [1]

PEP 237, [1], [2], [3], [4], [5]

PEP 238, [1], [2], [3], [4], [5]

PEP 241

PEP 243

PEP 247

PEP 249, [1], [2], [3]

PEP 252, [1]

PEP 253, [1], [2], [3], [4]

PEP 255, [1], [2], [3], [4], [5]

PEP 261, [1]

PEP 263, [1], [2], [3], [4], [5]

PEP 264

PEP 273, [1], [2]

PEP 274

PEP 275

PEP 277

PEP 278, [1]

PEP 279

PEP 282, [1], [2], [3]

PEP 285, [1]

PEP 288

PEP 289, [1], [2]

PEP 292, [1]

PEP 293

PEP 3000

PEP 301, [1]

PEP 302, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20], [21], [22], [23], [24], [25], [26]

PEP 305, [1]

PEP 307, [1], [2], [3]

PEP 308, [1], [2]

PEP 309

PEP 3100

PEP 3101, [1], [2], [3], [4]

PEP 3102

PEP 3104, [1]

PEP 3105, [1], [2]

PEP 3106

PEP 3107, [1], [2], [3]

PEP 3108, [1], [2]

PEP 3109, [1]

PEP 3110, [1], [2]

PEP 3111

PEP 3112, [1]

PEP 3113

PEP 3114

PEP 3115, [1], [2], [3]

PEP 3116, [1], [2]

PEP 3118, [1], [2], [3], [4], [5]

PEP 3119, [1], [2], [3], [4], [5]

PEP 3120, [1], [2]

PEP 3121, [1], [2]

PEP 3123

PEP 3127

PEP 3129, [1]

PEP 3131, [1], [2]

PEP 3132, [1]

PEP 3134, [1], [2]

PEP 3135, [1]

PEP 3137

PEP 3138

PEP 314, [1]

PEP 3141, [1], [2]

PEP 3144

PEP 3147, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20], [21]

PEP 3148, [1]

PEP 3149, [1]

PEP 3151, [1], [2], [3], [4], [5]

PEP 3153

PEP 3154, [1], [2]

PEP 3155, [1]

PEP 3156, [1], [2], [3], [4], [5]

PEP 318, [1], [2], [3]

PEP 322, [1]

PEP 324, [1]

PEP 325

PEP 327

PEP 328, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10]

PEP 331

PEP 333, [1]

PEP 3333, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14]

PEP 338, [1], [2], [3]

PEP 339

PEP 341

PEP 342, [1], [2], [3], [4], [5], [6]

PEP 343, [1], [2], [3], [4], [5], [6]

PEP 347

PEP 352, [1], [2]

PEP 353, [1], [2]

PEP 356

PEP 357

PEP 361

PEP 362, [1], [2], [3]

PEP 366, [1], [2], [3], [4], [5], [6]

PEP 370, [1], [2], [3], [4]

PEP 371

PEP 372, [1]

PEP 373

PEP 378, [1], [2]

PEP 380, [1], [2], [3]

PEP 383, [1], [2], [3], [4]

PEP 384, [1]

PEP 385

PEP 389, [1]

PEP 391, [1]

PEP 392

PEP 393, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10]

PEP 395

PEP 397, [1], [2], [3]

PEP 398

PEP 4

PEP 405, [1]

PEP 409

PEP 411, [1], [2], [3], [4]

PEP 412

PEP 414, [1]

PEP 418

PEP 420, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11]

PEP 421, [1], [2]

PEP 424, [1]

PEP 427

PEP 428, [1], [2]

PEP 429

PEP 434

PEP 435, [1], [2]

PEP 436, [1], [2]

PEP 441, [1]

PEP 442, [1], [2], [3], [4], [5], [6]

PEP 443, [1], [2]

PEP 445, [1], [2], [3]

PEP 446, [1], [2], [3]

PEP 448, [1], [2], [3], [4]

PEP 450, [1], [2]

PEP 451, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12]

PEP 453, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10]

PEP 454, [1], [2]

PEP 456, [1]

PEP 461, [1], [2]

PEP 465, [1], [2]

PEP 466, [1], [2], [3]

PEP 468, [1]

PEP 471, [1]

PEP 475, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20], [21], [22], [23], [24], [25], [26]

PEP 476

PEP 477

PEP 478

PEP 479, [1], [2]

PEP 483, [1]

PEP 484, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16]

PEP 485, [1], [2], [3]

PEP 486, [1]

PEP 487, [1], [2], [3]

PEP 488, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12]

PEP 489, [1], [2], [3], [4], [5], [6], [7], [8], [9]

PEP 492, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20]

PEP 493

PEP 494

PEP 495, [1]

PEP 498, [1], [2], [3]

PEP 5

PEP 506, [1]

PEP 511

PEP 515, [1], [2]

PEP 519, [1]

PEP 520

PEP 523, [1]

PEP 524, [1], [2], [3], [4], [5]

PEP 525, [1], [2], [3], [4], [5], [6]

PEP 526, [1], [2], [3], [4], [5], [6], [7]

PEP 528

PEP 529, [1], [2], [3], [4]

PEP 530, [1], [2]

PEP 628, [1]

PEP 7

PEP 8, [1], [2], [3], [4]

Python Package Index (PyPI)

.pypirc file

PYTHON*, [1], [2]

python.function.entry (fonction C)

python.function.return (fonction C)

python_branch() (dans le module platform)

python_build() (dans le module platform)

python_compiler() (dans le module platform)

PYTHON_DOM

python_implementation() (dans le module platform)

python_revision() (dans le module platform)

python_version() (dans le module platform)

python_version_tuple() (dans le module platform)

PYTHONASYNCIODEBUG, [1]

PYTHONCASEOK

PYTHONDEBUG

PYTHONDOCS

PYTHONDONDONTWRITEBYTECODE

PYTHONDONTWRITEBYTECODE, [1], [2], [3]

PYTHONDUMPREFS

PYTHONFAULTHANDLER, [1]

PYTHONHASHSEED, [1], [2], [3], [4]

PYTHONHOME, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13]

PYTHONINSPECT, [1]

PYTHONIOENCODING, [1], [2], [3], [4]

Pythonique

PYTHONLEGACYWINDOWSFSENCODING, [1]

PYTHONLEGACYWINDOWSSTDIO, [1]

PYTHONMALLOC, [1], [2], [3], [4], [5]

PYTHONMALLOCSTATS, [1]

PYTHONNOUSERSITE, [1], [2]

PYTHONOPTIMIZE

PYTHONPATH, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20], [21], [22]

PYTHONSHOWALLOCCOUNT

PYTHONSHOWREFCOUNT

PYTHONSTARTUP, [1], [2], [3], [4], [5], [6], [7], [8]

PYTHONTRACEMALLOC, [1], [2]

PYTHONUNBUFFERED

PYTHONUSERBASE, [1], [2]

PYTHONVERBOSE

PYTHONWARNINGS, [1], [2], [3]

PyThreadState, [1]

(type C)

PyThreadState_Clear (fonction C)

PyThreadState_Delete (fonction C)

PyThreadState_Get (fonction C)

PyThreadState_GetDict (fonction C)

PyThreadState_New (fonction C)

PyThreadState_Next (fonction C)

PyThreadState_SetAsyncExc (fonction C)

PyThreadState_Swap (fonction C)

PyTime_Check (fonction C)

PyTime_CheckExact (fonction C)

PyTime_FromTime (fonction C)

PyTrace_C_CALL (variable C)

PyTrace_C_EXCEPTION (variable C)

PyTrace_C_RETURN (variable C)

PyTrace_CALL (variable C)

PyTrace_EXCEPTION (variable C)

PyTrace_LINE (variable C)

PyTrace_RETURN (variable C)

PyTuple_Check (fonction C)

PyTuple_CheckExact (fonction C)

PyTuple_ClearFreeList (fonction C)

PyTuple_GET_ITEM (fonction C)

PyTuple_GET_SIZE (fonction C)

PyTuple_GetItem (fonction C)

PyTuple_GetSlice (fonction C)

PyTuple_New (fonction C)

PyTuple_Pack (fonction C)

PyTuple_SET_ITEM (fonction C)

PyTuple_SetItem (fonction C)

PyTuple_SetItem()

PyTuple_Size (fonction C)

PyTuple_Type (variable C)

PyTupleObject (type C)

PyType_Check (fonction C)

PyType_CheckExact (fonction C)

PyType_ClearCache (fonction C)

PyType_FromSpec (fonction C)

PyType_FromSpecWithBases (fonction C)

PyType_GenericAlloc (fonction C)

PyType_GenericNew (fonction C)

PyType_GetFlags (fonction C)

PyType_GetSlot (fonction C)

PyType_HasFeature (fonction C)

PyType_IS_GC (fonction C)

PyType_IsSubtype (fonction C)

PyType_Modified (fonction C)

PyType_Ready (fonction C)

PyType_Type (variable C)

PyTypeObject (type C)

PyTypeObject.tp_alloc (membre C)

PyTypeObject.tp_allocs (membre C)

PyTypeObject.tp_as_buffer (membre C)

PyTypeObject.tp_base (membre C)

PyTypeObject.tp_bases (membre C)

PyTypeObject.tp_basicsize (membre C)

PyTypeObject.tp_cache (membre C)

PyTypeObject.tp_call (membre C)

PyTypeObject.tp_clear (membre C)

PyTypeObject.tp_dealloc (membre C)

PyTypeObject.tp_descr_get (membre C)

PyTypeObject.tp_descr_set (membre C)

PyTypeObject.tp_dict (membre C)

PyTypeObject.tp_dictoffset (membre C)

PyTypeObject.tp_doc (membre C)

PyTypeObject.tp_finalize (membre C)

PyTypeObject.tp_flags (membre C)

PyTypeObject.tp_free (membre C)

PyTypeObject.tp_frees (membre C)

PyTypeObject.tp_getattr (membre C)

PyTypeObject.tp_getattro (membre C)

PyTypeObject.tp_getset (membre C)

PyTypeObject.tp_hash (membre C)

PyTypeObject.tp_init (membre C)

PyTypeObject.tp_is_gc (membre C)

PyTypeObject.tp_itemsize (membre C)

PyTypeObject.tp_iter (membre C)

PyTypeObject.tp_iternext (membre C)

PyTypeObject.tp_maxalloc (membre C)

PyTypeObject.tp_members (membre C)

PyTypeObject.tp_methods (membre C)

PyTypeObject.tp_mro (membre C)

PyTypeObject.tp_name (membre C)

PyTypeObject.tp_new (membre C)

PyTypeObject.tp_next (membre C)

PyTypeObject.tp_print (membre C)

PyTypeObject.tp_repr (membre C)

PyTypeObject.tp_richcompare (membre C)

PyTypeObject.tp_setattr (membre C)

PyTypeObject.tp_setattro (membre C)

PyTypeObject.tp_str (membre C)

PyTypeObject.tp_subclasses (membre C)

PyTypeObject.tp_traverse (membre C)

PyTypeObject.tp_weaklist (membre C)

PyTypeObject.tp_weaklistoffset (membre C)

PyTZInfo_Check (fonction C)

PyTZInfo_CheckExact (fonction C)

PyUnicode_1BYTE_DATA (fonction C)

PyUnicode_1BYTE_KIND (macro C)

PyUnicode_2BYTE_DATA (fonction C)

PyUnicode_2BYTE_KIND (macro C)

PyUnicode_4BYTE_DATA (fonction C)

PyUnicode_4BYTE_KIND (macro C)

PyUnicode_AS_DATA (fonction C)

PyUnicode_AS_UNICODE (fonction C)

PyUnicode_AsASCIIString (fonction C)

PyUnicode_AsCharmapString (fonction C)

PyUnicode_AsEncodedString (fonction C)

PyUnicode_AsLatin1String (fonction C)

PyUnicode_AsMBCSString (fonction C)

PyUnicode_AsRawUnicodeEscapeString (fonction C)

PyUnicode_AsUCS4 (fonction C)

PyUnicode_AsUCS4Copy (fonction C)

PyUnicode_AsUnicode (fonction C)

PyUnicode_AsUnicodeAndSize (fonction C)

PyUnicode_AsUnicodeCopy (fonction C)

PyUnicode_AsUnicodeEscapeString (fonction C)

PyUnicode_AsUTF16String (fonction C)

PyUnicode_AsUTF32String (fonction C)

PyUnicode_AsUTF8 (fonction C)

PyUnicode_AsUTF8AndSize (fonction C)

PyUnicode_AsUTF8String (fonction C)

PyUnicode_AsWideChar (fonction C)

PyUnicode_AsWideCharString (fonction C)

PyUnicode_Check (fonction C)

PyUnicode_CheckExact (fonction C)

PyUnicode_ClearFreeList (fonction C)

PyUnicode_Compare (fonction C)

PyUnicode_CompareWithASCIIString (fonction C)

PyUnicode_Concat (fonction C)

PyUnicode_Contains (fonction C)

PyUnicode_CopyCharacters (fonction C)

PyUnicode_Count (fonction C)

PyUnicode_DATA (fonction C)

PyUnicode_Decode (fonction C)

PyUnicode_DecodeASCII (fonction C)

PyUnicode_DecodeCharmap (fonction C)

PyUnicode_DecodeFSDefault (fonction C)

PyUnicode_DecodeFSDefaultAndSize (fonction C)

PyUnicode_DecodeLatin1 (fonction C)

PyUnicode_DecodeLocale (fonction C)

PyUnicode_DecodeLocaleAndSize (fonction C)

PyUnicode_DecodeMBCS (fonction C)

PyUnicode_DecodeMBCSStateful (fonction C)

PyUnicode_DecodeRawUnicodeEscape (fonction C)

PyUnicode_DecodeUnicodeEscape (fonction C)

PyUnicode_DecodeUTF16 (fonction C)

PyUnicode_DecodeUTF16Stateful (fonction C)

PyUnicode_DecodeUTF32 (fonction C)

PyUnicode_DecodeUTF32Stateful (fonction C)

PyUnicode_DecodeUTF7 (fonction C)

PyUnicode_DecodeUTF7Stateful (fonction C)

PyUnicode_DecodeUTF8 (fonction C)

PyUnicode_DecodeUTF8Stateful (fonction C)

PyUnicode_Encode (fonction C)

PyUnicode_EncodeASCII (fonction C)

PyUnicode_EncodeCharmap (fonction C)

PyUnicode_EncodeCodePage (fonction C)

PyUnicode_EncodeFSDefault (fonction C)

PyUnicode_EncodeLatin1 (fonction C)

PyUnicode_EncodeLocale (fonction C)

PyUnicode_EncodeMBCS (fonction C)

PyUnicode_EncodeRawUnicodeEscape (fonction C)

PyUnicode_EncodeUnicodeEscape (fonction C)

PyUnicode_EncodeUTF16 (fonction C)

PyUnicode_EncodeUTF32 (fonction C)

PyUnicode_EncodeUTF7 (fonction C)

PyUnicode_EncodeUTF8 (fonction C)

PyUnicode_Fill (fonction C)

PyUnicode_Find (fonction C)

PyUnicode_FindChar (fonction C)

PyUnicode_Format (fonction C)

PyUnicode_FromEncodedObject (fonction C)

PyUnicode_FromFormat (fonction C)

PyUnicode_FromFormatV (fonction C)

PyUnicode_FromKindAndData (fonction C)

PyUnicode_FromObject (fonction C)

PyUnicode_FromString (fonction C)

PyUnicode_FromString()

PyUnicode_FromStringAndSize (fonction C)

PyUnicode_FromUnicode (fonction C)

PyUnicode_FromWideChar (fonction C)

PyUnicode_FSConverter (fonction C)

PyUnicode_FSDecoder (fonction C)

PyUnicode_GET_DATA_SIZE (fonction C)

PyUnicode_GET_LENGTH (fonction C)

PyUnicode_GET_SIZE (fonction C)

PyUnicode_GetLength (fonction C)

PyUnicode_GetSize (fonction C)

PyUnicode_InternFromString (fonction C)

PyUnicode_InternInPlace (fonction C)

PyUnicode_Join (fonction C)

PyUnicode_KIND (fonction C)

PyUnicode_MAX_CHAR_VALUE (fonction C)

PyUnicode_New (fonction C)

PyUnicode_READ (fonction C)

PyUnicode_READ_CHAR (fonction C)

PyUnicode_ReadChar (fonction C)

PyUnicode_READY (fonction C)

PyUnicode_Replace (fonction C)

PyUnicode_RichCompare (fonction C)

PyUnicode_Split (fonction C)

PyUnicode_Splitlines (fonction C)

PyUnicode_Substring (fonction C)

PyUnicode_Tailmatch (fonction C)

PyUnicode_TransformDecimalToASCII (fonction C)

PyUnicode_Translate (fonction C), [1]

PyUnicode_TranslateCharmap (fonction C)

PyUnicode_Type (variable C)

PyUnicode_WCHAR_KIND (macro C)

PyUnicode_WRITE (fonction C)

PyUnicode_WriteChar (fonction C)

PyUnicodeDecodeError_Create (fonction C)

PyUnicodeDecodeError_GetEncoding (fonction C)

PyUnicodeDecodeError_GetEnd (fonction C)

PyUnicodeDecodeError_GetObject (fonction C)

PyUnicodeDecodeError_GetReason (fonction C)

PyUnicodeDecodeError_GetStart (fonction C)

PyUnicodeDecodeError_SetEnd (fonction C)

PyUnicodeDecodeError_SetReason (fonction C)

PyUnicodeDecodeError_SetStart (fonction C)

PyUnicodeEncodeError_Create (fonction C)

PyUnicodeEncodeError_GetEncoding (fonction C)

PyUnicodeEncodeError_GetEnd (fonction C)

PyUnicodeEncodeError_GetObject (fonction C)

PyUnicodeEncodeError_GetReason (fonction C)

PyUnicodeEncodeError_GetStart (fonction C)

PyUnicodeEncodeError_SetEnd (fonction C)

PyUnicodeEncodeError_SetReason (fonction C)

PyUnicodeEncodeError_SetStart (fonction C)

PyUnicodeObject (type C)

PyUnicodeTranslateError_Create (fonction C)

PyUnicodeTranslateError_GetEnd (fonction C)

PyUnicodeTranslateError_GetObject (fonction C)

PyUnicodeTranslateError_GetReason (fonction C)

PyUnicodeTranslateError_GetStart (fonction C)

PyUnicodeTranslateError_SetEnd (fonction C)

PyUnicodeTranslateError_SetReason (fonction C)

PyUnicodeTranslateError_SetStart (fonction C)

PyVarObject (type C)

PyVarObject.ob_size (membre C)

PyVarObject_HEAD_INIT (macro C)

PyWeakref_Check (fonction C)

PyWeakref_CheckProxy (fonction C)

PyWeakref_CheckRef (fonction C)

PyWeakref_GET_OBJECT (fonction C)

PyWeakref_GetObject (fonction C)

PyWeakref_NewProxy (fonction C)

PyWeakref_NewRef (fonction C)

PyWrapper_New (fonction C)

PyZipFile (classe dans zipfile)

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Index – Q

qiflush() (dans le module curses)

QName (classe dans xml.etree.ElementTree)

qsize() (méthode asyncio.Queue)

(méthode multiprocessing.Queue)

(méthode queue.Queue)

quantize() (méthode decimal.Context)

(méthode decimal.Decimal)

QueryInfoKey() (dans le module winreg)

QueryReflectionKey() (dans le module winreg)

QueryValue() (dans le module winreg)

QueryValueEx() (dans le module winreg)

queue (attribut sched.scheduler)

Queue (classe dans asyncio)

(classe dans multiprocessing)

(classe dans queue)

queue (module)

Queue() (méthode multiprocessing.managers.SyncManager)

QueueEmpty

QueueFull

QueueHandler (classe dans logging.handlers)

QueueListener (classe dans logging.handlers)

quick_ratio() (méthode difflib.SequenceMatcher)

quit (pdb command)

(variable de base)

quit() (méthode ftplib.FTP)

(méthode nntplib.NNTP)

(méthode poplib.POP3)

(méthode smtplib.SMTP)

quopri (module)

quote() (dans le module email.utils)

(dans le module shlex)

(dans le module urllib.parse)

QUOTE_ALL (dans le module csv)

quote_from_bytes() (dans le module urllib.parse)

QUOTE_MINIMAL (dans le module csv)

QUOTE_NONE (dans le module csv)

QUOTE_NONNUMERIC (dans le module csv)

quote_plus() (dans le module urllib.parse)

quoteattr() (dans le module xml.sax.saxutils)

quotechar (attribut csv.Dialect)

quoted-printable

encoding

quotes (attribut shlex.shlex)

quoting (attribut csv.Dialect)

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© Copyright 2001-2020, Python Software Foundation.
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Index – R

r"

raw string literal

r'

raw string literal

R_OK (dans le module os)

radians() (dans le module math)

(dans le module turtle)

RadioButtonGroup (classe dans msilib)

radiogroup() (méthode msilib.Dialog)

radix() (méthode decimal.Context)

(méthode decimal.Decimal)

RADIXCHAR (dans le module locale)

raise

état, [1]

raise (2to3 fixer)

raise an exception

raise_on_defect (attribut email.policy.Policy)

RAISE_VARARGS (opcode)

raising

exception

ramasse-miettes

RAND_add() (dans le module ssl)

RAND_bytes() (dans le module ssl)

RAND_egd() (dans le module ssl)

RAND_pseudo_bytes() (dans le module ssl)

RAND_status() (dans le module ssl)

randbelow() (dans le module secrets)

randbits() (dans le module secrets)

randint() (dans le module random)

random (module)

random() (dans le module random)

randrange() (dans le module random)

range

fonction de base

objet

range (classe de base)

RARROW (dans le module token)

ratecv() (dans le module audioop)

ratio() (méthode difflib.SequenceMatcher)

Rational (classe dans numbers)

raw (attribut io.BufferedIOBase)

raw string

raw() (dans le module curses)

raw_data_manager (dans le module email.contentmanager)

raw_decode() (méthode json.JSONDecoder)

raw_input (2to3 fixer)

raw_input() (méthode code.InteractiveConsole)

RawArray() (dans le module multiprocessing.sharedctypes)

RawConfigParser (classe dans configparser)

RawDescriptionHelpFormatter (classe dans argparse)

RawIOBase (classe dans io)

RawPen (classe dans turtle)

RawTextHelpFormatter (classe dans argparse)

RawTurtle (classe dans turtle)

RawValue() (dans le module multiprocessing.sharedctypes)

RBRACE (dans le module token)

rcpttos (attribut smtpd.SMTPChannel)

re

module, [1]

re (attribut re.match)

(module)

read() (dans le module os)

(méthode asyncio.StreamReader)

(méthode chunk.Chunk)

(méthode codecs.StreamReader)

(méthode configparser.ConfigParser)

(méthode http.client.HTTPResponse)

(méthode imaplib.IMAP4)

(méthode io.BufferedIOBase)

(méthode io.BufferedReader)

(méthode io.RawIOBase)

(méthode io.TextIOBase)

(méthode mimetypes.MimeTypes)

(méthode mmap.mmap)

(méthode ossaudiodev.oss_audio_device)

(méthode ssl.MemoryBIO)

(méthode ssl.SSLSocket)

(méthode urllib.robotparser.RobotFileParser)

(méthode zipfile.ZipFile)

read1() (méthode io.BufferedIOBase)

(méthode io.BufferedReader)

(méthode io.BytesIO)

read_all() (méthode telnetlib.Telnet)

read_byte() (méthode mmap.mmap)

read_bytes() (méthode pathlib.Path)

read_dict() (méthode configparser.ConfigParser)

read_eager() (méthode telnetlib.Telnet)

read_environ() (dans le module wsgiref.handlers)

read_events() (méthode xml.etree.ElementTree.XMLPullParser)

read_file() (méthode configparser.ConfigParser)

read_history_file() (dans le module readline)

read_init_file() (dans le module readline)

read_lazy() (méthode telnetlib.Telnet)

read_mime_types() (dans le module mimetypes)

READ_RESTRICTED

read_sb_data() (méthode telnetlib.Telnet)

read_some() (méthode telnetlib.Telnet)

read_string() (méthode configparser.ConfigParser)

read_text() (méthode pathlib.Path)

read_token() (méthode shlex.shlex)

read_until() (méthode telnetlib.Telnet)

read_very_eager() (méthode telnetlib.Telnet)

read_very_lazy() (méthode telnetlib.Telnet)

read_windows_registry() (méthode mimetypes.MimeTypes)

READABLE (dans le module tkinter)

readable() (méthode asyncore.dispatcher)

(méthode io.IOBase)

readall() (méthode io.RawIOBase)

reader() (dans le module csv)

ReadError

readexactly() (méthode asyncio.StreamReader)

readfp() (méthode configparser.ConfigParser)

(méthode mimetypes.MimeTypes)

readframes() (méthode aifc.aifc)

(méthode sunau.AU_read)

(méthode wave.Wave_read)

readinto() (méthode http.client.HTTPResponse)

(méthode io.BufferedIOBase)

(méthode io.RawIOBase)

readinto1() (méthode io.BufferedIOBase)

(méthode io.BytesIO)

readline (module)

readline() (méthode asyncio.StreamReader)

(méthode codecs.StreamReader)

(méthode distutils.text_file.TextFile)

(méthode imaplib.IMAP4)

(méthode io.IOBase)

(méthode io.TextIOBase)

(méthode mmap.mmap)

readlines() (méthode codecs.StreamReader)

(méthode distutils.text_file.TextFile)

(méthode io.IOBase)

readlink() (dans le module os)

readmodule() (dans le module pyclbr)

readmodule_ex() (dans le module pyclbr)

READONLY

readonly (attribut memoryview)

readPlist() (dans le module plistlib)

readPlistFromBytes() (dans le module plistlib)

ReadTransport (classe dans asyncio)

readuntil() (méthode asyncio.StreamReader)

readv() (dans le module os)

ready() (méthode multiprocessing.pool.AsyncResult)

real (attribut numbers.Complex)

Real (classe dans numbers)

Real Media File Format

real_quick_ratio() (méthode difflib.SequenceMatcher)

realloc()

realpath() (dans le module os.path)

reason (attribut http.client.HTTPResponse)

(attribut ssl.SSLError)

(attribut UnicodeError)

(attribut urllib.error.HTTPError)

(attribut urllib.error.URLError)

reattach() (méthode tkinter.ttk.Treeview)

rebinding

name

reccontrols() (méthode ossaudiodev.oss_mixer_device)

received_data (attribut smtpd.SMTPChannel)

received_lines (attribut smtpd.SMTPChannel)

recent() (méthode imaplib.IMAP4)

records (attribut unittest.TestCase)

rect() (dans le module cmath)

rectangle() (dans le module curses.textpad)

RecursionError

recursive_repr() (dans le module reprlib)

recv() (méthode asyncore.dispatcher)

(méthode multiprocessing.connection.Connection)

(méthode socket.socket)

recv_bytes() (méthode multiprocessing.connection.Connection)

recv_bytes_into() (méthode multiprocessing.connection.Connection)

recv_into() (méthode socket.socket)

recvfrom() (méthode socket.socket)

recvfrom_into() (méthode socket.socket)

recvmsg() (méthode socket.socket)

recvmsg_into() (méthode socket.socket)

redirect_request() (méthode urllib.request.HTTPRedirectHandler)

redirect_stderr() (dans le module contextlib)

redirect_stdout() (dans le module contextlib)

redisplay() (dans le module readline)

redrawln() (méthode curses.window)

redrawwin() (méthode curses.window)

reduce (2to3 fixer)

reduce() (dans le module functools)

ref (classe dans weakref)

reference

attribute

reference counting

ReferenceError, [1]

ReferenceType (dans le module weakref)

refold_source (attribut email.policy.EmailPolicy)

refresh() (méthode curses.window)

REG_BINARY (dans le module winreg)

REG_DWORD (dans le module winreg)

REG_DWORD_BIG_ENDIAN (dans le module winreg)

REG_DWORD_LITTLE_ENDIAN (dans le module winreg)

REG_EXPAND_SZ (dans le module winreg)

REG_FULL_RESOURCE_DESCRIPTOR (dans le module winreg)

REG_LINK (dans le module winreg)

REG_MULTI_SZ (dans le module winreg)

REG_NONE (dans le module winreg)

REG_QWORD (dans le module winreg)

REG_QWORD_LITTLE_ENDIAN (dans le module winreg)

REG_RESOURCE_LIST (dans le module winreg)

REG_RESOURCE_REQUIREMENTS_LIST (dans le module winreg)

REG_SZ (dans le module winreg)

register() (dans le module atexit)

(dans le module codecs)

(dans le module faulthandler)

(dans le module webbrowser)

(méthode abc.ABCMeta)

(méthode multiprocessing.managers.BaseManager)

(méthode select.devpoll)

(méthode select.epoll)

(méthode select.poll)

(méthode selectors.BaseSelector)

register_adapter() (dans le module sqlite3)

register_archive_format() (dans le module shutil)

register_converter() (dans le module sqlite3)

register_defect() (méthode email.policy.Policy)

register_dialect() (dans le module csv)

register_error() (dans le module codecs)

register_function() (méthode xmlrpc.server.CGIXMLRPCRequestHandler)

(méthode xmlrpc.server.SimpleXMLRPCServer)

register_instance() (méthode xmlrpc.server.CGIXMLRPCRequestHandler)

(méthode xmlrpc.server.SimpleXMLRPCServer)

register_introspection_functions() (méthode xmlrpc.server.CGIXMLRPCRequestHandler)

(méthode xmlrpc.server.SimpleXMLRPCServer)

register_multicall_functions() (méthode xmlrpc.server.CGIXMLRPCRequestHandler)

(méthode xmlrpc.server.SimpleXMLRPCServer)

register_namespace() (dans le module xml.etree.ElementTree)

register_optionflag() (dans le module doctest)

register_shape() (dans le module turtle)

register_unpack_format() (dans le module shutil)

registerDOMImplementation() (dans le module xml.dom)

registerResult() (dans le module unittest)

regular

package

relative

import

URL

relative_to() (méthode pathlib.PurePath)

release() (dans le module platform)

(méthode _thread.lock)

(méthode asyncio.Condition)

(méthode asyncio.Lock)

(méthode asyncio.Semaphore)

(méthode logging.Handler)

(méthode memoryview)

(méthode multiprocessing.Lock)

(méthode multiprocessing.RLock)

(méthode threading.Condition)

(méthode threading.Lock)

(méthode threading.RLock)

(méthode threading.Semaphore)

release_lock() (dans le module imp)

reload (2to3 fixer)

reload() (dans le module imp)

(dans le module importlib)

relpath() (dans le module os.path)

remainder() (méthode decimal.Context)

remainder_near() (méthode decimal.Context)

(méthode decimal.Decimal)

RemoteDisconnected

remove() (dans le module os)

(méthode array.array)

(méthode collections.deque)

(méthode frozenset)

(méthode mailbox.Mailbox)

(méthode mailbox.MH)

(méthode xml.etree.ElementTree.Element)

(sequence method)

remove_done_callback() (méthode asyncio.Future)

remove_flag() (méthode mailbox.MaildirMessage)

(méthode mailbox.mboxMessage)

(méthode mailbox.MMDFMessage)

remove_folder() (méthode mailbox.Maildir)

(méthode mailbox.MH)

remove_header() (méthode urllib.request.Request)

remove_history_item() (dans le module readline)

remove_label() (méthode mailbox.BabylMessage)

remove_option() (méthode configparser.ConfigParser)

(méthode optparse.OptionParser)

remove_pyc() (méthode msilib.Directory)

remove_reader() (méthode asyncio.AbstractEventLoop)

remove_section() (méthode configparser.ConfigParser)

remove_sequence() (méthode mailbox.MHMessage)

remove_signal_handler() (méthode asyncio.AbstractEventLoop)

remove_tree() (dans le module distutils.dir_util)

remove_writer() (méthode asyncio.AbstractEventLoop)

removeAttribute() (méthode xml.dom.Element)

removeAttributeNode() (méthode xml.dom.Element)

removeAttributeNS() (méthode xml.dom.Element)

removeChild() (méthode xml.dom.Node)

removedirs() (dans le module os)

removeFilter() (méthode logging.Handler)

(méthode logging.Logger)

removeHandler() (dans le module unittest)

(méthode logging.Logger)

removeResult() (dans le module unittest)

removexattr() (dans le module os)

rename() (dans le module os)

(méthode ftplib.FTP)

(méthode imaplib.IMAP4)

(méthode pathlib.Path)

renames (2to3 fixer)

renames() (dans le module os)

reopenIfNeeded() (méthode logging.handlers.WatchedFileHandler)

reorganize() (méthode dbm.gnu.gdbm)

repeat() (dans le module itertools)

(dans le module timeit)

(méthode timeit.Timer)

repetition

operation

replace() (dans le module os)

(méthode bytearray)

(méthode bytes)

(méthode curses.panel.Panel)

(méthode datetime.date)

(méthode datetime.datetime)

(méthode datetime.time)

(méthode inspect.Parameter)

(méthode inspect.Signature)

(méthode pathlib.Path)

(méthode str)

replace_errors() (dans le module codecs)

replace_header() (méthode email.message.EmailMessage)

(méthode email.message.Message)

replace_history_item() (dans le module readline)

replace_whitespace (attribut textwrap.TextWrapper)

replaceChild() (méthode xml.dom.Node)

ReplacePackage() (dans le module modulefinder)

report() (méthode filecmp.dircmp)

(méthode modulefinder.ModuleFinder)

REPORT_CDIFF (dans le module doctest)

report_failure() (méthode doctest.DocTestRunner)

report_full_closure() (méthode filecmp.dircmp)

REPORT_NDIFF (dans le module doctest)

REPORT_ONLY_FIRST_FAILURE (dans le module doctest)

report_partial_closure() (méthode filecmp.dircmp)

report_start() (méthode doctest.DocTestRunner)

report_success() (méthode doctest.DocTestRunner)

REPORT_UDIFF (dans le module doctest)

report_unexpected_exception() (méthode doctest.DocTestRunner)

REPORTING_FLAGS (dans le module doctest)

repr

fonction de base, [1], [2], [3]

repr (2to3 fixer)

Repr (classe dans reprlib)

repr() (built-in function)

__repr__() (object method)

repr() (dans le module reprlib)

(fonction de base)

(méthode reprlib.Repr)

repr1() (méthode reprlib.Repr)

representation

integer

reprlib (module)

Request (classe dans urllib.request)

request() (méthode http.client.HTTPConnection)

request_queue_size (attribut socketserver.BaseServer)

request_rate() (méthode urllib.robotparser.RobotFileParser)

request_uri() (dans le module wsgiref.util)

request_version (attribut http.server.BaseHTTPRequestHandler)

RequestHandlerClass (attribut socketserver.BaseServer)

requestline (attribut http.server.BaseHTTPRequestHandler)

requires() (dans le module test.support)

reserved (attribut zipfile.ZipInfo)

reserved word

RESERVED_FUTURE (dans le module uuid)

RESERVED_MICROSOFT (dans le module uuid)

RESERVED_NCS (dans le module uuid)

reset() (dans le module turtle), [1]

(méthode bdb.Bdb)

(méthode codecs.IncrementalDecoder)

(méthode codecs.IncrementalEncoder)

(méthode codecs.StreamReader)

(méthode codecs.StreamWriter)

(méthode html.parser.HTMLParser)

(méthode ossaudiodev.oss_audio_device)

(méthode pipes.Template)

(méthode threading.Barrier)

(méthode xdrlib.Packer)

(méthode xdrlib.Unpacker)

(méthode xml.dom.pulldom.DOMEventStream)

(méthode xml.sax.xmlreader.IncrementalParser)

reset_mock() (méthode unittest.mock.Mock)

reset_prog_mode() (dans le module curses)

reset_shell_mode() (dans le module curses)

resetbuffer() (méthode code.InteractiveConsole)

resetlocale() (dans le module locale)

resetscreen() (dans le module turtle)

resetty() (dans le module curses)

resetwarnings() (dans le module warnings)

resize() (dans le module ctypes)

(méthode curses.window)

(méthode mmap.mmap)

resize_term() (dans le module curses)

resizemode() (dans le module turtle)

resizeterm() (dans le module curses)

resolution (attribut datetime.date)

(attribut datetime.datetime)

(attribut datetime.time)

(attribut datetime.timedelta)

resolve() (méthode pathlib.Path)

resolve_name() (dans le module importlib.util)

resolveEntity() (méthode xml.sax.handler.EntityResolver)

resource (module)

ResourceDenied

ResourceLoader (classe dans importlib.abc)

ResourceWarning

response (attribut nntplib.NNTPError)

response() (méthode imaplib.IMAP4)

ResponseNotReady

responses (attribut http.server.BaseHTTPRequestHandler)

(dans le module http.client)

restart (pdb command)

restore() (dans le module difflib)

RESTRICTED

restricted

execution

restype (attribut ctypes._FuncPtr)

result() (méthode asyncio.Future)

(méthode concurrent.futures.Future)

results() (méthode trace.Trace)

resume_reading() (méthode asyncio.ReadTransport)

resume_writing() (méthode asyncio.BaseProtocol)

retours à la ligne universels

retr() (méthode poplib.POP3)

retrbinary() (méthode ftplib.FTP)

retrieve() (méthode urllib.request.URLopener)

retrlines() (méthode ftplib.FTP)

return

état, [1], [2]

return (pdb command)

return_annotation (attribut inspect.Signature)

return_ok() (méthode http.cookiejar.CookiePolicy)

return_value (attribut unittest.mock.Mock)

RETURN_VALUE (opcode)

returncode (attribut asyncio.asyncio.subprocess.Process)

(attribut subprocess.CalledProcessError)

(attribut subprocess.CompletedProcess)

(attribut subprocess.Popen)

reverse() (dans le module audioop)

(méthode array.array)

(méthode collections.deque)

(sequence method)

reverse_order() (méthode pstats.Stats)

reverse_pointer (attribut ipaddress.IPv4Address)

(attribut ipaddress.IPv6Address)

reversed() (fonction de base)

Reversible (classe dans collections.abc)

(classe dans typing)

revert() (méthode http.cookiejar.FileCookieJar)

rewind() (méthode aifc.aifc)

(méthode sunau.AU_read)

(méthode wave.Wave_read)

RFC

RFC 1014, [1]

RFC 1123

RFC 1321

RFC 1422, [1]

RFC 1521, [1], [2]

RFC 1522, [1], [2]

RFC 1524, [1]

RFC 1730

RFC 1738

RFC 1750

RFC 1766, [1]

RFC 1808, [1], [2]

RFC 1832, [1]

RFC 1869, [1]

RFC 1870, [1], [2]

RFC 1939, [1]

RFC 2033

RFC 2045, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14]

RFC 2045#section-6.8

RFC 2046, [1], [2]

RFC 2047, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12]

RFC 2060, [1]

RFC 2068

RFC 2104, [1]

RFC 2109, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14]

RFC 2183, [1], [2]

RFC 2231, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14]

RFC 2295

RFC 2342, [1]

RFC 2368

RFC 2373, [1], [2]

RFC 2396, [1], [2]

RFC 2397

RFC 2449

RFC 2487

RFC 2518

RFC 2595, [1]

RFC 2616, [1], [2], [3], [4], [5], [6], [7], [8], [9]

RFC 2732, [1], [2]

RFC 2774

RFC 2818, [1]

RFC 2821

RFC 2822, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17]

RFC 2964

RFC 2965, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19]

RFC 2980, [1]

RFC 3056

RFC 3171

RFC 3207

RFC 3229

RFC 3280

RFC 3330

RFC 3339

RFC 3454, [1]

RFC 3490, [1], [2], [3]

RFC 3490#section-3.1

RFC 3492, [1]

RFC 3493

RFC 3501

RFC 3542, [1]

RFC 3548, [1], [2], [3], [4], [5]

RFC 3659

RFC 3879

RFC 3927

RFC 3977, [1], [2], [3], [4]

RFC 3986, [1], [2], [3], [4], [5]

RFC 4086

RFC 4122, [1], [2], [3], [4], [5], [6], [7], [8]

RFC 4180

RFC 4193

RFC 4217

RFC 4291

RFC 4380

RFC 4627, [1]

RFC 4642

RFC 4918, [1], [2], [3], [4]

RFC 4954, [1]

RFC 5161, [1]

RFC 5233, [1]

RFC 5246, [1]

RFC 5280, [1], [2], [3], [4]

RFC 5321, [1], [2], [3], [4]

RFC 5322, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20], [21]

RFC 5424, [1], [2], [3]

RFC 5424#section-6

RFC 5735

RFC 5842, [1]

RFC 5929

RFC 6066, [1], [2]

RFC 6125, [1]

RFC 6152, [1]

RFC 6531, [1], [2], [3], [4], [5], [6], [7], [8]

RFC 6532, [1], [2], [3], [4]

RFC 6585, [1], [2], [3]

RFC 6855, [1], [2], [3]

RFC 6856, [1]

RFC 7159, [1], [2]

RFC 7230, [1]

RFC 7231, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20], [21], [22], [23], [24], [25], [26], [27], [28], [29], [30], [31], [32], [33], [34]

RFC 7232, [1]

RFC 7233, [1]

RFC 7235, [1]

RFC 7238

RFC 7301, [1], [2]

RFC 7525

RFC 7693

RFC 7914

RFC 821, [1]

RFC 822, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11]

RFC 854, [1]

RFC 959, [1]

RFC 977

rfc2109 (attribut http.cookiejar.Cookie)

rfc2109_as_netscape (attribut http.cookiejar.DefaultCookiePolicy)

rfc2965 (attribut http.cookiejar.CookiePolicy)

rfc822_escape() (dans le module distutils.util)

RFC_4122 (dans le module uuid)

rfile (attribut http.server.BaseHTTPRequestHandler)

rfind() (méthode bytearray)

(méthode bytes)

(méthode mmap.mmap)

(méthode str)

rgb_to_hls() (dans le module colorsys)

rgb_to_hsv() (dans le module colorsys)

rgb_to_yiq() (dans le module colorsys)

rglob() (méthode pathlib.Path)

right (attribut filecmp.dircmp)

right() (dans le module turtle)

right_list (attribut filecmp.dircmp)

right_only (attribut filecmp.dircmp)

RIGHTSHIFT (dans le module token)

RIGHTSHIFTEQUAL (dans le module token)

rindex() (méthode bytearray)

(méthode bytes)

(méthode str)

rjust() (méthode bytearray)

(méthode bytes)

(méthode str)

rlcompleter (module)

rlecode_hqx() (dans le module binascii)

rledecode_hqx() (dans le module binascii)

RLIM_INFINITY (dans le module resource)

RLIMIT_AS (dans le module resource)

RLIMIT_CORE (dans le module resource)

RLIMIT_CPU (dans le module resource)

RLIMIT_DATA (dans le module resource)

RLIMIT_FSIZE (dans le module resource)

RLIMIT_MEMLOCK (dans le module resource)

RLIMIT_MSGQUEUE (dans le module resource)

RLIMIT_NICE (dans le module resource)

RLIMIT_NOFILE (dans le module resource)

RLIMIT_NPROC (dans le module resource)

RLIMIT_NPTS (dans le module resource)

RLIMIT_OFILE (dans le module resource)

RLIMIT_RSS (dans le module resource)

RLIMIT_RTPRIO (dans le module resource)

RLIMIT_RTTIME (dans le module resource)

RLIMIT_SBSIZE (dans le module resource)

RLIMIT_SIGPENDING (dans le module resource)

RLIMIT_STACK (dans le module resource)

RLIMIT_SWAP (dans le module resource)

RLIMIT_VMEM (dans le module resource)

RLock (classe dans multiprocessing)

(classe dans threading)

RLock() (méthode multiprocessing.managers.SyncManager)

rmd() (méthode ftplib.FTP)

rmdir() (dans le module os)

(méthode pathlib.Path)

RMFF

rms() (dans le module audioop)

rmtree() (dans le module shutil)

RobotFileParser (classe dans urllib.robotparser)

robots.txt

rollback() (méthode sqlite3.Connection)

ROT_THREE (opcode)

ROT_TWO (opcode)

rotate() (méthode collections.deque)

(méthode decimal.Context)

(méthode decimal.Decimal)

(méthode logging.handlers.BaseRotatingHandler)

RotatingFileHandler (classe dans logging.handlers)

rotation_filename() (méthode logging.handlers.BaseRotatingHandler)

rotator (attribut logging.handlers.BaseRotatingHandler)

round

fonction de base

round() (fonction de base)

ROUND_05UP (dans le module decimal)

ROUND_CEILING (dans le module decimal)

ROUND_DOWN (dans le module decimal)

ROUND_FLOOR (dans le module decimal)

ROUND_HALF_DOWN (dans le module decimal)

ROUND_HALF_EVEN (dans le module decimal)

ROUND_HALF_UP (dans le module decimal)

ROUND_UP (dans le module decimal)

Rounded (classe dans decimal)

Row (classe dans sqlite3)

row_factory (attribut sqlite3.Connection)

rowcount (attribut sqlite3.Cursor)

RPAR (dans le module token)

rpartition() (méthode bytearray)

(méthode bytes)

(méthode str)

rpc_paths (attribut xmlrpc.server.SimpleXMLRPCRequestHandler)

rpop() (méthode poplib.POP3)

rset() (méthode poplib.POP3)

rshift() (dans le module operator)

rsplit() (méthode bytearray)

(méthode bytes)

(méthode str)

RSQB (dans le module token)

rstrip() (méthode bytearray)

(méthode bytes)

(méthode str)

rt() (dans le module turtle)

RTLD_DEEPBIND (dans le module os)

RTLD_GLOBAL (dans le module os)

RTLD_LAZY (dans le module os)

RTLD_LOCAL (dans le module os)

RTLD_NODELETE (dans le module os)

RTLD_NOLOAD (dans le module os)

RTLD_NOW (dans le module os)

ruler (attribut cmd.Cmd)

run (pdb command)

Run script

run() (dans le module pdb)

(dans le module profile)

(dans le module subprocess)

(méthode bdb.Bdb)

(méthode distutils.cmd.Command)

(méthode doctest.DocTestRunner)

(méthode multiprocessing.Process)

(méthode pdb.Pdb)

(méthode profile.Profile)

(méthode sched.scheduler)

(méthode threading.Thread)

(méthode trace.Trace)

(méthode unittest.TestCase)

(méthode unittest.TestSuite)

(méthode unittest.TextTestRunner)

(méthode wsgiref.handlers.BaseHandler)

run_coroutine_threadsafe() (dans le module asyncio)

run_docstring_examples() (dans le module doctest)

run_doctest() (dans le module test.support)

run_forever() (méthode asyncio.AbstractEventLoop)

run_in_executor() (méthode asyncio.AbstractEventLoop)

run_module() (dans le module runpy)

run_path() (dans le module runpy)

run_script() (méthode modulefinder.ModuleFinder)

run_setup() (dans le module distutils.core)

run_unittest() (dans le module test.support)

run_until_complete() (méthode asyncio.AbstractEventLoop)

run_with_locale() (dans le module test.support)

runcall() (dans le module pdb)

(méthode bdb.Bdb)

(méthode pdb.Pdb)

(méthode profile.Profile)

runcode() (méthode code.InteractiveInterpreter)

runctx() (dans le module profile)

(méthode bdb.Bdb)

(méthode profile.Profile)

(méthode trace.Trace)

runeval() (dans le module pdb)

(méthode bdb.Bdb)

(méthode pdb.Pdb)

runfunc() (méthode trace.Trace)

running() (méthode concurrent.futures.Future)

runpy (module)

runsource() (méthode code.InteractiveInterpreter)

runtime_library_dir_option() (méthode distutils.ccompiler.CCompiler)

RuntimeError

RuntimeWarning

RUSAGE_BOTH (dans le module resource)

RUSAGE_CHILDREN (dans le module resource)

RUSAGE_SELF (dans le module resource)

RUSAGE_THREAD (dans le module resource)

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Index – S

S (dans le module re)

S_ENFMT (dans le module stat)

S_IEXEC (dans le module stat)

S_IFBLK (dans le module stat)

S_IFCHR (dans le module stat)

S_IFDIR (dans le module stat)

S_IFDOOR (dans le module stat)

S_IFIFO (dans le module stat)

S_IFLNK (dans le module stat)

S_IFMT() (dans le module stat)

S_IFPORT (dans le module stat)

S_IFREG (dans le module stat)

S_IFSOCK (dans le module stat)

S_IFWHT (dans le module stat)

S_IMODE() (dans le module stat)

S_IREAD (dans le module stat)

S_IRGRP (dans le module stat)

S_IROTH (dans le module stat)

S_IRUSR (dans le module stat)

S_IRWXG (dans le module stat)

S_IRWXO (dans le module stat)

S_IRWXU (dans le module stat)

S_ISBLK() (dans le module stat)

S_ISCHR() (dans le module stat)

S_ISDIR() (dans le module stat)

S_ISDOOR() (dans le module stat)

S_ISFIFO() (dans le module stat)

S_ISGID (dans le module stat)

S_ISLNK() (dans le module stat)

S_ISPORT() (dans le module stat)

S_ISREG() (dans le module stat)

S_ISSOCK() (dans le module stat)

S_ISUID (dans le module stat)

S_ISVTX (dans le module stat)

S_ISWHT() (dans le module stat)

S_IWGRP (dans le module stat)

S_IWOTH (dans le module stat)

S_IWRITE (dans le module stat)

S_IWUSR (dans le module stat)

S_IXGRP (dans le module stat)

S_IXOTH (dans le module stat)

S_IXUSR (dans le module stat)

safe_substitute() (méthode string.Template)

saferepr() (dans le module pprint)

same_files (attribut filecmp.dircmp)

same_quantum() (méthode decimal.Context)

(méthode decimal.Decimal)

samefile() (dans le module os.path)

(méthode pathlib.Path)

SameFileError

sameopenfile() (dans le module os.path)

samestat() (dans le module os.path)

sample() (dans le module random)

save() (méthode http.cookiejar.FileCookieJar)

SaveKey() (dans le module winreg)

savetty() (dans le module curses)

SAX2DOM (classe dans xml.dom.pulldom)

SAXException

SAXNotRecognizedException

SAXNotSupportedException

SAXParseException

scaleb() (méthode decimal.Context)

(méthode decimal.Decimal)

scandir() (dans le module os)

scanf()

sched (module)

SCHED_BATCH (dans le module os)

SCHED_FIFO (dans le module os)

sched_get_priority_max() (dans le module os)

sched_get_priority_min() (dans le module os)

sched_getaffinity() (dans le module os)

sched_getparam() (dans le module os)

sched_getscheduler() (dans le module os)

SCHED_IDLE (dans le module os)

SCHED_OTHER (dans le module os)

sched_param (classe dans os)

sched_priority (attribut os.sched_param)

SCHED_RESET_ON_FORK (dans le module os)

SCHED_RR (dans le module os)

sched_rr_get_interval() (dans le module os)

sched_setaffinity() (dans le module os)

sched_setparam() (dans le module os)

sched_setscheduler() (dans le module os)

SCHED_SPORADIC (dans le module os)

sched_yield() (dans le module os)

scheduler (classe dans sched)

schema (dans le module msilib)

scope, [1]

Screen (classe dans turtle)

screensize() (dans le module turtle)

script_from_examples() (dans le module doctest)

scroll() (méthode curses.window)

ScrolledCanvas (classe dans turtle)

scrollok() (méthode curses.window)

scrypt() (dans le module hashlib)

sdterr

stdin stdout

search

path, module, [1], [2], [3], [4], [5], [6], [7]

search() (dans le module re)

(méthode imaplib.IMAP4)

(méthode re.regex)

second (attribut datetime.datetime)

(attribut datetime.time)

seconds since the epoch

secrets (module)

SECTCRE (attribut configparser.ConfigParser)

sections() (méthode configparser.ConfigParser)

secure (attribut http.cookiejar.Cookie)

secure hash algorithm, SHA1, SHA224, SHA256, SHA384, SHA512

Secure Sockets Layer

security

CGI

see() (méthode tkinter.ttk.Treeview)

seed() (dans le module random)

seek() (méthode chunk.Chunk)

(méthode io.IOBase)

(méthode io.TextIOBase)

(méthode mmap.mmap)

SEEK_CUR (dans le module os)

SEEK_END (dans le module os)

SEEK_SET (dans le module os)

seekable() (méthode io.IOBase)

seen_greeting (attribut smtpd.SMTPChannel)

Select (classe dans tkinter.tix)

select (module)

select() (dans le module select)

(méthode imaplib.IMAP4)

(méthode selectors.BaseSelector)

(méthode tkinter.ttk.Notebook)

selected_alpn_protocol() (méthode ssl.SSLSocket)

selected_npn_protocol() (méthode ssl.SSLSocket)

selection() (méthode tkinter.ttk.Treeview)

selection_add() (méthode tkinter.ttk.Treeview)

selection_remove() (méthode tkinter.ttk.Treeview)

selection_set() (méthode tkinter.ttk.Treeview)

selection_toggle() (méthode tkinter.ttk.Treeview)

selector (attribut urllib.request.Request)

SelectorEventLoop (classe dans asyncio)

SelectorKey (classe dans selectors)

selectors (module)

SelectSelector (classe dans selectors)

Semaphore (classe dans asyncio)

(classe dans multiprocessing)

(classe dans threading)

Semaphore() (méthode multiprocessing.managers.SyncManager)

semaphores, binary

SEMI (dans le module token)

send() (méthode asyncore.dispatcher)

(méthode coroutine)

(méthode generator)

(méthode http.client.HTTPConnection)

(méthode imaplib.IMAP4)

(méthode logging.handlers.DatagramHandler)

(méthode logging.handlers.SocketHandler)

(méthode multiprocessing.connection.Connection)

(méthode socket.socket)

send_bytes() (méthode multiprocessing.connection.Connection)

send_error() (méthode http.server.BaseHTTPRequestHandler)

send_flowing_data() (méthode formatter.writer)

send_header() (méthode http.server.BaseHTTPRequestHandler)

send_hor_rule() (méthode formatter.writer)

send_label_data() (méthode formatter.writer)

send_line_break() (méthode formatter.writer)

send_literal_data() (méthode formatter.writer)

send_message() (méthode smtplib.SMTP)

send_paragraph() (méthode formatter.writer)

send_response() (méthode http.server.BaseHTTPRequestHandler)

send_response_only() (méthode http.server.BaseHTTPRequestHandler)

send_signal() (méthode asyncio.asyncio.subprocess.Process)

(méthode asyncio.BaseSubprocessTransport)

(méthode subprocess.Popen)

sendall() (méthode socket.socket)

sendcmd() (méthode ftplib.FTP)

sendfile() (dans le module os)

(méthode socket.socket)

(méthode wsgiref.handlers.BaseHandler)

sendmail() (méthode smtplib.SMTP)

sendmsg() (méthode socket.socket)

sendmsg_afalg() (méthode socket.socket)

sendto() (méthode asyncio.DatagramTransport)

(méthode socket.socket)

sentinel (attribut multiprocessing.Process)

(dans le module unittest.mock)

sep (dans le module os)

sequence

item

iteration

objet, [1], [2], [3], [4], [5], [6], [7], [8]

types, immutable

types, mutable

types, operations on, [1]

Sequence (classe dans collections.abc)

(classe dans typing)

sequence (dans le module msilib)

sequence2st() (dans le module parser)

SequenceMatcher (classe dans difflib), [1]

serializing

objects

serve_forever() (méthode socketserver.BaseServer)

server

WWW, [1]

server (attribut http.server.BaseHTTPRequestHandler)

Server (classe dans asyncio)

server_activate() (méthode socketserver.BaseServer)

server_address (attribut socketserver.BaseServer)

server_bind() (méthode socketserver.BaseServer)

server_close() (méthode socketserver.BaseServer)

server_hostname (attribut ssl.SSLSocket)

server_side (attribut ssl.SSLSocket)

server_software (attribut wsgiref.handlers.BaseHandler)

server_version (attribut http.server.BaseHTTPRequestHandler)

(attribut http.server.SimpleHTTPRequestHandler)

ServerProxy (classe dans xmlrpc.client)

service_actions() (méthode socketserver.BaseServer)

session (attribut ssl.SSLSocket)

session_reused (attribut ssl.SSLSocket)

session_stats() (méthode ssl.SSLContext)

set

display

objet, [1], [2], [3]

Set (classe dans collections.abc)

(classe dans typing)

set (classe de base)

Set Breakpoint

set type

objet

set() (méthode asyncio.Event)

(méthode configparser.ConfigParser)

(méthode configparser.RawConfigParser)

(méthode http.cookies.Morsel)

(méthode ossaudiodev.oss_mixer_device)

(méthode test.support.EnvironmentVarGuard)

(méthode threading.Event)

(méthode tkinter.ttk.Combobox)

(méthode tkinter.ttk.Treeview)

(méthode xml.etree.ElementTree.Element)

SET_ADD (opcode)

set_all()

set_allowed_domains() (méthode http.cookiejar.DefaultCookiePolicy)

set_alpn_protocols() (méthode ssl.SSLContext)

set_app() (méthode wsgiref.simple_server.WSGIServer)

set_asyncgen_hooks() (dans le module sys)

set_authorizer() (méthode sqlite3.Connection)

set_auto_history() (dans le module readline)

set_blocked_domains() (méthode http.cookiejar.DefaultCookiePolicy)

set_blocking() (dans le module os)

set_boundary() (méthode email.message.EmailMessage)

(méthode email.message.Message)

set_break() (méthode bdb.Bdb)

set_charset() (méthode email.message.Message)

set_children() (méthode tkinter.ttk.Treeview)

set_ciphers() (méthode ssl.SSLContext)

set_completer() (dans le module readline)

set_completer_delims() (dans le module readline)

set_completion_display_matches_hook() (dans le module readline)

set_content() (dans le module email.contentmanager)

(méthode email.contentmanager.ContentManager)

(méthode email.message.EmailMessage)

set_continue() (méthode bdb.Bdb)

set_cookie() (méthode http.cookiejar.CookieJar)

set_cookie_if_ok() (méthode http.cookiejar.CookieJar)

set_coroutine_wrapper() (dans le module sys)

set_current() (méthode msilib.Feature)

set_data() (méthode importlib.abc.SourceLoader)

(méthode importlib.machinery.SourceFileLoader)

set_date() (méthode mailbox.MaildirMessage)

set_debug() (dans le module gc)

(méthode asyncio.AbstractEventLoop)

set_debuglevel() (méthode ftplib.FTP)

(méthode http.client.HTTPConnection)

(méthode nntplib.NNTP)

(méthode poplib.POP3)

(méthode smtplib.SMTP)

(méthode telnetlib.Telnet)

set_default_executor() (méthode asyncio.AbstractEventLoop)

set_default_type() (méthode email.message.EmailMessage)

(méthode email.message.Message)

set_default_verify_paths() (méthode ssl.SSLContext)

set_defaults() (méthode argparse.ArgumentParser)

(méthode optparse.OptionParser)

set_ecdh_curve() (méthode ssl.SSLContext)

set_errno() (dans le module ctypes)

set_event_loop() (dans le module asyncio)

(méthode asyncio.AbstractEventLoopPolicy)

set_event_loop_policy() (dans le module asyncio)

set_exception() (méthode asyncio.Future)

(méthode asyncio.StreamReader)

(méthode concurrent.futures.Future)

set_exception_handler() (méthode asyncio.AbstractEventLoop)

set_executable() (dans le module multiprocessing)

set_executables() (méthode distutils.ccompiler.CCompiler)

set_flags() (méthode mailbox.MaildirMessage)

(méthode mailbox.mboxMessage)

(méthode mailbox.MMDFMessage)

set_from() (méthode mailbox.mboxMessage)

(méthode mailbox.MMDFMessage)

set_handle_inheritable() (dans le module os)

set_history_length() (dans le module readline)

set_include_dirs() (méthode distutils.ccompiler.CCompiler)

set_info() (méthode mailbox.MaildirMessage)

set_inheritable() (dans le module os)

(méthode socket.socket)

set_labels() (méthode mailbox.BabylMessage)

set_last_error() (dans le module ctypes)

set_libraries() (méthode distutils.ccompiler.CCompiler)

set_library_dirs() (méthode distutils.ccompiler.CCompiler)

set_link_objects() (méthode distutils.ccompiler.CCompiler)

set_literal (2to3 fixer)

set_loader() (dans le module importlib.util)

set_next() (méthode bdb.Bdb)

set_nonstandard_attr() (méthode http.cookiejar.Cookie)

set_npn_protocols() (méthode ssl.SSLContext)

set_ok() (méthode http.cookiejar.CookiePolicy)

set_option_negotiation_callback() (méthode telnetlib.Telnet)

set_output_charset() (méthode gettext.NullTranslations)

set_package() (dans le module importlib.util)

set_param() (méthode email.message.EmailMessage)

(méthode email.message.Message)

set_pasv() (méthode ftplib.FTP)

set_payload() (méthode email.message.Message)

set_policy() (méthode http.cookiejar.CookieJar)

set_position() (méthode xdrlib.Unpacker)

set_pre_input_hook() (dans le module readline)

set_progress_handler() (méthode sqlite3.Connection)

set_protocol() (méthode asyncio.BaseTransport)

set_proxy() (méthode urllib.request.Request)

set_python_build() (dans le module distutils.sysconfig)

set_quit() (méthode bdb.Bdb)

set_recsrc() (méthode ossaudiodev.oss_mixer_device)

set_result() (méthode asyncio.Future)

(méthode concurrent.futures.Future)

set_return() (méthode bdb.Bdb)

set_running_or_notify_cancel() (méthode concurrent.futures.Future)

set_runtime_library_dirs() (méthode distutils.ccompiler.CCompiler)

set_seq1() (méthode difflib.SequenceMatcher)

set_seq2() (méthode difflib.SequenceMatcher)

set_seqs() (méthode difflib.SequenceMatcher)

set_sequences() (méthode mailbox.MH)

(méthode mailbox.MHMessage)

set_server_documentation() (méthode xmlrpc.server.DocCGIXMLRPCRequestHandler)

(méthode xmlrpc.server.DocXMLRPCServer)

set_server_name() (méthode xmlrpc.server.DocCGIXMLRPCRequestHandler)

(méthode xmlrpc.server.DocXMLRPCServer)

set_server_title() (méthode xmlrpc.server.DocCGIXMLRPCRequestHandler)

(méthode xmlrpc.server.DocXMLRPCServer)

set_servername_callback() (méthode ssl.SSLContext)

set_spacing() (méthode formatter.formatter)

set_start_method() (dans le module multiprocessing)

set_startup_hook() (dans le module readline)

set_step() (méthode bdb.Bdb)

set_subdir() (méthode mailbox.MaildirMessage)

set_task_factory() (méthode asyncio.AbstractEventLoop)

set_terminator() (méthode asynchat.async_chat)

set_threshold() (dans le module gc)

set_trace() (dans le module bdb)

(dans le module pdb)

(méthode bdb.Bdb)

(méthode pdb.Pdb)

set_trace_callback() (méthode sqlite3.Connection)

set_transport() (méthode asyncio.StreamReader)

set_tunnel() (méthode http.client.HTTPConnection)

set_type() (méthode email.message.Message)

set_unittest_reportflags() (dans le module doctest)

set_unixfrom() (méthode email.message.EmailMessage)

(méthode email.message.Message)

set_until() (méthode bdb.Bdb)

set_url() (méthode urllib.robotparser.RobotFileParser)

set_usage() (méthode optparse.OptionParser)

set_userptr() (méthode curses.panel.Panel)

set_visible() (méthode mailbox.BabylMessage)

set_wakeup_fd() (dans le module signal)

set_write_buffer_limits() (méthode asyncio.WriteTransport)

setacl() (méthode imaplib.IMAP4)

setannotation() (méthode imaplib.IMAP4)

setattr() (fonction de base)

setAttribute() (méthode xml.dom.Element)

setAttributeNode() (méthode xml.dom.Element)

setAttributeNodeNS() (méthode xml.dom.Element)

setAttributeNS() (méthode xml.dom.Element)

SetBase() (méthode xml.parsers.expat.xmlparser)

setblocking() (méthode socket.socket)

setByteStream() (méthode xml.sax.xmlreader.InputSource)

setcbreak() (dans le module tty)

setCharacterStream() (méthode xml.sax.xmlreader.InputSource)

setcheckinterval() (dans le module sys)

setcomptype() (méthode aifc.aifc)

(méthode sunau.AU_write)

(méthode wave.Wave_write)

setContentHandler() (méthode xml.sax.xmlreader.XMLReader)

setcontext() (dans le module decimal)

setDaemon() (méthode threading.Thread)

setdefault() (méthode dict)

(méthode http.cookies.Morsel)

setdefaulttimeout() (dans le module socket)

setdlopenflags() (dans le module sys)

setDocumentLocator() (méthode xml.sax.handler.ContentHandler)

setDTDHandler() (méthode xml.sax.xmlreader.XMLReader)

setegid() (dans le module os)

setEncoding() (méthode xml.sax.xmlreader.InputSource)

setEntityResolver() (méthode xml.sax.xmlreader.XMLReader)

setErrorHandler() (méthode xml.sax.xmlreader.XMLReader)

seteuid() (dans le module os)

setFeature() (méthode xml.sax.xmlreader.XMLReader)

setfirstweekday() (dans le module calendar)

setfmt() (méthode ossaudiodev.oss_audio_device)

setFormatter() (méthode logging.Handler)

setframerate() (méthode aifc.aifc)

(méthode sunau.AU_write)

(méthode wave.Wave_write)

setgid() (dans le module os)

setgroups() (dans le module os)

seth() (dans le module turtle)

setheading() (dans le module turtle)

sethostname() (dans le module socket)

SetInteger() (méthode msilib.Record)

setitem() (dans le module operator)

setitimer() (dans le module signal)

setLevel() (méthode logging.Handler)

(méthode logging.Logger)

setlocale() (dans le module locale)

setLocale() (méthode xml.sax.xmlreader.XMLReader)

setLoggerClass() (dans le module logging)

setlogmask() (dans le module syslog)

setLogRecordFactory() (dans le module logging)

setmark() (méthode aifc.aifc)

setMaxConns() (méthode urllib.request.CacheFTPHandler)

setmode() (dans le module msvcrt)

setName() (méthode threading.Thread)

setnchannels() (méthode aifc.aifc)

(méthode sunau.AU_write)

(méthode wave.Wave_write)

setnframes() (méthode aifc.aifc)

(méthode sunau.AU_write)

(méthode wave.Wave_write)

SetParamEntityParsing() (méthode xml.parsers.expat.xmlparser)

setparameters() (méthode ossaudiodev.oss_audio_device)

setparams() (méthode aifc.aifc)

(méthode sunau.AU_write)

(méthode wave.Wave_write)

setpassword() (méthode zipfile.ZipFile)

setpgid() (dans le module os)

setpgrp() (dans le module os)

setpos() (dans le module turtle)

(méthode aifc.aifc)

(méthode sunau.AU_read)

(méthode wave.Wave_read)

setposition() (dans le module turtle)

setpriority() (dans le module os)

setprofile() (dans le module sys)

(dans le module threading)

SetProperty() (méthode msilib.SummaryInformation)

setProperty() (méthode xml.sax.xmlreader.XMLReader)

setPublicId() (méthode xml.sax.xmlreader.InputSource)

setquota() (méthode imaplib.IMAP4)

setraw() (dans le module tty)

setrecursionlimit() (dans le module sys)

setregid() (dans le module os)

setresgid() (dans le module os)

setresuid() (dans le module os)

setreuid() (dans le module os)

setrlimit() (dans le module resource)

setsampwidth() (méthode aifc.aifc)

(méthode sunau.AU_write)

(méthode wave.Wave_write)

setscrreg() (méthode curses.window)

setsid() (dans le module os)

setsockopt() (méthode socket.socket), [1], [2]

setstate() (dans le module random)

(méthode codecs.IncrementalDecoder)

(méthode codecs.IncrementalEncoder)

SetStream() (méthode msilib.Record)

SetString() (méthode msilib.Record)

setswitchinterval() (dans le module sys)

(in module sys)

setSystemId() (méthode xml.sax.xmlreader.InputSource)

setsyx() (dans le module curses)

setTarget() (méthode logging.handlers.MemoryHandler)

settiltangle() (dans le module turtle)

settimeout() (méthode socket.socket)

setTimeout() (méthode urllib.request.CacheFTPHandler)

settrace() (dans le module sys)

(dans le module threading)

setuid() (dans le module os)

setundobuffer() (dans le module turtle)

setup() (dans le module distutils.core)

(dans le module turtle)

(méthode socketserver.BaseRequestHandler)

setUp() (méthode unittest.TestCase)

SETUP_ANNOTATIONS (opcode)

SETUP_ASYNC_WITH (opcode)

setup_environ() (méthode wsgiref.handlers.BaseHandler)

SETUP_EXCEPT (opcode)

SETUP_FINALLY (opcode)

SETUP_LOOP (opcode)

setup_python() (méthode venv.EnvBuilder)

setup_scripts() (méthode venv.EnvBuilder)

setup_testing_defaults() (dans le module wsgiref.util)

SETUP_WITH (opcode)

setUpClass() (méthode unittest.TestCase)

setupterm() (dans le module curses)

SetValue() (dans le module winreg)

SetValueEx() (dans le module winreg)

setworldcoordinates() (dans le module turtle)

setx() (dans le module turtle)

setxattr() (dans le module os)

sety() (dans le module turtle)

séquence

SF_APPEND (dans le module stat)

SF_ARCHIVED (dans le module stat)

SF_IMMUTABLE (dans le module stat)

SF_MNOWAIT (dans le module os)

SF_NODISKIO (dans le module os)

SF_NOUNLINK (dans le module stat)

SF_SNAPSHOT (dans le module stat)

SF_SYNC (dans le module os)

shape (attribut memoryview)

Shape (classe dans turtle)

shape() (dans le module turtle)

shapesize() (dans le module turtle)

shapetransform() (dans le module turtle)

share() (méthode socket.socket)

shared_ciphers() (méthode ssl.SSLSocket)

shared_object_filename() (méthode distutils.ccompiler.CCompiler)

shearfactor() (dans le module turtle)

Shelf (classe dans shelve)

shelve

module

shelve (module)

shield() (dans le module asyncio)

shift() (méthode decimal.Context)

(méthode decimal.Decimal)

shift_path_info() (dans le module wsgiref.util)

shifting

operation

operations

shlex (classe dans shlex)

(module)

shortDescription() (méthode unittest.TestCase)

shorten() (dans le module textwrap)

shouldFlush() (méthode logging.handlers.BufferingHandler)

(méthode logging.handlers.MemoryHandler)

shouldStop (attribut unittest.TestResult)

show() (méthode curses.panel.Panel)

show_code() (dans le module dis)

show_compilers() (dans le module distutils.ccompiler)

showsyntaxerror() (méthode code.InteractiveInterpreter)

showtraceback() (méthode code.InteractiveInterpreter)

showturtle() (dans le module turtle)

showwarning() (dans le module warnings)

shuffle() (dans le module random)

shutdown() (dans le module logging)

(méthode concurrent.futures.Executor)

(méthode imaplib.IMAP4)

(méthode multiprocessing.managers.BaseManager)

(méthode socket.socket)

(méthode socketserver.BaseServer)

shutdown_asyncgens() (méthode asyncio.AbstractEventLoop)

shutil (module)

side_effect (attribut unittest.mock.Mock)

SIG_BLOCK (dans le module signal)

SIG_DFL (dans le module signal)

SIG_IGN (dans le module signal)

SIG_SETMASK (dans le module signal)

SIG_UNBLOCK (dans le module signal)

SIGINT, [1]

siginterrupt() (dans le module signal)

signal

module, [1]

signal (module)

signal() (dans le module signal)

signature (attribut inspect.BoundArguments)

Signature (classe dans inspect)

signature() (dans le module inspect)

sigpending() (dans le module signal)

sigtimedwait() (dans le module signal)

sigwait() (dans le module signal)

sigwaitinfo() (dans le module signal)

simple

statement

Simple Mail Transfer Protocol

SimpleCookie (classe dans http.cookies)

simplefilter() (dans le module warnings)

SimpleHandler (classe dans wsgiref.handlers)

SimpleHTTPRequestHandler (classe dans http.server)

SimpleNamespace (classe dans types)

SimpleQueue (classe dans multiprocessing)

SimpleXMLRPCRequestHandler (classe dans xmlrpc.server)

SimpleXMLRPCServer (classe dans xmlrpc.server)

sin() (dans le module cmath)

(dans le module math)

SingleAddressHeader (classe dans email.headerregistry)

singledispatch() (dans le module functools)

singleton

tuple

sinh() (dans le module cmath)

(dans le module math)

SIO_KEEPALIVE_VALS (dans le module socket)

SIO_LOOPBACK_FAST_PATH (dans le module socket)

SIO_RCVALL (dans le module socket)

site (module)

site command line option

--user-base

--user-site

site-packages

directory

sitecustomize

module

sixtofour (attribut ipaddress.IPv6Address)

size (attribut struct.Struct)

(attribut tarfile.TarInfo)

(attribut tracemalloc.Statistic)

(attribut tracemalloc.StatisticDiff)

(attribut tracemalloc.Trace)

size() (méthode ftplib.FTP)

(méthode mmap.mmap)

size_diff (attribut tracemalloc.StatisticDiff)

SIZE_MAX

Sized (classe dans collections.abc)

(classe dans typing)

sizeof() (dans le module ctypes)

SKIP (dans le module doctest)

skip() (dans le module unittest)

(méthode chunk.Chunk)

skip_unless_symlink() (dans le module test.support)

skipIf() (dans le module unittest)

skipinitialspace (attribut csv.Dialect)

skipped (attribut unittest.TestResult)

skippedEntity() (méthode xml.sax.handler.ContentHandler)

SkipTest

skipTest() (méthode unittest.TestCase)

skipUnless() (dans le module unittest)

SLASH (dans le module token)

SLASHEQUAL (dans le module token)

slave() (méthode nntplib.NNTP)

sleep() (dans le module asyncio)

(dans le module time)

slice

assignment

fonction de base, [1]

objet

operation

slice (classe de base)

slicing, [1], [2]

assignment

SMTP

protocol

SMTP (classe dans smtplib)

(dans le module email.policy)

smtp_server (attribut smtpd.SMTPChannel)

SMTP_SSL (classe dans smtplib)

smtp_state (attribut smtpd.SMTPChannel)

SMTPAuthenticationError

SMTPChannel (classe dans smtpd)

SMTPConnectError

smtpd (module)

SMTPDataError

SMTPException

SMTPHandler (classe dans logging.handlers)

SMTPHeloError

smtplib (module)

SMTPNotSupportedError

SMTPRecipientsRefused

SMTPResponseException

SMTPSenderRefused

SMTPServer (classe dans smtpd)

SMTPServerDisconnected

SMTPUTF8 (dans le module email.policy)

Snapshot (classe dans tracemalloc)

SND_ALIAS (dans le module winsound)

SND_ASYNC (dans le module winsound)

SND_FILENAME (dans le module winsound)

SND_LOOP (dans le module winsound)

SND_MEMORY (dans le module winsound)

SND_NODEFAULT (dans le module winsound)

SND_NOSTOP (dans le module winsound)

SND_NOWAIT (dans le module winsound)

SND_PURGE (dans le module winsound)

sndhdr (module)

sniff() (méthode csv.Sniffer)

Sniffer (classe dans csv)

sock_accept() (méthode asyncio.AbstractEventLoop)

SOCK_CLOEXEC (dans le module socket)

sock_connect() (méthode asyncio.AbstractEventLoop)

SOCK_DGRAM (dans le module socket)

SOCK_NONBLOCK (dans le module socket)

SOCK_RAW (dans le module socket)

SOCK_RDM (dans le module socket)

sock_recv() (méthode asyncio.AbstractEventLoop)

sock_sendall() (méthode asyncio.AbstractEventLoop)

SOCK_SEQPACKET (dans le module socket)

SOCK_STREAM (dans le module socket)

socket

module

objet

socket (attribut socketserver.BaseServer)

(module)

socket() (dans le module socket)

(in module socket)

(méthode imaplib.IMAP4)

socket_type (attribut socketserver.BaseServer)

SocketHandler (classe dans logging.handlers)

socketpair() (dans le module socket)

sockets (attribut asyncio.Server)

socketserver (module)

SocketType (dans le module socket)

SOL_ALG (dans le module socket)

SOL_RDS (dans le module socket)

SOMAXCONN (dans le module socket)

sort() (méthode imaplib.IMAP4)

(méthode list)

sort_stats() (méthode pstats.Stats)

sorted() (fonction de base)

sortTestMethodsUsing (attribut unittest.TestLoader)

source (attribut doctest.Example)

(attribut shlex.shlex)

(pdb command)

source character set

source_from_cache() (dans le module imp)

(dans le module importlib.util)

SOURCE_SUFFIXES (dans le module importlib.machinery)

source_to_code() (méthode statique importlib.abc.InspectLoader)

SourceFileLoader (classe dans importlib.machinery)

sourcehook() (méthode shlex.shlex)

SourcelessFileLoader (classe dans importlib.machinery)

SourceLoader (classe dans importlib.abc)

space

in printf-style formatting, [1]

in string formatting

span() (méthode re.match)

spawn() (dans le module pty)

(méthode distutils.ccompiler.CCompiler)

spawnl() (dans le module os)

spawnle() (dans le module os)

spawnlp() (dans le module os)

spawnlpe() (dans le module os)

spawnv() (dans le module os)

spawnve() (dans le module os)

spawnvp() (dans le module os)

spawnvpe() (dans le module os)

spec_from_file_location() (dans le module importlib.util)

spec_from_loader() (dans le module importlib.util)

special

attribute

attribute, generic

specified_attributes (attribut xml.parsers.expat.xmlparser)

speed() (dans le module turtle)

(méthode ossaudiodev.oss_audio_device)

spécificateur de module

split() (dans le module os.path)

(dans le module re)

(dans le module shlex)

(méthode bytearray)

(méthode bytes)

(méthode re.regex)

(méthode str)

split_quoted() (dans le module distutils.util)

splitdrive() (dans le module os.path)

splitext() (dans le module os.path)

splitlines() (méthode bytearray)

(méthode bytes)

(méthode str)

SplitResult (classe dans urllib.parse)

SplitResultBytes (classe dans urllib.parse)

splitunc() (dans le module os.path)

SpooledTemporaryFile() (dans le module tempfile)

sprintf-style formatting, [1]

spwd (module)

sqlite3 (module)

sqlite_version (dans le module sqlite3)

sqlite_version_info (dans le module sqlite3)

sqrt() (dans le module cmath)

(dans le module math)

(méthode decimal.Context)

(méthode decimal.Decimal)

SSL

ssl (module)

SSL_CERT_FILE

SSL_CERT_PATH

ssl_version (attribut ftplib.FTP_TLS)

SSLContext (classe dans ssl)

SSLEOFError

SSLError

SSLErrorNumber (classe dans ssl)

SSLObject (classe dans ssl)

SSLSession (classe dans ssl)

SSLSocket (classe dans ssl)

SSLSyscallError

SSLWantReadError

SSLWantWriteError

SSLZeroReturnError

st() (dans le module turtle)

st2list() (dans le module parser)

st2tuple() (dans le module parser)

st_atime (attribut os.stat_result)

ST_ATIME (dans le module stat)

st_atime_ns (attribut os.stat_result)

st_birthtime (attribut os.stat_result)

st_blksize (attribut os.stat_result)

st_blocks (attribut os.stat_result)

st_creator (attribut os.stat_result)

st_ctime (attribut os.stat_result)

ST_CTIME (dans le module stat)

st_ctime_ns (attribut os.stat_result)

st_dev (attribut os.stat_result)

ST_DEV (dans le module stat)

st_file_attributes (attribut os.stat_result)

st_flags (attribut os.stat_result)

st_gen (attribut os.stat_result)

st_gid (attribut os.stat_result)

ST_GID (dans le module stat)

st_ino (attribut os.stat_result)

ST_INO (dans le module stat)

st_mode (attribut os.stat_result)

ST_MODE (dans le module stat)

st_mtime (attribut os.stat_result)

ST_MTIME (dans le module stat)

st_mtime_ns (attribut os.stat_result)

st_nlink (attribut os.stat_result)

ST_NLINK (dans le module stat)

st_rdev (attribut os.stat_result)

st_rsize (attribut os.stat_result)

st_size (attribut os.stat_result)

ST_SIZE (dans le module stat)

st_type (attribut os.stat_result)

st_uid (attribut os.stat_result)

ST_UID (dans le module stat)

stack

execution

trace

stack (attribut traceback.TracebackException)

stack viewer

stack() (dans le module inspect)

stack_effect() (dans le module dis)

stack_size() (dans le module _thread)

(dans le module threading)

stackable

streams

StackSummary (classe dans traceback)

stamp() (dans le module turtle)

standard

output

Standard C

standard input

standard_b64decode() (dans le module base64)

standard_b64encode() (dans le module base64)

standarderror (2to3 fixer)

standend() (méthode curses.window)

standout() (méthode curses.window)

STAR (dans le module token)

STAREQUAL (dans le module token)

starmap() (dans le module itertools)

(méthode multiprocessing.pool.Pool)

starmap_async() (méthode multiprocessing.pool.Pool)

start (attribut range)

(attribut UnicodeError)

(slice object attribute), [1]

start() (dans le module tracemalloc)

(méthode logging.handlers.QueueListener)

(méthode multiprocessing.managers.BaseManager)

(méthode multiprocessing.Process)

(méthode re.match)

(méthode threading.Thread)

(méthode tkinter.ttk.Progressbar)

(méthode xml.etree.ElementTree.TreeBuilder)

start_color() (dans le module curses)

start_component() (méthode msilib.Directory)

start_new_thread() (dans le module _thread)

start_server() (dans le module asyncio)

start_unix_server() (dans le module asyncio)

StartCdataSectionHandler() (méthode xml.parsers.expat.xmlparser)

StartDoctypeDeclHandler() (méthode xml.parsers.expat.xmlparser)

startDocument() (méthode xml.sax.handler.ContentHandler)

startElement() (méthode xml.sax.handler.ContentHandler)

StartElementHandler() (méthode xml.parsers.expat.xmlparser)

startElementNS() (méthode xml.sax.handler.ContentHandler)

STARTF_USESHOWWINDOW (dans le module subprocess)

STARTF_USESTDHANDLES (dans le module subprocess)

startfile() (dans le module os)

StartNamespaceDeclHandler() (méthode xml.parsers.expat.xmlparser)

startPrefixMapping() (méthode xml.sax.handler.ContentHandler)

startswith() (méthode bytearray)

(méthode bytes)

(méthode str)

startTest() (méthode unittest.TestResult)

startTestRun() (méthode unittest.TestResult)

starttls() (méthode imaplib.IMAP4)

(méthode nntplib.NNTP)

(méthode smtplib.SMTP)

STARTUPINFO (classe dans subprocess)

stat

module

stat (module)

stat() (dans le module os)

(méthode nntplib.NNTP)

(méthode os.DirEntry)

(méthode pathlib.Path)

(méthode poplib.POP3)

stat_float_times() (dans le module os)

stat_result (classe dans os)

state() (méthode tkinter.ttk.Widget)

statement

assignment, [1]

assignment, annotated

assignment, augmented

compound

expression

future

loop, [1], [2], [3]

simple

statement grouping

staticmethod

fonction de base

staticmethod() (fonction de base)

Statistic (classe dans tracemalloc)

StatisticDiff (classe dans tracemalloc)

statistics (module)

statistics() (méthode tracemalloc.Snapshot)

StatisticsError

Stats (classe dans pstats)

status (attribut http.client.HTTPResponse)

status() (méthode imaplib.IMAP4)

statvfs() (dans le module os)

STD_ERROR_HANDLE (dans le module subprocess)

STD_INPUT_HANDLE (dans le module subprocess)

STD_OUTPUT_HANDLE (dans le module subprocess)

StdButtonBox (classe dans tkinter.tix)

stderr (attribut asyncio.asyncio.subprocess.Process)

(attribut subprocess.CalledProcessError)

(attribut subprocess.CompletedProcess)

(attribut subprocess.Popen)

(attribut subprocess.TimeoutExpired)

(dans le module sys)

(in module sys), [1]

stdev() (dans le module statistics)

stdin

stdout sdterr

stdin (attribut asyncio.asyncio.subprocess.Process)

(attribut subprocess.Popen)

(dans le module sys)

(in module sys), [1]

stdio

stdout

sdterr, stdin

stdout (attribut asyncio.asyncio.subprocess.Process)

(attribut subprocess.CalledProcessError)

(attribut subprocess.CompletedProcess)

(attribut subprocess.Popen)

(attribut subprocess.TimeoutExpired)

STDOUT (dans le module subprocess)

stdout (dans le module sys)

(in module sys), [1]

step (attribut range)

(pdb command)

(slice object attribute), [1]

step() (méthode tkinter.ttk.Progressbar)

stereocontrols() (méthode ossaudiodev.oss_mixer_device)

stls() (méthode poplib.POP3)

stop (attribut range)

(slice object attribute), [1]

stop() (dans le module tracemalloc)

(méthode asyncio.AbstractEventLoop)

(méthode logging.handlers.QueueListener)

(méthode tkinter.ttk.Progressbar)

(méthode unittest.TestResult)

stop_here() (méthode bdb.Bdb)

StopAsyncIteration

exception

StopIteration

exception, [1]

stopListening() (dans le module logging.config)

stopTest() (méthode unittest.TestResult)

stopTestRun() (méthode unittest.TestResult)

storbinary() (méthode ftplib.FTP)

store() (méthode imaplib.IMAP4)

STORE_ACTIONS (attribut optparse.Option)

STORE_ANNOTATION (opcode)

STORE_ATTR (opcode)

STORE_DEREF (opcode)

STORE_FAST (opcode)

STORE_GLOBAL (opcode)

STORE_NAME (opcode)

STORE_SUBSCR (opcode)

storlines() (méthode ftplib.FTP)

str (built-in class)

(see also string)

str (classe de base)

str() (dans le module locale)

strcoll() (dans le module locale)

StreamError

StreamHandler (classe dans logging)

streamreader (attribut codecs.CodecInfo)

StreamReader (classe dans asyncio)

(classe dans codecs)

StreamReaderProtocol (classe dans asyncio)

StreamReaderWriter (classe dans codecs)

StreamRecoder (classe dans codecs)

StreamRequestHandler (classe dans socketserver)

streams

stackable

streamwriter (attribut codecs.CodecInfo)

StreamWriter (classe dans asyncio)

(classe dans codecs)

strerror (attribut OSError)

strerror()

(dans le module os)

strftime() (dans le module time)

(méthode datetime.date)

(méthode datetime.datetime)

(méthode datetime.time)

strict (attribut csv.Dialect)

(dans le module email.policy)

strict_domain (attribut http.cookiejar.DefaultCookiePolicy)

strict_errors() (dans le module codecs)

strict_ns_domain (attribut http.cookiejar.DefaultCookiePolicy)

strict_ns_set_initial_dollar (attribut http.cookiejar.DefaultCookiePolicy)

strict_ns_set_path (attribut http.cookiejar.DefaultCookiePolicy)

strict_ns_unverifiable (attribut http.cookiejar.DefaultCookiePolicy)

strict_rfc2965_unverifiable (attribut http.cookiejar.DefaultCookiePolicy)

strides (attribut memoryview)

string

__format__() (object method)

__str__() (object method)

conversion, [1]

format() (built-in function)

formatted literal

formatting, printf

immutable sequences

interpolated literal

interpolation, printf

item

methods

module

object representation

objet, [1], [2]

PyObject_Str (C function)

str (built-in class)

str() (built-in function)

text sequence type

string (attribut re.match)

STRING (dans le module token)

string (module)

string literal

string_at() (dans le module ctypes)

StringIO (classe dans io)

stringprep (module)

strings, documentation, [1]

strip() (méthode bytearray)

(méthode bytes)

(méthode str)

strip_dirs() (méthode pstats.Stats)

stripspaces (attribut curses.textpad.Textbox)

strptime() (dans le module time)

(méthode de la classe datetime.datetime)

strtobool() (dans le module distutils.util)

struct

module

Struct (classe dans struct)

struct (module)

struct sequence

struct_time (classe dans time)

Structure (classe dans ctypes)

structures

C

strxfrm() (dans le module locale)

STType (dans le module parser)

style

coding

Style (classe dans tkinter.ttk)

sub() (dans le module operator)

(dans le module re)

(méthode re.regex)

sub_commands (attribut distutils.cmd.Command)

subclassing

immutable types

subdirs (attribut filecmp.dircmp)

SubElement() (dans le module xml.etree.ElementTree)

submit() (méthode concurrent.futures.Executor)

submodule_search_locations (attribut importlib.machinery.ModuleSpec)

subn() (dans le module re)

(méthode re.regex)

subnets() (méthode ipaddress.IPv4Network)

(méthode ipaddress.IPv6Network)

Subnormal (classe dans decimal)

suboffsets (attribut memoryview)

subpad() (méthode curses.window)

subprocess (module)

subprocess_exec() (méthode asyncio.AbstractEventLoop)

subprocess_shell() (méthode asyncio.AbstractEventLoop)

SubprocessError

SubprocessProtocol (classe dans asyncio)

subscribe() (méthode imaplib.IMAP4)

subscript

assignment

operation

subscription, [1], [2], [3]

assignment

subsequent_indent (attribut textwrap.TextWrapper)

subst_vars() (dans le module distutils.util)

substitute() (méthode string.Template)

subTest() (méthode unittest.TestCase)

subtract() (méthode collections.Counter)

(méthode decimal.Context)

subtraction

subtype (attribut email.headerregistry.ContentTypeHeader)

subwin() (méthode curses.window)

successful() (méthode multiprocessing.pool.AsyncResult)

suffix_map (attribut mimetypes.MimeTypes)

(dans le module mimetypes)

suite

suite() (dans le module parser)

suiteClass (attribut unittest.TestLoader)

sum() (fonction de base)

sum_list()

sum_sequence(), [1]

summarize() (méthode doctest.DocTestRunner)

summarize_address_range() (dans le module ipaddress)

sunau (module)

super (attribut pyclbr.Class)

super() (fonction de base)

supernet() (méthode ipaddress.IPv4Network)

(méthode ipaddress.IPv6Network)

supports_bytes_environ (dans le module os)

supports_dir_fd (dans le module os)

supports_effective_ids (dans le module os)

supports_fd (dans le module os)

supports_follow_symlinks (dans le module os)

supports_unicode_filenames (dans le module os.path)

SupportsAbs (classe dans typing)

SupportsBytes (classe dans typing)

SupportsComplex (classe dans typing)

SupportsFloat (classe dans typing)

SupportsInt (classe dans typing)

SupportsRound (classe dans typing)

suppress() (dans le module contextlib)

SuppressCrashReport (classe dans test.support)

SW_HIDE (dans le module subprocess)

swapcase() (méthode bytearray)

(méthode bytes)

(méthode str)

sym_name (dans le module symbol)

Symbol (classe dans symtable)

symbol (module)

SymbolTable (classe dans symtable)

symlink() (dans le module os)

symlink_to() (méthode pathlib.Path)

symmetric_difference() (méthode frozenset)

symmetric_difference_update() (méthode frozenset)

symtable (module)

symtable() (dans le module symtable)

sync() (dans le module os)

(méthode dbm.dumb.dumbdbm)

(méthode dbm.gnu.gdbm)

(méthode ossaudiodev.oss_audio_device)

(méthode shelve.Shelf)

syncdown() (méthode curses.window)

synchronized() (dans le module multiprocessing.sharedctypes)

SyncManager (classe dans multiprocessing.managers)

syncok() (méthode curses.window)

syncup() (méthode curses.window)

syntax

SyntaxErr

SyntaxError

SyntaxWarning

sys

module, [1], [2], [3], [4], [5], [6]

sys (module)

sys.exc_info

sys.last_traceback

sys.meta_path

sys.modules

sys.path

sys.path_hooks

sys.path_importer_cache

sys.stderr

sys.stdin

sys.stdout

sys_exc (2to3 fixer)

sys_version (attribut http.server.BaseHTTPRequestHandler)

sysconf() (dans le module os)

sysconf_names (dans le module os)

sysconfig (module)

syslog (module)

syslog() (dans le module syslog)

SysLogHandler (classe dans logging.handlers)

system() (dans le module os)

(dans le module platform)

system_alias() (dans le module platform)

SystemError

(built-in exception), [1]

SystemExit

(built-in exception)

systemId (attribut xml.dom.DocumentType)

SystemRandom (classe dans random)

(classe dans secrets)

SystemRoot

Navigation

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© Copyright 2001-2020, Python Software Foundation.
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Index – Symboles

! (exclamation)

in a command interpreter

in curses module

in formatted string literal

in glob-style wildcards, [1]

in string formatting

in struct format strings

! (pdb command)

!=

opérateur, [1]

" (double quote)

string literal

"""

string literal

# (hash)

comment, [1], [2]

in doctests

in printf-style formatting, [1]

in regular expressions

in string formatting

source encoding declaration

$ (dollar)

environment variables expansion

in regular expressions

in template strings

interpolation in configuration files

% (percent)

datetime format, [1], [2]

environment variables expansion (Windows), [1]

interpolation in configuration files

opérateur, [1]

printf-style formatting, [1]

%=

augmented assignment

& (ampersand)

opérateur, [1]

&=

augmented assignment

' (single quote)

string literal

'''

string literal

() (parentheses)

call

class definition

function definition

generator expression

in assignment target list

in printf-style formatting, [1]

in regular expressions

tuple display

(?

in regular expressions

(?!

in regular expressions

(?#

in regular expressions

(?:

in regular expressions

(?<!

in regular expressions

(?<=

in regular expressions

(?P<

in regular expressions

(?P=

in regular expressions

* (asterisk)

function definition

import statement

in argparse module

in assignment target list

in AST grammar

in expression lists

in function calls, [1]

in glob-style wildcards, [1]

in printf-style formatting, [1]

in regular expressions

opérateur, [1]

**

function definition

in dictionary displays

in function calls, [1]

in glob-style wildcards

opérateur, [1]

**=

augmented assignment

*=

augmented assignment

*?

in regular expressions

+ (plus)

binary operator, [1]

in argparse module

in doctests

in printf-style formatting, [1]

in regular expressions

in string formatting

unary operator, [1]

+=

augmented assignment

+?

in regular expressions

, (comma)

argument list

expression list, [1], [2], [3], [4]

identifier list, [1]

import statement

in dictionary displays

in string formatting

in target list

parameter list

slicing

tuple display

with statement

- (minus)

binary operator, [1]

in doctests

in glob-style wildcards, [1]

in printf-style formatting, [1]

in regular expressions

in string formatting

unary operator, [1]

--annotate

pickletools command line option

--buffer

unittest command line option

--catch

unittest command line option

--clock

timeit command line option

--count

trace command line option

--coverdir=<dir>

trace command line option

--create <tarfile> <source1> ... <sourceN>

tarfile command line option

--details

inspect command line option

--exact

tokenize command line option

--extract <tarfile> [<output_dir>]

tarfile command line option

--failfast

unittest command line option

--file=<file>

trace command line option

--help

command line option

json.tool command line option

timeit command line option

tokenize command line option

trace command line option

zipapp command line option

--ignore-dir=<dir>

trace command line option

--ignore-module=<mod>

trace command line option

--indentlevel=<num>

pickletools command line option

--info

zipapp command line option

--list <tarfile>

tarfile command line option

--listfuncs

trace command line option

--locals

unittest command line option

--main=<mainfn>

zipapp command line option

--memo

pickletools command line option

--missing

trace command line option

--no-report

trace command line option

--number=N

timeit command line option

--output=<file>

pickletools command line option

--output=<output>

zipapp command line option

--pattern pattern

unittest-discover command line option

--preamble=<preamble>

pickletools command line option

--process

timeit command line option

--python=<interpreter>

zipapp command line option

--repeat=N

timeit command line option

--report

trace command line option

--setup=S

timeit command line option

--sort-keys

json.tool command line option

--start-directory directory

unittest-discover command line option

--summary

trace command line option

--test <tarfile>

tarfile command line option

--time

timeit command line option

--timing

trace command line option

--top-level-directory directory

unittest-discover command line option

--trace

trace command line option

--trackcalls

trace command line option

--unit=U

timeit command line option

--user-base

site command line option

--user-site

site command line option

--verbose

tarfile command line option

timeit command line option

unittest-discover command line option

--version

command line option

trace command line option

-=

augmented assignment

->

function annotations, [1]

-?

command line option

-a

pickletools command line option

-B

command line option

-b

command line option

compileall command line option

unittest command line option

-C

trace command line option

-c

timeit command line option

trace command line option

unittest command line option

-c <command>

command line option

-c <tarfile> <source1> ... <sourceN>

tarfile command line option

-c <zipfile> <source1> ... <sourceN>

zipfile command line option

-d

command line option

-d destdir

compileall command line option

-E

command line option

-e

tokenize command line option

-e <tarfile> [<output_dir>]

tarfile command line option

-e <zipfile> <output_dir>

zipfile command line option

-f

compileall command line option

trace command line option

unittest command line option

-g

trace command line option

-h

command line option

json.tool command line option

timeit command line option

tokenize command line option

zipapp command line option

-I

command line option

-i

command line option

-i list

compileall command line option

-J

command line option

-j N

compileall command line option

-l

compileall command line option

pickletools command line option

trace command line option

-l <tarfile>

tarfile command line option

-l <zipfile>

zipfile command line option

-m

pickletools command line option

trace command line option

-m <mainfn>

zipapp command line option

-m <module-name>

command line option

-n N

timeit command line option

-O

command line option

-o

pickletools command line option

-o <output>

zipapp command line option

-OO

command line option

-p

pickletools command line option

timeit command line option

unittest-discover command line option

-p <interpreter>

zipapp command line option

-q

command line option

compileall command line option

-R

command line option

trace command line option

-r

compileall command line option

trace command line option

-r N

timeit command line option

-S

command line option

-s

command line option

trace command line option

unittest-discover command line option

-s S

timeit command line option

-T

trace command line option

-t

timeit command line option

trace command line option

unittest-discover command line option

-t <tarfile>

tarfile command line option

-t <zipfile>

zipfile command line option

-u

command line option

timeit command line option

-V

command line option

-v

command line option

tarfile command line option

timeit command line option

unittest-discover command line option

-W arg

command line option

-X

command line option

-x

command line option

-x regex

compileall command line option

. (dot)

attribute reference

in glob-style wildcards

in numeric literal

in pathnames, [1]

in printf-style formatting, [1]

in regular expressions

in string formatting

in Tkinter

..

in pathnames

...

ellipsis literal, [1], [2]

in doctests

interpreter prompt, [1]

placeholder, [1], [2]

.ini

file

.pdbrc

file

.pypirc file

/ (slash)

in pathnames, [1]

opérateur, [1]

//

opérateur, [1]

//=

augmented assignment

/=

augmented assignment

0b

integer literal

0o

integer literal

0x

integer literal

2to3

: (colon)

annotated variable

compound statement, [1], [2], [3], [4], [5], [6]

function annotations, [1]

in dictionary expressions

in formatted string literal

in SQL statements

in string formatting

lambda expression

path separator (POSIX)

slicing

; (semicolon), [1]

< (less)

in string formatting

in struct format strings

opérateur, [1]

<<

opérateur, [1]

<<=

augmented assignment

<=

opérateur, [1]

<BLANKLINE>

= (equals)

assignment statement

class definition

function definition

in function calls

in string formatting

in struct format strings

==

opérateur, [1]

> (greater)

in string formatting

in struct format strings

opérateur, [1]

>=

opérateur, [1]

>>

opérateur, [1]

>>=

augmented assignment

>>>

interpreter prompt, [1]

? (question mark)

in a command interpreter

in argparse module

in AST grammar

in glob-style wildcards, [1]

in regular expressions

in SQL statements

in struct format strings, [1]

replacement character

??

in regular expressions

@ (at)

class definition

function definition

in struct format strings

opérateur

[] (square brackets)

in assignment target list

in glob-style wildcards, [1]

in regular expressions

in string formatting

list expression

subscription

\ (backslash)

escape sequence, [1]

in pathnames (Windows)

in regular expressions, [1], [2]

\\

escape sequence

in regular expressions

\A

in regular expressions

\a

escape sequence

in regular expressions

\B

in regular expressions

\b

escape sequence

in regular expressions, [1]

\D

in regular expressions

\d

in regular expressions

\f

escape sequence

in regular expressions

\g

in regular expressions

\N

escape sequence, [1]

in regular expressions

\n

escape sequence

in regular expressions

\r

escape sequence

in regular expressions

\S

in regular expressions

\s

in regular expressions

\t

escape sequence

in regular expressions

\U

escape sequence, [1]

in regular expressions

\u

escape sequence, [1]

in regular expressions

\v

escape sequence

in regular expressions

\W

in regular expressions

\w

in regular expressions

\x

escape sequence, [1]

in regular expressions

\Z

in regular expressions

^ (caret)

in curses module

in regular expressions, [1]

in string formatting

marker, [1]

opérateur, [1]

^=

augmented assignment

{} (curly brackets)

dictionary expression

in formatted string literal

in regular expressions

in string formatting

set expression

| (vertical bar)

in regular expressions

opérateur, [1]

|=

augmented assignment

~ (tilde)

home directory expansion

opérateur, [1]

Navigation

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modules |

Python »

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© Copyright 2001-2020, Python Software Foundation.
La Python Software Foundation est une organisation à but non lucratif. Les dons sont bienvenus.
Mis à jour le juin 29, 2020. Vous avez trouvé un bug ?
Créé via Sphinx 2.3.1.

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Index – T

T_FMT (dans le module locale)

T_FMT_AMPM (dans le module locale)

tab

tab() (méthode tkinter.ttk.Notebook)

TabError

tableau de correspondances

tabnanny (module)

tabs() (méthode tkinter.ttk.Notebook)

tabsize (attribut textwrap.TextWrapper)

tabular

data

tag (attribut xml.etree.ElementTree.Element)

tag_bind() (méthode tkinter.ttk.Treeview)

tag_configure() (méthode tkinter.ttk.Treeview)

tag_has() (méthode tkinter.ttk.Treeview)

tagName (attribut xml.dom.Element)

tail (attribut xml.etree.ElementTree.Element)

take_snapshot() (dans le module tracemalloc)

takewhile() (dans le module itertools)

tan() (dans le module cmath)

(dans le module math)

tanh() (dans le module cmath)

(dans le module math)

TarError

TarFile (classe dans tarfile), [1]

tarfile (module)

tarfile command line option

--create <tarfile> <source1> ... <sourceN>

--extract <tarfile> [<output_dir>]

--list <tarfile>

--test <tarfile>

--verbose

-c <tarfile> <source1> ... <sourceN>

-e <tarfile> [<output_dir>]

-l <tarfile>

-t <tarfile>

-v

target

deletion

list, [1], [2]

list assignment

list, deletion

loop control

target (attribut xml.dom.ProcessingInstruction)

TarInfo (classe dans tarfile)

Task (classe dans asyncio)

task_done() (méthode asyncio.Queue)

(méthode multiprocessing.JoinableQueue)

(méthode queue.Queue)

tau (dans le module cmath)

(dans le module math)

tb_frame (traceback attribute)

tb_lasti (traceback attribute)

tb_lineno (traceback attribute)

tb_locals (attribut unittest.TestResult)

tb_next (traceback attribute)

tbreak (pdb command)

tcdrain() (dans le module termios)

tcflow() (dans le module termios)

tcflush() (dans le module termios)

tcgetattr() (dans le module termios)

tcgetpgrp() (dans le module os)

Tcl() (dans le module tkinter)

TCL_LIBRARY

TCPServer (classe dans socketserver)

tcsendbreak() (dans le module termios)

tcsetattr() (dans le module termios)

tcsetpgrp() (dans le module os)

tearDown() (méthode unittest.TestCase)

tearDownClass() (méthode unittest.TestCase)

tee() (dans le module itertools)

tell() (méthode aifc.aifc), [1]

(méthode chunk.Chunk)

(méthode io.IOBase)

(méthode io.TextIOBase)

(méthode mmap.mmap)

(méthode sunau.AU_read)

(méthode sunau.AU_write)

(méthode wave.Wave_read)

(méthode wave.Wave_write)

Telnet (classe dans telnetlib)

telnetlib (module)

TEMP

temp_cwd() (dans le module test.support)

temp_dir() (dans le module test.support)

temp_umask() (dans le module test.support)

tempdir (dans le module tempfile)

tempfile (module)

template (attribut string.Template)

Template (classe dans pipes)

(classe dans string)

temporary

file

file name

TemporaryDirectory() (dans le module tempfile)

TemporaryFile() (dans le module tempfile)

teredo (attribut ipaddress.IPv6Address)

TERM, [1]

termattrs() (dans le module curses)

terminal_size (classe dans os)

terminate() (méthode asyncio.asyncio.subprocess.Process)

(méthode asyncio.BaseSubprocessTransport)

(méthode multiprocessing.pool.Pool)

(méthode multiprocessing.Process)

(méthode subprocess.Popen)

termination model

termios (module)

termname() (dans le module curses)

ternary

operator

test

identity

membership

test (attribut doctest.DocTestFailure)

(attribut doctest.UnexpectedException)

(module)

test() (dans le module cgi)

test.support (module)

TestCase (classe dans unittest)

TestFailed

testfile() (dans le module doctest)

TESTFN (dans le module test.support)

TestLoader (classe dans unittest)

testMethodPrefix (attribut unittest.TestLoader)

testmod() (dans le module doctest)

TestResult (classe dans unittest)

tests (dans le module imghdr)

testsource() (dans le module doctest)

testsRun (attribut unittest.TestResult)

TestSuite (classe dans unittest)

testzip() (méthode zipfile.ZipFile)

text (attribut traceback.TracebackException)

(attribut xml.etree.ElementTree.Element)

Text (classe dans typing)

text (dans le module msilib)

text mode

text() (méthode msilib.Dialog)

text_factory (attribut sqlite3.Connection)

Textbox (classe dans curses.textpad)

TextCalendar (classe dans calendar)

textdomain() (dans le module gettext)

(dans le module locale)

TextFile (classe dans distutils.text_file)

textinput() (dans le module turtle)

TextIO (classe dans typing)

TextIOBase (classe dans io)

TextIOWrapper (classe dans io)

TextTestResult (classe dans unittest)

TextTestRunner (classe dans unittest)

textwrap (module)

TextWrapper (classe dans textwrap)

theme_create() (méthode tkinter.ttk.Style)

theme_names() (méthode tkinter.ttk.Style)

theme_settings() (méthode tkinter.ttk.Style)

theme_use() (méthode tkinter.ttk.Style)

THOUSEP (dans le module locale)

Thread (classe dans threading)

thread() (méthode imaplib.IMAP4)

thread_info (dans le module sys)

threading (module)

ThreadingMixIn (classe dans socketserver)

ThreadingTCPServer (classe dans socketserver)

ThreadingUDPServer (classe dans socketserver)

ThreadPoolExecutor (classe dans concurrent.futures)

threads

POSIX

throw (2to3 fixer)

throw() (méthode coroutine)

(méthode generator)

ticket_lifetime_hint (attribut ssl.SSLSession)

tigetflag() (dans le module curses)

tigetnum() (dans le module curses)

tigetstr() (dans le module curses)

TILDE (dans le module token)

tilt() (dans le module turtle)

tiltangle() (dans le module turtle)

time (attribut ssl.SSLSession)

(classe dans datetime)

(module)

time() (dans le module time)

(méthode asyncio.AbstractEventLoop)

(méthode datetime.datetime)

Time2Internaldate() (dans le module imaplib)

timedelta (classe dans datetime)

TimedRotatingFileHandler (classe dans logging.handlers)

timegm() (dans le module calendar)

timeit (module)

timeit command line option

--clock

--help

--number=N

--process

--repeat=N

--setup=S

--time

--unit=U

--verbose

-c

-h

-n N

-p

-r N

-s S

-t

-u

-v

timeit() (dans le module timeit)

(méthode timeit.Timer)

timeout

(attribut socketserver.BaseServer)

(attribut ssl.SSLSession)

(attribut subprocess.TimeoutExpired)

timeout() (méthode curses.window)

TIMEOUT_MAX (dans le module _thread)

(dans le module threading)

TimeoutError, [1], [2], [3]

TimeoutExpired

Timer (classe dans threading)

(classe dans timeit)

times() (dans le module os)

timestamp() (méthode datetime.datetime)

timetuple() (méthode datetime.date)

(méthode datetime.datetime)

timetz() (méthode datetime.datetime)

timezone (classe dans datetime)

(dans le module time)

title() (dans le module turtle)

(méthode bytearray)

(méthode bytes)

(méthode str)

Tix

tix_addbitmapdir() (méthode tkinter.tix.tixCommand)

tix_cget() (méthode tkinter.tix.tixCommand)

tix_configure() (méthode tkinter.tix.tixCommand)

tix_filedialog() (méthode tkinter.tix.tixCommand)

tix_getbitmap() (méthode tkinter.tix.tixCommand)

tix_getimage() (méthode tkinter.tix.tixCommand)

TIX_LIBRARY

tix_option_get() (méthode tkinter.tix.tixCommand)

tix_resetoptions() (méthode tkinter.tix.tixCommand)

tixCommand (classe dans tkinter.tix)

Tk

(classe dans tkinter)

(classe dans tkinter.tix)

Tk Option Data Types

TK_LIBRARY

Tkinter

tkinter (module)

tkinter.scrolledtext (module)

tkinter.tix (module)

tkinter.ttk (module)

TList (classe dans tkinter.tix)

TLS

TMP

TMPDIR

to_bytes() (méthode int)

to_eng_string() (méthode decimal.Context)

(méthode decimal.Decimal)

to_integral() (méthode decimal.Decimal)

to_integral_exact() (méthode decimal.Context)

(méthode decimal.Decimal)

to_integral_value() (méthode decimal.Decimal)

to_sci_string() (méthode decimal.Context)

ToASCII() (dans le module encodings.idna)

tobuf() (méthode tarfile.TarInfo)

tobytes() (méthode array.array)

(méthode memoryview)

today() (méthode de la classe datetime.date)

(méthode de la classe datetime.datetime)

tofile() (méthode array.array)

tok_name (dans le module token)

token

(attribut shlex.shlex)

(module)

token_bytes() (dans le module secrets)

token_hex() (dans le module secrets)

token_urlsafe() (dans le module secrets)

TokenError

tokenize (module)

tokenize command line option

--exact

--help

-e

-h

tokenize() (dans le module tokenize)

tolist() (méthode array.array)

(méthode memoryview)

(méthode parser.ST)

tomono() (dans le module audioop)

toordinal() (méthode datetime.date)

(méthode datetime.datetime)

top() (méthode curses.panel.Panel)

(méthode poplib.POP3)

top_panel() (dans le module curses.panel)

toprettyxml() (méthode xml.dom.minidom.Node)

tostereo() (dans le module audioop)

tostring() (dans le module xml.etree.ElementTree)

(méthode array.array)

tostringlist() (dans le module xml.etree.ElementTree)

total_changes (attribut sqlite3.Connection)

total_ordering() (dans le module functools)

total_seconds() (méthode datetime.timedelta)

totuple() (méthode parser.ST)

touch() (méthode pathlib.Path)

touchline() (méthode curses.window)

touchwin() (méthode curses.window)

ToUnicode() (dans le module encodings.idna)

tounicode() (méthode array.array)

towards() (dans le module turtle)

toxml() (méthode xml.dom.minidom.Node)

tp_as_async (membre C)

tp_as_mapping (membre C)

tp_as_number (membre C)

tp_as_sequence (membre C)

tparm() (dans le module curses)

trace

stack

Trace (classe dans trace)

(classe dans tracemalloc)

trace (module)

trace command line option

--count

--coverdir=<dir>

--file=<file>

--help

--ignore-dir=<dir>

--ignore-module=<mod>

--listfuncs

--missing

--no-report

--report

--summary

--timing

--trace

--trackcalls

--version

-c

-C

-f

-g

-l

-m

-r

-R

-s

-t

-T

trace function, [1], [2]

trace() (dans le module inspect)

trace_dispatch() (méthode bdb.Bdb)

traceback

objet, [1], [2], [3], [4]

traceback (attribut tracemalloc.Statistic)

(attribut tracemalloc.StatisticDiff)

(attribut tracemalloc.Trace)

Traceback (classe dans tracemalloc)

traceback (module)

traceback_limit (attribut tracemalloc.Snapshot)

(attribut wsgiref.handlers.BaseHandler)

TracebackException (classe dans traceback)

tracebacklimit (dans le module sys)

tracebacks

in CGI scripts

TracebackType (dans le module types)

tracemalloc (module)

tracer() (dans le module turtle)

traces (attribut tracemalloc.Snapshot)

trailing

comma

tranche

transfercmd() (méthode ftplib.FTP)

TransientResource (classe dans test.support)

translate() (dans le module fnmatch)

(méthode bytearray)

(méthode bytes)

(méthode str)

translation() (dans le module gettext)

transport (attribut asyncio.StreamWriter)

Transport Layer Security

traverseproc (type C)

Tree (classe dans tkinter.tix)

TreeBuilder (classe dans xml.etree.ElementTree)

Treeview (classe dans tkinter.ttk)

triangular() (dans le module random)

triple-quoted string

True, [1], [2]

true

True (variable de base)

truediv() (dans le module operator)

trunc() (dans le module math)

(in module math)

truncate() (dans le module os)

(méthode io.IOBase)

truth

value

truth() (dans le module operator)

try

état, [1], [2]

ttk

tty

I/O control

tty (module)

ttyname() (dans le module os)

tuple

display

empty, [1]

fonction de base, [1]

objet, [1], [2], [3], [4], [5], [6]

singleton

tuple (classe de base)

Tuple (dans le module typing)

tuple2st() (dans le module parser)

tuple_params (2to3 fixer)

turnoff_sigfpe() (dans le module fpectl)

turnon_sigfpe() (dans le module fpectl)

Turtle (classe dans turtle)

turtle (module)

turtledemo (module)

turtles() (dans le module turtle)

TurtleScreen (classe dans turtle)

turtlesize() (dans le module turtle)

type, [1]

Boolean

data

fonction de base, [1], [2], [3]

hierarchy

immutable data

objet, [1], [2]

operations on dictionary

operations on list

type (attribut optparse.Option)

(attribut socket.socket)

(attribut tarfile.TarInfo)

(attribut urllib.request.Request)

Type (classe dans typing)

type (classe de base)

type of an object

TYPE_CHECKER (attribut optparse.Option)

TYPE_CHECKING (dans le module typing)

typeahead() (dans le module curses)

typecode (attribut array.array)

typecodes (dans le module array)

TYPED_ACTIONS (attribut optparse.Option)

typed_subpart_iterator() (dans le module email.iterators)

TypeError

exception

types

built-in

immutable sequence

module

mutable sequence

operations on integer

operations on mapping

operations on numeric

operations on sequence, [1]

types (2to3 fixer)

TYPES (attribut optparse.Option)

types (module)

types, internal

types_map (attribut mimetypes.MimeTypes)

(dans le module mimetypes)

types_map_inv (attribut mimetypes.MimeTypes)

TypeVar (classe dans typing)

typing (module)

TZ, [1], [2], [3], [4]

tzinfo (attribut datetime.datetime)

(attribut datetime.time)

(classe dans datetime)

tzname (dans le module time)

tzname() (méthode datetime.datetime)

(méthode datetime.time)

(méthode datetime.timezone)

(méthode datetime.tzinfo)

tzset() (dans le module time)

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Index – U

u"

string literal

u'

string literal

u-LAW, [1], [2]

ucd_3_2_0 (dans le module unicodedata)

udata (attribut select.kevent)

UDPServer (classe dans socketserver)

UF_APPEND (dans le module stat)

UF_COMPRESSED (dans le module stat)

UF_HIDDEN (dans le module stat)

UF_IMMUTABLE (dans le module stat)

UF_NODUMP (dans le module stat)

UF_NOUNLINK (dans le module stat)

UF_OPAQUE (dans le module stat)

uid (attribut tarfile.TarInfo)

uid() (méthode imaplib.IMAP4)

uidl() (méthode poplib.POP3)

ulaw2lin() (dans le module audioop)

ULONG_MAX

umask() (dans le module os)

unalias (pdb command)

uname (attribut tarfile.TarInfo)

uname() (dans le module os)

(dans le module platform)

unary

arithmetic operation

bitwise operation

UNARY_INVERT (opcode)

UNARY_NEGATIVE (opcode)

UNARY_NOT (opcode)

UNARY_POSITIVE (opcode)

unbinding

name

UnboundLocalError, [1]

unbuffered I/O

UNC paths

and os.makedirs()

unconsumed_tail (attribut zlib.Decompress)

unctrl() (dans le module curses)

(dans le module curses.ascii)

undefine_macro() (méthode distutils.ccompiler.CCompiler)

Underflow (classe dans decimal)

undisplay (pdb command)

undo() (dans le module turtle)

undobufferentries() (dans le module turtle)

undoc_header (attribut cmd.Cmd)

unescape() (dans le module html)

(dans le module xml.sax.saxutils)

UnexpectedException

unexpectedSuccesses (attribut unittest.TestResult)

unget_wch() (dans le module curses)

ungetch() (dans le module curses)

(dans le module msvcrt)

ungetmouse() (dans le module curses)

ungetwch() (dans le module msvcrt)

unhexlify() (dans le module binascii)

Unicode, [1], [2]

database

unicode (2to3 fixer)

Unicode Consortium

unicodedata (module)

UnicodeDecodeError

UnicodeEncodeError

UnicodeError

UnicodeTranslateError

UnicodeWarning

unidata_version (dans le module unicodedata)

unified_diff() (dans le module difflib)

uniform() (dans le module random)

UnimplementedFileMode

Union (classe dans ctypes)

(dans le module typing)

union() (méthode frozenset)

unique() (dans le module enum), [1]

unittest (module)

unittest command line option

--buffer

--catch

--failfast

--locals

-b

-c

-f

unittest-discover command line option

--pattern pattern

--start-directory directory

--top-level-directory directory

--verbose

-p

-s

-t

-v

unittest.mock (module)

universal newlines

bytearray.splitlines method

bytes.splitlines method

csv.reader function

importlib.abc.InspectLoader.get_source method

io.IncrementalNewlineDecoder class

io.TextIOWrapper class

open() built-in function

str.splitlines method

subprocess module

What's new, [1], [2], [3]

UNIX

file control

I/O control

unix_dialect (classe dans csv)

UnixDatagramServer (classe dans socketserver)

UnixStreamServer (classe dans socketserver)

unknown_decl() (méthode html.parser.HTMLParser)

unknown_open() (méthode urllib.request.BaseHandler)

(méthode urllib.request.UnknownHandler)

UnknownHandler (classe dans urllib.request)

UnknownProtocol

UnknownTransferEncoding

unlink() (dans le module os)

(méthode pathlib.Path)

(méthode xml.dom.minidom.Node)

unlock() (méthode mailbox.Babyl)

(méthode mailbox.Mailbox)

(méthode mailbox.Maildir)

(méthode mailbox.mbox)

(méthode mailbox.MH)

(méthode mailbox.MMDF)

unpack() (dans le module struct)

(méthode struct.Struct)

unpack_archive() (dans le module shutil)

unpack_array() (méthode xdrlib.Unpacker)

unpack_bytes() (méthode xdrlib.Unpacker)

unpack_double() (méthode xdrlib.Unpacker)

UNPACK_EX (opcode)

unpack_farray() (méthode xdrlib.Unpacker)

unpack_float() (méthode xdrlib.Unpacker)

unpack_fopaque() (méthode xdrlib.Unpacker)

unpack_from() (dans le module struct)

(méthode struct.Struct)

unpack_fstring() (méthode xdrlib.Unpacker)

unpack_list() (méthode xdrlib.Unpacker)

unpack_opaque() (méthode xdrlib.Unpacker)

UNPACK_SEQUENCE (opcode)

unpack_string() (méthode xdrlib.Unpacker)

Unpacker (classe dans xdrlib)

unpacking

dictionary

in function calls

iterable

unparsedEntityDecl() (méthode xml.sax.handler.DTDHandler)

UnparsedEntityDeclHandler() (méthode xml.parsers.expat.xmlparser)

Unpickler (classe dans pickle)

UnpicklingError

unquote() (dans le module email.utils)

(dans le module urllib.parse)

unquote_plus() (dans le module urllib.parse)

unquote_to_bytes() (dans le module urllib.parse)

unreachable object

unreadline() (méthode distutils.text_file.TextFile)

unrecognized escape sequence

unregister() (dans le module atexit)

(dans le module faulthandler)

(méthode select.devpoll)

(méthode select.epoll)

(méthode select.poll)

(méthode selectors.BaseSelector)

unregister_archive_format() (dans le module shutil)

unregister_dialect() (dans le module csv)

unregister_unpack_format() (dans le module shutil)

unset() (méthode test.support.EnvironmentVarGuard)

unsetenv() (dans le module os)

UnstructuredHeader (classe dans email.headerregistry)

unsubscribe() (méthode imaplib.IMAP4)

UnsupportedOperation

until (pdb command)

untokenize() (dans le module tokenize)

untouchwin() (méthode curses.window)

unused_data (attribut bz2.BZ2Decompressor)

(attribut lzma.LZMADecompressor)

(attribut zlib.Decompress)

unverifiable (attribut urllib.request.Request)

unwrap() (dans le module inspect)

(méthode ssl.SSLSocket)

up (pdb command)

up() (dans le module turtle)

update() (dans le module turtle)

(méthode collections.Counter)

(méthode dict)

(méthode frozenset)

(méthode hashlib.hash)

(méthode hmac.HMAC)

(méthode http.cookies.Morsel)

(méthode mailbox.Mailbox)

(méthode mailbox.Maildir)

(méthode trace.CoverageResults)

update_authenticated() (méthode urllib.request.HTTPPasswordMgrWithPriorAuth)

update_lines_cols() (dans le module curses)

update_panels() (dans le module curses.panel)

update_visible() (méthode mailbox.BabylMessage)

update_wrapper() (dans le module functools)

upper() (méthode bytearray)

(méthode bytes)

(méthode str)

urandom() (dans le module os)

URL, [1], [2], [3]

parsing

relative

url (attribut xmlrpc.client.ProtocolError)

url2pathname() (dans le module urllib.request)

urlcleanup() (dans le module urllib.request)

urldefrag() (dans le module urllib.parse)

urlencode() (dans le module urllib.parse)

URLError

urljoin() (dans le module urllib.parse)

urllib (2to3 fixer)

(module)

urllib.error (module)

urllib.parse (module)

urllib.request

module

urllib.request (module)

urllib.response (module)

urllib.robotparser (module)

urlopen() (dans le module urllib.request)

URLopener (classe dans urllib.request)

urlparse() (dans le module urllib.parse)

urlretrieve() (dans le module urllib.request)

urlsafe_b64decode() (dans le module base64)

urlsafe_b64encode() (dans le module base64)

urlsplit() (dans le module urllib.parse)

urlunparse() (dans le module urllib.parse)

urlunsplit() (dans le module urllib.parse)

urn (attribut uuid.UUID)

use_default_colors() (dans le module curses)

use_env() (dans le module curses)

use_rawinput (attribut cmd.Cmd)

UseForeignDTD() (méthode xml.parsers.expat.xmlparser)

USER

user

effective id

id

id, setting

user() (méthode poplib.POP3)

user-defined

function

function call

method

user-defined function

objet, [1], [2]

user-defined method

objet

USER_BASE

(dans le module site)

user_call() (méthode bdb.Bdb)

user_exception() (méthode bdb.Bdb)

user_line() (méthode bdb.Bdb)

user_return() (méthode bdb.Bdb)

USER_SITE (dans le module site)

usercustomize

module

UserDict (classe dans collections)

UserList (classe dans collections)

USERNAME, [1]

username (attribut email.headerregistry.Address)

USERPROFILE, [1]

userptr() (méthode curses.panel.Panel)

UserString (classe dans collections)

UserWarning

USTAR_FORMAT (dans le module tarfile)

UTC

utc (attribut datetime.timezone)

utcfromtimestamp() (méthode de la classe datetime.datetime)

utcnow() (méthode de la classe datetime.datetime)

utcoffset() (méthode datetime.datetime)

(méthode datetime.time)

(méthode datetime.timezone)

(méthode datetime.tzinfo)

utctimetuple() (méthode datetime.datetime)

utf8 (attribut email.policy.EmailPolicy)

utf8() (méthode poplib.POP3)

utf8_enabled (attribut imaplib.IMAP4)

utime() (dans le module os)

uu

module

uu (module)

UUID (classe dans uuid)

uuid (module)

uuid1

uuid1() (dans le module uuid)

uuid3

uuid3() (dans le module uuid)

uuid4

uuid4() (dans le module uuid)

uuid5

uuid5() (dans le module uuid)

UuidCreate() (dans le module msilib)

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Index – V

v4_int_to_packed() (dans le module ipaddress)

v6_int_to_packed() (dans le module ipaddress)

validator() (dans le module wsgiref.validate)

value

default parameter

truth

value (attribut ctypes._SimpleCData)

(attribut http.cookiejar.Cookie)

(attribut http.cookies.Morsel)

(attribut xml.dom.Attr)

value of an object

Value() (dans le module multiprocessing)

(dans le module multiprocessing.sharedctypes)

(méthode multiprocessing.managers.SyncManager)

value_decode() (méthode http.cookies.BaseCookie)

value_encode() (méthode http.cookies.BaseCookie)

ValueError

exception

valuerefs() (méthode weakref.WeakValueDictionary)

values

Boolean

writing

values() (méthode dict)

(méthode email.message.EmailMessage)

(méthode email.message.Message)

(méthode mailbox.Mailbox)

(méthode types.MappingProxyType)

ValuesView (classe dans collections.abc)

(classe dans typing)

variable

free

variable d'environnement

APPDATA

AUDIODEV

BROWSER, [1]

CC

CFLAGS, [1], [2]

COLS, [1]

COLUMNS, [1]

COMSPEC, [1]

CPP

CPPFLAGS

DISTUTILS_DEBUG

exec_prefix, [1], [2]

HOME, [1], [2], [3], [4]

HOMEDRIVE, [1]

HOMEPATH, [1]

http_proxy, [1], [2]

IDLE*STARTUP

IDLESTARTUP

KDEDIR

LANG, [1], [2], [3], [4]

LANGUAGE, [1]

LC_ALL, [1]

LC_MESSAGES, [1]

LDCXXSHARED

LDFLAGS

LINES, [1], [2], [3], [4]

LNAME

LOGNAME, [1]

MIXERDEV

no_proxy

PAGER

PATH, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20], [21], [22], [23], [24], [25], [26], [27], [28], [29], [30], [31], [32], [33], [34]

PATHEXT, [1]

PLAT

POSIXLY_CORRECT

prefix, [1], [2], [3]

PYTHON*, [1], [2]

PYTHON_DOM

PYTHONASYNCIODEBUG, [1], [2]

PYTHONCASEOK, [1]

PYTHONDEBUG, [1]

PYTHONDOCS

PYTHONDONDONTWRITEBYTECODE

PYTHONDONTWRITEBYTECODE, [1], [2], [3], [4]

PYTHONDUMPREFS, [1]

PYTHONEXECUTABLE

PYTHONFAULTHANDLER, [1], [2]

PYTHONHASHSEED, [1], [2], [3], [4], [5]

PYTHONHOME, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14]

PYTHONINSPECT, [1], [2]

PYTHONIOENCODING, [1], [2], [3], [4], [5]

PYTHONLEGACYWINDOWSFSENCODING, [1], [2]

PYTHONLEGACYWINDOWSSTDIO, [1], [2]

PYTHONMALLOC, [1], [2], [3], [4], [5], [6]

PYTHONMALLOCSTATS, [1], [2]

PYTHONNOUSERSITE, [1], [2], [3]

PYTHONOPTIMIZE, [1]

PYTHONPATH, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20], [21], [22]

PYTHONSHOWALLOCCOUNT

PYTHONSHOWREFCOUNT

PYTHONSTARTUP, [1], [2], [3], [4], [5], [6], [7], [8], [9]

PYTHONTHREADDEBUG

PYTHONTRACEMALLOC, [1], [2], [3]

PYTHONUNBUFFERED, [1]

PYTHONUSERBASE, [1], [2], [3]

PYTHONVERBOSE, [1]

PYTHONWARNINGS, [1], [2], [3], [4]

SSL_CERT_FILE

SSL_CERT_PATH

SystemRoot

TCL_LIBRARY

TEMP

TERM, [1]

TIX_LIBRARY

TK_LIBRARY

TMP

TMPDIR

TZ, [1], [2], [3], [4]

USER

USER_BASE

USERNAME, [1]

USERPROFILE, [1]

variable de classe

variance() (dans le module statistics)

variant (attribut uuid.UUID)

vars() (fonction de base)

vbar (attribut tkinter.scrolledtext.ScrolledText)

VBAR (dans le module token)

VBAREQUAL (dans le module token)

Vec2D (classe dans turtle)

venv (module)

VERBOSE (dans le module re)

verbose (dans le module tabnanny)

(dans le module test.support)

verify() (méthode smtplib.SMTP)

verify_client_post_handshake() (méthode ssl.SSLSocket)

VERIFY_CRL_CHECK_CHAIN (dans le module ssl)

VERIFY_CRL_CHECK_LEAF (dans le module ssl)

VERIFY_DEFAULT (dans le module ssl)

verify_flags (attribut ssl.SSLContext)

verify_mode (attribut ssl.SSLContext)

verify_request() (méthode socketserver.BaseServer)

VERIFY_X509_STRICT (dans le module ssl)

VERIFY_X509_TRUSTED_FIRST (dans le module ssl)

VerifyFlags (classe dans ssl)

VerifyMode (classe dans ssl)

verrou global de l'interpréteur

version (attribut email.headerregistry.MIMEVersionHeader)

(attribut http.client.HTTPResponse)

(attribut http.cookiejar.Cookie)

(attribut ipaddress.IPv4Address)

(attribut ipaddress.IPv4Network)

(attribut ipaddress.IPv6Address)

(attribut ipaddress.IPv6Network)

(attribut urllib.request.URLopener)

(attribut uuid.UUID)

(dans le module curses)

(dans le module marshal)

(dans le module sqlite3)

(dans le module sys)

(in module sys), [1], [2]

version() (dans le module ensurepip)

(dans le module platform)

(méthode ssl.SSLSocket)

version_info (dans le module sqlite3)

(dans le module sys)

version_string() (méthode http.server.BaseHTTPRequestHandler)

vformat() (méthode string.Formatter)

virtual

Environments

visit() (méthode ast.NodeVisitor)

visitproc (type C)

vline() (méthode curses.window)

voidcmd() (méthode ftplib.FTP)

volume (attribut zipfile.ZipInfo)

vonmisesvariate() (dans le module random)

vue de dictionnaire

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Index – W

W_OK (dans le module os)

wait() (dans le module asyncio)

(dans le module concurrent.futures)

(dans le module multiprocessing.connection)

(dans le module os)

(méthode asyncio.asyncio.subprocess.Process)

(méthode asyncio.Condition)

(méthode asyncio.Event)

(méthode multiprocessing.pool.AsyncResult)

(méthode subprocess.Popen)

(méthode threading.Barrier)

(méthode threading.Condition)

(méthode threading.Event)

wait3() (dans le module os)

wait4() (dans le module os)

wait_closed() (méthode asyncio.Server)

wait_for() (dans le module asyncio)

(méthode asyncio.Condition)

(méthode threading.Condition)

waitid() (dans le module os)

waitpid() (dans le module os)

walk() (dans le module ast)

(dans le module os)

(méthode email.message.EmailMessage)

(méthode email.message.Message)

walk_packages() (dans le module pkgutil)

walk_stack() (dans le module traceback)

walk_tb() (dans le module traceback)

want (attribut doctest.Example)

warn() (dans le module warnings)

(méthode distutils.ccompiler.CCompiler)

(méthode distutils.text_file.TextFile)

warn_explicit() (dans le module warnings)

Warning, [1]

warning() (dans le module logging)

(méthode logging.Logger)

(méthode xml.sax.handler.ErrorHandler)

warnings

(module)

WarningsRecorder (classe dans test.support)

warnoptions (dans le module sys)

wasSuccessful() (méthode unittest.TestResult)

WatchedFileHandler (classe dans logging.handlers)

wave (module)

WCONTINUED (dans le module os)

WCOREDUMP() (dans le module os)

WeakKeyDictionary (classe dans weakref)

WeakMethod (classe dans weakref)

weakref (module)

WeakSet (classe dans weakref)

WeakValueDictionary (classe dans weakref)

webbrowser (module)

weekday() (dans le module calendar)

(méthode datetime.date)

(méthode datetime.datetime)

weekheader() (dans le module calendar)

weibullvariate() (dans le module random)

WEXITED (dans le module os)

WEXITSTATUS() (dans le module os)

wfile (attribut http.server.BaseHTTPRequestHandler)

what() (dans le module imghdr)

(dans le module sndhdr)

whathdr() (dans le module sndhdr)

whatis (pdb command)

where (pdb command)

which() (dans le module shutil)

whichdb() (dans le module dbm)

while

état, [1], [2], [3]

whitespace (attribut shlex.shlex)

(dans le module string)

whitespace_split (attribut shlex.shlex)

Widget (classe dans tkinter.ttk)

width (attribut textwrap.TextWrapper)

width() (dans le module turtle)

WIFCONTINUED() (dans le module os)

WIFEXITED() (dans le module os)

WIFSIGNALED() (dans le module os)

WIFSTOPPED() (dans le module os)

win32_ver() (dans le module platform)

WinDLL (classe dans ctypes)

window manager (widgets)

window() (méthode curses.panel.Panel)

window_height() (dans le module turtle)

window_width() (dans le module turtle)

Windows

Windows ini file

WindowsError

WindowsPath (classe dans pathlib)

WindowsRegistryFinder (classe dans importlib.machinery)

winerror (attribut OSError)

WinError() (dans le module ctypes)

WINFUNCTYPE() (dans le module ctypes)

winreg (module)

WinSock

winsound (module)

winver (dans le module sys)

with

état, [1]

WITH_CLEANUP_FINISH (opcode)

WITH_CLEANUP_START (opcode)

with_hostmask (attribut ipaddress.IPv4Interface)

(attribut ipaddress.IPv4Network)

(attribut ipaddress.IPv6Interface)

(attribut ipaddress.IPv6Network)

with_name() (méthode pathlib.PurePath)

with_netmask (attribut ipaddress.IPv4Interface)

(attribut ipaddress.IPv4Network)

(attribut ipaddress.IPv6Interface)

(attribut ipaddress.IPv6Network)

with_prefixlen (attribut ipaddress.IPv4Interface)

(attribut ipaddress.IPv4Network)

(attribut ipaddress.IPv6Interface)

(attribut ipaddress.IPv6Network)

with_suffix() (méthode pathlib.PurePath)

with_traceback() (méthode BaseException)

WNOHANG (dans le module os)

WNOWAIT (dans le module os)

wordchars (attribut shlex.shlex)

World Wide Web, [1], [2]

wrap() (dans le module textwrap)

(méthode textwrap.TextWrapper)

wrap_bio() (méthode ssl.SSLContext)

wrap_future() (dans le module asyncio)

wrap_socket() (dans le module ssl)

(méthode ssl.SSLContext)

wrap_text() (dans le module distutils.fancy_getopt)

wrapper() (dans le module curses)

wraps() (dans le module functools)

WRITABLE (dans le module tkinter)

writable() (méthode asyncore.dispatcher)

(méthode io.IOBase)

write() (dans le module os)

(dans le module turtle)

(méthode asyncio.StreamWriter)

(méthode asyncio.WriteTransport)

(méthode code.InteractiveInterpreter)

(méthode codecs.StreamWriter)

(méthode configparser.ConfigParser)

(méthode email.generator.BytesGenerator)

(méthode email.generator.Generator)

(méthode io.BufferedIOBase)

(méthode io.BufferedWriter)

(méthode io.RawIOBase)

(méthode io.TextIOBase)

(méthode mmap.mmap)

(méthode ossaudiodev.oss_audio_device)

(méthode ssl.MemoryBIO)

(méthode ssl.SSLSocket)

(méthode telnetlib.Telnet)

(méthode xml.etree.ElementTree.ElementTree)

(méthode zipfile.ZipFile)

write_byte() (méthode mmap.mmap)

write_bytes() (méthode pathlib.Path)

write_docstringdict() (dans le module turtle)

write_eof() (méthode asyncio.StreamWriter)

(méthode asyncio.WriteTransport)

(méthode ssl.MemoryBIO)

write_file() (dans le module distutils.file_util)

write_history_file() (dans le module readline)

WRITE_RESTRICTED

write_results() (méthode trace.CoverageResults)

write_text() (méthode pathlib.Path)

writeall() (méthode ossaudiodev.oss_audio_device)

writeframes() (méthode aifc.aifc)

(méthode sunau.AU_write)

(méthode wave.Wave_write)

writeframesraw() (méthode aifc.aifc)

(méthode sunau.AU_write)

(méthode wave.Wave_write)

writeheader() (méthode csv.DictWriter)

writelines() (méthode asyncio.StreamWriter)

(méthode asyncio.WriteTransport)

(méthode codecs.StreamWriter)

(méthode io.IOBase)

writePlist() (dans le module plistlib)

writePlistToBytes() (dans le module plistlib)

writepy() (méthode zipfile.PyZipFile)

writer (attribut formatter.formatter)

writer() (dans le module csv)

writerow() (méthode csv.csvwriter)

writerows() (méthode csv.csvwriter)

writestr() (méthode zipfile.ZipFile)

WriteTransport (classe dans asyncio)

writev() (dans le module os)

writexml() (méthode xml.dom.minidom.Node)

writing

values

WrongDocumentErr

ws_comma (2to3 fixer)

wsgi_file_wrapper (attribut wsgiref.handlers.BaseHandler)

wsgi_multiprocess (attribut wsgiref.handlers.BaseHandler)

wsgi_multithread (attribut wsgiref.handlers.BaseHandler)

wsgi_run_once (attribut wsgiref.handlers.BaseHandler)

wsgiref (module)

wsgiref.handlers (module)

wsgiref.headers (module)

wsgiref.simple_server (module)

wsgiref.util (module)

wsgiref.validate (module)

WSGIRequestHandler (classe dans wsgiref.simple_server)

WSGIServer (classe dans wsgiref.simple_server)

wShowWindow (attribut subprocess.STARTUPINFO)

WSTOPPED (dans le module os)

WSTOPSIG() (dans le module os)

wstring_at() (dans le module ctypes)

WTERMSIG() (dans le module os)

WUNTRACED (dans le module os)

WWW, [1], [2]

server, [1]

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Index – X

X (dans le module re)

X509 certificate

X_OK (dans le module os)

xatom() (méthode imaplib.IMAP4)

XATTR_CREATE (dans le module os)

XATTR_REPLACE (dans le module os)

XATTR_SIZE_MAX (dans le module os)

xcor() (dans le module turtle)

XDR

xdrlib (module)

xhdr() (méthode nntplib.NNTP)

XHTML

XHTML_NAMESPACE (dans le module xml.dom)

xml (module)

XML() (dans le module xml.etree.ElementTree)

xml.dom (module)

xml.dom.minidom (module)

xml.dom.pulldom (module)

xml.etree.ElementTree (module)

xml.parsers.expat (module)

xml.parsers.expat.errors (module)

xml.parsers.expat.model (module)

xml.sax (module)

xml.sax.handler (module)

xml.sax.saxutils (module)

xml.sax.xmlreader (module)

XML_ERROR_ABORTED (dans le module xml.parsers.expat.errors)

XML_ERROR_ASYNC_ENTITY (dans le module xml.parsers.expat.errors)

XML_ERROR_ATTRIBUTE_EXTERNAL_ENTITY_REF (dans le module xml.parsers.expat.errors)

XML_ERROR_BAD_CHAR_REF (dans le module xml.parsers.expat.errors)

XML_ERROR_BINARY_ENTITY_REF (dans le module xml.parsers.expat.errors)

XML_ERROR_CANT_CHANGE_FEATURE_ONCE_PARSING (dans le module xml.parsers.expat.errors)

XML_ERROR_DUPLICATE_ATTRIBUTE (dans le module xml.parsers.expat.errors)

XML_ERROR_ENTITY_DECLARED_IN_PE (dans le module xml.parsers.expat.errors)

XML_ERROR_EXTERNAL_ENTITY_HANDLING (dans le module xml.parsers.expat.errors)

XML_ERROR_FEATURE_REQUIRES_XML_DTD (dans le module xml.parsers.expat.errors)

XML_ERROR_FINISHED (dans le module xml.parsers.expat.errors)

XML_ERROR_INCOMPLETE_PE (dans le module xml.parsers.expat.errors)

XML_ERROR_INCORRECT_ENCODING (dans le module xml.parsers.expat.errors)

XML_ERROR_INVALID_TOKEN (dans le module xml.parsers.expat.errors)

XML_ERROR_JUNK_AFTER_DOC_ELEMENT (dans le module xml.parsers.expat.errors)

XML_ERROR_MISPLACED_XML_PI (dans le module xml.parsers.expat.errors)

XML_ERROR_NO_ELEMENTS (dans le module xml.parsers.expat.errors)

XML_ERROR_NO_MEMORY (dans le module xml.parsers.expat.errors)

XML_ERROR_NOT_STANDALONE (dans le module xml.parsers.expat.errors)

XML_ERROR_NOT_SUSPENDED (dans le module xml.parsers.expat.errors)

XML_ERROR_PARAM_ENTITY_REF (dans le module xml.parsers.expat.errors)

XML_ERROR_PARTIAL_CHAR (dans le module xml.parsers.expat.errors)

XML_ERROR_PUBLICID (dans le module xml.parsers.expat.errors)

XML_ERROR_RECURSIVE_ENTITY_REF (dans le module xml.parsers.expat.errors)

XML_ERROR_SUSPEND_PE (dans le module xml.parsers.expat.errors)

XML_ERROR_SUSPENDED (dans le module xml.parsers.expat.errors)

XML_ERROR_SYNTAX (dans le module xml.parsers.expat.errors)

XML_ERROR_TAG_MISMATCH (dans le module xml.parsers.expat.errors)

XML_ERROR_TEXT_DECL (dans le module xml.parsers.expat.errors)

XML_ERROR_UNBOUND_PREFIX (dans le module xml.parsers.expat.errors)

XML_ERROR_UNCLOSED_CDATA_SECTION (dans le module xml.parsers.expat.errors)

XML_ERROR_UNCLOSED_TOKEN (dans le module xml.parsers.expat.errors)

XML_ERROR_UNDECLARING_PREFIX (dans le module xml.parsers.expat.errors)

XML_ERROR_UNDEFINED_ENTITY (dans le module xml.parsers.expat.errors)

XML_ERROR_UNEXPECTED_STATE (dans le module xml.parsers.expat.errors)

XML_ERROR_UNKNOWN_ENCODING (dans le module xml.parsers.expat.errors)

XML_ERROR_XML_DECL (dans le module xml.parsers.expat.errors)

XML_NAMESPACE (dans le module xml.dom)

xmlcharrefreplace_errors() (dans le module codecs)

XmlDeclHandler() (méthode xml.parsers.expat.xmlparser)

XMLFilterBase (classe dans xml.sax.saxutils)

XMLGenerator (classe dans xml.sax.saxutils)

XMLID() (dans le module xml.etree.ElementTree)

XMLNS_NAMESPACE (dans le module xml.dom)

XMLParser (classe dans xml.etree.ElementTree)

XMLParserType (dans le module xml.parsers.expat)

XMLPullParser (classe dans xml.etree.ElementTree)

XMLReader (classe dans xml.sax.xmlreader)

xmlrpc.client (module)

xmlrpc.server (module)

xor

bitwise

xor() (dans le module operator)

xover() (méthode nntplib.NNTP)

xpath() (méthode nntplib.NNTP)

xrange (2to3 fixer)

xreadlines (2to3 fixer)

xview() (méthode tkinter.ttk.Treeview)

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Index – Y

Y2K

ycor() (dans le module turtle)

year (attribut datetime.date)

(attribut datetime.datetime)

Year 2000

Year 2038

yeardatescalendar() (méthode calendar.Calendar)

yeardays2calendar() (méthode calendar.Calendar)

yeardayscalendar() (méthode calendar.Calendar)

YESEXPR (dans le module locale)

yield

examples

expression

état

mot-clé

yield from (in What's New)

YIELD_FROM (opcode)

YIELD_VALUE (opcode)

yiq_to_rgb() (dans le module colorsys)

yview() (méthode tkinter.ttk.Treeview)

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Index – Z

ZeroDivisionError

exception

zfill() (méthode bytearray)

(méthode bytes)

(méthode str)

zip (2to3 fixer)

zip() (fonction de base)

ZIP_BZIP2 (dans le module zipfile)

ZIP_DEFLATED (dans le module zipfile)

zip_longest() (dans le module itertools)

ZIP_LZMA (dans le module zipfile)

ZIP_STORED (dans le module zipfile)

zipapp (module)

zipapp command line option

--help

--info

--main=<mainfn>

--output=<output>

--python=<interpreter>

-h

-m <mainfn>

-o <output>

-p <interpreter>

ZipFile (classe dans zipfile)

zipfile (module)

zipfile command line option

-c <zipfile> <source1> ... <sourceN>

-e <zipfile> <output_dir>

-l <zipfile>

-t <zipfile>

zipimport (module)

zipimporter (classe dans zipimport)

ZipImportError

ZipInfo (classe dans zipfile)

zlib (module)

ZLIB_RUNTIME_VERSION (dans le module zlib)

ZLIB_VERSION (dans le module zlib)

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Index – _

_ (underscore)

gettext

in numeric literal, [1]

in string formatting

_, identifiers

__, identifiers

__abs__() (dans le module operator)

(méthode object)

__add__() (dans le module operator)

(méthode object)

__aenter__() (méthode object)

__aexit__() (méthode object)

__aiter__() (méthode object)

__all__

(optional module attribute)

(package variable)

__and__() (dans le module operator)

(méthode object)

__anext__() (méthode agen)

(méthode object)

__annotations__ (class attribute)

(function attribute)

(module attribute)

__await__() (méthode object)

__bases__ (attribut class)

(class attribute)

__bool__() (méthode object)

(object method)

__bytes__() (méthode email.message.EmailMessage)

(méthode email.message.Message)

(méthode object)

__cached__

__call__() (méthode email.headerregistry.HeaderRegistry)

(méthode object)

(méthode weakref.finalize)

(object method)

__callback__ (attribut weakref.ref)

__cause__ (attribut traceback.TracebackException)

(exception attribute)

__ceil__() (méthode fractions.Fraction)

(méthode object)

__class__ (attribut instance)

(attribut unittest.mock.Mock)

(instance attribute)

(method cell)

(module attribute)

__classcell__ (class namespace entry)

__closure__ (function attribute)

__code__ (function attribute)

(function object attribute)

__complex__() (méthode object)

__concat__() (dans le module operator)

__contains__() (dans le module operator)

(méthode email.message.EmailMessage)

(méthode email.message.Message)

(méthode mailbox.Mailbox)

(méthode object)

__context__ (attribut traceback.TracebackException)

(exception attribute)

__copy__() (copy protocol)

__debug__

(variable de base)

__deepcopy__() (copy protocol)

__defaults__ (function attribute)

__del__() (méthode io.IOBase)

(méthode object)

__delattr__() (méthode object)

__delete__() (méthode object)

__delitem__() (dans le module operator)

(méthode email.message.EmailMessage)

(méthode email.message.Message)

(méthode mailbox.Mailbox)

(méthode mailbox.MH)

(méthode object)

__dict__ (attribut object)

(class attribute)

(function attribute)

(instance attribute)

(module attribute), [1]

__dir__() (méthode object)

(méthode unittest.mock.Mock)

__displayhook__ (dans le module sys)

__divmod__() (méthode object)

__doc__ (attribut types.ModuleType)

(class attribute)

(function attribute)

(method attribute)

(module attribute), [1]

__enter__() (méthode contextmanager)

(méthode object)

(méthode winreg.PyHKEY)

__eq__() (dans le module operator)

(instance method)

(méthode email.charset.Charset)

(méthode email.header.Header)

(méthode memoryview)

(méthode object)

__excepthook__ (dans le module sys)

__exit__() (méthode contextmanager)

(méthode object)

(méthode winreg.PyHKEY)

__file__

(module attribute), [1], [2]

__float__() (méthode object)

__floor__() (méthode fractions.Fraction)

(méthode object)

__floordiv__() (dans le module operator)

(méthode object)

__format__

__format__() (méthode datetime.date)

(méthode datetime.datetime)

(méthode datetime.time)

(méthode object)

__fspath__() (méthode os.PathLike)

__func__ (method attribute)

__future__

future statement

__future__ (module)

__ge__() (dans le module operator)

(instance method)

(méthode object)

__get__() (méthode object)

__getattr__() (méthode object)

__getattribute__() (méthode object)

__getitem__() (dans le module operator)

(mapping object method)

(méthode email.headerregistry.HeaderRegistry)

(méthode email.message.EmailMessage)

(méthode email.message.Message)

(méthode mailbox.Mailbox)

(méthode object)

(méthode re.match)

__getnewargs__() (méthode object)

__getnewargs_ex__() (méthode object)

__getstate__() (copy protocol)

(méthode object)

__globals__ (function attribute)

__gt__() (dans le module operator)

(instance method)

(méthode object)

__hash__() (méthode object)

__iadd__() (dans le module operator)

(méthode object)

__iand__() (dans le module operator)

(méthode object)

__iconcat__() (dans le module operator)

__ifloordiv__() (dans le module operator)

(méthode object)

__ilshift__() (dans le module operator)

(méthode object)

__imatmul__() (dans le module operator)

(méthode object)

__imod__() (dans le module operator)

(méthode object)

__import__

fonction de base

__import__() (dans le module importlib)

(fonction de base)

__imul__() (dans le module operator)

(méthode object)

__index__() (dans le module operator)

(méthode object)

__init__() (méthode difflib.HtmlDiff)

(méthode logging.Handler)

(méthode logging.logging.Formatter)

(méthode object)

__init_subclass__() (méthode de la classe object)

__instancecheck__() (méthode class)

__int__() (méthode object)

__interactivehook__ (dans le module sys)

__inv__() (dans le module operator)

__invert__() (dans le module operator)

(méthode object)

__ior__() (dans le module operator)

(méthode object)

__ipow__() (dans le module operator)

(méthode object)

__irshift__() (dans le module operator)

(méthode object)

__isub__() (dans le module operator)

(méthode object)

__iter__() (méthode container)

(méthode iterator)

(méthode mailbox.Mailbox)

(méthode object)

(méthode unittest.TestSuite)

__itruediv__() (dans le module operator)

(méthode object)

__ixor__() (dans le module operator)

(méthode object)

__kwdefaults__ (function attribute)

__le__() (dans le module operator)

(instance method)

(méthode object)

__len__() (mapping object method)

(méthode email.message.EmailMessage)

(méthode email.message.Message)

(méthode mailbox.Mailbox)

(méthode object)

__length_hint__() (méthode object)

__loader__

(attribut types.ModuleType)

(module attribute)

__lshift__() (dans le module operator)

(méthode object)

__lt__() (dans le module operator)

(instance method)

(méthode object)

__main__

module, [1], [2], [3], [4], [5], [6], [7]

__main__ (module)

__matmul__() (dans le module operator)

(méthode object)

__missing__()

(méthode collections.defaultdict)

(méthode object)

__mod__() (dans le module operator)

(méthode object)

__module__ (class attribute)

(function attribute)

(method attribute)

__mro__ (attribut class)

__mul__() (dans le module operator)

(méthode object)

__name__

(attribut definition)

(attribut types.ModuleType)

(class attribute)

(function attribute)

(method attribute)

(module attribute), [1], [2]

__ne__() (dans le module operator)

(instance method)

(méthode email.charset.Charset)

(méthode email.header.Header)

(méthode object)

__neg__() (dans le module operator)

(méthode object)

__new__() (méthode object)

__next__() (méthode csv.csvreader)

(méthode generator)

(méthode iterator)

__not__() (dans le module operator)

__or__() (dans le module operator)

(méthode object)

__package__

(attribut types.ModuleType)

(module attribute)

__path__

__pos__() (dans le module operator)

(méthode object)

__pow__() (dans le module operator)

(méthode object)

__prepare__ (metaclass method)

__qualname__ (attribut definition)

__radd__() (méthode object)

__rand__() (méthode object)

__rdivmod__() (méthode object)

__reduce__() (méthode object)

__reduce_ex__() (méthode object)

__repr__() (méthode multiprocessing.managers.BaseProxy)

(méthode netrc.netrc)

(méthode object)

__reversed__() (méthode object)

__rfloordiv__() (méthode object)

__rlshift__() (méthode object)

__rmatmul__() (méthode object)

__rmod__() (méthode object)

__rmul__() (méthode object)

__ror__() (méthode object)

__round__() (méthode fractions.Fraction)

(méthode object)

__rpow__() (méthode object)

__rrshift__() (méthode object)

__rshift__() (dans le module operator)

(méthode object)

__rsub__() (méthode object)

__rtruediv__() (méthode object)

__rxor__() (méthode object)

__self__ (method attribute)

__set__() (méthode object)

__set_name__() (méthode object)

__setattr__() (méthode object)

__setitem__() (dans le module operator)

(méthode email.message.EmailMessage)

(méthode email.message.Message)

(méthode mailbox.Mailbox)

(méthode mailbox.Maildir)

(méthode object)

__setstate__() (copy protocol)

(méthode object)

__slots__

__spec__

__stderr__ (dans le module sys)

__stdin__ (dans le module sys)

__stdout__ (dans le module sys)

__str__() (méthode datetime.date)

(méthode datetime.datetime)

(méthode datetime.time)

(méthode email.charset.Charset)

(méthode email.header.Header)

(méthode email.headerregistry.Address)

(méthode email.headerregistry.Group)

(méthode email.message.EmailMessage)

(méthode email.message.Message)

(méthode multiprocessing.managers.BaseProxy)

(méthode object)

__sub__() (dans le module operator)

(méthode object)

__subclasscheck__() (méthode class)

__subclasses__() (méthode class)

__subclasshook__() (méthode abc.ABCMeta)

__suppress_context__ (attribut traceback.TracebackException)

__traceback__ (exception attribute)

__truediv__() (dans le module operator)

(méthode object)

__trunc__() (méthode object)

__xor__() (dans le module operator)

(méthode object)

_anonymous_ (attribut ctypes.Structure)

_asdict() (méthode collections.somenamedtuple)

_b_base_ (attribut ctypes._CData)

_b_needsfree_ (attribut ctypes._CData)

_callmethod() (méthode multiprocessing.managers.BaseProxy)

_CData (classe dans ctypes)

_clear_type_cache() (dans le module sys)

_current_frames() (dans le module sys)

_debugmallocstats() (dans le module sys)

_dummy_thread (module)

_enablelegacywindowsfsencoding() (dans le module sys)

_exit() (dans le module os)

_fields (attribut ast.AST)

(attribut collections.somenamedtuple)

_fields_ (attribut ctypes.Structure)

_flush() (méthode wsgiref.handlers.BaseHandler)

_frozen (type C)

_FuncPtr (classe dans ctypes)

_get_child_mock() (méthode unittest.mock.Mock)

_getframe() (dans le module sys)

_getvalue() (méthode multiprocessing.managers.BaseProxy)

_handle (attribut ctypes.PyDLL)

_inittab (type C)

_length_ (attribut ctypes.Array)

_locale

module

_make() (méthode de la classe collections.somenamedtuple)

_makeResult() (méthode unittest.TextTestRunner)

_name (attribut ctypes.PyDLL)

_objects (attribut ctypes._CData)

_pack_ (attribut ctypes.Structure)

_parse() (méthode gettext.NullTranslations)

_Pointer (classe dans ctypes)

_Py_c_diff (fonction C)

_Py_c_neg (fonction C)

_Py_c_pow (fonction C)

_Py_c_prod (fonction C)

_Py_c_quot (fonction C)

_Py_c_sum (fonction C)

_Py_NoneStruct (variable C)

_PyBytes_Resize (fonction C)

_PyImport_FindExtension (fonction C)

_PyImport_Fini (fonction C)

_PyImport_Init (fonction C)

_PyObject_GC_TRACK (fonction C)

_PyObject_GC_UNTRACK (fonction C)

_PyObject_New (fonction C)

_PyObject_NewVar (fonction C)

_PyTuple_Resize (fonction C)

_replace() (méthode collections.somenamedtuple)

_setroot() (méthode xml.etree.ElementTree.ElementTree)

_SimpleCData (classe dans ctypes)

_source (attribut collections.somenamedtuple)

_structure() (dans le module email.iterators)

_thread

module

_thread (module)

_type_ (attribut ctypes._Pointer)

(attribut ctypes.Array)

_write() (méthode wsgiref.handlers.BaseHandler)

_xoptions (dans le module sys)

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Index

Symboles | _ | A | B | C | D | E | F | G | H | I | J | K | L | M | N | O | P | Q | R | S | T | U | V | W | X | Y | Z

Symboles

! (exclamation)

in a command interpreter

in curses module

in formatted string literal

in glob-style wildcards, [1]

in string formatting

in struct format strings

! (pdb command)

!=

opérateur, [1]

" (double quote)

string literal

"""

string literal

# (hash)

comment, [1], [2]

in doctests

in printf-style formatting, [1]

in regular expressions

in string formatting

source encoding declaration

$ (dollar)

environment variables expansion

in regular expressions

in template strings

interpolation in configuration files

% (percent)

datetime format, [1], [2]

environment variables expansion (Windows), [1]

interpolation in configuration files

opérateur, [1]

printf-style formatting, [1]

%=

augmented assignment

& (ampersand)

opérateur, [1]

&=

augmented assignment

' (single quote)

string literal

'''

string literal

() (parentheses)

call

class definition

function definition

generator expression

in assignment target list

in printf-style formatting, [1]

in regular expressions

tuple display

(?

in regular expressions

(?!

in regular expressions

(?#

in regular expressions

(?:

in regular expressions

(?<!

in regular expressions

(?<=

in regular expressions

(?P<

in regular expressions

(?P=

in regular expressions

* (asterisk)

function definition

import statement

in argparse module

in assignment target list

in AST grammar

in expression lists

in function calls, [1]

in glob-style wildcards, [1]

in printf-style formatting, [1]

in regular expressions

opérateur, [1]

**

function definition

in dictionary displays

in function calls, [1]

in glob-style wildcards

opérateur, [1]

**=

augmented assignment

*=

augmented assignment

*?

in regular expressions

+ (plus)

binary operator, [1]

in argparse module

in doctests

in printf-style formatting, [1]

in regular expressions

in string formatting

unary operator, [1]

+=

augmented assignment

+?

in regular expressions

, (comma)

argument list

expression list, [1], [2], [3], [4]

identifier list, [1]

import statement

in dictionary displays

in string formatting

in target list

parameter list

slicing

tuple display

with statement

- (minus)

binary operator, [1]

in doctests

in glob-style wildcards, [1]

in printf-style formatting, [1]

in regular expressions

in string formatting

unary operator, [1]

--annotate

pickletools command line option

--buffer

unittest command line option

--catch

unittest command line option

--clock

timeit command line option

--count

trace command line option

--coverdir=<dir>

trace command line option

--create <tarfile> <source1> ... <sourceN>

tarfile command line option

--details

inspect command line option

--exact

tokenize command line option

--extract <tarfile> [<output_dir>]

tarfile command line option

--failfast

unittest command line option

--file=<file>

trace command line option

--help

command line option

json.tool command line option

timeit command line option

tokenize command line option

trace command line option

zipapp command line option

--ignore-dir=<dir>

trace command line option

--ignore-module=<mod>

trace command line option

--indentlevel=<num>

pickletools command line option

--info

zipapp command line option

--list <tarfile>

tarfile command line option

--listfuncs

trace command line option

--locals

unittest command line option

--main=<mainfn>

zipapp command line option

--memo

pickletools command line option

--missing

trace command line option

--no-report

trace command line option

--number=N

timeit command line option

--output=<file>

pickletools command line option

--output=<output>

zipapp command line option

--pattern pattern

unittest-discover command line option

--preamble=<preamble>

pickletools command line option

--process

timeit command line option

--python=<interpreter>

zipapp command line option

--repeat=N

timeit command line option

--report

trace command line option

--setup=S

timeit command line option

--sort-keys

json.tool command line option

--start-directory directory

unittest-discover command line option

--summary

trace command line option

--test <tarfile>

tarfile command line option

--time

timeit command line option

--timing

trace command line option

--top-level-directory directory

unittest-discover command line option

--trace

trace command line option

--trackcalls

trace command line option

--unit=U

timeit command line option

--user-base

site command line option

--user-site

site command line option

--verbose

tarfile command line option

timeit command line option

unittest-discover command line option

--version

command line option

trace command line option

-=

augmented assignment

->

function annotations, [1]

-?

command line option

-a

pickletools command line option

-B

command line option

-b

command line option

compileall command line option

unittest command line option

-C

trace command line option

-c

timeit command line option

trace command line option

unittest command line option

-c <command>

command line option

-c <tarfile> <source1> ... <sourceN>

tarfile command line option

-c <zipfile> <source1> ... <sourceN>

zipfile command line option

-d

command line option

-d destdir

compileall command line option

-E

command line option

-e

tokenize command line option

-e <tarfile> [<output_dir>]

tarfile command line option

-e <zipfile> <output_dir>

zipfile command line option

-f

compileall command line option

trace command line option

unittest command line option

-g

trace command line option

-h

command line option

json.tool command line option

timeit command line option

tokenize command line option

zipapp command line option

-I

command line option

-i

command line option

-i list

compileall command line option

-J

command line option

-j N

compileall command line option

-l

compileall command line option

pickletools command line option

trace command line option

-l <tarfile>

tarfile command line option

-l <zipfile>

zipfile command line option

-m

pickletools command line option

trace command line option

-m <mainfn>

zipapp command line option

-m <module-name>

command line option

-n N

timeit command line option

-O

command line option

-o

pickletools command line option

-o <output>

zipapp command line option

-OO

command line option

-p

pickletools command line option

timeit command line option

unittest-discover command line option

-p <interpreter>

zipapp command line option

-q

command line option

compileall command line option

-R

command line option

trace command line option

-r

compileall command line option

trace command line option

-r N

timeit command line option

-S

command line option

-s

command line option

trace command line option

unittest-discover command line option

-s S

timeit command line option

-T

trace command line option

-t

timeit command line option

trace command line option

unittest-discover command line option

-t <tarfile>

tarfile command line option

-t <zipfile>

zipfile command line option

-u

command line option

timeit command line option

-V

command line option

-v

command line option

tarfile command line option

timeit command line option

unittest-discover command line option

-W arg

command line option

-X

command line option

-x

command line option

-x regex

compileall command line option

. (dot)

attribute reference

in glob-style wildcards

in numeric literal

in pathnames, [1]

in printf-style formatting, [1]

in regular expressions

in string formatting

in Tkinter

..

in pathnames

...

ellipsis literal, [1], [2]

in doctests

interpreter prompt, [1]

placeholder, [1], [2]

.ini

file

.pdbrc

file

.pypirc file

/ (slash)

in pathnames, [1]

opérateur, [1]

//

opérateur, [1]

//=

augmented assignment

/=

augmented assignment

0b

integer literal

0o

integer literal

0x

integer literal

2to3

: (colon)

annotated variable

compound statement, [1], [2], [3], [4], [5], [6]

function annotations, [1]

in dictionary expressions

in formatted string literal

in SQL statements

in string formatting

lambda expression

path separator (POSIX)

slicing

; (semicolon), [1]

< (less)

in string formatting

in struct format strings

opérateur, [1]

<<

opérateur, [1]

<<=

augmented assignment

<=

opérateur, [1]

<BLANKLINE>

= (equals)

assignment statement

class definition

function definition

in function calls

in string formatting

in struct format strings

==

opérateur, [1]

> (greater)

in string formatting

in struct format strings

opérateur, [1]

>=

opérateur, [1]

>>

opérateur, [1]

>>=

augmented assignment

>>>

interpreter prompt, [1]

? (question mark)

in a command interpreter

in argparse module

in AST grammar

in glob-style wildcards, [1]

in regular expressions

in SQL statements

in struct format strings, [1]

replacement character

??

in regular expressions

@ (at)

class definition

function definition

in struct format strings

opérateur

[] (square brackets)

in assignment target list

in glob-style wildcards, [1]

in regular expressions

in string formatting

list expression

subscription

\ (backslash)

escape sequence, [1]

in pathnames (Windows)

in regular expressions, [1], [2]

\\

escape sequence

in regular expressions

\A

in regular expressions

\a

escape sequence

in regular expressions

\B

in regular expressions

\b

escape sequence

in regular expressions, [1]

\D

in regular expressions

\d

in regular expressions

\f

escape sequence

in regular expressions

\g

in regular expressions

\N

escape sequence, [1]

in regular expressions

\n

escape sequence

in regular expressions

\r

escape sequence

in regular expressions

\S

in regular expressions

\s

in regular expressions

\t

escape sequence

in regular expressions

\U

escape sequence, [1]

in regular expressions

\u

escape sequence, [1]

in regular expressions

\v

escape sequence

in regular expressions

\W

in regular expressions

\w

in regular expressions

\x

escape sequence, [1]

in regular expressions

\Z

in regular expressions

^ (caret)

in curses module

in regular expressions, [1]

in string formatting

marker, [1]

opérateur, [1]

^=

augmented assignment

{} (curly brackets)

dictionary expression

in formatted string literal

in regular expressions

in string formatting

set expression

| (vertical bar)

in regular expressions

opérateur, [1]

|=

augmented assignment

~ (tilde)

home directory expansion

opérateur, [1]

_

_ (underscore)

gettext

in numeric literal, [1]

in string formatting

_, identifiers

__, identifiers

__abs__() (dans le module operator)

(méthode object)

__add__() (dans le module operator)

(méthode object)

__aenter__() (méthode object)

__aexit__() (méthode object)

__aiter__() (méthode object)

__all__

(optional module attribute)

(package variable)

__and__() (dans le module operator)

(méthode object)

__anext__() (méthode agen)

(méthode object)

__annotations__ (class attribute)

(function attribute)

(module attribute)

__await__() (méthode object)

__bases__ (attribut class)

(class attribute)

__bool__() (méthode object)

(object method)

__bytes__() (méthode email.message.EmailMessage)

(méthode email.message.Message)

(méthode object)

__cached__

__call__() (méthode email.headerregistry.HeaderRegistry)

(méthode object)

(méthode weakref.finalize)

(object method)

__callback__ (attribut weakref.ref)

__cause__ (attribut traceback.TracebackException)

(exception attribute)

__ceil__() (méthode fractions.Fraction)

(méthode object)

__class__ (attribut instance)

(attribut unittest.mock.Mock)

(instance attribute)

(method cell)

(module attribute)

__classcell__ (class namespace entry)

__closure__ (function attribute)

__code__ (function attribute)

(function object attribute)

__complex__() (méthode object)

__concat__() (dans le module operator)

__contains__() (dans le module operator)

(méthode email.message.EmailMessage)

(méthode email.message.Message)

(méthode mailbox.Mailbox)

(méthode object)

__context__ (attribut traceback.TracebackException)

(exception attribute)

__copy__() (copy protocol)

__debug__

(variable de base)

__deepcopy__() (copy protocol)

__defaults__ (function attribute)

__del__() (méthode io.IOBase)

(méthode object)

__delattr__() (méthode object)

__delete__() (méthode object)

__delitem__() (dans le module operator)

(méthode email.message.EmailMessage)

(méthode email.message.Message)

(méthode mailbox.Mailbox)

(méthode mailbox.MH)

(méthode object)

__dict__ (attribut object)

(class attribute)

(function attribute)

(instance attribute)

(module attribute), [1]

__dir__() (méthode object)

(méthode unittest.mock.Mock)

__displayhook__ (dans le module sys)

__divmod__() (méthode object)

__doc__ (attribut types.ModuleType)

(class attribute)

(function attribute)

(method attribute)

(module attribute), [1]

__enter__() (méthode contextmanager)

(méthode object)

(méthode winreg.PyHKEY)

__eq__() (dans le module operator)

(instance method)

(méthode email.charset.Charset)

(méthode email.header.Header)

(méthode memoryview)

(méthode object)

__excepthook__ (dans le module sys)

__exit__() (méthode contextmanager)

(méthode object)

(méthode winreg.PyHKEY)

__file__

(module attribute), [1], [2]

__float__() (méthode object)

__floor__() (méthode fractions.Fraction)

(méthode object)

__floordiv__() (dans le module operator)

(méthode object)

__format__

__format__() (méthode datetime.date)

(méthode datetime.datetime)

(méthode datetime.time)

(méthode object)

__fspath__() (méthode os.PathLike)

__func__ (method attribute)

__future__

future statement

__future__ (module)

__ge__() (dans le module operator)

(instance method)

(méthode object)

__get__() (méthode object)

__getattr__() (méthode object)

__getattribute__() (méthode object)

__getitem__() (dans le module operator)

(mapping object method)

(méthode email.headerregistry.HeaderRegistry)

(méthode email.message.EmailMessage)

(méthode email.message.Message)

(méthode mailbox.Mailbox)

(méthode object)

(méthode re.match)

__getnewargs__() (méthode object)

__getnewargs_ex__() (méthode object)

__getstate__() (copy protocol)

(méthode object)

__globals__ (function attribute)

__gt__() (dans le module operator)

(instance method)

(méthode object)

__hash__() (méthode object)

__iadd__() (dans le module operator)

(méthode object)

__iand__() (dans le module operator)

(méthode object)

__iconcat__() (dans le module operator)

__ifloordiv__() (dans le module operator)

(méthode object)

__ilshift__() (dans le module operator)

(méthode object)

__imatmul__() (dans le module operator)

(méthode object)

__imod__() (dans le module operator)

(méthode object)

__import__

fonction de base

__import__() (dans le module importlib)

(fonction de base)

__imul__() (dans le module operator)

(méthode object)

__index__() (dans le module operator)

(méthode object)

__init__() (méthode difflib.HtmlDiff)

(méthode logging.Handler)

(méthode logging.logging.Formatter)

(méthode object)

__init_subclass__() (méthode de la classe object)

__instancecheck__() (méthode class)

__int__() (méthode object)

__interactivehook__ (dans le module sys)

__inv__() (dans le module operator)

__invert__() (dans le module operator)

(méthode object)

__ior__() (dans le module operator)

(méthode object)

__ipow__() (dans le module operator)

(méthode object)

__irshift__() (dans le module operator)

(méthode object)

__isub__() (dans le module operator)

(méthode object)

__iter__() (méthode container)

(méthode iterator)

(méthode mailbox.Mailbox)

(méthode object)

(méthode unittest.TestSuite)

__itruediv__() (dans le module operator)

(méthode object)

__ixor__() (dans le module operator)

(méthode object)

__kwdefaults__ (function attribute)

__le__() (dans le module operator)

(instance method)

(méthode object)

__len__() (mapping object method)

(méthode email.message.EmailMessage)

(méthode email.message.Message)

(méthode mailbox.Mailbox)

(méthode object)

__length_hint__() (méthode object)

__loader__

(attribut types.ModuleType)

(module attribute)

__lshift__() (dans le module operator)

(méthode object)

__lt__() (dans le module operator)

(instance method)

(méthode object)

__main__

module, [1], [2], [3], [4], [5], [6], [7]

__main__ (module)

__matmul__() (dans le module operator)

(méthode object)

__missing__()

(méthode collections.defaultdict)

(méthode object)

__mod__() (dans le module operator)

(méthode object)

__module__ (class attribute)

(function attribute)

(method attribute)

__mro__ (attribut class)

__mul__() (dans le module operator)

(méthode object)

__name__

(attribut definition)

(attribut types.ModuleType)

(class attribute)

(function attribute)

(method attribute)

(module attribute), [1], [2]

__ne__() (dans le module operator)

(instance method)

(méthode email.charset.Charset)

(méthode email.header.Header)

(méthode object)

__neg__() (dans le module operator)

(méthode object)

__new__() (méthode object)

__next__() (méthode csv.csvreader)

(méthode generator)

(méthode iterator)

__not__() (dans le module operator)

__or__() (dans le module operator)

(méthode object)

__package__

(attribut types.ModuleType)

(module attribute)

__path__

__pos__() (dans le module operator)

(méthode object)

__pow__() (dans le module operator)

(méthode object)

__prepare__ (metaclass method)

__qualname__ (attribut definition)

__radd__() (méthode object)

__rand__() (méthode object)

__rdivmod__() (méthode object)

__reduce__() (méthode object)

__reduce_ex__() (méthode object)

__repr__() (méthode multiprocessing.managers.BaseProxy)

(méthode netrc.netrc)

(méthode object)

__reversed__() (méthode object)

__rfloordiv__() (méthode object)

__rlshift__() (méthode object)

__rmatmul__() (méthode object)

__rmod__() (méthode object)

__rmul__() (méthode object)

__ror__() (méthode object)

__round__() (méthode fractions.Fraction)

(méthode object)

__rpow__() (méthode object)

__rrshift__() (méthode object)

__rshift__() (dans le module operator)

(méthode object)

__rsub__() (méthode object)

__rtruediv__() (méthode object)

__rxor__() (méthode object)

__self__ (method attribute)

__set__() (méthode object)

__set_name__() (méthode object)

__setattr__() (méthode object)

__setitem__() (dans le module operator)

(méthode email.message.EmailMessage)

(méthode email.message.Message)

(méthode mailbox.Mailbox)

(méthode mailbox.Maildir)

(méthode object)

__setstate__() (copy protocol)

(méthode object)

__slots__

__spec__

__stderr__ (dans le module sys)

__stdin__ (dans le module sys)

__stdout__ (dans le module sys)

__str__() (méthode datetime.date)

(méthode datetime.datetime)

(méthode datetime.time)

(méthode email.charset.Charset)

(méthode email.header.Header)

(méthode email.headerregistry.Address)

(méthode email.headerregistry.Group)

(méthode email.message.EmailMessage)

(méthode email.message.Message)

(méthode multiprocessing.managers.BaseProxy)

(méthode object)

__sub__() (dans le module operator)

(méthode object)

__subclasscheck__() (méthode class)

__subclasses__() (méthode class)

__subclasshook__() (méthode abc.ABCMeta)

__suppress_context__ (attribut traceback.TracebackException)

__traceback__ (exception attribute)

__truediv__() (dans le module operator)

(méthode object)

__trunc__() (méthode object)

__xor__() (dans le module operator)

(méthode object)

_anonymous_ (attribut ctypes.Structure)

_asdict() (méthode collections.somenamedtuple)

_b_base_ (attribut ctypes._CData)

_b_needsfree_ (attribut ctypes._CData)

_callmethod() (méthode multiprocessing.managers.BaseProxy)

_CData (classe dans ctypes)

_clear_type_cache() (dans le module sys)

_current_frames() (dans le module sys)

_debugmallocstats() (dans le module sys)

_dummy_thread (module)

_enablelegacywindowsfsencoding() (dans le module sys)

_exit() (dans le module os)

_fields (attribut ast.AST)

(attribut collections.somenamedtuple)

_fields_ (attribut ctypes.Structure)

_flush() (méthode wsgiref.handlers.BaseHandler)

_frozen (type C)

_FuncPtr (classe dans ctypes)

_get_child_mock() (méthode unittest.mock.Mock)

_getframe() (dans le module sys)

_getvalue() (méthode multiprocessing.managers.BaseProxy)

_handle (attribut ctypes.PyDLL)

_inittab (type C)

_length_ (attribut ctypes.Array)

_locale

module

_make() (méthode de la classe collections.somenamedtuple)

_makeResult() (méthode unittest.TextTestRunner)

_name (attribut ctypes.PyDLL)

_objects (attribut ctypes._CData)

_pack_ (attribut ctypes.Structure)

_parse() (méthode gettext.NullTranslations)

_Pointer (classe dans ctypes)

_Py_c_diff (fonction C)

_Py_c_neg (fonction C)

_Py_c_pow (fonction C)

_Py_c_prod (fonction C)

_Py_c_quot (fonction C)

_Py_c_sum (fonction C)

_Py_NoneStruct (variable C)

_PyBytes_Resize (fonction C)

_PyImport_FindExtension (fonction C)

_PyImport_Fini (fonction C)

_PyImport_Init (fonction C)

_PyObject_GC_TRACK (fonction C)

_PyObject_GC_UNTRACK (fonction C)

_PyObject_New (fonction C)

_PyObject_NewVar (fonction C)

_PyTuple_Resize (fonction C)

_replace() (méthode collections.somenamedtuple)

_setroot() (méthode xml.etree.ElementTree.ElementTree)

_SimpleCData (classe dans ctypes)

_source (attribut collections.somenamedtuple)

_structure() (dans le module email.iterators)

_thread

module

_thread (module)

_type_ (attribut ctypes._Pointer)

(attribut ctypes.Array)

_write() (méthode wsgiref.handlers.BaseHandler)

_xoptions (dans le module sys)

A

A (dans le module re)

A-LAW, [1]

a-LAW

a2b_base64() (dans le module binascii)

a2b_hex() (dans le module binascii)

a2b_hqx() (dans le module binascii)

a2b_qp() (dans le module binascii)

a2b_uu() (dans le module binascii)

a85decode() (dans le module base64)

a85encode() (dans le module base64)

ABC (classe dans abc)

abc (module)

ABCMeta (classe dans abc)

abiflags (dans le module sys)

abort()

(dans le module os)

(méthode asyncio.DatagramTransport)

(méthode asyncio.WriteTransport)

(méthode ftplib.FTP)

(méthode threading.Barrier)

above() (méthode curses.panel.Panel)

abs

fonction de base, [1]

abs() (dans le module operator)

(fonction de base)

(méthode decimal.Context)

abspath() (dans le module os.path)

AbstractBasicAuthHandler (classe dans urllib.request)

abstractclassmethod() (dans le module abc)

AbstractContextManager (classe dans contextlib)

AbstractDigestAuthHandler (classe dans urllib.request)

AbstractEventLoop (classe dans asyncio)

AbstractEventLoopPolicy (classe dans asyncio)

AbstractFormatter (classe dans formatter)

abstractmethod() (dans le module abc)

abstractproperty() (dans le module abc)

AbstractSet (classe dans typing)

abstractstaticmethod() (dans le module abc)

AbstractWriter (classe dans formatter)

accept() (méthode asyncore.dispatcher)

(méthode multiprocessing.connection.Listener)

(méthode socket.socket)

access() (dans le module os)

accumulate() (dans le module itertools)

aclose() (méthode agen)

acos() (dans le module cmath)

(dans le module math)

acosh() (dans le module cmath)

(dans le module math)

acquire() (méthode _thread.lock)

(méthode asyncio.Condition)

(méthode asyncio.Lock)

(méthode asyncio.Semaphore)

(méthode logging.Handler)

(méthode multiprocessing.Lock)

(méthode multiprocessing.RLock)

(méthode threading.Condition)

(méthode threading.Lock)

(méthode threading.RLock)

(méthode threading.Semaphore)

acquire_lock() (dans le module imp)

action (attribut optparse.Option)

Action (classe dans argparse)

ACTIONS (attribut optparse.Option)

active_children() (dans le module multiprocessing)

active_count() (dans le module threading)

add() (dans le module audioop)

(dans le module operator)

(méthode decimal.Context)

(méthode frozenset)

(méthode mailbox.Mailbox)

(méthode mailbox.Maildir)

(méthode msilib.RadioButtonGroup)

(méthode pstats.Stats)

(méthode tarfile.TarFile)

(méthode tkinter.ttk.Notebook)

add_alias() (dans le module email.charset)

add_alternative() (méthode email.message.EmailMessage)

add_argument() (méthode argparse.ArgumentParser)

add_argument_group() (méthode argparse.ArgumentParser)

add_attachment() (méthode email.message.EmailMessage)

add_cgi_vars() (méthode wsgiref.handlers.BaseHandler)

add_charset() (dans le module email.charset)

add_codec() (dans le module email.charset)

add_cookie_header() (méthode http.cookiejar.CookieJar)

add_data() (dans le module msilib)

add_done_callback() (méthode asyncio.Future)

(méthode concurrent.futures.Future)

add_fallback() (méthode gettext.NullTranslations)

add_file() (méthode msilib.Directory)

add_flag() (méthode mailbox.MaildirMessage)

(méthode mailbox.mboxMessage)

(méthode mailbox.MMDFMessage)

add_flowing_data() (méthode formatter.formatter)

add_folder() (méthode mailbox.Maildir)

(méthode mailbox.MH)

add_get_handler() (méthode email.contentmanager.ContentManager)

add_handler() (méthode urllib.request.OpenerDirector)

add_header() (méthode email.message.EmailMessage)

(méthode email.message.Message)

(méthode urllib.request.Request)

(méthode wsgiref.headers.Headers)

add_history() (dans le module readline)

add_hor_rule() (méthode formatter.formatter)

add_include_dir() (méthode distutils.ccompiler.CCompiler)

add_label() (méthode mailbox.BabylMessage)

add_label_data() (méthode formatter.formatter)

add_library() (méthode distutils.ccompiler.CCompiler)

add_library_dir() (méthode distutils.ccompiler.CCompiler)

add_line_break() (méthode formatter.formatter)

add_link_object() (méthode distutils.ccompiler.CCompiler)

add_literal_data() (méthode formatter.formatter)

add_mutually_exclusive_group() (méthode argparse.ArgumentParser)

add_option() (méthode optparse.OptionParser)

add_parent() (méthode urllib.request.BaseHandler)

add_password() (méthode urllib.request.HTTPPasswordMgr)

(méthode urllib.request.HTTPPasswordMgrWithPriorAuth)

add_reader() (méthode asyncio.AbstractEventLoop)

add_related() (méthode email.message.EmailMessage)

add_runtime_library_dir() (méthode distutils.ccompiler.CCompiler)

add_section() (méthode configparser.ConfigParser)

(méthode configparser.RawConfigParser)

add_sequence() (méthode mailbox.MHMessage)

add_set_handler() (méthode email.contentmanager.ContentManager)

add_signal_handler() (méthode asyncio.AbstractEventLoop)

add_stream() (dans le module msilib)

add_subparsers() (méthode argparse.ArgumentParser)

add_tables() (dans le module msilib)

add_type() (dans le module mimetypes)

add_unredirected_header() (méthode urllib.request.Request)

add_writer() (méthode asyncio.AbstractEventLoop)

addch() (méthode curses.window)

addCleanup() (méthode unittest.TestCase)

addcomponent() (méthode turtle.Shape)

addError() (méthode unittest.TestResult)

addExpectedFailure() (méthode unittest.TestResult)

addFailure() (méthode unittest.TestResult)

addfile() (méthode tarfile.TarFile)

addFilter() (méthode logging.Handler)

(méthode logging.Logger)

addHandler() (méthode logging.Logger)

addition

addLevelName() (dans le module logging)

addnstr() (méthode curses.window)

AddPackagePath() (dans le module modulefinder)

addr (attribut smtpd.SMTPChannel)

addr_spec (attribut email.headerregistry.Address)

address (attribut email.headerregistry.SingleAddressHeader)

(attribut multiprocessing.connection.Listener)

(attribut multiprocessing.managers.BaseManager)

Address (classe dans email.headerregistry)

address_exclude() (méthode ipaddress.IPv4Network)

(méthode ipaddress.IPv6Network)

address_family (attribut socketserver.BaseServer)

address_string() (méthode http.server.BaseHTTPRequestHandler)

addresses (attribut email.headerregistry.AddressHeader)

(attribut email.headerregistry.Group)

AddressHeader (classe dans email.headerregistry)

addressof() (dans le module ctypes)

AddressValueError

addshape() (dans le module turtle)

addsitedir() (dans le module site)

addSkip() (méthode unittest.TestResult)

addstr() (méthode curses.window)

addSubTest() (méthode unittest.TestResult)

addSuccess() (méthode unittest.TestResult)

addTest() (méthode unittest.TestSuite)

addTests() (méthode unittest.TestSuite)

addTypeEqualityFunc() (méthode unittest.TestCase)

addUnexpectedSuccess() (méthode unittest.TestResult)

adjusted() (méthode decimal.Decimal)

adler32() (dans le module zlib)

ADPCM, Intel/DVI

adpcm2lin() (dans le module audioop)

AF_ALG (dans le module socket)

AF_CAN (dans le module socket)

AF_INET (dans le module socket)

AF_INET6 (dans le module socket)

AF_LINK (dans le module socket)

AF_PACKET (dans le module socket)

AF_RDS (dans le module socket)

AF_UNIX (dans le module socket)

aifc (module)

aifc() (méthode aifc.aifc)

AIFF, [1]

aiff() (méthode aifc.aifc)

AIFF-C, [1]

alarm() (dans le module signal)

alaw2lin() (dans le module audioop)

ALERT_DESCRIPTION_HANDSHAKE_FAILURE (dans le module ssl)

ALERT_DESCRIPTION_INTERNAL_ERROR (dans le module ssl)

AlertDescription (classe dans ssl)

algorithms_available (dans le module hashlib)

algorithms_guaranteed (dans le module hashlib)

alias (pdb command)

alias de type

alignment() (dans le module ctypes)

alive (attribut weakref.finalize)

all() (fonction de base)

all_errors (dans le module ftplib)

all_features (dans le module xml.sax.handler)

all_frames (attribut tracemalloc.Filter)

all_properties (dans le module xml.sax.handler)

all_suffixes() (dans le module importlib.machinery)

all_tasks() (méthode de la classe asyncio.Task)

allocate_lock() (dans le module _thread)

allow_reuse_address (attribut socketserver.BaseServer)

allowed_domains() (méthode http.cookiejar.DefaultCookiePolicy)

alt() (dans le module curses.ascii)

ALT_DIGITS (dans le module locale)

altsep (dans le module os)

altzone (dans le module time)

ALWAYS_TYPED_ACTIONS (attribut optparse.Option)

AMPER (dans le module token)

AMPEREQUAL (dans le module token)

and

bitwise

opérateur, [1], [2]

and_() (dans le module operator)

annotated

assignment

annotation

(attribut inspect.Parameter)

annotation de fonction

annotation de variable

annotations

function, [1]

announce() (méthode distutils.ccompiler.CCompiler)

anonymous

function

answer_challenge() (dans le module multiprocessing.connection)

anticipate_failure() (dans le module test.support)

Any (dans le module typing)

ANY (dans le module unittest.mock)

any() (fonction de base)

AnyStr (dans le module typing)

API provisoire

api_version (dans le module sys)

apop() (méthode poplib.POP3)

APPDATA

append() (méthode array.array)

(méthode collections.deque)

(méthode email.header.Header)

(méthode imaplib.IMAP4)

(méthode msilib.CAB)

(méthode pipes.Template)

(méthode xml.etree.ElementTree.Element)

(sequence method)

append_history_file() (dans le module readline)

appendChild() (méthode xml.dom.Node)

appendleft() (méthode collections.deque)

application_uri() (dans le module wsgiref.util)

apply (2to3 fixer)

apply() (méthode multiprocessing.pool.Pool)

apply_async() (méthode multiprocessing.pool.Pool)

apply_defaults() (méthode inspect.BoundArguments)

architecture() (dans le module platform)

archive (attribut zipimport.zipimporter)

aRepr (dans le module reprlib)

argparse (module)

args (attribut BaseException)

(attribut functools.partial)

(attribut inspect.BoundArguments)

(attribut subprocess.CompletedProcess)

(attribut subprocess.Popen)

(pdb command)

argtypes (attribut ctypes._FuncPtr)

argument

call semantics

difference from parameter

function

function definition

argument nommé

argument positionnel

ArgumentDefaultsHelpFormatter (classe dans argparse)

ArgumentError

ArgumentParser (classe dans argparse)

arguments (attribut inspect.BoundArguments)

argv (dans le module sys)

(in module sys)

arithmetic

conversion

operation, binary

operation, unary

ArithmeticError

array

module, [1]

array (classe dans array)

Array (classe dans ctypes)

array (module)

Array() (dans le module multiprocessing)

(dans le module multiprocessing.sharedctypes)

(méthode multiprocessing.managers.SyncManager)

arrays

arraysize (attribut sqlite3.Cursor)

arrêt de l'interpréteur

article() (méthode nntplib.NNTP)

as

except clause

import statement

mot-clé, [1], [2]

with statement

as_bytes() (méthode email.message.EmailMessage)

(méthode email.message.Message)

as_completed() (dans le module asyncio)

(dans le module concurrent.futures)

as_integer_ratio() (méthode decimal.Decimal)

(méthode float)

AS_IS (dans le module formatter)

as_posix() (méthode pathlib.PurePath)

as_string() (méthode email.message.EmailMessage)

(méthode email.message.Message)

as_tuple() (méthode decimal.Decimal)

as_uri() (méthode pathlib.PurePath)

ASCII, [1]

ascii

(dans le module re)

fonction de base

ascii() (dans le module curses.ascii)

(fonction de base)

ascii_letters (dans le module string)

ascii_lowercase (dans le module string)

ascii_uppercase (dans le module string)

asctime() (dans le module time)

asend() (méthode agen)

asin() (dans le module cmath)

(dans le module math)

asinh() (dans le module cmath)

(dans le module math)

assert

état, [1]

assert_any_call() (méthode unittest.mock.Mock)

assert_called() (méthode unittest.mock.Mock)

assert_called_once() (méthode unittest.mock.Mock)

assert_called_once_with() (méthode unittest.mock.Mock)

assert_called_with() (méthode unittest.mock.Mock)

assert_has_calls() (méthode unittest.mock.Mock)

assert_line_data() (méthode formatter.formatter)

assert_not_called() (méthode unittest.mock.Mock)

assertAlmostEqual() (méthode unittest.TestCase)

assertCountEqual() (méthode unittest.TestCase)

assertDictEqual() (méthode unittest.TestCase)

assertEqual() (méthode unittest.TestCase)

assertFalse() (méthode unittest.TestCase)

assertGreater() (méthode unittest.TestCase)

assertGreaterEqual() (méthode unittest.TestCase)

assertIn() (méthode unittest.TestCase)

AssertionError

exception

assertions

debugging

assertIs() (méthode unittest.TestCase)

assertIsInstance() (méthode unittest.TestCase)

assertIsNone() (méthode unittest.TestCase)

assertIsNot() (méthode unittest.TestCase)

assertIsNotNone() (méthode unittest.TestCase)

assertLess() (méthode unittest.TestCase)

assertLessEqual() (méthode unittest.TestCase)

assertListEqual() (méthode unittest.TestCase)

assertLogs() (méthode unittest.TestCase)

assertMultiLineEqual() (méthode unittest.TestCase)

assertNotAlmostEqual() (méthode unittest.TestCase)

assertNotEqual() (méthode unittest.TestCase)

assertNotIn() (méthode unittest.TestCase)

assertNotIsInstance() (méthode unittest.TestCase)

assertNotRegex() (méthode unittest.TestCase)

assertRaises() (méthode unittest.TestCase)

assertRaisesRegex() (méthode unittest.TestCase)

assertRegex() (méthode unittest.TestCase)

asserts (2to3 fixer)

assertSequenceEqual() (méthode unittest.TestCase)

assertSetEqual() (méthode unittest.TestCase)

assertTrue() (méthode unittest.TestCase)

assertTupleEqual() (méthode unittest.TestCase)

assertWarns() (méthode unittest.TestCase)

assertWarnsRegex() (méthode unittest.TestCase)

assignment

annotated

attribute, [1]

augmented

class attribute

class instance attribute

slice

slicing

statement, [1]

subscript

subscription

target list

AST (classe dans ast)

ast (module)

astimezone() (méthode datetime.datetime)

async

mot-clé

ASYNC (dans le module token)

async def

état

async for

état

in comprehensions, [1]

async with

état

async() (dans le module asyncio)

async_chat (classe dans asynchat)

async_chat.ac_in_buffer_size (dans le module asynchat)

async_chat.ac_out_buffer_size (dans le module asynchat)

AsyncContextManager (classe dans typing)

AsyncGenerator (classe dans collections.abc)

(classe dans typing)

AsyncGeneratorType (dans le module types)

asynchat (module)

asynchronous generator

asynchronous iterator

function

asynchronous-generator

objet

asyncio (module)

asyncio.subprocess.DEVNULL (dans le module asyncio)

asyncio.subprocess.PIPE (dans le module asyncio)

asyncio.subprocess.Process (classe dans asyncio)

asyncio.subprocess.STDOUT (dans le module asyncio)

AsyncIterable (classe dans collections.abc)

(classe dans typing)

AsyncIterator (classe dans collections.abc)

(classe dans typing)

asyncore (module)

AsyncResult (classe dans multiprocessing.pool)

AT (dans le module token)

at_eof() (méthode asyncio.StreamReader)

atan() (dans le module cmath)

(dans le module math)

atan2() (dans le module math)

atanh() (dans le module cmath)

(dans le module math)

ATEQUAL (dans le module token)

atexit (attribut weakref.finalize)

(module)

athrow() (méthode agen)

atof() (dans le module locale)

atoi() (dans le module locale)

atom

attach() (méthode email.message.Message)

attach_mock() (méthode unittest.mock.Mock)

AttlistDeclHandler() (méthode xml.parsers.expat.xmlparser)

attrgetter() (dans le module operator)

attrib (attribut xml.etree.ElementTree.Element)

attribut

attribute

assignment, [1]

assignment, class

assignment, class instance

class

class instance

deletion

generic special

reference

special

AttributeError

exception

attributes (attribut xml.dom.Node)

AttributesImpl (classe dans xml.sax.xmlreader)

AttributesNSImpl (classe dans xml.sax.xmlreader)

attroff() (méthode curses.window)

attron() (méthode curses.window)

attrset() (méthode curses.window)

Audio Interchange File Format, [1]

AUDIO_FILE_ENCODING_ADPCM_G721 (dans le module sunau)

AUDIO_FILE_ENCODING_ADPCM_G722 (dans le module sunau)

AUDIO_FILE_ENCODING_ADPCM_G723_3 (dans le module sunau)

AUDIO_FILE_ENCODING_ADPCM_G723_5 (dans le module sunau)

AUDIO_FILE_ENCODING_ALAW_8 (dans le module sunau)

AUDIO_FILE_ENCODING_DOUBLE (dans le module sunau)

AUDIO_FILE_ENCODING_FLOAT (dans le module sunau)

AUDIO_FILE_ENCODING_LINEAR_16 (dans le module sunau)

AUDIO_FILE_ENCODING_LINEAR_24 (dans le module sunau)

AUDIO_FILE_ENCODING_LINEAR_32 (dans le module sunau)

AUDIO_FILE_ENCODING_LINEAR_8 (dans le module sunau)

AUDIO_FILE_ENCODING_MULAW_8 (dans le module sunau)

AUDIO_FILE_MAGIC (dans le module sunau)

AUDIODEV

audioop (module)

augmented

assignment

auth() (méthode ftplib.FTP_TLS)

(méthode smtplib.SMTP)

authenticate() (méthode imaplib.IMAP4)

AuthenticationError

authenticators() (méthode netrc.netrc)

authkey (attribut multiprocessing.Process)

auto (classe dans enum)

autorange() (méthode timeit.Timer)

avg() (dans le module audioop)

avgpp() (dans le module audioop)

avoids_symlink_attacks (attribut shutil.rmtree)

await

in comprehensions

mot-clé, [1], [2]

AWAIT (dans le module token)

awaitable

Awaitable (classe dans collections.abc)

(classe dans typing)

B

b"

bytes literal

b'

bytes literal

b16decode() (dans le module base64)

b16encode() (dans le module base64)

b2a_base64() (dans le module binascii)

b2a_hex() (dans le module binascii)

b2a_hqx() (dans le module binascii)

b2a_qp() (dans le module binascii)

b2a_uu() (dans le module binascii)

b32decode() (dans le module base64)

b32encode() (dans le module base64)

b64decode() (dans le module base64)

b64encode() (dans le module base64)

b85decode() (dans le module base64)

b85encode() (dans le module base64)

Babyl (classe dans mailbox)

BabylMessage (classe dans mailbox)

back() (dans le module turtle)

backslash character

backslashreplace_errors() (dans le module codecs)

backward() (dans le module turtle)

BadStatusLine

BadZipFile

BadZipfile

Balloon (classe dans tkinter.tix)

Barrier (classe dans multiprocessing)

(classe dans threading)

Barrier() (méthode multiprocessing.managers.SyncManager)

base64

encoding

module

base64 (module)

base_exec_prefix (dans le module sys)

base_prefix (dans le module sys)

BaseCGIHandler (classe dans wsgiref.handlers)

BaseCookie (classe dans http.cookies)

BaseEventLoop (classe dans asyncio)

BaseException

BaseHandler (classe dans urllib.request)

(classe dans wsgiref.handlers)

BaseHeader (classe dans email.headerregistry)

BaseHTTPRequestHandler (classe dans http.server)

BaseManager (classe dans multiprocessing.managers)

basename() (dans le module os.path)

BaseProxy (classe dans multiprocessing.managers)

BaseRequestHandler (classe dans socketserver)

BaseRotatingHandler (classe dans logging.handlers)

BaseSelector (classe dans selectors)

BaseServer (classe dans socketserver)

basestring (2to3 fixer)

BaseSubprocessTransport (classe dans asyncio)

BaseTransport (classe dans asyncio)

basicConfig() (dans le module logging)

BasicContext (classe dans decimal)

BasicInterpolation (classe dans configparser)

baudrate() (dans le module curses)

bbox() (méthode tkinter.ttk.Treeview)

BDADDR_ANY (dans le module socket)

BDADDR_LOCAL (dans le module socket)

bdb

module

Bdb (classe dans bdb)

bdb (module)

BdbQuit

BDFL

bdist_msi (classe dans distutils.command.bdist_msi)

beep() (dans le module curses)

Beep() (dans le module winsound)

BEFORE_ASYNC_WITH (opcode)

begin_fill() (dans le module turtle)

begin_poly() (dans le module turtle)

below() (méthode curses.panel.Panel)

Benchmarking

benchmarking

betavariate() (dans le module random)

bgcolor() (dans le module turtle)

bgpic() (dans le module turtle)

bias() (dans le module audioop)

bidirectional() (dans le module unicodedata)

BigEndianStructure (classe dans ctypes)

bin() (fonction de base)

binary

arithmetic operation

bitwise operation

data, packing

literals

Binary (classe dans msilib)

(classe dans xmlrpc.client)

binary literal

binary mode

binary semaphores

BINARY_ADD (opcode)

BINARY_AND (opcode)

BINARY_FLOOR_DIVIDE (opcode)

BINARY_LSHIFT (opcode)

BINARY_MATRIX_MULTIPLY (opcode)

BINARY_MODULO (opcode)

BINARY_MULTIPLY (opcode)

BINARY_OR (opcode)

BINARY_POWER (opcode)

BINARY_RSHIFT (opcode)

BINARY_SUBSCR (opcode)

BINARY_SUBTRACT (opcode)

BINARY_TRUE_DIVIDE (opcode)

BINARY_XOR (opcode)

BinaryIO (classe dans typing)

binascii (module)

bind (widgets)

bind() (méthode asyncore.dispatcher)

(méthode inspect.Signature)

(méthode socket.socket)

bind_partial() (méthode inspect.Signature)

bind_port() (dans le module test.support)

bind_textdomain_codeset() (dans le module gettext)

binding

global name

name, [1], [2], [3], [4], [5], [6]

bindtextdomain() (dans le module gettext)

(dans le module locale)

binhex

module

binhex (module)

binhex() (dans le module binhex)

bisect (module)

bisect() (dans le module bisect)

bisect_left() (dans le module bisect)

bisect_right() (dans le module bisect)

bit_length() (méthode int)

bitmap() (méthode msilib.Dialog)

bitwise

and

operation, binary

operation, unary

operations

or

xor

bk() (dans le module turtle)

bkgd() (méthode curses.window)

bkgdset() (méthode curses.window)

blake2b() (dans le module hashlib)

blake2b, blake2s

blake2b.MAX_DIGEST_SIZE (dans le module hashlib)

blake2b.MAX_KEY_SIZE (dans le module hashlib)

blake2b.PERSON_SIZE (dans le module hashlib)

blake2b.SALT_SIZE (dans le module hashlib)

blake2s() (dans le module hashlib)

blake2s.MAX_DIGEST_SIZE (dans le module hashlib)

blake2s.MAX_KEY_SIZE (dans le module hashlib)

blake2s.PERSON_SIZE (dans le module hashlib)

blake2s.SALT_SIZE (dans le module hashlib)

blank line

block

code

block_size (attribut hmac.HMAC)

blocked_domains() (méthode http.cookiejar.DefaultCookiePolicy)

BlockingIOError, [1]

BNF, [1]

body() (méthode nntplib.NNTP)

body_encode() (méthode email.charset.Charset)

body_encoding (attribut email.charset.Charset)

body_line_iterator() (dans le module email.iterators)

BOM (dans le module codecs)

BOM_BE (dans le module codecs)

BOM_LE (dans le module codecs)

BOM_UTF16 (dans le module codecs)

BOM_UTF16_BE (dans le module codecs)

BOM_UTF16_LE (dans le module codecs)

BOM_UTF32 (dans le module codecs)

BOM_UTF32_BE (dans le module codecs)

BOM_UTF32_LE (dans le module codecs)

BOM_UTF8 (dans le module codecs)

bool (classe de base)

Boolean

objet, [1]

operation

operations, [1]

type

values

BOOLEAN_STATES (attribut configparser.ConfigParser)

bootstrap() (dans le module ensurepip)

border() (méthode curses.window)

bottom() (méthode curses.panel.Panel)

bottom_panel() (dans le module curses.panel)

BoundArguments (classe dans inspect)

BoundaryError

BoundedSemaphore (classe dans asyncio)

(classe dans multiprocessing)

(classe dans threading)

BoundedSemaphore() (méthode multiprocessing.managers.SyncManager)

box() (méthode curses.window)

bpformat() (méthode bdb.Breakpoint)

bpprint() (méthode bdb.Breakpoint)

break

état, [1], [2], [3], [4]

break (pdb command)

break_anywhere() (méthode bdb.Bdb)

break_here() (méthode bdb.Bdb)

break_long_words (attribut textwrap.TextWrapper)

BREAK_LOOP (opcode)

break_on_hyphens (attribut textwrap.TextWrapper)

Breakpoint (classe dans bdb)

breakpoints

broadcast_address (attribut ipaddress.IPv4Network)

(attribut ipaddress.IPv6Network)

broken (attribut threading.Barrier)

BrokenBarrierError

BrokenPipeError

BrokenProcessPool

BROWSER, [1]

BsdDbShelf (classe dans shelve)

buffer (2to3 fixer)

(attribut io.TextIOBase)

(attribut unittest.TestResult)

buffer interface

(see buffer protocol)

buffer object

(see buffer protocol)

buffer protocol

binary sequence types

str (built-in class)

buffer size, I/O

buffer_info() (méthode array.array)

buffer_size (attribut xml.parsers.expat.xmlparser)

buffer_text (attribut xml.parsers.expat.xmlparser)

buffer_used (attribut xml.parsers.expat.xmlparser)

BufferedIOBase (classe dans io)

BufferedRandom (classe dans io)

BufferedReader (classe dans io)

BufferedRWPair (classe dans io)

BufferedWriter (classe dans io)

BufferError

BufferingHandler (classe dans logging.handlers)

BufferTooShort

bufsize() (méthode ossaudiodev.oss_audio_device)

BUILD_CONST_KEY_MAP (opcode)

BUILD_LIST (opcode)

BUILD_LIST_UNPACK (opcode)

BUILD_MAP (opcode)

BUILD_MAP_UNPACK (opcode)

BUILD_MAP_UNPACK_WITH_CALL (opcode)

build_opener() (dans le module urllib.request)

build_py (classe dans distutils.command.build_py)

build_py_2to3 (classe dans distutils.command.build_py)

BUILD_SET (opcode)

BUILD_SET_UNPACK (opcode)

BUILD_SLICE (opcode)

BUILD_STRING (opcode)

BUILD_TUPLE (opcode)

BUILD_TUPLE_UNPACK (opcode)

BUILD_TUPLE_UNPACK_WITH_CALL (opcode)

built-in

method

types

built-in function

call

objet, [1]

built-in method

call

objet, [1]

builtin_module_names (dans le module sys)

BuiltinFunctionType (dans le module types)

BuiltinImporter (classe dans importlib.machinery)

BuiltinMethodType (dans le module types)

builtins

module, [1], [2], [3], [4]

builtins (module)

ButtonBox (classe dans tkinter.tix)

bye() (dans le module turtle)

byref() (dans le module ctypes)

byte

byte-code

file, [1]

byte_compile() (dans le module distutils.util)

bytearray

formatting

interpolation

methods

objet, [1], [2], [3]

bytearray (classe de base)

bytecode

Bytecode (classe dans dis)

Bytecode.codeobj (dans le module dis)

Bytecode.first_line (dans le module dis)

BYTECODE_SUFFIXES (dans le module importlib.machinery)

byteorder (dans le module sys)

bytes

fonction de base, [1]

formatting

interpolation

methods

objet, [1], [2]

str (built-in class)

bytes (attribut uuid.UUID)

(classe de base)

bytes literal

bytes_le (attribut uuid.UUID)

BytesFeedParser (classe dans email.parser)

BytesGenerator (classe dans email.generator)

BytesHeaderParser (classe dans email.parser)

BytesIO (classe dans io)

BytesParser (classe dans email.parser)

ByteString (classe dans collections.abc)

(classe dans typing)

byteswap() (dans le module audioop)

(méthode array.array)

BytesWarning

bz2 (module)

BZ2Compressor (classe dans bz2)

BZ2Decompressor (classe dans bz2)

BZ2File (classe dans bz2)

C

C

language, [1], [2], [3], [4], [5]

structures

C-contiguous, [1]

c_bool (classe dans ctypes)

C_BUILTIN (dans le module imp)

c_byte (classe dans ctypes)

c_char (classe dans ctypes)

c_char_p (classe dans ctypes)

c_contiguous (attribut memoryview)

c_double (classe dans ctypes)

C_EXTENSION (dans le module imp)

c_float (classe dans ctypes)

c_int (classe dans ctypes)

c_int16 (classe dans ctypes)

c_int32 (classe dans ctypes)

c_int64 (classe dans ctypes)

c_int8 (classe dans ctypes)

c_long (classe dans ctypes)

c_longdouble (classe dans ctypes)

c_longlong (classe dans ctypes)

c_short (classe dans ctypes)

c_size_t (classe dans ctypes)

c_ssize_t (classe dans ctypes)

c_ubyte (classe dans ctypes)

c_uint (classe dans ctypes)

c_uint16 (classe dans ctypes)

c_uint32 (classe dans ctypes)

c_uint64 (classe dans ctypes)

c_uint8 (classe dans ctypes)

c_ulong (classe dans ctypes)

c_ulonglong (classe dans ctypes)

c_ushort (classe dans ctypes)

c_void_p (classe dans ctypes)

c_wchar (classe dans ctypes)

c_wchar_p (classe dans ctypes)

CAB (classe dans msilib)

cache_from_source() (dans le module imp)

(dans le module importlib.util)

cached (attribut importlib.machinery.ModuleSpec)

CacheFTPHandler (classe dans urllib.request)

calcsize() (dans le module struct)

Calendar (classe dans calendar)

calendar (module)

calendar() (dans le module calendar)

call

built-in function

built-in method

class instance

class object, [1], [2]

function, [1], [2]

instance, [1]

method

procedure

user-defined function

call() (dans le module subprocess)

(dans le module unittest.mock)

call_args (attribut unittest.mock.Mock)

call_args_list (attribut unittest.mock.Mock)

call_at() (méthode asyncio.AbstractEventLoop)

call_count (attribut unittest.mock.Mock)

call_exception_handler() (méthode asyncio.AbstractEventLoop)

CALL_FUNCTION (opcode)

CALL_FUNCTION_EX (opcode)

CALL_FUNCTION_KW (opcode)

call_later() (méthode asyncio.AbstractEventLoop)

call_list() (méthode unittest.mock.call)

call_soon() (méthode asyncio.AbstractEventLoop)

call_soon_threadsafe() (méthode asyncio.AbstractEventLoop)

call_tracing() (dans le module sys)

callable

objet, [1]

Callable (classe dans collections.abc)

(dans le module typing)

callable() (fonction de base)

CallableProxyType (dans le module weakref)

callback (attribut optparse.Option)

callback() (méthode contextlib.ExitStack)

callback_args (attribut optparse.Option)

callback_kwargs (attribut optparse.Option)

callbacks (dans le module gc)

called (attribut unittest.mock.Mock)

CalledProcessError

calloc()

CAN_BCM (dans le module socket)

can_change_color() (dans le module curses)

can_fetch() (méthode urllib.robotparser.RobotFileParser)

CAN_RAW_FD_FRAMES (dans le module socket)

can_symlink() (dans le module test.support)

can_write_eof() (méthode asyncio.StreamWriter)

(méthode asyncio.WriteTransport)

cancel() (méthode asyncio.Future)

(méthode asyncio.Handle)

(méthode asyncio.Task)

(méthode concurrent.futures.Future)

(méthode sched.scheduler)

(méthode threading.Timer)

cancel_dump_traceback_later() (dans le module faulthandler)

cancel_join_thread() (méthode multiprocessing.Queue)

cancelled() (méthode asyncio.Future)

(méthode concurrent.futures.Future)

CancelledError

CannotSendHeader

CannotSendRequest

canonic() (méthode bdb.Bdb)

canonical() (méthode decimal.Context)

(méthode decimal.Decimal)

capa() (méthode poplib.POP3)

capitalize() (méthode bytearray)

(méthode bytes)

(méthode str)

Capsule

objet

captured_stderr() (dans le module test.support)

captured_stdin() (dans le module test.support)

captured_stdout() (dans le module test.support)

captureWarnings() (dans le module logging)

capwords() (dans le module string)

casefold() (méthode str)

cast() (dans le module ctypes)

(dans le module typing)

(méthode memoryview)

cat() (dans le module nis)

catch_warnings (classe dans warnings)

category() (dans le module unicodedata)

cbreak() (dans le module curses)

CC

ccc() (méthode ftplib.FTP_TLS)

CCompiler (classe dans distutils.ccompiler)

CDLL (classe dans ctypes)

ceil() (dans le module math)

(in module math)

center() (méthode bytearray)

(méthode bytes)

(méthode str)

CERT_NONE (dans le module ssl)

CERT_OPTIONAL (dans le module ssl)

CERT_REQUIRED (dans le module ssl)

cert_store_stats() (méthode ssl.SSLContext)

cert_time_to_seconds() (dans le module ssl)

CertificateError

certificates

CFLAGS, [1], [2]

CFUNCTYPE() (dans le module ctypes)

CGI

debugging

exceptions

protocol

security

tracebacks

cgi (module)

cgi_directories (attribut http.server.CGIHTTPRequestHandler)

CGIHandler (classe dans wsgiref.handlers)

CGIHTTPRequestHandler (classe dans http.server)

cgitb (module)

CGIXMLRPCRequestHandler (classe dans xmlrpc.server)

chain() (dans le module itertools)

chaining

comparisons, [1]

exception

ChainMap (classe dans collections)

(classe dans typing)

chaîne entre triple guillemets

change_cwd() (dans le module test.support)

change_root() (dans le module distutils.util)

CHANNEL_BINDING_TYPES (dans le module ssl)

channel_class (attribut smtpd.SMTPServer)

channels() (méthode ossaudiodev.oss_audio_device)

CHAR_MAX (dans le module locale)

character, [1], [2]

CharacterDataHandler() (méthode xml.parsers.expat.xmlparser)

characters() (méthode xml.sax.handler.ContentHandler)

characters_written (attribut BlockingIOError)

chargeur

Charset (classe dans email.charset)

charset() (méthode gettext.NullTranslations)

chdir() (dans le module os)

check (attribut lzma.LZMADecompressor)

check() (dans le module tabnanny)

(méthode imaplib.IMAP4)

check__all__() (dans le module test.support)

check_call() (dans le module subprocess)

check_environ() (dans le module distutils.util)

check_hostname (attribut ssl.SSLContext)

check_output() (dans le module subprocess)

(méthode doctest.OutputChecker)

check_returncode() (méthode subprocess.CompletedProcess)

check_unused_args() (méthode string.Formatter)

check_warnings() (dans le module test.support)

checkbox() (méthode msilib.Dialog)

checkcache() (dans le module linecache)

checkfuncname() (dans le module bdb)

CheckList (classe dans tkinter.tix)

checksum

Cyclic Redundancy Check

chemin des importations

chercheur

chercheur basé sur les chemins

chercheur dans les méta-chemins

chercheur de chemins

chflags() (dans le module os)

chgat() (méthode curses.window)

childNodes (attribut xml.dom.Node)

ChildProcessError

chmod() (dans le module os)

(méthode pathlib.Path)

choice() (dans le module random)

(dans le module secrets)

choices (attribut optparse.Option)

choices() (dans le module random)

chown() (dans le module os)

(dans le module shutil)

chr

fonction de base

chr() (fonction de base)

chroot() (dans le module os)

Chunk (classe dans chunk)

chunk (module)

cipher

DES

cipher() (méthode ssl.SSLSocket)

circle() (dans le module turtle)

CIRCUMFLEX (dans le module token)

CIRCUMFLEXEQUAL (dans le module token)

Clamped (classe dans decimal)

class

attribute

attribute assignment

body

constructor

definition, [1]

état

instance

name

objet, [1], [2]

Class (classe dans symtable)

Class browser

class instance

attribute

attribute assignment

call

objet, [1], [2]

class object

call, [1], [2]

classe

classe de base abstraite

classmethod

fonction de base

classmethod() (fonction de base)

ClassVar (dans le module typing)

clause

CLD_CONTINUED (dans le module os)

CLD_DUMPED (dans le module os)

CLD_EXITED (dans le module os)

CLD_TRAPPED (dans le module os)

clean() (méthode mailbox.Maildir)

cleandoc() (dans le module inspect)

cleanup functions

clear (pdb command)

Clear Breakpoint

clear() (dans le module turtle), [1]

(méthode asyncio.Event)

(méthode collections.deque)

(méthode curses.window)

(méthode dict)

(méthode email.message.EmailMessage)

(méthode frame)

(méthode frozenset)

(méthode http.cookiejar.CookieJar)

(méthode mailbox.Mailbox)

(méthode threading.Event)

(méthode xml.etree.ElementTree.Element)

(sequence method)

clear_all_breaks() (méthode bdb.Bdb)

clear_all_file_breaks() (méthode bdb.Bdb)

clear_bpbynumber() (méthode bdb.Bdb)

clear_break() (méthode bdb.Bdb)

clear_cache() (dans le module filecmp)

clear_content() (méthode email.message.EmailMessage)

clear_flags() (méthode decimal.Context)

clear_frames() (dans le module traceback)

clear_history() (dans le module readline)

clear_session_cookies() (méthode http.cookiejar.CookieJar)

clear_traces() (dans le module tracemalloc)

clear_traps() (méthode decimal.Context)

clearcache() (dans le module linecache)

ClearData() (méthode msilib.Record)

clearok() (méthode curses.window)

clearscreen() (dans le module turtle)

clearstamp() (dans le module turtle)

clearstamps() (dans le module turtle)

Client() (dans le module multiprocessing.connection)

client_address (attribut http.server.BaseHTTPRequestHandler)

clock() (dans le module time)

clock_getres() (dans le module time)

clock_gettime() (dans le module time)

CLOCK_HIGHRES (dans le module time)

CLOCK_MONOTONIC (dans le module time)

CLOCK_MONOTONIC_RAW (dans le module time)

CLOCK_PROCESS_CPUTIME_ID (dans le module time)

CLOCK_REALTIME (dans le module time)

clock_settime() (dans le module time)

CLOCK_THREAD_CPUTIME_ID (dans le module time)

clone() (dans le module turtle)

(méthode email.generator.BytesGenerator)

(méthode email.generator.Generator)

(méthode email.policy.Policy)

(méthode pipes.Template)

cloneNode() (méthode xml.dom.Node)

close() (dans le module fileinput)

(dans le module os)

(in module os)

(méthode aifc.aifc), [1]

(méthode asyncio.AbstractEventLoop)

(méthode asyncio.BaseSubprocessTransport)

(méthode asyncio.BaseTransport)

(méthode asyncio.Server)

(méthode asyncio.StreamWriter)

(méthode asyncore.dispatcher)

(méthode chunk.Chunk)

(méthode contextlib.ExitStack)

(méthode coroutine)

(méthode dbm.dumb.dumbdbm)

(méthode dbm.gnu.gdbm)

(méthode dbm.ndbm.ndbm)

(méthode distutils.text_file.TextFile)

(méthode email.parser.BytesFeedParser)

(méthode ftplib.FTP)

(méthode generator)

(méthode html.parser.HTMLParser)

(méthode http.client.HTTPConnection)

(méthode imaplib.IMAP4)

(méthode io.IOBase)

(méthode logging.FileHandler)

(méthode logging.Handler)

(méthode logging.handlers.MemoryHandler)

(méthode logging.handlers.NTEventLogHandler)

(méthode logging.handlers.SocketHandler)

(méthode logging.handlers.SysLogHandler)

(méthode mailbox.Mailbox)

(méthode mailbox.Maildir)

(méthode mailbox.MH)

(méthode mmap.mmap)

Close() (méthode msilib.View)

close() (méthode multiprocessing.connection.Connection)

(méthode multiprocessing.connection.Listener)

(méthode multiprocessing.pool.Pool)

(méthode multiprocessing.Queue)

(méthode os.scandir)

(méthode ossaudiodev.oss_audio_device)

(méthode ossaudiodev.oss_mixer_device)

(méthode select.devpoll)

(méthode select.epoll)

(méthode select.kqueue)

(méthode selectors.BaseSelector)

(méthode shelve.Shelf)

(méthode socket.socket)

(méthode sqlite3.Connection)

(méthode sqlite3.Cursor)

(méthode sunau.AU_read)

(méthode sunau.AU_write)

(méthode tarfile.TarFile)

(méthode telnetlib.Telnet)

(méthode urllib.request.BaseHandler)

(méthode wave.Wave_read)

(méthode wave.Wave_write)

Close() (méthode winreg.PyHKEY)

close() (méthode xml.etree.ElementTree.TreeBuilder)

(méthode xml.etree.ElementTree.XMLParser)

(méthode xml.etree.ElementTree.XMLPullParser)

(méthode xml.sax.xmlreader.IncrementalParser)

(méthode zipfile.ZipFile)

close_connection (attribut http.server.BaseHTTPRequestHandler)

close_when_done() (méthode asynchat.async_chat)

closed (attribut http.client.HTTPResponse)

(attribut io.IOBase)

(attribut mmap.mmap)

(attribut ossaudiodev.oss_audio_device)

(attribut select.devpoll)

(attribut select.epoll)

(attribut select.kqueue)

CloseKey() (dans le module winreg)

closelog() (dans le module syslog)

closerange() (dans le module os)

closing() (dans le module contextlib)

clrtobot() (méthode curses.window)

clrtoeol() (méthode curses.window)

cmath (module)

cmd

module

cmd (attribut subprocess.CalledProcessError)

(attribut subprocess.TimeoutExpired)

Cmd (classe dans cmd)

cmd (module)

cmdloop() (méthode cmd.Cmd)

cmdqueue (attribut cmd.Cmd)

cmp() (dans le module filecmp)

cmp_op (dans le module dis)

cmp_to_key() (dans le module functools)

cmpfiles() (dans le module filecmp)

CMSG_LEN() (dans le module socket)

CMSG_SPACE() (dans le module socket)

co_argcount (code object attribute)

CO_ASYNC_GENERATOR (dans le module inspect)

co_cellvars (code object attribute)

co_code (code object attribute)

co_consts (code object attribute)

CO_COROUTINE (dans le module inspect)

co_filename (code object attribute)

co_firstlineno (code object attribute)

co_flags (code object attribute)

co_freevars (code object attribute)

CO_FUTURE_DIVISION (variable C)

CO_GENERATOR (dans le module inspect)

CO_ITERABLE_COROUTINE (dans le module inspect)

co_lnotab (code object attribute)

co_name (code object attribute)

co_names (code object attribute)

CO_NESTED (dans le module inspect)

CO_NEWLOCALS (dans le module inspect)

co_nlocals (code object attribute)

CO_NOFREE (dans le module inspect)

CO_OPTIMIZED (dans le module inspect)

co_stacksize (code object attribute)

CO_VARARGS (dans le module inspect)

CO_VARKEYWORDS (dans le module inspect)

co_varnames (code object attribute)

code

block

code (attribut SystemExit)

(attribut urllib.error.HTTPError)

(attribut xml.etree.ElementTree.ParseError)

(attribut xml.parsers.expat.ExpatError)

(module)

code intermédiaire (bytecode)

code object, [1], [2], [3]

code_info() (dans le module dis)

CodecInfo (classe dans codecs)

Codecs

decode

encode

codecs (module)

coded_value (attribut http.cookies.Morsel)

codeop (module)

codepoint2name (dans le module html.entities)

codes (dans le module xml.parsers.expat.errors)

CODESET (dans le module locale)

CodeType (dans le module types)

coding

style

coercition

col_offset (attribut ast.AST)

collapse_addresses() (dans le module ipaddress)

collapse_rfc2231_value() (dans le module email.utils)

collect() (dans le module gc)

collect_incoming_data() (méthode asynchat.async_chat)

Collection (classe dans collections.abc)

(classe dans typing)

collections (module)

collections.abc (module)

colno (attribut json.JSONDecodeError)

(attribut re.error)

COLON (dans le module token)

color() (dans le module turtle)

color_content() (dans le module curses)

color_pair() (dans le module curses)

colormode() (dans le module turtle)

colorsys (module)

COLS, [1]

column() (méthode tkinter.ttk.Treeview)

COLUMNS, [1]

columns (attribut os.terminal_size)

combinations() (dans le module itertools)

combinations_with_replacement() (dans le module itertools)

combine() (méthode de la classe datetime.datetime)

combining() (dans le module unicodedata)

ComboBox (classe dans tkinter.tix)

Combobox (classe dans tkinter.ttk)

comma

trailing

tuple display

COMMA (dans le module token)

command (attribut http.server.BaseHTTPRequestHandler)

Command (classe dans distutils.cmd)

(classe dans distutils.core)

command line

command line option

--help

--version

-?

-b

-B

-c <command>

-d

-E

-h

-i

-I

-J

-m <module-name>

-O

-OO

-q

-R

-s

-S

-u

-V

-v

-W arg

-x

-X

CommandCompiler (classe dans codeop)

commands (pdb command)

comment

(attribut http.cookiejar.Cookie)

(attribut zipfile.ZipFile)

(attribut zipfile.ZipInfo)

COMMENT (dans le module tokenize)

Comment() (dans le module xml.etree.ElementTree)

comment_url (attribut http.cookiejar.Cookie)

commenters (attribut shlex.shlex)

CommentHandler() (méthode xml.parsers.expat.xmlparser)

commit() (méthode msilib.CAB)

Commit() (méthode msilib.Database)

commit() (méthode sqlite3.Connection)

common (attribut filecmp.dircmp)

Common Gateway Interface

common_dirs (attribut filecmp.dircmp)

common_files (attribut filecmp.dircmp)

common_funny (attribut filecmp.dircmp)

common_types (dans le module mimetypes)

commonpath() (dans le module os.path)

commonprefix() (dans le module os.path)

communicate() (méthode asyncio.asyncio.subprocess.Process)

(méthode subprocess.Popen)

compare() (méthode decimal.Context)

(méthode decimal.Decimal)

(méthode difflib.Differ)

compare_digest() (dans le module hmac)

(dans le module secrets)

compare_networks() (méthode ipaddress.IPv4Network)

(méthode ipaddress.IPv6Network)

COMPARE_OP (opcode)

compare_signal() (méthode decimal.Context)

(méthode decimal.Decimal)

compare_to() (méthode tracemalloc.Snapshot)

compare_total() (méthode decimal.Context)

(méthode decimal.Decimal)

compare_total_mag() (méthode decimal.Context)

(méthode decimal.Decimal)

comparing

objects

comparison

operator

COMPARISON_FLAGS (dans le module doctest)

comparisons

chaining, [1]

Compat32 (classe dans email.policy)

compat32 (dans le module email.policy)

compile

fonction de base, [1], [2], [3], [4]

Compile (classe dans codeop)

compile() (dans le module py_compile)

(dans le module re)

(fonction de base)

(méthode distutils.ccompiler.CCompiler)

(méthode parser.ST)

compile_command() (dans le module code)

(dans le module codeop)

compile_dir() (dans le module compileall)

compile_file() (dans le module compileall)

compile_path() (dans le module compileall)

compileall (module)

compileall command line option

-b

-d destdir

-f

-i list

-j N

-l

-q

-r

-x regex

directory ...

file ...

compilest() (dans le module parser)

complete() (méthode rlcompleter.Completer)

complete_statement() (dans le module sqlite3)

completedefault() (méthode cmd.Cmd)

CompletedProcess (classe dans subprocess)

complex

fonction de base, [1]

number

objet

Complex (classe dans numbers)

complex (classe de base)

complex literal

complex number

literals

objet, [1]

compound

statement

comprehensions

list

compress() (dans le module bz2)

(dans le module gzip)

(dans le module itertools)

(dans le module lzma)

(dans le module zlib)

(méthode bz2.BZ2Compressor)

(méthode lzma.LZMACompressor)

(méthode zlib.Compress)

compress_size (attribut zipfile.ZipInfo)

compress_type (attribut zipfile.ZipInfo)

compressed (attribut ipaddress.IPv4Address)

(attribut ipaddress.IPv4Network)

(attribut ipaddress.IPv6Address)

(attribut ipaddress.IPv6Network)

compression() (méthode ssl.SSLSocket)

CompressionError

compressobj() (dans le module zlib)

COMSPEC, [1]

concat() (dans le module operator)

concatenation

operation

concurrent.futures (module)

Condition (classe dans asyncio)

(classe dans multiprocessing)

(classe dans threading)

condition (pdb command)

condition() (méthode msilib.Control)

Condition() (méthode multiprocessing.managers.SyncManager)

Conditional

expression

conditional

expression

ConfigParser (classe dans configparser)

configparser (module)

configuration

file

file, debugger

file, path

configuration information

configure() (méthode tkinter.ttk.Style)

configure_mock() (méthode unittest.mock.Mock)

confstr() (dans le module os)

confstr_names (dans le module os)

conjugate() (complex number method)

(méthode decimal.Decimal)

(méthode numbers.Complex)

conn (attribut smtpd.SMTPChannel)

connect() (dans le module sqlite3)

(méthode asyncore.dispatcher)

(méthode ftplib.FTP)

(méthode http.client.HTTPConnection)

(méthode multiprocessing.managers.BaseManager)

(méthode smtplib.SMTP)

(méthode socket.socket)

connect_accepted_socket() (méthode asyncio.BaseEventLoop)

connect_ex() (méthode socket.socket)

connect_read_pipe() (méthode asyncio.AbstractEventLoop)

connect_write_pipe() (méthode asyncio.AbstractEventLoop)

connection (attribut sqlite3.Cursor)

Connection (classe dans multiprocessing.connection)

(classe dans sqlite3)

connection_lost() (méthode asyncio.BaseProtocol)

connection_made() (méthode asyncio.BaseProtocol)

ConnectionAbortedError

ConnectionError

ConnectionRefusedError

ConnectionResetError

ConnectRegistry() (dans le module winreg)

const (attribut optparse.Option)

constant

constructor

class

constructor() (dans le module copyreg)

consumed (attribut asyncio.LimitOverrunError)

container, [1]

iteration over

Container (classe dans collections.abc)

(classe dans typing)

contains() (dans le module operator)

content type

MIME

content_manager (attribut email.policy.EmailPolicy)

content_type (attribut email.headerregistry.ContentTypeHeader)

ContentDispositionHeader (classe dans email.headerregistry)

ContentHandler (classe dans xml.sax.handler)

ContentManager (classe dans email.contentmanager)

contents (attribut ctypes._Pointer)

ContentTooShortError

ContentTransferEncoding (classe dans email.headerregistry)

ContentTypeHeader (classe dans email.headerregistry)

context (attribut ssl.SSLSocket)

Context (classe dans decimal)

context management protocol

context manager, [1]

context_diff() (dans le module difflib)

ContextDecorator (classe dans contextlib)

contextlib (module)

ContextManager (classe dans typing)

contextmanager() (dans le module contextlib)

contigu

contiguous

(attribut memoryview)

continue

état, [1], [2], [3], [4]

continue (pdb command)

CONTINUE_LOOP (opcode)

Control (classe dans msilib)

(classe dans tkinter.tix)

control() (méthode msilib.Dialog)

(méthode select.kqueue)

controlnames (dans le module curses.ascii)

controls() (méthode ossaudiodev.oss_mixer_device)

conversion

arithmetic

string, [1]

ConversionError

conversions

numeric

convert_arg_line_to_args() (méthode argparse.ArgumentParser)

convert_field() (méthode string.Formatter)

convert_path() (dans le module distutils.util)

Cookie (classe dans http.cookiejar)

CookieError

cookiejar (attribut urllib.request.HTTPCookieProcessor)

CookieJar (classe dans http.cookiejar)

CookiePolicy (classe dans http.cookiejar)

Coordinated Universal Time

Copy

copy

module

protocol

copy (module)

copy() (dans le module copy)

(dans le module multiprocessing.sharedctypes)

(dans le module shutil)

(méthode collections.deque)

(méthode decimal.Context)

(méthode dict)

(méthode frozenset)

(méthode hashlib.hash)

(méthode hmac.HMAC)

(méthode http.cookies.Morsel)

(méthode imaplib.IMAP4)

(méthode pipes.Template)

(méthode types.MappingProxyType)

(méthode zlib.Compress)

(méthode zlib.Decompress)

(sequence method)

copy2() (dans le module shutil)

copy_abs() (méthode decimal.Context)

(méthode decimal.Decimal)

copy_decimal() (méthode decimal.Context)

copy_file() (dans le module distutils.file_util)

copy_location() (dans le module ast)

copy_negate() (méthode decimal.Context)

(méthode decimal.Decimal)

copy_sign() (méthode decimal.Context)

(méthode decimal.Decimal)

copy_tree() (dans le module distutils.dir_util)

copyfile() (dans le module shutil)

copyfileobj() (dans le module shutil)

copying files

copymode() (dans le module shutil)

copyreg (module)

copyright (dans le module sys)

(in module sys)

(variable de base)

copysign() (dans le module math)

copystat() (dans le module shutil)

copytree() (dans le module shutil)

coroutine, [1], [2]

function

Coroutine (classe dans collections.abc)

(classe dans typing)

coroutine() (dans le module asyncio)

(dans le module types)

CoroutineType (dans le module types)

cos() (dans le module cmath)

(dans le module math)

cosh() (dans le module cmath)

(dans le module math)

count (attribut tracemalloc.Statistic)

(attribut tracemalloc.StatisticDiff)

count() (dans le module itertools)

(méthode array.array)

(méthode bytearray)

(méthode bytes)

(méthode collections.deque)

(méthode str)

(sequence method)

count_diff (attribut tracemalloc.StatisticDiff)

Counter (classe dans collections)

(classe dans typing)

countOf() (dans le module operator)

countTestCases() (méthode unittest.TestCase)

(méthode unittest.TestSuite)

CoverageResults (classe dans trace)

CPP

CPPFLAGS

cProfile (module)

CPU time

cpu_count() (dans le module multiprocessing)

(dans le module os)

CPython

crawl_delay() (méthode urllib.robotparser.RobotFileParser)

CRC (attribut zipfile.ZipInfo)

crc32() (dans le module binascii)

(dans le module zlib)

crc_hqx() (dans le module binascii)

create() (dans le module venv)

(méthode imaplib.IMAP4)

(méthode venv.EnvBuilder)

create_aggregate() (méthode sqlite3.Connection)

create_archive() (dans le module zipapp)

create_autospec() (dans le module unittest.mock)

create_collation() (méthode sqlite3.Connection)

create_configuration() (méthode venv.EnvBuilder)

create_connection() (dans le module socket)

(méthode asyncio.AbstractEventLoop)

create_datagram_endpoint() (méthode asyncio.AbstractEventLoop)

create_decimal() (méthode decimal.Context)

create_decimal_from_float() (méthode decimal.Context)

create_default_context() (dans le module ssl)

create_function() (méthode sqlite3.Connection)

create_future() (méthode asyncio.AbstractEventLoop)

create_module (fonction C)

create_module() (méthode importlib.abc.Loader)

(méthode importlib.machinery.ExtensionFileLoader)

CREATE_NEW_CONSOLE (dans le module subprocess)

CREATE_NEW_PROCESS_GROUP (dans le module subprocess)

create_server() (méthode asyncio.AbstractEventLoop)

create_shortcut() (fonction de base)

create_socket() (méthode asyncore.dispatcher)

create_static_lib() (méthode distutils.ccompiler.CCompiler)

create_stats() (méthode profile.Profile)

create_string_buffer() (dans le module ctypes)

create_subprocess_exec() (dans le module asyncio)

create_subprocess_shell() (dans le module asyncio)

create_system (attribut zipfile.ZipInfo)

create_task() (méthode asyncio.AbstractEventLoop)

create_tree() (dans le module distutils.dir_util)

create_unicode_buffer() (dans le module ctypes)

create_unix_connection() (méthode asyncio.AbstractEventLoop)

create_unix_server() (méthode asyncio.AbstractEventLoop)

create_version (attribut zipfile.ZipInfo)

createAttribute() (méthode xml.dom.Document)

createAttributeNS() (méthode xml.dom.Document)

createComment() (méthode xml.dom.Document)

createDocument() (méthode xml.dom.DOMImplementation)

createDocumentType() (méthode xml.dom.DOMImplementation)

createElement() (méthode xml.dom.Document)

createElementNS() (méthode xml.dom.Document)

createfilehandler() (méthode tkinter.Widget.tk)

CreateKey() (dans le module winreg)

CreateKeyEx() (dans le module winreg)

createLock() (méthode logging.Handler)

(méthode logging.NullHandler)

createProcessingInstruction() (méthode xml.dom.Document)

CreateRecord() (dans le module msilib)

createSocket() (méthode logging.handlers.SocketHandler)

createTextNode() (méthode xml.dom.Document)

credits (variable de base)

critical() (dans le module logging)

(méthode logging.Logger)

CRNCYSTR (dans le module locale)

cross() (dans le module audioop)

crypt

module

crypt (module)

crypt() (dans le module crypt)

crypt(3), [1], [2]

cryptography

csv

(module)

cte (attribut email.headerregistry.ContentTransferEncoding)

cte_type (attribut email.policy.Policy)

ctermid() (dans le module os)

ctime() (dans le module time)

(méthode datetime.date)

(méthode datetime.datetime)

ctrl() (dans le module curses.ascii)

CTRL_BREAK_EVENT (dans le module signal)

CTRL_C_EVENT (dans le module signal)

ctypes (module)

curdir (dans le module os)

currency() (dans le module locale)

current() (méthode tkinter.ttk.Combobox)

current_process() (dans le module multiprocessing)

current_task() (méthode de la classe asyncio.Task)

current_thread() (dans le module threading)

CurrentByteIndex (attribut xml.parsers.expat.xmlparser)

CurrentColumnNumber (attribut xml.parsers.expat.xmlparser)

currentframe() (dans le module inspect)

CurrentLineNumber (attribut xml.parsers.expat.xmlparser)

curs_set() (dans le module curses)

curses (module)

curses.ascii (module)

curses.panel (module)

curses.textpad (module)

Cursor (classe dans sqlite3)

cursor() (méthode sqlite3.Connection)

cursyncup() (méthode curses.window)

customize_compiler() (dans le module distutils.sysconfig)

Cut

cwd() (méthode de la classe pathlib.Path)

(méthode ftplib.FTP)

cycle() (dans le module itertools)

Cyclic Redundancy Check

D

D_FMT (dans le module locale)

D_T_FMT (dans le module locale)

daemon (attribut multiprocessing.Process)

(attribut threading.Thread)

dangling

else

data

packing binary

tabular

type

type, immutable

data (attribut collections.UserDict)

(attribut collections.UserList)

(attribut select.kevent)

(attribut selectors.SelectorKey)

(attribut urllib.request.Request)

(attribut xml.dom.Comment)

(attribut xml.dom.ProcessingInstruction)

(attribut xml.dom.Text)

(attribut xmlrpc.client.Binary)

Data (classe dans plistlib)

data() (méthode xml.etree.ElementTree.TreeBuilder)

data_open() (méthode urllib.request.DataHandler)

data_received() (méthode asyncio.Protocol)

database

Unicode

DatabaseError

databases

datagram_received() (méthode asyncio.DatagramProtocol)

DatagramHandler (classe dans logging.handlers)

DatagramProtocol (classe dans asyncio)

DatagramRequestHandler (classe dans socketserver)

DataHandler (classe dans urllib.request)

date (classe dans datetime)

date() (méthode datetime.datetime)

(méthode nntplib.NNTP)

date_time (attribut zipfile.ZipInfo)

date_time_string() (méthode http.server.BaseHTTPRequestHandler)

DateHeader (classe dans email.headerregistry)

datetime (attribut email.headerregistry.DateHeader)

(classe dans datetime)

DateTime (classe dans xmlrpc.client)

datetime (module)

datum

day (attribut datetime.date)

(attribut datetime.datetime)

day_abbr (dans le module calendar)

day_name (dans le module calendar)

daylight (dans le module time)

Daylight Saving Time

DbfilenameShelf (classe dans shelve)

dbm (module)

dbm.dumb (module)

dbm.gnu

module, [1]

dbm.gnu (module)

dbm.ndbm

module, [1]

dbm.ndbm (module)

dcgettext() (dans le module locale)

deallocation, object

debug (attribut imaplib.IMAP4)

(attribut shlex.shlex)

(attribut zipfile.ZipFile)

DEBUG (dans le module re)

debug() (dans le module doctest)

(dans le module logging)

(méthode logging.Logger)

(méthode pipes.Template)

(méthode unittest.TestCase)

(méthode unittest.TestSuite)

DEBUG_BYTECODE_SUFFIXES (dans le module importlib.machinery)

DEBUG_COLLECTABLE (dans le module gc)

DEBUG_LEAK (dans le module gc)

debug_print() (méthode distutils.ccompiler.CCompiler)

DEBUG_SAVEALL (dans le module gc)

debug_src() (dans le module doctest)

DEBUG_STATS (dans le module gc)

DEBUG_UNCOLLECTABLE (dans le module gc)

debugger, [1], [2]

configuration file

debugging

assertions

CGI

DebuggingServer (classe dans smtpd)

debuglevel (attribut http.client.HTTPResponse)

DebugRunner (classe dans doctest)

Decimal (classe dans decimal)

decimal (module)

decimal literal

decimal() (dans le module unicodedata)

DecimalException (classe dans decimal)

decode

Codecs

decode (attribut codecs.CodecInfo)

decode() (dans le module base64)

(dans le module codecs)

(dans le module quopri)

(dans le module uu)

(méthode bytearray)

(méthode bytes)

(méthode codecs.Codec)

(méthode codecs.IncrementalDecoder)

(méthode json.JSONDecoder)

(méthode xmlrpc.client.Binary)

(méthode xmlrpc.client.DateTime)

decode_header() (dans le module email.header)

(dans le module nntplib)

decode_params() (dans le module email.utils)

decode_rfc2231() (dans le module email.utils)

decode_source() (dans le module importlib.util)

decodebytes() (dans le module base64)

DecodedGenerator (classe dans email.generator)

decodestring() (dans le module base64)

(dans le module quopri)

decomposition() (dans le module unicodedata)

decompress() (dans le module bz2)

(dans le module gzip)

(dans le module lzma)

(dans le module zlib)

(méthode bz2.BZ2Decompressor)

(méthode lzma.LZMADecompressor)

(méthode zlib.Decompress)

decompressobj() (dans le module zlib)

DEDENT (dans le module token)

DEDENT token, [1]

dedent() (dans le module textwrap)

deepcopy() (dans le module copy)

def

état

def_prog_mode() (dans le module curses)

def_shell_mode() (dans le module curses)

default

parameter value

default (attribut inspect.Parameter)

(attribut optparse.Option)

(dans le module email.policy)

DEFAULT (dans le module unittest.mock)

default() (méthode cmd.Cmd)

(méthode json.JSONEncoder)

DEFAULT_BUFFER_SIZE (dans le module io)

default_bufsize (dans le module xml.dom.pulldom)

default_exception_handler() (méthode asyncio.AbstractEventLoop)

default_factory (attribut collections.defaultdict)

DEFAULT_FORMAT (dans le module tarfile)

DEFAULT_IGNORES (dans le module filecmp)

default_open() (méthode urllib.request.BaseHandler)

DEFAULT_PROTOCOL (dans le module pickle)

default_timer() (dans le module timeit)

DefaultContext (classe dans decimal)

DefaultCookiePolicy (classe dans http.cookiejar)

defaultdict (classe dans collections)

DefaultDict (classe dans typing)

DefaultHandler() (méthode xml.parsers.expat.xmlparser)

DefaultHandlerExpand() (méthode xml.parsers.expat.xmlparser)

defaults() (méthode configparser.ConfigParser)

DefaultSelector (classe dans selectors)

defaultTestLoader (dans le module unittest)

defaultTestResult() (méthode unittest.TestCase)

defects (attribut email.headerregistry.BaseHeader)

(attribut email.message.EmailMessage)

(attribut email.message.Message)

define_macro() (méthode distutils.ccompiler.CCompiler)

definition

class, [1]

function, [1]

defpath (dans le module os)

DefragResult (classe dans urllib.parse)

DefragResultBytes (classe dans urllib.parse)

degrees() (dans le module math)

(dans le module turtle)

del

état, [1], [2], [3]

del_param() (méthode email.message.EmailMessage)

(méthode email.message.Message)

delattr() (fonction de base)

delay() (dans le module turtle)

delay_output() (dans le module curses)

delayload (attribut http.cookiejar.FileCookieJar)

delch() (méthode curses.window)

dele() (méthode poplib.POP3)

delete() (méthode ftplib.FTP)

(méthode imaplib.IMAP4)

(méthode tkinter.ttk.Treeview)

DELETE_ATTR (opcode)

DELETE_DEREF (opcode)

DELETE_FAST (opcode)

DELETE_GLOBAL (opcode)

DELETE_NAME (opcode)

DELETE_SUBSCR (opcode)

deleteacl() (méthode imaplib.IMAP4)

deletefilehandler() (méthode tkinter.Widget.tk)

DeleteKey() (dans le module winreg)

DeleteKeyEx() (dans le module winreg)

deleteln() (méthode curses.window)

deleteMe() (méthode bdb.Breakpoint)

DeleteValue() (dans le module winreg)

deletion

attribute

target

target list

delimiter (attribut csv.Dialect)

delimiters

delitem() (dans le module operator)

deliver_challenge() (dans le module multiprocessing.connection)

delocalize() (dans le module locale)

demo_app() (dans le module wsgiref.simple_server)

denominator (attribut fractions.Fraction)

(attribut numbers.Rational)

DeprecationWarning

deque (classe dans collections)

Deque (classe dans typing)

dequeue() (méthode logging.handlers.QueueListener)

DER_cert_to_PEM_cert() (dans le module ssl)

derwin() (méthode curses.window)

DES

cipher

descripteur

description (attribut sqlite3.Cursor)

description() (méthode nntplib.NNTP)

descriptions() (méthode nntplib.NNTP)

dest (attribut optparse.Option)

destructor, [1]

detach() (méthode io.BufferedIOBase)

(méthode io.TextIOBase)

(méthode socket.socket)

(méthode tkinter.ttk.Treeview)

(méthode weakref.finalize)

Detach() (méthode winreg.PyHKEY)

detect_api_mismatch() (dans le module test.support)

detect_encoding() (dans le module tokenize)

detect_language() (méthode distutils.ccompiler.CCompiler)

deterministic profiling

device_encoding() (dans le module os)

devnull (dans le module os)

DEVNULL (dans le module subprocess)

devpoll() (dans le module select)

DevpollSelector (classe dans selectors)

décorateur

dgettext() (dans le module gettext)

(dans le module locale)

dialect (attribut csv.csvreader)

(attribut csv.csvwriter)

Dialect (classe dans csv)

Dialog (classe dans msilib)

dict (2to3 fixer)

Dict (classe dans typing)

dict (classe de base)

dict() (méthode multiprocessing.managers.SyncManager)

dictConfig() (dans le module logging.config)

dictionary

display

objet, [1], [2], [3], [4], [5], [6], [7]

type, operations on

dictionnaire

DictReader (classe dans csv)

DictWriter (classe dans csv)

diff_bytes() (dans le module difflib)

diff_files (attribut filecmp.dircmp)

Differ (classe dans difflib), [1]

difference() (méthode frozenset)

difference_update() (méthode frozenset)

difflib (module)

digest() (méthode hashlib.hash)

(méthode hashlib.shake)

(méthode hmac.HMAC)

digest_size (attribut hmac.HMAC)

digit() (dans le module unicodedata)

digits (dans le module string)

dir() (fonction de base)

(méthode ftplib.FTP)

dircmp (classe dans filecmp)

directory

changing

creating

deleting, [1]

site-packages

traversal, [1]

walking, [1]

Directory (classe dans msilib)

directory ...

compileall command line option

directory_created() (fonction de base)

DirEntry (classe dans os)

DirList (classe dans tkinter.tix)

dirname() (dans le module os.path)

DirSelectBox (classe dans tkinter.tix)

DirSelectDialog (classe dans tkinter.tix)

DirTree (classe dans tkinter.tix)

dis (module)

dis() (dans le module dis)

(dans le module pickletools)

(méthode dis.Bytecode)

disable (pdb command)

disable() (dans le module faulthandler)

(dans le module gc)

(dans le module logging)

(méthode bdb.Breakpoint)

(méthode profile.Profile)

disable_interspersed_args() (méthode optparse.OptionParser)

DisableReflectionKey() (dans le module winreg)

disassemble() (dans le module dis)

discard (attribut http.cookiejar.Cookie)

discard() (méthode frozenset)

(méthode mailbox.Mailbox)

(méthode mailbox.MH)

discard_buffers() (méthode asynchat.async_chat)

disco() (dans le module dis)

discover() (méthode unittest.TestLoader)

disk_usage() (dans le module shutil)

dispatch_call() (méthode bdb.Bdb)

dispatch_exception() (méthode bdb.Bdb)

dispatch_line() (méthode bdb.Bdb)

dispatch_return() (méthode bdb.Bdb)

dispatch_table (attribut pickle.Pickler)

dispatcher (classe dans asyncore)

dispatcher_with_send (classe dans asyncore)

display

dictionary

list

set

tuple

display (pdb command)

display_name (attribut email.headerregistry.Address)

(attribut email.headerregistry.Group)

displayhook() (dans le module sys)

dist() (dans le module platform)

distance() (dans le module turtle)

distb() (dans le module dis)

Distribution (classe dans distutils.core)

distribution simple

distutils (module)

distutils.archive_util (module)

distutils.bcppcompiler (module)

distutils.ccompiler (module)

distutils.cmd (module)

distutils.command (module)

distutils.command.bdist (module)

distutils.command.bdist_dumb (module)

distutils.command.bdist_msi (module)

distutils.command.bdist_packager (module)

distutils.command.bdist_rpm (module)

distutils.command.bdist_wininst (module)

distutils.command.build (module)

distutils.command.build_clib (module)

distutils.command.build_ext (module)

distutils.command.build_py (module)

distutils.command.build_scripts (module)

distutils.command.check (module)

distutils.command.clean (module)

distutils.command.config (module)

distutils.command.install (module)

distutils.command.install_data (module)

distutils.command.install_headers (module)

distutils.command.install_lib (module)

distutils.command.install_scripts (module)

distutils.command.register (module)

distutils.command.sdist (module)

distutils.core (module)

distutils.cygwinccompiler (module)

distutils.debug (module)

distutils.dep_util (module)

distutils.dir_util (module)

distutils.dist (module)

distutils.errors (module)

distutils.extension (module)

distutils.fancy_getopt (module)

distutils.file_util (module)

distutils.filelist (module)

distutils.log (module)

distutils.msvccompiler (module)

distutils.spawn (module)

distutils.sysconfig (module)

distutils.text_file (module)

distutils.unixccompiler (module)

distutils.util (module)

distutils.version (module)

DISTUTILS_DEBUG

divide() (méthode decimal.Context)

divide_int() (méthode decimal.Context)

division

division entière

DivisionByZero (classe dans decimal)

divmod

fonction de base, [1], [2]

divmod() (fonction de base)

(méthode decimal.Context)

DllCanUnloadNow() (dans le module ctypes)

DllGetClassObject() (dans le module ctypes)

dllhandle (dans le module sys)

dngettext() (dans le module gettext)

do_clear() (méthode bdb.Bdb)

do_command() (méthode curses.textpad.Textbox)

do_GET() (méthode http.server.SimpleHTTPRequestHandler)

do_handshake() (méthode ssl.SSLSocket)

do_HEAD() (méthode http.server.SimpleHTTPRequestHandler)

do_POST() (méthode http.server.CGIHTTPRequestHandler)

doc (attribut json.JSONDecodeError)

doc_header (attribut cmd.Cmd)

DocCGIXMLRPCRequestHandler (classe dans xmlrpc.server)

DocFileSuite() (dans le module doctest)

doCleanups() (méthode unittest.TestCase)

docmd() (méthode smtplib.SMTP)

docstring

(attribut doctest.DocTest)

(chaîne de documentation)

docstrings, [1]

DocTest (classe dans doctest)

doctest (module)

DocTestFailure

DocTestFinder (classe dans doctest)

DocTestParser (classe dans doctest)

DocTestRunner (classe dans doctest)

DocTestSuite() (dans le module doctest)

doctype() (méthode xml.etree.ElementTree.TreeBuilder)

(méthode xml.etree.ElementTree.XMLParser)

documentation

generation

online

documentation string

documentation strings, [1]

documentElement (attribut xml.dom.Document)

DocXMLRPCRequestHandler (classe dans xmlrpc.server)

DocXMLRPCServer (classe dans xmlrpc.server)

domain (attribut email.headerregistry.Address)

(attribut tracemalloc.DomainFilter)

(attribut tracemalloc.Filter)

domain_initial_dot (attribut http.cookiejar.Cookie)

domain_return_ok() (méthode http.cookiejar.CookiePolicy)

domain_specified (attribut http.cookiejar.Cookie)

DomainFilter (classe dans tracemalloc)

DomainLiberal (attribut http.cookiejar.DefaultCookiePolicy)

DomainRFC2965Match (attribut http.cookiejar.DefaultCookiePolicy)

DomainStrict (attribut http.cookiejar.DefaultCookiePolicy)

DomainStrictNoDots (attribut http.cookiejar.DefaultCookiePolicy)

DomainStrictNonDomain (attribut http.cookiejar.DefaultCookiePolicy)

DOMEventStream (classe dans xml.dom.pulldom)

DOMException

DomstringSizeErr

done() (dans le module turtle)

(méthode asyncio.Future)

(méthode concurrent.futures.Future)

(méthode xdrlib.Unpacker)

DONT_ACCEPT_BLANKLINE (dans le module doctest)

DONT_ACCEPT_TRUE_FOR_1 (dans le module doctest)

dont_write_bytecode (dans le module sys)

doRollover() (méthode logging.handlers.RotatingFileHandler)

(méthode logging.handlers.TimedRotatingFileHandler)

DOT (dans le module token)

dot() (dans le module turtle)

DOTALL (dans le module re)

doublequote (attribut csv.Dialect)

DOUBLESLASH (dans le module token)

DOUBLESLASHEQUAL (dans le module token)

DOUBLESTAR (dans le module token)

DOUBLESTAREQUAL (dans le module token)

doupdate() (dans le module curses)

down (pdb command)

down() (dans le module turtle)

drain() (méthode asyncio.StreamWriter)

drop_whitespace (attribut textwrap.TextWrapper)

dropwhile() (dans le module itertools)

dst() (méthode datetime.datetime)

(méthode datetime.time)

(méthode datetime.timezone)

(méthode datetime.tzinfo)

DTDHandler (classe dans xml.sax.handler)

duck-typing

DumbWriter (classe dans formatter)

dummy_threading (module)

dump() (dans le module ast)

(dans le module json)

(dans le module marshal)

(dans le module pickle)

(dans le module plistlib)

(dans le module xml.etree.ElementTree)

(méthode pickle.Pickler)

(méthode tracemalloc.Snapshot)

dump_stats() (méthode profile.Profile)

(méthode pstats.Stats)

dump_traceback() (dans le module faulthandler)

dump_traceback_later() (dans le module faulthandler)

dumps() (dans le module json)

(dans le module marshal)

(dans le module pickle)

(dans le module plistlib)

(dans le module xmlrpc.client)

dup() (dans le module os)

(méthode socket.socket)

dup2() (dans le module os)

DUP_TOP (opcode)

DUP_TOP_TWO (opcode)

DuplicateOptionError

DuplicateSectionError

dwFlags (attribut subprocess.STARTUPINFO)

DynamicClassAttribute() (dans le module types)

E

e

in numeric literal

e (dans le module cmath)

(dans le module math)

E2BIG (dans le module errno)

EACCES (dans le module errno)

EADDRINUSE (dans le module errno)

EADDRNOTAVAIL (dans le module errno)

EADV (dans le module errno)

EAFNOSUPPORT (dans le module errno)

EAFP

EAGAIN (dans le module errno)

EALREADY (dans le module errno)

east_asian_width() (dans le module unicodedata)

EBADE (dans le module errno)

EBADF (dans le module errno)

EBADFD (dans le module errno)

EBADMSG (dans le module errno)

EBADR (dans le module errno)

EBADRQC (dans le module errno)

EBADSLT (dans le module errno)

EBFONT (dans le module errno)

EBUSY (dans le module errno)

ECHILD (dans le module errno)

echo() (dans le module curses)

echochar() (méthode curses.window)

ECHRNG (dans le module errno)

ECOMM (dans le module errno)

ECONNABORTED (dans le module errno)

ECONNREFUSED (dans le module errno)

ECONNRESET (dans le module errno)

EDEADLK (dans le module errno)

EDEADLOCK (dans le module errno)

EDESTADDRREQ (dans le module errno)

edit() (méthode curses.textpad.Textbox)

EDOM (dans le module errno)

EDOTDOT (dans le module errno)

EDQUOT (dans le module errno)

EEXIST (dans le module errno)

EFAULT (dans le module errno)

EFBIG (dans le module errno)

effective() (dans le module bdb)

ehlo() (méthode smtplib.SMTP)

ehlo_or_helo_if_needed() (méthode smtplib.SMTP)

EHOSTDOWN (dans le module errno)

EHOSTUNREACH (dans le module errno)

EIDRM (dans le module errno)

EILSEQ (dans le module errno)

EINPROGRESS (dans le module errno)

EINTR (dans le module errno)

EINVAL (dans le module errno)

EIO (dans le module errno)

EISCONN (dans le module errno)

EISDIR (dans le module errno)

EISNAM (dans le module errno)

EL2HLT (dans le module errno)

EL2NSYNC (dans le module errno)

EL3HLT (dans le module errno)

EL3RST (dans le module errno)

Element (classe dans xml.etree.ElementTree)

element_create() (méthode tkinter.ttk.Style)

element_names() (méthode tkinter.ttk.Style)

element_options() (méthode tkinter.ttk.Style)

ElementDeclHandler() (méthode xml.parsers.expat.xmlparser)

elements() (méthode collections.Counter)

ElementTree (classe dans xml.etree.ElementTree)

ELIBACC (dans le module errno)

ELIBBAD (dans le module errno)

ELIBEXEC (dans le module errno)

ELIBMAX (dans le module errno)

ELIBSCN (dans le module errno)

elif

mot-clé

Ellinghouse, Lance

Ellipsis

objet

ELLIPSIS (dans le module doctest)

(dans le module token)

Ellipsis (variable de base)

ELNRNG (dans le module errno)

ELOOP (dans le module errno)

else

conditional expression

dangling

mot-clé, [1], [2], [3], [4], [5], [6], [7]

email (module)

email.charset (module)

email.contentmanager (module)

email.encoders (module)

email.errors (module)

email.generator (module)

email.header (module)

email.headerregistry (module)

email.iterators (module)

email.message (module)

email.mime (module)

email.parser (module)

email.policy (module)

email.utils (module)

EmailMessage (classe dans email.message)

EmailPolicy (classe dans email.policy)

EMFILE (dans le module errno)

emit() (méthode logging.FileHandler)

(méthode logging.Handler)

(méthode logging.handlers.BufferingHandler)

(méthode logging.handlers.DatagramHandler)

(méthode logging.handlers.HTTPHandler)

(méthode logging.handlers.NTEventLogHandler)

(méthode logging.handlers.QueueHandler)

(méthode logging.handlers.RotatingFileHandler)

(méthode logging.handlers.SMTPHandler)

(méthode logging.handlers.SocketHandler)

(méthode logging.handlers.SysLogHandler)

(méthode logging.handlers.TimedRotatingFileHandler)

(méthode logging.handlers.WatchedFileHandler)

(méthode logging.NullHandler)

(méthode logging.StreamHandler)

EMLINK (dans le module errno)

Empty

empty

list

tuple, [1]

empty (attribut inspect.Parameter)

(attribut inspect.Signature)

empty() (méthode asyncio.Queue)

(méthode multiprocessing.Queue)

(méthode multiprocessing.SimpleQueue)

(méthode queue.Queue)

(méthode sched.scheduler)

EMPTY_NAMESPACE (dans le module xml.dom)

emptyline() (méthode cmd.Cmd)

EMSGSIZE (dans le module errno)

EMULTIHOP (dans le module errno)

enable (pdb command)

enable() (dans le module cgitb)

(dans le module faulthandler)

(dans le module gc)

(méthode bdb.Breakpoint)

(méthode imaplib.IMAP4)

(méthode profile.Profile)

enable_callback_tracebacks() (dans le module sqlite3)

enable_interspersed_args() (méthode optparse.OptionParser)

enable_load_extension() (méthode sqlite3.Connection)

enable_traversal() (méthode tkinter.ttk.Notebook)

ENABLE_USER_SITE (dans le module site)

EnableReflectionKey() (dans le module winreg)

ENAMETOOLONG (dans le module errno)

ENAVAIL (dans le module errno)

enclose() (méthode curses.window)

encodage de texte

encode

Codecs

encode (attribut codecs.CodecInfo)

encode() (dans le module base64)

(dans le module codecs)

(dans le module quopri)

(dans le module uu)

(méthode codecs.Codec)

(méthode codecs.IncrementalEncoder)

(méthode email.header.Header)

(méthode json.JSONEncoder)

(méthode str)

(méthode xmlrpc.client.Binary)

(méthode xmlrpc.client.DateTime)

encode_7or8bit() (dans le module email.encoders)

encode_base64() (dans le module email.encoders)

encode_noop() (dans le module email.encoders)

encode_quopri() (dans le module email.encoders)

encode_rfc2231() (dans le module email.utils)

encodebytes() (dans le module base64)

EncodedFile() (dans le module codecs)

encodePriority() (méthode logging.handlers.SysLogHandler)

encodestring() (dans le module base64)

(dans le module quopri)

encoding

base64

quoted-printable

encoding (attribut curses.window)

(attribut io.TextIOBase)

(attribut UnicodeError)

ENCODING (dans le module tarfile)

(dans le module tokenize)

encoding declarations (source file)

encodings.idna (module)

encodings.mbcs (module)

encodings.utf_8_sig (module)

encodings_map (attribut mimetypes.MimeTypes)

(dans le module mimetypes)

end (attribut UnicodeError)

end() (méthode re.match)

(méthode xml.etree.ElementTree.TreeBuilder)

end_fill() (dans le module turtle)

END_FINALLY (opcode)

end_headers() (méthode http.server.BaseHTTPRequestHandler)

end_paragraph() (méthode formatter.formatter)

end_poly() (dans le module turtle)

EndCdataSectionHandler() (méthode xml.parsers.expat.xmlparser)

EndDoctypeDeclHandler() (méthode xml.parsers.expat.xmlparser)

endDocument() (méthode xml.sax.handler.ContentHandler)

endElement() (méthode xml.sax.handler.ContentHandler)

EndElementHandler() (méthode xml.parsers.expat.xmlparser)

endElementNS() (méthode xml.sax.handler.ContentHandler)

endheaders() (méthode http.client.HTTPConnection)

ENDMARKER (dans le module token)

EndNamespaceDeclHandler() (méthode xml.parsers.expat.xmlparser)

endpos (attribut re.match)

endPrefixMapping() (méthode xml.sax.handler.ContentHandler)

endswith() (méthode bytearray)

(méthode bytes)

(méthode str)

endwin() (dans le module curses)

ENETDOWN (dans le module errno)

ENETRESET (dans le module errno)

ENETUNREACH (dans le module errno)

ENFILE (dans le module errno)

ENOANO (dans le module errno)

ENOBUFS (dans le module errno)

ENOCSI (dans le module errno)

ENODATA (dans le module errno)

ENODEV (dans le module errno)

ENOENT (dans le module errno)

ENOEXEC (dans le module errno)

ENOLCK (dans le module errno)

ENOLINK (dans le module errno)

ENOMEM (dans le module errno)

ENOMSG (dans le module errno)

ENONET (dans le module errno)

ENOPKG (dans le module errno)

ENOPROTOOPT (dans le module errno)

ENOSPC (dans le module errno)

ENOSR (dans le module errno)

ENOSTR (dans le module errno)

ENOSYS (dans le module errno)

ENOTBLK (dans le module errno)

ENOTCONN (dans le module errno)

ENOTDIR (dans le module errno)

ENOTEMPTY (dans le module errno)

ENOTNAM (dans le module errno)

ENOTSOCK (dans le module errno)

ENOTTY (dans le module errno)

ENOTUNIQ (dans le module errno)

enqueue() (méthode logging.handlers.QueueHandler)

enqueue_sentinel() (méthode logging.handlers.QueueListener)

ensure_directories() (méthode venv.EnvBuilder)

ensure_future() (dans le module asyncio)

ensurepip (module)

enter() (méthode sched.scheduler)

enter_context() (méthode contextlib.ExitStack)

enterabs() (méthode sched.scheduler)

entities (attribut xml.dom.DocumentType)

EntityDeclHandler() (méthode xml.parsers.expat.xmlparser)

entitydefs (dans le module html.entities)

EntityResolver (classe dans xml.sax.handler)

entrée de chemin

Enum (classe dans enum)

enum (module)

enum_certificates() (dans le module ssl)

enum_crls() (dans le module ssl)

enumerate() (dans le module threading)

(fonction de base)

EnumKey() (dans le module winreg)

EnumValue() (dans le module winreg)

EnvBuilder (classe dans venv)

environ (dans le module os)

(dans le module posix)

environb (dans le module os)

environment

environment variables

deleting

setting

EnvironmentError

Environments

virtual

EnvironmentVarGuard (classe dans test.support)

environnement virtuel

ENXIO (dans le module errno)

eof (attribut bz2.BZ2Decompressor)

(attribut lzma.LZMADecompressor)

(attribut shlex.shlex)

(attribut ssl.MemoryBIO)

(attribut zlib.Decompress)

eof_received() (méthode asyncio.Protocol)

EOFError

(built-in exception)

EOPNOTSUPP (dans le module errno)

EOVERFLOW (dans le module errno)

EPERM (dans le module errno)

EPFNOSUPPORT (dans le module errno)

epilogue (attribut email.message.EmailMessage)

(attribut email.message.Message)

EPIPE (dans le module errno)

epoch

epoll() (dans le module select)

EpollSelector (classe dans selectors)

EPROTO (dans le module errno)

EPROTONOSUPPORT (dans le module errno)

EPROTOTYPE (dans le module errno)

eq() (dans le module operator)

EQEQUAL (dans le module token)

EQUAL (dans le module token)

ERA (dans le module locale)

ERA_D_FMT (dans le module locale)

ERA_D_T_FMT (dans le module locale)

ERA_T_FMT (dans le module locale)

ERANGE (dans le module errno)

erase() (méthode curses.window)

erasechar() (dans le module curses)

EREMCHG (dans le module errno)

EREMOTE (dans le module errno)

EREMOTEIO (dans le module errno)

ERESTART (dans le module errno)

erf() (dans le module math)

erfc() (dans le module math)

EROFS (dans le module errno)

ERR (dans le module curses)

errcheck (attribut ctypes._FuncPtr)

errcode (attribut xmlrpc.client.ProtocolError)

errmsg (attribut xmlrpc.client.ProtocolError)

errno

module

errno (attribut OSError)

(module)

Error, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12]

error, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17]

error handling

error() (dans le module logging)

(méthode argparse.ArgumentParser)

(méthode logging.Logger)

(méthode urllib.request.OpenerDirector)

(méthode xml.sax.handler.ErrorHandler)

error_body (attribut wsgiref.handlers.BaseHandler)

error_content_type (attribut http.server.BaseHTTPRequestHandler)

error_headers (attribut wsgiref.handlers.BaseHandler)

error_leader() (méthode shlex.shlex)

error_message_format (attribut http.server.BaseHTTPRequestHandler)

error_output() (méthode wsgiref.handlers.BaseHandler)

error_perm

error_proto, [1]

error_received() (méthode asyncio.DatagramProtocol)

error_reply

error_status (attribut wsgiref.handlers.BaseHandler)

error_temp

ErrorByteIndex (attribut xml.parsers.expat.xmlparser)

ErrorCode (attribut xml.parsers.expat.xmlparser)

errorcode (dans le module errno)

ErrorColumnNumber (attribut xml.parsers.expat.xmlparser)

ErrorHandler (classe dans xml.sax.handler)

ErrorLineNumber (attribut xml.parsers.expat.xmlparser)

Errors

logging

errors

(attribut io.TextIOBase)

(attribut unittest.TestLoader)

(attribut unittest.TestResult)

ErrorString() (dans le module xml.parsers.expat)

ERRORTOKEN (dans le module token)

escape (attribut shlex.shlex)

escape sequence

escape() (dans le module cgi)

(dans le module glob)

(dans le module html)

(dans le module re)

(dans le module xml.sax.saxutils)

escapechar (attribut csv.Dialect)

escapedquotes (attribut shlex.shlex)

ESHUTDOWN (dans le module errno)

ESOCKTNOSUPPORT (dans le module errno)

espace de nommage

ESPIPE (dans le module errno)

ESRCH (dans le module errno)

ESRMNT (dans le module errno)

ESTALE (dans le module errno)

ESTRPIPE (dans le module errno)

ETIME (dans le module errno)

ETIMEDOUT (dans le module errno)

Etiny() (méthode decimal.Context)

ETOOMANYREFS (dans le module errno)

Etop() (méthode decimal.Context)

ETXTBSY (dans le module errno)

EUCLEAN (dans le module errno)

EUNATCH (dans le module errno)

EUSERS (dans le module errno)

eval

fonction de base, [1], [2], [3], [4], [5]

eval() (fonction de base)

evaluation

order

Event (classe dans asyncio)

(classe dans multiprocessing)

(classe dans threading)

event scheduling

event() (méthode msilib.Control)

Event() (méthode multiprocessing.managers.SyncManager)

events (attribut selectors.SelectorKey)

(widgets)

EWOULDBLOCK (dans le module errno)

EX_CANTCREAT (dans le module os)

EX_CONFIG (dans le module os)

EX_DATAERR (dans le module os)

EX_IOERR (dans le module os)

EX_NOHOST (dans le module os)

EX_NOINPUT (dans le module os)

EX_NOPERM (dans le module os)

EX_NOTFOUND (dans le module os)

EX_NOUSER (dans le module os)

EX_OK (dans le module os)

EX_OSERR (dans le module os)

EX_OSFILE (dans le module os)

EX_PROTOCOL (dans le module os)

EX_SOFTWARE (dans le module os)

EX_TEMPFAIL (dans le module os)

EX_UNAVAILABLE (dans le module os)

EX_USAGE (dans le module os)

example (attribut doctest.DocTestFailure)

(attribut doctest.UnexpectedException)

Example (classe dans doctest)

examples (attribut doctest.DocTest)

exc_info (attribut doctest.UnexpectedException)

(in module sys)

exc_info() (dans le module sys)

(in module sys)

exc_msg (attribut doctest.Example)

exc_type (attribut traceback.TracebackException)

excel (classe dans csv)

excel_tab (classe dans csv)

except

état

mot-clé

except (2to3 fixer)

excepthook() (dans le module sys)

(in module sys)

Exception

exception, [1]

AssertionError

AttributeError

chaining

GeneratorExit, [1]

handler

ImportError

NameError

raising

StopAsyncIteration

StopIteration, [1]

TypeError

ValueError

ZeroDivisionError

EXCEPTION (dans le module tkinter)

exception handler

exception() (dans le module logging)

(méthode asyncio.Future)

(méthode asyncio.StreamReader)

(méthode concurrent.futures.Future)

(méthode logging.Logger)

exceptions

in CGI scripts

exclusive

or

EXDEV (dans le module errno)

exec

fonction de base, [1], [2], [3]

exec (2to3 fixer)

exec() (fonction de base)

exec_module (fonction C)

exec_module() (méthode importlib.abc.InspectLoader)

(méthode importlib.abc.Loader)

(méthode importlib.abc.SourceLoader)

(méthode importlib.machinery.ExtensionFileLoader)

exec_prefix, [1], [2]

EXEC_PREFIX (dans le module distutils.sysconfig)

exec_prefix (dans le module sys)

execfile (2to3 fixer)

execl() (dans le module os)

execle() (dans le module os)

execlp() (dans le module os)

execlpe() (dans le module os)

executable (dans le module sys)

(in module sys)

Executable Zip Files

executable_filename() (méthode distutils.ccompiler.CCompiler)

execute() (dans le module distutils.util)

(méthode distutils.ccompiler.CCompiler)

Execute() (méthode msilib.View)

execute() (méthode sqlite3.Connection)

(méthode sqlite3.Cursor)

executemany() (méthode sqlite3.Connection)

(méthode sqlite3.Cursor)

executescript() (méthode sqlite3.Connection)

(méthode sqlite3.Cursor)

execution

frame, [1]

restricted

stack

execution model

ExecutionLoader (classe dans importlib.abc)

Executor (classe dans concurrent.futures)

execv() (dans le module os)

execve() (dans le module os)

execvp() (dans le module os)

execvpe() (dans le module os)

ExFileSelectBox (classe dans tkinter.tix)

EXFULL (dans le module errno)

exists() (dans le module os.path)

(méthode pathlib.Path)

(méthode tkinter.ttk.Treeview)

exit (variable de base)

exit()

(dans le module _thread)

(dans le module sys)

(méthode argparse.ArgumentParser)

exitcode (attribut multiprocessing.Process)

exitfunc (2to3 fixer)

exitonclick() (dans le module turtle)

ExitStack (classe dans contextlib)

exp() (dans le module cmath)

(dans le module math)

(méthode decimal.Context)

(méthode decimal.Decimal)

expand() (méthode re.match)

expand_tabs (attribut textwrap.TextWrapper)

ExpandEnvironmentStrings() (dans le module winreg)

expandNode() (méthode xml.dom.pulldom.DOMEventStream)

expandtabs() (méthode bytearray)

(méthode bytes)

(méthode str)

expanduser() (dans le module os.path)

(méthode pathlib.Path)

expandvars() (dans le module os.path)

Expat

ExpatError

expect() (méthode telnetlib.Telnet)

expected (attribut asyncio.IncompleteReadError)

expectedFailure() (dans le module unittest)

expectedFailures (attribut unittest.TestResult)

expires (attribut http.cookiejar.Cookie)

exploded (attribut ipaddress.IPv4Address)

(attribut ipaddress.IPv4Network)

(attribut ipaddress.IPv6Address)

(attribut ipaddress.IPv6Network)

expm1() (dans le module math)

expovariate() (dans le module random)

expr() (dans le module parser)

expression, [1]

Conditional

conditional

generator

lambda, [1]

list, [1], [2]

statement

yield

expression génératrice

expunge() (méthode imaplib.IMAP4)

extend() (méthode array.array)

(méthode collections.deque)

(méthode xml.etree.ElementTree.Element)

(sequence method)

extend_path() (dans le module pkgutil)

EXTENDED_ARG (opcode)

ExtendedContext (classe dans decimal)

ExtendedInterpolation (classe dans configparser)

extendleft() (méthode collections.deque)

extension

module

Extension (classe dans distutils.core)

EXTENSION_SUFFIXES (dans le module importlib.machinery)

ExtensionFileLoader (classe dans importlib.machinery)

extensions_map (attribut http.server.SimpleHTTPRequestHandler)

External Data Representation, [1]

external_attr (attribut zipfile.ZipInfo)

ExternalClashError

ExternalEntityParserCreate() (méthode xml.parsers.expat.xmlparser)

ExternalEntityRefHandler() (méthode xml.parsers.expat.xmlparser)

extra (attribut zipfile.ZipInfo)

extract() (méthode de la classe traceback.StackSummary)

(méthode tarfile.TarFile)

(méthode zipfile.ZipFile)

extract_cookies() (méthode http.cookiejar.CookieJar)

extract_stack() (dans le module traceback)

extract_tb() (dans le module traceback)

extract_version (attribut zipfile.ZipInfo)

extractall() (méthode tarfile.TarFile)

(méthode zipfile.ZipFile)

ExtractError

extractfile() (méthode tarfile.TarFile)

extsep (dans le module os)

état

assert, [1]

async def

async for

async with

break, [1], [2], [3], [4]

class

continue, [1], [2], [3], [4]

def

del, [1], [2], [3]

except

for, [1], [2], [3]

global, [1]

if, [1]

import, [1], [2], [3], [4]

nonlocal

pass

raise, [1]

return, [1], [2]

try, [1], [2]

while, [1], [2], [3]

with, [1]

yield

F

f"

formatted string literal

f'

formatted string literal

f-string, [1]

f_back (frame attribute)

f_builtins (frame attribute)

f_code (frame attribute)

f_contiguous (attribut memoryview)

f_globals (frame attribute)

f_lasti (frame attribute)

f_lineno (frame attribute)

f_locals (frame attribute)

F_LOCK (dans le module os)

F_OK (dans le module os)

F_TEST (dans le module os)

F_TLOCK (dans le module os)

f_trace (frame attribute)

F_ULOCK (dans le module os)

fabs() (dans le module math)

factorial() (dans le module math)

factory() (méthode de la classe importlib.util.LazyLoader)

fail() (méthode unittest.TestCase)

FAIL_FAST (dans le module doctest)

failfast (attribut unittest.TestResult)

failureException (attribut unittest.TestCase)

failures (attribut unittest.TestResult)

FakePath (classe dans test.support)

False, [1], [2]

false

False (Built-in object)

(variable de base)

family (attribut socket.socket)

fancy_getopt() (dans le module distutils.fancy_getopt)

FancyGetopt (classe dans distutils.fancy_getopt)

FancyURLopener (classe dans urllib.request)

fast (attribut pickle.Pickler)

fatalError() (méthode xml.sax.handler.ErrorHandler)

Fault (classe dans xmlrpc.client)

faultCode (attribut xmlrpc.client.Fault)

faulthandler (module)

faultString (attribut xmlrpc.client.Fault)

fchdir() (dans le module os)

fchmod() (dans le module os)

fchown() (dans le module os)

FCICreate() (dans le module msilib)

fcntl (module)

fcntl() (dans le module fcntl)

fd (attribut selectors.SelectorKey)

fd() (dans le module turtle)

fdatasync() (dans le module os)

fdopen() (dans le module os)

Feature (classe dans msilib)

feature_external_ges (dans le module xml.sax.handler)

feature_external_pes (dans le module xml.sax.handler)

feature_namespace_prefixes (dans le module xml.sax.handler)

feature_namespaces (dans le module xml.sax.handler)

feature_string_interning (dans le module xml.sax.handler)

feature_validation (dans le module xml.sax.handler)

feed() (méthode email.parser.BytesFeedParser)

(méthode html.parser.HTMLParser)

(méthode xml.etree.ElementTree.XMLParser)

(méthode xml.etree.ElementTree.XMLPullParser)

(méthode xml.sax.xmlreader.IncrementalParser)

feed_data() (méthode asyncio.StreamReader)

feed_eof() (méthode asyncio.StreamReader)

FeedParser (classe dans email.parser)

fetch() (méthode imaplib.IMAP4)

Fetch() (méthode msilib.View)

fetchall() (méthode sqlite3.Cursor)

fetchmany() (méthode sqlite3.Cursor)

fetchone() (méthode sqlite3.Cursor)

fflags (attribut select.kevent)

fichier binaire

fichier texte

field_size_limit() (dans le module csv)

fieldnames (attribut csv.csvreader)

fields (attribut uuid.UUID)

file

.ini

.pdbrc

byte-code, [1]

configuration

copying

debugger configuration

large files

mime.types

modes

objet, [1]

path configuration

plist

temporary

file (attribut pyclbr.Class)

(attribut pyclbr.Function)

file ...

compileall command line option

file control

UNIX

file name

temporary

file object

io module

open() built-in function

FILE_ATTRIBUTE_ARCHIVE (dans le module stat)

FILE_ATTRIBUTE_COMPRESSED (dans le module stat)

FILE_ATTRIBUTE_DEVICE (dans le module stat)

FILE_ATTRIBUTE_DIRECTORY (dans le module stat)

FILE_ATTRIBUTE_ENCRYPTED (dans le module stat)

FILE_ATTRIBUTE_HIDDEN (dans le module stat)

FILE_ATTRIBUTE_INTEGRITY_STREAM (dans le module stat)

FILE_ATTRIBUTE_NO_SCRUB_DATA (dans le module stat)

FILE_ATTRIBUTE_NORMAL (dans le module stat)

FILE_ATTRIBUTE_NOT_CONTENT_INDEXED (dans le module stat)

FILE_ATTRIBUTE_OFFLINE (dans le module stat)

FILE_ATTRIBUTE_READONLY (dans le module stat)

FILE_ATTRIBUTE_REPARSE_POINT (dans le module stat)

FILE_ATTRIBUTE_SPARSE_FILE (dans le module stat)

FILE_ATTRIBUTE_SYSTEM (dans le module stat)

FILE_ATTRIBUTE_TEMPORARY (dans le module stat)

FILE_ATTRIBUTE_VIRTUAL (dans le module stat)

file_created() (fonction de base)

file_dispatcher (classe dans asyncore)

file_open() (méthode urllib.request.FileHandler)

file_size (attribut zipfile.ZipInfo)

file_wrapper (classe dans asyncore)

filecmp (module)

fileConfig() (dans le module logging.config)

FileCookieJar (classe dans http.cookiejar)

FileEntry (classe dans tkinter.tix)

FileExistsError

FileFinder (classe dans importlib.machinery)

FileHandler (classe dans logging)

(classe dans urllib.request)

FileInput (classe dans fileinput)

fileinput (module)

FileIO (classe dans io)

filelineno() (dans le module fileinput)

FileLoader (classe dans importlib.abc)

filemode() (dans le module stat)

filename (attribut doctest.DocTest)

(attribut http.cookiejar.FileCookieJar)

(attribut OSError)

(attribut traceback.TracebackException)

(attribut tracemalloc.Frame)

(attribut zipfile.ZipFile)

(attribut zipfile.ZipInfo)

filename() (dans le module fileinput)

filename2 (attribut OSError)

filename_only (dans le module tabnanny)

filename_pattern (attribut tracemalloc.Filter)

filenames

pathname expansion

wildcard expansion

fileno() (dans le module fileinput)

(méthode http.client.HTTPResponse)

(méthode io.IOBase)

(méthode multiprocessing.connection.Connection)

(méthode ossaudiodev.oss_audio_device)

(méthode ossaudiodev.oss_mixer_device)

(méthode select.devpoll)

(méthode select.epoll)

(méthode select.kqueue)

(méthode selectors.DevpollSelector)

(méthode selectors.EpollSelector)

(méthode selectors.KqueueSelector)

(méthode socket.socket)

(méthode socketserver.BaseServer)

(méthode telnetlib.Telnet)

FileNotFoundError

fileobj (attribut selectors.SelectorKey)

FileSelectBox (classe dans tkinter.tix)

FileType (classe dans argparse)

FileWrapper (classe dans wsgiref.util)

fill() (dans le module textwrap)

(méthode textwrap.TextWrapper)

fillcolor() (dans le module turtle)

filling() (dans le module turtle)

filter (2to3 fixer)

(attribut select.kevent)

Filter (classe dans logging)

(classe dans tracemalloc)

filter() (dans le module curses)

(dans le module fnmatch)

(fonction de base)

(méthode logging.Filter)

(méthode logging.Handler)

(méthode logging.Logger)

FILTER_DIR (dans le module unittest.mock)

filter_traces() (méthode tracemalloc.Snapshot)

filterfalse() (dans le module itertools)

filterwarnings() (dans le module warnings)

finalization, of objects

finalize (classe dans weakref)

finalize_options() (méthode distutils.cmd.Command)

finalizer

finally

mot-clé, [1], [2], [3], [4]

find() (dans le module gettext)

(méthode bytearray)

(méthode bytes)

(méthode doctest.DocTestFinder)

(méthode mmap.mmap)

(méthode str)

(méthode xml.etree.ElementTree.Element)

(méthode xml.etree.ElementTree.ElementTree)

find_class() (méthode pickle.Unpickler)

(pickle protocol)

find_library() (dans le module ctypes.util)

find_library_file() (méthode distutils.ccompiler.CCompiler)

find_loader() (dans le module importlib)

(dans le module pkgutil)

(méthode importlib.abc.PathEntryFinder)

(méthode importlib.machinery.FileFinder)

find_longest_match() (méthode difflib.SequenceMatcher)

find_module() (dans le module imp)

(méthode de la classe importlib.machinery.PathFinder)

(méthode imp.NullImporter)

(méthode importlib.abc.Finder)

(méthode importlib.abc.MetaPathFinder)

(méthode importlib.abc.PathEntryFinder)

(méthode zipimport.zipimporter)

find_msvcrt() (dans le module ctypes.util)

find_spec

finder

find_spec() (dans le module importlib.util)

(méthode de la classe importlib.machinery.PathFinder)

(méthode importlib.abc.MetaPathFinder)

(méthode importlib.abc.PathEntryFinder)

(méthode importlib.machinery.FileFinder)

find_unused_port() (dans le module test.support)

find_user_password() (méthode urllib.request.HTTPPasswordMgr), [1]

findall() (dans le module re)

(méthode re.regex)

(méthode xml.etree.ElementTree.Element)

(méthode xml.etree.ElementTree.ElementTree)

findCaller() (méthode logging.Logger)

finder

find_spec

Finder (classe dans importlib.abc)

findfactor() (dans le module audioop)

findfile() (dans le module test.support)

findfit() (dans le module audioop)

finditer() (dans le module re)

(méthode re.regex)

findlabels() (dans le module dis)

findlinestarts() (dans le module dis)

findmatch() (dans le module mailcap)

findmax() (dans le module audioop)

findtext() (méthode xml.etree.ElementTree.Element)

(méthode xml.etree.ElementTree.ElementTree)

finish() (méthode socketserver.BaseRequestHandler)

finish_request() (méthode socketserver.BaseServer)

firstChild (attribut xml.dom.Node)

firstkey() (méthode dbm.gnu.gdbm)

firstweekday() (dans le module calendar)

fix_missing_locations() (dans le module ast)

fix_sentence_endings (attribut textwrap.TextWrapper)

Flag (classe dans enum)

flag_bits (attribut zipfile.ZipInfo)

flags (attribut re.regex)

(attribut select.kevent)

(dans le module sys)

flash() (dans le module curses)

flatten() (méthode email.generator.BytesGenerator)

(méthode email.generator.Generator)

flattening

objects

float

fonction de base, [1], [2]

float (classe de base)

float_info (dans le module sys)

float_repr_style (dans le module sys)

floating point

literals

number

objet, [1], [2]

floating point literal

FloatingPointError, [1]

FloatOperation (classe dans decimal)

flock() (dans le module fcntl)

floor() (dans le module math)

(in module math)

floordiv() (dans le module operator)

flush() (méthode bz2.BZ2Compressor)

(méthode formatter.writer)

(méthode io.BufferedWriter)

(méthode io.IOBase)

(méthode logging.Handler)

(méthode logging.handlers.BufferingHandler)

(méthode logging.handlers.MemoryHandler)

(méthode logging.StreamHandler)

(méthode lzma.LZMACompressor)

(méthode mailbox.Mailbox)

(méthode mailbox.Maildir)

(méthode mailbox.MH)

(méthode mmap.mmap)

(méthode zlib.Compress)

(méthode zlib.Decompress)

flush_headers() (méthode http.server.BaseHTTPRequestHandler)

flush_softspace() (méthode formatter.formatter)

flushinp() (dans le module curses)

FlushKey() (dans le module winreg)

fma() (méthode decimal.Context)

(méthode decimal.Decimal)

fmod() (dans le module math)

FMT_BINARY (dans le module plistlib)

FMT_XML (dans le module plistlib)

fnmatch (module)

fnmatch() (dans le module fnmatch)

fnmatchcase() (dans le module fnmatch)

focus() (méthode tkinter.ttk.Treeview)

fold (attribut datetime.datetime)

(attribut datetime.time)

fold() (méthode email.headerregistry.BaseHeader)

(méthode email.policy.Compat32)

(méthode email.policy.EmailPolicy)

(méthode email.policy.Policy)

fold_binary() (méthode email.policy.Compat32)

(méthode email.policy.EmailPolicy)

(méthode email.policy.Policy)

fonction

fonction clé

fonction coroutine

fonction de base

__import__

abs, [1]

ascii

bytes, [1]

chr

classmethod

compile, [1], [2], [3], [4]

complex, [1]

divmod, [1], [2]

eval, [1], [2], [3], [4], [5]

exec, [1], [2], [3]

float, [1], [2]

hash, [1], [2], [3]

help

id

int, [1], [2]

len, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11]

max

min

open, [1]

ord

pow, [1], [2], [3], [4], [5]

print

range

repr, [1], [2], [3]

round

slice, [1]

staticmethod

tuple, [1]

type, [1], [2], [3]

fonction générique

for

état, [1], [2], [3]

in comprehensions

FOR_ITER (opcode)

forget() (dans le module test.support)

(méthode tkinter.ttk.Notebook)

fork() (dans le module os)

(dans le module pty)

ForkingMixIn (classe dans socketserver)

ForkingTCPServer (classe dans socketserver)

ForkingUDPServer (classe dans socketserver)

forkpty() (dans le module os)

form

lambda

Form (classe dans tkinter.tix)

format (attribut memoryview)

(attribut struct.Struct)

format() (built-in function)

__str__() (object method)

format() (dans le module locale)

(fonction de base)

(méthode logging.Formatter)

(méthode logging.Handler)

(méthode pprint.PrettyPrinter)

(méthode str)

(méthode string.Formatter)

(méthode traceback.StackSummary)

(méthode traceback.TracebackException)

(méthode tracemalloc.Traceback)

format_datetime() (dans le module email.utils)

format_exc() (dans le module traceback)

format_exception() (dans le module traceback)

format_exception_only() (dans le module traceback)

(méthode traceback.TracebackException)

format_field() (méthode string.Formatter)

format_help() (méthode argparse.ArgumentParser)

format_list() (dans le module traceback)

format_map() (méthode str)

format_stack() (dans le module traceback)

format_stack_entry() (méthode bdb.Bdb)

format_string() (dans le module locale)

format_tb() (dans le module traceback)

format_usage() (méthode argparse.ArgumentParser)

FORMAT_VALUE (opcode)

formataddr() (dans le module email.utils)

formatargspec() (dans le module inspect)

formatargvalues() (dans le module inspect)

formatdate() (dans le module email.utils)

FormatError

FormatError() (dans le module ctypes)

formatException() (méthode logging.Formatter)

formatmonth() (méthode calendar.HTMLCalendar)

(méthode calendar.TextCalendar)

formatStack() (méthode logging.Formatter)

formatted string literal

Formatter (classe dans logging)

(classe dans string)

formatter (module)

formatTime() (méthode logging.Formatter)

formatting

bytearray (%)

bytes (%)

formatting, string (%)

formatwarning() (dans le module warnings)

formatyear() (méthode calendar.HTMLCalendar)

(méthode calendar.TextCalendar)

formatyearpage() (méthode calendar.HTMLCalendar)

Fortran contiguous, [1]

forward() (dans le module turtle)

found_terminator() (méthode asynchat.async_chat)

fpathconf() (dans le module os)

fpectl (module)

fqdn (attribut smtpd.SMTPChannel)

Fraction (classe dans fractions)

fractions (module)

frame

execution, [1]

objet

frame (attribut tkinter.scrolledtext.ScrolledText)

Frame (classe dans tracemalloc)

FrameSummary (classe dans traceback)

FrameType (dans le module types)

free

variable

free()

freeze utility

freeze_support() (dans le module multiprocessing)

frexp() (dans le module math)

from

import statement, [1]

mot-clé, [1]

yield from expression

from_address() (méthode ctypes._CData)

from_buffer() (méthode ctypes._CData)

from_buffer_copy() (méthode ctypes._CData)

from_bytes() (méthode de la classe int)

from_callable() (méthode de la classe inspect.Signature)

from_decimal() (méthode fractions.Fraction)

from_exception() (méthode de la classe traceback.TracebackException)

from_file() (méthode de la classe zipfile.ZipInfo)

from_float() (méthode decimal.Decimal)

(méthode fractions.Fraction)

from_iterable() (méthode de la classe itertools.chain)

from_list() (méthode de la classe traceback.StackSummary)

from_param() (méthode ctypes._CData)

from_traceback() (méthode de la classe dis.Bytecode)

frombuf() (méthode de la classe tarfile.TarInfo)

frombytes() (méthode array.array)

fromfd() (dans le module socket)

(méthode select.epoll)

(méthode select.kqueue)

fromfile() (méthode array.array)

fromhex() (méthode de la classe bytearray)

(méthode de la classe bytes)

(méthode de la classe float)

fromkeys() (méthode collections.Counter)

(méthode de la classe dict)

fromlist() (méthode array.array)

fromordinal() (méthode de la classe datetime.date)

(méthode de la classe datetime.datetime)

fromshare() (dans le module socket)

fromstring() (dans le module xml.etree.ElementTree)

(méthode array.array)

fromstringlist() (dans le module xml.etree.ElementTree)

fromtarfile() (méthode de la classe tarfile.TarInfo)

fromtimestamp() (méthode de la classe datetime.date)

(méthode de la classe datetime.datetime)

fromunicode() (méthode array.array)

fromutc() (méthode datetime.timezone)

(méthode datetime.tzinfo)

FrozenImporter (classe dans importlib.machinery)

frozenset

objet, [1]

FrozenSet (classe dans typing)

frozenset (classe de base)

fsdecode() (dans le module os)

fsencode() (dans le module os)

fspath() (dans le module os)

fstat() (dans le module os)

fstatvfs() (dans le module os)

fsum() (dans le module math)

fsync() (dans le module os)

FTP

ftplib (standard module)

protocol, [1]

FTP (classe dans ftplib)

ftp_open() (méthode urllib.request.FTPHandler)

FTP_TLS (classe dans ftplib)

FTPHandler (classe dans urllib.request)

ftplib (module)

ftruncate() (dans le module os)

Full

full() (méthode asyncio.Queue)

(méthode multiprocessing.Queue)

(méthode queue.Queue)

full_url (attribut urllib.request.Request)

fullmatch() (dans le module re)

(méthode re.regex)

func (attribut functools.partial)

funcattrs (2to3 fixer)

function

annotations, [1]

anonymous

argument

call, [1], [2]

call, user-defined

definition, [1]

generator, [1]

name, [1]

objet, [1], [2], [3], [4], [5]

user-defined

Function (classe dans symtable)

function__entry (fonction C)

function__return (fonction C)

FunctionTestCase (classe dans unittest)

FunctionType (dans le module types)

functools (module)

funny_files (attribut filecmp.dircmp)

future

statement

future (2to3 fixer)

Future (classe dans asyncio)

(classe dans concurrent.futures)

FutureWarning

fwalk() (dans le module os)

G

G.722

gaierror

gamma() (dans le module math)

gammavariate() (dans le module random)

garbage (dans le module gc)

garbage collection

gather() (dans le module asyncio)

(méthode curses.textpad.Textbox)

gauss() (dans le module random)

gc (module)

gc__done (fonction C)

gc__start (fonction C)

gcd() (dans le module fractions)

(dans le module math)

ge() (dans le module operator)

gen_lib_options() (dans le module distutils.ccompiler)

gen_preprocess_options() (dans le module distutils.ccompiler)

gen_uuid() (dans le module msilib)

generate_help() (méthode distutils.fancy_getopt.FancyGetopt)

generator

expression

function, [1], [2]

iterator, [1]

objet, [1], [2]

Generator (classe dans collections.abc)

(classe dans email.generator)

(classe dans typing)

generator expression

GeneratorExit

exception, [1]

GeneratorType (dans le module types)

generic

special attribute

Generic (classe dans typing)

generic_visit() (méthode ast.NodeVisitor)

genops() (dans le module pickletools)

gestionnaire de contexte

gestionnaire de contexte asynchrone

get() (dans le module webbrowser)

(méthode asyncio.Queue)

(méthode configparser.ConfigParser)

(méthode dict)

(méthode email.message.EmailMessage)

(méthode email.message.Message)

(méthode mailbox.Mailbox)

(méthode multiprocessing.pool.AsyncResult)

(méthode multiprocessing.Queue)

(méthode multiprocessing.SimpleQueue)

(méthode ossaudiodev.oss_mixer_device)

(méthode queue.Queue)

(méthode tkinter.ttk.Combobox)

(méthode types.MappingProxyType)

(méthode xml.etree.ElementTree.Element)

GET_AITER (opcode)

get_all() (méthode email.message.EmailMessage)

(méthode email.message.Message)

(méthode wsgiref.headers.Headers)

get_all_breaks() (méthode bdb.Bdb)

get_all_start_methods() (dans le module multiprocessing)

GET_ANEXT (opcode)

get_app() (méthode wsgiref.simple_server.WSGIServer)

get_archive_formats() (dans le module shutil)

get_asyncgen_hooks() (dans le module sys)

GET_AWAITABLE (opcode)

get_begidx() (dans le module readline)

get_blocking() (dans le module os)

get_body() (méthode email.message.EmailMessage)

get_body_encoding() (méthode email.charset.Charset)

get_boundary() (méthode email.message.EmailMessage)

(méthode email.message.Message)

get_bpbynumber() (méthode bdb.Bdb)

get_break() (méthode bdb.Bdb)

get_breaks() (méthode bdb.Bdb)

get_buffer() (méthode xdrlib.Packer)

(méthode xdrlib.Unpacker)

get_bytes() (méthode mailbox.Mailbox)

get_ca_certs() (méthode ssl.SSLContext)

get_cache_token() (dans le module abc)

get_channel_binding() (méthode ssl.SSLSocket)

get_charset() (méthode email.message.Message)

get_charsets() (méthode email.message.EmailMessage)

(méthode email.message.Message)

get_children() (méthode symtable.SymbolTable)

(méthode tkinter.ttk.Treeview)

get_ciphers() (méthode ssl.SSLContext)

get_clock_info() (dans le module time)

get_close_matches() (dans le module difflib)

get_code() (méthode importlib.abc.InspectLoader)

(méthode importlib.abc.SourceLoader)

(méthode importlib.machinery.ExtensionFileLoader)

(méthode importlib.machinery.SourcelessFileLoader)

(méthode zipimport.zipimporter)

get_completer() (dans le module readline)

get_completer_delims() (dans le module readline)

get_completion_type() (dans le module readline)

get_config_h_filename() (dans le module distutils.sysconfig)

(dans le module sysconfig)

get_config_var() (dans le module distutils.sysconfig)

(dans le module sysconfig)

get_config_vars() (dans le module distutils.sysconfig)

(dans le module sysconfig)

get_content() (dans le module email.contentmanager)

(méthode email.contentmanager.ContentManager)

(méthode email.message.EmailMessage)

get_content_charset() (méthode email.message.EmailMessage)

(méthode email.message.Message)

get_content_disposition() (méthode email.message.EmailMessage)

(méthode email.message.Message)

get_content_maintype() (méthode email.message.EmailMessage)

(méthode email.message.Message)

get_content_subtype() (méthode email.message.EmailMessage)

(méthode email.message.Message)

get_content_type() (méthode email.message.EmailMessage)

(méthode email.message.Message)

get_context() (dans le module multiprocessing)

get_coroutine_wrapper() (dans le module sys)

get_count() (dans le module gc)

get_current_history_length() (dans le module readline)

get_data() (dans le module pkgutil)

(méthode importlib.abc.FileLoader)

(méthode importlib.abc.ResourceLoader)

(méthode zipimport.zipimporter)

get_date() (méthode mailbox.MaildirMessage)

get_debug() (dans le module gc)

(méthode asyncio.AbstractEventLoop)

get_default() (méthode argparse.ArgumentParser)

get_default_compiler() (dans le module distutils.ccompiler)

get_default_domain() (dans le module nis)

get_default_type() (méthode email.message.EmailMessage)

(méthode email.message.Message)

get_default_verify_paths() (dans le module ssl)

get_dialect() (dans le module csv)

get_docstring() (dans le module ast)

get_doctest() (méthode doctest.DocTestParser)

get_endidx() (dans le module readline)

get_environ() (méthode wsgiref.simple_server.WSGIRequestHandler)

get_errno() (dans le module ctypes)

get_event_loop() (dans le module asyncio)

(méthode asyncio.AbstractEventLoopPolicy)

get_event_loop_policy() (dans le module asyncio)

get_examples() (méthode doctest.DocTestParser)

get_exception_handler() (méthode asyncio.AbstractEventLoop)

get_exec_path() (dans le module os)

get_extra_info() (méthode asyncio.BaseTransport)

(méthode asyncio.StreamWriter)

get_field() (méthode string.Formatter)

get_file() (méthode mailbox.Babyl)

(méthode mailbox.Mailbox)

(méthode mailbox.Maildir)

(méthode mailbox.mbox)

(méthode mailbox.MH)

(méthode mailbox.MMDF)

get_file_breaks() (méthode bdb.Bdb)

get_filename() (méthode email.message.EmailMessage)

(méthode email.message.Message)

(méthode importlib.abc.ExecutionLoader)

(méthode importlib.abc.FileLoader)

(méthode importlib.machinery.ExtensionFileLoader)

(méthode zipimport.zipimporter)

get_flags() (méthode mailbox.MaildirMessage)

(méthode mailbox.mboxMessage)

(méthode mailbox.MMDFMessage)

get_folder() (méthode mailbox.Maildir)

(méthode mailbox.MH)

get_frees() (méthode symtable.Function)

get_from() (méthode mailbox.mboxMessage)

(méthode mailbox.MMDFMessage)

get_full_url() (méthode urllib.request.Request)

get_globals() (méthode symtable.Function)

get_grouped_opcodes() (méthode difflib.SequenceMatcher)

get_handle_inheritable() (dans le module os)

get_header() (méthode urllib.request.Request)

get_history_item() (dans le module readline)

get_history_length() (dans le module readline)

get_id() (méthode symtable.SymbolTable)

get_ident() (dans le module _thread)

(dans le module threading)

get_identifiers() (méthode symtable.SymbolTable)

get_importer() (dans le module pkgutil)

get_info() (méthode mailbox.MaildirMessage)

get_inheritable() (dans le module os)

(méthode socket.socket)

get_instructions() (dans le module dis)

get_interpreter() (dans le module zipapp)

GET_ITER (opcode)

get_key() (méthode selectors.BaseSelector)

get_labels() (méthode mailbox.Babyl)

(méthode mailbox.BabylMessage)

get_last_error() (dans le module ctypes)

get_line_buffer() (dans le module readline)

get_lineno() (méthode symtable.SymbolTable)

get_loader() (dans le module pkgutil)

get_locals() (méthode symtable.Function)

get_logger() (dans le module multiprocessing)

get_magic() (dans le module imp)

get_makefile_filename() (dans le module distutils.sysconfig)

(dans le module sysconfig)

get_map() (méthode selectors.BaseSelector)

get_matching_blocks() (méthode difflib.SequenceMatcher)

get_message() (méthode mailbox.Mailbox)

get_method() (méthode urllib.request.Request)

get_methods() (méthode symtable.Class)

get_mixed_type_key() (dans le module ipaddress)

get_name() (méthode symtable.Symbol)

(méthode symtable.SymbolTable)

get_namespace() (méthode symtable.Symbol)

get_namespaces() (méthode symtable.Symbol)

get_nonstandard_attr() (méthode http.cookiejar.Cookie)

get_nowait() (méthode asyncio.Queue)

(méthode multiprocessing.Queue)

(méthode queue.Queue)

get_object_traceback() (dans le module tracemalloc)

get_objects() (dans le module gc)

get_opcodes() (méthode difflib.SequenceMatcher)

get_option() (méthode optparse.OptionParser)

get_option_group() (méthode optparse.OptionParser)

get_option_order() (méthode distutils.fancy_getopt.FancyGetopt)

get_osfhandle() (dans le module msvcrt)

get_output_charset() (méthode email.charset.Charset)

get_param() (méthode email.message.Message)

get_parameters() (méthode symtable.Function)

get_params() (méthode email.message.Message)

get_path() (dans le module sysconfig)

get_path_names() (dans le module sysconfig)

get_paths() (dans le module sysconfig)

get_payload() (méthode email.message.Message)

get_pid() (méthode asyncio.BaseSubprocessTransport)

get_pipe_transport() (méthode asyncio.BaseSubprocessTransport)

get_platform() (dans le module distutils.util)

(dans le module sysconfig)

get_poly() (dans le module turtle)

get_position() (méthode xdrlib.Unpacker)

get_protocol() (méthode asyncio.BaseTransport)

get_python_inc() (dans le module distutils.sysconfig)

get_python_lib() (dans le module distutils.sysconfig)

get_python_version() (dans le module sysconfig)

get_recsrc() (méthode ossaudiodev.oss_mixer_device)

get_referents() (dans le module gc)

get_referrers() (dans le module gc)

get_request() (méthode socketserver.BaseServer)

get_returncode() (méthode asyncio.BaseSubprocessTransport)

get_scheme() (méthode wsgiref.handlers.BaseHandler)

get_scheme_names() (dans le module sysconfig)

get_sequences() (méthode mailbox.MH)

(méthode mailbox.MHMessage)

get_server() (méthode multiprocessing.managers.BaseManager)

get_server_certificate() (dans le module ssl)

get_shapepoly() (dans le module turtle)

get_socket() (méthode telnetlib.Telnet)

get_source() (méthode importlib.abc.InspectLoader)

(méthode importlib.abc.SourceLoader)

(méthode importlib.machinery.ExtensionFileLoader)

(méthode importlib.machinery.SourcelessFileLoader)

(méthode zipimport.zipimporter)

get_special_folder_path() (fonction de base)

get_stack() (méthode asyncio.Task)

(méthode bdb.Bdb)

get_start_method() (dans le module multiprocessing)

get_starttag_text() (méthode html.parser.HTMLParser)

get_stats() (dans le module gc)

get_stderr() (méthode wsgiref.handlers.BaseHandler)

(méthode wsgiref.simple_server.WSGIRequestHandler)

get_stdin() (méthode wsgiref.handlers.BaseHandler)

get_string() (méthode mailbox.Mailbox)

get_subdir() (méthode mailbox.MaildirMessage)

get_suffixes() (dans le module imp)

get_symbols() (méthode symtable.SymbolTable)

get_tag() (dans le module imp)

get_task_factory() (méthode asyncio.AbstractEventLoop)

get_terminal_size() (dans le module os)

(dans le module shutil)

get_terminator() (méthode asynchat.async_chat)

get_threshold() (dans le module gc)

get_token() (méthode shlex.shlex)

get_traceback_limit() (dans le module tracemalloc)

get_traced_memory() (dans le module tracemalloc)

get_tracemalloc_memory() (dans le module tracemalloc)

get_type() (méthode symtable.SymbolTable)

get_type_hints() (dans le module typing)

get_unixfrom() (méthode email.message.EmailMessage)

(méthode email.message.Message)

get_unpack_formats() (dans le module shutil)

get_usage() (méthode optparse.OptionParser)

get_value() (méthode string.Formatter)

get_version() (méthode optparse.OptionParser)

get_visible() (méthode mailbox.BabylMessage)

get_wch() (méthode curses.window)

get_write_buffer_limits() (méthode asyncio.WriteTransport)

get_write_buffer_size() (méthode asyncio.WriteTransport)

GET_YIELD_FROM_ITER (opcode)

getacl() (méthode imaplib.IMAP4)

getaddresses() (dans le module email.utils)

getaddrinfo() (dans le module socket)

(méthode asyncio.AbstractEventLoop)

getallocatedblocks() (dans le module sys)

getannotation() (méthode imaplib.IMAP4)

getargspec() (dans le module inspect)

getargvalues() (dans le module inspect)

getatime() (dans le module os.path)

getattr() (fonction de base)

getattr_static() (dans le module inspect)

getAttribute() (méthode xml.dom.Element)

getAttributeNode() (méthode xml.dom.Element)

getAttributeNodeNS() (méthode xml.dom.Element)

getAttributeNS() (méthode xml.dom.Element)

GetBase() (méthode xml.parsers.expat.xmlparser)

getbegyx() (méthode curses.window)

getbkgd() (méthode curses.window)

getboolean() (méthode configparser.ConfigParser)

getbuffer() (méthode io.BytesIO)

getByteStream() (méthode xml.sax.xmlreader.InputSource)

getcallargs() (dans le module inspect)

getcanvas() (dans le module turtle)

getcapabilities() (méthode nntplib.NNTP)

getcaps() (dans le module mailcap)

getch() (dans le module msvcrt)

(méthode curses.window)

getCharacterStream() (méthode xml.sax.xmlreader.InputSource)

getche() (dans le module msvcrt)

getcheckinterval() (dans le module sys)

getChild() (méthode logging.Logger)

getchildren() (méthode xml.etree.ElementTree.Element)

getclasstree() (dans le module inspect)

getclosurevars() (dans le module inspect)

GetColumnInfo() (méthode msilib.View)

getColumnNumber() (méthode xml.sax.xmlreader.Locator)

getcomments() (dans le module inspect)

getcompname() (méthode aifc.aifc)

(méthode sunau.AU_read)

(méthode wave.Wave_read)

getcomptype() (méthode aifc.aifc)

(méthode sunau.AU_read)

(méthode wave.Wave_read)

getContentHandler() (méthode xml.sax.xmlreader.XMLReader)

getcontext() (dans le module decimal)

getcoroutinelocals() (dans le module inspect)

getcoroutinestate() (dans le module inspect)

getctime() (dans le module os.path)

getcwd() (dans le module os)

getcwdb() (dans le module os)

getcwdu (2to3 fixer)

getdecoder() (dans le module codecs)

getdefaultencoding() (dans le module sys)

getdefaultlocale() (dans le module locale)

getdefaulttimeout() (dans le module socket)

getdlopenflags() (dans le module sys)

getdoc() (dans le module inspect)

getDOMImplementation() (dans le module xml.dom)

getDTDHandler() (méthode xml.sax.xmlreader.XMLReader)

getEffectiveLevel() (méthode logging.Logger)

getegid() (dans le module os)

getElementsByTagName() (méthode xml.dom.Document)

(méthode xml.dom.Element)

getElementsByTagNameNS() (méthode xml.dom.Document)

(méthode xml.dom.Element)

getencoder() (dans le module codecs)

getEncoding() (méthode xml.sax.xmlreader.InputSource)

getEntityResolver() (méthode xml.sax.xmlreader.XMLReader)

getenv() (dans le module os)

getenvb() (dans le module os)

getErrorHandler() (méthode xml.sax.xmlreader.XMLReader)

geteuid() (dans le module os)

getEvent() (méthode xml.dom.pulldom.DOMEventStream)

getEventCategory() (méthode logging.handlers.NTEventLogHandler)

getEventType() (méthode logging.handlers.NTEventLogHandler)

getException() (méthode xml.sax.SAXException)

getFeature() (méthode xml.sax.xmlreader.XMLReader)

GetFieldCount() (méthode msilib.Record)

getfile() (dans le module inspect)

getfilesystemencodeerrors() (dans le module sys)

getfilesystemencoding() (dans le module sys)

getfirst() (méthode cgi.FieldStorage)

getfloat() (méthode configparser.ConfigParser)

getfmts() (méthode ossaudiodev.oss_audio_device)

getfqdn() (dans le module socket)

getframeinfo() (dans le module inspect)

getframerate() (méthode aifc.aifc)

(méthode sunau.AU_read)

(méthode wave.Wave_read)

getfullargspec() (dans le module inspect)

getgeneratorlocals() (dans le module inspect)

getgeneratorstate() (dans le module inspect)

getgid() (dans le module os)

getgrall() (dans le module grp)

getgrgid() (dans le module grp)

getgrnam() (dans le module grp)

getgrouplist() (dans le module os)

getgroups() (dans le module os)

getheader() (méthode http.client.HTTPResponse)

getheaders() (méthode http.client.HTTPResponse)

gethostbyaddr() (dans le module socket)

(in module socket)

gethostbyname() (dans le module socket)

gethostbyname_ex() (dans le module socket)

gethostname() (dans le module socket)

(in module socket)

getincrementaldecoder() (dans le module codecs)

getincrementalencoder() (dans le module codecs)

getinfo() (méthode zipfile.ZipFile)

getinnerframes() (dans le module inspect)

GetInputContext() (méthode xml.parsers.expat.xmlparser)

getint() (méthode configparser.ConfigParser)

GetInteger() (méthode msilib.Record)

getitem() (dans le module operator)

getiterator() (méthode xml.etree.ElementTree.Element)

(méthode xml.etree.ElementTree.ElementTree)

getitimer() (dans le module signal)

getkey() (méthode curses.window)

GetLastError() (dans le module ctypes)

getLength() (méthode xml.sax.xmlreader.Attributes)

getLevelName() (dans le module logging)

getline() (dans le module linecache)

getLineNumber() (méthode xml.sax.xmlreader.Locator)

getlist() (méthode cgi.FieldStorage)

getloadavg() (dans le module os)

getlocale() (dans le module locale)

getLogger() (dans le module logging)

getLoggerClass() (dans le module logging)

getlogin() (dans le module os)

getLogRecordFactory() (dans le module logging)

getmark() (méthode aifc.aifc)

(méthode sunau.AU_read)

(méthode wave.Wave_read)

getmarkers() (méthode aifc.aifc)

(méthode sunau.AU_read)

(méthode wave.Wave_read)

getmaxyx() (méthode curses.window)

getmember() (méthode tarfile.TarFile)

getmembers() (dans le module inspect)

(méthode tarfile.TarFile)

getMessage() (méthode logging.LogRecord)

(méthode xml.sax.SAXException)

getMessageID() (méthode logging.handlers.NTEventLogHandler)

getmodule() (dans le module inspect)

getmodulename() (dans le module inspect)

getmouse() (dans le module curses)

getmro() (dans le module inspect)

getmtime() (dans le module os.path)

getname() (méthode chunk.Chunk)

getName() (méthode threading.Thread)

getNameByQName() (méthode xml.sax.xmlreader.AttributesNS)

getnameinfo() (dans le module socket)

(méthode asyncio.AbstractEventLoop)

getnames() (méthode tarfile.TarFile)

getNames() (méthode xml.sax.xmlreader.Attributes)

getnchannels() (méthode aifc.aifc)

(méthode sunau.AU_read)

(méthode wave.Wave_read)

getnframes() (méthode aifc.aifc)

(méthode sunau.AU_read)

(méthode wave.Wave_read)

getnode

getnode() (dans le module uuid)

getopt (module)

getopt() (dans le module getopt)

(méthode distutils.fancy_getopt.FancyGetopt)

GetoptError

getouterframes() (dans le module inspect)

getoutput() (dans le module subprocess)

getpagesize() (dans le module resource)

getparams() (méthode aifc.aifc)

(méthode sunau.AU_read)

(méthode wave.Wave_read)

getparyx() (méthode curses.window)

getpass (module)

getpass() (dans le module getpass)

GetPassWarning

getpeercert() (méthode ssl.SSLSocket)

getpeername() (méthode socket.socket)

getpen() (dans le module turtle)

getpgid() (dans le module os)

getpgrp() (dans le module os)

getpid() (dans le module os)

getpos() (méthode html.parser.HTMLParser)

getppid() (dans le module os)

getpreferredencoding() (dans le module locale)

getpriority() (dans le module os)

getprofile() (dans le module sys)

GetProperty() (méthode msilib.SummaryInformation)

getProperty() (méthode xml.sax.xmlreader.XMLReader)

GetPropertyCount() (méthode msilib.SummaryInformation)

getprotobyname() (dans le module socket)

getproxies() (dans le module urllib.request)

getPublicId() (méthode xml.sax.xmlreader.InputSource)

(méthode xml.sax.xmlreader.Locator)

getpwall() (dans le module pwd)

getpwnam() (dans le module pwd)

getpwuid() (dans le module pwd)

getQNameByName() (méthode xml.sax.xmlreader.AttributesNS)

getQNames() (méthode xml.sax.xmlreader.AttributesNS)

getquota() (méthode imaplib.IMAP4)

getquotaroot() (méthode imaplib.IMAP4)

getrandbits() (dans le module random)

getrandom() (dans le module os)

getreader() (dans le module codecs)

getrecursionlimit() (dans le module sys)

getrefcount() (dans le module sys)

getresgid() (dans le module os)

getresponse() (méthode http.client.HTTPConnection)

getresuid() (dans le module os)

getrlimit() (dans le module resource)

getroot() (méthode xml.etree.ElementTree.ElementTree)

getrusage() (dans le module resource)

getsample() (dans le module audioop)

getsampwidth() (méthode aifc.aifc)

(méthode sunau.AU_read)

(méthode wave.Wave_read)

getscreen() (dans le module turtle)

getservbyname() (dans le module socket)

getservbyport() (dans le module socket)

GetSetDescriptorType (dans le module types)

getshapes() (dans le module turtle)

getsid() (dans le module os)

getsignal() (dans le module signal)

getsitepackages() (dans le module site)

getsize() (dans le module os.path)

(méthode chunk.Chunk)

getsizeof() (dans le module sys)

getsockname() (méthode socket.socket)

getsockopt() (méthode socket.socket)

getsource() (dans le module inspect)

getsourcefile() (dans le module inspect)

getsourcelines() (dans le module inspect)

getspall() (dans le module spwd)

getspnam() (dans le module spwd)

getstate() (dans le module random)

(méthode codecs.IncrementalDecoder)

(méthode codecs.IncrementalEncoder)

getstatusoutput() (dans le module subprocess)

getstr() (méthode curses.window)

GetString() (méthode msilib.Record)

getSubject() (méthode logging.handlers.SMTPHandler)

GetSummaryInformation() (méthode msilib.Database)

getswitchinterval() (dans le module sys)

getSystemId() (méthode xml.sax.xmlreader.InputSource)

(méthode xml.sax.xmlreader.Locator)

getsyx() (dans le module curses)

gettarinfo() (méthode tarfile.TarFile)

gettempdir() (dans le module tempfile)

gettempdirb() (dans le module tempfile)

gettempprefix() (dans le module tempfile)

gettempprefixb() (dans le module tempfile)

getTestCaseNames() (méthode unittest.TestLoader)

gettext (module)

gettext() (dans le module gettext)

(dans le module locale)

(méthode gettext.GNUTranslations)

(méthode gettext.NullTranslations)

gettimeout() (méthode socket.socket)

gettrace() (dans le module sys)

getturtle() (dans le module turtle)

getType() (méthode xml.sax.xmlreader.Attributes)

getuid() (dans le module os)

geturl() (méthode urllib.parse.urllib.parse.SplitResult)

getuser() (dans le module getpass)

getuserbase() (dans le module site)

getusersitepackages() (dans le module site)

getvalue() (méthode io.BytesIO)

(méthode io.StringIO)

getValue() (méthode xml.sax.xmlreader.Attributes)

getValueByQName() (méthode xml.sax.xmlreader.AttributesNS)

getwch() (dans le module msvcrt)

getwche() (dans le module msvcrt)

getweakrefcount() (dans le module weakref)

getweakrefs() (dans le module weakref)

getwelcome() (méthode ftplib.FTP)

(méthode nntplib.NNTP)

(méthode poplib.POP3)

getwin() (dans le module curses)

getwindowsversion() (dans le module sys)

getwriter() (dans le module codecs)

getxattr() (dans le module os)

getyx() (méthode curses.window)

générateur

générateur asynchrone

gid (attribut tarfile.TarInfo)

GIL

glob

module

glob (module)

glob() (dans le module glob)

(méthode msilib.Directory)

(méthode pathlib.Path)

global

état, [1]

name binding

namespace

global interpreter lock

globals() (fonction de base)

globs (attribut doctest.DocTest)

gmtime() (dans le module time)

gname (attribut tarfile.TarInfo)

GNOME

GNU_FORMAT (dans le module tarfile)

gnu_getopt() (dans le module getopt)

GNUTranslations (classe dans gettext)

got (attribut doctest.DocTestFailure)

goto() (dans le module turtle)

grammar

Graphical User Interface

GREATER (dans le module token)

GREATEREQUAL (dans le module token)

Greenwich Mean Time

GRND_NONBLOCK (dans le module os)

GRND_RANDOM (dans le module os)

Group (classe dans email.headerregistry)

group() (méthode nntplib.NNTP)

(méthode pathlib.Path)

(méthode re.match)

groupby() (dans le module itertools)

groupdict() (méthode re.match)

groupindex (attribut re.regex)

grouping

groups (attribut email.headerregistry.AddressHeader)

(attribut re.regex)

groups() (méthode re.match)

grp (module)

gt() (dans le module operator)

guess_all_extensions() (dans le module mimetypes)

(méthode mimetypes.MimeTypes)

guess_extension() (dans le module mimetypes)

(méthode mimetypes.MimeTypes)

guess_scheme() (dans le module wsgiref.util)

guess_type() (dans le module mimetypes)

(méthode mimetypes.MimeTypes)

GUI

gzip (module)

GzipFile (classe dans gzip)

H

hachable

halfdelay() (dans le module curses)

Handle (classe dans asyncio)

handle an exception

handle() (méthode http.server.BaseHTTPRequestHandler)

(méthode logging.Handler)

(méthode logging.handlers.QueueListener)

(méthode logging.Logger)

(méthode logging.NullHandler)

(méthode socketserver.BaseRequestHandler)

(méthode wsgiref.simple_server.WSGIRequestHandler)

handle_accept() (méthode asyncore.dispatcher)

handle_accepted() (méthode asyncore.dispatcher)

handle_charref() (méthode html.parser.HTMLParser)

handle_close() (méthode asyncore.dispatcher)

handle_comment() (méthode html.parser.HTMLParser)

handle_connect() (méthode asyncore.dispatcher)

handle_data() (méthode html.parser.HTMLParser)

handle_decl() (méthode html.parser.HTMLParser)

handle_defect() (méthode email.policy.Policy)

handle_endtag() (méthode html.parser.HTMLParser)

handle_entityref() (méthode html.parser.HTMLParser)

handle_error() (méthode asyncore.dispatcher)

(méthode socketserver.BaseServer)

handle_expect_100() (méthode http.server.BaseHTTPRequestHandler)

handle_expt() (méthode asyncore.dispatcher)

handle_one_request() (méthode http.server.BaseHTTPRequestHandler)

handle_pi() (méthode html.parser.HTMLParser)

handle_read() (méthode asyncore.dispatcher)

handle_request() (méthode socketserver.BaseServer)

(méthode xmlrpc.server.CGIXMLRPCRequestHandler)

handle_startendtag() (méthode html.parser.HTMLParser)

handle_starttag() (méthode html.parser.HTMLParser)

handle_timeout() (méthode socketserver.BaseServer)

handle_write() (méthode asyncore.dispatcher)

handleError() (méthode logging.Handler)

(méthode logging.handlers.SocketHandler)

handler

exception

Handler (classe dans logging)

handler() (dans le module cgitb)

harmonic_mean() (dans le module statistics)

HAS_ALPN (dans le module ssl)

has_children() (méthode symtable.SymbolTable)

has_colors() (dans le module curses)

HAS_ECDH (dans le module ssl)

has_exec() (méthode symtable.SymbolTable)

has_extn() (méthode smtplib.SMTP)

has_function() (méthode distutils.ccompiler.CCompiler)

has_header() (méthode csv.Sniffer)

(méthode urllib.request.Request)

has_ic() (dans le module curses)

has_il() (dans le module curses)

has_ipv6 (dans le module socket)

has_key (2to3 fixer)

has_key() (dans le module curses)

has_location (attribut importlib.machinery.ModuleSpec)

has_nonstandard_attr() (méthode http.cookiejar.Cookie)

HAS_NPN (dans le module ssl)

has_option() (méthode configparser.ConfigParser)

(méthode optparse.OptionParser)

has_section() (méthode configparser.ConfigParser)

HAS_SNI (dans le module ssl)

has_ticket (attribut ssl.SSLSession)

HAS_TLSv1_3 (dans le module ssl)

hasattr() (fonction de base)

hasAttribute() (méthode xml.dom.Element)

hasAttributeNS() (méthode xml.dom.Element)

hasAttributes() (méthode xml.dom.Node)

hasChildNodes() (méthode xml.dom.Node)

hascompare (dans le module dis)

hasconst (dans le module dis)

hasFeature() (méthode xml.dom.DOMImplementation)

hasfree (dans le module dis)

hash

fonction de base, [1], [2], [3]

hash character

hash() (fonction de base)

hash.block_size (dans le module hashlib)

hash.digest_size (dans le module hashlib)

hash_info (dans le module sys)

hashable

Hashable (classe dans collections.abc)

(classe dans typing)

hasHandlers() (méthode logging.Logger)

hashlib (module)

hasjabs (dans le module dis)

hasjrel (dans le module dis)

haslocal (dans le module dis)

hasname (dans le module dis)

HAVE_ARGUMENT (opcode)

HAVE_THREADS (dans le module decimal)

HCI_DATA_DIR (dans le module socket)

HCI_FILTER (dans le module socket)

HCI_TIME_STAMP (dans le module socket)

head() (méthode nntplib.NNTP)

Header (classe dans email.header)

header_encode() (méthode email.charset.Charset)

header_encode_lines() (méthode email.charset.Charset)

header_encoding (attribut email.charset.Charset)

header_factory (attribut email.policy.EmailPolicy)

header_fetch_parse() (méthode email.policy.Compat32)

(méthode email.policy.EmailPolicy)

(méthode email.policy.Policy)

header_items() (méthode urllib.request.Request)

header_max_count() (méthode email.policy.EmailPolicy)

(méthode email.policy.Policy)

header_offset (attribut zipfile.ZipInfo)

header_source_parse() (méthode email.policy.Compat32)

(méthode email.policy.EmailPolicy)

(méthode email.policy.Policy)

header_store_parse() (méthode email.policy.Compat32)

(méthode email.policy.EmailPolicy)

(méthode email.policy.Policy)

HeaderError

HeaderParseError

HeaderParser (classe dans email.parser)

HeaderRegistry (classe dans email.headerregistry)

headers

MIME, [1]

headers (attribut http.server.BaseHTTPRequestHandler)

(attribut urllib.error.HTTPError)

(attribut xmlrpc.client.ProtocolError)

Headers (classe dans wsgiref.headers)

heading() (dans le module turtle)

(méthode tkinter.ttk.Treeview)

heapify() (dans le module heapq)

heapmin() (dans le module msvcrt)

heappop() (dans le module heapq)

heappush() (dans le module heapq)

heappushpop() (dans le module heapq)

heapq (module)

heapreplace() (dans le module heapq)

helo() (méthode smtplib.SMTP)

help

fonction de base

online

help (attribut optparse.Option)

(pdb command)

help() (fonction de base)

(méthode nntplib.NNTP)

herror

hex (attribut uuid.UUID)

hex() (fonction de base)

(méthode bytearray)

(méthode bytes)

(méthode float)

(méthode memoryview)

hexadecimal

literals

hexadecimal literal

hexbin() (dans le module binhex)

hexdigest() (méthode hashlib.hash)

(méthode hashlib.shake)

(méthode hmac.HMAC)

hexdigits (dans le module string)

hexlify() (dans le module binascii)

hexversion (dans le module sys)

hidden() (méthode curses.panel.Panel)

hide() (méthode curses.panel.Panel)

(méthode tkinter.ttk.Notebook)

hide_cookie2 (attribut http.cookiejar.CookiePolicy)

hideturtle() (dans le module turtle)

hierarchy

type

HierarchyRequestErr

HIGHEST_PROTOCOL (dans le module pickle)

HKEY_CLASSES_ROOT (dans le module winreg)

HKEY_CURRENT_CONFIG (dans le module winreg)

HKEY_CURRENT_USER (dans le module winreg)

HKEY_DYN_DATA (dans le module winreg)

HKEY_LOCAL_MACHINE (dans le module winreg)

HKEY_PERFORMANCE_DATA (dans le module winreg)

HKEY_USERS (dans le module winreg)

hline() (méthode curses.window)

HList (classe dans tkinter.tix)

hls_to_rgb() (dans le module colorsys)

hmac (module)

HOME, [1], [2], [3], [4]

home() (dans le module turtle)

(méthode de la classe pathlib.Path)

HOMEDRIVE, [1]

HOMEPATH, [1]

hook_compressed() (dans le module fileinput)

hook_encoded() (dans le module fileinput)

hooks

import

meta

path

host (attribut urllib.request.Request)

hostmask (attribut ipaddress.IPv4Network)

(attribut ipaddress.IPv6Network)

hosts (attribut netrc.netrc)

hosts() (méthode ipaddress.IPv4Network)

(méthode ipaddress.IPv6Network)

hour (attribut datetime.datetime)

(attribut datetime.time)

HRESULT (classe dans ctypes)

hStdError (attribut subprocess.STARTUPINFO)

hStdInput (attribut subprocess.STARTUPINFO)

hStdOutput (attribut subprocess.STARTUPINFO)

hsv_to_rgb() (dans le module colorsys)

ht() (dans le module turtle)

HTML, [1]

html (module)

html.entities (module)

html.parser (module)

html5 (dans le module html.entities)

HTMLCalendar (classe dans calendar)

HtmlDiff (classe dans difflib)

HTMLParser (classe dans html.parser)

htonl() (dans le module socket)

htons() (dans le module socket)

HTTP

http (standard module)

http.client (standard module)

protocol, [1], [2], [3], [4], [5]

HTTP (dans le module email.policy)

http (module)

http.client (module)

http.cookiejar (module)

http.cookies (module)

http.server (module)

http_error_301() (méthode urllib.request.HTTPRedirectHandler)

http_error_302() (méthode urllib.request.HTTPRedirectHandler)

http_error_303() (méthode urllib.request.HTTPRedirectHandler)

http_error_307() (méthode urllib.request.HTTPRedirectHandler)

http_error_401() (méthode urllib.request.HTTPBasicAuthHandler)

(méthode urllib.request.HTTPDigestAuthHandler)

http_error_407() (méthode urllib.request.ProxyBasicAuthHandler)

(méthode urllib.request.ProxyDigestAuthHandler)

http_error_auth_reqed() (méthode urllib.request.AbstractBasicAuthHandler)

(méthode urllib.request.AbstractDigestAuthHandler)

http_error_default() (méthode urllib.request.BaseHandler)

http_error_nnn() (méthode urllib.request.BaseHandler)

http_open() (méthode urllib.request.HTTPHandler)

HTTP_PORT (dans le module http.client)

http_proxy, [1], [2]

http_response() (méthode urllib.request.HTTPErrorProcessor)

http_version (attribut wsgiref.handlers.BaseHandler)

HTTPBasicAuthHandler (classe dans urllib.request)

HTTPConnection (classe dans http.client)

HTTPCookieProcessor (classe dans urllib.request)

httpd

HTTPDefaultErrorHandler (classe dans urllib.request)

HTTPDigestAuthHandler (classe dans urllib.request)

HTTPError

HTTPErrorProcessor (classe dans urllib.request)

HTTPException

HTTPHandler (classe dans logging.handlers)

(classe dans urllib.request)

HTTPPasswordMgr (classe dans urllib.request)

HTTPPasswordMgrWithDefaultRealm (classe dans urllib.request)

HTTPPasswordMgrWithPriorAuth (classe dans urllib.request)

HTTPRedirectHandler (classe dans urllib.request)

HTTPResponse (classe dans http.client)

https_open() (méthode urllib.request.HTTPSHandler)

HTTPS_PORT (dans le module http.client)

https_response() (méthode urllib.request.HTTPErrorProcessor)

HTTPSConnection (classe dans http.client)

HTTPServer (classe dans http.server)

HTTPSHandler (classe dans urllib.request)

HTTPStatus (classe dans http)

hypot() (dans le module math)

I

I (dans le module re)

I/O control

buffering, [1]

POSIX

tty

UNIX

iadd() (dans le module operator)

iand() (dans le module operator)

iconcat() (dans le module operator)

id

fonction de base

id (attribut ssl.SSLSession)

id() (fonction de base)

(méthode unittest.TestCase)

idcok() (méthode curses.window)

ident (attribut select.kevent)

(attribut threading.Thread)

identchars (attribut cmd.Cmd)

identifier, [1]

identify() (méthode tkinter.ttk.Notebook)

(méthode tkinter.ttk.Treeview)

(méthode tkinter.ttk.Widget)

identify_column() (méthode tkinter.ttk.Treeview)

identify_element() (méthode tkinter.ttk.Treeview)

identify_region() (méthode tkinter.ttk.Treeview)

identify_row() (méthode tkinter.ttk.Treeview)

identity

test

identity of an object

idioms (2to3 fixer)

IDLE, [1]

IDLE*STARTUP

IDLESTARTUP

idlok() (méthode curses.window)

IEEE-754

if

conditional expression

état, [1]

in comprehensions

if_indextoname() (dans le module socket)

if_nameindex() (dans le module socket)

if_nametoindex() (dans le module socket)

ifloordiv() (dans le module operator)

iglob() (dans le module glob)

ignorableWhitespace() (méthode xml.sax.handler.ContentHandler)

ignore (pdb command)

ignore_errors() (dans le module codecs)

IGNORE_EXCEPTION_DETAIL (dans le module doctest)

ignore_patterns() (dans le module shutil)

IGNORECASE (dans le module re)

ihave() (méthode nntplib.NNTP)

IISCGIHandler (classe dans wsgiref.handlers)

ilshift() (dans le module operator)

imag (attribut numbers.Complex)

imaginary literal

imap() (méthode multiprocessing.pool.Pool)

IMAP4

protocol

IMAP4 (classe dans imaplib)

IMAP4.abort

IMAP4.error

IMAP4.readonly

IMAP4_SSL

protocol

IMAP4_SSL (classe dans imaplib)

IMAP4_stream

protocol

IMAP4_stream (classe dans imaplib)

imap_unordered() (méthode multiprocessing.pool.Pool)

imaplib (module)

imatmul() (dans le module operator)

imghdr (module)

immedok() (méthode curses.window)

immuable

immutable

data type

object, [1]

objet

sequence types

immutable object

immutable sequence

objet

immutable types

subclassing

imod() (dans le module operator)

imp

module

imp (module)

ImpImporter (classe dans pkgutil)

implementation (dans le module sys)

ImpLoader (classe dans pkgutil)

import

état, [1], [2], [3], [4]

hooks

import (2to3 fixer)

import hooks

import machinery

import_fresh_module() (dans le module test.support)

IMPORT_FROM (opcode)

import_module() (dans le module importlib)

(dans le module test.support)

IMPORT_NAME (opcode)

IMPORT_STAR (opcode)

importateur

importer

ImportError

exception

importlib (module)

importlib.abc (module)

importlib.machinery (module)

importlib.util (module)

imports (2to3 fixer)

imports2 (2to3 fixer)

ImportWarning

ImproperConnectionState

imul() (dans le module operator)

in

mot-clé, [1]

opérateur, [1], [2]

in_dll() (méthode ctypes._CData)

in_table_a1() (dans le module stringprep)

in_table_b1() (dans le module stringprep)

in_table_c11() (dans le module stringprep)

in_table_c11_c12() (dans le module stringprep)

in_table_c12() (dans le module stringprep)

in_table_c21() (dans le module stringprep)

in_table_c21_c22() (dans le module stringprep)

in_table_c22() (dans le module stringprep)

in_table_c3() (dans le module stringprep)

in_table_c4() (dans le module stringprep)

in_table_c5() (dans le module stringprep)

in_table_c6() (dans le module stringprep)

in_table_c7() (dans le module stringprep)

in_table_c8() (dans le module stringprep)

in_table_c9() (dans le module stringprep)

in_table_d1() (dans le module stringprep)

in_table_d2() (dans le module stringprep)

in_transaction (attribut sqlite3.Connection)

inch() (méthode curses.window)

inclusive

or

inclusive (attribut tracemalloc.DomainFilter)

(attribut tracemalloc.Filter)

Incomplete

IncompleteRead

IncompleteReadError

incr_item(), [1]

increment_lineno() (dans le module ast)

incrementaldecoder (attribut codecs.CodecInfo)

IncrementalDecoder (classe dans codecs)

incrementalencoder (attribut codecs.CodecInfo)

IncrementalEncoder (classe dans codecs)

IncrementalNewlineDecoder (classe dans io)

IncrementalParser (classe dans xml.sax.xmlreader)

indent (attribut doctest.Example)

INDENT (dans le module token)

INDENT token

indent() (dans le module textwrap)

indentation

IndentationError

index operation

index() (dans le module operator)

(méthode array.array)

(méthode bytearray)

(méthode bytes)

(méthode collections.deque)

(méthode str)

(méthode tkinter.ttk.Notebook)

(méthode tkinter.ttk.Treeview)

(sequence method)

IndexError

indexOf() (dans le module operator)

IndexSizeErr

indication de type

indices() (méthode slice)

inet_aton() (dans le module socket)

inet_ntoa() (dans le module socket)

inet_ntop() (dans le module socket)

inet_pton() (dans le module socket)

Inexact (classe dans decimal)

inf (dans le module cmath)

(dans le module math)

infile

json.tool command line option

infile (attribut shlex.shlex)

Infinity

infj (dans le module cmath)

info() (dans le module logging)

(méthode dis.Bytecode)

(méthode gettext.NullTranslations)

(méthode logging.Logger)

infolist() (méthode zipfile.ZipFile)

inheritance

ini file

init() (dans le module mimetypes)

init_color() (dans le module curses)

init_database() (dans le module msilib)

init_pair() (dans le module curses)

inited (dans le module mimetypes)

initgroups() (dans le module os)

initial_indent (attribut textwrap.TextWrapper)

initialize_options() (méthode distutils.cmd.Command)

initscr() (dans le module curses)

inode() (méthode os.DirEntry)

INPLACE_ADD (opcode)

INPLACE_AND (opcode)

INPLACE_FLOOR_DIVIDE (opcode)

INPLACE_LSHIFT (opcode)

INPLACE_MATRIX_MULTIPLY (opcode)

INPLACE_MODULO (opcode)

INPLACE_MULTIPLY (opcode)

INPLACE_OR (opcode)

INPLACE_POWER (opcode)

INPLACE_RSHIFT (opcode)

INPLACE_SUBTRACT (opcode)

INPLACE_TRUE_DIVIDE (opcode)

INPLACE_XOR (opcode)

input

(2to3 fixer)

input() (dans le module fileinput)

(fonction de base)

input_charset (attribut email.charset.Charset)

input_codec (attribut email.charset.Charset)

InputOnly (classe dans tkinter.tix)

InputSource (classe dans xml.sax.xmlreader)

inquiry (type C)

insch() (méthode curses.window)

insdelln() (méthode curses.window)

insert() (méthode array.array)

(méthode collections.deque)

(méthode tkinter.ttk.Notebook)

(méthode tkinter.ttk.Treeview)

(méthode xml.etree.ElementTree.Element)

(sequence method)

insert_text() (dans le module readline)

insertBefore() (méthode xml.dom.Node)

insertln() (méthode curses.window)

insnstr() (méthode curses.window)

insort() (dans le module bisect)

insort_left() (dans le module bisect)

insort_right() (dans le module bisect)

inspect (module)

inspect command line option

--details

InspectLoader (classe dans importlib.abc)

insstr() (méthode curses.window)

install() (dans le module gettext)

(méthode gettext.NullTranslations)

install_opener() (dans le module urllib.request)

install_scripts() (méthode venv.EnvBuilder)

installHandler() (dans le module unittest)

instance

call, [1]

class

objet, [1], [2]

instancemethod

objet

instate() (méthode tkinter.ttk.Widget)

instr() (méthode curses.window)

instream (attribut shlex.shlex)

instruction

Instruction (classe dans dis)

Instruction.arg (dans le module dis)

Instruction.argrepr (dans le module dis)

Instruction.argval (dans le module dis)

Instruction.is_jump_target (dans le module dis)

Instruction.offset (dans le module dis)

Instruction.opcode (dans le module dis)

Instruction.opname (dans le module dis)

Instruction.starts_line (dans le module dis)

int

fonction de base, [1], [2]

int (attribut uuid.UUID)

(classe de base)

Int2AP() (dans le module imaplib)

int_info (dans le module sys)

integer

literals

objet, [1], [2]

representation

types, operations on

integer literal

Integral (classe dans numbers)

Integrated Development Environment

IntegrityError

Intel/DVI ADPCM

IntEnum (classe dans enum)

interact (pdb command)

interact() (dans le module code)

(méthode code.InteractiveConsole)

(méthode telnetlib.Telnet)

interactif

interactive mode

InteractiveConsole (classe dans code)

InteractiveInterpreter (classe dans code)

intern (2to3 fixer)

intern() (dans le module sys)

internal type

internal_attr (attribut zipfile.ZipInfo)

Internaldate2tuple() (dans le module imaplib)

internalSubset (attribut xml.dom.DocumentType)

Internet

interpolated string literal

interpolation

bytearray (%)

bytes (%)

interpolation, string (%)

InterpolationDepthError

InterpolationError

InterpolationMissingOptionError

InterpolationSyntaxError

interpreter

interpreter lock

interpreter prompts

interprété

interrupt() (méthode sqlite3.Connection)

interrupt_main() (dans le module _thread)

InterruptedError

intersection() (méthode frozenset)

intersection_update() (méthode frozenset)

IntFlag (classe dans enum)

intro (attribut cmd.Cmd)

InuseAttributeErr

inv() (dans le module operator)

InvalidAccessErr

invalidate_caches() (dans le module importlib)

(méthode de la classe importlib.machinery.PathFinder)

(méthode importlib.abc.MetaPathFinder)

(méthode importlib.abc.PathEntryFinder)

(méthode importlib.machinery.FileFinder)

InvalidCharacterErr

InvalidModificationErr

InvalidOperation (classe dans decimal)

InvalidStateErr

InvalidStateError

InvalidURL

inversion

invert() (dans le module operator)

invocation

io

module

IO (classe dans typing)

io (module)

io.StringIO

objet

IOBase (classe dans io)

ioctl() (dans le module fcntl)

(méthode socket.socket)

IOError

ior() (dans le module operator)

ip (attribut ipaddress.IPv4Interface)

(attribut ipaddress.IPv6Interface)

ip_address() (dans le module ipaddress)

ip_interface() (dans le module ipaddress)

ip_network() (dans le module ipaddress)

ipaddress (module)

ipow() (dans le module operator)

ipv4_mapped (attribut ipaddress.IPv6Address)

IPv4Address (classe dans ipaddress)

IPv4Interface (classe dans ipaddress)

IPv4Network (classe dans ipaddress)

IPv6Address (classe dans ipaddress)

IPv6Interface (classe dans ipaddress)

IPv6Network (classe dans ipaddress)

irshift() (dans le module operator)

is

opérateur, [1]

is not

opérateur, [1]

is_() (dans le module operator)

is_absolute() (méthode pathlib.PurePath)

is_alive() (méthode multiprocessing.Process)

(méthode threading.Thread)

is_assigned() (méthode symtable.Symbol)

is_attachment() (méthode email.message.EmailMessage)

is_authenticated() (méthode urllib.request.HTTPPasswordMgrWithPriorAuth)

is_block_device() (méthode pathlib.Path)

is_blocked() (méthode http.cookiejar.DefaultCookiePolicy)

is_canonical() (méthode decimal.Context)

(méthode decimal.Decimal)

is_char_device() (méthode pathlib.Path)

IS_CHARACTER_JUNK() (dans le module difflib)

is_check_supported() (dans le module lzma)

is_closed() (méthode asyncio.AbstractEventLoop)

is_closing() (méthode asyncio.BaseTransport)

is_declared_global() (méthode symtable.Symbol)

is_dir() (méthode os.DirEntry)

(méthode pathlib.Path)

(méthode zipfile.ZipInfo)

is_enabled() (dans le module faulthandler)

is_expired() (méthode http.cookiejar.Cookie)

is_fifo() (méthode pathlib.Path)

is_file() (méthode os.DirEntry)

(méthode pathlib.Path)

is_finalizing() (dans le module sys)

is_finite() (méthode decimal.Context)

(méthode decimal.Decimal)

is_free() (méthode symtable.Symbol)

is_global (attribut ipaddress.IPv4Address)

(attribut ipaddress.IPv6Address)

is_global() (méthode symtable.Symbol)

is_hop_by_hop() (dans le module wsgiref.util)

is_imported() (méthode symtable.Symbol)

is_infinite() (méthode decimal.Context)

(méthode decimal.Decimal)

is_integer() (méthode float)

is_jython (dans le module test.support)

IS_LINE_JUNK() (dans le module difflib)

is_linetouched() (méthode curses.window)

is_link_local (attribut ipaddress.IPv4Address)

(attribut ipaddress.IPv4Network)

(attribut ipaddress.IPv6Address)

(attribut ipaddress.IPv6Network)

is_local() (méthode symtable.Symbol)

is_loopback (attribut ipaddress.IPv4Address)

(attribut ipaddress.IPv4Network)

(attribut ipaddress.IPv6Address)

(attribut ipaddress.IPv6Network)

is_multicast (attribut ipaddress.IPv4Address)

(attribut ipaddress.IPv4Network)

(attribut ipaddress.IPv6Address)

(attribut ipaddress.IPv6Network)

is_multipart() (méthode email.message.EmailMessage)

(méthode email.message.Message)

is_namespace() (méthode symtable.Symbol)

is_nan() (méthode decimal.Context)

(méthode decimal.Decimal)

is_nested() (méthode symtable.SymbolTable)

is_normal() (méthode decimal.Context)

(méthode decimal.Decimal)

is_not() (dans le module operator)

is_not_allowed() (méthode http.cookiejar.DefaultCookiePolicy)

is_optimized() (méthode symtable.SymbolTable)

is_package() (méthode importlib.abc.InspectLoader)

(méthode importlib.abc.SourceLoader)

(méthode importlib.machinery.ExtensionFileLoader)

(méthode importlib.machinery.SourceFileLoader)

(méthode importlib.machinery.SourcelessFileLoader)

(méthode zipimport.zipimporter)

is_parameter() (méthode symtable.Symbol)

is_private (attribut ipaddress.IPv4Address)

(attribut ipaddress.IPv4Network)

(attribut ipaddress.IPv6Address)

(attribut ipaddress.IPv6Network)

is_python_build() (dans le module sysconfig)

is_qnan() (méthode decimal.Context)

(méthode decimal.Decimal)

is_referenced() (méthode symtable.Symbol)

is_reserved (attribut ipaddress.IPv4Address)

(attribut ipaddress.IPv4Network)

(attribut ipaddress.IPv6Address)

(attribut ipaddress.IPv6Network)

is_reserved() (méthode pathlib.PurePath)

is_resource_enabled() (dans le module test.support)

is_running() (méthode asyncio.AbstractEventLoop)

is_set() (méthode asyncio.Event)

(méthode threading.Event)

is_signed() (méthode decimal.Context)

(méthode decimal.Decimal)

is_site_local (attribut ipaddress.IPv6Address)

(attribut ipaddress.IPv6Network)

is_snan() (méthode decimal.Context)

(méthode decimal.Decimal)

is_socket() (méthode pathlib.Path)

is_subnormal() (méthode decimal.Context)

(méthode decimal.Decimal)

is_symlink() (méthode os.DirEntry)

(méthode pathlib.Path)

is_tarfile() (dans le module tarfile)

is_term_resized() (dans le module curses)

is_tracing() (dans le module tracemalloc)

is_tracked() (dans le module gc)

is_unspecified (attribut ipaddress.IPv4Address)

(attribut ipaddress.IPv4Network)

(attribut ipaddress.IPv6Address)

(attribut ipaddress.IPv6Network)

is_wintouched() (méthode curses.window)

is_zero() (méthode decimal.Context)

(méthode decimal.Decimal)

is_zipfile() (dans le module zipfile)

isabs() (dans le module os.path)

isabstract() (dans le module inspect)

IsADirectoryError

isalnum() (dans le module curses.ascii)

(méthode bytearray)

(méthode bytes)

(méthode str)

isalpha() (dans le module curses.ascii)

(méthode bytearray)

(méthode bytes)

(méthode str)

isascii() (dans le module curses.ascii)

isasyncgen() (dans le module inspect)

isasyncgenfunction() (dans le module inspect)

isatty() (dans le module os)

(méthode chunk.Chunk)

(méthode io.IOBase)

isawaitable() (dans le module inspect)

isblank() (dans le module curses.ascii)

isblk() (méthode tarfile.TarInfo)

isbuiltin() (dans le module inspect)

ischr() (méthode tarfile.TarInfo)

isclass() (dans le module inspect)

isclose() (dans le module cmath)

(dans le module math)

iscntrl() (dans le module curses.ascii)

iscode() (dans le module inspect)

iscoroutine() (dans le module asyncio)

(dans le module inspect)

iscoroutinefunction() (dans le module asyncio)

(dans le module inspect)

isctrl() (dans le module curses.ascii)

isDaemon() (méthode threading.Thread)

isdatadescriptor() (dans le module inspect)

isdecimal() (méthode str)

isdev() (méthode tarfile.TarInfo)

isdigit() (dans le module curses.ascii)

(méthode bytearray)

(méthode bytes)

(méthode str)

isdir() (dans le module os.path)

(méthode tarfile.TarInfo)

isdisjoint() (méthode frozenset)

isdown() (dans le module turtle)

iselement() (dans le module xml.etree.ElementTree)

isenabled() (dans le module gc)

isEnabledFor() (méthode logging.Logger)

isendwin() (dans le module curses)

ISEOF() (dans le module token)

isexpr() (dans le module parser)

(méthode parser.ST)

isfifo() (méthode tarfile.TarInfo)

isfile() (dans le module os.path)

(méthode tarfile.TarInfo)

isfinite() (dans le module cmath)

(dans le module math)

isfirstline() (dans le module fileinput)

isframe() (dans le module inspect)

isfunction() (dans le module inspect)

isgenerator() (dans le module inspect)

isgeneratorfunction() (dans le module inspect)

isgetsetdescriptor() (dans le module inspect)

isgraph() (dans le module curses.ascii)

isidentifier() (méthode str)

isinf() (dans le module cmath)

(dans le module math)

isinstance (2to3 fixer)

isinstance() (fonction de base)

iskeyword() (dans le module keyword)

isleap() (dans le module calendar)

islice() (dans le module itertools)

islink() (dans le module os.path)

islnk() (méthode tarfile.TarInfo)

islower() (dans le module curses.ascii)

(méthode bytearray)

(méthode bytes)

(méthode str)

ismemberdescriptor() (dans le module inspect)

ismeta() (dans le module curses.ascii)

ismethod() (dans le module inspect)

ismethoddescriptor() (dans le module inspect)

ismodule() (dans le module inspect)

ismount() (dans le module os.path)

isnan() (dans le module cmath)

(dans le module math)

ISNONTERMINAL() (dans le module token)

isnumeric() (méthode str)

isocalendar() (méthode datetime.date)

(méthode datetime.datetime)

isoformat() (méthode datetime.date)

(méthode datetime.datetime)

(méthode datetime.time)

isolation_level (attribut sqlite3.Connection)

isoweekday() (méthode datetime.date)

(méthode datetime.datetime)

isprint() (dans le module curses.ascii)

isprintable() (méthode str)

ispunct() (dans le module curses.ascii)

isreadable() (dans le module pprint)

(méthode pprint.PrettyPrinter)

isrecursive() (dans le module pprint)

(méthode pprint.PrettyPrinter)

isreg() (méthode tarfile.TarInfo)

isReservedKey() (méthode http.cookies.Morsel)

isroutine() (dans le module inspect)

isSameNode() (méthode xml.dom.Node)

isspace() (dans le module curses.ascii)

(méthode bytearray)

(méthode bytes)

(méthode str)

isstdin() (dans le module fileinput)

issubclass() (fonction de base)

issubset() (méthode frozenset)

issuite() (dans le module parser)

(méthode parser.ST)

issuperset() (méthode frozenset)

issym() (méthode tarfile.TarInfo)

ISTERMINAL() (dans le module token)

istitle() (méthode bytearray)

(méthode bytes)

(méthode str)

istraceback() (dans le module inspect)

isub() (dans le module operator)

isupper() (dans le module curses.ascii)

(méthode bytearray)

(méthode bytes)

(méthode str)

isvisible() (dans le module turtle)

isxdigit() (dans le module curses.ascii)

item

sequence

string

item selection

item() (méthode tkinter.ttk.Treeview)

(méthode xml.dom.NamedNodeMap)

(méthode xml.dom.NodeList)

itemgetter() (dans le module operator)

items() (méthode configparser.ConfigParser)

(méthode dict)

(méthode email.message.EmailMessage)

(méthode email.message.Message)

(méthode mailbox.Mailbox)

(méthode types.MappingProxyType)

(méthode xml.etree.ElementTree.Element)

itemsize (attribut array.array)

(attribut memoryview)

ItemsView (classe dans collections.abc)

(classe dans typing)

iter() (fonction de base)

(méthode xml.etree.ElementTree.Element)

(méthode xml.etree.ElementTree.ElementTree)

iter_attachments() (méthode email.message.EmailMessage)

iter_child_nodes() (dans le module ast)

iter_fields() (dans le module ast)

iter_importers() (dans le module pkgutil)

iter_modules() (dans le module pkgutil)

iter_parts() (méthode email.message.EmailMessage)

iter_unpack() (dans le module struct)

(méthode struct.Struct)

iterable

unpacking

Iterable (classe dans collections.abc)

(classe dans typing)

Iterator (classe dans collections.abc)

(classe dans typing)

iterator protocol

iterdecode() (dans le module codecs)

iterdir() (méthode pathlib.Path)

iterdump() (méthode sqlite3.Connection)

iterencode() (dans le module codecs)

(méthode json.JSONEncoder)

iterfind() (méthode xml.etree.ElementTree.Element)

(méthode xml.etree.ElementTree.ElementTree)

iteritems() (méthode mailbox.Mailbox)

iterkeys() (méthode mailbox.Mailbox)

itermonthdates() (méthode calendar.Calendar)

itermonthdays() (méthode calendar.Calendar)

itermonthdays2() (méthode calendar.Calendar)

iterparse() (dans le module xml.etree.ElementTree)

itertext() (méthode xml.etree.ElementTree.Element)

itertools (2to3 fixer)

(module)

itertools_imports (2to3 fixer)

itervalues() (méthode mailbox.Mailbox)

iterweekdays() (méthode calendar.Calendar)

itérable

itérable asynchrone

itérateur

itérateur asynchrone

itérateur de générateur

itérateur de générateur asynchrone

ITIMER_PROF (dans le module signal)

ITIMER_REAL (dans le module signal)

ITIMER_VIRTUAL (dans le module signal)

ItimerError

itruediv() (dans le module operator)

ixor() (dans le module operator)

J

j

in numeric literal

Jansen, Jack

Java

language

java_ver() (dans le module platform)

join() (dans le module os.path)

(méthode asyncio.Queue)

(méthode bytearray)

(méthode bytes)

(méthode multiprocessing.JoinableQueue)

(méthode multiprocessing.pool.Pool)

(méthode multiprocessing.Process)

(méthode queue.Queue)

(méthode str)

(méthode threading.Thread)

join_thread() (méthode multiprocessing.Queue)

JoinableQueue (classe dans multiprocessing)

joinpath() (méthode pathlib.PurePath)

js_output() (méthode http.cookies.BaseCookie)

(méthode http.cookies.Morsel)

json

module

json (module)

json.tool (module)

json.tool command line option

--help

--sort-keys

-h

infile

outfile

JSONDecodeError

JSONDecoder (classe dans json)

JSONEncoder (classe dans json)

jump (pdb command)

JUMP_ABSOLUTE (opcode)

JUMP_FORWARD (opcode)

JUMP_IF_FALSE_OR_POP (opcode)

JUMP_IF_TRUE_OR_POP (opcode)

K

kbhit() (dans le module msvcrt)

KDEDIR

kevent() (dans le module select)

key

(attribut http.cookies.Morsel)

key/datum pair

KEY_ALL_ACCESS (dans le module winreg)

KEY_CREATE_LINK (dans le module winreg)

KEY_CREATE_SUB_KEY (dans le module winreg)

KEY_ENUMERATE_SUB_KEYS (dans le module winreg)

KEY_EXECUTE (dans le module winreg)

KEY_NOTIFY (dans le module winreg)

KEY_QUERY_VALUE (dans le module winreg)

KEY_READ (dans le module winreg)

KEY_SET_VALUE (dans le module winreg)

KEY_WOW64_32KEY (dans le module winreg)

KEY_WOW64_64KEY (dans le module winreg)

KEY_WRITE (dans le module winreg)

KeyboardInterrupt

(built-in exception), [1]

KeyError

keyname() (dans le module curses)

keypad() (méthode curses.window)

keyrefs() (méthode weakref.WeakKeyDictionary)

keys() (méthode dict)

(méthode email.message.EmailMessage)

(méthode email.message.Message)

(méthode mailbox.Mailbox)

(méthode sqlite3.Row)

(méthode types.MappingProxyType)

(méthode xml.etree.ElementTree.Element)

KeysView (classe dans collections.abc)

(classe dans typing)

keyword

(module)

keywords (attribut functools.partial)

kill() (dans le module os)

(méthode asyncio.asyncio.subprocess.Process)

(méthode asyncio.BaseSubprocessTransport)

(méthode subprocess.Popen)

killchar() (dans le module curses)

killpg() (dans le module os)

kind (attribut inspect.Parameter)

knownfiles (dans le module mimetypes)

kqueue() (dans le module select)

KqueueSelector (classe dans selectors)

kwargs (attribut inspect.BoundArguments)

kwlist (dans le module keyword)

L

L (dans le module re)

LabelEntry (classe dans tkinter.tix)

LabelFrame (classe dans tkinter.tix)

lambda

expression, [1]

form

LambdaType (dans le module types)

LANG, [1], [2], [3], [4]

LANGUAGE, [1]

language

C, [1], [2], [3], [4], [5]

Java

large files

LargeZipFile

last() (méthode nntplib.NNTP)

last_accepted (attribut multiprocessing.connection.Listener)

last_traceback (dans le module sys)

(in module sys)

last_type (dans le module sys)

last_value (dans le module sys)

lastChild (attribut xml.dom.Node)

lastcmd (attribut cmd.Cmd)

lastgroup (attribut re.match)

lastindex (attribut re.match)

lastResort (dans le module logging)

lastrowid (attribut sqlite3.Cursor)

layout() (méthode tkinter.ttk.Style)

lazycache() (dans le module linecache)

LazyLoader (classe dans importlib.util)

LBRACE (dans le module token)

LBYL

LC_ALL, [1]

(dans le module locale)

LC_COLLATE (dans le module locale)

LC_CTYPE (dans le module locale)

LC_MESSAGES, [1]

(dans le module locale)

LC_MONETARY (dans le module locale)

LC_NUMERIC (dans le module locale)

LC_TIME (dans le module locale)

lchflags() (dans le module os)

lchmod() (dans le module os)

(méthode pathlib.Path)

lchown() (dans le module os)

LDCXXSHARED

ldexp() (dans le module math)

LDFLAGS

ldgettext() (dans le module gettext)

ldngettext() (dans le module gettext)

Le zen de Python

le() (dans le module operator)

leading whitespace

leapdays() (dans le module calendar)

leaveok() (méthode curses.window)

left (attribut filecmp.dircmp)

left() (dans le module turtle)

left_list (attribut filecmp.dircmp)

left_only (attribut filecmp.dircmp)

LEFTSHIFT (dans le module token)

LEFTSHIFTEQUAL (dans le module token)

len

fonction de base, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11]

len() (fonction de base)

length (attribut xml.dom.NamedNodeMap)

(attribut xml.dom.NodeList)

length_hint() (dans le module operator)

LESS (dans le module token)

LESSEQUAL (dans le module token)

lexical analysis

lexical definitions

lexists() (dans le module os.path)

lgamma() (dans le module math)

lgettext() (dans le module gettext)

(méthode gettext.GNUTranslations)

(méthode gettext.NullTranslations)

lib2to3 (module)

libc_ver() (dans le module platform)

library (attribut ssl.SSLError)

(dans le module dbm.ndbm)

library_dir_option() (méthode distutils.ccompiler.CCompiler)

library_filename() (méthode distutils.ccompiler.CCompiler)

library_option() (méthode distutils.ccompiler.CCompiler)

LibraryLoader (classe dans ctypes)

license (variable de base)

LifoQueue (classe dans asyncio)

(classe dans queue)

light-weight processes

limit_denominator() (méthode fractions.Fraction)

LimitOverrunError

lin2adpcm() (dans le module audioop)

lin2alaw() (dans le module audioop)

lin2lin() (dans le module audioop)

lin2ulaw() (dans le module audioop)

line (fonction C)

line continuation

line joining, [1]

line structure

line() (méthode msilib.Dialog)

line-buffered I/O

line_buffering (attribut io.TextIOWrapper)

line_num (attribut csv.csvreader)

linecache (module)

lineno (attribut ast.AST)

(attribut doctest.DocTest)

(attribut doctest.Example)

(attribut json.JSONDecodeError)

(attribut pyclbr.Class)

(attribut pyclbr.Function)

(attribut re.error)

(attribut shlex.shlex)

(attribut traceback.TracebackException)

(attribut tracemalloc.Filter)

(attribut tracemalloc.Frame)

(attribut xml.parsers.expat.ExpatError)

lineno() (dans le module fileinput)

LINES, [1], [2], [3], [4]

lines (attribut os.terminal_size)

linesep (attribut email.policy.Policy)

(dans le module os)

lineterminator (attribut csv.Dialect)

LineTooLong

link() (dans le module os)

(méthode distutils.ccompiler.CCompiler)

link_executable() (méthode distutils.ccompiler.CCompiler)

link_shared_lib() (méthode distutils.ccompiler.CCompiler)

link_shared_object() (méthode distutils.ccompiler.CCompiler)

linkname (attribut tarfile.TarInfo)

linux_distribution() (dans le module platform)

list

assignment, target

comprehensions

deletion target

display

empty

expression, [1], [2]

objet, [1], [2], [3], [4], [5], [6], [7], [8]

target, [1], [2]

type, operations on

List (classe dans typing)

list (classe de base)

(pdb command)

list() (méthode imaplib.IMAP4)

(méthode multiprocessing.managers.SyncManager)

(méthode nntplib.NNTP)

(méthode poplib.POP3)

(méthode tarfile.TarFile)

LIST_APPEND (opcode)

list_dialects() (dans le module csv)

list_folders() (méthode mailbox.Maildir)

(méthode mailbox.MH)

listdir() (dans le module os)

liste en compréhension (ou liste en intension)

listen() (dans le module logging.config)

(dans le module turtle)

(méthode asyncore.dispatcher)

(méthode socket.socket)

Listener (classe dans multiprocessing.connection)

listMethods() (méthode xmlrpc.client.ServerProxy.system)

ListNoteBook (classe dans tkinter.tix)

listxattr() (dans le module os)

literal, [1]

literal_eval() (dans le module ast)

literals

binary

complex number

floating point

hexadecimal

integer

numeric

octal

LittleEndianStructure (classe dans ctypes)

ljust() (méthode bytearray)

(méthode bytes)

(méthode str)

LK_LOCK (dans le module msvcrt)

LK_NBLCK (dans le module msvcrt)

LK_NBRLCK (dans le module msvcrt)

LK_RLCK (dans le module msvcrt)

LK_UNLCK (dans le module msvcrt)

ll (pdb command)

LMTP (classe dans smtplib)

ln() (méthode decimal.Context)

(méthode decimal.Decimal)

LNAME

lngettext() (dans le module gettext)

(méthode gettext.GNUTranslations)

(méthode gettext.NullTranslations)

load() (dans le module json)

(dans le module marshal)

(dans le module pickle)

(dans le module plistlib)

(méthode de la classe tracemalloc.Snapshot)

(méthode http.cookiejar.FileCookieJar)

(méthode http.cookies.BaseCookie)

(méthode pickle.Unpickler)

LOAD_ATTR (opcode)

LOAD_BUILD_CLASS (opcode)

load_cert_chain() (méthode ssl.SSLContext)

LOAD_CLASSDEREF (opcode)

LOAD_CLOSURE (opcode)

LOAD_CONST (opcode)

load_default_certs() (méthode ssl.SSLContext)

LOAD_DEREF (opcode)

load_dh_params() (méthode ssl.SSLContext)

load_extension() (méthode sqlite3.Connection)

LOAD_FAST (opcode)

LOAD_GLOBAL (opcode)

load_module() (dans le module imp)

(méthode importlib.abc.FileLoader)

(méthode importlib.abc.InspectLoader)

(méthode importlib.abc.Loader)

(méthode importlib.abc.SourceLoader)

(méthode importlib.machinery.SourceFileLoader)

(méthode importlib.machinery.SourcelessFileLoader)

(méthode zipimport.zipimporter)

LOAD_NAME (opcode)

load_package_tests() (dans le module test.support)

load_verify_locations() (méthode ssl.SSLContext)

loader

(attribut importlib.machinery.ModuleSpec)

Loader (classe dans importlib.abc)

loader_state (attribut importlib.machinery.ModuleSpec)

LoadError

LoadKey() (dans le module winreg)

LoadLibrary() (méthode ctypes.LibraryLoader)

loads() (dans le module json)

(dans le module marshal)

(dans le module pickle)

(dans le module plistlib)

(dans le module xmlrpc.client)

loadTestsFromModule() (méthode unittest.TestLoader)

loadTestsFromName() (méthode unittest.TestLoader)

loadTestsFromNames() (méthode unittest.TestLoader)

loadTestsFromTestCase() (méthode unittest.TestLoader)

local (classe dans threading)

localcontext() (dans le module decimal)

LOCALE (dans le module re)

locale (module)

localeconv() (dans le module locale)

LocaleHTMLCalendar (classe dans calendar)

LocaleTextCalendar (classe dans calendar)

localName (attribut xml.dom.Attr)

(attribut xml.dom.Node)

locals() (fonction de base)

localtime() (dans le module email.utils)

(dans le module time)

Locator (classe dans xml.sax.xmlreader)

Lock (classe dans asyncio)

(classe dans multiprocessing)

(classe dans threading)

lock() (méthode mailbox.Babyl)

(méthode mailbox.Mailbox)

(méthode mailbox.Maildir)

(méthode mailbox.mbox)

(méthode mailbox.MH)

(méthode mailbox.MMDF)

Lock() (méthode multiprocessing.managers.SyncManager)

lock, interpreter

lock_held() (dans le module imp)

locked() (méthode _thread.lock)

(méthode asyncio.Condition)

(méthode asyncio.Lock)

(méthode asyncio.Semaphore)

lockf() (dans le module fcntl)

(dans le module os)

locking() (dans le module msvcrt)

LockType (dans le module _thread)

log() (dans le module cmath)

(dans le module logging)

(dans le module math)

(méthode logging.Logger)

log10() (dans le module cmath)

(dans le module math)

(méthode decimal.Context)

(méthode decimal.Decimal)

log1p() (dans le module math)

log2() (dans le module math)

log_date_time_string() (méthode http.server.BaseHTTPRequestHandler)

log_error() (méthode http.server.BaseHTTPRequestHandler)

log_exception() (méthode wsgiref.handlers.BaseHandler)

log_message() (méthode http.server.BaseHTTPRequestHandler)

log_request() (méthode http.server.BaseHTTPRequestHandler)

log_to_stderr() (dans le module multiprocessing)

logb() (méthode decimal.Context)

(méthode decimal.Decimal)

Logger (classe dans logging)

LoggerAdapter (classe dans logging)

logging

Errors

logging (module)

logging.config (module)

logging.handlers (module)

logical line

logical_and() (méthode decimal.Context)

(méthode decimal.Decimal)

logical_invert() (méthode decimal.Context)

(méthode decimal.Decimal)

logical_or() (méthode decimal.Context)

(méthode decimal.Decimal)

logical_xor() (méthode decimal.Context)

(méthode decimal.Decimal)

login() (méthode ftplib.FTP)

(méthode imaplib.IMAP4)

(méthode nntplib.NNTP)

(méthode smtplib.SMTP)

login_cram_md5() (méthode imaplib.IMAP4)

LOGNAME, [1]

lognormvariate() (dans le module random)

logout() (méthode imaplib.IMAP4)

LogRecord (classe dans logging)

long (2to3 fixer)

long integer

objet

LONG_MAX

longMessage (attribut unittest.TestCase)

longname() (dans le module curses)

lookup() (dans le module codecs)

(dans le module unicodedata)

(méthode symtable.SymbolTable)

(méthode tkinter.ttk.Style)

lookup_error() (dans le module codecs)

LookupError

loop

over mutable sequence

statement, [1], [2], [3]

loop control

target

loop() (dans le module asyncore)

lower() (méthode bytearray)

(méthode bytes)

(méthode str)

LPAR (dans le module token)

lru_cache() (dans le module functools)

lseek() (dans le module os)

lshift() (dans le module operator)

LSQB (dans le module token)

lstat() (dans le module os)

(méthode pathlib.Path)

lstrip() (méthode bytearray)

(méthode bytes)

(méthode str)

lsub() (méthode imaplib.IMAP4)

lt() (dans le module operator)

(dans le module turtle)

LWPCookieJar (classe dans http.cookiejar)

lzma (module)

LZMACompressor (classe dans lzma)

LZMADecompressor (classe dans lzma)

LZMAError

LZMAFile (classe dans lzma)

M

M (dans le module re)

mac_ver() (dans le module platform)

machine virtuelle

machine() (dans le module platform)

macpath (module)

macros (attribut netrc.netrc)

MAGIC_NUMBER (dans le module importlib.util)

MagicMock (classe dans unittest.mock)

Mailbox (classe dans mailbox)

mailbox (module)

mailcap (module)

Maildir (classe dans mailbox)

MaildirMessage (classe dans mailbox)

mailfrom (attribut smtpd.SMTPChannel)

MailmanProxy (classe dans smtpd)

main(), [1], [2]

(dans le module py_compile)

(dans le module site)

(dans le module unittest)

main_thread() (dans le module threading)

mainloop() (dans le module turtle)

maintype (attribut email.headerregistry.ContentTypeHeader)

major (attribut email.headerregistry.MIMEVersionHeader)

major() (dans le module os)

make_alternative() (méthode email.message.EmailMessage)

make_archive() (dans le module distutils.archive_util)

(dans le module shutil)

make_bad_fd() (dans le module test.support)

make_cookies() (méthode http.cookiejar.CookieJar)

make_file() (méthode difflib.HtmlDiff)

MAKE_FUNCTION (opcode)

make_header() (dans le module email.header)

make_mixed() (méthode email.message.EmailMessage)

make_msgid() (dans le module email.utils)

make_parser() (dans le module xml.sax)

make_related() (méthode email.message.EmailMessage)

make_server() (dans le module wsgiref.simple_server)

make_table() (méthode difflib.HtmlDiff)

make_tarball() (dans le module distutils.archive_util)

make_zipfile() (dans le module distutils.archive_util)

makedev() (dans le module os)

makedirs() (dans le module os)

makeelement() (méthode xml.etree.ElementTree.Element)

makefile() (méthode socket.socket)

(socket method)

makeLogRecord() (dans le module logging)

makePickle() (méthode logging.handlers.SocketHandler)

makeRecord() (méthode logging.Logger)

makeSocket() (méthode logging.handlers.DatagramHandler)

(méthode logging.handlers.SocketHandler)

maketrans() (méthode statique bytearray)

(méthode statique bytes)

(méthode statique str)

malloc()

mangle_from_ (attribut email.policy.Compat32)

(attribut email.policy.Policy)

mangling

name, [1]

map (2to3 fixer)

map() (fonction de base)

(méthode concurrent.futures.Executor)

(méthode multiprocessing.pool.Pool)

(méthode tkinter.ttk.Style)

MAP_ADD (opcode)

map_async() (méthode multiprocessing.pool.Pool)

map_table_b2() (dans le module stringprep)

map_table_b3() (dans le module stringprep)

map_to_type() (méthode email.headerregistry.HeaderRegistry)

mapLogRecord() (méthode logging.handlers.HTTPHandler)

mapping

objet, [1], [2], [3], [4], [5]

types, operations on

Mapping (classe dans collections.abc)

(classe dans typing)

mapping() (méthode msilib.Control)

MappingProxyType (classe dans types)

MappingView (classe dans collections.abc)

(classe dans typing)

mapPriority() (méthode logging.handlers.SysLogHandler)

maps (attribut collections.ChainMap)

maps() (dans le module nis)

marshal (module)

marshalling

objects

masking

operations

Match (classe dans typing)

match() (dans le module nis)

(dans le module re)

(méthode pathlib.PurePath)

(méthode re.regex)

match_hostname() (dans le module ssl)

math

module, [1]

math (module)

matmul() (dans le module operator)

matrix multiplication

max

fonction de base

max (attribut datetime.date)

(attribut datetime.datetime)

(attribut datetime.time)

(attribut datetime.timedelta)

max() (dans le module audioop)

(fonction de base)

(méthode decimal.Context)

(méthode decimal.Decimal)

max_count (attribut email.headerregistry.BaseHeader)

MAX_EMAX (dans le module decimal)

MAX_INTERPOLATION_DEPTH (dans le module configparser)

max_line_length (attribut email.policy.Policy)

max_lines (attribut textwrap.TextWrapper)

max_mag() (méthode decimal.Context)

(méthode decimal.Decimal)

MAX_PREC (dans le module decimal)

max_prefixlen (attribut ipaddress.IPv4Address)

(attribut ipaddress.IPv4Network)

(attribut ipaddress.IPv6Address)

(attribut ipaddress.IPv6Network)

maxarray (attribut reprlib.Repr)

maxdeque (attribut reprlib.Repr)

maxdict (attribut reprlib.Repr)

maxDiff (attribut unittest.TestCase)

maxfrozenset (attribut reprlib.Repr)

maxlen (attribut collections.deque)

maxlevel (attribut reprlib.Repr)

maxlist (attribut reprlib.Repr)

maxlong (attribut reprlib.Repr)

maxother (attribut reprlib.Repr)

maxpp() (dans le module audioop)

maxset (attribut reprlib.Repr)

maxsize (attribut asyncio.Queue)

(dans le module sys)

maxstring (attribut reprlib.Repr)

maxtuple (attribut reprlib.Repr)

maxunicode (dans le module sys)

MAXYEAR (dans le module datetime)

MB_ICONASTERISK (dans le module winsound)

MB_ICONEXCLAMATION (dans le module winsound)

MB_ICONHAND (dans le module winsound)

MB_ICONQUESTION (dans le module winsound)

MB_OK (dans le module winsound)

mbox (classe dans mailbox)

mboxMessage (classe dans mailbox)

mean() (dans le module statistics)

median() (dans le module statistics)

median_grouped() (dans le module statistics)

median_high() (dans le module statistics)

median_low() (dans le module statistics)

MemberDescriptorType (dans le module types)

membership

test

memmove() (dans le module ctypes)

MemoryBIO (classe dans ssl)

MemoryError

MemoryHandler (classe dans logging.handlers)

memoryview

objet, [1]

memoryview (classe de base)

memset() (dans le module ctypes)

merge() (dans le module heapq)

Message (classe dans email.message)

(classe dans mailbox)

message digest, MD5

message_factory (attribut email.policy.Policy)

message_from_binary_file() (dans le module email)

message_from_bytes() (dans le module email)

message_from_file() (dans le module email)

message_from_string() (dans le module email)

MessageBeep() (dans le module winsound)

MessageClass (attribut http.server.BaseHTTPRequestHandler)

MessageError

MessageParseError

messages (dans le module xml.parsers.expat.errors)

meta

hooks

meta hooks

meta() (dans le module curses)

meta_path (dans le module sys)

metaclass

(2to3 fixer)

metaclass hint

MetaPathFinder (classe dans importlib.abc)

metavar (attribut optparse.Option)

MetavarTypeHelpFormatter (classe dans argparse)

Meter (classe dans tkinter.tix)

METH_CLASS (variable de base)

METH_COEXIST (variable de base)

METH_KEYWORDS (variable de base)

METH_NOARGS (variable de base)

METH_O (variable de base)

METH_STATIC (variable de base)

METH_VARARGS (variable de base)

method

built-in

call

objet, [1], [2], [3], [4], [5]

user-defined

method (attribut urllib.request.Request)

method_calls (attribut unittest.mock.Mock)

METHOD_CRYPT (dans le module crypt)

METHOD_MD5 (dans le module crypt)

METHOD_SHA256 (dans le module crypt)

METHOD_SHA512 (dans le module crypt)

methodattrs (2to3 fixer)

methodcaller() (dans le module operator)

methodHelp() (méthode xmlrpc.client.ServerProxy.system)

methods

bytearray

bytes

string

methods (attribut pyclbr.Class)

(dans le module crypt)

methodSignature() (méthode xmlrpc.client.ServerProxy.system)

MethodType (dans le module types)

(in module types), [1]

métaclasse

méthode

méthode spéciale

MH (classe dans mailbox)

MHMessage (classe dans mailbox)

microsecond (attribut datetime.datetime)

(attribut datetime.time)

MIME

base64 encoding

content type

headers, [1]

quoted-printable encoding

MIMEApplication (classe dans email.mime.application)

MIMEAudio (classe dans email.mime.audio)

MIMEBase (classe dans email.mime.base)

MIMEImage (classe dans email.mime.image)

MIMEMessage (classe dans email.mime.message)

MIMEMultipart (classe dans email.mime.multipart)

MIMENonMultipart (classe dans email.mime.nonmultipart)

MIMEPart (classe dans email.message)

MIMEText (classe dans email.mime.text)

MimeTypes (classe dans mimetypes)

mimetypes (module)

MIMEVersionHeader (classe dans email.headerregistry)

min

fonction de base

min (attribut datetime.date)

(attribut datetime.datetime)

(attribut datetime.time)

(attribut datetime.timedelta)

min() (fonction de base)

(méthode decimal.Context)

(méthode decimal.Decimal)

MIN_EMIN (dans le module decimal)

MIN_ETINY (dans le module decimal)

min_mag() (méthode decimal.Context)

(méthode decimal.Decimal)

MINEQUAL (dans le module token)

minmax() (dans le module audioop)

minor (attribut email.headerregistry.MIMEVersionHeader)

minor() (dans le module os)

minus

MINUS (dans le module token)

minus() (méthode decimal.Context)

minute (attribut datetime.datetime)

(attribut datetime.time)

MINYEAR (dans le module datetime)

mirrored() (dans le module unicodedata)

misc_header (attribut cmd.Cmd)

MissingSectionHeaderError

MIXERDEV

mkd() (méthode ftplib.FTP)

mkdir() (dans le module os)

(méthode pathlib.Path)

mkdtemp() (dans le module tempfile)

mkfifo() (dans le module os)

mknod() (dans le module os)

mkpath() (dans le module distutils.dir_util)

(méthode distutils.ccompiler.CCompiler)

mksalt() (dans le module crypt)

mkstemp() (dans le module tempfile)

mktemp() (dans le module tempfile)

mktime() (dans le module time)

mktime_tz() (dans le module email.utils)

mlsd() (méthode ftplib.FTP)

mmap (classe dans mmap)

(module)

MMDF (classe dans mailbox)

MMDFMessage (classe dans mailbox)

Mock (classe dans unittest.mock)

mock_add_spec() (méthode unittest.mock.Mock)

mock_calls (attribut unittest.mock.Mock)

mock_open() (dans le module unittest.mock)

mod() (dans le module operator)

mode (attribut io.FileIO)

(attribut ossaudiodev.oss_audio_device)

(attribut tarfile.TarInfo)

mode() (dans le module statistics)

(dans le module turtle)

modes

file

modf() (dans le module math)

modified() (méthode urllib.robotparser.RobotFileParser)

Modify() (méthode msilib.View)

modify() (méthode select.devpoll)

(méthode select.epoll)

(méthode select.poll)

(méthode selectors.BaseSelector)

module

__main__, [1], [2], [3], [4], [5], [6], [7]

_locale

_thread

array, [1]

base64

bdb

binhex

builtins, [1], [2], [3], [4]

cmd

copy

crypt

dbm.gnu, [1]

dbm.ndbm, [1]

errno

extension

glob

imp

importing

io

json

math, [1]

namespace

objet, [1], [2]

os

pickle, [1], [2], [3]

pty

pwd

pyexpat

re, [1]

search path, [1], [2], [3], [4], [5], [6], [7]

shelve

signal, [1]

sitecustomize

socket

stat

string

struct

sys, [1], [2], [3], [4], [5], [6]

types

urllib.request

usercustomize

uu

module (attribut pyclbr.Class)

(attribut pyclbr.Function)

module d'extension

module spec

module_for_loader() (dans le module importlib.util)

module_from_spec() (dans le module importlib.util)

module_repr() (méthode importlib.abc.Loader)

ModuleFinder (classe dans modulefinder)

modulefinder (module)

ModuleInfo (classe dans pkgutil)

ModuleNotFoundError

modules (attribut modulefinder.ModuleFinder)

(dans le module sys)

(in module sys), [1]

ModuleSpec (classe dans importlib.machinery)

ModuleType (classe dans types)

(in module types)

modulo

monotonic() (dans le module time)

month (attribut datetime.date)

(attribut datetime.datetime)

month() (dans le module calendar)

month_abbr (dans le module calendar)

month_name (dans le module calendar)

monthcalendar() (dans le module calendar)

monthdatescalendar() (méthode calendar.Calendar)

monthdays2calendar() (méthode calendar.Calendar)

monthdayscalendar() (méthode calendar.Calendar)

monthrange() (dans le module calendar)

Morsel (classe dans http.cookies)

most_common() (méthode collections.Counter)

mot-clé

as, [1], [2]

async

await, [1], [2]

elif

else, [1], [2], [3], [4], [5], [6], [7]

except

finally, [1], [2], [3], [4]

from, [1]

in, [1]

yield

mouseinterval() (dans le module curses)

mousemask() (dans le module curses)

move() (dans le module shutil)

(méthode curses.panel.Panel)

(méthode curses.window)

(méthode mmap.mmap)

(méthode tkinter.ttk.Treeview)

move_file() (dans le module distutils.file_util)

(méthode distutils.ccompiler.CCompiler)

move_to_end() (méthode collections.OrderedDict)

MozillaCookieJar (classe dans http.cookiejar)

MRO

mro() (méthode class)

msg (attribut http.client.HTTPResponse)

(attribut json.JSONDecodeError)

(attribut re.error)

(attribut traceback.TracebackException)

msg() (méthode telnetlib.Telnet)

msi

msilib (module)

msvcrt (module)

mt_interact() (méthode telnetlib.Telnet)

mtime (attribut gzip.GzipFile)

(attribut tarfile.TarInfo)

mtime() (méthode urllib.robotparser.RobotFileParser)

muable

mul() (dans le module audioop)

(dans le module operator)

MultiCall (classe dans xmlrpc.client)

MULTILINE (dans le module re)

MultipartConversionError

multiplication

multiply() (méthode decimal.Context)

multiprocessing (module)

multiprocessing.connection (module)

multiprocessing.dummy (module)

multiprocessing.Manager() (dans le module multiprocessing.sharedctypes)

multiprocessing.managers (module)

multiprocessing.pool (module)

multiprocessing.sharedctypes (module)

mutable

objet, [1], [2]

sequence types

mutable object

mutable sequence

loop over

objet

MutableMapping (classe dans collections.abc)

(classe dans typing)

MutableSequence (classe dans collections.abc)

(classe dans typing)

MutableSet (classe dans collections.abc)

(classe dans typing)

mvderwin() (méthode curses.window)

mvwin() (méthode curses.window)

myrights() (méthode imaplib.IMAP4)

N

n-uplet nommé

N_TOKENS (dans le module token)

n_waiting (attribut threading.Barrier)

name, [1], [2]

binding, [1], [2], [3], [4], [5], [6]

binding, global

class

function, [1]

mangling, [1]

rebinding

unbinding

name (attribut codecs.CodecInfo)

(attribut doctest.DocTest)

(attribut email.headerregistry.BaseHeader)

(attribut hashlib.hash)

(attribut hmac.HMAC)

(attribut http.cookiejar.Cookie)

(attribut importlib.abc.FileLoader)

(attribut importlib.machinery.ExtensionFileLoader)

(attribut importlib.machinery.ModuleSpec)

(attribut importlib.machinery.SourceFileLoader)

(attribut importlib.machinery.SourcelessFileLoader)

(attribut inspect.Parameter)

(attribut io.FileIO)

(attribut multiprocessing.Process)

(attribut os.DirEntry)

(attribut ossaudiodev.oss_audio_device)

(attribut pyclbr.Class)

(attribut pyclbr.Function)

(attribut tarfile.TarInfo)

(attribut threading.Thread)

(attribut xml.dom.Attr)

(attribut xml.dom.DocumentType)

(dans le module os)

NAME (dans le module token)

name() (dans le module unicodedata)

name2codepoint (dans le module html.entities)

NamedTemporaryFile() (dans le module tempfile)

NamedTuple (classe dans typing)

namedtuple() (dans le module collections)

NameError

exception

NameError (built-in exception)

namelist() (méthode zipfile.ZipFile)

nameprep() (dans le module encodings.idna)

namer (attribut logging.handlers.BaseRotatingHandler)

namereplace_errors() (dans le module codecs)

names

private

namespace

global

module

package

Namespace (classe dans argparse)

(classe dans multiprocessing.managers)

namespace() (méthode imaplib.IMAP4)

Namespace() (méthode multiprocessing.managers.SyncManager)

NAMESPACE_DNS (dans le module uuid)

NAMESPACE_OID (dans le module uuid)

NAMESPACE_URL (dans le module uuid)

NAMESPACE_X500 (dans le module uuid)

NamespaceErr

namespaceURI (attribut xml.dom.Node)

NaN

nan (dans le module cmath)

(dans le module math)

nanj (dans le module cmath)

NannyNag

napms() (dans le module curses)

nargs (attribut optparse.Option)

nbytes (attribut memoryview)

ndiff() (dans le module difflib)

ndim (attribut memoryview)

ne (2to3 fixer)

ne() (dans le module operator)

needs_input (attribut bz2.BZ2Decompressor)

(attribut lzma.LZMADecompressor)

neg() (dans le module operator)

negation

netmask (attribut ipaddress.IPv4Network)

(attribut ipaddress.IPv6Network)

NetmaskValueError

netrc (classe dans netrc)

(module)

NetrcParseError

netscape (attribut http.cookiejar.CookiePolicy)

network (attribut ipaddress.IPv4Interface)

(attribut ipaddress.IPv6Interface)

Network News Transfer Protocol

network_address (attribut ipaddress.IPv4Network)

(attribut ipaddress.IPv6Network)

new() (dans le module hashlib)

(dans le module hmac)

new_alignment() (méthode formatter.writer)

new_child() (méthode collections.ChainMap)

new_class() (dans le module types)

new_compiler() (dans le module distutils.ccompiler)

new_event_loop() (dans le module asyncio)

(méthode asyncio.AbstractEventLoopPolicy)

new_font() (méthode formatter.writer)

new_margin() (méthode formatter.writer)

new_module() (dans le module imp)

new_panel() (dans le module curses.panel)

new_spacing() (méthode formatter.writer)

new_styles() (méthode formatter.writer)

newer() (dans le module distutils.dep_util)

newer_group() (dans le module distutils.dep_util)

newer_pairwise() (dans le module distutils.dep_util)

newgroups() (méthode nntplib.NNTP)

NEWLINE (dans le module token)

NEWLINE token, [1]

newlines (attribut io.TextIOBase)

newnews() (méthode nntplib.NNTP)

newpad() (dans le module curses)

NewType() (dans le module typing)

newwin() (dans le module curses)

next (2to3 fixer)

(pdb command)

next() (fonction de base)

(méthode nntplib.NNTP)

(méthode tarfile.TarFile)

(méthode tkinter.ttk.Treeview)

next_minus() (méthode decimal.Context)

(méthode decimal.Decimal)

next_plus() (méthode decimal.Context)

(méthode decimal.Decimal)

next_toward() (méthode decimal.Context)

(méthode decimal.Decimal)

nextfile() (dans le module fileinput)

nextkey() (méthode dbm.gnu.gdbm)

nextSibling (attribut xml.dom.Node)

ngettext() (dans le module gettext)

(méthode gettext.GNUTranslations)

(méthode gettext.NullTranslations)

nice() (dans le module os)

nis (module)

NL (dans le module tokenize)

nl() (dans le module curses)

nl_langinfo() (dans le module locale)

nlargest() (dans le module heapq)

nlst() (méthode ftplib.FTP)

NNTP

protocol

NNTP (classe dans nntplib)

nntp_implementation (attribut nntplib.NNTP)

NNTP_SSL (classe dans nntplib)

nntp_version (attribut nntplib.NNTP)

NNTPDataError

NNTPError

nntplib (module)

NNTPPermanentError

NNTPProtocolError

NNTPReplyError

NNTPTemporaryError

no_proxy

no_type_check() (dans le module typing)

no_type_check_decorator() (dans le module typing)

nocbreak() (dans le module curses)

NoDataAllowedErr

node() (dans le module platform)

nodelay() (méthode curses.window)

nodeName (attribut xml.dom.Node)

NodeTransformer (classe dans ast)

nodeType (attribut xml.dom.Node)

nodeValue (attribut xml.dom.Node)

NodeVisitor (classe dans ast)

noecho() (dans le module curses)

NOEXPR (dans le module locale)

nom qualifié

nombre complexe

nombre de références

NoModificationAllowedErr

nonblock() (méthode ossaudiodev.oss_audio_device)

NonCallableMagicMock (classe dans unittest.mock)

NonCallableMock (classe dans unittest.mock)

None

objet, [1], [2]

None (Built-in object)

(variable de base)

nonl() (dans le module curses)

nonlocal

état

nonzero (2to3 fixer)

noop() (méthode imaplib.IMAP4)

(méthode poplib.POP3)

NoOptionError

NOP (opcode)

noqiflush() (dans le module curses)

noraw() (dans le module curses)

NoReturn (dans le module typing)

normalize() (dans le module locale)

(dans le module unicodedata)

(méthode decimal.Context)

(méthode decimal.Decimal)

(méthode xml.dom.Node)

NORMALIZE_WHITESPACE (dans le module doctest)

normalvariate() (dans le module random)

normcase() (dans le module os.path)

normpath() (dans le module os.path)

NoSectionError

NoSuchMailboxError

not

opérateur, [1]

not in

opérateur, [1], [2]

not_() (dans le module operator)

NotADirectoryError

notation

notationDecl() (méthode xml.sax.handler.DTDHandler)

NotationDeclHandler() (méthode xml.parsers.expat.xmlparser)

notations (attribut xml.dom.DocumentType)

NotConnected

NoteBook (classe dans tkinter.tix)

Notebook (classe dans tkinter.ttk)

NotEmptyError

NOTEQUAL (dans le module token)

NotFoundErr

notify() (méthode asyncio.Condition)

(méthode threading.Condition)

notify_all() (méthode asyncio.Condition)

(méthode threading.Condition)

notimeout() (méthode curses.window)

NotImplemented

objet

NotImplemented (variable de base)

NotImplementedError

NotStandaloneHandler() (méthode xml.parsers.expat.xmlparser)

NotSupportedErr

NotSupportedError

noutrefresh() (méthode curses.window)

nouvelle classe

now() (méthode de la classe datetime.datetime)

NSIG (dans le module signal)

nsmallest() (dans le module heapq)

NT_OFFSET (dans le module token)

NTEventLogHandler (classe dans logging.handlers)

ntohl() (dans le module socket)

ntohs() (dans le module socket)

ntransfercmd() (méthode ftplib.FTP)

null

operation, [1]

NullFormatter (classe dans formatter)

NullHandler (classe dans logging)

NullImporter (classe dans imp)

NullTranslations (classe dans gettext)

NullWriter (classe dans formatter)

num_addresses (attribut ipaddress.IPv4Network)

(attribut ipaddress.IPv6Network)

number

complex

floating point

Number (classe dans numbers)

NUMBER (dans le module token)

number_class() (méthode decimal.Context)

(méthode decimal.Decimal)

numbers (module)

numerator (attribut fractions.Fraction)

(attribut numbers.Rational)

numeric

conversions

literals

object

objet, [1], [2], [3]

types, operations on

numeric literal

numeric() (dans le module unicodedata)

Numerical Python

numinput() (dans le module turtle)

numliterals (2to3 fixer)

O

O_APPEND (dans le module os)

O_ASYNC (dans le module os)

O_BINARY (dans le module os)

O_CLOEXEC (dans le module os)

O_CREAT (dans le module os)

O_DIRECT (dans le module os)

O_DIRECTORY (dans le module os)

O_DSYNC (dans le module os)

O_EXCL (dans le module os)

O_EXLOCK (dans le module os)

O_NDELAY (dans le module os)

O_NOATIME (dans le module os)

O_NOCTTY (dans le module os)

O_NOFOLLOW (dans le module os)

O_NOINHERIT (dans le module os)

O_NONBLOCK (dans le module os)

O_PATH (dans le module os)

O_RANDOM (dans le module os)

O_RDONLY (dans le module os)

O_RDWR (dans le module os)

O_RSYNC (dans le module os)

O_SEQUENTIAL (dans le module os)

O_SHLOCK (dans le module os)

O_SHORT_LIVED (dans le module os)

O_SYNC (dans le module os)

O_TEMPORARY (dans le module os)

O_TEXT (dans le module os)

O_TMPFILE (dans le module os)

O_TRUNC (dans le module os)

O_WRONLY (dans le module os)

obj (attribut memoryview)

object

code, [1], [2], [3]

deallocation

finalization

immutable, [1]

numeric

object (attribut UnicodeError)

(classe de base)

object.__slots__ (variable de base)

object_filenames() (méthode distutils.ccompiler.CCompiler)

objects

comparing

flattening

marshalling

persistent

pickling

serializing

objet

asynchronous-generator

Boolean, [1]

built-in function, [1]

built-in method, [1]

bytearray, [1], [2], [3]

bytes, [1], [2]

callable, [1]

Capsule

class, [1], [2]

class instance, [1], [2]

complex

complex number, [1]

dictionary, [1], [2], [3], [4], [5], [6], [7]

Ellipsis

file, [1]

floating point, [1], [2]

frame

frozenset, [1]

function, [1], [2], [3], [4], [5]

generator, [1], [2]

immutable

immutable sequence

instance, [1], [2]

instancemethod

integer, [1], [2]

io.StringIO

list, [1], [2], [3], [4], [5], [6], [7], [8]

long integer

mapping, [1], [2], [3], [4], [5]

memoryview, [1]

method, [1], [2], [3], [4], [5]

module, [1], [2]

mutable, [1], [2]

mutable sequence

None, [1], [2]

NotImplemented

numeric, [1], [2], [3]

range

sequence, [1], [2], [3], [4], [5], [6], [7], [8]

set, [1], [2], [3]

set type

slice

socket

string, [1], [2]

traceback, [1], [2], [3], [4]

tuple, [1], [2], [3], [4], [5], [6]

type, [1], [2]

user-defined function, [1], [2]

user-defined method

objet fichier

objet fichier-compatible

objet octet-compatible

objet simili-chemin

obufcount() (méthode ossaudiodev.oss_audio_device)

obuffree() (méthode ossaudiodev.oss_audio_device)

oct() (fonction de base)

octal

literals

octal literal

octdigits (dans le module string)

offset (attribut traceback.TracebackException)

(attribut xml.parsers.expat.ExpatError)

OK (dans le module curses)

OleDLL (classe dans ctypes)

onclick() (dans le module turtle), [1]

ondrag() (dans le module turtle)

onecmd() (méthode cmd.Cmd)

onkey() (dans le module turtle)

onkeypress() (dans le module turtle)

onkeyrelease() (dans le module turtle)

onrelease() (dans le module turtle)

onscreenclick() (dans le module turtle)

ontimer() (dans le module turtle)

OP (dans le module token)

OP_ALL (dans le module ssl)

OP_CIPHER_SERVER_PREFERENCE (dans le module ssl)

OP_ENABLE_MIDDLEBOX_COMPAT (dans le module ssl)

OP_NO_COMPRESSION (dans le module ssl)

OP_NO_SSLv2 (dans le module ssl)

OP_NO_SSLv3 (dans le module ssl)

OP_NO_TICKET (dans le module ssl)

OP_NO_TLSv1 (dans le module ssl)

OP_NO_TLSv1_1 (dans le module ssl)

OP_NO_TLSv1_2 (dans le module ssl)

OP_NO_TLSv1_3 (dans le module ssl)

OP_SINGLE_DH_USE (dans le module ssl)

OP_SINGLE_ECDH_USE (dans le module ssl)

open

fonction de base, [1]

open() (dans le module aifc)

(dans le module bz2)

(dans le module codecs)

(dans le module dbm)

(dans le module dbm.dumb)

(dans le module dbm.gnu)

(dans le module dbm.ndbm)

(dans le module gzip)

(dans le module io)

(dans le module lzma)

(dans le module os)

(dans le module ossaudiodev)

(dans le module shelve)

(dans le module sunau)

(dans le module tarfile)

(dans le module tokenize)

(dans le module wave)

(dans le module webbrowser)

(fonction de base)

(méthode de la classe tarfile.TarFile)

(méthode distutils.text_file.TextFile)

(méthode imaplib.IMAP4)

(méthode pathlib.Path)

(méthode pipes.Template)

(méthode telnetlib.Telnet)

(méthode urllib.request.OpenerDirector)

(méthode urllib.request.URLopener)

(méthode webbrowser.controller)

(méthode zipfile.ZipFile)

open_connection() (dans le module asyncio)

open_new() (dans le module webbrowser)

(méthode webbrowser.controller)

open_new_tab() (dans le module webbrowser)

(méthode webbrowser.controller)

open_osfhandle() (dans le module msvcrt)

open_unix_connection() (dans le module asyncio)

open_unknown() (méthode urllib.request.URLopener)

OpenDatabase() (dans le module msilib)

OpenerDirector (classe dans urllib.request)

openfp() (dans le module sunau)

(dans le module wave)

OpenKey() (dans le module winreg)

OpenKeyEx() (dans le module winreg)

openlog() (dans le module syslog)

openmixer() (dans le module ossaudiodev)

openpty() (dans le module os)

(dans le module pty)

OpenSSL

(use in module hashlib)

(use in module ssl)

OPENSSL_VERSION (dans le module ssl)

OPENSSL_VERSION_INFO (dans le module ssl)

OPENSSL_VERSION_NUMBER (dans le module ssl)

OpenView() (méthode msilib.Database)

operation

binary arithmetic

binary bitwise

Boolean

concatenation

null, [1]

power

repetition

shifting

slice

subscript

unary arithmetic

unary bitwise

OperationalError

operations

bitwise

Boolean, [1]

masking

shifting

operations on

dictionary type

integer types

list type

mapping types

numeric types

sequence types, [1]

operator

+ (plus), [1], [2]

- (minus), [1], [2]

comparison

overloading

precedence

ternary

operator (2to3 fixer)

(module)

operators

opérateur

!=, [1]

% (percent), [1]

& (ampersand), [1]

* (asterisk), [1]

**, [1]

/ (slash), [1]

//, [1]

< (less), [1]

<<, [1]

<=, [1]

==, [1]

> (greater), [1]

>=, [1]

>>, [1]

@ (at)

^ (caret), [1]

| (vertical bar), [1]

~ (tilde), [1]

and, [1], [2]

in, [1], [2]

is, [1]

is not, [1]

not, [1]

not in, [1], [2]

or, [1], [2]

opmap (dans le module dis)

opname (dans le module dis)

optimize() (dans le module pickletools)

OPTIMIZED_BYTECODE_SUFFIXES (dans le module importlib.machinery)

Optional (dans le module typing)

OptionGroup (classe dans optparse)

OptionMenu (classe dans tkinter.tix)

OptionParser (classe dans optparse)

options (attribut doctest.Example)

(attribut ssl.SSLContext)

Options (classe dans ssl)

options() (méthode configparser.ConfigParser)

optionxform() (méthode configparser.ConfigParser), [1]

optparse (module)

or

bitwise

exclusive

inclusive

opérateur, [1], [2]

or_() (dans le module operator)

ord

fonction de base

ord() (fonction de base)

order

evaluation

ordered_attributes (attribut xml.parsers.expat.xmlparser)

OrderedDict (classe dans collections)

ordre de résolution des méthodes

origin (attribut importlib.machinery.ModuleSpec)

origin_req_host (attribut urllib.request.Request)

origin_server (attribut wsgiref.handlers.BaseHandler)

os

module

os (module)

os.path (module)

os_environ (attribut wsgiref.handlers.BaseHandler)

OSError

ossaudiodev (module)

OSSAudioError

outfile

json.tool command line option

output

standard

output (attribut subprocess.CalledProcessError)

(attribut subprocess.TimeoutExpired)

(attribut unittest.TestCase)

output() (méthode http.cookies.BaseCookie)

(méthode http.cookies.Morsel)

output_charset (attribut email.charset.Charset)

output_charset() (méthode gettext.NullTranslations)

output_codec (attribut email.charset.Charset)

output_difference() (méthode doctest.OutputChecker)

OutputChecker (classe dans doctest)

OutputString() (méthode http.cookies.Morsel)

over() (méthode nntplib.NNTP)

Overflow (classe dans decimal)

OverflowError

(built-in exception), [1], [2], [3], [4], [5]

overlaps() (méthode ipaddress.IPv4Network)

(méthode ipaddress.IPv6Network)

overlay() (méthode curses.window)

overload() (dans le module typing)

overloading

operator

overwrite() (méthode curses.window)

owner() (méthode pathlib.Path)

P

p (pdb command)

P_ALL (dans le module os)

P_DETACH (dans le module os)

P_NOWAIT (dans le module os)

P_NOWAITO (dans le module os)

P_OVERLAY (dans le module os)

P_PGID (dans le module os)

P_PID (dans le module os)

P_WAIT (dans le module os)

pack() (dans le module struct)

(méthode mailbox.MH)

(méthode struct.Struct)

pack_array() (méthode xdrlib.Packer)

pack_bytes() (méthode xdrlib.Packer)

pack_double() (méthode xdrlib.Packer)

pack_farray() (méthode xdrlib.Packer)

pack_float() (méthode xdrlib.Packer)

pack_fopaque() (méthode xdrlib.Packer)

pack_fstring() (méthode xdrlib.Packer)

pack_into() (dans le module struct)

(méthode struct.Struct)

pack_list() (méthode xdrlib.Packer)

pack_opaque() (méthode xdrlib.Packer)

pack_string() (méthode xdrlib.Packer)

package, [1]

namespace

portion

regular

package variable

__all__

packed (attribut ipaddress.IPv4Address)

(attribut ipaddress.IPv6Address)

Packer (classe dans xdrlib)

packing

binary data

packing (widgets)

PAGER

pair_content() (dans le module curses)

pair_number() (dans le module curses)

PanedWindow (classe dans tkinter.tix)

paquet

paquet classique

paquet provisoire

paquet-espace de nommage

parameter

call semantics

difference from argument

function definition

value, default

Parameter (classe dans inspect)

ParameterizedMIMEHeader (classe dans email.headerregistry)

parameters (attribut inspect.Signature)

paramètre

params (attribut email.headerregistry.ParameterizedMIMEHeader)

pardir (dans le module os)

paren (2to3 fixer)

parent (attribut importlib.machinery.ModuleSpec)

(attribut urllib.request.BaseHandler)

parent() (méthode tkinter.ttk.Treeview)

parenthesized form

parentNode (attribut xml.dom.Node)

parents (attribut collections.ChainMap)

paretovariate() (dans le module random)

parse() (dans le module ast)

(dans le module cgi)

(dans le module xml.dom.minidom)

(dans le module xml.dom.pulldom)

(dans le module xml.etree.ElementTree)

(dans le module xml.sax)

(méthode doctest.DocTestParser)

(méthode email.parser.BytesParser)

(méthode email.parser.Parser)

(méthode string.Formatter)

(méthode urllib.robotparser.RobotFileParser)

(méthode xml.etree.ElementTree.ElementTree)

Parse() (méthode xml.parsers.expat.xmlparser)

parse() (méthode xml.sax.xmlreader.XMLReader)

parse_and_bind() (dans le module readline)

parse_args() (méthode argparse.ArgumentParser)

PARSE_COLNAMES (dans le module sqlite3)

parse_config_h() (dans le module sysconfig)

PARSE_DECLTYPES (dans le module sqlite3)

parse_header() (dans le module cgi)

parse_known_args() (méthode argparse.ArgumentParser)

parse_multipart() (dans le module cgi)

parse_qs() (dans le module cgi)

(dans le module urllib.parse)

parse_qsl() (dans le module cgi)

(dans le module urllib.parse)

parseaddr() (dans le module email.utils)

parsebytes() (méthode email.parser.BytesParser)

parsedate() (dans le module email.utils)

parsedate_to_datetime() (dans le module email.utils)

parsedate_tz() (dans le module email.utils)

ParseError (classe dans xml.etree.ElementTree)

ParseFile() (méthode xml.parsers.expat.xmlparser)

ParseFlags() (dans le module imaplib)

parser

Parser (classe dans email.parser)

parser (module)

ParserCreate() (dans le module xml.parsers.expat)

ParserError

ParseResult (classe dans urllib.parse)

ParseResultBytes (classe dans urllib.parse)

parsestr() (méthode email.parser.Parser)

parseString() (dans le module xml.dom.minidom)

(dans le module xml.dom.pulldom)

(dans le module xml.sax)

parsing

Python source code

URL

ParsingError

partial (attribut asyncio.IncompleteReadError)

partial() (dans le module functools)

(méthode imaplib.IMAP4)

partialmethod (classe dans functools)

parties (attribut threading.Barrier)

partition() (méthode bytearray)

(méthode bytes)

(méthode str)

pass

état

pass_() (méthode poplib.POP3)

Paste

patch() (dans le module unittest.mock)

patch.dict() (dans le module unittest.mock)

patch.multiple() (dans le module unittest.mock)

patch.object() (dans le module unittest.mock)

patch.stopall() (dans le module unittest.mock)

PATH, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20], [21], [22], [23], [24], [25], [26], [27], [28], [29], [30], [31], [32], [33], [34]

path

configuration file

hooks

module search, [1], [2], [3], [4], [5], [6], [7]

operations, [1]

path (attribut http.cookiejar.Cookie)

(attribut http.server.BaseHTTPRequestHandler)

(attribut importlib.abc.FileLoader)

(attribut importlib.machinery.ExtensionFileLoader)

(attribut importlib.machinery.FileFinder)

(attribut importlib.machinery.SourceFileLoader)

(attribut importlib.machinery.SourcelessFileLoader)

(attribut os.DirEntry)

Path (classe dans pathlib)

path (dans le module sys)

(in module sys), [1], [2], [3]

path based finder

Path browser

path hooks

path_hook() (méthode de la classe importlib.machinery.FileFinder)

path_hooks (dans le module sys)

path_importer_cache (dans le module sys)

path_mtime() (méthode importlib.abc.SourceLoader)

path_return_ok() (méthode http.cookiejar.CookiePolicy)

path_stats() (méthode importlib.abc.SourceLoader)

(méthode importlib.machinery.SourceFileLoader)

pathconf() (dans le module os)

pathconf_names (dans le module os)

PathEntryFinder (classe dans importlib.abc)

PATHEXT, [1]

PathFinder (classe dans importlib.machinery)

pathlib (module)

PathLike (classe dans os)

pathname2url() (dans le module urllib.request)

pathsep (dans le module os)

pattern (attribut re.error)

(attribut re.regex)

Pattern (classe dans typing)

pause() (dans le module signal)

pause_reading() (méthode asyncio.ReadTransport)

pause_writing() (méthode asyncio.BaseProtocol)

PAX_FORMAT (dans le module tarfile)

pax_headers (attribut tarfile.TarFile)

(attribut tarfile.TarInfo)

pbkdf2_hmac() (dans le module hashlib)

pd() (dans le module turtle)

Pdb (class in pdb)

(classe dans pdb)

pdb (module)

peek() (méthode bz2.BZ2File)

(méthode gzip.GzipFile)

(méthode io.BufferedReader)

(méthode lzma.LZMAFile)

(méthode weakref.finalize)

peer (attribut smtpd.SMTPChannel)

PEM_cert_to_DER_cert() (dans le module ssl)

pen() (dans le module turtle)

pencolor() (dans le module turtle)

pending (attribut ssl.MemoryBIO)

pending() (méthode ssl.SSLSocket)

PendingDeprecationWarning

pendown() (dans le module turtle)

pensize() (dans le module turtle)

penup() (dans le module turtle)

PEP

PERCENT (dans le module token)

PERCENTEQUAL (dans le module token)

perf_counter() (dans le module time)

Performance

PermissionError

permutations() (dans le module itertools)

Persist() (méthode msilib.SummaryInformation)

persistence

persistent

objects

persistent_id (pickle protocol)

persistent_id() (méthode pickle.Pickler)

persistent_load (pickle protocol)

persistent_load() (méthode pickle.Unpickler)

PF_CAN (dans le module socket)

PF_PACKET (dans le module socket)

PF_RDS (dans le module socket)

pformat() (dans le module pprint)

(méthode pprint.PrettyPrinter)

phase() (dans le module cmath)

Philbrick, Geoff

physical line, [1], [2]

pi (dans le module cmath)

(dans le module math)

pickle

module, [1], [2], [3]

pickle (module)

pickle() (dans le module copyreg)

PickleError

Pickler (classe dans pickle)

pickletools (module)

pickletools command line option

--annotate

--indentlevel=<num>

--memo

--output=<file>

--preamble=<preamble>

-a

-l

-m

-o

-p

pickling

objects

PicklingError

pid (attribut asyncio.asyncio.subprocess.Process)

(attribut multiprocessing.Process)

(attribut subprocess.Popen)

PIPE (dans le module subprocess)

Pipe() (dans le module multiprocessing)

pipe() (dans le module os)

pipe2() (dans le module os)

PIPE_BUF (dans le module select)

pipe_connection_lost() (méthode asyncio.SubprocessProtocol)

pipe_data_received() (méthode asyncio.SubprocessProtocol)

pipes (module)

PKG_DIRECTORY (dans le module imp)

pkgutil (module)

placeholder (attribut textwrap.TextWrapper)

PLAT

platform (dans le module sys)

(in module sys)

(module)

platform() (dans le module platform)

PlaySound() (dans le module winsound)

plist

file

plistlib (module)

plock() (dans le module os)

plus

PLUS (dans le module token)

plus() (méthode decimal.Context)

PLUSEQUAL (dans le module token)

pm() (dans le module pdb)

point d'entrée pour la recherche dans path

POINTER() (dans le module ctypes)

pointer() (dans le module ctypes)

polar() (dans le module cmath)

Policy (classe dans email.policy)

poll() (dans le module select)

(méthode multiprocessing.connection.Connection)

(méthode select.devpoll)

(méthode select.epoll)

(méthode select.poll)

(méthode subprocess.Popen)

PollSelector (classe dans selectors)

Pool (classe dans multiprocessing.pool)

pop() (méthode array.array)

(méthode collections.deque)

(méthode dict)

(méthode frozenset)

(méthode mailbox.Mailbox)

(sequence method)

POP3

protocol

POP3 (classe dans poplib)

POP3_SSL (classe dans poplib)

pop_alignment() (méthode formatter.formatter)

pop_all() (méthode contextlib.ExitStack)

POP_BLOCK (opcode)

POP_EXCEPT (opcode)

pop_font() (méthode formatter.formatter)

POP_JUMP_IF_FALSE (opcode)

POP_JUMP_IF_TRUE (opcode)

pop_margin() (méthode formatter.formatter)

pop_source() (méthode shlex.shlex)

pop_style() (méthode formatter.formatter)

POP_TOP (opcode)

Popen (classe dans subprocess)

popen() (dans le module os)

(dans le module platform)

(in module os), [1]

popitem() (méthode collections.OrderedDict)

(méthode dict)

(méthode mailbox.Mailbox)

popleft() (méthode collections.deque)

poplib (module)

PopupMenu (classe dans tkinter.tix)

port (attribut http.cookiejar.Cookie)

port_specified (attribut http.cookiejar.Cookie)

portée imbriquée

portion

package

pos (attribut json.JSONDecodeError)

(attribut re.error)

(attribut re.match)

pos() (dans le module operator)

(dans le module turtle)

position (attribut xml.etree.ElementTree.ParseError)

position() (dans le module turtle)

POSIX

I/O control

threads

posix (module)

POSIX_FADV_DONTNEED (dans le module os)

POSIX_FADV_NOREUSE (dans le module os)

POSIX_FADV_NORMAL (dans le module os)

POSIX_FADV_RANDOM (dans le module os)

POSIX_FADV_SEQUENTIAL (dans le module os)

POSIX_FADV_WILLNEED (dans le module os)

posix_fadvise() (dans le module os)

posix_fallocate() (dans le module os)

POSIXLY_CORRECT

PosixPath (classe dans pathlib)

post() (méthode nntplib.NNTP)

(méthode ossaudiodev.oss_audio_device)

post_handshake_auth (attribut ssl.SSLContext)

post_mortem() (dans le module pdb)

post_setup() (méthode venv.EnvBuilder)

postcmd() (méthode cmd.Cmd)

postloop() (méthode cmd.Cmd)

pow

fonction de base, [1], [2], [3], [4], [5]

pow() (dans le module math)

(dans le module operator)

(fonction de base)

power

operation

power() (méthode decimal.Context)

pp (pdb command)

pprint (module)

pprint() (dans le module pprint)

(méthode pprint.PrettyPrinter)

prcal() (dans le module calendar)

pread() (dans le module os)

preamble (attribut email.message.EmailMessage)

(attribut email.message.Message)

precedence

operator

precmd() (méthode cmd.Cmd)

prefix, [1], [2], [3]

(attribut xml.dom.Attr)

(attribut xml.dom.Node)

(attribut zipimport.zipimporter)

PREFIX (dans le module distutils.sysconfig)

prefix (dans le module sys)

PREFIXES (dans le module site)

prefixlen (attribut ipaddress.IPv4Network)

(attribut ipaddress.IPv6Network)

preloop() (méthode cmd.Cmd)

prepare() (méthode logging.handlers.QueueHandler)

(méthode logging.handlers.QueueListener)

prepare_class() (dans le module types)

prepare_input_source() (dans le module xml.sax.saxutils)

prepend() (méthode pipes.Template)

preprocess() (méthode distutils.ccompiler.CCompiler)

PrettyPrinter (classe dans pprint)

prev() (méthode tkinter.ttk.Treeview)

previousSibling (attribut xml.dom.Node)

primary

print

fonction de base

print (2to3 fixer)

print() (built-in function)

__str__() (object method)

print() (fonction de base)

print_callees() (méthode pstats.Stats)

print_callers() (méthode pstats.Stats)

print_directory() (dans le module cgi)

print_environ() (dans le module cgi)

print_environ_usage() (dans le module cgi)

print_exc() (dans le module traceback)

(méthode timeit.Timer)

print_exception() (dans le module traceback)

PRINT_EXPR (opcode)

print_form() (dans le module cgi)

print_help() (méthode argparse.ArgumentParser)

print_last() (dans le module traceback)

print_stack() (dans le module traceback)

(méthode asyncio.Task)

print_stats() (méthode profile.Profile)

(méthode pstats.Stats)

print_tb() (dans le module traceback)

print_usage() (méthode argparse.ArgumentParser)

(méthode optparse.OptionParser)

print_version() (méthode optparse.OptionParser)

printable (dans le module string)

printdir() (méthode zipfile.ZipFile)

printf-style formatting, [1]

PRIO_PGRP (dans le module os)

PRIO_PROCESS (dans le module os)

PRIO_USER (dans le module os)

PriorityQueue (classe dans asyncio)

(classe dans queue)

private

names

prlimit() (dans le module resource)

prmonth() (dans le module calendar)

(méthode calendar.TextCalendar)

ProactorEventLoop (classe dans asyncio)

procedure

call

process

group, [1]

id

id of parent

killing, [1]

scheduling priority, [1]

signalling, [1]

Process (classe dans multiprocessing)

process() (méthode logging.LoggerAdapter)

process_exited() (méthode asyncio.SubprocessProtocol)

process_message() (méthode smtpd.SMTPServer)

process_request() (méthode socketserver.BaseServer)

process_time() (dans le module time)

process_tokens() (dans le module tabnanny)

ProcessError

processes, light-weight

ProcessingInstruction() (dans le module xml.etree.ElementTree)

processingInstruction() (méthode xml.sax.handler.ContentHandler)

ProcessingInstructionHandler() (méthode xml.parsers.expat.xmlparser)

ProcessLookupError

processor time

processor() (dans le module platform)

ProcessPoolExecutor (classe dans concurrent.futures)

product() (dans le module itertools)

Profile (classe dans profile)

profile (module)

profile function, [1], [2]

profiler, [1]

profiling, deterministic

program

ProgrammingError

Progressbar (classe dans tkinter.ttk)

prompt (attribut cmd.Cmd)

prompt_user_passwd() (méthode urllib.request.FancyURLopener)

prompts, interpreter

propagate (attribut logging.Logger)

property (classe de base)

property list

property_declaration_handler (dans le module xml.sax.handler)

property_dom_node (dans le module xml.sax.handler)

property_lexical_handler (dans le module xml.sax.handler)

property_xml_string (dans le module xml.sax.handler)

PropertyMock (classe dans unittest.mock)

prot_c() (méthode ftplib.FTP_TLS)

prot_p() (méthode ftplib.FTP_TLS)

proto (attribut socket.socket)

protocol

CGI

context management

copy

FTP, [1]

HTTP, [1], [2], [3], [4], [5]

IMAP4

IMAP4_SSL

IMAP4_stream

iterator

NNTP

POP3

SMTP

Telnet

protocol (attribut ssl.SSLContext)

Protocol (classe dans asyncio)

PROTOCOL_SSLv2 (dans le module ssl)

PROTOCOL_SSLv23 (dans le module ssl)

PROTOCOL_SSLv3 (dans le module ssl)

PROTOCOL_TLS (dans le module ssl)

PROTOCOL_TLS_CLIENT (dans le module ssl)

PROTOCOL_TLS_SERVER (dans le module ssl)

PROTOCOL_TLSv1 (dans le module ssl)

PROTOCOL_TLSv1_1 (dans le module ssl)

PROTOCOL_TLSv1_2 (dans le module ssl)

protocol_version (attribut http.server.BaseHTTPRequestHandler)

PROTOCOL_VERSION (attribut imaplib.IMAP4)

ProtocolError (classe dans xmlrpc.client)

proxy() (dans le module weakref)

proxyauth() (méthode imaplib.IMAP4)

ProxyBasicAuthHandler (classe dans urllib.request)

ProxyDigestAuthHandler (classe dans urllib.request)

ProxyHandler (classe dans urllib.request)

ProxyType (dans le module weakref)

ProxyTypes (dans le module weakref)

pryear() (méthode calendar.TextCalendar)

ps1 (dans le module sys)

ps2 (dans le module sys)

pstats (module)

pstdev() (dans le module statistics)

pthread_kill() (dans le module signal)

pthread_sigmask() (dans le module signal)

pthreads

pty

module

pty (module)

pu() (dans le module turtle)

publicId (attribut xml.dom.DocumentType)

PullDom (classe dans xml.dom.pulldom)

punctuation (dans le module string)

punctuation_chars (attribut shlex.shlex)

PurePath (classe dans pathlib)

PurePath.anchor (dans le module pathlib)

PurePath.drive (dans le module pathlib)

PurePath.name (dans le module pathlib)

PurePath.parent (dans le module pathlib)

PurePath.parents (dans le module pathlib)

PurePath.parts (dans le module pathlib)

PurePath.root (dans le module pathlib)

PurePath.stem (dans le module pathlib)

PurePath.suffix (dans le module pathlib)

PurePath.suffixes (dans le module pathlib)

PurePosixPath (classe dans pathlib)

PureProxy (classe dans smtpd)

PureWindowsPath (classe dans pathlib)

purge() (dans le module re)

Purpose.CLIENT_AUTH (dans le module ssl)

Purpose.SERVER_AUTH (dans le module ssl)

push() (méthode asynchat.async_chat)

(méthode code.InteractiveConsole)

(méthode contextlib.ExitStack)

push_alignment() (méthode formatter.formatter)

push_font() (méthode formatter.formatter)

push_margin() (méthode formatter.formatter)

push_source() (méthode shlex.shlex)

push_style() (méthode formatter.formatter)

push_token() (méthode shlex.shlex)

push_with_producer() (méthode asynchat.async_chat)

pushbutton() (méthode msilib.Dialog)

put() (méthode asyncio.Queue)

(méthode multiprocessing.Queue)

(méthode multiprocessing.SimpleQueue)

(méthode queue.Queue)

put_nowait() (méthode asyncio.Queue)

(méthode multiprocessing.Queue)

(méthode queue.Queue)

putch() (dans le module msvcrt)

putenv() (dans le module os)

putheader() (méthode http.client.HTTPConnection)

putp() (dans le module curses)

putrequest() (méthode http.client.HTTPConnection)

putwch() (dans le module msvcrt)

putwin() (méthode curses.window)

pvariance() (dans le module statistics)

pwd

module

pwd (module)

pwd() (méthode ftplib.FTP)

pwrite() (dans le module os)

Py_AddPendingCall (fonction C)

Py_AddPendingCall()

Py_AtExit (fonction C)

Py_BEGIN_ALLOW_THREADS

(macro C)

Py_BLOCK_THREADS (macro C)

Py_buffer (type C)

Py_buffer.buf (membre C)

Py_buffer.format (membre C)

Py_buffer.internal (membre C)

Py_buffer.itemsize (membre C)

Py_buffer.len (membre C)

Py_buffer.ndim (membre C)

Py_buffer.obj (membre C)

Py_buffer.readonly (membre C)

Py_buffer.shape (membre C)

Py_buffer.strides (membre C)

Py_buffer.suboffsets (membre C)

Py_BuildValue (fonction C)

Py_CLEAR (fonction C)

py_compile (module)

PY_COMPILED (dans le module imp)

Py_CompileString (fonction C)

Py_CompileString(), [1], [2]

Py_CompileStringExFlags (fonction C)

Py_CompileStringFlags (fonction C)

Py_CompileStringObject (fonction C)

Py_complex (type C)

Py_DecodeLocale (fonction C)

Py_DECREF (fonction C)

Py_DECREF()

Py_Ellipsis (variable C)

Py_EncodeLocale (fonction C)

Py_END_ALLOW_THREADS

(macro C)

Py_EndInterpreter (fonction C)

Py_EnterRecursiveCall (fonction C)

Py_eval_input (variable C)

Py_Exit (fonction C)

Py_False (variable C)

Py_FatalError (fonction C)

Py_FatalError()

Py_FdIsInteractive (fonction C)

Py_file_input (variable C)

Py_Finalize (fonction C)

Py_FinalizeEx (fonction C)

Py_FinalizeEx(), [1], [2], [3], [4]

PY_FROZEN (dans le module imp)

Py_GetBuildInfo (fonction C)

Py_GetCompiler (fonction C)

Py_GetCopyright (fonction C)

Py_GetExecPrefix (fonction C)

Py_GetExecPrefix()

Py_GetPath (fonction C)

Py_GetPath(), [1], [2]

Py_GetPlatform (fonction C)

Py_GetPrefix (fonction C)

Py_GetPrefix()

Py_GetProgramFullPath (fonction C)

Py_GetProgramFullPath()

Py_GetProgramName (fonction C)

Py_GetPythonHome (fonction C)

Py_GetVersion (fonction C)

Py_INCREF (fonction C)

Py_INCREF()

Py_Initialize (fonction C)

Py_Initialize(), [1], [2], [3]

Py_InitializeEx (fonction C)

Py_IsInitialized (fonction C)

Py_IsInitialized()

Py_LeaveRecursiveCall (fonction C)

Py_Main (fonction C)

Py_mod_create (variable C)

Py_mod_exec (variable C)

Py_NewInterpreter (fonction C)

Py_None (variable C)

Py_NotImplemented (variable C)

py_object (classe dans ctypes)

Py_PRINT_RAW

Py_REFCNT (macro C)

Py_ReprEnter (fonction C)

Py_ReprLeave (fonction C)

Py_RETURN_FALSE (macro C)

Py_RETURN_NONE (macro C)

Py_RETURN_NOTIMPLEMENTED (macro C)

Py_RETURN_TRUE (macro C)

Py_SetPath (fonction C)

Py_SetPath()

Py_SetProgramName (fonction C)

Py_SetProgramName(), [1], [2], [3]

Py_SetPythonHome (fonction C)

Py_SetStandardStreamEncoding (fonction C)

Py_single_input (variable C)

Py_SIZE (macro C)

PY_SOURCE (dans le module imp)

PY_SSIZE_T_MAX

Py_TPFLAGS_BASE_EXC_SUBCLASS (variable de base)

Py_TPFLAGS_BASETYPE (variable de base)

Py_TPFLAGS_BYTES_SUBCLASS (variable de base)

Py_TPFLAGS_DEFAULT (variable de base)

Py_TPFLAGS_DICT_SUBCLASS (variable de base)

Py_TPFLAGS_HAVE_FINALIZE (variable de base)

Py_TPFLAGS_HAVE_GC (variable de base)

Py_TPFLAGS_HEAPTYPE (variable de base)

Py_TPFLAGS_LIST_SUBCLASS (variable de base)

Py_TPFLAGS_LONG_SUBCLASS (variable de base)

Py_TPFLAGS_READY (variable de base)

Py_TPFLAGS_READYING (variable de base)

Py_TPFLAGS_TUPLE_SUBCLASS (variable de base)

Py_TPFLAGS_TYPE_SUBCLASS (variable de base)

Py_TPFLAGS_UNICODE_SUBCLASS (variable de base)

Py_tracefunc (type C)

Py_True (variable C)

Py_TYPE (macro C)

Py_UCS1 (type C)

Py_UCS2 (type C)

Py_UCS4 (type C)

Py_UNBLOCK_THREADS (macro C)

Py_UNICODE (type C)

Py_UNICODE_IS_HIGH_SURROGATE (macro C)

Py_UNICODE_IS_LOW_SURROGATE (macro C)

Py_UNICODE_IS_SURROGATE (macro C)

Py_UNICODE_ISALNUM (fonction C)

Py_UNICODE_ISALPHA (fonction C)

Py_UNICODE_ISDECIMAL (fonction C)

Py_UNICODE_ISDIGIT (fonction C)

Py_UNICODE_ISLINEBREAK (fonction C)

Py_UNICODE_ISLOWER (fonction C)

Py_UNICODE_ISNUMERIC (fonction C)

Py_UNICODE_ISPRINTABLE (fonction C)

Py_UNICODE_ISSPACE (fonction C)

Py_UNICODE_ISTITLE (fonction C)

Py_UNICODE_ISUPPER (fonction C)

Py_UNICODE_JOIN_SURROGATES (macro C)

Py_UNICODE_TODECIMAL (fonction C)

Py_UNICODE_TODIGIT (fonction C)

Py_UNICODE_TOLOWER (fonction C)

Py_UNICODE_TONUMERIC (fonction C)

Py_UNICODE_TOTITLE (fonction C)

Py_UNICODE_TOUPPER (fonction C)

Py_VaBuildValue (fonction C)

Py_VISIT (fonction C)

Py_XDECREF (fonction C)

Py_XDECREF()

Py_XINCREF (fonction C)

PyAnySet_Check (fonction C)

PyAnySet_CheckExact (fonction C)

PyArg_Parse (fonction C)

PyArg_ParseTuple (fonction C)

PyArg_ParseTuple()

PyArg_ParseTupleAndKeywords (fonction C)

PyArg_ParseTupleAndKeywords()

PyArg_UnpackTuple (fonction C)

PyArg_ValidateKeywordArguments (fonction C)

PyArg_VaParse (fonction C)

PyArg_VaParseTupleAndKeywords (fonction C)

PyASCIIObject (type C)

PyAsyncMethods (type C)

PyAsyncMethods.am_aiter (membre C)

PyAsyncMethods.am_anext (membre C)

PyAsyncMethods.am_await (membre C)

PyBool_Check (fonction C)

PyBool_FromLong (fonction C)

PyBUF_ANY_CONTIGUOUS (macro C)

PyBUF_C_CONTIGUOUS (macro C)

PyBUF_CONTIG (macro C)

PyBUF_CONTIG_RO (macro C)

PyBUF_F_CONTIGUOUS (macro C)

PyBUF_FORMAT (macro C)

PyBUF_FULL (macro C)

PyBUF_FULL_RO (macro C)

PyBUF_INDIRECT (macro C)

PyBUF_ND (macro C), [1]

PyBUF_RECORDS (macro C)

PyBUF_RECORDS_RO (macro C)

PyBUF_SIMPLE (macro C)

PyBUF_STRIDED (macro C)

PyBUF_STRIDED_RO (macro C)

PyBUF_STRIDES (macro C)

PyBUF_WRITABLE (macro C)

PyBuffer_FillContiguousStrides (fonction C)

PyBuffer_FillInfo (fonction C)

PyBuffer_IsContiguous (fonction C)

PyBuffer_Release (fonction C)

PyBuffer_SizeFromFormat (fonction C)

PyBuffer_ToContiguous (fonction C)

PyBufferProcs

(type C)

PyBufferProcs.bf_getbuffer (membre C)

PyBufferProcs.bf_releasebuffer (membre C)

PyByteArray_AS_STRING (fonction C)

PyByteArray_AsString (fonction C)

PyByteArray_Check (fonction C)

PyByteArray_CheckExact (fonction C)

PyByteArray_Concat (fonction C)

PyByteArray_FromObject (fonction C)

PyByteArray_FromStringAndSize (fonction C)

PyByteArray_GET_SIZE (fonction C)

PyByteArray_Resize (fonction C)

PyByteArray_Size (fonction C)

PyByteArray_Type (variable C)

PyByteArrayObject (type C)

PyBytes_AS_STRING (fonction C)

PyBytes_AsString (fonction C)

PyBytes_AsStringAndSize (fonction C)

PyBytes_Check (fonction C)

PyBytes_CheckExact (fonction C)

PyBytes_Concat (fonction C)

PyBytes_ConcatAndDel (fonction C)

PyBytes_FromFormat (fonction C)

PyBytes_FromFormatV (fonction C)

PyBytes_FromObject (fonction C)

PyBytes_FromString (fonction C)

PyBytes_FromStringAndSize (fonction C)

PyBytes_GET_SIZE (fonction C)

PyBytes_Size (fonction C)

PyBytes_Type (variable C)

PyBytesObject (type C)

PyCallable_Check (fonction C)

PyCallIter_Check (fonction C)

PyCallIter_New (fonction C)

PyCallIter_Type (variable C)

PyCapsule (type C)

PyCapsule_CheckExact (fonction C)

PyCapsule_Destructor (type C)

PyCapsule_GetContext (fonction C)

PyCapsule_GetDestructor (fonction C)

PyCapsule_GetName (fonction C)

PyCapsule_GetPointer (fonction C)

PyCapsule_Import (fonction C)

PyCapsule_IsValid (fonction C)

PyCapsule_New (fonction C)

PyCapsule_SetContext (fonction C)

PyCapsule_SetDestructor (fonction C)

PyCapsule_SetName (fonction C)

PyCapsule_SetPointer (fonction C)

PyCell_Check (fonction C)

PyCell_GET (fonction C)

PyCell_Get (fonction C)

PyCell_New (fonction C)

PyCell_SET (fonction C)

PyCell_Set (fonction C)

PyCell_Type (variable C)

PyCellObject (type C)

PyCFunction (type C)

PyCFunctionWithKeywords (type C)

pyclbr (module)

PyCode_Check (fonction C)

PyCode_GetNumFree (fonction C)

PyCode_New (fonction C)

PyCode_NewEmpty (fonction C)

PyCode_Type (variable C)

PyCodec_BackslashReplaceErrors (fonction C)

PyCodec_Decode (fonction C)

PyCodec_Decoder (fonction C)

PyCodec_Encode (fonction C)

PyCodec_Encoder (fonction C)

PyCodec_IgnoreErrors (fonction C)

PyCodec_IncrementalDecoder (fonction C)

PyCodec_IncrementalEncoder (fonction C)

PyCodec_KnownEncoding (fonction C)

PyCodec_LookupError (fonction C)

PyCodec_NameReplaceErrors (fonction C)

PyCodec_Register (fonction C)

PyCodec_RegisterError (fonction C)

PyCodec_ReplaceErrors (fonction C)

PyCodec_StreamReader (fonction C)

PyCodec_StreamWriter (fonction C)

PyCodec_StrictErrors (fonction C)

PyCodec_XMLCharRefReplaceErrors (fonction C)

PyCodeObject (type C)

PyCompactUnicodeObject (type C)

PyCompileError

PyCompilerFlags (type C)

PyComplex_AsCComplex (fonction C)

PyComplex_Check (fonction C)

PyComplex_CheckExact (fonction C)

PyComplex_FromCComplex (fonction C)

PyComplex_FromDoubles (fonction C)

PyComplex_ImagAsDouble (fonction C)

PyComplex_RealAsDouble (fonction C)

PyComplex_Type (variable C)

PyComplexObject (type C)

PyCoro_CheckExact (fonction C)

PyCoro_New (fonction C)

PyCoro_Type (variable C)

PyCoroObject (type C)

PyDate_Check (fonction C)

PyDate_CheckExact (fonction C)

PyDate_FromDate (fonction C)

PyDate_FromTimestamp (fonction C)

PyDateTime_Check (fonction C)

PyDateTime_CheckExact (fonction C)

PyDateTime_DATE_GET_HOUR (fonction C)

PyDateTime_DATE_GET_MICROSECOND (fonction C)

PyDateTime_DATE_GET_MINUTE (fonction C)

PyDateTime_DATE_GET_SECOND (fonction C)

PyDateTime_DELTA_GET_DAYS (fonction C)

PyDateTime_DELTA_GET_MICROSECONDS (fonction C)

PyDateTime_DELTA_GET_SECONDS (fonction C)

PyDateTime_FromDateAndTime (fonction C)

PyDateTime_FromTimestamp (fonction C)

PyDateTime_GET_DAY (fonction C)

PyDateTime_GET_MONTH (fonction C)

PyDateTime_GET_YEAR (fonction C)

PyDateTime_TIME_GET_HOUR (fonction C)

PyDateTime_TIME_GET_MICROSECOND (fonction C)

PyDateTime_TIME_GET_MINUTE (fonction C)

PyDateTime_TIME_GET_SECOND (fonction C)

PyDelta_Check (fonction C)

PyDelta_CheckExact (fonction C)

PyDelta_FromDSU (fonction C)

PyDescr_IsData (fonction C)

PyDescr_NewClassMethod (fonction C)

PyDescr_NewGetSet (fonction C)

PyDescr_NewMember (fonction C)

PyDescr_NewMethod (fonction C)

PyDescr_NewWrapper (fonction C)

PyDict_Check (fonction C)

PyDict_CheckExact (fonction C)

PyDict_Clear (fonction C)

PyDict_ClearFreeList (fonction C)

PyDict_Contains (fonction C)

PyDict_Copy (fonction C)

PyDict_DelItem (fonction C)

PyDict_DelItemString (fonction C)

PyDict_GetItem (fonction C)

PyDict_GetItemString (fonction C)

PyDict_GetItemWithError (fonction C)

PyDict_Items (fonction C)

PyDict_Keys (fonction C)

PyDict_Merge (fonction C)

PyDict_MergeFromSeq2 (fonction C)

PyDict_New (fonction C)

PyDict_Next (fonction C)

PyDict_SetDefault (fonction C)

PyDict_SetItem (fonction C)

PyDict_SetItemString (fonction C)

PyDict_Size (fonction C)

PyDict_Type (variable C)

PyDict_Update (fonction C)

PyDict_Values (fonction C)

PyDictObject (type C)

PyDictProxy_New (fonction C)

PyDLL (classe dans ctypes)

pydoc (module)

PyErr_BadArgument (fonction C)

PyErr_BadInternalCall (fonction C)

PyErr_CheckSignals (fonction C)

PyErr_Clear (fonction C)

PyErr_Clear(), [1]

PyErr_ExceptionMatches (fonction C)

PyErr_ExceptionMatches()

PyErr_Fetch (fonction C)

PyErr_Fetch()

PyErr_Format (fonction C)

PyErr_FormatV (fonction C)

PyErr_GetExcInfo (fonction C)

PyErr_GivenExceptionMatches (fonction C)

PyErr_NewException (fonction C)

PyErr_NewExceptionWithDoc (fonction C)

PyErr_NoMemory (fonction C)

PyErr_NormalizeException (fonction C)

PyErr_Occurred (fonction C)

PyErr_Occurred()

PyErr_Print (fonction C)

PyErr_PrintEx (fonction C)

PyErr_ResourceWarning (fonction C)

PyErr_Restore (fonction C)

PyErr_Restore()

PyErr_SetExcFromWindowsErr (fonction C)

PyErr_SetExcFromWindowsErrWithFilename (fonction C)

PyErr_SetExcFromWindowsErrWithFilenameObject (fonction C)

PyErr_SetExcFromWindowsErrWithFilenameObjects (fonction C)

PyErr_SetExcInfo (fonction C)

PyErr_SetFromErrno (fonction C)

PyErr_SetFromErrnoWithFilename (fonction C)

PyErr_SetFromErrnoWithFilenameObject (fonction C)

PyErr_SetFromErrnoWithFilenameObjects (fonction C)

PyErr_SetFromWindowsErr (fonction C)

PyErr_SetFromWindowsErrWithFilename (fonction C)

PyErr_SetImportError (fonction C)

PyErr_SetImportErrorSubclass (fonction C)

PyErr_SetInterrupt (fonction C)

PyErr_SetNone (fonction C)

PyErr_SetObject (fonction C)

PyErr_SetString (fonction C)

PyErr_SetString()

PyErr_SyntaxLocation (fonction C)

PyErr_SyntaxLocationEx (fonction C)

PyErr_SyntaxLocationObject (fonction C)

PyErr_WarnEx (fonction C)

PyErr_WarnExplicit (fonction C)

PyErr_WarnExplicitObject (fonction C)

PyErr_WarnFormat (fonction C)

PyErr_WriteUnraisable (fonction C)

PyEval_AcquireLock (fonction C)

PyEval_AcquireThread (fonction C)

PyEval_AcquireThread()

PyEval_EvalCode (fonction C)

PyEval_EvalCodeEx (fonction C)

PyEval_EvalFrame (fonction C)

PyEval_EvalFrameEx (fonction C)

PyEval_GetBuiltins (fonction C)

PyEval_GetCallStats (fonction C)

PyEval_GetFrame (fonction C)

PyEval_GetFuncDesc (fonction C)

PyEval_GetFuncName (fonction C)

PyEval_GetGlobals (fonction C)

PyEval_GetLocals (fonction C)

PyEval_InitThreads (fonction C)

PyEval_InitThreads()

PyEval_MergeCompilerFlags (fonction C)

PyEval_ReInitThreads (fonction C)

PyEval_ReleaseLock (fonction C)

PyEval_ReleaseThread (fonction C)

PyEval_ReleaseThread()

PyEval_RestoreThread (fonction C)

PyEval_RestoreThread(), [1]

PyEval_SaveThread (fonction C)

PyEval_SaveThread(), [1]

PyEval_SetProfile (fonction C)

PyEval_SetTrace (fonction C)

PyEval_ThreadsInitialized (fonction C)

PyExc_ArithmeticError

PyExc_AssertionError

PyExc_AttributeError

PyExc_BaseException

PyExc_BlockingIOError

PyExc_BrokenPipeError

PyExc_BufferError

PyExc_BytesWarning

PyExc_ChildProcessError

PyExc_ConnectionAbortedError

PyExc_ConnectionError

PyExc_ConnectionRefusedError

PyExc_ConnectionResetError

PyExc_DeprecationWarning

PyExc_EnvironmentError

PyExc_EOFError

PyExc_Exception

PyExc_FileExistsError

PyExc_FileNotFoundError

PyExc_FloatingPointError

PyExc_FutureWarning

PyExc_GeneratorExit

PyExc_ImportError

PyExc_ImportWarning

PyExc_IndentationError

PyExc_IndexError

PyExc_InterruptedError

PyExc_IOError

PyExc_IsADirectoryError

PyExc_KeyboardInterrupt

PyExc_KeyError

PyExc_LookupError

PyExc_MemoryError

PyExc_ModuleNotFoundError

PyExc_NameError

PyExc_NotADirectoryError

PyExc_NotImplementedError

PyExc_OSError

PyExc_OverflowError

PyExc_PendingDeprecationWarning

PyExc_PermissionError

PyExc_ProcessLookupError

PyExc_RecursionError

PyExc_ReferenceError

PyExc_ResourceWarning

PyExc_RuntimeError

PyExc_RuntimeWarning

PyExc_StopAsyncIteration

PyExc_StopIteration

PyExc_SyntaxError

PyExc_SyntaxWarning

PyExc_SystemError

PyExc_SystemExit

PyExc_TabError

PyExc_TimeoutError

PyExc_TypeError

PyExc_UnboundLocalError

PyExc_UnicodeDecodeError

PyExc_UnicodeEncodeError

PyExc_UnicodeError

PyExc_UnicodeTranslateError

PyExc_UnicodeWarning

PyExc_UserWarning

PyExc_ValueError

PyExc_Warning

PyExc_WindowsError

PyExc_ZeroDivisionError

PyException_GetCause (fonction C)

PyException_GetContext (fonction C)

PyException_GetTraceback (fonction C)

PyException_SetCause (fonction C)

PyException_SetContext (fonction C)

PyException_SetTraceback (fonction C)

pyexpat

module

PyFile_FromFd (fonction C)

PyFile_GetLine (fonction C)

PyFile_WriteObject (fonction C)

PyFile_WriteString (fonction C)

PyFloat_AS_DOUBLE (fonction C)

PyFloat_AsDouble (fonction C)

PyFloat_Check (fonction C)

PyFloat_CheckExact (fonction C)

PyFloat_ClearFreeList (fonction C)

PyFloat_FromDouble (fonction C)

PyFloat_FromString (fonction C)

PyFloat_GetInfo (fonction C)

PyFloat_GetMax (fonction C)

PyFloat_GetMin (fonction C)

PyFloat_Type (variable C)

PyFloatObject (type C)

PyFrame_GetLineNumber (fonction C)

PyFrameObject (type C)

PyFrozenSet_Check (fonction C)

PyFrozenSet_CheckExact (fonction C)

PyFrozenSet_New (fonction C)

PyFrozenSet_Type (variable C)

PyFunction_Check (fonction C)

PyFunction_GetAnnotations (fonction C)

PyFunction_GetClosure (fonction C)

PyFunction_GetCode (fonction C)

PyFunction_GetDefaults (fonction C)

PyFunction_GetGlobals (fonction C)

PyFunction_GetModule (fonction C)

PyFunction_New (fonction C)

PyFunction_NewWithQualName (fonction C)

PyFunction_SetAnnotations (fonction C)

PyFunction_SetClosure (fonction C)

PyFunction_SetDefaults (fonction C)

PyFunction_Type (variable C)

PyFunctionObject (type C)

PYFUNCTYPE() (dans le module ctypes)

PyGen_Check (fonction C)

PyGen_CheckExact (fonction C)

PyGen_New (fonction C)

PyGen_NewWithQualName (fonction C)

PyGen_Type (variable C)

PyGenObject (type C)

PyGetSetDef (type C)

PyGILState_Check (fonction C)

PyGILState_Ensure (fonction C)

PyGILState_GetThisThreadState (fonction C)

PyGILState_Release (fonction C)

PyImport_AddModule (fonction C)

PyImport_AddModuleObject (fonction C)

PyImport_AppendInittab (fonction C)

PyImport_Cleanup (fonction C)

PyImport_ExecCodeModule (fonction C)

PyImport_ExecCodeModuleEx (fonction C)

PyImport_ExecCodeModuleObject (fonction C)

PyImport_ExecCodeModuleWithPathnames (fonction C)

PyImport_ExtendInittab (fonction C)

PyImport_FrozenModules (variable C)

PyImport_GetImporter (fonction C)

PyImport_GetMagicNumber (fonction C)

PyImport_GetMagicTag (fonction C)

PyImport_GetModuleDict (fonction C)

PyImport_Import (fonction C)

PyImport_ImportFrozenModule (fonction C)

PyImport_ImportFrozenModuleObject (fonction C)

PyImport_ImportModule (fonction C)

PyImport_ImportModuleEx (fonction C)

PyImport_ImportModuleLevel (fonction C)

PyImport_ImportModuleLevelObject (fonction C)

PyImport_ImportModuleNoBlock (fonction C)

PyImport_ReloadModule (fonction C)

PyIndex_Check (fonction C)

PyInit_modulename (fonction C)

PyInstanceMethod_Check (fonction C)

PyInstanceMethod_Function (fonction C)

PyInstanceMethod_GET_FUNCTION (fonction C)

PyInstanceMethod_New (fonction C)

PyInstanceMethod_Type (variable C)

PyInterpreterState (type C)

PyInterpreterState_Clear (fonction C)

PyInterpreterState_Delete (fonction C)

PyInterpreterState_Head (fonction C)

PyInterpreterState_New (fonction C)

PyInterpreterState_Next (fonction C)

PyInterpreterState_ThreadHead (fonction C)

PyIter_Check (fonction C)

PyIter_Next (fonction C)

PyList_Append (fonction C)

PyList_AsTuple (fonction C)

PyList_Check (fonction C)

PyList_CheckExact (fonction C)

PyList_ClearFreeList (fonction C)

PyList_GET_ITEM (fonction C)

PyList_GET_SIZE (fonction C)

PyList_GetItem (fonction C)

PyList_GetItem()

PyList_GetSlice (fonction C)

PyList_Insert (fonction C)

PyList_New (fonction C)

PyList_Reverse (fonction C)

PyList_SET_ITEM (fonction C)

PyList_SetItem (fonction C)

PyList_SetItem()

PyList_SetSlice (fonction C)

PyList_Size (fonction C)

PyList_Sort (fonction C)

PyList_Type (variable C)

PyListObject (type C)

PyLong_AsDouble (fonction C)

PyLong_AsLong (fonction C)

PyLong_AsLongAndOverflow (fonction C)

PyLong_AsLongLong (fonction C)

PyLong_AsLongLongAndOverflow (fonction C)

PyLong_AsSize_t (fonction C)

PyLong_AsSsize_t (fonction C)

PyLong_AsUnsignedLong (fonction C)

PyLong_AsUnsignedLongLong (fonction C)

PyLong_AsUnsignedLongLongMask (fonction C)

PyLong_AsUnsignedLongMask (fonction C)

PyLong_AsVoidPtr (fonction C)

PyLong_Check (fonction C)

PyLong_CheckExact (fonction C)

PyLong_FromDouble (fonction C)

PyLong_FromLong (fonction C)

PyLong_FromLongLong (fonction C)

PyLong_FromSize_t (fonction C)

PyLong_FromSsize_t (fonction C)

PyLong_FromString (fonction C)

PyLong_FromUnicode (fonction C)

PyLong_FromUnicodeObject (fonction C)

PyLong_FromUnsignedLong (fonction C)

PyLong_FromUnsignedLongLong (fonction C)

PyLong_FromVoidPtr (fonction C)

PyLong_Type (variable C)

PyLongObject (type C)

PyMapping_Check (fonction C)

PyMapping_DelItem (fonction C)

PyMapping_DelItemString (fonction C)

PyMapping_GetItemString (fonction C)

PyMapping_HasKey (fonction C)

PyMapping_HasKeyString (fonction C)

PyMapping_Items (fonction C)

PyMapping_Keys (fonction C)

PyMapping_Length (fonction C)

PyMapping_SetItemString (fonction C)

PyMapping_Size (fonction C)

PyMapping_Values (fonction C)

PyMappingMethods (type C)

PyMappingMethods.mp_ass_subscript (membre C)

PyMappingMethods.mp_length (membre C)

PyMappingMethods.mp_subscript (membre C)

PyMarshal_ReadLastObjectFromFile (fonction C)

PyMarshal_ReadLongFromFile (fonction C)

PyMarshal_ReadObjectFromFile (fonction C)

PyMarshal_ReadObjectFromString (fonction C)

PyMarshal_ReadShortFromFile (fonction C)

PyMarshal_WriteLongToFile (fonction C)

PyMarshal_WriteObjectToFile (fonction C)

PyMarshal_WriteObjectToString (fonction C)

PyMem_Calloc (fonction C)

PyMem_Del (fonction C)

PYMEM_DOMAIN_MEM (variable C)

PYMEM_DOMAIN_OBJ (variable C)

PYMEM_DOMAIN_RAW (variable C)

PyMem_Free (fonction C)

PyMem_GetAllocator (fonction C)

PyMem_Malloc (fonction C)

PyMem_New (fonction C)

PyMem_RawCalloc (fonction C)

PyMem_RawFree (fonction C)

PyMem_RawMalloc (fonction C)

PyMem_RawRealloc (fonction C)

PyMem_Realloc (fonction C)

PyMem_Resize (fonction C)

PyMem_SetAllocator (fonction C)

PyMem_SetupDebugHooks (fonction C)

PyMemAllocatorDomain (type C)

PyMemAllocatorEx (type C)

PyMemberDef (type C)

PyMemoryView_Check (fonction C)

PyMemoryView_FromBuffer (fonction C)

PyMemoryView_FromMemory (fonction C)

PyMemoryView_FromObject (fonction C)

PyMemoryView_GET_BASE (fonction C)

PyMemoryView_GET_BUFFER (fonction C)

PyMemoryView_GetContiguous (fonction C)

PyMethod_Check (fonction C)

PyMethod_ClearFreeList (fonction C)

PyMethod_Function (fonction C)

PyMethod_GET_FUNCTION (fonction C)

PyMethod_GET_SELF (fonction C)

PyMethod_New (fonction C)

PyMethod_Self (fonction C)

PyMethod_Type (variable C)

PyMethodDef (type C)

PyModule_AddFunctions (fonction C)

PyModule_AddIntConstant (fonction C)

PyModule_AddIntMacro (fonction C)

PyModule_AddObject (fonction C)

PyModule_AddStringConstant (fonction C)

PyModule_AddStringMacro (fonction C)

PyModule_Check (fonction C)

PyModule_CheckExact (fonction C)

PyModule_Create (fonction C)

PyModule_Create2 (fonction C)

PyModule_ExecDef (fonction C)

PyModule_FromDefAndSpec (fonction C)

PyModule_FromDefAndSpec2 (fonction C)

PyModule_GetDef (fonction C)

PyModule_GetDict (fonction C)

PyModule_GetFilename (fonction C)

PyModule_GetFilenameObject (fonction C)

PyModule_GetName (fonction C)

PyModule_GetNameObject (fonction C)

PyModule_GetState (fonction C)

PyModule_New (fonction C)

PyModule_NewObject (fonction C)

PyModule_SetDocString (fonction C)

PyModule_Type (variable C)

PyModuleDef (type C)

PyModuleDef.m_base (membre C)

PyModuleDef.m_clear (membre C)

PyModuleDef.m_doc (membre C)

PyModuleDef.m_free (membre C)

PyModuleDef.m_methods (membre C)

PyModuleDef.m_name (membre C)

PyModuleDef.m_reload (membre C)

PyModuleDef.m_size (membre C)

PyModuleDef.m_slots (membre C)

PyModuleDef.m_traverse (membre C)

PyModuleDef_Init (fonction C)

PyModuleDef_Slot (type C)

PyModuleDef_Slot.slot (membre C)

PyModuleDef_Slot.value (membre C)

PyNumber_Absolute (fonction C)

PyNumber_Add (fonction C)

PyNumber_And (fonction C)

PyNumber_AsSsize_t (fonction C)

PyNumber_Check (fonction C)

PyNumber_Divmod (fonction C)

PyNumber_Float (fonction C)

PyNumber_FloorDivide (fonction C)

PyNumber_Index (fonction C)

PyNumber_InPlaceAdd (fonction C)

PyNumber_InPlaceAnd (fonction C)

PyNumber_InPlaceFloorDivide (fonction C)

PyNumber_InPlaceLshift (fonction C)

PyNumber_InPlaceMatrixMultiply (fonction C)

PyNumber_InPlaceMultiply (fonction C)

PyNumber_InPlaceOr (fonction C)

PyNumber_InPlacePower (fonction C)

PyNumber_InPlaceRemainder (fonction C)

PyNumber_InPlaceRshift (fonction C)

PyNumber_InPlaceSubtract (fonction C)

PyNumber_InPlaceTrueDivide (fonction C)

PyNumber_InPlaceXor (fonction C)

PyNumber_Invert (fonction C)

PyNumber_Long (fonction C)

PyNumber_Lshift (fonction C)

PyNumber_MatrixMultiply (fonction C)

PyNumber_Multiply (fonction C)

PyNumber_Negative (fonction C)

PyNumber_Or (fonction C)

PyNumber_Positive (fonction C)

PyNumber_Power (fonction C)

PyNumber_Remainder (fonction C)

PyNumber_Rshift (fonction C)

PyNumber_Subtract (fonction C)

PyNumber_ToBase (fonction C)

PyNumber_TrueDivide (fonction C)

PyNumber_Xor (fonction C)

PyNumberMethods (type C)

PyObject (type C)

PyObject._ob_next (membre C)

PyObject._ob_prev (membre C)

PyObject.ob_refcnt (membre C)

PyObject.ob_type (membre C)

PyObject_AsCharBuffer (fonction C)

PyObject_ASCII (fonction C)

PyObject_AsFileDescriptor (fonction C)

PyObject_AsReadBuffer (fonction C)

PyObject_AsWriteBuffer (fonction C)

PyObject_Bytes (fonction C)

PyObject_Call (fonction C)

PyObject_CallFunction (fonction C)

PyObject_CallFunctionObjArgs (fonction C)

PyObject_CallMethod (fonction C)

PyObject_CallMethodObjArgs (fonction C)

PyObject_CallObject (fonction C)

PyObject_CallObject()

PyObject_Calloc (fonction C)

PyObject_CheckBuffer (fonction C)

PyObject_CheckReadBuffer (fonction C)

PyObject_Del (fonction C)

PyObject_DelAttr (fonction C)

PyObject_DelAttrString (fonction C)

PyObject_DelItem (fonction C)

PyObject_Dir (fonction C)

PyObject_Free (fonction C)

PyObject_GC_Del (fonction C)

PyObject_GC_New (fonction C)

PyObject_GC_NewVar (fonction C)

PyObject_GC_Resize (fonction C)

PyObject_GC_Track (fonction C)

PyObject_GC_UnTrack (fonction C)

PyObject_GenericGetAttr (fonction C)

PyObject_GenericGetDict (fonction C)

PyObject_GenericSetAttr (fonction C)

PyObject_GenericSetDict (fonction C)

PyObject_GetArenaAllocator (fonction C)

PyObject_GetAttr (fonction C)

PyObject_GetAttrString (fonction C)

PyObject_GetBuffer (fonction C)

PyObject_GetItem (fonction C)

PyObject_GetIter (fonction C)

PyObject_HasAttr (fonction C)

PyObject_HasAttrString (fonction C)

PyObject_Hash (fonction C)

PyObject_HashNotImplemented (fonction C)

PyObject_HEAD (macro C)

PyObject_HEAD_INIT (macro C)

PyObject_Init (fonction C)

PyObject_InitVar (fonction C)

PyObject_IsInstance (fonction C)

PyObject_IsSubclass (fonction C)

PyObject_IsTrue (fonction C)

PyObject_Length (fonction C)

PyObject_LengthHint (fonction C)

PyObject_Malloc (fonction C)

PyObject_New (fonction C)

PyObject_NewVar (fonction C)

PyObject_Not (fonction C)

PyObject_Print (fonction C)

PyObject_Realloc (fonction C)

PyObject_Repr (fonction C)

PyObject_RichCompare (fonction C)

PyObject_RichCompareBool (fonction C)

PyObject_SetArenaAllocator (fonction C)

PyObject_SetAttr (fonction C)

PyObject_SetAttrString (fonction C)

PyObject_SetItem (fonction C)

PyObject_Size (fonction C)

PyObject_Str (fonction C)

PyObject_Type (fonction C)

PyObject_TypeCheck (fonction C)

PyObject_VAR_HEAD (macro C)

PyObjectArenaAllocator (type C)

PyOS_AfterFork (fonction C)

PyOS_CheckStack (fonction C)

PyOS_double_to_string (fonction C)

PyOS_FSPath (fonction C)

PyOS_getsig (fonction C)

PyOS_InputHook (variable C)

PyOS_ReadlineFunctionPointer (variable C)

PyOS_setsig (fonction C)

PyOS_snprintf (fonction C)

PyOS_stricmp (fonction C)

PyOS_string_to_double (fonction C)

PyOS_strnicmp (fonction C)

PyOS_vsnprintf (fonction C)

PyParser_SimpleParseFile (fonction C)

PyParser_SimpleParseFileFlags (fonction C)

PyParser_SimpleParseString (fonction C)

PyParser_SimpleParseStringFlags (fonction C)

PyParser_SimpleParseStringFlagsFilename (fonction C)

PyPI

(see Python Package Index (PyPI))

PyProperty_Type (variable C)

PyRun_AnyFile (fonction C)

PyRun_AnyFileEx (fonction C)

PyRun_AnyFileExFlags (fonction C)

PyRun_AnyFileFlags (fonction C)

PyRun_File (fonction C)

PyRun_FileEx (fonction C)

PyRun_FileExFlags (fonction C)

PyRun_FileFlags (fonction C)

PyRun_InteractiveLoop (fonction C)

PyRun_InteractiveLoopFlags (fonction C)

PyRun_InteractiveOne (fonction C)

PyRun_InteractiveOneFlags (fonction C)

PyRun_SimpleFile (fonction C)

PyRun_SimpleFileEx (fonction C)

PyRun_SimpleFileExFlags (fonction C)

PyRun_SimpleString (fonction C)

PyRun_SimpleStringFlags (fonction C)

PyRun_String (fonction C)

PyRun_StringFlags (fonction C)

PySeqIter_Check (fonction C)

PySeqIter_New (fonction C)

PySeqIter_Type (variable C)

PySequence_Check (fonction C)

PySequence_Concat (fonction C)

PySequence_Contains (fonction C)

PySequence_Count (fonction C)

PySequence_DelItem (fonction C)

PySequence_DelSlice (fonction C)

PySequence_Fast (fonction C)

PySequence_Fast_GET_ITEM (fonction C)

PySequence_Fast_GET_SIZE (fonction C)

PySequence_Fast_ITEMS (fonction C)

PySequence_GetItem (fonction C)

PySequence_GetItem()

PySequence_GetSlice (fonction C)

PySequence_Index (fonction C)

PySequence_InPlaceConcat (fonction C)

PySequence_InPlaceRepeat (fonction C)

PySequence_ITEM (fonction C)

PySequence_Length (fonction C)

PySequence_List (fonction C)

PySequence_Repeat (fonction C)

PySequence_SetItem (fonction C)

PySequence_SetSlice (fonction C)

PySequence_Size (fonction C)

PySequence_Tuple (fonction C)

PySequenceMethods (type C)

PySequenceMethods.sq_ass_item (membre C)

PySequenceMethods.sq_concat (membre C)

PySequenceMethods.sq_contains (membre C)

PySequenceMethods.sq_inplace_concat (membre C)

PySequenceMethods.sq_inplace_repeat (membre C)

PySequenceMethods.sq_item (membre C)

PySequenceMethods.sq_length (membre C)

PySequenceMethods.sq_repeat (membre C)

PySet_Add (fonction C)

PySet_Check (fonction C)

PySet_Clear (fonction C)

PySet_ClearFreeList (fonction C)

PySet_Contains (fonction C)

PySet_Discard (fonction C)

PySet_GET_SIZE (fonction C)

PySet_New (fonction C)

PySet_Pop (fonction C)

PySet_Size (fonction C)

PySet_Type (variable C)

PySetObject (type C)

PySignal_SetWakeupFd (fonction C)

PySlice_Check (fonction C)

PySlice_GetIndices (fonction C)

PySlice_GetIndicesEx (fonction C)

PySlice_New (fonction C)

PySlice_Type (variable C)

PyState_AddModule (fonction C)

PyState_FindModule (fonction C)

PyState_RemoveModule (fonction C)

PyStructSequence_Desc (type C)

PyStructSequence_Field (type C)

PyStructSequence_GET_ITEM (fonction C)

PyStructSequence_GetItem (fonction C)

PyStructSequence_InitType (fonction C)

PyStructSequence_InitType2 (fonction C)

PyStructSequence_New (fonction C)

PyStructSequence_NewType (fonction C)

PyStructSequence_SET_ITEM (fonction C)

PyStructSequence_SetItem (fonction C)

PyStructSequence_UnnamedField (variable C)

PySys_AddWarnOption (fonction C)

PySys_AddWarnOptionUnicode (fonction C)

PySys_AddXOption (fonction C)

PySys_FormatStderr (fonction C)

PySys_FormatStdout (fonction C)

PySys_GetObject (fonction C)

PySys_GetXOptions (fonction C)

PySys_ResetWarnOptions (fonction C)

PySys_SetArgv (fonction C)

PySys_SetArgv()

PySys_SetArgvEx (fonction C)

PySys_SetArgvEx(), [1]

PySys_SetObject (fonction C)

PySys_SetPath (fonction C)

PySys_WriteStderr (fonction C)

PySys_WriteStdout (fonction C)

Python 3000

Python Editor

Python Enhancement Proposals

PEP 1

PEP 100

PEP 11, [1], [2], [3]

PEP 205, [1]

PEP 207

PEP 208

PEP 217

PEP 218, [1], [2]

PEP 227, [1], [2]

PEP 229

PEP 230, [1]

PEP 232

PEP 234

PEP 235

PEP 236, [1]

PEP 237, [1], [2], [3], [4], [5]

PEP 238, [1], [2], [3], [4], [5]

PEP 241

PEP 243

PEP 247

PEP 249, [1], [2], [3]

PEP 252, [1]

PEP 253, [1], [2], [3], [4]

PEP 255, [1], [2], [3], [4], [5]

PEP 261, [1]

PEP 263, [1], [2], [3], [4], [5]

PEP 264

PEP 273, [1], [2]

PEP 274

PEP 275

PEP 277

PEP 278, [1]

PEP 279

PEP 282, [1], [2], [3]

PEP 285, [1]

PEP 288

PEP 289, [1], [2]

PEP 292, [1]

PEP 293

PEP 3000

PEP 301, [1]

PEP 302, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20], [21], [22], [23], [24], [25], [26]

PEP 305, [1]

PEP 307, [1], [2], [3]

PEP 308, [1], [2]

PEP 309

PEP 3100

PEP 3101, [1], [2], [3], [4]

PEP 3102

PEP 3104, [1]

PEP 3105, [1], [2]

PEP 3106

PEP 3107, [1], [2], [3]

PEP 3108, [1], [2]

PEP 3109, [1]

PEP 3110, [1], [2]

PEP 3111

PEP 3112, [1]

PEP 3113

PEP 3114

PEP 3115, [1], [2], [3]

PEP 3116, [1], [2]

PEP 3118, [1], [2], [3], [4], [5]

PEP 3119, [1], [2], [3], [4], [5]

PEP 3120, [1], [2]

PEP 3121, [1], [2]

PEP 3123

PEP 3127

PEP 3129, [1]

PEP 3131, [1], [2]

PEP 3132, [1]

PEP 3134, [1], [2]

PEP 3135, [1]

PEP 3137

PEP 3138

PEP 314, [1]

PEP 3141, [1], [2]

PEP 3144

PEP 3147, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20], [21]

PEP 3148, [1]

PEP 3149, [1]

PEP 3151, [1], [2], [3], [4], [5]

PEP 3153

PEP 3154, [1], [2]

PEP 3155, [1]

PEP 3156, [1], [2], [3], [4], [5]

PEP 318, [1], [2], [3]

PEP 322, [1]

PEP 324, [1]

PEP 325

PEP 327

PEP 328, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10]

PEP 331

PEP 333, [1]

PEP 3333, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14]

PEP 338, [1], [2], [3]

PEP 339

PEP 341

PEP 342, [1], [2], [3], [4], [5], [6]

PEP 343, [1], [2], [3], [4], [5], [6]

PEP 347

PEP 352, [1], [2]

PEP 353, [1], [2]

PEP 356

PEP 357

PEP 361

PEP 362, [1], [2], [3]

PEP 366, [1], [2], [3], [4], [5], [6]

PEP 370, [1], [2], [3], [4]

PEP 371

PEP 372, [1]

PEP 373

PEP 378, [1], [2]

PEP 380, [1], [2], [3]

PEP 383, [1], [2], [3], [4]

PEP 384, [1]

PEP 385

PEP 389, [1]

PEP 391, [1]

PEP 392

PEP 393, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10]

PEP 395

PEP 397, [1], [2], [3]

PEP 398

PEP 4

PEP 405, [1]

PEP 409

PEP 411, [1], [2], [3], [4]

PEP 412

PEP 414, [1]

PEP 418

PEP 420, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11]

PEP 421, [1], [2]

PEP 424, [1]

PEP 427

PEP 428, [1], [2]

PEP 429

PEP 434

PEP 435, [1], [2]

PEP 436, [1], [2]

PEP 441, [1]

PEP 442, [1], [2], [3], [4], [5], [6]

PEP 443, [1], [2]

PEP 445, [1], [2], [3]

PEP 446, [1], [2], [3]

PEP 448, [1], [2], [3], [4]

PEP 450, [1], [2]

PEP 451, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12]

PEP 453, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10]

PEP 454, [1], [2]

PEP 456, [1]

PEP 461, [1], [2]

PEP 465, [1], [2]

PEP 466, [1], [2], [3]

PEP 468, [1]

PEP 471, [1]

PEP 475, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20], [21], [22], [23], [24], [25], [26]

PEP 476

PEP 477

PEP 478

PEP 479, [1], [2]

PEP 483, [1]

PEP 484, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16]

PEP 485, [1], [2], [3]

PEP 486, [1]

PEP 487, [1], [2], [3]

PEP 488, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12]

PEP 489, [1], [2], [3], [4], [5], [6], [7], [8], [9]

PEP 492, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20]

PEP 493

PEP 494

PEP 495, [1]

PEP 498, [1], [2], [3]

PEP 5

PEP 506, [1]

PEP 511

PEP 515, [1], [2]

PEP 519, [1]

PEP 520

PEP 523, [1]

PEP 524, [1], [2], [3], [4], [5]

PEP 525, [1], [2], [3], [4], [5], [6]

PEP 526, [1], [2], [3], [4], [5], [6], [7]

PEP 528

PEP 529, [1], [2], [3], [4]

PEP 530, [1], [2]

PEP 628, [1]

PEP 7

PEP 8, [1], [2], [3], [4]

Python Package Index (PyPI)

.pypirc file

PYTHON*, [1], [2]

python.function.entry (fonction C)

python.function.return (fonction C)

python_branch() (dans le module platform)

python_build() (dans le module platform)

python_compiler() (dans le module platform)

PYTHON_DOM

python_implementation() (dans le module platform)

python_revision() (dans le module platform)

python_version() (dans le module platform)

python_version_tuple() (dans le module platform)

PYTHONASYNCIODEBUG, [1]

PYTHONCASEOK

PYTHONDEBUG

PYTHONDOCS

PYTHONDONDONTWRITEBYTECODE

PYTHONDONTWRITEBYTECODE, [1], [2], [3]

PYTHONDUMPREFS

PYTHONFAULTHANDLER, [1]

PYTHONHASHSEED, [1], [2], [3], [4]

PYTHONHOME, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13]

PYTHONINSPECT, [1]

PYTHONIOENCODING, [1], [2], [3], [4]

Pythonique

PYTHONLEGACYWINDOWSFSENCODING, [1]

PYTHONLEGACYWINDOWSSTDIO, [1]

PYTHONMALLOC, [1], [2], [3], [4], [5]

PYTHONMALLOCSTATS, [1]

PYTHONNOUSERSITE, [1], [2]

PYTHONOPTIMIZE

PYTHONPATH, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20], [21], [22]

PYTHONSHOWALLOCCOUNT

PYTHONSHOWREFCOUNT

PYTHONSTARTUP, [1], [2], [3], [4], [5], [6], [7], [8]

PYTHONTRACEMALLOC, [1], [2]

PYTHONUNBUFFERED

PYTHONUSERBASE, [1], [2]

PYTHONVERBOSE

PYTHONWARNINGS, [1], [2], [3]

PyThreadState, [1]

(type C)

PyThreadState_Clear (fonction C)

PyThreadState_Delete (fonction C)

PyThreadState_Get (fonction C)

PyThreadState_GetDict (fonction C)

PyThreadState_New (fonction C)

PyThreadState_Next (fonction C)

PyThreadState_SetAsyncExc (fonction C)

PyThreadState_Swap (fonction C)

PyTime_Check (fonction C)

PyTime_CheckExact (fonction C)

PyTime_FromTime (fonction C)

PyTrace_C_CALL (variable C)

PyTrace_C_EXCEPTION (variable C)

PyTrace_C_RETURN (variable C)

PyTrace_CALL (variable C)

PyTrace_EXCEPTION (variable C)

PyTrace_LINE (variable C)

PyTrace_RETURN (variable C)

PyTuple_Check (fonction C)

PyTuple_CheckExact (fonction C)

PyTuple_ClearFreeList (fonction C)

PyTuple_GET_ITEM (fonction C)

PyTuple_GET_SIZE (fonction C)

PyTuple_GetItem (fonction C)

PyTuple_GetSlice (fonction C)

PyTuple_New (fonction C)

PyTuple_Pack (fonction C)

PyTuple_SET_ITEM (fonction C)

PyTuple_SetItem (fonction C)

PyTuple_SetItem()

PyTuple_Size (fonction C)

PyTuple_Type (variable C)

PyTupleObject (type C)

PyType_Check (fonction C)

PyType_CheckExact (fonction C)

PyType_ClearCache (fonction C)

PyType_FromSpec (fonction C)

PyType_FromSpecWithBases (fonction C)

PyType_GenericAlloc (fonction C)

PyType_GenericNew (fonction C)

PyType_GetFlags (fonction C)

PyType_GetSlot (fonction C)

PyType_HasFeature (fonction C)

PyType_IS_GC (fonction C)

PyType_IsSubtype (fonction C)

PyType_Modified (fonction C)

PyType_Ready (fonction C)

PyType_Type (variable C)

PyTypeObject (type C)

PyTypeObject.tp_alloc (membre C)

PyTypeObject.tp_allocs (membre C)

PyTypeObject.tp_as_buffer (membre C)

PyTypeObject.tp_base (membre C)

PyTypeObject.tp_bases (membre C)

PyTypeObject.tp_basicsize (membre C)

PyTypeObject.tp_cache (membre C)

PyTypeObject.tp_call (membre C)

PyTypeObject.tp_clear (membre C)

PyTypeObject.tp_dealloc (membre C)

PyTypeObject.tp_descr_get (membre C)

PyTypeObject.tp_descr_set (membre C)

PyTypeObject.tp_dict (membre C)

PyTypeObject.tp_dictoffset (membre C)

PyTypeObject.tp_doc (membre C)

PyTypeObject.tp_finalize (membre C)

PyTypeObject.tp_flags (membre C)

PyTypeObject.tp_free (membre C)

PyTypeObject.tp_frees (membre C)

PyTypeObject.tp_getattr (membre C)

PyTypeObject.tp_getattro (membre C)

PyTypeObject.tp_getset (membre C)

PyTypeObject.tp_hash (membre C)

PyTypeObject.tp_init (membre C)

PyTypeObject.tp_is_gc (membre C)

PyTypeObject.tp_itemsize (membre C)

PyTypeObject.tp_iter (membre C)

PyTypeObject.tp_iternext (membre C)

PyTypeObject.tp_maxalloc (membre C)

PyTypeObject.tp_members (membre C)

PyTypeObject.tp_methods (membre C)

PyTypeObject.tp_mro (membre C)

PyTypeObject.tp_name (membre C)

PyTypeObject.tp_new (membre C)

PyTypeObject.tp_next (membre C)

PyTypeObject.tp_print (membre C)

PyTypeObject.tp_repr (membre C)

PyTypeObject.tp_richcompare (membre C)

PyTypeObject.tp_setattr (membre C)

PyTypeObject.tp_setattro (membre C)

PyTypeObject.tp_str (membre C)

PyTypeObject.tp_subclasses (membre C)

PyTypeObject.tp_traverse (membre C)

PyTypeObject.tp_weaklist (membre C)

PyTypeObject.tp_weaklistoffset (membre C)

PyTZInfo_Check (fonction C)

PyTZInfo_CheckExact (fonction C)

PyUnicode_1BYTE_DATA (fonction C)

PyUnicode_1BYTE_KIND (macro C)

PyUnicode_2BYTE_DATA (fonction C)

PyUnicode_2BYTE_KIND (macro C)

PyUnicode_4BYTE_DATA (fonction C)

PyUnicode_4BYTE_KIND (macro C)

PyUnicode_AS_DATA (fonction C)

PyUnicode_AS_UNICODE (fonction C)

PyUnicode_AsASCIIString (fonction C)

PyUnicode_AsCharmapString (fonction C)

PyUnicode_AsEncodedString (fonction C)

PyUnicode_AsLatin1String (fonction C)

PyUnicode_AsMBCSString (fonction C)

PyUnicode_AsRawUnicodeEscapeString (fonction C)

PyUnicode_AsUCS4 (fonction C)

PyUnicode_AsUCS4Copy (fonction C)

PyUnicode_AsUnicode (fonction C)

PyUnicode_AsUnicodeAndSize (fonction C)

PyUnicode_AsUnicodeCopy (fonction C)

PyUnicode_AsUnicodeEscapeString (fonction C)

PyUnicode_AsUTF16String (fonction C)

PyUnicode_AsUTF32String (fonction C)

PyUnicode_AsUTF8 (fonction C)

PyUnicode_AsUTF8AndSize (fonction C)

PyUnicode_AsUTF8String (fonction C)

PyUnicode_AsWideChar (fonction C)

PyUnicode_AsWideCharString (fonction C)

PyUnicode_Check (fonction C)

PyUnicode_CheckExact (fonction C)

PyUnicode_ClearFreeList (fonction C)

PyUnicode_Compare (fonction C)

PyUnicode_CompareWithASCIIString (fonction C)

PyUnicode_Concat (fonction C)

PyUnicode_Contains (fonction C)

PyUnicode_CopyCharacters (fonction C)

PyUnicode_Count (fonction C)

PyUnicode_DATA (fonction C)

PyUnicode_Decode (fonction C)

PyUnicode_DecodeASCII (fonction C)

PyUnicode_DecodeCharmap (fonction C)

PyUnicode_DecodeFSDefault (fonction C)

PyUnicode_DecodeFSDefaultAndSize (fonction C)

PyUnicode_DecodeLatin1 (fonction C)

PyUnicode_DecodeLocale (fonction C)

PyUnicode_DecodeLocaleAndSize (fonction C)

PyUnicode_DecodeMBCS (fonction C)

PyUnicode_DecodeMBCSStateful (fonction C)

PyUnicode_DecodeRawUnicodeEscape (fonction C)

PyUnicode_DecodeUnicodeEscape (fonction C)

PyUnicode_DecodeUTF16 (fonction C)

PyUnicode_DecodeUTF16Stateful (fonction C)

PyUnicode_DecodeUTF32 (fonction C)

PyUnicode_DecodeUTF32Stateful (fonction C)

PyUnicode_DecodeUTF7 (fonction C)

PyUnicode_DecodeUTF7Stateful (fonction C)

PyUnicode_DecodeUTF8 (fonction C)

PyUnicode_DecodeUTF8Stateful (fonction C)

PyUnicode_Encode (fonction C)

PyUnicode_EncodeASCII (fonction C)

PyUnicode_EncodeCharmap (fonction C)

PyUnicode_EncodeCodePage (fonction C)

PyUnicode_EncodeFSDefault (fonction C)

PyUnicode_EncodeLatin1 (fonction C)

PyUnicode_EncodeLocale (fonction C)

PyUnicode_EncodeMBCS (fonction C)

PyUnicode_EncodeRawUnicodeEscape (fonction C)

PyUnicode_EncodeUnicodeEscape (fonction C)

PyUnicode_EncodeUTF16 (fonction C)

PyUnicode_EncodeUTF32 (fonction C)

PyUnicode_EncodeUTF7 (fonction C)

PyUnicode_EncodeUTF8 (fonction C)

PyUnicode_Fill (fonction C)

PyUnicode_Find (fonction C)

PyUnicode_FindChar (fonction C)

PyUnicode_Format (fonction C)

PyUnicode_FromEncodedObject (fonction C)

PyUnicode_FromFormat (fonction C)

PyUnicode_FromFormatV (fonction C)

PyUnicode_FromKindAndData (fonction C)

PyUnicode_FromObject (fonction C)

PyUnicode_FromString (fonction C)

PyUnicode_FromString()

PyUnicode_FromStringAndSize (fonction C)

PyUnicode_FromUnicode (fonction C)

PyUnicode_FromWideChar (fonction C)

PyUnicode_FSConverter (fonction C)

PyUnicode_FSDecoder (fonction C)

PyUnicode_GET_DATA_SIZE (fonction C)

PyUnicode_GET_LENGTH (fonction C)

PyUnicode_GET_SIZE (fonction C)

PyUnicode_GetLength (fonction C)

PyUnicode_GetSize (fonction C)

PyUnicode_InternFromString (fonction C)

PyUnicode_InternInPlace (fonction C)

PyUnicode_Join (fonction C)

PyUnicode_KIND (fonction C)

PyUnicode_MAX_CHAR_VALUE (fonction C)

PyUnicode_New (fonction C)

PyUnicode_READ (fonction C)

PyUnicode_READ_CHAR (fonction C)

PyUnicode_ReadChar (fonction C)

PyUnicode_READY (fonction C)

PyUnicode_Replace (fonction C)

PyUnicode_RichCompare (fonction C)

PyUnicode_Split (fonction C)

PyUnicode_Splitlines (fonction C)

PyUnicode_Substring (fonction C)

PyUnicode_Tailmatch (fonction C)

PyUnicode_TransformDecimalToASCII (fonction C)

PyUnicode_Translate (fonction C), [1]

PyUnicode_TranslateCharmap (fonction C)

PyUnicode_Type (variable C)

PyUnicode_WCHAR_KIND (macro C)

PyUnicode_WRITE (fonction C)

PyUnicode_WriteChar (fonction C)

PyUnicodeDecodeError_Create (fonction C)

PyUnicodeDecodeError_GetEncoding (fonction C)

PyUnicodeDecodeError_GetEnd (fonction C)

PyUnicodeDecodeError_GetObject (fonction C)

PyUnicodeDecodeError_GetReason (fonction C)

PyUnicodeDecodeError_GetStart (fonction C)

PyUnicodeDecodeError_SetEnd (fonction C)

PyUnicodeDecodeError_SetReason (fonction C)

PyUnicodeDecodeError_SetStart (fonction C)

PyUnicodeEncodeError_Create (fonction C)

PyUnicodeEncodeError_GetEncoding (fonction C)

PyUnicodeEncodeError_GetEnd (fonction C)

PyUnicodeEncodeError_GetObject (fonction C)

PyUnicodeEncodeError_GetReason (fonction C)

PyUnicodeEncodeError_GetStart (fonction C)

PyUnicodeEncodeError_SetEnd (fonction C)

PyUnicodeEncodeError_SetReason (fonction C)

PyUnicodeEncodeError_SetStart (fonction C)

PyUnicodeObject (type C)

PyUnicodeTranslateError_Create (fonction C)

PyUnicodeTranslateError_GetEnd (fonction C)

PyUnicodeTranslateError_GetObject (fonction C)

PyUnicodeTranslateError_GetReason (fonction C)

PyUnicodeTranslateError_GetStart (fonction C)

PyUnicodeTranslateError_SetEnd (fonction C)

PyUnicodeTranslateError_SetReason (fonction C)

PyUnicodeTranslateError_SetStart (fonction C)

PyVarObject (type C)

PyVarObject.ob_size (membre C)

PyVarObject_HEAD_INIT (macro C)

PyWeakref_Check (fonction C)

PyWeakref_CheckProxy (fonction C)

PyWeakref_CheckRef (fonction C)

PyWeakref_GET_OBJECT (fonction C)

PyWeakref_GetObject (fonction C)

PyWeakref_NewProxy (fonction C)

PyWeakref_NewRef (fonction C)

PyWrapper_New (fonction C)

PyZipFile (classe dans zipfile)

Q

qiflush() (dans le module curses)

QName (classe dans xml.etree.ElementTree)

qsize() (méthode asyncio.Queue)

(méthode multiprocessing.Queue)

(méthode queue.Queue)

quantize() (méthode decimal.Context)

(méthode decimal.Decimal)

QueryInfoKey() (dans le module winreg)

QueryReflectionKey() (dans le module winreg)

QueryValue() (dans le module winreg)

QueryValueEx() (dans le module winreg)

queue (attribut sched.scheduler)

Queue (classe dans asyncio)

(classe dans multiprocessing)

(classe dans queue)

queue (module)

Queue() (méthode multiprocessing.managers.SyncManager)

QueueEmpty

QueueFull

QueueHandler (classe dans logging.handlers)

QueueListener (classe dans logging.handlers)

quick_ratio() (méthode difflib.SequenceMatcher)

quit (pdb command)

(variable de base)

quit() (méthode ftplib.FTP)

(méthode nntplib.NNTP)

(méthode poplib.POP3)

(méthode smtplib.SMTP)

quopri (module)

quote() (dans le module email.utils)

(dans le module shlex)

(dans le module urllib.parse)

QUOTE_ALL (dans le module csv)

quote_from_bytes() (dans le module urllib.parse)

QUOTE_MINIMAL (dans le module csv)

QUOTE_NONE (dans le module csv)

QUOTE_NONNUMERIC (dans le module csv)

quote_plus() (dans le module urllib.parse)

quoteattr() (dans le module xml.sax.saxutils)

quotechar (attribut csv.Dialect)

quoted-printable

encoding

quotes (attribut shlex.shlex)

quoting (attribut csv.Dialect)

R

r"

raw string literal

r'

raw string literal

R_OK (dans le module os)

radians() (dans le module math)

(dans le module turtle)

RadioButtonGroup (classe dans msilib)

radiogroup() (méthode msilib.Dialog)

radix() (méthode decimal.Context)

(méthode decimal.Decimal)

RADIXCHAR (dans le module locale)

raise

état, [1]

raise (2to3 fixer)

raise an exception

raise_on_defect (attribut email.policy.Policy)

RAISE_VARARGS (opcode)

raising

exception

ramasse-miettes

RAND_add() (dans le module ssl)

RAND_bytes() (dans le module ssl)

RAND_egd() (dans le module ssl)

RAND_pseudo_bytes() (dans le module ssl)

RAND_status() (dans le module ssl)

randbelow() (dans le module secrets)

randbits() (dans le module secrets)

randint() (dans le module random)

random (module)

random() (dans le module random)

randrange() (dans le module random)

range

fonction de base

objet

range (classe de base)

RARROW (dans le module token)

ratecv() (dans le module audioop)

ratio() (méthode difflib.SequenceMatcher)

Rational (classe dans numbers)

raw (attribut io.BufferedIOBase)

raw string

raw() (dans le module curses)

raw_data_manager (dans le module email.contentmanager)

raw_decode() (méthode json.JSONDecoder)

raw_input (2to3 fixer)

raw_input() (méthode code.InteractiveConsole)

RawArray() (dans le module multiprocessing.sharedctypes)

RawConfigParser (classe dans configparser)

RawDescriptionHelpFormatter (classe dans argparse)

RawIOBase (classe dans io)

RawPen (classe dans turtle)

RawTextHelpFormatter (classe dans argparse)

RawTurtle (classe dans turtle)

RawValue() (dans le module multiprocessing.sharedctypes)

RBRACE (dans le module token)

rcpttos (attribut smtpd.SMTPChannel)

re

module, [1]

re (attribut re.match)

(module)

read() (dans le module os)

(méthode asyncio.StreamReader)

(méthode chunk.Chunk)

(méthode codecs.StreamReader)

(méthode configparser.ConfigParser)

(méthode http.client.HTTPResponse)

(méthode imaplib.IMAP4)

(méthode io.BufferedIOBase)

(méthode io.BufferedReader)

(méthode io.RawIOBase)

(méthode io.TextIOBase)

(méthode mimetypes.MimeTypes)

(méthode mmap.mmap)

(méthode ossaudiodev.oss_audio_device)

(méthode ssl.MemoryBIO)

(méthode ssl.SSLSocket)

(méthode urllib.robotparser.RobotFileParser)

(méthode zipfile.ZipFile)

read1() (méthode io.BufferedIOBase)

(méthode io.BufferedReader)

(méthode io.BytesIO)

read_all() (méthode telnetlib.Telnet)

read_byte() (méthode mmap.mmap)

read_bytes() (méthode pathlib.Path)

read_dict() (méthode configparser.ConfigParser)

read_eager() (méthode telnetlib.Telnet)

read_environ() (dans le module wsgiref.handlers)

read_events() (méthode xml.etree.ElementTree.XMLPullParser)

read_file() (méthode configparser.ConfigParser)

read_history_file() (dans le module readline)

read_init_file() (dans le module readline)

read_lazy() (méthode telnetlib.Telnet)

read_mime_types() (dans le module mimetypes)

READ_RESTRICTED

read_sb_data() (méthode telnetlib.Telnet)

read_some() (méthode telnetlib.Telnet)

read_string() (méthode configparser.ConfigParser)

read_text() (méthode pathlib.Path)

read_token() (méthode shlex.shlex)

read_until() (méthode telnetlib.Telnet)

read_very_eager() (méthode telnetlib.Telnet)

read_very_lazy() (méthode telnetlib.Telnet)

read_windows_registry() (méthode mimetypes.MimeTypes)

READABLE (dans le module tkinter)

readable() (méthode asyncore.dispatcher)

(méthode io.IOBase)

readall() (méthode io.RawIOBase)

reader() (dans le module csv)

ReadError

readexactly() (méthode asyncio.StreamReader)

readfp() (méthode configparser.ConfigParser)

(méthode mimetypes.MimeTypes)

readframes() (méthode aifc.aifc)

(méthode sunau.AU_read)

(méthode wave.Wave_read)

readinto() (méthode http.client.HTTPResponse)

(méthode io.BufferedIOBase)

(méthode io.RawIOBase)

readinto1() (méthode io.BufferedIOBase)

(méthode io.BytesIO)

readline (module)

readline() (méthode asyncio.StreamReader)

(méthode codecs.StreamReader)

(méthode distutils.text_file.TextFile)

(méthode imaplib.IMAP4)

(méthode io.IOBase)

(méthode io.TextIOBase)

(méthode mmap.mmap)

readlines() (méthode codecs.StreamReader)

(méthode distutils.text_file.TextFile)

(méthode io.IOBase)

readlink() (dans le module os)

readmodule() (dans le module pyclbr)

readmodule_ex() (dans le module pyclbr)

READONLY

readonly (attribut memoryview)

readPlist() (dans le module plistlib)

readPlistFromBytes() (dans le module plistlib)

ReadTransport (classe dans asyncio)

readuntil() (méthode asyncio.StreamReader)

readv() (dans le module os)

ready() (méthode multiprocessing.pool.AsyncResult)

real (attribut numbers.Complex)

Real (classe dans numbers)

Real Media File Format

real_quick_ratio() (méthode difflib.SequenceMatcher)

realloc()

realpath() (dans le module os.path)

reason (attribut http.client.HTTPResponse)

(attribut ssl.SSLError)

(attribut UnicodeError)

(attribut urllib.error.HTTPError)

(attribut urllib.error.URLError)

reattach() (méthode tkinter.ttk.Treeview)

rebinding

name

reccontrols() (méthode ossaudiodev.oss_mixer_device)

received_data (attribut smtpd.SMTPChannel)

received_lines (attribut smtpd.SMTPChannel)

recent() (méthode imaplib.IMAP4)

records (attribut unittest.TestCase)

rect() (dans le module cmath)

rectangle() (dans le module curses.textpad)

RecursionError

recursive_repr() (dans le module reprlib)

recv() (méthode asyncore.dispatcher)

(méthode multiprocessing.connection.Connection)

(méthode socket.socket)

recv_bytes() (méthode multiprocessing.connection.Connection)

recv_bytes_into() (méthode multiprocessing.connection.Connection)

recv_into() (méthode socket.socket)

recvfrom() (méthode socket.socket)

recvfrom_into() (méthode socket.socket)

recvmsg() (méthode socket.socket)

recvmsg_into() (méthode socket.socket)

redirect_request() (méthode urllib.request.HTTPRedirectHandler)

redirect_stderr() (dans le module contextlib)

redirect_stdout() (dans le module contextlib)

redisplay() (dans le module readline)

redrawln() (méthode curses.window)

redrawwin() (méthode curses.window)

reduce (2to3 fixer)

reduce() (dans le module functools)

ref (classe dans weakref)

reference

attribute

reference counting

ReferenceError, [1]

ReferenceType (dans le module weakref)

refold_source (attribut email.policy.EmailPolicy)

refresh() (méthode curses.window)

REG_BINARY (dans le module winreg)

REG_DWORD (dans le module winreg)

REG_DWORD_BIG_ENDIAN (dans le module winreg)

REG_DWORD_LITTLE_ENDIAN (dans le module winreg)

REG_EXPAND_SZ (dans le module winreg)

REG_FULL_RESOURCE_DESCRIPTOR (dans le module winreg)

REG_LINK (dans le module winreg)

REG_MULTI_SZ (dans le module winreg)

REG_NONE (dans le module winreg)

REG_QWORD (dans le module winreg)

REG_QWORD_LITTLE_ENDIAN (dans le module winreg)

REG_RESOURCE_LIST (dans le module winreg)

REG_RESOURCE_REQUIREMENTS_LIST (dans le module winreg)

REG_SZ (dans le module winreg)

register() (dans le module atexit)

(dans le module codecs)

(dans le module faulthandler)

(dans le module webbrowser)

(méthode abc.ABCMeta)

(méthode multiprocessing.managers.BaseManager)

(méthode select.devpoll)

(méthode select.epoll)

(méthode select.poll)

(méthode selectors.BaseSelector)

register_adapter() (dans le module sqlite3)

register_archive_format() (dans le module shutil)

register_converter() (dans le module sqlite3)

register_defect() (méthode email.policy.Policy)

register_dialect() (dans le module csv)

register_error() (dans le module codecs)

register_function() (méthode xmlrpc.server.CGIXMLRPCRequestHandler)

(méthode xmlrpc.server.SimpleXMLRPCServer)

register_instance() (méthode xmlrpc.server.CGIXMLRPCRequestHandler)

(méthode xmlrpc.server.SimpleXMLRPCServer)

register_introspection_functions() (méthode xmlrpc.server.CGIXMLRPCRequestHandler)

(méthode xmlrpc.server.SimpleXMLRPCServer)

register_multicall_functions() (méthode xmlrpc.server.CGIXMLRPCRequestHandler)

(méthode xmlrpc.server.SimpleXMLRPCServer)

register_namespace() (dans le module xml.etree.ElementTree)

register_optionflag() (dans le module doctest)

register_shape() (dans le module turtle)

register_unpack_format() (dans le module shutil)

registerDOMImplementation() (dans le module xml.dom)

registerResult() (dans le module unittest)

regular

package

relative

import

URL

relative_to() (méthode pathlib.PurePath)

release() (dans le module platform)

(méthode _thread.lock)

(méthode asyncio.Condition)

(méthode asyncio.Lock)

(méthode asyncio.Semaphore)

(méthode logging.Handler)

(méthode memoryview)

(méthode multiprocessing.Lock)

(méthode multiprocessing.RLock)

(méthode threading.Condition)

(méthode threading.Lock)

(méthode threading.RLock)

(méthode threading.Semaphore)

release_lock() (dans le module imp)

reload (2to3 fixer)

reload() (dans le module imp)

(dans le module importlib)

relpath() (dans le module os.path)

remainder() (méthode decimal.Context)

remainder_near() (méthode decimal.Context)

(méthode decimal.Decimal)

RemoteDisconnected

remove() (dans le module os)

(méthode array.array)

(méthode collections.deque)

(méthode frozenset)

(méthode mailbox.Mailbox)

(méthode mailbox.MH)

(méthode xml.etree.ElementTree.Element)

(sequence method)

remove_done_callback() (méthode asyncio.Future)

remove_flag() (méthode mailbox.MaildirMessage)

(méthode mailbox.mboxMessage)

(méthode mailbox.MMDFMessage)

remove_folder() (méthode mailbox.Maildir)

(méthode mailbox.MH)

remove_header() (méthode urllib.request.Request)

remove_history_item() (dans le module readline)

remove_label() (méthode mailbox.BabylMessage)

remove_option() (méthode configparser.ConfigParser)

(méthode optparse.OptionParser)

remove_pyc() (méthode msilib.Directory)

remove_reader() (méthode asyncio.AbstractEventLoop)

remove_section() (méthode configparser.ConfigParser)

remove_sequence() (méthode mailbox.MHMessage)

remove_signal_handler() (méthode asyncio.AbstractEventLoop)

remove_tree() (dans le module distutils.dir_util)

remove_writer() (méthode asyncio.AbstractEventLoop)

removeAttribute() (méthode xml.dom.Element)

removeAttributeNode() (méthode xml.dom.Element)

removeAttributeNS() (méthode xml.dom.Element)

removeChild() (méthode xml.dom.Node)

removedirs() (dans le module os)

removeFilter() (méthode logging.Handler)

(méthode logging.Logger)

removeHandler() (dans le module unittest)

(méthode logging.Logger)

removeResult() (dans le module unittest)

removexattr() (dans le module os)

rename() (dans le module os)

(méthode ftplib.FTP)

(méthode imaplib.IMAP4)

(méthode pathlib.Path)

renames (2to3 fixer)

renames() (dans le module os)

reopenIfNeeded() (méthode logging.handlers.WatchedFileHandler)

reorganize() (méthode dbm.gnu.gdbm)

repeat() (dans le module itertools)

(dans le module timeit)

(méthode timeit.Timer)

repetition

operation

replace() (dans le module os)

(méthode bytearray)

(méthode bytes)

(méthode curses.panel.Panel)

(méthode datetime.date)

(méthode datetime.datetime)

(méthode datetime.time)

(méthode inspect.Parameter)

(méthode inspect.Signature)

(méthode pathlib.Path)

(méthode str)

replace_errors() (dans le module codecs)

replace_header() (méthode email.message.EmailMessage)

(méthode email.message.Message)

replace_history_item() (dans le module readline)

replace_whitespace (attribut textwrap.TextWrapper)

replaceChild() (méthode xml.dom.Node)

ReplacePackage() (dans le module modulefinder)

report() (méthode filecmp.dircmp)

(méthode modulefinder.ModuleFinder)

REPORT_CDIFF (dans le module doctest)

report_failure() (méthode doctest.DocTestRunner)

report_full_closure() (méthode filecmp.dircmp)

REPORT_NDIFF (dans le module doctest)

REPORT_ONLY_FIRST_FAILURE (dans le module doctest)

report_partial_closure() (méthode filecmp.dircmp)

report_start() (méthode doctest.DocTestRunner)

report_success() (méthode doctest.DocTestRunner)

REPORT_UDIFF (dans le module doctest)

report_unexpected_exception() (méthode doctest.DocTestRunner)

REPORTING_FLAGS (dans le module doctest)

repr

fonction de base, [1], [2], [3]

repr (2to3 fixer)

Repr (classe dans reprlib)

repr() (built-in function)

__repr__() (object method)

repr() (dans le module reprlib)

(fonction de base)

(méthode reprlib.Repr)

repr1() (méthode reprlib.Repr)

representation

integer

reprlib (module)

Request (classe dans urllib.request)

request() (méthode http.client.HTTPConnection)

request_queue_size (attribut socketserver.BaseServer)

request_rate() (méthode urllib.robotparser.RobotFileParser)

request_uri() (dans le module wsgiref.util)

request_version (attribut http.server.BaseHTTPRequestHandler)

RequestHandlerClass (attribut socketserver.BaseServer)

requestline (attribut http.server.BaseHTTPRequestHandler)

requires() (dans le module test.support)

reserved (attribut zipfile.ZipInfo)

reserved word

RESERVED_FUTURE (dans le module uuid)

RESERVED_MICROSOFT (dans le module uuid)

RESERVED_NCS (dans le module uuid)

reset() (dans le module turtle), [1]

(méthode bdb.Bdb)

(méthode codecs.IncrementalDecoder)

(méthode codecs.IncrementalEncoder)

(méthode codecs.StreamReader)

(méthode codecs.StreamWriter)

(méthode html.parser.HTMLParser)

(méthode ossaudiodev.oss_audio_device)

(méthode pipes.Template)

(méthode threading.Barrier)

(méthode xdrlib.Packer)

(méthode xdrlib.Unpacker)

(méthode xml.dom.pulldom.DOMEventStream)

(méthode xml.sax.xmlreader.IncrementalParser)

reset_mock() (méthode unittest.mock.Mock)

reset_prog_mode() (dans le module curses)

reset_shell_mode() (dans le module curses)

resetbuffer() (méthode code.InteractiveConsole)

resetlocale() (dans le module locale)

resetscreen() (dans le module turtle)

resetty() (dans le module curses)

resetwarnings() (dans le module warnings)

resize() (dans le module ctypes)

(méthode curses.window)

(méthode mmap.mmap)

resize_term() (dans le module curses)

resizemode() (dans le module turtle)

resizeterm() (dans le module curses)

resolution (attribut datetime.date)

(attribut datetime.datetime)

(attribut datetime.time)

(attribut datetime.timedelta)

resolve() (méthode pathlib.Path)

resolve_name() (dans le module importlib.util)

resolveEntity() (méthode xml.sax.handler.EntityResolver)

resource (module)

ResourceDenied

ResourceLoader (classe dans importlib.abc)

ResourceWarning

response (attribut nntplib.NNTPError)

response() (méthode imaplib.IMAP4)

ResponseNotReady

responses (attribut http.server.BaseHTTPRequestHandler)

(dans le module http.client)

restart (pdb command)

restore() (dans le module difflib)

RESTRICTED

restricted

execution

restype (attribut ctypes._FuncPtr)

result() (méthode asyncio.Future)

(méthode concurrent.futures.Future)

results() (méthode trace.Trace)

resume_reading() (méthode asyncio.ReadTransport)

resume_writing() (méthode asyncio.BaseProtocol)

retours à la ligne universels

retr() (méthode poplib.POP3)

retrbinary() (méthode ftplib.FTP)

retrieve() (méthode urllib.request.URLopener)

retrlines() (méthode ftplib.FTP)

return

état, [1], [2]

return (pdb command)

return_annotation (attribut inspect.Signature)

return_ok() (méthode http.cookiejar.CookiePolicy)

return_value (attribut unittest.mock.Mock)

RETURN_VALUE (opcode)

returncode (attribut asyncio.asyncio.subprocess.Process)

(attribut subprocess.CalledProcessError)

(attribut subprocess.CompletedProcess)

(attribut subprocess.Popen)

reverse() (dans le module audioop)

(méthode array.array)

(méthode collections.deque)

(sequence method)

reverse_order() (méthode pstats.Stats)

reverse_pointer (attribut ipaddress.IPv4Address)

(attribut ipaddress.IPv6Address)

reversed() (fonction de base)

Reversible (classe dans collections.abc)

(classe dans typing)

revert() (méthode http.cookiejar.FileCookieJar)

rewind() (méthode aifc.aifc)

(méthode sunau.AU_read)

(méthode wave.Wave_read)

RFC

RFC 1014, [1]

RFC 1123

RFC 1321

RFC 1422, [1]

RFC 1521, [1], [2]

RFC 1522, [1], [2]

RFC 1524, [1]

RFC 1730

RFC 1738

RFC 1750

RFC 1766, [1]

RFC 1808, [1], [2]

RFC 1832, [1]

RFC 1869, [1]

RFC 1870, [1], [2]

RFC 1939, [1]

RFC 2033

RFC 2045, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14]

RFC 2045#section-6.8

RFC 2046, [1], [2]

RFC 2047, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12]

RFC 2060, [1]

RFC 2068

RFC 2104, [1]

RFC 2109, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14]

RFC 2183, [1], [2]

RFC 2231, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14]

RFC 2295

RFC 2342, [1]

RFC 2368

RFC 2373, [1], [2]

RFC 2396, [1], [2]

RFC 2397

RFC 2449

RFC 2487

RFC 2518

RFC 2595, [1]

RFC 2616, [1], [2], [3], [4], [5], [6], [7], [8], [9]

RFC 2732, [1], [2]

RFC 2774

RFC 2818, [1]

RFC 2821

RFC 2822, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17]

RFC 2964

RFC 2965, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19]

RFC 2980, [1]

RFC 3056

RFC 3171

RFC 3207

RFC 3229

RFC 3280

RFC 3330

RFC 3339

RFC 3454, [1]

RFC 3490, [1], [2], [3]

RFC 3490#section-3.1

RFC 3492, [1]

RFC 3493

RFC 3501

RFC 3542, [1]

RFC 3548, [1], [2], [3], [4], [5]

RFC 3659

RFC 3879

RFC 3927

RFC 3977, [1], [2], [3], [4]

RFC 3986, [1], [2], [3], [4], [5]

RFC 4086

RFC 4122, [1], [2], [3], [4], [5], [6], [7], [8]

RFC 4180

RFC 4193

RFC 4217

RFC 4291

RFC 4380

RFC 4627, [1]

RFC 4642

RFC 4918, [1], [2], [3], [4]

RFC 4954, [1]

RFC 5161, [1]

RFC 5233, [1]

RFC 5246, [1]

RFC 5280, [1], [2], [3], [4]

RFC 5321, [1], [2], [3], [4]

RFC 5322, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20], [21]

RFC 5424, [1], [2], [3]

RFC 5424#section-6

RFC 5735

RFC 5842, [1]

RFC 5929

RFC 6066, [1], [2]

RFC 6125, [1]

RFC 6152, [1]

RFC 6531, [1], [2], [3], [4], [5], [6], [7], [8]

RFC 6532, [1], [2], [3], [4]

RFC 6585, [1], [2], [3]

RFC 6855, [1], [2], [3]

RFC 6856, [1]

RFC 7159, [1], [2]

RFC 7230, [1]

RFC 7231, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20], [21], [22], [23], [24], [25], [26], [27], [28], [29], [30], [31], [32], [33], [34]

RFC 7232, [1]

RFC 7233, [1]

RFC 7235, [1]

RFC 7238

RFC 7301, [1], [2]

RFC 7525

RFC 7693

RFC 7914

RFC 821, [1]

RFC 822, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11]

RFC 854, [1]

RFC 959, [1]

RFC 977

rfc2109 (attribut http.cookiejar.Cookie)

rfc2109_as_netscape (attribut http.cookiejar.DefaultCookiePolicy)

rfc2965 (attribut http.cookiejar.CookiePolicy)

rfc822_escape() (dans le module distutils.util)

RFC_4122 (dans le module uuid)

rfile (attribut http.server.BaseHTTPRequestHandler)

rfind() (méthode bytearray)

(méthode bytes)

(méthode mmap.mmap)

(méthode str)

rgb_to_hls() (dans le module colorsys)

rgb_to_hsv() (dans le module colorsys)

rgb_to_yiq() (dans le module colorsys)

rglob() (méthode pathlib.Path)

right (attribut filecmp.dircmp)

right() (dans le module turtle)

right_list (attribut filecmp.dircmp)

right_only (attribut filecmp.dircmp)

RIGHTSHIFT (dans le module token)

RIGHTSHIFTEQUAL (dans le module token)

rindex() (méthode bytearray)

(méthode bytes)

(méthode str)

rjust() (méthode bytearray)

(méthode bytes)

(méthode str)

rlcompleter (module)

rlecode_hqx() (dans le module binascii)

rledecode_hqx() (dans le module binascii)

RLIM_INFINITY (dans le module resource)

RLIMIT_AS (dans le module resource)

RLIMIT_CORE (dans le module resource)

RLIMIT_CPU (dans le module resource)

RLIMIT_DATA (dans le module resource)

RLIMIT_FSIZE (dans le module resource)

RLIMIT_MEMLOCK (dans le module resource)

RLIMIT_MSGQUEUE (dans le module resource)

RLIMIT_NICE (dans le module resource)

RLIMIT_NOFILE (dans le module resource)

RLIMIT_NPROC (dans le module resource)

RLIMIT_NPTS (dans le module resource)

RLIMIT_OFILE (dans le module resource)

RLIMIT_RSS (dans le module resource)

RLIMIT_RTPRIO (dans le module resource)

RLIMIT_RTTIME (dans le module resource)

RLIMIT_SBSIZE (dans le module resource)

RLIMIT_SIGPENDING (dans le module resource)

RLIMIT_STACK (dans le module resource)

RLIMIT_SWAP (dans le module resource)

RLIMIT_VMEM (dans le module resource)

RLock (classe dans multiprocessing)

(classe dans threading)

RLock() (méthode multiprocessing.managers.SyncManager)

rmd() (méthode ftplib.FTP)

rmdir() (dans le module os)

(méthode pathlib.Path)

RMFF

rms() (dans le module audioop)

rmtree() (dans le module shutil)

RobotFileParser (classe dans urllib.robotparser)

robots.txt

rollback() (méthode sqlite3.Connection)

ROT_THREE (opcode)

ROT_TWO (opcode)

rotate() (méthode collections.deque)

(méthode decimal.Context)

(méthode decimal.Decimal)

(méthode logging.handlers.BaseRotatingHandler)

RotatingFileHandler (classe dans logging.handlers)

rotation_filename() (méthode logging.handlers.BaseRotatingHandler)

rotator (attribut logging.handlers.BaseRotatingHandler)

round

fonction de base

round() (fonction de base)

ROUND_05UP (dans le module decimal)

ROUND_CEILING (dans le module decimal)

ROUND_DOWN (dans le module decimal)

ROUND_FLOOR (dans le module decimal)

ROUND_HALF_DOWN (dans le module decimal)

ROUND_HALF_EVEN (dans le module decimal)

ROUND_HALF_UP (dans le module decimal)

ROUND_UP (dans le module decimal)

Rounded (classe dans decimal)

Row (classe dans sqlite3)

row_factory (attribut sqlite3.Connection)

rowcount (attribut sqlite3.Cursor)

RPAR (dans le module token)

rpartition() (méthode bytearray)

(méthode bytes)

(méthode str)

rpc_paths (attribut xmlrpc.server.SimpleXMLRPCRequestHandler)

rpop() (méthode poplib.POP3)

rset() (méthode poplib.POP3)

rshift() (dans le module operator)

rsplit() (méthode bytearray)

(méthode bytes)

(méthode str)

RSQB (dans le module token)

rstrip() (méthode bytearray)

(méthode bytes)

(méthode str)

rt() (dans le module turtle)

RTLD_DEEPBIND (dans le module os)

RTLD_GLOBAL (dans le module os)

RTLD_LAZY (dans le module os)

RTLD_LOCAL (dans le module os)

RTLD_NODELETE (dans le module os)

RTLD_NOLOAD (dans le module os)

RTLD_NOW (dans le module os)

ruler (attribut cmd.Cmd)

run (pdb command)

Run script

run() (dans le module pdb)

(dans le module profile)

(dans le module subprocess)

(méthode bdb.Bdb)

(méthode distutils.cmd.Command)

(méthode doctest.DocTestRunner)

(méthode multiprocessing.Process)

(méthode pdb.Pdb)

(méthode profile.Profile)

(méthode sched.scheduler)

(méthode threading.Thread)

(méthode trace.Trace)

(méthode unittest.TestCase)

(méthode unittest.TestSuite)

(méthode unittest.TextTestRunner)

(méthode wsgiref.handlers.BaseHandler)

run_coroutine_threadsafe() (dans le module asyncio)

run_docstring_examples() (dans le module doctest)

run_doctest() (dans le module test.support)

run_forever() (méthode asyncio.AbstractEventLoop)

run_in_executor() (méthode asyncio.AbstractEventLoop)

run_module() (dans le module runpy)

run_path() (dans le module runpy)

run_script() (méthode modulefinder.ModuleFinder)

run_setup() (dans le module distutils.core)

run_unittest() (dans le module test.support)

run_until_complete() (méthode asyncio.AbstractEventLoop)

run_with_locale() (dans le module test.support)

runcall() (dans le module pdb)

(méthode bdb.Bdb)

(méthode pdb.Pdb)

(méthode profile.Profile)

runcode() (méthode code.InteractiveInterpreter)

runctx() (dans le module profile)

(méthode bdb.Bdb)

(méthode profile.Profile)

(méthode trace.Trace)

runeval() (dans le module pdb)

(méthode bdb.Bdb)

(méthode pdb.Pdb)

runfunc() (méthode trace.Trace)

running() (méthode concurrent.futures.Future)

runpy (module)

runsource() (méthode code.InteractiveInterpreter)

runtime_library_dir_option() (méthode distutils.ccompiler.CCompiler)

RuntimeError

RuntimeWarning

RUSAGE_BOTH (dans le module resource)

RUSAGE_CHILDREN (dans le module resource)

RUSAGE_SELF (dans le module resource)

RUSAGE_THREAD (dans le module resource)

S

S (dans le module re)

S_ENFMT (dans le module stat)

S_IEXEC (dans le module stat)

S_IFBLK (dans le module stat)

S_IFCHR (dans le module stat)

S_IFDIR (dans le module stat)

S_IFDOOR (dans le module stat)

S_IFIFO (dans le module stat)

S_IFLNK (dans le module stat)

S_IFMT() (dans le module stat)

S_IFPORT (dans le module stat)

S_IFREG (dans le module stat)

S_IFSOCK (dans le module stat)

S_IFWHT (dans le module stat)

S_IMODE() (dans le module stat)

S_IREAD (dans le module stat)

S_IRGRP (dans le module stat)

S_IROTH (dans le module stat)

S_IRUSR (dans le module stat)

S_IRWXG (dans le module stat)

S_IRWXO (dans le module stat)

S_IRWXU (dans le module stat)

S_ISBLK() (dans le module stat)

S_ISCHR() (dans le module stat)

S_ISDIR() (dans le module stat)

S_ISDOOR() (dans le module stat)

S_ISFIFO() (dans le module stat)

S_ISGID (dans le module stat)

S_ISLNK() (dans le module stat)

S_ISPORT() (dans le module stat)

S_ISREG() (dans le module stat)

S_ISSOCK() (dans le module stat)

S_ISUID (dans le module stat)

S_ISVTX (dans le module stat)

S_ISWHT() (dans le module stat)

S_IWGRP (dans le module stat)

S_IWOTH (dans le module stat)

S_IWRITE (dans le module stat)

S_IWUSR (dans le module stat)

S_IXGRP (dans le module stat)

S_IXOTH (dans le module stat)

S_IXUSR (dans le module stat)

safe_substitute() (méthode string.Template)

saferepr() (dans le module pprint)

same_files (attribut filecmp.dircmp)

same_quantum() (méthode decimal.Context)

(méthode decimal.Decimal)

samefile() (dans le module os.path)

(méthode pathlib.Path)

SameFileError

sameopenfile() (dans le module os.path)

samestat() (dans le module os.path)

sample() (dans le module random)

save() (méthode http.cookiejar.FileCookieJar)

SaveKey() (dans le module winreg)

savetty() (dans le module curses)

SAX2DOM (classe dans xml.dom.pulldom)

SAXException

SAXNotRecognizedException

SAXNotSupportedException

SAXParseException

scaleb() (méthode decimal.Context)

(méthode decimal.Decimal)

scandir() (dans le module os)

scanf()

sched (module)

SCHED_BATCH (dans le module os)

SCHED_FIFO (dans le module os)

sched_get_priority_max() (dans le module os)

sched_get_priority_min() (dans le module os)

sched_getaffinity() (dans le module os)

sched_getparam() (dans le module os)

sched_getscheduler() (dans le module os)

SCHED_IDLE (dans le module os)

SCHED_OTHER (dans le module os)

sched_param (classe dans os)

sched_priority (attribut os.sched_param)

SCHED_RESET_ON_FORK (dans le module os)

SCHED_RR (dans le module os)

sched_rr_get_interval() (dans le module os)

sched_setaffinity() (dans le module os)

sched_setparam() (dans le module os)

sched_setscheduler() (dans le module os)

SCHED_SPORADIC (dans le module os)

sched_yield() (dans le module os)

scheduler (classe dans sched)

schema (dans le module msilib)

scope, [1]

Screen (classe dans turtle)

screensize() (dans le module turtle)

script_from_examples() (dans le module doctest)

scroll() (méthode curses.window)

ScrolledCanvas (classe dans turtle)

scrollok() (méthode curses.window)

scrypt() (dans le module hashlib)

sdterr

stdin stdout

search

path, module, [1], [2], [3], [4], [5], [6], [7]

search() (dans le module re)

(méthode imaplib.IMAP4)

(méthode re.regex)

second (attribut datetime.datetime)

(attribut datetime.time)

seconds since the epoch

secrets (module)

SECTCRE (attribut configparser.ConfigParser)

sections() (méthode configparser.ConfigParser)

secure (attribut http.cookiejar.Cookie)

secure hash algorithm, SHA1, SHA224, SHA256, SHA384, SHA512

Secure Sockets Layer

security

CGI

see() (méthode tkinter.ttk.Treeview)

seed() (dans le module random)

seek() (méthode chunk.Chunk)

(méthode io.IOBase)

(méthode io.TextIOBase)

(méthode mmap.mmap)

SEEK_CUR (dans le module os)

SEEK_END (dans le module os)

SEEK_SET (dans le module os)

seekable() (méthode io.IOBase)

seen_greeting (attribut smtpd.SMTPChannel)

Select (classe dans tkinter.tix)

select (module)

select() (dans le module select)

(méthode imaplib.IMAP4)

(méthode selectors.BaseSelector)

(méthode tkinter.ttk.Notebook)

selected_alpn_protocol() (méthode ssl.SSLSocket)

selected_npn_protocol() (méthode ssl.SSLSocket)

selection() (méthode tkinter.ttk.Treeview)

selection_add() (méthode tkinter.ttk.Treeview)

selection_remove() (méthode tkinter.ttk.Treeview)

selection_set() (méthode tkinter.ttk.Treeview)

selection_toggle() (méthode tkinter.ttk.Treeview)

selector (attribut urllib.request.Request)

SelectorEventLoop (classe dans asyncio)

SelectorKey (classe dans selectors)

selectors (module)

SelectSelector (classe dans selectors)

Semaphore (classe dans asyncio)

(classe dans multiprocessing)

(classe dans threading)

Semaphore() (méthode multiprocessing.managers.SyncManager)

semaphores, binary

SEMI (dans le module token)

send() (méthode asyncore.dispatcher)

(méthode coroutine)

(méthode generator)

(méthode http.client.HTTPConnection)

(méthode imaplib.IMAP4)

(méthode logging.handlers.DatagramHandler)

(méthode logging.handlers.SocketHandler)

(méthode multiprocessing.connection.Connection)

(méthode socket.socket)

send_bytes() (méthode multiprocessing.connection.Connection)

send_error() (méthode http.server.BaseHTTPRequestHandler)

send_flowing_data() (méthode formatter.writer)

send_header() (méthode http.server.BaseHTTPRequestHandler)

send_hor_rule() (méthode formatter.writer)

send_label_data() (méthode formatter.writer)

send_line_break() (méthode formatter.writer)

send_literal_data() (méthode formatter.writer)

send_message() (méthode smtplib.SMTP)

send_paragraph() (méthode formatter.writer)

send_response() (méthode http.server.BaseHTTPRequestHandler)

send_response_only() (méthode http.server.BaseHTTPRequestHandler)

send_signal() (méthode asyncio.asyncio.subprocess.Process)

(méthode asyncio.BaseSubprocessTransport)

(méthode subprocess.Popen)

sendall() (méthode socket.socket)

sendcmd() (méthode ftplib.FTP)

sendfile() (dans le module os)

(méthode socket.socket)

(méthode wsgiref.handlers.BaseHandler)

sendmail() (méthode smtplib.SMTP)

sendmsg() (méthode socket.socket)

sendmsg_afalg() (méthode socket.socket)

sendto() (méthode asyncio.DatagramTransport)

(méthode socket.socket)

sentinel (attribut multiprocessing.Process)

(dans le module unittest.mock)

sep (dans le module os)

sequence

item

iteration

objet, [1], [2], [3], [4], [5], [6], [7], [8]

types, immutable

types, mutable

types, operations on, [1]

Sequence (classe dans collections.abc)

(classe dans typing)

sequence (dans le module msilib)

sequence2st() (dans le module parser)

SequenceMatcher (classe dans difflib), [1]

serializing

objects

serve_forever() (méthode socketserver.BaseServer)

server

WWW, [1]

server (attribut http.server.BaseHTTPRequestHandler)

Server (classe dans asyncio)

server_activate() (méthode socketserver.BaseServer)

server_address (attribut socketserver.BaseServer)

server_bind() (méthode socketserver.BaseServer)

server_close() (méthode socketserver.BaseServer)

server_hostname (attribut ssl.SSLSocket)

server_side (attribut ssl.SSLSocket)

server_software (attribut wsgiref.handlers.BaseHandler)

server_version (attribut http.server.BaseHTTPRequestHandler)

(attribut http.server.SimpleHTTPRequestHandler)

ServerProxy (classe dans xmlrpc.client)

service_actions() (méthode socketserver.BaseServer)

session (attribut ssl.SSLSocket)

session_reused (attribut ssl.SSLSocket)

session_stats() (méthode ssl.SSLContext)

set

display

objet, [1], [2], [3]

Set (classe dans collections.abc)

(classe dans typing)

set (classe de base)

Set Breakpoint

set type

objet

set() (méthode asyncio.Event)

(méthode configparser.ConfigParser)

(méthode configparser.RawConfigParser)

(méthode http.cookies.Morsel)

(méthode ossaudiodev.oss_mixer_device)

(méthode test.support.EnvironmentVarGuard)

(méthode threading.Event)

(méthode tkinter.ttk.Combobox)

(méthode tkinter.ttk.Treeview)

(méthode xml.etree.ElementTree.Element)

SET_ADD (opcode)

set_all()

set_allowed_domains() (méthode http.cookiejar.DefaultCookiePolicy)

set_alpn_protocols() (méthode ssl.SSLContext)

set_app() (méthode wsgiref.simple_server.WSGIServer)

set_asyncgen_hooks() (dans le module sys)

set_authorizer() (méthode sqlite3.Connection)

set_auto_history() (dans le module readline)

set_blocked_domains() (méthode http.cookiejar.DefaultCookiePolicy)

set_blocking() (dans le module os)

set_boundary() (méthode email.message.EmailMessage)

(méthode email.message.Message)

set_break() (méthode bdb.Bdb)

set_charset() (méthode email.message.Message)

set_children() (méthode tkinter.ttk.Treeview)

set_ciphers() (méthode ssl.SSLContext)

set_completer() (dans le module readline)

set_completer_delims() (dans le module readline)

set_completion_display_matches_hook() (dans le module readline)

set_content() (dans le module email.contentmanager)

(méthode email.contentmanager.ContentManager)

(méthode email.message.EmailMessage)

set_continue() (méthode bdb.Bdb)

set_cookie() (méthode http.cookiejar.CookieJar)

set_cookie_if_ok() (méthode http.cookiejar.CookieJar)

set_coroutine_wrapper() (dans le module sys)

set_current() (méthode msilib.Feature)

set_data() (méthode importlib.abc.SourceLoader)

(méthode importlib.machinery.SourceFileLoader)

set_date() (méthode mailbox.MaildirMessage)

set_debug() (dans le module gc)

(méthode asyncio.AbstractEventLoop)

set_debuglevel() (méthode ftplib.FTP)

(méthode http.client.HTTPConnection)

(méthode nntplib.NNTP)

(méthode poplib.POP3)

(méthode smtplib.SMTP)

(méthode telnetlib.Telnet)

set_default_executor() (méthode asyncio.AbstractEventLoop)

set_default_type() (méthode email.message.EmailMessage)

(méthode email.message.Message)

set_default_verify_paths() (méthode ssl.SSLContext)

set_defaults() (méthode argparse.ArgumentParser)

(méthode optparse.OptionParser)

set_ecdh_curve() (méthode ssl.SSLContext)

set_errno() (dans le module ctypes)

set_event_loop() (dans le module asyncio)

(méthode asyncio.AbstractEventLoopPolicy)

set_event_loop_policy() (dans le module asyncio)

set_exception() (méthode asyncio.Future)

(méthode asyncio.StreamReader)

(méthode concurrent.futures.Future)

set_exception_handler() (méthode asyncio.AbstractEventLoop)

set_executable() (dans le module multiprocessing)

set_executables() (méthode distutils.ccompiler.CCompiler)

set_flags() (méthode mailbox.MaildirMessage)

(méthode mailbox.mboxMessage)

(méthode mailbox.MMDFMessage)

set_from() (méthode mailbox.mboxMessage)

(méthode mailbox.MMDFMessage)

set_handle_inheritable() (dans le module os)

set_history_length() (dans le module readline)

set_include_dirs() (méthode distutils.ccompiler.CCompiler)

set_info() (méthode mailbox.MaildirMessage)

set_inheritable() (dans le module os)

(méthode socket.socket)

set_labels() (méthode mailbox.BabylMessage)

set_last_error() (dans le module ctypes)

set_libraries() (méthode distutils.ccompiler.CCompiler)

set_library_dirs() (méthode distutils.ccompiler.CCompiler)

set_link_objects() (méthode distutils.ccompiler.CCompiler)

set_literal (2to3 fixer)

set_loader() (dans le module importlib.util)

set_next() (méthode bdb.Bdb)

set_nonstandard_attr() (méthode http.cookiejar.Cookie)

set_npn_protocols() (méthode ssl.SSLContext)

set_ok() (méthode http.cookiejar.CookiePolicy)

set_option_negotiation_callback() (méthode telnetlib.Telnet)

set_output_charset() (méthode gettext.NullTranslations)

set_package() (dans le module importlib.util)

set_param() (méthode email.message.EmailMessage)

(méthode email.message.Message)

set_pasv() (méthode ftplib.FTP)

set_payload() (méthode email.message.Message)

set_policy() (méthode http.cookiejar.CookieJar)

set_position() (méthode xdrlib.Unpacker)

set_pre_input_hook() (dans le module readline)

set_progress_handler() (méthode sqlite3.Connection)

set_protocol() (méthode asyncio.BaseTransport)

set_proxy() (méthode urllib.request.Request)

set_python_build() (dans le module distutils.sysconfig)

set_quit() (méthode bdb.Bdb)

set_recsrc() (méthode ossaudiodev.oss_mixer_device)

set_result() (méthode asyncio.Future)

(méthode concurrent.futures.Future)

set_return() (méthode bdb.Bdb)

set_running_or_notify_cancel() (méthode concurrent.futures.Future)

set_runtime_library_dirs() (méthode distutils.ccompiler.CCompiler)

set_seq1() (méthode difflib.SequenceMatcher)

set_seq2() (méthode difflib.SequenceMatcher)

set_seqs() (méthode difflib.SequenceMatcher)

set_sequences() (méthode mailbox.MH)

(méthode mailbox.MHMessage)

set_server_documentation() (méthode xmlrpc.server.DocCGIXMLRPCRequestHandler)

(méthode xmlrpc.server.DocXMLRPCServer)

set_server_name() (méthode xmlrpc.server.DocCGIXMLRPCRequestHandler)

(méthode xmlrpc.server.DocXMLRPCServer)

set_server_title() (méthode xmlrpc.server.DocCGIXMLRPCRequestHandler)

(méthode xmlrpc.server.DocXMLRPCServer)

set_servername_callback() (méthode ssl.SSLContext)

set_spacing() (méthode formatter.formatter)

set_start_method() (dans le module multiprocessing)

set_startup_hook() (dans le module readline)

set_step() (méthode bdb.Bdb)

set_subdir() (méthode mailbox.MaildirMessage)

set_task_factory() (méthode asyncio.AbstractEventLoop)

set_terminator() (méthode asynchat.async_chat)

set_threshold() (dans le module gc)

set_trace() (dans le module bdb)

(dans le module pdb)

(méthode bdb.Bdb)

(méthode pdb.Pdb)

set_trace_callback() (méthode sqlite3.Connection)

set_transport() (méthode asyncio.StreamReader)

set_tunnel() (méthode http.client.HTTPConnection)

set_type() (méthode email.message.Message)

set_unittest_reportflags() (dans le module doctest)

set_unixfrom() (méthode email.message.EmailMessage)

(méthode email.message.Message)

set_until() (méthode bdb.Bdb)

set_url() (méthode urllib.robotparser.RobotFileParser)

set_usage() (méthode optparse.OptionParser)

set_userptr() (méthode curses.panel.Panel)

set_visible() (méthode mailbox.BabylMessage)

set_wakeup_fd() (dans le module signal)

set_write_buffer_limits() (méthode asyncio.WriteTransport)

setacl() (méthode imaplib.IMAP4)

setannotation() (méthode imaplib.IMAP4)

setattr() (fonction de base)

setAttribute() (méthode xml.dom.Element)

setAttributeNode() (méthode xml.dom.Element)

setAttributeNodeNS() (méthode xml.dom.Element)

setAttributeNS() (méthode xml.dom.Element)

SetBase() (méthode xml.parsers.expat.xmlparser)

setblocking() (méthode socket.socket)

setByteStream() (méthode xml.sax.xmlreader.InputSource)

setcbreak() (dans le module tty)

setCharacterStream() (méthode xml.sax.xmlreader.InputSource)

setcheckinterval() (dans le module sys)

setcomptype() (méthode aifc.aifc)

(méthode sunau.AU_write)

(méthode wave.Wave_write)

setContentHandler() (méthode xml.sax.xmlreader.XMLReader)

setcontext() (dans le module decimal)

setDaemon() (méthode threading.Thread)

setdefault() (méthode dict)

(méthode http.cookies.Morsel)

setdefaulttimeout() (dans le module socket)

setdlopenflags() (dans le module sys)

setDocumentLocator() (méthode xml.sax.handler.ContentHandler)

setDTDHandler() (méthode xml.sax.xmlreader.XMLReader)

setegid() (dans le module os)

setEncoding() (méthode xml.sax.xmlreader.InputSource)

setEntityResolver() (méthode xml.sax.xmlreader.XMLReader)

setErrorHandler() (méthode xml.sax.xmlreader.XMLReader)

seteuid() (dans le module os)

setFeature() (méthode xml.sax.xmlreader.XMLReader)

setfirstweekday() (dans le module calendar)

setfmt() (méthode ossaudiodev.oss_audio_device)

setFormatter() (méthode logging.Handler)

setframerate() (méthode aifc.aifc)

(méthode sunau.AU_write)

(méthode wave.Wave_write)

setgid() (dans le module os)

setgroups() (dans le module os)

seth() (dans le module turtle)

setheading() (dans le module turtle)

sethostname() (dans le module socket)

SetInteger() (méthode msilib.Record)

setitem() (dans le module operator)

setitimer() (dans le module signal)

setLevel() (méthode logging.Handler)

(méthode logging.Logger)

setlocale() (dans le module locale)

setLocale() (méthode xml.sax.xmlreader.XMLReader)

setLoggerClass() (dans le module logging)

setlogmask() (dans le module syslog)

setLogRecordFactory() (dans le module logging)

setmark() (méthode aifc.aifc)

setMaxConns() (méthode urllib.request.CacheFTPHandler)

setmode() (dans le module msvcrt)

setName() (méthode threading.Thread)

setnchannels() (méthode aifc.aifc)

(méthode sunau.AU_write)

(méthode wave.Wave_write)

setnframes() (méthode aifc.aifc)

(méthode sunau.AU_write)

(méthode wave.Wave_write)

SetParamEntityParsing() (méthode xml.parsers.expat.xmlparser)

setparameters() (méthode ossaudiodev.oss_audio_device)

setparams() (méthode aifc.aifc)

(méthode sunau.AU_write)

(méthode wave.Wave_write)

setpassword() (méthode zipfile.ZipFile)

setpgid() (dans le module os)

setpgrp() (dans le module os)

setpos() (dans le module turtle)

(méthode aifc.aifc)

(méthode sunau.AU_read)

(méthode wave.Wave_read)

setposition() (dans le module turtle)

setpriority() (dans le module os)

setprofile() (dans le module sys)

(dans le module threading)

SetProperty() (méthode msilib.SummaryInformation)

setProperty() (méthode xml.sax.xmlreader.XMLReader)

setPublicId() (méthode xml.sax.xmlreader.InputSource)

setquota() (méthode imaplib.IMAP4)

setraw() (dans le module tty)

setrecursionlimit() (dans le module sys)

setregid() (dans le module os)

setresgid() (dans le module os)

setresuid() (dans le module os)

setreuid() (dans le module os)

setrlimit() (dans le module resource)

setsampwidth() (méthode aifc.aifc)

(méthode sunau.AU_write)

(méthode wave.Wave_write)

setscrreg() (méthode curses.window)

setsid() (dans le module os)

setsockopt() (méthode socket.socket), [1], [2]

setstate() (dans le module random)

(méthode codecs.IncrementalDecoder)

(méthode codecs.IncrementalEncoder)

SetStream() (méthode msilib.Record)

SetString() (méthode msilib.Record)

setswitchinterval() (dans le module sys)

(in module sys)

setSystemId() (méthode xml.sax.xmlreader.InputSource)

setsyx() (dans le module curses)

setTarget() (méthode logging.handlers.MemoryHandler)

settiltangle() (dans le module turtle)

settimeout() (méthode socket.socket)

setTimeout() (méthode urllib.request.CacheFTPHandler)

settrace() (dans le module sys)

(dans le module threading)

setuid() (dans le module os)

setundobuffer() (dans le module turtle)

setup() (dans le module distutils.core)

(dans le module turtle)

(méthode socketserver.BaseRequestHandler)

setUp() (méthode unittest.TestCase)

SETUP_ANNOTATIONS (opcode)

SETUP_ASYNC_WITH (opcode)

setup_environ() (méthode wsgiref.handlers.BaseHandler)

SETUP_EXCEPT (opcode)

SETUP_FINALLY (opcode)

SETUP_LOOP (opcode)

setup_python() (méthode venv.EnvBuilder)

setup_scripts() (méthode venv.EnvBuilder)

setup_testing_defaults() (dans le module wsgiref.util)

SETUP_WITH (opcode)

setUpClass() (méthode unittest.TestCase)

setupterm() (dans le module curses)

SetValue() (dans le module winreg)

SetValueEx() (dans le module winreg)

setworldcoordinates() (dans le module turtle)

setx() (dans le module turtle)

setxattr() (dans le module os)

sety() (dans le module turtle)

séquence

SF_APPEND (dans le module stat)

SF_ARCHIVED (dans le module stat)

SF_IMMUTABLE (dans le module stat)

SF_MNOWAIT (dans le module os)

SF_NODISKIO (dans le module os)

SF_NOUNLINK (dans le module stat)

SF_SNAPSHOT (dans le module stat)

SF_SYNC (dans le module os)

shape (attribut memoryview)

Shape (classe dans turtle)

shape() (dans le module turtle)

shapesize() (dans le module turtle)

shapetransform() (dans le module turtle)

share() (méthode socket.socket)

shared_ciphers() (méthode ssl.SSLSocket)

shared_object_filename() (méthode distutils.ccompiler.CCompiler)

shearfactor() (dans le module turtle)

Shelf (classe dans shelve)

shelve

module

shelve (module)

shield() (dans le module asyncio)

shift() (méthode decimal.Context)

(méthode decimal.Decimal)

shift_path_info() (dans le module wsgiref.util)

shifting

operation

operations

shlex (classe dans shlex)

(module)

shortDescription() (méthode unittest.TestCase)

shorten() (dans le module textwrap)

shouldFlush() (méthode logging.handlers.BufferingHandler)

(méthode logging.handlers.MemoryHandler)

shouldStop (attribut unittest.TestResult)

show() (méthode curses.panel.Panel)

show_code() (dans le module dis)

show_compilers() (dans le module distutils.ccompiler)

showsyntaxerror() (méthode code.InteractiveInterpreter)

showtraceback() (méthode code.InteractiveInterpreter)

showturtle() (dans le module turtle)

showwarning() (dans le module warnings)

shuffle() (dans le module random)

shutdown() (dans le module logging)

(méthode concurrent.futures.Executor)

(méthode imaplib.IMAP4)

(méthode multiprocessing.managers.BaseManager)

(méthode socket.socket)

(méthode socketserver.BaseServer)

shutdown_asyncgens() (méthode asyncio.AbstractEventLoop)

shutil (module)

side_effect (attribut unittest.mock.Mock)

SIG_BLOCK (dans le module signal)

SIG_DFL (dans le module signal)

SIG_IGN (dans le module signal)

SIG_SETMASK (dans le module signal)

SIG_UNBLOCK (dans le module signal)

SIGINT, [1]

siginterrupt() (dans le module signal)

signal

module, [1]

signal (module)

signal() (dans le module signal)

signature (attribut inspect.BoundArguments)

Signature (classe dans inspect)

signature() (dans le module inspect)

sigpending() (dans le module signal)

sigtimedwait() (dans le module signal)

sigwait() (dans le module signal)

sigwaitinfo() (dans le module signal)

simple

statement

Simple Mail Transfer Protocol

SimpleCookie (classe dans http.cookies)

simplefilter() (dans le module warnings)

SimpleHandler (classe dans wsgiref.handlers)

SimpleHTTPRequestHandler (classe dans http.server)

SimpleNamespace (classe dans types)

SimpleQueue (classe dans multiprocessing)

SimpleXMLRPCRequestHandler (classe dans xmlrpc.server)

SimpleXMLRPCServer (classe dans xmlrpc.server)

sin() (dans le module cmath)

(dans le module math)

SingleAddressHeader (classe dans email.headerregistry)

singledispatch() (dans le module functools)

singleton

tuple

sinh() (dans le module cmath)

(dans le module math)

SIO_KEEPALIVE_VALS (dans le module socket)

SIO_LOOPBACK_FAST_PATH (dans le module socket)

SIO_RCVALL (dans le module socket)

site (module)

site command line option

--user-base

--user-site

site-packages

directory

sitecustomize

module

sixtofour (attribut ipaddress.IPv6Address)

size (attribut struct.Struct)

(attribut tarfile.TarInfo)

(attribut tracemalloc.Statistic)

(attribut tracemalloc.StatisticDiff)

(attribut tracemalloc.Trace)

size() (méthode ftplib.FTP)

(méthode mmap.mmap)

size_diff (attribut tracemalloc.StatisticDiff)

SIZE_MAX

Sized (classe dans collections.abc)

(classe dans typing)

sizeof() (dans le module ctypes)

SKIP (dans le module doctest)

skip() (dans le module unittest)

(méthode chunk.Chunk)

skip_unless_symlink() (dans le module test.support)

skipIf() (dans le module unittest)

skipinitialspace (attribut csv.Dialect)

skipped (attribut unittest.TestResult)

skippedEntity() (méthode xml.sax.handler.ContentHandler)

SkipTest

skipTest() (méthode unittest.TestCase)

skipUnless() (dans le module unittest)

SLASH (dans le module token)

SLASHEQUAL (dans le module token)

slave() (méthode nntplib.NNTP)

sleep() (dans le module asyncio)

(dans le module time)

slice

assignment

fonction de base, [1]

objet

operation

slice (classe de base)

slicing, [1], [2]

assignment

SMTP

protocol

SMTP (classe dans smtplib)

(dans le module email.policy)

smtp_server (attribut smtpd.SMTPChannel)

SMTP_SSL (classe dans smtplib)

smtp_state (attribut smtpd.SMTPChannel)

SMTPAuthenticationError

SMTPChannel (classe dans smtpd)

SMTPConnectError

smtpd (module)

SMTPDataError

SMTPException

SMTPHandler (classe dans logging.handlers)

SMTPHeloError

smtplib (module)

SMTPNotSupportedError

SMTPRecipientsRefused

SMTPResponseException

SMTPSenderRefused

SMTPServer (classe dans smtpd)

SMTPServerDisconnected

SMTPUTF8 (dans le module email.policy)

Snapshot (classe dans tracemalloc)

SND_ALIAS (dans le module winsound)

SND_ASYNC (dans le module winsound)

SND_FILENAME (dans le module winsound)

SND_LOOP (dans le module winsound)

SND_MEMORY (dans le module winsound)

SND_NODEFAULT (dans le module winsound)

SND_NOSTOP (dans le module winsound)

SND_NOWAIT (dans le module winsound)

SND_PURGE (dans le module winsound)

sndhdr (module)

sniff() (méthode csv.Sniffer)

Sniffer (classe dans csv)

sock_accept() (méthode asyncio.AbstractEventLoop)

SOCK_CLOEXEC (dans le module socket)

sock_connect() (méthode asyncio.AbstractEventLoop)

SOCK_DGRAM (dans le module socket)

SOCK_NONBLOCK (dans le module socket)

SOCK_RAW (dans le module socket)

SOCK_RDM (dans le module socket)

sock_recv() (méthode asyncio.AbstractEventLoop)

sock_sendall() (méthode asyncio.AbstractEventLoop)

SOCK_SEQPACKET (dans le module socket)

SOCK_STREAM (dans le module socket)

socket

module

objet

socket (attribut socketserver.BaseServer)

(module)

socket() (dans le module socket)

(in module socket)

(méthode imaplib.IMAP4)

socket_type (attribut socketserver.BaseServer)

SocketHandler (classe dans logging.handlers)

socketpair() (dans le module socket)

sockets (attribut asyncio.Server)

socketserver (module)

SocketType (dans le module socket)

SOL_ALG (dans le module socket)

SOL_RDS (dans le module socket)

SOMAXCONN (dans le module socket)

sort() (méthode imaplib.IMAP4)

(méthode list)

sort_stats() (méthode pstats.Stats)

sorted() (fonction de base)

sortTestMethodsUsing (attribut unittest.TestLoader)

source (attribut doctest.Example)

(attribut shlex.shlex)

(pdb command)

source character set

source_from_cache() (dans le module imp)

(dans le module importlib.util)

SOURCE_SUFFIXES (dans le module importlib.machinery)

source_to_code() (méthode statique importlib.abc.InspectLoader)

SourceFileLoader (classe dans importlib.machinery)

sourcehook() (méthode shlex.shlex)

SourcelessFileLoader (classe dans importlib.machinery)

SourceLoader (classe dans importlib.abc)

space

in printf-style formatting, [1]

in string formatting

span() (méthode re.match)

spawn() (dans le module pty)

(méthode distutils.ccompiler.CCompiler)

spawnl() (dans le module os)

spawnle() (dans le module os)

spawnlp() (dans le module os)

spawnlpe() (dans le module os)

spawnv() (dans le module os)

spawnve() (dans le module os)

spawnvp() (dans le module os)

spawnvpe() (dans le module os)

spec_from_file_location() (dans le module importlib.util)

spec_from_loader() (dans le module importlib.util)

special

attribute

attribute, generic

specified_attributes (attribut xml.parsers.expat.xmlparser)

speed() (dans le module turtle)

(méthode ossaudiodev.oss_audio_device)

spécificateur de module

split() (dans le module os.path)

(dans le module re)

(dans le module shlex)

(méthode bytearray)

(méthode bytes)

(méthode re.regex)

(méthode str)

split_quoted() (dans le module distutils.util)

splitdrive() (dans le module os.path)

splitext() (dans le module os.path)

splitlines() (méthode bytearray)

(méthode bytes)

(méthode str)

SplitResult (classe dans urllib.parse)

SplitResultBytes (classe dans urllib.parse)

splitunc() (dans le module os.path)

SpooledTemporaryFile() (dans le module tempfile)

sprintf-style formatting, [1]

spwd (module)

sqlite3 (module)

sqlite_version (dans le module sqlite3)

sqlite_version_info (dans le module sqlite3)

sqrt() (dans le module cmath)

(dans le module math)

(méthode decimal.Context)

(méthode decimal.Decimal)

SSL

ssl (module)

SSL_CERT_FILE

SSL_CERT_PATH

ssl_version (attribut ftplib.FTP_TLS)

SSLContext (classe dans ssl)

SSLEOFError

SSLError

SSLErrorNumber (classe dans ssl)

SSLObject (classe dans ssl)

SSLSession (classe dans ssl)

SSLSocket (classe dans ssl)

SSLSyscallError

SSLWantReadError

SSLWantWriteError

SSLZeroReturnError

st() (dans le module turtle)

st2list() (dans le module parser)

st2tuple() (dans le module parser)

st_atime (attribut os.stat_result)

ST_ATIME (dans le module stat)

st_atime_ns (attribut os.stat_result)

st_birthtime (attribut os.stat_result)

st_blksize (attribut os.stat_result)

st_blocks (attribut os.stat_result)

st_creator (attribut os.stat_result)

st_ctime (attribut os.stat_result)

ST_CTIME (dans le module stat)

st_ctime_ns (attribut os.stat_result)

st_dev (attribut os.stat_result)

ST_DEV (dans le module stat)

st_file_attributes (attribut os.stat_result)

st_flags (attribut os.stat_result)

st_gen (attribut os.stat_result)

st_gid (attribut os.stat_result)

ST_GID (dans le module stat)

st_ino (attribut os.stat_result)

ST_INO (dans le module stat)

st_mode (attribut os.stat_result)

ST_MODE (dans le module stat)

st_mtime (attribut os.stat_result)

ST_MTIME (dans le module stat)

st_mtime_ns (attribut os.stat_result)

st_nlink (attribut os.stat_result)

ST_NLINK (dans le module stat)

st_rdev (attribut os.stat_result)

st_rsize (attribut os.stat_result)

st_size (attribut os.stat_result)

ST_SIZE (dans le module stat)

st_type (attribut os.stat_result)

st_uid (attribut os.stat_result)

ST_UID (dans le module stat)

stack

execution

trace

stack (attribut traceback.TracebackException)

stack viewer

stack() (dans le module inspect)

stack_effect() (dans le module dis)

stack_size() (dans le module _thread)

(dans le module threading)

stackable

streams

StackSummary (classe dans traceback)

stamp() (dans le module turtle)

standard

output

Standard C

standard input

standard_b64decode() (dans le module base64)

standard_b64encode() (dans le module base64)

standarderror (2to3 fixer)

standend() (méthode curses.window)

standout() (méthode curses.window)

STAR (dans le module token)

STAREQUAL (dans le module token)

starmap() (dans le module itertools)

(méthode multiprocessing.pool.Pool)

starmap_async() (méthode multiprocessing.pool.Pool)

start (attribut range)

(attribut UnicodeError)

(slice object attribute), [1]

start() (dans le module tracemalloc)

(méthode logging.handlers.QueueListener)

(méthode multiprocessing.managers.BaseManager)

(méthode multiprocessing.Process)

(méthode re.match)

(méthode threading.Thread)

(méthode tkinter.ttk.Progressbar)

(méthode xml.etree.ElementTree.TreeBuilder)

start_color() (dans le module curses)

start_component() (méthode msilib.Directory)

start_new_thread() (dans le module _thread)

start_server() (dans le module asyncio)

start_unix_server() (dans le module asyncio)

StartCdataSectionHandler() (méthode xml.parsers.expat.xmlparser)

StartDoctypeDeclHandler() (méthode xml.parsers.expat.xmlparser)

startDocument() (méthode xml.sax.handler.ContentHandler)

startElement() (méthode xml.sax.handler.ContentHandler)

StartElementHandler() (méthode xml.parsers.expat.xmlparser)

startElementNS() (méthode xml.sax.handler.ContentHandler)

STARTF_USESHOWWINDOW (dans le module subprocess)

STARTF_USESTDHANDLES (dans le module subprocess)

startfile() (dans le module os)

StartNamespaceDeclHandler() (méthode xml.parsers.expat.xmlparser)

startPrefixMapping() (méthode xml.sax.handler.ContentHandler)

startswith() (méthode bytearray)

(méthode bytes)

(méthode str)

startTest() (méthode unittest.TestResult)

startTestRun() (méthode unittest.TestResult)

starttls() (méthode imaplib.IMAP4)

(méthode nntplib.NNTP)

(méthode smtplib.SMTP)

STARTUPINFO (classe dans subprocess)

stat

module

stat (module)

stat() (dans le module os)

(méthode nntplib.NNTP)

(méthode os.DirEntry)

(méthode pathlib.Path)

(méthode poplib.POP3)

stat_float_times() (dans le module os)

stat_result (classe dans os)

state() (méthode tkinter.ttk.Widget)

statement

assignment, [1]

assignment, annotated

assignment, augmented

compound

expression

future

loop, [1], [2], [3]

simple

statement grouping

staticmethod

fonction de base

staticmethod() (fonction de base)

Statistic (classe dans tracemalloc)

StatisticDiff (classe dans tracemalloc)

statistics (module)

statistics() (méthode tracemalloc.Snapshot)

StatisticsError

Stats (classe dans pstats)

status (attribut http.client.HTTPResponse)

status() (méthode imaplib.IMAP4)

statvfs() (dans le module os)

STD_ERROR_HANDLE (dans le module subprocess)

STD_INPUT_HANDLE (dans le module subprocess)

STD_OUTPUT_HANDLE (dans le module subprocess)

StdButtonBox (classe dans tkinter.tix)

stderr (attribut asyncio.asyncio.subprocess.Process)

(attribut subprocess.CalledProcessError)

(attribut subprocess.CompletedProcess)

(attribut subprocess.Popen)

(attribut subprocess.TimeoutExpired)

(dans le module sys)

(in module sys), [1]

stdev() (dans le module statistics)

stdin

stdout sdterr

stdin (attribut asyncio.asyncio.subprocess.Process)

(attribut subprocess.Popen)

(dans le module sys)

(in module sys), [1]

stdio

stdout

sdterr, stdin

stdout (attribut asyncio.asyncio.subprocess.Process)

(attribut subprocess.CalledProcessError)

(attribut subprocess.CompletedProcess)

(attribut subprocess.Popen)

(attribut subprocess.TimeoutExpired)

STDOUT (dans le module subprocess)

stdout (dans le module sys)

(in module sys), [1]

step (attribut range)

(pdb command)

(slice object attribute), [1]

step() (méthode tkinter.ttk.Progressbar)

stereocontrols() (méthode ossaudiodev.oss_mixer_device)

stls() (méthode poplib.POP3)

stop (attribut range)

(slice object attribute), [1]

stop() (dans le module tracemalloc)

(méthode asyncio.AbstractEventLoop)

(méthode logging.handlers.QueueListener)

(méthode tkinter.ttk.Progressbar)

(méthode unittest.TestResult)

stop_here() (méthode bdb.Bdb)

StopAsyncIteration

exception

StopIteration

exception, [1]

stopListening() (dans le module logging.config)

stopTest() (méthode unittest.TestResult)

stopTestRun() (méthode unittest.TestResult)

storbinary() (méthode ftplib.FTP)

store() (méthode imaplib.IMAP4)

STORE_ACTIONS (attribut optparse.Option)

STORE_ANNOTATION (opcode)

STORE_ATTR (opcode)

STORE_DEREF (opcode)

STORE_FAST (opcode)

STORE_GLOBAL (opcode)

STORE_NAME (opcode)

STORE_SUBSCR (opcode)

storlines() (méthode ftplib.FTP)

str (built-in class)

(see also string)

str (classe de base)

str() (dans le module locale)

strcoll() (dans le module locale)

StreamError

StreamHandler (classe dans logging)

streamreader (attribut codecs.CodecInfo)

StreamReader (classe dans asyncio)

(classe dans codecs)

StreamReaderProtocol (classe dans asyncio)

StreamReaderWriter (classe dans codecs)

StreamRecoder (classe dans codecs)

StreamRequestHandler (classe dans socketserver)

streams

stackable

streamwriter (attribut codecs.CodecInfo)

StreamWriter (classe dans asyncio)

(classe dans codecs)

strerror (attribut OSError)

strerror()

(dans le module os)

strftime() (dans le module time)

(méthode datetime.date)

(méthode datetime.datetime)

(méthode datetime.time)

strict (attribut csv.Dialect)

(dans le module email.policy)

strict_domain (attribut http.cookiejar.DefaultCookiePolicy)

strict_errors() (dans le module codecs)

strict_ns_domain (attribut http.cookiejar.DefaultCookiePolicy)

strict_ns_set_initial_dollar (attribut http.cookiejar.DefaultCookiePolicy)

strict_ns_set_path (attribut http.cookiejar.DefaultCookiePolicy)

strict_ns_unverifiable (attribut http.cookiejar.DefaultCookiePolicy)

strict_rfc2965_unverifiable (attribut http.cookiejar.DefaultCookiePolicy)

strides (attribut memoryview)

string

__format__() (object method)

__str__() (object method)

conversion, [1]

format() (built-in function)

formatted literal

formatting, printf

immutable sequences

interpolated literal

interpolation, printf

item

methods

module

object representation

objet, [1], [2]

PyObject_Str (C function)

str (built-in class)

str() (built-in function)

text sequence type

string (attribut re.match)

STRING (dans le module token)

string (module)

string literal

string_at() (dans le module ctypes)

StringIO (classe dans io)

stringprep (module)

strings, documentation, [1]

strip() (méthode bytearray)

(méthode bytes)

(méthode str)

strip_dirs() (méthode pstats.Stats)

stripspaces (attribut curses.textpad.Textbox)

strptime() (dans le module time)

(méthode de la classe datetime.datetime)

strtobool() (dans le module distutils.util)

struct

module

Struct (classe dans struct)

struct (module)

struct sequence

struct_time (classe dans time)

Structure (classe dans ctypes)

structures

C

strxfrm() (dans le module locale)

STType (dans le module parser)

style

coding

Style (classe dans tkinter.ttk)

sub() (dans le module operator)

(dans le module re)

(méthode re.regex)

sub_commands (attribut distutils.cmd.Command)

subclassing

immutable types

subdirs (attribut filecmp.dircmp)

SubElement() (dans le module xml.etree.ElementTree)

submit() (méthode concurrent.futures.Executor)

submodule_search_locations (attribut importlib.machinery.ModuleSpec)

subn() (dans le module re)

(méthode re.regex)

subnets() (méthode ipaddress.IPv4Network)

(méthode ipaddress.IPv6Network)

Subnormal (classe dans decimal)

suboffsets (attribut memoryview)

subpad() (méthode curses.window)

subprocess (module)

subprocess_exec() (méthode asyncio.AbstractEventLoop)

subprocess_shell() (méthode asyncio.AbstractEventLoop)

SubprocessError

SubprocessProtocol (classe dans asyncio)

subscribe() (méthode imaplib.IMAP4)

subscript

assignment

operation

subscription, [1], [2], [3]

assignment

subsequent_indent (attribut textwrap.TextWrapper)

subst_vars() (dans le module distutils.util)

substitute() (méthode string.Template)

subTest() (méthode unittest.TestCase)

subtract() (méthode collections.Counter)

(méthode decimal.Context)

subtraction

subtype (attribut email.headerregistry.ContentTypeHeader)

subwin() (méthode curses.window)

successful() (méthode multiprocessing.pool.AsyncResult)

suffix_map (attribut mimetypes.MimeTypes)

(dans le module mimetypes)

suite

suite() (dans le module parser)

suiteClass (attribut unittest.TestLoader)

sum() (fonction de base)

sum_list()

sum_sequence(), [1]

summarize() (méthode doctest.DocTestRunner)

summarize_address_range() (dans le module ipaddress)

sunau (module)

super (attribut pyclbr.Class)

super() (fonction de base)

supernet() (méthode ipaddress.IPv4Network)

(méthode ipaddress.IPv6Network)

supports_bytes_environ (dans le module os)

supports_dir_fd (dans le module os)

supports_effective_ids (dans le module os)

supports_fd (dans le module os)

supports_follow_symlinks (dans le module os)

supports_unicode_filenames (dans le module os.path)

SupportsAbs (classe dans typing)

SupportsBytes (classe dans typing)

SupportsComplex (classe dans typing)

SupportsFloat (classe dans typing)

SupportsInt (classe dans typing)

SupportsRound (classe dans typing)

suppress() (dans le module contextlib)

SuppressCrashReport (classe dans test.support)

SW_HIDE (dans le module subprocess)

swapcase() (méthode bytearray)

(méthode bytes)

(méthode str)

sym_name (dans le module symbol)

Symbol (classe dans symtable)

symbol (module)

SymbolTable (classe dans symtable)

symlink() (dans le module os)

symlink_to() (méthode pathlib.Path)

symmetric_difference() (méthode frozenset)

symmetric_difference_update() (méthode frozenset)

symtable (module)

symtable() (dans le module symtable)

sync() (dans le module os)

(méthode dbm.dumb.dumbdbm)

(méthode dbm.gnu.gdbm)

(méthode ossaudiodev.oss_audio_device)

(méthode shelve.Shelf)

syncdown() (méthode curses.window)

synchronized() (dans le module multiprocessing.sharedctypes)

SyncManager (classe dans multiprocessing.managers)

syncok() (méthode curses.window)

syncup() (méthode curses.window)

syntax

SyntaxErr

SyntaxError

SyntaxWarning

sys

module, [1], [2], [3], [4], [5], [6]

sys (module)

sys.exc_info

sys.last_traceback

sys.meta_path

sys.modules

sys.path

sys.path_hooks

sys.path_importer_cache

sys.stderr

sys.stdin

sys.stdout

sys_exc (2to3 fixer)

sys_version (attribut http.server.BaseHTTPRequestHandler)

sysconf() (dans le module os)

sysconf_names (dans le module os)

sysconfig (module)

syslog (module)

syslog() (dans le module syslog)

SysLogHandler (classe dans logging.handlers)

system() (dans le module os)

(dans le module platform)

system_alias() (dans le module platform)

SystemError

(built-in exception), [1]

SystemExit

(built-in exception)

systemId (attribut xml.dom.DocumentType)

SystemRandom (classe dans random)

(classe dans secrets)

SystemRoot

T

T_FMT (dans le module locale)

T_FMT_AMPM (dans le module locale)

tab

tab() (méthode tkinter.ttk.Notebook)

TabError

tableau de correspondances

tabnanny (module)

tabs() (méthode tkinter.ttk.Notebook)

tabsize (attribut textwrap.TextWrapper)

tabular

data

tag (attribut xml.etree.ElementTree.Element)

tag_bind() (méthode tkinter.ttk.Treeview)

tag_configure() (méthode tkinter.ttk.Treeview)

tag_has() (méthode tkinter.ttk.Treeview)

tagName (attribut xml.dom.Element)

tail (attribut xml.etree.ElementTree.Element)

take_snapshot() (dans le module tracemalloc)

takewhile() (dans le module itertools)

tan() (dans le module cmath)

(dans le module math)

tanh() (dans le module cmath)

(dans le module math)

TarError

TarFile (classe dans tarfile), [1]

tarfile (module)

tarfile command line option

--create <tarfile> <source1> ... <sourceN>

--extract <tarfile> [<output_dir>]

--list <tarfile>

--test <tarfile>

--verbose

-c <tarfile> <source1> ... <sourceN>

-e <tarfile> [<output_dir>]

-l <tarfile>

-t <tarfile>

-v

target

deletion

list, [1], [2]

list assignment

list, deletion

loop control

target (attribut xml.dom.ProcessingInstruction)

TarInfo (classe dans tarfile)

Task (classe dans asyncio)

task_done() (méthode asyncio.Queue)

(méthode multiprocessing.JoinableQueue)

(méthode queue.Queue)

tau (dans le module cmath)

(dans le module math)

tb_frame (traceback attribute)

tb_lasti (traceback attribute)

tb_lineno (traceback attribute)

tb_locals (attribut unittest.TestResult)

tb_next (traceback attribute)

tbreak (pdb command)

tcdrain() (dans le module termios)

tcflow() (dans le module termios)

tcflush() (dans le module termios)

tcgetattr() (dans le module termios)

tcgetpgrp() (dans le module os)

Tcl() (dans le module tkinter)

TCL_LIBRARY

TCPServer (classe dans socketserver)

tcsendbreak() (dans le module termios)

tcsetattr() (dans le module termios)

tcsetpgrp() (dans le module os)

tearDown() (méthode unittest.TestCase)

tearDownClass() (méthode unittest.TestCase)

tee() (dans le module itertools)

tell() (méthode aifc.aifc), [1]

(méthode chunk.Chunk)

(méthode io.IOBase)

(méthode io.TextIOBase)

(méthode mmap.mmap)

(méthode sunau.AU_read)

(méthode sunau.AU_write)

(méthode wave.Wave_read)

(méthode wave.Wave_write)

Telnet (classe dans telnetlib)

telnetlib (module)

TEMP

temp_cwd() (dans le module test.support)

temp_dir() (dans le module test.support)

temp_umask() (dans le module test.support)

tempdir (dans le module tempfile)

tempfile (module)

template (attribut string.Template)

Template (classe dans pipes)

(classe dans string)

temporary

file

file name

TemporaryDirectory() (dans le module tempfile)

TemporaryFile() (dans le module tempfile)

teredo (attribut ipaddress.IPv6Address)

TERM, [1]

termattrs() (dans le module curses)

terminal_size (classe dans os)

terminate() (méthode asyncio.asyncio.subprocess.Process)

(méthode asyncio.BaseSubprocessTransport)

(méthode multiprocessing.pool.Pool)

(méthode multiprocessing.Process)

(méthode subprocess.Popen)

termination model

termios (module)

termname() (dans le module curses)

ternary

operator

test

identity

membership

test (attribut doctest.DocTestFailure)

(attribut doctest.UnexpectedException)

(module)

test() (dans le module cgi)

test.support (module)

TestCase (classe dans unittest)

TestFailed

testfile() (dans le module doctest)

TESTFN (dans le module test.support)

TestLoader (classe dans unittest)

testMethodPrefix (attribut unittest.TestLoader)

testmod() (dans le module doctest)

TestResult (classe dans unittest)

tests (dans le module imghdr)

testsource() (dans le module doctest)

testsRun (attribut unittest.TestResult)

TestSuite (classe dans unittest)

testzip() (méthode zipfile.ZipFile)

text (attribut traceback.TracebackException)

(attribut xml.etree.ElementTree.Element)

Text (classe dans typing)

text (dans le module msilib)

text mode

text() (méthode msilib.Dialog)

text_factory (attribut sqlite3.Connection)

Textbox (classe dans curses.textpad)

TextCalendar (classe dans calendar)

textdomain() (dans le module gettext)

(dans le module locale)

TextFile (classe dans distutils.text_file)

textinput() (dans le module turtle)

TextIO (classe dans typing)

TextIOBase (classe dans io)

TextIOWrapper (classe dans io)

TextTestResult (classe dans unittest)

TextTestRunner (classe dans unittest)

textwrap (module)

TextWrapper (classe dans textwrap)

theme_create() (méthode tkinter.ttk.Style)

theme_names() (méthode tkinter.ttk.Style)

theme_settings() (méthode tkinter.ttk.Style)

theme_use() (méthode tkinter.ttk.Style)

THOUSEP (dans le module locale)

Thread (classe dans threading)

thread() (méthode imaplib.IMAP4)

thread_info (dans le module sys)

threading (module)

ThreadingMixIn (classe dans socketserver)

ThreadingTCPServer (classe dans socketserver)

ThreadingUDPServer (classe dans socketserver)

ThreadPoolExecutor (classe dans concurrent.futures)

threads

POSIX

throw (2to3 fixer)

throw() (méthode coroutine)

(méthode generator)

ticket_lifetime_hint (attribut ssl.SSLSession)

tigetflag() (dans le module curses)

tigetnum() (dans le module curses)

tigetstr() (dans le module curses)

TILDE (dans le module token)

tilt() (dans le module turtle)

tiltangle() (dans le module turtle)

time (attribut ssl.SSLSession)

(classe dans datetime)

(module)

time() (dans le module time)

(méthode asyncio.AbstractEventLoop)

(méthode datetime.datetime)

Time2Internaldate() (dans le module imaplib)

timedelta (classe dans datetime)

TimedRotatingFileHandler (classe dans logging.handlers)

timegm() (dans le module calendar)

timeit (module)

timeit command line option

--clock

--help

--number=N

--process

--repeat=N

--setup=S

--time

--unit=U

--verbose

-c

-h

-n N

-p

-r N

-s S

-t

-u

-v

timeit() (dans le module timeit)

(méthode timeit.Timer)

timeout

(attribut socketserver.BaseServer)

(attribut ssl.SSLSession)

(attribut subprocess.TimeoutExpired)

timeout() (méthode curses.window)

TIMEOUT_MAX (dans le module _thread)

(dans le module threading)

TimeoutError, [1], [2], [3]

TimeoutExpired

Timer (classe dans threading)

(classe dans timeit)

times() (dans le module os)

timestamp() (méthode datetime.datetime)

timetuple() (méthode datetime.date)

(méthode datetime.datetime)

timetz() (méthode datetime.datetime)

timezone (classe dans datetime)

(dans le module time)

title() (dans le module turtle)

(méthode bytearray)

(méthode bytes)

(méthode str)

Tix

tix_addbitmapdir() (méthode tkinter.tix.tixCommand)

tix_cget() (méthode tkinter.tix.tixCommand)

tix_configure() (méthode tkinter.tix.tixCommand)

tix_filedialog() (méthode tkinter.tix.tixCommand)

tix_getbitmap() (méthode tkinter.tix.tixCommand)

tix_getimage() (méthode tkinter.tix.tixCommand)

TIX_LIBRARY

tix_option_get() (méthode tkinter.tix.tixCommand)

tix_resetoptions() (méthode tkinter.tix.tixCommand)

tixCommand (classe dans tkinter.tix)

Tk

(classe dans tkinter)

(classe dans tkinter.tix)

Tk Option Data Types

TK_LIBRARY

Tkinter

tkinter (module)

tkinter.scrolledtext (module)

tkinter.tix (module)

tkinter.ttk (module)

TList (classe dans tkinter.tix)

TLS

TMP

TMPDIR

to_bytes() (méthode int)

to_eng_string() (méthode decimal.Context)

(méthode decimal.Decimal)

to_integral() (méthode decimal.Decimal)

to_integral_exact() (méthode decimal.Context)

(méthode decimal.Decimal)

to_integral_value() (méthode decimal.Decimal)

to_sci_string() (méthode decimal.Context)

ToASCII() (dans le module encodings.idna)

tobuf() (méthode tarfile.TarInfo)

tobytes() (méthode array.array)

(méthode memoryview)

today() (méthode de la classe datetime.date)

(méthode de la classe datetime.datetime)

tofile() (méthode array.array)

tok_name (dans le module token)

token

(attribut shlex.shlex)

(module)

token_bytes() (dans le module secrets)

token_hex() (dans le module secrets)

token_urlsafe() (dans le module secrets)

TokenError

tokenize (module)

tokenize command line option

--exact

--help

-e

-h

tokenize() (dans le module tokenize)

tolist() (méthode array.array)

(méthode memoryview)

(méthode parser.ST)

tomono() (dans le module audioop)

toordinal() (méthode datetime.date)

(méthode datetime.datetime)

top() (méthode curses.panel.Panel)

(méthode poplib.POP3)

top_panel() (dans le module curses.panel)

toprettyxml() (méthode xml.dom.minidom.Node)

tostereo() (dans le module audioop)

tostring() (dans le module xml.etree.ElementTree)

(méthode array.array)

tostringlist() (dans le module xml.etree.ElementTree)

total_changes (attribut sqlite3.Connection)

total_ordering() (dans le module functools)

total_seconds() (méthode datetime.timedelta)

totuple() (méthode parser.ST)

touch() (méthode pathlib.Path)

touchline() (méthode curses.window)

touchwin() (méthode curses.window)

ToUnicode() (dans le module encodings.idna)

tounicode() (méthode array.array)

towards() (dans le module turtle)

toxml() (méthode xml.dom.minidom.Node)

tp_as_async (membre C)

tp_as_mapping (membre C)

tp_as_number (membre C)

tp_as_sequence (membre C)

tparm() (dans le module curses)

trace

stack

Trace (classe dans trace)

(classe dans tracemalloc)

trace (module)

trace command line option

--count

--coverdir=<dir>

--file=<file>

--help

--ignore-dir=<dir>

--ignore-module=<mod>

--listfuncs

--missing

--no-report

--report

--summary

--timing

--trace

--trackcalls

--version

-c

-C

-f

-g

-l

-m

-r

-R

-s

-t

-T

trace function, [1], [2]

trace() (dans le module inspect)

trace_dispatch() (méthode bdb.Bdb)

traceback

objet, [1], [2], [3], [4]

traceback (attribut tracemalloc.Statistic)

(attribut tracemalloc.StatisticDiff)

(attribut tracemalloc.Trace)

Traceback (classe dans tracemalloc)

traceback (module)

traceback_limit (attribut tracemalloc.Snapshot)

(attribut wsgiref.handlers.BaseHandler)

TracebackException (classe dans traceback)

tracebacklimit (dans le module sys)

tracebacks

in CGI scripts

TracebackType (dans le module types)

tracemalloc (module)

tracer() (dans le module turtle)

traces (attribut tracemalloc.Snapshot)

trailing

comma

tranche

transfercmd() (méthode ftplib.FTP)

TransientResource (classe dans test.support)

translate() (dans le module fnmatch)

(méthode bytearray)

(méthode bytes)

(méthode str)

translation() (dans le module gettext)

transport (attribut asyncio.StreamWriter)

Transport Layer Security

traverseproc (type C)

Tree (classe dans tkinter.tix)

TreeBuilder (classe dans xml.etree.ElementTree)

Treeview (classe dans tkinter.ttk)

triangular() (dans le module random)

triple-quoted string

True, [1], [2]

true

True (variable de base)

truediv() (dans le module operator)

trunc() (dans le module math)

(in module math)

truncate() (dans le module os)

(méthode io.IOBase)

truth

value

truth() (dans le module operator)

try

état, [1], [2]

ttk

tty

I/O control

tty (module)

ttyname() (dans le module os)

tuple

display

empty, [1]

fonction de base, [1]

objet, [1], [2], [3], [4], [5], [6]

singleton

tuple (classe de base)

Tuple (dans le module typing)

tuple2st() (dans le module parser)

tuple_params (2to3 fixer)

turnoff_sigfpe() (dans le module fpectl)

turnon_sigfpe() (dans le module fpectl)

Turtle (classe dans turtle)

turtle (module)

turtledemo (module)

turtles() (dans le module turtle)

TurtleScreen (classe dans turtle)

turtlesize() (dans le module turtle)

type, [1]

Boolean

data

fonction de base, [1], [2], [3]

hierarchy

immutable data

objet, [1], [2]

operations on dictionary

operations on list

type (attribut optparse.Option)

(attribut socket.socket)

(attribut tarfile.TarInfo)

(attribut urllib.request.Request)

Type (classe dans typing)

type (classe de base)

type of an object

TYPE_CHECKER (attribut optparse.Option)

TYPE_CHECKING (dans le module typing)

typeahead() (dans le module curses)

typecode (attribut array.array)

typecodes (dans le module array)

TYPED_ACTIONS (attribut optparse.Option)

typed_subpart_iterator() (dans le module email.iterators)

TypeError

exception

types

built-in

immutable sequence

module

mutable sequence

operations on integer

operations on mapping

operations on numeric

operations on sequence, [1]

types (2to3 fixer)

TYPES (attribut optparse.Option)

types (module)

types, internal

types_map (attribut mimetypes.MimeTypes)

(dans le module mimetypes)

types_map_inv (attribut mimetypes.MimeTypes)

TypeVar (classe dans typing)

typing (module)

TZ, [1], [2], [3], [4]

tzinfo (attribut datetime.datetime)

(attribut datetime.time)

(classe dans datetime)

tzname (dans le module time)

tzname() (méthode datetime.datetime)

(méthode datetime.time)

(méthode datetime.timezone)

(méthode datetime.tzinfo)

tzset() (dans le module time)

U

u"

string literal

u'

string literal

u-LAW, [1], [2]

ucd_3_2_0 (dans le module unicodedata)

udata (attribut select.kevent)

UDPServer (classe dans socketserver)

UF_APPEND (dans le module stat)

UF_COMPRESSED (dans le module stat)

UF_HIDDEN (dans le module stat)

UF_IMMUTABLE (dans le module stat)

UF_NODUMP (dans le module stat)

UF_NOUNLINK (dans le module stat)

UF_OPAQUE (dans le module stat)

uid (attribut tarfile.TarInfo)

uid() (méthode imaplib.IMAP4)

uidl() (méthode poplib.POP3)

ulaw2lin() (dans le module audioop)

ULONG_MAX

umask() (dans le module os)

unalias (pdb command)

uname (attribut tarfile.TarInfo)

uname() (dans le module os)

(dans le module platform)

unary

arithmetic operation

bitwise operation

UNARY_INVERT (opcode)

UNARY_NEGATIVE (opcode)

UNARY_NOT (opcode)

UNARY_POSITIVE (opcode)

unbinding

name

UnboundLocalError, [1]

unbuffered I/O

UNC paths

and os.makedirs()

unconsumed_tail (attribut zlib.Decompress)

unctrl() (dans le module curses)

(dans le module curses.ascii)

undefine_macro() (méthode distutils.ccompiler.CCompiler)

Underflow (classe dans decimal)

undisplay (pdb command)

undo() (dans le module turtle)

undobufferentries() (dans le module turtle)

undoc_header (attribut cmd.Cmd)

unescape() (dans le module html)

(dans le module xml.sax.saxutils)

UnexpectedException

unexpectedSuccesses (attribut unittest.TestResult)

unget_wch() (dans le module curses)

ungetch() (dans le module curses)

(dans le module msvcrt)

ungetmouse() (dans le module curses)

ungetwch() (dans le module msvcrt)

unhexlify() (dans le module binascii)

Unicode, [1], [2]

database

unicode (2to3 fixer)

Unicode Consortium

unicodedata (module)

UnicodeDecodeError

UnicodeEncodeError

UnicodeError

UnicodeTranslateError

UnicodeWarning

unidata_version (dans le module unicodedata)

unified_diff() (dans le module difflib)

uniform() (dans le module random)

UnimplementedFileMode

Union (classe dans ctypes)

(dans le module typing)

union() (méthode frozenset)

unique() (dans le module enum), [1]

unittest (module)

unittest command line option

--buffer

--catch

--failfast

--locals

-b

-c

-f

unittest-discover command line option

--pattern pattern

--start-directory directory

--top-level-directory directory

--verbose

-p

-s

-t

-v

unittest.mock (module)

universal newlines

bytearray.splitlines method

bytes.splitlines method

csv.reader function

importlib.abc.InspectLoader.get_source method

io.IncrementalNewlineDecoder class

io.TextIOWrapper class

open() built-in function

str.splitlines method

subprocess module

What's new, [1], [2], [3]

UNIX

file control

I/O control

unix_dialect (classe dans csv)

UnixDatagramServer (classe dans socketserver)

UnixStreamServer (classe dans socketserver)

unknown_decl() (méthode html.parser.HTMLParser)

unknown_open() (méthode urllib.request.BaseHandler)

(méthode urllib.request.UnknownHandler)

UnknownHandler (classe dans urllib.request)

UnknownProtocol

UnknownTransferEncoding

unlink() (dans le module os)

(méthode pathlib.Path)

(méthode xml.dom.minidom.Node)

unlock() (méthode mailbox.Babyl)

(méthode mailbox.Mailbox)

(méthode mailbox.Maildir)

(méthode mailbox.mbox)

(méthode mailbox.MH)

(méthode mailbox.MMDF)

unpack() (dans le module struct)

(méthode struct.Struct)

unpack_archive() (dans le module shutil)

unpack_array() (méthode xdrlib.Unpacker)

unpack_bytes() (méthode xdrlib.Unpacker)

unpack_double() (méthode xdrlib.Unpacker)

UNPACK_EX (opcode)

unpack_farray() (méthode xdrlib.Unpacker)

unpack_float() (méthode xdrlib.Unpacker)

unpack_fopaque() (méthode xdrlib.Unpacker)

unpack_from() (dans le module struct)

(méthode struct.Struct)

unpack_fstring() (méthode xdrlib.Unpacker)

unpack_list() (méthode xdrlib.Unpacker)

unpack_opaque() (méthode xdrlib.Unpacker)

UNPACK_SEQUENCE (opcode)

unpack_string() (méthode xdrlib.Unpacker)

Unpacker (classe dans xdrlib)

unpacking

dictionary

in function calls

iterable

unparsedEntityDecl() (méthode xml.sax.handler.DTDHandler)

UnparsedEntityDeclHandler() (méthode xml.parsers.expat.xmlparser)

Unpickler (classe dans pickle)

UnpicklingError

unquote() (dans le module email.utils)

(dans le module urllib.parse)

unquote_plus() (dans le module urllib.parse)

unquote_to_bytes() (dans le module urllib.parse)

unreachable object

unreadline() (méthode distutils.text_file.TextFile)

unrecognized escape sequence

unregister() (dans le module atexit)

(dans le module faulthandler)

(méthode select.devpoll)

(méthode select.epoll)

(méthode select.poll)

(méthode selectors.BaseSelector)

unregister_archive_format() (dans le module shutil)

unregister_dialect() (dans le module csv)

unregister_unpack_format() (dans le module shutil)

unset() (méthode test.support.EnvironmentVarGuard)

unsetenv() (dans le module os)

UnstructuredHeader (classe dans email.headerregistry)

unsubscribe() (méthode imaplib.IMAP4)

UnsupportedOperation

until (pdb command)

untokenize() (dans le module tokenize)

untouchwin() (méthode curses.window)

unused_data (attribut bz2.BZ2Decompressor)

(attribut lzma.LZMADecompressor)

(attribut zlib.Decompress)

unverifiable (attribut urllib.request.Request)

unwrap() (dans le module inspect)

(méthode ssl.SSLSocket)

up (pdb command)

up() (dans le module turtle)

update() (dans le module turtle)

(méthode collections.Counter)

(méthode dict)

(méthode frozenset)

(méthode hashlib.hash)

(méthode hmac.HMAC)

(méthode http.cookies.Morsel)

(méthode mailbox.Mailbox)

(méthode mailbox.Maildir)

(méthode trace.CoverageResults)

update_authenticated() (méthode urllib.request.HTTPPasswordMgrWithPriorAuth)

update_lines_cols() (dans le module curses)

update_panels() (dans le module curses.panel)

update_visible() (méthode mailbox.BabylMessage)

update_wrapper() (dans le module functools)

upper() (méthode bytearray)

(méthode bytes)

(méthode str)

urandom() (dans le module os)

URL, [1], [2], [3]

parsing

relative

url (attribut xmlrpc.client.ProtocolError)

url2pathname() (dans le module urllib.request)

urlcleanup() (dans le module urllib.request)

urldefrag() (dans le module urllib.parse)

urlencode() (dans le module urllib.parse)

URLError

urljoin() (dans le module urllib.parse)

urllib (2to3 fixer)

(module)

urllib.error (module)

urllib.parse (module)

urllib.request

module

urllib.request (module)

urllib.response (module)

urllib.robotparser (module)

urlopen() (dans le module urllib.request)

URLopener (classe dans urllib.request)

urlparse() (dans le module urllib.parse)

urlretrieve() (dans le module urllib.request)

urlsafe_b64decode() (dans le module base64)

urlsafe_b64encode() (dans le module base64)

urlsplit() (dans le module urllib.parse)

urlunparse() (dans le module urllib.parse)

urlunsplit() (dans le module urllib.parse)

urn (attribut uuid.UUID)

use_default_colors() (dans le module curses)

use_env() (dans le module curses)

use_rawinput (attribut cmd.Cmd)

UseForeignDTD() (méthode xml.parsers.expat.xmlparser)

USER

user

effective id

id

id, setting

user() (méthode poplib.POP3)

user-defined

function

function call

method

user-defined function

objet, [1], [2]

user-defined method

objet

USER_BASE

(dans le module site)

user_call() (méthode bdb.Bdb)

user_exception() (méthode bdb.Bdb)

user_line() (méthode bdb.Bdb)

user_return() (méthode bdb.Bdb)

USER_SITE (dans le module site)

usercustomize

module

UserDict (classe dans collections)

UserList (classe dans collections)

USERNAME, [1]

username (attribut email.headerregistry.Address)

USERPROFILE, [1]

userptr() (méthode curses.panel.Panel)

UserString (classe dans collections)

UserWarning

USTAR_FORMAT (dans le module tarfile)

UTC

utc (attribut datetime.timezone)

utcfromtimestamp() (méthode de la classe datetime.datetime)

utcnow() (méthode de la classe datetime.datetime)

utcoffset() (méthode datetime.datetime)

(méthode datetime.time)

(méthode datetime.timezone)

(méthode datetime.tzinfo)

utctimetuple() (méthode datetime.datetime)

utf8 (attribut email.policy.EmailPolicy)

utf8() (méthode poplib.POP3)

utf8_enabled (attribut imaplib.IMAP4)

utime() (dans le module os)

uu

module

uu (module)

UUID (classe dans uuid)

uuid (module)

uuid1

uuid1() (dans le module uuid)

uuid3

uuid3() (dans le module uuid)

uuid4

uuid4() (dans le module uuid)

uuid5

uuid5() (dans le module uuid)

UuidCreate() (dans le module msilib)

V

v4_int_to_packed() (dans le module ipaddress)

v6_int_to_packed() (dans le module ipaddress)

validator() (dans le module wsgiref.validate)

value

default parameter

truth

value (attribut ctypes._SimpleCData)

(attribut http.cookiejar.Cookie)

(attribut http.cookies.Morsel)

(attribut xml.dom.Attr)

value of an object

Value() (dans le module multiprocessing)

(dans le module multiprocessing.sharedctypes)

(méthode multiprocessing.managers.SyncManager)

value_decode() (méthode http.cookies.BaseCookie)

value_encode() (méthode http.cookies.BaseCookie)

ValueError

exception

valuerefs() (méthode weakref.WeakValueDictionary)

values

Boolean

writing

values() (méthode dict)

(méthode email.message.EmailMessage)

(méthode email.message.Message)

(méthode mailbox.Mailbox)

(méthode types.MappingProxyType)

ValuesView (classe dans collections.abc)

(classe dans typing)

variable

free

variable d'environnement

APPDATA

AUDIODEV

BROWSER, [1]

CC

CFLAGS, [1], [2]

COLS, [1]

COLUMNS, [1]

COMSPEC, [1]

CPP

CPPFLAGS

DISTUTILS_DEBUG

exec_prefix, [1], [2]

HOME, [1], [2], [3], [4]

HOMEDRIVE, [1]

HOMEPATH, [1]

http_proxy, [1], [2]

IDLE*STARTUP

IDLESTARTUP

KDEDIR

LANG, [1], [2], [3], [4]

LANGUAGE, [1]

LC_ALL, [1]

LC_MESSAGES, [1]

LDCXXSHARED

LDFLAGS

LINES, [1], [2], [3], [4]

LNAME

LOGNAME, [1]

MIXERDEV

no_proxy

PAGER

PATH, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20], [21], [22], [23], [24], [25], [26], [27], [28], [29], [30], [31], [32], [33], [34]

PATHEXT, [1]

PLAT

POSIXLY_CORRECT

prefix, [1], [2], [3]

PYTHON*, [1], [2]

PYTHON_DOM

PYTHONASYNCIODEBUG, [1], [2]

PYTHONCASEOK, [1]

PYTHONDEBUG, [1]

PYTHONDOCS

PYTHONDONDONTWRITEBYTECODE

PYTHONDONTWRITEBYTECODE, [1], [2], [3], [4]

PYTHONDUMPREFS, [1]

PYTHONEXECUTABLE

PYTHONFAULTHANDLER, [1], [2]

PYTHONHASHSEED, [1], [2], [3], [4], [5]

PYTHONHOME, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14]

PYTHONINSPECT, [1], [2]

PYTHONIOENCODING, [1], [2], [3], [4], [5]

PYTHONLEGACYWINDOWSFSENCODING, [1], [2]

PYTHONLEGACYWINDOWSSTDIO, [1], [2]

PYTHONMALLOC, [1], [2], [3], [4], [5], [6]

PYTHONMALLOCSTATS, [1], [2]

PYTHONNOUSERSITE, [1], [2], [3]

PYTHONOPTIMIZE, [1]

PYTHONPATH, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20], [21], [22]

PYTHONSHOWALLOCCOUNT

PYTHONSHOWREFCOUNT

PYTHONSTARTUP, [1], [2], [3], [4], [5], [6], [7], [8], [9]

PYTHONTHREADDEBUG

PYTHONTRACEMALLOC, [1], [2], [3]

PYTHONUNBUFFERED, [1]

PYTHONUSERBASE, [1], [2], [3]

PYTHONVERBOSE, [1]

PYTHONWARNINGS, [1], [2], [3], [4]

SSL_CERT_FILE

SSL_CERT_PATH

SystemRoot

TCL_LIBRARY

TEMP

TERM, [1]

TIX_LIBRARY

TK_LIBRARY

TMP

TMPDIR

TZ, [1], [2], [3], [4]

USER

USER_BASE

USERNAME, [1]

USERPROFILE, [1]

variable de classe

variance() (dans le module statistics)

variant (attribut uuid.UUID)

vars() (fonction de base)

vbar (attribut tkinter.scrolledtext.ScrolledText)

VBAR (dans le module token)

VBAREQUAL (dans le module token)

Vec2D (classe dans turtle)

venv (module)

VERBOSE (dans le module re)

verbose (dans le module tabnanny)

(dans le module test.support)

verify() (méthode smtplib.SMTP)

verify_client_post_handshake() (méthode ssl.SSLSocket)

VERIFY_CRL_CHECK_CHAIN (dans le module ssl)

VERIFY_CRL_CHECK_LEAF (dans le module ssl)

VERIFY_DEFAULT (dans le module ssl)

verify_flags (attribut ssl.SSLContext)

verify_mode (attribut ssl.SSLContext)

verify_request() (méthode socketserver.BaseServer)

VERIFY_X509_STRICT (dans le module ssl)

VERIFY_X509_TRUSTED_FIRST (dans le module ssl)

VerifyFlags (classe dans ssl)

VerifyMode (classe dans ssl)

verrou global de l'interpréteur

version (attribut email.headerregistry.MIMEVersionHeader)

(attribut http.client.HTTPResponse)

(attribut http.cookiejar.Cookie)

(attribut ipaddress.IPv4Address)

(attribut ipaddress.IPv4Network)

(attribut ipaddress.IPv6Address)

(attribut ipaddress.IPv6Network)

(attribut urllib.request.URLopener)

(attribut uuid.UUID)

(dans le module curses)

(dans le module marshal)

(dans le module sqlite3)

(dans le module sys)

(in module sys), [1], [2]

version() (dans le module ensurepip)

(dans le module platform)

(méthode ssl.SSLSocket)

version_info (dans le module sqlite3)

(dans le module sys)

version_string() (méthode http.server.BaseHTTPRequestHandler)

vformat() (méthode string.Formatter)

virtual

Environments

visit() (méthode ast.NodeVisitor)

visitproc (type C)

vline() (méthode curses.window)

voidcmd() (méthode ftplib.FTP)

volume (attribut zipfile.ZipInfo)

vonmisesvariate() (dans le module random)

vue de dictionnaire

W

W_OK (dans le module os)

wait() (dans le module asyncio)

(dans le module concurrent.futures)

(dans le module multiprocessing.connection)

(dans le module os)

(méthode asyncio.asyncio.subprocess.Process)

(méthode asyncio.Condition)

(méthode asyncio.Event)

(méthode multiprocessing.pool.AsyncResult)

(méthode subprocess.Popen)

(méthode threading.Barrier)

(méthode threading.Condition)

(méthode threading.Event)

wait3() (dans le module os)

wait4() (dans le module os)

wait_closed() (méthode asyncio.Server)

wait_for() (dans le module asyncio)

(méthode asyncio.Condition)

(méthode threading.Condition)

waitid() (dans le module os)

waitpid() (dans le module os)

walk() (dans le module ast)

(dans le module os)

(méthode email.message.EmailMessage)

(méthode email.message.Message)

walk_packages() (dans le module pkgutil)

walk_stack() (dans le module traceback)

walk_tb() (dans le module traceback)

want (attribut doctest.Example)

warn() (dans le module warnings)

(méthode distutils.ccompiler.CCompiler)

(méthode distutils.text_file.TextFile)

warn_explicit() (dans le module warnings)

Warning, [1]

warning() (dans le module logging)

(méthode logging.Logger)

(méthode xml.sax.handler.ErrorHandler)

warnings

(module)

WarningsRecorder (classe dans test.support)

warnoptions (dans le module sys)

wasSuccessful() (méthode unittest.TestResult)

WatchedFileHandler (classe dans logging.handlers)

wave (module)

WCONTINUED (dans le module os)

WCOREDUMP() (dans le module os)

WeakKeyDictionary (classe dans weakref)

WeakMethod (classe dans weakref)

weakref (module)

WeakSet (classe dans weakref)

WeakValueDictionary (classe dans weakref)

webbrowser (module)

weekday() (dans le module calendar)

(méthode datetime.date)

(méthode datetime.datetime)

weekheader() (dans le module calendar)

weibullvariate() (dans le module random)

WEXITED (dans le module os)

WEXITSTATUS() (dans le module os)

wfile (attribut http.server.BaseHTTPRequestHandler)

what() (dans le module imghdr)

(dans le module sndhdr)

whathdr() (dans le module sndhdr)

whatis (pdb command)

where (pdb command)

which() (dans le module shutil)

whichdb() (dans le module dbm)

while

état, [1], [2], [3]

whitespace (attribut shlex.shlex)

(dans le module string)

whitespace_split (attribut shlex.shlex)

Widget (classe dans tkinter.ttk)

width (attribut textwrap.TextWrapper)

width() (dans le module turtle)

WIFCONTINUED() (dans le module os)

WIFEXITED() (dans le module os)

WIFSIGNALED() (dans le module os)

WIFSTOPPED() (dans le module os)

win32_ver() (dans le module platform)

WinDLL (classe dans ctypes)

window manager (widgets)

window() (méthode curses.panel.Panel)

window_height() (dans le module turtle)

window_width() (dans le module turtle)

Windows

Windows ini file

WindowsError

WindowsPath (classe dans pathlib)

WindowsRegistryFinder (classe dans importlib.machinery)

winerror (attribut OSError)

WinError() (dans le module ctypes)

WINFUNCTYPE() (dans le module ctypes)

winreg (module)

WinSock

winsound (module)

winver (dans le module sys)

with

état, [1]

WITH_CLEANUP_FINISH (opcode)

WITH_CLEANUP_START (opcode)

with_hostmask (attribut ipaddress.IPv4Interface)

(attribut ipaddress.IPv4Network)

(attribut ipaddress.IPv6Interface)

(attribut ipaddress.IPv6Network)

with_name() (méthode pathlib.PurePath)

with_netmask (attribut ipaddress.IPv4Interface)

(attribut ipaddress.IPv4Network)

(attribut ipaddress.IPv6Interface)

(attribut ipaddress.IPv6Network)

with_prefixlen (attribut ipaddress.IPv4Interface)

(attribut ipaddress.IPv4Network)

(attribut ipaddress.IPv6Interface)

(attribut ipaddress.IPv6Network)

with_suffix() (méthode pathlib.PurePath)

with_traceback() (méthode BaseException)

WNOHANG (dans le module os)

WNOWAIT (dans le module os)

wordchars (attribut shlex.shlex)

World Wide Web, [1], [2]

wrap() (dans le module textwrap)

(méthode textwrap.TextWrapper)

wrap_bio() (méthode ssl.SSLContext)

wrap_future() (dans le module asyncio)

wrap_socket() (dans le module ssl)

(méthode ssl.SSLContext)

wrap_text() (dans le module distutils.fancy_getopt)

wrapper() (dans le module curses)

wraps() (dans le module functools)

WRITABLE (dans le module tkinter)

writable() (méthode asyncore.dispatcher)

(méthode io.IOBase)

write() (dans le module os)

(dans le module turtle)

(méthode asyncio.StreamWriter)

(méthode asyncio.WriteTransport)

(méthode code.InteractiveInterpreter)

(méthode codecs.StreamWriter)

(méthode configparser.ConfigParser)

(méthode email.generator.BytesGenerator)

(méthode email.generator.Generator)

(méthode io.BufferedIOBase)

(méthode io.BufferedWriter)

(méthode io.RawIOBase)

(méthode io.TextIOBase)

(méthode mmap.mmap)

(méthode ossaudiodev.oss_audio_device)

(méthode ssl.MemoryBIO)

(méthode ssl.SSLSocket)

(méthode telnetlib.Telnet)

(méthode xml.etree.ElementTree.ElementTree)

(méthode zipfile.ZipFile)

write_byte() (méthode mmap.mmap)

write_bytes() (méthode pathlib.Path)

write_docstringdict() (dans le module turtle)

write_eof() (méthode asyncio.StreamWriter)

(méthode asyncio.WriteTransport)

(méthode ssl.MemoryBIO)

write_file() (dans le module distutils.file_util)

write_history_file() (dans le module readline)

WRITE_RESTRICTED

write_results() (méthode trace.CoverageResults)

write_text() (méthode pathlib.Path)

writeall() (méthode ossaudiodev.oss_audio_device)

writeframes() (méthode aifc.aifc)

(méthode sunau.AU_write)

(méthode wave.Wave_write)

writeframesraw() (méthode aifc.aifc)

(méthode sunau.AU_write)

(méthode wave.Wave_write)

writeheader() (méthode csv.DictWriter)

writelines() (méthode asyncio.StreamWriter)

(méthode asyncio.WriteTransport)

(méthode codecs.StreamWriter)

(méthode io.IOBase)

writePlist() (dans le module plistlib)

writePlistToBytes() (dans le module plistlib)

writepy() (méthode zipfile.PyZipFile)

writer (attribut formatter.formatter)

writer() (dans le module csv)

writerow() (méthode csv.csvwriter)

writerows() (méthode csv.csvwriter)

writestr() (méthode zipfile.ZipFile)

WriteTransport (classe dans asyncio)

writev() (dans le module os)

writexml() (méthode xml.dom.minidom.Node)

writing

values

WrongDocumentErr

ws_comma (2to3 fixer)

wsgi_file_wrapper (attribut wsgiref.handlers.BaseHandler)

wsgi_multiprocess (attribut wsgiref.handlers.BaseHandler)

wsgi_multithread (attribut wsgiref.handlers.BaseHandler)

wsgi_run_once (attribut wsgiref.handlers.BaseHandler)

wsgiref (module)

wsgiref.handlers (module)

wsgiref.headers (module)

wsgiref.simple_server (module)

wsgiref.util (module)

wsgiref.validate (module)

WSGIRequestHandler (classe dans wsgiref.simple_server)

WSGIServer (classe dans wsgiref.simple_server)

wShowWindow (attribut subprocess.STARTUPINFO)

WSTOPPED (dans le module os)

WSTOPSIG() (dans le module os)

wstring_at() (dans le module ctypes)

WTERMSIG() (dans le module os)

WUNTRACED (dans le module os)

WWW, [1], [2]

server, [1]

X

X (dans le module re)

X509 certificate

X_OK (dans le module os)

xatom() (méthode imaplib.IMAP4)

XATTR_CREATE (dans le module os)

XATTR_REPLACE (dans le module os)

XATTR_SIZE_MAX (dans le module os)

xcor() (dans le module turtle)

XDR

xdrlib (module)

xhdr() (méthode nntplib.NNTP)

XHTML

XHTML_NAMESPACE (dans le module xml.dom)

xml (module)

XML() (dans le module xml.etree.ElementTree)

xml.dom (module)

xml.dom.minidom (module)

xml.dom.pulldom (module)

xml.etree.ElementTree (module)

xml.parsers.expat (module)

xml.parsers.expat.errors (module)

xml.parsers.expat.model (module)

xml.sax (module)

xml.sax.handler (module)

xml.sax.saxutils (module)

xml.sax.xmlreader (module)

XML_ERROR_ABORTED (dans le module xml.parsers.expat.errors)

XML_ERROR_ASYNC_ENTITY (dans le module xml.parsers.expat.errors)

XML_ERROR_ATTRIBUTE_EXTERNAL_ENTITY_REF (dans le module xml.parsers.expat.errors)

XML_ERROR_BAD_CHAR_REF (dans le module xml.parsers.expat.errors)

XML_ERROR_BINARY_ENTITY_REF (dans le module xml.parsers.expat.errors)

XML_ERROR_CANT_CHANGE_FEATURE_ONCE_PARSING (dans le module xml.parsers.expat.errors)

XML_ERROR_DUPLICATE_ATTRIBUTE (dans le module xml.parsers.expat.errors)

XML_ERROR_ENTITY_DECLARED_IN_PE (dans le module xml.parsers.expat.errors)

XML_ERROR_EXTERNAL_ENTITY_HANDLING (dans le module xml.parsers.expat.errors)

XML_ERROR_FEATURE_REQUIRES_XML_DTD (dans le module xml.parsers.expat.errors)

XML_ERROR_FINISHED (dans le module xml.parsers.expat.errors)

XML_ERROR_INCOMPLETE_PE (dans le module xml.parsers.expat.errors)

XML_ERROR_INCORRECT_ENCODING (dans le module xml.parsers.expat.errors)

XML_ERROR_INVALID_TOKEN (dans le module xml.parsers.expat.errors)

XML_ERROR_JUNK_AFTER_DOC_ELEMENT (dans le module xml.parsers.expat.errors)

XML_ERROR_MISPLACED_XML_PI (dans le module xml.parsers.expat.errors)

XML_ERROR_NO_ELEMENTS (dans le module xml.parsers.expat.errors)

XML_ERROR_NO_MEMORY (dans le module xml.parsers.expat.errors)

XML_ERROR_NOT_STANDALONE (dans le module xml.parsers.expat.errors)

XML_ERROR_NOT_SUSPENDED (dans le module xml.parsers.expat.errors)

XML_ERROR_PARAM_ENTITY_REF (dans le module xml.parsers.expat.errors)

XML_ERROR_PARTIAL_CHAR (dans le module xml.parsers.expat.errors)

XML_ERROR_PUBLICID (dans le module xml.parsers.expat.errors)

XML_ERROR_RECURSIVE_ENTITY_REF (dans le module xml.parsers.expat.errors)

XML_ERROR_SUSPEND_PE (dans le module xml.parsers.expat.errors)

XML_ERROR_SUSPENDED (dans le module xml.parsers.expat.errors)

XML_ERROR_SYNTAX (dans le module xml.parsers.expat.errors)

XML_ERROR_TAG_MISMATCH (dans le module xml.parsers.expat.errors)

XML_ERROR_TEXT_DECL (dans le module xml.parsers.expat.errors)

XML_ERROR_UNBOUND_PREFIX (dans le module xml.parsers.expat.errors)

XML_ERROR_UNCLOSED_CDATA_SECTION (dans le module xml.parsers.expat.errors)

XML_ERROR_UNCLOSED_TOKEN (dans le module xml.parsers.expat.errors)

XML_ERROR_UNDECLARING_PREFIX (dans le module xml.parsers.expat.errors)

XML_ERROR_UNDEFINED_ENTITY (dans le module xml.parsers.expat.errors)

XML_ERROR_UNEXPECTED_STATE (dans le module xml.parsers.expat.errors)

XML_ERROR_UNKNOWN_ENCODING (dans le module xml.parsers.expat.errors)

XML_ERROR_XML_DECL (dans le module xml.parsers.expat.errors)

XML_NAMESPACE (dans le module xml.dom)

xmlcharrefreplace_errors() (dans le module codecs)

XmlDeclHandler() (méthode xml.parsers.expat.xmlparser)

XMLFilterBase (classe dans xml.sax.saxutils)

XMLGenerator (classe dans xml.sax.saxutils)

XMLID() (dans le module xml.etree.ElementTree)

XMLNS_NAMESPACE (dans le module xml.dom)

XMLParser (classe dans xml.etree.ElementTree)

XMLParserType (dans le module xml.parsers.expat)

XMLPullParser (classe dans xml.etree.ElementTree)

XMLReader (classe dans xml.sax.xmlreader)

xmlrpc.client (module)

xmlrpc.server (module)

xor

bitwise

xor() (dans le module operator)

xover() (méthode nntplib.NNTP)

xpath() (méthode nntplib.NNTP)

xrange (2to3 fixer)

xreadlines (2to3 fixer)

xview() (méthode tkinter.ttk.Treeview)

Y

Y2K

ycor() (dans le module turtle)

year (attribut datetime.date)

(attribut datetime.datetime)

Year 2000

Year 2038

yeardatescalendar() (méthode calendar.Calendar)

yeardays2calendar() (méthode calendar.Calendar)

yeardayscalendar() (méthode calendar.Calendar)

YESEXPR (dans le module locale)

yield

examples

expression

état

mot-clé

yield from (in What's New)

YIELD_FROM (opcode)

YIELD_VALUE (opcode)

yiq_to_rgb() (dans le module colorsys)

yview() (méthode tkinter.ttk.Treeview)

Z

ZeroDivisionError

exception

zfill() (méthode bytearray)

(méthode bytes)

(méthode str)

zip (2to3 fixer)

zip() (fonction de base)

ZIP_BZIP2 (dans le module zipfile)

ZIP_DEFLATED (dans le module zipfile)

zip_longest() (dans le module itertools)

ZIP_LZMA (dans le module zipfile)

ZIP_STORED (dans le module zipfile)

zipapp (module)

zipapp command line option

--help

--info

--main=<mainfn>

--output=<output>

--python=<interpreter>

-h

-m <mainfn>

-o <output>

-p <interpreter>

ZipFile (classe dans zipfile)

zipfile (module)

zipfile command line option

-c <zipfile> <source1> ... <sourceN>

-e <zipfile> <output_dir>

-l <zipfile>

-t <zipfile>

zipimport (module)

zipimporter (classe dans zipimport)

ZipImportError

ZipInfo (classe dans zipfile)

zlib (module)

ZLIB_RUNTIME_VERSION (dans le module zlib)

ZLIB_VERSION (dans le module zlib)

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Documentation Python 3.6.11

Bienvenue sur la documentation de Python 3.6.11.

La documentation :

Les nouveautés de Python 3.6
ou toutes les nouveautés depuis la 2.0

Tutoriel
démarrez ici

Référence de la bibliothèque
gardez-ça sous votre oreiller

Référence du langage
décrit la syntaxe et les éléments du langage

Installation et utilisation de Python
utilisation de Python sur différentes plateformes

Les HOWTOs de Python
documents explorant certains sujets en profondeur

Installation de modules Python
installation depuis le *Python Package Index* ou d'autres sources

Distribuer des modules Python
publier des modules pour que d'autres puissent les installer

Amélioration et intégration
tutoriel pour les développeurs C/C++

Python/C API
référence pour les développeurs C/C++

FAQs
foire aux questions (avec les réponses !)

Indices et tables :

Index général des modules
accès rapide à l'ensemble des modules

Index général
toutes les fonctions, classes, termes

Glossaire
explication des mots les plus importants

Page de recherche
rechercher dans cette documentation

Table des matières complète
lister l'ensemble des sections et sous-sections

Méta informations :

Signalement de bogue

À propos de la documentation

Histoire et licence de Python

Copyright

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Le contenu de cette page à déménagé dans la section L’index de paquets Python (Python Package Index : PyPI).

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© Copyright 2001-2020, Python Software Foundation.
La Python Software Foundation est une organisation à but non lucratif. Les dons sont bienvenus.
Mis à jour le juin 29, 2020. Vous avez trouvé un bug ?
Créé via Sphinx 2.3.1.